diff --git a/.github/workflows/test-addon.yml b/.github/workflows/test-addon.yml
index 5fc354ef..c19413f3 100644
--- a/.github/workflows/test-addon.yml
+++ b/.github/workflows/test-addon.yml
@@ -2,9 +2,9 @@ name: Test in Blender
on:
push:
- branches: ["main"]
+ branches: ["main", "4.2", "extensions-platform"]
pull_request:
- branches: ["main", "4.1"]
+ branches: ["main", "4.2", "extensions-platform"]
jobs:
build:
@@ -13,57 +13,44 @@ jobs:
max-parallel: 4
fail-fast: false
matrix:
- blender-version: ["4.1"]
- os: [ubuntu-latest, windows-latest, macos-13, macos-14]
- # os: [macos-13]
+ blender-version: ["4.2"]
+ os: [ubuntu-latest, macos-14]
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: 3.11.7
- - name: Test in Blender MacOS Intel
- if: matrix.os == 'macos-13'
- run: |
- curl -L -o blender.dmg https://download.blender.org/release/Blender4.1/blender-4.1.0-macos-x64.dmg
- hdiutil attach blender.dmg
- cp -R /Volumes/Blender/Blender.app /Applications/
- hdiutil detach /Volumes/Blender
- /Applications/Blender.app/Contents/MacOS/Blender --version
- /Applications/Blender.app/Contents/MacOS/Blender -b --python tests/install.py
- /Applications/Blender.app/Contents/MacOS/Blender -b --python tests/run.py -- -v
+ - name: Cache Blender
+ uses: actions/cache@v2
+ with:
+ path: ~/blender.tar.xz
+ key: ${{ runner.os }}-blender-${{ hashFiles('**/test-addon.yml') }}
- name: Test in Blender MacOS ARM
if: matrix.os == 'macos-14'
run: |
- curl -L -o blender.dmg https://download.blender.org/release/Blender4.1/blender-4.1.0-macos-arm64.dmg
+ curl -L -o blender.dmg https://download.blender.org/release/Blender4.2/blender-4.2.0-macos-arm64.dmg
hdiutil attach blender.dmg
cp -R /Volumes/Blender/Blender.app /Applications/
hdiutil detach /Volumes/Blender
/Applications/Blender.app/Contents/MacOS/Blender --version
/Applications/Blender.app/Contents/MacOS/Blender -b --python tests/install.py
- /Applications/Blender.app/Contents/MacOS/Blender -b --python tests/run.py -- -v
-
- - name: Test in Blender Windows
- if: matrix.os == 'windows-latest'
- shell: pwsh
- run: |
- Invoke-WebRequest -Uri "https://download.blender.org/release/Blender4.1/blender-4.1.0-windows-x64.zip" -OutFile "blender.zip"
- Expand-Archive -Path "blender.zip" -DestinationPath "blender"
- .\blender\blender-4.1.0-windows-x64\blender.exe --version
- .\blender\blender-4.1.0-windows-x64\blender.exe -b --python tests/install.py
- .\blender\blender-4.1.0-windows-x64\blender.exe -b --python tests/run.py -- -v tests/
-
+ /Applications/Blender.app/Contents/MacOS/Blender -b --python tests/run.py -- -v tests/
+
- name: Test in Blender Linux
if: matrix.os == 'ubuntu-latest'
run: |
- wget -nv https://download.blender.org/release/Blender4.1/blender-4.1.0-linux-x64.tar.xz
- tar -xf blender-4.1.0-linux-x64.tar.xz
-
- blender-4.1.0-linux-x64/blender --version
- blender-4.1.0-linux-x64/blender -b --python tests/install.py
- blender-4.1.0-linux-x64/blender -b --python tests/run.py -- -v tests/ --cov=molecularnodes --cov-report=xml:coverage.xml --ignore=molecularnodes/ui/panel.py
-
+ if [[ ! -f ./blender.tar.xz ]]; then
+ wget -nv https://download.blender.org/release/Blender4.2/blender-4.2.0-linux-x64.tar.xz -O ./blender.tar.xz
+ fi
+ mkdir -p ./blender
+ ls -lrta
+ tar -xf ./blender.tar.xz -C ./blender --strip-components=1
+ ls -lrta
+ blender/blender --version
+ blender/blender -b --python tests/install.py
+ blender/blender -b --python tests/run.py -- -v tests/ --cov=molecularnodes --cov-report=xml:coverage.xml --ignore=molecularnodes/ui/panel.py
- name: Expose coverage as a CI download
uses: actions/upload-artifact@v1
if: matrix.os == 'ubuntu-latest'
diff --git a/.gitignore b/.gitignore
index 151b7edf..dbf28b8c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -6,7 +6,7 @@
*.blend1
__pycache__/*
.vscode/*
-molecularnodes_*.zip
+molecularnodes*.zip
*.pyc
.Rproj.user
/.quarto/
@@ -27,5 +27,5 @@ poetry.lock
*.vdb
docs/nodes/*.qmd
!docs/nodes/index.qmd
-
-
+*.whl
+*.MNSession
diff --git a/build.py b/build.py
index ae123f55..8cc314e6 100644
--- a/build.py
+++ b/build.py
@@ -1,24 +1,163 @@
+import glob
import os
-import zipfile
+import subprocess
+import sys
+from dataclasses import dataclass
+from typing import List, Union
+import bpy
+import tomlkit
-# zips up the template file
-def zip_template():
- # Define the directory and zip file paths
- dir_path = 'molecularnodes/assets/template/Molecular Nodes'
- zip_file_path = 'molecularnodes/assets/template/Molecular Nodes.zip'
+toml_path = "molecularnodes/blender_manifest.toml"
+whl_path = "./molecularnodes/wheels"
- # Create a ZipFile object in write mode
- with zipfile.ZipFile(zip_file_path, 'w', zipfile.ZIP_DEFLATED) as zipf:
- # Walk the directory tree and add files to the zip file
- for root, dirs, files in os.walk(dir_path):
- for file in files:
- # Get the path of the file
- file_path = os.path.join(root, file)
- # Add the file to the zip file
- zipf.write(file_path, arcname=os.path.relpath(
- file_path, start='molecularnodes/assets/template/'))
+
+@dataclass
+class Platform:
+ pypi_suffix: str
+ metadata: str
+
+
+# tags for blender metadata
+# platforms = ["windows-x64", "macos-arm64", "linux-x64", "windows-arm64", "macos-x64"]
+
+
+windows_x64 = Platform(pypi_suffix="win_amd64", metadata="windows-x64")
+linux_x64 = Platform(pypi_suffix="manylinux2014_x86_64", metadata="linux-x64")
+macos_arm = Platform(pypi_suffix="macosx_12_0_arm64", metadata="macos-arm64")
+macos_intel = Platform(pypi_suffix="macosx_10_16_x86_64", metadata="macos-x64")
+
+
+required_packages = [
+ "mrcfile==1.4.3",
+ "starfile==0.5.6",
+ "MDAnalysis==2.7.0",
+ "biotite==0.41.2",
+]
+
+
+build_platforms = [
+ windows_x64,
+ linux_x64,
+ macos_arm,
+ macos_intel,
+]
+
+
+def run_python(args: str):
+ python = os.path.realpath(sys.executable)
+ subprocess.run([python] + args.split(" "))
+
+
+def remove_whls():
+ for whl_file in glob.glob(os.path.join(whl_path, "*.whl")):
+ os.remove(whl_file)
+
+
+def download_whls(
+ platforms: Union[Platform, List[Platform]],
+ required_packages: List[str] = required_packages,
+ python_version="3.11",
+ clean: bool = True,
+):
+ if isinstance(platforms, Platform):
+ platforms = [platforms]
+
+ if clean:
+ remove_whls()
+
+ for platform in platforms:
+ run_python(
+ f"-m pip download {' '.join(required_packages)} --dest ./molecularnodes/wheels --only-binary=:all: --python-version={python_version} --platform={platform.pypi_suffix}"
+ )
+
+
+def update_toml_whls(platforms):
+ # Define the path for wheel files
+ wheels_dir = "molecularnodes/wheels"
+ wheel_files = glob.glob(f"{wheels_dir}/*.whl")
+ wheel_files.sort()
+
+ # Packages to remove
+ packages_to_remove = {
+ "pyarrow",
+ "certifi",
+ "charset_normalizer",
+ "idna",
+ "numpy",
+ "requests",
+ "urllib3",
+ }
+
+ # Filter out unwanted wheel files
+ to_remove = []
+ to_keep = []
+ for whl in wheel_files:
+ if any(pkg in whl for pkg in packages_to_remove):
+ to_remove.append(whl)
+ else:
+ to_keep.append(whl)
+
+ # Remove the unwanted wheel files from the filesystem
+ for whl in to_remove:
+ os.remove(whl)
+
+ # Load the TOML file
+ with open(toml_path, "r") as file:
+ manifest = tomlkit.parse(file.read())
+
+ # Update the wheels list with the remaining wheel files
+ manifest["wheels"] = [f"./wheels/{os.path.basename(whl)}" for whl in to_keep]
+
+ # Simplify platform handling
+ if not isinstance(platforms, list):
+ platforms = [platforms]
+ manifest["platforms"] = [p.metadata for p in platforms]
+
+ # Write the updated TOML file
+ with open(toml_path, "w") as file:
+ file.write(
+ tomlkit.dumps(manifest)
+ .replace('["', '[\n\t"')
+ .replace("\\\\", "/")
+ .replace('", "', '",\n\t"')
+ .replace('"]', '",\n]')
+ )
+
+
+def clean_files(suffix: str = ".blend1") -> None:
+ pattern_to_remove = f"molecularnodes/**/*{suffix}"
+ for blend1_file in glob.glob(pattern_to_remove, recursive=True):
+ os.remove(blend1_file)
+
+
+def build_extension(split: bool = True) -> None:
+ for suffix in [".blend1", ".MNSession"]:
+ clean_files(suffix=suffix)
+
+ if split:
+ subprocess.run(
+ f"{bpy.app.binary_path} --command extension build"
+ " --split-platforms --source-dir molecularnodes --output-dir .".split(" ")
+ )
+ else:
+ subprocess.run(
+ f"{bpy.app.binary_path} --command extension build "
+ "--source-dir molecularnodes --output-dir .".split(" ")
+ )
+
+
+def build(platform) -> None:
+ download_whls(platform)
+ update_toml_whls(platform)
+ build_extension()
+
+
+def main():
+ # for platform in build_platforms:
+ # build(platform)
+ build(build_platforms)
if __name__ == "__main__":
- zip_template()
+ main()
diff --git a/docs/.jupyter_cache/__version__.txt b/docs/.jupyter_cache/__version__.txt
deleted file mode 100644
index 7ceb0404..00000000
--- a/docs/.jupyter_cache/__version__.txt
+++ /dev/null
@@ -1 +0,0 @@
-0.6.1
\ No newline at end of file
diff --git a/docs/.jupyter_cache/executed/3df5b303d4d64f98bd74427624d48ba8/base.ipynb b/docs/.jupyter_cache/executed/3df5b303d4d64f98bd74427624d48ba8/base.ipynb
deleted file mode 100644
index 1757188d..00000000
--- a/docs/.jupyter_cache/executed/3df5b303d4d64f98bd74427624d48ba8/base.ipynb
+++ /dev/null
@@ -1,264 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "id": "965597ef",
- "metadata": {},
- "outputs": [],
- "source": [
- "\n",
- "# imports\n",
- "import os\n",
- "import sys\n",
- "import types\n",
- "import json\n",
- "\n",
- "# figure size/format\n",
- "fig_width = 7\n",
- "fig_height = 5\n",
- "fig_format = 'retina'\n",
- "fig_dpi = 96\n",
- "\n",
- "# matplotlib defaults / format\n",
- "try:\n",
- " import matplotlib.pyplot as plt\n",
- " plt.rcParams['figure.figsize'] = (fig_width, fig_height)\n",
- " plt.rcParams['figure.dpi'] = fig_dpi\n",
- " plt.rcParams['savefig.dpi'] = fig_dpi\n",
- " from IPython.display import set_matplotlib_formats\n",
- " set_matplotlib_formats(fig_format)\n",
- "except Exception:\n",
- " pass\n",
- "\n",
- "# plotly use connected mode\n",
- "try:\n",
- " import plotly.io as pio\n",
- " pio.renderers.default = \"notebook_connected\"\n",
- "except Exception:\n",
- " pass\n",
- "\n",
- "# enable pandas latex repr when targeting pdfs\n",
- "try:\n",
- " import pandas as pd\n",
- " if fig_format == 'pdf':\n",
- " pd.set_option('display.latex.repr', True)\n",
- "except Exception:\n",
- " pass\n",
- "\n",
- "\n",
- "\n",
- "# output kernel dependencies\n",
- "kernel_deps = dict()\n",
- "for module in list(sys.modules.values()):\n",
- " # Some modules play games with sys.modules (e.g. email/__init__.py\n",
- " # in the standard library), and occasionally this can cause strange\n",
- " # failures in getattr. Just ignore anything that's not an ordinary\n",
- " # module.\n",
- " if not isinstance(module, types.ModuleType):\n",
- " continue\n",
- " path = getattr(module, \"__file__\", None)\n",
- " if not path:\n",
- " continue\n",
- " if path.endswith(\".pyc\") or path.endswith(\".pyo\"):\n",
- " path = path[:-1]\n",
- " if not os.path.exists(path):\n",
- " continue\n",
- " kernel_deps[path] = os.stat(path).st_mtime\n",
- "print(json.dumps(kernel_deps))\n",
- "\n",
- "# set run_path if requested\n",
- "if r'/Users/brady/git/MolecularNodes/docs':\n",
- " os.chdir(r'/Users/brady/git/MolecularNodes/docs')\n",
- "\n",
- "# reset state\n",
- "%reset\n",
- "\n",
- "def ojs_define(**kwargs):\n",
- " import json\n",
- " try:\n",
- " # IPython 7.14 preferred import\n",
- " from IPython.display import display, HTML\n",
- " except:\n",
- " from IPython.core.display import display, HTML\n",
- "\n",
- " # do some minor magic for convenience when handling pandas\n",
- " # dataframes\n",
- " def convert(v):\n",
- " try:\n",
- " import pandas as pd\n",
- " except ModuleNotFoundError: # don't do the magic when pandas is not available\n",
- " return v\n",
- " if type(v) == pd.Series:\n",
- " v = pd.DataFrame(v)\n",
- " if type(v) == pd.DataFrame:\n",
- " j = json.loads(v.T.to_json(orient='split'))\n",
- " return dict((k,v) for (k,v) in zip(j[\"index\"], j[\"data\"]))\n",
- " else:\n",
- " return v\n",
- " \n",
- " v = dict(contents=list(dict(name=key, value=convert(value)) for (key, value) in kwargs.items()))\n",
- " display(HTML(''), metadata=dict(ojs_define = True))\n",
- "globals()[\"ojs_define\"] = ojs_define\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [],
- "source": [
- "#| label: setup\n",
- "#| code-fold: true\n",
- "import molecularnodes as mn\n",
- "import bpy\n",
- "import sys\n",
- "import tempfile\n",
- "import os\n",
- "from IPython.display import display, Image\n",
- "\n",
- "sys.stdout = open(os.devnull, 'w')\n",
- "sys.stderr = open(os.devnull, 'w')\n",
- "mn.register()\n",
- "\n",
- "def clear_scene():\n",
- " bpy.ops.object.select_all(action=\"DESELECT\")\n",
- " bpy.ops.object.select_by_type(type=\"MESH\")\n",
- " bpy.ops.object.delete()\n",
- " for node in bpy.data.node_groups:\n",
- " if node.type == \"GEOMETRY\":\n",
- " bpy.data.node_groups.remove(node)\n",
- "\n",
- "def orient_camera(object):\n",
- " object.select_set(True)\n",
- " bpy.ops.view3d.camera_to_view_selected()\n",
- "\n",
- "def render_image(engine = 'eevee', x = 1000, y = 500):\n",
- " # setup render engine\n",
- " if engine == \"eevee\":\n",
- " bpy.context.scene.render.engine = \"BLENDER_EEVEE\"\n",
- " elif engine == \"cycles\":\n",
- " \n",
- " bpy.context.scene.render.engine = \"CYCLES\"\n",
- " try:\n",
- " bpy.context.scene.cycles.device = \"GPU\"\n",
- " except:\n",
- " print(\"GPU Rendering not available\")\n",
- "\n",
- " # Render\n",
- " with tempfile.TemporaryDirectory() as temp:\n",
- "\n",
- " path = os.path.join(temp, \"test.png\")\n",
- " bpy.context.scene.render.resolution_x = x\n",
- " bpy.context.scene.render.resolution_y = y\n",
- " bpy.context.scene.render.image_settings.file_format = \"PNG\"\n",
- " bpy.context.scene.render.filepath = path\n",
- " bpy.ops.render.render(write_still=True)\n",
- " display(Image(filename=path))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [],
- "source": [
- "#| label: setup-scene\n",
- "#| code-fold: true\n",
- "\n",
- "# load template scene with nice HDRI lighting\n",
- "bpy.ops.wm.read_homefile(app_template = \"MolecularNodes\")\n",
- "\n",
- "# change the background to a custom color\n",
- "try:\n",
- " world_nodes = bpy.data.worlds['World Shader'].node_tree.nodes\n",
- " world_nodes['MN_world_shader'].inputs['BG Color'].default_value = mn.color.random_rgb()\n",
- "except KeyError:\n",
- " print(\"Oh no, didn't set up the base scene.\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [],
- "source": [
- "clear_scene()\n",
- "mol = mn.load.molecule_rcsb('4ozs', build_assembly=True, starting_style=\"cartoon\")\n",
- "mol.rotation_euler = (0, 3.14 / 2, 0)\n",
- "mol.select_set(True)\n",
- "bpy.ops.view3d.camera_to_view_selected()\n",
- "render_image()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {},
- "outputs": [],
- "source": [
- "clear_scene()\n",
- "mol = mn.load.molecule_rcsb('8HXZ', center_molecule = True, starting_style=\"preset_3\")\n",
- "orient_camera(mol)\n",
- "render_image()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [],
- "source": [
- "render_image('cycles')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [],
- "source": [
- "clear_scene()\n",
- "\n",
- "mol = mn.load.molecule_rcsb('6N2Y', center_molecule=True, starting_style=\"preset_3\")\n",
- "mol.select_set(True)\n",
- "mol.rotation_euler = (0, 90, 180)\n",
- "orient_camera(mol)\n",
- "render_image()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [],
- "source": [
- "clear_scene()\n",
- "mol = mn.load.molecule_rcsb('8CPY', build_assembly=True, starting_style=\"surface\")\n",
- "orient_camera(mol)\n",
- "render_image('cycles')"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3 (ipykernel)",
- "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": "3.10.0"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
\ No newline at end of file
diff --git a/docs/.jupyter_cache/executed/de71a169159ed73044f382b0474e0e6d/base.ipynb b/docs/.jupyter_cache/executed/de71a169159ed73044f382b0474e0e6d/base.ipynb
deleted file mode 100644
index 63c73d1d..00000000
--- a/docs/.jupyter_cache/executed/de71a169159ed73044f382b0474e0e6d/base.ipynb
+++ /dev/null
@@ -1,798 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "id": "1adb8c23",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
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\"/opt/homebrew/Caskroom/miniconda/base/envs/mn/lib/python3.10/site-packages/pandas/core/computation/engines.py\": 1695878709.5165439, \"/opt/homebrew/Caskroom/miniconda/base/envs/mn/lib/python3.10/site-packages/pandas/core/computation/parsing.py\": 1695878709.5158355, \"/opt/homebrew/Caskroom/miniconda/base/envs/mn/lib/python3.10/site-packages/pandas/core/computation/expr.py\": 1695878709.5179307, \"/opt/homebrew/Caskroom/miniconda/base/envs/mn/lib/python3.10/site-packages/pandas/core/computation/eval.py\": 1695878709.5175016, \"/opt/homebrew/Caskroom/miniconda/base/envs/mn/lib/python3.10/site-packages/pandas/core/computation/api.py\": 1695878709.516933, \"/opt/homebrew/Caskroom/miniconda/base/envs/mn/lib/python3.10/site-packages/pandas/core/reshape/encoding.py\": 1695878709.4991865, \"/opt/homebrew/Caskroom/miniconda/base/envs/mn/lib/python3.10/site-packages/pandas/core/reshape/merge.py\": 1695878709.4989378, 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\"/opt/homebrew/Caskroom/miniconda/base/envs/mn/lib/python3.10/site-packages/pandas/io/json/_normalize.py\": 1695878709.5479054, \"/opt/homebrew/Caskroom/miniconda/base/envs/mn/lib/python3.10/site-packages/pandas/io/json/_table_schema.py\": 1695878709.5480688, \"/opt/homebrew/Caskroom/miniconda/base/envs/mn/lib/python3.10/site-packages/pandas/_libs/parsers.cpython-310-darwin.so\": 1695878709.747788, \"/opt/homebrew/Caskroom/miniconda/base/envs/mn/lib/python3.10/site-packages/pandas/io/parsers/base_parser.py\": 1695878709.5407438, \"/opt/homebrew/Caskroom/miniconda/base/envs/mn/lib/python3.10/site-packages/pandas/io/parsers/arrow_parser_wrapper.py\": 1695878709.5409052, \"/opt/homebrew/Caskroom/miniconda/base/envs/mn/lib/python3.10/site-packages/pandas/io/parsers/c_parser_wrapper.py\": 1695878709.5410795, \"/opt/homebrew/Caskroom/miniconda/base/envs/mn/lib/python3.10/site-packages/pandas/io/parsers/python_parser.py\": 1695878709.540441, 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- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/var/folders/r4/ym_ncgbd3qddtxqvrmhps8q80000gn/T/ipykernel_13789/809095269.py:20: DeprecationWarning: `set_matplotlib_formats` is deprecated since IPython 7.23, directly use `matplotlib_inline.backend_inline.set_matplotlib_formats()`\n",
- " set_matplotlib_formats(fig_format)\n"
- ]
- }
- ],
- "source": [
- "\n",
- "# imports\n",
- "import os\n",
- "import sys\n",
- "import types\n",
- "import json\n",
- "\n",
- "# figure size/format\n",
- "fig_width = 7\n",
- "fig_height = 5\n",
- "fig_format = 'retina'\n",
- "fig_dpi = 96\n",
- "\n",
- "# matplotlib defaults / format\n",
- "try:\n",
- " import matplotlib.pyplot as plt\n",
- " plt.rcParams['figure.figsize'] = (fig_width, fig_height)\n",
- " plt.rcParams['figure.dpi'] = fig_dpi\n",
- " plt.rcParams['savefig.dpi'] = fig_dpi\n",
- " from IPython.display import set_matplotlib_formats\n",
- " set_matplotlib_formats(fig_format)\n",
- "except Exception:\n",
- " pass\n",
- "\n",
- "# plotly use connected mode\n",
- "try:\n",
- " import plotly.io as pio\n",
- " pio.renderers.default = \"notebook_connected\"\n",
- "except Exception:\n",
- " pass\n",
- "\n",
- "# enable pandas latex repr when targeting pdfs\n",
- "try:\n",
- " import pandas as pd\n",
- " if fig_format == 'pdf':\n",
- " pd.set_option('display.latex.repr', True)\n",
- "except Exception:\n",
- " pass\n",
- "\n",
- "\n",
- "\n",
- "# output kernel dependencies\n",
- "kernel_deps = dict()\n",
- "for module in list(sys.modules.values()):\n",
- " # Some modules play games with sys.modules (e.g. email/__init__.py\n",
- " # in the standard library), and occasionally this can cause strange\n",
- " # failures in getattr. Just ignore anything that's not an ordinary\n",
- " # module.\n",
- " if not isinstance(module, types.ModuleType):\n",
- " continue\n",
- " path = getattr(module, \"__file__\", None)\n",
- " if not path:\n",
- " continue\n",
- " if path.endswith(\".pyc\") or path.endswith(\".pyo\"):\n",
- " path = path[:-1]\n",
- " if not os.path.exists(path):\n",
- " continue\n",
- " kernel_deps[path] = os.stat(path).st_mtime\n",
- "print(json.dumps(kernel_deps))\n",
- "\n",
- "# set run_path if requested\n",
- "if r'/Users/brady/git/MolecularNodes/docs':\n",
- " os.chdir(r'/Users/brady/git/MolecularNodes/docs')\n",
- "\n",
- "# reset state\n",
- "%reset\n",
- "\n",
- "def ojs_define(**kwargs):\n",
- " import json\n",
- " try:\n",
- " # IPython 7.14 preferred import\n",
- " from IPython.display import display, HTML\n",
- " except:\n",
- " from IPython.core.display import display, HTML\n",
- "\n",
- " # do some minor magic for convenience when handling pandas\n",
- " # dataframes\n",
- " def convert(v):\n",
- " try:\n",
- " import pandas as pd\n",
- " except ModuleNotFoundError: # don't do the magic when pandas is not available\n",
- " return v\n",
- " if type(v) == pd.Series:\n",
- " v = pd.DataFrame(v)\n",
- " if type(v) == pd.DataFrame:\n",
- " j = json.loads(v.T.to_json(orient='split'))\n",
- " return dict((k,v) for (k,v) in zip(j[\"index\"], j[\"data\"]))\n",
- " else:\n",
- " return v\n",
- " \n",
- " v = dict(contents=list(dict(name=key, value=convert(value)) for (key, value) in kwargs.items()))\n",
- " display(HTML(''), metadata=dict(ojs_define = True))\n",
- "globals()[\"ojs_define\"] = ojs_define\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "id": "setup",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "no zipfile\n"
- ]
- }
- ],
- "source": [
- "#| label: setup\n",
- "#| code-fold: true\n",
- "import molecularnodes as mn\n",
- "import bpy\n",
- "import sys\n",
- "import tempfile\n",
- "import os\n",
- "from IPython.display import display, Image\n",
- "\n",
- "mn.register()\n",
- "\n",
- "def clear_scene():\n",
- " bpy.ops.object.select_all(action=\"DESELECT\")\n",
- " bpy.ops.object.select_by_type(type=\"MESH\")\n",
- " bpy.ops.object.delete()\n",
- " for node in bpy.data.node_groups:\n",
- " if node.type == \"GEOMETRY\":\n",
- " bpy.data.node_groups.remove(node)\n",
- "\n",
- "def orient_camera(object):\n",
- " object.select_set(True)\n",
- " bpy.ops.view3d.camera_to_view_selected()\n",
- "\n",
- "def render_image(engine = 'eevee', x = 1000, y = 500):\n",
- " # setup render engine\n",
- " if engine == \"eevee\":\n",
- " bpy.context.scene.render.engine = \"BLENDER_EEVEE\"\n",
- " elif engine == \"cycles\":\n",
- " \n",
- " bpy.context.scene.render.engine = \"CYCLES\"\n",
- " try:\n",
- " bpy.context.scene.cycles.device = \"GPU\"\n",
- " except:\n",
- " print(\"GPU Rendering not available\")\n",
- "\n",
- " # Render\n",
- " with tempfile.TemporaryDirectory() as temp:\n",
- "\n",
- " path = os.path.join(temp, \"test.png\")\n",
- " bpy.context.scene.render.resolution_x = x\n",
- " bpy.context.scene.render.resolution_y = y\n",
- " bpy.context.scene.render.image_settings.file_format = \"PNG\"\n",
- " bpy.context.scene.render.filepath = path\n",
- " bpy.ops.render.render(write_still=True)\n",
- " display(Image(filename=path))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "id": "setup-scene",
- "metadata": {},
- "outputs": [],
- "source": [
- "#| label: setup-scene\n",
- "#| code-fold: true\n",
- "\n",
- "# load template scene with nice HDRI lighting\n",
- "bpy.ops.wm.read_homefile(app_template = \"MolecularNodes\")\n",
- "\n",
- "# change the background to a custom color\n",
- "try:\n",
- " world_nodes = bpy.data.worlds['World Shader'].node_tree.nodes\n",
- " world_nodes['MN_world_shader'].inputs['BG Color'].default_value = mn.color.random_rgb()\n",
- "except KeyError:\n",
- " print(\"Oh no, didn't set up the base scene.\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "id": "00ba55bf",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Finsihed opening molecule after 0.19645000000000046 seconds\n",
- "Adding object to scene.\n",
- "Added res_id after 4.399999999993298e-05 s\n",
- "Added res_name after 0.00045300000000025875 s\n",
- "Added atomic_number after 0.0005510000000006343 s\n",
- "Added b_factor after 1.7999999999851468e-05 s\n",
- "Added vdw_radii after 0.0005730000000001567 s\n",
- "Added chain_id after 0.00010099999999990672 s\n",
- "Added entity_id after 4.399999999993298e-05 s\n",
- "Added atom_name after 0.00033500000000064034 s\n",
- "Added lipophobicity after 0.0005610000000002557 s\n",
- "Added charge after 0.0005750000000004363 s\n",
- "Added is_backbone after 9.300000000056485e-05 s\n",
- "Added is_alpha_carbon after 3.0000000000640625e-05 s\n",
- "Added is_solvent after 2.899999999961267e-05 s\n",
- "Added is_nucleic after 0.00021599999999999397 s\n",
- "Added is_peptide after 0.000332000000000221 s\n",
- "Added is_hetero after 2.200000000041058e-05 s\n",
- "Added is_carb after 0.00021200000000032304 s\n",
- "Added sec_struct after 0.0002940000000002385 s\n",
- "Finsihed add object after 0.006109000000000364 seconds\n",
- "Device with name Apple M2 Max supports metal minimum requirements\n",
- "METAL API - DETECTED GPU: Apple M2 Max\n",
- "Fra:1 Mem:51.22M (Peak 61.08M) | Time:00:00.11 | Syncing Camera\n",
- "Fra:1 Mem:51.22M (Peak 61.08M) | Time:00:00.11 | Syncing focal_point\n",
- "Fra:1 Mem:51.23M (Peak 61.08M) | Time:00:00.11 | Syncing 4ozs\n",
- "Fra:1 Mem:53.15M (Peak 61.08M) | Time:00:00.13 | Rendering 1 / 64 samples\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:52.18M (Peak 61.08M) | Time:00:00.23 | Rendering 26 / 64 samples\n",
- "Fra:1 Mem:52.18M (Peak 61.08M) | Time:00:00.30 | Rendering 51 / 64 samples\n",
- "Fra:1 Mem:52.19M (Peak 61.08M) | Time:00:00.34 | Rendering 64 / 64 samples\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Saved: '/var/folders/r4/ym_ncgbd3qddtxqvrmhps8q80000gn/T/tmpni4y3e0b/test.png'\n",
- " Time: 00:00.47 (Saving: 00:00.11)\n",
- "\n"
- ]
- },
- {
- "data": {
- "image/png": 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uXrTKd0X2z7ijI/s93jxdNTpRa0wM7daQySeIy2r/4K3BrB8csWV+eLF8cpxbmObAp1HcsFJVP++C4+ufqjP3EWN7TQzrpWef8c37rE83fs7BqNkS5otx7fQ836Kv7/wJO/g/8+L8O7v+qy/u//zzL0j107PveLThj+PRcyDRAVnKAtnI5+/yn9YFhdkhV1a+mJ8Rz3cNr+he0EycsTroQ/cP7PoJ8jqrizxgtT36Yju8LNjBbDYCScVZE9lNigrGxTCf9nn0HdeLJORVZq7s0bu4MbLX+nDQv1guz/LBRsxY9cfwhMFC3PE5jwPQPbB/uYzAeAMOtS32o7jPGa0DXXxMT/t5+4s1D3nHfzEqiN085FVU9tjyqIbzykXOz8jmib0FE5h2oNj1aFqxLgc2HxqL/yiqAUZ1LltrV1Iu5nTT3CfAntiPAl8uAHx6nyY6a3vRKdevelMX4hVw+zsUemvdtZrQDC/1qVFUVmxueHZXW/kUc16wL3j3lc7BcAPj47BnOo5M1B8fIeIIYBzevKexdp1DGbcz8izjfmoPh2dp4F3sN5iN5ic344m99XSpDp2J58N6CPns99wyrJzQB1YdjZ+mhi/DFFRHQsy12hDczJDphBRYx2f9sRIkbuyA1e6iOeTl+0QCrS2LhpXJWJfd42OAfebrNXqfXPIN96gnqbFE98yOsfTGT+ODDAQUdtHmaXauZsFGHwSU7MEXVO6sfZ5C89m/kzZpJHrrIU5g7SzHP026c4kUx5D2irrngOmcap4WZmr4KBPWxD842RSbBSCB/Xpmc++g34GMAAEALz8tmCbj48KP0LVH0TgPUKojPBy7FseKSA7qw+H6obj8tsV1goxDDF9IHTeb40ygkoJIo21WfVuuofoX9lBlET4G13KwOMDxrvaJa6PBrLYsn5E6k/ybTzY4eTytYl1m/DwYje16N0hrKGY2Yp8cj147nzRlk3e+ywuXfOQizRJnJo6Pp97sy1g96L8MzX3cxsFz9Rz64Vm+J9cBTpKcXLoP0RwjujzyixvyxT69eLg/ZwMc7fasJT816qJ45L+J68deHzXiBfKN1U/PeLcNrjxYtJOdMW3oL0rTzorcMiRPMW+W5uW8m38x41QUzsV+6hCLHf3mOP2Haa6zBcOYAjd3QYMFzhioOEOqba4rwIDxo639bZ2r1dq+xDWYiyXxJ6u0PzQ2Lzre2hqg3iwX7J6a0UG+kYJhZL9eubdX4HC1CjniXC7DArAP2BvodZdWCw1EWMnP9GqurznqT13mfPMuptLLdXSwQWfMtGCzThbN7pWYajq1n/u2ltZHVM+LFTEdxvMX0zHsnhfHnp7dfZVFAz5zY2v/arj2tgijggRGwDvVVtNzfXPzy4P+N9+kVAuVZlPMre8XDBCg35jNh/WXDuHai/S9I8+75S9fc9Bvf4CQEIlX93LHvvuH+XnwfY09ft81L84X6th9wZ53zPOCnO+B7P/cO+f3wt1312GQCi7YOtZTemH+x3UK2Z+NCdXrmXzPvr5sMy4AUnpRY/v7az015SwHmt6oBqANnmooY23kqPZhjCD38LfGYu30LR8iLpYNOZ9zM7oX+yL4jDYNJVN/vHPfzNTUF3w65n5qjF0EF9fV0Qxw92GhF2yt8NmQ49fX+6yWqxFaOQC/XN1p8t5864ynn42zXjguzwLpoz6eX2NcHeRwS0RiLmyZ7VoBBVaCV3lYWVv0P7G1NV/W8OfDPoC/JEjjDLXcjO0Z2HQTW47Hl8U3nfYztHYCqLXAhze2fW2vD0BcL8ejhZpKOv+rAksCIEbcYs9kvRA7zniYxvW8x/8TFyCDsHDv3FoX5vdekQuN1JUQrnJK4U68PK4a7zXcxZaPEPiYr5UvHzZzrB/NdQcT7/8eZZtmdIIb+9ZDlfPZKej0JERd1JrFuUzayhMbH+ixD8/8exgPFr4M4sTRb1bYcekvQ/Nk3e2Tp0BJYvupQRD3h+7T5vZUws8+8z4Kbow1cU4QwXNc021szMdmPd4vYkm6GkEciqn05jXffB/Xa0oA+i4c/HSxpl9qD4DcalPn9TJr0i2Gte6LNSZrhtozl0NTL3Djx4ew4+z+cGJi+Qi11CU72DEwOZaTjXjruR2xeVhfruTrnkX1MKPXB5jLx9/NGXjlyy6IH1jQGf+3ePCOOMA1ruu5iJtdIeBICBmPeKn/wcxc58FWDkBLIvAQ78JGX2FPDXE/v708KPlhkWp8N6PFwZzHGlUjUY9Djo+KEoYHHVUJNrmaiFU59b+4U0Oy5nviyVrvZWXLZxCXOQvWjibVUFtz4KOOdyTP/RCqdS65mw9S6PYgVvrYf3AdLxTr/xS7v7jFgGs/smDdybOQA76dCX7WOFyDX8Rj1jd+ERcPthrgrD6osI8F/tJfEtmaDJ+PbOUHkgfr2WuQ/rXzwzIZwN0MDlnuyXF6WLKuffeN1tbO8iMtUMdJIdTB3HWu+Ww/ah327dFRXp/QuUcjoubpC/RYe305iMH2VHSr2sGD5fFGY22M+WzI+l/88lZHwKH7MRIDBofTOYEtVm7tCBw/+Ffri4GqOo8q299JT8ZwzBY/LVBQ57v/b/0fToQDyFB3l7fLpDuX07F6TXmBtRHfvL8p2Nt/6S4ZsUmodvzn47mgtvTK2uLQ13l6kCPT1XreTpD5CJMcN7PmuSaff/tn5Vmy5UIfxELR/ezZJdf1EzwQktdxC2rv0jjW3wE3eRyQ3P7m58U19e9P3uf7T17I+xxJWF6k50Fue3V7bM+fuMNhncsDtr+lME80+EL/eJDEsvdk+65MesJguvvEF99ZPy/Mb827688Lc16cszema+LZMuhle5GkkCMTR0TwsVH4BZ35dkLg2dBNgixmhYv1GL/rxlVT7c0M5/og5uEr684QzmHB1WvE1Zb1Et9MfxjLNz88DLmzZLde3S7QkHBIN1iB/36MeRh7ns2Xbwz7mgWLf3b2Ds9ryhAly7wXoIojiJJsa+l19Y4dKyzv2PNhLHNkXl2Lw8lHa220mCRcWPdEkKV0q7HRh3TafRFsP81pXOqECwdQ2XIZlxZ6geMAUhKc0UijnpjCJNEmHo4uIDeWK/qZ2/km8X7UGKvYchFnvc7NTfCPXhHHuF6p7KnvnMMUWc6sNYu9NTSHccrG/BjlJ0Lj6fyAdV304e0z/NE/zURUTq4srBdvh7OaGoOjPSh2a7jpVc+S2Pf+aT9fTr1qYGUFb+wlfnmK2dXzCGZz9ZLtAh/gFutBlEYjO79OrDObq82J1lyY/EFf1STUc2zarVkrvmLFjUSwGT/EQNurxcjzi/9r+9bG9xm0tRJo6TkiaiEODZPgTL4gWlNjCAKrOp8nJYHIAbbctYuFB508HOWQ67VkBcbPrnMlk9pUEt89N4+rPkjQWv3Ylgm7j9MsMmtnr9eTixF9fklubU0P3kWpUxMx6xG6rjuX+bTIE8++3x/FJvsEzxnK0Y01Jkmrw8bZtae/49qD+uH4t+ISwqbkzOtyrAHo43CyGb6puTYO+4bJ3ZyQjyDwNIFcZWsUFvMcye88Xw2FvAVauvJeFX+Q5rKAr6bLSnPOppzdNCX+RL0aOcC3rgBDQA4blM38pYjD/OzwuQWs+3tFB2NaydG9KVx7U5xRPJcPf/t452YE/tWYdfCLg/25GTnP/DzJF41pBUFwAfjZ5koN2D0HV91zXX7Bwa1PpeMalofLXZheLxwV4EpANVLk+h48Ifz8m18rLUebWwVlPA7AyVkbVyt3vx5rMcVyHK85xwOAz/IR0/FZkYeYfOwcwYBo/tN3IbPXOswDJlQuF66D+dbylvP2Ibiaq4Xk7znjjLJwbKghtqfvBl+/zo5po5rDgVEscxZSZubzn+sB9xPfUDynwuGRQ/z1aTzr31MjaOLKW41wd/zo8dUk9w/8STv/Um2umBHSG9a55BP+nU158TUrWqDceTcG1uY7lHsvllD/k/u8tRIoISma/7/OBcj1LMoah7KF1AbNb9sM1vQBPLkp+DO2038gbE/ObLwHsGVhn+4+4AUvyHHwYvX7L4XTYyWMFy7qkSehceYWensg2+XAl72Xiyf69wDV8wuUb6YZoPhFwYavodkgRgpwL9eeHyjLF+lCy4WPOvcn/dJUmXzUgs+agh2r5/dumtp9jeCfcXJqQWNW2PKAhxflvpsf++IMD0wfRPc9TY7jlka6MnM92rf8ulaR+neubzGVRBrG7i1rVmRs5KdX8d/JibvT1NZz6nnxBQh2GuV1w+oGAAdnQN7qX4b14j2/adg5NDt5/yuZXKdFZzORg2E+9GDoxlnN7E+Nq+D6fAIEC3Uld9bTqB8Z2OIvKmsX6CxjPaeb/B87GHGXozHFgqOjRjwJTkOth8gEL8Fc1H75gtvZoaZag5X0zotN8jf3B+0X8nhOi3mKWd2SQRkCPPSH7yPu7A38aMzEfDbj7x6PFYdXz/bZJj/PAfBfjZ3py1cbfsPfhXRnLPUJgA7Cplw+9GyMaqRqTYIvBixa9GVNNN+fOzfH7YLripykKX+ul8ia4MCJH957DgIDrL72l5+h/gnnesGTrr0f85ohXS4ZnM+lMwe2R/undrFcgq4f7uzgpL5f2AcTe3u5qreXytgqqB4y/BgWGYs6p7RYd+aP/1xqYmutBN1JolHYzboStAB0BqtuuNY7/IzzueRyfMyOzSFsT7A+d1G5d8/G89JWw2JQ15/bPzwHVpascGeM5Jbz7yw4W/oyFQSAIc7ZZWzy1NKf7cDdvWMfCWK8tvbp9nX2en0wp5TlvR8hQnGZ12syxdT7pSUtTI712ex4rqjV8plfGemiNUpszvWEePm97p5IJt/Sro6HJ8D97NusGE7Cw/N4YmE9f5dPwMUxYfv33Mz2TM+JS0dobYNBfJv0FuDNYvwlBpoxIb9nElXAy/w05A6k8dIobPizJDDKHp7kzReKarFdDWLZiMPYWsp1WnWjZ/4ngzl6U0IBr2DtUB1D82Ujx0ODt5utPsx62I/DHh3woZAhrBjy6M3DAgkYZ3P58/Jordk8V8Pbt3BQIHz5QIO4XP0myQZIJpcvXNLaGzE9ReIuH/v1rbOhH9Ig/GZy9kyo+GK3tn6Tzp/c/RTfuqqnLOMM/gopBpIg0g9e7Ht/XL/sA/aMr+7GVTa+ZWH9c6yHZ905bHvdHF+S9N7CT17wGTsPNKgzljKnFpJ/cOK3h+P0PznMeZrjsxdrHD57Wr/Zj7956yYHODnxM8K15Z6gphc5yy/dg7yI+Qss3109f+jzsW8KyzR+oE8dYjUQ9F2wudGOsrHG5JX/ya+1zutfz7/hw+oCmodfI6yT86oSbN2xY3t+6CKPmYe8c8ecsV51k6v4s2f91QKPegS3C6V+7/OdjcikPJQ85HoGvmnAOBe2rR9wFrFjtpvwHOZ5t/leCDcFzgO4aiKu6un2g4iDBLG0h2+P4DNnboj2qjgiGG9N7Q3PKXx0BBsCNaVYXnA+9xE/DGXwQzCNKLcG16OQK5D+RQAxfSd9v9y8Upoz7ie3wsHH5u8v0JdU/BIrPnsvBoY7pSNrztjccwneF75Z+s65JsL437EE10DfVY+xKnUHmOgYgJhfSzkfAw43mY6LGPEHNUe/KJ8w8le5BCbcczr29WKzthDzUdqLM/3Pe3iK9vzCnrHz21wjNR6nlB/eywTu0fF1H2ecN56FvZjO1tmzG9KCA2h/QTKIDzp93L0ph/qyEh8MsJypUSXQZp+VcH06Hjmg/zEufuJNXaTLD7a8EmudPvNX1AdtBdlXwxxP/4JnDcee58Rc0vlWPw36qSdZ8zm/iulBBhXB3tzTIfwuunqhNxdjTiOPp4XFy4jNF/9lXe11laHxWFRjiOs39FzlNxb055yNzp7h/cj6U1ezn888UIbvgzP4uex8m5p4hrcLszt8VywGlrc9t9P0UKfrgFh3LHC7fi1JZAnxJ+nyUDPDpwOW8Y2LrX7w1gWykprFAG3E9LSXT/MLvm3rSZx5cFd7U19sN1bEsqMx9jeG2heb3fTpGOvSh5eyifPegaus6yV7/Xd+uxe+vVjW1gpZ8q830I2DNZJU+ekH2kgiLvbFg18/yJ+4nisOxgKZ3yG/rihCB7jbdxGs+6Zl+Y6KfTXGi7ZnnO7wMtaH9XlcxNsP6IDGYQnEqIloUBdxOQrFVu2gGEVBks3zdV6G2kpg7/i+z/PucUrw4Zjmch4HoKtp9vI28NEprGdEX0jx4LOi6vUirg41Q39nIer+N2tNn8CXpUFHrtgEdn5cLrD5BfiVcES1Vxzr50FyNIYB8RusFfgR8rtosQRTSHCN70HD5g8+R/jwXSaxqxE9n4+r7mqptomzRjjtQWdzXU3FVQn68THsl3myOa2k0d/h9AAAIABJREFU/9b0yMGajT07XtewXL1wBlZetJhL03E2r+k/PvfGNjv7unszqDNGvYhwtL/u0BMb+S6De5Qw9OrLPthx1xeUPyxnR959CMJAnoel9bPFL9fqfPXEI9cFsiveBX3sfbFKNItpr9RA3vsheXnw4iO+NTXN+nwU6jqEfTCP9RS/fOVQ7ZlWfbeG/I84IsjZ869mmKvrcgT06roewUUz1X854OIjZ1DN97Vij6qHXvOh3lzdna5pUAWa8uGaPK46E+N4MKJmfWb1kUNcQ7C99TZDo69W8ljTm5NVVRejJ5z7KLL8Y4RTlVc7XvqyXGq7Mhbzgy8+7POVvdf3bDinszGpO3mibWPanueqCyjivNk8MTjecGtUg3GnkPPNnl0Co7FaCQOLHdv6XH98vOB70N33zEXHd/Gf/PLdC3EBd4GbMvcn4ERag7GsA8yD2eWtCbd/9Iq0t++qnKxbW/W4h+S/Ro2tIU5y3PNP9fH2UZj235LDmn3/dJ0/cc+74/rBzNc/fd+fqze25/z3/Vm8McT5KL7r4/E+I/Vx8tcFflDAFV259gJTe4K/6wdGn+7cmPuPxvVX+7UT0fuBFT2wr+Ekvz3BzBm2XdWVzW2tPUaD0el68aXMteFPzdkHohEdjR4jPr0CrO3ZE3Q1xlaNidvNoLPcjRP+8L1nffc4XPbnjbEy+kboI6l6tE4azsv75X06Q0+CBT6/PnsFd/zyg4gn+6d/XTV4+MDaP4LcGJcL0dLBxKh6rvdx9Zh/oMRMV6NyVQ+7Lrg2ffM19CGId+sLNE9t5oLK0X6XbCzRxnIULqsXtmqLU1As9Ad+9swPZmpL9PQx/hNPd0A/eyK+tbNuBb2nXJfuwZkbzgz4TsHtsCaAz8Vl4/15hi//QRpDg+ssHmZiAGX+5tU2XlISKPRl/Nn31oVWUoxLjCGXWK6w3b02tnE1/s5QLHyJPXxNCnls5AJjLQ9u+ZoBXj69ryEJbjnVi5M8znclxP4Qjb/x31ldchFzWkVeDPGnaRlALjcp1fSmNrr9wYiqolXAOWlrPgGHaM9FaW4/skTDDW3bOC9HdYjEdHoW+WQNlxHWBUHBy8WsX+5yvoayPdUcudzGxXPfk3yujH/3STOFuZ/H3lzli+k4dMqNp2p6xdhzudQk+Ik5B3hK7Ggc65eNVWOp+YH+XkHyOBtTTsKnjmV8P3CHImR1AVEUxp8xWsSdff445L5Y1mBR3Jj4uwIIrUN/9q0N7Ov7s4eCaVTXgCt27ah3hG9S6uwPQJeAuJffALbN40Jbi4en48tPvPYzrkBm4uSTak8unbE/scdc/BFdjCCbt7oJvJpsXFWtN/iW88c6xt3kKl4xgBj4zcN6WrM+3E9OdsXv8Jo/4HziHX3PpL0whjgQ9oYZawflcCQMpuJeG3vdgIg/neQTixeSDHGfubbGFBEL8YTgzGCW2vXbg9YwJ8xBXv5sMkqym1ZTIC9v1KmrnCcx/oK8v8LnxwRcNNkwfch+1FZe3HADVI2zlyQzz/nQtPxFw/+s3jhsKwCrkGVgX/+Zr74Lf2Jb08LV8eQqVv2xvcijfnQHl7X+4JC0nOXFUxtclfygCL6Cia33Wy82rIvwDNWDMdaQmwHdDY/jfC7IHn3EgGEMR3w2XOcTIW66seQRUKNPUTYi5KjvwprguLMxA7WX6Viyfyo7jtWjIAI3QvxIPhux5H8q+HBgJ8vD35QfGyRjvLXxBa5NeLiPnhzuWys2cxBHAI+s348A9E1H8VAYeEnUaI6sQsWD8a6T/+yvD0NxJ85Nqy5e3cF4rsPCS4BaL/4hIicaXnD5ioPHWPCDsAx+/y06v0xg3Rfa/dP1vXjXfr7//Oc/icOfF9/j+I+LJmOZlX/6zsKcP/vTvzK4e4p62v7DtsSYEtn7xD6IK7b/Pfq9EI+9/6p79seFX9LFsGOdYYvWpybBe74Tb2GHRQXmq2UlybULRh0/8/jiPIGw9/G9t58QWBbu+pJZjpHjBlchLEjm3rM9jATYszBbFnW1xibgGm9M7YsMwVFrH/jNEaQ2Q6ofJjinhRkePppLcPmwkKim+qHOvj8zjLPxBTTm5apO9+8lUHCnw/yvJtLpz3Vnj40xXjOqBZ5qJ6ZxaC5y19abHXCZPro+6FYUlgaKfGKzU480YAry+g2wsNVAEJ/Xo0tODMtuu2vuGI9re3JS1/aWxrmA2yNhLxtoVWn18nAWNq4HFbrZpmm+7kl1NS8n6SEH4GJfLxiiGVyWVVPfeoadfPiWVypqnVZrbN7dB6Rh7QdY45u+PEGohcQunMdJDgcu/Qo0pJiLiRn/o42c6HktTxr4Lqra5UVZta5GUwLOkD6Ilx+OIIi9PEXWXlyiCMwQoj52Hx6S3DCfWsC3V8YTXGf5Lob6/eBF78dWuipu4vIpRSFLSNDOz2raj1jH3YSX/5JU2zibZ32R8XL8OB9rD7YiFICfOKXjupqFFKGNvZhcGj7EzduKE2n0iHFjVeP6W6bjwx8tyb/aylLi1vFJUnav9gnOPIyBw3zZXR+emYgSm89qAi7/wb889wtfQtQVH+zL0BnSjvazWCzEoKt6NJhXO1s88TPV1h78mwBEO2f5CMR+AvG1FqK3KYFCTnxBV7Xh7zrbkVTYu5Vy+Z3NEU35eWN6jI/dfFfsxCwLVdzRuDKGpgQ/nuWx5gSKN1/QmfcnD3Aa16LiKnfjFxBu3imgsYxMX9waXS/kYJIRTXyUTBtOtGCXSEyWt82q41KBWdrVNx0Lkev9+6NwxfMG9QcFwORePviDQ43Jv/6LL2Rc2WUpDKoMUgjNukzU1UHshjxn6PrrBdUa7WP+ZKX9wfryWg7kamgWcQ/+ra1xi5ddfcSqmZQb8PFnMlCerEcdxeWJ2P+O64K/94E1K6zho1wSKL/j4XXB5e3/90yruF7ii+yiPYoln/I/h3BcaF4hrAwuPtt6YjT2Obzszgb8G1+291wf6jj256jFsEfU7qhyyscFl9xlFwU2b+79lPy5F8zxxparXzusn0z3tUkHLClnJicXzw/sshMl06mpLvkCab/QFJw9efHWZxRcxzGq619JG/OcldnNYDLbtOyLVx/K1us7z8tExlWwe2UzVCqCOJ/+ppx1xoN58sRvc+pbJZ3pW7Tzw8dGHNLmIpeuRcH14YuK/FNmF/ligrBb84yaufXiOXzywFn5ievC/WOPBmR0X63o7ovq7g3j4ifa/btz+abDPiTuMtcnz9VqlmlBLBwZEvSMx4+xeqpN2BmogVz9V9dlkJk/V78U+ofrTJ5Tmhq23KJ8vKvevE++Lip6vcNmW1oX5lOPxzW82km0tKfb2DMXY1BzZCk1RJ+VvQW8YP2lxkr+Dc/4cmLTs0tmaz+/p3Whu3eWS21Hqo9ANdQIzt4+mCsVvuN3GZzbxM7VuAMRzzLO4dSAnZE4cwXwniXm2PcDIGuxcHxO43hXm1xSgj9dr6p4WhNUCurCZTnOME3Li5k6s2f0erantlhfhyqvYmRZ4/wqM46A1vOcixarbQ8++YhrlwUl3+W8s3vSx/0R0/5SC7hzrTtnaa7HP6bNDXt7UBXTrI4fvQ1eaT2H9faH/kD63At0eYovH4CffVDFncFygzD67GKwXW9W0rgis9roh5tFGPTbEmMC9gPwQcnX/HijnlyBtYpeSUNO72PWMc+vhNMrTvedj6B2an1oHCThULeraugSFWp/enlBTMuBnu+PvhO1PshBwxL0XTeeaxyr6XRYOxpwz+cSnmbnZ0Jid/8R8+rEh7uW/Wchl620Al6V5EGKEQAZD42O6tF2vMppjxYro4mmBr+G8C0fZV2S8LkyP5var8zqUcuH5/aVePaE/Y65DOW8/izvc+ZXD1xTt5kKXEN0OoH3Pl195A0uus13OMT8zrW4cZHRIX/4LOCxWpCIXJZDvJoRkk9eO0DoZ3L6ekSU7OOsBRg1HZ8rye8fiTsBH36Qi3WmCMUsGMoVO6yHWNyP4Gxo00QcoUwxdqinIpu7AhVN/Dd/8hlGXgDnd44JH4/3ENltNIAfNpG7wxF7dRy7AcsPo2uJTyeIxMgI2cW7X7rv/Mv/PSRbF+71qPqh/PKb0NqkDejVT+zPYR1w5klj/QPhei9WroHrVU+pTKzvU+L3/MOMrk/NdHvD/56TPHlY47l+3wPTAbAQI0bzzsqopiT1iXdnZN9yIQ8f5CjLW7M6YRNDrkuYvYNanqj4jw+fX2jAKrAo4qRoJjXIIVsux3srUEUy39cBQcKKxd+RlWAvmlydRs8kBu9ffqhLuL3I/JzHuBNT9vgufhY1mygpmsBFuS4qMRtPD2Nor+dRAsfShdPiZkTnz/Pg+xi5fv9i4yEh1PHhum9+J/jxLot8sRKh7dF/Foz2Bi3vGpjbmJ5xOPfH49lRB8ZcvGcMziazvYurig8n9vUT69cO9oxHKy9+C3t+WH/+MZ/DIdrY1ZCA1ixr3Mw31Lz91Xs20epOSmPCkvTjqh8fWsPnzIJ1jXun2Dhjx9WargniyWG0XGjpnjzT7Hr8QbN/g3RkWw30QIug9qSGXON77s+J04nr4rN//lvymPIeurn0Rpu3WS5Pr6HlnfPjYRqXgTsHAYeKNjFoxKRW5vtH5PK1O9MAwi6ufXHziU18ooh7uKWMBd1M8LoA1XXPlRgsF5sVHKtjv3zpP6ZXrp5Cf1PmPz4XfHW1IHlPNCkZ9ZhZ7uGxM/Z9t7vq2bXRd53YAW9eHgox1xGjZcmjPstofUytFSvDmrNEmzbWeu5KEvJvHJa44dRxGHM/2GFqaAx5GNVxS6f52bxrcvMgDoVZu52uZpQTVwplDYSrPT+ttbXWcpS14HmxfVOU49FDWn9eyOKAq5mZfGLtZzU8zMTSJw1nvb6BPMdpRudML5bVzP0+huFyZtlRhPfxwFfwtB4iXKwy0EFC9TxWHNY72KFfbAz9AVwk6EFfbnNLFTApinnOk/yX2szXk/m/Z/ilujCmR4/6Lof2lLVzEZZEj0ZfOFxspp0buGlkTV/2S5r2B04kH9f1DdtGdfRcZpvfGgHQB2I/o7zlJov7nYszcfW0L27V0hW9DWc+vdfgDt4se6F0fslLVhDYjG/tb69Q0gxw7T6Xw3Renpx0Bpz6De1eJTpa29Pb1NbnqOo37+oNS3kuBt7nHslm43QYG9v6Yz9kuD6w7mc0VuWH+T2T5FA6XMuR+cntz5xFcF1PwIq3pngy29P0/813hNYYDL7DPfyw5NPY4bY3vGw/MORG991b9NRinU5LqkJfXV7xZpzOeacbF6Hat7kd53Da4NSLzUUup7eh79kW0OurhTTBfPOqMojY/j0HYU12gu+H/4bHSfHNfOKyMwvCms4GFaXNxFnh/x67eRKmzVqbs7qqgiiZrxHN/6jB3R4xw38NWnRnk8hjwF3EBgA/76QlPOMOkO1IPpFg6dVbyXeV9X0DW7PRu7U3z/GTiaGviWdwpyZW1JPJnoOm/8l/5nIAywcDyTy4lvsoxLB+cZC0xp/YRjcn+Oe5PI5GgxhPayZp874+ELOpWUW1za5GvkDvC76sueYTbd+6YGbsXm1P3r1NwW/WMj3YkpVP7ikoXh329Y2rBkTM1qrfvMp5e3rxy1lvr9MEFX6YVFBD9m8etYDwZ2LOpoP54cFk7M3ns18BFgukZ7y4a2pzw/Hpy/uDbDP+jOlJ+KSn8GpZ39BiVWi65K0TfaRJHfhIeQ/Wi6/O9eCTCwxfU9wfW3d5ecqLVrkAXU1Oy3n5F4reqoH0WRF98eePbzGg7AmGbIzSf2fEOnmeH2gqwKhDG/ND67HLa+qQ53Pq7NkJMP+nDnv2qFua9WMZpYvzO769olwTtg2kvxyIxcV4bFmrI7WqzSYIAdXF3UjWOVOI/LhzLDYW7JdzLKt9+yM99iQ055uYPxmH+zusCQM6cQXeWtoftD//jfzVkslhXwNmO1tj64fI2tkCePacv6kEWgfufPAO/T9x0hp7GYS/wETcYvDxl+pGcyGO2Yt7nfweIUTiDG8EKFT7L+YncD0wH3u8R15e5PdP+/3FQ9a1byZ3B39GH0LxvEgH2D+l/2gTWgzipqdr8n/G+QHRs45G9CyP9/GBI2is9YOt+eqNeXVXQUMe2+VtjmSV35OqjsR7trHvxRcY8KCwvTraJyk+JfR7GYbxBkFviRfHvFXrEN3mi8C9rchc1BCjz8Ggnn5kmfPhebK3U7UmnRytnTw9G/kCrJ4pAVtd9Z/GsykKQTqDvZ+X2ovsTSaqULJFH3D7OR7+64us36qhFGWcglntRj0vGZraLjzxz3MtIXmMidzN8mb65hmLNvroaPR4MO3nkvpz/TitC8yjDFQ4pAkQDUuvGUchOB49QPPR8yig69jue1/PppyLFTPtzJfMLJ+9sYfz3sm6fG8MWVcPa++tj63n3I5uDWzc8Oq9uh4u6k+aryZkfjnwrpbGpTfRSIz8+K82ctqry1MQVsbqOv5YiEMC6lzwvFkDIMPHgQo5Mqu3UQR/RjyLx9oQ/Y1Rdfan/+G6Go9Z7NW0Gu0JkeMXFJ7ftU8AZ7o+KKW6lfTUrTS9r7LXth7s6xmPetYbcpunMUqihtPU8t/9mPFbRmbP6+nD8YSzdbMPljSuSHd8ew6QA+eXS/ZyfPTVekTXJ2xwMzwVE4XrNNTTfdfNv/NoP+JJfrkQK2NZt2ts9e+uAybqR66ftpeFFLAxer/QGzT/m+Q1O3V9hS/ZGvfsiQGT0eifHF/bcLv54CASjHMuj03KZcGP820obiFcWeCT683fVYzxyBud39yzTUH/JEUS/1W/2s97zVUHlEfuXgm92RSBP6Oyqhl9a/zPm6LYVTr+9WRE3fc63ka26q7JuUNt1eNb4UO/51idFDTs3vUuQ3ImSF5qgOBGtv2hwEWNKHyak9XyaSbH7pXETEPnhq1Ce5Xg8p3P3GeZI7a+s43+4uHzC4qk5Av2Db28DzhutAAF7/rtocHLhT9DnMruzGu2nnHBs/HUdzndJx6EXKcR/EEaGjtK0PBwuAcY5OV4YiSklle/39wBLMfFNTeODHlunW3vAxC4yM2C3RbZ/PjhLvZvveDuhzCijDO02iCD9zzO33gM9WaRuKeexGD3fLNyhufAeGczHXs+Pr2Cm4E/jkf3W3N711+kNdcPbaTjSSSf4yW9ueG8gW3+rPwkhrF6qhEcMupUx+31n71xn6tBpcXKMBZ8fH1hQf1K9aqLF1kfTnUG1fs2cbhBB0MslyrTaE19MTwaUcUTTCcMyNpPOItBH2u58yoUaz1ZfHaFg8urUF1BnebG1twYzjx77sdPXSC2n35y9wX58RbUFzW8eE58Y75cUwhL+7O81LpBnDLQgKB8asuae0PeAozyvyEH6y8r0EM/uq8GaAjY3FyEPFxEmA+QUGNuefHEVUPTo7Nxy7N/6G7/nb0Cc9k5U48xkYmmP//6y786UF7y+y/FZ0OdG55z9moBmL86gOdFlGs/FC522tmzNu9FzdccXyb6e9YszM2MKTn9cs1lnJr1YiFHT/LLj2T1jpigDM+EIO1vX5vn2EaUeeHrdeNP7GUXjk5otZEpgxoQkrnae27ig7abJDAtOCX34vrwBrxcJa/2riEoTefu39yhFPFiMGizUT+jW8kbg/etLtxo84PFMddsluUFSHnsn/qzIiLmY7jVjHoaA5l5SxIuYi+fHOVqf0FfLnKCy6fnZlxzCvq1H/a+LTSDsiAwojavVBLqj99liQv+sY4XyTfh2r00O76yPlAZqKv13nw4bed745qEqyxuT6uJPnmBJB6c9yD+brW4zsVzBHsDtr3QrIaFJd58P3P0vBpsrNmoJePwMCDFe4SZ5AOcRuHcQ9QcH1J59D7Dm1GSTT2fmNc/Sc1JpFkrQT7q0iwvXiXc7uU4vsM2IldFjeDTc/Wff/qb9QltTVfUY23Gbqm5/jKvJisKJHlJHYi/4CMnfSJ4Pbk1rM+ZxneKj/90f3LBwaO49QQyeKCvNuazZlruJ738w6pJzD0nhKhapTWo9wJ6Xv6nBz9ymQ41pFdP87+q6/B6F9DovZjTgtMqrqZuytncq7G45ZRUujfnfOo/Xuq//w/6AVP4GgfJDmbfUEdyOs1a6W0KMTaVRQYaxvcV/D1CcD84ErSDbIKPJh1EpAxx0b3m1KyPJcOqALomCxajnbu7/D7Tfg4XbENLRBy5sC8QDbfprKi+Kx/8B1adPy1q4LJDoUft9asDCZSNluVSxxmfvKY+4CPcMFI4fp8NRm48czwrduS8voeyZ1ed+J4zZY3hxvRZ5uc3wO/9E2AP7v1N/MVWxc8ayw7r6hr4NNMD6qYGzyb+s00ZyNUCC/7pP7aroWf7gweABRopXD5Xp8n8MZCXcfdbeWKLH4pDC/Eirt1vf8lPePWCeTgaEMP14shaqgJFYHb4giwrcly9+Ih+9Bt8sbc+eF9AxPVgoSI+JHKoPQZsnQ4L/0bqkKOY2XcvGffkbe/Ri2njq9defF9ohlCsHIkw12WZviODx144n2bjqJBxcVYD0exgPz3TX7Scxl482mG6GdQjwwyXI3n9xj5c9sQ8EoItdzU0qr0kE95X3VmuTnPDl4/nnj/+trVs6gRTxSXZFa6PHnj2oo1otToTMC1hagI5lz8pgHDbamctMGDvAw2YGtyJd2n5c/JqzcYQc2M783qLimcsJAb+G2xeAvMn2/CKz2XvGP/9N//oG/s8mCGBHmACKvV6GZf9FFWtgJ/ekItfLFx+csABF7mz8XMvWBWWe5lfippO3HiBV5M5AVyfZArs0jSWMCEX73Rrybu2xux9Yb45tfOP4/EineH8iSGy/zBdXqDH/hfvoKcg3lUnwv9W3gJXS4RQN2S/eDA5sGfAXVzmbC5KX/3tn74AhyWdFPQvi9lBwOm4HDrPuF4yY+rZlMz1EyqjuycmIi4TkSkxe76/uQN6MR47vSivVQICASTry15pZ8O/XJoAH8dvbXuXvr9QL0HLZZ1xUzdNXhRrNLcWbdcLxG3fuFdnV1d/QOKeYlqNxYV+Wp/eBj1ebOvhj3OzJ28s+e1f5Rqz3uArN6A35ul3k50OAYQc9lneon770QbGHoXhGJ90WrE1bFdq2fe32oZm1z4z+6DPLBnOvXdaQ82ItD/x9+uh4IXt3IivlHpc371S3aQIf2w7j2WQ0QLLYT6MxhcF62JrWT4yLflxk4Ovg4og8pPz8JAUkHDiY1d6so/Oiqpmud/oby9/aYE7A7q7E11h2bl++cQm6Wzsn3PJujyiuDRZ8Mq96xlVDGQxYqztN77R5ARMzQSTd2dKrTy4tCfu3HQFOOgLfjO0lkp7+9c89T19IbcOqcjmeO6Rr3bPlMxEGFh9scinK/bblyOe1ZiYRgu5y8vTe+blZ8UgFxSuAhdhzZdXf6w2Kfca+3yg5PklUAjQ84zAvz2o3apcnuSsZSnnhStlRMe7GtGgvvgf/sNqP39Nh/gS3rpZr3YZiRjzv/b/QQ/sVVrOmNqAuPLNkKI9iDf2iI7uBH3dp+HhnhiYh1tx7lc0QAaaPqM3Qg3Effc0DHy/4M5nfHO1GrT+5ITNOj+5egivWrkvzqM1VXmMvWdUJVyY2tK3kKOUydmr8bosBib8+SnvPQbjru/1PsrVF5txJk2sqWR5cVk1M+RAuieOQSjSu+YHWX4Aw56oaGHd1F+W2tAwq2ti8rFzWaz95mduksUohnW4jbsng3H1B+oTxZmokQvhV3OWjuNkbcTh2QufPRt7Bh4He8+GTWNrzpUFaYP9cq623/fP7MR1XUbrgeB45mue6mlP3lz4HOhMLeurNHGs4/sTTDVS84Yasrn7SPPqYBOoXx9PjKdV2PnR0Hyp334+qp6ezP56pPBSNdO083p7Oc2WyGXjQsx/9dPRagkoi52JfXkPypW1PcqvBmq3VllDklPIsiZPyIhJWD4Bd1+WF8R1n/gL2JleNq3tKPmwvkWpOZzG2NfxUeN9XTzzaRMH0/RbAQaZa03sztt0zb1eFfvyszLaRjQPGEbDG+8++f16RNdjLkM1Pcbr85SmIsjyII4XciBf/qxioyfgep5kDEpQLuqryeXZ7WAMxuAAcjN97F6jdCbWWNzeMf7Pf/7Pvj1/7v4qbOpQ9R9vQxPMGOBlSz09N6jzEpfJQT1wggG/NVv/1D0L332OZnys+QVIniJ9MUxFfI0yP0Li157YH7WGc2N6NP2wl8e4kJDTHuRfpf/PvThnzz00bjjVn/nPP9HYvP+w/guleef/n//86195V32p0Oc5Ryux2NWc1bRhidu+MDHsS2b3uTjbAFZlb/yBgzAGony6PhFyB0ZYz0u2A3FeCUFfvV2j9WAHgMHx9qM1NbYcYB9dQUOBFoZxGhJ3L+53z6wXdMWoTOiRu4WV63Sah7Xk9A/9HabIcj+fYa2vPYef2rAt74vR2Is9CCL3AOCf/Njo0c5R1Y1DwI3maabZcKs7mjfsw6c2krWmZq3OoD910pDWD2Hx+Dde3Tgfq2Db5opLc4DwjJgvYDo5i42t6it2ONLwGAY5L32sOO7nwkeTtmb8X3nI2zqvCPt+SeS/+wRgEpjby6W7nn25FaW4N+ZV0NW3/1Jfrq2dvbz3qWnJx4ILOdCU9XOPqr+1aDvc+sm2ccWUEzpX9RmTJexe6vvWKM3OsV3JLmA/CSL44tieCXM7wGJfYywPsDnu1SV93CDQ0K+KbBiG0YOu4Tbr1UBEiyh4HBdIYhwZicxyfZJE3xEXIlLdrr4dmYv8H4Vw7ufeD9V6oz40DxOaN/4CbppSShODvtP8fa4Yp7Ox9NkKP6qfU6hwGMGE8+k75LEzXJGLPRjtm4XUoo9945iemCR4zrkh4T0OabueBvI4TpP7cMiMK4/nvLUiUKI4RVV4WXrFTCw8zlneC7J9DfivuJ9PHoF6G8v1AAAgAElEQVSEU0CjJVmjwGI2t37DWvhFGD6Rh3+O4ETLU6CNQutE+duQw8FuGyzmovCBZzuc81Pvo2c9MMAg4lZbDuG4PIj4p2v16r/Duayt8rHFapJp++qCj4MG0mgsJ1VJTx5yB7L8u3m+2PnkMDq8ny+mE6IHLFUympv156ZLnH4TRGVm/7zUQAsykpiW2p61CrDlpqz2rn7XcJotuV1yee6AU9W4xRuAPvVk1xCjvGlvj73Kk1/Ni8leTQOWsc1uDfUUX83LClW8ib+vj2eP2ClnHq4CqwXE9pdV+ZqzWnwxYDOS6z0XlDE+2qglmswXjwjre/W8WogFUcb+qfmZTn+x4Dp2ZuyeXtCD7/6kYjtmvATEcJbDUCWf2Ds3Cm5H7E+eWg5LH6DsPOy4Fl9leI/nyfMqw8sbmfuBVc/y4yP6+XqJ90h9gRt7NaA/WsARc7o8e3L7gYo+BIFjf4TfvM89o7+4goO/1sBhTEid3eciab3POjYwu6fKf7wXchGG4BmnMcSTJ5dxUMuk0C7LiLG9py/4vbhu7HSF/+rGYj64j+iv9RXMh5utYV764u7CmwsmODKA8CKW+I352Lc+FObjYrBvzcxjL87/5n+Zlhen/K/T+AXEXpyOfv2yriT3AxGsnXKB3ysXjG8+PHthTt7+N9uBpBf8P8v3gh67frggvneyfSE/G/XwiN935snGOh99XuwaXjGBcuu25oBVCQf0fbecd82p3fqzXm8a894v/PKAF+X/oPuvcqDFF+okyeCXGP7v3rL3Ly3QoTq9qQs+RuIzHu3uZr1NgOt9+1m750De4zi0/bR/9A56vqDyaQ56trG1uJ88xicZVsIX++j4ckCPRvo/zvmZ4WeQ+nDq0bQ+4F6Pq7F7QKx+jRjUwnz6QYDbflLMLsb0D5fYo13uZooH3rJlUY3gm6FBq7U9qXc9ePuE/WGyli+m0oOJ2Ec3ETFVNynL3dw0EBOaiAOFX/TF3FoXFZX7bgPjRmlOU7TGaSgf/HFuEBTBzT0NmF7b1BCiqkoBbOzD99mvjw1osm//RvHklvjNv1oePxXGqK7QLd4+pF/uFwRXxnqkzuzf/DpbjF/CIFtzsbDRu8xycSrt5er6kS/oxT0a0aq5YvpiJBaN0OKPr59Zv/U9Oq2nduJ6jqVgby4WcOU56d0jaDlgI9PpuDX3jXFeWcMLV0Z8rq/f7N943cUBXc/Psv0PrfKSkAeFfOJyn/ka6FOrFbEXWu3P/fjcl5LIzD0itewGqab9uLQHePQ1sjji5EAfVJxNObvW/NSKz34Iv3MOBCtazHs/XJfRUt4LfT0OYwhriuc6/seOnCcf1mx+5SD41X6Zp+fJ96R4kn5rlzYQ815PYOrzTDl3tqIC7L00XpUrj3Aw9tLVi3me48yB/f7E/YG0WrcSUW8+5ITyyM+wSaIX1/TlbOTTIJAchAJaWG8YcEF5SKwo0Kv54fJFdUzGYoi/iMNjygd+f+Bu6mIqnKgnh+tcvl+U2bVGuM1fPNiWfjfaVz8576YAN12oeQ7t8F+9QNWaPCf1mcVRB+oz0wtsDA5WbXCCyG+95cl6PErPZjFE1zfO+IyDotyyyYkJfLDj5odYbPjzWG9Y56eysysnlw0Zsyl+70b9c984noosNjDFJgbx8J54dDgOd9NjWw8xqE/P8RALHz6vm2srF56sgnNv7s/e2PZNDlzauDI625/nG8JZr2f2UtzOgbgpYp2R7XrOWlbi6xCyjDj3QhNbmd7VU4sB55VLmpDruE0yAMGEfb3nB/CLr59NbNlYqxwNPI92SLF+r/iNmf3y1/bprbmDjl/OXNY79h3XEzfBgZnmyjN+yuqTyK/15ST80ST47uPLDTGx5Vk1ncmJ46bM1TQ+7AxiHeNk8wQ9ixqvBrk+9TzxR1rOy2deEO2S2Kzh+Gpwd+l233jO9ye5FUU/pHKmFkZnOG9QNz40Zvh1fdjuY49v75pLeVheORqVfb9Wx3H8lwSfKa6Dzy8OzVgQka4CvLB61RLvGdHK85j/WJvvFOfF6f/9Xx68QM18NjSvVlVWKOY8+ImV+XQz16D9uZA2efE1fd9Z3y+c+S/O/46TF9Pm4gVzfpvmX46j83gX3+f9n/dWe9N7kxx0DjXwtad9Ib7nW2zvu+a8QM8vJXyBnjUv0tGQve+iIx79EUC8W3T9kzU14c6aP3dPFVnz7jr+nHfs5s++g14RIFnia3/0PvtVe2GZnloSjzeGiso8tPPtS0WuYOvIVCQmzRQlHgW/eNyD71hk51LqiUHb8WCTi3OLzbG5zkOMg2jWU+VWzmM+/1sKTu8V4lrI25/sL6u9t2/aei/Y/iGiUb8Z6m+fIf74nj4BtFojqrxYdTw96MnuvgSszArvPXEivU/jXa/WDSPCZxz54Xj42U1H5+Xq1wfexoB0XA3UFaLXezrku3zkbnTzu0/cerVaPOeQV0Fzlv4hHe3VF2TT37k1pkUmRiJmFsp8erXcOnLx6+pTB36Gmi5ew13KmM3qqNCmBpPwMlSGYU8QWnp/0LtXCxGKFr54chiqplpLlfXlb8BxwgLvw/L2ukyN4+dKGuc9gx7xvbJ5sObFjlZBD7Laz3e/uC9i+Ye/POEounbWHRBH5/zosadYGVGTxXr13J/6vlqzLlAu3JWcaz6XbzyvpUTyGtkorI+Oh7ek5WqdrOkNPZs2Ei4fPIzV92ipLH3Lw2Zxr4pPrCyHAXB9kiQXTTAoqob3NK6vgBUcEL3Oh9q+NcL0/flFvuIIZywF69Z2/h/nF9QB8T55CZrD9eeCjrs/i0okeh3JlCWU0mVq76jNjTlEg4vxGyvW0PL5r7jD6E1hA+I9oWvMzyY3EAkUvTGstZ5CbH7mm3QbdGIvSKzZ7mCMi9Xi6/1xY1AMOS+t/IkBORu1rAz8RohZtiZ/eVvFtI7nJzoxZ5Dx4au5vst1ULL0Cy2BwTO+nOZ726efrfaI8NAMqD51SXW9Otr9lhCCQz6JetizfrIn0dsjUzdfsu9maVSu0X7yH18jTkA3ObLqWhb41UwuK3/a8OpUR8/UXhGUBz9QO7J+eFhfLqbtpvfrQ3DTl2e+Y9U3W0WOMYgV+2ZQU3/YATcW1t3J1YTR+/YQ7ev+D+wixdbTX/KEOzHvvdn45TYPcHOhY104Gz7NsWduTzFciHNZ6DpDfVlKiZ91Nsbq76WZ4nx+wUJMOar3SC4GHtmZw9d7MRa/tjU1Gt+eH4zBgM3NsWX/6avM4UGn43IReOluDmA8meeDf/fb6jQ2GPLsB4j5Hu3zV/klRwTc3HMV1Gutr+XqmfOETxO5GHC4/g1f3PVhvW98rjRDjt370sm4HlhHMMaAJYQdhgzXfU3ZvXxkAjMBurzsTHyHWGzMz6FkHdt6R7Rp6O8wMbrGpr895MWifch3YGhPXtZRAudxfe1q4d4647B9cc6L1sbywhx+X5zzDjovUPOi1Th0jfQ08i7yv/4VPxr3QAEinF10O12I/gyeo/suOi/G8+56XhAz9qfuwNFHKiLpN/WDgt3+Z0YDetXCXnS12K/Lay/4U5IM8P5359bcF+f/R92fF+n0qrg7r1Dy+7mOW2R6esoL9gjtn7vnrLJPEn9pCJr81hKMWtBJYXIws9lodc1y9/7lCs3CSH4bkE9Hzn98ceHd9ZsFIPt93QjL5cV0dS1UtxgNzbmYb6+tac9FCz7gVIJfptmA9Jza893XF/pMP+3tz+LGsd587cZxv1pW8md+VSSSrxUMGWCdu/lROx7rDYG9i6E25t6ns//gT5ysT28gLxfzYkVF51MnWtDt4cNftGIvQbFkbf6yEfbluRxfm/iXrylUaU76aD4kXOamnL2ntzyhe3JW5nF9NWc9ndOtW3vik5Moe2z+y3z187xrXL4gnWPnTBsFiSJO7+VfrNZUYILyVsP6ViXqkxMdZ4M3Y7XOjk26IImbJuwBdy9LCds/nUKa3+Vk9R5Vc3FgoGiealWjYctRDoDzTWP3zeyanoHiXlwf1TgdZIrv9GO1W2hAi0LWMzYZ1x9dtdzVIOPJzSA3Y7remNNu7bFeD5jkZ854ni6zf94MNA2aHnmVabBh3UsguPlJo6LmMz61MO/8yggOpcWP7DlveVbhYQ5vEHGkzQd9rat8Wm+J73mOWrznTwxJVNb4xZggdgJ1F4ubbef2VuhjL4GYO79p69lc7JO3+Pnkik/r8man/9F594mSGv9f98rVLNN0nO7v1wcp/v02PGR+NoFJVXSRri1Ngax4dNTeayxZ7Gb3Rj+Uck/QN255samHnw7EMfNZbX335xspYw3BNJfoZ41zdg67N0MwHx0eUnCzPXhiaTzY05Gdw/7sUGJxf5kAdP/O3mifnPPDtyq6po6Mh5vEedzeSaCCzCOBQQRSby/k4JMY19gzus8CN77wU3PrjxFXp7NpOnywvrvCf7MOV/5kc098mX0XSE5I8uDnW+Y8zOFmgJgv0fcMtk5UY53zQ2TmRH4up/s4f3BdTcBLQuQVVZbsrteHwfuctxJjUbeA6ocXqlzat5f1aJy8h4L78Q34yV8+rrvX1OLBVOP277msiqtj+RVTvupBOJ8f4ZeukeW/iOvEATLJEc7f2PYKK5hcWKq3hplqA908lRdwgrRkKQs5JDqtofkOXPt6l+OwPZ/zJaAcxx1MlZODbNUwTW5Njr8L+HrfHNYpXtxZw9wcxYuNnXcH4dD/ZCL4SaC/zZJUT1fVqwYLhe+XjqOBT7Q5Y7w+IBBItXd+9dRX9Xe/Bvt7DD9+CHf+pDFV6mzK9TZRNidsaFJF1on92qnT/0XX+cv7KrBewq5uZt/1vReWaKqGvtCshgRkwXPM6oZx6/fP4BeLF2w4IsgXt/LuBWlfnPcXghRMRzdsRl7HJDbPcQz+KgA1fdGOhaJvZsqgbvTwwSf3cF6WC9Mevr/y327/k7fSk128/j9kTg+OhO+BsEB4g/h+TXyeC+e8fLyy9gfRhJuPF+Z59AU5v5D4J7+c+O7pQfsjPznor++MUwX9g4tS+QUBG7Qef/6b9L4Yvzrz36bTn7/Ty/5Sgl+27JtARPXTuqlwA/58oVk/y7DncX1znS015QMdaJVr90L2fl8SWwZYrAXNfr1iecfyiz4euJu7OOItfmHbxyz36VhGbPI+Bui6UbvxrWNlMY/L2OW6eVRElbszds9M3HuvgNGXutXfBLFGWxzVQdCQXQWM0WF/s7LXlxdO9uk+jK4E51JLd7KMOjPYd1wNMVRHz/LNHLtniWWZiE6cROS//XMWsdHjJw44eYp0xo85D6zmrumxzf/yrM6LW76LA88o362DeXtX267Tzf45t+CN/+gdfopJywD5g/scXy7X4TIWzunJlyzw9eSSHqv0d2nPH9ynb/SFOHUkg/cWuS7Pl2X3kk+faABP+GmGyxwIPY3lO345x2g1ODyI5ceL6eW8cyWHUhVbfeJymdbMIzza53kzjgzq6sokZ0Prfm5R/xP80ZiAH+dk7IDNCg8aS3taLiGT6CzMwa6GC8j0fK8qwv4+3hLjad/HU4A287M6PSZgbaIsMkvDpXybmMcB+tkTyydwHOpnavyxEKG7OQbWLFYNF4N18SKiy/sNex7P8xnrj0/s2RKwrXMzqlyS1SLv9cWYrMdP4JfF6NX6YS+Ge/3pZLysLzpaxjPEKSkK/2Pgf7NG4hj7xfF7buYVMOama5p9UbGDd00CKw5uP8ZV+3bEIGg8a0P5IInT6X/d9GXhOv1JZwg2OdbwGVbEj5hp7A09DQ8n2IuTE65YGLtZvtgmHguoam8EezTGlh+MmLGj2z6YiSw8LstvDFh8cLAKgRwEhIgfYBnaujTgzI2N33e9D+cPok1pTQaQ59vQMHLDiiVB9r13siT2SXBq0HecoH8Mfb3fnh+QY+Pjd0jZekZwDGP9SxCQdvZH8N63Ov2isV8BCOGCC91Z50rBXK+u1ndorE+Jgu5CXj53L2iGTK54z/eNaQCWsgNnOK8mDOqKFYfSqu+HzrnAO+jVwenpw/dq+frlGm6/HGMPy6V7FjERy2i9d17gJH0CusWsHbb6Bl0z64n1iY+FoFGhf/pI/OCeTUwaYyhW0MWVJ36/cxADKjigWTdXz4Hr9uQE48x0azCPOQvbC1HY6skSwP8YcD/3iTEHCp6tvDfrOSNS9KrpyO9cn1TBPH+J8eU4op1XKYjK4yYg97pLfUfdlBevQNbJ09ZyTmd4nPVrxnXDnqIvL3Zdx+47yCHY3hfS4knQQHXk4vbkmvwRWCy1rRwih6+sxJ9/7yjDUZvIRKD4sz7+YvjpNs97VyMvcKuZmEQR5rJnS8zDlBfi/cfVcl/lhSsvVv/mxXjq9s/CT0fPhBe+ECWGF82s6njW6NfGiy9eCGf2BXIQ/mcF2fvxnyqA5z/7s/as3xfqfWFOLdTdcluI/C2tLWEdF7wuo2k9MFeCOUvWzrmRPNt0jNnO8UuOcFCOw1Ttl/vY5/JrOZvlqz3YfLBmfsAIl7eekgMKdr0rQYwvhwSGICQDPHMuUPZrHTvGZ3Kh31+g1NfnHlwBx0nIbJoK63X+aPPeOt/WxsbHc7a26KEO1s+cmJN10YAwXg1ZtocvavzAqi0+YzJNy+WAh4F7GCxPTcGLERDHm4aI1n9a5io0Vxb6uv5Zl87mVcNlnL4TMy3GYjvsuBWhmX7cmav5agqATFzsM+vTm2awweJYr8TH7BxP51yX+xtzuY7C/uKuboIXl/UTD5oEnHWm00MMj+q7rGJSWx3RcjVeDHCGaGzkK0uud48YK0yPmGB794J+AZcVUeqrZiiLqp/tcUN72hQRgBrjf2LBTNZS4Y8RVn4ROb65jbV3yEiw+eO9p82eFcSMaYt1/bqE4xVmbyrl0YP42Cl3fWiNvRYNhjSZ1SxbL7EtJzz7halOObMC4wfW1nxpn1jpYxzXsv/MyO5R5H3jLmDrvNqphM+kcuBjjLNGrzG29/qzbo3ufuHX44tLAmjhdD6enVVR8X6SVtLL0zPc/u4BNDDU3K6BEAvd84r2S33+iyF8NPAYfwbjxZED5E1na3ayVZeA1XZYMD/vq5OrHy0Z5KM/THDX2PW5NYG94Qt0jXbqGtLIFnHA90BLoVwLWMYAm7kRwOJfwtInKos2t/jxIryexUmAMRxdjwtLOWbJzlxB7pf1xl0jbg2NkseZDfv2rQdaxlxHHewGJmRW6s/arDVExXwPBKVGeH048oOUiS+R/8sduV/e1bn8zF9+eUv947cuJKIm31GCcxjm2FHZ926CQccNz8KetC+X7PlFAvlaYTh+PIGiKiOxfDHCzdxvILGfm1iy7czligGt73+bXnh7tmzYFE4Wh5TGlvzhhIzBF+0V/u1TGa+Og15AJ8VeT5iCIWa1dz7oM8WKFvdcs7ncmo7uyyMGJHGnw3s4m9WyvRyytq/as98TNwT2+lKDJ6W05s7qfA/n8mYWGyFCM+8J1b08Mj2s4j85fYILRIY49y4fSU0LZ6IZxt6ivVxvdT9aqGl9wLNfMvyw6QinQnum1bB8LwdKqga8AU2YPCT9WEbobIz4q+BqacpG2S8LbcXrQ4uPjRyP1jeTOrLtL+aOq8jBq+F6IcvCiQtq3HCtrp3fqBryOde+9tOt1qyGwQiP70bCKYq6NtKR6FlerC1v5/gijchWPhj6WTMv6MLPGBfznrOw+9+Ni6G28dxz1qVhggemnS8b7bn0lw4HhjQesRXdWmLFdnIAnSasn3EArVn3Hdv6+85yn3PR4y8/yZFPXoj/+c9f/KPn6kpgFrzcjxa+cHnhnJvAF7N8/8qoYq7VYK/Cy46rvboX63uX6v3FKbXcXwlk/s//9cU4L+599zzP+ehFo4yZHUxJaT+5KfuaemKKQXNi9/z/N78IqKiUlJj8Y3L0hcGvI+5n5/w5PLUwmBOQHpj7tjS//w1+DVACK2agpsJ1FEyPFs8/PD7/LE9mossUn+vLbRKkZH894DgeBecn5GEBFwB44soHomCvXCQqb/nKS93ul8/I6tJUJwSpA2d5s3JNND0h9+sLJp+Eeu0iNslqHX4z6CehkIuXqvyYg1GxVKdluYiHLw+fn1kbs4tBjT+B65u5Db+YRoI6/BkyLcb5wYHMSLgyWF899geH1MU1FoNJ5VzPzvqrpxCCvvpdXd91SC5GTmnPFh1mxTaBXQX/jVvmwxFlDdDGx+e4YjlWnK9Wz1OTOc2X1XN/nB893q/XozeC+ki7GDyizTe+gj5fJ0MtP/GEZtiz2En12PSb6TACPznQgEbdXlbDZlXlYh/YZOAzX7e9fnyQGie4OVhqW64BEKDi1tm8lwP9wdMnRs/1eLQ0UmL24DdfUUun5uNp6HGCuxxim/DhIoTntv0s9OVBD50wZebfL1rxWE98RVXvY8+ifURAfd/DKK5q58fmiE6e7nYOYlu97h89u/ou8lTTKyteYmsGg3Vfu+Zb/5Nz9nGh6w5pkd1/OIY1W7jkFB0FJrP8jy4ido+tx9nzugm8tYfndClBR93j116ntVlv9usZWawHEXK1Pv8b9BYq4hWWYIvAnEcbyIqBs159E5dZawOe4svQSNa9UUqDdXma5YJjhNYnKObrHl45vO5g21zrEJBgSIkDzji9q6ONaZxu1ZadQHPHgWUxXR0GfdK+h7UGg5c/JI0PNouTQDqobgzTKBxaDORCXA+LmPIdRp8Q7a7I2TC3pOn36bPH14wfnDG1lghfgP4g31zuETDdkobcBOXyjM4vfgWHi+ryY+JpekieekhGSmuVdhh6l3jfiZlmgZe695Nn9M1tpveyMyGoeeLLIkw+uRTZWsGWCt3tl7WhQ2DPo75FgmP0usNWu3yNFHKBIrOeHrPGOOQxvZR4AG/c2hx3j6iTfIG1uvZntS7UJMavVvJW2DQ/iRNE1vVAjolWTjNh58gbz+76O15MGeUK9jS23uupBIAkFt9LtXl/xFctR5apHMxZCSX+zuvuw+n6YtY7RcnTPNV4rI/OD7eANy88Gz2Dqx6KUlrTekyjfG57U/zqL3HNN+5qipmvPT4zz3c0LeO0NNfpCN2wWCDY/iP9xL5Yea9/e+EVUPNjvz5gMB9kDQqoTt7Z/Q7PML6+u/r1NJS7Bm190ds1ex8Hf97tJ8fxk82RvbVl9h8qw38YcvdP1fGhOL8oQF4If9RXInnUm/zPTIH5NAehYE+vf04+rcTkeesv/uG0vDgvMr8TN6//ZTuV2gf/7B18xPDCDGV8Qg6GpS+o8yKbgZbOeRmcH9r2D89hXq94Qd7HXqzziwB+fcqL8/JkifTmeqerNbLD/YxbfvtAKOf0T/60XTsvy/nChjhF/0Ff4bhfJsB10lm+yc+Ito3ViLieZ+veGqSSLICoi3UaTxnB8TDmFtvvHM03wHFyDjIEDK41HvdSkPrGizfgsZr5Uzi5v0Oqx3gLNPRAWycBuD7p1fPUjzvOfmbtzhAOmTB/uD/Ocl9dcBf5A1/rET4YmcLH/Uo69hk/dGQfrd4KQ8RvZcKvkIvRDh80N0spTawX28w9E7HYrYc4Uv7iwMcvlJhBZN45wm+QMfifrV+DsKnfULoZ/+kF+/Q3nKUPPyJ+jZrQVd3KkO0FruZvuDoDeeJYk0gNqOFBynK7nb6T8ryYw3k+8fZhfDDFap+klJW8K6hamk8ENSPWPNff8D/S4lr8ekZeBiz6jl49OHieCOTJ8qkF9+zlxUK+cr5erTijD98lYc5+94qJAIGhF9Ru/qpcrkLoL9DFN+d0NwJkz/eN3eqLKA/oDVV6HlmV2gn902uuYOZvXWX49pJaqEk87qvvh22Jg+3X5wwG2A+/KcrzZur9QU0RaazKP5rK06qpZSd19z2qCBU22/blXI+bBX78375eXF3hW48wlJn5W/88u1eq6giO3yL8QYCMjPPTz8/24cZ8vW5e7pEY86kmk8aS+dFyVMXXPupH03Ne0OdP3CWDVRqMeUz7CWgwiRF1QmDOeHJ222uM/3++/kYxYutGtkYT28nMnPd/2XPGTm6tVSiSsvPdLYncGygUCiD7h90tyWYE35P+nCGQmqae6eGOx5OxFYbgPNGADEa1p/kVUvtxfjU/udVvZIL5rnbLSB7XD7kpuiFnhVYn9fB85pK82mOjlj2JMWZ5wBPYbI0l8q09CzHcEK8zqrJyXz0HEI8czAPPz7Cs53owJ84nt8NOF+BoWn/Y80U+n7CxPizcHTFgoyffzHeHJiXu6JX3nvdxLOWmB/Inj/PSlTtbCcIdAvVUYlPqbpzcsYJrD8qwcyZPOWOPx/juBQYG/i+DWmP8s491PX+KePCfLtCT008djb047LGsZuus5UcD0Gw+ekNIN0waS15r0lT7xRBLdID2zlo+HE/uC50+einW7fpQy7Jg/caTqTUcy5PzjTvPE9djFsYnJJPry+O7hOb7MW8Q25/1of1Tr8cgKKmr2foefaRsjPVcf+zpCZv/6b2cyfvtpTqwtV+GosM+FQs/XOVDtuqf/NJ9+sravjaR+bQZB3NW+YYFu0NA1veksxniuVzeRV0viEJDc2RF0fzICFv1MmPoejPVeFtvd8vB/uZcZMsLjrzHXffUbX964rQ3x3GJS3C2cbLnpxeBaK9+bNaV+97W3Bzajt/Yotz2RT6k5x3t/O40f5Ec3t59f+qglgxznJ4dy+31ixKY+8/p5F3q/nV03PbnevRrfqPs73/PhSx/cy6+/uQYpID3CSJ858zefKwZuci1pmgGxJYXG6gnlMU+/eFifBfm3a+HXLQ/PLYtG/ppI8J3j2fkJoc9zZ6F7/gz30gcw202vAhLzf+iJn4fPX3+9e7baWXhJL3jR3CX3bO+QYVquBya0ZnJ8gWQ+asB7dTGQLccrmoxUo75YMOar+VpuHnY+ILY5R3LYhrNamWsj7WxrYYgwwH1Nz2N8rwAACAASURBVMb125g4X/3Eem7LQRwcWDOy/56LmP7cq2bDw3iOonUaK1f7WcxtT8MXQ3yTgmkF/196yFtquC/OqM7xYgfTHBYD8dXFvhyv6tiiq4+3KAgXYdlw3OBpr04bbuwPdSfapH+1xQO1OY1eLEYN8ZmMrD0+0607BFex8PK9x1GtUNzoGtQ7xodlKdkX9RO7KHPGNb6U+8xfzDt7dZSv2t8++ylOOHTY2bcetdAzxtV2WHh3DDhuz1poVk2X1U2SAPyWwPRgu7Ha1xdra/IiBsiq0x1P9BfYx8j6BbFpIkDVQDw2SZq/0YFaC+lqOVopsNjPTDwns6KT1fvlu9jjeDFvrWSAVOTpenhi7xF692VsjLFM1zs0/1nofIJV/XBiWp3E9bi82qqjax8X1FOtWKuls/Xj5XyVY6PnSUCpGRwvtl09uetie9ztqwY3xc//Xcl1hqdHH54nn5P3eFn/aavGZmvt3/lp1dRePTXjkncCsjhbO07pPTboBMqP+dgzLpQeucyuv4N+AY+1mUrInFyQ3wM3BMdRDSmuJ6kMbio8GQaU85FaYbhPlWLVxeZt3rnFEa2O8+OjibuBWCE6dyIwz5cFjMhVeXSpFqNFFvVwnA7c98APmwo/eG7gaz50q3IpV+Oq/Z6M8tEj6jju9Yw1o5jO1fkSx/iyO88FMloY24+vaXrs8OnPnmtq7sxksjjDoVOX8eqLEr4zJ+qXf+VJbb58EnoXDBd53MSXhj8YtYsKMTat/Ke2oYcnN9zNJY1kq6n2+HnVK1x0D59dvFgItTeyPudXWuaWmL19pUEPqvl1ZfPgnGHNMI/pjW9+HNF0uGmCmlOGYZ+z3xHXfgmUIAogxoyLq8afJleHK/picMRujsR/rKXjGOpHVxNM66MTP4sEeywS2T3UcJskm1bCytj4NsCAZXA77ay6xmkCAWUsOFvzwr4MjUdFRzxwJ+mjh2W+lrPRGh8b/nJcf46NnTwtQt5Hg7YAslflp8YEna1Eh+jiizO8mqmgKqaB2q4vxCCZ+9uLH5ZE1Qg9oMOUsBzMM4xBWzD2I/bSFYxNeyigYoDlwg7Td5AGEBeD5PQdW/M3Rm84Xhw5tx6Tbw2rEUufGEVlLuhOWO4jOlVb7lN2Ubk/9IbM53fV0cTFajSh23MVfRbJOhewXohH9y95AS8fwf6FP9AWPx8559Hv77lYdUBsE1q5fXF97qul9qYwFfkz7LH3pEjiD7Hlf62TJ7X57rig4IoW398ZT/67gO/ZTe9TQwbHb3tqtj76E81cZDNOvbVqcNNjKF/koWMvIDC3BmRDr/xsmqo5WLC+H4/pM0fVbj0GHwe7aN/vvmdO7QxCmcVSnT1JcJlPKQEdm3Y3Gs4KSUZNnIfRcLb2qThqs09Zqket9BTN4+Lc3Dw45vk27oOJ48E1Vbb5Bn6pTxP8UlRXAGqKxu99HhmNQzsY/VIcT3aez+BevcZdDMCnvnHEx1hN+OXXWl1s1RSb3Go8APFZO9y1HlqxHpYF3Nk+Ma2J6HI0z7p9tmm6uMd7eX0OByZf3i+EDd7mh7tDtqv7zRefPIlAIvN8f3tINDnau+6/PSIe7qdHTU6YGthrgqPGWmp84qZ3x2LRozPWhTOYyo/e1N/aUTI9ma53WC//8sQkcnVVXLjFXT/FHC7znR/EMlYzMwS0D1enfjZow9NhDGnyRZZx7HnycOgg1n2MMlwN5qvlr/DcDn7oDMWXxxv/8ar35upoEuGUZIqziSXbnzQIi9M+GrBAwqtlNTy1ywHuMHTieLMzdfOPq13aufFpixwIfuND8IitrsW9fWhucvR5MGVFLckz9MpxR+fLx50nWHAIyTD3aWCtfZgC2Ia3eLelifV6BCCk43xu119NYCy+O3XEDx96Sg/xzY9PfR8354Bn+MPtKrbESkYvlqr6vH19eAEAZWgG/5nrOOfCurx6E3/pJSimxxEc+WZbT7Cv/tU0nY8PSIy/fYtp4zloiD6ZVyjkJWs532TYGdoetRU2+xtbLFVV+Isz750s5g+gKOmzWTO3r5YWu4YdNjy9Q7l8Zx6fWhP+XjQWd9XFMSTT9aMkYoSjEhy5Uadge7ee0MZyEguoeKDrV7Wsv4G8AcB+DHmPkyddZGVoH5gc5qm7WrAJ9Qme02yKK37JiktNPMG6J6BeYH8BeXbKHz9i0MMrLTvm6Qsas4G/+0dpMNjn7zvfMFk2k89Qy6cf8DKKJ0nXbHc0yNccJBl4gfQ/5ofoEt5uKsvH9pPrzZpZv4oA9BBo6mq19/zAQZS5BRwqO57sw/GtocetdVkHBNZDwOrJnu+Yxm3PYzT+7iHGC8UzSA8Pe6bdGbf+vBrqLAY2xgU+83J9rWWthe1qV6sMrRk+dd+xay+a4dXQKuD0PDOGFRxTU74sn1zLWc3d4n97qDLX8u5YskdP9tPmPqEX8ZlA+NfjRzbyrwbqiuX0Mmd0X2u99Oe9bwpkBU5bDGDKR47SjJk9/uXGzYebt86yA8eRzzfT9OgGRS/yooH2gOoXLRd3F488vJx7CKM88ZviI64MBme9P4zGuv1KBfaeq9La9uIBlNh8EQNd8OVG5IuFc3JZ6EesU3fEcXH+a+6r/p3fk2YQ80su3F/NzaETIxILze6Z6Gbjx8WD4WLZUulw4vi3bb/nf6x7/NIvPvaej6rZCnuYFwpy/Z5132nm/4oT126QlGt2PinUOS+G8qBgTyYjnPTLZWIZ57Ku6uUcoKa3RvspNh7zEvkdPUd6fGgBGtrf2X7kOe0wgDTfPWaggXfceZHl7/x7uWD9dYfsrSybVR1TCSDaXH81wEV+e8CxvmxdE9SBB9vbu81Dmu+96AWOUWz2GtY1HfrHYzAE9+CsRHR8ctFt9RB5CcS5DlOwzxobRcshICGsm4k95xQrNYDdGI99EEJmQjKuRzWfRWUPBqbWdXrGJ8KQp9dv/citPvI8dY4L3adRHdGm/oJxSgxGk3GY/rwyWrN8Cdvzod7GWkuk3rj49fGjoT0pfueuccFWR2Mvo0pK2qTGr46le/brHfytApd5Php6fA9Lhnx/+2Qs2jPWG0FAkQH79QzM+Ls3qh0cJvtXz84JGMkxze8xgAG740et1zccp6+1lGX5q7zhbkPVTMru7e1xo+JyOet8HKye26dGdNZb5RBNVyzk+tG7+p50TNaXywt+/cdNuDwu2Kgi2+WuRkA3U9HDcUZVsjH8zn2WT/5yvxxNbJxhy5dFRHlfcU5p5XF2nJ3vOKiOV2tjnu1a92pYsXNsTQNmc1bu1cxq/vZFA4mst0c1HNejv/T4ou3F5Vz/dny3h/Bnz5p9eHUoL/nChXTrTY6H/+S5q8SnJ1Zq/BvHMWvOOPBls9veQbHIoY6mNmapDPssrKfiPJZzIVhO9tc/8/nc6c6Bi0Nr3kNA3cI7abKCK3z+n/sV1URvY1tUhUSFQQj24N76y7v4Cf7iCJbBYtB3PHOkmFpjuDpsIv4b8M42NdelI2/o4zuiaf7yODdn61tu94/G+HjHmEZnnCyVC8GYZFXOIsMnNVbeNf6Rx0KctWP0G2fw7Jidfe+sPLnBHsgL6cTwhGkx83UNtrdydfIXfpOXPvAkkz72QRcxvIuTNRfq+QLz1GY+BZun3PcOUFLztBLv4tj/GObEQg/rGcIH6SRqzPzNX2SCAx43BGijTveyZiPhbNkrl1gcJ2DJS3zb+oVreWcspc2WXHw/+fEcdUFdWMfhpMumyzI9t4nT4tpGXwfohbUlTvsbvwe78h4fi4vXz/pqnqIvD1jPke2Htzw3V7SqW+IH63Eg343v+XZKu4vfcysinmM3+quvHojo7+0faiYfe91y79i7CGz9EiL3Q6J+7AwZ7U3n7RNZNpLveZe7+XtU4n9A1z/4Pn0YV8/JgbuH6YFOWlyb/oyplp81NZ589juxvc11TZYvFwzYxF5idp7DYF1klX1raLT8BGc4p5cX3wySOB03r0Nh+MlD7uNISGvhPkdVrvHLkWjv45IH7y959q6arP23buwx8IpXgriP8p1c/kJb1v/m34Llo+1E/YvPmmcODyG7+M/0ycW8I7EAHY3g3XcvzhOt5rvPx/b777/Hx7vIf3/+OByt4f7yl/yBOF9ICC4TdY2Z/Xq4Pe8//5uPxkPAID21/OkHb8+/9qbQHpNpb2hj9cdQ2kU3B9z27VKC3XhkBIOm9Q1uhmseRqLGj82mXo7Dr7mB+6JF/mAceuBp1kBvbpTzesBxke+K8+FwrfNy3Pvz5OfnIc+U4wyW+PUPDOtnRIj3PRrqNQaBEwoP9V6Qe5ONpQvszMBuMNvFubYY0CLmOIdWI7EaTvtkGFwFSCsXwN4GnGHnYZsYPKtBMLqEZ8PkRjCjQ+eGtjm4nXH84iwFjq1jyfcDzYJ39PQCzpiO7l+sQbsCT+6DWxGqduzhwIsNjvW3KsJ3saxnWwz7FT5N4xgW3hVBC8rDdiNz7NdPdDbmbAf76gr4KOEhc/WPsVnCZMJjI4bxqWc8tbNt/euldjeNvc6vIvcKMRJgEU/Nt26PTtU1gTpnb2RremvJGhP4fE+TSq5+4hiLYS9Y63d25usxdcOLzvW96oIbhhAxR4YLQebAVn3MmvY9Bur4aBYAb4Yc1PRwoaG5BOA5bDH1YZvmn/U2auwVU219If7jN++bGQ9x5SsOA7Deb11Ndye2fug/OJUYkF01hI14/dnyDSg/xutoJzWyToCWzJ8cD58o2Z7Wnw8sQ8rMWTnXOk8xW7XZzVPbndXf3KdnWqR7+APMsaAmM341BNheviqoqzi0dY53ql5fbDjkXiVDqcDedBbY5f3GL0P7eciHYpyg+iG/7AzXgNmCnyeeS9V9kQ3ejXENWkHY71xZkDkoHFEM58s7cdmPX9CDy+TiQJCHsQPf1a0fZ3Iwz2b6SNNUJpKn8J8n3viG3vrhSTjccK0HHNL7fvQRp59J9IPfeGR+uILe99V2qGD6Xslb+/ciW274keCeedfzQfxnH2tEu1Pd9YracMXWj7S6YHkPmO+7O2JE3uYkc3x5h4l3rninhz4cS+ZwJxKN2fuuCjYB1f40IuaDZ1J9McUWqzHvscMuR3Cefw8noVmE/3s8xDfp5cZCUJZtgPimWe+pY5WchFsvnQzZjGPkJ8H4nv+mMscXW9/VlVTkw2be61nrqY6Ha7JIFDQHEdN0NRuuswLJV/2rDzf+Dnwb0xXBRwpBEeNxlfg3LrNLNx7207/jgq1ZP3pOxrhemp4HlrmmQuB4jw8z9Kn7SKit03F0TyhPKucr17B6w3bry+l6vWxA4+N/87RVupGDpgzqfh48br3jJSBM5cdZSydYjyNmZnNrzaYvGsR3FzREU1mPK+gwfI4xfgeamGRTztRLrXy7xxrM2Zwb2I0f2XbaaLaPPmIYt5cjy8lg/WrqnLW2kHTftTHZUCdx/cl90i/5o2Tw91vuXJ6nz8FybO9ddH6vi383Zs4oPGW5cLeD5sLW1eVG+kcvXi+yE/N73g7nj5T3X4+FO333Ij32X3Jhurr4uP2/YvtXdJCfd/JbYzsJv/eF5mLVUTu/Z85F+ozwRgXHGKVZcGFclb1CC7tg9FgrfggMrC9dEYOO9rFrPz2lp5sxw29kw9V/EQHGOHsmcPoCxt/zawU52fNaSMIPIO31Rk2EVsObEbzfRwv/5SfpcqkdHL4YwyfX1g0zwPMAPz3IkIZ4Z+WoPZ7YRckfxOkUq7scCKnv8Md77OXAZjyY4BPK2uM//PGTH07YzbU0WT0Zzob+pxHMri6s1nbH/omMUTuADOPlWhIt8nQWkJxdoefREL1Yyflgj9Ma661lupZmLFnbl6BUI1fZzAM+yyeMOGKGd9/N+hvCO80uyr4y79pY8mDP6JNoSEn0Hss3cXEt58NhcDYxtV4oytHYcQKc7+bdPRrKEaP1S5l0lxdzvrpie3Ma4YpstTPDOuznaD2YcXnc0Mt3blflKmd7M/1vHmM/1wblOqXWPu2PiDs/hom9dKeRrOQOE/ZOO3nqS73qe5xyBiQXWlvLWwdEaAOwuxzpH2z0xKB+71PwCq/NRfPtPJFuIKAcqy/f2YQA5jtJXtX1aEAf9eX75xslT7Tc1R5QhjrAh9DcEDmvrfrocysvkxABjYEoP/YTXhbHB3FGjxS+5r2EcghQQ7J431JUta3jjRsbCFMed+0yHd2Lf9Rfb5Ew29PrC53Ox4+9zSHolc/CdfX5fABscpB52jE9nDuuGG9UZakI7Jra2vHVNQ7Cxu9xDMBjHqvYaT0m02grDl35qzXH8uwS7A0whiNQCA2T4TacXA7kxCNPxTbf+e/kXxPeKGaJTNz3ZGtxcT38zXLoUCcHQYxH063vxqAY35io5unryd7QBFvfk5t1tPKlLT2Yz8NofUY1f9Y/Xh0JLYeJ70ze2Ls4tVDeMcEJVwZQuZkwz97857c3OAjxBgXGtyZAewORI7xo5QdSnhQxZdEnZ7NpLA7vYemnsQRrZx8lsT9/OCTr3tlMPPkC40kXIwuP/p07f/iOTy7OfSKsrPbLY0en+nFH9mbLxn5TKwVvLF3W3rCMD1jN7AKA4IbLfQoATu1R9rlDaq0NaC74sm7TdIxXTVNU8lvBbJAawGkBw2jizrOVj/3hil7anqet6RuY+eprKvmc3p0jBrjMethqroT1sh3/ymqe+V/POnI61pMsl+fhV97h1EE9V78iASQuHOt/vRgtpZvDzIKLfhG3QdwTS71dPBjy9pjhWyygcowK3OrYMSHHa2+MUQrByzgtD3djsI+vuFhybBSLyEs8KvLIFbu241tP30zLB8XN40TzziGwsLEtWw1ygcvyCZ2WGDkW3JYVQHiGvcBHFIEZu1iMk29AxTEdSEeyt5hZTVxTyY4SWkdr+lqpYHVuDm9/vnHjVXPub3rhnQvxaOEimLEe9P3x8ppzDaGWu3iewmqS3XiLAU+NHx1SEDSb/vzN8t9y6f9/dfg76LyLjiYYuZj/1x+/5uK877pXC0qfdjsTizY46XJTP/XE4nHJywvd6wdbmU7is/7HGFZFx8A+P0SQiy0meNn6+JILaoz827ND8DKHeC0NFE88Wnkxlr9LkOrKRbw/1ZKVa8+92NuX6iCXhZofcnLNpoRyVo5wrJXHEYYbw/EFzfeA7aWMMYHpl7UTBjRfWH/u4/gMj1nW4kzYWIWQ/5iYuZTz8FiemOU5YASI/2ibjip7ceRm6Pfk2Oq0sDw+q2RO3uztw6PhcoKXzUlLOcyrKT55ilXDeOuCvHlcn8pgeE7VWprf/nvggrk87cuLM8t0wpHk9f6cY9NCbh4PWcut+Z3H3FpeE5zkxV61Im4tazaxffmO9qk18VdpTMmO5sdWPkKahcnXVo8p0JLRrVldL245iF7NnWNoHQbHuJjapXHz7WANY0VW6pBneLJQ2/nO/HCYvHmfc+qJX08ALb58rJe1tWbbJLYGCkf2ahKPZXoAhGH+TMQ9z41PM6j49hDXXhFbTdMQQ+tmXxemSrr9JTOy2YuYhqM86mqzmBFl3/w12Nf0W1tJrGHwjwya8ImFKF5jQDPKbGUcQ5TnGxiDdRmy0K8502LnJ95Ruq26X77sd560BqSYmZTyX9qusV3s+LtfTVmdY/7Gd6tthVhnc0DbAeIyZvrn40e9r55o9/myHbIny0kN1MX4eS6/0S9TM5bli29++4Iq+NBk/bFmrdr7ZBNOOZfX7LeJbZmJ+41C2siQ/CAMpS72JMmOpPKwLVHX9cv8Hx4k1wSwjTwxtxvbblCYvycPgpvnAtCSr3E98UOdY40ErfgnHMZwZlfeby2xxdimtpHSpQFHa+z8NGZaCRzfY4uFbM+DEdEx+DHAI6yaOuizASwzcc3sJu4zZ7+PFnIRznq/w/m9QOfE5JK+cc0Lcwy3u1jXUU3xybtjxmsKfcEGfKvD72r6s1gcyYrkxOdJG0/e8Nee56k3ysHinRWDDep2E7afw95GbzXWp7KDGnfa3siqog9zyaPaD+q0tj9VsAB7GOgbf3345B2/6lN07xhS1+VtVetfmK4OFYiJ7UlAD6sXmVXTOvz93lj0r7mno9W0unUXSn4YZcgEfeOf/XKby/n69ZKTjuH+ONSH/eLxmyf8n4RaqV6K5c/+KCX4ng/wOEgG18Mf7RCbJAjt+FtTg+ZcDaM6DPAnM1hGWEvTu4yj2O2BfJMwnT33DSVaABgHuhmQOhqF1dyxj+8A1rTbE8eHIcuntke3wXBcP8CC8wHJ0Gfjp1nCB6PxiV0NgKCaXBaPj5L4yLjDRcFGYMzFIi/MZRCjliy9f5Uw1pZhHFyg1YH/fNjfFyA5RgeSGA4jNJLDd9Bzh/L3XJR7kc6dC3nlhDd4TfFnzu+gN2kx/w6ePhkDq/zd20PyMj72GqoePPe1a5rvpCeH76wnEb+HvuPI/te8w88fjDNG2h57fO9PtKI/ovaR/dxre4H8rz/A4b+PyCd/H1fKsy1ybQHtApMvjksi3beGboGQrRtW7eFjwgWZmkKXL323ZokNzI89hMlNj/yiz5+/WcJrAO8TimKbgxrhzIYh/03OpAsZlxPMR07dNIHaP7pYlxZdP2OagZh833MYMI8MF11Sz6QIMYwZ/nqGKQX4186U28arp3H2Ce42ILPOOcZ3DVLbX/LAHULjmtF1rLXDTzp8lyvzHlccDcXn/YYvsn94Tg/+ZkpsBD065Y2NeEC3Bd0+ZE++2QNabZiKqZ5qLItwSG/S8ppH8zKRPwaiCodxTmz9sukh+eYQz4aA0nz6BElH9Qd4Pd55ZULy0w8X0Hx6YW+qixRg5teqgDjEwb95sWSv3qyf4wC/QJLVDlBra//z/f915MG2HsONZDMMM+s77QNUd/WTl+F53Gm2ZfA4P1pxFlz95TbEvjlLvqLYb1wKK62tFsLWa+3XCuYgXJ72p2cx+iZB7GJ2g5JgCoktgzrUB9slUKTJEwCOuB6L7jVkQ7JGgQM5NEwM9xpXSRHv+VFk9TRCpvCBmXfnTXseXGjqddK51KyDMv7V/RyTE6Vf3DQanIDlBJhhL1rXelxN4DtDi315+tb8hLdfn4hgei5VJ7Gg4J5meN+I5ga1a6uGmNS4B5EgIpvzO4/j+oF1vVwPvo+t+O2/qu6YE7va0LEcaM4X39/xvvEdbPr58AUnz1k6T2Ts/B3bpwFvI6A16kliEN0hqfvIuTUmBhg48LcZADJewM1rWBGHEvrl4IAtlGRyS0eDGNXw007y8QsW+WEiSocav7w03AenIoRxdRt4I7I/POuX8/RYOzrrkyVFsKyi1cAqF648ablRXviR3wP/9QPDbq23948EhaIX5PUNwx10s+BvHmPD049CwidpOUmM1mCrpR8BraDqQsMGGGqQo7csi+wLD7EfT34TUz7wPOHsBT+Rf+WEe8eGvOhVSyoBrxb2GcVhBdNaumqtuwGoE5GC2Mn03KhfLkjDWhLMJLG+nYeNrN380/fdV2lUoTlfd+HyxAaLQtNcXJuI8RIiFwT+IuULovofjtYKrpzpWb6a62zjTOzylhP6YhfbVI0zFw9ixhMcbGrhuDpwaY7dpsE/vmDyPe0nqP5gfcKZWPYe368OeAnXZgbT7dx9Yg+nvgqB0bgGuHxy7lyijnyfdjBZZLD9qbe5re3hf2usNzHX37JIdRsQGSRbA1Tzc/XwCEZB8DHay+uVNMeyfkkJd7/jbe/tR+zDqS/e3ebhUtnJs2ZSZr0YAFUCpw71+I46mvgiAN8NY4PKb1g/x+B9QJJl0CeKGL52xsEWKRmdccy+P7qCMHcgvVhNxrswj+Huv6ODc5W69kTMXsXwW64M+dXzXORi4qLxOTeawO1sy299Bhzo5tz38vc5GL/944/8/CMaeDGD36EnUb6DRevvuTj/7d/8q7X2jT3a9+IC/eqnFuqHw1lwSGXhRXv+Aj3Hk2tcxl6YJY/rZ38PXgm0jrBwkV61IcsLqNVS/h4N9CbV3W+NrzWghnMi9ZnjdIGHLjYV31xjekMbsPMrAAxeKKFlv3DBnsBj0ZdF85Mqw4oyZ6muP/kFYRN8Qrqyr9+ewPGMxTyG5jCRtuiyzDvfrBcHLD1jx8dqc0MvP5pmN0J5sVwh7ddpJ+brL9HTU3uUULtln5FBBsK6Z82MY9HHrNqnAazH2/ysMo4DZgaxHWS8uo6e3H67jjf7x7aoEPjYz/kTgHpRxTKY0aNjx2Y28QhQU/YUcTjVlEaW1bxYuB2JNY88sUhX79O784HUg05sGaZu2Kt35Mc17MNHXJmgeGtWiBLOzu5ync9zwNzkj/Fyra9E9D7s9WHrSMyFsUbDju9bvkyH727n3YKh+OaV53R8XAb/rHNeGfTD49MGGhkRz/OwepvmmlxlL2O1B0hZFoCIt0DDLtU0uvzwjQ3uzUndmrHBeJzXpOGO+lLWOtubp+ct+mYDqV4S3di5zXJa/lyTmrydtP3zyxxy/acRBPnQz+i+WyAa0of5zZm1GgVI+HBUffAJePQ5l/61dXkJ4Fh74M6X+sgaX5Ndr6exoSBItrwHxupYrehR1NmlxFSU29kO8njk1kkfrna8CX468/QzdrAQPzVkzpKNQgoQgi2DHGUP/3FVG96bjVf8rHfeHKycZgpp456wLKffPxK3ppHQRkHCeES6yOYoToe3xFA9xMzhuP3b6GvW4qB7Su28ktAKNozmLgof329DRlT7GNivMObEKI7dars97uYpROg9qMyChMCV4hOWXZwkttRxXvHL2/7VOBu5ILmSbg8D5v+vvd5s4AJ3H2M/DTwp88IcX+Y8KPok/Pj2rrrBxjNDkbvuO7XIaRugTzIBnL40okogeGfWyKtBwYHEs3eIeFJqzsT6Ec88KeOd37/fH2b6t0+e86TxcDY7EQwz0Hzmt3eBHp884rvzLbaeG1XQWN1AriTORoZZRAAAIABJREFUq8yzLqtsxnnMwOGLMzuHzw8yszKMd2e6nggy5r3d2I9kmOYdX7t33OpIMLavf3N5T4WlX47mc6FYJO28bkxr0172hx9/e9R6mP988IxyqPmaQIKuKYuNm2/V/af8XsAfxnA2jAvak7feJ5Gzx8Wk5MrPeAkz/YIxZO49DA5XxDiVSyj2FFGmLA4riuLIkRhrCgpG48SVH9JKzh5++iXB+F4d7SXOCjk5W2o/9MNRympZ5EdxcD03npywXB3PsSAQpEKvb1cboltfZTxzxa1+CZ4+6AoXufm+cgSxdKDB2x/u9g7uzdVIeG7bfOWeyb18JfjBXdWjVsGTpsdpthPEceAn70ajw4+0Z+2744nMNBvud97BfTf3Od4b+b+5ie275+vpi86MGldwplXAtkZjdiy4wOZqM+5ff80Fel4A+Mdv/4g0XozsfTZ6+cvu/Ou1976x94no9iI9GO8vLYA6evyni/vjnoeUx0fffvN30sn7fBIgC7V6DmTu/SsM7xztv/TGFz8d+Rw7Vuow4tWTsr/HidXTo/ARw1A/fVFEdtQfe2PRQL6+rMDxgMMXdKLhKN5YCI/HPf1gco8ZrY0L/uRu+uZ/gogHj65SjQ7q9feUY8qo0touVnPtQo4/ig/9pK/bYM63YzM5t4GMq8F+qeuyozMIoALxgb9t1Wc53GM3ShjHFRZHJjJe7hphfByPPur48hsHVyY9rvCefrCXZ3HzLZ/378JWc3guLTrEsQ8PmRXfias9PiyPQkp+eBaJpZeIjFUucsIQO88hF0/u9ds4MAKZZDAnPyH5al11MG+Ol6M9AS/xU9tqsVvUxn0kmg736Cn141uOk6AUIE6IfUbPt+ZvNjWou3CtT0wr2fEZjXIgP4rWffF3vqwHQp4+B/OZl+940LC8mmZ/9TPzbicTeUgcWPXg3HGM8RmbnyLuPjI83lfDM4cvw4hxmUBz7fqvj+dbf4xOXHuqyFfcaku8+PGD/45KUAQelkXMMVs9Tddz2edil+drR8+hm5t8Id1tyjyLu3zNVl6DiXkknLJnxyR8JnX2YA9Sv9sqcXv49d++PDkk7O0wuOfciHn9fjoR7R5dk5WA9YOLqdqcyFXUYdHB4LrIE4zYxrx5m8NONqw5nb/6nrzjfHpPgtMJ9+nzXMmcMdvbR83V4vQS13xRs7XTWx3E2N8wXknaScSwQR6EC9s8+x6Uv2KKPPydNOX6TwUU99fCsNtKiyaeaG3P43HXug7lwaj0wDPhwLN3hG96Tp4eNncQDngNBR/LhY/GO11481WFb9QyLWeupx19gmqaR8O0TBLA2d6TESPfJeKBy5wJ8okfF+Q8MQRxTxDh6M/4LBD61uPs5nF9sdZozcSkPk54ngDnyS6a/FojHr71+JqFNooKrg/UvEPTpL7LwyKc6IWzNVdzEniD5vkXIfjEpD6f7MdoljxRtZjcGJsK3PCfWC4QLgd7B9LghvP2kOo3X2HUWlTxWB8OPdiPEwJyza4YFqrNpFhzmr9xy7A48k0HkQxZXTQGTpdoLeT6fIuXLIbDjked4D55IBtRXVknLnZzf/g8HsIXoBLrRHePZeJ4YnI6h4Sa9K7tDwtwXxum1/bma3C52JIXddUJD5USK0bIEQNl4GM+XeSRp1zGiz0uYprBTC5pytnqZQmvgVnUrwhsipk5i8eUOd9gjrNQ4t+w8o31aoMuMfa6NFikAYH6I7cfyoBc6vhNFHwmPtc5uL0+PkztfXPWZ2A8GSVh8kztn0WdDZJ7MsU7tnyjAXPHYo83u96XzV8NxacqX5xsalTtHWcubp3zEXeOBdqOEiawaGPmC4SZe0EfU++Dyrn71ud/u8dvXENfHtbydet9JCb+SFx8v+V+7bff//G3f+RddH6Qwrvr/D2OP/6V38/mHWvwGXzUnd9Zd8/8c6GOVoDo7zBxb1tYubjN77L/ms+Jc3tTP+9Gc27wlT2RfcEWhtqww4TP+a3B0bsda/Oacpz06bSMg37DM3tXR27G6OLRL9x5mPpX6u8nqNKPvJBBjb9y3P7osQvVc/xkhv9yQJ201Xi4aSXOAeB6EaBqtCtbpQc8uE/oMj/98rHEja0J2xNsGWMRYyeBgp3z0y9Nb08PHo7iPRLE3VAGa/JeJnvnfOcxnh1DVHS1ardv3LiyZ5qv5xjn8aos9RTwilFB6a2NaXvi5LIWj6/4cEb77v/bl3j4zs/bpkboJ5bjkLEc6ydWbWy98z5D4SUlkLruMeeW6nGul/AJWL+2DqBJEvMQO5v+6ao7qIPtOEJwFHIw5zlMSbJnXNAXh5/IJ28a1MeSWo03eGSHD9fLE9sT15SEfBU5T8Bzfnuibf0iGw3z5QtO2eY7ncyx55h5v8P6zqUyta/m0j4tnzjFr9fV33OgGOpeT4Q+PchEQRpYvMsAe4oc759w1kTd2tknXPLiXa4v0Gs+HzV+Y3HWJd877cz+XMyOJ5TSY2/iS3IrdZ2k+Omf43ZPbzW2juXFZCnE5Qus6xrjDbLftYtB+kfLF/ujVhMaR77CLi7xs+14sWasBy6oJd+9jeLMzxv4cAJ7ZKhx9cjSEEAZXwqPaTR7jEAF0+PVuFcLukk9jqwuIR2z55o6bxfhhRLewO9+CAZCtyfTet++YjlbCGa7dHV+7GWauahp6v9Bry84VXRPgiu2AndgELqk2x/5eIwFl0k2poT7x4g13xPfffgIOdzTTPPF/r0jfloUjnyZa3GnG7I1Ds7yXR11mo2s5LVOcch+I37Wiw+N9ffeGG5skthGphuU/nC7eNdg6jP6wUGiKogPs3ckfHecJz9gbs8TTqg3lm/KfnABUtNNWF6sVeVE9MI8FRFnL+JoTzhpq5WCybOTCTYHuiRkjyXAHDufePKaAs8/w+GTZJ5UyQGsv4Pad5IaxgOAebrMlknzd0chj6n+bbUrEgg0Avd43+Vf/Se6+Gx7VoIm1Z0/hsEKb9nlr0n7F9ucQVwc2DLDZwnuDdS3XFgI6r7Y5tMicaxAaHa+P4fHhQ+oBMZpZGHiWHdwXDc763A7PnFbU4Ael4eveOohwUVLVkq2lxsIADjD47FnLSQTRFw+zWB4QoB94zh+2AJW254YEJzxYmqw5whgKWX7X3C2wprLLbnuyTxr+RJvrhBIA99qKal0LfRqtK7y9rZB+qwxJdy0jXpy6NdTL1vym1s+ZrUZmoXc4ayk5nseHIfFSWTdSL9w7PCxKUcx2KnDm3H1NXPndQeTyc2LDQk88fAMClrvL+PshZ0erPKgfT8GQQeRA186cvcdv+Sdau5P+KEn00wS+rY+EEpe70bA48vx/DUB4/YN96VJYnXOf3b45YkejwG68mYwHM2f+7NcgP/j938+F+i//vpb/x96MPzVdrVEw2+5MPcnfi/MuTjPD8fJ+8jLydFtrvbnCIIlb/XrT28bkj3nalbI6xNEsH2sOFDXkAUE2k8AXL30ydEm6OfTAOsVvvWBppN/NjzkTbXa2KCHvvAiBtg/fvndGn/N8fvD40c8x/V44MvP8+sUmRNnns/cj/qbJXiKIHceA8G51NfNzoXLUOPTM9rQY764PbHesa0fXQm1seRszLP+5ENA+1jG8QPBUh3sN+N4HV9sPSrxpxb5jcncJTjipjbTjFpqe7xLdntydLw4I48XSlMeqiketif/3OyP+tWfHNoulysoVI3nIvTfccWdwblizcEYku3TC+IMVWzQ60Kwy4l4RnCLX77VPnv7fXhiMsVGinc0vw+x8Zj+mLcDO27josHzB+ojW9yXfZlbryQHvx5cf94YetKaEYvd1bf2zOU190XK83YLjdNbjspsSAXvvIMfjLjUZc9aDCTNj471vdmfdZ8jkDEjcS8s2e5+Sp+iq4spfGokIHHTCcHOEWwM8Kun3Wmi575PDCQyy3UyFTQc9cDWWsrdLQnyE191dI/FgujD6TXWvlTT127vnsTN1eVqahpKbh3hv7zL9WgNqOcknnYCVVtRKcvLch7dz3w5jG7oT3U2tjFswf+l/tib4wO+XixSLRSlnvTqcnVd1Pom1xN/5xXH5XlQ+qnjFWykKrG112D/A//Vca7uPPaZ3l49eLLG5Pp4G3Bb07L5Oaqm/dq5qRoEmUOyzPM9kXG1D3DdMU0v8g56GkEpxORxdAf6aVoImTfRiTnWJ1YO88Hu4JgwnhMzBk2hYK+EzdkTgIPH9pvGeHnrShDfGTt4N9fWTf1CtnGPfQ2o7tMQO4PUbNWVmfWiA102FX9YWLLPeE9al1rhIeTnuxfHFx9Uct+Bal/nb137nXGetPQJV/m5TwPPDxe34m6ObXpAjzezBiNq81punShqSryTzO9IWbv1U7Q/QIqHAuZht642tNx9sJhozrPgXpDnKbLP3/qHjiDhdIKHvn73lwBq87ZGlz83f6pNTQhAIPyHZu8dRPDlAoQxEdTPuL1Ylp/o587lSKcV9c1iIU/C6TDXcqZYs6J5Ocn7jHE9BulfvT1H3nVwUHFyZN/jhYQeA3NAmfGtCdx06TCi8ZXVPOvXtMoPwHhS9riVfBmwfzKyuLp/5AyPLoIJZZytx6Trkg0A5GoDXwL3PT7zHV7qztWUjbi7bXEYGJaU/R0dLJgd9ipr8jKeHrgq0vPnk2slwS9nYo1mo404tN55D1B+9ibpPlPjGlYNQhur/uOOudwr6tbsyLlR/azCLHmc81+NaMG03OzvGorAjChXczFP3+RJbPateMRGaGs/sxZEX8u4/dF7H9qeAziexPhxby7uvKj1il2dvagLNHC5S8sis1yk/pEXHlNEZlnnfuib8DS8Ib19uCb8608cy+c8hD8/v8X+j9//+Ns//+uff/uvf/7X3/75z3/+7f/97/8VRwQvevLxd95d53fVf/tHLtBzsb460Ibu9ucSZmdvSYGYlMv/K+Mctjfpg/vk5jHn33knXbmG93Eif54u2fOV+4hiE5MvButfcsXPmgvpLL1YPu9h3Ln50dczq4us/YYgudrlZMiLE/1ov4chMb6o8r/9o3k8xnk8Y1/t8lwftHGsw8mLMqz7IkZ6ACY+Ri/wuS11sEcXP9/HlxaIkXytX4zY3hYXG1P7JTxWYmQEbDATMbUfEzs9bG5heG+z9ZEFyh4vapm2vStZPxne0XmPHnN+PKYHqY5y49TPJsP5zdYp8+++OYCLrJScZKzl1FGva8nqNc9NDby5u9V1edUa3pN09VeZz3dyAr41ZJ74Pbat508qe9djJn028E9aThnlUFXzvVkfvBUSWAu5qfrb0wbH8yZuHrQ9epu7HQtXbmuUvlqwT4OY64u3N3MGi41xWqr7csT1cMsl+Qfb48t2mqgEEcQtdvd59pXkGZtvTxge5UAB6LDwDFfm+rAZxPIm9nJxd8zlhfPIXV9nVImBHNics75puN5zBGt7sJpEUS+4fE0HOHVjPb8+dEgTv8+fFnf65Gka6hcLPuNb79bm/eRfTPUQlJ/wdETBTa2J82UPsNoR14xvPVAkjuu0E/Oy4ftZs+mCP2hmHfZWZ32zu7fORcDJyFb84s/mkqj8IMgpnF8wdrvd4Nuaa5bL2WOy+HNeP1k1Jv6zeXs0146vqcwPV48RUdGQmN1+2euPfcdsGtXOgaGeGw8Gpo8e5+SBH3WkyX2pdTDP13vsgjMvpJlkPPHkqslY2Byx+Q56GxMTuBh3IziYxidIFfEcIRNian4bZYE6YAlAfFmeUFwZ6wXFwIPB+eIXG99zULAdTtZn3hxNmBaxlBadbeaZ4rgxrorUaNzDOeDPyPWNJwA0wRMiBSyPfgqijn6/c3LG6EUreXjyFEs7iC/e/HEdA+XMEx4wuXX2HfTM711z8vGzd6RhObLEIy4DDVdPDfTm+ozhYEyw+8QnttbEk6oDZFedwUCbA0JuFvxLNWvPvC8ygCyeF154Z/z9/cfYE5dU3uHwqU1zkRviZPkerWJ1iDMnsGfUV3sj1WQOkpSxk2p/QtH/jO8RgLNcqEEYDwYvGh+jNnVfHu2GH5pw0Uw+fTdeClnsASGQTdenBuD24sMFzjv3xE3dU2Fo3jskoqeDfcbVw3xr9+fD+ubDeMMy5ovNIDbrCTOjSaG767FLIIiOM+pnFsxH1w+fx2CWVAuNyzeaHmBrL5mToTkMAJ/h8bo+gxUDXx2u5c7GfrIgIRgZbi9H5l48kadeY8BnzOp9hZZ4j2S4YRZgHQH1Pi/W4FcJMc9xGQb/5Sv4dMTf24XM3WDjSYG+3DiTXB14D48PvsceV3vUOIuKbfcNzUHO5s3kGe0p1OejWAsuO/ddC5MHPcH6QqcsycmFmj+9UOOcVyM6d/8ElhSJX/9W+24jXpDSJ+KW1BxsEJVtduQiVsny6cn6LooPNw3E/vHHb3/75//+Mxfp/+VF+v/9f/83tt99p9x3zbkw/2d++Hi7F+f5qDefBkALidQEcYtAMxqeGoYzd0XVlwvt2LjfNZKYfHHx75NPVnwM/k9xxPbCHC5y9cL6r30hMszyIpMsHbtIdoU5GjYCVzu/g+/jUxz2K3X9kT72uFF77LvYPu71lU8Z4Pv19/tVgPRrNmoWno/Qv5LaS2qJ92M/LHXwuHUi2Vsv2mfMhCWjfmZn+fSgtyEwT+BQjZv5wz0sJvsYDMeh8wWQ+OYUxvSzVglx+Rr1X+IT8h0P8wWwtu7sN3+0cXu6fMthIzm2fUAxxkhMa372OYtMu9qMe7RXURFon/oweX9U/7ae20AYx9EM7Zd9w6WfTQe563uC41jW6pU71il4eKG4eKaOJdjtEmP0rOe6L1V70U7SC3xvjmo4KUf98pg3TqmmoQsSXr4Sfvvl/O4rToY1XAJ3bjg+SHiOR9CTNFvcq2uB1pBYB3VfRcWd+Yie/DEvBIQcxAEIx9Y9v2BMt+7BrraLGQkxT27IYX3kGw/ptOsmNjHFRfc9AIPp8ccfb3az/YiHf/dnYALO7k3KPKO6Onc9XBbiT4epbt48F+vtbWD2RuGEzv1ZWl8LTT0nPuv1kX0CkjcRTO+8gKaDPqIrfkizcJcp+3eR1UuPJ8tgT3/XFxMOoB3Xo+DWF3PFaXz2T6+fZKf3GESeRs8L8upD02Gdzk7Ejdjfc7xROpmezvWm+3EIKMmRTfd69OS2koLenhB6XLpOZ6zrWdWcpux+6FxdcuDMBfoatuL2hKAU3T6K1/CAX38XCkAIniRisH0YLhZ7xeI/nMAVEytCl4sAhrRXvIaX/cIv19mXL0s0Ye1o1jb+5ojMz179YCnehjUKG0MfnJmA2ZM+bvfNUf2Cs/GJp1Hx54ZuxgCpkR8Gf9129WLqkxYwfYLh/rDs9iSq79JzYV4euJaD+lp1hCGalRyxo3UhLKIq70sMdvjs9N07FvFOV9/BkDIFFueTr+DVInnrW84ISzzY/OR3D/cRTfY8L1tfdm40F2C+0UhsaxCrRasz8sgtNJurbzHjlRAn4IzGrTdalu2BqgG+5GDXFBdzPF64o2H+Y3lJGmlrThxYaYnJYr5pXd2iAD7Zs3iCT9NHm1Dg4G8B/BnmquOnXcc3S9v0EoZvi+TNdP0t93FeMW8dhKU3z5O+9C4Be3BxfgU5R1Qmt5N6XG9+ONrvv8Qv8tOT6iNpj9s9D3j68/o787xVAEIuJrzkIshj04Ucatn6QREKSQa3/ZuyBM/3c4yvZ0jfOSnN+v1oaIz5PnwyXn5ry6bHhmzVoZvjMK4/7dUEFkz26mCvEPK6uAmLDDlqWq0fyULsZe5fukdFqk7cd6jpuR+L7/zTKpaQu6jjgm2/CvOTC9A1ooqbJnz2mubk+/tEDcBqRRvRvhtPIdxpbbgOf/ZgGLxIymfO/55/gQYH747/nnfO/ysX6P/z3//zNy7Q/1/eLfadc+z/3XfWeQfd30HnYpM7wOjrCx3orwruG8nlGv3XEy2xby0gRh4XkGstp9Fy/f302sHit4Lse0HP/2jPR9Dj+1f+N7wX7JIG654t3WvdJ8P807A9eo1B73Gwi/kem1hFZ/LkN/Otezg5bsGxXR5eZODXBXjc8VMH/D95X+DIZ/3v4n3/eo6kUFCjMxYQuc4uS7aqw4bfgcDOamq1hh+igCdA6x4Tvc2F4CjcF1nLpRfRzsQOII7FMGHenI2u9N4eqcNja1ht4yrV4VTWjSUS92b51Nkcry/xJMxYnh1FMSHDP/wX+wgnGA5qAS8ZMR3jA1Bb9+D2+GAcHBgvJ/saPjwjDdA8hHgni+PLvkhRwSan2kxwSHir10wPN+ZbrK6YrD12eBg7Di4+G9zr06vxAPKRM4oC1H97WFmr8BZv7+KAdxfk4aGLXqQnAHhreRbhkUnPNh7L/6Afruf+EfDpfHuGsVmYOR6erNYnaiHtjfVhterKRm2LpxYeB2L/kSH+rTd7nq8To598TTist8vYdvuclmn4ZvlZXz1o43ePkbd+NUOZls/9akiMeqwN3J+LOVt29prlxZrH9eX/D9pfeKvs0a8+fPbzQLtN1c62vM/saRQ9amdX39MjMPR12MPBAXbm9YC1tqsJ3J+AZ2o0WDQ/xzVr+7BjmcXO9ToKeOqUDYnXd4Lz7frUtabvVkAjEfARyBI11oxLP8bGo6GYupYXaCtiFoSgBre++WvDP/yzz6S1lyJ/xZ3xhntQdjAWdXLw/XUcSNeEYzvWxFjXiVGSPJ/2Bl4FH/5negeO+OmKHtzc6L5x2oZhASZrdYN9LhDwHIfiaMrduC+OBKN6OMxaOwy3PKZ3rUuecOYLbkuOg7UfRbwnowfzSRFeB0/mO/NobeXF93H1QpgnVNU++HdPdkSSk++8/9TcR/7UxRro9eLLsTm9A88PYzcY996hps6Iwd0XDk7XcVMDfp6Eov2X/JEj/qqvLzbwkc3j7ZNMnhRfnux7bKgEc+zXTDiNi2PxQDzeRSe6X3LAeeG9OARshCh8W9tzfeOrItjMG6jzHVjW0dY8OstFyvAI6wlrmiAEla1+W/CprxmLqzYEvgN55NwdK56TLGhzo+TFn559NMtxNa2vzcI26ByrHWtJs1mvzRsu+sDoccq8xbp/NFz+A0LtBStm5q3vuKeP2ghgLdEL7DFoXpx8/XUkXjnny6LnRpCX943ruYRf26hLsApNYeijEaq3BwDXM/ssLka/u6/UZa620VHrzqMmSwwDOyQEQ3NPRGGpnS0+amT37j9h+qG7suQb/gJNIa8g0BnhpDe+OHeGxrl48t7qT7vTjVY4/8PwuOjqMQM3bFLfO8y9n+gncTKP3RAAGe3o9U/Deow8ugOw+V8ZuTBmke+dG+0nBdcOlaE+fkABR5P+3X/oDYBfSf9Njn/88w8vxP/P//k/f/vf3//3b//4336s/X/+5398Z/0fuVD/7Z+8g753guELLRfqz4hefm89udYHj0/8yODevCNVISUbPsrO8BzW6NL7XXh8McH6E+NjTGJy8c6c4YusvPCRtPDl8v3K7DGBd1q2J445P6akZb6oEc4Q1ddjBZZRaeheD1t/vdv24p1jwwvYf/zCX8hvf//F2wrWDFn6zv+iCQ6junzBI+mt9Uk44rOCNbzrxR+cJfF04VEXoz2Yh3ywAkbIcWjS0/rYjgtfOR9WTI+/mhsnp7TBJtf6v74R9Ukjh2Sn2bxqq9XexGj+1ZK9j0+BiHdTPXC/ucoB6luLQcbG3oTXo+HffGBX+6UJKGy0AgM/DNaMO567P50W3QTFLyyBP2oLwY8ab02C9vdN8eYP13FWDtgbsZv78s1O9s6zzTfu8ROppuxbM/vY2AAmkPrytZ4UiatWkIODcWRH6KNVzY3BgU4er4X/0FuGHutg/lOczNUkwfVDzuVk/zz2TEttwG0CmMxZdlvt5WmHrpo7Zw538Sft4qF8NT2cwwal/7Rad0Fmf3trRbZtbyo9PT2Vdf7MJ0lytLZUM3FJZA0rJPvHl/ydv05myKrs1vP0FWsdTZeFupPrqQ3b93zJMfZ2cRjjLzrAaiOf54Dklx1Qj//DDf64zcw8vJ6FN4cTFoSqzTnLWD8Y1uY8+9MB48uwXD0iVzqa5Cw/iycPjvX3yYv32M1ZDG55yB+/c42ZRcOOw6GsuzFT2jhxmrKxFunMCYLedITzapue+rIK5DknVj82AkMr/vp0hjpK7Pb5iDtBBLgPGWOJmOl7yK6JsQ63WNYmti6liFpELc1WLNs3t/Lj7slXD1sKpRGbe0dD0TlR+bJJh3GdrI8dfwLWSLLJEzvTaa8/nvC01Lcfr278hrtT061rDZ/05Kvlnv+YHxsxhbyYHs3g8XdXIiTGQArj5gTH/IY6MqdmvnH5FG7vAGHARWEZpwBTgCBTqwtq749s9NdmBPKJ15e12rBnsmOEhnwQ//QlExd5cvZJoLr8vUeSc+xMH0xW0buyzItNWLZXsHmC4gUHLugPASqjdVTXz3OGeO3kBCdzO2GO4y9fVagBVn0V48VR3I18s4shjEI2jnOmY71YNFy2TAwt4KKXIRjtH93hnTbAzdjtG4UUiGM5PDU7v9rViu8yds3ilE745Xjk3WQ9JEJo04325QVw40q5gqux/T2AmjOPLsa2as/q0XreVwOeoE+D8y5jv7ofbkyJvBxHFVQ5yGm+88/uuUe/LJYMVWe88yDNUc8TB6+6ip+dOHN9Y37kLPOXv31BZ7W+vsxCdtLcyw0gRtBq8A4JnYGDj3m3USAYer6xCMBHGvapyXeMuQU3/sTvUBHwjPeY0vvHnIlKmpcV2k505++FuBfjJjFjcO/9g5Tv5jgoqhl8HknarKfFzOvF5U4g3wF9e1KNhDsCkONPxwa9XNj+kgt1pPya/1H+a363/J95p/x/coH+ez7e/s/f/8t31lnz0ffnd89/a53+DjpJkjIK7gVOPp7O/Zvi52yN1BesUjJR6bdGHPj3wJP7d3luz5y7/L1Q7MdKIfQfxHO/nXuKQoPlAAAgAElEQVTvYKSRPK4fixo9ViHaCwtcTHPWs+Uj7f5V/FykU8ev/8rFNTScPzd2zLvEW170KSd7dHDMeVf/93//rgzrsl5Cem6Rw09mxfRLcniRAl2OKcxSvym00Tkhy0fSzDG2DqYguo4IeasvHrCC3z349UAqHj9xx1quw2rScfZJnC179RAK443MVTQf7nNhcpGJGh8trQHfh6lRP7jjj9g91pDXY3SYY3k4yMFYza7OhnZ47IXCmq4SrxdZqNPA03z9ag8Tg4bYGE//4LsYJnKCE4NFpxgjBbz9ladBb4+NLu1q7rkV3tCtRvkQc3U20zA65hJTzcdLjnzv/CWPPZS0ql9tAMP71LriEPM5voexj7EvnxkXK7+p/8RZLlQXss7Ry+T4PG9DizlAVtqjjSh1hod+yAXe+eVA58WC6DkGPnZvo+wvnjoIluHVtn5ZVvgYzIWxzuI9nxoH6ulNFswZ5o2OqsSynjI///jQbRIruzkoUv60yYeUepsnmF20euwvhH5UB5qYL45eZRxP+17fdONu6mB/SGhFcP/UTMCZsnvGHRej4reN52zeGqvtJWDNeJ4/zXDHocWMsMez2o2y7s62ne7KtKg7Vq0luOQoBzqov8esueo/jySrRe1/4jJbHHJb1vJf72nqaiq17RNqbnpF75tx51V1/wg9zdUOJzmbDeI3X5nwx3vcz/9BJ+AFXIKAqvGEZO0IsO/gNKkoXNgflhhMDmvmFsy+FD5w4ufOl9gNluQZbvbs1wxM5gQT6M/89bLV6bYJCm8tbejsbdiTsmYZtqnpHF//aZje50DFsMNg6XszIoT1RF3qnHYpP9eatIBhP7PgNwOxNWaVFfNtFnwem+iC4qlpUPYx7vh5XDDtQv6Ds9/kzL3l/qr7jgH7ajRjOe9khd8793D5bvrDSYwV35ParscJDM15quWxlg7Dp4rm1aiurw/kxhc3G/v3qLAKD71g6rx6mGMzSzZX4VmCwR9xT59TkzXQEGrHbzDYjm/ediBQezjER8cUHd+Lq65mGL46x18d5Dze7JhZ4/W+tZWL4zF+OO6gdvfUguetuxUd/4U0b23wM7pvHCqKKRN+L6AMOR/GZ6xLMawACJ2r1HNpuQpJDBNqeu5XMBAWm67uUUft4/72rVxLZvgxJCrOeuBpdvGZLjcR9TSv6zOsT6uusQSDShwnPfpdMH3zCDjB1rNz0MSlIPwdUTiiGEmx2yWYcZera+wbpbrjvopixF7fOL4G5nir+0dvElWp8YHhJwYuvjhe/BE3QwnP5MG4vDXzkKr96o4Ja3fJe628dbHiwzk9RnCfl7BeWObimgvYfI2p4CCPUD0PK5Pm4uLci3QfTfM/yrlAz7vk//0//+2F6v/mIp2Pvv/3f//33/6R3z/f757zu/BeWIbpqTW5PHXJeXnZVVN78FywnINY6uPHcbu/3UfbuQ8eZ3F9oPmVmDST/reWXAj/Xt84ywcuuV2gIXq4ME//wPmlEZ30OD0MN+39hT8ukvHv/B863t//V/7lXOuqXiQT+mgPxl6g7eZgSA5mv0rF/5QH9zt/bC6fRMDPMJaL9ZTBR1OrMQ7ubA5je7IxA+b87GJEDoHND6q2UqCBGs8McX4gPr3Zs8K2f8vjMmsQQ6rzkCksnpOXCXocFr4MMT72eCtL2Pp1QfrMg9aHDO+0ZfbhxmNNOVS1T2vPK7j0Z9L6G8G2yi/P1YGdmho1jomP1YYnkmPE7R6daFO0wWxukDRTd1e0F46PWWfZ36aUqmvPRQjMcUhyng4Sq+ENN3d1oazYPmfasbIj6irYbbFmwtVceJaLtvSYnLZAnE2Lq8XhxNv1o8d+nS5yrRbm+eL+kZp+UAXTjAachqsb7PqzXKCb9o4P1cBRfldqu8jTFKKOcP754m2xrWj6u7+g7KpyatdD15ePntQeKy9CKr/1ts+wledZZ4kF6OeuwPVZCcr01d1+E3dcRYjZscDEnGEbM23bzNQ+1y0G52qqoprHAcnyLvNf8KUmY5OZv3OmO9e+XISsAZ4fjT5TBU6Dq+vxUzvFLc+nH2DRp2Zuy9w2ybVkzltJ7WwPM86a5PlGyv2jH1fu8gfQ3kSlc6KbhZljObrIdoqHy9oXiAqnZ62TNViW0Xv2Wh6X2NnUAl2+nEt1sQmh7/jmZ7+KyOnKelsXee8j7tcwxcSJGGkaXtExaY3tyFgX+cZga49WaNJecd8ChttJYZg4PdeQcpGjRwBOF09eDGoQhK83+B64pW6TbDRUu1ED/zEWG6Okl+6WQJ+WbqIt/F5tnN8mr26iMnJ0+hFzHpWytg6m5GTcljDXsaTPmD2kzJmxZsr49itLcDwhWZ1AmPvHjljccdAeLN/YlBNcj3thzuNg7xex/LBy1zj8fQcpT+7uI43oI+f+tRBr3pWJKft7NyfdyELN6n6qRt1nkCuDPMi1JwpwgZwY85OB2d/bZEHSDOMU4OoHnoDdaMAdonlcsUlfLomM4RIJZxNe/hORiDLdRFi0L+7LBf2N5a/u4woRuRf7Zrgy4KQGdSDnyczC2qDHilwm8lkTa1b4ytzzpxw7Ky96LT4txUh5GppgibJ3yH76gg62Ml77cuNbZkKr6Fi8urh5NK8fslSEObTjJ7qJEjT85ZSmGHuxRyt6kNgnsfDrzxkxvQBmb55par+KE396n/7A8EklRpqdV58MAB3sm31rlel/7Y+NOhhzXUKX8x23x/wBL19DVxO8cgfHfee/eVfU665eoBVHTzua9t0+ZcSNFRwxGzt/WXP/xX2HLwhmT177HN8b0cVzP875MS+gLL9xsWB6BvPnXd8WkpyxJtZKOWYPOpNo3W3LWndMRR/wEvw7vxO9Pwb3X7kgB/8P/khcPp7N76X77nku4HnX3IvzxO0ikhxtC1qiID99whNVd9y66/pSVkAczxNiJPsYVx66aG0513v/2Mgey+ThmpyY/Hi/zZWTf6AUCbGG28MdHl7M8IUFLs45TumbXwjjB5aAeawjLR/8rz1TYvl/8L6LTjb4u9kxhssXbPQ2/16QgJAvBrr8/XneLed/rKde4tSfguiXx/T+MF57+x5HaNbTHlNZsyk/q87u/Aufa45JfnphCQqe1lHEKuntWWwwlDnt8Dz2OmLpeDQlwjm5zEzeaiKEgR2ejd2VDTUuso+jWBUca9AUkPHl0hDzmyN5yP8W+9Tw51gw5Vpe2bo5Hxl3XKvmw41PdQ2ho6tNpTnn1j8REiiuGoOnK9PhvFRP3Msvo15wPyesvjU0hxEjtf/HkZ28OyajBuvBi3dxQT79xpZReLbHad2xW2v6xpc2j8Fbn3GX0/wXAyeNsA+Z1qdBe/nJd0AUSJadz2crzDjshAogsj4ik+COT3p1x1dzNqCOEpOj6zeemNYM1duXBwc/LNfDHvsy70Ww9XLPw5fL+0848wXfJ+sg+lg0x4txrZ3UidzBY9qAamKeseP0zIN6bPTzSX4T6grvzOrLWm63w0mfDRyxYS7YpVOMB69/LPUSYA/uOmVwawxEFNw3sE+ZGF3jCv6OExaDF+fjaMDxk2PHdpGascNvrTJI8eR7uOc77Yd6UyqKNHrI+fb7vd1WA1EKyq5xWBj2xT2bjw+xGbvvwaV+ra2hknZuNaf5DqM45w0e10pZboh9/LYn0+S/WWtx6oqeCqjIyvtkkoT1nUSCb64VrsR+btww9bwOW5K4ThyN/PPoATur7uCzvzYZv5hFs8e/g2DBp6vFtGk/4hIAfidImwTLy+qru/DEhnX9gUcULkYWnsBMA+ocxMv3Z23WlKb09+aOpFTyNSNMdDNf94KCOlgrpvkIQCaQ5vzumYPLJpgnruDYNIYB//XDfV06KANYdtz2CHlOQLDY80TtjzQMu++s0DyCWLN/iDJ1UAOYPHkzOTuZyk1cfr5jvd39yyfwgV1bul5aaPmRrpOHOQGPhWByqpmYCzqeW+lXS3DVFNPdKaH5eWKMCoLYhetHPSmCVH8Zw5/D3iEpX6sf0mrRqs5HG7gc2+r55F1N8B4fJHBuqH3rq51MYTSoe9DXkONUF1yHckZx4Rh7LxxMfPcFursJSDjUDEPJK5MmuBjsnj4maPrBPsmYO5IffOb2EdvFiM+y9X3sl0d8UxLlkOueGGKQA+H5tgdPEa376WcCm1/xV0Tl9gi2x9Zlzj/jyYbj+nk0Y7AGc+MA66Y5CWMZf61dYnbEqAY1Jm/WDeFos26PWflR41x0gWFYs+jG1JotHCflyYPzuMrP8ojwnVEbF3f8TYr02gtXLtJzV4FPf7DkNn9uR+bIOqjYBB4fGNO6twHg0IGc/HC/JafcsXF8z4df7uy/j2doYhh3iD0JhI++8Y4u75TvQvT3vNv7a97V9V+r8Zfbg2PtBeTVBV/PI+ozhSJ9ISGG5mtejtnWh6R6ddqbGH/5tf21nsSXuy+OMmfsjx8xrz8xn8J7oVyeNOdeUGjP+uJC59PS+x205XwJJ8ekWvtuN3Xzom3fsTepeZGT8q9fxOXXBdRITajLoE/swoGWbLAGl5/c58GrLwH0oh+vz0w7F+soYiSOUKnBlgcjx24Jsbu+XmHHC3r1Zpp1LMGUssfp+0LJ+KmPsT4/9uOtdyzHWyNRJDXHcoGoogeESeizd1ltdfx1ay0UFjbm67tU1DXhQDKmHx2O8/eJ56sItVutqnE1Z+IvLzxgxlnz+HEw1rHTsCIffWGIJqLgenJlpRU3p0CdzRVwc9XsFj/j0nc3YBCX44sZ2JrpmUmS9eZQwrMelXuJYl/fY0ItA81PD2NvZS/W6EA/LBfT6PY48wM8Pb9+yX95h9X25+fuYY3ACKgu2L9jOqo3MJ5/wEvcje/85SKymJ5zgLO+ML2ZT9vqaE/BNof5M++eTO3b6nV/vJTWNamqivWOS2PhXt4PZr2iD84D+vREvZrI39FoYO+x/JFfO5UMf5Pwl3us5cArVvc1ypCeKett6wB0fJfB2I/Jrj2Ycj8lcRc73ycQ/2rQfFqxvceR2NZcDpDXl0vw9PrhPox8P+v0GKUG+xj/boOt+vIkfPmHs1RqwEf+j8Zmw1UWejde4jgnysNC8jy+vBpa12EIyLAv1OdtqDmXW398lm/y08O1GPwCyMPk1ZrfQe9QA1OFllwstmuqvBcMkQVEQYsH53fxAbd4OCHJgJt9+MpVjI0VLyg+Ml92OPWxvlzOiigjIFQ0lXyZN89lwpmf9WL0Cskdt7+Ht3j2AZYxC8YEM838WqKdue6Hf+DPPkccrcgwOCQ8QeuTOGyHza7cHMygDcguB5I1+wPI19/RqyZUgGmNzGu3Dub54vsZAD4D1x2hxwqf74bQDVKLgbe17KS2J9mw58nbv/Y/h/PXejcWs7Rw+fHLTJa3+huD7tnlwCz2WpA1/uHYGx+bOEVVKyZ7bHIWGdoaw3y1zAUJcGDqyOQHv56ftpoIIioj55bTFZ0FOvugUIhIE5HgY2PRk19a4t7RHN9+4bZkHyQzz/n1hJwcCoKFZe9QXkZ7Gb/HaXp1v7lGSK8Yb/9ZncL5FDNR2RvCeclxZWTb6x17r0nrednJdT07vpp7bnC7hRbbdLeu+mPOOA2ZTS/W1b8e7tjCOJy8WZlH3dWSYGmHfUTkeOFCNxyC4lQjtcTpnb8WVDA+XFdjbVfZ2dR7XI3DTypyvfsK0JUN3MmvKEHVgrvhQQQjATu0nqPRt31zEFpJ/OIN9fYgrn8Qqzwg9wRQOzpPhxmwZXgxBRN4tMYGpxfQXJDlXdJyL08A0HFfyDukvCvL/evFkwLqdw0vmcIdJxfpDnCZcDMJ2B8Urx6CcHkTjL8cRBJ1wcxyMewf7YwGL9H5q+O5EP/HP6v71/udaP8SOe+ce5GZvmVvP0htH8kebm6/ZsGKRYA5wT8/oqJGYYfJ3HpCU5VM0M6KEjt3Tc3guSCOry/CkLmc9jdL9HKfznHi35t1ff/q7vRcMmOTxJu1txlyZJhXnlxM8w568k4Te37oz949R4/+TJQJCVrtWfpGkcsdVx9Hyu27aPwR0nyRl8evXZv10x9oqi4wG7Xg+vYraWPiB3/36M3ihja0YNTRo4abGQMzWjaobXzYniMtDxa4Gm1UCT46Gt8MzE+zeYyWfxlRsfnOge9+54gak6v4RJxOetJS0AVZ6+Ucecpiwm0SgP5L6rL61gNQR+hs2lywiYGaFG3tQU/LFyTR6V1O/MbQv+szsQrl2NUGrHm7laXCzL1YUJuf+xNnVNcPb1HqpxewkQJNG67jwYE9O0yb8BgRB5HNLQ5TbfgWwVx9wXibwSPnccsUmyKgqA77MN7s+5iOllOSqbzif/ZgtakC7WKz9znHFlMfO9VBe1ydH38W5om7o1jgjGoAEwr1MjtOrA9vp/h6jMvLWgz75Y/BMrMu2wtZn7BcK/pYkzxi5YBMRGxYx6c5qy8riPecwzUvcfXZIecwlPFQL1jyHbfnOAbdFhSI/tYP/O1BM0jRDXX8wArX98ZneThELQ97hyn/mu/pYSWZB55SyZLw7KfhanAdD2Gcj2oG8xn6ODD6cWgR8dRozCcPqD/xfDv+nL/HJufkHXPznVFb+7Fte0ZOonc7PaCWzOPeOSxeePsCsr5MruT8PdQZz6JvJ9N78sRsgd+DPzIKbbITT/OYeufNxGh3TwODee8QgDeGJhQthTeQWuIPQ+NjIR6LB4kZeJDFacjmbVRZtO/gfvbFVWrZPviRHfWP4wwsP+zsx2Hap9rAz8e7QX32khi0o4HY/PxhLeWCkArRBQ5+9hvaLr72HgP8wPbRH5Lh35NgicS8uWE92Xia93K1jti48ODJ0fEzcX7HoU+oW9z+bRyxPKF6XoQA689qDG/u0K0KMjjPn1WWGBmtmzpmwfr6r/Y49+S7EaAyCDoDu3Y1e2qaH0ic6rnacRnng84BZozOck5TE6BfImPjI0E21W42dXu+fbBNWa6Xo3hTQoNyevB9EJxzmk3YKqevT/TQohhYWquxPbeeZ7DY6IO+5Y+h5dX60Y1DXQcwQr9QrdzODYc311h98hE/4PMtzvrU2XhAFy3WhsKjtaJ6FDPX/sl7kXeUf9wftReEtC/kJb6aul/1MD45wGP46JZDWyngaWyVM380JI751uyf+r68BCEJXRniPvMzqsNswZvT3OE0j6hnU8rLeFzkIPDFTxnJ8eEstxdPt350Zc3c+Js/CW8CzYZxwXnfzz4O6ycdmrHlZ+NZQ3J53HORl9vB3/2Vmc7fWqI3vl40Nw4+dXCxn/nfc6HphGv+y9ddL5rR9OggL7Bwqt+Gsd4LBsEyDQg9v/D71nkX/V/5w2j/yGOg938pyYtbLnR99/wuzk3/qTf3STw++GGAZp089diP5FcbvSLebWLonxd1CJEmtkwAxcdgynHkohU8F7Yke/ocANXiI6IfaQ+a+/78+NF899W/3BDj7yejqo8/CMfXr/wBvfvVJnoBF8MXANifNvY5Kg+HStCh9NRmEriTKw33fvBsVDYc3JwePsHjvjLDetnnxRTy2D944SI2XyA1lSgrtMQPRybOmcZujAYpitWO/7TOynECyw8Dzs7cquXs3RWHquJOH3E9ScPXPGyfWhLc+cURfMe/97lnj47pn47VP421o2OI5avFHsLCufrUhUBFaHt1xQgV43SvjvHUpVPYk1Zu4keQnOTYkgmG+MvVcLeLWf+JQzP22Ka74debIKCmHxtPby4PdryTIe1sYvCRo0bjOQ4sMXs+uSxRph6PxBhH4MUCaGTx5o3hSngnMVgP/Aa89V2mywVD82H42f8iDYdPXMPg3H2Lfr0nM9iddzsG1VAx5UPqcndeHiqmRhK89vE0Al3Xh+lqMOYfNbwc5SUSKDzL4QLb9ESs8+3vRacnBlzlZV+snAWEqaOaV09zbrvzfditFyOOpoVzusi12/nwxJM7oO6Zsm51XSEXLlbgjhdksfHH7nz+/4Q9HpHmC6dcOkzssRv/+exzyatBIU6rRWnZfDSc9/ReNeCCMaccmbsk1u+nB9pZEZNBGAiXzqH5HLt48eESk017XdwR6Hy6FrD3dzy2wDV+edrnvaj9nmtPtMn6mJWAZIXB2tRXrTsf1tf+aVXwj1wXz3pFzerJs6quec+rqO2KUBPdg+NOkp4UO2Eq3EJsU8KMX+FrX0uhOuvI1oaShfqaze23hmGIWbEN6EFqGFzNV4L/P6vVLFs12QsVPM6UUM42HnuwEaPqg00bTzB9JhEMLp64ND7rby/x88SydH1She0M7pOEY+WTL06eYJu3QWCKSyCawTCV4+3BOgDXxmK7r85PaKbwtW4v1DP/V+J3cW5dZqtGYuUPxi/C+WKdn+l6NeCNVL+Izjh5w2rLwsdBayXH4Qp6g8gzG/nswWn6hDR/st4LTYRoOzx6GGrTmUV8qH048c4WPA9yVMIA8640dRP76IZjTz3gO7qwDunOmTkYGKoV9M85iO8TKzltVrEl6DlRjuVajq++2WRt5tV79cHqEUSsWrsz76mluPYj1sStCmPPZ+hxl3FH4EgDNjIb8z11x4DNGtOL7xPuIHeslEJmJBBL8oxlIf7B1pVtMh1wxxPbKflE9xi0BajsWI6t8ag9dToHUEFCWkPY6VEeKEjFkeqJDyRxT6AhbvbA8VoyU3jxrw6CO1TwLk9XfAFzf+QFWW4b5PxqNBrMHSt4qvt6tdoCvBLkBsMFHPV7IcicjyhjpyhThStz/1WjifDnfhMdFAFGfV2yfm5y2OO0d2rg3WOCGkMN9t4lXYXsvV9m+VxcTk/CrY1CYuPc4n98cxHOx9jz1+Hyb8L4hW58XNT2whZeUhs7zXBmqE9Z7/nGhTLYxWfaWPUnLt/4n54fFzhHqcXxR+0YHEN4fef8cwFB6B/xUU9I5UX7XmDgnW61UCt+uPgJPpVDnXXr7ao+/N/+WWfB4smnzGzkCjESYKuDeYY18fjChPzVgevBs2CkDB4TjUdMpmjuR94byzv9UoInVRbPOthHJ/4M4knErsTsG4Nc/OrXCPZFNbZoe8SUAZ87eCXWjJ2B0hKFO1+sxvXkAkiyeO2kGl/9wxs8KNjL/cTJwCZZSudeDco4jYlDHiawDw9GRnbTeijNUtztFU3EbahRwCfW9RklzTzfT1ziv9pgG++zj214mT454zC922zUoPKqWmb2z3Fo1QWwTR0+Fmux+7duRKsJbI89hsDIyJ68cmbid48xVnsYjTEXsXrPhv5qviw7bnJ3MxWsxDbNZUx8Tvrl73G8quUC3PwvZf1octzEiu6YNs8bBz8rvsTd2vgajgp/+Ut+26euMETPxnjXg2efmpptSOLe+pfBeqcZqPcr7XUIHE+O9Vqi10fny1ftq/FVSQu7EoeOhH97xOPaNLF3ZPKcV8bf+fDojbJgeszeGGfHVysJBX5ylOvF1n8saqMORjyO9armq/XqmoYnxnyLbe8tBkp8YWVrr7Iut2lqbeqEGKBD7rMXef0gwnrLOL1isvB51/nNl8zLW+IPqdMd8WZh2/alZiZNUyM+zrXdp+HUP93l3nlJ76ah7PV3zrZ9TUH5I3EQOf7UbEFxJLZtBGR7KtQYhGUSjqVYWdKe8Y2/IBs+guwPd1RdP7oyYb4E7O9OTga7hhv9p4+AfHPAGOa/+dcG2vWlKIshboZdch7nN5rpk4N8cbbWLjggr61aeELEE6OnKA928Dm44Ptk7nUvX/fVKy/1wJU9a55k8UV+n8wS4J1uI3nfiFQdiY2PcTQfczne2h9XweFfnkwdW7Nn+ESUCdrY8US7M7XyxAo7uh9Rx0XYsKsNmzmu3hcDNgP75bYgTPlZDaXOlm9uSBR9mIUVExbaClBMcV3qOLvk6pfLxo6zTCZw83I0163Jj+477n2S+MZSUasursur0phKMWJhVxeRrQEB5zwflh/1sxb16sJgvw/rcfrpLn9FBfwcsURcRtI+Me/xWaveHhvipnl2JO/cwXM9spQ7LlBb2f+PrTNQbCPHle1Mkt33/3+7d2eSvDqnAJLyLGN3k0ChUEC3pG5LdpjMCyrQ/SEgc0fw9pn9FRRgoodLnlm37tbTLjQPUH0Hh91I+6l2Eh5eFlNDYjE3faKcj/H1xd5j0x6cEHXCVz92fdmoIfv3mKpTvYaIBQdN5QWRBRwySIa8AGrJdueajPXJ/hQSPh7XrL1B5s6Hm0+0THgTlHdyezMoR3nJz9jcLiau2rKQtO98e8OVjb8/zfuinHu58aqOSbK5wqodPQz2ecHitpw/aOlzcdZeGEESP97zU26fIzUajlT7Fj3wimVvY0Od8/Bbbs5/52P3f+ac5YcM9gIk/Q62z32N55jEVR5vbIsxWfDS2ov2wJt/SmDJzX5VYTk3lXCai+c5PdVM0OLVG5/vKqMrXLkjh6bfilq9fdecm3L/3/b5HXpvtIP3h688PhPKkJua6B01IDZ8+4MXRYkstl4DGzs+dtTvO/IUkkB3mdFHqzGpG3sCaod/QA4cx9cbc16D8oOc/GPNSzDHYo8L3J4r+KeaZsw6PNszG4QwR9VXXuOm3OEIw2BvnQQmAqCBl9v8y7178zQfW45q9ZV7teLZ3BB/5pMk5vJwsrS2tVeKvYqpqEeXWYczTnMOFQxMvYjORDPJM6x9ysQ05kxW9WcNH5rCtHiPkfHHYiJX4cJv7GpSR+JtCEoyyEn9g6+CzTh6hv7Dii1xupbXVbm4/s3X0bo9fs+Zsk+OPQZoGj6mes3lYkgr6ObocQOLRnLUl9Xw6kOvvsTnq77qVezBkksAEsqJEtLC0WC5jJucy7f5N5Z9E7ptDTV2qxzIM9RQnV3SReIEqRmkaz2EPJgKqocQzunVPL6iDySgsMGho0eZHLMk8x3BYb/5RcnRPIV6HIxsfqa14Se6PK33WsobzkNLYBY0P8+nPH3m6/jBFToBQEU1758AACAASURBVEEI6vxqgaq9vVq3P5AGP8ddjuFerVCSBQjnlxNs6Jv9pGWlhHo2rrmau6ziz+YD3RLWRIIkXt2aR2tdNzPrxW0f7MGDJ/7UoP6e14s78ZCFBLVWoQYsmLOdY7OPN843hwnAdMkWbr5k8zhcHzyEMBbHnOOBlo7pWWz+FfcNURyYJCNf4d16IEmpI7bBLbD+iW3I5gq2YLcI8YK7OQBtbeXgxKr4asjaZuANgwIOZS/eveEzaOQEBzTc5KS+PpmwavHashJkwu0CRvjnQJ6maZUQljvIMgPs6otpHwTksLYVxAXRXNxy2aDImMjpBU/2zP1o5JOsfISeP7FrYg+sqVMbGia3s6ytXWs2MWJvyfhYx8L1WRaHa//I0MTHYZwbckyd0BqnI1VSY0YvfplhgBccV0qjJ0B1sfdis324+olF6eygQcssx+MayEKdz2brAetRR8PjW6wP4CyKW8Cst6BJUExY8oVWjuvZi2mfsHeQtHO3mRc/8XOR+BW79RBzekK2GFxnUt0oEtS9ebFV6d0ncGLlEA379qR41NMrxmHg4GXQzztiy7raelz090AjUiWyEwZcAeXd7eFripuzIbqbN4DBYGwuJdz+oM/ielwMnqBbKTwQoQb8oJ4a9/gUM8eTWodroxF0JG29OkOa9fruDZ9p1dteDHdEOEvAyGmt1BLP2qQGSy6e80yQzcZZO/XANnEG9cZETx7nEG7/mqhbNKkjftrR7N2Dl3Pq8ldomjrgn5PtfsrH+I2ZvdyoQ78i0EHurH1uQGEH+Xgu9OPgP6M/N708HxLLjWXDY0sT0AlP311GeHsk0+FnEmw44fCn3eFkvkNd6WvkNLQhzXWumKr/I4bkM/hINytv/pKr/7MFN9PoioMdOZjmdZBSHGgDgDbnQOMHH/NJkYnPl2PozsihoZfl52I0X669MJ1Uu+vvzueECEZtOEjJ94B6DPoX57/lY/v9iHuPjXnQk2NgT6ExPhrcxydR/iu0HF/rUltrpT57gNyJm7Rineej8Qx/sIPIlqbtqdq1utmErGkyz4Qc/CkUfhOdo+MZlDX5PRbGZE0odibZw6/G8csZyzjNyZV0j2224HBnJHynh8fHUDD4cNq/Z69tfDCor2isGZBfu3m1TLa5aBSF2OSy5/Mas/bTcyjD2brKi2V1OWfDSPDQl9Mi6prs9tIexKwtm+Wilo7kg2tWb0/uvORgsPUcIgat0TnBojIvetmJufyrZ9JVexbt7cZWXa8ze3xW38Z7roW32uslL1rM53HFMsdnCUgssDm7DFtslxtrxsZMgddvdgE7215tHOfxxZcbjAKXehuX9fGhGxy2yQ9PJXeP7xy/48Nae6Mps7PtLV5Gcwl2/bA14tHV2GUc/tEH3c0wVPATb60sEjN1gBA/PutyDmDUAjB+dpNLxMGio1zb4yyfMeePrx2LJKa99Xk46NPnryJfpmgZuTdpq0idETt6T4+TjowMa81+j99HI9a/5Kdno/1LrfBBvNUczgo49oGd2lxTA5PJtecFbNUdL/nFdPP29c4t9tTjauMSBq95vm4VfR8PuD84s/Zx/HBVTbewbr1aqOfpD4rbtZk1jEUi+/h3ERRh2weiGKs6k5pmzw4vxs3nDboBsSsqjCc5fLE3ZFR4Izc8UJ0iG1WBjTEwGMeEi4dwCm4jmgHb0m2hLaZC8PVigHi+2MQYx9BbGCcylkY1fYnhh6S2E7NJ3UtMj/KCtIjWeWrFDMfuJ0UfgCX3wABzEqVrMCgOLhT9QUXfddp3GLwQ5a36fPF7417gwc8TcPD8g6uSEYkzY2q6eY7p1Mw7CLZsgyZmeyPP1LTHhX17FjBzYtNfWxMTx2A1Qbd/E27/Qj16uHBOueWZK1LftXl0m48nOAbFnX4Nf9OOPzug6IEfq2smz4BmHJkOLhb4+WaYh34KxtB6dGYjzKrlqjfHYMIBjGr9RRIMXzzg8m2PNDeQbY9j12ceHVuK2l1sDL78G1utKJYsSbC88Thu7i1x49QUMns/Ws/5g47xwaGWkrF1GLfz7NXB1kTscSbLJqxBXj3jIK79KQO+zuop0c5nlVhosV5ttRFf1MyCXUxjhmtrD2z9iL09wDGe0Xp6BXXIYNrt5uzjmrjq2Rhr5LFjaI9T4yX5khf0Nq4RGwlBe0+Gyf4eq5kjOdNg++7zVLIym3TUWPPUKGli93qgJHAln89Zkja3AnZ91NxjHk6scATVPTw+byOFPnATlie8zKiLb0cCfO7IO9G+Iwo6Pp8r4cicG0hiPcL5w2Bo9IcHk2+YDu+f6QWvD+Dg5FPo8PEDxfZAGeJRrOYhId9Yqm+2a9+byL5rjPbeyPKOCNV10MOsyOcFXa3TJfNuV8h99ZePGL9RNv0RtS0Lr1xZY7pPqbXDSQ1o5rscsSTuDHlr43maj7bz7vn5gYka8pzOD1WCtX7ywTm1ZYGhIrIzDxtHuTlyf/BnaoPbd7z9OwfB7e+yQwBv/iRdewHnDI9h1rBiBvH+1548SWsfjTkM/cRFjLC4la66bAHrLMsZbl0wN6ZI8hk4SopnYVz2692++noxMaZoguJimKWTcygkOUzBVAdB+7F8VG3O7nuO+jjNcVI3efMFr7qzh2uHHA0u1zzGzZdYWPYGkHrk3OCp1fCpb6iaQdub7bM3fT4ZMnJVpIbOmbYHL8vO0cJY7HToVLdaBIHDw1dyEYlfq8A2aY+tiJpEYSePMcSz5gHGXmu1CIbVWrqC60MzvLgWI035W9LDNb6Fy/jEV2fxzqHNt/om62vHu7WgnTlDPdNPLHKwn/rgqJ1KbtxBjk55nuMId8kavRxl26Mryk11N0guApLPeTNnu0e68Ty+7K97adTaXF1zPC63pAmeo/LGTT+MOjHNJ7pCEjvHNGvPp6ePp7bBbB3YqyMx8+Rs2BPLOdHzM1hehKmEfrJXNiqaoeo16gJ2YqZLdSjXzTDF2+H6S/7mmfpKP+js1LfLyW2dlbe897xqxuYhvhz0b0cfK6y3oswbpmX7qTd2ufUPyFDmGeGFepkw6aE5sd9z4LVDsOvswWnJ3LhdLWZzde1xHcGrccKffBMzO/1IsnccUXJlwzGf3uTlMYsBEWCioLYBLbKBEkGQsXYiJNhystwHwiYxIP7GFL9Nko4NZoWC3gcDcxxsId4V0wopm5DaCu8c/HBar6+SD7ZTuZcP075ocNGwAx6+lUMXH9/FUDvfaON75q5dVlenuVoAxYViLywN4dpNRybxexGUjx/+4qANd1WxTXRsyOIB7WK5Z10VQM/MOAp5a4bbXj04e+4TBJlmJA329jXWdWg/1NMDYrg57+Vp3yVL3uTgmws+e4VWX+gmPrvyEx8fgzxb4+ZEa2xFDA7sTPFQI0vD2Wfheut0jaYJy36f4MA1J/E9JzEx5OjUuZYYl5aI7efWgnyEtGao0Veuxd566v9IRD5FESVVlj0WGr5srD+CzGHyhp+er0YR+KZfo+uTjjzVLuPWqh60ZGIOslUf8bjvSiWte3U9mNVbHqKf+ISaP7bLB6KcNN70WDgId1G8OlsfrF22/7C0dvaJf2IHCKQ85lmenhNVML1LAOllYuLFLusd7UglNn/Pg9EMPxyBq5EwF7WsjRX2PRZdNvbcRAvCM9o7Hf7HaYI66R16HlOENOu2BWVY9jFxmGI0dvPkueOc17HJwnOdN9WJTy6PFX85MzZuylzDHZ9/2DLPHfw9C29Kw/fr72DJk1teeOTnd77lpH44E4+PFQsH+1gsIj/45LjwDnr2xoYTKGtvfrK4tahcluVsXZiG18xKMyd5zz/mUiwPicidWkg6NDcfhmDBZCaETVPh5GlVfmzk6rEJPgHkdQzeHsSBXd31ElhdiAPLmjwTTw/5BIO9dz7vpGdufeTNP48T/Ejmh8r0cFjYQwcrW+jRAada4cgk9//uk1Ek/wWn/YhPjrEalHjrCMe3+Mnny0f2jI0rVks2Zo0TP7bsg/ciGU0IrEh9brIeRqNdAcTId6aEiBnSmmvVDtFTw4snxPzrl6+1EcYoH/uyEU/S5XaNOibhoUohNCRDM/tMlmutyyHQ2MF4bCafNATD/Tm6Xuv1mycJPQ4lT/5yXA1QZoX5oZVtsORkXH9yEDLcYK1X6qJa/0QYvx2RSjbTftVzk7RO/YHv6UheKBK80KtDz/SXOZg5Fi5vbySBa2sYvj4EA951s8mTjcMeKqF8mJu5PfpaqTosdnFBm6KEPoamD/DIl3VvDk05/DmWI2I1nJuIEWBucs3YY697zR+5Hg3J0n4RvEqYn8DHPn09PiKOiIQMrxFj357Gpf7sb77Fh3ePyWS2P/CMPdOJ67ld9jCV4uoIaqvYfI1sdQYEsPzwWoNBiBvCJ9/a8DTv1WUOsNSZ75NTYLTO8+LWcdjJ89QMs305SSYTnGrJhtr0twdYmo/ImWPMKK5zzxcQEEk2eNzoYJdvFDDMbN5mdu350zoFBareLIyVZxlElG34yQNPz5ftkyTazWwO2WQ1+6NDZYrBbURzV3HccWKuKztyTl9dBRIfoT1u1XQEDGcYpPAddBaM5p0ENXWLYwNPAbi2yaOm6ECbFGtFAGWlRZS5wuWLJHbmEweuBx2CxoqfQiVwA1+HMOJYHt5xahsq3LNuvqxCQyXbTNye1NGDbH+nm4m16wTSkhLOuy9g+FijuePjoABnc3uQmAc/5PFzEZQLjXDwpkSmXH4iiokv4vAx52IS3dzUO9DFSJ6ZKezkHB9SxJAD6rnxJok6416TfWDBl4HgsXZfU9fvcfIBOXnYOQDnv0Gy18xTIP26xJnycXrIQ2A5uE2OmWM654nCwVWHH6PP8h1tR2Pg3E9BbG/K13ji4A5d00+xYjL3hWq0rA5i1t/zRzkyvc9IYBz02wzBkYjosbmM5SiY4i2TubkBZKJP8IiFaqsSuhkD72MpiGLjaS7OkRtjHfG4z/EGszUZ+2UD4vhfTZPGHE10Io0h/6Ppax7XiVhMebI99Wkp55O31lsPAKs4cTGcOXUyqoVYasF22MO9FycfWqibuIa73959re/GBU3uISeXybyTmLlqIMW1/CgqlFBWp+eZw781aWcNah+vBGBaM08aWRgnG4rjPHFxOxIYszpdD0GM7ZIsxcgzYXi5AJBvmNDg6MSb4dfPH03Lmgz7e9p8/BjyzaUOZfYm8fvv3LAlzzeeJ/MrPh7WucH1ZjxzntP6/EjyPj/KZy5m6CFvnl35XXG+83yk/tjyPrp9QpfQE0FYrB7PxJi8ywHWZrnZ7LGesPamvcA3M2PydD6j/fjKDZYPVPmpAPh8jWEdPJr4zsCcbXWQ4STBXjy23hjnXON8Sc9Y+3v8h6/YfpQ9vX9vzM/NOrnpVbD5xzjnAFqpKccKCeJGTzU3jmBfBwhmnJ4a1d5AneXpGPPg4AFOfl4zfyQfdn7d4Xv0/sr5hR6OqEBUPjEVRtLwsINMjNuTr7WJAOXY/Cxa+d1rM081ypvwZfB4JdfG3clwEBvd5xiF8MRCfgb1ZKHuMU4NRowGPMCEut/MsFJd2dnWMlY14p1j+PgzncjGrsJd1Y806tzMWDte21fv9ocMy4dtf2CqzcKXjeyxDtjqsmmOB0NPJ255qw+MAQjONPOls58xbYA4/DVk1hqNGVvmHj+cM24eqKNj+bJvvQAf4wZq20qufsxak8O+nD43sEcMTL87GUFon1SH2XhiwSSa9dZEPeM/WrNetYSsFvqCfWPZE1sb/BlnncDnPCdv9QRdGY1zkThsjk6qKRFiyVFFWxPQ0mzfskpuA7JbfNerEQxxjdx69SbWdUXItevtDy6wjb48a2dvT6ZuzoPJrAz18ZwchuV56ynPcKBHA/vMwsXY3LtebR5OAPQgw9hszX8eG9fX/MML+JwHjbz6JnV4R8LJ0aISi8OwTspQztac+VXufPnfvGb4ot/I1Xb2sSbVexz3fCHN9kS99HHi5CpganmPJd4phAIajNHePOXVpgCTyb99p55iFRjUzc9jWa/8+LOKrTfoIxQiG2FeEjTfFiVBMDuYyTcG/BtfXx+kuI1dwgmCFwKxDy/GzdkMBICbpiVgb7zqad6hjZPCy9s4wzd79x/50JGAvJ77F1/JlRPXWHD5Vqv74crcB2n2v3JRcA70PACbvXYi8O8LLwK8ucyVlzflNCHD6xqwfHuVk7z8MaO5iqN+9XnBNh210GrlgDJTF/ZnrD59YupMyBkbsRjJ4gcj3fLnok5bIu1L9vIPExeL/flBTzo+9r5yrCvrvbn2Ik3RE6ygKqm0bo8mYOrpMZ+o7BKTWKzOBdXbTjF/fKLePK0FC/ief84mLjvj65+p6Had3DtG8y4H3OzDWbntm7qXPTx5ouafhPGtFvLcF/iwpan7RN+MDbEPNDxGY7b59jaiZo/eaj9COzHW4KemogcwmiYOHUwRMTlZek7s4yH2UxO+wZ3jiqZ8nfHOUZm12LGzO3xxvhdGxX7SnVUCt+YTDxccBA5ve94VeOvLtvOnFztNrPXOHsEjdTiz83Hz4PRkk/6Rb/HTTQqc472eYAdHLjSz3vg9N0Rjn6HEd73HF7r8O/mybg3s4SYy83wbHtukU+tRfAEXDzPPoeQKw35KyL7y3OZdZ2+mqr8312a70n3O/DM/4OPGnHdzEcBzIO8+o4Xnmp9Z89xa7ZmHn38KV1E3Hl/qmpvzXz/JSU2x5WufPwns88jEsQOTYc+Tk6VtxIaDNbvsB4o1A3Cx/KBCC7uY1RubS3tbv6BsPCdC9pu6Z4DwOZPk+d7XBtzg+7qSBe786+sLztqaC00y5QcVvpjEWT29Ic/H2tM/30HnBn2+WXvecfxCQX57AJdzjNwUy5Z9ushxAsqBAszXN/4PdaZjA2EMcUgzgllr0uYKVVMnuP2EfM6J9PF7DP66Qn6Y4x8B5DhznmUkU4eJe3TpPKeDYrJrXtZAN4J9QLPDY2In8PTxc/ZqB0NIg+iZMbFtaXjWXgmDwbFj47JHW/sVJyQNcm5usOPyHHU1MCMJ2DHYWa5OlnA5gGS6cnZ/Cqh7aiDi8jNbrUj1PFf/xS160lzM1ApSHwQz337t+t2HIBKC9WvZRz+unB/EN9/1w2FvJx5P80DVbjRqcPgJssL4V9/Ee55rI6nAszl9EBu3mg6TOLiX/wRigZM4SWc9SFQaM7wlAjMMibWuoA52nHucWG5/tx8f++Fayu3k6lm7OsmTnEfTysheGz7kuXcyuvRWfrZVnRieR/JvvXs8hrb4Uzuoqjm4FZd8JOYfuQd26h4iS+jzQqlOX7JUA7meAf2wzsydNsiOIuY8D6pn6mGJloacfTlZ3pnO4bue7ZLe2fzTZs3hYs9Xj08mvqSOlomO1bSyVJqeD1Y008vsq7DHqB2KxS887Q3Yzdk94Wb6Un9j2MKtXjnKdLWPmgDFuAfDmoFhc7LKOl8dl1eYESAOYIHjmRwgoNXaej1PNvLxFVglGyF9TGSBo5pWS/Mvt/HB/bBZ8BgV9zR8m4iZ0X3JoIK+ZPUoJRttVJHZRi3ukwPWoOYgkQBO4ya0zVguPGbJ5OZuqmWW8snc9cd2KQZFneYshVBs/ovNeZ5IqQVo+1Kl/Uhm34GZe2jOiRlR64L92vJ4CNB3lKZW30Gai02uJbgU45ICPqVFp+8MaU/dOvt/y3rRG7saAScRJ4zHhzm+fDPQUh0VA4Yv7HvxDE47kQW73uOyXF5458LW+jA+9a2t7/igPW6KApSFtEzzT2z2euOgDv/KsXyx1zWhEPkljurA39H5Vs1KjJmSCzw2uDMxhcEb56KbwbBYnhXT9VhH88Kvr7lJcs+X1rvrOE7C7Rk5Vr9OX5hGa7j2hQqfOennzMU/euDfDOa08LATwBj/m0/9D4f9Xfywuczm1QJX+9uMYDZ3hbIe33HcGtTjpk62c7TmeA3/XNAArawiXR9h40sdxcQbfWfkBfIcgxWavUxTO6vjeiYbt7UUFOz2LCTAt7dMe45jw1wdZ//6AWcYXzVH52rTjLbk26Fv+o/tPq6K2FysqpNZdZDtdmk54UfraFdzUDyGybMwaQQxW+FiyLkZmj8rv2Jnnz8qR15++Mjwk0c8L/Jfqnmj7ROGPjTzO9AQ+C56CL7xh8PgyfMm/x0YmvyhFjfm3sz2Rg0C+cBakyK09TmsHL/zAwB7w/nFBVTIvbGdYtu3xKpZdzbExhYMHkYRVpb5Noqe5Tn2Z7z9yo5J7fiM1VSb/bOHE5MndV8z8pzrSAxxfns+K6MCgIQSVmrgHeXszMduDmMBQnOTn+bsR9n5iQevUb9zk0sveH3qMSEfx4ob987h3fPLP4pn7vjCG1B8HE+OVeoijvzsM6n26Tv+GOECs5yKDCd1oHsx6zdP7PAnW/Z+ZZMfavP/rvMPTULKLWdN8nVN7mhTWJ0eo8Gx2+ui1fC4zFMtTTYd0G5sNng8UyzQBa7ayavQjdTlRkt89ZRla9g+CIzraB6+TWVf6W/+weM+615cFlXmztkG1P6oy0UkvjrMenSzMs4teFzBo+XxVcNg0SRnAA2Zx5QhmEYD60QuX/YwbB14BbtDIyNbJhszc4z1DyaBWkJZ1sas982z/doaIq7nBYGqaeyeI+Sx/miQOxtzo59YwtjyJUfn7cnEiNHpjE3zE107TNqkjZ181H0iSFG8tuk7biIVwAJdGWI7rS1znj+xlxPno+9LLnwdQaMFzrfejY2tOeEFF80kmtWQDLqseMsYFLpEQ9Oc9TcfzvZhlRezthaDBjJlb3A0qAvbDHjudPLe84bnQzmJY6BlOZ9aMPE84ghWzVmbz7D6YBmmYiVLDWvcWodDM86En94MeHW15iEm5//MgP/y7FGBf1QfrQhTvyHEmJwCDwcYxsndpbl7rKv2aiHLR7Zbj7HBQ/9gnJt+j8fkB2+dUFYffVbzrMnGIOOOt2ZsKhr81dbI1S1msNYFHtbk/0c8mvSDANMsi/vsKT+AXnXyUeSVQShrOVhkKMB9VyQpJii6l8G6SCez+WQqZlzE2YSuP0SacXkbtfygW2z9jb4PlranVrcfaeI1rLHMzes+81x8se53fdjIt++yw8lFpgeeP2PjtQgE6QlXFI6ss9iDklUvgOgqSbnI24uYefeB61by+k5QeHpxBiEXtNTHxU8uSrgIIh7rHEjsUO8FE71aH7EMIrhcoj/yJH9ZktMnSECZe7FLvurRljzEwVSN5RQU247mBJv+QD762E/E0QV2uchVhcEF+IQt9dnjA1/MLKYS8+ObbNU8ebAJN9kgoI2RURFMasEMdBI2il4Nf+mMU0+esEdGghgB+tVIF+HyBWZyrc7PwOQIzt4ER7QKRwcxWxcOcJPNOF8MJn59Hl9JKOf2nZrtGTmGH05zwDtz9mC3EvKVbuJ17Hz3izH4I5Z4xtZPRREwORK/52NBxjYfQZu58fYi4UjQM1q6cnF6BMC+jnrot0fg5VIHnsU6sz+LNVc2eywEZ1Nlo2+Oy/q+7pcLtNBM7ANrq3FSTTCfuoLbY6URFfgRBNv42efbemPvnucT1Wf/DpHljdlUuKeGjzonh9FfNG1NG4cCn1OXS93VyN/X4LHAzVt/Osl5I+ts8lyXd11zz+i7pHDi5m/H7z1rgelWbth9Po2hvaGGkKNvOM8PJKcmtPrc7q/aZG4t/6xdy/CAUSPPv6s1U7nABOCxyHZ/t96ekAtfgl0bSwCT+uDOTA5uTln10wPlzVa/9bHwiYhs4QwNS8Tx+9mEq5ONXG0PPwz2D6QbQFCiiUmfv33r/xLieuzMzZc9QyrCvDWuVux4Sc8EqHPWmfVTYbHnOHusxcDAuQii9ft3V6RsdP/XdgFU2L4RMAnsOZ+EyLHgEKre10Vee3Le5B+C48po74/Qpi6VmKKo1ThjDBezPFuXPYcf/OYIhcd2Yo05zSB/HLNmeuLgYUhXHSywouZ/DrFFNWLjQI86Ta3b8/xoEZLg4mDZ6PYMhvIcjTFw7IkY1+hv/Zx8niev3ASwtO5MjuvpN3Ty7s1O2WebiAT7egbIcbU2EIL1jG4Ja0eBitmk3rMervKzEAVIOpCtp+S1gst6pQxxj1H7YBphb/xHQBsCjX0IeFOXnegZw2b4zN1NHZnzmLcma7tUN+PWQ2D9peu60ZPuFNYS9wb01h4cwYTOuWRu583Y82Ozg+98OfRrQzz+jbjHFcvyet7+j3Njz7VWUVHS2dOHM9pI53Nj9v6dkeS8PdcYIUitBp4j5X/6sXmONq71dpgAznw7Hwd5M83OwX6jtIPFpkbAjd9etdfRNHobP+fZxiyHTFsDKi9OHlO1r+a078mnkFjCI78aHp2jCeceE0JEDKf3PM5rBnseO4k/P5y47utHALU8r6dbv3k2Pymr0DbtsvKb/DwWBklN21txrOPbY2gNMXhuyI0TRAZ95Vt9xTQLlp0BDJvkxLCuT9OTHw99wKumLzj95BrqfMQ9C9aQfJ0HrZ0s+DYKpMthwZ0hrNNZN2YbvZhyzolD8dv83cPl/ES0mNFocclW3qxqmJw9GBsJN/nGeSrQMiXhBsPJ4T7g2npzTCw3yYz9aCW5ueBQhS4uC3Jx49kBIV9XC7GTzgkwD1Ae4PtOuFqD4o+q5ZLMdw44JtsK8Pcd99GbCxPf7Qn/7u0d+fbiw8wo6ICv+qpJawqmHjRbjn1DIysCMqYpQbKIj97mIoiLtJiG9pl81m8hgiy+fHJ8wYVdjeR0RJOisEMwY2hcZT4Ql/sgWGijUF6V8Mll3OSPEY7ay+Y69tZ6cUEFizc2oc3Aixlil3+siUdJI1wAyFgNLmrJtj63gyMfFDLEVt7iWOw5XkzXRGgHFkd96GWRb3kGAyRrodNjtTU02xkvZtIP8dWQ+K8vqJUwQqa+6qkuKnNMbqyrFzvm3qwXd5imFygHz3AfPIAIngAAIABJREFUe2cEWqq97rGKjzhIqSfLc3xlIHYG4fTr1Sc3ocWxX9kPMhH0uip2uzxEih0OsmmTiKB45e3xkWuTxL5Yc5/YatpzyhiIpzOlbJ943GLfx3drSE5FsWFUhyamWFbvQsRls+vgNu8+J3iTOZoVHjjPedTAQG9/RBhtfPw5Pm/gcG4PgtbGu+kTyO59PlbE9I3+Ha3wZPh4gGeeGI3feuJf/OK2pMMFN2NeC7Zo47aYuEHJPUKVRFyMXoBkyg9595zDFbVLR8mti5AsOFL+kDa/e8+Hz7FRg8c5yege5OSsxOrsw3weR4m5+WLLneyf+cQCN/59p5vXln4CwU8swBsyX+MglTIbeM5F6T97rArh8Vk4qjrUk1jjg+F4tgbJ7/PP4pPrY9CX/Cs6nnH7+pk5fbIb8+6569jp7R7bDZLDZg3baIW/50fJ1YcOsVY3WUYL9j6UkqdcN1fbBhPPA0d7Yr5iRqXcbHyegi5Ydj6fOqku8HpiUxX8mSMHbqDjmbnAloFTPeSBjw4R2yiPcSHaAbcPMc44nSDQcc+Ltza1bA1HFxqrdWMn0aNdiTxQzP1yjvypa3BwP3lGVPlsSixbH9MF7D7x24kt6fR3uAHYqeUzdnrDvAQ9dmYoU4+HZ2GsyZyv2gia4zgNWCweCc1V4j1/iBC3OmimPCAmpxY4roe5/pyvPdbFNiSs09jNU7xBTBuzfaIGjLOB72ha+2h/faZQ7+SGwOnTH3LBMQNeDMv/7mNUlzZAE9jX+RJgqn/WcGHLvz4ua69159MPUVt7Y0BQmrHWQloMcViOBWXevT5yTT82A3sQhEnInpG42qcnAsBW79tPgYeE4IInxBisl/PmrLqGfPQHjkfDxssNMYFTW8+VyTYx+LG0bqMDj3ZDT9b6WdIXfGAy1aSl9a9xI9cPfgc9uce8uYjr8Q1uoDcikcl1ru1wqGN4DLk8anuCW4sU1kUC5Lz2Ui5fg/XrmHoVkdz2B0GtqL3w/0EvOjTDPqK2TQZMVDA9dRKTL2MWB68FNllZ2RbXA7mr7BXUtZVpKq8i4280mC3GWdJUjwdkc15loAF2cDG18rHgYk03M3GXmWO4etFHw8vjRdXMvVEHFxd/rMgTIxdLvTjwmc+f4ttg3hHKOOkTt3PeRSh/Lgi4SIpO0F7M8kvbWfDRQ7RwEe2Dkjy5qMqVjfqxy8G7Rhn+sfTkGNXathXGx2KJAHKh9G0u0uXg1Z0aA0BHjxdq6RF5MhfCBUz71nf2qQnCm1cLoTGLzZTRPJkkXmbF6HKjjRl0KmAPHE+HHJnuDUYm65LzrlCUOELFlIO63tE6gYx9dlVIeCOItoeDc11y6eRB5/I47XErAOKwrl0jfWxCuM3puvaWTaYRlT0rSYzHlcz5vqjmaMiTf+owbDQw36Nmbvl1CluOKkfF8KHRr+rqkyBcV+nWCZHxNcgLbofz+HyMZXEvGIfbuKBd9lgQ6zkR23tMzHNUUNlw5NxVm729Opur64FCaK7KffpdqpUtH1iPn0UcV3zNvT2tpwRLY0iTVNsJBzH9wPZyx+UxiHH1NWwych7omLhNRlTmUKmJiT42fbQbh3Ee5/rDZfrlHdqqGI4Alk4sgZ0E1iMAi783PjnRQt/YV24CsPEcmPvv92PRyeKo7tSX575v50+bhvdP/mAcweXc+nxMQD5DTOY9X/j99etTCLhwdNeJMUiDP6PnOedEY/cm2xgxtS9++epny5iPq0ebz2FtQNs++XkN8DVIOD1MnfnDZ30nC+372oE2aiIwqmaPPEt/awRhrmAb5A3yT3lzo5y+8u1H4v2VAil7Ew03pMblNWhumiJyEuGq+D3/9lNmdKSvTn0tyLI6uMn3Zr219PxLFnmIQif7d1zbesjLDbXnTuqvCnLmhw/5py6MQ9njz+OkOuwTKYKpBqbLknn4rf3DKlxKetJeN4lHa0kPDVZwSRrb5WQZg/aCi5lAdlPohKJ0xuBHHb2EV+7Jv/PmK17K4Ha4XkZrzWL0WLd9C0ruAo/GJw8xzUOUQVTWmgnLoqXUxwI/28Wztx8isWc0aCwYPkdzLld81DD6QU64tu3HJWu2xe3xacwIfvisB3BsZQYTNGvrnyXemHvxjzbwWc8GHWcYPrWKAYVftDBXY975ctu7E5LVaCFwewNf2QrkYYUmY5XipmWcvBsBsn4A5oc73/bLRBAuR3PpJ5H9oRqTVhOPfeGHWcZYLfvqNuoj1zmGia+X1Ftf+LSXCPbVeJ+7p4bRdTDqR4HKHx1oxca3Zrerw6dcffELsQqxZzMU+9zGWV7O8qlZTHN0C90co6F8mbd22op9Y3bGGgz1o5VhfNbnHDExUib6YKdvsbdbhic+uOc5eaLivKjNV194nBy15SidUYv/rK2A1g/9zbR4itnHgNmFXByz9oUedqDiUYrsOzwf6r34uLUvrJ5l2dUS3SpDvH2+Qq4Ozn/G1MVrF2kAnPNKA7+Djn0b8DSf+M8xSSky+BWz+V3H7tqiiodjkzaOcm58V2ozXXVtC2qHk7F79L7zer+0/0ND8ASkAWu+GRuNH33eKNTkVntm+ibpvmuj9tj4C+zcHPOxGXD+RJ8XTG6cc9EDBxV50CIAjAM9XCBn7XMZF5+J4Y/O8ZNjLjP8f75ZZ9l3OorneA6LF1FwegEXa5+MQGTMDvTeWLcP6deffTdmb/S5aFUncUsOBU0zYYzo1998msGQX9/UR4g9KFEqJMoh35lDiRaYGMtjqjVl0eluUcqA1Vh6yLxCZx7/6KLHjEaxzfrxrb1/fLDYoovdY7a5jEezSZOV/PCV+dYzeWMoNvjFYDhzU0omA3nM2We4Y7MOcsXCOPFdjmF6cXpaJ1jHato1+zgxF8MxfrSJo7O3RrWjkfM0Qdt34k+vhg2utbXm4Z8azQkHeq2t1Wk3NxtYVp/L2kazEdn40bXJu/FEwu0ajEzs39F6jyU6Nh4bWDugfTwP5nBNTyxlMoie2ho59Z+g7V+14QXuCOaNx6Z+7eURMOsNirQP/SxiMpoXtnJ2XWS9WqiLOiDJ6JwnOObZsY8d78FlwZphn7Ja36klNt85zzkDR49DtfCDRz/Gnfg8w+Xj1/M8t8FJCBKziLlJr5656T0KwHRsDe/a33nHQJ3ZqSDz1b9Y9vh36I/hf3EWaFGFD1m5y9Mb7+TJc7zP65DTiCroUz469nv6xfH6mefSb/m/yLg55qPriAXn701PfKshPRySs3BwLAzKtjf6TDqHn3ezeef81/ccB197xk8YI/nkiK/x6I4NLUOthfUz3pV6kwPb9+iBh9jzTnocHAVwvnM/wawZ9HLnN2kIxCcu2vhhgOcPIf4AmkCPgjgynHWeWz1HVUQAhXScczdLNK2HvWqyocW1r7V86FkPbOomauyNgfWOE3KMw3HWL2NZy9Ctr7/Shd2Y0UxvYn9omvT0BF91b29331NmdJgSrucYDDcuYrZnQrOZrrM0h5NRsprai/Ws1nLRr3xxuDI2gmnmOI4tmXQPmDhCMlYT7g/trkF0LFspJzo77S4nv7lbz/KdHFzvJDfrI5y1Kcp5eotVWPHaeWwJvhHnuCa8/czE2iEtx6mgKRS9x3SxuGB1nyTV8dmnXjc+eogJtpcgS65xbEMY1uNtAuuwF2YNDgRcrEf/xrRaMBkfvmrRP3Zr2PmpI3GZE9veyzRzBUF815sYmynrO9cyJqRfmcxcxsmx1d5jiTc9Hb49H4xJrsWvRkmhnjo2h9oJWvsQsGxdIxwd6IpjS3ljsaldb2c3N3qa+7O0u3qPkVbr3jqmZ2rrRr5g6F97cLkaRcz05+HaPpkvIUZZUCuoUsT2fH11tXDBjatBLKr2svn0BWPgV1ljMWvNEos5ZmYt2ou93R6e0SXDaszeHxzMsaFq6cLs+XLqjP2JEZQY8p/zMMS9zAnQg82ZYLYRUOZYxn6SNksfgARUOsX3RMKWAR+CnfbAgi3mM2ZFkenlsUlwlWWVlBtbwS1elNnO2nziwpyvXBplBQaKsPvtUn/t+AAIGvvltdHhECMpN9VZ+8tvCvLjg9TJg1D82wf6nXFOnqz5XUqvJ3Kh5F/W5SrDP17EJUcHF5b77gX3/rLAlRzk8eJtuIvTNdHN2QvcZYyNcLiYMs9Vhz8IyLsS8saWSWBOGkjhYlNbgqxR1OCAUg+bCTNeO47gRieEsbjFduYbOL5DtGuw6GC4J0PW5hgBcZk3/kHWPSsj0AIF2Jl0ngW8GCcYN2P9m3+fDF7fxkyoPUINSuAp17NlGvAqFbOCnlrNbXy5ytQssj21wreM2380e17iob4Mfc4W3UW1hjVfB2s/qpK6lRj41oWhLzxTq/ghz06N7MdubjQBQQ7xTNUWjtHLcmMEqgm+7QOxfi3R0JUvxvLHujGeb+bZuCVlT0D2nbDI0Kj5az90AWfsfqaWlY37cZa5Wox5CIqr1a29SofjYLpje26PYvSozGO5mAXD+D/GSWRk+xuYHTNX4sHMMWg7yuUWN6I+hOV45IWaoS8Y//gbe25MeREP3rn7YjkW3/h94di4Af3x/YfnkX+kjMT52sbSA2/qePXKcy4xf+YPd5S351Irol8GEvwxXjNx1AmSm2j2++s+WFlPRTs5XM0NoHnkYgnn7pOM9X6PI2tnoIa/a3C8A+2npWKyV9lTs5+24kY6vWS+eo18izqM1VXm1OJyfljbILdw84Nhc/AiMeKo/vxKwArmJUmebPLF64elxG/dXfRY49k4M+HMt/HZRZDHiB7lH/n2mNnSQPcHKnB78WPa9hRuYsybV3f91BE776H72jQXjiQ1H/kdk3M1aCsfU3j5IsdGjEEec/JDhsf/8dwnCX4mGW1+1ltrXdU++Q6YgOZFQkfjmDOzT1s/69FrnypcNuL5XhnqSJwsxKMry5snroy9JlP24OQ+dVRh4+AoV+vBGlIOYgFHw3iO/h73wML7wZ91sVUuzeRe+4mxp+GIhlZm9mqymttz6lcj/FLP8Z1Y4dmQw5zZr0Zq1Jrd+WEwdcdaH7vt6askCL4mXr5oPvrrLPck3XP9FnRrg+wcn2YfWPOw6HEwLeomf/zqLU499FRdhdUfU5a3lq45Itr0hdJY6ihWKZkz3E29GiAMq7vxdx4k4GBZy5k9a7/JiR1btkKxxL82cRHx1kz4cjHnJ6D8ULBsUCVaDFQcs/LLlanxwDAzSJndyTmrqkYLnosgpPmnZlxg8sWx2x90yrdhCgXHQCm6COja2AfTnHG/NvElbF2NlyK45ZM7Rjsy8WjRTjpHe4qdb5t0OGT8tBlTsLllH87osu4QyXU0/1MrEeiUg3zyFsf87YuYfR5+6rBn9IKh/WXBuEzw959QPHVlVp8Z6RV5GPAhJ2P7d/TCG4K9L2g/C27vO99js/vyJV9yYGP8UEcWBCJqHaS9B0qU8U1QHFYGVEWwoKAx2jQWLQKk2EkuzqTxH+wjvqHDP7FjswGZi56czFfz1TNZTbY6YktMZTx1V1CfRKNLbvQxc3Hjbp9GUB5wHBH+e5c2mJvpXi3zrniM50E5EdmFW/r2f5/w/YgnF7Ph88KJeAcfQ4yG5OofgUvOyYE8fEM3FzVY9TQcDIAMavdYZk4cke0HWvquv2R4Jmj3h5GAEkFwcNurplKR/gGRaqk7d81pvmpnZqIeh30hWQx5mSepQT3uWkzTzVG6xO3GxGDc83mO9tFwji95gvd8IZ0pyQn31IGRF1t2W/zMt2cHb+7GBnLwvBhfaz1sW9+r84sNjIHNzvLOcMzK3fTsOWZF9LHQXhwLVOrjicbqhkPHsyFiB30CRmT3VbD+sw9u4xbnMUwfGGszr/ljnJg9HsWQh9my7eyp9fEWGazwxmzd5p9jDeeuwTZH9pPqI+MYDyb5GMsLdlWx3/Zrz+aca/E1ZvGThXMDDSyPPjCMzcosoPcFhPWMRVFTgPNCaXI5ob5JMtew+10YHQk8P+xzEpjxh3p71ppiH5w3mXne8qPuebecNTeXyGHvx5RZBvOd59LYvucmHQg3ot4khq51xMhIXt715WPa/qAwpt7MES/CzfZ3Zd7i4iYBqinH50FW9Ht/RxydpKLGIR0iq84cCvFBoKkXIezDgW3ilwF/zcPnqhu1htD+JJ41/eF957/pw9/fU3N+Fz03oebxOd8sIYBv50u6x2zd+KPNJedbVjln+H/hqZFef//F7/knLqCPurMuW7mIBYMNHPMdncZjrXAFg2ZJi5JbAc3D9GNA8tj6CbBJAjjcnIsncfiF84TF66JVtj6fn+M8P3xGNZrCY95XPCTqJAAJ9Kt5z37qOByD7zoxgROxN2SZnnzMTcGe5InlaW+58V2Ei27iWF4M9hZbIhvTHE+E0yof67Mgn7Un2OMSiP1AD/N9LplQdJJna169YomYWoDLPaoWf+LjV+9oob8OKIillzuWFnu+W//1H6yBxQCcl5HGhPVDK/xSxJo9sqtgldROMmD6ITQHARVX9GJi1EVERog76znmAsP0aCisdbMaBnAoWO/xZr+xdWe7JAnQTQAjueHEutysPsdGxCO+aXs+Mi/eFELDZE0PJyVPrI+vTRCb4lKrfnFYVucKbw7CylPV0izHq5veMSasWZY1/GiZnMBkG31G5nyunvKceYjO4/CtW1j5JyKcaIWcPpjEY8S0wpqD1faeeccIx5PgrdnjdIgH+tRhwgaYYrWSQREKyhRMRl8XOj89iM9zCP/0yVIDe3WsQonYkCJGSx5Nb48HMv6swo0c8i4OJasDfIt35tQZmmoaWV25ndqr7cFNTPtR3uVQBHwGNXKqqFHOcWuBl+jLn0XDx0bI4cWZcWs8mWMlX9alA+ZoPNNid63+QhqZcLUE1o+4iwxi6jgFTxCOpkyE3U/4YIcq5hQ2PD3hngeDz5ZlOElW/WM27uT8ghzcwgu7HVg7ezSVK/s9u+JA4447Wwv74UsdzqyJCwBulovrzTPRyTB87qg9Ey6s/sz/r2tfYiM/fy23MnoSnF5NfJmDAZ9/pkLDrmcfV3zxCpioXJSQFxPbjT85gCVejHfiaId79sSRK/t9d74XMYYYe9IxyTd0d9AHLoyjg8HiBbjGrteNNGKq4Rgzwbw1bMSm6z5VCirhPhl9/LTZThDdfjjjydkLOhI0r9vVm8Uez0ZOLydXc8YzsWDOiG1pDk4No1ypzAd3A52NZ+oSFSTqr9aGSKTOYVZPjx4BiyeWsecDdg3anO2aPRfo2XvOZNn+w1DQbsnT+WgbiLnIndELUqdix7qCmsO4VU22uou96842dJmC9hhUnSxxjenz3IB3j58dSWzWpt+sHjj0xl6H/lqyjX/1rRIzw4NvEwMFSYrNML5VfvMOex0XDwc3NMdO5hnYFLju1Qs+xyW5zGtOZkPyqEff2ocqFmyMPVcyJe0CcJ0x0Qlg9tYuBKLE+vvHIx05i9PEOjBuOj/eIea/rshNIjfi3swHRez+F2urUbHR5trHND8QzU0lPTg3tOjr2BvtZsVG9vlOArT5Dn843ucHzhs0ypMNWs7AHpuHap5H6aND4P3hrA+s8YnIhpzoYr06l7u+cKeWj+/5gQHPs/SETxbwe+n8d2L5oFX0IBKWbIbULjEfTeYgdyaYp4t3Hw5/UMIfKaUfwcoLOkGuM69d08GgtZb6wZgoe/sYbmxrR8PqqBpWd5B386wfyv7wO/tI4n8Z6eOl+oj2B505Jr4eBW8+HOoTERBf2UQBWweEs36P5dExMINRHjiKjacu/Ah89j0mtW2+AQrD1hohGxw6nLOG/ajRjqXW7JkwMpEn2ObElu9ctExZsqjBmIfzi4byQLnkpKVPXb+RpL4j/uBUPXrqa11wMC4rq8HPrL7NhD/Dy5vJD0AtepoLxiHVHRfSm+3W4fUB+XDkeeMgJrYkGwVJESInJ7EL3/0bRzXbt9MzeEwKkkUF1p/5DGOLQKU8YITH7gwd09t336IguqrKh21q2rixqDOu4oZf+Jec2KYG2L/Wt0erUeM3ZSzZt+bRsPHUhS+aOFZHv/PnMREXDG65AE/MyRM7c/4VodunW9cQk+TLePUw32MTGseNZYlx+Ld/o9ljYwz+RJmO+cUv54cKC4bb7MNPcLOd4wpisdSxtayNhEQ/1wtgyAWkr2WzEFh+pgzPP4FXvy9lw8vODOZlFu7MtWVV9XcN50f+4OFbHD7rmccz8K2VOcMsJwf5rr1MqjjYRjw22iRPVRpuXkJW+WgWO5pwNzD7nlf+sCcx7egTX5GhyyTcaPT4Q+CcVPjYE0e+TJhjmwHvG7cuQ9wEHvLz53Y2eE+Kl2CDSaIgNlkUwzYrLpZiH+5YOq8t1oi+/omdIk9ThvPETjHEwttM7DuORnWtdXDRsvh2Z2Iq/ZKMLjDIcQTju9kassjFiv9lTR4MvgNUMaW1F8HzQOEelVhy54Ig10/V8GfanLXves87FavNk5Skw7P52bfqchSXnh6RzdMl/WTsQU/s1nIm488arNz6MiN35vsX6PkjRHtR9clZRYRBv1r6k3YKJwdjdSyw1gUQZ2pZHh/2XRbgml7h2T15TioC6Hd2PCGs3X69PcUfrBydbKYbr0XCD5/Vbg49ySJHs7klLDaOfcUQlWxAD29pGwU8VamxOTcW6g1pPJxr/Cdfq4p9iNmdY0NcvvrYe3q4mPE1YbendyFCS76c9EmfFV1EU/HsiynOosd1dmDhmuI8DjjtARMZmRSTwlfHhIow3nyLr9czRxGk2Tq3bmnN1QNSoBqS37rm+evNv3nlNnssGDO8OWdPPQt8juVVITqbBprZHjSox2Uo0JJ/W8v1YYNiE7nIOviYWg0cg0OS2PEBAKfWoKDJOHExfNSxjsI+t6P95dg5+RlwbX72fuf5sbSsuZnr8Pk0Yew9bjmJN5YfGFoV/79apry722OrWQI41c7KG3bqIg4Nm6c8QI42dXETnOc9LtjNzxO4qXz+DrhasocTlv7Ry8zm8YjE/rCTuOCgOg0BJ6WbozOr1pbJ4FcXofYkrxfc9PLpgJ9/5xMCf5eHG/MfP/7uJwfI18/AhUchzcN5Mf82p5qSyzW1k3gwEawd7fj55gb3J3+QFBSiiOEYxh4AyzBYsXaBg239ea2M/hObgPxNVXmx8+sMkkiEluZmWV1Ze1y6Jme+VN0NsK15dKAnMd6kzz7NHFiD9znyxpYfBaYmiQcVewY5+DJ8UGBiT6ZCtg/uhWtvrok5oq+fmV65rl0dmzuAzaMJMRlmjg76+3ExuVyB7bEWbQ3NZy+D2yFO0rDSL3PGEMxFZY1dQybZZ6vxoKYv6zt2cbuhmmWFAdT0Etr/oav1B3VylmvtW99mYH9qWj61NR/pb6xg61lVxpcEQYfLaPjGtlrlgnPrJ9YBlqgdkyG2KpnjgSDH7kkxPdF3NajdPM23uKMtE3Tsed7ehvyLZtZkW3WrCAv0DB9HQS0G35uvqJelumuXKdGNR5P94jkEfRGoL+Fl+MIdfUdICKu2zPY503MuYkakNZEvC0nZN/LUIC6bMYC1JooeLHvs8gwOPvNmr+7NaRyhJMTX0eu6Zx02VwPYepYT3867D3A0wUiYelbjrIEwNm9Xo1VHPUfzYF+udCDW3To99UBBCvGDa7LRC4B+RUjPDcBBH53tJSTWnFRKHuE7J3ZrqJrBwe+o9/SmLHJubmDqhJTH2OY0ns0w6x/jJj22PQ7oudqNjkYogFLzhmLcuTTxqWMwix9BBA8HRHp1HU7yzOgNuusm2Qe2/sSCNSkG5q26C0H4AW6qMU7idfTg7YOhAo9tBG+ZldxcYOCG7usThq4IRjMaekEG8ISov6sjtlhJayMfKRjW5412rP5ieDy8YDNi96OWvIjx2+w5CXIZdYLVGnYuqhjT0XD2o47+TtzT4P0o+baUC6DtgQQjDE2+Q8GaETng+kMRy9V8TtTg9hj7REECmkJg5q6yp19qwA4CG/t891LViKwby7bxmcGjAeMMzPlnDc7Xkb1YNs21Hvs9CyHM4c6uvSAP67WkbtYKjW0L/eDAXoM1eaIsG8RXw52NeY4PtTGtv1sUTCG9WNWAvnL2fE4Msepl/2RQN+syHZfxcMejq4bDhz3fN1LQCCYK/8Q4zyY1bmYeN/xby+4XIBuJbwIoe4HMBPvxLStaiQmbobHnoWC/ickwZ/zFxTCaVJNY60sYelYhca273KwzE8P8crgaUzU9D62jTcDqXOnRceqBnBETGpyMe8y1sZgxKPHnGC331AIPpnP+MZffSfM/0+3l9qo/DClMW7Ctvb0q//QWX8bJRc9ryTY6tl4w2Kl1bn6OJmJOYY32uNg7gjLGD92OZyovdvNlvzeh5IALe2NL5M0Unzbqg9l4MD9zA/fH33+fG7zv+cNlPP99z00dN47tRzk2/+VGgCpGRxHVlHm+uMnc51O4/NEAjxF02ATimZIjA93ZiWXCCHancgaLpfXFH+fWH7Ahu2kcN7DM8p0vuLWTK8/LHH9eR/7OzfnP9OInd7dB+BH0eQedXvxK/1Y2z+W+JpTJtOc8IkeOefuAErP5mFVzNr57HrLWzQ9sVxP4jISguW2Jzkxa9bjDYaXWEDBfwdNresPoH6Gbd77Piwy+yQUyS3jIw3PLPMFMXozgG+Mn3P05QnJT38/qNzYogqRgOlHGYodieNBnNdQQ3+ptUnwdzfpGwVtm4+UZMNxwdZeg4EaEMc6bj4i9qHeeuDMy5bgRo7bMK31iu5B6YzyGJM6wNvlYS2a8GgScai136AYD4BnwBCBnzBvZtQq1kmcr0GcfEtj04zWTNdGkkfusxx80s60d5uZtT+pEYzxvbyZOz9g5R8xVdOuNb7WyJ5eZtdezj5v1w3lH1fA6iwbr1Zk1Xz2JywlCkmjNfnmBt1r8AB7DqOs5QEzdfdxDwleNt0fBhAcMHlPLmgWdAAAgAElEQVQ+9ZQhnpNratjUYCcebM3N0dhsg1nuiwHMOY+veDHZqCGbtZenR7Pz69MaDsb2oxrKfeySI2XOBfidB2HfJy8Bax99crDJ2Bjy8rXrKYFQBxr4tm8YJ3+fS3Rkc/uidnAEDQfeVp0ZmjgGaBXHfnlOCIZhJfX019jFkiOssREOZXmaGhRDn/tqKCxWuEakMgCrC771BY08sUO2u4kv9uYx4MT0sVFxy3OPpylXA+kxmJBdcX2OxEMlmCV33k0UxGVseno4Diy12AQMRAAu6mMeWx87W/twrg79VPs5znryrYKmyjZfJ92JrhYwraecsM/P3xGxzkkq14rbffg5EGQw0Ta3NhpzcnqTO0XpwEVQIeT7OigGfmjAgdlc2DVvdVl3ejUIIMvocPfEzbQ6ZI8WLziajHytr+LJzZrLi1xlICZ7LpKSI3MuPPiIIRyM5uNqoReA3hjlvwHKl9lg1Zt3gmrxyqJ6YxEUkz1I3ndf99Sq0MLdsp5BDMO+rU3D2RzrYvqDgo2Lmzq7jKSSsz94XuQGZn5yJqbYngsgii8RulhnW8YAZGFD+LxwYtROPP/QAsQcTllkEvvkZb8x6NhcvjA2ffEmGv9YwC+fvw6xyIcT7kPjvLVg5Z8VhWefPNQi7Y3SpmwcITGSfSoxV+yCamv1meMbjXUXt8dZdPiAMLZfGweOfzvQquat2z1pWofnclOYGx2nRkk+45dZ3jyjXWw9yjqg7VGI1jYT4hjwEFMeTWMdxOoeXMFzDA4XBLdvb6/aJgosn3WHc+tvxhv7cX48/PKUxpDyMn37lRzRUeva29ZWeduwuNW9fOCuT/psphcyw9+u3Rrqr8b4AsFyziMcaxu9UPl4ATxjNe6amB1wqWtsqwjb0RuwN2jYmBOcOGIb33Ud8U7R3KD6dDtc/HeWf/z+l7zclPINFn0yiyNXbwR5BzoLso3GcrfszPUnNjpy++uno/gfLVYbcerrT5yUpfaxr9/+hPR+2qgZFNeigGY0Gk7eredd+2KiN9pFsNs+Ze4759yg//XXH3/9/Zdr8nzL7+X/+PHXH//617/++JnfRUeDryb0JHl+eYMqZTfJOSl87WpeXCTE1x8e8wjCJl/uen/nh9O/9qIRD69xgWyFkIbaHvYHvSzmOLPnOzHenPv6mDWPOf7+AB+hT97f6cPv9GP7SDyDHIxZnpxdD4bkYla5y7tpeXIna/ch6HHdOgKSrpzgGMUPFTGrgJRAChsAuxjs88ZfV5/bdx3miTUXp6ick8OGzjzAk0b67Qqp0rf0tHD28QUD/qLIGVz+6c+K3Os/PT/2eHBaL1zV0f1dt4CX5dWJArA3z/FO7j3fLyqOaQqaxLtWTGE9tQOrJnK05iEl53AcHxNGejzt6Tpb9HUkGxRtpPvNcXRHxto2yqAsjl5m0zu47Y6G0TXGtS/f7qtIgqstMavBrsAxo8gvUfHvcV5/n8rPqhqH4+ZeUs+I+zhf/XHLM2vm6Lqsu65FmXMsbn8gIU828zziKpzoqGfOU9f3vF0/mCLveWkg1rkRV9fclIEl5VR1euOxK5G+1tJ8GwOmcquPvoKAbWsn91o6ScTUYlYJME2v3Ne4muDYY3b44KDX7J2OBhWRcTjneFRoQnARkwHne3yxmgcNw60G5MS5NhchXGq44s235C1T//C3HK8b6MuOrfljPaSr82gKSC3RJsOU3h7BMLxLT20+92WPb2purrF1ofS6e860Thgbt5X1/G7Q9g3MlDc54M6gh3hW7+Q6XPh0b3yF49eRZFg+8LHUlhzyozGY1Jp30ElX9zqhYgDA5lxMbSuuScuAzfXeaJUymSqlWDK1wG1ApZlsVJmum2kCCo3nII9NgNLYVGO1NhN+1vnyhONC4d6Ihs8n/WgZeHe9gCJGh5Pcbgf7i4CcGN++5wILXnIiJzYuC9UVuycBXurOF3kZ9rKzLKoFf29MdaiXmbrDW/1mijXgyenOXohmI78fE92ComUvHIkMGWGOQoZPa/qRZSAZtbcO1j1ezBxx49s02PqHmbCzwlcOYzMnc6zHzvz6EjHnzImTBy40tc+GaMgm/q1G6IgRG7zsLSbzZiPUAR2axEkULiinTkwTazsm7OuuNRF3uZbHuGy2zhMLt08u6L868MuXc2Z7lWCEAHr2xRk88SUCEv1PXfKDkTubM770Z3L05uyAhrbRl/cz/7KDYpxcTlpL7T1a9gON6QFg47J2b8+d2YMSxqedajr22MxqWpS4qYM9LIZNozyvYpBl+xnM2gdM1ESUoH6saC1vph2n1/UD4jxefR7Hg2kvWl3rNhMxYSt/aZnXMDVlaRy6dRUNY8+NxzoYXYuWsFB5J6P6rOrWdTU1l6/6Pn8jCVztPR/m7iImbrZ2TDpb6s1Zk56+2FN0+p2dN5a+h11MyzOfh9Tnz99//DeLb3/35vz+0TiTT2rVIyZf6BklHvfMXVY/SP/xg9Pw89fL+ZRTb/yZN7zahmeyoB+/Xcv+nCN54d3+0DfnFJBhDDmyhvN7fsD7Bx/xzuiNKppRpCGPj35igI+2/513z//6Lzfpf/tuOhp//PjhDTofd/cTXcaNloiDB43kbS/QzByPWQSArCm2dVE733OsmTF8LcFmDWOLTuqRd2jt67x29ea8tZBnX4/QzXMAf5vF54K04r4zX+7KbL/kp6DVrg5WJLWKmdF11jn+1vCEgBibF2RE0hMZsmFkUc7MT7+cYoiT48ogitFsnc/2Iay3WHLWVb3yTE3Yyetz8M6zV9+8XsDe41f7PtfAg509+TZLJp2b3k1NZoID91Qbt7/Sl3iQ8HS2nIQCYs94+hAiqA5Xpq5HyngTQUxXZqW/8zpgRPCto4HFD9nk/eDSZhDZL7Myj1CpWcHaoj/n6t7juvvRalCCzXv0LdlhjSFqwb29GC5s8Ow5bI3YoIHCzhALphximXNdNKOvg3vuPH1czSGwZ3KWJ4ZhHxISREx7u/jkIM0bp5Yx6Oqx2+OzcPYEuzemK/nRo7Y4AEgXngGDsU4YwHKeLyw+YcQTMDzyseYLPuuBujjPJ67rAcTHv1mV//Tz5Z34yb4xxiXc/C7CmbHXSUcLRnKtRrTUlH1jKNrjpyz8w0Usgzqss8tuJxbe8VHN9sPSDh81xCdvZvDtmNzVF+NxoZkYBufCzDHEcdayxjj2xlfT1lyGOZ9YDGtZJqGaICkO1EcPm+BoJ5Z61GH907cYer8Awx3bI2XGbNbkZK2eyV9ejbWDLEjj5Zl6yD2jz8+Ln2PaqGynJz5fzxFO7Nuj5fnYh15pGlWdGTmjNI78kbgSg1IcwJ2jZZpDkNjYlqbJDcim/s1mXWZugY1pw+C5UVcMZXUVL5CGKtT5eUJH4tVtGkKkzcav7onr9SM31twYbz4UkCL/tBlWZVnzOO/PFuKHON++w5ppnyz5y7rhzDMFF3f+AIDrgtEMW1+A+l8H8ft8XJL5zntu9r/5LgLczU89DC9qZo5t7e9cYOH2SHg2YSKrNjY8H92PWRp19MGHVmL3dyhZ13aKyLog98wzihvM7mLUzT6Y8i4++8HlMlWONbDSYvCQrw1knZko1PoofbLYH7RZD3gGGhBAMPHc+CoIZ+z0XEchmAqsG599xMyQjwlA+tzRDPRxLFCPb3fFxK4eqXQZEZv71ctCjkt06th6hlioTwYxEH/s1a5/co4rmKKobTV/9A2q/Lu1R8fUtj2GC9PFaHENuzmmho3JssPJ5mZRPTi7uqzqG/36psbqJU4yQjNtXC94sgY71H3sLn+xOD0eifuaBzpG6xjerD/UQo6B7zzIzPFIamowHN86ug/+0a0t7saDJy85M2FuHidyZTZs8EIV5LhZNuzmxCQHLoAAMrD1vOq627qL37q92mlMMzovV+tqHzWrRQ0hNB3VdBJA8SXjB6Fw805qMBwPn9uTl3O6oGxRxke9Y+OmNTji+COc1mB/AmlAbOQl/lQ0NmqGae0uYDb4z7xbzHNg/weO1mwf8g62HxsneGMzZ8WNqVZ9MWCbOXtyuT/1J3cC0E+N35ITrSkrxvh4kcqO53+es+v75Q06N+l/5130v/76r5y8e/7vf//7j+/5f9H5GPqf+Rsn0pCfL94BD217gaF8OvUgFj3x0XdH98b4+pQY3+kfnri92TdmQhLODxOg3E8fEc+gRubsee1jnr8/3/rS118/+XWF2MP3O6+farGjCQ5vAtzDT8fJ3X7GnENkHrSAA8qOfNYHAVFw1w8/04LLR6ypNOPsMWMpDSYAGXDPNLbMyEu2wZQ7rjwfqK1Rbj0vTjw8mzXB6AIFj5v1kQL/WIWyIGcW4A20SnnKkfz5N6xKBdi+kGPzSdieyFNOphdbnrsmXHB1sEQL/NDNDZC9kq49A9HR2abbx4kZL8gc8GJaPdtDeEaBOus3pBrU10h1DHi5BmQP4SzvrVk4HK8eMmV9cikCTOtjyTAfE3g3nsAdiz8ms5VX33Am3uqNbdaG7LbHhSMJrizrIz08fBUHoNqKXDmsmqeWw5fYF1nmtRnx+LMeAPEM8p9elNotsCKWsU6eI5awHINUIL5XzcR0Zy699G/OvxW0UbJ95QoeO6P96upqb/StQwLQxrhJyLLUW47lxXtHEM+S6ZuXHsxh62NqF8HVR2fevrbv9ivUqprzBU2u3TTtTGEjcWXtgevqH9vK7db7lLIGl3hoXF/UXU+MjJsZG0ETOxroL2NR9dOLWnwcCRkEu43ZOjRNzaoiIMB8lX99zVXvPMZOLMTT3zf3+LNzWOP2LbjlxykDz/9zPrN2MGnqLuHPWgVvLdhwrS2IfMR9REH/kOxBPlpC3TwU29mkuPayK4IkL65i4uJBtKQi3w0CGrXPcHug1HMa0hgbMeHk28K2Dtj2d9L2BZ6f4u9Fkj/9n3h2zZX804r+tCwsuYjkj8TBq44cAF745YqFd9C/5SOS+3/xrg74xHANk4uQXJc4vHzK2wfmA1Oz/P4QIeu9sV4uIHTGOhGS+fZxjwYYzLrZRfP2TyNhE0qNjM99g4nB3vhgvJgG26CNIdnOd2+CLIpMfi5I0dF0h4M+mj8ee3oJRiMRxbBXdjbLPHTywt/RmM0nbxFHp5PA13djYZg8h+3hQ59pxjYYd9qrYXsEb9kKbHlT68Q2IovVv/uYmoXJ5J099R9mQCIrzaUhPU/UAmdirROqrMHtkwgMN3+n94WueCA9JyRg6VgtLDZ3ImwT+O3t6wMLotpcdI0jY49vdaq0tqnDnNQwpKuhy+mou9Pdwz8UtwckxGiG7jFZzLFjGK5NOkTmzPxExuALytTeWtZfjoOFlkgNU4w25vfxIio5FnHi0ZJFd/iz5ktKN/b4HoMyqEaSOUdkHo28uFDb+NsbRTVRxdQALgNWZl1hyTwLeDY3NnXmeVTk0c5zILjkrXA/Wg1ZP6aeqhLCc6ikcfDRb2xgyp9JBjZ6wLnLudVP9UyN8xwEEow3lZIYyufJM+mNYMnhK8/yNbL2UOQHBj0HPY8Hu/VqU1M5au+cWD4B4CCOm9XcfPopfm7S1dXXlt6s//Ij7v/973+tl9eu//zn396g/8gN+vdv/b187/HhtUg26OO1ZfszTWOXwWtbsjKjkdrQyQ2/fwMAT+ZbU8+bnidr2zonuLtseW7xHx9nz3cKzOtZegx/9PPa5g+is+cn4ay56U43jOvrbnnUMLVsXttENnRbz9UvB4CnJqCtvjh84PjqJwyGxt5ju35rfNa2c7g5VoZkzT9zjI85o3omb03ZDhY/LnRok0GeA9UdO5jRAYrAqTpzna7xWdtqzHq1gdvn/dUlVyIqY8Rkde3NQkqHvM0CcxtAzgyhibUpsbnGUw62ajOOgMV0XkO2AYpFrzVji+VLnRtlhq1XIdmID8KYiZ+APY/EYAtm+8Fy+3zme80KrkXI3+mcs8QRwMhkj6eY0a0W/Y28mOnZ1pD9do3QCDSfjwV99Zbl5rcGk9djqqyxd/Sc2dX2E5+2bHrMaim6ka1p5u6ICCKpvF4gJSBrXb5gAgDD2McSS/NpDYS8mZOvmHHsziRbxeTcng75cu6x3V7cPNOnAM2z3OzleJBTA8iOVYdOCY5e/FX29hkrWWacnEGG+5xftzFtG2uC5nW42KyVVraqbC2wW8uEnZpH/+ZZfVUPuOeXvS4J2+odTYcLx2hm+nVcXHuk/8Fv566GYWg59s5OqTkztbVHIFvvgLNav47RKm5yQkMh9kX2GLTBURWsy2OkWDEggMlLrs2fvfqkyHMocfUNYw27PSkheweEW0Ptxr96zIngjnzEvSRbEEINirm2hRa3Qlmhudge8KHS0Qd6UHbs1GxjxKFBkvJulmYlLIB0aA+Ie7kMMq8XcdBsQ3nBZ302ne8F2XJwcbB1uA/+NBpdrNjnm4sFLx55zYc56z4h5WIjPP4OXXBciPBRSS5GsoHkDCxKhIGaguHiiNx8qxc09PjFdY4u1nwJgUiNY2A+U/wus/GFGMM6g5EHRObnrxETgw6gd3O0Ad4eCVEzsw59iWtottHHfG/MiSeXg93KHpvYRtcVPy60VlUDGrq20tkK9IAObC/ySzfJcBRxgqyXVwUy5qv1gdvx9GP94351wQC3+QZH372oj4eQYUKhMCLWXgXXjq+jx9zY6BefTePKuXzu47CGrTV7tREwWe3S2lHFA9RGL2v3NSWeiZplavKsBxUG5qx2BNeQ+tRyTEffZvOAmazxa//kXF/zVEnmr6SjYXoWTh/ngAZHqfC2JjiXDwBzvhufiU/SRTTGUjRkA7/ojSLimU9N5Nrnm/fdII/D5D88c86ocUWzD0AMnCbhuI7O51jqG0iByIwBWwi6g6lzjHN4CoBV0CYEhyEju9ZP7tEze9yyEhxQn7tiPEDsoHA//Ydw9DkFMBzWF2M+Y3Riv3nD1X5i5PmbfDz/7zu43JD7uMvjmptA7/ykjQbwUw/PEUryeRqa+kamOZlTAs9h9LHfMcQKt+u8+3t9xYAwMsH4wFK3NrdxRGefDwGBz+Cd6hHgjWvmvkbkNaV/KC5/JC438v3hxJ9//L//+78//ptv3knn/4onF++m22P1oa3U9hd6OCcJ+DvHp7MB2da/dQdLr4IpLvPEQ5+Z9pPMJcekWH6wQsxq5yNk1PeLv0qfj+mL89i0pxxPcsOMJJKAwaYPA+5Rr061IQON3RsLbIa+zKWMk38kMBdGPXc3CnCIm8nA8A5iOKQAhPavyQtNBBMoeBzV2Pxo0aV3Z+TgKDGqd0rXlvjJBULmJ7d4I7uxT2hlaWgfS66FHAENmO3yrN5qHz1SDcOXcPptbcN949/YOL/ErU7CrjZJrFdePVUmZuouPlv6jy3fPu/O8dhrNlK+ejan8Th5HjEmC6715CcG6umhK3wYL5+8EtW+/do6b1/6+Nse9Vo5MYyQbp0ef7WUFDvDfUzmCzl7Y/aHXOjETwmLZ5/v1qM1MeXY4wxAjPUFPHi4F9Oc9RWQrXHtjc8VR1txN+e7Zj7ZKC9TWz2P9yLZ4swwx6v/mK3fjlI3ePnoQSZj81i4Lsf2cuvRT6C1blaJkvpyjWKTm5NZYZngzTDPMX7655zyeI2eE6b2FqoutIPJ+OhrTEd3MOQzG/MzGmsevXGMpGIBLn/2EwcDOW9c9eCeLObz5CFqOLd/7NvzdsN1Yne/PvhOD7pordYT2gqRCzc1gu98YscOZ/XGMBBxi4/ImseZ3cg+HjhqLQVt3x67v25hxIs8vUKTxonrwjzj2HljgyXJiSG2Z1S35eLV/TJjC9nEBJ6BP2Ob2UZ8nhD7QDDS4OeAr2qppsmh7IkHeORk6j2TluLI/J4se4DYr473Jl17Yhg9oavdglZHSa0NvdWRADTl4gastgnVnotFL+xyMVEaLg7JAh7huZykT7mg4p3y3/mPaVfr4Q+uF46EJIZrTPKTc8bGsCc9e/7x9Y7ighA3PQWff8rGHj0HB4GEOW4lllJsNtgWrz9c1V0eAGKPHTWIKt+pETPYITk3ql/0QwbfNT+rTCO/Yy6m8e44NU7uJWrKIImXebRPD8vRc619KeNIrZbk/ehD1kgxFt7RVQ1Y1/DsxXXdrlWNHMFrm9C3lneOMnDa6KeJsy8J7tiy4GtEUdOJKcLtVlAVY8qOsOVr7hEVn2kCaBXwYmSLFhZsyLaj69MgvUXpSez2fLnUO9qXhb3nzogTQ97FuYeh2jq7SjZ2ESqcWGwKztp5F7eSJROXBbjRLc9zLrLeeqbykk8uKPbibmswp/63nyLb2hBVf/c3rloAyRHF3ff8oBeHG72lRMCnhrVPP8uxRrCd455G2fbNihlI6270lKNtwjvvk+NgN2Z5qY95h73M2vPYdw7ITk29KSsqz6c+9+a4J6kfAScH99YZ3GT/4hNJse1fIgfnXJGbM8yrjbjMcZ+bdG74WYMZjRyTfsydTHODzk12nre9WWcPZp7HqQ28Lw3cfBpPNeFlbheJZ84vSeVfnB7vJGfN4EaWv9zOzW1rRtvvfMz9rz/+Lzfn//nPf7xB5ybd51lIiP6dTxhES1lIn4z6UhMI1hQ5Og6QNV9I5t/EWT/HJb9W0Dgw+8OJcsYBcf2Zg/M7feQH1/TTd9KT9Vs+rv8jP1TQzi/YBcsrIBhyIYLDqv6h50ZfFzmeY1PJBa22hBq7PxxgDS4qsk++8ZtreYnIvNDuD1C29RWBNvU924Zz/N7RnrSu2M1HLjBFMmXGd+eJcdacMce32OnRuDamfEtQKznpibFT2+LWTh79hKSvvqQM6epaFe6z0Z7zwRHepYanfFtZEBy0JbCGyTdG8Ay0yphlZ0waO5k+zo9BNx8CTq3wEcf+phavKTPd9Ys5BQxrXHg/+jdcaNFneGv32C4HiuLTBnmG+E5rHwOvoz0Oy3mRJ/fWlcR93Z0eP/23Xvwm245O4uxaVe2vrpHkDkwRz/FJbq8xIktuG/dGQR5PCt6sVgAYO6PNmDrHpj0blnMNs+cjLmsPY9GCpofRE97Fus+6fZkerh40D1ZONhnEdEL65a5t8ex9LXribwyze56XJfFDi9dp8sDPP7vjGi/+4jcftrfWxdRGwHT3GDCVH49VsEZ3vo3PmrG9aYL4jMOBsmrZPlZWeRd3+CcPEaqFn1zscwy3zjif0QzrMyMmBmFsWBfWifaYhv/UyTp46wOT9YYt5c0T6I5oBGs90xvmZXtSL372ajVn2duHzLENDxx6MX2JR+vxLy77tbF3mCOzMcBj7hi2nv43a4UPskL6E0c0HTqJFMOGA+M+/gfSk6QGtuKzRfJ9EW4qUeEnZt/93PilNn74LTtzNPkNJ75jy5zlaPbFfNblzQLR8XMRwIUVL+TvH9pRcOzAVL9CaBl/3IbYXKAQi57Vgu17/P6F3nze0IvIYDevNGVErhqsO5gzMq+P18tzmWIeHAevtsZNRKXyhPdlUMemYC7CJ/itEV6CqlVMNtS18/rBlAC4v+coxmC1gTij5i6Zo5/d2FEfBWNsFQMzL/5iMgkOxKn/H2swQwXOxdaQLCEyw6NX0Nitb5Mp6epSY+LqlrmJkiNmtkeXx7pGHOYkXvXB6ofJuF3DU82YP7H1wWXm0cGacZ6A9Q6pjrB4wesCkuYWwiZrzoFMWcFtf92zrmXrEbNAXaocThyNh0xeLaOPNNOT5Rt3AOE52oaHdf4ZMzmJuxfm9SOxfRstkiIu3+zCs9wfe1xiu2Vq7VmuPnPrWGRzcp4cX/xzZOU75xBxBQbcTpZq6goaeSOC2cfocRDxJVdDLC0R7De/+bK2Tvbz/c880+/1q7NxEB4+j5fRQQJGVYcY/a2HZynFvJjw8nx4goDkplWWEMlFPp4MvDsTkE040UTq8PE7yzv+P11noODGjSvbJE52//9zb2wnr84pgKTG+ziebhIoFAroHqlb0oz5pFJvzOHN4yswPtfNXwIn5hn0gfw8p8gXwh63VhH3GWjC500+MfFxA2quKrUv9Ngb8qT6Yz5W/o3/l31u1Pf/aPdF2LxIy//uESCFuwvQsiwOXYn1U1RY0wfi/DQAS15wUMPdCxutvUn/Ox9z/zt/MO7/zEFBf0W8N+epwTZmsz83pw/kBgyA21Z7oQVrBr3orNvrg+Mffh0A3oD6GBM/ENYE+q++9vGpITA/aZbaTEIe8IlTHxxNOvvmvj7BQczPlXk3gMgYhg9rj2t1wQxcxiduooAHwarsXo+4ktKMtuzRmC5YxsAS2PzLVHx1mBdgU5hrH79pW4XNfjBWOYH2iPDp1a7pzXuMW2dt+pKp3YK081tnTCiJyx67fPHT52AY8lH/aKjoy7n+5VqN4lIH9VZfyOCwaIzlN4m27WMtbMu5yom9o3k8Gsu4LEQOcHLMBchq1ImLuga9Ed03bo8FNw+rAtuvNU6eybq77SQd4Oed8WEb4NZyxGCnPxzn7E9OTi5PsPFPvHW9Gk2VKDiE3r7j2lp0shk8uVySA8nkdn4j0KIexbYevcQSnlDynrjYdt6QqSm85hu/nMQNDTrg9fmCRUZ5mE0idszDZV1omCE3WtYwNYnduIUnrqY1bBD76MSLCw4JszEXi2icLOo1YmLMiX/G6BO/xuHdZXmLtydmD8fhWiSaqnstRE0lHz5TkDsccvLCHLrlTJAE2QRzbPF34Ozc80Hwm7f1gZAz/u6Jzsy0r400G9N8fUwMZuzEIQ1ha1sVV185Qe0QsxxPbWgjDi7nBDRBQ6+x+eL7fNxCSdjzr3os6mCxyceeMbm66Hbzo5ExSDokd9ftRz5nZq4DpNSbvBS3EcJklCwPNJDtVofCL6deGgVVLrLOk4lx3bRVQc5NQxlHJu9qBOY4E1ajLd69mcXtRQ6KtkEYA+WCi3ctvKjI3pMzPnTZaC8gkcgVIyMIRQPiQguijOz4+KUx4TF3rje8MKPOXC6zrcQAACAASURBVLxVQ6pSA3Hlks5VLLOQB94MM4zuZitHtcaC1ny9D1Qao41unD6G+74rRO/bD/aL49qxutjf0d/dvPrsWdzETbPkk0vj6JaitQJWM4rGhG2n7Hex54Ph9GTqZz30gpn3OL3HlrqzztdiW+HFkuejLxgY2RHjcXBuBgJFlGdsZjGqgVCglR0b4kf7Rhyfk0/r6u2xT6aNdQ8XiB43uLsi6dfR2hUQl+dbZVXe8LlQM/FzLgzVqwyc6/Tg9NGIQc2FRVmynV4NVXOyGM1KScywjj0K0HL0MN/FHsfZV4xQhcEdjfYtIfJnI7+c5bEPQMFn7L6LoAPbY4CNKFGPDk21jr/ce75A2uMHyIUhRTV6j+E5xwOz9gTjY6w2V9lQi7zUmccsAO1fOTfXqx9PtZQN9uImgeQ3J/iThxlhT77mbI9sCQFnSJZVdSYxU9fOMzu1hZMXQOVm77QaPUYT1/wEVos9lsdQ++AZyc8Fj91850aRPxaXP6MW+mqRh7jkCkJd5plex9VZdDhHEroyzg0xv6qUvrvmuQf3YKiDF2Z5IZYbYfY87rvPDTdzvtHH88i3fIybtf3IR+LjUKsi4IQvfkfWP7cA9dx3z+u/z03fv//47e+/eRedj7hXw56XvGjAX0lnvd9vP+jL/hgbE/InranYGJs95RPDur3K3hcy0uMJ9Dl156mDL18gYc4F4LzYQB/543B9fqSt6UlehPE85yVzOBDneTHLxBwVw42bSH+WCOHnxKDkEj8h7Mgfm/IC80Wb5Gia1EWoitlTqTtMrhKNpYhOXe8GPGZ7Mf6FvX2n9mq82dZyjgfZY0QFec29ZJNQfdQza/EpzrpTzOqYw1FcwK2zQRvb/DfbxhoUJ/nFelyqxyk06lp/1603rjkGdjMEroOHX774zV3yilrOwVfL4BLV2e2NB3R4JEic7JO7pDeOdbNbWFYWgKjO0WasohBNSEb95O9117Lgv/2Wj/OKiBNLfIf64yRarnVkf/r+8CkL3+SX2Bh6Hk3hKk/mA26fVxNKMqJlZleXJUYHOnFCIbj45dNm8KgOHhvfmN/jbJY46NGZX9Y44px8Ug5PdiXbNZjEkWMdpwcvf2CLAjwKJ471Rmdesik1+vKY0HuN5jJVNgOTaxfU+J6LkLC2RsKJs7bOu22fmIPTr2PiCrp5hifABOyi+onlfDJf4qx5IcLJVd7VQR1vXuud4mbnsRMfQzmHdPKz2vNY/3BmF3y+R6s48hMHF3rBPpqpa8+VTOIXEY2EMDfUgmtbzDgwPlNzwE9ORoOGqcu193EeWzgXrobiDF0eauKbIWbmqnySMM33au98bBNP5Ad31h94cOY91uCHeLDUd/6KO4sXWmmxheg0wkASQ8QYPyc8Tw6a2M8Jo8VKWriCKtSGKZK1pViRduI2RebV8uYldZCDYdcnaQSEjVfo2WOnrjlKmtEsLB/Ty8UMIE82I3DEvxdNBQafr+mD+2Dg5dv/Bz217zpXpNyt5wIte/6tSPjD58cf4f2ofXDkqARzhpUV2ZrfPiuq6/hmJUpOAxq3N9tI2Lkaph6gb13VV0aImX30pgbrIvZkx07KEOx0tcN5R+rLRZnvptEzg8ZbyS7ONMH0D9bFbj/VFZ/2BPQQK+JX7KNqubaulbD8+FfzsVnUUXXKqYbVf3PfHuBD3PTR6RzLOS9WvyzWygwVO2795Dv1x21vVqxJCE3kcO9+lwtZZpLgM5uit2IQiLUbmVUDtljV5j65fBAfDT1Wh72TKUQN2eyLcLu/aIS89SVwYvtE0XVz4BgtpzgVWz4/estVJHBqYIcT6vJtjyZa1tNnewl6c3V+uPXHN9wVvGsyJBe+3LCZ59X11KqklZMYtQULfQc8Mzu5agKyNWF5uYzYOHljmbxqAyBB9vDiEzfH4WAP+tE0sVRpUrPDmDHFMDv5ST0vaGLPnHH0st6wzLtkH/68U+5NIY8ZPLQz4JU7n1riXd0ZmMiZ2+zz1975taPmjiP/mru6ya9+953zB81+8NHyPN7ujfvWSCzvoHsjzON8vvlvz+5N+vhyk0wsvjjzki439XS3Q55MWa8eOkKe+82L043g8Xv/X3L0/d//9d1z8vLd40hstITDd9JjtI/RCI95kgR+zjFvVtmTg94DnsGLFGrMU2T+iP7xqS0+v2jejH2hAf8OsUHClaTeVOt/8njxmP+61EHoHOOF6JGy8axPhj0fJid2+LwWcCErpWmjHr7m3+Nsfat99wUIPzk3nnpIoT74s4a/1rWP2gCLzRYNrDs1BZzGXTJ5iWFopiEaGrgaiRQz7vt4HA+a4lysuAFf2yoGuCl6flRk49Uwsdj5Kjf6Bq8VELZ4BXRuhHqwtweBZ9z8xtAYzey1ZB/+p35o0eAeu+tuGkUE0eWC5SNLQuzN4cQgi7jlbf+WA8jkRNeJNVFbRaCJ46dHzuvHbjUPRmwDcJZDisnZ3SLiyZh69/ipyTyqri5hXUNarbcD8pz+bekrLGt+9n3OgijfU4ipT1GjEXe+zBbfSP6o9fS6iYu1f1fbHqOqtiCZCXn5WRfDjJEVmsJnfzGNiK7rw9w6WBcDbKbZV/vRwQXlxxgP6fJlT8ff82TBk3yYwXmsJtnJN/XPhWu1mbNKwL3HbXW1F3pNeGrc9Jtg15TLsczY41C9seGrh2Q9Z7MmL49RBVQ/efh6bcSXYPsRw54rRWbbiX3gsTkUt9ewmag0k7eWctq7UEzm0pnD6RyHjcA2fPTXkQxf8YHYRzAf88YS1lNKp4zLhuOirq7jb9Jniye1uO1eZxoBj73opJjM92ePmD/PCUSULJN+xMOyJwqQd4i0EutMOATMl4NVbGD4niWmxW7k7rH7yvrmTwyRSmO/VPqn+VIzJw3Zm7PmPLHjgCAbb1RpDhoAjN2DGE51AcfOfk5uo313PUYfvLLnZjNEXIjRIy9quAhTSC4S488lXNfmId0QqylzhJiI+Z6UfYFBc/DVhiYPZ/eDJdbcaEUkQ/HdkWZvzussvrBG4PcYGzp6CjAEy/rVav26TJUUJj/5WaMnBvKvMNRjpB59uMCANzh2J1paNz5qdM92jnOjxPdCszzkuNjGYkAH3HN2jIbhk7sb/Zwfy79FrO7BtobGw4zibqsDmD2zFDSvLrRkfvjCgT6eFKEbO/EjAXfHyxFLjwmFJbP1xWi+6r85apYnWC/iDLjHHU2M7RHz7QHziphYlqNTzo09NlhGQ3wwH62mycYfwDhcF2sRN1VmcQ83wLJSa/uXdGcOD1oOfuO0N4ZU5+cZv8e5cWxVinlywclQ+7FPThyTw7zisC0fgHKuHyePF3yJswBgkvehoGFPHeTHyP7WUYs0sHUIbG9WOw7zk2Im5h97a7g6iTsf76XPZY6xhXmDLA+5q7u+sKqPgNifwWq171668HA8zDFF4sfAvh40RF9uQjm2VRSAKZoHrtyl60dLHz1hDX5x8jZuWfDJSUy++RncG3I/ip2bdP6iOTZw7BlqCx83pXxzg3xv0jNn/Vdv2onxj7mRLH/IzRtntFhkdqOB5Sx83ui7y9h4/OaFZGpJ/sSuFv6yO7nwbx3/sY7YtIc0eH4333TM55seMOx3J5m318aQh7gE8tV/ff78ETv5oAhMJrDLiUE/vKtbpsl3/OUVNholw5CEPm8zC2yHv8dP7ozZNURTzw6nE8NueYzJxh+3m/okME9IrbcpKNvBHhM1et2gZ0Cxcx5Ts7iY+/CGv5H0Wf+EtO8bT8BwTx6P07pjs4/DdgpfbHKoa3JVR5W/FNYFMsadQ73aFIFhBxQe4B5ZGbc/cZnzqbusxcp1klcLtHtekH+R2LMg/A7zskRse8fqhbA6PR/f+uVH6xjcsQmdujN3DyPzqQtVH1m+1i+FJAmb/MHwRWj3TPS6X40JPfU7T4D41076jLBdfVqK3f5pOpvbhzV94PKzRRnNlartCxk6+gJ4jwYYsKcNwVbNgHXBl5zzM7tMIsfeHtPNYuUbWplWQ4Ja8nCaz7bF8WgRZRETHvxowdCfyWUivj05vhG5GqFb3WAoui9uZS4oOzTm6/YrEY9u485m2NhNDbqGQ4HJwRjkpOF4aK49Th+fMI1DStCvrucafMJLQphAwuuhBrg2L72R2x5R+tQYhBJNNf017igox/AuYbO0V9r027lVgijHaz2C1dy+EKo+AibmRmK6xs86bn0yGR5bCur5Dct2oIxNUd3nGI/2PV7bQ2I9l5eFRm2O4dXfiywTVN9mbQ/b4OanF5aTA15lsXjwqRFL/ps1oG1IJlO74BFqQ459RYIYkp1ClNEiarzFDdqigpB78y5nghO2FwWrZfk2pll58u5H30tFvsR69egEcp6ZSwNvAsnENRb/By1XceOdC9IeSPIQmmdcKDtiaAaWNLF8/jG4zEFuHL1EI+/4/PGv//M5EQR2WEAw5Imlx3MQ8gJg7D5TgIKzU0sW/OOHNBO4+OglY2vqqnisexHHu9eFgmgOOTcg1l40U0dPXng7FJ+wZvH38MeE/yjOhBy6Zs/CWj+ZXJnaACI2mPmvA6sXQ/PkQO325oE28sbLzzIHqg/k029sycsP8KLB7spjGZ/oBeiflLGZPkGN+9xbM/E2POCp0bW8zYUmbUuCrHyDt76jTuPRZ69AImJGj9nEL298rbs4tvInbueryfjJS92ep0fXorPPPznA5KvxsU2NyPklDCNj64KOMcA39jRW9wBWLzkQsBqsH1vzV/P0TugCG1bh5Zgz4Wp4nvjA8XhUZulJaY2bA53aBNfX41G7UcE0D7adh1t7eTeJubBb4+YkQ7gH33z1sdV7Nw9vj43IEMNdpkdbbFsfelh43LNn/WrEHcNE4Ms041Z0MxxWTQXC219Hihe7mdjveudBBlBIH4etJA8g3Gzh+Z0/zBk4Gvgr77y7rF4pqq1Z2Q5XDa589sia5ww4Gtt6d+1NexbcZPf/8u6NOlgGj6noZO876Nn3L6t/++2vH3/mJv2v3/7k3X3w//mrMXlK8AXTOb5hjx4F2BvW/+bFhgQVD3++/yVH9vsiAe+ic4Pu437s9mp4yPuN5x9u0vGps4x+gosjhh2+ZGHP8DlC3z5HoCE+/NQgjLh0Pn+Mjh7W7NEZP3moJ6HTp+UnR+dzfo/fcyw5tq+bD4p9jiE168mU2XI5zWZyPktsxOxg5Qtk/IxLWMb6ibfAo6MrvM1qiODO1u8+tVw/EasU+1PbaML78gZS3Cq2N5PX/uOfHmS9z1n2c/p4AGosmNA72g/0DFPV7HGIVV/ceyx2fzkE/Q//dHq0ndpGwD7v7qc2mv+yUofHpwrkV2Vo8azipwsGG7f119KasjVI29bNolxjDiY+oOTP5PRmwmsbKmqJ/WjP0rpiW+3NVDtQdC/nYjTKU8DbYzFvni189CWiP0PWPM7FxPehdxPBB8aRCbErDht+djYik9UmBjzeKMuePonLgvl4rJGV+TdEL8Z862SXSYF6t18sqn39ZhTfvgkXw2x56D/02zefr30Ox9pUIuZn+x5n3dnM+SC858B69rjt2gYQQe0W0bz1hyD9WF81U+jF9Geglu05ae0jzf1fAzP1cB0iXXJ4zk7/j5bG74smUO3xaf8TDCT4zYQe65CjOv20MT0h2djhMnnWRIBUymwbCShDTPaFadrY6ic2zhL483OOHbGxb+/ePVbG0sLRc+32XMzorlLI4Jw9zKbYowdf4vOlJb7G1Q54/QcTDczrU5JrdPE93sYZjy0e/nEOkiCjfJmoDcvqKKSS+Yj7iNAcqwVsQUOqoCUdX/OkALRKT5KOxbNqK4q4Pzw6kqss4MwLU3JuEVvUwQ28/BQ7eAmotfqJIxfwkyIL+gM9Fzl+jD0XZ9xE+5H4XMTMYWoMPxD8YDAgiT8T/21T+4Y6vlTpAwCXO4Vhy2VOQuOf4Xwoq5WMGdngKzSLwTQZy37tO8XarbXxvYjJnLhN5yKxcpWQnKz94VMTi/ITaL2JJ5trMEwZ8BI89WxOAdokMpbOC8+Kuqw1J8rWXD4Sxe8i00x2zoMRedEhF0tS50ttALM2AFydohs1WPiT/2hAiyj2DEl31rXbKiGuowlPjEqIpqbmEidsu8fi+qu7fOoxAMb2ir7aH2Jkzj7wIgS7sQcmbZwdnDUAY9GdQMyhM8Py+OQqEEvG1oi0BKxfbzYnDuzJM7GuB/Pw1Hu35wmFdNS3T5auuzEPPXgzDqcx2smFUMVutLo+e0pZYLqH+6hpImMuTTIELiaTZWfyHhPylmexVWKi5R2FHzhtExtOf46nd8T2/G3e5u55K+Wj/fahWGPDfc6BClZUsdW59bDvKLO9HqGcazxm0Te/AcYm+/TS2Oi219mTV+5wALmqgsTGz/EMj8fyGbWe7OmFu+zhzbePLxqlCj/29DCPw70xR2dsPPbmf83IRg42yuXGGxEZ0JufaqhRXfiq2HqpO3brkMDQZ9NaFotj/9sz9j/y18m5wWXPu+k/fuQmPb8r/lduzHl+4Yb6r//857e/8sXvXVuywtCZb/76OnqCZdADPkb/82fqzY022X3eMrA1epOev+re5zK0t4Y/89+YkXc//r4vJJD0/Cqac/LwvMcnwJIrGrxJnz06eAGDlLxzXR9/vA9sXvRFr8raSX6u7VI27TcMyZFvYvcbXVGyB0YEPNoIgMWky978Ib0oNLEe6EQZXRFMyRxeuJgB5uR5BzLyhYsH3JTLJDFwD796iI9nuEpRfrViCKB1JY688M7XICHwcV04mKy3V41BMaOaxS3veBYv5/hEV2CFDrfxy0huDAyToLFjlqc/H/ZAnsjhb9ytcRRLtNFApxr61mkCM3E9vrBTe8fahv9QrYKJhQVulhPJbnu4JtjosZjRsjaDn8rA3Phqqu2trceMY03+Mr/7srLVp8QnBsEIyLfn0nA072RTp4qDA8wOvjuwnq6tb3v60etBlUaC1awUdWAOO3Ez0MPgeYEZMTDVfHtDWG2LIgqqYFYXhqkD8E73WmPxdWzCZsSmquVj7/Vh81VZ5+Y7JSQ+c2zlRwPfXRNnz4cXZ88TgwaXefzobC2QV8/mwgKmfhaMzdEuNuqxK0ygOdFEBIrYmlN41mCx5nnrDM1PTl2DO7BOji6oM8wweq/OsR+Ek2dD/UhJzvS+9wkYEhdH+3bIJcPO4Cje+tCEne/qZ/qeK3pGX9HlHwFyJThhIFlyPIJ8qWM/sc4wxDJarYF1k+f4Zq67nHHIj65JMyyqwz2j55jaYtnoMqPr6wjiqU1Ngaj/QGc1ZL6DTrHb/BW65PpOqkQRmCTrZ33m8EwiYcwx0ACm47S5H3GcmlpvwwmDZA60fFMcpHLxZJsn1Ea+mb/YwkE8WPWoKbbo8h2JXJz8ASYnH7+7yIUEuK3ynIA1wuTFbOsKsxeD913qPWkLm48fZmHa3SefJwAgKPLlMfCCaH4QpmE92R88HJbbPjSfNPcHefoGPdhyX46hxp1x7Yoc7vq6BV8dWWdhPw9JO4Wfr4konri1PZqWg8hGRUMCy5sUkGTDEwT7Zd1adU/+owtjkHCqKEHuD7GA2TRv+zIm9JFTlok181jaBHvZ87JgNYJTT/e1NQfs1EiuF2stZosfR/Lvcaqi2GZcTcDaq/U1dRCx2+vKGhyRceWbXuhnPRzLC0IJ4gYPX8spAxIzEwsXHPakPbN+MaDQeHvcsIt3Pf2cbEFnZGNOAeVlrV3OAY0SHFsLnjMPN/OO0ZEYuU9eA2TyPDmcsZ/41TxcxsJazs4QPbozte5TxMVZRqGCM23GYJnvsd9jBFMR2fNvH0dJyliNIfaGAlMLNOzyLEv5tKN3D7hk2fDkC8QaQeUL0YyxYWivHttMeTxcTs+LcN1jAIh19lOXuVhmiJc57DjyfV4EzJK5N6h0jMfraPeFDrjyjwG1j+E8HpsIpdUEJ9/4O9g3UOwptP7Fg5WFWGpPbp5I+jvatz586PM7N+z//MzfX42NL5TxzMI+NPkdcd7dpga44oeXfXy8u+53gDwPfcu3nwzLJwbgw7b/9VqW+W/X/jZ+c+P773//Gx25Sc876T/nL86bL7G+m56s22PfQ08ub9ynRnLAZ+W0qNIIMj+fLICvNac29QeXMXD50Ucebsj5FQRecOCbCzw/RRAAmPYg2L0Ija19ozQB8oIk4FjwhR/D4tQ6dbzHkHqAoq8BLDiyG9s6dGvrrHjiwJO52d/t5QAXj5qKgKX+7Kkv5lPB6Gymr9tFjV0SuJhkQJX6Z9X6xXCO4QRUjqny4G3pBkoFPnHRZx+3BHyHC74yEno4k6NUl3CVYzldCP+btxfJMNKxg3IG99rI3zrBYM9W+K95EXJUkCyxajBxfWN+hYlDyQ7pk+nVb94AmroI8Ohszirevry+2rA8+gwKz9SHzzpZD+et/c2QkKmH2Da1urDbu1MvcbGBY2ivrUrw1TWNmgXeOIS2VjVNPiynJkowanSvpobFucdvYqCNDtzLw8rzbrIfbtaHr7URtD9Htx648A+nubNxD0U8M2en3gXbMxJ19FwbnjVSLRQ8dxCXRcMfTZPj5mqNS3HsBsITjtF0+NCyNitKtMdsNEs23VE3ZEAa5Cq8PY90oVymIrPKpH4mxbR3WQOKbXu5DKcS8AcDtgTLZ5zxj17wqBBapu2FlcRv3OoGvmN7RB6EZzQjSwK7klXIa1sSMGsvh1RO77m5xEXMuRR+1uo0d7iwbWyC9poM457XG9Fq0UHcWllnqL/T3TbP7RHr+9+sQTAP0M1/xW+iFYrIwM9oUSx7MnSmpkc03ti8CCy315s0+RJM44mN3SRx8m+XWbRBcdusCQ5Aqjhr78UPNgkmz8agwxyB9QeP+CZhn8sn+RSxCWGauQ+SzhOTCxrAxgfzR/7ojZykzkAh30h591k2JkZ7q0Z6mLVP5io054ljMmOe73uxAzMXflM/vV0ommGC857Yt4+tKVmpJxo2Djk75JOnWuULcmtWqfFETCBE0ja/fNg2ge4AgMfW8hc7HHHt2DqqgDC0XjLmRDVy42PNVH1LJGZQT5HLj6c9IQBh7LMbrMeedb7uq28iqmY5kTax8mVezWCbA058fQC7OYoQJedb61ZMu2na1XF5Gk/yHs/O7ly/xwvb9DxGudHUWbRNAa47b/5yedDIEle7PxwmmNilGE525pza7YGNCgNEjGDKmSkJ3xgBA5r6jikTGeAmaAazI8NJay615FtKj/3okGHnCoFnag/n5tAmuP5NXezN1QgEFFxPtZ1Wj2as5Q9LQuwZtjluC3MJYyb279S+FTfXapkyTh2rxsfjZIHD39vd8HDzzq55N+nuR4sc5o+OeR5ZCPujLVm/jmkbBd7HqDH2cfBGcIP5Lx8bBzuF0Jt+5y+hz02yERgHw03n777Lni6OrV2/3Pabm+b5o3LguCHnj7t9+51fV8p95ty4coMJjX8AzZq6BmP/gvvpu+q/59303pD+jIaf3KBaW7Txq1Y7z57Hbur1xjy/r/4tdYLnU17k4Wadj9qr6fe8CBCbH8PPTXr/z/QfvoP/PXn/+/0//Yh93s3/M1z9w3b8bnr47AV6mwvNvgufvX/0lFy8yx1NtJBxfi4juD2J0XNC92w4TznLWtfy+9yRur5RU/JTB8Pj8Bwjf90Ae5vSPf0JnZwEZZw4FuSLUGQWOoKzgAcsmjheeMqDR1LXSjA+1j5ZZJUR4eLJkW/PxZirbx4Dhh/4SPWxvBisDMSQb7RpiW3WGwcSk31n8Qzz42AAApcv9GHVtVri30zlHvyEK8eoRd3HFCHwwAvpQmbyUZd+eoMAdDTb7pEqBxPHYqq3OQhtnDSDY6c15Dfniml9+AHZG+a6Y9Bx7SxxyZ/zoLjWRywFbI4JDbpRG3vteLJ6HVDka2vdawIhNic+kme4nPCuHx2xy4Nj+D96iX0cuNU9x8iOMM9orj03JNXezQixCfHhnh4siJzyBcq8rMXdtQhD9mdMnL0gbvOU4yFpzBisd84jT2Lj6ddkZffU2Bxs4c8+/5B/ew99tYl1WWwrGV+CWN/8hIE7zHJvGV9//mSMrp57I0IxUqjn+FYI++SomuLcTt4PfeveWNcSZLZ7jK2DvbzZyCPn6HvOeR7TKqPnnbQjqHq1nI39MQLTZ8++9qRB4W+Cy5HnE22xeJymBwsAjniVTWxrqAN5e2yYOjTO8YthWpiZbFhaJxacnkOpxjy6hV50I6F9dXQNG7MdExVT3ySo/cQOWh5cJ8mbf5mvf/u/tZPzzxObxSGENJXgWxr2Do3reYuKd8zsTkM0t5HY9JErE7kzOdzEzUIkGDrKDyuBOdAb2JODi6nYeBc9fp6EuWDZdzn2YEhJfIZzaDLjXQZuxL0YjZ/f8YMObi7EuJA5miULaPblcVvibCeFOfqA0QNyARN/DAR9sWUJj3Uzf1IAZeyDEUD9U2jflcDP91wEBc+BzmWhDiigfLn0xwBNPJM7vQi4tjj4F0Pje25gPHXqMbwbk8w0LxxIhoSYTBPiaiT7gM2XOaARSEZ7QVzFiD89MAUBTiTviiPMKPuTWeturGjzxviuzT0s4O86ASSJHjShZfW4BpzROTouDjqrdT99hKchT44x4IF/fwYMLreuwJSSxXlSO2zLcZVjAe+Yfg7BGKt32k+JDtcr8mREWtiQyOkmeOKHbXdUaN7U0XlVbI/alcEEuX2ccnUvx3YLJoaY0cFqj0UdAIqjC/g3Hv9pazAqCk9fRISZ8b/0wrJ9LFuZY4vjzOEKL1/tE1EAaoedgQ8cvtWA3R7EgOtidMhRKiN8bDx1ERwnjFszliJrNVfyQl5758uxZ0w1ZKVGWMKTY732rjUcW2sBF04em1FC2hkvF71gUKOPX4MZ8btyf3qQGOZjPJh/8ufGedzmD7wxtgM8ju/jOWG2+kTtBL585wDyGApKnQAAIABJREFUznZujc3BzSQeb8xzj74a4OCG8hsvxj6E6nr04etH3PvuOu9wc5O8Onp8ykv95Os7zbmZzQ3tn6nHF5MT0+c29G4zy/0jOfir8z/y0Xb/C7Z87P3/8u75f/ORen8PPjx//ZW5N+rcoM+NeurcFwTQ7Ufped7jHe8Mb+R5DqSGrO1QNj7X8ryZXlFHRzAjyx4QI2deUPHhnxt0/uI9LxY06D2HDO6J1USbcDi3x3BzLJojUM+x6mj+cKMrX+IQlxhzOWXOBEfHvqjtyny3Fm2JFx6fOkiRb3nYsAYIrsYvOdBHAP/Qdvfbq2agZ2YsHlz4apoa4OF7hnHBVPbFimBTh32SSx0YdbhdNqVnkUxl1zCJPnbN18e6oJk4Zn/yZrLa4t8eLBbt9rOGbqdPq0Ft0Hjttxztp7Hhb+9IkO8tYjhXGcuD0wfpgLLrcYltOKajoznA6ZvuoN+SocG+tXaOoRnxb6oeOhEAgohnajgaxrbHmZI24ug6lmqX7Kn95Tq5BZG0fbek5+Zpa4T6XG8EvsdIDWySB85T3dGns/bFTW03JoHPKGwUii1v9QcYV3Nhv/Pbm8Z6bq8/hYEl0P5aKAbGquYcyoofuKlHr9hymjjG7fntKUjCJvcAzYk9X/daTCApkm/PaqLvmGwx3Ly9LlnG4RzEJwuYVQjnneNpOfMzQn56/FEjvkRNLTDsmk4x7yb7kXf9OG/s/nzvzyp4sNoBSraTyeuyDjWcHEyMzrbGcRExY2rJCuQen9OB1HneTKNuvgJsrV0vU/dT7xi3HphPDWaZ2HB9RqyG2J9e2/PlzN7KEMKIrm19831WOR9xn0TxkXALzVQCeI7YYOrX6pwZSd5G0hjDce4gFjvi8zUSISS4+8GKm4sDTfBbVIAnEL6uj26E+KTtHUOePLhYI3Fy4mOV/fLXlifzuajLnwtOeP1cEH1LHO9U9OZXERBUQlKb348vhnia3lds6sPUrFsiWgaLHrjkWZsCWyvuaLE2cQEObEmbcju/Eop7se05/rA1SEFwo2HVscylWkzpATSu2zuWiyOC4ZHMwhpq6hbw0pKTJZzO6vL3G12HhSfgDPXJakA6ywXz5GcvqvFMYdQ4OcYShlcAmHxjyvc+eBpbErb6PB84ZcCebFmG32G65jQHz9TW9WBMkvXkvE/mwWaUqcfVHGiXhp4XI1AkDlZsJhLeGaaY2u0uOidEzWq7+IZ51IYtlnFPhc06OdZG3GVhhucJNE+sMbeEyTF6iO9JMudzYvcY7XHYHvdn0oDJ0rOmWpq386Mgk9XE9OH25sDss2lWiO0XE8iC86EkNCsZPWqBem9KRxFkZgxmnwSwMVbJ1kFGNQ0f6bZWwNVr6K+bOQ6Svt7p91c73OR3KOSsWovFjc0+DXTzZHkjrk7dkDMCUD+1Z7G11cl2gUB7LPrH4aqufaEn8DQfP+PvePvT48AP5TMekfBxM+YfDs3jyO6BcMO7N3TLSap9AbNaWo83q/w+O08dGeC9UU89PCb6m9NzE+mLuvOx80rJNv/gkN89cSYrob0IjJtunqPwsU2ALwanDv7vdP7A27c8H/Eu9s9vuWHmhjS6UEPM1tG8vDaTLvNue95V//7jux97J5ab9L/+zB+qy1+U/4836Pzhunx/S47cKIP5lrl1p64/fPGgv+/uwSFbuM0XjW+vnFtofzYDO7r2qFsiBfox+37UnZze+Ft6K9jfu29OzieCwjKTrZc9NnsKJhx7MdjH9DUaPrqLIeby1Y9OSDhHO2ebOUvHTLLjeahHK2519Tg0FjBiAqQn7stAjCzG1LZb7D7us5+kJ4c3TruCY+uWzTzUTrod25/J+HAHlPzt262DrFs9Mb7YMTXsY5oaN8Hsa2uk+WOQW5XMq+C0IhN65rEbwZNG4MHDP+XJouMz7kAgyPDcgPs4bn79U2H1xbKJNx7QYGSZ/LeXeBECrHUwBTbW+rPY+tyLGTKxFpNZB7nkPU2KfYuYPD0G29k3X7DS0Zu1z/GAJPG/HD/ykCIBnHOy3uBJPedG7CvFoGzAq1kHKcrHk+agRYDkn8Im2Lgay6u9REBlgm/ywnhH7VzTo51xdFAn0UC4fmQtfLmziHOPh8GAw+B2+LCzJnixMuCP49Se2dbCjCHkaJu8w1N/csGR7+3TCXRiis4EhePhk19xjbfeicPS6FrlD4fXX8RUjvqNzlqqsf/y+DH1QS+jHGEdvHZteDFuv2RNitoow4IJWBEHi23wM9vjWlaOzfjZTQM8LiHex/vD25TJUpHsL3tzHdvw6VdkWTiX9+eFCPHSGVAJaxebRVy9zr14ec2e4OjuGujOYicvNdkrYp/BYnThICrPztlxcs9FiXCjItP9JUD4GUN0nhh5No778P8a7M3HeeAzLSdvJvn3UpODJwsP3CHUWuwWPPng6EcNg+GmPhc0nuSpa989OQkSsycEe6C/58KGyy9ujrih//cfTj8aHH9slkbpaLGutHymcGBijQZK+byUpMYYyStnFq5ZdWw8XPIC4G2H7O0PM0maxyg4GLM/F7iSfbiMJb7QEUtyNa3aVRPzvOPdiLFPflRXJxozh5cpKdmQ5AlBDqO7VXCNtwsPboPgJgffkrB9EmBjCS47cDVk56z5tGU6WY/+RmHnuPV80yZ2uXpMt2aPg0TZSF9iekA/6m/sMqDPeDQ98+Zd3fWh2zrgk3P16bCGMZ/0xVUnGhhgmFfDns/rKWb1TXdxZmz8ZqmF47C1GRe3D1CTj0h757qx4nFk1Nc54vrgVgVFZ47e7OylFVz9E5nd1HkN5Vb3q3FwISeLI+TVRC4VjRn74Cpm8NXtiybWBaZsL0ywBHhXA7FFb0zPz3AMFxwkPr1BAxqb/dTVXKeKUVBto5pyjAPV+LDyeDZro9vY+mfefGCbe7Wxr8xmlzUkhoE9ebBNxuy9cc2SmnYOGIy5Zg/Da5uS/+eumkiaxyoS59tdBPJ/oHtznsdeXmTl490+iQcBhkGeb7lJ3Bda37zMGaD9NNUfuSE+T4ZUkTp4TsjH0anH/wGEvD4+Jw4t2VQjdbcu3gXnuYdvXiToTamNMZ85E7f5WfPO+rfciPMu888fN/ZHNKKy2OTi+Zph7u7jtA8Yf+QmHey3v/kv3/70d9H5fXRu1v/Du+p5EWD/2rwvCHijnnzcPKeHf+RFgX+w8fw5dcBHVnTQb8bRobWa9hjzNLwBPDfxfL6/f+6NYNxw+SJt/K7oI7Ms6/vsD3npo6gA2xU4XLhu/J5r+IrzhW6cGNiZCR+A1oYPzvXhxcYXeoq+mt68utnIH5YWYExjLysKPJZgxRGYQZD5mGsZHPOrw3hMYqrX45PY8g76AJkwuj/mGkNza9aXzQfm0QWy0kAEd3JmHZwXutSlszu2lZrt+My5uEcB/PDIS9Ryjt2dbO2nx0D+qjIjFE5uXRNSJcmLQjQw9sgsA75T1yB8gDVKA0F9zJ3emLGkA1gNLKtj+Ul7rpt94G69IF8K5wRlsse16eYYTO4XR79K8vYQ5o7WPPUf7eM766DMa2J7sT1yT8IkWa7tYxMHQVgQ2MGrvSHaSx70HAdcXA9Iy0JUV42PaTjx1kOdqjFWvfGYOwvPCyF7vhIZQ8NYnCxbB8Fxy+/PU2Zdr7LWcs+5cNiz7rWrc/GmwenkvebZKrYGAPUjMHMzEzo1xl9Wtrev5Fz9zQIumOG4MWRgTKzTnW828g0LjWywSpjiufkgwKaVQFfYCLWXsTEvYnsponFxHL6hwRtrvolln/Hs3xcRsZ9ayS8u++WauD1GzRW+xaoZ/mbcLSnNPw1oT9rnw6HEzVl8897j1Tz4amOGxtvtSpk0xYUX+W6jr7+Dbp4JzFxAnPdVBQDXbmO2eLluM3uSmeFsbLS8D27i5IWepBY9+82HGnzR0+awxoCtO6Twxga5f3KTzB11riH4qCKt8ffrvKjgopHXwhsKn9qkgXf43IHyPj/4kHvBQaL0BXqvUZbJvhtuW4RFLz9cvZaRiwQ9VABiKt2jobC6snVSrAd1TKBizcVKDEnICSQvRmLYGcu+Pvz2AwxjuPYTCDWXgHeXwPM1NIZYW0NdNwkSqgHw5QHS3HAw2u/Rhu9oB7mowWbnzfnEaZ2iwK42IukBSltr49WmffPBN1rtG1qr1h/ATI1H03DBtE+k6iPeTJOD3eaQ6taE3cFuStMif11yDqgaqmgfhO65WTzbUjVSLfbk+veYTGnij2aw6Mp+e8GrT8wLnPxLN/jbFxzkTsDW7ao9KweYJQTGnJSTG/zaDMBbjFHAMM22lWZJ4QeQyWoDmqGr05knwJiyWcNwCtPHpjC2pdzjH8fUKGgEvBFkPbUoKV5qsz6QfIcvxODOXiueIA6WuKwRgR+8s+IKHoOAbHxM4mg83NOXIYPIoO0jvLWsvWStgx7MjfX0w+BRUqqpJTdKldpP27Co5tGfnbVh92QLEwGSgNnete/a31cZUBl8kYRVN1vneQBm77vH2fP73nx8vDfr9W0vedzjJju3n5OfftG8DnB8c8N5njO0cWOed7dz08zzhn9IFP3+i47g+Zp/wx3Z/ExFuB9X5yPd511j3gVvLmKYO8iFIdve1M+72+nxd61sjOxqm2KMROdmeeRlTQ96M83vp//4md9P//PHb9+z7007v5ued9fnd9R5J50XBniu3HfW9fG/nOTFDR+TUExh4W3lTOxAdDGlr85cMy/f/Sg9N+lE99hIZBVgOZY+9yCc0VR9si3xeXGA577NZ/cMyWZjXGcBDSnzPJyOZJIcGI9Wjvt9kvbFaf1sQCcm/4glrvXfmsndB1Ap9W8M+EWak/hmz4wxNWSGso/HAtwzfuWIA/366Vl5WNqT8bRlVUEus8TYPFlKcGPbk9FEsDnYw9x4dbLMaC2xzPG6uatJkO7VqsVIZp+9GDmxw3PGmX/pFdHqH2RwR5uOi4e558oE5HEmFjLlmzmr5tQytctMftfThkmXEP4Vwja4ntO1bYxRAEMj92A7b16ffyes7u3XF93QbD+mXvB7Tqpn7MtJXTtHsevsnaG5BJ4Ty719VePkmxIaGULjZJv2cN1tYH2G3cQIJ1N7UKdrlMwkGmYew9djQmS9bB8ure1mMfHXXdo5lovAd3IeHri31/hJUZLGtW81T31A8o3HwTk1jWuPj3n0DE4948uuWra2FzPzgxhM4n1h9LYhLBd7jqHW2q3HlLcOl4nbcyeT1pwQouwHfnlGp4vNBW75J7akpw/+TGgrGyxEddtE5PdnM/1bPvMXJJa4+sgzSYb3GOZ4TcDhMnPOTeytNRGDPacnvuE1t9zoRARjnODy9TVe3EKDPtPkkS81wn/rKzfre84HMLjmM/L+kbgVc5Kjaw6aRKZNauJwdVcBM99dqQc6eHwrsPOL3pvEtaz/NnQt2Zs4haHtGeqOjQscX+FPRzb+dw8Qjb1/6Aj81grNvisgZaiJ5dWrtdPIXqRM0tRFaX1Cn4o98NUl/zbr6ZItzfXA5p5zZUglnKgeRG6gArZumUs/bcDeE0Zt+A42C7HDgwvmMaOY7x1C5YrlnK3lNywA8QB5IGXhHAZ+gDKS2z3zjF74xAecYzCjNXfdeRxg3kVMXDaRYs/N5myuY4ufHjBgxI4Kcu85cmhj1x8gIXJkvnlZ95wpE5rta5cAg9iRGcQh4oJnInTC5/mjPR6cGeVmOQb2TKWqDf4TT9Bwk6dLcMvv1E2jmQ4PeKfVzHQP6+Z8c5kTjGzsozJBBxM7A+32rQ4B8ma9HFWQbSfFjy6Mm2O5gGGjxnK4MlszxsVJxFjarZNIXJOLeIe2zieysPjPeYEWc07+wHuMWjs8u3YeBjRbw/S38QRirrdYlmOPQQ2T+2gEWE/3K5QUGbMLIo40mfXmI30BczzIxfiiocZsg7e3e2NzHJtnauNxLl+3ksYdnUgpWX6unbVH8Clq+KzdpJcPbavT/BTxZVjkrxzUxTB+eHhs5meUP5zGzfl+8066fZoO8jPcd8+TX43RPVrZt6eR/w19SZJew73PJfkkO5+vMle2AILrDbCP/zHVjkDdtqK/T96bbW7S0eG3ORvTDhIzvQqGm0/1Ycs3lAhrDlfmIZYb2jzjiettZlA+cNLbzAOnFv77N/fp01/5mPvP/JX5P3PD3ht0/ku2zn3nP1r//MZfoqen4P7sO+nc6aIJRfyzWezpxf25GtmnDl90yI356Tnnz2hjSh3lotb0PXl2bfXmTEjGZD/+Sri50bWDMHlGJ7GOWTNXN3sdlLdaVFhteAHwM5j9I8co6ajDBPw8MlC+88tfWxCbMEipJ4aVGrxmied//DySqP0xKLJu/djNsSJX3GZ58lqMFcKznAMwDnvXH2Gi8dS6PaPuzb369pibK3AiVlqmH3WwBr/Pp8YANs3tJefLMEEwKqhghkk6NzQIYx7sQnuUiG00a/MCmN71HAGx6JtrfROekM01GaK/NtarsKqo4VQydW41n7pB1rK9rmJsy1lt9nt0yy9vcKvj2ftCDX7G4Da+zPV1O3WxqBR3xRMPyTjkbG1YB3iP62o42sG8sY3ZYwIBbi4BhhpWB30xtbqmB/F4rPZYsH5ynl6KggZLePK4SyKUyInLUW1u2fD4jCDE1GU8c/Koe+woEjTYPRewbu82lzbQ6F69SnrW5l191P553M1txgo4/tgsKubNu2tcb//RszoDnloxQpF8o08Dsa2+PkD481UP7qyntxrxnqJbm22q08ibY+LtHzURWA3A1WPwEJJ+yKwTzPQS/OdAZwa0DGrNrrU7e1xv3aJBErSLE+e5VKb6OGZZr9bt/64Bbd7OhzNh8/+gY94TM87NGeIrgRmDE6LpthEUtMBFqanw+owZ2DaMPDY+e0kxwMpB42Vv3LWRUSw255nsRXvwvOqPDi+seILPRxJZ22wvLHLRlpv3AGKDecYsuKGLp2niCposufjJRyO5aEgsFz7IqSRUCjdH2ZZ49rusM9vEzI2qZX8IOSBx5lhTFmjZ4bwEMeVdH07+GaclR11iJataezJwWP3onyythUTKGowlYIN/bGc/Od1trbuPkVxGZsfUY0HOfO3xxf/xAwQuX47oLscmxvoFHz69U6PcWOYB4Y3kwKHjwxZG+wBznGrBhgSAsTmdfSyDLxYnfgcaSMBwV+bjxxeM3GFpH6qmuhum5aVhPlqg9niiR3t0PDb4Gfat6VyPVVnOh38N7zHAf1JmLv6pTa0bL3sDmqP6Tv4cB/sqLoj8u2uM28cQDqd+45r7U1tB9sDwG8dyNdgcex1/9urBv3owE5DB/hwL6InDQYP7TwTWzdsaLq/riTNXCMDDuz738M+YLCe3fn3N03XVYV5NnxrwkKXDfTaRUv2a7zG4OT7xrNDjY+CQgW1WM5cTC+Sa2Nd3GsXSuOwZg7Xv+SNuHYJO6KahW8efaWuQuYcCYB4/0cU3j/XelPvuOX81nRvKVBA7Y/vEYw0fFbP2kB57HtP91aDYeLa59ebhY27Av5mnuvpi7OL6fEMeZLlJWfsx+hjMww2vN73JxXPU5s7EuesQuLdgGDuqp7Vi6Tp18QW2/7KL+vzjopHS+0LDcEpFvzOICYYe/fZbfhUgWzjRjMafeXedFxL4dYAfc8PO76z/+NF317lxhmNrKF3yyN0NtpmJ8yPyc3NeH/Xssyt0aJon1gRSW/s8+ybRDi/KiYnsjB4XUjJbXdunYsDdsT4IGr0sYCpe/nj7ON3Yw03UPMm+NnTfkfmIQsNenIrRjpEaquBGsh57jLojAn8x8Zk/OCjmsUyWL1y+uGxQNvlXt8jpORRwczwCIQ+4J1fjJsbiNv8BBVLybDWCgLBrjW7Kgr34t/5GzlYg0Zl89Ki2y0Oa8plT8TeGPOaivkeBi1dc4vqCAPWjzX9P7EbXL2fyYgXfc4Sg0WwuNiJGo+DOE0O/Ge4KO7hl2b3ALMyjvulhokuTbSdqbk+MyjquPRbBoN318BQlyCn14GcQy+biMcy5wlTE5h5NBm3OLFjbq/gH2v5d/tXOsWYcvV/W+zNUP0e8Og1Koo2TZWL3WBWTnNgTpqw1asAexjwOAjEufnAGnDmTYvUqgQ0RBgpHm7HqGPz0NeDBk3L7Jnp6VNvWg66to6jVVSZzJY/40VZFVV4t0y+5God3JU32ljRGbMtDxMu/xwL7q4lcr80FGHV1tXiSFx37o2u1oLj/2ss3/+pq/PTnsplI/fJmtkk35xIM0h49Gi8BoU/vpr/vz4mxBOTn3zozPY8JwV8dOOo7x7amGEdg9DkapH0+4h4LPgqYn6RSVx7M205iX4FFJHhyNEO34PhooFyB7M0jAndU7AYni1S7RhbYrKfYj0QDUw83vsKy4Worz+Q9qHysMBchxFtf9oGogfWjxZh8FJKLAEHwB8x7FOqgNwTznUGspw9LLjIc6GVonP3kG7O6Mi9y8OGS1bBqBH5H/Mmr3jwxZ1IZ2AJCUnmnPgKnNv0STQwuv7OlhgSbNjZmngPg124uEI0jmHz+jumSs68S974QAYbjog9/pp69rYN6tKlzdA92j+liBM6mD6TU3Z4Rsq9oyljaqjk5ch7OCeixTJBVgzXn7e+n/eL2B2/j3ZM7XwyPjWsolw//jsyoFU3syVtSOZYP/54jcGM/3BtL6JwHZFg/vJvv+jc/SLyjgZVSnpjYVofyilbvxn4cG0DLyfQdw41JWLZwyKOMyaRmDGFCEAOJ+eIfNd2hVf/qJMbjL+iJSRyR+KTBL6/AbuSud88r8m1GPO/YPqPCYwTgaG6UMSYmd6PFXhWZNWcLpMQB9oBY8s3dY7IROI8v+BOLFNIdZ6Yf/mW4MaZLiNnRQO3PxWZrfAgHq/6Yy0j0cEM4K1ihxOLDs1rwmk3d93gHy0Mo5zT+7NpjjLWhhW9uzP3dc945z035uVHnI+58x8+LsTwNbIwKk3/z+ZfUw8sLr2vjOJrp9IB4btablz8gCh8g95BOjcyYnxGMv3sdTn+3/Nyk9ib34DIxP5w0aYb8cM/j536UH3cojeEdeuSAba94sbYavckNzlamp+To74LzfCgLgfbq33/z7no+JmDf0j96wosJvOv+54+8m56Pwv/0XXRu3qdf0ytO8OXmecQc+cv2+7vr3tSrecSgNLhUporzSSdqyAsA1AlH/Y05XRmKXcsTfAKtxT4Quxz4+DbX7gMnc3rSvrHQcjSNNHXy/MVXzwyQ1YZGeKWHIoMMpSIviyzVVvPyEINZriz4cVPBaD9xkjTfZJMP3QZkv7qOFjiISwAS5BV3JGUiYmJBAZx+IAx+ovPPeLad+HjWp1EMEzuzydw4f47jmHF4XH+uFmMOKakrNOogdfEHhy/f1zraJ0Z8ANvvF80LETYfMki2F9TtMDMOccDbLUwEFCcqa4/hWPEyTt6A+vh/e+s59/T6xU6wDMybaXNm5ZT9KNqE5Bm0HG7qhKMM3bY3jddnTZsr+9FmNPW9Wq0XYU+/w765z/GK/0qIt4lUaL0YKi+7TlbXRN5jP1zbtz0eq2sTNa5noPOpS7/5kid788dY/PQBFxYPFntaPOeg2KIR3XjWEzvcVFFtw4U/jx3qjI9BDhR0zP5Sx3x7SdwZ1pJ1007m43Wia2q2llgLX83AynF6iWnlMDnzYu2WfRim5QcXfe+xIPbWtt2Bp/Nqgochgfo+15AEs/WOoEWv7o/zH/jg4CKPrRut2HocmEF/zwEgYO3115xZi+X5V9luSgLPzMjX/MEjFM/WkDW+xRoSn2uxjbyn3XDpow3736wNGN4OJhPMDLHzhAa7a4FPsazhaWijsx45x77+3W+Be0IqYYXIFwTGbMjbJ8ZJFZtNjJ0n3ACCy8VZ7D95YQCbT7DZg836d97FMa6czPcdF9J5Q0lT+cNA8XG7TnovE82RND0SsUrlCYC2rKD7MrAzsnfKAQPUA1dvtgRGs71Fk/4lWxS6wHWP1YtQicld/EgZzol1l00wojrNehjwS51KF1PVw1tNpkIdz9LDsT1j7VkTAWog3jnAIctkUjYfacln7ixmffqALsfUPFR7IbfEdPOkSE4u9lg3dL1rGI85Bzt5YGkNMF/cFgRMK4IzxM52Y8XEbw1iJsaIMcBO/nwt08kHwSaKEz9Lh41djbWyKscwWf/kbxJJ0AOTfGCG8sTi5/4hX6sdiLoGzIsc8sz66N88ZDDPkH+Jx9qYzb71oefNm3m++MfQ50JrbeRkJB+wxahRe2xggAXQXQmtSXP70J+dAzJu+wXVcju31sTtY07Cbk3lB7cDyyidGZbFte4KfFCTo7hV2wrQenr8pddmKmw0VUWZW+vpYIz7Ituh8eo7iJGHjHdsP1cej4XtTVAx+oW+PmL2HA8HNL4QmMlqb47tRSIn2b7D6nPj4MVm4815HDzm7M04N5J870fc5Q/239xMIoD/NIz8y9+b8r57zo0kXm48GfYmkiyfPTz5Uv8Y0bI1tFF6jemsTN6s0pMY94WA1WAyWTtrwvBaW551eBGC+TwngCKWx7VK5bmi/x0aWvBVa4BoHhvxJzaBq2n3iOt53HOBvxiftOXKR/7Rwf8t77vrufnvzXtv0sm5H8f/N33knfffuTnneVatKZyGZKwe1syz/cXXd855rm18gMGVgJkh4XVSovFiuj0QkfW+SOGLHEJ6HDMVvzsoOcaMZHa+aawDm1qEiKmu0VeJmohfNudwo22ivFhMf3rR2EC3FdEEZ1uu5UTiORcHs2uWW8dlxTt1xdnLlmou8+iK4xyfqdNdQOI+aq9tykzW5Wue6khUYupZBJ5a7OU46e9i2bdWsJPnJEIJtuyZJr4ZIIoJHgYnb36U2/OaiAE7CPOtRxlt3CYcXNA64YSfiPI0llWM2IP74J+afOVF9+SGj2Gdsx/sttjzTb7hh3nwyuH5V5L41VSZ1XEg8ZGYAAAgAElEQVQ8RagtuTdHIre/u59oJMXXjm5d5G3uEA01O1/wDic+B+6ZE7vneJ3dDlKZco2mKaF5tAUfI+dq1TR+j+/abr5Ku/UEbyw0sDcz257/8F37yR9c+0RI59Y+dS7ucmYmTfmXET8axU/Q4UXL8mV/3lTYPpIaDENoCWrpsTv+QKoFuaOdc39yyhGSj9zQggVETguQyHzkafjNS7yPnzFhBaMGw2FaLB4o73mhhxxD3Nxdsm3kjWd2anl6IiKbvfZsTVERW6m35zLECDjKwsGX+HEpskKbH/us7YnW1tIejR+mmIWbNLPs4ecfZbphGWBps8jYbd8gXLCR+kUAUjOR9THLO+jZ1QZinJOAIJ5sR0RWZBdVRYngAQPlwfTglL5R2GEthv2odY8MbGtvOjQUJp8r4sq/S6PoCv+448M/D17o4UIi1xVx5kLmaEsUVzdx6M8j7/6+orxnk4hwcHECPw/Q/B/pnKi+QJA81Vbc1pSI6BgfF0bKq0apMw1tRjadtI2JwYbLk4l9vt0MrlwY2wdx8fFFL3Y45wl3DKeHQ2imcXa3SKlbV0x0re9+cJHIfDOE25DUl7zenKuDkvDF6b/ZZ61WWoOP62DrHb6YGOTY2sXFtnv81jFYd9EDneemPx2gOjwfmE7N9mgw/aGF7wBKlCV8tbZY48beHt9e47sDPBb8jP2ZYBrLEouY3IYXbx00WBwVxc5FHOt8k/ujRGxrgKfpG7d2ZEwOph89z9J+5nw+PNrA8a/22/+s5Wqi9iJYcOzYjnaXzwYsfPxjkE+bddVGfJlHj9hyT5gci9q9tPZCBWKW0Vz29LXAWcUKGi1q55ykd9aRmNUHJvOPnrgOnLLy7cdDTYPaOX5StQZ7DTAsZF8N9mUissM9Ixw82Wac4xMdHA/iu+96f5TEbby5QD7jiTcP+iaHyvJ4hS5v2M3SWKnQDV4EdriD/pKCx0a0jXIJYnHtTWDyrXdZcG6Nnm95zLVfcbDn8UV7ePem1V9HCu7cpOeddHz8X+D6glVh4tlfTXOjnPMCbt9F35vW7EGDjSt75Ttxmo3a156Vj31byLFj6GLrgo/6/VWkzH0OIZt5biDHwxqnnr4AUdu+iGw6tOdmeOfv3tQPr7VPMeoxtvXvOnC1EFs1nfCH93iRAw6eJ7/l99J53vz5kxcJ+i47L9Qy53seJKwP7v1WaDb7wsv2lnODAU6fr9wKxDrHIOriZ1FctTGf01f7YhLWOPdgm+Ps126GuEm3OnYezJhKu9ilwpl/aGC4dQ5TQevzfFoQWhoy+9S0j1GG9bwtA0F3xurEumDNGZsRGHmZY6mGG6tt+gCm2MZuHDT0aKPO8w+MkwQKHyaFFslWd0DUegbaxrk3IhsB34mbENVUXBnBmDAAE1CfE+3Mu2I7JECz3J5jrTexOBhjXIzW1S3N4IQ254YO2eSFKv55AF41xbSPHIkRtGnVsX1SW3KjbecRn8xZaziVobx5Y29fM1EvGjOFZzDnmOrXqadnRnFVH7Oe2aDD/Ak8dS1AVeZc/lFNchRXYELRbo3MOb8PBXNElZ8ZA6seeBp87K2RiPrIs/mNR3PQrZ9Zse+emtYD//YfzK4vh9bLZz+wqdrtakDbZNd/uKxhakL3Fkr08q1t1iy39t0vVm1kMF91nLzUn2O1WGBtCPuteurP8mp5fGqZLKOdLFrondDia8/8Lk150oqvHmlnHYHFqZcjOHXAk0XrARIfMUwztqcbf3GPTznNae8aerY9X8oo99a4SZL/YIYLTbUpDyX2wT6PPmpwfOVpwxJI7+K0dolLljWxpzaqFUbdmTy+/DdrWUmAeQKZZpS8c3xbvCLz7FgdJWRxBN8QY7YpxplvuEfMwuH3I/HzRP2hJj7Fm45mNd/XgkZUdqOPC6PcHPrfpWXuBV9iO/rOibrWMvzUwr3kFsWFk/riJ7wHrzwnvsu0M9HgvtSH3R7OATJloOXKinhCs/eQuMl6nsSPbAPBmcSYMcnFHCq2vfDpipocXe7qw0ZK85wf+ka1RvgK78V9j5C+OPBp4aJ62L3ozEqt2PTNRXiOkX8QiKgEgDk9mvjdyTiki9OXGJ9UFL1ozo3mpNR+ZNdJiztF9BzZJdHiiZ2vzes7hasPYIbHtwHG2biQbcxe5AzkxjjbzfVaXuJv3EN+RFJbBrhmPccftI1kTw3z5Ogym/vgDCx+AvLtfEBqn7l8U3NNcwCyAIcfCzzIa9fZ76y4xpqqwDWIZCHLPf5jwdMam3e1qdsLCJMaXWyZnD+69yKqWfCW7/ZqKhEwxSSzw74//lpHcvPXFMyE0Gd/Plgr9ri6lvOxEZh/PQ6d33O8Vd9j1+6aE/6Mi511yLZXt1REVXYnDSYn3wgYWd7kljPWOYfwTTqETqIjQJuY1It1VCMu3zlXeDw58My5uyqw2D2e6MiX9ebF1R2rk8ez3sTuHzGbj7XPzTnvojvyHGJMFnsDSU3U03ehc0POTWa+fdF2EvEuMEP9U6brqbm9EpIb/O5fG3Py3DEv6saA2ZvzTM6P5mCJ47kP/f7F9Xx0nxccuDFWS3Dwch/MM5O1yNP59tLHjumtuqgheVejvZ2cPQDomgMBdYZYX3/l+TgE+SvwdMSuZF3e1kkvjc8Bo7a+CIHWwPk2LtujaW069fP4DAfHluEcD7k5LyRjzZQXAjh/gh07MeUPVgwGrMRUZ2OfHNOw5ioYDOa1GVNTZERjSIXsiUwCtOSr1bBlTp7mbQDmRMKRvXURS1TMZXU1NrLoGt6uy66rG8xNvDvt7WV1lOXRMvoAbvjnfqtEbsl7HFgT9da77JsLf8Zoch9y+BkNzzaGQqic2HXiGq2a4sl5VX2gCKSHj8bx2t8wFbuETcTxYHCOUEOP68txuSGAY7d3rZQwlev4A8DWOkreeEm+bCDfeFxl81w5vPEDUcfLNMZl5DySAUMV6KI/TCb+nAsT7jGV9uWeasJp7DSp2MHRtHhbZ/mNCrb64wmk2ZsMGsY934e/1uZibj6BEGCYPfMMeBeDaySZa/qwwHbiPSatDVr1ET+apY5RXxafOQASdPEnbu0QZCBnY80P5+RQo3iJ/PmXODb1bJIhOvHDeXs3gOChG2FNHgWmqOP0e2/c9zn8NEDBkiyTfB+ax60e+fd8m3Pg42fwtKp8FJZROdnOuk6319dlMrRnfd4nBkc2+Xc0eA7UhntfeOn5V6LPfq0GJLRHsh590zC49niVfvSVsygcKMkqT0GbBx9a1JOtWue5rudEPTDdmIlCB/8oOv/kjqtPg9X7p8wkdSKk82lG4hwmfookpHXKPIsY+TdBCkz07vV1M6zd2bzJtzdslYOujNk5BTfDd2wyXwsXWn6kL8/d/TglnpxQ+X/OewCqhYsILvLcI9+LkZKCI0UvpCaRhca4iRDXfwNgmYby4NszzH64DMInBi8MWdCcYIfLuGE5occPqAeK3NbgeoJnZzh1nDUPmlzAbIw0rtn0R6xL1BDG3pHFmWOANCdcbblYPPPg0kPsnniZsN9vubA5AZTvSbQPGD2n1odm4htAWnkJc8F6OTJRZ/b+6wUv/u3RsDQtF7XxNaYeF2n4xjABAqYXAE4Fe9GLP9+UYE8IbPLGYccfrWJcDh7fGW9OjIg+zqFWSTzEx5klFmC1gb9B2Gopov0iqB57ol5hasTnmF0X42f3+sHsHQW05ONf0h0VYN41S44bY3QUsmdf7LjNM7YAGqHD+Lfn/HxsrauhKYpfflEs4FsNpit7priSq3nZdtRfn8HKg2KPg4gYFrlrKbZneCNW32sjyfSCqSwBeZ57v0EcnownrqaeW9c158bEbxgE8sWArTc9s3DdWvdmSOzY35/taZBcck8fPR42ROvCTi3oc4CZWj0GwPOYxA3WPjYNMvbMPLho3xfvOreK8PC47s3qvrucxx5t7vOHz7Ln2+rsHQ/qcwcNffScd8x5LM43N+4+FkWbnxYKRpkh8fEfgZlbM+e/5JL52If7HdvL19ZWPXWFxBwBsadH/dRC/otQbsr5/p6P6/uR/a0xZ3twqOtjJ4931W8N3CRTDzevjEngcyFrahjxr0bLCa+28H34sOfrj/xuOpn9hNNgwW0s9LCjxx7PvnbLc/MZY+XBDyqT0+8xnnOGYkimHY19F58iz026ftKoCvAkznQ0l2SAIZwKQDrYbzSTtY/b2kpfp2dKQJULehlq5HRmTDnlnhtEkAw07PyJ9lhaCxwQLMjUJTY/DNoGp2ttZSyaZD1/WEPJz/rhjY1hzzELEBkr+9pevXqD2zq399VFuon7miT2eqS9G+xx9PyuuflaBzrMKW8b4jYayKVmdAoa/yQ6fsxH8/Yeo0GI1s9yj2/n6AmutMKHGkftMVTvLAGgjWO+jx2JV0tcje8W7fYLDgrwuQDijipcvY3Ftsdrce7tD7MRS29Ykip5mri9xLzHCwxWYc7jYzE8G95rXOyM5WNaptaXubnCN8dm7WRoLgnKbh4o5ljiysXFYptntHHRgTvfv/DEUlRrEYiugOVC0wxjY+fYVFsw9iqe0RND82TPRA7iWZ9BPcNL6GBx33rQlbVxWxdRV+/SNYfqzDOzZhj95hg+eQ0+KoaqGg1ZEIvVkH0VjJ7hJl9A1XvwQzmeatq6L9YXHwfq8Z+5KTPvOYFx646w/MPuMRpg+3Rx5FOXJVXh0WgVsxqu28Pay09w8iR8+0fug6UfOtET6PQHBKPR2cZ5zhOjZRXTTXngPbgnp9TDOWKszSzg5jkCVsa8gz4CGr15lqbr+Hrj8hyYxS/7rC3mzIvfRijaDoQ2TdgbaZtmg9qETYpp02yb9GHMqL9NA+hpmuuUfOhO7n6EPYbchfviey44+Cu2HoxcoPkHgHp2PIScQBkjxfMmGLkx6xxAdnKxzMDnHyJxPsBTwAnEC/yX0Xp6EcvcijKhfyfm8OnVV2zpxGJIyN5EdU+f7qO/PbdpYLmgzV5ucjGJ2WKrdS/gu39s0xDtO8/+8ENEioTYq5yEfUead1/qa9o35zji5lMPxsV0zpPHBr3DPiXHyldidR4IE5KCHQ444Sej8wHTR/MOBf4EHoxpiKPWiTkTydYYTMl1lye5YJv4RbZH44txmaujWYwbH1woF5eF8fqw3/HOtTb54bcuFcUbTT12INODvcBgCVFirYcNCVcQ/tFiPnwGVOG4fRxh3l6XUPzy1TR59Dx6DLRv8iU5X2RQEykZu7+TZ1bI3W5C4hq4yg/GxtKXVJSNfvXeOjZmzydLP0aYCE6uxDdj9nPBsRcKQuIljyDCVp7GZwkYnCMgqWs45wTGtQMnt43qXIrYliZQc2sZLI8MfY0LgrkJHF/xl7NaqpG83EDyYugeo321eBOuHvY7nEej3P7aULX6znl+Zvej3zyO77vp3qxRR3L1RCjbvnt+97kZ5Pel/YvqgUYfw3OcPV8kZp6J+mqtZHLg83fXiwcLTiwxGE6B8PA9fYtn+a0z3Oz9PfrcmH//++/f/v77+2/fn9+ph81eJNAb4fw8+vve4fyW/7vc358fX5FEoGB6qrba9qZdvfSSFz7omfhiuuUcTVbrDQ//pkb8rYnjG02+0NGPuW8f0cHjK4PnHD+5tvHZd9Arbu7TG3tE79t/35kPN3WTjBxgsfzjO/rFos8n9qUMXJ1gETlrC3DVTZlhXI2mcUM8kR7/yQnKQzg/r1khC+vsOzdQMMc11xn5qu4q0LWgwUGzGFjMLzmAfM+TeDFB59/RWASGZc1eYUR23gSTA130RmbCeu6barrB3Fg2YXNd49U5PJO1GafWfUxL+DCGZjSpM3PyP5rNNzbmjK2DOTpN1c1sl2O1kC+wAW+Ix3FywUUwkGsf3aMx7uYKxnpt1rCx+xiQFY75uCXpOUidDPrYmnqsNJ56omGvMY0Nln1iidY0OsZ9+qf3aITVQCYd8dnrEJUrKhbiHiv5skBr/tWNzsTyczx4+1F4uYljNrblsL/4TDT76cMhmzC6j81KmXq9cQirKf7VFMSMYtSYaPyiMtlzS2DWHy8sKK5RpN4Y4h3jx2M/UsOoq9Lt0+xXd2tPlDXHirx82zOIxZvBTe3LjD//LMmNuQBu9r1xPTobMrgeKziaeJ3lv/W/0eSxenUS28wxM1JAEdd+jucBVt3mNP3EWq/zZLkOLCdfEx6y+iKkmR/79g6NNnagg7SK/oD1WB/lmwsBzOdnT76ZL3bTPXX3mNXBdo/B7QhGiKtrumlXqcE6Elh9X7UniNjRYg+XK5H0Ou+gE51wsvPtmIM6mdusIQ9Bk5Zgn6/g3b4hxh8QebfZQx/b8TE3aSL8oQxJbCMBRgxdustm9Oraa0VQcoEOBqzQaoTylAYiBiC8OHDeBRZUvP3I2o/ryV1KcqsIrGP1Je5jXS8wMnlCZd7Y+I6YiVu64e1ytuPzByNxX6Ali7FK8JbTdXpK7vUx8x0sLeHiokc/xEOSafHZ48s3FnbOM/Edn1nXdrG+00IEYY4zyarH21rWG6A9Gq86xseu+S//HLnqtRvtyOJccWF3jhHzqwd/scnLxTn5xbbGix1d67eMREuQsNU4k9Yw/RJWpafmiSecsX3rqmt1yD+aEkPHKODUd+boY9yeLsaaxg4Ce9VUrOsER21rj5k5Qw3iXRCMU/9WBE709gZovjRm15tOEKMN3+i+F0+Ppml6dYaGnDsyL9Pk1B6+M5KZJbgA1zOU1Rk3+uzlxMFp/We/keVQgZurB+3WKV+JlgM2faFRDus8OG4tZX+31dTqFDHcVXYeD6kA0/avad02zzWc/sWxvBxPb8qmFrKC88U0UNDPjRRMwrKxf8fAh2hSDz9XBKwWQBnk4Iuc48ZaX2z2ZR7feZ4xBxrNm8eT7NU+fBNYzhCqN/v9o3DgmfvYbWy4hnd5oFJXJtzccdHHz7s3fjrjx54sPM573pOxsisyi12C8/w5tno2n+96yQcSzRPrc1TW53UD4m5NOPxYe27O//7+92/fv3/vzXpu0H1hg7qmqdzIopN6eIHB/xKNfezWGOo9FvaQTPSvHe+cfmHPTfk/+d2v3/+Bc/7yvfjnUwg0w4PFubyM5OicnNtj+6edDfX1pn+PLfn8L/DQswdrKRPSuui/i9R0jxv17U1C86WpEdS20ODmgs54j1VrXK3rM3ePEKbMgoPI2cxLTBW1IimQRbkfzcyT1LzwkJ84xPVFGThik3Oz6J6FaFjk363FYaQAk7BgtO7OSiH/JwiU2t1PfHsjxUFLj1bRdgPqGdSx82Yho5ynJxsLcOeNwVLekrTP+LKuSaC6XFczNfv4lKbjs/fTb/vy9KSqJs5sQ/y1FDPdjXF7vDg2jN0v/9SIHQQ6Oqprj+mtK5iJJaJwtCGGkolrmlpIgCPIOOSvQ3wJtsLNP/0vQgiWEpGDsf1woXFpl82ext2c402wTGpq7Na4cVg3W7HJHv1lSIUYMzZffbN6auw1QrGAF+cLuDE3x8tdUp9T9bI2MKsnKQLyb/Mzb9/Dlce+dRw/E2Po4h6r5o1nhUCzoZrdELcHdKwsW0/248agxuDpI+fI6Vnw2ExgEggmdgjETgyuIti2cs85HAw4Zrc3k8UHi57xCVK7Mx17DOoLlXrrVyPkkMxg1vN9e3fSK8O8D77CY4V3rgc8AW1auKA38uYglXncCzgGNYWOOhtnGc6rt2tZE1rbaB0q+NU5DPvzWxtJy3x6jPY9ftmbe2zLAyNRy1XBTbi6yMtwTfyoUKv2bBLSPxIXQNjKg3XGnhhH3Khm583tATb0Nol0Axazc7jjeQsc3EoQzgJkLgCcJpyDh0Q2R89KjZMSBU8dYMTF11fjs8/z+F44wLN4cbmA8IKNHKYx2XBkDn58rRbTMTTIbWs8J/eEUgA10N4TxgW8xlK3nD0hFDGpYjOu+ejtHpujRXEwjC8/ANWQ/Xwhr+zMModUXuZasoGddS7UsGXTXfY8wGHaPT4u+Njnm4sx/WCyZvQixWn6m33MXAJOljp2O8eEvm48+481/fJVocmVnFwokk7dbNDBA0DGfZEF/PaGCz4u6oZj9KBv8xGL+/RaAza0d2y0vMN1j229IIt/oqwzduqc3CYLt3WcY7eJLpeAmK9le1m+9Zt0QGbOBm6G5+0uslaDmgLoP+sGS4g1TSwk9iQej6H2bACZY+zLB4mkqiju5CZzTFkvPSR0Bb49B6SA/EHtVO0T/CKYn/6ult1Pjs1pHSbB8hyTkLTGTRCD2gcTc2OZVO/8OMeO2vSCnIplP0MdzOu3TmGXZw9Wo7K170tw99Y4/bRzzDdV5t5YZ+2LamTEn3+sd86e72qFm1qaI7dxU2PWPH6i3cfKfHwcUNako1b+rR7Lxg5PAD5mMN8xc/zeaMcupmTGLL/6kpMbVt8153ezWc876D/zjqqP66MnTNGRm8f8HO333kzy/32jmfXarJs6Tu7OP3qCr798Zjwr/XQHX/56uRDtBwIMOX088i6duMaimRcafuSm3HfNuUnPO+i9Sefj7vkjbQGvDvKg+dyc73xq8Qbex47mP7FRxvHxsTp/mV17bsx54aafJqvE39PTRPY4IJvH0ZzQ9DJby4g5I/2LmFcX2qi/z6/1NU//33VfbAifv4YAr4oas+cde47XHpv8lyt+OuAfjuX4uu9jfuOorDwcCHK2muyYsWRkD3KPERGNjA9uQVZgrg1bThB88dQDqrm7d344xheQWpRTNuNHQ+CwHE0gajIQp6P1xOcLPhe/ugCdutDA+WIO2cpZJgRlVnsgUPwyMBW1s67ZUufWtL0rigiYS3j0ZH3mhYgovyGT63NOjqPNesavfnoxZDWri9pOLvJmbb/dt2rziptAdjHusWQuRzC6ulNzoeWErRpbr/ETiw7E3xtQSEpkr0bPKXD0WNP0t31ESXWT+/83DlZeKz7QUdea0Jwv+trnqGAzb58SMsm8AX64er6rXF5nwV5705U7nFPPiqg+VkG0Dc3f5KZlA29FsKPPXXePCe2373ZHXOsaeHYqdLmsaiAHruEoIIZwIAuWRlYkMXqE1DYNqxYIJGRXXRLBsvr1Ewt32QnD3zFxWWw+jw18E7PHZ/dVSi/gSRR7hpzNAXvNXevXNjWN/3BCkqCjgYAv63apvFc9abv6zBQcNdiHamw9xVfbiBiltyemPvo3Tj23WBKg8oyusl1xmSBtXwjAv1z9ed3jDcXti/HTD/BnZLrr9/FHxMDYfag6BnQ1ejPRa4aanl5hq9bsM/Ej7hbCRlfdHizPllDgGndp91BCd8cmXZV7gA4Cjgx/uKfBb9aTA8ECK7I5p5g4SpNs3lBBCG7aF7Hg532AIeCE5qIi9uyJOwmCBv9v3onoKLa9GFN2YEA2d+fXy2zjdn69HgQ1Jj766KcnSTTb4oGSo5nGP0ty1oeBTOTqHrJeQK0yyOOzD3s6NA6O5u6aOQNs98y5SLs257lwA3JxLLr2Qj8XXK2rPB9qE+gPiZxPXRDPaPrgEI52LwzrLG/n1ExeMOanf/kCYz91lQPB5FXRzgenjZNh5EqXOfs5G5zl9ib7GW34LhI6weTPF7EelOzsE3zmABfvJgG/OtjXcesK7ld/qeWVrTkzbd2kCBej29gzMSXG0c76DG0BqeF/5eSYwlG9Jy6TU/skMOfUcnJgJMc5lqLMt8qEyLeWh3vq4bhu3RTn2n6fTCPt6cnh3JzwJnaWXZVrihxdUM25RH4eqBzsT/BYxpadfbL+uKbX8ohst5ap4Gr12E+cx5xep1+et8vHUZwc0MFjPmyz3nPo2JnAlS3DpXuOaY9rX6AKJuvzwlrm7XfPe+Z88zO+N2TcaHEDBWn+ZaCoo7HL0ey2Y3G7yLo6yM1ji4bhG14LDXv2vmMurjfl+9F2bsy9OU/PfBxaIdHkDXqC1Tr7d75QNJPEfXT0XfXqg6OjNTFvVbUicR9jmE8B05I5KtSWx4Hf/Tng49nUm++s+7H2fJzdG3RuzPPfxfEx9/l4e7GTazTyAgM36O/33tBSw343qnVUWvpqOT3e//6RmtI/8D9+5P9bDehHtP70nG+V51zJ4yDPjr4oH3xfUOlN8/+j6wy0JLdxZOt2t+fs/P+/vh3P2O0X9wZAMsuzrEqJBAKBAKTMkjKrq/vzov/3Onq9kQyGwZpjx28IUO/HJ+jw0ZuMVzP9/JV/jkYtmXNzzm8KaP+JLfXn+IbZczIHGCYOBISHz8lslIPu+DlP5I6PPTbUGqmPoGM5GtM98c3R+kCekdgA+C4kjnRInWBknNwLkDMe9o7Rw9LzCs53hGRfw7Z3uJO1HINn3dF4tosB+Y67mtkUUG3Tlw04kKsZE31krCbzW3DzLsuYVLd5jYxueaaOq/XmgV87NZJPMqLy8JwtO5bNt32tjbBgsmiJaw0KG4R8Yw5gzwuMy7O6yEA2h3hoh+8jdpU8eIIQkPHRLy3gDrPB+yPoI/fEK3zzltEVDC1juHg5n6cJsJF8amytW/PEuEtWz6lEkNN5bMsFJrbVtjxkOPmNCS7xw2zecmEeawKIWgw674g1B8Z+Zbq4rQNc2bGwaC0gXca7MZt3e//6ha+ApoTMb/FDLymbrQ3UqaOqmi/z0aI7y6ODcBNCxCh5o02predsfXCdEE1hyLHltYKI5bsxARlTT1Hk6rhHJGucU48aVrfQHuEBBdpci9s4+ZAITx6LQw/Pq+25cW8ukyOAgbfbr3o3Hj7muzcgmzI07+FRS9tgX5bcoCpkauzwIgGPeHTPV3F7LiViakiYiOINTr2Dm72xBYa5GGxMd5Bndfg6FB8/lzsMJpBswG6kQTkJ2iBXatsQWRVbn2XTQKUMjzuKDnPmpBCNHVt3zQGIMbsuvm5LciBZ7gFTCoQztMvZg0rM1rL/XlxRSbgXZZWQdeo2B5s8nMN7JuVsa9sjD9TB9uKWENhEfnAAACAASURBVKrc0lpxTKtrCL3gGdA9Iac/2C3uRLfmObC3h/BOPnZZ9CRzKoVUdj2206tMlj97b5RxM/fhQrjrXHRdH/Om5ZMZetAcw3/6kTUmU7V3Csj6Zy4ah/zUNYwNuk3XL9Y6y0dwGHozYZJEjx+enfeHTntSYnyTe0RTV3OPRpYzmgXuOd7ak2gwphye5XgvIvCXv4pZe87I0zPJBs1ajuiRd47l5l6enqUVwByNHoMn14kfrhMTrR/vClJ7wfIgo9hT4kftQq2XuKwSrxKW/PDIXj2S6rGybh5mXIHDtyjqY63FSdflI12Mo3dfFGFoTLmWbXuynKd3k6zp4SNf9ktC9th80YxxcwM4XERs7WAnVirjMRbj8+rlbjZQYsoJYKLpQQixYzHNxMClL2v4W9OQn/DEEZt1Hzu/b7ypPRSLg+7Nvzc2COBTXzJ8+8atUgyT7kySBJNaIpZz60CgzYJKvNHjhjUm/wDceXPwMIGWx5u98PSPp+XGPH9MjRu/2vuGQmtPbHLymzP+O+39dJnXcR7o4RH7529MJdG5Ie9rSIDmV2Ar8ob/5AkH/fS5AzYPfNyYURNOcm0f2PNAMzfn/nvz33//5fff/501v9rePxLHv7H2TQni4ZGDHTfF/eSfm/J+kv7rLz++5332YKiHN1IY9DeW5mZNbh2x53W2b9BgyIf/uQHGD+fi/sx51eQBpL3cEJPDN2ryJgHH60/++Gp6ynHAR4L95wL7psr+lgNrudEBd0a3lndW33ITzpvo1hHKX6P11+Dh/Ul9+Q0ABn+8LiBx1Ambx1Mvm2XP7E6j8wDUY4/AgmkJxpax2BfTebFnzhJiuTey6yjuTfpXEVkTQ0+MeDROOSYvZXDpgfNYK7X8q1stw2nBclcSvq+cXuLFiGw07Dh6xvBqPJgk3eO9NnVkUY3hu5QzrWG19LUU2AXeeW2srcs9mWI3QfZC0hcnxckNDIw1rT8mCmVk1xq7NkebMJz1FwuYELDNrW57m5zbN7U0rXFsFjN7IIdH/ARNgHXE1L62qvdnpzqHt7UtFmPrRyaalnl/NpQHDNDZT0nodLr25bI2CPOAE7/zctRuV4yHg1Gd03fiYju9xz887BnvsVCJ6erbfLciQ5LvHlfzTY8PnhxA0ZtxcrAMdUtqDgHZiMzriYKpQo7m8U3HIoTvcfxgoB64D8dStW/lazbi0Lq25Vn9cYyi7GduKSzz1aokyebB4MGZmGU48xY99sEJhS9r8gzG/mbdOslz3V00DfjtkzrCXhoCEvdlbN9q/nIMB2sPNg4yxxyHzLGQcwqpO9u3n+hdv3yuiXn6QuRbV4kN3T5s+lf3239CbipmGCDlu8epGcHV/mIWDvr0mshJDOMPG/zRaMJI/Y4eiLWYfPPBIpxJBnYakcc54bTXf5iZ5GRueK1s9wDtntAOvcjPi1Aso1kCASYmuT400au9MDh2QvPoH+QgkBVDa6esCJ7BfHomZ81T38QXjQ1v9tl+jet/99U4L5AEF0vA6dlo2RfWo+0VwUUOMeTJF31huFZDj1nrqA8/LrBq0cwcT0YmTL1YZjZ2emgcQDC62Bewx1sK1EzvcPsr5lljUxagZ9yaoS4/bm8ImHCwSZNg3EMt1jz4cEuuSnF+Whb7yw8JuAk5esyLzw9hSCJld1zJxERnWkFziBD6gCV2M+7OT+VPKACXQPI8UKdR9ZgvYqs/Nql6nOErfggtiojhLDgxzc/S/rjJPOuL3Rhy9Nw8wuRd0ssfi/nZQ/xqZ64ZjXzBCUxrfU7ZoCNiehxTVUHjnn6PTZ7JtfGkOjFw5Us4mzjJdnq/rOq5fWzU5DICzcMrwStqOUvWFUmSBSyBjCfE/Kzz2N4wL2RzjR6KeTheHdvHZmhV5G/9U7e55yYrwcqPjecvAw4e3CDidF9hxUgGJ+p6XI8G4xOWWJ5bXAgS35s72UEwecZTT6yw+kk3pANFz/7aM3Mc7i8k637iTD5vynNDyH9F5s1fbhSLLyHa1ceNbG4kmfOp897Y4u8DmcTgY84oh1ONPS/45FhIXyBOf8THAZ/SCRyu4tvDl9Z6o5mb89+5Of/Xv9xzc+5vBqTW8zNLOupJ/rw2tTbmefMhN9XWlv/rTbs1UlvrWT39sGt6Osf0GzmoKY+00izo4kGPtwu+gZIF+f/KDTHH4WdeD/1bAMTyCXzip2Rvluk5Fm4O4Dq1hAfenotETBbsK3bMvCbQc27SwxA/6OgdnPmc53P9fNpOLxjoo/6OzbH7myfq5A8jM+Eew5m/8donLzrPz2Q0hdo3euhAtO4gRtExwO56ncPlEr61E7Ja6qRibdS9+sDzEBvy1bc5fPNDQOtqfuR0vdHL0ZsPSGNRz+QcZdZsvmySlTg5QrcaNNUaW0f5Zy734E0Dz4uYoOy2HixFNKd1jJ8k7dXqAb0jnviXBw7HxGCvTRBEebDpYPbGsDg9oD+nTwBxEnd1bJ+/7pfz6ELHJFusTKNl8fqy2LyLxc+89veY6dG+PVIjWieGNRHasxkZ+rvBktEk1tmfb4Q8tc68DMCbW0zyrVb7O73a+j+Tbr7Eb03kf3rhtCV8aKjI5rYfaljx5dgjTs7qxxKyygWUB7mJazVby6TEYT3TxsDB04vpvQ4SlGupT70y1PphG56mXr5DPxJrR9vlVZBrtLcubCZygxRerzh291wBOXnUWp4GwJSxSZYsL3T2oyIHkN3En9wb+GiATprbONfEMLZ/G/I+J8wZ3GLBVF+2+T7nF0TRcmVfblwdT4+ixdiJwb/cRk5d5ziZa1ku9viNT2S+sTFWe/e4ZJ7na+cCBY+eMcgxGvoJOsQCQ/QWehiasElKTrwCk3jOMdHb8G1gMQ8R4ZOsGmo4x09nMukMG83ZcLWlmBxFKKqVmStRYrnIyKQcGzzrJp0f/pDUf/NnnQVmmZ1T47QaDVygEipXNZalWxscgPokph5oMY7dix7qiE2yxipnLzQS1BRaqwuDZAjIY/IYDc8z2vvF18kFcmvmU6cJiK32Em7fmgpbL6zZrw0Mc8i670lm56wZ9vK7J22Wk5FAhy2BKyvf/YUsRns3GILgIHaOvBjdowGEXmN787EXi6XpMTTP8JNH8cPvby+EZ4+bFzsJBtaeGa0SFWNnqKGTIjKHUzsdqeqLo5YGnQs+wod5Cfdi6/ZiEh09Rdq3iS7L4LK4s9ZVv/LiW13sq7O5prAeWJmJY8zhca6MGDzPZg9guXZPNnNN37efPh9kkjmb5rW32qP+FmDyIrLN98V9ztFAGNjFXC119Njgn1GwC0+LwgQsh5w6T1SDk2+HmCy6hzTz8bua+YkoxB7aO3o0b74VP1xf88ZpTeFjD2rzsJc/e5/XqwF7Hji9UWIqtjZZWMM9DzTFm9EcXYc3X9wK5QPP3MBxo5TJYPd8MCybmIdjLJPXm0Gd6OqNtjd0ef1mfNQDNzd8fHLLTXnm3Kxzk+gfjIufvPvgprw3sN17k4ufCxa0Ophn8qxRWv1jxk8DxGQy+5oTDw+5n9dzfeglLgNf31yoZm/O//X7L/+am3P+3XlraQ9OXHJRA0m2rn5Kft98wM/rXN+AuLUhs3X0/Li9RG5/SfzPJJI/Gn/6x+Iav3Ho4LjkvYNfvmex5w41ZZVzizd6ss/x+P5nP9H/9oeJAWTc15y+ltIZBs72Dh5X69LfjRSzyWFOnX1u/OTJyzWA50x7Sx3V3U/6l2brbv/Wmj31pEl8VYOJDsC4aGKPtOzC3/UF4cjjv2gvuDFgrFLsgMl/iMBBPlwkY8REqWsmcjyt1Tfe7vG1ln1hIzycWz90Hc27lY+yKaEZ8DFWofmHa7VUWwW+/kZezdsH+OQN2FrhZ24ujQ2CLGM19Og05hyLKMO/lXQf2/Twxhaz+YxJUjVOPdujxl4Oc+WptzlbR8TtsanM06PVjIQdJ9aMFvvleMB3a91+Ex9zc9Fiap28WxuUe71ESu3BGLexLNSTzePzmgPMqN/+GCx0+iAG2CHS4uokIsH0dPDbU5amn+1bA9fw+t+G1QLdKNMwOM2Xr8QxpubgdynnbnS0d6+/AWuvh871HLDbJ39tEMaf1/GTbOrfjvdY3yy4t69YWZsje8Y5jva2+i+GPA+GhbjY+Qbo2PM7i2NbzwWuRjyxHujqe/thdHJV30vKnHx3CxN857nBep5XmBnNl6h8n5pl2fXkCnDPD/TsUWDfKsvX/J0fvqeoVZgg+e5vVa6W7jfWY0K+OQ9vb9FMtqtLjNq0xvGpDhkb055kSU9i1kclJx5wrHXsDqMcrTN/xb1JY1yB7EfY+iSVqwlkA0ajwfquNXuWUDMNNuvOMWQ9F561ggMwII07TzR4+AfRmUstk+bkWw97fOjwMT/Ejv+tD2NSys0mviqY3GD1ri4CGFeZkFjUm5z9tGFPsGLZtpdTBQIn0N6erKMlPjKYdVIv/yp6ZW2v1tcsE9/kp8hi6E21ebyywE6rtrLt3cDsJRF7wc+8g2OVuATbPYgyLHE+zGgtPabo3loINI9JKpE4b5TZFzwXKeGfN0bCcHqjftZoMDE3DEqQG7t4P4LKLAnExY5rVE9AefDA6zErWj9x8kmAzkbLGBt8VRYLhbjunm2lZItPwcUZl3X5DBtsazqcy+GeKPIzOkdH1xMXTuo9xkE2JMj4qq5yeDEbqiKFhHNqIc765SVHo7fW3YvLpnr2XN76dj9+CEeH3JnH0hHD9mRtk9FzQtDGumgupvRs9e28x5N0ZWk+A9VgjicnnpeDFVo7hpUlP7hntN/0/cbiWm5h1oilXObIVH34nps9MGvfquQg+uGBicdRMjrZWa/7gsYlHt/mF0dTnlhyv7XUHbLcm3GTzgnRfx4S27lJynxGNZI3WeDVVT9b8+sLH2+s5nUE233D8GL6iWyyenPePTfqDnRkgl5vWvOmAZ+s2rt4rKNIm1Q0lbdetHDGgENmdhN79xrF8QITUIDizTw4aiEP8aCEFcvrGjfi+2/Of//9X7lJ/z1/vf0/1uSbJsY1mF/Rb3/MNpxz006KnCc89ub0vj7ibIWZschSVcPHGyy5sa9St8vTUorlV+3v8clNeG7iKYgb879+Rlt6z5sj/DdvaoiW9jxrPsnfF2Lz0w2VuHWRzP6F9ipoahr/XwY6gHFeWApLZHbDxKm/gg/G49i9dOIy+6CfYwUAP7l3/4GLa5+Tg1mYukxAeIPco8+62DPiw53Atdfa16m9NupRq21/Vr1Sdk5epcic+fD3udpUJN4+mCsBR69asul360aefKA7/lu8+ofbHBYG1eh2/clEzPpNchJkEmjrSTzXEdNrIMjkQd+2ry4fksMLLI/FVxHoDA7YGUHAly/zPvvSBgvJhMiJaY59acrBHB6+5TJm+1CvtU/vTz+TX957EHNeN678HxLUYn6diTRPc7e3zYVsnCMjgNb44Z3ateGn5wZSBCHdW1NA5QRNzzomw2YyHz57Ab8cqHjy57h6HLI7tQYrBu6KyJo8sH32aC3sHdtDsHzDpbM5ncoPEy6+wOgpxZtrsJv79CFI4928/YIqXKNDVNbtZzWYxNzMmnefg+Z54vGSwjGLHtssXMfbbythgdmesstjtePYdrTqCRSTDaMBFBEsi2v7yKvDTH3tfYEjaKLVo9RgNu/u5bTeQbhL7uHYNNU9tS2ZztlsMgu4dX5AQrLnkz8vps/vMUWs/YKPR9ZqcTq6XtKdDxd4mrx5cPf1pPahzAJgd/0xbKC57M32vpCREky+89+sEZnN3k0zRwAXSvl6kz95QDl4536Lwgjef4MM2E5TaIbzxnQbf8YHv4ZsEuAJI6TxNrKucoHNMF8uFJBsnNbGk9KbvWjZE5B9m5iASnBnrTNjRyPVpm5OljGKyWpjN3GSg5d7bOw8AC2IrdFu4GUtj8nU7xLjgoN7e2QYvAOROmKJK6O0R8uHMSj6Mal9IaFuLw6Ij2MfKJUvG/bYGb0AytqExevIxvrhC5QLNkV10/lwCbDwYokv/c2/+eQO1n+TGO0lInke/NEgePJNXUHBlHpi8uIQXEesitbu+TLnBBBcedzjR8w4Sr4ksOtZRB03FjLPldmLj0b7CjiJVGXBzZHUFcA+3o0pVrQeNmD7gjOLweOzF23kqQV7R/La86yC2f5uzaxVQx86A3Z48NU+dNaHsbWd2PkhbE1CO7t9m/rRQoJ+l5S1QzY1dkZuBgqCmZw1xZa4aoV7I/TOanlJeTHv3AwJ3b7cCNK1RhWc+fBwMAZ8awR58xwlFammIlrRYu8xKCF8DuI6sT7zYMrj628TwbHwrYVQYur73OvLa/0ZmW69HCJ6/TG+rHntUMPfjvuNIvcp2h5Hz4hcrSpEe8L6yeyLiT3PWXP5+sVrGEge3aoyG7TzJul+Yt6b9X66CrbnB8BiS5FjRV15wPixfeoVA4mjTDNdKfKWE5bRF63cWHID/kduaPn35/y7c27Of5+/2u6xCRk5+OIPo/VmtBzkUUpkov3URd+Vnihjy4GN9NhkuDSuCQuJGHJ7g028HIlJn9HrsQj0lz/S8/y3bGC//Zlfb//1j9EwMYnjRv17/j38jx8/3H/PntdtbrgQ6XbnWYRqZZqXNG8jEyoGFMeTUZaLumVVh6DZWDtJ3vEuyQ+t+7mOQW++9tjBgQjrBkr9+ToKXj6xeF7jTT5URptYbYNtefITYY7Y+vICZnDZwbMaJqw5l2o1x8qNEBhdxELOyBydetXRmusvUWsv/ANveHuCl3T4GRu/+k+/yDfXKYsk//Z1dXmuqKcoGMXM8SfRVtSUoxV4pvVtLPswC8me78zJWw9cHasXF17s4Lqf+blG3qB4o/XWkPUErEYinQeHC7z7odhkcnjcoFiSmRFjkzfo+uG7I/PgMA1i8u1qK09ETPTigI2rtqX0DXsgwtl2dA0n4Ynh2MRov6YGeIsLqFDxLkxAbcMR5K1v4xIdrqORaLj3EvDlb3L9PRYfCc17+Xs+jZibF7EZq4k9XK9t5M7rGdiMoyN4dWw/hlAG2wPYGLnBEnHyLkarz1v4Vg9woNTR653p2YmfCfk8Bl2fGrTdHOfNv5Kax3zgHKwm/1PjOKvFLZbijAgWze0G8w7rmMXy9litf7TRkNHkZJagCMdF/I7mqu3kiFsFammMb96MGvOfHq1CEsnQ/pFgeTIRhbbpT2bDFhh5hq8MgwPvGMWae16BW86ZFWqRjYP3xxZLQ0kupwmH+iRJJHZo+cYuvmQ13+T4yMVgP6iz6hOG7MMpsPH9FFp69fii6jMVEGOZw5uLCPlJkAdF8WB0zqwXG5IFfZsJJu4QoJYeMzOahTViy6gTaEaD4B9zOfWBwN5aDJCnfFUWyPBPerVCK5+iRhtsrNcHjRnANpdwpgycYNKXih1DHNsXYQnia0d7BSaxmNc/EN+IwcaaXNwEm38YuDdm5CTvxXHm8fNVHXoBaPeNE7napzc/n5CBw+YNNUmHay8kW8twj6hcTuZ/O+rnQhzFhvFGAccW0Ywem84rLZedQJovk0SKW0x5aj/1xAhKPgrswlKvZ4zZeT5wrg4UNeDY7wB9bCwqatxkHj72fIt5ODTo0tkI/FsTZjTEMtiSNIV0R0MwFakT3zD7w+MUAl++9GUn/6w379caRRuXsAld9nJtJqwdyN3eoXk5m2/6m6ZspbdXrcPzpUWU8PTgEi9XRQF7A7CGdXMrpn6P2YhTZzMYvwy6ec5gxXhez7aW9rHHf/IEbHw2Q1/mrL1WnCaYMwCf8yLCAsbHzHPuZelNX0lGRxacD9yMkYOhBvhY8Fz0zS4WGRhXFzH57fY+l+cFYPzbK7g+eh+/598k47Xiz9zwQdrXGP4AXfTkq7p4LWjas1UY1goGZ9rs98Z197x+9OYurJlXDzea+yvR1F0ej+3OD/tkoeY0tLmyJzdYmsxgmV1a4rDmzNjz6Kf//eN2fGLO/3m+N+f8e3poVgd9gNtc2pez+8VRC1nBY1t7Jmpxgyg1bo9yONNS/8aa/648N+fTC/rkDXXi1exNenrl6/EvOU55/No/CFfc6ql2/qnDb7/945ffAvztH1XnzXplzoVtdap3ThmeCqzbs6cOqkO/exo8j5pSREz1ZrvHBFu5Tj+IH1t25mmcFGVDY8bebOD32GHzC+zkIPH41S0m/vSpdTTGCJ93xMG3QEXIgn1rZ05kOxdwv81ubptRr07xRNx8Y4K0CSXtvPoX8VkD4gqdOHRoY22Co0OG2PbYFFfegc5i+wV26jpBtZHXGPyjgTVjjxnHRJ+xqPx7DOgd1vmFT29eNNuDchiTKdwMX5IT15fmwZDz6Jp6NiZhaORzgdUO9vJKm8301lltsPNwM/kbC7p5ltM+YDs1GamuZmPdGna31HseLK6RyTA1gXOwfmolTgy2jOI7b7bitSR2shfrdnqT+fICsrblhhc/++lBMxiE8fi3jjZt7Xs8ywN+c23PwrQhZEEMpsE1L5aN04lKoLzxkLF98F6Dc9GflfiuDnCbc/GNvvFg6mPCipjd1uD5pK2ati9KHz2NQuMbUz2Gau768GsrHgyz1Ssmm82tRvzPcTr9WRt9DAkdIL6duJwxOZonW+L44Th5jIMjo9tM9njHsP5qAQFTseV0mU1XRaBlzolw729pWNdQbG1GW8PLNlVwHpmL7YzRWhlTs7hmXNirG5vsaHHBamsox662C1uvPMH+aGgDV3xXcp2DNNJbfgB78KY/KllM1aBkCnxPJE3Pp+5NM3Vv4de4LYLCk2RcezBdxre/EjmpPHmph8H+xDOpubtJsD8EJkDtwHLpYxn2Buw222mDr64hliRQ9slnj8d1+rbxaGMONtzbwz0u7LU1FajyYd0TPr6TeXC0HttyUzbD8s+CdXh8ZO7FxOJGidj2QO1l+TgWm5vUxcRCnxDxjGpJPQbEh8YuMgkwDy5k/dXJY+eCML5chPLrkL15bx4D5CIJF0f83757DrVzeBjAjh5lLY5fs6THylHPjSw5+T3+EL2aWTPgC1TaWWJW+BBbJ4CS3f3g5NeHgaA8zl0YxwLbHdSy+cBOGgHVX45Ka604jaG3id/zR/vJzWryAZuY5Wfv2OOTBWh7S+/h9RhcdQ2gxxs92hVXW9HFNKdOdfbNwK1yakAZ38m12sr6qaW5gQ736CNoVIR4GYKmDxkeL5au7l7f2Ku8PK15A1ZToqcn3bcGexQByy0PenJlqKZ1bB5olrrCs/oyAihmgzcCx8zRkq89DiD3+eLhBxavGH8NJbM8p04vpjetOFB0hVN6N9QARXKkFvNgFyO5McTRA26ieQnj/h8sr7W84nJz/mv+nTSvA2L2xicx6OEve/OmADeUfGLLfxdGHTyP+dQWm3ZyEMMXOZXcddJ5/vciDL5qmkmQd/A0NBYuiCgFg3v4GJfDcyE4f0Vce2/Q/fQ8N+P8G3r+S7X/5C+3/zuP/aOcKksc/aBuebggjDjSktv8yWb/0gvsDOpYzFiyo6vFrt7D+SeeGeGwT8kJb6MSnbzn9dhjwOvz1YO//SIHf00+n/r7+v0PDEnJp+o5jp7X5IolOs1VsWKyQarD3JlvnRqpnS/28A63cQ27eHjIByfTPJSZcwrjec0DgKMIoAe81k+SQrqV1SnnYSpqG1Kbb3TFYx3kA7WE5NNGDF9zfNQhnRZrH9v2wU8zR2+l8zx9h5kmH/VT3/q79njFtHLe+Au9sXAYIxX5GqFyn9+07Kkj3CAeJa4aR3yde34BNB7+vBAgmTG7jwW21S/f25/wwKk9wEg72GopVTHMp+8l1bn9IsfyoI8Du77Gjd+o2YwW/Kg3T140pMcyfVzde2jemmSKo2+cNxL8aj6xj82GmXurvHEmhxQ/vM5bAXMtwltPNU9fDJs65Te6Wj5q2YolOjnaL7i2d9VgL0FNv1Y1+2YoH1JX990/PtHlTwpevA4n65dPrt1M4zcXyDMniDFUQMs1mGg2fPbFpovWkuA6R5neaop9+2HXs97zmBjPt8nVozTH4PDNOaCu0QKn14bF3oqXiL3ZRgM7YpuheAHyVAMJ+C5OZmOk+twMDiOMq2KfJ6Mins0EN/0r1nw5Zuz/65ja0WPM4FZ9ed/YcmPfGPIxtDFx3RUeXiNwFjXagrEG4ZlPZUS9WtURY499nCfLKFyekNMb64VjkEjZ+80qKg4mh9yZpQ/5I3GgY2EH2WAOkmQTZTLiWJMlY0I1erDGvn4wINvoLvbfw5kTghn84P7I//jks7LimRbbiQ2MEZs3mqOjjU1M1l6MfuHsSYO7bLIPphdvFdcDJ3ty7KnSmQfg5SVk8z9ouceOUNS2muATL0/T6ZNGzByZzSFHNHBh6xVu6wvUPpe5GvaYbH3sHwlmY11/8uQCSy2jwwt01bTW9ue+wbL6e3wXg7atB+2hhI8NCzYaG62mGPh1ys9/95iLbi9Uc2HIr1fmopJ/47i1cFPe/9y3xwN7jxM5mqI9XpW120ZuIrJkfvnCs2tCAEyzzLA+4saNfeM3tzriN1ZC8ER0OF+tTw69h9hkSsC+/XUOl+KzUl8YhWMcGzzg2E8N1aVDzSNN7qu1HIZBMRz7YqQOLqb8oQh18JNja7QP0vR8gOUeB2ZxGlYt2zc03LydqytWY1AT0be/MG8EhJn7gwtdXYLYxV7kTlYcyAhD+d2roQic/TkICtzWM+s2XR8bcjLam11sluZhxePV0PoHb1JpRILbmmFYDzPzjWmP7XR3cOxu71gRszrJeLn1mpOZmsB6tds15e5DzOiRj9eNvak8x8EMyfcc15joM/w8+occk4evse2bAvylcW6Avudjejmy/pm/2i06N/C5D0/UH2rKS6GD1wsecs/eWkYrud/x/uZAceutdjIYk9yZdizF7NHmYM0c6NjY+8U+PeLfoPtfquVG3f8HPX+B7X3TEe0BALAuZAAAIABJREFUanMO8fTFHK5nNvlX9/ZIr1qUouxCUws9nOfvvVkNjufzjHMDjeZo8Q/xeeM9nxDDGF9fr3ts0fpn3hzhZ2y+cwz4GwA/jN2/sk5uv+jl1LTaXU9++sU3PvsoPJFZ86aMMWMjDnDgatrXpVKNvZD6F49IRupaPtOCzRjvM6m9vnqphQz0iE7/ld8EUfNCN4cYICGP7VE8SJg6Km90EzL2CTJfNmMvU1efMd7wnp/BS2L68/pEFdYu38OVNWy9CYB96iQxI9C9QahBk1M5nTXGfkwfmqEcy2khN6jkw7Tn856n1Qo4D8hQuVOWsW3MudE1aROgiGPgOUX06nps0o7PfPAujnkTT9+afNx6Tz2DNWcAy+vxhWVyeuRXY3BVSmWbCaKu3IpdC5j2GZTc8/PPqMlrTwYwL+dZhQ3CjMbNxGLCOppYMme54x6Ha996lnfxezxaQqxLiDaThNXCcFUQsc7AMF8sWvRhH5TXIeVqfEAE52XU3sjZHnlTNty9QbvnQuu9a/OHiCxtxtWnikm/ilpD49WWvHAYrwZkVVv7VyHbt+YhBwlvLuxbqxgYH259OCaO2JK0ZpY8F06eFEoOuZSzvYTikuyx2WNC0MtRGeCvnVwlHsXEaAB31H+5psI1feMgIC7fLWnnXUHvyHKPJWvY2az+9WE/PM5Fgq6js2CCisuaHx5hagIuoMkgzYCtkm+d2vBRh364v5wLmuoXBM5JtuNjDUd+xd3ZuDUH0/1IEOinO9NIwQcDugLcJlQLXRoNtwGNHBVtyJjKsn72cyKFD6E9OYx0vUj7wIbv7Puo9877A1SrAdAjtA9OYKRmNRt2rrCM7fmkdULNmU1PZg7SYJUD44w40MIoL/Me1Ga+fjxgtqfEZNEfiKtzj0PAlAA3ufvafGtpFrYd1SCSIB+rC4SRcHOxDbE2ttONsWl5/DKGrxeUHDd+hRSKXjb7wzKg2iDNwvPjaqOXPCorSphkcPFqfzmEXrvmwpBP2HIB2L6gOl/8n8yJUXsuFtFAfjsZKtJx8QZvqY0yJ3na8eruelzUSUy+wPDF9+rbWPbYei40NrCJZTKjZRWHkPB3V22glmND4Hm5tQ8P86NttSrR7EcncHhXt5wSQQBD/Ahh75a9RMd/fDGfiyZ/QE5AdocfLTYK34glLlM8e65Sv0ZgenDSxzFnD57HNY5BvVE5dYkBR44sXi32b/irpltrXH3EOt7n09p2T1z72NjM81V9plZ4fSDjGWHqMRwDUcRlHptqSq1tQoqjH6Rfo+As9ieRvqtJZjE4OrAx6AtE9oO+8fy6DrXTf1p7bnZIBSZjaVkz5/DLCRc6m0Ava2tmBSGc42fP6wXP7/1jbtzw/cVz9rkJ9xNZeILzJjA3uOVI5/gbFOHuTWFfn/k1dvjA4gW7uo6eLSKCfI1iHaJq3coojL7zZqTuYlzFgO0L91iNC9lBwksdPPxr7d6kc4POf62W/y4u9pDJ9/IyV7vE7Rc5+eKb0V6QK370aMOT2ZQyUIyOwJCnW67MWTP8J0UBwMWvp6Pt33/mr8zntxR8yQ5v6+n/1b5VgreOcPCbTv/Ir7pTq9gcV95kYfgzIvn7R+Q+lW0//cNxCqJmMKrs+cjKc2Tt7YcrCmOwo6ZuWtvYdDwYpgx0EsdZM6lPb/XD9eBcaFhGjkDPxR6T6MIww+MYQ4/UEWPMMmwAmeRAiGm3y0hMbL7lG02b4+yTxzMhsZVAwHgn1nWdceDMAn0Wz6rOblvbsm0trg0Nyv4lauLJ1ho26pNPPzkS356MCqk09uc1H0A09Gi73Oianj7Nbm8QkId6ijEu6zXv9QAaJkUmmWXN+OgFZmOrTRxR2KZvhFF/e9djJu/4PSbwlnxywheUefXg7cA8Jnv0aIO3ejYbBsKymXyssmgehXQN5pxfYmbz5pr5iBxASFJfhwpMaXdJO2Arn3r2HCBGvdh3JGaPvdETQ4atyvnU04zxiSM286NnSWPzmiTe4PbY/L3e+HsRUr6E94iV/+9ae940S5DS335YB7Yrw9nLU63p1mgWOxoAi5VhlVTT1g2G0tG9eTZvUp9R/J6HMcewOY+eaDB2ekszT48e/LENO5lVZ607b65Xf4VWP6Egd+yxrc5Yo4U5+yIf7OrDgy7eXMYmEv4ZQ7b6Ngfe1sAk39P70wfDwwL5zBvLIvbFZ9UUyY951mqf2LV1P4IGO2xy6IldXS6yWTi9sNCa/BV3D5Ry2igPAAIEbkMqDB7GYlpobbvFxiCeiyfQzJlCyXDd6WzhH6FRuw0cqoN512LiSWQevQk/uvaF/SRNcqSgg12n2XZY68ccVHUTcHU3VqhGcB32MTVY/9YZV0+qpldfQvq8bKy5V+cUqIdNeP7Wi7cJJ/dMGmKvEb0XVXh7DJpzMldrfKVENDVzg1uEjdLaurnAOr7YbUyg+1sRhHkRRox2GAVi0dZ61o5tHiJ7Mbs5VjMvur/mrwh7c66+3Fjk3076WxFHU/TzLV/wWXDR78XgW5N60DzHqsqyTb/8iRg7588Z7YvyZsqTmGPJF6Yd+wKiUYov/gCNpTnMs5dy16xmLiAbkObIpPmMqNVjjGNR6xss52h8eBm35lYQg36iHK6ZTW0+Jy+mx27RChJrbDaXH9pbO9kQQeRqQTLp2PR4B585D7FzdbLq3xfGcg9bNDIrcUltBzaGOnq85F8BhndhfKBlakbmJ/dRPjzNqH9jSbXxiIHZ9YhZPjw35sGlwKrJPhP7QD/CY73ydE0u2AUWke30sSTG3D4FGni5+lppm6fXPE/wkXPkmoE6iJISTWPNk+rO17YRQ+AxTQyxffT4AuP53Nf7MAbv85t/E82NbPYEEL9v9vl/b2fNaws3fh5HPrHMV3/rBu3wPjfoagwiz/0WhXqIu0fmX3kzQK7w2KuBwgWuv57NomOPFjzi7Vfr4gbVMIhn7JsHxHXOm46ds/b/gFdIObz5DM9f+TV+BvVRmOcC2rOshuwT50NcreChe/ESQUds9sQw1BO29q03w/z3dP6q+m+/meevnz/yRgL/vIi4+RmbeP57PX6bob+2nzcawrd5f/z4Tftv1DGvo2ZMDMN+2+A7b2zXzHtjfvEfceFRM31B2HBRHy3aYS/MGSPfJgkcmO+JMNvjDrq9M14eNhJoggPtdLpYQRDfEPyuOTbFNzjbGIhjdD/xY8O/lglOjPBnE0O+Pb74QrfH89hiHtezH81DSN+MOzkT0cO7aspCbwdD5Ts2J2uex3qC2+EhydJeuYinIHd2YbQ7byHWY299se+5eY7vxLt2Tl7qQmL3zifV/PiQk6Trg5+XBOq6PYs33/JYc5bZnzrNl5gd0xOXk/u4rHBXDwcJELHXFssfoZYbl+cFMF6jwru1EtZRza136lfvFlik26nDnBtOv9aOjTk7t2+R1S0WZ1ztdRb53j5V93ACOz0drlNDMI+Qdw5h6zHNhz51bX+3TuUMf2zGTt6d4/U6MPt3GJUN7ZU7zubuii3rHa/PiAKM1bf9M6bHgyqAUeN5RuNHK8c+zq1/z1+PgxzNTbzAYej60Yoh+LX/HS+gHFPOHvejm3xyXJ1AvSadvia9o3amY3DW/Guphqzoibvwwj/rU+vDsrq3T6y1GROS0RdzU+OEm/VgtpfdoynewQHrMWTCykgXtS+2CupVfPBDcrRcWmo6tcFGLxmx73NiluYdJiVUH/midcJWl75wYSaHfyRug89+BG1hEpHNMCenfpv/2PUSH9vG28hYNOM5B20OnvmMjI/9qq4fW+1tyiDdgWw5tZ7QSDAGKWskj99pw/i9IcOWB+PWMwZttbcPa6/G4qUFWS0LgTDjcHfJxwdbUJWdclsJ4Tz6IjKca4NjxHsww9B0RmylEpyThpgyds/ViT1t4vZW0N1sg4jI3DqnEC6CzZZAc2fz15zMA7H3Oy8px/KU3WOTeBSoU0IWKG3N2Pdc6UUAF7bRPhdXXhCHFDRzLt59cmjj52Bs8wkYF6PWUTHZNiG2uJpYH2sSjCk+NYym1UHWxhpsHYRwbN+b9HJLLGVp95jVvsmMjwnG7QGItdfDtjl5IbWp1gDneohqvdU+HIGDOLoJz7ojWRTXNVs0mDPHthqoGVPzLM96N17s0mLM9x5HJZdVLuw7Lt9YTl1di4Vr3FsLBmzVZnYN8tUztQU02qVIkNoJWR3OscJ4j9PNhU3QMgd3O7/9JLpDZZmOJaGN7h4Ma0cK8JiyiNEuJ4x85sQ2P+A/9Za724DmVZ8Yy3KdOTdMNRQDNz3OV7HDE8weC6XYWGa1B9wxdqK83j1m8pYLLHCW5jDb5ScPB86LqYD8BJ3nHyMxaPOmPTeOf/F/oO/zPFfYPN97w86NvQnU7a9oJ5x80oQvt/ZqqC6w9bklr8hsdD19G8fbJzmz+eiZga1z/dsD9rw+se8bDuz7Wsaem1x08Mk/OP4a+kiPtccGTkfwDOIc9K6z2U5vjRuctTZnY/LamDwMXMzg8HU9Bv9f9T+wkePnL7/94NPv/k2ATIz1zYXoptcg+aN3f37j/6Wff4dOfTkmfmV+9QZNDN8TC6fTmcA4UzHE7nlCnMc3x7/x5XGO3PjNNe2ZXRxw1EdHWdPCkzfzKM6aMzn2eR3nufTBHVS/y9y69nzHl0dIX96mqx1uesJABYN1FWHLLN+tYXMPn2ETvT1J/OHBJmEt8o4Qfy5u3rUF3dzdH6LRBNxzgHre3OT4GOQdjrXThx2Zs6KPmLef57jqDwfXRRlToXMbKVd8+Tb+wZRz+tQIQfbRrIIn99XpDTD46GkPyq0pSVDSY3v95Zyg7MTM/l3Z3lP+mbQu6yeIYth96VsTH1Z79GSCDQgPCdiqF77xZrc4UesHEkN/xpQBv8a7m2xBAuFh0J4DrDHsfnjEDHz8J8PiF/ro2fNSV3qhtnDtMYHROX2auLPHg2186Nrj3nPs01eJydSTuTVYRzZjmzL0wd3RvToEhCN7lQ3mnhs3Yspt/2xkYrz2H9rsVjvp4Th1b00DrYLiyd3x4DUcB2TJS63ZTY8aU8zWxgqo/Xr2xhiAIjASdv4ei1jWJzybjaU1exzwdc6MGLYzWHDJDe/hwxeHwCr4m+8cn0ADub3LnJonCxQhZ4vDub6NX1v2R1Pmq/flQhAqGYcj3MrEKCfrybc4AYf94gkBM66tceXmE3S8oUNcQDpMMgJwlyKzm2C9iveke5qeeJtt1mRQAYmq/xyIUQFHh1VkGj2ExSx/RQ1mdS62say4DDvvDA+674JIeVo2aX2X/qQGso7Jj4534NbyYabunlhgPTD4Q4wy+Je3lqypCzCDyZCuX/uY13YuQHGG9M1Z/GE85GoBXiWZJZE3n1PAyT1824wUaglEMH8eq5Wc1kWd6OGC5pFAr0jb48d+GYPNFPvWBtcNTtBA4QfH6Cd8uXjkU7bYvCHPBS1xQMwno+Qzg+iOzxXiquMinnXT6qqcGq7myTvBhzuwfREG2x4FdACZo3ni2J1eMScme2Mn6OXBz3A7/eFoNUaXK2M2ycFNbPIbkRMRy8nnMSrHbu2td19vAUQndnmWBXDGcg7qvvgc/M0J/uM8ghncXKwtBziFOtn4WZiRtjY/F1/0tNV1z3OuFbTa99y6xyN5S4EoC7GPk+bwky9+XzP19Zi9qtQdPT3tN/nirpbViIbW2mTVyvzO7Msey9m32cHkZgjk8zSTyN7W483s3pgRd3KThXoZ9NBp9k9ufbr7q+S73v1BU/MY3x5D6euzvjnG9DBr+8qcmvCniO11fbkZ4wYXDL9FkxtDRv/6e7X75oPWrvdmc0zewHPv5eson07TL/JlusfIHnC32ns0BLcFWe/rj/8mX1K0tlKPC5V0qf3Vz5w89N580FJLvghZrK9pe4NoZwQWG3wmd44GUsItC2y1sSMR/dp5JzcXaH4baf3U91f6+pNfuc9/A5dJesVvH33LDXr+EB9fJ0Ez/jv/Rdzv//5Pzqvv59fZ4bs1BUfBGaPEuevR5i6bDz+LtbHPWgR71rwRK6Z25uTZ112wKPR40odI0L9BqijvtG52nA83bkVpc9G6TxHK7DGUYB0knGB1YDf3AlqHwmLvDVNrWQTl2bnhWl0uoQOYRTO1XkwdRjo92tukVpE4480NrHj61oF/OduTcWgXNrlr37jWRU5GtWVCHi3VvX5NYpvNfpAh+A9MgRIe3yEf4qzb62Z6jxSlM9bTVTUS1fMEa+s20cFf9IkffajeLt1YaJYbbwexzIlwgEEYu2G5Oso6yBMJ78aXq1SnJyWukSjwk8N+EIR9tmpaDMxDur0/fvQ9uQlfXufxw+qlZX5uvzzi8BrvRLT40bM1UV8lUCdjtqffGjfbIBaZPdNwbBz93VrGCcC49Rk99y84qiWYxOpbTbOWb2shYNKhHPyJd7V1TE5smbbKKuKHz40Zm7iNIUl5ibt9VN04Z/5wF/fUb19O9Z+caDd28m+tZbeSmXYeLBlbc2f0KwYH084hbbWY7rFxJYgQXv+MQccym+PRv74NXbrsSSZPYp3JFyA1h/j2bHCAjWDfwXVBz1U01Ltx1QSu/PrJYWi3Uk7ccu9zhKyXQ5pANgusmeebfAzxQ5g/s6PFHSCGdXnD9YiQbwRu0dlXxBI33mTbgGnSeO4uIQrpkWExB4kcn2OF10rORE4x2JDmtRS6TqNrXy1vg9C8OfhVOuZTuhr0h19bNuwXv0Drjt0qwFJHvj2oAR9Ogp/xLp2z4XES7Bpdw0u8mAvSN2HqTd1gerDx1vn2yTk6t3fgOVE0TS4C6U8wfDrlyPrcMM0FZB23zoaFKGNzrn7S9ZjhhbsXhivDmInj4itXe/YTnu2zdYUH23nkAhI8F5IRG7uFnFh1IIxhnKXam1EaLD6/hbEhlx2c2K0DDhkmBtQZElXficcpd+rIl8upydrq1s6miGpZPCvTnbjC129/RldrQW11vbrLLdPRQvHahTdu+91aR9rUoMZ5YSGknM3W+WifXrx452uP3hufyI91eIOzP+ynFuMno1ni84eKtaOl2O1L8dkOF+vmnGORxY2pM1DL5lzv8dmqiiRCHnP2uNx80z+o4I44+LqZKhSAkUnHaoAa1K6FCrkdWF+xcSrHwMN4dE8N5rrpImd6GttHn6eP1UsN0ZKHN3njO+fGpKY+beqQsIqJrSzXbsAEAtWtqG6f8+TKklcc9iWAp8ei/y4Zkv5Kuv58YksefuW9f1DOSGNMJ2d4SRpW/nq6f2RM+wgiV8Psp7/SnnOcc0BdgRnO6yuvTdm1D+Vlzte5gQcAvzlmL8EkCV/jnRTXK9sTgySObT8pzmQGeaBqPbsfHeQLFKr76+GIHdzE9U2C3JqnF/DwZof9Y/+T/+4Nne37j3xy/iO/ucBA8/l5EAg8v+VX2b99+9/8Nfo/fvlHHvxFeqLRHTXG2Qe0ufrc2DsOIA/yZseG3Se+mIMXFtzGEpX5iQMuB3lhKnb7NqYkAUXq1Juvr/+cAR+8W8OQYnao0X7BXx4mck09zBf9UVP8G785tup+utsKStx6CJA7k0l7uJnYj0mCHod5Ut/Uqr5gzB5fYWVdqXBzBOVjP1TusrCPYPIciVsuGIonNqMNuZEHVxP4UeF+e2CsxYErP3v0Nmb5cdf/YQc3xe9xtVmxRYJZF08GDRaMdfKN9sV3/2iI4eVQ83A15yG2P6vHRVytxUnnUwc6Lf0hVDXa4zg5EdTwTrJtCNtXdd0bd3s4BOH9+Bk6dR+uTPCv7s5Gh0JjmRhhwavz1QuOPK+tCfz5ssq3J2rFv/zUA8VU+GoZmtsbY8ZqWDbP2OOgxuEXkXn5UdH59hu/vqOHcuZ4WFcAmzepG4fK4WEf3BmZtqd7PiWDfoPNZqmY87V9eesuF54Zqw09Cm4+tDBYaZ7ZZ60AWg9YcV/iZBh5Ms9m31gEXqVQAeTbDT8MPM7yTn7ng9tekpshdafPGitRHdtjVqdHU8MnH1rm2Ga/eW98/EP992s+4poVqXuMjy3eHpuwjrTN3f5OzNS5OtqXaiGOl2WZMn9rKWf+SFxoYMrj0GYaAgtbT/0VVLhoioYY1RkKnBvFWjSGpKCeMANuwNZGenMu2d+wh7BaquzRtQdoLkzV12uLVhao6NWKNJLyHUd/2PTJNO3Td9ImmtAerLHSI/JOv7SSZE7KJdi+7QFEyea2TvqzI9PND/6zdwVh3ycHFo8VOsLTiwyMlweMXEy0Tx0sJ/fRRs6MxXOROhZtddeio++MOH0/xSLP5SQRuaSGfTSPLQ54F39yx8iF4Egi7Ay4oONXLb8HYO1jRMe3+aNEYOzVYOQG5/qDMkjQPBh33hhsyYM930gBsZopDpsSH39MjrfPYsm/byYRu/o2YBKQg+H5Yo44TJL81DE+z7EssYxbH7mw6NcL5uYDBDdf2OE89ea8dh774jaD8jZ/tHeUhZyNGGv8HoOxg96IqonhCO8EJniKu2gNgbw69WbTmMN4eoqKV0+pPywfz3/wzXgxnc165FA+pW+1Yz5cogGJi5cXmh3P8d44oCRu/5e1AWBeC2tfapnkwbO08RgyXODik9Lm3eNqmrkTxmYvIcl354mnMHYYHYnKT5MyjRaJQICJuqwJa+ixTnzW8VnDkoyHnAxZZt6bvAGQgddYCs4vzXBz6R+Wiz2f9TrIxk0yAs2RZFuvNp5r/vdsvbnUFwxY8jJ8M0L9uRnNl58wp2ZveLk5n+fr6iXQ+dRz8s+6PjLkK3VdLM+r3sg2d49B3wwpJ/X479Gtg54irLXJg97lVD3r9t5P4vfmKUbW/Dt9AJ1HC5+QZ82bFrxhun4w9J4b8+/ffiPL0XFu0GNdHnT9v//9l1w//9WawKGfsVrh5XHWdYedshCOdvqgwXghg6P8UhZgP2L6b4PcXvhAmzh+RjC0z5xV1LSvgNEAbK4ZVodv/pLYb3gHF+KJsi74BcHh66YGTfVQW5ylqhNshjpkyyJ+cNaHP/OBTb74mM3zl3iGWhTNvLmqMGv7SlzG8DmnOcZMjsw3hpzrFgsnSsDrhAvC5nOhHVwGXEvAcsH4MljDu1qxNE/JCTVXJuecgcNjVST+QUMkmzFoTNzWggegucwzcSbBeXNIAynWj9yNh6g5BVTPaPW4NdKtETlOVz/mIXeW+ebaCHLmy96Bwe9mAV1vLVg378bddRTcdG0R+Dy2th6jL+vhBFhc9rE1MjvrdXOs7bXM2uptcmPhetCrEVM7qrMrsS8DOnC9/IDKaEEb7v5hfGGJv+fE7aAs2dgrOAfnccPJg9RGO2ExtptAvI7JIid8MR6OWerDjr96jQLnmImxgGO0/sYDuedI69r8vTdo/G7dy0Hk5pMltLem4sceXNfx+7xrbvhvxJ6rtcD1nlMLvPmnN4F7BMCTrgWqrAhyjA/AJjSu+KMN9+YdJhCNv8Hil2diwH3Ys/jsR18b+jxobfucMs7jB8dDjGN6RK/EkSijcyvnh6U2tWdmVx8a0P0r7oXd4ElKyBH2JDqNI26zh9gEs64EjDejjY//baapszko8ORf4ok/fj27AvdonJOdeDVuHeTMFxce2XUQmtGTvE3001hw5NaPvVx8guNQHzN0ZgeUk3deiEnBIM1Mzx67PWDCgGI0nZ5m3Xmi42/51SERxIRO7J4YxnhRNoBg1I4Iecb+Zd03JsYI8U6nEPQx7R4nDygfTa5wtTqwe7NedFXC85781OAaByKl6Cc12Huh2V9pt0+BuReXTZvgBdh+atNj16zwlbdrtlysic2eNXX4zToGe6avx+Gcq4Knh9AGzBN1b7Llia313VrQSKiDBEsRuw5MTCfnBRDx8nRlJ+fFEoQdD8fVvbh61TU8sNk/EjJ3eyd94VlB4UHXlwtBOYxrv2QixLvF5VTNU+rXfO2T5wl10zfQ9qdY1l/1SbgJWRRqAR4ndZGbyOM81s1xsa0R+NrEJPTlWC0wHk3M9pWaDHGa8YtZnuA8LwyeuuZ4X/uWL4t5qgFeVampWm7/LK7pFbcxtdPXvFklGzdVy1Ot1jznrJ49L7DNzShI46kvdfS+j32eaXO87mvIqsmeWlvKqL8+4nhuMzz2vqGG1g55Z86ONF4g5Fzkn7gAJJ68/OFIbtqpZf/5C/6tmZN4c6HJv/weQnL4hZZRWFtTcbMNHzeb20H83qQ+tSl618mLDh7mZM+avmevcAMefYjCp54Wq46s1cvGB+SdxTD18+TsaxocIBn+Vhh5eaRPf+bTbfTsa7L7+Pj0HG36eHODY554/g286f0TstXB/2eOrurs8ePvAfD/zqOKN0z+IFce/R82wFAzWqODfXK+b6bKBwDnimeaPIFOp7oG0OM16wD8DYcnWJrw2Gv2+MBpG76Tpwmq7BjNgST1LOEYDha44fQrWiecPMrppv0iVn8Csi+Ucx1dXRFU7vhDttYY5Xa9RcDHoEEOvDtffnSVFUgv2JnQ12rW6xwErkSQD14Tjj2LamuOal5L84DEu2FWAB38HzmLXNzqIbDsyxH+laHGarg5it4Y1JjTIBPfOk3WBFU9Wk8/51ggDRsjPOaCL8NjTI7pUXtQnIqFETtxpNvY+IYVKkd5pjdkEv/kAbUajAYzIE+2q9nUpS0ycZvv6MZvfDx8wzH6dr96pVrtWewxLA7m1EiO5RssleO9yZvDCPBGIkPUwDonzBHf1TG9jIMa197KBz72cj/5fQ7dYwG6+obftO3pKrCm0roVn58v5g20fe7EEpjOz3924u1JFhW0QfU1VO5NH9OBNvWCloB+lRsBe95sXEWxypgQnwd1PPg9XoUCLpyePccm7nLjvePki2nS6KwepovYPMu56zeqx4UQ4vd8aP+D43zKjzXOUZAys3HMWtWf3CpO7ELvjfFj2zi45iAad+zkp8bscQyZGOyJ2fPk5oFM58HvtTAaM7gvAAAgAElEQVSeDhkyjRYCz3njwlSb0BzBbfr+G/ShEbSesZ3GuR7CYLTTYEwZfMKxg9lpi40oHn9PjSLhYGzk+nhHn/naQbzr197CyE+Ocu2Blz/2PQnI5cUkkxn6qNnRxtwmlbQ3fwM52E7I6QxR5GfBhc48uVe3e+zxA2XtIEbL2rH25HS2/ZPcCE/eozH+vZjefhZV3pOfvOQieQYXmuB5oGT/vaKHkes+Rc6nRwSICnJk+yKPNfnPJxRo2QSZy2vOSSq+XJuXFfUTlpCMSZDZauwNQF3k2z/kA3qHfOHwIlDx9Wyfq6vcp9+rNVA9ymRTPcyM184iq8QQthxoZt549s1RjrEHZP4E1pst3xIt+YjY5ezFgzN9Vswxjt/czBHyDoUl3+xxGZKNe8/FxMi11XS5NOe5Eo7CjJwYLbFnH/OmL+LmLarJfW6MEOw7emyySm3E41vduxYrWTOYN+vmr00RmfZ4xDl9MzZWOD1PZo9dG75J4N7QtTWHGnEuR4N97hFM/dUK6NaBTxmYZ4xaY9a2e+uWqZZ7ZLqmXusjIWP1zJpc158ZFyt5UlONb7b4Gy/BuBccf7nUv8dA0yptfRbCQXz6amjWcowWNH1gktvXCMWh5Y69ed5zwOPx8IPUN0F7HMDxxR80++uPyW8Bl5tE3Hy3usz9FXd++oczPSE+szzaUyNjkplf7Y6LfNyo81zl9ehP9tRnjZMrtuoPDzfCrLkptcnl0Cbf8KM/B4SbaW9ok4w3PeD2zY+htk5y/ZfRT77B73mNLG6u++YJWvhr62TcX2U/+tRYrVJnTZre3P/yy49vP6ojxmoIZ7S+evj0nRtyArlZZv6vf/+em3XyV7A35+kDx5mbePqwx8720+TJgU7iAhGj8ln7iTGcAHbvksUMamIqSTngOqae9E0QI64nWlyPY2M1iFnU7hObaaoshy9sw+YP0IsjAatbExpH1CgwMprNHTAyYaZPYqce6vJnhoSrf7niK9p8YrcAIWGKCEIb2RqvrXZSdZbtxNWydcDR43SAiTGMIk+uT/zm7LERFNPqqfKm3iom6wqa163lGQa12KM2uD1MKFzYORwjydTDam7mYgatD56M1dL96NQXfepeT/sBE32ZwO5WO5Rxbdz2/OvexNkULltN8Ex97KsQzmCy0CLmpB+W6pZvtDe4HGSw/sSuNvPEDh1YEO+oKpLiJK45QfHw9DeA1TPUl2wJKMfknpVIfY2Ry+ytAesyNr64O2/E5a8uC4mLcqagmFpva43PYvHTZ/aLv/tjsy/RlNfCFpzd6s5eFdkTaW+z56vzsjhP+O0VaIgz5F/qLtQHZ7+LG3wzxZRJceiBJxrzuuR0ey99a/e13NctjRtUomxXx05JsH0bibhmVLs1kNBRlL0xf9bxqQe/IenE4I0tzfRzFoHSrw1pn95zYgjEbQ/WFg5okuT0UKbH5nTxOHduIIaxtJ9rZT9FkLSgT+c9Ho9+9DR2Q1odtoZP/nByfsyvuJstNBT+AdOxDTIPUfkuDncJafTqLG5ccxbaIEw9e2a/IrHnsdiwl9WAbPDNnCR4F8DyLO4FxmrpxQvaolisG2N60DKtIzRzIDHl4YiPi8uNV76OFcAi6BPQ5b5QbO/cB2MUm7kJXn9ZlmSOw12Gvk9ycAzi0HSeAMHuTbP+9NInqIJx5kEdXGTtE1MmfBAun9HFM53e2EeWgLHNeYAOfh0UHVtLjzGUKRTujGPr6m7VVUrh4mlQA7dG+4U1eNO7D2aCsN/R+eaMsKFjkjG7XaxM9bMAMntlbNjYNlXNn0fGMzeAyymZupezeU6FpwYTJyHqt5etpBZ0m3N1iMsGQWPDL8OuZx/zx9gaPnuxkFGQ2M1/9JxcVtrUe7M/ZF+Pxebauj135Gm+zw5SSjuLt7UUR/x0IoY2o/rqbw/av+nU0S8CWsN6ro9cc1TbPgfI81aOPbHZqG05II0dF9R7rhJbW+Kmh/gLujj0goOB/HK4rc3tm5Pn9ETIxxwOMaA7FsMK3bRTTG6S2O8nmwM/O+LsMXxjrT6t3giSEg7uIvpG2SISoBYCW8vO3uMJr+8wg8lifezVXTpaAk33EO1aAgwMOGKIDy1/5d+k545cHux8WRM3iMyC8zqfyYz2DmuHMdw0J3ZvKvVwsZNUvCHw8YbkCaww8vYT6e79t955foSOYtkYwc0+N7J8Mv3nr80PN3Y0ccP79UadQCisOfPWlnWOq8zemEvvxovIPw3oDXr+jThA40NEDJttrXnn5h4djNfmzw7RtfM3Ovn362Ct2Qg+gc//Qz9ayEK/PB6zB6YGjlV6TU0KydbjocjxYeNi2NFzPZaurKUx9cfuN+evR/qD73CYk59b4OCc6EzQwnrf9K6UYI7OYtkqmwnxU0P5hhAfwwSLLviEDEvzhSYCTg82Q0LlVW/TlVhyfSA8VoudfRGcKcn4yqLQNr76Mo+lOMlZZUS7P+rBpgfnDQJ8A9mmdbnGutHk6AVccx5bSZp58EU3RPfUlRhwl321xm9h9XQO10Vi22tLrPY39divrO355Fp/e3M5yNY0jQNOilbXbCh80l5eUGCpm7wN/dse0GKYb3b1J4bjQEbzMOWYzDg1wEoCNnHD0iXriwehb46FfTuQxEwucPCUdON7LPqzTfbkuHpBq1O+yY9l6l9kK7n+yy6BKXuT+YkpTdD5LmfxrRU9OjT6OpPZi8NhvS2sx0lSQ9ygZZgyI/+t0IrtpTNxBBHjCNc9HmUyP06lJe6AN09yPHGLN80cNxQ4SilZFWQKZXDEGRvM9rlasBsy+wA0YBve0hhH38uzvkczccTgknMwhy/20QrH6mLvWFsWhO92dVZ3sfQdLlY8NjX25cXhsT/O9cW+OaW7bObFl5jtV1NVkckmZ3ZPL8qhmoWGp3wgt5pMNrdWHIm1iKtrlgbt+8fAV7e/4g75ATLJUMY4LJ6GhB277YpvScSzJi4i2k5J1gjkjM23DZ6U9Wfhi6nFgdwRh4EPWveuowx9HCSV8POk8bMbX7xS1Sfn4L0Q+JK3sXajtKSb0AmLXlKujtGb5f5QwHL65qIE21f43vDWUNumMqdPmsu/+esDb2ECTr4t3rzTwsxVG1+lt2/YhM+Tc/WtHrW4MVoO83DWTfDq3WPLhdvXoUwuuh6XeC6CvNnruxeeSwH34sgE6vPGYBNRw9HUi0q4eHCRWB2n4Mis9sM94lorZUSDNx+TAC6s5DG05zdeax99rM0LHzZ4Jo41Q0bE4s9+tR3sxoAdv5HEJ4z45Ti5IJYfT/Oy71hm4qqndcoi/sXRSDU1y2xhg7es+BmU8aQRo53NM4ztE6R8XuiGg+PsBd/06WQIN+cGI7ne3LVmO/0Qo5DEjC5EoXDlNebpB+FStyY5gqbf41mTvWCxx+LkCLS8Nw+4Hs9JkCzLuBzsGdtDFx89j7JZq2Vkm8u+GYHa1kgqeyti6Q5/a+KY8kSj33k+vG+mJJZbu+3OCu450FzayDh9xqr+1b2plb6Lxl6eHmOP5hwnfE53D2++/NXyPG9XlLWCWUOpb41ZkxV5YrPfT66BqiFOePH/ys1s1quUebVsF7LPx84/c9PMjSe+73/lhnNuzFnfm9fGxEQiFcLLmhtzb1rJl9z95BpFaE3+PL5//+HjH7Hxpgk2uP0V89j8+RVbx2gmT7Bwiyd2quETakTQvv7sS23hg5PXQl5vtzf2hY4MvzfUwbGuDS3JzRp+p+tHUXHf0pdv+X/S//nPf1rDX/+kD6s5MPXSg2pmzyft9zkODw1kD2/78DBgHE3Q4deinQ226mvUORLYHy1bqz2CBPcMoZnL7aZOYhbm/HBWp7nhmBje2vnUHjWJoYftDLOmLm5W5IFbY/HQthbWDTI6ODStnvIA6LBOdb6Y8hf71ISu0YfvaoArWXh96XeXsc7h0q6QiTOesIx3Lk0224MkUTs46zj7G8XMngJwdGL9cR6dvv4tBr72apka9eQOtPXefY/IckzCPR4xb58R2/6DZaHKasE0a+pj3sui6mlD4K6y5mQtk1YXbODRNf45Pj3qywCs+TcPHjEJG08x0JSKoMNdzPVtX8SgIzEN6xY8M/Y9x2YRfbU3f3mzjXFx5R6PGnDy3fMvTA4QcDky2ZqLxIqxx1MhT6/rjW9qJLYZCRuN8Z06Ccja83l49ti5x90k6oCXWGKKg0BF5pSnpomaBTqsZdZQiICmGtWpffjIk3H0M+u3+40r40XRno6N7zGRdXzsthb7/6yJ3ZrhmpBY0dkvam/GFzCWr7oDMUd+Zk0QKc60/N3C4DGb/qojxqFU812MzobKWbHV4XZ8tRTyVgSDx1M9H4m006O+IVkfdHTT4/8RC/dmadJisXfYg+kb9bznqLHY+Hm7xcqXPxJn4DS/J/RSZ0VQ+Ju6B6iYFrYH2cYcfV9wPfuPTCb3INRsaDaedPskGIETGCeo1Zbpl+X6Tn0TaCMOSSdeeMi1Dk+F9oaDMma4tgdHs75J/gKx73riN8XpE9zBLC9+f/5RVoznZ82pFU56jd9p5xI3mcdPAFi+PYWCIKjjVsSaOG5ei9MycxkT1jdIuMjrDa8hADPefpYpNmPi9GL05kXC1q6uAP30PoE+MYZgOT97bLqV27wKzCbf980XjGFPDflWqns2jrA+OjDZG2QGsk/QtXsOxtFzsViYap9YORpxtCfJzYivWk7c+Ms7/IDm2NmfmRO5cUBKvOxaEDL2As7xVizHFkCfi7QCviIFTHjm48N6BmZPzMahreNyLB92/QdSDHUdO6aI2Jq2Z2AGnf3Tv9OHZiX23BwTgT42DLGdmyam9WnNpnkH32YY+rFJsFqgP1rbx9UNHhZwF4s1w7jureX/4Ni4lW+cYXqsE/32N8lWy9YJCpvPuclp5JQXd/y9sWRO3OFgbQHNxZKxNXVh9hZIfo1sJllmtBDODdxzDYOHA/q4mXc9CH5Ix0Bt3GQCY8+wXmf5VDZfzdE67D8Gcdz4PjwNbx4weQ2qjt7ALi97XjN++po2PhmbWxy0+bK2+PxEe34t25v0/AD9hu7cvHsMwrf8UJ351hcsvwbeX/NGqAnSmtyc51PmH7kh/hF+KvMNgWjjZtpPz7PfsccP/s3hTfq3vsOZqIh96iADvcjj1/B/T094M+DX7//Jf6HWhvkmQ/zgvDnPHk/tdLDx+rlwUCWUl1sfN6TRzZwbb/rH/+suQ2x8eu4jPt5U+DN/nO576H7mTRBzBU9sYBnZwN+Ze3z19A1XF2rL7Moy9DMQZGPf1zLjY958yz9ptNuJhrbfow9MtSK2x954jovEbDo3nABKApuvVrZSQWDFnhmCDBp/jRNTTjwDGTv5vo5gh2qxIMyzRWbt68cbGjAaFtJ6FBEH+61huAqImcBWeOjwxS5X5svbWsujTdYT9TlZIbEWWz7mKeb0YTtjb/GBz6OKWTUfVjHj3bjrB5tV8q4212yG98aPx3TNWdgeH3rCd33WzZSawuV0tujEUhvu1YkyfB1yGD+G42G9qOp/lvKB6Hna/KwZlEV3HOH2ecJ6NGoHQ97YQbYHLO96GMRkQ4A7E+TcKLImtm+NkBZ9cXsMxIXL+KGsiIefaAp5xge/dvAXQw2rSaahuDdjUychhk7VyeNy93l990MGckifDbWrp1kg2E4Bai+BlAu+jQHH+vS4yUCUY0qA443Tb87BGbGbCYIDefwMY2L+sJij2MPpMroXk+wCBZQHiLUEU2+3Hjt+Rq5/vFs3+c5xffjBlwHmGaNt+7FxvfZpL5upZRzuTOCCsbFdmeE5PiA+av5yzbvHqGTLFM6h2/o9fmRLPY49Pll6TCfn1qGOhTZCIRvfNgPIH4nDbx9oVtUe0gop0OAYSGJSo4hNUL6vkJmHd5tHjh3myqJ8WK2CrWNFag9xc42TRMO6eZcPhPorlxWmjGPoUtNkC2TrETUhV0PjyxBnJpuXmThsSWyt73y4T1LXodiDiL58bz2Ib//BNOqc1GE3h/mVIRZca4aox0ba2KWAE4+E8I9m8z45Gm7Q/pZEtRUzQptLUwP2+JJrKQCdi+6quF5FrbbEPE8IaLlQXM4pLOAwc95ZKKiOXbvXhwIGNXZm+s2ZFw1EbpyIAHVnr13I9CgA+tYOggZ5qnSGxnMODAKkMYGqI2FTpmulmqeM4DuqYc+PVtNtVaJlVKArL7T0Gd34Xzx8iyUCHWedibpMen0i4M3XarBkcbLo66z56Mj2aPf05MaVHwpeS9BQH5Gu2nfttRk+OoAcLVm0Ts7jm3d5iJYmG5nZWKgrY8nNas+B5Yav2Pi4GSEOQu6Rljiggx+zOjJ3NM2ualoAfMSvN1hTum7P620O7iFLN+vgGhvsqwNgxmI7mZjBIcGG5Y+p8elp8zbC51Xctsk9WY5Kp3vukrcP6DzDC12qMH8873PvyO3jnhf9TZpq2/aSGH33BjYBjNj9lHtuQGuKLuzj92YQoli6Yz/aZ9+coyGJuH385m8TUEO5qrmxhKk3mmDiD9DxifuvP/0rdL/8lZvdX3kt4t+kWzeb5mfdtF2T20/OY+Tff7vmNWhH8Nygnht0OOPj5pxP0DNDpG8qGIK2ifXfloOwpnQZrsQ7YZGc8MjHGwzRwh9z++3Pf/zyx1/5NXeo+Zobb2sh19g8ulnvMSctWskvJwGP/1uOE9j/+Z//sdZf8n+jb++JVS89gIOLt/Tw58RwDvrbA9ScBPA7yJERdHNG3ebXMIserxOlDokCIvYdaGTsMU4DWFxI3CDECWXT/A9KPFSE9pzDa0e7xodlgl4dW0/35ReWKat3NHzrH4DEg+I4R4j1bHTWXIAXlhgw+Toa4lgNmwt/caP7cFTBRi+P/anLgMs3iClkfz7ZqyRr3HI2OyvshmSx6/aVngwZO2spRpbnZ3qPadA6ym3oE9NIONvTQX3uBh9R5lu6owP033xlBnN6od7Whm6Hu6KqosemlM13gRAEKw+B4R4eTIxdM68t2QM1w2IHvP2xwaIF3sjgPT7DtJqxbU0nx4kic/N1ZoHPNBF8x1wPOaNObaMVfl7ChJIB8Gph1ciSlqfHuFzWZRLCelylD6jnG5EPR51bpTEgim1u1rH4fUKzNLQeBaMWf9k33+aqcrrnmNIgwWJfM5ejCOeHi5WL9n8gH3Gn3gDloZcj0noICge97Z6eN0P5Eoc/X8ulPTZUvhpday8e3Mslq/XMOTtE2kk+Y/NVz6M3/osC/OljzVidXV0tG22pp6/hyNepg0bg+z/6BAftsXdTi2lrNH/PPadyoVlbqKuJHDK5xraaiVIPHh1YMmbucRCx5nyCfgOYMVKAu65qic0f5m8yVcQ9TSDSooiABY9MTakhG0znxuIA50lM7jkwe1aFs7+SCEHH0Uej18jeRjJpXmfyMBv3dYlq/fUXwwFkls1zYKyNfNSYq1b33CSBEZ25IaOIOepW4Kw/epIcMVcu0A3FKBlOhsHFskIgWAMEF5NtU+LE3mGWgXHhJoY6wsPDT6QC7c3JRnVPCtK9o72ojtZPpQCDGnyuCUcLkejJiJ8f2n56H1OjqqOAQKanXCzG45ZAsNaduSM7Z7PEZj2JL46cRol7Z7JOs62NzayJ6fjck8ZanWReg9AxTRwMVa49G/JhbX/L65YNrhn2NQbiGetqNIYwbeCJLdYA4vptrPHE1BnfOGdN5GI0WRS2qwH76gF82qSW4zHc5BPrMQiYvTdBTdQ02cZcrsEcA6J24PtIiqM1aIdTQVkdQhNVivASNr0BCYH3GZNTr3zxZbG6rWHtE/bmL1e3dkSJ1e5abdRshpV8BdRcXTPHSWxZqU9DY09kEWIKFHR6kSBLG+3WYSxWRR4m1pOiNvliM3G1z/TGBOOvjg8VaejtPhDNnCdLttlzi0xr175Yna1t4rGITA5jSI4Ps5zd89rlza/LfEqrr7yFGoE33+HIEwjI0AHJ6E1ibyozB5ABhpvz797U53WLm/W8fvrJb5zbmz2frFU2Nnx63r+S3v9nnE+QWfeFkddA/jjcj3yyzeCTeUb/wNp8kj5Hv0XHGc698eV2nP/7/Ttvaia2fV7d7VUS+FrLp+d//UjvzQ0NDeB7amAeHuq1JmoT4BZZp+aaA9zYzHiTgZ4QS61/Rs9/5t+701vy0dP99+pwmCy/KeHvD3BtoSYcM1hbOBpTY9bo8yx1vudQbPuan5C+wQwHi+yGcmvGtnz6BTxAIs1N4DwnHlkxOoxAECOLVOl0TSaWgh7WJ7Dw2Bprv5PvIJjgyrFC542JI9/FFyOUXuSrmscfEf00MCHEDLs9JDT+xZO5WkB9cgU6vunD8EiKM95uLTRTBTapHiyo3EVWima9MZkeSPOsl/3XYT0JXR4VZLE9eFj9WbnpxJEz3/bh9KDJtyeLJ8HptVUckfMzuL2xjx50Kr198ue0IbcDamDj6+Hyl/c9NuRerkwcrs2TcF4rLMWN9QiK3xwsiHNRC9vN4Z7nHMNGDjQxzTs+3PmyD2LPJgGcYwK6QRtrhvtsHtseH5yXvdi95mu/X10P0p6Mzk1kism7ucO+/2Rma1sdsrEJFjiakCjusbUHGOI0aDDEJMD+QbA6Xvv6s7c/Q0FMhwnNSX75cSEETL7bb1TgRuN9vuqXqDzSEgqWDXu4GNsz6vgyzG1UHauFc4vjcbjiXh3MLvfEPbmw3PNnoiqTQuxbo0bo6NrcfeNmEZwnfU2SKfHtJ0TNZL8Ggw20iQrIthygkSHePrOG8NUEIKbptX4Y4J2Yksgk9mZLHmsZH9Q4M2bn/kbimOMrt0nEm7dJxcwfibuFeCLtk9cMT6bJgKUFCJCYzSluivxoUGJXrAUjjAsG9hlijYOoFrPgH8HNi39sYxfuhriOod2l+9fWmFQBB9mzQ9fWEHGnRp+Q8QldRiRwMmsneBy7H7H6w7/96mGxMmu+gcSXT1uOsJpiRbcaSAI/3Awc7DSuubk8jgZin/yDJ8aLTCYZaGSI2/kUuz6pji3YvzUjotC1GPkq8Sd/qGjWaD49kLR5BUxt5kyIUtzcGpkRYV+Ty9pjagXtBPMzC4bsrKVyQTxS45s89rckh59Aowdzf5BgB1bH4Zg8xMinKpCyiK8ugqMJDezzNYjaj7NWalXaScRKBeJLUttal7cA4NOrgDefrGiAN8McydVezP54BrOijakuVN7jMTxHa33SzMbja75kVPbU+YK2PvUFRg8eTnMmuHUm0Algvifn2PaF3yyxUQIbU8/FDlBGrctR2vZu5oW53WNc9csw/EU0B3OlBZMa9gahfUi0vSwGqOvg0dcBptq0RXuzjVoLAol3dGAbXlD7z1bkW5j7Z5HXHLEbN7z95yTwxju21t503HxtDf5RtInfm8lpuKnVaMrWVE5uPFu3PMYD4oa7OZp2zsm4vCmfvMRw8+mF69hIpl2utmJb0n254rFN8HEDXV7w/dnEr4fLGyH+unhuRvl1dPpELxJNqs8RE/Fwfdyc59fdSUZlfEpOX+9fNu85i29vdiFtX9EIHzf1UmiH3+cFvxuAzmDUnX8zT9l7QSMfN9E8xLWpPZatw3mS+8+aogsdbHqTmP1cE/S3nNAIglh26Mo8j3/+/Gd/1f1/f/7yxx/8X+s5VtnQB3KwLy+x6WV6zmf3vmkLTx797QmTW4NvAk3hcZsXzlGZHD2G6KDmvR5d7P5WWHsZP8cMHtrgnlx819jnZ3o7bzpsHJkd5MkEO3vHk5f1+te3wGbA2jNHvYNXQQzKQrzk2XzJYyygjJYQHRwP+9DzSPtgti8GyOlsJPUc3l7CWEi2TCSaoFeHFHGik7xZ93yafWzEr00AMZ6UBjfGqdGAzde+EhwnOSeHUGwZ2Mg6kce2vcJevmCQkv4srxTY4GUAJk++PNYxY1qpzHc0ohayV3J7Js0CYfO5en2wooVhv5l/1LYax0+yCVitq08XKocPTrHLV6GaBcXenNHjuYL1amuP37wTKm828iXZ8NvLnYsJFzmid3mrbQRWsKSv5BaQOLlGE/MmVLM1G7noWbAzX9ctmexEr1YwGgLNBPN8ZafNvmS+xxseQtiurWuNhOlbm/HwTj/0Ti7m5vv/dL3Zghy3kkQpiaIoqf//Q6cfpnW1kGPnmDuAou6gKgOAL+bmjsgFGZlV5nTjtUYgEBgrWiwJeAmEAWtkBPWaZd4sr6gutcVma6bn4ueBcT0XV9ug0Qwd2+NLDpPT2qMzz9iJPTaTydRAuB5GoV8kjVTfk8OY17RkL1MoTAKnvjMfv+VT3tSgbf0au5mjaw70k4OstjKNV6zVw/vWtuitQ7FXP4GtMr4fsbCyZsYb25Aoj8XQK5NWZ96+b0pLHP/vi6dkqqs1hwGpdxLMvIvW4FtkTSGbHxNNoS3AFh6/kdVmyNNFF6WCHiE3Mro1XVnmC7sq+svhkcZHHitifmzjkd/CDt+xq83o8fgXeLLAV7Q4xWRfJCzovmBuX/t9ZeGLLHhYk/pvXTbUUDmxN1btpp4YSRMvbm3f18c4IZmXSace9+TGpy+g60ct8kLzQ6MibY7I15/IfIVd3TKYPVEs0pYfSgTzAvQ8oa7TqDvFqS/mIrZh/31eLl60xknvRyk1mmBRMN3zvj0VbNuaVqChQ88JnvDHrpDVE00EQMCvc45rjdOO0TLuei1fi9ITzwfN5YVlYevvGsWueUeWQTejE1xsxjQiwY1o9e9ksFYDHmPi0yxQh/KIbv1VrR2muS1X/YGokQCdgs108PVKxDprx7CDjj7MiRdjZQ4zksPtqwN/ZA8HRWgWZ164Ea/3t12LMhQrTidnDNNOntHU5rXHIj7GwBjs0TfR5rv0ME+DsS1yMCeDii7Amhy5duLGZ3cn0fY+XCQ/9QNifhdbgBMVlLZzXmGZX/GjKt5a9f7EjM0hGyYMu9Ht5rTQqRwAs9kRI+TUBbwAACAASURBVFxnBQWzThq3ljw+5BGngXUObiwtAVhpxDl9bIjPTaztY1BsTZ9DK4Du3uC83xlno855wF8pz0fOc/X567f8QTfyzG030OSynNpDvDy293+NI8vG1A11WLAJZaP7s/9DXJdcQWez3ZTRw5D51hTySL95NZnvcrOtrQ0fuf/6KTHC+afcNid9AsKGl++8f80G/We4TO1W30Dlxbh5tccGGRvwuPriHlof3uCFWb5Y7sb2yw/ZpGdz/lc/5g4n8w7GbtJJbs8luP6UG3nxnX+WF51/LJD/cb+F4DmHc5uksWmnCF4Jk9xHwTjnm89TY0gccMXXfu+3MdhX4QJjE4PYbjtcgY98NyGrp1+blfU5kpqU9kWrhTwc1oaQxh0AckKCX22H18jMpUb1eMeV3OODvV8rO/7UJWtrED0yZgoegbk9bafmq76Szjs+NgUqRITUIr9pHLseqzT3cazNcMAcjvQ5Ht3rH+HylQemU4+dqz9yUBKsv8Om/DCBaE+Jkjaq3DgsAwxXzziasbETvLadY5B5TtStNzmDrRW607rWaPDd+Gu/ZrokT/Ez8RyfYKAx1AfDsRNz6tnIU9vx0yPj1a1YbJiOr/KDCaPqHE0u9QExLbaY5DeHtWUWub/hoXxsx3gxXBN8wXmasMYDv7jljmltjTnPi47LyLgLZZz4n3hR1DZHfsVaPevSuiHeGq8veRSv6OqN3/XGA2zZBaB5D/9olos20TOnmSZ++CgZDGToF7Xm18I5SYxhjWd+ja94bRtb3DegLmsN5oMx3CqZPK/6chx2u1ZgLH8e6n09Hz+gqR/NutLnhmTtmZz5VU6dlnj9jDOis07BKoID/TrKUbzNI/2sLfqeE45yKANmjZF15L6uPLYs3qlTxvxmrhc65zqfXPD1j8QV1GMPxziDtIFxVAnDLVvGBjfG2EaWthYP9fAgbBMFi5NtX1PuYq3NSYjENI7DEkD2CpdDQRMh2sjWPNNnjLZtC1eub5BIxmxf9IoWk95htvTBGSqHt6II+c2jtouKbPLoPEo4U4scsbXPUP0GV99YY75uuOhHt7GROTbWImJRTaMMpxPj+gseeXPEbxuy8l2Muge3vxrWYmJxRWfcm3u0cVoUx0nq6FCk9SNKvMhCMMId6RxUigGB9AypGbe3sabUotLhhIF+DsZiReWihzyp+/JtL5+s6dZHbOJCJT/InRJjQsqL2mGGPE1bsUWQwJhHS9TY5GD8AK5ffZFrVrsGfDAGiXg8SKCPZXkE1+nHHIwTK9nsYbjiazxRdkS478aZih07mpiRrVXjn5nBrJfW1HriOxfAkXLdxuIZr//yr6sJCFBfHVTBAZ9BOuRWrmf0W6sajH+6faxC7lU8Eh68C4p2MeqbGcLmbBcebJTgM/N6SXNN1cgWTmIM9/jJWYv6cIR/I16Z87X3pMKKW1pwaZu/E2J535Nea6GiB+s3fpxf/PTfibGR7YYMORszbLdxRdKruOkTQF3jlgb5sTEzg7idNwIdN+/FIw6tV44/xmpctdpwePMDg3k3jsSpPxvIvXFlV7/U4evXn83v8+d8VHzuT3wUfZs1Xz7y7yqAK3ZwyaUVz4Y0sbmCznfao+B3akxOXde9cm3Wkz98Yxj7/mszrP+O86dszv/5Ozyz4TcmKLEDi+Zm9afYRa9UPqzxXQNtso74eRUdx4zFiRNrkyWbntwlbS7Y0cgrLyh++MIG/fffreXXr39r2815+GYK5t/5IW+40+f9A9+F8ep5BNjc76nXBw68iZzO+yEvcLSLiM05X8MHC27UwdYHUYfn/poZXFvbYjhuGnWLnnZwMrYWgwsXfjcWQyIiBwvbYVAzTJEtr2PPwOgffDGvlNEdH/wHB9xtphtd+SyDao/ViRf5bM7hJefpF2/Jb1zk5t5Bk8YoflOQQ4f7yvGfOOOg7VuLw41cxKqrGXCYxyPC0uQDVyb3QZmZNb56LLBrL+oNMXKdrl1wm43ow4fxrO32W/caC83dfzfgxp01Nz55SWPRez5MlOBXvX7UoTrs295zYk+ws27HJjhTx/brTX/X2TGisd00alU7OPBzeIytsV3T4WZegrX+sduaty+qGd50CJ4b+Okjt1eUqDM3PhMtoYtBzGvQcY674Vm8WqGYOsudeX23RgLk8J6PRwY3X7vphKv+940uHZXBX5bh1dgcMzYuWWDWPkMbOu97JRVZPVEe+XhGsCN9TX/NiaFPERpTEdIHNnY8SNDsqHiZVYB+YgdzTdf+rs/Ei2Lzw0Ypfhl3fYoB80btkZjaTI8vFmDJJ2Zaxmjx7/psfQloxFn7yLNWRorzsDBOg40Ot0oJm1YmIuEH5tTaNcj8xJbU2uCJYPjoxlgkYVmjwt/8iz/5EV4MfMpveaPxCvqSqF3JAPI+wGqTO+TKCpfjcLG4hgAWYZktLaSH0iSvSIgcNhGszCoDdE+x9oHPWMhPizP+tsp9AiYO09GtC/DiRuELJ2OMu+ZT5PiWS+fCLDfNF5hJi9s8Hv/BQ441361umx6594I772iP4FqKcGmvYFDsMMVomva8+JoXdBUP/qBtjV3n8Tsnd+bKT645ZeLui9OcA1wVMWA6R9jlBua6OEbrbw5yTI8ndum37MsBE9dlF0qDYq4IfxzXx2nA9RO0GMTYj2OauaEnPhA4clwumZUVor4QbuWR157c9s0D7kTYqxsMEAfY4Y7hogp/B8StCQhgTYQKnSFDd1tzBKQeT7H1EGsKZUxMz5MoMQka3svntY1GLbIMyguX8tN0/C6j8Tm+M1982TcHsMV6YnK+bR3Lrf7gN+/y3bzLTyC5Yr26VgTWWLXd2nWtnE8++G4dtH5yE2E2YsOAqhX5wpd7/N4abY7E8v5i0BwGv69Zg8Z9PrVQjW3RS3yOuLzn2yrJmZs+sWFTg3tDPZjGjII28dGeNw0N8OjEiT3nTBrHiwbErTd4bpJj7oY4ie3m/PyLMWxmky5OdlGfIvuW3dhP2Zj1o8Q38zsi1mzuwY/P8j85g/Pdbe2Q07a3ViPzfHl0y7l/bZ0N+t9uLPuXyMvRNx+42h2Mr7maznPL13+SETvWtJattTEmsVgSHn+lXj4R6JtdafXxBYv2F/vYNPz7xuTMqWv+oBp/BI51o574/JNN+ub3lT9ml5pyvhF65dz3fVMk9pX1DYG3HkTRztUml/DZ9c+YuTJS2LHDPJN9Z1fufYaDZ6+i/79+5J041Hi5/ZxPJHS8/XDL89bGfPs5Gc0frKvLOEnzPM9XAD6Zc/M9H1F3EeKEHQVK461jKk8OszrKvz8Qx9SjuD2+W9PvPXoeIHVlibkmGeNXpCPcgQ4+Bw9HFI0Jh6LQy+l7rIljTvjF3NyQY8taITxIoI+MdWWaBjZ222/8avHAMlIKrtPl1kqhHps1ieHWXRdMjFFUYiQgQm+NmaHiwcpYH4Iq0mtsIkpMa1Tx2AA8An1q4/MO8f5riz310I3DZtW1qxfjNPgOTrnN9PHFxlpqT/WujzolxdsaYco5vTUBzrojY2zwyYXJyJeLKddU+z1cHoNDFrjncaO6E2lquXYTlGluWsEhg3s+bBRyAbTzazsCxR3fcxnh+IFrm1plXNEqxndzfqw1NBeEng2K9nl489zzyN76PXnU46A2kcT0nK74+jUG0mXneDA3vz1PsLm+WM78eG+m6U+5dtDe2qL2/Lhm93ytrHMj5FBcY2fMDDT5YXIkjCONUg+MJhZ4nSKoHcfaKRg90rSAuIL0qcflEw+c6lL/gxzhyMX4cFje6wiPyxWpXLbf+0V61/3EAHQsB6p16P1JApETrRCZMAeHwjCh68Hj6rzPoqKZf7qEWl6IvZ/Bm8k0xvW9OS5mPvFGAWMRq3XGb+UfgLTdRLBKm2CSEKiy0qr3DatHniz6zj2zoxsOylqZJhF8CJ4kM7iLHevR149jW4uZ8YcEOi3Wcqt9cy/rPVqTRKacb0lho7fUPtbDwo79Zd3kfDGWISeMjVx4gQDOUL1rURMsj0wbJUe2hSk/UGixATOOWH9sBOV3bWMaAm5mz70wOkhNc8Nap+FefNXYjW27MNGVA4HQE+upIOs5Pqux/gAi2DY2frwyslWdtX0K0/M1uMpiO8bt+iCxsLeXqPyfx9+en6zRg6Fl5uMRiHkAeiQvrq4hIS+t0fZcaZmDRAheONHIFfBzcjuJKHGiM68xwRavWuBMq83GW/3WqqWK1N8cglHbPRPKrUiDPwFcOcZp4FpcuVRYs+uPCemwf7E/bEcBBEZm58ADsiKuLBKFjSDYWNR/7eiHxdrveSDgU69nTTbzemNzc8Dd2kfpd2DXDzlJTdvx2uiFuoln8DKtH8eVesUQrIUcBd2KUP//thiah3513vu9GAFhky8WOWRrojwjcuS+2Q3+d9Hgn8fpJbr3q5tvMHMfYc4bdnslGxmbs/eGDTc2tGx2P+VPk/6cH6+awh4i+e0bf0+moWC88RcnvI1LRvklTrrYdTOMtz5Pj2xbeXSdxZNvr5z/ncu7fG96N+kEkFs21HhwY2tHXb5lU/zjj/1e9WJTTloYkk54dOZ6ZOKV6eSa9ybEzTY7/Kkx+f9lbD86jmNE+rN2GVib5OhaTr3Y8LqZTw34uLz5TB12vcQLDa+eb539bjibZcP4eIeqreuxa1KcyHwvgn7WC4Ljgw23swcM0K/5f+j8SzXW5//+7/8y7nnxjTcavuXqeX44B2jLkRx/ypV+8QJGvRo/oZjP5j2ukcdx4s4wOeZNipDiPNP2cO15gp015TA3YopVz5MTvGjUtHnq3cCeavUTDzut2+9z28rIAZwiELswAHuukMfwASazI8e259NH2doYVuyDnnyG65LDqGHFZqKN+timjzq6jVV7CtNchjBG0/RAnPkHLoNiUcGXSzp9Jwfj45h5bMCQAB12UFoBOgUCODxG4ui9Vvot3slxOIAKV4MNH8dKlxvqiQXqhgVjyO16FCqz2KjGPm1NQdwJMI2dwTpgnLY81RumQbc25gP3uYMVC7y04STRUSAvx9VjKDADAuqnTXyKO3gmDJNbD0MQHwzcPT4xnJdzVSBjVw/z2KIc3+hHNlblPC/EioDx4rYnNng0x47GOmIh0WXAOWeOCJVhkEHdG1/NHIYPIJ6vx7a1WFP4dm1iEC7U7+SI0eGHfsId2egTY/OQk+ISIyxt67KztTOmBstD4wQqYf0HhLBNi/Vbu8XufHkYL0anblE3z8lh/emDdvysVyoN/Ymrfgr9Yqi2JuVTl+MkMjIiWuf066/YQ+wT7PjifoJHSsLbIr/rUzPV449ZrRt1YxLfAGsATn56Pi24FTv8irCA5ahlF0B/eVKvhdBpcnlcUGP188lFZYuG8wY7YwbKa1N9SdcmEot0E16MesYK/eBM57ziJN9HcRPGjvfipb64Q/bDZgrZAevQBY28aTd6uaPHGK5Xf+6M4uSAmsPT8BN374zMNdV4zgkB9LpLUBweMMTMk/sZizlBcJ2QzRk7XqBkFrk+Uwc9lNUHe/THH5w77YQjMjEI1qbpcjtCYhaz9utXYN9gwOfh03G5SjhYRMnrH5wX+UNvTSORu5rLq4axGNHaMF3OM9Lfeke5CLUvX7DefBZLGcqNwTht87qsG7V8K91jXY0eXpGikPSMwRM0/Z7fkSy/jSXO8Bjz0Or9y/VNDYVGCT7ro0V7clisUoiWus86rY6rB9gWpmsoF/Cm2DvHzhjidKxv5uZUmIEbf2zT7oMixDYkgT/6aoz9oJDz5te8hyyGhRpL5tUR8dQik84jZHBmTk6Nti5FKPCuD7JizDmeSd+k4oW+NLyqC9etK5H2Ci7j1hJcsmjs0g3TuU/LuibxiM2sFb710B04g1qPzdk6gwXbjw1Oi2EPNI9b2dAxh2flwyvuHWFYLPQMDxbxMIJv7tROc2CDQ226IZ9NWGReRUc/V01bp9ixuc0P+GDtVWiiymmYOLZOxUQPRm/dXBLzgxxfOKbZxR6ctWP8zsFCx6aczTkfw/47f32cPprQswLJN2ub+vGx95/yyfdefWVzTC7wNuQzID4bTBRV8v3qSJwSly0//myy5YXdtz+zNkXXC//hGNNcNW9i2G8NGdM+Z4NOLj42Z44cfGD7SaJxzqYYHd+Jh/zBwZBf8PClf2WDufpMte0cy/FX/lmM34PP+lPbr38mN2vN/2Tn8+yJzbmTN2ucx3av9vs1iDxO5WzxvHWjzvN17I1nDELw/EifFzL5+oFXzP10Rqqb9eLH77Wnhs2HclKH8qK2e6MOfCrBjb25a9YDZvkxNjyjXxyqBOIry+zoF6C+WKbh5KHzxVopiBtLdAOML0aN6IghdOWnRPDqEsMzRVExTw0XDl1qix0o6w0ev503H8c5UDY8bM7xm5xzn73ca4ID6Ja1sFVE/hEnNuf11fjaETCWu14jGwZDCCIDm06dRCu/9cHGqtRGl8WvTlHAgMPyXbtKsYh24hXICtTDvEbN2AXC+IODOQkz9g+hY0mkZrPxyCxju8kjY15amCP3k/HAkzGtlvQ4jruDzuutKof16mjX5OY+Jrj25Gvsk+fGuTieNLpVJg/WBz7geA6WxTJqRVs/z9v/cm7suVaf4glnTZutdQk3wlEn0uO5/n0tNMIoM5r14HFf/KceG+dwC6fTDJD51mFVxAV3DOlXpRw/ZHLEONLITr11uHzrTz5TG/wXQ6TNAZbXTgI4Ixs2fpoENhKJyrjlggli2jmHCZUf5tXlOJh5OJ4xDh0fP+yHYzSrvrhIyD+P8QNsnLVFtzk2SPCIQRuXmxOicKxKv62tsvCgtzY4M+PXPDxkgkUanOV9bcYiLjvCcPggUlwdKB/WCcvgoZXTYKxdxCANhh9xb+CelN+NY1zwuh2vQ6Yk0G4jEE0CBMpoC+cUCQViMejfcQxaWJK9Y/DwPRwz2TioFs9xEPCleZw4CnIofmdFmRwoWknrh++b3YkRIX7LEyTG6BtwHAOAnF/kjjXQGjdb44wREoaxQy4hBzOOsnXTZGwxrJGuAEztVq42hzc/vOSs+yinbnKduh0bHQjZn57MmZ8XyQAKWosZ4/Y2uLhBSN+acR5I+Zjt+imAk8STO3nyC7Z9JOk7oa9C0QF9ZFhWOTGZRJ/ffRJyTO4nwagzds2Dec/LyOsaZ/SyMID1AzNCw0W3g4gPlmKMzI/Zbfhhu0dGRwYPBGPBZNdpbZgvZ82iqC7yPBlK7rUBP3P5tUjmShT8TsOG3HhiKsEaZHw4UD9eTD9PqOIukXEsn8UfsImNtPrKEct7fIvXmGtHT7OH5DKPQM6ACJdDBJ5n6fnp/SryscVQ0z0yEbPnL7muyFoblOg1YxNuS0xVG/vYRR4bXgRgoDgue+4zB0G3DJajmPAAN0YbuyLuSzcXxm/bHMHmPviqF6fpRreBJTZxwtJNILDrT58cwAKDzTr/o1z86fcPpcllHi9++rGf6eYqejdFL9PmDV/CQ8VNs7ESgx9jbT+xI8fDvONjTpzrT4P/1oExuLsx7xX0v40XZ89fNnbw47UHpzxc0M1ALOARE/usH4b+RhZ/c9EZm0KwTeWj9D/+hWE3+3+ykZ389v5IvL7hcblvHAPnsG8w7Ipv7+aW+MG02fUcAXM3rqVGBqHCKy0GOXyUw5N8VGb49mOLG38wLjaoWSvq/PV//9c3Bfb/1yPj37PtOjJ3Yx6n/Xd21izc/Yg/YLkhu+dLN/vG2hrT54YNOfQNIDb6qW9iICQWc9c4EuY5yIVzYd9AMH7ikUMi50jrETrnNHjvw1pMrWNDY7ZrqQhMnGnpwIIXcUYae0XRU8t0vjmRPn4DKycmesX+PqyvTfFqr2FjIcCeEPJobrueJDYmwydzE47DtMMUEFts5rw4uUUu3/iK93AnbPPGecisPaI0oedNmRdzudHTtBOb86Mxq+n4cH9yWN+1I2dwugqVynrwFsNKPThEv3UToGt3KjgcBvkDpmGQwMYsZn2XXWRNSGAYosF+66obxaw008FRkoP9zUp9ztdyrm1dgjo0Ng6+WoxZa9AIpwRjgO5wWsfh/uoMId8BJYLDcmwtyOY21z6CxX/7CM1FGV7juE+/oCCqvpjL3Tw3vKrlxGTqEXJImztUawMGMcAd6wl0beB2dPHb+imcAxZSBnBb/Cqfmoxq+b711PCAAFDjRVu+cFmztzdkjD/UB4xjP0jmkjFTAJwz5Jy8NqjQIzlyzXvuHj6rl0z95ZChouhB0H4WTOxIV7+11zI2d80bixPaNcJjnBcDH0ie15SCDmvGuTU37Obcfpyx1KUwzijJK1e/vKZe6sexNY9khNaLMWixZ535Yl2mqF5DTZTr3IPzFjg++dXn0Mw8gLYhU+za7cLUJ1bHJj6QQQRW6XwYK+SJCvzo+zzw8Q7dwD1uLGfPOzKNcW2KhzSNQtonxHBDcrDGjDl+6hZ7dOI8/LE7/oTIbV8vFruxfGKL379gzBdAlDfm1uE4jIl2R7iEl4HRo4XTjSXHyde8CYXNsz579RAkxUmi45kHj9j48FP0Z2Qe1+bkiVx7dIma6cZeXtqOHCvMm78DRZs38rW3XvgZI2arW3rjuXR9504ZBvBo2/VSFgyzGgyga50+g8aac1kd44MkIDZbW3PlHEqTO6ZTd7vM17uja3sCwyjGuhaJVIdYz1XFZd5h9JfDYFZTvsOhMbqOi7E5wrOeYZYBY8OO0NoMjroKhMFum2NqMvel+4KxQMZj6PSJKV5i4vvGOZWYtYor/OS291eCDx7y8lFwvJH6B8sqNsaJ4wt9asgNA9ag8+bj6/17PkQoz2C6KQ9n6Lv+8W0PkYw54fK7sZxEVb7twGre+KCk00l5Je8x/JL7pKL1HZc31msjNxJigNwcqScNGfnOrbMz70ex6+NmLLVCxtXnB7I8ySMP5pTTDRXw0xqrMdg0sYnicQiME9txZbipn4KQC/TBMfMCSt+r+tQjeL163qvmf+Uvj9OoLX/1nI0afxiOjNnI8ofd0HXTS8VnTKDxc+M39hBwA5wdFia94ltbBOSxfzTvx3wJHWzaf/7zH9/gYAx3cs4ZNetjNiQLoD3qL7/8Ip51yhws8YjLE2aMduOZT9YH69+bffLxlzwJmbb5LLfdhN15do/TjJlY9L6pwR/Sy5g8WUNifv2D3Kg750U26aPjI/r8lfzju7WeHh7wI2U36Jmzwafx/XvW5Kef5iq6bzCUh6XDKY0x/PnZ+rWMmceG2HDi/GguiWkK81gimFBiiSkA4FUaY+I1Yo9HHjvqUUbB9cFp+MBPzQSajmBAPlMCEl57sZLX3i/gTjNOxo1Xe459jNVElFqPPWKD9XGpdOIl7/qIT75PHMaNM/UNsrHGhknjcOwEPePNmX68Rp5uyI0XDh9aY4pYW2o7/DEcd2VbDwEMPvelsavf+gzhBw8X8cjdETaRTC2mIzvFffEPNyTjq3nnK9wcakMEEVRzWDwGO15sa3dcMlsS+GWMCq/2NeQpBk76Aigq9nCs5bDNDEuNNDD+eOx55otanJFPTO18LjPYiaV+Ho+IO8giGhnzw7tsxJrzSJ01v1yvffBi3AzKfDn2NQo5N+auNbOOjSIPEQ4PByN/sOEYHuCShzfHjY70tIHY1zZwkGgMsJazNgKIhq/csMAobboZXyGjeqK6GFQPjtSHpoecM7eG9MSvHlnHtyatlu4xjd3zgni8orxWG6+64DjoOpbDR6+1n2wMtOPmD/z1WXt4733A6JpcO0bgHAznZLA20e4wuq3H+ik6cga0MluUnS3QzTIoW+cFRFSQPh8znrz2tQoGnsv4sj5p+YBZHLcAT/HVfjhM0KAIMuE2vuSC4xxwMCeIBOYJBMgWbdMZn40VVzRKyzGaM3BIDFDachI44Fgspib4cnBcbOwO4g7Qp9Vsl0BRbJvzXkkl9OGXsScNQlppVDaYylFHt7nVuneEvYNsRQZCMoNaiMEgtraPcmVXNMa7BnlRxAvEUooOLrndihlC+aby8nIM5KnTEwnZ5uqQSwoD9Z09XrxoLd9auVYkbeN7iNQ7/umPWFKZH0EGjGO331HHfbGI0Bqlz4s5DU26btgS5KzdgcOzDXhDRLBX1MFkjI2xHoy3lsZeZ+GcSGNGwSC+NBrQWhF/eGV+75KR+QOZyCVQtw/HiXn4PUpUNp13Mj1rEnltZgy3VZM3P2Oz+Ny3ccKvMvp6WQPl9StU88DG2m9MMYriuTaYE35QGkeZIcC9sQnb+2i9QKMZKwx5sY2DrqN0XCOO4ukBML/0yPPCXVF656B+b5P5yclzXFNlbCrkETlrzjPXVwZO6FotbfaFTd1NEG2Zd23gpi+9L3gyGCyIlnX5Q9MFclOKruuMuJY54qMh/dxHGcALXDbHwjQ+Ks3BcDz+O+a8yG8/As8GXcVcHQY2uKkJdfmUK65sjPw+tUQL6oaOjT01T/wTUCaXs/GVxY/eUM3DjW3m23aT301/PtKejeM/+Qj2X37//K98VPyzG1k2458/f853u9n8UYNy3k06gnt1ujpk/vC4pQ89J1305AqIk+oZUnM26T9mk/njj38692o451t+qMvaYetH4FlHfkg8jaMfI8cnsuZYGzjReCxFR5+KZx0iG38NmD+2mXV+KE8uUwd8MNdn/SqoPPn+mD/a9svosC+3bz/84SadN13CO2+K8MYBfzN/XydQV99MCP55MyQ4bszD61u+p/4z/3/mc2XYuoG37okbW34oTPMmm2JRFXT7CRHoOXYwOhypI19p8GsJ8UBPo3vqVqlC10Fs6qxxD9WunxYq4DKDQo4T0jD0aBIP2mIVBZuisJZ1z1HYmY9ckcHmYI10F4H8zvk0+Zmy4yGWx6zNT5QTk5JE92Dgge22k2vJqdkMXxs8sLXewSS8PI5HDBCgOLKJtDL8BnQ5LZ/NEfVl15I5W8muJgAAIABJREFU5yAO/cgFUzGxkd9anBh7H1t+0zdOGW18GUfxoW65X99cNzZxyqVZQqpYZlDwS3Zs3xqO6FYrQcrjY53YTK3f4Rlb5GVDn3ZkGY9uGTlHv7mdKscCOfPhvz4nBbA/6HoeqB8545fbjidgOvABIhxjJnrd+QaO4eK5hjxHRYAbTa4zriCT4G3VNnZNuMcWb88HfQK59gIvnzidx9+JIV+cJlf98YbWySVSxvjIpVavL+nJPb47urHhE2l8J6wAx389hoM2xt48pmZ69SBebHj8bg1e5CtT92ARkxpunfUCbHi3z/S1G16a9DB56KgtCD1nmT5cYnJnY48x0kyRvHWTr/LaMt8mzvBCdnKJzDcOwrN4AmBhroTSlzw2Lzli11q8r6n7V1owABAn2oIcQiPHRnUNWlwcVk5MsJClgZd54Y9wbD76SAqfuNsNjjGU9Q4wBIq9RGO73LfAO4eMsqUVTnIEM5TKgrDFr/hyhQs2XWhG1TXPzlY2KnM4MgBo5hAsa7LTCg+/QG/85rGuayfl4boY2y//2OaX17ONCd+gUU8JFqs8MMwvnGhPzZ2jYzD6taNX9MjVzbwu31Ug2EbWN6ismUG0hmH1E066Srb2pVdrxuXuZ08j3Be/ypuiDh1OIt5rWydwsJU3RnDnxfTksPD6L55O2MY0P1uP9TGh2DaTxszRttluVQo5R7rcGno9yHud4z1PHmg1H+7mMJXUnPqOWwedy8kYrSe2y/9WntTGG9v8iLl1IraFGZshs/G0NftK9Nd+CZU7yMaMmT5Tc+Qk3RBgtMZdJ1SSgrmOuIHzcr6RKsWnvOpW1PqIS12ftjUBm7Hz9GeD6YaJDSVbirTXjnni4QPVThlUhtDzFJvcuJrOpoN2WaCLv5v0ykEwG4zmHFaSeXPInZ2AJe1YDpu5ctQTJV1Ng8qTam5uBFXX5h+4gUlDlKG1juPAiW75EGiLUXPFhXjcdpPpZl0wPlqejyenlmyUAWIjli16hthztX2uuoKtTzpa5mXF5izb73wxm5/+Nh563MBoWZAzn6v56YnbW/8wHN89h+cvuRL9czbpXDnne92/ZJPeNw4GdLhaDcBn3jcTYZ9cIIYqObE+XfPOIXRlrZUf6Y6t9Yo/PHjjwCv6wekbFbv5Tn3gz3mYpPpVhW8//Ccfjd+Pj0siOMSJu5vUdI0bybf8Vfg9b4gZoMzhqlUM+fWgHba24a4VMufFBUUzZPywWWHDzHfvtYVu14f+z3xKgBy/pVakYi75o3u8WcF9g3MAPzfl4cYaROKcq+2+0eCnHPa75xO3UFBs3KZnnciziugyVBUuZMcG3/OUtDSrATKQ/RsC5KEOCZQzmU0Z/FV5DP/04uJDQ8lYR86TWlfV8aAimlYrrGm6jgZA6yr/4ukfI3gtlmG/9zWParSdvMB/2z7nmAKYGRx7DAMBw/oZ+NgctvM4hjl2y8d+eCzGv/Cjrw/W9beGM9ZvOUVW7NYMe5u1mOFyHR+wdq2NENtGqj2xudGWI+usNF3fDI7FxlDH9K7Nh6xj2k3ZrFdqc3ImkmToDZnpjCckcXaI0Vmfcaju+sCDNnAOdvNgZTHFJnVoXo27+eB9c8lYrDkH1OGKL3nU1mAZ0+zkMALp3BojVYSlk8kPMBq+49/YCGXueixPnSePN+eKiiVMnqz6ON2oJR3vmDTP4jdmQ+M9bCLwd+ZIy6qsuR9cGUg061O2Nccmv6ydj5EhhtdApR9uyKIBuzXuXN/HpjFxu361H27gm2BDgH/nGccMjPVvBpEbfzjgIxsOGR2MifnK1k8z/LYqGcfOvKMDD5y2f3OFrfbEmvjN4CMedXPt8jgM3psHOvkSxFhGrdjAzKnw8nz0Vak/EYPHmtnAAz8NvRzIT66xybiPLY0QTW2nVkw++ChXes4LZvzb0mNY34lKUIljVrZozuJKBF151oLJ+NNZNCyaBJZqxxcfCxihiVeJ9CwkoRHfBFX7JP7G3PFy3rlY5jESutzuQr6WxebookTVB9QrHzKtWQ1rGwWPp+rHf7I9Mh/QU2Tk/HThH+zIGnmzrc2xFX/WZRYUnQnRz5Al8OSOpuMqekIQLxizBmhOiwx7GnqxM9+eteIOps2jHweC6oeBMBjKs72yGHsO4UQ+dLHpbflWTuS1BQYH+nFzsHq14qzv2I29a6PqYkKyuIm0gwHf88MViO7UAE7BOfNDpljWZu6ZTb8Ett7y1QgyU6eM9s4ckcSnE1TfeQDCS9LBEKtk6qSz7jNaFBKNCT74lxijCRcemFADBrFaZs70i24wdPwvB2xBNEZG2yN9xwM0HDsTGruC4GLzPhKZ/uEhH9ZDnpgQr3w3xkKsT62EE0eUwUKAHXCLuVdZz1VzbLnlxbp9NkjcD9gc4Ug85Cc+Y2rJDX7p+OvV9jmgcxOXNS3e2GeObnFkTAhhMlC3a/NYRb4Nf/jQxM6Mflvvv2yCm4s9Y/NhM6JjHo+zYew+88PjWvMsh0WV807i7tXM4L2NOF79pV65seHxu+np85/NvCr6E3Ud/am1b4S0huD1U0AXm6un37LRc1OPQVRomzN5ZsO7uHDIjY3suznnr7ZzBZrk+dg0m3Q25m7Ws1Fng02OX2OHf9coMtfrbmyRs67Ed323H3/0tLXLAKKeR9o7TX1++Zor+p+zQecPq3WtsIO36+UGvW9iNM98Rz91qq7nowsJ/hMT2z7P8qYQu+L0yCTVw76BhLBycgdmToaYmUeElWvVvMFSrkP8ywXZPv7u+uL1Y95UYJ1zANQ14w2XgPm8C37/Wn5qn0lryicNsiax4Rz6iU84YI9/MDmPc3TNM4iu/BjTYISE3nrA0jjUY5qBQ8n7Z87J/FDbxqlNUo1B42He0501uvhxE0Pe8kNH9Ns6TwSwcEirBcfMJ44KNbVhbq4aN6YyidV6j9cDp5UyjB/+ue155PoFw7Df1W7PFes2+YCmLUfAJr7Yk8naH/+GrKNjk3DOaLlkWBmwHfr8sHVSvflObOyGEKMZcm6o6RyfMWSIaxns6sQafZ6M7NCzQBjpADJTBWOTMVgF1g5fhNRU8YIFA0+atTkzzGJUR/U8H+rmAZwnkwWp10URvzlvRoeXqEbOAYBohk9DEINfZrVwmBx4LczPwZTO5JL6XDoixXmwtTNSoY5lYxBn63B4JlajXxsXSmMO0pTL4UoeExM9jDY3uXl/ro3+Yw+prlHzq68AHpqzHjIvtck7wPc1SzkTk/ZUxHkZj8aagEHGcIp8/DR+8lCOAfqHKxH4XT9zYMpj0Nx3Tw3ivzytiXgxFvbyKHMZ9ECIhj21fWuMkRTohws0ibt2iJcH9hpOIH2QxQk7GirsaR7luqv82I1P1w7j9coYEjS7GQ+yQjFHrVlrgGR5HPeRyXVxUabdHL/3yhzRhtZ257UtXjGisWFOvc0kZv2Iu5bRDNhJuD4qdCQiBGO/iz1QESexwdkT7sh4cBO8PUf8lBV4hk9xoh46tRy7NRdiMYr0zDZO++KE1TpvkXc+nsPoga5BT41y6wucRaxp84Vw5UiPbMeJ4R2X10YxuwuLNb5byU5frF0P0MuR405mjCaLUq5DZddV/Ls+BDuqcBY3gr64GZ6NMGHyAokXUU/TK45G5NUJgGBtDQBN8xzowLkHqJpJZo7tnPC4AuaeS8sz4toyMBYC2r0K2XmOg7khkPPCs1xEOqbmruHDHQjtJ1RyMmRcNz0A5JlzGwzGGGmHMo2xDf8nBuIpzxh0vjmLpaYBT60i03dIGOtgo6w9rtjR5MjsBBzNzulTdB+ExXp8xqmmzWHdFn/7m3jZI8eWXpsphmswSuWPXYbO1m/rULs9Rjv51z5yVIjT9b7Sia+ppib1xuOuETI22a073kAnKnsGfhjn5pXfnOP70eH3ajr3GX90L8ZZrwnK5ub991GNlw0H8eN94hOX/3l9nlxhtMwPKkJbS7q8mzt8byt/5s0L3cjMqxs+Nh9slumNloMPUymgmxLODzyXSsZKZt5PA7AZ6lXgqD0delWWx41Yz/ovZz9WPv7ky0bbj/zjTJvaM3xjOU4cWv8QHX8Rvfm5QZ0xa8Kvj1tgZZ3Qe9U2fTflfMS9m3N0n9jw8X3m4H9mk/7lFz/m7gYruP/8HY5c9Q2e+YQ/PVf/aT43ZP5p5lu7k7/23dDXn2w4D8It+XsVd/LmzQH+YNwfudLcK//PWuUEhS83Gh+75+PYfFx8119eqatXfl2/REr8wKflEB//HkIFCMOk+Sw3BIydj04jjb+TowdzzhWD4YttZD7GZEg433wJd3B5E8J64q9x9ZSQ+xn3GxS+gRpna5o5/1KNc4bHdWVEiilvYvxoXZDzmN8cNk3vB3DC2GP7WEXUdbWGxNQ3RBjk1z+ql3MkKs0HQp7mBF5ig3jWgTsNOFOb+mCxEHMuDUFqUt/I4eRzuuY5IGsDQR5MxyeeGTaehomtTYy5PxQPB+8dDNIar36RUwOkBzzWyhr59dT9HIhb7c0BZXM99Tj21ZmHVpvbnDNrZ/kf7sOv3rAvL+aMti6NevNwg03eKDgftwbHfb2jomV6uE1MfNd8+xu1iFu3UzNwDIrlgk7NG8kjlUMPruNZ03JgZTOCx8jfvkkBc1kVDxkIaeuXoZisL5D5Iar42CWG+leGKbGFaYzNr4yLg7v5GzI46dUzmFb96MIBGoe/4+d81KfxeuX/iTP8YFsLdIlnTAaRPnGFQoz1yBnv2uisfn3xAHHwg2fOw5lxYVq/wjK+9ot5sx9soGOJbfHh1GhnXbGwOJigHJSVERBVHiNnqA1WmCDXdO2B0KOHzQVcaxIfanfAmDM1LiPyndy0gv2dY4rtiY8uk2aZAb5wmfsz5psrY5pRToyt7/AoS2Ou7WoaNTPCiCNzx417PbBQq+1wQl3H9JOXPDpGvbGGZKZBId/4WT8AHGOKbl2IlzlBkU2D8+u3Ksy0TUe9+xF3hGOxJ8ULsM44SohDJrXhmJlPhpM8eNO6qBCMffwksL6T5CnKyCGD3Y27qVSycuODge1wghWendZyYz4rqI9Bonx5lRL+N8rW5Ma57ljJ1dwSPWdJ2Q6nGHgibjbM4yP+OJuHkGV6YzeO/LZW9TbqBzuwaNZjgjgtJqqLkzECj7DNTIHMqiF/f1UoK/O+iHeFmsjkF/Ot2fbxMvpQ2LrQS9PDUMY2dpi23mOtb6Id2wP2cHqGobsYMB9rB0WEeR4lktxuOKi/+a/xTI8ca2QATpNPBGI8cl+eMS+JOmVMjddMHGWVYir+8JhUxUDe9cHqtqmOgkXuA2ywIj31Gi6u/bBYX/vA+iAP0oRAvrkvF/D6oC/byWUykuP486Kw3iBOI0iHrdtwRBTc8q4BR3nFwZjUWBk+cx5EcGOsR2K8/L0fxif+IxZFjFl4a5v4bATIE1tvRIqM224C2QztR6TVZZNETztX0gHcRl4zZrPxLTHZMPBCw6vHXBn+MZuy9GwwYPmpJOIVO/g4yqFEZ94Y6uB7bGqWqXUoR2fNyU1L32xgk8lHzLnqzJVkN53kmrnrM8TlRWx82WAMD4MW+h7HB3/9gheXuJJLlZVzD+GdiBzh8UP+MFs2W8y7ubv2yHxjLe4iwEGswUt0+FOss3ZwTMNi14X17Ya26+v3zpN/r6L3jQn0XDVn07e3z798mTGPF4RJHN5ImJgrO7xZ3yz25kvPxizJWRNZhZgb+vTqY88q8r/RfWMmPqwN3H7//fdcSef/o/fKvecidQtXbuLGn7omUs7H1jUQpzFePsRXx/lPmfaWIf60k0sM4VX+F0P9BBC3gI0xcqDUge84OWb8KZ9G+PLrl9Tvf4z9v7H/zx8/Jb9+vYC69IzGvxiyinNrRY3y/fTZnMttYppKzl/ikEugHPtBAUBiJ5bH1FAHjUl7WmxihErbHOh9uMAUHTW23nU55x12Ae084zw+wBk+ORN9xoljedX1xMHnvzXlw6H6rgljeEEIm34EdHTMowKyawA2xPM7j4n4vZ8M1G7wKAz5ih+QD8yQKyieNrE8VhaIQPU/crBPYx0WFQSs4Ax4ZhCftrzUYTW4R49D5OSjchXpF+/ItRn7B8do6kQ6CFgu7uUx/EIE2XI1ljS+5xGhJ8/CGk1ZmXStbuTRx9x13fyoDxxpJw70yoH44k2BkHedMJ8Y33GmLkQb1EVQsqF4rjr+xI7V8lq/cn9mcJgGq/Vfrpxf8gtBdTEvj++wzeXB1arA+NPOuegkB3Mi3+gFpSfKzRPVPcGRT1wwx5YeuTjY0wJi3PSbUwwQqttzgVi0vX+ducY6qy+riwnI4reP7XDCARz5LMeZTynUY7dta0QutMPZ8UcsVglJjw7jVr/Mmubyp1c1fDGgXiHScwOHMD08W8u6xTG/lnSI7xjfjUiPXF36tmpPbUZrXhMbu7NmOXcJcVHRDjLAbzBUR7brgOfljok1iZ+8Hr5vFGGoB1Zjs/ZDCKTBAFWtqrWn39YNuvOmsndsDRpDiDEJEEK0F6RkNtRCK41V7MQpaRcxQaDVBeXEmISwTUNH20VXHCGI9amePOr72OIHwsbIHNSeftgxWZxG4libDKZVw+S1nRy0rg7csl4ulTR73TGUE0+QUFsHa5nJrVSRdl7jHE/NBdL/1g70tOAuNP5ltcyqdG1d/FhE9G5MChLouIC9HJUvzCPcWCcqPgG9d8xFbN+cMsZxGkNe8NFaC4dyc+2nNozhW+fUKxMoFfOQA2TsUGYcTuDffMrxrJiu6z92hElrrXhpFf2aVOWRF8hyJsbk1HpOPlhRExIGIt3hO/YojrUBpa2PHPXXPXaH9fgsfvq0hZyIcXrsebB6EK5mfHEmiXWmR7Rrw3x0r++/MOfJd9zl5Hm62OQQpeGGz54vy5C4xDCfyX9l9JtX9ZkyGLspoWbggdTW8XL3fFAXuSbRuN+B396yCWKcdWZdTz8bc9YfV+TXZ6IRbpobtvx/5W502Ezh0yJwtZy6g8TmjHj7SQ9S8txFNycYsjDRx5HDbh4JhxlcMWmDN5uRburkylzO3eRxVdCbm5s6sgmKVAj4U0rWKYTElsOGSN/7QfveV/smBHZuqH4KVj4vzxsA2a8Hjk1stivmFSsTCz4hI6eJiT43t5/pqceRx7DriE3+NVbw//mHWvC3AbYAYDOjBuTbNyTYPPGR8PuxcFagXFkHrqJ/yvec+a4zV9JLs3o251ztbuzSZW03b4yxlyd5uJlrHlfG2bm5sG2bGnN/i/Nvv/3aNy8S69cvv3olvZvz5MD5R1JpP3/K969jz8fyuYpOs0bkwKcBcgMPG/IjZnvkFibFSczgYbO3AgUjMvxprKNNUWXoqgZv1GPPDDzk8NWfun3+9sMv2aSHiOchNn/+h006/3avnJar/oUVy3MpOfEGCnVlbo7YdKG9P0oq50PLNBwz4So8laMO3s+859UXjku9uWLZHDz3SV96nMu9T+06YLeb83/4mwizRsRgPXiTCvB+hSNvRrUsyhqXIvHrATjzVTjG2o2csezkXF9sMzrN2kVPw7q1ZI59/amDbfHQXjhjvJjajoGYEQyTxgheMRtnfTe+9QI/6ms3ucKhdMvVeQXYipjYrUPPY6KLU2Xp4ecoupzbHSfGyFmPN3/TiW650uOjn/Jq5B756g1xDo3pVV65Ll6s+e2T1OUiSJinX1ygDlcUr2DYNXd8quYu3HXGt0Lma0eAvZsb8snnBDixJocNje34Y1vxMqz3rWPn4wopOSwnvOSa3oebkyl+u7qMnzwi39r03F0O38kFpybUPAzye/K37vWTuTYJMvyIt5zX598YWIHZHnt9qBvCiU9+12Jqie3a4TQ2aJt1RnDSZvAcg2SUdUGQcQGwx6++aAY88nOeP/GKhN2hKxYcahZceOwsU33kQtTVRZrfrdXQaTf+tb1xdDg+4Y01uHBZn/TbDocIaoUzk+bsY/HwxOfUl4ktEZZ/1v9gAGOY5DJ4Q/zwMdBwI17vO5v78Fke6s1mA0/0mU68ZdDQOeZ3QzQx7JtjaXWMFPR+Bz2DiE+yBavBFuwEoqhEMNDeWSqzADoHbJ7QwJ3KGHC4TOFQbpOetkLE8XJC/HDEZXlAhTF8FgpymJw5AzIYuVi15on1LVhU4mC5OeNtDGLlRznuGiEEQ+Xo8UgrSMdOMB1/LTGgtS9DIuy8OjjRDLmTinJcvBFEz+PSci9WAPq7RhsS6mmzjhOnRpkkp/Mu6hTpNbGeESjDNo6tE6OPDR59QS6s9aJm1i2mfcHUOk4oc/AJFajJe+1Pb9QbC/muFXnRPEpuOY4wMiTY2+w6Zp9DO7pmOcLpqHV+etUMY3+rNOqARGKcnKRl9NphPnISxwVe8+SiQHmx6k/lL/b6gGSGwITb1uK1lUcctDuOscAeJrNJcqyssWo/eeA/dSamfPFF1qm9CkZSfTWiK980lyOayzET5wPhJBbhpRXGafjefNa2HLFd7FrHEwhIQ22wzlc4sGfxIWYxaoMdt7NZx2/nM4YVTX+CpP3oH+TqwyGbLEbgsMkAy31P5mye0X3N4+ZPia17zOnxAw3vXQcnyiKdIvaqai3dqKMn5uJniA06+n/+5urxXEU3fgwsTnixDxFq8DOmjif+5pcYNG2R4ZPG+eGbDrNZxBeEcVOPjTc4jg9zs8ybAasHk01z52BzpTVoOfyYzfkP7O2y7/k5X9hy8/0P9+k5kWNpDbDXp7n3TYrat77Z6GZDThw35lxNZ5POd9CzSNj/mA0zY6/aD+cQCGr4kQsv/tPOmxpUqwuMsI9/2JEQv/gy1622zb+fDODq+S+/9LvwjE1Y/P7LNP4VHJtzNur+xXk/fi2YPKwqU8JwcJja8GRpeZBlTeBoLeEAHxxqX568RaJz+eqVIbb5YW336je+1HvzOOMAfMonRojz9XPOwfybtV9//83zHl8+6s7XHvZ+CO62xaL2++kG+n0+kWtiEqvLQhDf9uJDKoePXMSNnhau50XYhkvf1KNj0EnNQ967CTPwcz8C02bIvnkij+hyPT/3aN5ISE2wxS0/5OH9JTLoLC/jBc/cyWWBMXt5ZAweIn0dWNqnajh3bdYXqnGxGWMmlWfC3PhglUf7O0f/EWV51hfw1+JoJ/ap17GKQkxQy/fGQBfAfXNEbiW9tdqELm5wnlpxnk95oGYDsi3sMlks+l2LwzvhVrZe5ffwhfnUDmwZDgd5jXDli7f9rdiJqmhnVuWSFp/pxtIuk81bKvDQ58zKcZK4sUcQvlrOOblYxvAg+3t/+S7+eMvp3/WBDHFyGHxnU+9q5jFjzi9y2vVATzMd5PnZ2rRQ5aZP7ljMpJx+Z5uP3Ap0cBZvfbAp3TkfrE21xoBM2ko6iIfc0QSxlCIq1lvv5aTlGi4eGMjoHd5zshFRtTb4l2g6yOCDKP5vPKTmv370OMJxYtRXy8MdrGMUw9Fe/Mlx9wi1H347Sf/yXZ6HkxGaLzI4kUZrhEDp6SDXx7706CZnLPEqy84WC2fwWgNm9Zv0W7vJZeuGzYgmBthpW7v0w8xgBwuv/BZHh6NXkQLg98E+ksoSQ3w4xia55go61KtepYhjgIw29CbJBVQlQolnzosUfAqZvlQ4FqXFAqGa4lP4fzVhprhY63BjizF3SHwbsqh7kiJvhsGZExcZWOaGeaft4RGgojT2GpDWvgjDRiYEpc38xmrcWjX2qRHGaYY2XubDrSdRc+zxscNHVw5DPCPrkLn2ES8HwzSIVpJcPyAOVsdd68GJiFitUUCSvOPIoEzz1MgEzr5zh4D1J8bYm88Q6ThabW7PCxiaH/3Ee/CXqlNf6GL1rIm2a4ymP8SBK3WwLWCmpMy03OnJCysODvLaKz1yxZWZO/Np4g8uL8U2N8CJ2u/lOrr5RONmYPywLE4jn3c/DVnfsB2bqTHxIRy1MWdsF1xY3829ZpPVEEcPxEjxkDMxUTDnF/yxtJ7zxHrr0Po61w/fbWYWGEBpGWVI2s25r5pahjrLu8bXLwZbk1H54Hx4giwuGBMgAmeG9nDqxGyZHWpi1I5cuvRhkwHYnAuMWbe9MsYYZTd5DNElLvVXF9AEYI5NN3jdjIPnxjVyeLqZw39ylRcYmYPRKms4acMVHSaunlyUMgcrMcBhfDeilTN3U57NEG8KdJMeGRta4lqhDNlE4J8b22Egd0PkBjlyKcYeO8ZuRHLiuAHBd3IXN/6w5aP+uwbwx3Zv4HJFVIvoulm8G3XsCdTHi8aNsR8PhwObNjbPjPmjfMTXhWJFRk12uPVBzJhYbHK9ZVP8c8bc+n/K4VIenAOMfQNA51mL+MsP9nCfwGesvPG7aSeV9amcXKgF7UuuovNX3P/68y+vov/xxx8//JU3U6ihV/iTK39l3jcT8lfn+c76/k916vM9NvlJN/7Rmi9xuu7Nn7lN7mBcjpTJnKYn61T5yN6xGFNrqzNj4sMDzt++sMHtJpfH/T/++JRc85fdOS9jWPyph45Zdzblubk5p04xsl45p8wDwuHEfcxhxvkOiRw3F5/UmBBj7L0Pkk1k/NDANaeMu17Iw6HAfX8jom/5BErPBbyoMTkBXw7mGA1/0d40MAsya8Bvo9FHxoOuWvSo8SmOcgCQh0PXs/OtV7210E50TTYK4mbY1CfbqPereVgSN5HFYNSG0Qzh6jACuDAOt1U754D6WOLTmZbx83FqjdM3jzpis6oF/oBlMJ1kom1pxHyZRIBJO7lq7DwKnOBNjVFsHw9jqZ8cMj52NRYFNyLEtevi9GJ6jo0vtRLD4sdemmWLaDGwgTRrvG2vHGL9oY7LGWx0YpYLGEUfFHDjvRi1TwzCvH5yGYGqxmz+u4Z14yhLfToTd3NFi4FwwRljbMwTRthyn12z6DQjNxzM8aldROZpPs1xMXwzB+/o+KGBJf6p54s7/hN9ffSLu/GdgELHgiqQAAAgAElEQVRcggM/GAiJxTw/+BsPX0c4ZRQ907XDDTubOpQroB8tuNag6q2HtgdvdPoEBLxtE7txIzwqOG8UeM+YsFGceTDNY+T1L6ePudzcF7UoE1BOgNQug9aC3GwGONxbx+Fl/q0v8b1fDOw4nxoNytDsWshn4hf3eGUA4M4znFqTs7aHX3Q+Pq/9rKmujYqv51l6IZkn7sxukHcUQ6kp26SKhy/XHIbU9BgCCjG42OM4hDNcmLPoSqrfaLh1zGB9IMu4CEUdySSyhSnk2JEBZvNuqDbYc4dDR8vQDWUcRRz5Fuf4RGv89dMXD6CClVtnIxNvfAS+/K2NnjjPIDYb0/qEo3fOjbd11SWx9IsTcaOTQ3Rb/wMcvRDilwM2nDTkY05Dgc58hSXAQw4cJCPqkySGeLUd/hEeTsSyMnqPHJ7xAYyBNkwbgxczjPKyJrfa+AJH06DhCyp+MyYEwzMfDliqCAwMygXhxKbDYPyvRTm8xcPfNkXYmmPjTwz2RdfVEQkFno6EKNe8mLvPjFAwp/NmBR7Bbp7RgmGXAcYeVhhsZQaKhvqlDVeGCJB17TKmfiWWvvmqf310UzrhCyIvMJEmsBYcbMMp4/OCsG6NBv4zP26xr2e5MBa4XvJVhpyGYwSvjJzenJ1rRj1ujouL7y5BAlQMNzjmpv74Eys/T0DXmbn26BnGJi8c/KGfF94oNXv85TS+cbWJCdfI4Y+5HMFNrd2KNVDt0eemH5tLPqKsE7XAxEnxBleOaMIP78bM3Bj4zDh6Nq9u2DNmE7Mf8Vamfd9EqK8B9Sc3K9oQEx82XQfqbTNPNk4pVLRspLRiPXKlm4vd3K88X/VJDfL4uFfH3WxFzmOEm6LAnjftsmE6fuKB1bDs0L9968fOiUk+bcSF2/RDM9MWOh1ry/xuzvOH4fgDcbnxR+N2M4gd9wE+4i7m+Qh1SSiDF2D8ytHBcBhG8qk+Cn6PHp+vqd2nb/n3bl++/PDb73//8B/+HVmunv9Pvo/+//zvnxhng3uvmv+SzXk36dmss4EtYOyI19w61pUsWjj1mEGgpmCTjRg8b2W8byYoy1whfRpXh9e31hESEg4ti73npGE4ZH3DP28p9L6V85A4yKn3X/nDeH7cPf7WHKwJwlq4HumJ4XkT3YYCpo3zgVsw+Hg5NMVZ/TEz7p5I2Jw8FrWUM6uOP6wHV22zVt/y8Y2vf/HAkF9VPBewaSd2709E83HkU++fxdLl8sLBmOTLOEcBRyp2dJEpxwRuHLAnv7ql2wgVY4WsbTIUO+PB0RkY0da2ONc3yq0jPJiCAz6+OWdo8AO3PA4tNOq1wj5YRcmxKvXEABfR8nH9xqhRPuKLxbkkv3rKY4yVGKM26oJe3GIRXHMwtC0dtZmjE0dDbKjPbcXMXP4jfxNb+4Ndb3HVDWb8zV5ftUOnjuhYRX46JtbqCA8Ov7WLWdeEwdMO8vA5eJm/lqMemcwefeaPP/Cuxeb6xMOsuItYpc9dExAOzSW9w9iSz3dtEYillnhz/i2h9TLu91ixfzGOD7WXe73Pmr68lksAFkX4QVzc5rHGsbgKh12nCqnBLFvvUzuJe3XkudzAbN3NPtCyDW9GcHLuoWFnqN+pp/Zg/fc2zFSyzzBWZ4J2fq3uvLLG3MjIcpu8zB3JcFir6qnFeI/bZNhufcYGSu86UQENA1H8qYdyWZjLrl19iTf1fWMPdjqbOW7dYrf4KEXIObjnczMYBZSmdd2NdvMn5pZn8wtiPuI+pIB/QHaRD5eAE7DyjlbSuFPUcbhJt1iJUvgQ6YP6hFsoQdY2wnnmsFaZikfy4pPJyBjkd7n3JIkIGeLYU5DlI/8zH7fYbGSdxOuiIsdqcQ3XHRTg0TUzYhybkfuA8QE7cTIfaiIzOTL88rt+PVlrRpxcaDBmo9YP7dBtnmYyFsSaQhADvg3BeGuZYR4cbNhikM5cMCN36kUcAmkzZvJBpneFmoCdQW68wHazmx5X66R9IszceJ0cKKZtZzDTU+WrJxZtTI2dsamsO4BrF4X1iAsbFRXpkPXGuC/yVwa8PmIsEFLyyDzwhOrGorXtu63dcJjsYJgqrtMWjVoLguB73szDz65Dbe46rQs2rFf7OEVRPoRbaHNBkHbH0WJ+nuiurutWHDBob0mZr5yRHFgAWkgv7wqYr4SaV786ejitRXPEiNHUFmXatWE28dKZ/52iNA4OpVXPpQiS9V/EKI5ucARZfSbeL9YocHKTwwShQNMw2xetz8qM9Ud7whWbHr7xOFD1Xjm63ZASoze4lzT3bUbM15Yr6JzffPd85cc+dr3Kj1PJo2PzDCcaR1TOSgSxZDXJQZZJ2CuRvPjIXp1NHlc6qdNe5S3ubL7fTbhwsYys0BkDnttuQuEFFky80p/vB7B55S+0s0cnRvbTbvx8Y0DMHEJeL7CCDw4b9C/5vjcbc8b8QTP/hdfPw41IsXdduPKbPPq4iUyG00OR/Bu/kSrDCqNjH351zTEcUPCx+vrnu9rZpP/+P//jX2f/kjHfR+evzn+ej7T7poL/s71/3I6ry9x38d9YEIELDSmqrZqfBEGIjS7R5HE6mWVPG5x5HBCzZjl+16Cdn64FuoxZbwP1PmQ+ya9n4qxf/jr753xSIQs3gF0L0cKBNRQzY5pv5PAGxGzOTcSEohSCxPrmj+/PTLx8RsQ3EpoftQledK1R7xMGyOGVdTmmltif899CQcjzsH/EJ+fZX/yvwGZ4+YDPc0w+RZN6eF/0QSDyXaNJn446TjJLyd6IplfenU8sgm2txRgcAk/Dsj7lwORfa6ZvWcBB+xw3ymKZkFosJra+neo7uZEqkTanoq8fumi16biCHCPTlppRexTk812e2ucgovqZIDlzxutfDzBt2wd364G8MY3aMfcD8WIlMY3KMZ5b30E1XmXooH39wRfr+I3/2oye6PVFUP+9H8EVbanc+OaA1LywqVXtd9Z6qXxiap3DXY/ialdX4535ckg4Hycgg4WYE2Pwb5kTIBNMy65o3DeZW7Pxr2aOW3unsTJMsZqrkYsxwbYWN87UKb7GeQPo81geDjClLTtGAjwSZNXfOuPTPBnVhfM4P8E+59dwpWaGZE7InG/aaJu51MqlLJtLoYM7buC/Ndw4yAs8fomDpI93o9puOB2syCEH1n9r125jfLSvtLmXw6AM3PpPAU5tNh7+1688zEfgy+nUdWh0jbGM4Ng6c97agD01wYYZkOZKrLoqd4EwiHre/8dlEDG5LQp0m8NVALg5VLr8Dh9j4t2W5xcYcZwiCp5DxJXVcO12USUvDrbFwMcWEueOTmJpa8Jgzarw+ByqNw62Me44JoXqPFOS4sdYJo7JwwUeSGJnIbCdeQM6cwh0IzuIFfOGLOLFLdbqwSyXoZcZLfb97fTDcdE/CDMJcpLZxbq8sbt4b5xbm6mFkM3ZIQWkUStvDMu5sugEzEFb+srAxnabY9cTnpGO3Vbp2vNiq3HwzctOIfRhngHj9oO1yoAip22IBoog8aorJ/OIrS++4NmBnuv7rikA3rkK3xdMI/CjiMEA05TPmBfj8ewBhDJjnthCLV+eyHkxNi/m0PLC7mvWVN6+4J3g6PQDJ5BPQzxRGhcdgjRMwYUH4+3FgtMjc1LBsV1ZKb84Q4PY+wKbGAShDTbDja9o9O04tkI9V7DeVt3O5G2iy3k0m7jTxatNY2TcQSK9Pj1XebHgeYHR2PH4oCzz47O+6U9qGWCHDTJzOOP6Aomeer9xsD/rGb2Fi3A3OYho38+RNU7xWNWhjUod55PCBkHovsYX/GwWZ5Mjd3jrSbKTS/ReJR9bNuDO0c9tgsWX8zIzDg8ROapA9XAMZj8izP0E77SswU9cYR57HqBj5qbmU2xo1MGr42C9t7mPvLK1h9DG5n4FUv/QHjkXl43zJ/54Gt8ATixq5wYpvX84LVfaf8oX7L+G30+TO3u23379LRv0Lz98zr9W+/mXn/1L4VyZ3vuy6MnjE+dXrsp+zZsB3/yi/pRpcyU3Sjc5yZ2qKBy5whYXO1twrWqmP+XdDDZ+vIHyaz7q/sf/ffGrCH/99mf+YNx/wiFXoPkI/lw9l2PyE2vximpdkp7NNXSUHKZexHRMLaLzzcYMfDwMj8BS3D60oieXt7mewx07jTHICEBGnp9MYhd33hhg/fy4Ol8niH5xyeHP5MfH3f2uPwCR6Z2F2hxhgc+e+w2GNCeauXAfyWNx1imrjbHnG2Mw4Hk+FUCMtJ7jS3rqwX2G2m4y8cWf89c3snKJg7/Arz95+j16evyTV4Z8Wqb8JgZk0uRBLZxxKNDOE8amFDvnzBhwG45YoRyOlSJs+xAnZh/mmjTu2m+/OF0bZuX6UR7r79x9HFjy+lyu1/fffsuL+Hh8aMET9/u8Z46tPKmBsZkl2tTEx92MW73LZ2MaDyX3Q30yybqhx0mPyLXziC726jog4hgoJ5r24GKK/3BT5zguo9coss0T/plELMrJxZwMhZwY4+PTxIzR4z5xwRaJmJMfnb5qaqDNxMNn69PK1R75aaUQhObq/ZHY32E0Zr22psPo1hFqPBZMXca6XYh95H/ExqJWWzdDb63p83PqTc5TYxCWZ/m3Nq1BtUS9voyuT1EVlJxa5uDkduY7jPecU+dcAJBbmlxm0RxvDtF9qGugD28XsTPPC5E4tI6nJoiGkp0xt9bUqA3x1mdQP/KD7DmHJKJ+62eFrHndWjHGk+ToiHZq0IlxPU+ALRGM0Brz5Bd986ocmzMfc33WN9lVPMp05MtsNY2DdORw0Gr6GqtHfCznXGK+4U7dIqu8cXdcX5QZVXUiUadzXsWEt+svcgQmS58mEPq0LWYL8fGE6B0O6EQz4LPgmRcBPjdWxw2yiRlHUShGSBTDYwCIXXXYXryN0PD4mShcouoDoOwKUnFtxjYi8Yj7tkIUfxEmSc0mRFDesl4EOIIpn6kleRhlDvgi0WbGJi4XjbTH6kOc8a/FjWntYtxcJj4cMLRvLOe48aBBZxQETy2GM/q8KuGYvljWX4VCANQt2tEbKIb9NbXV0TcEQAIA1oa9yaGDZnkzVoIjN/DBQZEjU5Eiaw0EUStC/tIuFtphy4uwvJjbq+m8MKa5bu4sOvaKk7mo9mAejIifF+5w+JarQ8h94Rx7c/SJP3pe7GHjbXRLL4rm0B6x+CfmGEQReLSiMHLNMye/xSBKMdBjta11AUOEgzf6CPUcnxsLezQTYwJd6DsqcPCMseuQqT6DQm2W0obWoITenFSbBB7Na12LCXZ0g1mOnWO3cfH92O78jmoBnpuJ9Iw9lxxz1bUbU7+76ZMuobueBz9rTjh8eYEov2TMhrYbv244uDpIqz59fhZr4yKzSbJ5cd5yzmLbWzmIMOb6m3NtIOTV30kWP9r2bFrkuvHU5hD5v5vJNTbK2ATdnMlvN8ZgizsAhaIOczN/NuyJ4a2bKZgRlfsMbe0ROlbYN//46LP342yq+Tdluf6aj4dxBZ2/IGfW2Ujl4+/ZVGsLU+7b8WMj/mv+sjhXdPmjcMz5V14/5iPJ3l9dx+ZFehFm/fAPEeY5wKe65QZJdJ2bl2MlHNQnAgaZ3HPHfIMLl3sV/e8ffv/t91jXlj8M519v56oyfIKxNZZLEK1/PjYu5Vlng3K+EB+ZsZmkZcpjH2vHx8KtJ9fSOXdRC0TP/bZrbc88OHsOgYOpbZzsIm0fjT79CsEPXz4fGsbGkYD5uLvrh204Hd3gGw/+zrd+YRSZj+Go2D3nl1rwZBKU5NZ6Ld++KU7QAaanxefdnCO1XD3kDYbkbGGqsC7EDj7jfFDFPOStD+c1pFq/DROr1td+7kMIh8auJ6vmWCKmU5Oxc2Kc2skH5MSzbTfxxUNPDjyOMGQcO0xneF1XPo9X4C70PR/qp5O5Ojpo2G1ixKeRE1KmRz++ylGdjdvUTnPGOMVKIsVbUjMrppOga7oa3Gb8cEACp1O/UpOjOl2ae9djMMIFOGXxoWnfYeUj4HVN8cdGHs32xF4OEe/rIGrmmw2CL1j0M0dim8HWU0uS/y8Nm67F1jbW1IMTgiE++A7mgVCGZxUcDeEhkxbjQx311RB9MIGNXXniXy7GNHLR0Z+6ZKxPbFuXUrPuwWrY2hCvWI2z8Rvvcj/YYoYgPADahsjxR37M3rroMfkQwwjOC2Q2YD34i7tA2CxnkhHzCJrHYiM+tQgmbXlvbQoW3fIgR+z4QYafacw6jN3y2F4jPKOnPvZZw+Vi8HNohNUZERFtYkmiZhGC52/WtPhyi7z5PDwPv10T+nddjCJHfbGf2sA56N5O6DHfTq5wgFNa84dfeVU2WkRavYfGWPn2i0hvM0ZGI8DO2BFsPv2EVs3HMmZx9EEgji3OGGRuMA4sjD1GB2AKgeAtmIZiEVgM3XLgeTNApNT81WqzhSkaYRg9LQ5HN8lOpMZA29/jZOL4NUzzm7EEYr9recQTtyfyxmykAvck2jxeO/THUo5nNrVaajJLpFmc2Db+tYdYT9r6kAP5065VR8i5rdzQ5I0x0sHP815meTEx1uQO/76gCSd8piDYFTFyXsCJgcNg5hGBLNrac9zvZ4N7TDNwLvZb03G3k1xHDGO7T9TGZh4Ob3MGdoTdRGFTuw+2MQSrmxWu8KUCzPVLnzFXYPDxRqGibTijOIY+vGi+mKcPlh8VzWbAP3qVYvFg2e9MesI3d14IpxFViNhYa+o6mMu5ESY+4YkrWxAygdjziLy5U3EwxCt5IxafyOPezjmxDDEbk4brkVjENRxh8Z8DnS9AVyRHqGlgjoyW9yCJCAg6jst5g8DVtYHY6DsaW2VFthYoQZq8T88aHs4Tr0H1YM24J2xchTjwy4v6CHq/QBOWyDm3iA/HU98nj9hsTbDZ28AaQubqMmXS0+LgEecUT5OS9jgxe/5GSYs94n0MZ75Nuzoqgo85ZdaNBO5x4Hf41hcnZENOogCzBqVdfSXGhzjn/nlcaM2xX2z6THLj99aHaG445SCyPgYb/3FquQBtUO+3PLH0CiwbeJRRZ1PNprb3+/DKVWjegOFj7V9yBZ3NMOOfs1Hn6i71sIZwg0d+8GXFeWPEjZ3z8oYzNvOLk3HNEd3M1e9YC3Spq+b14eP1n77lDYO5iv5nvove/7+ei7P5w3Fwc73i78qAl9uJQbz89H4Ti42XxzQ1McfPtReA8mWQ33/ybwH9BMTIeVihDv26EvmXI7ae+8Gx9vjbBhwtvhjSjr5DKJlDap0vpadFAPTkguTbf7Blp5s+t3P+Ldbp0U8cMfAjPut0nIFJWzmKbfEFK6I17yBrne9J9I8X5vGB8uXcggc3Hi+ozf6Fejb0X7/O1xTmPyR4Hsem51JjGmoerxkbC+gTPEPrEBnU8qPKfFJResxjwxozcaxdZe9ckNWlp+EvMu4WiemuLza70mNPrOhbU6Pr73kG9ugXazkaCX6B2Tw+xAnmbYP7imAiP7xpzd0hs+G82Ngsu46wHMB54bcc0agirwyv33rWz0qYA3ZX9u8cJ47A97CVNNhymBU43KAyuRwyQFCfrW18tKEe1mT02KWZl7kMRxKKz34C5OAnAKrNBSvb2GNHK97wIp7YqkD1ZzGYOcYX95gT93CKbMfqsR+98UYvDvKBIRq4vmHQ0IfXCUQ8QMPRvOAwTWy4rMA8MsF2/dY8fhWtYJ3oN7/6FjCoxjJqRI0iXz3GZ2p3OAw/7VdIyOGf0eA6EhdMcQ/W4zi8V6J7MxFHaCBz2w0wsX1+iHTXufSDErwjWxyVrYvrNvPFBp34zJt/cy+nSKIAs7oYYUcc+vyg63rEZuRoSNfaj2xjXH7FxGqbNothvaKJUK5wiO7wboC6XmE5RPfxcQuYAIElvkkdW2QSpqdNrE56tAb6dj6W4UMtyIXWeuTPqRprRIwraHDSJEb78TRLwXxxOj4wXjAjNIxayKCG7D6ZSAVZbgPsExhukW1+JozJtF0Uyxs8o5qsI/0swGLG7xQEEtiy8aBlPI+VneaIrrkjohoUbdqktPPFLRdsWtSGxiqaSaSzsUn35rF4xNv6F0OExp+6KI/Dre6OEZJPObBBw8jvfFL39YhsOT2iAYkS2+GsnloRTJKycwhTc2iWVXPUDpiLsxsUsmcJ1kybgIs1uhMb4wVT11ru+lTVtZHuxtWPHHWyB3NxvSqUOS/MPRcZszmf3iuSM6eGXlXHlhs/OX+3HIzgTlLk8mNeTMPPcdaBF7kY5xOb3XjnxVxe1uUj77HhxX/i9Lu4XHEBZpPYOjNPlOjOebrBzTN6ePEI0mFLJgwHbsOxAfQiF02cvYfw0uPq142wYJ0WQ3StRqX6alLON0ijjWpoZUa+YHDOTmQxJs6eHxtWlPjsWnYOHDigG2HNRTx8zwDrsj54eFDgrLcxWR/x+BQEG9hxZlNEfARx4b5FkFjJyfWbgnUFu8m03vFzw2dvZHlmGv+ZB9Or6cHg/DgNIyhG4N2RMRMP6TgnPS9rh19xGKVhmxhk3dopcE5oN0lQiJg3kZgvV3IqF1hitG3Gw0H35ZPevHK4axsGbGriLiYwYD83kTOX+8TysTq8rG2c115bbXI/C2e+ay4jYnL/TT2aA3/UjRseAJ1yuIHnKvtvv/Ld814958r5fpebYu/9eWsnn4DkrAgQ/IOZXxorVp4Eowa76UYbGb8QoU4Sqk25XRtHwf75M3/47nN4fskbCPn+ef6qOxhf8+/xdk2wfZtLAB9opQ78oUHP1xtE5VC+rusDQG5OU0MGPH7x9hRfJ4D/qUXIAOunTESKLr7nirRkAoGPuBsuNvkZtbUgH+r+s/4BTTNWOPz1Vx+jKy0GeI2Vlcjj7jZl+CJ4yg+WvNhQc1+H+LTySKJXFM1wtBKZJYbnsvfLAPMpqeUqXA6Ua+L8mK9K8G/jyElFjuXgIIdKCQkdmh2Y+bHGAlb34ajNSKA99ZUfeSmrXswcOE23KcsEEbE2GjgjtIdD/ZGX0Zpod/QF29rT00Dm17mclAxWVAXX1kMJnXVtzOIQnbZsdZaTYuOIPrErbWZjUT7gCFW8ksg4ZPYxX/uDA8nJ3YVqDuWT+rwFiR7U4mzU9toTJj+MTX1MXowdtza1l/DQZdw8y8rxGLfOy2kcnhodXlP3XRfIHD7kPXjKhBnW0SHjhvhdZ/OLYt+wLqYIzdI6xau/yo7WGMPBupvVREE+EV/8+KzVxnrrOh6NM4EIYyZ5TOnzSiUaqetI3PUh5+EuTeJmvuuJx65ZvTm2Th2Nv8r/cj5+T9T8NbbGYLNuxotYbhJx0vtKpOYuT2xgcOPyXIiKNt29j0VQzAGd+Mz2fFGf+eUQnbEqQe+5ABZ8sX04E3zPlQwab9AWW14Jaly4izKEh5q4iIgB/nAdp/VwGjPBfKh3GMzBwW+xjLc45MSNps2MZVNmr+PhGJWW9OPP/AN25h/ssTPukcYeD261hef5K+4lvYSaAMYEPIXQEenqS6i+I5ugtSlNOS+hiBbTZMqndcn4+kGyVGdwCjxSeW1B9EsMT1WKq7Mz/a5dvOU4+MSHk0Eg0Jy1QT78ADTPzQMS2OrnpECRDeTFxBSTtBOn0++9K10OzDKm8YDS+E6t4dGJEjvzwKUcOmeDER2/yIEbzOmUy2xyNF4LqF8jTtx3MuOt7fZrwnxhkDGHgxt21+epH7xsJ4ljj7hc689861g5yUV3XfGoz8EFo3XhBSVK53kRywa9N2R9cY+OKyfagpYaqhPvAYXLJMmLzLyG9cVzX6ROjGDxQi2IuTqVqy28aEvM7CDs+r+yLUjQLh5jIgEPZet3Tkhkc66SK8bmX+OijRytBh4G9AJbS93Grs4GNXahB6IY5RNFpmvTq4qR1dLOF6yZY8+BGjHs1adi1aPngowHk4Q2D4MMx0MPnGCKBzxzfwpgfRDmxliwsT+k9YpN2p6fffLm1X18+NrCBKRjK0AO5MrGkJyEHiPjiBX/wXYDrF82n9jl1s1jhpKKEv1gvL0i+IeL8ROMPiI8HPWTHlDJuav0vmGwfGpNLvGpUbw7/8pmAz83pN2ca58867eRcspiOG3z9s2uyIiFjADtRa1zpN4/6MNBHk++leEbH385TL1Kwzmcj17zPiZwnxq4SD+HQT7mzqfbJ5bxTFx31+GfbF5pXjmfj7j7x+Eipxau0Sac+y34nG1wQGdtvb9HkbbcHGGbWshpOGikYbFkgi4/4MoVHJ0ySGy+n81H3X/97TevnOPDXzr3yjdeG8N+cSPP48s3vn8df94nAJ4GNrwJsb533WIQIXL+GJ3nN07Y85AVPl2ncgZ0n1sEJAjO4dge5wzDAdvloGwm5ZJ6zlrIKwaff3m4Jq45i11vjg1H5VgTWo90nstIMuYNHypMIbj/IbMdPAyRwHOP34/gnziYZM1xJS0fK8Z0a9tPTRGbPx7XN1X03djEwrdd+ll/JPm1JqMDGrv/j64zUZDkxpGsVKWje/f/v3W6JZVq7T0DSEZph5nhJHEYDKBHpDOuvEccu4aKJ3dyiqbEmIAJX0Vq0BbrB/+jzWAx4GSSdltfACrfmlMH2GuffrGcGxx98yufCINhHRvs0wdAmn1RYUUtazhcJjf5aN8D3hPWqEh3zlg2QOF/MBebEIMfXfmWTzFGF8TrK2RLtYHML0hLZuRm89hsPjKMHPuqJ2Y7zZDb4JwGN3v4Mhy5vJyOx8nzrk0dN09ypjUyIzd0uc+cwJOIIWb86TVY0Q1lKnQgT60Bhy8dYA837E/tb2Asr9zYhVXhoTjgGbMOoyFSGE1tuiDMK4brDCc68+HBxeRHG03E8lzM2PQ8WeNbASxZD9dqgp14+JPPe9FqzFuHnmOt6fJqjUDhVr7EOW0DrCCqfYzadShf4i8Kg0SY9SOu55QG5U98fur0mROynnfBcY2OZVkIH588YDbdzQnPKNPMZuJW8sOUhlIAACAASURBVNRu9JUTYkfQvgmvn3jKGSXCj/YxJG7r+44vLi775DtS+Qm3jJlU/qGv+DmWX4+JuZoUon7wK5A2Gbte9BHnBYQpNo5r4TgTHDEk2SdJ1Kg8dtBg2iEdIXgB9YRYFqNrYQeDwK1IRmNPnx+O5yTWF9DIEqsP8k3aiJgyAK6RCWB8Bzn01JlZ7MR/arCLhoUPVITDigsdcBNAEWIaMnR5QFtd9SDjc+VyVBo/cWo5lP9hvzYXt5jG9erAUXm5cwgsImAZ5OYF1J3KkRqBSZvuh9yeOFoFkjw+xtQhgShK2nS1G9CTe01qR50y6mtpOJZD/adesVhfnTBbDE9sKls2yGFii2ge4/CYB5xYIueCNdJeuHJh2assej6zityNBnZx6IadouLTePXJ3PyW43JrPC8AE4jzgRz2yQBe4suWzgt7P+fJBSlrmO7NdcfU1hw37zIxU/Kgbc0chNNrig0YJo8it+qDmzsOPzzbrU3Uez5Yzzhbx8htBTvDuNrOuWU9VpZXqDbY+NmVbPnEtLLpmUdgvsDIN4eVaXz5whW4U6shjdvBOJywTc4NgJPwmy/hCMiDMcvRlvluario5/PG8Wf9EXNW+PlTMMEbniCLC5E05/Tws++450bG2eShQ60NZt5qj8+EUIzhPquNrsIdzAMA4rh/5hdhgEgPufGywGwy2dz7pEF0vIVZPpF3U7O8AshvHJcPfWO0NiokxP0HHbiQISixqEZ+5n5x8+YOwK8HY8RjepxnjBriO3fUA1Jyc0N5PrTFEyhf8qrzXyDHd2/DITy+fGM1s0Hnbe187jyb/N2Ubyxw17+5M0tDkUY+9vI3CwOZn5rGLQ4kKhR/xmD57oJHR21Zl+95RZ9/+8aThb/993fPwV+ze+XL4rqWPFHAY1tzMUDw4ErjcY36Z9WtwfaISYI5Pb+0rimDnOd5pZ45//qNObVh88ljwyxFDMHGf84D5gYHMIYjJ9+RIGoAOppzMOGYJzD5/L8BiqXv+Jxx5sYZ+qYRKNzAhyvAPbeTJdyx5WaL0RorY+2aC/3a3FElPAbwWFHX9LxLKm2fzCBurxW4L+VLBXNeWQOTpNogEptjemfp+QW3okgvi2OjFIdjhCrt5d11WO/XcmPjvmO9k8xdMwF7gOrUCBxrEeeLnXGKiq86NTerSW89xWycxl/LKj7MJi4ayC6/4aADh8jzoC1FZ1cPR3lJzFmVgVs58c0lNs1h7CI97cf8o5D31LBY+AFCCMEyGKzhvojYbzvxwVz5qLF/9cxEXLsFsX/XoIqDx3RqJDdQWS/ymta/KWZlDFXwkMQO1np4kRd/MGOzSFqOXO6M4Q0gyrTpMrjyyjpf3rjwQNN+PW8wcxCv3r3fLBLlb03wVDcksVg+I8IEYf+2Gpc5FMMpP7deCo+/fucwaPqXh6rBkITJCF1VjlZozEXIAb6K4ksTEgnTTOTDg1nV22nLoStZO+auuzyYZQ4PsK1R55urFA1F7sXQf1CR6UvvJFPGOWpXJ5Vd/erGSJvlh2YbGOsqPxwKPCYvi4o+8yjf0ei75969ZhrCg9gQP6yxNY8di2B9lkSzAUEUa0iYyTtyx/xxBDjt8zwbuQVW3XphmlhiInHxFaLwy2ILhM9w0XiIWswjX5I/BFu89JdwRmIAXOiz+CPvQgxWzXryaV/SQmsyJEbQEyq4mYMLlvGwTfsojn+rzSQaAdp74UIZejPCHoJHtquR+8xWlqlNHaaaQwZeAjUfDDK1i/xwjbBWwLA4YIwkPSM5IE9ba81y2BzfvMfQeEBhe14FFntOgmi6wWq8Ezb2vaiZoAAasPE3B8WdQISpbfOWWyTbq4wZVeXX3MavXbMl/+ZVXkXluDGmfvPHYVK6ZhktB7BOXoxHpz5z8mfMbTfnyLgIWww20zLBjpgP/vpaL+jlOpbvjfqZL6LiC6linyqbD9fDfl8RMTNA5zUkPonQt/UCnhsdd1rry3hk6bYK2uw83PCrHTG3DYbTAUaZmFvzkcan923me9GFGzniYgiNqZeaj16biIXPhoEA9WuEkx+u1ehfHr2YnnS1aNwgxL02DItFXRwfbjdnddR9LhyJpe0SFP05BKs8y4ovBmNttvWVayyiZ8ESkzetulmfi/HaTA5ulK4/nuWfOE6YdyMsZmRw9hYm9LTWq2PmIPYPTfM5PvpW3/qUf3GWR/qxQ+73HPCHAMz5oQjo3IQlLzfUmd/GOBF065iJ0+3Rc36zYUzfV+YBxio5Z002Bj034nJwM8qIOToJoanN2nu/VI8ZtQgrN02x40kB4uTzzDzBsjnQf/v21VeF8WEz9e1L/hVb7of4+/Z2PvOdzRQb0HN/buhYBLqJf4zlrzws54LJc0S/6yx3Pedw9BnAgLowyjD05LTnGu+8+fprHk/+/PWnf/2ff/tt7nzbfF9F72ezsdlzSk6gsSasBY8jcAvqUFUOE2xZq7eZZ3hQGfz5GE5J8X/ts9kMlDEosEzbnesSQ1FVGjE7pndMzOCacCzIXN1guZEeudrYN6d8Nj5PUrgBDhaP1zDAjZrRtve+Y9yuC2plcI8DMaSpM7LJF5C08kRejRbBA1/Y2Pydz8W3fsjzRFf+awC9LXboOBf960EJho+RBsTcJ29CfcxHjqv5T8l2zmPBjuVL4KXLmIYPstPG5xhSjRgNH/FKpDWI38E+GBkEc+XbGwybBPzxcUox4HG8j6cKENqsZbhQA9MIp/Z6dVzLHMuU6X2cV4mkOWFzct+8sXnkwkSHKLzJZaIfs8oGimLi04NCH9oiIwK+jRSVsvot5trIS5xAATn1L3Jw3jgWAbvyw6Z6AEa5NpF88D36GGBjy4B4646MeHQWIoPlpg32aG+dtKNW47d5gWL8dcGNtrHSW4sajkrwjsGEqHojOi++JqdWa7d11oYa8ZjlY3FxgZLAXETddS4eOm00vzVGu+u2ltYtk9Z4kZd/+lkj/LYm+DKmea44qi1DNHc9VX4eMCAf8jJksAPUOkewNZsYH4+tsz4TpMFiXzblY45ilGc/50+sxR46M49XBFOzVs75Ym6NxqzOiyV/fDNwXA7WKjbkhNx5Bm9f8hudvvZ3PQHEH4DmuLmtTGRDqJGbOOZjYBCgIP7WFrTlgpPoU7Od12dnDz9EIPLLOUiAtOJlIF8km29NmgZvcTcQ8E3OGk2SCyohLe7CGWdImtQEBumwyKgLzSBS7JeQIRe5LojqT58Rv8Etx6IucezgqsPwXR9S2bwsBPOD3UJkmtaTZfEPNzSC16aluX47kuvaSQj7NIKlFW+CZ34wI+opUsO1e6EEeA8Pvl7A4hC5J1nGlGE345+uuWjnQmx9fuCCozWYOnZVZq0IgF8W4sRhlAcNYuHy5ksuJ09JLM7U4yV2xglgHPrAgYvkYI2eQBvPvvKt5TwGw2440OcSiTohY+OdB7rdgCNnM4bMW8yWO723EjpypplsyqUjvho5E8sLyMjlwoNrLvx7UdkNVF+VJYm02HEdzEUkfH31B8rbnjGhXCZ08A3E5o/o5s6kxXrcjYUdlm2tNWD6ChrNxMHmpjd1GqFVgAP8rxHarp2jHv4OUdeT82gu7unrVoaOh9ZhngFauK2MuB0X+54nsSuUnNDelQJkMGKzPkiOzdSr9a0ta+ETLRF+4fzRJmvV0DOIrU43j4OPvL+nV5S1JgfsdsPgeGTUwmdTZ64zldjEwVzfGIdmz+/Y4/udr5BmI4L9tI3X82w5Rzk2nneSQ1Y9MdpSpV3DBFBOsbnvxMB3oKQ+nAfevyKHiG89PwWAEpzYJIdwoItPLKYeOFoTgZmgQZVD4ypEoW2Th0X0wV2ea89b2f/ic9t/NS6vqlMD74/B5BXq/ku1i5+R+P/7oXmXf1IlOmvKDbJpWOyYeceLG48MjYM9NY2vPXN+c//4khp//Z5vbP81H7f59pv/dg3+v/76n5/++18e2zSNbXpqmrZr0S+rdIlqBAeAp8kvMc9FHUmk7WMgSX2bryKvrLyolRv7BAVN3fhKaGTki06OE9ZYj0+rGAHVCgb21im8yIa8fvr5N584+TNfjse51dbzjDH2+khPRjPvmLVWf9YDstGlK370w7/xBZULNiox176YkTpPdYsdXRhlPGtAHsTl3w0izw/rQlgQOFr/6ZF0Tk+rlVKwnFdjvcdCvmtfgnHBburoaBCpk7YKazNzLTiU/rGrJ2yO5+DX0bxkPox1uLaHK4VeMAbOK1iMIq5s8A/UMhjfqMVmWlOPez4hA4kbnq6zddGs8Y+2svpQa9quz2JEBFgOnkvBau3rVXb11Qw7kDJxXSdf+WGQ2+Jgpw32OmBQFnOSTayIp9VCtLgM562p/VoWG9hty3VDWRvidaDZIHvqN1ZZFmf5xnQoyzuTYW1u99yM3al9kIdLn8gpq61F8wcXrKA9uYkXeR+vygoCsKGvvnjKdW8wU2O4wfXqWuJHXDhszNoFAFn0zYXsWuuNhQSb6pnQGpOeUb0eOWTGZPOu3VjLA5jMsU3zb4OjHBQ/MUtC7Zjj4fzwAjrNCDFCfkisHIMl5ngPXTO4Uvv9O0WI1sGqLbh98WGhUePKaeMOh0zFDR8Yv/w677qcWsgbOyzT6xfLda54pmCiSKMw2G4OzMFI78ZZ9Tir2bg4F177xRtpYYaLsqVC7B9b45VzdDpj/1rObKj4hkCSXeLYHoBgqEMIBsXBkaTS2RqzcpVHfG0QYXcks+BKCtCCj3zBE49wNHr8d+Gd5a+qenjZamUY/o4vzgyrra2q5HEuTj6wi3b48tc7DvtHHG2hOV4O1ND50LCOyA4/1f4R3BoXJ/K0kx8uzjnUf+3LfpXlIYOYccEpRtRllWMcGK/c2eFTK3eH1EJ5LEm0Oz9lTSv6/NikVMwKkHNhTLyxqWLoz/kVlVjR3Z64GKOkT/zFWKNR20VHLrTd6MnrhGVQ/XJhRm3kh2NMWPfdqK9u5/odPBxAaA7WmAvh5Yg6jbXv+tf6zKXT2vaSs/YcweLVOssdfOLy4LcbQolag8l5ON3QguNpPZlZi9AtY/wUKlBWl9qhSxPvGCpBGn7oOFRm/SLstHzVaIP0OUeYwT3i/ePS/KjdXKgm8c1F25izthMB6DaMCkX3Q4s9fzRGga/jHOQe64s58dShGFCHF5lwWYZcVrf5dnaKkXXHavMQPxhzTat9XwmObUB2451ZecfZ84K54TxoS0BrsPgajD6yBs48YOSjyM1oX7nj4/B++WDiem7Tk4jBsacubFDzanLe5uEGWZSGLx/yDjp5jmC5t4bYBge0wfa+wzmROect9yHfdYIdGNkcZ1Aag9vP6N4YAG68t+e8MR6cBgPK5ECDwmdjJXpu5Svb883axe2TAtnsJv6+Cvtt3r5Nrvx7NV89f/IGd3OEn+PItvYb+/JDN424/MxmjTIcf8aLM3nhdZ5owzi/J7mM4c3n0HnLOV8W99//+W8451X0v7Jh9aMzfQUdnMZtEGFYG1/dZYbB0ycJ7oq2ktyJfN2Ehyz9NzaXEJ91taadRvyPhdB2nxQG2se0sMO2DO79k6Cnjoxzw4cY/dK1nq+cA3t+XR9GIILLOYUv58Gcf5EiO3P0TNXTPzwMjCbSWWB8K17HyRbh03Z9Of/2HNaRQ7DgLQ9qrl/5Xb+CqePwPDYOYQ3KvVys2UjFQTnrs7GFEiBx0dVkizDekaKb+xu+J+8daEktisF51lnnL+BmWIt1JH7GCNPuY3bPiUpBxOTKvN/LuxqPHIbHAUQUbOFXb8FjSeD8yod+B/io0MvZSJRrNlIgz9xEqth6gFObY6WEWWtVe+Y2ByUjvwhdn5BbzJt7vRoheBvftSGqWSi3dqPfNbrn45sFmFm7JeS0WODp+8jkNPGKMo6ZdDS8l9NCZb7n3WK64V3O8QZ7a3BiM6AdPM6zRCIej//gm2ejyw8RLsbOwR6IsV99ekmjD0YREDLtHNWVJzIQXAMgzISuMVEg+uyrjdG01ddRh+EZg8UjNoFtoKeZY8NW3tjlDQtM6uQsWOZQVcLNumg5eRBn+OqfSKLiE6itpS7j75gwxwbbxm28iaP/w7ekzpoIsbUCLL/GW94N2mNk1oM4+KQ1IlMcO7NSmryyQtRj5cUQyuHU6gGuxZwD1Ck6a2PsBEG2vmHTdxxgBNdZs/HYmRzgJxrB0uTf4R6rrxf58XM+sUfm+wDd+DkOwVOADRA5rcf47SD6JSXGMToG1lQiJINjfvHaBrFiVFYcjsxbMDz4hcar77ze5K+ZMMVExJT4WGmiYYEodr1jgxyOsadt8eW+UgEjWeCR3zqimBYjH1jFlVoUl8eaQWo5InvvfJVXj9HWqlGCtQWBN2N/6+XFEhETf3WNKdAGJWL0zek8IGGYINakTsceLGqSS5BP/dhJiZjMsSV/W3u5qM1c42orN6xipMSxpdu1GkkNUZJzcPaGM7C7CSen1SnnQRebBd7Rw5PcCIDfieeo+WxO9F4c2nesDr77ysrhiGy4Yg91CSGnXjCK3G5i4/DRBFDSL2P7UAYwc1zGzRwfCKISpzzwrYN2O2VCfd6bF/1Xhpvc8dmWOM2qvbWRCBsoNL3Ypi7rWz6zY5hcpeu4aPKdGCsZ041sFnB+Uo2OWYgubqaUm+YaOSKnbmLhhIdrgWEuCvoYkLGnQwGwoWH/FWwE4Ga8Q98yHaGSdWDGePhkFAvW4hggOuryGURsEsOaZhOT7dnYshEgOJ//bl2J2cejbE6z0ernrPl28K4fjqRn9AyMX8HJAXSfmBpumB//2PLY0k15+rzi6jw8wOJdB7vhF5s6hhubr6HdmEz4jY/ZTI+vyUaKXIz0GQQjGvNdC/rYURs3G4MHboz5zPmXv2aj/rWfr3aDnn+35ueeY0OUPu6R5dwPwUs8n8Cj8NsypA5EzeqXO7xzg9/mgfmOVYFrreuJpfrF1WEkxE4uPKnBv3/D71///lc+g/7HT//5z//4hAPoMOCXVk7zlvDUWu48PvMTLOzHo1zH93DKesoIyNzMOwN6BUHgCYOuRfBe8tJwFaCShl9HjIlRmj2Kl6IoJxg3vKwfazybdNYmMjhwrpVT30Gw6NQWLtg5VDDa5Uj80aPZWtVvbJHnhsvQgbm4lYfvXPQQC4yezxtkcIgTEU++iNjUVFb0CMaFwPowf+A2vmbkgF0mINDjw8F80GdKq01m2DOhpW+F1qq5AaoJOPlxfddkEOtXGAGHC3e6xdzeUCcos7Upl8bI2AKVcyk2KGPyuTGXzGMbo9oIn0MEOl75TM3A8z+YNHBFemJg21av9b3y+m2M7ZtLrcwnQ32NlRyGutPREUfuu26Ri4NC54kl84pWgdr1or7BNo+pdWPNGgK0ZcPnTBBGhxpSEtMgoq0L6qf6sblzI+qw94FACV/kG1QElegrX9RTN+RPLj0nYo/fK8+0d6hGQV/XBmju5bYhG3OZj25yufHBLbdBbuyKokruU1/stMm8596QkAwEofzolgj9+mo1h4nbmvzAfX01FSCj7RHu/WPzQhu9mMOBx3zzyIFre7yiv/kUsrmAeZv10QNZYynb/J6a1Cv4DXBA+Hu6ZsacGqwB5vCT2fg2hypK3eO6aI9H+ZHPqkQTUKiM7r4r1sZRjfuTWcfAvDw6J9wJoEUOcug7i51poe9YdxzdofTGX+Sr3/pv7sT85fhmcgCJNxkv4UPQrFsYzJzaZzQTOlaEgGSxi4JMXcS7YB1gR3txtZxUi9EEGsRCL8hw7QlHHtbu5DAz8R3HACZbkLo3xj64NX+tnlzwHi5eGDZWRKcx5IQ47EfnSRLdqaMe67/SGjfqYhRaXP3hvhlFmt9cpigjf3Iin4uRixr5REdy+bUNyNaBdbAe9lxR9YJIxt6py/Hgxp84BFazuBWJ5XpHT3wufe+i48tFTWJGvuugHtBwiPVHMy8l0WPyWGD7hJfTCoAjvvPt6HNbG+OeBxHQqJm7MI2MJf1wfezgRNvNBpsimpsBHhT5nQtL5YczMcqBEZhcNMZUH8htftT2juu065xZYygOl2B8tExhaAwUY1LWTHf0GkU+ecHDjwXM3IviXCDjJWdqlIko2E4MJa5hIvPL+cN8ZRHu2075102eBzpPCrEzJPyRC3PZjmnEHWkSnxqDwXjInDEw4xHdqrECv3HgyIYkNWewLcbCIErK3fxhszif9vh6Tqdfjh9PROAYBj4Rlp5zREIViy92SIkV64MJJ8gTI103MGySMwtvPzqBLnPfUot5xl+zwfv6NV82xrmG6eyaXN/YAMbbmbH1CYXB1zhjqeE4bf3tI/dV1rzCy/2GV6fpv/Ky/tuCw32kr6BTa1DTpt/5SPukiJEj8bd9XSb/+c4AHl95NdmKY5YbTnQ/5y3ZP/v55W742Kh/zc10cj/9hX+txv0UFxpY1Ee+s4KRoac+23ZI3/vw1bWGWOqV8pLveKYvs2oX7/SBObbjDz836dkY/8a/hfvPf376/fd/hWc+ly3PPl677iHEOwXy6fV+wRssAMzv92/l6PlUVg2LOjb7Srf38k0wFuTH565pnP/Y9nGvYxUc8AHHx89i9q3dreOpX+xgkrA25NTk6omDqnG0DS5nFP++DJ7f8k3zgHDumR/WscmvuEQA0wlQaeih6J5QwcrKpqw09VDc6hSYH5Dliv2+o2NzOXYHJjwgRVw5OZRW+cCzjUi05b31MF5ydoNJjjVrP7UkscpHz0TA+lljeSBsJI6LRWpMulKY1CajH1qrxOWEvHrRFJuxP3EzWG7Rbg0KBtdnvTfC1Gk5yA2Y5B7zwYhv7KyNOWOFHkM4MG8bRk6UKrj6a1c+usq5nuWc8WDj6RoucHqGxZ66AKq+68DQKXYa3vjmOTn03GgE86hxh2CmNQLxLsbK3txfrBO7EJLouRA8zqmFmhyB3icZjGlNiZnGwfowdGJy6maufO0mt+sDyG01G4baFrf8YxcVWuy0nX5J7/3DfGoe1VQnjtbXvKK0LevmbZ6TD+qz3kyW1gxuTVFGHT/70cNv5+cJBgXxhEt4DGQN53hlM0rH49NkodXWA4tPlFblxdgxmi7pntvxpMYVNjrzjDYXhDsnPuMe0g/w1aO8vsXNfO6r2GOrHEPBdjBxnVYhhxODgd45VjgqPKZNLplhuetDb0ueZ99lnpnHsLkSv3FrzPFTsvmAfHIwyvjG/dNjOUSeQFtr+wlSntUrCq/82hrvM8t5i/sEio6AJkomNL0fgrFpIVCOLWb52cdpQvTBG5vPtqRjnmaGhti4a60dmxztoEFRttW6ujEYlbEz1naKhIo5HGlg0bboq7tyjGq/RVt+4kZneTiMnXiJot44W5uio9dpYyuAS8TmOYse39b3+jmK3YDXM0JEtOoB6pyjuUS0Nurcc84FjzzikIXiWmqZ47snF2OaaQo/9geUQWTBqs9M9alcfYY0OJmvxWM/0TW1tijSRuWgORRbXQ5anfg/zCck9bOtnXGPVJV8OUm9Uhv+aPS5MWtMFt18v8+YeW5gMKS9YM3Ui31kua3MTZh1aDFah4arJGOEfsucUXtAubWZvHZzRAivg7lgxmwv4PAMVPm15hpgH9WBZLBtYtQCn9yC1zVrT9wjy5iL5AXTLljDhOAi+0pu6gwXNqk+eZXNBr7WKVazFxq+YZDY9canjJYmcnKgbe/4+Fx/9dRkuOjEISDwTFbVxZBxW9ZsYuIHF5beuLmf9EklHSRwbKgXeOBm/D7pgPfm1DigNTdispnxyR0w5EYO2NDb/S+HomFCLTk3iXPWqBBu4HgLN+v386zpl/wLLm2ziWaDg+5r/pdW15hXUNOo29TggwYx5sY6+qq55wNvhf7mzVfU8+33v/DqdDCoEzXhuxgY+8SVIViHhqIm/W3vJDo2oGSK37XJyDnLw3mZeWoQYrllQh+wrkPG6JDEx1plU65JZL6rgHNz8DTEPa1P7hG9viMWv/57DkUTgXax1S6Hfo/AXWtCbNwdb9yVE/cdB8S/EfLOF8Lxlvx//evf86/HeEWZfwJPbeKXdXD988RXqhBx8+55i0VrqzU+DCYYTxLapkPM2tKz3vy3i/wDtp/+4g6S5vcLpK7yhyP+NW7+sZFLZjzUZrah7hiXnEPoION5lVFtweTJpbw7ITG/ZM0wow6cp7wbgk363lcIMtRFgA8/YB6FMmJtRAg4vQfmL5C2YxR/4Yg1dRjq7agBTdjxSSeHak44w4zJqMYvswRZCvTn/Cc4DR4+tnVa0eQ6Eai5MSQDHqQuLsHiMdaTT5PzcRrM+t8YV1ZP042R2INVvlKcWpUXNXjP9ev7xCGgLSgCcc5cP1SawDNtz7kPWSbVlpe1EwyPaKgdmPgjyhEbfvhVMjaO1/eRYVZf+ozyuzwXWzzRxmbBI0NXPx0LZuwclp85bmVrUj4TPHpMymPWgxjxPxuTMUVGk5s+T1zkVRYLXOcc2mAhZxWEKB5/sMZaC9mgknt99RN5LZEXCFORwJu4IN5WOX+U4U47PMgTb0x4DGGu+WJnEuWuh84YB8Hjw5E5zmsrAvooTu4ZbS6MaJocbhN3cKrn3BVaX53WcSbGZlzy/MGbXBMNCmOwscctHfFQWoXix5j7veLSuVqwohrq/3z8iJYYNBExDgE4bJNL1rz5l2ej11ZPKRkJ4biuLdPVdbTrWtS5X6zZFMB1SfCuM8rBpQvc8m6N0G+DadfbsMEz+hRVd2u2PItlDevQNQicONpmEpDaXPtmxTFYG0fTapQTl5y41dL+TIYXEHjxPjWuQrjKuQ3fABTiij9kA+TiQMbAAT1cPr2ZeXEeg3MnwA+5x9oz1/acpCWKTLnMwYhgGO6DNJLjj1b8LlB9XwsM6nAWUPUmUKyGWNSNePNdCRzOSRRcotIudjCGj4rRLuFbgz1N63/kQ+uyA7wJeJz4iOBB89ihczl28updSgAAIABJREFU5BELTMV8gPVnIftbIPWx59pX5K4BZtjtRZbziHxFGE75aUY5Zk1pxuzwcNXv4YrR8m0+jaq/8YXq4cVizHUkjTGYAQdfnMxvmMp3V1ReMcw9j3O181rj63kGbho5OScGcxOgzx0JiDOvXVHGpy7yAYdXq3zFDcc0bAfWib4IMigPrBi3Vz7DCiGAeQ3MffQD0wBN8OBoHRni3hj31UTW947DWJvZDNQxETgnUnxz7wacbcJ5Nj6bhu85B774eNNX69g3LSd8fVUZ/6kfcW4xyKkNH9oP6pj2nFs5+9ytA1isy8HYGMFxvXSqfvHpEXODKzXgfMFV88htnNsa5jxxzGQaeWW4El/xYx4X4i7nglLnSpjvehvX3OIIKbpDYmNGSPn58HWC7caFDQ2b16/02dgIoJ7NXW7ZrOd1ydyHcc4o579PnrVg8m6sZtDzYM6HbA7ZLLExt+fVc+aRW3dyDLqvmif+9mYN/1g5nscGxv6ae9S0jHv/6LgifMmR+2Xy8hvZw/uv5ADN+NSCMfH7tn6eLOBdBn/niTDSE5u6aJZjhXL3DzCKsXMNWgL10aizHhY+MZP7d/hElVC6NjXOK4HqxHGxGORmjVc7OjEcwzsb09yHOL9+y/9t//df/zfWP/30n//5jzr5ZU79aa1NH1vmhfPUMU/MRNdYwSKALdyTMDqfLDqBw5ucwo/+z6zrn/nf3v/O2+y/58kXv2We2savTwY4yrjxSY3xvqLe+ZzX8eGhwAb+/OzKkcc+kcMHOUIsm/U+sUSBqQNf/NdX0htX+cRm/XzXGLYTxi6EtlaxKEFsw8F6uPCxnBoMMgIZtmY4+BseD/gkvDnoGxx+Wt3aVh8txDCyPVYSrlV1rc6ajzqqy+nwl1fsDY73Bmh/xAX+4KYuhw+bjzpwf72YN2Y8yJOgBn7CZli+OY7OTNfuYUA24IiL12KO3E60VhM72q3UzhXHvPPOarkchtWxaV7N/eSlYzB4sH6xRuS5IAdyi8mCfAxnjcSqoq+wHhDzRf1COJ6wjWM5pjbgELMZMqwzsupuDTOf1jqtT/2PbvBIongBygCcraM9+JEs1mftY4FbLJBj3/uLLsoLDvVFjW18hAVaq87q//h2WJvNnXgEJJrjcgamNUBHi0DZmRlz88AZGCLD2djOywWNcoJgw43Ab0zGImjSQ8mZ46BHPpiTA4Z92Bk80cFvjZbX+rcuzXP5Y0PTQx7LZGKpvXkFXFv81/euVXzGbWPbW6O1JtfRmmPllgc78OVRTmMpQ/0i+DhHD00G+I7g6c+1FfEiP7nOHL+lZHCQ1G0sBfqSvy1hGmniKWxtGLYmnBvlpBemJ6ZWE1dGUqgeXWWM4HSrXYits3bBLSvy2M+gZ/wWSoMo91k4XYZ7k03AKVoLfYt5TrIJ06BDauJIFPxlRsB9ANy4JqKlROVkTEcHXYuVg3+vP2Mj8LUNNgVqbWfMhFuvohxvOfF+nL2aAILCnfyXr6bFXDwfdIgn0Czw5LwnDSri7TzTtEoZGUf/0jyacMaH1K1kBr6iuT6RlmM8YkOKu3bA48PcC6cQfPMhrk3u+ONNRw7FUjAyrk0Dpm4vuHxgyQWlgaktxUCJnRc0xW0OsqvNAoO2cSeBuIpHpF0jzaU39cUHQ/r+fnDGj4v98tTRi8AUr3J6PGKjNjj07zWYdYxseznE3groOtbwhQu3hmoNmaOSmUMPG28vorfe16IjU8xwz5u7duiLbTxCa4e88daH+hBP/R7YSKYw/kRJHC6Swd8ePZs3++hoJ76eCqzNbhSok6/+RZX/QJdNBm9F7meBgeB8oGKMPWVaiEhSoalVJjbmjfd5DugSC1Kh2eNLEs5jX2Fm3N+OyrEeyua+iBW+MdRNr+Je39RhA2+M9FeIvgbdlC93GAgdTs0RTL7xmVc6t25uSlEMg2fYGAqIB1ZZ8gesMXmCpG8xZ5MDLjiuQ+yx+c67NcDmiZPMc8x9oBugb3/nlUnjLv/6EKznAnM2992M0/+VVzPZmPOFYsz9Yxpe27M5Jz43+Qr9rDG2TUNenBebVwSjOwbi7lsJiSd3/md9xtZ7TIvBuia36ACyttQgOboJjIwZJ0l9Oz/xzzr+cH5AjBZYPq7xnSc7eKE39xPyXv9zHhgx+rhAT7lJEw8Bh9vqNzjBc0Ocd0P8+tv3n37Lv1vz1fP4/JW3feNr3XlyJHy/+D+6sxbkO+vvhnXg5WaNWnfm3LifyC124PA3AlxvGVM7NsXUTcMEtrb94x8vQXE2kq/MZ8wMje9KyGzUys8k+lrqmrfk94kjngJgk57QcuRVdfj4nvfo+mV5jVfACWbXbIxv0PLrsTnqE8Eb2ydpS6P0kp8127yuUxNDTv02MciCuPNLaewbu1aItkKTB7HhNP7Y0ewj67yc1oY+q1g7Ow4Pbjid67rRry9Juv7TOwdLOsVZpPIY7NjTbuziVLhyZ3Mw8OG5mkprvzI4tLWuE1Ffy7uGsTvcBLr2rezLiQphXY/OGkcJwBuX3nmtNxxlMcygWKuX0PjohWFgxAbgcIVFeKF4WuuIYHJ4cN+1Wrc9J+Wz2KP8xJ94wXUUW32C77lOrkSdxJjtuTIp1JP7gZZT80x8vNOxOqHexAb7YhYBJrZ0+1jO/Mc1oXrr0Ur2WH9R44VNrJpGYeGU2GvB4MQcQ2sUqXWHB54vX3RrGzl68IrJkUlQp3DFO+Iajv+eS7rksPyN+WEzuMdi8k8Man1IGOba7vlRjpUXG8Obh26Jt+dOecW+v0bdPECRp6DFxH9rom7qhXzrQA0bG4ui4HW4RYStdefvrjYtl6VED6De4093WpGcbvw6HCwjT72aa/DH9pye8dnxRAkkPAdseDEV7wd/7dY0nmcYO/GSDPg3v2Izv+d8DMauFSiT8yVxh8yCkjVVcr5kmaMo0YZcXeWHHizHVo3zR+Cwi9IHAQzSIl+rckoaUxAUbvzoazrF6CLj7oIvCEaTAzpPBER4DSZjL1oMyqE8tNEs+QVDDsyxMD524baLv/7EM/4uR6eK8R2s9wEt4rrswHnj5mro8FYt+2JvWbiAgi8xdpO++dlHviegJ2nDeTTPjA4vQAFKb64G7RpTg30b5FkT9UJRjZlRA74tOhdzXIyj4bqYXNRYuchN29g4bmjGKJljUc6ZXOeo1xtbaoQ6hxYhc8a6Dw5YqPMqFPWKXTcr3XDghzmfmz2+4c9FqGHBdQBsxv0FUNxilwfY5VyXzWtl2C5fvMEjpkjy60apyK3qVLGOBgOEX0hNYx4nKG2sRxujmRGcFkNfKbVnh1ELzk34cAHM2D7zjzHzwUEOebGaxfDYtWPTmXGu5xMlFjEefNbAzU3ODXgDSS8g3VAlLxsG/M4JXfE64g8AliPTKeMBt84GwIiac05OELzYxIFBw029Q6byX4y+2g9K7etHnTjZZ6M9WOh6P3058oQEm5xwyO1LNnj8Ozrm+XVj5TpyH8rc1CgiLQLmxhxdhPmFC/5zfocbMYxTR9cRK14973kSPzaVcsWetzODz5adnkA4s+Y5Jj9yYd13M84GCTw36L4q/81/XQZvNpXcdiPsxpWnZKIDc89VclKE07Sjy/yMa4Q5why6jjzN44Um91vkIWs5RSVO7fXIhLwmYhRppokstUE3GDjqMzZMWit8uvp7H/Bfm6V2fvN/gh8ITROAuOCkxTUNMGfpiaLk2DArz2rg5Hqmnr/9/lt0nGvR5TPprAv1p32B19QBnz4ZE9OMzQsjx3R+SEDcf3xvQLiRmzcI59f7cbB7b+iTHtwf94nFWJQzcfGBXzradB23AP8Ya/4Y+nfjz7zVXShq2/sAvH/OucoTEcahFjRxd81Yn67pP6obftgar8qMw3lYQuGdFxp7PaoFAntwyFfpHs6sNhFDzfqjmnaHxRXHx9RosM/PctJl6zr+nPO7ptSBn51vLQSC9w1WMqIDNGu1BhC1td8ZIsZlWql84aBu6jD+Hzxiri+G01y3naTH3vswMjBcIyfiM3rrj01ZlBP6Q3CGCPR5bLXLYStbzM5bM5xlm67+2Gy0TWF1UdnO/JBqXas+XjWW19CdPBe/7ssbm0q21q1C+RWs3Kz38DZvcWOXXm5P73U3etrYrX+RX9bDBVGp2NUef0BGISb20wRL9bb+y+FaxPX1LdSuCbio50/jCQM6dTGOvKYGkbtWcVqMrZvy4cm4HEGJLU9iDsfKiUArN48cuFaBkDXTQH/MiCOqxvBgcG17fhRxa7exsGT8uU4/zI1bO1CIJXe53HyR0Y6+EwNv3AbTjCAdyH9i6hOEiWkaxMtcjIkBaLmXC1jWIP6iMp/aThBL53ixJrwh8Vs5gh2nb+blgGrz24oQ8OROTbBJD94/GzzTVvWRuyvxqN68F2n5dC5n6pOf5j/Aw3u5bv13jveue8flTfD5P+iIb5EnLwtzKUwwkx3AfwCDQwvWmks1E4FCCcUUDIK3eEmKwNhp0gJh6wIByzhK7Zhim2ZB0Gk6RfeEQIkRfhw3RwOMbrWrY944PCLwsyfLWeSJszzrOf5AJ9ZQK/2JTtdFzCB88SgzDe5ByuhjtoWEh5Iik66vRGRajiedplyzYhDFQBzWn/HM7QRS3SWKkMHEP7kvy8HHgSEQC/csjPkWD74+trXH+MR10FqJW/BVl9QEHjD5nMAZAJf1sr6eJ4xzoT5xNOXKMrJeSDYGqFzw4id0TNiQWlPeKpzGUZxeF97zzzia1II1FaT2h97UvNS7jusKbu8D8cE/P27GMZ6GjJnY6fHtEzE5f/yrVV/My3hs4+QDI4q0i9h5QavBj/NpL8R3U06c1qYbTMbori/DIO+1ccbNJzLiv29JHa5g7DOHjrduECTvzH/OBqRjptS1nIEgSdcDc4IYSLGHmnLEGD5AVerFPmOnAmWMXZqGdDOfajLTP3JOAVw9RzLfWrhRGjts3dye2lGc5OCmBv9w4ifA32IL/nkiyM14dFwEEI9zk/Mx4/0jx8aEZgy8zcXDweUVUzcwsXNzjj8BiTdrwjzvTK977Hi9/a+8fZmGz5/5f9vwppk/efGTvMj7vf2VjSFf3sUruWzasfft7G6i8tZkvogtcd2kk6M/IBffPkMorky+q0achh9GpuIc/q0TTxr4SnHOHbjYUhbuVdY3nCaAMjTMEceEzPrQVRIKwU7C145p3i9+TAiCP97UJXVwzfLHiU1r/0bBgIazg505pVaub6SeO6OVz/okYPPoBvXr97yC/I3Po/+Gk7H/+O9/02eTHn/Whsc5eeI7N6DPWEzmzQ97HMISq9xgcNeadY06LXYUzbiRZT1JhPpLtyoMP5q5kSvSAn3owUDp37UMty752LvnPnPy4v+w850KPFlvgzN/7/2oBk8qxR4O1d54yIgPAfVrUUN5RdEKkPnTokReaY/CmE80dSZADDMZZ/8GjVJc7rpjQ7kgt67rBEeEdNUPWCZGRoFJcsZWrcYXi3OxYRug6uJ4vxKCXOMPFucqMRtyA4ufCTQ8Nv4RRF6iqwcPwM518gAu6GtPMPNUfvEloLekjo1+UV4cwhTPmJK/Ptjzsx7NTAobrJHjxzUWP7cumJBB5RiuXrn2sdG32v4NKTskjdccrcXki0/cj0WA5dNcSm1EqjQMgKd6fHG+3NDGevCQLw4aM9C+Zkc/ONjYhlC5FaycCXfrQiBM1RV9Yg+nKoZDJszjYO2GZus3GOqHA5w0Byvth/n+7ds1B/O2m/fr21jXbtf3DWsCU4+9z+gHBQPUv2OEGVkvegw44JE5RpmaLypzGHt9ENIaYXPZXPuY1VqedYyf1vbr3Z6jsRLnrlMrM1SGS/T5gTfytkjkX9oepVrh+q/9i79rAc7qa399J4jd1v21J/iE/+BVPDKO1t9yfuPj13ggTn0uGsLqzTeWBTWOMRdgLGHycrwAuD61m7V/7yf64pBrSDEy9L4Kn9jLc+sOlYjP2mKLr+dJ+ndBGEfeV9ANXIN9NbnQpVeYFpQAS7B5rw2RbtvAlwzM6vESQX8aJiZ2JJIerwhruz7Im0dPULxqm6OmOZzk1xurNGPNIN2NgWxb/XczsdJSTMwUowskE9WdF08KQe4S90RbS2kNh8auHhDK1PovAnR7EvEgAtmtgfYUIb9cvLQN4tQWlJ48cyKOVWvXCdHP2hItyj3hdgwOBV88uTBLMkod3thuDLAfeTXNrFGRTCwEGoDe4c0xCsjZutZWdWWrQl/ImjLRJv1cXPYdAHHIr/mxEFM3L3gy5q3BiN/4rlcJlkX0GNFpnG7rFAET8btxw6ok+ypqc8CMy8m8CORFbv25gsM/v+nwZOxl52JyDtASnxEpdlU01Qe+buQ00NoDeEck/mwy0bJQINHza5zOHSMbDnzmWHZriytNwumxzdhXzg2aOGyg8kVkcNN8fN1MzEW+nMnLOCKWVj0CfwPgTvPxKHqm6MVXOQbppDDTS5J8xj+DzW1CBc17RZ97EKC8gSEmX6CleHTkAcZuzgG/sgZHjxySuPUcTD/366+rm/9VzrQb7BiTY5x41fBwzFzMaNlgYQvmubFxSXOzHjlVIrJP8GQ9vv7Mn4C+6gqOm0t2DvP2d16RjZvnAr7w2Zz6+fVszNmc51VzN+m8ip668BZkNlLcp+T09HJr5eQZduEQYHp/p4dvxNZI/Y5jWmvtfcIN7hXrwyv238MlK5Bb8IBPby5K3ClVHM3WELMdazwW/l0UZ+7X+1CLvTbhmnjW9gs1S0w2ULHzgiZ2k0x7/SbP4bc4mIIa7eEiJ4pBPbLGvMuBTSpzdL9DPI1Num97z5i3tpNzn6zpOdGcIo2u64AJT6AECxnnz5xDfkn6PNaw5vBnLcHz39KJ3/gM4UG+NOkMN7nXwBjqYwu7tjkvY8PjDLzwwYVmXYIlhwh97MkpyzlmnNjps4/18dWZngZQxmuriLUhRg08jkXG9Vse+Pq4FDn2aFln8x2JHtpVLuDwgrf2+qPHH1qDgR0OM+8QSXk0HjN4DL5q+OipLbhi4Bfx+sn/oDFopvXFKm1wwZcg3oVB6a9miA3JYXxnFGaV4Jf6vq2zlX3Ojh1iIafOJkTo9TuWml1pInvexD0+2sMzPwdyXEmPXG3E2lqs7HiQRJAGp/Y41FfcibVSelrjxoJfhV2zXbuPXo61HWcRGBMDtI4yc0h/66yJ7rV27qFskBahx9am/uqCRVvv5aaU/FKD3hen1/iOT66RY1f1oDlNxAYyhvYIappufNAST4R/Yi2HXY/lVfP1C6/8iDFchpDYEFl94zQ6mNbFxYomvz2P0gdAnUDYg4/3+JrLxbn2ke1jmb7FgUHb9CXSQAc7thZtTYs6YSfy6KaT0dZfQ9PQtpwxjFV+Ty0RLR0GZ1xbq+WaiH7XVzqpgi6px6znzQ2oC9b4YHCjCXBmdx751LO2xVjr5c15oqaKj1isjaV71n8fG4jseRMPM4o/tuU/YEU+NcK3RJc7KCOy7zlFDp4+GG8Ocb21102dSIRTG9GEhruZqYs2OfTfrI1xT4qxXmdgWCQecEnarglCRJ0ZDOrwKCR20MFv/dvfRVU7RRI+9vVZRDFwmxPeNFBG9vIitGJD1Pu8Yh+NqGNwCjc5wG+fSQWnvINH7nKPbHMwiuERYh5uOhlDQadodnpGrXPFcsI2OMTCqOGmxg/Cniytebnx1/L4JTpj549f8zZxgzZ+8P0jGq0UeyGrb0TlA8jkjyf8ts147azn5kD1gMV3/lAfz8FTtzb4Bbcn+MTmomb0hKx984s49tQnI2zwPgGwmcXAcRoXne8dtVfzsU0cL+a5I6Z9z6vm1iBTX41DCBG6iecssl2z1lMTffXPZmlfPWHeck0MyEod8tV5nobjtpPfxBQgbsWOFYCFE0s/OKnqmmG73Cofl0x8C+/A4IvtviMDQDeZR683Zmm7oY9M7lb/cojFnqfZGuhB/UCQCz6ZeV+jrpRCqEhzLud12XxOPX63FGJsHqbMIT4rE6SiwIGjy2BjmPnGYUB8giIe248LcF1yWJ2WqckIcO2rfNSpn/fdTSvn0xmT6zOve2QEDQgM5ME4pP1sb3TIPF8z5q3KEPk5TxoxLm8wSg8McLsJ7uaKL4OLIZqxf+IQFZzcL3/Oq7Ce/9w3IvvO24Wz6XFDkVdVicV5cN9FEdfko23s2ZB3k85bq/v5837rd/6wZMMHFpsobuTWvKjj0PNKvzzh21dwobd5vvfB5Ba/4+usODFvnsmDtU84c+TdCTzRwE89FzvTaWqIlx/W1LVZ3dQw6PNYQPRBAvujdU38Erd8cRlPepCvb8dOzciPBr91VeRk+KHLD/K1cRDBWAxM5lk/N8nBPPVqCL/d/c8//zAeB74Qz9qDY9Cquh75/+o8kRK5T/Bgw/kDgYzBZk33iRqIeO6Aw68xby2Yc754ztDHv/yyNlH6ETUdw8H55GyGi9fzubWIz+gI2HjN2bWCQ2rBx024D/TczZyaJ7Y6ayoxOYCDjsYxM+vOnFjGfWz2voiehj1tfVvTnVXHUd6T/873GuasmXYcLids28qs+QffX87VxsamXMcaiPygL0tm8AI+KA45LCK2+Yni8Nm61Ews6yxKUcU/JBZPcK2sB3kbqVzLqRLxRvnaul5GbLA3j0Ye5hO7ERqXdTYg/B3eOtR858GeHDGUhrUfsqcbPJzP3bfnRiQ2q1jw4Dz4u5Y+vj1rUqrGx818x3Yp7TrJq9Xv2mCeG38jFwZXmnN5HE0VI7s17nqj7BnAqD4t265ZHPPLOnleOMF2OQQnwc95MbbowfUcZz2e9sGMyeS9VsZRhi6/sSmbgphDhivb2PgLh9M2fcul2rHB0LZehlICbuuUafLe/E5fR/M7EYUp6CKaP1jYe0i3ecF06obMaz7sdvEZYkPTtACVgPn/Of8wHb55sD0xxQjIR+y1hRgx4UWjy5Q4lfToHL6DO2axq7E5jMfyRvaujTEGWJ4N5fEzVmt2cnlqol0Onvuba3ruXoVuXahPE8G49YWXNRhVDNrQM/JAn4ExH0PmqyfrnRoUe3496F4MYJqLBoHGnGNf6M2MWPVUowVGcr46RjxtXhJF0cGkZFYw0j8NEROD0D0LgizksN6TSayxsSRkSTt2nZ754IoQU/xFJK6B69+xAhWe7AgH3kV5YmGpShMKmAHjnHyvLXYqGtXZnjS38GuTfvMQtzGsyXNnAVPc8AODG2T6R2W4GCmywem0J96o2uFXtMZmMwqcuNfSGC0SFMVlWvzPmMLlbO/b3NiAFc88ArkbTeLuWgQSImLTX07I0U4wNL7VMnOkdsic3gP8Ryb3aLjIQ0RM8cnDeXs0OPGz7/yA0F5gNu/W3DVm05fcaOYWdy7qbHTQTtO2w3NEJocQePXNra7w1ir5w72t8bGAjzZdhCYxcbHec9h8ebupPtFMXSxaQBpn4Ldb7Emn3+AdPvqybmlbPCCj8CJ2wSGXBvbK3aRPPNTegiRm6l4PvaDatlwXdzC9O0THZ3MxoT48AUKu57PcCUA9kfGLJbCWC9380XduNHwxbFBs66Ay4iGjYlWR5XfdrEPMiYT1mKYHFxwPxtE2jvgaNwM3IrkPUrMds0nAiFeVqSFQu3EF8ce259DfORe/sJninIzvftYWDlSFp9C+cDEdyFYxSKHnq5q8fTy160Y9winSXrgu982XDTObJ+bE47PTxOPJEfEiZ4P9859f8rb1P0ghcVtvN+3kHo67eWMDR970xPYt7cFlc04Mv7AuPUB0Nnqpwn1lsc2EeNujqb5nBHg6okjzrsIgTvyrON/bkc8ls0/n7u6mLf1iZJjW3Pd+6nmfnLwYgRRtwtBhZ82ZULf89NyroR5TEyUJ9jffiJi2a0J8fZSGLL/xMY69BsCXrIPYpK6ITsMlYODyFzy/jdEEW/v/5iMKf/zheviKeqDLv/Xddf8654xvG8//WOejJeBaj3xMwF4+ExP73DhnzGtimn94UGtoc178nY8CtL4Qzvm1fjwGxK8cZr3NiXoQp7EyHDsyj/1e9KPnYxq5L4ChlseSOIRZ4hbbJ9HCZ//OggE4OeHFjRhZdSBmXh2y2uQYNeNtxOHeiBxPcbRZpMiGl2/7x/EaPWCJQU4FFF4zRxxAfxrKtyWGInlcvmVxfbHyPItv8bGt7+YpbHisF7zqE7sJIs2MxWCSxlH11FUhB7iNcjci6wHe8auwbATWWVDjE8cA5Yy261f+VQ5Iwwa7tWiM5rTrsYGLsdDjb2cwwgzO5g+4wtJZ/Vy0LJvaTEyCmezOmW5dBy75IRPaApc1brhLKUOazHJoXTNQObmCMzab/3EGN9pE9kccR6Be3K4ZtrmdvNagCKpyaCyO2DLPeKZNGXlEc59FdQz0gU0bOl3BqbMKfcbInKxTs9AeK2VQGA4Rtdq35/wTK5q3/nXvepz4CGN98OK7raPGMUYEs3KaLHZzmJyIeSHE1Xhlg890c98eDrSTa6Y7PnHJn2uxh+c12qwn/0wvl0dnmEG2/kStj3XQtPaVZ3ynGNsQ1b58hA2vzadG8O0KoSdcQgXuAoqhMfrJ7dRi7R5dRPhv7HE9nefO4B8bg49JxsdmsOBUmfRimAjR4Z+DaEDYltL6mFQ02NUpE4ELFjm+J7fRNe+CrS5/kQuUI4M6KmzSCqpqMKxAH5KyztQCSxDj207hYlH06janekpXqLNh/rDGinYxNoF7wkGpBK7t8NJ3TzhhcgibmFvASbIsNFZiToz2JNGremPsIUD1beS6ZMyUIAzya27zB9nHv/GDy+axOOSy9XKNCSsekFht64mJSJ9XBUbmuS5Kw84uo/JpfoODjXf0XEiFY65rEHg7dkOk59wEgtPT9gGZmlFbbMFh87Bt8wK+9W8kLq7c0IzhB3Qmmzd8FqM2w+Xx64ZwcjaPKt38oLT1DiSPN0O1AAAgAElEQVRuk7I21uwjeHl6zsXPvPCfHCmsiDlwQcYGanN2s5YZId34ThwsbD0RLIAowfKVxCURHlBB1/y3j1Bdc2ydYwcR5BmYq96LYUQPdyMSvLmoJgnPoVgQz3UPVuujUBkh0NMa7q5HBTCu8sWBinFzKlhLc4V/rKxDfDjxcvEPgr6TmF1DNr/C5whoOhpO3OwuJ/Oo2KM1GuY4r95cEqh1LoPqG6I5xwq+WdDzBEbGuznvRj0bVzfntXXTMvYQKH4Jef7nzu+7NZJ7N+m7dpxITYr71fKUOjXkJ3zdqM3YczP3ta0dNoz5yZBj+haJzuwTnw01n/VlQ+2GNvx/zrftM/8jH0v/ln+f1nUiVzZhbM5747PJvs1deb5dPJ+LdsM3mz3Pw8QiKhg+CRMi5Fy+L6fhJs/NET9ok0sV5geiv+MTfRj1iY28O4B/Lcb9YB9XGru2OFqTwCF3M0kQmsHoyo8YPnafuo3vxH430Pv49Y3/VMBjPRXGL7XJoDdjoLnx5GbotY92eGAOX3jhASpHHlL7kZG87Vvsrh9vc+ct66zBX/kegfPuBp9EydMXeTdG/93cF/+nOp9j/yU33+mQNaMZm56fxPUdEKzX3hKva9e+9s3HLwzM+eIXCGYR+HHN8y1vxBWPDb5PKrUm4NuczjiCjdGkOdcbj1pWh1fsqW8aH2HifOvjmyXzbysPL4TYvPSBV37gp6/HHMCg1hHzpPXbdrb4xoohjI3NuIEmBB65FWxwF2VUBiiGTthWJa7+mRtDzRwwQ3i7jhOfPMmtvssJ9cqrWYvb33qYBx7wyS9pEdD1ZJgGhc5VKltOGx4bWt1zBEsJnpP3uDtvoNhEmPrjf3KJrq8iFxU2olmzM5toBMLeYHMfTnjvik+esqktcDVfp51LZXiAN/r0cGse5Fa+jfjjEfBJVNVkddYKITmnw5TDaSPc+cQpWhmoIl8G488aei6Me8/NMdChByPJI/P4kMc5jzXHYvPMsA7a9lwL28gavcGAoXn+dFRuP46NpyEAaTmM75gOl1EZe2JNHbQLqVbi7UsVOPkBPTXBp9zHZnlg4wMGBtf++AlG/DbobF2NP7UrNmDgCBRcrZUpqvIAHf/BvLXDpL6NW7xdB0NUceq9G/dzTT4cBqYxBxXsza9rWPWtZ8/GM0999vwkrPEHcTmXTo7mvMrFpa8FI7CI73111yEyfk9M5ZXlaC2NG/xF2thg0l75O65uJbELtutV+ON3MVDAJD75u7txQICLfHKUKxf7UfScqAac6zNe1IVfks6v2FGd/UN8ePI9bcNokjnWWO4SjMVTiPXARlKSw62JijoYi3pkDGgQnA5TsbioeeKirz+2XUQStZgTa7kYG+5atie1LYyKzF+OmyEy7zzLWUIClRfOr4w482C7+cNvbeSnfh7UWFyxteoYzKmf8PGHtXxJ6jST0EeL4Lw5IXvnuHHxDBe5Wa9eEB9IAgFLR03C737OsrLaln/HsnP41rC6awF1c0UEBwI4pO/FXucc06hBVOaRKREVT08OM/yQH5vJRWWAAncauFzUrcw+MjGBja2v1GXgBVY8dV+HABz+0TE+c8Bp9Pjnh801mwTwXYOoWZtugoOcMZeS++rgl6xTN9J45wJ07BsDJq2/nNQN94yNKQVwyw27xUZPk4voyzfC0dFhJfuR4YOw3ukdxBf3TCpvvzyxGXTdPeAyNdKHw2CgR8erXG6geFDjs9XMiKFvX8mrLZW57ZzvwRASVdxdCs0ycY62bUfHPmJ5R0Dk1de6EjZcRBA3C4c9GprrCldvWXVfUWbzOrKsbTeza4Nzx0VoDcDLC46eB368PA/Y3SAk5wTuK5p47HkMzmxWPGNSNTY8x7aPk/ieOplFOStPFrt2vBoJ9918sXHi/03//Xc261+zSc+G7s/vf3qByxNQntfJg3cI+Epp8vSL4eYxh43eL1/zFneeaIFTbvy4yWXzRE0jIwdyZ7g1zsA8OdLKsTbOMVj7DPDXh5JkyP2Pt+r7ld/oIv3GX7zEIs4a6xdHNpPlvmsU0+TGfRL0fmcF8TNDXpAzjgWgT2Ozz2v4kef3F16V9kvYQil1zMIeW2tCjIi8zzLAk/sCfW7+7VZe2cpd1yvy3Q7UmydK6H/J/yhng86X5SHjy/vA5XGIHHh3BNy0iy2bdPyoJU82+UTj5Os7OfIYyp/md03hQvuxBnDzSRs26TlHoMl/KPgp33fwJe8q+JnvoQiYNQaXWk9dBWR9meeWYxvjsXFjrybII0uEbtKZZ8i31vOkwN/5CIrvfgCIBKYtZ92BifyUcwcRMtQrhltzfOGSoz9jEeNoIt8o2hMPOX3qSryjjwgUGrKNRW021o8O174egS4ewEIllrLRiw542RoDU84xTJ5mfRGLpWW09JWZt7NKsdvTeXPd7H+cj5s8ingkHVAjYv+wRsXDozU8G5xISp+KdD0Akg/8d5xevX9QEIJYvPWfbORmveEBOgaO0++cYWQgnDZ2xonQKQaJ1ce8SJyncx3WvyieSyTPLwlwVwFkWuFZvza8GO96jXiUaGljPfEaPzLVrWWtascR6WLba1u98wzPxhVnYmjDcFbKeBmTQMbmSx1GTgQQjxswM9k6oOfxem0bZ7ixjqhz+wdOJLVCf0D7GJq5nPQe35jsfU2s4biu8idO5MgOH+ankU850Xnej/rmA6/BGY748HN4Dl5jTGbyMXQsAWgcYwyeuPoeFs7qNS5rNGsS6VmP5bC1mQjle+wHMt3W4OUpfGy9ZhnTxWO65VKG8ck7k/wiv3/nMl+HsYOTvMYXhDJBzs/MButyq7z4OMc2xls/Yh9baq0yVgLuuhoU03jnGOWeyxN1GMTAVhxwj90T83DFtmSGP/Mgzt8IJxHNBp1QtXeQMT2y0+LsJi7SlqQQElGGpUzqIhO0SItEAUoAsJphIc+1YXF+JB7T5bKLpztFBWbsjxGiI2fMrEwYngVaO7SDtTpPtqUCVpqYO4iu2S3+KIa/ER0jbzPXHRuviIuDSgl/oGehmjdEynH5hTC/kOiN2iLjJw/w46Da/EtI3DwqpWS1b8CMtYzXyNszJ4DOwd9KRgb/xcAi421eeDHNrbGrI8bxQQReVc0BDubQiGIiGj+wuk6Xu7JwbBzc4/BgMq2AQeMtV+rENamY1ARK5KWLs/CLwTT81vftrR3wwTMKdqBkAt7e+up6a8ArpZ5juVDGR9q4EH8ulA/vGBBPm1gbY0mlNxZziokRf8TyexrT+cOmDBNA0ognYKcjv+eDMed81ITcFDbA+r/hzCEEyjRe+uCdWHJsSDZ6XJxrB0dJQ6y5guPbYuPjK5P42mKJbGb1yET9SO22Vtf2JrtYA5KuLtcfuJm1TtiEk0+2hLvjnERuwnN/3c04GzRKVP328VPYOVGZppgZpON8YDMToRsllTk/85bzGeJiI/dz/mVten9rT8arb/aUhfplNim3TK3J6sDwtdPl/Us+Y55NHW9N963uWZO/vmWTHpx9twD59lXS+Rx+dL9mU/hrNny8Is9GnduJQfzUy3dLUNtspEvpJRabnd5BRvDFfnpzqql1xY3EqGV6a5LxlzxR8NP3v/zOu7WLgU9rwJ92nlhh02KjXtnoet8HMELWJ511xMZYrTVTPVko5amLAjbq1VGPnCnqMam8+TBdLtUQp1B+DGFyXp1KZKklj0/mHaWb3oD7LozEY/Pdt5r/7dvdsSNXN9yxd5Oe9aJ30zvEyJ06i5fzizUkJmo+orIbauuMML/UhTzaSD6rFRk37xep35fU17LkiK+vhiPPk0G0zeOMh48hZiwJDbB/HpszTDVA8Vv2O0wO8euTo+F+/MhuWvjR6AyBfSZF4og+Pfr83HMQ+8gxOa0T/XnMDI636NGAVLSZOSmX4hZIf8mMxzyeb2zAtHlwIzgxNrsT64TDZvIDAz45uCmeCZ2KwaYoXgKM8PLcOhWcI1mqnweaakRsrWJR3tHkd3OoRUQjE0o0ENrgic8cOsxsa/Ji9RoRLrX2HJj6gEAg7bdf3hBAvYcAiF9i1SxZbGyxjqyeDo+Y2cZGSB13tdd+PV2X5zpGe4zCm5DaD4/13ZzVHo564sigLTptIypWookd9cTA0POZQue36jlfeFwc+65vYfeIasMtBjDInW+P0DZgGSPZlTJTBLnvkLft5LWVWwy0HVu7jI3HUffOixHR3IecS65eQIhcN9XGtkACxWAjDN/lNP3ybu6Yxy/AphB8away9g3BsXKyn5zg4LDzkcpP26kJ6NsaiVnXitxv7RgX/+b/ehPB7HFnuEwySUu8ER/5Wc8lN+w25uEzNS5OUy/IOH4AHzDNIdLIj3xrB8epQ42XYxS9g3WtD3PyyM01YTznhXh7jgyZDffk3TWrQqsTe43Bzi2t98dO9oyRXUz3HPvkHifMh4s1XKyQpta/bB6eGBszijdYSzCFCcAJGrtZXgOtj+WlEOgnWRJgHJH+ek4chPIieQ0o3C4SnsBjsQQ78mTBB9zRi6MDgS5ePWN3/nhEfyDxH8wnyn12bbTg2ZjnJv6VUBc0yrEgF6fwYJCbso1XvFpheUfMNhpj2q5DZwVcmQuPQ25qJnfkDHMdxOWhF53r46tNgOETXtgdAIZpbGLtozMGMu3uYPPc3HQIC+WbUvquUWNh06VOLUpYtykPxja46rfxleMzBulY081ppNHPxo/kFmyU8Gf4db8QbvTk977avheArU1ishmSdPzp+XWOPBeisOCl0GlwApMLVC9SM24N0+cKnk3EfgkYF9t53Ss4veg0Z/kaxItMUyav2VjEeDMbHgn88loeiXstu44np2h41p51tlLx54kEGj779puBssPOG7ihB3oVSNuCWH9jRxZDc4c7TiLwKm036ZycRKX+bAA5X/3jIreuiy4TKlqjyhmeKIcPuiolZw7mogIV9pjnuLzkNAZ2IkqTjRWmPSC6Op5Ic401WBtynbeEJ79d81LEngAcYjebFt5J4atvKQLnApsidG6GsUxBWlEK0CKQx5bD81BNJcPQc7bx8YpuHQ5KBowjNz7nZG7E5xVY1se3q2f8xx//Pa+UszEnkfe8hgO2e+PL6i6vmLPArGd+iIGvmwM/d5/zIJ8b98kJGcFp1xVuKyQFyJaz/UkKe7Zp+YmvWBQ7nL7nyQb/FjHPzeqTNLc0XmWm3qDT5J0nENauF/2Vt47VrW098c2I33kcAOdnn7Dhi/N45Tgn9sTc/HZ9wDqtMGKd+2PgS5/7XeITdM5NsTKnnl+/5N+QReN5GR48Xvz2r987Dxfqgiu9NYLjUOcb0tGRHTpe9bcWCUbfTXWM9aHXOAeptg/A3i/6ZBbEsjLWOOf11B9jsen3sXXqj87HYnTIJpRxUWYOzvpfPuRUnWtgYtwfc//y/Ksv9geTQmpXPwsAfn7SaYcsv9phru9g11VLLGyuqYbl6LwhR59Ol3seid8oECkQ4DOsYNe9YiCoz0U5VsKbw4EyoI4LKXxiWePxKALHWK2hFkwaC78sqXHri25x8K3r1WW+OX3gBufkuPVODB4XEwCdcYhXsgwKnhhkZI4EfPlXofT/d4DXnj+H1/JbfGKaVqvrWLDy2jU9/jAYXzxwhV1rMDyhHgX0PMoTQfMchdoCyNRh40/9a1H5HBHdmGMwwsYj4vjHEFsx4Tx2yuQ0oiG7fmMmzdpOHQfglLDurfEm9eS41+GaJZ5rAbcpstjMA7jcGbzXej0PbqU1hEB+j4/TWS8e30dx9Az0mbpo0LiTkj7xXFfF1YEXgE0aG/BWNGoEng3mkkrG6OQVW2rrYhgEgDR8PYzt+KCqBceeY55zKGhgTHf+Zo0EmvVSkElmYy+F4acWlfPayhFjQKYx6vne/F5sddg99iUucP/ua5SDRUuXYTNCcZtmmbaGDmLMr4f4oalPOdz7HHM9o24OwzXzeghVmxz3/ls/xEU+Nc6csbVJv9cUyDYWiHgtViM14FoF2eYczPGWazRixaWvoMfAIskYoAk1ZA65YU2HiSQah4ltZWMaGaFHqUXm+A6pJjFFGJK1voUoeJzqeBOHasMag3HjTvSxr5QiYD9Ong1TyPF+i6TPR+EIVIRBkY6yiC2h+JEkbi/2msNn/SqDhtGhE/9WabhNKGUB9ieqbcSifrbpjn+QuKCTw9qAMHZeFFMXNkKRkxHj6mu0ceVILtpp2ZhzXA54oWXeC74R0MV/828PF2rQmsUkA489XLAr1DaKoVDzcVI8ivGQFz6Z3416eEQgR3KagiwnwBmrTz1+bB8XsuaEBT7EyGVyLv64aG682ZwlhheGXBzmxmarrNx9+orO8qim9l/yVtBb83IpN2LO+cNQK+KWBF1b5wnqNCztwaSVL7E6p9M3vRIOjwD/+oLT+OsDxuKA7Ti+Wg4+8m6/6ed8IgZvRU4TI7i+WmwNkc4axaRr1BwkmGE9sWM8sx/kpIBm19W1+eCkM6FmQN+4ijqdYESZXAPKxsPNKZ6D2U3JzgcnJJofiJd1P3M/c/BUM5+8c++EV55DOvm7mSUpbijd1GRDkjk5mica1OhnbZRz8m8j3ow1zZg5G6K8rJ3/ZNBNFK/A/pW3KfMK5695O/R/svP5OxtdXoX1fAafOkwcNua+eh5/NvjeZwDOzbfQQ4zdUwRs1tTnXpDXm7OhTMxwpFbwlX7sHMejbdgu+emtPy6Ze64Gg4Yvrw7zBWVJqk8IRMWrytbEWDyJwI6OJ4bYxFVHrXuf7pMMUsohjGIvujHgeThGwQ8saPDiXQhM2TB/y5eXZbtrnvLkXMdO4xwyMX+lGUOgwnakgW2ajyXkCZnpzTf1RXTeQZDNOg2//k3aGXkQvXPi+mq9OfRc+JaafMmTCjxxUl613Xe19Ik0arKs4MW5Eaw81p37B3rknD+jx0avUPh4bE2+0uIQG8/JqUe5Nhfqt/TtAQs+5yUKcvPJEGrGeZW++cWOtHsapq+t2AAlpp0CbJOfF/Y4cfs8Mo+LPjKTRzAj3/sFNjSkZC2SUHeOW0U5AjiNOtHYmLz+8hrdYiLbi1Vs9fPIITjaV86UPH9siIhY/8beIzWVTwSzeka54wIePtGecUHGfnI9scoCE+OH5+GW8bg2NjaTd73CtE43FnHBiMH2jsd38fTP5NwPMpbv4G8YfGnNhdngD0n9xzcBAXS9dJJ9ZHpdPifB2KM1p/iVb9kq1/N/P+w6rR8V31beSKjF9BHyOEkO0N/6lAS6y0EP7PND9vXCJ7cjV9wY5t18Kl1fZpEPNeM3eFEjJ8LGwHDn7YnJOTHc6PHUbsbHHY8JNCjyJwaqwcDcqMHAGpR61nfrhZDYNgCwNy5OeNCVV8PWRo16fFv/w2vxiDrjjbe1gZWyiXVi4oOOADwmlIK8zEdtRzuHI21jdIxLcxYkNFcv5A/zVukTUQqH/8musaYmYMKx+Twxl0T0tsFhTMUqnVxHeO6nWJzEUV57nZUkImZe01S/HHp/be7EQrv5NbiErwyTGK7N+/ijf0Hqiu025CYCXr03EnWhyempFTI0umbgl8SZiAeA6uhiebYEAusJtsC1QlgV/XrOYE6ASrcIEOT3FFvwLqIxVodc3UU+86gG5ARfUR84cFUSKsTvyd5h5IhOURjzOzxR94ySTn1rn+OhcOwVosjNk4Z6TQx0UaDiMLCCNAaB1a5V5hjTncGJ2ZRmPWLDhYMXHbF1I6jnnHiT/9ahmIb24sQ/5PKMb69p5Dhsm4N4BPJ3Z//sg+Orb+ZPnnORyJw00lc1RbAYmyPgrYHA2A8vzIi8OVgT9SNPh2w5OzZkZeccMz9qlNpwh8XPi3LRMx4dZKv+xJU/ismjydSUMbja9AIR2r7qlQEXqsTdG06sFa8umteJN6GDg7ybF3g+BgBzm5iHz4jeeUT/8AXpQjROQtnsiZ0L6K1H+dVOowGozziCGEFnF8zR5IJv8WHYVzjFSywukLloJ99eSPN69TyBkc41B79Ba5fxqQvyxJEaQadcxjRIDkOrJJjWcPP0vFlfsYdvxsZFR5y5LRfh1Y1+Y0+d6JLhRwOC1to6yIEaNCfODWthLM632UCaI3O8TXkGdwLm/kHycUXjCZgYO6rj1BAh2OmpC/5uBrIebLJ//e1XP8f8yy+//vT77//Kq+h/eG73saebMf2CwZfD7Svv5OAmMXzd4LCkNNZ8mveR5M3n3b+TZ/hvbc/6xra8w43FfZJweAr6qFBMnbbft1GDz5v5N45v4c/nonkLOq+i0+wztBacr8lt748aBLv8WA9uSNOnduAxb+4ZhAv555PQ2hJBuxhBXdfINg2QqOcV3JqUMx7IxtKecbCi+jt17Kvc76vj4YXBL7sITAhRZ869tokVHPjz/Bk2nJOcE8Tl+gBrXMkDPTWIlY8d3Jf7EY+7SUeGDXX9+jfvyhB4QgKUh4Fg2WI3kfRB1lozgktt6WnaFqJzBGAMf/4+7trxf+p55wdPpH5JHvLnnUzY55YE9OVMM69A3b+vDw9iHJaMqQc4YxM+1IPjNrJC1jiVOx+5dnJojlvb9a8++ANJvG2LbXEiZN62cSprvOuHzZ3NaDnA9UN/J+QAFo2jOTEeTsYf53Kp7eJtjz9jeIuTWTl+9pjQzJMYFjoC42XuuVnURnqPUes9POMjf31RJGIMlrP1JT/s9Lu5Gn/QqtMdZ3nX/PV9YqucA/zTPuq1qolag9hMoI/Y43/yH99lgQs577r4R4i7/hRCHdPJsf3yPgFB8DFZR2Jas8gWy0DUqTVaHOxPfH0kczIz75EfjnHo2sf2Hy2BsjD6QSM/ho4dPQ0OaGyzfjtfftpOXLFqra+MtzDIY9z7GoMg4Tfw44bwDG8eBSnHjIeLS5bpcsfRmAehWPU2pBbibhzXYBw0DwIPWT52PuepdhjkNuNP3GK0ZoNHcbY2GRKXnBHDBnR6MLeeSk6sWmHSWl07sKjl1ly/N5a4jQQ+TZv0K1U2PofbcERHq23jHhx88gtNa4lhQ+jRvMZ38bDnByfdWak6be70W6+aJa4DnZNv12N7wi6eMUv24cIQ7hr23AvU+Qx6vBtwSL2eOs0fY/xpBRsSzhUfOeTx28QYbXAXnnwJ2S4DRjtv2VokxaN4HOaRS8wx4WK/OMWq+ERQt0X68WQ5VluHwXQhZFnBiTcDc0kiuJlg/8Yf761Tc3147ckWS2MLkDEXsI67+X5CK0ZNI+76cQG4JwdV3ppvjhDTPg774MpFE60XLyLFivpF+OSGDaK+mtO4NUA6LXw3f3ngQaAR2mEaXMcCggvvYlhHJtGh9g6NPmPmbSgBYYZtNfBmtPm2Fq2DunWZi0DcgBDq4IGJfP76aFNHN/Po4LdYGfPKpRdwyNPeC09srXmYbe01AjfmzTcSiKcVu3V0rBCFvzEjEyZxSALir/P6Mw84+PktZvpTl4xpzo2LVddgSqm/58YKhp+gkVWMkPzYoIHYeDveeEOHEPnNhbE+mXhuKJ4X0VurFNNX2XajBh41/TrrZlLwZUBc8gwW5xET3/Y7XNJN63nABDs5qCGX+r28y3Fcp8OPdSYMHvjRt2XUMlpvsVbZhYYkiVirDscgnSOcogB3z5ueD4jDKPl7PyUOc2wz9EzFd4OKMT7RY3PzZXwblXiS6JLkviBuNjf7RWu+Ks4mPZsrNuC///Z7Ps/8ZzY67GDLGajdmPMZdDbcvr19wllnHm5y7p4n8qBNNPKJKq8151zglffdrPHERBlX3/HWSGjzniB0zGNGDtxNth2c5MU6+KopVvllw8w3nndF8zn7PAFB6yZ91jk8usmELlVvY13KPpC80syXn8XWz+xzzkoEWsTii9PyroEIs/Xtt65H7FqOfnG3RwwIj+9iADkysaOVV1isnvMETDaorMmeO8qoJ7dp+Jyb56fgarH3iRNtgr8cEhgIeLDh7ca6ONxX+3l++r61Hn76Qji/375mnVOryqPj8+cbNsDEpVm+lY9Bc29sjRCMPaauBucu9vn9OycB65Uoaku85Ht/zlrEnz8BOLRG2Nbe+wiqicHwbdiTM+o12diJLoz5SBzMaRhHho76E14TekwUMOgQcP/GVzTsCBpBqZq7WIOtT3SYeI6u7WA2Z+pN7Mvt8JlYL8cRJWS5G/sKHRFGUhdyzCpYLnv/tF764LVO7Y0T9u0H1wDRa1Ld1lJszMwVg9EzIlEatbTmy3RzWcynHhYHFAEZ9HFlMbZuclHdGG+csS2bwdF+nMbD3CPa80X7eQxBd2ogp/rWFgDOIcjBTyRRPWdi7wbOnDHt+YatNUSveOSLZW4A5gYmfo6LUflARAQGrTzvupgHftMWh572rsXmsLqNdzMqCHYrM17wF5ecihnbiXtiQCN605j4RRz++5gNOvlOHJ+wPhliW6BmMAjggX0wnELGuh1OpfAhW5zNF58yArNjU2Gan1PNIxwbNFJrdbSLv9om3fHawQV+zIkzNua9ctJ71J00DPbHX2TqBgwOOH62rVulP6zhmOq7boDZaks+SIg5iVSdI36nxmuYXjzn+Dx1wTPy8s24wIhwqi0ypko7AUGbyJEwbj/SyX3tGnEwBq/4cUzDHITG6Nj80OX2i0md5CaIITHe1uR31uDYLumCoTdQxE382hQ5xyG5GJv85b6W7W8Fb/T5izpY2A0PgqaxKDxQkX2TvXJNr4tFwI4/GHKKH9YurHgXZ5mtnX7xxQGfcp2xGMj4zQIYY040eM0fdtyKi3tjSY9hfspmdAbBg3l78MH2gmNEzKvHSLRS67Bx5jqTCyVMuJCJW1oi9huOgLbtWy3ZkNHMx1EOddI2CIMlkBbWUTNkg6hPxkwnkbUbuk+M64c5FWH9T10y2nPIvEfTEFpXPzDaDj27HPY+YL3lEz8u7vLj79rTT77yzZgyHl5gZc4RzHMbGa7qGeT2/+g6G+agCWsAACAASURBVOVGb2TJ2t22d27Eff/33I24sWO77d48J6sAsD0LiR+A+snKKoAUQVISXfEZbEOXcW79GwHxwBZ1LtDbv/hMP8HXOaZjeyQZCCFCcRTJ5LWaOhSflQbpPVh3fxYPInxBoXsvtsrQd79rQWwIeN2YRS9Gdg2/64tdwLDQGoEMOsfAelQZzRo2L6zGBY0Y9EUcQUzhuHHQtgG6I3AaWwnDuSlXV88ZBi+HAqC8fxS/aLGjQDRs1DPXGMZyls/ymtgyYi05cOWGyx4OsQeWmEUK5FB2b8w0HU6c4i4PdeGYr62FWD4eFc0XA/IvsSDnHxLjr3zno+48Vvyvf/3rp9/5/9r//r9Jt7jw6cE8B2wOqv61crAIzbrliBSb8ibr6PIt1+i/pS75jXdzgFc0+Ur8eYwSKBdrQu9gZ6tFH+QUBYTNDafWN714uQDgY0gOmLwiEA8P2xhg/yW/rx6+/AV09vb3HDaZ5xJbxgyzLv6l8P4RNaJiQ+14t94awiM3H2MZZ9KxDLWH533xM0bxqAzP2M+vE0gZNL+tYO0063qSOLz2YA4OB2j+aFxlzd00Ch+M3BfBhMfcihMwbHzIT27ZD5eXDlGyh+rLgBc1/Ovt9LxbnZ71x4/aUEt+ZeKrf92dd9OzV0aPzXkXPciZ6pMhs9ymZk6DuRIM1WHVujAnnu+iY59GGn33PJwTkwYinKgH9ubHGA1K8FJPbSIwj9Sy+cDx5VzMCHFUR89+NABjBKNnyFgZ4wya1diZS2LSYwc/ZdVrm1DLm55mbgyXR4ao4Nqm0rjFNts1inzjDN5wnKz0k0EEy2GAB/ONMmMJjP1wadTltAg3HyRl2hphydw8N/bUY0jhkhZW0W9dkJjJ+CB3HrsWBpeMpzGqPoOZuN5MqUWLWZvJC8P12Tr/2K9+ecnjwZ/wZ53WXpxMNu7iomdc+btmapS7PiRhnCLqnzkeynNRvQTskaQ1CMF9flyXJ9cIGq32u6Ygbp7idEGMd+QfQTde0DYnHPFLWxoOEE9clSMktvVYo+3BO+P1RRLUkhfRieG2HlVy3dZ6z+zsg6k98/Aq50YE7uSr22DG1nVANjgNXa71K1Q9Ngd6o+hGLOZwPzURSKFU/LkWWbnHOj61fThMnaEv3gZBQPNnKr5OctFKrEouD43GDZ2NufVhVpxWmVm5r4sv3GFy1q188RRGiBiMDVPb1EKcyaersAZPjbb+44PFYn/4r52xipPhsX3X1nzijIy2O2A5nHzRDz8NNX7WAt/H5vyCmrD63k1wAHCaQpYe19gFaA/CJyhAEFgsX1EybeH0Q0mL3WpGMuJIUUT4D7niKCeJMVOKyNhTgL0TKFaFdVzZcDFGr7/2jVS8p2Bj10JjT31im+8XX+C5FKkY2OqVGIzVMU5dugkhBNhFeJ8QyPHRGXPm0sbtDIKzB0sBiVG1tYHJ2PJvaPbJPKZ8CNP13HzlhH15HT9tRxibrj/l4Cn11iZyqJjs9X/nSDsndytkbYjzrg3MtG3lHGO9jYpu3MqL5xHQJ9yxhQcdAQ/+Iow80303pBx4Nk8cnHOzI9qMI7UNpoz2Yo+Wekx7Ym+dKcA+kWe88kaZvJSDUaTS4Mku70gPwwnyye2QWNez9sNovC1JbAKS2lCDbVtn+pWefRAjwtY+XHmhhxYMFNoNJoezSCJGkeHoXWc1EfLNk9n4g3X+yj14+GCXsT9wAMh35VV6RbbiDtfV2poFNv/B9+WmK3HTuO4LU3BznUYuDfZYnv67t1yrgEfGCxs4I/eQ4iQiDiQHNwPG5BU74PcdSea8IMH+cJy+8cDHK4xjY5AgikpIPpesvjaLzey27q0AyMWLWI9F4nHO/hpS3/MO8195F/1bDly8i/5f//VfOWj9mf+Pnn+QHv35vfP48EfF+sJR/Mg1h/O/81jnQYUcSN5XQ3MAzqSp9DCcU6QEvvOX6zno+zjNCxSsTiw3XX+KExqwtOk6TMyRm/urpjSDIY1MqKH19fEwOWf+7dvXn76RR/hwSP+WPMHaFyTwJRUuHHz3RQzeie8c5dQ4fsi4v8or+LyTbtxmVfrg58YBnrr1neg54HJ/iC4GweVQyX2f/dK5Qi7JrR/Zz4sG86kA7Ph3atjuXuq+eeoXV/TcQq9AjFODROZOXhkqUoMK49iY5/iyz/m/69z+TM3I5X088WdFPL58S93+TG1Z47yYwe/m+/Mw/vS05eiExJDRM0xYq2uPRjYMZlQ7MNxhmfo4m5pY33jby580AMIyX/i4PyOyGOiodbr5mW2guSgvIaOLlZFcsYEvLf6p8M0rjhGdZiwE5jca0tCvYlXjIc/UC1RiuXb0c9/ATBsIfrTGNVcZ7ByjRljuyxCExXI8pn3xYfytkdVGKzJo1G4TFTcA5ooN44l57AiQthySUbEefCToRzP91FbMi+F67J7CJ0GXl+PFlefFUMfD1WMv4R/qWQ43HjDbjq8RSwzZbRkrrtOLpRW2UZnr+G1dlEe2MZQzX3DsmTRZi726vY9hoMmSHnsxVwaesW9imi2YAaamE3v3CtN69bq5m8/s090L41qPYD+ZqHJ5XrylYw02TlFUcYF3HLdG1f4oH26JKBcPo0RvgpXhGT37SEynCI9dYxSrckJ3zhU0MNfirKO1Lf9rEyuoH+tMtIucbwxtvQ8Y5shWcw03FzSRysXx8HvrhJx5Y7+gjIl3ryCB1/sumsyn3ohpjRddvj/yUVet8gx3f2z81gvtzaDxhb54hVG4DAnsmmQ913vN6JeLMch314oANjh3sry6FyZnEnKvfOKvT2sSk3w1HqCxtbaNYHVQpk3XSWyIDMdfGpRZTZYElqs7QZ7iYy3xIOFaQIW4tmmU4WAvuYaPeO22F2gK8I8fhluYwZsk6hokOJh8UZczvGhI5TgxnIwc/dr/gxX5YbBNkFgPcBcabl0oe3jMvejkunGxU19AcH7El+sG2LjprTf9jBsz/mJHOEluTATlUYWxMpR6Jj7tYhIZGIsfiU9g6EuDfPVqj210pjg//Jj7xBwuaTdWAyCWZ3RYFE1LLjDNlbqlj3PnKjQmp5UtDn5Da0DBmDgqbpT9oQTKtgk109bqYg8X8dYj2JvvCVxd69NcuTI3esKdiC2Cc+JsLHoPZhg+t7VZOwuRQxsmHN6s0wGHx3JOZB48vA/1yXzJYCNKrjjKENHMyoMnr22zJ65Z7Fj7VtHnhzHkAGu2hEWX2LapEbUgB/v4g993g7GNx+IzYEyd0pzm0hfUFKk/n25otFFMDvpvPoAUTl7gEsKArb9jZIYc5xOq3JDasCHp4HRtcpD8OYetnFp4l/jvkXOI4d1VYuobP+s28OfFjIHdPDlEwIdDFjLfPQ8mhxhcuX+dvRBMDj/I8OFQl6ER+8RZmuJM2EaDiwL8hsDyoC9I88v+4fDJIf3Xv/ld9BwYc0jngM67o9/+z/+OfT/eziGUj0R7EAIn2OWVvcQfGUvQPaC1dnHEzHjRYZYcvua2f6Qu/0w9NUjeLI4nYl1i2B57mjUh3lF0TM17MD5pRTHOgWQICynkwv+D//VL/h84ufCihIfzb47Jm5y3/vTY8If07DOm537MusEl1dCHMfbuNRnPJfH34I1uD40czvv/y/sudMd8GB/O5Y8N5Lvu7ItMecEge4cDubixdz3k2jwjkVsutq3Z4o44eCk8OQQTLOTUioFjJ93jaHhxTd6pEYdz/jge+bBHyZ0brx39Faxvf3z56c8vf8oXfHjjqx1xyCt2DeFk4ncMDQTo4eJYlcwyLxaz3Y+80MC+T6jks7kkr6mne2kweNw82MFgvOu3n2qSH4oEtzoEKxv5Mwt4LoLaixqZpujTFnfjN3Lr6mMjNlr2suON3wjUKhq+I5ioDhYf73csKPerfg/Xx3divj473nyZE6yc26Pr/LAQaeXrO/DGB6P5JG/2iz+38K86UeS38ZyaJaMblzElr13jQ9E269wJvLu/jBvG2xcWkFiWgh11vbigFKOjjJ0GU59ZP5Rg5wvfkyNccsP05ARE1qNSHV8KctFWFf5r8xkrMGmDwmTiIt11Ormqjr/30VqA+3KSIypba8Zwed4e/IlBbd0b9SYezedOjN9c1U0Od7GGa9GXD/hI6G3xbQQA8z3YTJpjrMTHDylfxD8ImYHHPKOx3fnGJZb+Xt56ARXf4aFV5q1nOeBLa8ReP+I8/mVR+6F0+akMgX4fziL+kGN5SEuYZj2Oh0sG5oPg4TqyU5dSPl7d35ke5+LiRsNcqvbBzdfGd2y+Y2FXG+EGgHSQoj5gjLdtsHGq/Srbu/7ESpPz1PldU7Bda/C4ZQ5H2nJ28uNlsLBn7cUcm3ffDWQ05UG3jw+NNLWZ9QNCSHuMz++gB4oHa1vGEMid9hYUxeoviNI8mE5OdpDdDVgBOTRp4eeyaCc5KJBsvizS8RlLONEif/GMx0/ctFowtuwjyXwKKvbg1qK2+DYJEK7szWWiC8XFOabTrNVw//EHjGa5FDlXwygt3hOzcMuDdO8imrcgiW9OtRYpLqY2dVKfJ0iTroYf+cRunxS84fcVeGulorhbc3EnZ/KQH3uAZmzWJ0+E8mTXdVAl6aKhjKz8M0Zlm4Fd94AcJoGpeKkeUwZo2HPCqlcqFwKVz8tf26hq1/yy4eVkPlNDaDVfksAa294h3zq49vHhWNs4tV0b9wN7VHEuHLK3BvjMjSjHR4OZo0DHya+DuaMrLCfl0U9yuJeLg8Qo71Jgxlfxsdsn9NsDt7lyyBEX4bR6w2lUAVv7xo0iyq7OGIUUfuQIv236xVI/n6TEL5yKU3nvBfWwRuQpeuIixn5wnSvTpPqZiznBi4+CFq/Iy4FZ5gAFlxxaA0zGJqrmkTmGgyk3dHzxRJ93B/EXLAp0DwaWBFoZPWuQV06Lv/ctPXHuQGrx88WOfED875xwOSS3DpjlIAYtzBviOOK7dFRpmBE9bfjBxQNOcL//+v2n3/6ef9UVu//+7//G7Kd///vf+Xg7h3N+/3r2ZyCoIy/c/O3HwCc/oHNC2rqDTzN3SP79TR3/cu5LPv6MHR+Z569/8+8ItV8fPXMJ5cXrmpFD16Ty5hT32qluro2uVx+vxgaOX/7qu+P+JXveDc7Bk2a9o8fXd845lCd3P9ZODUYHam27X9gDtNJnbZ16kdtMe6jlYN7/Xc4f5eMdfD4azl+fh/6PL/DgSu35N26/5hMOhILPiR8vP5WSoD/nBSUNJv7SgA88Oj9SoM0PLBp7uuPWGEsO4fws4Z7CWO55Fx071mD3EXuUvwj/c/IBpzXjsbAv7HBfgcG+yEE8/ZVGB8Ef238QYdK4k1OS44UsPsmRS2I3zz6RDu/g9oWuyKEQDsA6BItZvt2nz+EfSxXTV19bRQcBJAHaodyCb04TDC6q8eVbOGSVL0z3ExVvW476DrYrksdTbPTOZe0RqEdizLueG8v724T9sBcv3sv1BFh8eEUo9IyJl2QwbWs81ymClbMvyuexSxzligZP9ghKUP8M5byu9uAxSM83PB4f/dRWjwpz5K1P547Pc+QoaVtn+DE1QAYBuFUfvmNDbhsTiA1mHcR7fDOXBz7oTlN64h+xgVNX4xe68cbejMY6ImpxjIO/a4E/bV9oZ8pqbeu8fPRxzYg3PDEISO10XtdODEBug7F+Wq1fvMl/sFRRAx6GcHvxiWSwzaG4+szl1q82qzty/NOWEz25vbKhe/aiUQ4PKgSP1OAfe7j0uOIjtoTjceKuDX3sfB6E/eQCNL7WBL/oqMfxn4GEkXd+chjbtTov/iEAM1/Gxc7GbOIHS7PlEn3ni1Y7PeB10Bi3mcdMFtccjn5SgbfgGHe8UUYS6Upay8qH6xiZj1wGDtxhY3zrcWWNJUvrIa2oxUk8YK3p1OfDkziDVwQc42FMHctYcfcVdos5I0MqHD/q4++go2F5AFWXS3kUTE8Tv0XwjjOyppFJvj82RENGDDopWYZeZhOvPTqS9IdmdC6efBKzrpiIQliDMYMrWNsydwGcw7ftiW4cXF9eWmmci7pILMYAoCNcOl+pG3XrVCyC+aBm/aZ2GHA4e/wdI5fr4AfZnAeXsbWJq+9PikGAGsgjzzT2jiaDFArKrWMeyYxBh3z4TDixmw2Rl0TgsSPPPiFbhZjIo3QcBVSMYecMyVkPwrv57GvfSIlBPomyXsSktSzIY4M+gnLFunoNMxE7E+X0cHPvaKE/IzCxxnDjjIQurQgb70pUqocHQO3Hxa5ceYdm242xzPIkN0/cz7tJGjZz+PqEdLGjK1/62sB9h805uBGATltdx60bHE7tYnDuQ9QohmV2a3tl/Rl4sDicb4vT7hV48ITLtVnn2HV/0Mu6nkPwMTM+T4rHwHk5AeI3EQZveAYUGy7WIe7EMSGw8BtI7TJ2Gh289B49nTa4o+dLsAiQ5av2sYzh4njoYZb1zILqi57XTn7mneI5yLgokJkcwfPd3JgSpqFEXRPCymE/TeFhz9NEvMGpueF8DArI8uHdaw5w/qEyDSFNDvAihe5Tc4oeqK5dsbtutYeHBxZs4sw7y1/zB9x+ySH9+/ccAIO1/+NcnOS8fxSuh/K+0yxm9jfce+PxipoRIbHAhmPyKCPeYc0h3U8QIIMjf8QtgwcHb0DQlXftEDPPlaGt2JWAx31wd/iJTY2ncT/Fwvvr1zzyxp4/lAfOX3/xu+mPberi4Zz8OJjjO/F7+Ouakxt198UORgTAx5i5AjmP79pq0Jx4J5rD+e+//57f/c//oeeFguj7+AlMPHIDm18/ID5jXtjwBZu8eNOABDOzjZp+GKTbxyaVWrb+tZl1UtnxsQsk8ZsPPHihppw8oCevzd2aZq8gJzRzaibf1PJUhD+21yLJ8F3DoSBD0xkiLRn5hFC+eZGrexiC+SbWOINNTH7G1W9K5H7s+pOSa0ltBQB26xDMaROxyAHrfGoElQlgbo7LgsCgMKNem2MlaHD2OzbdP9Y5QrTVOCiG12qUNoHCoTNe+dVrUCIXlx7F+mVWTvgi57s89I8MU9rlfkxXoQ8TcwToOFVWXqMfDmUWGfGQ+TN9eEZGFCkF68YeMv9Bpy0kPg49I40bGDQeJ+FnP3Hke3hRozisT+yd5/57eIi1NsLmMrV1VFksgOll4gdEpfss2sW0DmCcfPUkaOsgUn0ViLL4sX3s6hm/yAal1sxZm5VvLGRpte+YqxyjUzL4GqrraLQHF27rt/FhLV4waI3AIKPBVTbzCWiapy4x1xvuY7e6g1mD4goPPiFah/XDHgV09lyhTXB9TGcv5jFNe+xiffLMCMnaby47F1mOhmA6+WIpwYOljpgQoT186tU4qBr/YhSq83LIVZjBKpx+8NUml81DvuBOfPSnPitLD+b609PeujNHSlUC0J9ZE0c/MNTbxbgohW6NywW7xV/M8ZkItSCXrgF8P17kGIjNTW8DlWHRJgvWKIKtx7FlII3ql5v5aYT68l5zuTh5cygGUd6MFlOcaH4piTou+c5ApK4JT+FmowhHApMctg2R0Tgyt+1gEq5lNDwhAbNWh6IxGqCa4zcpWPRxOt5g8b1oRGngJplxcGjlXHsFr8+Tj2J5jI8QLWiR59pHcoxKcHKqFh7EolYODLk/bJi8NXQej7fWOnAZ/qefDD0MUJMGiDpPJoZKnoHULxxlPjwWqtiNt3GsYUoF3lbzrLtxSPPq1q+Z4nG5mDK8HNQSrHJtTeBSr0bDdPntem58EIBbjOqJVydxMqn/5IzT2zaATlFs/DPXIIrdQeMMrtKZl+5MfpSNMlDkuvn6nDRzD6XRvYfy2qw9ePCYBs6O6Z0MP8bLhcTNgxW6io7WqEDMsDkHRsTju3jYUOvWk/zBR4jxNMcRxogcWnWMYprtRwxMNj/lM0e2cjzqhQUhdp90zvVgXZE+HsgNopHa2m4dIooe/JqVp3mZM/TR0MYnxj3IDS8JTn5Pnn3HnkNGDm9ZYPLxEDIfPz755b7IO7DM3b/cSTm4TFi7qWGMwqO1cRjbxVEXYQ8vEvaH3t/f+Zh9vBLni7+D3kxrQVbNq1IspwVrDzJgnzqMnIKZD7mFB4e+n376NTc48SBOnfKR5hwe4ZhvillOfPQfWRYIW8fhlpljCCPvWrfyEajfd975nXfeOedxznfoqUVyNAODgQFvwvJC0uSGQCrxbdLpiYRddUz82HN8+D15WjlyH01uidP/HhB94uOX//IuP+432sL3XZ/B+GuewHmYFjjYbtROfAGGoa18zIOaBI9DP/F40YV/b/fH73/4sfH/+Z//sceNxxHWhhry4gj1YS2pz9e8orEHdD4J4MeyU/umzuG0NesLt6CxJvS08Mk3fLaxKgjlOPVSol002kYCl8T+5dffvP8Qj/2xdSAnsSLfX5egtv1If/ZLeBFq30kHNt/6nHVD0kSgacPGFrmrDK8INl7vy8t/DuexdcfAkb2z3AaKrjUgykZoRLEnOlROqaI4PFdRFyEIw9ZaXlkFUT7uz5EYF//DIX7sH2Vdq2JoMpfae41dMVY/uQ8mNuTAbVu9M3t8XW98CA2v8aD3xdmYMz55OMeWtojrR19xs+5Yf/C9z2DwyatOlW1t8WktIqf4CVV+OEcbzmu7LMA9No40/ScO+YOfb3DfehRh8wFxGjWy0bcaPu5lpiScds2LN3L0xxfXct/g8FjOchpuK8MevKKlG9KHPyL04DrGsutwbF7MjJsBbpMn/vWu70cujVz04gKw+9dYy3F6bcWs79CaCFe2vG//6CZP2UKPx43BJP5lDPrT5LDZIB/OHdZwoDAt1uaVXl17jSPofdek5TBuxYITNnWMrOOz5pFb53GyNgkq//FB1joCP1zAnCc+2ErUmiwQvdHkhGrXs5p6IQenHDDimxiNGQUm/2xjh+LYMpYzMqFOrwQs8uWLsT+DhgdAb5vcY1qf2NOI1b48nXgpttrxgfva1oR5/R3NtFbDbThi33rBtl7Mt8kjUPdxu7iH4eLE5eQL5sGK5eS/no00EcTGOL+Drtsp7IdZrQl2EjNcZ5GfgBkZiAWYRJrgQBjr6vZci7YEubZILWznah22OMWsRyUgLMaMJxfYuSFOsSLhh8DcmfXP5d00Bysh0Nc2g7Wb3OQa5kwXj2LqVBoZg9AOFSz9ffDFSF8LdGh5wngl5Krp2q+Rcak3eGz4pwUE2RHimydseZZkALyWF0Ps1hwcMF2/0WGzT6KrbyxjMFRfDJ4YjlYOnT9eCQSsLeKzPjz5veLyO4Zg333j+kM4Ta54zhPfzsuFFyrMK+vNQB21OL5FkINolgJQkQ+hzOGGGB5yGYn4rg38+gQe78bAa3zBCJ9THtgYh6UpJgFWVr/uXdZKpOg9NIh6Q5hX7kz0APSQMoGxXVCTYD9lgGk6qr61tadWKBsR79p2ZIxds3237cM/dnCUS8aLVgpdQ+w3xlkOqXuZSNSrXPupj2LJPaAebgZ8Y9DTQG+L5ATAf2rkaKw1Jg5+4Tc2xjlI2Jb7eFmzjeLhlUpy9yK33PDnMcEfoIpyCM4eR72/b62/tQgq8R0P6uTeOvZKHACkHLOySj+2vDiA9OvP/BGs7DUsOQwv7jpodSdyjQ0SCmGfIT94iFZJcTz4KY0m69xDZjy0zYErH1vm8TUfxAZNX/ZDa5SDtjXpY0R9yaYHfzMLDw6mZ48El4Pb5kgNwTq1iPs+5tQ/MacOzUcaZSJNpHEyTwTVezgbU+MjhyYlTDxY8gkCWlw71yBjlEoGLDPfHYY7XNCPyp8TmE8zTwBtrbXv+FIzXlSlTz342Lr/6i4H9V9y+P1z/w99wHHHVhrBoVa/U0fr1HVirbzxcy+WfKy8B8X1KgPJxh9Gd99ktvuDPnpy7jvTUaUs/kwFNzHhyQtR/NFAGuvDnFrsXgPb/QOP2LDG2HBgl3dAOfzlQ/6Z54WKfO366tCLeAbJhTrQNgb9aQ5zGRHrQP40ePRFGmqUSPjl+1ZmnHR+pbfm1xh/MMcOqAjgblUZo1JGmMWWyYFZG7Q34kzAxC/f1Ql4lPjQlM5znXKonKsc2QsZYN99iM+DZYjw/fjZiv1EiOkeEBYZb5qYjpo3+LsejVCMU5cnrG6TGUhyx9+f48sV/9wMiM0McZ5Y7jEUGInPeOwePofXIxM2thtbR7HGf/i1bg0+ak0br0M8qAIkFzehbFsX674cYzesT1/rSr1qawXEPHWModizZviZw9NjkG0utlcA0+o3A5OJ3XBiypjptpN7BCvffBZ35aeOS34B04sDqLp0xi6m1LBBvbZw0Rx5R3kwwkCs+scI5zw2WRsxZy8KWjV1ILETU7g7r2njW4DhkS4txhP+DB48uSWuIszlQNxI8t36Ie/Y/LBrKowuL8UNxnWNFttYh4sGOGtXBvHIfNenvSjGx6a1ZIpf267N1gfMF6Ncsb9yPSVZxOa15A77PmWfmtS8dTcm8nzXa8eLseTIacYy6GX5rw6Tg+P4cTJwhMoziarx/0Md0NVAO0HjJz6u1OaJZMzNjztPxtoSDPn4MN2Gj4rRMQf3FxxxOgaB2mBR6CSBGOwC4ZJJg2ktioDiRNcHguIqOzHq26REymXjv3O8Jn5Gh5PixkPW1OuPFFxa7ekrsx/fomqkga8iGaueYOovVPFQnw1UM67N2VpkQt4VHjQFkV9eGGxmwz/Y5kE//Gu1dp2p6mng2vEsKU1uHWUy/PMEKYY808wPuTwrydgnKE8Mhq5rGWQSM38gMkDX2gKdqXVx7czVbDESmyd/+0QUG5+Uj66W5eXPEMAeHuBjg27XDplB1TzyEkmaRdUOv8hbP+odKbKp/UyHKjNa+1ODw0cSqqGvZXSM5YZsIWZAHJ+UR7Vrga1msV/oSqJhbQoo/vKk9F+Rx8F3aAdv6wmDOpRAcx4ontwSaNa/FjXnKh9wR9R9TihGej9qSAAAIABJREFUkY5iIuiBqDWtEow+yeUA0ifmcgXzweZJPDgDOTXpfq8Gh+EUK/IAj1jqM5dX5uCia40c6stl3DQhoHMUg4UMPHO4idVQs3HC57SuNS8QbAtc2q4elMrTtY6OvZ4jJOG8r/Hk3z8gF0cOHp4dc+ho0+pjCG8amsZyqoRY1vNTIQf3XMD141Bj3KDBj7qleWWsf6tf/psHYa7cWrEmkS0COfQ9Rw4zwjbPuv70Zw6THB59RxRZ4vkX3PmdX3D8XfS+8/w9vwpAs3YJwB82Y2wOicPoPI7kDuEnPYIHB4z8OD12X8g7X0soOlMmNgGYIAsGNrybW/FkpXFrgPznHBQbu/9mjQMydY9z+aXH03gRA95agdFTH3NvWDa8dnKBDA1OE9uJ91fuu60Pjw3kxrvi5MyB989fv/30r3/9l48xfNSdOvvCYNbbA3Bg4cbvrOPjYy84D3c/L0cOfBAie1udPPFsi1puw7RjfMJ3ZXHESAf2ef5gQNa7h39/Bz6W/WvyeVefw3ducGIdXcN4yjH5gcU7/+h8pz3zX8HPfYnDc+ufcLOGt24xGdqvbMf20bMTGLOuq5M4l4TxZ0jqP+nMYxv7BWrs+YBAJ720wgks51WgTKOekRJLZyXVpDbgIF8u9VedC4kQsHNnBatK7+qMvXH0q/zjGl8i8l1IHMZifJ1XGYURY3xr1BzXP9x17/XkiFRXeoLFawsZe+uA+PEdhJHU39pEcqEyws8XUw6AtdMxl2LD69Z2da0xRrnJpzboPayM2PUg0A0BcIloE0WatUDM2o69dgRANnXDuvgGxlIK2B7fyEQVKxPxYm/cxkNqQzyi3T91Lm4xu1LFxCujibcgsCmRHZRza1Mrr2+sGV+/8bWeFwczq0vYMe59JlGnNstZvuS5LT679npPDYqJnUinvpXEUjsz/dhvC+vPDnjGbtemPiBvI3i5qIu40Yr/T66s/bZYCh/J1MM8kK3J9C9O7xvdC6i1HQ7Mdz0vk46wW+aWLz4bZ+OuHpzaw3es0oFNO3wy1zeA6uBuXRlc+yPTG5WrLaE7bqyXP7U33jDHa1t5tZ5Kw0VrOQ7+GBN/uUtvfw5Ej89Bncly2hjANIc67OPTqQMGoAxfxvUd+dYt04aIPubEXc7iF+VwOvHHdtDUi2PIjJxsH1xqYaJV+RF3FqoALdTOa1gHFzNG4HHdolXeohoL9SSF/9qtTuKQwy6tkTveDYyyP5AxGAtkDCcBi8SYV9AUD09k8MtXD97E6lzDjAMyw/HFthJ1p+Av1urPQgZ384vd1sRYnephNDdVoxp59LfOpBXPGG+9oLhjP7oIQ+NIcdkc3oUsxqmuwWPqWQpd6rBcfuAAINxthNoajQzz1WkHWb7T701BOPLkC5kQ6U4jpy6cqOSHWuyM96OSb+y6l6zyqdNib41OjOELqk+weOIcdw8uGVBCqRE7g74bfL1RyqkhJ8dAZL6+xsYF2UyWR9/FyxPUPSgN3kYAe9/5Wxk9PFK2tOc+A9E065Qx8Yk4YiYmw+7ehq52DPqEHx/KQGJk17oPNl3c2zHIaOLMwDrtiwX4mlu4spc0HQx8eUK9tYATqo/mD6TGOfWEE0bsza/rgaRj8PaGGevG3D2GgLZuZ0KMTNL1d53TIyI/xNmH1qKRlXFZ7Hd8fPQXcqHF8A1VD6I9UFgr4yTWxhtscD8RZqYdZKtuDWcyHpUN/1HxDmQ2z9Q8GX3pIZSt5JIHd/lHVN4UwhYsNkZs2LfYic6cmmPjpTE9OIrKu6W4/S/f5fX+3s3rIYu/Ot7gvd/xGO1BLnD+YbCJv4c0cDmM9q+g57D+PKZDwXdZw5N3WdH9FX58hPsenrEqR0ekFd6tVySZ8Bja/apCnR99Ro7T9GDChx4+xPOwOe+iW6Hgb03pRQgIh0znqWUGgALr/doXe/Aj1tOI7f0pvuxIytgl4ZDNv7Drx8X/NQdy/Inx55/543H+4TgCZN+xDQiWG7+v7osLeeGDGvOCxj4mSysb9mvuZ9YnguUEF2fWglljmQTQSs6guZZ16iT7xA3n/Es+6sZH9Pl0h3FwS2LwgKcv5hI7N2QDLn/+yJwvUuLrCwAGLk6GrOM2603e26Q38xUjS+z+HK3hcUnyrXe5wJWQcdCQerU+gGTs3uxjhwK12AJUuRgDUfvBwF9Uekb40UYa/5UYn+BHUEsF4KwOk8P12uMG6u2H2wDCq+uyMWPpA8ZhU2/j1Iadvm1jMt/nWXIeA9wwx1OuyHVfrMyHO6YzsaM253kCSsHSj79zxzAir6isve6aoeaphk2DqwN/1/jUEZR8izO1/dhbizWQ5HpEE/uoriaiqfMSgcvu38SxjvwsChh47guo8HOSdV0u+nNpPZvv5K8Ntqi5dLi+ypVymfUgGA1fOq8rrOTUQlw8qXUm+V5deQ9m3FYud2BODuOLLE2cDp01H2JAiQBVEhoM+80T0TFoDX1hJHpxYi/O9EXqVdhcKJOYwl9uyMDYVl5rOU7DR93WT5+uB+zwIMfDEz38WHthitmaYpy5GI1dLdfJZQgdPqqmLsbC4LXvWNmks3U9vImX28sT07eWFjKyyokxYI4afyVEVG8upDTrMfOTa620rs+tE3NlW4/hp7Ek6vza7F5q33ymFHUTo36D7uTHWi78zYEokR4u9dbuzQ0rakmLfO8TMy1EJljoC7kYWY9xKzLX6IKlXbDyDvot8tCxsBpNYmuDrK0+Hdfr+CrsbEkzK/H6F6+L4qZBP9hSkx3CNBOOAC5TFLmpy0XIWZTCmzhqlMau0YynCFEsv9pGUONiPlPFE3tNig69K6G4Yl6R0GuC2NTAGk50yE7eC5y+G656xCUY6wBRLmMDGjzGa2+8DYYxfz03T4LkxnOhQhjTHwQiY0eMaXOQgluxVzFzgvCdn3Tq5VDdwREPhLQJiojh5q82AnNBl9vmgc14NxbA+OZmjqPEvmu5noBcWaPVWD/Vkktd1g4OUaSBtXyMl0vnwwcobLnlSU1jDz51zl+jRseTIH69dc1PAFwJhv9pY5XYIqEn0bTltaYjrvtR1nZ1oBCj3ACpt7llyHHASLrlIp3Yc7gog3EKDqON4wECp+TGk1XtM37xZ3JigxhiW0ODETI+a6M7a8EPMPdoMDP0ncL80Sgaun1iubn5goDKAawlwA3gnAsRnpyJvXmGyHllFcvMt46bN3PPEeSRr0zFkyyzLLR+YH3cBJzoL/bYS7No4HrYtxjN13oYk3jwmsh78Im076KjbWwsKa4HWCede5B3ngB+g3VzPdjEiz9FuOvW2D6OsDAphgd2cw0K84z9l2D+YTP+D/bUm/tAfifdg2h45810D5AehHmXmMN5/jWY/0M94+VBDnIOD98lJufctTj4sS84pLsHm4b548u0+5gU6ovQd+LlhMHKzy44uZIHeX5JHvT7TjZjG7zSeOywZY4okNYVmfvplUMgj6mY2DTeYetEXF8wJGaN/ON8v/GH+XDPDRty/v3fX/NH4/7ICyL85fvklq+wNi7vRP+ev67f302//PWVU9Zp3tUmg8PJvcD9H2k18mGYtnvh2CewqlysGZOsXznmIJ4Y+fN63m9d08FBT9seEMascX+eJJu8zkTdPajxmIDPCay7fMTt1HnrhGFu/Z6+zr6Igb3TyoZO/Dd39mf3WO9TOMAZ+/q0Zz338aC1uLuJPRFbzKGe3jjugWKASCvGmkaqPb57P+z+EktrnEaX4cHZ9fBn9+BOcqUycVcWz5f/ARpOxHPHxh7/ItL/2G4NjoaEt2XMjDVG7Lqn3/2EUB5zf6r1OMNVrK1L812bYjb+4R/71mQ4MDf25bnPeyBm7IQzjH39d2+tnr3QVlxmjCq9Myir0Hg4KDJY94F5TU2u8SR3Ua2RESpbTWMyg3fzOnWKeO0+9HFSbqJFKIDXw6L0Y8mgE4jOHojsFmoMkHWo+egZ29Z+BIdv5rsvVRkjQH53DSBg/aNbv9OjCfauLby6RpU5Hz/GpThBlxu9Ci4njY6XtwbogqttMNLLbGzu3tBVD3NaUAsZH/Z4Q2m43MEFwxholrdW1wX76//Ya/cCR8DjAObUBb/HBhmNK5rVb98a16I2WE0Nh9vlWx3WtPUlRPk2VsdaGLPSzHHPQy/65o+All7oMviHbnLQNCa3dstBZyECrhn7gLHrtf4rS384Zbx8m0+xIARL2sEQj/hpYg4+8zTtTh4rG/tM8evjK+PE5Wvo5h10tBFALpYqDDLAqAuRUYkh2Sb5bLo3iZX1Se8UXRafdhInrjEuOtjo1ER/FnnC1/5yuHwe22CMOXCnbQHkmGTpaSvfAtc5MQiDydhdwSiUD9eYmZOq5oW6xb42h1l0Gxe/ffJguGDRlt999T/gYKrUZCb/HPtkhwh5wueTeIjkSZBNjhlNT8w2RmGzB/mS7xqsCbLcplPqGuGJnC9wuaQADL0E2qogIMwtTuVj1C16ncDbOgAktjTBX2ysOhYWeac+TnU2V33CRJsFqG7j0JuToA/VOkXwrueiByt6DkZ8WJbG4WNrfjAlHSWh5aDbzXHrZqLoyoXQI6rfud8RiXgFgzc+A311GwuJMXhcHNA9uIw8JrGZGkVmNvgz4JySbSQvDi0QS2MuwZkvD5Wrd7L21awdh9Ee4jbf7fOEPfE8HIbv+SG5wNMbNvxEJw8aXQQ+0R8RsrOnzHdrhWeN1n1SOXW3EpiMX98NiV/WIkc6Y/O45w9i72oTFPu5+cQ9cYq9MdP7tg4M8KH2c2Nt8g4lRdha7fqZm6rsuOATlzBctMn6rC29axQ1waHXSO1HTDd2aDXl6g3OrkMGrJX/qZOAE4+/Os4h/Zdv+b/pOaD5AgtOtJjxR8Tgwf2C31nmXeq+e96D+nLl8e47v5+cnOHsHxUzf4CmLunhog/iNGs2PoT1ndPMfbc8+uUkPjE4/IGXK9kWiwM6tSy2f3QtfJXtC5LR06x3PPk9dcrQQ3wGfEcAh1y1JUq9cMzNoBlgNILGxykcqG9P6vpz4cWJfcHAPyCXd9LJqYdbfFpbbJHxbjR6bl9z6v07/8rMmoU/tXprZx2kWp7uFekd1j1sm0dl2hAsjVp8zeMin+EITeu1+vb4GADzptzRTKvvi3LhN3+8z8KO20HI3FVDHmHXMb21bJ9V+Zy/zhNX+yNHSE2efp85RSje8J+wp37HjJhjU5TgpSafdWZ5IR0UcIcz+NvOSN1dqzGtZSbl8RmTHLaRn7gTD9zKMjA2lrW/8euz6FtTLIuFy5vlYWtea19uOF3kjQ+WzYTQx3rHsV+MNZNjTKibugO+FuGDPl801Ns+a7+a23ctsJ5anXosQvEO8nAg1q38+gKz2GYliHlntPxKNtKYLsrlUdTGwx08bG+MkaC8NXG2sTGPfbji7mqNqh1Yjw0sUBimFkcfoVh6GOTgMmtOiZAfKD4ePjhb+/rH2Bzw6noxemtS13KTDPpTb6wrNR/HsByMEnZWYXk7ljvozS2gk1NEPJbPmm0u6EWOXE4z795bfgOHe76wP/4TT4yNiSxglzv+eGBVXrXHbnhGQ8MGv1vHWlY54wd710u+GA3ei3owg8vaoxNpcxV8ZO84htg1546olwBgjEjB1g9/OaDkRmslfL6kiBrWGVP5DW9s1a0r3hC2DU4sHEXRfQ/Is86R49LH6uNchDwP6F4lDtHA77icMCu++tEhoy1a+17LAR04D3EBvOi7ee1aaT+A/AObiz4Yie0dbQlKQl0uKuma0BairoPKJPrOmmTjjP6ELHHNP5KoXeXF0v/YoL9Y7yKU8/G0LFgieZtzcshXCzg5YXnco4kzOW7xwBAPs9y5mOnvrhyMGJyYmFxAJup6QaPBTtV3owzW4B4OAKctB9y7BhHmSdH6ajR2RgGHZDhQ5YnbR4PC4qbXNCIPS1GAufH3CSlGxtr4scev6VA34vHOPf3iNwhPmjfvaCZgjTZOwbo+Ndk1GGzcWD/g4YxRGmP7dnNFi+JYOZWDANWui3mMR6oVzMQhj20b1FhcJujio+c7/btvrBf1ZA1osXH3nDyo6cTbGJljKIcHz3dH8UN9GhlRn+EjLr5zFJtHYXywgA9M9oWhGBbvxCme8fGI43nn4QnccOhjzwR/OFXRYAjG5/BDhO3sx2Efs3k3Lfq+L5iDb7jrF8z9uL15GANiuRm0YWZY/FUMh40Dn9YVrsMleLywVY6x9NGcSDTilAcYSlJAfqfagyRqeORmbVnn4ILVNai+v8qRcZTmPzmA6P0LDFrk/g4v9cnbzrzDHKRV2a8/HwP/9v3PkXFYzMEst9lpEwdemDSHMmhRwIVG8TBBjqD2XDuJHXwmRw6L+HBj/Es+du2BMId0uO/BkV6E2HFA9F3z2PevjfNR8h6GwfGj4skHTjTXKP1UxVhMtq5L1Rx4MYO6JZ5rkvlfHEzTLx/HkXGoK0bj+I5+4pMb96877+91n1yHK49tysgnv+LA2JL5mAdb1lcRaaSB3RF25X3rMtnGpHY97Nfuaz7r9tvPv539ge6PX//46bdvv+Wj7vd/joMOj62x60nuqQeH9S/5LDx10C6fTPFgazh2IwwyCTFGXv0ZF46qqsP3fpw/Oc5jI7XEjrowpH64NdH0FKMSpM7hZ7wWI0Ic8Wf9/JFWv8j4Aq+YADCKLPmdGMOduS8+itu4/TQA2CIkTBAN3/shiDRk21u/iVqv0aVrfWCgtXN85bkx1MFv2SqQr3ixM4b2jdDHWHIdXhEbgz4BumeDMzyLXB1xaJsDdRDHdayiPwZiSOxap98gip0TC+wTBttMdp1dd2C0oZaLhp2GeLQdu06pUT2Z3xqIYC2Qg9F+Y4xUVWMw1CtXjKdmjMwPjMhPQeq6V11HLw4Qw92hiFjPeuAAHP20MzLU1gtpDLE9sUFENDaqhy+q8IDKhW5U+JxcCsAV6NPKYWIKcLXL9dZwdMF1Lxh0eGZ8sDLwx98T6WCMz1srHOX58sWOOK+sAfpcYaJtTeSKfvGJDcTYvVkPzK2NPiPVLZen7TrIcfC1yLj4sOh4641e3eFDOrMe5hWDjZvQ9YPl4NDH7rQMW9PdT4mgXmejmSrifG1d3ryLhWbacoOPhBsPLjRmimf0mSsGzQdb7X7wE2HoiTyXfWER8zIFCkO+vXCIcJ3FnfiOx25rSWya0B0+c6R4tW2NmZ0aTQ6feHCZtU2/ca9/9APNY1nlCGj4NSpUd42PLNquTVCH2sZufcdn8lwerUu54MfDskgZv7kUk/8cYyPCgc0wACY2BLUOEitBGzAD5HJIb5FqonzCuwf3nLAOjbixJ2ET2uTjbXUAJOhwmH49TT6yLfCkf3zhh03tnTxj5mmLHY1pYkwz5EwugCoQ4cdGJfZpI9MZvHzRXIC1k1SEUWkx7lUXz02TJx+YnkMUOHC1TR8nngxt242yNh4yeBJFDG7HP9Phg8j6LfSA+S7OyPYJo/Hj4OEbOO6Eiyk+zq0NT56qm5ywN6MYHp+xxQs+Uo0sX61dRuDaSsYrduTOO02TB3GvHd5YItPYmM4SW1/kfEdYq7mm8x1kPOEpr/o0VmQTCxx5M48t+4En+H/ntjVbm12nrdf2ARNvwnQs58ovh/KBZXnMPI7SDIdTtwjKC677JHtSUUJ9WiGdhSwOWKSTBMQAM5Gu/djCYZ+oMcZluflOWOY0NdkL8hF85CSMQ+DJkZv7KgeePEXvi0TgPjficODgY6j4AmfOs0mApIHlk/dOP68bc6SslyLA0qx3+v5tCOqItE5joswY2ueQlsMP9ny0+K84iFE47599E5ycGktIfE0e+Ppwn8OX+7yHzBysWAfqUcyAlpBz9hQ3DmDfOaQHmHp95fZ3DmFzYMMGNygt78Ikrjzwm30CHWRgCZiJEl4r4LEGrtEH03XImN53xj0c539y2+cgnCDGkxcfTf/FdWXf7P/NtgTUBUKhsLFcd+ISK/jwpIHX+5YE9euhLgdRfzebA14O5/MiAe/qO8/BfGXAUt/FA9N8Bpv5to2nbPT88TZeYOCTAO9b3ayn3KwlxBclAZlIuTVhTDt5ouuikGT4BMuXWfpCCLbIqOEvie+LIZMj+a+vvy6QtdkXFYTMxd/n5/fFs7B/z69lwNW9FW6RbukHa9cuPTxTU1MIlrEyBdM9PHmMgWsE2M95YWlBvT/58yKSJ0/qAEb3X2PqQxwwUgNHsaOxDvWHRwSDpexZN7kArs/GLD6xuC8GPE0QcREtTvsxOTFFiy1usELfGOVBJioxbCuoY8MxqqOxtn64EdN9VkoxK3bDUYuMehcsdq6rQ4BeDKWZD29s4DdhUTiHiBGIOz7ajFo/MLGKjcYIdWo8J+Ok+ORQo80BCjTmQCxXJI0jyKktA9dgvHxGO5Y3l3jqnIv8ghG/4ukoPWNNHOOTv+3GUFLKgbhyzIrYTLTDv8+wjdua11JYPHxqMoAK71ikjVWHxoTjcCMdcxq9SVHbfJUJ6tZuc7rzcL7hdAUG0eZmnAg+5thYx5Wnx1HPdEx8wafg4lU4yjEZe32JEe1EP5wrKY5qstLWIBsx/HBtJOzIvkLkSN62lYnsNbNOZQHCVlBJLtbKNZ36lgimE6M+J5JxbwBrphK7NDFzwe5gzFQdcvTlqxd2thnoi3GE5l9/TO4eefgi167+e7UXA8+Nx/jHPY6M1urUPyRc78b2vFOjXBO7i6PEvWdOww/+aTf+1CZyqxmujVFyMKsFo9FVVSD9ili/BjhxN1b6F6seChnadr3EGZ6QWTlGh2Ny2hh7n9Jvc02001Dsmp78qtWnqHkM70xcXMB4YIjev+Ku7y3U3mmxPndcF71BfkCpUOyic32LXHiwUOQCaSdoSrI2qKrTH6An7haOAr0xPjDxz9dNNpaJBYy5TAWIWgyuN67c4DQPrIslH6iPf+109dKaFetK/znatI9lMM878YzhPjXAe+1uvSKMHQpk4g3ohw3O6GUM8SKNqzFqgkUaF+N36BMXi4a8cYo/MfGhbezOju3Wp1GrJLZtcYcTccshV/G6B7rey5j+IAwO5tRrDi66M0f97AM8dUXXwzMmp16Z7J15393su0AocsMZ/+U7eEx3rbYHyYYLB6IcAPYAy2qoBiuN+PJnrOQdICiWL0A4a06HE+ZNrDghRIzdo2AyfmirP7jRG1laJFO8zWV7zaAiYPAmpk/syS8qPzKsYS4JiK/sd/zMV2/ukZ8XWFIvdHnaHFkOCjy7AT/xOBjwLjqHrP3XUvfFH9wgPwS2Zyrn6e26B9b2poV/jBWstCJhxOSytzxEcOLGjUNNuHH4YN/In7zgGpvv+cNZ37+R59WT53lhL5DCkz8RnOcSG3LkEMZeyhFNw5alBykw+Qh2eeSd0ZhwUP/pT94lzeRp/uCOvfjzA5eJa0X9tiGbuu8Lg7sXMPt5/se5hy2yDTfWEFwO3JBZTA9vkX/Cl1f9Eitf7lvyzQ0c8sGJOc3aRUFvGXaMp9skh9N8ygBzOPPHyfz0QQ7rfuzeQ+z3jv2od/Q8buRrc1s+xOiNF112zNox7y0V7rrE9u+8MMP/7sbHF+Wyf8HG1twit01e5uQYbVoumOy4xqaZYeJia40ZMMyLMb/0d/B9EWcO6L7YQM1ig2XXhP3RPLzvZHnklk99bN5b42FDCO9nS5s1BBA7fbJ3dmygBFxf+kSTQw/AvU+bILoko20wXEujdf2tQXg1Lvs7OLyIQDzuYwlGXuTnCwX0LPi0HbJ3aa+u2EonbvcZXIyHc8CtdczgJs/IiEkzd0ejoyyxY0YzH4d6Rr6eURZeuyImLsGO/WBQl7FCx2Oe85tAtZus2vqiqG99yiKytSWnjLeKN5/L3ZodAuBNrm+OGROR65oy37H4mYj/EROG14fCb7zNoBhBjsDx8CXWjVHr9SmPyW3q1NyCIEguMS6Cw1mrItafBDSOwcSCBOJ8aSM2ZtfOAJohGz/CrW90Yy2WeMPx3WOYnzgYLQe9UQoaOWjDBzNsp6Fp3hV84OkfC77BGH7bL189l/vibezhYozFG9tbw8Zevi8nuG7tkEvGfi7BvDymllHht/JmXvtP7NlXCjdz4tW2/AZfWWs6avF3jIf2PFaRX7+VMhYTGQeRNDrtrQkGNcWWpk6bzjc86jWtZo2uVEiA8t3HF9Dq56CXA0TmGmMzfC63RsG4VtSsdVvM9mhvWx2Si774SNciWBPz4Dt/vcofF2y1ByF1lhX1zo+MPuZPrsDbNvfugsYqNteAbDV8zFMWybqDz0w5vHZ85JHBC4uqjcpQeXzK02l1guNUX03znE1/LbiIkD7RsT/7xsloG5CcliPa/g56Bm0xqt0KbuFWMrEkGrCJFX7AtXXUq8lGvGXqZh7Ksn2SneBnsaiKvthPAiMpDfRDaAoEJFyw30R1idnO8Soy7uRQdsSlCXW43U13Ymk1F+0EFxM2Hhzmzj3syidP2gpOEAyLsXF3PgSKBxlMN85EcXNG1QVtX7Tnig/+PmFZnD552cPjJ24pWbv4gm2cB1I6wwnsHZIKY6Jwm9Q69okwIFqJeXIe8a7N8VyA6M3R+azF8Yku8lfPDzAzDRliyB/f3FzlKBur+hKOj/jLPRY7N0Gc47iJRVn1XMeYznhZ+5/zDnA2gnOeKPtOqHoSIoHWDgSm+PmErTMMPhq5+KKJkZdIQhh0IB+PoEXX+GZcqseiflj1QFPYzB678qlLD0FNAB8KJPepswwSD1yxNYlF5s19gIcvnboM9rEDXG48b6VmPNHm6b4fb88CLTb3r+/5K9TyACZf9eU+r6B0mE1YxNYE2+UcJ9/NltOgpasdHrTMjj2au28Y7zuPHqA4RHDAmLpzGOGnjXw5zKdxV/ySQ4czHiN4ME8zOnvASfqMrQ+Hr7+yf+aAptyHES31xHTfKTXhQMo52B6u5Jy4vANu2ZzFAAAgAElEQVRNjDk4EooY7do7ob58ofO7un23GZt+siaBTTk1TS4eSGPag2F9kMnFOHBu/Y3TbL26R9DGzsM1a59xOQAaZW7w8hMG1jYiekPVwPxqmFp37+19r39QLbgjh4P4FNAASNrAYW/4RZ/9yA07dcmLhr91wX4+9QGfvlBD3/t+1DFmf7YudDM6OB8cyD0a4iegMYnL9Ev+T9qXvMjAmp/4se5a9/5MuH+0Ee5+3PWE49t2T+6LM3INnyW8ORCbW2F7v4AjLwDQdmzuser9ofY7xn9SPD4Eat6qEiOPYxjldms2Y8TwsLtaBMSVXwbliJAwa9e9qKgG0VRnrddsvF87f17MHqzLADghHs4LwGxyctQarBor4m0tKB8eyjAyEY18riKdiPVbkAgbZVI8OS+Nd63wvDGXOYiEomlxL8pQdb0Ta51KQkqswzrOsh77UUwuAgNWv2FeyM3CkLVnyJbSoL6DENHYgxVS1nBMrfmldDmDF/tFAuPwg3jacmk/PNU1Rn3wQld/+zrUf4sEZORbu/Y7v72Bc6n5RsBX59OXYeXsQzPRZnmDhFV5izfcFddD3vKfuhlx7KQeR6r7ts2V+sHL7kSL6JifQd3ll2hxKAbIHU/JQrd8ccAbu9oUYhHrX9kd1+Pi4w8ItZvxDM4+gbwmy6C2ytSsXyfFyxie+3MHl+WdXhbiLncY7rjI5hS/WyviiN6AARFHWWJN7RAib6t97SLJoHbwyTzgPeSufLjBBb7h7ws1gAE1nE8EZSirRr51e1Q1GO7mcAjWyljyzzw6qR3QcBp7fXFJe9fQuV7l0TqFi5bgnYDF3lqpjxWG5Pshf2QOL0YZ4qwjg4kQjDlbnByWhdiPy5A76zEIinMZdfnmunjITz7BZH/MR9yhUeUWYJ1WrkEnDmt3BWtPf6WQqeTiTnFnQ0CoxDZ+fDZhvRdxgMd6pZju5hIrgvaR86DuHWliCrHMg2Ccy2+57K45vPKEzjgrEAe+bYihRUGRFZaY5YIabI204djRyhx59N4BsKI2BsRzW4P392+NGJM8+c9XD261s3YZLta+m3A4ZQCTzXHjGBKxt3LBjLzsfHK6441/52MmH0Ccu8ZGa7wxas6tiU96Y2e6msYoc20yxIU77GkZoiO/o4vMfOkx9HI8zqA28V3JDsBvgaA+jdEaIErUVS7ZnY8HNnrAjc3Ag2D2IH68s8gTzbeZg1iR6oM3vk/cGa9IDrPRWoGyXCrWJijWjz4OH/UbaHzXZzlDtK9D1Gj9sOVIWb65W+X+AF/sabV7x5FxwHoOWYcHPpMMHhtDIE6v0XnQiJIDJXrf6Qwx5LuGPbzHiwMguUAZQPrSz+Adk28M/G4umCuTT3V7n+phTARtXJMnZ3CIs2uApYcxOGbdv+w7lOGP3Dg65TAUvTWkFrzhbBvAjKW/NSL/HNL/mvsfHyFfPR49TCFJTj7WZTznLWtHTdOw4GP3fCTbd+QHX+VcXIuhccbROZ4MTEGs+aN0weFdY3/ghyO5dhwZcuLk5mGX8eIxDh+w8+1e8SD97Bv+b/l9/KLS9RckY2tKeoaIlvtb6m6OwdnYzZ41pzBdj2Kg0ZmrPPEhB/NwHIv4Qbfy1J/1fWwGxdLw2O0BlRdqshdcn+FH7BqVESEptwVIAGJYk3QOmdYiuubLixPU7MvXX+1bv8SZGoLXPdFYi4+d9Yie5mPR7NGtMQSwoxmf+/lHm7XycawMNR/emC7fzdCcggZ7vrsmWM6+xPe0uV8OaH3KobRmDTM5cVATJLLGKtjqvUusdR43CddawrA1XUflDWQNB9YXCOWNrnTseBiuwAK4Biguj+I7Hz+U+472chRlnmPsOlV3gzGfKpoDPm2TA3qxYZRxXBcfP74+HM1l8CGYOTPtBL46sbD3/pWedGljYuLB6HSFVVs3bVujtb3+xL2eC33gE9e8xF9LvYcrdbmt/H+0C5cYLTNssFhu1tyA9VNOvscDZQAINHyQoG7s8UOwQTRdbg2+uMJE/2OP89owXqjyjb2CnRkgl7aTw/Kkl85wmDVee/q3BtYNF2PEZ2Jpf8YOIpr6UQviHInDuUQj3sTHZjhsZs3k6i/6gQiPiTUibBaX/IpZpfnIR4XC83im04CAsXYZ733uFByZNu25LteI9WyhNneka5tBYt31KJI8x+jljAiUXYv1W/tuQzCwa3/IyUuVIJvH4m+di9n1wJdSyN/BjC9MTJJv6l6ciQnLM2ScCfPFwv/gMakxGMuL3rayTHDf6/Is7/FvANEMN6FdD/YfMaPY+m1ejRn5xhQOr7ElLLr4L0aVZTT0txsbGQxnfAFpDIfGOOLi16RXYhXi8JqpTufH6mDi5EfcS3qAT5BI+c7c5DPZIph0dCf5AB2MKT7gRyZQBB/PokFrgS0mDmlLeGO6EErBW8TaOpcv8sYzFLLctvCLyWLQlve+cz5C7RtXSbnocxAOQSQfbTfCIwTL9rgzbx7Uc94ZsGY19To83UAjNpf1TRqGSy/W2kf/EerhRM5n6ni5Ie/Y64Nl6Ah5QkpTxQV7++qqzXiNwM8XnHmyaI8/Abqh0rcKdXn21vqZCfncPYLtj3P9iQylfKHn+8oNivI0Jcwz0EdiTMrJ/Uh+Nqxpy3diVJTnmeWHNU85Nz5P4Dlw8P+GPYyhyRNiWuPHI3Xi3cwTagZ0+NPA7fpkxLfdw0F95dYmRnIwCghtb22ac+Sz7iXQPMhn76a757Ye9McF98Gmq64Snvwz98DFo07EzLftgQD8zc9Y4MeImqDART966jz/u7mxkmcM8P9oG0bgaI7BKEbeSPWsSfAyeOXiw5Gijzsd0wOM6snNdSPl7CnH5JTb1/xBLrLl4+HuC+9TokXP4wCH+LbFY44tH5/+kv9vzl/gpnVdhlcrdjkuH/BrbnwO5bzj6osc6Bq63DdwhMRu/Klvku088qwBTRtHvbiOsSNfbqwf75C2zxyfFk1f6rB7ACxyPLf5uDZ89x1h4w/f5l4OxY1CWsxaEw7U5JpgR8fvoOMLv+Zzuc9o6tr69h3e4p1PHsRfDF4kyZi/NbC5Etu6YEPY5OSLqT7RgYZsG8orWKVoTtkDPH5gxZV3r+Fgaly4S3A4B0ke+NaaxxXk+VhJc5s1JP0IRscQX/C7r3yEieDGra56I2fI+gjE0NZuvIIJ1+YA8wQwxvozyThxyp1p7F0H4DKmIydHg6VmLg/e9+/Pr24QAlweY35ojapBUBu/nWCcNZm6VmWWCbwGZ0obnhhimZZYO9aOy6jUaxLhKgmLibhrrFLzjmaexbj7Eh6Vu64J4ky8jIJHWGpebOHOpWtRYtfmtbUiw2HlU31yHUomRyH63SlxDc4gt4Y5PGb6qsavOcmcelDLcV+YXX/kaq03M1qRtYnSWumo5dG7xzJTdaTMybkYa7O1a9wY2yaDqS2irSHu2mrCpLHPus2c9UHn40CctJIQjmXWmALJqkgSKK6q0VOvfC3/ImBWr40DtjZxG01tgCnUB/aJObqtx+aFT1W9nrhTE5UKy2w5bmz0cgRnciDDylDy3f2HnLYxnOA3DGqJVDD9agxOUNJVO3trfMsFt+EY25MnDus7a7ZrZ496GOF99gF11x4AGalbDsg+8sBXPmjSoKwFMKxt7SsfPPBXvqMYYstl/VQNluO6Zbj+u28yHx3d5mL9nzkYmzP24xIpPPtF7vL4MBjJj7wDYAx+htSEEGdY/F5Rb50bI5J8D6Sc76S4D8Eh2yBeC3tiGfjD4e49c76BEiY5ujfgXRLAUU3njD5ybdwhYZSVENcagJkxbr0PYF1UYd+fNbXkI+5dwNuPA64ACU6ILtASf3u0p+lTzHqDlxudiWKJUZA3QcaKWxSxD6+qIFL5QP2o1wyj6vfaIhdjcbc4SBu5fFqsSpE7l+OtEQ7VYdd2/Vby9ELPYurbMVzkqgyEzGl2RKBlVXiStnXySXztzGvrVuPx6GR9HlWGiULYwQOp4RIP2YOHjQeMobIqp5n4rn0mnd+YzLmJGwx4grX+an20Ih5+WLL7bo2sRcUYHL5OZn5wC3KCgkPbesojM+WdGBL9G1MnuORbrlsPfB6ei2u9UE1ieTo+OTY+eHJMn+eiLa9ryRsRUxOe4GseJk9/XxCJ0O/qNQGY9vBqLSrWnjTQazQ8KhBPMWuSL5+IcvhljAvxGPDsXZxcQo7Y81wtI16XuE+K1SklbioRPA5c27Zm3Qfk0kyMt0b2Iw83f79ZIpUdMzntbOoIHvLYy3Rdtl/z9M3zM/LHjLqwYAHc9XtpLHfjcbFgXh2ba+LuQXB76tFDH9hPM/jkkbGIyWfvo/DlsErLr7LHoP+ODEsPgOaeWqdfbssfVl12g7gmlIRXxz38iWfEE4+4vfGiQV90AqQI6JqrrhysI8AOOZgcIsmZd7HhxEGZOYfc6wmvcI6P+yTOe0DvwTyfGOAPvY3N7htZxIf9ZV2DSPvHmiYu+gSXl7WJ3c2ta6sn9aOlA8dhZMSint7QmBtGxUZODPXRGQ9nC9S6+246L8LG9jQKRxuRub1xkWOTfpa9+zE5e/+L3PVNv5+csi64ETu3doyZts6be8ywzI1A1e+vK2BrLQcDO7Bqhy2TFWToHUN1L0J2P3QPxoT75HCFpya5NO9xiwG6QS6H13ZCyE0rLAPidzkpAWcJq8ODVtsOG2XNUFUyvUBaVs5jIzZxEG1iiAsISpoPpM3ilEVHot/9pGku7on48wUCy+QAA5rCiakVomXKeOLW+rkGEVoDsQrjLFd0sbloNTbHga1OEpPb5BBTsdbZHJvhxhI4csMRh9oFqrkWp/Usz+P3DnSuYGsvBsnle2iKiZX1QJfGFX1tJl6krVm1cGmrfiauy3JDJsbgXv/RCLE4k6dA8Yp4Y5x6NQEjE3VYa9fZYixzYUQUo0V0fjVML4fuqzFBs9z1hde1ZVgeMYyenwtiRXGssMFXlstYYG2oybHdkfa14X7xoEVYTq0lEzBp14548HYdGF8j7d1MuJjLZ04V71ozo01enWT2xBq1tfAC3uRJYroO2+idbs9jAz8XwLAIOOJfR6IA0Pz1nFpiUix9xwc75qc2ughcjA7FeP0Mb0xojBFC251jIl8Gxg+KMWp5MJ2G99qIObbR4U67j2HAIAxz1oufVat/5PgQ76zrg499EbTqZbhtPdbPxy58d28U9mIPGxDrCzIt/bM+SD5y9gfs8ANDfnXDsnSCOXCbv5iY3cIUN3au6cTcPOSxGJCgTV1mmA6D/JG4FTT5zha0RGrYkk/Cp7BDe8AlDPToxQHSZikmyfgthkSHbexOUTJ2AbRDMbEkDuBweRMjxNpjkmiL1yzwyuiGi0W3VvF0qk2HY7p5D4fEaagCFeOOL9YYDhYdfE4DJA3R1o7F1uaVxaaboT32+wR7awTOwWByGnh9RzMWHatLJR4qDkcAjrjJPk89x/riu9/Qxck9nQuyXsgev+a6WEj5rkLImVP/6jYmRuKBodONrSc4aZbPQJkIMYrVjS+2W3fXKsTpddouAeWduSjIGV0iBhy2EWsgLvZyT/2Ujq42xTAu+n1Aj+X6EYnmk3xscsgBZ2OozAV7Fy1KcNzb8N51G712jGmZbA2ZwsP36uBYwMQ5Q/W1h0GR0HPe1g4841XPGCv7kXsoQIoOGQY0AJ7mGkS0edI7np46wNhbOuGZRb9x0RoDHJ4MnLVFobGOpZArdsNDvzVJj8MeLIiFGfi0XT+FFVWGT+b91ZNGaQ5dT1+4yR8vY215Dv7xUe/8IONOBIKf5sE9gcHDlrYcPcjmXWBa313tu7fYw4n7oo6TG3xpRZ/7MNi58fV3OG3r40Nss8hb175bDug0YmQoRUTBgQc+/evxGYPPYTy2/qX2jP/KIZk/UgbHvuM8vASCSfLho+B5jKInz/dwbt7yLRdqy97nIN8XA7LmfFUtB+jVjhcGqoBT+TLPDZzcOkzPN3N9eZe9h9Wt6Vm32DjewzkuIysmCMHnu3DmVBGxq+4AM1ff+NjQ4KFc3OECP5cxg9SIGoRI7Wetvb+4Lv6ZQteFx++/edcZ/1i7RsQwju6t2RSwFLh+1lRfCGo3/IJSOTjJY2uTPt+NOWPmWPf+Bc7o8QQT+3+0FVKj2xhv3ehRsv+Rt3YdE6KBmGPEfGvLMILE1g7/AmBU28h4PPlHQ4QriqmbrkyRpWkyk4mwDnENh/i53zZ+AOR4EBaruR/+AjcGsc2XPl826j2Yykb3cmA81nVhpt3wPhhNoBUrP32t23LAZ/GImNmA8xgCvzXffPHc+KaDDcJMdu6e0G4s6R6OMvPxM1jx33p+LNc/fPSS46AS9bNNjJIms7ZhOJN4x+7qhnezby7GLjdsbXatERVo3crkrc2iYUPt6t8cwakH4mWwsiBGZITR6S9E16Kkl9xF2/ot0nK2tnHCo3Gb93Iows4unxMnKtakGsiFndyGK2s3zy3grWX01sPZg1mteNrhiy1++e6YPoYJ2ppmPNEZjdJInRb/1F9nNMU8ruIjV5NL2aIvwsbrDCkjVtkWf4fBV364V811TTAUXVcQBgObx+/kq71KayBW7GxxdWhPzS+WcZDDMvLxkCcxP2Ixjy3ek/kHlqhiRPsAKderdMDY3BYfzc29dkiWa+F6XZ4bYrmU2eCcXFq7jUMf0JOXcZdsE0CtXjtYEahCicH/tMiZKhtTHSK0fuhyW874Vb64SNI0oivfDcEsH3FnYXBoMCCwlxR9mjaTyBssiupJWsOFfnyGrLiqY3kSbswt8sYxhmbF4wrZNiKtH1CNrXYLNpbiMZ6FKU6VHd8FbL4ztx6xexzKKXrjTR9cn8iGUnMgokwahPEP0xaq2Js3Ms3m4ka6CN0wzGcN8tzwtAO/64OG+p4WRjO9dcUEIbXMOE/4OuxcoRfmsZsDI6Ld7H2SusQ19lKE8VPycME8j8a+YxOdtYKH3Fs7aqIcGaqB3h/2VwCugJhl1C/Mi8Ro/UEZ+wyNsUXBxiC9HxgbR8xp6tr7pH14nfsLeLFdc+0zwawvomAQfWSs27H7hCaS7bwTFx9aub3jUaBD/ACeobnNLEZ9ZTym3sc3zwL0UDtYwlUPYZ5oba2Itfe05XTiRXdbpfolXo5IOSD0J7B8x7APlpkQg5OHsRgrsGfsQUTHMYgLe5c6ISZVXZwBo/FEoRs+i6FkmH+YIuv9Gq8dyyF23ZPVjNpYljp5ugfAG2ho1DdHpBxQOXxyQIX7OXxn1E8KxI0nm5njY05AZcBcQdQcVr/nkE7u33PzX5TlkMahRzMYrQ9cMud+6kg+jJJJbIixXBmLrXz17TcHecANiGkg8wfdOCzvDRW2/JuvX37LvyFLz7vpcP4rctbT36OWR4wnJvHLoS8SEOhwIm+AvcY/G9OcM+/HrzMPmY+cYg2PvT/14+bB8bETNHzuDXQaezGZR8sfB4gdNsjDn1bMFrN7kLFmxoeHLT38aT6+0kPQb+LfxgsHNDrwadvzr9CMA4/RW0NfOGW/LF9IFAfGxAapuQhJaHEJUfzZX0+e2GuI7fhvYszjyFXdDr4KWExwFx+eWBurYJkNx8xNe+yNKyCX2qwMFPMYDPMYmaaRb73wxqyNdSxa70uVYut86q40hhvVeScK98BZsFVsnEaTXxyb8ehURaILl2ZENtpFJO/01eSKGX4cbnkBZjiqX/uoaZpGb33GrrUmJsZ133utOcdv8y/GcIkxMV4s9PJUvhwjnFglem1kxOIf/eNjsCc/yJnB7ZgjpW3f2b2a1oZIr12E9JsfdaH5mEw/N0eZdC90DyyHrYk1xRlMc3ESZotaXKSnVthpMTzIA3NdridWJTq1fmq13BsTn2IVo+jqgN0XJgCbfIAOYeEdn0SM2rBvndhbNAqa5izDxh0daniYn5O9NBauuudiLpnT/oPs1Aq8WvWKa7jsmtxXdwB5LMPzSgxgnLNGI8Knf3Q2vpPbchONS2yLhS3zClbWGiCLUqexgVEc5IqxKPSPfPXp3QMDgU+bAY1JTcQ3cMbDo/XefOG4ezUIsQVhHYXFFcmEqH8EUVZeD7y2GfvlP1x8ns3j9mLFQYwherGLdOd1aO2IN153aN3qNeDzwLp16As3a8E+6f1EpOC0nhnonsskb5aZYr11AeVyqVT71BKzjXnXpXG31upBwHZ84pTmReMbLVzNZXTptn7Y0Na2MwSyHmyDqDJug2ozfySuxcBCwnvnrUDHN8JnsL3Dwar+m6TZTUJbbFIg39rSMZlCENeiI3o4GRwr3U5SXYAIlYNDw4oWZKEzX8xIr1YTBbtI2G+BrBEw8IOLizTe2428pR5u+jxx4vfqHyrKm/84EU3S8Zc7c3S9g+54rcd0jZqbxGO/Tw4zN76BM5q+awRSktkYGRufuTKgy3B54bFP+k9dEKbVBbyM7LoGPIkeOPG2HvWIoZyKIT/cR0Z07N/4O8dmcZUNi5UtD8lcgrWS4zDJuFjgTTz3Ip7wi0tseuB+uMix0byeCw64DBO7yMBQs5AoBB/pjz4VH5xMuxrxOTWbWINUeWUXFPNHNmHtlsKoT/5TEyPGxp9VYChvvRjDjb3mD9m/Wj9lcu3hgT9sBi9C3FziSzHivw2dN7L00D6984zztfZQES9XfxdXVbGG5sLeXp+un1jReDjaR9NgvTHWETxC2x5w90zkvP5QXTtzjJ01m5w4ZFEnquDvglMzP4IdCfdV8VuvriGpts6EVwZ/ggWbAxj/wo3DP28S/52e++WlCiAOwdnHczgN1oyE3YOwfe6rO4dUIBODP4x2P9Xx8vLgmkOkB/S8ePAtH02nke/XP/74if8V/suvv5izaxv58sQOfEi5DvDbW5laG14EcP9Gp0NO2fww5wUn4vjT0AdMoXKJPMBgsp68IOC/QuN3tS0AMBbcfsfwAX9fQHSei493Y7+HZdbL2GOEekwqORxmbYkbmR1PsNN44Qp+5pw5PKi9ddIisqxd91l4kU/mvuiFfb5Iv9Dsa0NEQx0TN3GsG5JNPDr82CnmjTyOVAN21Si6c+4fGtRHPuGBiAtxweLxEYH8Va6eaIOBD4THp1GdKn7UNcKTvGNvj0GcxXP8eVl5mdRWa/zXUyrFMIvBX1z49wXhOEz9S26J01+8ZzJSJMEAdyT0tO07C06/R07tmgH52pr40S+PMrgcvI8nXmtFbom1RsG448FF3wCx7bpXU85qMRBoyEw+teMa5fCr2SCOjADusTHV7xBZ7qvUWGHrxpwQrH0G6es/XWTwNm5FMddhrhEuN2jOOmKDVak7cmycaIiNgbhcatpBrvWowrppe9d5XLTkR9i7B0C9aWwQ+vEip4yJIUsGo9s6Lj9VsLwBa7u1wuC0GEUuJvjcT3W9vFvjN+5xbgzxigMneW59MQWXGOjyteZ1jh7BcJ0OrzRm8ROLWXHqUD7mrO1az4TOeJ0bUwT8lis2uUUpDuL5Wpl1iX635qUaLvimTef4jYNAf3CnHsg21urVjRz71ghUAmNFi4aAl8DYGUG9ZjHA3za+daHuFWzNnI8NT0jWs/HHdrAMHdHxTW1DCMHhgc5cIhZ7bCaTqUGpeR2FfhEMa31PDmNe03K6TKFQ2XJpgW6M5VPe1KBt/Rp7a978dqnMQVZbmcYr1uQYuLdeRW8dbl43Ll5vPRYLlBtvSFLbGMP5xsgMeWQ9oE8BDFZLjQdikQRiYgG0K8jOSzYzkG1PUSK0YLOgC1aEYIbD+p/0gIp9k2ra2ptQl/DHOOUyHA4PfC+XRdo735C1KIsnh7OKEjlmJNhcGD1BYsGMWPA4ujGZ55DKtYh8ZfIbQuQsCjURMbNZo6UUg7YGsk4KpFp+xQGpvMYj3aektee5CCem25ximgYP7IyfuXS8qBZxo7zoXT8c1i45sabxNbfI32qVy6OvW65TiZRmoI4fJsVgVLvFQXKadY2tSXzaWX94zfN9fCaiAc3J2MOfZ8YfLRYsG+2py5I1ZrXnWlmz6XjWfSwWBtpHT5iJ40FnJvW8FOAC/62L/E9kUypPckY+BvpMDH1njAk6vhitj3GtZzk6pzYcOomePe0+nGS2Dot95o8embfg7Fisqbk+EzMGUJvEEwvfMx/5mCBWS23Ci3EPi7CuTv4Z7x4dxeBrpOjoXRwcFAckwZSl9yBGlIzhkCdG/IssP0WSXKyLtuwlADh8jy0Sa5gBLWJMufh/zhOHQ8R38Dioc/icegnhRiZkHOdAWG6sS2CIl28OhLyAxgEbPA618PKgCHNqHgzeJe1Y94hIKDVMz8GMw+qf8f/27U99seId/j///EMd/6u9v49eWw/9+naNsZcTPfFzwITP/ss1/pJ9xLbveTECLn3dZw/ppjMGY8gMmnYZkAMg9CNlwOzsKW2L1Rwxr/70PMHFbuRg+JzXsLkkho/rhEq5wScn1wX1yZSlmfUYX3KGX9cwwG6J/sV8MPj0AP3PHORTA9a+ZBpHdGKBY8sYe0jOevEEPSEu/7HrfQEcWm3imjojgRMo6XPrYRy7YsNlMZFau4Y02xnW//nBC36E5QgAk53Hk0nfEcvwaVjSrFNsqOnKdEuOvnC4wkAtJw8RBF5d+kaaOo2usjFbm/TWAJs1CA+pA5hv5NR88RG1VYkbRpWTX7X6ZKiV7rVUG6NXTy47V0+8/1+LivrQfKcnAY5//PbAVneUwx+XH2B3ai3VV9J5x8emQIWIkDzzncY1cRFoDLsMxrE2mW5OcBy/o4vx9ccV55Fhi2++tXE64GKCUj3SmckvU5zmYCZA9LHQfa21ymX1nXdbb6WjY3PWagwyz/1y640l2FpRi9N2P9PDLzrgxn7NdEk+2MCZeu1dCzTk+mA4dmBphwu4Yo5xOj3iuDqxkYKNvT1WCu1BwQOdo8ll46wtJtoOn86i9Tv4yoMgTo0XwzUBfGIwpDHtGgqohTkAACAASURBVDtQUO4MI0sz5qyF47KPgWovxkn8E2/9hrQ/NzKuPn2+wCLE1nh94VO84qs3/tRwfVEHoHkP/40RjOLHe/Mo+WIXOkht9LtmR6hKgmoLmGGNp/yL8IoTaJLbfJ2Dh7kuC8L8wSCfNYnhwETSdjh+zDPRr578SPRnVGCBpn4060qfG5KDpc3Mr3LqhKDNEXFGdNZJdWMw3HorFm/zwLdri657wlEuZcTMXLDjvv5wNxkNAsp3uOgFIec6n9zw9Y/E6XP5PcbxShsYR5Uw3LJlTID4o0O6NmvxUMfYApCodgfn+i3eFqqY/4+uN1CMXLmRLWeu/ebt/v/X7oyvvXFOBEhK15MtMTOBQCAAskrFKnV3S/3N3T2x+McBJ3oOnKwMcgby4sBrO6XHgeLgIMn4nojCE6er+YoSmQO78WXpjUDT1gXfdDD7AGBvXCbG/N28R+O+7qYScFzQwOYnUm/oVngYgBAFQUdTrh9ndA6uX/Ji8kX/UWX/ys9ZwB7e0o9fG7j2FyI7pIz24MjvTNxMPusG6wb69v8wXknL8VR0546YjLOXy8TqbL923iu6BZEjf8hR6u4lQ//42bf3T9j2ZFyMTTFSPla+GFaG6nUS8YFq49Af6Hg7Vuq4Xp2VFNyg6qcO9Cb0rSd1cQFfDdYj4A5NRNS4ZtiUAOK5t0DMRNtbTfkk0HtO4oeN/a05G9QYF0zmnpcsvXnoHtt9k6ePFYgzop0bBmZpNCLm34xvDUDY8034Ckwm+SF7H5Pjuj6x3Q9a82MfvvvyEX8czOSB34WUrIONj3p9IofHvxcePNoYFEa8Xzfj6Jpff4aD/+aM/4Ob3zrgxsmeZbbfuXFi/oN/AR9KwhlQ5CehN+j7u9/cBHOzjk1IMP56erj/tb/LrSPByIINDiVmf1zc7KPBm8Q4uTEvhv/VIOuStD5YqHPz3ZhbV3TAwY0W3K4Vzif6XPe5plKflyEc1Ene2O07nKD6pc0oAOkPQHqW1R5jLNjVbSBrzlHmuzb174aUdfXzRgH94HoEv3Vm/rs4fnXmb3kT5T7V9+GXWLXC4TpR6GI/HW52aK9zLtZfHgl/pv/P42o1lfXtQcPLDS/UzPSuetlnnT8+uuJjzbUOlsH587dasiZfDbX90AqeohjOHODjWCez54cmjP8SmZcXaKSAg2MX7orHUI0Np9tHFB+xFfyEohHu++s+Pu6C0YZveOuSHb54c/05sn3qbIqKBMPe9FmkZ+X8Kfs44nwGS+PUkXX+EIsRu+cmGENIAn6Y9zUJRpPXH9gb1xgdxm715Mt+14wx4bn5YpLOcXnZsJ5x4hSrB/vJsXcH/XVtwkKuG4M1+Kn1ag9qj4sXP60aFg2dUrgeiL3zfdfHAGLK9NRizuGe/hzv4tAM581Poc1L0ru5CEwFXnfhMw85FFY+efRVC8dmDB7uxyeZIK+Pg8/85qhD9ot3vgDmcrf36MoYtqowrHePfTiKms36PKcnwqAc3muovSW2VcFqhQvJpns0gYGeGXhqb7vWczaY832PQ2sYtXZihoJnLgK81tpTCKBPzqvFmNq2fCbPt69hDCpnlu8bXYFWqOLMD7cMHN88asy+GpviPXflV1xd1ShTI8mzlQjTNpE1YjwpT61FfmgTwPMuw4k+HetmpVT3QQ//np8mNuLTR63ZM/f8ZB0QysEuqTnFxFqmYtCtHmMCj/POU6/ZclwM55bRm91w7fmXZFNRfmDnA18roRk6ayFu9aD3rpMnN8aM6297txpCI/643QPO985dFk/sqHAOBBtc1RNjP0E/EcUFFDIEfJ9gDcTGFZABhUQsHK+9nia901JIMeQ5Oxz22CurZN8cOg37FvZrHfLjq5Zw5pWGdejDmhjzFtGkw+yEzIO81rd6u2/TVv5Bna8Fp+HBx4HtYlh7Yn9EV8Oj57JDmm/609ZkrunJyfPGM3B+Bi+ifFH7sVlUcC0XLTh5SVblvvDCRN44+2cvyAQnJk/K7Sveck2gPITjuHPo/myr//uih9zqGVBWJT1CpS/F5c6O5E/NLOhPDeeC62y65hCdpvZBdjF1uuOdL7Yb4rO27jkuB5BvrbqfWPJ/lMXpH0BHCsGH0/p/OKOFHMKIq25tu7CeGkUBnKYE+Tievbj2UFL1DJswhtJINg3H7Y1DbiB7LU58zhM3hnyKx7XGp2i+MRRQ/x9wWKJ3fEz8PezTdzdHskVzb07SAdZo+3yj6IZlg8nCTxFD0DprMx3+/DF/eNQNgcnK9D1vvmGh2ejVGRL0L75RO6INL8QKmgavHTyY+XVlVtXBDBY+rb7A4aYyN6DYZQxkT1Snr4qkidNI4zlc3/NRc3qBkxv1cOYPb5L8wQ00N19xVcpyV4p60Hk1XD3oMSb3lvwf7Jyb/4xOb+qWHSyaW8/6FB924jnX/hp3rhvi+Yfp4JgSue5mXn5+gCbO+N2UEw+GOvv3zUnwp89aMTuoCF3M16uesxbtD+048Z9Wd70U5Xivi9YUGcEeHjTRjDtPZKKeF1fu63XqoK3Jkb/LkEUfI39LjT43r07y+jwNT/7YU0hPQOYfN8bQ4c+4vxrh/0NPbP6KSabGZjrc1XxafZ4fx72hA18VdMWLGblsDEVQL5zQRxPXbjakYzy5sABnUEP2RbHm0YglRwKfGjXOB29xsQozKfAnulzmjgb04GVvrixq675xYMoB7uuXts5lkLlrH6PE7tww5w/1HoeJiXfUx1KWaGvm7J9+PBaENGwBXqsfWzM3J5Bv7revOJqHnK0vc7SjkW/Pl7yvHpHYfp9H8LG9nFZC+nDLHl9mza82Vg58rA+SxfXKELzmGJxp+d6cMlTHeI05Ums5TMKT8+ebzskkZpqUVK1gWx95q+E9rh+Gcbiq0hP/gGTNVGyXtVFG5TYWzD026JlsghpfS2OvR/B5rfw+B6u54atlGGLsITOp+f41Xh11kpsvXo/VV80tIevLB495MmPeloUcZwSXtTZA7iZrXK8VZPPWtTiSO9oZljWdo8TfXhUTP5Dntdv7eGh9ybc67zpyXl1PHZJM/LPO3muaTFlGcK+f97F06vDX99Z31wmYNxbk9qvwrTTIk/AsalAnbpr2gd1rLDlz6P7ZsWjuBKmDPf3XcxZRldtlc1AvLYjNaKV4aHxP4PwSkkzs1fvqSa5PuuY/5sylHcl3Ot0D7LpfG37klvMeF5k97696q5B5VO1DH08KiJ1spciGPTzW2f0Jze7x9fl9mq0/qJU7666N97rBLofcb42X7+9tYFF30RlEgpATfENshP+gD84EgAhgLNlFv2nrvh8c7hZCSy7uxD3CFfIAS+IxCL7m+iLazFPwCcnywSX21q399rPqv3rfqp968HPi8udszOxfWxO2z3jzQpVXbpqzW89C5Wh8eTHQysOg6loLjs3lJx8mJtdkkjs7yLP2AvIFR/dgieGFLy9wbxA3Wc7AfD22V176CSUfA3wm87jnILXH64W6Ppobnn59bAbucOdQ7tjKY4nvExD1fpJPyZfG9fUJoc+TBYVltA3bZO/1+TzRU8eugcRag1Gxs29zZ9m0etzhX3/UgC+Oe+BiuyGVm9kEAobii5tWuesXxPIlken2V7+UcoXDeCw9328t47czZX55oOVa6SenFoMl1w8Y/p6sWPoXGE+OwLHRx5bRmTUS7o0hNL7+rWtIBq6TTHy/rdBWnj4WStBc4HgxZv8S5iD2OMajKbbrEQlqKyePD33UEIc6oMmma+Y+pslBrdRtmke/DrX3/6+uRq/dLykE3wHJCb7E89vnbzOyBsJNF8MqjG8ANdxo7O2Yd95m8nwF73PDpzbcJ1e2HODlV9bvJrlvNvTGUzwa/T/cm/9bhrE896R997xI7t6Q75Pz1ICOvpGQ9acO+LkaaRGPWzX88pOeXpCXs/KjD+z16WxxwX/7U/zrh55KnHNgtufa+zhQUva0Dn7+kcB7jr2e9jqIf8/JvpnhmynJRQanRH/PJznyrd9arD57wO90mi8n+/uGoGsCHsL+fMCU0RyuJgM97Z3caog/aR/ewjk+A589T57vDECezK22fnarBGUOz/s062yA55OognIk1y4uYvE0Z+Zs3prqbN/nkKbXQiODAfbwCQgJxto5r69a4ea8ny/nswfj0baUcFVXmFhcitVhf7R9dFEE8d/ciWWPA3j7mtVyqowtvuHKXQu4rWSAaUS7JuJdXrl0x4Y56x9axl/84sBkCZJMHD0XVycu/ZmYLXEGfBq2t8yB5FHtoY5GoqdGkwF5+1Qgicp1Ncj2q29EPlxPDUECpneh+LbHNTaSbHNZ4HoC3ACpDs+NS9DA0AuPuz1PvOdKu1pZJaZJKiub1098dmJZdu25SMw9/4gfybcfDbvenR7SLQf0xrlwXSlW1DquKYPo/9YtW/j8gVjuQkEyOqPxfUyetT0BImUw9JRrTo0YtQHIolTtu54dpgcSr9cH+/Nxbm88NwEw5/nZc7U82BhWr4ZsHtvWwV4dPVFALo7oxZ9YQOhhkJN5HF1jZ3U+AEKByf3ijjuA+cCqN/unb8aXby0TD5bFozcJeP5Svknmn3Z7ExMcuu3Jy2teQjaaC3/7fvHnl4V8MZzmN3msFHyDXj3n5+0H+OaZpu0up2q/AHim56U3u30g48EDy8ghMY6eAOO10a96FrRaPiG4Qf39SaazTSP4kn3XBEH12iq6+0RMEPsiXezwRmEopscTbdKYnhO/TD/28fvgeWofxwWHW40p7OIuHyFrKSBx+uqYqPL9jtXJSfLF1AJ+CDluBSwP7B3chNCevPTM9UOR5+kSXe8lk1X8fsJ4OS7myg26JrA9D0/85JlBnifoTL6o7XMhv4LKi7wPZktf3Lk+HzmzJh/zj6gWZOrpgfLbRwMwEipQgFxox6wjvrK9PV06EbxLSgE+kUjngWSNz/F6fA+F8vea0GbqZmleqHd1wKPxNOGr93rsLGy54ze95yUv0o2YDnz6OTab1wOYB1h+3bN56tfvB0eMI6BQ9dzPgoCLTRyfKHhdxX569/MvAdVtPFjo/jKXd4UBWGbyhLlbZ/81cvLsm/PjjUj+lQu4v+O2hL8c8JVQHVdIMOCX6qnDH+QayVkt314YgMxPbJZqMW8A4B9ifaCriX7dJ5ewXA3XL29ChTcGIm4kxI23LzbmZ0p9bx2mIkqN7uL0DY1g1Rbj62UlSQN3pGXHiYn1aXRvzvb27DdzfjrKQN/9NwMy340d2PumuMvVc7ToGO9NFi3B2R/EZZQ3N6nuesAGmTzwmrvn5PIx3426nVAuzeFmngO/NRCtWX+vdbmXl2zwMMDy5/ba2NvXaqFG/UrnwH4+Am6oHftuzmOX3ThA9DLceQzSZ/6qALx82+M8QPgEHGXmI0f+TAoEDn1Z+QYAYPNSQ5brIZu7VjEx2gPAXbPHZQ945yyJigGdASFjBKOp7Xz7LYUZAffnYQ1/PZ6YeOgxnNaDpvzB5jBZ1+0P+hrD/NRyOup89MMk+W9eYsFyzHkwA1B08eQqX9YL71ZUIojsGgZ8lpPF1/PUEafaAUMpGYEY1utnDUZQucY5sNN7bqrbGqH6Pabr+mvyBzN1CJ4GP00y90AWU5yYmc0Kt/vftWGvh6l1F0Nf1W6tR7YazGV5dVj3lye892J6oQPGkYz09PpKPYfB9q1Ju8Ie+9sfnHTzE591+eszXESRracFtRIQaCmyQq6Hb690U+PO9a+AVxsYqJ6CXmQz4Lh8Wzutjqy9nIPhZw55cTNeiTsH84ylGoY87BvV1Z2Tt/YRQ7K+28+nTvI/GWS/83Yc+j2XwQm9iPe8tKPtn9ftv7k27lqDYmpLZ08/nNFGOvpkK7lOeTHUwDNCsus5M2+uUtPTxYOjcb2PpmeYAM58u56HvB8WJFyUdrDY1Ai48derntBXb+OpZ70h/jhkYluN6hxOHlNVuzl57YQahcQSrPxq+Oi8mkiVP2glRMQ492NF6/H1/AQAfhoX9cljRjG+/imxeQ57PSl58UhyQJ/F9et5LGjj8PZJHPuYqWDVSuC1oSqcI0ezurPni23cDKLfETZCMGmuT9MnP3jfzGBOwKOZMPPAm6hR5+UzWevU8V0vqFrjuCgo3I4lHgam75BPCS+uYZ+G4YIMcTdrOrb67uItJ4CGnCbQXji6cE7POF8F76oXTwIYyX8euMqnx8M9GHqylktu3Il9muu2+mCEtHI6Z98Lgbgbl7n7nodTsFmq9u2E/oxK7DAVPy8aM75s1g3cT8bqFzPss54LMzEvEkRt92uW+MDRBzJ76WXxxvCgyG4Y7PaUeQU1LoYi9YAPEFCHYrbOdLXgPwjeexAcEhoQrYLztVjjrq+n/X3glLNxdw2AemTtEXvdQc9zLbCeAGRTl0cxLu1ZV9X/wKbrCBoJctp/BfnEhg0gsRa4G5kY3h9GKHrZvnqf4PhfvcHzQ0jOcrPhBo4cV6vr3HAQCDs3Vrzx008FJyp2cyROBR5qu73R2ZxeeO8cg1lZy53+5uaHD2C109dmeObjPZ577N2ec9lYOBItBywZ26Nplpmz86v1X7zOH4c3ihc5P0jcVL89Iy83zMynwxvo7cPbczWd7HcOiGHYn/DezRo8dLo1ctP9cvXmvPoWbm5y3P565Dk5TeQhLMk8L0omZjf1mZs3GPLnm19Rf4b8fDLPP/oWddHEP05pfwbCznBernuquvm4/fvp5KbOCGuPNlt9tUnIKQjf++ZY9VFMczWvDUCbnVudcKG9yjJfzcwane3J9glx8I+swc8bSeaJTt9gyK++117g4M2Qcw+vthxco8lXQdywX85Lxr7AWnLkC80TuMnAe/w+1yVOAknIzDB5OWrosXyHX8AnpnnavdbbuNEtDf29dLeKweBXRGmPfHi3F0NPiYPsMmT9jDgG5ZxxjagJP3bHQ2CC9qRc1grvdF2GUvaa8J0n05RQ/lES5jKHZG7KGB8Nyd+o9muCnscYefHz3FAJrwI98kue2ioT7nKS8eVnI4eEp6sIjzpJ1nhsfHNsH9zMUs8AxfAcx+pzHtRyNTy6TFEtjbhExpZlJuv+a7/Ua+xwcnOtwz1t0/Jo19mgyzEKgizlexae/sK9WPxNcpHzsZ0onx971gT1fJT5B6deLKip5sPqenKV+K4f8NdXw6xXa7bjCcHVeB449f++8TQkqMm4PMUbxHI9aIanlca2B48mwEoO4Xp3PlOotzoFLn/zVnWPEEERgFQ/82j/8gNaYM9B4zGZv9vn9Jkv1Kfku4LIfrRjqx1E0fjIoYbw0mNzyzdG65wvcc9zyXQwgVRyk9WTuNp3zQhobnLCYz3EAHxICC94IXHhzHg4X/g8hvzoDxwPfkzWkjVbczbaHi7nxeAHZk/InXH8j57Y9EOz2lvTqw+E+NXZjK8f/A168p7z9BrHbHIM+kbgzxdPmgjGoY7xaHp51PYJXpR5zIXS+L/2Uh5fg/XrSMoE2IMZnzWK8EUPn2+p9HEaFNPsZuxBXBucmHwZczhCLJDQomiv5iCxtJBGgXFPTNaMb8OPQ8d8jSfxMcVhPKhxsHzyvpyNqAcF1XPWhITn2T36i5MZZ76R6sVAlunG1ezjB5c/PpDOY1yAl2VBhwOGaZFZE7+bIKLiVHdyntJRGHWH1kZACE+UCwnKAXf+8PdUMw038KcPrbMA8h8fdob1Z9nd9rHrly6HYRcgx+GrNRiwD8+dG/iIQiujRy9crPahs+4hDJnBPhEm0eKviGHuurxz+WoxcKhOz/k8vYFcvrueqrn49kcVj4TKaZR8C2D97bH1VfKr4cHGJAWHZGb6yH10xvzcjGR9tbFsUGaTvom+msQ9h54tXrz+k7/cvMpbXUH8t2HcmCPmbga5+UJfeYd709UQ/HM+iQ7efvLu7q6f5/zEk89N/Qe3eIPJxwg3slzK9IFGjL/9x47K5ACnu9fY04/YDBXVtfjr91QecbUsCRnfJfR5oQwhuTpfT+WUi8d2gw5L/mrY0T52bUi87w0eSt4cMI3NfoivoaE5onnlf2xZRgdZvPHz7pf1zsduBgnAZp7Nxlmj3vrPhyk+eLkeuBn83qTD86/85Wz/m7icuH/mxPFsdAOtz7d1h4mgXlqFrT4k+H24kRDvvyx++8zq500Ke9uacIPt4wTFjM5U4N9sJ0FqOzu9cisufcnGaqcJBs81dQEc7fWVfP4v65mvTmJuYDPBh0/fzNDBL3U31oYVI2HmJUhTiR4b9gz6Q/NO18pJSPHU9N6stkY50BcMOh/Oab69sSYprks4OInNKwu947qbbmx8/z6iSXsO3oi6wxZD5Rr1PWBWhy/CskYv55+Yfhnacj48MWTnMKaox4YDv2nhNFEt5sPQ5ENOB/bAXs7aJVAEbQCz7E8S7IaSeqMY+kKqXMDyfs/JrZuveCmPP2GfFNMV4zTIDDn4fF/YoxGc7vizvrqqqD2864FERUvohtwoODzzombP1CCn4ol5R3O2joJ2TU7swu3r9cNoyZqNPbjWdSknODxXLyHyyc0KTGb21r+tXFnfdQcO2w7oeIbh9KDjejG0RtC2OotbH7d4gufwU0rByDremwtEFpUbS5zB4Mn6KsHTMyJIgGkW8Z5bCIu5nOJ8oJrsyaU/12pTvv3HYGapXr3Y5PrWxDrG03o5MbaGV/lpfF5TgKGucdgH11ovG+Trn4vZNRNdX+L6moPYfDO1ChbvGEU/QUY1WMGi1bx8BNXDvHMUH2PT1q+R1cXcij2ZqJP+MIxQc/ZXc4znx9Z18s7fbhme+MTtmsZS1q5uffm6D48LlHTIsfX1/j1/h+nc+rOefqzHD+E9BtRonlNRbeR8OIi1gsNQOIwbT73gOpy1PyAX1EBocRxL9FaZfeI83wfENBp/prJeXc+brwHYC2LJm/F3468Bn+br/XFYUooM/sRcfvexu7eo4qG4pHcibJoYnZ9ir4hrQfdw3pB/ebD1AnBlA6og9vFbZ4LMiWr7+eo3iHB70Lyt7c26EECt+5N/BcdePEe+nwsp6x9DslhG3759EBHYU4Okgti/GprpaIgkwrq/xjqWp47rCS4I7yKQvId3OX2HU9WafWmYp8w8x3/Xx/Xg0Sd+eT+18eLCoS09Tg96zSygzvZ1pnZp/eGk7pycHY86Y6+ut5ev5td3tfAJC8Vc/Gl/rquw+ikM/Mt7eg/T4EQqa9bTyLzxPB4qLdZn8cQelvkivdEEeyJvFrNrITb1SUAkBjdd33Lz5N3uFya3T4klDZp783319a7J31jAx7/SzQ1QCHkCtfrYq7Xz9YvZX4PfvdnTaxKZL+dnoQiDpk9u/QSSf2/sP/Pinn+hHH7S/vEHxtxACSaqmsl1/YD+Gc8G8jaIo7rdAqhdK7DzPyTN4RYnn/qIeQHcpHKzSo189V64ybH5J/mRzbBHmek3eH4wusYZE/qsBz83WtIChLyY556XvRx1Zecgp9cgeeGL9d4wMH+4CZUyaz715cby+tTliNlkPD0OlnXfsKldH/CMnvJu+uZA/+V3NTVrgTkep0ERNAo1txPRmXyMq+eJEdzrt5HRxTUKfjFgXX64SfLodQ1733jyGpz/8nz/i8qzUQuDLvpGFRveJZm9ednX1hqopXHn746wrKZ5FGnJvA8oOKD5I+u5id149QUxuzYgleL8vJAwjhrKWR3NgathOSbWKybLL5WypeaayBt2AA+Tek6PaTgoq9fk2YixpvcHfnkGaK8Rz/j3sRVVzGkafDmdaqJWtGXX3Jq31+hrVfxvtavlztF8jxrt36tCgEnnegXQBLJdScuyCHf2cV3g+e7RYsz2s39oSpH6xMdhfasXZ6/DZAfwCMs6vfccaKuvORtz12s8cl+l7Ku1K45Sb2bPuD6fHnKTSh1PRIAYHl1UdrV0bRyEGaeJfD+0uwfRsUhA42b2y59Bc0A4+9uLJ8feJPF6PuGZoSxTjuquFhxeY+HUzs8NwW/Ec16jpVUiCrWM4ArNemIxu4QrzmGJAOp8+bJjzwDbn7WNe3TO3shiEfk8DCV4eZbAOqztERggcew/msw9WqcfvmqxxNmt4dbhO51LmAn+Er71GzVfnPOzOD6wzxv4GDPUunUN2ST3VXu5C+mjnLVc00iuw59GmP06TAmqj0RnN2miw/HWYgLjq0XQj1jKUzvJt3pzoyfWkC6tBPK7WsQ0iFlPW8d6NiyTfOsfmOY+AJbanD9c16frs7kgK+PmTHCrN4jpEtLD6jBQLAx3fX7rAv7WPDxgrNli+fZNvdqLZX9DnunC9tQSm28cRGf5JABhDaQyljqurswVsD7tkxSs7/+DDuEVfySPoAl7khbQpoUluIqp0DesIkyfWGawNu3haszl/s0D853A5+SURjbPxLdRywJW1UpI5sxavHeo/scWJnI011XzJlFTxcco61uD9tp6rKzrzQ/bUT5cxfYYYzT/23F4ZvpovR9k7Op/TuwuBqy7Uq/7xD61Pn0jL9iX0xdn5HpNrm5Pt2547tiW5uFnX/zOoQHp8nh3hlqTvp2Dyzt96GWoLz7TYGLBiG0daEJf4NZp7GKANuz1vVqO/8p4rwfinrG89tC8pJ+QTRMae8/DXe/YuXl1H0K1ha99T7BfJSEN3zfMsX7UNiEH2Gx3puPtb5zkyR/rJWG+/HvCuKByEMiGa4y68CWKtdcWNzrlACYy/w83eG84wdLr3DCSh79hyw0EoWhpvVMlT3NbG5hcq2rMrE5jTwsz/VNUuNtHb3zzr1cz84EvPVeDWqo/NM84HWGxgMvTatB5q87ijD5P5tMBdnUI8bDG4GsD5cR15/1g5ib++WkiKoc36y3B8k3uB5X9/Zq7OgDH5t9XDsh+H5uU9BdHjkCPHFuGnwzzCSduuJdLWNbPDZo+YV5DxubFqecgOHXG6BsS2TPz36v9uFnnfwTICeP/dOc5zk/uwAAAIABJREFUily+8ZP5xvHI/7HfnnxVcRHVbanztIZ0ooX/xGNMLX6nSHvIPuN6eDWxBw6GmV6UO3gdhskVTynN2Zir5eJBk4lT3xvy6zc1VYNviOT/kmff+DDzThkW07IuFlv1sOrAi7QcH8NFPNjVO2BxF3LUJWmmsw1zfG9gVuG8N3p4KgZzOK85OGIwNfMFt6j6XmugRIMLcrGA0uV3q1+YdlbfuCJrKxtrrOk7YPoabmwcGcazpB4ttQKkf54T416/j3lZxvvELVa+U17nRVfvm4k8r5rDdobBcxht14nTi67junjTNjSFZUev0QnW/VV9oEDu9cR6cDWLBxYKFOI2elx3rRYQbwFOp8d5Oo7jL/zxm5pEzRCuJ1tzZ996zRb8ddOQGE/fR+ti4OpT72KCbabGkmnSmwtzMK01S563QFwOfWyvp8PKGhxfi7dmflY9+nWWO0uGL/RZPzTVV3cqvfMzlYXB05ieh27ha/441Vvc/YxqXaKeeuB7azkZn34H4LVgHcWam/wZTqtXA4R20t3JzKZa0GAN6YmD2MVr1/i5JuIrMkdwd17LOFMR0qRfPH9yjZSKOMOC5ZxhHVdWUtaCQ+xXhwbZsKIFghdBSB8ru65wgSHFtJgX84UpFAOjV3N73L2xH0xzJvxroxD3O1fumwL78fUaJEtxyxAp1HJjHNlqG3c5LCiO5muti9PUnhAnZ3DWHQO2anSRw0+tRMBnf9AMLDZwXz5MYu55eH0oP/BGNteXBb5jOp0ff13B1McM9f38dXPlh0cNpxferPvcYiQIElpTtUz3xaBTSPKlljuf+X/QX6CYFYj490RVLfHPyX2aVt4iJENejTaNDWxay/lt4oQdb9HTtI06ktz82sK1J0d8FHz5q5mdl50xNm/5neK+BtzpvrzEkUl7ln1CxVs7Ghhnx+pFoKNebcGrDf8FMdepzQsQv/lemKbZH+7EnSbaZ78SxyeQT6XHDZ8nvpz4cannMNNE+yvqxZR75mdqj0G356wWSa7l7MV3BR/i9u3IZWI2DnU/dK13z3ltfH9gJYoG8E3+XT8Pj9bPAV6gfGftZAwR7RNGMjIe+Pj9IUx92xd7+hpwMfIHxx4ct6h+Osh2dmuXKxw8gnM/5DBIYA74XrOxHw3Nh+jrZLU3seEttBQer9dqjDL28qBr3HfNvHt0T4c/2LrH3+s/DNSAWP+Lr3S093fLOQH3WA2ZdIRIzCIYhDDoRbDFMNfv39dlSa6MvknQGzpCvLGDG3cOfJIeie8THfwNNddzLmO2C+dP7NsDqbo3uCJf/+eagEd3Mdl28GkhnOzIv0XfzCDmg2cZjL2NvVETnclexC6MQondvjzxZd8byw8vuTNqgTfMCbenscqbmdj6NrtPnLkuvlztN6TlUvMyoImbWv7Vck3Tyv5+uP1n/kX3VsK54xPVCvRGdfmaqcfW967v8QBHb9Lr084bNdn6HS2vcmoE58H1pTI/rowv5m7K6b5vXoxOPQGCvV+j73nGtnPOD9m9gC5v87bfqGBvx7O6GSQjlojixyc5uBasE+OGuTnIc9b/fS4P/utDlg8dPNuTM3/UOTO4Nz64sxvUg9fPGtraqptYn8vIdXG/5+O3nhdGCOPt2bhq7uM9XEcNbWMwErUnguGvrkefeYMVvmzYfI9Ep4QvL9viON8X5/XvnvPG2WoNIOnk7Yi93JO0fTxoGDfxF3O4zldBd3d9kaMxlF1937gfls9GPRN7cVeLqrkAv2O1WWPO1ekVi3YvkiaQe6oOzzmBsfgtMj09gQLzt4ajvbjsL29ML3a54X4T3PKXVvgHZEloKz0lyYB/P4v0c4Iq7sDTXTU+J8BVYoRtlZrVdrpCEl/zsWR9O2SFhNwbPFezZb7+1p3jEzYNFzROrMf96DpMWSGdhuWZ1lNviuXmZ8EPzjirPzTpzyvHAPX23IMz07IeElzH9eHRSYCML8b6gc9UBBE1oI9ew8VA0ekzI8/Jw+B/1oH3HLW+xkrgoTVj7XmrtK6R6LnBrY6f+TU/h+pSWeKqLXh4ETjdwj91aPe8JP6jFR6+Ls4a2O7mH56nB4k/nd+6if/qOIXEOkjRtE9vvz0GowTmaaEM8h4O8+kAL3CJjMHGeWHOwAWe4XG1N+SDW0zPHeCLyvp6adCSjdkMcjYXeXqOyfby194jHrUeL+aMt8bqrbUVKP5Si83BfbHlK0fj6qbfVhJYf8Vd5AUv4ENc+QtCYPB3smftSR5PL7jPg+EvP6GRg8gl2fJ9ILSAk/BBEphxnpcFy4NzEYs6Dxv2mr7hC2okTUGD4zjGetp6MRRzzF5c1I4h35abhVhNQ2YyR4R4Yi+XeQNc/6RaCDKwd9vjYDguxPVzUWbndZRgz5O17MWwuQNY7PfTG/4u4H1KZg6edBUwwm1K91GUZfvSFuBfyujuBf/0ldSOt9diaJpftb/xh998J9H0idyT0Y93m5eTCJ58GL4rBZYarjl09cN3WPHBVXvmYN76Wo+kO5DhnuReHOVcrq7LPy5zf1hCYix50bR9eT+45WqvgAGs32vreGdjq4yHog7M30Hu6qPuanlawwKbSZMxW//+Kract/skgXNx/ye6+OCeHu5Z/mrrP1AYFNTyT5epPDx9gMsxHX9Ga77i/6N/lzef0/e/6MqNDA5JuVFqHS2oFK0BxJvDaz5hia69UjB0D/R5wiv/wzNN0oFfzjNLpabml0ojnOB7PcgXA30Bw/fvcWEWH05rjfHovX4SxP7Wjy7IyMW0Wu5c4GL0/HctMOfz34/rf7yKqggeY+91tNiJw+6f7cl1n7Cji7sifyuihK9+4z4qkop/O0M+fOPjBtab5e3j4Mvhmxbs88frEceVxjL3cX3eoz8NOl5qwteb9XhXo5ywq/2i1kM5+xseNMi+YgMLf2bPAWXDoTYWceVbG6v0hHX3LKZ/livjqetHfDZPZFnBO05z9r0iYgWy7PfYwGLI4pj82SZWOaut123xaOw4fe4SbHw2Nw+m4ZOe9tjne6ft8Ne+yuRxc4qLOA57iymZ7szQ++u5AurOMVH8nGPPgNNEWWfmOmD7+F3VQD7tcBN7cdnVh1dPcFsX2Di9zXGxzcdZKQPxZTCBccf6nE81Nsbr9glN1ict/mzY/+CkvleD6yDu+heNv4E/IvG9I8Trw9VQX9VfT03/BF2fqqi+yzSQvxX10a6Wl/mLJt7SkbLwq8PXB6jHkcdwM2Zq0i0uqlu5QC4nsQe/uZbGUc3la0xQ+XprZwP3ep7lDWMDhvd4iKsGroas0HGxn7lFwUR0R/lYV9s3ZyVUS3HjF/4rJzag68Hv+q7/jaK08lpFEumncRv1B40vWOCPftef69EYjMHyxJOYJ0+YWfOnCN3+mHavjjevJPCAnh7Wd25C43hj2WIcf/jswTR7bozBnyhpWb/44/yhwoLhNvv4CW42evK71+q9Hn7iYbk36ViDIxcQXxdnboPx+ZVFx9VCzOnvywKCMjK5Mi+rcIvVO/WrtaZAPvmDh69Vkjx7hO3xTMjVeuFmeXKQrx51yKQKjWdj06zhW43Wo50DeUE1ArQrsdOEm1w4eD0LRh1d437ixQRsk6ux+Zpcbn0XQr5YjZPIgznO2FDtjS+OfvdX3NkjMMMmZv4SzGUSmuanKiEvhmNsedL7nkAY1LRCKejx33pFQnz5yrZYBDGCa/Or5NFDZnyBwA0PTPvCSLTWLqbVzXto7u6fiyaxjY6W5QDRPHD2u1lr74mIxbqGddvamwFDfPyhN2CXaepPtnD48eujHvEaHy2FFHmqCgu3Qtvfb76jufPNvp/2tvcVQfCvoYbarlfHcXWgBL2NruY++NfT0YpQtt3IOcax/N+0JaRjZc1+TCu3u3uAEnravjTUKEcXr2vnurKqQSd5Qqp9GOzKCcddCxpA5Yv29EAshuxLQKjj4uzb/Gd7z9GDDsURY0uAfPMTf8s22d3TffX3/Ovw/I0g+lhd7iPm9Yt1TDw6+fa3Nbhp+OR/yoOcT5740AqCzM8L4uUwD33M9/Przk8xMLWY77l7buTH4TVqDTHkL6HnN6Ud3DD9K/943b/4i+m5WYOrNQSG4An99vfW/Xvw7/k8+MV8JfZKk928crMiRXK0N/RLdyncTADQyONT/ocXf76o4Z8piFCfT/ePn981+5R9oebouamOrl/iD3DaUMHfOXDO0tmDWWth+dV3uMxXr+eSfb7H4oqbWX6dHelcjs+/4h+g1wXoFPL0PmtvjnkzgNMGbqwQ4nNo7w1rDfSLgOCD4Rss8NvL9IbPl5g7UfhIy/WaxU92ePYdv3VnX+z2JkcA4YD5chM2HnPs6XWft/C5DjEzUG3RA//h0PfWgLJgSxaN1Pwyq0uq5b/aDCmPiQjJqDqOZXkWdbh9DuH68Rx2OptK2PMbA+ofJ3qCQUprrL3SUufxWMeyGbO+xOT1BYnr8S2vPyZmh799e4FErVx92U5H+H2OtKOae6jg08Xjw0bhRDRf5h7ziuu5xt3zezoC/4xTQ22l/fr12qhPSJZibBgxX45GY6HJaqaf+WNVrhMfWK8N8EFnen6WJa6v4SAZros+NwQuf0iaTZjG/ogpn5jLe/Ekzhe+X9EPSTthwFDVr0ziN9Sf9dVvTef82N+L7XUao4jxec6q6vSB1qtv61FYm/Z7DK0m66vNazR4c1Hz8KMo+12sGqcltuuPeaqi+AV7XodC2fVC7dOL7XDyrUHYe556DswR3+ErpWen+d8eu5rRN9/JPU34vvlqpqYXcT3BR5VkwfvkzmNLfRGoL+Fl+MVtLR9eUbCWy9l2DsOUmObLRlJmLB+F4nJg1r68O3dS0qv9ORwk6GZuDoMx1obejB5j/r2XyODhijxOIm/dOf5pOl6vmtWDTY2r4/JKjo9YxqOj50FTDl8uzhKWHl16nsEyYBJ/CJNNL4DkIF+vDcBBPzrJG4Z8eSYSq7LpuzWx0kIHxb4zbdT79KYscl5ugJeLJ2xSvKx4xwz5Nxmux7a61PNqB+K1nTig1HwUkN1amvjUMczhJ4jgcUCkV9fDmbgbvUF33yT3wBaQWLAmxcC6VXcjCD/ASzXjEp+jJ4+LIOIsAO4Wou3N8kR+G4+RPI0hx8ulJ7peXzU8uhFnRO1t1Jo4Owjw39H98ZZNDVZRPVXR2Kvj6pJrpE/bzJJs+bp/OKjMmKrzlFh/SOqPb1yHezhxsckow4CvYX68fKeKQNTpfMDFlURMQG9e1onvjTTLAZ26vnMUkHkMHqxE2Ri3XEwxbTd1hMYy/qst1viTP77Svxh8DPJLtpz2EJ58YzLPeMELm0PzHgDgTsL9jDWWoIz7h9DckLIp3LZxXT5awOTPnTu9Jl9IlVnbIiN5wk45+4+IH1xnX4i+8fdFaVi3v75enm9/Tw3guwG6dnGD1TQ7pkFoxF9MFp6b1gkvN7/+CYCbNfpmXcYVT86vBt8Vjq2RLrpTP3eOjOZmpQZvXNjlcZXv/t1stz1E8l23703/mpap+gs1zR2ch4N3lJjf84mWc2IFZWDq2qfyszY8CN5IyPBT3/w3ZL3R+dObzD+vN4nh3HFTRi/kzOR5oM/580f+Kztis31uHsHVFmPw10eu0T4emGNnX1bZsXFvgvXOmbUAekY8Ymoo/ADU1W+uHc7L3/rPyqlVrofn58K4mB4mxDAynQZrqvWxXz7mn9jFTo/+xbJGty+i9M+hsWuyy71rnp5zc67tyWV7DSjndZpg+ltC9N+axKBu3Pq1NPbp1eoHJ89mWHxjw8CycH1fbeTnDQfzotecrRvfMxbfFzQ4LgbEAcnNm1/Hkpk43VnMrnG9ubxAWjt8jS8ezu2/XA+Kaov45k2BvYmknqz5cz18ag/HcTMzSCEuC/jOrxNfCjIfc3iP03zZfXku9lCn87Scv1lBKfV5/iGnMQGal5rQ1QNuNbhwA66a1ZYNnBjZb/NoNES7KHnFCTTpVlkzji/LD92hhTyHj1air0/M1GRdP9nFnG5EtpZGw9sawlC5n30NcLI6ju6xNOecUPmYblR8OdFdv3bfJFy9qlUPPB2nyrjgWg+ay3T+wTe1C/350quifDnyxQUXJY8Wt2HOfLwQvX4AH8PU9Rolpu57Pifw2N8eBZMEvi5hCd2nnjIkEBGM+KB9t6l98biLWmIMjIvpbphsEkeu0yQvqQjJ4ewNo8Mv7/m0hoPh9cHcndyPXXKk7FzB7zoI+768BJx9+uTgkHEx5OXr9idtUtSgDhqFcfnpcwfeVsFK7eBqFoK3VWeFJrnG5xoYAaV34bpJwBPXWLwjj/1ujKE57WUC98hVIRoKCy86bje5nEfsp9c8msCO7KbFF/vm+RnTx4a8xF1M5huPhhjMwRH3avZn9nQS8/SXjYO+LDbn/+GAxjTRPr72B3BRJrp15j52ri/jPB36qfbnePbLdwq0IyBfl6KFEQ+4u9ZTTtj7d9CzQOIVWzICTtzNsSXJkTCzB9m1y7LvjX5Lb2fkw0mE9iJ3jBXlvqAv4NV0WqaRCHTAAgj+52Tg7CAPw3xwn46Lxbd39Ir6nFwjIe+4B8PTE/PGd7yZ3xN6QfgX/5iqmxfe7V0yD/P0cNibxJHHQTylrF/YXheexyDuEwe0oxjPYwzO8pW7CUZ73DefWIk4A3Tk4nY9iM2BmVROwdir7l8HDNVgjx93A0/j9Uq35zHk14PMpsSpubn8wbj8j5houDzGsFd/Zh+5h3wCT9Hm4j3vsVRCmCCbjicyC7gZfbGQtUk1PT6v3Y+9D+rGcWyXXTSwRW7dHI0pRjxaVuskFL885aRv1MNopuuzp2oceO/cyRls//u0xATIHy9+//u13IATXAJCpZY3fPfJ+e0LeI/mSfijo+H2+a8apz28yO/fVc+Cv/+c8Uf+n+meoGyom28mtG2Qx5o+tcLVOgnZ+QYf+w0ZOOzxcJxvXG+qxfHclJu7q8mc2T+fUqsH8tYDh3y5HrnJ6t8XJzM8aOOGvBjWd+OI30944ysbGOIqvdpaBEfaxnBaD2u5Y3kExu+1DDic0F4c6/smIXl8c4eYB9+gVzcRGfJ2xlcmjuBXY6zw9cU15utTcYT5RgdRu4lOiDewckpVPgWxjC7fxKEKC6kxR0jNIceHT5cagaBNaNsTQmKvXjiP695wWiJo/s2oDulz8BqBQW3Nx5a8coN5WH5qAYIQ/RB20RkfA6Em2/VfK47Vvnhh5JJEFCv29oB1uLgOHwQLuetj3bQKe1I/+JhPliTDX85GkdNkHKfx+DW9+bN9uRONvtmQ9fi+ONfnKT6mJ9b1HQ52exnfHp2bGSu5m/QqYhvvfkvlzrXXqlqr+XiA9rHRhF7/vm5BHr1vUc1XzJDmudhAnz57RhRmibFnw/7pFbpbk+YwiYFEIBkOwTpDX6YsR23++o4eL+NQmRf3sD058AW615LXJ6Jbc5xLhO/G1es+Pf7fz3nOAhQC2sfL8Zyp8J/t+P+ilz7YpEYpSUNjr9SzH9/NLVICoeaJrtPgWXjLs2S2fD9R2VzdtWVvzLOrxhXx5p4hekXyDm0Wx2UOD3jLia6XtToXXf2/z6eBO4zfXXKio572v73ddffxgymy1+H1Rut+BquLn7XDMt/u6pG/RPpaS/NZpolaHw2zT/am3qtdmPyx60q25xpMVpJntM8313ia8D+6wLLvBVmuGPC/5wrEuC7B8niur5c/YsYLPn7zMdMlYpej2lXwaDfZgQKc99X05G7/ip++25Di8mZ9OuVaDWoJBhvpssw08lrViRtxd89mBOBn/NRxXATD19rZJQZNiSNaTUt3vQZzCtobuAlY7zL/zDwuovJ1571WTWQymTmh0kKWcqHx4vSlVl7uESYU53d4cSy4dBG3E/1FyrCC+wIpLM0uL5zkeDO12FcazqoYkBA5TpOx5sbe7G20SBPUumqOL25i5ZlNRA7Gu3lPhvVNxI9TAD4J9BOTjX+mhXrZm+skJZ/Q2cEwHt44fdFJVLDlL0Ychhnh4fs5Xn1idOTQ/Ie9PIVedHNdBLMeDqcPTrdh+Njo4cN5/szHfOD2EOkJ1vmQQJvR8885h6+1f3p3tQVpzhNhbA+vEuiSRK7iLeWX1icUScOi4zRnodQ7Dw9e/ZfzsQJ3kNo6p1FzDie5V8BIwPIDCpBADOWRg6XudhkXkTdXL4YG2ecArn/xPPGuOUDAuLm7as7a/mvjuijXIPKy5hrteWLX8wSfj3X8i1NPHMz2BbiRvTG/G01u0t9r483ZeIOU617y5sjx0V1U2NMLetxz0D3tIcc/88k0Oe1mbNdj5lurkICMIlm//osVQA+f7+ZEXkd0cNOd4TEH/+utALxZzb59iVpxxYLx5nI3gsfhDeluxLnpZv+3fFrOzKfmfP/973/rjWtywN0YutFcaKE0KsLWKpvX6zDLlS7Cyteb9uftg338C1fzyBEur4fo4Ffc+aYudP4t/xI5Pmq9upLwx1BVBUbre73xKbEx9Ic/zPm+XnQfXnDXH3JxQx/bfZOMHLdnxiAnc759o+OJ/Y/oPo74yfuL79vPp5jwMOBzAGK9vTHnA3DAw2H7CwhjBvZ8E/KFn+/OQ50BCZQsS/YvBz62GO8aGH3COe8638PtMxMn3wfk42Qp3iBWzSI3v0FDTEzs62GuBmx6gnGdWZ/2z2GBcKmDKGlbE+tnZMO2fH/NCw46Ik8PNvrzxNk7vOhhXIJPzAWfKyi8D8eiLgL4ac8yuCAXu+qNx/ZQU8uK43oc/LVB5HgiyknM4pappMeHe2zlPJWt4VFwCYNthhi4jnYt4eZb3yTAxJ/yd12JsT2aArbfPd/4wUNB6yVlrWVajY2TOd9igwEL733jOE3ffsslefGEHg8RKsWf4GJZwqShMzGO5rteYLI2dIWDc+XIGrs6Yqq1rI/OYQ5XrArUgYIqGufVThzasheRPWPsrvUJaX3F10Uo3+r9aMB7HNaUPczAm8FOualt1unRixb5qR1oMQ+f+UoqLGAR1ytrLIexcoAHXX32qQKSYPwqH4bXXc/YOVge6lsVT4ToHOQlrsKrXb3juFxques8jOwvZTAqsoQz0ocNsM/mjBgIOK2jWz65dZPnztBI4Lux3NfrRxOViiv2iYACPnzjac+Pu3768q0RDCpAtVr2aB6zfDGIY4b+yZrd8dd2ce5Ws7wxPI8nWXq48zSW5g7/o2f5X43EDX1BWD65yO0em1+trKRX5cvz9OSY6RHuqXD5+xDeYnDcqoLoT/6RuF0AFDNxnBjXwXcmcCcgy6OBYFSP/zmpOOKvuMbAoHkM9dZyWMq+k3OZzBMY/5hPJQZDbp74zJE0y3Qn4MxrqXVU71tHowhEA1QUdzXNpuZpwgSEQ8bTLzY1We7l9J0eXtiF05jEn68hkrUnWSLj0a2mp5rEr2YClUbCsAVX3TgYRwRffXAagvtiDV/CTJo9NM6Kj4qeqAd6Ag3e/O5gmWzrpdbruXymJwnV1JeNnOxr714ufJ96Cmn3Dy//6px8Cug7kQRIu1wCot13WYdG8DXddK21WRQQimGtarXzthtLvLhd1+ZSA1V3cIPTd+peW98tncTl8IxfELSSjx6qy5VZzszqw874+L0uai3BYcJ/51PMxy7F7aFb/vuETNdpQidrjPfOOy8csz4X8+lg5puQp+XE/jBkjyk3R8UCYNBn4rvWpLWrh8/EsWXWxpsB/npur7kKu5ie6+7M4JI35C+rJOqLa0b6rQzRO/8vCUqDLdi1FmyIyhxh+Vw8EP5v9KhD6NWbf/iudcaeXv6TffyXj/MB892AIup+YC2lvJNmZtYy3DnS2f7Aa58EXZYaP7tGAMy3H/zZE/7awlCb7oa65y7v/+JXWM+d+m1NPxbrnnXGCmDyjQvUZ8N338ig9jj5wp4Q0j4Yfh6AWEwm1zE+PXKtIyu1vZjHBx5MhjftW7O/M0GdHdT3rGaDWmXiUcpeW+L8uXDx4hp2uCTnq8VRIftsn15T47kJdVOcfdcwwPKgW9gFKo/N80NVPzmojcuU1BiZjvLZa7vHAeDJYCa+UTNWm0VR77bycvCJEYaM1arvy0Nc9o0t/1/yXNbKidTTZZLlqa36zDKlXd9517gwZLWvrDLUgZNzyn7ULHn+06g3FtzkbP87d+85gYth+kvoZtdLXbRIbeGWf9Djvt6UilzlLf3nfJxn/bT1QkNIDqVAzihPe1WLeXTV6s+wREnn4y9R2fhUt5qPrZU0h7kirizUNH6m2O857/Rc7boHJbb+9uZ9XEHW8/Btby+zxJAXjfwBEHh1TNtsS5Op+p5cOMQ0/+HKWV9zZf0tzJzYLgLG5jw94NWnqNbxqmtg61a9ustyPqS9NYHi6+G/1JfXPDWClTtU5ay9zGdrp15/ewPSXMzJ//SiFB7hadwx1sl5u4TlGBIw/aOeX+MYyKWXvu36Myb4i5LtN1fwX44n5tHe6LcOCT6sWYbgWOot4/EKeHQH8Tpc9jwtJj2gTHZ9Xfji77r2/FCnnO271cegjV5lhSb3BZbz0RHM9VP84/jLYsq08xug63T2IYbGLC/q3dfW9BOhCoIWOw30l3Go+unFonELGYLpYq4OTdcXVBAQYL7Kf77mqrd9ClBMte+6/eaeHxxD3PUtuOOvL36e/3+9zkJHawAVDPwRoYJvLdgezfj/k19xn6jMX5I7yY8WiPNde1dnISmeHxdcAlv0z3aA6ZP60o2qqMO+/AhWGnz74Udhj43FwYWyialTm59NH2i2RJ3dT0O4L3ODc1T//NRmEojz5auXYjDYE+o6TGKxU2tPoGFQ5oUPvs8IXzEssLeP6rOIF+8Lp0IkPG7TAgNvEtbltd+wYo8NfobazOX2c6DWdzw65I/dHLCU54OsxTRluL7cBfti8U/HVj9yxvaj9GhvelDr8iicqM1RFjUHZ36roae0Fj+jAAAgAElEQVQHySLw+jJf6HDNU+OFPHXETPbX21X5ws82iYjjzSRuDRlT7OrOmTwCpwVZL11o6hyknGPLBWgufM8wd3eEwvWcYzX3GraT+gEEz3o6PfMJ5Ob4RvVGbUy5VRwSL59SvprlilX8cveGAmE3mvO01drHiPWud54sdJA0Ga2DoCTxhZu+iveHMnH2q4zWsxthYv7MTXpvOsrl45fwjW8sJs4Neb1LsZkFXojXA5hPTtaNw9w+uQ+s9TKXF/+Dybn0E3TqzM04N+vgsrKX3fMWwzQQm8bfDeLxdH8KwYYPDurIQIvPPZSlIdj05SJ6080J/dO8YtASLL+NcP+aKHsvP4uC9+Ujh7VwYcAdJ7UwF8nMuKz47jvWrKmDNx9E3TpwzvPZrTU+Bq/JiIOT6VnHISIH8OomQOyuAwNis1gpXmXijq++HMmS43WVfb85al2iyyfaPi7J+nZ+OCHB7CFrYk4T9eDjucTcEs49IHbeyHMLKgvTbBYND7wbxcTCYqMxzScZrhjb03Ie9jjdD4dCvnz+NV/4F//kXr7bqwMSQ9FYTynJzbUQ255sfFgPA1JtCAeVyX7NrzHr4gDku8SLw9RYsG+db6/tKjUYCCoRy5eAWWGx+vqWh1SMb46zdNbpsvGKe1y3kCeH94V6PHkQVnmONrF7sKf54suNI/19XjxynquZiEqe8NVSe7Mcl0226mklN9QchIbzbO6Hm7sdi6NhPpcQ+ozBCfVcnkZ6/qvOizFEP0FYc3j2rGO6vUsMLjqHlz93XtsXibT5M2b5ee4zR/Zd0rud+7KZr7b1dbrVDwYu8hm3+TDzk12UMqihfX21/TW/NRA1fqmWgzWMzdzd9ZPdpbE+3dU1pGKIfUcVkqr9wcMGrcdX3cqJ1+siG3jMR0gGj2n29mPxOu5gkl45okxT7tZqynIs2fXizbM+J9Y8x81szAf5aEAp49SxkuBjwVb/KWxM63T95Awi3M85nFZ6Zkr2pLz7HLFLr6NKqgLgalkY+b89vDzVBb5+6kXxPU5H3WmaHi6STDPL3+PFtQf6P/jr3KthDJUfHdPUBjy9QTuD+DaF+dM7iUeCZzmhoZCeY9hjeLBVwb69GScBYDK8/s1NrsfcXpGOWF4sdZntAmvqMSasV8PrgvBqOGjBjx5zvpx53UVWjpy0gp1jrq1Eh7uTqnh5clgzR6WI54Fux14I2GYc749NbeYlDmz85gRnPua2haLE6ruGjnCPepAtnuDW+DZOr0nrvdimupS1fn0VUn8v9qfBsnEY/tm/i2b93/ytQ4bU54VnqJW2keupKlzjy6BZDIupLns4/A9JwQxGO5/WvqqiMifxKKmnv8FA1M/+sCfu+LjK7wFjX6aRRE+fsu4bNXTjgo8nFhITx3kMu8f1w2RxF7Jusn8uOgg3LCB5DYptHM/fCTfNx2/YV1NraTi4t/bqWx4m6vMFEGpvNIZA9KkZ1xcitAaPHFpc02ZtG8RxEPBM8PY6QV1DgTw1a8VOsQtz/lk3rNaQE+0LY+Ccg42yvzb3j3sLpnzbhyyMz54f4vY8Go6TeVGxwXuZho/XM49uuVbDl2M54AfFJ61eY73HK2Ec/Ry9GPpCZvLZE1DdFP8cT+t1cnor50G5QFM0oJPxrVEDOZODb254z98bD/5xuHyann84jptQNPknM/+wHjfryKPA3znkefrR3K0vDbiYLKwA3Y7s9kPmTOqKMVTN06lodOS6Vpe5MC8XmhQnVKs1dIvkyng0Sq+3DD0PXG9097i8Xrhm1jM/Qd+adGeH6NbY0X/7J0nssPslyCC2GXfe3Bjb/pUHK3xVXQ6JCrc+MawoNgc0dHTt9RgOeeWadz3RPzXS7PHsOtDqqVojT46Jwnt5x+32A08BlxDKZHpjnlrGJTIHNBmHbgmhmE02WMDlwCK4Z48drL5PfADNnYvvqzUk9Jh/vLG9biiY1p79bixD7SAXbOp07TaHy4tRFSyy7No3+LY3l+9MiRDDyjoUL/Ccm1cn3I/ucyWShljnbGN7onBbu4snZ9GxZbQ2cB+rudiDwcH3aspKMLkzPlW7b2/TY3Y5/NiLaJzLz+F4Hu1hfrNCJWMlfePWl5qIeaNeznh/pT1dxI25FBp6rr9cxZS7MVnbf2wgk2098Xkz63avMa697tYbDP6cYpHv/ND1XGVpBHWRyCO+wk6TcwEND4db6IASb9Cu653gHy9bHj2woYHgkl4tzjF988rtU/76hJ/w5TU/TOSUk96U486J6czWfMTcOTlMc+LZAGqe1nqP0y/uzdmY7lmjLshxKC2Pc/2F6ndpjq/+AsZgr+wBvZJvPPS83tX+1gTD6aQ+18GXs1406lvfLl+9xSawpRgJaQx73Qruh3/XlFrFxQ9phvl30k7L9eJHXy2RpAn1JLYK11r1WO/TE0zT6WTO6zW1d1hfdL1xsXz1sVkvJBynPQqLHbHnDVuHaifFfF1e/tmPN5w+Jm4PeJpYIrb6aofz2U+rOHrj8JGU1faUsN154Ki1KFK3q5tftzDiRU6XfKPf2RBRex23bmzc1idMPRC3j9e1/D/ob7MLtNgtJYIkwwY8Yn5eEPcAlFYtnxOe/Qk6HHxds4AbS0cFRmiMZDE9AEic6gP98E0jNqiIk4cHCV/yX9FuRtcc54GPvN9xfNgO1yxF1f/m/Maqd5zifAEv0RN8/Myu14/Top7VrmhqVeNqJI5AR9kwHKzzA7Afn4D294kOrl+xp1p4SGp4VvswA8OHMdHtuDRoNQYNbsYT8yt0nEZM02u6c7DoX6BlDvelQkxTXQSY5U9O/tTTnt2THcSNG6c8vQa0Z4/nzdMdxxNd5lquPPWzgcT8BrwFxm5EfFYhbHor9In1OqjI1VCuXtrh6cVtjwVAfBxL+0yP3YQvTql1qguC0z1fdT4E6rud10lDmjx6PfcD3HVAP/wUNJw9JwHwBd5Fb7DRa93R4Kef9KnCoHi0uU4cv4aMw5gnVtP6Eh85F1s9USAnxmBVZDBKPD9PbrjB8o0z3+jvZucNhph43NTOGtv5++DRy4tA8Nz0cuORf8vuz/z5419/yxsJmWNgFoVoeUlczjj0aTjbZvPteQ//aWDtgO4ktiG1YzRPpmHuV6rffoHZmbOhFwrhaUO1Gztk1eMtz2mv8bBEvecxb0nkjYrD99fMuTaConc71zcj/LC1Nb826nrwsSP1+k8cavkKpicwa0NUNh8u9gSD68RsWLbadbBqbK8RMC+X0Bx8jnjM3+ukCM8jy+TtdegmB/Lf1Ucv3JLErOdBiuvLTXjGTy7Zqnq4tStIiDuZg2B7wNzCcS/pqwPbDeobhzGJ31+QeDjw059yEVCXvO62v/Vu1Ev7VNs0V6t548v+6YoJwMfpVw7mhtgAMwhj1QT/xieD2HIvevw4YLthxumybTxXie18aU4BnK0qDOLCd/Ex9DqNLwHPQ3A48WKL6zVEngFuyv7yWAPJeS6Ck3VwQLfMalLOTg0aEzPOl69x+iGb/9jMN+PVSU0yBvv4F7tMPk+2D9Vu+vB45Ygl0ZJN1KWW001WSDrRROx6wnEagJLr6d+Y8euTq7X3fGjQC3V1ZqullbMulkW+grvHONH3YcXh9J2G4QmkZ32TNkjrwOmX+1Nyrbh+moPi/80A03NxvQ2afnBBsCSG2Id8JNqIrIOjKTxk02b86KORAvGHE9rg1n17ZI0CyVx2/N9zcv2hj4zmlmxpe/7wwcIgpgtsx13bwx3tnovMD97g49k5kAiWxI92MBLJX2/0uzeg1QR/+bBWX/WUg/iNxEr/GFrHcRsFP7rX99N9vSlZkKcDbOhhVhtxlrHzMBz+wzELwhJ/knXOOTwtQp5DI89nxpI8uSQvLFHw+fWj/8aTDy2n89F3vWP+npeJCN5egCeWkXXZGsv691CrORvTPqAv6PEQpxfTb4JkePyHy3w2Zoc5spoBHnPHcPXcby424CgS2Hcc0fTQSaQYDpwY5/g/kDYCw7dhAuUisRyG5eCb6cW2fr2PwAq9JrTwiUVcFR+XWZFDgQwdYtzmIB9xBbS+reEDfOfyMY+hF8hymiFgRy8E/OaG4HJkCQ9IHwwNaNQlyu7FNH//K6ioHScBYtAovxTVr4/c4JunBZKVqI5ntbzHZw54M+Z6eK+XMhVSXHjxNUOO0ySnSgKrs7rljr7l0fkkY9dzZoh2Vnwzyno6f8/FXKU79+G4J5++kAlXchMbEdN7+stvGtws8tXzxaJK7lNlr53SJXUWAd/jhB3D+WoFmz/y6itKLeyzRVY5sgCrTnrM4Nh+z1DrnoEbockDeZ7/fzqWy91qt4f/Brnz5yzEm/GL+WBdrpfqq/iY+/em24+w8ByRX9umQJ5P/sanxPwL6xN89fPpaJPHwZd8nVlzU8HNIrrIkdsMJXhoCODGxbjw9TUAGswn03kxBp99aIFBWwFRjc/WXISZgLlxbKG6QR7G6IdH0BzxWYuCErj56qMc2vOf+b/P7YGt4lN0SPtJOvyE+dcOpIB7XDhn89q59ZTgZtC3uLLIsYvMgDG1tzXHkNPzcCUEO/v7hgarv7ruC3XOi1TWSm1o5b/T47He+uPnHJvEQwx+po3DeGa+OdfekIfTNX6+d8Pu+jDzJVAMyuBAzzMOMyPXofVlD/8NdWZTvdi9SmAOvih8rusm7eN7kopJADH632vnlP24ngDm6/KbidgMnmdMNX8fA3FQE5gnfzZ8WQ8R9aWTfR5wD9mr/+qyF2+Aq7fGJmn91NFr8rS2j2FaSoPN9azeBSDoEA0+a6eZWT/jNuK51gL3tzuy5kaygkZF/p5Tzu1pM1d4vG5CDJW0x71kZ1+qh/Pe+ARWzOpMbrHGV9uoEhvMx68W9uhdApYOtG2p7TbMwxi/PVldBvzUG6jr3WS6Fpd+fJ7romqkcMS3BFhJRn5zuS3mrboYjpeXeoov73Ge/7jEEUh+vpLn6iDpowsBz4Az318TFi+yU07sO5qndWEndCxbgR2hP7yPb27y5/tnXDkuTq0h7fktl3VbB/w462f3e7RWrORCHfDOlwPb1fKIqTHgXeOJefpvTwwC5bBP1jKNpkgmasx4+JMA13VUJ4fhwbklB5Kp0/UbgX7+nOVZE0t4Qp+fAbFhPg79xI7XfPPLg3006CCHbxiwySgPqyViYh2N1kWyDbnRcobVJPbiDp64ms5wQcyrFRccEuZgLjb0VGNWrIEsZr2rF2j5xZ9xvLc9TNAPj7wP1yETON1nIWaV/PCZgtzhUBvPp2iV00Q9BPPY4u+AvWvPWxguS/O2ZhByrvbzNW37URvSLqb5/LlG3OwwIY0OnI0tOV596zGwDTHH8ant4uByDb4JGvkamy++n89bKAl7vqonAcG43ixf+B1n626mtxYMQ2amF9RSK/X9nR3F1MS6hiavx0YcYLNkeaKB7I6mIsQMHuqlUdgRez9MEiW7h2J9UyAwBvm/s+sc3pMSf/hMB39XiRsmImBo2uRVQ3bMvrCMM+s9V0Jf/F7AKSvRbZruArKsr3ngNZNG6iQHeAzxxP8dj6axlP/t4ItNPFSLvzhncxbZExqr6cj36gJxdcvjSdBYnVk+5xawwiF6B/7TQBJrjRuqPmHW8uOFCeH2YXrY5lstXT2Zaqv/Ygj/d0PsV49l/zpH8r91k+jV/OqnUWi683XXD/aEWFttbPgC3Q4J2F4jh9XLknNww/PBBh2lcF14jFn0HOzaMZCe4yKAwBFcvJhqoifyCgVYELHVfDbqjS9fxHTcvC2I+RsLNiHcMFZEZvjHgzkDCxq8MZMbS/arzU9Gc7Pgi0a5CNin4yKLJTmRHoM7DUC4mXIfQPXXa4+abkydND12g35U4LUElILnsVb3Z0HDxtpIPq4Qss/kDeWVfT6izAE+TnjkOn4Dlj42by7SxD/yL57/85/5FD03pPer8O0jfPRhN+6PMDi2YTpRCuCAqfmJx+346lo8+RjWlp9Kk9h9Aj8p17YjTAQcfGV26bzaMZBYiCd2eYonwDgg3ojzCXpsWfsbFwn0/MfG3uspMd5gGyudHK4Qjj1/rD3rG6ze539hxnlNvTDhz3aLYmBtTxNd2kz4zPU8yOdabnx82SeXOWRc34resQnKvrW//n35DLwISbsZr2+MTRM9UvedTDie/JCnHqYMIVszqfCMgnIdwSdB84oDEzsQl8dVBjKUmyTGtm75NcmYVQggZMSJ7j///Ifz3Zjzxk/dRPca6Btq5G+tfb4p0fUXDQj0uuIJjesLzSWTU0hXHvGesjt/H/cwSrX2lgtjK7PvC+AxzV8ToUf+dY4uWq8iuqRRl/d/y1nMiJPq6r6/6kR66BlO5Kyk15YVJnK1yp7bGXWSv/E5Rpd7lrDsUH/31Mv+6oaZL/fBv/22smmUAcZyDu95M2c1NuKzpsD5jc3WfLG94z1/2PQjfNrFPY2K94kt9/GUMbXtB228ocD66Rn7+LG+PMcwfJxosI+vy74YmEPrDo4kGT81Y6HH6Cun64Hb5+NACfDr3EeX3NFBvcCyXzrxl1ybNFMdPDa+MX/Ps1nioEfP+mWNI87lk3I8mUp2ezCJI8c5uov9y++2KO05fPuK58kz2DH3dUiMy2WqHAbLnNXFUPO0y0fe7K1xCe6cHQ+Zj0tNOz+QGjfgk2c8T4/mxwx3X1sXZMyDpwRyrXZ1Vvo3r/VO0KPr6oqhnCO1J+3dXcf6o+W0w/HtifmJgwu9YLM/PHXdtULPh4h/uZ0JWt4sLmfJ4suQl/l6Mq0j0g9ulZQPTdrCOUd7Vpwajof+8c14dLKxQudHRAIfja6JIbzxzZn9cY8l04vT97AkHDV8L2P8z7/ifidab0BNkzkJn+YaCMX5K6ixsy1pMZWpZg74Mh3nFYMmMZmNcyO0GSvmaXA1Qld97C/OS1U78btw5S9JltWRSQsGNLlDwDhPqwEC3nz4EJ2vb3slig8v3A9n0Tl+bACMZyKCgd4M7Pi7dL4XWjPbQ/sZsHnUVH7P15cjPuPAHLGsPfTT+saS215+/JcTkr6bFGdwN8jfGAD4ICnAc8zycbW/PukMc1SEdsyCVjU/dNn+5LV3MfGzs92rFngebEVhyWparw/Sfc9AEBPSeCISM0nVtyM4crMNgPlw71z7XfNA3/USlYHonldrAbmxPqjjnmXiQl8fQ9MfnJjxvVVN5J08hHqjnERw5A9f1mAxy3t6HjyYfE+DdbA1mB7175D2ZrOfkPqPnCWZ5ztx/PdY19fJXL93w7XUcL+62jNc9PXnC/AFtACAoDSaJ/t++lYObXGfdgmNxZaOzQeFVDBl7Yvfvfgwlr7lRb5u33RsFwI1X28sdXsjqT3btbmxvdcIfc9j+0ZebmL799GvFiKr582LrklvohzvnKPGTwHBnD0EzX834vUNoM4/wZAoEOvcG6pyjKtJq0fo6gdjDdH/xx8Bt5nNaY0598z8QQiHwLrHdt/1PXb6zJd+s6jV/c4BdCXdTG5zwoINOdhuj5Xkequ7yFhj15UeEntDvTj49XshemTKQWbc+UPvLT8IOPQRowYNOq4fvValy6PlfROjljKExAF2Vbg3f12DkBvtiSMU62LFSjdDvJUU43pBRPU0S+s4PnBA25ur52UjOkNDrUqotY4veFp+mJIQ3j/z2zb8xg1r/8vE3JyzNmfm5yQk2Pg7Keytpaw8X/zBf/339/+T55//k9PH+WvQwwUf3DbsFN/8iE+exhW7vHG/chrTzOlRnhOp4R95o4GZN9j+ln+aN4sGe9O+9bjRRPxlZ32Z7Dq9J6Gj2CtdIfIUI8+DHcuv+GMioWvzJ5I4p+YwnYnap3IDueux3QP39qlrI443HP4IabJPncsJgZp7/aHK8zU8efE7o8d9D0CwdDbg2YNQTQD22FpqOxFPXHx3HoYI5PoQXU+slHnzOcz8TDUluoMu2SPoqoEvBMMOpKaDSnI/ZqWkJgdxGXf+1SRF7b3uoV8EfTIXyM94+jcZny69N7DBQ7NCpHyKmkbc+WO2+C6HtRpbrY+ew07TaVvHyiPLgn/xZzsMK0ZwaArf09+J6L4+oWpnn10mYJfF8+W+q74ZY9QOU0i6/HnrIf1dF0BhZZQZnOdqyZ58q38vXCHJN97lZzVMQ2tvr4trlmNkl/Fri5zndQo6p8fe4DOIRSzxm8s1jtpbHxEjH0fBxbUfwVPHi8Q5mujPc929Ti8KF6vpWN5aXq3nr50Ut0L2W/DFidfOKhl+4wMkb/v7Xb+8hPjXFcVOn3SnmE3tRLWPmn4dqq/Hz3Xiz2fi0FcCMeTlZwNzzH+/EybrIdhQIIEAXbN5R3c5zsz0LVgkfEiIgr6TYIK6roGnrh0Jenjm/OH4XMQmG0fi+yTfopUBtCmHdPfzBIXxGVnKH647iVcDmO87T7e2FglOx3Bp6vmaAeZoG/fQsKot4OQ2+9h+4rmDki+BzK2EaDSTszdD7sH4ghr/+gEIHHmu1zW8dvwywrkAvdhv0dX1pflIOATcWT7RM4uL9XoC/HTUdtWvbtKdVrmbQx5ildMjmo9XllwIeJrzJ7bW8725ToP1X6Ac4dqDh5Q9f8zKw9TetCCUaFCy3vldVy+W+/TE+Ktz+HcavpQxc+5eLzK/o/2M9SsugHaWnrT/Nic8pYrNm4f6wfBFPxgX6waTQc/iSNqXue1B1rwQvk99vUEN5z95MZyZF8iO5ZER7uzV4JJ6s9t3kwWphkzaDfFJzPpxUz/nIUCOHNx94qjPcy52v8YO9jOUlt5wgwTn/Vr95fEmPTmeX4FPElN4MGPYqIHH7umqFg14yT9dAfocBv/1XxvnB0w4jscQYr/jtt9cCTi9QFFlPu7JPe9sF5jJvGwFMnfxcHivuIjhc0rlvJDskJ3zn86lduY/83/Qt77xGfTJTVCGb7Yk+D4NJ5bc8NwLC7LXtjnXGfv7LlM1tI7kRNAz0NAcX83F1Af0rmPDEi92blvkGrseYbTy2WVxvqh7GBsbJ4sN/dv3usTxAuARQ9i03PULSlsvDk/Zg1/esn34uC7yxxdI8HmeJQ80M3FMjCbI/uuPfVti++v0rw5CT580h/3Ys1QDRA92Eo0Zlp9t3MxyDXFj/uc//vyPf/zjf7TxV3f4WVwOGFmnsvHcr+E/15E35n//j//629/zHJR/cie/oQL4j71RaBz1wEu9+4QeZrhHa5ZagsmX5+as7Pfzf2F9/MYPJ8+J//jv//mP//7//ic359GSa/u/8kYB1z7+f+XT9b6+iK7YOpphG5hc6kXnj9Fr8jSBvRuML/Lxo9fKxvm9Hr68JKNBaGSJL+tTZp7VoE/PKU1E6S+SaOtlhuOQ7N8E7pZ3jkffNAzC7nldFptyLxwfWhXWbAKQNbv6wY8fFKpkOu2/649X3fGLliur4bBZTPZyPdwx6zni8hRfTQM4leXtNWgZk++vY7V+HNT4DN8Eql6zTvP5+9q8Z4MclHJt4HzbjwProq/JyeMwWOAMkbPbW9bohnByNmX/2msb53QTwoOo88P+JPMcmrPR+dHm7o7P82MM+iYS2Ok53cSQyD6Ylz0Soyl/er3g0PjEE/YO/BlMq8H9OBRhMYXgUwsdagmGckCvpjmkxIIxG/XwPCHomUxX3jrAMaiBJPAwWn980QPkegXu+u15C/Z6QBbY5BjvETZLe6VNv52bxCAKIsOYUPKO4z49BiymKCJPxSyIbcB0Hh/2Yqmt1zc+1R/oxaApPE9fwHES7M+JqG4YZDH3cozXnt0LN3DDNCvHcp4AK4I+uQ7TNwU04uj/niMRUdMieE32tDz2E/kr2fFl7omt/y6Qo0avjZN7BShtCXDTKGEnOhsNL+Yad2Z4qeGb70dzfGezF1iLbAaeAE76LHVjDd/r5eRFx6RMUA3YLliybPJ1WqwHAJTB2p/seXLzE66HBZ7iNK1HnYjsuJXY4Ln47ocUiPNHQPjjJ1fWvGC5TzhH9WjsHmUdXjhZYuk6HvjmtzbqGXcxZC6C48XdbGg4DvVyD/s6ID6qZWSKTQznojVhLQ+rG6fz1JaOTwT9YEozqliMa7ofhuhEw73YIzEmvqthSG3Xo49kgeCjJS/8PFfmKE/1V1fVkqv1kYLRrQXP0OkvAhCkOILQ0B4X3fpezWGHcm/mFB0T5vXU+K3PpjaE+UQCQYcrhCb/g+VGjDeP8gMkLze9Po1PCJ9cqZUf7L4ghifxH44yF4aZtpXLbLq5lg1jtxe0fuqcLSheEPOQ50ba4VQyr11RT+ftWYHQ9Y0x9lSQW4VwNR9aEHR1BGo5/cFefmJq3ISZYTFd3rFaKHBu516Z9uxiuY7wkd9eDT8izOXCzjWm0Ne7OOkg6RdRYtD8fOJLUdScHvsr74FUi5WN853KyZ6bi95U97kmmtE9aHHJ44tFivnFG93PdUKN/QK0tQHmkZIt11hmRtWtTwRvvBUCCoreLAiUrfI87q9czK2dHPlm3UrGW1KSXgtdvxhWJboXB56XpxvlQzM9urpLdjYKIFH2W/a3qNgUo98LAwtCdd2he3bKxp9c+eO/TxE7DvPH1msmqoOhXoKZLbEGLMZfGmFLagops+Ir15GfVEPFOM74rubyUF+ZmLg+uCHn2vvzH//w+7//+7+1ccOuvvjUi/6sn4GIcPR65c2fv/3H//1//t//+D//9ffcGP+Xe94o9DvXamtNdjik6RPj059WH9ISezz+JGLvyMKaslklT+T97wf/+J98gp48/8lvBJAr2v/44++x8UYWe+x5toEfgw/28lmP9nfvz31p7tyxyfcJyLK9YHGjnZZf4Hr/nN/LndCzbT4G59XL+nBP4tTVa77cd223nNiyePO/rODu+rKM5O2Mpq0v+bSz/fHGyPytcg3TdnWz+diz7Ovp8JPfnG0ibTwdRLHmnJm6B43WBU/+UFczxRWu47h6Dy4K73oAACAASURBVAOVTmYoPz0W882jCHDVZ4j+Y898mDhbw/9P15koOHLrStZLt+375v+/dZ6XtifOCYCk2ndYVUoSCAQCYEqllGqp6TjAg3FkQr4Nx4afA3am+BhiwHehO1hxWezebl2Gar8Ul6d89qLAcW2yxBCLAP1w3J5iYmyvFkf/Ydi++f3Fi9fyNg5QZ3efpTNSj/DbY7zmkH2wNCDj6GR+/PGlN+tb7eIH0/tALdtzGO3jcOP9GACox++beJIjROZh37Znk4P67R/I2VddYmMMHkoGeqxRjtbSF/Zmb8decHOVnH2Rwdu3C/Af10k0Og169jjA7l/zubdA84Gu94iVAQUz/eh7eq5nerIY9YxN5jiIVcryTD6IG1fM9hYdqyUhzutj1TV85QT56AOAh0/OQZwZ5ctk9yWAtRkPNPV92RPKSIslRu8hbcohHZ95ZgMlnMSJNL2H3JSLSRO+a4qcsKYvzFBbCFkA1egUmrs2MUGSx5fjR8wUDQewfHF7s86JMHUcbUF5sohvML6N25l8iXVM3g3hWL5JnvXGI0bfWBa3VKv0U3VXskxK+mfJaKOGOaqB/CTKbe0+A5nebSdaCX1D2x4fpZXS72LXT9o8aGyPti5ZZy9U++jqg38QW2Sl2ZXqvQ2cspIkirKotoXCMbKWw5zYMIyP4+R/e9Ms1Dpj9RhX6zyWW59aFuyxvWr07RmZzaOjvWl/7juxp1/oR/OOrK1x6+ABeWp5qhl0czYCL5mDn0d/9/A20JjNO4tSbv6tfzXtWnDYhrd68qQ2H0e7JZA/3sQ5Mzcq+L6S23mnyovmrL1oxmk+4gw2lhcz9gJZefgGa4mrObbVwJGvt8a7brC6QlWBPBfPE+V8ELN56CNxPDnHiJ3aOc+xeZEOh5RlVPvQ5nLEWohb2e+szqkXmsnRdpm91ETDkW+09rTP5j++kcEbZajJrYLk0zA39uMUPrLxKS5Rik8suWDLSe9Fuf8HPThcqR37ZmsodeZXFXiRZAccPjG4F+n84bt9cco6wCYOTjTk9g6altGeZJ7PfUcdj181BzM4I1QUP4gOOBzW19hxNX/89iawrad6sE8oh0vZeVM16BAODt/Emn56Rp6lca74BtsTzq/VWzUl0paqcjy9H71LCC/sl5++VMbmrWQ47libSPQlqD9GzgVissXWdefVHfRg36OsalWMXLwzzQVwWHOfSe4KbQ+D5eHEmivk1pc1te6PsnP8M+868/XXn3/6bjq/j87jCBooavGQr4ytlHfLf/2NH2n/8sOXr7/49fMXLs55Jz3KCAgPZ/E/vBiV62Su06FuT1s/eRQNDp+JMN7x7AJK+gR63MUTxwsC9/fpfUExXOjJ++v6v/3zZ5Lkk/NiVEBjz103r/XHbmsjqnoHN3VBtLnpE4P1Ymt6YgEAm7v14hpJrrWAW2vt8GMRoetij1Z1BeQI6Oi8HMeXyTIA61gFExvjngcHgk0ljUcKX0TK8+geg76iAswgHj6+Gvt4MeAf7e++VF1jhckRlizk3BhZS748xDbvZFUnc3Bla66aNOemUcWInhzt7WIHtaKM2zyltzdU3ImBp4/qnx62GBm2T6dR1tUuQEBtH5pP7xM5Wvo9yHSnp9MwtcgW8NYmH7x+r4EET7vHsf7yaY8bG8PSmG5y8PlYneRlvjmLa098DqoO8s0es8Y95B+1BtPRLjYKy9gJPFPmi8OYtTqAZw0Wq88JnRq7uvXem4UTIfjomnxmCGf7MsYgtTfC28+b7pk50/t+D09EUsh/9CYKvXGVH4ig4UcTmZpNDDSjZ72f6+7L6QU9kWGO7AM5NrjmWY6PAHWVi/OHHOrI0QvnLFcz8D03lEo4xtHt1JvESrOa6ikzub8fwSXAnuEyGO4XOaupw7/ivmJ64lfohuiDAAPNIZCiSMBoztq3mpovZnHHMhueNXcTRRs79iVPPtJNeNGzQZaVb2T6j43VaPVV6sZyq3yPZTQFzfLOXsS7QbWMEJ9VhGPFDN+yrobddOUk1I1gE46+BAKed2xgN0NsmO1GsIasZXhKIXr3NRGMvbORZt+tjVlRHDNJ2J70RNyusrrrY2d/TWjygsgDKXTIQOd4SLXaBdQQSDF7nHCj5Fiy4IqR+PAOvdzyxoCGopJznuyjhZQ70OJ5hVaMbei4N7qMIA93eByLj6t7erG7pxw/sOq6e1Fn4gaXp57DpSLdMJh/TED3xx43b3muRiI+qwVBT4rRl+mual+WG9t+L244kr+aiud8YlwtBYhJAvTqa7LMq0RHA43nCTGC8tQ6p37fmfWnO+Ilx2klaxUAj9Z5orqazMdFI2QZ5OZr9wTb93NsDPchBB7RObV5NmXtu5PByRwcF6vGpQX7jrCG59wIiabGwj2aYv1eh/Xox1c/tfqRxyA+aODxyR1rzEGbxxvehVNDlE/tW9MLYy7nE13pVHj5xLDEnFp519O7VTSxX2Dt817UAJ3emB8/V2EJ4u8NeIH2LRcj+R10dG0fPCbWYZOb8pgQx8hh99eLdG3dZ/1AwCz+GAXOaur7DjMZiglEDowDtwcbOub2f2kNcmE9Xn1mucSsA1m6PS8aEHvI7NmQWucTW7m9r7Dx8sAXDLA3Ht9HD5ra5NoDOOWTj0W+5OEmM/j+8cfI85IV795y8etX3sWeH7sGyXhzW0PU7T6hlPn5NRbu5Tkf4APLxai/FkIt4VKKJ1l1YcPD92K+iOMd5704/5ML9LybfjRGN/nIy6Cc/tqJhZmT3zX/5Zdff/iFd9B//dUfLf/yNRfnOXf3ye72j5o9p0evvYkOuUPJbLHqxKGRSfOvFhz2J/HUqT/1+679j/kDkPOj+/w0AD/ujnh81M076sT8zR/Ga+gQ9HBTBpRP92RwbPG1xemoqu5T5vaNuGIHlDDJ7AsYkqND2E4GDCPsh3PWJn8wTMHB4Qjvm5d625+7j+DMmcgqR0fPUywweitpdbx5SUhOQbnZPTs14UqseRUz4AoxFmrpc3z1YzvrEwt2dVSx+aHNWN9rO/NM9E994sNrvcN5a29UM0TH5kf3zNVHfD6sN4S7R9uHuwG3mil9itvKJ5a0h3/6mXWjq4lFZ+zNxQiiqKkPjHoy8YIX6rERt5pjGt3MMrbGqY2g93kfaIa5PcYCMUCPUAQzcw5GcMNC3hxnoGNd4rRHeRacszqzKKb9hmdz7BFy6Hccu4EGjM4glo/cJ2jiY2N8aMGgzlq3d67CZQ0TgNLtDSzWQawTiKrUiohJuovH23hmFnQwrKut+SaP8Y/eijp7QsTm3pzmW93k2RGb/SAPejOacTm6slNCgllNy7GitZdDqtG1+73Em4Xj+tRp7iQJT6VsvY3AuOc11Ru/pBzRp3WEQRLbO94oesTH/TdrEOSb5opSBWLCcBqwCb5rwj2p7maO7BFxlRCqkEx4Al7h148w84368lQF4LPOpFyUWH/XjaZ+zNU2zbSW5gclRKCigt3cwWBHI/QZ2/xtYo25TcxSoI9x+0iGGQH5wDq89YyuLE4PSau2ItiPDtYzz4HZavSIVywEMKQ+ntmBy8c+uNjf4VzGW9Otn6hbfVebh8Z5nqSW1Se26QBP3k+daopnKxKoVmbNd/QFhKVjjttD0RBhL6opucW2yud8iUmLcG6K6rFrjewN8fA6L6sIzHxM74QZpHfCRBSz5sG3rmaU+qnBd1PkIjWBzdvD1tRdaqLxB2ldG2F/hsgDXO1BZ3euGyHJt70fycd2mcbDoeIpX3krFx2rcCCTolqpv+8a5cmwNNk3nhBnvj+KbpZ54sa/H/O+lcek5fNIQp7clyVHJO1aBrV9nJ+Y82Ue4v3skTseun0pgl6Ey3eS58k616LoRIR5JpaMaNgn+5sP8vakiLW//TGUm3D1i5h8kYfjfmXNHMxegKy+5dAfHX3Cm+PErlZwtodU8WkPnvEvTVwbmis8gXQL3v5v1Qlmmq90qzzhpm8/81fov/RCb8qxpuppbdWAgmdQJz3mo2l0nv5mZco4Bzq13Drwtx9QBbf0E+DaOcBiyScxTr4keY6ZOsxrUJcBkmPPKeaEckMPOau2vxwpSj8QuLAx5rBTVdP8YDoAxBrdpyZ8MT+hWeyqcUKOaeLDdF8Yyzz3Nb72wteL4FxA/pWLYc7F/ni294zT82llpY1GMvLj5D/BF+0//5C3o6PZF1jUyf0HEzr49YkcY/JujEbKCbG/b54XBv7Oj7hzUe46F7LVUyB5vh9bq/0Jz5dc+P72n//88Nv//M8Pv/76W37E/as2En1LXXxfdL+O/gjgIppzN139Jz/9gSb3cXr49p+d7IuHKMl8diIhnSUGfr05cvH/5etXf0z/L36fPrX9lR/bR+dPeVffnvKTB4bkp1N+DDYX6TDTMwY5lpMAY7SjgHqK7fm/ivA19qHSSMyo9Sh3SM2WnCff1L/YxiWEgbbRQrOWc4+FyCgcjo031JpCw/luxuq9uaC/MWv/wCphdKs1htJN7FkmQ+Y0meYxz4edenIQ+o6hknLt1qAjPC1Ent0ftoIAzx+zZk3OftZXSDXSb/yJse8kmsQfvcQ+Dtxwdt8apxYQ5A+uXJJimKEzc47x4Vbb2jFtXzo3FxHk8wMqO8dEDfVpHuZPvoR1kCujdZVlz72PXnpOCCQBQDNKM+cLLHxC+dH70SaWZOZc5dXNc/Gtc3tYnKmgldtipJheY08sVRC3Pdkci//wrRCOGwvPDvWRTkC517exruv/EBb0Rxy9gEfO0ec5DwFNHHT827NNePZwcxux/I0n2vNqa2dvdNERRhDK3HVSznM6vTinB8KNyM3qntjWAGLOs+kRFof0oyWG6x49iZMqvve6C5wI4jO56M5rHsfoBDMqMmNMVMD3+wAYPBfd+YVbd0BGK3h4li42pls7Ofl7og6b3tAxkO4mPQIJyCbv2mVMks5CztlAGHoHQNlI7hR6bc3i4uGVZdblOHcGrHIUs7vTE+5uzNpffucJQ8mekPZqdO6DW2NFqREswz5RW046VirIlBVzUdNo0Rrie+IDm7Hx282Cm3UCF1rmrtDfRK550kPtXgCRZ+rDebi0xUAcX1nPIcfb33imL0TefQZLT7AR2D2d4/g47Cj3MNCrzY/O8OiPrUJYlXv32BdvdHefDODGwNGBP0NNndSvpTlse5pFqj7mOxseghrv/q6eHHe/iyjqzg3iqqlyZK/NN2aRSY0mbxTzPT+n0vijPA+eZdk6klwdxHWyva5ozPSkT5wXBcc+0cH2OWYf7N2yBrH6SIMvY5CkcFhDfNXeuqonGT3nisMGndUMl55TCxxNc9yZcBGAVSn0yJr77hs/7s7FAxd+DaaHXDEn5vB2IvcQa4mBWOqiN1vHXlDt3liLusKdveCDd7fMiTLic3PXxcG7OUl7ekLROACMyPWvBuzs33IL41yKgQ9H5qc39iiMOXq+BOK7sz4IzI4RC+GMk6vt0arGzIzwPmHh802GebNbq3ztHxdUvsO4XKmPVMvXn/qoPt5B//mfXOj8/HeOpOWdT9OfG2hW6VKy7pw6MlvHRLkcm+3FHhGrAZecuynj5+B+DJZzVvHaiQnHzex9CJsaHl+m5qKvi++LJkMXvzXsUUEjGAnk2xENffweg9hi5ChTnVtsju6p+icO8BlDMmt1EpP1zkVEv9sRhxfm8w46F4T87jfvWvu739k0LtKN5/xLMPEMbJ5/4aK37MHP+X8w7Dd/hO2nv7P//BX/bz1fiWnungic1yj7m/MqDrj6YgB9n7/eHgz0nPM/5Z3nfyCXPwGTl2Nf3IyjGVx//eWXH37Ju+b8aDs/1g6GWu0fYjLQzDntT3xk7q7yOMNjsupaLfpMLD9TRPA5+6GoZu8tWqpdHHmC/xId33KRjga08ALElz//+OHrj7+oQz15Jx1+Hht+/jE/+p69ae5hpm/pGYQrS33EBEms9tx65KYO4/Y8ALe8zBpjuIueNeXL7X8Zzcc5bB/OyWyyEjoN82oLi/fVgZDfWLU8KShI3gLVhim1I7QciQ3O/bRmUPgBEse6oyyda9Vw/RdXPYb+S/PlJtLqMRE82H/PcXYfjoaAxDXJ+OOdGuA9EdTh5rakxk3uw0yOa3trf7k2/3LA23MhsZxT69j+Ze1zibHb5+Rxyc2p2QUCPuqyhsVNbTcGxXcUNgrFwsUZSC8y4sLLXOwcV/Rqs57C42oXCfRctq44Hdvh1m2dUw/uPb+EriwVoGP3R689ZIadod5Z97mY5gCCQEt0DOU4eri2meXQb4HLuLk5Tk2HoV15OXaOp1s6uslPj2uc5PiQuFGto/2cPq6MgSz+mCe2vOGa+ypiwWgn2wY049wKwFsNJwcTo3Nb47jE9mZqGeTuz+4HxZ/rLurmI5StteuHTJYjkZVgEDcP882DvOkQIEd9jd1et5f1w29lcDOia1v/sS/19h30tiIBmZDQJA8BjtPkYFYE6J17hChDPrm6fm9XtKDE84nAzbtYcXwzWk4bvN6i6xvAuFglyi92Ax4GNjQyjm1qXN+1Cxa/TVt9YKExlJvMl5cs+jFm1t70SJhBjx5MIuXZE4aod15W+9F0raWJcPbBtE10De/HUO/oAW/QgxhNWKSNHvPtOtajKQB91t3c+qYXrag8jckc0uU0F4Z4M6+r+WJoYIz2mzUYCSwicXfEktFbZt2j2uBlrCyoTLaHADZyj+DRpGMIjCNm1wVdDHAvtmCB9GUDDLT7KXfWUInmLUpHlA//WjS8Nue5Md+TQyJ3tHksmIxoBs988Idv93OyfecG9mpFccsKcDjPEYqmKVmDOxfevdU8RaLLd4uL8gHdcwE7Hz5pyDxP8sUm+XkVNDHIhY+hTuKm7xz2xQtsXqTDmfl+ZTKxOYxeLD/l+uHv3HgeoSGPP15MBLO8XLxOuBzPQ9TVFcD23j4Fab2jM4cME8vhxYmzqSfx6PG8io6tDSPf+H/kx8dz0VEabyc6/pKfdfN0CQ/usg8ka+vFZzHdA66vcsl1eOD1Ykh+eObkla954eGTH9n98pUKehH444/7P6ABTz0KoaDu3eomCpdpZAgfurD7MUYN2PlqLk1jd68z90LyRSR/IeWkF/blYd86eJYk+iNm46Q5scjwOmXkGMJN4ecI9+4nNW/uxR12CSZ4DmhhSm9aRTWwoA65Oa7ucRuTecuwury2mJMdQz65j/z157yzmx8t778E2z/INpnckOaAljeZGVD0xSt+8uSL913O554/AWROEl8YIVkCfEEn8T+Cy/0J/F5Ac9/3D6cJzU3ycpHd0aTenhv4awcDH+9W94u/2j7/USB5eUEFfu6L/Hg5F+f5DfX8nYzye46HS8ZQdp/mHFA7qdgzDulFzksxI2H3gHqVJM4Q66eOv7/xY+z56YRcfPNCCBxo+TkvQsDN14/MT2+4SJcxdkWNvua+lRM6ekRMUA7ueETfI4wMLKhmtJ4pro+3WkF9jpbbSCRBIPdwjYlShq66PNcNWPvGStE8FRNHgiWKPrRPHEqEsAkZb09Mhi2updkKq4+IeMIlJ8uMxdiJCTy9BI4Q7BNn0Nxoxg9kdC73dhZo8w951o3LLXVRSw4VXZsc1ngjgTA8iqc3s46VfNzCeS5MDr7R5SUm6xs8qYnPiD0so4dJ8fLrIEX5+hhZo7lhwKV2Q8MFr8byat6YwrcPWMvTWL1w7X0t5qODOuHNZy8Ks2I+uZszbFmTvYNZ14vDrj/Bi1UdPHHAszXscTUKOdqMsjfLLR8c+SL2jNF4cjsBFMzDJ3/MjM3dVS1V3krlpyekIWbSHW/WUo29z7Mu29aJxRg5wjp47dqKBNV+yVrtRLL0hogNXqws3DiaopjNb268dcrVPoYjj4val5fQ4La37ZHUc8NOzf4PH4fVZ7g9qwZc4l0aYP0zS1jUTU6PD17eirYXXSNvZwmkLzR0mmoakjLkHSzQmOaXnrI6FwsDDMFHsASPbTbA5MH2gfLUfQQQxjD34LqpQNq4FtBsiBJ7TtIKxaad2+RO6FhYTtGxnHi88neDGkvMIgB0eTZQN/4OZ+a5MS4TuPWWpBrOSRQQWRmXOxyjp+z1Oge/NeTYbzCNP3lG1hxKAQRDvvhRU8azQ7rUd2IzsXE9NoNhwmY2fcsKTTs2F/FnDoY9vHxELO/WJDw3ruE7fRi1aoILZ4YE2+Ngxv/eIQq8t2jY8+nkl7Dn2OGG/mipT/7U2jwRYRGALv9i9lwdiUL6vhDxnZWnumnh0cbcnlbhlt08/ZHQPukjb6JGE11aKUTWDkJYJyFzvb3Cl7n4eC4HqMk/4UURwKjvrZNohnlFkKuKjOXl3hmtHVAwk8r6WaAtB9HU1vfyNrRPnmPlogqUXOkpF4OHd883U8AX9qm5KnvLk/4dXgDnSbkXJRhfPNcpasrFOLmtZTiooWq9gKB+uLg2PXvT4E2lTnx3hMt8U4/p0zVspiEHkObEVnPX2P2ab0xeoOe+/lOe5LfBdGpG8oIlf3sOR9drB6m81Th5tx7xiU63Li8xeTwm5NYWbgyk2AOP2dHp/vF7tXDnK9chMrpGrLJy44sd/emfWHVsvz2CxRqo94sE2i3W5LQnkLEu2He1d51APvjUL1EzrH2LLPMkhLC0uvfHwuXB50AJ+MZAPeYc6tt3680d2MEAdH2DKq1cuOsZngnES834plxmore+c4z1JAy4FOFzHoYYuCjma/+dmRfq2Sz/Wjp5Jm9TEBPOnPueSxaQddLDyfcfblGMuP0JBO8vMfHYGLOx+5NDOV3mPCNufOwpTIDz5e9p1xRATDlnnDAH05VzVvh557y/D8/9lXfO82a+F8T8O7N5tM4LEfzou9p5sSvB1pWJ59q35jcYXhKB4WDezKY/ldHqiwCamuYbFnyoRtPP+fUPfgNAjsSjh4t11tZKHkZ+EgGbewBuPtShiGBGFL7FlhcV6FsME0aPx1xjtb6+AD4wFKgGUrrDlyv25kxEcD4Wx+aYA/NKLU/XU5vA9q45y3POseVEkTrggs0K2x/5zaAdyrt6RODAs/o+mN4YIFsXMVV242ryoX96U97SE8FYDczco5p19B3W8Ep9ezGZRI5LzO5r080eTO4Xtz3ieHu4iUmNqvbu7Nu47zooYWEenkZMJAnDsVw91iaCsCyxW7dkhmgveZDpsVRgM9l5o7tq/BPbKREQGENsU2TtfPopZHqVCGMatqvGqyqB7Hk8ZKYX5naNhRH/9IMV2PZs8CTPJ5EfY+rvwwG+zZLp1AC+fgSCAJNjjJ8RXalttNx9MCT4YIYDtIu6cnvrCrlY4puNfDObWgjD0qw52qNF4xuvcbUTai/Vt/G3t7AZF/jhGxry4ScKn+M58lgKN9o5nlpnbbblmrjdo+aC+uEgQeiaafKZtL1h2p5U8+EAujyDbytU5LR+nLUJi6bb7VJM8uLCi3xvw9/fQVfvbZqAOPeJr+DR3mKTcIuHLtizFgeDLDkW+24I6YmhBZ3ndp8Yb14LqbtYMODLu+wi1h6j10gcRYKirhnh7qaSfuYA+WLjGZlvO7WM2bx58kAYN6fezLdP1oiW4eMOB87SYmzFo8f8sPZEMHbyc9hx8qzBakiQ2GjGTy3iMI9eDkghDYOailtIMsZn/PgFomiC66s+OSB8xgf3E/dAbIUSJhc+1ypC39TwCgf0ptp5H8HINNHlwn3re/vbnXSv5WTdPrDMlE9ETB/yhI4nkmpBMM5nsJff2dr32nG5PkfsVKvHWPdkzjWetK02j+rIqTh+uQzPjcfVTo0xSBaSd5xNIWcrsWYw+IyJPW75k8u26iKmg3Qv/vYqua2Jy1n4QSauAU7L0Ck5+CI1EOrsU2TWdx+JqU72oisCeGo7kjE61O3sMjQGIxceEDTv5hded/kRE5hPooGbq0/o+dF61gXifJ/AY69uaumLMu2C67gZapwc+wLD3l+LCGY1dnZj0iB/FB+exdDDfFQvLzakMzyJFxG5XLiA8ZhpNrX60B8/NTlmPSs3JnP3iHMBxvDkUkJmK6OO2L3NwXal9jXb+7rNiYN3Mn/OBYmMwf71Y/+CdS+YqgGm9QeCSL+GavJ15YVV9O1F+TfrRysh/FpCLwAJgt16SloLvcka+2YH22KYxJcP9Nwj1n6dKIJHIFzMpxNx1Nk8WTKsqXpAbozCd32OyaK4SZIF9zKTSKbTNOaQPtnJ4QXwCAvfavGoTmz1s+w76Dl6gdgLdf96u6joDLTvjMfgaO57HoU5ROT2x9r5I4LZc/sXOxfEZpueowMfp6EX7SbIGo7Z1+5tbHDmi7/A7n5NnlWy/l2fY2LQzDvj1Xn/ZZt/cC4vPrwXwzzO/p13r/l1DB9z0SpZ+8Sia2qNI2ZyzyYdX/vavTvu+V5lvDdoy1e0LWfI5OIxhD8Mx3JfWDBPmsWad9p3KCO41ZCJmjyvNLfP4OFbbecY4z5fmQ2yxyDhJO/uq2tAo5+J+QXDqBDjGr65yyMsAfJNTA8Km/jrqLX4Y7XxrEZXZtXAOXJQajjatF+8sYmyp4Tk3OtOE9E69v4tB8QnbyyzLtoQgvh0aN/nhmNrDAviewBnTLg7R0V0SQC24/ZrangK3X1G34btOfnBPc5P/skXFc7CYUz4OSeWe9OpMXbGlNBIvrdorQbbY/1FedtgUYWW53KWASWOHPq8YpfVymojN+Ja0IVVVo+uG0Bo93x6ZXx8J+dhpp7tNf6MqbvMj5bYN2N9k4xzahpnz+HI4GGuaQZns3SN6gLMOXr2fCuqag9n4vs4ubyghntqwFLW2stda3eMOSO1qCe4PWZKlP3AL6rrLsrZ6M5VOP3Cvn2gh81dNljM6W0TgfV8T6NWm/kn8cbXl9VNTyaZchP7OBpwuMzM88HYWyvQYs/9Dt+EcygF2odsk4LLx/fx4hZ64qtJvtQI/62v3KzvOR/A4FpkzJ7REgAAIABJREFUlZw/EnfERHxdZEpW1yuWdey4FA92fbXjcXAY7F0/BqfdlH7DmLjYF3VybPPj8BUljkPfqKdpbDgMkOCcGtDgiaA5jt2kgM6T9BNEaDDCUh+c4FkT7zSLrPbO0g3GUXv7FghjzZkerucBTUxh5/bEbG6SM6S/OdBpXeTN5548i0XvGalh60KfxYyzvbaiYrATzPN69U8eluTJcVRk1vGROyZ6451idDWHZCWARU0BL0biLKZucsgRbF0AgePpaMvjn/pEmrv+VxdR+Il3L1jxqg5S4sNOa9hk+dRRDdpLKbbAxjVHY2opcHOr0Zyxw58bVMDxPumtprSdgFPi9JGoFXF8GkspreTt2eQBOiWBmEXpb42qOW5ApDIWjZ0Zy/7nqeYlKvvRdjQmzrzBzxtX8lMj5cmTSfnGRk79rMn+3Zj64b2FsGe97Cf35u/FIPbqIHRx3F+5CM5TYL1kgtP+AyQsoB/zBDlBfI4v9jjZs/ZuL3yBCRr73F+sAfv4MznnG3iG7thVUBM6WlHXG++LB4TBB57YYNUCVTi7VxMHEIt4zqvVjV2XHAJCJtfwmoY4dWZCSIiMjA2/cRpYdCzHXuD9mN+n5SKMC8D+mPFHZV5UEcMFHhcx9BZ8073krdN6kp1zyrqmj3BMMfJsTwC1hlWYYwOhYpEvq83tHOnjxKktmNZbOwvOW+K0e6uhVMMKAhfV7EWx3zOmf+piPjWInxiZ9R3r6M2BHkUfPbbupKYkvhh7fBcfOdDPR8XPMXycHz/33k0sbijNgWHHJFBDYriQ9MWhgKkv78tnYgVylinB2TMe2xISE9qxcTNCMvNCPz8jvz8m/+b+15wCHi3qsSdhREf+6Bx/ZO733/lf6vzxu7z4xO+lB8PgMWKbwB5Rf34hw3r3Jci3b8x7ZnLMIPfUicF+1UF3xXieEEfd9Op56NzzHF5ehOJXV35K/0OsLPb3H+47fD8jHyM8q8muDTfJyWne6UlrI1JlPUiCqbbyLqeM4wPY9ViNbBSeWqmrfalt14CZNyjYfiL/jK1jDfaIXmBAH+AuTv3bf3oERnfghxbDLOqjd59Y6BnA7NcEpJLmxR5u4va42I3juHXnxGF5sKt596re3gYllmM5o2Pq3Go+dYOs5fZWZeFZTpSHTx6wZT7r2NX6HH3eDZ4xcYsvQ329nR6W1hAxxhGPqRrlQouoMQfniwDYMt+eLiSGTuFjZOmezQJ3ny/Up9np5FHX9CD2d9/Abt/ateZi3mx0Ljzs4ZxPo4LQjOK95YbvTQja2kVkrWlYwWWgaBwe9nzB2l6D6dAGOtxHr5KetXk3htqnZrV0Dds5X9aPkURJsnl3jevtvzA0YA9vawUDxeyd+4RiRrOtFriY14M76+mtRrx116f2erg9+RdEvJjtUDUU2/obFUsgp/aJ316C/xxT45YR/MndGXSO5VDHIVk9New57bk08Xqiv51792p6ORk2L/jtHa75P+iYb5O3LzT2SmCWESf5JGSZL4QxmHckbuGmy4I1DTC4DUbIFg7A4sHlq41wQoJyK2xw0IHNsCH48rl3AB8w5eKmyu5WXl7i6721tkHB5BGBj/cOA54Aa5ZmWSceWyA5OJDV+WR5alH34E7ArgsnkXwlDdMQ/6tvxNHbGXcWPSsCLWDyKX3s7scqdl2MPaDBw2mc3Ho2TSI3U3WyOtIzt0b7WF6dPNkgl37wCjvrzYm9XW0OedGT2KsnS91Fk1HcPCA4P8zlq63MlT95Hu5qgm10Z2KarBnkP3tgjx7vg41Uyyk1mLmgw8Enfagg61rbNRIDYDQalnl6KGc8DPWicMjOPg93D63ZObSMoT+1xIT/dQM7Rp3wzNVRZtWxEZXAE0o08GTcHzsmLnMvALjwzRPRfGbk3av590OsdvQChJDE8IxW0VeXy9y0zuYilrUfIwdtfO0TcfrEhdKqBcsnlijKbRbJCT8Y+SVGQqyTmPp8B44aYzQ+OjeOEKHoyRcXBOg4D1pMk2f1gj+DNGjwK3H5cXa5AgC/F2XywhH7+uGgBvrMiNuvzgfLEwwiCCJ42wuYdQa5/WmSHPvNVeP4RHTubXWhh/jtKfz0yA7Bl9/vp28OsOSL99RK/4JXe1xqDAKUxBxY+FUrJqk4Lpe25sHH6cN5qD4CyIvDAQ/zseWgRW1A0R+NtYqz72MpF0QNNAfn9uGvLuzeZ3MR5k9HzNpzcXsSFl682dDVy4Ub94dTXzT1/tH7BudWX9ioBu8v6KMQdFlq+wy5WmLbPPWDn/saOhpJAwosGYRTeRBj8y+4s3fxwb3/r5yeobl6gCvI63Fs/I2Jn31HOb8TPu96+7vdiTNGEY3ZWPPDw9cUcHyx3RpyvqVvvJO//7Ktv/MdnX/3j8bxUxd5AqTm3glurtbPmjrJyqH1UNOumb7YegTrQKL64MgXLw7886fGBsrUFN0XXlSgZ5PU5DtPCAmeulfLniuL5Fxru2PJZ0OqTj2ZEmtFyikeRDk2bmLU2fqn4LGUfGNAkKxrId6UBXvxiFvNADZebleJeDDGxXl5SFM+c1IsRU4MeD42gmqPkFdc8NxX7YUcRd7ozUh/xiqeVI09vJvjGJ4ag1WvxyvFEKW3Z0gj4x5FZuFznMRSIypArbKZaG9PjCpKvPDrH56i8JWJenZPyADBam6O5AxUX9mRAYHc42gMC4AJsLfBAVX7cugnPgNNGUf/d+u9wKv/3VeiprfOuClXcykQkPuFiDetqsCjc+4z7W9xVb3z4bZfxMDKDRFZD7H14lJHueG/oxm2lqM3kMbeeogT7bEMpNkhPnnuPmE5Ui4f1ofDTCOpfLlVao3YlodcL//uBfbGbr4bi2/HPt6wXjxaJv2HrvqpOF4/e7948xO3+gBNNzedR/3bu026OZdgkNvDK+gmqBKEJM+cJ+/9xFh4uMZxv6MNfsiyvjpiygJf9x2MJnEuksPRIO3zI+6x4KMAGQgEVXkcAQDBvQKxXoyLc6NvTxytCeQlMMYjBLFnACHLwLTHf5fFbgx2wlcP+GJzK1SnNKw1deWi697eHAvgGB9NXt3rwpwPesVHe7Vs1as28e3h4tbuXiaEqI2vBk7NPRkgGF76cPo5d0jcEJWkbc2yfDGf3gYwuPUR9Pq1t5mpFwWto3GjRzl4oKsGJXCTsXbn6OXJ+cOFBNR5EoFWE1F8ZZw1qOmD+PgkF5U52ta/0aNXSHtiSJPmwRf65kl46MohvIZO86SO7AzjzeXy3GzfrI3YGbVnTThPupFhfPmAsb5PvqaXsdNPR472VhsUrVM1+FhbzMSQP+dnmRJkvqHiSR7+ZxC/XLILub27+Ro0aHU3d7BcLFDHcNX+kcTFe45gUAk1cBHGVWE4/p66+dHPaiVjayN+L9bQSjxw8jH4huqI0fqzPMfsIxrvBU9yZT3pGgcHNvgSy8WSFw5ZcMGNSvxkxO/DgOu58MzcdwMrarDAwSdgk+VYHhLOFyUMV2Yx94Oatz7n0ytfYAA4OLsAh3gd3hjz5GVNntfO3D5RYd6tU9vwYDcmbN2j5uh9loQdTQFPxlOHXmuPNM/LtgGcF5J+f0mWNjO5chapB1wqh5jPnR/udmV708R0Yy6+m9jbjZdogK0RS+s1p9xWkLgcydlZa0LLjPYLZ/uz/bOcmI2TIrOpn9BNwbnKHvZ3jnmhol+uPY/pSbU0phm0rZ080eS71cnIfcZfc8gLOP2x7tp4sPM+xv0/uFMG9C54jGsuBPIB/se8o835/N+G+/I43jX72scE6u2LMFz87o+T4+cCnLEX3t/+4Y/Q2TVz0w/+RR/6vA9Gnu8kqyf66DDz6DV35hzpz6tFfn1A23PeQedfm5lDCuqvVifI4Gtaog1TePqCEjnQj47C1GPnMCQQ3kwZHrFhJsDJHNCWfjDgMNTY4Wbv+DAfkWU9ebNPPSdgaIzJQQINvzGjp+mvbqIACk0etWEjLnZ7KVEQ+TSe2058GHDb3thhmcyN89yDuOPwuPxcLeZSbi9QSepJfoBVfa3JnPsQvbYG8Mr/rm64CPImR+i3F2s7Iig+mccfpNhXzeaim9BWLUfWsfCpcXobw/b4HB9sc5jIKZxlZZYvuNC5mjZhTP/uUZ1EGja34rZmfJkzwDH2PqU1vl2fY0GtI/NTK/Pl2l5KkoyK2B6VUzkTL6X1FcP6e67tVx9vry6wqKj+noHOR4vu6RlCdq+KZ5Wac9P9cmUzzCfz+CQCTy4LauxwL08Zxu85Sc4O4u5qrBVCCRnLnZw2bQKtJcDSBrWM489B1/bf1cJXM9hynF5iOlSZnHmxdiucp97lBxd9714Qe2uD6pLdnqGSIcGofNeQBLP1DseiVzd+2evI3JXM9rjNcC37PDYw9zwOfiGks9ff58xaLN+bAT9q31V3lPzBK0PC1pB1aydiBn1jKrbKjSMsH1r0QbH/Zm3APSlYQDHBzBDLAy5FeGiBNFPf4AM9o5TgygW28T22KZspR/1dr1WOMMpB2JzwPXF0fOgiuepN0WjfyUBnPmJWgrpnvTVw3AtTeKobfOJWm0d4h1sgrLHMdV1Xmsy3WDEbB0/GYtUWG7kQ2DTbO6HetNcwTi1wEMI63zV3/9bfgkeB3MGblH5MjayHY5IYtjVXzyiFI2N1O1/dekI1GJeFj2d0oDUf1RwXuUMoJ7WDHs5XA1TuifwT32LcN8I62seer7GoIbwh/k6OcJ607ZOvIbAG60DHNTo76w+7qtWO332aJ1KtAWsxhFECevBpdZF1YsSzphccM3qbo7U3Tn1Zy3UwRZo/sR5PNPWrTkt90g+iObludn/IX7frXdRHz7oHUgaoffDnwnnjrYMn3lFgvxNgHi8B1Wk94KdV8CVJDJK3F5U/dQw5IeHceI58ve9MUjd9Ypwn3FMQvqYg16QHzBNkuSY/PkmiLCamfXd47cgtRyxBM+c4B13rH5vOiYMvOXNZY6gvWIxfjczRE957EWWXIDi50XB1VMXx6ysp5/yq8b4SM2zMVb219loiqQe9Qcjhm5dxvLiReT5pATzVqls9sGInwi/wgGe9uo3VCkXvA5vyHmeWA3F0Bbq3L6UnU8bkIco9XKI61bqPF8cfzO178yzcIzUOQs1Z9ht0vbe8XiR6QZ53cznyjq4/7p85F7Hk7BexrWWP2N/95OK832tyHvj9kIvxXADnXWEuTuHn6IuA/Ch3+NIYe2AbpiVVmdsY/f/fOe24btSNeF3dLyr9GNNPm5757h1c/+Rfq1EbF8T+Hnps/hX2/Os9zmlsDCjiyQt00Z9z66f8GgRZPUfibJ37OAO+KvZI+/dcwWbsCD0Xt2kU/SOnfc+FOlh+koPHDILwOyTIzXBYCw7zzAt1yz92QjH1L9RPKDrjkA4n2rLecyTdcX/Qc3KZZnEQzlcOOzAtrzbSjJPqN19nUNd61tHR81OkqfGB668Nznk2/fCQHJRwepS5JZFXB5PlWzVxvT04iIuVr2EfWOpDz47ONtGuchxTa2vevf/Cgb+1wVTGu45pasRXGQaU1wjiMnTG5/0Mw3S6Kasdc8YH/9TfV3S/84G1Tie3/oezz+ke5YNXTu4rA00smSuTmt+6dIzt7sft7+1z2dq2dlRfYtFZrSxkbEvQk+TuI+bBdho7/eIx5xlHMzYW06NFmUcbvnwGUzUEAC9ybZsbq3Q2QKiGa2M2mE6z2qjO6m9Nkj31bZ3NDn5jM3Na0seqbvHejHZhuUnQ1rrP52JAgmPrQ8etGVf37vhj2T1cPs5T5ck0MdtTCwsLtQEi5/TUmCzzOeEV7hq9w4sVmxoyQd/RMPzbL7LLsvlNSe5ycKt/buHUN71/eyIuN77g//h5SlLN0Wi8DDECjrJgtaNhXOhyqD0z7Ax1lm0Vtkd1Y7NlLIUlMEf4+SS8HFmi0TCAur1F/wUbiTujHNVcDJHM8g56DhMHlGFRa7SQJhqnnipCU084fJ5QNgXKNk2uwbiZVMk4uC7P2kqx0eBq+WgCxeBFc5W48GTHOPSrBRTcp0QhrDNh7oMvk+E1IGu74CKu4E8NtZ3cWwcURiHnntSgYeML0XDx1WWD9GkRUt+sp5xZNcdqR7P91QsyTMmx34hPzmlKXGLs58aY4CqAW/8+yMZ/HnAhYJ0P+n170njjRob0gDPcCyb2GkM+HxzRu/QIN7bpU6ZZxyJd0dyeIHVtVYl9vzkQljg07PlEoHxwZLx78qRsoH7iiWKY+UNbiclPT6pV7dSRCyGVNQy2alku7cXJPjgv0EbM6d/WKe8SVhUPSuZH3+vqyXB0m5ZVuM65P0boQ1Ie/KcZ0TdpgJ7e4VdTY5q3yYeqecDNF3vDZfleSORp6nBHPXQkOOO/cCGQASUffPNwSXzXWI7dJ+mkFy1y8a3k1rk9aU1hSW2rh/juAzyxysc5lfWDMwABQkBmwkVubEaCxVcR8jA1jkP2kQusvbhh3ri+uJBQBxejSV2NmfenMuKFXPMcuS8Et/eJfTHKtfHCT0yrg8dP7a19cEd81lBTP0IUk4PXPaz5pGe42of96SyY9sUN5vS1tMUlxGG/D0/qXXuO+hYYIVxcMnaPFAcvxtWWBX50taYS9K+tA8zQxM3s3bExuUO9CirH9RA5NGhPbl9A4mI8X/yvcb68SGc9F+jGg91YdHJuV4putceUa3Hr8Bov+8u/K9v7E33lsePnaQjrWLL/UvSGJLG2V0x7/uTSsffFxbJv8R3c6CtJwm7Tg8l5io5geHEMPdYOR67JffEpF+6cd9YBll8yz/mCRvA/f0EnBXNBHFemqKfX1ZsD2lcTIAb6D8aJNlz7OECf+eL+RP5vP3PRPn/VPTR0nlxnLLUG+jCp4dRXfOMaVXMDl+vsIRAC1Q6fleXIZuKqrUzkChZ86VS2LwQsZnO4lhuqOb83ME5t+J2Xu9l3rst8k859QJPRtiWKsvS5b6z1Ea/83CTv5JCN+sbpczNidHz2cmWih8+uO5cPzskvBkhsq/8Jkj1pQ4G/VO0G8iRZ43AMtRGZK3Bwxk+eNQ3ppaqfxKutid29TNGeoOiFmnDP/WdtLcFITa18ZWUOllntAAOwfc1E59SaOPx8bf0neDn1FFcUhI1pcPKKJTFMj895cy7/qA52+tDkU3LFn+87hw3R5WfGIMxQeKZfa98azGmfuqOTKoG3d53dytr1QNQHY/nf83T34+QHFjV7jnU/NI6U1ip3Cjg9ICpadj8BV2PwW2gwJ/fa7LcdObVvDxZ7aj2cT17q57nf8Kh0A+Jj7H4h6Gp5fGqZIGJcU2f1lqZ4nNZ8l+bg5uKrpzTBy+kqIPR2Z7DInUn7CEt8Z7/wT21T38U9viTGbpyE8NzR+iv4YEw+mMwPZrjoQW0cGckQn30efbXrEnFiVgO4BhWEBIJi53BqCzefrRvQ9eWv92Q1xRNtoEYlYerI0WQLH5Gqjs3GBbPwidK+icteT2Uwt7U9IjLfuJvnRYMqdq1b3D3hEksd6DzY0eWaEwtMbgSECazNxGjoxO7cCEDlHgxYKfYmRKXVUA3wstyEmduHs2ElO/XMA+LyWMsU1w6NfsMyR3vm3C6HiVtKrM1/+4m3HMoy9vPm5glnEqihKVrH9OrtvXmkKXfPhxURL73JFzHG0Sl7kiDs6NSWA8+y1jf2o9VJKyWms8RP3+hDsc29OUfaHKoRhPFCn72d3By2RgKvJLB5kjmZzJm6qmWehHKFMoMng76zaN9K9D6pBUYeeDJhaS5/tHM0aKznEYJ+o677rC0qq9TaZ60H8/19ZVPbq0FtLSxVFNA5Dw5TJm2SvpEeGxHJm4NuYdXTXOWiZi88Azp9HtlXS7lOlRBuaWZpDvQSg5sbLg7Aac9jCR/YDRUUHKOGHljSnHyqPWvPK+uoRkI6MGb2IS8YP0DEsfcdMOIawNQxOlzbmMa/5wp/AZ13F7n/el/M1cr+isbSlD527zexhkvb7Du99fyK0WMhxZEX8IyD45v9FOheiJtzgP4EP910RjjVqTOzUhZ16AE4yk2uu8/ryzG4Pu5caXAsft8hN/9osWY0qmIzTt1DbTxz+h6IXcoRHnyz9fpZCw1qZWOq3uqXJFzloZa+Cwz36Rm18OGFKv/m67k4zzu5e8HIhSmJqiUXa2psf5ibI4L2Qs7cKgSaqLxjTd5cawLKhXkicvzyNeePF738ay8ueWPP4xH0+XSsVmtODHXCdYaGrsBUDfks1DzY0ca5y3mYU/YkgJ/7OaTU57Dc3BAXfbx48Hd+3N0XbKSeFwuI5ZUIhjnaGi7iGdRxH0sxAKv4agXVmva8oecF5p2Jv/s/2+FGu3+QrmURSKhJUF3WMb2+OIQ9mOogy+5dGayfOpIrd+mO0UsxaPh57PQNnoUBfuebs9aqgwoMK+sPR7JNZOYLCKr2i9+4Hu9ebT9XT+XW36zluLUmHWOdk361ax4dhRCJnhvjuomqk8dS3UMWnxckWkk16unZXQ1hbOKzzOhzIY6YnzrNVCx0MJ3xrHmc2N5dVPvZOqIxOj7iDxETyFp5zbNDZ6+wxj+lfjKNsYEnT9ngmazUC4ZU+TjnwoS/58FSDVxOY8NBHcUO7+nv7Jfm3NBH9ScbS7M3GTRyG9ssY8pieDCbD5MEGPzE5TBNbDnq4ugU29slOLuv93jCSg/1aIaj2gezOsCwT/kk5+L3eOwQZChrYs0bTYu1H/JI5P1f4tha7iQZohOf9XLg6jCT6UdYk08v99Ty/poA7ydomecDpwGlWVL1Q7T51Dxe9cjfPp/1eZ5gNdsSo05+V1PoZiN3BlXvLbM9V7mPRcipC3Enp/YY+mkv7R41QpKxubu6GXafX8xHneEWs9xLkGO5cRCRld+msx4fM74489TKA3xg9NOeswDDhmc0b+as+ZwnINoJ4XuoXL6D3hCRE+p8yEtpvhYAPIOU+mzO3ikq6ggZjgoyrKI7DUHZOQBl3Seb752OXJvtnkQ2M0EeR4snWFXldpRT8OQxbdZ7IrJeHDa+eSoEHQoaYtaAXxv8c49AX3m2EOLWP71hc4nHLJWMLlofddYnVxa7PpPVeA0TkUPG8uDmm5E2NVcdfA1d5mffRE+dA9OU+PYP0uGZ/rx9XcZWMFrowVUlHTentyxOPzrH5ICQJ3M5nrpiap7WVuDWdhXYe5wDI19RMZEPe+AcTg0aCZoMuw6IFrpc26biyQMkk4gcvrM5frin/YBK1Jl2+xAsR2tkvg+mmStzCcyzdbwdQZv36HIkSt7k3tpAb/2VAbmEK31U9RDvpx/o6sr8cFmfaHMplf4N9V0nghpjx5bLTrW6L6vTY+tXr9y80w5Za/KcHm5qtr66na8N+361dgr6HNSw+cGguedacMRH7H0iSJJe3AClBnsMJXVhzBeoPoa41IoO/RSPJet3wIVJnMTxAsmW8q7jP3nW7sWv8fWBdZh7prM/p6bEVmPrZK5v6iaqfo7lkDXz1lN/9c8c3OZuderG5gdHSfZFrJYy9GLVMBxThT2zSwHefnWuuMXnaB3k5nP79VHLZhNiYfZr6m+l6Jp9iYgzn0acNeXywd0LbflgAmwkOdl+4XY+hblv8AfcH2nnf8LPj7fngn3PZ2v2QjbxvKMaoj6OwDb3XevtnoKXG6RCgolI3jXn33fz+968UPVz/n3YV/0RwV9Z3/q0NZd/lC12XzCbCkNrXRw2pnOUJcEuOqPo6gzvuye46Rk2XyzI75jzKxztV3riBXrO8/07CMGDJcZzn3O+n9q9iB9fL+jjnBhlrbQs6AsYBihm/DrB/suyL/n3at+Sn32xn2iXrpzENSjx1Icu+rZkWb/jiZpALK19fX2cbpx9GoLjH/LNlQ413/BEwEm5PbS/WKOn7Qomn9e/SaIlHzAg3XPvswRrNFaAyKA5Tv2Zb0h5mhN/z8PN++81GEdqKOMaHnsc5/tfzK2NjEQ0zsfXUVEtPV+2n+7h7E33c3j2wZ0+Dd/WUv6s6K+1Tx2TevOodGwfNRxb++MSQLjoc5/TGj01NePe7n4jyyfr2fYp4Un5Xe+lT6YPITGecwQVXTsbPcXfPeh5Qr1QTY+dxyZ3eTb8XLjCTdTmt6+kR2c+7GP4WNOHsZOhuSRwvhwXF1/2a7HNM9rYR9z5+hdPLEXhH2HoylQuNM0wNnb2ptqCGY0bGoNTz7nlID72O1qv65DCsfG3HnQll3Fbl12K/eUidPngub1S+eg3x/DJO8lvdRjKa8iCWKwGua8G9wtOuabug9d4PGBendIHS33NGh4TN86UmWoTsPuURT6xu0cDbJ+I3V4xy5hYplWAnY9ZDdfVVnv5CQ424O0ffAdLP3QGJeGzD/ITbQLjn6yjICBHeeA959OT82gFWzGjn3X08HgBSOu5QEdo8U7wK57JjATtE9aKK4VCApbTDDBlYJgNszBMyVwBkAEiTQVxZLg53wsXp7t+cCxpKsfBDwWWx84clBXqOBu0OLzDtT5PtoRIHT9jJHcS39F8PEGEZzp8/I2+OVibD3IH2uCDOjZpaluHSPo59BvRk4o+LNdyl++yNnDra77JYT4zyeKeuHwcdY8/C/oV/ds3au4D+hUIO3vvcR5woVkNVzFWRvUUH36eYGVRPZmffM3bkqk8IMnAN1/Zyie1BpnV3SXPvAnZ/iXWZ+MY/ZwaReXGJEe/aUkZ+31QWSk6SmRYY2Gib+5bTDwht07cA9EHcAflcbHGk9vRBfb0MXxZGI98l4mFLlYn3RsWM3DQzyJY3Dl2+Bx3H1wOKYeTKJGuBXDTfi6F9Yw+8vBuXt8pLa7y2UdDuT3DJ9k5d3ynMVZVSVwhvPP03y7MV/+t71A6uT3+Trk6Y/Nok5xaU4VmSq9SyXcXAI1p77jAYMh+UqRee1v7dhg37wb6LuTmZ8PCb1cCwAe/7nYBSRIV0/5h4uJu313EemoND+t9RzF9TxDtAAAgAElEQVTT6hmdlAcnHPSPD2K52CNu88etf4DdG/C8mIJA/DozIWxiteuOV9wkJDGhIntusNYLjnrA8DnHvjNbffAytk4gO9a2a4/x+2sW1AVYTTc/iTCZir3OXhweHEhSHaDO0U5NXliTZDlj49zFtxfpvOhUd1iyx70kJ1+Fa0HjaOt5Nj0Itec8R98RzjFvn5Pj28Rzn+EnML584fFthGQm/3BmmYFvcmLvZz1Z4znR7EOG6MfBeba6gQjz2H5wjfktP+POH4Cj6oZyzGxw1Et/4LHW/LQI2ZaXmJ2zb44Y+2IGRyzEEDUanG0cnu7DX+kZXF+/5nfk/UmG/Ou12PhXZvyLM3lOIfRcJWolTTOU3LRGXHu1TJ0Bd108t6cH5JAgOTNn//hbAGVqIKm57/W+Uo99S5z9Cvpoon8kyNhjwjPPakDNnTrBxoZfGal9F9i2SMIA2oIxrn5Iq6HkYrHlw4s4QqWSMTRFnJgst4YiTKWNtAy1d6pOCXszt0il7tVS6f1ejJZqIPfmkm7XeyR+ePCrtOIfe9ioYcVKNGhcsz5uDfS5uQcZXIkXv5HWwOMM/nGSjsLh1GR+MB23pljGV4+Bg8phNLCP5UqWhXisaveIEyKfdU9veVwffPf3UjPDtX1ZDs8rfCaaI0bHkGWOZXfKSjF4Pg721LWdWw6IOrd3mcO6/bu90dhzUqGEJS685mVKZD/jvH6ND5ZsfG2NNjH+1V37+LFOAH5TWwsJOmrvuacFDcSYZW9RUcw+x5SrFPIaYo4pwsQBAJzn3feFlTfaaoSZMq5yDbm1Dc3m2/08wO1jDaYEi4bBQupUSHGbrwnHNjnIaE/rrHV7h8atT0+R3UMS5TM1txKOO935uxczXzEr46l79/jQnNwLjudQw9fF7pnqlBV7Pj+1T6y1BWTPyIT6cMW+f5mlJ8bmjKMneJO1BUNOEgoiaXAraJPXEkSS6Z9iScoJphaS8zF5MJpJgVahf/MaK2IFmt54i4J3/FVMsvLssZHBuXn0Kn7AOogfzjVBwTfth9tcsTdw+TVM/OigjliQYKusqzjtTSr3Gz1dWKAoKCTPjZuroSwCpyX0in4SdHqRtTHHt5gJ2h5NjW+/m/RanLWs06hyj0BrJN/IJSeaPao0qw2d2eibkgSdOdoc09PMb76pA79UuSHxDOufcGJWh2CgfMPJ6Pk3F+koHY6HamxT13C2ChnKUzLncgTnA634xqKzunLLN6AM7x+p033Lmou61ycoumKM5uqs5tgw5+PuC3k02ovjC8n2YHW7jgT3xnOgc/KpxZ65INiw7mN1g4tV32pnqbHfYVyoQU2tUX3xuLW5H1pLgyYYJ7Sfe26NpG7STBixBtevxuy+4j19Yl7DTFwQwGe1YDrjqXHyqQdd+ejlVMALA6MPrkz87F7YWjkw10dOmMbiDAtYX7hgEfePXNBMfYT65772wq4kIM/YfTBPrPY4R9+JnCxg/IpdBeFleJi5C/Irfv1zboENjheBfCELkhlKys3+ikHNZlmI9bCgLrKeF8OOPi72QOQmn/tCAlq46OS+8aP/oxsR2QvuR37OUXGx5/iROW7wFc+cz+KYn55BliEcR2bd81g2Bm9h2rT7zHf4IBisOaGhL3ORTi73IBqphQ8/0e6ov+abS2QwvOubJssnZ+b86DZzes8LF7yT7prfsaZuevXjL7Lj50Kwe5DUpMiN7eFakcfGrP1eTX9Hvz8Bg0TWHCauq3sL1w5yuJ4YY8nFz+NHB739Yf44HDGvJta+KIkw55d3c+BhfjyTB23UcXo+msD+/e2vH/5I3i9/fLVv5PwrfxOA39vHzzlJXMcQzsoDyUzM6p4fNRd/ohTGft7aiKJuX4xLvPeXrLcKyjV+NRwDkYxEI09O6mdaHbrnpudtc+1D8vaNBKtxtTU/gtcD0QOcLKdm8upe7cTtnNgylbecu7+fvNRAMY1AAUWxf/vCmHnIV7H6Vyb4rTUOV1C8U9ff3diz9LZ7Xn0yZXr1lKYZMmcvhvjEJeWt68aiqay3J6tzWeRSskmf5wwjVoK7u93HPeeKKddlNCSZoT0jxl0vW/cudkPHm/lZMsmwtrg3TltuiCg2eugjjlhsUWbDOL5ZZf+aj7yLKLgc4WqR5Q7L5S6OuO0s5wkJ7xoJLeKwu5x99rEtmIzjZ2JMeakTr3UDtMhzwHIHcXtOjpUlFLiIdQ0fixjh33MHKFhzDn4CGjsE9iBEq8k4AssqH1QOeDI4fF7QR0GMjRKSRVaDx9Feg8g4611iD9jCajOHHNu7S6cP2IM3eYn7vVtQbtokz43uJY47lqs9jH0M9i2yqLNxynauL9BWEy9pXI3WrKFhHAzz6UltMcg9dsBZn/0L1txjWx4Y0bNczdSEqwsqhmviRwVYdMmVSf/NWgA2CQ/uufPsiWEiXKOag98EEYGdYSyH2o49COTekXWcezK0iBXVqKJbYE9KLPE18BYe8zK3JStxsg++1uoyk3QETyNViH/iZM38o3FUgJ/g0Ss8N4WOd3TzYJAB5/ZPOPHqwlceOWNrrdI3dm3sz4TVkSXaDg+JEMHx9Y0W43FmZD4w8c6NHb+KcXWt5uH2Gyaq8yDaWqSAdKixK2AtXbsKZvIsN1r+63j0gGD5YidbQ6El5zN6blXV9mjdfOPHdp+EoTfPeGLDXn/Q4W2eHONvjrVMzklrjkF3TizC4A7Xi4vNd/845kkhPmPAAE9P8N8wHHcfr4LJYZ5AMuTZnjasdp1wu/zExYTWExtMc0Mw84cLEnphjIIHRa1EmiPzXeOeIWPsPXc/rLu4yJxj4MpHa5rTFLHvk2/2BpzYJPC4LHOBsXviO25wZvRH7qmCBTffD2qYnsYFhPfXOiNRPsN1X1DBBapxHFiSe7IQnDGYLtqmgKtxfRw7jJ8lb/A5fR63Fsex2NnLcZCbi9vVElkjsbnYpnJKkBvic1u39wdCHLHBZ4+ZB9S/ho2tF4iQMTcJ/nyQU+x/4fTd4H2s5K+JTf+IoR7uI30nOfN8sG+823nePS07HXQWcHLJMjc9EIe29oh3zmc3eUKILoZCO+WFDS6ehlXfmX9CGxB+wg/J0LZuenD3gPs3OsD2qLDOO41r2EZ31+Hx3eWc/7ko5w/N7e+yc/SnTfIL5/h++pYfdz8/Os6ekp//O553ab+s0tjYH3PRhOjhPsPggIkRP8uaRmvW8PlYRlycKSv3SwLq29p7Fsytm1Mtfcea3hhBVLWQL2lUxDxfE6YW0KunwVkFAG4fF7gQ3/9//tcff3hhzrvhX/3d/Gj5+68f/vzj93z9GttX424fQsc5WQHOQ31H5izt3VprMATTLMWskS7SE4vJ0Y/8DYH+mkHPiWooqf1LQ5uH6O4X5O0JHsb0kF7JS34UVIcTkOQeO8uPmgrSW9RWADuj/a1+VrUWtfPmrF5iqldrIQ8//nI36s7JcbRNPWLVH9Y5ShBGseKmD+TNWm1zdJ6A7U9jcxtdp+dqzM3wj2R5wLOmIm/lrXLjCcNHrPvwVkUMUcXo2QKDx2tNsVX3IhtD7P9vdJ/DMXqqr+gqwEIv5hgj9y2YkbB9qgh8V4MR4POB8ka1RJ7/1665Oay79dT6YtBYq/mbvKyxk2FzANx1j6Nz+8ORyKn5ZJSfiEk0LOokB67hIJtZwwEaxkY2lhg9MdIjBwTgzUsQERyCBSOsGD36Mbb/A5DDQHIM9+bb3pBb2+Q6OUdXqYOohOFksfWQoevmYjU1reetIzLXL+V367J+Msp+9J/qTLc9gRONrQeZu7cjIn7H8DCnY7VWr3P03GJZGLY3izdYYzISw/cza7kaen/d/QZ8+9Lkjdmahy4ulAX9ndYxN1TE3ABXGHyN3kz0hYH17RU2PIZm4h+JsxBvIGqgm+XZEgrQk2yJi8JYF8eNnMlsRq14FQNRPk+zJe8mmmN92PVd5rOOa0hO8jX1gYNQLclK/p7sncaOKRt8Tpast66jLbAyzAk1J8RKOviRIlgM/Zoc+OKQB1PydN5NUUiwawNdtWCZ9ajOjcWWGPKbB16flMoyD74BqYGg2uEKUjVq1zW1iSEfWsYmmpvlmIoLG2+5NwMuK0xMvwngydcWzvRoiGu4TzxrxtHuoutMVzeU8HI4OTEVkcP64g1o+8dTnXNnSC77Z9jOgyckMfJmYipWGkxinvYpitRcXrkT4ZO7BMxjQ0ONDx5jPntxHsw+WccfLmFOM3NfyIm1Slw92reeuldvIqYGo9A4a+Id2mJMDtk5Dm9VhMuY7c0GQiXryJrVxB9Ug7tkvmNw2/u3f4UVuyGe23kS68cYN5bjzlc7aco5CXPRsF3Vfmoszney3laTnoZkkI42/dcRe129LRYj66k30+lOKTRDutwC5Nk6iPCCmguESc5Bfyb7DoK1COl92gRZ34txLAl0JC4nxNCNbejlHE2ju23ueUEQFz3EejFNz/ngGI17gd1zfnQm77lITzb48sksnz2ftl5fKKuTn4YuJrdclHcf4+TKj58v4N/0KS5itrR4zn6PzcMzJwT9fG9AO4vNL0/swLH1wr15tsfE7DkkBmwjSpw1o2WAZjar0cuKvfnGH/tLPamGkA7EBd86qHvNDyamb54T9dH3v/7684c/c5H+Z/6lGbrg/yl/ndy/4J7Q84fQrKuK1E/+fKmQXpA7sbuHk1175yDBlWNV9Vyb8xWfhEKnFmwxkj9mCHpBz3RsePJ5L/TLDhU990hDaoal2k+yyREkvzrAixN8/ZmLcl60IP63//OfH375z69y/PH7Hx75dYMvvJiRd/N//9//G4lZf/3i47IdWf7p+dGxdpX0xv2e16SqGfTqv/O8hOXesnee9/TAc1uwWukVr2/1e/q86CVbeNKHfl+dmqcnJ+doY93R3Nwuph0ddw5FsJ4ZvUZDPmC5/rvgPLXmMe39z72OzfwTXC1lWb49Blql5ns1ln81g2O4psY9H6w3a5+zlrWZ3ttbQ+/PqQv9xuIjvtyIsb/jhxHPwcSwzPq4waC9HrR5HyM0Y6xA7kB/xmpoj+p+5wRbWlxvL7bf7NPNQHx35ciaPD6w8hA6YjiISfw9ru5qq+Bk3RxwOY9tuRp8tLVujabafqPMc9cJNBRWMbcW5FXPwJ5DOLMxxiFjcFsHwPatnLsHINe3MZt3e//6hSO/xrmvkRu54Rr6QWA801sHtp4z3K4WtyLLoyMo5nd0zi0SKqPn6snjHkyE8DDMY8XmxHv7HtDs2ydvOdqz4SPh1CM2cdRcHSCXAVvrW9zGyZeA9uri0MP9antu3JvLLM1EVxhiclyrtomBT21zxMcotnkPDzH5DLR9AdgURrSuiV0+8HwQZDg71SDszDmeuoXFJt7g1Du4OZJ2+cyZGEdpZwpvRnh8HIqv76CP0YQj6qmiQXwDnwYBX5E9XvTa4SIZ646b3OZitjAPARZXsyXEnY+3kNUmcR3rNkc0lmdzYp1ETreJwJ58mR+UOW68G3FqGK1wTWJrWZ3YuMMcUbNJgH1Qu7ylpCeDmSCfJD3cTYVhta/uHiv38lTY5LHG6aE1Xlzrgv2Oe4LFCz40W8rZxxgbOzkmfHEU357gqG5mxBsXk3dWjHnyQ852AEOGOjeSGGI7wLmwV9X4qbBIOeVZrRt/VA4jh+aAZ88CZxQ/2U33RDAlx70YipYBWWP22kyXggCNXADsRboxmOPTVuJmMn+news3Gu1v4oAw7xrD5B2cvAnGzwjCW/HOsBAU5ief+ILN16gaygRXtCQGqx7qw8kCTQRlbF+gZ74x9QIQ5dK8MUBVA6cIz3wz5GytsBfbJ+tihh+oOcOBxu/H6sFeLcUovyJP/qMDnvBTU+se2fLXCl/zoS3z71KrN7btAfgdhzcG9RHvY9kiPuP65B1wvpKMi1k5kMma2NFWHXg7ri4woOhm+TWwCocRE6bmfWs0IC/MZ82cnNYHV+bE0wC1rDbi1DR7xjuDwqJDbPZ51wiJrXuFnzVGqMnBJF8N7ZHF2BY7IYTpOpONCzBsmrnZd9U79/bkZQXUXhuSanJfNj7ryC3EObUHPucumnVTU/am5wkWOCaQS/aZnrqDwLY1+65+vsHQc35/mt+n/oN3gTMH84XfO0cFyYkDlxcEyOMaTfnr5ej+kneNC6024u9oj5sba/dSHoioGi5oFd2KMGBDZzGsw5+auXjmr8nHwk3P78TCthw6sibf5h714urCQkzQ4enoBS8X3fSFi9+f8j/gf/2f//zwMxfd+ZF+cnAxzMX7N370nz8Olw//SFzw9PFb3nWHnT9aR3/IwZovU1HLzjNz7jPk0auvorjl7CKv+1cG94SfOuHFA78XBMcf9duBpvJmFpxZYmAvb3+qSYFNJM5em3Xzrv4QSNosTrkhKsd378txM61+4Q2PwvJPSbW2bNMYPWucnfZ26/EJqL4LhLdjI+gFXWxPZFJI/ELq40Rwfye7B0+O8YcUv2P2Qx0xlBvfcmZGLPzzGFzNMSS23yefvESCzVhpXQQzujgCac7MNkBgb0SYIiyLn/z4+JC/GzYpwDJtnwD4vK2UnjP2RZ6JRxN+bhQ1qta+XGqEMF/owe+cOIUaL8XQ5ZDoauF46iBuxvJwZLiuotySrzZ8m08uDDPArc184V/ept0am/fkYLnSJ//lzGz6DWhj5M9FVrtUdOerYBjgg/twuMxN+1a+Yqmc2tbGmrH1EpNVvnKcuS1kmY9WZcAnBo9h1SYu8bJBsPPFER2b9ZBnMKyPPRjg6+6iacBfHFmSSxoCCPwc27daEzsgjmqNwx5sGGSOYsGYBTuTDWJ6tIx9/PIZSMz0IhBH7NWbFfgspNxeYct4db9aJ8VIGTHGQleuZhyO4Wufh9uw2QNNiUBUBq4vNvgUN0lMKWZuuhFraXKwJVqh+LvZ1jrNvslM2eUUALo8Yz4bVDsp4qHoM7LelxUNenRsYcH7QDp1rc5zB7ghZoe/F41pVDigLZZZvoanKuZkGV3LqRRtm21k1wGjX0TLl2+4oZX/rbW2OIRxZDIHuaAZA+EZaNhNPXsjZHIkjlDzxO6CwIxDOYjVphNshrGTo6ZYRsPmPvzBf987OLZPJ6FGuHtyTiqQ+Yg1ddfGbVU2R5fdJUgar2/7sHuT4+LKAD7jUroQE5uZp98F1WaMSEG7rGUuxu2DnuphCi+p7FW0eQEARZ4ogvfBnKw8qA/u4Kl/6sF29GvPmvMnH627AOdOB00tjBxCNTc5ZI1neffIueY+aZigA2wncTG2rxDvXmkDn1HtwaHB5J1vfFG93fz7ggc6pImDGsnGZTrzXozj7wc2MYGpg94u+YmHgfjBrOZHlyFZvxhs7tMhxPLUwzyPReg2Lmt6O7RXB7N8TlWQ1Ec4MXNBA8v266SEbPrh3kxwzSTrxdBWXUzs4RUaoH1ZURhnn6snWU0Bl64cN2ds0uCLLedcLxRYZi9ykVG67A8XKmB373Jcn8RZEGPOuPad1L/5ke3Epos+rCeLcDuaBTH7MSXpt2/2i+dVAAk8B2TME66e08U/AGLzMWE61JYZo3ZIOvN29WehPgQNxHyCsDHBcQd1eOG693X9vSgvhaTWu1H2K8T2ICAuLBnsJ/n4i/B/5J3iP/NOuv1UBBd8/LGx4PITB7nGU4rnQK25AOVfr/2sHnPTP+vsiyaL9ZpwChSSusBPGtl6I4sUaO1gX7FnjNtpbGjlq2mbm8fA3g+CwpSY82RXyvLpglcbWvqCxV6c/5iL3d/+57cffvntN/tArQgmpL8GkN/R/2felwgHGpBH/J+///7DX7/nj8fNhf7XX74ereSzL9zfyDn5j2ZZqHBGSHsawE4Ie5F3xOXmXX7+XkAfOyxmhQQLdXvHGZn9D8W6J22zpSjOw+qqx7hMG58jfM962JtD7p7JAyofdhHlgXmqGCuEfHoTb8fFbZaxj3jxo6X8Zd14jnvOO8+N9Xssp+fX5o6XnCOKWUYi4v+ep1KDjxZjMGxTmc9gdjhnYX9jP3227wApBvwb3/npP2KAekvI3S/2Fcdigex88a6zaN3UdvmY146C3TMia8emQPOU0fis1SxVUZsPDcZwkApwegY2X82D887LALy5xUydBZaD+K1faScp5Bn2c2pi/VErfow3b1c1ktt+LGiP9OjMNxZL4gg1NTdZzLyrOrnd0X7ParUmbuuVQM3NKM/bh0l4egDV8DR1tTYubJlUxdbAsTIJA1B9u//jzIFhPI+r4bnnCmonj1oHaEDznSRtSIKnXxUZZLOagHD5IBh14ljPYK1g1sGghxtX1b4h731iu7hYaQwKBzSrH9v0Qp6xNx4n4+nR7snE4F3uj/jFmQuUaQ/23Uc1Jtj7o7gEBbkatgb9r25Jo+2xvZh+p4JYYIsuNYY7SNQkluAcor0Q3s2SiGQWFYE8IXmSw7GisZdt8k86xeJIKFp2bBEoeU/sYsLKhFyT7+Jj0sVtQjnhpvlYrGEyuc58YyFlXs3onXlyLWY1mh4+kgwHccagCYF814YvfTm8DVCjoeMHp2LWpcQ0ekUef1ebu6vd6NY0eAgyzG3DXMgbq30hmbECZ05e9YPKYjUNH/paJ8EEfo7bqzoPRM7WeX4sZGwwTAdCScRonyP+Wtuf9nNQXMDuuXdD5dg92ei2YX6UN4z8COKeH+YIwDIVnWiPTa4u1jGe82hwKlkwfr7QlCd5mLu+754UarB827M9ooUOmJOFoz3Bs3bOuB131vMNOxn4cr8wuJdE5WPmmFs0k9E0puocjo3dYzjQIU+AMbPqkfXD5vkE/TPEgiJwvuDyC+5IIQNd49qjo9WUb7sQT81C+s4n8fFDkgHnDm2zPjyLC8iLwBx5Qt7oRqqHOHiX7CSePFZdOdYUXDO3V12BrT51Qewnu9L8zJhXVusAu5lPXK8MrFN/AxI5I7zDpBzdTTf24uDlfUaTJg9c5ysXG5TdH1EvxvwYM7gNZW76AgKr9ngdwQSU67Qc969X10Y0WHT12FjuO90b2YAxUVM84jFY22NXRm4KRxUIVgzWPZzHn+WoeQLLa/Tk3TjDI7ac1bEXxvookqvdPPvgwrTvrN/HgPKMDheoKp8X3rG5j/8Qgz0jcN+JzUU7f+Tsh/z+ft4szrE8xXFuNNacWfDYxgU8v3edvzxobd2yqHdC5u4rLyRi4o+6bV7ZJ0dgtZfAuHWVqzy9MA1HPvoiXC9W+0ICfVme5x69dZJEZs4VzqUd3UNS+2PtafiXX3/xR9l/+e3XvAiRv3+bi2C+uOAGw9x/c8eFci6yf/vPbz/8lKb5v9XTjq+/fs1F+h8//PF/c6GeFz7+ycU6/0+eXxngQt/v2XR/i1RK1jPozbRQiJ4Y+qP3fXcfm+/yZ7KcvKhAL37K/3inP5L01RGZiYH7gz8renz+LkzmnjM+ww04QepVkDRzc85SGAQu/2SQB3CRUp19PtiI4f7COa2N/VJD01xcMCwyPLMy3/sw0nq2aSzuxRrzb34s1trMuSWojxlM6RNDDEno6bN2tXqfI31XW0KsxccmcjVagfA9o7lrIN97atx+wFBh2O4g0faA6fU5A5vQU0cCmTuwx785tLNecmJZCM/N4/M5iLjidz8WL+dnIUs0UeR2OvbtUW0+VpB/vCNCrbXlXBmCk1v0RCj9JNCDHCyWw20nrSuOXQ5DDWjY/ZVlbj7sjaQT3Xu7nVXz10Zc/HvfJKTug+s+XBW4t7aFmwOqjLOPT5+IKSYRWRwMC3Gx8wnQwT0Y3Vkc23oucGvB80JXn9zTJ6OTq7lfUuZ9xNhbksKnAPWhJd6pSVduzJ/wj3oIM3pyhejETf7tRauErWWaM/PD9xR1tA3ffk8ndmEcN9Yc5LOJsZ+SM5k6VpcYtcGGH5arDt6NaU9AtUf6wJ54wLHWsQeMciAD7i9NymooOI6w9Z0kT/NBKzxMhkioMTczBGU+3CsOPkYzOu3N5NaeO8M2ps4W6nxwZcGSiHyWv6yreTFYmW+TR8LRsPh/qUpQGcmTIUnQQ9yN7kkmR7RVRwHYHKMZNmJZMozxGx2eqmR5a5m6D28lNHq0/cuXBOSQr7cnlzkneovI8v1m/rnviOEzOjjmS9qhoBC/UWgOtiUQYv53D0/vH71LSBhjMas6UJPajwGtj1yH/9UBPx9bX8TAi407FXb1Dd8/NJzcEPpZjFr0ED+I+WY/ZvHMq6886zO+gT5JYO07LuR4n2xqJxZVhxKpNcHBuzbRjWmMQd8ntLWuf8OSjx40yMgzlbN9wMGyT7iyUAaGTMkJxwxwgD0XRu+y7BEovaze28vtUS9QPu3GhPdURJ6kPe/YdglsBgAl5gZ9CkOw080vJrybmzWcfIDxAhTb1NjzBIryG58b7h/nfKB+PuTlwqHzLGGayOZ0gSR9w0lPL/3kxsYFCMdPvfvEgJzzSaLWsESn7jgm1825/fm3DjxT+nQE3lLQG6iKac+ydBwbwfna/hF55gn+6LsaraIkktO7Zhz36O/zal8QSVu2//TG8sKwe2ida1Tt0MfR8yf8E9eYpiAf5w4HL6BhzudiBkWoNmCGuGYxe6Vdlsbv9Agrbu/7eWvbPYaPsfvaBeQl8B13k0cRuQT0fPOP82nhBcXsVM5pLvK4GPZP7eWc/Cl5rCex1qSeXIjmf4B//eUb3/yPDvhJ23ek+V3p8PITEknqizAKvb33p4Biw9d3w9l3QfbLC02yxt/zIURbQGBOc+OPn2dFvr0ALwyyzEYzzAa1NV2gGf6svnJxnnfOOWL4xh/Q+yM/+m9+Lorzo+2p54///f2H3/NOObr/+N8/fvg1F+m//PbLDz//kgv19M933tOfv//8VT8/9s4F9S+/REv+FgY/ebCa0HnkZO5A8gg1d/bFPZkXCtTwx5/h4Ufv86sGeZeeC3R//53HkZAQxx+5a99a9ilefuSp0G0AACAASURBVPImM2AH50YXxsdm24BkcnieeROVzMhunvWUqcz/Ld7cw10ZjUADvq3/EXjsG1t2hOYrXGg0V/r18VxkIAHoB8uQp1Pz7Zoy4Pl/dL2NgiM3rqw5dtvt+bm79/1fdM+M3bY3vi8AkmrPYVVlkkAgEECmVEpJpQIPuX0wYAKNqd/U5HOZPWKEQRLghLBjub1grsUczGLJtzU8McKysSfT++VAn7wmL917MUEseYbOiXXhwDoOcsuvXSX6dUMweXEfb3LvXD3TgxZBCMUYsDvCM4jrOP0WceDlhV+OkpzzL+e3xyW7U6s9nBqIcay+zx7hvbWyGD+q5Ew+KXrOO5V/9bVb9GRH+VhnNtj2Zmso0krchPv0a3tVHWYJd/3VsHmasduPPNOndqo6jamkqTcL10H1O8sC2NpTdvlZO27Kwd+qJ9B1NowGBPBoHdvpiwkAd+KvapYnuLyEMZpvveHN1+Z3br2gEuGuGOmGoLqJG8IlZ8046062zjq79bZIrow+vMg8wHNu60AC9iz4cVrO1QzsL2OOmQKXc0DmZR77UGZRHezaP9b4pzcUMKOe0ZXFvNcrgLlIUSkCchJKoBiiCe1YElZ98Fi7goLfEzAEhp11YW6XzYZhQQLF5ou8FNgxSHQwKPz4Qk++aGUUwdy2jyVra/hsRhHFEqsAGa5N7sl19QYaPtcLzd5exWoNaDpxIAWQJIOThB3Bq3SJNFlTZ/Hr2uwyNfdolSVc27fJVo44q2syvbqeOfLouiNczKjdKl3EkCsnTpH3eMs+uVU2dVFajyu69EhNzdIRQxNYuDGgmLMVefsIPtixiiIPo2nbAzHwYyXFgHZfcPX1vBlecNOTai+zaTPdXAjQxobQbqYvFUQ8s3cPUixhQ7r7+iY2C2NrXLk1jk3AzoPgQTVS5Buh5j6iAU/PnaaP3+FYw4HZ3gXvnFrGVzsEjOJpxvrFzy/hVnNl4zNqJrRgNZgIxgNy0fXisic/n8bNq9leGKA43/TD3CSA+B1ZLy+Y9qoY3ykR7GrdntlHIHDlxydTAM0aepdj6uL2q/722zP2SEoUHI7oytddTR9jWL0DfNbgnzjpUFI9fZfAroaPDJvTBtx6QeLatr+e7zUEaZbFs7JPkMwoT/XUBGpmCaTefScDVuf0wCcm+JUzPXM/cVy0JJavasBe3s1PXnXhIv2ktQbnjVbfrIHuEwM0AK5XeedXD87mawKrIel/HRvdeCDE8pycWhH4XejWEqCMPefKwyuAic7vgodvnuBbCXzYGRd//ou1hOV1Xy/c0c2TXj96oXpfuf76S15lDoevaMfvRaR/v02OyJu/20YMOLi5cFQntcCXPWrb5yRiQayiqDdxeWUfbX/mbeXgfuCVaOLiK27yYTOOjIzhTgHHTorw00O4snNwkcvfm/+UV8Ax8gFxvFV9HxfwSjVa0M9FOHzMuVD3wzoT9Etsf+Qi3rf+B/NTLqB5RZ4LfS7q/VdsOQ5//laMUt2MCLV5VoQtX3lMwtvYefXczwsID6/ef0s82uk/Tyag3b+T508O4E+v/vgtt5No8B0APPliiqk2O38Ppz/koeWM243pv/2JP2AwRmezeAyNn4Z+8Ilu3zuV4OAnn8c9c9swuPKjKzOpZ06+PJipP0GZwec54QpbrOmBB7hLLMVgdwyf0RhG60zPuSKWDXyzz5THU+QdS7UHIzsb/UaJG1Pn00uDJYiXPucH3NYMB9Ux2GofzGJ1XkA5aKSxkzVrZ8S+51qtIQbfPOUjmH6Rs7lZDIuWgw7Ax5YLNq51LKVP2A/P1kMeOMpJ+sR4zLCPTgCxFyc4mx2rGQZUPnFnBX+io+loxEe93JkR9vKDNRm1b70E3HH7V8x6jp34jNXEHq7XZl4wcy6q/uhAMTq2H0MoQ+WxJUZuBXPuFGBJBxtczjX7uUmhJtaeEBcM/TjxM4FDe9enhsEu6ryohgHOfJkPnIMVesnBrLrHOetlK84IdPm18Y2QZ6iXt8dq/VMKDRlNTmYJinBcVYOlmmofrQOyHrUMHbwyNL69uzZRe/veHsQtTzIqHY7xfUSSB7v5VkDXilzFhve8ao/iPTFFtkjYceVzZc4BpPQkia1BKiqZaPPeJnjDGVvLyCLfh2+LTPAWCY+p2cwd8eLxUSS/2LgBYHfN3iAQjSetyWDDPzcYzVn3BGAVn8bJ2+zTzE9dwgRTRNnbjCHAR7rs9hXFpDr81Oh3DrKa7GUB+R0bjZqHLGv682p1PnwQh2xPRG9MUJ2eTo1Z0xt7OE1qZG1I7ujMnmpobqblPFEYWp8aGs0jgj0mH8eFeIp+9jIdnasA64xJpeaYNvpoS2whrX/PgVR07AZF38uOjqNN5O0BhwSsJVVgxTwEzcODUXiOMPuBYc+xewygKMGHbfTjPanoqfbwZP8x9GGp/SM1NcGCINw43TEZe2Z7DCp8YGie+N0bi52ccNbQfbZYmqaxSl2YqC78xY2T5eRxgelZ37yw7miWPf4l2W0xnt2Tt5aqYr4z+zj57MDM19+4bMMD1ou/qfnkzvpNU3sY6M/3P6HighJC6uqcLHOe+qb78FG/OJAPe2zetxES877Fr3wYTeshJHyk1vFwGlwrqc9oTHM3trnR4H1EkFWPnQpgUgjlTt6pRUjmIfKHLA04uoBsrfS2gHm1NEt6UP8oHptUJJzhhVPmWL4Qw1w/F/N9BZhec/vbY2LocGxmA3VkM0Ylm3dM8O8FT5yvRkOXjD1jCNxlc+qhXuIDETp4JOGaZfwgelGr7cTMOUJd5JmxeiKs9vN7kItZHplm4JtEPMHg8UlNXGDz8y2vvP6c/3nOBTX9A8r/Tuez4nqhnLeC/+eLn/zOq7ZcyhuXT4L/5qfB5zzPK7rp/FzMcgx+8NhwoUk+Ljz7r+6iJRe+jC/kyn7r4bjSCPFcrObC80te0WcNyBrAU48X6xv83n4ClOPiDY7RulMXsV7o5uKcnL/lVfHf/v2br/7vxTg5ePs4g7hf/vzFV6w5p/bifT9PwRr4d39c1OfnS94uT5/4l21e9KfXv38jbzWRkx77a3+OvK+AW3OOR+L4lH0uzOkvx+Xr17zS//VrdYf7R1+9R1+IOOaJTcP8abu4XWxfmNEWGtO8arbz9QlQVAA42YSIL5eYBGEeXvaYNy4rfcZi57s6gBEO1OnG1gy0Q3tXHAPVnSDi4wsmVM6bb5VNPjjO7QAufv4aUztp/+qTX9f0cTiMUQKIrCqk+8WMRsPDTQ/4RivCXXOqW2tQ2AHkp0qATW8hybiILIAac/fFJ344t+/2UBtBxZdLkrF1x1bU2+NYGpkMw33QrAe7cWKwZRTfOVs1xqclsejYsfPNtryANm7zV3/5iW8GJpkNr7ZZT0Lznb4Ebs6PGm7/qxH2oKaeampe/EcjMFQCzXnnanjPtQnXKPK07lNnxGHZvjV6ckze+kwhdzFsrSAMG1VN4B2PnnjEr68xl6NUXZctW2mGa7K9/YNyc6sxGGp8523K2KgndNRLjnaiHDuPGUj82cLF/drkMW56QrwjtYqXuj1u/mYAs7MTMxlqRwvZGvvxJMcEbj3ms4YqdG1kZhxvc90s6HcAh5+tuGbUp6e58TFaz3R2bMYOx/cVLac1JD7/EbVwyUZYqbHQ1x6QTXiETXEKCM7WTiAYx06Gt2Li4XdRbJtnFZijCRp/4p5CN+hEwzX5G5WKmrhFZh4eRm+EmfwXjvpGE/4RpV2KPWgysQnfENmLGKamZp9qqUGuq+H0cuKqE3yTbnpzHCGsxpM4H3RPf+THnXFz76x5NweY7Yun8vYGB4O1ujZOo9q2R9tPsi2vyggdG1FbD3OGmJH14vBo/sg7+Ucf8eT3BM6joXpvDnWEhH3H7jHGOnnlyQavGuKzLoMa3X5Kpi7/hzL4OkTSo0O5k+OPge9Z41a364Jfn+Ao0rayR0+TWULroB+Lgc85uqeHCbi9re3TpxjEnTtMcnzmLh/cqFX/swd/zwEkrPburdUokYAfTWtTwqFpV6BtfbtGZ29n3GlwYZAHxGCOKvgaY00cTyxg7E/UAc/G/fju8Sj2HI8Em3vCsfcngc67l5u8LnteetGe4FrhmfN1dLijF5nQsx2dxZ6TFEwVYH0wEb8aN+5/28tBKFqy9/igRVOM5MjiQx+mbdDOzRl7frG+vriNXR7XcrLJmB1TKF0+tiny1OOvA8Ii3GMb7L6qfmvGOJg2CXqfKCmGRFREolb69lgwmyfWc2Dwln5DDxymM/Af/s1SEzhrPRx5Uui83ENaehh18Z+aHizM5hp9++CQPuy5ysUgTyCy5+KTt4f3Ihxe3lXCq7P8//ZcDBuXi0keFIXZ673k42L9S+L+/e9/G8PFp28Hz4UjAx6PtQ1Jf82ZV3NzYcqci8281CwfvPkcuombV9fTH3DWGa3l6xM3UMKNZo6NF/ViaUSxkG29WGl3OZhrwdqRNa8+80o3Ob/lLe28bT0nrE8yEIedOOa8Og43r5bTB7jx0wP67a0yffAJp+B8RT1/q+/b0XlFnV7l4tz/q54nKzimvBXdJzSoIxz7IXBciDP/LW9n54dXz3ll/6efc2Gei3Nf8c/+R/7GPccSfQxkwffHt6gZ3dh9qEEDmVcpZaWLO94Z94Gvc+5zJh4k2Zqx8Sc6GLXEwN5zQarhNA5tvXWRx749nOVaxo1jnxHzuV2Sgy/4vegB8KmrQbWpRT8B5V+tcMpPz+Jb7KqA92BGAXn/wkP9MOmr3/XEl8NMscwYLWQgcPMsxfZRHvjjKJL0j8LRvsnBXy6Cqm1tJSJ+OZrx6Ece/PA6B9k+HczLmTlMsoy9/TG6seFCs/EBF795yUe6rOWi1s5Xa+OIauzum+HaVvfdP74qVI8CcrsTN2TVxOK7oZbWV0974bySdEa6cuHefsHfUro3JoY+FpkA+/LoHKLTA7qWmHPMZw4vueyNGcnfmrCpweXojc8XSQbbjJAsEfvhU0MQamuGozAwL2LxmQ8POZrTmmX6bjN92Rw9a1bzUbFqVNL+lVctOWanD9/RT6OV+fZr1bfKiDij+q3aQ5EZdWdoY+K6KzzenwLDR82pX130AYv9amVYXq3qiLHHHnRj2Dv7rp/laq5yBTn1b+T2EDZIqi9/g27YHJw5LGLORqGlgYQvV7FbaIDHNkUSu6KcZ7MNYG1yJhllZtsmJXCss9c1bfzQQnRHOWY+tahp9PTki4VfAnNjljEbdVGBeUdPCM0uNryLG4xao5zl8vWkGkHsBisP62jxgC4HDrNszjlBgOoRMJhazBFLE3MyPCcVvISs5ixYipk8hrJhSBmv++a6fIUIs59wl83t2sJL+OL2mGsLpmsTFGccMmHp8b59D27SAGNsrsUcvvg5h/DvtlmeeiHhwWmA59y7oIl/fGHyPBlKoIheDS6npnEd3+rjwXTT0pd7bMpRPhmHxwePkNHb1cZyoB7Sbl43EaVx19jNV9/wESUvjKSprjN/61MDhmINMyozvteO9nM7KufmQAOjtzdmT76Zyz5ceBeDffvI+VEVcJSvvjzgTkjfCg2++eBYfBnL5bzE8ojK+uSJDnsyx2PPE/b5dmwGFszrq/UcP5FVwXnZO98xBmq+7NsfBW2nAkoXSIaZ4b6dcU6cYhYAJnNjZq8JnvoWyVJT9ozO4yUsX1v7yX0m8abRvTC/sTJAkuHbVUnod9+hMAkKmG21B6a4GofCOrz/VM1gBvfWzEUpxfUJkOaECUxrcGFd50zgdi9oN+3KHgNW24MC6V8vHLWfXoDrKIOBYxl7yZA4UUSQP3vvf7LMBdyPc76ZWXDUAoEm6zGNQaNzePDxiffex8DlB4vdC3bQvorO26rzajsxq6bnfS4mkx/7b7/lLeC50P41ff32W+6z8sWrxfSz92HtK3wxey78+EMuYr2IykV6cH7QWdb8jTZ/KfcjOQP2XI+lTyDk4vg0LUYLzZ4x5zB13R/yA0p++sc88b2/4WmcDnUyjZ+LZi9oo/VbLoS5qJaPZIbzhAC8wPNqe/B/0Lvkpz7OP3xg0N63lueJjnnC4vdc7P/wNz50LhfSuUjnX8WRk/7xgXLg+qnvecdCeNHL2+Hpz16c/5q30oPhzw9+yafL/+v//r++tR08P9WQ/Pa3x9H+vL2jGLqCbc/t2OiUheLLjCFy7qO9fdTs1rZze8rESIrPBCYn7LO2/3P/2ixYJkMge4Gw1EQz5HR2j+GeE81QjuV80xqmoUxq57ikFsw9H4jvWpU7JWSOoedHG2Vcm9bpYswgpryrETtjc8/C3dbI4miJcWjEKJ83u9DX6DQmgI3VPPHmsDCgKSQ/VNfI7rPMqNXtOBd3+hhUU24m6Jp39wD4/USs205WagnQEQXlip4smV9W1lmJu3Zs5FnexZtbPLQTN3t5Yt6iG19OpYUPnpfDdQKo28A5l7/Pz4uA9kZNcy5KOumYH82Vxp3xaih0jht6yTY1q3DSO6eAh09twWpqYOMH1/5BSN7mNEM2m2JzYd9axVD3w60PB8l2SNKaMfHY7eQxX1VXzvYSikuixsSuDnK+HJUB/trJhf0oJkYDuKPe33lbaOHTA/qM9nxjV4/zrmB2ZMl5vMNpNqt/fdgPj/MnCMeMHq9gzX95cK+NbmahtikFS01PnScndZz4784FaMYvCJyTbMfHGsxP0pgAhOZsu181ANG2B6hcMZgEdMWIkya2mJAFEz9g3Y//YFkPzulZg4a37EeT5uZrZubldqYmopqt8PFPbFmlVpzPIpkrNvOBD9g0bpz3YM269DZxDyJN0hwNg4IwlD0BnYrAm5/H3l6CyIAnblhAZnn02NMnjnztJSCDjKqSMhQT3PLAuhozfesi1z5QQEqHDJlOH6fH+NTHPjZzEo/xWQsSbLJ742KJfccuFDE+eQpYtwmC2YvGiiB76iW5GhCR8dErEQ2vl4jOFjfLjbM3QWAm/7tuINvkJieoeVBjP+DEHU3KgoDHmTF6AURtg+FhstrjPscDf9aM42Ou5W4218bd43zjiDEXQpjn5/DEpv/xFROUwNOl6ontPGjyFyTosh2dNAS05sk0XCXZmOnRVYPDfvK47PLV2LwQZYzet5qmY8sriuy1VC8xGcvJ3HO2kNIccRzT5LGOwZ25LBvNQuy4TSnvIubawrxKsxFRNreZ2G6HyyXpbIg73HI+XnqAzJicMpcPw/DuXlzBasl0jvzw9xzEl5D2Rpo9T5c4xoyEZ8OrlMzyqh8XPBpxoAcWIOW1n1ow1r7+d79z41wIl4ci9yISa/M1afHNSdj2o/2b29erL1USb8SZTE8wojFfPU4wTk3Dcesqx4TMA5CAw2nN5JherObVNFTFGXJYzF9x5ecJof7k1eDM/TtpPmwsF55cYH7j75dzQem/vOOVWGoa/e1bLjX5e+28cst6b8NcfJa3ey7k/VOA7Dmm/TA58iXMC8of//br3/6dv8fmQ9jAcJGaXNbLk5S94IeTC3X/77icPY/oaZ8QiLyMuIx14TGh59inF+ErJPvoIQ8/vpsgr4rD54fA5cL49BWItIkJD5oIS+OM80Gr/yMeKupNBvNlT+yk5gL8W/5HOm+l//JT3kbvhXpyhod/w/Yb/5aNC/JcsPOKOa+Ue9Ee26+5gOciHUL+5vxf/+f/ySvn/8y/gfuH/6ed/9Xu+RFEj3OPCTyaRhNSdiw+yLC+nkVkT6348k3JbhcaQ2utWbc8FN1eNeJEZkmuWtluPw8vjUUree2h4Nb2aoi5PBWDysosP9ZSZUZc7lf2HIVR3Uwy7ENytdLsCZyhPuaY1EM3JqcxNROjnVwTWwFdbD51InVil9MobPBkT4a9GAq6a6jGTzaG2+Vi5S9sE+g/m5g8D42ZGksxpbV+tJeTyMwmH6ssWhsgR9Hbv7W6H26Ub97bGBCJje6O8rCyi6QdsJVHA9jmaYT9w74jMeZyneiJKefDP/XUkjzirPTjfFtazht1Bgf25D3aQZK8WuTTQubynxgt2ZzjhSGqA129Y7FnZcTS8fL0tlE9eMWOBtZitdpBTKc/VUZOjNvp8VOK6G6ExHJQMcDNOHqytvfTHwhOPQ/+2Eotp+rA56vz5nr1V2j1EQpyR3URM7q3t2oczgGTf7VTO/cH2uI/8WBnsZo2hy4Di9n7p9MHAC3eGfPGjn37lmVTxJ9SqIZ1xLVvTMfW/QgarNDx64nd3rrIZuHLhz943+Juk7PwgM0+uxJMwPoIInSbVnubOjkULeptbgxH+CQHg23HnsAo64GIZxqkDfDosUnMfXCIuY1yj7589cIbtV03z1FJgZq2tvqfhsO5XHWeGJbn5AmOLNVKb7oUQ7wnVdwxkGtHtWblCRT77jMVB1TaqW1jgcaFm9E5Wjuu5rU04NN+ayPKVOYfGcPeO+qomWR75/fmRwEdlmd6Vs7m0CEi6/jNpdrMJidWjpdMk6zqe+xuvuEEk9j3F7h5tuQszi945mDna9We4zcx7tCToZ5Mu8xkNOnMBhR1iKM2Fhl5M6e5hqZxZ3GXe/tpFHEd8kI2hOLOOtm0txIiqMWhnfkqG23kjm/ktQ+DpSMWmPWwzBrG5vCVkuGQGeypB53FsmVxeqpLpx51urz6jN3EF3o4Ng81P+76faBuSvnZbK/Anj5R6wTXNnBsyb3M28dTmrBakbharC/rXvyUeq6/J8KdG7hbd5Mxb1effo8C+ZXqRuubk2Notu0X3OiPGRNehrBZaWMzMWoxpmj1DEFvR7FsA7RXrzVn/eYRlwtDM+fiJU+H5BKd2wE/OZuT4nAhYXjZnzmMs9a9GDPpwn3whb/dDnEGx9Va5lElc+27DonHuWZ9BSQW/izoiOfHLo69vbqoAcNI3vOqe+N5W/LyqJ1EmTCfafw5fyyjurYf2zPfYk2YAYRTEe9SyKu0+X3nxTQXivnxIj37b3yoW24TXFDz9mpieH6KPPDwqu/XXGH/wgeT5UKTf7PWi82f5YCTi1D3ciTY0oluTuuI+J9/7jH48ce8Cp9Xh6mXt4zzwXG+cqVeroVzwZ8L2dJMA6hpBhqtJTVZI3H5Obeb4IiNqbMs9NPADHpPPIMLd85he18RYsHvkItOxsafH9A/8PaVTGA9d+fYJtB4uIP7Ro15Cf1HnhTxiYp86vs/Ul/y/v7tZy/Uf5yL9T/zFMYv8X39ez9d/+sv/bvzr//4pb+XRhb8fKkjF+b+nX/y9G/iVzEd2dGZuuqemkfrAMfV/iV0e7pM/m6kj/lpSLb8Eoquj47Zk2I4Mjva5672cRZcOwgDbl4XXdcyOYKBp/lcTP5k6gM8D0k3N77HiUx7rlyeSavSufk3WbSsz45z2pB76oMNXvVoY9m1vltaua1MjzyG71LELLK7vYoCRHDDZCx/hFouJgB8c8dEP1eLAWyquX2b+sVsgSSQ4sSaUyubrXkMxGZ0+xQZy+kFzrg8lorLfHpX3cMJ7PuenhqCmSzN14zMyd56TGPfyVdPtnC6yBY+TAcwsZNXnsxB7WNNA2ZjdDZ7v4+5uauHLesdr88uFaAefds/Y3o8UAfM2/XqxB/sPl7dXrSngBMhR3MTb77EY+n60Yoh+LX/FS+gkVPO3mcc3eSTY3VnSQQ2tOqPIaP2nWlS2WbBUg1BWgu7cpy8iSimfDfm5scvZvsx+sBWRPcvZnvZPTniBYBodnIwYWWki9oX+/Z5axiSo+XSftQGG71iBLu3iVmad+WAqj7yReuErS594RIXrryC3qY1sDW0ofFMYYuJgZwZt9EreQWwX9uK1qbwxpevB8VchAw3vqrDmLFxaMlczsxl2qTqyWLkjTfBq7OOakNdZsBPPSaqbKbAC2HFNJs52ZjPEBb7HaNvTN2hGwRZRyAG6pE5tjGzZwq8GrOavMsgouH2o30LmiDjy9tsm2P4Alg7fJv49IHkM4YuqyrqY/F0dnv21iC4EWxbFrkm3N2s6wzraFvNFlC8tU/MatwKWBs7+aEzM7pmntCM51hMjgROz9gHknXf2ljWGjPn2MjPHC4Djx0Tbns5ebVp37yt4vQLmoxJ21h4sW0tXTRP5sZWQJGBU7uiDHUlaWXMGp7g9vZCTn4MfeyszzkJQnES48pSQ+L2iGQ/GP1Z2CtxkyRCgOwwMgZ+MVmnzOMtmYvl24sTjOC7bl5fEYfcBzjk3qc1wv/Rp/Rh17Mn7Wt7Khpd4W3RZM7PjsypM8u9KG8dMVArTxBaR9fnk63fOreP2R9o4Jtl9xh8YKYvCzQz515cUGtGe2tp5JZ4C8BO5OcwRsLHXorhp2+Xu/g9bmFMIi4Qc/3QwYPcebDJhRJT6jsc9GcLDnTnSNheQlQJu519duKNL89S0XPm/eHYPLVm2gf39cPvebLBo1E7HEwy7Gn6zJoHb4yHtQa2GyDPm3sdwzXRXPS2R62hx4o+w5WN3yyyjEbs2ye16MlGSCzB9KK2r6Bzof01r4j7N8/8DTrQkHCh50V48v+SDyH7KReWX/OK78/8DTR/V531T+65iM4PvNmTG81wcLFP7+DWF272+PJ56aO3uXybd/Dnw+LCwd98//xH/o3YD3kbfHi3d1tfKDLSlzme8IKx7szVAsL5XOgb08172wPDRfrhDpXHcXiIgJd8aPF460tNeDLnnQCLgbsPpve45aTnOzn6d+dcpKdfqZPj8QNPeOQJiZ/yiOpbLuB/8l0KJsyG3vIECLedaGRO3U2mbvTv/2r3yYZcrHNeWw/3v2A5uFhnXx+2p2cs5gQ+8fjpRwnKaUzPX3uBb/RIwVoTmyCyuwzM3xGdViSojoo8czzoxby6e1yTNEa1pj+M1emCwuXKfqagFlPO5j/6gwcDqrv20Xyjc+9ngagNtHm6N8eug2BNjQy61v2N1TDW91hdO9gm029d7cXWMuEIyHQqsBbVaFvPeA3Zuk5c0wzD/+183AAAIABJREFU1pOIfBv/8JfA7VTVzGoiCT8G7TnAGsPuATDPT6bC/UXQeX2DX6g14WlHyaUrPfFFuviHToz++LbO7pvy2IiQVwVzjt3jjq+c4Zn7ebWx0UF8vhM+Ms1Xd/WpQ2wQ2XMekJ+x54aLbIS9i2H1PmtiQJ3zVz4Zi5x6Pyiy+Mzz4AVWi9O2wWLsEefbg1ndq9PbZPy7b18JuH078/dYUIOKb+6N5eHZW6/cwrafClIj96324vCtj15Xpf0/udY+uHN8s9Z1dbXybJnAFf1q3uOwtuGQMfPV23oMlpyuMw6HfHQnQ87hZ51x8k/c2srSuN6/Mq/uPVx5BR2GECKu2ifJCDABVCvQADYOxfPLjIIGszZvbLGZVIpP3Bb4PTvE+IhDVBvFfHKOvyu2bQGAg4114BemrTrVmLrZM7YxNgE+zdlv2YO7hnGAc1oea9oYWXHHkO+leA8GeTwYjxYFVcDV997p0ZN8tedVD7wKWgvWzXuSTw7kMcDvXIObI6iCEYdw77nCmLl5RgMht5fDJ/EwiwO1mao9UX7tjaCksh0sEVJR6wW0LjStNvbxN0Oxm80+bcPXuGmIGp79hb09XXrjzU2+6jEcYaPJ6azIvudg7nM6f/aZNiex+9ugLwLhGsq32uKRjrX7zn1yIQ/4ELZ2KFbzlk2fWleVdp6IALAc7nlgB8cO++CrDaB2TIY4b+b4AWcs5+VtXPWX5yKTf47f9p6Lcmzmdk+N4CbFmQwvwPy4IzuT7HmADSc/jN0zPxQV2SZg95iQPw+ildoaOw1Pja1bI2zTh/GRzQ6Rm4NQQ2xMOhqKZWzBWvOs29eTziD7kxzv3kwh68XECro5k7RaYQA3vWDZ3MSMQIyrJ/uWs5xoae5epDdmn5Ag0ldLuQDJl1VNP/A50IIt3+Rmvmv8rg/QSTbFrUbxWqU5vYDzjLccHPhi86KLY3KAZe1yrVW/K8Gj9wlD7OXxOMd7UwlF6/abuU82iUFQB098fp8LLzZ+2pPw5Dxi7sV5Lgy5+OUCm4vtX/L2af4WnMq4mCYnr6xzQf4Vfy4W9+3w/B3111yk7//hZn94c6FpXYnfC3EuFntRmleP418dG0cV/+Y+CFwuKr/kU+M4J7hv6iv8XKC3D+wZe+yZY/Mnzesea+3bz6xOH8cb7M4AhzOaP0ZsHMk2sf7m10oC81Gf/HmEiJ+114k2v4xwm066OPxTglxQ50kQXlH/fcUEJTZrjg194+3vcPKEiW9p/5K8uUDnuG0RxHhxLjb4HMMKZ9e62Knv0YWvy+R1Vr0n1nC00wzEt45bTzzSuylOisYsO/gd5ZL4yWh3hFRj8Wz1JPci2L98rQ9/0ObJPPgPjMz4twedH9LxE76ZMj0DvjvWc/cbQ4LO61NrAt/9iFAf9vXBf3iefm2WxbE3SrFZBUDcuU0YMGuxbDCCXX3HIuKzX5sRePAed/Cxj6s7uB4MKnCYpojjj1EuI0x5eFltz/aCjLjl2d43PnZrADCashevYc+4tangnA+Lq5WAzT17HVsEzv/lPDJwa8qCG7zHY/nCkVjzxW43Zu15+dSgk/B8gd9eMMMqhyCTYjIVzdZHqsEOQpaCsHSAIcfmyZ3sutTqAu58MfZ4qfesTa+fzQensVW9tdMSpL01XM3NdbVfPWfGCTX9a1y1LWMZsqKfAbQ2kJkFqj5FoJZ+xSeR4Km0vkptjwjueQ/Jc5xjF8fmiXaVx4o9V8lT756zrRHUcJGeHJhmK2VW3Xd7b3vKWGdDPH6Dg2M4YbQPQ8j/WfkMZBnnPpg5IpzIcsgQsI0oblhZTDMgr2+Is2MUia/l34NzvdK4HF651rq2AJ6DsCfmZlj00QBfhmub3IMqbtY6pZ8TZfgbWeaYqpw6g+3BjQ+ONH/rOXnBLEH20Ltm8zrAjEMuEq2NRDphb1+1oG8v4BePA1T2dLjL9rvZN234SSHR7BtqTWhgQNveblxB9dYn0Fz0AFuw3vnVs0nUXkJN9wwgT7QmsOcVuVr/2t+svWEPflLA/WKac5z/Zbf67v3d5AtW/dMb80/8Sj90B0gM2huLXz1I8iIcrXkgyANdeiPu6RW1qz+2Ibf/AbsfPBCPKbwnWSwEgZWjudvH5RNwekqAeeAxCu1a5MHqiH85+0RGV0W+c3BIGg4yDTeJquVylbzHj35UTDVZLwYdZyfo85Xzvv2U4DzMFUgItwcviLLwwW8iPTYwRN8f1J4fsHsOuI7fJz4kQXQMO6YueDhfUErMhUwRktZXZ3tUL2hmHY0ef+KWDYvzQOut7oZW93KQriPIzNV/RNW5262xhQc0Ws0SEP7OiTgk0tfXTDv3og2OXISg9w/P7WjfX0DSTJ6Gtq6YwJOOJ0MYZFveNbDGnoMk1qkaUfngV67gOLLuMcIBLuu9j9RyN0UEo2m7zTqWnMD6U+PH29nBxqFeuE8fLy9J/ftmiKFiA5m7ZiUM43J3xbbDc60KyiFnL355QoQLwa+5oNsL89/Tfz4I7adcxH/N29m5QN9Xy/t2eD7oLD/xn1eAwwkXPd5z37w5piTl/3F/y6vgviU8WthTN/G8ks45xP8U91+R5YkC8lAW58ZPeSKB+rhY3boTqo29r0A7wTaDNY3JAeQYehFtEP3kVWjYbVwDdmrMkoCgrybTyP1BH4uTuDj7zpWF4ha/hLEm3l5gImb23AfxhMR/8mn46AHz++/w990H+64DLsyJQcvf//WPv/396z/9l2/UTY3WAldwvDIv3vqeZKaWJBKip4T2Jq4MRFXrTKNbkznsg7dHQf3dLEfqFVbWWdh6srR3ixm+BFAr4Xu/KT/KJqmczMHtMORykRGSIpoLXmNPHBwQtObG9DAINAdro0QRsDrKB0dITkMmfmLYiYtfHvKNdqeqbI6tE02b03yDOVxZN0uAYE/uMtq/5N0XO/Tjik5LbzlyUDl6Ti1Qg7075w1h2xwHFMtqPfqXgJoDVw+4qftwZXJ+f5sFVo5RHHuMJkZJmt9jOTjy5OfUEDOD+nesarnx6xt/5toF35ihGU3EAFgrFBdbT3zLPT4Rub31GFFdc61W/B/1st5arCsGucrdOKQMD/vgHCOny57TIOsP5uGJ2bzlIXqCy+T6WLZO9GCcfFu/JRvXWXsZ5sQJzWaxhg8fvpNjMDC0h7DUC9zfc6ZuELp15w73nOcNjHlqNu7mVuJ3G/NN3Lq2x6yrInz5Wt6tRaHUmC/EoPYcO4IZdXlfVt5m5Fhs/ez32BwbJsOnTuanR5fjkIyO9qVaINjHKPbwqUHybHqBPqmGNplCIOEjgkpgYWRn0WqjAYM7AjcO8DYutvk9uAHbuLItjjwzJ9rukICko2H2qKkOmpkYNTc2rhOLPuKLd/HMWWcsdzyWCZhhylkMgXxxmS9xnoAGGWFMH6DO2mxwVWMiqxsi4kabaJaDt3b8Jw7qrvfOrRRTP77FD8cqOH3EEJginSbWdUP1jB7se4ze3m796FJH9g7jSjYy2iOamKGNx4E+6qrm2jsnH3kcQ9C8BNe8WxmnL6dP6wS7ktbGPnbPk0zY+0otQL7ju31HB9gGffZuzg9yD4+SDZDK2EYmT77Ace4z40ENDzi9SD/76vHiHTHBkdxewGsCzOVDrKZs+NocraEayO8QWA1sGcYsf9bEL4f9pnCgIWztjQMzjs7kRqqNGqbqNUKO+j1P1BvYxwD/GIbT+nmgKvWoe3B+EFbCFr4MrLkYoMfUwoNosZnjQyp6+8PbU0nfB9ZwWAu42P8yhuCU2ybNFnT78D5w1SlffMTvCMk5tydSNxRonPvAwqfzb3gcB08IfPn61NZozyM4zYktOK5UnO2WnmBoEvuAK2J6TrhY93h0B8ETHrwFOX2MiVdQV5y5QY8wKxktzJuHBmkMw0zj8zs7JuNmoR4u/oZSG9gzJDFcE3m2N7j4YbQf3H6u7fhEJOoYhmOx2BMIrwMxmXLXxiAnA3a1O+dOoP2UeAvARjAhSSj1+iBhwD1f6O7FL6+Szwe+JY4Q7kO+5NjyCu3P+VtzPtjsffWcuH312wt0uHjLNXtO+uyRwSfO/8BFoxeLXIzmVd1o6AVl/r48F95wwfGFXMHxBAh/i95jXl7m/FsxLjy5v+ULji997x6CrZuc51ygXoph4Cfx3B7gw8S7OOrGB0aUt/W+zZ466P3wxM+MeEz4CHNO3SXNngcpg2OfekQTHDD6+WbQE/51Gj//yb93+/f/5IPzxr1PdNAfPhTun//nX/aBvvkER+Lplxf6vHKe+ylzhYAv9HWAyUzNeJzyLNzRAQ50+86859hy0APrBij/cFC85OVlvjHmGTfcRIgCvyLY6zH72MFlwHX4cQ0YXwZrolYrluYpOaFqG+3EgOkNrEj8g96CGoPGxA3qhJpr8phffQ29vZs02W3fSgBOUZNTgJLMhRZqFlycEZ5aqNyBNr/l6aZrEOZEow1oOfZhw6UmzxyP2Dfv1nTX4XtSV9tKnnNie5C9cSdvApGqffUNmRrcqArr6mmPiu/RmVi4Fv38bts4XeP38D31YVbm01/PstHaHq6eahylU4MMgaVvewd9FJcbce1VedRVIRUuYdU2XzjxSz2V7Xq4yxmfPMUAJwrp5mthtRkAgjH4A45p+Cdrz5EsrCt4jp8j+83W/RwVFkJ6ZE77Ni7ujWNW3lKe3BM/Vgl7rjb3OYey1D7c8pp/tOAnx+uX7Wo/+Y9uAaNxeFpQtU5BW8P2ZYpuXGUqv6kn3/YgwWoaktXY2wHYzdsO9cScuazZqHd6HN7Vg7tzWXsfHps9Y08tjz7Q/RR3IuM5wZ40Y8tcgi1gsO7ejdxlZ9sySDkZEUoCuZmv7N3HB4e4aQOhT14bBwU49irO7OUkPl+32Pqhscmjh6zlYHvzkk/euWNdLm0J2nq44HiUtx6SnFH2s5zJqRu3EEldyJdayLHcpRxNawSd2F4ILDZ7+zC82ak5e8kS0HQcT2yNOzHCdDT/9LQiSwGPnIGpETijYZnEOxq3T/qxBfNeuMBzjieg5SSJ4OwjdFbudw7cob88rbU92Nwvvn2Ph5jtsWJN/JYw6ctLr7amOpI5NoY15EEWdYmLpTURNH4cO8g7fF6kQxwDCLbyzcoQYzeg2mtnS0RrYbX93JrZYwWzgpn1eDPDO2Mm5xeUIpWW2oIpXLAcM1M+88R/vjo5lQzvHmfDgNuHqTe52r9Z743b2gN+cjN/ud45F+F9wNs+4fOtuWOHCFsuG3wQ7wWetuiBN1+nNxRGUau/q2x3pL5gxq3R+NOc6xGVBLc/U1B224fDmrDDE3b1xEkrtMd29hiDJxO2sl5NO9Mjbs5NgOQhnukci10fWy5M9IWZdpguE5/QyIJPEfcdCly/5BzxNIGSB18FG5PLGCiTUhHauLhazJLH62BPXmtXI/O16cymFcNJyr0YMma82WVszqDU5J36caHh5ime/LK3PVKYpFHZWknK5FwCeyxiDdNRTxGAgt8HpgcUe4Y6rKWcW0e99duvMXB74YeLP/83dy4U+fA3+pQTzQtnXzXPK9m8ws6r6WC9mM6eJwc5flzk9X+pJ3B6bu4sv/z5Jf+OjOfv+5Z5n/SiX/k/614c53od7D5RQH+/5RXgP37NxXzuE0Ntb7gg9dXz7P/MRbrvlgjWJ9CoA82MM8mUXgQDg+cYnfbCOfvBwflDPoWdJ+A4/qubOfl/2H/QntPPfsVu20kFs4vo4AG78ZwbgmPj3SBkDwhf5oz3GPCEA5/YDhEa+LdrXLDzyjnjW0J/+fsvf/v7P/7uzy/Zf/17/9QArXLRB55ATMyf9I7YFQlJ5iNPHeTqiKJ3/gRVa88j9Sdgn8ynFvK2ImovDk77Rz54t2Ds+SpPc4s7lhuPd8PkV2L8HznJdGNWD4FlXw60zXz0ouHmKHpj8KgTbPIRfOpUVBOUobkWR5bDS6wShxkRGVjNIXfW/xW3KPxKMIrfLYxh7nwA9obsg99ei6UG41iBGRAnhJrbx6EvL0h64ApUj51r4zPjG46pbfce94lbG3HybW6Zp7fLNzz2h3iD2DfH4YBLMxY0uHV+NolZHa3+0q0d7Idv6r35yVsUW2Qw6h9+bQHFqQ5Ctm/44hKPni7YriP3J5nmrsJDkSkci7d3ckBKTHbZD5Nr3EN72qVjjY8V/athz1lol+MkwWCeMoGw9iS/2h6f8J4rE3qyct4c3pmtrXrKUz3Mp9DMVmMZ9vY4GGFWU60BiYfB/sdgszZbsXsbIqi1t5s3//ZjuNEhX/OuOlgPos2xUqKxmzVg908LmJKYfHueHE4nOsUIze+fIWaZsWTJAn4K6v1ya12MOdRSun0eWxpByzWW07hZb2LtEbzN84OMNsa9ylts1tuYnsyVU7WnrsFSxDSLrhgLvsJs1hTQyFo8GwPv8W18my6FCXcNa5kzsYaqIy+DY7dzY2rAo/9j045LSDQIHozzoKD1TUw4WtdEP5zNLoXxcgCjD4bPCZQEzZFuLN93e8ImY7DEZ7V1Sbk11r4XDsR1TO82ZuLNu7UudNSYx3urqjvujaWOfFl/bB5Lba1HRXAr3NWhYLI1lP2tjpDhVkvAw1vP1o+9ucihXiI3J5qYP2OPPyVMZCJ6HEQ+scU+fMOzx3WP1dbfR11hfXLakycXdfBDLrNmbv4nRmXaAW1fJjlrfLMXOxv1c47iIyw4bZm+LJ7DxARX2KBcuFETwVAxirh5G1ffIX+TZW5fJnbLs2dh27UMTale18NjHwfIg2sf/PNK3v6Ia/+4kN+3oXKR5auGycOFAzn3wXzLYRtb7HSILtQOYWbYk9c4G1BMoIMvjPUEOs0q4/I97smApWPPETOTMrcztZgvGAQFrsbs90iuUnzqdFL8YkXbt6DTC6bSOSHPHcT46qkUCPH6rpffxHntm5g5r9QdTi7oGFsHd4uM9qz5vJrTVjv+21dWrcuaRqQ1xE4bqPmte1uDh29G37GC0K61ZWMeFkD55eQcXDtoe7RlQy4u3vT1ONRFMOeBTcCUQaLYciHMRZhr+GcK/nCLbG62wKxIzgrefsTd/OH9MRehvBrL35p/yavg/HDhykUqr5LzwXDsvThHMxfmc4HOhTUSrYWDEn9fQSdDLtCD+z18/Is0exgtvuMo2n7981dfnSeWwd6/h+dVci44owGsb5sPvrctXnXPW9+tKedOcqqB+Hyxho5bBbU7z7nE/zVPiNpB4uCLAZdOAbXzCn5kq/ncf4k2IOF7Xic2Y1dNmFW4SqcYgsQV25zU6J8URN9v/D/5/Ds1/tacuon3SYv8mQH/8/wf//pXfv75t5/zBIrvXEid1R0u/pbdnuVCf2LtqecIPUAdxaOl+/f3FMqOfrsiut2xTyPdEqiL7jI0lP/YaidVZ9lOXC3kQgYc+RqcmMxdovHk+sRvzlOLSVZP6yzl1HySTqK93Yz2VkCOwaMrouxtYomiG70tubia4Q6+HK1n9W2PJmvrCtw19Rm6uhuFBmbuJ9DdNMm7lRiW+3/bSy5T6xqqLAw++60d+95XFDM6JQJVncz2YqBF73kyfZ++qd8aMyN5AkG8Qww2cMY1Jyh+rJWA6RVTB4SxtXbIJ7ezQvDjYcj1YNbGvhqY7Rw0o8e/7LV89iW4OM95MhpfvtWtDrBSl39t6rRBppyaMqc+TPJuffRy52ia+eHGhnW2TEIij9b0ZHq3dqHjK46YxTGNNcL7WCHT7X1g1Oox4P72PMPQ+KqAkfgIsY5asRnrXkRwDPAMvBkTw5RhLrlaodKYdqkfnNFrm1zYGXtLbRhbtHRsdlbMt9Z6gxK+vSna2AgRS9yH5mU0UJpags9krXKsCusjOWSzZzf2Vz+Yxi50zpkTPvkTS755i3u8GUDb5hu0dgFdOJ3DkXkJV9fQjxUxtVxechDWiOYsy863sEYvo2mzaRfWSg8+uGKQBzt36jkR8bPsWOVhsIFlwrr5y7eZEu6DzkSba3mqmZXc2fTGnL248nuCAno0ULoYctoHAMOTPYpWJXYs36WeGhu/WPcDpBojj/YHC2aGvc66Ohu8fSjD6KGv1lDx58atto0L6dRjCvGNX86R1R1U84DFQ6EmlMdxeDbvKtbryU+/7V8m1HF6eckmKEA6+mLIoci4yGUMuIyW0/mzXf6X/kIn9i95qvHNbS+AQ2StzDt1faboysLRuhcvR+xmfbRLS9D0bzUPydmZmpUExzyTiiG26eeYxOv5Ije2lrAXZUsm5qH0gXLAVsCe4/VopMi3HiWN/u0bSy8QM9HlnjmEtfWCvDbsuBhtc2tiHU8+bbp/R1t/L1aAc3GDtHOhPr11zbkajEwhH2j546EmuNmf+Yog0QSfHqovyBDeXi+IALSHk1rg3V+osbNWCTryZR+yP2YnMGSAQbv3BYvFnh+SO9AR1tg25zi6i53eEGIauPLl3WusrCD0WIOBZ55M0O7LDjg6mjYxfLOYOnZ+deEfzOBgiMma0YOOxsX23X0BvhROSINmR1xrzR4bhBn2MQu+7DG51441dbT3UzF1kmIJCk4EkwySZNCn/Inyfx0e+40PYv98A7DHfjh81Xh0eXH7BcK8Mp0tF9+MHqH+jToX2V6cx4efGH6Y06/3R7lKjj1iOVxfvuUinQvPH+hfqs4x54L9xzzp8tufv+XDzoLLF6/iM7hI51XlP/6TmKx9oEqezM0boe1vfOYnSuZpU3oaO7dzLvD7FvK8Ms25xr+RiygvcoNx8Ap6LmxjdanuuOBo38hbrHkbpR57lvW01r3HNgb34QW4fjj5ID7/5zmvlKcv/Is53tb+a97izt/fg+UdA1+//pJ/sfYPL8555ZyLc3rkkxDmpJd5EsOL8zwBwcV5flCKTspD325ZHL2x6i+AFUdGrD0VG47ZxxFEv0yAgYHYW5xzWHq0BLAxmVxgOS/Yt6UVBUZbz7xr7AxNDu+7JuexGTz6B190Q3TTj+TND3WicUe1xr+G7Nf2iQv36WkxMKkNSczh2H64aq7LnRmLYG5Nm3uxkqlRKOetBNnE1XxVxlbMswd0MeWMO7j2luNwV5kevUxXS1ifnKc2hDx4mPRVoDmIKyRckwucBUla7SQw1pwmW5DwBnDM4FtdiRoNW1nruv7LPjSJ73k8JU2W5UVXOdEA6+UyOdapubjhzW5VY6nGDwvU31XcmsEXuYhdo2BGBHJfWWBx5sdNP6YPogcmKsTbr8Urf2vYDKU0/KienL0PhIhvgN9xxkR6dGyPnBd5tvT9Q+fbsdW/HBU5fBYhDxs4rGn20qxtUL3Nrs72ebXX1xXVbGrPneStxtZ69C6/UojKcLdnXHi0yXg4NO5jrDcs2MMdEAodkqzuWD7NOIrbbXR5u3p0gZAGm780C97z1re4AzjAkyRWvrPuid/GbcPxLQmUh2Oa82GTiCQHxaK820wCMlbH5rwtJcfGF+tavdirwVTY8nMP3vqKW938sjGc4DnYzYthtETfVXWnJw4gYw4G9hMBJy5tnTlnmrE1FnQj1S0A247GX1/s654k8h1bjGiaXMuyuepq4EhXz8U1fm9cb307B9tj8tQoZfu650qzLOb6toAep72x0bONAFH7HjPKW161BgoaTcSBF0vp0kxDLqVhOjfGW00DGsIrq7L6QHECQlgue6c7+eDYB4EF1rbnNTwEZJRxQGtnD2R+mVsvWOKBZrO1T2SJsK9Bftg/ewewHbmz8q+SZSiOnljPKL0oeJtvtSD7CMgcXsbGuMjGXr2+9AoO8/CAD0y+eg4kPsS1geuFQbmKaX7isV5dGJZ3nJ9+4OHOpckRaS7yxcSrh/5yi7/2XrTj84KG+Bnow+7I3lqysA7OhaMNEFbwmXcpnliODUTG47dZXZejIXZkYhtH5NQuOVYGfJ2x3bjtCxoK7756sMyY2L7Fd7CjDyw8sLr/Pg+erSFzDh1392rg2BhZjlcHvFJx0RgMPdjbE0s5Ez2ZTx9dk+8dw2U/teOHrx/c9aL1aFChGbZfpSRDRhNxmJzKTU9coa92lueJJ2z2qhSLcU9OHrwx3HEcp6fEAMK18fDmiz7Yt9iPj8jU9lPeB/dHzjufQImfPXbexs7+vSjvnBxgyuk8JrB6sifHT3ll/puvYHMBWU3YvXZNDi5KPT55AZi/c+filL995+LVC/XUGbMjmYLtkwhUxP9Ib03kbM3oCL25fQt5+H/79Tc1iOXfmPGW/XlXAGDwXsBTkb1rL6nFzsUfx8mAGGoAiwtMR7nUoDUxcckZPIeMXP47ub04//96cc6r6eT7Obr2/53zd+dcpPNBfV+4OM+TJcSz8ZX2eUs7F+bYUOhxnVZ0h0aDqj9TK5Go2qxlKtjdamZtnQ//5S1687LH92rIKt+x9rtLOJEE2IDsM1YHLsbjmripUc72H9xSdX+jmHHcBDCfiSox0wPhIo+ffmHRdayst5cwFbOal+FEacgmOdTFuUI+U2IPcT2G6MNEVr7BklFoc2GHT3sJMu+odVfZn7pNZO5Xv1TCmJEPNWVxn+l4PP66SvXBXUwIxrf9MD/EsdfV7clLzqNxgNjyVR2TP2GLK/eoMhbnxNgXeBpntqZcaXoaHUfw5OLbnoZvHpqJ1wcsX40pDsp7e8iCMbFij65EjSa5ZApX/B7rg0u8ecq7GoYWlz9se4zwZKz+2FejOhNgSYH0HOramKlXnPKe2gq4wa7JjukeE/LWGvvUcvJtbROD5mmBPNYgm8lR0/EJan/Wx96aooE70BP0MbUHQKulfW7yWPK9KXouTQW6cE6Ss4stw+2FavvrZnqjNLg2oMeZfH1Csj68RMiuqXhzNWN8tQ3qpPQ4hB8saXpegR4kNh87smaI/Ft+tVfk3U8AoQQNFKqTZA/uc1DlZGPMFD5JNEobNvaCmLvwZMHK+p44q0uPQvYORKqje/zuyl/Wy703nL2T6IGTi3x0AAAgAElEQVRuHPWtnuf0HeXhUONqCbrflkEsWW5c+wUjowpi234lONNyTu2i8kuwaSbi+G4suOWRfDalaxzzo+DhODbcsYP+7EEjcauHbXB7TlScTm3O3pAYzqtlIT8u59s7ouLhO/Y9lnLTlOdcaoRZ5AL7DmOfnqoZjie3zwUleo9NvHeQP197PptErw6P0eaAs+NM6h/8XkwcfOyLNCfakUY/0Zih1DziJf/29h5b8JwPy7J7Ip8509I52Tq1cT6JbY3N11hzjtf5aoN+R2y+Wnt8m+hyXH3IIGCCVzf1YvRxcuKmJmCLfzk+SktsM8FJRHv34qmJB4/9ADhw73hiMKPFxMmciVMvTnJxwJqLc/fxZO9FDFMf5FdBzA73u6DWneMFE5PnVuzohddjDHYHU/lKiiKx+KV81ssz4YbK2TzwvN2CQj6IMvSRJsu+hbvnxot5a/BPlTx/KA3yTdzjCd95Jd0cwcC/F52r97tfNlAVzqQhnU0ejai6wwtIl7FLML7t60InCEz7uDUuPnvrb15LOomme9uf7EnluZaJ8wQfeOZ2ZPhcxNmYxOXOzSoIGOBqB+O7FB6feYTec8UwbAhlEfy+es75bp3zgGdvp/zNOXmJ8QI9yfrqeaw5j/v2derhBx37BBTrnP8cL1LhzOgrz/0bd1/h/TMXoWjJDxff5OGnfJuXt9DzSnG4kZ6Lz1yHVkdoKcdjqgaeUNiL874SDhd1eoGft453/81XqLkw5uJcjqMxTyRwgdtGn9sroFZBJbavk2ztKVrmfCUnnOrNRv+gYYEfrh719o+UfGJ7Ck3OL3/7Jbp4ZZ8Pw+Pna97ajlb+Bn3fwdAk3Ez6yjl5+L/rhx8NI9opNVrHzY6KgWS/sxF7dtRQqheB/j22QP0dfGIwkA5MjWgoS2b+Mk0vJr/7AgIhEDVrSBjT2OUifHgbXx5tkyG7v44VEk+x5WMO/9YGJ8N+4Mtgi7+YyRermPFuHKg7b49WG1xyDO+NPx7EsXBYn8tmXt5jt1e1rjb2WFbz1gphfVKL8PiddGciQ1GJMceukFdc7WF89cZ1jlvivC9BSTCHHYzHYjVW+WLw8eSdwzsIOINRPFyf/QX31ghPGS9OTjTggx81k7bCHn4cwb0DfI/Va71zfK1maOGGAh5q3XTY9A3b5Kn+wHIf4v2ZsYRVb/U0CwTN1STtJakI2vzkBIVubGydaGcqR0PsiQi1VuTyNRcROyYoS8vb38tZmAei77UYGsdikl2lI2vgPS+y2Ay4ez7U0lobu3VDfY6r/Fhim59Joc02xLH92Djvu4jdcyNo47IRk1UVtMbtq1lOz26KEHWh1MRyXOFefZJVRbli4D7vcCV+cksUu4zA8rW4rUMdzVgc8yfeWCvIu9PGN03rakl7e1O1iSA2icJL43rIFRKK2yTwOxZfeTwzUS78dkDgaUpW3zepBS524ic3wfZ5myrbbXKrIFNmS0FMvrq8WsUYv9CrdWukGrQyyrGkelpbSx6MwCdG880tNhvDq+D0J9TcEWxvyLQHnaLp5SoxHuqRc3oIR7Bq1vfkmJwbxlJTSNgzCOlcIg1P1uNt3BPvyRqrGttH4g6Ogzb6WxPZNhez0SBuHKfvuxYWpIWpDbgTdhkfxyontr39wHMebG2jL3nKQ3w0Vap8aN0aMKhdT+f6Bs+8tcGHMesTjbf6+gqYSyw7+ZjvOeD5sHckwZalWwKZlSFVmW/WcUz7RKzPiCzQtb16JfSYlbXz8lXPnpvxT31oAHFyya1pNwBO37Za81sPudCK+BXdOT3kTnRjmIFb3cD3gcH2u2qbjwsDLyKUOxfkuX1xIbOvOpKbWFWw9wKmx0/+8YubzaBZOczNDKGU0J1zsOjufSwrxARjn2ZN6KyJNj7JrTML+6CVUJUejoROxPjM3/MEno5Eae/q9G+8fQeDokimdfOw6qEZe97ufOJ9QM/xqI3eeYFJj4d7gluDNcYR5+lZl6K331SEDr7snQGEdS1nItqpu2e2dVr7isgirw03B9tMWVVlQXqxow2I+Z+1cclIgoZcIrhS814MAi03veFV2e5HvTbsYPZC3Jy8yHp0xoKewd2c/Rvv7YEfAhdN5zyn92iEfebnIh1hGZbw1PFjjunPvIqeV7L5VHdy/v77b0Gyz1vZuVKdmsnTt9Rnz8vm+bvsb3llmXfh20P+9t0co6PJTOrfq+ft6tToW9vD6wev5YkA/8Z73kLeV/MJCdNX6gi/H6zG/xTvkwreTvEzSJxpZE/tTtagHmoqtHtvU7HtHgIg4CzXP41J3nw6Pv8D/e//+KdYavbV/bxazivmPmHCExXkz31Vtv74gXDWx4fJNafb4EY1chzrxZ5qC0DMqe/q1E9UfPt4QBu15GvPH1Iyf3NdXBVRezmqYKOXx/7XZcDlG8SQ7wNd5AJv3HIi9toNiWtxe1zUBhCAtRQjC32NfY9VdQOe8ZcYo+yG+Rb37ieHPc68EaSRrEgLen2jO17wcg/8rdkTaf2q6LGB9AN3WJJVnrLenhBBO1bd5EwcJo/C+IwfbHMQueJ2Xi79VY8BZ3sbXiL4ocKqccGy2sfnbuiNyNwLqoFTEOeWPBPb82R7EWP83o6Zmk24dESqA45w0QOPTYynH4Jip3jmy+G0DHLgUQtUEmAAlZE1oGe5LmOpA2e/BapjQXEQKib7wxW/9tGO6x34IDWHv0f31lcUOlszUouDcTV91FMq2qTO/glbM5QtcVlayXBpj03ONxc5tBcv9am1/NURNsWISFT37rLBtX3aWvCNRKZqxXJq0VjSrXlTyDVZgMlzamnvNs8eY+s1JjWt2KlF/vx+5DwwB358g9vHa0qKnfrEnT14vhuPbzXXCj5WHbKc+epqzzDnHWjbVLpfxwgbwVCIGYE3mQ4zHNt/ixmxsJziTsHN2SbfPPJR5/ChC7Edray2Yk6twa8drLqZTJM/fXDeA+hB2HX2fH+SJTo81fa5F74PSkenenmAOmtlRN89ONPn6Sv5xZomqKkdEUKMhaW6xYOdDMhdzZ911+wWDmrgq+WMOQvDt2gW1YBnT2znZFRL/AiDKEPtzqBcVTjqrzVLLiq5AWT4IACu5WkCyIB3THjvxDHh2LzdFx4eI5L7nMuXRtci6MHqShBx7dnVPWkblm0lTv/iBMm2OZ22VA0A6B/kW18w3vB13fylsU9OE9L+Bv+MPe+aMciNc7LA2telFHQc98TNenEWh81zuFW9x/PM1TbB1nc8H4z2sg3z2N5jV5h5x//WRdz3jJ6vHiuq4GcQ3+UHt+cR/ECtnFjPt/qLq5+LCj7FmvOxc14Ry89wIXHnUmI3FK76PBCbK77Vv3VxUoBtr4lmsFJl7ZiDQ+oi1t+M8ZM7fnh3mIvlBJ21pvdc5rbRL7HwTH6Cm746KyhWc5nW02J1nbrIEU1cUDFkoVAH7LxCalnWxSuyK/28Ai988sKw4UTPgp0l6jsA/azwNdvUK7iO5StGYd0o5PZnOnD0UZP5wUHiN/pZPzxqbnatyws+P/JMQM+jdh0KNO3gQtfQsdI7BvleHKtz/Jcke/Tjaw76+PzM+eyFejg5160NDOutj1fUz7o+DV54/vS336IRrB8el4t0XtH+4cdcoP+aV+yTw//7nb0cyxPxfsjcrPsE5OgkO8XNT+vM1gn18K4Bngjg5TmK5APw8knxuWjnh1emMX/5/SefKODt9Zxw1pMIBhycx8w8b/eENDcd6zg9jcGe92DMfOKz474B1095ldwnIexz7LwTID7+5/uP/OQ+xb83p7dw8jQQx3JeMT9/uhObevEdLTuh3/SzHhGZFo+YevgdytHaGvSjK/YpE6+kYBImx+Lh7dGecwg0sTPqa9xRefywkYY9MeRE2I0/MQBj12XYxkwofrU4kbGzzy3xJ0UopIpRtt1PiPdhmeMTxzbf9iEkrbNa6RtrVmAXoyGbt46eU+CGA0GD2JkYqW+kfSpA9B77BDdf9msjCmh2DtfmiWmfmACR79YRWPzGELGFjAW7Ne2e2wKDhma4yrR5D0vXk7daRhC5ZmoyMLt2n422Gk+vBnQyAIuW9hs941HXQeFQai3lhGr7tXHtMf4g93iONmPZrD2Yw5eQRkWLs/Tfx2+mNiYz86kVsKMT60vcnkfs7U8SNOUGuGq9eLqE2NssZSOXscdiOcc4mpcn1kxh32sGewJ469yeYpvRyleTFCbex+d7bI+8EfpyQyWPesu1mkdRa1Eccjbf7Ge3HKvfeoLFDp/hydF+TrFY5QOTkU1nqxjT3IbUCQZQ41s/JqNhKMeei4iAAR0To6mbhS8q2sDz0932b9nZN+dYwqtN7szmoIs5Op//g/4heG+8JNsCmgFLiZ11VVnZ5nsLsnBj19tms1KL2CtaTeQ9+XqAmqFFrYQ2jALfA9A8VUdUKsIE33KyxJUhWj/uWsFvgzCJYeti9gQPibXGf+KXF5ugPbiQla19aZ5Xf7MNnhzgV3fmzaUjmxEgJYpZF+9s8VmoI3vfukr41rrHmIAMqKpH0ptidNPz1tnjcniNhKHHovnD5wlr4vmF0kTnZEcz3NGz/VMB5nydereW0dFM7dPBmL014J8Khr8RbHVURlJP7nWgI7eqdvO+jfdqS7gP0NZHB4qXAnoSDy91MW8fFjEYYaMyOHI6iLmrzLOWJn4gdWe/C6PGXhsQRqHYZpw8t0bzBrI1io5m+7p7w8vN9By/R6t9ePDy4I+NPhgjD6puvZsfFxyMZpLB9dpwLI8Y88fbMLGNbdhhGA1oWRvH0QtyXtWLnTm2tXsRY+LGnLyHIM7Mt25q7NvHq3+rqDaCqHlqpC37S0BtOLb6zIO8x2MTFoNPS+JORAyHm3D68YRhIkqt3zvqbD60EAz39Ja6S9e9cHE3zbnYTgzvTPh45Ree4L1bR8XDKzGE2JNaV/aVjq0zMu3s7ONDIzeDra2KpCvr/C7ZdrA/w4RZjdFjl/lH3WoPf+yVwqQMhoHHuYslV1PN1hB/4wnmJ7rRnh/+zhobF2ymi9u/pwbmaG9O4jWPb/WeOjLxPE7CXojPk030gm+E4Kugz/XkLOYm4pPY+ZAz/495LtK5rXCR7tvcfyeIv0X/rX+DztvszZ0L2XjUR4vyafP++7HEkp8e+GpOYn0SI9fguLYvBHNxykX4eVs7T6Qlllem7V1ewWeNLt4m/mf+LZy5Y1sezs0zMlWPBtTdgZ3ziOHtJHG+OwBrjrFv4Z2Q3leAnQ+m8+K8Pe3/k6dGePKTC3KQ+zb86kqxXGCZKVDOhayaffK5jkVjNuqLkaEOzp+75NbJ8cZoLfQgbk5PR9Z3PrbspM8WBUGMgzkjWyYSje/VISZOekxeIpjvHoFZrk2ATpAdxjidmVzQjR7omE8OoU2hjayXg3QGHNkBVVtA5z53UASWF9YsJie5JRjzs2M6rmAyzG4KNMqiHp3Z3Jz1GdHQqmD+UVvPXaqwFiboYQ0uY/XpUrfmbtQez1uDnnAkXs74eq6oxnoqg7g378ubuenLA/+eZ86B5pyGt+dz5tjQ8b+M62GWuGkgPW2tMuAx19IUvavs0eJycmZVTLbUzAIdmds7pn6Vw3xZ+w2W/G6ZZa6N+QzjmW/e8hlnDUVuLpDmw5dh32JpNNjadYIk4cuDBr+KWNzJPuGrednML3ssxwjTZi4vfMvFsWvq1uDv69ECxmgxcLIiONj8It5K9jjicoyjdZOrg9jNO6bDwfoqJdUUMFpuQSCnjvn90TX2G/fmpr2uQ1lpVQLneQyXPB/9I4Y8Pu6GuVWg63KjY8dnP5aLuHat8aLTP1pYFetHXLvTj3CZBqxw8n/fPC3DqxAZi9p1xUL+Cq1wkD14qAFT0Oa5xfbQKFnYiraF1QWFX5uIhjRPtYyGdUfOHnD9WYl//NusKh8Nq3P3Wxa5tLVPcC4Ve9an1vF5squiubfuPXjgz53B9GZ7Qq+O/km2eUzmDaQKxA0+qXV309X2idWKJobF1qSD+rBLW7VYOHZH8yUeBgA7qkdsApsjPijRN/3TDvHk2ZrPPnbzBjCQWS9n8xz+wW38qnG/fQ3DqWHqOXiSNaGiVtr6373HRWw2+bYuEm3vUOz8FIH3jIa6bT+Ohwl1wcvbPvvqVY9dzx8QaLkammvPs8YPB2BqzhfZppPSE1/vePbcGbv6C5n63vykH6cZul5dLeH22jxqzixxVUdepMDb4YPiLOSJyRyJ4zHo7+jzQXHsfDgTfLzIBq67uz39aQ5q4QE2gzh+uNjggQWvePkAOzrEmF8gYSXPsUCn62RbfbvfiuAHtOcDuoxDIUXAna8OvKyv/nra552bVKLbT32IoSfDt8d296ttm/NqMnHTy1GKqWuOKzkO1+RgZ271zHyMuSQ0lXmizXiPGUVmNfmOLkXUxbR2QNVRuCx4gWSM31xbe2yYD6SR2Py9mj3c1IKqrcm9588GBv/UDh8RO3ZmHMQaYFzuyli8q1N3onJb5m+Pf/+Wi8pcWHJBzjAn+mKzT7HZvZMiK3hm9KIvmJzPa/ViF+1zIXwvJjFx3sNBDBGdY+CLetofPPl5cvEJ5PxtNX8Tjp1/58aHwfXTy/tWbd4K/8cfvLWbV4/7xAA1oelveR7C/4fOMUi9PBBq3fQjnwqfi+89X8zO7Ts/P/30NY1Jvryd3At8SuN/qEUDtFxEw0Os/UM5Pl51D4zc3topiNxbU+bisRMD196JxML9LUZynGFse5R7CP34vC8irceBTuJKrMdx8pBgNYZ7acUmYqjJSLSjuXvmYfXYaKztrj8CZvHdjvTD7YNM9NIn+PKzF2yNwjm6SczPM3ZpL/XX0nXnB1OiUsRInfnOYNterlN9E1jMaACORvbZHt9HPGwEDydQayNnI3p+jH3yE0IUCPdLnhgei8FJvFnhcyyoa/nHtDEDLGkWG2kD5kIWo/xlR+gJQ9H6iG3+i1+gIdElfxbUiAYGbEy3BvqxXOLEFGXmiTMic3MaHWBGY4IkB+sahzMLjZMDYQGYe7EYYgZmreGZoIudOHIseLUSY6w+SDpY9hhfvkGqGVTjineusrHX3Pq2h2Mrdrfwb017fLKOeXu8WtHjvKH1zy+h7SsuGUOg/hYS68YOMna4GK2TnD0G2OrpftIBwDUjc5fx5lsXa8CuL/aaiwXcXICLl+uDH8fDER/oWmZ+3fGtt/s9VuRaX99xufXDVQL7+shYvIhAXC89Gg5nFnrhSR4wGec4uboit98FZXtqIpbjoye3tY3ZpEM8eZu/GI/diw+UeLz6XMM7ttHrh8SZbnOxOOAm3BCLE5zNkLuk4sSDBtuozvErQiCbzxPw8tw4O5igbVQ5E2d0iaqpOcnAwTm50YaeFdKQNgJe8Rjb8KthOch0878HwlJD/v0doQF1Ol1OcD04N+97sMjkidWUgE4tJWI9sdNnCjsHl0Iztv7W1h4T2Fghzhe3nI2tvyeUErJ5jkfdSBv7Ri/mOTaPxuVDhXMvTohJfPjhoxfFwZkx9dzY2IZThKHtfxlgjxFnCNuNy2PMLoVlQ22Tl4DTE2z5OuvMXBvSmFBVj7uyI4+xnDxYQ3/HE4fBupujalWPw9I9N86cghp/+U6phpPFGPLJjV+rwL2zA1wc+NFBDPEs8c/cCZvx1wvyneFuvHbm+d5eLHZvJ6yPThbhB+txZkJy+ZjsEQB3NfKwWRjmDPjOA+vRsjka1W3B4BsDhp99G6qv1vkAO34vXuZCgBwmYtPiXLPMWO30bmSeZ2F5vA/X7ZGoud8ol/Hw5Ofq7nHA6pmRhOIAZTwtJ+jDYIYVKCkBhg1/6xmTjqpq/p2TBD1qD9955vjlJnrWHi0ONOLo7cY39eSe+o2BNHAerFJDRKJp3wJNmPlnLz+AQnFnsNCTfeLxZwjJ3GUhtVMP1nxzzjSyPW52OIh6k7QHnCcEVmttnDPLRwnbq+7BzyBveLlg44dXm3n1mbduk86Uyrr5//CiNReBsXMO+QFvZAu4GprPHnEhmHOXv9lG52L8ALbkBmNM9r6inD0lUv85P7Nujmrm/kthxMbEBbf/JiwX3/DzCex/fOmr6b9RS374W3Eu2sHSF3L2AppeZ/BmgbwcwBy/PYErXxyPvagHip+3kP+Q2va+NH9lbgx+LrzpZf80gD084Q55f+gDNW0MPUgc5xsEM9AgcHBUu7qAnDk4BiTMvVMrZwyaZgNIDHnkJ+7Nw3oGrODwd578+fJ4YdYK4HKpEcxqwomuGb0Zts43HvdBnXwx2qTykxfNm1/KCdq85TlGRGZkrZ7aVw63703q/apYN8ac/pQBotYytcF2QtD5jD1Wk7EewDFYQ6b28rsLIwFiGgKPw5z0rc5Svb7O5QxGv+cD0VkxBzL3+yv89HR4xUyvgK9WWBibxWMQ3K7rbU07bw5Sz3Ebx9U2xxLDGbW198NvHT1bmm96d+yPjrGZuzewMo/9HJes+3tjY6022Ow/9NTevk/9m5e25qvHsUFs9/y0hhFMS/uuHOSQU8amCp99lrcSPF8nzwpqT3a1+3J5fD1ujb9PdAW3djOz2Zozz9hjqXarqX19aoteNV2XvFMeLPrLUVBrngBqySjX5hxfu+DCfu6DMnqWrz2nEx3MwxPOhWoe/M7BG3H6ONHEjRb6ttcqYJsD3K5ur9Rh7PoCD9Hp3+nzjfG4AIvP+Nzeq4pQVbjt9HsfehgPLqlPvnjsZzSdY1xpgyESw+gJzTmWUOLBLf2qCjZ8hA0VqAFV3+qOsR8StyKKqxhI3jtYi3+EklOiEbLpusTTpCuLZFXLnu/KA4lefU6Yri92bC7fwr6bS9mYTDPC6WOMNq6ezDM5qCfXHpDGFrO60EIMazwjbaBl25rXSQSc2sm5QcC/+0UDkfjDWM0ug4el/jkuDci2HvZ8B+SolpiS52o/7pNrNe3JAuLmKn4oW0sWW9fGNuPYR4IPHFL7YspBPwBkhY9f3Bm1IT8289doDYMlZtsnLgv98kmTDXzlwLKu5cV2B5mCkeeN2ShkovNGEODtgZiI/s5lXTwOwGM/4X/C1VeJOvLmzcaAMdeLBkg+fE7PpsdKMeUnluF+emggpviAnl+iIVzcxK3W91g1B6HtM77WtXnMeDYoWKmkdr3841m/XI8+fsmRj5jVVmItnZJd6bWB5xcxnL5iOHxjsG60l3P0rIDBemG+t8P4yhneXFzsHIa9MMKmiLKaCnFLq3l43hqpCcyDDHRsEbg+9wdrwGQK1geYtREx3co0UeGw1SUQxJTa0dw+2IkasYsqE8bxarVOCKXufuAi90HJIQEyPUXZvrCoZH2Jzt5BbxXbJeZ7bl4eaOTCX6jHdKYajTWvs7jSJ+pdfjliHffyuA+OvWXCAWbW3cM1sXHukwbtpwg2zQXRoeC40vMx4Bs9vKLLK8D832wuzPnQNX7SgFyY9qIX7XyBI9decOefkPsWcWznIocUyx39uTx3zbV6PF647ivNPvnkB/ihNRzoYo/O/HhbYM5yBtP7f92JyafJ5hVy/qf3f/7nf9TOK+VfY0Pv70nMq+vU9mMu3CMBBnXct4rzf8T7pAQX5bxyvjX8QI35NDnW/v22T37wqnveTh8u6NDkq/HB8Hftf+Tt9dTicUl+X7EGV6P5aZF+JpBonT22Hbiz9mvsanN+zyts6ICTxxdc8PeJBYi27urCYh95xXw40RBvPDc3ObE4MuE2dvAxgiQGHEN88lfLw5UcxW7e7PcxALrP74Flgi3xaKMelhn2Dzx9PJzrJYJ5YriRa77amDnOHcBAAtyalkn9szBq8t2cZqmO4T01E4dudvkh1L75AG80LN9qMqZawbY+gpcke0fiE9v7Ktk3e6CAGXPMpncAqq1aGtBYdJrLMBjGPnlrKd/2COg+jrr9SMDUTGkI33Nh7TYCFyn4+W5cHXVaD7Q8cSVptVVa5psPHvuZPeZZMmlPxgguRuUByrxYkmjAmNH56q+LuOBaXDDtDGj5Zntiv+NTP0BrIWpyMxvb1rnnkfupq8eFOEg2tj02p+f0eJPbfNkrg5CGQZApi7I4H5CpnlgxrAe/JI2R4tm0Z/pC77nCfhC9kN6+hsnpegvauleq/Y9r1Q5KTm2EkwONmc8yk2WYWOt7/BBNXbfH1MnI1vC37jJ7DJg6zmTW7VKPTExtpv1fNeWfPOMH53Ef9cV0u81rH95jjcR8BWafI4Xj7ZwgpVUf2/W9j29af6DhmGzWcc6bqYqdHPbw1ricP7WBRW2wQTQYgSxmiE260yTswZmAOQGMSbbRN23d+4vD1VFPsjKtuCNcIQdYErdB8D2uF9FmroInJNODS+zOW/uux6p/671Vn3rwc+DyRUSW2XfWvpYHm5i5KFhtqPro+bPWnvXh4XgMT+PwEc+K3HNinnnQ9u36LgafQEKbw1/gLrMhU+OwqAGbfFTZsSglvD50LWiYaolDzdvTgAJc/quvwdunasH29HllQCmghtVUhrtFO/xHx7he7kV7fuZOXekApgZ7djiOWfe5Q9w+JA4tp7YAdt17T4QHU9JJPfrYTR4tHHt5aw3pKKqyBhfTfLUTe3pooYpSBxyrzRLRak5yDP+RkwnzDLFHS42F3Xhwnpv7QtxROw4AM9Q3PVCi9uok577dvZm9AtlQe7L1ko8hB3GZe+eIfXxMRjrQzHOBFIOvkGZPj98fMbmwpBjs5roiT7L1nUT01gzkICCjJ2mnz/a4J2DQ0f/ZzxAdeufLEXNjuvXYDemeb8v1l31w/cU7yVc0jFuzB4GLwPQhcyBkOtAza35lsXlBuhJhDZejwicuvn541mE4E/t78tRsnZn2/HEyjWiVJ/hMmje/rasDeyQR31qyzxwSdp172eVzqthg9js7Ywo3wx5nSxxuLuB4ddmLWP43eC7Kf82nm//GxXmIco2b06J9JcSL2XD2lQcVu3sAACAASURBVOHEhsxXpJOcJ49+9ISOitjJA45zmIt5pOyHj/H32CvQC7Pk4jS2AgLz3Tn7DNbYrb+hhbgVwt+Df/371+TshfUP/P158F95qzv/Em3+r/cfv88TDtTOxXt+fvyB221vQ/wPc3rL2+Q7Ukt+9/DTejjvo5caEYaPYrLm7/HsjYjbL49hjuuP+YT1Hrd7YPrnQe87mpoVnOfV1AzvDjlil3eM7UR16A+8f3Nenr2g6jFob/bM2jxwaCtNVrVQm/GjpRWXl9Lt3YO1HXZFp8fBXpXduojh+JzBMovFeb7qX62rhu5nCB5dLDw/DlssJQS7euu9NZmfODDwjWaPsIHc1p58QRxJCiCGEfDWIr3iYp8eiRF1o+BV82gXQy4JWt/hxYqq1aLYss50ucQt92hB2tuek1Y11Q4N8I6udvtyVxIeSq6exmXuY7SeVdi0k9xZ9jPF/tdaYhULvHMxiSnv8A3J/0/Xuyg4ktxKltVP6UpzZ2f+/y93VlJ3qx9r5xjg7iz1eCYj3AGDwYAIMhkkM/PtR8O2dyebWdSQWZM7mVXxdpU6tikDUerYyFXFwflzsqtCQTK6F7l11DHe+PMtZSzk259t5tYGIJNSVZPRs1mNE/ti2/XizjkwAPh7rEJegQJb16YbfXjQPzEDdOfjSmb0jLF9cQEx3Az6yf7kZY4d44wCqutPcKsN9Na2nKdveJAqZnlFZdGascLV4+wCU4YWZ3seI8/oTCq1288611deYvnarBKy0j58qU+hok4Wc/C46vGBAxg//v2Ru1UPh+jJ6fyILACefKnlEaNN39WtDDaxO0afdWLL+lAIqZZTRqOCyc88jCWBr43ANNQS7RzcNqu2ii4+lhFUytsA+b9iKqZb41QXZEz3RMUfnsObNd8kH1F756sBvBE9KBOHrUzsZ4bcIZEPs+FuTs6N1Ul/5kFSpg8hy52IcKtrcpCz62bcOdzWzn6PjjG1g1MvdawfKPiT4+XEwYhzdnjlePb1t07yQ70hDauIfeDGaZYnJ5wv99ZBZjyqDO85ds5H++abmq4+dBB75dSXOGJ2cPGcO5kPJLGLkZPYxm//N3617j5BV9vylql28w3XsMJlHyYHF13o0r74PUcOJ5Pw+A0fE8DEhs16OQYS6J6NWOxgeKAhWhRYbPn6s3rEBXOfNG6exPskP0RwLffysR87/CQzxzPHho8cOxo1NejIfO4n9ziANvjEnopIBX7GyTnI9WDvpUipTs82EF1qa28It3cSZMM6507fgceIWPYCypKpvNn7kWCsuqc+lll73Ah34MOWBfuxopchdmx/tls/6OXofQiuYcuOuZyaam9/mXObjJC8x3I87cWcT49g88odoGNqxcF1S/argww7r113baSdLzHEzzhxse3j7Wsjw54r8BJKRYzq7tx1NvpbshlLWp3wlg/01as9dW+/6ZFI3oE12eMzO2suBHt8yxbbJreHpmg89gzOMS5YeVeZf6vFR9r//cu/vXHBypMELlC5uFZxcpgerXF6ETrHEK3c+Ddnc5XdPpE7g4tf68mSvOb+7jf/uBr9xMd9i1x7TOyz0c8Gfinbk/PYbx7U5clCLsb/+jf+MBt1/RLeb7/8mD8gB9+v/F59avuOd7ejgxr6UX7+UFpiYucj8GDg6eV2WOHPO+i/58aLEcT57n8Q9ALdQJRBvanFf9+nnbpitHmA6v/9V2qZ2vW3h1RrP8bH3N6NfecxArVfhO/whbws0ExefPX33E3VhSbcXpcmtj23x2AQm8nDMZrVy1e3TPEfsubYbcxoAdXYbuum8/FoGo2eywYsJMHFqXN4V/9y2jd8hJJzsnVN7vab+6HH9JVLnwmFLJPjsu5mKE8wHt+thYSMRNBzEnNzPBhsbcL42K1Q9nw/eLR+rBvv4xJx8THYgmw9awM73ppmvT1sH16WN57ICQiNRJ6DzroUsdTsj/nUPsYcN+sIAO3O3d+Y5SkSe9nY6vOgkJLoHZ+zPSYvQjAk0/fqiGE0Ns/lWfty6BebGMVsxD1OWJbXn9t/dm5MfilGlFHhLuP0Ra6kIiffnKfcMQjcMdr3XPdizv40Bmzh5VZbNN1BvYByGy4DYgaFlzEo59oHy3niY9DEb68acPVuvDo3ZjlkJX012kPmck7yqFlu/PZpBQYr/+JdoX8AcVr3WCZddkH0x1lNA/+6psVvuo/7BrXk8clUAaokQLBvT09+HQLFVDn4zIaGWmBaHZZlb8DdPsDf+38jzGdo1pCRgW+W2DOa/q5WTgG1Y/s4TsQ9Pb6aiytvooa2vxXGWtGZvPND3rATFRCFVji+DkzvoAHErAh8DXsahpB27e41LVv2aAvmaBwi+zaVbCb25g2vDMM99cZ7Zz05IMuYpjEtx4vEvSd546nJ+I3FzzwDXcxv3TEYNlYAGcX3JNlYgGcuUVbAM2dXzZkBkuZMNIgRXh65djN57fdBZ+JoPZ6Ah4QUDw84czZijwkrUqyShicyE1MDyMLjEkOP47Mf0oMtkqAhzR5SBsfzAp9jcCHCpl/GEOZkNIRMbZ4bxLV2jKRBJ7NNuf49B4jtyKTfm8AnGLXBGfNodX/iiG5g/QF9+A577Ou49yZsW49IwgeHnYj2uPcZDXHUl1h/MBnUWjc2e2L3vD57k8zmxVxpJj0aUtTXP1DlXSHu0UOfp0fDtTmbLU/c+SnJQH9498GtxmxHu7lboC7fyVp9wvg4KoAOKz0H5X5U1fzkGtynHowh3ZyDae4nKHbiPW+2rsNYA1sxwwWVttXEPj7ywy+XPszlWF9z0R9DevwCMQZiMvE9XOKXo1k3u2gijVYQoRwnzrlqyY7vZ5wjKW4dixk24+WeJ1pwfj2sQeNmRXcVrWX3K0KeobLGD62fOawDQoZ9hZ93WDnPLnbakxSxTd8IMXRzadioGHnCnAtMfh+7F+a8az4X5rlI58KV0T9MmAtPzsfhKhUXqd/1I+O5kPX3r7mgCu7+8TU+Fp8OzLOh36cWn9jInl/3zjv0P/yQC+W8CMAr8Hz1e+oObuPbrwYyR1D3jRnPieePvf3tf/z9yz/TIF504Fzk99O/++N7X9Dqx9jz79DyAoUvTKR++H78kj8il3fhv8+tL3xxPnVQT98xZ00fc+MHERJy48K9jSKi7757nwgGP8fOdXrPoDW8CGdvs2uiM/FFgDrjE4aPefe2IUv61seM7Ykoc7ZHzeX9MUGkZJzzEbmugws3bk3BGjPO5mttQ1Gugo3x8VTIQagP5+a7D+vb2ydngWovoaWrC1Vq28KjtWqKYWu9m9qaZnFswXA+45s+7pzYSl9dYJK1cCL8PngmGVLPCwov52rbcHFqTp4YXyzzo11nud9Y58HBQyfkc86mx2o5plMlcUtNYYCkBHMerKF6drVYdRmPZb0XexK0oCyrDCT4t67LVQnEjhSmxU9VVpe7CbRnWHBYRwaYdetyQ0ys2yemEMwG39G09sG/PlOEYwLds7Qm8zZz+wwRKQUc/s2jPb7Dj2rDw2aOWcIhN2zU2WOsLdSo+bMh73j3sbqRYSEVsSfP5JZvGV1YG1ngS0BTPbtKdju+ZsECjDDG6v2oFz5BAgY85+TEEEveD5g+HcbYU5YZpjv41TXRK0q2m9rAieF1SvtTJrfLv/27eUjYHGIyXZ0oET99w/6O7T02etJjXoEyaoMvkRP8NQfnnU76qA54xpSg5VHbV8Es9Wc/WZbt7kfDHnezTWB7EssY1TKE7YUvYxd9nBFazLC4mKh42uD48n2Km4ht9D0Z4CiOuLI0Ckyps6U5GW/Dl0PH+BpP4mWKg7nhw2FA56CWsxGFoqB61lqes4oeGBYnG87ckOrJ8BU3GHHAJEp9mTT/5MNOfHbVTZ7ijr0QEMZvH9BiuD+wBiTRzL8yfbjsNRrIHU+LyOozx+kVEL31Y6eWauG4wR7lA2IFc7u2nNgotl5WBmBywX5i4Fnj2FiWn3yMbtWir/bVvIiRxDIRiTlEE38qE6LmQiZytJwaC3N7j+dyR/9qz3571KQJwbn1g3Mk29O41U+sOYewPSdAdQ2NWqtYTqzBn56ICssJCf5g9+gEpIQK6lmBqUFXA9wQNq7e4UOj38PR5TAQ07K3NlC3N6YXszgsJ8v0htjGzTt/Xtw0n3HEBLP1UWav5UdMdv6OesCN6kdofcINBL7JdcSEs1/V2zh63uqLY46/K2vM4hPRegaib1WUc3qgaPjXCyeIxFuvU4wdSM6X2RK0/QVvRvqRr6Ho3shEnR+aMZAXfhJnbh8zbcfLxmp7C0UrvPtFQ3EGi6EFWa2NIYfvWgCmxBm2IPOpoFbq3KudWDxM4V59yysNm/jaykssRnEVBUfzt14T1UUGL8S4vpNnLvR6bOOOnRyM334rlt7Yt+xx+XvY+aj577kQ/9Xfx87H2X/6xY+4864w7eZvGvR3lhPDRafaG99c4Qywlpyv8CWW39n+jd/Zzi9k91M3QeSdczmC33ea7QN9Dq/vVP+RP61m85Ru7s0jNptKeHqCw1tjzjkQM1S8UPDlL998+evvf8sLAf/vqUfeifSd87xIgAb1+5fX++42T3S/ze/E+/HwzL/P75kz6Dt2cjOnOeR26rw2tcX4R44DXGgit3+5nTyZn0++QI2fjYOPwfOi31gIZsze1wGyfGtW0bwYgjD1ZLOY+rMdDhj14Xhsx54Jek9lnOcUPFhjZ65seDKEdDpbGGNfJnvBsW/f8O28+YpnuxcvYlgzySguk9Gjxq0jvCvraAQ3ccQ0fhW1x9snailaQherqL1oTyYK1uIb5Lx4U57NatYn9dQ/Yic88kbfaO4pkSi+AwLXuphvpli3n9QPxsw7y355ieqyODghzthIeaUkfsasi4Sf2cO/qzGbI+e13OQDPz5LAzC27Q18QBaIrKKYMOuQe5CLLfVgAhj27k8vL8/mFHdeMYKtSfXnXJUgm83OjFzCksd5l2L2PDKevAlsryhh8WEZQuLLWaa7bs491mLkU7FRiiCFvD1vTBgvQy58ieuPKWJzM3fzCdyNXIlTHKoHf7jim3yESDN7azRhMfgZx+6sNSlsorf2ZiujytSc9dacPXWW9M7bn7DgMxBEaj7ndEO6nfxZEMeqjOBBbM2736iVscev9k23LOegHqZqOlpWv+GbubLhWL63F/U232Y9fTDPIhJdyrFir7Ly3pqYdaAvK3QRixnTePeFzK3rvPgagOccsbkxvjd+C5zmD89XOzIgoQeRPWPzuw6Pa8jhnCSb1L0xaZoYFm+xW8S2oGs4d8g/Mdju87gqKhup0cA+oOyxg+i6czlbhjrItjiDBGAd93Bkh6VediElksG2JvLvyVEf/iJjf+reE2OlmA/wUycixLGXJ1uPV3O0tyeS6I+hPzpPf+LdkwAgkR07I0tzfOLqr4bMWUYn2O35amG9881LjuKImbw8YDMenuqtudsyDNI+qi/O5TuapspKW11Pvoo238aWN3o9oTYXR4ss+VLb5mrmDy2JW83dx2tw887iKQj8YxXGphm3d/cEf+pI4P+NdXPK5Ml+U67e9vnancW5etBAhipZ3Jy5AZWneryQjGE7ZQxEGbV99o/VMOW4kbM8crqubaOtdIodWvPXRA/XCTOxpnYup7Y+afdYk0Nv8wzcYJ+HEzR9cwodkwWS4KxvLeu2tmCsjdgM4FNs59na3w0SI6r2bM+hm3QbD9X2ZPu4euy32ujL5CWAEfum47Hng1+x6y3/1tHQ6oWg7ySANVF2EE9HSXrG7c3mOnqpL7hFrx0bQ0r2roLLZOd3NtHjUJGJlm35Lw6ofQ9uFCdX8Ln1Dw7St1XV5F3WtueqH3nP1Zz30VwgcyF6f9e8H2fnnXPfTebKPIO/fM7vcfccRGO04GKjhvCxzP8M/+b3XsjD24+J/5oL4cTH/j3/BzwfB+fiPFAicks9eQUmNHmhgGP725eff+LflOVdbT5Knxx2ZXMRxgi+SpCQGQRj765rM2TDxS1zXmT48a9/+fLXv//tyy//+il15n+R48j47de8q+4LHPnAtxfo+Uh7NDjPmj8sB5iHfOwM3pWHs58MaG1IQZuSglfD6EMVN44HuX7L78N/F25jcPQ6HURuxfa87XEnj4z7ZFPxkwu8CbKJfXviiyHDJVxBsDNUczR6ntShb7LJBxY02qZlyhwJznWX7Vk3S31sl3V6g1ad6GYy67GfXGKySZHi44CBOvfc3719OMKIgfPi7M/wWfPDAfdWCuRWWyX4makBQIY6dk/y5Ca9OkQ2VsPRVRZ51kacjMRWL/4P7a5382gBuMFMM5ebLYu5uKzW4d4cz/4IT0zjS3p6i1XKp/fed5P0jdh4dRCTCToc5egc+5iz2+MBVnM29JG5fXD22SepYz99gj5BXmhcaonAlhjH5dFGDLnUnomjAuBe/VD8x5ja6mtvZBg789PDJNn5JFRv+athc5Fnz4Xqvpq3V+e5zEhW68zVOb1Y3Zu7kGjJF9uTh6CAT6Y2BSX9nppYMohzrL0LS9AXO7mdA501sDdWjKSZqVlA4OhT0vxMILLjxGf5HiMlqbt1tMZybOzmg397ub6Nat72ZntCzmqKt99DXEYWxFHDwdmB2IDMXI1r78K7CYi3rpCUD8fgV7umbKxd3x5PkCY7e7CvLterMfveN+ZYEdtw0hto7Czsp5rBoS95ec4w/bj/Bz1OmuAY52F+MjRHAW0aESsmvCQbGhUhGITJiy3mM2Zzl//yWMCqXX2lYRtgIpJj45stdurBr7uatPguSfXjG1Qy/OcBMbgUpJghqzm9yNaOrfGAMLVeZ9WBY/It1fbhaBZ5dRDC2BRqpI+KGR31qs+cI/TNr4ps2ssyHix9qvxhurgxU4z1HjEGLA69GWzEoXd6QZhBPfFcBFNtja977zhTezDGzXHd/mzZ1mFRRjdvIlSi/TqNJedA6+nKiMmF5fIzDxs+jBNMLKP58XctwHk2edJ3jg/L3IzzXst6a8VeRvOWWG6meA7PaBlIfdm2KpAmL1v4u1rzooLL99Zk1BSwOsp/ouXXN3H424/hpDaIMrA4jaE/0Kvv7R+4wsFCyhrL5Bw+bP7F5sEUssfi1nd72fjmp0YyMZiE7YrUuTm3FqEn2JCatFXzoRz3vjuPNg6tOQevXhlurBhjC2Lbnm1QtRJ2Z6wy0M9xjcMppty259sHOzPvAhNWFHsY3/HmjD3u5lz7w617jq1PTs2iVTS6snI+4o6ueLDvOcee8fbfH0YyxOdxmvMmqOUxKJvmKYcsIb+115+fbuUZWI99Fxs5yNIqELaM5K+ernvRjo6ss7HS1MAb6t/6ZDq/e513zHuR2D8C9/NPP88aVOK88OQClI9Lc4HO21/hSjxMtmT6Qh4/zs2fLs+75vyfccYv+Sj5N9/+2ovzvKTuhT7vrPNudsae3+zpB3TE/vDLj/71dXUvzh43Zko/HLjI3OOj+fiY4NvBhf/f/vvvXlz/8//8Yy7Gp+Yg/5IL+L9zAU8N4e3H+tGH7vwLtfSDG++g9+K8fWFuPYhzzP0+4tDnxTVC8jj7y8/59YH0n3cZfuMFDDDRxScVeEHAAGpqk2WDg0GNvhibWI7J2vWx8Bswx/+tHAfndXvdC7YHkVz6EkP055BU7U/E4Sfus8tFXZ6rhZl9+shX/t4nyoVyZl2NGuqzJ62hPMUMwt15omhw88m9zQo5CnEbjZb42u/J+Ly6NpajZfUvx8Zql3I70v6bZ3KX6+a73G9nQ2J/IHu0rsbsuV/Xw+4zFs5J12NkkmqJwfNHhSdHfadHsd/OE8yqNmvmuQIW47NXTHCFVhsCDk31HSb5gddSWOYss+hxMG1tuDgecbKlOH9Wm4PoHfS1abeW5bp66+8xjBU8eiQuj9PTg9hMcXuMH5P6XUx9kDGInfjiMIpOXH2DLC5xV2cQgey5pJ3HbH6GbdY7Na5pYzTnUJqRvBmkzK45b3BV09OxAZpxSmGtPZh8c99CC7qIGrHds3bEn6/2eCxPjVg259atjaSnhs948+kPBO5ogmPj0aIdohmrUZ2qXc4pdPJtrw1TQnBZyD91WHeMco1GMmJ5tWGDT9v2aHDEVqMsxUwvs9j0Q1tM7e0ngFpXGTr7hU81TeIKjxnj6PnDMoumMnK1b6+4Q/SxxcgEdPRYNnCP7caWL1q2loTk/6CTq81onydr0t4DNQKD3ZPlCCEe++wRzlwjd4aniJrjf5to0ssLhvHJT8zNY7YYaBwaNyep7oE73uFSVYUi62jAPiJJPJV4UOJarWtf5NplnRoMn43xy0sQOfO19jHFrqP+GOHjdvJkZRzGjPrCM3HlpJ76N3D9rH1MHncZLtawkA59cz0Klt8Ic2J5RhbkqsawKIQ6t4Y7w0fs9oB9+YMBxhhBIoNvdDP6wwUoyyl46zw8kjybEpQ3c/O/vZs5ShgHngdQFnvfYG8smImBrbU00HpGM1wby7x6gzC2uTTDaqpVIJqATga/OdEXEvm0sRa6ym8NdYzdXfupFjgm1KOAhqOtx6X+xIy+Nmd0Gd3Na7FmzZNrcM22QdW0cXtcPYY5Wde+6PYuK46Bxz0Y3zEsFt174w9IVX1YrIc4vqNHEfOReWzDdfsYjI9ZjcWNr8exPJCUK2TGozLzeTyaKUZjwZgWEQ5qwGeUm+rAiUZ4Oy8iC3oyMQaevOCotwNlXjCwFCORzkWhnYD+oCQSDN6Zm//qkFOGQkXTg/A3sirZbh2bq7pANZ8ppJmexLU/jIyZ3OIteMrAEF+1TB76TTxauK9aVzLCwZidKnHPWt/XG3xgAvL45zrzXJxTZ24Hgq6M33ghIIOLcz7S7r9Qm98z779I67vlvTDNvwvj3fO9+Ezc7/mI+u+/5gI98WVM7lwobl/h5h1w3kVn8FHxvE+vP/96RS7sXtAzkaV/ZM1VMLxY8EPesaYmcHD78e/pUfPSslSXb0rbuXQU7Ui+jRGDMe9a553v/8rvo1PbT//815efc6MrvBDxww/ffPlf//t/5ffUfzG3L2SE9Dt7cHWjwb+0ngkvPKBDOdmgm7x724Owf4CP34HnEwNpkzm//6F/sI5/4ZaGcXAks4zhpUb/IUF21GgOpthneA60GcXEvu6e9eAJ7l59g3+fgBKz5ywMfKWaTeO+63jgyhejCLabVbMOzvm1et4HRo7GxPcWMmGLd/ks1ENgbhu3tQCzD8PR2OYBC271ikUVB27yyz2qFo+PdMXPJLvTEygwvzUs7cZlvXljutjJDfdNsNOvtMI/QKaEkrdKdLSMNJuVfg5QxdUQzzl2YuKEq8RXF7jTFzjAtQ9kvH3a3oSkEnCLZcdx39i6s0VPxvZjlsag7XIXJVj8Cc0quNFjiiH94CTV6C4nTMlgKVOLP3exMxJgv4a7JY8iIws7hYbVcqq65qqRa9AmHPrdbZ2seU7ueQkZazJObfYmjyf3XKRNxZPvra+xEjBVTns7x0hpU/eFHeRH7yA4o7ram8k/Xdn8B5rm7v3b5gTnsB7miqDITrOjXr77GNS57olhznjrdh2u7eMoFOcmOuhrs0UTWLTFtsMcWZT/OZaDI2qPRWNWSWJ2qsZ6Nxcr3YBGA8WekJnLkSB7WArxTpW5+m+dJo7PMqAfjS8/8YZ/5Kll02wv1PTpqvjpk342Yly19qxf3bh9XkOV+e5H3LdLk8CAmVfIFpgIEgbvA4ZOWo+5Bw6TxQZzbNxZVcZ+x9qynmmbhL+4lfAgJ3g9J/Sw6zFgdS427DVVyjA1dzN4ErWDQ0xsfautvakdG8OLdXrIckOYbF8zPyfofPzu48CSA/jkMm4OrPzjPxowMhK2xwGVjMVYqwBh0PdEkPeiJyhPWnK8eFWP45av1SJyjyV8erZyojO31HKaR9Jujh4VjAPoOSdGsw/ol10IsAk5uxYyjrCjmSdyE98A9HfsAwmYrU/Bi6h4+RZL5OmDx7V9kfujfyAjKLlbZ3TsMY/5zEsY3PSKtaPVtdabAy7LRONHvuK9Xx0Kap1qRyuuWq4uCY0ZbKmUz7HnPFreraXOuyXPhpkTqhhknLr3hStSgcV3sNhSj1DjqmVxcYM4nH0XHe+MwD0uXJzHpCdkp88xcgHCv6cyJ4Dc3+whSQe7FylwDEt3nCPqq0d3s5SiBvmggx78Do9aluaOd31lO9aBxzppXg/n6LVfbm0kzditS/Jnou54dl9O0HA04h5XQ/Rd7yBj0Oaec4vBFusd9tzai8DTYzN1x3w94wvH1QXjrMPD/93eJwLlmoyHBF6SzPlzQBix3XMTF4PQaY9rNh4T3jE1e832zHjOq3iSA8T+gUJ5GmwA784Sw8fa/Z/m7HMLpWPfIWa/7wjvx9v3o9IAe96mLo85F9D9Y2fY9513Ln5/zv9P5wI9b6q7h5PTmj8Qt9rJze+lsx4ZX3766Sf/yjp/xO33b/P711ykk3dzn97GwHjX4db02gKouSw75+PuezH3S14U4IWE7/7oO+O8yLDnBXz8b/Md/Ms26NH1/Y/0ik8axBBi3gWnEo4HeTz21si73fljcz9+++WHtOQvieH/s/OX4YmXMPZvv+1fyzeX8WGzFjhHQ9aazLFdm3OEwCSt9uKmahwaui7OaEROjvpY6CFD5wVmvpzN0QJje4udmDIQjvaNAwtLRiaeB/TLeGy5pWAxIdheandFIOM9h4LaHIectORtMnj+fMQfHN73eJOZAQdjJbsYHUrNvL7NVASH6uQXuLgyv+jykH+zVot5PfjUl1Ue50GoiKljo+8Sv1brR8fVf8KKMAhG+8/KmKI+apd0j5dhE1tu6lmeN06tcKY4+/HsyaV/Omh6tBxmJl/lnCaZa3IKNzvo6qiNcsq359fGbf+PgtP8WOxX8y5P8eOLwPJVfVImUfOKs4BW4fO7wE6e0ce6CHzhMyfZJGPy8v7aGwAAIABJREFUMcQiLMMaZ26wNjZBAWkB5d9+EzXnpKH8PAqUmPborpdzNQOTm10lZAa++TCd48vc8xSIYqSzXzEd7uf5AkYlQ5eJumb7hDCt/2gOku+jadYFZgsTVSwnlj1OgHa00rYv2PAtDmFqn94RsbVutFmsFUtrYYa9TFXR1d02a/PZw4mwHPPeaBjki9N66HGBTbTnn/1rjWRaFQarUbXtdwHZDncb8BHicTdPwT0+5SD/utTmJrbk6UfciRnEngCKr5p1mRBtfRK+B6jt8QLIoipgxR4h52SIf+cWQuLl2oa00BUNnoPdTEdqReNjNk2DYb4xxgP7VBwSLLPSx6a1dnlOmsQ2Olomh9jD+WpM1tjN41l5OqwEOWFT6OSHZ8Tc/I1rLdVTdYmxV9i2V5RXhUNrwGQ+Nbo2NllG480HWxBohnlO1vLVpsROAZMUJBM1yQk/Q348ILbrWdG/4diuSgFGO9bwzQ/RYZPSTQmLITDrD57kFaK9Yec4XhZklKOT69l4LWSHbcbW+4GJ/3A8ePjFN5baYAKxW2bL7nm1/Chjnm+oHfIRiX2Ny3TXBMF5ewxH/fvCxeexHx+YfL+ayXt6N1pEB3te4DAfmlTpvhiDIRzHs8NEOnJOqHVlbSzQtZMrHELzZJsBZnUyt3drj5dzl9/R5Z1JPgbLv21i0Blzhown/XCyce+UunxGH35+j3eevCPGUR6mdnnMasl860Ggmo0BRF09LsyJZshm8mI2xlXs6gX18NUGRWMkgo8fJtnJiTtf5QcKdvPpPFqvDzRR06OGHL7yribYBsfs4d+8R0v6r596BvfmKL7HfXFlZ9uhFGqLCObcbFvUEc+o+uPIeut5fHEXjS1fp8cXs8dwLwq5YOT3x8F70Uyy1ME74zHp4+Kcd4d5h9t3wZOE+PNOOedjLhh5xxjhXKBzXkIgf2zEepGd9535mcofmvPnKE+6MrxwzQXuD3ln+OdfcuGbC9rvv++/KqOtoMi3PfbxBgc1huvn8P/z//tH/8p6cPzu/Pzat/xsrDFMu6e+2uEnCf2W0jz+jBA9OO4v+WX4H//611x8f//lp3/868u//vHPfsRcIu53S8pfo+c+2Hffqa/5+Ng+H00f3MShCYD56V383D9/+I4e/J66eGGgLwQQ37BgYvsjf1X+jz/4K/P3AQQ2XgiaysR3Mz1L7zwX3ie902gefqun2BDPumz4el6z3qHyLLp/VyDOWq4bh91B7pN3TMNOFfSDY8+5s/mrK1yEUisTSLLjhaeN63O4coobvrwqxSEvLrFEn4FdQ/nkCvKgNl8w+I79EDCp0poWNb2EVr3j9Vg1Qrbhrffa6UPrXM/4pJ8KxDQfRTFj6NU385rHX7zHPVNX6MuNnq1W/XIGsfohtllE7TDbSUR/6h27sM49rs2odTWofepdDfiOtkyw9ziR6uZYPIRXu/TL0FzwZ8CBGpfKmvMNGwCHiF0cXgxq2vwhMae9K6eRWZdhuVvLZL68orqkDsY5F11kI9ecS9qCO/wYMoh9JJPNXmufMxaNQrNlwkiMeeEjPkMZw7f9HFe0dXbWwTO/xwWG5WSWnMO1ear18tgZ8gPPqMbO19bV8LrY+D0PtvxEbyFV5rI14bqM5jEbNuIgvnoJRLN9NKddHZ3kTYxhCcw3fG3enfPcksedd3wuTTo96hws3djcrM3FhNnmdL0xMUK8y91P729dMF/tUNiT4KsL7x07l5p+GNA0aqKfHzkGMGy46KM8YGf0Ar1WnXsC6U+QvFkMZBqE95JUwAo3MhslFidPi7XokFbPY6vF4I18G4+bPO9JsFx6UuH1VYM5nFbr8rZRzY17ccffcO145bW5iZk8MKInXr/Kcf3iwAzpIhNg64zXuTrKQ2qw7W/3cHEgWK3r1bTmreuAVJZVki0jvOXZuqTuA8roabc+Y8iBhtY9iOHV2E1A1dpHIjKxJvgZnFRVcZKoKdbjmZqJsn4mGR7z+DxPH0y90IUJssm5x+tqx3cF3dmY5w4ANdP6u63GbnuxOllHz55/oHsM2TdWpLh6Xa/rQy+eGj75quXV8Nax58xhn2MlWx75+OrRg2cSz05OezmpCcrok/FMwF1iXI49L3lglZPrl/AMbXNGR3EJGU2qAYcv4HNMYYUr9jOyBtOn2SgdH1P66W1yBJhlIL0IkidwMRDCBd7pxmLEmVgm5HZXnNpwgzH15Gcn7lkP5EYCuX2v/eW6tO3R1BHKPb9MY1GQo2Z0Oht8XAw4rDk/7BpS0dsHMWxCuse2L4phu7wGkwscFDtYqGENUBH3Och36tE1iOHE5MVC+Di2h+Dhtm9x4nYM7rG01nXrH7TzaoWb7JiMzcQyJm59BU18fK275xHvXnPNhpF3fVnzr9S8wOZCPnb+fdi5WMwFInPsvnM+c23QcPHO32ZPDH9Mrh9zj7rkCL0DHxezf/zxnX9Yjby/5oKbnPB6L0sA7+bvR+Nj1ucLTmHhHPrHP/7x5dt8FL1/MC4X87wIEG5GWW7NvMBAHzh+tUIIUXkNcg7GVZ0zpVY/8p58fOSdFzGKm3MLgRLSxwbRC18Uy322F89jR10LYoYA19jg5J34uufCXN5qJwsvjnhxnr/2TgHdMs0cLq3ZzPCcxRq/OaYDJskcPAOejeUYdF0LrFjWb8DGxHjua3JgwNl8YPdJvXOK25Hp6mv9zXtiETF5TwjxNErP5hj19CD2dgHA8GEjLHs2g2Z1xwBunaKDpe5+beRWoC9x1EDN3eFtrMcZDV3afzWNoX1FWzm6Btyc0qArgx6WJj7OKa3X7uPeYFSLnvN4qTxjDgeCwRwtq3qI3TUnfIA9Vkwn1se4rOTMxnOexcOLk5+jDPvBxAAmGYMFMlKstb0DWvDtETFRBG/DqwuiGcZM3yAVN2t7wn1zkxnTHIoBvTHDd5np+yqa/IGrPZtlaZjWYcBXL708Pd9jK+orO3A4o8X+n3ns21CmxIrJPnyHG3tG46vx+jmH1t89armBge8tRrve6aWwwQW/vcRrfdmbV66LK2fZJj0ZQbvfY9xYTGDjmxygGo3vc76+1dDIWL0PzOrpEzUuVqZAtlcjpztjetzLsnmzOjH127voWh72K9hjaMZjAphFj1l7uBnSR3tHVTvaJRAcf/fMJz7GHlPjBOljhm+1se99p8cKr1zDQ959rPnMDjJjcaNADHU8KQrEE+a6EtY5PirhdWknGHS67qYNVFYouv9oJiKEktUc9lJj4Y1C2OLcu/xqA0dJpg79K9i8cbgGlyRqmjk5J+Xhbdbqkns8b108EN3ItIQch+HOigvXaNheHd7o4OvEQ5ubGqRxpn/zcQAK6/70uFFHBZyNbv7r2BkJcgtosmSZ9WgCdeJ3HsPKohb85GFon9lq2r7XdxHAjjp5ljiYBybmWVdRsE2pVjAHslqsozlOHn1BssefceI0V4Pal38RU+vGUBexboeE3fZicex3qHPyHk0JajhMXeAj/ZHAZOI+KkodRuHzVtyeY91vb/6Te1qlvD1OLDa+OqpCbeNDbzE9b4nhPL/ncGL8biz+RFiPcUm8nrdmaym4W0HZnNpjxrZ2pnJpODD1lYGOat/62POO5LkQ8iKoF0YA+eIdOt6V8wt8LkC4GNDuhUFY6X18bw/RFROl6mP/OQDUUvazNFe7UsB2CFzn2Zps/eVp/e0D3OaPyzh6421VLCvr6Rn8wbTWtUIwCuVszuWuDrDLV67NcnqwBt3Dsbav9kLYTI1O1Tg5ntqaP3aw4luvcHDLHfced0xr3722Kao2OLlwLgHUTOkEA01sWDlnvWNi9mIVELnh8t303D/4WLvvpsfpO+NeTN+LYGy9wM675pkbz7mYc04876zHzseyedcZfy/2c3U+fehFey40wfku+g9ffhgsUolBu/rzTMKL/uTg10LoJ19b3b9ykf6vfz7vakNwBrXtO9k1st6asaB7ZNk05uVHB5K5D+mK3vyF93zk/L//9//z5e//87/9a+/9yH/vd5s28AyJOuNiam7JGD5eRMiezzijz6NFLuG9yLEHY6jZLRYvzgE30e6yHsPgxZ75do370YRS20Zv6H+kxMDxqGPduzLMBYi1ZsZjbSJ7/kMR5ObL/nxh2wYLA1d9xo6uMgdwRs+RjX391kRcqaxRXE3mBrMxVRpntNxxOlOTvoPUdlYJI516x1OLRi2HTZ6nqJ3SB1kSmX5oZpMbvN5Y4tt+bV4zdHMraIwX7ROHb3OIHu6m2WTxPFqMIN8cMaeIynd1CWfpebs9YE8u7Wg24Wyox6+uN4bV4rYOcHw3b/36wnHR4QcwwcR8ZDR/jvf+/M99nlEewohl+3meg3q5wKsn+09+DEFLmLnLy4Vjj+nmUG+hbpdb3uFp7V10Tt5NQ40dcpOfMbHNc3WOOf7GEaONuhO6+JIsDYhqX7tIAxLvMYASXJWpf0S8NZoLXGBb1/qJ3JvnjZpiIc/40O08tj0GrMd6fGJk09S+SwMSdZupyKJgfPmFKqoKimIL7rWtXnzYWR/b1HHwmayKoonKmNqol1h8bOXC76htVyQTc7ytbePUgg/DDLmzbo5xkK/f2u0PNUwMPNwYZhiNtYGa8wlvjBvXPSi4wGxtsw4476BrlhpRmygGD1yFgho6M1TcYmGI8sZyx56CNPgq1vLCMkLcVxq5VO7eVTdJuXhzkFAZ1aJP/tgnrTiW0ySIrBB9ox2a4sPjYvU1rjlubuCHfx64VgelDsXRqsgYqyUqv849CaojW0l6cFbjVjipEbYyiifrhsI39YqyztWP9igJBM7DwmR7N3b83O6gw8TsiVMPodoGfTipE8jmf+o2kjodcx6s5t2TJ1/bA6B7/jXubqts6iFfhtjRsHHorHdiI2HPDT1Zt0a0B5nvjV21E/mxU2csxIB373qUkSdfZZ9QuPMDcNpzdOCVjyeo1E+coZAQtPviFJyY9okJEHi/1jI0JDgD/uIx+Ypk4vaj8Auj9tV/eT/zLzt8DHnPpLXosKr65UoPAFMak5Y4dcdCuXcc1jFRJ9MS8H+huYjhnUQ/5sq7+PH6O7ug9vdSJ89+xHYv7LeHqwFmCWx5mBTTblB9hwLiykVgDFrBeyFTjMcxpPfcaN+Jb0xwxEx8GS/XNAW4mCn6dJLuFgOi55y1dNkY7JXTNfMW+qe6hEIr4+yXwNjW8J4PoHrOQt16m6x25DCWhvQyT1/fd01NYV3B7zmycOzzrisPW6sRN6Maxpokpqmr6TJvz9ZIzAwnzV5Mf/+ci/S8dy63yEB8bJhi9sUe6u6Fdy9s+3FtLixj94Wj6Jk9wvxodwjpBXz+i7b8oTl+591PZMdBX77LDe4fciEPDoXcjJenVfpiAp4sv/PnU+LRmo+ec47y+/H/yEfd/5KPofOigCO8COg7Eve+VydZdjTHrkyDaR6r9meIfYEzA828S8/vpn+XfL/mj7n9ml8H4I/pKexQDt6jhWCD5SgfJZls9rrsG1iPuRfv0KYGas9587v/9o3fx88JM30rKfx+u4S75w3LammXWdLD9qFlxU8OI2snBgYHDqbcChpv/ev+yEmOiVfH/DxeTd6f5ucFOa6esMxjjbyjC+4PAXCbvhrgwMDKmrY3wHiRJ1/6zqwVGoYHp+PpQ4gsd7nidz1SxpvQ8tccImqf+7gRcXgMjQY9OYaHtB9cajFIRcAYkWFsV9kC6c6ca5dL7mSa/hFcnmodKc0Lz/oLWqrs4YC+CnucFKJNDQWUw+YHj7BRi2k5jIfP+3LT7DuH7cvkobKjKf10LmnzZs3XGSSImOVw/9WDqdKyaQ2NFDc2MlN+mfB3jRH643vwNVaH/DHAuTnOeT68sMMDoezuhx9HbtcPOmvycT7xWh7exKBnsT7v4j6jaXgnj/XJyOwOeg6vY/b7PMler89c1Vyu0VqViKshRCOplGUeMJgxZD9d1aeG2OReLorLvMe8oefIWDhcxVDHVtZzrlwgWt32ZQzi40t4lUwP4NPWvmzuYsq5fEQ2pwFZzH76rD+209+1D85aYyOq9dPf9sj7xdJBlLE9Ij8u3fDjNK4BbGvT0c1juDzkfvUlzsfnMIiPmq9qItbzLPtC7vrJ9jkN8NBUdfxEJ3sc+SNxI4JiOPiMnaMFmwwjODaKZNwDhKX+YokToD0bY0BMakxjq2VzUBqaOro3DzJ48g0cDBp5AFNb0WWaHEMxrbKO6i3/nqhGTt344TPFbO3PamqCo4/eFBuWlayh1tXogVyd5AoWhNzGYUve+NQQX/uuupLHL0WgzUogs+nX8m/IeO3l+MjZUS5j47v2T271Db85AcrV3JeNOEa2Q3Zi5T8q45bE/dZq7cceGnMUSZc86Jsyvq0cnz2evk1q8b3zjB6eTMIpIPusl33SVjslCJuesmZwnElq5tsvTCA9VuMWxnxGMYm0Jqn0VMpwyR8kxuyscIhOHdOT5RW6T96IHwez9v7mvDFF6U8Mw/4tIPuNrwlNxX2em6PxxN2cKpkaNmZKIZkR2ikU1aXX3ro338DHDy9xe+GNAo9LLnz8eBYXQMPvR1ixZ719JxGPF3DsRZPptZGeYzG5q6zxzDWfKgBnZI1pHoPEbH36E5R1OXc/cfpVxKa6IaCkbNqHzLVhLBfpMtPPvvXVzZJ4YjcnJjlwqU2AtvYKRsPcE28dTBwwrVFVWvec+Spaouqb6JAVmz13oH7Lia7Gb02Nqc7kbcm9/kM7Bosujq251jfm5dx9MQV/2I5jmTQI9EWfnD+ca3u+7F91XxTvgKPAcynYs4/OvRjf/V5Q001/ZgXjJzsS92Pm5PG85kI2LzTBywXu9tl30XOhuxpo5Opi34/Xyx5Pj3/vJ1nNRdAf+Yj8Lz//9OW//vZfedd+P+IephQER0ePl++YY7C3HrZpdlGeSpmS8Qyam+Vq9jiGlxfEvv1r/t0bf6gutf07/xqtfW0kevlaNhiXl/3QlledWHgWXk/PlyxhyV/F74sc95MIZRsWH8SruTmxT33yBb29wDVhYlL0qRaMTQjLSx0gx3c1NcfWs/E9PiXP/M13Eo4uyEkFL9PJK79GlE2X9HVN3tNDRdNHAurXJHdQhyeTfOO72PLcdZxHb63780k6HguJz6J3d+KrX8doaP7WU5ZsVx7A5IB3pTHb2nWXTJ3Lj3+fHDdjj8ORC605yqVGugQg9mYLxgTYNjuG6ju5Hox41hnlbF1wOt7CMhe/vq7cbix5rUVRq2HVNdB+JOpDD/gYjDg1YYoRu7knYmi7yoJ1Blhdq7PmdUOTUS2dz+rEN0Cel0N/z8HlKLLbfYyCbXkVzSI8nA+DzO6TgV5pId+cf8YQEAc+a3LS3uICM7KDWRT41YkN2GpaTPYbmP2yrNcYIz9nZTuO0TTnaMw9d0vtUZhjKIvP80bl0ROs8zD3G0Pgq59ps9YKEyOr6Rnx7/jEVctuYZpOOyPX7dueE6BgKW+zZ4nAse3U+x3W0XCw1n2Pk/dZ6QYh1fBPfWR4j5P9wxh/+fcYYqySPc6uTy3Fr7Y+XlyNYK359K29LmOr9PF/fuaqmM3RrCWysk8JRm/9a8O1tiDyb9ZGFCytGx2ZtqjVAjW32jtbC3g8TVySNuzithQw54k0YQMhCgxbm7Bz/LnJNz/8xK0NJ5jR3tiYsGFOAeRcPeo/6wkLZjMbJN/UX5bRlAXpfCVFcg3LubmTTLsPGB/cQaIn3jOyODbi8r1xFgGVI+w+LyEbHFuTkkxp/yEgZnlvI4Zn2LYH4AqX866K29oEYRo+NH8OkBnZbB829j4AbwQdaPzO2O/AY5pCAi13eYd9At0dLWX5ONY0Irm2DdtTtcX3WcfmqZJmii38Pbexl2+liXRRS48BkuG6qObnzL3H/3hX/+5PFibJB3D2aDrMluumEMUAnXPDmATPGuntTfbzIGLI5g2U6f1BVzwYONsDxHSsFlZVwaxVr4ZPH95iygV88NofFjX1CKh/IpfX+Nwf8iZha+fdztTEz2h7T33DzV58avBj8cFSY995bF31t06lzIYW/udoFcaoczWYHBI1NHTr28o/ezXinxRE3XMExx4z59nIi7BQdgc+a74pGwe+ebwkbjp5fFejbNpfPDHDlF37J/KttyBSdQjIJpjVcF3pyf7E09ioZt/wrDDQP39JGdXEXT+8H7XQgBn0yXiox6wJPnXj593x1sMcmEr0N8h1pnt8yc8F9R/pJxfd3/H7zaODi2dwvUCPH04eqF8bWbRnl/hi5iI99r/+V15jysUr90n+UNzRGk3wM3hB4C8//mge/s0Y+bj49aPyueBm7QsBwcLvR+QTTy32MhL4fXcu0r/Pv16znsFmxyy39qX5Wee2vdKbjSO8beU0T9hs+KDDHCPyg8uX/aEH6R2/T0+t1VhGstEjez/x6EAnRmvCCWf+EGSHBoz5nnfMM1e/MXqEQgOsZc7xJ0xjzeRnEI/mfpN/1noFdBb8RMjDfHNPuLjN0SC28LFNitEEpmz1gdqxWlaXORNIqCz2qGt84qN5R7lxcF7EHhCY8oFq33e7+mq/PPLJ2ywntwzZCI3+6WPv7mDLwXZrzMTx8ZCAZeBi0WvvYyfvV3VKsCH6ZwHJWTPf+EZ4jJiCYYR3+8Fy+3zm/aFSnMIESWtcZiObEPNtz4WPbvXrb95S0fV77Bt/+Qi1KdHa+8DFfsaDKlfrMrDc+wDqyjJMs/3somne41GV483iY70Vx+jzBZ0s2u/KZt7zEhbPi1lXXbmRxxqKxdQzW46Tx4h1+FwOdxYnFi/OjO1FV7XY5xjab2GzuSjIiG2xa28GVr2PsC8PBMwZxnWa7a0brsYGkzrO+TXarY2UaAc4P7eLlVi+bE4uYPLmgHHMWG/Nq6N5VlcRqpq89np42DFu/5YzxtFci7DZ9FxsP+fcE94aAX1qUnVjZ7p+ciT56c2r4+Z9eucBuHynr9qvdntxsNMZUzV24Ah1eP5zHGJgN2aP2x5E3ihmIHkYa9jtBG0NNWOE8PYG++rbYyXkZM2/Wdvit8n4DApXbaVf3B5UxSskGwtqftERce7oVIGLmhmZ7LRrtx8b8xIH1pqYB1Iqi2RKUWL1bUOHfe711NLijbC22zi95q53Y5tqU9b6+iqk/nmAiJZat5R4+72GZ99sj2Gm0eO9rbnUbR8Gn5qa88mkn5bgqRchW+Otvd7NCcOwju6s1gDI5XsyzbG46M0m5WT2eHHw9w5j/ucHXAHwc44kyn3zbb84KuKe2pVGj6desYb3GEL1eQGgrPKEj/PEMRzn4yrD8XV3yGep69/w8KjP/YAURynJkydA/MAa02BhJ64DKhDFXPu49RYfRPSKz6ZxjV0+93G0L0X0mIeG5WQl27GTm/PFXjZm2WuKJiZqHtVyjRbi4+uKHIzgGlIfB6RWZVx9owi/yYQV88GIxigojdRLWG1ZxYdbqdnwgeRcyvTdSGIXYCA19eIIMi7OPU5oTuzhLGN7hY9qthYToan9gV+I/N3QGSjgW9z7btB2DrTa2c85U75lLE/rGxt50UOkc1jGt2GYMm49RRiDXW9WEM8cq/hrPPHgrV8fuYf7rNsLHWNbjeytMjtrtH+rZHUpwg2ek296vd4yVfTihr0pwOecVmvm+LgQZ1S/U1b9jo+avZg0tjHFF+YLFnxqK0uw3LwwzgWxnPF44bkXx0gY3H78neDaOPcynwt08uDbd7P/+ve/yck7wPwBOi9eE0AFvC7L73HnH7l9+TGPLb//zkV7/iJ7Ltp/zMU2HFzIsiaXHW7p3hfQyo0L41/yr9d+8EI/9USLIrK1KRGERmxbH4YzVw0AcCSYXA05fWXilxqSl/0cC14goyKvGfgjeHGWHwgX5GjqnNz+ZXs0+MkCXd2Ehuzk6g2zCQmO00IwdsSGd++LYOiVDxnZrQ9WIosmdDjPHu8ghoN0DvhYZAeio9iXdefmB7/xd5JQUHWopbSxYyNBbomd1VmT82pnhStMwarJ0GctonmcPpvlWb2s4fi0a3iikDW91UrMjbqx/xm3OglTq/GzOTVcrmK6bkzm9JPemDXZWLOa5yDtV2OcH96AMPCz25gscpLuMTKCuiBziy/TwGprxrMgfJBOgBJv0Phm7l0pfgd6+HmQvcdfLc2wtbiPCQRMIuHmdUGfIxKvS8rtuXpwyElvyoEfOIZqdiXBHpPlaE5pu5k8y4F2yF7c9nCjrm+yDYfSpvbFSsYiUNFH/0WcKuhBk1vLzUsn6UkSgcl+e0lq4qu//qq6/G/sKH6iGl91eDPM02nX2erKZs6pcy5g3zC1g2lFqxWOj75GprqVC7gd3Zp0PnWKhYSJ3Nllz2Iiy1f36c/6BnywrQ+CwxymcrG3tuFizdg9Pwxoj7bROAvzmiv+/njJpEKt8dSXgM2xWs666aQ8sdG5KmZS/7s1T4VZGRqsb3qEf4+rPoJr29xH6sQ1Z7WChn2xrA8f0xrsU89GDblAN+lSxZgsuzJouilx5k3weULsiW+kwRTVYV0zXxzLzpmYchCZ5wv2kweiJQn3+gg4fKMRG+nFwMOzAL5HkzsRmjObXGub+uDZsXysb2fKVFu5NufG7R6N1GKu1ZlwGWZDbNmvnlMbtZ8R//AR4ZCLuK09+8SsnuUe9EcMi8OTCXELMG54aotlkzydOL5WNISS9fgEUD1ORJnzptqDsQxHh7hjneSrMWL0j7mt3QjI26uQZdb+kMjVcgTVONCG3P5uOjD4stmw8g0A33GERVyL296zkkMdmU3o17qK2W21crz7hGH6T76Me2431+cxFyGulZVrDO6QfGvv+TJdqNYAhrlrwWghnE2rk2zWpw96ixKZ2D23rG7WrasMbBf70pk2DnwM+xES682Tqfx7Zwth/cc84eeiiXXeU0zcBCfG+9ThoJ97w5jbDHK2P9XduDDFiI/KmTOQOmQBAAAgAElEQVTYNnSwWnGUuzFEYAM956KFYURXNnGZZ/Y3Ls6KmTyf5/LhGwwZzni51jjFVTPGST6BtZOT780FDJvGLAq2t6xi37i1xXzit1fYGPZvOBpXxg978hHXPlx/Z+UZyVlMVg3VyfNEYv04Neo20eSnnvNRa9zkK63brlMXdWew57wCxLvatILhBfr6hmcvwok5Ny9M75rw+vIqeT7+jT6ehPlOesj5N2IMPpqeK/Dk+z0X4Fy8cmvyH/K/w7lA/9530Pkr8qlhngC1dzLYB9fx8fvxXFzzO+Hf5o/OceEfA9/VEGp0nWGqrqkZF1wd3bMGYQ4cx32Py8bsHtDSkE979rxg8sfU3hzwfpDO79nHxgUJriYf3VnkWy3h4+vmQk/92sNLPUPAhOzu3f2HrwjNmZZ7oh+N6y/6nkPUYW/FFsWUGbfOOQ+ZCcoe32KHa1wbc6AS1Lo9bZ0TsDuPV/PoJyTnhk+XhlSqmCek+yy0ey7jTMwA4EE34dwcNHcJtOKfBAG0zuA9Thquf2KXq+d1Y8vReLJ6EBUyyUbUphbvIjMkrWhSpm4lkVn6qiKm9VQB4c2evVzxEjo64854bDWgrvTsF1sR6jicD9L7ccjPMQyoOcmQ+dP/ZX+1mxptTprBOEEaPzarAaO9IkuwPsdYHjWDkImJGJrAF0MPZJunDZo64yhMbJsZG2Zq1UDo9h0YZGVndvoR+8Z4/EXVr57kWSw5r5wRcPJd5ed4B+zzEnSgfwc8zj/1bf4HRkFiq37rK8KMvOjLY/XwLy+1MsDUxiIrzMewfFeHvUD3FHp4h7+xIdh1DPwMgNZcxGVx8gZHul3f9DODx5iut3eSJK6jDOtjL2nNcr9rnaGTcfitK6DWE01f6Wz2N9tHm9RoLPVMb1rVZ8wIPju1omEEtg/VoS+e9TKZkk48eAb2HVg2pl4MM5sd+PLT/x7f/HR+x1BQEA8CWe7BFpW1Sdn4BJQ9oMvRRmC4J1CjIhtev4jjOxtO1jSPOVTbyBXYfRkm4iZLgJmWy6xFqRNvv0+MfMQV0PpmvrXssTxms4y2zWknyM6Ygzd1WMPg6lVGNuBhbdzWCgb7dKGzYM2PGGvIGn7tl6MduPFS7WbSNVuN5SyeBMu3xxkVay+K5FW2PyS0j5amyHZ0Vtlor9M6nAZzL8omBrJMqaOxUO2MKEbXp/7JvetiioIJNHqszZzlp//lPpTNu+nY57Y9EI8hceov8ybCnFHOzTVGHOWWLfHBnrqmrNXSYwAe6hdL6oKRBsmEsjo/tCvo8VD7PFHXlzhzCWGT9d6/4dESm3vWnTVmaicMs645H5Jn6xUVzHnyAHRiTg2Lx85AJ9omH+ZdG2N8vJMGPdj7V6U750n6xsDjH8aihzzhDPa7vK2gfy7at+fse1OJCvqOYuM2l97wAKiOFY8p+fjCfa+bFhhhIDpWI3htl2YQg9PfKGJ2YGH17je/wvAHv/7myepSNHo45aIg4nyRA9nT09Got0XLDdalQZnPk4xW2URlXB4C/M7F1OQSdo95vY1FM8O6tvaGTV31n0aU/pRIPMedC++90JXPt5ZClHBq5MQkR/VP3zBzi85cwnpMiSXxYnnBh/FdePyYfJ2J49MY8w755CLP/i43nP3Ye7kI851iuaX0D8F987c5n2L65ef83/PnQtUXBVIX/17MX9NIvu8z/4F30Oed894vyseWevi1jzuYJ0d4+O9j+H7/7ncv1PtCAzH32Hk+QZJjYeT46Ie9nmMUhP1yOTazEufE1pdn/eiCD3EHB/7exmUdyPAUyn4P5+owP2AHyjJGN712uCeCcSPAntUs5H1+2NUca4Dqk4PNrU9TAPx8M38MnmtTDzm4TcHuNkUg45z9EKjWoOZlusfEPfDk3ItM52FWf/r7rpt4fKOw1K1BreHjWJi3Cqt58eTaemiG3stpPuL1Xc3iAqdeumPeN0/mdwzvayKTnNvb4Zig9qLnJNGEDsvMAA7hPPFbjS0BX7lPXCY9Po07x4L6h8s+Wwf8BBAzeTA9oz2d+s/PBbIxbszWoum445/en5z0Y/rMMdthXa9GORIFxu8eLxa4tpaN15gNOhjlCy7rM1dcfH5JWyxx+CZXlua9mpavWmDYehtX/6lxYWFHzdYgL7Vj3CG2Gq1r9IO1FrQsdmOzf4+x7sRJu/Eb437rywIOCbMRWx/aEaZeYPlyZc72vJCKFy+PYfLusrySHB646Of2Ld4Mih/dNay1q/EdXvDUTmQeJ5YTs3URlZgiXNQVi1jd64+ldADLiT9f8s9ei7jLAb51DB5NaCCP+UVIipa1lRepmYmfHXOcs1u8NY1IIdO/A4dnxzU232iinh3bl9YYuzraD23DL/6dD8E9fjUsc/noDyN8ic1L86cmHbqp+zlANqIxhgKUzAs34qGkyCFjqY39NBY3Yv3BjHXKtDcG+OSICAb5373zbO5BIVc5rtao0lwtMDTtasiKuubJIvN5vIa+VcR3Diza86XEBWS/6200mBrbVIk0oAcVdXdWvq3jgz8xZJxQo64Wac6mXEBR05imqobNa/ypqcrNOUUYPxSSv3MMc4IV3n5oxjW50fLxxERAIujvlCNtFh8xwW198ieXAcT/yRA7enTL/dUxUtPwypd5D4jnzs63zXscVpeaQ961qs+qkpLUglXcbOgY7RsBtggmn1b7H3NrT6aNHb19dfOeS+CPbojP2OOBoPJtUlMOn/nVDCoxHgfm1dhoFtOFc5ymVEmDeu4s1hbciW04lAbhKQbOqR+KuGvfCbZ7XhQ5sdGTFA7rIUQbvcHc3lHP3s7x9FoKUBlVkan+KnDuWlg21A0/1BmYGUdz5suP8/SRxxNiv8JaF3zzmAfg/ACaLMQwzJkNOuV94tq/4iLAXKe/Y94YiKxAXJz/l5wnDxkRMfk2rCypaTRVIcDWCS85FY7ZrFk7um8vpy9gM4Rmj/6ud/9BlbzNtbo2sKmo8PJC/Xv+UjkfD+ffn3GBzvFgdNdXIN53tsn2ze+pPceuF7b8DjMX5xk25OoiN+88w++76PnLLfnsdczZB9sLcPp4b7XnYrqCLRz8+dlj/cU3X95Jz8X2f33zt/L8n2+9SPd8AzvvoPP/vb//gX+91v+T7sfbTWKi5KEv8Lb2777jfLITFDY3Ls77B9V4EeA7bnkXnwv9vQpuXjiePmQOAzb/QjqrfL8vAhQ9ceKw9JwuF7ExMaKBaX8XvWfE5U8u+plX8Ok5JbZ32I1ObGtVyxibLZyBnBqYI5QIHa2jLGwxZpCjs1n2PGOhuoE9kGEll6BszsQ+le/ahkkKpRBWUCIziZE9+f4sp9AUMSHFJ7m95dgjBI4BuMumjzumPbHNf7NtrIA4yd/4bDmWrJlCM5v6u0YD6x7n1oHBdfA9ngIMr0YZYsSe2+CrxQ7EdI/DmSukfmMThw+dd9w4bPpJImRwp1HxnthPniJTWw5UOaDASj/Awp5N/EwvD/YO8XESzzxRZ7wcOz+yRMINM2NiMe18wO0zftgHn7iNrLq4dE9vcGZ9IsgzfNgaPKrjw7bY9zibJQ56dOYiIcmwT+Hud01u76b5Kqg5mJNvM2aWE1n+uGoXcBAG1FTpzCVuKTLx4hUPKPZ0nBNDvLwbQ82jXTXkzXo1iNdP3B07B2e8rokb2MnTMitUTQVgBtOogoxBw3DIP4g9d3CtHSDPP7YHJ27riqGcIyL2mckKl/7hZM14e2I/0D1cbdflIfmeK/QcDTeHbNowYqfe6pQw5xQY6esPn9cb5GQ06NQ4Vu08tm6+vV+iZW2GZu0e4dzkBDPzQbvewGCO/yQkvDEL25xQvvjt32ONBohKBhad56+4V/QK2gZln4SnuSaBYv0V1Nix2TRazLoy1cwGX3bLucUE2r5kb9xTZAMoL7Nq7yJb8w5248ycPJgtEh3yowV+NiXSwnSweo2NYbUKFTC28Q3PabrM9Q2l+eUkJfiM7UlXpna6MV2gP1wZW/PpWQH1S5oNWHaNsC+ua2if4ttjMmbRBO3xVVt4iqub7cFngp58z4YJ/ud4A6Z32+PRBkldre29g8knD2yMsRibeQKH7modXrT6LT9x1SLLamhmeY9W4gXtrjnxX9fYKrzAZ+sxKmQEbh9aQV3Z5nuxe55uz1e/tNFbVajYgW14I2zjKumeJ02SGPsyoqb+7Z06lpZ9SPCZrYRAZmQ2T0h6PgjQ31lr8gFoGub9ccN3DzhDDdn0B2Ni/QFZ3zLvOX6scRiOKHO0fnGYHrWDFL//uutcGFsjAX0HFE44PCaZEwT9dr1/QIsgkPSh+rusvbXWf+t+1z1qFH6eDCQUTvGzJ729MT+perzJaT4ACnDS2E7dktEcsycFQzuTMRzeOKp3HACZPjpVzhqN+dq+OEcU+OwIdbMFxH404wQjNpPlYz9hhG/o2oDXyKTxq4N1/VxM8wfVoogLzfx+Mu9oY+OY+w5xbFx89jjnAo93meeJWd8t5lwo3vM856OlNUG1bzGx0Qkv0sP5bS56BSAoHo5v83QPEeuO8XG+O7Lne/1iWzIvFPBv0P7+3/3f5//Mv0b798+/9PewE0QN/mG4ebe+H1cvv7LD7wsbmypr7E3Vc5/cfcLW85De/ZZ/f/ZtXuDgd9O54O/fakgceYYjK7pljyUdz++8FW+O8vXcIghs60rCia0dPFFgiyuH87HTrv6HxH5i4AihXxDMQNPHgBLDgJjT6+pKbA/7hDS225o+La+n/tJOL+BepkDpszVl/+JGkUjPk+mNeDnKt2Tbw80u14KpbuqBkEj35GZNT8HiyZyZmgBlLNe1PR1MqGzGQQhX442ToHaisBWyjxGXy6MkAIrp1/JGn48LTTYVFCcheSA20oXHcMSZF7+arBV8cY3q8vRm3UDgtITEO6ltRTQ+2/i2f4MIZHLKAQmeDKZ8EvScW1PxikEolAB3nNwDgkMMUGzBd+eqsQDKsccPyD3muOs/jwPTcziHTm6yiCSvlmpm6uMDd0DJMQzi9ITIjWI2XMHVGh2wD6x9ZMHYvFmj7XCWsagm7lnz8B/2UpevPPRlMyzs9OxoGXUAM6Us2tVs1d4uRBdXdh9jPOKre93veVI2PE2y9U2SbUmPEwLOFeTMg9h+rv7qq70+uHPjO/G366to9pXgzyfyG3v6HWdsQDpJtjl+934BIPwcJ7+WtzbiS7D9wJCbzxudNUCaxPCzGc1LU7RbbRxDwtcf457n+Ne+NmA93+t5t7WDSE76PKM91TrHoDnOc7TBEcKLQZYT22rmpJFuDKvr+l8wZEV0Sx9neNzwXj4x5J37HuvvzwlE3CKcZ0FdCmXO4o6ush0zuz2wSVkgfEhIrA8iTaDvNHCrZc8BWjz7fLG9R9UsiR8sS7hr0YwJQ5GuzI+ZsQdoFuWfk1B/5gZn0ScyIs/cWmrqFvg88Vsfeqw7RNtfbKOme3UXWa34P/Ht+fQhIHsDBq6n7nLXDos4H92n96Zp5efYTP5df/TlaDVRNsn99KXzVsMxS0o1CRwzO3WsTjBgM6pdr6geZx2Tp9HU74xYAmeLdeuXJbXinyjzCnfT4FBp31zGq6c5Fq//edA7tQa7OcG+8TA3N9vqYH97dvXqpyeHL8rzfc61sYOTNLvWznqPcV3tJ4WhbXBKQM+bY/BwBut90YDMs2ZQD6NHpfOPzgibWHCjU/PGHhssoyE+2I5WqbPZR2rXsLRHgJVUWUfX2vG1V5lsPi4kyMNxy76h2fNAxxic07noWDt50cYXY2smDyuGcyQPN/mBgwXGDeTiDM0az2LKFHw0mgsKAgzMhu8NxJxcjuyqpXjs46nfLDOVr/Uc507kZ4OqJlq9WNSJGz+PHUKoLxP1sNsJe75bf2OIIxmbapyfbx6bjWX/VtDz4opcv3iRScRwtx9f77vk+84r7+DyLip7/qe4F+wcI0eYcsy/zZoL3Pzdc8m+yV8Cr9xs88TakrP/NhNe4OFiuQOezLe34aJJfa0HlcRnG//W4hwbPqIzlwWMhmKhhNvzavC8iZ2rcPF7Dnzzb/48XN5w5p1u/s5C5n5kPhNysa6R9bRKDI4Oem4673eJCRfvonNhQZ5fWcPPO/P8bnpuvKBx+pCC1QM/B3yG+eGJzXfS9V8Mdo4T40SJ5YqmYDHDiYlftedFkEyFODnBD4+sn5uhTAjRPX/hd62JTnSw3NF5Y5J1zNOzrDam++Fda4weY2oYCtts/pvBzKdOjtuyZe/3zUfhnJM7qIGhspmzxkptcG3Np97xg2Nc/51rT67yPwkbEGAyJl/zxJh5ecidOee2tga8VRmEORE7bh0Xqe8kGKR5mcdx9L1M+MKRc3ShZNlM9gRdGlzVGTr1xt6eEbQ1DA4W9DAkf+qPyRWyyG+OzAaHzeCsqfByQzaxnU7+5moGAE1clttrIjffhH/s7jGoeTW6gjOEq82e5bjt6HPzW2NriVcR6HmwWYHs/T4zecskkl7mmIhJ3GK3rlYXPMcNDVPvid36zZ3M9hX+0TH5tl74Gb2vdP4fXCK6WR9hUJc3O47X9GlTNcc9xv0B3donbUndHsE9J4YZTvvuDxgTnm6qJURTcu3UFwe+3XY2xvjVZe8EfW7GD8HpzR6HQe55QM2W7L467cnEonZ7sGzYPgXj0Tj6FaDFeOD52scycq8uQbOBo/k4FBO5jRGzqpsNU8+NrEe/tsEiyrzx9fzWMUlm/mCsk7zmzH6OF/Yd8mWhPLGTo8qbD/CE7LlLNTcx3BqyywRsci2mLwpoNMbfQW9Dsl5i4keozTz2ucNJF6NKJ44MMbWILj6LGziYKbp5J5CcGTaKfb4qOgshIwJQ8h7cyIBreQtJED4W+YEfJ0smuUmYKfV0NZa6DeyptNgtVb6Nhy5DH0SSBZHv1aJOAPG5i46rdTXJMjyQZGQnXVeH8yN/CFlvLxbaSLYkxZ+dzyube3GrseurZc+H8ppBEvQ4IIQz+S9mcAGAG2Vnv3GLIlsxg70OiEti0G5iE/P2Dxg877h1rPX4obCIyazQzM+5MSmsABlPfcaVsfVlnom9hbfLj3392/OArWvWCWxM9roeknDhA99jRMYdnLO7Zh8kImZsP4yPeY9l6y5uoozbuTj7UH17XN1DZuiis8+3ObI15xyz5UHOf4SNxlOXnBfoUanQ1gSn7u7JaS6fFOo69cGJlwsXLta6J0Hs9Hq4wA1Ulx9qDsTo4PwI89tPnwCWm4wymn847Rnx5Mk+5O3dPUrmb4bqd46scEDKmIk77Ks3rmXqD/vRYFA3aFJYNw8vbBOd6aS4NgOrXSR1M6FH2aGbr76ooMEMHCJZ2YsnBv/WPss142LQGy7WpjZDypRIzqOM0TCqqyE2L8ITy78Y6wU5yWv3ojy+8/H2oYGO8U3OB168QRWxXnxGw3us+cGYy/gvv3NxGKQy0Mkti65hY7wX8MXsvy3rBS3nWG+imXfCdstn5lodTGkA+TLhnXR+J50XF37+10++k875on7EMAznHMrEeY1DIUTL+iwiz43zjnl7zfNkrtCzT1+4YOfd9O++/y15/52P0X9//oCdTxwq8PBuX86xwpMc6FQie78w144UcplUkEE5Fi2d/oHp+d/7gVoxZuJOw8XsJ2bKRHBn0PcJD7Ys+j3c1QRyqDOjl2yboEqYxxoy+lrOotg6tG8sFuZzPmdVdDm7fTFjCagxs57esLIXmZSn6/2ZVd/lGOkkQIaau6hBvssUSCxvLnz55ngZMfvLkdmf+osnYZ8QUz89Q3VCdMeWye2rrvqDE7/e5CWS9HicF4k1t+Gdx2Jd4+/xM3DMtTTisWfqwwK5yG/OZtoM2wdjqQVHN0qwLnjy9R6/c3yC3noXoyh5dHpBO+XI/KfHdPQRe/3VSs/PMZy+qVfSJMJfQxOShfxrw8/SZme+2s66hi7n+JJn4rYuWOzhQyGxuTC2R80bY7+FsGn/M7Ee3VMBcR33eMTC93CoIXHnxQfEZjQOUGf3OJfvYIT3HFjPiV3DNKY619s8qiX/1Lg9IZQ5o/cBZlmf3jENl3rBlReUAyjnuM9DsGQeIvM8+eSMF5wUoel5hzFzczBfNbEJbW6yqrl3iIm9fe8xSYDka29UjFuh/KwvfnMnBniQ7kZPqjHW+84cM3UE9e43AwyMxb97MfJeTvs6NuL2+KhBHqLQFEvK2wq7rh1/7Y1y5XGGcePbma5ffUJ0nk9lmOezDwCqYzQgJzm+X8GaUwg9OidMQO9HKCR4GgAYyYpnk7EldLVcdexJNdWiwKlY8p545iSPIfZqnDyYNq+JCQpQ29cxUzQch7u2LDPmAAzfOYnxxNbRYHyrdmfII69jtDpf0+gyudBxZGd949h+QwWNvBJ1s+ubojx7p1UbNaBx9RyeRO0zTuhMEtvk2gx7bI2Pb2vtMWhmNGsn9vnBuFhQeyyaoHrQdR/8q93SDZh1Eyln+wBXf9DNySz0ardUOOwzfSsXJmbbj54vo0Xf8JFz+kUMDN2W5/ZStuPd7pCvqYufpOLak+v3eE+u6tl807341AtnvrD2AbS1KCwb7SZtnDXPuoytExGYE9CYTnscBLbWrR8cAR4npmK6b/X1Fz+x5h3M1AZPvXd7fqCEonU9PvJsX+IdZpLFTObVHw/f+QGCGVy9mWdhTy2YCLzYu28jNGkTm/P3EMVlN0tU3snxHhNQw9h9MKuhglgtYvK54yhNLDE5sGqb4M57PMvQ2mG6jMtR64QmW8+WU+Om3+NRGYNq1OYjkm9HXPuOxj0/666ywswWbu//UxOse6yqrlj6Oy0NUVDkiAE8gz34xox19eCfi+7fnv+b3Xd9+Svn+Vg7NzB5UkL+agiBxFGaXNaKiBjh+fab/Bu+xPUFHN6szkV54rkwdA/ScyN79KMOnsxVyrHLDBvr9WPiIp2+8AW6MkTjbgjeEpQua74dOuhZMd/+Jf+vPPr43fB/BsDFMz3lY+V/5KV1JHGzRrIRr60aMyWbOpoAPH3KPjXTO5zuB8D815/4P+vffPmVTx4kNy8W9NcC0JUbV9NPPuZwvvtehMdiPhLWv//6DgPaeOG4/1ota/qOnRzM5kk1kfUMTRZdw5vb4A+OnNgCIi17NufJ68Qs3nj1QUf+wYOTIBu42OnE2KFbNUBbE7Jr7/7MM9n7GNEHL3rXjTGhKehtedfDmoHM+pgfgRjxjFZmg492Yhya4P1Y9rlCTB9212vJYvITCSP80ImQ92KPVvpWGRAEzLqG5YBvQctgu7Wv9okFSTxL/d2cWvHPjUh5Ht1jwDOoG49lrbvXC2FYPQfC1d4XsTwvXpsSnxhVSXN44EM3sQ51DtNo3uNcf2trVCzBGEuRXKDN41fJBqX2tbBXmIegPU5sJ4JOH6kzFmqByYWzzVmqccTTYU2rC9PUAW6n8j344wAQLe3f5gkavth7P66qKuu8/iEkOmKwMSyN6SZnqr28rODenMXRk3wnpv2nuurZXFggr58FI8ySbxdrrTFzhRW2jwfIUiNQdeC/xj424szQ/OSsCF2HQ+FQTP8Sk+/BNBZ1hsa6vjNrqRPRY7a9X80EV6Jda+jURl7G9pNVUe1J6WPNd0Omr3G8544aA2i/wxBeuLrtXt7Ve/I+PoVcjl43TUC4eWrSWph0bF4LjGn1toZFVSuYG/liF5doAdlsLbgonJ3sTu9qCH0HfcXsD7BzUANfn+EUTyBFaRDQPBIOa80XAzauGxXWWadt8rXEsS/5UzjMxO+Bd5XOYt8mjjhceaAyAK8DUzmMEGKzeEAz38u9MSOEI5ipB7Kuhri9GjixyEJtuPakuvp0+0Nwe3x7QshzEoXH7PIQx1pEaybFAJbrPfFapWrmBEzs9LNPNkOQUdzkUniM4W2tm5xEHKmiW+bEDMdql/GtH7/aC1xd1Z4VE3SJIc/lzcIBt7xu6zfF/iAivtDiw2mN0GMxxwAm39azDwZ6w2PtWch/8k7+ifU4gx1we0XsxW3/Vhl74l7srTn5cNCDYLB37N5MownYVz0ydXLHbr5MVSKOWVy5eYycXQ5xg1CCuMHDJzeATPrtXC747UnzWb+YbALefGKkuHiWxYOd+Onn1lflYQKSxfZr7e7Hvgxy0edM/EvbF1TIai6QbUa1dj7r5zi0xuqskCLtdcy0wN7MfHujiGzEFbItsqgJO/M99osfwYkMku+5YCHOsRrN2ygxAVRtt2DxtiuZ2dDaBlg+esPXJsgaBpcYjbvHUL3z+AkGrBnhQRshMEvApOvF7h6Q+KIF+ZH1fOSad8x5XOOCj3fKf82NtRfoXGDCqa4mgcePR3NxmV9iljd+LjyBURG/mw7m29hg4CJYiqx+5w/H5Y7AfQF639k9BUztJs1m6iIHt47s/Y7NC86pbTSqJxpAG1ew+UvRvwY/8PyF9e++/PCXH7/8LXjeSf91Pu7+26/942l/5ALX+8XJX15aeUyQseDG8cqaftBDXPtznxiGGoP796//ziI9n5y8UIAe9nwKgYt4cp/zCbIM12P/2se9gb609tAzN6rysl0Z5ZIwm5E/KTy3FD9FkvnyXI7asqZuOGTNJkTHd0hLItfYoC/3Bvc+McZ1ZgmKJbzJR/xJRjrq9mANMu6Qb38MNn42OQFX1stzuoUuOA188mnbxFXVGPiKl3chidePb44nAk/dOzHP1jcxVns1DEQrc1K0K0ymnsnL8YAaVFUyL97+TeT2CFSx2Ur6n3lJKOX6m8C6CcdH7ZptwmQcnP7RgGfXg7rrE4ve1dEqzE9Axvpe25lnoj+59xyotvYD3PbhHD9ZsVtgCxktWHjOs/0CurmwOcQyF+1+XS1ueOMxp9DaVqvHcf3w5EG+7KMbQvIs1dQHZjn3eSgQbHBvD2IaPmYZh48+l9vHVVJQbyBNded7fqwG6x89zfk1L4k6Xk64O5KZ1PMYwuz2IdcAACAASURBVKJ5VxMyAdw9J+mklGL9DRTodJxTZvhO0MR7zN6eNDc9ntnpnXqjwxpcEDfHJYnEI5NY9ZJs/XEQExOZJ/z4M9G3e2WOtuUzzvhSiZUomYcX2/bi6CHf6jZoNrHZj6P3SjAWsRl2KtNP23CIiYinX5TeMb1iUaqpu/XvuVDegt7eErLHa/s5NGqZI3jIT1qo7D+TO1a/vNSer37EHUys+wDdnm5R1Na0R+gemOFekbRoRR0xhjbeNOTJFw3rRUmjhqoHym5tTjywsd4TJ+tS6Fk/slaBBwGYNHsSloX86ITVxsItdqPHjsZgGPug0h6MFQIeoNyDqv32EccMGq7A2Joujg18cbjRVtueJGCvffPHFs7WELo2oDICmefzFFMcGZ/5KJtccK4egcYU8/RqYJt3zw07tWXMftnuyVueUd9802Pqtb7Rl4WWze9+eziKrXdQTfn/0/UuCpLkOHJtVT9nVtKu9P+/ebUz089r5xhAMqpHrEx3EjAYDKBnZHhGZNZkHE4aoT1c6oNE3rte/bjszSBPT2EYwYt1H6UKP00GImbzTQDJdxrtzLuHZJt8CSTXfg1tjiJEWUPjIDRdz/LjWR2XRwAJ8Xm8uUcSAmLE395jN8PY4OhbW53l0EgxwzuFe4JlkU5mvaejPATmnNqpuZzICccImZMyAfjqeZzEnhHQrsFvsD2hvh3OBZ9oMI2GfHJjCXb3AYbV5zWRELmHd6+T5qtR3kld7FzbutttE2Zdz6huAcPMaWsNi9KHZ/ZtgS6zOLoHW1YdQltH8lvUrYO0I7eTJFsptbcf7fN6EsS+BYClHENsgjHiyXr5n+gAOgqvBxw/WNm3q/fG/PfcmP/qjaKvqueJ0l4nnkPAK7y+yjtnbiJ3b/oK8VdvSLkp5VVhXkXPnaY1cNPKdb6vEpOzsdN39OezOUfn2igB0fkEszkzwXPW69sz+8mg03Sn8MZgL09Acfh2d7l5u/s/7A3h+0fw4PIHCbn/g6vxLe3bBb2gPvubH1QQ63URfutLwK6J9V0K3sjTk/63bl9//jk9RNvNZwx4fp3A/uFLzPkBAhoTQBjF9oMUzovOfBpDV5Y/au3SYuOBJn5mDVe7NRzzeECgHTVz3WTeSNLJ1FxrNGJ5iYdhOcY+2OUt6h67f40Eyiv62yOs2jY3hh32h3wZH3qaX1jiCJVjYKGPYfcQtR3FZAV++XJuBxY1tYVUCDz5Zw0LGcbbueZDCFr4Brace0bB7QOrxVRLcxB6VDb/yZUINa3wFdP6qnUx0pPRDyi232Une1xeg+VBp0xPjs0UqGNjX7v16QgPTSVX/m2tfi+PmXOVhoom9UN9hJeicV6HUtGjdYIRhaX2WYtB95NfLeCSB7SamLpmwtgFZ1nEdRMFxLp9AVEFRk6f8MJTpqu/muKRul7itO/Fp7O8coZl8721tIYJfmrcusubFYbtA3DTVptYgB85x0dM/tmj4V+c8okbbiZeS08NxUw8QHNwJjARwZ5rd4UM3+Ev9N/rW9/GupZgPXNuHSSWNwdDRs+HbhDcryTywz6CqveT3v6UkajWtWd6+E3vyF7JkBpiLozaxVdrAXNU94BmbywoB5ms5yMii+0/9bjcQ870hWNQODcv09gcpAOQIe6cr45rH6BoDsGE13dDsoy7WNjRvPtSKBDxiQHxCD6Ctv92UL68xV0w+JfwEGAnvo3ALHs2GfxZag5TtXmiISSEoZuYeWwV59R4GzdcEFzeKuu6HC2gSdrzYlosnPX1SOpqbBWkG09O1jTNKqw59sFtG4giNLYWmEZLnoRYG7SbZqZcEGQSPb73pk7X+MUFX1iP2+9yFG3eMlY7EcN9nhC933zsRQJCshvfhSTn5p0cp6Y2YvCouPthKuuCkJY853C0X0w6wB8GehU4ueglvdBfw8TSs/bZ837lbO8JIMrAYrEwwM9k/DeHYQkC0fk9E7Oadn/linGvtd2ZYrcfAUgYLz2hJvqRcXu988Ys7ikh0+qid6uN/Hcl4/Rsc8aWKXwEkZVPuXyiMzGczvhkBe+Ag1GCzrOQa0AH8g2mGRNK3ejIE3HqgMz4YdvTsc1jh302ZPeS2OkHew6p/hySgsvh2MZXias3jGJy1lFdWxts7cLlkcbrLBzR3rDM5wajCuDJTGdjmdaXyahaG3RnTh2JtXb7RBSA2olm0EP3Mz7TgM1QU6amPxgdcpSqWG4ytz8Gz8o+Q5DhvM4ck4s88cmw/Kwz336be278qnFS06N5xW2vAesM2+rok+G7NjVSErePh+RWnW2hD9xAzmduDHnV/NdffvVGkbd4e7NNANozvvueV3L7NnB156abt5rzqjgVM3jl8s/wfJeXm+FvHclFz1Lo1gU3N6GM9h496DPhFL7z2q09/o1bXWqBaHQy3bn7kLyN1ZFDeKcZZlD67Fjm/Ddojc8r2/9qP8D9nre7Wyl4/9s4+B79XTQ2AfvOA96J8Bu/i+7+m0w9vuuE+Pk0PH1i/Phzfyf9h2jh99O7v+1Dmpk9Qkuw/h2+9tbfzY/JWknDY1Q+tufUxD967LlSzNfq26fdh/JJCIm8qgtPz4aSojkOn97iMz0PlfGjrXqqowzDc+Jnkpy+fR7NXEvA4BC+8cHgOLFMu6BOxnU3ZqH1Dj7G7ZO9ma+59kyasqJJUnrImGws6vjmaxVjM3Hc3Ji6PfW1iAD+Mpqvj3XRz8Qx55M3k9UWv9fAQpPMmmzUhHPi6yUYuuJyDnytIrQce03ElvhWi7/5BBot1czGKm1w3wwqkgfXXzRfbt1owwTHYP86x3mUsTBAnJEIsQNydPbUQl+oJ8OpM9ISt8w1rk1gVYnb7OsvG8HpbkhtF9fUOsYOxb7wQIZ7DRKLwQ/V72IpWO/XOnHmIYg5ZBkXu3T1FPtp49LCuzGdZzWG1bax67cmFkRbKHPGdBoz39d4PkKDZ9ye4cPIlVg/5/oLfu1FXnt/6NS1tZOP/o7pPV3bzHKah8nAWmhzN+P2YjuzOsp5V+Ba+ugmv/sez9bMOrjtAQp2Ta3MewDE4uL1oXWq2q9vuSRpfu1gEOOocyD2BbNx5iAlExBoqHFcQDO6KneR6Ch6kMm3zzOsO1HugbVPT+Taw9Q7ubceaz7aW62V5OCZI5OkrYabZ/MV1zyoW93sw25F8432kTRvcYc/FPFtgS/Bh8BHBOgV5Hm4OfXBe7I8JxtFsWJzZpr55l2oOG84a9kGd1V0OSbpBJo789Dm0AvSaQ5oZMDF2BrB4rt2Ddq2aatP3oS7X1PH8oLRb57tTdnJZ9Dm1kDe0RF7o1Vy5oWFwyZVxYTm1DpIqlvH5hvfKEqWU8/WfXhGE2uit2+3nqcWc0Vr6NXOA1z+tU8EN29VUJN0l9Nc4828/nBg51MDp2urXnw472imHrGe7gxvbVUE9eGekBO5k9Cr4/x6xDpIPbljcr9zJl8b0SvgYLTjEiQELdY3MmAxnn6F234Gf5/sEEBOE/bsGprYZpiCeBF3H0B0T9B28Q3b/VyStd7z5piqdVwW2WMbi8m3B9QN/NvrAlOAEYxa0Fd1eaoX1lkHwUfX19bYzV47eg9fTGeevYQXiYyeL68ejMH5TZHYrGHFt1ow9sYdcHNmIni/CbjOobE5zz7Jgz441EkYPAWvrYZvjsPxphQRuyoeKdg/NB+qajYPtU3M1V1djc9x/XSroRqfqT0Cp42atmknZ3m2f+QUk4tj6yWN/ddJID5OxfAKMTfl4LkR5WzOPLPiptu3XOfM/H31nDzNxSvr/G55b/iNzwvnJokOb/ZZxt8/HJdFhrGdevTmgCdz7tlnT6xBOz3g7el0pKP1ZW5I4/BTxuFKQQ2ZuJyIa4+uDTy/L//1b3n1Om/d//WXX3wV3JbYn74hwFf/+b75zcDyG6+E5wk5PeVt6+0L2TrIob5Zo4HP7/NDEP66O/9P+89/+1vOP7Xf1sIXDr0Ex7sUCKZAPqqDMzWaSXsgYwDhvhizIDjA24li40r1pOraU9YAvxnHZq65tknkwJieZy4VsxMwkDqO/+jQPng4st/6Dh7eYd4TcP0cnpFln4R/Yx96gqBglIp8S4Yxdb03V5qm1i1oqNUkX+OXF2Y6WFj4fb6VVbj3sQHfxWeRUVsjkYRh616856ZT915L1kAIMSd2OYc8J7Pqjz60C9ZRvRCAwp65q7VlUW914a0+IuJJjJwsM7YLskwgvF6XwPNPwrU1zCNw/cqozuUeVeKaf8hjaRzk1U8Kja8+67mRQBiexScDFGNtneX8y/6ZhxTRmKDWdIKbeq+n+OOpHiZJYDqmOnKGjzHP/5iujoIHCISch6G0eyTGuOnDpIOudo4Uuddm7K0BAKzxA4l218IzZzn/dj/gFMxxcdrGGuOLdf+ln2s9fFsLM4b9jzaxYzvXjn6uick3/sbRk8+xcfuDbzOwVwNk3T5uXDWszV0L2D0iBnEZTsmdD6lq/uvjR7xw4JZzOIamXIiRpyTbD50CE0ncipYNb3tkfsE9NEW5yPnBV2dj47E/7vNDULHGYW384x9OLWqfXKPP8Mz79VKftqnFbsSglNGw/e3XwmhuqDhzJX5rtZc1tga45beVV6yJJ2py5sfgMVB0XzgoGGAIOH2M1zYFmjx2v2AhXVUjYOPh8oEhgP0i2HMLaDbCxZ6LfpszdrxywDwxJJ18Jx4vuvKPSuQkxLY1bo14V/YtoEgxT0wjb72vBvONNrIyLnc13s3SLQJo++fEL7CN+0tfr9LJUB6/uTL96PvtC67dq7cHVYn3jt2XpprOAGQK/5lja4+xv2bYtibtObjGMfsCEb6jeVKN8cZPTf2COFFEnuE+y4u/o72evV3uuKBDS/fIouzNXi/U+VYjAm5ivNbgh4Sz4Ngx7XWBgsuOc3tK/M53j1kz5M7ZNXxyVgtT+MuMrW4xm3swnD7xaJk+LGkwy1FWohij5VvcU5txSeB+jHYi7bdrBZ16ro9ZxsaOgqLDSn052cvJb64NCv7WIc0HA9p3z4trIuYOuacXY8J++l3Uc2zPeCJdYWRoYDU/UESjP//2GmmmG7P7vGc4KLZ9Yw7F7hPLZunxCt7Z+qHpk/3mOrw0U70oyYC/J/Ni2ro+32aaKg4QTOHX1C5sfeZTdyyc3cDpRcPH1prqmbmJOq+6cldab/yAQJnb7bwynqrn5pw8zN81NXID69upWbDO4YcfKZWbyPn9de4keQklxXEDylu+veEKpv9dn6HIUPt+bWqIHlSafwy8mrp1E3kfj4mPgujoiM8vHAxTGDOmPAnNwN0ujD8n7fwgglp+Di4f3Gj3BxjJnX/5OYM3yXIBmIEuauemHDzvSOAVdOYO+jif4BgbYy9zc/7z3//+5af8LvyPvL09Oum5e5081E4BxjKHCzv1QRcp0iKJSfzHbjLsg591oYPFlmG+b26KzRNOKEm0++ITdmJoZny6C8kczQhDxlyvWZYfcH2N6nzoK/uQjW+dsoUvvOYYnr0ulpW89hc2e7Ge07WmlgU0A6XlBn1SZrY1HP0BYOMD4MbVcMyQOp6sDbmhA4BERrOZWyTm7V+C2Hf6Or0dyOTI6anVnIsL6+4+Z3DyIn45x+4JeyZBiiMBDB1YWXcUNQtP8XzkXaY3przum3Qc3rgsY/Ix99SEvzDTfExnjx7HPt42pvXiRtrVnjkLbbU2Xa+D7edHWgGJyfn0EOIZt9PPvq2Pxx97s90kcbWTg2E/XaCh4hatUBCEBbu59BeqvUWR6u5OH/NMYWS5mo+SIOXEqJasJt4vM52Te2onoD1oXFVtfFdwbR2bQ9vUDe1V2Z71hwGNr7bMN6e1V+Fm3Xr7cNCMRwXN2rE1eragEDd7dQBsPNbNufononoDuzGbgPNzLZ4au1N6LSgzdI205fH8apvOCTSuCgi1l/ZkdXT/9AW218TZH+J1oqKJz3KFxODXJOvB2x2XGy+5FMvdr+MgiQ/76Zuam64Zyb2jfWJV2OrvWUkfmstLDXCRpxqZkJs1U+KdaJD7JC/OWDBx+go684rHWB6c/alCeARwJkaweNdDRLxrT8Fgd2xjSrw4+S1loH0WTILzIL8MxQZ3qrzsTTHVJ4DnByt3G/HywCH61AFvPufJEfMiJscN9gcZhKFn66Af2yfzoXH4fNAhnxzdGLhdTn5iaptExM5was1bLxZwBe1eoMe61n1Qk8uIzNW9XImRqpitByN05cN3L9SLiT9DXM6rf+N0zuFIUuLo1kcUHO2lvcNObkahn/M+wn1oUqrwra/1KO7d6+GkBp8Ih78pGke9apmfItvbxOw3UvUZA/+KJPHUIdnUQiNid3AauBby1PPwXA3C5xvlt/0mrLFVYN93E4bz2RQt4Ls/BGeFrpz32uzbjfEBnFoydQz+7hFWcofjYHt9qKjJgrEKKbYG+0luoj2XSdDZidiQiBFM5lspJuhPDfBMHBHGDKZZDB4ywl58efp120i5h5OcXV/eZt+9q9e8Wwtyp19qlwFc99brDg3B11pp1TCW5SBqcJm2thbF8g7DWtfZo1fDybfXV3lbcY9QkKD6pk/Te1zd100+kTmRZrwJ35pwYC8eZTu2fny7p9gciTmdHv3r4pXxxuYV8/xCFjeG/Wvp3Kz398z3d8e9WQ8XN8TowM7kz/yf5/BzI97f2y7nH/51ePaEG9vc+npvmRx8cdg7T9U4glBMiXxWPxZum7P2LfKJ9+31YBBRDsLbs5l4am4d89gWmQ6vJTgTuHNy8PXKXz3/Ma9if/2u/z/6n3lrOz9gIGP/yJ1T0DN41Tx/nd0b9N++/POf/3TtW/pBRBjavuYHGzRj/xu6n3IzTh7+SB2vnPf/SKfnpUUbn/DQ3z/TTzRQgzfGW0us99v7vOo8HDINjtySGw/VJiot3PY8Zq/3JIoFM8eMXofyaG+8+5A1mPv1ZoAHOXWGQQ31wV3esSdRv3dc+8OiCCRD4QNsTsZ/cN4I1JlvcNZy3Z3JtyrKZ1Xh9JwM+7VPAHytlx5h4aCgno/AccW/GhC+XF5zm8P05VmmRE+eWIJj3NzlqXHtruZQ5atzPbUWv7blJlv544+T2L08xEbD0SbRxRs7fSqWaNDV3VXncrw9AjPrImSAkg+H9nneMKaJYUV8T+CMOVpRkV69xAFoIzRoa95CiVvscIgafR/cgztcriffCNp+Uh9fF6zL58lc7dMpIZGxRLC5VBofmp/68Um1hR2D3fj4GoTPkdP7tvBv9wRMkZIZgtrGo6d2z1O7MdObYg0bLPNY+Zh60AzcMb1oXPuG3R4Npj6tkJQ3vtNz8JXFDGATzPTGb22F7PXWFbwwDiYC9wcES3m4Qe4eBj9pYr2jTF2rc/pzciaouZp15dtXF8sKrnP5Jy/MPnYwiW1z95zj9prYfJzHmy6JkvXj8eezA2J6CB95Id/8TRSO2Gdsv5Zze/TG7KVKVCn2moJkuNKrpuq630sGfy6cjSesKshr3PDY91g89+awOcBJzYHPvUF3upUNaWy7aUto6mpL6KZ8CzGIQ1UO9q4fg9MVyWLzn3bcHNv8wHjydPbkRD0XZoq0gqWkcRPPxpBF7WNjfp9MbNBgDE0MnJNUBDpkSibefRDcaSz5aG7wYB1AMGccLh/Qih3X4CfKmHjy0QtqUJz2q94aqs2L4GBNNQo79xi8uuVIgkmFr/Vg+mY/xV7dm57QcUnN4Vz4Y+mDdlD5aO8nwj0xAoc8ByMxMVNXYNRWZTvP+VzYQuUxx8T1Dz9NnH2qKC3kDM6aacP48e0TMNDq92YZB4bRauNiIA6enNsPjuWTXzsJNLcOl2PAwVSq2ppm9UnWcHtQboLKjx/u91obHvDjkzOofRDSHuObq/szNrBwJv5gSJNxro86BMib9XJUQY6dhENnCWI09OECho1eliMrDXi2twAyDm3JN853AWXhXmoEW4xxOWCW//SSlFrHC8bKN2T2rDqur/1HC/En51wHBG8uJ8se/8HfDDNLBEGMkb3q7R+Pe3Ft/EIBt79GWrO4WfZUtHuX6/n0uIw5JiKQjbMn2zvsOPQO6drmgjJ/XGSpyp5ZM7QTczh6DdB6uPUX6pz8+Hzl+bv8XrOY3uny9bl/nX3f1v6BN3BvzuFgP7+3Zm7Cv+emPUnNO48hvtU9+fgd9R37lm0ki4U3AzY5RzdVycc5GLi+5xVz8mTdqNUxewXPcUh7D2s31wBDzdiHPFlzL/3D1/4l9d9/zSvp3/W/nUOP/z0ZCSopp+j6k9/f/zM35//yRp2bdfsWnaTcnvIH6fj8KW+l5+a8a97inlz8EGN4JVdUfjCQn4rzwwnGhxvi0b5TroGdG4D/Nazmtb+cwV1oe/nyXR/M7T175/d3TGdAXsQbry0k9fYsp4bM8IUQZq6DDhFd4YcXk4iptZCJxy+g4f/m6PXl84qw5aPZyiU88T7mbCyapvHUo0a+b2Ws3lE2fBNIc2RnvZzYMvRtFKx3NApfreq1L7Xtmgh1MYGvH9MfjJjL0VXx+/3UmKmL4O3a7GxCYkn8MqxfwyzqI/YTe/KhQe4GuK+jaXu3ZxCbbejV7/zbfps4h9mrZW/eVdyaWL37B6aI1f3kPXu/12CYBaM8ePsloyxnvTqeszcY4BkTt/gyvKqr1U2oONNuX7WXqVxo2bVkQe5erYZvyVYH58TIbZYss+bxT7mTv7BX1/QgDruToHIQ1+tb+3Ayly9rJbKHs/dw39GEHnM4zxEJrmsYmsecY/d6AjTYXksNa6/jGhJC6JmY1TuSjn70xQYOlq3HnK6xtw+ddV48x8SoZXqz9e4ZxsBWJ4teJ4Y2X7ByjG7yVPvkxZ9/a8d5eqa1ObBvrQ9V406OLHee8w7iGPblBCOcj+srpnkMUNflUeXyUmtArd3ZZY7vaC3Rc7x5YfDr8M2zWtdng9ml6VeYNi+kVZFJZM7/g455LlLcoBkhppQupyiFDuH4TrOIcSRu4abLQqJw49hizdXCAfTCCYEQJYuFTA0K24sjLjiFjy2gNjdGv9hwmhhYOLaealiRW98i26Cs8ojAv92YrRMxzqVZ1uHGRlozjnznk+WbWgZ2A9YgHA3lK2nXQLwwre32Y+vBv/kXq+HVXUf3Q/IY4qen7SECXIBsvc7aHac5UH1H94iV0nNmTle4mZYNvUzmhxOTIabMpi+yWRfQ29tEgRLn9XPyxu4z16LLEyTPtU1nFJElMM9j09w8Z5+xIQRY8E7nHMvRtdermnUkYLRX3q0At75cw71um1MOXPlnusxVN6SeFDDx+Pk6QI/2xq2N3jDu9emynGb55FdnQog3JnAYTspZyzu1dU/Le44JaOaHC1u+Dns9gSRRtS2WTEc7STPEGyf8G20FGbNYdJW6AWXJkSzlP7XBy/UH5ooIClsNng0Nbz9A6/3IG8vyqpm9DU5bJqzgXZ/nyh++5jP39L+WRO465xAMXvL2a/JcBiHIVXOF1Mbc3LjC1Zj6WvfimgsO89un4h/ZpR6St1eLWQ0+oZJ6+jLNpKSOTPLFsHFrIzc353nB28HcH4Rm5Svo3FRmHxcHH/McxtYEtcWcf76NPfVwo0k7//gj/10b/2LryCvB4f3jO/77Mt9Mb50+sQAApfuwe06+ci8D/rDklFeSY/ya/3PdOBOkj2jcMfPS1odO9scRx6RTJ6+av50Cy8e+i+Drb/n97xj8YcPmgC9zHm/4Y3q8PZ3f5ede+ocffxLlf5nGX7PP+J4b89yU8wfp/ENwWe/v5u+7ESRECa+a59cE7KNvcecG3WwjfOYUiFB8nuhQptRPgdsHlgEM8mDxl4lz/t0Q1zh9+G+Gz3hWfbA9zPZ3cr9xBn7LkbUDURmrbfehaq3s8hd6jtUb7dEh3p8Pdb/33X5D/8RQZNvDuR2o22vCQ+z2hu6A7Zm55fG1a2zZB4XbOBqJza5mwgsfxmkDlaFhcRpOz9FVSybh6pIKQ3bWxXDc/PYAreH+0CwULiawfWLa6+188xGP3ZyjdXlrtzqZV4H8FVt74nrjSP3Nj4TlvRnrN1vyiplYidTt4cn31Bisej0XckJIOz2bypP/KLYdXsbqa814m+3mXG3EMuQYXsBnPTxF5RgMY+M713A0T7KjE8w7mjPHfOy+TEKVop8s5Fgt9TfSefzbB68919W9zyOWe6uvhumt/Fiqo7lam1brLt+1Zjb98HmBodXUY5GdQ52Z/eIMKwcyZQ0oS7QxbQ3gMArGmiF6aiVOtA9Vjb31EPeXOkriUXzi7cvWMfnJePgyY9VMJcDHmOxO4MGMDe/iX/7dixu7+PJhb3Rn+3XFavmoa9Hd08H21GMA1Z8zfZg6ca4+ENPNWJdx/Nu7Tbo5ga0tE7nzPf8JPwngVunkR/eroxnbV+uEWmMO0avOR4dfB64DBOthxMTuaJDx8xb3AeRBfV9NLnXllaYNJcEKbNRiyr1HfXvhaEzg+Y54hdCcM4DQpZHTsBZfTLEbA4zw1QNmNbXZOk9oo7vE33WPb8pB5BQfTV7d68Ccf/SKf8wv22zWsbQ/i1tkaNUO5cb3DFM4BOBF3/0C9GLaNe7FLV/OG2ufTNg6oFqfWU7vpwZTRYX21lH+0UO++AqrJiVwyFi78+D2C7m1V2qO+QCZz9ME1hlnDapfGPbEGvCLUsP1wzRaD2BwmyPL3pSVwApID17u5pcT3cdenl0r22zB+3HjQH5cl2hKPbRyZTvTEAtnwktqznYW2+w30/zDfrjfHvmgIsnxw7v5vLkgzzOshcTwwK6UJ2byEVLmnstLzNTlE0CCQdbO7GMMN7aqIE//NWQqVjMcyOqZALVK3WgBtUr49qvXrAwjx641ZHqyrdgUzVRNosHpzGpS0n3Fr6xxoM2vRexLeHyxER/fbG+xGHTg2jnnWE/CrDNnqUcdvQY2AmejEkjujWUJ2XG2HnVqH2xieOzJfAAAIABJREFUNt99PAjgLXUEeJqeQKEctD05Tnqc2Pd8ptNPfEhYWAKVn3WJmQTCDXh83pTOjcafeRmdOGxc1+pOMOfePKIp5No4zavhmPKP20JuRv/8gb82zn+1lrfI5ybzN179JWny+FbtKabZ6JOU9gv52NuzOPJ9wViOyetb3LnJD29UWgfZ1WQsq7IYyDRDvpx7PcFZ1oWqP0LWvmtjeQxINt7+L3tqg2f3Fwxs/Mjhhx9++vK3/8jb43PjzV9z59VxegeWPwDHnBt+zryd3X2g1woJ/+jlsdRfD8gPIrxR545/8oTM+akJe2xdt0/+7FRYCMVPzfRwsOpnPxnB9gaXKf9qtw84B+MZF2n2sZG58Ns9cP7QZ2InyzKd8+3z6m8LyNieDCc1hGRKmfjYntzkrHKArNDQGJ5e5AOLGGeKLpAjfs+py97oup2QPTb6rCq4J47ZxsON0PoeK3HT+xZSHIhVt7M+HXpi4yjf9iMRXpdEdHzyfK4Wc0WOXhtK9uIPLpNbG9Zo38cJagAfQPtd7MbaVg9Dsr1Ym7lgz2dsvXmfaPVcNfaL3PmHQqIYXcfCh8bpLVj0hfecjS12gmVgDmdZmeUTLnSO5pMwpqqqAmHHuQy1wrTxzNHB0M55tGn9VutgQd+aWzsc2Pjo17oGGJVMTvMF0Bx4JqYoxGjL8uqi3lnLa4rlUCXeiRtdEq8v7ukZ59U9rMh1j+yfmxVPPrq3MLMsmlXjWVuttaB7eS4+Nq9JcnbAc1djLdUgqKO5Tg/x2Pd4BttsEzInXeDysbGFg779KV37Z6YVB+rMQVVr+zBMA6BN3+4FwfKNnpeq+ddbrtvVRU5vdq9kq4+jUeRgD3PWM45Zndrbp8Yi5zw2wEP89INywJ7vFYBnWDfY7OFb2KQ8pumSevocFMJ8Qu7HZ1/wUYsBOcg3pMtVHxT736wBiLUbO+gNxhPgKcLck5QC8JlSEogcpXx8K3rOu8GINaP27UWtyyg/eeeCt8UGPc0l5HBVM2ubhk7qw99kZ03DqMHG5dyWoaOE1rfaPEPAJxgOg/NlgbFhzxhPFzke7ompv/b2I4hKefpKePO114MfK18s8PoqtbxwtFYF4CcRxBnnGwZzAPrKISAwdVlrLHCN3sMhsAd89m9s73xkH3QVoG32A0M+zxOUo7uce42QF6h6rWPiR1e/MEhTlPUfzbV3WR4sjhS62F4nyYEeRU0+gPYI7s2AzS4VO8etSxXxy/3GQMCQKmjy598yWd/6JckiTvzNzqSOaqyVbpRjmOjj5m8SSbo3xa420p1YuPPs2TrgwJmhrllwnckz66N/8wTfPIZ6eOMxNGbZm39tV1f3eAtXkwsrLy85GdHarjSme4g93GCAOW9uQtSkuXWKE7TYqbNg8Zu512XinpuA1W8iYp5RbWsYMSrGRv5H4MA2R/lWbXH4To+n9mW32KGrpvXESA/yb2N3PnBVbKatFSPzuy/ls2tcL9FiPEVmuJpXCWuptXV2Dlef5Lc6dOmf/Sxt9fIKbl8VJksHN1d7A7A353h8Wznn2XO1JIyb+vya9hf+625vnnMT6jyvln/N5+95uzf5//gz/z96bjbFcCME1xyX61FhTA4k9OTBt3snD4u8kM4r13j5r7kcOVlfV59HfOb7NENg/goCdMfM/W/lwEU3v4++bznfvYbje/94XnrBf9mWOLD0ih4zWNPP9o95gmaoK99/3bv8rjk/5OB3zunV/QN54UgIkqjxDuKyQl9O9Y2hlgZOgJqHyJNBiSMew8YwY5n1uYEfWjkyB4/29i+7knXpAGaID2YEwzcUdWbNDzeqyQjjOZwaK+JogQFfzU9+7PukPYAJK+momsXHqXpjSsyoRtSZN0PzLYIqmb9reBp1vdisWT2QNoOnLPF/Wzu2K7fdItsO92i0Gj/wzb17A8eLJXd3p0zmOYl2RVD8SdfamtfHA6YIjx/fE/GsB2OKqjYnsQ3YkzlsjntGwHS6KatdnjcfMAQENA9yV0vB1G8qzoMFzuh6Utdk/8Erke+/Y9/rZ9djDvctZJ//oqc66ivmRpL//vpoMPlAZ7WyWHbO1e0+soyQncPrNe5jB0HNt+Guwrt1s8ZnHnvREHRvTCxhWZ5ab77G1wsyIxBQr811Q8fTxWLszeYffavJM7wZt2+ZERzsDnME0T4L1rV7uqo21z5v3Uql26pDZlwYmoFrptyb7/Rk+5nrNJCJGB1bkyzNJM/GAG9iZg2fo/Uk/q83qfGQKr6jweja3r2xSRK1VbcC6tmM6Op6e/72VRy5SItuIxMRx1D3TK3M+o0i+OHFzgfgHWrPghAGmOBrGCDr9cdzrgPt4PnwYPjWenD4iJtjX+jNanTWXg61ocnHDFlNne/MSYSIRTu9TYCMpp4BPwuTcIrXwjqnSNCNug06jR3sxQ3zxg2vDCEqg5NJCTu5PDpncR+I1hTAk+uUiDn/0MfHfsNcLDgdosql9qmz/sXkfHTD2097cr5YymbccHz2q34Yie8XZS/WtXHeIWa0N/di62kvQI/dRu2eYL9fImYkDL4Zu2++DZ0H2fjPAy5crOFO3bv39jLxZhkZpZN8aoplv9GFphdkUWTfMM9wY9v9y9wc0hXN8QQ9ujD6zXrdAULTvpJ3emFfIMkwzwCzlLuOHomvojmTRTH668VS3ayPdrUtdnMnTNPWmQh7jbH7w1qOaCP3Kxe9W488CE6o+V/g5FCkX/jOPLh37set1tCH59QQ5j64NVF7AU31o/n08KZonqkHfQzy8g/uJ7Pzo390N1vj2ts3v0LLE3M9k6Qht0ezvhwYgh0tarc/YfFawD36wGSu3mdPyERPgPv2UCgtcvZPqnLYa3lnPZWjh0GEY05aePzIOPscHduznptnQ8Ttwlx05BmrJzwtvXwHQezWlynRmPja71/pzlxKD7TOz0CqnrWVJGp1xAfavmdS8+Oc4EpCTwO4MeT3qL/mL7b734bxUyOZCIjMvYkkIwly8OwaAzbM2LvOTL7v/8hNeF4d7k34/MG5QOipN53zB97UAs9oYvoOaIspv76Z7s0xf1s9/wF78vZV6e5RroETPCS79hympZxWoc1rhfXYXi3MvSYST2/47A3057sC7Ed6+j1vvWeQL8Mb8czVhW3mcCLGJ+5cj1n3D+vxA4C+Uo+glQsXIVB8PNyUBmjtBGBjGEzABBpcF8cTGgh7aB9ylEJ9QwQFATpGA/HBQDnehwNbRzkzX45Mh1U6V3IMvc7R0DCJGtOjvYTHunT3MDwsQBbHbOLOLJOZU/egte2h9llNnu3RqSnutW0cvfZaSM5mvRy7Pt9/iFZzsHGyr6phkcFRd0C9XjRTWL9ngH+wRMB34kqjxhITT1AwJgwgc+M60U5Nmj0OCZHEkcMIQlvj7scm9roAn89GZC5NLWs1z5qGlByvn/mqaeLJSTIF7Zpl+0Qq6VKjexGDKNZ6YF1lnb8yplARi1s/PM6tB0iz2QvzbQTn6jAg2rpXiCmbRw4xra7l7xrsaF5czt27xPDQnSGPR7RkNExHfY1xn9Q7McK3f2TsjpoKX75XdD41S90cPYZn+Ei6/UcCY9efHN0jdZ1YJSeitXavRiM8Jeu16Z7XttcZbkYrceK6vVtuVagJuz0MqtYnRttY3bPEPzr32rCXhk1vzv7Cmfg0CD33uo9htOMxQ3gxVcXg8WiTHKfj4u81bn1yzm6MBlZ8GuP5Eu4PBLDs/sDDUPcEHR+c8dnrihU7GVvjCD6YdYLM3D6A8SOHY3MaUHJgRkc+ehWaxhhnGyMQC70zKPOcd4Qj0FPb1qS2wW1tvBOPrBM6gQvifF1NNqYVujlNosC19Ix9mwI7dEt5EcxoQLA+EQC06BdFWyYeLCsNZSRPddVeKwXyuUenORRrAyUZ3nETi89ock2PsJcXgKAcagNtRADGTnwWGE4fDJugVpkAYuQx2BzWF9uwlnsx0VOe9qR0ralxN6cM5AeUQdy/G+Qh1hoCsp8ACZj6Eeo+YVfzso2eqVnrzLd3G7e8nM01XPaJuaO8y64G1VFFa9n+oINxuDKXO/nPCEYdayPmyQ9XabZPjdVGLN7EFrXIZFy+0O1cjPDgZ5+I4PPVmKWWnutf3Y0bNFLov58XJyHBEGeoGIwjvc03L3uKxn4UE3/zZBL7W1PnZYjr1FTLcm/MpJYDBNHPno6lsaYKBI7loT6ydO31Mf5FLaKoUcdi4yY3eM24YJ29MkL65miumdvPjeScz7OfsEE+fpZMdzgHv4ZMnj77OIZr+IAJdU3wfL2AwRP7VNele4cPa/DRYXyO7Rm+ju1bkXCXq/hi2G/H4THNmpJ+2WNaKK+O8ooy/x+5rywngzfsOYeHm+eji2n+wbIKT359k4/85IrNlAekFOPjmh+y9Yaz/9/5vfk0PsFc3+czzwR7o9lY3wq/NeXsjSsY/lAcr6D7R89y5uY5n9TD2745WyPVMK8s505jw4iPilpLbfj/wE559o3/Bi3/3zj/pVm4+2pzQIZO4aMR07djs7ef3zTqAe/eockbqyTwd9O5WZ/6fLv65LLxpzcQIbg1kQXt/aQXTw2/8X+v53f3feWc37Ov6s2vpFI59bCFcf4ogd7FBoc9m8AsseuqqE2Tsz/yiI/re/kOGEu4Gi8DJI7i0em+gVlPE3UlKb7xRhemMYtxbkx9b/gCatuonkVPzxu5GibHwiGZnmCqknFOstoEcnBAvZl2P8A1pF9zW9fIMM1yFffWPvM4ULhbdHGrrf6RMWJmNWB0bS3VhhKcT2yX5hqXmNVafFiCY66mYdCIQPlW1xCG4OTi8YrInD85BjHJipJO4WedSZHDLeRydYmy/9eI58MJ21yTx2GBw/yCt57h9tqsvyy109/tsd6sex4/31eS89sBpo9puPH3mrm45qI6o13msPyxn/jhl2Z45a+SoYR/lAjMoinix0GWA8jy+vEwanvzdi/0rYYsoCVmLpHGAcrwMZNzPrdvN217h/36Aebznip79J39VO70cOKTwFCP+l8WKePf62H1VFu9ra8sUTQ5D8vooib++THXerETU8WnDmoDb53bpCasHuflPPqg3zzEwgGR506wHbwenJ2sj0Bjcczc7+lawbdmoro/wZl3fSxrA6Mm/Ngymmcwk/zobuLi3KPhNrbxyxEGSMKXf7ufww+m6Pr3+cPp+dTSDl5G+KTNAU3IYWiedd/bposUpBdCN0Q28S4vSWtrAjchSbC9m2xDTQSXxPo7yxElcyIdazaH8+bFX1W1HH6wNIozoeBs3HAug3Qv26fGzUSsP2lDyHCTm+yunZJpRjD3p4x8AZMjn8Qz1o+m4SMHEJDOxZEhdsJwcCI245gIi4nwj592iRBazl2D9wsz+O0n8YeUGTmqm5W+2HreNY7q1xIRRk09qzMo4/CVl3WYrKO7p2sOp/aBy0niEhTFOu9I7E/sV9XmuXtODuNHgUjzDl8MVTAx62uWxMaeGtl704P3p8dXjE968edTfvcRfz77UTb8cC334mc9oNnLoEyRwwYEUGodcZOvOCzAaoPpBo3yYolZfWgGmfXHXq0fmqZidobMiXVw4tNv7J3LGtu+mnJwCbyqmre+6oCGelavYPOMLYDGc2wdb899xXoErwZKaVRZ2/3MSQZfAWKutotlRvaOIlhps29wsM4BPoAxLHLXUmzP8EasvtdGbNY3GzhMsfju266BHVAA8ph8ZsN5asu6nsShmSeiGu68fqqa7MbADRZvPL4vG45q4obSt0uDzc3efuPxG6gvjSQGOsKbIBOZznL9ZoIHfeYE2bydZZ6eLZ2afLAbYjTqDJN655XfcOwaOv4Lth3NNWFk4/fOc/7+B27G+zvpvpI+N8/EsRe/5wb0+7zdvaM/iOAvwG+xSkFLRr+ukpO0sVHnDl5tPr8Lz57khwK0DV3tYbFe45ImcnjgWK7mWNacQ9VOjW3W4MH6u/s0Plzmwp9Px+5xFtu3l58fJHQ0yHYmePN5486FgptDhsdbdsNzvKXMbB9XIc1Ho4Hjv0M99MjksSPe2NZnTYnZ/LIvhef6tB/U8Nd4+8HamCeP1x34OBCZk71lYSMxbBC4wu6Mq4zAfD44enfWl9owYFBbWxbWBoVp6AV0AMqMHmb8KySWuBuH7faHBPS0MVnAfx4j8A7niNhYedGQga7m2ry1bav2Gtoc367LkmN0DOUxOcFOeft9Bmj+lY+IxvXVUJXFxxhdNigroO88S3n2m1V8RGBtfKaus1IAZ1hzBuAcDIs5xQbDGYOr3gkDQM94HuZzsKIX0/ge7S25+aAAvkYnHVGlv3qJwkbcp5AY4XEMQdbODCq+nQQ7HJmCwb7cnuUqz4Z3v2PTnAMORzrG0nzMXXRNH8b+Wf/QDMf2Qersl9jlz5mp+5Jz50/60dAKsE9gcqNZLjTNYEZ57E21saZX1a0yAAzOy7FrHT2sJl0FZhqup26R8k1dZuqcENIy1JmFZ/WYuu7Rj07GPmfdqvZcMjD5vMbMs3g1pMf825xyctACfPEaj0dzMK2b6GKnGnHGblgAi3EyObUiMYTu0VNXQ1fbXsOyDOvkfVUM11uPc/kb25KYZ+R0sPS6hU2bbn0DTaYMW3J9w4pnRnngPdfTxACAA5+jYsaGM/XyeLGJgptfPktQYnRMLBxMS7h8IaAQretTyrVMkxtYKbSZQQNOvCKmQZmv6I+b5KY10aFdffjUIrHzSWNUa5TYvBaIKExLRqjo2pivz4s/uejJplzshFzNh2XAA7SmDc6Z9XLYh+4EWfcj/iCgUSPoEhgXG+arqRcDkN0TtJW7kfsNzT2Y/oNhbM+br7ZmXJ0KqWOOR1GE3P2MM9x98L4CUU5ez/OAC83pMYuPAfLq3m9s7Vsyj35qPdqtnJxE7vXFnBFUKbvM8fRpSrOe+SbqnLoGre7b7LHfHOvfB0rDNp9kmzZZS95efMPfParx3d9SlLAPHp2bN/D2pTXZjwQYr29aMrng+hiSfPbx9HT6XHz68TzBsAmJtR57k8UKMqCc5rP5zLpj4851UjVep0OoZflYwGmeizWeA3ukABfTh+3xoIh3nImUa/08b8JY1dz0zTxIG8vep5ocYO2eEMI1Q91UOmv0Le2eQUyNNSVuerFPFITAZaLJvfHYMu7yrrXGsXHneomt2sDmMx93P1kYJOvcc4cjr5hz05qbWF4lt77RA5df56y5LvIBp+eZ5uTQ7LVDv8h1oZbSB4xgIbmDOIfa4jUNh/mM0xo4b6yuHLCBm7Hztfj2+dxs81fKuTn/IW95/523hCeGvLwCTr39I2j87jGvvidL/NCCUfvkbSpi9Yhb/Wjjpux3H1/Ku69o+6OC8JV3iOVO9CW486mHE7ng/oNXlBGQD3+YOYHYGfqgw/9y4qTGFpIpr0y3BmME92vMm0rhEAzJcsXS+qWrjtjghkfYyT06ERPHiRsOpYBl7NcEU9YBH5rRqRn/xBx/ArzJCaG/908iSdo14hwTpwsDAswT3c5je7ghaY4cx24Yh3eEYzN91PRgyhPDydlpeYkmRXjO10cta7ekxK4M7HJxzqhd68yb8eqKb0TIuV+jCoahsYKCQ0ZV9Vz+9ml35tiCPI9pMpWr1xUy0Q3pzuHs2LpmWdwslGaSzVRHa1ot5drnPPCC9lp8+sU+q2PPQS0PrCfN1L01EnfEAnTUZkzWW0tJUuvkAApmuRY/2bT37yjEs07O0b11NP/JML2EOUNt6zOw9vFZb9zl+muOwmKn0flYBs95/FoD8QDOpZkVGIPyxeg+o3lCdt/XLnTJGpUVrN0Dp3M9fmK3c1VQX+d42qW/XlviItBrskKnb2hNfD5kBlNSbV3EYiFvhuC213M2Nzys/RkcTPSg/PjlFr9JRJj7fJ0H1L4Wn2jHZt/niXIdX+Wy3DrQTCx69mv31n+jq8uoYbtcGpYni6OFGjJWS7NSZxF4nbnOagyG1WF8BR5wbed49/OaQkQ8p8mFr5U2jblI6TeFARcUI0IyVifrzGs9xAHULtYDCIU3/cld24GAkq+Mu2fqC1Rrcr7atx61wctnw62L/cv/ORPmGLUzZwzR3bo6lvwkDe5gIFD8SEMs/pwPLTZg+Wfk5CHfyT88w4IafUXANFqwJ86ck4v5MDUoa7ixb9T6PZuLDKurYVgY+6T55IbPQWCDOTK6mvzCElVj0qOjOCZcfpy3n+sUv7Cc26cxxPnyVJMgAWKttRmsaWOoT989GzQ2+lNVWx/erUikWkY21Lo/9FsjGreay7mlTzvMJcnoW/9mNSPaHOVhevNdW2UGS+IzpvesqW3rZC00tvlmAqepcp6yPBc6vMYTO5oCPNlmsv3bPWJdNLtNvsPIpLUckq7VSdDRjNyAkndrB9N5OGUa/mOfeCObwBpFP+sEv9dMqycVjuGeORLETkbSyrQ6s7ZajAl/HyBP3Oi7T57IQQUJmjzVSXrZ48NdZYOszbiZwqIzOKgWkQnrZSKXvRw/9mrb80aWw7gJXj1or+abZzlg0RcamLTnGjux5m2OzVRFm4S4RsrlkxSC4gey/ZOnh4uenOor/OSdODjsE7wOSS/95MHqK+d5UsaZez258lfU0eeNMZzB8Wo1bPJmRs3dhM0RJ0Ajmbo4EPYHgsaVh0hROcDbiHJ4jP5mJXZmk86vDUE1jFkcNfTrKzG5IacO3t7O72p7s55C9y37vlNgEytyNWEMaz/UhrtP9JyQ3UFNoqMRDD/w+OoPOw7At9vPypq2P/s1TnXbG3HJ616E7zyZZ74a57ycxYYBIRmsF8vextIPAewvzy/pEzUlO9rBDA47o89/wPWV4qHXV83BYAQ/TmLN7eSYSXQ0NQCa0TxYeE6O5Q2KHzBUIzEZ41ODuWOAY8bSuVzC0bUoexQiOO5g3k78paZ4imyvigz6aIFl+/hwAqB23DuycB3YZItnGA8wHrYOTGxb3nEP166rg3oIyVG68TLPoOb137zV0O9bEztqiZ5QdbZXWD/7VpwJSfPsczw4Z7CHXVeHfeFrJcm9DoEHUlwWB18daK6em6t1boa/nr1GqJs9sElgwiT96tk625X93gXuxAE98atRppaktqpbnZReS45MmrTPEepADCQZApzuc4hx4KzdWQ+GmPOuiVta68YfG1g5n4tIW1NKYG1Zb1xZH+7pX/nbP7ybr68IzirY5iPvIgruNZi9GGHqCMv2TLXG16YCdKd3/HvXLA975nKgc3/QABjAhDnhe3X+USfOs6dgSDMhOZ2h5tGwRpbiCcina/hYRCv8/Gu9xZqTa4CY+PgwVsPoQj+YIjxzwNKvCyYYisnszDGDxDXUWk4cqziOJhYfa5YT+fBvX/nibO/I0lFdmT94KUrc5xGCEEUyU8pjr4aHkzDPmbEYA4oaeyOqcvfxchLTGraO0kjBIQBpxy23lk0Xi75wz15w9v42NTofnrIhLQGQDg+9qAaB8vn18GG/tRDGd9hRUEkuJM1smmui4eQk0gPA+Qy2swYvG2jmH+spkIAtYnPBvzwn7+gIWCbssgZYLEFbGJYZp0HNztE8CzGeBRfYVVp30OG8DW3uMpNrfOQAOvGqMDSz0W0dhQUVpHUYVjpt1UbMGwevtjy4hMLP5oOn4dq31iyqgUliJhdzB/ydAexczFrbW1BYlts+ZHHPJ31QjUWn/skBg+smTgBsoMu9dWp8D9aCuOIUIXdBZCtHjrF3lJu5NsOf+ge13zCMH85SRGnywub1dXrSB0bZTUxN39beByhSEFbs6lqs1iBin2nzmZHQ1us3keYUO3b9z1wphOTf9ljdC9x0WTvNYWPAvUOO2LQGBG5FOn/h9qwGIyRtBARnP07/4Ip/IL0GdkFm3HNmPtVsbxa5eoRwGIeR3UD1Y96YrbPnWE/d27Gy3RWRcw3Axsf0xYqfmjbviY1vbSgAz3rjJWs6SM0jzvksg8eHCvoonzHB23cWKtHqauP1cN3UtSiv96nFWAD9ePilN9C8XIN8cuImnWk+0WY9uTHzJrcNMvNqtdcrIp5eD/EOibooR7pRySJjTl3gSkzzkTfpvTmPfedgtv7R9r7FvUETOzh+Bx2eH/J2c/4rsf1ddNb8nnr1IiE/oMg7CGw3wkbLaWUhHKub/K5yFE8or3LvDzry1vn8Lvpvv/765bdffu3vpvMuBX8I0v7IkNjV0Jto6OafPTSJGHDvZz2N15499B0BxPsDCPaSX1vY/x6tdm7LKzr/PRy9Db5Xc+3WNQdKQyc35/tKfeD2Cchqz5TF2R6W3tCDZXDez91D64sxa/eRtXmNKD5Bm2P7Nd5iExJEDvnc4OHAwphSumBN/t0/pzeAHPRsYw3Cnc8P27CZljmYAMCoB9PQZnrzuWDdzw9MTMSWkz0pHxM1z3p1vLahM6c1BGs0ZIraKB05lJ0jY89Cs24NXBUuZj1R4XzZWDV/ryJCFtAsWl7zx5z9dUuwPtxe02MzwAPXYtVuXlTJYXiUwcccPHxyjuKciC9HecCA7j+COhrBcfmLN94McREbMz3vP2LLVw3VsgV+1BQdrAvf7IOH5t8McjCMy5lVLXcOEyuOOOtPJPmwMR7d5Rpm8UQcpNMyGumh3KumdjHuDbOoSA61kMvR9Wq/OerHW63xTAjYtWH8yCjoeJOhusUkHind50l/NDAp7yi6vIm5+sq9GpZrz6HI2Guj+bCU+1U6xQy2/OwF9vo6r80qpm5YmgZrVva3ObZJ+Kt0sLgzTqzzrStoODjln9wcp7dd464ieLDxubrwOMc5A11bl/Ox317GQNCrX9YCdU0Mc1zw9LPzGztUEK7gTMxFTMJbW5XDAVBeuDOeMMhjaS+0jxO+rg+6LWeZz2sdZgxSdV0/HBfZGbmubaKN9Y/E6eTi1lO3ZQ1SYfjNhxHvOLPCw+d6LDBFfmxGvGXaEnUnAAAgAElEQVTIkc2nCQQsr00pkZuQ6dF8fJtpnFcCBvHNAW2qGm4crWcCOOWTurfOowfXaGu2yXliTNO4yXl0ss4w76RyTabRIhtz+Qo6toA3TA2so2Wh4ByJx3pqDMY5QrZmcyRy1wZ2D7YXrT8OMatFNYPOiV4Mh4jCcIjhsBG1ZKXm6tYLB3hcE6dF3I031+bbGBOQIQP8ftYyfKMAH/9MNddYcN2PqZ3EqWeQsiy++urHUdabW7CHcnXNHD7k5ZhP4ziwdoUdtEb1gD3XH3ZcjODQW/8YUCuXCFadAF87e5RPaKTK4aDAzPrDBou94ATgU5M6wqIP7IxmyWLIyCfmzYlx8jYMQwZ5JnBne9Ydoaw356mvzkRWI8vPgb0DWZ2PJSdns1zv4baOde51M0GaT9dOyrMHcQmZPlrz1Neo063GWj8xRBHca6f1pobcVK2uxucI7GQ2ZDLUuFrgOJfD4ksifpV4DuHGCSVH4nlLszeVzPPJ4Lh/ZO1r/quu8wfHNpmo8oFF/4SqRxZ1jBgM+awOveLG24TDOcCc2icKgd8ekX/Xi8c3GjCtlhMT7/e8gh4cNfkH4/JK+g8//Oic/yMc3/7uPftRhSNr+tL64iHZDHCg+w/JmfGDDuwT91v+S7dfc4O+n7//1ptlbsb3hnzxVvIk3/0o4eVcPLm84Z+86kA/3PlhQ2/SuWm/N+S++h/F3pjTO/rJD0K2ruTfvPD5MfH9XfdkH+zpSUCN36/J24PDS4xxU6COGAZQrmAyGXrKdPTmfRY4AUPjKSqz7mdqPj8AiXv6YJ9NQMDG9ocZ8kCtnxO9SpLAzn44bz6hwunv5J2c+KqrNSRMDs4MUljbGOB3Goe5PkBZpDfgW/IGl1Mo19oxlws+9s0Y50NwMxAqxsn2P4ujrSS6OfD1sQNXr5fNN9oHc+oAl0/xc85pcqCwcfXvdbNnkGDDAIDz0RDD2uJhChejx7URUt17LiZoNgIwtBiDm2XWoyEGfNirFdwYxpZTY+E7yM707WF0mJcQicw88wGGZpmqg8zpE/HDUTXFL5YV82KCZVF6rPXlSH7M1ZE657FKkPgqM4J84cHSH5RmrW32++Eh3pRqVIlYdPOJpZVgrg1eYwjOIL0SdkV69HEeH+cdxHeA+cyBnXwO9ybrnJli3dzjKi50MOKz37V+HiWAZPekeZZP8GjZwKMjhndeJXtsblYfucN1EGoPw9mzqTn2G9N4auST0Zp2zmqG06I8qpu9ZVDRHu8ZnPsHJOOjV/Qk/6wxwcTv9U5c+x+vPSSa0WzMqqR5WTM2JkkvV+LlKwSUeXfZGFbtBbFDLqQZp76pWU3xtrYimqU1WreUmcVdyuHHji0nYwJRA2aAeu7p1QIeBIQqSuz8kbgaw6QTjPNOTtAK1y1ZN6BiBCuq5E12C7vJ5U4qiOd08nXdi81yLKrc04ldeLagtfAsgxpkHSPzdlDfXrxbi0153qJRLBwd3bp3fRxO4Jl2Wo/p7Bgx05+tQW0TL2Vj1TuYfRACtRpXg9qH4/TVkstTGx0ZvWITrQnvk0+No2VOhz8BfetGS8K9+ejv6nmjSeFIbHvC6mo5uWOadzH5Kh0526WGw9/ONedlIG48GEejUZkbpx/X6o9WfDM6mz2JbWvaetQ4+O09oe3LkLxxwX7UOm03DzyuWWXiW7o69zha25fJYQr6S8iQbTey1j7dQhO5V+fWQOh21D5IVa4TP1wnJlztLdGkDr7gb3pkJWI2PzCh1ktcVuiSKEu/Jon799cN0U2VCIKyYG0859GqRWD78NG30cvb5pp5Ocu1bMZM38xBXIZvMyIXc7Jrztl8IGKKrbh7/QBYfcZu7WAnVirjMWJPzDzRkBhfPgsvppxYJhrz6MbmnDMI+1Os6Q/XjW9PNgfnaOh7q4LuKD98WW9aziH1L6LnZnZ/f3oBV9OQzMnwTY8oCJdTyvZwo9Q9/mnEuuYJSJy8nXowUobWErIgAzpfgMsh6/xQhiq15Dsf3/y4WeO/XusG/+i5f9ytvNR4eJGRdS+b3Ye6N4fXCf3NxJu7xPAX8NG+v8/P76TjP/8VGn+8jr+2zg8OvDkm9/Qoce5fzozdy+47D6HV0d7ca8K364Pn1V9i1eNEZnvWoL5anWZS2+Ylxtpjl9X8Huy1nP2FS2Q9Iwzbs9O67Rn6n+GiSg4UN/bHIGwOnsDoX2D7TWD/bsK9WQa6Yymrr1Z+QFNO6u8Pblr3oOOknO37qwucP+wIhmuG/dw9JprAvZnZfXWP7Q/u6YupSJQYxOjPpJsQMzh+UHCH/AbUtvsmZ0iWAu/FupMG+O1IZtIMPp69rpChlFyPazNwMfO4XtSAc2outC96pzWg04/xn75KsUE998pLfuqRLnYnOQupLwLtpdzgwHiBjh/T9JzGtJ5lhNuAFapf/qmxmsmd2ctL3k01aavLhM0z+ZB78yg+ljvsgynCGF7xk58V/1RMHWqYmogpesgay4LvM9Td78ETP5qpRR78YLGbANzmyHlw+tWThIgT06lhtRydQraOEhM0eboHZ60CGc1HLoZ7ZrquB5bT3Vf7Ev7qr27nZajMj5pNIX75qMIanmu6HM3jr0NecGagb59NheZ8tNdaWFKwdVxNwj5sU93wNkbhMNiLZDRlc6o1MPvAN8HFoMvfOnpw+qg5vszJZfzsCW7Xw4E6ebNunQ3g4YdvwaI3Joi9xmC2W/jMBXYGSTPKN4uitTeWaXul0eVi8cDPOZ9oZaJwgM2p3XkO41dLcI3B+IRFp/tyiUu5vSq89UgIbXXAwpzRVCNmaq+teDB67XG1Tmj3NYvT68y3DuJ+qMARWhqqGcoKUMyQE1SRrWprG3lNlLAyrJcoRtbjY4Ko3bSTiQJBTqFqGZsOCSabQTfHFkZsn7wli5tZ9sM54eaZwz6598b05Ccun+GzT+jPp/XDSx60ZQqyfWPuCncdgyWWaPl88DQohxEUnDHDWW7wpbYmQvQ3R5fVx/zsjTHDFyhoe71cgDOWRV0kCrc3EDizZBiLHX1rGQ1oxH744z+6sYI7tkw2oUaWex1gYLRHNxfxDWqOHM+NGOhdNy9x7kPyupesGXOiAH//ac9xVEMwUxOsjB4zMZYDltGXGXZ7yhzXwWFgqeHfYOo3BEi+Mdx68VEVezf2wz12/O7FOEY3VLU0r32ALksgZy+yvtiNAdecJZmgA2w10DDsM5PVyDxj7dulratxkD0jy/09Q/ZUjcfd60ItsckzuRbC1p4YuOgZTg5xku3sD/aM6rl9bNTkMiJxyyvBVmz0cEqVOYCMiPBrk0DXPXWaeCjyub1hjsnc5ho9FPNwvDq2j5Mh8VtDeZbRfsgx9WOYJ2rkEx3/e23JNTeN2+fqg7WvNPsKOm8Pj8O3KgMYHjUrVvp7COb06FqPTQ3S2AQR0g43N1v8tXU0cQPrjfX38zPl6VvkqZGz/3e6DYBqauScZy3ooJYd1PPnd/kjcXlr+9mXecv59/l69FXawLkByxvhDYP69H/zYDB3z1YcG5y0xFe0eUVVW+1gfvuVv/D+NW917+/A83b771IbZ+x7Y3e0jfB3zc05xJ7j38ft5r435uTDVsmJmbG/DrD7QHH7O6DWNNXatTmc6GtcOrKonXwOTzlQz6DUv+sYl49SDggsBgRjH9CBCAa0/Z0fdsRu7fa785KW4CN3Yqmbm+r2m2s711neIcLNK6nRwD74ijtL/b2WBPEb+8nFHvI3BvzMOyS2D/KG6OOmnJuAFNqccw6Gr6kXp2JEZOKeKCihM6YimE4+XPuKPxrOSKy1H8N2pV8TUpuLNRxTP9zT65svgMFquwfZi1v+JqRW6+DAlL42UwHPEezmVEtiei7nB9f4BBwO9h2JnzybHzt8Chpdzice/fqfpNU7uo2ppvYB/FYNU+dbw56b8+pSxyRbjKryOIyAxetjPXkXi5957Si4c1Rgr5bwmaeMxpti7IPafG0DARlNQvL5/jZU4zN/5lvzBEy62//ZEIPVxQaR4iTdfDGcmiCufWUs3lrR8Ay/Doit6HomcHecnI3FEqd+oCNm8nU1PX1ytN9jONfB03sTbPSwsg/DuwlPD6SqCKKIQJcMMRO23q1hJZPeXhn3aC2RVuPzeMNzk2ovqfyGD/jomy3ZJCoBGA7rhXajmWUOZf4Rsmox/2Vs/JyNNaLaN8QfgAWz1xY86+NsHjjI++jeXoBZu9gJal9H5/BvzOYAb67hPftkLlCnQnUcf+zWk2D7lFX3657lJd76dwVjxuphDgffI0ZDn+1gFIh9m/1JcsXU7qZMso+kVjkYuJ5kzb+iK+ZuFN4OGwxFuNT12jXHObkHphWThU1xc7JZ5DkbNxcca+MFNlP5eoGYdprXhtO/0R/44RNYra8e/OfCIIeaDbQv6/8okhJ4Qj19g4+aVNfQfMFpNev6XeQgbha7L2DWvprNbcPiDF8pkwcbH8c385CUL3C6tppGC/z2xmc3I+A5bd7t4+ppT2RMXfNAY5+srLnCsxc8lEVfcvNiH01GMg/P9qqYZEWv/DdeLbE1/mq4msmJhh6ZadkiTAjf1ME0Pm/ajJr9O7heFcI+vj7WXqBPuMOzdVVFuZWSqYpSk2d1rU7YT0RmrQ8bsvncvtGTZo5l5uCwd4DuwET7GHKA397Z18u1nCDNdXAJlufyVmnXrYYMAa0El9NHMufj4j7n6CYMtsVcLXV0bx76gslyLg9MEC2HnFMjrjNOn8q3VORkvNfR9vSUVYg9xGcvv32SFgX92jtRFmdNxGwecOqtMnXIqYoaOcZhTZ5ZJkjwhdAEboh18YozN8j8CB3cDvYzNyiamGPnIFcntmvw71zo9g3HDEzcZPBK5L4ayg0Sa35fPLdLeb6Qm6nvm88eJBYGe2RuyOK39nJvj6irIoOgLl5JNykx5Xkx1MNNHP/NmnJLJ5YKTcwpvOeqi37fTp0Abtrg2B80EHJ44P5Kbb9/+e433mbP293zVntu0v/sq7ng5TaIFfHsec/2m8yx9XPtqKuNkmd3jLvtDuYuoI4fMHG4zCLvt7jNW20GDp6sGSXIGY7UOZpdoDXcepjH6IoYrXOW6JqqTYbWmh/ecG3QY2r3bfxZw+hcPqTkGs1eEw/OkeS8M4S/SRBn/ls9TvwghpeKUBY0p98Hnzhv1v/sf53HTTPXBTfnv/7yi5+//OtfX37Jry8kCeGO/dsGXmvR8H1+CMP/CsDNOAnUlTOv5P+QX6/g068zuhKe/QedSjhk4Rr/znnOkLlXhk7o55o0sHp2CqSwWt7Hw899b2Jq9/oyLjFon/ww9zrodckaVvhHFLOsYzFUz7SpKg6ucoo1hg588mOBazxzpv7hJ1mGGPaC77HP2hW9ie/oNvZy6OPhD8xEKx6+Z1RDDeSDZsdfYuPDdkfm+SCOIdfEiwKb9akjmMVqj39zaGctE2SZsZAvh8fnc0txxAcy/Vm8nJ+FLNFEJeYk0tQ0nZ6ewleaFrW1W88Q9FqbQDnRyse/T1CmHDuxfosYCk66Zj8RsD06EItee4nIt73tlTX55SEyfvpkrEvprEnzjS+a2svNEba3ps1VTzUvpnuJbSMJxps1HyONhbofWEAOYwH6cQJexqOvNbUfBifXR+4acyTfPXaFobGs9+vJELFTdwK3rltzhVcrJZYdPdh2Tzor4yBcVONJMrZBhHr3vbzkb2bOG2sO8u1eEZ7hXqlndVGmpPLIFOxyEsPcXu4i/tYwviBWE5C1fswkNHvQ+Vs5TQpW+iPCMhU0SRCT9UexU8CKtOixmfQ4yr3imh55tYN1vA2Ybwjr4nzQg0NjRzz5KH9RbcxuLRtOHa3BJk5w0beRT5ZSU3dnw8Ai7Ce+zNRizukRq0F6tr+YAieWqEZG236XHUsxvUjJBY74rW/7p/nDB5qRozmaxXittw+FFc18vwE7t79QjAbpMudMyBIWHHsVuZ/4xAOrZmCMvcBvLTEO4VIuZq8NpICx9gGtDx3YHQEeHdOr4wtAXoDW0Jjm2syyeGjK6fs1d6az04/9CCWuaqteUPc6qJ/arXnO5YhvNMPB8AzUOavtMV78tYmbOYiuJy6c/oBijcYZTkJ1tBNdnutQY/xC2PdFFUdsH/tr3z7vufqqGJ3V9Vy/4UOS9kcHU3rDyRHD6c+YJqP5NQWPrTHNhX3zvvO9BlZn84HI2LxPTs2ylw/F7p0Bk4Hk+wQn0/b7sz/A1WfCLMxlsbjsA9S9HlP/PPaRQSxxiakKzh3tjcwxrP3yvnu8qHIcBqM2Ur6tX63RwtuvubkZgvZwItDEdJ4IIHevY/IoH7fqsk9zszauo/iogY8b85y5we3OJgW2L9yEtQ3e1EzPyaempjObrzgmCZrPXp+kITEmp9SVP07/5Q/eGfBHPrmRy40xA07/e7XkWZ4+QTO82iPIeoNHK3Wi2h8uoD/+/SGDNVBAUNtnC4olfztOnt/yA4i/ZQ0RKvhdeZKD3zpwM3jbPPm00xf+gUuv+JeFunlVGByEnnMwDlstzghhbB5rjtFrcJ2FyC15vFNSPSwaOOvqItzch78KzNXmnhvNm6KCxg1RqBNHjZn37eRzc55e8AMQ/gifN+y5aSaAufogNSU9GSU5c1PMK+bf5+8P/JE+/fAjr5bvK95ciuRqH7kW/vgtPTect5v3hy/cnP/j//7fL//657++/Jo/APj779lMvJOYfHzuDfm+Ss6Zzx9//OnL3/7+9y9ff+YdImj5Se4hiYbkyg9wqN/DyHeJmEx8+qA9h+drESf71+uh/eOHFUgjvj9EypprZvSShR9a8IMErnfj4cxYLlf2JRbjqgMJ+JRCwDNDw8YL0j+QBLXP0Rot+/i3DPJNvo21puE4vFkjZ68TFa8YdU4AuuADTz6X1Vd+SHAWz4klvOrUbNDMMncZjidGZw7WvrFzJr+8Ji/yrQMLOYfOiXUJjXUcGwOWiJ6nOyw23+u19onIHm8PYIC3/TOgGnXU2ShgFTAyDg7/7uWK3Gurj58kyEcuWjlmX+A5eeNpJX/tEZbVQA8ZYptYbg67T5tbfpHkPwxquLkePvK4N7UZ7+GzX1vTQdFvr6lqUKAaq5TjalLF5JAaHwCG9XT91jclt+btBUY+ErO1EI8Z+tvrS+3sAB6tCCB2uSFw9LzXtwkBmrgIQ8lZa87hHR58zq13EJ6KgcYRm7Im7pCN29NiJ6j4FwDH7F/Map4+32sMBx8kzJxPpyVf7bH+dQyXAeqUSNxedxQxlLHHzwBWepftzdP7QiaunPf9gvvkCfcIOEVKOkkkmaYyF2u+RLYpK9LGJYz1t6Nst4mkbdxu2MZMXk+SHb6ags8XBGOQTt5GbD02fbS4MSQ9UTvfc2tb7ZQJfHN6XmjOb7PpyYkzQkAJluNs4FEdf4c93bk5LqZ5cGJjxSl9zL/1NST+TNYG/kPXoxEc0Y7VFb89kiyePE/wASAP6AuVfXJrVFIywjcNq8pS45COGPym5GDAgPYk8vZRPjMereY51O2BCPjzj4/dhz03b/NjE5f8y2W/qB3DcJgiS03BUhNjz84T0xyXE+7lwwcjJMYtv4jaccO6McW+WaguiJFWwuKNtKdm+dhrfER2T5gmg/nDNbrbC11RQE4w14+l9kwcU8fEGwHe62NqHRwna/omzgSJqWJAO9v8zYEVSxVkdXqNqXtVreAbK9yI5t5163z5F59zPrYvq4S47dHnfHKxGSNwe9hc32qRvHoLmLDmR/fGXw2j4vSlnPbyCGxyj09fZE3ct3v2dgPM5h1JnrZezrwNuv8PeG5gecI+OTyDzrpB5GJEyZpctz3icMVHOegV143TyM0swxurPKbv7/MCWRs31dyceaOTV9F3bJ29zsZOviNmEudUL3WhIzdKuTnnZg1h7Ud1UOMwWbe++eLzq25rHxHUxE0Pr+jujaI3jrzCy+Mnhfw/Rt+hwA1iKhjdhc8eukAN/vaa834SVHb+4JsEJ9PWsMUcqoMYPI6pqVxmi2ne1h28PThxhcunrtZfje2z+uLrdQM+amhGxuZgrv05T7T90J9Do3LmlXN6msS+rTw35ryS/Vtujs8PROLbdzHQm619d9R3Y3zlXSFcW3/mRplfdZgb6YD3HQ/e0GZPid9fCWh9/YHAf/9///3ln//477xy/ot7jqa/DmzJnGTsEmf2hB8M/Pn3r1/+9h//yxvzH378Ob5ci3kHBQD0f+VaCp56rcNaGm8miDKcT518nbbv0My1kjN18kOM9iz9yg8UsBHM1xUxXIf04vfv+fUPfmhAT3hnQa+vzUw+n3cl/0iIBa9KnOGA0xjS5Lp8sTDWfzn2+0fIZrQW7VqGb/SgiyFvpnsdaVyPkCD4QMcTw/7jmJN0wFmD63nmuT7EEcIgOPXdGrKegO1DuYrTZT8a7nGS7U2dtIek+eSv0Livus1/2ep7EOobFmPxOZDKInpMF/5qwFSUP7AHks+th9iuqabY7hn29Cs8PneiL/Gb20TCtZhTjx0p7qnv5JPLJA0Gw4OAYcuPKxEGzbVStMdmSMjhL2Yh1VcKbO1Vz6cPTdi8YHiOIzaHp04VZf3Xa7jyOBJJjqonHOGl7gxUcLnWPvadEvMJN/bjm6D+sU+pAro1Hn7qh2MhcJBX0lbt+vRp/OAXO7GacqCKDupi1X/MXSWudF3PQpQW/MNwTuipkJg63yxgmVdZI95+winh8NqjiaEG/RPv9UCuo6C51LM9iKnKRyf48Rk5gtAj9+RVGTj5WY1iw7s3hFbP6pKxciYO/f4OOhQ2O6T42LRTjHMBJtQedr94R2DjMQKZYsKFe33bVGQ4toDg10bTjP/2vIAEMi0vx6zIN18w8sIXczGjZeIaHZ+5wVD1Q25QDhsP0b8b2kfr+E9fyBz/1uKS7+88GXzo9gIhv2njw915Z6uN/SDWGPPhaQ6/4egk5nKcfdAqazi2H9WIq5yb2ST9ooVzB9+YvnlgWK7d5T3LRH8de3654jB9bUU8vWTvhXRvTh+tmNBEEHRq2ZqHg2thtFejYAqtfeOSBA+j+fZcXNXRr645+wRjawvPJ6ZccF5PEQCtI0+GlBHM4jjvAO2+YmCxmlmrZPhw8iFm9zSQrRu4dU4P0S4hZjSkmsFujCE5XF3BdIFro533az9O8k8eF5ietT0LCJodSs5ir59JqLu+opm/A7nbu+asd3nsr7laKRV3tA5wx4Tj9OASL1e7AGg5mGMNq/WxsFjt3TO81HWjiV8G4X2eLyYbYCyYrfj2a/LUUU7STcRfT93T8wQLHflUz/DfdaPrK8avba/NJhSbJ+y5LZDHvHVZPwzt52qHZ64xwVkHTy8U0ZTOX66KTFxyL19vUHszQRXcpGwXwfyZVxN//z031bl5+H6fxPDYJFkTMXc3TpGd7GOJ2JhWszdEEcbNGKMvWFY8vWkcN3K5YfJxkI00Q7NundHHjSJvWed3zL1p9FVddAdEU1Aa3OrjBw3cqPFWaD7R4g8feBwLqpqI4ZVPElV3/ziZlQQlq2dmO/rq+WdvrDnXHjEwiUfX0acj5ikqLvMOtO9OuBj+4B0cwN2rTOgTw5o5j25t6MtHv16rwHcy8NOSGax3EAsvUvc66U1z8uRG/bdzw9lXz+8r62gYLUic3tNbbjh/yDfk/spG10okV7Doh+e8dd4LAl/+HkFuYKH67bdfv/zzv//hjTl/kX9rpS7q29YmKuvYMJtkzsH9/T/+55f/9V//+8v/+M///PLTzz/59nb5d+/zNxLQ+PV3do2vk2hCS0apJlHpTVMn6Xbf+aHPH74FH2vfkt9X+b9+/fHLjz99/+Xnv/1tfigQIrnb83TPa5F3BXizfjgBha3wTNFhiTPrHJHo0BewuBuU+PiCsQr84qVuDPmw+TWXs7Hw/TVmMv5b33QpYdVQTWNVwuivkHlobh6LjAYGWY3dmJhd+9wOHyBJMpl6TxzOjovI2jQSZYHn5tl+kMPc9uhWenpXEqPVIMvg3h7HvrUv90DVTZ/hlGP3w55jntrlGI3xiY2vysu28/GefQZ062gesHDAz5DPSWbDq230TMJT64knBo3o5Zx/q8p46XOYevbrVD2aGwdNCKDwunM1vHyNey1yRo8q0GyGk9NexV8rckYXzM5NAbWjSAUO18znuhf06Nnabs/IxGfjOO2qGnLUNf5BLo9PRdB7wulf6zo56JtNSd1bT/D2T74GL2dMisBKp+i7j5GhWUy/noUJh1e8cqfH5FLN8rcU9N1RvdViNveHelaf+85avoncmuSvzSyDad7NovAmDyv5y9VqFI4tn14b4WDsWr1jMxbcBp3zchLXHD/c4gMfYZIaFC+NhfglBzfFFUsqMGq6B1WhssnOVrQ6cY1vqHmwTq4bVz859yKqRQqn5p9la8JM3iRb7WqGf4DPaevBJHy0Gy/F1gCiTugcD+/JKcrA6dVCp5/4J64xu24lh9pcEaxhupU4L77p69FhzskzGrfYzYF3Nbpr25uGtXh1tUl7pA+nRxODqOVVWQ7gWkHnm795Y5vCXhwYzR95J/PJRWx7508XRy88rSgcme41hIodq42183WMVjkS6w9C1PKpjkq2TjkeTVJVQmuIgaVDQZmtLhxb454BZu7X3uJVGaU8sZON7LeehrRy5q2/SFZXffv6alcb+snpk3IiWCKy8/KRv5zE4NqzqKcH8hvPHkwtopePc3tYy2iXsEmZLoZ5EQjITL1VVdQcA+yegb8xe516BpqxPVl9ra1ZP7/ga7vX0cb3zPHbXiynGuhDEMV0bi2pwRbFI57zUNoBS8UW6zrGz3pzdraO57wA+/XYE7muPY+Q0MaHLhKYs4m4seu9al49Cx8YnuRzc8MQOrzVUw57fB+gF3jEELca2FKIuAaXn/N+gkQDMA7b48V7M5ibJf/LtBAtb3vb1HAxNi/79WIAACAASURBVG+FVz12vNTEW5m/yy8h57YtlrkBmq+N/uE50OBToU/yL6dsOcDx2y/vq5P9P895JZbeVcqqDFPyfs9bmvNW4h9/+imfuUnP2d9ZTl28zZgauUH7w7dNJ1aS9CVaNi831vyjbv1zb6tfzaje0a9B9wmu2av9+gIHtzzwzdjemyOIvu26b7NHY+uL/X0HRPjdI+iCYSg/tOSHa2/Mc8ubX/Uuxly5OT657F244vfxCl4/uTnPD0PmRtp3LSS/N9XpSX+AQc7iyW/O5OWP8f2Qt5b/+NPPvmJMzxfnfoWTmrj594bfdWzR4B8QzBPnf/7jH/khTP4gXGzeRHNzk4/7mEp/s6ajTJMXTs68Sv33//gfX/7zf/+fL//zv/7ry09zg+y7OKDhp/kJypvwxf6RH0j5ancuTT30xL0LeIb7dubEZq+tobX8+gvX9df8IODnLz/+/Pdcaz/6gwpy/v9sneuCHLexpEmJomTZXp8f+/4PuceSKYqXje+LTKB6ZMxMFZCXyMgE+oKu7h5e7LI2yYE5pI8vtfySdwZ4AV3sRiEqD02MnMv0nvExvZK7/mQbw6NLX3+wMmcJa5vTywDZvT3j0IhwJTiY+mXsY8Loa1WoYzMMjPcWJ2M4CYbzjunOj/pCDvBG4by3sQthPReHcyk3RManDff1JM5yNrfBWFmBJClEeQ1/JDiJH439WydtR3/ixLYZxM75iMH4A2fcAF0dMsIUnCOCzgnW5DoYc64NXvXdcxGuzLgvvrrModaicOC2J8/0M0ZknLHuKVLxnkJqNQ0n2kKhEGtsgl864GD4yA3DR34LtTlYn6njrgUQ1kc8YRsU/4Yg9qyBCFj/yhPLiySJ21jrUX9x9QwQcY9v0Qhti7yPZ42DzDmbmOaorIeNQtCNvPzwpd8z+ubAeQiEVnMxj8zZ3p41eR6mloA867XonDf+umGnfnzMO8r64LCMhpt1gQ+tc9n6xiO/7TcKGPZqHHVR11uHGlXHPJlD/YpFv3wMTf57Gyu6UXJIa1WZxzwjiRtgiNMdDo7lQTA7EywWjiNvQGiOLDBb9CUFkHaJsbp9Dld/LJrdJoVkvFbVMZkdLti0lf30H4XZyS1uWFIQb8zNBWLakIHYoOcnBJezqGs3Nnhjx3BfdbSGOK3D9DlRIfTmvRjqayT/qQ/95lOddTCnYhS+/XIIl9XjMvlNhuVpNnreHkHyKIurieR08WrL8WIDbiZXZh1qax2T2+F/8jGAcoMFptUt72fdIWdNcUkz4uA4Fj9Kfn2ijAV/imovx8hILPOt7eGiaXV0wcOOoMJQARU5WI2oyKk/KC/fumiFPx5gpdXHTmNJozr0+BCzsccOBQ0z4IZXkRk+bj/6r63GYz7W8DFcDuJVvrnEsxyj03trsOeFxhAAfh85vtyONhb5GCy24uB7Zcx59fQSVYqQG3s6YpRTfSuDQNdMbW99cQKDLABMn2eOjGb4HPigNjHWD0/nMP6eH3kAKRxg2m0ODifP6pC0F5ut41B7cpeYWHjUQPvxFiVA4+r5zn1za6S1KI412biIaBnf28mtfuvMetKktnMsBJuI6PNknZx8wuumIBgx2PnbjDHKlqhgOlzIU9PQReXBNILCBjwHrpqzeQmAnMgFbhvH+1i1ExtNDKyAG6RuMHBCTmPeylXHCqarfsWDQ4wf85ZnMMDNtUrM0sBEwh+jNs5WNGI2bl9yFZUNG5ua8z/O0+eKpZyYi9l4ebV8vhCMzfnHX3726qn/g50XQYLJPHDu5pZiEJGCNb4djfLCiWeq1fXJGec17QiPSqwd2ECNknAt3azfGQsdI86tbVAyX3wGvptjNs7dpO/by3kHAVjY6zPnjce8sEnljw0i809t/MK2xKpvNor54ert4hCHHIhvDM7U2D84ZM6IG+747roxbqS8GMIG1U1qNue8zZ0XaKrPnLPeE4O3gX9x7njrfPrzB/6HvHDiWs2c4/s+a6Z1mYLlkgcJ+BPgbrXTyS9fNMg7JH7+5dd3//N//++7X//xj7y9/W/yoCY0eDeD9EfmCwqRct17a0GMtdyziRTGujEffDb+Sz47//HjL+9+TizXW67WM6Hc9sCxbvH7+qWVcJ1GzyaeL63jBaKvf34OJl+AFxK5rfQ5HIPxSW/bUCgd41wb6kIjT/tLfp3MCotoyRH/zDNi6xGZMbXHRhUOGByfPl7hFLk+Y/fgs/NmjLERR5fGdvz0H4PDJfgvrsTzrszAzSYGjGgJP+fhamIRAZI/sqvn8NW6UrT6Yzp2a4vZ6nSJwvploJ8OnTe6T9LHj84ks89rGSImzrbVMV75rWEcDFDrncMSXny8qEnO7c65jiuCi33Oclvzyo3g893qO58T37vR1hiv1uBJDPKrL652kz/YnY3aOR4dnCyKcMNW3cSBdcaotbU3eBFuLoi3bsXUDfQTG7l1iqRYKA+z6lBM/PQOiPRmfOJMzmLFwLoclsejHIWqzHlMrc98BmDrvdiX4DAOp3IGoz2Or8+pUD1wySO/2tGx39FioNw9ZLwx8bBVQacs4vXEhNk5jfU0TbZR7bw0rypXpi8+QIwrVBWZ56I358XYuTtuOgWG86MVMkdCiNfzB81G0MgEeDBIXwd8p5CyLDNDHBIQRhJdi1Syyk6M6peEAMl6InboGEnTuotoAkxyxO2kTFHwWB380kTZ2B0MKsoI+M2KaQxdRo9xmnjpE/qR8xJubcYWLBSx3cUiRvxuvtiSl4CX7/Bee9WDgscuFHkOHraimV96szKbS+NsXsD7pLUeGQxDacR24puiT5hkModiwdne2KIkk5WZ+0LFZscaadycz42LIfJtO5DE6MSpwarlGpsnjmvOesGIdAZcPpVpE/nOhVLs0u7adtickA/DrenmJH5Nrw1c4Z4Gqj3iKZnDDM5aij0UnvEXY93AkfNgK3+AHm7oiZfT4Q04/vl7iTEydPrkdDbhCgejwU8ODEnsPGnyAXIcctq6NAcM0Q1ZhumC4Z008uGMVTU5xeiIY4w9f1c4AnNLpjHeOcXswjbu1YsybEZXNrrdw6zzml9xWThuvGEG34eV/JGY3kMj32u484Zd2VS3c1fPWC3+QLnu6T+czDEC6y5e+uodpN7l+Fy/1jgw3PvhB+Rsk0khG5Bo+hw+sboZEj+GUgF/+zthg1MLMoxRbDD1oGO75LVvaUfnZp3A9vUoPpjgp7E56qYVvLEpeteBVpVvfXeuOJcXRjI7Pm7U0GfTxlZIbocL9vXkSjlPUGUTTmLzWeZ829z7vCX5u5v0vuhgvOEOvl9IxsY8Mfj7KRslNkxsFD/kc79u+Nigwy15ep4JcDNFnlM/c2fomLzSHv1mV/HzWN6VkAXrQm8OUSqbPmNKQO2JT5/6uynOCw9ujJ9nNuZ57PBt2GNLDVojriDnnQrWIbVI/4MpRp7aZZ8uD20T2DjEJJ5/s/k+9ShuN+sQZr3yWek3jfgREfdDPkrAl7Jx5ZwXQyI0QV6IYhPul7xxVT55uM7iy3x7JTl6ueTsxxB4QcG5eo3nnK9oYjNEjj1Xzv/xf/717u///Oe7n//GW8v7NUDE20a9vZqOgPWTky9mBENRJF/zFvuZOWU9RK9Ja/37b79ng/753T/++a93f/vH330hCO7WLJtu35kRTPKFn7VPvM5TPm6RGvHW+x9/zIZePfNR27JyNblu0M/qkQJ6tRHX6nmUZC3SJQ+0IqRjDfHz/ofOZGeM9r0/yJgo+of3NvNgIKio2ijSx3Tmth/9DREfCBRJHsJEhnh8N9cRzu2js8FjaO+rZmzQuZ8YYOGXR2S+cGzcCbwECLtcsHtwi2r4bAUQECxtuO4A27ftuck+uhOLuDN467zyFteQzkDMZ8YjK1fr9eB8xgTcWOe5ZrynBqiKNTWMfGuvbjCNEz61P1l03VDf2PGj3ZyvVbz6JGTmq/VEj98LV4TgcZ5WPovddBg9bTB94mxNkdG0HQ6MFxO0WrSHneMcOm/jq12EazydtW8NG2hjctvfubcukyuuW3+Irf2tBQyJ25y1P33ynpqNTKzYLzW8tpVXxx63ttZl8Md44zN02l0vRds8F1ebHMA8POnriBb5xCUmcltkj375gRObmatirmxjxPkFB/zVba9jwiyGmg3pIIcxdw0MX0S+xX2Xg4QEAgrOMRkCq8MJtJ3Ayt8UbJJ6KW68ShDM8gGpkehFpl/0iStRWA/W6Q4f7ri0YYOQtomt3zmDi3Minfgbta7qTje6nbiLwQKk5Xgmku7UAY5TK2waSYeMNhcY0Hq0Ry50xnfrjckT4+S2voR7ILW/HNGVwy40Y0L9RY795Qqrxud84/cBImyG9t64n/EXmVS2ZvbD93IYTgEyVjTlZTDz5YFKThMMC7DxuPEGE5utfw21fh7O/IAyNd7YxQy2ODEA7jjfuhwhjnUe29ost3X1DpBYh3C5H306LzkmvqYn54ym/+qTUeIvbwd4Jpa3G31AEk1XbR95I7w1kYX+xMPLpj09vCPnAWQwRMaWsU1C2o7ggR+EBy7RAvdgh77Q4DsPxEu/c4UuBqL37G0+48Nj0Vw3GvYgXrrb5NH5Er9wC6TVZiRPM0d918HKl2vHrVJ9ZQVp86wmQx+ACRi5uqnrct9YRwcdbPCoD8gWi4Lpx7h65wiDrXXOWNHsjYsY4mE68z0xtZ0HPjYRzkXGRPiefwMGIOvaWHN/i6v84ERfQaPgWadioG8jLnM9eHB1oHVMjqGlMkImvdhRx4+Ny64VGYVXtg21xz08dv00ZrkR5olvn/iA3rA+eWEzpPlcUW28hEeILbVJHDa33aSxweRKcDbZ+XKtjz+HQzaL+5bv/uusXDVObX/KFVxe+GBj3qvI2ThmIyRnKKa5gcqGbTdDrU5iQoC4OUNDXg/ukHa5RWedI3iq9TEA9eLKMQ5C4kB3BpUjY1rREJqN6rfZkPP28r26zLsE9io2nNjIeh6/Ak+gBknuyQNkxPnhTN50eLs7/uft5bNR90UL8g++uQBga23hKp6cV8e5+r4Qkn9jx6sBMeaHK+V8Ezs5fP7MN7H3bevWVnxyv+sLX+bxQ87M2cZstBKCQ5jot18sBwYvDPz6j3+++/u//o9XznmLP3LysbZZb2KyMc2aYDN9UvEdBl372LN2vPKdWHIly5nTr8nh9//997vf/ve3vBDwL2O53oLLnH3L5r4vQuy7RMo+QGHdIn7/zkc0ur5Zn8R7/6VzNtmNU+Jm0U3mR7adIgaTROA6luZlqF2jDrRzPXhnv3XXWn8PFp0IxK2/c6SkZvABwoZ7+nPKOT++Dgb+xMUwfXEGH93WdmgLJ7aRHQa7gYblU1P70csAI9Y5bWL74mlExY0BvwzwWy46cCDfzXvOg4Pf3gHQXV/ljKfhv5yPjTqCbnvUQlwiQy0D3Vs7pwlOcEjrPGjg+OZQ3hUODgPdJlaGxpicV71zW67l6LzgO7lrk77nrXfOJ6PYzpIC1jJRPfuxM68MgBRbzSMfx4Bo0BN50+PXmCCCiRzxjA2TA/x87KgOyMNw8kBCw7/HWjjOwfzQIgBSu3q99scAi0K+ztGzbrFZHpiSy1n7E6Nygg2YveZZSfvorQl+Ox/GQnNtFqWcb3zGyrYezg1xJw+UYCtCNvHS3edaOyfY0Vqz9nssyGstH3U2QFD2udvh0rjAvuQ2McSO7d4mGOPKVQ8h0tUX9jGS3jM/7M1zuMQpV9BbtDrGAiPRohnntaEYbVOUCUfYpkwAWo/4dwSh/I578TopxsJobNEJq2f64dINCN34YJc/oRrGcRPTCbDplNeO11zbDJYfxocHA9zhSz/N88ReGXLNqNW25TfjapaDUaOJFz7JoZKMAaJNF7+je2Beme7lbN2iwUn/4mK7dQZ6fVeObAOfOiyPaAZubOI1D2jH9pmDxvXgWOfJezDL5Sgvt+VsAg1XrrDDeUk9pcGe+E/E7UsgROAqq4lR/fLMmd/gYPfkd/uEL4t6Bc8nI+DmZ3zBhSU2vP2PO2H5ReD0IE9Df3CU7KFSjrRidf4Yr7wajq2JtwvqMDyuR1GWH/5iTB1WDgw+beCkN4SRtuI4be3JuTbqT1zRj7+jhQU0v86F9mMG/sjTtS0v/ZEc/Opde/h0mPPUGYo1l6vqCMSr5gad+Tw2w2/zZth8QWSe226szj06Y6q+ld/7uHGbk6Dpbx3rvdh7Jt8+0JeuVuQhi1jlt2tro4/dy5xVttx8jBkWMuZC3QYUu0rnYvMN3q1dzIkbW67y9UELjDx5z50COlquJ545lqecovR36hNjcXYDFjzygSsH51c/YrLW+OOOJ23iAMDmFx19ryyTUzY72gAmYDFw7ZOi2jOOs6dzGHvkaPxs9PAQ7vRn7oGKHflzzvbP+0c+x/7xlx/fff7jczZX3dR0A883dvffVvG58/3stee87Znm7cNzN6chjRDySO0TCxkcjWsaHpQowyZtqiqEpao4vrHPr3VDQb8OIy/+yqUQCzZ0bGJZA15tzuftz1u/s7FUpzGRy4Rh4G302axu7gh3jZF7r1gP74zZsK6cjXpBcgRoUHdpfOCf2W8gDDGhIYND4rLZ5XPnnYeuVd6yzccRmK9uzvk3aY21LwR1DXJFO/OX+WU++zl05pz1HFkCcaaRe6nkiGx4sY5//fs/3v2aK+d8pIE6mB9X7/Nt6nAgz3L9YD0+fOMt5n1nBbX7lrWTX3U+iSYafCeGlc/tibn4z38+xbZv6fcqfWyI8/3bvADBY1TLc86sf9q+CP89//MdHz56AF9ud9/9PgTNzqE5z238IT1deM48pGuOnMmffFGKkXrS6J82epOs6fCtDf7iIK27eIskzsRZO2PtHSM8YoQ9elrtHuNYoO+9A+eJja3yHE6LlWAIarcq84pIvXnRf1O3EonLRIF7fjaS8TLs40zxNy/qiB9hp2foo69qkAdTiLsWdDBaFJiMGaTPY9vU6cTDaQJqjj4d+ra1H8HWFwvt46zKGPGN/cDFvRbE3zw8R4zNkWW0fTS7rnZ9HMypt/EW22DEzW8U1RUb/q6XPWvb4J25+jUTrNs024Hnicga33oMT3gTG4yNtfkuBHi0rVhZXvvDuWb3aLipR6StLBQWsabL37phF30xqWuipW7rvTW9fKsrUq2U5KFr70vQiWHYYh8GGGN75gbBNOIO19ZG5CivXMvYgKenKmLUVhl9hyTDbw6DOwlmfW91ApT+8n2uq3qW+cEIR6EhIiZjJG2W7looXPtznmI0x+EXSz4xlVHghpzjE0SshlqkWwYcwyeJzAPV0lyZN+gt8Kz8Z7Lah9iSarSN2cV3C4Wh7IZB+w5gKL8tKpMD7m1j3VjhJI85Y7Xj46Tz4mowYIs8Z+zsNpo5rYnRUEeQX2LQzh0d+ogoEYfVazREVtYnmcIAJKacNQ5If2c0cSauXhPo+uiCxZt2CBlHcvg6f8kkfdGHA85iyn/5RWhSKifGRip3ojvv2AEoaM52assRMfWbqBgEGp9oHmd4tdX2bCSInoJfxMWMfX9HV++NA9r6PKOvHmcpnKjTiWPvlLQYrgesRnEEf5ulOlx27W6dXnHgQvMYx86nK+xgbr3OOjt245v4esQACXnSuzUjQps5+uJMq1HpRFicRcE4bTHf8liu2GxM+zOPq/c8T9YWA7uZkNNtNIYTd+KTh5Arz5la7Hxi74PB2DORg6BdA8Q6QuuiIP3FR5EA57aQ8RO75vjHm8CAZ3jX6OWykbHtA9R6gwhukZFaF+YSOefhvf21JBxtwsqVgTUhzuiKf+2MpVORGHvfzh5RtG6kyj6G7Ilj6lvh2UguNzDSjJfzM8eEd8PM1WXkmHrfhkNaN+TNj7wgyxlGcLFPnAD1BQPi65j/ZY5xMMcHPJtEiulb1Lduo5YuxKYRYzfWpp7NDPMjGRmXU82Zj47ZlGO3GyJyIbSbm3QW1xye61s+4c2ZFy18ASNv7d5NOhHwhwOAtOm7JqxOOVRZPabzkDkWuHGVls1WeLNJEw/cepILfw6JwTic9qMIvWp+397OPO6/JMPnuzyHy3KdM7F6BbqfPTcnIiUM80IubsypQX66aY9yeMDFTT4x/EMCV+aguWBKuD2jZy7ZXPKxgjOvyd3NOf/HPF/49senT+et+WyK9WNjmg5bcNZ4Ywc/ePSfDe6nneDk1Fr88uuv+bb2f+Zqdt7WnqvRNDbSXL3/nM+J81lxcocfb783d9ZdGrzfD5fWMF9qlxq9/55Nft7hcu+HyDt58e/T8rlz3q3hCwHUMi9G8JZ2X5gRtXUju2VOHXdsDRMfPObYq/nWfPKO/K0fsPDbWqDXGj+UaUagKNvsdwbjqMUTY83gxe/R1fSqo8R9I6Hehs9tq7nn9SFA+9XJNY7P85AwR+SrA//gPPLbKGvHWS/JZpQzflRTnuPgOJYdcry2IIyE7q2JowFIn3lYTGdrVD0RF5zGZ8BDVcPUQv3ym7MhMKOmkdGwE4mHAO6jGaqe+Gj1tzP2jT2mnMQbCmMDUjGOfySV4kDfaD2r2CRQ3rWosYdyXp3e3BeTS07Foz/IkesxY9f25gIeStzhaZfjCEfWccQ1bNlSbCwxPTFrMXZGxcKGDTE2Dn6nMRc0ZTnwK358uA+JWt61Okcxyc+Jr79IJ9fIIii84AzF51wu7WmILk0bOxDBamTpt63F6KhnRE88TJdffahXjHTVWNzVNUZrRMyzPgN81k7k2knDw/BJ7NRJn1gQAu36GVfLwSI8MUbGadF67vHe9kJ7QTG2fwWLX3bFIhN++0iE02lDIk963pI4zIOtLlG3EIQr9JKZcJuIfEocnIi1hxw/OzkvOItYYxy0bZzBUjic0y9ng6GJ/bJ6jOJqHLlt7IfvcYohYWaSQaCNqFyCAb1O7mDkWdFrPnUypgiDkb4T91Sgdzw5aTAy61Dj4i+X2M4NcXlIEhZwyw+cGdCv14RhvKI9axvxI29o7HrArA0W05Mb/ck9CmN75zdGWo++gFJZTmBtTPOIoLorBwkeNJ6YHHslwO0NrDZINq3yrpwj48Uf95xaI3C0iZF7j70TxwvHKKeqdZ152vV3KhO7csIp/TecibGtFkI/eA3/41fr5d06ybRrKXYb27hT52KX+PrioFwS9ROPEME5Ld3F7Ca+o2I++8N9aoH/2ttfuRxbRo8v40hid+pEoacd3sjgDq/hiQ4m12bwBwsIkLDSBghHrS/KEzdzvfPY0LUkJnbVgVaM2hB95wqs4iVEWmuER/nVF82OkdyYi4VzfZ+2hdz4mmCWB9r2O4c3BjpbavWc30lHijWp3rqOi/YRtMxGjiZjNm3p7efUv8WGty3TnBPq7qC1wJ9NmBvzeeKPnbgQmVZ+qUpkiD1H9z7YrVVlcHCDLrfwBsi3Hc/mU7zIAEGXs5vzjTPnaNSPSfk4mI0dfvnCuKQr1Kll2ODrpm37cHzEczNIDvwgz59nY8c7v27CB5QrqG6gEn/P3vlAMX/glKC96aNDS+v5xsBnpRrIQUlMa7e+5DPrd0zxZo6+fe287WZ8zzt/5Ikn/mxpDy45O24sXhjA1iuy8yIBmYDDW82Zz9YgG/VcsQ+czRrnNsk39uPfUvYM/jbkTJ2iOcsgm3M2mDpGSRy+0I+N7O///u3dpz8++dZ2vsRNfjNP2/+ez8h3g96Ybs7NLbEMWAYbmpG1yZnXjniL+C9/+zVXzrM5Tx8evA39z1w1/y1vRf/8R99aTwx5kniIU0dfDCBvxuTOHy+ycOYFqRju/M+qUObHJqLjBRW+4C3vyQ8nXpyJTzhDe5+Yg3La6iO4ttjDaeLxgOiwnujkCkip13aekyCrquuLfrku8/qLo+E4UAS7zXHzM6pUqr9yjItVGOJhE7nckRL7HquuT20xqA9o2Pb84ADcoBhvbA5WxsfT0I24SK1lLMJL7A3CuMFEaBQBrH9jZjyvumG6rREWaM/R4q7R8l+PnJNn7+vBZBjLEFh7OuhVjhuMWycVBa+7/V0LncviGSfYR9YA5j+wrUMGYqO3EBNDTuOkZb2uZDhrvlIgxn+CvGCPTovH5mzzW67oX/JlvLlQv8M1nfzWj4q1Tp41iuPQ6bDzgdC619lodLElbnEyXme6achP2zzhI+HLBayBe4MXDOqKMoetle4H70R4scFl2dHD/OWLtTOWH2C54zrrfJicmuh3Y4P1tm0sELdtjRnfGk2tHrmghRw2w8haP/1HlfvT8qgt5q0NUa2RNYkWSOPuOaOhdtaFoMU4DsOjdZnZwzV4Zf7IZYMEuBt0Iw41+3EU8EGCoJIkcME4W+yIbFOclgMb2hQuPdxNVvlgABIbfu7EXZ8u3nXec7msZ4sZHzgPB0Ksrzyiu1zpEfXRLApSePZ8jJ5jrhqteuK5AOkvXDpuTBBoOw6H2ywa9dHFdyy035H8iX384NzxbnwKMXmjW/uLKKuthQOD4Um4+DquK7JzgyKUWcXK/O68YAcvbDnb0l/uK14/9MqsX+wzWE47b/C4tS9u/XE2wjkYcepy6jTaE3vHOWO/cYx9bpCjxPZNDESHp7rmj514URNbzuTDWJ+rZ0jbvJarfvvAMLU4ueIwAZaS82CMKAzywIxg5xH7UYMifyTqJ0H7yzsmYPOD/NYIxc5RWchBjOlRaMx2/geFmi3v1btORg6/y3FsD/F2jGC+InBowzEmT55i5VAf1I1+5qYuA5BTbHc+VsgdNLw3FzFfsnj4VIl57EFoxBF7Z4+r0lIpLg7bpv7HBxTUCKLrbfDak9vJS4wYSoBBeaPfqVioIkSOGcr4qCNf2o4drD7R6pAzG1s2BDzW8i+/eAtwuCCnz4uRNRZhDzxgs4kgMDTZHPD5Za8MMsbQc+wYBAOY/u0VbPKRiBthweLUjfZUhM1+ttDv2Qzkl7eZc2XRKznEt0YlRHIJZgAAIABJREFUARKhlBmyckRoyrN9RUjHf6H6Iggo/CV39fAGS5F5M17uezaAIWM4trsR57xXz/vCQ7BsZc2RhhvHyd4RfX7F94T+NlUZXp+uJY8BhJ9rB99xsxYZOV9oqXOEvsCyRm64xyHrqXmymWXDfimx8TS6t7HMEe/THlJ83pwrx7yVmjN/ZVEDN/V54cXNMleRjbnrg9jY5diTrn2ydWXwqn/jcnWZOFy1/py4nFnjP+T/gr/3RZ6Z10kCXz5zzgZ+284pdbpVW23P1Au7jz//cj4HzpjbDVfveXHg39mgs4nuxpzPnCd2as3V9S8/5O3l1vWd31mwMamBb8HPCw0/5MUD3t3A3LuWEhq+vIuDOH98+k98qV8UqZHrFXrp73q4KfCSm0azDigqWi2MkUGHqGaWW/uxycCakLvzHbmQo8ctbdebHOqAmRqZGRrfmYvVeQOspTlHDkadcwaLv/iNlZ5Q3XyRGx/iynFJJ02fdBlR75VXt55jN/7Gir/zjaEoIqQGF1vVBCxSJA17uBozwp1raQ03jYfT5gLmxt2c7nh4Drq5pf9itzVYXMaDKVXli/Mg2zvC2ua4fLbqt1LjG9dBDuFywHn9BPJAHf8ql2YUmwMI1H1ccmrELegw3ZKpN29543UjCxN3H4cGR22JXOjxIbRt52V43LVSbKB8ni7OcI0j7rjs4x4JKzP2GAyPa4y8gTc8UWjmlf6NnzqN0UbVlkHkx3+U10+4OYzxijZX/Bdc3a7Vorr2SC5D1/D4GUrIYY3+wVl98JpLg56+fkNEP/o3e0bazjy8Yl1n5aWJy5Rz1tTmFyPrMSDLce8LGI8K9iRJ8PYXG4PgMeR53NoTc/uefVxsPF3wWAyMY+0GXago6hwCExTrQ2wT0PEFRaBOcuUcmwbIYwtRAohdXKEO5YxiuhOsP66PuI0RCOyA0je9J6YFmTsAjLCMHhhzGT4tCBganbgYihsDuNPfc7q1ExbdtlgJOL6Kwb0W27e26FFrAmgFWsM1P+vZ9Ad3hbjCcx4AK87YOgxuTq2PHRwmXGtBEfE7PpqVs/HFWpLDPg5iRqyNvONYNxGsg6JVKtamfMc3SGc+YwJG84ZVBhN/RuVajX1cyMn5mTN+re/kOvbaBq+V3TrV11jzgIHFWrUugwMJmnH0kJ/rEFmwzWXP8E9bjHVvTqrESjAKCuzckBHUt1ZPnGrIgQe4bfDtbzksQi2a8WKCtpzwPyjT6f1uBhKaE0/sHpTEwDlCp4guLjxJzLlQW0WU4BSgugimTls3zwQRsLZdC7ovaHmoBimdmgJojBt79OPO6TDa2OrqB2lvT5EZ9xljZdpfKnClurSlsefyqIPzA+qpz1jltPnXkvHlUcbRjKz12PmcfA20MtYz9h6znnKmy/pEnuPOA6PtLwenqAvg8hgs/ye3G6dsdLJRwZermW4qeat6xn/mKt2PfEka90nxY5PQwkgiG6JsimaDzsa9m9DYRI0/PPYPX/q0yuzEdGSxx5/G5gQ5IyobVTjmLzIzByebL5qYMcCGBn9kxOdPMszV2qwhtjikwQBcOdPHxifh4EcQPiJl4AsUHU0e8WMdiJsztsYKP8X7DdkiBKyN0bNXDpWSOxH7gu3aCXcHx9uK1H795knCrhdfSFsdOVCfyUnu0VGFbpSDR7Ehj626dIPJj7wip1n7OW9ZWaJ8hpoNKlezfWs26yk/uwY+8CG8/LrpTCy/rExeYLIGic1vDuIHM6JdfkjlGlv65MDa6ee+/3j3KRvYz1m7vq3cuWgubMa7PvJt+3xJ2uTU3IhEnF5Zj4dNfHoQmAZfvq2f/3HP/xsnPrcDrpr/5/e+tR7sH/KiEg3M1irvKkhdjJdk2JDbp578kg9/JJor6dTMKqCLDM75p2h90SNfCvfhp9Ru6gUE1s6PZ13DLVCZD98dEx58Zn/fyt91OtzwD0DvYpprowenUBA8uZjTzA9R4942NgiKQga0MIvAPvXID1xvjFqvT/O48XA+MQVpgCI0ljUmiNgTi8LQlN8zUmNM4XYtv9qtVbAIJ7lwH5KDDHr0NeAsp7HfPLUlB2zzI+MFjfBpN/DA1jJ+4/FiV1IiK3/lnghZlzoCtPnbDd7GHuRTW8Zja33wPcGrc/jkBBZmEm9fgcLOId1mf+GIue1Fd7Cbd/MsAscJ1/kLOXEMS76pJLAZN6f2Kbz5RG8sx6C1k5tRbigZDX0w1t56IPfODZ90ox8kxxs+4lMuFY0WmQC1TXc57DyINyBg1DBH48x4UMa7dZga6lrzp+s65vyIP3bLiXpuzPLBbSXx1GDX4K6dsdHMbMo1WNqD4DwCThIbrbZ7G8IJCLT0bnxkgqinezfGEw/Z+KEnBnj6jdyohEdadU05Sqvr56GadVzOG/zltiTCHsKlCSjoY21DbUByMreG7Aa9JPF5JYbkFI4BbYyVTyFLvmqOcNijyTqqtIt5YGbBVIOsqd+YzaaEq2v4LWz0FjoBOGe4HmBtorABesfY8Gcjh/BwPGch02/EXQhFxqe9ap8VrzxYufHyYPrUGV/M8ZPv8ZDKRhgL/eWyucSgNuEcxc7B8wwQ/jTzPXEqx5bWxQ3XjNdBDXkX+8UOH32fxmVjHO+tOhamzuaw87k8wac2IOHBn7US2hGS0w7XSPRVQ1TGw7coB9cc0Jl/DB+wW5fyEkwu7fV46sRwfbeWGYsR1daq1MtlEDo/DGauNme8/KWeMx/6bEEYTMzFRbR1kOzoW3uVmNw2XI9PNLoQEqvMuzpjtpaIjUcnzTVsp1XfmjR+yaoJIOFoYue4cWtVxT6gYfSMc3BTC/zRrf+OI6pi6mXcGDZ+o0oi3c5NlM/aDifnfOcDWW6nyiaAvHRlLtvgcjhOvw/sV46tXCnE4RDhURRrmGoN9zfq5i1SfTcudhi/PBkYGeatVwRbw+GBSdvNp3WaOY99a3nXwKkb9QsOUGwQ2GQXNgITycY4Ap7U72bpa94O3U08dPPD/WDOQPm/s7M58v5W6PSzmfAtzOQWLDf2Eu7cvORF2KzbrYmb9Cwqv/UbOX+5gv79ezZCbrCKCWk2Qd3UwycNQml9i3lxScofuI2JVyUzRs6v7yYgH34Sr8Kug+XOGT15+b+9c85wNjQiE9o8ig9WHjSQ5cf5MFz68eWHWANDUjhjHEzs0+7BNeLYHFWIqw++a49/bIwHWEGU0UW3tU6nFvBJLXM9WZ3zE09zBosN47SJtMPQnk0obIjN5twNes9s0MsndU492CS/56p2YrL+WFfUk40m/OT9Nkiiuam86ei/63NzYvP7R761/XM+A04sePCiEw2b/qux2QQnPvnxt/mawNRya+Q8WSVAhOq/02NznppBlfXDBv1TvsTtt3//2xclPkaPvTn7Vvxy4HbCOxaWny9OzEc9TI+54A/eud15ZSsKPrPuYku8/h/0r+8+BssZfNQLX7nHB13nov/7nZj8j/f3+QI+54r1CQZnKv/AIVPGYHm/mLH9c+7tRZca4iJeYR76YMuzFgWm37A4qemxa0B7Ym8+sQAXee8v6/bCmVwGqTMzI3DGH3X5zTk62uZmP4f19zwOniagNYlg/f7bGaxtRAFrY09xIxRkeGO9keMxuvWiilQADPHk3hFj2tHF11ohHDupx3CrhIq2EUXFLzaL0zi1K870dYxVjJs7HjcmI1v02xfrYYMeGW1zvP2r2douTutSjuWcvrzjY66veFdmoFnPxReTAzwtUG02JnIs93lyaxq2xMtPOU0/g72txOXohIWaMoM1FlxHXuPqju9ywgbbgFOn9I6/4skdTqMFIq38sDcQRHA4bfGedijXZmblxQeI2IsF30IybA7VI9e7JkFsLOS0VrUujVIO1Wni4ZlrpQEE83AoV8OsTPXmgNf2dUQwksSMaqVibBLmF8NX5eT9yh+b+hZXF3BHvrlihe7lM+i3MDW7QEv6sB13xtVxBHIDrEcXwYYrWXH1qz1j7BsfspEIcPGiblO3UcBNe8EaTBTcqfMEkcnAjmN/6zNY1Vwu2Dcfnc6TI0GiKNaDQwUjj54xnB74l0P8RgWSN6aGyWiAMj79wfI0dpjtwvc8fvqMIdnQ9okdXI4tNtOs9eKJQ16tVxGCEVvs6l/y94oNtg2qPclhzyH9asCYOahaTA5ngwQHfOKBLb4dbVyHOaiVDzcYOHlndPjFxLqvPWewEiDy3nlWdHm/yQGXbQ8sY0WOiDaoJ0dksMdAWmNjHZThMRlg5ojE6+MwUuTN8mEDbn9rH5va0RkM/ZA/xlPHqF7a5gDmX9swiC89EA+fE8tMG9rNQ320PuD13WHnFbjJd2LDd/Hx2DqPt3krj9WN0mKUH9o0c2391mn5PxzFP/cxUBklHO46X89IrUPG+V1u2r7h//RdzHIqvcCL0djlb/TBbcQ1qs9iKp38mhuSprw2+I93FVqMLJPgfUHuDzeHh3EsH7Mwc3xyzNhNmVfggG5N6pO72Hh75Q05m9bYs5lBH0d2Hjmxwekmn43A3ezUnhz2D8bEsx6T0IyywWkMSuEXl7lhaLrgLrdvuaropi5xgWDDXr7EQ+Bvu4AhAnv7jJMLP/yyYdnm/42eAfbyzBhuDNCzIeubtYnbDSxnSksuIoO5MUdeLPhs/vTxu7cRYxZIbuU4dhAYzvihK6YgHDp+8K5VNHLRRCtrUVgI5JcrtnnhITI+lw0nmudnX6kuUmnAw8K69hsMaviNbwvPVV6upNMIyfrwqnHcdh5ZQ5WBtbEbn9LTpMGB/IbTaDwxj7wowpk1y5qhYetG1xqkauPv1e2JC/hEjUMCbpzoiWdTvNzyFsVcyfbz4NikgcuLA1w9/5QvpqP5DfnfeFt6r7AT5MDBM/Zf4s8GHR21IRp8/TiHV9BVyYkXMXizvC8+JQaftzefYW9QEAgCUBrfM/DlT67sf373+2//jiSB3vNvA/uFdFG3WdPrBwCqfT7QUU2Vi7N6/PInRmww0N9OcerqserOI/MDdi1r1Nl4rO+IV/ZqlyjUdLCxAcn1EaF9dFt0OCsFbxv1qM1ZV7GvvrxAnd+azotqOkbVeGXBUbjH+XJCW8x0YieyS+6O0BTL3omlQw9Rn9xmrT7j2p+5sG4h5G0+Xizvxspp+jfe1M/8W4Grw69RGnJrFLTDQcDJ6+orJeq0dHyOl+HKRM5AnhkUEy2ZXqwoBGk+aze4Dzwk/+22YRx0GKTtmmmf41q8ckND7D4OMqjdy5qZOqBFXfa6DRf6yx+bZTFnIbs+ahWbienjpvi4Fbz5xWT2Qi0muvHGTkwITZe5FWdrurYxWBzxI+dsItjsOF1G8Bqs5SNXZDXJub3y7NpqdqCh60iKA+98DC6hnfvhe/C1xUuIHO4sGlHekemnOkBqTOe4oVrswUAntZy2vvCgDQKKCvYYjN6ugK+OI9A4cWF3nVeff7OGbG5wqx0Zw95AOllvC23BY0srqTupxYVI8Q80AgdQeOAiTrt+TGB/liyjZ9Id49XojuWMXaRbeExoNbOgDlNA6TCYyZbTmMrF6i0rDC/HjkYwSGvpeSaoMoI3npAzWs43r1gfg/RxtmH50CFbXaFF3wUgBvEn52LkqG14qBpOg/OoRjnEaOd8+Wk6eYEp/5yRP3NxnDx28TKuzdZgSONHvsE855KMBp+7Rjqu/Vl7cQVJ//REh19+F08LjRRjbXma09S10ok8XJBBumC9cZ2c4gdtHhjPZqK5PblcDsPzkWtri/ze/sw3EfFD3/AkU3/TeOqkhxWacJkzYmRTkdMrvijRi37sSKjzVf21ArfWW3fSeLinW6z1idZmPO/0isGduxhbt+gup8HgAYBm/jd2pTkyvxtIIhkis5UJaiQ1S0/1rc7NMwoxosNmcQyj05mLfRJKmOIuXu3EBKvDsRo+yHGK7tSQQeTX744XAxej6Fvggal8DJHRrq4j6VDH/O1aXNYYFxFb6lxv1/TqEGE1D1xaXCeUluy5Wc62IUTYzHVTnh2Fm7of82jD/8/O0NtNrg+m39eI4Sa/xHJzbyDLI3dC+je5uNHKrsFNMQoSTdsrjl7FzxrzhYAE3PwbA/PaX0y8WyfTnf55opW4vjhAHbHMecqFJS6uHzZH6ucJ8/dw5P6BsxyjBMfoOeC5T5zsQyNa+XI7iK3YSMPZuJgQ/03r/FW4PoyOZTq94h6c8cXHCOPQskx8BhCdWnFybhSGNy++DNLWE4flyRmfpbrceTc3V+B9oYZ6YRek3XiC+tyII+ePK9zEZNNc4ENNDEDAscX2beMJkPxNni+i6ybddznE2BdhuEof/OaaDXauRu+Xx7mBf4ASa+uomERxnEYs3yaeHOmTPyZ8m/qn//zuCwRs3q1L5PvCFTw+xIeGTnleSOAFBbgis96J1fgknj/Ac2o+Wa9wzx+b7i/5t3hwuI9VMR836oCvL1q4bjM3vMMgV/k/5D8TnJrnhZQYToo4O5xTmcCZNqrp7BretTb8Y4fX2nYVnIyiiObArjwyxJPr3i+tIZHA4w+PdQe7LJDVxjqObU7TiwfOHBID/13PDOQoqJoxU1CfuO0V1NJvLDHhLMLaZ5g2SB1w3Lwnx/K8/Dc31wDmAejngre+RBFI7q6LCamP/eE1cquSvn7Ep2VcdY8nbqQXZwxzetZYBPAml80B68pQjo91QaOoMRty4ldTVlHE3nmQkEH62B0z3HaOdp7xfjuXxcI41kDm5/KKdjiJpbb6rrvRG39iDo6xCisX+GDRGA7EfsGNWD6konXOj5rgpZ4jnfzt2m2+WKShM2DXbc3vutkaaBO+Lxg8Rr3N+YVDa741IpTtxaa8VlU9tIKd+xX5jfL4ZzxsVb/MA5L8boiNLYQqlIw8zCmyNI8jrkTxm8PURmpgrcPUxjlFWR1aPERXVPvi97hcxqrxMoD7S73LcHIHLDYvj/fllk94tXPOxiRYSoVT6Uhemwi3UBu0LErNJ7nxOomYUIDAJVEbwJBCSHfkg91ElpcmEnmboJM5ag3oG6q4DMuVHuEei0zBesV+FmiZPHjKcblcLREYcd4FBuR60l8WWyeqYqpgirtWwRdwPI6u/Ms7uqmZprimyWHsL7soHhgvrCLXXywhYNWOx3LYWmn9wDq2T5f4sXmp7SMalPOD/HBLxzurYCoDGy75IyZtkKZPKpUryEFuY18+g8FpjGY/Ya7xiLwajsCV0410e2DEanmJMOOJTYiTK9wZx54ef7JN55nn6sG960HHHBrz5tlaFFnlHjBtI8jDQD5oJLDZNG8oLvbWq+5RjA630xD77G3zWq2ZxaX81l7MY1Ib8wQcucFuTs/b+1hbzwux0omQBO4DVnTCjjXzZJAJ46g6jzm09mPfYowH+Bhw5pQO8HNHufPUXGoxKONy1xXaq3vM8cQD46+tHltPR8SPz1kv2z/uGliPruHmt9hgOB/D8MSN274d+viNU+11dM1uSZwn/PjxyTmxsEsUn9NHzgPv5MYmvV+kFUQ3A2wI2GhEnn9dhdlPH9lwfHGzQXjyjBVdYe/a6JhstvklaomxGwk2FsbXgJjULcSmZt9mMyeHyPZqKHo3alQq8HDgj5Ldt7wHh4aMHK3B2IGfnz7Wled+VhfNyQFsxuB4aIyOVaKJEVbgqHG8vFAzP1qURjmPvHq9a6Mc6W34n/hwT7zFLL/oM02VlzP2W1ty+555pA7wcoMc+MOXPrcZWhPxIsuO8QHPOib2bp354jVy//jxJ9cEeHybu1fq02eT3re5h23ic4XZzeJsXsE/HMjJ+X/IRk+O5LLfNIyf8x15ebcmkIc+64s42+76ubKj207OxawAXvzvdDjzzhFrayG6flmnHRIRX76kjherysn5IacY4esLT7zd3Y+ZRKuzZbVfO6EAMy9eXODz7/28/ed8WV0221t9H5xiytyEgi8+ZcnD9ed82zyfkeeFgU/5F3Rc6ed/v//44Yd3PwfPL7QbP3jKeUNzdg3MPKQfOua6a835gGNM+fuvbfJDZ+1iicgagzdOnTHGKpVO+LFJ/eZnuWK9fq/9W+/F90wCade/I4Wjow9m7xPqvTGOvAnECizaItYSWXMdXQSNPNj6o6Ot5tkv/6fKesXEcuLy5JsxtwlbDNrNODYjNUzX2nKc3MDJr7e5uavcO0SzajKxeda6qDufxg1OEa/drnntwsvINTImddPJXNL33DQ4Yt/KXtmzh24zFJYD1MCZGitHpm7QJs7OkfcpuV1Yt9gaV/86EgWAxmqQvd3uvMRgYmLVWrxyrwwkSaYDhvw4PzgRri/UaFzzmV/9Y+v92hAWowmOQ7E7iBb7o88YB2KMtbnE5owjd+58vFwstEGhLtPOvIpfIVa1XKucJ95kGzrwJ2eotb/RRc9BeRzBAhHfrasR4BHfbfXzqDoB5rEi5+WneVkUCwIZH6z4Czu4cGz4xsZuuDQudrXVDuHDv7Jy9/KF7iZcS0kQRAwOTfIEIUGDoon3gO8k3CI1SMk0rLFANHkciemBzi1K+uA9i9S0r+0zNhhbsBMJ+CkyXo2d3oWQv8Oxk8PDoKaLXU7YiEUd7G99GBhUXI20qP04iY4/7cRGMDUN6bEBa4x88kE9p00cfKjlMjkGFVgTa5Dx1nOC3hiATi64SQVRfjbeyiVk7OphU5t7XNuzjrCQI3itFdbaTR63D+Ji0hsOE9Ngw9WICxSArcL1ry/Y1KDyOGRhdy0p6mHqSOSTtz7Y489p2beP3LzUXaxzO0AU3ex16epCR9frouGZn7WrtXwAWh9vO6wHn3Q++I49sGuLX7lLRcWUwpirW4UZrgGEp7UmRd36oO7tKxziY013nvRrbLrcl+BN7j04ck0ikSQIEV+s9tVHtxxebIpaWGDyJzIH82gcfPlldOZn8nQsr+hS1zEd5DjQErS8OlSUw9ai0sbq8cYBD7A5aborqfexjGKAzdTRMfhbV73BKQ9AyrvrQmeFOUxeRDQmBUPckT3GlXIsMzdkFaI2djsO3GDJBw4VVc0gaF6hy+dWuYLHE30/M8xG3fhfszmvzVfezpwn//Acaj0ndjdMwoopt8j94qpsnLo53y+cS0aJ3Vpmw+NuAzccOGezx084sKn8xiYvm6YfstHQL8U/pYo5ua2gdX+VUZrDN3iMe+D1XUfqzTdDY+csFfCxT/O8gUcpWmSI8ZfLYNRrQjVMRWAvTlC7HirziXN04DaXOt7+2rMqEhQenBafcfpg8rVtnJlf+0SP/syVtomEvU4YvDbi7sbeF1oy5v+NyzOovGgD/g95OzYbeV4okWs2yp0/1lH0rq1ulG+dSlqOG3bzYOwdcNYH3NKISa/rdQyt43Vqvv1itq7l8sCivHobyABIClV0xsKkXmzOeRGCNmbkztVpatEXJsj9q1fqwSV3PHyhCKjgcrv0xxekshviOxb4MRY8NDSM/ErSjTSbbf6l2+d8a/yfOX9MjacM2uPKHxt/8+I2kpg///Leb5r/9KlX+vms/i+/fHz3r//5n3c///CLeZlm3Q/kiR/JPj6xLghDLluvF9/IHcdo7cwNn0XGIPl6mpgpkrlYI3TgALDtLz5VUjHjrd3zPDGYT+ItXHnM6C+64R0cLMQ29mvOr7l33ja/Z20unWjFKeqtSS12zMiYOTuHGa1Oqisf3tjbDtHxM9ggJXeatZ16VdOa0Pe+ImZy17o+krEbK37THw3GGTNi/da364Q5ERUyvW/Rbzw5RT0nbcDafNUN5xp1PTTwYMBRm606w+pO/RcDwKGDW/HtKTYPwPsbxfA//lunib1Y0SOxrukjfrZaX/m6rc3Tr7lLQbX3pXubAJm7yQmPAfPV6Jp76G3hrpe1x+4lFuNgyX09T66AF5vKuoy02WiXBPlYfXKf+cP0JU/NLyd0tUiMqVllgyUrjYpz6kp2Nw7xmH/il1l1ekZOEz/3zbWLYHw2qd6/TPT44HW5gIAvv8SpbvuVIosGpSFzmP7yUqxvHiPrjEOD4YU9BLdpM1XfAhW8Flf2X3wiqjS4doIOtniNKWFCEjty8SS9nuTQ/majLdJgaQqVl4LFgjDIp8ggOMbUfidqJw7t4h7Q4wDYxHtzxtYcYgIfmm6MD+/I1MUSZfraOGBcGSf41DaDKF7s0eMJdv7KmLOKyvFxXDv7+oBVD31RYCKvwZUI8nJYPgSzH4fWnDx0JlJ0aNvgd8aDfdBzB7JP7MhRrMVpAHOAl21geyeO5JBu//CanCf2sqk1xwFPV37DC42YjJfHWI9G1/XBpFBwP2ww3QgnJ00nHtrWK4aRTXj99rB13drhTxPHTliYWA6cNVCANq3yVakO4cUx6MN87cxb91qaqwEETW+coj68wc3gAdf4iYZ014brbR40hrA+p9TB0HYFT0B0sD9BJWmayqGrLqP132wX51JPeB3e4DVHQNE+Y+3tQr/hAByxhaJ/uMU7v+ujfDh5Gr+c0kApMfGklaplIIdj01gOB2vxkW3/6XMxBC2eHK1YAyROo2+8nbPK60mA6DM4tvQz8EqopDJmbtOoP/+iis1MX6WfDTsPdmHBxop/28zmg/6P2ZTAHy0H4sDCX/nSLTabcjfo8eGL6thMsKmBR+MTi40kGMyNSHOWsJ9BZ+NBLGDtsvnLuOGCKwJj1mTP2OPydNy15hkleIlPd2WMvJqPlDRyGtPHOZI8ieo8xmh4mTfGtgqf72hZDcSNY4CRbpypIaDkskFlydhnaxBrM9w9xB4+XRc4k5d7u7/I8dexcQZPqYErgI6f3SdkzL0qn+5P+YiDZjFgA0kcPgbxPp/J3g29NcWNGocEYx9DxIJbdII0FgEYtq5wS0XxmT9fCHCt7vxTo9pR0/rh3yvpqOCLH21v23jcNomNQJ/hiog5BZe/vhhRPtwW/A8HWc9+1p7bSdZ3zB3rGx9uA7xj5EcxymvxgtQr4PEhLmMgNjMUAAAgAElEQVTmjz5vof/5b7+8+/bb7/nCuM++KEKc5ggf8iy+MgHI9cdccf8hG/qf5f5rYvMlfl9ym/slOmx9ZwExJ+d0W0dAj+z2CaZKBw6jOybBHL89L86e8Yfi4miXAWc5cR5jl2r66LTjmF/tAmK+Y838M8YX27WpGvmiRj9d6iwGhMZie9podz07L5pq7ZozkYlH7EkOL7A2rGPjRDSPp4t3eEf/9OlgZECdOk0cyTaZ9WtcR0S/PDtQQpcqPa06KdWUc3Anl7W2VpPQ8cUst2u5IXTXzxlexwqBokrKGait1/q1JuO78ymPQTMGWTLeHDLqr5JqU3+4aL98Gk+uANjaAcnaJVZziQQVEGDPPC+gNipjg465g2+7B5nwi32EdkqsuASJUOfaY7IxUb1tYMZi6jBrDe5ZW9b04dA0bn6qiCXXiS1SERdbJg0jv+WjIyAAp2kPDJgVyH3zRsoUtp7paJaD9vBKy6G9DYho8sJfG4zqX45A6I22GLsWtz7Rd41FL4iHNV+rcEM+upzkWsiHLfqJF1x6YMPh1mBs5Ln/B91ECq4bym3i5SBahY9uBFuE+OTXYBN0C4jXFhtk4bWtHL3FHFKM9c3YxW1wbAwxBcNjY1+cWgEQX4Lh9JgEhjRUHiLYScLeQlG8yLXh6GDO+A3IFrZnFNdnuZ07EMlMLLFnwdfNI7DnxoH98k7/xoDVEKArYz21XwztM4AHv+etTIPpExzccUgr6iwUBCsf3ruQUOxciqtnHZYZLl2wBp4HlAK2HhNgcoRr29b9ke/mPjzqGQ4rP57NgaFlsZOe0IN/FLHZ2NhjFpN7B1D89cWbnO8DCUCR8juYF7q6ztfY1Tr4BImMU2S0dMV2npSM7oWfqzLG639xdRGkMrq0xe0Iwc7tnT9RoQNumpwSV+57PpqxGf5ykTmxXudDnMN1ailOD9beeLHEOLbl+zBSopGh8Ln1w37zGN4CBCzn5UMf/HtnqdIp4GBonuyk9Yg5Us4P+aM+V0qsjE6dEpXheHvC2HrBtbyAfVlH2Ez++hD5xCuacmWwA2DmqA5VR/6wlsjARN7oD/Pbjeq5Vr1dzRNA3KD3dO/ckWs0Wfw7lxi5oaKubEzi5re7ZwfaK5VcvQ5vNjm45u23boCGSfHmKp7EZ1OSzRo4XlVlk5Krj2xg2MTt5lyee0PMwLVCjeTet0p79TWx4cLncn2b7sRmXfGlcnlsrs/KzSIozGFaV9wqyTN/DJPS9KzV9onJWqwRlrtm55y4awvMWRcM0uDPX6N3oH2hoot/+n2MHOOcFFrD+iNKscXRJ6Dgvm03VrXFT8QEUMLcUtesD79JXQAIDMepE/RoG8M1krnzhZt5GQU+XRd8U23+Z3fe5k7zxRi5Yw9S10H7pJZ5yibWlr6z7HlITBJ49oWiIMxt/EvWDTWGGLHJgTMb5NOAYd7YnM96cT2nT+zlRMbWx6oGkvoSdJu2HfhCTV5w0DR2XkFHz5PBfDEbvq7/mLffWoFPPdxQk8PY8Xb0HyYncmnKwSK16OSBMLV2o81VdF7cygsgfBEcObfFJ3kSwxe78EUhN/5V24d3v/zj73mbfD8nr11wuJ1/DxZ8aD2SXgtgjdBl2Ho9jdZ6eS+CxgrNQWf8yCe6iTUhlFEf0Bp14zcHo4yfVOAMlj/lU9yJPzpsDuBQnROGo6rE6FKDY/N5sT0xq+MIfHHG4SW35Ti5kNg4bG2XnyqyP3hjCx5CTqcxnszJM7x0pR8bILYWxlnh+mvAoDhw4mfnBTXvZgCX+1J1mquh95d2NfTiNwU8uJMAfMx5EGr9gDMe4+bCuTY5kjOD2NAXh64/xSjXJMwvtoOjG31lSKelQ3k2Dj3w9DOHWm6s1ZsfVuFiTiJii28RPRPwiYM26uVhHHCWEcppi8Zwa6ZaPNHRWI79uBveMt5DBPrOGd6MW6fomGfw8ics+eSOZ2PvPMLBNormPbGiaFyDjmF1yGm3RoQaaQOq1chD6/l8oftgjN8zNnV0HKNSw7q9/XjA5gy8c4tPfrqnQYp9eV1seEx7Uw9s2obr+CtDhxo+1FKhA8X7DT1jOwb6LKiqo6cjCIcADvYjAOCaa3kmNsJOXpSn0NgNRmQl2KmZKGot0kGLPxD+bCAWSLmX23BYtb5ro0XtH3qYkE/bcFieex4tBHYhblw8y7MYJ9fI1Ym9rPGq3U4e9nsjfMrsO3HDH/pxFRM+jqvrMP2xX7U2DNJZvg5L4fDenEQnZxy1KVskzN3hd4HtDZzQ41jbOLY2Awk/azpygCcOcvnvOXLjyrx2HS9mox78sVucIdOTcxA/Y09O08d/4y4+pE5OcmSNTQ3xi7a2OY6+sh1vrKolMYCcwAJNn+GhzfZzvncotTTMsNo8pIJM+yKD2T88aMM7vZPV4VwuanbtTK3AnHCtz+CIiGrtjNDx8tJPf7gUprodcYZE8nzhgjxNYS3OmHiRYw7+iXXirI6YEOTEmc50OS/O40kUdrsGVGPXSOntbcDIxy6K4YCthCYmIbM+zp01SNHPk6MnrhhGoAdOj0TcfnNAORy16ZjcxMM4fTNVNnpsm3453aH2qmNPMOpCTTf2YmFjrefsE3r4xfbkSD9/cGBDgO9+mzSbKm3RT/uebwuTcjYI1Cp7hTzJi7ubj2AH4OuXz2K5SZ+NOX026NvYUBk2go2BzE0Ym6zEZlPO/6L+kLcd0+/Vv9aKq/N9cpmNWbC3lerly5iROZod+ba0mzcWMwPaYrb21ENMOjR9mbtiCKnRYGqUPnOT5hxj5JpakDHa0wETXinucFheRepozQ0xfHAilrlFga/+TBDy+QZ3GRR8bOq57ME+jQ0um3PeRkETs13nh6u6P/VLBPfdEXezXrvlsWcwrNlCxiylsZXvcGdNRcHn2b98ad18kYENRX6oL28pP/EsBmBs5HnhqWuJNeL/EieCNtTFcOLQE8856giQwgUsv7vJxXHfRYCBb33P2oP3vmjAu01Yp85/bJ78eDLJRt3GeXhU8DzmLfNZ8x9//vndp9x+/syXxfE/0anF4pl/dJyt7bj3NvPTu4+//Ox8yTM2cP3z3ads+D+XW+xPvZumCFLCnhEUIyhNjo21Sq00XJtYkBcNXnaobhv2xKw/J2xHhgm++dXG4cVqhOqRlg22OKal4+Pu4Bl1uTwY1DRO47c+YnDYkCsgwGxk0ZlDnOs+INru/S9n4KtzfuyPFHF4GSbY6h2UEt1bp9qBVZzFndqOnx7pL5uK46ss0nQMC8+Jra3CiUGesTe2HDQWtLboQdbp2o7f0Wk2/KLTVz/w2hh2ji/es15Y1a/29mU28ooTsmtna3P86p0j+JsTo6lDxPa3/rE5t4UGq947psllfQVsXHM2x5mfyRc+/NGea3mgg3TblUW6g6ibUwT5LRReGDSPizBu+lZ3fDFSji+cZqgzsrbaY0G7NaoWH0DQ9rxzBeDq9kUALWJKfWnW9Xg+sZZPPBY+di/cRQeHeueUdubJUWPQxe+0IVHYztWqfQ6p4QYdYGLkp/Evd3Jsix2/GSNxXh1XixR/ZsAviVO8vgyOcTppWyD6lSB8OEzG6AqO5e1LoqIch/gswIMTvIMNXpy2UEv4ibOc6jMFiZNjEo9xaR3UFgLcteNsrItWHZFu/OdE1Dx+NTHedC2Ocesc9IhyaIwbd2Nqhg0oB6TjZYQNGchr6kJiZ3IJqM3coMgpP9YujvXVxH6nvXXaGNjQuqCGSnBXXu1TXtTWCi2xGwtuHcw86zx9NyflxwTpE/vGnWiTz3KpezG1oAu3OF/+EaJUpgdGE7njjmImv4z2rAL+wVyZ5/jNeOvJmWaowXdUceSLE6PogXadgDO+R762yAtY+1gemwAsL3Leprl26OO+vDfmIsVw7+ywrB32ccJ2MIvHvAxLOoxOzOaC9PZQX072MxQbwzS5R7ZWh6fa4BuicRlgZ2j1AthTLshYPPrExWfPdV2Ust3bqrqp1SBJTuvIDwaYm4ixbg7tFV/78WtcibQbPzCwWYExHao88ZQTL7bWTAfyikxx+vppMtri43Pas79C1TkMPswfHrfmcPUHx8Y+XPB9NOWR7ZUYXnQg9Obqmaty+EThN6oH0yuWj406m3yhObhJzmYk/6IMPFs2DWwSuGLOn2+xzZW7bnLYzc8t8r2RrDefMSc/NlZ8Md3+mys+78yXZvm5eDl0g8K1RPaMls6cukmHku8IKBMNvCKbcfN312csb/dbe87xbQbRiD2yDgbx1hhB7akHvT3bFcNAHKLfOu/60ocXNerq2cqES6SOO5eN0gyAemA5h1oHZoHqvLS9ckqY2TRi5wsdD3MxCakT/repixxz5pCzayhnNpHKmJA0IcMfGZMzmVgLcA6HWSvG0/PmsDKeG2eLXXyDZpwXBIiytWTTSWPMZv1DvrBt80YOFhtnYyeEb5lXXp8aYwdIzuGFbeDmsXrmO3HIiXj9nPnkiF9ni05aMjbv1IqN++SJiZyZ79HXPnHIJzjqia0xV9HzbfJ5h8JHbkP5LPmfn4P3c14uyX8WCEpeBLv/bg5uXLGn8cKJL6yR9yO+fExUM+cKLp3ZqUFUvtBmXq0HNrfd2iMbszqPHTI9OGx8jNPM1ZgdKcRu8q9vOJ2N0aLlrI0e4tQX58khuIXCB/EA0x0bJdSADgf6mHO3BNeRdw1cXG0GD3PnKmfLCUz6OOPXmnasWI3A9hoD39ZyfbE4/uIcOlEUu3HhpbGx9GOc9sS48vSG1xiMZU6H73DJ+NYeRCINEqfTKnftAI98sCiT8xy/fQ4uAvq0rnO7TtF5pw/2/jQieNhuTRb/nOU1eOAWcqVFGk6qEt7cOOdv5xCdvsQaDE4bV+5rM/o7dwKNtCc5H0n1LxgZGD82jUF8GUz2OD+4YI8Ep2mnvsrqi9Wu88loHHsiaJ+PjL0k9jYTYPQ5dX6wra7WPRKB1jh229d3dZEH6NSPBWF75ETstMaIPLf3RsNVFh7bfavTFe/8DWZCnHhIZ92cOR4KW2/8jm9gOmfpAIkGtfDLKnGsVz01EqMONddBlVfQl0TtogQ1IM87WAuJbIpUuJSgnWGyvChNQy0toyFC7q+D2A3GxNTiGWOSwekmdvuCiVo8/GHBlZhWZxnE58WkxG/uV0lveaHfMbGGWhN1gGUtVokHXI0Q1dZMs/NAgxY/UWtLP5hbUtRFRxbpBtftEfdCHV8eJC73jXRjLaetKZobq/ZlFw7kksHmtb6Sf/DH3jvS2K9NMaiHyQHWdYXt8H7GRYjYXDFIzpu2dluf8cW0bJmFRlvV4j5MNF2ezX18NhbGu3HwwR2XZ21kZ62qia4Qhqm2jBBsLM9jsXlXjz9ey1qjg794SA/fZ41QWKDmr42iRMxvnyxM9LWbgr7Y4pO/xqBPzkA393LG4rUN8vgOxuJPTpuZWAINbvI+czQ+G6F5F33zdlRSxiPa6sBhvGsAlsWg0/XoePJBv2uU/j4BUO5hsIlkvYuBCmDnnFwgVRPtnjkyL+XAEUOOI8NHSZlfW4XHumujMjyY5bo1tmUTqPKNdOq69lPfxixS2eQIlyi2lmiXL7GKzBEjfvPT/anj6tMFBPsA+jbcnOnz90O+2MoPoIPiRmftW+f3fK6VSNQan2wU2ETxmVvegvxjbpN8wzf6iDwTizF/3TxlQ5GNHv8aig2JVwC5cp7NOX02gdjpExDvI90oATh/yEkjQ+Lsl7/1rkCGRDWnZutIe/Lft8kliPloA0XG3K/kflkZ4WKhD5stbQYXgyb5Gkdi0KcGAgCibWuP7OqIBAsS6mN5+VeOH9YbGCDGbQdddTGJsbH3XQvrYS0nHzEHp/B8Rjobcm7vw90z9mvHmdqPxH/9FRFzDxfzjS+59I+56Ya5Opj0BwjKIzbmifstL+Iw93yzf7n3ow+ssS/5xvL3+ax2N86pUZy3vq4r5sw1O7HDyKvfBomOusDfQ06sMYZwTQN386XPH/n5tvOsacfJM0s0yLwFPuu87200937bfWtAHbPCtRMzY/PNGuJHB+JSy5zJg8/+88IVt4nGJDYvevXt9bwbhRfA3IwHDJ+9nfCizOZBLkKH+76gQYZnraRnxqm3XDJwPJj6c0gjxpSn/sMZ3uAtbmM3gj5oVI4MW0TE9EnKsFm8oo9Pee06fA0EK1r849vHA7DwqXxmWRsowLUFmXwiImwd6ovNqR/rf4OOXSUboWegG79GgzS4E2PCiA0PmsFzZnyhquKYuVQ+9uaDiPslQtmaZdfSE2QMBrr2zDfyZzxkFSEH4YUjOqXVoiudwTpEWhmsG3nir+/mjEFkxsDk5PJYRyNrnsRrrK7BOIXkznKjPXwH31e+0ifE9YudCa5C49iUKyj2x4jUnr5Yl4u9HESv9yO/huCIRWw0k/RUI4q1Xz6jOUNM5LNROi7m7TNmdJrzkzwiOliqawOVE/s4VeYMhtfOv7YP/lunRXYOCgvAEy39WndmGAYt2KRtObTAhZozqJ6z8z7s1dXihNh5KnYAxUw8IWYMjjXu+DhPLOdRPYK09ImVm/xGU7y1CMpp9Pf2Tg3kM/E+dMHEIlYvzgTACMW0LqZXmUWK3sTJiCZR6Tm8pS2WD+abzLiIMH7GTf8QB5dM/9Ke7IbD2LSYf3Eo5orJefrNnfFKolC/+Q4f7eHTNKUWGV7ynV7rWiww8SZv2nJjtDVX/hgrH9trs1zwu/HrOwsTH2LxM+Q6XjnW6DRkIB+5kYAN79oz3Hm/PDQyBlbYHkL0rRsd2gaaM7oEbzWrXvzlqVsOzzqVWmPRP5viDFwas56W+WLs+cQMjacv+uI1grlknsqp3mAutz2r2UkYDGT6h4s8MmgOSINP3uhKGHNrYafh7fYgq8bFx1jlGpCXqq69OY5uIk58Q8c5Un9ziF1zbMVQkBttc4yJ9sqHH7jkgem1x+z6Y6Jrw6irBEWBxDkIeBhKv45GguEhgu/T/1pWHhZrb6eY+Dde7CM/eU8eKJUdXXFfZIMHInJaMYO96yViZdHXgnAT+THn1Q3GqsdhhsF5refWvIHXKk7pdtSjczcxxTD3Yi0mlmvnA683iGDJ0QiUbLhP7fqK5yjXFNJB03b9gjz18S24bBx+6Ntnv+dzuHyTulfm5kx9rBGc2WzQRgZ6tlPv8s7nyHJlO/IfuEIefDYUtF3zbMDpe8U8fTbqXAlk7FVz7nuJwV8aGF7FZLORuDyIyzt6NnDojDMx9OGQBgKUpLXnwd0aBy0a4ixHNlKzdlTVWzbQetqObyOAMvNnXWtsnIytXaE037jFu2vTACJhNnNKTGVYt0ntxF9pGLjGYdL6rKZYkUXPz0uD6uTMFWw2UI41Gu7pkxb1382rXyaX+rN+3ueb+Pk3Yd/zNmvQN4KxRkDfPOZ2CPy++wFsli73uW5Av845tqyP4vUjGYy9qi2nvsjEGjAzY/WFINcJMcgt5+WUbsezFhgEJTnM1fvo+fz5l/xxJdtNcvK0JuTLmmMzwUYd4uBRl7y4kK9vsLWe8ckP9XGdxqZF1EMd3kVIJ7g86JEfL1LxOfT+/ZnY7/w/6XqmRmHhF/TlZtb67IsNgwdm56mbe/xa/xMtcVszzgbARvWsY/RTz9Y3BuNu2tHpC7gNwRjgt0biIGhTtYPYUCttdz6wzw/o/MJ8sTYHtCeWfQ6kUVvtFluoMA2W6pq2j8wg9SOc2Np0tMcndimhgSJ8r1+fo7Uy8BD/UYsNJ63xPfUtsLhLUPyEKu7yLauthw4ReduVTfmU4fpgtZKGKPdB2XrJdfXxfdS02SbfeQxqlk/c4pvbA6do9YbCzgPYrDl5IEzze5hanBlX7qAGcSiI67XBVF8+5JzKk5P1yDn4Z/zwqR4ONMnosTHwsQ3pjbGsDn6tmhz98ZPHoMPKGOvcSCMrP1zXbrEZv8R94RLNUPTEIfebbfHjfifNWoPCcNUP3F2DR51OPXu8XIR7ZFTe8DuwmmSUYAdPzjvac2Ow8XV+wMCNu0JePx1/4Ip9uRQ544pqAM7kBM42ZequubrDKaPp6xZbAA+GYSYX+KGeuGB/OIYqWwiAatMx/ZVtsa4eGOwjEb22I4lm2pNwRPjsUT/1Fe3CPcgHN178ElwCtQDptOhdEMFbHHTEw2UxpVuQ4mHA37S3virhwQKVT5C0l4jqwyYiFkXbRDW/nYiLUaxYjr68Mk6MLvyxXT2mAG+M2BlBPQoakp46X3h0gVVXTrUhTm0d240+v3vHzcAoyIYHuT6xN48i9wjRrePSl/vGe2ARQ521Nbx0tqZyXILcMfikK3Zx0kZM4vK3PEentPm7NoiU38NND73aGw5gAevBlHSaCNFFtrG1Yy6QuUYKNYDSsoYKMIpnTpeDCNFGeFpixE7OYEdePuVB7DMHiuqrnfjpjf+J04IZ4WDHBuLOLTFmTDBjmFT7EhguSzNmaeMvhe3vGV8ax1sFRXOwjlqUM3zMbR6wNYu7ua0jPNMqm1pkcGzonJGDU2+oWNdhpiV52gbLOlRSW/rNaetprBx2Lmr9zLdxVv7fzotldQTEv1xOtTK0HhIHpfozV45hYWIBaG3OnIKY/BjvOR3pGDe9jdkcFazJjYeVC5cQxFq7sCvciYGODQpfwEZMN+d5wv8tG3U2C/Jgo57by17VTIcM1PGt6+95+3rObMzdQOWztL41PjZ+q3XehgsOzc04eF4p7+ds90ogVMlQRmczNJvz+Mvlv+Qm9kkMBPIXBlqbfs6pLSFoU4cVsKGhv7d3Y8XZLyIrsePSUAGIvGHKbTeDgPMklngba7kzrk978hvuK+e8awArG/nT4YCBp8bQLwdiliry27iKfdpwPuN0dv1ZH+4XUwqByGHrGtFeTfZLAHP/jo66gb8bVzekCx4o55Yx/JTDkd5NBHpIuE9uDrX5Me/YYD2xZnxBhnh50ccXbbiqzWZ9rjADDaL/BQCsFsKz0eJrTWPFC0r8+uR1zt+zhtHDn43x5z8+v/t//+9/AQqHvrD0Ay9eJd5XeOaPWNSEHF1ZIeDjypChnvsikqJg24YbJOTGIe3bN74hv//27ceY7sb+cz5HzhX0cxtkjnxgiz8fBXHc/ItUX/qF3nXS+eS2YX2GDnY7z0PFWiKPYlimHyUpEK/rWYs5oAgfDDbPVqV6HQF4+ixg5a6/o17OK1h8xrEfIOCwbD4FB0cTzhXNmHojuPyrfvWPgTY9EouUnOHBUXSgi1jZzT1jaU4e6fcuOThxePEBX3OZx60xdQf2rJfqEd3EOto5eVqcIPgb8zXPxiHytJm3xVCvDPKx4f6FU34405A4TgxfuHqzNszL+PjU9njlPsR5C04x0UdLTH/rE7fblmPOcvGhp6zqXKoAbLxzmxTFCDGKz2AVqH5oaWNlX/Sxha+3lfG3VusUQ+YWvPU/tYn/3saMZ4zmsPh3DRdQbOEedXjg7GxIUrtwc3ERixRjAfhpb8YGrt0zpzUfdedo8gdw7zexk2MMDTM1WTn8Tnz4rH3OzLQcldVja1uYrY2WGEC09bW6HSsHSH4lsrcvXWrgkajynFF9hlf8N379bg3N0XoSJp0052p45HXSBkZpiAxPP8b2jYy2AJJBNoCA0jRrd8YaUa7YVlG3S7iLLlKwHpNQkvhQuOqevAw28YE+sX0iAZ6eVcQOm7bpxcR81/lhAxZ/1wd65VxhJ/ZwxBf9I0InsgjWzW5RsaXVfrDG9ym/NYmUGPhsjQ7B08GoNpqXjzH2MHGt87FOx9b85jZ4CgAi7kJgV+p6wOWZCzao5Zkj4a4fOBnld2t1zgN6bGtZJIQAAUoj/2vYeiB/mGg29aJPq8twWG7WEtfmThzCnBqn7zjyzfXqOm9YuIYngnfY4MQR28bN2U7xHWBwYtmdA4bVeRw7Mqgm0siKWzsGz3lA2trO/CCIzfr7KrW5g/OYw+BqWrLyh1Rj0Ut72kz4Ab4c4v/2AbUUhsjkVz6LP2ATG+nyJSxieT9qo35qAXPGNM+Rt4ejtM2ncxUdfoCST4ZnfkUYLgP2jCsRsXGtnbU2aCOut5zAFnMM/gt/1TngJyd6w215ibW1gfPYdp7Xt5yaF7KtSWLzG/9jz4tcFYOEIwbp00AvFmfXyGBtzprGzCfkmI+gJWnc3ci7QcWEjXF2TFzJdPP1tX02IV7lDoafLRaOtyID26uWX3/MVcS8VV0s4g5HeLPBonmFdDB289bbI1pIxovNsiTT98o54+o9pWudENHYLOa0c3zihpubsVQn2zoxzZoSBr91AGAaJvzkTF7kQRxebKDRbweU3n40jBALzPCvHSD+1kXfi40QW1pRgzfj8ipOc4rFkAUGr73lCeBhgxWNTfP6ymmieIIaQJiWwskNef9GFb0miU89uLLMZpHz17wtm/uQbFnP5v1sSAen1BJI/uVWzsQpdusFJzabu0a6ufcjEPPCD99vwNVzNtH+ZbPOBhle5OpHHTZusJ2jsBefJ/JZw32eMnmzJMkPHmDElxcAivfu3W+///7uJz6K8eFbvi39oxtxct6NunVKFOJuLKLCxZpPbcnXNW0lZ+1Qj/i1tjGwNNS4G/58buTd17H59J9Pkfd/0nubObclNvO8uqFz8yRybM2HnAjOkU7uWLfWcNy266Rm8Gub8DsqRkbaX6kLH9wnJhiGfNoF0EpF+bR9xjeXoXZ4BMN+/IvZM9DKJ7a5xaBVXW+sGlfjIXWfDzTY5lR1fPO7Mgb8NKOnHOw06m89idz6uR7IV92rTyMWDVSa9maHPBZuPKvzqFOshsbGQadqQBuv9ZnQx2DnSJt1HO5PnSHMZ0BhlO5y5Eyb1Wvf+Yx453LPOG7fM766Fw1yRaO3fWwaW1m6y8Rgj4O8R3ue142e1IAhLk3eBBNvER1UR/yphw5jwqkce6wOZpVz/0ET+hGrFgmX26MfH4pNuTzcELEAACAASURBVGi5HrimhV1e3BAKDm9bRJsHqiKU4Fqf+umPbhnUnjHN46yviXi4P3GxFRuH4eQcRqgIg1gYZerWCCo8vHCOjfe/w15sZcN0nN9ilGOkLkK8wMkJUX4WR25vnBmqLxtcJvrjPBzEX/0YiomHjxU3FnClkyvoMomRRIkWTYMOioNKCNtpiS6/J7nx2EKDUW+OtXsm2wI8CMEm7Vnwi1GGL7yYMFvO/OremFpnvBYmGtsztp88yPPgIGw2wh7+zVd4APK3flgvX1TYaFczR/cGWRzDLTcGG8c+8EUqzvB72KjNDbK4J9AJjB82tD2LRa75qT6ajHeuliO6kw8momDWPK9dsbAAhtZYzdHx5CMK/W045Hcl5VTZEcqTGDEVv/31sv7q1kYjI+izsXK2ngeoUXeVrNmuy819E+9cgFEPvLcW+DouS6HEMe/hEwO5bv4mE9SV69XaiheFMceuvmpy2BynFouJOvanJoxBgdzW7tg2jzHRp9bFNnacLoeLgUUhowcPjv6Ob4djY4STJyOsjh99hNPsB5MHGhR7J7ts6xdjQ6108XreuTPOYbEzB+ZkZ20zHrjG6rj4UZjfnGK//I7+LW8wNRoFEPmB6da0GhM4MBe3MarFsllYD4ZP7KgWt9OwXhMRvsNfv1XjdR40wQzo1IL+rrWt7vIWCw7BURa30lnLjneTjr1vER7OpzSE84kEufaKOrb8Cyg2AW7O84TfjXo2OnCqHqD8RfRjrv5BhM+yDzy0lMkzPrTdSNG/duTPhiIe+eVKpRslJCHZ/GMt4a7FLQ+7OjbyNGTdDBUcqbHVlc3MxJFfFmNrGOaJK6PIpFTA9LfOEVRZyQRXCuuMNS639YtazPUtJUBVwFVf9NE5TlLmkPnZJ4OobWPTAetkfOJcLOrNswvgmNv87BVXbFXhZ6Uy5kUXXphA0Y0vvs5HNq/8H/Q/c0WXq+j79u8fs5n8EnllX999YB7FA4t80nImxdcW2UO4fdacPMKFK+gf883+bJR5UYAEXReJ8eXrl3c/fUOet9d//yV/Rvr/dL2LlizHrWTJp0hKmrtmTf//T87qeymKr7a9DXD3PFR7VUW4AwaDARH5iMysKnM2mdU6tWaS+w4fdVcPOr/mvMcXTvj3fKPW9pN/Z9ZPEPCH6Rhg+D10/uPAnptopQZfwBot9kGS2PO13NuP8ptWXu4EtHEc+Ev8/t0H3qnv/5/nWHJs+Bg8NZy/2YAmOp1gXrSQJPNWmSVPwCJOrVo5Lk+/Oo2HwRa8W+fTLSMbV4x4NycKgo/RnMNlWM9NNQY54ZE3+vZEUFM2fAcEztuB0nQ2mjqJyR5r+XYG+NYdCMvisu8Lu6yLpysQoPmMWWfn2F4INO7ysTRHbj5yS0eihDJ3D3dt2xucuBZIvUUxYdYh9yAXS9wey7cHxpsQwOXZnPptbJNZV4z6uY8w7WE2B7lIvxyzvFrXN00+51+EGwuLvKuefT1syeYxIM1waHOuYlHkJbL4Ht/O1xOu3K69nU8dFuS8+YqcbUz2VnFVIt4s48sx3edAC1tFrSZb7jZjpD/8MHbOi4r4uqnPOOVEa44FNfPwyonClxyZL5c2qk44WLmhnJJg3edMJxW1Kao442qJgbzZNduzx1alSWOeSaF95/IKlGR80UW+gM7ta3ohAF8GW3jALt/Wh7/ezrq9fVhv47I96ddSZbtCUWNqMYAe7zHBHMh6z+PF6PZcwjk9p4f8ML6zkC2QG9R/GpjBEJgvDhz7d7iOXT7IBw9GfGzuA7BpYnQ2ZsjKSskw/XXIP3nw7kGifGVu3PCzw2ROMK4f/U0optkCNpZ9Y2FGO6DWCZL17IJH8S6Z2WBjNJ+NJ3DsHDxxh7vpAJoD72A2WA3R1Fpi9XihCejWVB0bs3v90bl9JWZPAjCsO3YGDxqixqatt3686mSZ3GBbM8tqObUGuXlhKY6YycsdNuPhqd6au91+dXV6lOXyHU2TrdJW15OvHTPfxlZBdPbVo0mMVRZrwrh46s3CHXuPp3WvqYytycA6CMuyaujTzDWwqYU89CDEsTGeOmJf64kvaMKnV89xww3WYZ93Mfs4Teeyx+uTm46HN6DyVM8+qOzxMGb4a0N545qJ+OGfGuXLZntb9Y9eA2tt7hhsALxTMpjMOX6bd7FEwu0aTINnK7nBi9dy6qyfdOrWPsgHg99BTTx4B7J5RGtAG2PqP0HlxqPWbIE7gnnjscmrvTwCZr1B25eusw3JpuNc/eAfbYvtbS/ckBg6eXKN4YOLucIXTo8ZF3dV1XViWOfp/ry6D7Bcni/hZcXFEO8YfpMn/fB4oc4FuxcQuYBlj7bNk4lPMDRoZoYIM3qEOzU/8qmBC5mTl4s7ko8dODmqqHZJKzeG9ZdrL5C2N3ARqw7CM+kFaOPUhhA1Zkdea4pacoCfHNnNiI+LPHQFbw/iMQdcGa1reLPzoaBiBllcwY09molHM+EAzMFk+9DYzQstERwX0u/H7bff7svU+mGy3jnPeGaZc4Tgfnqix5s+8IIH5wEXpPyueS/S8242+AxycrHMBbQXzwgolbLUT+5OjGHaaJe1JZf6w8vFLhef/FV//v0YF+n//vcv/ZWJnIv2PIT+vjgvDmgbLuvqvFOOU9f2JsetxwxbfBzHnHLUs/p5kQANXfcFhx7P9CIvVHzLec8T9hD6YsK+iIW9qfTt/UwWPb/xrpamx3UHbv29+Kb3P/7001f/f/5IHrcR9PATdd4WyS3f0EaNx4u+lBZLBscjX5wH7HewdmRHLR3d42E2CF3lGC6EUldAq7kRBNXX6LLIY46JkxHoHA9zdT6u5jbw0cK6EoWZ31l5eREG/6k3gJNjc62+2TdFSbcP9kbKG89thJDWNTLgx5TwxpC8XOJKXsCaWY0ue7jx5Mv8Hqd7tKiB+4O3LhLX/hDDNVjJWBvlZBKEi1xqX4HhIA7S0f8Fawk+fO1NHzoUJ+b0MHw7pyqSo7f8r4ZS73Gq7lv79srHiITLkRCvLaBlPttzhpumFayvvauGo0vZU+notQcJ2muAIfe+gjTlYd9RfVn7Gl9fZBMH9/SrL/hq2PJxTleWh1juW3pfqBPxCVNTYR67MWqpr/1aTeOYiMRPbdvLdWxU0+zxgf326fSDIBOwaQRbBMn7VnNwujdwF57LDZWBabjbj1nUlO1H7SdHj/TqBtxaDBO1urBs/ew9X5OrVWSrVtOTrLEet8mRGEF7vHjsG1z+zZrsRu/BrnOC8EvWfZM2uk0TMGIqdAUZh2BDtzl7kLaAxmzu8l8eD+SqXR1NyTZAiukBdGm2zIKFi802TcusceEbVKJuvaulBMXAYcAaqYv4Ho342mxob73Mbo7NV2t1YTN3g4xuzYa6OfjJ8WptNriShwOszplXSbf481Wu9kssfYoGHPVd3JghawLUADJgcdSNbezyTC8Iw2deHcbuebO9h6+4xnkBQVhqKXa87MJpHTMHVj10ZRL6bBVB5A8w/F2N/FkZMbnx27pMOm9cGyvVaLz+PU88BQp5Yms4ee3Z1Ecu3c+WqbkbwfKcc9MHQtSGL1+tagK1Abi1Cj6o4PK954hRaipXIh1PtJH2b+IAnHOGecTM6TZYAbFXJVzFE9lBXsba9/hoN0yLOoM6eqHcGLugJhDbB0j9zmTzN2ZzakbTxMB3jiGiIGiiUrBukN4zF0aO8hvTlMWdhNWjK5tC6ixztTToEtxZPTY5ulbaWMPX201vI/Ankovok38nML7jC3vczTn27A53wnbedwg/uU7/uBCRJ+gIRYOcsXshwZP9PPm3pfSfYvLDk/0/AuZi4Jv4uWDnuPC7uX/ME4lerPZiwXdsk4hj6PFLlr39odMnWZQabt9hZJoHPC/SJye5+bjviAF9xqknGk4duT+5HbOqTzzFUgM16x40hgyfPOlwNVzE6HazrJ7jOPJNfi4qGdWCHQeWvDsbHxdU8jQxDrogRq5SaW8VekNTnq6gyDqjW6flwRYsHTdtw4qPHRpHnGeOAXtliPUaHSO9ZJGDRk388G55L8x/y4UyvxPdd5e9OM8cvB9751wJtsd4yDnvFIA+Fbpi014mJXnGyu9aw8u707/lIpm/kP5DLtK5QP8luSniXjj3HWPewf/jBy7c59MbUzct3xwUu/Vzvgasb/1bK+vv85b5j/xf8n/9q/X7bnmfPHOe+oJA9KJzn0z76xtZWwl5qYg0HH+rU4y9INcRI246ZO/bc29v6QEvTjDnI/68cLCx/Xj7NG0ysPqDY5Oc7fr0NfTN0JrhWP+8ciQRmCirRvY0LFi+8LE29jRyWYiaHOMr15tvuUeTEdmopYvNQ2+2zt53TIxaNrD5VooIk1YLhZwXg0+O+k4NsZdl96w6V4v3K1MzHsUkCXmIFJrFho++uqcGcBNQ2MRnYY0yCZK3b2i13/TBx2qKVOuC6WvTbi3LRS5tgVYewFiliCX7HU5PDyYgUcQx8MvBzEV9e5tR08S/MYBBXk2wkfvtCX6Q5RbLCyDcNs06PkJj0l8oC6wT7/Rs8MDwjkFr11+DEPrC0JTN0bNaJldzAm4w213Rj94njW96AnZ7xW1SbzbFs2qP7uMPTm673I9krzgVgTQ1JiJ3VEPPF+aPqsZoKap8zeuxoEaDerzw+1wgNs1buxl77ORQQGvzXAtO/OCYo7fKM8ef4+oxHM7yI66R21/rnCpQUWXlOnwbtjrMTi8T4fmDgCz0DwsaqI993OTtfUu1YmK0vgZaw8agU/NTS/B+pkpSCMGQeAazlse2pZ0GrhA9xZV/BMJxkuIvk6Imh5bByEvMpG+hb0xdtWSb6uFU1YeW2puxmpersSS5da4u5Zkb1HA0jfjdjLzesakgnqfOxZ0+bUFxWPskgkc9TWfY2k5dYlrjYjno8kzOclKPFDgdJz94g8ffrF3IlWn8C3k1Alp+A8yJ5RlZkEvc+ImCr7g7QyS29vweP9dXgAiRc1w3476i6Yk/BW+d5j9VPPo2fRM3//ROnTOnAsaBb0PRQH3ZD4XrbbiyDdqqygOXmuB3Mfzm+8TgprZrNYANzQ1RNQBovscGxkA8Zbgz1rNy1+Oi9tFVRJRm0l4eC8xhTAw+eIZDx7MhYkdva6wmV2aE/WVMP7Gvv7m6Wpt5zR/gHoNo/8wD+qro7Kn18RYZhKAit+49Xnt/sWuwPbrZT6qPjGM8mORjLC/Yqy+s8MWoPRvydUQzDpdsQGTPuZGdabK5tRO1WZkF9D6AlAjQQVETtH2gHP7jbxL5R4ecMmQzOtG4mmXIBhV9gokE3mlt/8OYd8LzxJ41YHBnnhVcXEDzO8f54vdwuWDgQoULlKx815V3HCXgfp8H48RB14tULrYZZBuZyWGt7POTTXJwEcSaPXTgEZ8fDJmfaaK3TvD44Lt9IwzbhhfvA3i4+DSAWI4HuWYPB1zkYbByM0T1YhTVSbb0wjrq0FueXsAvCfHW5j6rfquVBXntXEBg7zjKANxcAYBbveJn0V0L4cJ3GbV8BCwHdecn2Pxxdue/59jv73rzJPTXXAByQQyGc4a/YstHsPmr516k591sn6xyzvhks/+zG829D41aclMfjXgGnH/mttRPavRd4u9zgcoF+i+//NAXBqJhnwyz5119P+ZOvvChqbXentzzIPzB2d9KKGh6QTxYcv7440++GIE8+kauU1c+fo5+sGrNhbQ12VgCquXPP+fj5j1CVhrXXVk+QnS5gYJ87Dmnvv/hb1/9/e9//+p//vu/zQ83F+f8vYf9zwjUU425jeYFEn4lwZp7s3gSkqvJmoMsk2+OSfOnnDr0269Z6x8OnaEzNAuYucnCveMc4+HXI7CITu+56XqbBFMMhKonW5AMJSSZePw8iQK0AfFU92LihOvElwcjvRrCADqHikH08mCTbUMFdNG7qsbWku2QVMFZmquVLHczsWUQv/mZeV4eez0fnKQ6/YWTkQyZbCyPUZczAfZruMWZaXIvEiWMZCOHX8TWthGLVoOujQNx4fS+56Vk44utSx8b3/tvamxdza0O+Hds4lmLz7znRnM3snrYbt8J+SKcSEvbc6m9Q3UjuydyeJLIL/YmHR+Pr0zdJMsI4nhg5NM6c7iynE+x6csm39zP5OXw9CPLPcfj4PFbSmjOuBXtbPcHkkkrqAU5pOv9bbTEa8ypQTGCqxkCMB3l6srtFFNtL65zOch5yMonm0Gt6+hArZymVSwINFLJ6iD+zdk8tcidjefbav90ydtj0+nQE2X4f9INRc/XYPLNQ8EtbBJ8FCpVhVrAdn/ssNh8eL6Ye1KphU3InW/gsxh3T8IRYUTn497AcrGKY1luVO3Np+KL8QQJ0j0EGRCYAIa9sXzasor6+ulNcxZr3umJdg0EZCL3orvHJlN4rHe1CAczcSSd4fEgaLDDJP/O2TdaYLmJj/Fg9ozA7gCbwU49YLcHjXJ7tALe+pkz0pno2nNmGOuq1zn9O76S6sWpZ5ybfzWfGFkmxDqK4A6XAlWFyYB7I0MbJu4smIibPhaqUfbFstgq2/vWd2INNKQbcsg5fSjx4aimiituY0s0Hnu4eY9HXhCMWj844t8YjuGOznosq/v1xFuq7hPH1/LSsVroQyHt4s6nP5OOnX2SZ/PcFLKgLT+mNa4ZmK4UzVndXDsHgZcYAhrRbSz5Zu6aPDPe9daDhmoFNIHix56gZXCfXNUj22WGJyt69vat8zLom4hqn/onH1oYR1vmnM+bcSoSY7KDnyjXFVyN4aM3muAu/+7BVHUsuhp1/QiYOqWZ+Rc8k/0vVusYTWbPhiU/fGyXC4JvefLvx9iD1pe9TxSyQDjV5wnEXgh44T4XSrx790cu1rhA+JMfLmryO8KumfPjO6xcxI1fXNbExQa2+ik1ufjhRQGt5O/M7fSCdyBYUx81MDiHeqzbMtexYwPvkyTuc4iUrMfecw8C+psfEUDAimsIkGmQe6XQMAe923ktKJdAzj3PukeTF3/ud944WPgxPhvPiOCWnZp3fiOokcBGsuuLGJiy0D5+17Xj44ce8sJKrPaLc95jx315vvlIOx9570fM+R3wP32Hl79+7kU6xzHHmuEx2HytAqOa1T45BWez+XnB57u5COVj7j/++KMX6uDg5kUDXijwnf1/56P3vnM8fYlG66Q3tGBH8t5mxZdjujWD2/n3+X/k//znP7/6KR8v9xw+5y0vHPUCGGIukvkYPhfKvqNtnuTgKPGiEVPqy1ePG+vJA3YPxWqc/ebkGNADPuaOtn0BhP+C4F+39/zti2vQ7W2SeXM7M09NqpBrPNUFPL1B7ue4ts4syHpaVbbRcKw0MSu2t6Qi4T22nWAjxm9wGdMzFurRiIOJFhYumzdWjmt83estl9NDAIKE/ZGi2j5ql7Q1lalbzIxR+dHDVQaP9YCzF91fBXeGlq6qHeato4nijau4Vw8WYi8X+K29ecFXcXFda1EXsUGg9+Q16/DWh+UjjymXOwu+t07A6J3zaOM4NIQBMz8bDNm4zmz3TEqH+qutK7YdcMs/htK5ldf7anjVsqD1t+/Vhy06gOSH3VtPI7bX5WlcgKuGOAkMDoEPlmHtWp9plg0IOcvnVg54+riKj/+AwmMU80ai9P1pD25XqkNsNu6bYhYoHnSczoYbWPOE09vzIMEF4w/1ZDDv+LST5PZmdaKix3nzGT8Umxe+Gzv1xkkMeg6zRc15o3YNlROUWed8rIJqvKjhPidjQ0s78cN2dU6d9CFfZwQOps82jjVpRwDgLeoEEgTWJk4hLMEm7uDkG7FiY1D0LUDs2CCVIxkrcXCEwRXcamF5yoAbHzyOQcmHzFUUP5D8bOxGGHY0QjeeE/vkIP6xXw4dJjCcDT9gcyNA1SpBgHHkHDH1zSIsHjyFsQGXH+i0Ge3saqkP/3o/9lNTeavl+umfdJ6szFiuXnM28QofRJYJNOcSRGdjy0LdUse/X3gcOI598k0yYwbmbvKvJluyCk2IJyD6fexPz4cLmeJW7+YwruUdzY9Pz3DXnFwPh/KmHo/J8Jktc/bvOBbrx9OKN1aqMTcy24ei6G7LO1Wba6Do87t7646h+0Zx/PbO/Eu7jJOTTB7rOZdZ19+ojxKfvjTLbJdr/BNpH+k5Awg/exvc/YRWu/EbsVGUmq/hXq86pycgPWbPGg1bFxJ6e0o2earQsKMvtsSrZ/bEb27yNbdVTFQZtjoxw48HPnxGYPc7LJmbZ7zEcX4fIxO+AfHjbiYBwzhK5cS//Tk1jEJxJhB1dK9pedjLQd7DvjprIaYXYFyItQ5j4ugaHcWAw3Yv2Iv32g3+ucj+3YvwXphzoc2ad1W94M4TDS9qgo3hxHgRAiYXWn6MPj6r4wmCTaMtqG3PrC0rtWFmsHiOD5h3bD/PPnz9CD51FPnuqZXhPlPiuJgH7F/rnj0YffSPhaP3rZsrCNXcdStZhURyvRvmRPPuO3W3nPP70AF0joPv9/47YWPbuu0buvN1tj1YuR/pryYoVe/OFtm15wZ1Uxs/mXfkL9bOX1QnrxfpHP+I9nfQcxx/ycfQ/WvrvIvLE8zsKWqPZ8IO185O0TGgm3TNzQtF/B76t37knIvlH374UdteoPtX3aOBf0X27/yeNhftPLHdAY+EcFvH1LMlxc6x3o+ng+EdcT7i/o+5QPeTFtbAiwL9gZMLZy6UuUiHo70KIcdkNZAnc+pvfpz8PBfVgTA4huB44YO+/ZZPJBDOxf+Pf//J38U3MLl8QeC7PjVsbxtLXn5aXpJkPKWOhhjRww4hfxkchR3LBD7z1K3O2S6wEdWwkezXLo66n4HPntiP+Ew1mWc5K/MSCsP+4Cv/7KMNPv1wPlrFYSLJ5gMomv0Oo4uJiVqrQfCAOveYHgXlbj2kbh71WDeZuX23e2hTC7ZNTa7Rj2mxzT/8g5U/DnzGL2hyYD2mJ8PLS1zji93cPZ+oYbgTX2z1w1HuWE1eA9MiiQ2i3/IQc6PIVwZxuB6q4qY/clxsZ5uHfg3viC1vVNhzUg5P8q2tOpvUowGWPJdcQQd3HGAAtV/eL3NBbXwJtq72pbm9D6JiIezn57k/Vkfu630hlHOEBwb3e5FOLZoQrtijvRYyTA0Fot/7pNjRuL2Ot9jst0Zt0bWcu4b6zJGE4RnlWkPZNs+13tzY0NnRPpzlYY/fPg9sk2JzfvnQ27qJwZ0vjoeD1R3Md11MVvRYCMGZZddBDmbrrdY1vXnmz4YWDJy31894eDVnY4N2IbBFMG3+JdhVxXgQgyB538JHM745wEZvbBVcX8ltPjG6l4uYFtgcxVI7+LYoC9cGUkRzDxNWWdwMJruTZ3TS5NVU6GaoJmtbbvZwlORqYR2HPh7gMynEw2Jy6yyiYEi27k67HjtBcpw1KzK0+tNvgLEttv2XKscEIY0jkrEs5YohGHytjPXkNeCJkqtIEetKiAN/VXSXpZpiPZ5TS3zqmlD0Z+15+mDqhSdMV7hY6rzaSUKWjjsb89wAoGZaf7fV2K0vvDhNRvbh3PPPT3dNRadXpFM3XOUY8i/0Cszm4ZuIG7nx1dUIRUipFz04MvhIFV9r2f0CxNtLwIa46Z1/phCd5MsaqDFhS4ycee7q7WMozBkdxcHRzKpJrP0KHdZVSGj7CGlzIamRLwfIDo9vpnPoNK62Wcg1dOXderberNFApvk2tAq61ZDNoMSfY34grQUSTPbj1DHJluDlml5ur/b8Wg5z27+Xf3qr88kVXDM1kf0Zfdoz32Prx+2IN6bnyPYB2eqxkpmrYRISNr6h12FPph4uLlQTAHZw1QYfFwHXQr6O1sVFJTQOnLy7mP+p3ne0M4+tFQYxwdY6nL7LGNdi6mNdSzPPPPF84VtW5v0IfS9KmFvbxoeg/cme+3JkTPTasZ06U0xRN46TVls29RVjvLau97JwyrReMOdijUQZ+wfcnGdjzRDb2x5fmoq9/dABPBeCfHSSrwwaX0GNZSlPvNYKKgYE6cgyczUxrVdf88TAgCfxfXGmn6rgd5/7TnH3/F70L7kg9kI5F8j8XQI+Zs7vp/+ad7PZc9ErB78XblPo09S3iVqJKzZTmWteFPqDd4p//+6r37/PvzrLxTcX6bzwY+6sf4vW77/6my8KYOOdZv643J+J5fc2aEcLcmIbqNtRp/1Ap3H2KhfFf/Ku9Y9f/X//63/Zvp//px8v/9rP/edd87zDzoU5H4XnIp3/R+7FcXgMMEEyDd8u1dLs5n3L57hwYU5P+Vd2v//2R/L8LS+KVBsvGvzr55/V2RcFeoE+dOb3j8MlnrHHd+vddc/WrjgaaKLvnhejtzsa1Gh81IKdcdfjl6N2zqV7nDtvmjka8MgSX+4/htJzhLm308F4xpA6Fyx7Cq+qw8FRBjPi1m+Ks2nO1p6caAQ4sfu4JGc2aND28CKUx1GjVkxFjLEazD92zvv2Kr6pdPvc9M0DvHHBOyulMSfX1DBre6LOV8TOZUOQWc01OVYsnkWbPxujsln7Yl+LfQ5GLEjiRhM2PPdY1IL17flm3r5vydiNCJ8cj5A9Bz78EBODDLA33fQd43XUzbYKXHNfSXBy9n5ql5yb+XqPIfN8cRtVH3VDQqyTkaD+3A6lHQwyxPT2SZjKuBnnMRM+IbwoG9s3wLw7UUUwpokRfSKtcbyTPc4Q8+EdDYMzZm5D5oQDY8bqhoe5Kqgrw9pnL1/mxYtaE8A4WsPe1zdDOOF6dGBfDdygmgnixuPvbY+42NmMno95bB538MMi1/CQFy1QSANVxpkvbmK1ozPfcf111DX3T2Uixj8SRxpiWiwcRddeNkkxJ8ni2PdgtggICS1Z50afBoqQ/2isicgqz4GWYgDmimsP5qkuIBsHzsKfNg5nmUYSBaij+62hN0xJIBJSJlXE1nKaf06S7fAI9aSJrTfkOaBHQ8tqblIsL7kGZJbWDk1jvAAAIABJREFUg2a+ULRjcap8Y074oLMue7aj0ZMxRAvdPXajhM5xDDc285h8exr74YPhIoAdvcGoVeJsHpgYOFbATu6jkrGGSlrg5t0e4Do9pBdyPv0iBXXE7sXHyTdiRiMrc008q/0dWpHTC9JNJFPHqcXKyR2E+Ug2PYvp1QyHJZuvi5XG+VMO7DuGZ2qhZjnM9ckNL7SM7Zf4GNHA1w5Yj/74DMzOnuHL7W9SYISxeIyOz3gQDHlzUskttp5Tt6Cg5MxiA2eyGuEhpjwEMWQv0v5Vl9yCp3+HKyHJYy+y/8txIINagRW39ZsuPBvb/jTfauxKWd7miVGLwW+/bu6tYORaEfBtw9E4epbPuNgcJ/EqWQZQyUtsvtq90ZR+rWVr2nNl8cuGcvNmY0oXT23HWNxqH5i1aDubaoLUnNl86+2dvlQl7/CqY0WZOx/tmvVS+aSWymLIU5g8iWGP4uVh3vrby8zh0l8sOtaHvZ0pJq5irZHY0R6UF668m+GTkOYxmiCGmrIfzfbZZTLAk6+FVsMEuYvH5D0KTNUdHdY3gdhYr4+JvXBfvdKpf+s8ZJKemsMlzP3ExuALHtQC59E8NcS/dRGsOrRVUJ5YcHHPwIi38z3HNCw2L8xwrflNniXyDjIXr7xr+13+3RkX57x7xOCda+L54Z1rLsz/9cu/vIAFh50ns1/nX/D17wkY5qbdbC3oPSMakIGA/f3ub3/vu9p/5KPuvBDAR715157jzp5TltxcpPux+OC/DUn/DgLcHhn1TOEnHV548tb8eeLt31OI/Yd8rP6//uu/cl797h+M46Pv3/Apglycc/FMX7ygJEM4fPfaxrbusKbTz3GZI9BjQJCAPUS+ew6Hvz7Au+j5CL8X47lI/yEvPvz8c/43e34nnR/yebxb3le/84fycmFPzx1jnxRj264fBepbvNiNV+tEj40uyuB6fYluoeYGw6i2iOjy6lqfqGzmwmNUa73zZINiLqI872M4OkCHn5onq/EGRenFZQYgOLidEzGxGteeXOW7e47iECz0cJGw1Fe169jN5T6zpVg8e4prtPvqylR49WfVESfPCc/jPz3JkCEbavX7xI5PzHLt8SeqMWtRBpt5fqE/Ofd8Amc/I2Lr2+MhWTYtZ3Ascl6cY5MgshL7jpdLO3EA8yO/ebMkXhu+aoBNfelFZnGwZZ+R3cxcnPNRp91ytvp2T9TmBdA4oeblPticmnjsQYPAsQjzPkXO7eEtNCp7kc/x5kKcP8Jqr3z8Ir5V+AIWD6TcP9FL0vhlKhY9J6iVk0N/bHMO95wFEz7yExAWvlxichUPGkIhwoLGFoTY0cQC99NBWdoEwOnH+zg8XAU9xwfDcM30cFp94tQCjNIUQW7s5RlTBWkLbvzs25ET6lrd5t0eFFWubJNs03WPZ20c60dXas076JXDfp2JcHgiJYAxx2cavYS6ZDjCvTNNzFFRAUdgHG8DTpkFIMNhuDTFb+HydtMUPTOMQ+qh8YQYnRxUCh9bM0xbDGhTsO+JBBPR2x18cswdVyUEsTkfrRafXH13CsyXuQPOMPVq+kJjEYsLcgqrXOy1NX/WGy9xfDFVP1C0aBqaxs6tigjtsPJzBwz42r+1o6F9KZq1DNTpNNu4/lI3Yh3T29W8e/Lk6z1OcPynUWXVTX0MsaNh49BZ77CEbs9rPeiMi8yukT45/3Pm8mxviQHvfniMy0Y+2Sc33HsnCXbqxitfzuXyBohodFDb2Re3lOdcFdK+fWoZGhKcgVYoW50P4snhuYpjBt7VvzqNI3lDRbDYsPrX3Fqg25l81DwP0saRG5B6yrTHltr7JOMkPLoJIXdbk7jTo62vfrbt07CGs7mufdfyEcAI3/a3vbh16qcOMEDFh28fuLQ1/h6PG9+YROV749kzlusc99j0oVs/CHpGcGwToHUwy4uTtjCWf3nV9dQAZqgOlphzLEwAz62LmCppbXuelABkgibx0eG6xk5h4Kv53W8dsfFwgpP06pu9sc0AIgMNtbLbuX0aP/d3g9BCzF856/p4EjBoz4fh3jj4+uQl3KObXXtB4D3u5vvyvOIBO2TwqS2b9go7FsjgYey8BrbGzXHc27TI0aItcx+WwU+yvfCbDoe6bPAdTOZe+PpJB1h3UGtx+449MXZ3RV3RG3R5E0x+3wXPxSEXvVwU8y7uH3/86AW6fMH0XfS8OBLer/OW9s95l5c/6sYfb/NiORe+YLlL4ULYJ4vUiI6MraWrbOFJfuzguVgmbwzpZS98ycmLA7wosDp/m4toXhjg3f6v8zbUt+TY5wMkyFrdk9weYc/gXfBvcmGf/2CWJ8y+upT35n/46u//5C/Y96/H048ffvqhH2334tyzP/eXqR8SNGaObvueF42QcHOyysiu9viITPP2D/Hx7jm9o0Xsv/+dFwXy19xzUc4nBP6WFw14ocBzGdD0yr//wO/hY5scO7FOtNXQ6hXgGaEVLyvNIOGdx4EVfOsAPbebBsixbPpMFufoAcZgif8MIFnoR+gMuViiOz96dm/uWPSz6/zgBC8TeziCC78hLMg6Noz2jZrJMTr6nLpqMS2HWGKfc6uPg9ybfdFH+JCw3CR1WcKya2qCoJfDvTes+BsGzeGaqOIP/9QITEDXrbE2qPY2tr2zOO0EVYN1LvacC0dKezXE5JKXcIbltfba21vu6LzwTF8sKThjw68mgzvfTMtLK4wRU5V7rGSBS3BzvbXd53WfmkqlAkX3+BczabJrVl6Y1O9x7wtknBMclNNPD1D1r215cKGJys+Ffbi4F+kLmdOjkOYeCKP4r/mUUu6Y9nybzrVWEC1a3kptfrVO8s1LpR3Vsas9/vaxJK3VekBNjyyYjtAjOCg/vthZY1BnW3boizksxjVmuA9vMSdw3Lu+PNXvepx7PYcMWHqb7BxhYPd5QyF3PRR/3bU07dv3BdHf/B/0Elv4NotmcJLQjGkOgsTGtr25BwhL/euUyqYgdWLjZLVCGlVLDyCHYHhW5eBF8bjGBMzRuGqwltt9zOw9qOwTWL2jZfxGl1Q/OkwxW2vOXM1NcPTDWWwSMCDTUOtq9PxeXnKd3MllDLbMRyNU7TszRkD9dtWsBibdaEv8l+NLX1WBSjWB619dE/xyv7Vrh8A8zT0hSGvZbCfJiZX/KDEn+Te3HIOpfXNUCTYP+iYJtlPFRM7t26QWvw9o6sk9L7hqyz7rZa8fFUe4vmZR3fAxJzPaO6qj+bVAPb7dFRM7+TPmVCsH2seoXhZyuMEzdwJxGL+Zq3YfFCBdD7P2/uaUCK5B6R8h9m8Bg7m1R8fgPs9NZLaeht6c5pgaNuYgnWy/WKxqyx7lw0je6ZnIqbF6iTus4sSsCexQ29fY9UMNZ5weD/oP8MnT7NOr2Ddu9/qNgSs/uZ98jx3+pi5ve85xHkGPbm0xNx48seTMhPlqmz3pYMEvG/rEkTXDsM0FejhwAeRnbO1L190CAg9iLSisUU24MvacAfXa4a8+Yerf4+VFbAKIAeO5UdhHzEhUR/kD2iDjupzQDx9E1qmzylrB6oKI/GvN4uHutBXsuQsnaAZP4KhRXBul3ftwrMvFlEI8boFkX10A6oNq6Ia/eD6Wb76Tq8cTKp5kqSYLqUsHZUZwJ89YOB5jW+hZr6HQbsHmSSJP7hhqDo4/DrZP3ownV+zYPo7/aAazvfDJ8uLhZ54vLzDnApmPXnPR+0c+as7vfRPMReh3v+ZfofF73/n5I3+xHB+/h8676FxU806vf1U9eLs5xyb05kcGw+PW6ec2ft/BT9wff+Rd69T+w08ojMafv/nq33k3vauv/Cvyv+RC1ty+0z3/ksznJKmLhuS7/8GgxwlV2NBDH77l97rRmB9fTMjnF3/K738z5w/VkY93zplzsU693+Sj9OjveRF+eu55ILvklLktz9QcGiYv+fzd88TxKwLMtXGhzoVLdJDzH//vf3310z//7gsEL80fvHueY0DevS1QWBVwLigwKbk6Ij22ItC2SneGDeOeSyIvyGK4f8LU+PBZYEHGSxF7qcpFLR70RqpjwFoML0Yf1UzjthrhJ9eTKbEnV3ImMLKbnyWjnLjw1QbmjMUfU/nlPb7RB4GxeoeugWjlONRTXSaMAcTmdw4Ku/wTUcfEZ8GauHzpWi01r1s84AnX6+rEN0Cel0P/3vbBTEDhnoMlf/tZ3fZg+9k72hZ8KJJt65v7rcO/FOSh9OS1a4PHwmjdJdy58Pjs9eTicAyNcXp7U9exknavDha+aEDIEmwvsoc0w7+nwSTFYMpdQgfFnWnnfLrF3PQ4prFWK1huj94Uw5XbBLfavKQnSx9DnDZ3chXzR15wzKuHpRagsikaxfaOGshI7sxmJde97RFeP7MqlO1Mi4Wm9tYAdLinbg+5kEGYdGKe3uxtjwRodcRf/lfLagZVXGMhLn617em2GuG0B6NZvByjB7/3z1mHTsWlpVCj5bDGid76x0YQx6PxeQfdcgJqYsI7tuDVcvJEkNgFKhBv7CapEOOftXkG45NDI7Jp6LA09uXfZsnHDVBBLaAaY4NjxsaSmrGYsx8NXRdDcm+IS0SsPcHOmJqHs6+kFDNttvbVugejL3L0NNj6l1daNuE8Wprs9nEPmripLLpW68aN3MahGJ7lvY2A5Qy0Gg8uVjiaYVeFmusLHXiI/RytE7I9Bhu7J9zFq9jlztjvUME6MFrz8g77+N0dLWVpX3oD3Jq2DWmSBb893Lw43uo3tn1qXDs1tW6grXAzx6D9eVHNv5oa2IjWp+XUsVli3d7PHk3wGmu5UzNQSQjZY4vmIGcNoL3Jfu4EPvIGKnwf6FybSU7P7w+N1QLH5g6D2lbDlz7WIMrlomscGXN0Ryesc9ubOqw/c9rB2H50Wa0JyZi5Mzhiick2Er8IjMPC3rFg7ViGa5MOkejMyxBYDN6pT79by/rLcbAmykrD5NVm8lVS1OhlceItJPkCt58mb34zBuiDhfVlfhhvzr2dlDc94cFl8CaWmaT0ezSO/+gYTeIfzGooT/Pvx+RqgwH7HWqkgeHZ89PzyKqHI/OtxRwrC5oP7eW2N/A9PutOnDx5QvL62k3JJNhclmbRJOz5A6oFSIa5o5BT2/4u/HjvLqRAGcjjcfFaaicv8fpFp6Isdr31qc+QMCSGd2O48PusbTmbldhevVa4nDkHvGsAEqLtFceDr2/ytjEuIxIg0yQXG0tj4oE+X+9tfSTKzRNNPsbNk8bv/si72DPIwO+l4+Ni8rc/+IOA+Uh2LhJh5K+5//pDPoqeC8x+1D3v/sTjR/TRQn/kejRU6WSgN0S0P1ykf/f9RBje+G/yAsGvuWgmN3j2/LG43/JOM78fzpjSW/PUDhPsI2J8YFNZLrzvi2N5h+SbvFudPvDz62/5SH8CuTg/cjko+fZ2kPx/goU8wK0SbGFz/gTAuoOL8+nf/P4+FwOcG3xqwf9qkBcn+F33v3//j6++/zEfb9+iwkvNxuciHdJTG+SjyzwV9WHrE1zFCmnsrNll7JPgrjDkJ0Cx1jHnGAWR40sNG6J/FtsQuIyBk/jsncLupPtg+Nrbyp7HhSQ/58rk7/17Y9VIXL6gHlYnr63nP/mPAPN+xj8MybWrhmSFLYurbY/FzW8NqECrDEhJHCfVZNSzS8jFjjvL93iAPQPas2ACSY3tD7as5Zzsw79x2wfWK8Eo8jbaGqvpQT31iKcX+aI2u7AJ4ACb75HB1LF4o/CDxcMmRb96Xp1AGIullXCceNdDU+jZGiNQlYnJV9Y9hsSI6GMdOdAeAPd9YviIDhA48mP8sLfOw6AVmHCSDDu1cFvPS5+9SE8OP0YfhKjcr/OJHq7L+Si8f+R0fdmbN/Y+Hldvs+CsJrWGbNVsr48/HmxvnEI3ngWao02uYK1PPyybt3a5pFs74eObNHiYfmKrAsfLLwtg8Cw4Dmooh3b1aU4vsMSXmGGsYbfDtTlqxhje0XmhkkzdCxlslv6RuC6nieKzUfV74mqwEZDbSBRaLZaNkaDCrRNM8TM57e7a7ceGA703EsFvc4LEBysaxE4ed8veW5I61NqIs25CeIhqnXA5sqtn7VhjHPceFJboWC2ttNvFTwgEzzDCuMfo1GhPkDBk3z7EuidNUJu/Afhi65mlF2JiGbd2YdrYkIefrcHVGgZgD4YHJNPNvVD2jOWpzOomt/mfBzhJCOAYSsiedUk6zWJ8+wRSd2ztx2DR47lQbZ8XAMEw4An5Pbbl6INWfMPRCowQb12j6eSELl/tAXtGtg+OOzIesMaUfVGNM4CU2otZnvq6rV5jo198pcqGffncbw1bK32CiMDOsk3M2lnRdG9XgB61mYrDFwI1QCPXaNHKXCPejOCHRnVqOaY5bhsfOH7zGyxTw1/O9dWGXyGdTPbFT0/C2ToDGhylktnjuBzZtzbi+Wk87uKZNcZSTJMN/GD0dl/kzKcmcm0fOc83xuPgarNmP+eMGlc0+wQZB6dJejxkC2et45tdgci8BmZVsHqzgthRZT3Hj/HEG4t+823tZYQN3saGTFIqHLsKwxm4NapplVTLzViNm89Q9A2gGbswZwCrAthqeNnRXNDTK7QsKTMhy5S90xixMxfbuvFhauYjbXDBeEd2Qggmg3tpMzPWBbnv8cTUAf6utI0JLuLrZVWHdT5h1hTxpgmB77rGL65J7laybAia0XNnjmtszcMkT+Zykczvi48Iw6CwV9l85mjf11ZcMJzvWZCHH38nm+vz0YCNi1Qu0Pk96d/zEUx+F/w730lv7P4bNC4ywfk4Aal1Vs/py1vDzoPb/DyB5XfEwfPz/ez1x8dH0HsRwt8+yDv5fNSbi2X1bs0Sjg057adHgSnapmbq9cI4b4/s7eLrv+d/kufj5tTJp3Kow38VmPmf/JGnQ5EZC9b54diYA+6xo6u++KOTC3JezPglL2xwsU0k/fMFnKnju2jiM/u+OAB5hv2g57zjLi7GStNPSR3Nd1bkj1PNq0+l1QvO0NG7ccbY0/Gvw4DwWVcrK7eObErUXmeuMFY9nqLmOUjjHg50Tr+k4bFbDUHmOSSaAlDvwbnC19TsGGTUxYJwbZ1rgseg8c18jxsYSM85IclhUefyNFUFkFdtvK4TzZ4To028Sp6cUx87Y+O3hhiazVVC5zhqx1O8k91Mnp6Hicht+2oraHt4Qxq0ud4+7n2DJE05YbuYhLPDyZRxjg89tKYv9iRKLZ5nq3OCq4WKM5tUm0LfcDbTl9sil6OKhqTBqPOLY317zouhvR8pjAMYLr7ZZ/S55My7swZ9WbfmTGZuUDbyxcj9EPnk8/zIC3z4c7sGQzw5eT7InB/vF+hTvtoPMH6XHm3EydQdS81w5sscM8+uPEzmvl8bOaZO+JxLFC7pN0/QwamVwAzm5GjS6nZN3A64HNTByHZNrp+NWBmEIIv6CXCvrqyJ10dsFqNL5HBv3KZa3cWMbsJJMnnxQdze2fWs8wIuyU4dYLJYYoMg0dwGtjFIuA07jW24+JMwfJ2jJ7NJ1nmg12ScAk/RcRJMjHt2/yHvaIQA7WIy8yIMCgtqXXuoSoe2NoVYNG0zy3T58N/OdLU2uC7Pdg/v5dy6NA6kZbWv7fvVc3plv8jAuNiuNamr9aAjqMSsHvat4kS43FqWGdhbu3HD08hYDtVGL2ezuZJQsh7vGKvHSbRWoxMC1pD9tOXokOpYJ7n9gKSVbXk9BTYCptsre0+ugJnfOqXRY+5s9hzYWrHLms2mLt/oIfo4IGApW6bFHA40YZvQL3Vhnmzi9FOnfNkXUNS+ADW52uPW9/LQBzjhegdhy/dlPcYH0Ag0Q8EWLSzYWAmLjK5PH2IBjVVPYm9PcHbdurJ+xjnvF0PeqbH7Mk/GDyUbuwgVTiy2ipp6RmF54m1QlUzOcy7g5AFsKODdetYmweqEZZ7ceVzCZ379bz9vOsirv/sbl0jiliNAudCgolkPBj1nDKdca9zahqXmACdwuVn3vChieyuuJ4F+vJd/NdmNE4//He1GbZuvuZ746CRObub5euOWj3jo8X85eHJzcwc5YHkyX5/ck0+aUNmmIWS+djjIhIlxNC0Gm84iPrejMbvL0bpufdIizgm7zzqm0iGoNkAVYE1njnkUsGMubTiGf89xfBMW3KQPBv/WSCg/XNxxkdm+DVZuydXdPPe4ka+p78e/5c4FcN4wcuTSuBfCWfGighffyUM+/to67/zwV9atKWTY++4w7/rOu+JzbvIJAvmnltaLAhrRVlCNXHNhY03TFzC+s/5bfj8+H2knL09c+evvfqIhF+pfR+9W3DBWk2McfMA0SWKNId8++eV30H33PrtvoyF2P02QWr/78/uvfk0u60wGXxDJ7+irH05/8T17yuA+ZnizYqYZF3X1wjwvbuSi/N//+sV3//0obQC8U8bv2BPD8EIg9Z2jnYLQ9XvedffJvAXGkO/3o+zN2ryHq5Tt7emnguXfmDkjxOGV2wpMMuuS7UUrxp6PzJgvluyjYHLOqngXiUyiPfdNORdqVIAvTlnIUX6Vja0ZeorFG849F0fltdVw4lgebEWow5T4HuTe3sGjFfic1kXxYgPDOjt/tdcHJ4Pt1CRI48emiJraWwtLzniY4iLWHrLRMja4dbg1xeZpg6bOjYcM0mQaKmuEs9/lGQy7obF/ewH/ng8ySokujgs96/EbMiDnxQMIkUh6fhjneOuQTJ56sx2gGZiP1vrrbHYsnJdCuImWB0OGyNHHp1PQmm/Bs3PtuTIBe5HdPvVTLc3VvPSfY9VjR47YJaufkrjfIR/nlh93T1Lz5/z/M/dHeQ3QYd/mZJM3VqnOfs7JZKu/efcFybKwrcLTV9aTA68aWRfWyZGdCcePPuWLPRH2REz7i3Upl2bXcR0OGnr62cx1ZwvHl8M+mhO2W+fqAX9yZ7K5l8fajFxL8RtzcpoDslqarWzL2X+zdnjIFhcPbtwJZNnmDAA3UzfswACqn10b4SzmNrIBWQVLjOGGZcPjV3LhaxSc5W48DSoDDuZnbEyM64F74yTSt/Fxzg1weaxPQQQWDIRRpbAV3ROk6/Ut0to4qfJ1ceutXX6rL+M5aaSHkUl71F4hov3AA772Vgn7aqva6sTuMMgurKW9t75soJ5jwp5hXWPvOvbc+K3roV8tTZHt6IRaLMF1mtNpMPeibGIGtzGLazArRlk355f7YooiDjR6rM2c1UT/iXWUslpnbmDm2wPxGBOnrjJvIswZ5dxcYzRFa+pxBdvcmRi3a+irGbOdPtj6IEPi6mDK2AfteodUR1h8gurCOHMLYZN8e/uGR8uroZbGTO2EYdY15wO9bBPCGEC+5Q2M8T4Au37wBdxjdHjsRe3wkQ8d1GPuGPf4tG+jpYQTkF149ph87HGJ7Zapxwn60Qe+kEU2Z903bo5sZdqXhoXI/H0CvVTlMBemSzNBg4vD+oCsjsyX/t1vfvMNfv3Ng47ydst6DdmjM2NN9tkFGqbdX/TEpUHxz/129Za3jHP8wCWAI+S7glk219Y4GmIkDs0MI9Ym4fUXB2qxzEfrmcEUfyFa2XgeqCZ88fV46zkYbUny9n7n9iekq+H0P9HKdN/zkeRTuRmLWFR8TyPPsUrMF5LVpe7g9zZg/my2TxXffAjZLPScdz49BptPZyLj619Ln4wnqGzW2oNVQ7ZcRO47qT7ZIxcXdXKvcoyE3FqcYQsfKM8Hjm/i+NmPm+e3wEc7tjyNzA8Xkd/lh3xcoLO3t+TNFxecXMSqIez9l3aBgPLdKXK4Imy0KQWjA7fxAXKRfnXl9+B5F993nf8cX3l5cYB3uKVenizasvYCHtc13mQoV1T6MZqolcHvnENKdVzc++mHeT7WT0K0bz2XE0COuW+UE8LY+uJF/yAcH8v/n//5OS9m8CsCHX/OX9AnFi7zf9ye89QsdfvX2/14e3sElq9eENyWmnbiyU+vxW3CmLjNHVsCOH4F0oQd2Bq/FvanXxqJvaO9oF+1wzYsMwM7Obhiyigfk/wg3ugnLvY+vjZOrYMlDwPbOQ4QGTN5RNxNa22W7V2zgbkxW4sm8jFs7uaaPT3mZ/2dta7gj0YhyQ6H37fvuBY34SOpObD1nEJC4p7jqs8OSGu4/TBJc20/GtdMO2/P4SVl8lWcOdRFvvzErabiXDWXtQ8niWRobZU52Lj8FaMYR775wJOXfUf31Ok4+6yAiV/0xuow8zLVsriGcsptjeKy6X3T05OIM7M60VqmfT5lXG6r/hqPatDQQdx06hrI8fiZwilvTuz9pMzv3n/mwj2+3JPmr77n/jW34xjUvCxwqWFYyXfWcSL3Yqpn/ey1iJvzV1us6fPBkROSWNYuawCoWVvx5MxM/OxWgAyXu+JMXo2Jg+vA4dlxjc03mt7+ooXRHpQ34GqMFV3wO955Lce/WQc5fIl9cHlpluIZOEKON4Y2YzxbwEZmX3ElEwUGUSzELbhipUDsPpgE+BFH2s0DxRS4+5ikvQeFXOVQK7GJUYI8KKycbVhj20D4xCvCVfHnQeqxdVoBmW/I8ppJ43BbOgb0tA9dQRQMHOoVcfgO8wFP7wj7YpSViAFn11TVYF5tWZ+awE7OTm/PLyGAZUWoNRSeOc4M1h810Hs99RFnf4cLvMdpmMFe2425F/BDdnajY3g1w/2hDyusk0ss5VSZ2FW5ugbTWmKcOtrXclFL7zhkhpDELJoNLnl6bHEzJnqw14oefNuPE3u0gOhxJFdXGy/1bPZ41LfHHKfyhs8FEAW9x7Omwxz8qwuehmnNQgLMpXqOubZ1J2hr7EXqxg8fpCUmLPNdtC84pTIMpozljkb7FuNiVA1oeOzDG0L8DmoM9uiLXX7YHh0HfvygEnt6Cnx1bmy5Vqo50Dv3eaQ4D0A3q6nUkA21yPvEWd8R1FyvflwbA20YsgEXx/815+QxI7gzfthZAAAgAElEQVRdN6wsra/5hyykoZTXPq/ZrCwY3dOr1Sk2nuXCzri3d1gvt+/esH50GUCMtW3iwQwW2vW0B1kNXt3ghuhomhyY7eP4l+gD74INWfihpsa5GH49cViv51Urbj0GGM5aSkwlKN/OR7taFxjf9hHYMpgBEk4ya+oTL0xbK3hHjP0L7FwM4x/M5nCfzWi35wnkApgnl/wfbd75tp48sUNDL47pL+cSWd6aNWBaqxjLIxd9yOMUvwvNuwbw8g72N7lIJJ/v9nyh8Vvfes/FKBeQDC6uub6Fi7Ub3nHqMVcBT0BJuiNCR1n7wYX/+NHz++981L4vHGDG50fqE8/vwnNBT1Kf8Ob+0Rcxwgl238VvKgt32t5kGtCj5OTl381RGy8A0CQu1L/1BQnCy3PiskRTj70L72+4GOcPwv3y87+++u///b/zb+J+lWuf8Ocvw9lvBaFDjmoyC7/7n/q4SDcnGbzSSOak4Rxj1xEba+qOYc+1ra7aqlPd1sSaaDelkbfxHoPFBbPZ4HRO8PgNztJ8sd1x47BVT/xCBlcRivm4L3p4ikxtHN98MaqH44yOWvpGRqieWMGLD454YstS78ux8yNLZAIP58RiWp4B2/fgTp3KqlKmZHaQPLXowZS1JpzkGT41GjKq5b7Y9zjLBc/yyikDrOWEOz9SYtLxudlzCN8HTnB07HmHloeA+eIPIwYw259ZmiM2lOBeWKaO0mab72KmV3jNu51MZL49ZrI0/t3KPeLMZUhYeU6Q0c5msrzZ7+C2ypcquN8C80Ue+UWUq4LcTixhvc9Dp4+rcx/up3b49aAT308l0R/v4+ZFQxQwVJaN7aR/o9XyVshV/Cj9on/LlX25WyUBpelx0RsAD2eMdiJ760gPt1eTW13BDdyJd1lj29ulx39shobHPQSHBA1Vt5ldrwj1jP8krLa4rtbV+AW+t3OznixVUTJyofP8FfeKXkFNQIVLtBqqbxtYQcZ65xUVCuoBaYFwoC4bfNnBacxpRpAlTsbJOUU2IAvWK6LLD47lM3PywGeR8JF2ckmhxvrRVNcKmPyr1QDJRn/mEx9qc1QOQHx8h8MV2442f/GS6ljERMcmwdG7NZ+eGbUay20BCStXtm99IeixXV09KhNZthdv+k/9q5EE6Mn3bDo5fRYwvuWcvoOE5xwneAYj3/rdj4VYMO7G9vLGJAd7tCWWsb1e/lZMPHXNubm6Dm0n+K/r2iRu5Z1m29vGLNW15z2Z+uM2i8V6biTBalNr0wTavlPJ1kL8q3nj8DPf89o8GLdnyJpeze5AcDmCx2e2Ej4VxuFtemsSoL+z1uSd3jRMPcu9e8AZasjGJ4jkzIPPkwyE2m998U9s71i7bg4cPcp7p2uObJDibWZ6XCTw9vYv/Ao70bLuba29rC/q5v7n6uwxjY7hruBd96iZ11oTJ0mP/clRaYZuVR6PpiF5xsQyO7l0tEVry54UDLjegWePczkGadJszMe+ODHRXeyyCTq0Wtkkxl691z7Y89MnBMVszXUZ+Oid4wM7fDMWu5Xh2WO+NXUfx4SVmXU5V995UiRpurF5lI9xhjyJ9bwuKVuWrrLfY6QlDqMLlYT1x7ECg39y6j9BvY0ZyObwlZCtULepNgb/hsQGNFm9mRsFiO8kvbElQlcZ8RFgRN+tNYwcU3+0jNts9JrYmH3nGpx/0C0XqvXhJuPgmEHAspvs65c3GzT47jAQBs8Zw/FNPneJnQtdf5c6T1LLih9IeXi3eOm/zjvDPPHkHeHW1pNy33lSm4mvmrcf6+872tRJjtbAjAvxfVebj9fbp+T6k7+2zgsK1OPt5saRiZSVG3sW5hzuJsg2LvLqgytzhhclPEHf6ksBfGyEsmqf+L39X/N/23/Ou+ZcnP+Sj7fDyV++96/W5wWH/mE8/p0a/G7Mj7Y/fs8P755TnxcGoR6t5OGcst+mz5xw5hlrVw/G8BmDtpnD1dtCIz5ignG4lwWSatQFH6bZj64mri7TBsKtirFrF6iJQS1OBrFpxWcRX/VuFCompxyQ1EcCr4E4XNqmYuYk5wdKJ5kzTu4BwSEGKLZAunPVWACQga2TrfdjY9/z9eN+N3nhHDrjySITebVUM1PuJ8/jM6DJBfc5hieK+OEKbnOo11jC8ZttMmX3cG38xgp6NqRveQ//0FV1+W+GqegYOkEH52qlBANsMI3osubxjw5gYtBtWCzDtS/AD9WhXZzHyuCStZ7crzE5A95UIwncVEa/c7sXRu2Z5BtMc231IQFTYxnPOqy8akl0bNx//Z7/iNH71XmRdnRYR6Do5QVR7kG9P0os1Py0f9E1LzBszuo2S0yvkMrx3OF+PK71yqe7/NYcjUhnwGnvmOdn7Wsr5nrq73ZvByp6+rza6KWYwOHr+b4ZsJEfp99HMw7pSJux2Wf5Bfgiips6MacRZGO7fGLI6/PFcn+3Nzpimo0w5oEzlSVlyaLHTVHZdkKaFkzIYlXNSRbfqpiA08C1mwcJg+/RqYBzVAcER/y9k2/RysjG/UhvC7Cto/yniuAqsTmx70Fjrm4mGd5pJedrMxu2uUNbn5zUka/tLza1aWWB7iLhr/8T34DhSbC9gdPw2Rs7GIgMerIRRy8zNoeLyW9v9BUzoKZmW9EffWmPjkPMREuNAe85lpm7Hh3t01b/aA/ococxGo3DLnO39tXzZnLkRMCj3azFGQJDlsD/0j/1NEexw+GNh8yJAWNwdA6HqCzaV3DUsFu8HY1lnhzgx+48vNsH9XEOARi70CHaOATs3HwGZGYM+TOMmZ4OF3bx+GPztmgxmcsRP2vc+dqO7H4c9S7u4UYXA66taXnIZW7zZCaUfVStsM25PJJJeXQRCKe8wZELyu0lvNINx2qqvbpI7Z0f1ODOnSSGqRvz5CJWj4nWTugch8m1ZWyJrDvKuX4YeOLEF9zn/NgHgg3EfeoAN2yZYB9Zm8S6XaizvTnOBWfv74mRdyJWL1hrPv0QhIhiyS+PwioIvnytixKqsxbgzAzU11hytwIQV8sStYTJC/LpMejGVk75pYm9+dZf68g2FX2ZNc6mP3HU+uVYLvKsbnMOH/iuMTDbiOJrmVh7edKKb/8Tg0+ijQhu8fpiT4riMp9mF9NzIoSOZXDPJqNysz2hcx5hgiuj5yQ6mMWf/T7mlWHzsOdiscMLZ3lYzxM6LybhRvOj25DynFpiUwHA8aOBJ4ZkoYRvo/GPPGnhf48PWl7h2fhR/fweJRfqfESc+xxLRwA/6MneFNH+pFo6qc6TNC6MA8qlcr4Snzl6O/qCAXNMXAyD+tvfftD9NS9UNF3hz9YntQgbLtdEQ639AUdvj0Xg+UJbn6xnPgHYGR4v5rHzu+a/8gfheOf8v//bd9H5BAD/xu77/Cs1/vr8/lqCf7E5ebTRHzueduXC/A//BRufjGj+vb9Wi1mx01ZeUPhrwWoLgPh3bB+P5nVKtovso6flQdJzBu8nX+zzuLnh65c//YCGKKozOLuee62r7vKDEgcQQoY62unlvrVNXDC9L+dsAUWu4crefJKVx6mowaNpE3psV+ryEdH59m85dn9z1LIaXcEZWavNnnERMKPnUxVgbS1M8qOeB4sJLdT1xQUXLTv21TvY8jx085xZO/UnRTu2Om7/yNgR20hpvRyt9W1cc6hjfKAMBOrUwlofxGOTgQTR5q8Hcf7gZh97o3ocDIKPEQe+jqJ2BaeWwewLhbaV+NiXkQxgV2uPNaCwqKUB1XPvC9HfQINBTwzrQyeGDFyk86tBvZsLT+4f+6tDgfAcILn8WxUT215mEVraoy6Fwq75+LZL6x4lPmSBxV99rO7YEugL+SS0SYtZZpAd4hpQTTE3b7aB2XuO28sz1DI8mPaUOPizfx5jm2348MJhI9ZWUvMBHonVJxsB44AbELtMTNdzRAt5V0Mw/SvuZsxK4rZwQTZzE4awIibZGzem1++BREmGOgYDd9cY1giqJ4eWYPaQFGIEoMBenEsP6pvvozklbHnNXJ5QLisQBwZGcuwDIaiWehs5zVpol5KFKd+r5Rx4KPOz6/rbB0io1RweHIB8bw8ENBaw6ADQmJWczvAhgp+JRws8wW5unfg31xhUIy2s9Z8bwRyzcUB6Oc2tEu1kH2Vnv3GDqqbRbA4ABBqsaEPuJjaDn1qE7zFZZHu6ebAyd0AB/6jaXBxnzXqQ0NXpGQwLWJ+EMcfOcSMHkHeP4fZ8gAnYnhabta6HZHgg7jGCeUdso+FkRMQMfPDyA2x727qLY1t/mcRThH2oPnUHVf3lOvkghpscYPLVmibf6MFvxpPQAECtS6cU5RsNouBgrXuY1Dc5YAYCwHyDHe49dgLkAphBTqHl7Hk6Nvjm1Uug4Hwy46Ibw58c7RlQwNmfGu5RArO3hx4fBdiDzpqLDK7BT+3YlonzFP8pAWcG62fz8BatP9PVsIw+FiQU+4OkCNetLTl59jTD3Nmoif263M/5Imc2Jn4D4+fJz8R01+rIuJxEbM3Mi8uWibmxZtjrmbq7CRszEib0ECwRMYTE7y58e95PZFyrK4ghXW3HVwra9UgaYpkJJRjbjvrdzrGGV9RznEVDnNGLtOEYG5zLPSg5ajesooLTT41zDPyIu6KDc08jggrGUt0Q5aS+oWQHtPdPvIPdd9KB+iIUeT6wgqVqTGL3whk9MpjaFwfIyG2Aj5Dz5DF/Sy2Xj1wIEpeae4d2NPhCQZxw+3vcUCaed4oIyjQjKmPvfPqgSpwEZJtd9ZEDixsmnRrfd7n9ODs1xMbvqX/Hx8YT5G3XZ78EGVBixdMpkixfNYGk6/qYjyQ+M9CLYAJ4yWAuhhE62mSEkr740fj8YbdcOH/3/Q/5qOr3X/3txx/9mD4X6vsOPR+Bp7d8+uG7vLO+mv7IH6j7c94954l7GE+eTGa0zyxWD2oYW8Pu1RiKOVznQqwNaIxxKRgNxFl66usehpkL12om43zhYrNrkUd+oI52tctg107PpAs/+c2pIRyF7blqCAfFVG4EWFfiim8NLGbWx/ZWcjAjqdKgnNsjBnnMc3OMcc7LcB9/tXqyeD4kfvqm3smrv4ZkmJgKHg2DhuPUiJhdV0uXOT5M8qMONXN8nuMWukaU/uXZGBsDzUDY9fhnMvXhG7W4Oyf3zJ3Mptg5hn85JwJSPBx7ZBoom+XPOTY4hJ3c+quPqKNzaAGaP7q3/9UzOUxSDK9lNT5B1Jng/ddmRZeDuede9PCvLR3BM0PpcriPcVIkZu4fBtvAHp9mnmNFjwL1Yh3G3BB48aA5Y5/7L1789F9rTm1vB0dVc+/iKKlS8p/zVQz5NSq6lQwrvc/4qG1qvRUKibV9evclDDt1BGa34KTPy509djWIIao2ghp3Y+UXMbbRB99yNB5/x+bec0FrnOd5lHk++wBmeYwPHsnflQTqrOYgvA2F9AaGdIqFZEVK2Hu6EakXxOCZAJ/4Lo2/SAoQRljgVJQJ+acZt5EtjgLEjKYbM7niNCa4hRKAbYcHYPh7IPEEMZBF74HCe21AD7BJAMzYXt10g81OreNYHFSUzM87dm07dCxP+0D89nblAGtcMhl4Y7bOq6EVLQ+y3h6ViVxbeSzPneBizTfHwmY8unwg+9CxAk0WQp2tLqbl6sVz62y74hm/tQI0JzFxPCq3nj3HP88jUpVrZl27hSdpTjOXF+vTg/ibuvim365iu36tw7c6zB+M0XLNcZgce3sYdpKLPudL1tasiKI8RuRJadtSMtAmED64Zl8nxmHXmehZg5cDSKeN0a931sJurwKu9279SGTisKjF+4qJi40E+sQUpWW0VP/yoWYVsc9IoZ89DWJjJ+9GTyJjLk0yjAYmy64uuPO1R7U81Yt/FNRgTo+IaZRWgcORBTE5sD2GOmfevM196+m6TK+OzYsuM3qwg1uBail/o3FMbWBH64ah65xX8S1N2Tdb+2Cvc/u3mNluv6+VrOVpDcltjo3qHry9fXKKp+9qXFysxEObAUYdjT42ufRqcnM1te/Li9OaB3/trXMT+hjIMQuevO/Y42hnLWYUoN2CiWFOrqm1Fm9rRRfDXA3wZOzxIEoCOJzjzHfWuyx/jMlp24YjiOIEokMSzKrY+3FPCUjAiUmmOQb6Yrtr3kXOs7tn8I4LFxp/5l1uLvrUx5O8jNKNIOKGV+fwgFEReZwBox+zj811NFZPe0W/+sMbQf1L6/nb7r5jzP8c5/kDF9IMcHJvrqk3TM7M78USPSje42E0BNVgbdn4JHZ5I4oeoJEL6q/z7NcX+4g9eefJM0VhJld4+s54fv8zCeRM+o8nc+FaheD9xACR5Ez/qImmJDo/+aN6eaecd/J/yP9rL1+PJX3gY+v96Ho+beDFOxfx/CG8X/3L8Vyc+y/g0BjOEGbMnGnG1VINC6mQ9ngCizX84Vq+6UPUPZyylSq5kNABinG1eGxYFjDeG8+MHyLlmXwCa9C3WrFTG3z8NPbxSs35F2+49nwirurm/MJ9bMyfGD0lXx72mxcuuI+C0fzmgqIIoopHr0VyTnHfrENjplmcdZk1YM6PraDiTghqTPZ9/kUMX8vz6CWx3G5gcVhTyHd9b0ejOSj5QJPaVX19DjIdnfrX7z42nkLAvfzQGI2BmjDAmdtOb9KdzxHSJyLAKg869W8euOA4a2p5sNaDwe9yb//aDjROALuIoBSPI3bZs50LYWI0uw8f94sEAGUXJ1OHWsg5/niOb0hcZ/72vbHl4uPr5y+3RwOPJf6BOPJw/8VPziPyMtDfY8r9GvgEhMM+DaZ6g48LO0NlwRYN185nFgfh8uDNvHn2SG3e7vd8XP7GESR1CDbvcuLISJLt/dYCAvs+jt5eTazC/i98ZVUrOYuqsVKq/1gENJ86cLTw9kggIDumNEz5T5xXjA8YMRyCxwfYgyLHkGDMsAUK2FUFaxfRzYl6DhiHeJunEpcT+RTetPeE6wk7jZmD0qoSSzjPHx4BTOWolLrmoNV0uQcSTAncZuOBfOP1Xw3vyYxrTwgOIKPbTNbnVHbcHuz2nq7MARYbZzjQU49waDKqm/k98ci1ORNn4YmdfvbGZfBBybV9zKK1ZqIN7828WPeluX7w5iO0NWxN2HExODddzY3gYPAtAZCsmqeR2xdT7ANR8rgOWn8491gZ22RNPvm2nt4ZmCj+sCSAmPLNbGNm73EGO+DmIvbit38fxyH+F/vW3I8fp1/BYO/Y/asJme3rgBS7msy3NYhD063n6BmOUSwCbWRcm+dLDJaFZ/xMOCrqwAmGJDNvjsGALUFwMw/eIZ4FP3OcoVs+rV2TAF7zuD0kH/04vQn37SNnFLHZwn3ykrpqm305Sbzxq3l8xsZfNiaZKW64uza3YpsbHAwnnF6MjUDme+yrKIaDiJfv54UNvEejNU0d+8wl7sszvUvyHtPWon/Kkk8dwSCGYW+qrcIBbz8yDXB7TEi9nViLFqU7W1r6Re7dyzm1wiEOLfD77OqLXFtHzM3qRL7XAg85GGS8hWmqBzeumph2jH3rw1htRfb4xmIAWVqTJ0Gwovb+ydhUHKy/TwyZI6jS3fsrmp9v+HtfAdDA2rbnmiYYCHFqyTR5jddGp9tr0bEtrx5EZUyosz0P0cFcv+ILnBB95LEXuMbhxzh5gsexy+i54Mw1AmAt3tmdJ+R8DFR0DNJkE6jnA6bNOzk3tx9zT/3+W7RcsObtH7b3iR+cS+nE94AhNJubLzixbR/ql0Ib70Ax1JU9F8z+jnouDPJSRSzpd3RvT8CpNTng9H+dk482ZMMFhf0aDSevfiH6KYj/ocygm1t/kn/F/zT3f9WHo3nR9af/C53/h84PH8n//oe/ffXj3/9u7G//7u+p8/H21UB71GKW2dCmaKEmpsqc9cKwM5C889Zco7bo6ak1txsCMvCd2xLzgIgFhcetBNgY3e7U1fqbwHgC1cN+JwatYfyxGT7MO2dvGDFzbJwee5Hm/0+2IVo/ZHu7ZC9Xdu13a9s+sC9aWFZLBsnExsV9+/YL5ObC5hBbrq1mXU0xvMYGJ3T5y00+LKuJ87DsqLqY1QVy6/tAhkSeCMC/mBpNoOQ+5tW/OX3hSx3tUxUKl1Q0fm4f1pzzP+693XEC8GVO/KznB5Z+6iaT2CjO+8vM5SNy7OonIEy90EaPTUtbsh9h57YJTp5w5j4KJD/kaRQhCVJ29mhjmbsRcWIbBI4UjMOfNUyuh3B24oSbn1heSOWj7aTnk0p5cY/HjSDx8SKPF+KbxCboVRczxbGNzq1L28CaD1y4grE2VnAGY9VONz574DuCa9r6iWneiZ2VvMt3bEtCBEngLvuWhF3tQIe4iOpY38YBaq3llnnjrGkrrL67KujL2jZn2W5N8lJ7vvJH4pSvwPPATsQkhBRRmqZAit1x4geBKGKOGKHZTAihLRgDBbMeJ54E3sKWRxUIGd6yE9VZ/a6DcY8pPx7gTFaX+yT5bH4ixBaXyDmJrhJ45DVjZ51Ws85u7hMkAbIN/8Rlh7zt8ayaAHt42iNKvjW3BiLhydg6aBqjzew+kHk+f3GB9Ia0nEZNrtH2BXcRxe8NC/E9UdvHF6OykUMN22+0fWZYzeFC14OlDPBFsJXVOrihU/fecIlsPCrKsrlwyJH9OZJj2/We20bTz0FaK0YYSJCxWDWwzpcPIEDEjOYumnxit3fGyBb3c/x6nt4cA8mOmiZXq5kt8TiquDqmLyeY5NXU2Z0LgSDx7Ro8lbw2MPtR0npaDGmXdwp31yMxHIN5d8cTAnOSe3sw2bfHFEkbyWWdb4ykbPC2pmPSwqZ1rb3IWVnGnJsx2eEAyMfosXpqHYf2+D+OoRrGRpLxj3mwN1ezwV1wPcTHMvnh6NgakjG+PU6vPnAeRvctYrF7PNpA6iuf/TSXWRP5JEZWcGs5Kic23ju0NVomhWTWIHGBuD48YUbXA5n5nn/x4BwBnh8sJBrXmU/3SEnufO/58/bI4zVNcj70SnNDIHKjK7j2iXUHcugh9qp0eWzGJfmeR6vVvXkR6LcxfSwhYdjqMv1U432KXJON/GqaGtZ3+WVCJWkcWz9ZwB/dJgwKB76j79bNRaT2+E8c9ce+gXLOcYBnh++sU9M3bPj4ZuLIkcETv9YByyrlqXPWcOWHC0r3NerzQlQzm2IXn6WD9fnI/mLQiw6zUTP93giX1lTLPfYlJIoxxyjh9iS1rHLqam+pV7BBe4G7GrlohqwX1OGLLrnz7BjMatr99t6/Yj9PlAlYu9GJI3cvwOOcddVlG5H7KQd+T54XLvgY/m/543E//PDjVz/kY+//+K//Jx9v/y6/t/6z/+vcvxqfMsxjPqufwma3xYPLj88xqAE149OOT0xWYx9UPQG7xh0SaxKfjZHDP3VhXTv7cseUePpmCozMWGS+9lk2Jv2kV0VO3slRa8MFZLOx7B0B9TzICh6KfvhMP/a9nZc3235LCl+5n/MOqnxh39F5GbD1+G69jS1vMHMA+jgy/SXohj8LjMue+dQAnBx2GEq/sAIhb71VqtV+bK/VcqlNsXoSah7do9W4cy4IaFuh3hG/vbSvocz+pmiMqrDnopzb196PwE8Yeg3qTCls8PmCGnVlzbHlMym+g6y/vSbj5+0PbCmzC09xm0Q9T8LVIY+JE9SEhigRHu4bFFwL3C0gMxcY7hD1YY8la+weRXSRJ2Nt+sfuXRM3YovpfSiRfOyeuP2xr8ZUjteK0doXSyBXCdTlSjbzZWM9pFhfsEVjmBEDPRNEHiaCBjv8C+/+nuO6m+AQsoRirxnQCE4YqEx6bg5u8TpYTA3aFZPZjgTjD4F8cZvLFXFTA/BNaP7FFy3b+Pcc2trh8B10GD4IiaISdvkhAL8Dsi/uUBejEGEB5bsJY5iDz14tmAbck8cg6auDqcjJm6ISWz7sQUlbzJXW9VE7NbSK5Wyuy4dOfM3RV+xYmuAcXE8yUaMlJyfDjH2Uco2VE2KUqVlc4VOPUHM0nuyMASX69mGwsexx2P3CuVHT4t5YytG+Jjb2PfBdNI2SdU+u6S/Zts8nT0NwqIG88u++Qdk2wqUrM3qnoz4cmfQOFs3TJSV3vbl9R1m8aZl1slgKm0FWBzv8J0eXbNcFTgomGUYGv8dXrhiPjgfd6kwwhXEeVvfW0rhyvxyLg04G99VFX7Exbo6uRVtPRG0Ro48gTDWHaw/qYVuOT1bwjuR1lKDzsHnuDehAvsCgi+hzHvAEVfB/OneLlnLuO+yzIfRgyacfaAjXWht3ObZbZGK8OljtsajDJOI2z8bjp2XmmXycO3t7MggtcIoK/ktdevcYZB/Oo3vOK+Mzb38AtL7ys9z11A82o+dMwy5GhxzoP7XywI7hjK7U7XEJdmoopDqqKZbVQH2Zb08I5eJjeciglvPgPP2OY89x9lkdbasEm4P6PjQNYu1wkeeczw1jq32WRNkpNhWszrJtNjDtr3XN+TcUYagfdHPW0xqmbjzTF2sUcjkXK9dqppb/MIy3Tpwq+wvqarr+lne1btDq0X+Mrab1hm20J53zPHudfs265D2uYic+tXisscFtTZLM/D0awxUs5PvRa/6yOR/X7LsyezEeCDhJ2e35X24Y1Cgsq3zDt31e7l6cQsJHw0vGR7qRWanERrsuWTOvNlIoNbG44ZKf/ToJbFixuXETw+MsPDg/1zGZKx7emuLZLwPQ7PeieeuBh98Hn6ze9+zx+ubb/n933smyvmD9t24rqqw3ftKgi3r4qDo6/p2L8n60/fevfszH3v+WPxT30z//6Ufgf80757/9+1+nvxyLHYduDc/eXkWPXbAXZO0Ya3w5rlg57AGuvaiey3tMJzSgABNCJEM1mOacte+pjf0er8NrLHFGGV8Wp7VquP56SFk9gsK/cZuvnOQtFoAsg2Vu1AaisYhNYUAzF43BOgd7NMjUGsF4PoTl5HBeJv6TS7YAACAASURBVMiP2vAU9dQzXOBOxPTOWrgfX8fYAXrfO/Y9Ri7ZJE0z3cVAddqzGIjbx9K3Ny+WXKv/1PnYwFpW9tMA99vbauN8nwtz7yc2Nx9vR2wyzI8dZx46blNo5b8Z7rvFfCImf28ydk7azIMBy4b96RUmHbUD2QbXPNvJyydYjmagNiGYfbwQFwekQyxGHDkmHtpj67SZiM23DcucwTwk0MFl7cPTDmhMH/JH49K33ndiMzC7+uWSbDLF7LECRk42GeIx8ckFYjFDIV8W7kWCYuK4cbGNuV0nQVUDvBF3tbGV0h6tHvJ5cU5smiBbbHvO7PGArWMtZMocvSZN7NF+OgdEzjMJFu+bh7jNvVlkX77omsM9+UwYqGT9I3ElrZhD+BAAPgIfEQhbQe6Hu/MtdmV13wO7hbdCT6DhAiUNDeVBdzlZ45yNjR/fARk7DRK7B6Nh6GL0AMU2NUKJ78Me6NUK560VGkPZgGOTAUZ5rtgkTkz9Bs3RWBweuTK50TeuuDnIWWxcU7RWbpTymAYEExewF5o9OtGzdY/jQhcdjLWvomcNnb4klQ9ejg1FPPmrovpwUWTjAI13jimx+HJvWlfc9ELb4cZH3B0wveKN0UTe5uj2QcHdQKPd7Dq+5lzXOkgNU0ZMHu/szQFZNII8GHKbR9DNR43g3F6N1FWa8HyIAwk/AWwmcni0xkzeIu9xEI1mtUkAfEZ6m6+yxTTuXcv1obVhl0X2z0DzoCU/AieHGjZtnMGhtvnN5BzE9s9jYMhTF/6xIbjzI13eRRB/IuexwtCHE4KjAbLguB2hfSWj55wPvAn28EJlF4LZBwHp184+eIb1Ejt8pNtaISmv0L9uhsNkrzd22ZuCJA5z/QWMM3g1kG/gy53gq1WoADU29Bg5cnwf/XjkDRAty50poz2evY0lHuAQ25PVY4gbvI1qrtujFdQjXBr4GPH5fY/beQyZlKvHg0wIWvjxOA6FJwK+VQBQatMxm+639s07OYiDc8tsLVLYt1NLHE09tWQB1vBsd14vVkb29rErpubqcvgGq4A4wOTnIy8m7ffYX38yQmGM7yeVQxMfhZx3qAq4NYVwVW4879z2XMkN7PzSI4lDaQ7yc+PbyDgy94s99nFZdtb9/+35X73mm9t6KPGT65ybrHO75Z1hfi9+7b5jBq1PJMmHmoyTN3Gz1o6Lr+DgaJ/y5J0vnsDHQW6iug+e3InRz0UDHHl8+/ICnVgupPevJuPvxTu605dE+nvkmfnX2L9vHVxQVMfiAsjYj8w3V9819yIpvn/845/5g3E/fPX3XJz/9M9/eNH+a94993fO429fW/u2ROHWBvuM04esKXjqPzGLYw92eqRentNh5oKF1y+eID1nnRWGcLe/jTPWTYEeUzCvLYul4RjhZd8RzzmGtZgmU1kmcI8zRCd24oYIl0Pm04eeDzhG1cU464ZYlB0tI0Ktw0Xt/4evN11yNUeSLGO5kRlZ2cuPnvd/whmR6arsqox99Bw1A8AbKQN3/wDYoqZmAOkESadv9I7qu5kYAQjFm2cx93fS8ROznNCZE/gDhh2PvzCz5swRDoDiTL3N0muIvnEzOjwcgD2+7a5d00JaH/XBY50rVXUvkfvuG7QhUhtyoMUnep/kioInpLjP4fbkk27c9gjY7+Y3yL9Gxlu7aRzMuY/gPsEnwcKHW+13+Z+P/g5JsFOD2HP7ti239IGzueeCw9yciD/jJeA6TwYqc6GkmHbvwVsnFWKm+OiWB35FZtQmreF2dOCqXsnMvP8LXm6T/DnOrqn5JopzfCEyOUTo452LxDpMwIlSv8qaZ7mBs5ZIdiy+893Do6Ez7sgTm/uN4wgIRGK31X/joUa5OrhvHpur7pNTwQbyiUsMqWSA3/5u621huAFktPbEwYf21gf/t57jVkNiwpGWDca7V/nYUW+YWZ/PFuMPZ50eyQAZHDLMH/wt7NdJL0H8umCMIFXsocdviyYSzWqx2OLUeopg7OuvHYgWqQVc2UWbkNLeYmZyCMxQ2DLoNX6zUKU8ccPBeNsPfIQDGe/hcxICavPeHOy3NlE7b6f5RRvPkWJHS4zbGnPnu1bFrN1rXbs3NpLB3SH4OLEQ49y1737BesSzJ2aWTjtwtg6xVLucN1SF1z96RL1BCHBiMKPd/bTxqXvZLGwtq18dnkiuf63fbLSAc2rcXEEiIfpcGNboco5czprcmuLffYlb9wbzmgmoXmwxrx11W8ztr12xsBGLy7GHy+h1qM1iFFU3nBzc+lTiL3WSXMwMXY+Jh5M+zkv8rPfRCW3JupZlUOuMwU5nLYfntRjfk8fOJ668u0blOPlCeU0DXk7Eaoaoersdu5KpB1zytZ8PoO2pz4OL4tRmOeDbym59d523JxR+rRvj4YI8rQybx2Ig33xWv7JS37yj1ZALTOzsNy6iFjwWPuJoFHlvEI2kZjb64pYvfIoucWtrLUmERr3p8rN7wZ51xj+5W4sa4HHbq3tsJxMJHd94GREa8yDzrvNw5WAgn/QYy2H8nJZPySLIT9qpsetb2SqBWYTmDWwd9WMBmCa2tgezfuuDjfWoVa7M6opnZ0Mb183DMZfopl72etd/dfjYzOPWvg/WqyKCPMZ2XSpLBgimDgPjdL3X3tpjzlqoDIJKZrx9slDFWl5RadN58+nfY0dRFMPHOXVl7/WBpCrzh1N/kkewwDDivgJdU+UcfuVB2Pxgh88eUjWtUD3HccGxCR5xlte+EqdsYpoKLrGCJ9i/MUn/q69sZ27/u/8K7bc8iQDfn3/62bei88FtP//0U2z6yhZ/U0/jFXC4f4meg8QPf/nBD3j7fp6AYK3AJQ54X/JBcD/8+IOf1M7b2v/b//yf/u05r6j/8s//7JMAEJcw/PI9PKcqyYF9UV0T0ky1eyP+9tox0roOYhWJonUfZL7jmBr+wON78apEdg27qo1y8CQWs4lNWNrl0rlMNtf4NFWw/R6f+E39gANDPGhsY6zPcGUOLslMYzRm9keOXxTqcMnX5vEaqo+tsGUw5WBtQatSuxd8HM1h/I6aWAbp/hB8lN6erE3rIkPWaTww0xf8jHYd1lp7LNRTiqkNHOAbubS54TGN4ZjWVekxHZt0Jnssx4ono/qEF4dybhPcVn7Ln3NwOOf2BHif5CLWccsgk2DyBYc+YResPPHok2FRc/vrk/a5D8q/boQVtwvTEGwmw21zJZC3n1oa1PrE/MnWuCj3TwithbgJbo8W0kScbqZ0TaH816T9yF4fxrShrL/j2Fbs7yhNfGs7o2kY5Ge5d0+tEkgwZi+VQHPjvn/vYAuh0y1dyRw86viR9zOFAC166gwb90Tm8nK6/sXFZLH1wRb/eLtWB6twEyGTbc2LmSEDaOTBAH85HI/JQdU6Ckxs7POjvwMFmw7m5LUcNY7Sf7OGYxUZ+D39Qa271zjxSx17Wjff3RQ+KDRqMKa92Ot34pAp9vzCPePITGQAiMlwYjK86PhO9jvEVJtaHVvjhDs6x7gyU9A+01pMjOusrdP4rh845gwErMADMpuzd8KLxgJ30U+NYquMHj40fBkOjHgjepWamUNG05vKwBSimyru5tSNGXOcCaJRbTYfNQdv+MW7pjpiYitn9gIUzD6BPm2Y4ctlYziPSF38kI/3GKNcqwdyC102xR0cqtz8yvXUhNDkQ0tAY828VOsH79d/feS1/PAnzokMZtd3a3rwC27MNSdf49CnXZzLwZp4x0Zd9ajxXJtJPTfnT4ObK3Jm5cwkMzDTw1f82ac1nFxwpI39WxcQvZ1u3s6mJg0WR7MQYnOwnubz3HYMilnz1AuK9fR6arTYTw5vLW/EjR4HfYpmDoM8wDHEoGbmlanrF0fCgF/vtSLPHdNHb07xjuHJcfIsctdW3IAWH8/+cF+6dgjFQBd5Y9VOhxVEb5Mjq/EZA97+GK/o5QbW5PTgR6QUuM3hhpqRscrVeLDjOzU8c3OBmYnYYaQF8Vw7g9z9h3lwisGkbq1LVH+6LTQe+Q3y4SwQPMF48lMEt60/aUxrRnriFGnw8ZXr1SL7utUcHvVf6xMn8r0bKx8SnRjJWP7GepG7PpPGU5dI+l0Mocrp4AwMvsuFfmMjp+lF3E6P7Uzt6r8W+OilN6WBzHfZ9O+HIWFF3UyxJlzN00EgeNX01PfYl4t7QHBi5RVyXiXmKy8kX1x0OSDPvnCdAA8nDtcO0aVRF779ACQEccWbi37hgiV8/mChfFW6spNEZG1dL165ftvGb+jmj28P7WAXHz07F/l3eSfBz/nUdP4m/J//9V8eqH/5+ZfA9nD90z//6QHhr/kgt1/y9nMO0z/kX6ER+//9f/7vb/7t73//5p//5xf/jvyPP340yLd8cH70HDDwIxr/+5x/ocbfmf8tPrx6jv6//vGPfFDcT61XeO3+gCs8d32slaw3Y5IxkRXYs0Y0+midWfsjHaRR0mFl34mSvSyeQGsHjxAcCPutvX7REeViXnukcpv9QQ5IypScqwfHGsze0iQX4ww+NrYEOrECtTWrTzEZG6dFXTeDLNet2aAK+soOLgZwwJH28Fl+8hl5H4/EDP7ac5k6KAFr1yD1wC8/WulgiPLXEywQghHwmoAeWSb7xCj+tijOuwHRD7b2jotw9kmm5Yy8+NhOINJ1rBbsCPaJKHpeQf81tyEO6RzK/fOOsdvY3S8EAriNf8nI/YYH83xo2vkTkpXBhXxJMq08BmA4tRvOFiOGmKCYthw6xXYxWkONedWdAOMLlGF3nn3pcIthgCHxxsGItvF3vqJxabd7oua+qwh2CVzOzz6J/PADS4DJ20mpyzIx35xL4e4ds47/xmHtgaMJax2LDerstBqcq0EadOJbIDEWLXh5sgC5axi7w+vx6d6b2OI/a7TMwok81v88RsHehdJxKWB4ctFvcJCCZL8PENCBL20u/OwB3SEQaQtKmCmSpt4xRyYArhvyTQSAsakaQdvX88EpttdSynBUN8YWMkimFYOFY650bHbBR3wNY0Vh8ZP72hdxghYLGx0NQrBEGXstEImUEu/iW+jaChZ7bJdHMYEaLJ5hor4xWJ3YmRtKqGjy3dhjZacQhTzNK1jALU9CY1qL9kzkrSITlNOaD6Jdz/E+IBkknlOG8XMtFkC4BzDy3mnHWNfFjY1Ex5Epw7UBAv3Omc4vzKq0zkZuj50j6g2/+FqDp75/qsnYWf+Arh6cyog0/IlNozN/BxUMV3+5KRm/xU/Pl8VCP3kry1yFGEDXt2Gah5HF0Lke2o0eF90uIhxpGwuDw7iq+kT4xiI+82MbP6COjai4YhdpFfbeqWS+GA2T68TTfngh1DV4i4UZspAeDGda1CqqXe+F3TwPFwBivXEMUgKLVlHisw7YwsWYEz/mrVtzx2bnjhMLHzwrr96YE68Ri3fk4AAQbo23VgjLxX6Ho16r1ruR139N5QLGGicGw6snRhua638t6lEIpe7TAQSami7+DLbO2N/9wKjR0Su/jmdt+kvoaut1AvxL7mRALHOwR7LrcHOuTWzPXorZO8bNVkuutLLuSM3wbzwY1l67rU9Ey/r6DxhQaeJHuTk6h7daFZl9ogCvKP3HfcvcBrSWHwGK1NsHSItlAC/lHkjWMY3asBe3nVoZr3u8qNAYHxiP0AfoiHPYQ7T7g1eaXPcscHtuzxNvghHa+Bs8+Hv/3gA5xMaIX6uGpM//AaaDTbv0sTEv+uHl/xMGf+6zT57axhNdXD045JDcvPsWft6Q6t/JEwAb5ozj27rVvqIn5v5+QLFvQ4wMX3PnSYDg+TeoETYOtn98w0H8l/x9OA+KebKDD4X7Ia/c/S0HaQ7WP+Rvxf/XD/+XcnLiEOG/cktPY/59Dt/w+4NXDflb9ozJi0M5/t9/n0N6el5l/Om/fspPXjXPgYZ/Scffon+Zt8yD51p/7DGkaZtMBxhaF3uH1MhnUdKjYr0wwtUqdl7R9Y2qtdX04i4wfbDoznoczAEj93FvpEwQzKQ61tJgx3ZcNLvYrGtm1FCY+nUOwo2Fv9hjmwV8eDaWMc7+OZTGL+YxaxzSrM/msj16HDZy9yza8hFB47JbnEU+8+Gx/vQeMIhLm/hrvxFUadCaHMKRHRsXXSMvxoh2kGPYOp4slsvgbiceTrMHyWib+VswPkOi+9y3s3Mwz6vmPNnFE1m/Zs5thDVz3cgTJhtT/KAiype3m+g41HM4/42Q5IMBH6GNXV6M93+BMzGvMrNWw3FdGmtXK+Z6BGPi4y/oXJsXIblnMLgmxca71jyxR8PClqnj4MK3NY+mZsdw1MpRGR0u+eq8iIu77vvOA/PZgPjEYOvqMsVxlit4xS2fUqEuYN/7eMBiOWQWSyPj9HLkTCc/+m3oac175ZDj++pqA8Rj8wQz39WFlLQyn9Gx3PV710UCXm7crcH6q16uUx8xQmdt5ZjLcqwvgvN/0IXJvMQsHqIAk5ZJMHKSRUhvIqP7E3AMh5Mk3M4DxC+rWWW9N3HAlzhxTiG6I4ZDmSw/sYIib4T5hotWc4dZIuOnJWYGwDjeuolyJh87j3zLbfM0QGS4yx+8xUZWg8LB6QA//EyiGtUzPBIpZ5Zvh1wIqEEiTF1O7oCoE+0dQtIHCQCZg5iZ8A1mI8y8NneTTD21A/toDGQtHWHHbOwjA9l56ln6Bs6jlNZTmfYZBb9znPBsJPxXh15d8lHufBk1em1jyWMYw+mFpfkdfSUjLt5ZZ0yhIKFG2gfKgLrm8HUNDFO0WRMnprAVqXq5d99OrfBJs072DQt3mt3DBdlZe+Wt28pYa9pZ50n/RvnEN0CUmxO+2J6QMxd31kWuEsN6WuYT6mIhy+3QumpGoHJbWyId7oOpvX7F/ORWI33AhNP4MT24yFOLfRBiPdAvH9Q4pNGbk+uHoPt1sQtPnfP11Jf54sp5/JQFVD3Is1fsP7iWwcZWD6GJs37yUJrLYGF17UFos+fSpCrMuLbvWqx9948z8y+WNed2GmTyoELbZO0lkqkHvK5FR+aFb7/lXg3OGVEv/a6nMYZH427UTwYNH78nbuNN6pHTNu93D43FAJNhc2y9Ix5eGKxf+4vd+GG4qUw+i7G3cVjzJVYum6m5xXfvV8QLGP4YoV/u5LgHAGs5j4jkjU4SN8JQikAUo8aqucBmamNMANFxwSjt+k9dRrF51Aq8uASL2ujvHN61ODVTuV709cFsX/UGrH7NG/lir528iTd/NwoSHIgDa/snFsPzCfKTlTXD3k93j5dvX6VPFOSS0NPh+8ByHyQTi2ZYYqyr0s8LnPsKXULyL99y//NTDhHJLq+K5/CcXPoqd9+GzqGbwzWy73JY/5K3sMthuIG3P0SiNhwyPJTMIV15FLwrgCcB/vHv/2H/e94mz7sJePsusfnf52ATkzN/d0vXHIyGBIh882NZYI4NbddxCoAoiq/3CWLa8ZuCuZ5VFW8Kahjl3QMMr4xZ4+MPZxidtQvGlZcrHvicruQ7H/+htFbRNeLmUu7Euvnt7OA+3gMuF8a9LbReERY+coaAbi2Kv9HxTIuwj0c0zLRWzWjy0mxz16tW1ijzCWltZi/VCl0xrOQZR2645Vzr1vZ4ngGMSrS5yFGat4K1EFRuZ806u/sNJPdC89EvG5TYHBzt51Vz3nnS/05wXz3/4JjU9hX/YpIrHKYzdXDzE/y+go6OPzkpDz4Jggk617GuuTY30pRucDfbiDIDoPVwHiO5pce+PD996oJsMTvY/QfOBHMYkHLaHunkhs53BkEwMrlJ1KSNv1iYQFab+Nnota+v+yMW+/kX2tSx5gShjWxm8oPLowqgkZS96/XAHc7Itm70i9NR+BiQWSVHH9tdA502JmYn0KxJ7gcf9+pjtznD1/0z/fJoROLEdmrV3/04D7OHB7o/5Tt+xLA1Yf3nLe7DNjvRZ5fBbshccdKjI3QBvEGawtpAijt0/T7sFidwIeIM0yUFswi7iZjQFBj94CPFOa2s6MunMqRp2uRykh9RtQu9hhPjTDMY9PifV+8eX/WpNl/Eb9s5sw92x+5IM7h51H9xxLSO4JDI1Pup59a/m6bhrGWgVrZzAw3e6sDd+IyNbSjyZdBNR/2MlV6W0dXsrXnM9YgPcRjHbg9D5hNZVRAsPoKNpRMGQ4po9cMeQAC00qZ5IEQ1XI/B2OG0fDxsFMAMUGEvdnHAlPeRF2ft9oZnXYn7cMXyzoeTeJe2I3w2T8IWVC7yAujwwKN1ONjri5l3KoKc2BnA3nb1I0hnLqcumcUY7OMz8fAocvviWqz4hNM8yaKR3lh/1QYbabXE6VddJmPjl8HuHyliZMgXuxmg33rh031EpMcnuHiiEwZ1BIxPi26CPDkt8le2sTzrEBTrBhhFpIk1PgM7y1vbyyKjZVTfxZ0FEUoNOMTK13qgrBeqjCZuLUfGBB/Wau0XYGRYWG9jMMNj+WcE9My3vzbDIIrlhm5DMKapy++D12ZRy4tKoK0UH9bLeMSHe/ge2WBiZ4vh7nN8tm1e/j5DiB391iN967Z1JY4Gyo3PdEB3fSi1NR3GrG9tt86Lmx487MGZLD+y1bE7AYvNlXH9pjKDY1XE24ppiWMGlT1oglQzdgG98SsTsy9+Dt+pvd7QAIHWOm02+wSoyWGS+6LzbrIUsq+tDzV8qXvMrEXf5z7jCStEbJKLrxTzqrJBotjmmsW+BS3m5F6TiRBZXw3PPN91Q0erM6+2u6Z9MVq+hRpw7BhG6L9TC4hTIA5mx6diD5dGu3kDRjwOGP6P9ryy/d//x4/ffMn/Iv/r3370wT+voMvJ0IlHTcXMc9q//u5beMHl/5hT62LxSe19u+8v+ft1/vaWV+U5sO+rij1Y8ARBX1n/yx9/sSZfvv3BVx0TPPM8FMxm9nZDjmnNYepQkVcq0Vpw/arptDjjWyB9jvXIzvwMruLWAiUx393Y5albNP4+YrkSm0iBwbo8D7h59xKZoWb1+F2atrdnfd04b8ziaZfLiy838Aw9duMv8+Elv8iXZzHi1PABbf4DJcX9HVIdhsOppvruisCtvqt857UC5+BPvA3v7XT02O18e/AJeHO/NRE1wGcPSSExpVw++p38y42rPsQLOpbnvmQK416IYv/enAP1L7xyvq+e+66Q3iYu1/BkT8PXPIsuH2RGIhs4Rjf43N75E/Z8Kxcvt9vfI+c25Dw67DvGEWP65sK0MbFRbG+cGKOnMVo75tWnl1PnsGbOt22dnVSL7uAQkGbgDusrChQbhz1vXeBBG2D1mcUffqChOfjKKj1YWoLRNkhOFuPquiZluZZw28DINmpjO9vaptdrzGamIfUz/cmLmOe+AdQ3pwm3jx+w3Uau2maftXbVTMgjKusy6GPQMIUA8f1u/RYXHblsAuINqDmODhEY/TdrnUmonkIEYxYHsruYxp6gS+Qp5huYAKWTAGs7vRsR8XB95yuVVvRiENcHElMSlJHVr0DFSszEsMAxsVDMTy743bljiikvsm/U8h6c0S3H1sjw9SPMLCQc2qZGg4fsYIOXtrZyM0ZGS+XUDsty2py0H2l/obTO8iOKvhMgrj4BDjAiusRqnGGATb6YKdcwM2zBGr4qcUc/bWu9c2Kf9gyRdVquxotA8wCKSSwM5TdxccIuX67JOJjj8OoNA0eMnzVbEb7agvK0BFucxSC+VjHsHohA4fWUo8KxHZ/ZmWWxOagrRIZtQsWa+Pkq3uSHBXp+UOSH7kTf/JE4Rr8Yg0QdN36DCNK1qa15B5dWr1zB21dSwKg6fUYz4ckqcWZ++G+c+DTOOIt//ZHWZwDUX9nlRVbkiAfhZ15pZcSkhStmayNH5ZFhg1kM2hXQnBQ3z90fxzZ+zePaN8pgUp+9T4zJzan2hN+GZJjOCMnaEX8JPlbWc+2Wbe12bcU/uS9ibAbuT3EjECk+NMZbb21XH93JVcvPiyxzufd5uzaADtfhpefwMSJ+xi+HE4nY5JymfuyUSa645RslpuBkDYo3oojfvMDTln72rlE2PGJMrDfjq3jHk1WxCB8zLPWdAOLKqzj7xG4Rey3v8ds1nt4Y5DR1CLxN+cRc3caHkDXhdhvXl7O2H+sQkKGx2PR3H6O0es0rPFrvaw3+8rxQ45e1sAaZLg/neMAfLQL0Oxc6mJMzagw4pGOH2O2iPBfvn3aCfjykgHF0kRlf/8kB2bwNG4/l1xi1AdV49EzSeJDKkw3Uwd+jkWFTCwLw3bw9yGML6KyjseAUGYeJn3/6JR/S1v9DzlvPyZP6+xbXnAo4dPNKN4i/5CDOQfsf//GPbPPv/NC4//zP/xQHeA/jsQGXtp9W7xMcwfKT6yP3FXn+Hj2vnPv3ujnMfPsrzBIlyVjDyPrqIWSbg2kyTrBmGNVXzdQ+ZF3LynNlwE/AphPP2cS2tmIQp3ZOMyEu9eRKkxMLkGnXcOTeF8fAulen7UEYX0CwmcbI3PTDoxFVr2wO/8j0zEW/klGqPPONqcXEKU8RvdzbVGuF7VJyLZgYoHjaB3hE9gB1H1Z+0ZuBc/hsDun52nVsL2tNa1Ye6oiHT36cX9PYlze6xukeYYytByLWQ6Ylvu5ISbaYK20sZWDUqDXJ7V2YmHIb8ZVunnzi7815WzuvpHM4Hy66jsvAQKoYPvjN+GlrY20SmJx+y22Qdfgt/2rt28Q6hY7sWz/soZDg4mc7McCIJHMwxCXbxEauLANy1VdjcqtTp9QXCJK/TZ+xV0rMNNdoYhk4sofOMqwtuijltXdoau4F/bbGTA1AHFAzDg/ut9a0MrAnr3o0mAy2FkVuXRgXdOebS4tYW2ME199vxF2fKFq16SUeib9csAeVWsaQb0kWkyIU984bE+kYUmuNaiM3hsqjIFQv1tQLMjlqqGPRwsN6g9kYlRdDbnACe+JjxdOmJbHWqrcImZjIh3ISw716CHUYWcbMSL/laYFK8yCSqgAAIABJREFUGr2mj93OUU0xFbWAxY4mfhZ6zM3RSwSbmH0NtB1eOMPW0FK4cfrsyvKqHezLplhyD/bJATGxAdx8d6qqtpjRQDMbbLAfXuVYPXbANcflURm6bdqACKixx1ZM5Cwy1sjHrpkPxMNteCyDxWYdfBv6/NI7d7iTs+sUX7i+NdGvIBOrXXPKeH/RQeuxM5WoTw925lsnULZWa4W+BVPZcQRy85fDqGNImlDHtzfawUNEsw5jmKl1q6JX/MtILUJzVdsL8MZ2+tTYmpEsrV5yUbR5Bt9aI4xvvvqgLXNrkejyF6SyFdQF6PqtvOGMqddXd8aunetxgZeX8TO59Q8f4kwN3vrUO9etocHuBVuz1j8IwVVmXmtXxI1LLmQD9riJsVbbo3T/xbC2a13c1rTjXsHEkhbb4SL3uVNvHqgbX5uMl5s1cR534wMztmAGv7bDDcmpZe2WA3Y0PGzTKeEJvzT3fQfNNePm3PW5LkHdSfiB8dEyvX7FNZc1wiV7UJsMX+/lWdSrKTek/OBT/44VHVlzDlJNxV9PdSHPF+jWi/GpW2T7y+0DnKQaF7H+j48aTCao2BO5sZDs2mXY6XbpR/DREyktcU4yznOZ3OjwPALHstFnUdfi3CeZQezgK3594LrYxLTOg6lCKhM88ssbmLsm+JZb2RUC7EobZCwGU8vhcuyX58FuRPR6R45fx4VfCOW5uJ6CT45LYQ0b7GJkbt7kgD/4+NSCQZuK6NOj7p5nrHExZrwkV8e8VrcHzlkHnWE0t/mv7c9eg0Ba53mwnwf6v+UPXPn/43/7+7/l/v27HjB+/RkjD9d/8LJdDuIc0n/550/5/+W/5EPk/tm38OYw4ie8c8jPoZy/N+dQwuFk2bLWHOj7YXEk079rl0cwf8vHyKPbD6SD4dD85vsWs68Qxmb/xICa7OpaywqAbrMWtdlcUTw7IOs1xum8GW9QDAPUStWLXE68jMUklQdzedSP6+Bjo20x69PVpTa2CsUlTm4dflV3YzMf07OXTk4LFQPu+2kV9br7idlG0CiIO7d+mkcWbsDIZOsxfMUq7MSYWCba2GBjN2Z3vOoJZq7gT9xVO+UiD6T5caE2VkXN/8bqHNvmJYFMSw15xnPGbJkI0uo4ih4fxrTmkJl8I9Co8j2cs/bs/R7M+3b3Go7xU5dGEhh4gKx19+nEjf2pXbCtYn735ujvq5fEAdLbQw7sHFW/zyH9VJuw0/a+FntbelIppVSLeb7a6O8MWe1YnwKUTcaZH0tUuNakJcqYnFbMutRX1Cj7JMPKRyoQ/AARNuPGPtEaN/En3LnvLVmQAJhueOxj12omHwNhaCQGh28pnAjPE//l43qNv0wGYusNF0Wx2dotfntWq/hgaTO00UOk9YqN37kcWXmiYFnKhdmt0UBfHw0L3FjN0FiK67v8Nye5CVaOzPNv1iC4bMdxIup4VSd5zUkUO/zT1nbNK618i2Jyoxi38ayXhM+h4RYArfjpV/qRHNVEB7F8F5sSXj8UyGupcfUUc6S1z3Qkp7ixWe4n/jGOf+J+xMrk1AZOxsBsNwfWDXLxmiHzzW15rQZU9NoYA5DKmnM0A73xzxMQ0mwNbsb150rDR2z63KNuzpmaY/O4/LjTbY3wLvbmKvf4+Ytn8jav2B2SyAWvv74nAQmrh1NbR8uzMbEbtTeMTk6tR2UH9tpotvGZfGIvrzGzHrsulIMfrww0Ahou4FTw2o/Jk68Ag1GtV2pyDkoDfmJgwRqlYTcsTvyR00HKA2onXvtLsoLWJ2MpgzXyBVMV6ehXO2axqo+MtCmzMuw+wnZrwdgYrMFpm8F4pX7yin6talH9YlHmPoCInNiDp3jHg8X0fSVTDutxuIynYQBsPKHOOLINhEKTXApIlDN2z3PARifZo+p84h7X8W3uxdm9Q6DPUFMzhNOubQU7v/ikNA7pVw4S6Kjwoa3s9JGjOf6M82WO2ucyTTljsIyTXmeEZmF/+R0lBtPu3vnEqL/ayQXvto7k/OQn080t/eEXpzc/MeK3EYrJjJ+0wBOybL/KPbm6bprO+CZdP2zEAgQwsHL54EqcDUQkzLpWzkY3YeJfG+wcCRd77jv8HQq81q7tjgnL4lWDN235QSFjeMUAXO2G5/psX89cz5OL9Snzxz9A+FzGnYgfhbqxEXMMZak+AvR5oNl9OnyxO6d1PNNiT6l02E06mWxuasHDavqTbOa7NzBYeCCxtzkJuzjP0HBVlgClFxuM8P4tb1H/a/5F2o97OOeQ/QsfENdXzQueg3r+LpyDOW9j5y28rAXr6YE8Pa8gYss698/oewLa/cABnLi8xd+3tmOHjJ8Q5C3C8IbPN3/wyfHT/uhfO+aP4vuOAdb0yY+1MIYg8aGnhYs/1NpGvy97rnFEiIHUsbZcqZNyi3XMIpwQ8Tm1hAOcqImA2AxWZBuNvt7Raa/g3i48r8we0qTj5VbE+hDcORf5DxYd3NpNv6yuTbm880E/WIk93LGqPddPrCL0aszlpc/kwpg60mIEwu55xZH5mEAKXmpb8zi0htTM8fQ1wn7rdBwIOPwTDXwzKH9jYorCtn25YVq2tYdzBVXslvI2EB23A56A8l0m3g4aE+jGKpr1PLyilFh5ylBjq/PoomHPa55g2SPe1jLgre2/8Tfp0RP729+5PRGz9viM55ZOHbd7DvanZbh3SUQ/ZTkGF9N9Hl+8i/CJgwuSU9FMWi9wW0juuy6Hu3bVgpA2IN7PJZ6+yKaNunHiSDqtb0s35A4OczHGFoX2C/jg1mld97YdA9YBklySC1VwtRq84mi5H5Df9HqYO6M29LSXg/wic/2M07E2hESH07SOq3BFIoAPDR2j+gxX9mYUxa8G2+szXnDlezYFUlpTaG5zr7xhuiH0mmIATzsL0+kQa4BTQO1mkWe8BTaDlQ3GMLEDX1sXZ1OpYVmVCUlbYBZlxoc98wm0PUR3QTbs+jFfO2T3lYtib3R5MYnNaRa3883/1A2j1S9H8PFvyTrWjrWMHKgp9vI9Ityiw703wtXQt+EKDja03Wy9Q06W+BNEVy+xmo1fDV6q8R+YDHY9IwmIcdKfGiIY+w57NRZBD7ZmXqzDTmMCqvHquhp7dZtUJGVee82XE5oIivMJdLmQwugK1NjgF0yAj1friJk9iZ81hdXUhOrNN1LArUs5NJbjqCYcRphpd2LiO00qw7F1KbeO9W6Oc8UNHc08M+4+g1s1Z6202tj1wXU5jro4w8FHqJhyu6TplgvfER1f5O+c6a7b8KhJ9xxQOhtnZDEoHtfmcWseXQJurvbY61D7xcdXWPVFbLg7XltwXEcMJnp1Os9aoYkvIs1aaTnOHF2DKoghuF/JZo4pTRRgITsPGusU5RrVqoKpp/b4P/Xdtacge0AjAmMw5cI8X4xb18lDnGjCYQwzyBD58LixVKH0/hJ1sbfH50rv+iV25Ea0H8fBLx7YY8Nwg48N3D+bmTRwMI1qLlAIjvwjz5i2PBlh7Xz9jn5w9BgGU8NqMNwcMybOsV1+x1JTDVS1BmMeMZ6xjW7vp5ez9cAwseQ/cbZ+G2mxNJ3fncWKROD25Zhr9iW+4hzit1Yoywo/w2vNBG5bywjv+KMG9Uf/IInF/cUEV9scykbBXKAtCepMQ6Bz48ODr5eL9rXONTr44urXURxKxkBsjLXVIbIy02tCW69gyQXk5abRXMZt02SK2W+/5pWQ/OszDud8QJt/N5t/n8ZhGYZ8c9lXBnsICfPoORDwllv55gKer5DjZl1y15zDN829Ez1vh8fuu3wgnLXKBBvm2/BlW/PK/vy17c0p/7INPvi0MoMtiQCrhkvqfKeK5RAvU5rrdrq9EwTHn4Qmzsi5P2pOixfF4dAIAKBt3MzQkzxtTNRDFHF0eKDUKhf1SgYnGOq8XruYpKHZ2J0ZLz5XikmxfFKJ9YFXfKk79MogooysI3q+hc+gBDCwYU8ztZrG5JMLevEZLADxmAIwgQ9TwghYa+Sarflwft3P409Bc8HBFjZMjQezrgt5b364HPwZ7BwGpVdA4jiKP7/DPJxzW+Dt7MyHGz7NoatKPIGGVUEBW7mo1UbGbUmsAMkdwDTG/LcDWNhlRBxuv9w++XyMb/PfJWj3Ci8k6ZHndngwT0LwzMaGTmz2rfl40Y59pwtu3zjYVNm9kvEqhvu60lt7TdgHsyaZg4E5rnvTyPBiqb/2qzN0HNd/qIjt75YRnN9BOiYG0ATMwJjKa4zc8kxi3oYnIJWEBT5N3BEToIxbvMzAhlu+yJXmWPyxjpgaj/LaRnb4jU0xalvveH2lG9TiDehycC1xeGJmaExNrUdzMwrcs7cR6xTLHtAFIDm99Y2Ob9PUmTEAJKJ0dZSgQZRs8mKhQVqED39JbAEv6XMHa5xSIdyBXTKo1gbiGDw64ZWXdwEi1fQaaifUFGoCwYPhQEhkbZ3gs3lNPQoexRiq31DpmS/G5w1RpWjWNkbdRFgXQL8/cQre5rjITxw8u9lBzezgluLyrzzG2Ofn8tRB+V6qx6ixz36IonfexMGvzIlbHjvCFUljOTiXymt/czu1Cu7GO9zDeHMDxjVbPOo14+W9e1fbXPTmRpEHt47Ja3zk8WyAypfD5Be9e2V8/hRQeTz5Hj5f43eNCiD/GBg7os2g69xsXh1Y8NYDvyhnZl/UynZsL8hdE3Nf8oNT+9ZmVYAux65zgJaQDsWEg4ayKPqoUwe1UVNrxtN3eBMgF+qPBUG34TdyfPkCR9GabR/dtjtayfYbOPOJg20jjw3yBLDLRT0BM9g81sc5uoXdHmN94FvmWwv2nzliki/HGNHWf7jdKRGr7uDxmzj4UivxthaZf95Wy5xXBWzGSY7LJX6H05gUqkzqbSlgvhbpn3Ua7teqNdAYGNok1upWJMYoi821uM0pyq3LyRm2iMu7MQGZQOk2n391u8LSnA5ea4jcWOI6Q9HBVxxGWpyp4+Y3ns0jk10ffN6cDsevHddn7rfA0y8crP7ymzzJxnwwTCu3yIbXq7sW1LgzvQtcwXNtpRuBcVeHGLNOK5FL7Aaz3axoJpZvdAvP1LAhsuPFxcbloWeSJgY9XpnwSvExUjqWiLUbW33jY5zN4Lo2+vqMc3xo5dex12CsrGsSaWR//bcf/VR2Htz/+lMO5zl9uj+Hkv+/mVcH+eFgnp5XuVeObXH5NOk88M+/iUPm342jkFaYJtYexh3nA+D4f/Ie4tU1IHP0HHY4PxovrxIaJ3ie0QO7fgQ3DEWOHwEZnuJPHke9A2wwmyePVoxsVAOMEcNI12cwsVV25jVgir29ZLT092xHM4erACvt/N7uWkvmmBlmxkS6u+/6H5KInthrQY30pT/6e5taO2NlYg65NDbaapZ3Z7keLBg0d0blvnOsWyOQ5BK/PSOaTwEncG0XA9dFsM8eWUEtiyU28A6iyY17MbCrfK7Ws95qLpmEK+9NTQxI8I2LfY614XEP5wQgHnub24xMeXbKxxe+0k1M2vad9RDEfkxzbcBxNvYEjQzd7/mzFP+ELW9v79vdGxN8/6vD2EGyH0zps0oXO/ITI/AeyE0qt730RLQfjuTOcKbiaEQNht6QtS7VUaQ0fPPlnjGFO8YXd37G2n4hcbetMgpxXnlkXd8I+wBCvA/HBZwcNeA5QORiTwC6ke36F4fr8D5MEcV4fO7t6XI0LJf83BfYlI7fjht/92mlB7gAcs/QhkV9tDq6yo4JVq5nEXcdzlpgmBxe7ptPcwse2EszSjjmn2jiOPKNOUAEaatiwU/Q2B0bTCU/1CCLPv2BRYYZwfmaOBA00nABB8l6oqsFBsMFWfyMObHWL6omFDnYyNdrIhUPYBXLq276AzEPmk9s8GxlhDMjWqHKu5jxGnzrtoZGBuddrCq1F62X1mkEUb44m8ckli6xzTXI9p13zVZ3e1DX7tZt81Oby9ZtRqXdmoXy7geswSBhuwom08R0TsbrOqPJafWYnVqTgw3/jm+8Kyto9K7N+kzt8Y/81IViaRrZ/DIB01Dpm9677wYXA5WDn3FtwZfkcAwGPGIG51oXr/dnK4PWgNTduTxxklMGQnGZtY8Km9aBGtB0+LCp383DHNcuHs6Fv7XZld49IbZ5lyf6y15ql6csBJTOuYMcrvrtmLyDdPGaHzmjMhtMtiHPWPnKnO0k6OO0/mge6hrCgajbGJXD9oC0nVhj3noHMwHMJWZrvRigqIui/plnjx1foeu1vmW0QfCrp1g+oMUpeky2fuL0cq2Hj/xq3jXH7eUQjw0uRCYLz5wC0uUHLlsv4wx2Acg6+QW7a62D9QGC2v+pITz49V2OyDcmzvs7Y7lXNzaBMaZ8ZNbgIiz3Rq/2q1jY9dtSHA6DgueiFmWu+gTLaa4ahRM8wrkcq8Wkc2pRmXbc5+SrmRSitsVdHwtIrQjDIyvR0lnDP2NTP60GgBi0eiJk/OBkvBwQe99EvJHXm2lGur8YoJF31LNHF4vefKN0/MQxb53w3wZI0E6MjRwB31M7rDV5emXi7S5FkhYIYwE1euVIidVJeyZr5wAXhPmJ8drWZWbaV7J4iGguVYcAyYMH33woHJ/QjuxX3taevzXfd7YQz0N5XqbjAMD/cebT1/mAuF/S+z/LI3f/BJFXx3/P4d7HJmFIrt1/rT16XuXjYP19PhgO3R7Gz2F7/MSM3kNDnhAgw+98tT6rF15//A5ODiK+8j5ZkjT+9gxbK9MGYIsxA8ysHHgOZq5DL+fwPjLz4QmMOL9wxtx44E247QmO1LmBJ2ApF32MPR8Go7EilGftG2fIpCti0ZEWYm5DieNaoghGGcejUMMF5eZdv5MXnOGB8yBrPJeVNuaAPgYrWbzOVzqIma6eOORj/sHxtk+taLHD0+lAwA3n9dNuLrVd/ghv3hvv5hZ1gBsvQ24sa5R+XzmcsPIQMfHB+DiYa8S+7t7lX4n1cBwF+yZfZ11hRX1ZJ3LhRx5P/Mh6X9O6oMeOML4DwsM/bnmre24P3+Y2Qj34TId+sCJMSWawMzbWmTestzBAo+eAT2PqfmOcmB2DRU6jG3m6NtQ0Q+LDM+tVlrXaSMZh7OW0vroLUOPlHNGaGG8mloQoh0TdqAOxl5rSTM7yao/2ApnnPr5hQwz4In2FJvbqnAyciPpej7UrrykRToSRQy1GJF1xIhB21CvDoOEiUXf3EmvlY5Xk6Fg0rMdniyYCwtgJool43h4+5DcX3PoK+jITO5f5TbMbZjfQwJanGehQMW6OINFcqoDSY5dZa1qyYut7yR+cGLohXGQKlJ8o6YTUb6LEBr/GwoBJ7ZHi4BWsGtrjVYZv/Bl/FG4wdd5YkY0Y2IMDb551hAJf8OBbEYaZaF8qnUyuevWC38l/3NTgDrcHZzGJc3W1KcYAy+GOmRZncgpmIAA5ZVrs8y8rkog2mGG7163X+CIvGlb5kS+49SLGn9u1i4OWuGFrVySvI54Yq8W0cYljbgZpLH8R5M5ha3IwyDuTUzt8dKktdp2Xx05lePJqiujgu01f2auYOqQbHqdG8cHtygfhwVrci95csdx1lKic6m98c4vNh131p07E6ffUtCkD1dzpn9qCJpFcMGI6+ilmAwg6+2pqNQrd90BWGXbFc43WMH4fdsYlfPjM+KXJmHp85HZiN8a4nVybzPiQjN+5bP0f/43brC7fTy7hhg/5ALZNHCbVm6dmF2dj1itX64qPhgxs5rj8opPX6Mwv90O7nxQPFexo5Q88XBQN0+rXDo2upTI2AtQp/tWHw2CJwDhfageAmflMPbUTBXlJmOX4ToDG1JiLFuNVBCRvPYhbtLWeek9NcN775CLe+onDffgCDHaTxLP12IFmY1s2aCJIDvRbg5eTvgaY2mXMiH3OYrSO9EUwNnp8IhQ59aKnuX5T0/VXbozyhWI9F7PeYi22PYbVGY9C6UwfCRR4oOqDw6remMQ9/GUY3nu/e6F1XMqa4Qj+2KhDRiudDlDw8zRtY9O/6cN49AM2ldPjQDEbHKLqu34x2v30EWpgPzBEzWWFkok/B2UO56hSTz6h3TUOBqYcPDiY90Pk8up6/u6cwzkHdV/VnoMzxtSPg42cQAkeY7/SezDnFfP88IQAPXoP2Pr3re/8DsSXn7bwgltiY8vh4Y8vfSWfv6El7h7ysV/Mc+BfnNjSnG6NCDG5qkQ+MudclsYINi/E1Grb8vX2scL05F/L2jrjNk7ckGFei8Er8CB87gpVmw8WCHBOQwxmsa4f9Rhkeyz2w+M+Qj1WosRtcyJP8mgfQ23b//9diUzbPBmvjDHtAzvK3ufB8fGb5NhfxRo22ItIJtMy5G4636ehdS8GZy1XBgPalnXjH0sNNakd9nyPA70HWmWJk9sUR9I+UZU9jdcceEnqhTMX12f4mnSwIUESw625cPtHlLUAx/jcZnmrOyGizO0SE578+iOvqvskEk9gARe57owY9NIIzHlnezD9Qa0PXrEcjh0rinecBIULRpUzkR8i/U4la/Bh+/itP1ZAA5oecXNN//7Om1ppi8+/wN3IYmBDE5N16J5eGFSf+GNMp7UDL+DRTkionho5qcFca58rDjbqHB/vMxEun8GhhpGu+fYNWJzNbUlsjd77H2JsaxRmg3wE4BWtLLDAZvNbbpWNtzB+SByBvdFYyTWKU29JZ/EAXOALf5Ncz4mt39rj2QUL63yfYpthrHYVV4c837ajO4KINbw2GOISEvA4xews16OoQabmPfLDU1gQ0HsVIQQfGRCdH45qezH2qIsAseGloDcwJQnSMF5FZbT1aV3qrHz9Y2kcVM8DH5bM0JC3bnjplMuuQSzy3fwjNlEyCpeM8cdLnIOBvn4lvFa1jXntUcanWweUzvVhmK/uAxyCsfk7NaKy6iKkyS89uAoqA70SRkwmLrD52hqaU3TtY2eOi4Td2GfziEc87PN1Wo1m+uoGN5o3HoZn7WBNOPNYHuunAgK1GTt8uxYIwMK9fOC43BojBqNbxrsPnA/3Igm3gPo1ZOu1tQIPyJvD+BFq66Ijc4TsG6tXQ4Ql3fl49c6tjuAMhJ7MD/bks3WI4vCpH55ve2oSseG9duKci62Dk5skVtk6GMzf1jgsy3pXMrJ01sn8MUWARXOjZ4q1TeNy3b0mkv6R88Bybs/1yTXfun1CzAx1LbcuW0OkfcCx8SfH6c7eAYkY7ewrCjJyH+yKFh6bVywghSMqRjHe/VMuSnPZgMzPzPuI0ei7yuXhXPtaNczFMnz0ZYbh9awMrsOpI226LReTtfjknunkwejyxXBvg6sAa9vRLY3ooKRNBtZnHgCdvRfQ5X9rtvEL3mtX1bVehwSuDzlUT0Dt7SuvVeu0XK0LsZ81k2xkbetLEJKYHuXsh/37zfIr53UX118C8QVy4wRIznEyktjsM+S3IaZVbfC7l/OkwKn18hJfj1wizHybI3z42ngojXmjVqe3cYFZ2ctD11zkqA0ScMhj5IgIXDGa3I5GGBliP/htXjX378/z4J8PhvPD4XLg4GBAfHz7PEjzNg/2Uc4FhOiTAF88NHDA5qD+JQcItMzXhqAcdL79ngMPJHr46OGnteEVdBpPDnz/Pf+qrRgcxj2QR7eHeGXB99+5fZU3nMly70KdVVTSBJlGPrSjzqD1bp3GrHoV80RDxniendNJ0cAYx+2Xk+suztrMbSZIYrmXRjZcgDprC1Ea/RDt2mbOfffcxjEZgg537m0fFXZp4G7boZrBRmeoMTKPCNybkW1+X/fGQQjOfZF1KLHem0L32L2f34BTDzwgGb5iLpakxjc2u1dhRNjGZ0QL1iRRbeVbCxwqrzVaf5AzYGVS5NpHELCtg5+wnv3pPo4cer4rBLdpW6t9/NE5wPDidoVhc4nIdrgRO7lzm+GJF/rv4gAGMYnv291FABHOl+PGBp+xc/sYTiyT3XGE1gp1ZEAtN4fOeuFV+fNBdGsXpxk+/rE/+APAPOBJp5zkF1ma+RA4WNY5MrnQ5+c8rpjHKsQrPLH7pV3G1JG687Ucbk0QrWd9A4Wl8skE0XCMnPyCt73KXIoyayjC+JhG7bUFfNobmQS7NhN7Et58cIErc/2sT+Mq07458qtPWQpFr+/gmV0DOxzita9hz09xmw+JI3I8ZkFEY9xB/aN/i1qSl+y1ngJRwPgfchnJaePgQMh2ja39FqGJ3xsJhuOQYbV7VeADW3MQtTIjrB+cGKdtLm8RP/iNezfPZvfEK4w42NQXYGyYNTPxJ2a5DbCQUyudCvjeuS/HxZP7rMupa9ywWxuiG5MwxohGOkg/7YbJ7WLoHdj0hCqru8nAbKzrxqh2DLpP1m9I3NhRdPPGdtajN15Q0oIPbfw3D+a0vXNVuVxVxDpYp17qEN311oxLnC9ukcmn0rVvDprjETxJjQB/GvJT+xKuvMrxGYX3aB17pbhpy2X35Qk0+s7jQS56DP+JfXJW+2ebN9bxH6yuY3hYr61FQnGPXWPjotk1r9Wb++gMhGEGwdcOGOcR5evEM4+9PMgNNJlU3/oyBqyyhmquxa/OZ/+NvJjrAvBwmLqJMTX2HKEee/hjnR6jaZjWbuqvfNe/LstF2/Ft5OgVBoP4b32Dg03NCVLbj1ohHt5YO6bHN7hr63zkMUJZGyNsDKxoAYWTFsVfsbozCTpQg3v445lfzmLso3B9rq3ohGMwTZzhNrvkyQ02y++OL8TW/rUpMH7L8Uo2Kv1GA3ewM9jbDxbkZgtfeWwY61T/ffJEe/PffMtcDuJktPWfvvVufMatfnmLl0tlw2XqZpdL6a3F2qDIt0YMzODE7qzV6Xj0Rrr5syeLDwDcdl9l9t5AosVO9pzlJl5RO7eO1gy7ypotEyVzRbcAjYsFzRg1bSyEzgdJcwQZlFA6hMUZU7xuRFTR2ynf28cYjULqa6THxUC8esJxEOheySRBmzaDGE6ujiRnAAAgAElEQVQs9oF7IQ5+5UDAJ7j/lsM4b2fnMMzb2Tmk75z1AIK3rFN/D4AJ0dpGng+o4mDBfuTVPH44MPM/z3tw7qvn1MayJDIHfp9U8RAOZnnxCr6f7i751uT333jlv6/+cyAHk1j2eWsvr9D3Q+ywySEhNubLbSKt7B1alKLCHxkXC9Qrw4gq+ezXcvsCwPuiOI5BscEC7MEXHgRa73/XtqGLDmdH+KqoXLjx5YZWG0wa45DBxrjY9MmUUqkda8fo+InZi25iP/cHqTl49amdGMNv9wKIcNqKDCvXF5vajU18tS0xa9V8IleBPoMSOrV0/3p/F3QDYNOhbk905poMd+NDL80aU4fJwfnD3vVRV578qjyHbXMJiAdq3mae+uRV7GzK5Nq9bYSIjIl9sHxSqsldwhCcNPtuh9gmP3MxTvc6Rsoj83YwtwVyQQdMb98KEjdcmj2KjoiT21zTioyBkUJ0f3fG5qyVWpkcf5jh5WVzwSfCA8f8w67mXMGu/8YOjxSX+57yV0sEiESXjts8mGxDxZlrUFt0+3sDSaWzf2b2mMttrWC6daJf3HevNDERtMXGOBYykzppYH4WIuI1TC9e+u634V1IDZEfe8boTIx1qmE5bXbL9eUflyWjb3mWxhPz8IPQYtODaWTH3R/VfynBBJPcGAlU+JpV3zFwC1iyxFp4A0VQ2YuBd+ajW1IltktFbYpkDwhcRgZCASYaeiM76CIgiT0b13D4m0/lQwxHm0i57IP7PSw2PiD5Cd6tTxfGwyJx4EYI0CbOZoNKxcmBbAcvNw71GshCf2WDeTgQAjeDBFP9Tpje9QHfmupDDAalceXxgW/aosgLKVjcK9LGyPWeGBVFP7jLEQ/x6dUhGbsjq6jA6GORxPBbPsgYr5z5smyMXN9npUxu2A9Hk8rYtZw1eRJ1rQnCmhd9OBhYkZdqc5VqLuQF12Aq6uw6OBpNurU62f0LfOnlF0PzXSjy6dopP34jD4dbn+E1nGp6OUh+TMqfvJvSwm4fUNfONCHGYH0ffFgS3xabl8sRw5GvCMDnp1Ed9AKPkOl+SZVqNAb4RTAycSbWIsDguICVL+dcDt9jodtyra2G49exKMGSiwFef7xuzM4QsCca0yCPy8khMmKvviZBiIj85UPQx6Y6cOuLzyAkz/EpYq5FLG8dqkHgfU31CI2FfwL0A3BmfDAbiVjez0Ve3OHBJN+7JuVXBvW8PMlnOZcQBCrZ+4muyWiB5nYpkAyO/wcS3GsUW4zTJtCpDXJznF77mjJs3PHV/0YQu+GPQ2vwcidk99z2cHBPx+vwEydxDJVJgD5y1has16ezw+iD5uQ+td3fRdZ1H/AFq5zqWAoZW7cbSxv4+EX8E/GMipAr7scu4yoiUSW2a4HAZDMYZWuBCXvu6jXNFHnrg+4rqIqMfNZlgXGDFz+DvZjgGQq8BY2EUNXdbMXQZnX18bapw+KPzyS/r16dmGAYFYnV9fcp3Hil+bvvv+Tt7BzMf/vmp5/4N2v99HY/2T0H5X3VHG8P59HDgU+MtkagM+crD6C/5NVyDudffvghNj1Qq+ewwQPs2NP66l8PMhzIibNvredwwwN13jLs/2KPPfX4PhgcxInhoR+8/PDW+e+/55X4Htx9FTEHeg8wf2BL4fMzRTmHFuvYg+sh9lk4xYqG+Kq3J++27lNmuw+Razf3d3cnV4NO/6FGnbhvPE9ArT/mhqnH4nR/zfpHXy6rxSnxkyNp8u/zTLfSXGONTy7YsLb9pXHx6p+TEcGJL04u8eGLSLsHatv7gTEVvwXApXGmImKsDzag1bb8wbgtOprAEx/RuGibi/VQPPZ1EPbGx6AYKI58XaIGmOnmqCgzXxGP78rxnRDuR15R5/PUs2lzzSvo2cOcJr+dQztx5Xhq0UjgzffB4/bln4ZwG80eZ9/vwRw+xOaHJ8Z8kkouz3gAm4kOBItPn2CgBHDp+t2/QUffhkHjHEecwKW/hletY3OxgJnjgQuNWL67IL77RCKyrWufmCunfmhl45sr9x+5bfSdAb3db25L2VjEyc+nbDWwoGUOfw3bX6zZ1zXs443YwvMT84kDFjDUZdvYI1m5/sbEvHGUDX4MP2KgE3FwqYNYxmqgtaE/ev3imW9kDNxjTy/u+BD3o20chGBw/zk252/QgYXtLcwnyCVTOQWWDElCaoMCNGOxnmCE0G/LEqi7UGjbLAphggXcNuWZUOoENc6YKW1tAEV6uth3cY5/7tE3H/21b6TizcIAMsVrwcvXseEbZznS11/HqWVj3wdROroI1ocMFwC3NJ+VmroZIfw0qes8aB5bHcqjknvtuiznsT+1mXUb/4pHBiWLGWWgd/ziUWM5pd+cXVt+W6oA+AyCs3bIxhe909H5m9aA2mO3mbX+nV0pMWpVmOKqFyZeTUwkMZi7d+p7uATA9dj1nr560NOWTElXNqpOJg8mkfcJlVl/ZI9/3cL34/YBQ4xq6BMlMew+AWAazoNFtzm2RoQe5TXDSpwMMmoc2MojNTmSGWPHmrWV7Yoo30q+rhk+i7V9GUV+agt2pACdpkD5Xd/IlgJ2L7e4Envb9akdGtBXfrlU0bV54GscJbwqR0T8xRBT5Y2Lya3T9Wt8EQ7P4tX3INSktSA/apRfjJAflfF72zteo++aftiNCR3yXZ/LDMLMiNUx/B3qMLqobsyg5bZpHQRm/jV+/QZR/QcoeGXkSAPXr9IClpDcGiK25WbY4w/Es59nH4gUiL293Nxjv76uH7AgpjXkjHXuGryYY1dcHMb3cXfd8Il667b7prfx4fXwNij2c5/ZPVns93rrRsByJM6mYNBM8JlVGuh31vgo4upP65NJg6FKm2jB++RdI3wZOcvFvDNj3jG6zBQIl0umvCRjVMYMWdcmof2uywZAhWPaEcVmxz2VNUjxanvGE995kDgk6lyzwb57y1gbMP1yokYNSs+eYxoWQyTT2yLrHolo8uEJsD9+59XxeIUDh+lff8m/aspt3FfO+X/oHpj7N9/lC2TjdS81BOvRNSsWB+LvczDn7ey8rR1s7O8rX3MYBpTDTA7iv+b/rP/C/1nPK/Zg7dvsocsD9z2gE/+3CHmbe19N58DCgfzbb349h/T+nTtx/4js9/x/6O9ycO9Bh4MSP92DlmvHBCPDxGdIDStR7GXnW19qjr3nMfyYH88d4VVMQJwZI2u/c33QxT9rID9tlmcxGmvqd3xBX0YgziwiR8EBE9/9wcqWRD0sZeIa+bEEiTW/iJbrKQiY6OJ3dfCeFvnGoIanPqOW/9rSw2nm3q4dwzO+PAahYZAhvnA8DaMbuWYLNkaPtb7GB1tFtVcW7ifv6Prd+PEBGlvCMqYdPixlhLiz3ziM8yFxBDIPzuiMY+Yr79xmWOd8mRdgAEusB2yeNOufhfzgwdz9m9tWYw5ughY1vfUqMzGDRXWrD/QJ4WiSIJ/6EN/wcCEZmvdP2PPEXPtrBHdsoN1YGnoZhTjjhxxbf2dnjHN+eALOJ+K8nff+Zv9LBDzkF3yePNp3C/j/HIJF2b/Nkxe0+XVV5sTJF/nT5CdZp9CoJjLro9nYajLyGLY+Dg4mPhe9WGDSxOtggiADOxaDh+3W3XG1x9d1g9vUfLZl85k8jj825kHQxMn3YiJhjN42CvEjUJcrWB1j9S9G+rWa5PdFYuY0EEOiosgyaBKBi+6QDfzH2HDYD0HmBttB7SuqzSlwTGxvAbhhPVjo8bU9HEegssnXqoVhuYjVojBqvhmVwsGsPWgnChPtrmScQD3+aLvJxJgaEbnuaxg7hnTp8apnfHfHj6Q2xSw2xq3H53YthoUeQg1Rflvf7Zvj1iSYmwTwT73PnjiEYTE1nBzi0hZeHBArTkYklbZm7xqe2p9cYoVhnCIapwyCt5wrB7/xx5rOWAf/5TH4R4epQBkQcvIunyEMHi16qcgBQfXQdE3BkXNx4Nnsa1nekWyMNQaKpj9BioMdPtIbH5Aaq6EOZrDKphZoO18OxSKMfKP0DkdwpPjRNv4yj1xbLlU7yFh+h1ftSrY60Ua/OSMrTPl07cJxcm0Pi+itQ3ngg7Q9INfHeqht8feONKBkMz5bB+Z/Hu8eWJ6WpXAkU4wTM6BpRS8eM+zaJgJTf2GPFH0w4Le+aMzJgJkYqxVCp51ukaGb26Lrzhw/cCcrfGhbz5m1e/KGB358ES2T4ZYZAnUqvHA7VtzZB/5yHCAtYATkNmMkpvV1ghrMroUYMX7t0NjeHAejEPW1Fmu7AbfHdxspzpi6yQVZg5pzLRBE4Xd7HJVOHVo/ZMWpx12PmHVtBGmeBYwi7Y0vNuL5cU2HwuUx8fXueCXEWozF/azJzhq7EHdMqEU8uggHtqJczxqhsw4l2Z0xZstF/8bQKkPqrCS9skWOYm1WdPZJIZofHNaRnrmXgq+pYFxWUKMhUNsk0HnsTl4ibgAnvUyBd79KZrFj4avAeYBrT1B0B+YaSnlzHXhfoc4B/fc8wOUt6B6qf/iLB+Xff/opB/YcgnkVew6M43a6s1cICXZ++sp239ouZg7JvLLHfZH22A4CBxWeIPkth/Kff/75m185oD+vovf3Nzn1pzXAOaMcgnhygUML90vGT/99cvFJAV5hz5MEHNKx4dDE23nh930OPnIKkSmvg1stRj1xoQcbnq01gkmgTJqXQDIbZXfmxY+YePnSPZg05tuQqMfOeN0fn5Yq64JrpvJ7cBD3/qVPtvQJjhx8Qmbf0lyAZJm14aPGOPi4PrGhntRpW/PPrERWPD35PIqpA+mV3uSrTeIP5wQrR2Hrf2/XCRUOfaLihBl+Ogz26DJbBltPwtBOOMbkZt2rtUaRn/oFpIdH9PnhOz/1GTCyJTfk4ZiijqJP9KXi6vGhtthp8l1e9Y0ltyfj4Z+vrjc9czA5hOadJ9m3P/zlL92/3IZ40mvWRD4YpzWH5u84cYtTA6/EysBXqzNYHxKEny29TxxEUPz6Y3DjjQwHHCcWQ/LYXDJIi61yRrVVrjiYuTPtk4Hcv8wBndt+xj45h2x+REss6tn7l+xNY4Ad9DwZIsdGynXVh8AK7KkF7msnb2dEoqHBZvyZ4JMpuahdZ3TbALV1UPuVjSbCcg0WZpIZ2foH21Vkrs1wwVwGa1jMcx0srPAQQ7JwH97pB1I0fYn3QG49uk+KXsThlcn8DXq8/K2IUcZDwGBbZcksCOVrJIswQQ0Y+yVp4RLkJVCEpkasLSJw9RtsnG1QTrMT7OBVFHtvmYtZ27cQm49FH1yLag6Df8bErQxuy50yYLIx7dc0/VvsDz89NCjAYpwFbKwoTzs1ieRsrtE2DpMSgkJIZta6VRrtrNtr/8HryU20rffyMuGHW+4XfR6BO0uDGvismUKDJyI5TsGWD9YocPUgMPwKprQpaagxluIz63phTa4lYByUabt3tIji1HBi3nWEf/WfPg0vfrjBUQkJ0DI1Kr6VnJ7prS36rkaE5TW9busvWKtjVZw3z+Ugz48o5WD8uhI5vOpszsPb8k6sDz0kIn/rwbi1UCV7IgG1eRFu1wAIlOUxOVbUX6bgaaShIyTab1+ChLm2BLQ1ucPp8XFd3npm7ANMubb2D6IxP9jI+8XvmOz43rosE+hsDT7HE4sbKMbjC1rb11w0AExO2NQNj9qefKcOh/epy9hhfwgWxetTF1E314ZYWvGOdb4Rd6fiXT70Na9syfqAKkHLHmfqHh8uBz+DmYJTBf3Dezk+bu5brYS9e3EQXj47hscJS32C27SI5XBuw1XBZeuJKe08MTruyDK00e9e84aAdHLWgPGxnngz1xcj6h8719U7TzgiU5nx5YRkaDHUD1u+zPTUHojibviT1yDUPiDkNUbltJaG8NKYaNMO8Q4rSiwfANfGrFnzx5yZkqbXRBBsQhlbh1h1rbW+DzmaoRjVYE+E4A5O/SvbKybaZ9DxOG1gQBYAJ6b0ytJlrkeEe/AmP2RjIg98vF+YtTxOHUTbdTQ3HPkGZPAdR8hhkAfLHGb/9vf/5vjnvM395z/6KroO+CcOfFqr4DwNGQ+ef8ih2AfRHo779+Z95RxfKJSHNODtg/O8rT1/984hncM6r9xvorwy3n2VYLqy7zjo9G9Utc3cQ2Vsfbv+L/2bdw77Xzjs5MkHDuvf5G3uYPG4bB/s49fbG6jTiGO+mStmf+SwBYFpiMuLY5fUNNUC/4U7/pqdS9XNpUFYh6q7RrW411FGMCPdGO9t6YAHiFckqSW57pMs/pmCdQOjObEm1oJ3GeTJjT/4u/0/yKkHolS5r5zGDi6Nx2gxOlagLHas6yazsu1jLv/oZ0ereXPyZow/0O4RuMZvMF2vxStaZi+31tIDdGDMddkHg1jGnvsLVP4ekdPo9MrY/Vds/I738sE3X/2XakUWL358OjobgfqyBiTBPsr/DPRP1Dvf/Q3Qt95+fvjLX92v7xNc3obYq0BuHajNjGXoGA7LM4M6yG/fKWEOMcMcf/YIvaa5iMBcvkgnx2iaa3XIsQVP2+QqDrxQpu1aOQ5UnyTKu2BSD2/72Y9+xkXesXP+vCV/ZrO3bzhCzFfPOaDP7X7jgks7TzBlPC7tJx85omMeg1C02TGJrH5wJ8+vGk4aoOmYKW0k+lVSmbUSKxYaFffUGmPqPNG2jhIc2cbC/ZBO4ItdjNV9UhxsYwCQZq7LnIhp4LFmY1c+y0tEAspV89j5N+hMXGqdM36T2aAn8Qz4ZgWU4c2w8w0OQdS0TZLxUj4JBH9lh/wmsf0ajH9xJzj8uJFuAy/2lZB8WyF6JY7FivZGj53Gq8scoH/VlN9CY7L520e/uYCZ38vh+AlXDkQfjglFNCksvpLIMkekj3zGjxrrhyc/F+Osg1JRz8YwijEGc+LpLSagxdOd7LwDhcfNDVTzfXq8Ds9TZ/hOq4E4SMrsqWV8FuONBTfleOAEDyGdZDwY7IXh3hqogVTl6xew+oM8kPRjV9lo9IFXczdsZGjxtgadiLma5YEhuNxBCx+vojWuMCIxmrwMfXPBEh/byS+zbIDNY+MZn5h6lN9y2pp6+ABssBwCh0gO8e4E1URu/N72J+rURouItubMb3whcpkagqefIl2xMGUZHBFiGzQPnfWNZnGsrzGb6akVLIbXJFHACFsDgDG4WI2EGYxuM5+NXVCVp16ZLc96bdUnBPcDY+MNd7yREevWK+yJU0UxS1HLP1+wHR+RytxY4PIL/cHH/8aC28bbIMUj8FnPgg06ds0N30AfPLBpi98x12Dma20ZUF3tyJWv5YE1mMzzRehtnysSqSCXD3bXBk8N7MXjQdJY3Hi1u5agjKdgsjy12D0H+8XSYfjrG7+Lf9AymFrP7yyQS0eHjA04subFS0Lez1uUi6tfTIYdgyE9PWEfTk6Jny9M6zBd6jLCwgwNJpsv4T/emgoSdnKY0GPfuIbvgzVj3no1PhyeZsxcwvk0hgni/ymeWKvb2MyrmtziwwPUfaCMHsh15zDE2iDgYQztVMTYnXGgZoSJdgugh07mztT7xENoDMH3C7MczvP28j148/v0x7/9zQMef4/u29zzoBiinmdyAY7o7qPgcABh3Fez+yoXOL4aiG72FHzMnQce6Pnb3Pjzt+/88K/e7uE8TxjwimGCgW1d3GyIyEPXySKyX5OHNeu/ZAPny5c80P+BWhEFjHLxkJS5OFCInzGQYZl4RiBPxiY8MYmb5t6bQ7u+Ua/FPibBbpaRYXwyT96XP4LwMqpDMerz2CVvYgCAThw5NuLGJYZvFZ5XIjnw8BkC1MJ1TL37Cvp4BKNPVPRw/n3+hd33eRJjX6k1XtZv8elLI6MQkYuycmVug2DazYzZojCmbdbFwRYb66p+LuTM/pncIdDaN1rtOx4EawU6Pidqlc4bq/zkhWm+lu9lFrn3y5dQKsYtZnDjEdzPPdO1MgYxWW8eX1HH7Hv737AZnXkFNXudd3b85a85nOeV88/DOXGaAPmyZhAAjyewOMzKI7oCB5/EcaGVJOWoWixyY/O3nfy1qXPNGnvHWPc2zKj1PfdniUeMFmeCSTvj3FFx37evirM390kk/qzFD6bk9p/7HOrFAZ7WOsaXV8mTK/uzMcCEC7+Etj7UI/O0qGzahgM4sh0F8s2JeNRKmyistfPFaJ7YW6cM7r4rYFTGpL8tWJnoY3xiJkpcKouyoIM3nsrAvWhGgZvSK9emQaKZeNo1Y0mpaWx400SHi5PKFoZKtW0f+4m9vL/UVZhHCZ3KSNRgE1BwQCa5sYp1RkzeJqsIJugpREG0rH9dNynsq2whGGtHoifGGag0fr3CvYGbZMbLXc4DNrbbbT7MNR/uYglxuWwewNke3BMzCn3JffXIMt48V16f6ghurkWeXCIx1miC4eYD2zhj/Iy3Bq0c15d/cVjjyyXOiEn+4Vs2+OZLefQTt6SKJX7uHDa/loZrETIQHghG5Ydvm+I37sRYflgd7MRZz0ZAG8xM1v4cQNXEdxzK1mggxgu/zvtEyOSqphkeu9jTNoYTLogDfFFHOHIU+jAvydtr2j3R+iKgBdBHhQW5VawWWzSNXa1zRc0LjPW+uhjMGu8dpjDyYkQDj/iFJxLzYtVCjB2im7zoyXXYjQXdcupYPgImiNpeN87ZH+SJSWzl9Ngic81Gtj4vF1Bp6MQefpkoU0k9AKORR9qu8UhXW12uyMscl82542V6+GBNTejypT29aIMDnySqzypGr/vEHOvV3P6SOXsdv9anuK0twrqd+5AQUxSOrUTzwWrrpiLz6lHEg7pZu85F2XlE2w61FYzrYp+e+4/YGMMHi0/88d21Je6xwycTc2iRnewa4qpt+kcdn64FytXTbxNPTfXKl6CTWa9xWDz7ecBYUuNPvNj2gXCduiYHYKJhlJ+Q2YOGflymWYfMiSXGJNb6xGj85aJPnRtv1nfuFPf2NS7WcnnXa/b3rAkPWNFTc1t676qY4wAXmt0Y0t3sHNUq19UhAAPgxQAm4xMr83/VioVzm3XIcH0LOXlwgFx8en/SSTgsNV7fxdx+I0z/cG2ssUsH7PIm99949coH63O4zttpf/z7v3mY+K//83+++cd//Mc3v+QV9V1zI0gPZs2wB4y+vZy35/q3ogk0KcRl9hiCrBdfMgoRRhw0eHD9fV5dLDd8i709cfExH580WAGatCjNJ4f1/LO44HHABycfsJUfI0VVJrXXCV9cZsM1BvNo3VPlgRkyZnJXkDEP8NOg6xoxHiuxqo1w1tD5OKQzX3yRM5mDf2M12sftBZybhTHx9WAz70DYwzl/17/vSuiTH8ShAvliHUJ6n1j58vsPPbTlzQYxyf+cz1JlyKfmkxHfcpRSUGZ9lpu6WNYQfSXNQKm6zssBTGPJCZsIlFUv19QEJMUcdlvokcQ9evfE9MXbeDGjBWBtxFyM9Mt/sjPW+jRo/Ys7vAvocuHXUsC977TgiTHq2z8PoX49YLLP2Od7e+N3Kwfz77/kMxvyLo+//JgD+t5+YgdGuYQ1eyOxut9a2+aOLipN4RcrL+S8WYEyRrpef+sRLw7QuLEG1bI/wEBKq//Gotd2BWtb5zWPHzXmySHe2cHBnM+cyJNG2avuT55A4j9H+CQdt//mSk+tjB8OvLODUFuHwFof3m7N51LE0lju62GrjfJbF6wuxa4dc2uZeu/tOaKv2njGePcSBki5VrvICrVTPz4moHX1nRcBT88HyaUocKN2cI9NvjtmxRrXUY1ro3wE44Ox/uAEjzl+xXKKpVSoHflrp1UUONhc7YDlb9AVApbG7XxNxk60lgRdv5YEtoX6TAzfJeUYuykA87k/MdZEjvQmhQ1z0JvRzNk1CqpFSivGjJ/CbMwWK9wpCDfEwJAJ39owExusfIWgkaYux25scDRv/MUTSLyyyByANDq3QbDMezHU10j+Ux/GzWcAGjxAmR8+HZfD1i0yXCY/Jky1cZSJTJAOlL9UMwE73xcPi/EmJkN5lxk8dgNjicGpNZiIjg0z6lUZWGV2faqPBbrEOWnq0li4N2bs+E6cxUEHvownriBZb22/4lIyAsr75hbuAokUs0SAz3zhx5x24mV0ZEO8PrETBqfYj66+Ak3sSAYTXYF1UA4EbevrWCII86NveS8PZeg25uCXFwrcWudSLB/tx1ZoLTPie34TyeO9HWGvceuEi7kOcXdD9I3ngKpGgBuOY88ATnSMc1U7OF3r2jaPNVwPADOWp1An/dYj0dBNDKITA3h4MLJXjy4tyqZdElgtZ9TNs7ox1+nIG0Lsr+0boQbaE8xG0GXXHj05d4bRjulpl39hrrw16fzk6RSfeFozQerqMHmemItFlPAt8cMRcy38ZTPjyDDTdHA2zta5frPGT2TkN0Rj71zN0KFbjvDasWtdcKSMCjh+TFqt668N+tx3nl/c1luNACCdPei4sITo2hR595eyS9yooInBHnvqjtwW2T7h1JKY5dHdfT/JgJEmVvrqZy/s7RU5Nod9OZzwE8KqmPNww4O5Ie5+YLrx1GkziaYTIjbokLreCba1GzIa9uAxudQlt7diLawcFmxt0h8cx0Z5YiGsSUd37Acd8WoQbYrgA82JqzjB5WsynCjD0fEUy/EkCLdJofUq/7qMPWi5ffBAmbe0E5dD7Zf8HToPjH/8t7/5llsOcP/+v/+3h3R5BNvHF1LtwdoH0vHxUGyo2uya0CsORw7j8OZBO+mBzyHwh7wVHZvdLzMhpM3DckabDw/IeTVz82yM8AkebxP+y19/9NDzQ/Lh7+uJA0/P3B46peG+sXTBcwm2bhN3O7k98cunecJJtyRkDyAOtu5ZckVX8bP3IkAmB/1jhfsZOxHJ2ggw/gCm/cFb2vPjq5Lzb/JY01/4s4E5FNG7CuPfNeshkidUvm6sMfC/hwfcXUsE43/slSEcMih2OrZFqtz1w7pFl9Oat73oCscAACAASURBVAgAEC+XxV7bs3fQz/20MTJfHb4AiNw4Plnw0LOOWAWXmrB61oa5gQtSl7u22JdSfNaW+7T4dD9P5NTTV7Y5YLLhOD7CNxyZcX+67zDhb805nHefcljn7/+HrPESMz2ivQ0sRWVVmPTmEgDng+K0HIFZrNsDX+aN3Nrj3bUHgFkIjB1y6odwPGsw88gQx/78rbl7lHd18KTR9NmTv/j2dvZv/yRj48DXGqbvbYFY7Mdv/DDJzoYH4fLExllnfPI1KxdTyAylSDtjvvJYMnwKsf7GRv74k3d9kQ9aOs9SWk5pol4O6LCmGarDjFeKYrC0yTiqrfPeXnBbmb74ADGupoAog+aAR3NejOV+3Cbv1eNBK2SuB6+4X6RsgDVrML0Ai4cE8A3BAkcuWb0lB7GJra5FKlmDnxhADqZBuNTuTJ3jNfHfueIbt4syRcFDzuUKXs0Hf3yLijICvrNjwEFNq35mUwOEXazGXuPWZmzBQhGT3SwCfuSLLRgCXr7De+1VDwoeu1HkOXjYimZtM5qd2VwaZ/MCnhvVbhgWCxalEduJT0nuMzsYbCses62x41zUHA4D9cwbSEcSuTcuSlBvoApkD4mZbj+W2sH14GA78zgtN3uIqY6elrElkpshhqxw9b2m0i4/bFs75y+msAQCKjYUkHF+HEUm5OCqRGehI7TvfLkvxrEN0out/ME73AbT32MmXt4HJ3pxiJ+fA5EBYw8n6qrdXON0bM0pl8OVX9a0ATtyuKw8/tuMk4l30jgN5+rXhzoSI9LZs2qOEDkg4xX55qXkwNaAelZf/EpH9wIVTmDha36kDdrpxYtRiH6YOkdOeo/mqQMou27YlU2xd8/VM1aLP1Ds4a9p4yOeNcJwECdmY+EWnepyPhziVzES3NEjmfHmMbHHSpuqIomu48YwtDjAlc/BDKzx7DsqlzL3gVUskNVzaXdvDLMyHKDepvCvR/Fm7UNsOZAS7a4hxCsbRbtc371jmMlHc5Jl/oEdWQ3F0G7yUDCXlwtsrctTo5c7LnJtcYswRRHfcetC9oY/Vav5XsunM3lvtTa2uUTPJosx4pOfzkWwxsSNPRLdM4Di1nVl+4D6E2v8oDKG+8Dt8IqA8eIXm5jzg+/TsN3G7zCar6DJk0NtDkc8kM/pUNPIez+0e6PxwPctnfGHu59srm1fdSqj0tgcDYZjk6xSohnG139hFl3fYs6D5D+++eGvv37z17zV1g+N+8sP3/z9f/x3+f7jj3+fB8apsgGgDece0n0lNmO+PIQ3eKPFnsOJdSNJcskcH14xFI9c+Nm33jKhNun7iuP454gTjT+pno8fpmDhnoN5Ducceny7MIfz4Dc2h1B49DAKPG33sBxyeoKjKi5wjaGyEXY8zqhnTcmJ3L2N1E0/gxgHPGZj88hEQ7extNsYoE7LoDRyHRsOOxy+/cnhnAMP73ig5zDkJ+OH464Zfuwj885ph787/yNvHQa4EcGOUX6+8F7W+fdg58lw+BsbvjU9zpGbP6q1UQLd+E3RVRGDRtfArlOMdjrywyrzNdRTu6KQQ6HQYNUqp58wyjIx7ydo+T5c4m0YRbCeCOADNvx2H7C3wHQv4kv0uY+AxXf5gDi2NE9e7YfE8SQSt539e/P9bwf0E2L6oMVZzibS+1FC0KznUDcsF+aj14j52igYvxkfF5Ne0ziMD2Jy7dTs5jEZkpnLDcDIjA3v3s+dt7Nnj7of5wkkXzV/3vGBd2/nwATHd8kkLp+NwBd1R5b+2+xLn3BKDdnf8Pvt274t/vu8WwYePVeUIezB6PoNRQJGRiOTZngLhz3N2o+/glx27ZlDdc8meIB1UbD4/9h6F203biXZVpJlW3727nPG+f9vvN3b2y9JvjFnZAJF2dBaVUA+IiMTIFVgkVxXtjyU6ahadHp3nh0VXBPmHWSw05+5uvGQNa5W1Aj8acvpmeNyXAxtMtDNQQ7jeHihD6ZvcT8FglCEO26RS0Cy0aHnCBCtciblxIiwupfiaotNECZ4/Tm2tRjRh/lO1mLpBuwUxCLRnw3CJrZ+5xyXLVY5NkMjNhlAgZ/WfBlcjNWX21qe/MjXRdAIWz/siF0c0wZ13Y98fbfemDwx9Kcm60u4B1L7y3FixrZ4hKvD1mG9D//B0j79plKe+5+FI2CoN3Ufn5zSzNLe1ozBrg0V1AFOwQDrcDHY6pC2XvgQg2PtT/aTF2TGtoZaPw/P/FqLYpQtOTz8gdO5xxNtsSFRIp4Xw5weQfcJRDDsyfmhb/eRI2snjbrRwDVOD8pOjJi0DyL2OacGPm70Rz66nHbdMF9jbe12jqxsJ7txsXJs2Mbif/9j88TERkI1NgKmN7fGqXrzGnYKlxP4zT+1Sr9zBVYtyj7jCQfW5lAOotv1IN7Q4pT89QlH8YGlSaYDurQibb2o0OqH+XCdiOrre/V1GQyvnsCIPr6di/Ip4bE7Oljc+PiIz/yeOdZErlji2hwrLy6i5R45TcPKxZyY2GNKJGuPbQWodDMOYnUctkWyV4iCYoMsen5HpjXjXrNXTG4Tx+cZ81iXGGe8cnKRQ3zKJUplxAEYW0+vOSA/eQpZoxwxL1ZFXVOVI7HywTaFhtNwwrDrus+H8NL2notO/Pyu04MLETYnyRi0/o7jZGyjDoFnHDYsGix4h4zgfnMrSiVRwnM2DsSBEjiiOEivINURvxBiMqSZSns56n0wnJLxof7Fxqp2uG1PfQaaY4tiwe0zHkqcH+DFXiRA2QTzDc7cWUs0fuPMBpVzKUVGvMRgDB6f76yyAavHJgvWa4x+ZrP//eksRgECsk3e5SPGXJ+YrCF6J5W76X5uORfRvM29d/fev/nhp5/C//ObX/73f7yIzrbcf8C74R2ecj/YxEt2uYhGzobctZh4m2cU1oDasGF5n3r0Mrv5YwgKutaXGgUvQl9cID7/gu1neLM5//Dd8M4mfTdCxKdxYhNA/B0ndOSsPc7Bsl/MWmkZZZzynKIrdvlnixxZx8xm86MjZwQKUdAXIZ3XhgkkilVTRTkc/BCHJxHdAIX8btDZ/PCWYe6a90/W9U5l833mnLnOpvHt1Jw75KkKoW6c9M2QPKN2HaLNoHM3/CQ9fvCqiXlTS3gXqb0djTcqG1rrNxPjfFU4GLXDpmsojvzEfsxCLbrHc59yyKfpg8PgNz78Ol+oAKq1Ljk0lmdEqwym3UlWV4PlAMaJSe0iYP17Fx0dj1s283nnCHfN5/PmfiQkd921H467MT/rvlMkj66rJQRuM4ImHCAoLwUjG0XlrVux+5jA9HCPLf0dH9Cgmh4xnnjh/LQlBdYdm3NfOJo75vxlCP6kIpvzlcMBuH1hbjnJEx21y+OOd8vwPEAZ3rJRT/v0tpvzjS3nT3muyd+F599eAnSegzg8iaHPxgYzLExLZMZPya6TYoijHWOdPcPZAoGff/5I4o43iBzE2APe5Pu0LSdxcWROBm/jKNYTddfs1mNrWT/RDeYcpoScrX2k5Ts1kAOmjaxuagV27qC3IJu7pqJtAg2mexzbJjFDovkSo8GW9C3getff2GYARLGlvWHAj74bELotCraaNIy+Taz48NlIw8Thmi+f5YdyC60h7jG+9hrMhGpxzZY/kuU3Jhu7Z6NG05zIoZKML1272B/dA/PKTLmcrVs0OAlVXGzPAjx46SDfgFvzOaNd1cCNYPDxXFsCpi8njevBMcLRjbsnbNNqJgd9l7MJ1N65GPklpLW45jXxC3lzGivjNH9djLe2YO58NxYVGX5SuH1yZHpKO/I8aGubSOGw9VgbLuaem/QtV2NzJPoDX0nRl/viN3JjazaHIwecOgyPWwWCJMaRX4yt3fL2sbXgYA3h5lNePPvSAwWTU5ODjzC/o+NE0TyP/MYdMz1av9pFfvAAiPSLsZwj3vytE4QSS74A+aTKefCqEc5u8sPWhs3w27wZNl+s7jzdWMg0WuTY3cr/8zVh7SfahL7YaG3JZeejskRdjsTMT9cWzJqFdjNnC7NndLWqxPoh0KnKdskIxHBifQfvPi5iDi/MH/IiFh9f5qpkry1O4m9eBalrZPLJ6NRs8ljOyvUBpx05sDHB9sHryUcduI1uzaYL0+kWb20QtvZItrrLpOh4bGv44bFCz+tTjMVvXOxbM4lwEKI+RqbG4Hiobedi/ap3rtaQc/zghJ/DYI84Zdp80NXAizHmLD/6TcxdX8qBFXKxcmbesE3b8+lNfJUT/NgThHhpnI5vOtvveqiNpGJoTWIhXHyb49owrjdn3n7ctxrnEjMXlm/f5U8ofZ071NzZjYtcYrcv+hh45K0DcRCQ525U65crUS/2//oru0wvZEmk8Ts/k8UmI/cMHM9aZwjP/HpRHY6//VquP/z0o2+/5UurfvjxB98O/+t/fmkM8hdvuAxOwgOojgtqGnn2TEzVjzGC2YRn87Jc2BTu52KR8TiwfmDlt59JjWMabw/m7vluzn07e+pL48L/Ey8ayTcX+KmTEJIqT3S8gLA8vZNZaPMoEIImsvOP3LkhgTSP5p55yr/Fw4ox7rXs+cw9cv2Kf8CUO4pfr6g7Txll80M92Oi8bM7ZqOe3397Oxjx+E/SgI9u1FAzUfIwDbPB4wePtu3zh3qfUK3JeZOGFpX1nBHaP5CAvHmu0ocjXdHNOHTahFRKPfJUvq3quKaTRPKRijVNjZnCxY5nBxTXI4SlnwLHxtMgVNCfUIIY1OTmauctoyTCvLUFrdsb8H2C5qRWPVerfPnP1FbLA8NjnnSP9MrjeTW/Y1q+b83mpanioh4K0yxlKCKwUtLcpywBits21ZzFWFP19AQy48OWFhNGbW2xAap4PxzHqc02NwD5r08+az/rMmvTFJO6az7qFuRlLqLGDYk7lfuvL9Q81dJPOmo0PcXeTzvPFJ9dtuFNrP7ax+ZPO8OZFnNh2fskpNhMfa6yOVwbaRrorDXoRHh9wd83oOVjapX/wdLm2jZEjHXzs5rD+yoI8GItXvphdLJxZpTS5rG/GShmrIVgbKRh0/J4jVHoUMn1iDXbOuYPO6JJzfIKgLLReZbASz5LPZD2TWFkvsIIIHhfOdm+yTRCCJUWsbS0DftHtJM3FNzT0xVhOxX7aRlIVNmmMacYKnhznrPzE0ewLXBwNlM4iz7lkjl5ea2K04RoZMWnWxV7YRER6HFavativjAsnQmOKk/XxrCAyf3QlR9rhgtcEMu/R/q3uuhFHQsdHX+cviMGp2c4jZp0jQ4CNgRj0saP12DF9cOqnvaDYpTPzXKvmsXXA4qwHYkzQW9Mi99UvrePwykF6+KXZz3nYZfwqn+gjLbaOWMZ0/aw1Vsj4z8PuI781NOhGKZKlWvsgYmpt6AFFDc21bKqNUWSdz/oUDfHIg2k74wrWZ3FOvKn74nA2R6/9IDKa4FHvJ84Q1QAzMHvE0MHDfjUzL+JRT8bDvdebHQcg0gVNf/DmvAHwpzH3gYxHx9byuOPdeq49Sa7lWUcFEOPEW3ysl7MRJw+ZFUmy4FooSMFrdQ4VbmQ4OG/ioR+eniu0PolrPpwXb/rleRD1VBY9rYjLtfW5ska0lhEaIx7WveE9Hg7wPYjNTayR09+IlIvGadfxct/46JdBLcsBp7IYELhN3lvP6wfK2NGllUi7U6dabB1mlJOmEmpEnBat60Ll5HG12KCvf3zDT9kGH92tKQ74pzE3Y199xRyLMeOYyWHmEh98nY99vlydzhN04mw4LmTZfJ7nCHyanIGAOnE3RjT6E2+wn2tVGXKg8q9rJDhrj+rRP/bg12mCTnCixN6Y4KbpM3yQM3ZDlPP5AqRckP76n18df/Phuzc//vTdbICK5NqLvS0Alk0O6fv/K9zZ2HPR3E1ajcMFPrlb9DlvTWen7l2odJXHaFeTpAeT3LoSYhD/gDf0nPkcM7uM37gYzkXu9z/8kLt9+YbpfIEV/b5tmm9+35oS2KAPWXOj5rupM8gcuNA2XNz2cQMvGne9927au+GEDb9fJSa+bcXG/tt83py3tLNJ5/O8+8IAtrwjwD9z1TQ3jDak3/qzMW059k4/m/TFYS0+XxwZAp728WFN5UseJJYfu/hiWlkJIFPosNSYlzbOqHfc0lRAHcjL3NjsJL/eOe/GnE2Q9WLt2IjTfjlmlOG7fCFfFpWD2gczpm50Ugxy58u8OPON+53vPk4P6eW4uQA8/X3MQcG4I7deJqf0wQ3LbaxceBOpmHDcRl+I6GrVDOtTO+T2UisfO4vDBm2uhSyEORCj6NYiXfmDceLGwB9Qoz37C4Z11habyQ876ueXxREz4/e8qJY16/ci7BpDZZzUhM9iT17NRLcc8AZ86mYNiukLWRoz3lpMB0GLBYD5bO1qWdnm2Xme+iZG/4QcINitR8en3nKPLktq1ybvuPHFo6zRP7NGeSu6f2Ug9e9zTDEWydRG5ByYX2NWzFzPJh1B6uq3vfu4ffvmY+rLY5S3ur/Na3O8sPR80W2g+5jsyiDkM8CaqGXdbZ22qqQJh60V1bAGGlBcfwan86S9CvCwAaQYumUcyfx3R++2vjCNFXGKTWz6xtV0sCJcHVraovXcYzlUB51jZP8KFn9WWzlyzE9f+jTEHoaEzycluCQO82BLMFG3EIRbBiUz4SbJ+pY4fWqHPeT4h3V7D5xFrDEKbRpnsBTeSWjhnskvq3o7iqt85baxo5mxyuFHkXaSQaCNqFziAz3rgA6M/G/xmk+dWiMQBiNna/VUoHQ8OWkwMgJVOfjL5eZfwJhhihXc8q/D1rhK+rQc6Sy0hh2TE/nQoNH61FxhDuRJWzu05h6xsfcJulY5jr6AAERSAiBtzK6r1V05MBuLC+Fjj2Kx7W9+SA3jub073ji6HL9yLJ/Y+v+rBYhFzgOI1WnIomiN6q8uJrsWGKufug6MZhyE0Dp966NDwz1yrW2taydTAdwczJwZd+o81gAGryMm1Z5pYN16gu/kccZgcnDYKyFEi/L3PjG3jT1DudIJv+sf2zNO35+pY3BqKYWoFjfecIfX5IpO/sdm+IFx6oFs8gfi+MAJyNreC4KNV0tiYtc5TicNTRvRu+YIh6n5qm4WeNS+vvjtGElxcVis7WN5bQt5MeDE75b61FmvsfM084tt/hX94mKCb9cQeLUJMZHWnoEcPLe3eOhunx6YClFNjvUvamNqyMH4nUvsF33jWVufUwYbzPyr/jkbI7coE+/ksYQOKqHSMg6FIkNlZid+xiARKBqtVk+bL9HGrNDjpYzDcNm1Cc72x6GmDCwUh/WbPAfjMtZQ3k+MSkdCDgXsvJiZyEqvFntGbYSa9O0YWjq9C7QvRHH3sbnE7wHGNDyGpRDAZy2H1gSy4ukn8AQDl+afEcpF6d49+v3XX9/89ttv2Zz/x43Od9/96EbSDc+Q5sQF7eFG3hamZ81mk85ngdkwYwvGS5uNVouBLyCbHOuQfudyVZuXvMMBn965yxnvbNJ+ywsL3On7Nmv7Xb5t+tvvP7z59vcPbz7/0k2g8QINH+8W8pnmcLGfVwyiki+cyQVOcttYE3eUcvT/T/HCu06XW8a+3dokEjcbHT7H++2HD75deO9MEmPf6u1baZMLue3b7YHlYr7tvoiAnDtv/PK5/J2r8/l6NgHJa5+DoDEUC5UB/6wgMSLdF4Q2nvnHrjOU44KM/QCJgT8g2NKoa78MjruS/FkqvuCPz5n3s+ZsfMTHeIjJYepVRiLFDmCQu15Yh27O+SwvP5kD6v+RtUZePL8l95TcBrzuiNO6auw4RgJ31LMCU4tVMbftb/owqagerROyWTNPPY+/06qXDzHTzhwIuvo9w7tri/zsjxenWf0imR94BT/omoOBvboEynlSUs3jyiTnxPzzyxplPfkCkI9nQHj+YO6yThnEl5ehuv6DGhHgzH8xC3r4kbH6yStjdZHlZ96JgsGOBS+o4OlO2/XT7FY6QIbdmoHcBj1geCHsE3/yMI83XijyT6jxIpKPv1ln5GCrP7x9PoVzundTSr4i17wViRXPL5HnF9tEiiz/sk7f5V0frNPPrFV+DFGd9iDh62N/Z7rwROo8t4avsQG6XIQlwEOGfeWEJhfGcw6Rixcrbeu/cZ/+cRP6b9d8+OEuV2zsXdkwspJD965xQDGIYkGGh5VIX5cc+v/i1ufmsAbz3qSABUhYPCEmYM4OjzCjtAy1zrnFqRiMVz/kExQ3/IZ7NQyK/SwwrBe3D5x13rMEjyfApzjDQfwJZkiLshO7BcFqGrYQTDsTXGpHbkCeQ2umHXF3U2QcANJ5eRudjshbH3K2fjgQU244pjEce3NHf/yA7rh3iJuPNR8buGi/GEW1PtM1BjaYWOecabjSzMcz8STZXI2+NcQAW87YpJlHQYbG8Ru1j1e5x2Dndvn3WuxBZnPSmUPbRDPu+pb8F7Fj3pXEGXoTk3OeWBwDuYATGtFpxwfJoMVOPCTDkfjIhBo9HtuIRds51Y9XmJ2Hng+fdcp5KTkPxkgEgzQfMSPoPHI+6qIYd/SV1HZ5Y5/+rqdTI23JaYJhZ5/ksN/4sfGCIgZ53MogMZc3MMXHgR8wwdr2tK1NI8XCfLEb63XCDJ21G2108psYej1yjPg2oV8kzWExY9lQrzY7h0sn5pQirTnUJzLqEZ3Sgdh5PiSG2/EBBVsE0fUxOM6KO4fpTnhiRC9Aa2FtB9A+xmlnXUFWyKldlfKkdoVqzOYVg+ODMa36PTZcj5Utv5hOHnUBfy2Kopf4K4+FRQBj88UK/Zxz8sIiNdY/9u1hU5y1XibUvjUoRmdLenFZ6/ouhvMF4vBJd1SLMejjX2lkgZGXDnNY5eYRn0Z91GTCL4uN35RWuuya853j4Bijdme+nxzSb7Sxcdz8rM+Ox+ekTQdwk2oi4vjEP5hzMXuncu1yIZkE2IwQ1chPvKlDQ84aNjDxDDhsGPfi9zNv5czF6Uc/A/xn3iL+65tffvm3myg2ed9++P7N9z/m7eL5c0qF2DVVPC7OIQIXLm5pL3OcMfV4m89X+rn1XOCDyy+Abv74XDHXKGCFi/PAlZZYnnLA1own74fymTf9uHJh/duvv3lXmgtgN+vZDJPf51x4w5FfNiNhZD2IJNdGU//MmY0gjxUab3WNa8c59+8aFxOw1qBzkGQpitjI+dKtvWvuZ3nZ+OQXXf+E0x9vfv/t9ze///67mx82r26MUjueC/tFad0s9FvMgx1O3HXDjs+xek7cj0nAerOxQuc3bZNB1xB+rTRz2Nw6ZlVWhtzRGuJOozgUIec5RVgMxu23Fm7AU7PdnHNnklzZDL1szuPF+mZehEgfpsWDa/Hc88zHCowUA+YHi3fvgpnc2XT99Tnn1M/1hqFYNxFzJJC5aOA8mBNiPNTTGUFOtoUZ/1un1ov53P/Lz3pY/vE1QzDIMbbA2NJZOoYYxVNfMkup9bl6eiUn9xfiY2WA9B+xfSzCGR3Nx1u4ZVPonXM36O3Xncc+sXksbHTsiZ55ij9IqiK0HsAiy+926sksV7HhWQMyeThYz/l77OA+qoa3jceof388QMUSpUEJwjC/PN3QWDe7Pjl3c94Xkhj73RtyidNA1TMYxIhOWK9TOher5wzPNuqV5wKeOxTkxTQ26R/zOM16pc4+/+T8ObXjcYwztfRsMgcsCCXjMWJrPsGqiVv+/a2PYGH0g4xRjkK/Fu8L/+ss7uLgaX/ibdIxcm1ofDmSZ9fDxkUHGRymv9j4Bo8htR6ojLBr80z903ad6bEYavwza+BHmp+ah8AERXiIbQKF9HgPJS9IhBITDeSJCFECiF3c+jeqfWhoRxEix/UR18IBgR3nifGCiX/+bU5aJiYw5jJ8iFoMjoQZTuMPNBiLZSxk6nXAZFq0Ata+wqKvBWxp1pYOak0ArUALuOZfrYm3ukhWiCs85gGmmLG1xb5NznQxiL7hWguCIn76EBlj44vFWAINHQcxI9KmqppIYuqg1yqF1KZ8M944Ta7Y41PO8Z34jFuP9vA+jZzRzxk5bmUH10ZCgqLjrdOe1T5ivOZPFsVMB1o9FS/jXTecMfRsfgxjLbfGEAhAmvY512QeyAddEwNiIk5HsPOKbizMKm63DmuHQXNZnNd5NbQ2Qk1o8eCWxtHcZ3xkk8PQQtwLP3kwkk39VRK5bBgC+qwb+W39rEtMOuda49g2cSvI4DEWTytiTzLjxukw2thj27iBmnkyrrgX48llqZCDcxGcpbHnYzNxzYYL5SjWB6eTt1wYXx5YijOycsCbKK0X9vaV9fEsiFKVJy/k5opLGv9xeG7QwVV0eO36XV8YiUqt1o888n+4FHJqVJEFaxS4RTMc9LUew/H4PTgh61CcAk982A4HTIZKOWE9uS0Z88aw+w4sbIvxap8Y8d9awfDSSI9gZGOM0ZrGcBtjTtUm9wx2TOf0ZbHjmb+RfXnCZ5ksbm26JtwwRiCVtfwiUNfQxhs/Jw+/Gvc8NpNr60S0sqDXbsYWv1G37Cojws/NuWZB5goz9uIJEiNchS0GYirpOlfeGGym+xbqz2/+yGbwl3//280rnwGmuYnMHd7vv9/NOW/RpKZ563By9O5q+PTitVe69G9LnyGUwvEtd6hjny/efvP268vZt/DG/fPn/qmiZSuOtVjEAWty5oMETH/dnI1tFGzQ//yz3wjO29x7xzp/szkvNLAxpOHn3ddcHNPPwV9PieCmmwRq7HPy+uxGnbGPP7nSt9IXR305AsNFOJvxr7/Nt7Xni7bYoHcTZzbhw7zwlu8/3vzxx+9uFqjJbrj7zfGtt/MPfnDp4wsN+Hydb7En1/fZkHt3Pm+fx/fdR/4cXevh80FsiWyzU/6mE+GuneY5dpFqRaGIntPaHxx4YBcdNe67AXL27mTXHi9yoBNrAOAuauYkyg1ofhvOmGgi2PqT/1u/0b1rknhffcoX9+Xt8O++ahxC+Of0pff4KQAAIABJREFU8E2fQL4ONP2Vod4GvslFIEXJ1R03WqkDBt6c564pejHopJFrc9x5qx6M0iAAdtsqbS0jzdB6aRQM6mRhULV263t8sAXG9py7leUcApi4KU7fF22R5ZqYmu2LO7zQAddde30RJPMUmSE8oC/XE4FhHSc35q7a8k4uM7Yy6e9z3cFIB9vHqqAYjfU0Sp/4vqsmj7dmVnAo1Kl84L/vHGLN7OacPrXQFhdQ+H85wam/LyL5fJhaBROVMbHMeHND5jhyEx+F9WHtR2n8rNXPfIPZ5FP+8c0mnXgJr4752GuNQjYvTWLTGhOKKq7TVkCkU+damVntD1HDGXDQjRk0kziy4BcxYnyNiU3ljV98qERtEyd9HwfU56qGm8pj73OtTvW/x0QHc3Rblw6L+vJYi6l30C9WerU7mE7YIiId405kC0ki5jtecFi2Y3EKM88HhdnJH78zLRZhiTyKdwraIhljA89kNf9Odif9gMthUcsxuvh5QYZZ4uqv0U5EzmIXWTPczCCyR8VrEQwe/7N5xtKW061lLB+YjWo2Wi9HsDEDw1wI5yjRo9g5eDljjpGnJ3dQ6kOQzQlf2okZ52OHfHgaF9sS0sdAy8P/ObQanc4xCXPyIMLxb39jygCdbc8zhM+Tg0zRrd3w3XHExCr2+q55fazl8jZM7e3O4dYFriN8EBYjYjybXwabp+abN0ZTd/UoA8QPOZ+8KyMWYbbZH5utwzHAPf/2wqU+eACSM/HmvHio8sP/bNVpDsprXEz0bceQW5MOUOBDnIZjLHaO+O4TkLIcXCJjRNhtBzd8sUW3vHesrVzpBR8rf3LYGpor2tGvXOdycq5i15iR5XGqbAIQAtwrK5faoxt7iS2OLuX+wqFYVQAMt23lSLxnjq35WA0PPJZXnz+bi0hRnPnHbXMeHto0oWIgUDcxsM94nwONE1nP9YYgvJ41UQMOSu0hQrd5nXVJuPxzZifkTRjfaB/YzmswMJWDmIQpp4UQExkcEKrIIWMxIjqydF/nuaqDYaT4Tlz8TG15gzVt89Mg9rLENf/Mo0FrPfzO2hkM8xps+vwWaXqT02I2RuuqpXqDpnytCyCbt+uBWKdjakbxbaLoaEDoz/yUh2LySozOApLxh56NXEdmDfDNpjFXg61BjACMtOogDWalwBestQnzxZ64DPt8kS02m6RsAv/IHdr//PsX38ruxjwx+EZxNqa8jdW/b8xdWzASzzWd/4u5O8VmnItYAw0XN7sTbwuwNYQnF8zZouWzlhmwWczFPhe6S5bNxl74Y9/2UsmWIYqzBhJ7a4EvfT0CS56f/IKn/n30blTf54WI2MzmDypxym8xN5ryElg1hmL7ooRusQ5/L9zp5rkPnbNPXsHtCz2tHbbUl80zteUz5/pbg5j7Fls+93o35+TDnXFeVPgrbyt2E57YnMUPI/vLxzXzLnObdw9QY+6ap668EPDhu++8c0/uyN2oR2f9N/GwtxbBowanzk1nhLNFgjctvrj3kLOOHbrRYbOTO5G9Y95v2++mhPmqn+skj53zuWH5dEeETe8uptMfosmta5LHST7/X0PP9FmP/noHPdiB23oad+hf8hEM9zkR2FjG4zBD6L20iQ1WHy91JV5divilH/DI+O1jBYAREGCec1x5BdL4+LGOh+PmXwDMwFonwNLg87Bvd2zUudXs85gLO89EWXe7jnod3vnv443aC9t4ZCEoGUm1dE5ay6fZapTDckLbO+f3uW6euAafF1nyeODJLHEau7HM2G4y93kqeuaFOqRdXjxCI2N9zB3yrk826Fmrrht8YMNv/bd/38ESfNbUXvvFchthn9xEQRjbvrCdeeCxF3xqy59k44UQZF3rvZvu+rGemrp+Wzk45Tc/qgmAxHxBHUFO5HrG2OCUhsVijfVoVNu3ZoOpB4YZP+X6rkx18S8KPR0VVRsMuEfCWIw5tnAPlyon5it/XEZ9cKBLTZBvrowYv3wG/RamZheoFGNfdjmdAk4xSnoW0jWLXX3XvjEwqMeOGW2/xYxA7/ozsnUVDWqTesUqBxcBj8s8OJygOutgXluV4Q+/jY992TVkF3T6OEbRutQGC2ON+oy/wL8c4geGIIk58fUb5Je+MVmwhkYlgX0geB4/a1xy80APvg9GfBpr50EcoeKQn4tDXq/xrMX6D/m+JToAGS8mdiYn7urKu5hDLoa1TejMT2OPLGjYXpyrBx4rfHeN4Msjh/HiWA4D6KCPScamT4AkjAQ+4G0OxV4vzzWxa6z0AtMx/fndcLBvratTTo2GH45GMT6jIJADz322gp9YRxab/tQ+ciwjMt7W6+QCZtriOMih6HVRVrODVT2VCRK8NXLUHsmLbabW4j7hF8y5iTUjkG69JhgacYTU5ln5rQ9a52jcmtvkDAYwhehxeFVWp+Wv4eKQ18YXAyvQ7zwZ1/iRWofY5Gfrqe3gYfulb/1jIKchiT0wW0P9Yzm4OaWtkQNtialULKwY6Sz8rq3ymJo84h5uPBfM82G9sSU4sZbx1mZjTG4Zlt+wDD5xGzP9gBBytHMGN/CjuBGw30acO7IrTuNu/fTFbPOyP9ggZAwS+luPUXCRQTe/jdaedRlpuWGFP8aJDxaiHJ2DDBYboO3jWzssy5vx8inC5AM+grRrM4MVWK8gATD5Li5+m2MBujb+0U7j5+HylN0SgSk/BDQeduQ8F9Oxq2lzcD6VDOGpFVZQPm3U643SecIeo8mN4O0manx6JwgDNpD5ZvZszPnyt3//z/9kM8i3ZvMW4G7kereMjV3eFj4bSPhhYwsgfTe/I2PeIMCmnruijLHhrhubRy5AJZQY4vhO+HCbO+kyy5Vuv9HdUQ4B5Ce/+9Z242dMqSiFjdhprSF5M3/5B93YcsFN3Ylbm9pSE55nfSssF8WxyVa4AXXtugc7ji8X8uA0ai6u4c3/l/BK8wvMoq1NiconPtTj/WzM3fD4OV7mCHs49g4efWR8c/Z+azS+vqgQyEClz0aCz7DSGpw49NHRJ2een8Bi0/97Nu18KR1fmMcdfPRs4pk3NgWnFbTD7U9+Cql5Q90hNSEPJBBMA98NUDZBzAPv2ODspn2eQ7DrCzPx8cXFcd+C7kwHc2Bx0ehtaoKvazd9N5IzZoVonwMvmliLvIujHOHJHG5yAD77fcyoj7h2eDRuQLRulghp9ac0Ns8cxs94o5v++teqluveF9Nqj92RI5oBcyZ6DMSi/qdIkz+xhtSZn8J6xFz9+GHaF0nYIM4Ldo/asjZ53Mg2fQPDh183zfgTsyqDzEGO9BvUM7Jz7Ts+d15aO/6L7aY9LhOnL+zNF6slGDGbQqP4QlleSPwUYZ52XBtwXBty8AVD1kZeQPL5LOfK+ly3jzde4OrjM3lxfU3+ickLBci7YW/OTQ89vbadk85D7PI8w+Ofd7h8lV9esOPFQ18czV/KcOMefB+T4jQnau0cJom9zjfO5L8h90z16OPdSkKrkspMw5og77xFH6W+wa1ydQzxFDAHvcQHVVtk+qmOTE3OGJzT2CAshso1Jb+H8YgHX8seqNHBbUdEHPLL8iwQcavPmxQ2JEEOdPsZArjJb0FMGsBN/uAGY4pUXHyLf6AROAC19uIiTrt+5dNy6FROLzEhgVd5y1/OlZ/CY0Kr2eHtq5nVkEwXE5zGVC7kc1jVeDmuazmU4+o8D9fKimN/eRgrA1VoaDkbk276K45Rlt3VjSmn+mMa7ms/86BOozlMLKA73/EaH/xP23mMcucUnRbrkHExJjbBFh9dMHZu8Ss/shjMoh38jbPnuBzbXWvgLC76Den8NbgxqwoZuQ6vCJvhI6dw7KYdrKnI5gxIE66uwSen2AKfJz8vKrSdCo6/uWuEUqriyDXy6pFvf2qD7eiX7/pTXgLjW13Gm2MkkwFWaSK3Sww9xgYg/Wrn8ciwxbs65ytdZDsPpKUgJ/rLpvEjnKZv/5cq3nDnlVnrFl3xL6Dzj785wrehOJfVybzBkZ5cyuTVJ/a63OpY+0U2meiaoFFQ3Vxb7/Mf87CAS+OUj5gtRjEeWnMaUgcXUlMP9eSw9SmkCEbRt8KBOdEJhowkrw7h8KOO+aXezzowaLV0HrzmvZkBuHlj62xBA6hT88IensCN7swlgfWB1tQTgbao2v+yhmtrbCHWp7UoAEcQDrHiYYqPeVc33tUPJ3zlS70WFr+6U0btrRZ1RLD5jZXoyMDIv60NGM92MI1NvPjMvJg7eMLfOGIHZGsB3j/hNxZzZNqYtYNAYWdwuspOP3zk/eBvnkCEAJ5igGn+c+KxPXl7PkZlfUql2cSIvW8HBavECpaRXjil8XnzP/K3ptmc/+//1805Mbgw7MXh3imbzXouIkHgAnY3UdTJTZYb38TPxSt5cRHLRS559YI2PS7myYVfLnLzHMXnKr0Izp30z2eDmjDB4MLVFzVg3R+x4X6aF1CJOzmtfGPtPFIGPh/PJhb+f5lLrdms0T59lbzCAT5/Zc04XwS+r+5qx4G8Fpt0WmdoP/0Y906ub3Unhxib2XwunBc9+HVTnJpYG2MCykayb1Pny94+5/PTli+5HG6aNS8en+U09SDeMMOeRs2pA5vid7kLv2+f58+6fZc76n/lzvqbN/zd9dnEZIQnOPYggGCFJp+B41opiqBcauwce3dyNuSJ7yaINRJO2Fob5rEA53HL/2UEaM7JFT21Yp7Sd71lPl23vsAw78bABq/MJWvQNZsxMuPhn3g8xNzcghUtejI+NWNOiak4PMdEW/wZT6tPbAo00lqM5+BeL6DFflgvDqK1nPAvttiBW4xaUg/yo9m3fg57iG4xH1JtHUePH8368liIg4/trENe+GiM1p/HGiy9VoubsfHvj7WADqI9xzOPqtb+aXDrrPvwHOfY+3BPtGd94Ck47xYBc7zkFFdj8k3/+XEjr0Ofl+iih7PvhMma4Nx3erR/mCSBpDD46TNgTJ5gGLcD6gPO+t677FDFEbu+g2afA3yHUj5uwotv3aDzIhMvOrF+ay9ZggJhY64SO7wvodXlDC9tu7bLCMFww5dumrzOgBAo0YyBJ8Eafv0w+cc2cxG7Yq1D1yfxOt8lgRYPjvycNSx24y6XsWrUDMByrUZSXe3PnGBDDZPf6unlz6yV5DmjJXqU1IKeUBlow9mK97wk8RJ4/E8iSiNUKVItBwM/8egMdhNZXijS4vplgiSwiMPSOE1x3IzT/uLeeOsVcinO4q+0YBJPpOY/VJpOBmhf4jWUR3S0OzmpIIQpLL82zsTmNLKje/pGNzWrR70LV7/WYirywGjQ2kNY/0ddmNfXloziv7wvV5iO7RcuXMRbh4Aflf3nPEbDD7bgExSecJnc5BEZHGnYYPtsT24vfMZMn4cDaGu3usZ/8ID98Y/V8pLJjB9cTq7wHjk9fpet/eD0XB24W1fkNS6/m+eTF0Y0rdvlmCB3Co1QnWb1x8i8I3tiIzc9MEen28ZA7LN6/bZ2+NEYXzwE10LggmpHV7fYtOaYNxq2Wyt6I33FNmDwIWy7HIrNuJ7bWzZKc2jcQbdoN5a+A33mdJ4od57guREGZXhPfYfZ1UW++U48MP7e6rH1dBSz44vD4hx3DazH1uw5F2A0/3HYuBke+7FZyK0XSb5sxuFuszLTk1L66K6cgvQOrGajxWRqZx2qu3zrb/4B4GzE+MDtrBP6aAx5fYhP04f+1qqGR4ONZcjz642FdNpLjYB5Xasv68eQwyF9esQ/PmDFv5lE26GBViZf6pEG3K7tky8+oMZZffr2GKBDhR82tnJARlNaAwe1CkY69JcTJtvPf4DpBycGjVodDuYGMMY2ULDb1vEhFvH67FzD9cSLfu+Sc+Fm3l5EF4cLFTZHbM74dvNf/vffXpCeTXl2Z2wI904kF+Zc2LqJyUVnLlutKbgfvRvatynDhYtL5N7hDQ/vorOhT+hPH9mQz1uPuRAO7l/RUTW4v8vnLtlIMW4+jRlBSuNtdms31dBui9Q6sB6obtDyQw3YfG+94eVbqZGpqz0X48T/Kmf/pFE2zG5k3RyHb758bK5yYdILbxwY7Tn9fSECufyjJKYXz+So8c5B31JOffilLoBRp93w8BZw/JmHt/lGcvC5w7936hocPqkvQcOldUuXzUGEjYZy2vDFzjvaqQWfs+WFGj7i8EO+ABA5GwTu5MkLVHhZpQCw0GmeUIwMo20ThyH5GIsNOuuFO+d8KRx1j2/rEjj9iQK7aeB4N79zBhHWo5v29HeN+nEFP2OfO46pJe82cEMZG/DFXr5Cs+ZSA3TGGJtn3H/oO58jN0Vyh+0Qbo0iqjKlqoKMVrfnEBPpYGY45rWVd3L1sZsTyhvKEKDaGU6ctp7tPxTbBSfYpy6RWx9k2CyJkSPzOSB19fEJh9gYZ3JgfktE5eUk3+YuDn75tzlHPcspvQbPWUvnpi80YoVh5HLvMIOWfdRuZDGj1vy5RluxeAx+ymOCj4VsG+oOd332Yxddp+R3awnqP7VwOPRiw7WNL6TluW7eTfMX79SIKwg+j2Zt+lybevLlkPT7d+TzQl1k5sFzMO9kCR41J4ZxcvD5IdwYN7vOR9lNfakBEQmcht1WRMEeIpwqmivz4osN4hcDU2GIh1xspNvn3HFJ3Uj1q1YC8M887PpRo/nWCKwI8hyDTQIGOGe7gwvHCbdrablIw0C11Q7hw7+ycj+fQTcxNVu4BBGjBAh0gkAKcuLmnJ/6V3aL1CD4aTRHR1NIVT0ANwW2+7cibYmqBfHGltsUrCyujvEyMA8G08BwKJ8Km+v2OXfCMHRSIhHTySmP43M4NH5Raj9Oh0uRgQcfUA5pGZdvxnT4zQOhdcUgbeJw5gIPE6MMxAiivn7br+4RA5/JpXHL9xlv5ZIxNj3md1t7QpVJ9fDDKgC1n/V13NANl8FFJZpgEwPdtib7YsMDpig1qvUYInqJAebFMzd4WoMHvxljSreZDFeEQICrrnE57hoxuuBjig6DsVfPwMYa6FwJrVjryat1QAxPnhjPE0kssDw5xUhqBQ4/9FOfKODb9uS+iuGAwbGjW4z2Gg+12MPb+MzT8Ss+UDyXwKk6DBydWpVUEKQxsaaPG/bL4dh4IVacDXmQEZvo6qPJD6MzP1MIxwPgf2A1HYbETjs5dqgoh3JaWWP1eOOYc4SEOLrNx7hULhpsZq4cgz/jegNw56e8OxcHmQCTF2djUjDEh4FBG1NND8Si1bqxq+kRTmI4AWVU2xy5rsB/dID4vATkY62evOSC+c3HKONPJBuQy+jwGx9iGCiW6MaFDt0+ntE1Tg2OUeEPJsNX3Rh4QtdYIi+jmuTY9d1qIIQBI/Ozv9VHmn7iXuvpRbbozkXEL2sT4OvECKQ5o0I52Fx8ESOiPWsf8ztFqWOItwTggLYBlsn1r27jMYrt4ivuGASHNSXsxLCXzVDi5ILUMzmXgHZryOboj9//yJfB/ZKNUt7a/BWbsW5quEjcjQ8XlPSXBxeyYCP3kjzYbLZ4a/y5eMc4zQ3lbMLou2nHP7Wz7tSDGz+zttlo/sUXezU7MfZilFTNOx2flnLuW927YSbXvn2aO+S9Q9waJB54+SG/nKwH31TPn1Hav/EOH3ObeuEDZkqhnBcsnGfZtaZbVt96+lc3067HUTTHOFA/ORAd3r0LuRfpbH7Is5uRbsD3by/rkAOQ5AUC64KauQmPoH7pJAfnWqPOgXFnPnTOYe8Wix0z8uZPubE5+Zi3vv/w409vPnz/vfP83i+X4zK2m4TdcOLrfCwI5y3IxlO388MGKb95YYi1559Yy7h/kgtOPCOFuGlMnwX2SMP/O0bGXGYn7uaGtwUz5uMCrrO8uECO1l+SWxvusNIedcqImsX6b/xfHjfqobdYOYMU3tIORnNQ/HIohXmhbBiIk/64175Q4o1Z5MXFoBFryhFcmwG2e+vYGPErZe3FcDzeA7q2oMgJOXMyefl8wEaRX0PFA+Cw8jE67AbukNOEF/TAwroC9azjjdsU1rt18ZozImzcK51iYbdJ5+wP4/bT6fVbX9MzZvPgOSJoeVzz0ZOukXKCVp8/5u55BDz+aeXMYy58s2apC/n0/9/aYLePY/uhoiaHvXv+VZ4HeMGrLybxAhjvVOEjJazXvKj5OJ/n0l3HgIJ4cmWUMT+kTkufQnXI+dZX/cvh6mo/XsmbXkec6QHc5mhs0Do34d76RqtusYMVnS1ymnapY+0iQI9u7JznjR65KelJNBr2/Fye268Ui9hgbEiw2996KBYpd9DrjEOD4YW9pDinaTMETaBCdXZNGsOFfvhEVGlw7QT9JNyYLfL1aTEvHm6UtK3ZLO/lo/alYLGI0FymyMUpSvt3Ast9xng1zADEZziXW+wy9kE9QcwhoMhpxmV8eEemLpZiT52nrppFL6/IzsVlJC/2YgfAWMQZnw06MY2PY8b2OQZfzvggR6E4A7sI2kfpAxy5OBtnco/jyvFFizeARRkccx55cNxU8gCgYbJEODNeCmOCGa2b0XQkjWCMc163RgamMvyAWUarP/M2eq0OD7xKhbM0EgDfk6MBc+C8Njkr5hwsYujjom9SrVcdpJ/us+lHnFFuCeodSzCNObGX3AGpfHmozgEeNhT8Tlu7U1PsIpT303D7qNUHQC5T54NZROvEPE0dvFCTggfRRn1s5AD4wUoM/OX0ItRGOXD4YHUAG+PgjGvD6zA+cXtps37Fq2Ln4XCLeKIpwuo+ToOdn/VRfmpw/QZ5kEYurVQt4HTbStw8EQzW4iPa/tOnGCt55gRS5KgCPTNXmaKxBVjp8Im9OZ/6aiwOeOUQ39KtcQPImUfNJqYtFMRa03VkXJwjSTJDdxhJjqjFULk8l0tt1rJnEA+qoh0BsZMJv11HnB2jHpsdl1QQYnNrUP6aqop/LqBItc3qp9vIFUeWjnV5WFkH5Mg4pP98R8uYqjT+Mzc54dY4HiVBxOWzXrURD7XZOMpFlQKnTj6SqI1Hrrp035rpruygDib21IINVjeZSLrx4uzzA+fUn4tpbLiTzJ8d46KUzz7uBto7ZbkI50KSOULOL3LutP6VDRYkuNNM427u+/fvskF/411YbM83i8fmPTvcnHe+8YEHHLhwtVLwCn/l4eUmAPzIqRn10Y9RwypBvT59qzbfdp5fNpvB6efN8a0/m2zc8WFjTu7cOYYLf3+cXza7xN8NOThfZSNI7uBYC1FEiqwNeaNQk27my7+cTSWm1KEb9NQ3fIpXDPLcenzO3y4nHlz3F56L6QskYkWUO3RsoGv/qJEFinhqhn5bRUehmFz/49+6/+ifdPvxp5/efMNa+TprhG96zwYD/tuKxjEyxbDPukvczncG8Acj88ua81uxU3dejCkd6rGInHcQ+bwIIRZGCYUsq9K6dbMz30bPxie/bHj27cDLlfrRvBFtMGoKNbhlfQUafswF4ZHLYomNf4esxzZt6NZYP5PBX2PWBP+wqbXYxxEe5I9gOGKbVsjxYYzN8ECPNdUe9DpEj7xIWKVlgG/j4lFMjYAc6yPH5QHQmkSbxzk45YpN1+JzTUYpuu6AaE+MqdnIDJC8+/EVWd6Y8WEwM6BSxpFvDlJGyMTxAxYe+KZ5JjzzmbXXFxA6xyyCd3lHzGfvas8OPj7M/3kOwidj2sbkbEuMoCofCWnK1+hw0oARryaVz9t8lpwNOGuUF5LsZ8wa9jkAkPz2xdE8T82Ys3mQNAGHx4k9m118dy6PTofAlgXO9hCQHyGEjNRwDFaIxljgpuXQHmhKcryzZAzsx78rAYjaAiFG+FpTWQUh+p2vEhVpzdeq/z/XACLnemjROT9WH4FlCfaJpx/4yzMbdCOZSAPrRhLbjJBDIyh9dDPeIoBO3CbEGRIKPVK+2gqv7ZIGZQuBTxq+MeTCr6lwLloLhnRjX5xaARBf0sBJHsie2gxGL1eGGVvE2BsehyZV5eKAmbaF7bkyIPFZbsu1ZOoDJ+KsTT3LTXshgrTxQuzGGNINI697cQwiorHPQAnx1mgwfbUXDBzSiko9m8GRW8SLicNyx2btyYZmTvHpW2UN3CeTTqTcajo63DZPvBHn38mX+BFal0Ot42OzcSHwYJQuhG4bfwQ7L6gnRB9U43PmIbG1ATeGxsRhuBoDjPy2rW44T3wxTC76DGpP1R71fCAsKf0ST/vj3xgbETztRatU0YOVNXR844kKHXCB8HBzbH0j5WdtLFYMh8s+Pk9tFmc5xc5aAt4wHWtXbOStQ4Rftpg0VNhOTAS3bsP7xBus5Sn3guLDj9M3NT3/0U3cqXRSBlDzEkj/pmCwyoPTOgUdbL16FEIe1BysGGCz/wmoQ6FGTxDufAwOGsCjk9eJOS6o8+9aEySjhtPLgebNsGhCin2kg43p0pO78WFQn10bO+/iPXk9cZbBPgcJQSZdi4JODcChuWboTFz4K2O82HbDHBl9zPFJqy09JE9NRwcDE9pgyGkSX6/WpmZ6x1bUOes+kVufHOEDTjqVTQyxVTrP+5ECMLBvXRltW/4Z46a4x3KtvNYxwPyZ77i7puJGmj7RaVevc0QJhxHsHOPkpdzqvXgqB0zrAfhBsoM/j6/d+Hh3J9bcnVTuxSkXo71Q5MyvXImZu0lszrsh7YXi84JxL853s/5VfHKvPNjBSB7dnL8X87vvvnnza74NnQ0y+v3TXcTjopNmvvFz3kiHi2AvZtPP2vUOFn8GKzbao5+k2Q8g9q375A3/YPPLpu/P3/Mt9LxNm99w2Du1jUkQvyjeXInD3P72n998UeO//vWvN//6v/83bzfljlY2obFls/rrL7/kjnLySSxy5cv00HPnK6Lyj635ZDNQ1hGgy79eWNcO/924stGlJtxB7xqODw1QckxO8De/8IALvxYgNn78gDrWi1cEOif4930NQtmnaMoxnrXnmHlANY97tAjSUPMFcrRGMn8UAAAgAElEQVTvEvc77qZHmKVibF5goC20ucKGvHOSmalkLc4cdT4mr2C6IZKHUD1A/9nASBDWiXchCZDYrR13IvsW/Oe303tnPQzuZjuchgOEyQOqck3XsTxWuATIJwaPpuuYzUkoaSEA3xMDQox/TtSKtueqrh09fYPou26wpT8Y5GAtxi6no6O//vTH5Z4RmDuivjCmA34QGpr6Pg7LFZvzC3wejN304gjDPgdTS3uQwUdb+v6MVXXW1rhY0Z4kInPY7Hc9+U6RyKtqZ73hx2PsY94V0xevwsTFiPfUEX755XElMhBMKgTVdWweYwsu43suVTngGT2tNulw7dEn8+h4oRNe83jnuybmjvneLWedFqs4cKP59nZjBzvrf8Ko68FKyxv+zeOqQdvUVjqZRlHere7NwSBfOsXY+uch3xgTN6AvuRMPWQ5bi8aTCRrXdTr6Ld+dW7jc/6vxvHZFuHF5kin2tdFhuaqtxCKMsbwUB5H5Tb8b9OckYhDNFkf7OVzSEUyFlwjjBqCzXhAtcc/EocB71qyRzgKz3Ad1/AlGSGyjA+LYXQ1WWoqfATDT9kFgwSOTz0OvmZNPr9aH5wtf9MlpYoijpF4btPoG4NgNzrKePPCbmNjv9etTZj82ZUTcBhMz3W3WJQPtsB9+rQdW9pr3dbK3XNfHHAwUH1MoerEyC8t5ML+Am2Fz73xvbaIC8oVfBABPHDis3vPAYDBhT1RyHcf06NOGa4bLs3JU1DHN2qydhvpv3IMV+xMexwysbzrWijN4HNVjjWzHhEpfPw3t08MSF35ptUPqIAY4BSmn5bU+y2p9CCGi9tfqRhE0MZcvNmn4bVeesaBG9ofbw0ZdnE583Qdg4Y5/5PMfkLkwxGawT+CpwFPemsQa28FtJ+OtCwJNrkxd8PTCjl6D1g/JihaH/7DgDF6Um79qEdSk16wH/djVraBU5gYgZHDPkzWe0SeeZo0orhinJ+uMsN75is8hPhxxoinHDpuME5OUOTO0ro45DKd2eyTRNLgKwWnqgHwg6Q5W7ZtN89NGC+zLO1f7UuPQ+qIZS2N2pNtwMMbTBt/B5exjgTOyB8+unV2VKNN0XFlR1q7EilMzuB7mrUUgiGMswPJjfw/hjO/JKf7UXOxHPscmnfbvGShQes6ANkZrq2jwbsXi9TTQcQ+D9tTH2DnFBDVtzx2dOWKucLWl78Wiwdh85iI8/5zPWcdruptla0xW8XHjlreX72YHLO4aswGFgLG4GCXm/Krn7mXa19zRmbs63h1NTM5scpyvXDxysbsbzVxdps9bwVvTT9ngZ8+WO8/f+Hb5DzlT4D/DiY3y17kgfZdfeFkf5jA/cHGtpZ8IyiiXF/5coHLRGps2HbThHQKbx25aydUNeuL9nrfs87Z9xh/Z0AoR/vncdvMhypvwiw1vy4/tt99+/eann39689O/fvaiGD0XxL/9+mtiZU7cTCLL5jJ3tdkcIrdeyWdpdl7wTkuYXJLLFQ5+EV7E72LMPPZFEO5Gl+J9FGYcG2KSH3XmDFdfVAgHNiFsVjn3ua5riI0rRfXFDTBYS/m4gPWCRGRdeelDMG1rzEbiw4fvswHPN0jnM7F8WRW25OQGgv9n4kPOzGVKgDcW2jACX1xOtujNhbrx23WJP3nVfkynEJxo+LlePCcvvgPAaOTd+vUbr3sHcjfs7/KZXZqPlZx9HARj81SZA+PGQJK1Hvy34cSjBt+hkXTSM58cEOJ3tD5SlVE/NNrigk/OuqRLRxj6tNG338H6iDM23mFGAY/8LgaRAdkxHfvD1xOCIUDXfCOQdTDFgBf9ODzHhG8DYGoCaH63dshPn/iaYoMmDVl7HU4cfMxH6dN+HNELcs/L0Xj4RdUXCR6W48787fNNv5gxmfFYyXPVrinWon3mPOtRTsOHOtyxwuNHCCq3q8B3QYVvU8Jv7Yk1j/M8WPYFpD7X5kU51zA7Xn90MiZjnhjT/vozGNjBnWfJnDuvMGg7pQJoWjnewbGVeeXEIn+bHDxYJ5AWwzUh9uSIZpWxE+ewsXJI5Qn21ruRLseX+orXnKyrawzv+G9BT9AiGSOyxi+u+TztY4q/+ZCr4+IaJwJm0i+JU3z5PYwbsDB1riT9Eyz9KSa6gtd2+5KoCOMSj49Yi5PzwQYvTluoJfzEWU71wZd0BoPEY1xaB9UJEXftOBvrohWDSDf+cyJqHr+ayHm61s24dSaUdo1xa7MxNcMGlAPS8TLChgzkNXUhsTO5yyOy1mtqwX8ycWyV8a78WafKBCdM5yUeQp75uPW78mUEJq0+9h8cu0DLwT4PZnF7Bo9a1K5I6Gnr62Awiz+6mMGfZo6v7sapTpOxxJjYexZEmfHURfaFjTVb3rjm9/LLaGKfXGrQMBtrjYJT0SNv7YdWsDHQxnNqHD43HuGod420W96LXW959dXNBui6awKun6m19J99OAwnurAhDu320h8f5V/6D0cvdPUM5PIUPAHy07xkIHZ74zBBzdG+PUictnXZcxWLMrV+2HduR45xdFo/a5xc5Dr6x6kO9Sj38cPGtjUB90X35KLyzCn0tjZYbTV2XZsbRmkP+ONTzUN5BMhmYO3JdQWVGztduUYnywiXD1bjWgfYhcT6tYBhiiy/cG49Gxo543oQn5ZjfnglH2yaeI96bXzPGmAxbYMDw5VXxqslemNVMvANNLzhr11MvDgaZ07Xn1jFWtlyMc8pCrGQ7/p7vZsQT+glnmjj40AR7EaXWPLCZjBrV670jTWcML9xib/FnCzywBPZYflB5kSMvP5c9k/fi0FGXBjGILz3ApG8yEMOwWm+5AcRXawlF6BwcfOWjSj+3J1kU2oZ5gUrsQYT2/p0M4vPN9mMcQHYOzpsvHMRmFjeQZ4++bhhydl5DA/GbO/hCy8udr/95ts337z9pn3+XFc2ZPKbC2EuUGnEgOubr1Lz9ElrL5Z5uze5wu0tftG3tS74/fFb7+qaW5Ll7jYvOJwNunfQkaUW8JtGjl/7Fu1cvAebBPhyOr5I7NvvPrz54b9+dnO6a/XjJ94mHxzuxCcXasfm/OPHP33RgYvvfn40L2akT50o/q4XwhLdzTJ9Jia/1K417Qsd9KmBc92O89+42aQnD17s6J++Y51yBzt38KeerkmmITj9m959R4Fcsg6o5WniM5q1mh5vteXb27/98N2b7/N2dnLqLy+79E+xUUfu5lE3PyKQawxerODJxXlYXGsAfhsp77rrixudp8pY5WkcJu92Fqw1oT40jv5d6OROrtw5300PZ9YKdWH+pEHwNKLwQsXWgfPOBbbMLS3fv2cM79LHd1M516AR6IfVEO9cxw8dQn+Yo+UwpnFBtjbpthkn8hOsYtTLvn51WAz1w/HYpvPsT/oTqIDVF7ncpw83HA5Ac1pnH4dwtJEFfjk6/6yDqRcQMUN7uDKWDP7EEaRG01WIIybq461fz0eBLGuROWMtFrcg5IM/575wFtv0O2aeeezl8ZDzNtZCcWK7HIegePCNMblArM+7kbzYoOmc9wx6PHiRk7vmWZusT55/ePHI59KsVTCBIQ6PjebVnMqZDXl+85wY59pJ3QMh/H+ZzXzZSZHgfaEk4K4rxsZR1Xyoi70HVmRmMrnRR8I5we11PxS5/7/Ud2ujhRAgP3W65qCymEJmDEci5GwdNnbdlRVKq/rqBrd0gNQ/B/qDB2fnL24DhXKMtqdDZHMHfUnULkrIODmctYvqlWjFoTJ6fWJ65BN0CyKKjHLwx0HsB2NiYreLWywCjN9N7CY5ypgUzzhg8v+nRV1NfF5MyvTmfpX0lhf6HRNLSILg7gDLWqwSD7gaIarNR7M8ENsEsKv9SOUzfeyLHjzQNjjhRqPphVpP/zMod3xv21iH07O+sTz6uBgmR3Mhj+kf34FdH4dwFHO9kYLBqTovTjKWF6JHXAwrvzibtnYZqOfQENMJ9zG8eDcfbcdHvsJHgM+jL2SeaMvXSFETc7Eq61pEE51OoZFW7aWGqk8eqwsSRuOz2Pje1ngYLZ46HOFrjaaPYmTkLy9FscOU9YYeJE5p2uX8YqtmZLo2dm2X8wCMLadBfj0bj4iJGU2PE9fkp58nU/5RAwEGD1x8FD5yNdaA6YPd1GRjrRzvYmh0cqYWtS0H7GjM0TZ72Mk1o+Gw6wtg59zY8aqJds85aCxQh7SmrYc+qJaNvBR4KJvYpka3tVqOJ7a0NanHRjp1/aKwTz3Ezzgd61IYinPC2sth/8NdBfLrk96CRX506dnfWh1n6osd2lZouuU08anztZnaRdJ5H8fYMD7zo3jWFeAi9ixHuvic52I4mImxLtbEQYsJvz0YCw9SPrUSfPKNht4+NywmZ70Ga+XgIu/6WUzGiT0gE6128BCDU3ky7BRUYT8Hccf4rJfIl6kpcEGY5z3ic1HmBeJcnHUDyGYB/XAzDwISpZs9VFxoFoM/b9Zvw+6Xq9WO/5ibJxskNiRBdZPS2ENTXO/oeBHJ5qYb5N1EMndsWDhTQ3jEyrfEe0c3mJStdynzh7myuUP+Nhvmr/KZ9I+//eFj61P8eveHC2XuQPct8V4+RPfeu57Nm7oQi4vwr3LuXHFhnc+K5+3lv//2uzUlP3Lu5pzPnWcTmw31H7kzTp9NP3nC/dtsQnm7PfzYMLtBt6JsUN+/+fG//uvNdz/+4AYPJ2LjT7zd0DFmk8wGPajWADsuwn36SJHZ7Mt3z1gmHhOwa5BzNzx9oYP5lChHJ6ovoLBBNx9ymncEsHZ4R0I3op0rd+Xh7J9fc647V2BRM+/cp09djYQNhUljc/7Djz+/+fm//+Xm/JsP3/rijN8onxzI/ds3Hzq/eOGWAzWg/knEP9OXSOKx+jTJUT3jcIZHN1VsiNiMdFOn09jeOnTOn4CUkFjUjbW5dyHZvOymvC8cUO+icuLjBMZKPOZ85xILa50lAoZ9eBinGLwAQw7UqnPX3BafSS/nCQhouidvxljEgX++mwHnNfc8GACNqph1xdfx+Oy8vco2TLlm9NqctOg8owqbk8Q1/ScZPm4ozQHXycXvDmA99Bfu+9GNPRsvcs7n3QXkYa4oJrayGdOfVj94Y8p6yjnzyPMLj0X6ri3WUpTEOOs265H1EAP/SkQm3jwy9K8x8P/9zsl5PpYPcfJv6rNxYUAzJ3uGnB798ISDXLumzjqdDXo37Dzj0TofoPax0eeWfV4il/rnuzz+yjuQwofvKeCxjo//Vxlr6pI+z3PwpVGrAECYngJ6yJWsHN1LMxNttKcOsXUuYrcY9Iwx+hByLmBAFHVzVKRva1uOscsPloWYMThy67gRh+DonteQcDOnHBqzts4fvMeVE/36bo7xHcz3XWy1enEmAEYPqBbjVWaRCJBfM+JsItJjRKoID5YTpo1KTNJiM35L7hAPj/5PU8t7fLIbDqNsMa/l9sR8DGBGa+7LtTJS35KV/8aAT+lKDf/8Fru91rXoi0HetOXGaGuu/DFWPrbX5tbeuPArpLWd7vQTdchRJXR7hq1+EEbOXMNtxuqRj0C9Pk+ba2XcANZOR2CN2WMrYwA53zwwWvzLT/eXOpXa5rHYsYuC54cY60StFTrqAQ21MJ+o96J50vO0Dy6886xTTgN15i+qw7GgJ26jDy/qCY/8kFulOZ8aDTAaJyKdv7X6GQ887CJCSq6LwNkm/M7BrULjG7rOcVAbjK17MRYRs8EvBccEPrEOF9mgEhO/bcriQPqXTbQIRtJI61H8i4B8Io5PfZ/+h1FsR47IoNV5zPhYPuZga4rSWhwdsb+QkbOtNaZbSbB3vYSCssTbPM78dpGKUF2PC2uKBxOcWa96oIDkDNYJQcTl0aNzN3oxzL1Yi4nlsRMzh8W2Q47BnecEkd2xLBnO67DnxofM5rJVUCPgF7Uzp5mb9HetLmKjRT92yMHyPEE21qETg9cXNYrCUT5x3vW4vmLOoLoG6YUNDmZQYY7HP4jbX7/luvWRK7llM3DIl0mQKtI3IVyD1nwrhzct/sa6Yzkjm9p0fcRKE2K1nvcCdHKo43DBvj5cVLJJ+PJ3LzS1I4cH9wlmLC7U4PIxeGLkQpUN6uJ3M52Lu1zglSOb3S6qfhEV+YccOHnLJJsb7/LkYnY3P31rey8ku2GPeS72rEGYvcvG+33eEv42d7ID4xTshpZNORteuHG32i9hc4OWO8HB+Pz5z1xw9o4z3+KOHReiXKTyOOh45jFvOSYv2rmIzWa1d5K7IfSCfTbObqhnc86LFvBlM8sX1PFnjHi3ABs7Zyi45hObD/m73z/k7e17h58L9uw2fOu7m8nYwsPNHiryCe9Sq47/16hRC8LJKOdsEnPYWpI3bUro6mPMxpwXBs4LDnlBgnzkFT1z5jsemDPiwA+cvIWfO2Zy5UvP4HTGV0cMNi5755zP3f/8f/7l29p55wQTuvyJBY5y4iR3/jlXbrTzJXZxYU31Tj5Moieb2FOnf/wFK780OdpzJH6EidU5lkvGnJk/1qu/3I3MGoILtYQX88Z1hY34vDCQFxOoHetj55Oq8w3++hEnWHm/hTHkk4sXXygNlGhwhUMpH7ZJIn1yHRHGFemnOAewfEyqvO6aj33r0YD6GRi8jBL7n9qElyT+mOk7xpXxuHroYqcfNkDDnw6O5Dih5MNgBdr3cVDXRsJ84yCnfsoYpDl/7c74hErItYVIvIQsLuPl8DmfKfexzuMgc8pGlsfEftzFmFkD/EnAvnjjonTDnol2k/6OOQ0DMJ3brJO3fElcwlIfa4IBD2NqoiC92LUP/UdmOCIBbzUR+S3tWac+Tj3zEYx9bqgPeDwueEcQufSFP/Lp2+55oeE9d9y/4nsuknsL49lr6IlNfGlyZu0XHrGKScHhU6Va6WQUV2I8bagB4Jtb52dHe8avNfBxAwZueUj1v51lvtSwpj9rDu+KapB4q3ukWJm6a16gcnz2zWESPxiGmVzWZeIS7/0xVNlCAFSbjumvbIt19ZYr9pEY/CZcGylGuNE7Bm8t9VNf0S66g3xw48UPwILXAqTTDMNkPBdvI+GymNItSPEgxO+05cCwYoH7JPtS5Mky6sMmovvgn6iTv6NTi8E0yPRjgA018cFNdOIdn+GjqDrsT7w6gyBQ5yt2QdVG7npo0ji1rQDL6PPDEwDnSkYmDzh0Id96aqg5GllKr/Klz9mmiQZTt641c41BvRoH++PHYB7wQHlNR40c4LXxwL7+WwfmVc6orcXa4AdI2sitDWOxOes0EYKz+BHrGT9cb91wpoF949UoLCJ+5aDZ49A5kzPY0RhneLzMgdQmTixdO5KZx8HxF8EY2Ig9eFvks05iujFKSoHplM2RHrym2vjkWazhPYV8+hahcejLjoN8488Eb0u3NWieNV7ZrMeoagMGjjtycOqNr7kvCJbUyzZY1qWS2tJvTmsreg6vdXrm+8Qt1pfHxZq0dYYB7dQqQ/rEqar6M1cK0ZpYMEDjNOfIzSHjPaeDBR5p7dslzvg1ZrQNp3z51nY9mCv65XB4rxF4ASFWoRp11dVN3RW2ry1+8S8+EZA+bMXGKXKIztjMDBg2ihtz+a/+jIcjthBVLybYAtGx1WQ5zNm1ejNfDy5QrOcInr6F39oFOsEnfAbF3flaZGHWCPv8IrNNDE/Jx9xWSWKRNU0uxOKbizFsvChzY5OLM2T5ReYGnQsx4mDPecYnJIBpa888aBsZNWTjt59rlnbM+XZq76yLGbvYgMLWkBhueHLxiF83P/CejV8MXQ/4mA+CxuJO9O+5GP7z93CwknnH+J+52MwFKRvzP7Kp5CLTi1sukJMjF9PEoB6MaXv3krE5GJMXFxjnjF1ikwOb/d7F7mfQKQdjLmr3DDZ3sb/ibdrZkH+TO8Td0PYtovsCB7GpEZv273/+OZtTPjffmlAXLv69U5++jfzbsz5wMm/kXOhT+0edwNgN+Poj2zpyZlzZAiefxOVuORfsf3Dn3LfrZxw5VODLCw5gkxc4rV3z2Q26/Fg/btR5kWbiUfv0371Lbb798Oa//9//6+acO+fyZ30FKwfyw4/Gkfjg0vcOXz64yZ+lt0KJw030z5/51nla6wY3fnv3/LFBjvogFzg+cGRd7BmctnKjxrw4wbrqixvwoVmDdIn6F5u54Bib9QGHrEE5kFeMDIkf30uQ+cP2/dds+FMbcmRO4Tj41oJAac6Z7InW+I2McsdYpuEPjgPs0zzVt5Ic49cX1ehXqindOOuPKv/g9ygZZqcdTzoYEf6B19iVdSbrWtx5kaPPDiqwIfaz3j4mAQpu54tgBsqpZ9dhbLz2iiyMGyjH7S0tVpp1BpK+luDkJ+uVd2u4KffdMn23kB//yGOCxzshfV5Lh+cJPp7xNr+0d/lb5Mzlu9TXu9Pp89cYaMRk3t98asQzr8NDm9j3MdqzDEO8GZH/cBeR13nuRy14rvOuOc+D3a2ak39mkE35PJ/1nTL9ixPA+LENHrd8BChjeJIjzsTdNYkEMfVE1tr1jM7W1PTb2mqbuukcI/y3fxGRbzyRNGw8PeJC/q8eYluTmFsn9A9O5KJ7MSYxjPsLEX4YTtimcEcdL6fKke1ccKYdflMbAKnj0TOYKPnwVQajhPBLH7NJCgXAbemLseOVjvpapUc5YzemdeviERt52d2zIixpFC5GsdEeghVDzq4QlUYGt9jggi3msaslRtNTVbsvbXDRDfNprcPYRwuicdCDn198aPLJYaNaN8MWFVta7QdLSQ8rN7/JZXNobvEv1KAU79hEunzE2oNxM3B8+TVq8zkLEJvAmmcc6qKg5jnuokeAflyaP55DEz2Dg2IfUWt266RlDsdyQB9xqUfJaHznQLoL4JqJ12nrUuThNrU1x7/1683RuxDRy1c7pdaGqH1gNwJPuuRai81jz5PpwQj2xD1E7YA1tsFqe2BM3U7GhqxdPaHQenOGDP8/qxt5AmNkpbVJkPOKKzrGe8Z5W3yI9MJb4I2p0v/AqEV5SCGx9IwB5+HjeQAUbqwzU53uiO9mfet7YyK5ngEibyU4dgjn8yRM7lMDTOkv1+UHHXwbt5xjONicKtMv4jGf7EBJDLCPhs74pId8MVYjJ2wmzvISC5mGk/+DM6h12bwmvg7x4+dpP9x3Tm79ZKVXa3iAA9EaoRwmp7c4jYoFNrVqHWQY6fKLtKWwImtpDG3in3VXXo1rbTpZFM4YoqY/UDfHzTUKbbQm/MRnjI5x/oGwc7HjdTEN4lFg3OjTMjTHHQMYG/+/GkzNdCMYnRvvGQfEogMx+SKLcKIRuDow5FKvY3M4ko+hLqiC4q7OzU58ulHIJiUXR2wokbuJcNOQjRMbdzYWsaUvtBuWUIqP9SD2tF6Uzoabu4q5OGTzQjL+/7K+ccGrz025WJ2NHRxobsiz4WETxK/+YOR5pfkjatWoJT9gsEn/lLebclGMEDw2ttzFMkbG8PGt8FwQ0iwim1fwelkEOzZef/EZ0dDns6LmCodcTG/9cLcO1M+YGVOr5Ok5dXRzDrfZmO+FO9G6yaNXP7jxmesffv7RXClSN3W8lf4P45KvNY2St5BbI17QmHp4B1eeUyv7STPF3vXFmqeB5Rmb1NkcI+DML6uJi3W+OZ2a8WV3vEjQdwx0LXLxTn057/zsxwBC7qwnZPwJqb+4q87jmxisITakGfN585/+9d++tf2rbPppmzvzCFM3L8HZdWE8ssjcIXPeWXex/ZR3RvSFnc2rObnGg8fmaDfI4hLQNuuCGtFNvK2L6qkVtfTty5kzzaIkn2y7w0NLBEidt5G4JonnncrUoBxaC3KwETObKB575J1h/vRd4s0cka9B499Z5BwMR8tmHLVBnfrHYh83kYw9dvQHE4VRqVfkORDf+Ros0oqo/lF+jMDHT2KguOsKv4Ebe5yKNbrI25KzLHrGLs88YlHV5S2XOJy9QWpZfotz4LBqEAwccYZAfuym89Ii9CcHVffFB58HfVElzym8pT3PK2xoeXzsnXPmddcKc8Tj9NMnni8ImI+CsFEPFzfKCYHed8GwYNijR/buU1/o4jmZP7vmY2Tq7qY6fecqx4onh+U9+RDH36wZ4vmbePtc26Ll3TF5HLgh910yeeEtL8Dx+O68s+b6ohvPDz7HECe/NE6wsQ1HlKtH7gsmEYyVda2eLApkzQYTn+ISJz3zBWgURDxgtdn/dzESJn7+f4PT2D5cCDGx0edXQvWpy8WxDl84M7x0W4HDOTr1w2HJqh9HMUHg4Z74Yslh6eQO+sCU6HhrWPhhUAmD0kiE/LSwEy0xzoxMMXc6sMNvCXiR/CREcdKcIHsOCKGP2rU38OWDgXhGwDnW+VkLoOmfsf3wAW+KgRfc14ZiEXN501+Q9VMH+KjodbSxBl+byZ8AMTIOsTeO/cbDoDjXn7EPMtzzgO2CRZhf2gTWTmFsqqkqcZrLuMBpcn8u/q0/vkKms3luzM5jLUwttsYK3vGffESZONIBVC6OhlOEyAVBvmsFPMaTy2Baf2wGZ2PWs770aXDnR6D1b2bqOey6PDjGHN/oFxEYarB2jgsOTHGMMQDI4IiMZjJhlKFyZE+89OU7dpzqiv9i9nwwwYjh4o22fg4e8WWIQ9pwaPd4Zdh1Uq4OPWCxLLoOIvFn5ib/y+262Ho+89RfQYAGaxF3jryGSZB9kgVH2/VzuNLYtTied06Mc5nKSYzwk7+13cgbq+MJB7C5eYo9fiuju23lxnawGvBuPQRT1Xx6nJgNUm7HvVn4nzmyJ3ZUW+flV7eJCN/h/woaLy6mgrW8zxxHeNdP2U21dNjwp95e0RC1c7F6kTOgxPV/cI2k1ru+yprj1qo1bnzkO6f2402c5WmQ64nJ6O0+bOPFz9YN+MlXn6mVuF7sQn6SiMHWuvGKTR8uNP2w5zfPy5SmsXKON21tz+A8Vhaf87N1PhT2PzYxWr9ru9xOnVW6PGMAACAASURBVAw00eABgxf/yCJnfvZiD9/dnPTb03NhmYtELjD3Fx7bf55hjK0N0DQuHLnYfJfNKxdy9nNG7qYjBLrZHw5csEIK39hBjupyh7mbqm643ICJo2V0yW5+dcYfHH6ygfkmX6zGnfLWJpgJw8U0HPhM+R+/ccFNODa3/OZFCSInLptA7Hi8fGKu4sum49NHLpSHa2zkm7jUhHp6gT1kasWAIN2A863e3GXezdfy3zPW8GHM295/9Fvb++V15hGdF81s0GMLlzDKHTju3HZDAIczB8nBt1vP2819TJZO6wQ3+cVHrKACjDQcqIfPGRmz8fj1P7/6u18Kx110cgeXb1fnl4t+5tyNY/zMZ85szMWdHD9TWx4zCcLjhs06b4///scf3/yUz53zbe3yymaI+Lww4efds2nwTl7i0PjYgi+8kC+xXQcCyg0ZX77FHcO//Nvt5dV5zwaZte4LULHJP15UoYlDx5pQC7i2QOg2jrjxM4+okYPJF7vh7OMpmNJCRCc4YPl4ypn84KPMzR9meTxoCj8eQ/giz2MiuvesxdQMcTH3zBpQapyCaGTXXguu30w5lNp0ZUAHTsDwURXU5FPD1uLaoCUsr09tbVij9JlbKcWVPGnFXXxFOVy7aIqzqmrjh5wdTbE5l0sweSyynkoWuqjbIPAYywuNeMEYs6cNOogLl4PPlXlXzG7EXZfzQhUbdZ47WEs+JwTI0PH3eTCPQ14MQmezIKzfvAgVQ15OYsm4V8vZx3RqhS+4mwe8cbXGBUrfapnLyT06bfO44OxjJhv0fezs8y3AvKjYu+W8CJfv0pgX4nxBbHx9Dk6f5y98d24Pj6mV4ymmXCyCZGR7DpF3Oqj9qf5R0znSYNvPAXxHOc9/b3e+9a4XR0JPZdTEo74z8nQOzHN9EeFb6kNUu5WUz45ApYHflrH8ckaFGNFo9/mxCyuqzHPM9YEDOW5d3+u/xHjg/lMzABGg0EQumTo4nkJ2kmqPdoN6jtiiwYjg61OYSeJZyFHMCRcu4jnTenfLnr5HM/icMDYm7CeXw58xbQHp6Mu5cmw7eTzoItR2HDjFfieJYUXYjU1k21xgkW8OF7vhsDMGKI88kcvB8PBAwLF9a6v0NWYt6mvsktdyF8FGBNKmU+Ors2irMvLNETF5kpN1mzFZZLy8zrxEXbvyFI3/bGjgpB0/41Z2dFqQ8/iQv3GJsPJGw8L4oz957vhwxo8Wvj7qJ6ZSUcTRYn2pgH3cwiZYzTUxFQ2/yenYGgWk4cbZwR4a79aguWC1eVKLJ8PtgyDl0Wt/ZFRMZgTW9OWQsIjLGsvW5FrWf3NcPn1yuXXXavDptwVlODG+ud31genmt9mt94As+wNJ54UnYTJ/G3f9tWGO6qDPdDlNa747gu/6I6MOm9viP21OnRJnn3Bf8nCtLObU9zgVu3Gwye8Gj43d8V8bCMmnHQkeXpHducQjLSAbjrW68Koe2Ixb086N+libCzG9MAQJBEnkNJluAJyie85zTQcnWrgyotmTU1ldbo1xrTTWB9dnOPquH12KbR5jJKa68rJA0Sk3p+JRG5pyewNAH521wvZVbq5Kqa2BihH78xwExPjhvSyB/nLtj7P2oMkHLIynFbe8FTWsXZ/HzGVqHt/epQmDyN0c5GKRizAvLHORxkaGizXWr3d/ueCl74Uv5/zOZuZ5Ibx3a7mY9BuBPXeT7gUd7LcOqTV3pMmDI3huWsOJf6wvNyvop97UZi8QSc5xZFsjuxwq6IYxbw3/yIZsrmnMjc9R5grYu9yx90I7+XfTnItYN3OpyTs2JLNOYJU7vr2oYgOYcTDgTaM+OyeH1/j6lt9g8oIDNbIWietcH7aApA769IL95//z32++zlu7aVt/Ngf82TXmanGnrFjlt7jEcKPquS+OlJdhwgHU1o6KEZt/8EtXlTkxyC931rhb/p///JI/7fabb2nv5/ebv2/tDigX/r3474ZgoAkgDmsIbtS1YbJhyV1zv1zKTdW7N998yDfW//Rz/957bMmVnH/533/nN/F/40/L8UJJ4/FOCTbnbOa/4e59xn6pX2psnNhaa9cGuUU+a77rv+uPF2iIZYOuDGeY+cUdPHyec8dGUdvoeHcFOtYUMuxzMJ7hLbkVD3Ar4OMJzEjgsI8vJiGIlYfX56whpyxAzH1fKOJjIKzH1Fu8gYU28DnABxodZQwIAgiNfM/aZgDv5XN809l8XKegn3WPrjEKWn7gJaU8buDXpgzj/iis71pEhAB+tCwP10xH5aBqeU79o0cMjebM2iT/wi2BHce7Hpyi3JDNzSpVHn9xY8f66Mact4DzYlHeQZK1yQubfLmkm2+eG/EcJyuZtf0pAT7l7erU0DoSdkjBdz9yk/vb/eK4vLqzz69dExSS50VefCh+yjpZGLExDUzO5A555iLPyVknfZGAO+d9fKoPC2zJjd8//tjNeV98450aPO8xB3yxHb6sva/42+lg52xIrrkgFEbw8/nJFClEWil6btydAVauVWpS2CnJ8OG2I2LVc5QZ0eQw/RnkelxVhsOBIXWpmIE9jjvjCNqvdLltzD3XDuPOqePpE8/YibUoS43aQEAOMzCGHKMcfjy21i6f1mkglGfxCIIGRE73TM8konYh1GDIREewMdcPwkJscXLWZhOoz8Yu/sUxgWW7PIi5MahG8Na/0QxYE9UtmhFnDAQGZRGIsqx440RPkwOcRRwheeHf2Yiuiw37my+9G2PjVQrt9IJh7Drp3Zx19XDsJ8aTa6OBFajwFpOY9I99xobaOdB4nZymmGpPwPrmnH7ECGpLH4HYY5fA2HnQrjin1uiifOZ48fU8eHiaO+Fwy6GQjiqMrvMB7PVHKRP5eQBBKXa1bP7EVwf39NeaGmKIdtdoC6u5dvRWf3AKp9HqJuCezhPGxsO480gsXSd2wRDtXKLfWOKPb7Ma0spyOLnSz28O9Ynd5puzXluHk9la49f+ztvG37qImcNyd05wIoxxZy4lXyrEtOmXEWccZg5K9MmtuidvbQBR1XW1s2vsDZABNOAb0zZ5XZ//n64zYbMdt5Fsvn2pKtvtpXtm/v9Pm6972nbZrn1528Q5AVDKZzcz7xUJAoEASClFSfcmfScuNS5/9YOlRneA4xvh5qPORu04VLVdgZHPsClyudSqvdSv2uKVF8O1+a7ezN3Jn3nIucmls0RAvJebfLrqc+VwGOyYbT1/edPYbLd/2ztPIL/6O9fd3nMNQR1e+W87zurCvNYe5CHJ1mqU/F371YnniX8tTMY2SODkv9mYDuX0DB7Yw9fxrbKxE281ByHtjX0fyafneJr+nWf0Bf72TnT5uXFYa+M357gOYsPW2mbamgFIN23qFAlsg46R4YsTvZwEsMj05Iw7eAFy0cKCIP1CYJOyuUDO3UHs8QWmd015nDgnb/sFYd65PY9EolgeGyPx9qSQE86ABOzJ+HQhHPW921Sb9KOj0/KxLixySU7MPal/lQUuJ9DgmN+8czLNyaqLi/gzHuPtos//TR4o6LrYzElnFyIZ4ySWn08ZDxZTxIs9MrchwckrdwuNJzD47UWL+uREd2MgLtPL1np8JGdf5vHuN1/l0fbgIQebfLMo4HFo6aXPCxbx5798Y5H25P0sTsM9d6KXPzi94yitsQ+3GVs2nFBvuRYGvbP8a+6m/fjDjw/fZ5HsHWwXoNUmds7LuQDhRQjmwYy70eukcThEMXPumdcs2OOXeccFEHLz9osvH169fZ0xem7sxPvdN989fP3nvzz88MP3xs+C/FUW5ASw4+fC6d3Lh5eZzx9zYYYx3pg82Q1PBxX/BKzP5hUMLwjZQVcTwxarjgFjlH0iXeYrC2Zh8k4OtCEWFtnhgBYpFcPcooV0AMRl7nc/2oVhEtHxht/wYP6gx2Hgfd7IN3MPQOY2CyN0nA/Og3TkF3P9xxclonKQD43hREdKx702jslwWB6OG0GnkDO30dl5Ckx1k4907zznUYLW4294aTyMyIlMhhcuztilz2+Yjwbyg6lt/a1uWsKWm2zMwYYLN1hzIWpUywfcvJqr1OAI0safFvOwc6zf/9D9gMfa+4g7PjdPY8omJUgbV/C4y756+sPxlOcv8N0x8SMMjDvHaJ6O+fgsF8Z234ca82T0Y3OfV8BtnjzeMGeCtRftMlFaj7nzHu7sA15k4IJmx9Q5FWwX55ljHEO4gMlC3WPa7GMc8xgDQ8mW4lhFAk9jilgZXEdWPTPdvlSbEzAqJw5laRc5cNaIeOYN2nAOD7Z5A7r6VIdT5dHJz+kX7cKaKNTQTNX1E720/fsEgL6EKkraF9/IA9DzYKKpT7Qdm+GI/NjgcP1tLNH3GapNjDpjDBj6TUyTZnuBIIRSyuoV/5JDsk7BqbakxoeS0ZH4goEp/t3m8iOrRA+mwT/iUnk9NjWLVTScFJ/t8pKeAaA1GKluktGlqJJt77SM9S1Oleg/srXAdrmVl3zqTjM0aZ64bvXVhY84g1/MyNbNbI//BdUDbyIZR7EqWmnVaRVo8bHc8RwXilBzkqVyfFJPb/WuGiSRNWvNRfGjgxpFo8fjejh48hNVdCbg9akOOaHcXD6qp0v/OzbMm6njcU3ZurO30vgO98Brc9PX30ZVuabBVHdwIHa3XR1c1xrJlsEZXxfP9N9lqKt6Bb1MJtoq2N1xMXdgjKnZhsPGle3Gb16X32BoyNu4HKaKu69RHV+jdpQ1ohvkljLBIjazwlAmft70f9nA87EfFQdNdZTraebJ3ZeeFVS6cev/YJuVyQnsZWTql89irvDoDJPFreVqx0uqpFp53jbXcqZDVd7QyDY5WRsMr9hxtF6pRTcHd4txC2RztYx9fFZWP6eu/+RueIh5eJTa5r+WE0e8bBzrq0w6Dtt3cWvvYuGubsp59d2mz/7Z/5H1uBxP6VDnczIDZ/qaUOE3n/I4b0QJz4DgK3J9mIMdr2ZClTivO/yjfIt9+CyvkwsVBa7XtRNp5Nje2wIL3ziv3mLwLt/YmRC8DcLgYw1XSk/sWNh0gcxJJy8X6t7B64mmpmsEYvLNedUubAvYRzd71zTf7JtFFTF7MpgTOk7sSM7SwCf9bLHHJ180Rsm/knl4Oo96noVwZD5SGr1PL0oG+8U0vwFCRBL0ZD2t7APcVX3xKneEfvrpHFMCqV8eN/+FBW9OSuEA9/fvgzB8iwgxFkcs3gHOHd3k6NO7LLrxmBNW+jg5tzfxgkNhAUWuePwcW77p+ZzYpR87ktBtrPGRk18/e51vLWeBSaGfk2cXCPNIuSfd9iaWDAoL4lzdCB8+rRjcwHECjV/vXpIgxE0UXmnImbrjhC/Ghb7twXfwmR8/J4cs0vk3cbWsjzjQD4/pXnfpMu6WaIqhRzm5EI1vF3vhSHxPE19Acic8/zTti7d+PhcKH7Mg+TmP1f/9668f/pbXu3wh1+vcYYevedFH888YcMGHixjkOeYhCA/2hkaEb9vqdlHOXGQengUWKlPKmrx0n9hxJneOW/Ccg8LmLe3isAyMNZsQgcveXZRX3twHhhn4YJY0zrHFJwDRtZ0781Hh6YAP7/MvAp/y7/R68WdzDBfmkP/CK2DNQmMWSIt9q8Q/teFtPg0BffxPLKjZP/qTi5JFN93wT3H6xFZ7u8IgnKmeRTQCmCEPbksaiNO0m+r0EYN1+imo8rcwP87nOzfzBSY2ffoA/dpjmPyk99ECcXxqlX62UeDdgq2Prmcu8tTIL/nvEH7MJB+zYJ/04t/hGtM1PFsIXHLy+oFvL0xZN29DMlrG44UXWuGy+yvxUHjvhZPqwg3Z+qR1z99+3hxMjwPZb6j3WEb+IgfYAkqPBcyx6rTHO/Cx6/7N4rwvfPWYVizsHS/Mws0/1R4jM4OHmGOR7ssvym0xplZpGlQqG5wdamwnhunGZ8y0gQeVKZtgMWrLCJcjvoqvmtX2gXpDSYtS2foZD27wuWMxylc3QMNDTNt010PxoNI2PfjjTzk8+e0j7qtQNjWYOkYUDbHAIfqnX6g0N0C6Wpe4utGP7HO7AzLdm3CZaVEn0w2NKeM8HQRDixd6Fg0iie99ZBF5+VBRq29rNCPVoUzXYrQSk8Zkqj7T1Ye+8HGzVTlAEV4TozqPBhYf0B1fj/NEGO1XaeAlH7HnZTfZ5hAe4kWHGrbFWYLIqU+Jj040pnH5aoNtfrfPZswulGinsZNs/dc7rVvsx1cq/eugRB336MuqjNfg5k/HEKIvljno+UdZPEW+YU+BN8V8o2suBRFixw4+q6t+ApXX6NcuPeItOpopkTUHk4fhtjlRZ8bw5FHvww2I/KDf+UyruWhl/VW/GKLqu/MGA/KCTvVAENcBHH10KKtCff3GFizxxarieG0fopTj0zpvxb3vb+i1pM/uO/YdoR6KsLETyl0++BAfOb2ipGtE5nAb9htH4zJoYo3d8YKh0JG3o02xUTyaK9G6OUvfOlYKt+GEh+kTvkzHb5Tx0o5HPZ4oHzkRTEG2OVa0fHE4eQVQn8Q4IBCaOpGsvL332KR+jqf0V19n521Rz/6wPekAm5iL2jbdZZC+/Jx9IkJ0D44O17KMsRvqgtgb4cZgH0rIdvCwOWV8HhBU8RmF+/FHHsIcSPDkF1WxiQ9f48dYcYzvOz5YwM9xKdU0NDx4tiKrtH6Lq/ZwABiklpMZsJDnF/vtZdv8TD+dmqOYBv6y2cWMd4SyqPFEMyfZLHB2PDDFeOMXKD7Jg3djA8ldHj7/y11zF+ecAM6LE0LvqnCCBsvkgjVuNvJgYelrTvixY6HMyd8nMVh08rnvfq7TXJeUHEoPqQHOiaJSkmDhhPJt/n84Cz2+bXlj8UKB/HoHnDxQXNCeGJ/MF6DxDdovMpaJl2cNwc4kYFHC3dIt5JTCAunFYDzkm46Ji7tsyW5VY9+FYir+MiZ99PvNF188/PYPebR9v7U9yYIzfPl8KOOkj+DvuJJj7Fm0lAFpY6G2F0dSD4f6MqUnZ2CZP8JifKLno//wmvnCEwcsTH7KAv3nLE5cpIIfXfzwqKt307wgMHdxp+8sPIP1NByBdIEUu/qun4jNG4+389l7cggv4v32H/94+CYv5iZzbO/qAQGKHxtIrNTh5oJp5pTHUQesOcQnpYscg9SG/BFv9auTlhw8RAS8uMFBzsKGnG7BeUoxMgq0CSpbHxE2Xvwhaye5M8cIU/dvJgkSP5ts6Uebi0jcuWRf4LPB7QsT4s0c92kDcp6XHPL5iz7B0jGq45jhWx/lAEFibvzpIm+gkwv08ss+qjByxx5G4qAHZl4p1me76LFQTqzOeeKMDq+4FXcvWpFv/aQTrZ1n0Yq78NzOdURHymUHqoJ5A2gwVz4qyx8xZHqxRLYSM35t+sQNeWEf4Gkc7px3Yd78EwYFjuA65ytCemoNjvfmgPmUr7Q45e3DF9o//5RjaY6pG2Zxa91xwQRDXuAzVpgGl+PS1nd+Qiv1XqxDpzzZetzgYlaGmGOzHw156HdkcGy7c+gdc75grhdiXazPQt7ji1QYJyhJQopeNMZnRIxVL9Tgu/Q1qxWWFudea1fP4ONBH+lHdHJgPa0AF7q96kZm2JMvmNibTrSdg1UcuHoBi9H63GNh6kWEVOsNEoM9MW+H/SsbrsQJ/mKM+NqkC51e8r3EHcSaXQBxbNGoiYCWAa5uCFxO0R6ycWIIErwCUHdkF9ZiVm/TQIa7v5XHsCGCmE6Y4weE+W2/3kOcXKRgS5XXI5y0ETooYOVV3byPD1TgTcHPhZHa+ococVHAsNm4KsO2fUtm8zg9x4f6KOEymGLdvF5cqoL+eL5tI0EITAC6c844qD+d1OEN3/w0+gg1RCdFVcmkgSL6xbSfenvcLhKNvTN6cFFMB+lqSWVOmmdEt0NXYDRPVi5+4JAYChCtnTin6abh3flOb+yxk5LvixKh2Pi866R/Yq8VbQAYo8v2OmDgR6JUDnfy7R/n7cPHQKuo2/AVEvuW1q72Iq6eeYJfinlP1bGPn93aNzp3zitfGSgiEVv+svaAhoeQ2lDhrCHKOqNlt/JbwzlmX+eK+lhPflHtPOw4wQM34Jy49Ff5enHOjDPq6mIT+8NhuW3c0cLXxnViHr31u/NRjwhTztiqiyAvBm+Ysi2LiI6stcZc3eVnCy5wQj+/V9/EcPDBjEX2F0Qb38a8tutZBfSG64lzO8DaOIatIgCic3BXL9I7hv3QUZs3eIGJXtop6qz/tODifI3CzXWVb+9XFicHix2d07cJOEDoIqzzwx+fyCVFf2NTlRb2SlEpBrbgwBWznJ93u3oYjB+x1+0xwEfssB1/zjnx6Sifu6z0REOh+IKMfjYWCRV/RfftxgABTkS9W5g7hixKWTjuIv2ckG2AAfGi5yYGgPS5uCWHeXEXmkUTLxZVu2jjhJB+T9zAyQ+n/p/mAgCQ8OIk1YsCOQEGm4UGJ5L1EVke4eTfbrk4jS4nheQKbAqbTQmVkz86/M1d9DwO/frtm4fvv83/HteG9yycwtfPyocri3dKcbvgJC8uBuXD3bj85KQ19468A0aMu2jciwj9XGY+QyrHLjrpg/8ubjqXGr8pzRt+3+TR7n/79z89vMqX21HIT3PURef7X/torBc9OJuGTzbMUD5bT2EMushirMZHKuA4FtmuHVu4gEHhi/WwMYdUUuQwixO+EM7H/8HiIsrwQ28v0CBvzjL+2KPnSgzc3i3Hzr44tg5O6swlxul5xgsFcsvdyu+//dbtPlZL/Cx6XcQnD/gEr3OOEGaOh7fjiZ9ZDeKPstzZMi77JYl8dAMExxo7dlhs4egmb3FWOz4GkjmfDvzoK7bMX/rdd5R3caTjfQsMfgrGO7iNi/FzMevCOHzij/i6YM02eXmXpxiwR/fZh+wz2Y/Zd9gPzXme2vARD/nwGfWoUwgiDeeIHFhA32JLvb5VVh1q6Jwy8Z92Ktu9eowBvxb8qUBWWzgWdGyKDT/CPblbwrE7MFqXK9VemOpYHeDA19dYsZGvHXKyB1yxi2fdsYcHOWAekCr2rWtxzjGBceDV/owtDDNPwNhjYzmo4hvthgQZRPX7If/2LzU5dv6MjfFx8bC4jFccyKvYkUfEnMeYhTklKs0r0tlHekyOHgTywk+5lNNy49halR7/iNv9Qe6V7RzjX/6xPzIGe8w3jM01PuDjG8xSUmdPLdO2q0Vnx9HY1obtZ4VcISaG5gEFMxg52EW/cFOLwcqptUQI0DZ3W2U7HI/Ezo946NNDkvPb5oVsnxoDTd5GCLwY2D7ycVkdH/jEBWOKYUoX6DbqcMa7vfEiblqjYoJOQ60JIvUlfoy1S7841TPogKHbCdKES3JZFUBf6tCOwQZaPx2UXeDswNknePUbVRyOT6FDqLhFQkZ8xn6JJp7RbRCHk/oywkMHxO1iswVz8OAul+FmH39sU6lKceBy5WKU13c7HRPediLVAiDwRI4mW15sLkTtkMFPjJrcY5cnKpi6XZz2lO90ZmM5ftOifgCP9ihO/0RdJ4NPV15aTCy2qSNMAwbEvQvPxnvZGenN5c4L9A72jSsyysCnVokuWQDZHtnRjFYOoOhUBJ9o5rU4zfjEMpgYPNq/PnNOs5hFeYx3xbioCwuH9Wd+EEy89jn+Gws443g2hoFjCWDR4vyiinz7zN2tHz+aRoE/HMFBlQKnzrHBHk7Id1zIh5zNTS0bNzZtp6aOoAfD1ohGrxtlch97k4rd9lOhDjAvStrNYfvopnS7rcrK5xYfekeFOXAx3jixrNzKAo9m+sx/5zZOd34Bax8AxJCfC3/06Us5vqLXsIbHxosOigH1QgttBo+iTfVPviKeXlUqx/wEa/2RjlBXHCdmEIhrbM+8KPLhdTTOfGgs5gGtExvVjXOsLlobwvCfuKIvzuT6YMohffccIIuZ/NfOxdHI0n25i5YuIumvfmOW7fIfrvbnbe1RalMbO9bvdMAhp2jpSge6+somTjGnEBl6yhAMBjHx6oI4i3PvxrI4n89QcreEhUiwfFwaU+4SApDiSSknbHm5UIjsWe7ysEjqZ86pRz/2vFwMTv1wwYdo5YI/8FjAIudk8FVs3muPhMUOdwfxj2458m+CxSSmaF3xpkW8sR9HeuNElUWv/7s7Cz4LqtFj8f7mzZuHv+bxaRcm6YQ7unyeeoHwwcKTk1b3SU9+c0Eh573w8rH3nDGzCOUz5OBSPiS/fJM8OiVbzgxYF0IZr2CxOP/9//r3h9dfvoWYthsD47YXKOjowo8T7qrxN0duu3AIXkg63iilW9/Oa64spZgic0C9QOgxv2jzcs4k74w3rL0wEFVP2jMNnz0vFnew8b8XaDxhhwMB8DeHfw/FT7AW1/jlUT/E8DLfF8C/nmKRRiHXv+QL6b777jsJLz6+AtRFenzDc4tz1njiL3LnqrFsPkIp8TCecGDcjI967tbL07yEa7g3Z6iSl8yNLGKe5UJCbdgXsM+dfec+LILMpLDWubT5VIgH0pK3PVfgRJwxZd9k0TVviQ+WM36xS03ufNkYhXx6FzPxkBNiYV/iaY/8Fz99PGOhnv3H/VGr5rXV5UJuRsJ4G2tj3zGj15xVzXfHMpwo1K+CLG1TPMBX51iMAMdj67hjFhH5rhwe8MsxhXGMGbGcsY0988KO1JFT4Mq4kA/yufzoXx30rgsVm4vaixF/fMGkFzH9nDl4cwySc8Y5cxv8cbuhYB55MFs7/jFDV3kq8OLpnnefcsFllWMTtVxomYttGRMKxwvGo/kYHeZyMLrPaJV2jsPJEfJuaVPPCxUKJGhkG3HmbHI4BF7GluMV+x8fO9pC3p1v0WW+Leb2Yw9Vc52tpxSYj082x63idjAepYJx0ZYn5hTF6OWHrLLvUMdnXbSu8pGuXTXtC3DHH4xIdEwPvsf5vR7ZOTfV32AOjjkOF6B4bTn11Rtb5dG/u1gbt+0ytmc+iAAAIABJREFUtwUstl8SZ+DROglGw99NxsSAjAQRUOpsT9AhEpFyOU3eDB1ilm7X303UbnCZiGlRpegrW/1WwHv94wg9A9/BiGDcFanNchZZ/Y3hOhDRF4tsdgIUfF00Fyf+4QBRJk23QE/OgEthYyzoUNxKWt0K+45fOPODxpbm+OKx8qjdSuPWH9JN4LodzTVh8umDbXT1MbKyE2R4zJgDO3F8zs923sTZBlsc5mVMcKJt2YrK8m3u6NRArfv4I1B7cwjEYM7sU0GcyB3HdaNlGhMr+vbLUaCAVbmiawxs47zeo3Xlo2MVDfwNL/Trjt4WZY/diKNq7A6X0QegNuMrtrZ5z695Xl362pntVMCcWC8WRT384Yt+Ns19suKRtnoRxgOZGn6STXuw6UdDMXqZVJcu2PlF4Shtjm6y6dx4iJoIigMyBdn4ki+A1avy8qsj3+8cjUMg1ZcYehvLxl+tzXk0bv6GgYzN8sYnm1qCfc/BPa6NCTrDXiwsV4+cMm7ii9t8iw5hO5YJ0grNELYqtL8cL4lzQ3zRHsWOBOb3UvvIFae1/rOl77F2LZVtByZyou+yoGZJX70ub5oatX9jiRonBRRMNqLdihK7HUOi3zos+bnvF4CsjZW2QPd19aUGH8YDm7yKgwbi5RQ5ZyWHQ5Gkj4x9SgOMWn30rmw4qcJIjM1uxxcbeqZ5YOACDPlpgS9tFiB9VJwtd4JYhPLYpidjOdFzYYV19Dmx86Q+9Zx+as8JYhcmnCSzYGVhNidtc2fbxVMce2K420BysucJHd+ELsduOdnkRJqEsMD3zlW4ffRkki/6Kh+550SWfngwDsY+WOSpkTdqkzBVNixa3uSzzfxfdB4Xdh5lrFiEf/nlVw9/+uOfHr799hv73r0rEndpuQ2ZB637cDrxT1682cyJef73OM9sk19eLR+D+9LPqf78488+Elv5jEUaLgzCmRy/ymPd//anP3r32JzTP1jkx8+75rFa6u1PTvhN7OidLTnzrBhvUUhZXsyk++KV5CGTfN7JpTnk5D6YLmwjdzzSZhHOmPJ/kJk7oDuO8Ihf8rtPUTjOcBvcXrnNgot0Tor0jM9UwCEuMHoXrx87eJdvyP7um298rB6/LNAYry46YNDiI+4zLkjMx/Sx2RzgrIubkvDuJOeZmfvsA+gR99oQB31wep3/y/7y1euHL3/7myx+X2XR9mvu7H+Xz8f/YBDeSWQfGB9kl33jEVeCTekmvrjYww/HhQj9lu/0G0/y/TEHXGciB94dV6r5YX9wAZr/q/0s+wUcySF3OF3IRYfxqL8uYsnLOD9ydNsAN2XacKNoY61+3W9GTr7wybY5L98r37EvyMIevPH6OD/g8kreev5RvmIzTsyp+HJuEssU8tHrlu2X6eh1Qc0X1DU+Z336liPjS2mbbdswwS/z4kO+O4ILiRTi5575zhNwP+ab2SUeGhm29GV7/GGFP7apMdanE74Rohsj5hRdCPC9F1muMSrIxbXjWnwMGYe8jzMwLOG8xfmkXuamW3xBCVvuoEcaLo7r/NtGCQaAPi/CkoOMETr1CQBV0CdQtlYv39BaSvBx3JDB7/RNriIjV9UHlblVKzfy3P7B2m6NdK4qhpt/MJqD9V9ctD2/qRNz2GjWbxRmsEROXZxs19OY2rZPv2tfrerkPc70CezhtLLEK/70JZ7syaXDdjtjZ3HQJDdBROrgD7kltoTdOnZxfVigtWS3fiX+hHmB6VtzYZqQDVzcvtXFHsBiD9UDw2AtTwY19eWuA1mtwfLb+NBYjmxbxNhJrzDsL4jolavBx2f/aKLzue8iynV4MiPvetVYvWhOYG5wioCGKnlbe6iO/PBBNSpjdbNFsWWhhFuhEQFXbiuuVfODzLGhQpwK8o6/z+M+4LXd+XW2+MnPfZzAuBda5Vr5mRfYojsc1o7+8q0dvC5/AcNEzBk7qI9P5I9LNZE1t40dfbwsjnZ5q29bhQHbg88VZ31NO3P5PmbEwrhe2/brKIjNE5VyvvKGnmK6Vj01SsdoY/SiQnx0gVEbbA+P1O/50m5DGm74oBxfVsJh8lj55jdy/1ihn57+EsAg1HcB4VU2tvMGJngtYZnuE/eNj2YT+fZLe/MZgJXXN4hEPQU/6iKF5t0vgsbX2NKGB39c6jjN2pcv1pd9bWKATU1PTPhCDv7yQse2XXbKpzp0lrd82xy8yAWsH7oWV163GMbsnzhtPABBSc53u1sd/8XFD/Tr/P5uLLA/xIag0PExx/PtR79+G2OaKdiUzLGW36ArTF0VZlkE+qNeu8I8xqw1ZhvHSGJ7/Gg4GGBKDiE+bgipnhgUj000H3GYnB188E5DZ30bGS4Wie1p4P6mThX/3J3jpJuXnynO4vy9i/PcveZYBEAMOeliUbF30YmYk1Ff2KfOSeyTp3xOkbuJPJIefe6ohLMvMCYfPYkLvZwPPGF/J4fmK0vf2OzdUpzLM/g8ar1/M/HH8p0TQhaq3JnGjs+ou/gJbzjqj8Dzuu9/xE9Bh0enuZP+U77ozBJOWdI8vI7sj3/8owsaF+lZ8LzPt6GDw+dBuZPFQhUMvvANnvoMB+rEDjdyzF1PYuLiR/9neH0dG/iKJamHt7/56uGP/+d/P7zJ5+SJAb3NHXW/ITpYnjRPTpurxDn5Ri+NiGMbTq4QEply3ES+ryT24GOzc4jUOY9KK+/kccYxHeTCiy/rMxlgbOCAnIUzn5sldi4EAMZSpvgOCq618U7ocEKV+cc84nP3LDTJLdjk75t/fBMMMMkruN2CoROJ8tY4XUDYp+BwDGTzcQKlgqfKyQ8+vSBhXMyN55kvbx6++u3vcnHnCy+gvMxcgQvj8Tqyf/zlr/nivO+g5R39wBk3OSFnvSgC7fJ1ARin+OL7CeI29cy3XDgyn4dVeCUv8NI2od8LchalHz7FLvPufb40jtw9J4a84PfxxceHl1HjkXf2e3DECpWIzxtQDhSi1GEaRbfN0PLPNjFh3HhQnIKRoGCkkhcXQADx+EL86FgyhnKhMZyo2U879RwD5JX+5gCcLpJZsHqciiJ9xiav2uo3+5jHu2y5mCEY+otxOxaZr+DYFx3zxFwLfbHCzTkrx8hz15zh0HfwuKDAse3jU/LOPoifxmMuDHySMzkwpish0uMiwJPMgydPfnn4NftDL1jlgksw+ay6uY89tvviI0AdV56iYJ9n/yCBvCCcFxvaKR67rXds2Clhpmp2RsNO/9PE+DHfY1CeKMQPP8Guv+Ixv0HYv9cgbY5DE4/FUL22OANry+e50ArjqLhZ1XA4uunYmPCxZWWYIC2F6KowgCNfWLt4uwnEkUJ85mdxVfPvu50a9dx0Aaq7c15IeDMvsv0fS7qaLzjL+qgSc74kbgDwu0AkwYk/MhGGcPQW5gyikvZvp1BjRwb0k3eoLhFwOmCAbmtwDs3qazeTX7zDcdkgvelGTHsnBLHtIMtl+rWeuOmHB3a1XrzhVAeHP5jV1QDlMatUf0xs5IuLr7QLFV/aIEt9OILmWNBnSaW/tk7ORBlucP+sHLx04Y/X8aystnKwj95qtUkuRmdyBE/J3PQ6tuNhzFe2OS9KY2wuIlnOxD54miuPhAb1yZkqacOg+Ukd28nbuFa/O08kYowvm7HOjrb+2k+0Y427/NQL8pTgN0d4Xq7Dg7ZE7ZIbJlvkmobaYOsGDISzhdeleHRROXHQfyvYN7epwK+INLTf/pvJ0YHLcj4YR1HLaR3C6u94me9g8Nty2cjDrvrAppmKpvrr+xgLQeuedfnFlmKfMTZmNG/OEVZnIdFFJcX8RS4GAjDTaSypf+4HFUrjGNy0j72dAUfAy/0bzGlnU9foBH86uk2nRmzHR9TkCGFhJl/UlVkRK7VBAzeFuKebJvZYr09EYtCFIq+RNS9t9x0l9NFYCUgrXFmxUFMymFipqkU4aNY8w6H+oyN+NskbsjbxUnz1Ijz4wNK1dnVz7OycvnTdMCc30ax5Ea2HD/z0ecO+9HC3/GKnfhnKDzpNFC5vBQTK5bv8ijVEyjGwapuDxn/5HP9o5FdXeduTfO4oNRpdoRw90BaHJifKPIabE9V55NPHpXMiyOOb14kDCy0WWH1UOSBj2xN+78qJVSIsSlmE+JpFOgQ98XYhxS6R01g45Y0T2g/5V0vmEN7o5oSSf5XFl4/5ee/oo+7iKwPjQpa768Hj5BUdFjJdCAYx9pQzBvqaFNizb/gD5qnfEE5O+P/FxA6xLGuySH/z8Pv008e3leOLE3sg0WMB6gl/eLAQ4rlhcsrrSfT439yM0YuX+RKlnNi++47/Gf6j/XQE1uICEMWU3//Hf+TOeT5zns9du+CIjJ6dWyy83vGlbNmSq5bGol58W4y7OZVv4uhCc0zuG4hM/lesOQ2SNERdZOfSSFDNL/wc62wZH+/yhtOZB5kDXZinLzqMSWOtF3DYc+gzSmjk76+y4PC/y1mkl0P+lVguHv34/ffODe5ieuc8mH72nGNtXl4MmONHvcR8fuqHdhfDeCK2ze3qk1vHkS0XTjLfuFvPF9XxsYOvfvfbfMngl/Lm8/DMDQoLdy4WffW73zmXOI7Ajcf+4bB3tFUmr/cSHs4l9sfMp09ZffWOeC+edZ6xr5COsQ0+hXxRkBPL5rXf7cCiNPzzYpFEP/sQn+1nnFy4YZGcAQ4W9pSotmaTNwT09qf1iLRFNzr+dov6cts6T3+TW/TES2V14L+x7VY+ke/YiWMMXSinC5Fv4lJHXx/MuV1QJ5+R9e53c/wx+yg25oQtMMEm1z3ORBL7c9HRRViPGfBiwU0xfurkAZPR82MKBYCEWOT0XjpmlcR6yozhKHPc4UkNLo4hYst+8cSLdAVEzjFJ/uyjOW6yb3osZ38I8uZqc7verm38cryFSGHljL6yHBg/Pzdo34xb7BoD/Mllc0s+KXDrdvTQB3jwd4x3u/qCoZafnQ91IKjVEt75O7gGXb/woewWn8Uv1/YuSnGQoYNfLK03EZ4jbD9binoTo/omsTGLwDjw9yUNeRQWJ1qLAb4qHcu7DKPLPheKTcgSrB/0h/Tgpn38BLnBqIbm9Eau47ZPoENMP9hGxwkwlgLHZKzEuuOLiS4c3TnQzItAljfkpqzt5PjorO4OfttjpP9bXOCJrScajXn87M6JDkQWc7mufPlWaybE4I7nWxy6UXzyOAM5QlMFtv7wO1hDt/knN3XY/isR45LOuI187Ue9Ma5xQA0v7fLBSEPMtbVye4MXvzsGmxf8UEyfVRkfGSL79D30LxWJVAfhoms+mMU/KOZlxkUNYqi+lajfczg92RjBcFlPkYF3xqLE1qO2NipRD6TYFK3odb+cKjsYk59JuJ31kur6HUGj/2dkJJuZM7baxku2joEY6IXfHER0dvyTAdTRSEnjjF1kzQEavJqfOxOF6VuMY9uOvNdOrnKrqNxR2gjqd2N1C0c45OfSvziUcfHrZuq6mJgLYUzmAJfGXlTQLHZir2eURj79hwtdEy8a6eaEbfNd6+0vRlFRpqQ1+m3zrvNlopg8jueqqxZJbJvGGfvxr0f6+GNhfKDeEMZncSs3pzd9Hc+bejiiDJ4QlchJ3o9cRAMlSrZmmMVXmqoNzrRUO/MuCmd+6rdAm8+jB0Z0wVPjETc9Rp7cBOPKQ3Sjh414rhvKSxJatHbe6/40rSz/YIsjiZsiVWR5W99tV95uFVCyyHUb2da88z0JiWD0Y6wnmx37XbRz8RF/Pdm/Tla5s7uLAYzlnPddbHsHdnyvLXdw/NbinHh6V1VOsczJIy9OsqyTg9sLnl0U5Jw1fPABDgU9FnosZF7lzqmLrbRf5C7stdBjIcxnSfvIJXx+yee5sQGL/5mub6KI7Q4FWbmPNf4299jyb7xo83g/WfXqQXL46snrhz/kTvqPP/zw8EMWh7/++ksW6lnw5E5n4KOZBSaV/erlPAofAH69Y86FjxdZoLFQgyeP0m/BFp/km3/99rs//PHhd3/6Q0/GBU//bHHGgut9/BMUYgoxmY/MAXD4dfx584BTjviy/6yF61v/wRCOZFEHQxDhioe1fdnmWLALAB6ZfpXFA//qzLznBJ+FH08msFjlIgLjImhwWcRvzFIkB/zges7hMgvE6n8CyJjmhwtHPJHwj7//3QU6i/Plvtsdb2OZ3BBLMwCFNPLCn/L47CIiuRsj5tW+6HuSF4vZl3mc/bf/9m8PX+TpBhZHPHHhfwDIfvAuY8I8ZB/64iv6E3/4vfv1Z33ClZzoIm+TZmgZM/zZhWWaOvsDX/jG1rvoXCjgotQWgJq8SsAhrtjuFmfkDZmL0HDTTyxocxGAsXOfYV/NxzKanyhgOwmaWYNAPMTtYw7wYkwVyqWytMnyxAdXfCtLnF5YSls+0+fY6yH4zi8wWjgOaJ5mj/3pA5s2HdbrrxeueLoF5vGF7ejpL+NFH4t1n0TZRTrjHvlexDBnaZMfvu/C8UucvSiWuNHN1QYwYxoyvLFzzXEJYea65HisITk2iOizJQ7Sdi/kLj0RXfGyv3BsYIH+4iWvV91PWJ1N3oGhysch4AOVJ3kj9rznYqMJEtmP6OgXT80RxhWVG/7Bo8gmdTWBQXfGI5sU3tDqxmsT4cDfB3OTuUshn6ipmX6K/LMlp9YRD2bnQPQjg51jBwu5RFgIYE65x4M+hUOg9toWRzl9+eFXJ23ZPrZ0rTL6NMTt+EgVeUnVNmFSEInf5vU+RuujHZLQ6C5ffsg0IxaAJ3g/rNImCqn5mzdZj5EeFIwxMZBILFf3tk1VLEzUqX5hSPGtPGpU7iBgR6IWw+02mxY4qDs6VeE9hVk0PBp8GtHGknaLrZHTu7blL7a9aKdvuuu9TVBFJh+ozfvqrye7zttyOYJTEWP4nRwTi7Jwj+b618g8RdaZZS8UNsYr9vJdR/jhVTwatFJuhBnfxaEDCuv7ka1mjX9oOjew1f9wrMPxGJkXatwGQEDi6xjVWYQ9Guj3YA1PkcQuaWz/qZy8Lb9s9TkRxOS+Q9R+ohyV9rdHfuOTbonf9Dwo56g2Inmj1bioNcVoFKa82rPvj/NgnHlzq0rR+x77jWFjzZa+psOaPMzf2ONbpbFZdDGxVwGV2herGZa7Ed25R09jNtETt/b3nJ0Y6DcBEhK+Ubd9f6/Xwk9QdoN1tSdnwWycwyca5OdwuNk0NlB4Xd6rj2LzYCg6yxv4aq8Verf6xET+dr76hz46pAefG8/B4Q85fxDxpxaI0Y6COmBSGJf8aG8d4fTNBgllx8963tZn1dIC2FIW6h/Z3T4WKGuA7+k77eaoUBfWxl4DzO+xlc3hAmZeq8N2wxLXfjVsrt5YXZwGY22GotzrK+/8no7xmfx6+MRQN8SbqkaNiXeKoirZLpf2rM4NPjCVCqt9EXDAzyUX7nrbDiTmI4JAyanVyoOgvxsaJ0p78skCgEWFd5Vywu5JVCBZfLHY2rvne0J27Fgo5kV8fjlYbDiRZUG1J/3Yd4HNQj053HlKPqfOiRmYtFeWSha0+ebuPDbMogScsxjjJJdY4pe4sKWfRfOzn+M/Cw5OpE0ceWjwsWlZu7qfEZkNiyoeKX/IQpx/mwQId87IxWs4JTa+OO67fHs4/1aMBRR3tig8Ws/JPdyzWgmvLNrSv3diWVj+mn5yvYXx9TPUycFvf5+F+R//4EWCXcySD6ltDNnyedRPflYeNzvQZiSn4WmnYOMxauI/eaUTlSg4tzxvQJj2+oiCftMuWjrxwyZW9PlKvIjJPXeV/aw5C2Z0XNDk0fR8WNY54Ml354BAYCen6uZdIEjva/zxxWuMJxd5uItNLn/8/od8JwCPjofHbU7hx4UbH4NIH1DP8HHi0nPbI/NOfuoswlm0sN2Crx0rvqDuzdsv8zlz7pp/4QWcv3/9N/0xv/fJDeYi84E76mYr2FycAQtO6CKn7Ldrt8k+mrkx+xML/dpVtvtcsp2Yw3f2lyyBmjMRO4agg5Us6NOuJIO5mSz2OxMyF4kVf2C7z/iETC+sYLsF3jTN99kWe2MKdH2l3zmpAUTQs9Oxpo9HrZ/kwhag2J3xKYhuj8/o6B47LPLGmDHuCiLbqgtrdCJgHhAXJZopOWZgEh/6hI316GXLcYz9k5x0cX4tJpl7XIzxmHaeOOAYlBJb51BcMf/0qN/0Z5z0DV94850U1VCu7nAi3s0DcQ7ZxMI+1gt3b/PUBh+n4AmN/ssz9PLUULi9f5aPJXlYqTVY+MaW4xCPpYN1L1FBYfxKxGRik1/Hq+MXPWEjByDBlG+qQIrDtnaogO1cjm/Gwi9czJw2X8h0jmY5uh8nPx4rwpVH8rO3xxX7TJwMH/1eDiNmXvBTnAt348IU1tWSv7HgOeXwAEcBqv+6NGGrZY4W2y39TZx89QXY5FgWg71262p5V2fmDZ7EQ6sWbImk7yjwb9ZideJQ1oRQlQQgKU6KQwbAW5KOowurVtVpHT6pjbPW6+TuX4I3P5IwOZBoKCfgxWM7ZcMVJxMAe3YgjNtno7CRGIc95bfYOtOqPi8EapTi6CetC6dyVZBPLBuX8lFpWN0hyEuxZpA2NpOz8V26iw+N5QAsmo/GanGOQSsb5yIrlQO15gVOxNWS2lb1OWI3jX6q7cB2DOSDdOwWRsVDunFUDWFicdO6At7MB53xeesS01gX58rV5meyY34W73AUOxrzB0DqwcfF8l13jQfpSJYT24iv3Fbnwph8junJS4wOx4mhGW0Mu6CQ0xD3KY7gtK8+j81hPEHZxvcaRz8H0sa+vodUVNRLLBsvuBVuzolz6zcf5qFelgs52n0AzcUy9snb5RnYtMzjHDu2rZvNZLmtnZhgj27lxDtY+p23YNMPE7gVMfU27SE2OCzvcl5dVMsN5WUkwMQjiH/QrhiANy7yQR0fU6yaUvzSdbdDprB2aw8HlLc9OkhOuWOtcGMbtIqjOIabS9rgH5baRVu9UW4j9K6YnPvpxm7l97ToL1g7pwGsz2yHGzqbg2I01vYXW5zhV/xmQ9t2dl9e52BTbKeeX7kqqm99ERr86Uc/RdORa7d+6UNwNNEefeXTnjpRbLlqxdA3UFOWG9i72KFOtoBpLd5pAjbxcfLPSSgnsCzO2fJif0fPu5ux2QU6C9SCBIeTLRb0c2LvSfAQ9S5TFmacUHEyeG27WAaP4hiJ7xtn3NUdfsSlbbrfvs03lxsRd61YKOeEM/z3goCcc0IHH47L/B9i77hmYQfc0/lyI/wSW12QE2Kd+URndGnrOyeHfGkcfPkyMowSkXd4nuVfZ3GyzoKNR+G/z930n3/KZ8mDbV7Dg7xz0u63POesmUXei9jwf9whAQe4YMQJ95e/+Z13XLkwwCK3d+foT4FTNp3riTsYH3OXGik4zC010uBv3WjXQfojmOKssIlYy1nZoOLiLRhswUWx+5IVZXJOJ2OzL761/GniY5HwMk87vHyXL8DLxQMXrIwBC3PmA/ziT986gEJaOOdlobcXahyb6DOndtwZa55s+DF3rXmcHDwfpw8+hbmIPrB9gVdwY0lLDul03mI0BHZuzsDMvpBsJuiXuVvJI+3cFecu5vfffPfw97997ZMRXFz58jdfxl++oC6+n8Exc3AX93zTPHep+z0Er72rjk/HDWpQtMyCMjLmsh+juG2JnaAIlXEg/8QA71iKsE9tdm401+aRZKSYjRjzBMbG+dTPukcW/GfPs1DP/7lGE3zWtJTmjDGEQvt2a39k26eBwtbQgwP+9B+xY4EBJXL2LXWoRRxtdW1MHQiE9O/TFxw3iPJj9n9S8NRvZ+TL28gL0BFS4fgmKhhprwdyh2ne8E/e2Vd7TKtD1Pkf88xv9nkX6WmXYGzxRaLyGXNgjSXvO7/IIzQcE3RmkY5fqZDjfFb8Pk7UeWFLrl6/zXccvHnrsYL/ZsBFRPapvZiEDi/m/ns+KpRLMNjHW3xnn8iWiUNEXCDB1v0dVtGLyOK4qESTzLZERR26BImB9Ukl9rQXB8zzdyU5JRfkiSeO9u/OYuqH40LGgkV53vzPAmBxPOOC1j75JT888ZtOGJpXaCmuDAV+ToFfmkPX7dYhDV8Uio/VZX30DlgrZge7QSuPYm3mthcqn+OsB+Rb0F8bthZ9pDZb9ItPrNX3DrrKvuEtXewcSR6IBrgKdFP3bcAAzy+FzUl0lBoYPRikFV0IaK5Z3jLT8EWf9vSmglbt2RZBDOC2rE0Uan08aS+QfWsfQ+IbO2CMT0I2NEGFssk62Me2cag8msaWfjkfPTtPLPi9GEJlHCEeLTCNPbr2ilVP6G8O1/dyO/YYgSdmt1tNq5jzzmbxzIP9EY68+rHmQgeAN6DlgsgRGp7VnPy0U29Wo7MLSnOBDSWd5k2ke26xohR1fX6+rc7GduVtx+Sc3JDT9Tkh6Xy46wZvtO3fOMqj82HoZONwhvmdzwiltDF1VgA5Ties5dIxkIn5AZc+tMFD/V4XHNngtPc0bPJHuaHGsoB1gHHaZ/+GP6KzxbwS+WELg7nY1a6Zh5u3sUctx+IU2YZftvk9c0t98NoPwWuMkFd38wkeqrYTT83ge+FSX+5VaB8xLvajLT5wNO+tBRP44bd8wTj9eA306UvH+kaLvgM5OOQMMUUOd66FbuftvbHU6rGvwq8btuu/ztdH9Q7OIz+xmpjUkvQlOnkXG3wqtVkuNpGnbL4aZR1txKuPPSP0iKOqog9+8ZqjiLAIz9GoL97PeFSf98e+K2kv498aWlDYnLiVUuWr5Ra+iC/jUzc/QYEX0I2sTpBRLtnMUxWrLQ8tU6uTaUV3AIpWrH2XbxQOp+he+xZajVXf2U84aUKXlydTOYEiHH0G577waSTEy6t27ziRnZMv0LXLto8pzgIuJ1s9uY9XT8IcZeP32LJ2OR7sgp7EHawsfvifupyk8fg9J8fw5UTvYxZqxhp9YjE3+XxesdKxAAAgAElEQVQ3j47zCDm6nuDmZJTSBdhmjkAUi0FOLJFZT5OnBvi/23D5lbuh2aoVvOe8spBmEcodfu+kZ+HMwgD/LMy5Y+Sd1CziOcEfD57kM1bwe/vFVw9f5nPMnHzzGDg5QLFxWbHNG5+T/cCdcx5xTg4WLwOVOrqcJnU+nbkwx3dicLwTpHcw0YuMk2Xi8kQ/xyHangxHdsrU4bTjwskx4/z0Q0+qvbv44oOPuBPzx59/hI4cselCY8aBGJlIu8XR+GDzab98Kg3GzMV5dPHP4onFLx8z4ALNi6cZY/Xqw8V58nFKbMxlBPLHJ3Xf6/b6G0jWOK3tHXCexmC/4FHiV3ms/cvf/EaMv//164ev//qXxhD957mANDPDBVKUHn794ef8CzgWe8xR5mf/ZzsXfRhn473RhI6PAs9+iV/nOPskYxKMzT268MT8kpG4Cr27nF7jJjcRU4zfBNdOf8knn9Gmz9cszvsoNN+X0P0Xb/jCnLF07NOoy8jJOSQjQa9V2ikQwBAfVqmnkhcSGUbUeYk8c2uw07KAV4jF6ML1E1+8Rl8WuKyRxc2bizp84Iqc4sdFcEQsAuliv8mLufss48N+y9Ma7Cc5sA1UnszJcYD9nHnAPs/imBzgV66pazNLc9ff8dhjrwSiGJ/BTeayFmfZnDYXFVi5U5iX4UlhX2yu81RGLn69yvzizvnrbPmiRC+Wlp36cCA38GIM3z/jP3AkvsjgJddq2k8Gd3/HtmPf+UI9ye+YkDNAUqoDJmM+Y+bARl+d5V7++/eEnO7CnKdBujhfn8VnHweXOcW+z7xkwYlP1uoZpOZux238wQwuFN8jUEYMW0+fMURW/VGmkbL6NsHVduZ12sY9eo1TszqskTr4OOuHUXFep958wan4yJUNvur3+tqPTDfitKN45YgE3/mr2GB4V4GM6G8Hq4pC0EfJ9g7WeEqymRkllZuM+ALInQqdnSobHKomXJvgk9CU3VrPWwdlWsEDFp3KwypmxYEhftq+6xw/UWYNsUX9TGJ1R7gYNmmkrAk46OpJ4fJYrfRAaGxa64Qq382jKqN1V37MZbXYDhXzaCv+dZW35aUe7RNTmcN3c7DbG+DCVTQx1jJ8RpH2oxji5+JEJySJv9U2id2aupdschrBteiE/b1MLsKngaYP7Ds/CYCKysQY2TJTd1kOrwAcHHEnjvIs1uoIjD1+Yje9j+yR0U05/cvZztXYsQ3O9G8+vQMUlG2DuDEUed5j1/lVj3cdIA9v8S9COyagLBvqG5O5G/aGupFsYNrFcnKlbc1bjR5cwO4idbwojxtweKlAPY3NAcK07dJsolqB3enHJKa8ORJiFvS+z40Km5b4wa4xVoSVQPBor5KRSnUJnzFZHirZ0GYRaJiD+ONEQli46iyyQYULRbFqMy9udreZFoD6OvmteeOxD1cAoZfO/9Hn+ImCHPA3eZfL+AF+MlawgKpPh/mikvJP9rVbnou9sZz4zwEYVD2XM17A/wwXe6htH1vH5Bbz+uxYgVH99U2TspzWxyOZGn276zd4AUFQofDDffKzrfsJLjI4GLsnbeWOXP0xOqkP8Oq74KpzfV7VGMWAecVJGy/iYs5x14gysJ7Q7UlTQXjHQzgFAL195y4MWL1r2UUSJ9f9F1LNCAv9XXjCgX4RZ7t1T/pZ9EX/fb59+sizSH/9hoV6HuP0W4w5ce1dsk9+SzV3xzipzZ1c+IUTd7Z5XJmTU/53eh93j07+xv2r0njSQ3cCBIOi/ZtXCLJgymPKyZf8gwl9fH76lM9Y564qeahx74CyQIcHoOSHBTmLM+rw6aK238ZMfg63HYgZEaiwKOeuOYv05SgBO4+BInirFDHnthNKYmHf3d6pn3w08MI1h9UcfcdqkhMC7DO7eH6a+fM8i5iPufvKRxC4y5gPJTz8ygk5TOLjvMRBCFZL90t4dhRs0582duYL7vkh/zyFwB10ELzjJpdyOrnB8cSKF8czbbAZU7BZyDLXrn6WcZFnUQz+rz/zJEaeCMi/uXubf7WH3V/++79z5zyPtcee+cVFHHNBjMNjF3DvPnLBhn0rjvP77pf+z3vmAHOZx7y3GPvsl72Lm/EOD/dV8kA+WKAkfn6c59GHk7FlwYecuMJEWLcRuTiNZL1Vr+OCIvZcaBtzNc175Bg1Z7Nvb5ztEFPcqK6H8kHKK97sAyuMhh/HEfzJUQDs14KxTtEwnfbDmnqVjUGDRuvijtxgQ17nOOAuiYlYovbpgeCgS/74l41e+Mu8RcYxkQWsH22IHgtiFufMbRfz2Xehoau+sdyuLYtrLgRgFz2/LyB8vNsbXwFPFNnXY9fjBZY5bpAL5nj6J+AcU157wYuPVLA457scLLHlQmDtOmeJgxiYM8w/9hligSdl59FT+JpQcoRb8oWMbX2PiXp0LQbzAE0Mu33cooe/P16gy3yCI/OKJ178qMb06QaUAfbYkP2Q/4DBxSK+04OSyyYypa7vjAu65Zr3hkB3yrKO7VaDT56dE6hsMNNfL8gvLGR7c9D8tdt4xaIf3sMdzM7AdOh42vgYB6f/OByMY5E23Kbc9fVl35EGFt3qI4Xn+Rb3kt4MlBLKC7Ruyg+yLSaYYJJVZeMUZ5WAEV3e6Mvm2JxkRBOddGs3ckQ1sBIf3e67nEd360yx1rG0pZ1xxFAIObbfgdDREoBv6stVg7TtTmP7IEHTjmlQj6yx3/sqQ2tzQp0CLAU3rQtQDsjoYBu/HSNay5F6ipzWHg410tcc0MDeMVmf2iK/6+uesQOvmkc/FfiIXheiorfYmtC3mHCbQu2MEzijs1D2Rwc0y+Y6Hav7CHcx2EYHewpc3C6Hi1Rqw3V5javFp//qaieyllGe1ubdbn1tHuDQl+9pdE6V244lMOYt/SIHo54uj/TQUi/ELp7p4cC2ZIuAo3SAtttp1tng00gZlYMRO3m0F9dR2Zhg1v7WcJVefA0HuNH3qIxASvRzIMZkttVFVpwrvsjG1n1g6vVBY7jETMB5h0r1m6tq0llu/4QvscX4LM/msn24EVfyg21/eAx2CW+7mdOvsQZBkMt2uUgB3tDMD5bjBucpY0vt+LKjKVpZtriggHUvBxdo9UdTp+vPTv07t8K7uihRYjNj3fb4CZ612cgfhZjtnV7ygO3yX51lTBsvQKjLNgUZPeVPf/KjUjrG7/bVuDaLI/P1nf2FYgh5O388Iz77AAo11u80FGFnV7ayHT0Ajx/sj2UU8mvfZzKE0CLPKA1FrbNzyJEeAaiMD7WjrMcCi08OyK2YeePErSekZePdSk6WgqMeyJMPfaTNQo8YWdx8+tgvBNtFK32UUoleThx7UgW1nJrGRiLRMZdRn6xox4mlNus/vp1jkXM3ybt+nOFFDgdexNRHWvGdWy6JizhYHIPlyevLLrbxj19i+1el8w5GnUtw5QTdf5/1Sy4cZNHZE2vdiH0CugFuzCy28M8Lv/LJQksP5HHkRrGUiAvHKY4Bd6GyMO/Ju5lt3OqjdxmSD0z3eEu+mqPBZKe41PXj+MaGuOCJHz8jPHn6PF/6wE1sjIuLKiwK8ug/j99yZ5s+FvDeKMx2499tzFsGzLxTjy3FuZGt+uFEgSd35Djh53P91UmmBsNtYiP31gO3w0ybRVw6IkNJSGPFnJgRscDgkXTu0vNlcHx7P/8uDd9//fOfH77+y1/CgS8GzDzNC0yw94JW/fbpin4GHWxyTtKf+K/heCqji3i4lA/4zu349+5jtu6bsXMuhBxbvozszD/8NowNxoVhnFU3W33Ti/vkxQsKyed9P4Oz3Yw9NX7Dx625Su7S1/2eWPuif+e5uUubIh51hUimMTk4nARoDGiMKwxaJj6th+N2PdqSmyjBZfPpTeooMeSc8zGtzr4AYHyXcxfp/KtEcvM8/3qO8e0+0BC4mPIyi/dnLNAZc+Zj+Ag6RPrUSRq5fU4XKuSQY8enkGHRzgU7om1f+cKbz6XznQId1+aai1xcFHqT/xDAfPGueXQZn+tYwH7GxQX22fDKHPYiJk9FMC/5/+tYJLFyzpY6sfGlnD5tz8UC+UUzHwWKujrEgC/wWzpH4N+LK1ffpNO8+URV8tcnQN7nGMwXHOaJorz2ghM+SP7ZZ4YDMo7f2ctVaRu9PP2TWOj2/H3/hpiP5vGaU2C0KDu+Ng5DDL6sb/E1N2tbb7cc4Cu5c75nu4Wq369Af4THi3m+BHK/mp8pg1aNvnduIiXg4sKvauqkXi61fN6dDo0qVZt61BFrnLBu5FGtRd5byeY2sKuLxxA0ActiDM4EWbl+0B59/SPER4DEGiVk6fdELfZ00aMq2wiqqTT1bFtNl0BoqWcrWDsR5DW68q6mO+Xm6kKIIrbZYXsQKZf2R56fu01hZRM+6F5I1D7XL+fBwVV+1EH3Fvdd3kCLBnXSu7leH8jX/7C5uIzpci2HwaiweABTHCe43UtR5XXniW5KuW/0V0z4av7Bjm5srSHXcuwj3fmoj0wEepobJNXTRFChlFdnOMinPqo7GO48eL7xYZzlMZ6Ia+zvOxs2tVxbJOOv1cYv3swBIJlDbEeu6ol7DTcP9bHjSrjlFj2dT06Pj9FHkV+UNUimdEqzrM2nIG33HV5wSO/q3bDFou/IQBkOuMrPlStwEJaLrlIVdrHrivfDCz0w9GGuqLdfbPof6UdAUV4uwHvwU57GOUgiqI7U8gZ/6vboiCbybAPEtqTHb5qoYWMf/akdG9uxi8/FXt4RakdKLNnueIg3cmOP76E1yjd/TYg5Op2rjIvxo/8oLF905XnyEWV8Gmcq1tFKxSSyHRtt04MJeqOcZmpjSMzLLbJGgAY2xaoqehHiQwHV5lroyLCmXBo2T/vz7Kg9b+vqANxx9FmsfV8sfNfzjjsa7ZXXzXbZoW8oA+Z4NohKUMw85m4f5uZBi9TT5v5Jx5u+MSEX02ifhuaoC1xAwyubzp9wiP6TnEwC4aJo7D1ZNWvY5KQOec4wuTOUf608dwLre/HYWrItpdhxpkwZjvq7cUQerZwE5yT5PXeCOMnLSR1gubmH/Vn8Jx89gc6WM+/ocHLLSSDxcCcJfB7Bf8Kd9JxUv0oMPJ5KOVwakjLeOodKkDo/WzgesPjcE+A+rnkCDHcDUH3rcOBCAeVcwJg80LfJuPvl3JN4ElG2GV8X53ledaiw4djaGYb/CyddozdyNuG9tlAE1q26KFQntVRRmG5O4qNLzuOu8wOo1OFbxcSXfhYP3PX6mFi5k86/xoMWMbIo8c5j+s4JuZxvOPgcWcCKX6fhn4SkD4+OScbex9wztpTaMd/pJ7heoHH0gqF5OKI3rGMUtWkwfzie0gv+/n967py//eo3Z3H0//7vfz78v//6T/uJh3kp5mzJs1zih7FmgcUinG91D7DY+OVz6Ly4i65feTe2Lm66MGe/2wUbweVXzsTF/kms3SYQBgrwmTtUzEW6GFO4dfGZz0+HO3OSi13lG51OuvGXuILvvpYt+45PokQH/d0H5YNPfEwMNGnntyVx09n5jQgF+hND8Ny3RydK8qDvAnFU9CsmusSz/mhRd5uY80Obv53+n26Om+SGNhMfXY4dWPArHhhg5pV9k8/fs5CkMK+R858JzmfPPbbYnW9K71jvF1jii1wzDLh10c2c5Jn3LIK9oIljXlmQ9yICnDmKRxT/jAXf0s73UvDiyZzKsy/lYw9coOL7Axiy8hbNMeIig3fQHd/+Rwxi3GM++eZohKxyLkqZiFz4oe6h1jEmNeBLjI4UNtgh7hvtynbuMm85Dn/Ik07sSxwnr2/Ib+6TafPUg1ECcb/N+DFe+XmavHLBg3jVJVFpr1+3IQY/8lYScCpHRfuGDD15d0sXIfgO/8Hac9btKnhaN53F0acO0zn42qkebtnKk7e1V7o5KC42m+fDScdpVZBNMfiDvzq9KBDgkfRb3PW4wJjhuUq4FVcTegADLvK73Yju/QS9RbTRAbttBCtEcxKemgnbPlW0QEm/7S9NaOxgVaFtKaqft/Epb3GRXS1cWHBDCWgHtvwa6pXIWh7VNhtUbNOc2OU5eRIp8otr86C7GKk2duW2uYZPMcGg4RjBMa0rV/RBokE4FtjlZ306aVBLWY5tVQ/T1Tnc4ZRXUTVE+cKUhUyUozfMzlYfxI65ryu29TcdAFdJo32LTONbLAdnddiW5/pBQt0ChEGUnf7I4S222qn0OL6KAjN9A0kLm/VRe9qppfPkEH3jKn/yiY5jEz1zsMaLF/2ObX3Wd5V4P+1gbREvDfsXl/al0rAxiOzoDzfbx29Q4FmXNRBZw/rYGEbHOIbPxoerUyRW3Bttu2tLFfy8dEwsAx5ZpM1VyZeDQALbtzlnW1OsMMxLgG0s9tX3+YmvF99Qn7L+1wc8C0lMw00+lWuW9sZgfst6xnaAS7896E/s9C4S8/RRCGOKf0n07YZbbftTXQ6LyJygD/lNkyBsN7b4zB/WLeprV+PTpcrOV+zR3KKVuOSz4LMRpvkxzjHrnrH2bA0ASlfZHB3Idl5sJy01LcZEPD2bgEqDdx9XHDWS4OJ4gM94RPCoftM5wOOvH1spdWxcQOyJJnHE1iyk/sGT9GYQl40q7uVXVvULLzRGa5OjQZhHnxPDnNdNvTLvShNZ+j35RI8TUBcI/J/vjgd9DNcVS2qR1TfytOPzLPz1Bxf8+S41T/5ZEOQk+KnfSNyIxOekNHd4WPy8Sx08FiHcrXUxExm58VHryFxkZMsJIp9X5gSSb95urHWsa04GN3NgbooiS7SQ09eqcLL84mm/KMp/SZcT0Wiod95qZnBWCdKYiwWHFuxa3/nkvA8esZlDT14PcrWxX5cLEe7gKp7+uil+hs04PlFJwV9LbLKDZ2nQ2NspLTMTNeGyXZPFXX+MG99ez7ixCHgZBWQvswjlcXTuPnLRxI89YOxveVD32FlQKYmbscMxcwasK2f9+ABkDh6hTDidFxNZ7GuXBWoWy2f+qd4cw4I8M69ZaPEv03D91e/7Te3E9Lc/f/3wzT/+bs56saGfe2desthlEUvBV19ZbMUf317/61O+II7H3FPCkTrfj/Aq31vAXOKO7y5uUOl8zthHl/nH3CwmF8XiLz/I4iHyLr7Mp/X6R8/+xNSFOXeG8++5+HIx7xL3QhU5AYp9pXOtC9pdcLII3CdO4HDlDyMGDsbZbHPal6A62N4VjSvzWjnGU4w1dSXk0vrartb2X/nRoMoISy15lT/5ig+Wn9wx/sS3++dgRZ45lpApEInNcYwuFwmZD++f5k505F6Yy1z2uJQ2PpizHq+IHdm0DQfusWfXZbw++jl5ZF2M8neyOWYbncjhWF9v8n0H+UjFV196UYD5xaLbj9dk7rCFN7jZpASXBDjW0X3Wu+gvPrzIsY8Ffede9/eOr4/gc9Ezfv2bHVrs/FlWkwrCyzZ84rtzLz6I2YGZ7QjAPU98hKcXz/KEyy7QaW9/OUj5YMk9uIyQByCOe+SMxMQHW15wlotPGnCBAtLlCi3pZGudDko4m51wvLbVwWD50CehiQlT+pCbi0IFuzKcrJ+1ZUt/5bWyJQ6I2GBfzm3f+SFJicI5j9JPbU6AUVkcfUU/LvKI+xCW2gR3drABvQwDOsECAgLEBMxEoMZ7JVZGP/V06Av7NhFoqwBZgNrLNjUawS1HUMGPcP3qGMOVrQ0q1dUmeqsK6N2rAzB4V7KigQHQo70D9ViW1qVYJyhM2VzpXNmAZmMc07F6QBEyr3vZNtsiLE7zjf3mdulgX7t40vCy2TgvDo1ycXByz1GRrnyKzYFqnK2u/mYsZHrjxdhKaAluu87Sd4sufYvVxXPjbPDpmX6hUNQnNgVtNIjL8cyFGNTL4NHCBIhH7xVufFVqtuql/V0wrTcBgrNZHR1dxN/hGDR51CNWaiKDb36Wd/cH9IpV3cVq1rGIAaB06/2Mx5iKmT40HAcV67/t1sEhJrvnbSCan/XjNgqzVWfspHMhHD6NGZrhnx+5RE9veVuMZm/4DObmRErKHlnLY/GLVD/SGIziRlJH2piziQk1vaay6MaS/uZPw+oMDP3oWhY3Gsc+HWIqI+4UbJL0nQ+IWq/f2gYjPOrxc4xK1y9x6ZE4BOtm58O01MK5+BMzyGtGx+ExvgvX+IuzYzf8RWsO4Fv99ZLWPYbU67v6V2zFXF0wRDocVz/S/C1olOW0c2kix/TEaWPe1hdIu29tvzFvHBNDuYxVNvxhdcxi1CjXevJgbOlBdxgaLXiRtR6bgeQkkJMz+PtKm8LJCfsfJ1CYcsL2uceBL1T6V6P515mYBeTkO7LocdLmYIMPKidM8dv46aoOd5I9cYoZC3UWq5/8EqacWOU+Te+OYT/xwiEvsNlQNqfb5tSARQvYH95zgpmTu9wx4tzt3a+9Yyq/QNYf+ekdGzgAzB1bT165w8oCJJw+ZpEo18T4+tObh4ecbJtDuPQ8b9IXAoFpjqimkbJtG3mDPnd49s4wPPeCRDO9sa3FbumtD0HASX6UZV/fL38j5/e9CRrkqDysjCAAkJliv4oVHN6RMQyA0F08ZEQY/ySeQuy01VsZkqtoDh/mS8rOBx693gUOizrmE4sQcrT/fm3n1iDLpxhCNRdwhcPMw7WpBnOt+4Pzq5nrQsPADjLJulIT8cZgNNNQO2+14tvh8y/wsrjgX6n5md9w53Pof/3zf+dLAH/0W/iXL7ESO1sX6btgGFB487GIX37+ydxDzy8by4KfxTILZTwzb9jHiYuFzC6UOzaN2hykypa54fGNscvraRZ/LNudM/SzmIkzXuR9v9jMz1D7mHYulPDYNd4hNUV/YMInLzImjuOcsSSfGlW+dptZLjS0zvbCvWRjIQYq0SmJbFMZLlTXvvV03+DWDC3nyag7rtFD9cAB67iUM1/ORh8Ze545qqvEyheTJXAvMj3J+JAL793GGRf8+Ab/7us57u68j8lHvsyQY2Py30fU8Z38x6cXA+axdfqhAa7HqXDcpxa4e05hDnHnnHnnFwlm7CgssP2PANmXnBuMCxzy22N2lJIgxgofXHTxv0wEjy/X/PCBY3GOhdEnXscZ4PAmD9jJi7zEV+/Cc1EAe/55V35yTOZvjPOFBANG9hMPnODIHD6L88xjPoLCBV77yC2JDwbFqrWOxZM8YeDxIh2kg6cf/NuXxu4XqHtBxYU6x3X+/nGsaGELV+fB8KOnfmWrFA6eu+Krptpga5l8mBfGVs7l3vk/mHdbdAgqBRQ4HDylhF6d5ftYd5SwVqH+4A6eeUPUVgQoTUv9/Kk7jgkgxNE9AJpsMOmCrBgXZFQKP4BtXemkf8uxCo4wkkkN3yYicpvSh0jjCoD6Rw8T0KZfW7wUVULsHwNDT+O8RHbd8OgpB7Rblm91owH8lEIXVXE4dNDD4p7H+DCo2B1zRR2k9QEs9s19I9PHmoPvz5UT+4c3dQ8q+KM+3th2AsZ68uk4qrWcymV5BnJiTcXcgnmyTbdyt4Nz+tEnUE2LuzEh3xyUZlqTn6Oj6QCIvRmqpfFErgYHNCobl/L4DOaOlRwnJzWSWDQnx+kzxEispBubMpjacFyujvPmBf1Hf8RiqX9swQEJ6PLyoIss3feY+/hxdZC3jG0aw6RbsEajQLgUMNLaqK9eNZGSyUd8BuPMkYNZlDNfVh48ceRH3jam8mt+sEULjleOhbjp237EecbZMGqLTuNQW9xGo7RCfIBra+tp5ffK4/CIDtSvXFWwuYHzKeFW+41x+uSMVjFbw9li0zO2krr09FNVlekWdfjDC5/NX5GrEU1+54wGO8tyDMjeoVVnFC4cUBqHY0oSUuxv1TbJgTshWoaLTeNGuTrZ4HRyJD1FtaPriht71e1Et31sy2Iwo3X04AKGf0yjdvcVM/ZvdPfdqniX5MQSRTyCcS+2SmEsL9uhduLDDn/lnDq5kcclLfu+o+8JV/TqPVts2HCyTCWxiYOKJRXP+NII9s4/vU67cyR9+aFeswIgo+YidaDQxH7vmqD/hBM289rHbRcHvjkN9AQOvZxGxkfODnNiBQwLM08mjUlW5UAehss50c3J6/Gdfv4cc6fKE82cGPLZQx7vp7B4YpHSk+60cxKIbO8SdWHxkJPp+aczfAbT+PLN7lmw/5B/h8bC3n+VFR1j5eQ28TRDGX190SLnuj1v5jnCS4xtP2+8Y3DGSb3JcwzWqnrJA37JBRPUvFUD/30UVgr6Ru/OS+GSuGEThcwbzLTG9tEcqIJxd3I6h+pnuE4eQMSV78HglKUnyh0TkSL3brCa3H3kxJ9py4l38pPxBLtjPuTQBZiCchplbxXp5Ge2iOFEXnll33AuxJa231xuTv3+Z0/s2XeeMVfxzxhnPlHQ33jAgxsfJfjpx5+D+czP/bLwZsH8l//6r8ybb7Og5g5r4yAbFPi6QGdfJAa5sGvSTx//BSD/s/p1nirIgou75vz/auY2sfClf796ESr7S3LB/GUB53khCMHjYyfMjHrE6+wvCBgCLoakP6bRR5NMZh+Kb755Hv88ns1c52VhH4pD8zjxI/cCwMQhIfzSJlK3qe6YYWAj/agceW2IRyF21NHhTd0IFg9xSsWjuGqrqzrjHChULApTQ4n3K/bjkmOSchavxJCUZdGYCSyO537JBXnnyZLneUKHQ8azT5lDUX6aheOL53wsoMeKkz9QN2+45wWd/DyLz/0+jM0Z+Bwn/FLCHDd37rbd4xl3zffRdu7gU86j4nxMwvLJYxtx8BrRbJoP/HABhjnGfvcu3+j+lKBiwALcOZUtsXxKLuQo9+QmaujwHyc+feQiKZ9l71NL4GobnI1r5w/xsa/4RNHcMT93zTlgMGixQ99jxwwiI8bs9RhIAleeLbl5lv15OT8NOZ968Fve0xc+qhPaDAB4rU9usoFr5Q6RPlYfrXidQi1gAV2MmE4pd5tj0C50MRMICuAAACAASURBVOl27UDt/Ki5yGsHaPSnqa+rVWmx1zX6U19RvSp2TNLOl8RJX2UOdkuKxOMQUGSUQ3TayI49jWhs0g4ZTfNWCCAHBwEB10pzeuQ9yiLSIwuIWGv77rv9WJ1FBaK83FlTWV5u42TjbEySiG719Ph5wqMi/nIRPJr+8WCLlW/+0Sg+JCgQgUsRULNnfExrzaNPnLVdnug0BuT1szvH7liTzHSnn99CxPQW760OM8rJgT4fY1djJqp8NWj+Buuuo/X4BXfzDSf6LvajBE/ll65pyls1LgviMIduY6QidsVtJADWFx1iIFILm+WQCk0xrAa+HOg5OQWhqke341jMXRAVZjgvZvDWVrzgmI+6q7/o0td5mv61HZ3GtHZGM3mBY5SiL18Ge/ypNX3AWEU1P/ZZpyMt/Odn82P/yKJx9K1MHpCDhh32trLpSKwNSGNw7ERXQZ/4CYfOcZRaF3Cg0eMEBVfHRgXe6qOorSM1Fk3ac2lSS5FPY0YDXH4nFDltQ4Tp2Dlxz6O2QhIL4OP/Vpe3+aK3rXLnvZk3enmhs2VyjM7Eo+8Zt9WymUbn2KULtmWINc/xDze7eDuN0aWvnBA0jI7LxnpMorfWIg2vcSeeqYvS2so/zotbGu2rz83xob5/kwQqTuOY+iiKEdDdfzYXHAT1KTf8fca5xEuEvugtvgHM28rLsolZGcb4bxzwMrnFmZwIM3V6XejmJGfvvDAoTznpiS03foq1XKrniTZAJo8+GrFIxZNR7duNrnfHcqLkIib4vbtTG76hG/7KGB+4pbDlRJBHKinPsn3HneRxxue/vXvCya8/+ANHY218G470mXNwc1LIZ2X5/KV3FYPZXOckLXyi6ELq44frm9VxCzbxvHcbXthxspktmPzbqg8f8r+zo8hCyS9+YuH1JHfN4AEIPLDLS2qI7eL9KvRTdts6742xSINlZ05+k4stz3L3h0UDJ6wW8FLdPKweMvJip0L0kXQOwrkIfZe3mM2n7GkvROr6mAX4+rmPeZGmJw2QKJpky4iCQcKFBT957zdERwGA5PRJ4iU+8u0ixTtl6auC4yWxgohHPBbhYxvcq5BPFhFdWOBm44UPP+Ch44JMW/LcCwXioML8Zwv72fIUBLhv8sVc/C93Fjjf/ePbLNp/yAMX+dZ1LhqxQM+YfXifBUliIy7kvPBBexeC3FHmW7d/+/r3zmM+c35f5HAR69ck1KcvQphFnf9Wjf0lbWKwhF+Qrzynw3NXFHJhxzoXeKLnxbTMZ/iw77zKv+7jwoCLrPADkgXPx8S6+hxfGAi47/6PX9OSd4473qmMMWNIfPa7gVc6dI8gr/z2eDJtnK5OfDQu+pDCv3UFcLCiRWsj23EGDq3C6ngsKhcVJ/iqVjHTJpPP8oVqzEuPg9EjdX7WnAuByMPH/wyQPi6OeKFwxpcxxq9cUjcY15f4Yj6waEyOMgaMBXXnhO3IM//9F2vatv3kRceL4xH/arEXb3Jcy4VEvgyRf9PHXPGYmDlJGPdxMjjTQEfiCTb+q8/c5G545yvG3Q+bm+7zHCfzG75kiAtaH/J/1PlXbd1vejxen/1cPuklFxj2Lj/HaY7Nu2UImqf44q73jBKyLchsh4LHlNwxx2eEzgu4WvZvUC78fcgrWcjxun/LiBUSouKT2nGWrujphyqaKG7/6cEOVWzTma3VyCwRcWpJWfNu6UBY/1bVUHXeIqV/eNB9bFPj52QHAIr+y1siS3j6zWvUtBMvH+1q3wzsGgyYmzEoVRtxVH36sT/EtoE0v3WY3kkOW1QwaC1k6ROBDmoTQDVtI0WveNU30dpqpO0m5LBDybLby9eFF3S76+McWOrgDK4TLljygwt/DFIaz4WLlAmhPPW1uybCcrFz7MGlbF8jWAy7yEF+duAdj1F3J4wyO9sEM3mNpaLlQ6Nu9vh5MCe/+No8b5+ydsgBDMdtt9OHMxiufrzhvgeJVKjH0PxsHhHVpPlf395Rpi9G1zAGW/jmgm4KXqfS/uNj1GOERpldW2yW0xknJPk9PI5V/Zj30YGYevjLi1I7q48wVg84eKC9PlI5XprBZQpO6sZTXmus7aiJlY6TB5QOxNqvj2rzfnSAPiYzx1QoR1SLXdthH/OOmf3bJSxcDgG6q2stPe4fdXDV0e84gV/5zU5+7b8iwebGN5NavzMWUpBXuTQGrNtmw35QlfEd292fpLv4akVf7vCqXRkOBrJ0iEcdLMc22HBKXcuRp2FZPfqwZbwp+hqzS8eO6uBrdDk5PXHVejiu3+hODHbTezhFspyIL3UYyB01TlaQGEvrcpvjjRyiV76NOa1y0yyd93Lze40JFC6uWJxj8c2WGOEGi6tuU37gbR7qFf1yMq7b3y5QigFirc5x2rFqrPQRO/bESLljrmz5yJ0cVlX9GFjUJY/zqlT4izfu0qHJzScnSp7o0JdOqIDDiRpztpggNp496aLNiR1/H1aPb6ruiVwXxtianwB7IphvD0bXhUkQTyjR444Kix36IbE817PkaFDSuRcxqbNAL+cPDz/nW7V9/Bu9QHmxItveye2JGjGzgOq/QuPR6pe5r8+dySgmBgoLJNrffvPtw9tcQHifxQufS4eH+Wo6qnvLJ9y1z5tPNGQrbsRu7b3ekHm3txH3pDjd5JU8Pc/i3HjP4Fy2imjicvmgnldZ0MmcGU50pC0PqlN3jARAFt3oMe/62zY9qDhHqUcMP6Hxl7ZC3q3TTp05FLyOF9YIZ14kx7Q5baY453L6/YzFXV58U7SU08fWR6MLkHqduP9MPxgUuVOJLvOO8Voccp0ZaJ8LkHQ8fcY3bmehkruRT/jcsfo6chzIRltw7MckuNPOgpZ9gM/Q/vjdty6O+D/3XaBzsSeWL1hA9QsMefQZLjz10AJyqCSP5iR9/mu9YOPQbLmFP3dvZ/5mgeO8IbfJQ/ff1rECnRzsscWFefTQdS54vOLzx3ykYL7UbLihI98s9LiIxp1RigvSHBNchLqfN09eVCGmxOAYwTEYLG6zOXk3//OHkVzih+Cp+0YiFETSLgSnr3MUO+YchmyrcvRSUUQfwryRB/FXX4fTyQZiKGfTLnB7IQI580eV1MkBvh1D481nsclPDhnIOKYwHxwP8MClADDFcYknRYw760oGLAvyTPq2WdBmAdp50T6+NJ2nG/ZCCnOUizRcNPHL1bI4JyGMBwttbPcYUvchk9wtFWY0NynKOxcXwhv+T5/logz7SLAYx0/vo+N4h1sgiMT8M84Bwx+um6desGCsmqMu/uFKcf8ONnnkIpP5DA7FuZr6zlmFI8dxTBJPBOG0x3547Nwmj+zZfAyAixR82z3+wIP0s2w5FpkXYAjkXxTYaMM2eB2viVkoDMtZ/6NvTvBvhiI8ZSUiF1tzuC4JvEjTt0p1pqvlsLk52+OjjA4e41aK428aeMmvz1wUNE4iOIBLSOsbQe0IjtK0UBcjfZTWN9jK9t1Ega1utlTxO1i1ByQ+2CkWkzad89aDFwLKKFmrXtXYgdtHG16UI5sYt++RPKoXVzCvWIHRdOJYXHT0qxc9PU66+hefagwWmMc6/ka3eI0D0T/hE0+EoPYggwat+rkshn9AzuSIlmVV0xA/Osa+jG5tFOzj4JsfOF95Aq3++z5jQWMxHI/pnTHdOZejTM3TvbgBP7kA415K+yKvDQri1kffr2xA7xyMF2wh0kcsJ3VX5cqZ3dXBn2CxAeLKK/Lxs9vhxSaiRxyJC06gFAkFCpr1VVJalmN7FONXzZOr0SZfmBPTKalH7pjRiSU6ramll43p2KGDFmW1t42ovXJRPPNjOGhmfeZMMIb1wd38XXwvDTjJq5FO/cbJGPFZLseSPxY1LAB/+NDJG4xtIeBvWraMw1KGz5kP+YPTnKHcuHlvvG2naVGe2saBD20HD4SNFaji1vaf3nfsHrvAqCxWDmiKvoZfJZXCuRw0JfxWVJo4U6+8FTki0AdvRad9+NMdLrZRoS+bLRubuU787nszVlXG983vGBajMYK9ONXEEbVoya9tG4omHnD3bwgq6ZOHxhim4FwCww17JwJ91WdLCY1u815mmO48Fr5KkSFfu1pd77sQxeK605V+8jMvbD2J0aw54mSUBatxDwPse/JUfNxKNDg9Ec/EBZOTV35Y05KH2HlXJ1tPcqGb+tMsOFzI4GfjxT7A+OFkzpO2nHDql1iBzJuLQOHXMA1Kmh3Dnhz6Tdcf8x+1g8cCowuLziH4c3L7Np/Z/OknPudbv2yf+ch4Pnc+d76A5o4nCzDIovM9j7vnM8ec+PqFXfnit3Twe4pjQ0th7IgAHUT5G8QPEawN+vZWDSXjeT4LAk5Ge3dOGuKYPABIovYkAadbAItvHUW2fZN0OSJbOVViLHrEjfdx/3ImEnQp5WB9sHQRATJERrcKckUY6XBJS99eOIkMHpzkw9H5SJsT+6NfVJpR6bwAL3Vs8Ypt1dPmN/tpFx4sljvP1MVuTtb3IxLOURc2mdPu3wEGnBJQ52cuIrFlX+Obzf3cbTj+zP9B/+Vnv+jOb/B2kcbneXlqowtcYJijzGe4ETeF93UDR/DdndLv2KSTPFhnbrOPZOGBUeMdnNEXFNRg3Qv2YOs7E4R4+d/ZXmRInUXUfg6YL+vjs8x8LMS76LEzbwHciw8s7l2MMl9zR5mx27vJjiP5TSDkCj24mk3SGpyNHqnHb2ThqM6jpKTRX/vUJ7AFMXlR2C192LMR75HDyvO+ubv8RaafSMhlfnKUACX5Zywzf/JTux4/iJd/WYYfLqCQGy/uMMaQ4BcO/5+vM2GTHLmRbHXdfUgtjWb2//+7+XbnkLpbXfex9p4BTkb17Hpmku5wwGCAOyPpJCNi8idFiEfG1P7Cc+LOtfhJu4v0RBh9sPNymZLxzy1P55sL9Nf6chHKxaKMERcaiR//5N7X6OB2kdycGk90jPfkKtIQ8aJL3kfO23049pgHzh/1y0e70tEX/viDIjE+yUKegPGNXzDJ2/PnzDm8r1lyF/zO9fLpOJGs/AIrZjYpUs0eF2CwdSy8oNFxIHVxRkK9aOAH++U4Adf/H9nzuRedg4syfoLn/6pBB6pOkacedXbstWQzHBFLbEiah3br2/VkrRvTABp1MArFa1byM756LDBmt+NCRwBHNvVmlEbtia2EpTdadONorDLBuSiTWRpBDkwn3aWqMjweiqRHMkA6hwztG/7JGMIUtiQBPQ+c0N99A6jeBsXBYCDYjX0xKlhU9fV92auHDf7w409xLrQBlTZ6lGxb2VaJK6zO8TvxjsIV14lveuQw2MNn4PRxtw/h+IfQ5gZKtLurQQmyLZeRokcB4xRsr/aOVTErv3rX6O4b2eBuFTyM9uikKken8kNoK8e0MVwcd8z1vxzXVYUHlxjWpVhpqdKGW8c5ekC0r2NPa2FXXayjWYvLvtr3aNQAO3E2JpCComo2VKt0cU4nGMaZzs7F5mrr7Y/5xK+uyI3gUMQBJbtjk2bdZ7u+1amufTfctVN55GiW5WBhry+t7VM04h1P7XDLf0mxVv/ebr60P7qDZntA4wVr+J1xXqNKR2NsI0O/jDfWIig9c3FzL7IWvM4Zg74227hFDocHWAVo7ecD0L1ol0ekKXe/A7a5XZsd590bR3RlYlKHSxEn7sa7GHQ1ajJwsRhz+R1cFdtjNR2rJ1/BIoncsZzo5K3BEMmunspFs+hiU7wCk1tzqXa0yOtANO8AoUs06Rt9QTz5GWUJoTYkHJ/FXsDpHxX9AO0Y4wZJOv2NL/HhE7ldzShVirzllsaYIq9+QKZv9cHVhcq4iYAynIUYHLmkDjc0+4cqIBhVwkJgP125UrbEzUlSPJDv3HG458U7J+JWd/Ncn2E/J2GQReYdwfh8lruF3P3kBIxHyuEBHfMwNhPKhi4lFg4sgD9lAfMpH/jmCeOJaYLJDl+HpzEQd+Xc/Xnxsu13b95GmpNH1kackHDiykkjOrlbzt36d+/y/dV8OFF8U7DkvYr4YPHhSS+xKcvdqoDxCe/Y/vzXv0S7Cx491u2gQLRzovlVFZG5SMvSuVNdXkM8sY6//Ca/+aMeTV8O14aY6aed/uNbxdogw3KfFpuuBmjPgGXn2AhGQ0M32qS9+XafHgwW/9KnIwUwOGdXHfbkgVPB7FNx7AggBcypuEhwfQIG8yd/6GLXxSqaoG4Z26DfD/HyRad+nfdR6MWhcjA78GQ+ZjHDItuv68ueT1NnvDvHMiYMBMcJ8zNfwcdjxPQzt1+97leQQetD+sB78fRFvmYrj7x7x7EXnWBKG7+9Q0m90TCCPhWgJC1iZ1W24SknV9UnH/s2DlRIl8pp7GPEmhIfmSOHwRSgmso8vnIs7Cfm83g2CzOPixw77/Jhdb/zbQbwyZ+vIYmbO6nEwmP8LJL4UDSPj/Q9y4KJxSrHWowiTzzhR3/Zw2lKKuSY+CvrvCKXJ9idH8jyd2aeybjGUnlAio5PletoJyOwwNRZdYID9Cli6EpRcWsAJnOBRR6F2KHB2xeIb8e7bw/YBftyiQ25mGM8pvqHpneWyQPvlWZRjLv87YUA3tpC/n1ag/edz+cDMM/5QEw+C4HH2uGCDvPZ1zDmdnjtMQYskaFnScX8Z4/OxkAcXIT8lO/EJEZ0uMDCvIRY8xCQyKlTmmLqbZMneFBcFBP3cMHGvGqvipyQO35ARxz6+qUzXvNT3+aQzoMDr3JlaPjmDvrIJXMW3l5sAGcendeC8Qgmv6IztvkZMtRSyFcUbFV340Zqn3GIZNs4tKlZcVI/pdHQrFptG3+EGNAR3C3HD10I7acSxupTBYfeCsQ+EOjVjwjp9A66wa9hbHcAelVBV3hpiRFygCjV7aDY1i82l12dCnzs6D5EDYRWjK1nf4gCVU1kWy701JQvfjWkMRyO7mDbZx3TwaRNSdMJkKqSy1jdym7xwm0hsACPdibWHhDt7sCArf5wMerYdILVv44HprENF4FhUIY7ITZnm4YoDMQOdi3QR6d8gyNUdU4esB1uO25yxqsOQG8p5/SCSR4Qf6ND7MqzWXvbqNInJziM9HRu5Qa5iVb3HhtYaR8sgTVcH5Ho0JiIjyadY0fjbk+dIi/68Bn95uLidmRidV5ou3mQgFCo6vSG3OSM74OF78g2X5jVZmMOGwT4aAcqLcNbZ+os53QPLvudm1sXB5+orfFN37ypZCbKT120Jz/jD49LbGNoTsrhyA55M3OsrhYoE6DY2biPhvv1sh7rt9vVjU/dlmdbCPK3J6AKm9ON0zROPmpTh2zvXk8sUNp8MS46GJvIxd19etFQ6+imld+dd+URpdE7yamo24nB/C/2nYOyYaIcFx1j5k5jqYOO4RXD6VstfclYBMclMvabM+fj8lN/UYKOv+Gwcw6ZJWqP8UaXXNA58Tz2Ry7/mXujo8W4vOsrwlf0lI9b4KnSf3Q2noOJVu2o3Q2kH6Lj0m42xIkfy3Ruu4v0ClcPV+aEE+QFi5Cqi/MizbbY4HFSw94Ts+w5ufLEE1tOvjjZmhOus0+fJ5XeMcl7tHOC9Emu5Us1VsZw5uLySF/99c73pyyCuJPDJwO76Ej/sRGzlIlvm8acJF53vWvz4ev7LMDzODsLrywg6OcxYxblr/M+ThZWfhp3FupwQJc3pTtvE2ufEIifOOM99NxRxC925irc+HoiZORic8OJbjIIifwN3/RDmEXgFjDwxgl6OldVmzHTpmMKjzhE052JOfiXMf30qRrUVjU5oLe5VDWViBs7bcJdHP1NLGAR0zfF4xXZOEOF+VPVxJwuTvgPk+ihamkw4pqF5Im+5pdjnMUQPTffyYMhSgXC60u1csR5/hgL/lj4wr0Lcz63IAtUvkqMBXrmhWOtTcwkBy4L1NxRzBhzV5kTf+bO0ywEfOw3yeoj73m6IotVMFmgMt/Y75MALBK4m0j8coAHVPEzY0qTfhfUE5zzI7rmIvlEn6dDjGFyAhDzjj5QOz4CI9Bvx7HHMl6It3fO+153Fnt8ndubPAnw22+/ZZ8nRnLnn3SA/TIXtZY3Cx+//eBzLlrFDbnl8wTQ5U76l+94P3KXAPXbMFlXUZRBb0qZwnw4Z8c85PWiF3ZiqD4a8eP/V8DaNkhsxFdRLoWPMPm1Swv80xNJVa3Sv00qxHLaaAtAB7+ZU8k9j3eLlf0e9ywQyRM8KdTzahowxgVMMEDIbhbf1I3ThScNOvM3hYuFfSsCn7KftwDFKY+086GBHBsuyr1rzusyfpjzmQ/jZ3EKWmb6Tz9YXEjJKMaWD4PrxQbjiZS5iM7n/Dn+kWUqW7qOS0zp8y9SdHhMnzFi7tcnGVj7yY3pqQydHuPAguVOLHAtpI2k5BddYkO3eWWPvHzR7xwNj5D9Lu+R93jJAv0rxwx8A7TpBgmA7nVRDvgCOEV3atl04//c6BgzmIdrbaQ7VXaXn/W0ep0Pa795VWsdH/tU5F+/6CzHRtX89hhJJ/yD0ZcY/JVJj8406xp5YZrkwG6bowoSy9Uw0CVhuN8yOohG155v29MnDRMG4bjIZroGNx7sL75hRWHhxuroMAjqCwZg/gYQOU35DiZ1I1anRuhoqG1kixmpGohEiiUvxtFroqurVvDRrYEqtJwk8vOfog5Eog/9jY+GEyoqjR9dFbqBvzE0XnQdnolrVYtZbDElm17t0WppPOjteJab5ASRSJtUYzaZKwB0lA5gduTmHsPmrERHL3ZGJnz019e2o8ZBC992qT35pnPs6c/fGf/1DStinYL16sktXdtPX2XVl78vinRomJ2VCiSULjBGJbsLX87txOqKm1iwSJkX+TuHw49+MbJncCmDueNVmINm/7e+DuNxuWTlHbzNGXpHF6XRl4/OEUUfrU42DTpmuKZvzS579dNnyW51xAoOXcjALIatCLBpbOf4yuuQSINXLqPKbv3oRM1ip6+ixpumyI19/MNj4jowG6f2O+MHY/T1Of7q8fK1zo0ooJtr/LfYk2r2Wx2QC4u+ycPJ0dqT8/SvcnxQXajVYn/le2ymsxaF0O4Ws9AkY/GnsnlG/xoDalV8HMc6OjaqoNt87n7oRDr62W19+4whjfFyjdfook/f5ln7P+QsCiKThxZtrFa2/NcfHEHuv8HUyQk7pbM5YEjv3IvJyV174MdCJnJO2EcXc0+4yD+FHQ450aGKz2VsXfHDBh20OJkjB5wA7eJcxcCxYKGge07szkla5OmDB3+8BtavJtZpcwePk1HuEj7Lo5F+cNjEUk22BmBzx2OxeE1/lpPkF7mLSV2fPO6eBQgnxBtevgfWu1Gvc1fKTz/m7iF38G/vt/3EYj3yL1lsvYhLFmrPs/Dg0fk3//wt7a9ZqOfDmcIZTjz6zt351z/0O6td9JEvc8YJMwuj5IjcpW4Ogvk1sTIW3qUKr45G5/AEqQz7/J66rSpHmDEHNEWdVq828vRzcuv7wYMiBzW6sT8xWWIPk2IyVgi2feM29rLWcQTDSVviOTEVk3692DcAs+v/5PQPD+YR84U57h1MOEU3GWygRap1AqKPjXyops68ZLHMUyLUWVDyWQfMkeevuvhhke68BH9SYK7Cg7nIBRkWHCzQOcae5UmPLcwbxo6vqfLO9CzOOT6eO3czJ2PHIr3sa+mcXc4Llj1y4ubTsTtm5DC2kYPh2y+yfP2SW4b0eywSKGXxZiHiBS6ywUKLrAVDXjnGuJuPPZg8Nv82d85//eWXJ3/Pd7h/zOLvRXL2Io/xc2GK494LHTOfuRhBovHahVjy7OPaObaTP8cej+EBtRPHscKaIit1GPIji5E4VVGTzj0nqBjbILip7eZ0hpDe2lbTOnxWqpO++EY4BOhHIftGuLPp7iP1AHFBpheieL2FSCwiN/6AwGfnbSEB7wKTPvOC1diI9WzGS5LJe8aAT23nwqKvaRmrr195KxAXnHg6iBzndXUW6cxjIsRciGwac3PdOHsMOz/Ch34W9V7IzN1zF/jDy/e5w5kyiWHOUTdOxR0LgJqz5kKbbCorH+p9ehAdCjniYkzzInRknJsZxfiifizgQVzmKhC+vMKHXFTr+EQ1kwt4PnSP+YxtftX9A67y6U/dEn+Gnob4cVFaoFDwufW2bgbtJV+jt5pg7TwQ5mETzCiW34zX3c8QMp/Rklf0tw2UrG56wkdnvge93tbB5C0ekUwQZZAGRAfw/wUMVQztL40F6oFLQEXewAlviaNrXYDqEsAyWX7nBXptVSW5KXmB0uf4qfXGo4PhsKiHcOQgpO3+GhhfVAqkrXkgH3XkFk47uKoOjeMlRvIziPGJ4lSPRKW08lt9dNrWA/Zp83NydYwPHMhRDyP6NCmGHNPuVSA92I+eE7Fe9WEvvi2NbhrRWjlxNReDZo/8kkdk5o9KDkI4K4M/tcmLaONr8bYPferE05zThjY91a5u2n3tmz4MU1DTj0iKKi7eHoBw2Hyh3/Z6LPfVpZN+i/hTV1hmWC4G3GkQ/8GICRprLrsBdacxSoMjRurKa+ccQECfqqnbLOpIEelHJRUrWD6IavG4L2+shyvYtmZzaz9gbZyqxSK/xr224Xy4F779OX4NJ3oPeEZQmRAojR3g5YQsf/Ht/B4O6PuPE590C9C9+Sd3YGFH32AjogOpXO1qm1jsBXPslAUAfXB3nN1XXZvxos7GWE71s3byiMVyeuSg92C0uGeD8gpTFws+8Bxddsa9beNHQgqiy3GaVnku2PBYEGwowb00Wit2+icvR0c/saErqndLsexfv0rcXPhX5g5mNOqv/IiTsnFvfhWagUXrGIGoLuHAd+zXzn66DuYgnVjAK9bdfr2c5KzAtOSkPScjWuITLFCyQ2YMOlQcdPA5Scs+Jzic/NUW3eqwpd+fnADu4lwZwHWhnBP5ry6IyNwA6Hgw5iTfRXzmgouvYMKLk30WvNyt9A5l+HzJHZAuD6GfnQAAIABJREFU/okFJhep5WdMdFHS7Ylm/HBy7MLbRfo8xh+jHq95TzDqacOl7+lkIcV7MPMXGYUTR+7os2Bhoff6h3w3enx8yNcZwZ2T6ucvuXuaD9z6/lUWff2qpb1I4EnjxEz+zFXsPnMXDBcRgbExqKNnugi4WTT0aTMwnlxnoqvj6xqyjGGwVCu0SKLExgRm//A+cDykq/4HlwD59R/WAgVbDCHLJDotF5+ClTd8LOsbUAocstuYqCPJiNHrgvBAK2eO0j94au0G35EL2Phd6IOTRQfv+/7+x++1Z174HvHI+ORy755nbMFmEcyi4Eti5gOl8MQc8G5l5oOfa5DFLHPAPMdf35+dCzeReQEne+8o5xigMK+q23nSu5XpIH4cZK+nyRNpQraFfJcb4h4r7jPGCc2LCugyF3zRs7456h7/fv0aK5QcZ9zJ91H77JnbXnDyzvmvT3759R9P3n94dx5dd1GenDWmWQiyAAw06MQX58Ye8HAkXhZA5LN/9FNHX0bZ2CZmQ0Vv+qLzUNBJYYsOWNYRpm0OKy6U/TtXUKLUP4a1jmgc8jomz1hLRz4a1c+NmEzEZ0RWJwtojj211ShZugFMAf/B9/gcbXV2fEgtw+RFtNgzVjzp8Dx3zuWafJvjWDHH7xdKd1Hd3OJy+ZQvLWrGOYy3B9m1wOeCTO+kf/DiY18fIWosCYeXLX2LOfXYeBwGjD0Y4FLkBKO0yy856z9pdZHxWt1FOtwzLvxPyk/1QcFYtO7JFXbx85SnV3LssfcpgOTN/OQ4NC4OluGFDfMWOXgenwUG3IKboW6P9WzYm0MmnkIEzeKlCMTwzhg9QBcgvcyZeImtOZs93Ci7Rd1+9gqzIQ50sKHGb8RtpyOFfvQsg6mQeuTziPsoOOFAwBBZ6bFHGLEOTJROgX3U0VmSQljULzJaYwDDYgV2A618vAwdWsLYWQ5j/iDR2wRH3YK74bBtRTba1Xa3d5dVGX8keV9dbrbmJNnm5/i0RZsy9vZeekeaylA+9osjJoO2MUTDPN7yuXntpKk7cxmzlW1bR4O3fYCvf+r6xp/xUpk41ifySDGqWjkhUk4XNvihHr2eXCEtVrsgWPy7L41QGFJ4qx36AOaPPQXsm+7iXwpV02j55B/lPb/g2RYb8LSj27zefCLHMb+qxdtw3P3BPdzxXI7FE14k41vuxuTm+Fbz8KhvsI6vtYVVXrfES337aRMSxZOf4VRJ8cyLAQUjyuVYqysHR4tU6adxTlzkE2MLe7Wmfe2WV3vh1h9JhtsjdvgtZjr0J/QduywwHGttuqBCLwabo8Gn7zAU9+K3+RNtY1peRbspk4ZygYV5A/hw3r7IlkpFtxyvzjJif+Eud9zYo/oeC4WFc61iuLGKMjbLJyTu43mSkP4Th/ZjDA8gaQ6Bbe/eLnWGQToYh+XDHt0t9uX1864jdizMX/btvewYL/0FrDmOzsoC3N7xEMWd53e/zqMIzsIFPUwm9vZjsXODXKmA0/qnOaDr07SAMR3f8nJ2olRvFwCxZH6tuFGnmRMD3Hbel8PWIzZ+9hR8yvhsVr723WsPLgHxy8mHlZEFxQVI/vs/48Q/i5pneU8qJ0OFhicnlbzAJNbI7UtcPEJJfsBmQfThfe8eLmeWO5xQudjFlh/zoVkkcGlcjQZXOcnMXc3vnvaro1iIeLdbGhND/OGjd8HIBSAsPPp4Jj44afS9ulnIcceME0J4P8uC/PmLYM8Chq/J8hO4o8Pd8/Itr6EHunF/zmP8vH+UtwJ8TZ4CaF/jmAiIL+aGyb7WVjYv4qVHu1FMOM0NFcttXgE44uIVF7zms7qqZKNOcO0fLHb022dlmOmf+vRuNc2efAcnMsWHG+0KscL78ktTTlwEySCEQ7qcc9mnrru78uiDQ4Ezf9wt5+0MPpqeOeRj6Bk7T9wHDzBfE1hUgJk2Y/whj33vvPnERZvcvWTRZD52/mYP1otcpHFhk7GneNc7vLnr3k/bjiw/3PX0AonHbY4BFhgYyHfjGt1wgRfHCr7527g8FrCBb4oXxkhfZI0Fafsc2/TtYoYLXnDh7jnfesCd81/y9+bNm8bAwia8WPRwx1GfwUJGPaZdTOGBNouryQOdHDOc364dTOQAHcYyeZejWAGjnDr4yFBOIf7U6baZjVXUKlJd82nTIcL4uaBqIefoysFOfHxDAaz4wNdYqY+YAsbdvsoyG+dICtA9c4rxX8TRDVYjZBbk9SBi3kKBHq8x/B2b5JV5hZ6f1B6dc9FnmQq72BNXLCjycL8+2+AJmZ1P4DlPmJfEmP0kIPy5cMmFTpl6XKMTY2Pgwhbvgce+BdxyMb8j3bGHHfXtQ5cf54//J/q6aL961QUGvX5QI6/DfNXhvj6zKCd/0Kpvjg1efHphuXI5nHl4Qkwl3mKHT8uQAwubJeuNhsDbrT6z9Jj3tQr9Wzlxe+xfHeNCe6TEZm6oi2EwBZdCfR2E+DdS3U0+B1ROKGrHPheU78pN0mirt4GQsGhCwN04jTNlusROIze2ol862K199/oq3EkclfSmsH0cYETMd+xMCQ4iK04N1wqZCQZKzk2i/dpdbQd4dJoYFIBGe3Dkvr7oXR1U0IPbxUFBdKanTXTWbmzaX/nGcaic3GFefxsTONgi7T/S5lmMSFdvlXgh6ThVvzFPPOkC6GA2jMaFA3gM34OBzZTN9bbxfcqtiqzNctVfBKqHn7kw5ijGnzHgFyP08uOYjMHpR/34RPlmm5b22BoDKLcCPD7TtxjwUCuKnQMRKLwsaVY4uravuGSxMaTPtjqzESro+M8Ps5FfOdp3M4qO7td+4x8bxPTzt9vN1caGKgq0cSQecWOSsvvV2zGtfLIwSj7OBM609SHICtaP0G6a+6u9/FaC5coOXhwgk1P6YWF7ttgc3PBpiNWRI+DQJMlDbY8VunZs63exJq6x23ytfr2MLvnb18ToF6eRoH8v6V4KU0PCH4VxGDu4TpE3eVZv2VaPvnKje2NfxOgM3B/8RiCSuK1vvtXdfr0iufO2ecni43rN27HBYLgOr2MgXPqwO3HRO1nF98Rv/+g1Dxdu+aYzv8SeM4+TC0Wo5mfjSrO67PNCeOQND2kzLLHDZuSX0kRVrHW0tmrrdXgVB7WjekGpTUcx6bDR+WQ+5thsstINCrvuUe/jzyBwktT37okYHbTQ5QSOk7kjx16I6nByxveJs1i1zGPjo+TJEydMYHz+nMeDi1T8LII+MMbzpx/gl2OUd5FWcLbMkxRsWiNRHRNOFtP/HN4s8NNmwWWJfk/YeIyUPoPQF/7LNzrhie0uuvHDo8ucOL/+oWresU9M6wOsHsfth78xscjL3XzuvLI4/xIu9VVvJEHXEJyYu4MbeVkxMV/HeE8W9w4muo2le7PTamFIjxr2BNT/5Wuip2y2wH3qcKG+HG2vUOzGuaYbW8cF/osESLV0q+1YrQ64UfLx7Ew37syuvabZnHmBZuxYJDqmEz9jwMn6qzz18DEXRBA79zJ+1B0XFpbxRR2X/M9mMe6dcxbG+du3QbDQ5g48ivhiLvHEyV64WQwfZ5+F+ccPvMWiC2tCi5l36CdakzmpUAQH44xwLwRubF6sIG6PwahH+WExNOuiXgQj30D2wtnXfM7B3mn0OAgnPvSOD4N7k+9v549jm0epeVoE3C62yEvqOQZcvKXeceiCEw9w9oJcdJiLfStA5oK54xPGN6aZA8Pb8dv6AoU0tMGcANJI3iJ3MYiY/vydShor09rOyO4L4gDah+KUUdMWkV0rXKWzT+86WWVE6mdzt5s6/oxR4F4gcY6aQxcemqGjPK9WT/m08fz0Ay15KwKXJzu3E5B153Uv69jGOWPivOigiwFNqOhe7vuaUSHcM7pp8OTDHBupwAe/vAXIp3syjuSftwrxdBNPkzjOeWSc/5VhnZ0H6Rx/wR2cgD/Ut90LDfUFQ2mHo3bB3GPg0gco7rJ5mtdrFuU+DcM+c5YnmJjXvk5nTzxiEl5KIC3QbEaIPEIumOl38oRs28NHQZTg1tGZcdU8SgsZJ7pxE+EDidUDtCaagdvK6OMtOqjRIUaaq0dHym57o3eVtZz+4KIU+65DagFkLiFmR62yy2CZYfTY2R4ZFbQvAuAHKOT0pVVTZLIkTb8ubnrbpmuSqagJLHZ6Yif+qOv+xsHA0jbQ6CwX1SdhupbC5ee8MNg5A2CEjQN7Ex7sJp5kpeAbm413m3bNpEUvBQujQQd9gkE2GPRTkDbG5VGZnbNRB0SM9D26YiLfHCAfPZEX5cZteBRs/MfGyHnB5EiJQ3NEffjST77hes+JdiW4ztw3plR9Ec4eqJtemjI8e7CRHX64jgSb9rg9RqcPBsN7MTGLHSrYwlvXFSCsAojjz7y143RXdpEuit1no29btxzLTeLpWd9W3UDr8NH/5DT5Nv7I8H2ni8HJ6VJi8ZGfK0+Xj9Ti5IqAJnr3sVsZ2IvT/OMg+u7KtkhIO07ktbmj/7Gg++04ruzSjkSIO/9i1/twwo8+u5cr+UmzktUuh52/tuwCE01KBDG0Td79D5g+x4Du+lcn9Yec2G5OUOdOS1FxsuMAROWb60jUWw5gUrCwzE5JjhXKGeczXoM77cskqNuA1DASRKC7XXHv4yKFmXPEslnCdHkW9eopN6R1TFyLuVora8xBqqr4a2lfyPOjb2KjPjHC4fxzs8EmJf1Ri029fWtjDyrjVOzxXF9I6rN4NkcD6y3VOxJ83rgdOerpIy7K7rdivm620reNdqKIQB0MqAPAAiUnXRuDmqGDbf3mZJgTQ2Ice07YOUGnX7xWMbCszAtZscX0eT7VndKTz1R0wB3Hvl/36ztO+uZudfjBhxMsFkRf83VoqGsiVuzznkNPB3uWBZXhSF6iVHcRpqQPPOx3EfMidiyiWUBAEPV7TNXDKX43zi6CPCkmb+mjvMh3Z5dcT2zXZmWHS5xw54k75TzW7okt8XEswq9wVFNozzxduXs75aQWymuI4NR71J/xHhJ0F+Ha1wjpMQYprUtbTmmupBxVU+iCkWZg9pyHnJ95NU7vY9O7YyDyF7vol68NZSeHaenD//EdyzJsjhbXOQIeBG/+WViyeO6JfD4/gHEwE6vHY7RB5I6lQWShOXeqWXz7nu+MWxcnPV5cfGrVO9BxmE9v59jowhX73jXPYuZdviWAuRaC23/4Mb8ardvWw4IYpjgXJp6ds+TKC0HMZY4DcPJHcWudXLGUmfzSF357ccKLC+HFtxjwbQYszjkOeVJk74BWN76Cw+K8PuBHHnj8n/dBN39ZPppXviKQbzvIfff4zmc00D/cyBOl493j0Fg4plLO4p94UOWP+qniO410HMx0bj89FpTWZzoZ782j/RgIPi7SEkN/7dr/8Z0r6I/FOhtcDds9CgOC//C488TL/RjZvobERZQ+hQAcTy2chSb/P5NHHHRRG4vlunEYMyqiqbtUN0P1R0TVGYrpPmD65GIji13UGPuFxLef0RE5Fxg/5hPswXyWz+UoYqAGtBd6Q+NW7vPaenQ7ulXClHyuP8dMHWTJZfKQ2egcfvHyVR/9Z2GeC8Es1vHNcXFewwPX1/bJgHdiGy6+OmdvvnEeKTjmaH2PTM0NVM3OK+Sd04Kq5ia64BhjutwfGX2USDEj6PyOZ3vSaFmbko6sHJuoVULckZU/+QJgsK2PHb7yJp0arAfIVGn2CCiQwjFVZDdgZNpEvurIKMg3KQZXcaRb1LAhYV/gJXWwwFxO16QdXJHq9UoecKTwsoNZUelLCX/7jWnsI15ep49go7Pcj38VAIrFYq01JtR1WHs0Nw/oW7K78Boh7R04einbQ41+dYCdXtvWUxvo9b8vNCjrX7xFxqgorRUfW64Ib8yqTB6wXH68Xjgn9Nn8kquWEkRn49Yu9odkMBsbFuhLsuZTlwt9FiKFcXnKBXLbfbNfn2M45jcf2qx/Go/Yy2vUzMeJWw5AxjfhqgT98i9S25vzUYk6BvdyAdRXOJ2F0vQdFTQm9lQP1oCLvBMgpPzndXelTQXLCzqnnq6BUkn86R+r7tQjd9XftO+oYLc52D2Gj/wqUYZXLiAEaLksj8ZI68LEn2jOyYvz8rH3jEU0WXynFGVrCFbSftsbTNnedKKL+hZNsxlTK1PfOa9qyd7UojRjdEzpVTzzkWbsyAVOH1xFDv6dy6Vbctu+8HGJUUr2K99xogsbysrOHn+ajT31/Bij+tlMUU4dLP1krzFC7Nu4+J1OFKZc4/yIUXt7JxasW1qT8y0+mW5s2R9+MbrHJ0bs1kMxaQ3rwOOybCtHWa+JdXNrP/7tGBT00sZevemcrE7eo8Avfe7rGU/qecKTDiLg5OV2MenMEZRTuMN8x0LWsQ1S8Bsl0hZPkvgAnzzi/mz+93oyH136eHSWxxN5XPhD7uIdDs+JM5yIN1Iev+V/DXyw93ukg8nX96CnLrHBU66NjkVg2yIDV92E8TT2cg4uBV1O5MRKW9xtyxcm5b06UbpO/nhdzY85RVVtQgh+sH2fMou08OeO+S60DsHoywTb2DgMIxs4FUzL+tFi/JIH7Ipi3jBodDCfAp8plU1bv+m4FKeR/iOjOuM8+p0jUY3a1hmjrR93VMIROTGYQ2z4Uda+tdOTAxp5cpu1nx+Ixhh9ySfxg9ECCIC0jlBMFjSOI90x6Hx7/uTju48uQL0rD1AgOvapZj5w19yvr0qdWPbOuXMwyizUvcAAr/jkK652EcCCXpv5vINPuXP+MXX8M88z+tJm2cyHVSHnk8B5LDgN+9ykXu7NN3lhzjS3qAYhx9Dy9u7/LHIvGHJ6wS6HLl4Sa/rg+zaPtL+dxbmPs2eB0/en9xhlzGvbhQ9jxh1VCvPaiw+R8QFx8DA/XNiIjDv2FHNtpRfjwKP0iZQ8aZNFFh8IyYUU+4y/HAPDL6m+ivbNjf23vupWAHesnVdgilBZAeeY1UPkzrnm7JqL9a9VwHE9//YPn5PndB67CKWpDVwpyECi0MHTBn16g5lBD/38MV/2YgqvIeDyIYfYUb9wNIptPYASjYlVdYHlPzpkAh0tiCdqFKgRi77j/3M+++N5noVGhs8vCZxHo1/nh4s5PgUU+YO/AVp+y5W52wU2TFKyu8ZnfS+T3SPHP/Ey5/tI+31x3ieX+rkPCwxfYjEJ1D1WuQDSJxHAK+fF7t5MRP88tZJ5Lk6gsLkStZ4qn4jEpMfYo751+Y/56tqnRjvMRTrhtX3U+As7c8VrEDEVvz3oXjagRz5cjaMmqCmmH62+CcdqgRBqPLMAKaXNGtnORocCQ619O1C1CVpIGNQASZpOCgRnZ4LRZZCyX7/07wSxHsUOQnSnDmf0bY/lQRDujjZ663v0sd278HKWkB4nBh0gaMF+XgHgV3+Rrd32L0fw6cMsCNZBwiQ//NrBbrgdEWYD3dem7WHfIiZII9rJdvL54Oey77jJIEAdQxAP8vBXEhL6yd5cQwrB6LfarYj0w0mNa3NiRxSVcmj90mrNvg0qojIvTz0tJ3oi0Jd+L6SLS1S2r0D1PeOyAA936/CZOYmdOQV2csKoz2+dRYfYyqG+rGOSP/niEZ53n7V2q3g4Ni+x1M3G3H0Ra4gepZ7LQSdwRj58VZq2/Qjgsh2zv+fLXkB88az+ELrOubDT0SPWGefhUZU9VmJjUiqVaarlYsfhrSwb7/hNrI4j+tspBXJTW1NovwownD6rQ7dc7hr0LiPAwcFHc8I+JQL9pnPbiE9OlU6fRNBS8+jUR2SIo8M6xXyN2oSpXUVDBPXpvOe3cdfNmacBN08Vy3v7uh+rBiOHpRmT8oHo1qlM2xzAmz7kKd1ne2KmeuVofdKvLpsHPFDoK9LpHJ2NG62WAXA3XIxl/FKHo3yWH5a3cadfyfZf7foIxPzDbU/0gntkg42uNHF5DFOBG/oMsI2e/KsyXDHYE/IVYYY6e12oA07v/vFdstiZyY0hxnDjZKg4URAoO/bg3f5n5SbHOaayDI9C2jmhyxlfc5bFBJ9MzF1NPp2Ykz2/7oxHkAe4J1P5Sqmc7BMj9+e+z0keOe/jxPPhP8EybzrJBv4GwPgELQTZ71ipltccv3dY5Zy4ZcFewwal7tgi7/szBzZtMAEF1wSccUzbYWBEWVRlmRLOX3JHlRioZ3WTnquUHwTB4q8c2rhrTp9OUUtcA8OcwQxLhmGh6FYWAfq1SeMo7BERtiiuvjWUsBehvvANPvv8DRX3yODQxVttt1+EaXR+I2nZ/4GHiXqLjbPqcg6Vh8Rzh4x/GZFtwIHBdk+qyf9XF7+MqTTdM2d8BDZ3i1nsuvihh/GJD9524J1zxiy++OuTHZon/o57Y+xiAx4f1X/y5H0uJLG4hz62H97nznnGHXYcg+Q+VxlCHrygMWc4TiJHX0O003bBjT6hE0/6+esCvdy5s8lTKAcb2/lfihllx5u9+QUyXMDhiQ44cvf8fT7skEJO/Ko4PlNhOIOJPYVjkYUS/PfCBQv0qEbO4jp0c8HiY47zTx+5mML8L3cBUCDW7OH97BnfrMDTLLlznw9CS4d/8Nj5qAjjsROCJuORn+5pTxm9tirdPCCrBTXsu0cLOe2DY183d7n92TQnxEZ9lNM4nFh8007fxTV6CzaByE09FNFvvhlbxko1XjN4/Uj/6hRbcGWNoP48n0H3FBhcrmG0BTqWVD5/zpzn4kqOhX4zBbGxMK7K0/yP+JyxpfDoO1ze59sNKOJLdrDxP7G0Wq7mQj1s0FENqJQeC51jvE42n3yAHrnwQzhz55wPd9zH2XuRqheGAPFzJoLP65BPfcRudTqXdYnnq5SG7Z13RlnKxuk4wXWsShcFaoz6xEN/RMudfucKPlRvTCpVtZjf9F2oAFKKA65jj9XY0JuqPqmPo5G1vf8jVnP+K8doiMW6Jfs67x7hmaRCLoRULomJQDl/qRejoA/29KOSn86D0Vki2Y+KWAe2amM8Os3oRTS92hZY3gaINL8eQEU4PprMq88r3fE1EGofPmPb6IDcHsDXOdU0lq/VK6Zz4IpVPVTFOhzBLYAeyGeaFydyV5+Hg1D1I56JoxfDoE0ii4xGivJTjebyvHW0G9UyCs6349mLB/jBrnr7QvuHxVXdDuruyoct+d/YTq6C23FaVOyu2GgRHhwtaRSxMnGvXvu05sSJf3D5Kf6YZ7cckBT30hEvnJwrNZnkjPI6x5Lf4bP87vbHPMJJn/42gvIooHYx2HGCt46z2/hXZ3HX57Yb/JVHY99sDY66AfSEoq6NQx8ASjQdD86KqT8U5VZ06+nYRcKOJQDGgNGasM+fcVMVKxUKnPBtIQu1v4/VdGYHUMtVW8nu13Ha4wfd9aAW8vh0l439M1DGQd/YbHuH5ewB0qZ85Z3/NNpl/hkjbvJjfQksPRSjfZrDddXo0O7mp9XiMf8s4fB4rMrg/IM3yPgxVrjoczgVYdJaJrWuCO2r3MZpfdu/mKO5ARROfw8YNq45JB/yvZizP8cI8cWG/qk9OkqnaPTPeKCwcZz69qFP3Q7yEs001X+Qr15zsCcRJFJ7kx7P2lZHfp5Lgzmg8bO2xrCuIwdnL9JyFyynZWifXBye6OZvi1xp3LDkFYE2noh3sYSSd1ImNj686/PnfLq2C4Z8INd8lZVQOYPgZJATeT9gKx/WhT3vDeZO3ytP0qKUxYSL+RiVf1iHFH8U/G25xpXIoq8jNo2CfuxM1ywsNr8smvZiiHdMUQJakDrbE0Hi2QW5df4P4CUn2ewdm/HJjvZZYNqfTTqWGa26WVn3ytXcCEQyBozrc2yDZ5TEYQ3rBmvMgt3mPu2Uo9sQHxdc9JuzdjbVzSEkyB096gA2xdcLA4pgcemLrJyL0XwjzrwZW8cw478YjgUso9Cxqr/+Tyw4/2dY9LGocI5lEZmJ4dzgwwmdIzPe5AK/HANw4275xsgeHyzcWXy//ukn88GihnnJ94i7cJ1H3F08Z/4S6hfmcg6Dr7nT7LTJsflsLooZE8lDlzSwOMMo/vzJHp9cAEDun7hTX1n26FPEsU2NixrBzmK4PRxbX7K4euf7icFGa58yWHz4Y0ciPMH3f8n1VAF5c37Hmru7fFvCx/fImqflKji0SsVKc9MnG4gfrCz5TmG8Lv1UjcUhUWehKr9i9sho09c69ALPNhhZNJ/8NFf0q4PKN+Uupx4A58LFK9J90Um3fo4R/jRiM04YL5ikjxfipravI/Ai18mDC/PkmtLXL/LPrGlgzpdUxUGpoO1e/OVKfwgTbWtRa7VmqWOOHy6UeNHmbb6dIvODOOnLzM0ehJ2jeaT9ZceMuSOfgHPMRN22H4KYNriM9eVzcwgnlIc2jk4BR8fu+RDOfb85T13wFBWLdgq4fnBdjjm4EMMu0rnI4VMh2HPRKbY6HcekgbhKbnkJ22xNboxFJp09ZQ7xi+cGuHiNRg8Hf3XqAQ36uz3nUCOzoyAxGz8RdiThgf+GwyDtGGg3bh08EsTfYsUIjn1TQoTKMaAM0AxNBO1Y8OM0ekcHABwsNcjSn/2BRSZaA6FfTHHGzeCAu5aI6gek4YIsdvocX9T/wGd01mr73ZeMmFtlv4V/GFfSgxD8FrRqsfptjX/V4qFCMVTXGM8oTOwjY6e+7W6If/HpbK7at3FMOrKLrrFeeTn5PX2r0zge8qenjQ8fG9HFRV8TE907H9QgN3KsJePUSK8YLtOpTUy0tjSuYlVWHOqXv0tWmpKJxiIFZatnbtALbnF44d38qBs9ol/O+JPLxNXOAY1idaNEJUXdNHaMaFcbr+Gr3somlrHFHjvHA6Otp7+cZ+zxMznD8eJTJ+CTH+3q92CrXYf1hdX4jLjRF1//GJIY4p/+i70i++SMKvjAZ9cFeBrDyb6toxMlfaOM0fgx1UjUQS8lDZqjqaitqaYHc/WAUvPSXyjkeG2p/3KAAbkEZHu2Re/kAAAgAElEQVSRpYz65pXXstVb7cXAv33pkA6YmWPH9oZfL9VvdPVVbJymj3/8S4KThM1fjd3WT9Wol0PbjnFE13xBIR5UpE5JIz5ws/ZI24aNBOxbvGrCOhwD1rEugK/1MXn0AWIKwhnYtT2YZ4yjI2azstzLZ2VRIR+b72Fb1st9XGb3B1/o9/ebuIJbs8qnfsHXP2LHCWV4D4/sTtzwxc48GDdtTtyQdU6wfyhpK4pYaHSp5YVDvFRZFuDP6ZB6vi5crfXdfXHAqg+ti0UVeX5ONNPmJJS71Yyhd+ejii8KX8XGHXTantwFnDt6BLk63z190ZPU3F1/+/ZNFhQ90WIhxCL91et8VVbOu7hbAqrQ2bReP4SD3BjTI08VK8u2dtGjzrmwOSOoKcS8i4rPqbcf9R5TLOBzqlpDsYOTk0UKKI4S8ujBTmSJoVGe1FpWp36aiyu3ZXXri6CyiSONO6J1NihN3AZA/abIwqo61VUdQqpVd8fl2qMQbsFamZjEecOuDPf4gOB0Uo99qd1lfR0obhZ90eIJX9qOBQu41Fm4kNuHeR/l6nUFRJ8L9HySO/q//iNfJZbPN9jFxfp2ATe8GCNKm1e97V5M+vNffvZuHjjv3rx/8vtvv3kxiXniXeDYs4zgMXZjzD5LCN+dHeTUEsscv86tgGPXDxrMQj5txgTO3t3PIoTFG7r7RxusfV0nVrOJyxR6yffagcfdRRb73P3kggUFv773PLr9/nVeFVKkDpew/YRt9uHlgq4DEvf94EXevrEXqWQRLMcanBQ5ss/P5+DxuiAW2MGVuzbhnbjucTTvGgM142u1eowXcbI/pfMSyGToJqX9qIfd8eH/yJuGALSZe9hS2o9HL+YggYJ9s1FxhHlxpW99iDXaxI2qtsTt+DJzItWA3kZQr4S6niKJDujKrBdsPBZnfImj6eYm/JP7Tx9zgYUnKt7kSZDMM8ozvi5vCj7MLxd6MqmYL3xeAbbMIcaPhSyf+I6u+rE1Njil7+I8sW4/uRR/vaU/Y8CFAfxwt5yvmfMtUXNBlow4B3Mhgbv9zGf+J/gUC7j5eZmF/Of8vfjCh5X2k/A5tijNuFW8m+pumlfsuWiKHzcRU2/vjkU79xxcjYW66WqHYSprX8vyVDg5Ig/mKvtTR7lMyoGxB3RkUQxEkZFSldODfGKhP7b5l9lKvF1gnAEgXhL03Qqtqui9Pam21aRcFqbwwVpXQ8rJoO1F/uBE0QkR3UYT1FSlgyh/7Ch7IaADOt51ZG825VU8DBRFWr+7R/vUHxK3EdUxW5M9Yig20uDBm3+io2OM0esEQTEN9Zd/ZXLTqhtxAPavZvZgDrcbzmIS19U3XMZe28CdAnQaxenEoB4IfdpHffxwIBijezpqf7ZwKgFxkRcNpPyJgx/aiGbf1mwvvRioiRm67qiqOW3U7dleVOvXcdQYg7HKuPCiYq61FdoclF7610aT6jYnxbE+iDKs4cVVtfqjWv2blfqRD4+To/AmJZcc6xSEW6Z+SRor3TuOxjo+lM9G7Ac9OtCemFHo7+TUpsNmcCrXnzZEJpFs8EczGMYzOdGBoI1SvYmhvmOWtjAqr16xap9t8B70xkAeUyfD5VUr8mF7ubifPnW3Xu7N89gQjL/ZLN8bjnESNkqwxxexf8sFm1t0ejw8mnfn4qoNzvpEbAFbX7TGSWrGCD8Vh4MGo3Wf72sa3c34Ysp9nHVXH6t3TLFddwjHBiEWy+cKsbztrUJMUiEelb7xMP97gJXT5aA1MOpp9rQU2r/+0SK2pSde9OyfnKgzeOzQBgvd1TsA9JYUZpZ6bd0+lOuo+3Q1hlSi0Byj8P8pASUFcuHkuMAaGOf0TcgF0mcsck6D3eYHfxRjmbjQuPJVTipl07ucvAcXo6DM/zDubigCOoU2mO+zSM99kCfffUpH2s9fYBQG4f35Y7jnRMy7nFkgEMarbITInkVx6c2Y0EDpVjixQ0SXsaTiD6rRIzoXRjcbpD7uGQU4Ps1VjL2r7qOf0WVRoTUAKcfrOLvnHAIdw2qt37aYK8d6OBV09R79NPfY8MGSlKEgCZHwd0kb93A8mKmAsXrNo3B1N4KVs9+5MFqNiXhT4GDViVdGDzlQKfLJhfojW04ipZ8fxo1lG3es8Uu+v7CYiuyhZKLxHm+61l/H7KnfYc+d3n/+8msu+Lx1DFkQ+XQDE32Kdvgd6MUhKhYuH/NYOHcbuZvnAiKLCO7c9aJM5x7vLYcnixfnfmyz5IgHLlbha99zXZ4uzLzbx52++I4tiz/iZuFh/AnK991mj77Ry5s2fJE01+7SdF5OIGDwHnvvduezH1jc7IfCdWFejF1oO0c3DmKRD3fcEwPY8Q00fq994zaVDi+cworXR7A4z2NOgGds4NqU66sAM8a+pYYRH5sNCyxlVCwYU+G4merKcWOdfWtsVw+/8D57dNNINEffzoNRW5qLgS4tclOwyxc87cM33YmtajgFBRN00pz/H5tT7PgmjfJxh7beNHBTpm03QiU4Sdl6XxfWN64Ziy5yyTWL8ze/96KVPKE3GNEqR16Dw5/PG+BbOnj1fpnxYwyZR+gTg5+vgHOOK17rr8MK6RUvjm45qD94xU/mFXe8ObZe5APgnqbuY//p4zhD91PmLxeZ+CYC3qZBHMxv7FnYA06MXrz9woeWcuEB7HseJqOZkx31jgU8t4CxRKWbjcfa5KchlHecOD4T1oZXc4DS0VEaSESDw/G+5VYVo6zYCgDpFI2nv6iMNwUk6hsVsrG2kleeOvb/hcRqqNH+E7mxWOALvk4WWNR2GtDqIy+JEt/JTqLos001f61XD1xHzz42FByoeDlHjEm67B3O9d8hnY4qRImE268NVsVYboXoQMqB7qFw4lpKGnfjQA4cEocEutbZBNPZFEnqQgzw6iyHkwtUY0q/9qnpB1xfTERxgbA6zVvla30mAnjwGDyQHaGRHV/OibY2VyWMZbHXg1jIYtOpQ0/bqlKtl2xTBhstysZMfO2r3HYVakc9OtjJyRqN8Rtw4wQ/xThT717B2Nk7rpILXtjwMP5nZFB65BOdq29wVbn81WSwwKQLXGyzJ9bm3w4IV2f0HvvHvfaoXf47Pxa7MGmdeQDs5hLoU8gNeHCJ8IHT9NFdfFGO6Yldw/EpjtmrHibrQ0mt+uJWQyQDcWI62ONy80B+lk/tsLyXKydIde92GitcGR51Hs3dD5sTMy8mFhWmnp0mI8tOXsafPmNGtbGxLxdkKQ1C6c41kbCP7f7z79yIviTHbJAe8FCBd4Sbl82huGzUYYvltWucFQ3EZKAycA1nTtj0sHGKM0zWB/w3jviqWBYL6H5YOEdPfeJsHB2SGjUu6sUbizRI5cqtKrh7hcNwak0jYxpj+8G+cQezcVAbP4aRzOKIFzf2+SttGjRXTjsGdTRKnCj3jpRd8ho1bO/BDJbjk/opx1/05bOx4mtHHQ49Fsqt2FVPtPiZjlqQn54syRqonLBxrvYlmHvO1ns06czXlXUhn33ucrD4gQsnXPwRG3fqshHnY07GqLO4oHA3vYt2FjR4hA7zDM6to9+CHFlswWWTLhbdnGxSV9OYRiVauMIu/xZTinUW5Uj2wgdwsVVN+dabP61nXMjVzhHkeFPmNs26USeg1SCmrR99vLWfbeffGI+O3ZDHtkq1CR7jh8jtEle1uvW3PqKFeDiwIy8U/FqQtWZFPqP/GG/1on5ipJ/iPjb4wdQT7VS4mzsr3syjGUMUjC227BlGcIDKH3GBx9shXv/ww5Mf8ng63/n9IQsL+zHPAC+3XQzse7GZG6Cw6KbGXUMW+X/513958up7ngL58uSnP//85B//9Z9ZpDPvQ+BWmKXw2QUEr8df8yFcTqq5k8y853MZeKSXgI0785G75y7Q42M59mJRLxLhZvN3FoAIQ5R4/EtszSPvM87d0sTNJ7hjSTyL2/mMrcba+l7yOCCHOUA85jxOXJxHL1xrJ4suymKPP2A4HvfYlpReBcSR9j6aHGU+FHJzTyzPOCYLG92U1MFERDnzTZkMRycCy8jUHdHs0OA1Bp6UxWTPUUgp/lUHzVY28IDcttmTF/KN0As/gJAH9mdDOw0mBdMkVc8RmbfY5q+caqdPOKbLnGI99VbSKAtUUlu7NCTSXvqwo+Df19Zc0ORrAN++eesdaDvjCnd83duWtmMMDRbPHmv5PJAsnD9zcYoLo4nd+Z0+ecbIt+5cMLGd2ErUmPCxY+C8zlztBwfy4YFZmOePBTc6XrDirnkusvk4ft6mwVe+feJtKyk733uBiRg4RpD3j+OUz1txfOFFSARHRuA95yTK4DhlVAnfYj92AXa8kaa5ejUly9Wpvl6qr64jK141Z56IK7VYRwb5lY0d84U+Svup4Yt9Cl1TFwMZXJHnr5fGR1jw1UaDMmRi1AStFHmdY3FpVw5W5e1BU+QNAnEEs0ulem2jXd4nqbjVlgpFtNmOhBEWp1iVpr52cKKesrGYlD2hoWP5UU8hxrK0efkrjDjo2BzVy2byMz43RpGkOLki2uXFScsNG93FOxMgsmvQG8vqoH0GWh/pkRfSm791IpnZRHFP4DwROFSKqZayIXizPZJgkNu2dTxm4zuiPb8lH8S0Jx2LD+1aFscwkDm2ANAYrhilDtaOaTEnL/RNae3KD/mgBCk/kx/1G8OYyXFUFR276DbWIAM+RPUjJ9Sng/8wU1diLJg0xp2XB2T6245F2tiBoc34PjHfsO86d1/HfrCIWvxgNbfD8DYHzatea33G4ha7OAN1xgKqUe6cpQr/VaJzS6UqAx6Vu9Y1lwCrTftveSNX2J0Xw8WMTOUdsdgc3pHhL8UXwwAcjsoBbD9bXSA/9kh3/GV/xUp+x3ZciK3F2FPfIiyNiePMqVjxS1neCIiuXDFpu3K2tDWg0/o1R+xgI4L+ql3udOhvnNqItwAurjyYHyn8oxTDua3IzeqiZR4WLm37BKQ2OLecXCMHxyaR7WjWfuQ4q0Z11y/yy7qtem4dG7FT2dzQ41ylEmfbT7Pey7Yn1lFAZ+KHG/rlmZwbNCoCdS/O4E6dnTYz7ooLdkOLlH4KeWJHHWj5777+ldl/UxgGzpoxQrsRFds7KMGDe+PqooLFyne5E4Mz5Pxxks8nSHMy9uHl+3ncPe+XzZ3ynFZ5wqieXIMf/h9y5wTe+33i5J331xKaJ3dgs5Agpyn91N/5ACYWZCiGg/OdPQsZF+mJIidz8OYCSH6j5684jsW0qRNttMwfG+uTCQ2yIS/AUFbfXEEhP9bFTN0TxUuXgLCh8Lqif7ivVGD81/f6UmWdskegvUjGSG1LVYdLhPDipBh/7iMTkz6TgiU82tYv8vyenI7Bpd8F4TlGoi+14DhOhRPTRXbkPq2AD6VgsxiggXLnzi520pUcdYHMYu+UwWVR8X0W6VzU+ed8QBqxZY1hTHzFFRcBmI88kM7U+ZjHu/WV1yTiYJ7+9ss/nrzMWyx++vOfskj//smPmXcf8vQHn4rOHMKij7eXAe2n8UMsfF5cL9xHxsI8XF7m7R4uzuvp5Jk7gzy+y51Vjg1i4mKFySB34UcGyR35gR++NlcqpEW+XZSF296RNxaPu16coN0FcnECQyWbIDInx4c6elHjYcNw13d9wuo+F8ox/KMXRuaZ+U6M+HrHkw3xQ/6xdQw3IG1KB65bOt+JG0VwOQ5aDpfp0w6cJYpC2rPTCBT05D09i22Woc//qxjteefaA0vZ15aLZxAyr8yH/FJLnIeHPUJGFoDoog85QpWTrdRs3PmlgxLFcz6rEngwo9wROhfe52sA3/7+xkVudYSQU7km0JRMPWWmHB/8ZHy4ww1/LrBcd9FzUUmjjF3mGnobgOMywZz8CoqPvnUDTOY5+87FXkyIhj74HnYukDGHuXvOsepxEZw+XcICP+9Vj/3zF7wlqscL/jj2mgeCopqcICOljOctRyjws+M+Bu6QY0ef4zdwQCoPrnXaW9cP+ghRQ6MNcKp/+aNHP1VWtTKqtdNmAMWr2JDQOvZYrOPgPadxBmCpqnCRwv3dqCTbv1oSWKJxXoLbC3NK2tO3pEpsw9hkzB4QuJggARDkd7zRL2crhyPxeNKNO+yN54Y55msNxJ7cc9CA1iRSy1/wzJO+OjAPBzUuABs/G80ZV+Q2iHbweBGVB5ZDKHpVS1s19lRmhyoFpfHV5jU+4JtTVTq2YGF6yY9H5WKMBtg9ADSgKz3FaQ4qKQeolMvBT/fK9GpAKxMMja2cvCLZYi+5UA9pA6+PbM9CDKRt10fHOybx61hungqha8YaaPei15dUVw+I/LlVlo0Kg2sfvdWaZnYDkN2ZB6uD6nSjb5P2vPhfSER1y/mxG3ksr/kYAHglTqCKMU7cZZPfUm/vt/+oDjw5j6K65E3csRWGPLWYZ6oR3LlsuskLjNqnWpQDci9ghkzny/g9/fgK+DgUJ3yO3+iBtnxomDPsES6Rfa1AnrJcq6si0vwtEpzTsiubFWOMB/qs22otyr7erM9ViKbVad+5V7S+aI3TG8bFI71pjJY+QW4MQ6aerrE7OLHytaYe0a7dzKHJ//+UF7MiTryNc/Vo5PfUoyjXYI8a0bSk49RvMqr7OrGx2Q30HJ+CGmcNH5CC2+wGXXLRGUcnN8jR273sikV1Yx6JustVbBoEZNkcVKOYdYnKGYt0L/3lAS8pZsMJFIXXWBc5qa8Lc7j9MVKuu9XQdNPSPViDz1511cKIk0wdUofDpVCOO4e633zojZM1jFI4IeOPr87iZJyFCotqTqhefugn9XLSx11OMHi08dn4XQwWQpyo8adOFknczSnhnJDNI8PklTudz/Jp0/jh5I9EcEd149nHk7OqciHjgk+ivJRGmTxPe8cJR4aTjjNW0WvMuMCCHt25VW90gFM3r9X4q2Z0aduJXfNVwQhNdHXcTk7bO2NMI50HM015IEuFcSOOO7p1O6PDCWv6KftUAgvZe9mWOOmTt2a1M093g1t9fasZP5PdwxdV+jrXWjee4SC15Zo5mangPILz8Zu6C73soyEI7R//9NOTf/n4r57Y//7P3zJn+ngsS8J8YX3yE/1g8uFnLjYmJhYCFOYMc+7Xv/+930bww+sn3//0Qzj8jV6/vozXRwPQItyyZ7nF/ATlS+by8xedi69//N7vc2Zu3gsLahYkzE36iNkPbjMu4kSWPf/ro+tiKADmNDyaY+ZjF3vg+V7d4FEnHu2Dcy5eNenK0QHM+Z+89XHhLjKJU/yMwV6QWO6dF9d2XyKcbeG7x1wgZp6lktcBLkbkpqjH5X6Tw4vEZlxRaTxU8B7/RnrxCPAt+rI5OurG7jZ/bupQGbTuEZCK+lms7j1micOf6oQcFYtV7UdQsfypEoe6ONi2e8YfxkHGPuPy9Uve0qFSN5tDFMacDpSv2CqZLdZaoZK51AX1+3wYHE8s7HvOUQav6Sky4+TMZRpEVI9cZMpcyHxAmdfSl5lPzOv94xzZvDOfU3ehnrl25b5czQN+g8WFMxbkvtc8exfnkWPDPOTT5feRdi7M+jofW96aUVvmJwt7Fue90Muc5gPi9o464+UxHruT1OATXCOuP4NVxcyr69MAkVUPgNYxV7j5j2B1xlpd8kDZYwalEal/wVzjCF9+m6fJaQQ7p4s4/QtWbwhPvsXgf8ro9A46wDJCvqQXsiiHLAgpEJIM+s6I0QdowMW6OTt29QaIOMj1TyXFyQFchH+QK07n+Bw1pYj0ffynnTKHUXFp50V949Fe/Xoq3i1hk7ydFsY9xOQpPl7K9c6nuQwWucKHnOMndV+o2Q9WEbo9J2/pB0999jUtFu2U7W/rcdtxQQc/LctZbiYscvwUqGMZZW0xkXat73iH03BEo3FijCHlVOpDSTXbk63NxtkFsw7VL6JAUasdrWpXvu3CNE77h7d5HxsxCNRxWPvJTQA2J/c93nbsyUXLxUVaKx5m9CLnnx0V80L1Zq9OBD1R2g48UW+7J17DC/stN/doboyHJ7iju8jy6CCnr34uXo2RtrGv9ehjezjhb/4Wc4+lzo8La72oB6c9lgZO/eEp/owLPFqy3yqC8DkxBgOuWy6b6tFTN9W5uLTjujhTBA8FVaOZgVt7KoutTI4q1pDtAw/8ToCjsTyRru4i6Bf54G6OFLFJwf/mtpJsA2ZM5qRS9QZYrtjSf4KTwbBDPmiLQTuG4qR6+UTYeUy/Ezt71Q9+7QZRHBXGG/IrL+tIsKoBPIQ2DnoBGu2bPWDhE9+Uh/kfZWOO/IpdLST1gdnYjnMUpq/5OtircHCXzZh0Z660Sfc1hnGES/8HWm3fLKhAshAListr80A7heZUzUHHZ2xUSP8quN9G5Jy4c4IWBM/hA9ZxZRFCboPjfI8NZr5oNcbOG7CbE98DG3sX6cHcBTQnVzzK/iILFB5hZGEBFJzYh0Q2LPBdQmXBlK8IygIdPb/+KSdrL752Ic7XOPEp1s84eXvdDxyibUoEAy53Tlm4xB65cWTf+XXlyygmMcQihnzglZiCVxtaAw5ddYg5dWJHhu60ESgbLHYt15gsFxXpjL0+BRlBxTSiNojp37mnl/trEYqQG//E3XZsdpFJ/5QzD4N5zj/Sx3zUHy5p028d35WxveeEk+V7W7b7mgAG/SZJQze7KF27+uhcciHq1OTud2Rcq6lCbMspqwvnwU8//yxnFp0s0j9kZahq/HFCL354My9Dg9+ARZo/l6hR5m7vL//99yd/e/FvLtR/+vlPHhs8Rs6npJMDZukW8uU8z9xkUc6d99c//uB72VmkmLMoky5i+Zg7hZ9zIWCPjY2d9uYbzs0R+TaD0Jy6rHXPRRaOi75Xlw+cI7s8DZBFTJ4IOD6IF//5UyeYoLBIFy12rUSHgx89+vKH3zwaI59ysVt9OIKnjuLYxsaCXTIlXI6/9+/ezsKKRXsuaGRFAb+OicGVQsydoxWlv9yGabHPdmdMBboc92MmH47fy88ao1gnxmGsIigmKOT4LyQ8kNV+c9FxIh30b19fR1cHafNazNWrNhRraKxw8q+96/2SzfEjdxbnjH8/rf1tFufURQNzyLYK7o7nBKFkPUQWRcaEwoe4vci4sZD2SZtgcYGL8yEv8jB2eW1d/c0htsj45gIW5Hz9pu83F5fPIuiFJF7TP+RbEnivORfGwGQ+7oKcBXo/qb0LdNr08b/kPI3BfN842VOMeWLPRQeKKuzNTGNPGM2TOUnm5/Xzrm99tDoTrtlAH2Mi2uTZuRDpciqjaJBatbEZv2OzHcX/hlPV18JWMUcUDPwT1/M6pVWVJaHCZEAnkEn7kI3JQ30Ad/KkWcgC0VS/ASEsASu70V+nMy/Oi3+6TyUoE0RFaSu6Et3EBMNQi3nFlFopmEcwqk8NhrcSvUsyRmgfe3rrV4zJEZ4p9Z/K5LI8i1nL2J5ZVUl1NpZyx558MGgHE1icTN6o4lWNVDpxr7387vYbBDa3fJ85MWjsapt9HeCqJb75Z1Zx2EhoeaBPz6qmk/aJJXW7g4Ed9YnlcFcO/uQBlXUinADaHR6D/wff0MDlcGqcOLiV9Nfl+mu/1DCWX/W/HQ80yy1s1wc29zLxLc5iIDY36oJSIvVrZyTL6fJTdjsnOj+A0C6d/BNrcgWezIGdznCkm0LzzEOFCJorT+6q1vgip2yM3+7pQ6V8y82I4u/aT/+NR2GvGCF18jNMl7Fx4WhiqO3mgXhqi8rWHW9Nxoe+0UghJexLXJ5liLAY+DoJaySKeK3aYq7EuLhoD/CqTR4WzJjwP7k4fDFAd+QAgLplcyPuEd/8jt2Og/6UBUeOm80iwl2xzeYPj5TlOM2R2WGdjZoBdj7UTLuyBqEk73onnuFqjINRiMZTHifI49OKwYwoKuP6jDtuq5IexlANtFL3t3vESicPGqVL/ic35Ki2QHVOYX/L3dpHr+/tS782cKxt7aBAH3uqyVD+F8gV+cSlxmkzH9C9nTRjDywFjOxs1lBc/JnryBSr3Hp1a4ebBfBCMb6GB47BcQGQE7N9zJ07M/1Aq36YFXXumng3L2D7/mC4sfDgpK1z5DsXPDwyvB/ixaPILNKfv5pPBM5C3VwRF9yJmxyFJieMfcTZCC7e0cOGiKYHw0ZMLPxOc9JwbDd2dC6V+Ms5occb9nCJYTN6aS2WfGnos/rVHtsaq74Ye8zAK1qa7p0gFbNRziYFaG31sUbpqIvmjKZ5qJy7aZuTw3HwTrAhAC5FH9inUpzW7czGxbH+K9GuRljj3A7+r6zfs083uC706E89J6PJcy/86DP15/lT9rx3sBsfc4j30gY+LqJRP9lhh9/6QZ5aZMzJ33/71Xn213/7Wx5Vf/nkT3/92b7//j//28UEp/0bJ3P6VR6vf/1DF+Z+XWA+aA7sejNCF2gspPkjXO4KrgZY5jmUvC2fnitnCDeH9Ys9d03hyzznLSM8jaIei/NZzIhLXpaL+yyC8n/Iu/ZaXHN/F16eHwXbNjqx4xi1fYKCc/N4RBPRldP05yJCRsFHl9/k0WsXb/HfmOEWHTYpjonuGBcKeqClLz9oddhGXw36WppDWh1XpXZmk1/7D4jox+f6xqZxTSVphX+YZGgy8rFfXfCom8u6LRnpta86sY9uh0hCwHThOxj4bUmP9jc/CIaUr4nzuohv/ngs/F3unvd1uLlbjti1zh4P2NRFKbPw7vzCBS9gmTIuhnl9xR8f8ukiPX08f8JCWV+sBdLPYhwfjK1/affJqT7avnniQ90+8v7yLMh5igTeHG8ULqr5PvXsmb++zjuPrzvxrD26OGdezMUdrRkd8mWjG+I+M6Mi8zC5XU3nVXAtARgkx6uA6fM3m8WnOs7Q/9bPYu+YbbbFji0Fe6vZdxyQTmd29/87csTP+FzN2qGc1xOEMsyLZEu6Z9LozDo920/tIs8gbYA6JIFDEhTCmroAACAASURBVL+FwuVjKVqCQYESldoN9iE9/e6yiXwDqij6zMSU0bRyT8TGI+/BNam3FDYIEMAq0k5AsafLnnB2v6pwz8/iP9ipqUKxU60tFtRt4eKUk5NIjGNzlHb9oIpdMciJvuUwEZj4R/0HXunfPIq2+Sa/oOvzxq3nRTnOI0PBEt3xrVBKyNa+k/VSH2xshl/B9NiQFrosDsfNEwjMEIp+Rv/Ow7r8q4T2xlq/9f9oc2UUnS5KE9CmICB6Nd463S5a2NQH/DoazLvlsv4hrZ1g1IhowXFHdOVX3buXclBSUzxXvyQIVBnhN756aPdgRWf5LO+jG3M4aEV9YygqMC0bx60f150fRrSK7o1parIoQdzw2yJ3quu/uTq2sekCeHONamVgkAn4CjigIh3cdMn7jt86Xne8rF+sTg5GpSnGFzw5QOv85HvtN49tZ2uCKkVWs/pHutx2bE4WD//Gp97EJ8qeACf2tb3jQbPhpCJdN4rVa+dsySNq44BGiifZibXs02feo0f83+CPCVbagrZ+dj4Bv2aOWTTx6PA5RtMelOVTm+Kt/eYVgJ0rYk3ewMTbwbAdCf/zBqQ69Yn2sS8hRJLr63HqseUkcy3UR2UkdXGLm74IOwXgcpU7L8cvnZw4q5ONdmymIL/n7ICpAq+Lx9bOFELZuFE+oymvxjJ+xuDwnbZ+o8JJ7dd8OJF3PrIYf5a72i5qUmdxThwsMgbNvXcF0+cj6iHJyZh34bmrw6ds+0nb/URgFjrcmScYWQLECSwLmGDkn/78kWNK8uX8bHjEgtwc2t+Ni5Rpm+HgGyMnpamQO7HG0nhRyC881Lkh332g2/HDKz2CzR6AtGfXPkYe3avY/oPOxKHqdAI1pivWd6CcO9MJp8Milc2lscR344uReCxKVhu6LFnbV5RZtER08RRUNTfMLQvyK6ecotGzC0g5IwxPFgtf8oFQ+Yg175g7PVlNCB3PGZs+Ats58f2PPz757R9/9yvYWKhvTLg1Hj3RQBKmzsNczMm8+cd//Vfwnj756//625OXeSvFn//2Vxcm//Hv/55Fdu6AZ/HyOnfLf/jTn1ycs5DnA+FYvIgWvnJPA3gwsWNBQu542oPUw0k9Yticyud/boPqayz44WtOkhf440j/zNFgLRfkHkOR4dtFDmNWAnNe3AWWC0ADuPm3PXMg9t4NzjHEocXY+b9tbNgZE695UCKW7MFlYeb70ZMj51t4+tg7EKqxpTQrxmpLITDnvJI6RdlYE49tYORG/2hGZj1NfPf4FOLa0Efu8qMOryOal9di7TiJMVgEyg+52JgDFmylmbd9KkhnwQTW4y976vUwfuJUNIAkkLn/iQsx4ZM/colRn6Do3XPV5IDJ8MfZ1DHAj6/pFcvTu+KxYy7JVc55vc1TE8wf5rRPMHnnOxdT88PnMHzHh/3lx4VyfLAwNwfZ+1kheUTCHOJLzokhx0A/zLBvYSIOdJiPLspzsYv3mPcD5XifOQv9zJVg+C0bwUY/v6CyaSFNW2dP/12gvvRMZ+1roKrJq83+b6AXCE3tL4gxp8PWAtmefGiIYPWnGpG2WDIm6FHQW/9qRKY5Y1K9ziDqWKWTvVXqmOeiJRsKNAClyT+xGlUJmzVUDo6vopHXvPqRr3OwtNO0QQIz6vrSWXytzIHHtzxu+1UY++KyTQf6mQingBdxJcTRUohuwccUhpf36Km8fWkD9D8V5eTqwj95AQT5xGAzx8i+bi5cOeB9MOIKb1JYfCWRpY1IGwHGjhxrhyV/F8ad26De+JYj+sujOjrRnw5RsMQPL3DyuGKDq3Hf9rA4PE+e4TulCmIhMd5sD1/yhnzyt3siU44FRuGytvTBQwzmAslSpXIR5RL52qVae6wHkv3oVTY92oDS2MEGh16szUEbYm7P8kDROHJCInysila/wohEDbxpLGfaehknJz7Eo4/KynGIz/Gy+6rAIZLRXRv7ssG3cWLdBl3AnW2P/clecMAfh4G72ut3NKMzOURbPUULro9iHVEUWqB76Kxtuhbn+EofXO8+m8ZIG0QBTw4AjjbdBzfty1n1xQz/1SmofSdfaaX75rsO2arO68DoeOCONTIInBhS0087TjyiFVKLa9MxLbfmuJxATV9eq5cje8rlC27rLw7HyTkOjDdyuBwC6BWpehee4Dd82phi7NgGw33awMljfBweaKMHL+2wb5HCNtgLcvFZUVWWdPfi5Ris58Hf+Ea6FovD6+uw7JiE8ZkD1CVQbwwyfZSO33U3oHEk2jhwsTKOOOH2NTxtRfALxt59aoCcEAYXORmL4vrRmYKxV1ArqmIuJ9roitVO2QpNbfrQGJtLcsnSnTOrLrZklBMsOXMyGBhODime8LMHK39932NP3ujv4jyPSsaehdC+l9H3InKyv/9zPHHlZLaL+z2Z/Zq78eC29BjA/8Z8Yo2CdXXTm/2krPbQw5BycrljiRzE6jBfqd3bpxfc6T1pHn7qrH/t67G28dWJFvvW1wN+Dqb5qAOtozTwqJ2irXGkFuNyTve9bjMCOEcXHPK9vgQDaAVrK7i96jcVq4j+rU7TRGSBiY/80BYyaoy375nHJAT61og8cfE1C/F8ZZ+L+SjzYXCosEDgIs7rLNC/z6e78x3pb3JX/O3vv7tILhdGpxcSdg5zh29oODf//h//mUXCUxfnPL6+i5Bfs+gH/8cszr//6cf6i0/KYm08LEq4UOTbNjI/eX9tl2pEZziTisRLzEsgfd/WF5sYuaNJTlz45q48bx2pPMeNnyLPgi65S07wBJYLnsSzbQcTDvMTsOjRn4Vgjls+HfvuM6pq7/EGEFjMCS/YTAMejl7a3hRzvvS4fpfHmn30meOWWJ/Di9ctOMKFEkap0A+3Eels+egqHeqgPAW/6iyWOMVdG/rVC/ZdP40oDhb1Kehrk9cfsrPe5AsWC8fookMeGBfmCm0Le1/Mb9ipIgbDPIw9An7sTD+vhY5zBpNFNPnkAmYUMpczxqlrP77wcPdNGyz2cnRDY3Ic6fbVbVrRYd5kiLJYzhzLxai3n996THjYgsdfuPB6tMcFT0r5ZEhs5TC+maM82s7bmvwQOF6n45WFOXOyi/Pa8l5z8slx8jRPw4DTP4jnT/5GlWoa4XHmAMlUYXYnsLRTtKoJaZ64nQGtY14HxkfLonLBVIlQLHynLo9q2hoIteh37qgVKw3Hd3B3joietvjBpWjrfozWOLJiglMOOYxu6kNMUI3Su87u4OhNcNVlMqS2/mBBkVX2g3sEuqxy7Wu6QaFvOXbtx6cTqZ3VYRt1/Y9k0qHM+uCVc/VH9ew2HgSqD3ftU9/E1aCdpMBiLlIbHut/fR+/UaG+ca58B2M5bE7ALlYk+pqeycNyWhrVZ7t21LBh2wG3oQzkSE9uVCJQSK6ZdjTQXn7o1CfbchI/C4GN795fBqNpR/GOk6AovvsdH8sP3gfbBQeS2m2Emm88s0dHhkPC+rDHWt4YpvRCyMRqT/GP3tjdOdUw2wAXZfdpIajD5pl2SV57ACJzLO1DQIkhF8EGBJ73Qi7obXd7bStqXGAgM0Z0U9QhN/j0n8vI8U3RDRb4rz6eirG46Kk4JvEj9+6NpZ7s7+Zmmz69Sa449X75qQYEUkMlCnJqtdvIHLORrc2dS7os9z7HD+iymFjKAH+UHeORVpdG7IaOe3TPvERLgzIFf/NGvkxRJOqzx3h0AOOOrJzWqf3drM96v3WIQu+U2HoBhaZ1GBR395rQzXEkr8lE6vVTeSEagx0RHB4Gk9bOg7RF2TbGU5bdCSsV1NBfTu55/YiNPvJPnsrqLNaOLQBHDxt1U2mSMYwMjRZ1U71121+88Zn+y0KIIznyJSjsjJf1+jtzISfExz82KZtrTmBO351jnBgV5znY5G/vZLQ9QHQRSITixG7jUm/bixfNlqB7zMOtJ4B1fx+Haha/nAFnUVxZMIJLotjhl3hy9hX5nNCOHD36OZHj77kGsQsHPhTOE7ScxHNiv3UWCRhhJ1dAou/7cXNSGyC5wKd3h4YvgYNfVrEHh9/maHN/XvPwYSDpn5MKdB8xBi3iyutL4Agqzl6ywzmYyE2S8rFJHd97oR5fkQysxC+8W8+Ow/5vEu0PfHBXDLboYmcdg31dsZ4NusuN/ZbIYX/vUhVma4NumqbsyOhfEPDW8wgHcGMp1+oxd8BiYfosez/sLU/HYslTFWuz+z5lkQ+7yucTsEh+//YvLtD7Cdf5DITczeW94Mw3iH7Jne1nz/op0zB8nu9qZqHvo7j5ikDeUvHqx3wqe+YhF4ne5T3Vz3LHD38w3PKQ32Bz1xz/5IW56DHgR8olljzlscbEsdzZizMpWjk+Wif37eQiF39+M0KeEnj69Hli4kIDn1wfn/H9InFw3PjoO3nMD/4cK3TyhIt3UqPD/xZS4nGMjgVf5Kkm2foL9/IcvmooDA6H4Cze8DHGHJ/cRYfLd0+/Nw5igR9aeFIXGGo2ItwO9inFq07jcUZujzqaiDPiyZmdBzitwZxdmloaA+PVBXF8JTF8K4R62dzfZlTOzQPxoCtA/FxjGa3LCQA675aqoIqx7+K8i/J9bfQ93Njxm7+ahHF47pjtHOwcUdVjnbhxz+ni2ra37Z5H9jUBvLzaxg2Pm788n7buPOH/L7nwqwoDFhKM51445RjRd5zAmzg+5SsA2fNaHGgfi8eGi6w+BZXXdu6W9yJSL96Aw7yAI3x9AWA/hdjNQ3bmfPuQK9vo2lbGBgIBrM0aVWfnoK3jM7kdwcNcE4Z550xtbpdQ9DuP2K+PGMAtTfuGQ006T6a7aug5ruWK4fKQjigoJf9FxTztyKpYtUVbQsDwsyTQpX5kgdlJxL6oxbwnzRf32NYeX6XfwadNmd52td3RPL1Wslk/tBdDTglQHox4bPsPkjq/bjqYtMRuPPv+GLEAjeqdPwLjRj6TgmSi11Js6ogcyPQb9/ipbg3kv1zVX8vZD399KIodeCAHrzGPT/nUrr47PkjKZHzilAPSfW0vPHTHWt8026YHo45vsdDd/HDS/xiPDo4MWHN/s9EeDfqMRy80Dy6S+owev/GzOPTVy00f3vlHou7hO1rsKPfciXDLR9p6QGd+spMDpoNkD7yU4TPl5KYBRFBedmZjho5vDbZrgDWQX5Frf/xIRCB1RLxxIy4JDh/bumksOJMjNsCgpw386/GhlkYXfTPOnmhig9n4Ih6dLh5eoIFx9eoHMwynD50bT/Q7rpqpB86RRbf5VYj1VADEEe2atUbj1idPNGqXntTq0/0tDmmqhlb0gNHO5pW3Nh841mc6YgN3uWyewdKmHBp/fYyB/UjQoL9jXyt1jgZAm5P0C7NYaT/4nDjtnrr9YIzp1C6fi4UX8FRws1U1mBMRrDZ99g93Y0xnc1HLk5djVez2VhfJtq2NA3bLEV5bN+8YReGMFQBjV2ln07EZff7Bu2gbzohbilQrWRw4Y2Z+pag1dXUv4hcX+mN0fBeg9vrtWPIhQTGaE5lidw7cQ4kX5iv/7ANrPTZDoRylVn7aZ5xyeiUHFDnZho/OykI8+FHcc1Ka4qJn5D2vH9uca6HXu23E1jYIeOYET9/ICWow9kQN/t6twiAF/l1gZc/JH3+cOMIjf+TGCwxVV99F9oayo4NzPQ4T+vn/SIkTu7MvndFpb/rsndZtFzXzjCiG9//p8N68iQ92fsDasUFOOfjaKHKz+kei/nBGmPa3zMytXfREdziyCEHi0gOINNDlzvSijFgbXzuxjap+TExa7BG2I/Cxx/Beto1OExr9RJP68qv9GKFvf/WfMsVwQ3wsTrOw/vwpJ6hZLCMDZ8eOx3BfvuA7zb/6mPoP+fo0vs7pYxbcLBQpfBAhhDnnc4GTBYGPqmfxwNzqY+v9NHIW/S/z6e7MQeak39sMdhYwxMLiwpgiCzHnpPMyOA3VxEw9QWRS7Diypzgv6CIOZF2fiGuO5Mq8bqzYNBcdKTh7nOdr5HzUuI5dpHNXUlxksT92sUlEOVR7/HZRNMeW4+TG47bHGwSrC7/iRARfJ3pfZ+RLLlKoO67Z8SnjfE83/OTDIixyXxfQzQ/RRNS9MaS12AKpKOZeONMG3f0fE9fHrRhXvmNdPrjO/CIGHEpXPyiUgZDMj9EhV5l64VsINHGEdk3q2Ph53ZxCjchEtUErJbjsuRDAHCTHvq5HRr0L3H5eh29VSL5qHqT+ApL/AcGbYYmgfLM3dD0rpCslPtGVzO6Zpw5o9/+XrzfbkiQ5kiwjIvdMAI050///a336baYwBaCQyD0isuleYhZRi6wz4u6qIrwQE7OoqauY2hLHfWJn34/OS9SdM3Rx43Gwx/2en/e84eMwd/k5F+PDKyXgwt4757lb3jvld2FOPJ/ESi5Q20372aZW1tXCjYH1i04jZP//7Tz5ynw+miMLO8IGPRZl1PhMgMfDmpJYZM7o9JcPYRTBvRbx2uOAgPgRrMeBYXV6jVG72RJOvO59UtvioB+wKSEWynSIYwuI7DDD6ZJArCAI6UOLsbIJipqsloTjsWufbRM2TryLA8oEkFfjNvUpCharo3Jpem3sDkApJ2z45YGcH9S06mckXvqE7mzU6KjjN7HEYhPb8qrpa744EkHAy3d462EcqBUFj8Yu7p0HbCIzv/RadL3ugTG1gVP0K4+TLEojvhPf0J4IQX42IynYGjMgEzWHw0A9xg2EcXM+50mG9QaqQO7hM8Pdj6V2LzjYDm6clpt7iKmOnpa+JZKbIeqLau2u6eQGCLatnXzXVg2wYwPuHAvAKI1MyMEdl5nPCHeus1/ui3Fsg4TuRf7AO9yahBdPcorNRBdqjxt48XcgtIssMWg7J5sr9V1bc8rmcOW/GW0MjnzqoHxwa0YdY65bnIYzurLKbsXKtu6oDaz0mcAzr3GpevOJn/VTulRLeOeuoMvgyXE17CdXaex8lNNoagx/bM3jodk6IIpu5639urJdTutZ7io08vEzGM0GjxFYo6OMunk21mCrnhwTXN/4VTxzHb9KEpI+uDTg0j3zjJWq+JkvRhFog/3EQalG4+kvHDLiji12+vUMWE8hjUu8RXFf93KM8WQwePexs5wNTsSJIYsFRDlciXuPrVsfTBs32wdPcaJBtxzSVfKH8cSoT/HkM3X2w3tC4EO+uscLpFxgeYG+F5SJ0N/svXjrPHD3x+iQ14ROuvTnIpG7NYybm2YMcgGVeyu5yHqXr1FyweyVqob6DsvBTdD4gOEP/zNiz4WY2L6XsTGID677cxE6usnXxXf6XXjzctIuVp6Lc2y0g5Jor5tCXU1rTuJSjTH90cPbYTZB2/m58404tqjT0OPZY0bRY1NMzZM8GNZmLPo/J4PILw7jG2IQlBFzeQCx3JCLmz08qDN7bWaPtSABtFdgbZAwV9S4Vi9KoA+eA70+BcKfHAu5OCcv5EtB1wzGdkhkNwL12Acvxw64fKCgdzbDkU/pZ5nNAloPcP1/k+OMBQeHVBanLrC/+SrHRu/ssQgqP+6S8uFteMdnjkFGXsxn76IpxxV3+b78Nt8gENvfP+aT4vmwK/qx+Sp32XkHOncZWZRwl9+6w99crWr7sWMhErM2iWM3x0V4WCuOQ3k95Bkrct/HEovb94kH+DteoRLst3nCKkFcEPEkgl+jNeHkBakQ6GMRP2oLb+oc16h/z8sVGPNkHSmclnjFOJJ2zJMuGH35si9Zzqd5UzM+HZw9MQObPk8ahG9nrjGsARjkzp605jyS/lRReaAOL+XkNLLOp96xKfuBG9/mgJ/zGZvdgwE27ezT99jJkxPaJYfqQUCZKOaUUfZWDQF/6ndXO+1TBN5b3ldZ9NgxRmQszDkH+6qgFisLWmJmsUtsgk4cQzAuEfnN8y3HhugyWT6MI9j8isUBybm5xwUPI141wPEDn3O+DR8X84DChzvosfMvHJ2vgIP9WV6q/jYH0+/5usvPPs9blGLHAt09r5CK/fpSV/7II7+nwXuvO0+uJtOc5DkK3P2/yEFsgnEe2wUFW1U6V5XBXDT10Yeux0SNYgm4LXL3Y2nsapDrF3OwtYvevGqirLpaI2ZMWx81GRjSQTZjfs4T6OPjS9wJWoCS27GBh4DEYoQTWx/E6VVOMidGhMXDf+0mfjzTm+Ag1ZJe/PWLfvxqOxa40R0+/acXvsyg4hbKBIcf/riIk96zr1Nd8YbVtOIwOFhHH6szkXQnP4ghH/5bPzDkAGfwEMzW3sjXd+uNyRNDHsRaX8I9kNq/OTTvycOgddg6rPfhP1jGT7+p6Jg5WfQaWe+XfCJvlnROzeyHb2MyKn/nzdFkYLDVYT011Wb91psx/OJLramJ+8o/3T7zWx+yMsZwO/4tkVpwTq2hScOxzu4XA7s10cwTXCQIsf9EjwSlcenBnzZ7cNevCoYTI6btPyKmBmLoj3wCAxPZa97RTs2IQ9WpIbGNe8aNbKy9kNDmiYmNhGpMP23x6RufTpr4hEu/lt0zhkPrUb7ljC2WbAc7u0pqX84FFEezbMQDeNrkZz7RHVvJLOIaK3SA5Ymt12JPvTIUc6xlZz0RgMvOaO2ri8ez3hNhc268bmUad/fxYZ4Y2dJdfsBWxx6tm6np8Uinvmdehg/2QIMnDyEUCKVZbAxz4emlxW5zPNSQVaWTdjPutU/FAfbYjZ/nmQlQmMZfOZz58fhiD4IycAkGhrvXHJCfPMnxtlJsXki3LgNzYujTcDqr1zm++f+z8+leu/KkCBdr44K2+okZfvj+oU1M32t9rsrqg613v4mRc85Gsi5E3ZwHG/znBSJ9PyEaU96X6AVV7iy++zLTCRfqEgLgQHk5EkuqbKp7lws0u1nYf8ytUOcoF4JeoKc+LDLmOtwLwTgWL3G0ifvmz7684JvFA8HY+5f+2mZfGAUdREkdqoJ9eg4kLO9+sN/MWXj55Hxi7HXEJEcFezzhX/f673xTFwuxBowJN9i4McZOHgVhRNM9e6Qrg/tOc/NAU7/dRfBo1Tm35LCxsHgCL8wGjdo5iY/VmhAs1azZRojcuQSsyVw642Oo+af+EJmT48NrXNconKS1uBsTbixWkMMnBw5P0uRK3w9go3CdK/QF2WMoa0LbM+7vv3fhuGHFzYCasSh5l8V8F0x5C0bu/LFIp7391w9v3n/IXcXE/5iXs7MYtcEnj4EhPzJ28AouOkahZmrp37msmyapWeegduLh52KodyXBYbFPnXh5O38sgHgC4k+8D59vP5iX4/s4IZKPz3DOYoxz6750GS7ML69U+D118tzBYzWLfhY9LKSKQVQaWNmRSH558o5XM/Dd119/860L8i/zlgCUvE2ABSfnEMa8+gFbPgDMIkQKHlCC0adra37GRkhpr1IL6kfDcvtrvzLkPe+AXfu1HWexUS0P9kxrnxCKdf6PUQdqlqWl1HdBCwaoT2pwQP8hL/Nmbugvn6EQearOPLAoz7zxOQvMn3KOP97fnUWwrzqYuWeuMjGHr+cEA3eB3Md51fDq/9Ayw1XiSc78FSAk761R4nIey9NOnyUY31AAP7jloMTQ+e5bj1hos+hOZlHtXXQKwfHxWeaYxx93z2s3/eSyj5nGCoEHl+aYUGWmEr5db0gh9jOTBNai9uYVEVIgq4aHmjPegOJqy7GBX2vDvNDnl5o96IlRLpEmgMcbXXEQVXbmwoQAD2LsFk1uqRN78PlrzLGQQ4Qij264gJ076CVdRwwBAy2acV4bZG2T2IQj7CGuASMgar9FgLhy7VukTXCxpb1hwA+XLkDKq4XSimwGcPg8/SbSMHG05stn+aE8PBiAE+Nrr8GpByY0zajVtvRfMJW3NqDVsjmRbyUZA0SbLnZH98C8spgKE0trHA1O+hcXW7jUZ/EI0rrTqy+7JYBMTay2i2Dwozy2BFx8jevBts6T9+CdY6hmIIFqEPsm0KA9/lDhvIQmk8Q0r4nfcDenzVdo+UlzsLYOiT3xGotIw9eIt0+OrUD5eEGnLTW58702nOD4Jyku6Q398mQ7OO3OtvyXe7k8c3oxlisSH0/kMTyuR5TkfuSdEny2djuPPrZQ0MAaws0nY7LPiZIeKJhgo/7gI8zf6Nhh4H7kN+6Y6RHG8MQ+7clXq4OvVluMG7176wxF/bPZxSLx8a/mBh3uIuI0/DSbYTFQXm7OCcnLF8YHWYzltOc4oOREx9bR5ireaFYmFTmVrjEybvVjld8eWxt97MLptYFY7k+Nc47gBNwuEWAUH/4pkuPkqnn6Ij7kG69w2Y49+7WlYyhkcKyirpHJBzqA0CaPHfb4Ro6rzuXGRYR4j1gCaHpwqs2QK2KJVN9u8dYGfR8LSHY2l0nBB8IBmq2R8qNsrEUQP7pNHwaTpjhGG4HHa/riNmT7KQQ59CIw+PnlAo9GHOq4F4JLY2sL9E7NU8ZFuf5xcGGRwV5QuUiYizKNUpG3ueO2L89MTw69mxIumx8X/Blwkcuel8ty0c6nA9PIa/98NRfHQL4AWy7hs/ySzO2TGws003YTIH8RaVd4YnDMz+yZuCLMtcUOHyxoxEO39T5jlHDjuLEb1HQ5tRyO4E+sE1Pr3cR4D2yCMF3s00St+x2PYnMhDj/WCw/4sE9TZ/zhgxou5CNHzQ3ExfNpw3nzrXG08MK3nQoybrRRl9hAodFpxuk/h5GuLwr72cgNz9gigw5cpBUJC1abAozCIXNP6XiC5rPf+17yt28/dy6wbi6tk8DICmygzRXb1icLSFYWEbBw+Mj/Ns55mWsWKCzSeU86TwL8/O98gFYW5xyj3HE2x+DcfTkqSNcLegIhzvvQXZg83IhPQ16jbMlfaTfyjcyXCnv3kgV53oOexyNePM6//urrLM7z9W/5w452jgluj5PevFSdhaaL9GDmYRlVUPJE2rs8Vj9mz2O551nQb9sS8n3XX+fr5ngp9FeJ90X2LMjPe5N1Z2Yx+wAAIABJREFUG9/sPuStBb+/4a56sKbO90gCP6MBX1fzz8BjmHPdpWHOjNVFI2z8wQdmXxWKl/NrhNZVg3isDlj9QIs/H1zYOuVVCnnJtrwCmiVm5zu13idgceC44hzgPKfvQjtP4nAnvE8acSxHPucv9BxTvN3Cz0bgWJ7jjHnmSYxvvuJD1OZry/b/GkTh7YLfrhJql1k0n3ScZxTWR27DMTLU1jEdcXIeaH4o0bLYTowcP/mk8Mxtjvl8PRqNY4r/AT5pG06YI+txW2zP6VmUkwd2/s9Inz32bkKg9WOMCIWsVp1xWsQeKtEzV0GRa/OCv73qwMhYG+DSithtJfXXtIJsmwdYyDcG3sAzXiRcakes6R+9npjUR+eHN2M1Q46R3Vf8HZ390G/+y8c76EXw4BM6mxMk/bRX/BJYjYlkEt1PEis7D3zwPLJfkzUtVPkxRkHdtgwoKWi0ixFtGYwHA7wZPmwdopo21o0VvJ0A9rQdC66AzeJqgCBtkWdfMuWn9uFjNDwq21j7f5tMCO8EDidDuLm8GO5FJlHNM5hyZgzp/s6ovhtXzhPo+sQ/P+LpVRiBSsg4ksPX+Qti+qJnLz5u9OXf6mgghsqJMZGOHzg7txs7e5yJlcaWWMTZ2ikHOziHW4a3pvgEdzBEifIiDib+acXXasavcjStlGqxTw8KHWglGjJPtMNDrjFaQ+wTu1HqbKkikPdBgjOJYX7r1JqPfxw7n5UWLS4r3yBnXMH6NGKpvdZskaSafBhDZOTBo95PnCGqAWZNly2G9bv2j5ioxAsD8syP+7mudBwA5mBAd7ewjcF25pS5D2T0Ddzc1r2IGDSejsfyHEcFEKO5PPCxXs5xJ5I2+kyySJjnAxiX4YdHMclq7MkdTijTYFncWiKTrzZju3jI8B/UxcRTb3hN31o4Grz0K7veOF3ZMqrT4XDiNRq5EWV5PCNuUiD1XF47EPUZg2VAdJrI6SJvlDoQg7b1vH5Iq6NnK5F2p06LXtWMsnMsoUbEadEe06isJV2kcql/tstvsuN8JmzwtNk9A4ACY07AOU7n7PHJgyEX3voGm8WKL/WLuXts82cUjLARwkF1OjcOF2b5aKnJI165qGJRzaf18uFt+7JGMcdvc+Li08W3pKEOn8R0H+NgcwfcRXrOgx/zntletGUOh44XenCOzx4P+pO/3Pdiubgbm1HpDBACW4+PSgFpox7wu80KORRHB4MmbnWt23hoBCVqP/rBwwu1/NmfMDem8OQY3dqJzPhxzbQcKcniCh7j1dGDgU+KCAIv/sZD4h0T64qnxpJhUz/wFSlQXAFSIdnTKeYo3clDxUHQjk1j12+Twcpgsy/sYkc7BuM1GNeHO7JvPySn3KV8lwXjOxasLF5ZGAywvgF+YTT8t/are3JkHnhLx4ffec97cBP2s7yk3g+Oy13jn7//MQVg0dn6N4WZB4/hQZVA2FD7LMJ2cd75ig1mbPTp0GMAaXyd56h5bGMKHHcleS8vI2rAXPMY/TZfA8ddTx+ng+fjMo5x5xkA83BhluMarD1ufMKG2+hnkR4nks6d9JxMQq8LTPJgUf71t9+9+ctf/698J/w3c1e85wrzFDfM40fzSZTMS49JOIOHpnNHYloO55meFgN/tBjoc3YZkkPnVmk4Fudpgx8Bxm4MxlJIRTGjlT/8+mQIMhfp2VMr6sg5rIHSjx22nG/5od688oLPK/jt11/8YEIwyF1dFuYsxvvKh+Blsd66xCg4PMHB1/n5FgU+4TyytuzJz7k44av3CZVmwTFDUnDxMYA73CZJYwWTOdGQOcIGePZ0c2FHip9xLPHqiC/yaex5LzqvYNn/ARyj+x5zjml4WjMPmtZIWXSAF3sDDBmjsdlx9T0yEXcetj58dR35M+5fOTdOnwAwa7mAGzzSY5e9Ncng7Kco4g8FdG1Ur3HAP/LFEX3ywVKuxIEBrdtF675b8AjDiK6dddl/hiIsxvWGCb/zPeh4bRsSHJufkJCL0UaXqCWxZBugZCbVxZBg9eBEnGaZM2xh2C9VtLpoNn7KVnplZL9cu1+bBwY4ixhX48htY2++0Rz3GBJm8IXIZkQxi2EwyMU6oAPTk+LmNl7YLMBiZG+tngpsHE9OGoyMQINCdTErl5t/AUcRrdxiiR2DVphR/cU7QOvXvQesMctza/ykO7Ns3vFKm3omhLF54BocHZ3RkxcG+V1OaqfWe3DvEfHkAg+ai4K1ryRwm9fuwd/IGNXXWBltHDRtrRE45ROPnOM4UckXtAGcqtYNWRR7/G1dACknDap/cC6bB8SJG3uUydVw7MevkYpX/jKVFzXZ+hg3PouxxLemHCuiSALrxpDN1HhzRWfcObFMxJpmWzalLCc12TxPRHChwTG7jrI94/T9nTqS78StfT2MAvcIN1cykX8BakIsMCaXYmQLD3bHB06IB2N8pjoyRbN+xhlMbaBFDvmbrqbWQQHw/DSmwYan/vgKgX8dkNx+lGk7xoJ4p+kckQWJ3R8ec9hjPfObfvErXlxM4NxjKLrgPWNNKgBV7l6Lg4dusdsDUyGqU6OHyJhxQqvxnj+RLHr3+Ec2j0X56jU8p0L4oZOHx19x9jjYfBe91nglShzxc0Qt0sFPLBJJf/2Nb73qsxx1Rpn/oT3+lYhFMbQjkfk/gZaXDuYyrrrZ1qvYe2zhDwNecuqdMWwj64I4d0lyQeYcemEWhIm3uTuOjFypoxeh4uVijbsk81LF817I6Mw/eKSDK5d8Xvgh4EKS95sjpG7Ux7s1EeQuupXDd+62YJV1VmLjnDbHLBfFcqQuacsXppXIuDorwDgNQs7Ja59p33ms58xhzMDT1205Mlau4moX/2LFMK328cjvWmMDHWa4uYyhHg+E2Kx+fTwctItuHnfLk30bwXTWf0oVFSgcFWViPZjbkiFY/WKpO2CRFVfCBEUqgnJdiLXSUWZXrr3jTVTjbSwchKSuHBTFLaagAD6IpK+YmsU+ODcvVHpGll4WRLzd4+P7HKtZ4LCo+H3u3nlOkEOqwL6w3ccXyR5T5+KfO5r+5djLPiuuvKw9+zQW6V98k7d75Pj++d8/yJEN2HKaGBpPjoj6hBmx0JS7NgikFf99zGgUYX4PJ73q50KJu5kB9idz+uWXuYOd9w2zePYxPzyca/H6OAKBl2yTs6ch+nkc8snumJFDaESXRScPyDSeiGdRyQfofZOF+bd//ku+cu5PLs43lgvU4PBybV/ZEj9fWZMc1gYs8ulcyqR1I7DpZgMDdtvUMXcIWmM82zp/9OFd71FhG1/83K9YyzOwQw3rTA2K3vnsE4o5pJJXF9iclgLhOZKv+aMunLLEQBV/6snd8R///aOLdIL4IYUhY62xkRt5Dc+A8KTLVyzOXRjnOPZJmGKCYYMq/xMS12rAl8QhVUn5IQzZfvJ8LOd99BEYe7HqN94UPnw4B3/1RY6jxOfJhs+/eP/m3c8/x6+vfPL4iw38eled/xdZsFsIyJRLiWQMRfIkqBuYpvs0VUVOrQem++QFT2zg5ytcyFdvLNKC4RMK5JXhHmvWLoKEVd74WNR7j4l6YWc1j94OtiPv/Nb60LZTPidOfCrJtuGKEX7FwCCKdRi5yJMDfk5FOkBYk/TgoiCb+ZJHGbYctXRyD8FxN2BMGUqCAPnBzkaSEil+5S2IWPgd48EY7Fdy10eygJvs7gMySZZHk9oHA3va+hpS++W6BdGsG4tSv/Ufao2NFWoepDVrrvHbRdFJLR3v4CLQdhymPgjlrT66yYUQ2Jfd8CeX45cuBsYseCEe+a89dmnoaVsLB6iCsbFuPmqbDyaEEiGMgkv/db5rIxau5tG4Q+P4jdp/AtYGPDjo1j7xbu0JnnjGxUhTN5vT0ZsLBjU6sSMpY/bFNiaYOdEc7AV8xDAQm+WpbtDSFy9q8OQ8PIUa/cEQpuAnPn6cfIf74iyV9a0X8aIxRvZjtLU685JHO/YvGPFB8pw3+8sbbfrOCVabrwTC74HWfvC0bz2ztZY1LxN4Lm/kxY/EXzBhtO1pWxu0xjJf7MZ6nTBbnulrG119llfGjxxj9tKeUVHsok8Mxi/WHWy9VxUKlIKA5rs+xSJdiNYaLtjNqAHOmOEcR4BYX7zXvvpBLDfwvAi6+NjLJyL7VbVW9OVAB7thK3fmZDIfTqu+PvjRymm3Rel22Q7yyaMuZliIQdFOTtdza1xr5Fg99hn6uMnjV//wbQ+b4qx1faHR2q7d1tUczXdjBGIwtj7LB83mQefEGP9F2HPpqd+1FKI4198c3MC2PDt3ES7IBCPUWchG94433bLfxS/2+ePCmZdvnkY3vlyQ9ZyTf2O56NocudhZHC98MtY7GD7O4IUgYy7lY+3Yi1B0yDIf6LU3HvPSiy/icie9oJglUy7G0rBhU7+Nd0zR2rRLpDNdwXCgYK3WOPiQouH4MkejWH+4RNSaYz+R4uN8zGNMaXT3eIh2sEFsFT6JFb0m6tODB4LTyqUX10doPXekxfDvhW59zpMga5h9F0XpQCw+W9Mdy7KAGF1xZObPvkkN6mV/EtGyaZRJ423f9BaPeokEn7tYV4RCY6g+vEdu7SOfVGJcBTxZSPMqDb5OjYU6x5N301lhBpPjjeNY25ifPXPJKLgfc7c8qx8fK8anXjPXv/+EUy6O81LuL77+IrZfv3mfO6W8ZcMGDHFA231kLs5HsTnxuGDRRzOnxIfv6slPTTr9ITSLwebA90d/ma+GYxHNYmTvnrNI53EfuLQSYoufCxwepTzGqA0W5Bod16qIfUUOal4Sb02yje7Pf/kfvpT9u3wy/lfffO17zakFViw++3Jt7g5/9JPzedVB30Pd96i7kDMpPG4LBGlOYw6mu7IWYtKZeV9z9xxLPCZv8/z1glvdQjvKYKDNb/3Za5eOHziYPXa8guD9b7yfvAv1zEKeZ+TJKOyz0Yt929px55lF7mmPuMiw8zjNHHyVtyjwCgg+P2Dft/9pbkxan68aIK7tcgxwjBwOkopn5gLuzAn7W1sG19x8UUbM+Z8nCHgyBqd3mVuOHRrfa84inGOXY4w91zSOsSGIrXvORQYi3NKlWrEzJraasoEvteU9+bzk/z4xi69P0mXPExNbk328uEDnf1045F0uHOz6w8tzaPY34JMLBIbCw8A6ZW6ltnIgIF2hu50795GMKvsYWnDMIW+Y+gZEmOzX/nIYePimFRf3B4aavNJCg1HUPAQmKC6nOLLWC8jtzJ4CIauc7R5IpYkKLBTZ2G+0oRpFWhy3GPoLWUzVw6H/UG+MF0ywLRdgA5qYuPaAKR7R6VlY+stp/KOI/mLJR+rIdOiefnrmtr7Kim7XjV5yOGpNDBTR4MJ1+0ilWx6PgOXrAfngY21FdyNneoQOUMO1FhvvzvXWYuKLhYcEGjo4YkYkx6pqYnpTB71WufHjex5A6OBRG13Hp5wjn/iMdx7ovbSpt3NXhp0HPYiw7NMJXsep12K7L+KN8Zq/TC/BiwlelHvcmEtkzak8T5wl/YjHfAgWbLuTy4PxYb9zJBdq4JVaQc0qGNZJjCKUcnNZTHOUw/ATYpJjJ6V0INRh6znjI6ta3XQ96ZJP0WTjbDmOP3Zn/qZO5PVp/W7sOa4JWtBNYwRB3OCRiPOI/qLUY2qxMSOTEbkFv/54Ja64BG2AHhs6HCo9nlZfXUeXLlLnB9S5+Ds18Mqu+a+3U/OIb9rDrRyW09atEdC1F71O2QGWtnnBl/42LtRoe4wuxsr0k1DsxpdcRI3v8UM9/5/1ZWOb+PaZy4wXB1zrcW1ubzjFr/NQtAae+NRzOJDFpVmUKOt0hhkjCs9VYbAYR6h9YsRoa4Vo0NojGNkINNr1iwbj9bn7W937v6vGYuMTY2rK38Yu142OAfix4QIFd0S5u+MCfRfpyHNRf5uW45udge5FKRdlG7e6ywFT78JxYZiBF6o5hzObTB9ZcU53nh5hFgcOe9GH3Uu9SWt8zpycVA1MKW1j1j714SdOyHcatFE2cdDhkc31L+LaMtrHwZgeW3JwHmK8/hsTiTPq+if5N1JrO0HFBjTa6iMZIHbqKfD0x+3YKJ98AqyrNigEOKPyRP5Jk+/zf0X8mhOd6Q8p7sCCeHMcMDhS5Ann3DpM/ZFPDk1ofS7FutdO2pjQmd2JBxaK0ZXnhNUxm4mHpf0chB8+/MLIxwQcWKgfTvrVFjwxMV6cLA5sG9rYPMH1/s2vP1b3GXer853r+CDPrfaBn2MAOEDie85X4igVPg+xuA8ZY3PCzJxu7TLyeMI6MuT83Q9m+zwvPe5dXhZULPBYCPPY2rz8gKzEYLHGotI75cHwriQE0t5NDRh1MSfRxOIlze/ycvY/vfnTX/7y5uvv8p7zPDlBA88PN8sC9Neff3nz4w8/5vvOc5c18veph1+nFXzuCOez46AvLzBZhDFuFMByzOw/iyNETqT6Up5W42EQ2b5VbNQH9OU4wZW6DsIMF14uxQdvLbWy/q15Xj2RWnzga8SC1PrmyY28Goj59XxXF3GZA1/NlGORmhDE+AZqDmBQh7zUyLcJ8MSHd89zrHYOoyOx2HgczLHS46NzjEZb4mTlLh5O+jVO7Yfc7Iq34I6c+y/Cez+YDjDvooe/NZj/JcTry9t3cd79oJWwcVbSPFvj1o75Xg48qbavWOHYwM76Rs5inWuk8yRHlMWZmlNXav2xd/MJ+3k+4jyPyvxEzqu41gFcJ0tyLxtNUi7yhNdUbvpMADIM4kZaaVjyq4/6o5rHvMoj3Gu9ej+3k1OD9vwpPjYN+ORFeP+Tj32NHsRw8+DSmVHaGPeg68FY8lWzBXi3YxFZpdSNnjBT0GqQNfiNWcsWsrqG38JG3yO1+wzXA6w7AQ24Y2z4szHx4eF49kKeieCgS1S5bvTL9Y/yYPE4dTFaNo0DxEw+0R6YE10OROBv+chlc4mwiOEcxc7By55gOrN7ci9nbAmwOTl+xsSHeOb7sMNG39aAMAZaHvsPCPBtk6P8kB//9rGEqnQn3owWQe3hmhHc2ibJ5VsU3bEp9uYvzG5iWXl5gXZRGdFO/iBtqAdhMWKH58FJDhcpFo4xmnruGEx+yZk/W2XEIsw2+2OzdTgGuJMLENTaxh6Q7Ik3+1GqwpwrbHWag/IaFxP17Rhya9IBCnyI03CMxc4WX/NbWRQeImNE2G0HN3yXx/LesbZypRd84vqbzdZw9NZEXmXTOOXknIRbY0a2C4cJAERdidEGl8Nx+ltz8cZOrtGTRDkU6ySV4WXUHIbyxNqjZ6yA2rknRsY9f9YX0cpS8IKfWsx4jSKPpE3biYF9xnsO1GZtl6wmj+P8iWOyw4eQ+sY2P9YotmTlzD7wSiaCHBRbX2JbgWBgKhcxMxhOCyEmspN3bPAil3o6nM0n81zpwdAeLo07MDIYCeA2/vka89QQgvxW/mI//F7mELvFmj1j6zYK8Rst27BMLO4o8AQDS3Mv9mPrQp2LFi70vGAvQCzlJAQbuJZkfRDFDxkXUBtvU/IuBlquUalJ/thrny143LXgfavq0nWBR77iYkme5YML4X0ZLt34GxNYFGmHAycJYmGDiqE11yqb2jOi4bcY1TTuxl+dOMDm58gGv0izTWzFwb2tfbcjlps1uFbtFfRGgQ8pZS/XpiefyIWD1+QBP++AZtya1mapblVlSZ3+u2as+8TLmjhXGzhCY4oB2zR4aCxje1W0i7Yv4YYlP50NfYb/Wg5sD5uCtq7jg11tVnmCr6J8Rp37bBNxImzqiQuw9Y2KDyk7jtjgbyD6A5bukRG2EEgDVWAeA7/5cl/eC/55Phztyzfvf83dcNboWaSfkxvYCzD4ROnCa9B4HKWVRmo9j2VkzAEKq4lj/rxrmY9a/yIvs+dJgW+y+P0tX/sGj6/55PZw8aW98eW83ZcE4xycPP6oxf4Rw372zF1OJDwQjecncmf8Rb4ii7cL/OWvf33z3f/4sws3fLhbzvfL/5KF+b//9f2bH77/t18/99NPP3r3lzvn3AXuV3X1+7zffeCVOXCYpKlosHZdrnzqZKknZ3myYcxmywrnh71dbWL2VNnvo27VRWIU5W4z3OMeXoRyDqLvXGS+OdGmeRc3c0UmzKevOsj5iVnFlmsHX4lEPTMmCot04wfb8xxA2OaHu+bffZe3DGQO+WA4F/v44ZO9AOyZI86DAuGfvymnb3/xvFPhmpELHH1CJsbNmODNy1w7kA/fWf954vCkDT68OsI72jNv5geXaYx5IgKS5CLZ2R2isaGkz+ZCnBomBotznuyBS/sZT1weE/je42ZRWluOa58wqFGUnQNny4siAtd2n8wp+5KEM/MGdeXBseYggflozq9Wle+WMEUbjCJlEClGr8ozp8YdNTaY0Y4LuCNfW6ywez7VbgIV1+wCATVturWLbJJrsCkC4jFHQlv7Jh+BfrUnDlarOwdrvC7hGNAsxpXK8QVrMFH4yEoneu3Y9rfxB0vYiaVd7JsPmpjm4MFUkCi0eTBTN2rsHcPpgX85BHtUID0Pjq2RGBOlMcsfTrYQwI86uR9b/UvOE7f4h/ur7YWKw+I12JmHjcf+xBryfUl0FPCY+Nqjx56Nuuzo5mftENQ2djnZNIeRxcrqH5yrB7JI5SMOdnnkHH6YENwADGgMyDMMxCVhJDW83Iysx9k8sHaunN+L+hIO9sSR1thYh5krcJufjDKCS3z6P6FjbOT5sAG3v7Ufy4iMJwZ++TGv8V8czGikQ9scwHScDd3qQQhSMHa8leljs5Zuoe8xhmXBtDl4wSoIiJHSskc4w4lWldooHrrtN7dV1Wag62vOZt8Y2aq/BLQzr4esHqA/j6Mis20d0svv1lPb4dgor76LudwbuIRODfWP5eB67GjYWHT3uMb0HLuCNjgprw0xtcNR9dhkoA3z5D932LfJ08Eyrm2PJxQeCTzEWsvZbg0bMz5BlIuwjG+zZqaElNhPfWMc65rEv3HLg9gCMAE1Hbudj3M4RX/rEVMUyZs2LsU6PCpt9ljhj3Hig4UoW/peDM35KmaPONd7eW+s5bty4US8ElM6DlgILv7asyD24isXKhwHXLC8ZVE+L/lzkR7ZzXI92S94YpqQm6eBdYVH69l6eUeIrgRVppsLLC8gWyeyABMz6n6R2y9SQ2mDPcNgvuiMAdPWGpPataNtbBqjvvWvrBzHB8c6iAeW+si8wJVwBo//PcaKfOd8/+dD68VH3MIzDww3U2sXwfm6H8ISu5mcHsfRNtPOeBcuxp+CTqhJReC4IQ3P6S3OiB1Wly2/mS/vWs7coFsjYzN41OvJVTt1xJv5Dvk1Xyz2MiKeTrNJAOZrG7raVnLqsESOcn0SNTLnfGryEmDNdg+s/WzA2ra+M8akuOlgOnF1MV7deb/7+yxQ337VhRjft07Lzb8YsAgaY6XI8rd4ykYQGTHVeS5Ktdjn4SoPzslD2HqFL0/OcIeTPz5M7Kcff8ynt/NJ6v1qtV0s6T8fHtYY2SKcP2Qep3R43zjniFwXE1L+eXKPu7nf/vnPLs45n3CeYXH+848/vfnn3//hXfO//+f/5weIccecxSWNc5J38jkHZbyPHfwpeVuOAXLLbxfu7avTKb1jm37UdxzF0yZ91QG3flz3rQG65LxxlY+MWMeOAVzYsWGP3+BQ/5QzC1ee4MqTFHkyxvNu7KgZpz6ffHHMojXvKU89+PT/3/i6tSxC1VuD8AweZ2WeAGEeuXvOqyCo8ybnnE/eZ7E+x4TnoSbtlL7YhjPT6Zoa3ontop8nTnN89S0XpptQyTB/xAQOHU9mbW4szj94V5vHHEcGVrybZJ88YIyO/PEPEiILiWVraE3xjw4+4LNnbAwW5HlygJfR895z9ORMTJ+Enhgg0uDcP+6S88RPnrTyMfTQp1bIuNsPb+YSvD2/17JU6aMq79o+axp3/dnT3CFjPnS8OGJgEzllWB/7jgeEPo1cDm47bGdaZh61DFT1+Zo1AjJpJVt1ZUQFUF1QJDJ7dBZhHEoqGEQL4eKWM/j82ozLAJvanwSV1lRdnJYbvuJMke64vTMmFEdJ4pzCo6QNh+W9/2DVUWRyg9OYmgP5ALbOfxiNQJtrqcdwrXdxihkf3YgVuSo0tOyNSTf9FWv50I0pu/pjGry1n3lQp9FsJhbQxsZrfPA/bfx3ztdIi3WIcTEmNsEWH10wdm7xK7+psTk23h4zn+7hos/gdHxxGW9I+N18BhelXIdXzKuJ7eRHrTkObPSxAQs9TVU22mWcfXOKLfA5MXhS1HYqOP4HZ+Gx0an41ZPCYIKdHyITH31du1U+GFcXgfzR4ts9ZoPcLjFEGxvNhpg+pbZYaDBhu5yQEVfpI4wpid2IGsxG3561izd5cYbvP5PFv4C39ni3Hk8+5HkawdPOHOpR7sdnOJdd41l7GcVKjFQOh7UN7M3VQQSNZTw28UcCR1t8L3ckV6u8w4uL39RDPTCxMe5A4mIUfSscmMonNjKYYNuaFbtukcDNfzIATq56TCDE+aG91ibyyXtxLVFMtz76ZHN4FoTtrYe54lPZjREjZM/YzMfQoi7YGvthJ5ARdgMCThIrHungc/65bpSNJ+DxedZFv7ojFk8W1FF+xLo4Rm5ytaU/DRonoZGVWPhgN/xaXwzIeS6M8IwJMbkA8QN10vexAy/6/OGVfdvuZ+juE9mDn/XNGIutM3flHEfOOc4FJH3HvZ1DVBavEUG5KRpmB4iZlcEeO+derhuzdsWY+sr5QuKKHl/tRm8kCVSs3YztM5F11cBKISJ+VeoVxQ+8Go7fOXYQS2AtHPe8c4E6BZ2PIpE9Od1cBJjNkadjbptciZBwLBlQR9rYZcB87wX2E93j4Lht/WNrfsESu2gQO/ORx/nOlaGuSeAPIbIpBFyGVeclNssXc33GhtjGGqYHzkRGaFQcSc4oQ2EUK48F3VoUL7BSAAAgAElEQVSevZJVrHIBdjw+OC1VASbC7ojuzOUONt9z/fbdV/nLYiyL9Pe/ZjHxPrIx7rxlIOemgtKlmXwa3HhTL1xXtfuBy+kgC428N5wFsHcNsyj+Lt973pe1hxlx8kc8QFyWsEpLvfv+c9hbDTn3znkXVhyvPHr5FkTicAf8u7zv/Js/fVvbPNbf5+u2+OCz//zb39787T/+480veZKCrwv7Mrlzx5j3J3/Bkwe5o+pLoBNNTuCyME0Mz09wYAEJ1fQ9Vuw/jrPkcOo3894SzcTNDn8awx6vjIpKHYhJHPTNPv3kogk+BVW3fRGmhsjwY+8rV/jWjADyhIQfiEdenAuwSCx9UwdkLM79qrQ82dFFKc/gkFfnhCdSWZSzQOdVEfukagz4tXbElXkwvaac86qPGTXd8L31nHOtszEiT425dpFf9iBFxW83CcKTIz6pk/1vmcu4+GoIntj1LnfGXSj3/w7/Z97n2wuY3/fm0bz7BA5PXgC+wehTOzCwY1F+X7ZOTXyPfuLyxA/cvVvvAp1FfHxmkS4S4Mxp/jj+webJEhIC5zPmwvgc0/mGhxnUfhTsKC5uIwLbdkw639oAjj3NLjVLXGTzPwBtXbMdmzE/GgNmdG07AMvj9uiKtPMuh5c45ZZX8bdz9nLEmUKXkFAZaMOejGe/B2scSmr8Qa03+/w5LCkHg4GfeHQemIcPcpoh4TBQh7faGtA1FMHayrX9FijIxKbFrL10Upwt4EoLBtatEW6XQ7m0yGiuJ/1lQbwbG0U0/NkG393Iji54xze6qVk96i2XsW8u3V782G2+uMRZf7EWY3w61Ei+E/uJxbzYPnHhZGYdoLk49rd2CKPhF9tw1g7ucJEPzNIim5422D7bk9sLnzED9+kB2tqtrvEfPGB//GO1vESasdRqdHKF98jp8bex7Qen++rAvXO6xuV383zyio0NlEdLEEum6BFVs/rDxLwje2IjNz2YjU43mQYQMf/tjq7azQzMi4f9Vjd9gOuYbTFawpvTffxZxdjLCGvbCzYS8MVl0Ope7Ik3GjCWzUzN5YQ7BtSOvi29QmY32Bb2ztPJKfr1q+XU9yLZg/+Z48F6Yox5dkWDrz4oUvfjyzj+6oZjyccmMfgB4VmvWOvfeCpB0a32GwvLyXezCpjzrvngjPOGZ9+6GnkQBp9/omNYLfJy1Gl0l28ZmH8c2eOHT+M4QlKNoNdng9UqHlsrUUTQl00gSU4cEC7yKtkX8Vn/2x8PcGI4cNMj9M5TNOk3k9hpiA8SnRlow1D1p/lm3FRrUGwu9vKLjn/kQLgFgb9sc+Fi6wS1n61cYqxvxl44oh28BuvFtWL45M8Le42KffwwsjUu/nIhxsjhXNe1wYJ+/lStZfk5J2OKxHGsW7UqrEM0IJ1mnHVsjBf9WqvCDmR3pfIwXpTynG0uHhuCuDHOYOuYjuMLeD2F1ZYcKj+hHm5AYADmsXycAwwejQick6e9pF2tceBihjHQ+sDOwmMBor01rnDH8Lj96QG2HLPvLExtcIeQTUMErRtIse8xXDNgFur6jftgLBrDtS0GsdM2nvkOrhoE8QZgQXRYG5ynjdniI91jLCBrlUVFvgs9YHwHuAvmfNUbH9jln3YEIm64wWvj4rUqsGsVMx6nGRGYFSwK1iE0YMaPRdXeRecuNwsdTfSLW8D5y3IoD15wMsd5aTz4vg0GPixm4sSTC54dIjNcakQu3+U959/+OYv/LLi5s8lL2v/9X9+/+Y//5/99849//P3Nv/71Lz8EjoX858mbhfn5DvT4y4HzUXh4zkg87w6z6CIuBYBH3iM8R6R2koheK9zp45A2LtrhXzEWtPLHA9/6XQt6K9c8G20YoMzgjI8sEjiCN8FdGAqbDQ75oD8X/PmKun6eAC7ctc0rClITPheAtyF4dzjHiwtKwsWXxfu3f/pTvz8+fbDxPS+Bh0faPk48FoxN4J7T5RYZYmseYH4+8pV5yIPHmMW7RgDaOs/v8vYIPq8EO56Y+TVcfXl+juMPeRKK+d/z+1vmLqG98+17vrtIBu7dhz4pQQ7Oc2LSfNUQVDL/PJnjE8k5DlmQ/5YnfPal7HsXnUV5n8yY/Ib/wBUzW5+s8LGRXDm2IuOIBte54rMbOQ5n/RYYaw7A9q1ZiuJ+5ressWo9b81SQ8/52cspBjgmJj7OA4IUaI8VdPxib3NuNK49MdMrAhbY1RaN7eFfWe3Pe9Alo2YOfIKIwaayE2QzVxOnAZdwZE1scFBKRvA7Mnkcox6y9rYoGYD3LNKWCDua44kNxhbsRBod42bBPj1jCiFGKVCQtk7l9tkvdjkhEXMmBB7Hh8nY3BZw7MfJ8Ks6sRE4kdnHH7n50eHv5QkElI3DvhfrkRHgBRizW8Pti5fNiYHP5FJZYU7tURe9PWMjuzXbwEKNrXr4QSoAtd/jIkY0sYbL4CrejbUcO2Q0yKSZ6nLPA6YoD90aItqaTjw51VQratNF4IOfNUkA6CdmMxmuCCd2dQOWncchIRGxWdN2lemK/nDsMUbNtdcZKywYtNbCxcYT0p5IRndyKoRe+mOfH3ECSYi2SMbWoCpitwbHrhyKD8rl4jGS2vVYIVECvOIz4lxiNurYODq1KqlEwD3xjTX9ou28PGz4LzLxNuRBBt7k8KN1Kw98kEyeztcAbH9xahnjdITTsxtDTC2uZDOD2ngP2NYNW/JzrC4jcykndPzwe2ox/Mn3lXfn4kQtqdIJ4cKXR0dVLYc7etRjhI0d+YzhJMaj5kXOlv+cU+8GDSPi48y5a45V88J0UKnR5mOYwSaSLbv1KVjH+iTs1kndEh30Pp4NNnOBwTEqvATBob3qxsAdusbC5jAaXXYRP6XkB6b52W/GyIySuI1ZCH2nXqcmMTjHEGYZc1et2EXqBTiyXLznQoUGft+/nBippwvtM2dG105b8s/cWE/6/mYcWQfVndwQN7R7u/AGX1X3i6MwmzPHses15NQTnYyNpvkgpJ8eg8RURmzb1CBY4I7JmGf05Djo8BfD+AOUWnLcLKz6Wp24XvBu2N0Pvn5TM9zwZ0jHnQbtP13VR0fJNBk7AboBqS4LCG+k6zeOYHCxi+4o7WLQ+ngsoKeNH936TC/AE0FFn6hrbc51oIRjl70wTzjBBnSUfYwGVT/y7bwRscGzjy1qxktN8w0wJLPMiH6M0YVvTcB32L1gL/AdxLj2j9gNn+00MI2Hy4NrPD/mJbnvs7Dpy5m7QP/t1y6YzQVwibBf/+2rdIEhi8TZ943zKeosxH3599BonVo3F4qR8xj+NQud3359n5e552uwNl64YX8WKC5fch5gkR6/XQy6uMlichc5+PDBbl/n+81ZqLFw4omI7//5rzf/+3/9rzf//Oc/vVvJp8h/kU+Rd4Eeu31Ju3vi8iRC5Cz6wKR57qAGDptHtqaObGuclLThOOkTGzrIG1wcyKECE55+NWBiUa/HfI2pT2QegOBIYe0BngixWaw9T4kZsj2lNgfupEPec07OHa07C9XcIc/nAnz1Wz7tP8cJC959MoXPDeC959w9p89ikva8flOwm5c0Ozh1wi+cPOezN3eTMre3udvdl6TXbiHh97nfBPC7r4bg2OOu+a/5/nbObyzOeZKHmsOO8wmPL84b5OGTEFkcf8znC7Aod3HOojh6arrHqPMYPxbn/HG32yctguECPU8A7aLc/0nMO8lNO/kwjpgj2KeV8qqBEciToG8/8HkQffyBLSdq4nFTXtCzgsgTR77s80MstMqI5zhb9PN/Ie4UEmH3DHEjaVrk4nc00gZtLrXcPjFqHxsgxMpm+stLcdSwzEvcS5jIVTDGec0Ku4mYgHo2bVf23/hEdHDtBP0k/CAcKLmcYiJYz5JttGazvDe2li8Fi0WE5jJFxsaxseh3onbiGmXrcYwadjgb73DsxAMKFomipxmH8WSvTF0sUaavjQPGlbGDz7m4jOLFHv2JRb8RilWc1kYgcdXpA1Y9Jh2JXs4Si2N9vcC2G3kc5EZEuZNH5ZifmNEXBWsUs0dObC4meACoG/3iNICcBalVTfHDzc34YXR4TV1QTU1w1MVt/N0D0RxWrxU85YG0FNjLFFV+To7yzIb92mSvmD31CZY+PqJBqWyNTlmi2bZ1vfNRTb3TB9OYE3vJLQDgD5XqbOBhw5e/aXRrM3pGEcr7abh91OpxhEuPiVUXfOpkLZvz/sOeaJqPWkCPoxU8+BFM7i/FisFwlLy6WK0/QtJZnNkj2vgmMaM1w0GbR6wzD5uLGMVBZO/YR5Df44N8/ZDH2Fz0YtTIlSNMLTN4sXmOxbr4ekxsqbBhDKCZKLBX4CDPkwDYzMydeOfYxl1p+RQgkslFNTECD9fmm9oZN3L3BsAJi/KKvbb4bS6ATQ52YwuOEKNrFhMLWRqYPWYyiD8QjLf2GrnBmwbiQT0SOlrAJw3/zXPx0KyNegwRNGi6N+6p6fLZcxY+tZRFo40sg/KOk37s6OiUTfr6VoCOmE+5dz64g5bLlyFnLwOt3X5aH8KRg0agKkBoavjYV59NQspgNlzYjXdqNhdQh5feGV2edI03MXtktN7aEbdhiGgrp8Qd7kxTj4/6FS+4yFEuoYd/pMUKfuNkuHjDZUzGvSDnOMxwFxRNp3q2i21uAwKNZ9saYK/nOC5dc0MzQcgJCGdSowGMfGW5vhYL+ptCX+1QTtaCeKPMtXUVsZdfNqvjsTReeNhfXQbhQvyxGTx3zzwf/VpfL10Xl/04L+piE8G2WLtfeYHkfec6RvnVl/3QNMz6r6ymQWvu1n3yIQTmLhLHnmNvs0BETT5k8cVih7/eceYlzdwtbRWHooT6+AhG5pUw+Ps43f5Myu+81jyOxuO6yDmPiPj087d3Pr0LzmIni5+st7IowZc7iwHNAUusxuuxYmChsgiLKYsmFjIcDiy6v8nL5nnCobl98EPg/vGff3/zX//1X31Je3S8NJs7xLzUm68E60Ioj/fk81kW73CAJws360Re8IKSn6zdmBTY42ofTFBPw4fzB7VxrwQ5mts6ArQ+1dw5Wilztk+qGS+G8Ov1dJyJ64QgB4W5Az1/wINPV1PmoAtQauyTo+h8AHLOw76fFfBF8v4ynw+AjuudLkzztoAs3Ll7vi+BXwx8XauLN3MdmceBJOnDrnZwsmGfmPy4hEXhGF7YcrzxV8wvvvzKO/e83zxvXshi+613tHm/PO8515fFtvMYixwj1IpjhQj8vX+bt3lk7lmo+2RM5rr2yZ0kJj574rIIv3fNe0d976D3GCAJs3FDjPVd6TkeSIr/o3kiCxfnlxjc+X+v55vfeJn75ADOO5/0Yl7L/8QCK3rG9Szfjal8cqiems7crO944rP4zpnH9Xhlx/+Ptdl952wVk8+JhxN+YEAw+8ScD4kLiQmsG8pt4mXDfsSPboT40rLN7yZ0JuJoKVhthdcWl3qrG1LCTUH2HzKyjeuJK/rFQ7c4tRoJ0DiBNW17Rh29XKMnvDhgx1Abtg5mD86AmGv03TfA+iy35So4rmCJfetRz8Jqj+BZi/RvDCIMAbrR7cEATzRgaG8oN5GND/Gx4SRKG3FR73Fw5PBIW0wcqJGR4rt1R0IzbzkVEX5doEWPPXiaOoByxgrqjRj8yIysffrsFdwYx2bjZv9kpP1CV6WF3cFFPd3WkRhwQEgLD20CtjWoLvIqNBvr9AsgN4FVFwOHkdW+dTz1rGnTHFKGSF/7498YYy5fcRMFe1qpNUoFO7d3/kSNCVxpWifWcm99I+V3bYa/ycMrrjvntR8cCQjeWgLeMB0br9jIxYDEp60Q+sjB+FhvPuNw4mX8rBMhJi4+/ALRTfZc3KSNSVJFSQ4PubkjF2F0GU+c5h0d2OMvCBDD93hj4z/ROaaxiSO7beDRXrGQjSSYW2sNI99xrbI1bvPSazAXo3ZCGr/I9TvxSfGY0MO7m8aL13DR7slr+jUf9J0IIajwzKHFaQ0aBfpGkhsYMFFmkZsv5JB5XNDXSuOxrd+rpqMYWLNa4xgAfzfO9Sr7tUyU2MbUuOz1m9xkDfcorI2WGNfuJQcuPFpRUO5x4UiIxtHXiNDGcvCQ5Y/ft7nY4k6D+oqx1CsyFnCoGNvIN81z82Jkf/ihyx/85nLfEpmTF9PIt9WyoxJAa5WiYv2+xyc2tZ7cM8DulfboJByt3DMYzuVQH7BOG3vHudCxtpHtuatxitO6lwkMcN1jQnzmBiHHSX747UZA7dcbjSaCOBq9TsdNzdiM5mKPfOs/7F0oNHYZG8dN68LdtFJjzCV7L6yJ9THcwdtFFKREMTHyQ9D8it6cS0XjJmM26RqoWvvT1Sg6YTOwfmNQ2dz91rBO5axxYekap3nQZUzti6ezssLEABD+hgexxN3xqCnMYqhyM/nX48AQT0B3og1oFx6eG4PHIv3Uj8Kf4OMflPsqlkBgEpnf357FDwItfXKLeeNuYV6CnPMIuCw4WAK+y51CFr/e5czLrPe5lqgakx2GAdtaYcSc+6+NIDbu9LKY/+iCm69R80PvEutj7kD+kq9O4wPh/va3/9DmqyzMicmdcxZhLNLZk6aL9PTJqHeELaj5cZ7hVdeS34kpgdkOIRciq9j5MQljrIb9SeEpnL5VXIPQaFXr4/xQeP7Cxbmzt6XbYx+wOO//p6ZjXLuokm6y187vtZ/5A5N6UCs+wI/mK1pS/9/yqf9+5zkf7Jf3nmNjmMD0vAuwvzeWCHdT5s8xxwlPsvRIuE+ONvccLalfvPKVbiymv/3zn3y+hLXs779k4cwTCP7xYXbkT3lY8M55I30+4T0Cy9Zrrhy3e5c6PuThMZm8f8sB4ecQpEAcGyzseYk7d7f7cnbeY94Pi7tZ5LgJx4RKmwKsMkLFyO1jW47uOah5m0GekP6Q/3l5m7zH4IfPuNMPB+zzx/kfhzQQ6YFLaTwOVCHfYyB76waj9IkTmzE7vuAVKbrgg1Xs7qsGs75ro1wete44W4owxoul59ShC/RNZILhsGU6QGKBNKSNUyuTyKYB6Gim5S1OEiAOhHav2WCcZFuyiSIPJDTS1hoIfzZQNVhpKX4Gq1a+NsWS10Mfk3KzMxyW5+7VaTi5EGInqJw26MkV2Pz1ImFZTx7oqAf6xOD4oD1l9p2X4Q/92ImpdTfWJV2ZYz81aD2weeRdl4KgmfzWRwUyfORU9GKFx3IezE/gZniSEQZeNiBf+EWAauLAYfXuBwaDCbtI2R/H6RNhuE4cY+6GuPQnX6BP7tFs3MM19if8hLK+kerHXuxs1WONbMeLX7WmA2hs4itcu1EOP3juCcW6jP2yOtwFia/2i8x++wSZ44euckW3uzV5mZtXG+szOKCY8mLt+PgnNv+ENxeG2DjGmxGtFXjKK4ke22NBJ+Pgs1dTwCPrAVKfA39sQGLeGtnHWvpnsYw6yj0GDINo+OEl1IzXrm6Nuf/MkNG0SQ3Wz17+wSF44na0s8qItvPVkcRXTo3tYwYeeY0kfeORgOqVOyyndlfgHq6A+j9q6oAC74GaGIO7/PhHiA3GaYxk8FzgBAD5sRSwI502wPiLhgweGhTfx4I22aiOHuypwdrq4mBrWs3agUs7vAdjmIu5+lrGP7/2dxMfUM2iRYtNJadggKRpU4gT87gE5fKI8ULohzewCCe+vcQ+V+rpiE0d0rcWGNWHntcaCaKEzUvAV/mNtfMTBzCnxlrPmOMdalTiHH9Gbk6GccN4gz739YUjOAcjJs6rXONp/ltvrEkBHHzKT/uRiZULai6yavc4TgzfMeZFgUf6QCFxMDts/jCeIyVyTnE0StLWjnfZNsDaxACobrKPXNXoTXOCm+2C4xObnRtM6PPHgsh+LqjtZ2+LnHryx4U4BAnDBf3KR+ACo7XHp3pJSlbXQuK/5DfhYzM1wTKxbXB2PJzwgcS0jVkbbK8fJltDpeN6ShIhcOiAJKR9eR0kcxWLTRoa7Wfkropc+BfQSmXSF6/2DdAnRFiUZYHOgtU74FgEmwNFgt0v11MOVnlZWEGRRZwLOQ+6zFGELpJQYmZj7voe5y/zHmfmhgWzTw4Q21zXVNAO8M+Tde8Sw3xjZy0zDb5EOTgszl0whhwvm+el7f/4+9/nZe356rTEYVFODBegWezB0byzX3n3zZ8FmS11DLvzQXRUnd8egTNvGTsR9XD+AmvNnyprF/n6dlbGiV0M4FAfeNBrO4+XDLUozafFWPbYJYY+CzP2xk6f6ePhxV1ozqmiZv4wY07yLu7458MEx4/37H+XT8fnyRBqDU+NJ8HDz8SbB3rPWwPytGkNqACL6QnSQ8qcWLhzDH72GZ8qnznMEwPC8IQqxzaeWSyzkOWzBDhfZELDqbyIxR9DHrG+TH/q+2HkmvL+9fh5LHl89lUl8ObxwXHMscBifTEDJ+diJ+48OPbGoXFlyKYcsrP5uOCY4glocslE8ATFuzz2Esk76e8DTF7Mg49RAqXNzj4bqndk6RB35XawQVZ3AS63ztHy6v8lvDAGZ51il5/6Fd+5X0fs+M1YLwg5Bms4RsBR6YfEjdSdm2OcTlph7ILTdoJlOBmjswBrklFlxh/pEI+PWIuT/cEGL8yfxSvdi7Oc6jMFmXhx5HdoHdSMB3ft2Cu7aOXfom7850TUPH41OfmZHPDEZQCH7Hr+fY27MTXDBo/BQ9ZcrwA8eQ1/EjuTO2Zglu/UgjNIHMXWu/LFPpgEHIweUBwWyLCndUvvytf72qDT8sGxeOVg33+A5XHqM7zLkyAls77EdSIjLj4mwcj4zlo0Ko/76Yx4UzxYxRREmZhyJ1C8slsba2Y9isb28suo4pjvsa1BIRZnjYJT0dgiF3BCxhUDbdwn18VFl7ZzeOyW92LXW9x7si/OUWGbv+Jl++yvsGqUuiG+PVyOwelPKWLJcbTzhGcky9OEm3frWC/ta9rtwLPr480eJE4787BchMpGmzHciya8hkNj1a4uOx+xCZZcsd+QJ+YINLtzg6lteWSw8zaaQomTzWNO5fLCqx4+JqAIn4k/u2KdesZ+cScYQ/NaB22RraCGayfX6Pjh986VVBFNk5Bj8Wvc8xE8/YkpZuyU0S9CfbJFn6sAaNG0zWCPqY3vXoPLoMYRAsPcRrXa89gYycA3ULhoNzyz64XLOLO7/gSdY3j3Q9b5mHqCaO02T/Y3qH0eg3IdH5DbMGxw53qwkDV/rFrT9m6sxevx3xpgc4oa2K254lJIF9tqljf6faLKvjzLy3E2zsuEsUa9Qm1eXBjmZ23tLiXE6cOmxXjkgHibNgyChGl+wNz/c5otFvs09e086hUBsQsyVoRevAbafMXYfFHhl9b6R/uS5yHZlGaoS/qlB+LEG54CujHAHdZB+3EOSDIXF8AxQLlYdCPvAi+XqVwIc1Gci2FesupFMauIuAPjndj83/VnFnXkxgX27j/yxE4aMi7NufBeX0tT72yHRAlqowSqqwuCtcuYBQBxYYJsbZDg5xxlb0OYhv3aWQhrUPnq9SYmIOxRzBZBx5Us2sZsmB0tLhHzE8fmWwRt05UP+9QVzvxZuywGeJltF0zFcuFgrqVk3trHP4CtjYQ1YO4ySQp4FPFydpp1iz1zwWKri/l8YrgL6zw5UCNtef93FzEsYGTbBX/m0np6DLN4y9yGGy975iXuZIYfHwz3fT4M7vvvv793y5ObL2eOvU9EzF4ZxxMLJhZpHDPRmUdi0z7mTj+LJV6+z53Ot+/ytWKx753b8AsffuBCIv10cTw7JjeRps7A+uQHJunjZhejM6Df3NFhsjjWII7WHrD4OIex8Bicf656D7bOwah5j2Pmz4cIAeBE/AjICzdeAfH5F0HJ2Pf2v/3uzTd5j79PqlgnOCVm4rHftsdTASPvb4a9Oy/H9OUn/foeP6Yg5IjL4pz3vH+RxXlKHhkLWOaDec9bFn7lffCZO45dzh1B/TDnOPD4Yy7REWXHJEyfvFEwd+BwPHz8wFsdegxjoi1z3IF1P/Kq2Tp1YxLI8M/PPl40cLPzFlR4eojPfFD3fCii5753fVk9PN7mrReAw0064kyECHwc3gDGbmIRRr/HCb7k8MJpAGsDiFaUxLpoz0gB/pXTqesjH3xsa1S0Hhu19g76khCBAx5UDmIKsoGifBKtOFCjL5M1bzEYLa3DgyD+ZpOGpRgTE9mZWA3go9T46/taIEyKh6WoHC9WZzXh/2JS4jf3q6S3vNDv2Chrhrv4N9etAR7wM0LsNx+BeNTYBLCn/UjlM33six480IwXpRw2bsYXaj198JQ7vrdtrMOJ4ovXGEcfF8XZmksGm9fxHdj1cQhHMdcbKRjsqtvjSl6I8nMwTt0uzqatXQb6iWdE8UFZXhfvgQud8TGW8BEA/uhjxtOj5Wuk4bZYlfX4Aym2OuHYEOxXxH4vMsdzsLHCjnyqqaTSyibXVWxdrVF8tjDsIyN/eYG7efUsHQn2BdIOiUmObVWVxa68qoOLphtvbNmZ36f7sXvmgN2n/HwZUrCJJdDgZDcVifyRq7EoleaMJgfjVWHeaoqxPphgQc3Kq3zG1Dlqf/lsLUWYurQPkHNOURCBDXg2zxxPLHTGxXTmFB8DDpvRV4oVwBnlv8naNW7lBkyXvGow9hlWNHkMzu6KFRe5l4v2URipMAMMg+Lh3wuLylZ+fdIDfPzFlFgzabzraz1if/JcwOyFMbH0iTugZIQOycGbmIxf537zx75eZrjd4HKB0fbK9mJNHBAw4W+4OM/BFWG4bgEWDd49TuL/ODZuzYpf3unnp8cPYYrCbu8yrN9iDRU5ISu3W4eyE+D8L5dTLMubfXrr+pATnabdw0DTXBg113Ud7hIKok5BAIQ+AvpJRtHWK4NV6YI2guecA1A8IPQGKH9q2IhbUQb4K4ITzRESR91/WqOHym58Ym60x/lz51N54uz/sQk0IFCof3cbFxZ1XwkAACAASURBVLxy4gJx21MLc3TP41gWxKJm+eXimb4L81xE9xOT+RojXlbarzDiQh07L1bjy8X0fkDVkXEhm4UdjwH4nr+M32VRxQKL+cKXReLJMeMWZjIgl51PjFSXK6r1g5MDheOzWGNGLZxjOthlD8fOe8PsYwGTaxPj/LZEasyHOnWEbXKcMdA7R8DojHBadfW94owXjL3xZj4zrCrjxFmzY4NMYfUuZjKWH5zyxIrznhLx/mIWtV3vdF6oP4srsLmr7RwyfwSAYLDkDP+M54O9I+MiOG0En+Vlz9j53nHmNMa8FPnnn35688vPP/d95lnUbAzidCEGH7h0z+JuX+YMPMcaNPoKjizsEoNFIT/48UFz5MUnb//6y6/uOR7A+/yLvq+dD1ljQcUfjSpaiw5GRn1GS0End/aB7yZcGFhuvagzsagr9Wc888Y+/Jgc3PHZPQNtUSsfxDEgL580iS/ezBfv/aZmLMitc3LhZe/ePWe+wDKW2WmzY6KAwzE6huonhbNjSvsec55s4cmBy+vdu7wlIYvzL/1AOp4g6fkAH44Vas23AbzNh7d9lk8f49zxPueQvAyk+0D5XejUMI15TQD3xKGO5Ru75EJ8W/z6pB7FSZsasd/8eNw2v6ip3ZwPNDXn+JHKpHP2YAhZBW4g+SmJ2ckxenLxyUg+3Z1a5w+dTxTBPTjEYuOePnH5DTdk6R4Z87fzhcLjB3sdNGTTFkPzVD+y9MV8xosKHOIaa02R68ssoYvvYH4u8LB7cSYARvnZtsV+yjYYEHGo6QSblBO0AdaPCQLLNi5xbnGwHnJY3AP2GNbP7SJW9LQ4+A9rumKuLIP1ae6MV1LjLRme1zc2GZACKa+8e/xjO/Uj1GJ4MkA7uWO5NcdOfwFbe2WLo8+djzG7JY83ePrYbx0BhfmwGht0sSQgO2J4oup4q7DVVU8Wm+yYkRcgxo2udoq0UD42YBowMZ3fDR7x4i9PnbF+1KlUN4+iaUd+QtdiOS0GezQnZmy9aF7F6h+xcuYpp6EM5nLb/YBCEqTNprWgnvTy2xwWaGs04/hZUxE+3ci6ccGb2htN/Mlr3aIwx4m9EU4NV5C93GK3dUcl2clic4yJYsb81g5ZeoowWB6tkYKVYaYfnrVtvTpLyEaq28NqYJCkHSJY87f+o8dm5YLEBo5pbuN/LM9xGozJA6W1OLp6vsjQDd6pKWaR7vmM42rjYUsjRNutT3Xdrt4Usde4+W11sNTuD6ARxGF9cHXuBhSUneOVnzE1wU7MbBbbDn7BnXOC+PwvPjaNxPYKywIym8vyVyNg+eClzPgzN+lvXV/CJGh5Fg0/9P2HdmMdbjHwrjpBPmkikJfRM5pAYs6gujhG5z/14V2oOhx/uA3W+i3XsuwW2VnMTZwJrbe+IeHcWPNqt34wps/WFmL8KJsaZjj5xCa/FcdnzmXq42yus8cQxOUOdiMQq/0doxvjYM+FGf4FUH1x6gXIqYfz+xjHQ52esVefuOk2VxSwyHhuFBSrNFTEsvYdbc6MygUkctn61U4EQp5at7K7fYlwjovNKZwiOxf7Azla61Gci2J8cOoaD/rDsF1ZLga6MWFnvO56gez7O3NByqcke5Gdi1L3LNBzwc1x1Mc5ObKo4j3EXaTsS5TvS27Lg1pgR/Ou2Hwg2O8eP1yAx244l4um2YTr8F3J4e5xWmk/2IpUwg37wTK/pqtheT8EVsZyPOEHtKEZLM416ryrId7Y0OOY4HdmIJLbE4e5Om37mdXcjdRSuPWJ3rm9nKnTfUIC+Z0PykWj3pynMjtRV89enVs2zcGFcdatX2Z++O5xrk+cq8kLzIGVimOwYrcC2JI333vtAjJYvCLA4yafDs/Xbu3CHP4cA+z3TqmL8llAuzjnWIl+F0jsuesKJp9ino6k/pQPSEuyeVLgyyzMuVufYzbH7eb680+ziM8TENx1ZjHPh9ER+2bV7s7E+lIh2sp7Y6WPPv2pa/TFYu9ganLlYNDWp3Osp7b4nRjaIYa3bs4jd6Hx95ySVw5Qr34wXO9YY1nekIhvasIi1ZjgE4BN+p7TwNJSUXrbyC9+zm1cKHMMweMl7bycntg86cPL2X1ygrmXLwv0vHIi9jy5sG1f6fIhxzccsMXX+K6II8u8yjdO9ezx5Lk55waoe3xNsbTJphiM6PWYsA4aXCx6rXsDgEVttE1skwQlMOhC0AF1KN8cdzzhkHGf6MnxTcQ4+OqN9OUAUUBAwSBdRtuKz2j0dDUvv/JC2AZn4hdxpdkLRIDbN84ElQK6mIAplRioXregfn4MVTbQDXYDr0yCxXULweqIVGTGDWunmyfhSGrTrX7qq3BS7A7ywc2YX8IYqrEzui16Cxa8xUFZJPbTg25BioeYv2mf+qqEx/Okp71EVB82EfnAEwt9NJO/o1OLAExuZ0JjgA1yfMTE5vgYSqM/YOp3Ntp0viBavMaTBYYTh70jN9aFkHMSQHlk8jAjZc05xpNHkbulnlvHpc9+gpycFkPVAwe76mpax2z3gi1dL6IJhLO+xMY+gnTXf+vgsTH2h1ud8dJ3c2GvRGxBjdEI0S1+9NrFHgq3boWTSLobr0ZhFtuVLc/16L5zJmewIyyfbOWWYzw/+irCgmj12ye3jHH8RdCOGon9yeTscUUwsBsZFwUEeMiGE9qpOdrFWFmjsgWtPEHctvlrp1ntXhZbkbcG46/xyqYWcrucrDW8J+bWG5G5qyuLo4uM6MsdbW3tKV9b+WTzWqeJTz10+e8yrqrq5iNL5nXc1A1vdnKSeDVsL0eZyMOcB0Q9dvkxh8h3r109YlF/MOmvX2OSfzXIN/dKutVOGyK1fk+9SXnMNtJU6Jqoq1/Tb19IaxLU5TBcl1uxgYoBRMmdXX74RVZxkZf/6s9Yv9rWVWexBujwhcrmefacjBIYHW28c3Ez9TxwGedHyxiz39wkWvdjc+arHoM7UfDPH9Abz0423rVA+dTR/3QOqY9Wz00ZIlkd5dkoR/b4H4F22+p3DEkR3V8Oy3uDmCuYafaz91g8yalys8foqR22+Wk2ZcDY3yHErrL0rE306S78emuzpOKDqfnrI0g2T7/xBChoPaaIFl8o1Nk++o1Hp7Z0NHeDucNs0PPHSzlZCO2inE9KZpHOhSl30L2rngtqL6ZjxyKOv9+zqOOC3LuTvMw5434dU3jMKoN4e4eUT23e93N+zoIp3+m1d9W5+Ifz1l6yUxw4MhfomgpbajF5xU9nBbXZPFEhPncFta0fcu0iWyg1g+fjB3+EbMZXuY7UrxgoUaOj1bzbYTTSwcsID+8sxsy7bYPp4lSYwdy4Gwzd6lOYXRNZn8idmxi48MlYdxZt8xNvjxfulcc4g9R35pSCDI3uNSbHIcEumISfrna8ksI5jJxj4n3ef84ddHKBTxc382ntGXMtc96LnrvuvK8aQHDjlH1eIs3bK1gc5Vj8+eefPD4/i983uZPL92/3bns+RC0LcO6i/xBbmsdLsODx88+/eAx/8+3X+Uqyr7O4nYUtOWfx2bvgLLq2UEJMvrKZx9bkG8wtRaeD4zAy/PsbPX5UZyoU/SAV3NiT65iOpdjgOof6oSGn7PPLcUwtvbN85urOGTZ7bbNRwWIe4uo1rk9kHU6xn4RKu/n4SpeY87YF6kut+baBD+9/9TwAK/Drm3NA9Ly5gfMFNeW4xgYr3x7D+SN/2eS4jGfqyJjaIaMM/H0WLhxHeywtNwtDPMxjh9z4RPH/Y4Q0DmfnqPoaR0acac8+oqPCj/8RQMorfPnQuDxB9PZ9znk5DnlCkSdIOEY5fnjcYEsJm8XlZrgouF4+0Rkbk0TMxHibFz7oQWur/QzGpzaN2/lCb8Zx29oAIS/jVL6487GC4IU8IUlg+wHbpFAA3JZ+2c94pS9DPQhk2uNaNwpVwnuwWYSyFORMOCgQX/uMa5DtJAT0SCODW0a4IEURuwnPIH9pqmr3qQ0uumnYzRa57pa4cVCDnz98aPLJZqNaN8MWFVta7QdLSTcrN7/JZXNobvEv1KAU79hEunzE2o1xM3B8+TVq5+QcgNgElhyoY10U1DzbnUME6McFt/SpSWXoGRwU+4has1snLbM5lgP6iEs9Skbjc5w8TFC8PNhE1HyQh9vU1hz/0CcLSyDW5nrqH6TyTg6allQX59Xcut18ahpbipNWPLuPDVjFWDuSboTIp25lBwhwg6dnx3goj2r+b4xvHMy3c3J8gwHK1vTsnyfWp01DGh/HwyvYnnxzEl2ZuEUfhsdtMhsweNmaL4yUQPnwGJ4gTS2O3aBFQSKxwBE7hsE0TDb4oc9+dYsVYSmwxd24IxsfDXBM069hOnY78unv7C02nnGpL/v5a80zmjiMwTc/ZDTHmHxS36jLhQ6/W7v6vdgP9yAEkO3YlpVhiGNbLtgdv6qaRRHaB2ncxBoe+sHjte5YlkF7HrPaBC11L6/GtTbgDJ/jG9mJuTXZfRQXn2ATf5yt1+R/c2tcTGzSnrgRrB3pOa/mhmVt/H81mEihq26Oo5Pjw+ZyFNQY+OGKjiZX8srPOZ60qZU06GJ7vP6Igf4cCwQZ/kXBviAbF/ttxo5P/28Pp1Vm3zyiFyzWL9iLOPO52clheI4fAGWRbTsTZXJ/2LUeJ42x2zo9yMl7OL1gxgYOXIzS5eJvecstUvaPqnaEGL9cIMan55a1aiU2RZQ7P/puKaZitZv4RJpjBR9qyF1zF+fcLc/f3j3v4rx30lmYY+tFfgC9SzbBeOGwcwFe7mTxcV5cgLOQ2PqSy17w72INrM9zR5MFUy7L80d96mNJlHTD3VZa55w+8zw1onbkrEk2VWBuQwWza8MQpvUvpoNs0g7WJ0P+52QeiUOoXQScA7bms92oDNu/+6FqDnlSJE+GfP51F0AsSqx1FjfYmzab8DUmm0dzVjXCNkr1LBzSSSk/y/toseGIJ0/+IvY4TNf/3fdl61jFj1iu5MpbX3BxEF+rsiAOx2jsn29X4AkdvrebY4n55U6ji8rMr4sv9vnb42KfzOlcsIALbDBYGP2cl8h///2/fD87rzT4JrX6v//n/8xXjPFVbiwJk2rq9k3GPMH0S54UKI6kpYz8h3//4Jx986dvc9wlh6jXjj1cTq3s3bphWwd2WxdkwaC+6Gnso8biXCfWHK16TScWhntOuGaxIAb1TuMJifxmnEU2gc4rTsihjxf0m4NO2hMOm8lrSUaHGvzq6ovQeWCRygI588Oi+6tvvnX+vHOeOXWRHeLSiw/5m0fw8edVCnD5zE8/z3eWxwcDHu/I/eND3jhu4orcTrb480dsGvy2ab+DEbOTDzzABjC/uGXXPDNAZ67Z0/SzV78KcOxim+cR3vHA4HMO8iQij/WPfHp8vnbtfWrTJyQHdzBFBgLwNGpfPonNj0FjIM9yQOg5RXvd3IA1MOmJ4njl7uProfjMaQzMFw/KGL1YQwxzapGzbq0hV/Qx3NLVS0IYlEZ8AKjDpTngNzmwa4ffEljCO8aeBuHT0meEjdKMtTdwe2rT7WOx9lrHYS2ApH/G9mfSlm9kTMLaXP7N1/gDsgcR1ssXFTbaAZU/Rh645lQcww0f4p049vErUnGuP2Ow1PLAHPsJdAJrNxjlMCprB4fhZlFqsRzRfZoPUJvnxuw8ygT6NpHC6fgvPyLS39Ygh7bY2CA/ZlOrCIo/8z6Y1l9d5RuTEAdv4lkxqQ4PQxHstj0uD86o9Y1Z2ZQeNVg7YGtTB3HkePHluvmbTDziqBwKT7z0xRs7dnU1AazTiu1cVADYwRtt/RzMsTK+1WcwHBCTX/eNczlEOhjslsUeL+i2dlxBtL/7ct889TdxQ4m1iMaDD+f/7P+4uEH5ygWUrcFzTpC3lfGZq/CTv7XdyBuL8cTAeXi6iz1+K6O77coTy0Fp0l1OE3Vc4FQb9i/+CE575X7EdKLaOi+/6ok0x8HWmQANWT9yiewPcSO881SHwzs67QN16u3CgagwGTyGWOaXEq/X4RpJraknRjqM1+jkfRU7dxgVB+yZD4KIVFRs4Kn49CcWtGIuhm7NVx9jDm6vnmI8SYCXn/K9vAhCLJp8sOcv52VK01jZ12T2jILhrvlWUqwHer1IRGE1xaKP75jALXGfddqg2j/ymMC1x31A1t+5TczF3ggIuDBt3Yf3xJR/HrN7XMgjwh1Tpwya8mBvvAqhMTn4P42ook748jFjiJGPHqjjZ7EjI44Sd1sCB3hg68TQi2351Uf1yOlbMjrDt934DK+n1/ab99bIaBPjyXfl3Uu55BQYl5gBPTXK0hRsLzpzccwiiEW6C3PvnHeRzsuJufMFR+94BaOLKhYF96XKxY1VZNzxFDv47/meItrw4au0vPCOHQtzLsw/ftg78B9cyHlHNccFC65mudeYJvAoZLskab0250aMGHmEK7cQq4RTK2+M1QGEYHxa//WZeYjtRDx2W1cR47uPU4kxBsIYMh1A8HhZ9q9vfknNv/3rX13YYPvrr7/MoqWxvAbtBJpXF2VloU74eAY+FXUeGqT+PrmR+F3yoOlxx6LZD/HCVWqvtSQvrbNrj3175yXUOLKoAp89C6uIgPOu47zHHd2+vJzFjdjxEW3jMGcshLirmj3f9/1TFuf//vf3/v2SD5zjZeos0D/L3XY+fd66yjI0ckx9l6/+4iXU1PUu6BIngZjPH374wfPOt999G4xzDzEIzMd9DG++VgRfYoQThNEx3lq0yhi0dcGNzTy+naSZS01urGQ7tR/f7A6PnVxUCciHsf3OEy45N24NPfZkEz5J0mO2UK/nV8+Dn+qZq8kp57z19bmZbPzgt7yv3AV3asqd87603UdWa5pY1mo2zDM4HFuf5xUOv+UVMz7mSSFynnSBLnNM31pGXp85juZ48BghF/QTxx6D/HmaRv+ckQCuDfOT6mrx6eYP0sTgOLYGwSD23h3nVUHk4Dkp+7bUi7gtVnrkEA0JfdLgsZxQYVKzbHHK7tNjafV41qcSE4cbfhuvELVL3W2SiYnzHskcG82rNvmogMjHcP+R1fuxxVaSUAyd9JfsWjmOXDwmb+zRa7/BY4CVE4vx+gxQaU2xRvbcLV/2tHtXrYzKAAUcumNvTFhPLod/A2or4DrJPxIwJmcG+hncTf0CupOElL/mNzYFdovcepy8O0a5VMotvmOz7ntgNpdIOfrlhOnOyWvMWoye2LJrLDkK3ogbRyLkzx8ZW7Rq11LNyse2Ocfu4be8Ni4otStPc/7kgEWvn/i1K+bWaHMFbY8lIqy80cw9XG68YQ/uC2f8aInb/7SOGk0U+WixvtTRPm7BDV5zhRGiIi7vY4sOoLSnvU71RKN/a9BcViYesUQo1vYVSXfyXw7KyF1mBB7vxy42iP8PX2+6Y0mSZOl5bhGRkWtVo3t+EEOAM+D7Pw4xmBmQINjEgN1VlWtEZGYsc77viKjZjSpQ3d1MVZYjR0TtXjc1u0u59TjR7ZjUfzkvnz65XHXXavDptwX4zjm8mtvsseMXvtqV33ovBaRHVpNk1NjsDZv527hrq02wHetX54EIantrr2FEZzwWm9vi49Y+EaZtbvrccCe3Yk59j9PiwAT+/NGy3RgIpq5GG7l9dReGKOoFwXGhFHCsFr/6rftl3RoyRzTzBgMYHqstdDTF7Zx1iH1bMLYW5n7DiQGY5EmzJ6eyurjR29pipTFbQ9f7DHv86FJsazlGx5c4MxdL31sfscN0/xdqL/QtCnlPLsuqJpOrCK0daI05xzh+aetnLCtw2eG+ep3j08dbfQtRCySXrmjr7Shc2bc1hvM5pmh5qhPZ2mPJjGBQz9ZpEWJv7mCNXWkNyNiJFcXYsu/MBRldxhfvyQHbwYIT0bHbuRA5vgezoXCureMlg3Nx1wy28gCY7igYEtrmYPrZXTxxIec29lCxZVC5UqAz3vyOyfybLlek+sdYSfbwY3FNK3405JY/7oJzwt33neeOJ3fQc6exC3M+tf2y9WQ1AJyotn8tyJoPsYnVxZWL7+l7gh5fFmx7sv7uXV42SqwsuPSbu25r4wnxnAyDz9gaMHckwmbP0E1PbRTZq2NP1tOogfKzg3AgbkbpMoKPOaW/2lhWJwuMwKG66Uwo+3sxGBPBuhcHe3igy8UJPjzt1S+vnr7+85+ePnvWD2ijbm//+D0GoBFz5lzfKybyGOWve9IwNJ15HsXfl/WLE8tzLlQv3Lk7y7qzrIBsjy352ZRFchs6H3KsD2PwrQkryEFkUcP7v2mFK3PHSlmsBZuLNRLJwjx3XHlVAYvpn3/55emnn3/MRYzf5MZXjf34049P3+eT4b/9/runFzluiAk1LkTwgXAvv/4mx+6PqSN3bmnB59e/D0+vfn0lVz4FnUV6xLUJSO8Obx7V7Dy3HiNLxM6PzpO3ARZt9tcctn4J0t91dE8Gzjjw8BhWKDO0eObnbc95NYoF7XHZuqffIo/XNe7jJ+CZGky2Fg3X2A0DuV5M4UPhvIgRLry0nQU1x+0VYoCGOzzRsTgnHhcReNUMn20Ad87nmmO2EIgtxzt9h9lQh31+gU/t8I1dMIix7fhFSL81GO3Esx5b07GhtPC4tx6/cO7bJuDOy9g5fun7+RrJqzIW660R+UpqYoBZ5G7L9+pvj/joOn7kow/8KUrafW67hCh7Zm0BNI2jvjMwhgSxm3g8xsYuLyIRXeUGqxJNg+Noy56eUxC1Ba9i5CW6bvoluEgTHMxOyGLVZ2MX/8IxgWW7PIg5lHqWcSuU0dAXHzvi9R9/BjMe2hkWaFhWvHGq0kbO2o5wMTsb8WMqFovwFNvqHjnq5mOYqQOesWuRDk49x6477eqv8ZHSYY6NSSdt4288/hFt32DkWCdKpejwlTv2igGrLcCGngMJu2Bg50Y7TKYWuKGL8p5juSHVU/za1Y+SOs6mkNUqjM48EKGkuW/U2qhUZdzoa3nxRin36Nba0olf3cl7wgwLsdZXnNHTp+uxMrJVeZign3jYyk17RmkxXqbEEsd9/cZEvs3WaHXEToNFWHHHxmKuiJ+9OadPWx70b97263fFb26DGXdrNn7Gz6a5zlxiYF7Dr0FOjcTfmpjOnRu+DbK8wbKp6nF1OBN71OwKd8/uSNWSC7i0+gmawaKw34BYTV+z8Zv8GgybbfWdbI6rkaKiRvC+2IGHT03bc1hxeF4Wla//HlNazD93LZabnoNVxQwkYb/YV9Ril8v2r5NKXPq4YX6OL+5CVnd4xeah1ssr+63/gJgrU7L21IcjqU3wdBPI3/Vfm3DZk5vxcC6PO50rx2YXEQHVDB7Yw439adhpe5u1jB3d+OBxIqG/52kcEHXIcUB2xcXvQg5G/lHvCfvWCX3xG7fVB6/j1Z34qKaV58wXeRGWTVp12Xeo7EGncZWXXDNxpnf8zEvz8jqZHfzhMdmUC1aLuVEimzm4ahAbE4U1gBk4HkxXXR/5OW+YYVh7H4POX0Q5saP1osD0x26PcQ00EmEOhZ2/as8nAt9otXQVmENi7oK8eUcnvx5/lw13sFgU8R7fLtJZoPty98iHSqhnYTwTtyfOvpQ5/D2p9fjDmsV+F1kuvFn4syCPPjvrTK154TYlf58F+vuc+HqCHj/u1tHnO5Q/RP7h0+DlPe09RlPZT3K3zVjcnetdLMZdFM7ikIQBp+7YlhbbjHt3DLXj8N8F9AiYkbbxHag4V3zwzliJ6imxfHos9fi5YuT4GQDe3//b6ze5U/7H09d/+tPT199/6wKAx+QfuUvsJ6+HPWE86tJpJFNriquXSwlRlvd5SW5f8pv5wT9BmQPArNcWIDoWUuBqV4gr15I1Fqp9pKXrSD7CuknevDqCVz2AOWDZfZZP99472T32goU6APLMnnmn+SqOLATfpDYszn/59Wdf3v467z3nQhKvwODi0R+5gPHv//7/PX2VD4n7pxwvLMq3keOzF1mkv/v66ZcffzzY8CUseo7717++djH2PMeFx9NSjh7brTu49D2epibIkJIrv8wbk8uxiC9NXTvOwZhGgq3mwVxrDNu/TQ9CpYRdua9QgHMeI3BSEQO9x8hFdGolL1GyIT9xwvGOF58er0CRTI6XYLM471tP8p7yvBqBxzTHpXUIkHCxbZ4B9DfjcJOWx0PewuJd9D9Glli56Ofdc+Y8f8wFjWO0i+QgkhY/dNI8frYv+R4z+xaafbztcVSnbEuyQ7gGQ9uDzyKbz03g1QLJl8V5FuW8YoDPQ+hz0gc/HA8/FurEYM8/Mx9X3KP3+DWYscrakjgvjFsn1BS/O/qVZ/4Q838iezfu60fs5S528thDZ2Yep9YLoLT7MWsdB9djdGx4Y5EFwYD6tpBIpSDPZYv/AYKQVpdd8S95AWu0yUtqgm8i1oPgtHIvp4lQnyuOfJI9mCb/wKVybEZ7sJavYQ6HkbIzdjvyTXeLjA9t6J1/5HpbuOp3e+p0PPBdbrIOv7SG0w1shhfzq7+28BFnYhYzsiU2+xN/QY3ARiRZFauildacUYEWH8+dzwmhCDNi3TnheyFcPUje8TfPrbWAgj/O6+HAfw1+sdn5u9eBPu0W8qEflfHHB4ytExHXlf15HIwNY32jq8/N3nhmEZvKxUhf2wLi+eC7NrjUG8m2wZHrnWf0dxnmml5JL5PJtgaqOy/WbmqFq9WGw+CCv/lbe3T54Vff7GwT0vAjwg8xsbuv2zhHPtKpJ5Zr11gduWXDnBuf/szB8KslcTQEKq19OKkfcjsvR6u8ys3b+FuDeF9jsESz9OVTfUOiPRHHMrwOFlZDBNT8v0MlYjZba2wej5fxSw0O+kPuRp844MVqFhrOU+o1UY6NdZiYV93owSb2w7ncB3N1UYs4HBbdPPA2Hj6VdNvjYHUy/oiXxwzG/A3G2ruPHFoeC9lrT3AiDZdTIOym2ZWzxsMKwc1I286l9YsKbTmlFz5QMg62O/1H8wAAIABJREFU9q0i0YdX7VEvn7MHbfzRC8beIArYaFNaU69KKw8AeHKhv7p0fC4c3SqUTYCEFkOT8XV+yGtx3E+e+BEg+o2DpT5CXfJ1V7/zEKG266xRY63ocT+6zQF/+uwpPG325XBhGbcGscGHP4rdnSe/hdIK//pEGLPTZ3hixb2rpnRqB8TW6uzpjJ9znaK7n7sfhwO+wfbPk8SOXaAvGEzSZzG0PODunfOcHHNyyUKaP04+8a09HJJVeLDUI74nkIxyQku+W0tyxZcPhXKRlQXU7/kjNxp+2H7Oia25pVbhwx05eLznK5sy/iK84PgFeHm/LSfgn+RTqxu3WGz7IXTQA6cnzstpSgfpNFiyI3735KaUA9lBFOwjZds+HajqrT05jkE0lTMGV78R6d8g6Xbe+Lop1OT45tXrp59//Ck5ffb0/b/8cxbo3/aEPyAuhP5ggY7f4BoN7zCYGMbLhv3aqcqARV/nhVpGn4XS/38TbTMK6ALXiyGNOAR0SJxGV1c9sZESl+OBOUw/xwU+zDULMPTvciGoHLso59jh7RW8ooCXsfOe819+/SX9N/0AvVmcwwFsjq2//e0vcmYR9V0ucjj/wQeXBebzL5/nJfJfpt6v5NI5b3pkQbxXuQjARYovnvVr2MgDfrbsGm+Hres+7luOGI0dxp03Z0IcY6KXKXUJVtXXvvAb9djUDE8B1G8OxLJ+ELTtfkZwSTDnY/idcZCQU/OhBZwNfi7OUw9qgh2fI/A+F0V47z+G9xxxK66qwSg+i9f3mQ/uoLPQ//yPvtydY4LY1BlfHhMk9+m8ksG8zLp2zSGL4YlFEGTe6c480/e5hwsIk7NEsCPB/CKHuw3fPPb2U/D5qjo+x4BFORclOEbNPceFF5xi7/MXaJFZt8Dx/AUkrzKi4zgBMkojFkYO5tSiR5YskKM+g6EHz1vb3G9ml9YQtVfvGLWjphs1GNuw5mlv69KXuK9Bseow/QdHgLeQRy9UcsmkT+Dtn8kwS6Liv4iQmsF064ceAdrqb5bK734+h2u7Xhno0Hjnnzw2HhxjnJ2toVBmyEPtzqmyMml+luojW2NEsf9P7vElQ9zFTjzcHyYWB2Ts7XRcgrUtrXLDypYOMWkr2xoaA6kKNn1Qbp46FbTd8Lc+cSjG+AzG6hwmJmGFxjqDPcg2Ptoi3XJvpDruMRGZPoz93fiNsS4nnp0YsseTf5ScXPSRdOTlliHk0qy3/1TxLZrbko+s+WuM/bA3r9h0H8X4rp37yBbm2IWb/TWcY//U0QSGG7Bj3+OZUTm0c7KZcNR0Gtx2ZAw8iwuCuOiPaDx3DMw5doslx+FbZhiNjm7aiWmfTXHvjzfs2qJT3Rq3RneEkinC5p6I1npcC5BtbEeOlyhxtP4Em37jdoyy0eJBrirbXyyRUABKS9/HVnwbZ4QqBye75ahYboQoidU1XrdFG6yKDjfi7MlFLZDc2tZYUfLA31rc5xkfchzwG/tzLGgByD03Rs25CNUuCta0HV/HeeUoiEnOm+NyWEbGnxwIhu3BAXhqvXHwOwGx16lxUKnDKH/i0Hlot7qMvBwyuD//yEOYAwme/GIqNvkB36LHrtjG1qsB6hPdPC8pDX4cD54jZfVheytLhXWx39IgSBs5MvoOR7X1U6eGqIk7/yQqx4fHQ3VF2O2CVqs0xNYPbZ+f6A32YO1xW+sS274cD0pGJDtzfSJNPUwl/dbfIPGcWk8sgwMzcucnY48PlINlTaewzIv5sDtBNY64TBmhq226+MTfXVR1HS5gVN1O+hsfOxtYnOgGgPq4T78vEx57QYlRO3Lx5Dj22J3FOXfQs4A63GLHXaIdg8ZCb++gd8GcvOSfIOPLIuxt3qfqSX0WVSaVTe5LpQw52Q8P75LldNv1AVcruKWe9kneq0ot4Mcf8cHfP7hsf/f15OW38173AnUKgs1JN/EoPAsPF3HUVosEmzoH+HTp26xdTSqYLfromA8WIXBmRD2pCzx5JUL70aQOv73+LR9Q9kugU8MsWL77539++uZP32dBkE+CTmRO8t/lJdzvsvAUcCgsvUbAsorWAinmEkiv1q0Nx0PG/OYPE9Nykz41iXBx9phgQXLacVoJYMnR3NPNj5EjyKWU4DfeWp8LMMHhrjfHKItijjnis0j3pezZ/55FOTqOQe6W895z+mB6kYYbloFnYZWdi/3fg/PDD397+h//+q/O8dff5kLHvPwbW+b7Je9HDw4LfxopZVuu6fM+9defvdafhTpZ0fDH1Noy2GZNNnfBVqND/SpvfT6yCdR9DgknehydixFwbDX2pS958IIgJ5DqtySUx2Sm/nCyo1FzYevjAltjFaGL6dw5zisSOH59ZU2OSY5h4hs9znvcyK6Q6moQrBjyWPt0HsfcmeazJfj7LPPMnIDBBT2M+xjt++r3rjiMhHbSGhsZC2vubvOVbswxao6v33Ih5o981Z6Pw3XWtwMeqzwf+NkFuVv+Rb4yju9tZ4EODrjk7N3xuPBYhRs57wY4HiMc2xSZPLY5FzXUAb/OExYZJT7P+cqzRbdZ4WtjJ2c7dkcjhn3mviDHBWxlSoAIvpiJgO3HDfMovIN+1y1hiB2ARdYpeQzB2hB3kjlBQcSf3TCV4MhIHNuRBbEYZ1+7k2Ps+qTTTE4+YKMzTK1Bmt+JDXosJKPKrj7wo8kxe83KDVkRrxg1RYrpxVFHMRIJouRFA8Nh86tM68YEKqZbx9HEpzG032SCKZbsq1+7ey4TWSv8T+5x2Zq7L3j1ZhpbeMcOn2aPEY6DaiBi28EB0PppetWkHkXCfBfQB1eD6IGzbRwwUB5FuxG1TnYufpqOLRCD5oProY5DNxZ7jB/j2OEHVLeLkqEYxLzbRD+5H3ucnaPL93qwP+JuDeCxjyWZE2Og8YCQcyVk2S1S42qVzXAbO0abo3VfnAB27ou1NsjuDfnKsNQa2ZzgQNKI65Z9bTBOb/BQKwd8BicmHJFjT09MBIg6Xh6Lc/IyngxiXa3HjICgXcfvPd/DzZiE7LG2eXUsgcOn7NgSJzHZpZ25HSyFKsu9LPTAOn91pOdd7rE9HLAK1skRD/kVw/wWHwzw8rhEJKaSrWl9sTp1wc66fqSTl0oh6yPY4A4nFNjeaodka93nZ8YI4VViUo7o5BXx9n3sx2Bo4fl3bfHxesCO5dFtAQ5Q51W+sTMeyNHz00nEqbkholkf9vm75iWEiQ1vUup5szbaRbtN7MFSpgMxirnHc+cBKYp4jR0BwIAvARYP9bZNsbEf82yURhMDmMG516D5g1jgeuycNb488C8b6DR/a7hswK/f1g7Mg5cefuax8pt9n/trD+LWRVbUAue0cpdBRq3QxlE/dSNwfWojj+jEwxA2DZpcLilYODrnAOR5DlMsnJt0ekI9tcEG/waLXblij58NH2KzD17vVDJmochi/GbKyeQE1Af72HBy6SJ9cBaX7Fxc4hWddQsX6bDATAccTqrZ04rLyfHchc++z2H154TWE2/59mXrnABz0gweCzaQ4LUXCt591sW8AazB1LCCkItf+nC1x8D/IV2Yf/75s2Al/i5GUecVA4+LdDB7B2/fPtBEAc7fNGxIlfyoNxi0txH6NoHgwp3377O45K4tONwRf5av9eJltF9+860vZX/OOHcUzZmX+7Jg2ff3OleEbq5wKI3kkXjX0eZRMTqYDFl38U5sLbK3sB6XYwMO84fOvjvtyC8znLcWNMf937VzXnirjaeHe5mFAXWmMcfB5896JD/eC+4C3AtBfMZBP++gn3XQu+fY8n3pLJSJw0JJjnyCdrBo8NvGnLx68+rp//nX/9sP1ftf/7f/lA+I+6Z+mR9QOEb5ZHfmhnlpytQ2KARJ53Ve0YAdOXKntwsz9GTWGmFsThlWEl3s5UW+R47HgCPjfyh1InBioXEMvEDjGEVj1SZqDY5s8h9k44p8QgHGYNrKCYsom30cGDh4MgVXHl2wU3OPTRenccvCl7vn3OXGbEyH+wADf48HpHETIXVl8csH+/2RO+i8feVtFsJcwPI5CMf88TkI1MiahizPFcw9sOpZ2PMXrC9ffjV9jjcY9YIYF+k4xnKUlEB66Msh3+OeRTnf5e5XxuUxyOIczM75FZ/nRBr8zgVQ68TFIvC2CljVlh79asqpsspbkM7tOW60j+3A7bHU4e04ELloIoeLNpQu4jBKJ70WXWu6y019HTXzgvrQ7gLdwZAbBe4Hd6GMQTCUa9gDCYkxj3xH0eMi6XkwgAMCsihXd2GCRj6rY8CvQPoygrH/QNF8ZAsN7JtVBhNzgG8xlaD2ySwup7U7HJrEiaP9iUANCHHLBz5gDt7hUsPqOJAOL7zxKO/WYow3dpXhns7UroOiG0zl+A0ez04r0U+czUuoh9wvHsuivPClB5ZtxO3fNHA4/3CO9ThldzimL7EL6KBMzo7pawef1ngXnsVanpiN7UTb4+KB+y3+Rh54yOlpyHnyPrJq3PqPESdajD3ZCe7itOKlvf61q4vbj4I3VwGzSaYPeEVpyAm8/rHeeNYHiPiumlrxs5Ldr4Fo1lsgvG3UzgaQ5NgvKmlHTxx2GPi82+MeP2OSw2IPJ9lEZn5xwxebPpaBpI7FLs7gMzgYDNqwp3lM2NuYw5U08Jvh1cFJBwI0Jp3+DhK7dayteUUG5/scVXvFxmtt0J061NDtHQtea2NNYrEYGssrNpLGYuwH78QCZ9BBMO9JQXn6+0/s1EwfCwXRuIGe7mAXDrmIRyqHM2rHmoiB/w3h5ntsxlcrAsKX3TkemgsysU5uUNw8x0tHnHU370ZnG+Xm9JDf8qNO4I2tIFdM488//muOMGpbmUEjEiVOPBraX+zyPn7L6cYdXfGMap/nG4DWTE3ygLNNQWLc6+7FhCtuAXZcP7fZuPjZE5sV3uI5HwnU+SYrcBR0r4QI/KAd/XJsuDqMH45LX6zVYovg5LJ4Ea7P2JDv1mDMjU+IbcvI6sVvF3qHUgzP3HMMgJkfG6CbC4KJW223tSjl8dIfTE4gPZGMwj6yTVqmOx+F3rhgmj9PqvhO4F10l29McoKtXRysfeYQDjl9PnHWNgJtQiSA5FkfQm3jPcRg9vuyu8dw71ph9y458cfdN483Iw6CBWiOPXnuKwPQcgx7Ep+T7pcvv04c3s/O+0lzZywn/F4kyAl+j+G9kBGu4MuXTzTP+5xZ3DFHU8e3WVTSfst3aXunNws9+MfIhR1Z0rxzl25oP7389jsXA3ydF19Xxcuwe2GgdePrmt6/y8L8D1763oslAyOWm8Ke7BnyJ6/ErjrbdkwD46jcuMAJGUuGX358Ps4crkvENo9h5y31n5cyg9M6YAKKAuN3XhhTO1QgMufIGHJ3MS/nz53rv/31ry7UqR3HqovyzJXvaabG/sU9zbdAZO//D+Qcf2n4Eas3LJm7HgPIeSk8i/vn+WT3/5DgfPXap3w1VjjwxwLxWe6WcpFgF1/yDD6zT3w+NI67q8iZ2nRuNeqxEBGKZEnC0Ol+Da2vijl2Ro1oz+cKcR1boPmLrUqsCZ+B+KvgsaXG7TpRJ8Og5ESJXX6Ux1/vYGkDHnkhX/y4eExkz53hvv+6y7Z3qde7HKPlEeDxEfOQHV4NremBTmefT9g/zx1vLgoyV2+zYOcija+SEOt6LJl7wnHRkT6f1M8i+suvsjDPXPLYQ87zCLFocGLBzTH2IXfREZA9d+xdkOfYYHHOhxXy6gCeJ8x3LrThz9tmSKDHaN+qw3MMHIlLTblzz3egG5/Y1DJ/NLdsuLADMXT5eTySSnhld72a+Pl8Sn76D64Rbv21m3lo7GzzS+i/a1XN4wotkfN4w7YkcMxIw1o/kKvhIYcd9k2+SQIoKrZjz45CtHW/8ZStigHxeWBPtyIRGndt2MfIIhonAxchGpSDJgUvXgzl0f3JNfHsGzWxF/ckMqlEQbydHCItUZ8Iwt3nwrFTd5lMbASyUbMHTgY28eP4UJ9o1q6pNicdbl1ZZrzo1hKjsVnT3cMVPPRnHkdmHHStsEatUSTyH19tyk+sbOS6gwUKrjnN8VW3CG0aQ6K1VaZDtfik3WuQQSSRu+s+3topZg6Yj7VRA05sTpzOJyYHbzAqQt82nhlUcnLBNT/GId7w0kontBeGgwtMX7T4FWOM3SmRm7WH+sjpbD0UNa1qp17ktPN6sQCDSlVn3tjHHzx1eTyAb/TJ5+RIhK2ffheyvjmoLtvByQ58W3z2+Dmy6Ww+4JBnccZP2cSauMNQruY6XggMN/mjW2zQwB4ne+a9OY2W6FvzwoK4rB65FW9xB3vqpqV99NfxjahZXliHY5Qeu1Oz9ZPsP9yU29oVt7WSGzWPn/Wc2rGj3XNnfB5DDNLqn71cMmoo98Ws3X2rqZsCGEODy0NcZFMnuTVaghHnBgDzDD0hHJfNaPdY77GODLzGbUzxr6TFXx9zcrP8sC5eA0ceX47brZfytZFT5oyTr/zKFVn+TCm+u7geKZqHRmR0xk3vygWxSGI131qe4xPXNNNjM/Z6ZQN2kbEarFsspGKhQx2HjjGvfWNNfxDXlsCe3ObkaO0HRrAzDz2PHwrFwh5+bfhPT+GFR4w+b8Tg2NQT/L9vPQaUW5OtA7ktBP5XZbC9RjdeDxxjpFtjFgFPxIl555I+Y++c08/z6i5a1o541Hb3JVdsttjlN/rePcMOGXE5Sd15cpEOB5Kbtr1iIwxKhJiwCM+ZbLE0DPvMHy9PxmBPsjlJ7kl20eSa+NytIxdOjIH1Parp8DyhLnL49c437AmXE+fEffbiZU7CX+audU7IuUPGCX3itPEBTyy2E083apouuDk552W83L31Lnv2nOy/zQKal0eD8e5tXnaf/fMX+e7tLLjlTz5ZPBCbXLz7mz16F+RWkxjkk5P9t1mk/s7LvXn5dutFrvS3OX/oIoBmVY/H3IOMBGgBsYbixd455IHBnI7/mLpbv1hwHNG6gO0FCbDIywLZn6iQxZ79IGPrnWf2+dnGKwj+mgU6H+rG+8a5MOHdUWoVW/CZI14C7XNwcGECgq9aACgyeUweHAN77MKBO7y/vPrl6b/99/9ijf+X//gfM/f90Lh96wOLtJf5QLnXec95jx1qnjnjokSCcaz9+nPfgvDi0xfhQnq8qoPakWtoyIvt1eSZIfnbqAsm+XMu0tEGf2XoKgO0j5/Ozo4LVJj24ToAq3Qfb2KpApNO426MctAE1UVCR2zJsa9u6cu/u/j1+SQ14ThtDcaXcOHic3LC0ZrX5DLP01uOzltsfLw+ZZE+FxRzjIJB3Xm8iZMNfuaa/rO8B56LLjyOe4GLV1T0cbb4sU78vh2Gl6h/wd35vBqF9jwLexb3vGKFxf3iEKS8+PDKviKGl/Jz4YDjxQsIc4cf3rT1xe+TT7JY9+vuehy2ADOnnYKIrLa+u9n6d7Zv+pnEux7MtZgyO3aOiRF95bVqP1vPkalKbPKnvTPY/vqpSx24zJifmq5yCTvRk0hP0mJN5Ydcg04QCUXi803wCpl9qdR2+3OwSBLDtBqcve7C9MDexMXtpiHmqhT+UD0wd57pm9vIGhCK67DFjL82JdQDv9VBIgYHuINuTswbV5A5yHp3KijU5iF29GkirTz7u10t1i6WE9YdQREw0CSb9V/giJa/po4XZn1Fw+NACaeEjRWKrtxWXC/qUmvnRvOpoznF++O8D3h99/g6e+Lk514rMO6NUdO+xZbQcCRmbNYPbuU7ucftioehv7HBL5b5Xd9G+EfR8WkcfMyTvdymKsTx54YC9v5zxn/mDEvxciwXtzwCDFkIzb56AxFr6hz3clhb8UDt341BJB/VZ7B3gYEP9ocHGMNTHfYLOPGQ09a3nXDF9si3vpGnBthsvfXXtkhTQQLnMQTGBkwv41qBHEugNu8bH92i13bkoqwt7umLX+PiIacRR9tG35i7x3e5iAuPPDdsznhddYt8uQQaDHPEx3736bYBeONpzMPFaNrJj1641mXYDa5Rxnw0B1futxyEmc2d08nHehALiCv3ex2OHID8rW8pdFsetzrtPxahU7N5Pl9fodhMjukxyJ9CexXNfKExVPSacJRFEH8E/NSfXeuWHgM19PQwX2zTHuwQDMbSQGSMoosQk5MDc3fa8JRjhELN/GFzNx2fNV22RpnY5EpXGzhPvzC34+52/KATQ2NQ8RtPgQZv4rNDXIvyL/LQjYJcL8x1HDC8+3sBaTIx78fTxFqHXRRsdNzwohlzHnPmEBwvpMi2Nh/PXfNoXPie3IcKY9twon9/nG3sGl2slItRhJQDgnLk+W4X6i3AeDMntOzkNSDLgZNd7va7jwWfmK45eaKj5mDw63mJAH1Oi6HH33DACFsWXSy4OJFlIbSNxevKe/ec94Nzx5KVULA8gc8Je/aeNJ9FWNiiU78Ls8GVX3Bz5/P5ly+fXn719dMLFua5U8YJdfF3kdnFfaxbs/h2oZbFWRbhnNRzhzU01ffl0LnrlwXC199xB4/3p3JyHrzcdWNRTj7IqAP5Wg/qAtcsOrjzzok/VetCx076qasLQBKnxpFn0//d02eXPyauT1kzF4z9qZJjTN/IsHfOmKvYLTcsRTNW4mSvJDHJZ8cA2I86y6ind/nUfM/gJ2/vaIJEIDegEIg9rbilVGxeyvz//o9/tdbP80Fc1OlFFst+7Vb63DHfBXp5kCe1ZI55P3znH3Re3UCot3woV/yw/8Ad3ki58PLTLz89/Z//13/Lwuz505//6Z9yYeV1vsLuF4+J7/78T72Lnnn+Pa+E2Jy9IEMKiflHLpzw1gReQcGHhH3IS+tpbKmznGIHB2OjzMDxOe9COHPF3tH457FWRGyQrV1HYjHZ+QW/cxsdeToGuZgAKQum3AZCmQcMkaeZAKAZj9jHdYaB9Tjxoklqyvxgx4c28qFwu3gu0jjrNNhENy/A09Cxmw2HCZjMcVvqGptdEL/IAvn3HCOtb5/HPs3cv/zqmy6qOVaWV8DAu7gTJX/K87yTi2d8yJsfyBgZzwVclOGCnRfUgtPjPcdQFuI83vgMAh737HdxzvMCj394suDnuYQ4J276PJ6bZTlga2O3NR6LlSsmgbTO2cxxBXNuMjjktJgCNn6fI/AGJEfQHHcM/2GL4cI8Hn3I8woDDyhIJe4miEf/MY5MBA7XyGM3FAVoOkiqX6V5jt/qPOBjuUTqBQKgOxqcWzbGxSrPCeIS63DEr61IFLVw7KdU5qbP8CSPibygYsIDebUwYzycxmH5U6/a6oDxuFW6HIl1cLfWiMDWJ/bEjQ4fmnPRrpZg77BRGRFnuI1fBKcdvJjWEhW9RFZWXzmM12NGV+7ywcY4G7tOWyOxgU9b2da8kZqjucJ7OWe/cXVXHolUIZrOhozOrjLyuOo2obXvgycSMSaWw3jnCXLjVQ/j8SZcfhoFeVpitUZEXq7Dg7FEVckNl21yzUBrsA0DBsLZw+syPLaYnDzQ3xr+rW068CsiA/1Xf3M5NnBZzgfjGOo5o0NY+50vj6tg8Nt2+chDVWPg00rFUvuNfZyFYHSvuvziS1Nnjs0Zy1twhLVZSGwxoYHRX70cR2ku0X0cp05ECIB+sQEmP4XMtgL1OePtHK0stscO/DHuHvQlOTGAgyOER2U2ipCtbnK8c4nK+WtA/csTQcHu8yxWNMiMCfaxbKd1q7wM01e4som5foMBDiHJUw66tc7Ea71jM1z3YkaH9RHCfGu2EQ2xfg0zMBGOPb4069HeqMAuLwjaN/8ZVTkea9d9sRJD+/qaB3jWRLdNKYPD+MSe4PKq9Z3jurRqxFn+4ie3w51U88/eRi34y7D62z6CUqvBOe6sE/O+tusJFLZpxOeEwmMauzl+41sb9mm4pv1dPwL5Q4B4YzOhxfD9dTeFLAavYlHTTXS6g1NcpNCcOk0czXCOUj19WzT8rvC2p4t1fTOqQOxRXWCqJ3eVxys2UcJjAFy85AQSudR3zgZ/0jkou6hcfwhzDk57lxMeTp6znBTvs8TxTqoxuRdCcpkZ4g8HVA2VreIuyqm7L1/PSTKm3C3mxLrHcxfJLJiJ92nulvbl3sXdu2h+Ajx3tBKEBRcLXfNMRPos/k06eo4Xcnvx5Vd+5zUn49wl404bL2nvy9Rvi+Zh3cyBAbOLdOKzmOYl7HzXMyfkX7LYz4l9X/acSuSY1cfY8Y/v2/dZ0LPSTnvL4jH8eAkvOfIybvYUKZH0jZe2LArtd1gpuKSnBV71y+40H58Zo1tLsLfZAySNfrszFj/9KPb4jkjLzevsp+7YkTdZFK9YEeKYpnQoClxpgc0fDBY+z/iUbF5CnWPgs0/zvt/sefkxNVr54jHHQsSXRfG7wcOO9/zztgU+XM5jiVdlTO2pDHfS/+t//T+e/vO7/105r6z4Mm934AILsZlXFp2+V3niMB1cDqBgb3IMeGEnvL74NK+CIFfKFluONxp9W+RUpLVB0uOywmtmdr6wxQPNysQd+SRdQGVTB/uXeKJHkB5/4S2JbtZz5rnOxlmziJa3nYy96JT60ODHceyrD0pavs0b/vhHMbpbOfSHT/HLlGOAmm57/+x9Hrcv5u51L7rxShXmh7vm333/vXe//aA6sKbu4NCKSq9jxZknjgc+8I3GBRYuru3nPfhcFDlz/zZfbcgCnVfI8Jhngc6+71/Hm+cyPtG9n2TP8wGLf2rkK2QwkQXzA5uL0dbE/Ee8b3mq13WM7P8NMTgA47SVK+Q8Bww+mD4P8ZyvbX2MKQ8soqIgmiy/S4bt/XkkL3HnQTakbnlUFuORAc0fB0dJEoqGQTUN3LH+EunYOPhG1kVHPcd1UC5boUF2duERXx6pEoqd3eFC+GnLbdxObpuj/KPc/HQL3ENepgP2cIQ3o4mzd3nKpZNkXlfQeMZj+G5WxMBnYMo4g8MFw7RTR/BGFmH94r9c1w/mvWARAAAgAElEQVQ8ytJaEQOQwX3gBHoBsV3/MYfx6LPXv/blkz7qwcP349b8MMOQSMl14jBWqhu94TG99cBOPpdJBCIP7qJjuZjLZVBij9XWCcQtg52Yr+4xj42z2CVhnQAwzMhq0q3ycugcQBmsyjAqs+V0c6O7tdz92DfcxG3YqcHfIyPZymzNO29B2TkQA7uEnCcRwl/x081wc2Cw9UF28CavrbEYZ1Nu2B7fm46uXLeexMgPnKhS943b0eRFbeCQn8u+HtcY9mnupu9wck6/JbjGzb2o1R4jO5uzvOBMAzpd+TnP44lMXXNXL1v0dRpXYQQa+xGc3UQykMff5WEO1AJI65yOPLGOjHqoy/PP+pYLINXhX10jWcOxn1Bnp93JPf5pbJdjJRndBMthja1wyB2/c6yvU3PRPqJzfBp3I2B75ercRVQpqto1hhFjXXtyoGmbPntr4tlteWmgR3tuD/hNRle4bOQXo7Ez3g6wi3xjM6RhatuaZgA9/i9e84RFRuufE4Q1ly32gmAWOwHwHk4zBjiS2tIBc2w6/8hUlEOwVg6++UhirS77xm8tRZA/ubTmJ/bt/3Z9NkbzMzCwxlm2jV5ZVM7TxJ44Mhpud65bb1SHQysAgK2PaxCau7x0GP7Y+ytIulrEF4/1wYBqruTCa5TKl09l3RKfP04oOXHVhvjJLd9aZmwsuzAJzixWXQSjiJ2Vwoc/OHDhmSeAjHszo7racfIavCzuuIjwmS8BZZ4wj1+UnuRm35N1MHsni4XAH/lzUeDCnFhhFg57QiyDmRewwGRx/lU+eI0PBvMuGYuw3E2noScnFva+uoB+/MH0zjn5svhLXBbo3FWlsdD/6tvgZc8JeZB6ty0vb59qOVNw8C5aTtzB9A45yUbL3cfWy+pGQt0iydB9atnscaVGwWq1I5/6ynXsLbDQ2dDIpTo65dJaq0Wn1W1PPXDSoHJxhklrM0pYxJa6gF3rXCBhkQUGMTeB4b2IIFj7HCcu+lIfF+Xx5W4kF3GeZU+fDwwj9x6jxYYhNYj3zFNu4seXOWMet08MFlGfpPy5AeunUX+ZtzdwIeBlFmZv8r50FmjffPcnPy2fGDRe+v4hd1V/+emnLkCVDvup0a+//CpnHgufhOdppE6++SV/uPLXVtZu0a/Y/WXFEO43RyQZ1oaeNtmsF1j0HzEjm7lIYXABODbD4x4jjlxs8+JbzMiLfnnEFz8fU8x1cKl1LjB5gUwJ8WvXuR/+xDfixbD1CfZo6t5YHD9wZt64OMNcsFD+IwvmDx9+f/oyjzkW5y/yaph9rpDjiV00UzPlR048z/Xr0vjgNz6JPt9rzuMzZFyYJxaPcz6I8M3rfJ1f3rrCnXI4cKzDi2PWu+ZZ4HuMZv95nlP4kLv9bAqeB0idSpNne9tnGA1zEiV6qY5lR5HkuZRaMF+05kknqj5tRHbpNdpNXfRf0YlEbOelGvHBNFZk0KKAwyrVWdcJFp1Osr4ltWnoPID2QR+U3d8xbvZYhckgOVoeM+gOi3NwggmG+9llHIlJaTs2NWGLUhLmchW6OV4FAgf75nmYRVTNygVs8HQbvUN4LBf2HbEPSH8ZfNT00O8jRWUzgfI299grK9uNr+/Uxn/M5hJbzckLt+ZsX0k3MOAPK/bWmH3d6DkHV61Sneg29oOvblOrAWT+8L1yABDDY3CdVI7IB0UIGMNgcehtFGUHKzDw1M386THu3sFuJh66hs8+Pvv2A1zuD4i6TZaTZPXViDMxUZvUzY4HPhdmRtRcYrXx8ZA3mhiZE8KHxjxfddA+m/phWPRuYxeFHDfX7NHp0B7RbrEaW9X4LLqY+EMurZksFqwqK8OJgyFgOrOLnbi1NZep2ckBvTKdB7f4lVzblZYRCG3t7XhqFszWdPjElPrIQYL41qe5PfqjrX3trBvdtF0EXVjru9XDKHEjpn57vOKHJQyLV7/KYj7HzIVrNHGUgUljXkSJp32Eo6NrY3zN38rKYK3xr6adoA7vle7868Fc8WfsbLXd8S3W2Nxzn8Rbi8N160G0q7/z5rHzUVrkvaTXrtmM/9RIX2DTho6dwmXL71GgKn/m3GYY8iXPC+SubtyxF4t+jz96d/7LRyitIIDRxJ5B89NbK3qnDRc4YIc7AB1PPHTL5Z4f8plbPRZrbSf+YoFMBGyJY//YMq6FCXxkh3LzhdxirkzmY1OcRMEobeOc4y6KuwwMfOpXDwYr31gCZtC5w27aBuLEa8htXdakZGRZGxVD0GxqCQekxvbiQwUe92gkSRx4sA/mRbzzkTEfguQC1/8XY+D/uzjSJjQvxwYT+xWSTiNkH3+/sus4mKEQxOfEGFW+ttw+GV6ftp1R9Nhwgu6CD9v8cGK8J8e8R5k7WPpF76Lt5MaCvLkSFAxO4rkb+s133+UuWT74KXfO79ickHeh0ZfMO05S8GBRvscMJ+ZcGCDHz3LHlA8Y4y4cWHwC/Fu/k3w+OM46wgP+fY/+h/jK6SyyexzthFCLjTWG1+MoKB4j2dO2qv6/RUAgbdhmuDIHYy2Z8c9OPP/BFPv4eXxSxCwvsgKQF6jIMUorTxZvXSEwdpGeGHoQK3XBp/71AzO/tubTPv4sBl88y9dYZf95ji8X6TkOeM85c8HiHSxyxRcf9l7oCQw25aWJc8IYPxq2LMxd8M3LoVn4M/46H9THV9mBETPnlFSfv3wh/quffza/wE1s5rR14EPj8POu6cSi4uYZo/Y/2te5WLcFGjyJqy+exEM4TSwwo7jssGBEe6g2ZEcF1hyHmDJtmR6tg/UwF6Dgl2aM5UqO1Cd/JTU8xr8v6wexcgF2M5zR3ZvMJ0n9oiSc8bPYZW4//aMXWFj48oFx33zzL0/fzp1zP0UewDgVK1vxuqcrIM9lDjBuvnkY5tjKojoLdOJRUd7CwmOeu+RvXudtD5lbP18ir5rh+QY7jheOKY5PF/d5PuFiD88rfso7j33IWOTG62yFyuTvbC0fbbHbptaB9NPrfMwxxawQYMwaCyNSrM0FDfhGrx5gpWPLuHiNhg4LvLplzNesGYDBtAAMBwEn65IIq5Ih5fbxMpFhd5FUc8h/bFcfnEkAbZsEb3EkgYHZsfsHcU+1SGlsSJQDhF/xmxfJ0wpHMZCMbOJqMLLFQ7Z2j/pOzoVTrNokzmBuXsrHpGnFH/4ZaDN8VtbiwJZ22XasaPw2d6Bqt/uHAo8jOtoiO5ADPXIqJ/cq01vjuH6UpazHzB0xzQE0+kjHb2E0BAiBuqJunXfetNvN8IZM9VWIaR2BAmfim9PEn0CbO56HI4O4ebLDgulwumpUdjEznzHQbzRwi3jxW7uykR+cMBjXU5cIOvcSKo+VmSf4t/ozOsd2Yy+n4jQa1ASbgEeajotCk9zYQyoe2lk3AYg8wvQMR57bv8Ug/3rrc5+Hh5oQnxpqX49mAaxK8bXZsWEW/6ppJTI+voxOHW4xpEZcsDpgyjuukxonH7vE3roWsbbWI/r1PXgTS5DMz/GnVgjVT3zymmY3YM29+819Y8GpHvinl19s4KWcfmzKaoAHszncgum3eMhjCFTakSqaWCoImI52YzxOB5/4YOcXTis3HBjbyGU4YNyY2UfeGpFKsYrRvE59Fkffdbkytx6x6cJluIJN27iGqs4YE8/jG/7o62HfAQLlrXmH4NZyew2VEb8aoaFfO8x7fCqOorm2DrXdOuDykIee8RMX0Fst43qvFzaiYatDsRYbqQYcqw6G1yTfENe8CBPLi3vnzvHEHhh3oNa2e/pDw93GbPTWFMdz3Iwx4wJunbQ6WOokG8T+FoPiW5/m1aDFMibqAmdbuRwHvkosVqfx+AitqhbHs0bZEsPFlgvoivdOIcfyLs45ARe0YRIttZjnDxQszFlw9g5bosFb4hMzfYeGoMfL1xM7a1P8MGYhw5hYvGSeO6Wc3PMSYU7+uwDoYp5FH4txTpp/5/2fuYv1G98B7sL5/RPvVf4knOBAjuTCMUpk7rjyNUtfZ2HO+0t5CSsn1ORALZhLFuP8iZ/3lrIA50IAOhcj4M0fKa2cT3jm0765e0ct3uTrt37/7XVy5aWzOenPS7Mh4eECmW329/jqMSTZ6F3gkAMCjpc4Mw2MnYfFeNhP3WMLzxnpF2LKOhinjc/qJAqxIzvH9WJjl+DMyVmkm0zlmFkLYkbOQgqm7z/lg926sAKCGnJ6YBax3QZX24oyZm6eZ+HMHOBHbBfl0flZBOMj5nIhh8iRlcPknNWna2WuBCUGi/wvcqy84KXMvAx5FtLcgvwyr6749k9/0p+7ps8yf3yVV4Cl2K9ee5f3qP+a97H3Ikvj9UPseO/8q3ygHIuzZ89Z4Keq+XMu7vPSyRRz75oyx4RBxR/tzDc45AnWyTcGiMayx0Xn8UJQWTzwFzO58rjj8YJthmw7R2MncsEvEMewgkpqffjw/vC+mqX8YkESNXSHXNE+rw+WeRuBWtUNW/BlFSdqTE0/y1euvX+f2ud4/u77Pz99nVfC8LjjsUaw488IrB5worMpIjrqWAF9L9tE6UWmXGDjucaFeR7Lr/P5AizO90Pk4MJL6vFzYU78/LFYd2FOP1yx84MvDbQUmheV4Ac+sJLm1isSurSbiOzGp1717/HgjER87NPBanGK1VG9kVS/Psd2+c4ee/GDtpjeQRfBTVypNk8yPFgy/IcHKd5pggE+EdntZKO9FwYjD4ahIDYb/n/4Dwzrxez+FEZ5NmCw25bY+mSzmiZGgu1hoM36kN/4ITK/yQc5xpjQFuNgH98b/ljugY6tNbjFAEcM8IeXvQ3EwGh0it1aIYavv+JuDSthq/PlD/fCpNP+WjBsaifBMyfWQX10+b3GBMeePQht5IgNIrJbnrWc+lRpTLvxuU5Sxwe4dK2bSPfa4kUr6sb8eF+bWoGENXyslTGLH4E11H5SMnhs4FBHXDNWv3mUR4+Hy87pJN4tFjG2bU4z+4GcoGNinBjLk33+qA8Q6LBmoPzWp0vz5L+9bAdURUZ7kQGUAl4mGZ/HN/z13j2pVyI/fMHmGECs6qrthpVlzDwH0Sj98TnHknUGDxB2F84eFztn+oyp9U0+dYNnubRurW4RkQ82dSPPW4zabxkAb4N7z+XjO35qzB37xiz9yw8e5h1jw6qCQwT4Jv9h0/HYK8NWOyOdzcZCYA1Gs6Yb0xP4wduc7/kdnMQph2wFkSToGVczaZ5aERKNWn0uLtYAg7Q9PpplcTfjwz0OVOmK1VoPeuVDafnrEVJlN7HYnfmojO1j7EqqTQUG11jpb03cSykRjk294GmOl/OZB4+lOExJjA3WRqW3fBrDzH1My0FPrINxChlLuKgrVrfYtVmX2O8JpvGzwefUGczb8SYe6ZlHOeNnsOz2cbH+6hpOH8a6HozLR+7qwZ1cxpfdhXVlIt7YnD61XhPqQcv46DNUemqlRTfHHoe7B+qCtK53H/AmjuLO3rpvvtb1EBNNP2nEaCm716kxil292zi0zlDEmjG23aPjxBtK+g415Cx0eS7l/iXvF+drl7q8i23snDdsgubJLqhzHgUWn/bNiasLAuRZzH34NDIQT257sh2P2MKCE2Y+IIq/N7wH9Lc3fhUXC/beNWcxBAcWcHkFQDgQh+Zd0izGXn79jQt0FtPIcGAhzCeEg8/iipfNvsmHhPHhT30JbS8WnBPv+HnhIL7Eup+gI38Xv99z0QCsfFpYXhqbD416Psc5PsnZGlpTjtK27UUbQaQUOfudVc2PrRaOCkMea2laH/lFv7W9AwWBHBonfeKuzG4w4Sw2grtzdCPax2rnezJIXd+9w74+HC9ezMlME9KwysDp384Xi5rnmaPvvv3+6Ycf/+o8ouOvC7H4p79smkOykFAjItvFGX6o9iXSvM+Y77Zmkc5bGzgGYcdnHHABh/n55aef5fD5F7nAQNzYiZlp4QKPx2EWbhtz82R+f88x5J30HIf4ebEJtvlNppS4fR4E1PdKhCRitoKxxZ4azZ7dY4N9tBgApns21qO6mZWaZMsYHy8EzflQawZI/jj+hLr5ixstx5Jx4I4+f1yUIR5/YwdMft24hx7jSrVFjqz7bIMHfLkFmTij9ZU94cVnA/z5n/N1iNH1mww2IJDFwMWa4J/+RpmSSBNpdfXh/9i7vM2EUzrulHOhjZe083zA8wPxeG7pXfMuwHkZO6/w6R10Ful9WTthKaEXIrP1WXIeg+UIo62tZMVfHdTQ8wtHLJUFGBt0VVWurhaxdEbiFIuxVTa+A9RaOejGudS+40Uu3jIAlk9xlxSGkwTWxis5NRCgXUhDrmBqh+RkczOeRDGC+Jxob+KbHPAQ2mYBM9g9cqkZZ0bp42EhlSdF8hGHdE3F8d3mxIkxj5lt2p9/cpUuhiMGaesCDrhGUpiayWOtooHQ+LRHXYdjBPgu3kFGoPHUDoCPWrHwGOPsDJXN8sLFvE9OjWRMazQ8NJwAF9xQuHNIv9K/z8E6FMMo4pB/s+qQXBsA/pesfQT7/23Y3HbDw/pO9mDPHIC1NbM7dUB2OGNbI231Ea84kp08ylMLlIM9QSRfCyRAdt47l6hp4z3+GEXoASdA5ybC43u4wLLzWLodC3rfkA8FrpE+qwbq8F7+Q2jnBFsp3ZwcUzs1Rd7+hNFa2dTq5t5uKMmfkYuGiaI8MZfy8OlBksHGdR/fkmlYbbPRLPyCcYkQEovNNcfqBya7ttQCuY+LlbkHo/4FG3Nsb3adqwg073y3zrVq3o28c3ie8yLu8T0c41LLBiA87OR25rayQwGH2J36jmJ90IF+zX3tMeuxgj5t8In3OJ58PWaCg6kW9BtcexTWi07awVv/+i3PrfdEk79u5wm42MWamBZk6hFFGQRB081xHie3nDfmPq5K+zqml/9yWu7EPjKJdHO3F+vUZutTv1pXZj+O5mudYEWZyCcdNvllvPj4aBNJravH1rm7GdYL64lhDzt83Bij8RZNo25iCJzxLCiDOZ7RGOvyW5atKabUPT7mU7/qGlu+jeSWONtOzBEaZfonDsZg53yBarRJym7nKdYn/nCmAJOZ/GqtHfnxc6HQi73yuqkbMVy2Aofjwm+UASvv5Qn1+GZhwCLEB/2o4CQEHX5dSA4I8awredXBuNhpn475zVj2WfAkRr9+izkplt8FHIj+u8npK65wju2H+TT4jRWhcRlzZ5s7WL/lxPl1Xm7KAv1V9pmIp5d5qTrflcwHe3GC7AI9iyouMoDLS9m//vbbpy+zsOKDm3Zx7h3z3EZkscVinDufr3559fTzLz/7AVCh5Z0yP6gsJ+F8OnkX/+EL58i2Ts2vJ/As/lg+uvjPceIifeoH5mefd7GJj3i5+9eqthbYgN+6tAaXrJarp+xywSAN7foxJ/bZ8jtzdwzjiJ62eB1VYE5izFEU48puHguAC3OIPaTSfKuAvW64CMPrJLLSZtqwsH5rjwR8avrlVy+f/pQ72T/99ANimxzBNsYcw9HcY1ZXDr1w0wVUP/WdO+d5j7HvD+5Lk1m8c5c+gX37A59JwMuZ+8n8ueDyInOeizLL0TnL3dGX3/ChcfkMghyPtF4E4JUYHHNP+Vq21+byVd768Alvo0C4jfJkuLIZ9jkluZODBmO/ns7CDOCjP7XALhvGjhQMPvLBYbd97LTPROQSVJ4KYphaaLNcI9pjZqKoN9Y8PzQUWKgmGEL+kCHKnqEC4gy+OSivKd0rrzVLZHIUIMdFLrJ9M3evqf9vr/P1g14cKLzH4ERrYBw7J+zFKZlLDVFj8CqAzGlemcMFljd5rznHAY3nDI4hFuP2M97nGe/sR87FGC/kpDZ9RVLqAjb58tgzePrw4wnQbnJTjzRyZDQ4xgeXznPtW7M10nJi4FP52RpvbKbm6ArNtk2OdE8sLW5UGNceWzicT3H/mFCDf3Rwxr2BKUhbD76MecAgmuJQhErAiJyNVWghjDfJkLDdcNNv5I2RbTvWvlG7vWNs34dO4gBhkvAIrsWHHq5yrJ5+wxEEAozTxwYMHQQb2ejEGQz6IqPjNxiRTEVGK9DI2keBHQ1J+wIcvo0fXTh1jmpdjvTT5Lv+cLjF8uArn52TjVlnzG/2hn/kf+zTgY/WdQkEtlbdvUmgW8wW11DgnHkCZ2wWSn1sQKtDJNi4G9kdNyIx2McGfxp5ul/bi1R6w3V5Hdh20F+qSybg8uogASGWAYGNtXWouN7Z5nfna4/vK/fUryZiNAdYbLvVN/HWz5CcvC7Z5SYnIsdi8p9deSws+zE5GDHE8zR452ePGwAGufvE8h/OcIDbxXtQRiAH9P5jDO7sa3WI3PKLbHx9DByc1uNwkXBZyw236SyfmpTbVb/Bn5zJkoAP82MtYYg0/j4xxy5ysUe/cUo4ltahlWMOmmv8DHH5LpeY6EqKxiFxwhDaNr7pX7Gq8UgxnkpDoLl8a3dwgcaemDQMyYt45kOdwpFjK3O0uWhbo3Zna5xNAMwI5ISe/j4wsdm6qdIziCWCDxJH4gEghJryR3/jPnFXN1APOEbZ2MlJTIThsq/awO88BjAoiTsjRTPdWEyt6OlszPohK++HuTJeFJObuZac1lsHfAGzGmMLHU3dxtKQktS84hnHUPsYKcn+8i3QNacz1xPnmoGJgSd4BoxvAEEFbx+/6mBBcdKMzVArRUrRyucjXfGiXYPsNxzexqFD7M1la6nPomKQ4xXbWyT7sd+ch6ZWBhrrDa/31KNGj9v6E4efi7b4xln7VGAWw31+Zxz7bIjFA7DHnEKSW8fusdN2/PaxCEjafqBUsRerrgRiCSCnvNy4j+WsC+b56wMLt4nXfe6Q5SubvLvNy9pz4szdaRbov776NV+L9Pbpa767nJcr53uLOWHuSTTL4/JkMeb7zn1Z+5cu4OHByT24LMw5yf/xhx+e+JCvX/MhYVwEIEcW+3vyzwKsd/NbEuYfmy7McgEhi4RP8/VanKC//Ppl8PN+5eBTj74Ef/axe/sHdeGOXD7sLvsvnvVu3B5Tvnohs2hFtx6nhD1mzqzEqDPeOSdvJB4E9PEn0ODpd2SXfOCpmrbY2RdiMLqqNpBWNRI/h5SvcB26xmV+WeBRB2rFBZj3uSLjp/7HnEUM9p1rwNICTJ35ILBvclGFT14nFinssaFNZIxNrW7lkWOAufiCePnh5exnQcUi6yysuCMeDrF3rnOc8Gn+HBMsunkJM3PLKyF4ST2cPs+FFRp84McinbdAbH6ff5GX5OeCD7bI3uS46p3VL6wDfrTlLBJC64Qif9ajNi3vPp6bT//Xx+60ccoOy50z1Nbn2E19Jwh2vnpl7EI6PHrxZF3kqVvAJwx75Geex/jMTcaarj0JKVnUdQAHo+GZfvkCXhvGXODjOOJx9Ox5Hr+5wHIeJzzec7HEV7pM7r4iQPdib7HlO6KidwsFn7MwyB/+fV7IW2eyOL/uiHMx7fr8Az9jIPO8F9h4ZQe2cIvYchouG/dTx5Nzwper2lMhaGiTx439fX7Vnk1+eY5ud/wQghchzZgcDRMb2cMAQRG6neca7TjO0DZ+sYpt3aPE53NInkkXBbc0KkpXlBxmh5VaxSrHHJqnKGsLHhQyrr8BBFjbZjuxsvOAxt74Q2BP8kom/pFHzz8n/A9qxogQsG8J6K+i+JjYjJferQaNW3UP5Onn4EV3lxkFGbrbBMOn0R995FY2cYV3LWtdng8xJhlrm761iT9eywOTu1xOtQCWMK2ldo2xivVjfLgIXhS3chiMh/4ZaHZlApoVL6/b/FhbtJN7fZil5pRduUKaHLK3hxzY2bYeaJDE/zyQWtOTixZ1BnLzBUsOmbvlqumMeHJu5Phgo3Nkg6FPBs0nwjkxxIvW7foqarx2T+ytg2l5fMVgjjFNjTdO7G5jYmw98S+32kQjf/QfHyfY+licnBYDO9rWaLOoVEW1a3fDNjieRwbKcAiA8xWdmAIihEhF7IVd7IjVoR6ZuQfDGPNYBNL87AzcsR/m2S0XVPtPx4Bn3hrQOYdafqzLQGxf+XCCeklP3Aw3RXXoE/n4OA5uYvKz+ShmwO86og5ZhnIe+dYXn6FmhGJk24KU+wo1FNDHiXFFxhx5DeV56hHhBJerfeyK0zi4Dkc0uGBXR2H1pUfOyy16/Dbw4WAM7FChF+zUoSMQ0dW7ModKdR19pRNFF+Z0ow7AHceY69V9eZbJ1t6Yg4fVNb58lCUYNcFU1jufNasUQ2zQ1akCtmuvLspjl/4UuzapSGy2DeQO5Vdtt3UFr9ltPeuwOJ2HxT9gIXHqMKY7xsb/g0PAY2MKDj3sjNVEJ2dqhAPOBbxSuXM0/dppO5v1xT1/IDVKeVbY+hDfFsP7vCIbjRzhAYZCeNdLKLrDUpvFQchiwXnAAaPZW58Mcnpw6VG70hr02C9uVDY4WLPYUbeNdYeHqy+NjgcnoSfHjLHTlroz6VkTUIIuhMmxfFRlwdC73P16KxboLM7f5P3dfF0W34vtXz6cjYWcd7BccIHZSHzPOZ+uzoKKk2ryYfHEnbJ3WXy9zp2yH/72w9OP+ePOOU0+MXz7G5+q3rtnnLRTjdYDabhObeHOQo7a7YeDoeNDq1ykZrHXx0L8Uxtyskbpg8tbBcDgfwALjogtErUmojWpiLC21TnGIK2qHif1o8bVdA9sMCNzT6D1HVyuoKwYDB9r2KAHJHvkdayTx1L+910mA5qdecXvE9/wDER11MfnX/fEyTAb5CyMubDCAv3bvOSc7xjHb33NCNvFAnL6foZB/Fkwsfg+dzlnoQ82L5XGXH3Gn6TmLP6Yu59+/Mn4uwDbV24wfp/5gR9xubjAZw9wLHGB50Xu+H+Zi0WfxI5C9Duy+/V7zO+zz59pi28rRQWtWEtpCiG1xVfXvDwvIkdedeD8zBxPDfa80HoAyd9pOEZAXOw7MnbrRx0J2zkgPv1ePGnN0Z8WqB4/V/ym1RwAACAASURBVBDsaQfjbjwHmHHxreEljW+i6FEbXoXA1y3m8Tb797wnPI+PD7moR339TId4wJ/HS99OQlVBX7Lp+zycfeyao2HOZmg79qJlLgbChWOIxfbTh37FHs8dxOJY4jHqtwBkz7HEqyuqC7fMDXXbc7nWd8INLTmSc4xv/yZiZPZjzBxI+6zhEGiRDRyt+cGsNzm2R+m2rvTqm51NXuB3lC0KgUeSvqLxIyJPyBasXv0U90asMUZ4jRFBBREazUUoaAZST1fTS78HFEZR1ZxOsDvGaRzTo4+PEvejq2Bs2d3tiksx7vEeijP+xBwm9sq3DDCx1UjQ+0WFpnoVsjh1UWdeGTPI73IxnzpfeWVcfesAClUvzhDI7qq1Bqc2tY5BHJra1hykJTL+cMnP1se6YJa2HDuqHe5rc7hzLMycjSPGF6YsZKIcBsPs7NdvrMpJvysemP5RCPoPLTKdb7lE3xrdDVvTjYOGvg0IcctuYzHPG65+HZ2agbAG01lMxPR3zL6y9NI5NYSAeZU/9YSF/GNnzdd58WKv/8RcZPaNN9GZn2lbD/WLC95lItrqj/1wc3zixgqeGOvPZgZgG3NyGLF5DJ/NT7Pd6JRNbG60iyQHugFHaWDiDDg+0fb4xGY4CCSwuq05+7rihWP+6Go69h0cnU/62Iydi44Mtyne+sh3OIET5ZV/5fohnzhITz/8tj/q7pCf3IElajC0P9SUsVF7bVI6cGlsxzvdU8eR+b9Aq9U0ToIfHvK9/YfDon7p8dtADRWvxsZ/sGJfhhCINCeYBZ+dMK2DTMetR5XOszGBx2NmakSo0qjzUtrIKCtji83ur6FS+G3ts6c1k/RvvM98RNt+52vrLhb+8LvhNLaw2Wil/861tUYDh7HQejFyUoLuLgPncfYy0rkY2PaYxLKcFmNze4hVcOkhp7mPq4w3ftEqxAjOBB4wOQ1Vy6B31OBoW597jcYctLRWdnMb2Mi35ulJLBbLSaNBIU5+rgsAglZWRzlXWszFqR8aAA2SfesJ+p1ThppsTR0rCqbJxjoQzTmdgUO2NAZCr30/ebNXxAtjXTNQX3Byfurjbj+5vRdGiFO9ePTT8S6x9eF9pLn7vB9WFRlYyFjc944WX2fUO+i8/5yXnnKy/FUWRC/zwW+8pJwTak+gg088/vi6JBZRfm1S7rzRuuDKp8Dn7hiL859++PHph7/+7enHn3607n74U068tZ27aby0/sPTc2W+1zaxLVISSRj5ukiIhXdk5+QdB+tPbeJjjeKQG3Ft5opNFui5YMDe4jAXe5zE3nmv6NrG1zljvmbyztwUXVvN4IhMvgLrK/eKzQOTkHCngIsGN2xqOsSO/1nYREfVfDrCLK327ft5BYFmoUvzWGGxaw2umPhg4ysRsuj9D//yL09/+bd/s3aLx7Hj+7pZDAGWMYsq9PzZn/Eu0Hfhr834ucDKccFdWb5f+1Vels5xwQfHebEFuwTwYs5nb3OMZeKkmo0XY3IMfpeLCH/OnVUWb8QXmzl78fTlu69clHtB6F2/f905hvO2TT2ZcHxM6QxjX311Kgmt7zje+vUfrROPEofFhtfGaF/3wcCfQ5A8MvWzSG+cqfRlnh41Nebgc7ebu9ku7jl2mAPthv8mkL2xBs0+fInvrhex3uYx0eeBcuKrzViQ9yLLHEep+95F17npE3XmqkHMIiLUxEDpsct+ThbIm2OPz5v4Kq+m4BsiOH784+64+uzjvRdqds7hFLU26hkEWyG7/Pj4JHh0nYeRaSkpDG24j6kdtOKOLXHBqLyxRNCpGI3RPtu1dc5WHNfNH4PjI4EarUz/4fV5QRrYhBIYUjsJ56qRgS/dkhzPCR69sdTaK1a6Qo5/h6cgGiKLW/3Zp8cgk7qJNgGBqjITHFe2PkDDZSYodmsKKDjbtNF2cdDEYkzWerHQXjJMj2GDYDDt1PGEm0525jc81g4oUubv3nbMvgiL03rjb77uL8/6JZKOl0/rdefQjBaHIPcaldFVTyLwBElM2toab+ZCpjdezK2Jbb123GDR3bKLbrH8xxIbx4ZLb/RCoTAmPgVtNojL8RwLccAcvuKxFXPiHWmFm1+NOmONUj3c7sdFoB1vDMeGiN3hGLTxQ08TDRl84Ta8+3goWi2xXaxW3ZzFHk5hUA35F1yfieM8AKYyO90wrGxPUpVkMxDu9QnP7mufYLVBTptxpWzLpzlfuWO92Otz1cXoGA/k5IyPsgfvCBMj8np1y7jO3e/sNWhkW7PZY65nOni0j1n5d/6IcYsSQ2xtiI2JPf4Kjv3OAbb2jdvRYh+seG0+xcLukcfaEseI4NWs+82/I60auTkt13WD9OER30Eb9I3W/A//yR7t1rtZj/3gMOrjmBiwyB4f91PTW0y9NbR37PhfUF6tRWu0soCJt8gdV9ZYbJ3PW23M2QjRrlwug5Od/wPzQLkj0xd7E1rfjLVjPIt6j6gMMR1tczpxYDa1xW/Adz5atMhVrRJeYTBDdVMzTv5WvmrJslmedIkZn61jA9zHmN9s1nb2wIEPjVLJlk6kmw8CU5JIrXsRTMOosx/ei6XpQS4e24J3Huoj+qQar4ldzKlnhNYcNbkszJivzpOnu81wgt4EGKogDPfpdU4fuWxtO0mkOHUFl7Y75HIcf+2mJNjkDz2n4A9ROdnlAHCu96iKaBZFxMs9TEP1A574ZHcWr4h6R1mlIw5VXhreT1PnDvqbvPecGn+VhfnL3B1nMcXLiL1jmpNkiEWdBR6Lrujz/nNO4GnEY6Hv4jwfAPWXf/v3p5/zlVk/5OXtzAHfs82JNs1jnCTzyyIBgi7ORxdxW4JpyyI7d/3AcT45YZ9zEWw/SdyexF818UOvYsOXcrP42zj7fejUY9v2wKJPju41YCaQdS4ZYUdbuw4uX3qPPlpEHN/B2T0g/BR35nvsOofR5oP++EAB7rRFZbMO+OaPeeSHHB1nj9nWipeGf5ZPfIe4i+kslPhaMz474PdckGHuuat6X4jLdRZGLtgnlv7Kc6w5D9w1J4OpUWKzoGZh7gfG5QPp4Pc6b5uAG380uPVuez8QkePmc95PzsWk6Nif9xxzR9SMSIDfLvZY8H14n/crv8tnGORCD39W0nrAh0BGY3MaHIiPEiw5zXgC5GFGrauvHbSYv8EdDEK0BQ/ICMr1kmNDDC7EcbhTn84VNvfHRIbB8LkSzeTNcYB9L1Q1Dp83YbBsqVeTrQSeQ8X9vtz+7e+5GMexgX2JumhmzOPrj3wIo3etv7jmiQU1zxHEN/+HcJ0XakjEg0ttiBzc1hp6PV4IzTzzWRFg8vzCPO7jl3Sw3T90K2uHbUCwoXevd2SoVKSzvLRbLqrBr2ErFWFaJVo7bg+co2w/W/PVav3Yj+16AwhqeG3t6CsapPU+MeLx+QmM455QkIDAEwigNE+OZd6CjEltJaBVNk11MS67kQRfmHiS3pLWz+GjHf7aT3KMnbSJw+S3aRVlRreTFHSIRsvQ8RW3kh5Uqt1slrLJxnkctbJBNfpMOuqHOjoJ5ddtDOK8k7Qx8COnyqnKzIG2gDJuvRZnOSzWXkkHqxXuvsdffLfup17oay3WyjNorhscbTlhvbbuEdhGDwagujaHzQl540VdkHbglb+tBUgTxX3j1HProgX/dOngPx7qA75zpW+DDS98ar22DuOvPGp8ajE9/DGaPfO0GBj3ytjFALvKwEGOefLTjyzBGpnR0ofw2GDbNr4ZxHw4rd+YCAS15VQf7cFbfDGuOWy9i2EdNuTAMjzHy8jgt3IYXTmVX+sDT6waW2y40SY/1YwfOA9T07h4Nw+Mi1skpRUuD0fDiZzze9WxeesValetAJ2ccDhNo/HfeSOnNEHaqSciggllSp3hsY/p2iE57s6Nbjoih1c5r+9aZ89v/wM1HgHX3u7k4Yk7/BoXBBpa8H1cJHZbpNvVqHVnWmzWBlkaQo1rQ/gTn27+DlQ65jKS1Ymj7c5HNXIbBGFjQywx8j9JPtnsfDL24YLdFTX9RlgezIO+8MHOgU5utC6F8byhjdxjfFzkBkY65Wxn4h6HC3ufn3ChllLAc1sUuKWd5yuTq/3KdIhcLrNHRn1Ooz/AZ8EysuZANQg0x0C6MEHXVl485sUd+Xgtzewbc7FMCljxhhMY+dlMnUfwJiHPI8JjeYEBC+zE1XYAB6W6+kQTqEV3pNXhBnZ+wCrPqSemlVgr7WNwarClwGz6gbJrTZCnqZJwx5XVQfEtNx6O6sOXE09SEyH7a540+Yeb8s+WX3w2t/T9TnIJ5qQ63hMqNtxlajUIxwk8L4XfhUDv3sGlC10S4tyBH97ry8vaWWC/zEvav84dri+z+OaO93WXFOz85PjmU8D5KjUWYOTXxXk/qZ1PZv4xd83/8pe/PP38009y8r3C5+WqvdtNfPkmAfkG15N0K3IdJz2v6piFBqn7XuQUGT/yDwUXEVxIUBYjFhXi85Lr/HkXFmxe3ZtPk9aQ8bY4nnkbmYckAWN8P17Wbl1rUS7OdQTI7jG0CVY5s08P7AbJPNeJ5YjzGl0qm1wxq273e67ZEDnmU7vlx0KbOvZpKAhc2GCeE8f6Zv3LAun5+xdP33zfl7h/yDy5OA8gC/ByIgfmm8tEbSyWevd7jjWC2CZ+YsCRRR5z/kVevszFnJ/zSgo+K4ALJaRCs07tOmC+eqc82IkJX7h/kgsTfhMBvKhaC6hnc6aO5YVw6wB3i60XuaQRHID8DQ2k1kcVJkrYBAHzWR8xQMe8Lbbz4TRiiIuzirNt9azBwTnhmVTrOsfBOrAHKvxcVPMYNuEcE3kp+utf3+Qu+m+to4+XMAkO82pOCeBCOjD6myo1o5YeSEaCV/+oaRs2XCR5m4s1PObhTL7gf57PceDDGGmkuRybX/AtjAVA2/pgmThD33joerGPt6X4QNSG48KFeIyJR6NWfU6bmMooDp38xdZZpL/NYJdgLKKNbMTskLdlX5pK7rqdbewWVv3YF+7uQYj7fDZG7SYcSVU8gvosI+ckGPmQuOFLsHlwCySAaYfUBpgQMwb5+BumpLAayyERq0KY4JVwyhM5Xm0cLEtxJexBA6N8Fh2vxqnecWzcI8pfzwkuXk5UgpBTTepb29rFswfRYDkmvJBjr0MEOSLh3BSwiO+pIwpa9vwGz052aqbGMxoM7OFW3+WJjdyVNw6B1UsAtwFmz28h4nrL99YnEu2aDxwesTWQDzDRo2aXGIzZ320cTVxwt95wG1f3guAYYeWXrZDgC8xWVAi0hu4R17NbjBtxY+EmRvaNXqgi4gVE9/TNZyzNFSEIY7K2ncdi7j/Twgznxdx6DTY4nUOBT/2INeeuD3zGyhzqZzbNScxsEgt65VGuWrEZHnYZ5kedfZwyis3OUyTVj+yMt3OVKpL6bQxCMYNrWqRxOH4TPTtjEiccPJb0bX9BihlLz0xvPhpspM0J7AayIukSY9ulXbM53jLULgZnfqcu+KqDCL2Bu9dxYyi76fGl1faKVcTioa+GXlrptz/b4gdl8mkcyF5m0s3QYzaGaws2bY/l1jm+cejxNnP4ABYHMPSEHy1IkW2uCjFQVioMN/7WCU+4YL++8g96cet7clwMHdnEb59LBSpOuUx/c2wQeepnURI8T4L3mjX+jXOJVwCv+C2+BGazcnTiu6ktzuRgHiQ2Nu6XhzWILmNq3wpnm74uqEbKY3lrKT0hyy0mR3fhL16xYn5s6r/IkRswEVHc7OC1vM9cSyyG/b14r+/swaFL/vf6WA910QbLGs5J7tb4mhtqcQecY2R53XStDZCNSny7npvuXEQGfzaEHxxjwKXKh5iVLYdiO0/pyjcY8o3vfu4JSNoQ6tZ2YeHjjNhpIg8ndo2ApvoEueJEqVuOf+Qa7zl0zq+NOTlhqCp7X9obF/IF1ZqDGyKevEeWpZ535LiLh9XWfRfXXdh99vTli7zfN1+bxuKbE2dO1nk8ihzw3hWtngUVjcWAd+Bycs9XaLE4//HHH+TBwg+MXegvn65CdXfB3R4FIHV4k8m21ogRJ+1Wgvz40SXs9CNHOsK0Lhx72uZOv1w+f3qX8fsPvAc+um1xI+JNUgGS/HosYdBBdkTHRGG2M8pwec2DRx8/TRr3tPtxJXGEhRHPDE0s6BlkCZZy9RgP8Xl+xGl4ZU/0xs02x4rNA4T3bOfD2PKVZhyfzCVzweL55bdfPX3z6lsXfW/z8mkXdUHZOTLnAHlcHX43/mfROY/bseXT/L/IRRy+cu/d2/dZWPLd2r27T6Icr9w9hy+5gc9ddnja93MDuJAEIIu6XGAJd443Fv/lhzJcwoF69m0i5bG1gPLQTqT0Y8fYfg8YOSBUFl0NOtp5QgyZSplpcHAaL3ZpcNdHkMoOXszx+TSPSX68cEJOHuf4Mdf5C5aw6z6YAY/Xk19NZv4Zkwsb9/YjG/u9+46VuJFj6UWW8bDWmZe15bmAr0D0Aksu4oQcqL4aggso/PVCQ4O2Ipo0Ll34u4Ft7Yh8chrefO3eZ7kAAYetwZibJ1DbyEFgBKd7m4c1vAGwDjqmvTo5VkfacYZwa3kySA10bBYPYTdMj4uOmmUxybtco0NEC3iPifaPYvSr0y9gYHgHHcMHwAFzlw0O6G3Gv8alUxuJaBZpfhswAjKezLEHagvNpCgQnF4fOAKoATCy2BWv9oUT7bhvQQ47jGy7v2JdeHFX3RgudPBZvrMntuLlwuSlyYAjIHIa233wOx4//1Grrx06YtT/7o2iGahjaMN25ZPhQO0VOR58k4z10k3RxCEaPvmTcroHc+qLz9Z5dcqq0B5/5233o1u0tYc/f4cfisShPs6zc48BitZ/Y3tHGbH86aRRy7UVuWJ42gyW3okx5mBHrOttj4+et9zFivDwOF7Y7pEVAwGTBXNIvMmlfiA/YqwdcPCoO7wMdqJcMYQAJcaR3p9ldInvJCRW7MTSbYJsX38qTqs121tQsVbfucGgObAvdn0X4z6Hpj98lB9wvAkFP1pq6HHf0dXH+WObm1/Ui8F+kIqHn9RavQ6EG6prX/7rD8wpq5yAC788tsUjSBreZZv+2F2yojVy/KJoFKCaq7wBjK9oIwebtnYcXcaZ4PdjZm10AEe8+q4M+3tj5LyNvHO4FosxPssptsQyh/Rx5cRwcRZTbvN8g721HN/yKA5AH/Mq98adSK2xOJUbZ5+klnL21tIx1Zp6MS5heSKn7ZYY8iWvYK6+NmDorP0+ppbz6ijEzgHWBFzMtZXPciaXf9QsaHSSk5lYyxaXC2f1zdN4cAVj2/SJdqTpiGG+6Q33uqIcy7ETam3YV1DAYGx+iMuotdiAtb/qujbaU4fEQaZ9je3vY6+4gGMz3OrM9sQUBz7z+MQUF8Dqutzrtbwx0TZ751AiV5wev5KUF95o8ZO3B4WBDpA5yrV+1bYG1P6kUYLGFTcKRRPe2CgC0LqlD2SM+OMu2CidB+05V8aG705Ln3rQyPf+EmROdpcHH7jEwofm/1945AeuLGhYKLEw568vN/18Xtb+LB8MlxPoWQyx6AUFHp/nU939rvPcIc0wfsEKXxZXb169efprFuf//pd/cwHy3Pev98OgwGCxTmwce3eMugRkCRNDss3rQxZqZ0EB99jCuRnFJj9M09ZAhQBGKVb88uL78KFs8z3r4eFzwnnOb00Wd2t09lKsFniPsQylblBI06jvtNNp3VbMnseA3OnnT0wUaWCy6Zoii5fUlinngjULM/youZ7Y0nSiU46d184Li9tPcmf0sz/6Xm4WRmDw8nFeBdG76K+fXuXtCNzldi5MrFignqQi6uM3CBBcBcfr+LCI3pe30//1p189vjp348e3DDDn+XNhHXd4soj/I1wbcpLLzgsqwf9kFoku2MP/YMQP3/Ip7x5XIDGemUwXOcj6ok4bSS117/GAjlpVz6jj+36nQLuG1k5LywJWm7ZuqENyz11xPpyNx4bn8e/5p0s05OUo38i8QMGCOX3mP94YDPK1ozbEfp9P9ed5gWR5rqi8dngHMe69aMKYCyU9bvrtCz725x8jHJjTvioFjPKjZ52z53lmmLtHDrvWLj3yvnbVhJ+L8+gsS6Tm/5AWAxiODRiXsZjFroVhRm950pdLBjI8vgQbzJWJ3YHWBGKoL13GoEyjwzSMbOOc/dplL7slDh6CNGzPAKv8ZtbYt6AIBKw1A3pp0R+Cax91fsDGCowFb79yvO/NB8PC4pnfYngoasr40a5j3diEi30NcaHTZux0a6aVCnqrA5u/5hSsyVM5WONWDhlgO0JVmKRTv/IuA6yw2L/G0AcWE8fuWOk3BvVmMNzGBrwziTifBq+0bMS5gykpq5pPfWO7V9HOnB48ocxrawX+1sfcjBVcf4t/6iQOHsU5GAUZjvjURr+ZB6R7ooGamMpGX4gwiFwe2PtHlP5keHw2RiNVjl7s7oZFBgDRYizSFvsoymcd1kYmBIi9uQgyQMszekz420ncfvNI8LXF5BZzvBCqYUvbWOavrjXpPIxNdp03jp07auPpJnDYZMBYXrufnJCt/EK5W8eAZozIY1z7zt8eO9okT+xgC1ZZE3uQ0efvijN56XzhMmyM+qoOLo2tdXAYJE9gVI1TMeVFOJAAi/24QME+NnJBgWy4D1DtY4P7eJ8e0tpPDPiJ9z/pOtMFSY7kODfmAgYDLLA8RPL930yifkg8lktcc2Jk32fukVmDVXR3ZoQf5uYeUdUVlXVo4tyAf7er5ovj5NVgN518wy568x3VsrlZpgvD8pHnwTTjm66WG0t+bsJjos+gm0qzjqbxd4hORDTVMbaO6Wg2WEgRwKJyPNoc69X7wrW552c/Nbxa+vxSZ2IAv3oA0uCBh7lZf4QaRj7+9NR1/nEdd30JYj66dh2PK6q2YLL2dm5WHGBljnMQN+fluXbF3ygrBbpcG0hH4y0/S7tsHWATE/4y3i5OlKZ5MkI9KCiwvHEtP2LXR4f069F6bA7oioDBYuoxB+q73dZjrBTSdxzf5SQefPKzvvwfY3z3LWqll8/E4hRhQ+N7y2VMNnZtMmpn4jCuHwx9II0eJ0+zFtI/HLejxcoHdHwEGAw1HlYwazE4vVpYINcqJvnbunvFGDXyBcp5r7JxxnbPmxv23ejNg+vYsKH+OlfO+77z+QCnPODnyiv+PEj3L5u8TdEH9dk48fVZ//WXv/jH1UG+guvOkU18efSqO/7Mc3lCH/3mgI6kcnYz0jEY/OHH2at62Xn3Q9Iy/6wdvaxUCw8m8mxG4IUfhfJKvBxQ37wmLm40kBSNYNTDtcKJpv3q6yvAcEocLaB1oSNCvhhr46Ytcupz/cEb/2L01QQgDKYK8FIf8qVeyXlfurxPxADAOmYT9s33b55++Pu/y5Mu38iL+F5Jtyatm3WdGlHH1h+d1qd+8OBVF7zK4nleFk3j6nkMJE3ee/+4mBtr5xXbVofbPPn2Dyzn0PnmCZf5y/jz/oUbDf/DTUkPgVJOfWjYyWlyQyav6BOVoefaV6LUdKqPB16Do8vEBhtNY6Ghj4yYnd/oEpvNLRRObfPEFP314UkqPuuBVyb4pJv5dh76xISmMu4aD15uN7wVpK8smE09ayJ1O7UnpkFgZs+55wPj+PO2MrXhCR1u+ySAZfOof8edJ++PIhi3iVV+y9Kay685rhzQrWo7AZp42hAojZN/V5BIKCzaaRgo2ttv+amN7hZpRcEssudOiPyP9cEfTGzuYTNek+J3RL4NEvvYEOU0MRYEjrkNeUyBulU/pn90RgXAtglkcMgwjnrj1xYy9eHoleUYsCjw23MTqB0eNp/9vWT0ipFOQynR3tiPtkbeOPHUV2A19laIVhyO7RxLbRTWplGufDc/F9rUoXmNRg7ABXj4DFw5NMDUL+jmsrXBDb+e6lCCHMtlpNjREuNq+F7jnatiVn5p1+seG9ngbhc8nHhGbZw791eNR3zlhG+E98W5c67tctxQFV7+0SOaJ/EE0wTcadd6WlpdY4wWdm3FOpOAtra7HrG7Z6NFOMC/udaiwNEG0PKPTWueOg4uyl0T+G+/+rhP/q3Jxk6MUpMNEYlzfDJEbeAS7PhgYd8qWRu56HDkrcOVKVqDFCnH+q+4uY99YnpV3xgyiX3OZ9x66XtsHUm8c1kGeIsa30qwO9LijiuWaFbfXm3tMxHidE5ZNCeL3M+ZA5I8/V+ceMVet4IRoi1na+dab9xFuyKO7T3ugF02A2htCNex8WPbugUngl0boJZhbTcu8pU86rci5QmW86N116L4i2twwIJ2swVb6wbJqA1zOBw3+qlh7SMFJrmU/1hR1/WnJjRrA1J0Yy/IPhFQIzltneC4tosHsPrhqRyZc1wukoreWOLDJ0YYB7PcDVjecoMj+p5PDVeneYNiVmPgJteDSxyD539rLcU8HlurCDQbburLrRScjUgvWnDv3EdYKld9qOkIq4qt3Cff6Z96BqvY5YgV/6dpnIZ5xzky3jneOKdeuPFH3lMvhzE49Yka+2K3IybyGK99bW55qt5csENHmGIDSsgCF1esk190eugkHyTH3u6Fr26IlROS1vbc7hYbO7FhhbVsFJ18InO9DgefXIj/waqTnhcnrm2Ra2lq0tTEdl7RZfPVl9T3Shlyfu6x1xYMr3xiY8EClfVJ141AOPGSY77v3E1AHox7BY3NubgByJmrcDxQ79pOrNzu+OPK66/ZiP17PhH8519/7uYj9vs92cR3I04njSt7H3/PB3qBbR3hYcbpxEAZHVrnGjvsMevGo/buY5IL3wHu1Tj917cIHN1skC+I4IT3FStChlnD6GjaeXTYQ4VT59gyhpD3Mze7dEFBfVpw+yrC6OKTUfSxWKO934iD/JYL8H4gWKyZxLRsvY4faZwnaaY+pAA27zumrs/zxyeA89V0+8Fr4OxV9O/+/EM+KO6do84KRAAAIABJREFUdX2XD/ij4dc5SZ95DuZXfFXWXJXlROP5DuJR35d5UuZrvpbvm7w9IrF+zdVznrjBoBxhBW54sTfzau8Vy5gTqy97bi2oh/NCICs78ynHeS9zcNumrhkgwYN2tBFUjia9YACrLB34VbMe6Ge9RIFOGlErjz/OeJ5gBNQop4iLvsfaWs/UsLXI+g2OtxE+EDCNuXv2vOsEXG7rfHYAf8yVaDGV720ts678TXzmyjdHyEXmysh5iJVUsGk73zyR4yfGMz/8Oe9cRc+H8eVzKvKSBrJNGH7ac+58ko0401DZ0ukdENSSaw7hZOlycG7BiU1Whh6tW7oZqvecIWoP5Bc0zUENJ9YO3uZeHuaUbplOPbHBsr8o7R+4DJ1bzqrwozNcjY+gdsiJq80BiWyF+A0SVpiUKAjYDT42UXY20pc8IGkCRInvHlWorMRJIKqBKTDEGA+I3vVq0AY0jjjEJ0LsOU2kMkZcolUl5vDBkoZcHUdj5kxXbc9lerOdeNrYx3U8GOe3KZhJkZD5t8svw9iefNO/4sQQPCBvcoZFBAN9/sBMH9/DoaLRFebEQYevbdCMUT5g7qJ8tLp5QI+hhwziT+N459B5GVls0a3NYuunf+KaTzIZPHTbjn0AzAXbafTWp1UcDGl50FIX3TjopRyLtaIizsvKlhuW9B231saMqGg5jm39K10bz2LW4V4noAFxNiQ5cwne5gncNJEjjzatGTc2FCrdPBhZL86Y226+Y38KsCbI1V1nMdErD1rO/Ni2r25jTcSRYW+Odahv8qhsdcQrZFE6OHO+OrD0xXaFjccRCecLfWw85XA4xShttPrc2ZvfKrHD7zZu/1GATec33sZZFo20/Fq7+p5cosRH6c79BCzWcPiSM7YAcxgMR2KoYGi7s70E1L/Ye1bnYCuy3IZzPMxzeca2c/nIEWsyMivrAXLnu7Lar29ADe3BUEVg3LrSyZ912lozXn39xQuW3hMXfyEHouNKrC+xxY4BNjcuWjEO1mLXqi70j836IlgM/NLvz+VDOPFy1Dxj2q4dZEP/4iPmVcMNoaOHIuobVEbbt24BZMyhfJr0vT5jUbuYthZI9YxfZR0BRqM+7c1o7BE2f7WajSFAtJHJfDGmXjUoNOadK8ZrWAtGzbU5U/u1aZ6123lYnIfYU1tklXua+VjcK95hINcLv0wCAk4OcnOYvhOqomrdyn5jcrYWdRdjzfAvxtREzmqNB9L9L8Z1zUm/jO8bFox58L2bzM51oKzf3ed+9Xwe9onFzmDsAsbGgK9S+4bNFVfJ96XtXL2FO+f8sWlnkw475yS7rD6Yf//0y08/P73Lp8Cjw7a8u3l0Yx+/8kyVJv+eO+Pk4hV9AKgk86MdhUXHZrM6uDMg9ieuEkbnBjzROweApA9mru7zsmnfP5tND08m8GnVnMVktxCsnZ9GuK9DJNMCKz0PuI2fvFpPsqnNGMXVXmwxoy99j6usDCVTjyV8RKpzx+q7FnY97Jn9Dw1/G2nlp1fQ++n6vA2BP+py1lWuzvKJ7j/+498//fgPf+/bF5rOHMNbdp7TIw921zm35hMvJ75HmyvxL77ulVa+aq8NH/7iRr1Xun110TOP7tyxSfY8icTaY825BnkveuUJHvtszvkTeHCpEYV8aJ3PI4VHfmi4njYDRHcM1+E4X+bp5Rc7alkfxtMOJ4yQFhE7GiJuWzy346qd29LDFe7kCCD45M2TZ/whc207D32ygnzg6ZwYmyjIRk/HVj7mNBKMnJeonKfEff/2XW4nfNf8x6fffv41f78E+48vlQeV2OSzdRA24+s8A+IYvmPoe5snLsZjZqUAvMk6yDFibRHYAZO8eaKQV4v0wypZ5/1gvHrCsb85Ay1hztUvrqojRHfNb8N5rAUYHV4e5IgwOm9jA68sVsuj4rE73gXra08aeuzWPQENOuN51uMiAX10XfB15jhEq34Qr6/CSYZTn7GfhR3BqII0MZjJaV3ARtFuvJwYTFwY2OOC+40Hk1dRjoNJDDM0RJ2w0VHfyFKHXcRaIBpgF3PsHq60EDz42C6PYgI1WFlEnbRyukzjhyMxqH9+G3sQPCk0BgbmFVvMlyd4mAK1ZzEZKYgG5bTmg2jnc7zWueB1jay4kyMYwt0AEW2O2Fv7xRyA8UMKsDYCZ7BjVNxzTT1bs8jOfyFNqydGeFqDjU1GFpQgtTWO9QK3cVcn/tjLn9irBL8ViKS+nPYJ77FsHuDH3golhjprCNjI6fLsMVATE7vDD70Y2Az6YO58wb94nNOi/zKWmFHdn4k8vLEPtjGxAcIzhUknbXX2IzS2ucQgDuLmvHZ1u/y1TxxbXYSmCo3duORYDFjQ8LGCiTHMchZp8MplTDltHM0bc9EqasyYivwQH26T14HZPGN/dPFsvzJjTrxGRB78rEELiq8BN9+1Qqim5+2Oeq3IkawZl29wcLXRz2iNc9ZujmvF+ar3+IyyyOsX4S1noSnG4k9n6wyPaw7KE9jHeURSGeeuQ2yb1Z7R0Ta35lHZHs0hg9JpPRPMcblU91Cn5FM+i8IZ66uOV6zKlr/xsub4wV67W33KY2ICS4vwwut4c2xuGzdWCh5RgF+A674F0PVGPxgaU9M6lWH0t1buuDTOruNT6bhufS6eG+vus6DIYknshs04fKxLbaxblIePOnLQteeaKlg7/WJbPl/GzvgPOAUs20NmUpvx5k28m8nBGuEdo2bU+JZD3OU1HLSfvkwj2HP9hi74UB8szhJB/De47drFzNtKNiStB340FNmMMAyuNfN/ZPHYrLIRxgc+XrHEZeuaM5uc7GoB8/8rY/RsqF/lveUv84nbL/LnV5QFazfaYNJno0T9wOf/HF/ZxAN4Prmdr1T79bdfQ4/3muflsNnMlyrWbW64Is027NS0eYQXxmSVR+1hJC8Dja9x2ZRlzCbOzXly6frj6+S4ip7xfPgYnH3yIJuMd9ls8N755y9eyR/OfCUXn+b+Kh+W1lcN9Opya96aJtXJYUnAMC3Y0t36R+r8Rm6jRtPXDhcUOXCTRca4ayI5r9GR06EWGmUucx30GZvieCR35oINSU5eed3HStYoPs553ncPvu8NDj4fAvfhRT4ALFe2n/kqiD6RAgu+SutzvtP+Y753nCczfv/9P/00730sRx2az8UcXJovsU4dvnqWl2Dz9gg+uT0xPr778PQ+66Kbeaiziep84dNvGOha9BO8I+NqLWuvr9TI+hG3Tw7tvPhycD+FnwdRbawhmuzCizN/HNGV9WXjmlETC+ewOl3OYfJjnO6xsxg1OnEj4wc7Wr/Cy46y5Y6663XWjySz2nOz4v3o5LZPemjHB7VN48kPavv6uzf5rIdfn375+Sdjclu45scAqTl5Z53k/e1yIXD+dk3KJ07nHHXL0NseefEp63xgHJvcn//6V4g//Zi3QvAyd+9HmMNgbmxCOOBssOY6yyQDfk14/BrfdZz8s5Tlw/2WWGJjI6CH5b81BBE96/RDNuRc3TdGwviNDqwpXzAeKaE9FO9gwSm/1qIq+xWXY+PhPwaecOK3t/09K0Q/xOGjzkIB0TEmwD3wQBjM+R50Rowb4HAPMDUpFxlk0EIIOLo/AIOEo/rSWCD/4UiwyCRc/8RWHqeo7AtA8rOIhwlmqibGSVrTsXWVxUoiddhycHaChmS1A8bAe8mMPZffxTN6bZqjcpObWgFdAyg2THsez+SbxMREM90jkVRG+bU7MWuXCNaKmFO3G8YXXUm07oEjZzEDyO+tPh3XpjnAa+o5tcJJPgRJs5b2sGuFV58w5cc/E/pg0JnNszL4I5w4+NCnLd7qsFeX3Fttxsuo1rWNpbfy1eGYZsCJV8mIi+fciB1TKIy93XAqq/hjA1/nQApF036ANZ68h621Hp8HjLg4j54bdoL19CUXMeJRYtLc9eCCAwdlfpWnA7VGGXzHihQsH8Sbxv0srgGHK9iLwfk2fsDaWmkbj/xau/U9dSxfoZDl9ks4YjzgtSKTV5QY5bet9Vagc8Zzth4xKm7wBxs/Ylj/mRtyRba4hccn0tE1h64DTRMHnmIRM03eII/O8+FaPTE2djH1rO/4mSN4qFZmNzGRiWCnPWJIpDL6d771uezP2PxhM9y5nWY0WQ3Y8FgnfGjhdaXWnnkRfOpybIwTH1QxvXuKNTxmFhRxuPBXg/Pl3XjlR776UC9+grmysVBPf3laI9KB7/ivX88XdrMGN/YJBQqDxfD+I9JmVy5jalw4+Tv80a1/8QYLI7js/zPc/L9U5F3fgk48sDaivDJifF+P2C/n9jm21f+OkL7DwYnZQ82Mi1daTledZ31eqjLJYyXqJid9y20EAEQKu/En/3GwvviAeWonOQQlsH6YqRp7LPzfM5bj31GUBZ1Yi4k8TYhyuuJGGLNGTT+90++w41kX5JCHya0Prt6+RG/o6TZd7CauZwDT0t/ag+c6Qoxx/nrVLN1gs7lhI/05a4fybZBu6piE/GZnx7pAtle3Ofv+8mze2DC5IWcHaLwsxfT5E5KY+eND3LhS9Rsbhl9+dmO+mNryElv88+ccZg1/ygN/UpM7XAYfXPsZbz6w5wIpcgKDid/+BcUNBBX25dzwTUPfzfn7cHsrv2fP3j598+23webl3rni/8tPfl3cm2A/z0v7zT0boo/Z0C83p2Cq3VmGBkzR7Gn6lVSc+LST9xc+YiXuhQlnHHTrgZxjcTAYx8haKFdrfXXlvoIGbjYm+o0dtWAeuCJ6vcQ9mz+eRBk/Xjr95ofvHXMV91deEZF5JSb7HOk0Qo8QJhYbxM99VYUvb8/Vc9YXmzu+X72J5ZS6yzMv28b1msP2rf98xgEcWY/g4IMD2fFqiV41Z+PVDeLWzOzDp7d9vazn3m8GBKQ0LOnnHFx4kFvntdq1FVOX2tYHQf31wShDstPeQo09idI0n5UzuWxBWQX8unRTI68Ey4mvCvwYOU8q8a+g70N//ebbp9/yZMr7vFrlXebTDe2EaaxgYE/twOMJndye+0QJT+xkjGH0u7aI3w8izPm2dniliU/sZB6//f57yuXtnrcv8BL4Zg1YAub33rr+RjLqlmPI5oSLMkTM3Y4t2Oiopy4aYdGx8s6f90UB4kmODx/emytPEMIT/L0/SwnNuXGYdyoxeOnByHmckPZz++gaqQ4rmHAEp7fHnBXmcPJAHwt+CREi2NM8w59mAXJmSD/yXkFfg6x1Pz0bnVYcM6hHe/oN0WhqedkAysZWv/QvMmsTlwR3hOmSAipCNcN3BEZfDprhnGYenhunsnHWJofNTWwspp2xhhMjug7TGfT4Xzfsy1d9qu3EHe8dY/fA7tgdaTqbemuNB9rWwMmWC4ep462eW9djJ15sc16ZtQVyJpvcVmcU8RvR2IYiXzqziDYmddDUGRJn5065HvGJXc3SnwXdGhEbTQ6uYMmcWDphMEUh2qktfnLTSpvmgRDVLngDjFE1E9Q7qMlAe/Aci10cMFvXCDdmYNZub3ib954P7uE+nA7eUgromYvEJKygQRhbLW9+YJPfiRVdaxSN9ymCHD06qNP8hzucKplcGjgD4gKHT72WB6Mi91zcSrXJHT7ntrXeKNd5eYMFEnGMpQuZIX6MjwjF3U6ZB6Xqx1seu2bxmqTENYepSWNpccFZn/L3AfPUV9tYfXnb33xgYd1w3TqINfgGxr+hrhpXYBYnNlTHcONnCHQnYddlh/d6nVwbpj7Lh3qn39gxoDSEGRkuzuGEZqzaTgnseM+Xjex0YB5m5Bnbbery/+BuA3/IbE2qndzQRK9FQLUJ3yOLvtqJEMNd5/e4m5f/zzDFjvPWI+fyKHf51UC58cfP08wPJ2sqw/hmXNsrn81viyEs+ebHdTO+dXQlEOLk2gF8pzIAGKfBjlxDHXO48CuG1dSxAo+Pvq1Bc1qjy+dCWF05MaJ8njGC3NRVYQ5mJe/gJYDzsfLcbyGjNZqd5ju2XRuagO78g2osJArLH6uiXRZn/vE9BrFykNOuA3STzMZcbmsD+MV/Qg8X41rAi4M5qUgVTqGWxDVPxWdTs6SwSctQPzDyh3osIu8DaxdepKx9ro55JdlNCw/suykrVjkwH1Ih77nvZuPDZpbNDw/iefDKy9p5kMtVJ+TYVJdLW9PY9CODFbXijytWvMf4l7z//Jdff3ET4UuQE88NBZusqQW+9PnZWpshWEG1dJzDMwb8Gms167dXGdlEcrUXeD4Jm5fokxefXk19PuQK7juuAAaPq+fE5MPSqNPHXD3/4e/+7um7XDFm095PpeeqbzY84enLjAmfBrszD2e88ynVprF2JXTylDe6yItF/ju3M8mXYGJGvzbRXRiRky+SnJPm1AlZG1FQGguj/JETdaUmT095lQPrJ3ONLlthx/Bzk/6nbNKz3n7KB/799Je/5qXNP+dtAnwlHbw3ysZK3Pgh5+0PvLydq+e0d3lihCcGShAO4ZIGAlfSif8871nfJ0Z4JYNvoZgnDdw8kXvcvLrMVfPMnRv0zZb0BvNLfq47+bYWxK5tc6APdls6+SUPRFhQ8zYq2TlAow7H2NrP4bKPbG5nyGjgnCvqWiLEH+0NLyI220kyT0T0CaZnefLLmnCJPSrmjVc7fPfDDz7JxGbUJ6biVV+gOx9uzOtkXqx7v+t+9P5vtT7woDULetxmoJJqP30KB9YPtxPO5P1VbtfcR/AEgmlAmyZeB6c7OsamF06TumNTc21sfLXFw5Z4OI7TWjEGk3p7nzG42FOTtx/ePr3INxe8zBNGvLIjyzxPTIS/y5454ckf5nUaWLnRWb9gojg6TBhHPF3pMOxjUJT5k1BOd1wdZjXpP3Ous7Bicah6v2ZtjE1eVeksuIWhcAT1NMksEekLssgnQOngt/49b6EzasQpPOOlOohBjxQ3n71jFGYoER/cy8vCxkAsOevhuH7XGF7kV35wadTyru5wHY6TZPGRpbkw4ONIyfQ3ixv2+KytdRa7ebUL/8tCxMlJe2Lmrw8QaytPa7PzUyP//5t47ZszKQ9+gA5m+kolgX+wjl1zWVbRqrN+DNLu/SllFejslavxiIswgGJOfuU3cdFjlx/rMQ6uyeHVGwbgBbvrFOGrLSi3lqBruxjw0CqGp/4KL0+5lnFthbzykkXiiS3e5LehhQo68fPDauRXjupuTrEx/PHFAI/6IEbP3x6L+bh2MYAPgcTbWh8vVULAY7kjELsBst6qq7CY1Y8BtIwTvGln/cx4+R19Oiu7x33McXJu5oY/uInXqtRGjoBHqM3h3jiodm4bd+x0wG/mZuq19mvbiUsd9z6RnPNTTJjc23A6Ishgs3Y3P9doDeV9mUy564vu1PjkvoixmXxPCCEjFI9zgeG79UbSB4J1bkUvqLIabpyAOf+8mqPacBNheFWW48QmxXIvBxT2ctj5VD92pw6DW75REoQ8MgfFG1HE97xOfDqzdnFtUDrtbpzNu/LlWEyNcSZ8VGj5m4yl5EFd5tU73g2FpcYK9GsxAhDA5CIOOTG+NeUTc3Ubn+jWhAcbE/e4Du5ExnTJjEmzvdaxrEBU35pUto54lCeSQc4Jn60DzupGLRh5xYLfnS/lHPCH2+DtHBvrIYeJoS32wBVz61d+USSeEeMvHudz9U8S+g+rGycQRwovrL5YY1fM0Ut+/G58FZdK8iNmHugyz+kvJ9akbU70t8sZtcjx3dzEAkPHOky2we/7sI2BKnb8sQmyH9nveUD6LB9AxYepMfdsxj99zAP+bM650vmVG3zs968YhBOL+738Oo+5D+AB/4f3fLXab3l5+3879sPMqF9i08p1NmepAZsGZOjBAZIm/viYcYx84B3rje1L13kwHgw20Gz+wGAzQevmvLgpR3S8zJXPQ84rA1gEacgI+f2PPz69+TGb8zev3SDubeEzL33HEC7W45YHnEaFCc36x6RWHMdodRhNc+7tN6d61956QS6/hM7J3AY4p+pQutEl7/xw25/M4jFEMM2fTzRQq/S3gc2G6+0v+SC4DF69zvuZs3fxpdCZDDdg2WC/+dN3bgT5NPaf813mP//XX+OXJzey8aGZS/w3J15+zRM4bPB5+Txr4/3bvLw9Z8mEKE+isNnkiZuXvJc6uODzVW9+5gEbc7DzZz3S84cnXfKECpv6fbn8ZQibbSR+1Y++WKPm9oSEY5uz11gYpmjE/TI3bNfXnjA4tDUGMzTYE6Bzik0txE2N9zFno4OIRWzyS98nTjKrrG+eSHrxka8zvG7L1JB1++bd927Sf80rV3gly97HmIcb6UZmHcPsq7wFxNtU5oL1Dp99pYXzHhvWTfNn+UePTf5effPa+eI93jwRAB9e5eATMLHLUF87yYF6NevinSx7x1YM9sp8D3rOMhWEfitiz+6AHz3IRYcbMVlvdPv2iBddpxn7BAKK/PLExstnqaUcAMa1dXBkLKQxvjVjMAZnuGkxsZs86s6/c4k5Pjn28UBG8M+48va4/SLvmqgGqzzFldMhFEkarhTWhtOBUlmNQTLOeYl3ITZwvegzaZt8MA+rtWsY5GtbSRkUO5roxR9zw984mFjGJiotYk2wUzAUj3FYqOUNMHnTOJYfIwt+zwEhsYEPNqcztH/VJEPRzAYX7IfXxm3MwjXH5VEZGNuMBSJOxh5bMZFvDZCPnQwX4cZteBRs4sfHjKgL/zUT0BrRnyTRU2+4WhvJYIpx4sT03ppTJHMDltbNDvMdegYb2eFH6EhQVtMQ63R0MBjei4lb7DDBF966VYCwBiBOPOtWxVFXtgGhQv+xGVvRrcZyW9uNHSNFk2eGza/41nTuOOFE7DtdfE9N6xK8zttVpyuGlKKnBIadePe5w2Z9zSMBW/969HZVhCLhUf7UtbVD/9iw/XIeV3ZZRyJE8OyAcdWmo9ahcjzDi1/qk2Elmx0ekc36daBqMZBEEEd+5L531rMGVKPjN7J7Tc4aMj4w5SpmHGo73OCROFtLeBoTCloyHt5zUpLbCu3kMBj4N+diYoXMXNbfHIqqTv3dD/PlhDIN31lz5ajUA/nQGusgilFp9eS1c71WK2vOQaqpnOkezNTQukUmt4zuHM8/N4gc8HQCsPXU/yGvaDCZoLgdHuALtHM3uOLdeBFg7K7AiAROZxrgmM6J4RHYn9jhcjMtemSNMmf4il8fpYNNAeG9Q2NI5ZJsXoS91xBfrJBdAJEQ74FV9IOZU1UK6GJ74Wxt13/xr/nCo/ic4QbmRtSPWEdXa8LayHdrnbNrv0Hs12ZsxVjsRtGeiBtwseKyPJr/jjs/dQC3vthuk2HwOg+XPSEurHpYH2Kiyl+7jDMCY/jIk/6osL83/biPSnNOI/DxLFdEwel2Eq0PUrHjmjcxaeBr5//xcM6ZK+Rswq/3mWdjlY3s52zeedDtFfDY7RXz5WjegAWdB+/dJOfl7b/95kvI4bfvH2YTBnev2EkkDOUQYTB8qTLyNPywpQb7cl0fcCcG0bgyzpnNALbo+NuvWIMP0G7g8uQDOsDKmyvrgLcpS/5f5yXCbHJ4T6/1iNqYOWNDQOudMXlXkFN7SuhXZwdHebLyrZUjrK6x5ZNOZORtKOYIG3Amln0OtxaVuPzfiR+1Yutl7rNGADGa96vxzZj55Aq00BER68PbPCHDppr5zhnZs/O/MD7ZbH+TGnHmqvg3r1/7knc23X79FhtC3u/L7mqAuUr5PJ/yDaHf3+fJm7x6gWz84Di+HixrjHq7KefDCCPjJcjEoBY05zbYbMTZPLLB4v8sObo5144Midu1bZD4piTmuzXubCC0IjlqgcB4W/M943z6gmg6XjeMwJTtnMNJP7iN7uAUorFxGgqr77CK1iCS/O6rDVjj1Jsaul5SCG5HPLnxp7/7c+qF8VfOTV9ZYHJGJQYNP+uZ+T3nfN86e/izTgmLPQsrzZsQRCJjnfEkCnP96SOvMOn74pk3nizgiRtdiTM+VmvHcgAqeeb3efi6MWcYmzbmEq+2cq5MybEbH6iOP2umOPXnyQbux7g/4EmLz7nf4O0WNOxYc+sr7yqa+hdran3ghu3WBzkg8qVM+ZEDvKgBAeqgqQcwdGMerBDGV38w0M1TVZjTxnHKY9hL1cBYIbsB47m2a46M5sRjG6IE3GZCDrRoD5sstC3yWnMWP+cyzHjwKq+l+OkW2/IcPzyRLyb8xaWAI3WcEe3o4HzjfuIf4/gv1kTGWV5C11/M2HXycE7L6cLbTO61qt1qQMWeH24/wK+s/WgGeuOfekqzNZCWvvXfLj5ic3aBHjBzpA4wPrWHAzLNil0bEFHmNycXYez0Q74kqQdGNuzBypk2/eVUIeyALU9i6D8u64PtxqzfHMHeGPpsfAaP2MtrzKzHyTvWZU2CuhqgtQBHr4QKT3MEvW1xZ5jTBdBY4ZQ7rvqN7phgMbmne7AGHLNTv0T0gRCybfp0sLwIf/pRDZRG4o9+vHrSjtrVfku6s4Lf1mDPOD7yq0QZUXOn/f+vF6wuTOKJ5nxenJeP2iGlJ/8Q0oqyPQQrqd7xJlO2N5vYYr5N1xzG1c70d81rWrI3sxgZt0B1yVHxrEeG8WNesH0IFTn4D1zWdritb7ErFItu8Fa+80QYfGgrO2fi6UbQNhiZY4aLhUY5HbCMk7PO1e7g4neUGEy75vkRwyoELlEgnIZ3W3tyvuUno80t58MvTvf8xIjfRigmI/7SAk/Isv0i96m9cxKL3pZqiat+2IgFCGBg5fDAlTgbCH/MOleORhcviXRWGDgU09jcd/g/FHitndvtE5ZWPu2XzdrWj3zKYsYyHud1y1ke7BSN1aq2jxEI9WkuGQ/E5rS8dj70mhph60138rBe6GjWrnW9+wJ/1jL+2EqDWsb+VhOULatWS22Fjp0nAQQBrQ3sFGljDysDln51a865sRYn5+kaffJBtvOOvPhFqf/2ywxQ8nVAnQOkAAAgAElEQVRzyQPUqHlg6veBp89aaM6Nt3oez+PH1fPfP/Wl7PS5usQGGIzdwEs8tr26FlBAyJ9tYYC8wpersbzM/COb56iZH+LGzTjkwia9VwULwaayD6qxqR2c2NRjXwyuIPbD0LxqJ69uvtmUELubufnQsbysXW7w4y814Uy7HsBPrNxWeHkuD+L5XynvmupXR2YjjQMcR78iFJ2jmW/yvtno8CAY5cHqmlzcnjk+4lSC7+oKeta6HuzRui7qHU6uhV7t/ERtM7YO2E9ObqCTP3JeXp5naZork0J2OfPy4Ocv/uSG8NtcVefKO28T4MPf3uWJGT5/ADs2b768fa6Qc6X9eV6ZwfuW2RChY43xcnbObu4yBywA306Q6WNOubrvh9Slz4eU7Vz48nfsafExz8njlDmJwWX+7dc2x67H5rP3A8rUAUe+aTl5fw7GYt3OO6dj7XzrGwKuhZut8hguDk/uGyDH9kA5zOs/Yx+/RcXdK4T6yoEIhufy5YmOH/+BD23Lk2u5TbzNW0yoOzGZU9Y4jU1qbtWd/2Bw++krabjPyG0sc+fayFq4USr3+DOPxPIT+c1DWOv2Mt91z5MoOBJXgOHp2GJ5SKzEyxVzX9VTiMve9DY+WFGBkw75XmGjmAkmL+ak4ZpzY3Y98mQhb8FBxodZ8p55sLyP48zV+/wc3oeTsJZCGnBAB48pEGPCQwWpOKkrhs4PynrdfPQaR3wBWKuKEWA1n+I+DsJHqnVkAQeeRvIkgCWtHgtcwshaxHotQUgvkDIRcpB8T+Az7qK84mKq/wAcfGwp1HAiouOxOwiEnjhg0daP/toh88bTRLVBT3R52YXkNDBngTgpxo3MRGKz+uUIvtjELAeRcCEG0Cg4Dd8jSgcR7t5xHGMs2sQEaUTWBR9vbMmSPn7o5V0P8kdet8f5FTmA5ROLgOiV86khgjRh7VUgIkEPtkoP1mGHMSmHCAZrVZzVbVIZN055ar6c0ESA3mQ5T7u4oJogQ/jgF0yA6+pPAaghftYU0dSEVT+/NYyN64gRKsbVDO8qoLBrQcOx4USqy7F1QcDv5ryYi1ydvhOl2BLA1ViL2RgGoSv2hVTRvV7x1ib33lUCWEJzp1RxA2k9gsZ1QO3qFTSqJkiNKcbK0m0Ujq3lqWFEzMv6mg/2OtSrNaqvsOqrg4d50Ulr1OLdLS5dwTtX44sIgwQ1bpQ7RpyJ81Sr0SnDaqKMzcZXHBmvvHTexmxLhF9F5WOYUWqvgFjjmNOpWWQ772pDenWeyUMiaMthYYC91uj0jcUhTd/OxkQeVwlgoNnGw7796tVyOCUbLhGcXFY5No0m7BwGwNNwSRza5peOfWTVtIe1Y/SjG88zxtLQ8w+3lhjHcuaR8+IefbxuaTWwgms+wG6esY1u76fPbZf6ajQ+E0dp+ouPybaDsQ+wBI52fCWSCedHnEM8480JLrgASn954JM+dd12+uMzXqs+QIu3rDesiQN3BHXddQIl2hUxfXJB8QWXLyAwjGeknu8IQopDjzrUN7k9RBo7beJPzJwWdpxq9IcjiBgfNx0zTJtowJGLssp9r2geJO/VY1UxWJsTW9zOBTqoufGKb16frmBf/uyVsth41TEvLQas9ePcTTi+/LFp6gN0xrmiin7s0ZvQsNk5wt4rnGyU80fjk9sxw8f1E5DFwY+/fVCtfwr1mQ8Xiw++jXW9LBXuCeMDemuUq36c/eT4xPzI+18z5go7IN4OgkVjEyJXOcCDeW7zKn82NQYOYeRw8EkNbvPThBo8E4PvKjmji2ClDgUDi/fBp3YzediM+WDcbldgrDPnW3uIN9ia5sAKpu/4GDIqJ+b5c9aFV9pz+z926ViP5MqVdDbZn3KFlJe7Mwc8cUFBupY6n305+kvfh+yHhuWKJJ+Mz4b647wP2k9v52XqFDON9/fD5Prwt+rYnFME10OuELMW2DzxhMGv+Sqvn/NtAMzr13nS4Nt8/RsbemzgE1aTsCG+OHDbqKgcOjPLh5hbg31s57xHYSVnrg4IY39buyOfqK1+B0Yy9jWvq3cdJoJrIAHP4xnsW6rqMiyER9czX4nOKwi4Ss0TaSmC9SUnNrpeSX/+Y+bsxdNPeRsCn+7uZwakXsSlmXOeVPsq9wOucf4XRGfuPLbavms/1qdIrIHGAOc//+3fn77NB9Q5zxmTD3rm57pC3fsLIhtf/nlSgNvpPsGSeKx354UO49j3SYx0hnFvFDOncKKZkqCxWu6txfM8OfHxY/MGmycoeh+SO5HE4Akgnvw5T8zx/3J5lEGOU5dGazxjz/wR05/hv3Y3P+spMGElzGi80mnhR9Yx84J4c+8GPQL8VRRHQnQLiAP6KYTS1ZWmmMiHSB2n4KH0B/86SFaea7NEch4TAx3Y5Qfg2ggQxU2nb4HlXV6R5neLJScOaS3mpfNlrMEbCG0OH0eEa8C9ARY8yjFUv5xyZrwYxgPcplI0sSIuR/Qbg24QMrw4MZkYE3KwhGocPPcZO5YTJpt7kbHASOjtxnJ53hRqNQVJh4f1ENPc3lGkg5+/gbYK0W0PVw2XMU7TKucI783t1Cq49g8qbt48OdmsT7sEKletls8YRmYcsLhReKe/+AVQfxV7Qlw2q3etnJjTIQwGtgz4HT7L4O6/lvKPgboIN4PWooB3HVid+0jx6+n4L+7G3HENkoudYmx/cbQNYB/4j+fGMPAMlpAmxTQeZACT4fQz7BMgcGWdoZ9zu3XBPH/mTVesdGj4MS82WNd/18sojn7HQP7ttoGjnTjD9jJH7vqDfyu18XZ9rs+OJ7UrH9BcT+Urb28XEWf9mSNh8mN/U1x6BDBXjlBVYBg0dFa2cRTLOzHHHp231ckpTjrz+N7mOOwilsvU92BjZOgSq3dFzP7VbvMk5jre1giiL/JsdReFWtWo2OM7Oaka7M4HpGdVRT69AZtAOZkX+tg2/+VfU3NaHfb0acQSt0Ni2ZCnLd5IrQa1lgfCmmnr/I8PtVU9OI2RXJV/4bg+c78FmHMTW+EHC8DNHzkotJ4j0XirWl2PVmcMb7Ox3G6mm9fFE9h7XWe+9LnlsXUb28t/44Xc1F++05fU8Nham9Dt/wu123x1O3xNePKfagyWnLGLw3IZi6mDyvTvGMhm3uimEe+SRccDTxdAzsaqP1ZtqSCqPJCGWB84gxM5pvnbejrHO3vDG2frwDkPkt3cRhe0hkM+kerfG7n4/M/LS8F9GWgeOLv5yYPZfLh2r25FD562waHJ3kOvSMPXTfbZCOQD2PIA+OVXfWiJjpfNc/WcPKAtXrA+clXLH2TdAG4uvo88vr0SmLj5WjkZhNOnFAZcr7QGY68s8p563kdPc1Mabs2ZWsyaRJk+KTx/0U2oNYvESkXBg/lMRP78PfXDtQ0mIExLt9WpVM0I5EHStq4Vuouws+M4B92uQ6KsL7relmp0YxB7N9/JF501nBz1Sr1AEYkDa8IY7VMProZ/escG+f3Ty7f5ujk26tkYe5VT+66FeLjOXrzaJ3V6VRx/NuxcRWUj/iy15X8aa4u3EMDdx1jBar15AqZXxplHnhzgMwz8FoBszt/mqjxriyddAvP0IU+k8KFzrAdeCcAej9rayMW8yDYtB0vuwKxHriC6mWtuYNuvWwEGqxvDDMg/ARCrytgAc1ajWeTcjJFjDwl/Z961j2oafiJ7Q48wbreusTDFxhY8vg7w44c8mZYr2U4iMmyCTd15MoSNM5+8zyfp//zf/+3cyrco2rNR9uPa8c0PLzfvV7KBlkZdEpYRG2qunvMVhO95AiVzzQdCMtcvMyedh75k3LebZD5lJVR6iUUpQAPz00fO6fBEQ059GX86NE9T7TrFNs5LJiadP61LEFwcp3jXYymD6svbKnKP4/0Gnqwjngxi8w4Xn4wyWyDHL3bOz5HjuTpiXqNqhkcG1YEU+/w2LWq8/uOMwtywW0NcWqO8JqJoAqxvHM4ijnppLPgJGjsLg4mMCmZ5E4zE98GsJshEayLoxRRHxcG5F8YcxvNwIWT8TGpi0f8Dn7Fpapdeu5Ix8HY5b9uJLmYQgt+GVT3WvqPB1yxeFU6OBzWeGEzuioui/Zrl7CTtOMrWqoKT51DaCQV663LqG+FdtnmsjPHJceNNfgMvF7BH7HnXgy7URo41gT2Y9xymHMrR1x67qx0epxjLjfJfbE7+guagbpGi3S65MSBcD+LwwGnro23sQAe3vfbFHf8DGsPaxoFOWvnEEx4Jx7gUpgbarQy6EYwv/ozlidP2heIQDOzTljPOiy/QzQZcIm0eYmtdjMbC66rN2rZWg23e8fEXWSPCQ6TlCS90CHPqBjyD4aRu+zpOTcSrHTmTIhEm1fQ6wEW5Ag6MtgV9nOpf3dobLqZwIGpb45t/BD1fmOu75qf2CWAu4hVpMSCtLs71z5hNwySzfvXiWHv8bTnVhnF0PCpRlYMP8osF9rbGqZlyOXTcOQ/m1L0+iXAHgCnwUa4/dh3Dht7kM9gziiYcA9a5rpH39XF5jCFEhVOL9V2O1G5j4rz/M5Z7dWMTosaUD6yr7fkaEbXa8jyxsO9v9Sev2l9+9G5NH+aMBomc4I1/OJdFtVh0HLMphnbc5+SnmVzxGAtXZJzERnhuS4Aq/yM2PPSfoMSoL05Tt1ogSLtxMEZEwVi5WIwmXiOiRUMbzFtuK1+O4k0eeqXfOWjshweixi7CHhFtNHvHZisbDnkAX44rG45x7BpqXRbzMZ+rLvDaYPYP3OksxDmr2Zxyhqu+6RV5TOHypezYTiUDBh4HHszCc18+L7D2PYC9pWi84Meeq93urL0SnaA8SI7h/gEPFv7wWZ/PuWKNjVeTX3x+epm+Ojb78+CVMX85pK55cOvmtdjdnHfDbD/6+ydEezU9obmSDUWvZCUGV9Cx59z3pw8nnhCIPS9JPZvzYBKf98Z/5j3UuW/kaj0bfK6es8HjQT6bVLBonPcqmgJqmx/aycWNR59IQF5trMIVbpcELeVbi+ET7tRk56E2sG8srWNjvCu6PayScW3XBjxkiBvq3lWoasx0ngNYbmTGlZiiD0fHkbHbpYY06lFuDcfmio3x7/+dDwPLJu/1d98+8VVePOnBBsZXA8ymWGzqnSu2ma3DGbzr/eR5UoZQ+XM95/6Pudr6Ujc25u/yMnk25lx9/TXfAoC8OHzmAHPx2a8RczMF8WkvdoM+9SDjneMmX0PV4dUnwWR++NKxDjHVjv+1yCS+wtEV7hyXZ5OsmBITe/N2PDEQOk+DL5McnCkcdFI6MWovP+YtenL4xHvRkzsbcTj7ipuGzXzwKeuvvcrO5wVwZf1dnvh4dz4zIE90ESfEyo24vU3z4ptrs9y6U3P+/AC/rIOf//qTNtw+eDLn6+Bv4wlCrqJ/+q33PeBye2eOCQk2V/8nvLf9HDLmNh8DUj/crjqs/ZkTAq46SuuSM08Msrb6fyFP6uSDK03uHMm5dYQ/vD68+CCvz3lyjzuo3h7CZVrQ7CmPiXMO28RDBm/7ya2mtZfzF7IYxn6JB5aQmD/INyLyfYk7RsyW2Dm4SPEbEp3JGLURoiY6VIibPUgYu3Ip3ewYE2pImbi+F/mDE0PsSKDZlKN0EKHaKLGpVY+KDURPxj2Kd0Txadw9Y336sb0KCgYN/I0V2YiBnely4lgkNGQ7uX1QgmGctC9aB5OrXj3gd/IfNzW4w+2Gs5jwuXS1KcYAl1YH6TMszuQUTFMKvjosJ84+aOj5QKRTUOOWwErIfvSxEQfc2ndei3MdL7s4aIkbtjckMUc8MVY7+es7NRJ8OGZe9okXwA8GeWdwaoePLp0D7Doujx3K8OTVFNHdc9PXSOOlfWznTvfUiJrD6chFesBa3GZTvJmxM48SnRhYGN/c2t/5HvSkNXUieH/jU9bEAaq5cyZ/su658lhhZIyRGx9vGqCD+CAv7G7Iart2hFr/aOL3YDcqeUy/NIk/SPF5yM3YG6WxGRlRZ4BuuUWmbnksd3CpQ8zLls4lKyb4scGH/O9NHATVm+eaDc7OM2Lb1H0GIyRs44ZI2nAYrVHv6x05wtjCjVb+GYM/wXqqfu2w1RXfdMb06kRY/XDATqfg5kftADACZNehdtgqLzJHOZ1I4NSkyFogKXbOSE49HG921cFB/dQkJv0HOQjL8+BwH25QLIsNxZUd3ms2tkeOIcXK+cK+OIFZsKldrORogbeOnItg7BxEiFDk3K42nvPHYWLWYnwTqUzu9Vrb1Q22MXAochmnT36SGQl1nEWDKgP1mjGO7c4HMm0H8+JWfozvMjcS+BsUsMD1NLgNd0lrCwa3y2MbH/ko4JCRPAGrVVNAnt/JD53Wkd3XYYaVY7z8BraIgzl23rZRgJ1AO24t5oExegyCfGwC000iqlQB39icxxU3rNaZB8DZ0HD5m7ZE7TO42lj4f4YPBOMBMldKn8/LzIl1/iLn/xEcvErrtXl4pz5s1MOKDfs+sRAz60OefCK3POouAeTE70a9L0PFn3g+yRAdeXuldN5HyxqQQ7/hKzVYm76svjVtjsXhpbTll5MU4E8zfoR8KBqbS68Q86QA6thiz1eJsRGCp4e6qsNO0xjCi0ZMfTUmYDR9gJw+KCJp2+x16piAafACD/0+KXd5aXIdGtaxXG7+CIdO+UGNGOOz8wonPtW+cTPKbZk54eooLy3/KV+p9ua7757+8Z/+x9Of/vxDXmaeD3ejZrcnbSQAZ/D13yc2shbZiEXGpt9vBgipvse8NrhwBfa3bB7ZtPsBaAF8PV/h1fdTs77Kf18h8DF4YP/+KXh5VYUvk9codn2ArQ+HrY2pWwMq3BqvnjrQeuTc3rHb+mlVxK2ZhY6cmloDXds3poeig3ePIhxc4JV24iX+4k20esZux3wIHJ9m/ym3S65sy4P1KlZuR5HzXn+uqLOJf5+3IPAkCFe9+3kB+Yq9hKXufvAeT2rFn9uYT6RNPvCgvnwiP3jcJnk7A7cb1gFXoHmCzCfy8j5uGjri+mqK8OwV9c4jWVJfvinAx4M8JowbH972txo6fFq34tOfko0L48p88iJYfGYFze9BT14EefEir+pIngyTrD7cz7zP1w1yP+Wrj3LfSZSdqynnhL/HTfGGzuHCNPKnPIf9J7RjOKrecwEqa10atxDIwQqz4MbZtW216uiCmQW/i6g+q2ckzByHG4A1Ke4OcoYaR36ZfNtUwTFwq0POmCavnLVVwOCSI6LhMuGX8xbbMyHB4Jw/86bjL8I0YdtvuE6aHFBHT9tiHo4VezT2wCFwSias7gFp/jFKf2XY4sZ469O61Fk5RvjnxziocsM6+dZUm9YNL1q9OweJYujJzaREFOdwwM3a1/eqoYrBLPJKHMWnSwe//J35I+yug6gGGyva5kx+xweF/DSAdltk+MnJHoOJS275WTznObqeYxff+gGF3dhzh0GEiT8zg9Ejn9hcusHVpOzOXEx+sOS3eSyP9VMBgdqMHdzlq+OEnzrAceN3fSx2YTKy/oM8zoVHZ1tu1gJqrdee4Uq44kPuahu7OU1Mca6qNp8wAMRWLx8AjyOS5bg5Hexx2zqAt3zqh+e9XTVBijsS25w63EEiGjzjPQ+bk/M+yDosCwdOM62vvMyfoAEzRHNjwPCwbRJKxRi/rTsPavb2rI8kJ/dBesATuzG3LltD/DeFxpfY8INq/WImwcUdK3PUBE7yCPLmiQ+5kFnBtTl5hGvFHAdx7A5+Oqc/eSJANqbpMa5VZeORgeHHVunyOTI4XLcj1wP89V3MrpJdZ80T7No1Pse0uCA/Ld2lrXp1mEB2OLZ04CVWaoncONrDUWjzpE/bOtKvrFVwzawDdvkxR3s61h7+9iCzvulOOzo4YQvJ4VOTBsEb/56uM/7XOh1C8R+L5greCoTJIHHOJnjs8bY2GdMn462z+cGNeGt//3+HbX7K4ApWnGKhFAI6cAINHigcjzf0NB5x7KwNZ2LEZ9yBiAT7ybmw+o/k5IQluFtnOcS+2JULGJu9Om0sYhBw1ozRDt96eCS5ie/Lh8ktGxh9yb1Gx8YxNuYTbsHkSjebe2S0faDOmKt1iJlvXhLP+SlXYbupa259v3p9idsNWh4I45hxc8UNolztytXvPICnPXvW9yTTd1OXK1tsxGhstMU2i6k24X0gzlX029VzNo9w5IF4HqSTQxu8rtzIiTqxCcQWHS/vlWp83Jz3kXxlAzOpWFAzLazjeE2omeeOVjrsiRRzgNKcnwg6rv9o6qexpvrXgnCX1cpGVGPBU9fE+X0ew3cer/j6pbbIeS8/Gmq+G2quZP/r//7Xp3/7t//79M//8i9Pf84nhf8p37nNy5x7VZU10bctQHZfyeCaAI0AbICyoWMT7uY/V1w/fuhmnNy5Ms864fzmuzdu4MFHxpNNvHUBIDaCbQFN6tBlY8naYO1STvIwpxhSH+Yjqrbo7XMeq609ePmtFCPAaMiPf+e0itvxBMCtfl3nja8EXrEbVOPf+xfaBosEGqPYXDq8Rn2pO3nlibBsoOWbA/k51/OP/1XWN0+scCWdJ0R4fz+bdfpcQf6UjT5z5pNsBOZ38mJ+2WzjS4zffvrFK+Rswvel7dzGtIcz9wv5JR5veUDOutjakMPGYmopmXwjl/Mm3WSLp1Nz8vbcEN628ekaKWc25q5Dcssfa9m1mhyw5fbeK+f5zvgsIvFy/8H66ppjPRtQbuXdFTMlGc6mKffWffJI/uRMXqwdc8s8FKE5NgDFmiQJOP2tBQCuveiu1/eACgvOtGUURCWR78SpVj4LAnOEaQ1SLPwOOe0j2DhDbE4nXsfglneLlAFN33ar3WNlLhB5470t/fWzeM1vc5HvFHHzvHIHv1ksWr0zmo4TMlZrevlMfYhPOzWlr2A8hyNi/qkcc42OjbUYjFPX2C6Hgl5z0hhhA178zHVJbhBobIvhPnjywdChUkzNlA3B9cv5SIJRPigNrNWJHVEXb8QzH8bSCtlmwblrr1XAjx4AnIYrfiRIfuoZokPUGzYmNNw4XrhFjvVI1745aI6H+DsqL0bIT+0BH6LGOT6j8A6zfY/DdbkYwxADMvqCxoNc1A//iX1yVvtHm3us4z9YZC1+sFrb1ui+BokLo9qeFB9yVzdQUcjVLHLY2jXPNTKROdyQG2hZqW996QJWl6I01+JXx5WHR7bEx7VSMK45i4x4ad4ZBvxwVB7HiYcNttpN3ava+ZfdlWuMjYsfzmnLYONX2iM24hmEWOSGJJoBuPyqK9dH23qgBzBHcWqjiEO1OYJ9Ipc7auNNUAdhAlR+wJUH91H0+YcMhmtbkYe1xco6LFzG6oYbfdqVW/rDT/n0iTuW9X+wwbJ+G/eStNfjRsN24kj/IgcPW0TymGHrVH9yPrc585+c6nHlR+9Wf6Gsd+ODSWTiLDNsKou8RV86KkpvLdZGsmcNB64+GzsjYjjfVVVvpHSH03J1wuSW+U7A3jaGIaHTSi2Dho6kilGXO3ZqRjd8MEXycJ+fMa3U63WvS+HvHK7bwPqJ2QKJtfU1WilYBYKAbSN3k9m5QJo+4lo0tKMIlc98DQ73lRs2arz15Ejtdm2DSbtwW182LrRTf+1YY4rrH0w2nLWTRnAkEFF6dPOHi1eC4szGmI0mDZkcN/j4oGOj6nrO5jzXR3NtiavZ/SR3uLNRch2IQSyufvVqG7d7IMEmBg+GX7189fTu/Tug9WOTmJ4PiGvYTTebQuNiGL5+5VJs+b5n3m2+D/y96pVCPsvVXt9rPhX2A+IGAxa74eal7TzZ8CGbjy0id08ypaiJQVwerLPpaG1ab9Reuc+D+84r3Du/nQ6AZu1hjK70cyRGWg1PnDP/6ou3vDBfp7oVe0F6/8poVxWw5V/X4uFrbIRpjiPomkpt4sNm1vrP40vqsXYHMzZsbHzZeTbT796/ffpf//o/n37K+5j/6R//6emf//mfn77NRpqr3HyaN5safPfDAdno0GeT7fdxZ83yvvL/+s//9CXWvITd2meD9+2bN9YeLN4rzaZuX3EBt3M/G5KvvuGly3lpd7iRA3e7mSkOzZEnCsLdPJCZWdOlMugokGugWdcGHIugmhsDgIpau1HrblBCHhxcTyMGdvM/Abn65cV5jJFvzZcCqvKjp8Wcxy95Lze7mcfPn9lcs9HMRpQrxDxBpRJToxPI28azV331AxtuXq7OHDNXzMlu3InM7Y/G7YDbCG914KsIuW1zX/D9jz/Y93YTu70dt2rN0CvsmWNug5unmKy9Jp9h+TX/5ghGEW78cTR1dHM/EjvuH7xvSO6mmgNPMFEL10ls+fq+V6945Uev+MOFT633CbjUDg7keT4wLnrWIU8INp/hSHx4pBlLkpIqt8h37k79leF35VlnpuQCpIvV+uuxcxfNi7OwIzxGh8XSuu4UCre2nIGUJ6piRFDZalWpRYGOI/Eac9MY8lhuEnBpFnrpvQ8IBbpi7KLE1wcWUSmbhA8mLtPs5rAP7veBQ20J0PjWKWxjGUm4D6/FlMrE2WykLUQx8PVuMYrrHzsGQyj++nDQhTOdOWFKU78Dhtf8gG9N9QGvWFhfciGFWhR5EQgsbki0DGnmOzEqin5wt04HP/YrmyTEWB7kVeDG2LpOqNrmuHIFdfIoz8z/qTFSx43b+SYEayBWMycDYWhfQkaqs47Mj+pAorQMW045KstBg8EtsdZ0+j0NQE4XxyJZz1FjazjG86B/rNTIKfGsg4b1WK5XfQIAL3IdzJOEsXIYk/In71os7J7BYJ5Mk7qJ2xMYjQ2P9Leuhp41h0XsaEHRvjwZ00Zpv0PfLmGcibu62IIxjsaD24k7aMUdLH3SR7hE9r4iItrWbetYTvBapObQGlzxdSajmN4sK46x9zcbcw1iaXfGd+4VbSxGAOd8wzDWqLaOW0GQm0MpLKvyjtXBCUBuz97+xrR+u+9KWB0AACAASURBVLaq+1t1IZb3c+Rx58Egv/rIueEwGTOyaQuP07/J6PY+gRow19PS2dtncyDPtgckfSaa5GIzhqc2cpvcj/0VZ3MeiUlsLGeOwY2YYYJDK3dClvue4bBvARJDgQ6DFYMAPeSMOn8NNz3jdI6jGl974xu72OiD7eTKfeG2cupYu63HGiSqNsNnsTjbFj92uI7wkeeKySD2l91RmNsqTs1jLuQEu9ejIuqKBaM1SpcwQu+x8+s6PXXAAO/YmDPjZKreXm+vkzdRNhao8tKv2PoVIXDRZm/Qyse2uwVJGU+7HDzHHwogChozONgQbDRy7ai6Hs1gNvDE2U0rGOdfNHzyy4NVOwAhQh4ZZ3T40FeuTQ4jQ4+Ihp6rS8UbWWLLBX36bAS6+Z8qTIxv8sD/dd73ygNesMGRi9ziLO9c5crGgCt26OOaf3+5AphS+EB5nhA4j0EiZyPYl+PGGH754WoZD8Z9XytX9LLZ5sOs2Dhgy/d9Cxr73oc5MiH489Jgr6C3DMqx4OXD5Aavely3wa0hcvUcqOF414O4iB/Pa0N9F+fhMape47fGi5Mx9Sfu4mJO9XdmiLY2uk8cFiA0ictGva9LwDvWEgCouGAzJ7y64X0+kZ2xH/CXDQvY737Ly5t5WXw+IZsNumsh8+UTJ1mQzKmbm2DAjc0PG8B/+z//R9yvv876yIb8Td7X/jobdDbmvIeZTREbwD5ZAtd9VQM82aTkK7zcML4Mp27M2VzC3/WMkflyzl+LgVQe5D+zURX1UEBnbDSuFV3ybX0ZtXXeZiBo668dY9Cd952J4MhrcWvzt2S1WDz8CjWopjWRTw7OG5/VkJqwbtmkf5X5YH1vsz7DwfnK/HHmQ9PYyGLLlWbmk037sw98JRmr5KNPtHD1nA8M5D7v63ySPpkxTzTXYm7rrBnfHoMwsbh9+haSYP/+vK/KeMiZ9TFrjsT29uYVbbMr9j6x1BqkynOnZ9yEIu7BCZ6vBMmZ9fT1N69dX2zS4Ywt9SJenvLJmJfCs4byJEPy58klN+d5hdDn1IdGnYzJmNiIq6p+6oqMNcCv9U5nV8Ceozo+8pjxCM3DPhjEg2tar6AjZKQccNpCOjBwC1P5WZQBktQA6jx97O/BirrkG8LE0m3MxjIOYSL8g1wxhKMJ/pgpRWRiJ37GaRQJy/LPOA9idsHor30jFS/2g0Ec8xgm4Fh0w2N9cTT8GV9++oAnZx07+ZEtlkBzYFFs3YygXYGF4bC2nG/jlXPuvDCTxGnbvMzJgkUe/0LEDhm/R3f173g4iIkvsYAhDg8QVRDvdBpDSS2rydHhYPjgcusEauVFqh/9S8po4nIeTuqFSXWbWLkRjLHzoKveIFfV/Lc2rRV5akGgaReXVVUxeTCIyf4TQCrCzb+Ikd9ujDixUjeQdw4x3Lwao9jLBevN8fDceAcJz2tNY0eci1dzVGINy85a4Rrrw2lGtZg1nnpuzfBZ9D0bG07HrnBnjWUo/swLPNpy3q4mxVY3dRlDc9k+HKxLBIt1cYkwvteTM/UidGPFMhO3/nQWQ5kc6d0aa2qaNrd6Ie46ahXhpsxjZC1kO9Quggd7/PPT294VxxxyuK8N7cakPBq7dV5JeRRzSBCX7tRAHcOTa3xz20TOrws7Z82HM+7q6dC0ozOg9ra/gWrESIcphvGjQsvx8tpexPc6TU2ZY363Jp4H8/AwJ2CLLjhhaOq+nANioltcxuNbMVpr5bxFvXXbevQ2Pv433nWM/dxn9v5is0bbvnltzOFYPiLkIDktZpZUPKx50E6d6tf6tH+OwYeH3G/9vb1g1woMt8mHuGedJQ5a4iOnbWz72Gpwsd2qrj2ezZ8zbfF3VFw1iXes7BdXhM2ZXI5R8aDWuep4ET0PpjUiC8bxN4+cxW7wHBcYfYdHskEjd11nPCZ5kNi4HHfNEIQY4NQ1SII2Sje21bNZYTODrw+S8+CcJ3tX5sZ8sWPT+SFasXz5OX0C5UH3swnKmO5uhshl1zCpsin+nAffz9gskUwan7b9MlfPX+eB8a/5wC82UOYbhz7gzyi+PIh2Qxcf8F8+f5VNX1+SnofMAe887ybgd74DO2GI72NkNuB5cE2+XBV+FR683PZVNtzkywaRB9ytTXjGDqxJzVqy4e/V89QkOpTmnDjyjo/zrV8TjKVPvJEwEmpCZ9JnFBk1tutBDHsIY5mT6+eYdB7rQs1rU2c8OtZ7dLWNhXOE/80G+/y27W1iPaogz84vY2o69b7hdePD2vrq6Ztcgfz+u++fvs0TL3zdGVe5XVdMRnw/8kQJc50+fj55k/5upogOzuvX2Zjn6jtXznlvO9+rzvuCeWIFPNfX1O/UCBxZ9mXT2TmdOGymiM/GlKTNKQvFWuXgfCHPT1Gu0oC/cs76GIcevni0XozWs7eByC+RfBgvpgDjASfaml+YyKpb2d1GnWFWCmD5iLnUgqF/5uLz57zqI3PxLPPz+6e+RSBFMQu43Wva1FKD1N33X8cOqrXj9jlXz9mcc/U8tf707qNPomBY5rzNJPG4L5CHN1NfCfNVvgaRWjmvAKeB2WxCPr+OiSl31k44xsZXevCEA2bMEzbTp8P9X2tA/zEveL7Kk0C8X/71t298Yo8n6vpye74PnrUb/rmv8D4o78mHB3++3D9vvyhnapO8CGz8nsk8Ec2HM/nIT0nnWbIz5nTslBUTv7a/0UNEXjkR78WZ8CnkJq/BRDcIHDPeiS5OydofwDtBIQskHwtOfMOXgIo9GK+J849mYx316STiJFFRxorwhc0WZgtazCun9Ep9rNcez/rTs8XukowTGRx/tI1rnaZGRKZtrmcmYz7zLq4+8wCtkRqwtVrsAB3czUn4cpu6NR4o5be12LOxqq3zJgH8rd5nTZgDhJuHbEiLzrbEZoNYcRSjW7P7HO7aunIROEjBEJxuOsFbzpWD3zkk7OqIdfDvPNJHfnTCXsRWXj4jB5gWSkiwqabH5oMyYwbH5poPLMvtio32oel/4TTO5r+2oGDTUAczsrK54nS8HK66gUSofSC8HGq/8alqW21xyFhh+/JLLbbJpSCnvlvPPWNbmPLp3IXjzGvPhIl+6kGEwl45ksD6WI/YLONuZhBUUt+tQ7DGNxanbyxdJoaxsUgLATFKPP12NvPliV1b58jS5LazzSdLdL24oLvXDc6Lj84MiD+1WO7aYDvyohwCpzZDFai0W9zxs85rpCzIctxqjqe8LEVxDs+LozA1bykuOlUF2HUwJdnYnDeaqrGDrU1e9OFWjEI0n3u9Jvx1wndbIHa0OISoSTTJqRZYpe9vzzgqnTroFBWx/+aaRScw/rc5NUZ11iJqsTnPn35D4eKhmSaxlMtKljbrfvN6rMmOCLCtfcK0XT1j3odjId/0T87kxz5sbnC4gFrXqy5Idq5rUcC1PfYnu1hNzXZd6JF4/X8yt1GFtShGEdu/c7n6y6Pn8jjzjiN/Lc2cY7lE93wzAWH/PzpvMV4W7S0YhvntYgt25bt2DIto/RHgwHhskbQNpwwWj1jtp5cHlfjkWnIeKqVmebDN+41zfUx37HyQPFyQ9sokZwb5NYl0+N+fB8hgPAM35zLvhldjUPGjAcAvTw5kf+v1TjbK2Wx5VTRX437Lp4HT2EzLDdz8+AQDG/s0Xo7OXSd5cDWvn7w+GwH59EE+GH3ZaXjmiuG5UubmPN/JnQfkPLDmKix5sHG419Ncpr5w8YOsXuX959hHvmvderK5D1cTHB+LkWJpl8GWIczNAzm/YlU0GtXpxyc1Uz9n+jTnc3y0Wc9C7qi25xiH478spFAe2MWk08RV826OHDvX3eQQlrXzYTbYwgd3ubF5e5ONDn+8MoKrrLzqYDc60k69/XDC1OyrfFAY80Db9ceHlLEh/zZXzr/N+XU2fItj7tSNn2ykmj+plcNu3tj071q+b/qoQWeq9s4DsfNnDoNtEW/1XDt4Eht7Gn1a9eVDDBrHvb14WxkneGFzrJhf1i7n8cW/5j2unNHa1R/LaSgHd9eXYzDz21ot98T3Pjpr933mIXPwO/MQDtRLGukvi0Zg3NsJfHi1A2258TYFrp7zRApFJqcW9vLx1SZsmHliMKTghJGb4PSfv8yTeB8zd3Ob2hyJsXGujTlBasGG2bkXrZysMH5EChcxMuLM/QZXynnp/tc8kZQ/Gna8x95XCsQGers+eTKROHw4IY37FD7MkE/Bl3/uSU8jKKlNYz7KBCFzkPPoN6+7xVFitkXQs77rA3wRORdz3oMeLzaJtvTJZIpo0QVdfZ1LEFNs17OTRECscxqoMaiZx6LVXkFM6jep4XyzFJDD8EIlRuK7eHY8inshNh8LO7gWQOJl0iToE7cybwRrPyo1iel5TeGen8V/8NNSg2KnW9+dYkewPs2azmjvFFbZOIzwm1kIR2PLYTKYebnbP/CibpObaNvP2bTwL1PU8yAtEu+QKjL+xDaqlOJPjvrPOjjmg43P8CtbIz6EmywOx6m4GbNCaMYZ7F07+Nk3fo2w3lwbt/EffRoehtj0qnQSIidaQIxqvhWtihE+jUHOnY0ID5eNH0EhBbNgMB5wwpFdOdT2HqVmSupK5NqXRAwADkr0zQ8fg8kRM2yWz/I+tjGFg170N4dIKgcgbfO46Qn9+A9Lw5qT0/Q8lyBhhl0xNTnx62M9UMSnG+Ct9SULTLy2bhkgSDMTa9Jx89z8wG+/xjfcBQBjcsRmaRNAX26gDX7qLdbqbzjUzBxqMG6ND9Zy27nZedNPn+an3eRn8Nx3W6M7zxvelWJiSdeDYuMOx4Wc6pQlgzSuoPal29V2LgJH/iOyM8Px6in4G+fU8uaGjEb81hf7GSOzj/bqg7c2W9fNbeW9DRcTz63nhDOnBVlZo0zsma9T/xid/yv0ZSytcp+xeSCO/+bbq+Rhpkxl+hcnJPDeZk1i67yiSeBmDERxN/zJaxC0myIsx3Jay40yZ/DS3dzLozL5zoNQrSlU7NuWB+PKynfUx4o5qF/PUWTY+Rmsre1gawfqcFv/CxmAxQCPuQErwuHSGRp8Nen3NyMsM4gfbtxvta4o2tcmfQ2wwUM+9xgTTajoDZCBPLCrn1aLFbFzhPWYHq6M8cF2GjFp3rfyIW3458BmF6T+YRG7yN3EJJ9uoAcHH22xa5vQ8YoPV7H7PUv5X98H63ou/Bj3AX9489Lm2EszD365+s4GmY0cX+/029vffKk0UZHDldrwAw82hi94OW7OhsiBq1rg88DZPLhi6g9TAIFu8OnynnWunPMSaa7e875z8v3wMR8ANZsNnjmgTl5Fl2hixY+r57zEHZ3RJ9HfebnwblYjI6Jt+szuY8MxDEOI3sGK2drioXxs1vYg1cDHsDvn2JM3NTACvnRs9dQtwl0bqAaqZqUWDDbQtWu+xdU2B87OwQRoXEJ/9fQ1V8/f5Oo57xPPBogNO3PpB2oRO765/pgQ6Sce84Zfr4SyccsV+Gya/pT3Lb/K5v7r18HglQ68dz26rYs1IX7yBINXQPRtCl0HJOSTKplv1ocb9sjMIWP8YEKl91UfGdwa9aud/LSvuhWmDwYILZzHsVuZKmzCvbY5xkYexKaXsfpbDGyLfq2TemG+cdeGc+yoaVTwVXMb8z/3qtmgx6yswMyspIa0zAIg1oxI7JW2Bg0Np8p0yIF55jb8Ik+uUOvfc2WZrz2UkPc5nSduZzwZgPzKWdKuk0/PcnvOXLP+fKFD4uzbdIiFv1zjv084klefIIs+scw+kNZEppeevPiAQZ5M+CZvm2CD/jJrlvb2l9/cfLM5J1/WDY0aUFLX0+/5rI3oWXPE5Co6X81GzmOuLWu77VYngSK9cbMOa0qQFlgjzLHd2gO562rPSE7CmMff96DjyyTBBkz+0dWpRvLjsHJwYK0Mb7odu3AULEJ1FJjWYzqbQDBXdsjLo8UQbw3Gn7AnOJzmBqMYvNjXhjzaCtEjcUw32iv6QOKx/gD9raacWl34m79n5JODcNzP7P3I4JUD0QcjoYgm38VXElnGiPTRf/wSgweMjOp9Ydy5DeqNLzniM5gTT28xAa1eo7CixmCKO7nB1XxvZ7wOz9hB7aHKNRAHbPPFItj2wR6MeyyAlGOF4dp3kONgsBaGezHVQKry9ZMXDEAeSM5jV9lo9GkWJ7fI0OJtDToYNjMYHhji1zvHjbf5CDJIiyfsxVnt5KHJRObkA3cNml+6IhOTmgy/w5ZcwqUPZjEuFgjCjT++lELhOdX2bDYi7zyMoSWeetziom1bPrjtfEczFBq/1iNaR2lOlIlZ1eKcXINbnHVtHthtHDWnBpGTKOrlxCxewRaIilw2+hAJ1+asC3DHY/UTgvsB7BFzw7VNHQZjseQyQJrHVo91G++DET7l3xoXZ7jxz/2Gj8+pF/31nTrg5TqnltYkRCSO57BBN750Fg8L2n3cNFqjtS2zsZsYh0f8IyqvOEwZxCXmQysJHVa3Z9APX3DIk2ffIZF2xaudUOOB3rGmk83wvK+TxcI+gNaL7uGvjxIM/NN//meBXDoJZP0NODJ0Ged/h/fzgmI2cTCNyak18CObFDE+nKLVV8w6HvvNqdHHR2wodO7I9dxvyHV1Ap8lrZ1U6mcQeU0+ECF+WuPZTT+j/JLfNnq6VmWuxxpbBzlq1LP1gLP/C8ZGvjjExgepg0JN08jRNrEXYwip2jo0GMfmJ4dM0JV3w1BnYSfs3R9bfvF1PhlMNgbLYTltPTx7YQfcvGQzP3h108IDYR5Ysvmhz6KZK0YSXFSAtw9OcogenuBbHhac3MlveAAX5eGU2vLgu+Nuxti8cXX0TV7G/Es+Bfw9HxYXAF+mTshg8mCdJwO46sV7xnsVnbh5EJ8HyTT4SzmHT8mTvLrBX4x+8vdrrpglnpvz+LC55oOieLBN/l64ISELwYkPgcrL4bNR5OWwqzKH5L9frxbLyRuX5DwFo2zltXXo/LdcrRU51uruNzqA09bCAYAWfzXoi3tqnajK4BJb1iaSxiLaFUvMPZSsdlYhBzdLlBn3jMXhTG0yHz6pk/lh4/Py+Us35149Z5w/6tZXMzRLNvdw41PwXXsZuwnL5ouXW/NkCC9tZ9ODfzdszE3WTOJsLXhyhgEfUvfe7+zmK7yyMcxtFV9eJcEHlnWjng0Wm/zE4s4x277mE38x2dhFZf3odNBYBEyjZjjxs+P2RwLW3Edb82D4+C2yPo5r3uu7ZxGZo9gTgbb+Vx8ho7blwujqB4NYrqcowIQPvPKzceqDrJBomNgdK42vn8mACr3+eKZlmJtK5oYnXqhr55HbCFfPXf+5XeXGEQq9fZpPXFlLWQyWVyyC3hpzzTx9Yl1lLpnP8gnc3NbBYi1wdqOcGOYMzZDzJe/1qpwMrEXXKN/5/g2fZ5D7AtYam34+qZ6XtX/MFfG9LzSP+MU56fMkT76Kjs18hv3E93zgXuL0Kjq3g94eYEGzolPU1hCo+22xdmCcWOnv2NIQG/3K1SKp3J6YSMDOkyXXVHYxPDpT/Fkkd3BAIidZCTjh6V1xiFUmnCfoERikxvWvqxMz9pwuv+qJeR7X3oMZ+grenPBpAcGhlTO4Dh8Omw9CzeGYJpaptmArVTc2AS7m8Nj4nsl99eClv3mufCdjOUDvQNuLRMFopg5dIJetnDikLYdNdmNUWxxuzBeXaBCT/I0vfijAW37YlB/HYonPHcPkd9djQdNy8ii/1UwO97gTY/nhf7ATZz2XgRwzWPvzQHLjjoMchj1R5U1c8BOzNYVdMx9N7cZvY+ikYw4Bru2eM0LQgOXF2BwxzoBa09I3rrKKdEyeC1I2q8OlFWyMO1c8ln3nCS1INM/EJWb++a3CucVASnikM+rF2zNmh7suwZd7z1tD7c5hOSF45F5Jj+WKHqYQSA9OGcqp3R4jc85Gtj53LlHZ7jrnz9ysxuQyffJI2zkeafkwiN/Q8Ywt8TbnupcpMTcf6oXOMfb5KfbUBT5JVJ4bFPBpG7PRV8p5SK0oQ59AGVXrU9zDZfD7LD28Wh04Nk7zKcTFj/HhYTIZ3dawKDvGeBo+tJNWOpjd6yO32wOLLx+MFCE+t7hy4UFCWvHSUc8Z2UZOv6K7Wn3xLv3lIQTI+dtjOoQ7RjNfGKS5BhLfc3jdb1+6hA/um5s+AWsGAlzQE2cfpOl3DINBnvkllrWbvDef5SkXAiEYe2yUhxS8rv+pMRCNNYEPLbN081M0de1qWYyOZiVp5kFfUKJPsMIiRFts7RwrKrdDoIgbS9uyTnedAC6ysvSXx+ZKcPt7n9ekxu4L7uZXbkQQmRANPpLOG55b8xMLZhPvJE08Ynfva1xffUIAmpzpgJdNx/ojSmPMHw96aY1ltteD0DzS3g2QG1Sw5vYBvlzASvea8xWXCEd9J97y2PPGJj48nz3jPZyco8kDfF7mzkuZf8j7O//jL/+RB78fzNWrtOHC5o4+m3PObuq4rbCpYlMdGOscnYzmTHwerPty1mz8uKL7Td5vejaMMeY7jdmkw40H+/CzQgBGz4iXXL/8ph9wtvOlOtheTcsGsa1Fcn5l1DUiP4mNGaf4tqlNqK6NCSsf6wdObEPP3NQf3yBEcT1uAaO3UyZrbT0PfoGI2fjVTf0k5K3O+D7pwUYIX9ZEXLB3STJ5xI6cDRXv5+ezBL7NXzfG/SRs9MwXzVgNW3wXVKTBccM1tzM25bztQZ9gmztzHUFm1Hzd9kXGB3Xxqe9v8/aIt9mkv33L12HlKmLeq85713l5PFd2qeHnrAE27uAwjzCSjoeiT7By0mLk6eN4L/2IqtjiEGckZ94mL9gbV5BYNbHJC7Q0dJHz02DpZcxasI3POmkX3MasDzLnzGHXgZg+NqztgI1lqZBgb+NF65MKSGE+ONjECDpsWH0SJXX9ivdq81aG9FkgfhXbbJzlGAc/vyJg4NHOk2LBIi0355/zxFownr/gQ9gq54kCX/kTjG7IrzNE1A2euB6a58ZiDfJEIFfNv/3+u/Mp81wB98r5bNBZ8/uKD6pAYa194nDfwKs5nidP5Nz2+Z54IvEWmec8weRab5IyEIScl8kIwEaU4dZn1wYWve2rrhl23Oeltl27za8WBXM1p5BlR0XTmFAATzMok1k9MPwsCWzpH1nMdvEtKbC0S4zVdeGM3GAGKtlDoOiGVpZDCktEmiJ7K+mghUHf5OVBfvG1IHPnhJ5fbzBYi918zodETV2O3djgaN74iyeQeGVRbPrpWaEE6g1mMVCoRY9R60P/McPFnjO2YIAHcvq7GISb/MAmhDYTh1GlusckWoKBB+TBM0i9MQBI3mV2cUVBu9V6HmRfNgYIctpglcPloz8W0DAfjB3G5Vo36rDjN3EWB1vwYXPsiTV3pisjP6040e61U3erR8ZGwGZ+cpIfroOk5qwdYqaVJ8lgiFN5qURUILlqY21HK7AOAKlGsznY1x9h/vQt7+WhDN3wqQ2mzQUM+6U2PCbmRBQaQ4LwO/8Q5MEdy96OiK/xhY3NEjdXhsQeuVnphmPcbzyx36zVxo52ZLFtHgpzwAojAAlUTCTtobrprEFk41e7xjS2+vGMsmljFQ9gLtSrbmphMHby0BihchFXDpY+HKcu4zsOw6521pwcTuztc6ZtTYKn6JK3Jh1vbXv/OznLqSjrtZyo8wBqYO4lPuObn/9sLmvMNA3+l3O/NaRehbsig7ghTj0bppox5bR1AW/7zjX2Mdg4Ap4QSIt8fMbeqwHkPJwRtxXpzsf4KEO2dZp4rp+RbSKababxxOZW98bAKHGik+o5DMjWEWM40sDwNNjGnnnd22v0WGOxPJ2Ph6IkbgzUx1huMy5yZfrBUV8wt5IBH+nW6EhOrsz1cNv6Y2QqjXJqkgW6seQU9fKwk9yIUx6NaN2W+9aHGvBrco3l/daJ25xRL1b51EBqdGmxAXbrlKEDb0sTbzkXY3KIIwyriw/14FQjUMT+f22diZIkR3JkCw10A417OFxyV0Zkhf//WbtCLmeGMyTOBtDX6ntq5hHZoFdVhLsdamrmkVnpGZGR4tmPPXFUoEvvxO3Ckxe/vPg8jnmxaQ6RdcHbRRSLWXIQC4M04nrWEwW41Ej+2fcEmXJsrdttf/KLKXH43vT3uQw9rIIDhyjym1s0PX3z7bde4v7jj997hkpe0cEJu91Td2uPa+TOD/9b8uf0pctn0GmcKX+RNwBYPHL2nM9D7+ef32Rxx1kzFvF9YQ3eZG9BEzP23Imahce+CSJwGLzNCuJtMMwxQuqU0IAoq53puZHzTJTluxtQR2qxGDEQa8Xui7u5MwfEpiG74iu6NuBiix3zl329EMRzMNDUqrkAAC61cWGEIA1/asHCnLq4oM6bH7TPnn/az55nIbOXt2MLBd8AwSgDeC8u3NDxRsnTe+4q3oXfdbly2A5H5xoC+d/x26+/eMd3PhPMGc1f8l3dP2ex/lvmlM+8c2aTRRSLJ/BdqMeVBdjejVtiVMOCbBUhmZaYHE+nZczx5puoCEe3NUN06ooyv85Pu+a9cbQ0p503jVWnd5DEDqiPE8Cnv8dcY+gQVaPjTyYYF4vuaqU1XGqP9+LdJM0VDCZPrliCOnwMkUg5Plio87ER5vRNvsfej33Maz6xwQib1gPMRdp9cCLkj7u588dj1Y8tZKFPfN548TgkF/4yp3pHDqvVIQOnsfIYzjHKJe2+YfNVz5x/lGP39S+vPXP+6sefrJOxySXHnz+lLI50gwsWZ91ZqHMFB88hvyXfX/PmEPHg4FUlMpo6Rb4TYTdg7iOGOVvw5Zs9sZGhM+74rz5imzos8ouOMftPBB1BIVDW3Mjp64DvFopw6VePl3AO9YyOJw9oMVZ2YiAYTKmxqd0ZOi4m3sWZsTtZR1Pd+iPdxOFKq/ngjy92arHhN4/c5YpP9VoAWOvsxHS8AI23scRiE9tOVWUdbQAAIABJREFUCWhpD/mCC6aAF9/FHXvVg4JHYxeX/skTJGsbqxZdrzMnGRkRTtGvnLxgweaeFyW53tnBYJsoDjY2AzCKP9j4Izycxig7FQkATRux690xQDRJFFd+FWpplwAHZwIyjvFycw+e6gmYviWSW7mXrHD1vUwnN0CwbX7yvWMaYmzAhbv2hjZnIQdXZTan5ptr9st9MY4tmd2wld/wDjexMgoFecYG3TZwxYkAlkejXWTUVV21m2ucjq3ZZXO48mKKNmBHDpeVD26H1DHmquM0nLVVg3LECrfuGdxtBRmvW17j0hibz9GXU6l2a46FcbsWwnfwOy3g13w4WOa1hb9GUL6BbB0QxWbnrf0rzHJaz52zDeLjZzAEMtoIrNFRQlTgxhpeqmceErzz3KjE0iP75QHGyQNl/M88YwUe2UTXfgTaIJ44KNMOpn28VkbcsUWmn49obSIC0rjEoE9zryJ9c5eJuuJdj53lrDKb1nWdV6rCgdyCuXZaTj6Nmy3jsSlCZDV0qF0EcLm3O5dTg1uN7tzxkwP5bRs4JfbhgXJruPtHh+WjFIfElNvikQtc84vtnceZOxVaxaaItescmBs4U6vl/rCHgPGh0GDn//Dywp/+xMO+mERVCMiwbGxgD27Y+3yPaO375DhuYJP4NT87l6Du8ZTuYy4IHhrW2I8dnYmonHIapnEOl/XRWks2aeGdF5fWhSG44IUrdzwHavGM43Mw+vyxIMK3briedv4vjASa5jsvvhHzv9+5NIcIBgDO1mNs6BuHs5jp82JW04J6Fr2Xjr7JDeN+8oWyZ895wZwc8O1Z9Tl7i19kvvGQvlwj4uZNxOaF8ou8yH+Zs+bcUZzLnY2fQvB9y7/mhXXvFt/3GfomRDJJIbwUN1iePfdztbyBQYW6Z3Hg4pyz72aBrhYAbF4u5hi0+OlkgB6+2VvzGePtGKDRM/s0t9jZz36S9U2my0J4D8/xkVshxmq4OcJoleVDAGLIL1Fz+wIbYz7D7+XDie0bLKk9i3TOTPp589Sbz6BzlULfCGG++saPrw/j1QyL6eMyuMZKPfkM9F4VwVy4sI6p8+4x0Oz9vHkW3hw/8GfPV7Nx7PC1e/yR1qufs/Ain2yKEa55A8CFHbLofLyMjbETTz7xd1+qToAln3qho1m9Y0ttK2e3j0UktaueGqyMioyHeGImxuLv66s71rwQ0t4aDpoxjHXhYyQWHOtxuDiczcVn2GS3MZ27Fiu+5abOvHnzpY9N3yBjEZ15MOML6sSkbPpmzljUs5BnD3d48lzEnqtcXAznTDrHBV/j513U44e/cw+b9P3jOYgz9uL0zSAyZiHN4vyLr756evnl5379G/ivc6XFzz/kIzU5A24jZnjIgXx4QxM++cvGGPThxRU/cPsoX/XIlRrGyH0teDMozz7ySCLFDSE5wbMSClBcxhFSJm1Or+NRK9UGWzoOsnEP3OANlpe4bzj2tSMEABmNw+rQgwYQrXIOzRNDH3T4r93EjyeYtcWmKPQiEzP68avtWOBGd/j4j5c+B5viJmaCww9/XMRJ797Xqa54w2pacRgcrKOPlVWt6ckPYlMrojXS2DCGJ3iKuqW78vXdemN4x9COmgwCuwtv+1cOzXvyMFwdtg7rcfgPN+On31R07D+PjQzMPLjv8cFrpTcntM2hMRmVv/PmaBAMtjqs06ee2nTLqBaM099aUxNrX/mH23t+61OsibexlooAF/fbkGT6d2yLwZzUo9F9AoTf2OF019dqeGewT9pJRJX1stsxwhMjovZviIklhv7IJ3B2e9yADZraqdlUOkINo1s/xkSdWPtKKRhasNenFmu7TveaG18kYhd3oihdTnDonBd78akwnmWfXoaV1L6cYxIhuCodoEcwTe7FAfvYSmYR1/hiiOWJrReBbrEz7HzgO3732iCmftvUxWP4lHAjbM4djQxMf7MhIZMaPKjkB0tgT8KRFxeRAyDaNKxc2fDBHlPw5IF1BajENw5idWy2RbI5HmrIoufvBJ/x/K/b+B67GfRFam3qEuebnFya6+SMUhk+BALD3WMOyE+eQtYoW8w3L4Sdl8oZUw+w5dMuYv3s7MIGm8TYed09lsQg/HJzMHyJsDkd0MGp48Q22BC4x0n8kpvEiZU/Yy52DQahdvLL8zh7mnlmL9sFcHzpKg6fK9T4RUCCK7deWwvQBwMzBmvHyPg95jY2XO71qwOejbF1BopG6IMp5HIsrjbGmbnAOMfr1t03BeA8ryPKaaLC9YYPDHbyM+e7gcFjvvyDgb0Eo5vCAUfb/SIgK8Mq5ef/2sq197n4joltNICw4GWByzh/+3/lYJKjMYrPopWTWTRzYn0UjtYBeTC3RuJreW322GHxxR2j5Rf1x8QeHl99/XUWZn2B/yY3b2OBBz/PatG35rWXD/DKEpucEhgfLofnJmOcNWfByItqzujC4be8OH+VM61cHg22+eeFP5y4Iz214Cy/N5LKi/qP43vsTCz8w5EX5OCdnHls46sNVEJokoTaTbNkV335kELa1koAMHjc0oIPrnWPqLiR8cvAmNgo6iayZGmMaMZk2IgHcJowWjhAtWpqzeK8daixZ6JTZxbjXNbOZ3n5DnQvA46cY6uWwOGfN04ATCM/9cSg7ln4sPAGg+abLuxjPy4Zcek0Nr0hHGfOmcOfc+8CvqbPs+eRUQJt4ogNl74z98amRi8ADhpx2VMsnOwTBqMM/BtdRh1355wru8Y7VDf/30Ahgftji7nwd+IYPxwaceYFCvCK777Jo59SlerKtWNjDWckHZNO539Ul/xuYx+P8TwhiiIGEwHnwdsa7BtkXpnC1QqZn3P8mmNgaeMODHFqw9UNPBVdi3QWx3yP/bsXeROMBXweZ89ytho7fFics3dB7j7987hF3txZTPMc8EUuaf/86y9zh3neoPvYN3O4rP23V73fBc9HXl6fuNSbcdvur1p6POa42eMYv+fPuM/Bx55Nf5Orat7zNY/WcWAYwSm4YZdRcU+NMkZSnRR8xxAaWNcjgzzA6QNWhN1iOMhxyhn0GlyhGlyjcV4bmQGqD4Dr9SFGgy3p6yDWOV49yNxvAclaxOzbdUSRuwApLzEngcnMhIxx9xu0YeKo/eDgmN/lh3InadzUX/YaaL8y7Aj34BeuD5gYmSt7ozomJ2pZyS3f6RLj6G6Yl0z3xrZu0eCkf3GxhUt9Fi82yGWOPRmw674Dt7ESbraDj+fa3nPQuB5s60zscXc345rJQW7L2QRqb01HvixIsHjlUJvyRrM5jZUcmn/TfNSHy8RbHPTi37mmT42IUtqx2Rd3keC79Vgb/kvcF+lbLqD+W3wU0TR+LbbfyJefptkcuUHjMzyuKmDUHLcGJ/ZNDt7+s6EPDn605oNXesm5/uSMqAw2/2qjGJ22cXPPNr/ykOeYBQa/5Zfhqefld9e3L5bsYDbzCEX9s5l/pgjkV80VdLgbDycACWi/w2Ig+OCYmPo036lBrAB4mBNlw2n6O2pujC7slUlleFQWq4zv9e2xVf9Gznbm7ISahO5pofNYBf8E3K4zUU4c38G7HhexSd5i3eQbq3CQjIVkL1ucDIW/OknUNTL5QAcQGjbs3I7cwOC0IzdfiTWm0vE7vjOuT/DOQrbYchq8tWHYxwKSnc1lUkL1a990NufhO5oZFWPxQbKfjqi7CeipA5EDbJwJpp9x1q96j581ZB8/IY2D7c0Odf5onctoH2pSbWHwm+CiZOxjSi0AF0dR17YxOipGOUYy3O66ZXSxxmxZoh0eOCm3Y7c4RWi9Ihm7a/aCNXBrrwk1GMXW2mPdMMQslHmySMuYPscoZTgch9PyvPLYHGK8BzYgiN3P0TXju8pQjRjz/CSG80VgDJWyT8vYM5rI83jgzJc8OVa0hSvdDNIhnNxVI8O8XLQJVxdurKl06Qvn6iK4taFeSTB4OIZE+cIlBrwwBv+bpz9E/i4Lrx/PGe4u5tDDAd7SOWffNm/yYzHOZ6I/47L2LBx71itfkZQX+1yS+iqLOc6egwWH05IzqfiCPQs6bib1gsvi8+L73uDGzaR6gzgyu+pk1SIyX7hCNG2PH0bqlO6meanoZhUZFUyubDLcOThGghaVLXPXqAwSGR9KplKRuNqg3EZ3HHfeGePn4TTxMfcYy7wxLyzIeW6gvs+zQKfeyJ0zjPFnQ3fiAcVlxtgyn7zxwsKLBfr6Hn74p+bo+6ZKbtKVKyA4a84bLT/mEuVdnHvPgbw5QOMNBMYs0n/N5fDw5LJ3uPhmDfFSl0/CAxnHDnvrGz8ZZ9N6C3lt0G89pmbsxuu2R8h8jJEaEgrukRWWeGtVSUe+KRWMtVp+iyFnlOGz9WW4Ho9x9vH7YSw8piXsPp6QnJyGw/LculA330CLootnVtLQgX+9l7MlQ4fGuqTDscNHXuCfIfP/Pvep4I2f9+/61WYswLlCAp/+dfEe89jwqC0ee6uW44n7GHBvCz5zzg3sWJy/zhnzVzlzzn0L4EZtera8zwNyDg+PyQD55gN5m0tjeLd7uO9CPTquAvg4b/wwVy7SfZMRNsTIlg14JGiWnRWHZ4xRW8PpuaLiZLTSfTzv/O885ww6VhlSrHFI1extiNpEdCOUUVoPIhLpBDWc/cgMCjvw5p/M3U4SqPKzsYoLcg8+fC30YsTggZ2c4m3oy9bhgsm0A2OFkzxmj2bHzREB0sXVAEHaIs++ZAAY7c0nIFVXRgwRuks3+vQpEZvVa1QCR7YvqDDFyfq4VyDfhW1UmA4X9hPIPA3Q+ornGNzBKqHjo2+f1c9xshz0gIf8W50mPciH431MH5Y7Xxt74vsIKBaUNle0tHM8wNO8Itvkoxd3MESJstG7FRM/bbUYfX3vcrRzJI79BkqUdItYK7z57ZPw8JBjXNdQcBhezXLr2nnF1Bxwyu/92HRO1cbIml8+i9i5iHyDrN3mnP0d58Q7NVskYpMPY4iMPHhg91iq9xDVADOk3WLo4Ga/GnhgBh71LC/3fY6VZ2sRkILubmED0AD4CZc8AhnpyLOH73JiPq/a4X5Z3muGWWMLKz/xx3+fM7HaPMBqg0C8D2BCHt3FZSNj67wdbxBbjxEZvzZju3g7v5PhYoJweE3/w3wapXG0NbfNm6Nk8ykL5+YhXqORm1ju8aMVfSFA6mOX0hS3FtuvF9FpIqdbFpUBeXwPxvrVS+fd3FT7uFj0qmZknDgh5Pg5HArUaVSphuPr4hm34x/f8AJ1q8BgPZHp6gajdMb+PjeLvmY4yaGB9bmO4VqJvA5TG3Boy4X/Izw/NWyPo0m1hg7KvlvEJBAfnh8Wd3irwzDN0JH3GIEv9tWU1hhOwB1VJ4Qb5MW6ZABVHg1KnXvMMTam4kHNbh8rOFhbcyjmwTefGDvn4OA3ccGlGyH1Q1wWlTP2eGavYToTq73ae2wcUDSxyhwYTNw6gycytos39S6v9SHK2OIvdjnqGF8fI3EC5rKNDXOiNJr4OWLj67W8OPXlNdh5AubFcnQsqFpLXKYSw6vgcMCHF+TMvx1zfPbsSxdXn+bM948/fJ+vQZvPeeNw/nRNuPCLmBf1XtKeS075mq5z1jyLMj67zuKRhdqrH3Om9aefIZhYWRgmLy+xZQwFwPJi+7MvcsOzb77086ZLFI7YgPUuC8RdGDSf8nEbI+we6hjcPd5Wh22riTHWbdtbO/YiSiAjuV7H5/p6vMZy/ddnjzdDFCwplY/QSxTo/GiP8QLFVrexc5fa+TV5WWC/4JR07N+/5Q77WZyz4O4LAOF3A4pHV8Ce7UI+/lwuTCMui59nL7Loj/x1YkgixxILc+aPjy8w17zBwhstXZznDZe5xJ25hCvHQusEcj/SwOXMxMivMmy4eoNjiFCnfuatEYZXGZZ/ZOS3uRxLsPVVYyz9g9+Pijojna44bbxWd4obafEEIpIEOneji+ryKWbt1oeotSHGxuH56rQWodixoNXuOi72eD0+6RB3MXHjf8MzPvRM7tQyC1O4Fh5LfNJMwHDqjMUxg47FeTpBmnF8OL5yv4q+ucad1nPVRBbo/PlGTo4D+PmcJTz94PAT30+5YSGL82++8h4SfO86d2p/9QNvzuXz4nMccbzAsMdFz4xzfNGQ3RsceFOImLzZ46I8x+k27D2uo+ctg3e5iz01t45MY+RF7La5tya7Naa1IH5A1sj+JSBP2lYQM2aG3z6aVO9mSHCQf0BCnHoP0RYjgxMClJKZcKuTD84YgE0Hv/5g3V7lbE8KNUakjcxhvy0Bl2v3x/PC0HbkcaVX3pSi/I/vcY8hYQZfCNwqKpdwg94eAGIwkWKS0TRstp+9GNlbq7sCG8eTkwYjsw41PpzFuPIvYIQEgIVx4cOwNa6yORsMyCWkYcfkRD40aLQ+Q08pbtWvHVq5RWxsX4iM8QRRX0DjtkpF2ph7cG8FVw7SxnJRMBxblYltuM2vfGG5lRNjxhtHFzetEWz0IW9ep9xeUAkU5VS1roK3XnCud1TUIT+bhzW8cSbGtuXXuASOxjljF4zxw37xyl8PE3RxMHNm3KlzsdleXJhU5ZLAujHAd/LY10Wdw3mBNxERRVez0yfmtrFnKFc64Xf5xPaM0/d36ki+Wm6MxY033LM7x0Ic5V8AHbQG49QD+Pq6Oz5wKr+tgfUGy0adLj9tBtMKYkYO+Zsu9JqvAuD5If4I2PubDb5C7NzUem3R0XYMAj6n6RxR/zPOsbrasXM385s+EcBBvLj2rWu02ATvHmvtQVZ+fC88dIvdXmxvjlujm6h1IjhsjN+5RNI4wwMLTOaxiEtxVt9M8EMnD4+/sZuabb6LXmu8ghZH/BzBJR04i0UiUa0/VhzTa8OeVu90VChyoH43wwVs2v2xrQDZdjQxGmTUqEt/90XJNr/ncRbtVtLjF08calw7+zqJvR4n9pobC+ljvtBxwZ9OocIpQXaela2X9auErTEkRJC1bATRJubabl7FLg8T0g7AIE6faR9GUTTWnZOxZdAKMTaOiku7mHesg4dHftcaGyhYw1s+2MNr87iPAdiaK8+mb3ZdM4fc+TNWoy0fRxsrj1e6yPgjHv+8eoxFgnLXSWODiZyzETN7b67Gc4kuc4wNT0GJwxjbFPq6XJqocUsMdWI9e3qZxysvtHkTgEU6Zz4NGltjEsqFYC7pzItkzohyszJuBsfnob1kNS/KudSdF9a/5gZiP+VMK2dcndPEIS0wuZ8c9s31mWfOv8gL+xf5XOm+WNeU2KnH29z5/W0+50xePb7Ssdrs26zp1iIxwGbORmtP67VRgT7S/O5x6wBsASPPHj8g7TBWIAAarDUwT8UZP9jU97BJZ+HWXHwGPCj2GNGhltKJEfXhxn/Pn7/wrOdeBVF/HRK6ZzjFjggfbr7H98p/8qKXnkPPNz5ceGWhFZvnebPll3yO/JdXP/tZYRb+PUP7Pl/Jx+L8RxdMvIHDZ5T9XDD5H/JGNHWOaRb4HlMT64VfCUZ87Jj/lqle3W4e1HL/V1Ks+xtQW1rfyEQXVyBP/TOAk+PsxdxJE6uPF2a2s9fHiQwASzs8RF+9zmgnILs+JiNJG2f7jG5j40cBHwmPx8gZ1bo9cItQrvhxtcPb3GF9F4Tkxxx2oVzsDMTBfxGiCRTyHBc5vriSwje7MOBxjyW88sdx8kneBNhjg0ve+SMGPj6PAMdP7LDn4xZffP3VE49hroLhjRjf0Mmbc5w5BwtsjsPssm8s+nvsnH2wOWaIAy2unCEuHLxyJPc04E2EbeIm3vs8qXATzB4n8NN99hm1uMbrcRJwmnHSR58+tbCC1gtZfuFZ6dHLV8ydDwbJSFj74HXyOjzCGKZlqHX2BBw6Yjz6YXwdZMsXKa0Ri73kS+7y2eI22TgtyCRZHuEQ/saevfjMUlrzctqHq2WaviZyFztDcGyl1pgIGOex74OAYeyIu4uiqw7YZIRAqME73KjZ6qObXGKtfdlBKTZwOX5AdrzvhBtieMhn7RtYCsCeOk4MMDFx/rJXPPvzj4NQIsSKGPnRvuYoWwuwBmC5D43jN+o8QPAhdmtX+dYR8Y3M5C36iLGfaOlccw6eCbGFNyG0LSN8dr4w4EVlc9Iom7RbjAqQDU91zR878aLe4047xjiOnu62zWvnVL88CT2MibUOs19KzoP6WIzRwYzAeUldsX/AiA+S+7zZn9oRBg57PJ0aoYhX59/B9EkOe0oDdmxSS1viyyByNNuKjwO/zfHieLetDXyNa76gjPU6YYZuJlnb6OpTnV63HOPy0O5RtSUH4zXIhro7bb1XFnNKoR/469MFZMRNWPOd5/rGcvw6LnfxkVtfvC/W5jYS4xA4x88GBR97+QTC/oBbK/oohZzaIUsStW0ExrTFuXwUZ1P9buUyJCo7lAThuaQu4K9FRSePiYnn1rjW2GN125MCjxv+EUMpvu1hU/y1XibW5mZHvjRzNPbGQLo60Q8fNFXV9sQY/0XgcVFPPbpZpQAZxKf+t5o07ESH26AoH+VSiNXWR6vYul+Mk+sV3l7sPBakEAyfL7JfuSgF2RqR3lJBXf/EW0org9H0GzVbBDNXJhYf3CI9MakFY+WHR226fQikXcwvFQQ/bMGRH8A0bVqjzWvIQqTPZUHWHM66ME695jGmd1R7fEJA02A3p+FxYoFz44bxsTXEUfeNsMY19nLRLPgNAJuJxYJ07KPbnN7nhWZJEaqx9wU2e7H5SCW++5yt9LKHpsjp8L+aM5LbNo7HuMlXM0x+N+CzyLyw9dLnvDDmMlcWXj1b+oMcrWsygA6LcxZyfoVaXpj7WeMomIO373O27VXOeuVF9Y/ff+8inRQ5dnlxTna8+P5o8mSxyOdUX3Kn55xB92wsQUiHXZxZmL/hq5WyONl6NfnmDDflJsh8I985MPjgRRc8bDV120DU8GBbIfz8lUo3HaP2sRjhPv7JMQB6ukm+jbNHwzKqiZwXVNHdN/i3xzye2PvuxiyYOWvudzsxv6k7taUx3Li4UAV8mWMWUl52nMUZc+CiJw6cQedrtagBACwCueKBu+3TWKBzeftPOXvOZ8u52R8ymlc/aMNX6zU2chZkbwTMPQfglto8z1xz7Lx7ljP2HC/MQzgmaP6ot4ObfDQVV48NfvkxN4friyF1nP2WdOflhh8j7UDBfF/rLge0IqnDNJ3gFB0hFrTpHOOIJh4imsdIBjsX5zgzj7GpZdGA1Hnj1UY/dOECpjXI3DMX6+L/ccyJd57808+4x2yVXZwzL5mLj/gsugG18c2czBP3g/Ax7Rl0Po+eOU0sePg3Ptyw8Ivcx+Krb7/xzDlvvPlxiHze/HWuutjFucdBiHaRTg7NRRj6Dqdz6/OcyNdAkufmav4xnTLpa9kDunVepM4xxhw3aU21U0cuykYnUlV0tef5KI2c6emxGGr8mrVLUfNO0qC3+ADk72r3PtJQVV85Wya5yGMLBiI29httqEaRFlPJxkZ/XG9xGyMe2EW1MR4wwc7PlWwsKa67keu7GCBdceUWf353QnavTHwdGE5LRAYTu8IyXAsBM/BBhRC1JgZyIB5c87PY8MbQXFeIhFj+wxlbxpDQHh8ijgO76BuutSjm8BkfIuNlfLEYVylSNmJGpE1VNRkD66DXKoXUZhcu63DmMya05i1ZiEXQvFdefrWtw+jHDlnj4wHXRkKOouOt0+7VnthYGW/ii4MjLYODCV7Ge7yaS2TNCS9CxlpuDuUgMYaRC1YTH1/LcKwxsrvzysga5J/sNn0ylPfEqh0WzWVx7nlVe23lIqUhFJU4hILrNGUzNL2V80JOHghkU3+G8ddv8mEu7nUjv63fxpIrvjQ40CZuBRmcMSF6LGD2+zreGG1sDGPZuOsPZHDENXGt7lyWSo+nElgauz82RijO9UJ/rJjDzXuiZPgQXxxk1m/zw3/rh2P6+WkPTLs99tJtXdJ5iJXhzOkeo4shztZIQsHeccCFp9ajA8bXS6Ww4QkI1DAb7ouDr8fLZXP1CNfR7XXAwE18Mh4OhB0qxy9KYy8Z5xhRX89Vl+1iPNonRvz1iQ1MBq09udXmaKW7tYlZLce3x5M8R3H6WhafWWzWI/xgVw7dllP7t+TjMTJ7d9thSs2IMrU7+9hvzT0LoklsyfXexy5/NNGzsfYVibtd4ljf84J5xiMH4QFrHdmjCPYek7UjYmuMXGzMKi7W5PegG7js0jCeHGKrqwCKO27X3D0GEvzwFL8IemctQY2YO7kN72VetthHn9/FoYf/qbkjMES57HAjPo4WujbYyY2OMTuvaD120efH4rDryHhbGx5//S7jsIzNcunZ8AVmobSxRJ/XHGBua2/5kLM1Gb5d4GURlR8W5166nruDc8OnH374wc8Tm8KznC3KpdKf5Uz3i+hZaMk8izqgOLvH92P/FB8uTbVFQSw4e1uqvNAGn+9x5rL2L/PC/ss/fOPZMeyaOwmxOMxl8rzI57OwCCKGO621y97CqFJmjTwGNI7BVME9vnrKt6rMy5gUWXg54yuniY098UHQNgJcywllpBh9YIfNNhkUSJHjUYIjeoS8ueNLCA8uDBqFN1J4Q4Y6+caMc0DoPHHCixryExv6nC3lzCN3x/csemofqCycYgdG5o5FVN6i6XETHGR8hZp3aU/t2f+aN0leZy/D+F1vCnA37iz48wMDFlHg7h/zzk0Inz176aL/43yXd5QkFA+oUCyqkGa3vEYzWY9l/MZyzc2b2EUDmn4ahulaQ4b087PHR/VwwTi77Fu5jo2jz4GqQlC6E4CeMDVefGAX4wQZF+VAxMLUE/zipqK6bJWvCI5bK2JCmkCnNUD5VOhRk+SXj+a7iaFzn0NiKws+c/s+xxnHDPNJcXY+fWMnMhbiXNb+JWfOv82Z89zckTfYeMPnVd7g+SV/56aQOUbB9WMKE/uex9KXY+yI1Tf3ww8uxE/Mt3kzmXIUAAAgAElEQVRz6E3enGKxv2fRqxNUnuDqH9CRnse3xV5TX9tsjZYBe3LNbibpvAbTZOvbI6WjucR97Ou5Gp3gRXkvi+0qpzDYJWi6p5Vnt+vbaYxdxGjqd7dEhrQTtn2k+O64YXbK47+B2R/s2tdvaKmuH1EbGSJBZpIwm72Q5i2bmOCMxUanRz+y38mDxT/u/mc7PphftYzfDXOiywHUQRZbLpGYC+HUJ3oUOwcP++g1cpd8T5xyxpYAK3cs5rpN7czrZoeNvrDb1jyM32f8KG76ia0e+fFvH0vy4a91tMPm1q4csGvdUevlHtnWEDHjYq/vmtfHWm79gBp7u7O56gLXEd4IizGezS+D5Hfnd+QTq3qwAsQv9eDPVln5jyg7Qq7NzlmFyPlNTCCotY19BFP74zPa+mQw/2TFCgch1mb2+tIPlqjLdUKoQjPhGIPDFt99AlKWzf5D0167brbW5Ikt8Mt7x1qeuFPnjGX2Aa/ODbyM3CDDyTkJt8YMTh6nZ56KJoFLVi61l1jtJXb3be7lTR+O2OfvlsTFqDk8qvfoGStTaH+xzouBoot/5h/Tzdn5hwBNoPUgocsO+5kr3I0TWfc6y5+87jVRAw7JaZ9+fmsTW/IHMI2snNkZ43IC5KC4Y+98HhMxYz+cFkJMZOaCPn9syKXglyyax3mu6mBoH9/g3WDwylgJ4LbNjzjYmwiu+TGPu/3wO8fOYMRTP33sXXzsTU6L2RjMCZ4JdmJnRAzgaMjZuc1m+NVcklE2o0HS5tRwHA9f/Qv2EAcK+WEBk25bfDFfrNUsVv0nQHbaxfPgHu4ARZFxj+sMfa5CpsOVH6Lb/9nGbJ3oy7Fg+soP3srAGszsTotRww9XFe1b/xHLjdg0HE4rKFFQnFFwmzOyB4faJF9rFUhfPyQA9tpSmxa3e2NFExgZZL9ntZCdAm2ffdrORXrHt2e8khmxAtYcGeOQfxM4pv4bHnJejo4cH7B5QcpOu/BOXZ7xveic4QwI9h/nbkd8zpnF1LMs1F/mctWXX3zhZ0h//vEHL19n0c4i3bP9IcMLfP44a87l7NwcjAWeOSe2Zydn/nOhrJdm80Kes+bf/vM/5nOrX/i5c3NLbHMi9/B8k7u/89Vq4gWwGURnJqY2ve6MabJW7zy3YW/N4tna3ewb8DqO4RD1HvP3fb26XUxjwsg6wx+iF8cr8sSGQ53MY3O5UPGYXIXl+OLMI29yZGHEGU/OfGaBRC4eG4dzUdwCkj+uiPB7pP2qqixuNnjU1JUbbL3JAfRp3nThnR5u0vciC6///Pvfn37M3dr3zOWbzDGXGb/IpfUs4PgDi/sN0FywJ16vAuEr23jDJjxfcwO7ly7S373rXf2RQyMo4QiOEPJtPZJZhNTeSkavzSnW6YzjtTtY1hng2A6WYWZu+rqH2nZejGcfrJET9xZKf4pKJ3JU57gicLBXDsoa1i5D5kk7upHy/JHHkPrxr21z5zHq4+cBCdw03LfjvkKPCRGP0E5tL0b3vHx8zTwuF+c1x867t9yCP2/kULf8eTxkz0cseOx+8e3Xfp0ab+yxOOdu7b/k0na+eo+UPC6CQHzGtL6ZtP3OdeU1sEbxWC5IOfY51nnTjucbAM11eHHcWdOpi76GmKA4rHD30Z/5mJppLbbOlwu4I/eYHGzs9yMHivaAItotzowKqiJdEqgTlsuvB9+O2bcUl31j4NAIO2a0/U2s3sUHy3Y72BjL4gGrHJww/rvME3jZZtvfxh+s4owfAyYmu/pkmCd08RBEUXltMFd3s3cMpxs+mMdvVCA58YCknZre+8asL5xskeFHndwPsv4Nkgcf1tEf7o+2g9SYiycOeT3GE2ljTV774G5eDSo/4xI5DY7s/KNfOwS1jV3mpzmMLDZW9uBceiCxwnePEeu3L2Ym3gmqfX1klBy2LoCUz+ZbpvI6fgTK3wiNhehKQ/XNJGOA4XxzhdfUD+jmV71bjPu/CHRMrAn7jiZCzPKLkq06exAaGdjmtePZ6zA++hZ4AC+sjecsxHfHrXrsTiwztRY9xrAcXtjMCC4zbN6rEceBfBe/fsEp1ORSu+a2qto0UvWtQWd1rdRfBDT0eLvJ6gH6NU+LYlbWIb387jGg7XDc6u0c47uYm0cDZwuMuW+OsRzcVhTLxrIXJTEJdY5dRw3O9N7jaoej6rHJQBueC+b5sBoiEdxI9NKtbWuJwiMhsenVju3WEH992B6bYGjbjTWLYGtS+zVojB3pKE5xy2N8JYh9mv3ycJixGuZqaoaJxU3edrOh98ijQJVhhT9GrbsY8XAOMlhsgLaPb+2KvfktH1CxQC4+gjR8ajODFXRSrfk9//rjNHOULgDGiwwsOK1P1bE1CEoN3GF8WB+M5Vgc51i3OOJLG9sOuhUHTqNfXfGHl0KCRspK8IaT7uFsTc981c6Uxqb54a6Xfvec5cCmoLccDehC9tjf/vfU75rz/b/JVLD4PT4TFjobo8UZ/Ozg2zZEzhgpVSnIySHSK15jVTfBCt36FuKaYnU1kCNYMxd6c7Ig8aVwCskYHy3MwxehsLvI6+glw1no8AJ2ma8JHItbUlwC7iI9Z7vhkJPiPRtFfBZL4EfIC+vnXBadhRsvyl9lof5bFt9+1jNW3gAui3IWW7wYZ48dmHI2j/Qlwg2oetnsy9xI6stcEstZ85d5ge+l9bNIm0x1P5e2+2bDlCHk1qZ57ojcEgr2JEBtTwEm/3hi3ZoWR9N97YVjDM4xBIz2j3vrubkNZswMy16nknA4gqqozVCkLsSHK+IOYMdgx+1yKTkPR2YHLV9Xxhsu7z6aA2dcsLb+2ZPHXtruAj1z+VHmAD0fF2C+uInbd//5Xb7+6penP/zxj3kzhrOgz56+/Obrpx++++7pO6+eyMcLqFEeh9xfgGMwyNKV/8TqvDPIwjyLKPhCtndvzzHEoioCz6bnLDpDcLkxGc81u+A3FYHT2wB4hvc1/P3s4zchjcsU2Rmv9RUfFTVN/Krr/XDMAODEFGaxKy6XtddsbDtDD6Ev3hPThbdAMCyjza/Hn/QaHzvggn+4Ixg5j9lU9TFL0prnTSKQ5HpTueZC3at9lo6P62Bt8427PJ55g4dFMXdop148d3z8yRvfvONz53zm/JMs1qnVr7ms/defe+UFYzDg7ZtJk+8zrqBIa57NyNw3nyrF2xwh3DdzkkdceJ55yhUgYFgXjrf8tRWzUUaUgTEYVj01YDyCMSUmdaFtzRhKDxzWqwO+eu7ZF1mL3PJGMDKMW+gUZAjvHh3EthW3dhArLkSKj71NFwbY3HBv6tXCZ7mhlt9DzFgevCvOvgDoRA1wARwsb17w6o40fXODU4blkL3VaxY6Yzr6HRekSKtzP1wr26zArKf5E0lV/UU/BpGtOEbM0nEGYnWFzjDcjyxC4qO7t4lVVR2Hpv7HFA5RePBNH53w65Cxc6KcusVn8dHFbw9e/MpvjjVzLNnOU+tPzB3HpT6D0/GFy3hD6tfgxqyqOVxGwz+oJ0awu/ABq9mcnAFpwtXRHy5YpusTi0+K2pIhPsU/OE1TdnW662E3dQIbboaprK7dKgd/OAys8UCB7GSAVZrI7aZfdmOj+SIwEPZgoRnp4YSMnGjkHoXNOsyg8Stnu3NOT7zhzosA65Z/oM35AnRudEZTvzufExgbiWR3jkk8yn33zEcb7Bqvx+XEFCMazNY2qitXBxFg39Zes23EyON7cccOq+FDjA4vXJhOPXo81sW4QxkXo+hb4cBUbraFJtbmR5Zg1y0c4ObiHMDIB/9w3zjZP9Ym5pM3tlYP3wBvfTKSxeGpYLiStw0++BA+KPBBQFPVvnJ86n5sjX2zE6jeswUNpwY5XPAx7+om4sQW8Pjc61JOk1ecij51lB94lWMlepOrLX317s6G+NoaIKjYzbycmphC6jNxtF8Og3vlD+Ji4sgImR0GE28kw7FzidYZpWPbup15iJS+dC+LYh5+zOUV5wywj00fm42jXfD2WLz80pvBeQwlirkDM/hyuY2VT03o09amFehWXTbmJ2gGVdUnW3gWA8PxO8cOBvjoTBTAbhiTHzbI2ayJuJu/SgyuWBpGD7ZqeNSuFRheqsFNR/9iOjib2IbDmbPpr6yo+LURp8fC9M7CIvrhbUrgRHQ9z3LYcuaVeGCx8C6Gi/S82MxSLd95HOW8ON+FEm9G55PLOTvUF+Ve0vr6ZV6E833muXFTPhf6mkV5/liQwZ3jpS+kKVHOruaz6rzA//Tl5/nLnd4//3z+XvaS61xG2+Mo2eX5C47UhEtZX+fzzmCzmLTMLYrdU5c47HG0taMAxLYQbsituFTAASLnZ2LGLiJV1JPOVX0UhdOmw5gAisKA8qgXwoGyUy8OVd9EAtkYa1cOAza+G6nYJaeq+qiZjy4wM78QEfNmwxssXO3A99FzY7gsrm2x85L1LMp/+O6Hp7//x9+e/vNvfxPrjx/9D+8JwJsy//Sn/+Xd/P/fv/3bUz51Lr1JNVjlRx7O38QmI45TznbyOWQWaLzJ46I+xwb2cOa71V+/5evX8hXpuYyaRfwTV2/wOE47czlloK5F3plhviIbQmMmnnPg80J9xrU6jlGCTjtT6DiYlHGV5DbOfex1TjEY5PM42/hqMnCcjfVZvN2jvIIolfMKqdHYbh3Ei4zH8hsfD62V/Igz9vSQ3f2q63Zx9vjbl0o7jyzEh72I2DOHfCTl3cddrH/6/rNI3/tVan6dWhbuPGfwHee80cNj1jgUFz6++SYroZmymIN8D9XjCLEtRoJklz3rcfYea8HkueujvDm1z2tncX6v3QBYzaYf5AENxu8aIRNk5wwL65t9ZyS+2HCMThz06HLotnP24hMsapwEY9gJ2oI7nqDR2gw8/qDWm33+HIJGy4CqECCtxUFMcTaR5aWJUB8mSAKL2Fhg8FtcPMWeYf2TKbFpkbeXzjzIO17UyOW4XC4tkIzYP8TLeBs62j0nQ4M5uReBnDEcj6O7+0Y3NdNU5IiyJy/axU6hMjebL4OY6i9WTZj7x8bcX3NxcSXG2H7gwot46xDwo7K/tSNCNPxiCz4iuMNlckOEDI40bDY/BTO+11S5hrW4dRWAtrxX1/g3HrCfoNouL5nEa5TL5eQ6td18Fp/A9uPXfcfgXNxjZMzyW2wsF88E3IBya1O2Ur5F1az+gJtLZHds5KYHs9HpxoCGmGfY/JbHyEs24sWvOXO3FgLXUTsVkIzN5nQ9/qyiIPQW4+J6w5/6w522eZ14kRlmdewvQKXZmBOGq7JXyIgHG8fbPF0xbhwFm/ravzDNc/MdrDvGmA8Z/K7a8CbAw/GxOMPRLCPjReDW7F6vIOnfeAmxdYt/7TcWlpPvViNpPyzG4W5bS6NPXdFdcqC8zHZ4VovJ1Mw6DNpyGn/zT5+9Ec0tXE781kjl6joQsCwTOPY9xjZ6NRgZMs+vV6xycbt8yCGCe/2v/mCZX/Pui67md+zACo9mErsODbMykSY34038ky8+5Be5+vSbVzmjQ1M8bGn3+Zw8lFaHkQuHD2okznJJvI2L18aUV4iUDYymTXfjsxcv8uNzclMJqIT3mAWitukxoN04LmbFH9ahtmJiMDUoHwXK7AlEgGZhrAwndU02/BJx7As2aE9tDjegbgDjvPk3ZoJicniVGaabs/ZCaahb9Qo7H8s5+83NeTIn8Jex7nK1dxmLsHOCg8eugerD1qlCRz9/3Scm/wumgYGORk08AyuvHn/v8jqK18hgcdadxdSz93z9Vs+wevYseurOC2zvSRYdZ105Y8YNxPjjTu2vf8tnxIPh50+zeGBBTkPGAvFFXsCz4OOO734OmkV5XqEbYyeWfcjAh8tkuSkcey/fhkPw0NHprnnsSzH0NcBEayRpao4OyTX31TF+kC+XCGuxiLUUPWSOLp0iDLb+QmazmkaoNL7m3Uz0mi6RmtnNz8Qnr/Hr/MaG2KN3sqZILCKYBz9znrpz+TF630xhcZw3WH7OHfa/+8//evr+v77L+PUTC3Hm8A//+A9+r/2nL18+/c8//YkAT3/5y5+ffmPBTdJN3EUZPDgm9s0CeeWxyGfVvSQ6OhbonDUHhwXg27fPjM+bBPoH92XuRUD7KLbI7JObPTbkioA5mPqlX9NLV896aYcnzw0uqgpz9yeZPlJa9Sa380O4Yol7jx+oHhV25JWe3KBKI4+7Hx6LB4fHdo0JuYtA8hUFoOECBjIfQ+xnAVx9DLXFPr8OJ7czLje5gBWevIFyXtMMN8L1zb1cMZHHK8eGl7Hncc2x9TKfOedx7eI9j3vq7Pezx+4567SMwUUmp2x8A6aT1hynCDvnW5Nyglsl1pLBCoL7NjEZEodkx/Skj4zAYls7/CO1j4oq6hrL1qE4i1RcTFZy96+MuHOTOAROjpoWXeLgDJlOfJ1iLAm0Uolf/Qc6euSSy34xaj+jsRG+G9TFsUcIJhgsFBPrZnuPjcEWrCyyze/6kwpy8zAvQIvpcONE1lxVT7TFjv1MpFjxoW2uHRhUmQEVNnYJFB1/2omNYLBDWrn5YcAfB+aNo7bE52AYe6M8AKO+/LY/Qa8Y+IDFLn9SoX+Lt3It4BkBLDdcvbpdW/Xww+rY73FBtDSxJt/BVbyb5YBuGwHSlLCBe54xiqJqeI0hotgwuo6RC2/l+863vMfHKDElRDMZHCJM7OpwaNtjxOiCj2nURhUrmJp3y+jMD9CKtZ68WmvE8OSJ1n8Qqcvytc5gxkhq4sMd36lPFPBti+fY6qEidmtw7IAsRnsXF7HhEB/j3+ZQ28EgH7NxzKa5ba1KKgjyWyy4DsDwJ8ax8b8EDv6a0kEGHl+4HU2Gihp7sXtMaOQcLB5WtWxHuJq5NYR1WWGt1+fKbfxvtuRhTSWcUf/jnTqi5/fUFVI08pmalHfn4jAl+JiSf+HLqCNR3BjjGl64I2vsC245dwIqL3K2+6rcyQlARD4vQeB2rG7M5UIOm49hx39njQTWh3xo8pjJUAcJxlUzaN5jLwa4So9RxrgtpiNlD5vFiG9jYX8Yaaokm7sUBkQ0P/vDSWn6wUXfNr3IFl1eEXeO125jYJUW/fInt7UV+/y/2OOsMRp34qUmPB4uDEAHu/AQKNeZFywe28xfgECVwzG4sAJS6ca0JhendRlmrc0O4mptD9zktNzirCr2xw5fhVdNhTP+AKVG8FpY9Y0MkP772e7qhiUOuDKcvNCPC1J11Lb9jYCcOk1Nx0NtnPG/t3pNXdEaIFLmgpbYHl/sj7fo0sLsxIORgJEUeAKuL1hjMjUa89i1RoPcOT4gAxZfuDzL6/F3HAvpeyadc7CRvX0TGYu5NBcJy5hYvEifBbx3eA7251/1jt4u0HtarAs35qyF8EU9L+z3MlcX5kaoRRMi35xZ5bu396ZwWQhs21I4ZjDH8fEdw9Z3c6VQrQlqGOl626/Qx8PWavbY4wVCcTNKHa6J0UCb2hZ9H6eVYT58xtxRZIWqzn702BKDqLQHTwDR+7N2w0laFxYYzBVnzllMteatcc+e/+rZcy5j5zuq0fMxhb/+5S/5N/DR07d//EMW98/96qw//cu/ePXDX/79359e5Q0Z9FBhYc7ijEXYe67AgF5++Kw6X8Pm2c3IvBx59rwW4rL6/W5rfHhzgGK8/BwM3ljgJnZbcSymDvElL2JsTY0aGXXBl98PddZSffmJPONKcJtKA0g3ehGJd2wjn1Zr5iKN1wQiDAaj8RMu/oUd+xsmdra42nV/5bdKnqPgnbc4tOuZbgP5+HqbejeXGOaXdkFfsiuvy0BzTAhycm390bGo9sT65MEbbb7hlptEfpIrZGhe5RLj57lag2PJYwIs8aghvFtL9vbjZx9/+vqlRj53oPPFyujq02pRn7wphH74rjxOIPmahr0tNuJ3NNLooJefelz99kQpBM4YY+iOeSgmGka5xB2gWKSI2jvGoSMMtZlZ8YFeIVvbJftvfCI6uHZIIB3xGtP4Qdo44kl6PUu20ZqNtqQQrEoAWDws0ycMXWI96NCia0GYTI13jBeONQKh+tiV2+O+5mBghtPEZSyIojO5Tb28W4focVuOMehiEb/YyWXsI7FexqJ/y3k4I6HbvIcLkuD3AJ7aYKR4OSNoH19fYAtTXzTWDBx+IDb5nphqQBmc0esZexeV80DRBP3iNEApQOXWuhiNAFuauHde5abqih42Ky9n9NZgeBWtOOWBRSmwVw/F/Jwc5ZkN+7XJXjH7YBNDH56cRKlsjSZ8dFfrsdxjC2m5rTeCIBozm4VdEsJUvir9s4HHqu/ma2feGsQuQnnfDbePWn2M5TKzDJCtiNaJeZo6MHelUB5aDdbayAFwlNvwxxH5abVRDpy6jCaegZSPw7giGhIH725GYG1usc5jeXMZSHAQ0a7HaQT5PT7grB9ybBshPUYlVnmGGetyt4ny+IgVq/+OH+7wQScsAwVFGy77JgA2M3MH3zkDx0bU8ilA0CYX1cQIvFbySe2MG7l7A+AkziRW7vhtLoDd84kzOAuFrllMLOzT4CaGyqlbMO+1WcvuQTyoinYEBDxp+G+e7B2jRnkbl1QQIrtqQISikoP+vvDDmYYlbWzsRxbhnXet4DGWmKd/vG/1imPj3GVj+4hZDEKbH7HB1S8OaYs/JM98inM41FIbfZvxOSvzQPoB1RyMN1yJhzd8jH3PIfEIaX7ZyRk9tupueTMm5xMbxzbxtx//xokgts7tPWbExpztOQ4HHxhCtGaMMs7Pto21MjWzAavojUD/2Mm7ddQKE/xm0XCxgsjEHBhNJ6+d784v6BgHKPpFPxwnf0zmfUFCM5TXw5wDoZw9veyNSQ+i5FIbJF7mnhe4LS11xp5VexdePF9yqfrHuRnch40X0mCRA2doaaYwsgqqhwrHXfNdWflh5x3qE8vPRPN59iwS3+fMKnWFFC/St2bYW7FM1EHQZpKP9KY5jw19YifJsWgtgg+QYJcn9lsspD1mG3FrujL1EJt27DPe/6eLt3lsLeqSglO8NLfZaMdgc/M4wII57OORkW186d9xuRKCN0W4vP3jLHiZA24EBqc3WRBzl+0fv/8hX6f2U+cnuF6mnMXzf/z1r0J/8w9/8GvZvvzD1/kKvM+ygP786d/+z//1q9Z20c1HG/jKN/KGtzedywIdPZe5v8hi7rN8XdcXuX8Bd/3nIw+cvX/+4jPPqnNGnwU6Z/FZ+MPhXS6f/4TFGiy2BnQtUKT5JW2m1McFnVZPDrhtnfb5Qde73Jp2bj0GYoDNztGMHO/8SSh+vt4eDsTqMRD5YCKTox1R5UoAmco3EUiClnHlM67UrbHVjjA+3DGfGn6W+wUA8SyPUbB4yGC/fOoRIfKJRRwae6LtPsWXB4BXDWoNIs8X3H3/jRQzP3xswqsdBiQ5cIzxbQGcaQeZY81jgsV5JF5REZnPB4dnFNOsX/rkAN1ySwfnDPz6RPppHCcJgDCjqZ9OGmrTzeiwgqNgowa6KRoL6Ym5kp2bqYv++jVuie73oMdpAxhWchPMQNk0gsJb19BAmm06kp2gGVTudid4ctcWr3oT18nWJw7sg9MHAjgXhbXTR82FUyuE8QUa18WcYXaNOvo9cLCXT+wNjyGWw+XglE6GrVv3Ghc32+W2XEsGqDjnlzhrU0/FrYFhJ+70rxhDWnk2UyOG8IOaByTcDDXxzhGDRWx44NA6lHf5fCC3iBcmDssdX+sVGLIpXOexl8VhEI2P8PQdklct1dGnJrYwwAY0+CMjPn32CnDv+NjErNx1GLOxX+iq2Np2XlBPiD6oiAEHhLTE1iaop67qynU5jXUcCiA3gUUphslFD77iPQa6r+XohlT5TZWPf2OsfcEn7giX82VDPWtjfePkOCK40tBSjOXe+kbK79psTsNlj7FTm8UpcetnLQFvmFPbjY/8mj9I3Fr8GirWE7NzsvmM7YmX8bFb7rVxJmNHCt1kz7GZ1i2pomR/k4OnfI+FGU+c1qnHw/oLolkTAPXEz2Nva2yY4DSaXuroPWI1pux2jmquZTk0D7nPPB0vc7hQK9fVejVWpIOtJdSPCb1WgVLssbHzrt2d1x1nMtmzkcWB5XUMMmdgNAo0zFRu2KNRdqs5xsg8LuhrpfHY1u9R01EMTp31ANffjXN5PcxDk5enL6gaLuM4p8ka7vAxB3IcxXAn143/u8uHo9MeHxu4xWMnlzHYOWdo9DEVQAHy7RR3fUa6nu7rPrFGQg74AKMeNS+GhkPMIqinfTdVGjsq/tdsXM2zwaLzeUmwR959eh2MbwYTx/JOnYh8mvYjySvsrdU+dx1cfQd8gjA6c0LOm+NwN8bmOf9Ll291+NNbRlfOSFTd9rVMvlFe+jCOwDEOJWXe6481+m3tMx9YRDe5iTGGV53Xq/udw+YRf/Kb3PQpJGUB2s12xR8mEyZ0q/UMVXBYiCPy/7/uLNSJlgVXQFmQs3hqI3d6qRtb9KNaLsXXBIN0yHe6GT20KFicc9b8bRYdXNJ+jsH4wkFco4lU9k1s8i3i5seolCoBw/yoeRRIH2xvx/3xGANzoa/jCq9jRr0pVre5+1iMXBXR1pXY8ijGITS88C9HuM4ZRIpnO4DiOgPoCHJrPI67OOeqhdxB3bPcXF7ez55z9prvuH+VxTlzzh35O495QyZz/SaXwH+XBTNRv/mHb59efvK5i/N//t9/yl27v3z687/+q59Z5/vQ+ew4Z1HZswDzUvYs8p9nzNl1FuZffvlVzsDne+5zOTSL9M+/nNyDz8ckfsvcv86d5H/ONwDAmwLAx7PzFCMNLu1Rg6nH5F2ds6zt46a2tcFhjqepqfN04BoX/x6DVBhlvZG3YReZE1Vnj1Pmbk3cr38GoyiDMzQOpnqus8+JGzl8x/lkGLt+VCEfEZgF8bOPn/exQ37B22PMWjJWvgEmnnkRPc16XPNiziW56ZEAABJESURBVKSISjuOn34dH1dWcMx0kQyXfAVijqMcdrlpRdjy5krw8gUR2ecSdzppfDsEzTcC7ZXPsiKOz0XEm9rO9J910Nq6j9L5y8Bx3IjQwwNJ43EstR5IWh91qbP2+CyWvLbm9a8o/TEWS2FikGf619uUGRwDfVA/NklHJGl5FmTH9Qd8/SA6E8ueqlDM3Ws2GJts0K/0gNqkiMtIclrVDpArTrkMh8MDi7XRQpx9PC5buTkYDstz95fh5LL8mjJe7ZEiHEqAbV8kYLFZjG5ssF8+p86R2Y/N+gE7JTDaUmoVJ0/sjc+Y4GfTvC8ne8t1fQxgIHLApOiFGU6RwunemtFKZkR+MTu2QD7wU3niwGH17g9oOEx/oxazwoO/XCfOsnFPXDrWZnKaPv4b92DF/oTHMQPt0rFW7AXOVj3WyHZMqPT103Dy7A4X/mi1m2jDCZ4cE8sLLfbLan0wF1H7y+qKgj75yW1sK6oJ2om5sQ7nBsS6PAaH8Z3LGZ+5hXgsBhc8mTnGmhFN8hOf8dY0emzTuqWTHgdB9soKeGTq1nrhjw1IzBvbQLjJ/vYiCuXmbxjsFi9edSmbtQPV2okZi6oRF+s8WYMUPf9tNFvDRd1ZXYidr7GDuG04zqgJkdfo55jdRcklr4O815c9ibqTlHXBBzsaqNOdGCsffv7TN6Wxr5wX4lIaLLJvLeMvYEc6bQDjGbE2+GpQfB8L2mQTxfI0x2CsrS4OVlbN2pXY5IZxfNEN84fcW9X459f+bibeyYlkyWP3ktCteRdCjHTdAwXD7h8czMVQ2MBP9UjEAuWDdhwqX26NN/OlqrnevaFOkDPv1kPBnewmNHnGZ+vQ10q1FYxu/GfSHmo/euLvDIGjDS7CZiynoPA8MpY9IkBGFluMwrU1qgx4r1LkGNRu9MyNUB3Tr8ekhR8S457do40+4z925eH2ALooHfCNMcGFB73yRByDU/tAtUS1aZjEHE/NJ+eJigfdNgx26H49r/yotfGi98167Aosn9UdnIFe2Nb1hrt42tXq4PqCevOND2dCkyBft9Z/ET14vJkbAacgckifzIfc2Vm/sUO4tSM8C3O+3/xt/t7zefPEs57Jb5HYX+wd9Lk5UnPTNn3jM8CDZpGy73iPWTUR/Q7zWOIaX47J+R+ALbGKuLgiiXNlXh051prY67cRsYFAeYECMMP9Hzeiw3E8jo/jOODDGydEW3RQWTjx3ecszM0hMjjxx83ZuG/AL7nTNnVnYU1tOAvOno8h7Ffo8V32+mWevvjmK+8f8Id/+sd+Pd5f//b0tz//2cU8PGgcHZ/mngP+fZobAuYz7NyvgD13AGcPNzFTXxqXyb/49Lfw+dlL7X/NYp0zs+/e8tVsMaA2WnaDLzzZo1PJPq3zQDUQ737MYq4MPDCwH5zsbOrnOWznr1gANi77OOJdnPS1iVxOaAZw4wC+ObCfcGKia5NgutHmlzA6Yex4ERjyk/tG5MoDzlgzxzxG373NZe58LAQfneE0QyUXBrnasrN3fCpm6GO+Q98Q4M0UPvf94tPeQ4LHyLtcas4Cfa+owLz5U6863+tMTVzYo6Jms4fzuXKwCYgDhP7LF3taFNZ7YhBs6w1qY46pxRwncdaJ42D9Wg+53+1jum/wq3NcXOMUoTeJU1yciYzzBqbQl3IpOEO1JlN7bAtexfbxPn5LPD7KlnT2xwa8OFmog5mEbzjLqT5TkFgsJrCldVAtrrhrx95YF1o5E+mKvy92yaLm8auJ8aZrksatM6G0a4yrNhtTM2xAOSAdLyNsyEBeUxdInMldHpG1XlMLnqji2CrjXTnj9i8+Edh6ILbOzG8r1y0GmilfRpcNOi1vHPfANiZ+/mMqD/D1Gd7lSZCSWV/ituiLj0kwYlaEyXFojvvBWfZFvbBmIgERX0y5R3DLoXVobZej2cMBbmwnCPNanIijF3rwj9HK13b9Y6cpkNt3nzjHFiVIncNjJ1+MJ+YihRcvFD3eIutxJ0CPn9gXL9t7f4VVoxQR8dXD5Ric/pQiluXYecIzkuVJzvzBLxhbV7Av/5gMPLs+3uwdecTjb4ehmAVmsACgTn84NBYE1mXnGNOt2bjJM33bcEh/j5l7HfDdtvO2Yz1VZ3ObU7k88KqHdTF2+Azs7MzmqmfsF3eCMSTrTZt4zXURarh2co0BP9oNH6zGtQ6dNExmrtKLgc9HM5fGbTjljMU9PpGg3yvJ1APTOcjQ/uM8EHHaBgeG//YZr/Y8NkYSbdvko93wZKr6nFQTdJc/sjmGdw9G2s574/ZY6XFMTow1yyZo0JtjovM1OolgaMe4V76Px9/Bk/BjjQ4Xnu+3BZY8wGtORAkmMkOOPMCHW56bN4eSvsCswuQgDn77/wW8JjmxsJ4w9uhHohBOmEcCHrJt4mRwOOMVzjNeM/fj15zwKebBIwz4YIoyMcVT6Lxjs/kQd2uDV+cq2q1r3JQVstDknWbdJhavPospLfVng81wR0a3bnjQry/1rOllXIvL5npNAlKsBcouLvKJVB/lRatJMTfdfcOwOXReTp4DvbtlM6EaN1FED+CR7/FgkOSSmriAIsv8WrbouFu730HMwm//svhrZYAfxvHxTHuGrQyMmud08kJ+7srO2bgsFj0rl4ViaxqrQ06Ps1kxtWpNkFi5KxaKAUCzmD1GgJqkcOU5bRbgyLHpfETZAN0POjpaa3JFKfbWtDbYlRkdYiLBd2N0/CADeGJAs4ujHmeLWv8LG1h0yA92+iyye4l7F1LowObqhL2knM+BP8uinM/xUgdsOHuOzLPvmV+OBRZlP3z3vfPEV2o9f9nvvmbh/XUugf/+P/6ey+R/Vr/HMzeXYzH+eb7nnnsViJdFt58ZDuM3v3FP+EwApUlcbhy4Z2d504BL3nuzwvDnZ0pDTajlqa0FZGN6seucC4wwjj7+2IthtbAmtE5Abjt1iqCVX015Phwflyql3flHaCDxF9tDYAcQSVufxlSEdDtknWNgxtk5jp49Tx7MsR8VeMnnwLnPwPN8PCRXoBBs+Zg/kMVZjA1ibLVX3XCnWesM+AgKmDxuX+eYQcGVHX5HOvq8OHBxnn5rTHhA+GtE+pM20GkTBDlDHofISE0JuBE57r7qsYvI8QTE1HoOV9ToaVd9tRKdjfYnAGOM85dOXeGMob9Apa3R9i4+nkFfErUzCgzOP+FCFLhFaky2xLLJ5CafoEurNmzLbOUUTgz8B+whBjL4Z3MldvVHGa1GGKYFk3fJ5LSa+DyYlPiV+6Wkt7zQ75hYk2YTdYBlLVaJB1yNENXmo5kHTTneuV9ljC9qWnyLjizSDU640dBDJbaDbnhyLPcbnmYdH073+gZI7gNnmEjMhTymf3wn3vo4hKOY640UDHbVnRd3VU0mw/PU7cLZtK1FBtbnIWdiNV8g7zU73GpinZQJHxDAb33MfJdbfCM1b/DJIz+0HotIItNJ8WiFVIBqX2SO59Si9nfMSthunMl1FVtXaxS0LQz7yJgXeYGweXG8ace+QNql+2A7MZoXpo1d22QNeXHGcHbmhyp/mrAfu9ZqcLCJ/B6TF278EEuAwclu6hj5LVdjTBB9sIPY5gfSjePhMyaMsS2v8kFEW85ELp/l2swe4gTIOTd2nEsTMg85nlgS2Tp0r08jN1d5yUTAk581Grlx4ZM2sU/qACLO3zDOnt7Yzw49bfM59mDjPXZw32YvG/6xrz865JdPegt218VKu60VjjTyNZzoxW3X/s4jdT61SK/x8dX5JMx4fYCH1/rVaKQFkLwvpBGXYeMS42BNnFg43/IrSY9lo+C+xAGffCe+fvgPJvurZh/Ewse6kFsw1yf+toxpi+WAzfpMHluHRipOOYYbwzLQXS5Tk0Ef2MkptvCoP77p7uJ8LYlfjQb2dR8M/XHEIRtfpbW7KmNPzjvnykBuJxQAkAFAjekQzEowrghOI1OpQQTFuNdIMzZrgmf6Wt6eP52b6JjhhzlooAODjuZWnAL3OQZ+Hd9zWQeeE5cbMjlMzI6v2JPpwOxxd4YukMCS98njlqaAiTA1Yyh35pMc8EXWTNKjpmS1/K9YEZ5p3f931YIJFHFilD92vdFXcs2ZM/74LOr7vGh79yyLahd0eQEXRy+jTjw/ZwovAqVtjTwWeTHPWXKwiLNvqqS7i5HljVoOkhKqmwUmt+g6VzVmG6S4rdHwMKfIYmCNYwUs427QxVYhIhCKKVS6legQTfd477ECzngUEh0xGlZ/YtQoQnSOB8txZGnLQ8SoixNGnh1tdhurlDGKY3beW4B58ew5C24+y411yp16c7d+Fna8OeIiSw1+tXVxv/3sceXmcXxenbPv3Ln783x3/SefvXj6JjeSYxH+83/9+PRjFvFgs7BmIc+l8M8/5fPIvMBPS2wuf/cz6sHj8niwr+Mjn1Pm2E/79ZffvLydhSBn00lOXerVTFoT+9lQA56qGDNv3RebWhpjhVMn4rSS+M0xw3wgBSv9fWxh2+MGZ1pB9MfloVWgbnAwX7P+n+mI7X28MBurUZZfoy4Sunfv3uTbDvJmBm+mPM+iOd9F7uXm5hMDw9zqcVhMpOibe/bka/3LDfwIIu9jlrP1vHHCvQOY09aVexrw1++3l2HdxSPv2gE2Crrb0Odn608s5rGxZ48t88JvioWuSNl64uCaLxRnvnXAtj6GnGOhj1klMRjMjTvinfvGqpD+Pt7LOr6D+UkPmFgMCYB1JgBGHYm0E3yXrX2Tdyu5lqE0PKhEmjFPxhSHNi52lFGY6rGQeMZWWIf75oHJBRWTg383R56/EzKD7bdwjFdSY8aN0m212cYXulIbzGJjEdupXwZi4r1PFMsNy8bFc7gJ2NorW5ypTVlM3Ilf3/jQSTMWUYdcxyvHAp2GDMqVB1FpRNIqbCxzueHpdLMybgBrB2AtymcDzV7OW1NBxq+y+tT/XqdCNkf6xy4DHnwB0WmZF6Fb7eEHsdj2yQufm/74RzbH59YIzN/VsKAn7kCVF3NmINQaNtipkYQN7hyVxgfb+hkXPMhEZBzx2wfJFgU2Z64ixPbUcENmL7dg3G0tTNGznToDYNh0wDcQMoXaIarZ1HdslGGmH55I2K21g5Wqulk5PhHHp753fzy2jVyQ9OGY5jb+x/Jeo8nDHLE5unpan5WxH7xTU8wi5XGtLWEVUcE2Qkwvskrv29WbYgxrvkfxZand70AjiMP6EMe5G1CPW3Pv3Fz5DV/sxMxmse2gD+48J4jvG57NpNt12H1ZQGZz2XzVCNi4+Csz/sxN+lvXRdw4PfaLhh/6/We4sQ7/GHhWvc4PWxHifKo7gcQcoOoaxH/qw7tAdTj+Cbr99VuuW1C5ktssastzK9M66EPIxGrNG8d6tFBxi06OJNgctN85NAmiLsdHPGESY/maT0zlB+C0xtnR4MVo4KMIwrw2ZqIbrfZi3wVY3/hdfGu0ectCu8j9nWNieG3tFusKQU2aAwwKUe3maT7B6b48J8it1ujJrNsLMT1rvjqN6s5cDe6ism/9Ws+tDrwXR1nCwDXulNAaObeED8Lab77KMIafSeLanPAA5Mq3eNoO99ooqR32PrYJWBLTK38xUQU1tuaEnW2zkqwS+cItbVh2n0F5oYCjVPtiGWzG48ciz1fGWV8Rl69rY88Cb9seP9Zyc4tbaxuklY1D3EVfDkRYWWu2yMtl7O84TSt+gLXOy2MTwvzgbgxkEx0/Y2+4GVUWzBs2mJsHXhn6h+vOWf3gjEU5+UA4+Jt3sRajLMCLZ+YDHHNywdwxtuKH0+WHYefCRZRzU0O4spjiknIW2rSdM/j6EywudUfuos+FGP3OLWfduQM8Z8C/+vbrpxeff/r0ac6QP/+nF7lh2cunX3565RswnDX3u81zB3nekOHsqx9lyKKcz7e/e9OFHTzgxZsFnDnnKg2TCbffsvDkLvQff8IZ/lytYRGkLVeqYOa+SEwFgnOf2629x0AstY/Bjo0TH1oruCEiyy81BRNQfGwKEXcMKq3+Y4Pn2OFv98TVeAPpOwZi+vg8PlEHcrlh3JkvPHPGNzH89surp094I4Rapd6vf83HUd791mNQpzAIJuw8fkGBP8VClr9lvs/fKtxw5py/d3nTJHOfueSe7bz5U0ewZnFODIOMd4DFRjjxyMX6R3E3xQOGvCHDXs/xUTMi8LaJ5dxPXBQNmB0z0+PhwT6YmqxQH8gQII2ajE1lQcKBFhMwpbIu6xbU/w/XN5ibSzFSXgAAADZlWElmTU0qAAAAABgAAABIAAAAAQAAAEgAAAABAAIBGgAFAAAAAQAAAAgBGwAFAAAAAQAAABAAAAAAbDclKgAAAABJRU5ErkJggg==",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "clear_scene()\n",
- "mol = mn.load.molecule_rcsb('4ozs', build_assembly=True, starting_style=\"cartoon\")\n",
- "mol.rotation_euler = (0, 3.14 / 2, 0)\n",
- "mol.select_set(True)\n",
- "bpy.ops.view3d.camera_to_view_selected()\n",
- "render_image()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "id": "5c77b916",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Finsihed opening molecule after 0.43906000000000045 seconds\n",
- "Adding object to scene.\n",
- "Added res_id after 0.00038900000000019475 s\n",
- "Added res_name after 0.004087999999999425 s\n",
- "Added atomic_number after 0.0049829999999992935 s\n",
- "Added b_factor after 5.600000000072214e-05 s\n",
- "Added vdw_radii after 0.005095000000000738 s\n",
- "Added chain_id after 0.0008569999999998856 s\n",
- "Added entity_id after 0.0003690000000009519 s\n",
- "Added atom_name after 0.003090999999999511 s\n",
- "Added lipophobicity after 0.0051989999999992875 s\n",
- "Added charge after 0.005217000000000027 s\n",
- "Added is_backbone after 0.0005509999999997461 s\n",
- "Added is_alpha_carbon after 0.00019300000000121997 s\n",
- "Added is_solvent after 0.00019099999999916406 s\n",
- "Added is_nucleic after 0.0007379999999983511 s\n",
- "Added is_peptide after 0.0011060000000000514 s\n",
- "Added is_hetero after 0.00016300000000057935 s\n",
- "Added is_carb after 0.0007489999999990005 s\n",
- "Added sec_struct after 0.0016420000000003654 s\n",
- "Finsihed add object after 0.04527799999999971 seconds\n",
- "Fra:1 Mem:64.38M (Peak 64.38M) | Time:00:00.01 | Syncing Camera\n",
- "Fra:1 Mem:64.38M (Peak 64.38M) | Time:00:00.01 | Syncing focal_point\n",
- "Fra:1 Mem:65.90M (Peak 65.90M) | Time:00:00.01 | Syncing 8HXZ\n",
- "Fra:1 Mem:76.50M (Peak 79.59M) | Time:00:00.01 | Rendering 1 / 64 samples\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:68.93M (Peak 79.59M) | Time:00:00.17 | Rendering 26 / 64 samples\n",
- "Fra:1 Mem:68.93M (Peak 79.59M) | Time:00:00.28 | Rendering 51 / 64 samples\n",
- "Fra:1 Mem:68.93M (Peak 79.59M) | Time:00:00.34 | Rendering 64 / 64 samples\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Saved: '/var/folders/r4/ym_ncgbd3qddtxqvrmhps8q80000gn/T/tmpch8l1p98/test.png'\n",
- " Time: 00:00.38 (Saving: 00:00.03)\n",
- "\n"
- ]
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "clear_scene()\n",
- "mol = mn.load.molecule_rcsb('8HXZ', center_molecule = True, starting_style=\"preset_3\")\n",
- "orient_camera(mol)\n",
- "render_image()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "id": "ac790075",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:57.36M (Peak 57.36M) | Time:00:00.01 | Mem:0.00M, Peak:0.00M | Scene, ViewLayer | Synchronizing object | 8HXZ\n",
- "Fra:1 Mem:60.98M (Peak 85.53M) | Time:00:00.02 | Mem:0.00M, Peak:0.00M | Scene, ViewLayer | Initializing\n",
- "Fra:1 Mem:49.24M (Peak 85.53M) | Time:00:00.02 | Mem:0.00M, Peak:0.00M | Scene, ViewLayer | Updating Images | Loading abandoned_factory_canteen_02_1k.hdr\n",
- "Fra:1 Mem:53.35M (Peak 85.53M) | Time:00:00.02 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Waiting for render to start\n",
- "Fra:1 Mem:53.36M (Peak 85.53M) | Time:00:00.02 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Loading render kernels (may take a few minutes the first time)\n",
- "Fra:1 Mem:53.36M (Peak 85.53M) | Time:00:00.02 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Scene\n",
- "Fra:1 Mem:53.36M (Peak 85.53M) | Time:00:00.02 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Shaders\n",
- "Fra:1 Mem:53.36M (Peak 85.53M) | Time:00:00.02 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Procedurals\n",
- "Fra:1 Mem:53.36M (Peak 85.53M) | Time:00:00.02 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Background\n",
- "Fra:1 Mem:53.36M (Peak 85.53M) | Time:00:00.02 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Camera\n",
- "Fra:1 Mem:53.36M (Peak 85.53M) | Time:00:00.02 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Meshes Flags\n",
- "Fra:1 Mem:53.36M (Peak 85.53M) | Time:00:00.02 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Objects\n",
- "Fra:1 Mem:53.36M (Peak 85.53M) | Time:00:00.02 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Objects | Copying Transformations to device\n",
- "Fra:1 Mem:54.74M (Peak 85.53M) | Time:00:00.02 | Mem:9.34M, Peak:9.34M | Scene, ViewLayer | Updating Objects | Applying Static Transformations\n",
- "Fra:1 Mem:54.74M (Peak 85.53M) | Time:00:00.02 | Mem:9.34M, Peak:9.34M | Scene, ViewLayer | Updating Particle Systems\n",
- "Fra:1 Mem:54.74M (Peak 85.53M) | Time:00:00.02 | Mem:9.34M, Peak:9.34M | Scene, ViewLayer | Updating Particle Systems | Copying Particles to device\n",
- "Fra:1 Mem:54.74M (Peak 85.53M) | Time:00:00.02 | Mem:9.34M, Peak:9.34M | Scene, ViewLayer | Updating Meshes\n",
- "Fra:1 Mem:56.18M (Peak 85.53M) | Time:00:00.02 | Mem:9.34M, Peak:9.34M | Scene, ViewLayer | Updating Mesh | Computing attributes\n",
- "Fra:1 Mem:58.93M (Peak 85.53M) | Time:00:00.02 | Mem:9.75M, Peak:9.75M | Scene, ViewLayer | Updating Mesh | Copying Attributes to device\n",
- "Fra:1 Mem:57.96M (Peak 85.53M) | Time:00:00.02 | Mem:11.11M, Peak:11.11M | Scene, ViewLayer | Updating Geometry BVH Mesh 1/1 | Building BVH\n",
- "Fra:1 Mem:57.96M (Peak 85.53M) | Time:00:00.02 | Mem:11.12M, Peak:11.12M | Scene, ViewLayer | Updating Geometry BVH Mesh 1/1 | Building BVH 0%\n",
- "Fra:1 Mem:57.96M (Peak 85.53M) | Time:00:00.02 | Mem:11.13M, Peak:11.14M | Scene, ViewLayer | Updating Scene BVH | Building\n",
- "Fra:1 Mem:58.01M (Peak 85.53M) | Time:00:00.02 | Mem:11.13M, Peak:11.14M | Scene, ViewLayer | Updating Scene BVH | Building BVH\n",
- "Fra:1 Mem:58.01M (Peak 85.53M) | Time:00:00.03 | Mem:18.04M, Peak:20.91M | Scene, ViewLayer | Updating Scene BVH | Copying BVH to device\n",
- "Fra:1 Mem:58.01M (Peak 85.53M) | Time:00:00.03 | Mem:18.04M, Peak:20.91M | Scene, ViewLayer | Updating Mesh | Computing normals\n",
- "Fra:1 Mem:61.25M (Peak 85.53M) | Time:00:00.03 | Mem:18.04M, Peak:20.91M | Scene, ViewLayer | Updating Mesh | Copying Mesh to device\n",
- "Fra:1 Mem:61.25M (Peak 85.53M) | Time:00:00.03 | Mem:21.29M, Peak:21.29M | Scene, ViewLayer | Updating Objects Flags\n",
- "Fra:1 Mem:61.25M (Peak 85.53M) | Time:00:00.03 | Mem:21.34M, Peak:21.34M | Scene, ViewLayer | Updating Primitive Offsets\n",
- "Fra:1 Mem:61.28M (Peak 85.53M) | Time:00:00.03 | Mem:21.36M, Peak:21.36M | Scene, ViewLayer | Updating Images\n",
- "Fra:1 Mem:61.28M (Peak 85.53M) | Time:00:00.03 | Mem:21.36M, Peak:21.36M | Scene, ViewLayer | Updating Camera Volume\n",
- "Fra:1 Mem:61.28M (Peak 85.53M) | Time:00:00.03 | Mem:21.36M, Peak:21.36M | Scene, ViewLayer | Updating Lookup Tables\n",
- "Fra:1 Mem:61.28M (Peak 85.53M) | Time:00:00.03 | Mem:21.36M, Peak:21.36M | Scene, ViewLayer | Updating Lights\n",
- "Fra:1 Mem:61.28M (Peak 85.53M) | Time:00:00.03 | Mem:21.36M, Peak:21.36M | Scene, ViewLayer | Updating Lights | Importance map\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:125.31M (Peak 413.28M) | Time:00:00.20 | Mem:85.41M, Peak:245.38M | Scene, ViewLayer | Updating Lights | Computing distribution\n",
- "Fra:1 Mem:125.31M (Peak 413.28M) | Time:00:00.20 | Mem:85.41M, Peak:245.38M | Scene, ViewLayer | Updating Lights | Computing tree\n",
- "Fra:1 Mem:125.36M (Peak 413.28M) | Time:00:00.20 | Mem:85.46M, Peak:245.38M | Scene, ViewLayer | Updating Integrator\n",
- "Fra:1 Mem:126.36M (Peak 413.28M) | Time:00:00.20 | Mem:86.46M, Peak:245.38M | Scene, ViewLayer | Updating Film\n",
- "Fra:1 Mem:126.37M (Peak 413.28M) | Time:00:00.20 | Mem:86.46M, Peak:245.38M | Scene, ViewLayer | Updating Lookup Tables\n",
- "Fra:1 Mem:126.37M (Peak 413.28M) | Time:00:00.20 | Mem:86.46M, Peak:245.38M | Scene, ViewLayer | Updating Baking\n",
- "Fra:1 Mem:126.37M (Peak 413.28M) | Time:00:00.20 | Mem:86.46M, Peak:245.38M | Scene, ViewLayer | Updating Device | Writing constant memory\n",
- "Fra:1 Mem:126.47M (Peak 413.28M) | Time:00:00.20 | Mem:86.46M, Peak:245.38M | Scene, ViewLayer | Sample 0/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:162.76M (Peak 413.28M) | Time:00:00.28 | Remaining:00:19.55 | Mem:122.70M, Peak:245.38M | Scene, ViewLayer | Sample 1/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:162.76M (Peak 413.28M) | Time:00:05.02 | Remaining:00:10.59 | Mem:122.70M, Peak:245.38M | Scene, ViewLayer | Sample 80/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:162.76M (Peak 413.28M) | Time:00:05.86 | Remaining:00:09.42 | Mem:122.70M, Peak:245.38M | Scene, ViewLayer | Sample 96/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:162.76M (Peak 413.28M) | Time:00:06.73 | Remaining:00:08.38 | Mem:122.70M, Peak:245.38M | Scene, ViewLayer | Sample 112/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:162.76M (Peak 413.28M) | Time:00:07.58 | Remaining:00:07.37 | Mem:122.70M, Peak:245.38M | Scene, ViewLayer | Sample 128/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:162.76M (Peak 413.28M) | Time:00:08.42 | Remaining:00:06.38 | Mem:122.70M, Peak:245.38M | Scene, ViewLayer | Sample 144/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:162.76M (Peak 413.28M) | Time:00:09.25 | Remaining:00:05.42 | Mem:122.70M, Peak:245.38M | Scene, ViewLayer | Sample 160/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:162.76M (Peak 413.28M) | Time:00:10.08 | Remaining:00:04.48 | Mem:122.70M, Peak:245.38M | Scene, ViewLayer | Sample 176/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:162.76M (Peak 413.28M) | Time:00:10.91 | Remaining:00:03.56 | Mem:122.70M, Peak:245.38M | Scene, ViewLayer | Sample 192/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:162.76M (Peak 413.28M) | Time:00:11.73 | Remaining:00:02.65 | Mem:122.70M, Peak:245.38M | Scene, ViewLayer | Sample 208/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:162.76M (Peak 413.28M) | Time:00:12.55 | Remaining:00:01.76 | Mem:122.70M, Peak:245.38M | Scene, ViewLayer | Sample 224/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:162.76M (Peak 413.28M) | Time:00:13.36 | Remaining:00:00.87 | Mem:122.70M, Peak:245.38M | Scene, ViewLayer | Sample 240/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:178.02M (Peak 413.28M) | Time:00:14.48 | Mem:122.70M, Peak:245.38M | Scene, ViewLayer | Sample 256/256\n",
- "Fra:1 Mem:178.02M (Peak 413.28M) | Time:00:14.48 | Mem:122.70M, Peak:245.38M | Scene, ViewLayer | Finished\n",
- "Saved: '/var/folders/r4/ym_ncgbd3qddtxqvrmhps8q80000gn/T/tmp20vrztbd/test.png'\n",
- " Time: 00:14.51 (Saving: 00:00.03)\n",
- "\n"
- ]
- },
- {
- "data": {
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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "render_image('cycles')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "id": "c7283125",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Finsihed opening molecule after 1.1233819999999923 seconds\n",
- "Adding object to scene.\n",
- "Added res_id after 0.0009770000000060008 s\n",
- "Added res_name after 0.010700999999983196 s\n",
- "Added atomic_number after 0.012960999999990008 s\n",
- "Added b_factor after 0.0001399999999875945 s\n",
- "Added vdw_radii after 0.013283999999998741 s\n",
- "Added chain_id after 0.0022139999999808424 s\n",
- "Added entity_id after 0.0009560000000021773 s\n",
- "Added atom_name after 0.007853000000011434 s\n",
- "Added lipophobicity after 0.013504999999980782 s\n",
- "Added charge after 0.013374999999996362 s\n",
- "Added is_backbone after 0.0013770000000192795 s\n",
- "Added is_alpha_carbon after 0.0004959999999982756 s\n",
- "Added is_solvent after 0.0004870000000209984 s\n",
- "Added is_nucleic after 0.002078999999980624 s\n",
- "Added is_peptide after 0.00273799999999369 s\n",
- "Added is_hetero after 0.0004179999999962547 s\n",
- "Added is_carb after 0.0018369999999947595 s\n",
- "Added sec_struct after 0.00584299999999871 s\n",
- "Finsihed add object after 0.11763099999998872 seconds\n",
- "Fra:1 Mem:156.63M (Peak 156.63M) | Time:00:00.02 | Syncing Camera\n",
- "Fra:1 Mem:156.63M (Peak 156.63M) | Time:00:00.02 | Syncing focal_point\n",
- "Fra:1 Mem:156.67M (Peak 156.67M) | Time:00:00.02 | Syncing 6N2Y\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:205.37M (Peak 218.66M) | Time:00:00.03 | Rendering 1 / 64 samples\n",
- "Fra:1 Mem:164.77M (Peak 218.66M) | Time:00:00.14 | Rendering 26 / 64 samples\n",
- "Fra:1 Mem:164.77M (Peak 218.66M) | Time:00:00.21 | Rendering 51 / 64 samples\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:164.83M (Peak 218.66M) | Time:00:00.24 | Rendering 64 / 64 samples\n",
- "Saved: '/var/folders/r4/ym_ncgbd3qddtxqvrmhps8q80000gn/T/tmprisvtehi/test.png'\n",
- " Time: 00:00.30 (Saving: 00:00.05)\n",
- "\n"
- ]
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "clear_scene()\n",
- "\n",
- "mol = mn.load.molecule_rcsb('6N2Y', center_molecule=True, starting_style=\"preset_3\")\n",
- "mol.select_set(True)\n",
- "mol.rotation_euler = (0, 90, 180)\n",
- "orient_camera(mol)\n",
- "render_image()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "id": "d877f8c0",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Finsihed opening molecule after 0.1895420000000172 seconds\n",
- "Adding object to scene.\n",
- "Added res_id after 9.399999999004649e-05 s\n",
- "Added res_name after 0.0009939999999915017 s\n",
- "Added atomic_number after 0.0012229999999817665 s\n",
- "Added b_factor after 1.6999999985500835e-05 s\n",
- "Added vdw_radii after 0.0012429999999881147 s\n",
- "Added chain_id after 0.00019900000000916407 s\n",
- "Added entity_id after 9.1999999995096e-05 s\n",
- "Added atom_name after 0.0007379999999841402 s\n",
- "Added lipophobicity after 0.0012619999999969878 s\n",
- "Added charge after 0.0012529999999912889 s\n",
- "Added is_backbone after 0.00015099999998824387 s\n",
- "Added is_alpha_carbon after 5.300000000829641e-05 s\n",
- "Added is_solvent after 5.400000000577165e-05 s\n",
- "Added is_nucleic after 0.000279999999975189 s\n",
- "Added is_peptide after 0.0004289999999969041 s\n",
- "Added is_hetero after 4.3000000005122274e-05 s\n",
- "Added is_carb after 0.00028100000000108594 s\n",
- "Added sec_struct after 0.0005590000000097461 s\n",
- "Finsihed add object after 0.011689999999987322 seconds\n",
- "Fra:1 Mem:42.31M (Peak 56.56M) | Time:00:00.04 | Mem:0.00M, Peak:0.00M | Scene, ViewLayer | Synchronizing object | 8CPY\n",
- "Fra:1 Mem:51.60M (Peak 56.56M) | Time:00:00.04 | Mem:0.00M, Peak:0.00M | Scene, ViewLayer | Initializing\n",
- "Fra:1 Mem:43.09M (Peak 56.56M) | Time:00:00.04 | Mem:0.00M, Peak:0.00M | Scene, ViewLayer | Updating Images | Loading abandoned_factory_canteen_02_1k.hdr\n",
- "Fra:1 Mem:48.69M (Peak 59.09M) | Time:00:00.04 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Waiting for render to start\n",
- "Fra:1 Mem:48.70M (Peak 59.09M) | Time:00:00.04 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Loading render kernels (may take a few minutes the first time)\n",
- "Fra:1 Mem:48.70M (Peak 59.09M) | Time:00:00.04 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Scene\n",
- "Fra:1 Mem:48.70M (Peak 59.09M) | Time:00:00.04 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Shaders\n",
- "Fra:1 Mem:48.70M (Peak 59.09M) | Time:00:00.04 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Procedurals\n",
- "Fra:1 Mem:48.70M (Peak 59.09M) | Time:00:00.04 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Background\n",
- "Fra:1 Mem:48.70M (Peak 59.09M) | Time:00:00.04 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Camera\n",
- "Fra:1 Mem:48.70M (Peak 59.09M) | Time:00:00.04 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Meshes Flags\n",
- "Fra:1 Mem:48.70M (Peak 59.09M) | Time:00:00.04 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Objects\n",
- "Fra:1 Mem:48.70M (Peak 59.09M) | Time:00:00.04 | Mem:8.00M, Peak:8.00M | Scene, ViewLayer | Updating Objects | Copying Transformations to device\n",
- "Fra:1 Mem:48.74M (Peak 59.09M) | Time:00:00.04 | Mem:8.04M, Peak:8.04M | Scene, ViewLayer | Updating Objects | Applying Static Transformations\n",
- "Fra:1 Mem:48.74M (Peak 59.09M) | Time:00:00.04 | Mem:8.04M, Peak:8.04M | Scene, ViewLayer | Updating Particle Systems\n",
- "Fra:1 Mem:48.74M (Peak 59.09M) | Time:00:00.04 | Mem:8.04M, Peak:8.04M | Scene, ViewLayer | Updating Particle Systems | Copying Particles to device\n",
- "Fra:1 Mem:48.74M (Peak 59.09M) | Time:00:00.04 | Mem:8.04M, Peak:8.04M | Scene, ViewLayer | Updating Meshes\n",
- "Fra:1 Mem:50.67M (Peak 59.09M) | Time:00:00.04 | Mem:8.04M, Peak:8.04M | Scene, ViewLayer | Updating Mesh | Computing attributes\n",
- "Fra:1 Mem:52.41M (Peak 59.09M) | Time:00:00.04 | Mem:8.05M, Peak:8.05M | Scene, ViewLayer | Updating Mesh | Copying Attributes to device\n",
- "Fra:1 Mem:52.38M (Peak 59.09M) | Time:00:00.04 | Mem:9.75M, Peak:9.75M | Scene, ViewLayer | Updating Geometry BVH Mesh 3/3 | Building BVH\n",
- "Fra:1 Mem:52.38M (Peak 59.09M) | Time:00:00.04 | Mem:9.75M, Peak:9.75M | Scene, ViewLayer | Updating Geometry BVH Mesh 2/3 | Building BVH\n",
- "Fra:1 Mem:52.38M (Peak 59.09M) | Time:00:00.04 | Mem:9.75M, Peak:9.75M | Scene, ViewLayer | Updating Geometry BVH Mesh 1/3 | Building BVH\n",
- "Fra:1 Mem:52.38M (Peak 59.09M) | Time:00:00.04 | Mem:13.61M, Peak:13.61M | Scene, ViewLayer | Updating Geometry BVH Mesh 1/3 | Building BVH 0%\n",
- "Fra:1 Mem:52.38M (Peak 59.09M) | Time:00:00.04 | Mem:17.81M, Peak:21.67M | Scene, ViewLayer | Updating Scene BVH | Building\n",
- "Fra:1 Mem:52.38M (Peak 59.09M) | Time:00:00.04 | Mem:17.81M, Peak:21.67M | Scene, ViewLayer | Updating Scene BVH | Building BVH\n",
- "Fra:1 Mem:52.38M (Peak 59.09M) | Time:00:00.04 | Mem:17.82M, Peak:21.67M | Scene, ViewLayer | Updating Scene BVH | Copying BVH to device\n",
- "Fra:1 Mem:52.38M (Peak 59.09M) | Time:00:00.04 | Mem:17.82M, Peak:21.67M | Scene, ViewLayer | Updating Mesh | Computing normals\n",
- "Fra:1 Mem:56.74M (Peak 59.09M) | Time:00:00.05 | Mem:17.82M, Peak:21.67M | Scene, ViewLayer | Updating Mesh | Copying Mesh to device\n",
- "Fra:1 Mem:56.74M (Peak 59.09M) | Time:00:00.05 | Mem:22.17M, Peak:22.17M | Scene, ViewLayer | Updating Objects Flags\n",
- "Fra:1 Mem:56.74M (Peak 59.09M) | Time:00:00.05 | Mem:22.17M, Peak:22.17M | Scene, ViewLayer | Updating Primitive Offsets\n",
- "Fra:1 Mem:56.74M (Peak 59.09M) | Time:00:00.05 | Mem:22.17M, Peak:22.17M | Scene, ViewLayer | Updating Images\n",
- "Fra:1 Mem:56.74M (Peak 59.09M) | Time:00:00.05 | Mem:22.17M, Peak:22.17M | Scene, ViewLayer | Updating Camera Volume\n",
- "Fra:1 Mem:56.74M (Peak 59.09M) | Time:00:00.05 | Mem:22.17M, Peak:22.17M | Scene, ViewLayer | Updating Lookup Tables\n",
- "Fra:1 Mem:56.74M (Peak 59.09M) | Time:00:00.05 | Mem:22.17M, Peak:22.17M | Scene, ViewLayer | Updating Lights\n",
- "Fra:1 Mem:56.74M (Peak 59.09M) | Time:00:00.05 | Mem:22.17M, Peak:22.17M | Scene, ViewLayer | Updating Lights | Importance map\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:120.77M (Peak 408.74M) | Time:00:00.19 | Mem:86.22M, Peak:246.18M | Scene, ViewLayer | Updating Lights | Computing distribution\n",
- "Fra:1 Mem:120.77M (Peak 408.74M) | Time:00:00.19 | Mem:86.22M, Peak:246.18M | Scene, ViewLayer | Updating Lights | Computing tree\n",
- "Fra:1 Mem:120.77M (Peak 408.74M) | Time:00:00.19 | Mem:86.22M, Peak:246.18M | Scene, ViewLayer | Updating Integrator\n",
- "Fra:1 Mem:121.77M (Peak 408.74M) | Time:00:00.19 | Mem:87.22M, Peak:246.18M | Scene, ViewLayer | Updating Film\n",
- "Fra:1 Mem:121.77M (Peak 408.74M) | Time:00:00.19 | Mem:87.22M, Peak:246.18M | Scene, ViewLayer | Updating Lookup Tables\n",
- "Fra:1 Mem:121.77M (Peak 408.74M) | Time:00:00.19 | Mem:87.22M, Peak:246.18M | Scene, ViewLayer | Updating Baking\n",
- "Fra:1 Mem:121.77M (Peak 408.74M) | Time:00:00.19 | Mem:87.22M, Peak:246.18M | Scene, ViewLayer | Updating Device | Writing constant memory\n",
- "Fra:1 Mem:121.78M (Peak 408.74M) | Time:00:00.19 | Mem:87.22M, Peak:246.18M | Scene, ViewLayer | Sample 0/256\n",
- "Fra:1 Mem:158.07M (Peak 408.74M) | Time:00:00.29 | Remaining:00:25.96 | Mem:123.46M, Peak:246.18M | Scene, ViewLayer | Sample 1/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:158.07M (Peak 408.74M) | Time:00:07.53 | Remaining:00:16.14 | Mem:123.46M, Peak:246.18M | Scene, ViewLayer | Sample 80/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:158.07M (Peak 408.74M) | Time:00:08.97 | Remaining:00:14.64 | Mem:123.46M, Peak:246.18M | Scene, ViewLayer | Sample 96/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:158.07M (Peak 408.74M) | Time:00:10.40 | Remaining:00:13.12 | Mem:123.46M, Peak:246.18M | Scene, ViewLayer | Sample 112/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:158.07M (Peak 408.74M) | Time:00:11.78 | Remaining:00:11.59 | Mem:123.46M, Peak:246.18M | Scene, ViewLayer | Sample 128/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:158.07M (Peak 408.74M) | Time:00:13.17 | Remaining:00:10.09 | Mem:123.46M, Peak:246.18M | Scene, ViewLayer | Sample 144/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:158.07M (Peak 408.74M) | Time:00:14.56 | Remaining:00:08.62 | Mem:123.46M, Peak:246.18M | Scene, ViewLayer | Sample 160/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:158.07M (Peak 408.74M) | Time:00:15.94 | Remaining:00:07.15 | Mem:123.46M, Peak:246.18M | Scene, ViewLayer | Sample 176/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:158.07M (Peak 408.74M) | Time:00:17.34 | Remaining:00:05.71 | Mem:123.46M, Peak:246.18M | Scene, ViewLayer | Sample 192/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:158.07M (Peak 408.74M) | Time:00:18.72 | Remaining:00:04.27 | Mem:123.46M, Peak:246.18M | Scene, ViewLayer | Sample 208/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:158.07M (Peak 408.74M) | Time:00:20.08 | Remaining:00:02.84 | Mem:123.46M, Peak:246.18M | Scene, ViewLayer | Sample 224/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:158.07M (Peak 408.74M) | Time:00:21.43 | Remaining:00:01.41 | Mem:123.46M, Peak:246.18M | Scene, ViewLayer | Sample 240/256\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Fra:1 Mem:173.32M (Peak 408.74M) | Time:00:23.05 | Mem:123.46M, Peak:246.18M | Scene, ViewLayer | Sample 256/256\n",
- "Fra:1 Mem:173.32M (Peak 408.74M) | Time:00:23.05 | Mem:123.46M, Peak:246.18M | Scene, ViewLayer | Finished\n",
- "Saved: '/var/folders/r4/ym_ncgbd3qddtxqvrmhps8q80000gn/T/tmpbq4s3mcs/test.png'\n",
- " Time: 00:23.09 (Saving: 00:00.03)\n",
- "\n"
- ]
- },
- {
- "data": {
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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "clear_scene()\n",
- "mol = mn.load.molecule_rcsb('8CPY', build_assembly=True, starting_style=\"surface\")\n",
- "orient_camera(mol)\n",
- "render_image('cycles')"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3 (ipykernel)",
- "language": "python",
- "name": "python3"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
\ No newline at end of file
diff --git a/docs/.jupyter_cache/global.db b/docs/.jupyter_cache/global.db
deleted file mode 100644
index a7561609..00000000
Binary files a/docs/.jupyter_cache/global.db and /dev/null differ
diff --git a/docs/_quarto.yml b/docs/_quarto.yml
index 6d570055..1e497447 100644
--- a/docs/_quarto.yml
+++ b/docs/_quarto.yml
@@ -40,9 +40,6 @@ website:
format:
html:
page-layout: full
- grid:
- sidebar-width: 250px
- body-width: 1000px
theme:
light: yeti
dark: superhero
diff --git a/docs/build_node_docs.py b/docs/build_node_docs.py
index cbb10f35..c03ebdfe 100644
--- a/docs/build_node_docs.py
+++ b/docs/build_node_docs.py
@@ -1,16 +1,27 @@
import bpy
from quartodoc import MdRenderer
-import molecularnodes as mn
+
+try:
+ from bl_ext.user_default import molecularnodes as mn
+except ImportError:
+ import molecularnodes as mn
+
import griffe
import os
import sys
import pathlib
+# from .. import molecularnodes as mn
-sys.path.insert(0, os.path.abspath('..'))
+sys.path.insert(0, os.path.abspath(".."))
folder = pathlib.Path(__file__).resolve().parent
file_output_qmd = os.path.join(folder, "nodes/index.qmd")
+
+def title_format(title: str) -> str:
+ return "## " + title.title().replace("Dna", "DNA").replace("Cellpack", "CellPack")
+
+
# open the data file
bpy.ops.wm.open_mainfile(filepath=mn.blender.nodes.MN_DATA_FILE)
@@ -28,12 +39,12 @@ def get_values(sockets):
default = None
if dtype == "Float":
default = round(socket.default_value, 2)
- elif dtype in ['Geometry', 'Collection', 'Object']:
+ elif dtype in ["Geometry", "Collection", "Object"]:
default = None
elif dtype == "Vector":
default = [round(x, 2) for x in socket.default_value]
elif dtype == "Material":
- default = '`MN Default`'
+ default = "`MN Default`"
elif dtype == "Color":
default = col_to_rgb_str(socket.default_value)
else:
@@ -44,21 +55,20 @@ def get_values(sockets):
name=socket.name,
annotation=dtype,
value=default,
- description=socket.description
+ description=socket.description,
)
)
return param_list
-cat = ''
+cat = ""
text = griffe.docstrings.dataclasses.DocstringSectionText
params = griffe.docstrings.dataclasses.DocstringSectionParameters
categories = {}
for category, node_list in mn.ui.node_info.menu_items.items():
objects = []
- objects.append(
- [text(title=None, value=f"## {mn.blender.nodes.format_node_name(category)}")])
+ objects.append([text(title=None, value=title_format(category))])
for item in node_list:
if isinstance(item, str):
@@ -66,24 +76,26 @@ def get_values(sockets):
iter_list = [item]
- if item['label'] == "custom":
- iter_list = item['values']
+ if item["label"] == "custom":
+ iter_list = item["values"]
for entry in iter_list:
- name = entry['name']
+ name = entry["name"]
if name.startswith("mn."):
- name = entry['backup']
+ name = entry["backup"]
entry_list = []
- desc = entry.get('description')
- urls = entry.get('video_url')
+ desc = entry.get("description")
+ urls = entry.get("video_url")
- inputs = params(get_values(
- mn.blender.nodes.inputs(bpy.data.node_groups[name])))
- outputs = params(get_values(
- mn.blender.nodes.outputs(bpy.data.node_groups[name])))
+ inputs = params(
+ get_values(mn.blender.nodes.inputs(bpy.data.node_groups[name]))
+ )
+ outputs = params(
+ get_values(mn.blender.nodes.outputs(bpy.data.node_groups[name]))
+ )
- title = mn.blender.nodes.format_node_name(entry.get('label'))
+ title = entry.get("label")
entry_list.append(text(title=None, value=f"### {title}"))
if desc:
entry_list.append(text(title=None, value=desc))
@@ -91,15 +103,14 @@ def get_values(sockets):
if not isinstance(urls, list):
urls = [urls]
[
- entry_list.append(
- text(title=None, value=f"")
- ) for url in urls
+ entry_list.append(text(title=None, value=f""))
+ for url in urls
]
- if len(inputs.as_dict()['value']) > 0:
+ if len(inputs.as_dict()["value"]) > 0:
entry_list.append(text(value="\n#### Inputs"))
entry_list.append(inputs)
- if len(outputs.as_dict()['value']) > 0:
+ if len(outputs.as_dict()["value"]) > 0:
entry_list.append(text(value="\n#### Outputs"))
entry_list.append(outputs)
@@ -116,10 +127,10 @@ def get_values(sockets):
"""
for category, object in categories.items():
- with open(os.path.join(folder, f'nodes/{category}.qmd'), 'w') as file:
+ with open(os.path.join(folder, f"nodes/{category}.qmd"), "w") as file:
file.write(header)
for doc in object:
- section = ''
+ section = ""
for sec in doc:
file.write(ren.render(sec))
file.write("\n\n")
diff --git a/docs/images/installation/blender_download.png b/docs/images/installation/blender_download.png
deleted file mode 100644
index 8c0b0a19..00000000
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diff --git a/docs/images/installation/download-blender.png b/docs/images/installation/download-blender.png
new file mode 100644
index 00000000..5b645aba
Binary files /dev/null and b/docs/images/installation/download-blender.png differ
diff --git a/docs/images/installation/download.mp4 b/docs/images/installation/download.mp4
new file mode 100644
index 00000000..3bd97807
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diff --git a/docs/images/installation/mn-download.png b/docs/images/installation/mn-download.png
deleted file mode 100644
index d99d9145..00000000
Binary files a/docs/images/installation/mn-download.png and /dev/null differ
diff --git a/docs/images/installation/mn-pref-install-packages.png b/docs/images/installation/mn-pref-install-packages.png
deleted file mode 100644
index 7551f045..00000000
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diff --git a/docs/images/installation/mn-pref-install-zip.png b/docs/images/installation/mn-pref-install-zip.png
deleted file mode 100644
index 080dfeb3..00000000
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diff --git a/docs/images/installation/mn-pref-open.png b/docs/images/installation/mn-pref-open.png
deleted file mode 100644
index ad7faa1e..00000000
Binary files a/docs/images/installation/mn-pref-open.png and /dev/null differ
diff --git a/docs/images/installation/preferences.png b/docs/images/installation/preferences.png
new file mode 100644
index 00000000..c16393da
Binary files /dev/null and b/docs/images/installation/preferences.png differ
diff --git a/docs/images/installation/search_install.png b/docs/images/installation/search_install.png
new file mode 100644
index 00000000..2a289883
Binary files /dev/null and b/docs/images/installation/search_install.png differ
diff --git a/docs/installation.md b/docs/installation.md
index 8de0754c..7a3e4c4b 100644
--- a/docs/installation.md
+++ b/docs/installation.md
@@ -3,69 +3,42 @@ title: "Installation"
---
::: callout-warning
-# Versions
-Molecular Nodes now has version numbers that match the Blender version it is targetted to work with.
-
-Molecular Nodes will `4.0.X` will work with Blender `4.0`. When Blender is updated to `4.1`, Molecular Nodes will start start using `4.1.X` for releases that work with that version.
-
-Blender also has minor version numbers (such as `4.0.1` but these will not affect the compatibility with Molecular Nodes, and you should just download the latest version.)
-
-Molecular nodes will usually work with higher versions of Blender, but will not work with earlier versions. If you get errors during installation or using the software, double check the versions you are using of each.
+# Blender 4.2
+For Blender 4.2, we no longer have to download anything externally. Molecular Nodes can be installed and updated from _within_ Blender, using the new [`extensions`](https://https://extensions.blender.org/) platform. The installation instructions below are now much simpler.
:::
## Downloading Blender
Molecular Nodes is an add-on for the 3D animation program Blender. It runs inside of Blender, so the first step for installation is to [download and install](https://www.blender.org/download/) the latest version of blender.
-{align="center" width="800px"}
-
-## Downloading Molecular Nodes
-
-Download the latest bundled release from the [releases page](https://github.com/BradyAJohnston/MolecularNodes/releases/). Don't download the GitHub repo itself, as this won't install inside of Blender.
