Skip to content

Instantly share code, notes, and snippets.

@NehaKoppikar
Created January 12, 2021 21:24
Show Gist options
  • Star 0 You must be signed in to star a gist
  • Fork 0 You must be signed in to fork a gist
  • Save NehaKoppikar/5f9a396de84c53d863cacea781878527 to your computer and use it in GitHub Desktop.
Save NehaKoppikar/5f9a396de84c53d863cacea781878527 to your computer and use it in GitHub Desktop.
github_analysis.ipynb
Display the source blob
Display the rendered blob
Raw
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.9.1"
},
"latex_envs": {
"LaTeX_envs_menu_present": true,
"autoclose": false,
"autocomplete": true,
"bibliofile": "biblio.bib",
"cite_by": "apalike",
"current_citInitial": 1,
"eqLabelWithNumbers": true,
"eqNumInitial": 1,
"hotkeys": {
"equation": "Ctrl-E",
"itemize": "Ctrl-I"
},
"labels_anchors": false,
"latex_user_defs": false,
"report_style_numbering": false,
"user_envs_cfg": false
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": true,
"sideBar": true,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_position": {},
"toc_section_display": true,
"toc_window_display": false
},
"colab": {
"name": "github_analysis.ipynb",
"provenance": [],
"toc_visible": true,
"include_colab_link": true
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/NehaKoppikar/5f9a396de84c53d863cacea781878527/github_analysis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:01:51.956116Z",
"start_time": "2020-08-14T21:01:51.948283Z"
},
"colab": {
"base_uri": "https://localhost:8080/",
"height": 17
},
"id": "tvMDExh0WWhz",
"outputId": "b88afc52-a2bd-48a0-c056-78ec0377cee6"
},
"source": [
"from IPython.display import Javascript\n",
"\n",
"def window_open(url):\n",
" display(Javascript('window.open(\"{url}\");'.format(url=url)))\n",
"\n",
"\n",
"window_open('https://datapane.com/home')"
],
"execution_count": 1,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/javascript": [
"window.open(\"https://datapane.com/home\");"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "xG5pIwirWqrm",
"outputId": "91cf5f0c-2c20-499d-a423-7aa0d89d4010"
},
"source": [
"!pip install datapane"
],
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"text": [
"Collecting datapane\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/47/7d/5055af377d01f99d408c807bdef1f44ab75c2ff25a20ba790e5e35128d3d/datapane-0.9.0-py3-none-any.whl (1.4MB)\n",
"\u001b[K |████████████████████████████████| 1.4MB 8.1MB/s \n",
"\u001b[?25hCollecting plotly<5.0.0,>=4.8.1\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/1f/f6/bd3c17c8003b6641df1228e80e1acac97ed8402635e46c2571f8e1ef63af/plotly-4.14.3-py2.py3-none-any.whl (13.2MB)\n",
"\u001b[K |████████████████████████████████| 13.2MB 15.5MB/s \n",
"\u001b[?25hCollecting boltons<21.0.0,>=20.2.1\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/71/e1/e7979a4a6d4b296b5935e926549fff540f7670ddaf09bbf137e2b022c039/boltons-20.2.1-py2.py3-none-any.whl (170kB)\n",
"\u001b[K |████████████████████████████████| 174kB 40.7MB/s \n",
"\u001b[?25hCollecting nbconvert<6.1.0,>=6.0.0\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/13/2f/acbe7006548f3914456ee47f97a2033b1b2f3daf921b12ac94105d87c163/nbconvert-6.0.7-py3-none-any.whl (552kB)\n",
"\u001b[K |████████████████████████████████| 552kB 39.2MB/s \n",
"\u001b[?25hCollecting PyYAML<6.0.0,>=5.3.0\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/64/c2/b80047c7ac2478f9501676c988a5411ed5572f35d1beff9cae07d321512c/PyYAML-5.3.1.tar.gz (269kB)\n",
"\u001b[K |████████████████████████████████| 276kB 45.8MB/s \n",
"\u001b[?25hRequirement already satisfied: pandas<2.0.0,>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from datapane) (1.1.5)\n",
"Collecting stringcase<2.0.0,>=1.2.0\n",
" Downloading https://files.pythonhosted.org/packages/f3/1f/1241aa3d66e8dc1612427b17885f5fcd9c9ee3079fc0d28e9a3aeeb36fa3/stringcase-1.2.0.tar.gz\n",
"Requirement already satisfied: tabulate<0.9.0,>=0.8.7 in /usr/local/lib/python3.6/dist-packages (from datapane) (0.8.7)\n",
"Collecting munch<3.0.0,>=2.5.0\n",
" Downloading https://files.pythonhosted.org/packages/cc/ab/85d8da5c9a45e072301beb37ad7f833cd344e04c817d97e0cc75681d248f/munch-2.5.0-py2.py3-none-any.whl\n",
"Collecting importlib_resources<4.0.0,>=3.0.0\n",
" Downloading https://files.pythonhosted.org/packages/8d/94/2f6ceee0c4e63bff0177c07e68d27c937a19f6bc77c4739755b49f5adb04/importlib_resources-3.3.1-py2.py3-none-any.whl\n",
"Collecting colorlog<5.0.0,>=4.1.0\n",
" Downloading https://files.pythonhosted.org/packages/4e/c8/c16d30bbed11a1722060014c246d124582d1f781b26f5859d8dacc3e08e1/colorlog-4.6.2-py2.py3-none-any.whl\n",
"Collecting validators<0.19.0,>=0.18.0\n",
" Downloading https://files.pythonhosted.org/packages/db/2f/7fed3ee94ad665ad2c1de87f858f10a7785251ff75b4fd47987888d07ef1/validators-0.18.2-py3-none-any.whl\n",
"Collecting requests-toolbelt<0.10.0,>=0.9.1\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/60/ef/7681134338fc097acef8d9b2f8abe0458e4d87559c689a8c306d0957ece5/requests_toolbelt-0.9.1-py2.py3-none-any.whl (54kB)\n",
"\u001b[K |████████████████████████████████| 61kB 7.0MB/s \n",
"\u001b[?25hRequirement already satisfied: packaging<21.0,>=20.3 in /usr/local/lib/python3.6/dist-packages (from datapane) (20.8)\n",
"Collecting flit-core<3.1.0,>=3.0.0\n",
" Downloading https://files.pythonhosted.org/packages/a8/66/67758f788959c2557c4d0f80e4895c3c0802873be95b82a5213ea39542d7/flit_core-3.0.0-py3-none-any.whl\n",
"Collecting ruamel.yaml<0.17.0,>=0.16.5\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/7e/39/186f14f3836ac5d2a6a042c8de69988770e8b9abb537610edc429e4914aa/ruamel.yaml-0.16.12-py2.py3-none-any.whl (111kB)\n",
"\u001b[K |████████████████████████████████| 112kB 44.7MB/s \n",
"\u001b[?25hCollecting pyarrow<3.0.0,>=2.0.0\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/d7/e1/27958a70848f8f7089bff8d6ebe42519daf01f976d28b481e1bfd52c8097/pyarrow-2.0.0-cp36-cp36m-manylinux2014_x86_64.whl (17.7MB)\n",
"\u001b[K |████████████████████████████████| 17.7MB 259kB/s \n",
"\u001b[?25hRequirement already satisfied: toolz<0.12.0,>=0.11.1 in /usr/local/lib/python3.6/dist-packages (from datapane) (0.11.1)\n",
"Collecting furl<3.0.0,>=2.1.0\n",
" Downloading https://files.pythonhosted.org/packages/9f/c7/e9dc30914bf048bcd06284bb93d9650d318ecac8668b684fc41e975558ff/furl-2.1.0-py2.py3-none-any.whl\n",
"Collecting click-spinner<0.2.0,>=0.1.8\n",
" Downloading https://files.pythonhosted.org/packages/93/2a/04893832bfeddc2d40a7de2e8153b3085f12d63507d91a9cf0157dc3a1c2/click_spinner-0.1.10-py2.py3-none-any.whl\n",
"Requirement already satisfied: requests<3.0.0,>=2.20.0 in /usr/local/lib/python3.6/dist-packages (from datapane) (2.23.0)\n",
"Collecting bokeh==2.0.0\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/e0/a7/875aad223b211951a043bf7b0eddcecb8b2afd5131c08945ff07ac968c7f/bokeh-2.0.0.tar.gz (8.5MB)\n",
"\u001b[K |████████████████████████████████| 8.6MB 17.4MB/s \n",
"\u001b[?25hCollecting jsonschema<4.0.0,>=3.2.0\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/c5/8f/51e89ce52a085483359217bc72cdbf6e75ee595d5b1d4b5ade40c7e018b8/jsonschema-3.2.0-py2.py3-none-any.whl (56kB)\n",
"\u001b[K |████████████████████████████████| 61kB 7.7MB/s \n",
"\u001b[?25hRequirement already satisfied: altair<5.0.0,>=4.0.0 in /usr/local/lib/python3.6/dist-packages (from datapane) (4.1.0)\n",
"Requirement already satisfied: click<8.0.0,>=7.0.0 in /usr/local/lib/python3.6/dist-packages (from datapane) (7.1.2)\n",
"Requirement already satisfied: numpy<2.0.0,>=1.18.0 in /usr/local/lib/python3.6/dist-packages (from datapane) (1.19.5)\n",
"Collecting glom<21.0.0,>=20.11.0\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/5a/e2/977d77f6e0c34902f05a0754beb5950ea70c3c3c935d571fccac9540b57a/glom-20.11.0-py2.py3-none-any.whl (97kB)\n",
"\u001b[K |████████████████████████████████| 102kB 11.8MB/s \n",
"\u001b[?25hCollecting dacite<2.0.0,>=1.5.0\n",
" Downloading https://files.pythonhosted.org/packages/06/9d/11a073172d889e9e0d0ad270a1b468876c82d759af7864a8095dfc73f46d/dacite-1.6.0-py3-none-any.whl\n",
"Requirement already satisfied: jinja2<3.0.0,>=2.11.1 in /usr/local/lib/python3.6/dist-packages (from datapane) (2.11.2)\n",
"Collecting folium<0.12.0,>=0.11.0\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/a4/f0/44e69d50519880287cc41e7c8a6acc58daa9a9acf5f6afc52bcc70f69a6d/folium-0.11.0-py2.py3-none-any.whl (93kB)\n",
"\u001b[K |████████████████████████████████| 102kB 12.2MB/s \n",
"\u001b[?25hCollecting lxml<5.0.0,>=4.5.2\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/bd/78/56a7c88a57d0d14945472535d0df9fb4bbad7d34ede658ec7961635c790e/lxml-4.6.2-cp36-cp36m-manylinux1_x86_64.whl (5.5MB)\n",
"\u001b[K |████████████████████████████████| 5.5MB 43.3MB/s \n",
"\u001b[?25hCollecting dominate<3.0.0,>=2.6.0\n",
" Downloading https://files.pythonhosted.org/packages/ef/a8/4354f8122c39e35516a2708746d89db5e339c867abbd8e0179bccee4b7f9/dominate-2.6.0-py2.py3-none-any.whl\n",
"Requirement already satisfied: bleach<4.0.0,>=3.2.1 in /usr/local/lib/python3.6/dist-packages (from datapane) (3.2.1)\n",
"Requirement already satisfied: matplotlib<4.0.0,>=3.1.0 in /usr/local/lib/python3.6/dist-packages (from datapane) (3.2.2)\n",
"Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from plotly<5.0.0,>=4.8.1->datapane) (1.15.0)\n",
"Requirement already satisfied: retrying>=1.3.3 in /usr/local/lib/python3.6/dist-packages (from plotly<5.0.0,>=4.8.1->datapane) (1.3.3)\n",
"Requirement already satisfied: nbformat>=4.4 in /usr/local/lib/python3.6/dist-packages (from nbconvert<6.1.0,>=6.0.0->datapane) (5.0.8)\n",
"Requirement already satisfied: pandocfilters>=1.4.1 in /usr/local/lib/python3.6/dist-packages (from nbconvert<6.1.0,>=6.0.0->datapane) (1.4.3)\n",
"Requirement already satisfied: nbclient<0.6.0,>=0.5.0 in /usr/local/lib/python3.6/dist-packages (from nbconvert<6.1.0,>=6.0.0->datapane) (0.5.1)\n",
"Requirement already satisfied: jupyterlab-pygments in /usr/local/lib/python3.6/dist-packages (from nbconvert<6.1.0,>=6.0.0->datapane) (0.1.2)\n",
"Requirement already satisfied: testpath in /usr/local/lib/python3.6/dist-packages (from nbconvert<6.1.0,>=6.0.0->datapane) (0.4.4)\n",
"Requirement already satisfied: mistune<2,>=0.8.1 in /usr/local/lib/python3.6/dist-packages (from nbconvert<6.1.0,>=6.0.0->datapane) (0.8.4)\n",
"Requirement already satisfied: jupyter-core in /usr/local/lib/python3.6/dist-packages (from nbconvert<6.1.0,>=6.0.0->datapane) (4.7.0)\n",
"Requirement already satisfied: entrypoints>=0.2.2 in /usr/local/lib/python3.6/dist-packages (from nbconvert<6.1.0,>=6.0.0->datapane) (0.3)\n",
"Requirement already satisfied: pygments>=2.4.1 in /usr/local/lib/python3.6/dist-packages (from nbconvert<6.1.0,>=6.0.0->datapane) (2.6.1)\n",
"Requirement already satisfied: defusedxml in /usr/local/lib/python3.6/dist-packages (from nbconvert<6.1.0,>=6.0.0->datapane) (0.6.0)\n",
"Requirement already satisfied: traitlets>=4.2 in /usr/local/lib/python3.6/dist-packages (from nbconvert<6.1.0,>=6.0.0->datapane) (4.3.3)\n",
"Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas<2.0.0,>=1.0.1->datapane) (2018.9)\n",
"Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.6/dist-packages (from pandas<2.0.0,>=1.0.1->datapane) (2.8.1)\n",
"Requirement already satisfied: zipp>=0.4; python_version < \"3.8\" in /usr/local/lib/python3.6/dist-packages (from importlib_resources<4.0.0,>=3.0.0->datapane) (3.4.0)\n",
"Requirement already satisfied: decorator>=3.4.0 in /usr/local/lib/python3.6/dist-packages (from validators<0.19.0,>=0.18.0->datapane) (4.4.2)\n",
"Requirement already satisfied: pyparsing>=2.0.2 in /usr/local/lib/python3.6/dist-packages (from packaging<21.0,>=20.3->datapane) (2.4.7)\n",
"Collecting pytoml\n",
" Downloading https://files.pythonhosted.org/packages/a5/47/c7f8a0f210ad18576840922e0b504f0b7f5f73aea4a52ab14c5b58517edf/pytoml-0.1.21-py2.py3-none-any.whl\n",
"Collecting ruamel.yaml.clib>=0.1.2; platform_python_implementation == \"CPython\" and python_version < \"3.9\"\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/88/ff/ec25dc01ef04232a9e68ff18492e37dfa01f1f58172e702ad4f38536d41b/ruamel.yaml.clib-0.2.2-cp36-cp36m-manylinux1_x86_64.whl (549kB)\n",
"\u001b[K |████████████████████████████████| 552kB 41.7MB/s \n",
"\u001b[?25hCollecting orderedmultidict>=1.0.1\n",
" Downloading https://files.pythonhosted.org/packages/04/16/5e95c70bda8fe6ea715005c0db8e602400bdba50ae3c72cb380eba551289/orderedmultidict-1.0.1-py2.py3-none-any.whl\n",
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests<3.0.0,>=2.20.0->datapane) (2020.12.5)\n",
"Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests<3.0.0,>=2.20.0->datapane) (1.24.3)\n",
"Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests<3.0.0,>=2.20.0->datapane) (3.0.4)\n",
"Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests<3.0.0,>=2.20.0->datapane) (2.10)\n",
"Requirement already satisfied: pillow>=4.0 in /usr/local/lib/python3.6/dist-packages (from bokeh==2.0.0->datapane) (7.0.0)\n",
"Requirement already satisfied: tornado>=5 in /usr/local/lib/python3.6/dist-packages (from bokeh==2.0.0->datapane) (5.1.1)\n",
"Requirement already satisfied: typing_extensions>=3.7.4 in /usr/local/lib/python3.6/dist-packages (from bokeh==2.0.0->datapane) (3.7.4.3)\n",
"Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.6/dist-packages (from jsonschema<4.0.0,>=3.2.0->datapane) (20.3.0)\n",
"Requirement already satisfied: importlib-metadata; python_version < \"3.8\" in /usr/local/lib/python3.6/dist-packages (from jsonschema<4.0.0,>=3.2.0->datapane) (3.3.0)\n",
"Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from jsonschema<4.0.0,>=3.2.0->datapane) (51.1.1)\n",
"Requirement already satisfied: pyrsistent>=0.14.0 in /usr/local/lib/python3.6/dist-packages (from jsonschema<4.0.0,>=3.2.0->datapane) (0.17.3)\n",
"Collecting face>=20.1.0\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/ae/ab/2b18c4815f3db1e04bce325271fefda55d0893738ea84e3a655218944b03/face-20.1.1.tar.gz (46kB)\n",
"\u001b[K |████████████████████████████████| 51kB 7.1MB/s \n",
"\u001b[?25hRequirement already satisfied: dataclasses; python_version < \"3.7\" in /usr/local/lib/python3.6/dist-packages (from dacite<2.0.0,>=1.5.0->datapane) (0.8)\n",
"Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/lib/python3.6/dist-packages (from jinja2<3.0.0,>=2.11.1->datapane) (1.1.1)\n",
"Requirement already satisfied: branca>=0.3.0 in /usr/local/lib/python3.6/dist-packages (from folium<0.12.0,>=0.11.0->datapane) (0.4.2)\n",
"Requirement already satisfied: webencodings in /usr/local/lib/python3.6/dist-packages (from bleach<4.0.0,>=3.2.1->datapane) (0.5.1)\n",
"Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib<4.0.0,>=3.1.0->datapane) (0.10.0)\n",
"Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib<4.0.0,>=3.1.0->datapane) (1.3.1)\n",
"Requirement already satisfied: ipython-genutils in /usr/local/lib/python3.6/dist-packages (from nbformat>=4.4->nbconvert<6.1.0,>=6.0.0->datapane) (0.2.0)\n",
"Requirement already satisfied: async-generator in /usr/local/lib/python3.6/dist-packages (from nbclient<0.6.0,>=0.5.0->nbconvert<6.1.0,>=6.0.0->datapane) (1.10)\n",
"Collecting jupyter-client>=6.1.5\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/83/d6/30aed7ef13ff3f359e99626c1b0a32ebbc3bf9b9d5616ec46e9e245d5fa9/jupyter_client-6.1.11-py3-none-any.whl (108kB)\n",
"\u001b[K |████████████████████████████████| 112kB 45.5MB/s \n",
"\u001b[?25hRequirement already satisfied: nest-asyncio in /usr/local/lib/python3.6/dist-packages (from nbclient<0.6.0,>=0.5.0->nbconvert<6.1.0,>=6.0.0->datapane) (1.4.3)\n",
"Requirement already satisfied: pyzmq>=13 in /usr/local/lib/python3.6/dist-packages (from jupyter-client>=6.1.5->nbclient<0.6.0,>=0.5.0->nbconvert<6.1.0,>=6.0.0->datapane) (20.0.0)\n",
"Building wheels for collected packages: PyYAML, stringcase, bokeh, face\n",
" Building wheel for PyYAML (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for PyYAML: filename=PyYAML-5.3.1-cp36-cp36m-linux_x86_64.whl size=44621 sha256=7a620409302433d963b26916a75dc7fc87de077654375999e03df38a971c1f68\n",
" Stored in directory: /root/.cache/pip/wheels/a7/c1/ea/cf5bd31012e735dc1dfea3131a2d5eae7978b251083d6247bd\n",
" Building wheel for stringcase (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for stringcase: filename=stringcase-1.2.0-cp36-none-any.whl size=3577 sha256=13a1d2ec893543afbec1843e3fab55c5608659815aca9f2e5c2d34668ec4bb25\n",
" Stored in directory: /root/.cache/pip/wheels/a0/16/a0/16e2c81dbd47503b5a35583dfabde5a93b4cf98dbf0033dad5\n",
" Building wheel for bokeh (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for bokeh: filename=bokeh-2.0.0-cp36-none-any.whl size=8982364 sha256=7bc85894986be28cb8e842ac0b580fcaebddc644efbc8b33771f17423dd6cec9\n",
" Stored in directory: /root/.cache/pip/wheels/17/75/72/3bc53765dfe425579a658ef8e9f3b7142e9a56d3fe492c983a\n",
" Building wheel for face (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for face: filename=face-20.1.1-cp36-none-any.whl size=51079 sha256=73f0632fdf3fd6a50e57f3a97c34a65da8fb451be046f6d41d29ec6f16ae36a8\n",
" Stored in directory: /root/.cache/pip/wheels/4b/3c/80/b247eb8848bb1ee6cafc32cc03670ad3e9e8825086873cc830\n",
"Successfully built PyYAML stringcase bokeh face\n",
"\u001b[31mERROR: panel 0.9.7 has requirement bokeh>=2.1, but you'll have bokeh 2.0.0 which is incompatible.\u001b[0m\n",
"\u001b[31mERROR: datascience 0.10.6 has requirement folium==0.2.1, but you'll have folium 0.11.0 which is incompatible.\u001b[0m\n",
"Installing collected packages: plotly, boltons, nbconvert, PyYAML, stringcase, munch, importlib-resources, colorlog, validators, requests-toolbelt, pytoml, flit-core, ruamel.yaml.clib, ruamel.yaml, pyarrow, orderedmultidict, furl, click-spinner, bokeh, jsonschema, face, glom, dacite, folium, lxml, dominate, datapane, jupyter-client\n",
" Found existing installation: plotly 4.4.1\n",
" Uninstalling plotly-4.4.1:\n",
" Successfully uninstalled plotly-4.4.1\n",
" Found existing installation: nbconvert 5.6.1\n",
" Uninstalling nbconvert-5.6.1:\n",
" Successfully uninstalled nbconvert-5.6.1\n",
" Found existing installation: PyYAML 3.13\n",
" Uninstalling PyYAML-3.13:\n",
" Successfully uninstalled PyYAML-3.13\n",
" Found existing installation: importlib-resources 4.1.1\n",
" Uninstalling importlib-resources-4.1.1:\n",
" Successfully uninstalled importlib-resources-4.1.1\n",
" Found existing installation: pyarrow 0.14.1\n",
" Uninstalling pyarrow-0.14.1:\n",
" Successfully uninstalled pyarrow-0.14.1\n",
" Found existing installation: bokeh 2.1.1\n",
" Uninstalling bokeh-2.1.1:\n",
" Successfully uninstalled bokeh-2.1.1\n",
" Found existing installation: jsonschema 2.6.0\n",
" Uninstalling jsonschema-2.6.0:\n",
" Successfully uninstalled jsonschema-2.6.0\n",
" Found existing installation: folium 0.8.3\n",
" Uninstalling folium-0.8.3:\n",
" Successfully uninstalled folium-0.8.3\n",
" Found existing installation: lxml 4.2.6\n",
" Uninstalling lxml-4.2.6:\n",
" Successfully uninstalled lxml-4.2.6\n",
" Found existing installation: jupyter-client 5.3.5\n",
" Uninstalling jupyter-client-5.3.5:\n",
" Successfully uninstalled jupyter-client-5.3.5\n",
"Successfully installed PyYAML-5.3.1 bokeh-2.0.0 boltons-20.2.1 click-spinner-0.1.10 colorlog-4.6.2 dacite-1.6.0 datapane-0.9.0 dominate-2.6.0 face-20.1.1 flit-core-3.0.0 folium-0.11.0 furl-2.1.0 glom-20.11.0 importlib-resources-3.3.1 jsonschema-3.2.0 jupyter-client-6.1.11 lxml-4.6.2 munch-2.5.0 nbconvert-6.0.7 orderedmultidict-1.0.1 plotly-4.14.3 pyarrow-2.0.0 pytoml-0.1.21 requests-toolbelt-0.9.1 ruamel.yaml-0.16.12 ruamel.yaml.clib-0.2.2 stringcase-1.2.0 validators-0.18.2\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"application/vnd.colab-display-data+json": {
"pip_warning": {
"packages": [
"jupyter_client"
]
}
}
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:01:59.583279Z",
"start_time": "2020-08-14T21:01:53.991403Z"
},
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "CAosY4YdWWiK",
"outputId": "4a4ee4a0-36c7-46ce-c3ce-ad0d84b33938"
},
"source": [
"token = input('Insert your token after signing in Datapane ')\n",
"print('Your token is', token)\n",
"\n",
"!datapane login --server=https://datapane.com/ --token=$token"
],
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"text": [
"Insert your token after signing in Datapane 95498cd878b98d955d0b035d0670e12924e23f8c\n",
"Your token is 95498cd878b98d955d0b035d0670e12924e23f8c\n",
"\u001b[31mInvalid host 'datapane.com/'. Host strings must have at least one non-period character, can't contain any of '!@#$%^&'\"*()+=:;/', and can't have adjacent periods.\n",
"Please visit www.github.com/datapane/datapane to raise issue / discuss if error repeats\u001b[0m\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:02:48.010719Z",
"start_time": "2020-08-14T21:01:59.584541Z"
},
"scrolled": true,
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "JEWQ-pH4WWiL",
"outputId": "349ad780-3b61-4ce7-87a2-399427c4a759"
},
"source": [
"import pickle \n",
"import numpy as np \n",
"import pandas as pd \n",
"import datapane as dp \n",
"import base64\n",
"\n",
"!unzip /content/test_df.zip"
],
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"text": [
"Archive: /content/test_df.zip\n",
" inflating: test_df.csv \n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "IoZoyZpvXG1i",
"outputId": "b069a26c-83c8-4b23-ad37-ce8cb47f9d6d"
},
"source": [
"from google.colab import drive\n",
"drive.mount('/content/drive')"
],
"execution_count": 5,
"outputs": [
{
"output_type": "stream",
"text": [
"Mounted at /content/drive\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:02:51.334514Z",
"start_time": "2020-08-14T21:02:50.901067Z"
},
"id": "LrB9bG0UWWiN"
},
"source": [
"new_profile = pd.read_csv('test_df.csv')"
],
"execution_count": 4,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:02:52.865818Z",
"start_time": "2020-08-14T21:02:52.857923Z"
},
"scrolled": true,
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "l6KveF1hWWiN",
"outputId": "326c31a5-f9b5-4e40-f005-4ed6c8c3e14b"
},
"source": [
"#Find percentage of missing values\n",
"new_profile.isnull().sum()/len(new_profile)"
],
"execution_count": 5,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Unnamed: 0 0.000000\n",
"user_name 0.000000\n",
"name 0.135158\n",
"type_user 0.000000\n",
"html_url 0.000000\n",
"bio 0.530680\n",
"company 0.549751\n",
"email 0.552239\n",
"followers 0.000000\n",
"following 0.000000\n",
"hireable 0.702322\n",
"location 0.320896\n",
"created_at 0.000000\n",
"updated_at 0.000000\n",
"total_stars 0.082090\n",
"max_star 0.082090\n",
"forks 0.082090\n",
"languages 0.082090\n",
"descriptions 0.082090\n",
"dates 0.082090\n",
"readmes 0.082090\n",
"contribution 0.000000\n",
"top_repo_contributions 0.000000\n",
"dtype: float64"
]
},
"metadata": {
"tags": []
},
"execution_count": 5
}
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:02:54.784314Z",
"start_time": "2020-08-14T21:02:54.757593Z"
},
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "DIwlQanpWWiO",
"outputId": "c2fc4a26-7084-4b0b-c91d-79befe3be021"
},
"source": [
"new_profile.head(10)"
],
"execution_count": 6,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Unnamed: 0</th>\n",
" <th>user_name</th>\n",
" <th>name</th>\n",
" <th>type_user</th>\n",
" <th>html_url</th>\n",
" <th>bio</th>\n",
" <th>company</th>\n",
" <th>email</th>\n",
" <th>followers</th>\n",
" <th>following</th>\n",
" <th>hireable</th>\n",
" <th>location</th>\n",
" <th>created_at</th>\n",
" <th>updated_at</th>\n",
" <th>total_stars</th>\n",
" <th>max_star</th>\n",
" <th>forks</th>\n",
" <th>languages</th>\n",
" <th>descriptions</th>\n",
" <th>dates</th>\n",
" <th>readmes</th>\n",
" <th>contribution</th>\n",
" <th>top_repo_contributions</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0</td>\n",
" <td>josephmisiti</td>\n",
" <td>Joseph Misiti</td>\n",
" <td>Owner</td>\n",
" <td>https://github.com/josephmisiti</td>\n",
" <td>Mathematician &amp; Co-founder of Math &amp; Pencil</td>\n",
" <td>Math &amp; Pencil</td>\n",
" <td>NaN</td>\n",
" <td>2495</td>\n",
" <td>273</td>\n",
" <td>True</td>\n",
" <td>Brooklyn, NY</td>\n",
" <td>2010-04-17T21:09:13Z</td>\n",
" <td>2020-06-18T19:43:56Z</td>\n",
" <td>46355.0</td>\n",
" <td>45243.0</td>\n",
" <td>11857.0</td>\n",
" <td>['CSS', 'Ruby', 'Objective-C', 'Python', 'Go',...</td>\n",
" <td>['review of algorithms in python', 'Applied Li...</td>\n",
" <td>['2017-01-09T05:56:49Z', '2015-04-08T03:18:50Z...</td>\n",
" <td>['SSBuZWVkZWQgdG8gcmV2aWV3IGFsZ29yaXRobSB0aGVv...</td>\n",
" <td>2</td>\n",
" <td>781</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>wepe</td>\n",
" <td>wepon</td>\n",
" <td>Owner</td>\n",
" <td>https://github.com/wepe</td>\n",
" <td>NaN</td>\n",
" <td>AntFin</td>\n",
" <td>wepon@pku.edu.cn</td>\n",
" <td>4508</td>\n",
" <td>47</td>\n",
" <td>NaN</td>\n",
" <td>China Hangzhou</td>\n",
" <td>2014-10-10T14:28:18Z</td>\n",
" <td>2020-06-15T14:01:30Z</td>\n",
" <td>7120.0</td>\n",
" <td>3811.0</td>\n",
" <td>5091.0</td>\n",
" <td>['Python', 'Shell', 'C++', 'Java', 'HTML']</td>\n",
" <td>[None, '1st Place Season one &amp; 6th Place Seaso...</td>\n",
" <td>['2020-05-12T13:09:02Z', '2020-06-03T07:27:42Z...</td>\n",
" <td>[None, 'IyDoj5zpuJ8t6ZyA5rGC6aKE5rWL5LiO5YiG5L...</td>\n",
" <td>0</td>\n",
" <td>326</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2</td>\n",
" <td>ZuzooVn</td>\n",
" <td>Nam Vu</td>\n",
" <td>Owner</td>\n",
" <td>https://github.com/ZuzooVn</td>\n",
" <td>A Vietnamese Software Engineer who is really p...</td>\n",
" <td>NaN</td>\n",
" <td>zuzoovn@gmail.com</td>\n",
" <td>1192</td>\n",
" <td>91</td>\n",
" <td>True</td>\n",
" <td>Vietnam</td>\n",
" <td>2012-02-11T16:55:02Z</td>\n",
" <td>2020-07-05T09:24:19Z</td>\n",
" <td>23898.0</td>\n",
" <td>23893.0</td>\n",
" <td>5644.0</td>\n",
" <td>['JavaScript', 'Java', 'HTML']</td>\n",
" <td>[None, \"Hextelor is a game that tests your bra...</td>\n",
" <td>['2019-12-30T11:08:25Z', '2016-08-11T10:40:09Z...</td>\n",
" <td>['IVtdW1NpcGxvSW1hZ2VdCgpUaGlzIHByb2plY3Qgd2Fz...</td>\n",
" <td>55</td>\n",
" <td>224</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>3</td>\n",
" <td>rasbt</td>\n",
" <td>Sebastian Raschka</td>\n",
" <td>Owner</td>\n",
" <td>https://github.com/rasbt</td>\n",
" <td>Machine Learning researcher &amp; open source cont...</td>\n",
" <td>UW-Madison</td>\n",
" <td>mail@sebastianraschka.com</td>\n",
" <td>12725</td>\n",
" <td>33</td>\n",
" <td>NaN</td>\n",
" <td>Madison, WI</td>\n",
" <td>2013-10-05T16:06:10Z</td>\n",
" <td>2020-06-30T19:31:04Z</td>\n",
" <td>47849.0</td>\n",
" <td>12707.0</td>\n",
" <td>15633.0</td>\n",
" <td>['OpenEdge ABL', 'Python', 'Jupyter Notebook',...</td>\n",
" <td>['My Solutions for the Advent of Code 2016', '...</td>\n",
" <td>['2019-03-11T12:13:19Z', '2020-06-10T18:06:52Z...</td>\n",
" <td>['IyBhZHZlbnQtb2YtY29kZS0yMDE2CgoqTXkgU29sdXRp...</td>\n",
" <td>745</td>\n",
" <td>5910</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4</td>\n",
" <td>lazyprogrammer</td>\n",
" <td>LazyProgrammer.me</td>\n",
" <td>Owner</td>\n",
" <td>https://github.com/lazyprogrammer</td>\n",
" <td>https://deeplearningcourses.com</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2809</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2012-01-03T19:14:42Z</td>\n",
" <td>2020-06-27T21:40:43Z</td>\n",
" <td>5369.0</td>\n",
" <td>5193.0</td>\n",
" <td>4985.0</td>\n",
" <td>['Ruby', 'C#', 'Python', 'Matlab']</td>\n",
" <td>['Tiny example of how to preview an image in a...</td>\n",
" <td>['2014-07-25T18:25:34Z', '2020-01-02T16:52:33Z...</td>\n",
" <td>[None, 'VGhpcyBmaWxlcyBhcmUgZm9yIG15IGJvb2ssIE...</td>\n",
" <td>2</td>\n",
" <td>92</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>5</td>\n",
" <td>lawlite19</td>\n",
" <td>lawlite</td>\n",
" <td>Owner</td>\n",
" <td>https://github.com/lawlite19</td>\n",
" <td>It's really nice for us to meet each other in ...</td>\n",
" <td>Southeast University</td>\n",
" <td>lawlitewang@gmail.com</td>\n",
" <td>616</td>\n",
" <td>48</td>\n",
" <td>True</td>\n",
" <td>Nanjing, China</td>\n",
" <td>2015-09-19T02:51:34Z</td>\n",
" <td>2020-06-28T15:19:19Z</td>\n",
" <td>3878.0</td>\n",
" <td>3085.0</td>\n",
" <td>2109.0</td>\n",
" <td>['Python', 'Shell', 'C++', 'Java', 'HTML', 'Ma...</td>\n",
" <td>['算法练习', 'OJ平台算法java实现', '博客相关文件存储', '个人博客gita...</td>\n",
" <td>['2019-07-14T14:38:43Z', '2020-06-28T15:19:26Z...</td>\n",
" <td>['566X5rOV57uD5LmgCj09PT09PT09PT09PT09PQoocmVh...</td>\n",
" <td>79</td>\n",
" <td>1226</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>6</td>\n",
" <td>Jack-Cherish</td>\n",
" <td>Jack Cui</td>\n",
" <td>Owner</td>\n",
" <td>https://github.com/Jack-Cherish</td>\n",
" <td>:octocat:公众号:JackCui-AI</td>\n",
" <td>Northeastern University</td>\n",
" <td>c411184003@gmail.com</td>\n",
" <td>2902</td>\n",
" <td>28</td>\n",
" <td>NaN</td>\n",
" <td>China</td>\n",
" <td>2016-01-25T03:38:06Z</td>\n",
" <td>2020-05-12T13:55:41Z</td>\n",
" <td>15132.0</td>\n",
" <td>10865.0</td>\n",
" <td>7738.0</td>\n",
" <td>['HTML', 'C++', 'Python']</td>\n",
" <td>[':art:冒泡排序;直接插入排序;希尔排序;快速排序;堆排序;归并排序;基数排序', '...</td>\n",
" <td>['2020-07-04T07:37:15Z', '2020-03-29T13:16:49Z...</td>\n",
" <td>['IyBBbGdvcml0aG0KCuWOn+WIm+aWh+eroOavj+WRqOac...</td>\n",
" <td>131</td>\n",
" <td>830</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>7</td>\n",
" <td>ujjwalkarn</td>\n",
" <td>Ujjwal Karn</td>\n",
" <td>Owner</td>\n",
" <td>https://github.com/ujjwalkarn</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1952</td>\n",
" <td>224</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2013-11-15T13:53:58Z</td>\n",
" <td>2020-05-16T17:36:08Z</td>\n",
" <td>16146.0</td>\n",
" <td>10402.0</td>\n",
" <td>5471.0</td>\n",
" <td>['R', 'Python']</td>\n",
" <td>[None, 'common data analysis and machine learn...</td>\n",
" <td>['2014-07-22T11:55:26Z', '2020-07-05T19:10:22Z...</td>\n",
" <td>['VGhpcyByZXBvIGNvbnRhaW5zIG15IHNvbHV0aW9ucyB0...</td>\n",
" <td>6</td>\n",
" <td>713</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>8</td>\n",
" <td>trekhleb</td>\n",
" <td>Oleksii Trekhleb</td>\n",
" <td>Owner</td>\n",
" <td>https://github.com/trekhleb</td>\n",
" <td>Software Engineer at @uber</td>\n",
" <td>Uber</td>\n",
" <td>NaN</td>\n",
" <td>4934</td>\n",
" <td>7</td>\n",
" <td>True</td>\n",
" <td>Amsterdam</td>\n",
" <td>2012-12-09T08:38:00Z</td>\n",
" <td>2020-07-05T12:54:26Z</td>\n",
" <td>96749.0</td>\n",
" <td>74060.0</td>\n",
" <td>16723.0</td>\n",
" <td>['CSS', 'Python', 'Jupyter Notebook', 'MATLAB'...</td>\n",
" <td>['🌾 Seed project for Angular libraries that ar...</td>\n",
" <td>['2020-06-27T05:51:31Z', '2020-07-05T15:13:39Z...</td>\n",
" <td>['IyBgYW5ndWxhci1saWJyYXJ5LXNlZWRgIC0gdGhlIHN0...</td>\n",
" <td>1</td>\n",
" <td>2672</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>9</td>\n",
" <td>Vay-keen</td>\n",
" <td>Wei Ao</td>\n",
" <td>Owner</td>\n",
" <td>https://github.com/Vay-keen</td>\n",
" <td>Talk is cheap, show me the code!</td>\n",
" <td>Shenzhen University</td>\n",
" <td>aowei2016@email.szu.edu.cn</td>\n",
" <td>192</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>深圳市南山区</td>\n",
" <td>2014-11-17T02:10:56Z</td>\n",
" <td>2020-03-13T12:18:55Z</td>\n",
" <td>4149.0</td>\n",
" <td>4097.0</td>\n",
" <td>1228.0</td>\n",
" <td>['Python']</td>\n",
" <td>['《深度学习》因封面为一簇花丛又称“花书”,是由深度学习领域老、中、青三代结合而成的经典之...</td>\n",
" <td>['2020-05-12T02:16:56Z', '2020-07-06T00:45:37Z...</td>\n",
" <td>['44CK5rex5bqm5a2m5Lmg44CL5Zug5bCB6Z2i5Li65LiA...</td>\n",
" <td>0</td>\n",
" <td>35</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Unnamed: 0 user_name ... contribution top_repo_contributions\n",
"0 0 josephmisiti ... 2 781\n",
"1 1 wepe ... 0 326\n",
"2 2 ZuzooVn ... 55 224\n",
"3 3 rasbt ... 745 5910\n",
"4 4 lazyprogrammer ... 2 92\n",
"5 5 lawlite19 ... 79 1226\n",
"6 6 Jack-Cherish ... 131 830\n",
"7 7 ujjwalkarn ... 6 713\n",
"8 8 trekhleb ... 1 2672\n",
"9 9 Vay-keen ... 0 35\n",
"\n",
"[10 rows x 23 columns]"
]
},
"metadata": {
"tags": []
},
"execution_count": 6
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "sXNpSSqZWWiP"
},
"source": [
"# Visualization"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "MB4ENl5eWWiQ"
},
"source": [
"## Bar graphs"
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:02:59.424757Z",
"start_time": "2020-08-14T21:02:59.415028Z"
},
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "NAeyX8zxWWiR",
"outputId": "b50bd7bb-994d-49b2-ddd6-cea476503097"
},
"source": [
"import altair as alt \n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import datapane as dp\n",
"import plotly.express as px"
],
"execution_count": 7,
"outputs": [
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/distributed/config.py:20: YAMLLoadWarning:\n",
"\n",
"calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.\n",
"\n"
],
"name": "stderr"
}
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:03:00.067596Z",
"start_time": "2020-08-14T21:03:00.056690Z"
},
"id": "SKVD49VIWWiR"
},
"source": [
"top_followers = new_profile.sort_values(by='followers', axis=0, ascending=False)"
],
"execution_count": 8,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:03:00.764825Z",
"start_time": "2020-08-14T21:03:00.712234Z"
},
"colab": {
"base_uri": "https://localhost:8080/",
"height": 542
},
"id": "S9FlV5G-WWiS",
"outputId": "2e71b8e7-68c6-41f7-de96-f89a1826b6d8"
},
"source": [
"fig = px.bar(top_followers, \n",
" x='user_name', \n",
" y='followers',\n",
" hover_data=['followers'],\n",
" )\n",
"\n",
"fig.update_layout({'plot_bgcolor': 'rgba(36, 83, 97, 0.06)'}) #Change background color\n",
"\n",
"\n",
"fig.show()"
],
"execution_count": 9,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<html>\n",
"<head><meta charset=\"utf-8\" /></head>\n",
"<body>\n",
" <div> <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script> <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