-
-::: callout-note
-# Safari
-
-When downloading on MacOS with Safari, it automatically unzips the file into a `MolecularNodes` folder. This is extremely unhelpful as Blender requires the `.zip` file to install the addon. Either download with a different browser, or compress the folder again to `MolecularNodes.zip`.
-:::
+{align="center" width="800px"}
-[{fig-alt="Screenshot of the Molecular Nodes releases page on Github, with the relevant download link circled in red." width="700px" align="center"}](https://github.com/BradyAJohnston/MolecularNodes/releases/)
## Installing the Addon
Follow the screenshots below to install the add-on. These steps should be the same across platforms.
-::: callout-warning
-### Windows Administrator
-
-If you are on Windows, you may need to run Blender as Administrator to successfully complete the following installation.
-:::
-
-### Open Preferences Panel
-
-> Click \`Edit' -\> 'Preferences' or press Cmd + , on Mac.
-
-
+Open the preferences window.
-### Click 'Install' while in 'Add-ons'
+
-
+Select the `Get Extensions` panel and search for `Molecular Nodes`.
-Select `molecularnodes_X.X.X.zip`. The `X`'s will be the current version number of the add-on.
+
-## Installing Additional Python Packages
+Clicking the `Install` button will download and install the add-on. The download is ~100 MB so may take some minutes depending on internet connection.
-To import different molecular data formats, additional python packages are required. These will be installed into the python that comes with Blender.
+
-To get started downloading from the PDB, you only require the `biotite` package. Each package will give a brief description of what it is used for, and display version information once installed.
+### That's it!
-
+All of the additional python packages now come pre-installed. To update the add-on, use the same panel and Blender should automatically detect updates.
-A message should report the successful installation of each package, with the button changing to Reinstall biotite once Molecular Nodes detects the successful installation of the package.
+## Installing the Startup Template
-You may need to restart Blender after package installation for them to work properly.
+There are a number of settings that are useful to have tweaked on startup. You can install the `Molecular Nodes` startup template in the add-on preferences or uninstall the template.
-If you have troubled with installation, search through the [issues page](https://github.com/BradyAJohnston/MolecularNodes/issues) for a potential solution. If you can't find the solution there, please open a new issue on the GitHub page. Please don't just DM or email me directly. It's better to do problem solving out in the open, as others might have the same issue or someone other than me may already have a solution!
+THis adds it as an option on the startup splash screen, or when starting a new file.
## Start Importing Structures!
diff --git a/docs/nodes/index.qmd b/docs/nodes/index.qmd
index b6dd67bc..390c73b4 100644
--- a/docs/nodes/index.qmd
+++ b/docs/nodes/index.qmd
@@ -19,7 +19,7 @@ of it first before making changes by doing the following:
1. Right click on the node and select `Show / Hide` -> `Node Options`
2. Click the `Make Copy` icon to the right of the node group's name
- 3. It will create a duplicate node group called `MN_style_cartoon.001` for example,
- which you can now freely edit without changing the other `MN_style_cartoon` node
+ 3. It will create a duplicate node group called `Style Cartoon.001` for example,
+ which you can now freely edit without changing the other `Style Cartoon` node
groups.
diff --git a/docs/tutorials/02_selections.md b/docs/tutorials/02_selections.md
index 43bacf09..218adf7d 100644
--- a/docs/tutorials/02_selections.md
+++ b/docs/tutorials/02_selections.md
@@ -1,46 +1,61 @@
---
title: Selections
+author: Brady Johnston
---
-
-Selections power every part of Molecular Visualisation. You are probably used to using selections via manually pointing and clicking with your mouse, or typing long strings of complex selection algebra.
+Selections power every part of Molecular Visualisation.
+You are probably used to using selections via manually pointing and clicking with your mouse, or typing long strings of complex selection algebra.
## A Simple Example
To create a selection of residues ALA, CYS and TRP, only inside of chain A, you would use the following code inside of PyMol:
-```python
+``` python
select my_selection, chain A and (resn ALA+CYS+TRP)
```
-Inside of Molecular Nodes, you combine different selection nodes using `Boolean Math` nodes to create increasingly complex selections.
+Inside of Molecular Nodes, you combine different *selection* nodes.
+The outputs of these are are a *boolean* `True / False` for each atom.
+The logical test being performed depends on the node.
+To recreate the selection above, we can use the `Select Chain` and `Select Res Name` nodes.
-This might initially seem quite verbose. The good thing however is that these selections can always be updated and tweaked. They can even be created procedurally based on the values of other selections or animations.
+This might initially seem quite verbose.
+The good thing however is that these selections can always be updated and tweaked.
+They can even be created procedurally based on the values of other selections or animations.
-In the example video below we are using the selection to apply the `Atoms` style. We can change the residues and chains that are selected by ticking and unticking the boxes. Each of these selections also take a _field_ input, so they can use the output of other selection nodes. The selections from the two nodes are being combined with the `Boolean Math` node set to `And`. Other boolean math operations are also available.
+In the example video below we are using the selection to apply the `Atoms` style.
+We can change the residues and chains that are selected by ticking and unticking the boxes.
+Each of these selections also take a *field* input, so they can use the output of other selection nodes.
+The selections from the two nodes are being combined with the `Boolean Math` node set to `And`.
+Other boolean math operations are also available.
-
## Different Styles Combined
-In this example, we apply the `Surface` style to one chain, and the `Atoms` style to another chain. We can join the two styles together with the `Join Geometry` node.
+In this example, we apply the `Surface` style to one chain, and the `Atoms` style to another chain.
+We can join the two styles together with the `Join Geometry` node.
## Combining Selections
-Selections can be combined not just through `Boolean Math` nodes, but also by connecting the output from one node to the input of another selection. In this example we are selecting two chains for applying the `Atoms` style to.
+Selections can be combined not just through `Boolean Math` nodes, but also by connecting the output from one node to the input of another selection.
+In this example we are selecting two chains for applying the `Atoms` style to.
-The selection of `Chain A` we then control though the `Cube` selection node. The addition of this node creates a new object called `Empty_Cube` which we can transform by Grabbing, Rotating and Scaling to change what is inside of the cube. The style is then applied to the updated selection, which varies for `Cahin A` but not for `Chain F`.
+The selection of `Chain A` we then control though the `Cube` selection node.
+The addition of this node creates a new object called `Empty_Cube` which we can transform by Grabbing, Rotating and Scaling to change what is inside of the cube.
+The style is then applied to the updated selection, which varies for `Cahin A` but not for `Chain F`.
## More Examples
-You can use these dynamic selections for any kind of boolean input. It can be used to select the atoms to apply a style to or even to change different aspects of that style itself. In this example, we first choose the atoms to apply the style to; then instead, we change whether or not we use cylinders for the cartoon style.
+You can use these dynamic selections for any kind of boolean input.
+It can be used to select the atoms to apply a style to or even to change different aspects of that style itself.
+In this example, we first choose the atoms to apply the style to; then instead, we change whether or not we use cylinders for the cartoon style.
@@ -52,10 +67,12 @@ Selecting based on the `entity_id`, to reveal the rotary axel of the protein com
To open a `.pdb`, `.mmCIF`, `.pdbx` or other similar files, use the Local File tab.
-You can set the name for the molecule, which will become the object's name once imported. Use the folder icon to select the file you would like to import.
+You can set the name for the molecule, which will become the object's name once imported.
+Use the folder icon to select the file you would like to import.
-The 'Default Style' was changed to 'Cartoon', but no other default import options were changed. The Default Cube was deleted with X as the protein was imported *inside* of the cube.
+The 'Default Style' was changed to 'Cartoon', but no other default import options were changed.
+The Default Cube was deleted with X as the protein was imported *inside* of the cube.
\ No newline at end of file
diff --git a/docs/tutorials/03_molecular_dynamics.md b/docs/tutorials/03_molecular_dynamics.md
index eee0b0dd..fadae4c2 100644
--- a/docs/tutorials/03_molecular_dynamics.md
+++ b/docs/tutorials/03_molecular_dynamics.md
@@ -2,6 +2,7 @@
title: Molecular Dynamics
author: Brady Johnston
bibliography: references.bib
+fig-align: center
---
::: {#fig-md-example-render}
@@ -15,91 +16,58 @@ Trajectory files are available via [MDAnalysisData](https://www.mdanalysis.org/M
As well as importing static structures, the results from molecular dynamics simulations can be imported as models in to Blender.
This is enabled through the excellent package [`MDAnalysis`](https://www.mdanalysis.org/).
-The imported structure will have an object created that will act as the topology file.
-Depending on the import method, the frames of the trajectory will either be streamed from the disk, or loaded in to memory inside of the `.blend` file as their own separate objects.
+The imported structure will have an object created that will act as the topology file, and a connection is maintained the underlying `MDAnalysis.Universe` object that provides coordinates and allows for dynamic calculations to be performed during playback.
-## MD Trajectory Panel
-
-To import trajectories, change the import method in the Molecular Nodes panel to the `MD` method.
-
-
-
-The minimum requirements are a valid `Topology`` file, that can be read by [MDAnalysis](https://userguide.mdanalysis.org/stable/formats/index.html).
-
-If just a topology is selected then a static model should be imported.
-If additionally a trajectory is selected, then the toplogy will have coordinates that change when the `Frame` changes inside of Blender.
+::: callout-warning
+## Saving the File
-Below selects some example `MDAnlaysis` data for import, without changing any of the defaults.
-
-
+When saving the `.blend` file, a corresponding `.MNSession` file will be saved next to your Blender file.
+When reloading the file, the `MDAnalysis.Universe` will be reloaded from this file, so ensure you keep it next to the `.blend` file.
+:::
-### Import Options
+## MD Trajectory Panel
-Before importing, we can change some of the import settings to be applied on import. More detail on each option is further in this tutorial, but the short descriptions:
+To import trajectories, change the import method in the Molecular Nodes panel to the `MD` method.
+To import a trajectory, select the topology and trajectory files.
+You can choose the initial starting style, but this can easily be changed after import.
-- `Style` Tick box whether to set up nodes to apply a style, or just import the data. If enabled, a default style to be applied on import is selected. This can be changed easily after import.
-- `Import Filter` a MDAnalysis [selection string](https://userguide.mdanalysis.org/stable/selections.html) to filter the topology when importing. Default is to import everything, but you can input strings such as 'protein' to only import the protein component.
-- `In Memory` Whether to load the selected frames (from `start` to `stop`, incrementing by `step`) into memory and discard the MDAnalysis session when importing. Default is false and streams the trajectory from disk.
-- `Custom Selections` Users can create multiple custom selections that appear as boolean attributes on the imported trajectory. Useful for creating groups using MDAnalysis [selection strings](https://userguide.mdanalysis.org/stable/selections.html) to then utilise inside of the created node tree.
+{width="500px"}
## Import the Trajectory
-Click `Load` to import the selected trajectory with the chosen options. The model will appear in the scene, and once you change frame in the scene, it will update the frame displayed in the viewport.
-
-
+Click `Load` to import the selected trajectory with the chosen options.
+The model will appear in the scene, and when the `Frame` changes inside of Blender, the corresponding frame will be displayed from the imported trajectory.
### Changing Style
-You can change the style by altering the `Style` nodes that are use inside of the node tree.
-
-As you can see in the example, if we don't apply the style, we can view just the raw atomic data that is being updated. Depending on which nodes we use to process that data, we can create different styles of further animations.
-
-
+To change which style is displayed, you have to interact with the *Geometry Nodes*,you use the same Geometry Nodes tree that you use for other structures.
+Adding new style nodes and specifying their selections to limit limit the style to particular selections of atoms.
### Subframes
-By default, each frame on the timeline matches directly with the frames in the loaded trajectory.
-
-You can add `subframes` which then tell Blender to add additional frames in between, which linearly interpolate between positions. This can slow down the animation and sometimes make it easier to view. The subframes for the trajectory can be adjusted in the `Object` section of the Molecular Nodes panel.
-
-The `Frame` number in Blender no longer directly matches the frame displayed from the trajectory, with the trajectory playing back 'slower' than previously.
-
-
-
-
+By default each frame on Blender's timeline corresponds to the frame in the imported trajectory.
+You can increase the `Subframes` number for this trajectory, and the selected number of frames will be created in between the frames of the loaded trajectory.
+If Interpolate is selected, the positions will be linearly interpolated between the frames of the trajectory.
+If subframes are used, the frames of the trajectory will no longer directly correspond to the frames inside of Blender.
+With 2 subframes, frame 9 inside of Blender will correspond frame 3 of the trajectory.
-## Streaming vs In Memory
+When linearly interpolating through subframes of a trajectory, we can correct for periodic boundary crossing with the `Correct` option enabled.
+This is only available if your simulation box is cubic.
-### Streaming
+### Custom Selections
-The default option will associate an `MDAnlaysis` session with the read topology file.
-This will stream the topology from disk, as the frame in the scene inside of Blender changes.
-If the original topology or trajectory files are moved, this will break the connection to the data.
-This is the most performant option, but will potentially break if changing computers.
+Creating selections through nodes is a very quick and powerful way of working.
+It can be easier to create selections through text, and some niche selections are currently unable to created through the node system.
-Below is an example of importing a trajectory, by streaming the frames.
-As the frame changes in the scene, the loaded frame is updated on the imported protein, based on the created MDAnalysis session.
-Interpolation between frames is currently not supported with this import method.
+With `Trajectory` object selected, in the `Object` tab in the molecular nodes panel, we can create custom selections using the [MDAnalysis selection language](https://userguide.mdanalysis.org/stable/selections.html).
+These selections will become available inside of the Geometry Nodes tree as a `Named Attribute`.
-The MDAnalysis session will be saved when the `.blend` file is saved, and should be restored when the `.blend` file is reopened.
+There are toggles for these selections to be updating and / or periodic in how they are calculated.
+These options correspond directly to the options that are possible through the `MDAnalysis.Universe.select_atoms()` method for creating atom groups.
-
+Use the `Named Attribute` or `Select Attribute` nodes to get access to these selections inside of Geometry Nodes, and use them to selectively apply styles, colors and animations to your trajectory.
-### In Memory
-
-The `In Memory` option will load all frames of the trajectory in to memory, and store them as objects inside of the `MN_data` collection in the scene.
-This will ensure that all of the associated data is stored inside of the `.blend` file for portability, but will come at the cost of performance for very large trajectories.
-It also breaks the connection to the underlying `MDAnalysis` session, which limits the ability to further tweak the trajectory after import.
-
-If `In Memory` is selected, the frames are imported as individual objects and stored in a `MN_data` collection.
-The interpolation between frames is then handled by nodes inside of Geometry Nodes, which aren't necessarily linked to the scene frame.
-
-This will create a larger `.blend` file and can lead to some performance drops with large trajectories, but ensures all of the data is kept within the saved file, and can enable further creative control through Geometry Nodes.
-
-All connection to the underlying MDAnalysis session is lost on import, and the selections and trajectory cannot changed.
-To make changes you must reimport the trajectory.
-
-
+{width="500px"}
## Creating the Animation
@@ -123,18 +91,25 @@ We also enabled `EEVEE` atoms to display in the EEVEE render engine.
#### Changing Styles
-We can change the style of the imported trajectory, by adding a new style node. We can combine styles with the `Join Geometry`. For more details on adding styles, see the (importing)[01_importing.qmd] tutorial.
+We can change the style of the imported trajectory, by adding a new style node.
+We can combine styles with the `Join Geometry`.
+For more details on adding styles, see the (importing)\[01_importing.qmd\] tutorial.
-We can apply the atoms style, only to the side chains of the protein, by using the `Backbone` selection node, and using the `is_side_chain` output. This selectively applies the style to only those atoms in the selection. The combined styles now contain only the atoms for the side chains and a continuous ribbon for the protein.
+We can apply the atoms style, only to the side chains of the protein, by using the `Backbone` selection node, and using the `is_side_chain` output.
+This selectively applies the style to only those atoms in the selection.
+The combined styles now contain only the atoms for the side chains and a continuous ribbon for the protein.
-
### Setting the Scene
-We can set up the scene a bit nicer with a backdrop. In this case we create a plane using Shift + A to add a plane, go in to [edit mode](#01-introduction-edit-mode) and extrude the backbdrop up with the E key. We can create a slightly curved corner by bevelling the corner. Select the two vertices of the edge and click Ctrl + B. Move the mouse and use the scroll wheel to adjust the settings, then left click to apply.
+We can set up the scene a bit nicer with a backdrop.
+In this case we create a plane using Shift + A to add a plane, go in to [edit mode](#01-introduction-edit-mode) and extrude the backbdrop up with the E key.
+We can create a slightly curved corner by bevelling the corner.
+Select the two vertices of the edge and click Ctrl + B.
+Move the mouse and use the scroll wheel to adjust the settings, then left click to apply.
diff --git a/docs/tutorials/images/panel.png b/docs/tutorials/images/panel.png
new file mode 100644
index 00000000..d47b482c
Binary files /dev/null and b/docs/tutorials/images/panel.png differ
diff --git a/docs/tutorials/images/panel_selection.png b/docs/tutorials/images/panel_selection.png
new file mode 100644
index 00000000..7bec6ad6
Binary files /dev/null and b/docs/tutorials/images/panel_selection.png differ
diff --git a/molecularnodes/__init__.py b/molecularnodes/__init__.py
index 33a31778..2dfb1d1a 100644
--- a/molecularnodes/__init__.py
+++ b/molecularnodes/__init__.py
@@ -11,70 +11,76 @@
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
-from .utils import template_install
-from . import auto_load
-from .props import MolecularNodesObjectProperties
-from .ui.node_menu import MN_add_node_menu, draw_node_menus
-from .io.parse.mda import _rejuvenate_universe, _sync_universe
-from .io.parse.star import _rehydrate_ensembles
-from .ui.panel import change_style_menu, change_style_node_menu
import bpy
+from bpy.app.handlers import frame_change_post, load_post, save_post
-bl_info = {
- "name": "molecularnodes",
- "author": "Brady Johnston",
- "description": "Toolbox for molecular animations in Blender & Geometry Nodes.",
- "blender": (4, 1, 0),
- "version": (4, 1, 4),
- "location": "Scene Properties -> Molecular Nodes",
- "warning": "",
- "doc_url": "https://bradyajohnston.github.io/MolecularNodes/",
- "tracker_url": "https://github.com/BradyAJohnston/MolecularNodes/issues",
- "category": "Import",
-}
+from . import entities, operators, props, session, ui
+from .ui import pref
+from .ui.node_menu import MN_add_node_menu
+from .ui.panel import MN_PT_Scene, pt_object_context, change_style_node_menu
-auto_load.init()
+all_classes = (
+ ui.CLASSES
+ + operators.CLASSES
+ + entities.CLASSES
+ + [
+ props.MolecularNodesObjectProperties,
+ MN_PT_Scene,
+ ]
+ + pref.CLASSES
+ + session.CLASSES
+)
-universe_funcs = [_sync_universe, _rejuvenate_universe]
+
+def _test_register():
+ try:
+ register()
+ except Exception:
+ unregister()
+ register()
def register():
- auto_load.register()
+ # register all of the import operators
+ for op in all_classes:
+ try:
+ bpy.utils.register_class(op)
+ except Exception:
+ # print(e)
+ pass
+
bpy.types.NODE_MT_add.append(MN_add_node_menu)
- bpy.types.VIEW3D_MT_object_context_menu.prepend(change_style_menu)
+ bpy.types.VIEW3D_MT_object_context_menu.prepend(pt_object_context)
bpy.types.NODE_MT_context_menu.prepend(change_style_node_menu)
- bpy.types.Object.mn = bpy.props.PointerProperty(type=MolecularNodesObjectProperties)
- for func in universe_funcs:
- try:
- bpy.app.handlers.load_post.append(func)
- except ValueError as e:
- print(f"Filaed to append {func}, error: {e}.")
- template_install()
+ save_post.append(session._pickle)
+ load_post.append(session._load)
+ frame_change_post.append(entities.trajectory.handlers.update_trajectories)
-def unregister():
- try:
- bpy.types.NODE_MT_add.remove(MN_add_node_menu)
- bpy.types.VIEW3D_MT_object_context_menu.remove(change_style_menu)
- bpy.types.NODE_MT_context_menu.remove(change_style_node_menu)
+ bpy.types.Scene.MNSession = session.MNSession()
+ bpy.types.Object.mn = bpy.props.PointerProperty(
+ type=props.MolecularNodesObjectProperties
+ )
+ bpy.types.Object.mn_trajectory_selections = bpy.props.CollectionProperty(
+ type=entities.trajectory.selections.TrajectorySelectionItem
+ )
- auto_load.unregister()
- del bpy.types.Object.mn
- for func in universe_funcs:
- try:
- bpy.app.handlers.load_post.remove(func)
- except ValueError as e:
- print(f"Failed to remove {func}, error: {e}.")
- except RuntimeError:
- pass
+def unregister():
+ for op in all_classes:
+ try:
+ bpy.utils.unregister_class(op)
+ except Exception:
+ # print(e)
+ pass
-# can't register the add-on when these are uncommnted, but they do fix the issue
-# of having to call register() when running a script
-# unregister()
-# register()
+ bpy.types.NODE_MT_add.remove(MN_add_node_menu)
+ bpy.types.VIEW3D_MT_object_context_menu.remove(pt_object_context)
+ bpy.types.NODE_MT_context_menu.remove(change_style_node_menu)
-# # register won't be called when MN is run as a module
-bpy.app.handlers.load_post.append(_rejuvenate_universe)
-bpy.app.handlers.load_post.append(_rehydrate_ensembles)
-bpy.app.handlers.save_post.append(_sync_universe)
+ save_post.remove(session._pickle)
+ load_post.remove(session._load)
+ frame_change_post.remove(entities.trajectory.handlers.update_trajectories)
+ del bpy.types.Scene.MNSession
+ del bpy.types.Object.mn
+ del bpy.types.Object.mn_trajectory_selections
diff --git a/molecularnodes/assets/MN_data_file.blend b/molecularnodes/assets/MN_data_file_4.2.blend
similarity index 62%
rename from molecularnodes/assets/MN_data_file.blend
rename to molecularnodes/assets/MN_data_file_4.2.blend
index 8bc3898c..412d3678 100644
Binary files a/molecularnodes/assets/MN_data_file.blend and b/molecularnodes/assets/MN_data_file_4.2.blend differ
diff --git a/molecularnodes/assets/MN_data_file_starfile.blend b/molecularnodes/assets/MN_data_file_starfile.blend
deleted file mode 100644
index f912728c..00000000
Binary files a/molecularnodes/assets/MN_data_file_starfile.blend and /dev/null differ
diff --git a/molecularnodes/assets/template/Molecular Nodes.zip b/molecularnodes/assets/template/Molecular Nodes.zip
deleted file mode 100644
index d38dc396..00000000
Binary files a/molecularnodes/assets/template/Molecular Nodes.zip and /dev/null differ
diff --git a/molecularnodes/assets/template/Molecular Nodes/startup.blend b/molecularnodes/assets/template/startup.blend
similarity index 77%
rename from molecularnodes/assets/template/Molecular Nodes/startup.blend
rename to molecularnodes/assets/template/startup.blend
index da33ff6d..7b140a1c 100644
Binary files a/molecularnodes/assets/template/Molecular Nodes/startup.blend and b/molecularnodes/assets/template/startup.blend differ
diff --git a/molecularnodes/auto_load.py b/molecularnodes/auto_load.py
deleted file mode 100644
index 72254c06..00000000
--- a/molecularnodes/auto_load.py
+++ /dev/null
@@ -1,157 +0,0 @@
-import os
-import bpy
-import sys
-import typing
-import inspect
-import pkgutil
-import importlib
-from pathlib import Path
-
-__all__ = (
- "init",
- "register",
- "unregister",
-)
-
-blender_version = bpy.app.version
-
-modules = None
-ordered_classes = None
-
-def init():
- global modules
- global ordered_classes
-
- modules = get_all_submodules(Path(__file__).parent)
- ordered_classes = get_ordered_classes_to_register(modules)
-
-def register():
- for cls in ordered_classes:
- bpy.utils.register_class(cls)
-
- for module in modules:
- if module.__name__ == __name__:
- continue
- if hasattr(module, "register"):
- module.register()
-
-def unregister():
- for cls in reversed(ordered_classes):
- bpy.utils.unregister_class(cls)
-
- for module in modules:
- if module.__name__ == __name__:
- continue
- if hasattr(module, "unregister"):
- module.unregister()
-
-
-# Import modules
-#################################################
-
-def get_all_submodules(directory):
- return list(iter_submodules(directory, directory.name))
-
-def iter_submodules(path, package_name):
- for name in sorted(iter_submodule_names(path)):
- yield importlib.import_module("." + name, package_name)
-
-def iter_submodule_names(path, root=""):
- for _, module_name, is_package in pkgutil.iter_modules([str(path)]):
- if is_package:
- sub_path = path / module_name
- sub_root = root + module_name + "."
- yield from iter_submodule_names(sub_path, sub_root)
- else:
- yield root + module_name
-
-
-# Find classes to register
-#################################################
-
-def get_ordered_classes_to_register(modules):
- return toposort(get_register_deps_dict(modules))
-
-def get_register_deps_dict(modules):
- my_classes = set(iter_my_classes(modules))
- my_classes_by_idname = {cls.bl_idname : cls for cls in my_classes if hasattr(cls, "bl_idname")}
-
- deps_dict = {}
- for cls in my_classes:
- deps_dict[cls] = set(iter_my_register_deps(cls, my_classes, my_classes_by_idname))
- return deps_dict
-
-def iter_my_register_deps(cls, my_classes, my_classes_by_idname):
- yield from iter_my_deps_from_annotations(cls, my_classes)
- yield from iter_my_deps_from_parent_id(cls, my_classes_by_idname)
-
-def iter_my_deps_from_annotations(cls, my_classes):
- for value in typing.get_type_hints(cls, {}, {}).values():
- dependency = get_dependency_from_annotation(value)
- if dependency is not None:
- if dependency in my_classes:
- yield dependency
-
-def get_dependency_from_annotation(value):
- if blender_version >= (2, 93):
- if isinstance(value, bpy.props._PropertyDeferred):
- return value.keywords.get("type")
- else:
- if isinstance(value, tuple) and len(value) == 2:
- if value[0] in (bpy.props.PointerProperty, bpy.props.CollectionProperty):
- return value[1]["type"]
- return None
-
-def iter_my_deps_from_parent_id(cls, my_classes_by_idname):
- if bpy.types.Panel in cls.__bases__:
- parent_idname = getattr(cls, "bl_parent_id", None)
- if parent_idname is not None:
- parent_cls = my_classes_by_idname.get(parent_idname)
- if parent_cls is not None:
- yield parent_cls
-
-def iter_my_classes(modules):
- base_types = get_register_base_types()
- for cls in get_classes_in_modules(modules):
- if any(base in base_types for base in cls.__bases__):
- if not getattr(cls, "is_registered", False):
- yield cls
-
-def get_classes_in_modules(modules):
- classes = set()
- for module in modules:
- for cls in iter_classes_in_module(module):
- classes.add(cls)
- return classes
-
-def iter_classes_in_module(module):
- for value in module.__dict__.values():
- if inspect.isclass(value):
- yield value
-
-def get_register_base_types():
- return set(getattr(bpy.types, name) for name in [
- "Panel", "Operator", "PropertyGroup",
- "AddonPreferences", "Header", "Menu",
- "Node", "NodeSocket", "NodeTree",
- "UIList", "RenderEngine",
- "Gizmo", "GizmoGroup",
- ])
-
-
-# Find order to register to solve dependencies
-#################################################
-
-def toposort(deps_dict):
- sorted_list = []
- sorted_values = set()
- while len(deps_dict) > 0:
- unsorted = []
- for value, deps in deps_dict.items():
- if len(deps) == 0:
- sorted_list.append(value)
- sorted_values.add(value)
- else:
- unsorted.append(value)
- deps_dict = {value : deps_dict[value] - sorted_values for value in unsorted}
- return sorted_list
diff --git a/molecularnodes/blender/bones.py b/molecularnodes/blender/bones.py
index d40e8633..d52148ea 100644
--- a/molecularnodes/blender/bones.py
+++ b/molecularnodes/blender/bones.py
@@ -1,6 +1,6 @@
import bpy
import numpy as np
-from . import obj, coll
+from . import mesh, coll
def clear_armature(object):
@@ -11,7 +11,7 @@ def clear_armature(object):
object.modifiers.remove(mod)
-def add_bones(object, name='armature'):
+def add_bones(object, name="armature"):
# creates bones and assigns correct weights
clear_armature(object)
@@ -20,27 +20,25 @@ def add_bones(object, name='armature'):
armature = create_bones(bone_positions, chain_ids)
for i in range(bone_weights.shape[1]):
- group = object.vertex_groups.new(name=f'mn_armature_{i}')
+ group = object.vertex_groups.new(name=f"mn_armature_{i}")
vertex_indices = np.where(bone_weights[:, i] == 1)[0]
- group.add(vertex_indices.tolist(), 1, 'ADD')
+ group.add(vertex_indices.tolist(), 1, "ADD")
object.select_set(True)
armature.select_set(True)
bpy.context.view_layer.objects.active = armature
- bpy.ops.object.parent_set(type='ARMATURE')
+ bpy.ops.object.parent_set(type="ARMATURE")
bpy.context.view_layer.objects.active = object
- bpy.ops.object.modifier_move_to_index(
- 'EXEC_DEFAULT', modifier="Armature", index=0)
+ bpy.ops.object.modifier_move_to_index("EXEC_DEFAULT", modifier="Armature", index=0)
return armature
def get_bone_positions(object):
-
positions, atom_name, chain_id, res_id, sec_struct = [
- obj.get_attribute(object, att)
- for att in ['position', 'atom_name', 'chain_id', 'res_id', 'sec_struct']
+ mesh.named_attribute(object, att)
+ for att in ["position", "atom_name", "chain_id", "res_id", "sec_struct"]
]
is_alpha_carbon = atom_name == 2
@@ -59,17 +57,16 @@ def get_bone_positions(object):
def get_bone_weights(object):
- print('hello world')
-
+ print("hello world")
-def create_bones(positions, chain_ids, name='armature'):
- bpy.ops.object.add(type='ARMATURE', enter_editmode=True)
+def create_bones(positions, chain_ids, name="armature"):
+ bpy.ops.object.add(type="ARMATURE", enter_editmode=True)
object = bpy.context.active_object
object.name = name
coll.armature().objects.link(object)
armature = object.data
- armature.name = f'{name}_frame'
+ armature.name = f"{name}_frame"
arm_name = armature.name
bones = []
# add bones
@@ -96,7 +93,7 @@ def create_bones(positions, chain_ids, name='armature'):
armature.edit_bones.active = armature.edit_bones[bone_a]
for bone in [bone_a, bone_b]:
armature.edit_bones[bone].select = True
- bpy.ops.armature.parent_set(type='CONNECTED')
+ bpy.ops.armature.parent_set(type="CONNECTED")
for bone in [bone_a, bone_b]:
armature.edit_bones[bone].select = False
bpy.ops.object.editmode_toggle()
@@ -105,12 +102,14 @@ def create_bones(positions, chain_ids, name='armature'):
class MN_MT_Add_Armature(bpy.types.Operator):
- bl_idname = 'mn.add_armature'
- bl_label = 'Add Armature'
- bl_description = 'Automatically add armature for each amino acid of the structure '
+ bl_idname = "mn.add_armature"
+ bl_label = "Add Armature"
+ bl_description = (
+ "Automatically add armature for each amino acid of the structure "
+ )
def execute(self, context):
object = context.active_object
add_bones(bpy.data.objects[object.name], name=object.name)
- return {'FINISHED'}
+ return {"FINISHED"}
diff --git a/molecularnodes/blender/material.py b/molecularnodes/blender/material.py
new file mode 100644
index 00000000..d34d0e4a
--- /dev/null
+++ b/molecularnodes/blender/material.py
@@ -0,0 +1,33 @@
+import bpy
+import os
+from ..utils import MN_DATA_FILE
+
+materials = [
+ "MN Default",
+ "MN Flat Outline",
+ "MN Squishy",
+ "MN Transparent Outline",
+ "MN Ambient Occlusion",
+]
+
+
+def append_material(name: str) -> bpy.types.Material:
+ mat = bpy.data.materials.get(name)
+
+ if not mat:
+ bpy.ops.wm.append(
+ directory=os.path.join(MN_DATA_FILE, "Material"),
+ filename=name,
+ link=False,
+ )
+
+ return bpy.data.materials[name]
+
+
+def add_all_materials() -> None:
+ for mat in materials:
+ append_material(mat)
+
+
+def default() -> bpy.types.Material:
+ return append_material("MN Default")
diff --git a/molecularnodes/blender/obj.py b/molecularnodes/blender/mesh.py
similarity index 77%
rename from molecularnodes/blender/obj.py
rename to molecularnodes/blender/mesh.py
index dc8e6eba..f241ef7b 100644
--- a/molecularnodes/blender/obj.py
+++ b/molecularnodes/blender/mesh.py
@@ -1,6 +1,9 @@
import bpy
import numpy as np
+from typing import Optional
+from enum import Enum
+
from . import coll
from . import nodes
from dataclasses import dataclass
@@ -16,13 +19,14 @@ class AttributeTypeInfo:
TYPES = {
key: AttributeTypeInfo(*values)
for key, values in {
- "FLOAT_VECTOR": ("vector", float, 3),
- "FLOAT_COLOR": ("color", float, 4),
- "QUATERNION": ("value", float, 4),
- "INT": ("value", int, 1),
- "FLOAT": ("value", float, 1),
- "INT32_2D": ("value", int, 2),
- "BOOLEAN": ("value", bool, 1),
+ "FLOAT_VECTOR": ("vector", float, [3]),
+ "FLOAT_COLOR": ("color", float, [4]),
+ "QUATERNION": ("value", float, [4]),
+ "INT": ("value", int, [1]),
+ "FLOAT": ("value", float, [1]),
+ "INT32_2D": ("value", int, [2]),
+ "FLOAT4X4": ("value", float, [4, 4]),
+ "BOOLEAN": ("value", bool, [1]),
}.items()
}
@@ -80,12 +84,12 @@ def new_objects(self):
list
A list of new objects.
"""
- bob_names = list([o.name for o in self.objects])
+ obj_names = list([o.name for o in self.objects])
current_objects = bpy.context.scene.objects
new_objects = []
- for bob in current_objects:
- if bob.name not in bob_names:
- new_objects.append(bob)
+ for obj in current_objects:
+ if obj.name not in obj_names:
+ new_objects.append(obj)
return new_objects
def latest(self):
@@ -149,12 +153,22 @@ def create_object(
return object
-def set_attribute(
- object: bpy.types.Object,
+class AttributeDataType(Enum):
+ FLOAT_VECTOR = "FLOAT_VECTOR"
+ FLOAT_COLOR = "FLOAT_COLOR"
+ QUATERNION = "QUATERNION"
+ FLOAT = "FLOAT"
+ INT = "INT"
+ BOOLEAN = "BOOLEAN"
+ FLOAT4X4 = "FLOAT4X4"
+
+
+def store_named_attribute(
+ obj: bpy.types.Object,
name: str,
data: np.ndarray,
- type=None,
- domain="POINT",
+ data_type: Optional[str] = None,
+ domain: str = "POINT",
overwrite: bool = True,
) -> bpy.types.Attribute:
"""
@@ -162,21 +176,20 @@ def set_attribute(
Parameters
----------
- object : bpy.types.Object
+ obj : bpy.types.Object
The Blender object.
name : str
The name of the attribute.
data : np.ndarray
The attribute data as a numpy array.
type : str, optional
- The data type of the attribute. Defaults to "FLOAT". Possbible values are (
- 'FLOAT_VECTOR', 'FLOAT_COLOR", 'QUATERNION', 'FLOAT', 'INT', 'BOOLEAN'
- )
+ The data type of the attribute. Defaults to None. Possible values are:
+ 'FLOAT_VECTOR', 'FLOAT_COLOR', 'FLOAT4X4', 'QUATERNION', 'FLOAT', 'INT', 'BOOLEAN'
domain : str, optional
- The domain of the attribute. Defaults to "POINT". Currenlty only ('POINT', 'EDGE',
- 'FACE') have been tested.
+ The domain of the attribute. Defaults to 'POINT'. Currently, only 'POINT', 'EDGE',
+ and 'FACE' have been tested.
overwrite : bool, optional
- Whether to overwrite an existing attribute with the same name. Defaults to False.
+ Whether to overwrite an existing attribute with the same name. Defaults to True.
Returns
-------
@@ -184,29 +197,39 @@ def set_attribute(
The added attribute.
"""
- dtype = data.dtype
- shape = data.shape
-
# if the datatype isn't specified, try to guess the datatype based on the
# datatype of the ndarray. This should work but ultimately won't guess between
# the quaternion and color datatype, so will just default to color
- if not type:
+ if data_type is None:
+ dtype = data.dtype
+ shape = data.shape
+
if len(shape) == 1:
- if np.issubdtype(dtype, int):
- type = "INT"
- elif np.issubdtype(dtype, float):
- type = "FLOAT"
- elif np.issubdtype(dtype, bool):
- type = "BOOL"
+ if np.issubdtype(dtype, np.int_):
+ data_type = "INT"
+ elif np.issubdtype(dtype, np.float_):
+ data_type = "FLOAT"
+ elif np.issubdtype(dtype, np.bool_):
+ data_type = "BOOLEAN"
+ elif len(shape) == 3 and shape[1:] == (4, 4):
+ data_type = "FLOAT4X4"
else:
if shape[1] == 3:
- type = "FLOAT_VECTOR"
+ data_type = "FLOAT_VECTOR"
elif shape[1] == 4:
- type == "FLOAT_COLOR"
-
- attribute = object.data.attributes.get(name)
+ data_type = "FLOAT_COLOR"
+ else:
+ data_type = "FLOAT"
+ # catch if the data_type still wasn't determined and report info about the data
+ if data_type is None:
+ data_type = "FLOAT"
+ # raise ValueError(
+ # f"Unable to determine data type for {data}, {shape=}, {dtype=}"
+ # )
+
+ attribute = obj.data.attributes.get(name) # type: ignore
if not attribute or not overwrite:
- attribute = object.data.attributes.new(name, type, domain)
+ attribute = obj.data.attributes.new(name, data_type, domain) # type: ignore
if len(data) != len(attribute.data):
raise AttributeMismatchError(
@@ -215,7 +238,7 @@ def set_attribute(
# the 'foreach_set' requires a 1D array, regardless of the shape of the attribute
# it also requires the order to be 'c' or blender might crash!!
- attribute.data.foreach_set(TYPES[type].dname, data.reshape(-1))
+ attribute.data.foreach_set(TYPES[data_type].dname, data.reshape(-1))
# The updating of data doesn't work 100% of the time (see:
# https://projects.blender.org/blender/blender/issues/118507) so this resetting of a
@@ -224,14 +247,14 @@ def set_attribute(
# is the case For now we will set a single vert to it's own position, which triggers a
# proper refresh of the object data.
try:
- object.data.vertices[0].co = object.data.vertices[0].co
+ obj.data.vertices[0].co = obj.data.vertices[0].co # type: ignore
except AttributeError:
- object.data.update()
+ obj.data.update() # type: ignore
return attribute
-def get_attribute(
+def named_attribute(
object: bpy.types.Object, name="position", evaluate=False
) -> np.ndarray:
"""
@@ -263,23 +286,26 @@ def get_attribute(
att = object.data.attributes[name]
n_att = len(att.data)
data_type = TYPES[att.data_type]
- width = data_type.width
+ dim = data_type.width
+ n_values = n_att
+ for dimension in dim:
+ n_values *= dimension
# data to and from attributes has to be given and taken as a 1D array
# we have the initialise the array first with the appropriate length, then we can
# fill it with the given data using the 'foreach_get' method which is super fast C++
# internal method
- array = np.zeros(n_att * width, dtype=data_type.dtype)
+ array = np.zeros(n_values, dtype=data_type.dtype)
# it is currently not really consistent, but to get the values you need to use one of
# the 'value', 'vector', 'color' etc from the types dict. This I could only figure
# out through trial and error. I assume this might be changed / improved in the future
att.data.foreach_get(data_type.dname, array)
- # if the attribute should be 2D, reshape it before returning the numpy array
- if width > 1:
- return array.reshape((n_att, width))
- else:
+ if dim == [1]:
return array
+ else:
+ # return an array with one row per item, even if a 1D attribute. Does this make sense?
+ return array.reshape((n_att, *dim))
def import_vdb(file: str, collection: bpy.types.Collection = None) -> bpy.types.Object:
@@ -378,6 +404,8 @@ def create_data_object(
if np.issubdtype(data.dtype, str):
data = np.unique(data, return_inverse=True)[1]
- set_attribute(object, name=column, data=data, type=type, domain="POINT")
+ store_named_attribute(
+ object, name=column, data=data, data_type=type, domain="POINT"
+ )
return object
diff --git a/molecularnodes/blender/nodes.py b/molecularnodes/blender/nodes.py
index c257f553..c9bd8df2 100644
--- a/molecularnodes/blender/nodes.py
+++ b/molecularnodes/blender/nodes.py
@@ -1,13 +1,90 @@
-import bpy
-import os
-import numpy as np
+import itertools
import math
+import os
import warnings
-import itertools
-from .. import utils
-from .. import color
-from .. import pkg
-from ..blender import obj
+from ..utils import MN_DATA_FILE
+
+from . import material
+from typing import List, Optional
+
+import time
+import bpy
+import numpy as np
+
+from .. import color, utils
+from . import mesh
+import re
+
+NODE_WIDTH = 180
+node_duplicate_pattern = r"\.\d{3}$"
+
+
+def deduplicate_node_trees(node_trees: List[str]):
+ # Compile the regex pattern for matching a suffix of a dot followed by 3 numbers
+ node_duplicate_pattern = re.compile(r"\.\d{3}$")
+ to_remove: List[bpy.types.GeometryNodeTree] = []
+
+ for node_tree in node_trees:
+ # Check if the node tree's name matches the duplicate pattern and is not a "NodeGroup"
+ for node in node_tree.nodes:
+ if not (
+ hasattr(node, "node_tree")
+ and node_duplicate_pattern.search(node.node_tree.name)
+ and "NodeGroup" not in node.node_tree.name
+ ):
+ continue
+
+ old_name = node.node_tree.name
+ # Remove the numeric suffix to get the original name
+ name_sans = old_name.rsplit(".", 1)[0]
+ replacement = bpy.data.node_groups.get(name_sans)
+ if not replacement:
+ continue
+
+ # print(f"matched {old_name} with {name_sans}")
+ node.node_tree = replacement
+ to_remove.append(bpy.data.node_groups[old_name])
+
+ for tree in to_remove:
+ try:
+ # remove the data from the blend file
+ bpy.data.node_groups.remove(tree)
+ except ReferenceError:
+ pass
+
+
+def cleanup_duplicates(purge: bool = False):
+ # Collect all node trees from node groups, excluding "NodeGroup" named ones
+ node_trees = [tree for tree in bpy.data.node_groups if "NodeGroup" not in tree.name]
+
+ # Call the deduplication function with the collected node trees
+ deduplicate_node_trees(node_trees)
+
+ if purge:
+ # Purge orphan data blocks from the file
+ bpy.ops.outliner.orphans_purge()
+
+
+class DuplicatePrevention:
+ def __init__(self, timing=False):
+ self.current_names: List[str] = []
+ self.start_time = None
+ self.timing = timing
+
+ def __enter__(self):
+ self.current_names = [tree.name for tree in bpy.data.node_groups]
+ if self.timing:
+ self.start_time = time.time()
+
+ def __exit__(self, type, value, traceback):
+ new_trees = [
+ tree for tree in bpy.data.node_groups if tree.name not in self.current_names
+ ]
+ deduplicate_node_trees(new_trees)
+ if self.timing:
+ end_time = time.time()
+ print(f"De-duplication time: {end_time - self.start_time:.2f} seconds")
+
socket_types = {
"BOOLEAN": "NodeSocketBool",
@@ -26,46 +103,25 @@
# current implemented representations
styles_mapping = {
- "presets": "MN_style_presets",
- "preset_1": "MN_style_presets",
- "preset_2": "MN_style_presets",
- "preset_3": "MN_style_presets",
- "preset_4": "MN_style_presets",
- "atoms": "MN_style_spheres",
- "spheres": "MN_style_spheres",
- "vdw": "MN_style_spheres",
- "sphere": "MN_style_spheres",
- "cartoon": "MN_style_cartoon",
- "ribbon": "MN_style_ribbon",
- "surface": "MN_style_surface",
- "ball_and_stick": "MN_style_ball_and_stick",
- "ball+stick": "MN_style_ball_and_stick",
- "stick": "MN_style_stick",
+ "preset_1": "Style Preset 1",
+ "preset_2": "Style Preset 2",
+ "preset_3": "Style Preset 3",
+ "preset_4": "Style Preset 4",
+ "atoms": "Style Spheres",
+ "spheres": "Style Spheres",
+ "vdw": "Style Spheres",
+ "sphere": "Style Spheres",
+ "cartoon": "Style Cartoon",
+ "sticks": "Style Sticks",
+ "ribbon": "Style Ribbon",
+ "surface": "Style Surface",
+ "ball_and_stick": "Style Ball and Stick",
+ "ball+stick": "Style Ball and Stick",
"oxdna": "MN_oxdna_style_ribbon",
- "density_surface": "MN_density_style_surface",
- "density_wire": "MN_density_style_wire",
+ "density_surface": "Style Density Surface",
+ "density_wire": "Style Density Wire",
}
-STYLE_ITEMS = (
- ("presets", "Presets", "A pre-made combination of different styles"),
- ("spheres", "Spheres", "Space-filling atoms style."),
- ("surface", "Surface", "Solvent-accsible surface."),
- ("cartoon", "Cartoon", "Secondary structure cartoons"),
- ("ribbon", "Ribbon", "Continuous backbone ribbon."),
- ("stick", "Stick", "Atoms and bonds as sticks between them"),
- ("ball_and_stick", "Ball and Stick", "Spheres for atoms, sticks for bonds"),
-)
-
-bpy.types.Scene.MN_import_style = bpy.props.EnumProperty(
- name="Style",
- description="Default style for importing molecules.",
- items=STYLE_ITEMS,
- default="spheres",
-)
-
-
-MN_DATA_FILE = os.path.join(pkg.ADDON_DIR, "assets", "MN_data_file.blend")
-
class NodeGroupCreationError(Exception):
def __init__(self, message):
@@ -176,11 +232,10 @@ def previous_node(node):
def style_node(group):
prev = previous_node(get_output(group))
- is_style_node = "style" in prev.name
+ is_style_node = "Style" in prev.name
while not is_style_node:
- # print(prev.name)
prev = previous_node(prev)
- is_style_node = "style" in prev.name
+ is_style_node = "Style" in prev.name
return prev
@@ -192,10 +247,10 @@ def get_style_node(object):
def star_node(group):
prev = previous_node(get_output(group))
- is_star_node = "MN_starfile_instances" in prev.name
+ is_star_node = "Starfile Instances" in prev.name
while not is_star_node:
prev = previous_node(prev)
- is_star_node = "MN_starfile_instances" in prev.name
+ is_star_node = "Starfile Instances" in prev.name
return prev
@@ -209,7 +264,7 @@ def get_color_node(object):
"Walk back through the primary node connections until you find the first style node"
group = object.modifiers["MolecularNodes"].node_group
for node in group.nodes:
- if node.name == "MN_color_attribute_random":
+ if node.name == "Color Attribute Random":
return node
@@ -230,53 +285,36 @@ def realize_instances(obj):
insert_last_node(group, realize)
+def swap(node: bpy.types.GeometryNode, new: str) -> None:
+ "Swap out the node's node_tree, while maintaining the possible old connections"
+
+ if isinstance(new, str):
+ tree = bpy.data.node_groups.get(new)
+ if not tree:
+ tree = append(new)
+ else:
+ tree = new
+
+ with MaintainConnections(node):
+ node.node_tree = tree
+ node.name = node.label = tree.name
+
+
def append(node_name, link=False):
node = bpy.data.node_groups.get(node_name)
- with warnings.catch_warnings():
- warnings.simplefilter("ignore")
- if not node or link:
- bpy.ops.wm.append(
- "EXEC_DEFAULT",
- directory=os.path.join(MN_DATA_FILE, "NodeTree"),
- filename=node_name,
- link=link,
- use_recursive=True,
- )
- node = bpy.data.node_groups.get(node_name)
- with warnings.catch_warnings():
- warnings.simplefilter("ignore")
- if not node or link:
- node_name_components = node_name.split("_")
- if node_name_components[0] == "MN":
- data_file = MN_DATA_FILE[:-6] + "_" + node_name_components[1] + ".blend"
+ if not node or link:
+ with warnings.catch_warnings():
+ warnings.simplefilter("ignore")
+ with DuplicatePrevention():
bpy.ops.wm.append(
"EXEC_DEFAULT",
- directory=os.path.join(data_file, "NodeTree"),
+ directory=os.path.join(MN_DATA_FILE, "NodeTree"),
filename=node_name,
link=link,
use_recursive=True,
)
- return bpy.data.node_groups[node_name]
-
-
-def material_default():
- """
- Append MN Default to the .blend file it it doesn't already exist,
- and return that material.
- """
-
- mat_name = "MN Default"
- mat = bpy.data.materials.get(mat_name)
- if not mat:
- print("appending material")
- bpy.ops.wm.append(
- directory=os.path.join(MN_DATA_FILE, "Material"),
- filename="MN Default",
- link=False,
- )
-
- return bpy.data.materials[mat_name]
+ return bpy.data.node_groups[node_name]
def MN_micrograph_material():
@@ -313,49 +351,28 @@ def new_group(name="Geometry Nodes", geometry=True, fallback=True):
return group
-def assign_material(node, material="default"):
+def assign_material(node, new_material="default") -> None:
+ material.add_all_materials()
material_socket = node.inputs.get("Material")
- if material_socket:
- if not material:
- pass
- elif material == "default":
- material_socket.default_value = material_default()
- else:
- material_socket.default_value = material
-
-
-def add_node(node_name, label: str = "", show_options=False, material="default"):
- # intended to be called upon button press in the node tree
-
- prev_context = bpy.context.area.type
- bpy.context.area.type = "NODE_EDITOR"
- # actually invoke the operator to add a node to the current node tree
- # use_transform=True ensures it appears where the user's mouse is and is currently
- # being moved so the user can place it where they wish
- bpy.ops.node.add_node(
- "INVOKE_DEFAULT", type="GeometryNodeGroup", use_transform=True
- )
- bpy.context.area.type = prev_context
- node = bpy.context.active_node
- node.node_tree = bpy.data.node_groups[node_name]
- node.width = 200.0
- node.show_options = show_options
+ if material_socket is None:
+ return None
- if label == "":
- node.label = format_node_name(node_name)
+ if isinstance(new_material, bpy.types.Material):
+ material_socket.default_value = new_material
+ elif new_material == "default":
+ material_socket.default_value = material.default()
else:
- node.label = label
- node.name = node_name
-
- # if added node has a 'Material' input, set it to the default MN material
- assign_material(node, material=material)
+ try:
+ material_socket.default_value = material.append_material(new_material)
+ except Exception as e:
+ print(f"Unable to use material {new_material}, error: {e}")
def add_custom(
group,
name,
location=[0, 0],
- width=200,
+ width=NODE_WIDTH,
material="default",
show_options=False,
link=False,
@@ -365,14 +382,14 @@ def add_custom(
# if there is an input socket called 'Material', assign it to the base MN material
# if another material is supplied, use that instead.
- assign_material(node, material=material)
+ assign_material(node, new_material=material)
# move and format the node for arranging
node.location = location
node.width = width
node.show_options = show_options
node.name = name
- node.label = format_node_name(name)
+ # node.label = format_node_name(name)
return node
@@ -412,9 +429,24 @@ def __exit__(self, type, value, traceback):
# rebuild the links based on names of the sockets, not their identifiers
link = self.node_tree.links.new
for input_link in self.input_links:
- link(input_link[0], self.node.inputs[input_link[1]])
+ try:
+ link(input_link[0], self.node.inputs[input_link[1]])
+ except KeyError:
+ pass
for output_link in self.output_links:
- link(self.node.outputs[output_link[0]], output_link[1])
+ try:
+ link(self.node.outputs[output_link[0]], output_link[1])
+ except KeyError:
+ pass
+
+ # reset all values to tree defaults
+ tree = self.node.node_tree
+ for item in tree.interface.items_tree:
+ if item.item_type == "PANEL":
+ continue
+ if item.in_out == "INPUT":
+ if hasattr(item, "default_value"):
+ self.node.inputs[item.identifier].default_value = item.default_value
if self.material:
try:
@@ -429,13 +461,13 @@ def swap_style_node(tree, node_style, style):
new_tree = append(styles_mapping[style])
node_style.node_tree = new_tree
node_style.name = new_tree.name
- node_style.label = format_node_name(node_style.name)
+ # node_style.label = format_node_name(node_style.name)
-def change_style_node(bob: bpy.types.Object, style: str):
+def change_style_node(obj: bpy.types.Object, style: str):
# get the node group that we are working on, to change the specific style node
- tree = get_mod(bob).node_group
- node_style = get_style_node(bob)
+ tree = get_mod(obj).node_group
+ node_style = get_style_node(obj)
swap_style_node(tree=tree, node_style=node_style, style=style)
@@ -445,8 +477,6 @@ def create_starting_nodes_starfile(object, n_images=1):
node_name = f"MN_starfile_{object.name}"
- # Make sure the aotmic material is loaded
- material_default()
# create a new GN node group, specific to this particular molecule
group = new_group(node_name)
node_mod.node_group = group
@@ -457,7 +487,7 @@ def create_starting_nodes_starfile(object, n_images=1):
node_output = get_output(group)
node_input.location = [0, 0]
node_output.location = [700, 0]
- node_star_instances = add_custom(group, "MN_starfile_instances", [450, 0])
+ node_star_instances = add_custom(group, "Starfile Instances", [450, 0])
link(node_star_instances.outputs[0], node_output.inputs[0])
link(node_input.outputs[0], node_star_instances.inputs[0])
@@ -536,10 +566,10 @@ def create_starting_node_tree(
# if requested, setup the nodes for generating colors in the node tree
if color is not None:
if color == "common":
- node_color_set = add_custom(group, "MN_color_set", [200, 0])
- node_color_common = add_custom(group, "MN_color_common", [-50, -150])
+ node_color_set = add_custom(group, "Set Color", [200, 0])
+ node_color_common = add_custom(group, "Color Common", [-50, -150])
node_random_color = add_custom(
- group, "MN_color_attribute_random", [-300, -150]
+ group, "Color Attribute Random", [-300, -150]
)
link(node_input.outputs["Geometry"], node_color_set.inputs[0])
@@ -548,8 +578,8 @@ def create_starting_node_tree(
link(node_color_set.outputs[0], node_style.inputs[0])
to_animate = node_color_set
elif color.lower() == "plddt":
- node_color_set = add_custom(group, "MN_color_set", [200, 0])
- node_color_plddt = add_custom(group, "MN_color_pLDDT", [-50, -150])
+ node_color_set = add_custom(group, "Set Color", [200, 0])
+ node_color_plddt = add_custom(group, "Color pLDDT", [-50, -150])
link(node_input.outputs["Geometry"], node_color_set.inputs["Atoms"])
link(node_color_plddt.outputs[0], node_color_set.inputs["Color"])
@@ -564,11 +594,11 @@ def create_starting_node_tree(
node_output.location = [1100, 0]
node_style.location = [800, 0]
- node_animate_frames = add_custom(group, "MN_animate_frames", [500, 0])
- node_animate = add_custom(group, "MN_animate_value", [500, -300])
+ node_animate_frames = add_custom(group, "Animate Frames", [500, 0])
+ node_animate = add_custom(group, "Animate Value", [500, -300])
node_animate_frames.inputs["Frames"].default_value = coll_frames
- node_animate.inputs["To Max"].default_value = len(coll_frames.objects) - 1
+ node_animate.inputs["Value Max"].default_value = len(coll_frames.objects) - 1
link(to_animate.outputs[0], node_animate_frames.inputs[0])
link(node_animate_frames.outputs[0], node_style.inputs[0])
@@ -628,19 +658,15 @@ def assembly_initialise(mol: bpy.types.Object):
Setup the required data object and nodes for building an assembly.
"""
- data_bob_name = f"data_assembly_{mol.name}"
+ data_obj_name = f".data_assembly_{mol.name}"
# check if a data object exists and create a new one if not
- data_object = bpy.data.objects.get(data_bob_name)
+ data_object = bpy.data.objects.get(data_obj_name)
if not data_object:
transforms = utils.array_quaternions_from_dict(mol["biological_assemblies"])
- data_object = obj.create_data_object(
- array=transforms, name=f"data_assembly_{mol.name}"
- )
+ data_object = mesh.create_data_object(array=transforms, name=data_obj_name)
- tree_assembly = create_assembly_node_tree(
- name=mol.name, iter_list=mol["chain_ids"], data_object=data_object
- )
+ tree_assembly = create_assembly_node_tree(name=mol.name, data_object=data_object)
return tree_assembly
@@ -655,27 +681,34 @@ def assembly_insert(mol: bpy.types.Object):
insert_last_node(get_mod(mol).node_group, node)
-def create_assembly_node_tree(name, iter_list, data_object):
- node_group_name = f"MN_assembly_{name}"
+def create_assembly_node_tree(
+ name: str, data_object: bpy.types.Object
+) -> bpy.types.NodeTree:
+ node_group_name = f"Assembly {name}"
existing_node_tree = bpy.data.node_groups.get(node_group_name)
if existing_node_tree:
return existing_node_tree
- group = new_group(name=node_group_name)
- link = group.links.new
-
- n_assemblies = len(np.unique(obj.get_attribute(data_object, "assembly_id")))
+ tree: bpy.types.NodeTree = new_group(name=node_group_name)
+ link = tree.links.new
- node_group_instances = split_geometry_to_instances(
- name=f".MN_utils_split_{name}", iter_list=iter_list, attribute="chain_id"
- )
+ node_split: bpy.types.GeometryNodeSplitToInstances = tree.nodes.new(
+ "GeometryNodeSplitToInstances"
+ ) # type: ignore
+ node_split.location = [-150, 0]
+ node_att: bpy.types.GeometryNodeInputNamedAttribute = tree.nodes.new(
+ "GeometryNodeInputNamedAttribute"
+ ) # type: ignore
+ node_att.data_type = "INT"
+ node_att.inputs[0].default_value = "chain_id"
+ node_att.location = [-150, -200]
+ link(node_att.outputs["Attribute"], node_split.inputs["Group ID"])
node_group_assembly_instance = append(".MN_assembly_instance_chains")
- node_instances = add_custom(group, node_group_instances.name, [0, 0])
- node_assembly = add_custom(group, node_group_assembly_instance.name, [200, 0])
+ node_assembly = add_custom(tree, node_group_assembly_instance.name, [150, 0])
node_assembly.inputs["data_object"].default_value = data_object
- out_sockets = outputs(group)
+ out_sockets = outputs(tree)
out_sockets[list(out_sockets)[0]].name = "Instances"
socket_info = (
@@ -697,29 +730,30 @@ def create_assembly_node_tree(name, iter_list, data_object):
"name": "assembly_id",
"type": "NodeSocketInt",
"min": 1,
- "max": n_assemblies,
+ "max": max(mesh.named_attribute(data_object, "assembly_id")),
"default": 1,
},
)
for info in socket_info:
- socket = group.interface.items_tree.get(info["name"])
+ socket = tree.interface.items_tree.get(info["name"])
if not socket:
- socket = group.interface.new_socket(
+ socket: bpy.types.NodeTreeInterfaceSocket = tree.interface.new_socket(
info["name"], in_out="INPUT", socket_type=info["type"]
)
socket.default_value = info["default"]
socket.min_value = info["min"]
socket.max_value = info["max"]
- link(get_input(group).outputs[info["name"]], node_assembly.inputs[info["name"]])
+ link(get_input(tree).outputs[info["name"]], node_assembly.inputs[info["name"]])
- get_output(group).location = [400, 0]
- link(get_input(group).outputs[0], node_instances.inputs[0])
- link(node_instances.outputs[0], node_assembly.inputs[0])
- link(node_assembly.outputs[0], get_output(group).inputs[0])
-
- return group
+ get_output(tree).location = [400, 0]
+ link(get_input(tree).outputs[0], node_split.inputs[0])
+ link(node_split.outputs[0], node_assembly.inputs[0])
+ link(node_assembly.outputs[0], get_output(tree).inputs[0])
+ if hasattr(tree, "color_tag"):
+ tree.color_tag = "GEOMETRY"
+ return tree
def add_inverse_selection(group):
@@ -740,9 +774,7 @@ def add_inverse_selection(group):
group.links.new(bool_math.outputs[0], output.inputs["Inverted"])
-def boolean_link_output(
- tree: bpy.types.GeometryNodeTree, node: bpy.types.GeometryNode
-) -> None:
+def boolean_link_output(tree: bpy.types.NodeTree, node: bpy.types.Node) -> None:
link = tree.links.new
node_output = get_output(tree)
tree.interface.new_socket(
@@ -753,28 +785,35 @@ def boolean_link_output(
)
final_output = node.outputs[0]
link(final_output, node_output.inputs["Selection"])
- node_invert = tree.nodes.new("FunctionNodeBooleanMath")
+ node_invert: bpy.types.FunctionNodeBooleanMath = tree.nodes.new(
+ "FunctionNodeBooleanMath"
+ ) # type: ignore
+
node_invert.operation = "NOT"
- node_invert.location = np.array(node_output.location) - 200
+ node_invert.location = (np.array(node_output.location) - [0, 200]).tolist()
link(final_output, node_invert.inputs[0])
link(node_invert.outputs[0], node_output.inputs["Inverted"])
def custom_iswitch(
- name,
+ name: str,
iter_list,
- field="chain_id",
- dtype="BOOLEAN",
+ field: str = "chain_id",
+ dtype: str = "BOOLEAN",
default_values=None,
- prefix="",
- start=0,
+ prefix: str = "",
+ start: int = 0,
+ offset: int = 0,
+ panels: Optional[List[str]] = None,
+ panels_open: int = 1,
):
"""
Creates a named `Index Switch` node.
- Wraps an index switch node, giving the group names or each name in the `iter_list`.
- Uses the given field for the attribute name to use in the index switch, and optionally
- adds an offset value if the start value is non zero.
+ Wraps an index switch node, giving the group names or each name in the `iter_list`. The
+ inputs can also be placed in subpanels and given specific default values. Uses the
+ given field for the attribute name to use in the index switch, and optionally adds an
+ offset value if the start value is non zero.
If a list of default items is given, then it is recycled to fill the defaults for
each created socket in for the node.
@@ -789,6 +828,16 @@ def custom_iswitch(
The name of the attribute field. Defaults to 'chain_id'.
default_values : list, optional
The list of default values to assign to each item. Defaults to None.
+ panels : list, str
+ List of panel names for the sockets to be assigned to. If None, then socket will
+ not be assigned to the panel. The will appear in the panel in the order in which
+ they are given.
+ panels_open: int
+ Number of panels to default to open. If `0` then all panels will be closed. Useful
+ for larger panel node groups, to keep them closed and help with organisation. A
+ list of panel names can also be given to optionally categorise the sockets into
+ panels in the final group node. The length of the panels list must match the length
+ of the iter_list. `None` values mean the socket is not placed in a panel.
prefix : str, optional
The prefix to add to the node names. Defaults to an empty string.
start : int, optional
@@ -805,25 +854,27 @@ def custom_iswitch(
If there was an error creating the node group.
"""
iter_list = [str(i) for i in iter_list]
- group = bpy.data.node_groups.get(name)
- if group:
- return group
+ tree = bpy.data.node_groups.get(name)
+ if tree:
+ return tree
socket_type = socket_types[dtype]
- group = new_group(name, geometry=False, fallback=False)
+ tree = new_group(name, geometry=False, fallback=False)
# try creating the node group, otherwise on fail cleanup the created group and
# report the error
try:
- link = group.links.new
- node_input = get_input(group)
- node_output = get_output(group)
- node_attr = group.nodes.new("GeometryNodeInputNamedAttribute")
+ link = tree.links.new
+ node_input = get_input(tree)
+ node_output = get_output(tree)
+ node_attr = tree.nodes.new("GeometryNodeInputNamedAttribute")
node_attr.data_type = "INT"
node_attr.location = [0, 150]
node_attr.inputs["Name"].default_value = str(field)
- node_iswitch = group.nodes.new("GeometryNodeIndexSwitch")
+ node_iswitch: bpy.types.GeometryNodeIndexSwitch = tree.nodes.new( # type: ignore
+ "GeometryNodeIndexSwitch"
+ )
node_iswitch.data_type = dtype
link(node_attr.outputs["Attribute"], node_iswitch.inputs["Index"])
@@ -831,7 +882,7 @@ def custom_iswitch(
# if there is as offset to the lookup values (say we want to start looking up
# from 100 or 1000 etc) then we add a math node with that offset value
if start != 0:
- node_math = group.nodes.new("ShaderNodeMath")
+ node_math = tree.nodes.new("ShaderNodeMath")
node_math.operation = "ADD"
node_math.location = [0, 150]
node_attr.location = [0, 300]
@@ -844,7 +895,7 @@ def custom_iswitch(
# to assign to the sockets upon creation. If no default was given and the dtype
# is colors, then generate a random pastel color for each value
default_lookup = None
- if default_values:
+ if default_values is not None:
default_lookup = dict(zip(iter_list, itertools.cycle(default_values)))
elif dtype == "RGBA":
default_lookup = dict(
@@ -855,24 +906,62 @@ def custom_iswitch(
# node group, and link it to the interface on the index switch. The index switch
# currently starts with two items already, so once i > 1 we start to add
# new items for the index switch as well
+ panel_item_counter = 0
+ panel_counter = 0
+ for j in range(offset):
+ node_iswitch.index_switch_items.new()
for i, item in enumerate(iter_list):
if i > 1:
node_iswitch.index_switch_items.new()
- socket = group.interface.new_socket(
+ # The offset creates but skips itmes on the index switch node.
+ # if we offset by 1 then we can index from 1 essentially, for attributes like
+ # the atomic_number
+
+ socket = tree.interface.new_socket(
name=f"{prefix}{item}", in_out="INPUT", socket_type=socket_type
)
# if a set of default values was given, then use it for setting
# the defaults on the created sockets of the node group
if default_lookup:
socket.default_value = default_lookup[item]
+ link(
+ node_input.outputs[socket.identifier],
+ node_iswitch.inputs[str(i + offset)],
+ )
- link(node_input.outputs[socket.identifier], node_iswitch.inputs[str(i)])
+ # if a list of panel names has been passed in, then we use it to
+ # assign all of the interface sockets to the panels
+ if panels:
+ pname = panels[i]
+ if pname is not None:
+ # try and get an existing panel, if None is returned we have to create
+ # a panel with the given name
+ panel: bpy.types.NodeTreeInterfacePanel = (
+ tree.interface.items_tree.get(pname)
+ )
+ if not panel:
+ panel_item_counter = 0
+ panel = tree.interface.new_panel(name=pname)
+ panel_counter += 1
+ # we can set a certain number of panels to be open when created.
+ # a value of 0 means all created panels will be closed on creation.
+ # larger cutoffs will mean that n number of panels will be open by
+ # default
+ if panel_counter >= panels_open:
+ panel.default_closed = True
+
+ tree.interface.move_to_parent(
+ socket, panel, to_position=panel_item_counter + 1
+ )
+ panel_item_counter += 1
if dtype == "BOOLEAN":
- boolean_link_output(group, node_iswitch)
+ tree.color_tag = "INPUT"
+ boolean_link_output(tree, node_iswitch)
elif dtype == "RGBA":
- socket_out = group.interface.new_socket(
+ tree.color_tag = "COLOR"
+ socket_out = tree.interface.new_socket(
name="Color", in_out="OUTPUT", socket_type=socket_type
)
link(
@@ -882,12 +971,12 @@ def custom_iswitch(
else:
raise ValueError(f"Unsupported value typee for custom iswitch: {dtype}")
- return group
+ return tree
# if something broke when creating the node group, delete whatever was created
except Exception as e:
- node_name = group.name
- bpy.data.node_groups.remove(group)
+ node_name = tree.name
+ bpy.data.node_groups.remove(tree)
raise NodeGroupCreationError(
f"Unable to make node group: {node_name}.\nError: {e}"
)
@@ -901,7 +990,6 @@ def resid_multiple_selection(node_name, input_resid_string):
selections in specific proteins.
"""
- # print(f'recieved input: {input_resid_string}')
# do a cleanning of input string to allow fuzzy input from users
for c in ";/+ .":
if c in input_resid_string:
@@ -911,8 +999,6 @@ def resid_multiple_selection(node_name, input_resid_string):
if c in input_resid_string:
input_resid_string = input_resid_string.replace(c, "-")
- # print(f'fixed input:{input_resid_string}')
-
# parse input_resid_string into sub selecting string list
sub_list = [item for item in input_resid_string.split(",") if item]
@@ -942,8 +1028,9 @@ def resid_multiple_selection(node_name, input_resid_string):
bool_math.operation = "OR"
if "-" in residue_id:
- # set two new inputs
- current_node.node_tree = append("MN_select_res_id_range")
+ # selecting a range of residues by using the Res ID Range node and connecting
+ # to the min and max of those nodes
+ current_node.node_tree = append("Select Res ID Range")
[resid_start, resid_end] = residue_id.split("-")[:2]
socket_1 = residue_id_group.interface.new_socket(
"res_id: Min", in_out="INPUT", socket_type="NodeSocketInt"
@@ -955,16 +1042,23 @@ def resid_multiple_selection(node_name, input_resid_string):
socket_2.default_value = int(resid_end)
# a residue range
- group_link(node_input.outputs[socket_1.identifier], current_node.inputs[0])
- group_link(node_input.outputs[socket_2.identifier], current_node.inputs[1])
+ group_link(
+ node_input.outputs[socket_1.identifier], current_node.inputs["Min"]
+ )
+ group_link(
+ node_input.outputs[socket_2.identifier], current_node.inputs["Max"]
+ )
else:
- # create a node
- current_node.node_tree = append("MN_select_res_id_single")
+ # Selecting singular res ID numbers by creating the socket and adding a node
+ # ensuring that we are connecting to the right node
+ current_node.node_tree = append("Select Res ID")
socket = residue_id_group.interface.new_socket(
"res_id", in_out="INPUT", socket_type="NodeSocketInt"
)
socket.default_value = int(residue_id)
- group_link(node_input.outputs[socket.identifier], current_node.inputs[0])
+ group_link(
+ node_input.outputs[socket.identifier], current_node.inputs["Res ID"]
+ )
# set the coordinates
current_node.location = [200, (residue_id_index + 1) * node_sep_dis]
diff --git a/molecularnodes/blender_manifest.toml b/molecularnodes/blender_manifest.toml
new file mode 100644
index 00000000..ead63671
--- /dev/null
+++ b/molecularnodes/blender_manifest.toml
@@ -0,0 +1,92 @@
+schema_version = "1.0.0"
+
+id = "molecularnodes"
+version = "4.2.3"
+name = "Molecular Nodes"
+tagline = "A toolbox for molecular import and animation in Blender"
+maintainer = "Brady Johnston"
+type = "add-on"
+website = "https://bradyajohnston.github.io/MolecularNodes"
+platforms = [
+ "windows-x64",
+ "linux-x64",
+ "macos-arm64",
+ "macos-x64",
+]
+tags = [
+ "Geometry Nodes",
+ "Import-Export"
+]
+blender_version_min = "4.2.0"
+license = [
+ "SPDX:MIT"
+]
+copyright =[
+ "2022-2024 Brady Johnston",
+]
+
+wheels = [
+ "./wheels/GridDataFormats-1.0.2-py3-none-any.whl",
+ "./wheels/MDAnalysis-2.7.0-cp311-cp311-macosx_10_9_x86_64.whl",
+ "./wheels/MDAnalysis-2.7.0-cp311-cp311-macosx_11_0_arm64.whl",
+ "./wheels/MDAnalysis-2.7.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
+ "./wheels/MDAnalysis-2.7.0-cp311-cp311-win_amd64.whl",
+ "./wheels/biotite-0.41.2-cp311-cp311-macosx_10_9_x86_64.whl",
+ "./wheels/biotite-0.41.2-cp311-cp311-macosx_11_0_arm64.whl",
+ "./wheels/biotite-0.41.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
+ "./wheels/biotite-0.41.2-cp311-cp311-win_amd64.whl",
+ "./wheels/colorama-0.4.6-py2.py3-none-any.whl",
+ "./wheels/contourpy-1.2.1-cp311-cp311-macosx_10_9_x86_64.whl",
+ "./wheels/contourpy-1.2.1-cp311-cp311-macosx_11_0_arm64.whl",
+ "./wheels/contourpy-1.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
+ "./wheels/contourpy-1.2.1-cp311-cp311-win_amd64.whl",
+ "./wheels/cycler-0.12.1-py3-none-any.whl",
+ "./wheels/fasteners-0.19-py3-none-any.whl",
+ "./wheels/fonttools-4.53.1-cp311-cp311-macosx_10_9_universal2.whl",
+ "./wheels/fonttools-4.53.1-cp311-cp311-macosx_11_0_arm64.whl",
+ "./wheels/fonttools-4.53.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
+ "./wheels/fonttools-4.53.1-cp311-cp311-win_amd64.whl",
+ "./wheels/joblib-1.4.2-py3-none-any.whl",
+ "./wheels/kiwisolver-1.4.5-cp311-cp311-macosx_10_9_x86_64.whl",
+ "./wheels/kiwisolver-1.4.5-cp311-cp311-macosx_11_0_arm64.whl",
+ "./wheels/kiwisolver-1.4.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
+ "./wheels/kiwisolver-1.4.5-cp311-cp311-win_amd64.whl",
+ "./wheels/matplotlib-3.9.1-cp311-cp311-macosx_10_12_x86_64.whl",
+ "./wheels/matplotlib-3.9.1-cp311-cp311-macosx_11_0_arm64.whl",
+ "./wheels/matplotlib-3.9.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
+ "./wheels/matplotlib-3.9.1-cp311-cp311-win_amd64.whl",
+ "./wheels/mda_xdrlib-0.2.0-py3-none-any.whl",
+ "./wheels/mmtf_python-1.1.3-py2.py3-none-any.whl",
+ "./wheels/mrcfile-1.4.3-py2.py3-none-any.whl",
+ "./wheels/msgpack-1.0.8-cp311-cp311-macosx_10_9_x86_64.whl",
+ "./wheels/msgpack-1.0.8-cp311-cp311-macosx_11_0_arm64.whl",
+ "./wheels/msgpack-1.0.8-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
+ "./wheels/msgpack-1.0.8-cp311-cp311-win_amd64.whl",
+ "./wheels/networkx-3.3-py3-none-any.whl",
+ "./wheels/packaging-24.1-py3-none-any.whl",
+ "./wheels/pandas-2.2.2-cp311-cp311-macosx_10_9_x86_64.whl",
+ "./wheels/pandas-2.2.2-cp311-cp311-macosx_11_0_arm64.whl",
+ "./wheels/pandas-2.2.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
+ "./wheels/pandas-2.2.2-cp311-cp311-win_amd64.whl",
+ "./wheels/pillow-10.4.0-cp311-cp311-macosx_10_10_x86_64.whl",
+ "./wheels/pillow-10.4.0-cp311-cp311-macosx_11_0_arm64.whl",
+ "./wheels/pillow-10.4.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
+ "./wheels/pillow-10.4.0-cp311-cp311-win_amd64.whl",
+ "./wheels/pyparsing-3.1.2-py3-none-any.whl",
+ "./wheels/python_dateutil-2.9.0.post0-py2.py3-none-any.whl",
+ "./wheels/pytz-2024.1-py2.py3-none-any.whl",
+ "./wheels/scipy-1.14.0-cp311-cp311-macosx_10_9_x86_64.whl",
+ "./wheels/scipy-1.14.0-cp311-cp311-macosx_12_0_arm64.whl",
+ "./wheels/scipy-1.14.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
+ "./wheels/scipy-1.14.0-cp311-cp311-win_amd64.whl",
+ "./wheels/six-1.16.0-py2.py3-none-any.whl",
+ "./wheels/starfile-0.5.6-py3-none-any.whl",
+ "./wheels/threadpoolctl-3.5.0-py3-none-any.whl",
+ "./wheels/tqdm-4.66.4-py3-none-any.whl",
+ "./wheels/typing_extensions-4.12.2-py3-none-any.whl",
+ "./wheels/tzdata-2024.1-py2.py3-none-any.whl",
+]
+
+[permissions]
+network = "Downloading structural data from the PDB and AFPDB"
+files = "Importing data files from disk and caching downloads"
diff --git a/molecularnodes/color.py b/molecularnodes/color.py
index ce14c611..023f69ab 100644
--- a/molecularnodes/color.py
+++ b/molecularnodes/color.py
@@ -1,5 +1,6 @@
-import random
import colorsys
+import random
+
import numpy as np
import numpy.typing as npt
@@ -34,6 +35,11 @@ def color_from_atomic_number(atomic_number: int):
return np.array((r, g, b, 1))
+def color_from_element(element: str):
+ r, g, b = [x / 255 for x in iupac_colors_rgb[element]]
+ return np.array((r, g, b, 1))
+
+
def colors_from_elements(atomic_numbers):
colors = np.array(list(map(color_from_atomic_number, atomic_numbers)))
return colors
diff --git a/molecularnodes/io/retrieve.py b/molecularnodes/download.py
similarity index 84%
rename from molecularnodes/io/retrieve.py
rename to molecularnodes/download.py
index 18d57bcf..98dadd32 100644
--- a/molecularnodes/io/retrieve.py
+++ b/molecularnodes/download.py
@@ -1,6 +1,17 @@
+import io
import os
+from pathlib import Path
import requests
-import io
+
+CACHE_OLD = str(Path("~", ".MolecularNodes").expanduser())
+CACHE_DIR = str(Path("~", "MolecularNodesCache").expanduser())
+
+# rename old cache directories if users have them so we aren't leaving cached files in
+# hidden folders on disk somewhere, I don't like the idea of silently renaming folders
+# on a user's disk on load, so for now this will be disabled.
+# TODO: make a decision on this (maybe a conformation popup on download)
+# if os.path.exists(CACHE_OLD):
+# os.rename(CACHE_OLD, CACHE_DIR)
class FileDownloadPDBError(Exception):
@@ -19,7 +30,7 @@ def __init__(
super().__init__(self.message)
-def download(code, format="cif", cache=None, database="rcsb"):
+def download(code, format="cif", cache=CACHE_DIR, database="rcsb"):
"""
Downloads a structure from the specified protein data bank in the given format.
@@ -31,7 +42,7 @@ def download(code, format="cif", cache=None, database="rcsb"):
The format of the file. Defaults to "cif". Possible values are ['cif', 'pdb',
'mmcif', 'pdbx', 'bcif'].
cache : str, optional
- The cache directory to store the fetched file. Defaults to None.
+ The cache directory to store the fetched file. Defaults to `~/MolecularNodesCache`.
database : str, optional
The database to fetch the file from. Defaults to 'rcsb'.
diff --git a/molecularnodes/entities/__init__.py b/molecularnodes/entities/__init__.py
new file mode 100644
index 00000000..58128dfb
--- /dev/null
+++ b/molecularnodes/entities/__init__.py
@@ -0,0 +1,23 @@
+from . import molecule, trajectory
+from .density import MN_OT_Import_Map
+from .trajectory.dna import MN_OT_Import_OxDNA_Trajectory
+from .ensemble.cellpack import CellPack
+from .ensemble.star import StarFile
+from .ensemble.ui import MN_OT_Import_Cell_Pack, MN_OT_Import_Star_File
+from .molecule.pdb import PDB
+from .molecule.pdbx import BCIF, CIF
+from .molecule.sdf import SDF
+from .molecule.ui import MN_OT_Import_wwPDB, fetch, load_local
+from .trajectory.trajectory import Trajectory
+
+CLASSES = (
+ [
+ MN_OT_Import_Cell_Pack,
+ MN_OT_Import_Map,
+ MN_OT_Import_OxDNA_Trajectory,
+ MN_OT_Import_Star_File,
+ MN_OT_Import_wwPDB,
+ ]
+ + trajectory.CLASSES
+ + molecule.CLASSES
+)
diff --git a/molecularnodes/entities/density/__init__.py b/molecularnodes/entities/density/__init__.py
new file mode 100644
index 00000000..78eebcbc
--- /dev/null
+++ b/molecularnodes/entities/density/__init__.py
@@ -0,0 +1 @@
+from .ui import MN_OT_Import_Map, load
diff --git a/molecularnodes/io/parse/density.py b/molecularnodes/entities/density/density.py
similarity index 100%
rename from molecularnodes/io/parse/density.py
rename to molecularnodes/entities/density/density.py
diff --git a/molecularnodes/io/parse/mrc.py b/molecularnodes/entities/density/mrc.py
similarity index 97%
rename from molecularnodes/io/parse/mrc.py
rename to molecularnodes/entities/density/mrc.py
index 9218a71e..98296f31 100644
--- a/molecularnodes/io/parse/mrc.py
+++ b/molecularnodes/entities/density/mrc.py
@@ -1,6 +1,7 @@
from .density import Density
-from ...blender import coll, obj, nodes
+import mrcfile
+from ...blender import coll, mesh, nodes
import bpy
import numpy as np
import os
@@ -21,7 +22,7 @@ def __init__(self, file_path, center=False, invert=False, overwrite=False):
self.file_path, center=center, invert=invert, overwrite=overwrite
)
- def create_model(
+ def create_object(
self, name="NewDensity", style="density_surface", setup_nodes=True
) -> bpy.types.Object:
"""
@@ -41,7 +42,7 @@ def create_model(
"""
# import and ensure object is at world origin to get corect alignment with
# structures
- object = obj.import_vdb(self.file_vdb, collection=coll.mn())
+ object = mesh.import_vdb(self.file_vdb, collection=coll.mn())
object.location = (0, 0, 0)
self.object = object
object.mn["molecule_type"] = "density"
@@ -148,7 +149,7 @@ def map_to_grid(self, file: str, invert: bool = False, center: bool = False):
pyopenvdb.FloatGrid
A pyopenvdb FloatGrid object containing the density data.
"""
- import mrcfile
+
import pyopenvdb as vdb
volume = mrcfile.read(file)
diff --git a/molecularnodes/io/density.py b/molecularnodes/entities/density/ui.py
similarity index 94%
rename from molecularnodes/io/density.py
rename to molecularnodes/entities/density/ui.py
index dd18976a..a43d3cd6 100644
--- a/molecularnodes/io/density.py
+++ b/molecularnodes/entities/density/ui.py
@@ -1,5 +1,5 @@
import bpy
-from . import parse
+from .mrc import MRC
bpy.types.Scene.MN_import_density_invert = bpy.props.BoolProperty(
name="Invert Data",
@@ -52,10 +52,10 @@ def load(
center: bool = False,
overwrite: bool = False,
):
- density = parse.MRC(
+ density = MRC(
file_path=file_path, center=center, invert=invert, overwrite=overwrite
)
- density.create_model(name=name, setup_nodes=setup_nodes, style=style)
+ density.create_object(name=name, setup_nodes=setup_nodes, style=style)
return density
@@ -65,10 +65,6 @@ class MN_OT_Import_Map(bpy.types.Operator):
bl_description = "Import a EM density map into Blender"
bl_options = {"REGISTER"}
- @classmethod
- def poll(cls, context):
- return True
-
def execute(self, context):
scene = context.scene
load(
diff --git a/molecularnodes/entities/ensemble/__init__.py b/molecularnodes/entities/ensemble/__init__.py
new file mode 100644
index 00000000..5937f6d1
--- /dev/null
+++ b/molecularnodes/entities/ensemble/__init__.py
@@ -0,0 +1 @@
+from .ui import load_starfile, load_cellpack
diff --git a/molecularnodes/io/parse/bcif.py b/molecularnodes/entities/ensemble/bcif.py
similarity index 81%
rename from molecularnodes/io/parse/bcif.py
rename to molecularnodes/entities/ensemble/bcif.py
index f99fe954..5aa162ae 100644
--- a/molecularnodes/io/parse/bcif.py
+++ b/molecularnodes/entities/ensemble/bcif.py
@@ -1,6 +1,7 @@
import numpy as np
from mathutils import Matrix
from typing import Any, Dict, List, Optional, TypedDict, Union
+from biotite.structure import AtomArray
class BCIF:
@@ -33,17 +34,15 @@ def _chain_ids(self, as_int=False):
def _atom_array_from_bcif(open_bcif):
- from biotite.structure import AtomArray
-
categories = open_bcif.data_blocks[0]
# check if a petworld CellPack model or not
is_petworld = False
- if 'PDB_model_num' in categories['pdbx_struct_assembly_gen'].field_names:
- print('PetWorld!')
+ if "PDB_model_num" in categories["pdbx_struct_assembly_gen"].field_names:
+ print("PetWorld!")
is_petworld = True
- atom_site = categories['atom_site']
+ atom_site = categories["atom_site"]
n_atoms = atom_site.row_count
# Initialise the atom array that will contain all of the data for the atoms
@@ -51,32 +50,36 @@ def _atom_array_from_bcif(open_bcif):
# we first pull out the coordinates as they are from 3 different fields, but all
# other fields should be single self-contained fields
mol = AtomArray(n_atoms)
- coord_field_names = [f'Cartn_{axis}' for axis in 'xyz']
- mol.coord = np.hstack(list([
- np.array(atom_site[column]).reshape((n_atoms, 1)) for column in coord_field_names
- ]))
+ coord_field_names = [f"Cartn_{axis}" for axis in "xyz"]
+ mol.coord = np.hstack(
+ list(
+ [
+ np.array(atom_site[column]).reshape((n_atoms, 1))
+ for column in coord_field_names
+ ]
+ )
+ )
# the list of current
atom_site_lookup = {
-
# have to make sure the chain_id ends up being the same as the space operatore
- 'label_asym_id': 'chain_id',
- 'label_atom_id': 'atom_name',
- 'label_comp_id': 'res_name',
- 'type_symbol': 'element',
- 'label_seq_id': 'res_id',
- 'B_iso_or_equiv': 'b_factor',
- 'label_entity_id': 'entity_id',
- 'pdbx_PDB_model_num': 'model_id',
- 'pdbx_formal_charge': 'charge',
- 'occupancy': 'occupany',
- 'id': 'atom_id'
+ "label_asym_id": "chain_id",
+ "label_atom_id": "atom_name",
+ "label_comp_id": "res_name",
+ "type_symbol": "element",
+ "label_seq_id": "res_id",
+ "B_iso_or_equiv": "b_factor",
+ "label_entity_id": "entity_id",
+ "pdbx_PDB_model_num": "model_id",
+ "pdbx_formal_charge": "charge",
+ "occupancy": "occupany",
+ "id": "atom_id",
}
if is_petworld:
# annotations[0][1] = 'pdbx_PDB_model_num'
- atom_site_lookup.pop('label_asym_id')
- atom_site_lookup['pdbx_PDB_model_num'] = 'chain_id'
+ atom_site_lookup.pop("label_asym_id")
+ atom_site_lookup["pdbx_PDB_model_num"] = "chain_id"
for name in atom_site.field_names:
# the coordinates have already been extracted so we can skip over those field names
@@ -95,10 +98,8 @@ def _atom_array_from_bcif(open_bcif):
# TODO this could be expanded to capture fields that are entirely '' and drop them
# or fill them with 0s
- if annotation_name == 'res_id' and data[0] == '':
- data = np.array([
- 0 if x == '' else x for x in data
- ])
+ if annotation_name == "res_id" and data[0] == "":
+ data = np.array([0 if x == "" else x for x in data])
mol.set_annotation(annotation_name, data)
@@ -115,42 +116,43 @@ def rotation_from_matrix(matrix):
def _get_ops_from_bcif(open_bcif):
is_petworld = False
cats = open_bcif.data_blocks[0]
- assembly_gen = cats['pdbx_struct_assembly_gen']
+ assembly_gen = cats["pdbx_struct_assembly_gen"]
gen_arr = np.column_stack(
- list([assembly_gen[name] for name in assembly_gen.field_names]))
+ list([assembly_gen[name] for name in assembly_gen.field_names])
+ )
dtype = [
- ('assembly_id', int),
- ('chain_id', 'U10'),
- ('trans_id', int),
- ('rotation', float, 4), # quaternion form rotations
- ('translation', float, 3)
+ ("assembly_id", int),
+ ("chain_id", "U10"),
+ ("trans_id", int),
+ ("rotation", float, 4), # quaternion form rotations
+ ("translation", float, 3),
]
- ops = cats['pdbx_struct_oper_list']
+ ops = cats["pdbx_struct_oper_list"]
ok_names = [
- 'matrix[1][1]',
- 'matrix[1][2]',
- 'matrix[1][3]',
- 'matrix[2][1]',
- 'matrix[2][2]',
- 'matrix[2][3]',
- 'matrix[3][1]',
- 'matrix[3][2]',
- 'matrix[3][3]',
- 'vector[1]',
- 'vector[2]',
- 'vector[3]'
+ "matrix[1][1]",
+ "matrix[1][2]",
+ "matrix[1][3]",
+ "matrix[2][1]",
+ "matrix[2][2]",
+ "matrix[2][3]",
+ "matrix[3][1]",
+ "matrix[3][2]",
+ "matrix[3][3]",
+ "vector[1]",
+ "vector[2]",
+ "vector[3]",
]
# test if petworld
- if 'PDB_model_num' in assembly_gen.field_names:
- print('PetWorld!')
+ if "PDB_model_num" in assembly_gen.field_names:
+ print("PetWorld!")
is_petworld = True
- op_ids = np.array(ops['id'])
- struct_ops = np.column_stack(list([
- np.array(ops[name]).reshape((ops.row_count, 1)) for name in ok_names
- ]))
- rotations = np.array(list([
- rotation_from_matrix(x[0:9].reshape((3, 3))) for x in struct_ops
- ]))
+ op_ids = np.array(ops["id"])
+ struct_ops = np.column_stack(
+ list([np.array(ops[name]).reshape((ops.row_count, 1)) for name in ok_names])
+ )
+ rotations = np.array(
+ list([rotation_from_matrix(x[0:9].reshape((3, 3))) for x in struct_ops])
+ )
translations = struct_ops[:, 9:12]
gen_list = []
@@ -160,31 +162,29 @@ def _get_ops_from_bcif(open_bcif):
if "," in gen[1]:
for gexpr in gen[1].split(","):
if "-" in gexpr:
- start, end = [int(x)
- for x in gexpr.strip('()').split('-')]
+ start, end = [int(x) for x in gexpr.strip("()").split("-")]
ids.extend((np.array(range(start, end + 1))).tolist())
else:
- ids.append(int(gexpr.strip('()')))
+ ids.append(int(gexpr.strip("()")))
else:
- start, end = [int(x) for x in gen[1].strip('()').split('-')]
+ start, end = [int(x) for x in gen[1].strip("()").split("-")]
ids.extend((np.array(range(start, end + 1))).tolist())
else:
- ids = np.array([int(x)
- for x in gen[1].strip("()").split(",")]).tolist()
+ ids = np.array([int(x) for x in gen[1].strip("()").split(",")]).tolist()
real_ids = np.nonzero(np.in1d(op_ids, ids))[0]
- chains = np.array(gen[2].strip(' ').split(','))
+ chains = np.array(gen[2].strip(" ").split(","))
if is_petworld:
# all chain of the model receive theses transformation
chains = np.array([gen[3]])
arr = np.zeros(chains.size * len(real_ids), dtype=dtype)
- arr['chain_id'] = np.tile(chains, len(real_ids))
+ arr["chain_id"] = np.tile(chains, len(real_ids))
mask = np.repeat(np.array(real_ids), len(chains))
try:
- arr['trans_id'] = gen[3]
+ arr["trans_id"] = gen[3]
except IndexError:
pass
- arr['rotation'] = rotations[mask, :]
- arr['translation'] = translations[mask, :]
+ arr["rotation"] = rotations[mask, :]
+ arr["translation"] = translations[mask, :]
gen_list.append(arr)
return np.concatenate(gen_list)
@@ -240,8 +240,7 @@ def _decode(encoded_data: EncodedData) -> Union[np.ndarray, List[str]]:
result = encoded_data["data"]
for encoding in encoded_data["encoding"][::-1]:
if encoding["kind"] in _decoders:
- result = _decoders[encoding["kind"]](
- result, encoding) # type: ignore
+ result = _decoders[encoding["kind"]](result, encoding) # type: ignore
else:
raise ValueError(f"Unsupported encoding '{encoding['kind']}'")
@@ -330,8 +329,7 @@ def _decode_interval_quantization(
) -> np.ndarray:
delta = (encoding["max"] - encoding["min"]) / (encoding["numSteps"] - 1)
return (
- np.array(data, dtype=_get_dtype(
- encoding["srcType"])) * delta + encoding["min"]
+ np.array(data, dtype=_get_dtype(encoding["srcType"])) * delta + encoding["min"]
)
@@ -406,16 +404,14 @@ def _decode_integer_packing(
def _decode_string_array(data: bytes, encoding: StringArrayEncoding) -> List[str]:
offsets = _decode(
- EncodedData(
- encoding=encoding["offsetEncoding"], data=encoding["offsets"])
+ EncodedData(encoding=encoding["offsetEncoding"], data=encoding["offsets"])
)
- indices = _decode(EncodedData(
- encoding=encoding["dataEncoding"], data=data))
+ indices = _decode(EncodedData(encoding=encoding["dataEncoding"], data=data))
str = encoding["stringData"]
strings = [""]
for i in range(1, len(offsets)):
- strings.append(str[offsets[i - 1]: offsets[i]]) # type: ignore
+ strings.append(str[offsets[i - 1] : offsets[i]]) # type: ignore
return [strings[i + 1] for i in indices] # type: ignore
@@ -555,8 +551,7 @@ def __init__(self, data_blocks: List[CifDataBlock]):
def _decode_column(column: EncodedColumn) -> CifField:
values = _decode(column["data"])
- value_kinds = _decode(
- column["mask"]) if column["mask"] else None # type: ignore
+ value_kinds = _decode(column["mask"]) if column["mask"] else None # type: ignore
# type: ignore
return CifField(name=column["name"], values=values, value_kinds=value_kinds)
@@ -570,8 +565,9 @@ def loads(data: Union[bytes, EncodedFile], lazy=True) -> CifFile:
"""
import msgpack
- file: EncodedFile = data if isinstance(
- data, dict) and "dataBlocks" in data else msgpack.loads(data) # type: ignore
+ file: EncodedFile = (
+ data if isinstance(data, dict) and "dataBlocks" in data else msgpack.loads(data)
+ ) # type: ignore
data_blocks = [
CifDataBlock(
diff --git a/molecularnodes/io/parse/cellpack.py b/molecularnodes/entities/ensemble/cellpack.py
similarity index 83%
rename from molecularnodes/io/parse/cellpack.py
rename to molecularnodes/entities/ensemble/cellpack.py
index e223703f..6a56afdb 100644
--- a/molecularnodes/io/parse/cellpack.py
+++ b/molecularnodes/entities/ensemble/cellpack.py
@@ -6,7 +6,7 @@
from .ensemble import Ensemble
from .bcif import BCIF
from .cif import OldCIF
-from ..parse import molecule
+from ..molecule import molecule
from ... import blender as bl
from ... import color
@@ -20,7 +20,7 @@ def __init__(self, file_path):
self.transformations = self.data.assemblies(as_array=True)
self.chain_ids = self.data.chain_ids
- def create_model(
+ def create_object(
self,
name="CellPack",
node_setup: bool = True,
@@ -61,20 +61,24 @@ def _create_object_instances(
array = self.array
for i, chain in enumerate(np.unique(array.chain_id)):
chain_atoms = array[array.chain_id == chain]
- model, coll_none = molecule._create_model(
+ obj, coll_none = molecule._create_object(
array=chain_atoms,
name=f"{str(i).rjust(4, '0')}_{chain}",
collection=collection,
)
colors = np.tile(color.random_rgb(i), (len(chain_atoms), 1))
- bl.obj.set_attribute(
- model, name="Color", data=colors, type="FLOAT_COLOR", overwrite=True
+ bl.mesh.store_named_attribute(
+ obj,
+ name="Color",
+ data=colors,
+ data_type="FLOAT_COLOR",
+ overwrite=True,
)
if node_setup:
bl.nodes.create_starting_node_tree(
- model, name=f"MN_pack_instance_{name}", color=None
+ obj, name=f"MN_pack_instance_{name}", color=None
)
self.data_collection = collection
@@ -82,7 +86,7 @@ def _create_object_instances(
return collection
def _create_data_object(self, name="DataObject"):
- data_object = bl.obj.create_data_object(
+ data_object = bl.mesh.create_data_object(
self.transformations, name=name, collection=bl.coll.mn()
)
@@ -96,8 +100,8 @@ def _setup_node_tree(self, name="CellPack", fraction=1.0, as_points=False):
group = bl.nodes.new_group(name=f"MN_ensemble_{name}", fallback=False)
mod.node_group = group
- node_pack = bl.nodes.add_custom(group, "MN_pack_instances", location=[-100, 0])
- node_pack.inputs["Collection"].default_value = self.data_collection
+ node_pack = bl.nodes.add_custom(group, "Ensemble Instance", location=[-100, 0])
+ node_pack.inputs["Instances"].default_value = self.data_collection
node_pack.inputs["Fraction"].default_value = fraction
node_pack.inputs["As Points"].default_value = as_points
diff --git a/molecularnodes/io/parse/cif.py b/molecularnodes/entities/ensemble/cif.py
similarity index 97%
rename from molecularnodes/io/parse/cif.py
rename to molecularnodes/entities/ensemble/cif.py
index c042171a..06be969d 100644
--- a/molecularnodes/io/parse/cif.py
+++ b/molecularnodes/entities/ensemble/cif.py
@@ -1,9 +1,13 @@
-import numpy as np
import itertools
import warnings
-from .molecule import Molecule
-from .assembly import AssemblyParser
+import biotite.structure as struc
+import biotite.structure.io.pdbx as pdbx
+import numpy as np
+from biotite import InvalidFileError
+
+from ..molecule.assembly import AssemblyParser
+from ..molecule.molecule import Molecule
class OldCIF(Molecule):
@@ -15,15 +19,9 @@ def __init__(self, file_path, extra_fields=None, sec_struct=True):
self.n_atoms = self.array.array_length()
def _read(self, file_path):
- import biotite.structure.io.pdbx as pdbx
-
return pdbx.legacy.PDBxFile.read(file_path)
def _get_structure(self, extra_fields: str = None, sec_struct=True, bonds=True):
- import biotite.structure.io.pdbx as pdbx
- import biotite.structure as struc
- from biotite import InvalidFileError
-
fields = ["b_factor", "charge", "occupancy", "atom_id"]
if extra_fields:
[fields.append(x) for x in extra_fields]
@@ -100,7 +98,6 @@ def _get_secondary_structure(array, file):
KeyError
If the 'struct_conf' category is not found in the file.
"""
- import biotite.structure as struc
# get the annotations for the struc_conf cetegory. Provides start and end
# residues for the annotations. For most files this will only contain the
@@ -195,8 +192,6 @@ def __init__(self, file_cif):
self._file = file_cif
def list_assemblies(self):
- import biotite.structure.io.pdbx as pdbx
-
return list(pdbx.list_assemblies(self._file).keys())
def get_transformations(self, assembly_id):
diff --git a/molecularnodes/io/parse/ensemble.py b/molecularnodes/entities/ensemble/ensemble.py
similarity index 64%
rename from molecularnodes/io/parse/ensemble.py
rename to molecularnodes/entities/ensemble/ensemble.py
index f6b85f68..af41062d 100644
--- a/molecularnodes/io/parse/ensemble.py
+++ b/molecularnodes/entities/ensemble/ensemble.py
@@ -1,13 +1,12 @@
import bpy
from abc import ABCMeta
-import numpy as np
from ... import blender as bl
-import warnings
+from ..entity import MolecularEntity
from typing import Union
from pathlib import Path
-class Ensemble(metaclass=ABCMeta):
+class Ensemble(MolecularEntity, metaclass=ABCMeta):
def __init__(self, file_path: Union[str, Path]):
"""
Initialize an Ensemble object.
@@ -18,14 +17,15 @@ def __init__(self, file_path: Union[str, Path]):
The path to the file.
"""
+ super().__init__()
self.type: str = "ensemble"
self.file_path: Path = bl.path_resolve(file_path)
- self.object: bpy.types.Object = None
self.instances: bpy.types.Collection = None
self.frames: bpy.types.Collection = None
+ bpy.context.scene.MNSession.ensembles[self.uuid] = self
@classmethod
- def create_model(
+ def create_object(
cls,
name: str = "NewEnsemble",
node_setup: bool = True,
@@ -34,7 +34,7 @@ def create_model(
simplify=False,
):
"""
- Create a 3D model in the of the ensemble.
+ Create a 3D object for the ensemble.
Parameters
----------
@@ -61,28 +61,3 @@ def create_model(
"""
pass
-
- def get_attribute(self, name="position", evaluate=False) -> np.ndarray | None:
- """
- Get the value of an object for the data molecule.
-
- Parameters
- ----------
- name : str, optional
- The name of the attribute. Default is 'position'.
- evaluate : bool, optional
- Whether to first evaluate all node trees before getting the requsted attribute.
- False (default) will sample the underlying atomic geometry, while True will
- sample the geometry that is created through the Geometry Nodes tree.
-
- Returns
- -------
- np.ndarray
- The value of the attribute.
- """
- if not self.object:
- warnings.warn(
- "No object yet created. Use `create_model()` to create a corresponding object."
- )
- return None
- return bl.obj.get_attribute(self.object, name=name, evaluate=evaluate)
diff --git a/molecularnodes/entities/ensemble/star.py b/molecularnodes/entities/ensemble/star.py
new file mode 100644
index 00000000..d76eedcb
--- /dev/null
+++ b/molecularnodes/entities/ensemble/star.py
@@ -0,0 +1,255 @@
+from pathlib import Path
+
+import bpy
+import mrcfile
+import numpy as np
+import starfile
+from PIL import Image
+
+from ... import blender as bl
+from .ensemble import Ensemble
+
+
+class StarFile(Ensemble):
+ def __init__(self, file_path):
+ super().__init__(file_path)
+ self.type = "starfile"
+
+ @classmethod
+ def from_starfile(cls, file_path):
+ self = cls(file_path)
+ self.data = self._read()
+ self.star_type = None
+ self.positions = None
+ self.current_image = -1
+ self._create_mn_columns()
+ self.n_images = self._n_images()
+ return self
+
+ @classmethod
+ def from_blender_object(cls, blender_object):
+ self = cls(blender_object["starfile_path"])
+ self.object = blender_object
+ self.data = self._read()
+ self.star_type = None
+ self.positions = None
+ self.current_image = -1
+ self._create_mn_columns()
+ self.n_images = self._n_images()
+ bpy.app.handlers.depsgraph_update_post.append(self._update_micrograph_texture)
+ return self
+
+ @property
+ def star_node(self):
+ return bl.nodes.get_star_node(self.object)
+
+ @property
+ def micrograph_material(self):
+ return bl.nodes.MN_micrograph_material()
+
+ def _read(self):
+ star = starfile.read(self.file_path)
+ return star
+
+ def _n_images(self):
+ if isinstance(self.data, dict):
+ return len(self.data)
+ return 1
+
+ def _create_mn_columns(self):
+ # only RELION 3.1 and cisTEM STAR files are currently supported, fail gracefully
+ if (
+ isinstance(self.data, dict)
+ and "particles" in self.data
+ and "optics" in self.data
+ ):
+ self.star_type = "relion"
+ elif "cisTEMAnglePsi" in self.data:
+ self.star_type = "cistem"
+ else:
+ raise ValueError(
+ "File is not a valid RELION>=3.1 or cisTEM STAR file, other formats are not currently supported."
+ )
+
+ # Get absolute position and orientations
+ if self.star_type == "relion":
+ df = self.data["particles"].merge(self.data["optics"], on="rlnOpticsGroup")
+
+ # get necessary info from dataframes
+ # Standard cryoEM starfile don't have rlnCoordinateZ. If this column is not present
+ # Set it to "0"
+ if "rlnCoordinateZ" not in df:
+ df["rlnCoordinateZ"] = 0
+
+ self.positions = df[
+ ["rlnCoordinateX", "rlnCoordinateY", "rlnCoordinateZ"]
+ ].to_numpy()
+ pixel_size = df["rlnImagePixelSize"].to_numpy().reshape((-1, 1))
+ self.positions = self.positions * pixel_size
+ shift_column_names = [
+ "rlnOriginXAngst",
+ "rlnOriginYAngst",
+ "rlnOriginZAngst",
+ ]
+ if all([col in df.columns for col in shift_column_names]):
+ shifts_ang = df[shift_column_names].to_numpy()
+ self.positions -= shifts_ang
+ df["MNAnglePhi"] = df["rlnAngleRot"]
+ df["MNAngleTheta"] = df["rlnAngleTilt"]
+ df["MNAnglePsi"] = df["rlnAnglePsi"]
+ df["MNPixelSize"] = df["rlnImagePixelSize"]
+ try:
+ df["MNImageId"] = (
+ df["rlnMicrographName"].astype("category").cat.codes.to_numpy()
+ )
+ except KeyError:
+ try:
+ df["MNImageId"] = (
+ df["rlnTomoName"].astype("category").cat.codes.to_numpy()
+ )
+ except KeyError:
+ df["MNImageId"] = 0.0
+
+ self.data = df
+
+ elif self.star_type == "cistem":
+ df = self.data
+ df["cisTEMZFromDefocus"] = (df["cisTEMDefocus1"] + df["cisTEMDefocus2"]) / 2
+ df["cisTEMZFromDefocus"] = (
+ df["cisTEMZFromDefocus"] - df["cisTEMZFromDefocus"].median()
+ )
+ self.positions = df[
+ [
+ "cisTEMOriginalXPosition",
+ "cisTEMOriginalYPosition",
+ "cisTEMZFromDefocus",
+ ]
+ ].to_numpy()
+ df["MNAnglePhi"] = df["cisTEMAnglePhi"]
+ df["MNAngleTheta"] = df["cisTEMAngleTheta"]
+ df["MNAnglePsi"] = df["cisTEMAnglePsi"]
+ df["MNPixelSize"] = df["cisTEMPixelSize"]
+ df["MNImageId"] = (
+ df["cisTEMOriginalImageFilename"]
+ .astype("category")
+ .cat.codes.to_numpy()
+ )
+
+ def _convert_mrc_to_tiff(self):
+ if self.star_type == "relion":
+ micrograph_path = self.object["rlnMicrographName_categories"][
+ self.star_node.inputs["Image"].default_value - 1
+ ]
+ elif self.star_type == "cistem":
+ micrograph_path = self.object["cisTEMOriginalImageFilename_categories"][
+ self.star_node.inputs["Image"].default_value - 1
+ ].strip("'")
+ else:
+ return False
+
+ # This could be more elegant
+ if not Path(micrograph_path).exists():
+ pot_micrograph_path = Path(self.file_path).parent / micrograph_path
+ if not pot_micrograph_path.exists():
+ if self.star_type == "relion":
+ pot_micrograph_path = (
+ Path(self.file_path).parent.parent.parent / micrograph_path
+ )
+ if not pot_micrograph_path.exists():
+ raise FileNotFoundError(
+ f"Micrograph file {micrograph_path} not found"
+ )
+ else:
+ raise FileNotFoundError(
+ f"Micrograph file {micrograph_path} not found"
+ )
+ micrograph_path = pot_micrograph_path
+
+ tiff_path = Path(micrograph_path).with_suffix(".tiff")
+ if not tiff_path.exists():
+ with mrcfile.open(micrograph_path) as mrc:
+ micrograph_data = mrc.data.copy()
+
+ # For 3D data sum over the z axis. Probalby would be nicer to load the data as a volume
+ if micrograph_data.ndim == 3:
+ micrograph_data = np.sum(micrograph_data, axis=0)
+ # Normalize the data to 0-1
+ micrograph_data = (micrograph_data - micrograph_data.min()) / (
+ micrograph_data.max() - micrograph_data.min()
+ )
+
+ if micrograph_data.dtype != np.float32:
+ micrograph_data = micrograph_data.astype(np.float32)
+
+ # Need to invert in Y to generate the correct tiff
+ Image.fromarray(micrograph_data[::-1, :]).save(tiff_path)
+ return tiff_path
+
+ def _update_micrograph_texture(self, *_):
+ try:
+ show_micrograph = self.star_node.inputs["Show Micrograph"]
+ _ = self.object["mn"]
+ except ReferenceError:
+ bpy.app.handlers.depsgraph_update_post.remove(
+ self._update_micrograph_texture
+ )
+ return
+ if self.star_node.inputs["Image"].default_value == self.current_image:
+ return
+ else:
+ self.current_image = self.star_node.inputs["Image"].default_value
+ if not show_micrograph:
+ return
+ tiff_path = self._convert_mrc_to_tiff()
+ if tiff_path:
+ try:
+ image_obj = bpy.data.images[tiff_path.name]
+ except KeyError:
+ image_obj = bpy.data.images.load(str(tiff_path))
+ image_obj.colorspace_settings.name = "Non-Color"
+ self.micrograph_material.node_tree.nodes["Image Texture"].image = image_obj
+ self.star_node.inputs["Micrograph"].default_value = image_obj
+
+ def create_object(self, name="StarFileObject", node_setup=True, world_scale=0.01):
+ blender_object = bl.mesh.create_object(
+ self.positions * world_scale, collection=bl.coll.mn(), name=name
+ )
+
+ blender_object.mn["molecule_type"] = "star"
+
+ # create attribute for every column in the STAR file
+ for col in self.data.columns:
+ col_type = self.data[col].dtype
+ # If col_type is numeric directly add
+ if np.issubdtype(col_type, np.number):
+ bl.mesh.store_named_attribute(
+ blender_object,
+ col,
+ self.data[col].to_numpy().reshape(-1),
+ "FLOAT",
+ "POINT",
+ )
+
+ # If col_type is object, convert to category and add integer values
+ elif col_type == object:
+ codes = (
+ self.data[col].astype("category").cat.codes.to_numpy().reshape(-1)
+ )
+ bl.mesh.store_named_attribute(
+ blender_object, col, codes, "INT", "POINT"
+ )
+ # Add the category names as a property to the blender object
+ blender_object[f"{col}_categories"] = list(
+ self.data[col].astype("category").cat.categories
+ )
+ blender_object.mn.uuid = self.uuid
+
+ if node_setup:
+ bl.nodes.create_starting_nodes_starfile(
+ blender_object, n_images=self.n_images
+ )
+
+ blender_object["starfile_path"] = str(self.file_path)
+ self.object = blender_object
+ bpy.app.handlers.depsgraph_update_post.append(self._update_micrograph_texture)
+ return blender_object
diff --git a/molecularnodes/entities/ensemble/ui.py b/molecularnodes/entities/ensemble/ui.py
new file mode 100644
index 00000000..8464dd48
--- /dev/null
+++ b/molecularnodes/entities/ensemble/ui.py
@@ -0,0 +1,111 @@
+import bpy
+from .star import StarFile
+
+from .cellpack import CellPack
+
+bpy.types.Scene.MN_import_star_file_path = bpy.props.StringProperty(
+ name="File",
+ description="File path for the `.star` file to import.",
+ subtype="FILE_PATH",
+ maxlen=0,
+)
+bpy.types.Scene.MN_import_star_file_name = bpy.props.StringProperty(
+ name="Name",
+ description="Name of the created object.",
+ default="NewStarInstances",
+ maxlen=0,
+)
+
+
+def load_starfile(
+ file_path, name="NewStarInstances", node_setup=True, world_scale=0.01
+):
+ ensemble = StarFile.from_starfile(file_path)
+ ensemble.create_object(name=name, node_setup=node_setup, world_scale=world_scale)
+
+ return ensemble
+
+
+class MN_OT_Import_Star_File(bpy.types.Operator):
+ bl_idname = "mn.import_star_file"
+ bl_label = "Load"
+ bl_description = (
+ "Will import the given file, setting up the points to instance an object."
+ )
+ bl_options = {"REGISTER"}
+
+ @classmethod
+ def poll(cls, context):
+ return True
+
+ def execute(self, context):
+ scene = context.scene
+ load_starfile(
+ file_path=scene.MN_import_star_file_path,
+ name=scene.MN_import_star_file_name,
+ node_setup=True,
+ )
+ return {"FINISHED"}
+
+
+def panel_starfile(layout, scene):
+ layout.label(text="Load Star File", icon="FILE_TICK")
+ layout.separator()
+ row_import = layout.row()
+ row_import.prop(scene, "MN_import_star_file_name")
+ layout.prop(scene, "MN_import_star_file_path")
+ row_import.operator("mn.import_star_file")
+
+
+bpy.types.Scene.mol_import_cell_pack_path = bpy.props.StringProperty(
+ name="File",
+ description="File to import (.cif, .bcif)",
+ subtype="FILE_PATH",
+ maxlen=0,
+)
+bpy.types.Scene.mol_import_cell_pack_name = bpy.props.StringProperty(
+ name="Name",
+ description="Name of the created object.",
+ default="NewCellPackModel",
+ maxlen=0,
+)
+
+
+def load_cellpack(
+ file_path,
+ name="NewCellPackModel",
+ node_setup=True,
+ world_scale=0.01,
+ fraction: float = 1,
+):
+ ensemble = CellPack(file_path)
+ model = ensemble.create_object(
+ name=name, node_setup=node_setup, world_scale=world_scale, fraction=fraction
+ )
+
+ return model
+
+
+class MN_OT_Import_Cell_Pack(bpy.types.Operator):
+ bl_idname = "mol.import_cell_pack"
+ bl_label = "Load"
+ bl_description = ""
+ bl_options = {"REGISTER"}
+
+ def execute(self, context):
+ s = context.scene
+ load_cellpack(
+ file_path=s.mol_import_cell_pack_path,
+ name=s.mol_import_cell_pack_name,
+ node_setup=True,
+ )
+ return {"FINISHED"}
+
+
+def panel_cellpack(layout, scene):
+ layout.label(text="Load CellPack Model", icon="FILE_TICK")
+ layout.separator()
+ row_import = layout.row()
+ row_import.prop(scene, "mol_import_cell_pack_name")
+ layout.prop(scene, "mol_import_cell_pack_path")
+ row_import.operator("mol.import_cell_pack")
diff --git a/molecularnodes/entities/entity.py b/molecularnodes/entities/entity.py
new file mode 100644
index 00000000..c91e4408
--- /dev/null
+++ b/molecularnodes/entities/entity.py
@@ -0,0 +1,180 @@
+from abc import ABCMeta
+import bpy
+from uuid import uuid1
+from .. import blender as bl
+import warnings
+import numpy as np
+
+
+class ObjectMissingError(Exception):
+ def __init__(self, message):
+ self.message = message
+ super().__init__(self.message)
+
+
+class MolecularEntity(metaclass=ABCMeta):
+ def __init__(self) -> None:
+ self.uuid: str = str(uuid1())
+ self.object_ref: bpy.types.Object | None
+ self.type: str = ""
+
+ @property
+ def name(self) -> str:
+ obj = self.object
+ if obj is None:
+ return None
+
+ return obj.name
+
+ @name.setter
+ def name(self, value: str) -> None:
+ obj = self.object
+ if obj is None:
+ raise ObjectMissingError
+ obj.name = value
+
+ @property
+ def object(self) -> bpy.types.Object | None:
+ # If we don't have connection to an object, attempt to re-stablish to a new
+ # object in the scene with the same UUID. This helps if duplicating / deleting
+ # objects in the scene, but sometimes Blender just loses reference to the object
+ # we are working with because we are manually setting the data on the mesh,
+ # which can wreak havoc on the object database. To protect against this,
+ # if we have a broken link we just attempt to find a new suitable object for it
+ try:
+ # if the connection is broken then trying to the name will raise a connection
+ # error. If we are loading from a saved session then the object_ref will be
+ # None and get an AttributeError
+ self.object_ref.name
+ return self.object_ref
+ except (ReferenceError, AttributeError):
+ for obj in bpy.data.objects:
+ if obj.mn.uuid == self.uuid:
+ print(
+ Warning(
+ f"Lost connection to object: {self.object_ref}, now connected to {obj}"
+ )
+ )
+ self.object_ref = obj
+ return obj
+
+ return None
+
+ @object.setter
+ def object(self, value):
+ self.object_ref = value
+
+ def named_attribute(self, name="position", evaluate=False) -> np.ndarray | None:
+ """
+ Get the value of an object for the data molecule.
+
+ Parameters
+ ----------
+ name : str, optional
+ The name of the attribute. Default is 'position'.
+ evaluate : bool, optional
+ Whether to first evaluate all node trees before getting the requsted attribute.
+ False (default) will sample the underlying atomic geometry, while True will
+ sample the geometry that is created through the Geometry Nodes tree.
+
+ Returns
+ -------
+ np.ndarray
+ The value of the attribute.
+ """
+ if self.object is None:
+ warnings.warn(
+ "No object yet created. Use `create_object()` to create a corresponding object."
+ )
+ return None
+ return bl.mesh.named_attribute(self.object, name=name, evaluate=evaluate)
+
+ def set_position(self, positions: np.ndarray) -> None:
+ "A slightly optimised way to set the positions of the object's mesh"
+ obj = self.object
+ attribute = obj.data.attributes["position"]
+ n_points = len(attribute.data)
+ if positions.shape != (n_points, 3):
+ raise AttributeError(
+ f"Expected an array of dimension {(n_points, 3)} to set the position"
+ / f"but got {positions.shape=}"
+ )
+
+ # actually set the data for the positions
+ attribute.data.foreach_set("vector", positions.reshape(-1))
+ # trigger a depsgraph update. The second method is better but bugs out sometimes
+ # so we try the first method initially
+ try:
+ obj.data.vertices[0].co = obj.data.vertices[0].co # type: ignore
+ except AttributeError:
+ obj.data.update() # type: ignore
+
+ def set_boolean(self, boolean: np.ndarray, name="boolean") -> None:
+ self.store_named_attribute(boolean, name=name, data_type="BOOLEAN")
+
+ def store_named_attribute(
+ self,
+ data: np.ndarray,
+ name="NewAttribute",
+ data_type=None,
+ domain="POINT",
+ overwrite=True,
+ ):
+ """
+ Set an attribute for the molecule.
+
+ Parameters
+ ----------
+ data : np.ndarray
+ The data to be set as the attribute. Must be of length equal to the length
+ of the domain.
+ name : str, optional
+ The name of the new attribute. Default is 'NewAttribute'.
+ type : str, optional
+ If value is None (Default), the data type is inferred. The data type of the
+ attribute. Possbible values are ('FLOAT_VECTOR', 'FLOAT_COLOR", 'QUATERNION',
+ 'FLOAT', 'INT', 'BOOLEAN').
+ domain : str, optional
+ The domain of the attribute. Default is 'POINT'. Possible values are
+ currently ['POINT', 'EDGE', 'FACE', 'SPLINE']
+ overwrite : bool, optional
+ Whether to overwrite an existing attribute with the same name, or create a
+ new attribute with always a unique name. Default is True.
+ """
+ if not self.object:
+ warnings.warn(
+ "No object yet created. Use `create_object()` to create a corresponding object."
+ )
+ return None
+ bl.mesh.store_named_attribute(
+ self.object,
+ name=name,
+ data=data,
+ data_type=data_type,
+ domain=domain,
+ overwrite=overwrite,
+ )
+
+ @classmethod
+ def list_attributes(cls, evaluate=False) -> list | None:
+ """
+ Returns a list of attribute names for the object.
+
+ Parameters
+ ----------
+ evaluate : bool, optional
+ Whether to first evaluate the modifiers on the object before listing the
+ available attributes.
+
+ Returns
+ -------
+ list[str] | None
+ A list of attribute names if the molecule object exists, None otherwise.
+ """
+ if not cls.object:
+ warnings.warn("No object created")
+ return None
+ if evaluate:
+ return list(bl.mesh.evaluated(cls.object).data.attributes.keys())
+
+ return list(cls.object.data.attributes.keys())
diff --git a/molecularnodes/entities/molecule/__init__.py b/molecularnodes/entities/molecule/__init__.py
new file mode 100644
index 00000000..4f88fe15
--- /dev/null
+++ b/molecularnodes/entities/molecule/__init__.py
@@ -0,0 +1,6 @@
+from .pdbx import BCIF, CIF
+from .pdb import PDB
+from .sdf import SDF
+from .molecule import Molecule
+
+from .ui import CLASSES
diff --git a/molecularnodes/io/parse/assembly.py b/molecularnodes/entities/molecule/assembly.py
similarity index 94%
rename from molecularnodes/io/parse/assembly.py
rename to molecularnodes/entities/molecule/assembly.py
index 6ae0b1a7..d0ef39c8 100644
--- a/molecularnodes/io/parse/assembly.py
+++ b/molecularnodes/entities/molecule/assembly.py
@@ -9,7 +9,6 @@
class AssemblyParser(metaclass=ABCMeta):
-
@abstractmethod
def list_assemblies(self):
"""
@@ -29,21 +28,21 @@ def get_transformations(self, assembly_id):
transformations on sets of chains for this assembly
| chain IDs affected by the transformation
| | 4x4 rotation, translation & scale matrix
- | | |
+ | | |
list[tuple[ndarray, ndarray]]]
"""
@abstractmethod
def get_assemblies(self):
"""
- Parse all the transformations for each assembly, returning a dictionary of
+ Parse all the transformations for each assembly, returning a dictionary of
key:value pairs of assembly_id:transformations. The transformations list
comes from the `get_transformations(assembly_id)` method.
Dictionary of all assemblies
| Assembly ID
| | List of transformations to create biological assembly.
- | | |
+ | | |
dict{'1', list[transformations]}
"""
diff --git a/molecularnodes/io/parse/molecule.py b/molecularnodes/entities/molecule/molecule.py
similarity index 76%
rename from molecularnodes/io/parse/molecule.py
rename to molecularnodes/entities/molecule/molecule.py
index 2fd858ad..6ab84f1a 100644
--- a/molecularnodes/io/parse/molecule.py
+++ b/molecularnodes/entities/molecule/molecule.py
@@ -1,16 +1,21 @@
+import io
+import time
+import warnings
from abc import ABCMeta
-from typing import Optional, Any, Union, Tuple
from pathlib import Path
-import warnings
-import time
-import numpy as np
+from typing import Optional, Tuple, Union
+
+import biotite.structure as struc
import bpy
-import io
+import numpy as np
+from biotite import InvalidFileError
+
from ... import blender as bl
-from ... import utils, data, color
+from ..entity import MolecularEntity
+from ... import color, data, utils
-class Molecule(metaclass=ABCMeta):
+class Molecule(MolecularEntity, metaclass=ABCMeta):
"""
Abstract base class for representing a molecule.
@@ -18,7 +23,7 @@ class Molecule(metaclass=ABCMeta):
(the object). If multiple conformations are imported, then a `frames` collection
is also instantiated.
- The `get_attribute()` and `set_attribute()` methods access and set attributes on
+ The `named_attribute()` and `store_named_attribute()` methods access and set attributes on
`object` that is in the Blender scene.
Attributes
@@ -40,22 +45,25 @@ class Molecule(metaclass=ABCMeta):
Methods
-------
- set_attribute(data, name='NewAttribute', type=None, domain='POINT', overwrite=True)
+ store_named_attribute(data, name='NewAttribute', type=None, domain='POINT', overwrite=True)
Set an attribute on the object for the molecule.
- get_attribute(name='position')
+ named_attribute(name='position')
Get the value of an attribute on the object for the molecule.
- create_model(name='NewMolecule', style='spheres', selection=None, build_assembly=False, centre = '', del_solvent=True, collection=None, verbose=False)
+ create_object(name='NewMolecule', style='spheres', selection=None, build_assembly=False, centre = '', del_solvent=True, collection=None, verbose=False)
Create a 3D model for the molecule, based on the values from self.array.
assemblies(as_array=False)
Get the biological assemblies of the molecule.
"""
def __init__(self, file_path: Union[str, Path, io.BytesIO]):
+ super().__init__()
self._parse_filepath(file_path=file_path)
self.file: str
self.array: np.ndarray
- self.object: Optional[bpy.types.Object] = None
self.frames: Optional[bpy.types.Collection] = None
+ self.frames_name: str = ""
+
+ bpy.context.scene.MNSession.molecules[self.uuid] = self
@classmethod
def _read(self, file_path: Union[Path, io.BytesIO]):
@@ -83,8 +91,6 @@ def __len__(self) -> int:
@property
def n_models(self):
- import biotite.structure as struc
-
if isinstance(self.array, struc.AtomArray):
return 1
else:
@@ -98,99 +104,6 @@ def chain_ids(self) -> Optional[list]:
return None
- @property
- def name(self) -> Optional[str]:
- if self.object is not None:
- return self.object.name
- else:
- return None
-
- def set_attribute(
- self,
- data: np.ndarray,
- name="NewAttribute",
- type=None,
- domain="POINT",
- overwrite=True,
- ):
- """
- Set an attribute for the molecule.
-
- Parameters
- ----------
- data : np.ndarray
- The data to be set as the attribute. Must be of length equal to the length
- of the domain.
- name : str, optional
- The name of the new attribute. Default is 'NewAttribute'.
- type : str, optional
- If value is None (Default), the data type is inferred. The data type of the
- attribute. Possbible values are ('FLOAT_VECTOR', 'FLOAT_COLOR", 'QUATERNION',
- 'FLOAT', 'INT', 'BOOLEAN').
- domain : str, optional
- The domain of the attribute. Default is 'POINT'. Possible values are
- currently ['POINT', 'EDGE', 'FACE', 'SPLINE']
- overwrite : bool, optional
- Whether to overwrite an existing attribute with the same name, or create a
- new attribute with always a unique name. Default is True.
- """
- if not self.object:
- warnings.warn(
- f"No object yet created. Use `create_model()` to create a corresponding object."
- )
- return None
- bl.obj.set_attribute(
- self.object, name=name, data=data, domain=domain, overwrite=overwrite
- )
-
- def get_attribute(self, name="position", evaluate=False) -> np.ndarray | None:
- """
- Get the value of an attribute for the associated object.
-
- Parameters
- ----------
- name : str, optional
- The name of the attribute. Default is 'position'.
- evaluate : bool, optional
- Whether to first evaluate all node trees before getting the requsted attribute.
- False (default) will sample the underlying atomic geometry, while True will
- sample the geometry that is created through the Geometry Nodes tree.
-
- Returns
- -------
- np.ndarray
- The value of the attribute.
- """
- if not self.object:
- warnings.warn(
- "No object yet created. Use `create_model()` to create a corresponding object."
- )
- return None
- return bl.obj.get_attribute(self.object, name=name, evaluate=evaluate)
-
- def list_attributes(self, evaluate=False) -> list | None:
- """
- Returns a list of attribute names for the object.
-
- Parameters
- ----------
- evaluate : bool, optional
- Whether to first evaluate the modifiers on the object before listing the
- available attributes.
-
- Returns
- -------
- list[str] | None
- A list of attribute names if the molecule object exists, None otherwise.
- """
- if not self.object:
- warnings.warn("No object created")
- return None
- if evaluate:
- return list(bl.obj.evaluated(self.object).data.attributes.keys())
-
- return list(self.object.data.attributes.keys())
-
def centre(self, centre_type: str = "centroid") -> np.ndarray:
"""
Calculate the centre of mass/geometry of the Molecule object
@@ -198,19 +111,19 @@ def centre(self, centre_type: str = "centroid") -> np.ndarray:
:return: np.ndarray of shape (3,) user-defined centroid of all atoms in
the Molecule object
"""
- positions = self.get_attribute(name="position")
+ positions = self.named_attribute(name="position")
if centre_type == "centroid":
- return bl.obj.centre(positions)
+ return bl.mesh.centre(positions)
elif centre_type == "mass":
- mass = self.get_attribute(name="mass")
- return bl.obj.centre_weighted(positions, mass)
+ mass = self.named_attribute(name="mass")
+ return bl.mesh.centre_weighted(positions, mass)
else:
raise ValueError(
f"`{centre_type}` not a supported selection of ['centroid', 'mass']"
)
- def create_model(
+ def create_object(
self,
name: str = "NewMolecule",
style: str = "spheres",
@@ -218,6 +131,7 @@ def create_model(
build_assembly=False,
centre: str = "",
del_solvent: bool = True,
+ del_hydrogen: bool = False,
collection=None,
verbose: bool = False,
color: Optional[str] = "common",
@@ -260,18 +174,33 @@ def create_model(
bpy.types.Object
The created 3D model, as an object in the 3D scene.
"""
- from biotite import InvalidFileError
+
+ is_stack = isinstance(self.array, struc.AtomArrayStack)
if selection:
array = self.array[selection]
else:
array = self.array
- model, frames = _create_model(
+ # remove the solvent from the structure if requested
+ if del_solvent:
+ mask = np.invert(struc.filter_solvent(array))
+ if is_stack:
+ array = array[:, mask]
+ else:
+ array = array[mask]
+
+ if del_hydrogen:
+ mask = array.element != "H"
+ if is_stack:
+ array = array[:, mask]
+ else:
+ array = array[mask]
+
+ obj, frames = _create_object(
array=array,
name=name,
centre=centre,
- del_solvent=del_solvent,
style=style,
collection=collection,
verbose=verbose,
@@ -279,29 +208,30 @@ def create_model(
if style:
bl.nodes.create_starting_node_tree(
- object=model, coll_frames=frames, style=style, color=color
+ object=obj, coll_frames=frames, style=style, color=color
)
try:
- model["entity_ids"] = self.entity_ids
+ obj["entity_ids"] = self.entity_ids
except AttributeError:
- model["entity_ids"] = None
+ obj["entity_ids"] = None
try:
- model["biological_assemblies"] = self.assemblies()
+ obj["biological_assemblies"] = self.assemblies()
except InvalidFileError:
- model["biological_assemblies"] = None
+ obj["biological_assemblies"] = None
pass
if build_assembly and style:
- bl.nodes.assembly_insert(model)
+ bl.nodes.assembly_insert(obj)
# attach the model bpy.Object to the molecule object
- self.object = model
+ self.object = obj
# same with the collection of bpy Objects for frames
self.frames = frames
+ self.object.mn.uuid = self.uuid
- return model
+ return obj
def assemblies(self, as_array=False):
"""
@@ -319,7 +249,6 @@ def assemblies(self, as_array=False):
The biological assemblies of the molecule, as a dictionary of
transformation matrices, or None if no assemblies are available.
"""
- from biotite import InvalidFileError
try:
assemblies_info = self._assemblies()
@@ -335,11 +264,10 @@ def __repr__(self) -> str:
return f""
-def _create_model(
+def _create_object(
array,
name=None,
centre="",
- del_solvent=False,
style="spherers",
collection=None,
world_scale=0.01,
@@ -351,14 +279,6 @@ def _create_model(
frames = None
is_stack = isinstance(array, struc.AtomArrayStack)
- # remove the solvent from the structure if requested
- if del_solvent:
- mask = np.invert(struc.filter_solvent(array))
- if is_stack:
- array = array[:, mask]
- else:
- array = array[mask]
-
try:
mass = np.array(
[
@@ -372,9 +292,9 @@ def _create_model(
def centre_array(atom_array, centre):
if centre == "centroid":
- atom_array.coord -= bl.obj.centre(atom_array.coord)
+ atom_array.coord -= bl.mesh.centre(atom_array.coord)
elif centre == "mass":
- atom_array.coord -= bl.obj.centre_weighted(
+ atom_array.coord -= bl.mesh.centre_weighted(
array=atom_array.coord, weight=atom_array.mass
)
@@ -403,7 +323,7 @@ def centre_array(atom_array, centre):
bond_types = bonds_array[:, 2].copy(order="C")
# creating the blender object and meshes and everything
- mol = bl.obj.create_object(
+ obj = bl.mesh.create_object(
name=name,
collection=collection,
vertices=array.coord * world_scale,
@@ -415,8 +335,8 @@ def centre_array(atom_array, centre):
# 'AROMATIC_SINGLE' = 5, 'AROMATIC_DOUBLE' = 6, 'AROMATIC_TRIPLE' = 7
# https://www.biotite-python.org/apidoc/biotite.structure.BondType.html#biotite.structure.BondType
if array.bonds:
- bl.obj.set_attribute(
- mol, name="bond_type", data=bond_types, type="INT", domain="EDGE"
+ bl.mesh.store_named_attribute(
+ obj, name="bond_type", data=bond_types, data_type="INT", domain="EDGE"
)
# The attributes for the model are initially defined as single-use functions. This allows
@@ -472,7 +392,7 @@ def att_res_name():
res_nums.append(res_num)
counter += 1
- mol["ligands"] = np.unique(other_res)
+ obj["ligands"] = np.unique(other_res)
return np.array(res_nums)
def att_chain_id():
@@ -688,11 +608,11 @@ def att_sec_struct():
if verbose:
start = time.process_time()
try:
- bl.obj.set_attribute(
- mol,
+ bl.mesh.store_named_attribute(
+ obj,
name=att["name"],
data=att["value"](),
- type=att["type"],
+ data_type=att["type"],
domain=att["domain"],
)
if verbose:
@@ -706,16 +626,16 @@ def att_sec_struct():
coll_frames = None
if frames:
- coll_frames = bl.coll.frames(mol.name, parent=bl.coll.data())
+ coll_frames = bl.coll.frames(obj.name, parent=bl.coll.data())
for i, frame in enumerate(frames):
- frame = bl.obj.create_object(
- name=mol.name + "_frame_" + str(i),
+ frame = bl.mesh.create_object(
+ name=obj.name + "_frame_" + str(i),
collection=coll_frames,
vertices=frame.coord * world_scale,
# vertices=frame.coord * world_scale - centroid
)
# TODO if update_attribute
- # bl.obj.set_attribute(attribute)
+ # bl.mesh.store_named_attribute(attribute)
# this has started to throw errors for me. I'm not sure why.
# mol.mn['molcule_type'] = 'pdb'
@@ -723,9 +643,9 @@ def att_sec_struct():
# add custom properties to the actual blender object, such as number of chains, biological assemblies etc
# currently biological assemblies can be problematic to holding off on doing that
try:
- mol["chain_ids"] = list(np.unique(array.chain_id))
+ obj["chain_ids"] = list(np.unique(array.chain_id))
except AttributeError:
- mol["chain_ids"] = None
+ obj["chain_ids"] = None
warnings.warn("No chain information detected.")
- return mol, coll_frames
+ return obj, coll_frames
diff --git a/molecularnodes/io/parse/pdb.py b/molecularnodes/entities/molecule/pdb.py
similarity index 92%
rename from molecularnodes/io/parse/pdb.py
rename to molecularnodes/entities/molecule/pdb.py
index 2eccd1b9..8bfb300e 100644
--- a/molecularnodes/io/parse/pdb.py
+++ b/molecularnodes/entities/molecule/pdb.py
@@ -1,4 +1,8 @@
+import biotite.structure as struc
import numpy as np
+from biotite import InvalidFileError
+from biotite.structure import BadStructureError, annotate_sse, spread_residue_wise
+from biotite.structure.io import pdb
from .assembly import AssemblyParser
from .molecule import Molecule
@@ -12,14 +16,9 @@ def __init__(self, file_path):
self.n_atoms = self.array.array_length()
def read(self, file_path):
- from biotite.structure.io import pdb
-
return pdb.PDBFile.read(file_path)
def _get_structure(self):
- from biotite.structure.io import pdb
- from biotite.structure import BadStructureError
-
# TODO: implement entity ID, sec_struct for PDB files
array = pdb.get_structure(
pdb_file=self.file,
@@ -41,8 +40,6 @@ def _assemblies(self):
def _get_sec_struct(file, array):
- import biotite.structure as struc
-
lines = np.array(file.lines)
lines_helix = lines[np.char.startswith(lines, "HELIX")]
lines_sheet = lines[np.char.startswith(lines, "SHEET")]
@@ -107,7 +104,6 @@ def _comp_secondary_structure(array):
Inspired from https://www.biotite-python.org/examples/gallery/structure/transketolase_sse.html
"""
# TODO Port [PyDSSP](https://github.com/ShintaroMinami/PyDSSP)
- from biotite.structure import annotate_sse, spread_residue_wise
conv_sse_char_int = {"a": 1, "b": 2, "c": 3, "": 0}
@@ -128,12 +124,10 @@ def list_assemblies(self):
return self._file.list_assemblies()
def get_transformations(self, assembly_id):
- import biotite
-
# Get lines containing transformations for assemblies
remark_lines = self._file.get_remark(350)
if remark_lines is None:
- raise biotite.InvalidFileError(
+ raise InvalidFileError(
"File does not contain assembly information (REMARK 350)"
)
# Get lines corresponding to selected assembly ID
@@ -185,9 +179,7 @@ def get_transformations(self, assembly_id):
break
# Parse transformations from BIOMT lines
if transform_start is None:
- raise biotite.InvalidFileError(
- "No 'BIOMT' records found for chosen assembly"
- )
+ raise InvalidFileError("No 'BIOMT' records found for chosen assembly")
matrices = _parse_transformations(assembly_lines[transform_start:stop])
@@ -210,11 +202,10 @@ def _parse_transformations(lines):
*REMARK* 290 or 350.
Return as array of matrices and vectors respectively
"""
- import biotite
# Each transformation requires 3 lines for the (x,y,z) components
if len(lines) % 3 != 0:
- raise biotite.InvalidFileError("Invalid number of transformation vectors")
+ raise InvalidFileError("Invalid number of transformation vectors")
n_transformations = len(lines) // 3
matrices = np.tile(np.identity(4), (n_transformations, 1, 1))
@@ -227,9 +218,7 @@ def _parse_transformations(lines):
transformations = [float(e) for e in line.split()[2:]]
if len(transformations) != 4:
- raise biotite.InvalidFileError(
- "Invalid number of transformation vector elements"
- )
+ raise InvalidFileError("Invalid number of transformation vector elements")
matrices[transformation_i, component_i, :] = transformations
component_i += 1
diff --git a/molecularnodes/io/parse/pdbx.py b/molecularnodes/entities/molecule/pdbx.py
similarity index 98%
rename from molecularnodes/io/parse/pdbx.py
rename to molecularnodes/entities/molecule/pdbx.py
index 67dfd6fc..737d2a37 100644
--- a/molecularnodes/io/parse/pdbx.py
+++ b/molecularnodes/entities/molecule/pdbx.py
@@ -1,6 +1,9 @@
-import numpy as np
-import warnings
import itertools
+import warnings
+
+import biotite.structure as struc
+import biotite.structure.io.pdbx as pdbx
+import numpy as np
from .molecule import Molecule
@@ -37,9 +40,6 @@ def _get_entity_id(self, array, file):
def get_structure(
self, extra_fields=["b_factor", "occupancy", "atom_id"], bonds=True
):
- import biotite.structure.io.pdbx as pdbx
- import biotite.structure as struc
-
array = pdbx.get_structure(self.file, extra_fields=extra_fields)
try:
array.set_annotation(
@@ -154,7 +154,6 @@ def _get_secondary_structure(self, file, array):
KeyError
If the 'struct_conf' category is not found in the file.
"""
- import biotite.structure as struc
# get the annotations for the struc_conf cetegory. Provides start and end
# residues for the annotations. For most files this will only contain the
@@ -263,8 +262,6 @@ def __init__(self, file_path):
self.array = self.get_structure()
def _read(self, file_path):
- import biotite.structure.io.pdbx as pdbx
-
return pdbx.CIFFile.read(file_path)
@@ -276,8 +273,6 @@ def __init__(self, file_path):
self.array = self.get_structure()
def _read(self, file_path):
- import biotite.structure.io.pdbx as pdbx
-
return pdbx.BinaryCIFFile.read(file_path)
@@ -288,8 +283,6 @@ def __init__(self, file_cif):
self._file = file_cif
def list_assemblies(self):
- import biotite.structure.io.pdbx as pdbx
-
return list(pdbx.list_assemblies(self._file).keys())
def get_transformations(self, assembly_id):
diff --git a/molecularnodes/io/parse/sdf.py b/molecularnodes/entities/molecule/sdf.py
similarity index 84%
rename from molecularnodes/io/parse/sdf.py
rename to molecularnodes/entities/molecule/sdf.py
index ab0d4861..ab98805a 100644
--- a/molecularnodes/io/parse/sdf.py
+++ b/molecularnodes/entities/molecule/sdf.py
@@ -1,16 +1,15 @@
from .molecule import Molecule
+from biotite.structure.io.mol import MOLFile
class SDF(Molecule):
def __init__(self, file_path):
- self.file_path = file_path
+ super().__init__(file_path)
self.file = self.read(self.file_path)
self.array = self._get_structure()
self.n_atoms = self.array.array_length()
def read(self, file_path):
- from biotite.structure.io.mol import MOLFile
-
return MOLFile.read(file_path)
def _get_structure(self):
diff --git a/molecularnodes/entities/molecule/ui.py b/molecularnodes/entities/molecule/ui.py
new file mode 100644
index 00000000..68d4d7cb
--- /dev/null
+++ b/molecularnodes/entities/molecule/ui.py
@@ -0,0 +1,584 @@
+from pathlib import Path
+
+import bpy
+from biotite import InvalidFileError
+import os
+import io
+
+from ...download import FileDownloadPDBError, download, CACHE_DIR
+from ..ensemble.cif import OldCIF
+from .molecule import Molecule
+from .pdb import PDB
+from .pdbx import BCIF, CIF
+from .sdf import SDF
+
+
+def parse(filepath) -> Molecule:
+ if isinstance(filepath, io.BytesIO):
+ suffix = ".bcif"
+ else:
+ suffix = Path(filepath).suffix
+
+ parser = {
+ ".pdb": PDB,
+ ".pdbx": CIF,
+ ".cif": CIF,
+ ".bcif": BCIF,
+ ".mol": SDF,
+ ".sdf": SDF,
+ }
+
+ if suffix not in parser:
+ raise ValueError(f"Unable to open local file. Format '{suffix}' not supported.")
+ try:
+ molecule = parser[suffix](filepath)
+ except InvalidFileError:
+ molecule = OldCIF(filepath)
+
+ return molecule
+
+
+def fetch(
+ pdb_code,
+ style="spheres",
+ centre="",
+ del_solvent=True,
+ del_hydrogen=False,
+ cache_dir=None,
+ build_assembly=False,
+ database: str = "rcsb",
+ format="bcif",
+ color="common",
+) -> Molecule:
+ if build_assembly:
+ centre = ""
+
+ file_path = download(
+ code=pdb_code, format=format, cache=cache_dir, database=database
+ )
+
+ mol = parse(file_path)
+
+ obj = mol.create_object(
+ name=pdb_code,
+ centre=centre,
+ style=style,
+ del_solvent=del_solvent,
+ del_hydrogen=del_hydrogen,
+ build_assembly=build_assembly,
+ color=color,
+ )
+
+ obj.mn["pdb_code"] = pdb_code
+ obj.mn["molecule_type"] = format
+
+ return mol
+
+
+def load_local(
+ file_path,
+ name="Name",
+ centre="",
+ del_solvent=True,
+ del_hydrogen=False,
+ style="spheres",
+ build_assembly=False,
+):
+ mol = parse(file_path)
+ mol.create_object(
+ name=name,
+ style=style,
+ build_assembly=build_assembly,
+ centre=centre,
+ del_solvent=del_solvent,
+ del_hydrogen=del_hydrogen,
+ )
+ return mol
+
+
+STYLE_ITEMS = (
+ ("spheres", "Spheres", "Space-filling atoms style."),
+ ("cartoon", "Cartoon", "Secondary structure cartoons"),
+ ("surface", "Surface", "Solvent-accsible surface."),
+ ("ribbon", "Ribbon", "Continuous backbone ribbon."),
+ ("sticks", "Sticks", "Sticks for each bond."),
+ ("ball_and_stick", "Ball and Stick", "Spheres for atoms, sticks for bonds"),
+ ("preset_1", "Preset 1", "A pre-made combination of different styles"),
+ ("preset_2", "Preset 2", "A pre-made combination of different styles"),
+ ("preset_3", "Preset 3", "A pre-made combination of different styles"),
+ ("preset_4", "Preset 4", "A pre-made combination of different styles"),
+)
+
+
+class Import_Molecule:
+ style: bpy.props.EnumProperty( # type: ignore
+ name="Style",
+ default="spheres",
+ description="Starting style for the structure on import",
+ items=STYLE_ITEMS,
+ )
+ centre: bpy.props.EnumProperty( # type: ignore
+ name="Centre",
+ description="Centre the structure at the world origin using the given method",
+ default="None",
+ items=(
+ ("None", "None", "No centering is applied", 1),
+ (
+ "mass",
+ "Mass",
+ "Adjust the structure's centre of mass to be at the world origin",
+ 2,
+ ),
+ (
+ "centroid",
+ "Centroid",
+ "Adjust the structure's centroid (centre of geometry) to be at the world origin",
+ 3,
+ ),
+ ),
+ )
+ del_solvent: bpy.props.BoolProperty( # type: ignore
+ default=True,
+ name="Delete Solvent",
+ description="Remove solvent atoms from the structure on import",
+ )
+ assembly: bpy.props.BoolProperty( # type: ignore
+ default=False,
+ name="Build Biological Assembly",
+ description="Build the biological assembly for the structure on import",
+ )
+
+
+class MN_OT_Import_Molecule(Import_Molecule, bpy.types.Operator):
+ """Test importer that creates a text object from a .txt file"""
+
+ bl_idname = "mn.import_molecule"
+ bl_label = "Import a Molecule"
+
+ directory: bpy.props.StringProperty( # type: ignore
+ subtype="FILE_PATH", options={"SKIP_SAVE", "HIDDEN"}
+ )
+ files: bpy.props.CollectionProperty( # type: ignore
+ type=bpy.types.OperatorFileListElement, options={"SKIP_SAVE", "HIDDEN"}
+ )
+
+ def execute(self, context):
+ if not self.directory:
+ return {"CANCELLED"}
+
+ for file in self.files:
+ try:
+ mol = parse(os.path.join(self.directory, file.name))
+ mol.create_object(
+ name=file.name,
+ centre=self.centre,
+ style=self.style,
+ del_solvent=self.del_solvent,
+ build_assembly=self.assembly,
+ )
+ except Exception as e:
+ print(f"Failed importing {file}: {e}")
+
+ return {"FINISHED"}
+
+ def invoke(self, context, event):
+ if context.area and context.area.type == "VIEW_3D":
+ context.window_manager.invoke_props_dialog(self)
+ else:
+ context.window_manager.fileselect_add(self)
+ return {"RUNNING_MODAL"}
+
+
+class MN_FH_Import_Molecule(bpy.types.FileHandler):
+ bl_idname = "MN_FH_import_molecule"
+ bl_label = "File handler for import molecular data files."
+ bl_import_operator = "mn.import_molecule"
+ bl_file_extensions = ".pdb;.cif;.mmcif;.bcif;.pdbx"
+
+ @classmethod
+ def poll_drop(cls, context):
+ return context.area and context.area.type == "VIEW_3D"
+
+
+DOWNLOAD_FORMATS = (
+ ("bcif", ".bcif", "Binary compressed .cif file, fastest for downloading"),
+ ("cif", ".cif", "The new standard of .cif / .mmcif"),
+ ("pdb", ".pdb", "The classic (and depcrecated) PDB format"),
+)
+
+
+class MN_OT_Import_Fetch(bpy.types.Operator, Import_Molecule):
+ bl_idname = "mn.import_fetch"
+ bl_label = "Download a Molecule"
+ bl_description = "Download a molecule from the wwPDB and import it to the scene"
+
+ code: bpy.props.StringProperty( # type: ignore
+ default="4ozs",
+ name="PDB Code",
+ description="Code to use for downloading from the wwPDB",
+ )
+ file_format: bpy.props.EnumProperty( # type: ignore
+ name="Format",
+ description="Format to download as from the PDB",
+ default="bcif",
+ items=DOWNLOAD_FORMATS,
+ )
+
+ def execute(self, context):
+ try:
+ file_path = download(
+ self.code, format=self.format, cache=self.cache, database="rcsb"
+ )
+ mol = parse(file_path)
+ mol.create_object(
+ name=self.code,
+ style=self.style,
+ centre=self.centre,
+ del_solvent=self.del_solvent,
+ build_assembly=self.assembly,
+ )
+ except Exception:
+ return {"CANCELLED"}
+ return {"FINISHED"}
+
+ def invoke(self, context, event):
+ context.window_manager.invoke_props_dialog(self)
+ return {"RUNNING_MODAL"}
+
+
+# Properties that can be set in the scene, to be passed to the operator
+
+
+bpy.types.Scene.MN_pdb_code = bpy.props.StringProperty(
+ name="PDB",
+ description="The 4-character PDB code to download",
+ options={"TEXTEDIT_UPDATE"},
+ maxlen=4,
+)
+bpy.types.Scene.MN_cache_dir = bpy.props.StringProperty(
+ name="",
+ description="Directory to save the downloaded files",
+ options={"TEXTEDIT_UPDATE"},
+ default=CACHE_DIR,
+ subtype="DIR_PATH",
+)
+bpy.types.Scene.MN_cache = bpy.props.BoolProperty(
+ name="Cache Downloads",
+ description="Save the downloaded file in the given directory",
+ default=True,
+)
+bpy.types.Scene.MN_import_del_hydrogen = bpy.props.BoolProperty(
+ name="Remove Hydrogens",
+ description="Remove the hydrogens from a structure on import",
+ default=False,
+)
+bpy.types.Scene.MN_import_format_download = bpy.props.EnumProperty(
+ name="Format",
+ description="Format to download as from the PDB",
+ items=(
+ ("bcif", ".bcif", "Binary compressed .cif file, fastest for downloading"),
+ ("cif", ".cif", "The new standard of .cif / .mmcif"),
+ ("pdb", ".pdb", "The classic (and depcrecated) PDB format"),
+ ),
+)
+bpy.types.Scene.MN_import_local_path = bpy.props.StringProperty(
+ name="File",
+ description="File path of the structure to open",
+ options={"TEXTEDIT_UPDATE"},
+ subtype="FILE_PATH",
+ maxlen=0,
+)
+bpy.types.Scene.MN_import_local_name = bpy.props.StringProperty(
+ name="Name",
+ description="Name of the molecule on import",
+ options={"TEXTEDIT_UPDATE"},
+ default="NewMolecule",
+ maxlen=0,
+)
+
+bpy.types.Scene.MN_alphafold_code = bpy.props.StringProperty(
+ name="UniProt ID",
+ description="The UniProt ID to use for downloading from the AlphaFold databse",
+ options={"TEXTEDIT_UPDATE"},
+)
+
+bpy.types.Scene.MN_import_format_alphafold = bpy.props.EnumProperty(
+ name="Format",
+ description="Format to download as from the PDB",
+ items=(
+ # ("bcif", ".bcif", "Binary compressed .cif file, fastest for downloading"),
+ ("cif", ".cif", "The new standard of .cif / .mmcif"),
+ ("pdb", ".pdb", "The classic (and depcrecated) PDB format"),
+ ),
+)
+
+
+# operator that is called by the 'button' press which calls the fetch function
+
+
+class MN_OT_Import_wwPDB(bpy.types.Operator):
+ bl_idname = "mn.import_wwpdb"
+ bl_label = "Fetch"
+ bl_description = "Download and open a structure from the Protein Data Bank"
+ bl_options = {"REGISTER", "UNDO"}
+
+ def execute(self, context):
+ scene = context.scene
+ pdb_code = scene.MN_pdb_code
+ cache_dir = scene.MN_cache_dir
+ file_format = scene.MN_import_format_download
+
+ if not scene.MN_cache:
+ cache_dir = None
+
+ style = None
+ if scene.MN_import_node_setup:
+ style = scene.MN_import_style
+
+ centre = ""
+ if scene.MN_import_centre:
+ centre = scene.MN_centre_type
+
+ try:
+ mol = fetch(
+ pdb_code=pdb_code,
+ centre=centre,
+ del_solvent=scene.MN_import_del_solvent,
+ del_hydrogen=scene.MN_import_del_hydrogen,
+ style=style,
+ cache_dir=cache_dir,
+ build_assembly=scene.MN_import_build_assembly,
+ format=file_format,
+ )
+ except FileDownloadPDBError as e:
+ self.report({"ERROR"}, str(e))
+ if file_format == "pdb":
+ self.report(
+ {"ERROR"},
+ "There may not be a `.pdb` formatted file available - try a different download format.",
+ )
+ return {"CANCELLED"}
+
+ bpy.context.view_layer.objects.active = mol.object
+ self.report({"INFO"}, message=f"Imported '{pdb_code}' as {mol.object.name}")
+
+ return {"FINISHED"}
+
+
+class MN_OT_Import_Protein_Local(bpy.types.Operator):
+ bl_idname = "mn.import_protein_local"
+ bl_label = "Load"
+ bl_description = "Open a local structure file"
+ bl_options = {"REGISTER", "UNDO"}
+
+ def execute(self, context):
+ scene = context.scene
+ file_path = scene.MN_import_local_path
+
+ style = scene.MN_import_style
+ if not scene.MN_import_node_setup:
+ style = None
+
+ centre = ""
+ if scene.MN_import_centre:
+ centre = scene.MN_centre_type
+
+ mol = load_local(
+ file_path=file_path,
+ name=scene.MN_import_local_name,
+ centre=centre,
+ del_solvent=scene.MN_import_del_solvent,
+ del_hydrogen=scene.MN_import_del_hydrogen,
+ style=style,
+ build_assembly=scene.MN_import_build_assembly,
+ )
+
+ # return the good news!
+ bpy.context.view_layer.objects.active = mol.object
+ self.report({"INFO"}, message=f"Imported '{file_path}' as {mol.name}")
+ return {"FINISHED"}
+
+ def invoke(self, context, event):
+ return self.execute(context)
+
+
+class MN_OT_Import_AlphaFold(bpy.types.Operator):
+ bl_idname = "mn.import_alphafold"
+ bl_label = "Fetch"
+ bl_description = "Download specified structure from the AlphaFold databse"
+ bl_options = {"REGISTER", "UNDO"}
+
+ def execute(self, context):
+ scene = context.scene
+ pdb_code = scene.MN_alphafold_code.strip()
+ cache_dir = scene.MN_cache_dir
+ file_format = scene.MN_import_format_alphafold
+
+ if not scene.MN_cache:
+ cache_dir = None
+
+ style = None
+ if scene.MN_import_node_setup:
+ style = scene.MN_import_style
+
+ centre = ""
+ if scene.MN_import_centre:
+ centre = scene.MN_centre_type
+
+ try:
+ mol = fetch(
+ pdb_code=pdb_code,
+ centre=centre,
+ del_solvent=scene.MN_import_del_solvent,
+ style=style,
+ cache_dir=cache_dir,
+ build_assembly=scene.MN_import_build_assembly,
+ format=file_format,
+ database="alphafold",
+ color="plddt",
+ )
+ except FileDownloadPDBError as e:
+ self.report({"ERROR"}, str(e))
+ if file_format == "pdb":
+ self.report(
+ {"ERROR"},
+ "There may not be a `.pdb` formatted file available - try a different download format.",
+ )
+ return {"CANCELLED"}
+
+ bpy.context.view_layer.objects.active = mol.object
+ self.report({"INFO"}, message=f"Imported '{pdb_code}' as {mol.object.name}")
+
+ return {"FINISHED"}
+
+
+# the UI for the panel, which will display the operator and the properties
+
+
+def panel_wwpdb(layout, scene):
+ layout.label(text="Download from PDB", icon="IMPORT")
+ layout.separator()
+
+ row_import = layout.row().split(factor=0.5)
+ row_import.prop(scene, "MN_pdb_code")
+ download = row_import.split(factor=0.3)
+ download.prop(scene, "MN_import_format_download", text="")
+ download.operator("mn.import_wwpdb")
+ layout.separator(factor=0.4)
+
+ row = layout.row().split(factor=0.3)
+ row.prop(scene, "MN_cache")
+ row_cache = row.row()
+ row_cache.prop(scene, "MN_cache_dir")
+ row_cache.enabled = scene.MN_cache
+ layout.separator()
+
+ layout.label(text="Options", icon="MODIFIER")
+ options = layout.column(align=True)
+
+ row = options.row()
+ row.prop(scene, "MN_import_node_setup", text="")
+ col = row.column()
+ col.prop(scene, "MN_import_style")
+ col.enabled = scene.MN_import_node_setup
+
+ row_centre = options.row()
+ row_centre.prop(scene, "MN_import_centre", icon_value=0)
+ col_centre = row_centre.column()
+ col_centre.prop(scene, "MN_centre_type", text="")
+ col_centre.enabled = scene.MN_import_centre
+ options.separator()
+
+ grid = options.grid_flow()
+ grid.prop(scene, "MN_import_build_assembly")
+ grid.prop(scene, "MN_import_del_solvent")
+ grid.prop(scene, "MN_import_del_hydrogen")
+
+
+def panel_alphafold(layout, scene):
+ layout.label(text="Download from the AlphaFold DataBase", icon="IMPORT")
+ layout.separator()
+
+ row_import = layout.row().split(factor=0.5)
+ row_import.prop(scene, "MN_alphafold_code")
+ download = row_import.split(factor=0.3)
+ download.prop(scene, "MN_import_format_alphafold", text="")
+ download.operator("mn.import_alphafold")
+ layout.separator(factor=0.4)
+
+ row = layout.row().split(factor=0.3)
+ row.prop(scene, "MN_cache")
+ row_cache = row.row()
+ row_cache.prop(scene, "MN_cache_dir")
+ row_cache.enabled = scene.MN_cache
+ layout.separator()
+
+ layout.label(text="Options", icon="MODIFIER")
+ options = layout.column(align=True)
+
+ row = options.row()
+ row.prop(scene, "MN_import_node_setup", text="")
+ col = row.column()
+ col.prop(scene, "MN_import_style")
+ col.enabled = scene.MN_import_node_setup
+
+ row_centre = options.row()
+ row_centre.prop(scene, "MN_import_centre", icon_value=0)
+ col_centre = row_centre.column()
+ col_centre.prop(scene, "MN_centre_type", text="")
+ col_centre.enabled = scene.MN_import_centre
+ options.separator()
+
+ grid = options.grid_flow()
+ grid.prop(scene, "MN_import_build_assembly")
+ grid.prop(scene, "MN_import_del_solvent")
+ # grid.prop(scene, "MN_import_del_hydrogen")
+
+
+# operator that calls the function to import the structure from a local file
+
+
+def panel_local(layout, scene):
+ layout.label(text="Load a Local File", icon="FILE_TICK")
+ layout.separator()
+
+ row_name = layout.row(align=False)
+ row_name.prop(scene, "MN_import_local_name")
+ row_name.operator("mn.import_protein_local")
+
+ row_import = layout.row()
+ row_import.prop(scene, "MN_import_local_path")
+ layout.separator()
+
+ layout.label(text="Options", icon="MODIFIER")
+ options = layout.column(align=True)
+
+ row = options.row()
+ row.prop(scene, "MN_import_node_setup", text="")
+ col = row.column()
+ col.prop(scene, "MN_import_style")
+ col.enabled = scene.MN_import_node_setup
+
+ row_centre = options.row()
+
+ row_centre.prop(scene, "MN_import_centre", icon_value=0)
+ # row_centre.prop()
+ col_centre = row_centre.column()
+ col_centre.prop(scene, "MN_centre_type", text="")
+ col_centre.enabled = scene.MN_import_centre
+ options.separator()
+
+ grid = options.grid_flow()
+ grid.prop(scene, "MN_import_build_assembly")
+ grid.prop(scene, "MN_import_del_solvent", icon_value=0)
+ grid.prop(scene, "MN_import_del_hydrogen", icon_value=0)
+
+
+CLASSES = [
+ MN_OT_Import_AlphaFold,
+ MN_OT_Import_Protein_Local,
+ MN_OT_Import_wwPDB,
+ MN_OT_Import_Molecule,
+ MN_FH_Import_Molecule,
+ MN_OT_Import_Fetch,
+]
diff --git a/molecularnodes/entities/trajectory/__init__.py b/molecularnodes/entities/trajectory/__init__.py
new file mode 100644
index 00000000..3695176e
--- /dev/null
+++ b/molecularnodes/entities/trajectory/__init__.py
@@ -0,0 +1,6 @@
+from . import selections
+from . import ui
+from .ui import load
+from .trajectory import Trajectory
+
+CLASSES = selections.CLASSSES + ui.CLASSES
diff --git a/molecularnodes/io/dna.py b/molecularnodes/entities/trajectory/dna.py
similarity index 91%
rename from molecularnodes/io/dna.py
rename to molecularnodes/entities/trajectory/dna.py
index 094a27cf..6c823fa4 100644
--- a/molecularnodes/io/dna.py
+++ b/molecularnodes/entities/trajectory/dna.py
@@ -1,7 +1,7 @@
import numpy as np
import bpy
-from .. import color
-from ..blender import obj, coll, nodes
+from ... import color
+from ...blender import mesh, coll, nodes
bpy.types.Scene.MN_import_oxdna_topology = bpy.props.StringProperty(
name="Toplogy",
@@ -176,7 +176,7 @@ def read_trajectory(filepath):
return np.stack(frames)
-def set_attributes_to_dna_mol(mol, frame, scale_dna=0.1):
+def store_named_attributes_to_dna_mol(mol, frame, scale_dna=0.1):
attributes = ("base_vector", "base_normal", "velocity", "angular_velocity")
for i, att in enumerate(attributes):
col_idx = np.array([3, 4, 5]) + i * 3
@@ -190,7 +190,7 @@ def set_attributes_to_dna_mol(mol, frame, scale_dna=0.1):
if att != "angular_velocity":
data *= scale_dna
- obj.set_attribute(mol, att, data, type="FLOAT_VECTOR")
+ mesh.store_named_attribute(mol, att, data, data_type="FLOAT_VECTOR")
def toplogy_to_bond_idx_pairs(topology: np.ndarray):
@@ -252,7 +252,7 @@ def load(top, traj, name="oxDNA", setup_nodes=True, world_scale=0.01):
# creat toplogy object with positions of the first frame, and the bonds from the
# topology object
- mol = obj.create_object(
+ obj = mesh.create_object(
name=name,
collection=coll.mn(),
vertices=trajectory[0][:, 0:3] * scale_dna,
@@ -260,23 +260,23 @@ def load(top, traj, name="oxDNA", setup_nodes=True, world_scale=0.01):
)
# adding additional toplogy information from the topology and frames objects
- obj.set_attribute(mol, "res_name", topology[:, 1], "INT")
- obj.set_attribute(mol, "chain_id", topology[:, 0], "INT")
- obj.set_attribute(
- mol,
+ mesh.store_named_attribute(obj, "res_name", topology[:, 1], "INT")
+ mesh.store_named_attribute(obj, "chain_id", topology[:, 0], "INT")
+ mesh.store_named_attribute(
+ obj,
"Color",
data=color.color_chains_equidistant(topology[:, 0]),
- type="FLOAT_COLOR",
+ data_type="FLOAT_COLOR",
)
- set_attributes_to_dna_mol(mol, trajectory[0], scale_dna=scale_dna)
+ store_named_attributes_to_dna_mol(obj, trajectory[0], scale_dna=scale_dna)
# if the 'frames' file only contained one timepoint, return the object without creating
# any kind of collection for storing multiple frames from a trajectory, and a None
# object in place of the frames collection
if n_frames == 1:
if setup_nodes:
- nodes.create_starting_node_tree(mol, style="oxdna", color=None)
- return mol, None
+ nodes.create_starting_node_tree(obj, style="oxdna", color=None)
+ return obj, None
# create a collection to store all of the frame objects that are part of the trajectory
# they will contain all of the possible attributes which can be interpolated betewen
@@ -285,17 +285,17 @@ def load(top, traj, name="oxDNA", setup_nodes=True, world_scale=0.01):
for i, frame in enumerate(trajectory):
fill_n = int(np.ceil(np.log10(n_frames)))
frame_name = f"{name}_frame_{str(i).zfill(fill_n)}"
- frame_mol = obj.create_object(
+ frame_obj = mesh.create_object(
frame[:, 0:3] * scale_dna, name=frame_name, collection=collection
)
- set_attributes_to_dna_mol(frame_mol, frame, scale_dna)
+ store_named_attributes_to_dna_mol(frame_obj, frame, scale_dna)
if setup_nodes:
nodes.create_starting_node_tree(
- mol, coll_frames=collection, style="oxdna", color=None
+ obj, coll_frames=collection, style="oxdna", color=None
)
- return mol, collection
+ return obj, collection
class MN_OT_Import_OxDNA_Trajectory(bpy.types.Operator):
diff --git a/molecularnodes/entities/trajectory/handlers.py b/molecularnodes/entities/trajectory/handlers.py
new file mode 100644
index 00000000..8e1ef63e
--- /dev/null
+++ b/molecularnodes/entities/trajectory/handlers.py
@@ -0,0 +1,43 @@
+import bpy
+from bpy.app.handlers import persistent
+
+
+# this update function requires a self and context input, as funcitons with these inputs
+# have ot be passed to the `update` arguments of UI properties. When the UI is updated,
+# the function is called with the UI element being `self` and the current context being
+# passed into the function
+def _update_trajectories(self, context: bpy.types.Context) -> None:
+ """
+ Function for being called at various points in the updating of the UI, to ensure
+ positions and selections of the trajectories are udpated with the new inputs
+ """
+ update_trajectories(context.scene)
+
+
+def _selection_update_trajectories(self, context: bpy.types.Context) -> None:
+ """
+ Function for selection changing. If the selection is immutable e.g.
+ when it is generated from an AtomGroup,
+ update universe will not be called to avoid invalid selection str.
+ """
+ if self.immutable:
+ return
+ else:
+ update_trajectories(context.scene)
+
+
+# this is the 'perisisent' function which can be appended onto the
+# `bpy.app.handlers.frame_change_*` functions. Either before or after the frame changes
+# this function will then be called - ensuring all of the trajectories are up to date. We
+# use the `frame_change_post` handler as we want the frame to change first, then we update
+# the universe based on the current frame value
+@persistent
+def update_trajectories(scene):
+ "Updatins all positions and selections for each trajectory."
+ for trajectory in scene.MNSession.trajectories.values():
+ try:
+ trajectory._update_positions(scene.frame_current)
+ trajectory._update_selections()
+ trajectory._update_calculations()
+ except Exception as e:
+ print(f"Error updating {trajectory}: {e}")
diff --git a/molecularnodes/entities/trajectory/selections.py b/molecularnodes/entities/trajectory/selections.py
new file mode 100644
index 00000000..50f94da3
--- /dev/null
+++ b/molecularnodes/entities/trajectory/selections.py
@@ -0,0 +1,201 @@
+import bpy
+import MDAnalysis as mda
+import numpy.typing as npt
+import numpy as np
+from bpy.props import StringProperty, BoolProperty
+from .handlers import _selection_update_trajectories, _update_trajectories
+
+
+class Selection:
+ def __init__(
+ self, universe: mda.Universe, selection_str, name, updating=True, periodic=True
+ ):
+ self.selection_str: str = selection_str
+ self.periodic: bool = periodic
+ self.updating: bool = updating
+ self.universe: mda.Universe = universe
+ self.message: str = ""
+ self.name: str = name
+ self.cleanup: bool = True
+ self.ag = universe.select_atoms(
+ selection_str, updating=updating, periodic=periodic
+ )
+ self.mask_array = self._ag_to_mask()
+
+ def _ag_to_mask(self) -> npt.NDArray[np.bool_]:
+ "Return a 1D boolean mask for the Universe atoms that are in the Selection's AtomGroup."
+ return np.isin(self.universe.atoms.ix, self.ag.ix).astype(bool)
+
+ def change_selection(
+ self,
+ selection_str: str,
+ name: str,
+ updating: bool = True,
+ periodic: bool = True,
+ ) -> None:
+ "Change the current AtomGroup, using the parent universe and creating a new selection with the given `selectrion_str`"
+ self.name = name
+ self.periodic = periodic
+ self.updating = updating
+ self.selection_str = selection_str
+ try:
+ self.ag = self.universe.select_atoms(
+ selection_str, updating=updating, periodic=periodic
+ )
+ self.message = ""
+ except Exception as e:
+ self.message = str(e)
+ print(e)
+
+ def to_mask(self) -> npt.NDArray[np.bool_]:
+ "Returns the selection as a 1D numpy boolean mask. If updating=True, recomputes selection."
+ if self.updating:
+ self.mask_array = self._ag_to_mask()
+ return self.mask_array
+
+ @classmethod
+ def from_atomgroup(cls, atomgroup: mda.AtomGroup, name: str = ""):
+ "Create a Selection object from an AtomGroup"
+
+ # set default value
+ selection_str = f"sel_{atomgroup.n_atoms}_atoms"
+ updating = False
+ periodic = False
+
+ # if class is an UpdatingAtomGroup
+ if atomgroup.__class__.__name__ == "UpdatingAtomGroup":
+ updating = True
+ # assuming it's a single selection
+ # MDA do support `u.select_atoms('index 0', 'around 5 index 0')
+ selection_str = atomgroup._selection_strings[0]
+ periodic = False
+ try:
+ if atomgroup._selections[0].periodic:
+ periodic = True
+ except AttributeError:
+ pass
+
+ if name == "":
+ name = selection_str
+ selection = cls(atomgroup.universe, "all", name, updating, periodic)
+
+ selection.selection_str = selection_str
+ selection.ag = atomgroup
+ selection.mask_array = selection._ag_to_mask()
+ return selection
+
+
+class TrajectorySelectionItem(bpy.types.PropertyGroup):
+ """Group of properties for custom selections for MDAnalysis import."""
+
+ name: StringProperty( # type: ignore
+ name="Name",
+ description="Name of the attribute on the mesh",
+ default="custom_selection",
+ update=_selection_update_trajectories,
+ )
+
+ selection_str: StringProperty( # type: ignore
+ name="Selection",
+ description="Selection to be applied, written in the MDAnalysis selection language",
+ default="name CA",
+ update=_selection_update_trajectories,
+ )
+
+ updating: BoolProperty( # type: ignore
+ name="Updating",
+ description="Recalculate the selection on scene frame change",
+ default=True,
+ update=_selection_update_trajectories,
+ )
+
+ periodic: BoolProperty( # type: ignore
+ name="Periodic",
+ description="For geometric selections, whether to account for atoms in different periodic images when searching",
+ default=True,
+ update=_selection_update_trajectories,
+ )
+
+ message: StringProperty( # type: ignore
+ name="Message",
+ description="Message to report back from `universe.select_atoms()`",
+ default="",
+ )
+
+ immutable: BoolProperty( # type: ignore
+ name="Immutable",
+ description="Whether the selection is immutable",
+ default=False,
+ )
+
+
+class MN_UL_TrajectorySelectionListUI(bpy.types.UIList):
+ """UI List"""
+
+ def draw_item(
+ self, context, layout, data, item, icon, active_data, active_propname, index
+ ):
+ custom_icon = "VIS_SEL_11"
+
+ if self.layout_type in {"DEFAULT", "COMPACT"}:
+ row = layout.row()
+ if item.message != "":
+ custom_icon = "ERROR"
+ row.alert = True
+
+ row.prop(item, "name", text="", emboss=False)
+ row.prop(item, "updating", icon_only=True, icon="FILE_REFRESH")
+ row.prop(item, "periodic", icon_only=True, icon="CUBE")
+ if item.immutable:
+ row.enabled = False
+
+ elif self.layout_type in {"GRID"}:
+ layout.alignment = "CENTER"
+ layout.label(text="", icon=custom_icon)
+
+
+class MN_OT_Universe_Selection_Add(bpy.types.Operator):
+ "Add a new custom selection to a trajectory"
+
+ bl_idname = "mn.trajectory_selection_add"
+ bl_label = "+"
+ bl_description = "Add a new boolean attribute for the given MDA selection string"
+
+ def execute(self, context):
+ obj = context.active_object
+ obj.mn_trajectory_selections.add()
+ i = int(len(obj.mn_trajectory_selections) - 1)
+ obj.mn_trajectory_selections[i].name = f"selection_{i + 1}"
+ obj.mn["list_index"] = i
+ _update_trajectories(self, context)
+
+ return {"FINISHED"}
+
+
+class MN_OT_Universe_Selection_Delete(bpy.types.Operator):
+ bl_idname = "mda.delete_item"
+ bl_label = "-"
+ bl_description = "Delete the given boolean selection from the universe"
+
+ @classmethod
+ def poll(cls, context):
+ return context.active_object.mn_trajectory_selections
+
+ def execute(self, context):
+ obj = context.active_object
+ index = obj.mn.trajectory_selection_index
+
+ sel_list = obj.mn_trajectory_selections
+ sel_list.remove(index)
+ obj.mn.trajectory_selection_index = len(sel_list) - 1
+ _update_trajectories(self, context)
+
+ return {"FINISHED"}
+
+
+CLASSSES = [
+ TrajectorySelectionItem, # has to be registered before the others to work properly
+ MN_UL_TrajectorySelectionListUI,
+ MN_OT_Universe_Selection_Add,
+ MN_OT_Universe_Selection_Delete,
+]
diff --git a/molecularnodes/entities/trajectory/trajectory.py b/molecularnodes/entities/trajectory/trajectory.py
new file mode 100644
index 00000000..60b18930
--- /dev/null
+++ b/molecularnodes/entities/trajectory/trajectory.py
@@ -0,0 +1,579 @@
+from typing import Dict, List, Callable
+
+import bpy
+import MDAnalysis as mda
+import numpy as np
+import numpy.typing as npt
+
+from ... import data
+from ..entity import MolecularEntity, ObjectMissingError
+from ...blender import coll, mesh, nodes
+from ...utils import lerp, correct_periodic_positions
+from .selections import Selection, TrajectorySelectionItem
+
+
+class Trajectory(MolecularEntity):
+ def __init__(self, universe: mda.Universe, world_scale=0.01):
+ super().__init__()
+ self.universe: mda.Universe = universe
+ self.selections: Dict[str, Selection] = {}
+ self.calculations: Dict[str, Callable] = {}
+ self.world_scale = world_scale
+ self.frame_mapping: npt.NDArray[np.in64] | None = None
+ bpy.context.scene.MNSession.trajectories[self.uuid] = self
+
+ def selection_from_ui(self, ui_item: TrajectorySelectionItem) -> Selection:
+ self.selections[ui_item.name] = Selection(
+ universe=self.universe,
+ selection_str=ui_item.selection_str,
+ name=ui_item.name,
+ updating=ui_item.updating,
+ periodic=ui_item.periodic,
+ )
+ self.apply_selection(self.selections[ui_item.name])
+
+ return self.selections[ui_item.name]
+
+ def add_selection(
+ self,
+ selection_str: str,
+ name: str,
+ updating: bool = True,
+ periodic: bool = True,
+ ) -> TrajectorySelectionItem:
+ "Adds a new selection with the given name, selection string and selection parameters."