" <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script> <div id=\"e2daa66f-cda3-44e3-bbd8-17c03129b82b\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"e2daa66f-cda3-44e3-bbd8-17c03129b82b\")) { Plotly.newPlot( \"e2daa66f-cda3-44e3-bbd8-17c03129b82b\", [{\"alignmentgroup\": \"True\", \"hovertemplate\": \"user_name=%{x}<br>followers=%{y}<extra></extra>\", \"legendgroup\": \"\", \"marker\": {\"color\": \"#636efa\"}, \"name\": \"\", \"offsetgroup\": \"\", \"orientation\": \"v\", \"showlegend\": false, \"textposition\": \"auto\", \"type\": \"bar\", \"x\": [\"llSourcell\", \"rasbt\", \"jwasham\", \"fengdu78\", \"chiphuyen\", \"justmarkham\", \"amitshekhariitbhu\", \"rhiever\", \"oldratlee\", \"trekhleb\", \"aymericdamien\", \"wepe\", \"roboticcam\", \"soulmachine\", \"susanli2016\", \"Jack-Cherish\", \"WillKoehrsen\", \"lazyprogrammer\", \"josephmisiti\", \"SamyPesse\", \"jindongwang\", \"bamos\", \"ujjwalkarn\", \"terrytangyuan\", \"benedekrozemberczki\", \"dipanjanS\", \"titu1994\", \"imhuay\", \"tapaswenipathak\", \"afshinea\", \"tirthajyoti\", \"woliveiras\", \"warmheartli\", \"cezannec\", \"polaris1119\", \"philips\", \"TarrySingh\", \"abhshkdz\", \"wkentaro\", \"layumi\", \"Yorko\", \"ZuzooVn\", \"parkr\", \"ljpzzz\", \"fperez\", \"RedstoneWill\", \"ty4z2008\", \"shuhuai007\", \"karthik\", \"aleju\", \"imathis\", \"liancheng\", \"guillaume-chevalier\", \"k88hudson\", \"firmai\", \"JustFollowUs\", \"willingc\", \"shervinea\", \"Gaohaoyang\", \"sckott\", \"kwhinnery\", \"hamelsmu\", \"mjpieters\", \"frnsys\", \"mcleonard\", \"e9t\", \"reiinakano\", \"JJ\", \"kailashahirwar\", \"treyhunner\", \"lawlite19\", \"yuanxiaosc\", \"Ir1d\", \"tdunning\", \"luispedro\", \"Spandan-Madan\", \"xxg1413\", \"stefanv\", \"arfon\", \"dimpurr\", \"zlotus\", \"idf\", \"dformoso\", \"demidovakatya\", \"vrv\", \"lettier\", \"jphall663\", \"jessitron\", \"stephenturner\", \"mrry\", \"Pomax\", \"zotroneneis\", \"haifengl\", \"ddbourgin\", \"rhnvrm\", \"daviddao\", \"tdhopper\", \"shaoanlu\", \"plusjade\", \"Sophia-11\", \"JWarmenhoven\", \"martinwicke\", \"katzien\", \"hangtwenty\", \"hslatman\", \"mappum\", \"lefnire\", \"alexeygrigorev\", \"humphd\", \"gvwilson\", \"KaiyangZhou\", \"scopatz\", \"swanson\", \"acabunoc\", \"timzhang642\", \"lukaszkaiser\", \"sayakpaul\", \"nfmcclure\", \"MaxHalford\", \"sguada\", \"pennyliang\", \"carefree0910\", \"zhunzhong07\", \"yulequan\", \"penberg\", \"ifesdjeen\", \"glemaitre\", \"alicoding\", \"wilsonmar\", \"andrewda\", \"pbharrin\", \"robertmartin8\", \"leviding\", \"jiffyclub\", \"Sea-n\", \"sjwhitworth\", \"13o-bbr-bbq\", \"arnaldog12\", \"Lax\", \"kevinlin311tw\", \"simensen\", \"dribnet\", \"albahnsen\", \"junlulocky\", \"cbuckey-uda\", \"yarikoptic\", \"robmarkcole\", \"bigsnarfdude\", \"RedditSota\", \"angeladai\", \"csuldw\", \"Naereen\", \"Tarrasch\", \"ColCarroll\", \"Metnew\", \"jaraco\", \"ethanwhite\", \"krishnakumarsekar\", \"meirwah\", \"ketanhwr\", \"omo\", \"studiomohawk\", \"clarle\", \"gavinsimpson\", \"ezefranca\", \"ethen8181\", \"knathanieltucker\", \"adarsh0806\", \"kinow\", \"NathanEpstein\", \"Tomotoes\", \"zhigang1992\", \"fmichonneau\", \"gumblex\", \"Horaddrim\", \"pjbull\", \"Borda\", \"Vay-keen\", \"loveunk\", \"xuhdev\", \"JohnMcLear\", \"navdeep-G\", \"fhemberger\", \"svaksha\", \"jeasonstudio\", \"jdblischak\", \"brainstorm\", \"ptone\", \"Mostafa-Samir\", \"DeqianBai\", \"ranahanocka\", \"schmich\", \"lorensr\", \"lazywei\", \"krother\", \"yurrriq\", \"yaph\", \"cailurus\", \"init27\", \"jakirkham\", \"kadirpekel\", \"Jasonnor\", \"zonca\", \"JerryKurata\", \"antmarakis\", \"kgashok\", \"cmhungsteve\", \"t-k-\", \"msabramo\", \"axsaucedo\", \"keveman\", \"vmirly\", \"bboe\", \"Borye\", \"csinva\", \"art-programmer\", \"brylie\", \"rozentill\", \"benmccann\", \"weakish\", \"naupaka\", \"keppel\", \"kuixu\", \"cdeil\", \"vfdev-5\", \"cgohlke\", \"xiaqunfeng\", \"bgreenwell\", \"sinanuozdemir\", \"abingham\", \"widdowquinn\", \"BillMills\", \"timClicks\", \"ZYSzys\", \"shaqian\", \"QuLogic\", \"brandly\", \"iamaziz\", \"wking\", \"Philmod\", \"btbytes\", \"myui\", \"lsvih\", \"dubzzz\", \"gisikw\", \"AmaanC\", \"RaphaelMeudec\", \"hsiaoyi0504\", \"secretrobotron\", \"philippbayer\", \"nachocab\", \"ffmpbgrnn\", \"matthewfeickert\", \"Keiku\", \"justpic\", \"kwichmann\", \"maxim5\", \"vict0rsch\", \"SeanPrashad\", \"ss8651twtw\", \"ebenolson\", \"SiyuanQi\", \"BirkhoffLee\", \"lexnederbragt\", \"yoavz\", \"joaopedronardari\", \"mikl\", \"DamienIrving\", \"fleeting\", \"yoavram\", \"codedread\", \"inejc\", \"masinoa\", \"lxj616\", \"haraldschilly\", \"Erotemic\", \"hex108\", \"umstek\", \"rmarquis\", \"wanzhenchn\", \"wdm0006\", \"Domon\", \"ahmadia\", \"alphadl\", \"QSCTech-Sange\", \"Bachmann1234\", \"joyoyoyoyoyo\", \"gyoisamurai\", \"sdball\", \"rdingwall\", \"AdityaSoni19031997\", \"davidrhodus\", \"umpox\", \"aaren\", \"stedy\", \"DiegoCatalano\", \"daeyun\", \"joaorafaelm\", \"gitbook-bot\", \"patricksnape\", \"atinesh-s\", \"volker48\", \"drio\", \"kieranjol\", \"juanpabloaj\", \"vyper\", \"koriroys\", \"dhingratul\", \"gdevenyi\", \"denisarnaud\", \"koobs\", \"geon\", \"beangoben\", \"gvn\", \"YichenGong\", \"magsol\", \"orlitany\", \"fish2000\", \"rwdaigle\", \"adam-erickson\", \"whatrocks\", \"DakshMiglani\", \"dmcc\", \"gaodayue\", \"rodgzilla\", \"eccstartup\", \"andrewschreiber\", \"unode\", \"jrbourbeau\", \"fmder\", \"wogong\", \"mtchavez\", \"mandar2812\", \"Xyclade\", \"silverstone1903\", \"thezillion\", \"jakemcc\", \"cmmalone\", \"tobyhodges\", \"thouis\", \"run\", \"ssusnic\", \"rafaelsakurai\", \"Nukesor\", \"twitwi\", \"harshavamsi\", \"phocks\", \"cmutel\", \"prajjwal1\", \"npbool\", \"danyaljj\", \"baldassarreFe\", \"ericdill\", \"ReadmeCritic\", \"jakubczakon\", \"EdwardSmith1884\", \"sdierauf\", \"arteymix\", \"daddou-ma\", \"anujgupta82\", \"dtchepak\", \"Sentimentron\", \"GitHub30\", \"ricardoamaro\", \"LarryBattle\", \"dlebauer\", \"andresgottlieb\", \"bertjiazheng\", \"jeff1evesque\", \"fhs\", \"Chandlercjy\", \"jayrav13\", \"rtlee9\", \"byrichardpowell\", \"vishwajeetv\", \"ilivans\", \"frozenkp\", \"synesthesiam\", \"jpallen\", \"ArionMiles\", \"MuminjonGuru\", \"yeonjuan\", \"andreww\", \"BioGeek\", \"pradeep1288\", \"cogmission\", \"iiSeymour\", \"RickEyre\", \"tommyjiang\", \"harshnisar\", \"acastrounis\", \"lukearmstrong\", \"ghthor\", \"lxieyang\", \"x1957\", \"rachpt\", \"langner\", \"espoirMur\", \"cbarrick\", \"jcn\", \"optas\", \"havanagrawal\", \"zlu\", \"AdilZouitine\", \"polymeris\", \"re4lfl0w\", \"Amir-Arsalan\", \"alexsavio\", \"jgraving\", \"pbanaszkiewicz\", \"arimbr\", \"synapticarbors\", \"gideonthomas\", \"ProGamerGov\", \"Microsheep\", \"kno10\", \"Alex1996a\", \"nashjain\", \"KiranPanesar\", \"blokhin\", \"gaborvecsei\", \"michaelaye\", \"dmoisset\", \"vivienzou1\", \"rieder91\", \"herschel666\", \"advancedxy\", \"WuZhuoran\", \"natowi\", \"flipace\", \"ecederstrand\", \"piyushchauhan\", \"ammarasmro\", \"shashankgroovy\", \"iamBedant\", \"adamyala\", \"orionr\", \"floydpink\", \"daveredrum\", \"fanglinchen\", \"egeriis\", \"Cugtyt\", \"wojdyr\", \"hmchuong\", \"jGaboardi\", \"filipefilardi\", \"okjake\", \"ajmeese7\", \"robtaussig\", \"skvrahul\", \"lacava\", \"imatiach-msft\", \"stonebig\", \"testrain\", \"BernhardKonrad\", \"Diastro\", \"adibis\", \"meawoppl\", \"HaveF\", \"graphaelli\", \"pilif\", \"enjoyhot\", \"albertstill\", \"toaarnio\", \"pkuphy\", \"zh794390558\", \"easezyc\", \"code0100fun\", \"JanLauGe\", \"ocdtrekkie\", \"ZhengRui\", \"mysteriouspants\", \"sebix\", \"apeeyush\", \"dmnelson\", \"d4n1elchen\", \"raghavbali\", \"JamesLuoau\", \"shikharvaish28\", \"benedictflorance\", \"sudeepraja\", \"iglpdc\", \"djoos\", \"habi\", \"rogerzanoni\", \"BetaPundit\", \"chi-hung\", \"alg\", \"pkayfire\", \"SegFaultAX\", \"juliangarcia\", \"RockySJ\", \"TehMillhouse\", \"TaurusOlson\", \"rachtsingh\", \"sourcesoft\", \"wendingp\", \"jacarrico\", \"wassimseif\", \"curiousleo\", \"ShengKungYi\", \"bryngo\", \"AnshulBasia\", \"idear1203\", \"dnguneratne\", \"sun254\", \"abought\", \"srayuws\", \"cjauvin\", \"NeerajSarwan\", \"schneiderfelipe\", \"cloudyan\", \"allardbrain\", \"jankrepl\", \"Soypete\", \"kmscode\", \"tvogels\", \"SylvainDe\", \"sivanWu0222\", \"niltonslf\", \"mogwai\", \"JustroX\", \"GageAmes\", \"jbencook\", \"ajkl\", \"snurkabill\", \"RF-Nelson\", \"chkoar\", \"zldeng\", \"autodataming\", \"wrichert\", \"testbounty\", \"hanhdt\", \"nipunsadvilkar\", \"tiendq\", \"sstarr\", \"chhh\", \"hamiltont\", \"jaycode\", \"ses4j\", \"iory\", \"gliptak\", \"oneTaken\", \"havk64\", \"SnailSword\", \"javierlorenzod\", \"opie4624\", \"sshekh\", \"acusti\", \"avinashsai\", \"abarto\", \"vallentin\", \"nahumj\", \"jackmaney\", \"ss18\", \"dmmulroy\", \"ReekenX\", \"PBarmby\", \"tncardoso\", \"frankhjwx\", \"kid1412z\", \"tommyblue\", \"selimnairb\", \"NeroCube\", \"pmn4\", \"CSerxy\", \"wzell\", \"tranek\", \"ismaeIfm\", \"0asa\", \"amitkgupta\", \"DanielMorales9\", \"ambientlight\", \"jsmith\", \"erjanmx\", \"pipitone\", \"IsakFalk\", \"azillion\", \"emptyr1\", \"jaymody\", \"An3bi\", \"iamc\", \"SaumoPal97\", \"shahules786\", \"ehrenfeu\", \"songuke\", \"xiuluo\", \"srhrshr\", \"nolith\", \"tychenjiajun\", \"justanhduc\", \"LukasKnuth\", \"pan-long\", \"luvegood\", \"hwmrocker\", \"yuanzhaoYZ\", \"NJannasch\", \"caub\", \"sjml\", \"mindw\", \"praveenmylavarapu\", \"jselmani\", \"buddhikajay\", \"chrish42\", \"p-s-vishnu\", \"steven7851\", \"RingoTC\", \"timmartin19\", \"maikelwever\", \"wltrimbl\", \"mjschranz\", \"calberti\", \"everping\", \"gaulinmp\", \"briansorahan\", \"jappre\", \"vahtras\", \"asford\", \"rayeaster\", \"kastman\", \"digital-thinking\", \"EtienneBruines\", \"eecn\", \"hjlarry\", \"Devinsuit\", \"ccyanxyz\", \"sergioburdisso\", \"wenyangfu\", \"kjappelbaum\", \"sebg\", \"matheusgmaia\", \"Amir22010\", \"sagunji\", \"XiaoshuiHuang\", \"cshan\", \"apatsekin\", \"arc12\", \"jogjayr\", \"liuluheng\", \"planetceres\", \"kbagchiGWC\", \"CrazyBunQnQ\", \"aoping\", \"olivertomic\", \"cmacdonell\", \"finnigantime\", \"itsliupeng\", \"LoveMeWithoutAll\", \"alexobednikov\", \"beckgael\", \"postBG\", \"jimthompson5802\", \"jovilius\", \"melzareix\", \"dangsonbk\", \"strange-jiong\", \"CorcovadoMing\", \"flyingpot\", \"taylan\", \"TocarIP\", \"athiwatc\", \"teopost\", \"Vijayabhaskar96\", \"jmchen-g\", \"ecolell\", \"allthroughthenight\", \"KevinCooper\", \"hbaniecki\", \"windpls\", \"lstolcman\", \"cxxgtxy\", \"gpailler\", \"mkuhn\", \"itsmeolivia\", \"AnkurDedania\", \"chneau\", \"joybanerjee08\", \"ebuildy\", \"xlfe\", \"jocelynlih\", \"jalateras\", \"jsgv\", \"idelgado\", \"SwarShah\", \"amyrhoda\", \"ande765a\", \"mangei\", \"adam2392\", \"cjpurackal\", \"daz\", \"doppenhe\", \"wayneadams\", \"niklaskeerl\", \"jboy\", \"fatihbaltaci\", \"lzcabrera\", \"stromnov\", \"Zzlongjuanfeng\", \"ackerleytng\", \"andsor\", \"appleJax\", \"RasPat1\", \"bobiechen-twilio\", \"nathanhillyer\", \"waterson\", \"TitouanT\", \"lukelafountaine\", \"samedhaa\", \"cPolaris\", \"individual8\", \"cako\", \"elwinarens\", \"kevinkyyro\", \"zahanm\", \"sudipbhandari126\", \"el10savio\", \"ebigelow\", \"hyqskevin\", \"mewben\", \"ploth\", \"kennethjmyers\", \"ooxi\", \"tomhoover\", \"rsbohn\", \"jwsy\", \"dylandrop\", \"FlorisHoogenboom\", \"NotAnyMike\", \"luntain\", \"stieglma\", \"jared-weed\", \"xcodeburpx\", \"proinsias\", \"SubrataSarkar32\", \"yakud\", \"LiEmail\", \"AlexZhou1995\", \"gukoff\", \"meghpatel\", \"jcsims\", \"dombrno\", \"salehjg\", \"SentinelWarren\", \"avn3r\", \"pw\", \"alimon808\", \"sedge\", \"bendoerr\", \"ACharbonneau\", \"vinodkkurmi\", \"Minki-Kim95\", \"PatrickZH\", \"MadhumitaSushil\", \"moonboots\", \"datamove\", \"peterfabakker\", \"taoyudong\", \"bobrosoft\", \"rajeshvaya\", \"PeterShershov\", \"TuanNguyen27\", \"kota7\", \"divik544\", \"davidlowjw\", \"ericbuehl\", \"n-kats\", \"ilam\", \"ayakubovich\", \"YJH1987\", \"njern\", \"danielsan\", \"jpvg10\", \"mapx\", \"basickarl\", \"jkuchta\", \"guillermo-navas-palencia\", \"mgschwan\", \"DanilBaibak\", \"vad4msiu\", \"Petemir\", \"anishthite\", \"jackeylu\", \"itailang\", \"pfsq\", \"LizhangX\", \"12wang3\", \"kyranb\", \"LiberiFatali\", \"Vincent-Vercruyssen\", \"vargas\", \"nbsantos\", \"Finance-781\", \"moutai\", \"sohamM97\", \"buddhiv\", \"drlabratory\", \"zdgriffith\", \"derrg\", \"fchouteau\", \"moshejs\", \"SoumyadeepJana\", \"PrinzOwO\", \"tomahawk28\", \"RequireSun\", \"qualityjacks\", \"victorhcm\", \"girishkuniyal\", \"PGijsbers\", \"nvh95\", \"mgoodfellow\", \"ayushs136\", \"dbarbier\", \"adriancampos\", \"douglatornell\", \"adamwkraft\", \"awesome-bot\", \"adyates\", \"jeffin07\", \"voskresenskiy\", \"soumanpaul\", \"slcott\", \"mexeniz\", \"CorreyL\", \"jhashanti\", \"DanBeard\", \"elfelround\", \"cjratcliff\", \"tuanphuc\", \"zairah10\", \"sailakshmi17\", \"alisezer\", \"eeeeeric\", \"dogHere\", \"koomar\", \"KodeWorker\", \"SusieXu\", \"hugosoftdev\", \"liliuleo\", \"thecjharries\", \"kshs010239\", \"jgyllinsky\", \"mikej888\", \"nitin-tm\", \"shrutibhutaiya\", \"Hefeweizen\", \"baogianghoangvu\", \"wenruimeng\", \"pleabargain\", \"cratonica\", \"malfple\", \"chess99\", \"mkotov13\", \"AkshayVarik\", \"Mintisma\", \"mckays630\", \"crouchred\", \"AJDBenner\", \"Mchristos\", \"mingzhang96\", \"tgray\", \"aosama\", \"mzakariaCERN\", \"vattay\", \"nmb10\", \"e173101\", \"rajasekharponakala\", \"DH-Diego\", \"ktolstikhin\", \"cavestruz\", \"fangweili\", \"anzellai\", \"whughw\", \"Karl-EdwardFPJeanMehu\", \"Suraj520\", \"ahnt\", \"firebreath1001\", \"trpapp\", \"SarthakYadav\", \"JsonAC\", \"wsbmxa198700\", \"olveirap\", \"HapeMask\", \"lacanlale\", \"timfrostmann\", \"frannievas\", \"kreuvf\", \"Div44\", \"kilsenp\", \"jacksonlo\", \"mraje16\", \"Ouss4\", \"dsych\", \"bob7783\", \"yhx5768\", \"kcrandall\", \"Amjad-H-Ali\", \"mgoldey\", \"itzamna314\", \"UjjwalAryal\", \"saiabishek1\", \"shenyyi\", \"DrDavidS\", \"anuj1207\", \"aaroncm\", \"eshizhan\", \"danielbogomazov\", \"RandomArray\", \"wenphan\", \"kacper1095\", \"IgorKovr\", \"jongoodnow\", \"databaaz\", \"rahmanhafeezul\", \"thanhnguyentang\", \"bon\", \"mollygibson\", \"beroe\", \"KeniMorri\", \"skervim\", \"borodenkov\", \"Budddy\", \"peter-toth\", \"samyag1\", \"McKenzyPG\", \"jlar0che\", \"irrationalRock\", \"phillies\", \"narisada014\", \"Jurilz\", \"JasonGitHub\", \"alishutc\", \"optixlab\", \"Adrien-Jecker\", \"LecJackS\", \"janismdhanbad\", \"ankitkul\", \"louispotok\", \"K-LV\", \"festline\", \"ronnierios\", \"agusnavce\", \"flytomylife\", \"Alveona\", \"varshapaidi\", \"2y2simple\", \"mirjalil\", \"npanti\", \"mybaseball52\", \"digitalduke\", \"Airatiki\", \"igorrocha\", \"junxnone\", \"wtollett-usgs\", \"alexlokotochek\", \"Zhi-lin\", \"jldohmann\", \"HemuManju\", \"Bachstelze\", \"daniel-kashin\", \"alcidesv\", \"JustinJudd\", \"MTietze\", \"busterroni\", \"TwFlem\", \"poyuwu\", \"m-maksyutin\", \"jaywinhuang\", \"martijnvanbeers\", \"BokaiLIAN\", \"codingcai\", \"jamesmyatt\", \"adpon\", \"elkfrawy-df\", \"swlsw\", \"muhammadyaseen\", \"esztiorm\", \"Owen-Mak\", \"sagardubey3\", \"joaoavf\", \"nschor\", \"oussou-dev\", \"IamThilina\", \"brigham\", \"Pooch11\", \"SeanPedersen\", \"rohduggal\", \"EtienneT\", \"maks-a\", \"Mrzhangxiaohua\", \"gcoter\", \"omytryniuk\", \"MarcelRobeer\", \"MUSSONT\", \"daanmichiels\", \"nitinagarwal\", \"lupusomniator\", \"giuliatondin\", \"lzamparo\", \"nektor211\", \"juholehtonen\", \"TusharShandilya\", \"Psimage\", \"LiLiu93\", \"LukeArn\", \"sagarcadet\", \"willalways\", \"mikelogsdon\", \"hanpum\", \"hetii\", \"gauravcharnalia\", \"testaccount553\", \"czenzel\", \"zylix666\", \"metrafonic\", \"fndjjx\", \"mosew\", \"harenbergsd\", \"robot-c0der\", \"eddyzhd\", \"Asterisk14\", \"Fatehsandhu\", \"grayskripko\", \"Ja1r0\", \"josephmmisiti\", \"curiousrohan\", \"binilj04\", \"chrisadami\", \"AselaDarshan\", \"stnk20\", \"Nebula83\", \"jaksmid\", \"credentiality\", \"smbeli\", \"maxnk\", \"kzhk75\", \"cgcgcg\", \"ini\", \"yangyyt\", \"jeffcore\", \"engineeress\", \"PaulDebus\", \"clappis\", \"Tirzono\", \"aniag\", \"jiangf13\", \"ulido\", \"Gabriel-Azevedo-Ferreira\", \"monomagentaeggroll\", \"cswef\", \"mmBabol\", \"miksago\", \"LeeMaria007\", \"yonatanf\", \"selay01\", \"Frenchhorn\", \"tomassvensson\", \"TommyBark\", \"sseidl88\", \"AlexanderKunkel\", \"SumanthReddyKaliki\", \"vicramr\", \"triangeljs\", \"dear983604\", \"wang1211\", \"YongshanKe\", \"ivigamberdiev\", \"cameroncan\", \"alexnich\", \"yjh\", \"Kacawi\", \"AndrewLiesinger\", \"libertatis\", \"vilmacio22\", \"ilbuono\", \"jackkuipers\", \"agngrant\", \"ao-song\", \"twigz20\", \"tomraulet\", \"Lincete\", \"ThatAndresV\", \"ipcenas\", \"drskd\", \"egorpolusmak\", \"matt-jay\", \"Dr-Zhou\", \"aggronerd\", \"SumitBando\", \"ThePhantomCoder\", \"GordianStapf\", \"ari-schaffel\", \"CookieDom\", \"bigwave\", \"nyoung85\", \"rafalgrm\", \"hungphandinh92it\", \"YINCHENLI\", \"hlkcrcck\", \"varan42\", \"marsben\", \"GLevV\", \"sudoes\", \"adityahiran\", \"JayJayBinks\", \"mkeds\", \"thedadams\", \"albertmolinermrf\", \"YoungMStudio\", \"zyc1gq\", \"K1t1k\", \"mzk912778163\", \"tuantp7\", \"chrissoulierserv\", \"mrtnbrst\", \"ss52\", \"bvonboyen\", \"kersov\", \"Charismatron\", \"lee709\", \"guedalia\", \"Bruce-Feldman\", \"grp-bork\", \"IMWP\", \"gsenseless\", \"seIncorp\", \"qhfgva\", \"itkinai\", \"Th30\", \"zzincubus\", \"163-0533\", \"thesimanjan\", \"ecbc1\", \"tairiUdacity\", \"Liam-Yang\", \"coderfive\", \"oleksii-trekhleb-epam\", \"peter-parque\", \"jliddie\", \"kylegrover\", \"eldaniz\", \"elesueur\", \"ExterminateWho\", \"wqiancheng\", \"Asmolovskij\", \"creinders\", \"Pirikara\", \"toddrme2178\", \"imaness\", \"qianguyizhe\", \"xkcao\", \"rumi-naik\", \"pdkovacs\", \"carlward\", \"ser-serege\", \"ritabentodosreis\", \"p1gd0g\", \"lisahdd007\", \"ntache\", \"ivesn\", \"hfanahita\", \"scraggard\", \"mikhailsergeevi4\", \"Digitalmobz\", \"justramgerry\", \"jvanlangen\", \"tushargt\", \"snowde\", \"synapton\", \"sirius999999\", \"Tom-Ren\", \"willgroves\", \"twotabbies\", \"cpdj\", \"serickso\", \"qiagu\", \"APorterOReilly\", \"mkilavuz\", \"KirillPanin\", \"bkhaleghi\", \"omrimendels\", \"aathauck\", \"amar00k\", \"wla80\", \"aquinasCode\", \"gceboh\", \"KaiNieRus\", \"sys0613\", \"JJLWHarrison\", \"njojic\", \"4may\", \"bluewoodtree\", \"sdsk\", \"ptaiga\", \"liuliu5151\", \"andrewd76\", \"jasonbhart\", \"maximkeremet\", \"svntjng\", \"dnn37\", \"acupofdata\", \"MdScntst\", \"mahajani123\", \"deeper-learning\", \"bkm009\", \"afromanF\", \"alexey-grigorev-sm\"], \"xaxis\": \"x\", \"y\": [36270, 12725, 9193, 8184, 5884, 5757, 5380, 5035, 5002, 4934, 4589, 4508, 3175, 3046, 2970, 2902, 2859, 2809, 2495, 2461, 2355, 2010, 1952, 1938, 1742, 1724, 1657, 1631, 1621, 1558, 1550, 1521, 1470, 1348, 1311, 1287, 1262, 1245, 1235, 1227, 1222, 1192, 1169, 1127, 1104, 1083, 989, 985, 928, 917, 877, 870, 863, 858, 840, 832, 813, 786, 772, 737, 730, 707, 697, 693, 693, 684, 683, 663, 658, 624, 616, 612, 607, 606, 603, 603, 602, 567, 563, 556, 544, 541, 537, 533, 532, 531, 529, 529, 525, 522, 521, 493, 491, 477, 472, 472, 463, 460, 459, 458, 456, 451, 449, 446, 439, 433, 430, 424, 421, 418, 417, 410, 406, 400, 389, 388, 383, 381, 364, 363, 362, 356, 354, 353, 351, 346, 346, 345, 339, 338, 318, 315, 308, 298, 292, 291, 287, 287, 286, 281, 278, 275, 273, 271, 262, 260, 257, 254, 254, 252, 247, 244, 244, 243, 241, 238, 235, 235, 234, 225, 221, 220, 218, 216, 215, 210, 208, 204, 204, 201, 201, 200, 197, 195, 194, 193, 192, 192, 191, 190, 189, 188, 186, 185, 185, 182, 182, 180, 175, 174, 174, 174, 172, 172, 170, 167, 164, 162, 159, 159, 157, 154, 152, 149, 148, 147, 147, 144, 143, 143, 142, 140, 138, 138, 137, 135, 134, 130, 125, 124, 123, 121, 121, 121, 120, 120, 119, 118, 118, 118, 117, 116, 115, 115, 115, 115, 114, 112, 111, 110, 108, 107, 106, 105, 105, 104, 103, 102, 100, 100, 99, 99, 99, 98, 97, 97, 97, 97, 96, 95, 94, 94, 94, 94, 94, 94, 92, 92, 92, 92, 92, 92, 91, 90, 90, 90, 90, 89, 88, 88, 87, 84, 84, 83, 83, 82, 82, 82, 81, 81, 80, 80, 80, 80, 79, 78, 76, 75, 75, 74, 74, 73, 73, 73, 73, 73, 72, 72, 72, 72, 71, 71, 71, 71, 71, 70, 70, 69, 69, 68, 68, 67, 67, 66, 66, 66, 66, 65, 64, 64, 64, 63, 63, 63, 63, 62, 62, 62, 62, 62, 62, 62, 62, 62, 62, 62, 62, 62, 61, 61, 61, 61, 61, 60, 59, 59, 59, 59, 58, 58, 58, 58, 58, 58, 58, 58, 57, 56, 55, 55, 55, 55, 55, 54, 54, 54, 54, 54, 54, 54, 53, 53, 53, 53, 53, 53, 53, 53, 52, 52, 52, 51, 51, 51, 51, 50, 50, 50, 50, 50, 50, 50, 49, 49, 49, 49, 49, 48, 48, 48, 48, 48, 47, 47, 47, 47, 47, 47, 47, 47, 46, 46, 46, 45, 45, 45, 45, 45, 45, 45, 44, 44, 44, 44, 44, 44, 43, 43, 43, 43, 43, 43, 43, 42, 42, 42, 41, 41, 41, 41, 41, 41, 41, 40, 40, 40, 40, 40, 39, 39, 39, 39, 39, 39, 39, 38, 38, 38, 38, 37, 37, 37, 37, 37, 37, 37, 37, 36, 36, 36, 36, 36, 36, 36, 36, 36, 35, 35, 35, 35, 35, 35, 34, 34, 34, 34, 34, 34, 34, 34, 34, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 32, 32, 32, 32, 32, 32, 32, 31, 31, 31, 31, 31, 30, 30, 30, 30, 30, 30, 30, 30, 30, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 28, 28, 28, 28, 28, 28, 27, 27, 27, 27, 27, 27, 27, 27, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 25, 25, 25, 25, 25, 25, 25, 25, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 23, 23, 23, 23, 23, 23, 23, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 18, 18, 18, 18, 18, 18, 18, 18, 18, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 15, 15, 15, 15, 15, 15, 15, 15, 15, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 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, 2, 2, 2, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], \"yaxis\": \"y\"}], {\"barmode\": \"relative\", \"legend\": {\"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"plot_bgcolor\": \"rgba(36, 83, 97, 0.06)\", \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"autotypenumbers\": \"strict\", \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"user_name\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"followers\"}}}, {\"responsive\": true} ).then(function(){\n",
" \n",
"var gd = document.getElementById('e2daa66f-cda3-44e3-bbd8-17c03129b82b');\n",
"var x = new MutationObserver(function (mutations, observer) {{\n",
" var display = window.getComputedStyle(gd).display;\n",
" if (!display || display === 'none') {{\n",
" console.log([gd, 'removed!']);\n",
" Plotly.purge(gd);\n",
" observer.disconnect();\n",
" }}\n",
"}});\n",
"\n",
"// Listen for the removal of the full notebook cells\n",
"var notebookContainer = gd.closest('#notebook-container');\n",
"if (notebookContainer) {{\n",
" x.observe(notebookContainer, {childList: true});\n",
"}}\n",
"\n",
"// Listen for the clearing of the current output cell\n",
"var outputEl = gd.closest('.output');\n",
"if (outputEl) {{\n",
" x.observe(outputEl, {childList: true});\n",
"}}\n",
"\n",
" }) }; </script> </div>\n",
"</body>\n",
"</html>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:03:03.029840Z",
"start_time": "2020-08-14T21:03:03.021663Z"
},
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "U1gPQewaWWiS",
"outputId": "520301fa-318b-49c5-8e1d-92bb319b185a"
},
"source": [
"top_n = int(len(top_followers) * 0.01)\n",
"top_n"
],
"execution_count": 10,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"12"
]
},
"metadata": {
"tags": []
},
"execution_count": 10
}
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:03:03.627437Z",
"start_time": "2020-08-14T21:03:03.617702Z"
},
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "UZbJaayPWWiT",
"outputId": "7533c4c6-2623-42b1-d547-6bec7a4aab5a"
},
"source": [
"sum(top_followers.iloc[0: top_n,:].loc[:, 'followers'])/sum(top_followers.followers)"
],
"execution_count": 11,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"0.4152247664237525"
]
},
"metadata": {
"tags": []
},
"execution_count": 11
}
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:03:04.771367Z",
"start_time": "2020-08-14T21:03:04.494619Z"
},
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "0zYLrBeeWWiU",
"outputId": "104d1730-5f3d-4166-9911-8a7315bab194"
},
"source": [
"features = ['followers',\n",
" 'following',\n",
" 'total_stars',\n",
" 'max_star',\n",
" 'forks',\n",
" 'contribution']\n",
"figs = []\n",
"for col in features:\n",
" top_col = new_profile.sort_values(by=col, axis=0, ascending=False)\n",
" \n",
" log_y = False\n",
" \n",
" # #change scale of y-axis of every feature to log except contribution\n",
" if col != 'contribution':\n",
" log_y = True\n",
" \n",
" fig = px.bar(top_col,\n",
" x='user_name', \n",
" y=col,\n",
" hover_data=[col],\n",
" log_y=log_y, \n",
" )\n",
" \n",
" fig.update_layout({'plot_bgcolor': 'rgba(36, 83, 97, 0.06)'})\n",
" \n",
" fig.show()\n",
" fig = dp.Plot(fig)\n",
" figs.append(fig)\n",
"\n"
],
"execution_count": 12,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<html>\n",
"<head><meta charset=\"utf-8\" /></head>\n",
"<body>\n",
" <div> <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script> <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
" <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script> <div id=\"b6129c77-54e4-4baa-ad70-7e5a0d48a066\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"b6129c77-54e4-4baa-ad70-7e5a0d48a066\")) { Plotly.newPlot( \"b6129c77-54e4-4baa-ad70-7e5a0d48a066\", [{\"alignmentgroup\": \"True\", \"hovertemplate\": \"user_name=%{x}<br>followers=%{y}<extra></extra>\", \"legendgroup\": \"\", \"marker\": {\"color\": \"#636efa\"}, \"name\": \"\", \"offsetgroup\": \"\", \"orientation\": \"v\", \"showlegend\": false, \"textposition\": \"auto\", \"type\": \"bar\", \"x\": [\"llSourcell\", \"rasbt\", \"jwasham\", \"fengdu78\", \"chiphuyen\", \"justmarkham\", \"amitshekhariitbhu\", \"rhiever\", \"oldratlee\", \"trekhleb\", \"aymericdamien\", \"wepe\", \"roboticcam\", \"soulmachine\", \"susanli2016\", \"Jack-Cherish\", \"WillKoehrsen\", \"lazyprogrammer\", \"josephmisiti\", \"SamyPesse\", \"jindongwang\", \"bamos\", \"ujjwalkarn\", \"terrytangyuan\", \"benedekrozemberczki\", \"dipanjanS\", \"titu1994\", \"imhuay\", \"tapaswenipathak\", \"afshinea\", \"tirthajyoti\", \"woliveiras\", \"warmheartli\", \"cezannec\", \"polaris1119\", \"philips\", \"TarrySingh\", \"abhshkdz\", \"wkentaro\", \"layumi\", \"Yorko\", \"ZuzooVn\", \"parkr\", \"ljpzzz\", \"fperez\", \"RedstoneWill\", \"ty4z2008\", \"shuhuai007\", \"karthik\", \"aleju\", \"imathis\", \"liancheng\", \"guillaume-chevalier\", \"k88hudson\", \"firmai\", \"JustFollowUs\", \"willingc\", \"shervinea\", \"Gaohaoyang\", \"sckott\", \"kwhinnery\", \"hamelsmu\", \"mjpieters\", \"frnsys\", \"mcleonard\", \"e9t\", \"reiinakano\", \"JJ\", \"kailashahirwar\", \"treyhunner\", \"lawlite19\", \"yuanxiaosc\", \"Ir1d\", \"tdunning\", \"luispedro\", \"Spandan-Madan\", \"xxg1413\", \"stefanv\", \"arfon\", \"dimpurr\", \"zlotus\", \"idf\", \"dformoso\", \"demidovakatya\", \"vrv\", \"lettier\", \"jphall663\", \"jessitron\", \"stephenturner\", \"mrry\", \"Pomax\", \"zotroneneis\", \"haifengl\", \"ddbourgin\", \"rhnvrm\", \"daviddao\", \"tdhopper\", \"shaoanlu\", \"plusjade\", \"Sophia-11\", \"JWarmenhoven\", \"martinwicke\", \"katzien\", \"hangtwenty\", \"hslatman\", \"mappum\", \"lefnire\", \"alexeygrigorev\", \"humphd\", \"gvwilson\", \"KaiyangZhou\", \"scopatz\", \"swanson\", \"acabunoc\", \"timzhang642\", \"lukaszkaiser\", \"sayakpaul\", \"nfmcclure\", \"MaxHalford\", \"sguada\", \"pennyliang\", \"carefree0910\", \"zhunzhong07\", \"yulequan\", \"penberg\", \"ifesdjeen\", \"glemaitre\", \"alicoding\", \"wilsonmar\", \"andrewda\", \"pbharrin\", \"robertmartin8\", \"leviding\", \"jiffyclub\", \"Sea-n\", \"sjwhitworth\", \"13o-bbr-bbq\", \"arnaldog12\", \"Lax\", \"kevinlin311tw\", \"simensen\", \"dribnet\", \"albahnsen\", \"junlulocky\", \"cbuckey-uda\", \"yarikoptic\", \"robmarkcole\", \"bigsnarfdude\", \"RedditSota\", \"angeladai\", \"csuldw\", \"Naereen\", \"Tarrasch\", \"ColCarroll\", \"Metnew\", \"jaraco\", \"ethanwhite\", \"krishnakumarsekar\", \"meirwah\", \"ketanhwr\", \"omo\", \"studiomohawk\", \"clarle\", \"gavinsimpson\", \"ezefranca\", \"ethen8181\", \"knathanieltucker\", \"adarsh0806\", \"kinow\", \"NathanEpstein\", \"Tomotoes\", \"zhigang1992\", \"fmichonneau\", \"gumblex\", \"Horaddrim\", \"pjbull\", \"Borda\", \"Vay-keen\", \"loveunk\", \"xuhdev\", \"JohnMcLear\", \"navdeep-G\", \"fhemberger\", \"svaksha\", \"jeasonstudio\", \"jdblischak\", \"brainstorm\", \"ptone\", \"Mostafa-Samir\", \"DeqianBai\", \"ranahanocka\", \"schmich\", \"lorensr\", \"lazywei\", \"krother\", \"yurrriq\", \"yaph\", \"cailurus\", \"init27\", \"jakirkham\", \"kadirpekel\", \"Jasonnor\", \"zonca\", \"JerryKurata\", \"antmarakis\", \"kgashok\", \"cmhungsteve\", \"t-k-\", \"msabramo\", \"axsaucedo\", \"keveman\", \"vmirly\", \"bboe\", \"Borye\", \"csinva\", \"art-programmer\", \"brylie\", \"rozentill\", \"benmccann\", \"weakish\", \"naupaka\", \"keppel\", \"kuixu\", \"cdeil\", \"vfdev-5\", \"cgohlke\", \"xiaqunfeng\", \"bgreenwell\", \"sinanuozdemir\", \"abingham\", \"widdowquinn\", \"BillMills\", \"timClicks\", \"ZYSzys\", \"shaqian\", \"QuLogic\", \"brandly\", \"iamaziz\", \"wking\", \"Philmod\", \"btbytes\", \"myui\", \"lsvih\", \"dubzzz\", \"gisikw\", \"AmaanC\", \"RaphaelMeudec\", \"hsiaoyi0504\", \"secretrobotron\", \"philippbayer\", \"nachocab\", \"ffmpbgrnn\", \"matthewfeickert\", \"Keiku\", \"justpic\", \"kwichmann\", \"maxim5\", \"vict0rsch\", \"SeanPrashad\", \"ss8651twtw\", \"ebenolson\", \"SiyuanQi\", \"BirkhoffLee\", \"lexnederbragt\", \"yoavz\", \"joaopedronardari\", \"mikl\", \"DamienIrving\", \"fleeting\", \"yoavram\", \"codedread\", \"inejc\", \"masinoa\", \"lxj616\", \"haraldschilly\", \"Erotemic\", \"hex108\", \"umstek\", \"rmarquis\", \"wanzhenchn\", \"wdm0006\", \"Domon\", \"ahmadia\", \"alphadl\", \"QSCTech-Sange\", \"Bachmann1234\", \"joyoyoyoyoyo\", \"gyoisamurai\", \"sdball\", \"rdingwall\", \"AdityaSoni19031997\", \"davidrhodus\", \"umpox\", \"aaren\", \"stedy\", \"DiegoCatalano\", \"daeyun\", \"joaorafaelm\", \"gitbook-bot\", \"patricksnape\", \"atinesh-s\", \"volker48\", \"drio\", \"kieranjol\", \"juanpabloaj\", \"vyper\", \"koriroys\", \"dhingratul\", \"gdevenyi\", \"denisarnaud\", \"koobs\", \"geon\", \"beangoben\", \"gvn\", \"YichenGong\", \"magsol\", \"orlitany\", \"fish2000\", \"rwdaigle\", \"adam-erickson\", \"whatrocks\", \"DakshMiglani\", \"dmcc\", \"gaodayue\", \"rodgzilla\", \"eccstartup\", \"andrewschreiber\", \"unode\", \"jrbourbeau\", \"fmder\", \"wogong\", \"mtchavez\", \"mandar2812\", \"Xyclade\", \"silverstone1903\", \"thezillion\", \"jakemcc\", \"cmmalone\", \"tobyhodges\", \"thouis\", \"run\", \"ssusnic\", \"rafaelsakurai\", \"Nukesor\", \"twitwi\", \"harshavamsi\", \"phocks\", \"cmutel\", \"prajjwal1\", \"npbool\", \"danyaljj\", \"baldassarreFe\", \"ericdill\", \"ReadmeCritic\", \"jakubczakon\", \"EdwardSmith1884\", \"sdierauf\", \"arteymix\", \"daddou-ma\", \"anujgupta82\", \"dtchepak\", \"Sentimentron\", \"GitHub30\", \"ricardoamaro\", \"LarryBattle\", \"dlebauer\", \"andresgottlieb\", \"bertjiazheng\", \"jeff1evesque\", \"fhs\", \"Chandlercjy\", \"jayrav13\", \"rtlee9\", \"byrichardpowell\", \"vishwajeetv\", \"ilivans\", \"frozenkp\", \"synesthesiam\", \"jpallen\", \"ArionMiles\", \"MuminjonGuru\", \"yeonjuan\", \"andreww\", \"BioGeek\", \"pradeep1288\", \"cogmission\", \"iiSeymour\", \"RickEyre\", \"tommyjiang\", \"harshnisar\", \"acastrounis\", \"lukearmstrong\", \"ghthor\", \"lxieyang\", \"x1957\", \"rachpt\", \"langner\", \"espoirMur\", \"cbarrick\", \"jcn\", \"optas\", \"havanagrawal\", \"zlu\", \"AdilZouitine\", \"polymeris\", \"re4lfl0w\", \"Amir-Arsalan\", \"alexsavio\", \"jgraving\", \"pbanaszkiewicz\", \"arimbr\", \"synapticarbors\", \"gideonthomas\", \"ProGamerGov\", \"Microsheep\", \"kno10\", \"Alex1996a\", \"nashjain\", \"KiranPanesar\", \"blokhin\", \"gaborvecsei\", \"michaelaye\", \"dmoisset\", \"vivienzou1\", \"rieder91\", \"herschel666\", \"advancedxy\", \"WuZhuoran\", \"natowi\", \"flipace\", \"ecederstrand\", \"piyushchauhan\", \"ammarasmro\", \"shashankgroovy\", \"iamBedant\", \"adamyala\", \"orionr\", \"floydpink\", \"daveredrum\", \"fanglinchen\", \"egeriis\", \"Cugtyt\", \"wojdyr\", \"hmchuong\", \"jGaboardi\", \"filipefilardi\", \"okjake\", \"ajmeese7\", \"robtaussig\", \"skvrahul\", \"lacava\", \"imatiach-msft\", \"stonebig\", \"testrain\", \"BernhardKonrad\", \"Diastro\", \"adibis\", \"meawoppl\", \"HaveF\", \"graphaelli\", \"pilif\", \"enjoyhot\", \"albertstill\", \"toaarnio\", \"pkuphy\", \"zh794390558\", \"easezyc\", \"code0100fun\", \"JanLauGe\", \"ocdtrekkie\", \"ZhengRui\", \"mysteriouspants\", \"sebix\", \"apeeyush\", \"dmnelson\", \"d4n1elchen\", \"raghavbali\", \"JamesLuoau\", \"shikharvaish28\", \"benedictflorance\", \"sudeepraja\", \"iglpdc\", \"djoos\", \"habi\", \"rogerzanoni\", \"BetaPundit\", \"chi-hung\", \"alg\", \"pkayfire\", \"SegFaultAX\", \"juliangarcia\", \"RockySJ\", \"TehMillhouse\", \"TaurusOlson\", \"rachtsingh\", \"sourcesoft\", \"wendingp\", \"jacarrico\", \"wassimseif\", \"curiousleo\", \"ShengKungYi\", \"bryngo\", \"AnshulBasia\", \"idear1203\", \"dnguneratne\", \"sun254\", \"abought\", \"srayuws\", \"cjauvin\", \"NeerajSarwan\", \"schneiderfelipe\", \"cloudyan\", \"allardbrain\", \"jankrepl\", \"Soypete\", \"kmscode\", \"tvogels\", \"SylvainDe\", \"sivanWu0222\", \"niltonslf\", \"mogwai\", \"JustroX\", \"GageAmes\", \"jbencook\", \"ajkl\", \"snurkabill\", \"RF-Nelson\", \"chkoar\", \"zldeng\", \"autodataming\", \"wrichert\", \"testbounty\", \"hanhdt\", \"nipunsadvilkar\", \"tiendq\", \"sstarr\", \"chhh\", \"hamiltont\", \"jaycode\", \"ses4j\", \"iory\", \"gliptak\", \"oneTaken\", \"havk64\", \"SnailSword\", \"javierlorenzod\", \"opie4624\", \"sshekh\", \"acusti\", \"avinashsai\", \"abarto\", \"vallentin\", \"nahumj\", \"jackmaney\", \"ss18\", \"dmmulroy\", \"ReekenX\", \"PBarmby\", \"tncardoso\", \"frankhjwx\", \"kid1412z\", \"tommyblue\", \"selimnairb\", \"NeroCube\", \"pmn4\", \"CSerxy\", \"wzell\", \"tranek\", \"ismaeIfm\", \"0asa\", \"amitkgupta\", \"DanielMorales9\", \"ambientlight\", \"jsmith\", \"erjanmx\", \"pipitone\", \"IsakFalk\", \"azillion\", \"emptyr1\", \"jaymody\", \"An3bi\", \"iamc\", \"SaumoPal97\", \"shahules786\", \"ehrenfeu\", \"songuke\", \"xiuluo\", \"srhrshr\", \"nolith\", \"tychenjiajun\", \"justanhduc\", \"LukasKnuth\", \"pan-long\", \"luvegood\", \"hwmrocker\", \"yuanzhaoYZ\", \"NJannasch\", \"caub\", \"sjml\", \"mindw\", \"praveenmylavarapu\", \"jselmani\", \"buddhikajay\", \"chrish42\", \"p-s-vishnu\", \"steven7851\", \"RingoTC\", \"timmartin19\", \"maikelwever\", \"wltrimbl\", \"mjschranz\", \"calberti\", \"everping\", \"gaulinmp\", \"briansorahan\", \"jappre\", \"vahtras\", \"asford\", \"rayeaster\", \"kastman\", \"digital-thinking\", \"EtienneBruines\", \"eecn\", \"hjlarry\", \"Devinsuit\", \"ccyanxyz\", \"sergioburdisso\", \"wenyangfu\", \"kjappelbaum\", \"sebg\", \"matheusgmaia\", \"Amir22010\", \"sagunji\", \"XiaoshuiHuang\", \"cshan\", \"apatsekin\", \"arc12\", \"jogjayr\", \"liuluheng\", \"planetceres\", \"kbagchiGWC\", \"CrazyBunQnQ\", \"aoping\", \"olivertomic\", \"cmacdonell\", \"finnigantime\", \"itsliupeng\", \"LoveMeWithoutAll\", \"alexobednikov\", \"beckgael\", \"postBG\", \"jimthompson5802\", \"jovilius\", \"melzareix\", \"dangsonbk\", \"strange-jiong\", \"CorcovadoMing