+ obj = self.object
+ # if obj is None:
+ # raise ObjectMissingError("Universe contains no object to add seleciton to")
+
+ obj.mn_trajectory_selections.add()
+ sel = obj.mn_trajectory_selections[-1]
+ sel.name = name
+ sel.selection_str = selection_str
+ sel.updating = updating
+ sel.periodic = periodic
+
+ self.selection_from_ui(sel)
+
+ return sel
+
+ def add_selection_from_atomgroup(self, atomgroup: mda.AtomGroup, name: str = ""):
+ "Create a Selection object from an AtomGroup"
+ selection = Selection.from_atomgroup(atomgroup, name=name)
+
+ obj = self.object
+ obj.mn_trajectory_selections.add()
+ sel = obj.mn_trajectory_selections[-1]
+
+ if not atomgroup.__class__.__name__ == "UpdatingAtomGroup":
+ sel.immutable = True
+ sel.name = selection.name
+ sel.selection_str = selection.selection_str
+ sel.updating = selection.updating
+ sel.periodic = selection.periodic
+
+ self.selections[selection.name] = selection
+ self.apply_selection(selection)
+ return sel
+
+ def apply_selection(self, selection: Selection):
+ "Set the boolean attribute for this selection on the mesh of the object"
+ self.set_boolean(name=selection.name, boolean=selection.to_mask())
+
+ @property
+ def subframes(self):
+ obj = self.object
+ if obj is None:
+ return None
+ return obj.mn.subframes
+
+ @subframes.setter
+ def subframes(self, value: int):
+ obj = self.object
+ if obj is None:
+ return None
+ obj.mn.subframes = value
+
+ @property
+ def interpolate(self) -> bool:
+ obj = self.object
+ if obj is None:
+ return None
+ return obj.mn.interpolate
+
+ @interpolate.setter
+ def interpolate(self, value: bool):
+ obj = self.object
+ if obj is None:
+ return None
+ obj.mn.interpolate = value
+
+ @property
+ def is_orthorhombic(self):
+ dim = self.universe.dimensions
+ if dim is None:
+ return False
+
+ return np.allclose(dim[3:], 90.0)
+
+ @property
+ def atoms(self) -> mda.AtomGroup:
+ return self.universe.atoms
+
+ @property
+ def n_atoms(self) -> int:
+ return self.atoms.n_atoms
+
+ @staticmethod
+ def bool_selection(ag, selection, **kwargs) -> np.ndarray:
+ return np.isin(ag.ix, ag.select_atoms(selection, **kwargs).ix).astype(bool)
+
+ @property
+ def positions(self) -> np.ndarray:
+ return self.atoms.positions * self.world_scale
+
+ @property
+ def bonds(self) -> List[List[int]]:
+ if hasattr(self.atoms, "bonds"):
+ bond_indices = self.atoms.bonds.indices
+ atm_indices = self.atoms.indices
+ bond_filtering = np.all(np.isin(bond_indices, atm_indices), axis=1)
+ bond_indices = bond_indices[bond_filtering]
+ index_map = {
+ index: i for i, index in enumerate(self.universe.atoms.indices)
+ }
+
+ bonds = [[index_map[bond[0]], index_map[bond[1]]] for bond in bond_indices]
+ else:
+ bonds = []
+ return bonds
+
+ @property
+ def elements(self) -> List[str]:
+ try:
+ elements = self.atoms.elements.tolist()
+ except Exception:
+ try:
+ elements = [
+ x
+ if x in data.elements.keys()
+ else mda.topology.guessers.guess_atom_element(x)
+ for x in self.atoms.names
+ ]
+
+ except Exception:
+ elements = ["X"] * self.atoms.n_atoms
+ return elements
+
+ @property
+ def atomic_number(self) -> np.ndarray:
+ return np.array(
+ [
+ data.elements.get(element, data.elements.get("X")).get("atomic_number")
+ for element in self.elements
+ ]
+ )
+
+ @property
+ def vdw_radii(self) -> np.ndarray:
+ # pm to Angstrom
+ return (
+ np.array(
+ [
+ data.elements.get(element, {}).get("vdw_radii", 100)
+ for element in self.elements
+ ]
+ )
+ * 0.01
+ * self.world_scale
+ )
+
+ @property
+ def mass(self) -> np.ndarray:
+ # units: daltons
+ try:
+ masses = np.array([x.mass for x in self.atoms])
+ except mda.exceptions.NoDataError:
+ masses = np.array(
+ [
+ data.elements.get(element, {"standard_mass": 0}).get(
+ "standard_mass"
+ )
+ for element in self.elements
+ ]
+ )
+ return masses
+
+ @property
+ def res_id(self) -> np.ndarray:
+ return self.atoms.resnums
+
+ @property
+ def frame(self) -> int:
+ return self.universe.trajectory.frame
+
+ @frame.setter
+ def frame(self, value) -> None:
+ if self.universe.trajectory.frame != value:
+ self.universe.trajectory[value]
+
+ @property
+ def res_name(self) -> np.ndarray:
+ return np.array(list(map(lambda x: x[0:3], self.atoms.resnames)))
+
+ @property
+ def res_num(self) -> np.ndarray:
+ return np.array(
+ [
+ data.residues.get(res_name, data.residues.get("UNK")).get(
+ "res_name_num"
+ )
+ for res_name in self.res_name
+ ]
+ )
+
+ @property
+ def b_factor(self) -> np.ndarray:
+ if hasattr(self.atoms, "tempfactors"):
+ return self.atoms.tempfactors
+ else:
+ return np.zeros(self.n_atoms)
+
+ @property
+ def segindices(self) -> np.ndarray:
+ if hasattr(self.atoms, "segindices"):
+ return self.atoms.segindices
+
+ @property
+ def chain_id(self) -> np.ndarray:
+ if hasattr(self.atoms, "chainIDs"):
+ return self.atoms.chainIDs
+ else:
+ return np.zeros(self.n_atoms)
+
+ @property
+ def chain_ids(self) -> np.ndarray:
+ return np.unique(self.chain_id)
+
+ @property
+ def chain_id_num(self) -> np.ndarray:
+ chain_ids, chain_id_index = np.unique(self.chain_id, return_inverse=True)
+ return chain_id_index
+
+ @property
+ def atom_type(self) -> np.ndarray:
+ return self.atoms.types
+
+ @property
+ def atom_type_unique(self) -> np.ndarray:
+ return np.unique(self.atom_type)
+
+ @property
+ def atom_type_num(self) -> np.ndarray:
+ atom_type_unique, atom_type_index = np.unique(
+ self.atom_type, return_inverse=True
+ )
+ return atom_type_index
+
+ @property
+ def atom_name(self) -> np.ndarray:
+ if hasattr(self.atoms, "names"):
+ return self.atoms.names
+ else:
+ return np.zeros(self.n_atoms)
+
+ @property
+ def atom_name_num(self) -> np.ndarray:
+ if hasattr(self.atoms, "names"):
+ return np.array(
+ list(map(lambda x: data.atom_names.get(x, -1), self.atom_name))
+ )
+ else:
+ return np.repeat(-1, self.n_atoms)
+
+ @property
+ def is_nucleic(self) -> np.ndarray:
+ return self.bool_selection(self.atoms, "nucleic")
+
+ @property
+ def is_peptide(self) -> np.ndarray:
+ return self.bool_selection(self.atoms, "protein or (name BB SC*)")
+
+ @property
+ def is_lipid(self) -> np.ndarray:
+ return np.isin(self.atoms.resnames, data.lipid_names)
+
+ @property
+ def is_backbone(self) -> np.ndarray:
+ return self.bool_selection(self.atoms, "backbone or nucleicbackbone or name BB")
+
+ @property
+ def is_alpha_carbon(self) -> np.ndarray:
+ return self.bool_selection(self.atoms, "name CA or name BB")
+
+ @property
+ def is_solvent(self) -> np.ndarray:
+ return self.bool_selection(
+ self.atoms, "name OW or name HW1 or name HW2 or resname W or resname PW"
+ )
+
+ @property
+ def _attributes_2_blender(self):
+ """
+ The attributes that will be added to the Blender object.
+ """
+ return {
+ "atomic_number": {
+ "value": self.atomic_number,
+ "type": "INT",
+ "domain": "POINT",
+ },
+ "vdw_radii": {
+ "value": self.vdw_radii,
+ "type": "FLOAT",
+ "domain": "POINT",
+ },
+ "mass": {
+ "value": self.mass,
+ "type": "FLOAT",
+ "domain": "POINT",
+ },
+ "res_id": {
+ "value": self.res_id,
+ "type": "INT",
+ "domain": "POINT",
+ },
+ "segid": {
+ "value": self.segindices,
+ "type": "INT",
+ "domain": "POINT",
+ },
+ "res_name": {
+ "value": self.res_num,
+ "type": "INT",
+ "domain": "POINT",
+ },
+ "b_factor": {
+ "value": self.b_factor,
+ "type": "FLOAT",
+ "domain": "POINT",
+ },
+ "chain_id": {
+ "value": self.chain_id_num,
+ "type": "INT",
+ "domain": "POINT",
+ },
+ "atom_types": {
+ "value": self.atom_type_num,
+ "type": "INT",
+ "domain": "POINT",
+ },
+ "atom_name": {
+ "value": self.atom_name_num,
+ "type": "INT",
+ "domain": "POINT",
+ },
+ "is_backbone": {
+ "value": self.is_backbone,
+ "type": "BOOLEAN",
+ "domain": "POINT",
+ },
+ "is_alpha_carbon": {
+ "value": self.is_alpha_carbon,
+ "type": "BOOLEAN",
+ "domain": "POINT",
+ },
+ "is_solvent": {
+ "value": self.is_solvent,
+ "type": "BOOLEAN",
+ "domain": "POINT",
+ },
+ "is_nucleic": {
+ "value": self.is_nucleic,
+ "type": "BOOLEAN",
+ "domain": "POINT",
+ },
+ "is_lipid": {
+ "value": self.is_lipid,
+ "type": "BOOLEAN",
+ "domain": "POINT",
+ },
+ "is_peptide": {
+ "value": self.is_peptide,
+ "type": "BOOLEAN",
+ "domain": "POINT",
+ },
+ }
+
+ def create_object(
+ self,
+ style: str = "vdw",
+ name: str = "NewUniverseObject",
+ subframes: int = 0,
+ # in_memory: bool = False,
+ ):
+ obj = mesh.create_object(
+ name=name, collection=coll.mn(), vertices=self.positions, edges=self.bonds
+ )
+ self.object = obj
+
+ for att_name, att in self._attributes_2_blender.items():
+ try:
+ mesh.store_named_attribute(
+ obj, att_name, att["value"], att["type"], att["domain"]
+ )
+ except Exception as e:
+ print(e)
+
+ if hasattr(self.atoms, "segindices"):
+ segs = []
+ for seg in self.atoms.segments:
+ segs.append(seg.atoms[0].segid)
+
+ obj["segments"] = segs
+
+ obj["chain_ids"] = self.chain_ids
+ obj["atom_type_unique"] = self.atom_type_unique
+ self.subframes = subframes
+ obj.mn.molecule_type = "md"
+
+ if style is not None:
+ nodes.create_starting_node_tree(obj, style=style, name=f"MN_{obj.name}")
+
+ bpy.context.view_layer.objects.active = obj
+ obj.mn.uuid = self.uuid
+
+ return obj
+
+ def _update_calculations(self):
+ for name, func in self.calculations.items():
+ try:
+ self.store_named_attribute(name=name, data=func(self.universe))
+ except Exception as e:
+ print(e)
+
+ def _update_selections(self):
+ objs_to_update = [obj for obj in bpy.data.objects if obj.mn.uuid == self.uuid]
+
+ # mark all selections for cleanup if they are no longer relevant
+ for selection in self.selections.values():
+ selection.cleanup = True
+
+ for obj in objs_to_update:
+ for sel in obj.mn_trajectory_selections:
+ # try and get a corresponding selection for this named selection
+ # if the selection can't be found we create one
+ selection = self.selections.get(sel.name)
+ if selection is None:
+ selection = self.selection_from_ui(sel)
+ elif sel.updating:
+ # if the selection string has, or some of the parameters about it have
+ # changed then we have to change the selection's AtomGroup before we
+ # apply the selection to the mesh
+ if (
+ selection.selection_str != sel.selection_str
+ or selection.periodic != sel.periodic
+ ):
+ selection.change_selection(
+ selection_str=sel.selection_str,
+ name=sel.name,
+ updating=sel.updating,
+ periodic=sel.periodic,
+ )
+
+ # Apply the selection to the actual mesh in the form of a boolean
+ # named attribute
+ self.apply_selection(selection)
+ else:
+ pass
+
+ # mark the selection to not be cleaned up, and add any message from the
+ # selection to the UI selection item for display in the UI
+ selection.cleanup = False
+ sel.message = selection.message
+
+ # remove all of the attributes and selections that are marked for cleanup because
+ # they are no longer being used by any objects for selections
+ for name in list(self.selections):
+ if self.selections[name].cleanup:
+ try:
+ self.object.data.attributes.remove(
+ self.object.data.attributes[name]
+ )
+ self.selections.pop(name)
+ except Exception as e:
+ print(e)
+
+ def _update_positions(self, frame):
+ """
+ The function that will be called when the frame changes.
+ It will update the positions and selections of the atoms in the scene.
+ """
+ universe = self.universe
+ frame_mapping = self.frame_mapping
+ obj = self.object
+ if obj is None:
+ raise ObjectMissingError(
+ "Object is deleted and unable to establish a connection with a new Blender Object."
+ )
+ try:
+ subframes = obj.mn.subframes
+ interpolate = obj.mn.interpolate
+ except ReferenceError as e:
+ print(e)
+ return None
+
+ if frame < 0:
+ return None
+
+ if frame_mapping:
+ # add the subframes to the frame mapping
+ frame_map = np.repeat(frame_mapping, subframes + 1)
+ # get the current and next frames
+ frame_a = frame_map[frame]
+ frame_b = frame_map[frame + 1]
+
+ else:
+ # get the initial frame
+ if subframes == 0:
+ frame_a = frame
+ else:
+ frame_a = int(frame / (subframes + 1))
+
+ # get the next frame
+ frame_b = frame_a + 1
+
+ if frame_a >= universe.trajectory.n_frames:
+ return None
+
+ # set the trajectory at frame_a
+ self.frame = frame_a
+
+ if subframes > 0 and interpolate:
+ fraction = frame % (subframes + 1) / (subframes + 1)
+
+ # get the positions for the next frame
+ locations_a = self.positions
+
+ if frame_b < universe.trajectory.n_frames:
+ self.frame = frame_b
+ locations_b = self.positions
+
+ if obj.mn.correct_periodic and self.is_orthorhombic:
+ locations_b = correct_periodic_positions(
+ locations_a,
+ locations_b,
+ dimensions=universe.dimensions[:3] * self.world_scale,
+ )
+
+ # interpolate between the two sets of positions
+ locations = lerp(locations_a, locations_b, t=fraction)
+ else:
+ locations = self.positions
+
+ # update the positions of the underlying vertices and record which frame was used
+ # for setting these positions
+ self.set_position(locations)
+
+ def __repr__(self):
+ return f"= 0 and scene.trajectory_selection_list:
- item = scene.trajectory_selection_list[scene.list_index]
-
- col = layout.column(align=False)
- col.separator()
-
- col.prop(item, "name")
- col.prop(item, "selection")
-
-
-def panel(layout, scene):
- layout.label(text="Load MD Trajectories", icon="FILE_TICK")
- layout.separator()
- col = layout.column(align=True)
- row_import = col.row()
- row_import.prop(scene, "MN_import_md_name")
- row_import.operator("mn.import_protein_md", text="Load")
- col.separator()
- col.prop(scene, "MN_import_md_topology")
- col.prop(scene, "MN_import_md_trajectory")
-
- layout.separator()
- layout.label(text="Options", icon="MODIFIER")
- row = layout.row()
- row.prop(scene, "MN_import_node_setup", text="")
- col = row.column()
- col.prop(scene, "MN_import_style")
- col.enabled = scene.MN_import_node_setup
- layout.prop(scene, "MN_md_selection")
- row_frame = layout.row(heading="Frames", align=True)
- row_frame.prop(scene, "MN_md_in_memory")
- row = row_frame.row(align=True)
- row.prop(scene, "MN_import_md_frame_start")
- row.prop(scene, "MN_import_md_frame_step")
- row.prop(scene, "MN_import_md_frame_stop")
- row.enabled = scene.MN_md_in_memory
- custom_selections(layout, scene)
diff --git a/molecularnodes/io/parse/__init__.py b/molecularnodes/io/parse/__init__.py
deleted file mode 100644
index e19866d0..00000000
--- a/molecularnodes/io/parse/__init__.py
+++ /dev/null
@@ -1,13 +0,0 @@
-"""
-A subpackge which provides classes for parsing the different macromolecular data formats.
-"""
-
-from .pdbx import CIF, BCIF
-# from .bcif import BCIF
-# from .cif import CIF
-from .pdb import PDB
-from .cellpack import CellPack
-from .star import StarFile
-from .sdf import SDF
-from .mda import MDAnalysisSession
-from .mrc import MRC
diff --git a/molecularnodes/io/parse/mda.py b/molecularnodes/io/parse/mda.py
deleted file mode 100644
index 0e684da0..00000000
--- a/molecularnodes/io/parse/mda.py
+++ /dev/null
@@ -1,985 +0,0 @@
-import bpy
-from bpy.app.handlers import persistent
-
-try:
- import MDAnalysis as mda
-except ImportError:
- HAS_mda = False
- import types
-
- class MockAtomGroup:
- pass
-
- class MockUniverse:
- pass
-
- mda = types.ModuleType("MDAnalysis")
- mda.Universe = MockUniverse
- mda.AtomGroup = MockAtomGroup
- mda.core = types.ModuleType("core")
- mda.topology = types.ModuleType("topology")
-
-else:
- HAS_mda = True
-import numpy as np
-import warnings
-import pickle
-from typing import Union, List, Dict
-
-from ... import data
-from ...pkg import start_logging
-from ...blender import (
- coll, obj, nodes
-)
-from ...utils import lerp
-
-
-class AtomGroupInBlender:
- def __init__(self,
- ag: mda.AtomGroup,
- style: str = "vdw",
- world_scale: float = 0.01):
- """
- AtomGroup in Blender.
- It will be dynamically updated when the frame changes or
- when the topology of the underlying atoms changes.
-
- Parameters:
- ----------
- ag : MDAnalysis.AtomGroup
- The atomgroup to add in the scene.
- style : str, optional
- The style of the atoms (default: "vdw").
- world_scale : float, optional
- The scaling factor for the world coordinates (default: 0.01).
-
- Attributes:
- ----------
- ag : MDAnalysis.AtomGroup
- The atomgroup to add in the scene.
- world_scale : float
- The scaling factor for the world coordinates.
- style : str
- The style of the atoms in Blender.
- n_atoms : int
- The number of atoms in the atomgroup.
- positions : np.ndarray
- The positions of the atoms in the atomgroup.
- elements : list
- The elements of the atoms in the atomgroup.
- If the elements are not available,
- then the elements are guessed from the atom names.
- atomic_number : np.ndarray
- The atomic numbers of the atoms in the atomgroup
- based on their elements.
- vdw_radii : np.ndarray
- The van der Waals radii of the atoms in the atomgroup
- based on their elements.
- res_id : np.ndarray
- The residue ids of the atoms in the atomgroup.
- res_name : np.ndarray
- The residue names of the atoms in the atomgroup.
- res_num : np.ndarray
- The residue numbers of the atoms in the atomgroup
- The residue numbers are based on the residue names
- and are stored in the data.residues dictionary.
- b_factor : np.ndarray
- The B-factors of the atoms in the atomgroup.
- chain_id : np.ndarray
- The chain ids of the atoms in the atomgroup.
- chain_id_num : np.ndarray
- The chain id numbers of the atoms in the atomgroup.
- It is the index of the unique chain ids.
- atom_type : np.ndarray
- The atom types of the atoms in the atomgroup.
- atom_type_unique : np.ndarray
- The unique atom types of the atoms in the atomgroup.
- atom_type_num : np.ndarray
- The atom type numbers of the atoms in the atomgroup.
- It is the index of the unique atom types.
- is_nucleic : np.ndarray
- Whether the atoms in the atomgroup are nucleic.
- is_peptide : np.ndarray
- Whether the atoms in the atomgroup are peptide.
- is_backbone : np.ndarray
- Whether the atoms in the atomgroup are backbone.
- is_alpha_carbon : np.ndarray
- Whether the atoms in the atomgroup are alpha carbon.
- is_solvent : np.ndarray
- Whether the atoms in the atomgroup are solvent.
- """
- if not HAS_mda:
- raise ImportError("MDAnalysis is not installed.")
- self.ag = ag
- self.world_scale = world_scale
- self.style = style
-
- @property
- def n_atoms(self) -> int:
- return self.ag.n_atoms
-
- @property
- def style(self) -> str:
- return self._style
-
- @style.setter
- def style(self, style):
- self._style = style
-
- @staticmethod
- def bool_selection(ag, selection) -> np.ndarray:
- return np.isin(ag.ix, ag.select_atoms(selection).ix).astype(bool)
-
- @property
- def positions(self) -> np.ndarray:
- return self.ag.positions * self.world_scale
-
- @property
- def bonds(self) -> List[List[int]]:
- if hasattr(self.ag, "bonds"):
- bond_indices = self.ag.bonds.indices
- atm_indices = self.ag.indices
- bond_filtering = np.all(np.isin(bond_indices, atm_indices), axis=1)
- bond_indices = bond_indices[bond_filtering]
-
- index_map = {index: i for i, index in enumerate(self.ag.indices)}
-
- bonds = [[index_map[bond[0]], index_map[bond[1]]]
- for bond in bond_indices]
- else:
- bonds = []
- return bonds
-
- @property
- def elements(self) -> List[str]:
- try:
- elements = self.ag.elements.tolist()
- except:
- try:
- elements = [
- x if x in data.elements.keys() else
- mda.topology.guessers.guess_atom_element(x) for x in self.ag.atoms.names]
-
- except:
- elements = ['X'] * self.ag.n_atoms
- return elements
-
- @property
- def atomic_number(self) -> np.ndarray:
- return np.array(
- [data.elements.get(element,
- data.elements.get('X'))
- .get('atomic_number') for element in self.elements]
- )
-
- @property
- def vdw_radii(self) -> np.ndarray:
- # pm to Angstrom
- return np.array(
- [data.elements.get(element,{}).get(
- 'vdw_radii',100) for element in self.elements]) * 0.01 * self.world_scale
-
- @property
- def mass(self) -> np.ndarray:
- # units: daltons
- try:
- masses = np.array([x.mass for x in self.ag.atoms])
- except mda.exceptions.NoDataError:
- masses = np.array(
- [data.elements.get(element,
- {'standard_mass': 0})
- .get('standard_mass') for element in self.elements])
- return masses
-
- @property
- def res_id(self) -> np.ndarray:
- return self.ag.resnums
-
- @property
- def res_name(self) -> np.ndarray:
- return np.array(list(map(lambda x: x[0:3], self.ag.resnames)))
-
- @property
- def res_num(self) -> np.ndarray:
- return np.array(
- [data.residues.get(res_name,
- data.residues.get('UNK'))
- .get('res_name_num') for res_name in self.res_name]
- )
-
- @property
- def b_factor(self) -> np.ndarray:
- if hasattr(self.ag, "tempfactors"):
- return self.ag.tempfactors
- else:
- return np.zeros(self.ag.n_atoms)
-
- @property
- def chain_id(self) -> np.ndarray:
- if hasattr(self.ag, "chainIDs"):
- return self.ag.chainIDs
- else:
- return np.zeros(self.ag.n_atoms)
-
- @property
- def chain_ids(self) -> np.ndarray:
- return np.unique(self.chain_id)
-
- @property
- def chain_id_num(self) -> np.ndarray:
- chain_ids, chain_id_index = np.unique(
- self.chain_id, return_inverse=True)
- return chain_id_index
-
- @property
- def atom_type(self) -> np.ndarray:
- return self.ag.types
-
- @property
- def atom_type_unique(self) -> np.ndarray:
- return np.unique(self.atom_type)
-
- @property
- def atom_type_num(self) -> np.ndarray:
- atom_type_unique, atom_type_index = np.unique(
- self.atom_type, return_inverse=True)
- return atom_type_index
-
- @property
- def atom_name(self) -> np.ndarray:
- if hasattr(self.ag, "names"):
- return self.ag.names
- else:
- return np.zeros(self.ag.n_atoms)
-
- @property
- def atom_name_num(self) -> np.ndarray:
- if hasattr(self.ag, "names"):
- return np.array(list(map(lambda x: data.atom_names.get(x, -1), self.atom_name)))
- else:
- return np.repeat(-1, self.ag.n_atoms)
-
- @property
- def is_nucleic(self) -> np.ndarray:
- return self.bool_selection(self.ag, "nucleic")
-
- @property
- def is_peptide(self) -> np.ndarray:
- return self.bool_selection(self.ag, "protein or (name BB SC*)")
-
- @property
- def is_lipid(self) -> np.ndarray:
- return np.isin(self.ag.resnames, data.lipid_names)
-
- @property
- def is_backbone(self) -> np.ndarray:
- return self.bool_selection(self.ag, "backbone or nucleicbackbone or name BB")
-
- @property
- def is_alpha_carbon(self) -> np.ndarray:
- return self.bool_selection(self.ag, "name CA or name BB")
-
- @property
- def is_solvent(self) -> np.ndarray:
- return self.bool_selection(self.ag, "name OW or name HW1 or name HW2 or resname W or resname PW")
-
- @property
- def _attributes_2_blender(self):
- """
- The attributes that will be added to the Blender object.
- """
- return {
- "atomic_number": {
- "value": self.atomic_number,
- "type": "INT",
- "domain": "POINT",
- },
- "vdw_radii": {
- "value": self.vdw_radii,
- "type": "FLOAT",
- "domain": "POINT",
- },
- "mass": {
- "value": self.mass,
- "type": "FLOAT",
- "domain": "POINT",
- },
- "res_id": {
- "value": self.res_id,
- "type": "INT",
- "domain": "POINT",
- },
- "res_name": {
- "value": self.res_num,
- "type": "INT",
- "domain": "POINT",
- },
- "b_factor": {
- "value": self.b_factor,
- "type": "FLOAT",
- "domain": "POINT",
- },
- "chain_id": {
- "value": self.chain_id_num,
- "type": "INT",
- "domain": "POINT",
- },
- "atom_types": {
- "value": self.atom_type_num,
- "type": "INT",
- "domain": "POINT",
- },
- "atom_name": {
- "value": self.atom_name_num,
- "type": "INT",
- "domain": "POINT"
- },
- "is_backbone": {
- "value": self.is_backbone,
- "type": "BOOLEAN",
- "domain": "POINT",
- },
- "is_alpha_carbon": {
- "value": self.is_alpha_carbon,
- "type": "BOOLEAN",
- "domain": "POINT",
- },
- "is_solvent": {
- "value": self.is_solvent,
- "type": "BOOLEAN",
- "domain": "POINT",
- },
- "is_nucleic": {
- "value": self.is_nucleic,
- "type": "BOOLEAN",
- "domain": "POINT",
- },
- "is_lipid": {
- "value": self.is_lipid,
- "type": "BOOLEAN",
- "domain": "POINT",
- },
- "is_peptide": {
- "value": self.is_peptide,
- "type": "BOOLEAN",
- "domain": "POINT",
- },
- }
-
-
-class MDAnalysisSession:
- """
- The MDAnalysis session.
-
- The MDAnalysis session is the main class that stores the
- MDAnalysis data in Blender.
- It is a singleton class that is initialized when the first
- MDAnalysis data is loaded in Blender.
- The MDAnalysis session is loaded when Blender is restarted.
- The MDAnalysis session is updated when the frame changes.
- When a Blender file is saved, the MDAnalysis session will be
- dumped (with pickle) to the same place as the Blender file
- with .mda_session extension.
-
- Parameters:
- ----------
- world_scale : float, optional
- The scaling factor for the world coordinates (default: 0.01).
-
- Attributes:
- ----------
- world_scale : float
- The scaling factor for the world coordinates.
- universe_reps : dict
- A dictionary of the universes in the session.
- atom_reps : dict
- A dictionary of the atom styles in the session.
- rep_names : list
- A list of the names of the styles in the session.
-
- Methods:
- -------
- show(atoms, style, selection, name, custom_selections, frame_offset)
- Display an `MDAnalysis.Universe` or `MDAnalysis.Atomgroup` in Blender.
- in_memory(atoms, style, selection, name, custom_selections)
- Display an `MDAnalysis.Universe` or `MDAnalysis.Atomgroup` in Blender by loading all the
- frames as individual objects. Animation depends on the machinery inside geometric node.
- transfer_to_memory(start, stop, step, verbose, **kwargs)
- Transfer the trajectories in the session to memory.
- """
-
- def __init__(self, world_scale: float = 0.01, in_memory: bool = False):
- """
- Initialize a MDAnalysisSession.
-
- During saving, the session is pickled/serialized to the same
- location as the blend file with the extension .mda_session.
- The session is loaded when Blender is restarted.
-
- #TODO: Is it possible to start blender only when
- #a session is initialized? (Probably not for now)
-
- Parameters:
- ----------
- world_scale : float, optional
- The scaling factor for the world coordinates (default: 0.01).
- memory : bool, optional
- Whether the old import is used (default: False).
- """
- log = start_logging(logfile_name="mda")
- if not HAS_mda:
- raise ImportError("MDAnalysis is not installed.")
-
- # if the session already exists, load the existing session
- if hasattr(bpy.types.Scene, "mda_session"):
- warnings.warn("The existing mda session is loaded.")
- log.warning("The existing mda session is loaded.")
- existing_session = bpy.types.Scene.mda_session
- self.__dict__ = existing_session.__dict__
- return
-
- self.world_scale = world_scale
- self.universe_reps = {}
- self.atom_reps = {}
- self.rep_names = []
-
- if in_memory:
- return
- bpy.types.Scene.mda_session = self
- bpy.app.handlers.frame_change_post.append(
- self._update_trajectory_handler_wrapper()
- )
- bpy.app.handlers.depsgraph_update_pre.append(
- self._update_style_handler_wrapper()
- )
- log.info("MDAnalysis session is initialized.")
-
- @property
- def universe(self) -> mda.Universe:
- """
- The universe of the current active object.
- If the current active object is not an atom style,
- then the first atom style is used.
- """
- name = bpy.context.view_layer.objects.active.name
- try:
- return self.universe_reps[name]["universe"]
- except KeyError:
- return self.universe_reps[self.rep_names[0]]["universe"]
-
- def show(
- self,
- atoms: Union[mda.Universe, mda.AtomGroup],
- style: str = "vdw",
- selection: str = "all",
- name: str = "atoms",
- custom_selections: Dict[str, str] = {},
- frame_mapping: np.ndarray = None,
- subframes: int = 0,
- in_memory: bool = False
- ):
- """
- Display an `MDAnalysis.Universe` or
- `MDAnalysis.Atomgroup` in Blender.
-
- Parameters:
- ----------
- atoms : MDAnalysis.Universe or MDAnalysis.Atomgroup
- The universe to load into blender.
- style : str, optional
- The style to represent the atoms inside of Blender
- (default: "vdw").
- selection : str, optional
- The selection string for atom filtering
- (default: "all").
- Uses MDAnalysis selection syntax.
- name : str, optional
- The name of the default atoms
- (default: "atoms").
- custom_selections : dict, optional
- A dictionary of custom selections for atom filtering with
- {'name' : 'selection string'}
- (default: {}).
- Uses MDAnalysis selection syntax.
- frame_mapping : np.ndarray, optional
- A mapping from the frame indices in the Blender frame indices.
- for example a frame_mapping of [0, 0, 1, 1, 2, 3] will map
- the 1st frame (index 0) in the trajectory to the 1st and 2nd frames
- in Blender and so on.
- Note a subframes other than 1 will expand the frame_mapping from its
- original length to (subframes + 1) * original length.
- (default: None) which will map the frames in the trajectory
- to the frames in Blender one-to-one.
- subframes : int, optional
- The number of subframes to interpolate between each frame.
- (default: 0).
- in_memory : bool, optional
- Whether load the display in Blender by loading all the
- frames as individual objects.
- (default: False)
- """
- log = start_logging(logfile_name="mda")
- if in_memory:
- mol_object = self.in_memory(
- atoms=atoms,
- style=style,
- selection=selection,
- name=name,
- custom_selections=custom_selections
- )
- if frame_mapping is not None:
- warnings.warn("Custom frame_mapping not supported"
- "when in_memory is on.")
- if subframes != 0:
- warnings.warn("Custom subframes not supported"
- "when in_memory is on.")
- log.info(f"{atoms} is loaded in memory.")
- return mol_object
- if isinstance(atoms, mda.Universe):
- atoms = atoms.select_atoms(selection)
-
- universe = atoms.universe
-
- # if any frame_mapping is out of range, then raise an error
- if frame_mapping and (len(frame_mapping) > universe.trajectory.n_frames):
- raise ValueError("one or more mapping values are"
- "out of range for the trajectory")
-
- mol_object = self._process_atomgroup(
- ag=atoms,
- frame_mapping=frame_mapping,
- subframes=subframes,
- name=name,
- style=style,
- return_object=True)
-
- # add the custom selections if they exist
- for sel_name, sel in custom_selections.items():
- try:
- ag = universe.select_atoms(sel)
- if ag.n_atoms == 0:
- raise ValueError("Selection is empty")
- self._process_atomgroup(
- ag=ag,
- frame_mapping=frame_mapping,
- subframes=subframes,
- name=sel_name,
- style=style,
- return_object=False
- )
- except ValueError:
- warnings.warn(
- "Unable to add custom selection: {}".format(name))
-
- bpy.context.view_layer.objects.active = mol_object
- log.info(f"{atoms} is loaded.")
- return mol_object
-
- def in_memory(
- self,
- atoms: Union[mda.Universe, mda.AtomGroup],
- style: str = "vdw",
- selection: str = "all",
- name: str = "atoms",
- custom_selections: Dict[str, str] = {},
- node_setup: bool = True
- ):
- """
- Display an `MDAnalysis.Universe` or
- `MDAnalysis.Atomgroup` in Blender by loading all the
- frames as individual objects. Animation depends on the machinery inside geometric node.
-
- Parameters:
- ----------
- atoms : MDAnalysis.Universe or MDAnalysis.Atomgroup
- The universe to load into blender.
- style : str, optional
- The style used to represent the atoms inside of Blender
- (default: "vdw").
- selection : str, optional
- The selection string for atom filtering
- (default: "all").
- Uses MDAnalysis selection syntax.
- name : str, optional
- The name of the default atoms
- (default: "atoms").
- custom_selections : dict, optional
- A dictionary of custom selections for atom filtering with
- {'name' : 'selection string'}
- (default: {}).
- Uses MDAnalysis selection syntax.
- node_setup : bool
- Whether to add the node tree for the atomgroup. Default: True
- """
- if isinstance(atoms, mda.Universe):
- atoms = atoms.select_atoms(selection)
-
- universe = atoms.universe
-
- mol_object = self._process_atomgroup(
- ag=atoms,
- name=name,
- style=style,
- node_setup=False,
- return_object=True,
- )
-
- for sel_name, sel in custom_selections.items():
- obj.set_attribute(
- object=mol_object,
- name=sel_name,
- data=AtomGroupInBlender.bool_selection(atoms, sel),
- type="BOOLEAN",
- domain="POINT",
- )
-
- coll_frames = coll.frames(name)
-
- # TODO: refractor it as a general feature
- add_occupancy = True
- for ts in universe.trajectory:
- frame = obj.create_object(
- name=name + "_frame_" + str(ts.frame),
- collection=coll_frames,
- vertices=atoms.positions * self.world_scale,
- )
- # adds occupancy data to each frame if it exists
- # This is mostly for people who want to store frame-specific information in the
- # b_factor but currently neither biotite nor MDAnalysis give access to frame-specific
- # b_factor information. MDAnalysis gives frame-specific access to the `occupancy`
- # so currently this is the only method to get frame-specific data into MN
- # for more details: https://github.com/BradyAJohnston/MolecularNodes/issues/128
- if add_occupancy:
- try:
- obj.set_attribute(frame, "occupancy", ts.data["occupancy"])
- except:
- add_occupancy = False
-
- # disable the frames collection from the viewer
- bpy.context.view_layer.layer_collection.children[coll.mn().name].children[
- coll_frames.name
- ].exclude = True
-
- if node_setup:
- nodes.create_starting_node_tree(
- object=mol_object,
- coll_frames=coll_frames,
- style=style,
- )
-
- bpy.context.view_layer.objects.active = mol_object
-
- return mol_object
-
- def transfer_to_memory(
- self, start=None, stop=None, step=None, verbose=False, **kwargs
- ):
- """
- Transfer the trajectories in the session to memory.
- This is an alternative way to make sure the blender session is
- independent of the original trajectory file.
-
- Parameters:
- ----------
- start : int, optional
- The first frame to transfer (default: None).
- If None, then the first frame of the trajectory is used.
- stop : int, optional
- The last frame to transfer (default: None).
- If None, then the last frame of the trajectory is used.
- step : int, optional
- The step between frames (default: None).
- If None, then the step is 1.
- verbose : bool, optional
- Whether to print the progress (default: False).
- """
- log = start_logging(logfile_name="mda")
- warnings.warn(
- "The trajectories in this session \n"
- "is transferred to memory. \n"
- "It is different from the in_memory loading \n"
- "because it uses the MemoryReader in MDAnalysis. \n"
- "instead of loading all the frames as individual objects. \n"
- "in Blender. \n"
- )
-
- for rep_name in self.rep_names:
- universe = self.universe_reps[rep_name]["universe"]
- universe.transfer_to_memory(
- start=start, stop=stop, step=step, verbose=verbose, **kwargs
- )
- log.info("The trajectories in this session is transferred to memory.")
-
- def _process_atomgroup(
- self,
- ag,
- frame_mapping=None,
- subframes=0,
- name="atoms",
- style="vdw",
- node_setup=True,
- return_object=False,
- ):
- """
- process the atomgroup in the Blender scene.
-
- Parameters:
- ----------
- ag : MDAnalysis.AtomGroup
- The atomgroup to add in the scene.
- frame_mapping : np.ndarray
- The frame mapping for the trajectory in Blender frame indices. Default: None
- subframes : int
- The number of subframes to interpolate between each frame.
- name : str
- The name of the atomgroup. Default: 'atoms'
- style : str
- The style of the atoms. Default: 'vdw'
- node_setup : bool
- Whether to add the node tree for the atomgroup. Default: True
- return_object : bool
- Whether to return the blender object or not. Default: False
- """
- ag_blender = AtomGroupInBlender(
- ag=ag,
- style=style,
- world_scale=self.world_scale
- )
- # create the initial model
- mol_object = obj.create_object(
- name=name,
- collection=coll.mn(),
- vertices=ag_blender.positions,
- edges=ag_blender.bonds,
- )
-
- # add the attributes for the model in blender
- for att_name, att in ag_blender._attributes_2_blender.items():
- obj.set_attribute(
- mol_object, att_name, att["value"], att["type"], att["domain"]
- )
- mol_object['chain_ids'] = ag_blender.chain_ids
- mol_object['atom_type_unique'] = ag_blender.atom_type_unique
- mol_object.mn['subframes'] = subframes
- mol_object.mn['molecule_type'] = 'md'
-
- # add the atomgroup to the session
- # the name of the atomgroup may be different from
- # the input name because of the uniqueness requirement
- # of the blender object name.
- # instead, the name generated by blender is used.
- if mol_object.name != name:
- warnings.warn(
- "The name of the object is changed to {} because {} is already used.".format(
- mol_object.name, name
- )
- )
-
- self.atom_reps[mol_object.name] = ag_blender
- self.universe_reps[mol_object.name] = {
- "universe": ag.universe,
- "frame_mapping": frame_mapping,
- }
- self.rep_names.append(mol_object.name)
-
- # for old import, the node tree is added all at once
- # in the end of in_memory
- if node_setup:
- nodes.create_starting_node_tree(
- object=mol_object,
- style=style,
- )
-
- if return_object:
- return mol_object
-
- @persistent
- def _update_trajectory(self, frame):
- """
- The function that will be called when the frame changes.
- It will update the positions and selections of the atoms in the scene.
- """
- for rep_name in self.rep_names:
- universe = self.universe_reps[rep_name]["universe"]
- frame_mapping = self.universe_reps[rep_name]["frame_mapping"]
- subframes = bpy.data.objects[rep_name].mn['subframes']
-
- if frame < 0:
- continue
-
- if frame_mapping:
- # add the subframes to the frame mapping
- frame_map = np.repeat(frame_mapping, subframes + 1)
- # get the current and next frames
- frame_a = frame_map[frame]
- frame_b = frame_map[frame + 1]
-
- else:
- # get the initial frame
- if subframes == 0:
- frame_a = frame
- else:
- frame_a = int(frame / (subframes + 1))
-
- # get the next frame
- frame_b = frame_a + 1
-
- if frame_a >= universe.trajectory.n_frames:
- continue
-
- ag_rep = self.atom_reps[rep_name]
- mol_object = bpy.data.objects[rep_name]
-
- # set the trajectory at frame_a
- universe.trajectory[frame_a]
-
- if subframes > 0:
- fraction = frame % (subframes + 1) / (subframes + 1)
-
- # get the positions for the next frame
- locations_a = ag_rep.positions
-
- if frame_b < universe.trajectory.n_frames:
- universe.trajectory[frame_b]
- locations_b = ag_rep.positions
-
- # interpolate between the two sets of positions
- locations = lerp(locations_a, locations_b, t=fraction)
- else:
- locations = ag_rep.positions
-
- # if the class of AtomGroup is UpdatingAtomGroup
- # then update as a new mol_object
- if isinstance(ag_rep.ag, mda.core.groups.UpdatingAtomGroup):
- mol_object.data.clear_geometry()
- mol_object.data.from_pydata(
- ag_rep.positions,
- ag_rep.bonds,
- faces=[])
- for att_name, att in ag_rep._attributes_2_blender.items():
- obj.set_attribute(
- mol_object, att_name, att["value"], att["type"], att["domain"]
- )
- mol_object['chain_id'] = ag_rep.chain_ids
- mol_object['atom_type_unique'] = ag_rep.atom_type_unique
- mol_object.mn['subframes'] = subframes
- else:
- # update the positions of the underlying vertices
- obj.set_attribute(mol_object, 'position', locations)
-
- @persistent
- def _update_trajectory_handler_wrapper(self):
- """
- A wrapper for the update_trajectory function because Blender
- requires the function to be taking one argument.
- """
- def update_trajectory_handler(scene):
- frame = scene.frame_current
- self._update_trajectory(frame)
-
- return update_trajectory_handler
-
- @persistent
- def _update_style_handler_wrapper(self):
- """
- A wrapper for the update_style function because Blender
- requires the function to be taking one argument.
- """
- def update_style_handler(scene):
- self._remove_deleted_mol_objects()
- # TODO: check for topology changes
- # TODO: update for style changes
-
- return update_style_handler
-
- @persistent
- def _remove_deleted_mol_objects(self):
- """
- Remove the deleted mol objects (e.g. due to operations inside Blender)
- from the session.
- """
- for rep_name in self.rep_names:
- if rep_name not in bpy.data.objects:
- self.rep_names.remove(rep_name)
- del self.atom_reps[rep_name]
- del self.universe_reps[rep_name]
-
- def _dump(self, blender_save_loc):
- """
- Dump the session as a pickle file
- """
- log = start_logging(logfile_name="mda")
- # get blender_save_loc
- blender_save_loc = blender_save_loc.split(".blend")[0]
- with open(f"{blender_save_loc}.mda_session", "wb") as f:
- pickle.dump(self, f)
- log.info("MDAnalysis session is dumped to {}".
- format(blender_save_loc))
-
- @classmethod
- def _rejuvenate(cls, mol_objects):
- """
- Rejuvenate the session from a pickle file in the default location
- (`~/.blender_mda_session/`).
- """
- log = start_logging(logfile_name="mda")
-
- # get session name from mol_objects dictionary
- blend_file_name = bpy.data.filepath.split(".blend")[0]
- try:
- with open(f"{blend_file_name}.mda_session", "rb") as f:
- cls = pickle.load(f)
- except FileNotFoundError:
- return None
- bpy.app.handlers.frame_change_post.append(
- cls._update_trajectory_handler_wrapper()
- )
- bpy.app.handlers.depsgraph_update_pre.append(
- cls._update_style_handler_wrapper()
- )
- log.info("MDAnalysis session is loaded from {}".
- format(blend_file_name))
- return cls
-
-
-@persistent
-def _rejuvenate_universe(scene):
- """
- Rejuvenate the session when the old Blend file is loaded.
- It will search through all the objects in the scene and
- find the ones that are molecules.
- It requires the pkl file to be in the default location and
- still exist.
-
- Warning:
- -------
- When a Blend file saved from another computer is loaded,
- the session will likely be lost.
- The Blend file also need to be opened from the same place
- (working directory) as when it is saved.
- """
- mol_objects = {}
- for object in bpy.data.objects:
- try:
- obj_type = object["type"]
- if obj_type == "molecule":
- mol_objects[object.name] = object
- except KeyError:
- pass
-
- if len(mol_objects) > 0:
- bpy.types.Scene.mda_session = MDAnalysisSession._rejuvenate(
- mol_objects)
-
-
-@persistent
-def _sync_universe(scene):
- """
- Sync the universe when the Blend file is saved.
- It will be saved as a .mda_session file in the
- same place as the Blend file).
- """
- if hasattr(bpy.types.Scene, "mda_session"):
- blender_save_loc = bpy.data.filepath
- if bpy.types.Scene.mda_session is not None:
- bpy.types.Scene.mda_session._dump(blender_save_loc)
diff --git a/molecularnodes/io/parse/star.py b/molecularnodes/io/parse/star.py
deleted file mode 100644
index b6a273a5..00000000
--- a/molecularnodes/io/parse/star.py
+++ /dev/null
@@ -1,219 +0,0 @@
-import numpy as np
-import bpy
-from .ensemble import Ensemble
-from ... import blender as bl
-
-@bpy.app.handlers.persistent
-def _rehydrate_ensembles(scene):
- for obj in bpy.data.objects:
- if hasattr(obj, 'mn') and 'molecule_type' in obj.mn.keys():
- if obj.mn['molecule_type'] == 'star':
- ensemble = StarFile.from_blender_object(obj)
- if not hasattr(bpy.types.Scene, 'MN_starfile_ensembles'):
- bpy.types.Scene.MN_starfile_ensembles = []
- bpy.types.Scene.MN_starfile_ensembles.append(ensemble)
-
-class StarFile(Ensemble):
- def __init__(self, file_path):
- super().__init__(file_path)
-
-
- @classmethod
- def from_starfile(cls, file_path):
- self = cls(file_path)
- self.data = self._read()
- self.star_type = None
- self.positions = None
- self.current_image = -1
- self._create_mn_columns()
- self.n_images = self._n_images()
- return self
-
- @classmethod
- def from_blender_object(cls, blender_object):
- import bpy
- self = cls(blender_object["starfile_path"])
- self.object = blender_object
- self.star_node = bl.nodes.get_star_node(self.object)
- self.micrograph_material = bl.nodes.MN_micrograph_material()
- self.data = self._read()
- self.star_type = None
- self.positions = None
- self.current_image = -1
- self._create_mn_columns()
- self.n_images = self._n_images()
- bpy.app.handlers.depsgraph_update_post.append(self._update_micrograph_texture)
- return self
-
-
- def _read(self):
- import starfile
- star = starfile.read(self.file_path)
- return star
-
- def _n_images(self):
- if isinstance(self.data, dict):
- return len(self.data)
- return 1
-
- def _create_mn_columns(self):
- # only RELION 3.1 and cisTEM STAR files are currently supported, fail gracefully
- if isinstance(self.data, dict) and 'particles' in self.data and 'optics' in self.data:
- self.star_type = 'relion'
- elif "cisTEMAnglePsi" in self.data:
- self.star_type = 'cistem'
- else:
- raise ValueError(
- 'File is not a valid RELION>=3.1 or cisTEM STAR file, other formats are not currently supported.'
- )
-
- # Get absolute position and orientations
- if self.star_type == 'relion':
- df = self.data['particles'].merge(self.data['optics'], on='rlnOpticsGroup')
-
- # get necessary info from dataframes
- # Standard cryoEM starfile don't have rlnCoordinateZ. If this column is not present
- # Set it to "0"
- if "rlnCoordinateZ" not in df:
- df['rlnCoordinateZ'] = 0
-
- self.positions = df[['rlnCoordinateX', 'rlnCoordinateY',
- 'rlnCoordinateZ']].to_numpy()
- pixel_size = df['rlnImagePixelSize'].to_numpy().reshape((-1, 1))
- self.positions = self.positions * pixel_size
- shift_column_names = ['rlnOriginXAngst',
- 'rlnOriginYAngst', 'rlnOriginZAngst']
- if all([col in df.columns for col in shift_column_names]):
- shifts_ang = df[shift_column_names].to_numpy()
- self.positions -= shifts_ang
- df['MNAnglePhi'] = df['rlnAngleRot']
- df['MNAngleTheta'] = df['rlnAngleTilt']
- df['MNAnglePsi'] = df['rlnAnglePsi']
- df['MNPixelSize'] = df['rlnImagePixelSize']
- try:
- df['MNImageId'] = df['rlnMicrographName'].astype(
- 'category').cat.codes.to_numpy()
- except KeyError:
- try:
- df['MNImageId'] = df['rlnTomoName'].astype(
- 'category').cat.codes.to_numpy()
- except KeyError:
- df['MNImageId'] = 0.0
-
- self.data = df
-
- elif self.star_type == 'cistem':
- df = self.data
- df['cisTEMZFromDefocus'] = (
- df['cisTEMDefocus1'] + df['cisTEMDefocus2']) / 2
- df['cisTEMZFromDefocus'] = df['cisTEMZFromDefocus'] - \
- df['cisTEMZFromDefocus'].median()
- self.positions = df[['cisTEMOriginalXPosition',
- 'cisTEMOriginalYPosition', 'cisTEMZFromDefocus']].to_numpy()
- df['MNAnglePhi'] = df['cisTEMAnglePhi']
- df['MNAngleTheta'] = df['cisTEMAngleTheta']
- df['MNAnglePsi'] = df['cisTEMAnglePsi']
- df['MNPixelSize'] = df['cisTEMPixelSize']
- df['MNImageId'] = df['cisTEMOriginalImageFilename'].astype(
- 'category').cat.codes.to_numpy()
-
- def _convert_mrc_to_tiff(self):
- import mrcfile
- from pathlib import Path
- if self.star_type == 'relion':
- micrograph_path = self.object['rlnMicrographName_categories'][self.star_node.inputs['Image'].default_value - 1]
- elif self.star_type == 'cistem':
- micrograph_path = self.object['cisTEMOriginalImageFilename_categories'][self.star_node.inputs['Image'].default_value - 1].strip("'")
- else:
- return False
-
- # This could be more elegant
- if not Path(micrograph_path).exists():
- pot_micrograph_path = Path(self.file_path).parent / micrograph_path
- if not pot_micrograph_path.exists():
- if self.star_type == 'relion':
- pot_micrograph_path = Path(self.file_path).parent.parent.parent / micrograph_path
- if not pot_micrograph_path.exists():
- raise FileNotFoundError(f"Micrograph file {micrograph_path} not found")
- else:
- raise FileNotFoundError(f"Micrograph file {micrograph_path} not found")
- micrograph_path = pot_micrograph_path
-
- tiff_path = Path(micrograph_path).with_suffix('.tiff')
- if not tiff_path.exists():
- with mrcfile.open(micrograph_path) as mrc:
- micrograph_data = mrc.data.copy()
-
- # For 3D data sum over the z axis. Probalby would be nicer to load the data as a volume
- if micrograph_data.ndim == 3:
- micrograph_data = np.sum(micrograph_data, axis=0)
- # Normalize the data to 0-1
- micrograph_data = (micrograph_data - micrograph_data.min()) / (micrograph_data.max() - micrograph_data.min())
-
- if micrograph_data.dtype != np.float32:
- micrograph_data = micrograph_data.astype(np.float32)
- from PIL import Image
- # Need to invert in Y to generate the correct tiff
- Image.fromarray(micrograph_data[::-1,:]).save(tiff_path)
- return tiff_path
-
- def _update_micrograph_texture(self, *_):
- try:
- show_micrograph = self.star_node.inputs['Show Micrograph']
- _ = self.object['mn']
- except ReferenceError:
- bpy.app.handlers.depsgraph_update_post.remove(self._update_micrograph_texture)
- return
- if self.star_node.inputs['Image'].default_value == self.current_image:
- return
- else:
- self.current_image = self.star_node.inputs['Image'].default_value
- if not show_micrograph:
- return
- tiff_path = self._convert_mrc_to_tiff()
- if tiff_path:
- try:
- image_obj = bpy.data.images[tiff_path.name]
- except KeyError:
- image_obj = bpy.data.images.load(str(tiff_path))
- image_obj.colorspace_settings.name = 'Non-Color'
- self.micrograph_material.node_tree.nodes['Image Texture'].image = image_obj
- self.star_node.inputs['Micrograph'].default_value = image_obj
-
-
-
- def create_model(self, name='StarFileObject', node_setup=True, world_scale=0.01):
- from molecularnodes.blender.nodes import get_star_node, MN_micrograph_material
- blender_object = bl.obj.create_object(
- self.positions * world_scale, collection=bl.coll.mn(), name=name)
-
- blender_object.mn['molecule_type'] = 'star'
-
- # create attribute for every column in the STAR file
- for col in self.data.columns:
- col_type = self.data[col].dtype
- # If col_type is numeric directly add
- if np.issubdtype(col_type, np.number):
- bl.obj.set_attribute(
- blender_object, col, self.data[col].to_numpy().reshape(-1), 'FLOAT', 'POINT')
-
- # If col_type is object, convert to category and add integer values
- elif col_type == object:
- codes = self.data[col].astype(
- 'category').cat.codes.to_numpy().reshape(-1)
- bl.obj.set_attribute(blender_object, col, codes, 'INT', 'POINT')
- # Add the category names as a property to the blender object
- blender_object[f'{col}_categories'] = list(
- self.data[col].astype('category').cat.categories)
-
- if node_setup:
- bl.nodes.create_starting_nodes_starfile(
- blender_object, n_images=self.n_images)
- self.node_group = blender_object.modifiers['MolecularNodes'].node_group
-
- blender_object["starfile_path"] = str(self.file_path)
- self.object = blender_object
- self.star_node = get_star_node(self.object)
- self.micrograph_material = MN_micrograph_material()
- bpy.app.handlers.depsgraph_update_post.append(self._update_micrograph_texture)
- return blender_object
diff --git a/molecularnodes/io/star.py b/molecularnodes/io/star.py
deleted file mode 100644
index 5b6743ca..00000000
--- a/molecularnodes/io/star.py
+++ /dev/null
@@ -1,58 +0,0 @@
-import bpy
-from . import parse
-
-bpy.types.Scene.MN_import_star_file_path = bpy.props.StringProperty(
- name='File',
- description='File path for the `.star` file to import.',
- subtype='FILE_PATH',
- maxlen=0
-)
-bpy.types.Scene.MN_import_star_file_name = bpy.props.StringProperty(
- name='Name',
- description='Name of the created object.',
- default='NewStarInstances',
- maxlen=0
-)
-
-
-def load(
- file_path,
- name='NewStarInstances',
- node_setup=True,
- world_scale=0.01
-):
-
- ensemble = parse.StarFile.from_starfile(file_path)
- ensemble.create_model(name=name, node_setup=node_setup,
- world_scale=world_scale)
-
- return ensemble
-
-
-class MN_OT_Import_Star_File(bpy.types.Operator):
- bl_idname = "mn.import_star_file"
- bl_label = "Load"
- bl_description = "Will import the given file, setting up the points to instance an object."
- bl_options = {"REGISTER"}
-
- @classmethod
- def poll(cls, context):
- return True
-
- def execute(self, context):
- scene = context.scene
- load(
- file_path=scene.MN_import_star_file_path,
- name=scene.MN_import_star_file_name,
- node_setup=True
- )
- return {"FINISHED"}
-
-
-def panel(layout, scene):
- layout.label(text="Load Star File", icon='FILE_TICK')
- layout.separator()
- row_import = layout.row()
- row_import.prop(scene, 'MN_import_star_file_name')
- layout.prop(scene, 'MN_import_star_file_path')
- row_import.operator('mn.import_star_file')
diff --git a/molecularnodes/io/wwpdb.py b/molecularnodes/io/wwpdb.py
deleted file mode 100644
index c8e31fc6..00000000
--- a/molecularnodes/io/wwpdb.py
+++ /dev/null
@@ -1,166 +0,0 @@
-import bpy
-from pathlib import Path
-from . import parse
-from .retrieve import download, FileDownloadPDBError
-from requests import HTTPError
-
-
-def fetch(
- pdb_code,
- style="spheres",
- centre="",
- del_solvent=True,
- cache_dir=None,
- build_assembly=False,
- database: str = "rcsb",
- format="bcif",
- color="common",
-):
- if build_assembly:
- centre = ""
-
- file_path = download(
- code=pdb_code, format=format, cache=cache_dir, database=database
- )
-
- parsers = {"pdb": parse.PDB, "cif": parse.CIF, "bcif": parse.BCIF}
- molecule = parsers[format](file_path=file_path)
-
- model = molecule.create_model(
- name=pdb_code,
- centre=centre,
- style=style,
- del_solvent=del_solvent,
- build_assembly=build_assembly,
- color=color,
- )
-
- model.mn["pdb_code"] = pdb_code
- model.mn["molecule_type"] = format
-
- return molecule
-
-
-# Properties that can be set in the scene, to be passed to the operator
-
-
-bpy.types.Scene.MN_pdb_code = bpy.props.StringProperty(
- name="PDB",
- description="The 4-character PDB code to download",
- options={"TEXTEDIT_UPDATE"},
- maxlen=4,
-)
-bpy.types.Scene.MN_cache_dir = bpy.props.StringProperty(
- name="",
- description="Directory to save the downloaded files",
- options={"TEXTEDIT_UPDATE"},
- default=str(Path("~", ".MolecularNodes").expanduser()),
- subtype="DIR_PATH",
-)
-bpy.types.Scene.MN_cache = bpy.props.BoolProperty(
- name="Cache Downloads",
- description="Save the downloaded file in the given directory",
- default=True,
-)
-bpy.types.Scene.MN_import_format_download = bpy.props.EnumProperty(
- name="Format",
- description="Format to download as from the PDB",
- items=(
- ("bcif", ".bcif", "Binary compressed .cif file, fastest for downloading"),
- ("cif", ".cif", "The new standard of .cif / .mmcif"),
- ("pdb", ".pdb", "The classic (and depcrecated) PDB format"),
- ),
-)
-
-
-# operator that is called by the 'button' press which calls the fetch function
-
-
-class MN_OT_Import_wwPDB(bpy.types.Operator):
- bl_idname = "mn.import_wwpdb"
- bl_label = "Fetch"
- bl_description = "Download and open a structure from the Protein Data Bank"
- bl_options = {"REGISTER", "UNDO"}
-
- def execute(self, context):
- scene = context.scene
- pdb_code = scene.MN_pdb_code
- cache_dir = scene.MN_cache_dir
- file_format = scene.MN_import_format_download
-
- if not scene.MN_cache:
- cache_dir = None
-
- style = None
- if scene.MN_import_node_setup:
- style = scene.MN_import_style
-
- centre = ""
- if scene.MN_import_centre:
- centre = scene.MN_centre_type
-
- try:
- mol = fetch(
- pdb_code=pdb_code,
- centre=centre,
- del_solvent=scene.MN_import_del_solvent,
- style=style,
- cache_dir=cache_dir,
- build_assembly=scene.MN_import_build_assembly,
- format=file_format,
- )
- except FileDownloadPDBError as e:
- self.report({"ERROR"}, str(e))
- if file_format == "pdb":
- self.report(
- {"ERROR"},
- "There may not be a `.pdb` formatted file available - try a different download format.",
- )
- return {"CANCELLED"}
-
- bpy.context.view_layer.objects.active = mol.object
- self.report({"INFO"}, message=f"Imported '{pdb_code}' as {mol.object.name}")
-
- return {"FINISHED"}
-
-
-# the UI for the panel, which will display the operator and the properties
-
-
-def panel(layout, scene):
- layout.label(text="Download from PDB", icon="IMPORT")
- layout.separator()
-
- row_import = layout.row().split(factor=0.5)
- row_import.prop(scene, "MN_pdb_code")
- download = row_import.split(factor=0.3)
- download.prop(scene, "MN_import_format_download", text="")
- download.operator("mn.import_wwpdb")
- layout.separator(factor=0.4)
-
- row = layout.row().split(factor=0.3)
- row.prop(scene, "MN_cache")
- row_cache = row.row()
- row_cache.prop(scene, "MN_cache_dir")
- row_cache.enabled = scene.MN_cache
- layout.separator()
-
- layout.label(text="Options", icon="MODIFIER")
- options = layout.column(align=True)
-
- row = options.row()
- row.prop(scene, "MN_import_node_setup", text="")
- col = row.column()
- col.prop(scene, "MN_import_style")
- col.enabled = scene.MN_import_node_setup
-
- row_centre = options.row()
- row_centre.prop(scene, "MN_import_centre", icon_value=0)
- col_centre = row_centre.column()
- col_centre.prop(scene, "MN_centre_type", text="")
- col_centre.enabled = scene.MN_import_centre
- options.separator()
-
- grid = options.grid_flow()
- grid.prop(scene, "MN_import_build_assembly")
- grid.prop(scene, "MN_import_del_solvent")
diff --git a/molecularnodes/load.py b/molecularnodes/load.py
new file mode 100644
index 00000000..e69de29b
diff --git a/molecularnodes/logger.py b/molecularnodes/logger.py
new file mode 100644
index 00000000..06bae942
--- /dev/null
+++ b/molecularnodes/logger.py
@@ -0,0 +1,35 @@
+import os
+import logging
+from .utils import ADDON_DIR
+
+
+def start_logging(logfile_name: str = "side-packages-install") -> logging.Logger:
+ """
+ Configure and start logging to a file.
+
+ Parameters
+ ----------
+ logfile_name : str, optional
+ The name of the log file. Defaults to 'side-packages-install'.
+
+ Returns
+ -------
+ logging.Logger
+ A Logger object that can be used to write log messages.
+
+ This function sets up a logging configuration with a specified log file name and logging level.
+ The log file will be created in the `ADDON_DIR/logs` directory. If the directory
+ does not exist, it will be created. The function returns a Logger object that can be used to
+ write log messages.
+
+ """
+ # Create the logs directory if it doesn't exist
+ logs_dir = os.path.join(os.path.abspath(ADDON_DIR), "logs")
+ os.makedirs(logs_dir, exist_ok=True)
+
+ # Set up logging configuration
+ logfile_path = os.path.join(logs_dir, f"{logfile_name}.log")
+ logging.basicConfig(filename=logfile_path, level=logging.INFO)
+
+ # Return logger object
+ return logging.getLogger()
diff --git a/molecularnodes/operators/__init__.py b/molecularnodes/operators/__init__.py
new file mode 100644
index 00000000..79bcf771
--- /dev/null
+++ b/molecularnodes/operators/__init__.py
@@ -0,0 +1,3 @@
+from . import node_add_buttons
+
+CLASSES = node_add_buttons.CLASSES
diff --git a/molecularnodes/operators/node_add_buttons.py b/molecularnodes/operators/node_add_buttons.py
new file mode 100644
index 00000000..a6c2f03d
--- /dev/null
+++ b/molecularnodes/operators/node_add_buttons.py
@@ -0,0 +1,269 @@
+import bpy
+from bpy.types import Context, Operator
+from bpy.props import BoolProperty, EnumProperty, IntProperty, StringProperty
+
+from ..blender import nodes
+from ..ui import node_info
+from ..ui.panel import STYLE_ITEMS
+
+
+def node_under_mouse(context, event):
+ space = context.space_data
+ mouse_pos = (event.mouse_region_x, event.mouse_region_y)
+
+ # Find the node under the mouse
+ node_under_mouse = None
+ for node in space.node_tree.nodes:
+ if (
+ node.location.x < mouse_pos[0] < node.location.x + node.width
+ and node.location.y < mouse_pos[1] < node.location.y + node.height
+ ):
+ node_under_mouse = node
+ break
+
+ return node_under_mouse
+
+
+def _add_node(node_name, context, show_options=False, material="default"):
+ # intended to be called upon button press in the node tree, and not for use
+ # in general scripting
+
+ prev_context = context.area.type
+ context.area.type = "NODE_EDITOR"
+ # actually invoke the operator to add a node to the current node tree
+ # use_transform=True ensures it appears where the user's mouse is and is currently
+ # being moved so the user can place it where they wish
+ bpy.ops.node.add_node(
+ "INVOKE_DEFAULT", type="GeometryNodeGroup", use_transform=True
+ )
+ context.area.type = prev_context
+ node = context.active_node
+ node.node_tree = bpy.data.node_groups[node_name]
+ node.width = nodes.NODE_WIDTH
+ node.show_options = show_options
+ node.label = node_name
+ node.name = node_name
+
+ # if added node has a 'Material' input, set it to the default MN material
+ nodes.assign_material(node, new_material=material)
+
+
+class MN_OT_Add_Custom_Node_Group(Operator):
+ bl_idname = "mn.add_custom_node_group"
+ bl_label = "Add Custom Node Group"
+ # bl_description = "Add Molecular Nodes custom node group."
+ bl_options = {"REGISTER", "UNDO"}
+ node_name: StringProperty( # type: ignore
+ name="node_name", description="", default="", subtype="NONE", maxlen=0
+ )
+ node_label: StringProperty(name="node_label", default="") # type: ignore
+ node_description: StringProperty( # type: ignore
+ name="node_description",
+ description="",
+ default="Add MolecularNodes custom node group.",
+ subtype="NONE",
+ )
+ node_link: BoolProperty(name="node_link", default=True) # type: ignore
+
+ @classmethod
+ def description(cls, context, properties):
+ return properties.node_description
+
+ def execute(self, context):
+ # we use the DuplicatePrevention to cleanup internal node duplication on appending
+ # as Blender doesn't currently do a great job of reusing datablocks
+ with nodes.DuplicatePrevention():
+ try:
+ nodes.append(self.node_name, link=self.node_link)
+ _add_node(self.node_name, context) # , label=self.node_label)
+ except RuntimeError:
+ self.report(
+ {"ERROR"},
+ message="Failed to add node. Ensure you are not in edit mode.",
+ )
+ return {"FINISHED"}
+
+
+class MN_OT_Assembly_Bio(Operator):
+ bl_idname = "mn.assembly_bio"
+ bl_label = "Build Biological Assembly"
+ bl_description = "Adds node to build biological assembly based on symmetry operations that are extraced from the structure file"
+ bl_options = {"REGISTER", "UNDO"}
+
+ inset_node: BoolProperty(default=False) # type: ignore
+
+ @classmethod
+ def poll(self, context):
+ # this just checks to see that there is some biological assembly information that
+ # is associated with the object / molecule. If there isn't then the assembly
+ # operator will be greyed out and unable to be executed
+ obj = context.active_object
+ try:
+ obj["biological_assemblies"]
+ return True
+ except KeyError:
+ False
+
+ def execute(self, context):
+ obj = context.active_object
+ with nodes.DuplicatePrevention():
+ try:
+ if self.inset_node:
+ nodes.assembly_insert(obj)
+ else:
+ tree_assembly = nodes.assembly_initialise(obj)
+ _add_node(tree_assembly.name, context)
+ except (KeyError, ValueError) as e:
+ self.report({"ERROR"}, "Unable to build biological assembly node.")
+ self.report({"ERROR"}, str(e))
+ return {"CANCELLED"}
+
+ return {"FINISHED"}
+
+
+class MN_OT_iswitch_custom(Operator):
+ bl_idname = "mn.iswitch_custom"
+ # bl_idname = "mn.selection_custom"
+ bl_label = "Custom ISwitch Node"
+ bl_options = {"REGISTER", "UNDO"}
+
+ description: StringProperty(name="Description") # type: ignore
+ dtype: EnumProperty( # type: ignore
+ name="Data type",
+ items=(
+ ("RGBA", "RGBA", "Color iswitch."),
+ ("BOOLEAN", "BOOLEAN", "Boolean iswitch"),
+ ),
+ )
+ field: StringProperty(name="field", default="chain_id") # type: ignore
+ prefix: StringProperty(name="prefix", default="Chain ") # type: ignore
+ node_property: StringProperty(name="node_property", default="chain_ids") # type: ignore
+ node_name: StringProperty(name="node_name", default="chain") # type: ignore
+ starting_value: IntProperty(name="starting_value", default=0) # type: ignore
+
+ @classmethod
+ def description(cls, context, properties):
+ return properties.description
+
+ def execute(self, context):
+ object = context.view_layer.objects.active
+ prop = object[self.node_property]
+ name = object.name
+ if not prop:
+ self.report(
+ {"WARNING"},
+ message=f"{self.node_property} not available for {object.name}.",
+ )
+ return {"CANCELLED"}
+
+ prefix = {"BOOLEAN": "Select", "RGBA": "Color"}[self.dtype]
+ node_name = " ".join([prefix, self.node_name, name])
+
+ with nodes.DuplicatePrevention():
+ node_chains = nodes.custom_iswitch(
+ name=node_name,
+ dtype=self.dtype,
+ iter_list=prop,
+ start=self.starting_value,
+ field=self.field,
+ prefix=self.prefix,
+ )
+
+ _add_node(node_chains.name, context)
+
+ return {"FINISHED"}
+
+
+class MN_OT_Residues_Selection_Custom(Operator):
+ bl_idname = "mn.residues_selection_custom"
+ bl_label = "Res ID Custom"
+ bl_description = "Create a selection based on the provided residue strings.\nThis \
+ node is built on a per-molecule basis, taking into account the residues that \
+ were input."
+ bl_options = {"REGISTER", "UNDO"}
+
+ input_resid_string: StringProperty( # type: ignore
+ name="Select residue IDs: ",
+ description="Enter a string value.",
+ default="19,94,1-16",
+ )
+
+ def execute(self, context):
+ with nodes.DuplicatePrevention():
+ node_residues = nodes.resid_multiple_selection(
+ node_name="MN_select_res_id_custom",
+ input_resid_string=self.input_resid_string,
+ )
+
+ _add_node(node_residues.name, context)
+ return {"FINISHED"}
+
+ def invoke(self, context, event):
+ return context.window_manager.invoke_props_dialog(self)
+
+
+def get_swap_items(self, context):
+ node = context.active_node
+ prefix = node.node_tree.name.split(" ")[0].lower()
+ if prefix == "is":
+ prefix = "select"
+
+ items = [
+ (item["name"], item["label"], item["description"])
+ for item in node_info.menu_items[prefix]
+ if (
+ item != "break" and not item.get("function") and item["name"] != "Set Color"
+ )
+ ]
+ return items
+
+
+class MN_OT_Node_Swap(Operator):
+ bl_idname = "mn.node_swap"
+ bl_label = "Swap Node"
+ bl_description = "Swap this node for another."
+
+ node_description: StringProperty(default="Swap selected node for another") # type: ignore
+ node_items: EnumProperty(items=get_swap_items) # type: ignore
+
+ @classmethod
+ def description(cls, context, properties):
+ return properties.node_description
+
+ def execute(self, context: Context):
+ node = context.active_node
+ nodes.swap(node, self.node_items)
+ return {"FINISHED"}
+
+
+class MN_OT_Change_Color(Operator):
+ bl_idname = "mn.change_color"
+ bl_label = "Color"
+
+ color: EnumProperty( # type: ignore
+ items=(
+ (item["name"], item["label"], item["description"])
+ for item in node_info.menu_items.get("color")
+ if (
+ item != "break"
+ and not item.get("function")
+ and item["name"] != "Set Color"
+ )
+ )
+ )
+
+ def execute(self, context: Context):
+ node = context.active_node
+ nodes.swap(node, self.color)
+ self.report({"INFO"}, f"Selected {self.color}")
+ return {"FINISHED"}
+
+
+CLASSES = [
+ MN_OT_Add_Custom_Node_Group,
+ MN_OT_Residues_Selection_Custom,
+ MN_OT_Assembly_Bio,
+ MN_OT_iswitch_custom,
+ MN_OT_Change_Color,
+ MN_OT_Node_Swap,
+]
diff --git a/molecularnodes/pkg.py b/molecularnodes/pkg.py
deleted file mode 100644
index 8c37d9af..00000000
--- a/molecularnodes/pkg.py
+++ /dev/null
@@ -1,435 +0,0 @@
-"""
-Handling installation of external python packages inside of Blender's bundled python.
-"""
-
-import subprocess
-import sys
-import os
-import logging
-from importlib.metadata import version as get_version, PackageNotFoundError
-import bpy
-import pathlib
-
-ADDON_DIR = pathlib.Path(pathlib.Path(__file__).resolve().parent)
-"""Folder for the addon on the local machine."""
-
-PYPI_MIRROR = {
- # the original.
- 'Default': '',
- # two mirrors in China Mainland to help those poor victims under GFW.
- 'BFSU (Beijing)': 'https://mirrors.bfsu.edu.cn/pypi/web/simple',
- 'TUNA (Beijing)': 'https://pypi.tuna.tsinghua.edu.cn/simple',
- # append more if necessary.
-}
-"""
-Possible PyPi mirrors to install from.
-"""
-
-
-def start_logging(logfile_name: str = 'side-packages-install') -> logging.Logger:
- """
- Configure and start logging to a file.
-
- Parameters
- ----------
- logfile_name : str, optional
- The name of the log file. Defaults to 'side-packages-install'.
-
- Returns
- -------
- logging.Logger
- A Logger object that can be used to write log messages.
-
- This function sets up a logging configuration with a specified log file name and logging level.
- The log file will be created in the `ADDON_DIR/logs` directory. If the directory
- does not exist, it will be created. The function returns a Logger object that can be used to
- write log messages.
-
- """
- # Create the logs directory if it doesn't exist
- logs_dir = os.path.join(os.path.abspath(ADDON_DIR), 'logs')
- os.makedirs(logs_dir, exist_ok=True)
-
- # Set up logging configuration
- logfile_path = os.path.join(logs_dir, f"{logfile_name}.log")
- logging.basicConfig(filename=logfile_path, level=logging.INFO)
-
- # Return logger object
- return logging.getLogger()
-
-
-def get_pypi_mirror_alias(self, context, edit_text):
- """
- Get the available PyPI mirror aliases.
-
- Parameters
- ----------
- self : object
- The object instance.
- context : ...
- The context parameter (description missing).
- edit_text : ...
- The edit_text parameter (description missing).
-
- Returns
- -------
- keys_view
- A view object of the available PyPI mirror aliases.
-
- """
- return PYPI_MIRROR.keys()
-
-
-def process_pypi_mirror_to_url(pypi_mirror_provider: str) -> str:
- """
- Process a PyPI mirror provider and return the corresponding URL.
-
- Parameters
- ----------
- pypi_mirror_provider : str
- The PyPI mirror provider to process.
-
- Returns
- -------
- str
- The URL of the PyPI mirror.
-
- Raises
- ------
- ValueError
- If the provided PyPI mirror provider is invalid.
-
- """
- if pypi_mirror_provider.startswith('https:'):
- return pypi_mirror_provider
- elif pypi_mirror_provider in PYPI_MIRROR.keys():
- return PYPI_MIRROR[pypi_mirror_provider]
- else:
- raise ValueError(
- f"Invalid PyPI mirror provider: {pypi_mirror_provider}")
-
-
-def get_pkgs(requirements: str = None) -> dict:
- """
- Read a requirements file and extract package information into a dictionary.
-
- Parameters
- ----------
- requirements : str, optional
- The path to the requirements file. If not provided, the function looks for a `requirements.txt`
- file in the same directory as the script.
-
- Returns
- -------
- dict
- A dictionary containing package information. Each element of the dictionary is a dictionary containing the package name, version, and description.
-
- Example
- -------
- Given the following requirements file:
- ```python
- Flask==1.1.2 # A micro web framework for Python
- pandas==1.2.3 # A fast, powerful, flexible, and easy-to-use data analysis and manipulation tool
- numpy==1.20.1 # Fundamental package for scientific computing
- ```
- The function would return the following dictionary:
- ```python
- [
- {
- "package": "Flask",
- "version": "1.1.2",
- "desc": "A micro web framework for Python"
- },
- {
- "package": "pandas",
- "version": "1.2.3",
- "desc": "A fast, powerful, flexible, and easy-to-use data analysis and manipulation tool"
- },
- {
- "package": "numpy",
- "version": "1.20.1",
- "desc": "Fundamental package for scientific computing"
- }
- ]
- ```
- """
- import pathlib
-
- if not requirements:
- folder_path = pathlib.Path(__file__).resolve().parent
- requirements = f"{folder_path}/requirements.txt"
-
- with open(requirements) as f:
- lines = f.read().splitlines()
- pkgs = {}
- for line in lines:
- try:
- pkg, desc = line.split('#')
- pkg_meta = pkg.split('==')
- name = pkg_meta[0].strip()
- pkgs[name] = {
- "name": name,
- "version": pkg_meta[1].strip(),
- "desc": desc.strip()
- }
- except ValueError:
- # Skip line if it doesn't have the expected format
- pass
- return pkgs
-
-
-def is_current(package: str) -> bool:
- """
- Check if the specified package is installed and the version matches that specified
- in the `requirements.txt` file.
-
- Parameters
- ----------
- package : str
- The name of the package to check.
-
- Returns
- -------
- bool
- True if the package is the current version, False otherwise.
-
- """
- pkg = get_pkgs().get(package)
- try:
- available_version = get_version(package)
- return available_version == pkg['version']
- except PackageNotFoundError:
- return False
-
-
-def run_python(cmd_list: list = None, mirror_url: str = '', timeout: int = 600):
- """
- Runs pip command using the specified command list and returns the command output.
-
- Parameters
- ----------
- cmd_list : list, optional
- List of pip commands to be executed. Defaults to None.
- mirror_url : str, optional
- URL of a package repository mirror to be used for the command. Defaults to ''.
- timeout : int, optional
- Time in seconds to wait for the command to complete. Defaults to 600.
-
- Returns
- -------
- tuple
- A tuple containing the command list, command return code, command standard output,
- and command standard error.
-
- Example
- -------
- Install numpy using pip and print the command output
- ```python
- cmd_list = ["-m", "pip", "install", "numpy"]
- mirror_url = 'https://pypi.org/simple/'
- cmd_output = run_python(cmd_list, mirror_url=mirror_url, timeout=300)
- print(cmd_output)
- ```
-
- """
-
- # path to python.exe
- python_exe = os.path.realpath(sys.executable)
-
- # build the command list
- cmd_list = [python_exe] + cmd_list
-
- # add mirror to the command list if it's valid
- if mirror_url and mirror_url.startswith('https'):
- cmd_list += ['-i', mirror_url]
-
- log = start_logging()
- log.info(f"Running Pip: '{cmd_list}'")
-
- # run the command and capture the output
- result = subprocess.run(cmd_list, timeout=timeout,
- stdout=subprocess.PIPE, stderr=subprocess.PIPE)
-
- if result.returncode != 0:
- log.error('Command failed: %s', cmd_list)
- log.error('stdout: %s', result.stdout.decode())
- log.error('stderr: %s', result.stderr.decode())
- else:
- log.info('Command succeeded: %s', cmd_list)
- log.info('stdout: %s', result.stdout.decode())
- # return the command list, return code, stdout, and stderr as a tuple
- return result
-
-
-def install_package(package: str, pypi_mirror_provider: str = 'Default') -> list:
- """
- Install a Python package and its dependencies using pip.
-
- Parameters
- ----------
- package : str
- The name of the package to install.
- pypi_mirror_provider : str, optional
- The name/url of the PyPI mirror provider to use. Default is 'Default'.
-
- Returns
- -------
- list
- A list of tuples containing the command list, return code, stdout, and stderr
- for each pip command run.
-
- Raises
- ------
- ValueError
- If the package name is not provided.
-
- Example
- -------
- To install the package 'requests' from the PyPI mirror 'MyMirror', use:
- ```
- install_package('requests', 'MyMirror')
- ```
-
- """
- if not package:
- raise ValueError("Package name must be provided.")
-
- print(f"Installing {package}...")
-
- mirror_url = process_pypi_mirror_to_url(
- pypi_mirror_provider=pypi_mirror_provider)
- print(f"Using PyPI mirror: {pypi_mirror_provider} {mirror_url}")
-
- run_python(["-m", "ensurepip"]),
- run_python(["-m", "pip", "install", "--upgrade", "pip"],
- mirror_url=mirror_url)
- result = run_python(["-m", "pip", "install", package],
- mirror_url=mirror_url)
-
- return result
-
-
-class InstallationError(Exception):
- """
- Exception raised when there is an error installing a package.
-
- Attributes
- ----------
- package_name : str
- The name of the package that failed to install.
- error_message : str
- The error message returned by pip.
-
- """
-
- def __init__(self, package_name, error_message):
- self.package_name = package_name
- self.error_message = error_message
- super().__init__(f"Failed to install {package_name}: {error_message}")
-
-
-def install_all_packages(pypi_mirror_provider: str = 'Default') -> list:
- """
- Install all packages listed in the 'requirements.txt' file.
-
- Parameters
- ----------
- pypi_mirror_provider : str, optional
- The PyPI mirror to use for package installation. Defaults to 'Default',
- which uses the official PyPI repository.
-
- Returns
- -------
- list
- A list of tuples containing the installation results for each package.
-
- Raises
- ------
- InstallationError
- If there is an error during package installation.
-
- Example
- -------
- To install all packages listed in the 'requirements.txt' file, run the following command:
- ```
- install_all_packages(pypi_mirror_provider='https://pypi.org/simple/')
- ```
-
- """
- mirror_url = process_pypi_mirror_to_url(
- pypi_mirror_provider=pypi_mirror_provider)
-
- pkgs = get_pkgs()
- results = []
- for pkg in pkgs.items():
-
- try:
- result = install_package(package=f"{pkg.get('name')}=={pkg.get('version')}",
- pypi_mirror_provider=mirror_url)
- results.append(result)
- except InstallationError as e:
- raise InstallationError(
- f"Error installing package {pkg.get('name')}: {str(e)}")
- return results
-
-
-class MN_OT_Install_Package(bpy.types.Operator):
- bl_idname = 'mn.install_package'
- bl_label = 'Install Given Python Package'
- bl_options = {'REGISTER', 'INTERNAL'}
- package: bpy.props.StringProperty(
- name='Python Package',
- description='Python Package to Install',
- default='biotite'
- )
- version: bpy.props.StringProperty(
- name='Python Package',
- description='Python Package to Install',
- default='0.36.1'
- )
-
- description: bpy.props.StringProperty(
- name='Operator description',
- default='Install specified python package.'
- )
-
- @classmethod
- def description(cls, context, properties):
- return properties.description
-
- def execute(self, context):
- installable = f"{self.package}=={self.version}"
- result = install_package(package=installable,
- pypi_mirror_provider=bpy.context.scene.pypi_mirror_provider)
- if result.returncode == 0 and is_current(self.package):
- self.report(
- {'INFO'},
- f"Successfully installed {self.package} v{self.version}"
- )
- else:
- log_dir = os.path.join(os.path.abspath(ADDON_DIR), 'logs')
- self.report(
- {'ERROR'},
- f"Error installing package. Please check the log files in '{log_dir}'."
- )
- return {'FINISHED'}
-
-
-def button_install_pkg(layout, name, version, desc=''):
- layout = layout.row()
- if is_current(name):
- row = layout.row()
- row.label(text=f"{name} version {version} is installed.")
- op = row.operator('mn.install_package', text=f'Reinstall {name}')
- op.package = name
- op.version = version
- op.description = f'Reinstall {name}'
- else:
- row = layout.row(heading=f"Package: {name}")
- col = row.column()
- col.label(text=str(desc))
- col = row.column()
- op = col.operator('mn.install_package', text=f'Install {name}')
- op.package = name
- op.version = version
- op.description = f'Install required python package: {name}'
diff --git a/molecularnodes/props.py b/molecularnodes/props.py
index c6234393..5fb868d9 100644
--- a/molecularnodes/props.py
+++ b/molecularnodes/props.py
@@ -1,58 +1,90 @@
import bpy
+from bpy.props import IntProperty, BoolProperty, EnumProperty, StringProperty
+from .entities.trajectory.handlers import _update_trajectories
-
-bpy.types.Scene.MN_import_centre = bpy.props.BoolProperty(
+bpy.types.Scene.MN_import_centre = BoolProperty(
name="Centre Structure",
description="Move the imported Molecule on the World Origin",
- default=False
+ default=False,
)
-bpy.types.Scene.MN_centre_type = bpy.props.EnumProperty(
+bpy.types.Scene.MN_centre_type = EnumProperty(
name="Method",
- default='mass',
+ default="mass",
items=(
- ('mass', "Mass", "Adjust the structure's centre of mass to be at the world origin", 1),
- ('centroid', "Centroid",
- "Adjust the structure's centroid (centre of geometry) to be at the world origin", 2)
- )
+ (
+ "mass",
+ "Mass",
+ "Adjust the structure's centre of mass to be at the world origin",
+ 1,
+ ),
+ (
+ "centroid",
+ "Centroid",
+ "Adjust the structure's centroid (centre of geometry) to be at the world origin",
+ 2,
+ ),
+ ),
)
-bpy.types.Scene.MN_import_del_solvent = bpy.props.BoolProperty(
+bpy.types.Scene.MN_import_del_solvent = BoolProperty(
name="Remove Solvent",
description="Delete the solvent from the structure on import",
- default=True
+ default=True,
)
-bpy.types.Scene.MN_import_panel_selection = bpy.props.IntProperty(
+bpy.types.Scene.MN_import_panel_selection = IntProperty(
name="MN_import_panel_selection",
description="Import Panel Selection",
- subtype='NONE',
- default=0
+ subtype="NONE",
+ default=0,
)
-bpy.types.Scene.MN_import_build_assembly = bpy.props.BoolProperty(
- name='Build Assembly',
- default=False
+bpy.types.Scene.MN_import_build_assembly = BoolProperty(
+ name="Build Assembly", default=False
)
-bpy.types.Scene.MN_import_node_setup = bpy.props.BoolProperty(
+bpy.types.Scene.MN_import_node_setup = BoolProperty(
name="Setup Nodes",
default=True,
- description='Create and set up a Geometry Nodes tree on import'
+ description="Create and set up a Geometry Nodes tree on import",
)
class MolecularNodesObjectProperties(bpy.types.PropertyGroup):
- subframes: bpy.props.IntProperty(
- name="Subframes",
- description="Number of subframes to interpolate for MD trajectories",
- default=0
- )
- molecule_type: bpy.props.StringProperty(
+ molecule_type: StringProperty( # type: ignore
name="Molecular Type",
description="How the file was imported, dictating how MN interacts with it",
- default=""
+ default="",
+ )
+ uuid: StringProperty( # type: ignore
+ name="UUID",
+ description="Unique ID for referencing the required objects in the MNSession",
+ default="",
)
- pdb_code: bpy.props.StringProperty(
+ pdb_code: StringProperty( # type: ignore
name="PDB",
description="PDB code used to download this structure",
maxlen=4,
- options={'HIDDEN'}
+ options={"HIDDEN"},
+ )
+ trajectory_selection_index: IntProperty( # type: ignore
+ name="Index of selection",
+ description="Index of selection, that is selected for the UI",
+ default=0,
+ )
+ subframes: IntProperty( # type: ignore
+ name="Subframes",
+ description="Number of subframes to insert between frames of the loaded trajectory",
+ default=0,
+ update=_update_trajectories,
+ )
+ interpolate: BoolProperty( # type: ignore
+ name="Interpolate",
+ description="Whether to interpolate when using subframes",
+ default=True,
+ update=_update_trajectories,
+ )
+ correct_periodic: BoolProperty( # type: ignore
+ name="Correct",
+ description="Correct for periodic boundary crossing when using interpolation. Assumes cubic dimensions.",
+ default=True,
+ update=_update_trajectories,
)
diff --git a/molecularnodes/session.py b/molecularnodes/session.py
new file mode 100644
index 00000000..75680c9e
--- /dev/null
+++ b/molecularnodes/session.py
@@ -0,0 +1,209 @@
+import os
+import pickle as pk
+from typing import Dict, Union
+
+import bpy
+from bpy.app.handlers import persistent
+from bpy.props import StringProperty
+from bpy.types import Context
+
+from .entities.ensemble.ensemble import Ensemble
+from .entities.molecule.molecule import Molecule
+from .entities.trajectory.trajectory import Trajectory
+
+
+def trim(dictionary: dict):
+ to_pop = []
+ for name, item in dictionary.items():
+ # currently there are problems with pickling the functions so we have to just
+ # clean up any calculations that are created on saving. Could potentially convert
+ # it to a string and back but that is likely a job for better implementations
+ if hasattr(item, "calculations"):
+ item.calculations = {}
+ try:
+ if isinstance(item.object, bpy.types.Object):
+ item.name = item.object.name
+ item.object = None
+ if hasattr(item, "frames"):
+ if isinstance(item.frames, bpy.types.Collection):
+ item.frames_name = item.frames.name
+ item.frames = None
+
+ except ReferenceError as e:
+ to_pop.append(name)
+ print(
+ Warning(
+ f"Object reference for {item} broken, removing this item from the session: `{e}`"
+ )
+ )
+
+ for name in to_pop:
+ dictionary.pop(name)
+ return dictionary
+
+
+class MNSession:
+ def __init__(self) -> None:
+ self.molecules: Dict[str, Molecule] = {}
+ self.trajectories: Dict[str, Trajectory] = {}
+ self.ensembles: Dict[str, Ensemble] = {}
+
+ def items(self):
+ "Return UUID and item for all molecules, trajectories and ensembles being tracked."
+ return (
+ list(self.molecules.items())
+ + list(self.trajectories.items())
+ + list(self.ensembles.items())
+ )
+
+ def get_object(self, uuid: str) -> bpy.types.Object | None:
+ """
+ Try and get an object from Blender's object database that matches the uuid given.
+
+ If nothing is be found to match, return None.
+ """
+ for obj in bpy.data.objects:
+ try:
+ if obj.mn.uuid == uuid:
+ return obj
+ except Exception as e:
+ print(e)
+
+ return None
+
+ def remove(self, uuid: str) -> None:
+ "Remove the item from the list."
+ self.molecules.pop(uuid, None)
+ self.trajectories.pop(uuid, None)
+ self.ensembles.pop(uuid, None)
+
+ def get(self, uuid: str) -> Union[Molecule, Trajectory, Ensemble]:
+ for id, item in self.items():
+ if item.uuid == uuid:
+ return item
+
+ return None
+
+ @property
+ def n_items(self) -> int:
+ "The number of items being tracked by this session."
+ length = 0
+
+ for dic in [self.molecules, self.trajectories, self.ensembles]:
+ length += len(dic)
+ return length
+
+ def __repr__(self) -> str:
+ return f"MNSession with {len(self.molecules)} molecules, {len(self.trajectories)} trajectories and {len(self.ensembles)} ensembles."
+
+ def pickle(self, filepath) -> None:
+ pickle_path = self.stashpath(filepath)
+
+ self.molecules = trim(self.molecules)
+ self.trajectories = trim(self.trajectories)
+ self.ensembles = trim(self.ensembles)
+
+ # don't save anything if there is nothing to save
+ if self.n_items == 0:
+ return None
+
+ with open(pickle_path, "wb") as f:
+ pk.dump(self, f)
+
+ print(f"Saved session to: {pickle_path}")
+
+ def load(self, filepath) -> None:
+ pickle_path = self.stashpath(filepath)
+ if not os.path.exists(pickle_path):
+ raise FileNotFoundError(f"MNSession file `{pickle_path}` not found")
+ with open(pickle_path, "rb") as f:
+ session = pk.load(f)
+
+ for uuid, item in session.items():
+ item.object = bpy.data.objects[item.name]
+ if hasattr(item, "frames") and hasattr(item, "frames_name"):
+ item.frames = bpy.data.collections[item.frames_name]
+
+ for uuid, mol in session.molecules.items():
+ self.molecules[uuid] = mol
+
+ for uuid, uni in session.trajectories.items():
+ self.trajectories[uuid] = uni
+
+ for uuid, ens in session.ensembles.items():
+ self.ensembles[uuid] = ens
+
+ print(f"Loaded a MNSession from: {pickle_path}")
+
+ def stashpath(self, filepath) -> str:
+ return f"{filepath}.MNSession"
+
+ def clear(self) -> None:
+ """Remove references to all molecules, trajectories and ensembles."""
+ self.molecules.clear()
+ self.trajectories.clear()
+ self.ensembles.clear()
+
+
+def get_session(context: Context | None = None) -> MNSession:
+ if not context:
+ context = bpy.context
+ return context.scene.MNSession
+
+
+@persistent
+def _pickle(filepath) -> None:
+ get_session().pickle(filepath)
+
+
+@persistent
+def _load(filepath) -> None:
+ # the file hasn't been saved or we are opening a fresh file, so don't
+ # attempt to load anything
+ if filepath == "":
+ return None
+ try:
+ get_session().load(filepath)
+ except FileNotFoundError:
+ print("No MNSession found to load for this .blend file.")
+
+
+class MN_OT_Session_Remove_Item(bpy.types.Operator):
+ bl_idname = "mn.session_remove_item"
+ bl_label = "Remove"
+ bl_description = "Remove this item from the internal Molecular Nodes session"
+ bl_options = {"REGISTER", "UNDO"}
+
+ uuid: StringProperty() # type: ignore
+
+ def invoke(self, context: Context, event):
+ session = get_session()
+
+ return context.window_manager.invoke_confirm(
+ self,
+ event=event,
+ title="Permanently delete item?",
+ message=f"Any links to objects that rely upon this item will be lost. {session.get(self.uuid)}",
+ )
+
+ def execute(self, context: Context):
+ get_session().remove(self.uuid)
+
+ return {"FINISHED"}
+
+
+class MN_OT_Session_Create_Object(bpy.types.Operator):
+ bl_idname = "mn.session_create_object"
+ bl_label = "Create Object"
+ bl_description = "Create a new object linked to this item"
+ bl_options = {"REGISTER", "UNDO"}
+
+ uuid: StringProperty() # type: ignore
+
+ def execute(self, context: Context):
+ item = get_session().get(self.uuid)
+ item.create_object()
+ return {"FINISHED"}
+
+
+CLASSES = [MN_OT_Session_Remove_Item, MN_OT_Session_Create_Object]
diff --git a/molecularnodes/template.py b/molecularnodes/template.py
new file mode 100644
index 00000000..26886652
--- /dev/null
+++ b/molecularnodes/template.py
@@ -0,0 +1,56 @@
+import os
+import shutil
+
+import bpy
+
+from .utils import ADDON_DIR
+
+SUBFOLDER = "Molecular Nodes"
+
+
+def is_installed():
+ base_path = bpy.utils.user_resource(
+ "SCRIPTS", path=os.path.join("startup", "bl_app_templates_user"), create=False
+ )
+ molecular_nodes_path = os.path.join(base_path, "Molecular Nodes")
+ return os.path.exists(molecular_nodes_path)
+
+
+def install():
+ # Construct the base path for app templates
+ base_path = bpy.utils.user_resource(
+ "SCRIPTS", path=os.path.join("startup", "bl_app_templates_user"), create=True
+ )
+
+ # Ensure the base path exists
+ if not os.path.exists(base_path):
+ os.makedirs(base_path)
+
+ # Construct the full path to the "Molecular Nodes" subfolder
+ path_app_templates = os.path.join(base_path, SUBFOLDER)
+
+ # Create the "Molecular Nodes" folder if it doesn't exist
+ if not os.path.exists(path_app_templates):
+ os.makedirs(path_app_templates)
+
+ # Define the path to the startup file
+ startup_file = os.path.join(
+ os.path.abspath(ADDON_DIR), "assets", "template", "startup.blend"
+ )
+
+ # Copy the startup file to the "Molecular Nodes" folder
+ shutil.copy(startup_file, path_app_templates)
+
+ # Refresh Blender's script paths to recognize the new template
+ bpy.utils.refresh_script_paths()
+
+
+def uninstall():
+ for folder in bpy.utils.app_template_paths():
+ path = os.path.join(os.path.abspath(folder), SUBFOLDER)
+ if "Molecular Nodes" not in path:
+ continue
+
+ if os.path.exists(path):
+ shutil.rmtree(path)
+ bpy.utils.refresh_script_paths()
diff --git a/molecularnodes/ui/__init__.py b/molecularnodes/ui/__init__.py
index e69de29b..ac676ffd 100644
--- a/molecularnodes/ui/__init__.py
+++ b/molecularnodes/ui/__init__.py
@@ -0,0 +1,3 @@
+from . import panel, node_menu
+
+CLASSES = panel.CLASSES + node_menu.CLASSES
diff --git a/molecularnodes/ui/func.py b/molecularnodes/ui/func.py
index ee04447a..7823a47b 100644
--- a/molecularnodes/ui/func.py
+++ b/molecularnodes/ui/func.py
@@ -2,21 +2,24 @@
from ..blender import nodes
-def build_menu(layout, items):
+def build_menu(layout, context, items):
+ obj = context.active_object
+
for item in items:
- # print(item)
if item == "break":
layout.separator()
elif item["label"] == "custom":
for button in item["values"]:
+ row = layout.row()
item["function"](
- layout,
+ row,
label=button["label"],
field=button["field"],
dtype=button["dtype"],
prefix=button["prefix"],
property_id=button["property_id"],
)
+ row.enabled = bool(obj.get(button["property_id"]))
elif item["name"].startswith("mn."):
layout.operator(item["name"])
else:
@@ -48,7 +51,7 @@ def button_custom_iswitch(
op.dtype = dtype
op.prefix = prefix
op.node_property = property_id
- op.node_name = label.lower()
+ op.node_name = label
op.starting_value = starting_value
if dtype == "RGBA":
diff --git a/molecularnodes/ui/node_info.py b/molecularnodes/ui/node_info.py
index fc5eafc2..60d5076c 100644
--- a/molecularnodes/ui/node_info.py
+++ b/molecularnodes/ui/node_info.py
@@ -2,59 +2,78 @@
menu_items = {
"style": [
- {
- "label": "Presets",
- "name": "MN_style_presets",
- "description": "Quickly switch between several different pre-made preset styles. Best used when using MolecularNodes via scripts, ensuring all atoms are displayed using a combination of cartoons and atoms.",
- "video_url": "https://imgur.com/gCQRWBk.mp4",
- },
{
"label": "Spheres",
- "name": "MN_style_spheres",
- "description": "Style to apply the traditional space-filling atomic representation of atoms. Spheres are scaled based on the `vdw_radii` attribute. By default the _Point Cloud_ rendering system is used, which is only visible inside of Cycles. By enabling 'EEVEE' it creates a sphere mesh object per atom. This makes it visible inside of EEVEE, but has poor performance at high atom counts.",
- "video_url": "https://imgur.com/3anAJqz",
+ "name": "Style Spheres",
+ "description": "Style to apply the traditional space-filling atomic representation of atoms. Spheres are scaled based on the `vdw_radii` attribute. By default the _Point Cloud_ rendering system is used, which is only visible inside of Cycles.",
+ "video_url": "https://imgur.com/KjKkF2u",
},
{
"label": "Cartoon",
- "name": "MN_style_cartoon",
+ "name": "Style Cartoon",
"description": "Style to apply the traditional cartoon representation of protein structures. This style highlights alpha-helices and beta-sheets with arrows and cylinders.",
"video_url": "https://imgur.com/1xmdfxZ",
},
{
"label": "Ribbon",
- "name": "MN_style_ribbon",
+ "name": "Style Ribbon",
"description": "Style that creates a continuous solid ribbon or licorice tube through the backbones of peptides and nucleic acids.",
"video_url": "https://imgur.com/iMxEJaH",
},
{
"label": "Surface",
- "name": "MN_style_surface",
+ "name": "Style Surface",
"description": "Style that creates a surface representation based on the proximity of atoms to a probe that is moved through the entire structure.",
"video_url": "https://imgur.com/ER8pcYf",
},
{
"label": "Ball and Stick",
- "name": "MN_style_ball_and_stick",
+ "name": "Style Ball and Stick",
"description": "Style that creates cylinders for bonds and spheres for atoms. The atoms can be either Eevee or Cycles compatible, with customisation to resolution and radius possible.",
"video_url": "https://imgur.com/kuWuOsw",
},
{
- "label": "Stick",
- "name": "MN_style_stick",
- "description": "Style that creates a cylinder for each bond. Cylindrical caps to the cylinders are currently not supported. Best to use [`MN_style_ball_and_stick`](#style-ball-and-stick).",
- "video_url": "https://imgur.com/tV4XalY",
+ "label": "Sticks",
+ "name": "Style Sticks",
+ "description": "Style that creates a cylinder for each bond. Cylindrical caps to the cylinders are currently not supported. Best to use [`Style Ball and Stick`](#style-ball-and-stick).",
+ "video_url": "https://imgur.com/4ZK1AMo",
+ },
+ "break",
+ {
+ "label": "Preset 1",
+ "name": "Style Preset 1",
+ "description": "Quickly switch between several different pre-made preset styles. Best used when using MolecularNodes via scripts, ensuring all atoms are displayed using a combination of cartoons and atoms.",
+ "video_url": "https://imgur.com/gCQRWBk.mp4",
+ },
+ {
+ "label": "Preset 2",
+ "name": "Style Preset 2",
+ "description": "Quickly switch between several different pre-made preset styles. Best used when using MolecularNodes via scripts, ensuring all atoms are displayed using a combination of cartoons and atoms.",
+ "video_url": "https://imgur.com/gCQRWBk.mp4",
+ },
+ {
+ "label": "Preset 3",
+ "name": "Style Preset 3",
+ "description": "Quickly switch between several different pre-made preset styles. Best used when using MolecularNodes via scripts, ensuring all atoms are displayed using a combination of cartoons and atoms.",
+ "video_url": "https://imgur.com/gCQRWBk.mp4",
+ },
+ {
+ "label": "Preset 4",
+ "name": "Style Preset 4",
+ "description": "Quickly switch between several different pre-made preset styles. Best used when using MolecularNodes via scripts, ensuring all atoms are displayed using a combination of cartoons and atoms.",
+ "video_url": "https://imgur.com/gCQRWBk.mp4",
},
],
"select": [
{
"label": "Separate Atoms",
- "name": "MN_select_separate_atoms",
+ "name": "Separate Atoms",
"description": "Select only the desired input atoms. The output is bits of geometry, which include the selection and include the inverse of the selected atoms. You can expand the selection to include an entire residue if a single atom in that residue is selected, by setting `Whole Residue` to `True`.",
"video_url": "https://imgur.com/VsCW0HY",
},
{
"label": "Separate Polymers",
- "name": "MN_select_separate_polymers",
+ "name": "Separate Polymers",
"description": "Separate the input atomic geometry into it's different polymers or `Protein`, `Nucleic Acid` and `other`.",
"video_url": "https://imgur.com/ICQZxxz",
},
@@ -67,7 +86,7 @@
"label": "Chain",
"field": "chain_id",
"dtype": "BOOLEAN",
- "name": "MN_select_chain_",
+ "name": "Select Chain_",
"prefix": "",
"property_id": "chain_ids",
"description": "Select single or multiple of the different chains. Creates a selection based on the `chain_id` attribute.",
@@ -76,7 +95,7 @@
{
"label": "Entity",
"field": "entity_id",
- "name": "MN_select_entity_",
+ "name": "Select Entity_",
"dtype": "BOOLEAN",
"prefix": "",
"property_id": "entity_ids",
@@ -86,115 +105,154 @@
{
"label": "Ligand",
"field": "res_name",
- "name": "MN_select_ligand_",
+ "name": "Select Ligand_",
"dtype": "BOOLEAN",
"prefix": "",
"property_id": "ligands",
"description": "Select single or multiple of the different ligands.",
"video_url": "https://imgur.com/s2seWIw",
},
+ {
+ "label": "Segment",
+ "field": "segid",
+ "name": "Select Segment_",
+ "dtype": "BOOLEAN",
+ "prefix": "",
+ "property_id": "segments",
+ "description": "",
+ },
],
},
- "break",
- {
- "label": "Cube",
- "name": "MN_select_cube",
- "description": "Create a selection that is inside the `Empty_Cube` object. When this node is first created, an _empty_ object called `Empty_Cube` should be created. You can always create additional empty objects through the add menu, to use a different object. The rotation and scale of the object will be taken into account for the selection.",
- "video_url": "https://imgur.com/P4GZ7vq",
- },
- {
- "label": "Sphere",
- "name": "MN_select_sphere",
- "description": "Create a selection that is within a spherical radius of an object, based on that object's scale. By default an _empty_ object called `Empty_Sphere` is created. You can use other objects or create a new empty to use. The origin point for the object will be used, which should be taken in to account when using molecules. Use [`MN_select_proximity`](#select-proximity) for selections which are within a certain distance of a selection of atoms instead of a single origin point.",
- "video_url": "https://imgur.com/xdeTZR7",
- },
- "break",
- {
- "label": "Secondary Structure",
- "name": "MN_select_sec_struct",
- # or can be calculated using the [`MN_utils_dssp'](#utils-dssp) node.",
- "description": "Select based on the assigned secondary structure information. Only returns a selection if the `sec_struct` attribute exists on the atoms. Will be imported from files where it is present",
- "video_url": "https://imgur.com/IindS3D",
- },
- {
- "label": "Backbone",
- "name": "MN_select_backbone",
- "description": "Selection fields for the backbone and side chains of the protein and nucleic acids.",
- "video_url": "https://imgur.com/Sbl6ns5",
- },
{
"label": "Atomic Number",
- "name": "MN_select_atomic_number",
+ "name": "Select Atomic Number",
"description": "Select single elements, by matching to the `atomic_number` field. Useful for selecting single elements, or combining to select elements higher than 20 on the periodic table.",
"video_url": "https://imgur.com/Bxn33YK",
},
{
"label": "Element",
- "name": "MN_select_element",
+ "name": "Select Element",
"description": "Select individual elements, for the first 20 elements on the periodic table. For selections of higher elements, use [`MN_select_atomic_number`](#select-atomic-number). Creating a node which includes more elements becomes too large to be practical.",
"video_url": "https://imgur.com/nRQwamG",
},
{
- "label": "Attribute",
- "name": "MN_select_attribute",
- "description": "Selections based on the different attributes that are available on the atomic geometry.",
- "video_url": "https://imgur.com/HakZ4sx",
+ "label": "Res Name",
+ "name": "Select Res Name",
+ "description": "Select protein or nucleic acids based on their residue name.",
+ "video_url": "https://imgur.com/kjzH9Rs",
},
{
- "label": "Bonded Atoms",
- "name": "MN_select_bonded",
- "description": "Based on an initial selection, finds atoms which are within a certain number of bonds of this selection. Output can include or excluded the original selection.",
- "video_url": "https://imgur.com/g8hgXup",
+ "label": "Res ID Single",
+ "name": "Select Res ID",
+ "description": "Select a atoms based on their `res_id` number.",
+ "video_url": "https://imgur.com/BL6AOP4",
+ },
+ {
+ "label": "Res ID Range",
+ "name": "Select Res ID Range",
+ "description": "Select multiple residues by specifying a _Min_ and a _Max_, defining a range that includes or excludes based on the `res_id` number.",
+ "video_url": "https://imgur.com/NdoQcdE",
},
- "break",
{
"label": "Res ID",
"name": "mn.residues_selection_custom",
- "backup": "MN_select_res_id_",
+ "backup": "Select Res ID_",
"description": "Create a more complex selection for the `res_id` field, by specifying multiple ranges and potential single `res_id` numbers. This node is built uniquely each time, to the inputs will look different for each user.\nIn the example below, residues 10 & 15 are selected, as well as residues between and including 20-100.\nThe node was created by inputting `10, 15, 20-100` into the node creation field.",
"video_url": "https://imgur.com/OwAXsbG",
},
+ "break",
{
- "label": "Proximity",
- "name": "MN_select_proximity",
- "description": "Create a selection based on the proximity to the Target Atoms of the input. A sub-selection of the Target atoms can be used if the `Selection` input is used. You can expand the selection to include an entire residue if a single atom in that residue is selected, by setting `Whole Residue` to `True`.\nIn the example below, the `MN_style_atoms` is being applied to a selection, which is being calculated from the proximity of atoms to specific chains. As the cutoff for the selection is changed, it includes or excludes more atoms. The `Whole Residue` option also ensures that entire residues are shown.",
- "video_url": "https://imgur.com/RI80CRY",
+ "label": "Attribute",
+ "name": "Select Attribute",
+ "description": "Select atoms that have true for the given attribute name.",
},
{
- "label": "Res ID Single",
- "name": "MN_select_res_id_single",
- "description": "Select a single residue based on the `res_id` number.",
- "video_url": "https://imgur.com/BL6AOP4",
+ "label": "Is Peptide",
+ "name": "Is Peptide",
+ "description": "Select the atoms involved in a peptide chain.",
},
{
- "label": "Res ID Range",
- "name": "MN_select_res_id_range",
- "description": "Select multiple residues by specifying a _minimum_ and a _maximum_ which will create the selection based on the `res_id` number.",
- "video_url": "https://imgur.com/NdoQcdE",
+ "label": "Is Nucleic",
+ "name": "Is Nucleic",
+ "description": "Select the atoms involved in nucleic acid polymer.",
},
{
- "label": "Res Name Peptide",
- "name": "MN_select_res_name_peptide",
- "description": "Select single or multiple protein residues by name. Includes the 20 naturally occurring amino acids.",
- "video_url": "https://imgur.com/kjzH9Rs",
+ "label": "Is Lipid",
+ "name": "Is Lipid",
+ "description": "Select the atoms involved in lipid molecules.",
+ },
+ {
+ "label": "Is Solvent",
+ "name": "Is Solvent",
+ "description": "Select the atoms that are part of the solvent.",
+ },
+ {
+ "label": "Is Alpha Carbon",
+ "name": "Is Alpha Carbon",
+ "description": "Select the alpha carbons of a peptide.",
+ },
+ {
+ "label": "Is Backbone",
+ "name": "Is Backbone",
+ "description": "Select the backbone atoms of a peptide or nucleic acid polymer.",
+ },
+ {
+ "label": "Is Side Chain",
+ "name": "Is Side Chain",
+ "description": "Select the side chain atoms of a peptide or nucleic acid polymer.",
+ },
+ {
+ "label": "Is Helix",
+ "name": "Is Helix",
+ "description": "Select the atoms in a alpha-helix or similar.",
+ },
+ {
+ "label": "Is Sheet",
+ "name": "Is Sheet",
+ "description": "Select the atoms in a beta-sheet or similar.",
+ },
+ {
+ "label": "Is Loop",
+ "name": "Is Loop",
+ "description": "Select the atoms not in a sheet or helix.",
},
+ "break",
{
- "label": "Res Name Nucleic",
- "name": "MN_select_res_name_nucleic",
- "description": "Select single or multiple nucleic residues by name.",
- "video_url": "https://imgur.com/qnUlHpG",
+ "label": "Bonded",
+ "name": "Select Bonded",
+ "description": "Based on an initial selection, finds atoms which are within a certain number of bonds of this selection. Output can include or excluded the original selection.",
+ "video_url": "https://imgur.com/g8hgXup",
},
{
"label": "Res Whole",
- "name": "MN_select_res_whole",
+ "name": "Select Res Whole",
"description": "Expand the given selection to include a whole residue, if a single atom in that residue is selected. Useful for when a distance or proximity selection includes some of the residue and you wish to include all of the residue.",
"video_url": "https://imgur.com/JFzwE0i",
},
+ "break",
+ {
+ "label": "Cube",
+ "name": "Select Cube",
+ "description": "Create a selection that is inside the `Empty_Cube` object. When this node is first created, an _empty_ object called `Empty_Cube` should be created. You can always create additional empty objects through the add menu, to use a different object. The rotation and scale of the object will be taken into account for the selection.",
+ "video_url": "https://imgur.com/P4GZ7vq",
+ },
+ {
+ "label": "Sphere",
+ "name": "Select Sphere",
+ "description": "Create a selection that is within a spherical radius of an object, based on that object's scale. By default an _empty_ object called `Empty_Sphere` is created. You can use other objects or create a new empty to use. The origin point for the object will be used, which should be taken in to account when using molecules. Use [`MN_select_proximity`](#select-proximity) for selections which are within a certain distance of a selection of atoms instead of a single origin point.",
+ "video_url": "https://imgur.com/xdeTZR7",
+ },
+ {
+ "label": "Proximity",
+ "name": "Select Proximity",
+ "description": "Create a selection based on the proximity to the Target Atoms of the input. A sub-selection of the Target atoms can be used if the `Selection` input is used. You can expand the selection to include an entire residue if a single atom in that residue is selected, by setting `Whole Residue` to `True`.\nIn the example below, the `Style Atoms` is being applied to a selection, which is being calculated from the proximity of atoms to specific chains. As the cutoff for the selection is changed, it includes or excludes more atoms. The `Whole Residue` option also ensures that entire residues are shown.",
+ "video_url": "https://imgur.com/RI80CRY",
+ },
],
"color": [
{
"label": "Set Color",
- "name": "MN_color_set",
+ "name": "Set Color",
"description": "The is the primary way to change the color of structures in Molecular Nodes. Colors for cartoon and ribbon are taken from the _alpha-carbons_ of the structures. Change the color of the input atoms, based on a selection and a color field. The color field can be as complex of a calculation as you wish. In the example below the color for the whole structure can be set, or the color can be based on a color for each chain, or the result of mapping a color to an attribute such as `b_factor`.",
"video_url": "https://imgur.com/667jf0O",
},
@@ -207,16 +265,25 @@
"label": "Chain",
"field": "chain_id",
"dtype": "RGBA",
- "name": "MN_color_chain_",
+ "name": "Color Chain_",
"prefix": "",
"property_id": "chain_ids",
- "description": "Choose the colors for individual chains in the structure. This node is generated for each particular molecule, so the inputs will look different based on the imported structure. For larger structures with many chains this node may become too large to be practical, in which case you might better use [`MN_color_entity_id`](#color-entity-id).",
+ "description": "Choose the colors for individual chains in the structure. This node is generated for each particular molecule, so the inputs will look different based on the imported structure. For larger structures with many chains this node may become too large to be practical, in which case you might better use [`Color Entity ID`](#color-entity-id).",
"video_url": "https://imgur.com/9oM24vB",
},
+ {
+ "label": "Segment",
+ "field": "segid",
+ "name": "Color Segment_",
+ "dtype": "RGBA",
+ "prefix": "",
+ "property_id": "segments",
+ "description": "",
+ },
{
"label": "Entity",
"field": "entity_id",
- "name": "MN_color_entity_",
+ "name": "Color Entity_",
"dtype": "RGBA",
"prefix": "",
"property_id": "entity_ids",
@@ -226,7 +293,7 @@
{
"label": "Ligand",
"field": "res_name",
- "name": "MN_color_ligand_",
+ "name": "Color Ligand_",
"dtype": "RGBA",
"prefix": "",
"property_id": "ligands",
@@ -235,141 +302,163 @@
},
],
},
+ {
+ "label": "Element",
+ "name": "Color Element",
+ "description": "Choose a color for each of the first 20 elements on the periodic table. For higher atomic number elements use [`Color Atomic Number`](#color-atomic-number).",
+ "video_url": "https://imgur.com/iMGZKCx",
+ },
+ {
+ "label": "Atomic Number",
+ "name": "Color Atomic Number",
+ "description": "Choose a color for an individual element. Select the element based on `atomic_number`. Useful for higher atomic number elements which are less commonly found in structures.",
+ "video_url": "https://imgur.com/pAloaAF",
+ },
+ {
+ "label": "Res Name",
+ "name": "Color Res Name",
+ "description": "Choose a color for each of the 20 naturally occurring amino acids or the 4 base nucleic acids (DNA / RNA)",
+ "video_url": "https://imgur.com/1yhSVsW",
+ },
+ {
+ "label": "Common Elements",
+ "name": "Color Common",
+ "description": "Choose a color for each of the common elements. This is a smaller convenience node for elements which commonly appear in macromolecular structures",
+ "video_url": "https://imgur.com/GhLdNwy",
+ },
"break",
{
- "label": "Goodsell Colors",
- "name": "MN_color_goodsell",
+ "label": "Goodsell",
+ "name": "Color Goodsell",
"description": "Change the inputted color to be darker for non-carbon atoms. Creates a _Goodsell Style_ color scheme for individual chains.",
"video_url": "https://imgur.com/gPgMSRa",
},
+ {
+ "label": "Rainbow",
+ "name": "Color Rainbow",
+ "description": "Generate a rainbow color palette, that changes over from start to finish along a peptide chain. Can be one rainbow over the entire structure, or create a rainbow of a per-chani basis.",
+ },
{
"label": "Attribute Map",
- "name": "MN_color_attribute_map",
+ "name": "Color Attribute Map",
"description": "Interpolate between two or three colors, based on the value of an attribute field such as `b_factor`. Choosing the minimum and maximum values with the inputs.",
"video_url": "https://imgur.com/lc2o6e1",
},
{
"label": "Attribute Random",
- "name": "MN_color_attribute_random",
+ "name": "Color Attribute Random",
"description": "Generate a random color, based on the given attribute. Control the lightness and saturation of the color with the inputs.",
"video_url": "https://imgur.com/5sMcpAu",
},
- {"label": "Backbone", "name": "MN_color_backbone", "description": ""},
{
"label": "pLDDT",
- "name": "MN_color_pLDDT",
+ "name": "Color pLDDT",
"description": "Assigns colors using the `b_factor` attribute, which contains the `pLDDT` attribute for models that come from AlphaFold.",
},
+ {
+ "label": "Backbone",
+ "name": "Color Backbone",
+ "description": "Color atoms by whether or not they form part of a peptide or nucleic backbone",
+ },
{
"label": "Secondary Structure",
- "name": "MN_color_sec_struct",
+ "name": "Color Sec Struct",
"description": "Choose a color for the different secondary structures, based on the `sec_struct` attribute.",
"video_url": "https://imgur.com/wcJAUp9",
},
"break",
+ ],
+ "topology": [
{
- "label": "Element",
- "name": "MN_color_element",
- "description": "Choose a color for each of the first 20 elements on the periodic table. For higher atomic number elements use [`MN_color_atomic_number`](#color-atomic-number).",
- "video_url": "https://imgur.com/iMGZKCx",
+ "label": "DSSP",
+ "name": "Topology DSSP",
+ "description": "Calculate the secondary structure of a structure, storing it on the `sec_struct` attribute.",
},
{
- "label": "Atomic Number",
- "name": "MN_color_atomic_number",
- "description": "Choose a color for an individual element. Select the element based on `atomic_number`. Useful for higher atomic number elements which are less commonly found in structures.",
- "video_url": "https://imgur.com/pAloaAF",
+ "label": "Residue Mask",
+ "name": "Residue Mask",
+ "description": "Returns the index for the atom for each unique group (from res_id) for each point in that group. Allows for example, all atoms in a group to be rotated around the position of the selected atom.\n\nIn the video example, the `atom_name` is used to select an atom within the groups. Each atom's position is then offset to that position, showing the group-wise selection.",
+ "video_url": "https://imgur.com/sD3jRTR",
},
{
- "label": "Res Name Peptide",
- "name": "MN_color_res_name_peptide",
- "description": "Choose a color for each of the 20 naturally occurring amino acids. Non AA atoms will retain their currently set color.",
- "video_url": "https://imgur.com/1yhSVsW",
+ "label": "Backbone Positions",
+ "name": "Backbone Positions",
+ "description": 'If the atoms have been through the "Compute Backbone" node, then the backbone atom positions will be available as attributes through this node.\n\nIn the video example, the `Alpha Carbons` output is styled as spheres, where the position is mixed with some of the backbone posiitons. The backbone positions can also be selected from the AA residue higher or lower with the specified offset.',
+ "video_url": "https://imgur.com/6X2wnpY",
},
{
- "label": "Res Name Nucleic",
- "name": "MN_color_res_name_nucleic",
- "description": "Choose a color for each of the nucleic acids. Non nucleic acid atoms will retain their currently set color.",
- "video_url": "https://imgur.com/LpLZT3F",
+ "label": "Dihedral Phi",
+ "name": "Dihedral Phi",
+ "description": "",
+ "video_url": "",
},
{
- "label": "Element Common",
- "name": "MN_color_common",
- "description": "Choose a color for each of the common elements. This is a smaller convenience node for elements which commonly appear in macromolecular structures. Use [`MN_color_element`](#color-element) for the first 20 elements and [`MN_color_atomic_number`](#color-atomic-number) for individual elements with higher atomic numbers.",
- "video_url": "https://imgur.com/GhLdNwy",
+ "label": "Dihedral Psi",
+ "name": "Dihedral Psi",
+ "description": "",
+ "video_url": "",
},
- ],
- "topology": [
+ {
+ "label": "Backbone Position",
+ "name": "Backbone Position",
+ "description": "Return the backbone position for the peptide residue, and recalculate if the attribute doesn't exist",
+ "video_url": "",
+ },
+ "break",
+ {
+ "label": "Res Info",
+ "name": "Res Info",
+ "description": "Read information about the atoms with the context of each residue the atom is in",
+ },
+ {
+ "label": "Chain Info",
+ "name": "Chain Info",
+ "description": "Read information about the residues within the context of each chain",
+ },
+ {
+ "label": "Res Group ID",
+ "name": "Res Group ID",
+ "description": "A unique Group ID that is calculated for every residue in the structure",
+ },
+ "break",
{
"label": "Find Bonds",
- "name": "MN_topo_bonds_find",
+ "name": "Topology Find Bonds",
"description": "Finds bonds between atoms based on distance. Based on the vdw_radii for each point, finds other points within a certain radius to create a bond to. Does not preserve the index for the points, detect bond type, or transfer all attributes",
"video_url": "https://imgur.com/oUo5TsM",
},
{
"label": "Break Bonds",
- "name": "MN_topo_bonds_break",
+ "name": "Topology Break Bonds",
"description": "Will delete a bond between atoms that already exists based on a distance cutoff, or is selected in the `Selection` input. Leaves the atoms unaffected",
"video_url": "https://imgur.com/n8cTN0k",
},
+ {
+ "label": "Bond Count",
+ "name": "Bond Count",
+ "description": "The number of bonds for an atom",
+ },
{
"label": "Edge Info",
- "name": "MN_topo_edge_info",
+ "name": "Edge Info",
"description": 'Get information for the selected edge, evaluated on the point domain. The "Edge Index" selects the edge from all possible connected edges. Edges are unfortunately stored somewhat randomly. The resulting information is between the evaluating point and the point that the edge is between. Point Index returns -1 if not connected.\n\nIn the video example, cones are instanced on each point where the Edge Index returns a valid connection. The Edge Vector can be used to align the instanced cone along that edge. The length of the edge can be used to scale the cone to the other point. As the "Edge Index" is changed, the selected edge changes. When "Edge Index" == 3, only the atoms with 4 connections are selected, which in this model (1BNA) are just the phosphates.',
"video_url": "https://imgur.com/Ykyis3e",
},
{
"label": "Edge Angle",
- "name": "MN_topo_edge_angle",
+ "name": "Point Edge Angle",
"description": ' Calculate the angle between two edges, selected with the edge indices. For molecule bonds, combinations of [(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)] will select all possible bond angles.\n\nIn the video example, two edges are selected with their "Edge Index" values. Those atoms which aren\'t valid return false and do not get instanced. The two edge vectors are used to calculate the perpendicular vector through cross product, around which the rotation for the cone is rotated. This demonstrates the ability to calculate the edge angle between the two selected edges.',
"video_url": "https://imgur.com/oQP6Cv8",
},
{
- "label": "Connected Points for Edge Point",
- "name": "MN_topo_edge_connected_points",
+ "label": "Points of Edge",
+ "name": "Points of Edge",
"description": 'Finds the conntected point for the selected "Edge Index", and returns each point index for all of the points connected to that point. If the connection doesn\'t exist, or the connection is back to the original point, -1 is returned.\n\nIn the video example, a new point is selected based on the "Edge Index". At that point, all of the connecting points are exposed as indices `0, 1, 2, 3`. If that index is not a valid point or connection, or the point is the same as the original point that is being evaluated, then -1 is returned. \n\nThis is one of the more complicated topology nodes, but allows indexing of the atoms that are bonded to a bonded atom. This helps with doing calculations for planar molecules.',
"video_url": "https://imgur.com/fZ6srIS",
},
"break",
- {
- "label": "Backbone Positions",
- "name": "MN_topo_backbone",
- "description": 'If the atoms have been through the "Compute Backbone" node, then the backbone atom positions will be available as attributes through this node.\n\nIn the video example, the `Alpha Carbons` output is styled as spheres, where the position is mixed with some of the backbone posiitons. The backbone positions can also be selected from the AA residue higher or lower with the specified offset.',
- "video_url": "https://imgur.com/6X2wnpY",
- },
- {
- "label": "Compute Backbone",
- "name": "MN_topo_compute_backbone",
- "description": "Gets the backbone positions for each AA residue and stores them as attributes, and additionally computes the phi and psi angles for each residue in radians.\n\nIn the video example, the Phi and Psi angles are mapped from (-Pi, Pi) to (0, 1), which is used in the Color Ramp node to choose colors. This is computed on the alpha carbons, but can be used on any of the resulting atoms for the corresponding residues, which is shown in the second video.",
- "video_url": ["https://imgur.com/9DNzngY", "https://imgur.com/W3P9l10"],
- },
- "break",
- {
- "label": "3-Point Angle",
- "name": "MN_topo_angle_3point",
- "description": "Calculate the angle between 3 different points. These points are selected based on their index in the point domain, with Index B being the centre of the calculation.\n\nIn the video example, the same calculation that is occurring internally inside of the `MN_topo_edge_angle` node, is being handled explicity by this node. If the `Index` is being used as `Index B` then the current point that is being evaluated is the centre of the angle calculation. If this value is changed, then the point at the corresponding index is used, which results in a smaller angle in the example video.",
- "video_url": "https://imgur.com/qXyy2ln",
- },
- {
- "label": "2-Point Angle",
- "name": "MN_topo_angle_2point",
- "description": "Calculate the angle that two points make, relative to the current point being evaluated. Points are selected based on their index, with the centre of the angle calculation being the current point's position. Equivalent to using 3-Point angle and using `Index` as the `Index B`.\n\nIn the example video, the angle calculation is similar to that of the 3-Point Angle node, but the middle point is always the current point.",
- "video_url": "https://imgur.com/xp7Vbaj",
- },
- {
- "label": "Point Distance",
- "name": "MN_topo_point_distance",
- "description": "Calculate the distance and the vector between the evaluating point and the point selected via the Index.\n\nIn the example video, each point is calculating a vector and a distance between itself and the indexed point. When the Point Mask node is used, this index is then on a per-group basis, so each point in the group points to just the group's corresponding point.",
- "video_url": "https://imgur.com/AykNvDz",
- },
- "break",
- {
- "label": "Group Point Mask",
- "name": "MN_topo_point_mask",
- "description": "Returns the index for the atom for each unique group (from res_id) for each point in that group. Allows for example, all atoms in a group to be rotated around the position of the selected atom.\n\nIn the video example, the `atom_name` is used to select an atom within the groups. Each atom's position is then offset to that position, showing the group-wise selection.",
- "video_url": "https://imgur.com/sD3jRTR",
- },
],
- "assembly": [
+ "ensemble": [
{
"label": "Biological Assembly",
"name": "mn.assembly_bio",
@@ -383,6 +472,11 @@
"description": "Move an instanced assembly to the world origin. Some structures are not centred on the world origin, so this node can reset them to the world origin for convenient rotation and translation and animation.",
"video_url": "https://imgur.com/pgFTmgC",
},
+ {
+ "label": "Instance",
+ "name": "Ensemble Instance",
+ "description": "Instance the items of an ensemble onto the given points",
+ },
],
"DNA": [
{
@@ -420,26 +514,37 @@
"animate": [
{
"label": "Animate Frames",
- "name": "MN_animate_frames",
+ "name": "Animate Frames",
"description": "Animate the atoms of a structure, based on the frames of a trajectory from the `Frames` collection in the input. The structure animates through the trajectory from the given start frame to the given end frame, as the `Animate 0..1` value moves from `0` to `1`. Values higher than `1` start at the beginning again and the trajectory will loop repeating every `1.00`.\nPosition and `b_factor` are interpolated if available. By default linear interpolation is used. Smoothing in and out of each frame can be applied with the `Smoother Step`, or no interpolation at all.",
"video_url": "https://imgur.com/m3BPUxh",
},
{
"label": "Animate Value",
- "name": "MN_animate_value",
+ "name": "Animate Value",
"description": "Animate a float value between the specified min and max values, over specified range of frames. If clamped, frames above and below the start and end will result in the min and max output values, otherwise it will continue to linearly interpolate the value beyond the min and max values.",
"video_url": "https://imgur.com/2oOnwRm",
},
"break",
+ {
+ "label": "Animate Trails",
+ "name": "Animate Trails",
+ "description": "Add trails to the atoms as they are animated, which trail the specified number of frames behind the atoms",
+ },
+ "break",
+ {
+ "label": "Centre on Selection",
+ "name": "Centre on Selection",
+ "description": "Move the input points to be centred on their calculated cnetroid point, which is based on the selection. The optional `Group ID` value applies this transformation on a per-group basis",
+ },
{
"label": "Res Wiggle",
- "name": "MN_animate_res_wiggle",
+ "name": "Animate Wiggle",
"description": "Create a procedural animation of side-chain movement. 'Wiggles' the side-chains of peptide amino acids based on the `b_factor` attribute. Wiggle is currently only supported for protein side-chains and does not check for steric clashing so higher amplitudes will result in strange results. The animation should seamlessly loop every `1.00` of the `Animate 0..1` input.",
"video_url": "https://imgur.com/GK1nyUz",
},
{
- "label": "Res to Curve",
- "name": "MN_animate_res_to_curve",
+ "label": "Peptide to Curve",
+ "name": "Animate Peptide to Curve",
"description": "Take the protein residues from a structure and align then along an input curve. Editing the curve will change how the atoms are arranged. The output atoms can be styled as normal.",
"video_url": "https://imgur.com/FcEXSZx",
},
@@ -469,57 +574,147 @@
"name": "MN_utils_curve_resample",
"description": "",
},
+ {
+ "label": "Attribute Map",
+ "name": "Attribute Map",
+ "description": "Sample an attribute from the mesh and remap from the minimum to the maximum to the specified values",
+ },
+ "break",
+ {
+ "label": "Between Integer",
+ "name": "Between Integer",
+ "description": "Test if an integer is between (and including) the upper and lower bounds",
+ },
+ {
+ "label": "Between Float",
+ "name": "Between Float",
+ "description": "Test if a float is between the upper and lower bounds",
+ },
+ {
+ "label": "Between Vector",
+ "name": "Between Vector",
+ "description": "Test if a vector is element-wise between the upper and lower bounds.",
+ },
+ "break",
+ {
+ "label": "Offset Integer",
+ "name": "Offset Integer",
+ "description": "Evaluate an integer by an index that is offset by the specified amount",
+ },
+ {
+ "label": "Offset Vector",
+ "name": "Offset Vector",
+ "description": "Evaluate a vector by an index that is offset by the specified amount",
+ },
+ {
+ "label": "Offset Boolean",
+ "name": "Offset Boolean",
+ "description": "Evaluate a boolean by an index that is offset by the specified amount",
+ },
+ {
+ "label": "Offset Float",
+ "name": "Offset Float",
+ "description": "Evaluate a float value by an index that is offset by the specified amount",
+ },
+ "break",
+ {
+ "label": "Boolean Run Fill",
+ "name": "Boolean Run Fill",
+ "description": "Fill in gaps in a set of continuous boolean True values, up to a specific size",
+ },
+ {
+ "label": "Boolean Run Mask",
+ "name": "Boolean Run Mask",
+ "description": "Mask a run of boolean values. Potentially trim the start or ending values and specifying a minimum length under which they are considered false",
+ },
+ "break",
+ {
+ "label": "Fallback Float",
+ "name": "Fallback Float",
+ "description": "Use the float attribute specified by name. If the attribute doesn't exist, use the `Fallback` value instead",
+ },
+ {
+ "label": "Fallback Vector",
+ "name": "Fallback Vector",
+ "description": "Use the float attribute specified by name. If the attribute doesn't exist, use the `Fallback` value instead",
+ },
+ {
+ "label": "Fallback Integer",
+ "name": "Fallback Integer",
+ "description": "Use the float attribute specified by name. If the attribute doesn't exist, use the `Fallback` value instead",
+ },
+ {
+ "label": "Fallback Boolean",
+ "name": "Fallback Boolean",
+ "description": "Use the float attribute specified by name. If the attribute doesn't exist, use the `Fallback` value instead",
+ },
+ {
+ "label": "Fallback Color",
+ "name": "Fallback Color",
+ "description": "Use the float attribute specified by name. If the attribute doesn't exist, use the `Fallback` value instead",
+ },
+ "break",
+ {
+ "label": "Group Info",
+ "name": "Group Info",
+ "description": "Based on the Group ID input, return the size of the group and the indices of the first and last items of the group",
+ },
+ {
+ "label": "Centroid",
+ "name": "Centroid",
+ "description": "Calculate the centroid point for the selection for each group in the `Group ID`",
+ },
{
"label": "Vector Angle",
- "name": "MN_utils_vector_angle",
+ "name": "Vector Angle",
"description": "Compute the angle in radians between two vectors.",
},
{
- "label": "Vector Axis Angle",
- "name": "MN_utils_vector_angle_axis",
+ "label": "Dihedral Angle",
+ "name": "Dihedral Angle",
"description": 'Computes the angle between two vectors, AB & CD around around the axis of BC. The first vector AB is treated as the "12 O\'clock" up position, looking down the axis towards C, with angles being return in the range of (-Pi, Pi). Clockwise angles are positive and anti-clockwise angles are negative.',
"video_url": "",
},
- # {
- # 'label': 'Determine Secondary Structure',
- # 'name': 'MN_utils_dssp',
- # 'description': ''
- # },
{
- "label": "Cartoon Utilities",
- "name": ".MN_utils_style_cartoon",
- "description": "The underlying node group which powers the cartoon style",
+ "label": "3 Point Angle",
+ "name": "3 Point Angle",
+ "description": "Calculate the angle between 3 different points. These points are selected based on their index in the point domain, with Index B being the centre of the calculation.\n\nIn the video example, the same calculation that is occurring internally inside of the `MN_topo_edge_angle` node, is being handled explicity by this node. If the `Index` is being used as `Index B` then the current point that is being evaluated is the centre of the angle calculation. If this value is changed, then the point at the corresponding index is used, which results in a smaller angle in the example video.",
+ "video_url": "https://imgur.com/qXyy2ln",
},
{
- "label": "Spheres Cycles",
- "name": ".MN_utils_style_spheres_cycles",
- "description": "A sphere atom representation, visible ONLY in Cycles. Based on point-cloud rendering",
+ "label": "2 Point Angle",
+ "name": "2 Point Angle",
+ "description": "Calculate the angle that two points make, relative to the current point being evaluated. Points are selected based on their index, with the centre of the angle calculation being the current point's position. Equivalent to using 3-Point angle and using `Index` as the `Index B`.\n\nIn the example video, the angle calculation is similar to that of the 3-Point Angle node, but the middle point is always the current point.",
+ "video_url": "https://imgur.com/xp7Vbaj",
},
{
- "label": "Spheres EEVEE",
- "name": ".MN_utils_style_spheres_eevee",
- "description": "A sphere atom representation, visible in EEVEE and Cycles. Based on mesh instancing which slows down viewport performance",
+ "label": "Point Distance",
+ "name": "Point Distance",
+ "description": "Calculate the distance and the vector between the evaluating point and the point selected via the Index.\n\nIn the example video, each point is calculating a vector and a distance between itself and the indexed point. When the Point Mask node is used, this index is then on a per-group basis, so each point in the group points to just the group's corresponding point.",
+ "video_url": "https://imgur.com/AykNvDz",
+ },
+ {
+ "label": "Cartoon Utilities",
+ "name": ".MN_utils_style_cartoon",
+ "description": "The underlying node group which powers the cartoon style",
},
- ],
- "cellpack": [
- {"label": "Pack Instances", "name": "MN_pack_instances", "description": ""}
],
"density": [
{
"label": "Style Surface",
- "name": "MN_density_style_surface",
+ "name": "Style Density Surface",
"description": "A surface made from the electron density given a certain threshold value.",
"video_url": "https://imgur.com/jGgMSd4",
},
{
"label": "Style Wire",
- "name": "MN_density_style_wire",
+ "name": "Style Density Wire",
"description": "A wire surface made from the electron density given a certain threshold value.",
"video_url": "https://imgur.com/jGgMSd4",
},
{
"label": "Sample Nearest Attribute",
- "name": "MN_density_sample_nearest",
+ "name": "Sample Nearest Atoms",
"description": "Sample the nearest atoms from another object, to get the colors or other attributes and apply them to a volume mesh.",
"video_url": "https://imgur.com/UzNwLv2",
},
diff --git a/molecularnodes/ui/node_menu.py b/molecularnodes/ui/node_menu.py
index 91cf96ef..50cd3f9f 100644
--- a/molecularnodes/ui/node_menu.py
+++ b/molecularnodes/ui/node_menu.py
@@ -1,7 +1,7 @@
import bpy
-from .node_info import menu_items
from .func import build_menu
+from .node_info import menu_items
class MN_MT_Node_Color(bpy.types.Menu):
@@ -10,7 +10,7 @@ class MN_MT_Node_Color(bpy.types.Menu):
def draw(self, context):
layout = self.layout
- build_menu(layout, menu_items["color"])
+ build_menu(layout, context, menu_items["color"])
class MN_MT_Node_Bonds(bpy.types.Menu):
@@ -19,7 +19,7 @@ class MN_MT_Node_Bonds(bpy.types.Menu):
def draw(self, context):
layout = self.layout
- build_menu(layout, menu_items["bonds"])
+ build_menu(layout, context, menu_items["bonds"])
class MN_MT_Node_Style(bpy.types.Menu):
@@ -29,7 +29,7 @@ class MN_MT_Node_Style(bpy.types.Menu):
def draw(self, context):
layout = self.layout
layout.operator_context = "INVOKE_DEFAULT"
- build_menu(layout, menu_items["style"])
+ build_menu(layout, context, menu_items["style"])
class MN_MT_Node_Select(bpy.types.Menu):
@@ -39,7 +39,7 @@ class MN_MT_Node_Select(bpy.types.Menu):
def draw(self, context):
layout = self.layout
layout.operator_context = "INVOKE_DEFAULT"
- build_menu(layout, menu_items["select"])
+ build_menu(layout, context, menu_items["select"])
class MN_MT_Node_Assembly(bpy.types.Menu):
@@ -49,7 +49,7 @@ class MN_MT_Node_Assembly(bpy.types.Menu):
def draw(self, context):
layout = self.layout
layout.operator_context = "INVOKE_DEFAULT"
- build_menu(layout, menu_items["assembly"])
+ build_menu(layout, context, menu_items["ensemble"])
class MN_MT_Node_DNA(bpy.types.Menu):
@@ -58,7 +58,7 @@ class MN_MT_Node_DNA(bpy.types.Menu):
def draw(self, context):
layout = self.layout
- build_menu(layout, menu_items["DNA"])
+ build_menu(layout, context, menu_items["DNA"])
class MN_MT_Node_Animate(bpy.types.Menu):
@@ -67,7 +67,7 @@ class MN_MT_Node_Animate(bpy.types.Menu):
def draw(self, context):
layout = self.layout
- build_menu(layout, menu_items["animate"])
+ build_menu(layout, context, menu_items["animate"])
class MN_MT_Node_Utils(bpy.types.Menu):
@@ -75,16 +75,7 @@ class MN_MT_Node_Utils(bpy.types.Menu):
bl_label = ""
def draw(self, context):
- build_menu(self.layout, menu_items["utils"])
-
-
-class MN_MT_Node_CellPack(bpy.types.Menu):
- bl_idname = "MN_MT_NODE_CELLPACK"
- bl_label = ""
-
- def draw(self, context):
- layout = self.layout
- build_menu(layout, menu_items["cellpack"])
+ build_menu(self.layout, context, menu_items["utils"])
class MN_MT_Node_Density(bpy.types.Menu):
@@ -94,7 +85,7 @@ class MN_MT_Node_Density(bpy.types.Menu):
def draw(self, context):
layout = self.layout
layout.operator_context = "INVOKE_DEFAULT"
- build_menu(layout, menu_items["density"])
+ build_menu(layout, context, menu_items["density"])
class MN_MT_Node_Topology(bpy.types.Menu):
@@ -104,7 +95,7 @@ class MN_MT_Node_Topology(bpy.types.Menu):
def draw(self, context):
layout = self.layout
layout.operator_context = "INVOKE_DEFAULT"
- build_menu(layout, menu_items["topology"])
+ build_menu(layout, context, menu_items["topology"])
def draw_node_menus(self, context):
@@ -112,12 +103,11 @@ def draw_node_menus(self, context):
layout.separator()
layout.label(text="Molecular Nodes", icon="MOD_PARTICLES")
layout.menu("MN_MT_NODE_STYLE", text="Style", icon_value=77)
- layout.menu("MN_MT_NODE_SELECT", text="Selection", icon_value=256)
+ layout.menu("MN_MT_NODE_SELECT", text="Select", icon="RESTRICT_SELECT_OFF")
layout.menu("MN_MT_NODE_COLOR", text="Color", icon="COLORSET_07_VEC")
layout.menu("MN_MT_NODE_ANIMATE", text="Animation", icon_value=409)
layout.menu("MN_MT_NODE_TOPOLOGY", text="Topology", icon="ORIENTATION_CURSOR")
- layout.menu("MN_MT_NODE_ASSEMBLY", text="Assemblies", icon="GROUP_VERTEX")
- layout.menu("MN_MT_NODE_CELLPACK", text="CellPack", icon="PARTICLE_POINT")
+ layout.menu("MN_MT_NODE_ASSEMBLY", text="Ensemble", icon="GROUP_VERTEX")
layout.menu("MN_MT_NODE_DENSITY", text="Density", icon="VOLUME_DATA")
layout.menu("MN_MT_NODE_DNA", text="DNA", icon="GP_SELECT_BETWEEN_STROKES")
layout.menu("MN_MT_NODE_UTILS", text="Utilities", icon_value=92)
@@ -135,3 +125,18 @@ def MN_add_node_menu(self, context):
if "GeometryNodeTree" == bpy.context.area.spaces[0].tree_type:
layout = self.layout
layout.menu("MN_MT_NODE", text="Molecular Nodes", icon_value=88)
+
+
+CLASSES = [
+ MN_MT_Node,
+ MN_MT_Node_Animate,
+ MN_MT_Node_Assembly,
+ MN_MT_Node_Bonds,
+ MN_MT_Node_Color,
+ MN_MT_Node_Density,
+ MN_MT_Node_DNA,
+ MN_MT_Node_Style,
+ MN_MT_Node_Select,
+ MN_MT_Node_Topology,
+ MN_MT_Node_Utils,
+]
diff --git a/molecularnodes/ui/ops.py b/molecularnodes/ui/ops.py
deleted file mode 100644
index ddc75912..00000000
--- a/molecularnodes/ui/ops.py
+++ /dev/null
@@ -1,154 +0,0 @@
-import bpy
-from ..blender import nodes
-
-
-class MN_OT_Add_Custom_Node_Group(bpy.types.Operator):
- bl_idname = "mn.add_custom_node_group"
- bl_label = "Add Custom Node Group"
- # bl_description = "Add Molecular Nodes custom node group."
- bl_options = {"REGISTER", "UNDO"}
- node_name: bpy.props.StringProperty(
- name="node_name", description="", default="", subtype="NONE", maxlen=0
- )
- node_label: bpy.props.StringProperty(name="node_label", default="")
- node_description: bpy.props.StringProperty(
- name="node_description",
- description="",
- default="Add MolecularNodes custom node group.",
- subtype="NONE",
- )
- node_link: bpy.props.BoolProperty(name="node_link", default=True)
-
- @classmethod
- def description(cls, context, properties):
- return properties.node_description
-
- def execute(self, context):
- try:
- nodes.append(self.node_name, link=self.node_link)
- nodes.add_node(self.node_name) # , label=self.node_label)
- except RuntimeError:
- self.report(
- {"ERROR"},
- message="Failed to add node. Ensure you are not in edit mode.",
- )
- return {"FINISHED"}
-
-
-class MN_OT_Assembly_Bio(bpy.types.Operator):
- bl_idname = "mn.assembly_bio"
- bl_label = "Build"
- bl_description = "Adds node to build biological assembly based on symmetry operations that are extraced from the structure file"
- bl_options = {"REGISTER", "UNDO"}
-
- inset_node: bpy.props.BoolProperty(default=False)
-
- @classmethod
- def poll(self, context):
- # this just checks to see that there is some biological assembly information that
- # is associated with the object / molecule. If there isn't then the assembly
- # operator will be greyed out and unable to be executed
- bob = context.active_object
- try:
- bob["biological_assemblies"]
- return True
- except KeyError:
- False
-
- def execute(self, context):
- bob = context.active_object
- try:
- if self.inset_node:
- nodes.assembly_insert(bob)
- else:
- tree_assembly = nodes.assembly_initialise(bob)
- nodes.add_node(tree_assembly.name)
- except (KeyError, ValueError) as e:
- self.report({"ERROR"}, "Unable to build biological assembly node.")
- self.report({"ERROR"}, str(e))
- return {"CANCELLED"}
-
- return {"FINISHED"}
-
-
-class MN_OT_iswitch_custom(bpy.types.Operator):
- bl_idname = "mn.iswitch_custom"
- # bl_idname = "mn.selection_custom"
- bl_label = "Chain Selection"
- bl_options = {"REGISTER", "UNDO"}
-
- description: bpy.props.StringProperty(name="Description")
- dtype: bpy.props.EnumProperty( # type: ignore
- name="Data type",
- items=(
- ("RGBA", "RGBA", "Color iswitch."),
- ("BOOLEAN", "BOOLEAN", "Boolean iswitch"),
- ),
- )
- field: bpy.props.StringProperty(name="field", default="chain_id")
- prefix: bpy.props.StringProperty(name="prefix", default="Chain ")
- node_property: bpy.props.StringProperty(name="node_property", default="chain_ids")
- node_name: bpy.props.StringProperty(name="node_name", default="chain")
- starting_value: bpy.props.IntProperty(name="starting_value", default=0)
-
- @classmethod
- def description(cls, context, properties):
- return properties.description
-
- def execute(self, context):
- object = context.view_layer.objects.active
- prop = object[self.node_property]
- name = object.name
- if not prop:
- self.report(
- {"WARNING"},
- message=f"{self.node_property} not available for {object.name}.",
- )
- return {"CANCELLED"}
-
- if self.dtype == "BOOLEAN":
- node_name = f"MN_select_{self.node_name}_{name}"
- elif self.dtype == "RGBA":
- node_name = f"MN_color_{self.node_name}_{name}"
- else:
- raise ValueError(f"Data type not supported {self.dtype}")
-
- node_chains = nodes.custom_iswitch(
- name=node_name,
- dtype=self.dtype,
- iter_list=prop,
- start=self.starting_value,
- field=self.field,
- prefix=self.prefix,
- )
-
- nodes.add_node(node_chains.name)
-
- return {"FINISHED"}
-
-
-class MN_OT_Residues_Selection_Custom(bpy.types.Operator):
- bl_idname = "mn.residues_selection_custom"
- bl_label = "Multiple Residue Selection"
- bl_description = "Create a selection based on the provided residue strings.\nThis \
- node is built on a per-molecule basis, taking into account the residues that \
- were input."
- bl_options = {"REGISTER", "UNDO"}
-
- input_resid_string: bpy.props.StringProperty(
- name="Select residue IDs: ",
- description="Enter a string value.",
- default="19,94,1-16",
- )
-
- def execute(self, context):
- node_residues = nodes.resid_multiple_selection(
- node_name="MN_select_res_id_custom",
- input_resid_string=self.input_resid_string,
- )
-
- nodes.add_node(node_residues.name)
- return {"FINISHED"}
-
- def invoke(self, context, event):
- return context.window_manager.invoke_props_dialog(self)
diff --git a/molecularnodes/ui/panel.py b/molecularnodes/ui/panel.py
index 833874b4..03a03b79 100644
--- a/molecularnodes/ui/panel.py
+++ b/molecularnodes/ui/panel.py
@@ -1,14 +1,22 @@
import bpy
-from .. import pkg
+
+from ..entities.trajectory import dna
+
from ..blender import nodes
-from ..io import wwpdb, local, star, cellpack, md, density, dna, alphafold
+from ..session import get_session
+from ..entities import density, ensemble, molecule, trajectory
bpy.types.Scene.MN_panel = bpy.props.EnumProperty(
name="Panel Selection",
items=(
("import", "Import", "Import macromolecules", 0),
("object", "Object", "Adjust settings affecting the selected object", 1),
- ("scene", "Scene", "Change settings for the world and rendering", 2),
+ (
+ "session",
+ "Session",
+ "Interacting with the Molecular Nodes session tracking all of the objects",
+ 2,
+ ),
),
)
@@ -25,16 +33,35 @@
("dna", "oxDNA", "Import an oxDNA file"),
),
)
+STYLE_ITEMS = (
+ ("spheres", "Spheres", "Space-filling atoms style."),
+ ("cartoon", "Cartoon", "Secondary structure cartoons"),
+ ("surface", "Surface", "Solvent-accsible surface."),
+ ("ribbon", "Ribbon", "Continuous backbone ribbon."),
+ ("sticks", "Sticks", "Sticks for each bond."),
+ ("ball_and_stick", "Ball and Stick", "Spheres for atoms, sticks for bonds"),
+ ("preset_1", "Preset 1", "A pre-made combination of different styles"),
+ ("preset_2", "Preset 2", "A pre-made combination of different styles"),
+ ("preset_3", "Preset 3", "A pre-made combination of different styles"),
+ ("preset_4", "Preset 4", "A pre-made combination of different styles"),
+)
+
+bpy.types.Scene.MN_import_style = bpy.props.EnumProperty(
+ name="Style",
+ description="Default style for importing molecules.",
+ items=STYLE_ITEMS,
+ default="spheres",
+)
chosen_panel = {
- "pdb": wwpdb,
- "local": local,
- "alphafold": alphafold,
- "star": star,
- "md": md,
- "density": density,
- "cellpack": cellpack,
- "dna": dna,
+ "pdb": molecule.ui.panel_wwpdb,
+ "local": molecule.ui.panel_local,
+ "alphafold": molecule.ui.panel_alphafold,
+ "star": ensemble.ui.panel_starfile,
+ "md": trajectory.ui.panel,
+ "density": density.ui.panel,
+ "cellpack": ensemble.ui.panel_cellpack,
+ "dna": dna.panel,
}
packages = {
@@ -49,94 +76,38 @@
}
-class MN_OT_Swap_Style_Node(bpy.types.Operator):
- bl_idname = "mn.style_change_node"
- bl_label = "Style"
-
- style: bpy.props.EnumProperty(name="Style", items=nodes.STYLE_ITEMS) # type: ignore
-
- @classmethod
- def poll(self, context):
- node = context.space_data.edit_tree.nodes.active
- return node.name.startswith("MN_style")
-
- def execute(self, context):
- nodes.swap_style_node(
- tree=context.space_data.node_tree,
- node_style=context.space_data.edit_tree.nodes.active,
- style=self.style,
- )
- return {"FINISHED"}
-
-
-def change_style_menu(self, context):
+def pt_object_context(self, context):
layout = self.layout
- bob = context.active_object
- layout.label(text="Molecular Nodes")
-
- current_style = nodes.format_node_name(
- nodes.get_style_node(bob).node_tree.name
- ).replace("Style ", "")
- layout.operator_menu_enum("mn.style_change", "style", text="Style")
- # ui_from_node(layout.row(), nodes.get_style_node(bob))
- layout.separator()
+ return None
def is_style_node(context):
node = context.space_data.edit_tree.nodes.active
- return node.name.startswith("MN_style")
+ return node.name.startswith("Style")
def change_style_node_menu(self, context):
layout = self.layout
+ node = context.active_node
+ prefix = node.node_tree.name.split(" ")[0].lower()
+ if prefix not in ["color", "select", "is", "style", "topology", "animate"]:
+ return None
layout.label(text="Molecular Nodes", icon="MOD_PARTICLES")
+
row = layout.row()
- if is_style_node(context):
- node = context.active_node
- row.operator_menu_enum("mn.style_change_node", "style", text="Change Style")
- else:
- pass
- # layout.label(text="test")
+ op = row.operator_menu_enum("mn.node_swap", "node_items", text="Change Node")
+ op.node_description = "The topology nodes"
layout.separator()
-class MN_OT_Change_Style(bpy.types.Operator):
- bl_idname = "mn.style_change"
- bl_label = "Style"
-
- style: bpy.props.EnumProperty(name="Style", items=nodes.STYLE_ITEMS)
-
- def execute(self, context):
- object = context.active_object
- nodes.change_style_node(object, self.style)
-
- return {"FINISHED"}
-
-
-def check_installs(selection):
- for package in packages[selection]:
- if not pkg.is_current(package):
- return False
-
- return True
-
-
def panel_import(layout, context):
scene = context.scene
selection = scene.MN_panel_import
layout.prop(scene, "MN_panel_import")
- install_required = not check_installs(selection)
- buttons = layout.column(align=True)
-
- if install_required:
- buttons.label(text="Please install the requried packages.")
- for package in packages[selection]:
- pkg.button_install_pkg(buttons, package, pkg.get_pkgs()[package]["version"])
col = layout.column()
- col.enabled = not install_required
- chosen_panel[selection].panel(col, scene)
+ chosen_panel[selection](col, scene)
def ui_from_node(layout, node):
@@ -162,34 +133,117 @@ def ui_from_node(layout, node):
col.template_node_view(ntree, node, node.inputs[item.identifier])
+def panel_md_properties(layout, context):
+ obj = context.active_object
+ session = get_session()
+ universe = session.trajectories.get(obj.mn.uuid)
+
+ layout.label(text="Trajectory Playback", icon="OPTIONS")
+ row = layout.row()
+ row.prop(obj.mn, "subframes")
+ row.prop(obj.mn, "interpolate")
+
+ # only enable this as an option if the universe is orthothombic
+ col = row.column()
+ col.prop(obj.mn, "correct_periodic")
+ col.enabled = universe.is_orthorhombic
+
+ layout.label(text="Selections", icon="RESTRICT_SELECT_OFF")
+ row = layout.row()
+ row = row.split(factor=0.9)
+ row.template_list(
+ "MN_UL_TrajectorySelectionListUI",
+ "A list",
+ obj,
+ "mn_trajectory_selections",
+ obj.mn,
+ "trajectory_selection_index",
+ rows=3,
+ )
+ col = row.column()
+ col.operator("mn.trajectory_selection_add", icon="ADD", text="")
+ col.operator("mda.delete_item", icon="REMOVE", text="")
+ if obj.mn_trajectory_selections:
+ item = obj.mn_trajectory_selections[obj.mn.trajectory_selection_index]
+
+ col = layout.column(align=False)
+ row = col.row()
+ col.prop(item, "selection_str")
+
+ # disable editing for immutable selections
+ # disable modifying updating and periodic
+ if item.immutable:
+ col.enabled = False
+
+ if item.message != "":
+ box = col.box()
+ box.label(text="Invalid Selection", icon="ERROR")
+ box.label(text=item.message)
+ box.alert = True
+ op = box.operator("wm.url_open", text="Selection Langauge Docs", icon="URL")
+ op.url = (
+ "https://docs.mdanalysis.org/stable/documentation_pages/selections.html"
+ )
+
+
def panel_object(layout, context):
object = context.active_object
- mol_type = object.mn.molecule_type
+ try:
+ mol_type = object.mn.molecule_type
+ except AttributeError:
+ return None
if mol_type == "":
layout.label(text="No MN object selected")
return None
-
if mol_type == "pdb":
layout.label(text=f"PDB: {object.mn.pdb_code.upper()}")
if mol_type == "md":
- layout.prop(object.mn, "subframes")
+ panel_md_properties(layout, context)
if mol_type == "star":
- layout.label(text=f"Ensemble")
+ layout.label(text="Ensemble")
box = layout.box()
ui_from_node(box, nodes.get_star_node(object))
- return
-
- row = layout.row(align=True)
- row.label(text="Style")
- current_style = nodes.format_node_name(
- nodes.get_style_node(object).node_tree.name
- ).replace("Style ", "")
- row.operator_menu_enum("mn.style_change", "style", text=current_style)
- box = layout.box()
- ui_from_node(box, nodes.get_style_node(object))
+ return None
+
+
+def item_ui(layout, item):
+ row = layout.row()
+ row.label(text=item.name)
+ col = row.column()
+ op = col.operator("mn.session_create_object")
+ op.uuid = item.uuid
+ col.enabled = item.object is None
+
+ op = row.operator("mn.session_remove_item", text="", icon="CANCEL")
+ op.uuid = item.uuid
+
+ if item.object is not None:
+ row = layout.row()
+ row.label(text=f"Object: {item.object.name}", icon="OUTLINER_OB_MESH")
+
+
+def panel_session(layout, context):
+ session = get_session(context)
+ # if session.n_items > 0:
+ # return None
row = layout.row()
- row.label(text="Experimental", icon_value=2)
- row.operator("mn.add_armature")
+ row.label(text="Loaded items in the session")
+ # row.operator("mn.session_reload")
+
+ layout.label(text="Molecules")
+ box = layout.box()
+ for mol in session.molecules.values():
+ item_ui(box, mol)
+
+ layout.label(text="Universes")
+ box = layout.box()
+ for uni in session.trajectories.values():
+ item_ui(box, uni)
+
+ layout.label(text="Ensembles")
+ box = layout.box()
+ for ens in session.ensembles.values():
+ item_ui(box, ens)
def panel_scene(layout, context):
@@ -232,7 +286,7 @@ def panel_scene(layout, context):
focus.prop(cam.dof, "aperture_fstop")
-class MN_PT_panel(bpy.types.Panel):
+class MN_PT_Scene(bpy.types.Panel):
bl_label = "Molecular Nodes"
bl_idname = "MN_PT_panel"
bl_space_type = "PROPERTIES"
@@ -246,14 +300,17 @@ def draw(self, context):
layout = self.layout
scene = context.scene
row = layout.row(align=True)
- for p in ["import", "object", "scene"]:
+ for p in ["import", "object", "session"]:
row.prop_enum(scene, "MN_panel", p)
# the possible panel functions to choose between
which_panel = {
"import": panel_import,
- "scene": panel_scene,
"object": panel_object,
+ "session": panel_session,
}
# call the required panel function with the layout and context
which_panel[scene.MN_panel](layout, context)
+
+
+CLASSES = []
diff --git a/molecularnodes/ui/pref.py b/molecularnodes/ui/pref.py
index 68079fc9..7a4f9466 100644
--- a/molecularnodes/ui/pref.py
+++ b/molecularnodes/ui/pref.py
@@ -1,44 +1,54 @@
import bpy
-import pathlib
-from .. import pkg
-from bpy.types import AddonPreferences
-install_instructions = "https://bradyajohnston.github.io/MolecularNodes/installation.html#installing-biotite-mdanalysis"
-ADDON_DIR = pathlib.Path(__file__).resolve().parent.parent
+from .. import __package__, template
-bpy.types.Scene.pypi_mirror_provider = bpy.props.StringProperty(
- name='pypi_mirror_provider',
- description='PyPI Mirror Provider',
- options={'TEXTEDIT_UPDATE', 'LIBRARY_EDITABLE'},
- default='Default',
- subtype='NONE',
- search=pkg.get_pypi_mirror_alias,
-)
-# Defines the preferences panel for the addon, which shows the buttons for
-# installing and reinstalling the required python packages defined in 'requirements.txt'
+class MN_OT_Template_Install(bpy.types.Operator):
+ bl_idname = "mn.template_install"
+ bl_label = "Install Template"
+ bl_description = "Install the Molecular Nodes startup template file."
+ def execute(self, context):
+ template.install()
+ self.report({"INFO"}, "Installed Molecular Nodes template.")
+ return {"FINISHED"}
-class MolecularNodesPreferences(AddonPreferences):
- bl_idname = 'molecularnodes'
+
+class MN_OT_Template_Uninstall(bpy.types.Operator):
+ bl_idname = "mn.template_uninstall"
+ bl_label = "Uninstall Template"
+ bl_description = "Uninstall the Molecular Nodes startup template file."
+
+ @classmethod
+ def poll(cls, context):
+ return template.is_installed()
+
+ def execute(self, context):
+ try:
+ template.uninstall()
+ self.report({"INFO"}, "Uninstalled Molecular Nodes template.")
+ except FileNotFoundError:
+ self.report({"WARNING"}, "Template not installed.")
+
+ return {"FINISHED"}
+
+
+class MolecularNodesPreferences(bpy.types.AddonPreferences):
+ bl_idname = __package__
def draw(self, context):
layout = self.layout
- layout.label(text="Install the required packages for MolecularNodes.")
-
- col_main = layout.column(heading='', align=False)
- row_import = col_main.row()
- row_import.prop(bpy.context.scene,
- 'pypi_mirror_provider', text='Set PyPI Mirror')
-
- pkgs = pkg.get_pkgs()
- for package in pkgs.values():
- row = layout.row()
- col = row.column()
- row = col.row()
- pkg.button_install_pkg(
- layout=row,
- name=package.get('name'),
- version=package.get('version'),
- desc=package.get('desc')
- )
+ layout.label(
+ text="Install the Molecular Nodes template file, to start Blender with useful default settings"
+ )
+ row = layout.row()
+ if not template.is_installed():
+ text = "Install Template"
+ else:
+ text = "Reinstall Template"
+
+ row.operator("mn.template_install", text=text)
+ row.operator("mn.template_uninstall")
+
+
+CLASSES = [MN_OT_Template_Install, MN_OT_Template_Uninstall, MolecularNodesPreferences]
diff --git a/molecularnodes/utils.py b/molecularnodes/utils.py
index e38a24af..eb2ec6b6 100644
--- a/molecularnodes/utils.py
+++ b/molecularnodes/utils.py
@@ -1,12 +1,32 @@
-import bpy
-import traceback
import os
-import zipfile
+from pathlib import Path
+
import numpy as np
from mathutils import Matrix
-from bpy.app.translations import pgettext_tip as tip_
-from .ui.pref import ADDON_DIR
+ADDON_DIR = Path(__file__).resolve().parent
+MN_DATA_FILE = os.path.join(ADDON_DIR, "assets", "MN_data_file_4.2.blend")
+
+
+def correct_periodic_1d(value1, value2, boundary):
+ diff = value2 - value1
+ half = boundary / 2
+ value2[diff > half] -= boundary
+ value2[diff < -half] += boundary
+ return value2
+
+
+def correct_periodic_positions(positions_1, positions_2, dimensions):
+ if not np.allclose(dimensions[3:], 90.0):
+ raise ValueError(
+ f"Only works with orthorhombic unitcells, and not dimensions={dimensions}"
+ )
+ final_positions = positions_2.copy()
+ for i in range(3):
+ final_positions[:, i] = correct_periodic_1d(
+ positions_1[:, i], positions_2[:, i], dimensions[i]
+ )
+ return final_positions
def lerp(a: np.ndarray, b: np.ndarray, t: float = 0.5) -> np.ndarray:
@@ -47,127 +67,13 @@ def lerp(a: np.ndarray, b: np.ndarray, t: float = 0.5) -> np.ndarray:
return np.add(a, np.multiply(np.subtract(b, a), t))
-def _module_filesystem_remove(path_base, module_name):
- # taken from the bpy.ops.preferences.app_template_install() operator source code
- # Remove all Python modules with `module_name` in `base_path`.
- # The `module_name` is expected to be a result from `_zipfile_root_namelist`.
- import os
- import shutil
- module_name = os.path.splitext(module_name)[0]
- for f in os.listdir(path_base):
- f_base = os.path.splitext(f)[0]
- if f_base == module_name:
- f_full = os.path.join(path_base, f)
- if os.path.isdir(f_full):
- shutil.rmtree(f_full)
- else:
- os.remove(f_full)
-
-
-def _zipfile_root_namelist(file_to_extract):
- # taken from the bpy.ops.preferences.app_template_install() operator source code
- # Return a list of root paths from zipfile.ZipFile.namelist.
- import os
- root_paths = []
- for f in file_to_extract.namelist():
- # Python's `zipfile` API always adds a separate at the end of directories.
- # use `os.path.normpath` instead of `f.removesuffix(os.sep)`
- # since paths could be stored as `./paths/./`.
- #
- # Note that `..` prefixed paths can exist in ZIP files but they don't write to parent directory when extracting.
- # Nor do they pass the `os.sep not in f` test, this is important,
- # otherwise `shutil.rmtree` below could made to remove directories outside the installation directory.
- f = os.path.normpath(f)
- if os.sep not in f:
- root_paths.append(f)
- return root_paths
-
-
-def template_install():
- print(os.path.abspath(ADDON_DIR))
- template = os.path.join(os.path.abspath(ADDON_DIR),
- 'assets', 'template', 'Molecular Nodes.zip')
- _install_template(template)
- bpy.utils.refresh_script_paths()
-
-
-def template_uninstall():
- import shutil
- for folder in bpy.utils.app_template_paths():
- path = os.path.join(os.path.abspath(folder), 'MolecularNodes')
- if os.path.exists(path):
- shutil.rmtree(path)
- bpy.utils.refresh_script_paths()
-
-
-def _install_template(filepath, subfolder='', overwrite=True):
- # taken from the bpy.ops.preferences.app_template_install() operator source code
-
- path_app_templates = bpy.utils.user_resource(
- 'SCRIPTS',
- path=os.path.join("startup", "bl_app_templates_user", subfolder),
- create=True,
- )
-
- if not os.path.isdir(path_app_templates):
- try:
- os.makedirs(path_app_templates, exist_ok=True)
- except:
- traceback.print_exc()
-
- app_templates_old = set(os.listdir(path_app_templates))
-
- # check to see if the file is in compressed format (.zip)
- if zipfile.is_zipfile(filepath):
- try:
- file_to_extract = zipfile.ZipFile(filepath, 'r')
- except:
- traceback.print_exc()
- return {'CANCELLED'}
-
- file_to_extract_root = _zipfile_root_namelist(file_to_extract)
- if overwrite:
- for f in file_to_extract_root:
- _module_filesystem_remove(path_app_templates, f)
- else:
- for f in file_to_extract_root:
- path_dest = os.path.join(
- path_app_templates, os.path.basename(f))
- if os.path.exists(path_dest):
- # self.report({'WARNING'}, tip_("File already installed to %r\n") % path_dest)
- return {'CANCELLED'}
-
- try: # extract the file to "bl_app_templates_user"
- file_to_extract.extractall(path_app_templates)
- except:
- traceback.print_exc()
- return {'CANCELLED'}
-
- else:
- # Only support installing zipfiles
- print('no zipfile')
- return {'CANCELLED'}
-
- app_templates_new = set(os.listdir(path_app_templates)) - app_templates_old
-
- # in case a new module path was created to install this addon.
- bpy.utils.refresh_script_paths()
-
- # print message
- msg = (
- tip_("Template Installed (%s) from %r into %r") %
- (", ".join(sorted(app_templates_new)), filepath, path_app_templates)
- )
- print(msg)
-
-
# data types for the np.array that will store per-chain symmetry operations
dtype = [
- ('assembly_id', int),
- ('transform_id', int),
- ('chain_id', 'U10'),
- ('rotation', float, 4), # quaternion form
- ('translation', float, 3)
+ ("assembly_id", int),
+ ("transform_id", int),
+ ("chain_id", "U10"),
+ ("rotation", float, 4), # quaternion form
+ ("translation", float, 3),
]
@@ -186,11 +92,11 @@ def array_quaternions_from_dict(transforms_dict):
matrix = transform[1]
arr = np.zeros((len(chains)), dtype=dtype)
translation, rotation, scale = Matrix(matrix).decompose()
- arr['assembly_id'] = i + 1
- arr['transform_id'] = j
- arr['chain_id'] = chains
- arr['rotation'] = rotation
- arr['translation'] = translation
+ arr["assembly_id"] = i + 1
+ arr["transform_id"] = j
+ arr["chain_id"] = chains
+ arr["rotation"] = rotation
+ arr["translation"] = translation
transforms.append(arr)
return np.hstack(transforms)
diff --git a/pyproject.toml b/pyproject.toml
index 9fc113e3..3bb22b87 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
[tool.poetry]
name = "molecularnodes"
-version = "4.1.4"
+version = "4.2.0"
description = "Toolbox for molecular animations with Blender and Geometry Nodes."
authors = ["Brady Johnston "]
license = "MIT"
@@ -12,7 +12,7 @@ documentation = "https://bradyajohnston.github.io/MolecularNodes"
[tool.poetry.dependencies]
python = "~=3.11.0"
-bpy = "~=4.1"
+# bpy = "~=4.1"
MDAnalysis = "~=2.7.0"
biotite = "==0.40.0"
mrcfile = "==1.4.3"
@@ -26,6 +26,7 @@ pytest-cov = "*"
syrupy = "*"
quartodoc = "*"
scipy = "*"
+tomlkit = "*"
[build-system]
diff --git a/molecularnodes/requirements.txt b/requirements.txt
similarity index 100%
rename from molecularnodes/requirements.txt
rename to requirements.txt
diff --git a/tests/__snapshots__/test_load.ambr b/tests/__snapshots__/test_load.ambr
index ca7db618..6632172e 100644
--- a/tests/__snapshots__/test_load.ambr
+++ b/tests/__snapshots__/test_load.ambr
@@ -384,107 +384,227 @@
[ 2.2e-01 5.4e-02 -4.0e-02]
[ 3.3e-01 8.1e-02 9.6e-02]]
# ---
-# name: test_rcsb_nmr
- [[-0.0 -0.0 -0.1]
- [ 0.1 -0.1 -0.1]
- [ 0.1 0.2 0.0]
- [-0.1 0.0 0.0]
- [ 0.1 -0.0 0.0]
- [ 0.1 -0.0 -0.0]
- [-0.1 -0.1 0.1]
- [ 0.0 0.1 -0.1]
- [-0.1 0.1 -0.0]
- [ 0.1 0.0 0.0]
- [ 0.1 0.1 0.0]
- [ 0.1 -0.1 -0.1]
- [-0.0 -0.0 0.1]
- [ 0.1 0.1 0.0]
- [ 0.1 0.0 -0.2]
- [ 0.1 0.0 -0.3]
- [-0.0 -0.1 0.0]
- [-0.0 -0.0 0.1]
- [ 0.1 0.2 0.0]
- [-0.1 -0.0 -0.1]
- [ 0.1 0.1 0.0]
- [-0.1 0.1 -0.1]
- [-0.0 -0.1 0.1]
- [-0.0 0.1 -0.1]
- [ 0.1 0.1 0.0]
- [ 0.1 0.1 0.0]
- [-0.1 -0.0 0.1]
- [-0.0 -0.1 0.0]
- [-0.0 -0.0 0.1]
- [ 0.0 0.1 -0.0]
- [-0.0 -0.1 0.0]
- [ 0.0 0.1 0.0]
- [-0.0 -0.0 0.1]
- [-0.0 0.1 -0.1]
- [ 0.1 -0.1 -0.1]
- [-0.0 -0.0 0.1]
- [ 0.1 -0.0 -0.2]
- [ 0.1 -0.0 -0.1]
- [-0.0 0.1 -0.0]
- [-0.0 0.1 -0.1]
- [ 0.1 0.1 0.0]
- [ 0.1 0.1 0.0]
- [ 0.0 0.1 0.0]
- [-0.0 0.1 -0.1]
- [ 0.1 -0.1 -0.1]
- [-0.1 -0.0 -0.1]
- [ 0.1 -0.0 -0.1]
- [ 0.1 -0.0 -0.2]
- [-0.0 -0.0 0.1]
- [ 0.0 -0.1 -0.0]
- [ 0.1 0.2 0.0]
- [-0.1 0.1 -0.0]
- [-0.0 -0.0 0.1]
- [-0.1 -0.1 -0.0]
- [ 0.1 -0.1 -0.1]
- [ 0.1 0.0 -0.0]
- [ 0.1 -0.0 -0.0]
- [-0.1 -0.0 0.1]
- [ 0.1 0.0 -0.2]
- [ 0.0 0.0 0.1]
- [-0.0 0.0 0.2]
- [ 0.0 -0.0 0.1]
- [ 0.1 0.0 0.1]
- [-0.1 0.1 -0.1]
- [-0.0 0.1 -0.0]
- [ 0.0 0.1 -0.1]
- [ 0.0 0.0 -0.1]
- [ 0.1 -0.0 -0.2]
- [-0.1 -0.1 -0.0]
- [ 0.0 0.1 -0.0]
- [ 0.1 -0.0 -0.1]
- [ 0.1 -0.1 -0.1]
- [ 0.0 0.0 0.0]
- [-0.0 -0.0 0.2]
- [ 0.1 0.1 0.0]
- [-0.1 -0.1 0.0]
- [-0.0 -0.1 0.1]
- [-0.1 -0.0 0.1]
- [ 0.1 0.1 0.0]
- [-0.1 -0.0 -0.1]
- [-0.1 -0.0 0.1]
- [-0.1 -0.0 0.1]
- [-0.1 -0.1 -0.0]
- [-0.0 0.0 -0.1]
- [ 0.1 -0.0 -0.2]
- [ 0.1 0.1 0.0]
- [-0.1 -0.1 0.1]
- [ 0.0 0.1 0.0]
- [ 0.1 0.1 0.0]
- [-0.1 -0.0 -0.0]
- [-0.0 -0.0 0.1]
- [ 0.1 0.2 0.0]
- [-0.1 -0.0 0.1]
- [ 0.1 -0.1 -0.1]
- [ 0.0 -0.0 0.1]
- [ 0.1 0.0 0.1]
- [ 0.1 0.0 -0.2]
- [ 0.1 -0.0 -0.1]
- [ 0.1 0.1 0.0]
- [-0.0 0.1 -0.1]]
+# name: test_rcsb_nmr[False]
+ [[ 0.1 0.0 -0.1]
+ [ 0.1 0.0 -0.1]
+ [ 0.1 0.0 -0.1]
+ ...
+ [ 0.1 -0.0 -0.3]
+ [ 0.1 -0.0 -0.3]
+ [ 0.1 -0.0 -0.3]]
+# ---
+# name: test_rcsb_nmr[False].1
+ [[-9.5e-02 -2.8e-02 5.5e-02]
+ [-2.1e-02 3.8e-02 2.3e-02]
+ [-3.5e-02 1.0e-01 -7.1e-02]
+ [ 1.3e-01 2.5e-02 -5.2e-02]
+ [ 6.0e-02 2.2e-02 4.6e-02]
+ [ 1.1e-01 -1.3e-02 -1.3e-02]
+ [-2.0e-02 7.1e-03 -6.4e-02]
+ [ 9.2e-02 -6.0e-03 -2.1e-01]
+ [-1.1e-01 -5.3e-02 9.7e-02]
+ [-6.9e-02 6.4e-02 -9.0e-02]
+ [ 1.4e-01 8.6e-02 6.3e-03]
+ [-1.6e-02 4.6e-04 1.6e-01]
+ [-1.4e-02 8.6e-03 8.3e-02]
+ [ 1.0e-01 -1.4e-02 -2.1e-02]
+ [-2.3e-02 1.2e-01 -8.5e-02]
+ [-1.7e-02 -1.3e-01 1.2e-02]
+ [ 7.5e-02 1.3e-01 -2.1e-02]
+ [-7.4e-02 -2.3e-02 9.6e-03]
+ [ 4.0e-02 1.1e-01 3.2e-02]
+ [ 9.3e-02 -1.2e-02 -2.8e-01]
+ [ 4.0e-02 8.6e-02 3.3e-02]
+ [-1.8e-02 -1.2e-01 6.7e-02]
+ [ 8.9e-02 7.6e-02 3.9e-02]
+ [ 9.4e-02 1.0e-01 2.5e-02]
+ [ 1.2e-01 4.5e-03 -4.4e-02]
+ [ 9.3e-02 -9.4e-03 -2.1e-01]
+ [-6.5e-02 -9.8e-02 6.7e-02]
+ [ 2.3e-03 8.5e-02 1.4e-02]
+ [ 3.1e-02 1.3e-01 -1.2e-02]
+ [-4.1e-02 -3.3e-02 1.1e-01]
+ [ 3.9e-02 7.9e-02 3.2e-02]
+ [ 1.4e-01 4.4e-02 -9.3e-03]
+ [ 9.0e-02 1.3e-01 -1.6e-02]
+ [ 5.1e-02 -2.6e-02 -5.2e-02]
+ [-6.6e-02 6.5e-02 -2.3e-02]
+ [ 2.8e-02 1.1e-01 1.7e-02]
+ [-1.3e-02 -1.4e-01 1.9e-02]
+ [ 1.2e-01 -5.1e-02 -1.3e-01]
+ [ 7.6e-02 -7.6e-03 1.2e-01]
+ [ 4.1e-02 1.1e-01 3.9e-02]
+ [ 1.0e-01 1.5e-02 2.2e-02]
+ [-1.2e-01 -6.6e-02 1.0e-01]
+ [-4.6e-02 -1.2e-01 2.1e-02]
+ [ 1.2e-01 -9.1e-04 -1.9e-01]
+ [ 1.4e-01 3.8e-02 -1.0e-02]
+ [-3.3e-02 1.0e-01 -7.7e-02]
+ [-2.4e-02 -1.2e-01 5.8e-02]
+ [-8.1e-02 -6.4e-02 -3.1e-02]
+ [-1.0e-01 -3.6e-02 5.6e-02]
+ [ 1.2e-01 -2.4e-02 -1.6e-01]
+ [ 7.2e-03 6.3e-02 -9.1e-02]
+ [ 3.4e-02 6.8e-03 9.1e-02]
+ [ 1.2e-01 -5.8e-02 -1.3e-01]
+ [ 1.5e-01 4.5e-02 -1.1e-02]
+ [ 5.1e-02 -4.8e-02 -8.4e-02]
+ [-8.9e-02 -8.7e-02 5.7e-02]
+ [ 2.8e-02 1.3e-01 9.7e-03]
+ [ 2.9e-02 1.2e-03 1.4e-01]
+ [ 1.4e-01 2.7e-02 -4.1e-03]
+ [-1.1e-01 -6.5e-02 9.3e-02]
+ [-3.2e-02 1.1e-02 6.1e-02]
+ [ 4.2e-03 9.0e-02 2.0e-02]
+ [-3.4e-03 7.9e-02 -9.1e-02]
+ [ 8.8e-02 1.9e-03 -2.7e-01]
+ [-9.7e-02 -6.5e-02 -1.2e-03]
+ [-2.1e-02 -1.3e-01 6.4e-03]
+ [-1.1e-02 5.2e-03 5.1e-02]
+ [-7.2e-02 -9.4e-02 6.2e-02]
+ [ 1.1e-01 -5.7e-03 -3.5e-02]
+ [ 7.9e-03 -3.9e-03 1.7e-01]
+ [-9.1e-03 -1.4e-01 2.5e-02]
+ [ 1.4e-01 1.0e-01 2.7e-02]
+ [-4.1e-02 9.9e-02 -7.3e-02]
+ [ 6.3e-03 -6.7e-02 -4.3e-02]
+ [ 1.9e-03 8.3e-03 -1.2e-01]
+ [-1.0e-01 -8.9e-02 6.9e-02]
+ [-2.1e-03 -6.3e-02 7.8e-03]
+ [-9.9e-02 -6.7e-02 -1.3e-02]
+ [ 1.1e-01 -3.4e-02 6.3e-02]
+ [-2.6e-02 -9.5e-02 6.4e-02]
+ [-7.6e-02 -7.9e-03 -3.4e-02]
+ [ 8.4e-02 -2.4e-02 6.0e-02]
+ [ 1.3e-01 -2.6e-02 -1.7e-01]
+ [-3.1e-02 -4.1e-02 1.2e-01]
+ [ 9.3e-02 8.3e-02 3.1e-02]
+ [ 7.8e-02 7.8e-03 -2.4e-01]
+ [ 9.0e-02 -7.1e-02 -8.7e-02]
+ [ 9.3e-02 -6.9e-02 -8.0e-02]
+ [ 2.1e-02 2.9e-03 1.4e-01]
+ [ 1.4e-01 8.9e-02 1.2e-02]
+ [ 1.5e-01 9.1e-02 1.9e-02]
+ [-8.8e-02 -6.9e-02 1.1e-02]
+ [ 1.5e-01 1.5e-01 2.3e-02]
+ [ 8.2e-02 -1.1e-02 1.1e-01]
+ [-5.6e-02 -2.4e-02 5.1e-02]
+ [ 8.9e-02 -4.0e-04 -2.7e-01]
+ [-3.0e-02 1.1e-01 -8.1e-02]
+ [-3.5e-02 1.1e-01 -6.3e-05]
+ [-3.2e-02 -9.1e-02 4.3e-02]
+ [ 3.5e-02 1.4e-01 -1.9e-02]]
+# ---
+# name: test_rcsb_nmr[True]
+ [[ 0.1 0.0 -0.1]
+ [ 0.1 0.0 -0.1]
+ [ 0.1 0.0 -0.1]
+ ...
+ [ 0.1 -0.0 -0.3]
+ [ 0.1 -0.0 -0.3]
+ [ 0.1 0.0 -0.3]]
+# ---
+# name: test_rcsb_nmr[True].1
+ [[-9.5e-02 -2.8e-02 5.5e-02]
+ [-2.1e-02 3.8e-02 2.3e-02]
+ [-3.5e-02 1.0e-01 -7.1e-02]
+ [ 1.3e-01 2.5e-02 -5.2e-02]
+ [ 6.0e-02 2.2e-02 4.6e-02]
+ [ 1.1e-01 -1.3e-02 -1.3e-02]
+ [-2.0e-02 7.1e-03 -6.4e-02]
+ [ 9.2e-02 -6.0e-03 -2.1e-01]
+ [-1.1e-01 -5.3e-02 9.7e-02]
+ [-6.9e-02 6.4e-02 -9.0e-02]
+ [ 1.4e-01 8.6e-02 6.3e-03]
+ [-1.6e-02 4.6e-04 1.6e-01]
+ [-1.4e-02 8.6e-03 8.3e-02]
+ [ 1.0e-01 -1.4e-02 -2.1e-02]
+ [-2.3e-02 1.2e-01 -8.5e-02]
+ [-1.7e-02 -1.3e-01 1.2e-02]
+ [ 7.5e-02 1.3e-01 -2.1e-02]
+ [-7.4e-02 -2.3e-02 9.6e-03]
+ [ 4.0e-02 1.1e-01 3.2e-02]
+ [ 9.3e-02 -1.2e-02 -2.8e-01]
+ [ 4.0e-02 8.6e-02 3.3e-02]
+ [-1.8e-02 -1.2e-01 6.7e-02]
+ [ 8.9e-02 7.6e-02 3.9e-02]
+ [ 9.4e-02 1.0e-01 2.5e-02]
+ [ 1.2e-01 4.5e-03 -4.4e-02]
+ [ 9.3e-02 -9.4e-03 -2.1e-01]
+ [-6.5e-02 -9.8e-02 6.7e-02]
+ [ 2.3e-03 8.5e-02 1.4e-02]
+ [ 3.1e-02 1.3e-01 -1.2e-02]
+ [-4.1e-02 -3.3e-02 1.1e-01]
+ [ 3.9e-02 7.9e-02 3.2e-02]
+ [ 1.4e-01 4.4e-02 -9.3e-03]
+ [ 9.0e-02 1.3e-01 -1.6e-02]
+ [ 5.1e-02 -2.6e-02 -5.2e-02]
+ [-6.6e-02 6.5e-02 -2.3e-02]
+ [ 2.8e-02 1.1e-01 1.7e-02]
+ [-1.3e-02 -1.4e-01 1.9e-02]
+ [ 1.2e-01 -5.1e-02 -1.3e-01]
+ [ 7.6e-02 -7.6e-03 1.2e-01]
+ [ 4.1e-02 1.1e-01 3.9e-02]
+ [ 1.0e-01 1.5e-02 2.2e-02]
+ [-1.2e-01 -6.6e-02 1.0e-01]
+ [-4.6e-02 -1.2e-01 2.1e-02]
+ [ 1.2e-01 -9.1e-04 -1.9e-01]
+ [ 1.4e-01 3.8e-02 -1.0e-02]
+ [-3.3e-02 1.0e-01 -7.7e-02]
+ [-2.4e-02 -1.2e-01 5.8e-02]
+ [-8.1e-02 -6.4e-02 -3.1e-02]
+ [-1.0e-01 -3.6e-02 5.6e-02]
+ [ 1.2e-01 -2.4e-02 -1.6e-01]
+ [ 7.2e-03 6.3e-02 -9.1e-02]
+ [ 3.4e-02 6.8e-03 9.1e-02]
+ [ 1.2e-01 -5.8e-02 -1.3e-01]
+ [ 1.5e-01 4.5e-02 -1.1e-02]
+ [ 5.1e-02 -4.8e-02 -8.4e-02]
+ [-8.9e-02 -8.7e-02 5.7e-02]
+ [ 2.8e-02 1.3e-01 9.7e-03]
+ [ 2.9e-02 1.2e-03 1.4e-01]
+ [ 1.4e-01 2.7e-02 -4.1e-03]
+ [-1.1e-01 -6.5e-02 9.3e-02]
+ [-3.2e-02 1.1e-02 6.1e-02]
+ [ 4.2e-03 9.0e-02 2.0e-02]
+ [-3.4e-03 7.9e-02 -9.1e-02]
+ [ 8.8e-02 1.9e-03 -2.7e-01]
+ [-9.7e-02 -6.5e-02 -1.2e-03]
+ [-2.1e-02 -1.3e-01 6.4e-03]
+ [-1.1e-02 5.2e-03 5.1e-02]
+ [-7.2e-02 -9.4e-02 6.2e-02]
+ [ 1.1e-01 -5.7e-03 -3.5e-02]
+ [ 7.9e-03 -3.9e-03 1.7e-01]
+ [-9.1e-03 -1.4e-01 2.5e-02]
+ [ 1.4e-01 1.0e-01 2.7e-02]
+ [-4.1e-02 9.9e-02 -7.3e-02]
+ [ 6.3e-03 -6.7e-02 -4.3e-02]
+ [ 1.9e-03 8.3e-03 -1.2e-01]
+ [-1.0e-01 -8.9e-02 6.9e-02]
+ [-2.1e-03 -6.3e-02 7.8e-03]
+ [-9.9e-02 -6.7e-02 -1.3e-02]
+ [ 1.1e-01 -3.4e-02 6.3e-02]
+ [-2.6e-02 -9.5e-02 6.4e-02]
+ [-7.6e-02 -7.9e-03 -3.4e-02]
+ [ 8.4e-02 -2.4e-02 6.0e-02]
+ [ 1.3e-01 -2.6e-02 -1.7e-01]
+ [-3.1e-02 -4.1e-02 1.2e-01]
+ [ 9.3e-02 8.3e-02 3.1e-02]
+ [ 7.8e-02 7.8e-03 -2.4e-01]
+ [ 9.0e-02 -7.1e-02 -8.7e-02]
+ [ 9.3e-02 -6.9e-02 -8.0e-02]
+ [ 2.1e-02 2.9e-03 1.4e-01]
+ [ 1.4e-01 8.9e-02 1.2e-02]
+ [ 1.5e-01 9.1e-02 1.9e-02]
+ [-8.8e-02 -6.9e-02 1.1e-02]
+ [ 1.5e-01 1.5e-01 2.3e-02]
+ [ 8.2e-02 -1.1e-02 1.1e-01]
+ [-5.6e-02 -2.4e-02 5.1e-02]
+ [ 8.9e-02 -4.0e-04 -2.7e-01]
+ [-3.0e-02 1.1e-01 -8.1e-02]
+ [-3.5e-02 1.1e-01 -6.3e-05]
+ [-3.2e-02 -9.1e-02 4.3e-02]
+ [ 3.5e-02 1.4e-01 -1.9e-02]]
# ---
# name: test_style_1[False-1BNA-ball_and_stick]
[65.5 32.1 23.7 35.4 42.1 48.4 28.0 78.3 64.3 27.9 35.0 42.4 40.5 50.4
@@ -874,7 +994,14 @@
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
# ---
# name: test_style_1[False-1BNA-cartoon]
- AttributeError("The selected attribute 'b_factor' does not exist on the mesh.")
+ [ 0.0 32.1 0.0 48.0 43.2 0.0 49.7 47.8 31.3 49.0 31.6 36.5 32.8 0.0
+ 0.0 52.4 72.5 0.0 39.5 52.7 43.2 0.0 30.8 0.0 36.6 50.3 44.9 39.4
+ 53.0 31.5 35.3 41.7 50.9 0.0 0.0 49.7 0.0 0.0 41.4 39.4 50.5 0.0
+ 30.9 56.2 50.5 54.6 0.0 36.6 0.0 46.7 26.9 0.0 0.0 0.0 30.8 50.9
+ 43.0 0.0 62.1 53.0 46.6 36.5 30.8 0.0 35.4 54.6 43.2 31.5 66.5 32.1
+ 39.2 50.9 0.0 58.7 43.7 43.0 0.0 42.2 40.9 28.9 65.6 56.8 36.5 61.8
+ 50.5 58.7 33.6 55.7 30.8 58.9 40.9 0.0 52.7 69.1 0.0 30.8 50.2 35.4
+ 28.7 56.9]
# ---
# name: test_style_1[False-1BNA-cartoon].1
AttributeError("The selected attribute 'occupancy' does not exist on the mesh.")
@@ -889,10 +1016,208 @@
AttributeError("The selected attribute 'sec_struct' does not exist on the mesh.")
# ---
# name: test_style_1[False-1BNA-cartoon].13
- AttributeError("The selected attribute 'Color' does not exist on the mesh.")
+ [[0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]]
# ---
# name: test_style_1[False-1BNA-cartoon].14
- []
+ [[ 0.2 0.2 -0.1]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 -0.0]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.1 0.1]
+ [ 0.1 0.2 0.3]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.2 0.0]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.2 0.1]
+ [ 0.1 0.1 -0.1]
+ [ 0.2 0.3 -0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.1 -0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.1 -0.0]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.3 0.1]
+ [ 0.2 0.2 0.3]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.3 0.1]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.2 -0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.3 -0.0]
+ [ 0.1 0.2 0.3]
+ [ 0.1 0.1 -0.1]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.2 0.3]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.2 0.1]
+ [ 0.2 0.2 -0.0]
+ [ 0.2 0.2 -0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.1 -0.1]
+ [ 0.1 0.2 -0.1]
+ [ 0.2 0.1 -0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.3 0.0]
+ [ 0.2 0.2 0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.2 -0.1]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 -0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.1 -0.1]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.3 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.3 0.0]
+ [ 0.2 0.3 0.0]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.2 -0.0]
+ [ 0.1 0.3 -0.1]
+ [ 0.1 0.1 -0.1]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.1 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.3 0.0]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.1 0.2]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.3 -0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.1 -0.1]
+ [ 0.2 0.2 0.0]
+ [ 0.1 0.2 0.0]
+ [ 0.1 0.1 0.2]]
# ---
# name: test_style_1[False-1BNA-cartoon].15
AttributeError("The selected attribute 'is_backbone' does not exist on the mesh.")
@@ -931,16 +1256,26 @@
AttributeError("The selected attribute 'charge' does not exist on the mesh.")
# ---
# name: test_style_1[False-1BNA-cartoon].5
- AttributeError("The selected attribute 'res_id' does not exist on the mesh.")
+ [ 0 20 0 4 17 0 9 2 1 6 23 21 17 0 0 14 11 0 2 10 17 0 7 0
+ 15 19 19 24 4 7 20 19 24 0 0 9 0 0 21 24 4 0 15 12 4 13 0 15
+ 0 9 16 0 0 0 7 24 22 0 10 4 2 21 7 0 23 13 17 7 18 20 22 24
+ 0 18 2 22 0 9 21 16 11 13 21 5 4 18 23 19 7 5 21 0 10 11 0 7
+ 14 17 8 5]
# ---
# name: test_style_1[False-1BNA-cartoon].6
- AttributeError("The selected attribute 'res_name' does not exist on the mesh.")
+ [ 0 33 0 32 30 0 31 32 31 30 31 32 31 0 0 32 31 0 32 32 30 0 33 0
+ 31 32 33 32 32 33 33 33 32 0 0 31 0 0 31 32 32 0 31 32 32 31 0 31
+ 0 31 32 0 0 0 33 32 32 0 32 32 32 32 33 0 32 31 30 33 30 33 32 32
+ 0 30 32 32 0 32 31 32 32 31 32 31 32 30 31 32 33 31 31 0 32 31 0 33
+ 32 30 33 30]
# ---
# name: test_style_1[False-1BNA-cartoon].7
AttributeError("The selected attribute 'atomic_number' does not exist on the mesh.")
# ---
# name: test_style_1[False-1BNA-cartoon].8
- AttributeError("The selected attribute 'chain_id' does not exist on the mesh.")
+ [0 1 0 0 1 0 0 0 0 0 1 1 1 0 0 1 0 0 0 0 1 0 0 0 1 1 1 1 0 0 1 1 1 0 0 0 0
+ 0 1 1 0 0 1 0 0 1 0 1 0 0 1 0 0 0 0 1 1 0 0 0 0 1 0 0 1 1 1 0 1 1 1 1 0 1
+ 0 1 0 0 1 1 0 1 1 0 0 1 1 1 0 0 1 0 0 0 0 0 1 1 0 0]
# ---
# name: test_style_1[False-1BNA-cartoon].9
AttributeError("The selected attribute 'entity_id' does not exist on the mesh.")
@@ -9568,7 +9903,14 @@
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
# ---
# name: test_style_2[True-1BNA-cartoon]
- AttributeError("The selected attribute 'b_factor' does not exist on the mesh.")
+ [40.9 48.1 43.0 48.0 0.0 32.1 49.7 47.8 31.3 49.0 32.8 40.5 0.0 32.1
+ 41.7 0.0 72.5 34.3 39.5 52.7 0.0 41.4 30.8 44.9 0.0 0.0 56.8 51.0
+ 53.0 31.5 50.2 54.6 66.5 41.9 44.9 49.7 45.1 41.4 30.9 51.0 50.5 31.6
+ 0.0 56.2 50.5 0.0 41.4 0.0 27.9 46.7 0.0 27.9 33.6 35.3 30.8 66.5
+ 25.0 40.9 62.1 53.0 46.6 40.5 30.8 43.0 30.2 0.0 0.0 31.5 0.0 48.1
+ 27.6 66.5 35.4 0.0 43.7 25.0 31.6 42.2 32.8 0.0 65.6 0.0 40.5 61.8
+ 50.5 0.0 43.2 0.0 30.8 58.9 32.8 27.9 52.7 69.1 50.3 30.8 0.0 0.0
+ 28.7 56.9]
# ---
# name: test_style_2[True-1BNA-cartoon].1
AttributeError("The selected attribute 'occupancy' does not exist on the mesh.")
@@ -9583,10 +9925,208 @@
AttributeError("The selected attribute 'sec_struct' does not exist on the mesh.")
# ---
# name: test_style_2[True-1BNA-cartoon].13
- AttributeError("The selected attribute 'Color' does not exist on the mesh.")
+ [[0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.8 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]]
# ---
# name: test_style_2[True-1BNA-cartoon].14
- []
+ [[ 0.1 0.2 0.2]
+ [ 0.2 0.1 -0.1]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.2 0.1]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.2 -0.0]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.1 0.1]
+ [ 0.2 0.2 0.0]
+ [ 0.2 0.1 -0.0]
+ [ 0.1 0.2 0.0]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.3 0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.3 -0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.1 -0.1]
+ [ 0.2 0.3 0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.1 -0.1]
+ [ 0.1 0.1 -0.1]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.1 -0.0]
+ [ 0.2 0.3 0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.2 0.3]
+ [ 0.1 0.2 -0.0]
+ [ 0.2 0.2 -0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.2 0.0]
+ [ 0.1 0.2 0.3]
+ [ 0.1 0.3 0.0]
+ [ 0.2 0.2 -0.1]
+ [ 0.1 0.2 0.3]
+ [ 0.1 0.2 0.3]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.3 0.0]
+ [ 0.2 0.2 -0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.1 -0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.2 0.0]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.1 -0.0]
+ [ 0.2 0.2 -0.0]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.2 0.0]
+ [ 0.1 0.2 0.3]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.1 -0.0]
+ [ 0.1 0.2 -0.1]
+ [ 0.1 0.3 -0.1]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.1 -0.0]
+ [ 0.2 0.1 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.1 0.2]
+ [ 0.2 0.1 -0.0]
+ [ 0.1 0.2 0.3]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.3 -0.1]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.2 0.0]
+ [ 0.1 0.1 0.2]]
# ---
# name: test_style_2[True-1BNA-cartoon].15
AttributeError("The selected attribute 'is_backbone' does not exist on the mesh.")
@@ -9625,16 +10165,26 @@
AttributeError("The selected attribute 'charge' does not exist on the mesh.")
# ---
# name: test_style_2[True-1BNA-cartoon].5
- AttributeError("The selected attribute 'res_id' does not exist on the mesh.")
+ [21 14 22 4 0 20 9 2 1 6 17 15 0 20 19 0 11 20 2 10 0 21 7 19
+ 0 0 13 18 4 7 14 13 18 22 19 9 24 21 15 18 4 23 0 12 4 0 21 0
+ 23 9 0 23 23 20 7 18 16 21 10 4 2 15 7 22 17 0 0 7 0 14 16 18
+ 23 0 2 16 23 9 15 0 11 0 15 5 4 0 17 0 7 5 15 23 10 11 19 7
+ 0 0 8 5]
# ---
# name: test_style_2[True-1BNA-cartoon].6
- AttributeError("The selected attribute 'res_name' does not exist on the mesh.")
+ [31 32 32 32 0 33 31 32 31 30 31 32 0 33 33 0 31 33 32 32 0 31 33 33
+ 0 0 31 30 32 33 32 31 30 32 33 31 32 31 31 30 32 31 0 32 32 0 31 0
+ 31 31 0 31 31 33 33 30 32 31 32 32 32 32 33 32 31 0 0 33 0 32 32 30
+ 32 0 32 32 31 32 31 0 32 0 32 31 32 0 30 0 33 31 31 31 32 31 32 33
+ 0 0 33 30]
# ---
# name: test_style_2[True-1BNA-cartoon].7
AttributeError("The selected attribute 'atomic_number' does not exist on the mesh.")
# ---
# name: test_style_2[True-1BNA-cartoon].8
- AttributeError("The selected attribute 'chain_id' does not exist on the mesh.")
+ [1 1 1 0 0 1 0 0 0 0 1 1 0 1 1 0 0 1 0 0 0 1 0 1 0 0 1 1 0 0 1 1 1 1 1 0 1
+ 1 1 1 0 1 0 0 0 0 1 0 1 0 0 1 1 1 0 1 1 1 0 0 0 1 0 1 1 0 0 0 0 1 1 1 1 0
+ 0 1 1 0 1 0 0 0 1 0 0 0 1 0 0 0 1 1 0 0 1 0 0 0 0 0]
# ---
# name: test_style_2[True-1BNA-cartoon].9
AttributeError("The selected attribute 'entity_id' does not exist on the mesh.")
@@ -13951,216 +14501,315 @@
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
# ---
# name: test_style_positions[1BNA-ball_and_stick]
- [[ 0.1 0.2 0.3]
+ [[ 0.1 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 -0.1]
+ [ 0.1 0.2 0.2]
[ 0.2 0.2 0.2]
- [ 0.1 0.3 0.1]
- [ 0.1 0.2 -0.0]
[ 0.2 0.3 0.3]
- [ 0.2 0.3 0.2]
- [ 0.1 0.1 0.1]
- [ 0.2 0.2 0.3]
- [ 0.1 0.2 0.1]
- [ 0.1 0.2 -0.0]
+ [ 0.2 0.2 -0.1]
+ [ 0.1 0.2 0.3]
[ 0.1 0.1 -0.1]
+ [ 0.2 0.1 0.2]
+ [ 0.2 0.2 0.0]
+ [ 0.2 0.2 0.2]
[ 0.1 0.2 0.2]
- [ 0.2 0.3 -0.1]
+ [ 0.2 0.2 -0.1]
+ [ 0.2 0.2 0.0]
+ [ 0.1 0.2 0.0]
+ [ 0.1 0.2 0.1]
[ 0.1 0.3 0.1]
[ 0.1 0.2 0.1]
- [ 0.2 0.3 0.0]
+ [ 0.2 0.1 -0.0]
[ 0.1 0.2 0.2]
+ [ 0.1 0.2 0.1]
[ 0.1 0.2 0.2]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.2 0.1]
[ 0.2 0.2 0.2]
[ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.3 -0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.0]
+ [ 0.1 0.2 0.3]
+ [ 0.1 0.2 0.0]
[ 0.2 0.2 0.2]
[ 0.1 0.2 0.3]
- [ 0.1 0.3 -0.1]
- [ 0.2 0.2 0.2]
[ 0.2 0.2 0.0]
- [ 0.1 0.1 -0.1]
[ 0.2 0.2 0.2]
- [ 0.2 0.1 -0.0]
+ [ 0.1 0.2 -0.1]
+ [ 0.2 0.1 0.0]
[ 0.2 0.2 0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.2 -0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.3 0.1]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 0.3]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.2 0.3]
[ 0.1 0.2 -0.0]
+ [ 0.1 0.1 0.1]
+ [ 0.1 0.1 -0.0]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.2 0.0]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.3 0.3]
+ [ 0.1 0.2 0.2]
+ [ 0.3 0.3 0.2]
+ [ 0.2 0.2 -0.0]
[ 0.2 0.2 0.1]
+ [ 0.1 0.1 -0.1]
+ [ 0.2 0.3 0.0]
+ [ 0.2 0.2 -0.1]
+ [ 0.1 0.2 0.3]
+ [ 0.2 0.2 0.0]
+ [ 0.2 0.2 0.0]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.2 -0.0]
+ [ 0.1 0.1 -0.1]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.3]
[ 0.2 0.2 0.2]
+ [ 0.2 0.2 0.1]
+ [ 0.2 0.3 0.0]
[ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.3]
+ [ 0.1 0.2 -0.0]
[ 0.2 0.2 -0.1]
+ [ 0.2 0.1 0.2]
+ [ 0.2 0.1 -0.0]
+ [ 0.1 0.2 0.0]
[ 0.2 0.2 0.2]
- [ 0.2 0.3 0.2]
- [ 0.2 0.2 0.3]
+ [ 0.1 0.2 0.1]
[ 0.1 0.2 0.0]
- [ 0.2 0.1 -0.0]
- [ 0.1 0.3 0.1]
+ [ 0.1 0.2 -0.0]
+ [ 0.2 0.2 0.1]
[ 0.1 0.2 0.1]
- [ 0.1 0.2 0.2]
[ 0.2 0.2 0.3]
+ [ 0.2 0.3 -0.1]
+ [ 0.2 0.3 -0.1]
+ [ 0.2 0.2 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.0]
+ [ 0.1 0.2 0.0]]
+# ---
+# name: test_style_positions[1BNA-cartoon]
+ [[ 0.2 0.2 -0.1]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 -0.0]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.1 0.1]
+ [ 0.1 0.2 0.3]
[ 0.1 0.2 0.2]
+ [ 0.2 0.2 0.0]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.2 0.1]
+ [ 0.1 0.1 -0.1]
+ [ 0.2 0.3 -0.1]
+ [ 0.1 0.2 0.0]
[ 0.2 0.3 0.2]
- [ 0.2 0.1 -0.0]
- [ 0.1 0.2 -0.0]
+ [ 0.1 0.3 -0.0]
[ 0.2 0.3 0.0]
- [ 0.1 0.2 -0.1]
+ [ 0.1 0.1 -0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.2]
[ 0.2 0.1 -0.0]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.3 0.1]
[ 0.2 0.2 0.3]
- [ 0.2 0.1 0.1]
[ 0.2 0.2 0.2]
[ 0.1 0.2 0.1]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.3 0.1]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.2 -0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.3 -0.0]
+ [ 0.1 0.2 0.3]
+ [ 0.1 0.1 -0.1]
[ 0.1 0.2 0.2]
- [ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.3]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.2 0.1]
+ [ 0.2 0.2 -0.0]
+ [ 0.2 0.2 -0.1]
[ 0.2 0.2 0.2]
- [ 0.2 0.3 -0.1]
[ 0.1 0.1 -0.1]
+ [ 0.1 0.2 -0.1]
+ [ 0.2 0.1 -0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.3 0.0]
+ [ 0.2 0.2 0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.2]
[ 0.1 0.2 0.1]
- [ 0.2 0.1 0.0]
[ 0.1 0.2 0.1]
- [ 0.1 0.2 0.0]
- [ 0.2 0.2 0.1]
[ 0.2 0.2 0.3]
- [ 0.1 0.2 0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.2 -0.1]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 -0.0]
[ 0.1 0.2 0.2]
[ 0.1 0.1 -0.1]
+ [ 0.2 0.3 0.0]
[ 0.1 0.2 0.1]
- [ 0.1 0.1 0.1]
+ [ 0.2 0.3 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.3 0.0]
[ 0.2 0.3 0.0]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.2 -0.0]
+ [ 0.1 0.3 -0.1]
[ 0.1 0.1 -0.1]
- [ 0.1 0.2 0.3]
- [ 0.1 0.2 -0.1]
- [ 0.1 0.2 -0.0]
- [ 0.1 0.1 -0.0]
[ 0.1 0.2 0.2]
+ [ 0.2 0.1 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.3 0.0]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.1 0.2]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.3 -0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.1 -0.1]
[ 0.2 0.2 0.0]
- [ 0.2 0.2 -0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.1 0.1 0.2]]
+# ---
+# name: test_style_positions[1BNA-preset_1]
+ [[ 0.2 0.3 0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.2 0.0]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.3 0.2]
[ 0.2 0.1 0.2]
+ [ 0.1 0.2 0.2]
[ 0.1 0.3 0.1]
+ [ 0.2 0.1 -0.0]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.2 0.3]
+ [ 0.2 0.2 -0.1]
+ [ 0.1 0.2 -0.0]
+ [ 0.2 0.2 0.3]
[ 0.2 0.3 0.2]
- [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.2 -0.0]
+ [ 0.1 0.1 0.1]
+ [ 0.1 0.2 0.3]
+ [ 0.1 0.1 -0.1]
[ 0.2 0.2 0.0]
- [ 0.2 0.3 0.3]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.3 0.0]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.2 0.3]
[ 0.1 0.2 0.0]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.2 0.2]
[ 0.2 0.2 0.2]
- [ 0.2 0.3 0.1]
+ [ 0.1 0.1 -0.1]
[ 0.1 0.3 -0.0]
[ 0.2 0.2 0.2]
- [ 0.2 0.2 0.1]
- [ 0.2 0.2 0.1]
- [ 0.2 0.1 0.0]
+ [ 0.2 0.3 -0.1]
+ [ 0.1 0.1 -0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.1 -0.0]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.1 0.1]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.3 -0.0]
[ 0.2 0.2 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 -0.1]
+ [ 0.2 0.2 0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.0]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.3 0.1]
[ 0.1 0.2 0.2]
+ [ 0.2 0.2 0.0]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.3 0.1]
+ [ 0.2 0.3 -0.1]
+ [ 0.0 0.2 0.1]
+ [ 0.1 0.3 0.1]
+ [ 0.2 0.1 -0.1]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.3 -0.1]
+ [ 0.1 0.3 0.1]
+ [ 0.2 0.1 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.2 -0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.2 0.2 0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.3 0.1]
[ 0.1 0.2 0.0]
+ [ 0.1 0.3 -0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.1 0.1]
+ [ 0.2 0.2 -0.1]
+ [ 0.2 0.2 -0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.1 0.2]
+ [ 0.1 0.3 0.1]
[ 0.1 0.2 0.1]
- [ 0.1 0.2 -0.1]
[ 0.2 0.2 0.0]
- [ 0.2 0.2 0.2]]
-# ---
-# name: test_style_positions[1BNA-cartoon]
- []
-# ---
-# name: test_style_positions[1BNA-preset_1]
- [[ 1.6e-01 2.6e-01 5.6e-02]
- [ 2.2e-01 2.0e-01 2.1e-01]
- [ 1.9e-01 1.7e-01 -3.6e-03]
- [ 1.7e-01 2.0e-01 2.8e-01]
- [ 7.7e-02 2.1e-01 3.0e-02]
- [ 2.2e-01 2.7e-01 2.0e-01]
- [ 1.7e-01 3.3e-01 2.5e-01]
- [ 1.6e-01 1.4e-01 1.7e-01]
- [ 9.8e-02 2.4e-01 1.6e-01]
- [ 1.5e-01 2.8e-01 7.3e-02]
- [ 2.0e-01 1.5e-01 -3.4e-02]
- [ 1.6e-01 1.8e-01 2.8e-01]
- [ 1.2e-01 2.0e-01 2.6e-01]
- [ 1.7e-01 2.3e-01 -9.6e-02]
- [ 1.2e-01 2.4e-01 -3.6e-02]
- [ 1.7e-01 1.9e-01 3.0e-01]
- [ 2.2e-01 3.1e-01 2.4e-01]
- [ 9.0e-02 2.2e-01 2.1e-02]
- [ 2.0e-01 1.8e-01 -2.1e-02]
- [ 8.5e-02 1.6e-01 1.2e-01]
- [ 1.1e-01 1.9e-01 2.5e-01]
- [ 1.1e-01 1.3e-01 -7.5e-02]
- [ 1.9e-01 2.3e-01 2.7e-02]
- [ 2.0e-01 2.5e-01 3.1e-02]
- [ 8.0e-02 2.2e-01 1.9e-01]
- [ 2.0e-01 1.9e-01 1.9e-01]
- [ 9.2e-02 1.6e-01 1.3e-01]
- [ 1.7e-01 2.7e-01 4.7e-02]
- [ 1.7e-01 2.6e-01 1.8e-02]
- [ 8.4e-02 2.2e-01 2.1e-01]
- [ 1.1e-01 2.0e-01 2.6e-01]
- [ 9.6e-02 2.3e-01 4.1e-02]
- [ 1.2e-01 2.7e-01 1.0e-01]
- [ 1.0e-01 2.2e-01 1.9e-01]
- [ 2.0e-01 2.0e-01 1.9e-01]
- [ 1.4e-01 1.3e-01 -7.3e-02]
- [ 1.4e-01 2.5e-01 -3.7e-02]
- [ 2.1e-01 1.9e-01 2.0e-01]
- [ 1.6e-01 2.5e-01 -8.3e-02]
- [ 1.0e-01 1.1e-01 -8.3e-02]
- [ 6.7e-02 2.0e-01 4.7e-02]
- [ 1.6e-01 1.2e-01 -3.8e-02]
- [ 1.6e-01 1.9e-01 2.6e-01]
- [ 9.3e-02 1.5e-01 1.1e-01]
- [ 8.6e-02 2.0e-01 2.1e-01]
- [ 8.7e-02 2.6e-01 1.2e-01]
- [ 8.7e-02 2.4e-01 3.1e-05]
- [ 2.3e-01 1.8e-01 1.8e-01]
- [ 2.3e-01 2.6e-01 2.3e-01]
- [ 1.3e-01 2.8e-01 5.6e-02]
- [ 1.1e-01 1.7e-01 1.1e-01]
- [ 1.0e-01 2.3e-01 1.4e-01]
- [ 1.7e-01 2.3e-01 -7.0e-02]
- [ 2.1e-01 1.6e-01 -3.2e-03]
- [ 9.4e-02 1.7e-01 1.2e-01]
- [ 2.0e-01 2.0e-01 1.8e-02]
- [ 1.5e-01 2.8e-01 5.1e-02]
- [ 1.0e-01 2.4e-01 1.4e-01]
- [ 1.0e-01 2.2e-01 2.1e-01]
- [ 2.1e-01 1.8e-01 1.1e-02]
- [ 2.1e-01 2.9e-01 2.4e-01]
- [ 1.1e-01 2.6e-01 1.3e-01]
- [ 1.6e-01 2.4e-01 -8.0e-02]
- [ 6.3e-02 2.0e-01 6.0e-02]
- [ 1.2e-01 2.6e-01 7.1e-02]
- [ 1.6e-01 1.3e-01 -6.9e-02]
- [ 9.6e-02 2.6e-01 -1.2e-02]
- [ 1.6e-01 2.6e-01 -7.0e-02]
- [ 1.3e-01 2.7e-01 5.4e-02]
- [ 1.9e-01 1.6e-01 1.6e-01]
- [ 2.2e-01 2.0e-01 1.7e-01]
- [ 2.1e-01 1.9e-01 -1.4e-02]
- [ 9.5e-02 2.1e-01 1.7e-01]
- [ 1.9e-01 2.2e-01 3.7e-03]
- [ 8.8e-02 1.7e-01 1.2e-01]
- [ 1.9e-01 1.7e-01 1.8e-01]
- [ 1.2e-01 2.5e-01 8.2e-02]
- [ 7.5e-02 2.2e-01 2.5e-02]
- [ 1.2e-01 2.5e-01 -2.0e-02]
- [ 1.0e-01 1.9e-01 2.3e-01]
- [ 1.1e-01 1.6e-01 1.1e-01]
- [ 1.8e-01 2.2e-01 -1.1e-01]
- [ 1.9e-01 1.8e-01 -2.0e-02]
- [ 7.8e-02 2.0e-01 9.0e-02]
- [ 1.8e-01 1.4e-01 1.6e-01]
- [ 1.4e-01 2.6e-01 7.8e-02]
- [ 7.8e-02 1.7e-01 1.0e-01]
- [ 2.1e-01 2.3e-01 1.5e-02]
- [ 1.9e-01 3.1e-01 2.3e-01]
- [ 1.1e-01 1.7e-01 1.2e-01]
- [ 2.0e-01 1.9e-01 2.9e-01]
- [ 1.2e-01 1.4e-01 1.6e-01]
- [ 2.0e-01 3.1e-01 2.5e-01]
- [ 8.2e-02 2.3e-01 1.3e-01]
- [ 1.2e-01 2.5e-01 -5.9e-02]
- [ 1.8e-01 2.7e-01 3.7e-02]
- [ 7.6e-02 2.2e-01 1.6e-01]
- [ 1.2e-01 2.5e-01 1.0e-01]
- [ 9.8e-02 2.6e-01 9.0e-02]
- [ 1.2e-01 2.6e-01 -1.4e-02]]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.3]
+ [ 0.1 0.1 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.3 -0.1]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.2 0.2]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.3 0.1]
+ [ 0.1 0.3 -0.0]]
# ---
# name: test_style_positions[1BNA-ribbon]
[[ 0.2 0.3 0.1]
[ 0.2 0.2 0.2]
- [ 0.2 0.2 -0.0]
+ [ 0.2 0.2 0.0]
[ 0.2 0.2 0.3]
[ 0.1 0.2 0.0]
[ 0.2 0.3 0.2]
@@ -14168,7 +14817,7 @@
[ 0.2 0.1 0.2]
[ 0.1 0.2 0.2]
[ 0.1 0.3 0.1]
- [ 0.2 0.2 -0.0]
+ [ 0.2 0.1 -0.0]
[ 0.2 0.2 0.3]
[ 0.1 0.2 0.3]
[ 0.2 0.2 -0.1]
@@ -14177,11 +14826,11 @@
[ 0.2 0.3 0.2]
[ 0.1 0.2 0.0]
[ 0.2 0.2 -0.0]
- [ 0.1 0.2 0.1]
+ [ 0.1 0.1 0.1]
[ 0.1 0.2 0.3]
[ 0.1 0.1 -0.1]
[ 0.2 0.2 0.0]
- [ 0.2 0.2 0.0]
+ [ 0.2 0.3 0.0]
[ 0.1 0.2 0.2]
[ 0.2 0.2 0.2]
[ 0.1 0.2 0.1]
@@ -14196,7 +14845,7 @@
[ 0.1 0.1 -0.1]
[ 0.1 0.3 -0.0]
[ 0.2 0.2 0.2]
- [ 0.2 0.2 -0.1]
+ [ 0.2 0.3 -0.1]
[ 0.1 0.1 -0.1]
[ 0.1 0.2 0.0]
[ 0.2 0.1 -0.0]
@@ -14204,30 +14853,30 @@
[ 0.1 0.1 0.1]
[ 0.1 0.2 0.2]
[ 0.1 0.3 0.1]
- [ 0.1 0.2 -0.0]
+ [ 0.1 0.3 -0.0]
[ 0.2 0.2 0.2]
[ 0.2 0.3 0.2]
[ 0.1 0.3 0.1]
[ 0.1 0.2 0.1]
[ 0.1 0.2 0.1]
[ 0.2 0.2 -0.1]
- [ 0.2 0.2 -0.0]
- [ 0.1 0.2 0.1]
[ 0.2 0.2 0.0]
- [ 0.2 0.3 0.1]
[ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.0]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.3 0.1]
[ 0.1 0.2 0.2]
[ 0.2 0.2 0.0]
[ 0.2 0.3 0.2]
[ 0.1 0.3 0.1]
- [ 0.2 0.2 -0.1]
- [ 0.1 0.2 0.1]
+ [ 0.2 0.3 -0.1]
+ [ 0.0 0.2 0.1]
[ 0.1 0.3 0.1]
[ 0.2 0.1 -0.1]
[ 0.1 0.3 -0.0]
[ 0.2 0.3 -0.1]
[ 0.1 0.3 0.1]
- [ 0.2 0.2 0.2]
+ [ 0.2 0.1 0.2]
[ 0.2 0.2 0.2]
[ 0.2 0.2 -0.0]
[ 0.1 0.2 0.2]
@@ -14236,9 +14885,9 @@
[ 0.2 0.2 0.2]
[ 0.1 0.3 0.1]
[ 0.1 0.2 0.0]
- [ 0.1 0.2 -0.0]
+ [ 0.1 0.3 -0.0]
[ 0.1 0.2 0.2]
- [ 0.1 0.2 0.1]
+ [ 0.1 0.1 0.1]
[ 0.2 0.2 -0.1]
[ 0.2 0.2 -0.0]
[ 0.1 0.2 0.1]
@@ -14255,7 +14904,7 @@
[ 0.1 0.3 -0.1]
[ 0.2 0.3 0.0]
[ 0.1 0.2 0.2]
- [ 0.1 0.2 0.1]
+ [ 0.1 0.3 0.1]
[ 0.1 0.3 0.1]
[ 0.1 0.3 -0.0]]
# ---
@@ -14365,208 +15014,208 @@
[ 0.1 0.2 0.0]]
# ---
# name: test_style_positions[4ozs-ball_and_stick]
- [[ 0.2 -0.0 0.2]
- [ 0.3 -0.0 0.3]
- [ 0.2 -0.0 0.0]
- [ 0.4 0.1 0.0]
- [ 0.3 0.1 -0.1]
+ [[ 0.3 -0.1 0.3]
+ [ 0.4 0.1 0.1]
+ [ 0.4 0.2 -0.2]
+ [ 0.4 -0.2 0.2]
+ [ 0.3 -0.0 0.2]
+ [ 0.2 0.0 0.1]
+ [ 0.5 0.1 0.0]
[ 0.4 0.1 -0.2]
- [ 0.5 0.0 -0.0]
- [ 0.3 -0.0 0.3]
- [ 0.2 -0.1 0.2]
+ [ 0.4 0.2 -0.0]
[ 0.2 0.0 0.1]
- [ 0.3 -0.2 0.3]
- [ 0.3 0.1 0.0]
- [ 0.3 0.1 0.0]
- [ 0.4 0.1 -0.0]
- [ 0.4 0.1 0.1]
- [ 0.2 -0.0 0.0]
- [ 0.4 0.2 -0.1]
- [ 0.3 -0.1 0.2]
- [ 0.3 0.1 0.2]
- [ 0.3 0.0 0.3]
- [ 0.3 0.0 0.3]
- [ 0.3 -0.1 0.3]
- [ 0.3 -0.2 0.2]
- [ 0.4 0.2 -0.1]
- [ 0.2 0.0 0.2]
- [ 0.2 0.0 0.3]
- [ 0.3 -0.1 0.3]
+ [ 0.4 0.2 0.1]
+ [ 0.3 0.1 0.3]
[ 0.3 -0.1 0.2]
- [ 0.4 0.1 0.0]
+ [ 0.2 0.0 0.1]
[ 0.3 -0.0 0.3]
- [ 0.2 -0.0 0.1]
- [ 0.3 -0.1 0.4]
- [ 0.3 -0.1 0.3]
- [ 0.3 0.1 0.2]
- [ 0.3 0.1 -0.0]
+ [ 0.2 -0.0 0.2]
+ [ 0.3 -0.0 0.3]
+ [ 0.4 0.1 -0.1]
+ [ 0.3 -0.0 0.2]
+ [ 0.4 0.1 -0.1]
[ 0.3 -0.2 0.2]
- [ 0.3 0.0 0.0]
- [ 0.4 0.1 0.2]
- [ 0.4 0.1 0.0]
[ 0.3 0.1 0.1]
- [ 0.3 -0.1 0.3]
- [ 0.3 -0.2 0.2]
- [ 0.4 -0.1 0.3]
- [ 0.5 0.2 -0.1]
- [ 0.3 -0.1 0.3]
- [ 0.4 -0.1 0.2]
- [ 0.4 0.1 0.1]
- [ 0.4 0.1 -0.2]
- [ 0.4 0.1 0.2]
[ 0.2 -0.1 0.2]
+ [ 0.3 -0.2 0.3]
[ 0.4 0.2 -0.1]
- [ 0.3 -0.0 0.2]
- [ 0.3 0.1 -0.0]
- [ 0.2 -0.0 0.0]
[ 0.4 0.2 -0.1]
- [ 0.3 -0.0 0.2]
- [ 0.2 0.0 0.2]
- [ 0.3 -0.1 0.2]
- [ 0.2 -0.1 0.3]
- [ 0.3 0.0 0.1]
- [ 0.4 0.2 0.1]
- [ 0.3 -0.1 0.2]
- [ 0.3 0.0 0.0]
- [ 0.3 0.1 -0.0]
- [ 0.2 -0.1 0.2]
+ [ 0.2 -0.0 0.1]
+ [ 0.4 0.0 -0.1]
[ 0.3 0.1 0.1]
- [ 0.3 0.2 0.1]
[ 0.3 0.1 -0.0]
+ [ 0.3 0.1 -0.1]
+ [ 0.3 0.0 0.2]
+ [ 0.3 -0.2 0.3]
[ 0.2 -0.1 0.2]
+ [ 0.3 -0.0 0.1]
+ [ 0.2 0.0 0.1]
+ [ 0.3 -0.2 0.2]
+ [ 0.3 0.2 -0.1]
+ [ 0.3 -0.0 0.1]
+ [ 0.3 0.1 -0.1]
+ [ 0.3 -0.2 0.2]
+ [ 0.2 -0.1 0.1]
[ 0.4 0.1 -0.1]
+ [ 0.3 -0.1 0.2]
+ [ 0.2 -0.1 0.2]
[ 0.3 -0.1 0.3]
- [ 0.3 -0.0 0.1]
- [ 0.3 -0.0 0.4]
- [ 0.3 0.0 0.2]
+ [ 0.3 -0.2 0.3]
+ [ 0.2 0.1 0.1]
[ 0.4 0.2 -0.1]
+ [ 0.3 0.0 0.2]
[ 0.4 0.1 -0.1]
- [ 0.2 -0.1 0.1]
- [ 0.3 -0.0 0.3]
- [ 0.4 0.1 0.1]
- [ 0.3 0.2 0.0]
+ [ 0.3 -0.1 0.2]
+ [ 0.3 0.1 0.1]
+ [ 0.3 -0.0 0.2]
+ [ 0.3 0.1 0.1]
[ 0.3 -0.2 0.3]
- [ 0.5 0.2 -0.1]
- [ 0.3 0.1 0.0]
- [ 0.2 0.0 0.0]
- [ 0.3 0.2 -0.1]
- [ 0.5 0.1 -0.0]
- [ 0.2 -0.1 0.1]
- [ 0.4 0.3 -0.1]
+ [ 0.3 0.1 0.2]
+ [ 0.4 0.1 -0.0]
+ [ 0.5 0.2 0.0]
+ [ 0.4 0.1 0.1]
+ [ 0.4 0.1 0.1]
+ [ 0.2 0.1 0.1]
[ 0.3 -0.1 0.3]
+ [ 0.4 0.1 -0.2]
+ [ 0.3 0.1 0.1]
+ [ 0.5 0.1 -0.0]
+ [ 0.4 0.1 0.1]
+ [ 0.3 0.1 0.2]
[ 0.3 0.0 0.2]
- [ 0.5 0.2 -0.1]
- [ 0.4 0.2 -0.0]
- [ 0.5 0.2 -0.0]
- [ 0.4 0.2 -0.2]
- [ 0.4 -0.1 0.3]
- [ 0.3 0.1 -0.0]
+ [ 0.3 -0.2 0.2]
+ [ 0.5 0.1 -0.0]
+ [ 0.5 0.1 -0.0]
+ [ 0.3 0.1 0.1]
+ [ 0.3 -0.1 0.2]
+ [ 0.3 0.0 0.1]
+ [ 0.3 0.2 -0.0]
+ [ 0.3 -0.2 0.2]
[ 0.2 0.0 0.3]
+ [ 0.3 -0.1 0.2]
+ [ 0.3 0.2 0.1]
+ [ 0.4 0.1 0.1]
+ [ 0.4 0.1 -0.1]
+ [ 0.5 0.1 -0.1]
+ [ 0.2 0.0 0.0]
+ [ 0.5 0.2 -0.1]
+ [ 0.3 0.1 0.1]
+ [ 0.4 0.2 0.0]
+ [ 0.2 0.2 -0.0]
+ [ 0.2 0.0 0.1]
+ [ 0.3 -0.0 0.1]
+ [ 0.2 -0.0 0.2]
+ [ 0.2 0.0 0.2]
+ [ 0.3 0.1 0.1]
[ 0.3 -0.0 0.3]
- [ 0.3 -0.1 0.1]
- [ 0.3 -0.1 0.1]]
+ [ 0.3 -0.2 0.2]
+ [ 0.3 0.2 0.1]
+ [ 0.3 0.2 0.1]
+ [ 0.3 0.1 0.0]
+ [ 0.3 0.1 0.2]
+ [ 0.3 0.0 0.2]]
# ---
# name: test_style_positions[4ozs-cartoon]
- [[ 0.2 0.0 0.0]
- [ 0.4 0.2 -0.1]
- [ 0.4 0.1 0.1]
+ [[ 0.4 0.2 -0.1]
+ [ 0.3 0.1 0.2]
[ 0.3 -0.0 0.2]
[ 0.5 0.1 -0.0]
[ 0.4 0.1 -0.2]
[ 0.3 0.2 0.0]
- [ 0.3 -0.1 0.2]
- [ 0.2 -0.0 0.0]
- [ 0.4 0.1 -0.1]
+ [ 0.3 0.1 -0.0]
[ 0.3 -0.0 0.4]
- [ 0.2 -0.0 0.2]
+ [ 0.2 -0.1 0.2]
[ 0.5 0.1 -0.1]
[ 0.3 0.0 0.2]
- [ 0.4 0.1 0.1]
+ [ 0.3 0.1 0.2]
[ 0.3 0.1 0.1]
[ 0.3 -0.2 0.2]
- [ 0.3 0.1 -0.0]
- [ 0.3 0.1 -0.0]
- [ 0.2 -0.0 0.4]
+ [ 0.3 -0.1 0.2]
+ [ 0.3 -0.1 0.2]
[ 0.4 0.1 -0.0]
[ 0.3 0.1 0.1]
- [ 0.2 0.1 0.0]
- [ 0.3 0.1 0.2]
- [ 0.3 -0.2 0.2]
- [ 0.3 0.0 0.2]
[ 0.3 -0.1 0.2]
- [ 0.3 0.1 0.3]
[ 0.3 -0.2 0.2]
+ [ 0.3 0.0 0.2]
[ 0.3 0.1 -0.1]
- [ 0.5 0.1 0.0]
+ [ 0.4 0.2 -0.2]
[ 0.4 -0.1 0.2]
[ 0.4 0.1 -0.1]
[ 0.3 -0.0 0.3]
[ 0.3 -0.2 0.2]
[ 0.3 -0.0 0.1]
- [ 0.4 0.2 -0.2]
- [ 0.3 -0.2 0.2]
+ [ 0.3 0.1 -0.1]
[ 0.4 0.1 -0.0]
[ 0.3 0.1 0.1]
- [ 0.3 -0.2 0.2]
- [ 0.2 -0.1 0.1]
- [ 0.2 0.0 0.3]
+ [ 0.2 0.1 0.3]
[ 0.4 0.1 0.0]
[ 0.5 0.2 0.0]
- [ 0.2 -0.0 0.1]
[ 0.3 0.1 0.2]
- [ 0.3 -0.1 0.2]
[ 0.3 -0.0 0.3]
- [ 0.4 0.1 0.1]
+ [ 0.3 0.1 0.2]
[ 0.3 0.1 0.1]
- [ 0.3 0.1 -0.1]
- [ 0.2 0.0 0.0]
- [ 0.3 -0.1 0.1]
- [ 0.3 -0.2 0.2]
- [ 0.3 0.2 -0.1]
+ [ 0.3 0.1 0.3]
+ [ 0.2 -0.0 0.1]
[ 0.5 0.1 -0.0]
- [ 0.2 -0.1 0.1]
[ 0.3 -0.0 0.3]
[ 0.2 0.1 0.1]
- [ 0.3 -0.0 0.1]
- [ 0.5 0.1 0.0]
+ [ 0.4 0.2 -0.2]
[ 0.2 -0.0 0.2]
[ 0.3 -0.1 0.3]
- [ 0.2 -0.0 0.1]
[ 0.4 0.1 0.1]
[ 0.4 0.1 -0.1]
- [ 0.3 0.2 -0.1]
- [ 0.3 -0.0 0.4]
- [ 0.3 0.1 -0.0]
+ [ 0.2 0.0 0.0]
+ [ 0.2 -0.1 0.1]
[ 0.3 0.1 0.2]
[ 0.4 0.1 0.1]
- [ 0.3 0.1 0.3]
- [ 0.3 0.0 0.2]
+ [ 0.3 0.0 0.1]
[ 0.2 -0.0 0.2]
- [ 0.4 -0.1 0.2]
[ 0.4 0.1 0.1]
[ 0.2 -0.1 0.3]
- [ 0.4 0.1 0.1]
+ [ 0.3 0.1 0.2]
[ 0.2 0.1 0.1]
[ 0.3 0.1 0.1]
- [ 0.3 -0.0 0.1]
[ 0.3 0.1 0.2]
- [ 0.3 -0.2 0.2]
- [ 0.3 0.1 -0.0]
+ [ 0.2 -0.1 0.1]
[ 0.4 0.1 -0.1]
[ 0.3 0.1 0.1]
[ 0.3 0.0 0.0]
[ 0.4 0.1 -0.1]
- [ 0.3 -0.1 0.1]
[ 0.3 -0.1 0.2]
- [ 0.3 0.1 0.2]
- [ 0.3 -0.0 0.4]
- [ 0.2 0.1 0.3]
- [ 0.2 0.1 0.3]
+ [ 0.3 -0.2 0.2]
[ 0.2 -0.0 0.2]
[ 0.3 -0.1 0.3]
- [ 0.3 -0.1 0.4]
+ [ 0.3 -0.1 0.3]
+ [ 0.2 -0.1 0.1]
+ [ 0.3 -0.1 0.3]
+ [ 0.3 0.1 0.3]
+ [ 0.4 0.2 0.1]
+ [ 0.3 0.1 0.2]
+ [ 0.4 0.2 -0.0]
+ [ 0.3 0.1 0.1]
+ [ 0.5 0.1 0.0]
+ [ 0.3 -0.1 0.3]
+ [ 0.3 0.1 -0.0]
+ [ 0.4 0.2 -0.1]
+ [ 0.2 0.1 0.1]
+ [ 0.3 0.1 -0.1]
+ [ 0.3 0.1 -0.1]
+ [ 0.3 0.1 -0.1]
+ [ 0.2 -0.1 0.4]
+ [ 0.4 0.2 -0.1]
+ [ 0.3 0.1 0.3]
+ [ 0.4 0.2 -0.2]
+ [ 0.3 0.1 -0.0]
+ [ 0.2 0.0 0.2]
+ [ 0.3 -0.2 0.2]
[ 0.3 0.1 -0.0]
- [ 0.3 -0.1 0.3]]
+ [ 0.3 0.1 0.1]
+ [ 0.3 0.0 0.1]
+ [ 0.4 0.1 0.1]
+ [ 0.3 0.1 0.2]
+ [ 0.3 0.0 0.0]
+ [ 0.5 0.1 -0.1]
+ [ 0.3 -0.1 0.1]]
# ---
# name: test_style_positions[4ozs-preset_1]
[[ 3.6e-01 -1.5e-01 2.5e-01]
@@ -14878,213 +15527,215 @@
[ 0.4 0.1 0.1]]
# ---
# name: test_style_positions[8H1B-ball_and_stick]
- [[-0.0 0.2 0.2]
- [-0.2 -0.1 0.0]
- [ 0.3 -0.0 0.1]
- [ 0.2 -0.2 0.2]
- [ 0.1 0.0 0.3]
- [-0.1 0.3 0.1]
- [ 0.1 0.1 0.5]
- [-0.1 -0.1 0.1]
- [ 0.2 -0.3 0.1]
- [-0.1 0.0 0.1]
- [ 0.1 -0.1 0.0]
- [-0.2 -0.1 -0.0]
- [-0.1 -0.0 0.3]
- [-0.0 -0.1 0.1]
- [ 0.0 -0.2 0.1]
- [ 0.0 -0.2 0.0]
- [ 0.1 0.2 0.3]
- [-0.1 0.0 0.4]
- [ 0.1 -0.1 0.1]
- [ 0.0 0.2 0.3]
- [ 0.2 -0.2 0.2]
- [ 0.0 -0.1 0.1]
- [ 0.0 0.2 0.3]
- [ 0.2 -0.1 0.2]
- [-0.1 -0.1 0.1]
- [ 0.1 -0.1 0.1]
- [ 0.0 0.1 0.5]
- [ 0.1 0.2 0.2]
- [-0.1 0.1 0.3]
- [ 0.1 -0.3 -0.0]
- [ 0.0 0.3 0.2]
- [-0.1 -0.2 0.2]
- [-0.1 0.0 0.3]
- [ 0.2 -0.2 0.2]
- [-0.2 -0.1 -0.0]
- [-0.1 0.0 0.4]
- [-0.1 -0.0 0.0]
- [-0.1 -0.1 0.0]
- [ 0.2 -0.0 0.1]
- [ 0.2 -0.1 0.2]
- [-0.0 0.0 0.1]
- [ 0.1 -0.1 0.5]
- [ 0.2 -0.1 -0.0]
- [ 0.2 -0.2 0.2]
- [ 0.1 0.3 0.3]
- [ 0.1 0.2 0.3]
- [-0.0 -0.1 -0.0]
- [-0.1 -0.1 -0.1]
- [-0.2 -0.0 0.3]
- [ 0.0 0.2 0.4]
- [ 0.1 -0.2 0.0]
- [ 0.1 -0.3 0.1]
- [-0.2 0.0 0.4]
- [-0.1 -0.2 0.2]
- [-0.2 -0.1 -0.1]
- [ 0.0 -0.1 0.3]
- [-0.2 0.3 0.3]
- [-0.1 0.0 0.1]
- [-0.1 -0.1 -0.1]
- [-0.1 0.2 0.2]
- [-0.0 0.1 0.3]
- [-0.2 0.1 0.3]
- [-0.1 0.2 0.2]
- [ 0.1 -0.1 0.1]
- [ 0.3 -0.1 -0.0]
- [-0.1 -0.2 0.1]
- [-0.1 -0.2 0.1]
- [-0.2 -0.1 -0.1]
- [ 0.0 -0.1 0.2]
- [ 0.1 -0.2 0.1]
- [-0.1 0.3 0.3]
- [-0.2 -0.1 -0.0]
- [ 0.2 0.0 0.5]
- [-0.1 0.1 0.3]
- [ 0.2 -0.1 0.3]
- [ 0.1 -0.0 0.3]
- [ 0.0 0.3 0.2]
- [ 0.1 0.0 0.5]
- [-0.0 0.0 0.1]
- [-0.0 0.2 0.3]
- [ 0.0 0.1 0.4]
- [ 0.0 0.1 0.4]
- [-0.0 -0.2 0.2]
- [ 0.0 0.2 0.2]
- [-0.1 0.0 -0.1]
- [ 0.2 -0.2 0.3]
- [ 0.1 0.1 0.5]
- [ 0.2 -0.1 -0.1]
- [-0.2 -0.0 0.1]
- [-0.0 0.2 0.4]
- [-0.1 -0.0 0.4]
- [ 0.1 -0.2 0.1]
- [ 0.0 0.1 0.4]
- [-0.2 -0.1 0.0]
- [-0.1 0.1 0.2]
- [-0.0 0.1 0.3]
- [-0.1 0.0 0.1]
- [ 0.0 -0.1 0.0]
- [ 0.0 0.3 0.3]
- [ 0.1 -0.0 0.1]]
+ [[ 3.8e-02 -2.2e-01 8.4e-02]
+ [-8.4e-02 1.7e-01 9.5e-02]
+ [ 2.1e-01 -9.0e-02 2.2e-01]
+ [ 1.6e-01 1.4e-02 4.4e-01]
+ [-3.0e-05 2.2e-01 4.4e-01]
+ [ 1.2e-01 -1.6e-02 2.7e-01]
+ [ 2.1e-01 -5.8e-02 8.1e-02]
+ [ 9.9e-02 -1.1e-01 1.2e-01]
+ [-1.3e-01 2.8e-01 2.3e-01]
+ [ 1.8e-01 -6.1e-02 3.1e-02]
+ [ 5.8e-02 2.1e-01 3.3e-01]
+ [-2.2e-01 -4.9e-02 1.9e-02]
+ [-8.0e-03 -1.2e-01 1.4e-01]
+ [ 1.8e-01 -1.9e-01 2.3e-01]
+ [ 2.6e-02 -4.2e-02 2.8e-01]
+ [ 9.9e-02 2.0e-02 4.7e-01]
+ [ 1.1e-01 7.6e-02 5.3e-01]
+ [-1.3e-01 2.3e-02 2.6e-01]
+ [ 7.6e-02 -2.1e-01 2.1e-01]
+ [-8.9e-02 -1.7e-02 -8.4e-02]
+ [-7.7e-02 -7.8e-02 -9.7e-03]
+ [ 8.2e-02 6.9e-02 5.1e-01]
+ [-7.8e-02 4.3e-02 4.1e-01]
+ [ 9.9e-03 8.0e-02 1.2e-01]
+ [ 5.2e-02 8.3e-02 2.9e-01]
+ [-1.5e-01 -2.8e-02 3.2e-01]
+ [ 4.2e-02 2.3e-01 3.8e-01]
+ [-1.7e-01 9.2e-02 1.1e-01]
+ [ 2.7e-02 4.7e-02 4.9e-01]
+ [ 2.4e-01 -1.2e-01 8.0e-02]
+ [-1.6e-01 1.4e-02 2.9e-01]
+ [ 1.6e-01 -1.6e-01 2.4e-01]
+ [-9.7e-02 -1.0e-02 -1.9e-02]
+ [-1.4e-01 1.2e-02 2.1e-01]
+ [-8.4e-02 2.6e-01 3.4e-01]
+ [ 1.8e-01 -3.2e-02 2.3e-01]
+ [-4.1e-03 2.3e-01 4.0e-01]
+ [ 1.3e-01 -5.9e-02 1.9e-01]
+ [ 1.1e-01 -2.2e-01 2.0e-01]
+ [ 1.8e-01 -1.0e-01 3.0e-01]
+ [ 3.9e-02 -2.1e-02 2.3e-01]
+ [-4.0e-02 3.0e-01 2.6e-01]
+ [-4.4e-02 3.0e-01 3.7e-01]
+ [ 2.7e-02 -7.6e-02 5.4e-01]
+ [ 7.7e-02 -3.3e-02 6.0e-02]
+ [ 6.5e-02 8.3e-02 2.9e-01]
+ [-9.2e-02 1.8e-01 4.3e-01]
+ [-1.9e-01 1.0e-01 1.3e-01]
+ [-1.1e-01 2.5e-02 3.9e-01]
+ [ 1.0e-01 -1.3e-01 3.5e-01]
+ [ 7.1e-03 7.4e-02 4.9e-01]
+ [ 1.7e-01 -1.2e-01 2.1e-01]
+ [-9.4e-02 1.2e-01 1.4e-01]
+ [ 6.4e-02 5.1e-02 6.0e-01]
+ [-1.4e-01 1.6e-01 2.0e-01]
+ [ 1.4e-01 -2.1e-01 1.9e-01]
+ [-2.6e-02 1.2e-01 3.3e-01]
+ [ 1.9e-01 -1.6e-01 2.3e-01]
+ [ 7.9e-02 -3.6e-02 3.0e-01]
+ [ 1.1e-01 -1.7e-01 3.6e-02]
+ [-7.3e-02 -1.8e-01 1.8e-01]
+ [ 6.9e-03 -2.1e-02 5.3e-01]
+ [ 3.4e-02 2.3e-01 1.7e-01]
+ [-3.1e-03 -2.2e-01 8.2e-02]
+ [ 8.3e-02 -2.7e-01 1.3e-01]
+ [-6.8e-02 1.7e-01 3.0e-01]
+ [ 1.5e-01 3.6e-03 2.2e-01]
+ [-8.1e-02 -2.7e-02 8.9e-02]
+ [ 1.4e-02 1.9e-01 3.1e-01]
+ [-9.4e-02 2.9e-01 1.6e-01]
+ [-4.2e-02 1.9e-01 1.7e-01]
+ [ 4.4e-02 6.1e-02 4.5e-01]
+ [-2.1e-01 1.4e-01 3.0e-01]
+ [-7.4e-02 -2.1e-02 3.0e-03]
+ [ 8.6e-02 -1.8e-02 9.0e-02]
+ [ 2.9e-02 -7.9e-02 1.2e-01]
+ [-1.1e-01 2.9e-01 2.3e-01]
+ [-1.7e-02 -1.8e-01 -2.9e-02]
+ [-1.4e-01 1.2e-01 9.1e-02]
+ [-3.5e-02 5.2e-02 3.6e-01]
+ [-1.7e-01 3.0e-02 2.4e-01]
+ [ 1.2e-01 -2.8e-02 5.4e-02]
+ [ 7.0e-02 -3.9e-02 5.5e-01]
+ [-1.3e-01 3.2e-02 4.0e-01]
+ [ 1.8e-01 -1.0e-01 5.7e-02]
+ [ 1.3e-01 -1.9e-01 7.2e-02]
+ [-5.7e-02 9.5e-02 3.4e-01]
+ [-1.6e-01 1.8e-01 2.1e-01]
+ [ 2.4e-01 -2.0e-01 2.7e-01]
+ [-2.8e-02 1.0e-02 6.4e-02]
+ [ 7.1e-02 -1.5e-01 1.4e-01]
+ [ 8.3e-02 -2.2e-01 1.0e-01]
+ [-1.4e-01 5.0e-02 1.0e-01]
+ [-5.2e-02 5.1e-02 3.6e-01]
+ [ 4.9e-02 -2.4e-01 1.5e-01]
+ [ 1.1e-01 4.0e-02 5.1e-01]
+ [ 1.1e-01 -1.8e-01 -4.6e-02]
+ [ 8.2e-02 -7.4e-02 1.5e-01]
+ [ 2.0e-01 -2.2e-01 1.2e-01]
+ [-3.8e-02 1.7e-01 3.8e-01]]
# ---
# name: test_style_positions[8H1B-cartoon]
- [[-3.3e-02 2.5e-01 4.0e-01]
- [-9.5e-02 -8.4e-02 1.3e-01]
- [-3.3e-02 1.3e-01 4.2e-01]
- [ 1.0e-01 -2.1e-01 6.3e-02]
- [-3.3e-02 2.2e-01 2.1e-01]
+ [[ 2.1e-01 -1.4e-01 3.2e-02]
+ [ 2.0e-01 -8.9e-02 1.7e-01]
+ [ 2.2e-02 -8.9e-02 2.9e-01]
+ [-8.7e-02 -2.9e-02 -1.5e-02]
+ [ 1.6e-01 -3.4e-02 4.9e-02]
+ [-5.9e-02 1.3e-01 2.3e-01]
+ [-3.3e-02 2.4e-01 2.1e-01]
+ [ 3.3e-02 2.1e-01 3.3e-01]
+ [-7.5e-02 -6.8e-02 1.2e-01]
+ [ 2.4e-01 -1.3e-01 2.1e-01]
+ [-1.7e-01 4.2e-02 1.7e-01]
+ [-2.9e-02 -1.0e-01 -1.5e-02]
+ [-1.4e-01 -1.0e-02 5.2e-02]
+ [-4.7e-02 1.8e-01 3.5e-01]
+ [-9.3e-02 -1.9e-01 1.2e-01]
+ [-4.5e-02 1.6e-01 2.1e-01]
+ [ 9.8e-02 -1.5e-01 -4.8e-02]
+ [ 2.6e-02 -7.3e-02 3.5e-01]
+ [-1.6e-01 1.4e-01 2.8e-01]
+ [-2.9e-02 -9.6e-02 4.3e-02]
+ [-1.2e-01 2.7e-01 2.7e-01]
+ [ 9.7e-02 -1.7e-01 9.8e-02]
+ [ 8.3e-02 -1.7e-01 9.4e-02]
+ [ 2.7e-01 -2.1e-01 2.7e-01]
+ [ 1.7e-01 -6.0e-02 2.3e-01]
+ [-1.6e-01 1.1e-01 3.3e-01]
+ [ 1.9e-01 -1.3e-01 -5.8e-02]
+ [ 2.7e-01 -5.8e-02 6.6e-02]
+ [ 1.8e-03 9.4e-03 3.9e-01]
+ [-9.0e-03 -1.0e-01 3.7e-02]
+ [ 8.2e-02 -2.6e-01 -2.5e-02]
+ [-7.4e-02 -6.5e-02 1.2e-01]
+ [-4.9e-02 -2.2e-01 2.3e-02]
+ [ 9.2e-02 -1.0e-01 5.1e-01]
+ [ 5.2e-02 -1.1e-01 1.2e-01]
+ [-4.5e-02 1.1e-01 3.2e-01]
+ [-3.5e-02 -1.5e-01 2.5e-01]
+ [ 1.7e-01 -6.3e-02 2.3e-01]
+ [ 2.9e-02 2.7e-01 1.7e-01]
+ [-1.3e-01 2.3e-01 3.6e-01]
+ [ 9.3e-02 -7.5e-02 1.8e-02]
+ [-9.6e-02 8.9e-02 4.6e-01]
+ [ 7.8e-03 1.3e-02 3.8e-01]
+ [ 1.7e-01 -6.7e-02 2.3e-01]
+ [ 6.4e-02 2.6e-02 5.5e-01]
+ [-1.8e-01 1.4e-01 2.9e-01]
+ [ 4.1e-02 -2.0e-02 3.9e-01]
+ [ 6.0e-02 -1.5e-01 3.0e-01]
[ 1.9e-01 -2.4e-01 1.2e-01]
- [ 1.2e-01 -9.7e-02 2.9e-01]
- [ 8.0e-02 -1.4e-01 -5.2e-03]
- [-1.9e-02 -4.9e-02 3.8e-01]
- [-9.4e-02 4.6e-02 1.5e-01]
- [-9.8e-02 8.4e-02 4.6e-01]
- [-3.6e-02 -8.0e-02 1.2e-01]
- [-8.1e-02 1.7e-01 3.0e-01]
- [ 2.2e-01 -1.1e-01 1.7e-01]
- [-1.5e-01 8.6e-02 3.4e-01]
- [-4.1e-04 2.4e-01 1.7e-01]
- [-1.4e-02 1.3e-01 4.7e-01]
- [-1.6e-01 2.3e-01 2.9e-01]
- [ 8.1e-03 -1.7e-01 1.4e-02]
- [-1.8e-01 1.5e-01 1.1e-01]
- [-8.7e-02 2.6e-01 1.8e-01]
- [ 1.1e-01 -1.5e-01 9.6e-02]
- [ 2.3e-01 -1.5e-01 2.1e-01]
- [-7.3e-02 2.3e-01 1.7e-01]
- [ 9.6e-03 -2.3e-01 1.3e-01]
- [-1.2e-01 2.5e-01 1.7e-01]
- [-6.8e-02 1.8e-01 3.0e-01]
- [-5.0e-02 -5.1e-04 3.9e-01]
- [-1.6e-01 1.1e-01 2.7e-01]
- [ 2.1e-01 -9.0e-02 2.3e-01]
- [-5.6e-02 1.7e-01 3.4e-01]
- [ 2.2e-01 -8.2e-02 1.2e-01]
- [-7.1e-02 -6.8e-02 1.2e-01]
- [-8.9e-03 2.4e-01 1.8e-01]
- [ 2.4e-01 -1.8e-01 2.8e-01]
- [-5.6e-02 5.2e-02 2.2e-01]
- [ 1.2e-01 -1.4e-01 9.0e-02]
- [-1.2e-01 3.0e-01 2.2e-01]
- [-1.6e-02 -1.9e-01 -2.3e-02]
- [-1.5e-01 8.0e-02 9.9e-02]
- [ 2.4e-01 -5.3e-02 1.1e-01]
- [ 3.9e-02 -2.8e-02 1.2e-01]
- [-1.8e-01 2.3e-01 2.6e-01]
- [ 2.3e-01 -1.3e-01 2.7e-01]
- [-7.7e-02 1.7e-01 3.2e-01]
- [ 1.3e-02 -2.4e-02 1.1e-01]
- [-5.5e-02 1.4e-01 4.7e-01]
- [ 3.1e-02 -9.0e-02 3.1e-01]
- [-4.8e-02 1.9e-01 2.9e-01]
- [ 2.6e-01 -5.9e-02 7.6e-02]
- [-1.1e-01 -9.7e-02 1.3e-01]
- [ 3.6e-02 2.6e-01 3.5e-01]
- [ 1.3e-01 -1.6e-01 -5.6e-02]
- [ 3.9e-02 2.6e-01 2.2e-01]
- [-4.9e-02 1.3e-01 2.8e-01]
- [ 5.5e-02 2.4e-01 1.8e-01]
- [ 2.3e-02 -1.7e-01 2.5e-01]
- [-6.1e-02 1.4e-01 1.7e-01]
- [-1.4e-01 1.4e-01 9.6e-02]
- [-1.4e-01 9.1e-02 1.3e-01]
- [ 2.1e-01 -4.8e-02 6.6e-02]
- [ 2.5e-01 -4.2e-02 4.1e-02]
- [ 2.0e-01 -1.2e-01 -6.4e-02]
- [-6.6e-02 1.3e-02 3.6e-01]
- [ 1.4e-01 -9.0e-02 2.4e-02]
- [-4.0e-02 -7.8e-02 1.2e-01]
- [ 4.9e-02 -5.9e-02 2.6e-01]
- [ 2.3e-02 2.0e-01 1.6e-01]
- [ 1.3e-03 -1.9e-01 3.6e-02]
- [ 2.3e-01 -1.2e-01 2.9e-02]
- [-1.8e-01 1.1e-01 3.3e-01]
- [-8.5e-03 -2.3e-01 8.2e-02]
- [-1.3e-01 2.5e-01 1.8e-01]
- [-1.6e-01 2.1e-01 2.5e-01]
- [ 2.0e-01 -1.6e-01 2.1e-01]
- [ 1.9e-01 -1.5e-01 2.0e-01]
- [ 2.6e-01 -6.1e-02 7.6e-02]
- [ 6.1e-02 2.2e-01 2.5e-01]
- [-1.4e-02 -1.5e-01 -5.0e-04]
- [-6.8e-02 -6.9e-03 1.6e-01]
- [-1.5e-01 6.4e-02 9.1e-02]
- [ 2.3e-01 -1.6e-01 2.0e-01]
- [-1.4e-01 2.0e-01 3.2e-01]
- [ 1.0e-02 2.6e-01 1.7e-01]
- [-1.8e-02 1.3e-01 4.7e-01]
- [-5.0e-02 -1.4e-01 1.2e-01]
- [-5.6e-02 -7.5e-02 1.2e-01]
- [ 1.5e-01 -6.3e-03 2.6e-01]
- [-5.5e-02 1.2e-01 2.3e-01]
- [-8.8e-02 6.3e-02 1.5e-01]
- [ 1.3e-01 -2.9e-03 1.2e-01]
- [-7.4e-02 2.2e-01 1.7e-01]
- [ 1.3e-01 -1.3e-01 9.0e-02]
- [ 4.6e-02 2.3e-01 1.6e-01]
- [-8.0e-02 8.5e-02 3.8e-01]
- [ 2.4e-01 -1.7e-01 2.6e-01]
- [-5.4e-02 -1.3e-01 1.2e-01]
- [-9.7e-02 1.1e-01 1.1e-01]
- [-7.4e-02 9.0e-02 3.5e-01]
- [ 2.3e-01 -1.4e-01 2.1e-01]]
+ [ 1.2e-01 -8.9e-02 1.7e-01]
+ [-6.6e-02 4.6e-02 1.9e-01]
+ [ 2.3e-01 -1.1e-01 1.8e-01]
+ [-1.6e-01 1.3e-01 2.1e-01]
+ [-1.4e-01 -4.0e-02 1.2e-01]
+ [ 5.3e-02 2.5e-01 1.7e-01]
+ [ 3.8e-02 -7.9e-02 3.2e-01]
+ [-1.5e-01 1.0e-01 3.2e-01]
+ [-1.2e-02 7.5e-02 1.4e-01]
+ [ 1.3e-01 -2.5e-01 6.6e-02]
+ [ 1.3e-01 -1.0e-01 3.1e-01]
+ [ 1.4e-02 6.7e-02 3.9e-01]
+ [-1.0e-01 1.1e-01 1.1e-01]
+ [-9.4e-02 2.0e-01 1.4e-01]
+ [ 2.9e-02 -1.5e-01 3.1e-01]
+ [ 4.1e-02 2.6e-01 1.8e-01]
+ [ 1.3e-01 -2.7e-02 1.5e-01]
+ [-5.1e-03 -1.5e-01 3.3e-03]
+ [-7.6e-02 9.0e-02 3.8e-01]
+ [ 3.8e-02 -2.0e-01 1.8e-01]
+ [ 3.3e-02 2.0e-01 1.6e-01]
+ [ 2.2e-01 -1.2e-01 1.7e-01]
+ [ 7.9e-02 -7.9e-02 2.0e-01]
+ [ 1.8e-01 -1.2e-01 2.1e-01]
+ [-1.9e-02 1.3e-02 3.1e-01]
+ [ 2.4e-01 -1.6e-01 2.5e-01]
+ [ 2.1e-01 -1.8e-02 1.4e-01]
+ [-1.3e-01 1.3e-01 2.7e-01]
+ [ 1.6e-02 -6.6e-02 1.9e-01]
+ [-3.1e-02 -2.3e-01 2.4e-04]
+ [-7.5e-02 -7.2e-02 1.2e-01]
+ [ 7.0e-02 -2.1e-01 -6.7e-04]
+ [ 1.5e-01 -1.9e-01 2.2e-01]
+ [-2.2e-01 -9.6e-02 2.0e-02]
+ [-1.9e-01 1.1e-01 2.8e-01]
+ [ 4.3e-03 1.9e-01 3.8e-01]
+ [ 7.8e-03 -8.4e-02 2.8e-01]
+ [-1.5e-01 2.7e-02 3.0e-01]
+ [ 4.8e-02 1.5e-01 2.1e-01]
+ [-5.7e-03 -1.9e-01 5.5e-02]
+ [-1.0e-01 -1.9e-03 4.4e-01]
+ [ 1.5e-02 5.8e-02 3.7e-01]
+ [ 1.6e-01 -2.4e-02 1.6e-01]
+ [-1.5e-02 2.8e-01 2.9e-01]
+ [-1.6e-01 8.3e-02 3.3e-01]
+ [ 5.8e-02 2.5e-01 3.8e-01]
+ [-1.1e-01 2.8e-01 3.5e-01]
+ [-7.6e-02 -8.0e-03 1.7e-01]
+ [-1.0e-02 -1.9e-01 2.0e-01]
+ [ 2.2e-01 -1.1e-01 7.9e-02]
+ [ 1.8e-01 -8.1e-02 3.0e-01]]
# ---
# name: test_style_positions[8H1B-preset_1]
- [[ 0.1 -0.1 0.3]
+ [[ 0.1 -0.2 0.1]
+ [ 0.1 -0.1 0.3]
[-0.1 0.2 0.3]
[-0.1 -0.2 0.0]
+ [ 0.0 -0.2 0.0]
[-0.1 0.0 0.1]
[-0.0 0.2 0.2]
[ 0.1 -0.0 0.3]
@@ -15092,15 +15743,16 @@
[-0.2 -0.0 -0.0]
[-0.0 -0.0 0.2]
[ 0.0 -0.1 0.1]
- [ 0.1 -0.2 0.1]
- [ 0.1 -0.1 0.0]
+ [ 0.0 -0.2 0.1]
+ [-0.1 0.2 0.4]
[ 0.2 -0.1 0.0]
[ 0.0 -0.1 0.1]
+ [ 0.0 -0.2 0.1]
[ 0.0 0.1 0.2]
[-0.1 0.0 0.2]
[-0.0 -0.3 0.1]
[-0.2 0.1 0.2]
- [ 0.1 -0.1 0.1]
+ [-0.1 0.1 0.4]
[ 0.2 -0.1 -0.0]
[-0.1 -0.1 0.1]
[-0.1 -0.1 0.1]
@@ -15109,10 +15761,10 @@
[-0.2 0.1 0.3]
[ 0.0 -0.2 0.3]
[-0.1 -0.2 0.2]
- [-0.0 0.2 0.4]
+ [-0.0 0.1 0.4]
[-0.1 0.2 0.4]
[-0.2 0.1 0.1]
- [-0.2 -0.0 -0.0]
+ [-0.2 -0.0 0.0]
[ 0.1 -0.1 0.2]
[-0.1 0.0 -0.0]
[-0.1 0.2 0.5]
@@ -15125,10 +15777,10 @@
[ 0.2 -0.2 0.1]
[-0.0 0.1 0.4]
[-0.0 0.2 0.4]
- [ 0.1 -0.2 0.1]
+ [ 0.0 -0.1 0.1]
[-0.1 0.1 0.2]
[-0.0 0.1 0.4]
- [ 0.0 0.0 0.5]
+ [ 0.0 0.1 0.5]
[-0.0 0.0 0.3]
[ 0.0 0.2 0.4]
[-0.1 0.2 0.4]
@@ -15141,10 +15793,10 @@
[ 0.2 -0.2 0.2]
[ 0.1 -0.1 0.3]
[ 0.0 -0.0 0.4]
- [-0.0 0.1 0.3]
+ [-0.0 0.1 0.4]
[ 0.1 -0.2 0.2]
[ 0.0 0.2 0.2]
- [ 0.0 0.0 0.5]
+ [-0.0 0.0 0.5]
[ 0.1 -0.1 -0.0]
[-0.2 -0.0 0.3]
[-0.0 -0.1 0.1]
@@ -15175,13 +15827,10 @@
[ 0.2 -0.1 0.2]
[ 0.1 0.1 0.2]
[-0.2 0.1 0.3]
+ [ 0.1 -0.2 0.1]
[ 0.0 0.1 0.4]
[ 0.1 0.1 0.2]
- [ 0.1 -0.0 0.4]
- [ 0.1 -0.0 0.1]
- [-0.0 -0.2 0.2]
- [-0.1 -0.1 -0.0]
- [ 0.2 -0.1 0.3]]
+ [ 0.1 -0.0 0.4]]
# ---
# name: test_style_positions[8H1B-ribbon]
[[ 1.2e-01 -1.0e-01 3.5e-01]
@@ -15191,7 +15840,7 @@
[-3.2e-02 2.4e-01 2.2e-01]
[ 1.3e-01 -7.8e-03 2.6e-01]
[-1.2e-01 2.3e-01 1.8e-01]
- [-2.4e-01 -3.6e-02 -1.6e-02]
+ [-2.3e-01 -3.7e-02 -5.2e-03]
[-3.2e-02 -3.7e-02 2.0e-01]
[ 4.3e-02 -1.4e-01 9.4e-02]
[ 1.7e-01 -7.4e-02 1.8e-02]
@@ -15203,15 +15852,15 @@
[ 1.6e-01 -1.3e-01 -3.1e-02]
[-7.1e-02 -1.4e-01 1.1e-01]
[-1.1e-01 -1.4e-01 1.1e-01]
- [-1.3e-01 -1.8e-02 6.8e-02]
+ [-1.4e-01 -1.5e-02 6.4e-02]
[-1.5e-02 2.7e-01 4.3e-01]
[-2.0e-01 1.3e-01 2.7e-01]
[ 2.6e-02 -1.5e-01 2.7e-01]
[-5.0e-02 -1.8e-01 2.0e-01]
[-1.6e-01 9.2e-02 1.2e-01]
- [-2.4e-01 -3.1e-02 -7.8e-04]
+ [-2.3e-01 -3.2e-02 1.0e-02]
[ 8.2e-02 -7.6e-02 2.3e-01]
- [-1.2e-01 9.9e-03 -1.9e-02]
+ [-1.3e-01 1.6e-02 -3.0e-02]
[-7.6e-02 2.4e-01 4.6e-01]
[ 2.1e-01 -1.5e-01 4.8e-02]
[ 1.5e-01 1.1e-02 1.8e-01]
@@ -15222,22 +15871,22 @@
[ 2.1e-01 -2.3e-01 1.3e-01]
[-4.1e-02 2.5e-01 4.3e-01]
[-1.5e-01 1.2e-01 2.2e-01]
- [ 1.1e-02 4.6e-02 4.9e-01]
+ [ 2.2e-03 4.9e-02 4.8e-01]
[-1.8e-02 6.1e-03 3.5e-01]
[ 7.4e-03 2.4e-01 3.7e-01]
[-5.6e-02 1.8e-01 3.6e-01]
[-5.8e-02 -1.3e-02 1.5e-01]
[-1.3e-01 1.6e-01 2.4e-01]
- [ 1.0e-01 8.2e-02 5.1e-01]
+ [ 1.1e-01 7.3e-02 5.2e-01]
[ 7.2e-02 -1.3e-01 7.8e-03]
[-4.2e-02 -2.7e-01 3.8e-02]
[-1.7e-01 1.3e-01 2.7e-01]
[ 1.8e-01 -1.9e-01 2.5e-01]
[ 1.4e-01 -9.4e-02 3.0e-01]
- [ 2.1e-02 -3.6e-02 3.7e-01]
+ [ 2.3e-02 -3.9e-02 3.8e-01]
[ 1.1e-01 -2.2e-01 2.0e-01]
[ 1.0e-02 2.0e-01 1.6e-01]
- [ 3.5e-03 1.8e-02 5.1e-01]
+ [-4.5e-03 2.1e-02 5.0e-01]
[ 9.3e-02 -1.2e-01 -9.1e-03]
[-1.5e-01 -4.7e-03 2.9e-01]
[-4.5e-02 -6.4e-02 1.1e-01]
@@ -15248,12 +15897,12 @@
[-8.9e-02 2.6e-01 3.7e-01]
[-4.2e-02 2.2e-01 4.3e-01]
[ 3.7e-02 -2.0e-01 1.8e-01]
- [-7.1e-02 -7.7e-02 6.3e-02]
+ [-8.2e-02 -7.2e-02 5.6e-02]
[ 1.4e-01 -7.8e-02 2.1e-01]
[-1.9e-01 1.6e-01 2.2e-01]
[-4.8e-02 2.7e-01 3.4e-01]
[ 5.4e-02 -8.8e-02 2.1e-01]
- [-2.6e-01 -4.3e-02 -2.2e-02]
+ [-2.5e-01 -4.4e-02 -1.1e-02]
[-9.4e-02 7.6e-02 1.4e-01]
[-1.6e-02 8.7e-02 1.1e-01]
[-1.5e-01 1.3e-01 2.5e-01]
@@ -15268,10 +15917,10 @@
[-1.6e-01 1.3e-01 3.0e-01]
[ 6.4e-03 1.3e-01 4.4e-01]
[ 6.7e-02 1.3e-01 2.4e-01]
- [ 1.1e-01 -3.2e-02 3.8e-01]
+ [ 1.1e-01 -3.0e-02 3.9e-01]
[ 1.2e-01 -4.2e-03 1.2e-01]
[-1.2e-02 -1.6e-01 2.1e-01]
- [-8.9e-02 -1.4e-01 -7.6e-03]
+ [-7.8e-02 -1.4e-01 1.1e-03]
[ 2.4e-01 -1.4e-01 2.9e-01]
[ 2.1e-01 -1.4e-01 3.1e-01]
[-1.1e-01 1.3e-01 7.9e-02]
@@ -15281,7 +15930,7 @@
[ 1.6e-01 -1.7e-01 5.6e-02]
[-2.6e-02 -4.3e-02 3.5e-01]
[-1.6e-01 1.8e-01 3.0e-01]
- [-9.1e-02 -9.6e-02 6.6e-02]
+ [-9.0e-02 -9.4e-02 7.2e-02]
[-2.1e-02 -2.4e-01 6.0e-02]
[ 2.1e-02 1.8e-01 3.3e-01]]
# ---
@@ -15391,208 +16040,208 @@
[-1.3e-01 1.7e-01 4.7e-01]]
# ---
# name: test_style_positions[8U8W-ball_and_stick]
- [[-2.3e-01 -1.6e-01 2.1e-01]
- [-1.7e-01 -2.0e-01 1.9e-01]
- [-2.0e-01 -1.4e-01 1.2e-01]
- [-2.7e-01 8.0e-02 3.4e-01]
- [-3.2e-01 1.2e-01 2.0e-01]
- [-2.2e-01 1.6e-01 2.1e-01]
- [-2.2e-01 -1.2e-01 2.6e-01]
- [-3.9e-01 -1.5e-01 2.5e-01]
- [-2.5e-01 -4.9e-02 1.6e-01]
- [-3.2e-01 1.7e-01 1.4e-01]
- [-3.6e-01 1.7e-01 2.4e-01]
- [-3.7e-01 5.4e-02 2.5e-01]
- [-4.1e-01 6.6e-02 1.8e-01]
- [-2.5e-01 -7.9e-02 1.2e-01]
- [-3.5e-01 -3.2e-02 3.2e-01]
- [-2.3e-01 1.1e-01 8.0e-02]
- [-3.0e-01 -1.6e-01 3.6e-02]
- [-3.3e-01 -1.8e-01 1.1e-01]
- [-2.1e-01 3.8e-02 1.7e-01]
- [-3.8e-01 1.6e-02 3.5e-01]
- [-2.7e-01 -1.9e-01 2.2e-01]
- [-3.6e-01 -1.6e-01 2.0e-01]
- [-2.7e-01 9.8e-02 2.7e-01]
- [-3.6e-01 -2.3e-01 1.3e-01]
- [-2.1e-01 1.0e-01 2.4e-01]
- [-2.0e-01 1.8e-01 1.2e-01]
- [-3.5e-01 8.8e-02 1.6e-01]
- [-1.9e-01 1.1e-01 1.5e-01]
- [-3.7e-01 2.1e-01 4.6e-02]
- [-3.3e-01 1.3e-01 -1.3e-02]
- [-3.8e-01 1.2e-01 3.4e-01]
- [-2.9e-01 -2.8e-02 4.2e-02]
- [-2.0e-01 1.3e-01 1.4e-01]
- [-3.4e-01 -1.6e-02 3.3e-01]
- [-1.5e-01 -1.8e-01 1.5e-01]
- [-4.9e-01 9.8e-02 1.7e-01]
- [-2.5e-01 8.2e-03 2.0e-01]
- [-3.3e-01 3.9e-02 1.0e-01]
- [-4.4e-01 -1.2e-01 2.6e-01]
- [-3.2e-01 1.1e-02 3.7e-01]
- [-3.8e-01 1.6e-01 3.9e-02]
- [-1.9e-01 -4.6e-02 1.3e-01]
- [-3.9e-01 3.2e-02 3.5e-01]
- [-1.9e-01 -7.7e-02 -4.3e-04]
- [-2.2e-01 -2.3e-01 2.8e-01]
- [-3.2e-01 -2.6e-02 4.1e-01]
- [-8.4e-02 -9.5e-03 6.1e-02]
- [-3.3e-01 8.2e-02 2.3e-01]
- [-2.1e-01 -2.1e-01 2.2e-01]
- [-3.8e-01 1.8e-01 6.9e-02]
- [-4.1e-01 8.7e-02 3.3e-01]
- [-4.0e-01 -2.4e-01 1.9e-01]
- [-2.7e-01 8.5e-02 1.1e-01]
- [-4.2e-01 1.7e-01 1.8e-01]
- [-4.1e-01 1.3e-01 4.1e-02]
- [-4.3e-01 -1.1e-01 2.8e-01]
- [-4.0e-01 -1.2e-01 3.4e-01]
- [-2.2e-01 8.3e-02 2.0e-01]
- [-1.7e-01 -2.4e-03 4.6e-02]
- [-2.2e-01 -1.4e-01 5.8e-02]
- [-3.4e-01 2.0e-02 3.2e-01]
- [-4.3e-01 -2.1e-01 3.5e-01]
- [-4.0e-01 -2.7e-01 1.1e-01]
- [-3.1e-01 8.3e-02 2.6e-01]
- [-3.9e-01 1.1e-01 1.8e-01]
- [-3.8e-01 -5.2e-02 3.7e-01]
- [-3.4e-01 2.2e-01 1.9e-01]
- [-1.8e-01 -9.1e-02 1.3e-01]
- [-2.5e-01 2.9e-02 3.0e-01]
- [-2.6e-01 -8.9e-02 2.8e-01]
- [-4.3e-01 -1.0e-01 1.9e-01]
- [-2.4e-01 -3.1e-02 3.5e-01]
- [-2.4e-01 -6.7e-02 5.4e-02]
- [-3.6e-01 -7.6e-03 2.4e-01]
- [-4.2e-01 -5.5e-02 3.4e-01]
- [-3.8e-01 -4.1e-02 2.0e-01]
- [-3.3e-01 -1.8e-02 3.2e-01]
- [-3.5e-01 1.3e-01 2.0e-01]
- [-3.0e-01 -1.6e-01 2.1e-01]
- [-2.8e-01 -2.6e-01 1.9e-01]
- [-3.2e-01 -2.1e-01 1.6e-01]
- [-4.6e-01 2.0e-01 2.0e-01]
- [-3.2e-01 2.0e-01 1.4e-01]
- [-3.7e-01 1.9e-01 1.6e-01]
- [-2.3e-01 -1.2e-01 7.6e-02]
- [-3.2e-01 6.1e-02 9.7e-02]
- [-5.0e-01 1.2e-01 1.4e-01]
- [-3.4e-01 -7.5e-02 3.9e-01]
- [-2.4e-01 -8.0e-02 1.2e-01]
- [-2.4e-01 -1.5e-02 3.4e-02]
- [-4.5e-01 3.0e-02 3.2e-01]
- [-2.2e-01 1.8e-01 6.3e-02]
- [-4.7e-01 -1.4e-01 2.0e-01]
- [-2.9e-01 2.3e-02 1.7e-02]
- [-2.1e-01 -1.7e-02 1.6e-01]
- [-2.7e-01 -5.5e-02 8.5e-02]
- [-4.0e-01 8.6e-02 3.2e-01]
- [-2.2e-01 1.1e-01 2.5e-01]
- [-3.9e-01 -2.6e-01 1.7e-01]
- [-3.0e-01 -2.1e-02 5.2e-02]]
+ [[-0.3 0.1 0.0]
+ [-0.3 -0.0 0.4]
+ [-0.3 0.0 0.2]
+ [-0.2 -0.1 0.2]
+ [-0.2 -0.2 0.3]
+ [-0.2 0.2 0.2]
+ [-0.5 0.1 0.1]
+ [-0.3 -0.2 0.3]
+ [-0.3 0.1 0.1]
+ [-0.4 -0.0 0.3]
+ [-0.3 -0.0 0.2]
+ [-0.3 -0.2 0.3]
+ [-0.4 -0.2 0.3]
+ [-0.1 -0.0 0.1]
+ [-0.5 0.1 0.2]
+ [-0.3 0.1 0.2]
+ [-0.2 0.1 0.2]
+ [-0.3 0.1 0.2]
+ [-0.3 0.1 0.2]
+ [-0.3 -0.3 0.2]
+ [-0.3 0.0 0.2]
+ [-0.3 0.2 0.2]
+ [-0.3 0.1 0.2]
+ [-0.4 0.2 0.1]
+ [-0.2 -0.1 0.1]
+ [-0.4 -0.2 0.3]
+ [-0.2 -0.1 0.2]
+ [-0.2 -0.2 0.2]
+ [-0.2 0.1 0.4]
+ [-0.4 -0.1 0.3]
+ [-0.5 -0.2 0.2]
+ [-0.3 0.0 0.3]
+ [-0.2 -0.2 0.2]
+ [-0.4 -0.2 0.2]
+ [-0.3 0.0 0.1]
+ [-0.2 -0.1 0.2]
+ [-0.3 0.0 0.3]
+ [-0.3 0.2 0.2]
+ [-0.2 -0.1 0.1]
+ [-0.2 -0.2 -0.0]
+ [-0.4 0.0 0.2]
+ [-0.2 -0.1 0.3]
+ [-0.3 0.1 0.2]
+ [-0.3 0.1 0.1]
+ [-0.3 -0.2 0.3]
+ [-0.2 -0.2 0.2]
+ [-0.4 0.1 0.3]
+ [-0.3 0.2 0.2]
+ [-0.5 0.1 0.2]
+ [-0.3 0.1 0.0]
+ [-0.4 -0.2 0.1]
+ [-0.3 0.1 0.3]
+ [-0.3 -0.1 0.3]
+ [-0.2 -0.1 0.0]
+ [-0.2 -0.2 0.2]
+ [-0.2 0.0 0.0]
+ [-0.2 0.1 0.1]
+ [-0.4 -0.2 0.3]
+ [-0.4 -0.2 0.1]
+ [-0.2 -0.2 0.2]
+ [-0.3 0.0 0.1]
+ [-0.3 0.1 0.3]
+ [-0.2 -0.0 0.3]
+ [-0.3 0.1 0.4]
+ [-0.3 -0.3 0.2]
+ [-0.4 0.2 0.2]
+ [-0.3 0.1 0.2]
+ [-0.4 0.1 0.4]
+ [-0.3 -0.1 0.2]
+ [-0.3 -0.2 0.3]
+ [-0.2 -0.0 0.1]
+ [-0.3 -0.2 0.2]
+ [-0.3 0.2 0.2]
+ [-0.4 -0.0 0.3]
+ [-0.3 0.0 0.3]
+ [-0.3 0.2 0.1]
+ [-0.5 0.1 0.2]
+ [-0.2 0.0 0.0]
+ [-0.3 0.1 -0.0]
+ [-0.5 0.2 0.2]
+ [-0.3 -0.0 0.2]
+ [-0.4 0.2 0.1]
+ [-0.4 0.0 0.2]
+ [-0.3 -0.1 0.3]
+ [-0.4 -0.1 0.2]
+ [-0.4 -0.1 0.3]
+ [-0.4 0.2 0.1]
+ [-0.4 -0.2 0.2]
+ [-0.1 -0.0 0.1]
+ [-0.2 -0.0 0.1]
+ [-0.4 -0.2 0.1]
+ [-0.4 -0.1 0.3]
+ [-0.2 0.0 0.2]
+ [-0.4 0.1 0.2]
+ [-0.4 0.2 0.3]
+ [-0.2 -0.1 0.0]
+ [-0.4 0.1 0.2]
+ [-0.4 -0.3 0.2]
+ [-0.5 0.1 0.2]
+ [-0.3 -0.0 0.2]]
# ---
# name: test_style_positions[8U8W-cartoon]
- [[-3.2e-01 1.7e-01 2.1e-01]
- [-4.1e-01 -1.4e-02 3.5e-01]
- [-4.1e-01 6.8e-02 1.6e-01]
- [-3.6e-01 -1.1e-01 1.7e-01]
- [-2.8e-01 4.8e-02 1.2e-01]
- [-2.3e-01 1.2e-04 1.7e-01]
- [-3.8e-01 3.7e-02 1.0e-01]
- [-3.2e-01 -1.9e-01 3.1e-01]
- [-3.5e-01 1.6e-02 5.8e-02]
- [-2.7e-01 7.9e-02 3.3e-01]
- [-3.9e-01 -1.1e-01 3.4e-01]
- [-2.1e-01 2.1e-02 1.6e-01]
+ [[-4.0e-01 -1.4e-02 3.5e-01]
+ [-3.0e-01 -1.8e-01 3.0e-01]
+ [-3.7e-01 -1.1e-01 1.7e-01]
+ [-2.8e-01 4.9e-02 1.1e-01]
+ [-2.3e-01 -1.1e-03 1.7e-01]
+ [-3.8e-01 3.8e-02 1.0e-01]
+ [-2.1e-01 6.2e-02 1.1e-01]
+ [-2.2e-01 3.3e-02 2.7e-01]
+ [-3.3e-01 -7.6e-02 2.4e-01]
[-3.2e-01 1.1e-01 1.8e-01]
- [-2.7e-01 -1.7e-01 2.5e-01]
- [-4.4e-01 8.3e-02 1.7e-01]
- [-2.4e-01 5.3e-02 3.7e-02]
- [-3.6e-01 -5.2e-02 1.9e-01]
- [-3.8e-01 4.1e-02 1.2e-01]
- [-3.8e-01 3.5e-02 1.2e-01]
- [-4.2e-01 -1.3e-01 2.5e-01]
- [-2.6e-01 -9.2e-04 3.3e-01]
- [-2.6e-01 3.3e-03 4.9e-02]
- [-3.5e-01 2.0e-01 1.7e-01]
- [-4.2e-01 1.1e-01 7.1e-02]
- [-4.4e-01 -1.7e-01 2.0e-01]
- [-3.3e-01 -1.6e-01 1.7e-01]
- [-3.2e-01 -1.9e-01 3.1e-01]
- [-2.5e-01 1.3e-01 1.3e-01]
- [-4.5e-01 -1.3e-01 2.5e-01]
- [-3.3e-01 -2.1e-02 3.2e-01]
- [-2.2e-01 3.7e-02 3.3e-01]
- [-3.3e-01 -8.4e-02 2.4e-01]
- [-3.0e-01 -2.4e-02 3.3e-01]
- [-4.3e-01 -1.7e-01 3.3e-01]
- [-3.8e-01 -2.2e-02 2.0e-01]
- [-3.3e-01 -1.6e-01 6.9e-02]
- [-3.7e-01 5.3e-02 2.6e-01]
- [-4.5e-01 -1.7e-01 2.0e-01]
- [-2.7e-01 -7.4e-03 3.3e-01]
- [-2.4e-01 3.6e-02 1.8e-02]
- [-4.5e-01 -1.8e-01 2.0e-01]
- [-2.9e-01 -3.3e-02 1.6e-01]
+ [-2.6e-01 -1.7e-01 2.5e-01]
+ [-3.5e-01 -1.8e-01 2.8e-01]
+ [-2.4e-01 5.0e-02 3.8e-02]
+ [-3.1e-01 1.8e-01 3.1e-01]
+ [-2.6e-01 -6.0e-04 3.2e-01]
+ [-2.6e-01 2.2e-04 4.9e-02]
+ [-3.4e-01 -1.6e-01 1.6e-01]
+ [-3.2e-01 -2.2e-02 3.2e-01]
+ [-4.6e-01 4.0e-02 9.7e-02]
+ [-4.2e-01 -1.4e-01 3.1e-01]
+ [-3.0e-01 -2.3e-02 3.3e-01]
+ [-3.6e-01 -5.2e-02 2.4e-01]
+ [-5.1e-01 1.2e-01 1.4e-01]
+ [-3.3e-01 -1.6e-01 6.8e-02]
+ [-3.5e-01 2.0e-02 9.2e-02]
+ [-2.6e-01 -7.0e-03 3.3e-01]
+ [-2.4e-01 3.3e-02 1.8e-02]
[-2.6e-01 -2.3e-01 1.4e-01]
- [-2.5e-01 -3.2e-02 3.6e-01]
- [-1.9e-01 9.3e-02 2.1e-01]
- [-3.4e-01 3.5e-03 4.5e-02]
- [-2.4e-01 -7.8e-02 1.8e-01]
- [-2.8e-01 -1.6e-01 2.8e-01]
- [-4.2e-01 -1.8e-01 3.3e-01]
- [-4.2e-01 8.0e-02 1.6e-01]
- [-2.4e-01 1.0e-02 6.1e-02]
- [-5.0e-01 1.3e-01 1.4e-01]
- [-3.1e-01 1.6e-01 2.0e-01]
- [-2.4e-01 -1.9e-01 2.4e-01]
- [-4.4e-01 -1.6e-01 2.0e-01]
- [-5.3e-01 5.9e-02 1.6e-01]
+ [-2.6e-01 -3.3e-02 3.6e-01]
+ [-1.9e-01 9.0e-02 2.1e-01]
+ [-2.4e-01 -7.8e-02 1.9e-01]
+ [-3.5e-01 -5.4e-02 2.1e-01]
+ [-3.2e-01 -1.9e-01 3.1e-01]
+ [-2.4e-01 7.3e-03 6.0e-02]
+ [-4.4e-01 -1.5e-01 2.1e-01]
[-2.8e-01 1.2e-01 1.7e-01]
- [-2.2e-01 4.7e-02 1.2e-01]
- [-4.3e-01 -1.8e-01 3.4e-01]
- [-2.8e-01 -1.4e-01 6.1e-02]
- [-2.1e-01 1.6e-01 1.0e-01]
- [-1.8e-01 4.0e-02 3.2e-01]
- [-2.0e-01 1.8e-01 1.7e-01]
- [-4.0e-01 -2.0e-01 3.2e-01]
- [-3.4e-01 4.4e-03 3.8e-02]
+ [-3.5e-01 -5.8e-02 2.3e-01]
+ [-2.8e-01 -1.4e-01 6.3e-02]
+ [-4.3e-01 9.4e-02 6.9e-02]
+ [-2.0e-01 1.8e-01 1.8e-01]
+ [-3.8e-01 -2.0e-02 2.0e-01]
[-3.1e-01 1.1e-01 3.7e-01]
- [-3.4e-01 1.2e-02 3.4e-01]
- [-5.1e-01 3.5e-02 1.6e-01]
- [-4.0e-01 -1.5e-01 2.4e-01]
- [-2.9e-01 1.5e-01 2.8e-01]
- [-2.9e-01 -8.5e-02 1.5e-01]
- [-3.5e-01 6.8e-02 3.2e-01]
- [-2.5e-01 1.3e-01 1.3e-01]
- [-3.2e-01 -1.9e-01 3.1e-01]
+ [-3.4e-01 1.0e-02 3.4e-01]
+ [-4.8e-01 -1.4e-01 2.3e-01]
+ [-2.9e-01 -8.3e-02 1.5e-01]
+ [-3.5e-01 6.7e-02 3.2e-01]
[-3.3e-01 -1.5e-01 2.1e-01]
- [-2.2e-01 1.4e-01 2.0e-01]
- [-2.2e-01 2.4e-02 2.1e-02]
- [-1.8e-01 -8.0e-02 2.2e-01]
- [-4.1e-01 6.1e-02 1.7e-01]
- [-1.2e-01 1.5e-02 7.6e-02]
- [-3.9e-01 1.4e-01 2.5e-01]
- [-2.4e-01 1.6e-01 7.6e-02]
- [-2.0e-01 -9.0e-02 1.2e-01]
- [-4.4e-01 -1.6e-01 2.0e-01]
- [-3.0e-01 1.8e-01 2.9e-01]
- [-3.2e-01 6.0e-02 2.5e-01]
- [-2.4e-01 -1.4e-02 6.5e-02]
- [-3.0e-01 7.5e-02 -9.9e-03]
- [-3.4e-01 8.0e-02 2.1e-01]
- [-2.4e-01 -2.0e-01 2.7e-01]
- [-3.2e-01 -6.7e-02 2.4e-01]
- [-4.1e-01 1.3e-01 4.3e-02]
- [-3.5e-01 -1.8e-01 2.5e-01]
- [-3.2e-01 -2.0e-02 9.5e-02]
- [-3.2e-01 -8.6e-03 1.1e-01]
- [-2.0e-01 1.8e-01 1.9e-01]
- [-3.8e-01 -1.0e-01 3.4e-01]
- [-3.6e-01 -1.2e-01 3.3e-01]
- [-2.9e-01 1.4e-01 2.7e-01]
- [-1.9e-01 -1.7e-02 2.1e-01]]
+ [-2.2e-01 1.3e-02 1.7e-01]
+ [-2.1e-01 2.0e-02 2.0e-02]
+ [-4.3e-01 4.9e-02 2.4e-01]
+ [-2.9e-01 -1.6e-01 2.9e-01]
+ [-1.2e-01 1.2e-02 7.6e-02]
+ [-4.0e-01 1.4e-01 2.5e-01]
+ [-2.0e-01 -9.3e-02 1.2e-01]
+ [-3.2e-01 6.3e-02 2.5e-01]
+ [-2.4e-01 -1.2e-02 6.3e-02]
+ [-2.9e-01 7.8e-02 -9.9e-03]
+ [-3.4e-01 7.9e-02 2.1e-01]
+ [-4.3e-01 -1.7e-01 3.3e-01]
+ [-2.0e-01 1.7e-01 2.1e-01]
+ [-3.6e-01 4.5e-02 2.4e-01]
+ [-4.0e-01 6.3e-02 2.5e-01]
+ [-2.8e-01 6.9e-02 3.1e-01]
+ [-2.8e-01 -2.6e-01 1.7e-01]
+ [-4.8e-01 1.5e-01 1.6e-01]
+ [-3.5e-01 -1.9e-01 2.9e-01]
+ [-3.1e-01 -1.3e-01 3.3e-01]
+ [-2.8e-01 -7.3e-02 6.3e-02]
+ [-3.8e-01 3.9e-02 1.2e-01]
+ [-4.4e-01 8.3e-02 1.7e-01]
+ [-2.5e-01 -1.1e-04 3.7e-01]
+ [-3.2e-01 1.7e-01 2.1e-01]
+ [-2.8e-01 -1.5e-01 5.4e-02]
+ [-3.1e-01 6.9e-03 3.2e-01]
+ [-3.5e-01 1.8e-02 7.8e-02]
+ [-3.4e-01 2.0e-02 6.0e-02]
+ [-4.4e-01 5.4e-02 2.4e-01]
+ [-4.3e-01 -3.4e-02 3.0e-01]
+ [-4.5e-01 6.9e-02 1.0e-01]
+ [-2.1e-01 5.5e-02 1.2e-01]
+ [-1.3e-01 -1.5e-01 1.7e-01]
+ [-5.1e-01 1.1e-01 1.4e-01]
+ [-3.5e-01 -1.2e-02 3.7e-01]
+ [-2.5e-01 2.0e-02 3.1e-02]
+ [-3.1e-01 -1.7e-01 1.8e-01]
+ [-3.4e-01 3.9e-02 1.1e-02]
+ [-3.3e-01 -2.0e-01 3.0e-01]
+ [-2.9e-01 9.2e-02 4.1e-02]
+ [-3.7e-01 6.8e-02 1.9e-01]
+ [-4.4e-01 1.6e-01 1.3e-01]
+ [-3.0e-01 -1.7e-01 6.8e-02]
+ [-3.5e-01 -5.6e-02 2.2e-01]
+ [-2.6e-01 -2.2e-02 4.4e-02]
+ [-3.9e-01 -1.9e-01 9.5e-02]
+ [-4.6e-01 -1.4e-01 2.0e-01]
+ [-2.6e-01 1.7e-01 7.5e-02]
+ [-3.8e-01 -1.8e-01 3.3e-01]
+ [-3.5e-01 -1.4e-01 9.2e-02]
+ [-5.0e-01 1.3e-01 1.4e-01]
+ [-3.7e-01 6.2e-02 1.3e-01]]
# ---
# name: test_style_positions[8U8W-preset_1]
[[-3.5e-01 -6.4e-02 2.4e-01]
@@ -15606,7 +16255,7 @@
[-2.6e-01 -1.5e-02 6.4e-02]
[-3.3e-01 -9.7e-02 2.4e-01]
[-3.2e-01 7.3e-02 1.2e-01]
- [-3.5e-01 -2.9e-02 1.8e-01]
+ [-3.5e-01 -1.8e-02 1.8e-01]
[-4.5e-01 1.9e-01 2.1e-01]
[-3.7e-01 -1.2e-01 1.5e-01]
[-4.3e-01 -1.2e-02 3.5e-01]
@@ -15629,7 +16278,8 @@
[-1.4e-01 -4.7e-02 1.3e-01]
[-1.6e-01 -1.7e-01 1.6e-01]
[-4.7e-01 1.5e-01 1.5e-01]
- [-3.5e-01 -2.1e-02 4.0e-01]
+ [-4.7e-01 1.4e-01 7.8e-02]
+ [-3.5e-01 3.9e-02 -4.1e-02]
[-3.9e-01 -1.7e-01 3.3e-01]
[-1.6e-01 -4.9e-02 1.1e-01]
[-3.8e-01 1.4e-01 2.4e-02]
@@ -15638,7 +16288,8 @@
[-2.1e-01 -6.5e-02 1.3e-01]
[-1.7e-01 3.1e-02 3.3e-01]
[-4.4e-01 -2.8e-02 2.9e-01]
- [-4.7e-01 1.2e-01 8.2e-02]
+ [-3.5e-01 5.7e-02 -5.2e-02]
+ [-1.9e-01 6.7e-02 6.3e-02]
[-4.3e-01 1.6e-01 2.1e-01]
[-2.4e-01 2.4e-02 3.4e-01]
[-2.9e-01 1.2e-01 1.9e-01]
@@ -15649,6 +16300,7 @@
[-3.1e-01 1.0e-01 1.9e-01]
[-4.8e-01 6.4e-02 2.5e-01]
[-3.9e-01 1.8e-01 2.9e-01]
+ [-3.4e-01 -1.8e-02 4.1e-01]
[-2.0e-01 1.2e-02 1.6e-01]
[-4.8e-01 1.7e-01 1.2e-01]
[-3.1e-01 7.9e-02 2.6e-01]
@@ -15657,10 +16309,11 @@
[-2.6e-01 8.3e-02 1.4e-01]
[-9.1e-02 -5.5e-03 1.7e-02]
[-1.4e-01 -4.8e-02 7.8e-03]
+ [-1.9e-01 6.4e-02 6.1e-02]
[-2.2e-01 -9.8e-02 6.3e-02]
[-2.8e-01 1.0e-01 -5.2e-04]
[-2.9e-01 4.1e-02 2.7e-01]
- [-3.5e-01 -2.3e-02 1.8e-01]
+ [-3.5e-01 -1.5e-02 1.8e-01]
[-2.0e-01 -1.0e-01 3.0e-01]
[-5.2e-01 1.1e-01 1.2e-01]
[-3.4e-01 -1.7e-01 2.3e-01]
@@ -15673,6 +16326,7 @@
[-4.5e-01 -1.2e-01 2.7e-01]
[-1.3e-01 -9.8e-02 1.2e-02]
[-3.7e-01 2.4e-03 2.1e-01]
+ [-3.5e-01 -2.1e-02 4.0e-01]
[-2.7e-01 -1.8e-01 2.3e-01]
[-2.8e-01 -2.3e-01 1.9e-01]
[-2.6e-01 1.5e-01 1.3e-01]
@@ -15689,12 +16343,7 @@
[-3.5e-01 1.6e-01 9.9e-02]
[-1.6e-01 -6.7e-02 1.2e-01]
[-5.1e-01 1.4e-01 1.2e-01]
- [-3.5e-01 1.4e-01 1.3e-01]
- [-4.7e-01 1.4e-01 7.9e-02]
- [-4.6e-01 -1.5e-01 2.0e-01]
- [-2.3e-01 5.8e-02 6.3e-03]
- [-3.6e-01 1.9e-01 1.3e-01]
- [-3.6e-01 -1.9e-01 1.3e-01]]
+ [-3.5e-01 1.4e-01 1.3e-01]]
# ---
# name: test_style_positions[8U8W-ribbon]
[[-0.3 -0.1 0.1]
diff --git a/tests/__snapshots__/test_mda.ambr b/tests/__snapshots__/test_mda.ambr
deleted file mode 100644
index 0647de7a..00000000
--- a/tests/__snapshots__/test_mda.ambr
+++ /dev/null
@@ -1,1712 +0,0 @@
-# serializer version: 1
-# name: TestMDA.test_save_persistance[False]
- [[0.4 0.3 0.5]
- [0.4 0.3 0.5]
- [0.4 0.3 0.5]
- ...
- [1.3 0.3 0.6]
- [1.3 0.4 0.6]
- [1.3 0.4 0.6]]
-# ---
-# name: TestMDA.test_save_persistance[True]
- [[0.4 0.3 0.5]
- [0.4 0.3 0.5]
- [0.4 0.3 0.5]
- ...
- [1.3 0.3 0.6]
- [1.3 0.4 0.6]
- [1.3 0.4 0.6]]
-# ---
-# name: TestMDA.test_show_multiple_selection[False]
- AttributeError("The selected attribute 'posiiton' does not exist on the mesh.")
-# ---
-# name: TestMDA.test_show_multiple_selection[False].1
- []
-# ---
-# name: TestMDA.test_show_multiple_selection[True]
- AttributeError("The selected attribute 'posiiton' does not exist on the mesh.")
-# ---
-# name: TestMDA.test_show_universe[False]
- []
-# ---
-# name: TestMDA.test_show_universe[True]
- []
-# ---
-# name: TestMDA.test_show_updated_atoms[False]
- [[0.4 0.3 0.5]
- [0.4 0.3 0.5]
- [0.4 0.3 0.5]
- ...
- [0.4 0.3 0.5]
- [0.4 0.3 0.5]
- [0.4 0.3 0.5]]
-# ---
-# name: TestMDA.test_show_updated_atoms[False].1
- [[0.4 0.3 0.5]
- [0.4 0.3 0.5]
- [0.4 0.3 0.5]
- ...
- [0.4 0.3 0.5]
- [0.4 0.3 0.5]
- [0.4 0.3 0.5]]
-# ---
-# name: TestMDA.test_show_updated_atoms[True]
- [[0.4 0.3 0.5]
- [0.4 0.3 0.5]
- [0.4 0.3 0.5]
- ...
- [0.4 0.3 0.5]
- [0.4 0.3 0.5]
- [0.4 0.3 0.5]]
-# ---
-# name: TestMDA.test_show_updated_atoms[True].1
- [[0.4 0.3 0.5]
- [0.4 0.3 0.5]
- [0.4 0.3 0.5]
- ...
- [0.4 0.3 0.5]
- [0.4 0.3 0.5]
- [0.4 0.3 0.5]]
-# ---
-# name: TestMDA.test_trajectory_update[False]
- [[1.2 0.3 0.8]
- [0.7 0.4 0.4]
- [1.2 0.5 0.6]
- [0.8 0.2 0.7]
- [0.5 0.3 0.4]
- [0.4 0.3 0.5]
- [0.7 0.5 0.5]
- [1.3 0.3 0.6]
- [1.1 0.7 0.6]
- [0.9 0.4 0.4]
- [1.0 0.2 0.5]
- [0.5 0.2 0.5]
- [0.8 0.3 0.5]
- [1.3 0.5 0.6]
- [0.7 0.6 0.8]
- [1.1 0.5 0.4]
- [1.2 0.4 0.8]
- [1.1 0.4 0.8]
- [0.5 0.5 0.3]
- [0.8 0.5 0.7]
- [1.3 0.3 0.7]
- [1.3 0.4 0.7]
- [0.8 0.2 0.7]
- [0.9 0.4 0.6]
- [0.6 0.4 0.3]
- [1.2 0.6 0.4]
- [0.8 0.2 0.5]
- [0.5 0.5 0.3]
- [1.0 0.3 0.4]
- [1.0 0.5 0.5]
- [0.9 0.4 0.7]
- [1.1 0.5 0.5]
- [0.6 0.5 0.4]
- [0.7 0.5 0.7]
- [1.0 0.2 0.6]
- [0.5 0.4 0.3]
- [0.6 0.3 0.5]
- [1.4 0.3 0.6]
- [0.6 0.5 0.7]
- [1.0 0.3 0.3]
- [1.3 0.5 0.6]
- [0.7 0.6 0.8]
- [1.2 0.4 0.7]
- [1.1 0.2 0.7]
- [1.1 0.5 0.8]
- [0.4 0.2 0.4]
- [1.0 0.3 0.4]
- [0.8 0.4 0.7]
- [0.6 0.5 0.6]
- [1.1 0.5 0.4]
- [0.7 0.2 0.5]
- [1.1 0.3 0.4]
- [1.4 0.3 0.6]
- [0.7 0.5 0.4]
- [0.6 0.4 0.3]
- [1.1 0.6 0.8]
- [1.3 0.4 0.7]
- [0.6 0.6 0.7]
- [0.7 0.5 0.4]
- [0.8 0.4 0.6]
- [0.7 0.2 0.7]
- [0.9 0.2 0.5]
- [0.7 0.5 0.7]
- [1.0 0.4 0.4]
- [1.2 0.5 0.7]
- [0.8 0.4 0.8]
- [0.6 0.5 0.5]
- [0.6 0.4 0.5]
- [0.8 0.5 0.7]
- [1.3 0.4 0.6]
- [0.6 0.3 0.5]
- [0.8 0.6 0.7]
- [0.6 0.6 0.6]
- [0.6 0.2 0.5]
- [0.9 0.2 0.4]
- [1.4 0.3 0.7]
- [1.1 0.5 0.6]
- [1.1 0.4 0.5]
- [0.8 0.3 0.5]
- [0.9 0.5 0.4]
- [1.0 0.4 0.4]
- [1.3 0.5 0.8]
- [1.1 0.4 0.4]
- [1.0 0.2 0.6]
- [0.6 0.6 0.4]
- [1.3 0.5 0.6]
- [0.6 0.3 0.3]
- [0.8 0.5 0.7]
- [1.1 0.5 0.4]
- [0.4 0.3 0.5]
- [1.0 0.5 0.3]
- [0.5 0.5 0.3]
- [1.0 0.6 0.5]
- [0.8 0.3 0.7]
- [0.6 0.4 0.4]
- [0.7 0.4 0.6]
- [1.0 0.6 0.5]
- [1.1 0.5 0.5]
- [1.0 0.4 0.4]
- [0.6 0.4 0.4]]
-# ---
-# name: TestMDA.test_trajectory_update[False].1
- [[1.2 0.3 0.8]
- [0.7 0.4 0.4]
- [1.2 0.5 0.6]
- [0.8 0.2 0.7]
- [0.5 0.3 0.4]
- [0.4 0.3 0.5]
- [0.7 0.5 0.5]
- [1.3 0.3 0.6]
- [1.1 0.7 0.6]
- [0.9 0.4 0.4]
- [1.0 0.2 0.5]
- [0.5 0.2 0.5]
- [0.8 0.3 0.5]
- [1.3 0.5 0.6]
- [0.7 0.6 0.8]
- [1.1 0.5 0.4]
- [1.1 0.4 0.8]
- [1.1 0.4 0.8]
- [0.5 0.5 0.3]
- [0.8 0.5 0.7]
- [1.3 0.3 0.7]
- [1.3 0.4 0.7]
- [0.8 0.2 0.7]
- [0.9 0.4 0.5]
- [0.6 0.4 0.3]
- [1.2 0.6 0.4]
- [0.8 0.2 0.5]
- [0.5 0.5 0.3]
- [0.9 0.3 0.4]
- [1.0 0.5 0.5]
- [0.9 0.4 0.6]
- [1.1 0.5 0.5]
- [0.5 0.5 0.4]
- [0.7 0.5 0.7]
- [0.9 0.2 0.6]
- [0.5 0.4 0.3]
- [0.6 0.3 0.5]
- [1.4 0.3 0.6]
- [0.6 0.5 0.7]
- [1.0 0.3 0.3]
- [1.2 0.5 0.6]
- [0.7 0.6 0.8]
- [1.2 0.4 0.7]
- [1.2 0.2 0.7]
- [1.1 0.5 0.8]
- [0.4 0.2 0.4]
- [1.0 0.3 0.4]
- [0.8 0.4 0.7]
- [0.6 0.5 0.6]
- [1.1 0.6 0.4]
- [0.7 0.2 0.5]
- [1.0 0.3 0.4]
- [1.4 0.3 0.6]
- [0.7 0.5 0.4]
- [0.6 0.4 0.3]
- [1.1 0.6 0.8]
- [1.3 0.4 0.7]
- [0.6 0.6 0.7]
- [0.7 0.5 0.3]
- [0.8 0.4 0.6]
- [0.7 0.2 0.7]
- [0.9 0.2 0.5]
- [0.7 0.5 0.7]
- [1.0 0.4 0.4]
- [1.2 0.5 0.7]
- [0.8 0.4 0.7]
- [0.6 0.5 0.5]
- [0.5 0.4 0.5]
- [0.8 0.5 0.6]
- [1.3 0.5 0.6]
- [0.6 0.3 0.5]
- [0.8 0.5 0.7]
- [0.6 0.5 0.6]
- [0.5 0.2 0.5]
- [0.9 0.2 0.4]
- [1.4 0.4 0.7]
- [1.1 0.5 0.6]
- [1.1 0.4 0.5]
- [0.8 0.3 0.5]
- [0.9 0.5 0.4]
- [1.0 0.4 0.4]
- [1.3 0.4 0.8]
- [1.1 0.4 0.4]
- [0.9 0.2 0.6]
- [0.6 0.6 0.4]
- [1.3 0.5 0.6]
- [0.6 0.3 0.3]
- [0.8 0.5 0.7]
- [1.1 0.5 0.4]
- [0.4 0.3 0.5]
- [1.0 0.5 0.3]
- [0.5 0.5 0.3]
- [1.0 0.6 0.5]
- [0.8 0.3 0.7]
- [0.6 0.4 0.4]
- [0.7 0.4 0.6]
- [1.0 0.6 0.5]
- [1.1 0.5 0.5]
- [1.0 0.4 0.4]
- [0.6 0.4 0.4]]
-# ---
-# name: TestMDA.test_trajectory_update[True]
- [[0.5 0.5 0.3]
- [1.2 0.3 0.8]
- [0.9 0.2 0.5]
- [0.6 0.3 0.5]
- [0.4 0.3 0.5]
- [0.7 0.5 0.6]
- [1.3 0.4 0.7]
- [1.0 0.6 0.5]
- [1.0 0.4 0.4]
- [0.4 0.2 0.4]
- [1.0 0.2 0.5]
- [1.2 0.2 0.6]
- [0.7 0.4 0.8]
- [1.3 0.5 0.6]
- [0.7 0.5 0.4]
- [0.8 0.4 0.8]
- [1.0 0.3 0.5]
- [0.6 0.5 0.4]
- [1.1 0.6 0.7]
- [1.0 0.5 0.4]
- [0.7 0.5 0.5]
- [1.1 0.6 0.5]
- [1.2 0.5 0.6]
- [0.9 0.2 0.6]
- [1.3 0.5 0.7]
- [0.7 0.5 0.4]
- [0.7 0.4 0.8]
- [0.9 0.4 0.4]
- [0.8 0.5 0.4]
- [0.6 0.3 0.3]
- [0.7 0.3 0.7]
- [1.1 0.6 0.4]
- [1.2 0.3 0.7]
- [0.7 0.4 0.8]
- [1.0 0.4 0.5]
- [0.5 0.4 0.5]
- [0.4 0.3 0.4]
- [1.1 0.6 0.4]
- [1.0 0.2 0.6]
- [1.1 0.5 0.7]
- [1.0 0.3 0.4]
- [1.2 0.5 0.4]
- [0.7 0.5 0.5]
- [0.6 0.5 0.5]
- [1.4 0.3 0.6]
- [0.7 0.4 0.7]
- [0.6 0.5 0.5]
- [1.0 0.2 0.5]
- [0.9 0.3 0.3]
- [0.7 0.4 0.8]
- [1.1 0.5 0.5]
- [1.2 0.2 0.7]
- [0.8 0.3 0.7]
- [0.6 0.6 0.6]
- [0.9 0.4 0.7]
- [0.6 0.2 0.5]
- [0.8 0.4 0.7]
- [0.6 0.5 0.7]
- [0.5 0.2 0.5]
- [1.1 0.4 0.4]
- [1.0 0.3 0.3]
- [1.0 0.5 0.6]
- [1.1 0.6 0.6]
- [1.2 0.6 0.5]
- [0.9 0.4 0.4]
- [0.8 0.6 0.5]
- [1.2 0.3 0.6]
- [0.4 0.3 0.3]
- [0.9 0.5 0.7]
- [1.2 0.5 0.7]
- [1.0 0.7 0.6]
- [0.7 0.5 0.4]
- [1.3 0.4 0.7]
- [0.9 0.2 0.6]
- [0.6 0.5 0.4]
- [1.3 0.4 0.7]
- [1.3 0.4 0.8]
- [1.1 0.5 0.5]
- [0.6 0.5 0.4]
- [1.1 0.5 0.6]
- [1.1 0.6 0.7]
- [1.3 0.4 0.7]
- [1.0 0.3 0.4]
- [1.2 0.5 0.6]
- [0.5 0.5 0.5]
- [0.8 0.4 0.8]
- [1.0 0.3 0.5]
- [1.2 0.4 0.8]
- [1.2 0.3 0.7]
- [0.7 0.4 0.7]
- [0.5 0.2 0.5]
- [0.4 0.2 0.4]
- [0.7 0.6 0.5]
- [0.8 0.2 0.6]
- [1.1 0.5 0.4]
- [0.8 0.4 0.8]
- [0.8 0.2 0.6]
- [0.5 0.3 0.5]
- [1.2 0.4 0.7]
- [1.1 0.4 0.4]]
-# ---
-# name: TestMDA.test_trajectory_update[True].1
- [[-8.0e-03 -1.4e-02 0.0e+00]
- [ 1.2e-02 -1.0e-02 0.0e+00]
- [ 1.6e-02 0.0e+00 0.0e+00]
- [ 1.2e-02 1.0e-02 0.0e+00]
- [ 2.8e-03 1.6e-02 0.0e+00]
- [ 1.6e-02 0.0e+00 0.0e+00]
- [ 2.8e-03 1.6e-02 0.0e+00]
- [ 2.8e-03 1.6e-02 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [-8.0e-03 1.4e-02 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [-1.5e-02 -5.5e-03 0.0e+00]
- [-1.5e-02 -5.5e-03 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [ 1.6e-02 0.0e+00 0.0e+00]
- [ 2.8e-03 1.6e-02 0.0e+00]
- [-1.5e-02 5.5e-03 0.0e+00]
- [-1.5e-02 -5.5e-03 0.0e+00]
- [-1.5e-02 -5.5e-03 0.0e+00]
- [-1.5e-02 -5.5e-03 0.0e+00]
- [ 1.2e-02 1.0e-02 0.0e+00]
- [ 1.6e-02 0.0e+00 0.0e+00]
- [ 1.2e-02 1.0e-02 0.0e+00]
- [ 1.2e-02 -1.0e-02 0.0e+00]
- [ 1.2e-02 -1.0e-02 0.0e+00]
- [ 2.8e-03 -1.6e-02 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [-8.0e-03 1.4e-02 0.0e+00]
- [-8.0e-03 1.4e-02 0.0e+00]
- [-1.5e-02 -5.5e-03 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [ 1.2e-02 1.0e-02 0.0e+00]
- [ 1.6e-02 0.0e+00 0.0e+00]
- [-1.5e-02 -5.5e-03 0.0e+00]
- [-1.4e-02 8.0e-03 0.0e+00]
- [-1.6e-02 -1.4e-09 0.0e+00]
- [ 1.2e-02 -1.0e-02 0.0e+00]
- [-1.5e-02 5.5e-03 0.0e+00]
- [ 2.8e-03 1.6e-02 0.0e+00]
- [ 1.2e-02 -1.0e-02 0.0e+00]
- [ 1.6e-02 0.0e+00 0.0e+00]
- [-8.0e-03 1.4e-02 0.0e+00]
- [ 2.8e-03 -1.6e-02 0.0e+00]
- [ 1.6e-02 0.0e+00 0.0e+00]
- [ 1.6e-02 0.0e+00 0.0e+00]
- [ 1.2e-02 -1.0e-02 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [ 1.2e-02 -1.0e-02 0.0e+00]
- [ 2.8e-03 -1.6e-02 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [-1.5e-02 5.5e-03 0.0e+00]
- [ 1.2e-02 -1.0e-02 0.0e+00]
- [-1.5e-02 -5.5e-03 0.0e+00]
- [-8.0e-03 1.4e-02 0.0e+00]
- [ 1.2e-02 1.0e-02 0.0e+00]
- [-8.0e-03 1.4e-02 0.0e+00]
- [-1.5e-02 -5.5e-03 0.0e+00]
- [ 1.2e-02 1.0e-02 0.0e+00]
- [ 1.2e-02 1.0e-02 0.0e+00]
- [ 1.2e-02 1.0e-02 0.0e+00]
- [ 1.2e-02 -1.0e-02 0.0e+00]
- [ 1.2e-02 1.0e-02 0.0e+00]
- [ 2.8e-03 -1.6e-02 0.0e+00]
- [-1.5e-02 5.5e-03 0.0e+00]
- [-1.5e-02 -5.5e-03 0.0e+00]
- [ 1.6e-02 0.0e+00 0.0e+00]
- [ 1.2e-02 -1.0e-02 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [-8.0e-03 1.4e-02 0.0e+00]
- [-8.0e-03 1.4e-02 0.0e+00]
- [ 1.2e-02 -1.0e-02 0.0e+00]
- [ 1.6e-02 0.0e+00 0.0e+00]
- [ 2.8e-03 1.6e-02 0.0e+00]
- [-1.5e-02 5.5e-03 0.0e+00]
- [-1.5e-02 5.5e-03 0.0e+00]
- [-8.0e-03 1.4e-02 0.0e+00]
- [ 1.2e-02 1.0e-02 0.0e+00]
- [ 2.8e-03 -1.6e-02 0.0e+00]
- [-1.6e-02 -1.4e-09 0.0e+00]
- [ 1.6e-02 0.0e+00 0.0e+00]
- [ 1.2e-02 1.0e-02 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [ 1.2e-02 1.0e-02 0.0e+00]
- [-1.5e-02 -5.5e-03 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [ 1.6e-02 0.0e+00 0.0e+00]
- [-8.0e-03 1.4e-02 0.0e+00]
- [ 1.6e-02 0.0e+00 0.0e+00]
- [ 2.8e-03 1.6e-02 0.0e+00]
- [ 2.8e-03 1.6e-02 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [ 1.6e-02 0.0e+00 0.0e+00]
- [-8.0e-03 -1.4e-02 0.0e+00]
- [-8.0e-03 1.4e-02 0.0e+00]
- [-8.0e-03 1.4e-02 0.0e+00]
- [ 1.2e-02 -1.0e-02 0.0e+00]
- [ 1.2e-02 -1.0e-02 0.0e+00]]
-# ---
-# name: test_martini[pent/TOPOL2.pdb]
- [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
- 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
- 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
- 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
- 0. 0. 0. 0.]
-# ---
-# name: test_martini[pent/TOPOL2.pdb].1
- [10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8
- 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8
- 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8
- 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8
- 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8
- 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8
- 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8
- 10.8 10.8]
-# ---
-# name: test_martini[pent/TOPOL2.pdb].10
- [ True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True]
-# ---
-# name: test_martini[pent/TOPOL2.pdb].11
- [ True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True]
-# ---
-# name: test_martini[pent/TOPOL2.pdb].12
- [ True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True]
-# ---
-# name: test_martini[pent/TOPOL2.pdb].13
- [False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False]
-# ---
-# name: test_martini[pent/TOPOL2.pdb].14
- [False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False]
-# ---
-# name: test_martini[pent/TOPOL2.pdb].15
- [False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False]
-# ---
-# name: test_martini[pent/TOPOL2.pdb].16
- [ True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True True True True True True True True True
- True True True True]
-# ---
-# name: test_martini[pent/TOPOL2.pdb].17
- [False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False]
-# ---
-# name: test_martini[pent/TOPOL2.pdb].18
- [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
- 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
- 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
- 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
- 0. 0. 0. 0.]
-# ---
-# name: test_martini[pent/TOPOL2.pdb].19
- [10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8
- 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8
- 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8
- 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8
- 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8
- 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8
- 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8
- 10.8 10.8]
-# ---
-# name: test_martini[pent/TOPOL2.pdb].2
- [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
- 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
- 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
- 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
- 0. 0. 0. 0.]
-# ---
-# name: test_martini[pent/TOPOL2.pdb].20
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-# ---
-# name: test_martini[pent/prot_ion.tpr]
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-# ---
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-# ---
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- [0.5 1.1 1.1]
- [0.7 1.3 0.9]
- [0.8 1.7 1.2]
- [1.2 0.9 1.1]
- [1.5 0.5 1.7]
- [1.6 1.6 1.7]
- [1.3 1.8 0.9]
- [1.6 0.7 1.5]
- [1.5 1.0 1.5]
- [1.5 1.5 1.8]
- [0.6 1.1 1.2]
- [1.0 0.9 1.3]
- [1.4 1.4 1.8]
- [1.1 0.6 1.1]
- [1.0 0.7 0.8]
- [1.5 1.0 1.5]
- [0.5 1.1 1.0]
- [0.8 1.5 1.2]
- [0.7 1.1 0.7]
- [1.1 1.8 1.4]
- [0.4 1.0 1.1]
- [1.5 1.5 1.1]
- [1.4 0.7 1.7]
- [1.1 0.8 1.0]
- [0.8 0.7 1.4]
- [1.6 1.6 1.7]
- [1.2 1.5 1.2]
- [1.0 1.4 1.3]
- [1.0 2.0 1.2]
- [1.5 1.5 1.6]
- [0.9 1.2 1.2]
- [1.0 0.9 1.1]
- [1.1 1.6 0.8]
- [1.4 1.6 1.5]
- [1.6 1.4 1.3]
- [0.8 0.8 1.2]
- [1.3 1.3 1.2]
- [1.5 1.6 1.6]
- [1.6 1.5 1.1]
- [1.6 1.2 1.3]
- [1.1 1.2 0.9]
- [1.0 1.9 1.3]
- [0.8 1.3 1.1]
- [0.9 1.2 1.2]
- [0.7 0.7 1.2]
- [0.6 1.4 0.6]
- [1.3 1.7 0.9]
- [1.4 1.6 1.2]
- [1.1 1.0 1.2]
- [1.1 1.0 1.5]
- [1.7 1.4 1.1]
- [0.6 1.4 0.9]
- [0.9 1.3 0.6]
- [1.4 0.6 1.4]
- [1.3 0.8 0.9]
- [0.9 1.6 1.2]
- [1.3 0.8 1.7]
- [1.2 0.8 1.0]
- [1.3 1.0 1.1]
- [0.9 1.2 1.2]
- [1.6 0.9 1.1]
- [0.9 0.5 1.0]
- [0.6 1.2 0.8]
- [0.8 0.5 1.3]
- [1.0 1.8 1.4]
- [0.6 1.3 0.9]
- [1.3 0.8 1.5]
- [1.6 1.5 1.6]
- [1.2 1.6 1.3]
- [1.3 1.1 1.2]
- [1.1 0.9 1.1]
- [1.7 1.4 1.3]
- [1.5 1.2 1.3]
- [1.6 1.1 1.2]
- [1.1 0.5 1.1]
- [1.2 1.5 1.1]
- [0.8 1.7 1.2]]
-# ---
diff --git a/tests/__snapshots__/test_mol_sdf.ambr b/tests/__snapshots__/test_mol_sdf.ambr
index 2511c8ce..8897af2d 100644
--- a/tests/__snapshots__/test_mol_sdf.ambr
+++ b/tests/__snapshots__/test_mol_sdf.ambr
@@ -19,208 +19,208 @@
AttributeError("The selected attribute 'sec_struct' does not exist on the mesh.")