\", \"flyingpot\", \"taylan\", \"TocarIP\", \"athiwatc\", \"teopost\", \"Vijayabhaskar96\", \"jmchen-g\", \"ecolell\", \"allthroughthenight\", \"KevinCooper\", \"hbaniecki\", \"windpls\", \"lstolcman\", \"cxxgtxy\", \"gpailler\", \"mkuhn\", \"itsmeolivia\", \"AnkurDedania\", \"chneau\", \"joybanerjee08\", \"ebuildy\", \"xlfe\", \"jocelynlih\", \"jalateras\", \"jsgv\", \"idelgado\", \"SwarShah\", \"amyrhoda\", \"ande765a\", \"mangei\", \"adam2392\", \"cjpurackal\", \"daz\", \"doppenhe\", \"wayneadams\", \"niklaskeerl\", \"jboy\", \"fatihbaltaci\", \"lzcabrera\", \"stromnov\", \"Zzlongjuanfeng\", \"ackerleytng\", \"andsor\", \"appleJax\", \"RasPat1\", \"bobiechen-twilio\", \"nathanhillyer\", \"waterson\", \"TitouanT\", \"lukelafountaine\", \"samedhaa\", \"cPolaris\", \"individual8\", \"cako\", \"elwinarens\", \"kevinkyyro\", \"zahanm\", \"sudipbhandari126\", \"el10savio\", \"ebigelow\", \"hyqskevin\", \"mewben\", \"ploth\", \"kennethjmyers\", \"ooxi\", \"tomhoover\", \"rsbohn\", \"jwsy\", \"dylandrop\", \"FlorisHoogenboom\", \"NotAnyMike\", \"luntain\", \"stieglma\", \"jared-weed\", \"xcodeburpx\", \"proinsias\", \"SubrataSarkar32\", \"yakud\", \"LiEmail\", \"AlexZhou1995\", \"gukoff\", \"meghpatel\", \"jcsims\", \"dombrno\", \"salehjg\", \"SentinelWarren\", \"avn3r\", \"pw\", \"alimon808\", \"sedge\", \"bendoerr\", \"ACharbonneau\", \"vinodkkurmi\", \"Minki-Kim95\", \"PatrickZH\", \"MadhumitaSushil\", \"moonboots\", \"datamove\", \"peterfabakker\", \"taoyudong\", \"bobrosoft\", \"rajeshvaya\", \"PeterShershov\", \"TuanNguyen27\", \"kota7\", \"divik544\", \"davidlowjw\", \"ericbuehl\", \"n-kats\", \"ilam\", \"ayakubovich\", \"YJH1987\", \"njern\", \"danielsan\", \"jpvg10\", \"mapx\", \"basickarl\", \"jkuchta\", \"guillermo-navas-palencia\", \"mgschwan\", \"DanilBaibak\", \"vad4msiu\", \"Petemir\", \"anishthite\", \"jackeylu\", \"itailang\", \"pfsq\", \"LizhangX\", \"12wang3\", \"kyranb\", \"LiberiFatali\", \"Vincent-Vercruyssen\", \"vargas\", \"nbsantos\", \"Finance-781\", \"moutai\", \"sohamM97\", \"buddhiv\", \"drlabratory\", \"zdgriffith\", \"derrg\", \"fchouteau\", \"moshejs\", \"SoumyadeepJana\", \"PrinzOwO\", \"tomahawk28\", \"RequireSun\", \"qualityjacks\", \"victorhcm\", \"girishkuniyal\", \"PGijsbers\", \"nvh95\", \"mgoodfellow\", \"ayushs136\", \"dbarbier\", \"adriancampos\", \"douglatornell\", \"adamwkraft\", \"awesome-bot\", \"adyates\", \"jeffin07\", \"voskresenskiy\", \"soumanpaul\", \"slcott\", \"mexeniz\", \"CorreyL\", \"jhashanti\", \"DanBeard\", \"elfelround\", \"cjratcliff\", \"tuanphuc\", \"zairah10\", \"sailakshmi17\", \"alisezer\", \"eeeeeric\", \"dogHere\", \"koomar\", \"KodeWorker\", \"SusieXu\", \"hugosoftdev\", \"liliuleo\", \"thecjharries\", \"kshs010239\", \"jgyllinsky\", \"mikej888\", \"nitin-tm\", \"shrutibhutaiya\", \"Hefeweizen\", \"baogianghoangvu\", \"wenruimeng\", \"pleabargain\", \"cratonica\", \"malfple\", \"chess99\", \"mkotov13\", \"AkshayVarik\", \"Mintisma\", \"mckays630\", \"crouchred\", \"AJDBenner\", \"Mchristos\", \"mingzhang96\", \"tgray\", \"aosama\", \"mzakariaCERN\", \"vattay\", \"nmb10\", \"e173101\", \"rajasekharponakala\", \"DH-Diego\", \"ktolstikhin\", \"cavestruz\", \"fangweili\", \"anzellai\", \"whughw\", \"Karl-EdwardFPJeanMehu\", \"Suraj520\", \"ahnt\", \"firebreath1001\", \"trpapp\", \"SarthakYadav\", \"JsonAC\", \"wsbmxa198700\", \"olveirap\", \"HapeMask\", \"lacanlale\", \"timfrostmann\", \"frannievas\", \"kreuvf\", \"Div44\", \"kilsenp\", \"jacksonlo\", \"mraje16\", \"Ouss4\", \"dsych\", \"bob7783\", \"yhx5768\", \"kcrandall\", \"Amjad-H-Ali\", \"mgoldey\", \"itzamna314\", \"UjjwalAryal\", \"saiabishek1\", \"shenyyi\", \"DrDavidS\", \"anuj1207\", \"aaroncm\", \"eshizhan\", \"danielbogomazov\", \"RandomArray\", \"wenphan\", \"kacper1095\", \"IgorKovr\", \"jongoodnow\", \"databaaz\", \"rahmanhafeezul\", \"thanhnguyentang\", \"bon\", \"mollygibson\", \"beroe\", \"KeniMorri\", \"skervim\", \"borodenkov\", \"Budddy\", \"peter-toth\", \"samyag1\", \"McKenzyPG\", \"jlar0che\", \"irrationalRock\", \"phillies\", \"narisada014\", \"Jurilz\", \"JasonGitHub\", \"alishutc\", \"optixlab\", \"Adrien-Jecker\", \"LecJackS\", \"janismdhanbad\", \"ankitkul\", \"louispotok\", \"K-LV\", \"festline\", \"ronnierios\", \"agusnavce\", \"flytomylife\", \"Alveona\", \"varshapaidi\", \"2y2simple\", \"mirjalil\", \"npanti\", \"mybaseball52\", \"digitalduke\", \"Airatiki\", \"igorrocha\", \"junxnone\", \"wtollett-usgs\", \"alexlokotochek\", \"Zhi-lin\", \"jldohmann\", \"HemuManju\", \"Bachstelze\", \"daniel-kashin\", \"alcidesv\", \"JustinJudd\", \"MTietze\", \"busterroni\", \"TwFlem\", \"poyuwu\", \"m-maksyutin\", \"jaywinhuang\", \"martijnvanbeers\", \"BokaiLIAN\", \"codingcai\", \"jamesmyatt\", \"adpon\", \"elkfrawy-df\", \"swlsw\", \"muhammadyaseen\", \"esztiorm\", \"Owen-Mak\", \"sagardubey3\", \"joaoavf\", \"nschor\", \"oussou-dev\", \"IamThilina\", \"brigham\", \"Pooch11\", \"SeanPedersen\", \"rohduggal\", \"EtienneT\", \"maks-a\", \"Mrzhangxiaohua\", \"gcoter\", \"omytryniuk\", \"MarcelRobeer\", \"MUSSONT\", \"daanmichiels\", \"nitinagarwal\", \"lupusomniator\", \"giuliatondin\", \"lzamparo\", \"nektor211\", \"juholehtonen\", \"TusharShandilya\", \"Psimage\", \"LiLiu93\", \"LukeArn\", \"sagarcadet\", \"willalways\", \"mikelogsdon\", \"hanpum\", \"hetii\", \"gauravcharnalia\", \"testaccount553\", \"czenzel\", \"zylix666\", \"metrafonic\", \"fndjjx\", \"mosew\", \"harenbergsd\", \"robot-c0der\", \"eddyzhd\", \"Asterisk14\", \"Fatehsandhu\", \"grayskripko\", \"Ja1r0\", \"josephmmisiti\", \"curiousrohan\", \"binilj04\", \"chrisadami\", \"AselaDarshan\", \"stnk20\", \"Nebula83\", \"jaksmid\", \"credentiality\", \"smbeli\", \"maxnk\", \"kzhk75\", \"cgcgcg\", \"ini\", \"yangyyt\", \"jeffcore\", \"engineeress\", \"PaulDebus\", \"clappis\", \"Tirzono\", \"aniag\", \"jiangf13\", \"ulido\", \"Gabriel-Azevedo-Ferreira\", \"monomagentaeggroll\", \"cswef\", \"mmBabol\", \"miksago\", \"LeeMaria007\", \"yonatanf\", \"selay01\", \"Frenchhorn\", \"tomassvensson\", \"TommyBark\", \"sseidl88\", \"AlexanderKunkel\", \"SumanthReddyKaliki\", \"vicramr\", \"triangeljs\", \"dear983604\", \"wang1211\", \"YongshanKe\", \"ivigamberdiev\", \"cameroncan\", \"alexnich\", \"yjh\", \"Kacawi\", \"AndrewLiesinger\", \"libertatis\", \"vilmacio22\", \"ilbuono\", \"jackkuipers\", \"agngrant\", \"ao-song\", \"twigz20\", \"tomraulet\", \"Lincete\", \"ThatAndresV\", \"ipcenas\", \"drskd\", \"egorpolusmak\", \"matt-jay\", \"Dr-Zhou\", \"aggronerd\", \"SumitBando\", \"ThePhantomCoder\", \"GordianStapf\", \"ari-schaffel\", \"CookieDom\", \"bigwave\", \"nyoung85\", \"rafalgrm\", \"hungphandinh92it\", \"YINCHENLI\", \"hlkcrcck\", \"varan42\", \"marsben\", \"GLevV\", \"sudoes\", \"adityahiran\", \"JayJayBinks\", \"mkeds\", \"thedadams\", \"albertmolinermrf\", \"YoungMStudio\", \"zyc1gq\", \"K1t1k\", \"mzk912778163\", \"tuantp7\", \"chrissoulierserv\", \"mrtnbrst\", \"ss52\", \"bvonboyen\", \"kersov\", \"Charismatron\", \"lee709\", \"guedalia\", \"Bruce-Feldman\", \"grp-bork\", \"IMWP\", \"gsenseless\", \"seIncorp\", \"qhfgva\", \"itkinai\", \"Th30\", \"zzincubus\", \"163-0533\", \"thesimanjan\", \"ecbc1\", \"tairiUdacity\", \"Liam-Yang\", \"coderfive\", \"oleksii-trekhleb-epam\", \"peter-parque\", \"jliddie\", \"kylegrover\", \"eldaniz\", \"elesueur\", \"ExterminateWho\", \"wqiancheng\", \"Asmolovskij\", \"creinders\", \"Pirikara\", \"toddrme2178\", \"imaness\", \"qianguyizhe\", \"xkcao\", \"rumi-naik\", \"pdkovacs\", \"carlward\", \"ser-serege\", \"ritabentodosreis\", \"p1gd0g\", \"lisahdd007\", \"ntache\", \"ivesn\", \"hfanahita\", \"scraggard\", \"mikhailsergeevi4\", \"Digitalmobz\", \"justramgerry\", \"jvanlangen\", \"tushargt\", \"snowde\", \"synapton\", \"sirius999999\", \"Tom-Ren\", \"willgroves\", \"twotabbies\", \"cpdj\", \"serickso\", \"qiagu\", \"APorterOReilly\", \"mkilavuz\", \"KirillPanin\", \"bkhaleghi\", \"omrimendels\", \"aathauck\", \"amar00k\", \"wla80\", \"aquinasCode\", \"gceboh\", \"KaiNieRus\", \"sys0613\", \"JJLWHarrison\", \"njojic\", \"4may\", \"bluewoodtree\", \"sdsk\", \"ptaiga\", \"liuliu5151\", \"andrewd76\", \"jasonbhart\", \"maximkeremet\", \"svntjng\", \"dnn37\", \"acupofdata\", \"MdScntst\", \"mahajani123\", \"deeper-learning\", \"bkm009\", \"afromanF\", \"alexey-grigorev-sm\"], \"xaxis\": \"x\", \"y\": [36270, 12725, 9193, 8184, 5884, 5757, 5380, 5035, 5002, 4934, 4589, 4508, 3175, 3046, 2970, 2902, 2859, 2809, 2495, 2461, 2355, 2010, 1952, 1938, 1742, 1724, 1657, 1631, 1621, 1558, 1550, 1521, 1470, 1348, 1311, 1287, 1262, 1245, 1235, 1227, 1222, 1192, 1169, 1127, 1104, 1083, 989, 985, 928, 917, 877, 870, 863, 858, 840, 832, 813, 786, 772, 737, 730, 707, 697, 693, 693, 684, 683, 663, 658, 624, 616, 612, 607, 606, 603, 603, 602, 567, 563, 556, 544, 541, 537, 533, 532, 531, 529, 529, 525, 522, 521, 493, 491, 477, 472, 472, 463, 460, 459, 458, 456, 451, 449, 446, 439, 433, 430, 424, 421, 418, 417, 410, 406, 400, 389, 388, 383, 381, 364, 363, 362, 356, 354, 353, 351, 346, 346, 345, 339, 338, 318, 315, 308, 298, 292, 291, 287, 287, 286, 281, 278, 275, 273, 271, 262, 260, 257, 254, 254, 252, 247, 244, 244, 243, 241, 238, 235, 235, 234, 225, 221, 220, 218, 216, 215, 210, 208, 204, 204, 201, 201, 200, 197, 195, 194, 193, 192, 192, 191, 190, 189, 188, 186, 185, 185, 182, 182, 180, 175, 174, 174, 174, 172, 172, 170, 167, 164, 162, 159, 159, 157, 154, 152, 149, 148, 147, 147, 144, 143, 143, 142, 140, 138, 138, 137, 135, 134, 130, 125, 124, 123, 121, 121, 121, 120, 120, 119, 118, 118, 118, 117, 116, 115, 115, 115, 115, 114, 112, 111, 110, 108, 107, 106, 105, 105, 104, 103, 102, 100, 100, 99, 99, 99, 98, 97, 97, 97, 97, 96, 95, 94, 94, 94, 94, 94, 94, 92, 92, 92, 92, 92, 92, 91, 90, 90, 90, 90, 89, 88, 88, 87, 84, 84, 83, 83, 82, 82, 82, 81, 81, 80, 80, 80, 80, 79, 78, 76, 75, 75, 74, 74, 73, 73, 73, 73, 73, 72, 72, 72, 72, 71, 71, 71, 71, 71, 70, 70, 69, 69, 68, 68, 67, 67, 66, 66, 66, 66, 65, 64, 64, 64, 63, 63, 63, 63, 62, 62, 62, 62, 62, 62, 62, 62, 62, 62, 62, 62, 62, 61, 61, 61, 61, 61, 60, 59, 59, 59, 59, 58, 58, 58, 58, 58, 58, 58, 58, 57, 56, 55, 55, 55, 55, 55, 54, 54, 54, 54, 54, 54, 54, 53, 53, 53, 53, 53, 53, 53, 53, 52, 52, 52, 51, 51, 51, 51, 50, 50, 50, 50, 50, 50, 50, 49, 49, 49, 49, 49, 48, 48, 48, 48, 48, 47, 47, 47, 47, 47, 47, 47, 47, 46, 46, 46, 45, 45, 45, 45, 45, 45, 45, 44, 44, 44, 44, 44, 44, 43, 43, 43, 43, 43, 43, 43, 42, 42, 42, 41, 41, 41, 41, 41, 41, 41, 40, 40, 40, 40, 40, 39, 39, 39, 39, 39, 39, 39, 38, 38, 38, 38, 37, 37, 37, 37, 37, 37, 37, 37, 36, 36, 36, 36, 36, 36, 36, 36, 36, 35, 35, 35, 35, 35, 35, 34, 34, 34, 34, 34, 34, 34, 34, 34, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 32, 32, 32, 32, 32, 32, 32, 31, 31, 31, 31, 31, 30, 30, 30, 30, 30, 30, 30, 30, 30, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 28, 28, 28, 28, 28, 28, 27, 27, 27, 27, 27, 27, 27, 27, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 25, 25, 25, 25, 25, 25, 25, 25, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 23, 23, 23, 23, 23, 23, 23, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 18, 18, 18, 18, 18, 18, 18, 18, 18, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 15, 15, 15, 15, 15, 15, 15, 15, 15, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 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, 2, 2, 2, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], \"yaxis\": \"y\"}], {\"barmode\": \"relative\", \"legend\": {\"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"plot_bgcolor\": \"rgba(36, 83, 97, 0.06)\", \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"autotypenumbers\": \"strict\", \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"user_name\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"followers\"}, \"type\": \"log\"}}, {\"responsive\": true} ).then(function(){\n",
" \n",
"var gd = document.getElementById('b6129c77-54e4-4baa-ad70-7e5a0d48a066');\n",
"var x = new MutationObserver(function (mutations, observer) {{\n",
" var display = window.getComputedStyle(gd).display;\n",
" if (!display || display === 'none') {{\n",
" console.log([gd, 'removed!']);\n",
" Plotly.purge(gd);\n",
" observer.disconnect();\n",
" }}\n",
"}});\n",
"\n",
"// Listen for the removal of the full notebook cells\n",
"var notebookContainer = gd.closest('#notebook-container');\n",
"if (notebookContainer) {{\n",
" x.observe(notebookContainer, {childList: true});\n",
"}}\n",
"\n",
"// Listen for the clearing of the current output cell\n",
"var outputEl = gd.closest('.output');\n",
"if (outputEl) {{\n",
" x.observe(outputEl, {childList: true});\n",
"}}\n",
"\n",
" }) }; </script> </div>\n",
"</body>\n",
"</html>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"text/html": [
"<html>\n",
"<head><meta charset=\"utf-8\" /></head>\n",
"<body>\n",
" <div> <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script> <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
" <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script> <div id=\"5a7390b1-742d-4be9-855e-b136b11fcb7b\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"5a7390b1-742d-4be9-855e-b136b11fcb7b\")) { Plotly.newPlot( \"5a7390b1-742d-4be9-855e-b136b11fcb7b\", [{\"alignmentgroup\": \"True\", \"hovertemplate\": \"user_name=%{x}<br>following=%{y}<extra></extra>\", \"legendgroup\": \"\", \"marker\": {\"color\": \"#636efa\"}, \"name\": \"\", \"offsetgroup\": \"\", \"orientation\": \"v\", \"showlegend\": false, \"textposition\": \"auto\", \"type\": \"bar\", \"x\": [\"t-k-\", \"Ir1d\", \"joyoyoyoyoyo\", \"woliveiras\", \"silverstone1903\", \"btbytes\", \"robmarkcole\", \"justpic\", \"philips\", \"yurrriq\", \"ZYSzys\", \"layumi\", \"adam-erickson\", \"oldratlee\", \"Naereen\", \"cloudyan\", \"kgashok\", \"autodataming\", \"brainstorm\", \"avinashsai\", \"hsiaoyi0504\", \"fish2000\", \"ty4z2008\", \"wkentaro\", \"hangtwenty\", \"rhnvrm\", \"TaurusOlson\", \"daddou-ma\", \"willingc\", \"josephmisiti\", \"wogong\", \"scopatz\", \"parkr\", \"sourcesoft\", \"firmai\", \"bigsnarfdude\", \"yulequan\", \"Alex1996a\", \"AmaanC\", \"brylie\", \"HaveF\", \"brandly\", \"mappum\", \"cmhungsteve\", \"alphadl\", \"joaopedronardari\", \"ujjwalkarn\", \"dimpurr\", \"Amir-Arsalan\", \"fleeting\", \"studiomohawk\", \"denisarnaud\", \"run\", \"matthewfeickert\", \"arimbr\", \"Philmod\", \"ezefranca\", \"whatrocks\", \"srhrshr\", \"svaksha\", \"eccstartup\", \"Borda\", \"idf\", \"swanson\", \"guillaume-chevalier\", \"ss8651twtw\", \"umstek\", \"keppel\", \"tomhoover\", \"Lax\", \"wilsonmar\", \"wassimseif\", \"kuixu\", \"glemaitre\", \"Gaohaoyang\", \"juanpabloaj\", \"fmichonneau\", \"cbarrick\", \"leviding\", \"rmarquis\", \"ketanhwr\", \"Domon\", \"terrytangyuan\", \"sckott\", \"ghthor\", \"kjappelbaum\", \"oneTaken\", \"phocks\", \"tdhopper\", \"soulmachine\", \"MaxHalford\", \"gaodayue\", \"BioGeek\", \"AdilZouitine\", \"joaorafaelm\", \"SnailSword\", \"kid1412z\", \"WuZhuoran\", \"zh794390558\", \"wenyangfu\", \"nipunsadvilkar\", \"abhshkdz\", \"dribnet\", \"kieranjol\", \"weakish\", \"kwichmann\", \"NeroCube\", \"mtchavez\", \"x1957\", \"RingoTC\", \"clarle\", \"ffmpbgrnn\", \"ericdill\", \"AdityaSoni19031997\", \"davidrhodus\", \"ZuzooVn\", \"testrain\", \"ArionMiles\", \"kinow\", \"meawoppl\", \"vivienzou1\", \"salehjg\", \"sivanWu0222\", \"Sea-n\", \"planetceres\", \"haraldschilly\", \"jGaboardi\", \"msabramo\", \"rajasekharponakala\", \"emptyr1\", \"Tarrasch\", \"andrewschreiber\", \"lazywei\", \"NJannasch\", \"An3bi\", \"chneau\", \"DakshMiglani\", \"andresgottlieb\", \"niltonslf\", \"dubzzz\", \"rayeaster\", \"ammarasmro\", \"thezillion\", \"d4n1elchen\", \"treyhunner\", \"jovilius\", \"zhigang1992\", \"yaph\", \"hex108\", \"drio\", \"gdevenyi\", \"hamelsmu\", \"adamyala\", \"koobs\", \"rodgzilla\", \"Jasonnor\", \"susanli2016\", \"QSCTech-Sange\", \"aoping\", \"cailurus\", \"havanagrawal\", \"naupaka\", \"pkuphy\", \"liuluheng\", \"dhingratul\", \"rogerzanoni\", \"baogianghoangvu\", \"volker48\", \"MuminjonGuru\", \"sdierauf\", \"IsakFalk\", \"prajjwal1\", \"hslatman\", \"SylvainDe\", \"advancedxy\", \"lxieyang\", \"mandar2812\", \"dnguneratne\", \"windpls\", \"iiSeymour\", \"postBG\", \"SegFaultAX\", \"pradeep1288\", \"javierlorenzod\", \"itsliupeng\", \"arteymix\", \"JanLauGe\", \"vishwajeetv\", \"daviddao\", \"jayrav13\", \"iamaziz\", \"xuhdev\", \"hyqskevin\", \"tychenjiajun\", \"ehrenfeu\", \"vfdev-5\", \"NeerajSarwan\", \"demidovakatya\", \"azillion\", \"Horaddrim\", \"wayneadams\", \"ebigelow\", \"herschel666\", \"navdeep-G\", \"GitHub30\", \"zhunzhong07\", \"andrewda\", \"dangsonbk\", \"jaymody\", \"wendingp\", \"jakirkham\", \"strange-jiong\", \"jacarrico\", \"daveredrum\", \"JJ\", \"lawlite19\", \"curiousleo\", \"penberg\", \"AnshulBasia\", \"chess99\", \"wepe\", \"shashankgroovy\", \"Suraj520\", \"mogwai\", \"SaumoPal97\", \"timClicks\", \"plusjade\", \"kadirpekel\", \"jappre\", \"skvrahul\", \"DanielMorales9\", \"CSerxy\", \"jankrepl\", \"Soypete\", \"divik544\", \"dmmulroy\", \"KaiyangZhou\", \"finnigantime\", \"TarrySingh\", \"cogmission\", \"sshekh\", \"Diastro\", \"axsaucedo\", \"ambientlight\", \"jeasonstudio\", \"individual8\", \"rozentill\", \"luispedro\", \"sudipbhandari126\", \"lsvih\", \"fatihbaltaci\", \"sun254\", \"bryngo\", \"dtchepak\", \"JohnMcLear\", \"gisikw\", \"jselmani\", \"stedy\", \"RequireSun\", \"kevinlin311tw\", \"cshan\", \"vmirly\", \"koriroys\", \"DeqianBai\", \"opie4624\", \"Dr-Zhou\", \"lstolcman\", \"proinsias\", \"hanhdt\", \"gvn\", \"idear1203\", \"tncardoso\", \"nitin-tm\", \"srayuws\", \"inejc\", \"samedhaa\", \"YichenGong\", \"mysteriouspants\", \"victorhcm\", \"espoirMur\", \"chiphuyen\", \"wdm0006\", \"alexobednikov\", \"qualityjacks\", \"jsgv\", \"jindongwang\", \"ocdtrekkie\", \"dmcc\", \"zldeng\", \"benedekrozemberczki\", \"ColCarroll\", \"langner\", \"habi\", \"blokhin\", \"rasbt\", \"benedictflorance\", \"jackeylu\", \"cPolaris\", \"robtaussig\", \"joybanerjee08\", \"secretrobotron\", \"justanhduc\", \"jhashanti\", \"alicoding\", \"djoos\", \"CorcovadoMing\", \"soumanpaul\", \"JustroX\", \"snurkabill\", \"yakud\", \"katzien\", \"adibis\", \"kennethjmyers\", \"codingcai\", \"el10savio\", \"teopost\", \"kwhinnery\", \"sdball\", \"Microsheep\", \"bamos\", \"jsmith\", \"SentinelWarren\", \"pbanaszkiewicz\", \"pkayfire\", \"lefnire\", \"acastrounis\", \"aymericdamien\", \"pmn4\", \"alexsavio\", \"sayakpaul\", \"piyushchauhan\", \"filipefilardi\", \"frnsys\", \"janismdhanbad\", \"ZhengRui\", \"ss18\", \"AnkurDedania\", \"Jack-Cherish\", \"Amir22010\", \"praveenmylavarapu\", \"rohduggal\", \"vyper\", \"tuanphuc\", \"juliangarcia\", \"ackerleytng\", \"egeriis\", \"xlfe\", \"xcodeburpx\", \"widdowquinn\", \"TuanNguyen27\", \"flipace\", \"guillermo-navas-palencia\", \"pw\", \"arnaldog12\", \"agusnavce\", \"RockySJ\", \"philippbayer\", \"timzhang642\", \"dmnelson\", \"nachocab\", \"CrazyBunQnQ\", \"graphaelli\", \"daz\", \"k88hudson\", \"lzcabrera\", \"polaris1119\", \"krother\", \"magsol\", \"rdingwall\", \"yeonjuan\", \"Bachmann1234\", \"ethanwhite\", \"meghpatel\", \"BetaPundit\", \"LiEmail\", \"tommyjiang\", \"anishthite\", \"ses4j\", \"frozenkp\", \"mgoodfellow\", \"n-kats\", \"thanhnguyentang\", \"sebix\", \"reiinakano\", \"havk64\", \"frankhjwx\", \"Tomotoes\", \"oussou-dev\", \"iamBedant\", \"xiaqunfeng\", \"taylan\", \"andsor\", \"karthik\", \"unode\", \"fhs\", \"imatiach-msft\", \"rtlee9\", \"abought\", \"MadhumitaSushil\", \"DiegoCatalano\", \"cjauvin\", \"timfrostmann\", \"schneiderfelipe\", \"jogjayr\", \"ReekenX\", \"shuhuai007\", \"fanglinchen\", \"adriancampos\", \"sjwhitworth\", \"ccyanxyz\", \"re4lfl0w\", \"jboy\", \"ricardoamaro\", \"nfmcclure\", \"Yorko\", \"sagunji\", \"mzakariaCERN\", \"lacava\", \"junxnone\", \"fchouteau\", \"ranahanocka\", \"daeyun\", \"init27\", \"kailashahirwar\", \"trpapp\", \"lukelafountaine\", \"iamc\", \"bendoerr\", \"sjml\", \"synapticarbors\", \"dogHere\", \"voskresenskiy\", \"p-s-vishnu\", \"mikl\", \"eecn\", \"tdunning\", \"titu1994\", \"zonca\", \"fengdu78\", \"tobyhodges\", \"codedread\", \"KevinCooper\", \"elwinarens\", \"schmich\", \"twitwi\", \"albertstill\", \"KiranPanesar\", \"byrichardpowell\", \"vargas\", \"yuanxiaosc\", \"ankitkul\", \"lxj616\", \"RickEyre\", \"dombrno\", \"RasPat1\", \"omo\", \"AlexZhou1995\", \"kilsenp\", \"jwsy\", \"Ja1r0\", \"RaphaelMeudec\", \"SwarShah\", \"TitouanT\", \"BillMills\", \"yangyyt\", \"Keiku\", \"easezyc\", \"maikelwever\", \"hwmrocker\", \"ande765a\", \"cmutel\", \"jgraving\", \"sagarcadet\", \"antmarakis\", \"JasonGitHub\", \"Asterisk14\", \"GageAmes\", \"gumblex\", \"0asa\", \"Xyclade\", \"nathanhillyer\", \"jldohmann\", \"TehMillhouse\", \"thouis\", \"caub\", \"everping\", \"shahules786\", \"apeeyush\", \"matheusgmaia\", \"drlabratory\", \"JsonAC\", \"krishnakumarsekar\", \"dlebauer\", \"Metnew\", \"mewben\", \"lacanlale\", \"Cugtyt\", \"rsbohn\", \"Zzlongjuanfeng\", \"RF-Nelson\", \"rhiever\", \"xxg1413\", \"adarsh0806\", \"kzhk75\", \"luntain\", \"niklaskeerl\", \"stieglma\", \"vict0rsch\", \"SiyuanQi\", \"shrutibhutaiya\", \"liancheng\", \"melzareix\", \"AJDBenner\", \"jakemcc\", \"LarryBattle\", \"IgorKovr\", \"Mchristos\", \"ptone\", \"hjlarry\", \"rieder91\", \"curiousrohan\", \"polymeris\", \"raghavbali\", \"mingzhang96\", \"optixlab\", \"shaoanlu\", \"yhx5768\", \"cako\", \"adam2392\", \"orionr\", \"BernhardKonrad\", \"yoavz\", \"nitinagarwal\", \"hmchuong\", \"gaborvecsei\", \"zdgriffith\", \"gaulinmp\", \"mangei\", \"sudeepraja\", \"loveunk\", \"ooxi\", \"yarikoptic\", \"mexeniz\", \"K1t1k\", \"jiangf13\", \"sstarr\", \"shaqian\", \"SubrataSarkar32\", \"ddbourgin\", \"ayushs136\", \"junlulocky\", \"code0100fun\", \"iory\", \"eeeeeric\", \"arfon\", \"bboe\", \"sergioburdisso\", \"imhuay\", \"derrg\", \"ismaeIfm\", \"elfelround\", \"YJH1987\", \"alisezer\", \"alg\", \"e9t\", \"databaaz\", \"NotAnyMike\", \"nolith\", \"jiffyclub\", \"SeanPedersen\", \"bertjiazheng\", \"atinesh-s\", \"vattay\", \"timmartin19\", \"gavinsimpson\", \"e173101\", \"chrish42\", \"ecolell\", \"zylix666\", \"Minki-Kim95\", \"danielsan\", \"robot-c0der\", \"jphall663\", \"yoavram\", \"lorensr\", \"digitalduke\", \"olivertomic\", \"BirkhoffLee\", \"jeffin07\", \"pipitone\", \"jrbourbeau\", \"PeterShershov\", \"mapx\", \"Budddy\", \"sys0613\", \"firebreath1001\", \"Amjad-H-Ali\", \"beangoben\", \"mgoldey\", \"alimon808\", \"LizhangX\", \"digital-thinking\", \"jocelynlih\", \"whughw\", \"ilam\", \"Gabriel-Azevedo-Ferreira\", \"irrationalRock\", \"mrry\", \"JWarmenhoven\", \"PBarmby\", \"ajmeese7\", \"CorreyL\", \"csuldw\", \"saiabishek1\", \"alishutc\", \"MUSSONT\", \"ktolstikhin\", \"KeniMorri\", \"tomraulet\", \"clappis\", \"olveirap\", \"trekhleb\", \"stefanv\", \"athiwatc\", \"pleabargain\", \"ericbuehl\", \"imathis\", \"ayakubovich\", \"kcrandall\", \"jacksonlo\", \"sohamM97\", \"phillies\", \"LecJackS\", \"mjschranz\", \"patricksnape\", \"chhh\", \"BokaiLIAN\", \"Mrzhangxiaohua\", \"FlorisHoogenboom\", \"mraje16\", \"peterfabakker\", \"buddhiv\", \"buddhikajay\", \"mybaseball52\", \"jwasham\", \"LoveMeWithoutAll\", \"mjpieters\", \"pan-long\", \"flyingpot\", \"Owen-Mak\", \"basickarl\", \"hbaniecki\", \"Nukesor\", \"pilif\", \"Hefeweizen\", \"csinva\", \"danielbogomazov\", \"sagardubey3\", \"jackmaney\", \"pfsq\", \"simensen\", \"svntjng\", \"K-LV\", \"Petemir\", \"ThePhantomCoder\", \"Bachstelze\", \"tommyblue\", \"amitkgupta\", \"tirthajyoti\", \"kevinkyyro\", \"maxnk\", \"moonboots\", \"vad4msiu\", \"harshavamsi\", \"vilmacio22\", \"zlotus\", \"ahmadia\", \"jlar0che\", \"PrinzOwO\", \"acusti\", \"LukasKnuth\", \"cjpurackal\", \"chi-hung\", \"chkoar\", \"jpvg10\", \"lupusomniator\", \"rachtsingh\", \"UjjwalAryal\", \"DanBeard\", \"kyranb\", \"Zhi-lin\", \"selimnairb\", \"sailakshmi17\", \"wsbmxa198700\", \"jcn\", \"SumanthReddyKaliki\", \"maximkeremet\", \"Chandlercjy\", \"floydpink\", \"jkuchta\", \"kastman\", \"sedge\", \"nahumj\", \"smbeli\", \"michaelaye\", \"briansorahan\", \"Pirikara\", \"ilivans\", \"Jurilz\", \"Div44\", \"ptaiga\", \"KirillPanin\", \"lettier\", \"allardbrain\", \"abingham\", \"juholehtonen\", \"girishkuniyal\", \"meirwah\", \"gideonthomas\", \"gcoter\", \"Adrien-Jecker\", \"ajkl\", \"llSourcell\", \"rachpt\", \"Sentimentron\", \"davidlowjw\", \"koomar\", \"fmder\", \"mkotov13\", \"omytryniuk\", \"SoumyadeepJana\", \"jimthompson5802\", \"jaraco\", \"jbencook\", \"erjanmx\", \"McKenzyPG\", \"beckgael\", \"DH-Diego\", \"alcidesv\", \"jgyllinsky\", \"12wang3\", \"enjoyhot\", \"acabunoc\", \"liliuleo\", \"jcsims\", \"zairah10\", \"maks-a\", \"dylandrop\", \"kbagchiGWC\", \"SusieXu\", \"jessitron\", \"muhammadyaseen\", \"wenruimeng\", \"aosama\", \"Vijayabhaskar96\", \"harshnisar\", \"douglatornell\", \"ploth\", \"twigz20\", \"pjbull\", \"anujgupta82\", \"Kacawi\", \"jongoodnow\", \"hamiltont\", \"art-programmer\", \"vrv\", \"doppenhe\", \"igorrocha\", \"wtollett-usgs\", \"kno10\", \"shenyyi\", \"gpailler\", \"anuj1207\", \"maxim5\", \"wenphan\", \"stonebig\", \"taoyudong\", \"Airatiki\", \"Ouss4\", \"Fatehsandhu\", \"slcott\", \"snowde\", \"TusharShandilya\", \"ecederstrand\", \"jaywinhuang\", \"jvanlangen\", \"masinoa\", \"nashjain\", \"njern\", \"kshs010239\", \"aggronerd\", \"IamThilina\", \"stromnov\", \"alexlokotochek\", \"RandomArray\", \"itzamna314\", \"songuke\", \"npbool\", \"bgreenwell\", \"zotroneneis\", \"DrDavidS\", \"vinodkkurmi\", \"crouchred\", \"harenbergsd\", \"benmccann\", \"daanmichiels\", \"cameroncan\", \"frannievas\", \"kacper1095\", \"borodenkov\", \"zahanm\", \"Mintisma\", \"Alveona\", \"QuLogic\", \"JamesLuoau\", \"JerryKurata\", \"Frenchhorn\", \"czenzel\", \"stephenturner\", \"metrafonic\", \"EdwardSmith1884\", \"varshapaidi\", \"imaness\", \"apatsekin\", \"keveman\", \"selay01\", \"kmscode\", \"jamesmyatt\", \"eddyzhd\", \"gliptak\", \"nektor211\", \"robertmartin8\", \"TocarIP\", \"EtienneT\", \"hugosoftdev\", \"xiuluo\", \"martinwicke\", \"rajeshvaya\", \"cratonica\", \"matt-jay\", \"malfple\", \"libertatis\", \"wrichert\", \"narisada014\", \"toaarnio\", \"WillKoehrsen\", \"TwFlem\", \"asford\", \"qiagu\", \"ACharbonneau\", \"okjake\", \"nyoung85\", \"ebuildy\", \"vahtras\", \"arc12\", \"hanpum\", \"hlkcrcck\", \"pdkovacs\", \"amitshekhariitbhu\", \"moshejs\", \"lzamparo\", \"Karl-EdwardFPJeanMehu\", \"busterroni\", \"moutai\", \"myui\", \"npanti\", \"warmheartli\", \"afshinea\", \"KodeWorker\", \"nschor\", \"lisahdd007\", \"oleksii-trekhleb-epam\", \"yuanzhaoYZ\", \"angeladai\", \"dformoso\", \"lukaszkaiser\", \"seIncorp\", \"ljpzzz\", \"tomahawk28\", \"kylegrover\", \"YINCHENLI\", \"AlexanderKunkel\", \"RedstoneWill\", \"pbharrin\", \"joaoavf\", \"beroe\", \"SamyPesse\", \"ProGamerGov\", \"humphd\", \"agngrant\", \"qianguyizhe\", \"wking\", \"wanzhenchn\", \"Psimage\", \"YongshanKe\", \"mosew\", \"swlsw\", \"skervim\", \"AkshayVarik\", \"geon\", \"ulido\", \"albahnsen\", \"Asmolovskij\", \"fndjjx\", \"ronnierios\", \"2y2simple\", \"thecjharries\", \"optas\", \"rafalgrm\", \"nbsantos\", \"willalways\", \"jmchen-g\", \"tomassvensson\", \"PatrickZH\", \"TommyBark\", \"mzk912778163\", \"adamwkraft\", \"stnk20\", \"brigham\", \"hungphandinh92it\", \"cdeil\", \"DanilBaibak\", \"zlu\", \"avn3r\", \"giuliatondin\", \"MdScntst\", \"kersov\", \"awesome-bot\", \"shervinea\", \"aaroncm\", \"daniel-kashin\", \"mmBabol\", \"aaren\", \"grayskripko\", \"MTietze\", \"liuliu5151\", \"bigwave\", \"ari-schaffel\", \"SeanPrashad\", \"baldassarreFe\", \"wzell\", \"rafaelsakurai\", \"poyuwu\", \"cxxgtxy\", \"iglpdc\", \"binilj04\", \"nvh95\", \"coderfive\", \"Tom-Ren\", \"sseidl88\", \"Finance-781\", \"shikharvaish28\", \"EtienneBruines\", \"dipanjanS\", \"tvogels\", \"twotabbies\", \"allthroughthenight\", \"aathauck\", \"lukearmstrong\", \"Borye\", \"omrimendels\", \"bobrosoft\", \"louispotok\", \"synesthesiam\", \"mkeds\", \"Tirzono\", \"gvwilson\", \"ethen8181\", \"alexeygrigorev\", \"albertmolinermrf\", \"bluewoodtree\", \"engineeress\", \"hetii\", \"ss52\", \"qhfgva\", \"CookieDom\", \"justmarkham\", \"drskd\", \"triangeljs\", \"cmmalone\", \"jackkuipers\", \"bobiechen-twilio\", \"cezannec\", \"dear983604\", \"thedadams\", \"gsenseless\", \"ao-song\", \"bkm009\", \"tairiUdacity\", \"cgohlke\", \"jared-weed\", \"LiLiu93\", \"Bruce-Feldman\", \"rahmanhafeezul\", \"163-0533\", \"DamienIrving\", \"jdblischak\", \"jaycode\", \"alexey-grigorev-sm\", \"luvegood\", \"varan42\", \"eldaniz\", \"alexnich\", \"cpdj\", \"kreuvf\", \"Erotemic\", \"Vay-keen\", \"JJLWHarrison\", \"gyoisamurai\", \"adyates\", \"idelgado\", \"natowi\", \"kota7\", \"waterson\", \"zyc1gq\", \"amyrhoda\", \"Lincete\", \"gauravcharnalia\", \"toddrme2178\", \"sdsk\", \"dbarbier\", \"miksago\", \"lazyprogrammer\", \"ahnt\", \"ReadmeCritic\", \"xkcao\", \"fperez\", \"adityahiran\", \"mrtnbrst\", \"m-maksyutin\", \"carefree0910\", \"mkilavuz\", \"justramgerry\", \"mcleonard\", \"yonatanf\", \"fhemberger\", \"chrissoulierserv\", \"synapton\", \"LukeArn\", \"jeff1evesque\", \"mollygibson\", \"tuantp7\", \"ivigamberdiev\", \"roboticcam\", \"lexnederbragt\", \"eshizhan\", \"datamove\", \"orlitany\", \"jakubczakon\", \"wang1211\", \"XiaoshuiHuang\", \"gitbook-bot\", \"PGijsbers\", \"KaiNieRus\", \"samyag1\", \"cjratcliff\", \"wla80\", \"credentiality\", \"dmoisset\", \"JustFollowUs\", \"bkhaleghi\", \"abarto\", \"13o-bbr-bbq\", \"jeffcore\", \"wltrimbl\", \"tushargt\", \"Pooch11\", \"NathanEpstein\", \"jpallen\", \"steven7851\", \"mkuhn\", \"appleJax\", \"itsmeolivia\", \"haifengl\", \"tiendq\", \"Pomax\", \"anzellai\", \"calberti\", \"mirjalil\", \"Nebula83\", \"amar00k\", \"carlward\", \"Liam-Yang\", \"adpon\", \"GLevV\", \"sudoes\", \"scraggard\", \"vicramr\", \"ifesdjeen\", \"cmacdonell\", \"knathanieltucker\", \"willgroves\", \"cgcgcg\", \"gceboh\", \"PaulDebus\", \"cbuckey-uda\", \"aquinasCode\", \"mikhailsergeevi4\", \"serickso\", \"marsben\", \"testbounty\", \"andreww\", \"festline\", \"wojdyr\", \"egorpolusmak\", \"andrewd76\", \"dsych\", \"HemuManju\", \"ebenolson\", \"nmb10\", \"ExterminateWho\", \"danyaljj\", \"SarthakYadav\", \"rwdaigle\", \"creinders\", \"peter-parque\", \"Vincent-Vercruyssen\", \"njojic\", \"ecbc1\", \"4may\", \"AselaDarshan\", \"dnn37\", \"RedditSota\", \"afromanF\", \"deeper-learning\", \"chrisadami\", \"acupofdata\", \"josephmmisiti\", \"Devinsuit\", \"mahajani123\", \"rumi-naik\", \"gukoff\", \"aleju\", \"LiberiFatali\", \"aniag\", \"fangweili\", \"wqiancheng\", \"ipcenas\", \"thesimanjan\", \"tranek\", \"grp-bork\", \"sinanuozdemir\", \"vallentin\", \"tapaswenipathak\", \"mikej888\", \"Mostafa-Samir\", \"Digitalmobz\", \"lee709\", \"monomagentaeggroll\", \"Charismatron\", \"hfanahita\", \"bob7783\", \"elesueur\", \"cavestruz\", \"mckays630\", \"GordianStapf\", \"JustinJudd\", \"elkfrawy-df\", \"guedalia\", \"esztiorm\", \"ThatAndresV\", \"bvonboyen\", \"ini\", \"umpox\", \"mindw\", \"jalateras\", \"SumitBando\", \"jliddie\", \"peter-toth\", \"itailang\", \"mikelogsdon\", \"yjh\", \"ilbuono\", \"HapeMask\", \"ntache\", \"ivesn\", \"IMWP\", \"Sophia-11\", \"MarcelRobeer\", \"JayJayBinks\", \"zzincubus\", \"sebg\", \"YoungMStudio\", \"ser-serege\", \"Spandan-Madan\", \"AndrewLiesinger\", \"jaksmid\", \"ssusnic\", \"flytomylife\", \"testaccount553\", \"pennyliang\", \"bon\", \"mgschwan\", \"sguada\", \"jasonbhart\", \"APorterOReilly\", \"ritabentodosreis\", \"cswef\", \"Th30\", \"p1gd0g\", \"ShengKungYi\", \"LeeMaria007\", \"itkinai\", \"martijnvanbeers\", \"tgray\", \"sirius999999\"], \"xaxis\": \"x\", \"y\": [1419, 1141, 1032, 714, 646, 628, 545, 541, 522, 495, 467, 437, 424, 415, 402, 391, 390, 371, 367, 363, 351, 351, 349, 329, 316, 315, 301, 279, 275, 273, 269, 269, 269, 268, 267, 265, 265, 260, 258, 255, 251, 250, 248, 242, 234, 230, 224, 222, 220, 215, 214, 212, 200, 199, 191, 179, 173, 171, 170, 169, 165, 164, 164, 163, 162, 157, 155, 155, 153, 153, 152, 148, 146, 145, 144, 144, 143, 140, 138, 136, 133, 130, 124, 122, 122, 122, 120, 112, 111, 110, 110, 110, 108, 108, 106, 105, 105, 102, 101, 100, 99, 99, 99, 98, 98, 98, 98, 96, 95, 94, 94, 93, 93, 93, 93, 91, 90, 89, 88, 87, 86, 86, 85, 85, 85, 84, 83, 83, 82, 81, 80, 80, 80, 79, 79, 79, 78, 78, 77, 77, 76, 76, 76, 75, 74, 74, 74, 73, 73, 73, 72, 72, 70, 70, 70, 68, 68, 67, 67, 67, 67, 66, 66, 64, 64, 63, 62, 62, 62, 61, 61, 61, 61, 61, 61, 60, 60, 60, 60, 60, 59, 59, 58, 58, 57, 57, 57, 57, 57, 56, 55, 55, 54, 54, 53, 53, 53, 53, 53, 53, 53, 53, 53, 52, 52, 51, 51, 50, 50, 50, 50, 49, 49, 49, 48, 48, 48, 48, 48, 48, 47, 47, 47, 47, 47, 47, 47, 46, 46, 46, 46, 46, 45, 45, 45, 45, 45, 45, 44, 44, 44, 43, 43, 43, 43, 42, 42, 42, 42, 42, 41, 40, 39, 39, 39, 39, 39, 39, 39, 38, 38, 38, 38, 37, 37, 37, 37, 37, 36, 36, 36, 36, 36, 36, 35, 35, 35, 35, 35, 35, 35, 34, 34, 34, 34, 34, 34, 34, 34, 33, 33, 33, 33, 33, 33, 33, 32, 32, 32, 32, 32, 32, 32, 31, 31, 31, 31, 31, 30, 30, 30, 30, 30, 30, 30, 30, 29, 29, 29, 29, 29, 29, 29, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 24, 24, 24, 23, 23, 23, 23, 23, 23, 23, 23, 22, 22, 22, 22, 22, 22, 22, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 17, 17, 17, 17, 17, 17, 17, 17, 17, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 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, 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, 2, 2, 2, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], \"yaxis\": \"y\"}], {\"barmode\": \"relative\", \"legend\": {\"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"plot_bgcolor\": \"rgba(36, 83, 97, 0.06)\", \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"autotypenumbers\": \"strict\", \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"user_name\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"following\"}, \"type\": \"log\"}}, {\"responsive\": true} ).then(function(){\n",
" \n",
"var gd = document.getElementById('5a7390b1-742d-4be9-855e-b136b11fcb7b');\n",
"var x = new MutationObserver(function (mutations, observer) {{\n",
" var display = window.getComputedStyle(gd).display;\n",
" if (!display || display === 'none') {{\n",
" console.log([gd, 'removed!']);\n",
" Plotly.purge(gd);\n",
" observer.disconnect();\n",
" }}\n",
"}});\n",
"\n",
"// Listen for the removal of the full notebook cells\n",
"var notebookContainer = gd.closest('#notebook-container');\n",
"if (notebookContainer) {{\n",
" x.observe(notebookContainer, {childList: true});\n",
"}}\n",
"\n",
"// Listen for the clearing of the current output cell\n",
"var outputEl = gd.closest('.output');\n",
"if (outputEl) {{\n",
" x.observe(outputEl, {childList: true});\n",
"}}\n",
"\n",
" }) }; </script> </div>\n",
"</body>\n",