# ---
# name: test_load[ball_and_stick-mol].13
- [[1.0 1.0 1.0 1.0]
- [1.0 1.0 1.0 1.0]
- [1.0 1.0 1.0 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
+ [[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[0.2 0.2 0.8 1.0]
[0.2 0.2 0.8 1.0]
- [0.8 0.2 0.2 1.0]
- [1.0 1.0 1.0 1.0]
- [1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
+ [0.2 0.2 0.8 1.0]
[0.4 0.4 0.8 1.0]
+ [0.8 0.2 0.2 1.0]
+ [0.8 0.2 0.2 1.0]
+ [0.2 0.2 0.8 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
- [0.4 0.4 0.8 1.0]
- [0.2 0.2 0.8 1.0]
[1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
- [0.2 0.2 0.8 1.0]
[0.4 0.4 0.8 1.0]
- [1.0 1.0 1.0 1.0]
- [0.8 0.2 0.2 1.0]
- [1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
[0.4 0.4 0.8 1.0]
[0.4 0.4 0.8 1.0]
- [1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
[0.8 0.2 0.2 1.0]
+ [0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
+ [0.2 0.2 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.2 0.2 0.8 1.0]
[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
- [0.2 0.2 0.8 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
+ [0.2 0.2 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
- [0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
+ [0.2 0.2 0.8 1.0]
[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
- [0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[0.2 0.2 0.8 1.0]
+ [0.2 0.2 0.8 1.0]
+ [1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
+ [0.2 0.2 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.2 0.2 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
- [0.8 0.2 0.2 1.0]
[1.0 1.0 1.0 1.0]
+ [0.2 0.2 0.8 1.0]
+ [0.2 0.2 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
[0.2 0.2 0.8 1.0]
- [1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
- [1.0 1.0 1.0 1.0]
[0.8 0.2 0.2 1.0]
[1.0 1.0 1.0 1.0]
- [1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
[0.4 0.4 0.8 1.0]
- [1.0 1.0 1.0 1.0]
- [0.8 0.2 0.2 1.0]
[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
- [1.0 1.0 1.0 1.0]
- [1.0 1.0 1.0 1.0]
- [0.4 0.4 0.8 1.0]
[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
- [0.4 0.4 0.8 1.0]
- [0.2 0.2 0.8 1.0]
[1.0 1.0 1.0 1.0]
- [0.4 0.4 0.8 1.0]
[0.2 0.2 0.8 1.0]
- [0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
+ [1.0 1.0 1.0 1.0]
+ [1.0 1.0 1.0 1.0]
+ [1.0 1.0 1.0 1.0]
+ [1.0 1.0 1.0 1.0]
+ [1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
[0.8 0.2 0.2 1.0]
[1.0 1.0 1.0 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
- [0.2 0.2 0.8 1.0]
- [0.2 0.2 0.8 1.0]
[1.0 1.0 1.0 1.0]
- [0.8 0.2 0.2 1.0]
[0.4 0.4 0.8 1.0]
[0.4 0.4 0.8 1.0]
+ [1.0 1.0 1.0 1.0]
+ [0.2 0.2 0.8 1.0]
[0.2 0.2 0.8 1.0]
[1.0 1.0 1.0 1.0]]
# ---
# name: test_load[ball_and_stick-mol].14
- [[-1.0e-02 -3.2e-02 1.3e-02]
- [-1.1e-02 9.6e-03 -1.0e-06]
- [ 3.0e-02 1.0e-02 4.3e-03]
- [-6.3e-03 -1.6e-02 -2.1e-03]
- [-6.8e-03 -1.4e-02 2.6e-10]
- [ 1.9e-03 2.7e-02 6.0e-06]
- [-9.9e-03 -3.0e-02 -3.0e-03]
- [-1.6e-02 2.9e-02 -3.0e-06]
- [-9.9e-03 -3.4e-02 1.2e-02]
- [ 3.3e-02 1.6e-02 2.3e-03]
- [ 3.9e-04 -7.7e-03 -2.7e-03]
- [-1.0e-02 1.3e-02 2.4e-03]
- [-3.2e-03 -1.0e-02 -2.6e-03]
- [-9.7e-03 -1.8e-02 0.0e+00]
- [-1.9e-02 2.5e-02 -2.3e-03]
- [-2.3e-02 2.8e-02 2.0e-06]
- [-2.0e-02 5.5e-05 -4.3e-03]
- [-7.0e-03 -3.3e-02 -8.9e-03]
+ [[-1.4e-02 -2.8e-02 -2.6e-03]
+ [-1.4e-02 -1.9e-02 1.5e-03]
+ [-9.0e-03 -3.4e-02 7.2e-03]
+ [ 2.0e-02 -2.5e-05 4.0e-03]
+ [-3.1e-02 1.8e-02 -8.8e-03]
+ [ 2.9e-02 -1.6e-02 -1.5e-03]
+ [ 3.2e-02 1.7e-02 3.0e-06]
+ [-3.2e-02 -8.1e-03 2.4e-03]
+ [ 4.7e-03 2.6e-02 -4.6e-03]
+ [ 2.5e-03 -5.9e-03 -2.3e-03]
+ [-2.1e-02 -1.5e-03 -1.5e-03]
+ [ 1.6e-02 4.6e-03 -1.5e-03]
+ [-3.1e-02 2.0e-02 1.2e-02]
+ [ 2.6e-02 -9.6e-03 1.5e-03]
+ [ 5.3e-03 -1.1e-02 -2.6e-03]
+ [ 3.9e-02 9.7e-03 1.6e-03]
[-1.0e-02 -3.6e-02 -8.9e-03]
- [-2.6e-02 2.0e-02 8.9e-03]
- [-2.1e-02 2.4e-02 7.0e-06]
- [ 3.2e-02 1.6e-02 1.0e-02]
- [-2.5e-02 -2.4e-02 1.1e-05]
- [-2.5e-02 -2.8e-02 3.6e-03]
- [-2.8e-02 2.2e-02 -1.2e-02]
- [-8.4e-03 -9.2e-03 2.1e-03]
- [ 3.3e-02 1.6e-02 -1.1e-02]
- [-2.7e-02 2.4e-02 8.9e-03]
- [-1.1e-02 1.3e-02 -1.0e-06]
- [-1.8e-02 5.5e-05 4.3e-03]
- [ 1.1e-02 -2.3e-02 2.0e-06]
- [-1.9e-02 1.5e-02 2.6e-03]
- [ 6.4e-03 1.0e-03 4.3e-03]
- [-1.9e-02 -2.5e-03 5.1e-03]
- [-3.4e-02 -2.2e-03 -2.4e-03]
- [ 2.6e-02 -9.4e-03 4.3e-03]
- [-1.9e-02 2.6e-02 -2.6e-03]
- [-3.0e-02 2.3e-02 -1.2e-02]
- [ 3.4e-02 1.8e-02 1.1e-02]
- [ 1.9e-02 3.7e-03 -2.4e-03]
- [ 1.5e-02 -1.8e-02 -2.6e-03]
- [ 2.2e-02 -1.6e-03 -3.0e-06]
- [-9.9e-03 -3.0e-02 1.2e-02]
- [-2.1e-02 3.3e-02 -3.0e-06]
- [-1.5e-02 3.2e-02 1.6e-03]
- [ 1.2e-02 5.1e-03 2.7e-03]
- [-2.3e-02 2.2e-02 -5.1e-03]
- [-2.0e-02 2.1e-02 7.0e-06]
- [ 3.7e-02 -1.5e-02 -3.1e-03]
- [-7.4e-03 -3.2e-02 7.1e-03]
- [ 3.3e-02 2.1e-02 9.0e-03]
- [-2.8e-02 2.0e-02 -1.2e-02]
- [-2.4e-02 2.6e-02 2.7e-03]
- [-1.1e-02 -1.4e-02 2.6e-03]
+ [ 3.6e-02 -1.3e-02 -1.5e-03]
+ [-3.3e-02 -8.3e-03 -2.0e-03]
+ [-2.4e-02 1.9e-02 -4.3e-03]
+ [-3.0e-02 2.4e-02 -7.0e-03]
+ [-2.0e-02 -2.6e-02 2.6e-03]
+ [-2.2e-02 -6.6e-03 -4.0e-06]
+ [ 9.1e-03 -4.9e-03 -6.0e-06]
+ [ 3.3e-02 1.3e-02 6.0e-03]
[ 2.8e-02 1.6e-02 1.1e-02]
- [ 1.1e-02 2.6e-03 4.3e-03]
- [-3.0e-02 -5.6e-04 2.0e-03]
- [ 3.9e-02 6.7e-03 2.0e-06]
- [ 3.0e-02 -1.2e-02 2.3e-03]
- [-1.0e-02 1.3e-02 -2.1e-03]
- [ 3.7e-03 4.2e-03 -8.0e-06]
- [ 4.2e-02 7.8e-03 -3.6e-03]
- [ 7.6e-03 -4.3e-03 2.6e-03]
- [-1.6e-02 8.8e-03 -1.0e-06]
- [-2.6e-02 2.6e-02 7.0e-06]
- [-2.6e-02 2.1e-02 7.0e-03]
- [ 3.6e-02 -1.8e-02 3.1e-03]
- [-1.9e-02 2.6e-02 2.6e-03]
- [ 7.2e-03 3.1e-03 2.6e-03]
- [ 4.0e-02 6.7e-03 3.1e-03]
- [-8.5e-03 -1.7e-02 -2.4e-03]
- [-1.2e-02 1.5e-02 -2.4e-03]
- [-2.2e-02 2.1e-02 2.6e-03]
- [ 2.6e-03 -1.4e-02 2.7e-03]
- [ 3.5e-02 1.5e-02 2.7e-03]
- [ 6.0e-03 2.2e-02 2.0e-03]
- [ 3.4e-02 -1.9e-02 8.0e-06]
- [ 4.0e-02 7.8e-03 -3.1e-03]
- [-2.9e-02 1.8e-02 8.9e-03]
- [ 3.5e-02 -1.2e-02 8.0e-06]
- [-2.5e-02 -4.9e-03 -2.6e-03]
- [ 2.9e-02 1.7e-02 3.0e-03]
- [ 3.3e-02 1.3e-02 2.6e-03]
- [-1.9e-02 -1.0e-03 2.6e-03]
- [ 3.1e-02 1.6e-02 1.2e-02]
- [ 1.5e-02 -1.6e-02 -2.4e-03]
- [-2.8e-02 -2.6e-02 -1.9e-03]
- [-2.9e-02 2.1e-02 5.3e-03]
- [ 3.4e-02 1.7e-02 -9.0e-03]
- [ 2.8e-02 1.6e-02 -1.1e-02]
- [-1.7e-02 1.3e-02 2.1e-03]
- [ 8.7e-03 -8.7e-03 -4.0e-06]
- [ 9.0e-04 -6.1e-03 -4.0e-06]
- [-1.0e-02 -3.2e-02 -1.3e-02]
- [ 3.1e-04 1.4e-02 5.1e-03]
- [ 2.4e-02 2.8e-03 -4.0e-03]
- [ 5.7e-03 9.3e-03 -2.6e-03]
- [-2.8e-02 2.2e-02 5.8e-03]
- [-2.4e-02 2.6e-02 -2.3e-03]
- [ 2.4e-02 1.7e-03 -2.6e-03]]
+ [-3.1e-02 1.9e-02 7.4e-03]
+ [-2.6e-03 -1.3e-02 2.6e-03]
+ [ 4.5e-03 -1.3e-02 -4.0e-06]
+ [-2.4e-02 2.1e-02 -2.6e-03]
+ [-1.3e-02 6.1e-03 -1.0e-06]
+ [-2.2e-02 -2.5e-03 -4.3e-03]
+ [-1.2e-02 -1.2e-02 -1.5e-03]
+ [-1.6e-02 -9.5e-03 -1.5e-03]
+ [ 2.9e-03 -1.1e-02 -2.6e-03]
+ [-2.5e-02 -2.9e-02 -2.6e-03]
+ [ 7.6e-03 -4.4e-03 -2.6e-03]
+ [ 3.0e-02 1.0e-02 4.3e-03]
+ [-2.5e-02 -2.5e-02 -1.5e-03]
+ [ 2.2e-02 -1.3e-02 -1.5e-03]
+ [ 1.6e-02 -1.7e-02 2.0e-06]
+ [-1.4e-02 8.5e-03 -4.0e-03]
+ [ 3.5e-02 1.1e-02 -8.5e-04]
+ [ 2.7e-02 1.9e-02 9.0e-03]
+ [-2.2e-02 -2.8e-02 -1.9e-03]
+ [-9.1e-03 9.4e-03 -1.0e-06]
+ [-1.3e-02 -3.5e-02 9.0e-03]
+ [-2.0e-02 -3.0e-02 9.5e-06]
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+ [-2.2e-02 3.3e-02 -3.0e-06]
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+ [-1.0e-02 -3.6e-02 9.0e-03]
+ [-2.7e-02 2.4e-02 -8.8e-03]
+ [ 3.6e-02 7.5e-03 -1.5e-03]
+ [-3.2e-02 2.2e-02 7.4e-03]
+ [-2.3e-02 -5.0e-03 -2.7e-03]
+ [-3.1e-02 -5.9e-03 2.6e-03]
+ [-1.4e-02 -2.7e-02 -3.0e-03]
+ [ 1.0e-03 1.1e-02 -6.0e-06]
+ [ 5.6e-03 -8.3e-03 -1.5e-03]
+ [-1.8e-02 3.2e-02 -3.0e-03]
+ [-2.5e-02 -3.0e-02 -1.5e-03]
+ [ 7.7e-05 2.1e-02 1.5e-03]
+ [-2.1e-02 2.1e-02 -1.5e-03]
+ [-2.9e-02 -3.0e-03 -3.9e-03]
+ [-1.3e-02 8.3e-03 -1.5e-03]
+ [-1.4e-02 -3.3e-02 9.0e-03]
+ [-1.6e-02 -2.9e-02 4.3e-03]
+ [ 2.4e-02 1.7e-03 2.6e-03]
+ [ 2.9e-02 1.9e-02 1.2e-02]
+ [ 3.4e-02 -1.3e-02 1.9e-03]
+ [-1.2e-02 -3.2e-02 5.9e-03]
+ [ 1.5e-02 -9.9e-04 -5.5e-06]
+ [ 1.0e-02 -1.9e-02 2.4e-03]
+ [-9.5e-03 1.1e-02 -2.4e-03]
+ [ 3.9e-03 1.9e-02 -2.6e-03]
+ [-2.2e-02 2.1e-02 -2.6e-03]
+ [-1.8e-02 1.6e-02 3.0e-03]
+ [-1.9e-02 7.1e-05 1.5e-03]
+ [-2.4e-02 -9.2e-04 -4.0e-06]
+ [ 9.7e-03 -1.8e-02 2.0e-06]
+ [ 2.4e-02 -5.3e-03 3.0e-03]
+ [-2.4e-02 1.8e-02 -2.3e-03]
+ [-9.5e-03 -2.9e-02 -7.3e-03]
+ [ 2.4e-02 -1.1e-02 2.6e-03]
+ [-1.4e-02 -9.2e-04 -4.0e-06]]
# ---
# name: test_load[ball_and_stick-mol].15
[False False False False False False False False False False False False
@@ -307,19 +307,19 @@
False False False False]
# ---
# name: test_load[ball_and_stick-mol].22
- [1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 1
- 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1
- 1 2 1 1 1 1 2 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1]
+ [1 1 1 1 1 1 1 2 2 1 1 1 1 1 2 1 1 1 2 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1
+ 1 1 2 1 2 1 1 1 1 1 1 1 1 2 1 2 1 1 2 1 2 1 1 1 2 1]
# ---
# name: test_load[ball_and_stick-mol].23
- [ 1.0 14.0 12.0 14.0 14.0 16.0 6.5 1.0 1.0 12.0 12.0 14.0 13.0 14.0
- 12.0 6.5 12.0 1.0 1.0 1.0 12.0 1.0 1.0 1.0 1.0 14.0 1.0 1.0
- 14.0 12.0 14.0 13.0 12.0 12.0 16.0 12.0 6.5 1.0 1.0 14.0 14.0 14.0
- 1.0 1.0 1.0 12.0 12.0 12.0 1.0 1.0 1.0 1.0 12.0 14.0 1.0 12.0
- 16.0 1.0 12.0 14.0 12.0 1.0 12.0 14.0 12.0 1.0 1.0 6.5 12.0 1.0
- 14.0 14.0 12.0 12.0 12.0 16.0 1.0 1.0 1.0 1.0 14.0 6.5 12.0 12.0
- 1.0 14.0 1.0 1.0 1.0 1.0 14.0 12.0 12.0 1.0 12.0 14.0 12.0 1.0
- 12.0 14.0]
+ [12.0 13.0 1.0 14.0 1.0 6.5 12.0 16.0 16.0 12.0 12.0 13.0 1.0 12.0
+ 12.0 1.0 1.0 1.0 16.0 12.0 1.0 6.5 12.0 12.0 6.5 1.0 1.0 13.0
+ 12.0 12.0 14.0 12.0 14.0 13.0 12.0 1.0 12.0 12.0 1.0 12.0 14.0 14.0
+ 12.0 1.0 1.0 14.0 1.0 6.5 1.0 12.0 1.0 12.0 12.0 12.0 14.0 12.0
+ 1.0 14.0 14.0 13.0 6.5 12.0 12.0 14.0 1.0 1.0 1.0 6.5 1.0 12.0
+ 16.0 12.0 12.0 12.0 1.0 1.0 14.0 12.0 16.0 14.0 1.0 12.0 14.0 1.0
+ 1.0 1.0 13.0 14.0 14.0 14.0 12.0 13.0 12.0 12.0 14.0 13.0 12.0 1.0
+ 12.0 12.0]
# ---
# name: test_load[ball_and_stick-mol].3
[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
@@ -348,9 +348,9 @@
-1 -1 -1 -1]
# ---
# name: test_load[ball_and_stick-mol].7
- [1 7 6 7 7 8 4 1 1 6 6 7 7 7 6 4 6 1 1 1 6 1 1 1 1 7 1 1 7 6 7 7 6 6 8 6 4
- 1 1 7 7 7 1 1 1 6 6 6 1 1 1 1 6 7 1 6 8 1 6 7 6 1 6 7 6 1 1 4 6 1 7 7 6 6
- 6 8 1 1 1 1 7 4 6 6 1 7 1 1 1 1 7 6 6 1 6 7 6 1 6 7]
+ [6 7 1 7 1 4 6 8 8 6 6 7 1 6 6 1 1 1 8 6 1 4 6 6 4 1 1 7 6 6 7 6 7 7 6 1 6
+ 6 1 6 7 7 6 1 1 7 1 4 1 6 1 6 6 6 7 6 1 7 7 7 4 6 6 7 1 1 1 4 1 6 8 6 6 6
+ 1 1 7 6 8 7 1 6 7 1 1 1 7 7 7 7 6 7 6 6 7 7 6 1 6 6]
# ---
# name: test_load[ball_and_stick-mol].8
[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
@@ -380,89 +380,91 @@
AttributeError("The selected attribute 'sec_struct' does not exist on the mesh.")
# ---
# name: test_load[ball_and_stick-sdf].13
- [[1.0 1.0 1.0 1.0]
- [1.0 1.0 1.0 1.0]
+ [[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
+ [0.2 0.2 0.8 1.0]
[0.4 0.4 0.8 1.0]
- [0.8 0.2 0.2 1.0]
[1.0 1.0 1.0 1.0]
- [0.2 0.2 0.8 1.0]
[0.4 0.4 0.8 1.0]
[0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.2 0.2 0.8 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
- [0.8 0.2 0.2 1.0]
- [1.0 1.0 1.0 1.0]
- [1.0 1.0 1.0 1.0]
+ [0.4 0.4 0.8 1.0]
[0.8 0.2 0.2 1.0]
[0.2 0.2 0.8 1.0]
- [1.0 1.0 1.0 1.0]
- [0.2 0.2 0.8 1.0]
- [0.2 0.2 0.8 1.0]
- [0.8 0.2 0.2 1.0]
- [1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
- [1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
+ [0.2 0.2 0.8 1.0]
[0.4 0.4 0.8 1.0]
[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
+ [0.2 0.2 0.8 1.0]
+ [0.2 0.2 0.8 1.0]
[0.4 0.4 0.8 1.0]
[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
- [0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
- [0.2 0.2 0.8 1.0]
[1.0 1.0 1.0 1.0]
+ [0.2 0.2 0.8 1.0]
+ [0.2 0.2 0.8 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
+ [1.0 1.0 1.0 1.0]
+ [1.0 1.0 1.0 1.0]
+ [0.2 0.2 0.8 1.0]
[0.2 0.2 0.8 1.0]
[1.0 1.0 1.0 1.0]
[0.8 0.2 0.2 1.0]
[1.0 1.0 1.0 1.0]
+ [0.2 0.2 0.8 1.0]
[0.4 0.4 0.8 1.0]
- [1.0 1.0 1.0 1.0]
[0.2 0.2 0.8 1.0]
[0.4 0.4 0.8 1.0]
- [1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
- [1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
- [1.0 1.0 1.0 1.0]
[0.2 0.2 0.8 1.0]
- [1.0 1.0 1.0 1.0]
- [0.4 0.4 0.8 1.0]
- [1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
+ [0.2 0.2 0.8 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
- [0.8 0.2 0.2 1.0]
- [0.8 0.2 0.2 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.2 0.2 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
+ [0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
+ [0.2 0.2 0.8 1.0]
[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
+ [0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
- [0.4 0.4 0.8 1.0]
- [0.8 0.2 0.2 1.0]
+ [0.2 0.2 0.8 1.0]
[1.0 1.0 1.0 1.0]
- [0.8 0.2 0.2 1.0]
[0.2 0.2 0.8 1.0]
[1.0 1.0 1.0 1.0]
+ [1.0 1.0 1.0 1.0]
+ [1.0 1.0 1.0 1.0]
+ [1.0 1.0 1.0 1.0]
+ [1.0 1.0 1.0 1.0]
+ [0.4 0.4 0.8 1.0]
[0.4 0.4 0.8 1.0]
- [0.2 0.2 0.8 1.0]
- [0.8 0.2 0.2 1.0]
[1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
[0.4 0.4 0.8 1.0]
@@ -472,116 +474,114 @@
[0.4 0.4 0.8 1.0]
[1.0 1.0 1.0 1.0]
[1.0 1.0 1.0 1.0]
- [0.2 0.2 0.8 1.0]
- [0.2 0.2 0.8 1.0]
- [1.0 1.0 1.0 1.0]
[0.4 0.4 0.8 1.0]
- [0.8 0.2 0.2 1.0]
- [0.8 0.2 0.2 1.0]
[0.4 0.4 0.8 1.0]
+ [1.0 1.0 1.0 1.0]
+ [0.2 0.2 0.8 1.0]
+ [0.2 0.2 0.8 1.0]
[1.0 1.0 1.0 1.0]]
# ---
# name: test_load[ball_and_stick-sdf].14
- [[ 1.2e-02 -2.5e-02 -6.9e-03]
- [ 2.7e-02 1.4e-02 -1.4e-04]
- [-6.2e-03 3.4e-02 4.6e-03]
- [ 1.6e-02 1.8e-02 -2.3e-03]
- [ 1.6e-03 -2.6e-03 2.0e-05]
- [-3.2e-03 1.4e-02 9.8e-05]
- [ 4.2e-02 1.8e-02 -5.6e-04]
- [-2.6e-02 1.8e-02 1.1e-02]
- [ 1.3e-02 -2.6e-02 -7.4e-03]
- [-2.6e-03 4.0e-02 2.5e-03]
- [-1.4e-02 -4.1e-03 -2.3e-03]
- [ 2.7e-02 1.6e-02 2.3e-03]
- [-6.2e-03 1.8e-02 -2.5e-03]
- [ 1.2e-02 1.6e-02 2.0e-05]
- [-2.1e-02 2.4e-02 -2.1e-03]
- [-2.6e-02 1.8e-02 5.4e-03]
- [ 3.6e-02 2.3e-02 -4.6e-03]
- [ 4.7e-02 1.4e-02 -5.5e-03]
+ [[ 3.5e-02 2.0e-02 -2.5e-03]
+ [-6.5e-03 -9.6e-04 1.6e-03]
+ [ 1.2e-02 -2.2e-02 -1.1e-02]
+ [-1.2e-02 2.2e-02 4.1e-03]
+ [-2.9e-02 8.9e-03 -5.0e-03]
+ [ 4.1e-02 2.0e-02 4.4e-03]
+ [-4.1e-03 4.1e-02 2.3e-04]
+ [-1.3e-03 -4.2e-03 2.7e-03]
+ [-1.7e-04 1.4e-02 -5.0e-03]
+ [-1.2e-02 -2.5e-03 -1.9e-03]
+ [ 2.1e-02 4.3e-04 -1.7e-03]
+ [ 1.6e-02 1.5e-02 -1.6e-03]
+ [-3.1e-02 2.8e-02 -1.8e-03]
+ [ 3.4e-02 2.3e-02 2.9e-04]
+ [ 1.4e-02 -2.1e-02 -2.8e-03]
+ [ 1.9e-02 -2.3e-02 6.4e-03]
[ 4.4e-02 1.1e-02 -5.5e-03]
- [-2.6e-02 2.8e-02 -4.8e-03]
- [ 3.8e-02 1.8e-02 -2.2e-04]
- [-7.8e-03 4.6e-02 2.9e-03]
- [ 3.5e-02 3.4e-02 -5.3e-03]
- [ 3.5e-02 3.0e-02 -1.7e-03]
- [-2.5e-02 1.3e-02 -8.0e-03]
+ [ 4.0e-02 2.6e-02 9.5e-03]
+ [-1.4e-03 -4.4e-03 -2.3e-03]
+ [-2.5e-02 1.9e-02 -4.1e-03]
+ [-2.8e-02 1.5e-02 -3.1e-03]
+ [ 3.7e-02 2.7e-02 -4.6e-04]
+ [ 3.4e-02 1.7e-02 -2.2e-04]
+ [ 1.5e-02 -1.4e-02 -1.7e-04]
+ [-5.3e-03 4.1e-02 2.9e-03]
+ [-1.2e-02 4.3e-02 1.9e-03]
+ [-3.0e-02 2.8e-02 -7.1e-03]
+ [-4.1e-03 2.0e-02 2.7e-03]
+ [-8.1e-03 2.6e-02 1.9e-04]
+ [ 3.6e-02 2.2e-02 -2.8e-03]
+ [ 2.4e-02 9.2e-03 -1.4e-04]
+ [ 3.4e-02 2.1e-02 -4.6e-03]
+ [-1.3e-03 2.2e-03 -1.5e-03]
+ [ 7.2e-03 -9.6e-04 -1.6e-03]
+ [-4.3e-03 3.4e-02 -2.4e-03]
+ [ 3.4e-02 2.9e-02 -7.6e-03]
+ [ 1.4e-02 -1.4e-02 -2.8e-03]
+ [-6.2e-03 3.4e-02 4.6e-03]
+ [ 3.8e-02 3.0e-02 -6.6e-03]
+ [ 1.1e-02 3.5e-02 -1.4e-03]
+ [ 9.3e-03 3.7e-02 1.2e-04]
+ [ 2.3e-02 1.2e-02 -4.1e-03]
+ [ 1.0e-02 -1.9e-02 -1.5e-03]
+ [-1.3e-02 4.6e-02 3.0e-04]
+ [ 3.8e-02 3.0e-02 -7.2e-03]
+ [ 2.8e-02 1.2e-02 -1.4e-04]
+ [ 1.0e-02 -2.8e-02 -1.1e-02]
+ [ 3.3e-02 2.5e-02 -2.8e-03]
+ [ 4.0e-03 -2.3e-02 8.1e-03]
+ [-7.7e-03 3.8e-02 2.5e-03]
+ [-3.2e-02 2.2e-02 1.1e-02]
+ [ 3.3e-02 -8.0e-03 1.1e-03]
+ [ 4.0e-02 1.7e-02 -2.2e-04]
+ [-4.4e-03 3.3e-02 1.7e-03]
+ [-9.9e-03 2.2e-02 -2.4e-03]
+ [ 3.9e-02 2.2e-02 1.1e-03]
+ [ 3.7e-02 2.4e-02 1.2e-02]
+ [ 2.4e-02 1.8e-02 -1.4e-04]
[ 1.3e-02 2.5e-02 2.3e-03]
- [ 6.0e-03 -2.7e-02 3.4e-03]
- [-2.8e-02 3.2e-02 -4.8e-03]
- [ 2.5e-02 1.1e-02 -1.4e-04]
- [ 3.7e-02 2.3e-02 4.1e-03]
- [ 6.2e-03 3.0e-02 1.2e-04]
- [ 2.9e-02 1.9e-02 2.4e-03]
- [ 9.9e-03 -7.9e-03 3.8e-03]
- [ 3.7e-02 2.1e-02 4.9e-03]
- [-3.5e-03 2.5e-03 -2.7e-03]
- [ 1.3e-02 -1.9e-02 4.1e-03]
- [-2.9e-02 2.2e-02 4.5e-03]
- [-2.7e-02 1.4e-02 -8.0e-03]
- [-5.9e-03 4.5e-02 1.9e-03]
- [-1.3e-02 2.6e-02 -2.3e-03]
- [ 9.1e-03 3.6e-02 -2.5e-03]
- [ 1.3e-02 2.4e-02 2.0e-05]
- [ 1.3e-02 -2.3e-02 -7.4e-03]
- [-2.8e-02 1.8e-02 1.1e-02]
- [-2.5e-02 2.0e-02 1.2e-02]
- [ 1.5e-02 -4.1e-03 2.3e-03]
- [-2.5e-02 2.1e-02 -4.9e-03]
+ [ 1.9e-02 2.0e-02 -1.6e-03]
+ [-2.5e-02 2.7e-02 -2.3e-03]
+ [ 3.5e-02 1.7e-02 2.5e-03]
+ [ 1.3e-02 -2.2e-02 -2.9e-03]
+ [ 2.2e-02 1.4e-02 2.5e-03]
+ [-3.0e-02 3.1e-02 -2.2e-03]
+ [ 1.2e-02 -2.8e-02 -1.1e-02]
+ [-2.5e-02 1.5e-02 -5.0e-03]
+ [ 1.6e-02 -2.6e-02 9.8e-04]
+ [-2.8e-02 2.9e-02 -7.1e-03]
+ [ 3.3e-02 1.8e-02 -2.9e-03]
+ [ 5.9e-04 1.3e-02 2.7e-03]
+ [-1.0e-02 -6.4e-03 -2.9e-03]
[-2.5e-02 2.4e-02 2.3e-04]
- [ 4.1e-02 2.4e-02 7.0e-03]
- [ 1.5e-02 -2.5e-02 -1.2e-02]
- [-7.0e-03 4.8e-02 3.0e-04]
- [-2.5e-02 1.1e-02 -8.0e-03]
- [-2.6e-02 2.5e-02 2.9e-03]
- [ 7.6e-04 1.3e-03 2.6e-03]
- [-1.2e-02 4.3e-02 1.9e-03]
- [ 1.4e-02 -6.5e-03 3.8e-03]
- [ 1.4e-03 4.3e-03 2.3e-03]
- [ 1.8e-02 -2.6e-02 4.8e-03]
- [ 1.7e-02 -2.1e-02 2.1e-03]
- [ 2.7e-02 1.6e-02 -2.2e-03]
- [ 7.5e-03 -5.0e-03 -1.3e-04]
- [ 2.1e-02 -2.5e-02 1.2e-03]
- [ 1.4e-02 -1.4e-02 2.4e-03]
- [ 2.2e-02 1.6e-02 -1.4e-04]
- [-2.8e-02 2.5e-02 2.3e-04]
- [-2.7e-02 2.9e-02 -6.7e-03]
- [ 4.0e-02 2.1e-02 1.3e-02]
- [-2.4e-02 2.3e-02 6.2e-03]
- [ 1.0e-02 -6.5e-03 2.5e-03]
- [ 2.0e-02 -2.6e-02 7.9e-03]
- [ 1.3e-02 1.7e-02 -2.7e-03]
- [ 2.5e-02 1.8e-02 -2.6e-03]
- [-2.2e-02 2.3e-02 1.1e-03]
- [-1.2e-02 -1.0e-02 2.5e-03]
- [-5.4e-04 3.8e-02 2.9e-03]
- [ 1.2e-03 9.7e-03 2.4e-03]
- [ 4.1e-02 2.0e-02 1.0e-02]
- [ 1.9e-02 -2.5e-02 1.8e-03]
- [-3.2e-02 2.8e-02 -4.8e-03]
- [ 4.0e-02 2.6e-02 1.0e-02]
- [ 6.6e-03 1.6e-02 -2.5e-03]
- [-7.9e-03 4.0e-02 -2.3e-03]
- [ 1.2e-02 -1.9e-02 2.1e-03]
- [ 1.1e-02 2.2e-02 2.6e-03]
- [-8.5e-03 4.3e-02 3.4e-03]
- [ 1.0e-02 3.8e-02 -2.3e-03]
- [ 3.3e-02 3.2e-02 -7.2e-03]
- [-3.0e-02 2.9e-02 -8.4e-03]
- [ 6.8e-03 -2.6e-02 5.0e-03]
- [ 9.0e-04 -2.7e-02 3.1e-03]
- [ 2.0e-02 1.6e-02 1.9e-03]
- [-6.1e-03 -4.9e-03 9.0e-05]
- [-1.3e-02 -2.7e-03 9.0e-05]
- [ 4.4e-02 1.5e-02 -9.1e-03]
- [ 2.3e-02 3.7e-04 4.9e-03]
- [-8.2e-03 2.5e-02 -3.8e-03]
- [ 2.8e-02 -4.0e-03 -2.9e-03]
- [-2.8e-02 3.0e-02 -7.9e-03]
- [-2.6e-02 2.6e-02 -2.1e-03]
- [ 1.0e-02 2.1e-02 -2.6e-03]]
+ [-3.7e-03 3.8e-02 -1.3e-03]
+ [-3.1e-02 2.0e-02 9.5e-03]
+ [ 3.3e-02 2.9e-02 -6.6e-03]
+ [-2.7e-03 7.0e-03 1.6e-03]
+ [-2.3e-02 2.2e-02 -2.1e-03]
+ [ 2.2e-03 1.5e-03 -4.3e-03]
+ [-1.1e-02 2.6e-02 -1.3e-03]
+ [ 8.7e-03 -2.6e-02 -1.1e-02]
+ [ 3.2e-02 -7.2e-03 3.5e-03]
+ [ 1.0e-02 2.1e-02 2.6e-03]
+ [-1.1e-02 4.6e-02 3.4e-03]
+ [ 3.9e-02 2.6e-02 1.2e-02]
+ [ 1.0e-02 -2.5e-02 -1.4e-02]
+ [ 1.9e-02 2.0e-02 -5.8e-05]
+ [ 5.0e-03 3.4e-02 2.6e-03]
+ [ 2.8e-02 1.4e-02 -2.6e-03]
+ [ 1.4e-03 7.1e-03 -2.5e-03]
+ [-2.7e-02 2.2e-02 -6.3e-04]
+ [ 3.0e-02 1.7e-02 2.8e-03]
+ [ 1.1e-02 2.3e-02 1.5e-03]
+ [ 3.2e-02 2.2e-02 -2.2e-04]
+ [ 4.5e-03 3.5e-02 1.2e-04]
+ [ 1.0e-02 2.7e-02 3.1e-03]
+ [-2.6e-02 1.7e-02 -2.1e-03]
+ [ 4.5e-02 1.8e-02 -3.9e-03]
+ [ 2.3e-02 1.7e-03 2.4e-03]
+ [ 4.1e-02 2.2e-02 -2.2e-04]]
# ---
# name: test_load[ball_and_stick-sdf].15
[False False False False False False False False False False False False
@@ -668,18 +668,18 @@
False False False False]
# ---
# name: test_load[ball_and_stick-sdf].22
- [1 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1
- 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2
- 1 1 1 1 1 1 2 1 1 2 1 2 1 1 1 1 1 2 2 1 1 1 2 1 1 1]
+ [1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1
+ 1 1 1 2 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 2
+ 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 1 2 1 2 1 1 1 1 1]
# ---
# name: test_load[ball_and_stick-sdf].23
- [ 1.0 14.0 12.0 12.0 12.0 12.0 6.5 1.0 1.0 12.0 16.0 14.0 13.0 12.0
- 12.0 6.5 12.0 1.0 1.0 1.0 12.0 1.0 1.0 1.0 1.0 12.0 1.0 1.0
- 14.0 12.0 14.0 13.0 14.0 12.0 12.0 12.0 6.5 1.0 1.0 14.0 14.0 12.0
- 1.0 1.0 1.0 14.0 12.0 12.0 1.0 1.0 1.0 1.0 12.0 12.0 1.0 14.0
- 12.0 1.0 12.0 14.0 14.0 1.0 13.0 14.0 12.0 1.0 1.0 6.5 14.0 1.0
- 12.0 14.0 12.0 16.0 12.0 12.0 1.0 1.0 1.0 1.0 12.0 6.5 12.0 12.0
- 1.0 14.0 1.0 1.0 1.0 1.0 14.0 16.0 16.0 1.0 12.0 14.0 14.0 1.0
+ [12.0 14.0 1.0 14.0 1.0 6.5 12.0 12.0 12.0 16.0 12.0 13.0 1.0 12.0
+ 12.0 1.0 1.0 1.0 12.0 12.0 1.0 6.5 12.0 13.0 6.5 1.0 1.0 13.0
+ 14.0 12.0 14.0 12.0 12.0 13.0 12.0 1.0 13.0 12.0 1.0 14.0 14.0 14.0
+ 12.0 1.0 1.0 14.0 1.0 6.5 1.0 12.0 1.0 16.0 12.0 12.0 14.0 12.0
+ 1.0 14.0 12.0 13.0 6.5 12.0 12.0 14.0 1.0 1.0 1.0 6.5 1.0 12.0
+ 12.0 16.0 12.0 12.0 1.0 1.0 12.0 12.0 12.0 14.0 1.0 16.0 12.0 1.0
+ 1.0 1.0 13.0 14.0 14.0 12.0 12.0 13.0 12.0 12.0 14.0 13.0 12.0 1.0
12.0 12.0]
# ---
# name: test_load[ball_and_stick-sdf].3
@@ -709,9 +709,9 @@
-1 -1 -1 -1]
# ---
# name: test_load[ball_and_stick-sdf].7
- [1 7 6 6 6 6 4 1 1 6 8 7 7 6 6 4 6 1 1 1 6 1 1 1 1 6 1 1 7 6 7 7 7 6 6 6 4
- 1 1 7 7 6 1 1 1 7 6 6 1 1 1 1 6 6 1 7 6 1 6 7 7 1 7 7 6 1 1 4 7 1 6 7 6 8
- 6 6 1 1 1 1 6 4 6 6 1 7 1 1 1 1 7 8 8 1 6 7 7 1 6 6]
+ [6 7 1 7 1 4 6 6 6 8 6 7 1 6 6 1 1 1 6 6 1 4 6 7 4 1 1 7 7 6 7 6 6 7 6 1 7
+ 6 1 7 7 7 6 1 1 7 1 4 1 6 1 8 6 6 7 6 1 7 6 7 4 6 6 7 1 1 1 4 1 6 6 8 6 6
+ 1 1 6 6 6 7 1 8 6 1 1 1 7 7 7 6 6 7 6 6 7 7 6 1 6 6]
# ---
# name: test_load[ball_and_stick-sdf].8
[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
@@ -1704,7 +1704,9 @@
AttributeError("The selected attribute 'atomic_number' does not exist on the mesh.")
# ---
# name: test_load[surface-mol].8
- AttributeError("The selected attribute 'chain_id' does not exist on the mesh.")
+ [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
# ---
# name: test_load[surface-mol].9
AttributeError("The selected attribute 'entity_id' does not exist on the mesh.")
@@ -1974,7 +1976,9 @@
AttributeError("The selected attribute 'atomic_number' does not exist on the mesh.")
# ---
# name: test_load[surface-sdf].8
- AttributeError("The selected attribute 'chain_id' does not exist on the mesh.")
+ [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
# ---
# name: test_load[surface-sdf].9
AttributeError("The selected attribute 'entity_id' does not exist on the mesh.")
diff --git a/tests/__snapshots__/test_nodes.ambr b/tests/__snapshots__/test_nodes.ambr
index 2593742b..8982cbec 100644
--- a/tests/__snapshots__/test_nodes.ambr
+++ b/tests/__snapshots__/test_nodes.ambr
@@ -1,1993 +1,12319 @@
# serializer version: 1
-# name: test_color_chain
- [[0.8 0.8 0.4 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.7 0.8 1.0]
- [0.5 0.4 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.8 0.8 0.4 1.0]
- [0.7 0.4 0.8 1.0]
- [0.4 0.7 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.7 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.7 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.8 0.6 1.0]
- [0.5 0.4 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.8 0.8 0.4 1.0]
- [0.5 0.4 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.7 0.8 1.0]
- [0.7 0.4 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.7 0.8 1.0]
- [0.4 0.7 0.8 1.0]
- [0.4 0.7 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.8 0.8 0.4 1.0]
- [0.8 0.8 0.4 1.0]
- [0.5 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.8 0.8 0.4 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.7 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.5 0.4 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.7 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.8 0.8 0.4 1.0]
- [0.5 0.4 0.8 1.0]
- [0.4 0.7 0.8 1.0]
- [0.4 0.7 0.8 1.0]
- [0.5 0.4 0.8 1.0]
- [0.5 0.4 0.8 1.0]
- [0.4 0.8 0.6 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.7 0.8 1.0]
- [0.4 0.7 0.8 1.0]
- [0.7 0.4 0.8 1.0]
- [0.4 0.7 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.5 0.4 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.7 0.4 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.8 0.8 0.4 1.0]
- [0.8 0.8 0.4 1.0]
- [0.5 0.4 0.8 1.0]
- [0.5 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.7 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.7 0.8 1.0]
- [0.7 0.4 0.8 1.0]
- [0.4 0.7 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.7 0.8 1.0]
- [0.4 0.8 0.6 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.7 0.8 1.0]
- [0.4 0.7 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.8 0.8 0.4 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.7 0.8 1.0]
- [0.4 0.7 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.7 0.8 1.0]
- [0.4 0.7 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.8 0.6 1.0]
- [0.7 0.4 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.7 0.8 1.0]
- [0.5 0.4 0.8 1.0]
- [0.4 0.8 0.6 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.8 0.6 1.0]
- [0.5 0.4 0.8 1.0]
- [0.8 0.8 0.4 1.0]
- [0.4 0.7 0.8 1.0]]
-# ---
# name: test_color_custom[chain_id-1BNA]
- [[0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]]
+ [[1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]]
# ---
# name: test_color_custom[chain_id-4ozs]
- [[0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]]
+ [[0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ ...
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]]
# ---
# name: test_color_custom[chain_id-8H1B]
- [[0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.7 0.4 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.7 0.4 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.4 0.8 0.8 1.0]]
+ [[0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ ...
+ [0.2 0.3 1.0 0.0]
+ [0.7 0.8 0.4 0.0]
+ [0.7 0.4 0.9 0.0]]
# ---
# name: test_color_custom[chain_id-8U8W]
- [[0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]]
+ [[0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ ...
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]]
# ---
# name: test_color_custom[entity_id-1BNA]
- [[0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
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+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.5 0.0 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.4 0.8 0.4 0.0]
+ [1.0 0.1 0.1 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.2 0.3 1.0 0.0]
+ [0.4 0.8 0.4 0.0]]
# ---
# name: test_color_custom[entity_id-4ozs]
- [[0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]
- [0.4 0.8 0.6 1.0]]
+ [[0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ ...
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]]
# ---
# name: test_color_custom[entity_id-8H1B]
- [[0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.4 0.8 0.8 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]
- [0.8 0.4 0.7 1.0]]
+ [[0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ ...
+ [0.2 0.3 1.0 0.0]
+ [0.7 0.8 0.4 0.0]
+ [0.7 0.4 0.9 0.0]]
# ---
# name: test_color_custom[entity_id-8U8W]
- [[0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]
- [0.8 0.4 0.6 1.0]]
-# ---
-# name: test_color_entity
- [[0.7 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.5 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.5 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.5 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.5 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.5 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.5 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.5 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.5 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.5 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.5 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.5 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.5 0.8 0.4 1.0]
- [0.4 0.5 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.5 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.5 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.5 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.5 0.8 0.4 1.0]
- [0.4 0.5 0.8 1.0]
- [0.4 0.5 0.8 1.0]
- [0.5 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.5 0.8 0.4 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.5 0.8 1.0]
- [0.4 0.5 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.5 0.8 0.4 1.0]
- [0.4 0.5 0.8 1.0]
- [0.4 0.5 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.4 0.8 1.0]
- [0.4 0.4 0.8 1.0]
- [0.7 0.8 0.4 1.0]
- [0.4 0.5 0.8 1.0]]
-# ---
-# name: test_compute_backbone
- [[-0.0 -0.1 0.0]
- [-0.0 -0.1 0.0]
- [-0.0 -0.1 0.0]
- [-0.0 -0.1 0.0]
- [-0.0 -0.1 0.0]
- [-0.0 -0.1 0.0]
- [-0.0 -0.1 0.0]
- [ 0.0 -0.0 0.0]
- [ 0.0 -0.0 0.0]
- [ 0.0 -0.0 0.0]
- [ 0.0 -0.0 0.0]
- [ 0.0 -0.0 0.0]
- [ 0.0 -0.0 0.0]
- [ 0.0 -0.0 0.0]
- [-0.0 -0.0 -0.0]
- [-0.0 -0.0 -0.0]
- [-0.0 -0.0 -0.0]
- [-0.0 -0.0 -0.0]
- [-0.0 -0.0 -0.0]
- [-0.0 -0.0 -0.0]
- [ 0.0 -0.0 -0.0]
- [ 0.0 -0.0 -0.0]
- [ 0.0 -0.0 -0.0]
- [ 0.0 -0.0 -0.0]
- [ 0.0 -0.0 -0.0]
- [ 0.0 -0.0 -0.0]
- [ 0.1 -0.0 -0.1]
- [ 0.1 -0.0 -0.1]
- [ 0.1 -0.0 -0.1]
- [ 0.1 -0.0 -0.1]
- [ 0.1 -0.0 -0.1]
- [ 0.1 -0.0 -0.1]
- [ 0.1 -0.0 -0.1]
- [ 0.1 -0.0 -0.0]
- [ 0.1 -0.0 -0.0]
- [ 0.1 -0.0 -0.0]
- [ 0.1 -0.0 -0.0]
- [ 0.1 -0.0 -0.0]
- [ 0.1 -0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.1 0.0 -0.0]
- [ 0.0 0.0 -0.0]
- [ 0.0 0.0 -0.0]
- [ 0.0 0.0 -0.0]
- [ 0.0 0.0 -0.0]
- [ 0.0 0.0 -0.0]
- [ 0.0 0.0 0.0]
- [ 0.0 0.0 0.0]
- [ 0.0 0.0 0.0]
- [ 0.0 0.0 0.0]
- [ 0.0 0.0 0.0]
- [ 0.0 0.0 0.0]
- [ 0.0 0.0 0.0]
- [ 0.0 0.0 0.0]
- [ 0.0 0.0 0.0]
- [ 0.0 0.0 0.0]
- [ 0.0 0.0 0.0]
- [ 0.1 0.1 0.0]
- [ 0.1 0.1 0.0]
- [ 0.1 0.1 0.0]
- [ 0.1 0.1 0.0]
- [ 0.1 0.1 0.0]
- [ 0.1 0.1 0.0]
- [ 0.0 0.1 -0.0]
- [ 0.0 0.1 -0.0]
- [ 0.0 0.1 -0.0]
- [ 0.0 0.1 -0.0]
- [ 0.0 0.1 -0.0]
- [ 0.0 0.1 -0.0]
- [ 0.0 0.1 -0.0]
- [ 0.0 0.1 -0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [ 0.0 0.1 0.0]
- [-0.0 0.1 0.0]
- [-0.0 0.1 0.0]
- [-0.0 0.1 0.0]
- [-0.0 0.1 0.0]
- [-0.0 0.1 0.0]
- [-0.0 0.1 0.0]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [ 0.0 0.1 0.1]
- [-0.0 0.1 0.1]
- [-0.0 0.1 0.1]
- [-0.0 0.1 0.1]
- [-0.0 0.1 0.1]
- [-0.0 0.1 0.1]
- [-0.0 0.1 0.1]
- [-0.0 0.1 0.1]
- [-0.0 0.1 0.1]
- [-0.0 0.1 0.1]
- [-0.0 0.1 0.1]
- [-0.0 0.1 0.1]
- [-0.1 0.1 0.1]
- [-0.1 0.1 0.1]
- [-0.1 0.1 0.1]
- [-0.1 0.1 0.1]
- [-0.1 0.1 0.1]
- [-0.1 0.1 0.1]
- [-0.1 0.1 0.1]
- [-0.1 0.1 0.0]
- [-0.1 0.1 0.0]
- [-0.1 0.1 0.0]
- [-0.1 0.1 0.0]
- [-0.1 0.1 0.0]
- [-0.1 0.1 0.0]
- [-0.1 0.1 0.0]
- [-0.1 0.0 0.0]
- [-0.1 0.0 0.0]
- [-0.1 0.0 0.0]
- [-0.1 0.0 0.0]
- [-0.1 0.0 0.0]
- [-0.1 0.0 0.0]
- [-0.1 0.0 0.0]
- [-0.1 0.0 0.0]
- [-0.1 0.0 0.0]
- [-0.1 0.0 -0.0]
- [-0.1 0.0 -0.0]
- [-0.1 0.0 -0.0]
- [-0.1 0.0 -0.0]
- [-0.1 0.0 -0.0]
- [-0.0 0.1 -0.0]
- [-0.0 0.1 -0.0]
- [-0.0 0.1 -0.0]
- [-0.0 0.1 -0.0]
- [-0.0 0.1 -0.0]
- [-0.0 0.1 -0.0]
- [-0.0 0.1 -0.0]
- [-0.0 0.1 -0.0]
- [-0.0 0.0 -0.0]
- [-0.0 0.0 -0.0]
- [-0.0 0.0 -0.0]
- [-0.0 0.0 -0.0]
- [-0.0 0.0 -0.0]
- [-0.0 0.0 -0.0]
- [-0.0 0.0 -0.1]
- [-0.0 0.0 -0.1]
- [-0.0 0.0 -0.1]
- [-0.0 0.0 -0.1]
- [-0.0 0.0 -0.1]
- [-0.0 0.0 -0.1]
- [-0.0 0.0 -0.1]
- [-0.0 0.0 -0.1]
- [-0.0 0.0 -0.1]
- [-0.0 0.0 -0.1]
- [-0.0 0.0 -0.1]
- [-0.0 0.0 -0.1]
- [-0.0 0.1 -0.1]
- [-0.0 0.1 -0.1]
- [-0.0 0.1 -0.1]
- [-0.0 0.1 -0.1]
- [-0.0 0.1 -0.1]
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- [-0.0 0.1 -0.1]
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- [ 0.1 -0.1 -0.1]
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- [ 0.0 -0.1 -0.1]
- [ 0.0 -0.1 -0.1]
- [ 0.0 -0.1 -0.1]
- [ 0.0 -0.1 -0.1]
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- [ 0.0 -0.1 -0.0]
- [ 0.0 -0.1 -0.0]
- [ 0.0 -0.1 -0.0]
- [ 0.0 -0.1 -0.0]
- [ 0.0 -0.1 -0.0]
- [ 0.1 -0.1 -0.0]
- [ 0.1 -0.1 -0.0]
- [ 0.1 -0.1 -0.0]
- [ 0.1 -0.1 -0.0]
- [ 0.1 -0.1 -0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]]
-# ---
-# name: test_compute_backbone.1
- [[-0.0 -0.1 0.0]
- [-0.0 -0.1 0.0]
- [-0.0 -0.1 0.0]
- [-0.0 -0.1 0.0]
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- [ 0.0 -0.1 -0.0]
- [ 0.1 -0.1 -0.0]
- [ 0.1 -0.1 -0.0]
- [ 0.1 -0.1 -0.0]
- [ 0.1 -0.1 -0.0]
- [ 0.1 -0.1 -0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]
- [ 0.1 -0.1 0.0]]
-# ---
-# name: test_compute_backbone.2
- [[-0.0 -0.1 0.0]
- [-0.0 -0.1 0.0]
- [-0.0 -0.1 0.0]
- [-0.0 -0.1 0.0]
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- [ 0.1 -0.1 -0.0]
- [ 0.1 -0.1 -0.0]
- [ 0.1 -0.1 -0.0]]
-# ---
-# name: test_compute_backbone.3
- [[-4.1e-02 -6.9e-02 4.1e-02]
- [-4.1e-02 -6.9e-02 4.1e-02]
- [-4.1e-02 -6.9e-02 4.1e-02]
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- [-8.4e-03 -4.5e-02 -2.2e-03]
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- [ 1.7e-02 -3.7e-02 -2.4e-02]
- [ 3.2e-02 -3.3e-02 -5.6e-02]
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- [ 4.3e-02 7.5e-02 1.9e-02]
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- [ 4.3e-02 7.5e-02 1.9e-02]
- [ 4.3e-02 7.5e-02 1.9e-02]
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- [ 4.3e-02 7.5e-02 1.9e-02]
- [ 4.3e-02 7.5e-02 1.9e-02]
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- [ 1.9e-02 8.8e-02 9.2e-03]
- [ 1.9e-02 8.8e-02 9.2e-03]
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- [ 1.9e-02 8.8e-02 9.2e-03]
- [ 1.9e-02 8.8e-02 9.2e-03]
- [ 5.2e-03 7.9e-02 3.1e-02]
- [ 5.2e-03 7.9e-02 3.1e-02]
- [ 5.2e-03 7.9e-02 3.1e-02]
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- [ 5.2e-03 7.9e-02 3.1e-02]
- [ 5.2e-03 7.9e-02 3.1e-02]
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- [ 5.2e-03 7.9e-02 3.1e-02]
- [ 5.2e-03 7.9e-02 3.1e-02]
- [ 1.6e-02 9.3e-02 5.3e-02]
- [ 1.6e-02 9.3e-02 5.3e-02]
- [ 1.6e-02 9.3e-02 5.3e-02]
- [ 1.6e-02 9.3e-02 5.3e-02]
- [ 1.6e-02 9.3e-02 5.3e-02]
- [ 1.6e-02 9.3e-02 5.3e-02]
- [ 1.6e-02 9.3e-02 5.3e-02]
- [ 1.6e-02 9.3e-02 5.3e-02]
- [ 1.0e-04 1.1e-01 6.8e-02]
- [ 1.0e-04 1.1e-01 6.8e-02]
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- [-4.5e-02 5.9e-02 -7.6e-03]
- [-4.0e-02 3.2e-02 -1.8e-02]
- [-4.0e-02 3.2e-02 -1.8e-02]
- [-4.0e-02 3.2e-02 -1.8e-02]
- [-4.0e-02 3.2e-02 -1.8e-02]
- [-4.0e-02 3.2e-02 -1.8e-02]
- [-5.4e-02 3.5e-02 -4.5e-02]
- [-5.4e-02 3.5e-02 -4.5e-02]
- [-5.4e-02 3.5e-02 -4.5e-02]
- [-5.4e-02 3.5e-02 -4.5e-02]
- [-5.4e-02 3.5e-02 -4.5e-02]
- [-5.4e-02 3.5e-02 -4.5e-02]
- [-5.4e-02 3.5e-02 -4.5e-02]
- [-4.1e-02 5.8e-02 -5.5e-02]
- [-4.1e-02 5.8e-02 -5.5e-02]
- [-4.1e-02 5.8e-02 -5.5e-02]
- [-4.1e-02 5.8e-02 -5.5e-02]
- [-4.1e-02 5.8e-02 -5.5e-02]
- [-4.1e-02 5.8e-02 -5.5e-02]
- [-4.1e-02 5.8e-02 -5.5e-02]
- [-4.1e-02 5.8e-02 -5.5e-02]
- [-4.1e-02 5.8e-02 -5.5e-02]
- [-4.1e-02 5.8e-02 -5.5e-02]
- [-4.1e-02 5.8e-02 -5.5e-02]
- [-4.1e-02 5.8e-02 -5.5e-02]
- [-1.4e-02 5.1e-02 -5.6e-02]
- [-1.4e-02 5.1e-02 -5.6e-02]
- [-1.4e-02 5.1e-02 -5.6e-02]
- [-1.4e-02 5.1e-02 -5.6e-02]
- [-1.4e-02 5.1e-02 -5.6e-02]
- [-1.4e-02 5.1e-02 -5.6e-02]
- [-1.4e-02 5.1e-02 -5.6e-02]
- [-1.2e-02 2.7e-02 -7.1e-02]
- [-1.2e-02 2.7e-02 -7.1e-02]
- [-1.2e-02 2.7e-02 -7.1e-02]
- [-1.2e-02 2.7e-02 -7.1e-02]
- [-1.7e-02 1.7e-03 -5.7e-02]
- [-1.7e-02 1.7e-03 -5.7e-02]
- [-1.7e-02 1.7e-03 -5.7e-02]
- [-1.7e-02 1.7e-03 -5.7e-02]
- [-1.7e-02 1.7e-03 -5.7e-02]
- [-1.7e-02 1.7e-03 -5.7e-02]
- [-2.8e-02 -2.8e-02 -4.0e-02]
- [-2.8e-02 -2.8e-02 -4.0e-02]
- [-2.8e-02 -2.8e-02 -4.0e-02]
- [-2.8e-02 -2.8e-02 -4.0e-02]
- [-2.8e-02 -2.8e-02 -4.0e-02]
- [-2.8e-02 -2.8e-02 -4.0e-02]
- [-2.8e-02 -2.8e-02 -4.0e-02]
- [-2.8e-02 -2.8e-02 -4.0e-02]
- [-5.3e-02 -3.4e-02 -1.6e-02]
- [-5.3e-02 -3.4e-02 -1.6e-02]
- [-5.3e-02 -3.4e-02 -1.6e-02]
- [-5.3e-02 -3.4e-02 -1.6e-02]
- [-5.3e-02 -3.4e-02 -1.6e-02]
- [-5.3e-02 -3.4e-02 -1.6e-02]
- [-5.3e-02 -3.4e-02 -1.6e-02]
- [-5.3e-02 -3.4e-02 -1.6e-02]
- [-5.8e-02 -6.2e-02 1.1e-03]
- [-5.8e-02 -6.2e-02 1.1e-03]
- [-5.8e-02 -6.2e-02 1.1e-03]
- [-5.8e-02 -6.2e-02 1.1e-03]
- [-5.8e-02 -6.2e-02 1.1e-03]
- [-5.8e-02 -6.2e-02 1.1e-03]
- [-5.8e-02 -6.2e-02 1.1e-03]
- [-5.8e-02 -6.2e-02 1.1e-03]
- [-8.0e-02 -8.7e-02 1.6e-02]
- [-8.0e-02 -8.7e-02 1.6e-02]
- [-8.0e-02 -8.7e-02 1.6e-02]
- [-8.0e-02 -8.7e-02 1.6e-02]
- [-8.0e-02 -8.7e-02 1.6e-02]
- [-8.0e-02 -8.7e-02 1.6e-02]
- [-8.0e-02 -8.7e-02 1.6e-02]
- [-6.7e-02 -1.1e-01 2.5e-02]
- [-6.7e-02 -1.1e-01 2.5e-02]
- [-6.7e-02 -1.1e-01 2.5e-02]
- [-6.7e-02 -1.1e-01 2.5e-02]
- [-4.1e-02 -1.2e-01 4.7e-02]
- [-4.1e-02 -1.2e-01 4.7e-02]
- [-4.1e-02 -1.2e-01 4.7e-02]
- [-4.1e-02 -1.2e-01 4.7e-02]
- [-4.1e-02 -1.2e-01 4.7e-02]
- [-1.5e-02 -1.2e-01 4.0e-02]
- [-1.5e-02 -1.2e-01 4.0e-02]
- [-1.5e-02 -1.2e-01 4.0e-02]
- [-1.5e-02 -1.2e-01 4.0e-02]
- [-1.5e-02 -1.2e-01 4.0e-02]
- [-1.5e-02 -1.2e-01 4.0e-02]
- [-1.5e-02 -1.2e-01 4.0e-02]
- [ 6.5e-03 -1.1e-01 1.1e-02]
- [ 6.5e-03 -1.1e-01 1.1e-02]
- [ 6.5e-03 -1.1e-01 1.1e-02]
- [ 6.5e-03 -1.1e-01 1.1e-02]
- [ 6.5e-03 -1.1e-01 1.1e-02]
- [ 6.5e-03 -1.1e-01 1.1e-02]
- [ 4.6e-03 -1.1e-01 -2.5e-02]
- [ 4.6e-03 -1.1e-01 -2.5e-02]
- [ 4.6e-03 -1.1e-01 -2.5e-02]
- [ 4.6e-03 -1.1e-01 -2.5e-02]
- [ 4.6e-03 -1.1e-01 -2.5e-02]
- [ 4.6e-03 -1.1e-01 -2.5e-02]
- [ 4.6e-03 -1.1e-01 -2.5e-02]
- [ 2.9e-02 -1.3e-01 -4.7e-02]
- [ 2.9e-02 -1.3e-01 -4.7e-02]
- [ 2.9e-02 -1.3e-01 -4.7e-02]
- [ 2.9e-02 -1.3e-01 -4.7e-02]
- [ 3.7e-02 -1.1e-01 -6.7e-02]
- [ 3.7e-02 -1.1e-01 -6.7e-02]
- [ 3.7e-02 -1.1e-01 -6.7e-02]
- [ 3.7e-02 -1.1e-01 -6.7e-02]
- [ 3.7e-02 -1.1e-01 -6.7e-02]
- [ 3.7e-02 -1.1e-01 -6.7e-02]
- [ 3.7e-02 -1.1e-01 -6.7e-02]
- [ 3.7e-02 -1.1e-01 -6.7e-02]
- [ 3.1e-02 -8.6e-02 -5.7e-02]
- [ 3.1e-02 -8.6e-02 -5.7e-02]
- [ 3.1e-02 -8.6e-02 -5.7e-02]
- [ 3.1e-02 -8.6e-02 -5.7e-02]
- [ 3.1e-02 -8.6e-02 -5.7e-02]
- [ 3.1e-02 -8.6e-02 -5.7e-02]
- [ 3.1e-02 -8.6e-02 -5.7e-02]
- [ 3.1e-02 -8.6e-02 -5.7e-02]
- [ 3.1e-02 -8.6e-02 -5.7e-02]
- [ 3.1e-02 -8.6e-02 -5.7e-02]
- [ 3.1e-02 -8.6e-02 -5.7e-02]
- [ 3.1e-02 -8.6e-02 -5.7e-02]
- [ 4.5e-02 -8.1e-02 -3.5e-02]
- [ 4.5e-02 -8.1e-02 -3.5e-02]
- [ 4.5e-02 -8.1e-02 -3.5e-02]
- [ 4.5e-02 -8.1e-02 -3.5e-02]
- [ 4.5e-02 -8.1e-02 -3.5e-02]
- [ 6.2e-02 -6.3e-02 -1.1e-02]
- [ 6.2e-02 -6.3e-02 -1.1e-02]
- [ 6.2e-02 -6.3e-02 -1.1e-02]
- [ 6.2e-02 -6.3e-02 -1.1e-02]
- [ 6.2e-02 -6.3e-02 -1.1e-02]
- [ 6.2e-02 -6.3e-02 -1.1e-02]
- [ 6.2e-02 -6.3e-02 -1.1e-02]
- [ 6.2e-02 -6.3e-02 -1.1e-02]
- [ 6.2e-02 -6.3e-02 -1.1e-02]]
-# ---
-# name: test_compute_backbone.4
- [-0.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5
- -1.5 -1.9 -1.9 -1.9 -1.9 -1.9 -1.9 -1.3 -1.3 -1.3 -1.3 -1.3 -1.3 -2.1
- -2.1 -2.1 -2.1 -2.1 -2.1 -2.1 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.2 -1.2
- -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2
- -1.2 -1.2 -1.2 -1.2 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1
- -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0
- -1.0 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2
- -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -1.7
- -1.7 -1.7 -1.7 -1.7 -1.7 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0
- -1.0 -1.0 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 1.3 1.3 1.3 1.3
- 1.3 1.3 1.3 -2.4 -2.4 -2.4 -2.4 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5
- -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2
- -1.2 -1.2 -1.3 -1.3 -1.3 -1.3 -1.3 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9
- -0.9 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.1 -1.1 -1.1 -1.1 -1.1 -1.2 -1.2
- -1.2 -1.2 -1.2 -1.2 -1.2 -2.0 -2.0 -2.0 -2.0 -2.0 -2.0 -2.0 -2.0 -2.0
- -2.0 -2.0 -2.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 -2.0 -2.0 -2.0 -2.0
- -2.1 -2.1 -2.1 -2.1 -2.1 -2.1 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5
- -1.9 -1.9 -1.9 -1.9 -1.9 -1.9 -1.9 -1.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9
- -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -1.1 -1.1 -1.1 -1.1 -2.6
- -2.6 -2.6 -2.6 -2.6 -1.8 -1.8 -1.8 -1.8 -1.8 -1.8 -1.8 -0.9 -0.9 -0.9
- -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -1.6 -1.6 -1.6 -1.6
- -2.2 -2.2 -2.2 -2.2 -2.2 -2.2 -2.2 -2.2 -1.9 -1.9 -1.9 -1.9 -1.9 -1.9
- -1.9 -1.9 -1.9 -1.9 -1.9 -1.9 -2.0 -2.0 -2.0 -2.0 -2.0 0.0 0.0 0.0
- 0.0 0.0 0.0 0.0 0.0]
-# ---
-# name: test_compute_backbone.5
- [ 2.4 1.3 1.3 1.3 1.3 1.3 1.3 1.3 2.0 2.0 2.0 2.0 2.0 2.0
- 2.0 2.5 2.5 2.5 2.5 2.5 2.5 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 2.8
- 2.8 2.8 2.8 2.8 2.8 2.8 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.8 -0.8
- -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.8
- -0.8 -0.8 -0.8 -0.8 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7
- -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8
- -0.8 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.8 -0.8
- -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 0.2
- 0.2 0.2 0.2 0.2 0.2 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7
- -0.7 -0.7 -0.3 -0.3 -0.3 -0.3 -0.3 -0.3 -0.3 -0.3 0.8 0.8 0.8 0.8
- 0.8 0.8 0.8 -1.3 -1.3 -1.3 -1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3
- -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6
- -0.6 -0.6 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7
- -0.7 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.8 -0.8 -0.8 -0.8 -0.8 -0.5 -0.5
- -0.5 -0.5 -0.5 -0.5 -0.5 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2
- 0.2 0.2 0.2 0.8 0.8 0.8 0.8 0.8 0.8 0.8 2.8 2.8 2.8 2.8
- 2.0 2.0 2.0 2.0 2.0 2.0 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8
- 2.3 2.3 2.3 2.3 2.3 2.3 2.3 2.3 -0.5 -0.5 -0.5 -0.5 -0.5 -0.5
- -0.5 -0.5 2.3 2.3 2.3 2.3 2.3 2.3 2.3 -0.1 -0.1 -0.1 -0.1 2.9
- 2.9 2.9 2.9 2.9 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.6 2.6 2.6
- 2.6 2.6 2.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.1 -0.1 -0.1 -0.1
- 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 1.8 1.8 1.8 1.8 1.8 1.8
- 1.8 1.8 1.8 1.8 1.8 1.8 -1.4 -1.4 -1.4 -1.4 -1.4 0.0 0.0 0.0
- 0.0 0.0 0.0 0.0 0.0]
-# ---
-# name: test_node_topology
+ [[0.2 0.3 1.0 0.0]
+ [0.8 0.4 0.4 0.0]
+ [0.8 0.4 0.4 0.0]
+ ...
+ [1.0 0.1 0.1 0.0]
+ [0.8 0.4 0.4 0.0]
+ [1.0 0.1 0.1 0.0]]
+# ---
+# name: test_node_topology[1BNA-Chain Info]
+ [0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
+ 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
+ 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
+ 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
+ 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
+ 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1]
+# ---
+# name: test_node_topology[1BNA-Chain Info].1
+ [49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49
+ 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49
+ 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49
+ 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49
+ 49 49 49 49]
+# ---
+# name: test_node_topology[1BNA-Chain Info].2
+ [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
+ 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4]
+# ---
+# name: test_node_topology[1BNA-Chain Info].3
+ [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]
+# ---
+# name: test_node_topology[1BNA-Chain Info].4
+ [102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102
+ 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102
+ 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102
+ 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102
+ 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102
+ 102 102 102 102 102 102 102 102 102 102]
+# ---
+# name: test_node_topology[1BNA-Chain Info].5
+ [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
+# ---
+# name: test_node_topology[1BNA-Chain Info].6
+ [522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522
+ 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522
+ 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522
+ 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522
+ 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522 522
+ 522 522 522 522 522 522 522 522 522 522]
+# ---
+# name: test_node_topology[1BNA-Dihedral Phi]
+ [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0.]
+# ---
+# name: test_node_topology[1BNA-Dihedral Phi].1
+ [[0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
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+# ---
+# name: test_node_topology[1BNA-Edge Info]
+ [ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True]
+# ---
+# name: test_node_topology[1BNA-Edge Info].1
+ [ 1 0 1 2 2 16 4 3 7 8 9 9 11 12 12 8 5 16
+ 16 16 19 20 21 21 38 23 22 26 27 28 29 30 31 31 33 34
+ 34 27 24 38 38 38 41 42 43 43 57 45 44 48 49 50 50 52
+ 53 53 49 46 57 57 57 60 61 62 62 79 64 63 67 68 69 70
+ 71 72 72 74 75 75 68 65 79 79 79 82 83 84 84 100 86 85
+ 89 90 91 92 93 94 94 96 97 90]
+# ---
+# name: test_node_topology[1BNA-Edge Info].2
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+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
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+ [ 0.0e+00 0.0e+00 0.0e+00]
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+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
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+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]]
+# ---
+# name: test_node_topology[1BNA-Edge Info].3
+ [ 22 22 23 24 25 0 28 26 30 31 33 34 35 36 37 32 0 39
+ 40 41 42 43 44 45 1 48 46 50 51 53 54 55 57 58 59 60
+ 61 52 1 63 64 65 66 67 68 69 2 72 70 74 75 77 78 79
+ 80 81 76 2 83 84 85 86 87 88 89 3 92 90 94 95 97 98
+ 99 101 102 103 104 105 96 3 107 108 109 110 111 112 113 4 116 114
+ 118 119 121 122 123 125 126 127 128 120]
+# ---
+# name: test_node_topology[1BNA-Edge Info].4
+ [[ 1.9e-03 -2.7e-03 -1.4e-02]
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+ [ 6.0e-03 -1.7e-03 -1.5e-02]
+ [ 1.4e-02 4.0e-03 2.9e-04]
+ [-2.8e-03 -1.4e-02 -4.9e-03]
+ [-8.1e-03 1.1e-02 -8.2e-03]
+ [ 7.8e-04 1.4e-02 4.1e-03]
+ [-7.7e-03 7.5e-03 -1.0e-02]
+ [-1.4e-02 -3.0e-03 2.0e-03]
+ [ 3.3e-03 -4.5e-03 -1.4e-02]
+ [-5.3e-03 2.8e-03 1.5e-02]
+ [-1.4e-02 -3.7e-03 -5.9e-03]
+ [-6.3e-03 1.6e-03 -1.3e-02]
+ [-1.2e-02 -8.1e-03 1.9e-03]
+ [-1.2e-02 6.2e-03 2.0e-05]
+ [-2.6e-04 1.2e-02 -2.5e-03]
+ [-1.1e-02 -7.0e-03 2.9e-03]
+ [ 7.9e-04 -1.3e-02 3.0e-03]
+ [-1.1e-02 -6.9e-03 3.4e-03]
+ [ 1.2e-02 -6.7e-03 3.0e-05]
+ [ 1.4e-03 -1.3e-02 3.0e-03]
+ [ 5.3e-03 -2.8e-03 -1.5e-02]
+ [ 1.1e-02 9.3e-03 -3.0e-03]
+ [ 2.7e-03 -1.5e-02 -2.1e-03]
+ [-1.3e-02 4.0e-03 -8.9e-03]
+ [-4.5e-03 1.4e-02 -8.0e-04]
+ [-1.2e-02 2.0e-05 -9.0e-03]
+ [-1.1e-02 -7.0e-03 6.6e-03]
+ [ 1.5e-03 -7.1e-03 -1.3e-02]
+ [-6.1e-03 -1.0e-02 1.0e-02]
+ [-4.8e-03 -1.4e-02 3.4e-03]
+ [-5.0e-03 -9.7e-03 -9.4e-03]
+ [-6.1e-03 -1.1e-02 7.1e-03]
+ [ 5.6e-03 -1.2e-02 3.8e-03]
+ [-8.8e-03 -8.2e-03 5.9e-03]
+ [-1.2e-02 7.1e-03 -1.4e-04]
+ [-1.3e-02 -3.5e-03 4.8e-03]
+ [-3.8e-03 -1.1e-02 5.2e-03]
+ [-9.0e-03 1.0e-02 -2.1e-03]
+ [ 2.5e-03 1.2e-02 -5.8e-03]
+ [-1.0e-02 8.6e-03 -1.5e-03]
+ [ 1.2e-02 3.2e-03 -4.6e-03]
+ [-1.3e-02 -7.2e-04 3.9e-03]
+ [ 6.1e-03 1.0e-02 -1.0e-02]
+ [ 7.1e-03 1.1e-02 7.1e-03]
+ [ 8.1e-03 -7.8e-03 -9.7e-03]
+ [-1.3e-02 5.6e-03 -6.9e-03]
+ [-8.8e-03 9.0e-03 7.2e-03]
+ [-1.4e-02 -4.0e-03 -2.8e-03]
+ [-1.7e-03 -1.2e-02 7.0e-03]
+ [-3.3e-03 -3.1e-03 -1.5e-02]
+ [ 3.2e-03 1.3e-03 1.6e-02]
+ [-4.9e-03 -1.4e-02 3.4e-04]
+ [-1.0e-02 -7.0e-03 -6.8e-03]
+ [ 1.7e-03 -1.4e-02 4.0e-03]
+ [-1.1e-02 -6.6e-03 5.4e-03]
+ [-1.1e-02 6.1e-03 1.3e-03]
+ [ 1.3e-03 -1.3e-02 3.7e-03]
+ [ 1.2e-02 -6.3e-03 -1.5e-03]
+ [ 1.3e-03 -1.3e-02 3.9e-03]
+ [ 1.1e-02 6.4e-03 -5.6e-03]
+ [ 1.2e-02 -6.1e-03 -1.9e-03]
+ [-3.2e-03 -1.3e-03 -1.6e-02]
+ [-2.0e-03 1.3e-02 -5.8e-03]
+ [ 1.0e-02 -8.5e-03 -6.7e-03]
+ [-1.4e-02 -8.2e-03 -3.7e-04]
+ [-1.2e-02 5.6e-03 5.4e-03]
+ [-9.7e-03 -1.1e-02 -1.6e-04]
+ [ 4.9e-03 -9.6e-03 9.3e-03]
+ [-2.2e-04 -7.7e-03 -1.3e-02]
+ [-7.5e-03 6.5e-03 -1.0e-02]
+ [-6.6e-03 -1.3e-02 4.8e-03]
+ [-5.6e-03 -1.3e-02 -3.6e-03]
+ [ 1.1e-02 -9.7e-03 4.9e-04]
+ [ 1.3e-02 1.2e-03 -4.4e-03]
+ [ 7.4e-03 -1.1e-02 2.7e-03]
+ [-8.6e-03 -8.2e-03 6.4e-03]
+ [ 2.3e-03 -1.3e-02 5.6e-03]
+ [ 1.0e-02 -6.4e-03 5.0e-04]
+ [-1.2e-02 -5.3e-03 5.1e-03]
+ [-1.2e-02 5.9e-03 2.5e-04]
+ [-1.1e-02 -7.2e-03 4.8e-03]
+ [-1.9e-03 1.2e-02 -4.7e-03]
+ [-6.7e-04 -1.2e-02 5.7e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]]
+# ---
+# name: test_node_topology[1BNA-Edge Info].5
+ [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0.]
+# ---
+# name: test_node_topology[1BNA-Point Edge Angle]
+ [False True True True True True True True True True False True
+ True False True True True False False True True True True True
+ True True True True True True True True False True True False
+ True True True False False True True True True True True True
+ True True True False True True False True True True False False
+ True True True True True True True True True True True True
+ True False True True False True True True False False True True
+ True True True True True True True True True True True False
+ True True True True]
+# ---
+# name: test_node_topology[1BNA-Point Edge Angle].1
+ [-1.0 1.9 1.9 1.9 1.9 2.2 1.7 1.8 2.1 2.1 -1.0 2.1 2.1 -1.0
+ 2.1 2.1 1.9 -1.0 -1.0 2.1 1.8 1.9 1.9 1.9 2.2 1.8 1.8 2.2
+ 2.0 1.8 2.2 2.2 -1.0 2.2 2.1 -1.0 2.0 1.9 1.9 -1.0 -1.0 2.1
+ 1.8 1.9 1.9 1.9 2.1 1.8 1.8 2.1 2.1 -1.0 2.1 2.1 -1.0 2.1
+ 2.1 1.9 -1.0 -1.0 2.1 1.9 1.9 1.9 1.9 2.1 1.7 1.8 2.3 2.0
+ 1.8 2.3 2.2 -1.0 2.2 2.1 -1.0 2.0 1.9 1.9 -1.0 -1.0 2.1 1.8
+ 1.9 1.9 1.9 2.1 1.8 1.8 2.2 2.0 1.8 2.3 2.1 -1.0 2.1 2.3
+ 1.9 1.9]
+# ---
+# name: test_node_topology[1BNA-Point Edge Angle].2
+ [ 22 22 23 24 25 0 28 26 30 31 33 34 35 36 37 32 0 39
+ 40 41 42 43 44 45 1 48 46 50 51 53 54 55 57 58 59 60
+ 61 52 1 63 64 65 66 67 68 69 2 72 70 74 75 77 78 79
+ 80 81 76 2 83 84 85 86 87 88 89 3 92 90 94 95 97 98
+ 99 101 102 103 104 105 96 3 107 108 109 110 111 112 113 4 116 114
+ 118 119 121 122 123 125 126 127 128 120]
+# ---
+# name: test_node_topology[1BNA-Point Edge Angle].3
+ [ -1 23 24 26 27 27 29 29 31 33 -1 35 36 -1 38 38 39 -1
+ -1 42 43 44 46 47 47 49 49 51 53 54 55 57 -1 59 60 -1
+ 62 56 63 -1 -1 66 67 68 70 71 71 73 73 75 77 -1 79 80
+ -1 82 82 83 -1 -1 86 87 88 90 91 91 93 93 95 97 98 99
+ 101 -1 103 104 -1 106 100 107 -1 -1 110 111 112 114 115 115 117 117
+ 119 121 122 123 125 -1 127 128 129 124]
+# ---
+# name: test_node_topology[1BNA-Point Edge Angle].4
+ [[ 1.9e-03 -2.7e-03 -1.4e-02]
+ [-1.9e-03 2.7e-03 1.4e-02]
+ [-8.3e-03 1.3e-02 1.2e-03]
+ [ 6.0e-03 1.1e-02 -7.5e-03]
+ [-2.1e-03 5.5e-03 1.4e-02]
+ [ 1.1e-02 -3.9e-04 -1.2e-02]
+ [ 1.2e-02 9.0e-03 4.7e-04]
+ [ 1.3e-03 1.1e-02 9.1e-03]
+ [ 1.2e-02 8.2e-03 -4.4e-03]
+ [-1.5e-03 1.2e-02 -6.4e-03]
+ [-1.1e-02 4.4e-03 -2.0e-03]
+ [ 1.1e-02 6.9e-03 -3.6e-03]
+ [ 1.2e-02 -4.6e-03 2.6e-03]
+ [ 1.1e-02 7.5e-03 -3.2e-03]
+ [ 2.0e-03 -1.2e-02 6.5e-03]
+ [ 1.2e-02 -5.1e-03 2.8e-03]
+ [-1.1e-02 3.9e-04 1.2e-02]
+ [-1.1e-02 -8.7e-03 -3.7e-03]
+ [ 5.9e-03 -1.7e-03 1.3e-02]
+ [-4.3e-03 1.5e-02 -1.5e-04]
+ [-7.0e-03 5.8e-03 -1.1e-02]
+ [ 4.9e-04 1.5e-02 3.2e-03]
+ [ 1.3e-02 4.6e-03 -3.9e-03]
+ [-2.0e-03 3.8e-03 1.5e-02]
+ [ 3.4e-03 -7.0e-03 -1.4e-02]
+ [ 1.4e-02 4.4e-03 3.9e-03]
+ [ 4.7e-03 9.5e-03 9.6e-03]
+ [ 1.5e-02 -1.7e-03 -6.4e-04]
+ [ 7.1e-03 -1.1e-02 3.5e-03]
+ [ 1.3e-02 1.3e-03 -2.1e-03]
+ [ 1.2e-03 1.2e-02 -5.1e-03]
+ [ 1.2e-02 6.9e-03 -4.0e-03]
+ [ 1.2e-02 -3.9e-03 2.7e-04]
+ [-2.9e-03 1.2e-02 -4.9e-03]
+ [-1.2e-02 5.6e-03 -1.2e-03]
+ [-7.4e-04 1.3e-02 -5.1e-03]
+ [-1.1e-02 -6.4e-03 3.9e-03]
+ [ 9.5e-03 8.8e-03 -4.9e-03]
+ [-3.4e-03 7.0e-03 1.4e-02]
+ [-1.4e-02 3.0e-03 3.2e-04]
+ [ 5.0e-03 -7.9e-03 1.1e-02]
+ [ 8.0e-03 1.4e-02 -7.5e-04]
+ [-3.2e-03 9.6e-03 -1.0e-02]
+ [ 1.1e-02 1.1e-02 9.0e-04]
+ [ 1.3e-02 -6.1e-03 -2.1e-03]
+ [ 9.9e-04 6.8e-03 1.3e-02]
+ [ 1.3e-03 -9.0e-03 -1.3e-02]
+ [ 1.5e-02 1.5e-03 2.4e-03]
+ [ 9.8e-03 8.8e-03 5.4e-03]
+ [ 1.1e-02 -9.2e-03 3.9e-03]
+ [ 1.3e-02 3.0e-03 -2.9e-03]
+ [ 2.2e-03 1.1e-02 -5.7e-03]
+ [ 9.7e-03 -8.6e-03 3.1e-03]
+ [-2.8e-03 -1.2e-02 6.1e-03]
+ [ 1.0e-02 -9.0e-03 2.7e-03]
+ [-1.3e-02 -3.4e-03 3.3e-03]
+ [-3.4e-03 -1.2e-02 6.2e-03]
+ [-1.3e-03 9.0e-03 1.3e-02]
+ [-1.2e-02 8.8e-03 -1.5e-03]
+ [ 4.1e-04 -8.8e-03 1.2e-02]
+ [ 1.3e-02 8.8e-03 -5.3e-04]
+ [ 2.2e-03 9.1e-03 -1.1e-02]
+ [ 1.3e-02 6.7e-03 2.5e-03]
+ [ 1.0e-02 -9.9e-03 9.0e-05]
+ [ 1.3e-03 7.3e-03 1.3e-02]
+ [ 7.2e-04 -1.2e-02 -9.9e-03]
+ [ 4.7e-03 -1.1e-02 8.9e-03]
+ [ 6.4e-03 5.1e-04 1.3e-02]
+ [ 4.1e-03 -1.4e-02 3.5e-03]
+ [-7.1e-03 -9.8e-03 6.4e-03]
+ [ 7.0e-03 -1.1e-02 1.6e-03]
+ [ 1.2e-02 2.9e-03 -5.6e-03]
+ [ 1.2e-02 -8.0e-03 -1.1e-03]
+ [ 1.8e-03 -1.2e-02 3.8e-03]
+ [ 1.0e-02 6.9e-03 -6.0e-03]
+ [-3.9e-04 1.3e-02 -4.6e-03]
+ [ 1.1e-02 5.1e-03 -5.4e-03]
+ [-1.1e-02 7.5e-03 9.9e-04]
+ [ 1.2e-02 -5.4e-03 -2.5e-03]
+ [-7.2e-04 1.2e-02 9.9e-03]
+ [-7.6e-03 1.1e-02 -6.5e-03]
+ [-4.8e-03 -4.5e-03 1.3e-02]
+ [ 1.5e-02 3.9e-03 8.4e-04]
+ [ 8.0e-03 1.2e-04 -1.2e-02]
+ [ 1.3e-02 -5.2e-03 4.0e-03]
+ [-1.7e-03 -1.4e-02 4.0e-03]
+ [ 6.5e-03 7.0e-03 1.2e-02]
+ [-9.0e-03 -7.9e-03 -1.1e-02]
+ [ 6.7e-04 -1.1e-02 1.1e-02]
+ [ 9.9e-03 -2.8e-03 9.9e-03]
+ [-5.4e-03 -1.2e-02 7.0e-03]
+ [-1.3e-02 -1.9e-03 4.8e-03]
+ [-2.0e-03 -1.2e-02 4.7e-03]
+ [ 1.2e-02 -6.1e-03 -1.8e-03]
+ [ 4.4e-03 -1.3e-02 2.8e-03]
+ [-8.2e-03 -9.4e-03 5.5e-03]
+ [ 1.3e-02 -3.0e-03 -3.0e-03]
+ [ 7.9e-03 9.3e-03 -5.5e-03]
+ [-2.8e-03 1.3e-02 -3.2e-03]
+ [ 6.4e-03 -1.2e-02 2.1e-03]
+ [ 9.0e-03 7.9e-03 1.1e-02]
+ [ 8.4e-03 9.7e-03 -7.4e-03]
+ [-8.5e-03 5.1e-03 1.1e-02]
+ [ 9.9e-03 -1.1e-02 5.8e-03]
+ [ 1.1e-02 -4.9e-03 -8.1e-03]
+ [ 6.9e-03 -1.0e-02 8.5e-03]
+ [-1.0e-02 -8.6e-03 4.7e-03]
+ [ 6.9e-03 5.3e-03 1.2e-02]
+ [-9.3e-03 -3.2e-03 -1.3e-02]
+ [-8.2e-03 -6.2e-03 1.1e-02]
+ [ 4.5e-03 -5.1e-03 1.2e-02]
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+ [-1.2e-02 6.3e-03 2.1e-03]
+ [-9.3e-03 -8.2e-03 5.1e-03]
+ [ 6.3e-03 -1.2e-02 1.1e-03]
+ [-4.6e-03 -1.3e-02 4.3e-03]
+ [-1.3e-02 -2.3e-03 3.9e-03]
+ [ 8.7e-03 -1.0e-02 -3.7e-04]
+ [ 1.2e-02 2.3e-03 -4.2e-03]
+ [ 5.4e-03 1.1e-02 -4.3e-03]
+ [-2.0e-03 -1.3e-02 4.2e-03]
+ [ 9.3e-03 3.2e-03 1.3e-02]
+ [ 1.4e-02 9.0e-04 -4.3e-03]
+ [-5.2e-03 1.2e-02 7.8e-03]
+ [-1.6e-03 -1.3e-02 8.4e-03]
+ [ 3.3e-03 -1.2e-02 -6.1e-03]
+ [-2.5e-03 -9.9e-03 1.1e-02]
+ [-1.4e-02 4.8e-04 3.2e-03]
+ [ 7.0e-03 3.4e-03 1.3e-02]
+ [-8.7e-03 -4.4e-04 -1.3e-02]
+ [-1.1e-02 -2.4e-03 1.1e-02]
+ [-1.0e-03 -6.3e-03 1.3e-02]
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+ [-7.5e-03 6.5e-03 -1.0e-02]
+ [-6.6e-03 -1.3e-02 4.8e-03]
+ [-5.6e-03 -1.3e-02 -3.6e-03]
+ [ 1.1e-02 -9.7e-03 4.9e-04]
+ [ 1.3e-02 1.2e-03 -4.4e-03]
+ [ 7.4e-03 -1.1e-02 2.7e-03]
+ [-8.6e-03 -8.2e-03 6.4e-03]
+ [ 2.3e-03 -1.3e-02 5.6e-03]
+ [ 1.0e-02 -6.4e-03 5.0e-04]
+ [-1.2e-02 -5.3e-03 5.1e-03]
+ [-1.2e-02 5.9e-03 2.5e-04]
+ [-1.1e-02 -7.2e-03 4.8e-03]
+ [-1.9e-03 1.2e-02 -4.7e-03]
+ [-6.7e-04 -1.2e-02 5.7e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]]
+# ---
+# name: test_node_topology[1BNA-Point Edge Angle].5
+ [[ 0.0e+00 0.0e+00 0.0e+00]
+ [ 8.3e-03 -1.3e-02 -1.2e-03]
+ [-6.0e-03 -1.1e-02 7.5e-03]
+ [-1.3e-03 -1.1e-02 -9.1e-03]
+ [ 1.2e-02 -8.0e-03 -1.3e-04]
+ [-1.2e-02 8.0e-03 1.3e-04]
+ [ 2.8e-03 -7.4e-03 1.3e-02]
+ [-2.8e-03 7.4e-03 -1.3e-02]
+ [ 1.5e-03 -1.2e-02 6.4e-03]
+ [ 1.1e-02 -4.4e-03 2.0e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-1.2e-02 4.6e-03 -2.6e-03]
+ [-1.1e-02 -7.5e-03 3.2e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 1.1e-02 7.3e-03 -3.7e-03]
+ [-1.1e-02 -7.3e-03 3.7e-03]
+ [ 1.1e-02 8.7e-03 3.7e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 7.0e-03 -5.8e-03 1.1e-02]
+ [-4.9e-04 -1.5e-02 -3.2e-03]
+ [-1.3e-02 -4.6e-03 3.9e-03]
+ [-4.7e-03 -9.5e-03 -9.6e-03]
+ [ 1.0e-02 -1.0e-02 -1.5e-03]
+ [-1.0e-02 1.0e-02 1.5e-03]
+ [-5.5e-03 -5.8e-03 1.3e-02]
+ [ 5.5e-03 5.8e-03 -1.3e-02]
+ [-7.1e-03 1.1e-02 -3.5e-03]
+ [-1.3e-02 -1.3e-03 2.1e-03]
+ [-1.2e-03 -1.2e-02 5.1e-03]
+ [-1.2e-02 -6.9e-03 4.0e-03]
+ [-1.2e-02 3.9e-03 -2.7e-04]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 1.2e-02 -5.6e-03 1.2e-03]
+ [ 7.4e-04 -1.3e-02 5.1e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-2.5e-03 1.2e-02 -5.0e-03]
+ [-1.2e-02 6.2e-03 -1.3e-03]
+ [ 1.4e-02 -3.0e-03 -3.2e-04]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 3.2e-03 -9.6e-03 1.0e-02]
+ [-1.1e-02 -1.1e-02 -9.0e-04]
+ [-1.3e-02 6.1e-03 2.1e-03]
+ [-9.8e-03 -8.8e-03 -5.4e-03]
+ [ 7.0e-03 -1.2e-02 2.5e-04]
+ [-7.0e-03 1.2e-02 -2.5e-04]
+ [-6.5e-03 5.6e-03 1.2e-02]
+ [ 6.5e-03 -5.6e-03 -1.2e-02]
+ [-1.3e-02 -3.0e-03 2.9e-03]
+ [-2.2e-03 -1.1e-02 5.7e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 2.8e-03 1.2e-02 -6.1e-03]
+ [-1.0e-02 9.0e-03 -2.7e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 1.0e-02 -9.0e-03 3.3e-03]
+ [-1.0e-02 9.0e-03 -3.3e-03]
+ [ 1.2e-02 -8.8e-03 1.5e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-2.2e-03 -9.1e-03 1.1e-02]
+ [-1.3e-02 -6.7e-03 -2.5e-03]
+ [-1.0e-02 9.9e-03 -9.0e-05]
+ [-6.4e-03 -5.1e-04 -1.3e-02]
+ [-9.8e-03 -1.0e-02 6.2e-04]
+ [ 9.8e-03 1.0e-02 -6.2e-04]
+ [-1.1e-02 5.3e-03 9.3e-03]
+ [ 1.1e-02 -5.3e-03 -9.3e-03]
+ [ 7.1e-03 9.8e-03 -6.4e-03]
+ [-7.0e-03 1.1e-02 -1.6e-03]
+ [-1.2e-02 -2.9e-03 5.6e-03]
+ [-1.2e-02 8.0e-03 1.1e-03]
+ [-1.8e-03 1.2e-02 -3.8e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 3.9e-04 -1.3e-02 4.6e-03]
+ [-1.1e-02 -5.1e-03 5.4e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 1.0e-02 6.5e-03 -6.0e-03]
+ [ 3.7e-04 1.3e-02 -4.9e-03]
+ [ 7.6e-03 -1.1e-02 6.5e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-8.0e-03 -1.2e-04 1.2e-02]
+ [-1.3e-02 5.2e-03 -4.0e-03]
+ [ 1.7e-03 1.4e-02 -4.0e-03]
+ [-9.9e-03 2.8e-03 -9.9e-03]
+ [-1.3e-02 -6.0e-03 3.6e-03]
+ [ 1.3e-02 6.0e-03 -3.6e-03]
+ [-1.0e-03 1.2e-02 8.7e-03]
+ [ 1.0e-03 -1.2e-02 -8.7e-03]
+ [ 1.3e-02 1.9e-03 -4.8e-03]
+ [ 2.0e-03 1.2e-02 -4.7e-03]
+ [-1.2e-02 6.1e-03 1.8e-03]
+ [-4.4e-03 1.3e-02 -2.8e-03]
+ [ 8.2e-03 9.4e-03 -5.5e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-7.9e-03 -9.3e-03 5.5e-03]
+ [ 2.8e-03 -1.3e-02 3.2e-03]
+ [ 1.3e-02 -2.8e-03 -3.2e-03]
+ [ 9.2e-03 8.4e-03 -5.6e-03]
+ [-8.4e-03 -9.7e-03 7.4e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-1.1e-02 4.9e-03 8.1e-03]
+ [-6.9e-03 1.0e-02 -8.5e-03]
+ [ 1.0e-02 8.6e-03 -4.7e-03]
+ [-4.5e-03 5.1e-03 -1.2e-02]
+ [-1.4e-02 3.0e-03 -6.0e-05]
+ [ 1.4e-02 -3.0e-03 6.0e-05]
+ [ 4.6e-03 1.3e-02 6.6e-03]
+ [-4.6e-03 -1.3e-02 -6.6e-03]
+ [ 1.2e-02 -6.3e-03 -2.1e-03]
+ [ 9.3e-03 8.2e-03 -5.1e-03]
+ [-6.3e-03 1.2e-02 -1.1e-03]
+ [ 4.6e-03 1.3e-02 -4.3e-03]
+ [ 1.3e-02 2.3e-03 -3.9e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-1.2e-02 -2.3e-03 4.2e-03]
+ [-5.4e-03 -1.1e-02 4.3e-03]
+ [ 9.1e-03 -1.0e-02 -4.1e-04]
+ [ 1.3e-02 7.8e-04 -4.1e-03]
+ [-1.4e-02 -9.0e-04 4.3e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-3.3e-03 1.2e-02 6.1e-03]
+ [ 2.5e-03 9.9e-03 -1.1e-02]
+ [ 1.4e-02 -4.8e-04 -3.2e-03]
+ [ 1.0e-03 6.3e-03 -1.3e-02]
+ [-1.2e-02 7.5e-03 -1.3e-03]
+ [ 1.2e-02 -7.5e-03 1.3e-03]
+ [ 1.1e-02 6.8e-03 8.0e-03]
+ [-1.1e-02 -6.8e-03 -8.0e-03]
+ [ 8.0e-03 1.0e-02 -3.9e-03]
+ [-4.4e-03 1.2e-02 -3.3e-04]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 5.1e-03 -1.3e-02 3.0e-04]
+ [ 1.2e-02 -1.5e-03 -2.6e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 4.9e-03 -1.4e-02 1.0e-05]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 1.3e-02 -2.9e-03 -3.6e-03]
+ [-1.4e-02 4.5e-03 3.6e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 6.0e-04 1.4e-02 4.9e-03]
+ [ 8.5e-03 7.5e-03 -9.8e-03]
+ [ 1.2e-02 -7.7e-03 -1.5e-03]
+ [ 5.5e-03 4.0e-03 -1.3e-02]
+ [-4.5e-03 1.3e-02 -3.3e-03]
+ [ 4.5e-03 -1.3e-02 3.3e-03]
+ [ 1.2e-02 1.4e-03 8.9e-03]
+ [-1.2e-02 -1.4e-03 -8.9e-03]
+ [ 1.3e-02 4.4e-03 -2.7e-03]
+ [ 2.4e-03 1.2e-02 -1.0e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-2.2e-03 -1.3e-02 1.4e-03]
+ [ 9.8e-03 -7.4e-03 -4.8e-04]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-3.1e-03 -1.5e-02 1.3e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 1.0e-02 -9.4e-03 -1.4e-03]
+ [-8.8e-03 1.2e-02 6.0e-04]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 7.1e-03 1.1e-02 6.4e-03]
+ [ 1.3e-02 2.3e-03 -7.9e-03]
+ [ 7.4e-03 -1.2e-02 -9.0e-05]
+ [ 6.0e-03 -1.4e-03 -1.3e-02]
+ [ 7.5e-03 1.2e-02 -3.3e-03]
+ [-7.5e-03 -1.2e-02 3.3e-03]
+ [ 1.1e-02 -4.8e-03 9.0e-03]
+ [-1.1e-02 4.8e-03 -9.0e-03]
+ [ 1.3e-02 -4.2e-03 -1.7e-03]
+ [ 8.8e-03 8.4e-03 -1.7e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-9.7e-03 -9.0e-03 1.7e-03]
+ [ 3.2e-03 -1.3e-02 4.3e-04]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-3.0e-03 1.4e-02 -1.0e-04]
+ [ 3.0e-03 -1.4e-02 1.0e-04]
+ [ 4.4e-03 1.4e-02 3.2e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 1.4e-02 1.8e-03 5.1e-04]
+ [ 5.9e-03 -8.5e-03 -1.1e-02]
+ [-1.7e-03 -1.4e-02 4.0e-03]
+ [-3.7e-03 -7.0e-03 -1.2e-02]
+ [ 9.8e-03 -8.2e-04 -1.0e-02]
+ [-9.8e-03 8.2e-04 1.0e-02]
+ [ 1.0e-02 -9.3e-03 6.0e-03]
+ [-1.0e-02 9.3e-03 -6.0e-03]
+ [-1.3e-02 -4.0e-03 2.9e-03]
+ [-7.5e-04 -1.3e-02 3.0e-03]
+ [ 1.3e-02 -4.2e-03 -1.1e-03]
+ [ 5.6e-03 -1.3e-02 2.1e-03]
+ [-5.6e-03 -1.0e-02 3.3e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 7.7e-03 1.1e-02 -3.6e-03]
+ [ 1.3e-02 -2.0e-03 -1.5e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-1.3e-02 2.8e-04 2.1e-03]
+ [-8.4e-03 -1.0e-02 3.4e-03]
+ [ 3.3e-04 1.2e-02 9.3e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 1.0e-02 2.2e-04 1.0e-02]
+ [ 9.5e-03 -1.2e-02 -1.9e-03]
+ [-7.8e-03 -1.2e-02 1.1e-03]
+ [ 4.1e-03 -9.2e-03 -1.0e-02]
+ [ 1.4e-02 -3.2e-03 1.5e-03]
+ [-1.4e-02 3.2e-03 -1.5e-03]
+ [-2.6e-03 -9.3e-03 1.2e-02]
+ [ 2.6e-03 9.3e-03 -1.2e-02]
+ [ 1.3e-03 -1.3e-02 1.1e-03]
+ [ 1.1e-02 -4.5e-03 2.1e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-1.2e-02 5.3e-03 -2.1e-03]
+ [-1.1e-02 -8.0e-03 -3.6e-04]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 1.1e-02 8.1e-03 1.1e-03]
+ [-1.1e-02 -8.1e-03 -1.1e-03]
+ [ 1.4e-02 2.0e-03 5.2e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 8.1e-03 -1.1e-02 4.0e-03]
+ [-3.6e-03 -1.1e-02 -9.4e-03]
+ [-1.4e-02 -2.0e-03 1.6e-03]
+ [-3.9e-03 -7.7e-03 -1.1e-02]
+ [ 1.1e-02 -7.7e-03 -5.9e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-5.7e-03 -8.6e-03 1.1e-02]
+ [ 5.7e-03 8.6e-03 -1.1e-02]
+ [-8.3e-03 1.1e-02 -2.1e-03]
+ [-1.3e-02 -3.3e-03 8.8e-04]
+ [ 2.0e-04 -1.3e-02 2.9e-03]
+ [-1.1e-02 -9.0e-03 2.5e-03]
+ [-1.2e-02 2.2e-03 -1.0e-05]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 1.3e-02 -4.2e-03 2.0e-04]
+ [ 2.2e-03 -1.3e-02 2.0e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [-4.0e-03 1.3e-02 -2.4e-03]
+ [-1.3e-02 4.8e-03 -7.5e-04]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 1.5e-02 1.7e-03 3.4e-03]
+ [ 4.3e-03 1.3e-02 -4.0e-03]
+ [ 7.5e-03 5.9e-03 1.1e-02]
+ [ 1.2e-02 -7.7e-03 1.5e-03]
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+ [ 1.3e-02 5.0e-03 -1.4e-03]
+ [ 9.4e-03 -7.5e-03 2.5e-03]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 1.4e-02 5.9e-03 -1.3e-03]
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+ [ 1.9e-03 -4.7e-03 1.3e-02]
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+ [ 6.0e-03 -1.2e-02 -7.7e-03]
+ [-6.0e-03 1.2e-02 7.7e-03]
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+ [ 1.3e-02 3.5e-03 -4.8e-03]
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+ [-1.3e-02 -1.2e-03 4.4e-03]
+ [-7.4e-03 1.1e-02 -2.7e-03]
+ [ 8.6e-03 8.2e-03 -6.4e-03]
+ [-2.3e-03 1.3e-02 -5.6e-03]
+ [-1.0e-02 6.4e-03 -5.0e-04]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 1.2e-02 -5.9e-03 -2.5e-04]
+ [ 1.1e-02 7.2e-03 -4.8e-03]
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+ [-1.2e-02 5.4e-03 1.0e-03]
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+ [ 0.0e+00 0.0e+00 0.0e+00]
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+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
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+ [ 0.0e+00 0.0e+00 0.0e+00]
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+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
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+ [ 0.0e+00 0.0e+00 0.0e+00]
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+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]
+ [ 0.0e+00 0.0e+00 0.0e+00]]
+# ---
+# name: test_node_topology[1BNA-Points of Edge]
+ [-1 -1 0 1 1 -1 2 2 3 7 8 8 9 11 11 7 -1 5 5 5 16 19 20 20
+ -1 21 21 22 26 27 28 29 30 30 31 33 33 26 -1 24 24 24 38 41 42 42 -1 43
+ 43 44 48 49 49 50 52 52 48 -1 46 46 46 57 60 61 61 -1 62 62 63 67 68 69
+ 70 71 71 72 74 74 67 -1 65 65 65 79 82 83 83 -1 84 84 85 89 90 91 92 93
+ 93 94 96 89]
+# ---
+# name: test_node_topology[1BNA-Points of Edge].1
+ [ 2 -1 -1 -1 3 17 5 -1 6 -1 -1 10 -1 -1 13 9 4 -1
+ 17 17 -1 -1 -1 22 39 24 -1 25 -1 -1 -1 -1 -1 32 -1 -1
+ 35 28 23 -1 39 39 -1 -1 -1 44 58 46 -1 47 -1 -1 51 -1
+ -1 54 50 45 -1 58 58 -1 -1 -1 63 80 65 -1 66 -1 -1 -1
+ -1 -1 73 -1 -1 76 69 64 -1 80 80 -1 -1 -1 85 101 87 -1
+ 88 -1 -1 -1 -1 -1 95 -1 -1 91]
+# ---
+# name: test_node_topology[1BNA-Points of Edge].2
+ [ -1 -1 -1 4 -1 18 -1 -1 -1 15 11 -1 -1 14 -1 -1 -1 18
+ -1 18 -1 -1 23 -1 40 -1 -1 -1 37 -1 -1 37 33 -1 -1 36
+ -1 -1 -1 40 -1 40 -1 -1 45 -1 59 -1 -1 -1 56 52 -1 -1
+ 55 -1 -1 -1 59 -1 59 -1 -1 64 -1 81 -1 -1 -1 78 -1 -1
+ 78 74 -1 -1 77 -1 -1 -1 81 -1 81 -1 -1 86 -1 102 -1 -1
+ -1 99 -1 -1 99 96 -1 -1 -1 -1]
+# ---
+# name: test_node_topology[1BNA-Points of Edge].3
+ [ -1 -1 -1 -1 -1 19 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 19
+ 19 -1 -1 -1 -1 -1 41 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
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+ -1 -1 -1 -1 -1 -1 -1 -1 82 82 -1 -1 -1 -1 -1 103 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1]
+# ---
+# name: test_node_topology[1BNA-Points of Edge].4
+ [2 1 2 3 3 4 3 2 3 3 3 3 2 3 3 3 2 4 4 4 2 2 3 3 4 3 2 3 3 2 2 3 3 3 2 3 3
+ 3 2 4 4 4 2 2 3 3 4 3 2 3 3 3 3 2 3 3 3 2 4 4 4 2 2 3 3 4 3 2 3 3 2 2 3 3
+ 3 2 3 3 3 2 4 4 4 2 2 3 3 4 3 2 3 3 2 2 3 3 3 2 2 3]
+# ---
+# name: test_node_topology[1BNA-Res Group ID]
+ [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
+ 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4]
+# ---
+# name: test_node_topology[1BNA-Res Info]
+ [0.0 0.1 0.1 0.2 0.2 0.3 0.4 0.4 0.5 0.6 0.6 0.7 0.8 0.8 0.9 0.9 0.0 0.0
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+ 0.5 0.6 0.6 0.7 0.7 0.8 0.8 0.9 0.9 1.0]
+# ---
+# name: test_node_topology[1BNA-Res Info].1
+ [16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 22 22 22 22 22 22 22 22
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+# ---
+# name: test_node_topology[1BNA-Res Info].2
+ [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 0 1 2 3 4 5 6 7
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+# ---
+# name: test_node_topology[1BNA-Res Info].3
+ [53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 50 50 50 50 50 50 50 50
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+ 50 50 50 50]
+# ---
+# name: test_node_topology[1BNA-Res Info].4
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+# ---
+# name: test_node_topology[1BNA-Res Info].5
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+# ---
+# name: test_node_topology[1BNA-Res Info].6
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+ 78 78 78 78 78 78 78 99 99 99 99 99 99 99 99 99 99 99 99 99 99 99 99 99
+ 99 99 99 99]
+# ---
+# name: test_node_topology[1BNA-Residue Mask]
+ [ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True]
+# ---
+# name: test_node_topology[1BNA-Residue Mask].1
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+ 89 89 89 89]
+# ---
+# name: test_node_topology[1BNA-Residue Mask].2
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+# ---
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+# ---
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+# ---
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+# ---
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+# ---
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+ -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1
+ 0.6 0.6 0.6 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.0 -1.0 -1.0
+ -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0
+ -1.0 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 0.4 -1.2 -1.2 -1.2 -1.2
+ -1.2 -1.2 -1.2 -1.2 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.3
+ -1.3 -1.3 -1.3 -1.3 -1.3 -1.3 -1.3 -1.3 1.2 1.2 1.2 1.2 2.6 2.6
+ 2.6 -1.6 -1.6 -1.6 -1.6 -2.6 -2.6 -1.7 -1.7 -1.7 -1.7 -1.7 -1.7 -1.7
+ -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -2.9 -2.2 -2.2 -2.2 -2.2 -2.2 -2.2
+ -2.2 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0
+ -1.0 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 0.2 0.2 0.2 0.2 0.2 -1.1
+ -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2
+ -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 0.4 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1
+ -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1
+ -1.1 -1.1 -1.1 -1.0 -1.0 -1.0 -1.0 0.3 0.3 0.3 0.3 -1.2 -1.2 -1.2
+ -1.2 -1.1 -1.1 -1.1 -1.1 -1.1 0.6 0.6 0.6 0.6 -0.9 -0.9 -0.9 -0.9
+ -0.9 -1.3 -1.3 -1.3 -1.3 -1.3 -1.4 -1.4 -1.4 -1.4 1.5 1.5 2.1 2.1
+ 2.1 2.1 2.1 -1.5 -1.5 -1.5 -1.5 -1.3 -1.3 -1.3 -1.3 -1.3 -1.3 -1.3
+ -1.3 0.3 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2
+ -1.2 -1.2 -1.2 -1.2 -1.2 -0.9 -0.9 -0.9 -0.9 -0.9 0.3 0.3 0.3 -1.3
+ -1.3 -1.3 -1.3 -1.3 0.5 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.3
+ -1.3 -1.3 -1.3 -1.3 -1.3 -1.3]
+# ---
+# name: test_node_topology[4ozs-Dihedral Phi].1
+ [[ 0. -0. 0.]
+ [ 0. -0. 0.]
+ [ 0. -0. 0.]
+ ...
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]]
+# ---
+# name: test_node_topology[4ozs-Dihedral Phi].2
+ [[ 0.0 -0.0 0.1]
+ [ 0.0 -0.0 0.1]
+ [ 0.0 -0.0 0.1]
+ ...
+ [ 0.0 0.0 0.0]
+ [ 0.0 0.0 0.0]
+ [ 0.0 0.0 0.0]]
+# ---
+# name: test_node_topology[4ozs-Dihedral Phi].3
+ [[ 0. 0. -0.]
+ [ 0. 0. -0.]
+ [ 0. 0. -0.]
+ ...
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]]
+# ---
+# name: test_node_topology[4ozs-Dihedral Psi]
+ [ 3.1 3.1 3.1 3.1 3.1 3.1 3.1 -1.8 -0.5 -0.5 -0.5 -0.5 -0.5 -0.5
+ -0.5 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0
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+ 0.0 0.0 0.0 -1.2 -1.2 -1.2 -1.2 -1.2 0.3 0.3 0.3 0.3 2.1 2.1
+ 2.1 2.1 2.1 2.1 2.1 2.0 2.0 2.0 2.0 2.0 2.0 2.0 -2.5 -2.5
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+ 0.5 0.5 0.5 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 0.4 0.4
+ 0.4 -0.9 -0.9 -0.9 -0.9 -0.9 -0.6 -0.6 -0.6 -0.6 -0.6 0.7 0.7 0.7
+ 0.7 0.3 0.3 0.3 0.3 -0.9 0.0 0.0 0.0 0.0 1.1 1.1 1.1 1.1
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+ -1.1 0.1 0.1 0.1 0.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.0 2.0
+ 2.0 2.0 2.0 2.0 2.0 -2.8 -2.8 2.6 2.6 2.6 2.6 2.6 2.6 2.6
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+ -0.1 -0.1 -0.1 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 2.2 2.2 2.2
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+ -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 0.4 0.4 -0.8 -0.8 -0.8
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+ 0.6 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8
+ -0.8 -0.8 -0.8 -0.8 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 0.0
+ 0.0 0.0 0.0 -1.3 -1.3 -1.3 -1.3 -1.3 0.3 0.3 0.3 0.3 2.2 2.2
+ 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 -2.4 -2.4
+ 2.6 2.6 2.6 2.6 2.6 2.6 2.6 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0
+ -1.8 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7
+ -0.7 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7
+ -0.7 -0.7 0.5 0.5 0.5 0.5 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 0.5
+ -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8
+ -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 0.4
+ 0.4 0.4 0.4 -0.8 -0.8 -0.8 -0.8 -0.7 -0.7 -0.7 -0.7 -0.7 0.6 0.6
+ 0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.9 -0.9 -0.9 -0.9 -0.9 0.3 0.3 0.3
+ 0.3 -3.1 -3.1 -3.1 -3.1 -1.7 0.3 0.3 0.3 0.3 0.9 0.9 0.9 0.9
+ 0.9 0.9 0.9 0.9 2.0 2.0 2.0 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6
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+ -0.6 -0.6 -0.6 -0.6 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 0.4 -0.7
+ -0.7 -0.7 -0.7 -0.7 -0.7 -0.7]
+# ---
+# name: test_node_topology[4ozs-Dihedral Psi].1
+ [[0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ ...
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]]
+# ---
+# name: test_node_topology[4ozs-Dihedral Psi].2
+ [[-0. -0. -0.]
+ [-0. -0. -0.]
+ [-0. -0. -0.]
+ ...
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]]
+# ---
+# name: test_node_topology[4ozs-Dihedral Psi].3
+ [[-0. -0. 0.]
+ [-0. -0. 0.]
+ [-0. -0. 0.]
+ ...
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]]
+# ---
+# name: test_node_topology[4ozs-Edge Info]
+ [ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True]
+# ---
+# name: test_node_topology[4ozs-Edge Info].1
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+# ---
+# name: test_node_topology[4ozs-Edge Info].2
+ [[ 0.4 0.1 -0.2]
+ [ 0.4 0.1 -0.2]
+ [ 0.4 0.1 -0.2]
+ ...
+ [ 0.0 0.0 0.0]
+ [ 0.0 0.0 0.0]
+ [ 0.0 0.0 0.0]]
+# ---
+# name: test_node_topology[4ozs-Edge Info].3
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+# ---
+# name: test_node_topology[4ozs-Edge Info].4
+ [[-0. -0. 0.]
+ [ 0. 0. -0.]
+ [-0. -0. 0.]
+ ...
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]]
+# ---
+# name: test_node_topology[4ozs-Edge Info].5
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+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
+# ---
+# name: test_node_topology[4ozs-Point Edge Angle]
+ [False True True False True True False False True True True False
+ True False False True True True False True False False True True
+ True False True False False True True True False True True True
+ True True True True False True True True False True True False
+ False True True True False True False False True True True False
+ True True False False True True True False True True False False
+ True True True False True True False False True True True False
+ True True True False True True False False True True True False
+ False True True True False True True True True False True True
+ True False False True True True False True True True False True
+ True True True True False False True True True False True True
+ False False True True True False True True True False False True
+ True True False True True True False False True True True False
+ False True True True False True True False False True True True
+ False True True True False False True True True False True True
+ False False True True True False True True True True True True
+ True True True True False True True True False False True True
+ True False True True True False False True True True False True
+ True True False True True True False True True True True False
+ True True True False True True True False False True True True
+ False True True True True False True True True False True True
+ True False True False False True True True False True True True
+ True False True True True False True True True True True True
+ False True True False False True True True False True False False
+ True True True False True False False True True True False True
+ False False True True True False True True True True True True
+ True False True True True False True True False False True True
+ True False True False False True True True False True True False
+ False True True True False True True False False True True True
+ False True True False False True True True False True True True
+ False True True False False True True True False False True True
+ True False True True True True False True True True False False
+ True True True False True True True False True True True True
+ True False False True True True False True True False False True
+ True True False True True True False False True True True False
+ True True True False False True True True False False True True
+ True False True True False False True True True False True True
+ True False False True True True False True True False False True
+ True True False True True True True True True True True True
+ True False True True True False False True True True False True
+ True True False False True True True False True True True False
+ True True True False True True True True False True True True
+ False True True True False False True True True False True True
+ True True False True True True False True True True False True
+ False False True True True False True True True True False True
+ True True False True True True True True True False True True
+ False False True True True False True False False True True True
+ False True False False True True True False True False False True
+ True True False True True True True True True True False True
+ True True False True True False False True True True False True
+ False False True True True False True True False False True True
+ True False True True False False True True True False True True
+ False False True True True False True True True False True True
+ False False True True True False False True True True False True
+ True True True False True True True False False True True True
+ False True True True False True True True True True False False
+ True True True False True True False False True True True False
+ True True True False False True True True False True True True
+ False False True True True False False True True True False True
+ True False False True True True False True True True False False
+ True True True False True True False False True True True False
+ True True True True True True True True True True False True
+ True True False False True True True False True True True False
+ False True True True False True True True False True True True
+ False True True True True False True True True False True True
+ True False False True True True False True True True True False
+ True True True False True True True False True False False True
+ True True False True True True True False True True True False
+ True True True True True True False True True False False True
+ True True False True False False True True True False True False
+ False True True True False True False False True True True False
+ True True True True True True True False True True True False
+ True True False False True True True False True False False True
+ True True False True True False False True True True False True
+ True False False True True True False True True False False True
+ True True False True True True False True True False False True
+ True True False False True True True False True True True True
+ False True True True False False True True True False True True
+ True False True True True True True False False True True True
+ False True True False False True True True False True True True
+ False False True True True False True True True False False True
+ True True False False True True True False True True False False
+ True True True False True True True False False True True True
+ False True True False]
+# ---
+# name: test_node_topology[4ozs-Point Edge Angle].1
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+ 916 916 916 916 916 916 916 925 925 925 925 925 930 930 930 930 934 934
+ 934 934 934 934 934 934 934 934 934 945 945 945 945 945 945 945 945 953
+ 953 953 953 953 953 953 953 953 962 962 962 962 962 962 962 962 962 971
+ 971 971 971 971 976 976 976 976 976 976 976 976 984 984 984 984 984 984
+ 984 984 984 993 993 993 993 993 993 993]
+# ---
+# name: test_node_topology[4ozs-Res Info].6
+ [ 7 7 7 7 7 7 7 7 14 14 14 14 14 14
+ 14 21 21 21 21 21 21 21 28 28 28 28 28 28
+ 28 40 40 40 40 40 40 40 40 40 40 40 40 48
+ 48 48 48 48 48 48 48 55 55 55 55 55 55 55
+ 63 63 63 63 63 63 63 63 71 71 71 71 71 71
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+ 114 114 114 125 125 125 125 125 125 125 125 125 125 125
+ 133 133 133 133 133 133 133 133 142 142 142 142 142 142
+ 142 142 142 151 151 151 151 151 151 151 151 151 156 156
+ 156 156 156 164 164 164 164 164 164 164 164 173 173 173
+ 173 173 173 173 173 173 181 181 181 181 181 181 181 181
+ 192 192 192 192 192 192 192 192 192 192 192 201 201 201
+ 201 201 201 201 201 201 210 210 210 210 210 210 210 210
+ 210 218 218 218 218 218 218 218 218 227 227 227 227 227
+ 227 227 227 227 236 236 236 236 236 236 236 236 236 245
+ 245 245 245 245 245 245 245 245 249 249 249 249 256 256
+ 256 256 256 256 256 265 265 265 265 265 265 265 265 265
+ 272 272 272 272 272 272 272 280 280 280 280 280 280 280
+ 280 287 287 287 287 287 287 287 294 294 294 294 294 294
+ 294 301 301 301 301 301 301 301 313 313 313 313 313 313
+ 313 313 313 313 313 313 321 321 321 321 321 321 321 321
+ 328 328 328 328 328 328 328 336 336 336 336 336 336 336
+ 336 344 344 344 344 344 344 344 344 352 352 352 352 352
+ 352 352 352 356 356 356 356 364 364 364 364 364 364 364
+ 364 369 369 369 369 369 378 378 378 378 378 378 378 378
+ 378 383 383 383 383 383 387 387 387 387 398 398 398 398
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+ 406 415 415 415 415 415 415 415 415 415 424 424 424 424
+ 424 424 424 424 424 429 429 429 429 429 437 437 437 437
+ 437 437 437 437 446 446 446 446 446 446 446 446 446 454
+ 454 454 454 454 454 454 454 465 465 465 465 465 465 465
+ 465 465 465 465 474 474 474 474 474 474 474 474 474 483
+ 483 483 483 483 483 483 483 483 491 491 491 491 491 491
+ 491 491 500 500 500 500 500 500 500 500 500 509 509 509
+ 509 509 509 509 509 509 518 518 518 518 518 518 518 518
+ 518 522 522 522 522 529 529 529 529 529 529 529 538 538
+ 538 538 538 538 538 538 538 545 545 545 545 545 545 545
+ 553 553 553 553 553 553 553 553 560 560 560 560 560 560
+ 560 567 567 567 567 567 567 567 574 574 574 574 574 574
+ 574 586 586 586 586 586 586 586 586 586 586 586 586 594
+ 594 594 594 594 594 594 594 601 601 601 601 601 601 601
+ 609 609 609 609 609 609 609 609 617 617 617 617 617 617
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+ 637 637 637 637 637 637 637 637 642 642 642 642 642 651
+ 651 651 651 651 651 651 651 651 656 656 656 656 656 660
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+ 679 679 679 679 679 679 679 679 688 688 688 688 688 688
+ 688 688 688 697 697 697 697 697 697 697 697 697 702 702
+ 702 702 702 710 710 710 710 710 710 710 710 719 719 719
+ 719 719 719 719 719 719 727 727 727 727 727 727 727 727
+ 738 738 738 738 738 738 738 738 738 738 738 747 747 747
+ 747 747 747 747 747 747 756 756 756 756 756 756 756 756
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+ 791 791 791 791 791 791 791 791 795 795 795 795 802 802
+ 802 802 802 802 802 811 811 811 811 811 811 811 811 811
+ 818 818 818 818 818 818 818 826 826 826 826 826 826 826
+ 826 833 833 833 833 833 833 833 840 840 840 840 840 840
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+ 859 859 859 859 859 859 867 867 867 867 867 867 867 867
+ 874 874 874 874 874 874 874 882 882 882 882 882 882 882
+ 882 890 890 890 890 890 890 890 890 898 898 898 898 898
+ 898 898 898 902 902 902 902 910 910 910 910 910 910 910
+ 910 915 915 915 915 915 924 924 924 924 924 924 924 924
+ 924 929 929 929 929 929 933 933 933 933 944 944 944 944
+ 944 944 944 944 944 944 944 952 952 952 952 952 952 952
+ 952 961 961 961 961 961 961 961 961 961 970 970 970 970
+ 970 970 970 970 970 975 975 975 975 975 983 983 983 983
+ 983 983 983 983 992 992 992 992 992 992 992 992 992 1000
+ 1000 1000 1000 1000 1000 1000]
+# ---
+# name: test_node_topology[4ozs-Residue Mask]
+ [False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False]
+# ---
+# name: test_node_topology[4ozs-Residue Mask].1
+ [-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
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+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
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+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1]
+# ---
+# name: test_node_topology[4ozs-Residue Mask].2
+ [[0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ ...
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]]
+# ---
+# name: test_node_topology[4ozs-Residue Mask].3
+ [ 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 2 2 2
+ 2 2 2 2 3 3 3 3 3 3 3 4 4 4 4 4 4 4
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+ 9 9 9 9 9 9 9 9 10 10 10 10 11 11 11 11 11 11
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+ 14 14 14 15 15 15 15 16 16 16 16 16 16 16 16 16 16 16
+ 17 17 17 17 17 17 17 17 18 18 18 18 18 18 18 18 18 19
+ 19 19 19 19 19 19 19 19 20 20 20 20 20 21 21 21 21 21
+ 21 21 21 22 22 22 22 22 22 22 22 22 23 23 23 23 23 23
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+ 25 25 25 25 26 26 26 26 26 26 26 26 26 27 27 27 27 27
+ 27 27 27 28 28 28 28 28 28 28 28 28 29 29 29 29 29 29
+ 29 29 29 30 30 30 30 30 30 30 30 30 31 31 31 31 32 32
+ 32 32 32 32 32 33 33 33 33 33 33 33 33 33 34 34 34 34
+ 34 34 34 35 35 35 35 35 35 35 35 36 36 36 36 36 36 36
+ 37 37 37 37 37 37 37 38 38 38 38 38 38 38 39 39 39 39
+ 39 39 39 39 39 39 39 39 40 40 40 40 40 40 40 40 41 41
+ 41 41 41 41 41 42 42 42 42 42 42 42 42 43 43 43 43 43
+ 43 43 43 44 44 44 44 44 44 44 44 45 45 45 45 46 46 46
+ 46 46 46 46 46 47 47 47 47 47 48 48 48 48 48 48 48 48
+ 48 49 49 49 49 49 50 50 50 50 51 51 51 51 51 51 51 51
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+ 53 53 54 54 54 54 54 54 54 54 54 55 55 55 55 55 56 56
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+ 81 81 81 81 81 81 81 81 82 82 82 82 82 83 83 83 83 83
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+ 86 86 86 86 86 86 87 87 87 87 87 87 87 87 88 88 88 88
+ 88 88 88 88 88 89 89 89 89 89 89 89 89 89 90 90 90 90
+ 90 91 91 91 91 91 91 91 91 92 92 92 92 92 92 92 92 92
+ 93 93 93 93 93 93 93 93 94 94 94 94 94 94 94 94 94 94
+ 94 95 95 95 95 95 95 95 95 95 96 96 96 96 96 96 96 96
+ 96 97 97 97 97 97 97 97 97 98 98 98 98 98 98 98 98 98
+ 99 99 99 99 99 99 99 99 99 100 100 100 100 100 100 100 100 100
+ 101 101 101 101 102 102 102 102 102 102 102 103 103 103 103 103 103 103
+ 103 103 104 104 104 104 104 104 104 105 105 105 105 105 105 105 105 106
+ 106 106 106 106 106 106 107 107 107 107 107 107 107 108 108 108 108 108
+ 108 108 109 109 109 109 109 109 109 109 109 109 109 109 110 110 110 110
+ 110 110 110 110 111 111 111 111 111 111 111 112 112 112 112 112 112 112
+ 112 113 113 113 113 113 113 113 113 114 114 114 114 114 114 114 114 115
+ 115 115 115 116 116 116 116 116 116 116 116 117 117 117 117 117 118 118
+ 118 118 118 118 118 118 118 119 119 119 119 119 120 120 120 120 121 121
+ 121 121 121 121 121 121 121 121 121 122 122 122 122 122 122 122 122 123
+ 123 123 123 123 123 123 123 123 124 124 124 124 124 124 124 124 124 125
+ 125 125 125 125 126 126 126 126 126 126 126 126 127 127 127 127 127 127
+ 127 127 127 128 128 128 128 128 128 128]
+# ---
+# name: test_node_topology[8H1B-Chain Info]
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+ 3994 3994 3994 3994 3994 3994]
+# ---
+# name: test_node_topology[8H1B-Dihedral Phi]
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+ -1.4 -1.2 -1.2 -1.2 -1.2 -1.2]
+# ---
+# name: test_node_topology[8H1B-Dihedral Phi].1
+ [[ 0. 0. -0.]
+ [ 0. 0. -0.]
+ [ 0. 0. -0.]
+ ...
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]]
+# ---
+# name: test_node_topology[8H1B-Dihedral Phi].2
+ [[ 0.1 0.1 -0.1]
+ [ 0.1 0.1 -0.1]
+ [ 0.1 0.1 -0.1]
+ ...
+ [ 0.0 0.0 0.0]
+ [ 0.0 0.0 0.0]
+ [ 0.0 0.0 0.0]]
+# ---
+# name: test_node_topology[8H1B-Dihedral Phi].3
+ [[0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ ...
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]]
+# ---
+# name: test_node_topology[8H1B-Dihedral Psi]
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+# ---
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+# ---
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+# ---
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+# ---
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+# ---
+# name: test_node_topology[8H1B-Edge Info].1
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+# ---
+# name: test_node_topology[8H1B-Edge Info].2
+ [[ 0.2 -0.0 0.3]
+ [ 0.2 -0.0 0.3]
+ [ 0.1 -0.0 0.2]
+ ...
+ [ 0.0 0.0 0.0]
+ [ 0.0 0.0 0.0]
+ [ 0.0 0.0 0.0]]
+# ---
+# name: test_node_topology[8H1B-Edge Info].3
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+# ---
+# name: test_node_topology[8H1B-Edge Info].4
+ [[-0. -0. -0.]
+ [ 0. 0. 0.]
+ [-0. -0. -0.]
+ ...
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]]
+# ---
+# name: test_node_topology[8H1B-Edge Info].5
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+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
+# ---
+# name: test_node_topology[8H1B-Point Edge Angle]
+ [False True True False True True True False True True True False
+ True True True True False True True True False True True False
+ False True True True False True True True False False True True
+ True False True True True True True False False True True True
+ False True True False False True True True False True True False
+ False True True True False True True True True True True False
+ True True True True True True True True True True False True
+ False True True True False True True True True False True True
+ True False True False False True True True False True True False
+ False True True True False True True False False True True True
+ False True True True True False True True True False True True
+ True False False True True True False True True True True True
+ True True True True False True True False False True True True
+ False True False False True True True False True True True True
+ True True False True True True False False True True True False
+ True False True True True False True True False False True True
+ True False True False False True True True False True False False
+ True True True False True True False False True True True False
+ False True True True False True False False True True True False
+ True False True True True False True True True False True True
+ False False True True True False True True True False True True
+ False False True True True False True True False False True True
+ True False True False False True True True False True True False
+ False True True True False True True True True True True True
+ True True True False True True False False True True True False
+ False True True True False True True True False False True True
+ True False True True True False False True True True False True
+ False False True True True False True True True True True True
+ False True True True False False True True True False True True
+ True False True True True True True True True True True False
+ True False False True True True False True True True True True
+ True True False True True True False True True True False True
+ True True True True True True True True True False True True
+ False False True True True False True True False False True True
+ True False True True True False False True True True False True
+ True False False True True True False True True False False True
+ True True False False True True True False True True False False
+ True True True False True True True False False True True True
+ False True True False False True True True False True False False
+ True True True False True True True True True False False True
+ True True False True True False False True True True False True
+ True True True False True True True False True False False True
+ True True False True True True True False True True True False
+ True True False False True True True False True True True True
+ True True True True True True False True True False False True
+ True True False True True True True True True True True True
+ False True False False True True True False True False True True
+ True False True True False False True True True False True True
+ False False True True True False True True True True False True
+ True True False True True False False True True True False True
+ True True False True True True True True True True True True
+ False True True True False False True True True False True True
+ False False True True True False True True False False True True
+ True False True True True False False True True True False True
+ True True True True True True True True False True True True
+ True True True True True True False True True False False True
+ True True False True True False False True True True False True
+ True False False True True True False False True True True False
+ True True True True True True True True True False True True
+ True True False True True True False True True True False True
+ True True True True True True True True False True True False
+ False True True True False True True False False True True True
+ False False True True True False False True True True False True
+ True False False True True True False True True True True True
+ True True True True True False True True False False True True
+ True False True True False False True True True False True True
+ True False True True True True True True True False True True
+ True False True True False False True True True False True True
+ True True True True False True True True True False True True
+ True False True True True False True True False False True True
+ True False True True True True False True True True False True
+ False True True True False True True False False True True True
+ False True False False True True True False True False False True
+ True True False True True True True False True True True False
+ True True True True True True False True True False False True
+ True True False True False False True True True False True False
+ False True True True False True True False False True True True
+ False True True True False False True True True False False True
+ True True False True True False False True True True False True
+ True False False True True True False True False True True True
+ False True True False False True True True False True True False
+ False True True True False True False True True True False True
+ True False False True True True False True True True False True
+ True True False True]
+# ---
+# name: test_node_topology[8H1B-Point Edge Angle].1
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+ 951 951 951 957 957 957 957 957 957 957 957 965 965 965 965 965 965 965
+ 965 973 973 973 973 973 973 979 979 979 979 979 979 979 979 987 987 987
+ 987 987 987 987 987 995 995 995 995 995]
+# ---
+# name: test_node_topology[8H1B-Res Info].6
+ [ 7 7 7 7 7 7 7 7 16 16 16 16 16 16
+ 16 16 16 24 24 24 24 24 24 24 24 33 33 33
+ 33 33 33 33 33 33 44 44 44 44 44 44 44 44
+ 44 44 44 52 52 52 52 52 52 52 52 60 60 60
+ 60 60 60 60 60 67 67 67 67 67 67 67 78 78
+ 78 78 78 78 78 78 78 78 78 84 84 84 84 84
+ 84 93 93 93 93 93 93 93 93 93 100 100 100 100
+ 100 100 100 108 108 108 108 108 108 108 108 116 116 116
+ 116 116 116 116 116 125 125 125 125 125 125 125 125 125
+ 134 134 134 134 134 134 134 134 134 144 144 144 144 144
+ 144 144 144 144 144 152 152 152 152 152 152 152 152 159
+ 159 159 159 159 159 159 166 166 166 166 166 166 166 175
+ 175 175 175 175 175 175 175 175 181 181 181 181 181 181
+ 189 189 189 189 189 189 189 189 196 196 196 196 196 196
+ 196 203 203 203 203 203 203 203 211 211 211 211 211 211
+ 211 211 216 216 216 216 216 223 223 223 223 223 223 223
+ 229 229 229 229 229 229 233 233 233 233 241 241 241 241
+ 241 241 241 241 245 245 245 245 253 253 253 253 253 253
+ 253 253 261 261 261 261 261 261 261 261 268 268 268 268
+ 268 268 268 276 276 276 276 276 276 276 276 287 287 287
+ 287 287 287 287 287 287 287 287 295 295 295 295 295 295
+ 295 295 300 300 300 300 300 309 309 309 309 309 309 309
+ 309 309 318 318 318 318 318 318 318 318 318 325 325 325
+ 325 325 325 325 332 332 332 332 332 332 332 341 341 341
+ 341 341 341 341 341 341 345 345 345 345 355 355 355 355
+ 355 355 355 355 355 355 362 362 362 362 362 362 362 374
+ 374 374 374 374 374 374 374 374 374 374 374 378 378 378
+ 378 389 389 389 389 389 389 389 389 389 389 389 397 397
+ 397 397 397 397 397 397 405 405 405 405 405 405 405 405
+ 414 414 414 414 414 414 414 414 414 422 422 422 422 422
+ 422 422 422 430 430 430 430 430 430 430 430 435 435 435
+ 435 435 443 443 443 443 443 443 443 443 452 452 452 452
+ 452 452 452 452 452 460 460 460 460 460 460 460 460 467
+ 467 467 467 467 467 467 478 478 478 478 478 478 478 478
+ 478 478 478 486 486 486 486 486 486 486 486 495 495 495
+ 495 495 495 495 495 495 502 502 502 502 502 502 502 511
+ 511 511 511 511 511 511 511 511 519 519 519 519 519 519
+ 519 519 530 530 530 530 530 530 530 530 530 530 530 538
+ 538 538 538 538 538 538 538 548 548 548 548 548 548 548
+ 548 548 548 555 555 555 555 555 555 555 561 561 561 561
+ 561 561 569 569 569 569 569 569 569 569 577 577 577 577
+ 577 577 577 577 586 586 586 586 586 586 586 586 586 594
+ 594 594 594 594 594 594 594 598 598 598 598 608 608 608
+ 608 608 608 608 608 608 608 617 617 617 617 617 617 617
+ 617 617 625 625 625 625 625 625 625 625 633 633 633 633
+ 633 633 633 633 642 642 642 642 642 642 642 642 642 652
+ 652 652 652 652 652 652 652 652 652 662 662 662 662 662
+ 662 662 662 662 662 670 670 670 670 670 670 670 670 678
+ 678 678 678 678 678 678 678 686 686 686 686 686 686 686
+ 686 691 691 691 691 691 701 701 701 701 701 701 701 701
+ 701 701 710 710 710 710 710 710 710 710 710 714 714 714
+ 714 724 724 724 724 724 724 724 724 724 724 732 732 732
+ 732 732 732 732 732 740 740 740 740 740 740 740 740 745
+ 745 745 745 745 750 750 750 750 750 758 758 758 758 758
+ 758 758 758 769 769 769 769 769 769 769 769 769 769 769
+ 777 777 777 777 777 777 777 777 785 785 785 785 785 785
+ 785 785 789 789 789 789 801 801 801 801 801 801 801 801
+ 801 801 801 801 809 809 809 809 809 809 809 809 816 816
+ 816 816 816 816 816 825 825 825 825 825 825 825 825 825
+ 829 829 829 829 837 837 837 837 837 837 837 837 846 846
+ 846 846 846 846 846 846 846 852 852 852 852 852 852 860
+ 860 860 860 860 860 860 860 867 867 867 867 867 867 867
+ 874 874 874 874 874 874 874 883 883 883 883 883 883 883
+ 883 883 890 890 890 890 890 890 890 898 898 898 898 898
+ 898 898 898 905 905 905 905 905 905 905 912 912 912 912
+ 912 912 912 920 920 920 920 920 920 920 920 929 929 929
+ 929 929 929 929 929 929 934 934 934 934 934 942 942 942
+ 942 942 942 942 942 950 950 950 950 950 950 950 950 956
+ 956 956 956 956 956 964 964 964 964 964 964 964 964 972
+ 972 972 972 972 972 972 972 978 978 978 978 978 978 986
+ 986 986 986 986 986 986 986 994 994 994 994 994 994 994
+ 994 1000 1000 1000 1000 1000]
+# ---
+# name: test_node_topology[8H1B-Residue Mask]
+ [False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False]
+# ---
+# name: test_node_topology[8H1B-Residue Mask].1
+ [-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
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+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
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+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1]
+# ---
+# name: test_node_topology[8H1B-Residue Mask].2
+ [[0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]
+ ...
+ [0. 0. 0.]
+ [0. 0. 0.]
+ [0. 0. 0.]]
+# ---
+# name: test_node_topology[8H1B-Residue Mask].3
+ [ 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 2
+ 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 4 4
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+ 10 10 10 10 11 11 11 11 11 11 11 12 12 12 12 12 12 12
+ 12 13 13 13 13 13 13 13 13 14 14 14 14 14 14 14 14 14
+ 15 15 15 15 15 15 15 15 15 16 16 16 16 16 16 16 16 16
+ 16 17 17 17 17 17 17 17 17 18 18 18 18 18 18 18 19 19
+ 19 19 19 19 19 20 20 20 20 20 20 20 20 20 21 21 21 21
+ 21 21 22 22 22 22 22 22 22 22 23 23 23 23 23 23 23 24
+ 24 24 24 24 24 24 25 25 25 25 25 25 25 25 26 26 26 26
+ 26 27 27 27 27 27 27 27 28 28 28 28 28 28 29 29 29 29
+ 30 30 30 30 30 30 30 30 31 31 31 31 32 32 32 32 32 32
+ 32 32 33 33 33 33 33 33 33 33 34 34 34 34 34 34 34 35
+ 35 35 35 35 35 35 35 36 36 36 36 36 36 36 36 36 36 36
+ 37 37 37 37 37 37 37 37 38 38 38 38 38 39 39 39 39 39
+ 39 39 39 39 40 40 40 40 40 40 40 40 40 41 41 41 41 41
+ 41 41 42 42 42 42 42 42 42 43 43 43 43 43 43 43 43 43
+ 44 44 44 44 45 45 45 45 45 45 45 45 45 45 46 46 46 46
+ 46 46 46 47 47 47 47 47 47 47 47 47 47 47 47 48 48 48
+ 48 49 49 49 49 49 49 49 49 49 49 49 50 50 50 50 50 50
+ 50 50 51 51 51 51 51 51 51 51 52 52 52 52 52 52 52 52
+ 52 53 53 53 53 53 53 53 53 54 54 54 54 54 54 54 54 55
+ 55 55 55 55 56 56 56 56 56 56 56 56 57 57 57 57 57 57
+ 57 57 57 58 58 58 58 58 58 58 58 59 59 59 59 59 59 59
+ 60 60 60 60 60 60 60 60 60 60 60 61 61 61 61 61 61 61
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+ 64 64 64 64 64 64 64 64 65 65 65 65 65 65 65 65 66 66
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+ 74 75 75 75 75 76 76 76 76 76 76 76 76 76 76 77 77 77
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+ 79 79 79 79 80 80 80 80 80 80 80 80 80 81 81 81 81 81
+ 81 81 81 81 81 82 82 82 82 82 82 82 82 82 82 83 83 83
+ 83 83 83 83 83 84 84 84 84 84 84 84 84 85 85 85 85 85
+ 85 85 85 86 86 86 86 86 87 87 87 87 87 87 87 87 87 87
+ 88 88 88 88 88 88 88 88 88 89 89 89 89 90 90 90 90 90
+ 90 90 90 90 90 91 91 91 91 91 91 91 91 92 92 92 92 92
+ 92 92 92 93 93 93 93 93 94 94 94 94 94 95 95 95 95 95
+ 95 95 95 96 96 96 96 96 96 96 96 96 96 96 97 97 97 97
+ 97 97 97 97 98 98 98 98 98 98 98 98 99 99 99 99 100 100
+ 100 100 100 100 100 100 100 100 100 100 101 101 101 101 101 101 101 101
+ 102 102 102 102 102 102 102 103 103 103 103 103 103 103 103 103 104 104
+ 104 104 105 105 105 105 105 105 105 105 106 106 106 106 106 106 106 106
+ 106 107 107 107 107 107 107 108 108 108 108 108 108 108 108 109 109 109
+ 109 109 109 109 110 110 110 110 110 110 110 111 111 111 111 111 111 111
+ 111 111 112 112 112 112 112 112 112 113 113 113 113 113 113 113 113 114
+ 114 114 114 114 114 114 115 115 115 115 115 115 115 116 116 116 116 116
+ 116 116 116 117 117 117 117 117 117 117 117 117 118 118 118 118 118 119
+ 119 119 119 119 119 119 119 120 120 120 120 120 120 120 120 121 121 121
+ 121 121 121 122 122 122 122 122 122 122 122 123 123 123 123 123 123 123
+ 123 124 124 124 124 124 124 125 125 125 125 125 125 125 125 126 126 126
+ 126 126 126 126 126 127 127 127 127 127]
+# ---
+# name: test_node_topology[8U8W-Chain Info]
+ [0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
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+# ---
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+# ---
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+# ---
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+# ---
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+ 2.8 2.8 2.8 2.8 2.8 -0.3 -0.3 -0.3 -0.3 -0.3 -0.3 -0.3 -0.3 3.1
+ 3.1 3.1 3.1 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.0 2.0 2.0 2.0
+ 2.0 2.0 2.0 2.7 2.7 2.7 2.7 -2.7 2.4 2.4 2.4 2.4 1.3 1.3
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+ 0.1 0.1 0.1 0.1 0.1 0.9 0.9 0.9 0.9 0.4 0.4 0.4 0.4 0.4
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+ -0.7 -0.7 -0.7 -0.7 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 0.4 0.4 -0.8
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+ -0.6 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.5 -0.5 -0.5 -0.5
+ -0.5 0.1 0.1 0.1 0.1 -0.3 -0.3 -0.3 -0.3 -0.3 2.4 2.4 2.4 2.4
+ 1.1 1.1 1.1 1.1 1.1 -0.3 -0.3 -0.3 -0.3 -0.8 -0.8 -0.8 -0.8 -0.8
+ -0.8 -0.8 -0.8 -0.2 2.8 2.8 2.8 2.8 2.8 2.8 2.8 -1.9 2.4 2.4
+ 2.4 2.4 2.4 2.4 2.4 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 2.2
+ 2.2 2.2 2.2 2.2 -2.9 -2.9 -2.9 2.1 2.1 2.1 2.1 2.1 1.9 1.9
+ 1.9 1.9 1.9 1.9 1.9 2.8 2.8 2.8 0.0 0.0 0.0 0.0 1.9 1.9
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+ 2.7 -2.6 -2.6 -2.6 -0.4 -0.4 -0.4 -0.4 -0.4 -0.1 -0.1 -0.1 2.8 2.8
+ 2.8 2.8 2.8 2.9 2.9 2.9 2.9 2.9 2.9 -2.9 2.6 2.6 2.6 2.6
+ 2.6 -3.0 2.2 2.2 2.2 2.2 2.2 2.6 2.6 2.6 2.6 2.6 2.6 2.6
+ 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.4 2.4 2.4 2.4 2.4 2.4 2.4
+ -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -1.2 -1.2 -1.2
+ -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2 2.5 2.5 2.5 2.5 2.5
+ 2.5 2.5 -2.2 -2.2 -2.2 -2.2 -2.2 2.3 2.3 2.3 2.3 2.3 2.3 2.3
+ 2.6 2.6 2.6 2.6 2.6 2.6 -2.5 -2.5 -2.5 -2.5 -2.5 2.8 2.8 2.8
+ 2.8 2.8 2.8 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 0.6 0.6
+ -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.7 -0.7 -0.7 -0.7 -0.7
+ -0.7 -0.7 -0.7 -0.7 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 0.4 0.4 0.4 0.4
+ -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6 -0.6
+ -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.7 -0.7 -0.7 -0.7
+ -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 0.5 -0.8 -0.8 -0.8 -0.8 -0.8 0.4
+ 0.4 0.4 0.4 0.4 0.4 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7
+ -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.7 -0.8 -0.8
+ -0.8 -0.8 -0.8 -0.8 0.4 0.4 -0.5 -0.5 -0.5 -0.5 -0.5 0.8 -0.3 -0.3
+ -0.3 -0.3 -0.3 0.8 0.8 0.8]
+# ---
+# name: test_node_topology[8U8W-Dihedral Psi].1
+ [[-0. 0. 0.]
+ [-0. 0. 0.]
+ [-0. 0. 0.]
+ ...
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]]
+# ---
+# name: test_node_topology[8U8W-Dihedral Psi].2
+ [[-0. 0. 0.]
+ [-0. 0. 0.]
+ [-0. 0. 0.]
+ ...
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]]
+# ---
+# name: test_node_topology[8U8W-Dihedral Psi].3
+ [[ 0. -0. 0.]
+ [ 0. -0. 0.]
+ [ 0. -0. 0.]
+ ...
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]]
+# ---
+# name: test_node_topology[8U8W-Edge Info]
[ True True True True True True True True True True True True
True True True True True True True True True True True True
True True True True True True True True True True True True
@@ -2028,343 +12354,6 @@
True True True True True True True True True True True True
True True True True True True True True True True True True
True True True True True True True True True True True True
- True True True True True True False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False False False False False False False False False False False
- False False]
-# ---
-# name: test_node_topology.1
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- -1 -1 -1 -1 -1 -1 -1 -1]
-# ---
-# name: test_node_topology.10
- [[ 0. -0. -0.]
- [-0. 0. 0.]
- [-0. 0. 0.]
- ...
- [ 0. 0. 0.]
- [ 0. 0. 0.]
- [ 0. 0. 0.]]
-# ---
-# name: test_node_topology.11
- [[ 0. 0. 0.]
- [ 0. -0. -0.]
- [-0. -0. 0.]
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- [ 0. 0. 0.]
- [ 0. 0. 0.]
- [ 0. 0. 0.]]
-# ---
-# name: test_node_topology.12
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-# ---
-# name: test_node_topology.13
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-# ---
-# name: test_node_topology.14
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-# ---
-# name: test_node_topology.15
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-# ---
-# name: test_node_topology.16
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-# ---
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True True True True True True True True True True True True
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True True True True True True True True True True True True
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# ---
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# ---
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-# ---
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+# ---
+# name: test_node_topology[8U8W-Edge Info].4
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-# ---
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+# ---
+# name: test_node_topology[8U8W-Point Edge Angle]
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+ True True False True False True True True False True True True
+ False False True True True False True True True True True False
+ False True True True False True True True False False True True
+ True False True True True False False True True True False True
+ False False True True True False True True False False True True
+ True False True True True False False True True True False True
+ True False False True True True False True False False True True
+ True False False True True True False True True True False False
+ True True True False True True True False False True True True
+ False False True True True False True True True True False True
+ True True False True True True False True True True True False
+ True True True False True True False False True True True False
+ True False False True True True False True True False False True
+ True True False True True False False True True True False False
+ True True True False True True True True True True True True
+ True False True False False True True True False True True True
+ False True False True True True False True False False True True
+ True False True False True True True False True False False True
+ True True False False True True True False True True True False
+ False True True True False True False True True True False True
+ True True False False True True True False True True True False
+ False True True True False True True False False True True True
+ False False True True True False False True True True False False
+ True True True False False True True True False True True True
+ True False True True True False True True True True True False
+ False True True True False True True True True True True True
+ False True True True False True True True False True True True
+ True True True True True True True False True True False False
+ True True True False False True True True False True False False
+ True True True False True False True True True False False True
+ True True False True False False True True True False True False
+ False True True True False True True True True True True False
+ True True True True True True True True True True False True
+ True True True True True True False True True True False True
+ True True True True True True False True True True False True
+ True True True True True False True True True True True True
+ True True True True False True False True True True False True
True True True True True True True True True False True True
- False True True True False False True True True True True True
- True True True True True True True False True True False True
- True True False False True True True True True True True True
- True True False True True False True True True False False True
- True True True True False True True True True True True True
- False True True False True True False False False False False False
+ True False False True True True False True True True False False
+ True True True False True True True True True True True True
+ True False True False True True True False True True False False
+ True True True False True True True True True True True True
+ True False True True True True True True True False True True
+ True False True True True True True False False True True True
+ False False True True True False True True False False True True
+ True False True True False False True True True False True True
+ False False True True True False True False True True True False
+ False True True True]
+# ---
+# name: test_node_topology[8U8W-Point Edge Angle].1
+ [-1.0 2.0 2.0 -1.0 -1.0 2.2 2.0 2.1 -1.0 -1.0 2.1 1.9 2.0 -1.0
+ 1.9 -1.0 -1.0 2.1 2.0 2.1 -1.0 1.9 -1.0 2.1 2.0 2.1 -1.0 2.0
+ 2.1 1.9 1.9 1.9 1.9 2.1 2.0 2.1 -1.0 2.0 1.9 -1.0 -1.0 2.1
+ 1.9 2.0 -1.0 2.0 1.9 1.9 2.2 2.1 -1.0 -1.0 2.1 2.0 2.0 -1.0
+ 2.2 1.9 2.0 -1.0 1.9 -1.0 -1.0 2.1 2.0 2.1 -1.0 2.0 2.0 1.7
+ -1.0 2.1 2.0 2.0 -1.0 1.8 1.9 1.8 2.1 1.9 2.0 -1.0 -1.0 2.1
+ 2.0 2.0 -1.0 2.1 1.9 -1.0 -1.0 2.1 1.9 2.0 -1.0 2.0 1.9 -1.0
+ -1.0 2.1 1.9 2.1 -1.0 1.9 -1.0 -1.0 2.1 2.0 2.0 -1.0 1.8 1.8
+ 1.8 2.1 1.9 2.0 -1.0 2.0 2.1 2.1 2.1 2.1 2.1 2.1 2.1 1.9
+ 2.0 -1.0 2.0 2.1 -1.0 -1.0 2.1 2.0 2.1 -1.0 -1.0 2.2 2.0 2.0
+ -1.0 2.0 2.0 2.1 -1.0 -1.0 2.2 2.0 2.1 -1.0 1.9 2.0 2.1 -1.0
+ -1.0 2.1 1.9 2.0 -1.0 2.0 2.1 -1.0 -1.0 2.1 1.9 2.0 -1.0 1.9
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+ -1.0 2.0 2.0 1.9 2.2 2.1 -1.0 -1.0 2.1 1.9 2.0 -1.0 -1.0 2.1
+ 2.0 2.1 -1.0 1.9 -1.0 2.1 1.9 2.1 -1.0 2.1 1.9 -1.0 -1.0 2.1
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+ 2.1 2.1 2.1 1.9 2.1 -1.0 2.0 2.1 -1.0 -1.0 2.1 1.9 2.0 -1.0
+ 1.9 2.0 -1.0 -1.0 2.1 2.0 2.1 -1.0 1.9 2.0 2.1 -1.0 -1.0 2.1
+ 2.0 2.1 -1.0 2.0 1.9 2.1 -1.0 -1.0 2.1 2.0 2.1 -1.0 2.1 1.9
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+ 1.9 2.0 -1.0 2.1 1.9 2.0 -1.0 2.0 -1.0 -1.0 2.2 1.9 2.0 -1.0
+ 2.0 2.1 2.1 2.1 2.1 2.1 2.1 -1.0 2.1 1.9 2.0 -1.0 1.9 -1.0
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+ 2.1 -1.0 1.9 2.1 2.1 2.1 2.1 2.1 2.1 2.1 1.9 2.0 -1.0 1.9
+ -1.0 -1.0 2.2 1.9 2.0 -1.0 2.0 1.9 2.1 -1.0 -1.0 2.1 1.9 2.0
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+ -1.0 1.9 -1.0 2.1 1.9 2.1 -1.0 2.0 2.0 2.1 -1.0 -1.0 2.1 1.9
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+ 2.1 1.9 2.0 -1.0 2.0 2.0 2.1 -1.0 -1.0 2.1 1.9 2.0 -1.0 1.9
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+ 1.9 2.0 -1.0 2.0 2.0 1.9 1.9 -1.0 2.1 1.9 2.0 -1.0 2.0 2.0
+ 2.0 2.2 2.1 -1.0 -1.0 2.1 2.0 2.1 -1.0 2.0 2.1 2.1 2.1 2.1
+ 2.1 2.1 -1.0 2.1 2.0 2.1 -1.0 2.1 1.9 2.0 -1.0 2.0 2.1 2.1
+ 2.1 2.1 2.1 2.1 2.1 2.0 2.1 -1.0 2.0 2.0 -1.0 -1.0 2.1 1.9
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+ 2.1 1.9 2.1 -1.0 1.9 -1.0 -1.0 2.1 2.0 2.0 -1.0 1.8 1.9 1.8
+ 2.2 1.9 2.0 -1.0 2.0 2.1 2.1 2.1 2.1 2.1 2.1 2.2 2.0 2.1
+ -1.0 1.9 2.1 2.1 2.1 2.1 2.1 2.1 -1.0 2.1 1.9 2.1 -1.0 2.0
+ 2.1 2.1 2.1 2.1 2.1 2.1 -1.0 2.1 1.9 2.0 -1.0 1.9 1.8 1.8
+ 2.1 1.9 2.0 -1.0 2.0 2.1 2.1 2.1 2.1 2.1 2.1 2.1 1.9 2.0
+ -1.0 1.9 -1.0 2.1 1.9 2.0 -1.0 2.0 2.1 2.1 2.1 2.1 2.1 2.1
+ 2.1 1.9 2.1 -1.0 2.0 2.0 2.1 -1.0 -1.0 2.1 1.9 2.1 -1.0 2.0
+ 2.0 2.1 -1.0 -1.0 2.1 1.9 2.0 -1.0 2.0 2.1 1.9 1.9 1.9 1.9
+ 2.1 1.9 2.0 -1.0 2.0 -1.0 2.1 1.9 2.1 -1.0 2.0 2.1 -1.0 -1.0
+ 2.1 1.9 2.1 -1.0 2.0 2.1 1.9 1.9 1.9 1.9 2.1 1.9 2.1 -1.0
+ 2.0 2.1 2.1 2.1 2.1 2.1 2.1 -1.0 2.1 1.9 2.0 -1.0 2.0 1.9
+ 2.0 2.2 2.1 -1.0 -1.0 2.1 2.0 2.0 -1.0 -1.0 2.1 1.9 2.0 -1.0
+ 1.9 2.0 -1.0 -1.0 2.1 1.9 2.1 -1.0 1.9 2.0 -1.0 -1.0 2.1 1.9
+ 2.0 -1.0 2.0 2.1 -1.0 -1.0 2.1 2.0 2.1 -1.0 1.9 -1.0 2.1 2.0
+ 2.1 -1.0 -1.0 2.1 1.9 2.0]
+# ---
+# name: test_node_topology[8U8W-Point Edge Angle].2
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+ 127 1170 1169 1171 1172 1173 127 1174 128 1177 1176 1178 128 1179
+ 129 1182 1181 129 1183 130]
+# ---
+# name: test_node_topology[8U8W-Point Edge Angle].3
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+ 308 -1 -1 310 311 311 -1 314 -1 315 316 316 -1 319
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+ 1168 -1 1171 1172 -1 -1 1174 1175 1175 -1 1178 -1 1179 1180
+ 1180 -1 -1 1183 1184 1184]
+# ---
+# name: test_node_topology[8U8W-Point Edge Angle].4
+ [[ 0. -0. 0.]
+ [-0. 0. -0.]
+ [-0. 0. 0.]
+ ...
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]
+ [ 0. 0. 0.]]
+# ---
+# name: test_node_topology[8U8W-Point Edge Angle].5
+ [[ 0. 0. 0.]
+ [ 0. -0. 0.]
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+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1]
+# ---
+# name: test_node_topology[8U8W-Res Info].4
+ [ 5 5 5 5 5 5 5 5 5 5 8 8 8 8 8 8 8 9 9 9 9 9 9 27
+ 27 27 27 27 27 27 27 27 27 14 14 14 14 14 14 14 14 32 32 32 32 32 32 32
+ 32 32 32 32 4 4 4 4 8 8 8 8 8 8 8 20 20 20 20 20 20 20 20 12
+ 12 12 12 12 12 12 5 5 5 5 5 14 14 14 14 14 14 14 14 14 14 14 14 14
+ 14 14 14 8 8 8 8 8 8 8 12 12 12 12 12 12 12 34 34 34 34 34 34 34
+ 34 34 34 34 18 18 18 18 18 18 18 18 5 5 5 5 5 27 27 27 27 27 27 27
+ 27 27 27 27 27 27 27 27 27 27 27 16 16 16 16 16 16 16 16 13 13 13 13 13
+ 13 13 13 18 18 18 18 18 18 18 18 32 32 32 32 32 32 32 32 32 32 32 5 5
+ 5 5 5 9 9 9 9 9 9 14 14 14 14 14 14 14 14 32 32 32 32 32 32 32
+ 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 14 14 14 14 14 14 14 14 8
+ 8 8 8 8 8 8 32 32 32 32 32 32 32 32 32 32 32 34 34 34 34 34 34 34
+ 34 34 34 34 16 16 16 16 16 16 16 16 13 13 13 13 13 13 13 13 29 29 29 29
+ 29 29 29 29 29 27 27 27 27 27 27 27 27 27 4 4 4 4 8 8 8 8 8 8
+ 8 18 18 18 18 18 18 18 18 4 4 4 4 8 8 8 8 8 8 8 33 33 33 33
+ 33 33 33 33 33 33 33 33 8 8 8 8 8 8 8 4 4 4 4 4 4 4 4 9
+ 9 9 9 9 9 8 8 8 8 8 8 8 4 4 4 4 29 29 29 29 29 29 29 29
+ 29 5 5 5 5 5 34 34 34 34 34 34 34 34 34 34 34 8 8 8 8 8 8 8
+ 27 27 27 27 27 27 27 27 27 9 9 9 9 9 9 14 14 14 14 14 14 14 14 9
+ 9 9 9 9 9 29 29 29 29 29 29 29 29 29 32 32 32 32 32 32 32 32 32 32
+ 32 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 8 8 8 8 8
+ 8 8 14 14 14 14 14 14 14 14 29 29 29 29 29 29 29 29 29 13 13 13 13 13
+ 13 13 13 8 8 8 8 8 8 8 5 5 5 5 5 29 29 29 29 29 29 29 29 29
+ 29 29 29 29 29 29 29 29 29 5 5 5 5 5 37 37 37 37 37 37 37 37 37 4
+ 4 4 4 37 37 37 37 37 37 37 37 37 13 13 13 13 13 13 13 13 8 8 8 8
+ 8 8 8 14 14 14 14 14 14 14 14 13 13 13 13 13 13 13 13 5 5 5 5 5
+ 27 27 27 27 27 27 27 27 27 27 8 8 8 8 8 8 8 4 4 4 4 11 11 11
+ 11 11 11 8 8 8 8 8 8 8 9 9 9 9 9 9 8 8 8 8 8 8 8 5
+ 5 5 5 5 29 29 29 29 29 29 29 29 29 9 9 9 9 9 9 27 27 27 27 27
+ 27 27 27 27 27 27 27 27 27 27 27 27 27 14 14 14 14 14 14 14 14 5 5 5
+ 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 37 37 37 37 37 37 37
+ 37 37 32 32 32 32 32 32 32 32 32 32 32 33 33 33 33 33 33 33 33 33 33 33
+ 33 4 4 4 4 34 34 34 34 34 34 34 34 34 34 34 18 18 18 18 18 18 18 18
+ 5 5 5 5 5 8 8 8 8 8 8 8 9 9 9 9 9 9 5 5 5 5 5 8
+ 8 8 8 8 8 8 8 8 8 8 8 8 8 12 12 12 12 12 12 12 34 34 34 34
+ 34 34 34 34 34 34 34 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33
+ 33 33 33 33 33 33 33 12 12 12 12 12 12 12 34 34 34 34 34 34 34 34 34 34
+ 34 9 9 9 9 9 9 34 34 34 34 34 34 34 34 34 34 34 29 29 29 29 29 29
+ 29 29 29 29 29 29 29 29 29 29 29 29 27 27 27 27 27 27 27 27 27 27 11 11
+ 11 11 11 11 18 18 18 18 18 18 18 18 27 27 27 27 27 27 27 27 27 27 33 33
+ 33 33 33 33 33 33 33 33 33 33 32 32 32 32 32 32 32 32 32 32 32 5 5 5
+ 5 5 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 18 18 18 18 18 18
+ 18 18 9 9 9 9 9 9 5 5 5 5 5 18 18 18]
+# ---
+# name: test_node_topology[8U8W-Res Info].5
+ [ 0 0 0 0 0 5 5 5 5 5 10 10 10 10 10 10 10 17
+ 17 17 17 17 17 23 23 23 23 23 23 23 23 23 23 33 33 33
+ 33 33 33 33 33 41 41 41 41 41 41 41 41 41 41 41 52 52
+ 52 52 56 56 56 56 56 56 56 63 63 63 63 63 63 63 63 71
+ 71 71 71 71 71 71 78 78 78 78 78 83 83 83 83 83 83 83
+ 83 91 91 91 91 91 91 91 91 99 99 99 99 99 99 99 106 106
+ 106 106 106 106 106 113 113 113 113 113 113 113 113 113 113 113 124 124
+ 124 124 124 124 124 124 132 132 132 132 132 137 137 137 137 137 137 137
+ 137 137 146 146 146 146 146 146 146 146 146 155 155 155 155 155 155 155
+ 155 163 163 163 163 163 163 163 163 171 171 171 171 171 171 171 171 179
+ 179 179 179 179 179 179 179 179 179 179 190 190 190 190 190 195 195 195
+ 195 195 195 201 201 201 201 201 201 201 201 209 209 209 209 209 209 209
+ 209 209 209 209 220 220 220 220 220 220 220 220 220 220 220 231 231 231
+ 231 231 231 231 231 239 239 239 239 239 239 239 246 246 246 246 246 246
+ 246 246 246 246 246 257 257 257 257 257 257 257 257 257 257 257 268 268
+ 268 268 268 268 268 268 276 276 276 276 276 276 276 276 284 284 284 284
+ 284 284 284 284 284 293 293 293 293 293 293 293 293 293 302 302 302 302
+ 306 306 306 306 306 306 306 313 313 313 313 313 313 313 313 321 321 321
+ 321 325 325 325 325 325 325 325 332 332 332 332 332 332 332 332 332 332
+ 332 332 344 344 344 344 344 344 344 351 351 351 351 355 355 355 355 359
+ 359 359 359 359 359 365 365 365 365 365 365 365 372 372 372 372 376 376
+ 376 376 376 376 376 376 376 385 385 385 385 385 390 390 390 390 390 390
+ 390 390 390 390 390 401 401 401 401 401 401 401 408 408 408 408 408 408
+ 408 408 408 417 417 417 417 417 417 423 423 423 423 423 423 423 423 431
+ 431 431 431 431 431 437 437 437 437 437 437 437 437 437 446 446 446 446
+ 446 446 446 446 446 446 446 457 457 457 457 457 457 457 457 457 466 466
+ 466 466 466 466 466 466 466 475 475 475 475 475 475 475 482 482 482 482
+ 482 482 482 482 490 490 490 490 490 490 490 490 490 499 499 499 499 499
+ 499 499 499 507 507 507 507 507 507 507 514 514 514 514 514 519 519 519
+ 519 519 519 519 519 519 528 528 528 528 528 528 528 528 528 537 537 537
+ 537 537 542 542 542 542 542 542 542 542 542 551 551 551 551 555 555 555
+ 555 555 555 555 555 555 564 564 564 564 564 564 564 564 572 572 572 572
+ 572 572 572 579 579 579 579 579 579 579 579 587 587 587 587 587 587 587
+ 587 595 595 595 595 595 600 600 600 600 600 600 600 600 600 600 610 610
+ 610 610 610 610 610 617 617 617 617 621 621 621 621 621 621 627 627 627
+ 627 627 627 627 634 634 634 634 634 634 640 640 640 640 640 640 640 647
+ 647 647 647 647 652 652 652 652 652 652 652 652 652 661 661 661 661 661
+ 661 667 667 667 667 667 667 667 667 667 676 676 676 676 676 676 676 676
+ 676 685 685 685 685 685 685 685 685 693 693 693 693 693 698 698 698 698
+ 698 703 703 703 703 703 708 708 708 708 708 713 713 713 713 713 713 713
+ 713 713 722 722 722 722 722 722 722 722 722 722 722 733 733 733 733 733
+ 733 733 733 733 733 733 733 745 745 745 745 749 749 749 749 749 749 749
+ 749 749 749 749 760 760 760 760 760 760 760 760 768 768 768 768 768 773
+ 773 773 773 773 773 773 780 780 780 780 780 780 786 786 786 786 786 791
+ 791 791 791 791 791 791 798 798 798 798 798 798 798 805 805 805 805 805
+ 805 805 812 812 812 812 812 812 812 812 812 812 812 823 823 823 823 823
+ 823 823 823 823 823 823 823 835 835 835 835 835 835 835 835 835 835 835
+ 835 847 847 847 847 847 847 847 854 854 854 854 854 854 854 854 854 854
+ 854 865 865 865 865 865 865 871 871 871 871 871 871 871 871 871 871 871
+ 882 882 882 882 882 882 882 882 882 891 891 891 891 891 891 891 891 891
+ 900 900 900 900 900 900 900 900 900 900 910 910 910 910 910 910 916 916
+ 916 916 916 916 916 916 924 924 924 924 924 924 924 924 924 924 934 934
+ 934 934 934 934 934 934 934 934 934 934 946 946 946 946 946 946 946 946
+ 946 946 946 957 957 957 957 957 962 962 962 962 962 962 962 962 970 970
+ 970 970 970 970 970 970 978 978 978 978 978 978 978 978 986 986 986 986
+ 986 986 992 992 992 992 992 997 997 997]
+# ---
+# name: test_node_topology[8U8W-Res Info].6
+ [ 4 4 4 4 4 9 9 9 9 9 16 16 16 16
+ 16 16 16 22 22 22 22 22 22 32 32 32 32 32
+ 32 32 32 32 32 40 40 40 40 40 40 40 40 51
+ 51 51 51 51 51 51 51 51 51 51 55 55 55 55
+ 62 62 62 62 62 62 62 70 70 70 70 70 70 70
+ 70 77 77 77 77 77 77 77 82 82 82 82 82 90
+ 90 90 90 90 90 90 90 98 98 98 98 98 98 98
+ 98 105 105 105 105 105 105 105 112 112 112 112 112 112
+ 112 123 123 123 123 123 123 123 123 123 123 123 131 131
+ 131 131 131 131 131 131 136 136 136 136 136 145 145 145
+ 145 145 145 145 145 145 154 154 154 154 154 154 154 154
+ 154 162 162 162 162 162 162 162 162 170 170 170 170 170
+ 170 170 170 178 178 178 178 178 178 178 178 189 189 189
+ 189 189 189 189 189 189 189 189 194 194 194 194 194 200
+ 200 200 200 200 200 208 208 208 208 208 208 208 208 219
+ 219 219 219 219 219 219 219 219 219 219 230 230 230 230
+ 230 230 230 230 230 230 230 238 238 238 238 238 238 238
+ 238 245 245 245 245 245 245 245 256 256 256 256 256 256
+ 256 256 256 256 256 267 267 267 267 267 267 267 267 267
+ 267 267 275 275 275 275 275 275 275 275 283 283 283 283
+ 283 283 283 283 292 292 292 292 292 292 292 292 292 301
+ 301 301 301 301 301 301 301 301 305 305 305 305 312 312
+ 312 312 312 312 312 320 320 320 320 320 320 320 320 324
+ 324 324 324 331 331 331 331 331 331 331 343 343 343 343
+ 343 343 343 343 343 343 343 343 350 350 350 350 350 350
+ 350 354 354 354 354 358 358 358 358 364 364 364 364 364
+ 364 371 371 371 371 371 371 371 375 375 375 375 384 384
+ 384 384 384 384 384 384 384 389 389 389 389 389 400 400
+ 400 400 400 400 400 400 400 400 400 407 407 407 407 407
+ 407 407 416 416 416 416 416 416 416 416 416 422 422 422
+ 422 422 422 430 430 430 430 430 430 430 430 436 436 436
+ 436 436 436 445 445 445 445 445 445 445 445 445 456 456
+ 456 456 456 456 456 456 456 456 456 465 465 465 465 465
+ 465 465 465 465 474 474 474 474 474 474 474 474 474 481
+ 481 481 481 481 481 481 489 489 489 489 489 489 489 489
+ 498 498 498 498 498 498 498 498 498 506 506 506 506 506
+ 506 506 506 513 513 513 513 513 513 513 518 518 518 518
+ 518 527 527 527 527 527 527 527 527 527 536 536 536 536
+ 536 536 536 536 536 541 541 541 541 541 550 550 550 550
+ 550 550 550 550 550 554 554 554 554 563 563 563 563 563
+ 563 563 563 563 571 571 571 571 571 571 571 571 578 578
+ 578 578 578 578 578 586 586 586 586 586 586 586 586 594
+ 594 594 594 594 594 594 594 599 599 599 599 599 609 609
+ 609 609 609 609 609 609 609 609 616 616 616 616 616 616
+ 616 620 620 620 620 626 626 626 626 626 626 633 633 633
+ 633 633 633 633 639 639 639 639 639 639 646 646 646 646
+ 646 646 646 651 651 651 651 651 660 660 660 660 660 660
+ 660 660 660 666 666 666 666 666 666 675 675 675 675 675
+ 675 675 675 675 684 684 684 684 684 684 684 684 684 692
+ 692 692 692 692 692 692 692 697 697 697 697 697 702 702
+ 702 702 702 707 707 707 707 707 712 712 712 712 712 721
+ 721 721 721 721 721 721 721 721 732 732 732 732 732 732
+ 732 732 732 732 732 744 744 744 744 744 744 744 744 744
+ 744 744 744 748 748 748 748 759 759 759 759 759 759 759
+ 759 759 759 759 767 767 767 767 767 767 767 767 772 772
+ 772 772 772 779 779 779 779 779 779 779 785 785 785 785
+ 785 785 790 790 790 790 790 797 797 797 797 797 797 797
+ 804 804 804 804 804 804 804 811 811 811 811 811 811 811
+ 822 822 822 822 822 822 822 822 822 822 822 834 834 834
+ 834 834 834 834 834 834 834 834 834 846 846 846 846 846
+ 846 846 846 846 846 846 846 853 853 853 853 853 853 853
+ 864 864 864 864 864 864 864 864 864 864 864 870 870 870
+ 870 870 870 881 881 881 881 881 881 881 881 881 881 881
+ 890 890 890 890 890 890 890 890 890 899 899 899 899 899
+ 899 899 899 899 909 909 909 909 909 909 909 909 909 909
+ 915 915 915 915 915 915 923 923 923 923 923 923 923 923
+ 933 933 933 933 933 933 933 933 933 933 945 945 945 945
+ 945 945 945 945 945 945 945 945 956 956 956 956 956 956
+ 956 956 956 956 956 961 961 961 961 961 969 969 969 969
+ 969 969 969 969 977 977 977 977 977 977 977 977 985 985
+ 985 985 985 985 985 985 991 991 991 991 991 991 996 996
+ 996 996 996 1004 1004 1004]
+# ---
+# name: test_node_topology[8U8W-Residue Mask]
+ [False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
False False False False False False False False False False False False
False False False False False False False False False False False False
False False False False False False False False False False False False
False False False False False False False False False False False False
False False False False False False False False False False False False
False False False False False False False False False False False False
- False False]
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False]
# ---
-# name: test_node_topology.7
- [-1.0 1.9 1.9 1.9 1.9 2.2 1.7 1.8 2.1 2.1 -1.0 2.1 2.1 -1.0
- 2.1 2.1 1.9 -1.0 -1.0 2.1 1.8 1.9 1.9 1.9 2.2 1.8 1.8 2.2
- 2.0 1.8 2.2 2.2 -1.0 2.2 2.1 -1.0 2.0 1.9 1.9 -1.0 -1.0 2.1
- 1.8 1.9 1.9 1.9 2.1 1.8 1.8 2.1 2.1 -1.0 2.1 2.1 -1.0 2.1
- 2.1 1.9 -1.0 -1.0 2.1 1.9 1.9 1.9 1.9 2.1 1.7 1.8 2.3 2.0
- 1.8 2.3 2.2 -1.0 2.2 2.1 -1.0 2.0 1.9 1.9 -1.0 -1.0 2.1 1.8
- 1.9 1.9 1.9 2.1 1.8 1.8 2.2 2.0 1.8 2.3 2.1 -1.0 2.1 2.3
- 1.9 1.9 1.9 -1.0 -1.0 2.1 1.8 1.8 1.8 2.0 2.1 1.8 1.7 2.2
- 2.0 1.8 2.3 2.1 -1.0 2.1 2.3 1.9 1.9 1.9 -1.0 -1.0 2.1 1.8
- 1.9 1.8 1.9 2.1 1.8 1.8 2.1 2.1 -1.0 2.1 2.1 -1.0 2.1 -1.0
- 2.1 1.9 -1.0 -1.0 2.1 1.8 1.8 1.8 2.0 2.1 1.8 1.8 2.1 2.1
- -1.0 2.1 2.0 -1.0 2.1 -1.0 2.1 1.9 -1.0 -1.0 2.1 1.9 1.9 1.9
- 1.9 2.1 1.7 1.8 2.1 2.1 -1.0 2.1 2.1 -1.0 2.1 2.1 1.9 -1.0
- -1.0 2.1 1.9 1.9 1.8 1.9 2.1 1.7 1.8 2.3 2.0 1.8 2.3 2.3
- -1.0 2.2 2.1 -1.0 2.0 1.9 1.9 -1.0 -1.0 2.1 1.9 1.9 1.9 2.0
- 2.1 1.7 1.8 2.1 2.1 -1.0 2.1 2.1 -1.0 2.1 2.1 1.9 -1.0 -1.0
- 2.1 1.8 1.8 1.8 2.0 -1.0 1.8 1.7 2.2 2.0 1.8 2.3 2.3 -1.0
- 2.2 2.0 -1.0 2.0 1.9 -1.0 1.9 1.9 1.9 2.0 2.1 1.8 1.8 2.1
- 2.1 -1.0 2.1 2.1 -1.0 2.1 2.1 1.9 -1.0 -1.0 2.1 1.8 1.9 1.9
- 1.9 2.1 1.8 1.8 2.2 2.0 1.8 2.2 2.2 -1.0 2.2 2.1 -1.0 2.0
- 1.9 1.9 -1.0 -1.0 2.1 1.8 1.9 1.8 1.9 2.1 1.8 1.9 2.1 2.1
- -1.0 2.1 2.1 -1.0 2.1 2.1 1.8 -1.0 -1.0 2.1 1.8 1.8 1.9 2.0
- 2.1 1.8 1.8 2.2 2.0 1.8 2.3 2.3 -1.0 2.2 2.1 -1.0 2.0 1.9
- 1.9 -1.0 -1.0 2.0 1.9 1.9 1.9 2.0 2.1 1.8 1.8 2.3 2.0 1.8
- 2.3 2.2 -1.0 2.1 2.3 1.9 1.9 1.9 -1.0 -1.0 2.1 1.9 1.9 1.9
- 1.9 2.1 1.8 1.8 2.2 2.0 1.8 2.3 2.1 -1.0 2.1 2.2 1.9 1.9
- 1.9 -1.0 -1.0 2.1 1.8 1.9 1.8 1.9 2.1 1.8 1.8 2.1 2.1 -1.0
- 2.1 2.1 -1.0 2.1 -1.0 2.1 1.9 -1.0 -1.0 2.1 1.9 1.9 1.9 1.9
- 2.1 1.7 1.7 2.1 2.1 -1.0 2.1 2.1 -1.0 2.1 -1.0 2.1 1.9 -1.0
- -1.0 2.1 1.8 1.9 1.9 2.0 2.1 1.8 1.8 2.1 2.1 -1.0 2.1 2.1
- -1.0 2.1 2.1 1.9 -1.0 -1.0 2.1 1.9 1.9 1.9 1.9 2.1 1.7 1.8
- 2.3 2.0 1.8 2.3 2.3 -1.0 2.2 2.1 -1.0 2.0 1.9 1.9 -1.0 -1.0
- 2.1 1.9 1.8 1.9 2.0 2.1 1.8 1.8 2.1 2.1 -1.0 2.1 2.1 -1.0
- 2.1 2.1 1.9 -1.0 -1.0 2.1 1.8 1.9 1.9 2.0 -1.0 1.8 1.9 2.3
- 2.0 1.8 2.3 2.2 -1.0 2.2 2.1 -1.0 2.0 1.9 -1.0 -1.0 -1.0 -1.0
- -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0
- -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0
- -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0
- -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0
- -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0
- -1.0 -1.0 -1.0 -1.0 -1.0 -1.0]
+# name: test_node_topology[8U8W-Residue Mask].1
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# ---
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# ---
# name: test_selection_working[chain_id-1BNA]
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+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.2 -0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.3 -0.1]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.1 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.3 -0.1]
+ [ 0.1 0.1 0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.3 0.0]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 -0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.3 -0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.1 0.2]
+ [ 0.1 0.2 -0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.1 0.2]
+ [ 0.1 0.1 0.1]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.3 0.3 0.2]
+ [ 0.1 0.2 0.0]
+ [ 0.1 0.3 -0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.3 -0.0]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.1 0.2]
+ [ 0.1 0.1 0.1]
+ [ 0.2 0.2 -0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.1 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 0.2]]
# ---
# name: test_selection_working[chain_id-4ozs]
[[ 3.6e-01 -1.6e-01 2.5e-01]
@@ -3103,106 +14215,106 @@
[-0.3 -0.0 0.2]]
# ---
# name: test_selection_working[entity_id-1BNA]
- [[ 1.7e-01 2.6e-01 2.3e-01]
- [ 8.6e-02 2.6e-01 1.7e-02]
- [ 1.7e-01 1.5e-01 1.5e-01]
- [ 2.2e-01 2.6e-01 2.3e-01]
- [ 9.2e-02 2.0e-01 5.8e-02]
- [ 2.0e-01 2.2e-01 -1.2e-01]
- [ 1.8e-01 1.6e-01 1.5e-01]
- [ 2.0e-01 3.0e-01 2.2e-01]
- [ 1.7e-01 3.3e-01 2.5e-01]
- [ 2.4e-01 2.2e-01 1.9e-01]
- [ 1.3e-01 2.4e-01 -4.8e-02]
- [ 1.0e-01 2.6e-01 -3.4e-05]
- [ 8.2e-02 2.1e-01 7.7e-02]
- [ 1.8e-01 2.2e-01 -1.1e-01]
- [ 1.7e-01 2.3e-01 -8.9e-02]
- [ 9.4e-02 1.5e-01 1.4e-01]
- [ 1.4e-01 1.6e-01 1.4e-01]
- [ 1.8e-01 2.1e-01 -1.2e-01]
- [ 1.9e-01 3.2e-01 2.5e-01]
- [ 1.7e-01 1.6e-01 1.5e-01]
- [ 6.5e-02 2.0e-01 5.5e-02]
- [ 1.8e-01 2.5e-01 1.9e-01]
- [ 2.1e-01 1.8e-01 2.0e-01]
- [ 1.9e-01 2.3e-01 -7.2e-02]
- [ 1.1e-01 1.8e-01 1.0e-01]
- [ 7.4e-02 2.4e-01 3.9e-02]
- [ 8.4e-02 2.5e-01 3.8e-02]
- [ 1.5e-01 2.6e-01 -4.1e-02]
- [ 2.1e-01 2.5e-01 2.1e-01]
- [ 2.3e-01 1.9e-01 1.7e-01]
- [ 9.4e-02 2.6e-01 2.0e-02]
- [ 1.0e-01 2.4e-01 3.2e-02]
- [ 1.5e-01 2.4e-01 -6.9e-02]
- [ 2.3e-01 2.3e-01 1.9e-01]
- [ 1.9e-01 2.4e-01 -7.5e-02]
- [ 1.8e-01 1.4e-01 1.6e-01]
- [ 1.5e-01 2.6e-01 -6.9e-02]
- [ 1.7e-01 2.2e-01 2.0e-01]
- [ 1.1e-01 2.7e-01 -1.8e-02]
- [ 1.4e-01 2.4e-01 -5.4e-02]
- [ 2.4e-01 2.6e-01 2.1e-01]
- [ 9.8e-02 1.9e-01 9.8e-02]
- [ 1.3e-01 1.3e-01 1.4e-01]
- [ 2.2e-01 2.5e-01 2.2e-01]
- [ 1.0e-01 1.5e-01 1.4e-01]
- [ 2.3e-01 2.6e-01 2.2e-01]
- [ 8.3e-02 1.7e-01 1.2e-01]
- [ 8.2e-02 2.2e-01 5.1e-02]
- [ 1.9e-01 1.6e-01 1.5e-01]
- [ 7.4e-02 1.9e-01 9.7e-02]
- [ 8.3e-02 2.2e-01 5.6e-02]
- [ 1.3e-01 2.1e-01 1.1e-02]
- [ 1.9e-01 2.1e-01 -9.0e-02]
- [ 2.2e-01 1.8e-01 2.0e-01]
- [ 1.5e-01 2.5e-01 -7.1e-02]
- [ 1.3e-01 2.6e-01 -2.6e-02]
- [ 1.8e-01 2.3e-01 2.4e-01]
- [ 1.6e-01 1.4e-01 1.7e-01]
- [ 2.3e-01 2.6e-01 2.0e-01]
- [ 2.0e-01 3.0e-01 2.4e-01]
- [ 1.1e-01 2.6e-01 2.1e-03]
- [ 2.0e-01 1.9e-01 1.8e-01]
- [ 1.2e-01 2.7e-01 -4.7e-02]
- [ 1.0e-01 1.4e-01 1.4e-01]
- [ 8.1e-02 1.9e-01 5.2e-02]
- [ 2.3e-01 1.8e-01 1.8e-01]
- [ 6.8e-02 2.3e-01 5.3e-02]
- [ 1.1e-01 2.6e-01 1.2e-02]
- [ 1.2e-01 2.7e-01 -4.1e-02]
- [ 1.5e-01 2.4e-01 -5.7e-02]
- [ 1.3e-01 1.7e-01 8.1e-02]
- [ 6.6e-02 2.2e-01 6.1e-02]
- [ 2.1e-01 3.3e-01 2.3e-01]
- [ 1.2e-01 2.7e-01 -3.4e-02]
- [ 1.3e-01 2.0e-01 8.1e-02]
- [ 1.9e-01 1.6e-01 1.9e-01]
- [ 1.2e-01 2.4e-01 -8.1e-03]
- [ 7.6e-02 1.7e-01 9.1e-02]
- [ 1.5e-01 1.5e-01 1.7e-01]
- [ 1.2e-01 1.5e-01 1.2e-01]
- [ 1.2e-01 2.5e-01 1.2e-03]
- [ 2.2e-01 2.4e-01 1.9e-01]
- [ 2.4e-01 2.6e-01 2.2e-01]
- [ 6.6e-02 2.0e-01 4.6e-02]
- [ 1.3e-01 2.6e-01 -6.2e-02]
- [ 6.6e-02 2.2e-01 3.4e-02]
- [ 2.0e-01 1.9e-01 1.9e-01]
- [ 2.2e-01 2.4e-01 2.2e-01]
- [ 9.0e-02 2.6e-01 -1.4e-02]
- [ 1.3e-01 2.1e-01 4.6e-02]
- [ 1.7e-01 1.5e-01 1.8e-01]
- [ 1.4e-01 1.3e-01 1.5e-01]
- [ 1.8e-01 2.3e-01 -6.1e-02]
- [ 2.2e-01 1.8e-01 1.9e-01]
- [ 1.1e-01 1.6e-01 1.1e-01]
- [ 9.2e-02 2.1e-01 6.3e-02]
- [ 1.9e-01 1.7e-01 1.8e-01]
- [ 2.3e-01 2.2e-01 2.2e-01]
- [ 9.3e-02 2.6e-01 -2.5e-03]
- [ 2.1e-01 1.8e-01 1.9e-01]]
+ [[ 0.2 0.3 0.2]
+ [ 0.1 0.3 0.0]
+ [ 0.2 0.1 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 -0.1]
+ [ 0.2 0.1 0.1]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.2 -0.1]
+ [ 0.1 0.3 -0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 -0.1]
+ [ 0.2 0.2 -0.1]
+ [ 0.1 0.1 0.1]
+ [ 0.1 0.1 0.1]
+ [ 0.2 0.2 -0.1]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.1 0.1]
+ [ 0.0 0.2 0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.2 -0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.1 0.3 0.0]
+ [ 0.2 0.3 -0.0]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.3 0.0]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.3 -0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.2 -0.1]
+ [ 0.2 0.1 0.2]
+ [ 0.2 0.3 -0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.3 -0.0]
+ [ 0.1 0.2 -0.1]
+ [ 0.3 0.3 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.1 0.1]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.1 0.1]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.1 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.2 -0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.3 -0.1]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.1 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.3 -0.1]
+ [ 0.1 0.1 0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.3 0.0]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 -0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.3 0.2]
+ [ 0.1 0.3 -0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.1 0.2]
+ [ 0.1 0.2 -0.0]
+ [ 0.1 0.2 0.1]
+ [ 0.1 0.1 0.2]
+ [ 0.1 0.1 0.1]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.3 0.3 0.2]
+ [ 0.1 0.2 0.0]
+ [ 0.1 0.3 -0.1]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.3 -0.0]
+ [ 0.1 0.2 0.0]
+ [ 0.2 0.1 0.2]
+ [ 0.1 0.1 0.1]
+ [ 0.2 0.2 -0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.1 0.1]
+ [ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.2]
+ [ 0.2 0.2 0.2]
+ [ 0.1 0.3 -0.0]
+ [ 0.2 0.2 0.2]]
# ---
# name: test_selection_working[entity_id-4ozs]
[[ 3.6e-01 -1.6e-01 2.5e-01]
diff --git a/tests/__snapshots__/test_ops.ambr b/tests/__snapshots__/test_ops.ambr
index e74455fa..90c16886 100644
--- a/tests/__snapshots__/test_ops.ambr
+++ b/tests/__snapshots__/test_ops.ambr
@@ -1,13 +1,13 @@
# serializer version: 1
# name: test_op_api_cartoon[1BNA]
- [29.5 23.6 29.0 33.5 38.1 34.0 36.6 26.9 37.5 28.6 23.4 33.0 29.6 27.4
- 50.9 34.0 35.3 39.6 31.8 33.9 28.5 42.5 42.5 40.4 34.6 27.7 35.6 31.6
- 36.0 28.7 28.5 38.8 29.7 32.6 26.4 45.3 40.5 26.4 29.2 41.2 36.6 38.0
- 32.5 33.9 28.7 37.6 42.7 27.7 32.0 28.6 32.3 38.5 29.2 31.8 33.9 39.1
- 29.2 39.1 28.7 37.4 34.8 37.6 29.2 35.3 28.0 46.7 46.0 30.1 28.6 29.3
- 26.4 37.4 36.5 40.8 33.9 29.9 27.7 38.8 49.3 26.1 33.9 26.6 29.0 31.5
- 27.5 28.3 30.6 40.8 35.7 35.6 34.5 34.9 35.7 39.1 44.0 33.8 37.0 31.6
- 31.6 47.6]
+ [66.5 44.7 28.9 39.4 34.7 47.8 31.3 64.8 37.9 55.7 31.5 35.5 32.9 56.2
+ 58.7 43.2 39.5 40.7 27.6 32.3 35.4 52.4 35.4 40.6 41.2 49.7 32.6 61.3
+ 51.0 42.3 35.4 37.7 42.7 41.6 48.0 49.5 65.6 48.0 67.1 53.9 28.7 43.0
+ 31.7 32.3 42.3 34.2 48.7 49.7 47.0 55.7 32.0 35.0 67.1 27.6 32.3 28.4
+ 62.9 33.5 42.3 25.0 42.3 34.2 67.1 29.2 48.5 48.1 52.7 72.5 55.7 56.9
+ 48.0 25.0 40.9 31.9 32.3 55.0 44.9 37.7 56.7 40.4 32.3 50.8 28.9 30.5
+ 62.8 52.1 31.7 31.9 36.8 32.6 47.1 43.8 36.8 33.5 63.3 56.2 39.4 40.6
+ 40.6 54.7]
# ---
# name: test_op_api_cartoon[1BNA].1
AttributeError("The selected attribute 'occupancy' does not exist on the mesh.")
@@ -123,7 +123,7 @@
# name: test_op_api_cartoon[1BNA].13
[[ 0.2 0.3 0.1]
[ 0.2 0.2 0.2]
- [ 0.2 0.2 -0.0]
+ [ 0.2 0.2 0.0]
[ 0.2 0.2 0.3]
[ 0.1 0.2 0.0]
[ 0.2 0.3 0.2]
@@ -131,7 +131,7 @@
[ 0.2 0.1 0.2]
[ 0.1 0.2 0.2]
[ 0.1 0.3 0.1]
- [ 0.2 0.2 -0.0]
+ [ 0.2 0.1 -0.0]
[ 0.2 0.2 0.3]
[ 0.1 0.2 0.3]
[ 0.2 0.2 -0.1]
@@ -140,11 +140,11 @@
[ 0.2 0.3 0.2]
[ 0.1 0.2 0.0]
[ 0.2 0.2 -0.0]
- [ 0.1 0.2 0.1]
+ [ 0.1 0.1 0.1]
[ 0.1 0.2 0.3]
[ 0.1 0.1 -0.1]
[ 0.2 0.2 0.0]
- [ 0.2 0.2 0.0]
+ [ 0.2 0.3 0.0]
[ 0.1 0.2 0.2]
[ 0.2 0.2 0.2]
[ 0.1 0.2 0.1]
@@ -159,7 +159,7 @@
[ 0.1 0.1 -0.1]
[ 0.1 0.3 -0.0]
[ 0.2 0.2 0.2]
- [ 0.2 0.2 -0.1]
+ [ 0.2 0.3 -0.1]
[ 0.1 0.1 -0.1]
[ 0.1 0.2 0.0]
[ 0.2 0.1 -0.0]
@@ -167,30 +167,30 @@
[ 0.1 0.1 0.1]
[ 0.1 0.2 0.2]
[ 0.1 0.3 0.1]
- [ 0.1 0.2 -0.0]
+ [ 0.1 0.3 -0.0]
[ 0.2 0.2 0.2]
[ 0.2 0.3 0.2]
[ 0.1 0.3 0.1]
[ 0.1 0.2 0.1]
[ 0.1 0.2 0.1]
[ 0.2 0.2 -0.1]
- [ 0.2 0.2 -0.0]
- [ 0.1 0.2 0.1]
[ 0.2 0.2 0.0]
- [ 0.2 0.3 0.1]
[ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.0]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.3 0.1]
[ 0.1 0.2 0.2]
[ 0.2 0.2 0.0]
[ 0.2 0.3 0.2]
[ 0.1 0.3 0.1]
- [ 0.2 0.2 -0.1]
- [ 0.1 0.2 0.1]
+ [ 0.2 0.3 -0.1]
+ [ 0.0 0.2 0.1]
[ 0.1 0.3 0.1]
[ 0.2 0.1 -0.1]
[ 0.1 0.3 -0.0]
[ 0.2 0.3 -0.1]
[ 0.1 0.3 0.1]
- [ 0.2 0.2 0.2]
+ [ 0.2 0.1 0.2]
[ 0.2 0.2 0.2]
[ 0.2 0.2 -0.0]
[ 0.1 0.2 0.2]
@@ -199,9 +199,9 @@
[ 0.2 0.2 0.2]
[ 0.1 0.3 0.1]
[ 0.1 0.2 0.0]
- [ 0.1 0.2 -0.0]
+ [ 0.1 0.3 -0.0]
[ 0.1 0.2 0.2]
- [ 0.1 0.2 0.1]
+ [ 0.1 0.1 0.1]
[ 0.2 0.2 -0.1]
[ 0.2 0.2 -0.0]
[ 0.1 0.2 0.1]
@@ -218,7 +218,7 @@
[ 0.1 0.3 -0.1]
[ 0.2 0.3 0.0]
[ 0.1 0.2 0.2]
- [ 0.1 0.2 0.1]
+ [ 0.1 0.3 0.1]
[ 0.1 0.3 0.1]
[ 0.1 0.3 -0.0]]
# ---
@@ -253,14 +253,14 @@
AttributeError("The selected attribute 'mass' does not exist on the mesh.")
# ---
# name: test_op_api_cartoon[1BNA].23
- [29.5 23.6 29.0 33.5 38.1 34.0 36.6 26.9 37.5 28.6 23.4 33.0 29.6 27.4
- 50.9 34.0 35.3 39.6 31.8 33.9 28.5 42.5 42.5 40.4 34.6 27.7 35.6 31.6
- 36.0 28.7 28.5 38.8 29.7 32.6 26.4 45.3 40.5 26.4 29.2 41.2 36.6 38.0
- 32.5 33.9 28.7 37.6 42.7 27.7 32.0 28.6 32.3 38.5 29.2 31.8 33.9 39.1
- 29.2 39.1 28.7 37.4 34.8 37.6 29.2 35.3 28.0 46.7 46.0 30.1 28.6 29.3
- 26.4 37.4 36.5 40.8 33.9 29.9 27.7 38.8 49.3 26.1 33.9 26.6 29.0 31.5
- 27.5 28.3 30.6 40.8 35.7 35.6 34.5 34.9 35.7 39.1 44.0 33.8 37.0 31.6
- 31.6 47.6]
+ [66.5 44.7 28.9 39.4 34.7 47.8 31.3 64.8 37.9 55.7 31.5 35.5 32.9 56.2
+ 58.7 43.2 39.5 40.7 27.6 32.3 35.4 52.4 35.4 40.6 41.2 49.7 32.6 61.3
+ 51.0 42.3 35.4 37.7 42.7 41.6 48.0 49.5 65.6 48.0 67.1 53.9 28.7 43.0
+ 31.7 32.3 42.3 34.2 48.7 49.7 47.0 55.7 32.0 35.0 67.1 27.6 32.3 28.4
+ 62.9 33.5 42.3 25.0 42.3 34.2 67.1 29.2 48.5 48.1 52.7 72.5 55.7 56.9
+ 48.0 25.0 40.9 31.9 32.3 55.0 44.9 37.7 56.7 40.4 32.3 50.8 28.9 30.5
+ 62.8 52.1 31.7 31.9 36.8 32.6 47.1 43.8 36.8 33.5 63.3 56.2 39.4 40.6
+ 40.6 54.7]
# ---
# name: test_op_api_cartoon[1BNA].24
AttributeError("The selected attribute 'occupancy' does not exist on the mesh.")
@@ -413,7 +413,7 @@
# name: test_op_api_cartoon[1BNA].36
[[ 0.2 0.3 0.1]
[ 0.2 0.2 0.2]
- [ 0.2 0.2 -0.0]
+ [ 0.2 0.2 0.0]
[ 0.2 0.2 0.3]
[ 0.1 0.2 0.0]
[ 0.2 0.3 0.2]
@@ -421,7 +421,7 @@
[ 0.2 0.1 0.2]
[ 0.1 0.2 0.2]
[ 0.1 0.3 0.1]
- [ 0.2 0.2 -0.0]
+ [ 0.2 0.1 -0.0]
[ 0.2 0.2 0.3]
[ 0.1 0.2 0.3]
[ 0.2 0.2 -0.1]
@@ -430,11 +430,11 @@
[ 0.2 0.3 0.2]
[ 0.1 0.2 0.0]
[ 0.2 0.2 -0.0]
- [ 0.1 0.2 0.1]
+ [ 0.1 0.1 0.1]
[ 0.1 0.2 0.3]
[ 0.1 0.1 -0.1]
[ 0.2 0.2 0.0]
- [ 0.2 0.2 0.0]
+ [ 0.2 0.3 0.0]
[ 0.1 0.2 0.2]
[ 0.2 0.2 0.2]
[ 0.1 0.2 0.1]
@@ -449,7 +449,7 @@
[ 0.1 0.1 -0.1]
[ 0.1 0.3 -0.0]
[ 0.2 0.2 0.2]
- [ 0.2 0.2 -0.1]
+ [ 0.2 0.3 -0.1]
[ 0.1 0.1 -0.1]
[ 0.1 0.2 0.0]
[ 0.2 0.1 -0.0]
@@ -457,30 +457,30 @@
[ 0.1 0.1 0.1]
[ 0.1 0.2 0.2]
[ 0.1 0.3 0.1]
- [ 0.1 0.2 -0.0]
+ [ 0.1 0.3 -0.0]
[ 0.2 0.2 0.2]
[ 0.2 0.3 0.2]
[ 0.1 0.3 0.1]
[ 0.1 0.2 0.1]
[ 0.1 0.2 0.1]
[ 0.2 0.2 -0.1]
- [ 0.2 0.2 -0.0]
- [ 0.1 0.2 0.1]
[ 0.2 0.2 0.0]
- [ 0.2 0.3 0.1]
[ 0.1 0.2 0.1]
+ [ 0.2 0.2 0.0]
+ [ 0.2 0.3 0.0]
+ [ 0.1 0.3 0.1]
[ 0.1 0.2 0.2]
[ 0.2 0.2 0.0]
[ 0.2 0.3 0.2]
[ 0.1 0.3 0.1]
- [ 0.2 0.2 -0.1]
- [ 0.1 0.2 0.1]
+ [ 0.2 0.3 -0.1]
+ [ 0.0 0.2 0.1]
[ 0.1 0.3 0.1]
[ 0.2 0.1 -0.1]
[ 0.1 0.3 -0.0]
[ 0.2 0.3 -0.1]
[ 0.1 0.3 0.1]
- [ 0.2 0.2 0.2]
+ [ 0.2 0.1 0.2]
[ 0.2 0.2 0.2]
[ 0.2 0.2 -0.0]
[ 0.1 0.2 0.2]
@@ -489,9 +489,9 @@
[ 0.2 0.2 0.2]
[ 0.1 0.3 0.1]
[ 0.1 0.2 0.0]
- [ 0.1 0.2 -0.0]
+ [ 0.1 0.3 -0.0]
[ 0.1 0.2 0.2]
- [ 0.1 0.2 0.1]
+ [ 0.1 0.1 0.1]
[ 0.2 0.2 -0.1]
[ 0.2 0.2 -0.0]
[ 0.1 0.2 0.1]
@@ -508,7 +508,7 @@
[ 0.1 0.3 -0.1]
[ 0.2 0.3 0.0]
[ 0.1 0.2 0.2]
- [ 0.1 0.2 0.1]
+ [ 0.1 0.3 0.1]
[ 0.1 0.3 0.1]
[ 0.1 0.3 -0.0]]
# ---
@@ -1326,13 +1326,13 @@
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
# ---
# name: test_op_api_cartoon[8H1B]
- [32.5 14.8 42.2 25.2 17.2 35.9 20.4 64.2 16.1 17.8 31.7 19.0 19.1 16.5
- 30.8 18.9 37.9 20.9 24.5 45.9 25.9 19.3 18.7 16.0 27.0 64.2 19.3 61.7
- 23.1 34.1 26.7 24.2 25.0 38.1 18.8 29.4 25.7 16.9 31.2 16.3 21.7 16.1
- 17.6 19.8 28.9 25.8 41.3 17.7 30.9 28.3 24.0 22.3 21.2 35.1 25.1 16.4
- 18.7 29.2 20.8 22.5 18.6 18.3 22.7 19.0 35.4 22.4 19.8 18.9 17.7 64.2
+ [32.5 14.8 42.2 25.2 17.2 35.9 20.4 66.1 16.1 17.8 31.7 19.0 19.1 16.5
+ 30.8 18.9 37.9 20.9 24.5 44.8 25.9 19.3 18.7 16.0 27.0 66.1 19.3 62.7
+ 23.1 34.1 26.7 24.2 25.0 38.1 18.8 29.4 25.7 16.9 33.1 16.3 21.7 16.1
+ 17.6 19.8 29.5 25.8 41.3 17.7 30.9 28.3 23.5 22.3 21.2 38.6 25.1 16.4
+ 18.7 29.2 20.8 22.5 18.6 18.3 22.7 19.0 34.7 22.4 19.8 18.9 17.7 66.1
21.0 25.0 15.3 38.7 42.9 14.5 18.3 25.4 19.3 28.5 18.7 15.4 21.0 18.6
- 32.4 26.0 16.5 53.8 45.9 42.2 26.6 34.5 32.4 19.1 24.3 18.9 15.4 35.4
+ 32.9 26.0 16.5 56.0 45.9 42.2 26.6 34.5 32.4 19.1 24.3 18.9 15.4 34.7
30.8 19.3]
# ---
# name: test_op_api_cartoon[8H1B].1
@@ -1468,7 +1468,7 @@
[-3.2e-02 2.4e-01 2.2e-01]
[ 1.3e-01 -7.8e-03 2.6e-01]
[-1.2e-01 2.3e-01 1.8e-01]
- [-2.4e-01 -3.6e-02 -1.6e-02]
+ [-2.3e-01 -3.7e-02 -5.2e-03]
[-3.2e-02 -3.7e-02 2.0e-01]
[ 4.3e-02 -1.4e-01 9.4e-02]
[ 1.7e-01 -7.4e-02 1.8e-02]
@@ -1480,15 +1480,15 @@
[ 1.6e-01 -1.3e-01 -3.1e-02]
[-7.1e-02 -1.4e-01 1.1e-01]
[-1.1e-01 -1.4e-01 1.1e-01]
- [-1.3e-01 -1.8e-02 6.8e-02]
+ [-1.4e-01 -1.5e-02 6.4e-02]
[-1.5e-02 2.7e-01 4.3e-01]
[-2.0e-01 1.3e-01 2.7e-01]
[ 2.6e-02 -1.5e-01 2.7e-01]
[-5.0e-02 -1.8e-01 2.0e-01]
[-1.6e-01 9.2e-02 1.2e-01]
- [-2.4e-01 -3.1e-02 -7.8e-04]
+ [-2.3e-01 -3.2e-02 1.0e-02]
[ 8.2e-02 -7.6e-02 2.3e-01]
- [-1.2e-01 9.9e-03 -1.9e-02]
+ [-1.3e-01 1.6e-02 -3.0e-02]
[-7.6e-02 2.4e-01 4.6e-01]
[ 2.1e-01 -1.5e-01 4.8e-02]
[ 1.5e-01 1.1e-02 1.8e-01]
@@ -1499,22 +1499,22 @@
[ 2.1e-01 -2.3e-01 1.3e-01]
[-4.1e-02 2.5e-01 4.3e-01]
[-1.5e-01 1.2e-01 2.2e-01]
- [ 1.1e-02 4.6e-02 4.9e-01]
+ [ 2.2e-03 4.9e-02 4.8e-01]
[-1.8e-02 6.1e-03 3.5e-01]
[ 7.4e-03 2.4e-01 3.7e-01]
[-5.6e-02 1.8e-01 3.6e-01]
[-5.8e-02 -1.3e-02 1.5e-01]
[-1.3e-01 1.6e-01 2.4e-01]
- [ 1.0e-01 8.2e-02 5.1e-01]
+ [ 1.1e-01 7.3e-02 5.2e-01]
[ 7.2e-02 -1.3e-01 7.8e-03]
[-4.2e-02 -2.7e-01 3.8e-02]
[-1.7e-01 1.3e-01 2.7e-01]
[ 1.8e-01 -1.9e-01 2.5e-01]
[ 1.4e-01 -9.4e-02 3.0e-01]
- [ 2.1e-02 -3.6e-02 3.7e-01]
+ [ 2.3e-02 -3.9e-02 3.8e-01]
[ 1.1e-01 -2.2e-01 2.0e-01]
[ 1.0e-02 2.0e-01 1.6e-01]
- [ 3.5e-03 1.8e-02 5.1e-01]
+ [-4.5e-03 2.1e-02 5.0e-01]
[ 9.3e-02 -1.2e-01 -9.1e-03]
[-1.5e-01 -4.7e-03 2.9e-01]
[-4.5e-02 -6.4e-02 1.1e-01]
@@ -1525,12 +1525,12 @@
[-8.9e-02 2.6e-01 3.7e-01]
[-4.2e-02 2.2e-01 4.3e-01]
[ 3.7e-02 -2.0e-01 1.8e-01]
- [-7.1e-02 -7.7e-02 6.3e-02]
+ [-8.2e-02 -7.2e-02 5.6e-02]
[ 1.4e-01 -7.8e-02 2.1e-01]
[-1.9e-01 1.6e-01 2.2e-01]
[-4.8e-02 2.7e-01 3.4e-01]
[ 5.4e-02 -8.8e-02 2.1e-01]
- [-2.6e-01 -4.3e-02 -2.2e-02]
+ [-2.5e-01 -4.4e-02 -1.1e-02]
[-9.4e-02 7.6e-02 1.4e-01]
[-1.6e-02 8.7e-02 1.1e-01]
[-1.5e-01 1.3e-01 2.5e-01]
@@ -1545,10 +1545,10 @@
[-1.6e-01 1.3e-01 3.0e-01]
[ 6.4e-03 1.3e-01 4.4e-01]
[ 6.7e-02 1.3e-01 2.4e-01]
- [ 1.1e-01 -3.2e-02 3.8e-01]
+ [ 1.1e-01 -3.0e-02 3.9e-01]
[ 1.2e-01 -4.2e-03 1.2e-01]
[-1.2e-02 -1.6e-01 2.1e-01]
- [-8.9e-02 -1.4e-01 -7.6e-03]
+ [-7.8e-02 -1.4e-01 1.1e-03]
[ 2.4e-01 -1.4e-01 2.9e-01]
[ 2.1e-01 -1.4e-01 3.1e-01]
[-1.1e-01 1.3e-01 7.9e-02]
@@ -1558,7 +1558,7 @@
[ 1.6e-01 -1.7e-01 5.6e-02]
[-2.6e-02 -4.3e-02 3.5e-01]
[-1.6e-01 1.8e-01 3.0e-01]
- [-9.1e-02 -9.6e-02 6.6e-02]
+ [-9.0e-02 -9.4e-02 7.2e-02]
[-2.1e-02 -2.4e-01 6.0e-02]
[ 2.1e-02 1.8e-01 3.3e-01]]
# ---
@@ -1658,13 +1658,13 @@
12. 12. 12. 12. 12. 12. 12. 0. 12. 12.]
# ---
# name: test_op_api_cartoon[8H1B].23
- [32.5 14.8 42.2 25.2 17.2 35.9 20.4 64.2 16.1 17.8 31.7 19.0 19.1 16.5
- 30.8 18.9 37.9 20.9 24.5 45.9 25.9 19.3 18.7 16.0 27.0 64.2 19.3 61.7
- 23.1 34.1 26.7 24.2 25.0 38.1 18.8 29.4 25.7 16.9 31.2 16.3 21.7 16.1
- 17.6 19.8 28.9 25.8 41.3 17.7 30.9 28.3 24.0 22.3 21.2 35.1 25.1 16.4
- 18.7 29.2 20.8 22.5 18.6 18.3 22.7 19.0 35.4 22.4 19.8 18.9 17.7 64.2
+ [32.5 14.8 42.2 25.2 17.2 35.9 20.4 66.1 16.1 17.8 31.7 19.0 19.1 16.5
+ 30.8 18.9 37.9 20.9 24.5 44.8 25.9 19.3 18.7 16.0 27.0 66.1 19.3 62.7
+ 23.1 34.1 26.7 24.2 25.0 38.1 18.8 29.4 25.7 16.9 33.1 16.3 21.7 16.1
+ 17.6 19.8 29.5 25.8 41.3 17.7 30.9 28.3 23.5 22.3 21.2 38.6 25.1 16.4
+ 18.7 29.2 20.8 22.5 18.6 18.3 22.7 19.0 34.7 22.4 19.8 18.9 17.7 66.1
21.0 25.0 15.3 38.7 42.9 14.5 18.3 25.4 19.3 28.5 18.7 15.4 21.0 18.6
- 32.4 26.0 16.5 53.8 45.9 42.2 26.6 34.5 32.4 19.1 24.3 18.9 15.4 35.4
+ 32.9 26.0 16.5 56.0 45.9 42.2 26.6 34.5 32.4 19.1 24.3 18.9 15.4 34.7
30.8 19.3]
# ---
# name: test_op_api_cartoon[8H1B].24
@@ -1863,7 +1863,7 @@
[-3.2e-02 2.4e-01 2.2e-01]
[ 1.3e-01 -7.8e-03 2.6e-01]
[-1.2e-01 2.3e-01 1.8e-01]
- [-2.4e-01 -3.6e-02 -1.6e-02]
+ [-2.3e-01 -3.7e-02 -5.2e-03]
[-3.2e-02 -3.7e-02 2.0e-01]
[ 4.3e-02 -1.4e-01 9.4e-02]
[ 1.7e-01 -7.4e-02 1.8e-02]
@@ -1875,15 +1875,15 @@
[ 1.6e-01 -1.3e-01 -3.1e-02]
[-7.1e-02 -1.4e-01 1.1e-01]
[-1.1e-01 -1.4e-01 1.1e-01]
- [-1.3e-01 -1.8e-02 6.8e-02]
+ [-1.4e-01 -1.5e-02 6.4e-02]
[-1.5e-02 2.7e-01 4.3e-01]
[-2.0e-01 1.3e-01 2.7e-01]
[ 2.6e-02 -1.5e-01 2.7e-01]
[-5.0e-02 -1.8e-01 2.0e-01]
[-1.6e-01 9.2e-02 1.2e-01]
- [-2.4e-01 -3.1e-02 -7.8e-04]
+ [-2.3e-01 -3.2e-02 1.0e-02]
[ 8.2e-02 -7.6e-02 2.3e-01]
- [-1.2e-01 9.9e-03 -1.9e-02]
+ [-1.3e-01 1.6e-02 -3.0e-02]
[-7.6e-02 2.4e-01 4.6e-01]
[ 2.1e-01 -1.5e-01 4.8e-02]
[ 1.5e-01 1.1e-02 1.8e-01]
@@ -1894,22 +1894,22 @@
[ 2.1e-01 -2.3e-01 1.3e-01]
[-4.1e-02 2.5e-01 4.3e-01]
[-1.5e-01 1.2e-01 2.2e-01]
- [ 1.1e-02 4.6e-02 4.9e-01]
+ [ 2.2e-03 4.9e-02 4.8e-01]
[-1.8e-02 6.1e-03 3.5e-01]
[ 7.4e-03 2.4e-01 3.7e-01]
[-5.6e-02 1.8e-01 3.6e-01]
[-5.8e-02 -1.3e-02 1.5e-01]
[-1.3e-01 1.6e-01 2.4e-01]
- [ 1.0e-01 8.2e-02 5.1e-01]
+ [ 1.1e-01 7.3e-02 5.2e-01]
[ 7.2e-02 -1.3e-01 7.8e-03]
[-4.2e-02 -2.7e-01 3.8e-02]
[-1.7e-01 1.3e-01 2.7e-01]
[ 1.8e-01 -1.9e-01 2.5e-01]
[ 1.4e-01 -9.4e-02 3.0e-01]
- [ 2.1e-02 -3.6e-02 3.7e-01]
+ [ 2.3e-02 -3.9e-02 3.8e-01]
[ 1.1e-01 -2.2e-01 2.0e-01]
[ 1.0e-02 2.0e-01 1.6e-01]
- [ 3.5e-03 1.8e-02 5.1e-01]
+ [-4.5e-03 2.1e-02 5.0e-01]
[ 9.3e-02 -1.2e-01 -9.1e-03]
[-1.5e-01 -4.7e-03 2.9e-01]
[-4.5e-02 -6.4e-02 1.1e-01]
@@ -1920,12 +1920,12 @@
[-8.9e-02 2.6e-01 3.7e-01]
[-4.2e-02 2.2e-01 4.3e-01]
[ 3.7e-02 -2.0e-01 1.8e-01]
- [-7.1e-02 -7.7e-02 6.3e-02]
+ [-8.2e-02 -7.2e-02 5.6e-02]
[ 1.4e-01 -7.8e-02 2.1e-01]
[-1.9e-01 1.6e-01 2.2e-01]
[-4.8e-02 2.7e-01 3.4e-01]
[ 5.4e-02 -8.8e-02 2.1e-01]
- [-2.6e-01 -4.3e-02 -2.2e-02]
+ [-2.5e-01 -4.4e-02 -1.1e-02]
[-9.4e-02 7.6e-02 1.4e-01]
[-1.6e-02 8.7e-02 1.1e-01]
[-1.5e-01 1.3e-01 2.5e-01]
@@ -1940,10 +1940,10 @@
[-1.6e-01 1.3e-01 3.0e-01]
[ 6.4e-03 1.3e-01 4.4e-01]
[ 6.7e-02 1.3e-01 2.4e-01]
- [ 1.1e-01 -3.2e-02 3.8e-01]
+ [ 1.1e-01 -3.0e-02 3.9e-01]
[ 1.2e-01 -4.2e-03 1.2e-01]
[-1.2e-02 -1.6e-01 2.1e-01]
- [-8.9e-02 -1.4e-01 -7.6e-03]
+ [-7.8e-02 -1.4e-01 1.1e-03]
[ 2.4e-01 -1.4e-01 2.9e-01]
[ 2.1e-01 -1.4e-01 3.1e-01]
[-1.1e-01 1.3e-01 7.9e-02]
@@ -1953,7 +1953,7 @@
[ 1.6e-01 -1.7e-01 5.6e-02]
[-2.6e-02 -4.3e-02 3.5e-01]
[-1.6e-01 1.8e-01 3.0e-01]
- [-9.1e-02 -9.6e-02 6.6e-02]
+ [-9.0e-02 -9.4e-02 7.2e-02]
[-2.1e-02 -2.4e-01 6.0e-02]
[ 2.1e-02 1.8e-01 3.3e-01]]
# ---
@@ -2975,7 +2975,7 @@
[0.6 0.3 0.5]
[0.4 0.3 0.5]
[0.7 0.5 0.6]
- [1.3 0.3 0.7]
+ [1.4 0.3 0.7]
[1.0 0.6 0.5]
[1.0 0.4 0.4]
[0.4 0.2 0.4]
@@ -2994,20 +2994,20 @@
[1.2 0.5 0.6]
[0.9 0.2 0.6]
[1.3 0.5 0.7]
- [0.7 0.5 0.5]
+ [0.7 0.5 0.4]
[0.7 0.4 0.8]
[0.9 0.3 0.4]
[0.8 0.5 0.4]
[0.6 0.3 0.3]
[0.7 0.3 0.7]
[1.1 0.6 0.4]
- [1.1 0.3 0.7]
+ [1.2 0.3 0.7]
[0.7 0.4 0.8]
[1.0 0.4 0.5]
[0.5 0.4 0.5]
[0.5 0.3 0.4]
[1.1 0.5 0.4]
- [0.9 0.2 0.6]
+ [1.0 0.2 0.6]
[1.1 0.5 0.7]
[1.0 0.3 0.4]
[1.2 0.5 0.4]
@@ -3029,17 +3029,17 @@
[0.6 0.5 0.7]
[0.5 0.2 0.5]
[1.1 0.4 0.4]
- [1.0 0.3 0.4]
- [1.0 0.5 0.5]
- [1.1 0.5 0.5]
+ [1.0 0.3 0.3]
+ [1.0 0.5 0.6]
+ [1.1 0.6 0.6]
[1.2 0.6 0.5]
- [0.9 0.4 0.4]
+ [0.9 0.3 0.4]
[0.8 0.6 0.5]
[1.2 0.3 0.6]
- [0.4 0.4 0.3]
+ [0.4 0.3 0.3]
[0.9 0.5 0.7]
[1.2 0.5 0.7]
- [1.1 0.7 0.6]
+ [1.0 0.7 0.6]
[0.7 0.5 0.4]
[1.3 0.5 0.7]
[0.9 0.2 0.6]
@@ -3049,21 +3049,21 @@
[1.1 0.6 0.5]
[0.6 0.5 0.4]
[1.1 0.5 0.6]
- [1.1 0.5 0.8]
- [1.4 0.3 0.7]
+ [1.1 0.6 0.7]
+ [1.4 0.4 0.7]
[1.0 0.3 0.4]
[1.2 0.5 0.6]
[0.5 0.5 0.5]
[0.8 0.4 0.8]
- [0.9 0.3 0.5]
+ [1.0 0.3 0.5]
[1.2 0.4 0.7]
- [1.2 0.3 0.7]
+ [1.2 0.2 0.7]
[0.7 0.4 0.7]
[0.5 0.2 0.5]
[0.4 0.2 0.4]
[0.7 0.6 0.5]
[0.9 0.2 0.6]
- [1.1 0.6 0.4]
+ [1.1 0.5 0.4]
[0.8 0.4 0.8]
[0.8 0.2 0.6]
[0.5 0.4 0.5]
@@ -3323,7 +3323,7 @@
[0.6 0.3 0.5]
[0.4 0.3 0.5]
[0.7 0.5 0.6]
- [1.3 0.3 0.7]
+ [1.4 0.3 0.7]
[1.0 0.6 0.5]
[1.0 0.4 0.4]
[0.4 0.2 0.4]
@@ -3342,20 +3342,20 @@
[1.2 0.5 0.6]
[0.9 0.2 0.6]
[1.3 0.5 0.7]
- [0.7 0.5 0.5]
+ [0.7 0.5 0.4]
[0.7 0.4 0.8]
[0.9 0.3 0.4]
[0.8 0.5 0.4]
[0.6 0.3 0.3]
[0.7 0.3 0.7]
[1.1 0.6 0.4]
- [1.1 0.3 0.7]
+ [1.2 0.3 0.7]
[0.7 0.4 0.8]
[1.0 0.4 0.5]
[0.5 0.4 0.5]
[0.5 0.3 0.4]
[1.1 0.5 0.4]
- [0.9 0.2 0.6]
+ [1.0 0.2 0.6]
[1.1 0.5 0.7]
[1.0 0.3 0.4]
[1.2 0.5 0.4]
@@ -3377,17 +3377,17 @@
[0.6 0.5 0.7]
[0.5 0.2 0.5]
[1.1 0.4 0.4]
- [1.0 0.3 0.4]
- [1.0 0.5 0.5]
- [1.1 0.5 0.5]
+ [1.0 0.3 0.3]
+ [1.0 0.5 0.6]
+ [1.1 0.6 0.6]
[1.2 0.6 0.5]
- [0.9 0.4 0.4]
+ [0.9 0.3 0.4]
[0.8 0.6 0.5]
[1.2 0.3 0.6]
- [0.4 0.4 0.3]
+ [0.4 0.3 0.3]
[0.9 0.5 0.7]
[1.2 0.5 0.7]
- [1.1 0.7 0.6]
+ [1.0 0.7 0.6]
[0.7 0.5 0.4]
[1.3 0.5 0.7]
[0.9 0.2 0.6]
@@ -3397,21 +3397,21 @@
[1.1 0.6 0.5]
[0.6 0.5 0.4]
[1.1 0.5 0.6]
- [1.1 0.5 0.8]
- [1.4 0.3 0.7]
+ [1.1 0.6 0.7]
+ [1.4 0.4 0.7]
[1.0 0.3 0.4]
[1.2 0.5 0.6]
[0.5 0.5 0.5]
[0.8 0.4 0.8]
- [0.9 0.3 0.5]
+ [1.0 0.3 0.5]
[1.2 0.4 0.7]
- [1.2 0.3 0.7]
+ [1.2 0.2 0.7]
[0.7 0.4 0.7]
[0.5 0.2 0.5]
[0.4 0.2 0.4]
[0.7 0.6 0.5]
[0.9 0.2 0.6]
- [1.1 0.6 0.4]
+ [1.1 0.5 0.4]
[0.8 0.4 0.8]
[0.8 0.2 0.6]
[0.5 0.4 0.5]
diff --git a/tests/__snapshots__/test_pdbx.ambr b/tests/__snapshots__/test_pdbx.ambr
index e6115bf1..a51dac7c 100644
--- a/tests/__snapshots__/test_pdbx.ambr
+++ b/tests/__snapshots__/test_pdbx.ambr
@@ -7,16 +7,5 @@
# name: test_secondary_structure_no_helix
[2 2 3 3 3 2 2 3 3 2 3 2 3 2 3 3 2 2 2 3 2 2 3 2 2 2 2 2 2 2 2 3 2 3 2 2 2
3 2 2 3 2 2 2 2 2 2 2 2 3 2 3 3 3 2 2 2 2 3 3 2 3 2 3 3 2 2 3 3 2 2 2 2 2
- 3 3 3 2 3 3 2 2 2 3 2 2 2 3 2 3 2 3 3 3 2 2 3 3 3 2 2 2 2 3 2 3 2 2 3 2 2
- 2 3 3 2 2 2 3 3 3 3 3 3 3 3 3 2 3 3 2 2 2 3 2 2 2 3 2 2 3 3 2 2 3 3 3 2 3
- 3 2 2 3 2 2 2 2 2 3 2 3 2 2 3 2 2 2 3 3 2 2 3 3 3 3 3 3 3 3 2 2 3 2 2 2 3
- 3 2 2 3 2 3 3 2 3 3 3 3 3 3 2 3 2 3 2 3 3 2 3 2 2 3 2 2 2 2 3 2 2 3 3 3 3
- 3 2 2 2 3 2 3 2 3 2 2 3 2 3 2 2 3 3 2 3 3 2 3 3 3 3 3 2 2 3 3 2 3 3 3 2 3
- 3 2 2 2 3 2 2 3 2 2 2 3 3 3 2 3 2 3 2 3 3 2 2 2 2 2 2 2 3 2 2 3 2 2 3 2 2
- 2 3 3 2 2 2 2 2 2 2 3 2 3 2 3 3 2 3 3 3 2 2 3 3 2 3 3 2 3 2 2 2 2 2 3 2 2
- 2 2 3 2 3 3 3 2 3 3 2 2 2 2 2 2 3 2 2 3 3 3 3 3 3 2 2 2 2 2 2 2 3 3 3 3 2
- 3 2 3 2 3 2 3 2 2 3 3 2 2 3 3 3 3 3 3 3 3 2 3 2 2 2 2 2 3 3 2 3 3 2 2 2 3
- 2 2 3 2 3 2 3 2 3 2 2 2 2 2 2 3 3 2 3 2 3 3 2 3 2 2 3 2 3 3 3 3 3 2 2 2 3
- 2 2 3 3 3 2 3 2 2 2 3 3 2 3 3 2 3 2 3 3 3 2 2 3 2 2 3 2 3 3 3 3 2 2 2 3 3
- 3 2 2 2 2 2 3 2 2 2 2 3 3 2 3 2 3 3 3]
+ 3 3 3 2 3 3 2 2 2 3 2 2 2 3 2 3 2 3 3 3 2 2 3 3 3 2]
# ---
diff --git a/tests/__snapshots__/test_trajectory.ambr b/tests/__snapshots__/test_trajectory.ambr
new file mode 100644
index 00000000..79b44d85
--- /dev/null
+++ b/tests/__snapshots__/test_trajectory.ambr
@@ -0,0 +1,4447 @@
+# serializer version: 1
+# name: TestTrajectory.test_correct_periodic
+ [[1.5 1.1 1.0]
+ [1.4 1.1 1.0]
+ [1.4 1.1 1.0]
+ ...
+ [1.3 1.4 0.6]
+ [0.0 0.9 1.2]
+ [2.6 2.3 0.4]]
+# ---
+# name: TestTrajectory.test_save_persistance
+ [[0.4 0.3 0.5]
+ [0.4 0.3 0.5]
+ [0.4 0.3 0.5]
+ ...
+ [1.3 0.3 0.6]
+ [1.3 0.4 0.6]
+ [1.3 0.4 0.6]]
+# ---
+# name: TestTrajectory.test_trajectory_update
+ [[0.4 0.3 0.5]
+ [0.4 0.3 0.5]
+ [0.4 0.3 0.5]
+ ...
+ [1.3 0.3 0.6]
+ [1.3 0.4 0.6]
+ [1.3 0.4 0.6]]
+# ---
+# name: TestTrajectory.test_trajectory_update.1
+ [[0.4 0.3 0.5]
+ [0.4 0.3 0.5]
+ [0.4 0.3 0.5]
+ ...
+ [1.3 0.3 0.6]
+ [1.3 0.4 0.6]
+ [1.3 0.4 0.6]]
+# ---
+# name: test_martini[pent/TOPOL2.pdb]
+ [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
+# ---
+# name: test_martini[pent/TOPOL2.pdb].1
+ [10.8 32.1 10.8 32.1 10.8 32.1 10.8 10.8 32.1 10.8 32.1 32.1 10.8 32.1
+ 10.8 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 10.8 10.8
+ 32.1 10.8 10.8 10.8 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1
+ 10.8 32.1 10.8 32.1 10.8 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8
+ 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 10.8 10.8 32.1 10.8 32.1
+ 10.8 32.1 10.8 10.8 32.1 10.8 10.8 32.1 10.8 10.8 10.8 32.1 10.8 32.1
+ 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 32.1 32.1
+ 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8
+ 32.1 10.8 32.1 10.8 10.8 32.1 10.8 32.1 10.8 10.8 32.1 10.8 32.1 32.1
+ 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8
+ 32.1 10.8 32.1 10.8 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 32.1 32.1
+ 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 10.8 32.1 10.8 32.1 32.1
+ 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8
+ 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8
+ 32.1 32.1 32.1 10.8 32.1 10.8 10.8 32.1 32.1 32.1 32.1 10.8 32.1 10.8
+ 10.8 32.1 10.8 32.1 10.8 32.1 32.1 10.8 32.1 10.8 32.1 32.1 10.8 32.1
+ 10.8 32.1 10.8 32.1 10.8 10.8 10.8 32.1 10.8 10.8 32.1 32.1 32.1 10.8
+ 32.1 10.8 10.8 10.8 32.1 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1
+ 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 10.8 32.1 32.1 32.1 10.8
+ 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1
+ 10.8 10.8 32.1 10.8 10.8 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1
+ 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8 10.8 32.1 10.8 32.1 10.8
+ 32.1 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1
+ 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1
+ 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 32.1
+ 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 32.1 10.8 32.1 10.8 32.1
+ 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 32.1 10.8 32.1 10.8 32.1 10.8
+ 32.1 10.8 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8
+ 32.1 10.8 32.1 32.1 10.8 32.1 10.8 10.8 10.8 10.8 32.1 10.8 10.8 32.1
+ 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8 10.8 10.8 32.1
+ 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8
+ 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8
+ 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8
+ 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 32.1 10.8 32.1 10.8 32.1
+ 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8
+ 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8
+ 32.1 10.8 32.1 10.8 32.1 10.8 32.1 32.1 10.8 10.8 32.1 10.8 32.1 10.8
+ 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 10.8 32.1 10.8 32.1
+ 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1
+ 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8 10.8 32.1 32.1
+ 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 10.8 32.1 32.1 10.8 32.1
+ 10.8 32.1 10.8 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8
+ 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 10.8 32.1 32.1 10.8
+ 32.1 10.8 32.1 32.1 10.8 10.8 32.1 10.8 32.1 10.8 32.1 10.8 10.8 32.1
+ 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1
+ 10.8 32.1 10.8 10.8 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 32.1
+ 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 10.8 32.1 10.8 10.8
+ 32.1 10.8 32.1 10.8 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8 32.1
+ 10.8 10.8 10.8 32.1 10.8 32.1 10.8 32.1 32.1 32.1 32.1 10.8 32.1 32.1
+ 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 32.1
+ 32.1 10.8 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1
+ 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1
+ 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1
+ 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 10.8 32.1 10.8 32.1 10.8
+ 32.1 10.8 10.8 32.1 10.8 10.8 32.1 10.8 10.8 32.1 10.8 10.8 32.1 10.8
+ 32.1 32.1 32.1 10.8 32.1 10.8 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1
+ 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8
+ 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8 10.8 32.1 10.8 32.1 10.8 32.1
+ 10.8 32.1 10.8 32.1 10.8 32.1 32.1 32.1 32.1 10.8 32.1 32.1 10.8 32.1
+ 10.8 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8 10.8 32.1 10.8 32.1 10.8
+ 32.1 10.8 32.1 10.8 32.1 10.8 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1
+ 10.8 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8
+ 32.1 10.8 10.8 32.1 32.1 32.1 10.8 10.8 32.1 10.8 32.1 10.8 32.1 10.8
+ 32.1 10.8 32.1 32.1 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8
+ 32.1 32.1 10.8 32.1 10.8 32.1 10.8 10.8 32.1 10.8 10.8 10.8 32.1 32.1
+ 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8 32.1 10.8
+ 32.1 10.8 32.1 10.8 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8
+ 32.1 32.1 32.1 10.8 32.1 10.8 10.8 32.1 10.8 32.1 10.8 32.1 10.8 10.8
+ 32.1 10.8 32.1 10.8 32.1 10.8 10.8 32.1 10.8 10.8 10.8 32.1 10.8 32.1
+ 10.8 32.1 32.1 32.1 10.8 32.1 32.1 32.1 10.8 32.1 10.8 32.1 10.8 32.1
+ 10.8 32.1 10.8 32.1 10.8 10.8 32.1 32.1 10.8 32.1 10.8 32.1 10.8 10.8
+ 32.1 10.8 32.1 32.1 32.1 10.8]
+# ---
+# name: test_martini[pent/TOPOL2.pdb].10
+ [[ 1.7 1.3 1.0]
+ [ 1.7 1.3 1.0]
+ [ 1.7 1.3 1.0]
+ ...
+ [ 1.4 1.2 1.8]
+ [ 0.9 2.3 0.7]
+ [ 1.9 1.9 -0.1]]
+# ---
+# name: test_martini[pent/TOPOL2.pdb].11
+ [ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True]
+# ---
+# name: test_martini[pent/TOPOL2.pdb].12
+ [ True False True False True False True True False True False False
+ True False True True False True False True False True False True
+ False True True True False True True True True False True False
+ True False True False True False True False True False True True
+ False True False True False True False True True False True False
+ True False True False True True True False True False True False
+ True True False True True False True True True False True False
+ True False True False True False True False True False True False
+ False False False True False True False True False True False True
+ False False False True False True False True True False True False
+ True True False True False False False True False True False True
+ False True False True False True False True False True False True
+ True False True False True False True False False False True False
+ True False True False True False True True False True False False
+ False True False True False True False True False False False True
+ False True False True False False False True False True False True
+ False True False True False False False True False True True False
+ False False False True False True True False True False True False
+ False True False True False False True False True False True False
+ True True True False True True False False False True False True
+ True True False False True False True False True False True False
+ True False True False True False True False True True False False
+ False True True False True False False False True False True False
+ True False True False True True False True True False True False
+ True False False False True False True False False False True False
+ True False True True False True False True False False True False
+ True False True False True False True False True False True False
+ True False True False True False True False True False True False
+ False True False True False True False True False False False True
+ False False False True False True False True False True False False
+ True False True False True False True False True False True False
+ False True False True False True False True False True False True
+ False False False True False True False True False True False False
+ True False True True True True False True True False True False
+ True False False False True False True False True True True False
+ False True False True False True False True False True False True
+ False True False True False True False False False True False True
+ False False False True False True False False False True False True
+ False True False True False True False True False True False True
+ False True False False True False True False False True False True
+ False False False True False True False True False True False True
+ False True False True False True False True False True False True
+ False True False True False True False False True True False True
+ False True False True False True False True False True False True
+ True False True False True False True False True False True False
+ True False True False True False True False True False False False
+ True False True False True True False False True False True False
+ True False True False True True False False True False True False
+ True True False True False True False True False True False True
+ False True False True False False False True False True True False
+ False True False True False False True True False True False True
+ False True True False True False True False True False True False
+ True False True False True False True False True True False True
+ False True False False False True False False False True False True
+ False False False True False True True False True True False True
+ False True True False False False True False True False True False
+ True True True False True False True False False False False True
+ False False False True False True False True False True False True
+ False True False False False True True False False False True False
+ True False True False True False True False True False False False
+ True False True False True False True False True False True False
+ True False True False True False False False True False True False
+ True False False False True False True True False True False True
+ False True True False True True False True True False True True
+ False True False False False True False True True False True False
+ True False True False False False False True False True False True
+ False True False True False True False False False True False True
+ False True True False True False True False True False True False
+ True False False False False True False False True False True False
+ True False True False False False True True False True False True
+ False True False True False True True False True False False False
+ True False True True False True False True False True False False
+ False True False True False True True False False False True True
+ False True False True False True False True False False False True
+ False False False True False True False True False False True False
+ True False True True False True True True False False False True
+ False True False True False True False True False True False True
+ False True False True False True False False False True False True
+ False True False False False True False True True False True False
+ True False True True False True False True False True True False
+ True True True False True False True False False False True False
+ False False True False True False True False True False True False
+ True True False False True False True False True True False True
+ False False False True]
+# ---
+# name: test_martini[pent/TOPOL2.pdb].13
+ [ True False True False True False True True False True False False
+ True False True True False True False True False True False True
+ False True True True False True True True True False True False
+ True False True False True False True False True False True True
+ False True False True False True False True True False True False
+ True False True False True True True False True False True False
+ True True False True True False True True True False True False
+ True False True False True False True False True False True False
+ False False False True False True False True False True False True
+ False False False True False True False True True False True False
+ True True False True False False False True False True False True
+ False True False True False True False True False True False True
+ True False True False True False True False False False True False
+ True False True False True False True True False True False False
+ False True False True False True False True False False False True
+ False True False True False False False True False True False True
+ False True False True False False False True False True True False
+ False False False True False True True False True False True False
+ False True False True False False True False True False True False
+ True True True False True True False False False True False True
+ True True False False True False True False True False True False
+ True False True False True False True False True True False False
+ False True True False True False False False True False True False
+ True False True False True True False True True False True False
+ True False False False True False True False False False True False
+ True False True True False True False True False False True False
+ True False True False True False True False True False True False
+ True False True False True False True False True False True False
+ False True False True False True False True False False False True
+ False False False True False True False True False True False False
+ True False True False True False True False True False True False
+ False True False True False True False True False True False True
+ False False False True False True False True False True False False
+ True False True True True True False True True False True False
+ True False False False True False True False True True True False
+ False True False True False True False True False True False True
+ False True False True False True False False False True False True
+ False False False True False True False False False True False True
+ False True False True False True False True False True False True
+ False True False False True False True False False True False True
+ False False False True False True False True False True False True
+ False True False True False True False True False True False True
+ False True False True False True False False True True False True
+ False True False True False True False True False True False True
+ True False True False True False True False True False True False
+ True False True False True False True False True False False False
+ True False True False True True False False True False True False
+ True False True False True True False False True False True False
+ True True False True False True False True False True False True
+ False True False True False False False True False True True False
+ False True False True False False True True False True False True
+ False True True False True False True False True False True False
+ True False True False True False True False True True False True
+ False True False False False True False False False True False True
+ False False False True False True True False True True False True
+ False True True False False False True False True False True False
+ True True True False True False True False False False False True
+ False False False True False True False True False True False True
+ False True False False False True True False False False True False
+ True False True False True False True False True False False False
+ True False True False True False True False True False True False
+ True False True False True False False False True False True False
+ True False False False True False True True False True False True
+ False True True False True True False True True False True True
+ False True False False False True False True True False True False
+ True False True False False False False True False True False True
+ False True False True False True False False False True False True
+ False True True False True False True False True False True False
+ True False False False False True False False True False True False
+ True False True False False False True True False True False True
+ False True False True False True True False True False False False
+ True False True True False True False True False True False False
+ False True False True False True True False False False True True
+ False True False True False True False True False False False True
+ False False False True False True False True False False True False
+ True False True True False True True True False False False True
+ False True False True False True False True False True False True
+ False True False True False True False False False True False True
+ False True False False False True False True True False True False
+ True False True True False True False True False True True False
+ True True True False True False True False False False True False
+ False False True False True False True False True False True False
+ True True False False True False True False True True False True
+ False False False True]
+# ---
+# name: test_martini[pent/TOPOL2.pdb].14
+ [False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False]
+# ---
+# name: test_martini[pent/TOPOL2.pdb].15
+ [False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False]
+# ---
+# name: test_martini[pent/TOPOL2.pdb].16
+ [False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False]
+# ---
+# name: test_martini[pent/TOPOL2.pdb].17
+ [ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True]
+# ---
+# name: test_martini[pent/TOPOL2.pdb].18
+ []
+# ---
+# name: test_martini[pent/TOPOL2.pdb].19
+ [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
+ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
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+# ---
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+# ---
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+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False]
+# ---
+# name: test_martini[pent/TOPOL2.pdb].34
+ [False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
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+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False]
+# ---
+# name: test_martini[pent/TOPOL2.pdb].35
+ [False False False False False False False False False False False False
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+ False False False False False False False False False False False False
+ False False False False]
+# ---
+# name: test_martini[pent/TOPOL2.pdb].36
+ [ True True True True True True True True True True True True
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+# ---
+# name: test_martini[pent/TOPOL2.pdb].37
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+# ---
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+# ---
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+# ---
+# name: test_martini[pent/TOPOL2.pdb].8
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+# ---
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+ 72. 72. 72. 45. 45. 45. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 45. 45.
+ 45. 72. 72. 72. 72. 72. 72. 45. 45. 45. 72. 72. 72. 72. 72. 72. 72. 72.
+ 72. 72. 45. 45. 45. 72. 45. 45. 45. 72. 72. 72. 72. 72. 72. 72. 72. 72.
+ 72. 72. 72. 72. 72. 72. 72. 72. 45. 45. 45. 72. 72. 72. 72. 72. 72. 72.
+ 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 45. 45. 45. 72. 72. 72.
+ 72. 72. 45. 45. 45. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72.
+ 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 45. 45. 45. 72. 45.
+ 45. 45. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72. 72.
+ 72. 72. 72. 72. 72. 72. 45. 45. 45. 72.]
+# ---
+# name: test_martini[pent/prot_ion.tpr].10
+ [[ 1.7 1.3 1.0]
+ [ 1.7 1.3 1.0]
+ [ 1.7 1.3 1.0]
+ ...
+ [ 1.4 1.2 1.8]
+ [ 0.9 2.3 0.7]
+ [ 1.9 1.9 -0.1]]
+# ---
+# name: test_martini[pent/prot_ion.tpr].11
+ [ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True]
+# ---
+# name: test_martini[pent/prot_ion.tpr].12
+ [ True False True False True False True True False True False False
+ True False True True False True False True False True False True
+ False True True True False True True True True False True False
+ True False True False True False True False True False True True
+ False True False True False True False True True False True False
+ True False True False True True True False True False True False
+ True True False True True False True True True False True False
+ True False True False True False True False True False True False
+ False False False True False True False True False True False True
+ False False False True False True False True True False True False
+ True True False True False False False True False True False True
+ False True False True False True False True False True False True
+ True False True False True False True False False False True False
+ True False True False True False True True False True False False
+ False True False True False True False True False False False True
+ False True False True False False False True False True False True
+ False True False True False False False True False True True False
+ False False False True False True True False True False True False
+ False True False True False False True False True False True False
+ True True True False True True False False False True False True
+ True True False False True False True False True False True False
+ True False True False True False True False True True False False
+ False True True False True False False False True False True False
+ True False True False True True False True True False True False
+ True False False False True False True False False False True False
+ True False True True False True False True False False True False
+ True False True False True False True False True False True False
+ True False True False True False True False True False True False
+ False True False True False True False True False False False True
+ False False False True False True False True False True False False
+ True False True False True False True False True False True False
+ False True False True False True False True False True False True
+ False False False True False True False True False True False False
+ True False True True True True False True True False True False
+ True False False False True False True False True True True False
+ False True False True False True False True False True False True
+ False True False True False True False False False True False True
+ False False False True False True False False False True False True
+ False True False True False True False True False True False True
+ False True False False True False True False False True False True
+ False False False True False True False True False True False True
+ False True False True False True False True False True False True
+ False True False True False True False False True True False True
+ False True False True False True False True False True False True
+ True False True False True False True False True False True False
+ True False True False True False True False True False False False
+ True False True False True True False False True False True False
+ True False True False True True False False True False True False
+ True True False True False True False True False True False True
+ False True False True False False False True False True True False
+ False True False True False False True True False True False True
+ False True True False True False True False True False True False
+ True False True False True False True False True True False True
+ False True False False False True False False False True False True
+ False False False True False True True False True True False True
+ False True True False False False True False True False True False
+ True True True False True False True False False False False True
+ False False False True False True False True False True False True
+ False True False False False True True False False False True False
+ True False True False True False True False True False False False
+ True False True False True False True False True False True False
+ True False True False True False False False True False True False
+ True False False False True False True True False True False True
+ False True True False True True False True True False True True
+ False True False False False True False True True False True False
+ True False True False False False False True False True False True
+ False True False True False True False False False True False True
+ False True True False True False True False True False True False
+ True False False False False True False False True False True False
+ True False True False False False True True False True False True
+ False True False True False True True False True False False False
+ True False True True False True False True False True False False
+ False True False True False True True False False False True True
+ False True False True False True False True False False False True
+ False False False True False True False True False False True False
+ True False True True False True True True False False False True
+ False True False True False True False True False True False True
+ False True False True False True False False False True False True
+ False True False False False True False True True False True False
+ True False True True False True False True False True True False
+ True True True False True False True False False False True False
+ False False True False True False True False True False True False
+ True True False False True False True False True True False True
+ False False False True]
+# ---
+# name: test_martini[pent/prot_ion.tpr].13
+ [ True False True False True False True True False True False False
+ True False True True False True False True False True False True
+ False True True True False True True True True False True False
+ True False True False True False True False True False True True
+ False True False True False True False True True False True False
+ True False True False True True True False True False True False
+ True True False True True False True True True False True False
+ True False True False True False True False True False True False
+ False False False True False True False True False True False True
+ False False False True False True False True True False True False
+ True True False True False False False True False True False True
+ False True False True False True False True False True False True
+ True False True False True False True False False False True False
+ True False True False True False True True False True False False
+ False True False True False True False True False False False True
+ False True False True False False False True False True False True
+ False True False True False False False True False True True False
+ False False False True False True True False True False True False
+ False True False True False False True False True False True False
+ True True True False True True False False False True False True
+ True True False False True False True False True False True False
+ True False True False True False True False True True False False
+ False True True False True False False False True False True False
+ True False True False True True False True True False True False
+ True False False False True False True False False False True False
+ True False True True False True False True False False True False
+ True False True False True False True False True False True False
+ True False True False True False True False True False True False
+ False True False True False True False True False False False True
+ False False False True False True False True False True False False
+ True False True False True False True False True False True False
+ False True False True False True False True False True False True
+ False False False True False True False True False True False False
+ True False True True True True False True True False True False
+ True False False False True False True False True True True False
+ False True False True False True False True False True False True
+ False True False True False True False False False True False True
+ False False False True False True False False False True False True
+ False True False True False True False True False True False True
+ False True False False True False True False False True False True
+ False False False True False True False True False True False True
+ False True False True False True False True False True False True
+ False True False True False True False False True True False True
+ False True False True False True False True False True False True
+ True False True False True False True False True False True False
+ True False True False True False True False True False False False
+ True False True False True True False False True False True False
+ True False True False True True False False True False True False
+ True True False True False True False True False True False True
+ False True False True False False False True False True True False
+ False True False True False False True True False True False True
+ False True True False True False True False True False True False
+ True False True False True False True False True True False True
+ False True False False False True False False False True False True
+ False False False True False True True False True True False True
+ False True True False False False True False True False True False
+ True True True False True False True False False False False True
+ False False False True False True False True False True False True
+ False True False False False True True False False False True False
+ True False True False True False True False True False False False
+ True False True False True False True False True False True False
+ True False True False True False False False True False True False
+ True False False False True False True True False True False True
+ False True True False True True False True True False True True
+ False True False False False True False True True False True False
+ True False True False False False False True False True False True
+ False True False True False True False False False True False True
+ False True True False True False True False True False True False
+ True False False False False True False False True False True False
+ True False True False False False True True False True False True
+ False True False True False True True False True False False False
+ True False True True False True False True False True False False
+ False True False True False True True False False False True True
+ False True False True False True False True False False False True
+ False False False True False True False True False False True False
+ True False True True False True True True False False False True
+ False True False True False True False True False True False True
+ False True False True False True False False False True False True
+ False True False False False True False True True False True False
+ True False True True False True False True False True True False
+ True True True False True False True False False False True False
+ False False True False True False True False True False True False
+ True True False False True False True False True True False True
+ False False False True]
+# ---
+# name: test_martini[pent/prot_ion.tpr].14
+ [False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False]
+# ---
+# name: test_martini[pent/prot_ion.tpr].15
+ [False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False]
+# ---
+# name: test_martini[pent/prot_ion.tpr].16
+ [False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False False False False False False False False False
+ False False False False]
+# ---
+# name: test_martini[pent/prot_ion.tpr].17
+ [ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True]
+# ---
+# name: test_martini[pent/prot_ion.tpr].18
+ [[ 0 1]
+ [ 0 2]
+ [ 0 6]
+ ...
+ [11235 11236]
+ [11237 11238]
+ [11238 11239]]
+# ---
+# name: test_martini[pent/prot_ion.tpr].19
+ [ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True]
+# ---
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+# ---
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+# ---
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+# ---
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+# ---
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+# ---
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+ False False True False True False True False True False True False
+ True True False False True False True False True True False True
+ False False False True]
+# ---
+# name: test_martini[pent/prot_ion.tpr].35
+ [False False False False False False False False False False False False
+ False False False False False False False False False False False False
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+ False False False False]
+# ---
+# name: test_martini[pent/prot_ion.tpr].36
+ [False False False False False False False False False False False False
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+ False False False False]
+# ---
+# name: test_martini[pent/prot_ion.tpr].37
+ [False False False False False False False False False False False False
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+ False False False False False False False False False False False False
+ False False False False]
+# ---
+# name: test_martini[pent/prot_ion.tpr].38
+ [ True True True True True True True True True True True True
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+# ---
+# name: test_martini[pent/prot_ion.tpr].39
+ [[ 0 1]
+ [ 0 2]
+ [ 0 6]
+ ...
+ [11235 11236]
+ [11237 11238]
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+# ---
+# name: test_martini[pent/prot_ion.tpr].4
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+# ---
+# name: test_martini[pent/prot_ion.tpr].40
+ [ True True True True True True True True True True True True
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+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True True True True True True True True True
+ True True True True]
+# ---
+# name: test_martini[pent/prot_ion.tpr].41
+ []
+# ---
+# name: test_martini[pent/prot_ion.tpr].5
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+ 0]
+# ---
+# name: test_martini[pent/prot_ion.tpr].6
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+ 7 1 1 1 2 2 10 10 7 5 5 13 13 13 13 11]
+# ---
+# name: test_martini[pent/prot_ion.tpr].7
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+ 0]
+# ---
+# name: test_martini[pent/prot_ion.tpr].8
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+ 4 4 7 0 7 0 7 13 16 16 7 13 13 16 7 1 10 11 4 2 7 11 7 8
+ 10 10 4 12 7 10 7 0 7 7 11 7 14 14 14 7]
+# ---
+# name: test_martini[pent/prot_ion.tpr].9
+ [-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
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+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
+ -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1]
+# ---
diff --git a/tests/conftest.py b/tests/conftest.py
index 089da26c..aa3de679 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -2,6 +2,10 @@
import sys
import pytest
from .utils import NumpySnapshotExtension
+import molecularnodes as mn
+
+# mn.unregister()
+# mn.register()
DATA_DIR = join(dirname(realpath(__file__)), "data")
diff --git a/tests/install.py b/tests/install.py
index 0080a40f..29ec296b 100644
--- a/tests/install.py
+++ b/tests/install.py
@@ -1,25 +1,20 @@
import subprocess
import sys
import os
-import pathlib
-
-REQUIREMENTS = pathlib.Path(
- pathlib.Path(__file__).resolve().parent.parent
-) / "molecularnodes/requirements.txt"
def main():
-
python = os.path.realpath(sys.executable)
commands = [
- f'{python} -m pip install -r molecularnodes/requirements.txt',
+ f"{python} -m pip install -r requirements.txt",
+ # test
# f'{python} -m pip uninstall pytest-snapshot'
- f'{python} -m pip install pytest pytest-cov syrupy'
+ f"{python} -m pip install pytest pytest-cov syrupy",
]
for command in commands:
- subprocess.run(command.split(' '))
+ subprocess.run(command.split(" "))
if __name__ == "__main__":
diff --git a/tests/run.py b/tests/run.py
index 49695580..2279ad82 100644
--- a/tests/run.py
+++ b/tests/run.py
@@ -1,13 +1,15 @@
import pytest
import sys
+
argv = sys.argv
-argv = argv[argv.index("--") + 1:]
+argv = argv[argv.index("--") + 1 :]
# run this script like this:
# /Applications/Blender.app/Contents/MacOS/Blender -b -P tests/run.py -- . -v
# /Applications/Blender.app/Contents/MacOS/Blender -b -P tests/run.py -- . -k test_color_lookup_supplied
+
def main():
# run the test suite, and we have to manually return the result value if non-zero
# value is returned for a failing test
diff --git a/tests/test_assembly.py b/tests/test_assembly.py
index edd3e7c7..4705a924 100644
--- a/tests/test_assembly.py
+++ b/tests/test_assembly.py
@@ -4,17 +4,16 @@
import numpy as np
import biotite.structure.io.pdb as biotite_pdb
import biotite.structure.io.pdbx as biotite_cif
-import molecularnodes.io.parse.pdb as pdb
-import molecularnodes.io.parse.cif as cif
+import molecularnodes.entities.molecule.pdb as pdb
+import molecularnodes.entities.ensemble.cif as cif
DATA_DIR = join(dirname(realpath(__file__)), "data")
-@pytest.mark.parametrize("pdb_id, format", itertools.product(
- ["1f2n", "5zng"],
- ["pdb", "cif"]
-))
+@pytest.mark.parametrize(
+ "pdb_id, format", itertools.product(["1f2n", "5zng"], ["pdb", "cif"])
+)
def test_get_transformations(pdb_id, format):
"""
Compare an assembly built from transformation information in
@@ -30,7 +29,9 @@ def test_get_transformations(pdb_id, format):
cif_file = biotite_cif.PDBxFile.read(path)
atoms = biotite_cif.get_structure(
# Make sure `label_asym_id` is used instead of `auth_asym_id`
- cif_file, model=1, use_author_fields=False
+ cif_file,
+ model=1,
+ use_author_fields=False,
)
ref_assembly = biotite_cif.get_assembly(cif_file, model=1)
test_parser = cif.CIFAssemblyParser(cif_file)
@@ -43,7 +44,7 @@ def test_get_transformations(pdb_id, format):
check_transformations(test_transformations, atoms, ref_assembly)
-@pytest.mark.parametrize("assembly_id", [str(i+1) for i in range(5)])
+@pytest.mark.parametrize("assembly_id", [str(i + 1) for i in range(5)])
def test_get_transformations_cif(assembly_id):
"""
Compare an assembly built from transformation information in
@@ -55,11 +56,11 @@ def test_get_transformations_cif(assembly_id):
cif_file = biotite_cif.PDBxFile.read(join(DATA_DIR, "1f2n.cif"))
atoms = biotite_cif.get_structure(
# Make sure `label_asym_id` is used instead of `auth_asym_id`
- cif_file, model=1, use_author_fields=False
- )
- ref_assembly = biotite_cif.get_assembly(
- cif_file, model=1, assembly_id=assembly_id
+ cif_file,
+ model=1,
+ use_author_fields=False,
)
+ ref_assembly = biotite_cif.get_assembly(cif_file, model=1, assembly_id=assembly_id)
test_parser = cif.CIFAssemblyParser(cif_file)
test_transformations = test_parser.get_transformations(assembly_id)
diff --git a/tests/test_attributes.py b/tests/test_attributes.py
index e29bd35c..8f461d49 100644
--- a/tests/test_attributes.py
+++ b/tests/test_attributes.py
@@ -7,24 +7,23 @@
from .utils import sample_attribute
from .constants import codes, attributes, data_dir
-mn.unregister()
-mn.register()
+mn._test_register()
formats = ["pdb", "cif", "bcif"]
@pytest.mark.parametrize("code, format", itertools.product(codes, formats))
def test_attribute(snapshot_custom, code, format):
- mol = mn.io.fetch(code, cache_dir=data_dir, style=None, format=format)
+ mol = mn.entities.fetch(code, cache_dir=data_dir, style=None, format=format)
for attribute in attributes:
vals = sample_attribute(mol, attribute)
assert snapshot_custom == vals
-def test_set_attribute(snapshot_custom):
- mol = mn.io.fetch("8H1B", cache_dir=data_dir, style="surface", format="bcif")
- before = sample_attribute(mol, "position")
- mol.set_attribute(mol.get_attribute("position") + 10, "position")
- after = sample_attribute(mol, "position")
+def test_store_named_attribute(snapshot_custom):
+ mol = mn.entities.fetch("8H1B", cache_dir=data_dir, style=None, format="bcif")
+ before = mol.named_attribute("position")
+ mol.store_named_attribute(mol.named_attribute("position") + 10, "position")
+ after = mol.named_attribute("position")
assert not np.allclose(before, after)
diff --git a/tests/test_cellpack.py b/tests/test_cellpack.py
index a321c552..71d6d605 100644
--- a/tests/test_cellpack.py
+++ b/tests/test_cellpack.py
@@ -1,37 +1,29 @@
import molecularnodes as mn
import pytest
import bpy
-from .utils import (
- sample_attribute,
- NumpySnapshotExtension
-)
-from .constants import (
- data_dir
-)
+from .utils import sample_attribute
+from .constants import data_dir
-mn.unregister()
-mn.register()
+mn._test_register()
-@pytest.mark.parametrize('format', ['bcif', 'cif'])
-def test_load_cellpack(snapshot_custom: NumpySnapshotExtension, format):
+@pytest.mark.parametrize("format", ["bcif", "cif"])
+def test_load_cellpack(snapshot_custom, format):
bpy.ops.wm.read_homefile(app_template="")
name = f"Cellpack_{format}"
- ens = mn.io.cellpack.load(
- data_dir / f"square1.{format}",
- name=name,
- node_setup=False,
- fraction=0.1
+ ens = mn.entities.ensemble.load_cellpack(
+ data_dir / f"square1.{format}", name=name, node_setup=False, fraction=0.1
)
- coll = bpy.data.collections[f'cellpack_{name}']
+ coll = bpy.data.collections[f"cellpack_{name}"]
instance_names = [object.name for object in coll.objects]
assert snapshot_custom == "\n".join(instance_names)
assert ens.name == name
- ens.modifiers['MolecularNodes'].node_group.nodes['MN_pack_instances'].inputs['As Points'].default_value = False
+ ens.modifiers["MolecularNodes"].node_group.nodes["Ensemble Instance"].inputs[
+ "As Points"
+ ].default_value = False
mn.blender.nodes.realize_instances(ens)
for attribute in ens.data.attributes.keys():
- assert snapshot_custom == sample_attribute(
- ens, attribute, evaluate=True)
- assert snapshot_custom == str(ens['chain_ids'])
+ assert snapshot_custom == sample_attribute(ens, attribute, evaluate=True)
+ assert snapshot_custom == str(ens["chain_ids"])
diff --git a/tests/test_density.py b/tests/test_density.py
index b3bd2fb3..6e470dc5 100644
--- a/tests/test_density.py
+++ b/tests/test_density.py
@@ -4,17 +4,14 @@
import numpy as np
import itertools
from .constants import data_dir
-from .utils import (
- sample_attribute,
- NumpySnapshotExtension
-)
+from .utils import sample_attribute, NumpySnapshotExtension
+
try:
import pyopenvdb
except ImportError:
pytest.skip("pyopenvdb not installed", allow_module_level=True)
-mn.unregister()
-mn.register()
+mn._test_register()
@pytest.fixture
@@ -30,10 +27,9 @@ def density_file():
def test_density_load(density_file):
-
- obj = mn.io.density.load(density_file).object
- evaluated = mn.blender.obj.evaluate_using_mesh(obj)
- pos = mn.blender.obj.get_attribute(evaluated, "position")
+ obj = mn.entities.density.load(density_file).object
+ evaluated = mn.blender.mesh.evaluate_using_mesh(obj)
+ pos = mn.blender.mesh.named_attribute(evaluated, "position")
assert len(pos) > 1000
@@ -51,10 +47,10 @@ def test_density_centered(density_file):
# bpy.data.objects.remove(o, do_unlink=True)
bpy.ops.wm.read_homefile(app_template="")
- obj = mn.io.density.load(density_file, center=True, overwrite=True).object
- evaluated = mn.blender.obj.evaluate_using_mesh(obj)
+ obj = mn.entities.density.load(density_file, center=True, overwrite=True).object
+ evaluated = mn.blender.mesh.evaluate_using_mesh(obj)
- pos = mn.blender.obj.get_attribute(evaluated, "position")
+ pos = mn.blender.mesh.named_attribute(evaluated, "position")
assert len(pos) > 1000
@@ -63,18 +59,17 @@ def test_density_centered(density_file):
def test_density_invert(density_file):
-
# First load using standar parameters to test recreation of vdb
- o = mn.io.density.load(density_file).object
+ o = mn.entities.density.load(density_file).object
# Then refresh the scene
bpy.data.objects.remove(o, do_unlink=True)
- obj = mn.io.density.load(density_file, invert=True).object
+ obj = mn.entities.density.load(density_file, invert=True).object
style_node = mn.blender.nodes.get_style_node(obj)
style_node.inputs["Threshold"].default_value = 0.01
- evaluated = mn.blender.obj.evaluate_using_mesh(obj)
+ evaluated = mn.blender.mesh.evaluate_using_mesh(obj)
- pos = mn.blender.obj.get_attribute(evaluated, "position")
+ pos = mn.blender.mesh.named_attribute(evaluated, "position")
# At this threshold after inverting we should have a cube the size of the volume
assert pos[:, 0].max() > 2.0
assert pos[:, 1].max() > 2.0
@@ -83,8 +78,8 @@ def test_density_invert(density_file):
def test_density_multiple_load():
file = data_dir / "emd_24805.map.gz"
- obj = mn.io.density.load(file).object
- obj2 = mn.io.density.load(file).object
+ obj = mn.entities.density.load(file).object
+ obj2 = mn.entities.density.load(file).object
assert obj.mn.molecule_type == "density"
assert obj2.mn.molecule_type == "density"
@@ -92,14 +87,14 @@ def test_density_multiple_load():
assert obj2.users_collection[0] == mn.blender.coll.mn()
-@pytest.mark.parametrize('name', ['', 'NewDensity'])
+@pytest.mark.parametrize("name", ["", "NewDensity"])
def test_density_naming_op(density_file, name):
bpy.context.scene.MN_import_density_name = name
bpy.context.scene.MN_import_density = str(density_file)
bpy.ops.mn.import_density()
- if name == '':
- object_name = 'emd_24805'
+ if name == "":
+ object_name = "emd_24805"
else:
object_name = name
object = bpy.data.objects[object_name]
@@ -107,11 +102,11 @@ def test_density_naming_op(density_file, name):
assert object.name == object_name
-@pytest.mark.parametrize('name', ['', 'NewDensity'])
+@pytest.mark.parametrize("name", ["", "NewDensity"])
def test_density_naming_api(density_file, name):
- object = mn.io.density.load(density_file, name).object
- if name == '':
- object_name = 'emd_24805'
+ object = mn.entities.density.load(density_file, name).object
+ if name == "":
+ object_name = "emd_24805"
else:
object_name = name
@@ -119,20 +114,23 @@ def test_density_naming_api(density_file, name):
assert object.name == object_name
-@pytest.mark.parametrize("invert,node_setup,center", list(itertools.product([True, False], repeat=3)))
-def test_density_operator(snapshot_custom: NumpySnapshotExtension, density_file, invert, node_setup, center):
+@pytest.mark.parametrize(
+ "invert,node_setup,center", list(itertools.product([True, False], repeat=3))
+)
+def test_density_operator(
+ snapshot_custom: NumpySnapshotExtension, density_file, invert, node_setup, center
+):
scene = bpy.context.scene
scene.MN_import_density = str(density_file)
scene.MN_import_density_invert = invert
scene.MN_import_node_setup = node_setup
scene.MN_import_density_center = center
scene.MN_import_density_name = ""
- bobs = [bob.name for bob in bpy.data.objects]
+ objs = [obj.name for obj in bpy.data.objects]
bpy.ops.mn.import_density()
- for bob in bpy.data.objects:
- if bob.name not in bobs:
- new_bob = bob
+ for obj in bpy.data.objects:
+ if obj.name not in objs:
+ new_obj = obj
assert snapshot_custom == sample_attribute(
- mn.blender.obj.evaluate_using_mesh(new_bob),
- 'position'
+ mn.blender.mesh.evaluate_using_mesh(new_obj), "position"
)
diff --git a/tests/test_dna.py b/tests/test_dna.py
index 617f5bde..58236a93 100644
--- a/tests/test_dna.py
+++ b/tests/test_dna.py
@@ -1,13 +1,8 @@
import numpy as np
import molecularnodes as mn
-from molecularnodes.io import dna
-from .utils import (
- sample_attribute,
- NumpySnapshotExtension
-)
-from .constants import (
- data_dir
-)
+from molecularnodes.entities.trajectory import dna
+from .utils import sample_attribute, NumpySnapshotExtension
+from .constants import data_dir
def test_read_topology():
@@ -21,11 +16,7 @@ def test_read_topology():
def test_topology_to_idx():
- top = np.array([
- [1, 31, -1, 1],
- [1, 3, 0, 1],
- [1, 2, 1, -1]
- ])
+ top = np.array([[1, 31, -1, 1], [1, 3, 0, 1], [1, 2, 1, -1]])
bonds = dna.toplogy_to_bond_idx_pairs(top)
expected = np.array([[0, 1], [1, 2]])
@@ -34,7 +25,7 @@ def test_topology_to_idx():
def test_base_lookup():
- bases = np.array(['A', 'C', 'C', 'G', 'T', '-10', 'G', 'C', '-3'])
+ bases = np.array(["A", "C", "C", "G", "T", "-10", "G", "C", "-3"])
expected = np.array([30, 31, 31, 32, 33, -1, 32, 31, -1])
ints = dna.base_to_int(bases)
@@ -49,11 +40,11 @@ def test_read_trajectory():
def test_read_oxdna(snapshot_custom: NumpySnapshotExtension):
- name = 'holliday'
+ name = "holliday"
mol, coll_frames = dna.load(
top=data_dir / "oxdna/holliday.top",
traj=data_dir / "oxdna/holliday.dat",
- name=name
+ name=name,
)
assert len(coll_frames.objects) == 20
diff --git a/tests/test_download.py b/tests/test_download.py
index a4b98eab..7b6608ce 100644
--- a/tests/test_download.py
+++ b/tests/test_download.py
@@ -1,16 +1,18 @@
-from .constants import codes, data_dir
+import io
+import os
import tempfile
-from biotite.structure.io import load_structure
+
import biotite.database.rcsb as rcsb
-from molecularnodes.io.retrieve import download, FileDownloadPDBError
-import os
-import io
import pytest
+from biotite.structure.io import load_structure
+
import molecularnodes as mn
+from molecularnodes.download import FileDownloadPDBError, download
+from .constants import codes
# currently can't figure out downloading from other services
-databases = ["rcsb"]
+DATABASES = ["rcsb"]
def _filestart(format):
@@ -42,7 +44,7 @@ def test_fail_download_pdb_large_structure_raises():
@pytest.mark.parametrize("format", ["cif", "bcif", "pdb"])
def test_compare_biotite(format):
struc_download = load_structure(
- mn.io.download("4ozs", format=format, cache=tempfile.TemporaryDirectory().name)
+ download("4ozs", format=format, cache=tempfile.TemporaryDirectory().name)
)
struc_biotite = load_structure(
rcsb.fetch(
@@ -53,11 +55,11 @@ def test_compare_biotite(format):
@pytest.mark.parametrize("code", codes)
-@pytest.mark.parametrize("database", databases)
+@pytest.mark.parametrize("database", DATABASES)
@pytest.mark.parametrize("format", ["pdb", "cif"])
def test_fetch_with_cache(tmpdir, code, format, database):
cache_dir = tmpdir.mkdir("cache")
- file = mn.io.download(code, format, cache=str(cache_dir), database=database)
+ file = download(code, format, cache=str(cache_dir), database=database)
assert isinstance(file, str)
assert os.path.isfile(file)
@@ -68,35 +70,35 @@ def test_fetch_with_cache(tmpdir, code, format, database):
assert content.startswith(_filestart(format))
-databases = ["rcsb"] # currently can't figure out downloading from the pdbe
+DATABASES = ["rcsb"] # currently can't figure out downloading from the pdbe
@pytest.mark.parametrize("code", codes)
-@pytest.mark.parametrize("database", databases)
+@pytest.mark.parametrize("database", DATABASES)
@pytest.mark.parametrize("format", ["pdb", "cif"])
def test_fetch_without_cache(tmpdir, code, format, database):
- file = mn.io.download(code, format, cache=None, database=database)
+ file = download(code, format, cache=None, database=database)
assert isinstance(file, io.StringIO)
content = file.getvalue()
assert content.startswith(_filestart(format))
-@pytest.mark.parametrize("database", databases)
+@pytest.mark.parametrize("database", DATABASES)
def test_fetch_with_invalid_format(database):
code = "4OZS"
format = "xyz"
with pytest.raises(ValueError):
- mn.io.download(code, format, cache=None, database=database)
+ download(code, format, cache=None, database=database)
@pytest.mark.parametrize("code", codes)
-@pytest.mark.parametrize("database", databases)
+@pytest.mark.parametrize("database", DATABASES)
@pytest.mark.parametrize("format", ["bcif"])
def test_fetch_with_binary_format(tmpdir, code, database, format):
cache_dir = tmpdir.mkdir("cache")
- file = mn.io.download(code, format, cache=str(cache_dir), database=database)
+ file = download(code, format, cache=str(cache_dir), database=database)
assert isinstance(file, str)
assert os.path.isfile(file)
@@ -117,8 +119,8 @@ def test_fetch_with_binary_format(tmpdir, code, database, format):
@pytest.mark.parametrize("format", ("cif", "pdb"))
@pytest.mark.parametrize("code", ("A0A5E8G9H8", "A0A5E8G9T8", "K4PA18"))
def test_alphafold_download(format: str, code: str, tmpdir) -> None:
- file = mn.io.download(code=code, format=format, database="alphafold", cache=tmpdir)
+ file = download(code=code, format=format, database="alphafold", cache=tmpdir)
- mol = mn.io.load(file)
+ mol = mn.entities.load_local(file)
assert mol.array
diff --git a/tests/test_load.py b/tests/test_load.py
index a9b4ed41..8e17d178 100644
--- a/tests/test_load.py
+++ b/tests/test_load.py
@@ -6,8 +6,7 @@
from .constants import data_dir, codes, attributes
from .utils import sample_attribute, NumpySnapshotExtension
-mn.unregister()
-mn.register()
+mn._test_register()
styles = ["preset_1", "cartoon", "ribbon", "spheres", "surface", "ball_and_stick"]
@@ -15,13 +14,13 @@
def useful_function(snapshot_custom, style, code, assembly, cache_dir=None):
- obj = mn.io.fetch(
+ obj = mn.entities.fetch(
code, style=style, build_assembly=assembly, cache_dir=cache_dir
).object
node = mn.blender.nodes.get_style_node(obj)
- if "EEVEE" in node.inputs.keys():
- node.inputs["EEVEE"].default_value = True
+ if "Sphere As Mesh" in node.inputs.keys():
+ node.inputs["Sphere As Mesh"].default_value = True
mn.blender.nodes.realize_instances(obj)
dont_realise = style == "cartoon" and code == "1BNA"
@@ -52,7 +51,7 @@ def test_style_2(snapshot_custom: NumpySnapshotExtension, assembly, code, style)
"code, format", itertools.product(codes, ["bcif", "cif", "pdb"])
)
def test_download_format(code, format):
- mol = mn.io.fetch(code, format=format, style=None, cache_dir=data_dir).object
+ mol = mn.entities.fetch(code, format=format, style=None, cache_dir=data_dir).object
scene = bpy.context.scene
scene.MN_pdb_code = code
scene.MN_import_node_setup = False
@@ -65,14 +64,14 @@ def test_download_format(code, format):
mol2 = o
def verts(object):
- return mn.blender.obj.get_attribute(object, "position")
+ return mn.blender.mesh.named_attribute(object, "position")
assert np.isclose(verts(mol), verts(mol2)).all()
@pytest.mark.parametrize("code, style", itertools.product(codes, styles))
def test_style_positions(snapshot_custom: NumpySnapshotExtension, code, style):
- mol = mn.io.fetch(code, style=style, cache_dir=data_dir).object
+ mol = mn.entities.fetch(code, style=style, cache_dir=data_dir).object
assert snapshot_custom == sample_attribute(mol, "position")
@@ -83,7 +82,7 @@ def test_centring(snapshot_custom: NumpySnapshotExtension, code, centre_method):
"""fetch a pdb structure using code and translate the model using the
centre_method. Check the CoG and CoM values against the snapshot file.
"""
- mol = mn.io.fetch(code, centre=centre_method, cache_dir=data_dir)
+ mol = mn.entities.fetch(code, centre=centre_method, cache_dir=data_dir)
CoG = mol.centre()
CoM = mol.centre(centre_type="mass")
@@ -104,7 +103,7 @@ def test_centring_different(code):
positions are in fact different.
"""
mols = [
- mn.io.fetch(code, centre=method, cache_dir=data_dir)
+ mn.entities.fetch(code, centre=method, cache_dir=data_dir)
for method in centre_methods
]
for mol1, mol2 in itertools.combinations(mols, 2):
@@ -115,42 +114,48 @@ def test_centring_different(code):
mol1.centre(centre_type="mass"), mol2.centre(centre_type="mass")
)
assert not np.allclose(
- mol1.get_attribute("position"), mol2.get_attribute("position")
+ mol1.named_attribute("position"), mol2.named_attribute("position")
)
# THESE TEST FUNCTIONS ARE NOT RUN
def test_local_pdb(snapshot_custom):
molecules = [
- mn.io.load(data_dir / f"1l58.{ext}", style="spheres") for ext in ("cif", "pdb")
+ mn.entities.load_local(data_dir / f"1l58.{ext}", style="spheres")
+ for ext in ("cif", "pdb")
]
- molecules.append(mn.io.fetch("1l58", format="bcif"))
+ molecules.append(mn.entities.fetch("1l58", format="bcif"))
for att in ["position"]:
for mol in molecules:
assert snapshot_custom == sample_attribute(mol, att, evaluate=False)
-def test_rcsb_nmr(snapshot_custom):
- mol = mn.io.fetch("2M6Q", style="cartoon", cache_dir=data_dir)
+@pytest.mark.parametrize("del_hydrogen", [True, False])
+def test_rcsb_nmr(snapshot_custom, del_hydrogen):
+ mol = mn.entities.fetch(
+ "2M6Q", style="cartoon", cache_dir=data_dir, del_hydrogen=del_hydrogen
+ )
assert len(mol.frames.objects) == 10
assert (
mol.object.modifiers["MolecularNodes"]
- .node_group.nodes["MN_animate_value"]
- .inputs["To Max"]
+ .node_group.nodes["Animate Value"]
+ .inputs["Value Max"]
.default_value
== 9
)
-
+ assert snapshot_custom == mol.named_attribute("position")
assert snapshot_custom == sample_attribute(mol, "position", evaluate=True)
- pos_1 = mol.get_attribute("position", evaluate=True)
+ bpy.context.scene.frame_set(1)
+ pos_1 = mol.named_attribute("position", evaluate=True)
bpy.context.scene.frame_set(100)
- pos_2 = mol.get_attribute("position", evaluate=True)
+ pos_2 = mol.named_attribute("position", evaluate=True)
+ bpy.context.scene.frame_set(1)
assert (pos_1 != pos_2).all()
def test_load_small_mol(snapshot_custom):
- mol = mn.io.load(data_dir / "ASN.cif")
+ mol = mn.entities.load_local(data_dir / "ASN.cif")
for att in ["position", "bond_type"]:
assert snapshot_custom == sample_attribute(mol, att).tolist()
@@ -167,11 +172,11 @@ def test_rcsb_cache(snapshot_custom):
test_cache = Path(data_dir)
# Run the test
- obj_1 = mn.io.fetch("6BQN", style="cartoon", cache_dir=test_cache)
+ obj_1 = mn.entities.fetch("6BQN", style="cartoon", cache_dir=test_cache)
file = os.path.join(test_cache, "6BQN.bcif")
assert os.path.exists(file)
- obj_2 = mn.io.fetch("6BQN", style="cartoon", cache_dir=test_cache)
+ obj_2 = mn.entities.fetch("6BQN", style="cartoon", cache_dir=test_cache)
assert (
sample_attribute(obj_1, "position") == sample_attribute(obj_2, "position")
).all()
diff --git a/tests/test_mda.py b/tests/test_mda.py
deleted file mode 100644
index 73e5f255..00000000
--- a/tests/test_mda.py
+++ /dev/null
@@ -1,366 +0,0 @@
-import bpy
-import os
-import pytest
-import molecularnodes as mn
-from . import utils
-from molecularnodes.io.md import HAS_mda
-from molecularnodes.blender.obj import get_attribute
-
-if HAS_mda:
- import MDAnalysis as mda
-import numpy as np
-from .constants import (
- data_dir
-)
-from .utils import (
- remove_all_molecule_objects,
- sample_attribute,
- NumpySnapshotExtension
-)
-
-
-@pytest.mark.skipif(not HAS_mda, reason="MDAnalysis is not installed")
-class TestMDA:
- @pytest.fixture(scope="module")
- def mda_session(self):
- mda_session = mn.io.MDAnalysisSession()
- return mda_session
-
- @pytest.fixture(scope="module")
- def universe(self):
- top = data_dir / "md_ppr/box.gro"
- traj = data_dir / "md_ppr/first_5_frames.xtc"
- u = mda.Universe(top, traj)
- return u
-
- @pytest.fixture(scope="module")
- def universe_with_bonds(self):
- top = data_dir / "md_ppr/md.tpr"
- traj = data_dir / "md_ppr/md.gro"
- u = mda.Universe(top, traj)
- return u
-
- def test_persistent_handlers_added(self, mda_session):
- assert bpy.app.handlers.load_post[-1].__name__ == "_rejuvenate_universe"
- assert bpy.app.handlers.save_post[-1].__name__ == "_sync_universe"
-
- def test_create_mda_session(self, mda_session):
- assert mda_session is not None
- assert mda_session.world_scale == 0.01
-
- def reload_mda_session(self, mda_session):
- with pytest.warns(UserWarning, match="The existing mda session"):
- mda_session_2 = mn.mda.create_session()
-
- @pytest.mark.parametrize("in_memory", [False, True])
- def test_show_universe(self, snapshot_custom: NumpySnapshotExtension, in_memory, mda_session, universe):
- remove_all_molecule_objects(mda_session)
- mda_session.show(universe, in_memory=in_memory)
- bob = bpy.data.objects["atoms"]
- assert snapshot_custom == sample_attribute(bob, 'position')
-
- @pytest.mark.parametrize("in_memory", [False, True])
- def test_same_name_atoms(self, in_memory, mda_session, universe):
- remove_all_molecule_objects(mda_session)
- mda_session.show(universe, in_memory=in_memory)
-
- with pytest.warns(UserWarning, match="The name of the object is changed"):
- mda_session.show(universe, in_memory=in_memory)
-
- bob_1 = bpy.data.objects["atoms"]
- bob_2 = bpy.data.objects["atoms.001"]
- verts_1 = mn.blender.obj.get_attribute(bob_1, 'position')
- verts_2 = mn.blender.obj.get_attribute(bob_2, 'position')
-
- assert (verts_1 == verts_2).all()
-
- @pytest.mark.parametrize("in_memory", [False, True])
- def test_show_multiple_selection(self, snapshot_custom: NumpySnapshotExtension, in_memory, mda_session, universe):
- remove_all_molecule_objects(mda_session)
- custom_selections = {"name_ca": "name CA"}
- mda_session.show(
- universe,
- in_memory=in_memory,
- name="protein",
- selection="protein",
- custom_selections=custom_selections,
- )
- bob = bpy.data.objects["protein"]
- assert snapshot_custom == sample_attribute(bob, 'posiiton')
-
- # different bahavior in_memory or not.
- if not in_memory:
- bob_ca = bpy.data.objects["name_ca"]
- assert snapshot_custom == sample_attribute(bob_ca, 'position')
- else:
- # attribute is added as name_ca.
- assert "name_ca" in bob.data.attributes.keys()
-
- @pytest.mark.parametrize("in_memory", [False, True])
- def test_include_bonds(self, in_memory, mda_session, universe_with_bonds):
-
- remove_all_molecule_objects(mda_session)
- mda_session.show(universe_with_bonds, in_memory=in_memory)
- obj = bpy.data.objects["atoms"]
- assert obj.data.edges.items() != []
-
- @pytest.mark.parametrize("in_memory", [False, True])
- def test_attributes_added(self, in_memory, mda_session, universe):
- remove_all_molecule_objects(mda_session)
- mda_session.show(universe, in_memory=in_memory)
- obj = bpy.data.objects["atoms"]
- attributes = obj.data.attributes.keys()
- # check if all attributes are added.
-
- attribute_added = [
- "vdw_radii",
- "b_factor",
- "atomic_number",
- "res_id",
- "res_name",
- "chain_id",
- "atom_types",
- "atom_name",
- "position",
- "is_backbone",
- "is_alpha_carbon",
- "is_solvent",
- "is_nucleic",
- "is_peptide",
- ]
- for att in attribute_added:
- assert att in attributes
-
- @pytest.mark.parametrize("in_memory", [False, True])
- def test_trajectory_update(self, snapshot_custom: NumpySnapshotExtension, in_memory, universe):
-
- # remove_all_molecule_objects(mda_session)
- mda_session = mn.io.MDAnalysisSession()
-
- obj = mda_session.show(universe, in_memory=in_memory, style='ribbon')
- node = mn.blender.nodes.get_style_node(obj)
- group = obj.modifiers['MolecularNodes'].node_group
- if in_memory:
- node = group.nodes['MN_animate_value']
- node.inputs['Frame: Start'].default_value = 0
- node.inputs['Frame: End'].default_value = 4
-
- if 'EEVEE' in node.inputs.keys():
- node.inputs['EEVEE'].default_value = True
-
- if in_memory:
- mn.blender.nodes.realize_instances(obj)
-
- n = 100
-
- pos_a = sample_attribute(obj, 'position', n=n, evaluate=in_memory)
- assert snapshot_custom == pos_a
-
- # change blender frame to 4
- next_frame = 200 if in_memory else 4
- bpy.context.scene.frame_set(next_frame)
-
- # if in_memory:
- # socket.default_value = 250
- pos_b = sample_attribute(obj, 'position', n=n, evaluate=in_memory)
- assert snapshot_custom == pos_b
-
- assert not np.isclose(pos_a, pos_b).all()
-
- @pytest.mark.parametrize("in_memory", [False, True])
- def test_show_updated_atoms(self, snapshot_custom: NumpySnapshotExtension, in_memory, mda_session, universe):
- remove_all_molecule_objects(mda_session)
- updating_ag = universe.select_atoms("around 5 resid 1", updating=True)
- mda_session.show(updating_ag, in_memory=in_memory, style='vdw')
-
- bob = bpy.data.objects["atoms"]
- nodes = bob.modifiers['MolecularNodes'].node_group.nodes
- for node in nodes:
- for input in node.inputs:
- if input.name == "Frame: Start":
- input.default_value = 0
- elif input.name == "Frame: End":
- input.default_value = 4
- elif input.name == "To Max":
- input.default_value = 4
- elif input.name == "EEVEE":
- input.default_value = True
-
- mn.blender.nodes.realize_instances(bob)
-
- bpy.context.scene.frame_set(0)
- verts_frame_0 = get_attribute(bob, 'position', evaluate=True)
- assert snapshot_custom == verts_frame_0
-
- # change blender frame to 1
- bpy.context.scene.frame_set(1)
- # bob = bpy.data.objects["atoms"]
- verts_frame_1 = get_attribute(bob, 'position', evaluate=True)
-
- assert snapshot_custom == verts_frame_1
-
- @pytest.mark.parametrize("in_memory", [False, True])
- def test_update_deleted_objects(self, in_memory, mda_session, universe):
- remove_all_molecule_objects(mda_session)
- mda_session.show(universe, in_memory=in_memory)
- bpy.data.objects.remove(bpy.data.objects["atoms"])
-
- # trigger depsgraph_update_post handler
- # by creating a new object
- bpy.ops.mesh.primitive_cube_add()
-
- assert mda_session.universe_reps == {}
- assert mda_session.atom_reps == {}
- assert mda_session.rep_names == []
-
- # remove the cube
- bpy.data.objects.remove(bpy.data.objects["Cube"])
-
- @pytest.mark.parametrize("in_memory", [False, True])
- def test_save_persistance(
- self, snapshot_custom: NumpySnapshotExtension, tmp_path, in_memory, mda_session, universe
- ):
- remove_all_molecule_objects(mda_session)
- mda_session.show(universe, in_memory=in_memory)
- # save
- bpy.ops.wm.save_as_mainfile(filepath=str(tmp_path / "test.blend"))
-
- assert os.path.exists(str(tmp_path / "test.mda_session"))
-
- # reload
- remove_all_molecule_objects(mda_session)
- bpy.ops.wm.open_mainfile(filepath=str(tmp_path / "test.blend"))
- bob = bpy.data.objects["atoms"]
- verts_frame_0 = mn.blender.obj.get_attribute(bob, 'position')
-
- # change blender frame to 1
- bpy.context.scene.frame_set(1)
- bob = bpy.data.objects["atoms"]
- verts_frame_1 = mn.blender.obj.get_attribute(bob, 'position')
- assert snapshot_custom == verts_frame_1
-
- assert not np.isclose(verts_frame_0, verts_frame_1).all()
-
-
-@pytest.mark.skipif(not HAS_mda, reason="MDAnalysis is not installed")
-class TestMDA_FrameMapping:
- @pytest.fixture(scope="module")
- def mda_session(self):
- mda_session = mn.io.MDAnalysisSession()
- return mda_session
-
- @pytest.fixture(scope="module")
- def universe(self):
- top = data_dir / "md_ppr/box.gro"
- traj = data_dir / "md_ppr/first_5_frames.xtc"
- u = mda.Universe(top, traj)
- return u
-
- @pytest.fixture(scope="module")
- def universe_with_bonds(self):
- top = data_dir / "md_ppr/md.tpr"
- traj = data_dir / "md_ppr/md.gro"
- u = mda.Universe(top, traj)
- return u
-
- def test_persistent_handlers_added(self, mda_session):
- assert bpy.app.handlers.load_post[-1].__name__ == "_rejuvenate_universe"
- assert bpy.app.handlers.save_post[-1].__name__ == "_sync_universe"
-
- def test_create_mda_session(self, mda_session):
- assert mda_session is not None
- assert mda_session.world_scale == 0.01
-
- def reload_mda_session(self, mda_session):
- with pytest.warns(UserWarning, match="The existing mda session"):
- mda_session_2 = mn.mda.create_session()
-
- def test_frame_mapping(self, mda_session, universe):
- remove_all_molecule_objects(mda_session)
- obj = mda_session.show(universe, frame_mapping=[0, 0, 1, 2, 4])
-
- bpy.context.scene.frame_set(0)
- verts_a = get_attribute(obj, 'position')
-
- bpy.context.scene.frame_set(1)
- verts_b = get_attribute(obj, 'position')
- # test the frame mapping works, that nothing has changed becuase of the mapping
- assert np.isclose(verts_a, verts_b).all()
-
- bpy.context.scene.frame_set(2)
- verts_b = get_attribute(obj, 'position')
- # test that something has now changed
- assert not np.isclose(verts_a, verts_b).all()
-
- def test_subframes(self, mda_session, universe):
- remove_all_molecule_objects(mda_session)
- mda_session.show(universe)
-
- obj = bpy.data.objects["atoms"]
- bpy.context.scene.frame_set(0)
- verts_a = get_attribute(obj, 'position')
-
- bpy.context.scene.frame_set(1)
- verts_b = get_attribute(obj, 'position')
- # should be no difference because not using subframes
- assert not np.isclose(verts_a, verts_b).all()
-
- for subframes in [1, 2, 3, 4]:
- frame = 1
- fraction = frame % (subframes + 1) / (subframes + 1)
- obj.mn['subframes'] = subframes
- bpy.context.scene.frame_set(frame)
- verts_c = get_attribute(obj, 'position')
- # now using subframes, there should be a difference
- assert not np.isclose(verts_b, verts_c).all()
-
- assert np.isclose(verts_c, mn.utils.lerp(
- verts_a, verts_b, t=fraction)).all()
-
- def test_subframe_mapping(self, mda_session, universe):
- remove_all_molecule_objects(mda_session)
- mda_session.show(universe, in_memory=False,
- frame_mapping=[0, 0, 1, 2, 3])
-
- bob = bpy.data.objects["atoms"]
- bpy.context.scene.frame_set(0)
- verts_a = get_attribute(bob, 'position')
-
- bpy.context.scene.frame_set(1)
- verts_b = get_attribute(bob, 'position')
- assert np.isclose(verts_a, verts_b).all()
-
- bpy.context.scene.frame_set(2)
- verts_b = get_attribute(bob, 'position')
- assert not np.isclose(verts_a, verts_b).all()
-
- bob.mn['subframes'] = 1
- bpy.context.scene.frame_set(3)
- verts_c = get_attribute(bob, 'position')
-
- assert not np.isclose(verts_b, verts_c).all()
- assert np.isclose(verts_c, mn.utils.lerp(verts_a, verts_b, 0.5)).all()
-
-
-@pytest.mark.parametrize("toplogy", ["pent/prot_ion.tpr", "pent/TOPOL2.pdb"])
-def test_martini(snapshot_custom: NumpySnapshotExtension, toplogy):
- session = mn.io.MDAnalysisSession()
- remove_all_molecule_objects(session)
- universe = mda.Universe(
- data_dir / "martini" / toplogy,
- data_dir / "martini/pent/PENT2_100frames.xtc"
- )
-
- mol = session.show(universe, style="ribbon")
-
- pos_a = sample_attribute(mol, 'position')
- bpy.context.scene.frame_set(3)
- pos_b = sample_attribute(mol, 'position')
-
- assert not np.isclose(pos_a, pos_b).all()
-
- for att in mol.data.attributes.keys():
- assert snapshot_custom == sample_attribute(mol, att)
-
- for att in mol.data.attributes.keys():
- assert snapshot_custom == sample_attribute(mol, att)
diff --git a/tests/test_mol_sdf.py b/tests/test_mol_sdf.py
index 573d3328..f9ef58e1 100644
--- a/tests/test_mol_sdf.py
+++ b/tests/test_mol_sdf.py
@@ -6,32 +6,30 @@
from .constants import data_dir, attributes
from .utils import sample_attribute, NumpySnapshotExtension
-mn.unregister()
-mn.register()
+mn._test_register()
-
-formats = ['mol', 'sdf']
+formats = ["mol", "sdf"]
@pytest.mark.parametrize("format", formats)
def test_open(snapshot_custom, format):
- molecule = mn.io.parse.SDF(data_dir / f'caffeine.{format}')
+ molecule = mn.entities.molecule.SDF(data_dir / f"caffeine.{format}")
assert molecule.array
assert molecule.file
@pytest.mark.parametrize("format", formats)
-@pytest.mark.parametrize("style", ['ball_and_stick', 'spheres', 'surface'])
+@pytest.mark.parametrize("style", ["ball_and_stick", "spheres", "surface"])
def test_load(snapshot_custom: NumpySnapshotExtension, format, style):
- mol = mn.io.load(data_dir / f'caffeine.{format}', style=style)
+ mol = mn.entities.load_local(data_dir / f"caffeine.{format}", style=style)
assert mol.object
- if style == 'spheres':
- bl.nodes.get_style_node(
- mol.object).inputs['EEVEE'].default_value = True
+ if style == "spheres":
+ bl.nodes.get_style_node(mol.object).inputs[
+ "Sphere As Mesh"
+ ].default_value = True
mn.blender.nodes.realize_instances(mol.object)
for attribute in attributes:
- assert snapshot_custom == sample_attribute(
- mol, attribute, evaluate=True)
+ assert snapshot_custom == sample_attribute(mol, attribute, evaluate=True)
diff --git a/tests/test_nodes.py b/tests/test_nodes.py
index a823ac04..b5ea9ea7 100644
--- a/tests/test_nodes.py
+++ b/tests/test_nodes.py
@@ -10,12 +10,11 @@
random.seed(6)
-mn.unregister()
-mn.register()
+mn._test_register()
def test_node_name_format():
- assert mn.blender.nodes.format_node_name("MN_style_cartoon") == "Style Cartoon"
+ assert mn.blender.nodes.format_node_name("Style Cartoon") == "Style Cartoon"
assert (
mn.blender.nodes.format_node_name("MN_dna_double_helix") == "DNA Double Helix"
)
@@ -26,28 +25,28 @@ def test_node_name_format():
def test_get_nodes():
- bob = mn.io.fetch("4ozs", style="spheres", cache_dir=data_dir).object
+ obj = mn.entities.fetch("4ozs", style="spheres", cache_dir=data_dir).object
assert (
- nodes.get_nodes_last_output(bob.modifiers["MolecularNodes"].node_group)[0].name
- == "MN_style_spheres"
+ nodes.get_nodes_last_output(obj.modifiers["MolecularNodes"].node_group)[0].name
+ == "Style Spheres"
)
- nodes.realize_instances(bob)
+ nodes.realize_instances(obj)
assert (
- nodes.get_nodes_last_output(bob.modifiers["MolecularNodes"].node_group)[0].name
+ nodes.get_nodes_last_output(obj.modifiers["MolecularNodes"].node_group)[0].name
== "Realize Instances"
)
- assert nodes.get_style_node(bob).name == "MN_style_spheres"
+ assert nodes.get_style_node(obj).name == "Style Spheres"
- bob2 = mn.io.fetch(
+ obj2 = mn.entities.fetch(
"1cd3", style="cartoon", build_assembly=True, cache_dir=data_dir
).object
assert (
- nodes.get_nodes_last_output(bob2.modifiers["MolecularNodes"].node_group)[0].name
- == "MN_assembly_1cd3"
+ nodes.get_nodes_last_output(obj2.modifiers["MolecularNodes"].node_group)[0].name
+ == "Assembly 1cd3"
)
- assert nodes.get_style_node(bob2).name == "MN_style_cartoon"
+ assert nodes.get_style_node(obj2).name == "Style Cartoon"
def test_selection():
@@ -65,7 +64,7 @@ def test_selection():
@pytest.mark.parametrize("code", codes)
@pytest.mark.parametrize("attribute", ["chain_id", "entity_id"])
def test_selection_working(snapshot_custom: NumpySnapshotExtension, attribute, code):
- mol = mn.io.fetch(code, style="ribbon", cache_dir=data_dir).object
+ mol = mn.entities.fetch(code, style="ribbon", cache_dir=data_dir).object
group = mol.modifiers["MolecularNodes"].node_group
node_sel = nodes.add_selection(group, mol.name, mol[f"{attribute}s"], attribute)
@@ -82,19 +81,21 @@ def test_selection_working(snapshot_custom: NumpySnapshotExtension, attribute, c
@pytest.mark.parametrize("code", codes)
@pytest.mark.parametrize("attribute", ["chain_id", "entity_id"])
def test_color_custom(snapshot_custom: NumpySnapshotExtension, code, attribute):
- mol = mn.io.fetch(code, style="ribbon", cache_dir=data_dir).object
+ mol = mn.entities.fetch(code, style="ribbon", cache_dir=data_dir)
group_col = mn.blender.nodes.custom_iswitch(
- name=f"MN_color_entity_{mol.name}",
- iter_list=mol[f"{attribute}s"],
+ name=f"Color Entity {mol.name}",
+ iter_list=mol.object[f"{attribute}s"],
field=attribute,
dtype="RGBA",
)
- group = mol.modifiers["MolecularNodes"].node_group
+ group = mol.object.modifiers["MolecularNodes"].node_group
node_col = mn.blender.nodes.add_custom(group, group_col.name, [0, -200])
- group.links.new(node_col.outputs[0], group.nodes["MN_color_set"].inputs["Color"])
+ group.links.new(node_col.outputs[0], group.nodes["Set Color"].inputs["Color"])
+ for i, input in enumerate(node_col.inputs):
+ input.default_value = mn.color.random_rgb(i)
- assert snapshot_custom == sample_attribute(mol, "Color", n=50)
+ assert snapshot_custom == mol.named_attribute("Color")
def test_custom_resid_selection():
@@ -131,10 +132,10 @@ def test_iswitch_creation():
def test_op_custom_color():
- mol = mn.io.load(data_dir / "1cd3.cif").object
+ mol = mn.entities.load_local(data_dir / "1cd3.cif").object
mol.select_set(True)
group = mn.blender.nodes.custom_iswitch(
- name=f"MN_color_chain_{mol.name}", iter_list=mol["chain_ids"], dtype="RGBA"
+ name=f"Color Chain {mol.name}", iter_list=mol["chain_ids"], dtype="RGBA"
)
assert group
@@ -164,33 +165,6 @@ def test_color_lookup_supplied():
assert not np.allclose(np.array(item.default_value), col)
-def test_color_chain(snapshot_custom: NumpySnapshotExtension):
- mol = mn.io.load(data_dir / "1cd3.cif", style="cartoon").object
- group_col = mn.blender.nodes.custom_iswitch(
- name=f"MN_color_chain_{mol.name}", iter_list=mol["chain_ids"], dtype="RGBA"
- )
- group = mol.modifiers["MolecularNodes"].node_group
- node_col = mn.blender.nodes.add_custom(group, group_col.name, [0, -200])
- group.links.new(node_col.outputs[0], group.nodes["MN_color_set"].inputs["Color"])
-
- assert snapshot_custom == sample_attribute(mol, "Color")
-
-
-def test_color_entity(snapshot_custom: NumpySnapshotExtension):
- mol = mn.io.fetch("1cd3", style="cartoon", cache_dir=data_dir).object
- group_col = mn.blender.nodes.custom_iswitch(
- name=f"MN_color_entity_{mol.name}",
- iter_list=mol["entity_ids"],
- dtype="RGBA",
- field="entity_id",
- )
- group = mol.modifiers["MolecularNodes"].node_group
- node_col = mn.blender.nodes.add_custom(group, group_col.name, [0, -200])
- group.links.new(node_col.outputs[0], group.nodes["MN_color_set"].inputs["Color"])
-
- assert snapshot_custom == sample_attribute(mol, "Color")
-
-
def get_links(sockets):
links = []
for socket in sockets:
@@ -199,14 +173,18 @@ def get_links(sockets):
def test_change_style():
- model = mn.io.fetch("1cd3", style="cartoon", cache_dir=data_dir).object
+ model = mn.entities.fetch("1cd3", style="cartoon", cache_dir=data_dir).object
style_node_1 = nodes.get_style_node(model).name
mn.blender.nodes.change_style_node(model, "ribbon")
style_node_2 = nodes.get_style_node(model).name
assert style_node_1 != style_node_2
- for style in ["ribbon", "cartoon", "presets", "ball_and_stick", "surface"]:
+ styles_to_check = ["ribbon", "cartoon", "ball_and_stick", "surface"] + list(
+ [f"preset_{i}" for i in [1, 2, 3, 4]]
+ )
+
+ for style in styles_to_check:
style_node_1 = nodes.get_style_node(model)
links_in_1 = [link.from_socket.name for link in get_links(style_node_1.inputs)]
links_out_1 = [
@@ -224,134 +202,99 @@ def test_change_style():
assert len(links_out_1) == len(links_out_2)
-def test_node_topology(snapshot_custom: NumpySnapshotExtension):
- mol = mn.io.fetch("1bna", del_solvent=False, cache_dir=data_dir).object
+@pytest.fixture
+def pdb_8h1b():
+ return mn.entities.fetch("8H1B", del_solvent=False, cache_dir=data_dir, style=None)
- group = nodes.get_mod(mol).node_group
- group.links.new(
- group.nodes["Group Input"].outputs[0], group.nodes["Group Output"].inputs[0]
- )
- node_att = group.nodes.new("GeometryNodeStoreNamedAttribute")
- node_att.inputs[2].default_value = "test_attribute"
- nodes.insert_last_node(group, node_att)
- node_names = [
- node["name"]
- for node in mn.ui.node_info.menu_items["topology"]
- if not node == "break"
- ]
- for node_name in node_names:
- # exclude these particular nodes, as they aren't field nodes and so we shouldn't
- # be testing them here. Will create their own particular tests later
- if "backbone" in node_name or "bonds" in node_name:
- continue
- node_topo = nodes.add_custom(
- group, node_name, location=[x - 300 for x in node_att.location]
- )
+node_names = [
+ node["name"]
+ for node in mn.ui.node_info.menu_items["topology"]
+ if not node == "break"
+]
- if node_name == "MN_topo_point_mask":
- node_topo.inputs["atom_name"].default_value = 61
- type_to_data_type = {
- "VECTOR": "FLOAT_VECTOR",
- "VALUE": "FLOAT",
- "BOOLEAN": "BOOLEAN",
- "INT": "INT",
- "RGBA": "FLOAT_COLOR",
- "ROTATION": "QUATERNION",
- }
-
- for output in node_topo.outputs:
- node_att.data_type = type_to_data_type[output.type]
- input = node_att.inputs["Value"]
-
- for link in input.links:
- group.links.remove(link)
-
- group.links.new(output, input)
-
- assert snapshot_custom == mn.blender.obj.get_attribute(
- mol, "test_attribute", evaluate=True
- )
+def test_nodes_exist():
+ for item in mn.ui.node_info.menu_items:
+ if isinstance(item, str):
+ continue
+ if hasattr(item, "function"):
+ continue
+ for name in [node.name for node in item.items()]:
+ mn.blender.nodes.append(name)
+ assert True
-def test_compute_backbone(snapshot_custom: NumpySnapshotExtension):
- mol = mn.io.fetch("1CCN", del_solvent=False, cache_dir=data_dir).object
+@pytest.mark.parametrize("node_name", node_names)
+@pytest.mark.parametrize("code", codes)
+def test_node_topology(snapshot_custom: NumpySnapshotExtension, code, node_name):
+ mol = mn.entities.fetch(code, del_solvent=False, cache_dir=data_dir, style=None)
- group = nodes.get_mod(mol).node_group
+ group = nodes.get_mod(mol.object).node_group = nodes.new_group()
group.links.new(
group.nodes["Group Input"].outputs[0], group.nodes["Group Output"].inputs[0]
)
node_att = group.nodes.new("GeometryNodeStoreNamedAttribute")
node_att.inputs[2].default_value = "test_attribute"
- node_backbone = nodes.add_custom(group, "MN_topo_compute_backbone")
- nodes.insert_last_node(group, node_backbone)
nodes.insert_last_node(group, node_att)
- node_names = ["MN_topo_backbone"]
- for node_name in node_names:
- node_topo = nodes.add_custom(
- group, node_name, location=[x - 300 for x in node_att.location]
- )
-
- if node_name == "MN_topo_point_mask":
- node_topo.inputs["atom_name"].default_value = 61
-
- type_to_data_type = {
- "VECTOR": "FLOAT_VECTOR",
- "VALUE": "FLOAT",
- "BOOLEAN": "BOOLEAN",
- "INT": "INT",
- "RGBA": "FLOAT_COLOR",
- "ROTATION": "QUATERNION",
- }
-
- for output in node_topo.outputs:
- node_att.data_type = type_to_data_type[output.type]
- input = node_att.inputs["Value"]
-
- for link in input.links:
- group.links.remove(link)
+ # exclude these particular nodes, as they aren't field nodes and so we shouldn't
+ # be testing them here. Will create their own particular tests later
+ if any(
+ keyword in node_name for keyword in ["Backbone", "Bonds", "Bond Count", "DSSP"]
+ ):
+ return None
+
+ node_topo = nodes.add_custom(
+ group, node_name, location=[x - 300 for x in node_att.location]
+ )
- group.links.new(output, input)
+ if node_name == "Residue Mask":
+ node_topo.inputs["atom_name"].default_value = 61
- assert snapshot_custom == mn.blender.obj.get_attribute(
- mol, "test_attribute", evaluate=True
- )
+ type_to_data_type = {
+ "VECTOR": "FLOAT_VECTOR",
+ "VALUE": "FLOAT",
+ "BOOLEAN": "BOOLEAN",
+ "INT": "INT",
+ "RGBA": "FLOAT_COLOR",
+ "ROTATION": "QUATERNION",
+ }
- for angle in ["Phi", "Psi"]:
- output = node_backbone.outputs[angle]
- node_att.data_type = type_to_data_type[output.type]
- input = node_att.inputs["Value"]
+ for output in node_topo.outputs:
+ node_att.data_type = type_to_data_type[output.type]
+ input = node_att.inputs["Value"]
- for link in input.links:
- group.links.remove(link)
+ for link in input.links:
+ group.links.remove(link)
- group.links.new(output, input)
+ group.links.new(output, input)
- assert snapshot_custom == mn.blender.obj.get_attribute(
- mol, "test_attribute", evaluate=True
- )
+ assert snapshot_custom == mn.blender.mesh.named_attribute(
+ mol.object, "test_attribute", evaluate=True
+ )
def test_topo_bonds():
- mol = mn.io.fetch("1BNA", del_solvent=True, style=None, cache_dir=data_dir).object
+ mol = mn.entities.fetch(
+ "1BNA", del_solvent=True, style=None, cache_dir=data_dir
+ ).object
group = nodes.get_mod(mol).node_group = nodes.new_group()
# add the node that will break bonds, set the cutoff to 0
- node_break = nodes.add_custom(group, "MN_topo_bonds_break")
+ node_break = nodes.add_custom(group, "Topology Break Bonds")
nodes.insert_last_node(group, node=node_break)
node_break.inputs["Cutoff"].default_value = 0
# compare the number of edges before and after deleting them with
bonds = mol.data.edges
- no_bonds = mn.blender.obj.evaluated(mol).data.edges
+ no_bonds = mn.blender.mesh.evaluated(mol).data.edges
assert len(bonds) > len(no_bonds)
assert len(no_bonds) == 0
# add the node to find the bonds, and ensure the number of bonds pre and post the nodes
# are the same (other attributes will be different, but for now this is good)
- node_find = nodes.add_custom(group, "MN_topo_bonds_find")
+ node_find = nodes.add_custom(group, "Topology Find Bonds")
nodes.insert_last_node(group, node=node_find)
- bonds_new = mn.blender.obj.evaluated(mol).data.edges
+ bonds_new = mn.blender.mesh.evaluated(mol).data.edges
assert len(bonds) == len(bonds_new)
diff --git a/tests/test_obj.py b/tests/test_obj.py
index 4f3f44bf..f340e2e1 100644
--- a/tests/test_obj.py
+++ b/tests/test_obj.py
@@ -1,9 +1,11 @@
import bpy
import numpy as np
import molecularnodes as mn
-from .utils import sample_attribute
+from molecularnodes.blender import mesh
from .constants import data_dir
+mn.register()
+
def test_creat_obj():
# Create a mesh object named "MyMesh" in the collection "MyCollection"
@@ -11,7 +13,7 @@ def test_creat_obj():
locations = [[0.0, 0.0, 0.0], [1.0, 0.0, 0.0], [1.0, 1.0, 0.0]]
bonds = [(0, 1), (1, 2), (2, 0)]
name = "MyMesh"
- my_object = mn.blender.obj.create_object(locations, bonds, name=name)
+ my_object = mesh.create_object(locations, bonds, name=name)
assert len(my_object.data.vertices) == 3
assert my_object.name == name
@@ -19,13 +21,15 @@ def test_creat_obj():
def test_set_position():
- mol = mn.io.fetch("8FAT", cache_dir=data_dir)
+ mol = mn.entities.fetch("8FAT", cache_dir=data_dir)
- pos_a = mol.get_attribute("position")
+ pos_a = mol.named_attribute("position")
- mol.set_attribute(data=mol.get_attribute("position") + 10, name="position")
+ mol.store_named_attribute(
+ data=mol.named_attribute("position") + 10, name="position"
+ )
- pos_b = mol.get_attribute("position")
+ pos_b = mol.named_attribute("position")
print(f"{pos_a=}")
print(f"{pos_b=}")
@@ -34,8 +38,23 @@ def test_set_position():
def test_eval_mesh():
- a = mn.blender.obj.create_object(np.zeros((3, 3)))
+ a = mesh.create_object(np.zeros((3, 3)))
assert len(a.data.vertices) == 3
- b = mn.blender.obj.create_object(np.zeros((5, 3)))
+ b = mesh.create_object(np.zeros((5, 3)))
assert len(b.data.vertices) == 5
- assert len(mn.blender.obj.evaluate_using_mesh(b).data.vertices) == 5
+ assert len(mesh.evaluate_using_mesh(b).data.vertices) == 5
+
+
+def test_matrix_read_write():
+ obj = mesh.create_object(np.zeros((5, 3)))
+ arr = np.array((5, 4, 4), float)
+ arr = np.random.rand(5, 4, 4)
+
+ mesh.store_named_attribute(obj, "test_matrix", arr, "FLOAT4X4")
+
+ assert np.allclose(mesh.named_attribute(obj, "test_matrix"), arr)
+
+ arr2 = np.random.rand(5, 4, 4)
+ mesh.store_named_attribute(obj, "test_matrix2", arr2)
+
+ assert not np.allclose(mesh.named_attribute(obj, "test_matrix2"), arr)
diff --git a/tests/test_ops.py b/tests/test_ops.py
index 6ce5d36d..9e6002e8 100644
--- a/tests/test_ops.py
+++ b/tests/test_ops.py
@@ -2,15 +2,15 @@
import pytest
import numpy as np
import molecularnodes as mn
-from molecularnodes.blender.obj import ObjectTracker, get_attribute
+
+from molecularnodes.blender.mesh import ObjectTracker, named_attribute
from .utils import sample_attribute, NumpySnapshotExtension
from .constants import data_dir, codes, attributes
# register the operators, which isn't done by default when loading bpy
# just via headless float_decimals
-mn.unregister()
-mn.register()
+mn._test_register()
@pytest.mark.parametrize("code", codes)
@@ -30,7 +30,9 @@ def test_op_api_cartoon(
bpy.ops.mn.import_wwpdb()
obj_1 = bpy.context.active_object
- obj_2 = mn.io.fetch(code, style=style, format=format, cache_dir=data_dir).object
+ obj_2 = mn.entities.fetch(
+ code, style=style, format=format, cache_dir=data_dir
+ ).object
# objects being imported via each method should have identical snapshots
for mol in [obj_1, obj_2]:
@@ -49,27 +51,27 @@ def test_op_local(snapshot_custom, code, file_format):
scene.MN_import_build_assembly = False
scene.MN_import_del_solvent = False
scene.MN_import_format_download = file_format
- path = str(mn.io.download(code=code, format=file_format, cache=data_dir))
+ path = str(mn.download.download(code=code, format=file_format, cache=data_dir))
scene.MN_import_local_path = path
scene.MN_centre_type = "centroid"
scene.MN_import_centre = False
with ObjectTracker() as o:
bpy.ops.mn.import_protein_local()
- bob = o.latest()
+ obj = o.latest()
scene.MN_import_centre = True
with ObjectTracker() as o:
bpy.ops.mn.import_protein_local()
- bob_centred = o.latest()
+ obj_centred = o.latest()
- bob_pos, bob_centred_pos = [
- sample_attribute(x, "position", evaluate=False) for x in [bob, bob_centred]
+ obj_pos, obj_centred_pos = [
+ sample_attribute(x, "position", evaluate=False) for x in [obj, obj_centred]
]
- assert snapshot_custom == bob_pos
- assert snapshot_custom == bob_centred_pos
- assert not np.allclose(bob_pos, bob_centred_pos)
+ assert snapshot_custom == obj_pos
+ assert snapshot_custom == obj_centred_pos
+ assert not np.allclose(obj_pos, obj_centred_pos)
def test_op_api_mda(snapshot_custom: NumpySnapshotExtension):
@@ -81,19 +83,14 @@ def test_op_api_mda(snapshot_custom: NumpySnapshotExtension):
bpy.context.scene.MN_import_md_trajectory = traj
bpy.context.scene.MN_import_style = "ribbon"
- bpy.ops.mn.import_protein_md()
- obj_1 = bpy.context.active_object
- assert obj_1.name == name
- assert not bpy.data.collections.get(f"{name}_frames")
-
- bpy.context.scene.MN_md_in_memory = True
- name = "NewTrajectoryInMemory"
+ with ObjectTracker() as o:
+ bpy.ops.mn.import_protein_md()
+ obj_1 = o.latest()
- obj_2, universe = mn.io.md.load(topo, traj, name="test", style="ribbon")
+ assert obj_1.name == name
- # test the 'frames' collection doesn't exist, as it should only be created when reading
- # into memory
- assert not bpy.data.collections.get(f"{obj_2.name}_frames")
+ traj = mn.entities.trajectory.load(topo, traj, name="test", style="ribbon")
+ obj_2 = traj.object
for mol in [obj_1, obj_2]:
for att in attributes:
@@ -101,10 +98,10 @@ def test_op_api_mda(snapshot_custom: NumpySnapshotExtension):
# capture positions, change the frame number and test that the positions have updated
# and cahnged
- pos_1, pos_2 = [get_attribute(x, "position") for x in [obj_1, obj_2]]
+ pos_1, pos_2 = [named_attribute(x, "position") for x in [obj_1, obj_2]]
bpy.context.scene.frame_set(4)
- assert not np.allclose(get_attribute(obj_1, "position"), pos_1)
+ assert not np.allclose(named_attribute(obj_1, "position"), pos_1)
assert np.allclose(
- get_attribute(obj_1, "position"), get_attribute(obj_2, "position")
+ named_attribute(obj_1, "position"), named_attribute(obj_2, "position")
)
diff --git a/tests/test_parse.py b/tests/test_parse.py
index c3d26aba..eed5f73f 100644
--- a/tests/test_parse.py
+++ b/tests/test_parse.py
@@ -6,34 +6,34 @@
@pytest.fixture
def filepath():
- return data_dir / '1f2n.bcif'
+ return data_dir / "1f2n.bcif"
def test_bcif_init(filepath):
- bcif = mn.io.parse.BCIF(filepath)
+ bcif = mn.entities.BCIF(filepath)
assert bcif.file_path == filepath
def test_bcif_read(filepath):
- bcif = mn.io.parse.BCIF(filepath)
+ bcif = mn.entities.BCIF(filepath)
assert bcif.file is not None
def test_bcif_get_structure(filepath):
- bcif = mn.io.parse.BCIF(filepath)
+ bcif = mn.entities.BCIF(filepath)
structure = bcif.get_structure()
assert structure is not None
# assert structure.shape[1] == len(bcif)
def test_bcif_assemblies(filepath):
- bcif = mn.io.parse.BCIF(filepath)
+ bcif = mn.entities.BCIF(filepath)
assemblies = bcif.assemblies()
assert assemblies is not None
def test_bcif_entity_ids(filepath):
- bcif = mn.io.parse.BCIF(filepath)
+ bcif = mn.entities.BCIF(filepath)
entity_ids = bcif.entity_ids
assert entity_ids is not None
- assert entity_ids == ['CAPSID PROTEIN', 'CALCIUM ION', 'water']
+ assert entity_ids == ["CAPSID PROTEIN", "CALCIUM ION", "water"]
diff --git a/tests/test_pdbx.py b/tests/test_pdbx.py
index 60a9e7b3..3880748e 100644
--- a/tests/test_pdbx.py
+++ b/tests/test_pdbx.py
@@ -1,5 +1,4 @@
import molecularnodes as mn
-import numpy as np
import random
from .constants import data_dir
@@ -7,13 +6,14 @@
def test_ss_label_to_int():
- examples = ['TURN_TY1_P68', 'BEND64', 'HELX_LH_PP_P9', 'STRN44']
+ examples = ["TURN_TY1_P68", "BEND64", "HELX_LH_PP_P9", "STRN44"]
assert [3, 3, 1, 2] == [
- mn.io.parse.cif._ss_label_to_int(x) for x in examples]
+ mn.entities.molecule.pdbx._ss_label_to_int(x) for x in examples
+ ]
def test_get_ss_from_mmcif(snapshot_custom: NumpySnapshotExtension):
- mol = mn.io.load(data_dir / '1cd3.cif')
+ mol = mn.entities.load_local(data_dir / "1cd3.cif")
# mol2, fil2 = mn.io.fetch('1cd3')
@@ -26,7 +26,8 @@ def test_get_ss_from_mmcif(snapshot_custom: NumpySnapshotExtension):
def test_secondary_structure_no_helix(snapshot_custom):
- m = mn.io.fetch('7ZL4', cache_dir=data_dir)
+ m = mn.entities.fetch("7ZL4", cache_dir=data_dir)
assert snapshot_custom == sample_attribute(
- m.object, 'sec_struct', n=500, evaluate=False)
+ m.object, "sec_struct", n=500, evaluate=False
+ )
diff --git a/tests/test_pkg.py b/tests/test_pkg.py
deleted file mode 100644
index 7d19f995..00000000
--- a/tests/test_pkg.py
+++ /dev/null
@@ -1,18 +0,0 @@
-import molecularnodes as mn
-
-
-def test_name_versions():
- for name in mn.pkg.get_pkgs().keys():
- print(f"{name}")
- print(f"{mn.pkg.is_current(name)}")
- assert mn.pkg.is_current(name)
-
-
-def test_is_current():
- assert mn.pkg.is_current('biotite')
-
-
-def test_get_pkgs():
- names = ['biotite', 'MDAnalysis', 'mrcfile', 'starfile', 'msgpack', 'pillow']
- for name in mn.pkg.get_pkgs().keys():
- assert name in names
diff --git a/tests/test_select.py b/tests/test_select.py
index 255ba642..56469b75 100644
--- a/tests/test_select.py
+++ b/tests/test_select.py
@@ -5,11 +5,10 @@
import pytest
-def create_debug_group(name='MolecularNodesDebugGroup'):
+def create_debug_group(name="MolecularNodesDebugGroup"):
group = nodes.new_group(name=name, fallback=False)
- info = group.nodes.new('GeometryNodeObjectInfo')
- group.links.new(info.outputs['Geometry'],
- group.nodes['Group Output'].inputs[0])
+ info = group.nodes.new("GeometryNodeObjectInfo")
+ group.links.new(info.outputs["Geometry"], group.nodes["Group Output"].inputs[0])
return group
@@ -20,29 +19,31 @@ def evaluate(object):
custom_selections = [
- ('1, 3, 5-7', np.array((1, 3, 5, 6, 7))),
- ('5, 9-20', np.append(5, np.arange(9, 21))),
- ('1, 7, 8, 9', np.array((1, 7, 8, 9)))
+ ("1, 3, 5-7", np.array((1, 3, 5, 6, 7))),
+ ("5, 9-20", np.append(5, np.arange(9, 21))),
+ ("1, 7, 8, 9", np.array((1, 7, 8, 9))),
]
-@pytest.mark.parametrize('selection', custom_selections)
+@pytest.mark.parametrize("selection", custom_selections)
def test_select_multiple_residues(selection):
n_atoms = 100
- object = mn.blender.obj.create_object(np.zeros((n_atoms, 3)))
- mn.blender.obj.set_attribute(object, 'res_id', np.arange(n_atoms) + 1)
+ object = mn.blender.mesh.create_object(np.zeros((n_atoms, 3)))
+ mn.blender.mesh.store_named_attribute(object, "res_id", np.arange(n_atoms) + 1)
mod = nodes.get_mod(object)
group = nodes.new_group(fallback=False)
mod.node_group = group
- sep = group.nodes.new('GeometryNodeSeparateGeometry')
+ sep = group.nodes.new("GeometryNodeSeparateGeometry")
nodes.insert_last_node(group, sep)
- node_sel_group = nodes.resid_multiple_selection('custom', selection[0])
+ node_sel_group = nodes.resid_multiple_selection("custom", selection[0])
node_sel = nodes.add_custom(group, node_sel_group.name)
- group.links.new(node_sel.outputs['Selection'], sep.inputs['Selection'])
+ group.links.new(node_sel.outputs["Selection"], sep.inputs["Selection"])
- vertices_count = len(mn.blender.obj.evaluated(object).data.vertices)
+ vertices_count = len(mn.blender.mesh.evaluated(object).data.vertices)
assert vertices_count == len(selection[1])
- assert (mn.blender.obj.get_attribute(
- mn.blender.obj.evaluated(object), 'res_id') == selection[1]).all()
+ assert (
+ mn.blender.mesh.named_attribute(mn.blender.mesh.evaluated(object), "res_id")
+ == selection[1]
+ ).all()
diff --git a/tests/test_session.py b/tests/test_session.py
new file mode 100644
index 00000000..0217b44f
--- /dev/null
+++ b/tests/test_session.py
@@ -0,0 +1,15 @@
+import bpy
+import molecularnodes as mn
+
+mn._test_register()
+
+
+def test_session_present():
+ assert isinstance(mn.session.get_session(), mn.session.MNSession)
+
+
+def test_persistent_handlers_added():
+ load_handlers = [handler.__name__ for handler in bpy.app.handlers.load_post]
+ save_handlers = [handler.__name__ for handler in bpy.app.handlers.save_post]
+ assert "_pickle" in save_handlers
+ assert "_load" in load_handlers
diff --git a/tests/test_setup.py b/tests/test_setup.py
index a2a1ee18..ab882534 100644
--- a/tests/test_setup.py
+++ b/tests/test_setup.py
@@ -3,6 +3,13 @@
def test_template():
- mn.utils.template_install()
+ mn.template.install()
bpy.ops.wm.read_homefile(app_template="Molecular Nodes")
- assert not bpy.data.objects.get('Cube')
+ assert not bpy.data.objects.get("Cube")
+
+ mn.template.uninstall()
+ try:
+ bpy.ops.wm.read_homefile(app_template="Molecular Nodes")
+ assert False
+ except Exception:
+ assert True
diff --git a/tests/test_star.py b/tests/test_star.py
index d53df983..fa51c8bb 100644
--- a/tests/test_star.py
+++ b/tests/test_star.py
@@ -4,43 +4,35 @@
import starfile
from .constants import data_dir
-mn.unregister()
-mn.register()
-
-try:
- import pyopenvdb
- SKIP = False
-except ImportError:
- SKIP = True
+mn._test_register()
@pytest.mark.parametrize("type", ["cistem", "relion"])
def test_starfile_attributes(type):
file = data_dir / f"{type}.star"
- ensemble = mn.io.star.load(file)
+ ensemble = mn.entities.ensemble.load_starfile(file)
star = starfile.read(file)
- if type == 'relion':
- df = star['particles'].merge(star['optics'], on='rlnOpticsGroup')
- euler_angles = df[['rlnAngleRot',
- 'rlnAngleTilt', 'rlnAnglePsi']].to_numpy()
+ if type == "relion":
+ df = star["particles"].merge(star["optics"], on="rlnOpticsGroup")
+ euler_angles = df[["rlnAngleRot", "rlnAngleTilt", "rlnAnglePsi"]].to_numpy()
- elif type == 'cistem':
+ elif type == "cistem":
df = star
- euler_angles = df[['cisTEMAnglePhi',
- 'cisTEMAngleTheta', 'cisTEMAnglePsi']].to_numpy()
+ euler_angles = df[
+ ["cisTEMAnglePhi", "cisTEMAngleTheta", "cisTEMAnglePsi"]
+ ].to_numpy()
# Calculate Scipy rotation from the euler angles
rot_from_euler = quats = R.from_euler(
- seq='ZYZ', angles=euler_angles, degrees=True
+ seq="ZYZ", angles=euler_angles, degrees=True
).inv()
# Activate the rotation debug mode in the nodetreee and get the quaternion attribute
- debugnode = mn.blender.nodes.star_node(
- ensemble.node_group).node_tree.nodes['Switch.001']
- debugnode.inputs['Switch'].default_value = True
- quat_attribute = ensemble.get_attribute('MNDEBUGEuler', evaluate=True)
+ debugnode = ensemble.star_node.node_tree.nodes["Switch.001"]
+ debugnode.inputs["Switch"].default_value = True
+ quat_attribute = ensemble.named_attribute("MNDEBUGEuler", evaluate=True)
# Convert from blender to scipy conventions and then into Scipy rotation
rot_from_geo_nodes = R.from_quat(quat_attribute[:, [1, 2, 3, 0]])
@@ -51,15 +43,13 @@ def test_starfile_attributes(type):
def test_categorical_attributes():
file = data_dir / "cistem.star"
- ensemble = mn.io.star.load(file)
- assert 'cisTEMOriginalImageFilename_categories' in ensemble.object
+ ensemble = mn.entities.ensemble.load_starfile(file)
+ assert "cisTEMOriginalImageFilename_categories" in ensemble.object
def test_micrograph_conversion():
- from pathlib import Path
-
file = data_dir / "cistem.star"
- ensemble = mn.io.star.load(file)
+ ensemble = mn.entities.ensemble.load_starfile(file)
tiff_path = data_dir / "montage.tiff"
tiff_path.unlink(missing_ok=True)
ensemble._convert_mrc_to_tiff()
@@ -68,32 +58,20 @@ def test_micrograph_conversion():
def test_micrograph_loading():
import bpy
+
file = data_dir / "cistem.star"
tiff_path = data_dir / "montage.tiff"
tiff_path.unlink(missing_ok=True)
- ensemble = mn.io.star.load(file)
+ ensemble = mn.entities.ensemble.load_starfile(file)
assert not tiff_path.exists()
- ensemble.star_node.inputs['Show Micrograph'].default_value = True
+ ensemble.star_node.inputs["Show Micrograph"].default_value = True
bpy.context.evaluated_depsgraph_get().update()
assert tiff_path.exists()
# Ensure montage get only loaded once
- assert sum(1 for image in bpy.data.images.keys()
- if 'montage' in image) == 1
- assert ensemble.micrograph_material.node_tree.nodes['Image Texture'].image.name == 'montage.tiff'
- assert ensemble.star_node.inputs['Micrograph'].default_value.name == 'montage.tiff'
-
-
-@pytest.mark.skipif(SKIP, reason='Test may segfault on GHA')
-def test_rehydration(tmp_path):
- import bpy
- bpy.ops.wm.read_homefile()
- ensemble = mn.io.star.load(data_dir / "cistem.star")
- bpy.ops.wm.save_as_mainfile(filepath=str(tmp_path / "test.blend"))
- assert ensemble._update_micrograph_texture in bpy.app.handlers.depsgraph_update_post
- bpy.ops.wm.read_homefile()
- assert ensemble._update_micrograph_texture not in bpy.app.handlers.depsgraph_update_post
- bpy.ops.wm.open_mainfile(filepath=str(tmp_path / "test.blend"))
- new_ensemble = bpy.types.Scene.MN_starfile_ensembles[0]
- assert new_ensemble._update_micrograph_texture in bpy.app.handlers.depsgraph_update_post
- assert new_ensemble.data.equals(ensemble.data)
+ assert sum(1 for image in bpy.data.images.keys() if "montage" in image) == 1
+ assert (
+ ensemble.micrograph_material.node_tree.nodes["Image Texture"].image.name
+ == "montage.tiff"
+ )
+ assert ensemble.star_node.inputs["Micrograph"].default_value.name == "montage.tiff"
diff --git a/tests/test_trajectory.py b/tests/test_trajectory.py
new file mode 100644
index 00000000..4ec1ec2d
--- /dev/null
+++ b/tests/test_trajectory.py
@@ -0,0 +1,209 @@
+import bpy
+import os
+import pytest
+import molecularnodes as mn
+from molecularnodes.blender.mesh import named_attribute
+
+import MDAnalysis as mda
+import numpy as np
+from .constants import data_dir
+from .utils import sample_attribute, NumpySnapshotExtension
+
+mn._test_register()
+
+
+class TestTrajectory:
+ @pytest.fixture(scope="module")
+ def universe(self):
+ top = data_dir / "md_ppr/box.gro"
+ traj = data_dir / "md_ppr/first_5_frames.xtc"
+ u = mda.Universe(top, traj)
+ return u
+
+ @pytest.fixture(scope="module")
+ def universe_with_bonds(self):
+ top = data_dir / "md_ppr/md.tpr"
+ traj = data_dir / "md_ppr/md.gro"
+ u = mda.Universe(top, traj)
+ return u
+
+ @pytest.fixture(scope="module")
+ def Trajectory_cross_boundary(self):
+ topo = data_dir / "martini/dode_membrane/topol_nowat.gro"
+ traj = data_dir / "martini/dode_membrane/traj_imaged_dt1ns_frames_1-10.xtc"
+ u = mda.Universe(topo, traj)
+ traj = mn.entities.Trajectory(u)
+ traj.create_object()
+ return traj
+
+ @pytest.fixture(scope="module")
+ def Trajectory(self, universe):
+ traj = mn.entities.Trajectory(universe)
+ traj.create_object()
+ return traj
+
+ @pytest.fixture(scope="module")
+ def Trajectory_with_bonds(self, universe_with_bonds):
+ traj = mn.entities.Trajectory(universe_with_bonds)
+ traj.create_object()
+ return traj
+
+ @pytest.fixture(scope="module")
+ def session(self):
+ return mn.session.get_session()
+
+ def test_include_bonds(self, Trajectory_with_bonds):
+ assert Trajectory_with_bonds.object.data.edges.items() != []
+
+ def test_attributes_added(self, Trajectory):
+ attributes = Trajectory.object.data.attributes.keys()
+ # check if all attributes are added.
+
+ attribute_added = [
+ "vdw_radii",
+ "b_factor",
+ "atomic_number",
+ "res_id",
+ "res_name",
+ "chain_id",
+ "atom_types",
+ "atom_name",
+ "position",
+ "is_backbone",
+ "is_alpha_carbon",
+ "is_solvent",
+ "is_nucleic",
+ "is_peptide",
+ ]
+ for att in attribute_added:
+ assert att in attributes
+
+ def test_trajectory_update(self, snapshot_custom, Trajectory):
+ traj = Trajectory
+ bpy.context.scene.frame_set(0)
+ pos_a = traj.named_attribute("position")
+ assert snapshot_custom == pos_a
+
+ bpy.context.scene.frame_set(4)
+ pos_b = traj.named_attribute("position")
+ assert snapshot_custom == pos_b
+
+ assert not np.allclose(pos_a, pos_b)
+
+ @pytest.mark.parametrize("interpolate", [True, False])
+ def test_subframes(self, Trajectory, interpolate):
+ traj = Trajectory
+ bpy.context.scene.frame_set(0)
+ traj.subframes = 0
+ traj.interpolate = interpolate
+ verts_a = traj.named_attribute("position")
+
+ bpy.context.scene.frame_set(1)
+ verts_b = traj.named_attribute("position")
+
+ # should be different because we have changed the frame
+ assert not np.allclose(verts_a, verts_b)
+
+ for subframes in [1, 2, 3, 4]:
+ bpy.context.scene.frame_set(0)
+ frame = 1
+ fraction = frame % (subframes + 1) / (subframes + 1)
+ traj.subframes = subframes
+
+ bpy.context.scene.frame_set(frame)
+ verts_c = traj.named_attribute("position")
+
+ if interpolate:
+ # now using subframes and having interpolate=True there should be a difference
+ assert not np.allclose(verts_b, verts_c)
+ assert np.allclose(verts_c, mn.utils.lerp(verts_a, verts_b, t=fraction))
+ else:
+ # without using interopolation, the subframes means it should default back
+ # to the previous best selected frame
+ assert np.allclose(verts_a, verts_c)
+
+ def test_correct_periodic(self, snapshot_custom, Trajectory_cross_boundary):
+ u = Trajectory_cross_boundary
+ u.subframes = 5
+ bpy.context.scene.frame_set(2)
+ pos_a = u.named_attribute("position")
+ u.object.mn.correct_periodic = False
+ pos_b = u.named_attribute("position")
+
+ assert not np.allclose(pos_a, pos_b)
+ assert snapshot_custom == pos_a
+
+ def test_update_selection(self, snapshot_custom, Trajectory):
+ # to API add selections we currently have to operate on the UIList rather than the
+ # universe itself, which isn't great
+ u = Trajectory
+ bpy.context.scene.frame_set(0)
+ sel = u.add_selection(name="custom_sel_1", selection_str="around 3.5 protein")
+ bpy.context.scene.frame_set(5)
+ sel_1 = u.named_attribute("custom_sel_1")
+ bpy.context.scene.frame_set(50)
+ sel_2 = u.named_attribute("custom_sel_1")
+ # when we are updating, the selection around the protein will change from frame
+ # to frame
+ assert not (sel_1 != sel_2).all()
+
+ # if we stop the selection from updating, then even when we change the frame
+ # the selection will remain the same
+ sel.updating = False
+ bpy.context.scene.frame_set(100)
+ assert (sel_2 == u.named_attribute("custom_sel_1")).all()
+ # if we change the selection to updating, then the selection will be updated
+ # and will no longer match with what came earlier
+ sel.updating = False
+ assert not (sel_2 != u.named_attribute("custom_sel_1")).all()
+
+ def test_save_persistance(
+ self,
+ snapshot_custom: NumpySnapshotExtension,
+ tmp_path,
+ universe,
+ session: mn.session.MNSession,
+ ):
+ session.clear()
+ traj = mn.entities.Trajectory(universe)
+ traj.create_object()
+ uuid = traj.uuid
+ bpy.context.scene.frame_set(0)
+ filepath = str(tmp_path / "test.blend")
+
+ # test that we can save the file and it is created only after saving
+ assert not os.path.exists(session.stashpath(filepath))
+ bpy.ops.wm.save_as_mainfile(filepath=filepath)
+ assert os.path.exists(filepath)
+ assert os.path.exists(session.stashpath(filepath))
+ bpy.ops.wm.open_mainfile(filepath=filepath)
+
+ traj = mn.session.get_session().trajectories[uuid]
+ verts_frame_0 = traj.named_attribute("position")
+ bpy.context.scene.frame_set(4)
+ verts_frame_4 = traj.named_attribute("position")
+
+ assert snapshot_custom == verts_frame_4
+ assert not np.allclose(verts_frame_0, verts_frame_4)
+
+
+@pytest.mark.parametrize("toplogy", ["pent/prot_ion.tpr", "pent/TOPOL2.pdb"])
+def test_martini(snapshot_custom: NumpySnapshotExtension, toplogy):
+ universe = mda.Universe(
+ data_dir / "martini" / toplogy, data_dir / "martini/pent/PENT2_100frames.xtc"
+ )
+ traj = mn.entities.Trajectory(universe)
+ traj.create_object()
+ obj = traj.object
+ bpy.context.scene.frame_set(0)
+ pos_a = traj.named_attribute("position")
+
+ bpy.context.scene.frame_set(50)
+ pos_b = traj.named_attribute("position")
+ assert not np.allclose(pos_a, pos_b)
+
+ for att in obj.data.attributes.keys():
+ assert snapshot_custom == traj.named_attribute(att)
+
+ for att in obj.data.attributes.keys():
+ assert snapshot_custom == traj.named_attribute(att)
diff --git a/tests/test_utils.py b/tests/test_utils.py
new file mode 100644
index 00000000..48b1997f
--- /dev/null
+++ b/tests/test_utils.py
@@ -0,0 +1,12 @@
+import molecularnodes as mn
+import bpy
+import numpy as np
+
+mn._test_register()
+
+
+def test_correct_1d():
+ assert np.allclose(
+ mn.utils.correct_periodic_1d(np.array((0.9, 0.1)), np.array((0.1, 0.9)), 1.0),
+ np.array((1.1, -0.1)),
+ )
diff --git a/tests/utils.py b/tests/utils.py
index cc7586b5..1f2e2a85 100644
--- a/tests/utils.py
+++ b/tests/utils.py
@@ -1,7 +1,11 @@
import bpy
+
+# from .conftest import molecularnodes as mn
import molecularnodes as mn
+
import numpy as np
import random
+# import pathlib
from syrupy.extensions.amber import AmberSnapshotExtension
@@ -11,14 +15,21 @@
# and when comparing them, reads the list back into a numpy array for comparison
# it checks for 'isclose' for floats and otherwise looks for absolute comparison
class NumpySnapshotExtension(AmberSnapshotExtension):
+ def __init__(self):
+ super().__init__()
+ self.custom_suffix: str | None = None
- def serialize(self, data, **kwargs):
+ def serialize(self, data, cutoff=1000, **kwargs):
if isinstance(data, np.ndarray):
+ shape = data.shape
+ if len(shape) == 1:
+ if len(data) > cutoff:
+ data = data[:cutoff]
+ else:
+ data = data[: int(cutoff / 10),]
+
return np.array2string(
- data,
- precision=1,
- threshold=1e3,
- floatmode='maxprec_equal'
+ data, precision=1, threshold=2e3, floatmode="maxprec_equal"
)
return super().serialize(data, **kwargs)
@@ -41,23 +52,21 @@ def serialize(self, data, **kwargs):
# else:
# assert (serialized_data == np.array(snapshot_data)).all()
- # else:
- # super().matches(serialized_data=serialized_data, snapshot_data=snapshot_data)
+ # else:
+ # super().matches(serialized_data=serialized_data, snapshot_data=snapshot_data)
-def sample_attribute(object,
- attribute,
- n=100,
- evaluate=True,
- error: bool = False,
- seed=6):
- if isinstance(object, mn.io.parse.molecule.Molecule):
+def sample_attribute(
+ object, attribute, n=100, evaluate=True, error: bool = False, seed=6
+):
+ if isinstance(object, mn.entities.molecule.Molecule):
object = object.object
random.seed(seed)
if error:
- attribute = mn.blender.obj.get_attribute(
- object, attribute, evaluate=evaluate)
+ attribute = mn.blender.mesh.named_attribute(
+ object, attribute, evaluate=evaluate
+ )
length = len(attribute)
if n > length:
@@ -71,10 +80,8 @@ def sample_attribute(object,
return attribute[idx, :]
else:
try:
- attribute = mn.blender.obj.get_attribute(
- object=object,
- name=attribute,
- evaluate=evaluate
+ attribute = mn.blender.mesh.named_attribute(
+ object=object, name=attribute, evaluate=evaluate
)
length = len(attribute)
@@ -91,21 +98,17 @@ def sample_attribute(object,
return np.array(e)
-def sample_attribute_to_string(object,
- attribute,
- n=100,
- evaluate=True,
- precision=3,
- seed=6):
- if isinstance(object, mn.io.parse.molecule.Molecule):
+def sample_attribute_to_string(
+ object, attribute, n=100, evaluate=True, precision=3, seed=6
+):
+ if isinstance(object, mn.entities.molecule.Molecule):
object = object.object
try:
array = sample_attribute(
- object, attribute=attribute, n=n, evaluate=evaluate, seed=seed)
- except AttributeError as e:
- print(
- f"Error {e}, unable to sample attribute {attribute} from {object}"
+ object, attribute=attribute, n=n, evaluate=evaluate, seed=seed
)
+ except AttributeError as e:
+ print(f"Error {e}, unable to sample attribute {attribute} from {object}")
return str(e)
if array.dtype != bool:
@@ -126,19 +129,3 @@ def sample_attribute_to_string(object,
array = attribute[idx, :]
return np.array2string(array, precision=precision, threshold=threshold)
-
-
-def remove_all_molecule_objects(mda_session):
- for object in bpy.data.objects:
- try:
- obj_type = object["type"]
- if obj_type == "molecule":
- bpy.data.objects.remove(object)
- except KeyError:
- pass
- # remove frame change
- bpy.context.scene.frame_set(0)
-
- mda_session.universe_reps = {}
- mda_session.atom_reps = {}
- mda_session.rep_names = []