"</html>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"text/html": [
"<html>\n",
"<head><meta charset=\"utf-8\" /></head>\n",
"<body>\n",
" <div> <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script> <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
" <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script> <div id=\"a355aabb-aabc-4de2-bb0c-9c802d8e4d7c\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"a355aabb-aabc-4de2-bb0c-9c802d8e4d7c\")) { Plotly.newPlot( \"a355aabb-aabc-4de2-bb0c-9c802d8e4d7c\", [{\"alignmentgroup\": \"True\", \"hovertemplate\": \"user_name=%{x}<br>total_stars=%{y}<extra></extra>\", \"legendgroup\": \"\", \"marker\": {\"color\": \"#636efa\"}, \"name\": \"\", \"offsetgroup\": \"\", \"orientation\": \"v\", \"showlegend\": false, \"textposition\": \"auto\", \"type\": \"bar\", \"x\": [\"jwasham\", \"trekhleb\", \"llSourcell\", \"rasbt\", \"josephmisiti\", \"fengdu78\", \"aymericdamien\", \"k88hudson\", \"ZuzooVn\", \"SamyPesse\", \"amitshekhariitbhu\", \"chiphuyen\", \"afshinea\", \"ujjwalkarn\", \"Jack-Cherish\", \"benedekrozemberczki\", \"soulmachine\", \"aleju\", \"kailashahirwar\", \"ty4z2008\", \"oldratlee\", \"imathis\", \"firmai\", \"hangtwenty\", \"justmarkham\", \"jindongwang\", \"titu1994\", \"RedditSota\", \"ddbourgin\", \"polaris1119\", \"WillKoehrsen\", \"lettier\", \"navdeep-G\", \"rhiever\", \"Yorko\", \"wkentaro\", \"sjwhitworth\", \"wepe\", \"Pomax\", \"warmheartli\", \"guillaume-chevalier\", \"dformoso\", \"yuanxiaosc\", \"reiinakano\", \"nfmcclure\", \"timzhang642\", \"lazyprogrammer\", \"humphd\", \"Spandan-Madan\", \"haifengl\", \"meirwah\", \"susanli2016\", \"abhshkdz\", \"tirthajyoti\", \"layumi\", \"hslatman\", \"daviddao\", \"ljpzzz\", \"luispedro\", \"JustFollowUs\", \"roboticcam\", \"swanson\", \"Vay-keen\", \"bamos\", \"shaoanlu\", \"dipanjanS\", \"zotroneneis\", \"lawlite19\", \"schmich\", \"JWarmenhoven\", \"plusjade\", \"Lax\", \"umpox\", \"shuhuai007\", \"KaiyangZhou\", \"zlotus\", \"karthik\", \"Sophia-11\", \"tapaswenipathak\", \"NathanEpstein\", \"jphall663\", \"xxg1413\", \"RedstoneWill\", \"pbharrin\", \"TarrySingh\", \"alexeygrigorev\", \"mappum\", \"loveunk\", \"tdunning\", \"jiffyclub\", \"MaxHalford\", \"jaraco\", \"scopatz\", \"robertmartin8\", \"robmarkcole\", \"Metnew\", \"frnsys\", \"svaksha\", \"Gaohaoyang\", \"zhunzhong07\", \"ethen8181\", \"DeqianBai\", \"Tomotoes\", \"dubzzz\", \"krishnakumarsekar\", \"Naereen\", \"demidovakatya\", \"ssusnic\", \"stephenturner\", \"philips\", \"xiaqunfeng\", \"shaqian\", \"woliveiras\", \"13o-bbr-bbq\", \"kevinlin311tw\", \"iamaziz\", \"jeasonstudio\", \"katzien\", \"Tarrasch\", \"ranahanocka\", \"Jasonnor\", \"synesthesiam\", \"aaren\", \"Borye\", \"shervinea\", \"JJ\", \"Mostafa-Samir\", \"csuldw\", \"brandly\", \"parkr\", \"ezefranca\", \"dribnet\", \"sckott\", \"Nukesor\", \"rmarquis\", \"yulequan\", \"liancheng\", \"hamelsmu\", \"carefree0910\", \"treyhunner\", \"kadirpekel\", \"yaph\", \"ColCarroll\", \"abingham\", \"tdhopper\", \"zhigang1992\", \"wanzhenchn\", \"andrewda\", \"xuhdev\", \"wdm0006\", \"lefnire\", \"flipace\", \"ilivans\", \"geon\", \"sayakpaul\", \"Erotemic\", \"kwhinnery\", \"SeanPrashad\", \"imhuay\", \"ecederstrand\", \"unode\", \"rachpt\", \"penberg\", \"andresgottlieb\", \"jdblischak\", \"art-programmer\", \"myui\", \"kuixu\", \"ZYSzys\", \"masinoa\", \"juanpabloaj\", \"mcleonard\", \"gumblex\", \"yoavram\", \"atinesh-s\", \"rdingwall\", \"ifesdjeen\", \"inejc\", \"iiSeymour\", \"martinwicke\", \"msabramo\", \"rhnvrm\", \"gyoisamurai\", \"ProGamerGov\", \"maxim5\", \"csinva\", \"angeladai\", \"djoos\", \"baldassarreFe\", \"tranek\", \"timClicks\", \"Bachmann1234\", \"albahnsen\", \"pennyliang\", \"RaphaelMeudec\", \"jakemcc\", \"vict0rsch\", \"ptone\", \"terrytangyuan\", \"idf\", \"jankrepl\", \"egeriis\", \"gaborvecsei\", \"jessitron\", \"ricardoamaro\", \"stefanv\", \"cezannec\", \"optas\", \"gavinsimpson\", \"alphadl\", \"fperez\", \"nachocab\", \"EdwardSmith1884\", \"lazywei\", \"joaopedronardari\", \"byrichardpowell\", \"sun254\", \"e9t\", \"gvwilson\", \"knathanieltucker\", \"bigsnarfdude\", \"bboe\", \"lorensr\", \"mtchavez\", \"SiyuanQi\", \"philippbayer\", \"cratonica\", \"wilsonmar\", \"stedy\", \"fhs\", \"mysteriouspants\", \"mikl\", \"Philmod\", \"zonca\", \"kinow\", \"pilif\", \"dimpurr\", \"arnaldog12\", \"widdowquinn\", \"fish2000\", \"jeff1evesque\", \"Sea-n\", \"yoavz\", \"bertjiazheng\", \"KiranPanesar\", \"robtaussig\", \"Chandlercjy\", \"JohnMcLear\", \"btbytes\", \"rieder91\", \"DiegoCatalano\", \"abarto\", \"YichenGong\", \"cmhungsteve\", \"glemaitre\", \"krother\", \"twitwi\", \"natowi\", \"Borda\", \"rwdaigle\", \"mgschwan\", \"lxieyang\", \"wojdyr\", \"oneTaken\", \"ebenolson\", \"JerryKurata\", \"rtlee9\", \"jboy\", \"easezyc\", \"CrazyBunQnQ\", \"weakish\", \"iamBedant\", \"ketanhwr\", \"secretrobotron\", \"LarryBattle\", \"NeroCube\", \"fhemberger\", \"Diastro\", \"crouchred\", \"junlulocky\", \"volker48\", \"daeyun\", \"jgraving\", \"bgreenwell\", \"apeeyush\", \"magsol\", \"omo\", \"sdball\", \"gpailler\", \"wking\", \"herschel666\", \"floydpink\", \"ambientlight\", \"ooxi\", \"Xyclade\", \"jackmaney\", \"drio\", \"hsiaoyi0504\", \"Ir1d\", \"sergioburdisso\", \"vfdev-5\", \"cjauvin\", \"hanhdt\", \"GitHub30\", \"habi\", \"mogwai\", \"vallentin\", \"adamyala\", \"gisikw\", \"postBG\", \"hjlarry\", \"el10savio\", \"toaarnio\", \"cbarrick\", \"nipunsadvilkar\", \"rsbohn\", \"re4lfl0w\", \"tommyblue\", \"testrain\", \"orlitany\", \"eecn\", \"ArionMiles\", \"kyranb\", \"lexnederbragt\", \"BillMills\", \"dhingratul\", \"anujgupta82\", \"vivienzou1\", \"vmirly\", \"Amir-Arsalan\", \"polymeris\", \"leviding\", \"JamesLuoau\", \"MuminjonGuru\", \"clarle\", \"flyingpot\", \"keppel\", \"SylvainDe\", \"fmichonneau\", \"Keiku\", \"tgray\", \"matthewfeickert\", \"studiomohawk\", \"xlfe\", \"Sentimentron\", \"rodgzilla\", \"TehMillhouse\", \"yeonjuan\", \"arfon\", \"prajjwal1\", \"erjanmx\", \"axsaucedo\", \"andreww\", \"kno10\", \"ffmpbgrnn\", \"whatrocks\", \"mrry\", \"itailang\", \"sivanWu0222\", \"caub\", \"mjpieters\", \"harshnisar\", \"PatrickZH\", \"sinanuozdemir\", \"Finance-781\", \"joaorafaelm\", \"zlu\", \"jsmith\", \"keveman\", \"daveredrum\", \"njern\", \"ethanwhite\", \"jrbourbeau\", \"RockySJ\", \"init27\", \"ajmeese7\", \"vrv\", \"wzell\", \"BetaPundit\", \"dmcc\", \"sudeepraja\", \"kmscode\", \"yurrriq\", \"gaulinmp\", \"lacava\", \"xiuluo\", \"DakshMiglani\", \"mkuhn\", \"jocelynlih\", \"AdityaSoni19031997\", \"t-k-\", \"zldeng\", \"alg\", \"timmartin19\", \"justanhduc\", \"jpallen\", \"sebix\", \"vishwajeetv\", \"arteymix\", \"waterson\", \"code0100fun\", \"hex108\", \"synapticarbors\", \"tvogels\", \"lxj616\", \"adibis\", \"pradeep1288\", \"cgohlke\", \"digital-thinking\", \"yarikoptic\", \"havanagrawal\", \"cxxgtxy\", \"jcn\", \"jackeylu\", \"JustinJudd\", \"BirkhoffLee\", \"daz\", \"wogong\", \"iory\", \"lsvih\", \"hamiltont\", \"tncardoso\", \"dmoisset\", \"jayrav13\", \"LoveMeWithoutAll\", \"ZhengRui\", \"ajkl\", \"cjratcliff\", \"teopost\", \"arc12\", \"FlorisHoogenboom\", \"willingc\", \"vyper\", \"danyaljj\", \"kieranjol\", \"ebigelow\", \"rachtsingh\", \"mewben\", \"rozentill\", \"rajeshvaya\", \"bendoerr\", \"antmarakis\", \"sjml\", \"lstolcman\", \"run\", \"thouis\", \"pbanaszkiewicz\", \"RandomArray\", \"ghthor\", \"iglpdc\", \"lukearmstrong\", \"kwichmann\", \"chhh\", \"cdeil\", \"amitkgupta\", \"kgashok\", \"jaycode\", \"everping\", \"meawoppl\", \"davidrhodus\", \"fmder\", \"briansorahan\", \"Vincent-Vercruyssen\", \"Horaddrim\", \"acusti\", \"ss8651twtw\", \"mangei\", \"lukaszkaiser\", \"ss18\", \"WuZhuoran\", \"MadhumitaSushil\", \"kilsenp\", \"jimthompson5802\", \"graphaelli\", \"dtchepak\", \"alisezer\", \"RF-Nelson\", \"iamc\", \"maikelwever\", \"cmmalone\", \"planetceres\", \"rayeaster\", \"raghavbali\", \"DamienIrving\", \"girishkuniyal\", \"alicoding\", \"koriroys\", \"HapeMask\", \"nvh95\", \"TaurusOlson\", \"jcsims\", \"SegFaultAX\", \"beangoben\", \"SnailSword\", \"brainstorm\", \"andrewschreiber\", \"langner\", \"zahanm\", \"hmchuong\", \"olivertomic\", \"EtienneT\", \"arimbr\", \"melzareix\", \"gaodayue\", \"ocdtrekkie\", \"frozenkp\", \"andsor\", \"LukasKnuth\", \"schneiderfelipe\", \"benmccann\", \"avn3r\", \"varshapaidi\", \"NeerajSarwan\", \"gvn\", \"ebuildy\", \"MarcelRobeer\", \"alimon808\", \"naupaka\", \"alexsavio\", \"gdevenyi\", \"PGijsbers\", \"fleeting\", \"PrinzOwO\", \"adarsh0806\", \"zylix666\", \"dmnelson\", \"skvrahul\", \"kid1412z\", \"guillermo-navas-palencia\", \"QSCTech-Sange\", \"chi-hung\", \"emptyr1\", \"pjbull\", \"haraldschilly\", \"AdilZouitine\", \"umstek\", \"blokhin\", \"ammarasmro\", \"stonebig\", \"cako\", \"AmaanC\", \"frankhjwx\", \"npbool\", \"DanBeard\", \"kota7\", \"XiaoshuiHuang\", \"beckgael\", \"codedread\", \"nashjain\", \"selimnairb\", \"ahmadia\", \"ses4j\", \"pipitone\", \"vattay\", \"hwmrocker\", \"albertstill\", \"SwarShah\", \"filipefilardi\", \"acabunoc\", \"michaelaye\", \"maks-a\", \"wassimseif\", \"nolith\", \"Suraj520\", \"phocks\", \"asford\", \"jbencook\", \"jakirkham\", \"opie4624\", \"tiendq\", \"nitinagarwal\", \"piyushchauhan\", \"wltrimbl\", \"thezillion\", \"ericdill\", \"jeffcore\", \"Amir22010\", \"cloudyan\", \"enjoyhot\", \"moutai\", \"n-kats\", \"DanilBaibak\", \"adriancampos\", \"justpic\", \"tommyjiang\", \"tobyhodges\", \"ploth\", \"eccstartup\", \"NJannasch\", \"NotAnyMike\", \"wenruimeng\", \"Vijayabhaskar96\", \"cbuckey-uda\", \"dogHere\", \"ande765a\", \"rafaelsakurai\", \"ayakubovich\", \"eeeeeric\", \"Mchristos\", \"dmmulroy\", \"luntain\", \"ReekenX\", \"ackerleytng\", \"anzellai\", \"danielsan\", \"autodataming\", \"shahules786\", \"jongoodnow\", \"BioGeek\", \"liuluheng\", \"avinashsai\", \"KodeWorker\", \"PeterShershov\", \"athiwatc\", \"cailurus\", \"nschor\", \"JanLauGe\", \"okjake\", \"anuj1207\", \"patricksnape\", \"simensen\", \"curiousleo\", \"thecjharries\", \"itsliupeng\", \"songuke\", \"jalateras\", \"pmn4\", \"ccyanxyz\", \"denisarnaud\", \"jGaboardi\", \"fatihbaltaci\", \"shashankgroovy\", \"stromnov\", \"x1957\", \"dlebauer\", \"shikharvaish28\", \"tomhoover\", \"Alex1996a\", \"0asa\", \"strange-jiong\", \"bobrosoft\", \"snurkabill\", \"IamThilina\", \"sdierauf\", \"thedadams\", \"hyqskevin\", \"QuLogic\", \"yuanzhaoYZ\", \"qhfgva\", \"allardbrain\", \"vinodkkurmi\", \"DanielMorales9\", \"fanglinchen\", \"mingzhang96\", \"d4n1elchen\", \"Soypete\", \"cameroncan\", \"stnk20\", \"Mrzhangxiaohua\", \"EtienneBruines\", \"DrDavidS\", \"jpvg10\", \"juliangarcia\", \"srhrshr\", \"adam2392\", \"ahnt\", \"kastman\", \"mexeniz\", \"metrafonic\", \"HaveF\", \"aoping\", \"cmutel\", \"CorcovadoMing\", \"Microsheep\", \"Ja1r0\", \"ini\", \"mindw\", \"moonboots\", \"daanmichiels\", \"calberti\", \"idear1203\", \"jacksonlo\", \"jakubczakon\", \"ehrenfeu\", \"cjpurackal\", \"smbeli\", \"itzamna314\", \"cmacdonell\", \"SaumoPal97\", \"RingoTC\", \"curiousrohan\", \"RequireSun\", \"nbsantos\", \"adam-erickson\", \"ayushs136\", \"vahtras\", \"abought\", \"aaroncm\", \"lzcabrera\", \"sshekh\", \"douglatornell\", \"ericbuehl\", \"jldohmann\", \"czenzel\", \"srayuws\", \"wenyangfu\", \"joyoyoyoyoyo\", \"havk64\", \"advancedxy\", \"junxnone\", \"jhashanti\", \"Domon\", \"p-s-vishnu\", \"daddou-ma\", \"jogjayr\", \"espoirMur\", \"dylandrop\", \"aosama\", \"sudipbhandari126\", \"niltonslf\", \"Cugtyt\", \"ecolell\", \"LecJackS\", \"sebg\", \"chneau\", \"taylan\", \"ACharbonneau\", \"LiberiFatali\", \"datamove\", \"kylegrover\", \"Psimage\", \"libertatis\", \"brylie\", \"dbarbier\", \"luvegood\", \"AnshulBasia\", \"divik544\", \"agusnavce\", \"joybanerjee08\", \"dangsonbk\", \"jaymody\", \"RasPat1\", \"yakud\", \"aggronerd\", \"vad4msiu\", \"kjappelbaum\", \"kcrandall\", \"Alveona\", \"12wang3\", \"LiEmail\", \"triangeljs\", \"bryngo\", \"finnigantime\", \"zyc1gq\", \"bigwave\", \"nathanhillyer\", \"p1gd0g\", \"pan-long\", \"victorhcm\", \"CSerxy\", \"appleJax\", \"mandar2812\", \"acastrounis\", \"ao-song\", \"optixlab\", \"jwsy\", \"harshavamsi\", \"busterroni\", \"IgorKovr\", \"pkayfire\", \"TitouanT\", \"samedhaa\", \"mgoodfellow\", \"pfsq\", \"zh794390558\", \"rogerzanoni\", \"mckays630\", \"fchouteau\", \"sourcesoft\", \"pw\", \"festline\", \"PBarmby\", \"proinsias\", \"AlexZhou1995\", \"Tirzono\", \"danielbogomazov\", \"soumanpaul\", \"davidlowjw\", \"brigham\", \"SentinelWarren\", \"peterfabakker\", \"jselmani\", \"jasonbhart\", \"mgoldey\", \"Gabriel-Azevedo-Ferreira\", \"itkinai\", \"nektor211\", \"RickEyre\", \"Frenchhorn\", \"Airatiki\", \"TusharShandilya\", \"buddhikajay\", \"chess99\", \"lzamparo\", \"ismaeIfm\", \"hlkcrcck\", \"ilam\", \"aniag\", \"jacarrico\", \"JustroX\", \"jkuchta\", \"zdgriffith\", \"DH-Diego\", \"chkoar\", \"koomar\", \"databaaz\", \"BernhardKonrad\", \"amar00k\", \"kennethjmyers\", \"ulido\", \"daniel-kashin\", \"gukoff\", \"cavestruz\", \"cPolaris\", \"MdScntst\", \"koobs\", \"Pooch11\", \"IsakFalk\", \"sedge\", \"sguada\", \"tomahawk28\", \"Asterisk14\", \"mkotov13\", \"mybaseball52\", \"willgroves\", \"gcoter\", \"Karl-EdwardFPJeanMehu\", \"MUSSONT\", \"lupusomniator\", \"benedictflorance\", \"Div44\", \"eshizhan\", \"SumanthReddyKaliki\", \"saiabishek1\", \"lukelafountaine\", \"vilmacio22\", \"silverstone1903\", \"beroe\", \"cogmission\", \"UjjwalAryal\", \"SarthakYadav\", \"nahumj\", \"baogianghoangvu\", \"poyuwu\", \"pkuphy\", \"sstarr\", \"Budddy\", \"meghpatel\", \"pdkovacs\", \"hbaniecki\", \"irrationalRock\", \"bobiechen-twilio\", \"rahmanhafeezul\", \"jaksmid\", \"amyrhoda\", \"fndjjx\", \"shrutibhutaiya\", \"ktolstikhin\", \"giuliatondin\", \"Bachstelze\", \"Amjad-H-Ali\", \"KeniMorri\", \"anishthite\", \"adityahiran\", \"alexlokotochek\", \"AkshayVarik\", \"e173101\", \"mikelogsdon\", \"tychenjiajun\", \"HemuManju\", \"GageAmes\", \"sys0613\", \"Adrien-Jecker\", \"LizhangX\", \"thanhnguyentang\", \"KevinCooper\", \"sagardubey3\", \"samyag1\", \"LeeMaria007\", \"alishutc\", \"YoungMStudio\", \"dear983604\", \"adamwkraft\", \"jamesmyatt\", \"gliptak\", \"elfelround\", \"gceboh\", \"credentiality\", \"Zzlongjuanfeng\", \"mjschranz\", \"jeffin07\", \"mikhailsergeevi4\", \"timfrostmann\", \"praveenmylavarapu\", \"drlabratory\", \"mollygibson\", \"npanti\", \"Nebula83\", \"steven7851\", \"buddhiv\", \"wendingp\", \"tuanphuc\", \"yhx5768\", \"SubrataSarkar32\", \"AselaDarshan\", \"njojic\", \"sohamM97\", \"YINCHENLI\", \"stieglma\", \"mapx\", \"PaulDebus\", \"nmb10\", \"2y2simple\", \"xkcao\", \"ankitkul\", \"cpdj\", \"hugosoftdev\", \"mosew\", \"sirius999999\", \"mmBabol\", \"gideonthomas\", \"SumitBando\", \"oussou-dev\", \"sseidl88\", \"deeper-learning\", \"imaness\", \"GordianStapf\", \"doppenhe\", \"sagunji\", \"matheusgmaia\", \"hanpum\", \"allthroughthenight\", \"mkilavuz\", \"hungphandinh92it\", \"peter-toth\", \"dombrno\", \"4may\", \"thesimanjan\", \"swlsw\", \"creinders\", \"andrewd76\", \"tomraulet\", \"Pirikara\", \"igorrocha\", \"orionr\", \"individual8\", \"dnn37\", \"K-LV\", \"taoyudong\", \"louispotok\", \"wayneadams\", \"An3bi\", \"ipcenas\", \"nyoung85\", \"basickarl\", \"wenphan\", \"jlar0che\", \"azillion\", \"Minki-Kim95\", \"joaoavf\", \"varan42\", \"YJH1987\", \"Tom-Ren\", \"willalways\", \"kreuvf\", \"malfple\", \"borodenkov\", \"jsgv\", \"omytryniuk\", \"adyates\", \"idelgado\", \"zairah10\", \"drskd\", \"trpapp\", \"kbagchiGWC\", \"engineeress\", \"wtollett-usgs\", \"ptaiga\", \"AnkurDedania\", \"eldaniz\", \"BokaiLIAN\", \"matt-jay\", \"binilj04\", \"janismdhanbad\", \"ss52\", \"rajasekharponakala\", \"gsenseless\", \"seIncorp\", \"Hefeweizen\", \"liuliu5151\", \"elwinarens\", \"Petemir\", \"javierlorenzod\", \"MTietze\", \"Jurilz\", \"tairiUdacity\", \"lacanlale\", \"JsonAC\", \"coderfive\", \"jaywinhuang\", \"LiLiu93\", \"flytomylife\", \"KirillPanin\", \"jappre\", \"snowde\", \"voskresenskiy\", \"maximkeremet\", \"jiangf13\", \"mraje16\", \"wsbmxa198700\", \"rafalgrm\", \"selay01\", \"derrg\", \"ThePhantomCoder\", \"McKenzyPG\", \"JayJayBinks\", \"ilbuono\", \"ronnierios\", \"carlward\", \"muhammadyaseen\", \"jvanlangen\", \"alexobednikov\", \"Mintisma\", \"AndrewLiesinger\", \"justramgerry\", \"martijnvanbeers\", \"ser-serege\", \"Ouss4\", \"salehjg\", \"maxnk\", \"clappis\", \"apatsekin\", \"TuanNguyen27\", \"jgyllinsky\", \"kzhk75\", \"kacper1095\", \"yangyyt\", \"yjh\", \"K1t1k\", \"Liam-Yang\", \"itsmeolivia\", \"ivesn\", \"sailakshmi17\", \"grayskripko\", \"vicramr\", \"adpon\", \"AJDBenner\", \"mzk912778163\", \"YongshanKe\", \"esztiorm\", \"Owen-Mak\", \"pleabargain\", \"digitalduke\", \"bon\", \"qiagu\", \"slcott\", \"SoumyadeepJana\", \"agngrant\", \"juholehtonen\", \"hetii\", \"skervim\", \"ari-schaffel\", \"robot-c0der\", \"elesueur\", \"xcodeburpx\", \"twigz20\", \"frannievas\", \"alcidesv\", \"scraggard\", \"jovilius\", \"niklaskeerl\", \"bkm009\", \"kshs010239\", \"Fatehsandhu\", \"chrish42\", \"CorreyL\", \"codingcai\", \"Th30\", \"sagarcadet\", \"gauravcharnalia\", \"mzakariaCERN\", \"phillies\", \"Devinsuit\", \"shenyyi\", \"narisada014\", \"wqiancheng\", \"dsych\", \"qualityjacks\", \"moshejs\", \"TwFlem\", \"olveirap\", \"kersov\", \"JJLWHarrison\", \"firebreath1001\", \"peter-parque\", \"JasonGitHub\", \"kevinkyyro\", \"TocarIP\", \"cshan\", \"ecbc1\", \"mirjalil\", \"whughw\", \"nitin-tm\", \"Asmolovskij\", \"synapton\", \"Lincete\", \"toddrme2178\", \"harenbergsd\", \"liliuleo\", \"ReadmeCritic\", \"sdsk\", \"alexnich\", \"alexey-grigorev-sm\", \"m-maksyutin\", \"bkhaleghi\", \"wla80\", \"KaiNieRus\", \"gitbook-bot\", \"wang1211\", \"jmchen-g\", \"tuantp7\", \"chrissoulierserv\", \"TommyBark\", \"yonatanf\", \"tomassvensson\", \"163-0533\", \"imatiach-msft\", \"Bruce-Feldman\", \"CookieDom\", \"albertmolinermrf\", \"jared-weed\", \"mkeds\", \"fangweili\", \"guedalia\", \"ThatAndresV\", \"bvonboyen\", \"mikej888\", \"grp-bork\", \"awesome-bot\", \"rohduggal\", \"SeanPedersen\", \"lee709\", \"Charismatron\", \"testaccount553\", \"eddyzhd\", \"cswef\", \"zzincubus\", \"IMWP\", \"marsben\", \"GLevV\", \"sudoes\", \"cgcgcg\", \"aquinasCode\", \"serickso\", \"afromanF\", \"wrichert\", \"chrisadami\", \"josephmmisiti\", \"mahajani123\", \"acupofdata\", \"dnguneratne\", \"svntjng\", \"testbounty\", \"Zhi-lin\", \"qianguyizhe\", \"ExterminateWho\", \"egorpolusmak\", \"oleksii-trekhleb-epam\", \"rumi-naik\", \"SusieXu\", \"tushargt\", \"vargas\", \"ntache\", \"lisahdd007\", \"ShengKungYi\", \"ritabentodosreis\", \"APorterOReilly\", \"hfanahita\", \"monomagentaeggroll\", \"Digitalmobz\", \"bob7783\", \"jliddie\", \"elkfrawy-df\", \"Dr-Zhou\", \"twotabbies\", \"AlexanderKunkel\", \"jackkuipers\", \"bluewoodtree\", \"omrimendels\", \"aathauck\", \"Kacawi\", \"LukeArn\", \"windpls\", \"ivigamberdiev\", \"mrtnbrst\", \"miksago\"], \"xaxis\": \"x\", \"y\": [130077.0, 96749.0, 56737.0, 47849.0, 46355.0, 45302.0, 42975.0, 33995.0, 23898.0, 23371.0, 22593.0, 20039.0, 16750.0, 16146.0, 15132.0, 14711.0, 14607.0, 13632.0, 13392.0, 13274.0, 11177.0, 11023.0, 10784.0, 10399.0, 10176.0, 9633.0, 9565.0, 8974.0, 8813.0, 8476.0, 8327.0, 8172.0, 8074.0, 7862.0, 7777.0, 7762.0, 7398.0, 7120.0, 6732.0, 6482.0, 6064.0, 6008.0, 5915.0, 5873.0, 5668.0, 5411.0, 5369.0, 5340.0, 5209.0, 5169.0, 4902.0, 4679.0, 4636.0, 4463.0, 4420.0, 4405.0, 4405.0, 4274.0, 4256.0, 4230.0, 4161.0, 4152.0, 4149.0, 4147.0, 4041.0, 4010.0, 3942.0, 3878.0, 3766.0, 3590.0, 3581.0, 3489.0, 3428.0, 3372.0, 3131.0, 3075.0, 2837.0, 2780.0, 2751.0, 2618.0, 2564.0, 2521.0, 2421.0, 2401.0, 2394.0, 2349.0, 2325.0, 2309.0, 2289.0, 2276.0, 2217.0, 2079.0, 2047.0, 1937.0, 1848.0, 1848.0, 1841.0, 1818.0, 1796.0, 1742.0, 1712.0, 1696.0, 1621.0, 1611.0, 1607.0, 1607.0, 1604.0, 1505.0, 1504.0, 1475.0, 1446.0, 1429.0, 1419.0, 1386.0, 1370.0, 1248.0, 1239.0, 1178.0, 1163.0, 1155.0, 1151.0, 1111.0, 1101.0, 1084.0, 1080.0, 1048.0, 1015.0, 1001.0, 1000.0, 958.0, 954.0, 924.0, 904.0, 900.0, 894.0, 893.0, 876.0, 867.0, 862.0, 860.0, 852.0, 841.0, 836.0, 830.0, 826.0, 819.0, 805.0, 792.0, 782.0, 773.0, 771.0, 759.0, 757.0, 738.0, 735.0, 725.0, 725.0, 717.0, 709.0, 708.0, 703.0, 697.0, 696.0, 693.0, 681.0, 672.0, 665.0, 649.0, 643.0, 616.0, 604.0, 604.0, 596.0, 592.0, 585.0, 579.0, 576.0, 575.0, 570.0, 567.0, 565.0, 560.0, 558.0, 540.0, 523.0, 519.0, 509.0, 501.0, 498.0, 491.0, 489.0, 481.0, 477.0, 475.0, 448.0, 444.0, 442.0, 441.0, 433.0, 419.0, 403.0, 394.0, 388.0, 382.0, 374.0, 369.0, 368.0, 362.0, 361.0, 358.0, 357.0, 353.0, 352.0, 350.0, 348.0, 346.0, 337.0, 337.0, 334.0, 334.0, 328.0, 326.0, 322.0, 321.0, 320.0, 319.0, 319.0, 316.0, 314.0, 313.0, 312.0, 308.0, 306.0, 301.0, 300.0, 293.0, 292.0, 287.0, 286.0, 283.0, 283.0, 280.0, 271.0, 270.0, 269.0, 269.0, 268.0, 267.0, 266.0, 265.0, 262.0, 256.0, 254.0, 254.0, 251.0, 250.0, 244.0, 240.0, 235.0, 234.0, 234.0, 233.0, 230.0, 227.0, 226.0, 219.0, 217.0, 215.0, 213.0, 209.0, 205.0, 204.0, 202.0, 200.0, 196.0, 195.0, 194.0, 193.0, 192.0, 187.0, 186.0, 182.0, 182.0, 181.0, 180.0, 180.0, 178.0, 177.0, 175.0, 175.0, 173.0, 171.0, 168.0, 166.0, 165.0, 163.0, 162.0, 161.0, 161.0, 160.0, 155.0, 154.0, 153.0, 153.0, 149.0, 148.0, 146.0, 146.0, 145.0, 144.0, 144.0, 143.0, 142.0, 141.0, 138.0, 138.0, 137.0, 135.0, 132.0, 132.0, 131.0, 130.0, 130.0, 129.0, 128.0, 126.0, 126.0, 125.0, 124.0, 123.0, 123.0, 123.0, 123.0, 122.0, 120.0, 119.0, 117.0, 117.0, 115.0, 114.0, 113.0, 111.0, 109.0, 109.0, 108.0, 107.0, 107.0, 107.0, 105.0, 104.0, 104.0, 102.0, 101.0, 99.0, 98.0, 98.0, 98.0, 98.0, 95.0, 95.0, 95.0, 94.0, 94.0, 94.0, 92.0, 92.0, 91.0, 90.0, 89.0, 88.0, 87.0, 86.0, 86.0, 85.0, 84.0, 84.0, 83.0, 83.0, 80.0, 80.0, 80.0, 78.0, 76.0, 76.0, 76.0, 76.0, 75.0, 74.0, 74.0, 74.0, 73.0, 73.0, 73.0, 73.0, 72.0, 72.0, 71.0, 71.0, 70.0, 70.0, 70.0, 70.0, 69.0, 69.0, 69.0, 69.0, 68.0, 68.0, 68.0, 68.0, 67.0, 67.0, 67.0, 67.0, 66.0, 65.0, 65.0, 64.0, 64.0, 62.0, 62.0, 61.0, 61.0, 60.0, 60.0, 59.0, 58.0, 58.0, 58.0, 58.0, 57.0, 57.0, 57.0, 57.0, 56.0, 56.0, 56.0, 56.0, 56.0, 56.0, 55.0, 55.0, 54.0, 54.0, 53.0, 53.0, 53.0, 52.0, 52.0, 51.0, 51.0, 50.0, 50.0, 50.0, 50.0, 50.0, 49.0, 49.0, 49.0, 49.0, 47.0, 47.0, 46.0, 46.0, 46.0, 45.0, 45.0, 44.0, 44.0, 44.0, 44.0, 43.0, 43.0, 43.0, 42.0, 42.0, 42.0, 41.0, 41.0, 41.0, 40.0, 40.0, 40.0, 40.0, 39.0, 39.0, 39.0, 39.0, 38.0, 38.0, 38.0, 37.0, 37.0, 37.0, 37.0, 37.0, 37.0, 37.0, 36.0, 36.0, 36.0, 36.0, 35.0, 35.0, 35.0, 35.0, 35.0, 35.0, 34.0, 34.0, 34.0, 34.0, 34.0, 34.0, 33.0, 33.0, 33.0, 33.0, 32.0, 32.0, 32.0, 32.0, 32.0, 32.0, 32.0, 31.0, 31.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 29.0, 29.0, 29.0, 29.0, 29.0, 29.0, 29.0, 28.0, 28.0, 28.0, 28.0, 28.0, 28.0, 27.0, 27.0, 27.0, 27.0, 27.0, 27.0, 26.0, 26.0, 26.0, 26.0, 25.0, 24.0, 24.0, 24.0, 24.0, 24.0, 24.0, 24.0, 23.0, 22.0, 22.0, 22.0, 22.0, 22.0, 22.0, 21.0, 21.0, 20.0, 20.0, 20.0, 20.0, 20.0, 19.0, 19.0, 19.0, 19.0, 19.0, 19.0, 19.0, 19.0, 19.0, 19.0, 18.0, 18.0, 18.0, 18.0, 18.0, 18.0, 18.0, 18.0, 18.0, 18.0, 18.0, 18.0, 18.0, 17.0, 17.0, 17.0, 17.0, 17.0, 17.0, 17.0, 17.0, 17.0, 17.0, 17.0, 17.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 15.0, 15.0, 15.0, 15.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 13.0, 13.0, 13.0, 13.0, 13.0, 13.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 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, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 8.0, 8.0, 8.0, 8.0, 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, 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, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 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, 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, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], \"yaxis\": \"y\"}], {\"barmode\": \"relative\", \"legend\": {\"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"plot_bgcolor\": \"rgba(36, 83, 97, 0.06)\", \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"autotypenumbers\": \"strict\", \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"user_name\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"total_stars\"}, \"type\": \"log\"}}, {\"responsive\": true} ).then(function(){\n",
" \n",
"var gd = document.getElementById('a355aabb-aabc-4de2-bb0c-9c802d8e4d7c');\n",
"var x = new MutationObserver(function (mutations, observer) {{\n",
" var display = window.getComputedStyle(gd).display;\n",
" if (!display || display === 'none') {{\n",
" console.log([gd, 'removed!']);\n",
" Plotly.purge(gd);\n",
" observer.disconnect();\n",
" }}\n",
"}});\n",
"\n",
"// Listen for the removal of the full notebook cells\n",
"var notebookContainer = gd.closest('#notebook-container');\n",
"if (notebookContainer) {{\n",
" x.observe(notebookContainer, {childList: true});\n",
"}}\n",
"\n",
"// Listen for the clearing of the current output cell\n",
"var outputEl = gd.closest('.output');\n",
"if (outputEl) {{\n",
" x.observe(outputEl, {childList: true});\n",
"}}\n",
"\n",
" }) }; </script> </div>\n",
"</body>\n",
"</html>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"text/html": [
"<html>\n",
"<head><meta charset=\"utf-8\" /></head>\n",
"<body>\n",
" <div> <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script> <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
" <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script> <div id=\"20d1cd9d-3aa8-4e84-beae-214601582e8c\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"20d1cd9d-3aa8-4e84-beae-214601582e8c\")) { Plotly.newPlot( \"20d1cd9d-3aa8-4e84-beae-214601582e8c\", [{\"alignmentgroup\": \"True\", \"hovertemplate\": \"user_name=%{x}<br>max_star=%{y}<extra></extra>\", \"legendgroup\": \"\", \"marker\": {\"color\": \"#636efa\"}, \"name\": \"\", \"offsetgroup\": \"\", \"orientation\": \"v\", \"showlegend\": false, \"textposition\": \"auto\", \"type\": \"bar\", \"x\": [\"jwasham\", \"trekhleb\", \"josephmisiti\", \"aymericdamien\", \"k88hudson\", \"ZuzooVn\", \"SamyPesse\", \"fengdu78\", \"kailashahirwar\", \"ty4z2008\", \"rasbt\", \"Jack-Cherish\", \"afshinea\", \"ujjwalkarn\", \"hangtwenty\", \"chiphuyen\", \"imathis\", \"aleju\", \"RedditSota\", \"ddbourgin\", \"soulmachine\", \"amitshekhariitbhu\", \"llSourcell\", \"sjwhitworth\", \"Yorko\", \"polaris1119\", \"lettier\", \"nfmcclure\", \"jindongwang\", \"oldratlee\", \"timzhang642\", \"firmai\", \"lazyprogrammer\", \"wkentaro\", \"humphd\", \"haifengl\", \"rhiever\", \"warmheartli\", \"navdeep-G\", \"dformoso\", \"ljpzzz\", \"Vay-keen\", \"Spandan-Madan\", \"roboticcam\", \"wepe\", \"hslatman\", \"benedekrozemberczki\", \"meirwah\", \"yuanxiaosc\", \"plusjade\", \"shuhuai007\", \"Lax\", \"swanson\", \"WillKoehrsen\", \"zotroneneis\", \"lawlite19\", \"daviddao\", \"justmarkham\", \"shaoanlu\", \"JustFollowUs\", \"guillaume-chevalier\", \"abhshkdz\", \"susanli2016\", \"TarrySingh\", \"JWarmenhoven\", \"umpox\", \"schmich\", \"KaiyangZhou\", \"loveunk\", \"pbharrin\", \"layumi\", \"luispedro\", \"zlotus\", \"xxg1413\", \"RedstoneWill\", \"reiinakano\", \"tapaswenipathak\", \"scopatz\", \"titu1994\", \"alexeygrigorev\", \"jphall663\", \"Pomax\", \"ethen8181\", \"Gaohaoyang\", \"dipanjanS\", \"ssusnic\", \"krishnakumarsekar\", \"dubzzz\", \"Sophia-11\", \"xiaqunfeng\", \"13o-bbr-bbq\", \"tirthajyoti\", \"bamos\", \"jiffyclub\", \"demidovakatya\", \"DeqianBai\", \"karthik\", \"tdunning\", \"robertmartin8\", \"Naereen\", \"stephenturner\", \"Borye\", \"Tomotoes\", \"katzien\", \"Metnew\", \"svaksha\", \"jeasonstudio\", \"jaraco\", \"iamaziz\", \"ranahanocka\", \"carefree0910\", \"synesthesiam\", \"rmarquis\", \"woliveiras\", \"ilivans\", \"aaren\", \"SeanPrashad\", \"ecederstrand\", \"robmarkcole\", \"csuldw\", \"wanzhenchn\", \"andresgottlieb\", \"MaxHalford\", \"lefnire\", \"shervinea\", \"imhuay\", \"unode\", \"masinoa\", \"Mostafa-Samir\", \"Nukesor\", \"mappum\", \"xuhdev\", \"atinesh-s\", \"flipace\", \"gyoisamurai\", \"Erotemic\", \"NathanEpstein\", \"kevinlin311tw\", \"brandly\", \"myui\", \"philips\", \"rachpt\", \"Tarrasch\", \"zhunzhong07\", \"jdblischak\", \"pennyliang\", \"shaqian\", \"ZYSzys\", \"kadirpekel\", \"RaphaelMeudec\", \"vict0rsch\", \"hamelsmu\", \"andrewda\", \"liancheng\", \"rdingwall\", \"dribnet\", \"tdhopper\", \"abingham\", \"tranek\", \"frnsys\", \"djoos\", \"timClicks\", \"yulequan\", \"baldassarreFe\", \"martinwicke\", \"geon\", \"sayakpaul\", \"jakemcc\", \"optas\", \"Jasonnor\", \"yoavram\", \"Bachmann1234\", \"sun254\", \"kuixu\", \"idf\", \"iiSeymour\", \"art-programmer\", \"treyhunner\", \"inejc\", \"stedy\", \"csinva\", \"zhigang1992\", \"e9t\", \"cezannec\", \"joaopedronardari\", \"mcleonard\", \"alphadl\", \"ColCarroll\", \"nachocab\", \"DiegoCatalano\", \"cratonica\", \"philippbayer\", \"mysteriouspants\", \"Chandlercjy\", \"YichenGong\", \"jeff1evesque\", \"egeriis\", \"maxim5\", \"rieder91\", \"robtaussig\", \"jankrepl\", \"JerryKurata\", \"sckott\", \"JJ\", \"jboy\", \"SiyuanQi\", \"KiranPanesar\", \"penberg\", \"wdm0006\", \"crouchred\", \"yoavz\", \"ptone\", \"angeladai\", \"ProGamerGov\", \"ifesdjeen\", \"pilif\", \"yaph\", \"oneTaken\", \"ezefranca\", \"cmhungsteve\", \"rhnvrm\", \"easezyc\", \"juanpabloaj\", \"Borda\", \"byrichardpowell\", \"Xyclade\", \"terrytangyuan\", \"jgraving\", \"wojdyr\", \"albahnsen\", \"EdwardSmith1884\", \"arnaldog12\", \"ebenolson\", \"parkr\", \"hsiaoyi0504\", \"kwhinnery\", \"weakish\", \"mogwai\", \"gumblex\", \"bertjiazheng\", \"nipunsadvilkar\", \"hanhdt\", \"GitHub30\", \"msabramo\", \"gpailler\", \"sergioburdisso\", \"adamyala\", \"postBG\", \"eecn\", \"natowi\", \"apeeyush\", \"volker48\", \"mgschwan\", \"Amir-Arsalan\", \"lorensr\", \"stefanv\", \"vivienzou1\", \"gvwilson\", \"rtlee9\", \"ricardoamaro\", \"flyingpot\", \"Keiku\", \"toaarnio\", \"habi\", \"LarryBattle\", \"gaborvecsei\", \"Diastro\", \"lazywei\", \"rsbohn\", \"fperez\", \"jessitron\", \"twitwi\", \"CrazyBunQnQ\", \"cbarrick\", \"kyranb\", \"glemaitre\", \"fhs\", \"widdowquinn\", \"itailang\", \"zonca\", \"dhingratul\", \"TehMillhouse\", \"bboe\", \"Finance-781\", \"mtchavez\", \"Sentimentron\", \"dimpurr\", \"SylvainDe\", \"ooxi\", \"lxieyang\", \"knathanieltucker\", \"Sea-n\", \"re4lfl0w\", \"RockySJ\", \"mikl\", \"gavinsimpson\", \"leviding\", \"keveman\", \"wilsonmar\", \"gisikw\", \"ketanhwr\", \"NeroCube\", \"kmscode\", \"Philmod\", \"fish2000\", \"bigsnarfdude\", \"jackmaney\", \"harshnisar\", \"jocelynlih\", \"AdityaSoni19031997\", \"secretrobotron\", \"el10savio\", \"bgreenwell\", \"mrry\", \"sivanWu0222\", \"xiuluo\", \"orlitany\", \"floydpink\", \"kinow\", \"JamesLuoau\", \"vmirly\", \"vrv\", \"njern\", \"testrain\", \"ArionMiles\", \"wking\", \"clarle\", \"BetaPundit\", \"yeonjuan\", \"btbytes\", \"sebix\", \"timmartin19\", \"arfon\", \"magsol\", \"drio\", \"jsmith\", \"jcn\", \"dmcc\", \"whatrocks\", \"polymeris\", \"wogong\", \"daeyun\", \"jackeylu\", \"anujgupta82\", \"abarto\", \"ebigelow\", \"hjlarry\", \"iamBedant\", \"junlulocky\", \"tncardoso\", \"sudeepraja\", \"cjauvin\", \"init27\", \"erjanmx\", \"Ir1d\", \"t-k-\", \"rwdaigle\", \"ajmeese7\", \"mkuhn\", \"fmichonneau\", \"BillMills\", \"run\", \"vallentin\", \"andreww\", \"ethanwhite\", \"lukaszkaiser\", \"rodgzilla\", \"gaulinmp\", \"davidrhodus\", \"MadhumitaSushil\", \"krother\", \"digital-thinking\", \"mewben\", \"sdball\", \"keppel\", \"xlfe\", \"prajjwal1\", \"waterson\", \"kno10\", \"daveredrum\", \"studiomohawk\", \"wzell\", \"tvogels\", \"herschel666\", \"alisezer\", \"kieranjol\", \"lacava\", \"fmder\", \"ss18\", \"vfdev-5\", \"JustinJudd\", \"daz\", \"iamc\", \"rayeaster\", \"mangei\", \"arc12\", \"matthewfeickert\", \"fhemberger\", \"HapeMask\", \"omo\", \"PatrickZH\", \"zldeng\", \"EtienneT\", \"vishwajeetv\", \"lexnederbragt\", \"cxxgtxy\", \"tommyblue\", \"Vincent-Vercruyssen\", \"jcsims\", \"adibis\", \"tgray\", \"jrbourbeau\", \"varshapaidi\", \"RandomArray\", \"pradeep1288\", \"SnailSword\", \"hex108\", \"avn3r\", \"nvh95\", \"kilsenp\", \"olivertomic\", \"FlorisHoogenboom\", \"bendoerr\", \"justanhduc\", \"MuminjonGuru\", \"RF-Nelson\", \"acusti\", \"iory\", \"ambientlight\", \"ajkl\", \"kid1412z\", \"antmarakis\", \"WuZhuoran\", \"chi-hung\", \"NeerajSarwan\", \"havanagrawal\", \"alimon808\", \"codedread\", \"stonebig\", \"caub\", \"DamienIrving\", \"PrinzOwO\", \"PGijsbers\", \"LoveMeWithoutAll\", \"code0100fun\", \"amitkgupta\", \"teopost\", \"MarcelRobeer\", \"guillermo-navas-palencia\", \"ffmpbgrnn\", \"dmoisset\", \"raghavbali\", \"rajeshvaya\", \"chhh\", \"iglpdc\", \"XiaoshuiHuang\", \"lxj616\", \"hmchuong\", \"beckgael\", \"joaorafaelm\", \"cgohlke\", \"jpallen\", \"JohnMcLear\", \"vyper\", \"mjpieters\", \"npbool\", \"pbanaszkiewicz\", \"graphaelli\", \"zlu\", \"ZhengRui\", \"maks-a\", \"hamiltont\", \"Suraj520\", \"sinanuozdemir\", \"SwarShah\", \"frankhjwx\", \"everping\", \"pipitone\", \"kgashok\", \"albertstill\", \"gaodayue\", \"planetceres\", \"zylix666\", \"blokhin\", \"rachtsingh\", \"briansorahan\", \"kwichmann\", \"pjbull\", \"dmnelson\", \"dtchepak\", \"cjratcliff\", \"koriroys\", \"sjml\", \"Vijayabhaskar96\", \"arteymix\", \"wenruimeng\", \"danyaljj\", \"cbuckey-uda\", \"synapticarbors\", \"ss8651twtw\", \"alexsavio\", \"lstolcman\", \"meawoppl\", \"benmccann\", \"DanBeard\", \"arimbr\", \"ploth\", \"LukasKnuth\", \"nschor\", \"yurrriq\", \"rozentill\", \"girishkuniyal\", \"jeffcore\", \"DakshMiglani\", \"maikelwever\", \"axsaucedo\", \"Amir22010\", \"eccstartup\", \"Horaddrim\", \"alicoding\", \"lukearmstrong\", \"ghthor\", \"NJannasch\", \"cmmalone\", \"songuke\", \"alg\", \"QSCTech-Sange\", \"ocdtrekkie\", \"AdilZouitine\", \"dmmulroy\", \"gvn\", \"asford\", \"selimnairb\", \"cdeil\", \"dogHere\", \"langner\", \"gdevenyi\", \"ande765a\", \"lsvih\", \"kota7\", \"ayakubovich\", \"Mchristos\", \"ericdill\", \"wltrimbl\", \"patricksnape\", \"hyqskevin\", \"tiendq\", \"willingc\", \"ses4j\", \"cloudyan\", \"IamThilina\", \"qhfgva\", \"beangoben\", \"schneiderfelipe\", \"tommyjiang\", \"enjoyhot\", \"jayrav13\", \"ahmadia\", \"jimthompson5802\", \"x1957\", \"filipefilardi\", \"SegFaultAX\", \"nitinagarwal\", \"tobyhodges\", \"moutai\", \"PeterShershov\", \"opie4624\", \"QuLogic\", \"danielsan\", \"andsor\", \"michaelaye\", \"andrewschreiber\", \"thouis\", \"KodeWorker\", \"calberti\", \"Mrzhangxiaohua\", \"piyushchauhan\", \"NotAnyMike\", \"stromnov\", \"n-kats\", \"thedadams\", \"0asa\", \"fleeting\", \"cameroncan\", \"yarikoptic\", \"jaycode\", \"liuluheng\", \"ackerleytng\", \"yuanzhaoYZ\", \"DrDavidS\", \"eeeeeric\", \"adarsh0806\", \"skvrahul\", \"bobrosoft\", \"ericbuehl\", \"frozenkp\", \"luntain\", \"melzareix\", \"ccyanxyz\", \"Ja1r0\", \"BioGeek\", \"advancedxy\", \"dlebauer\", \"DanilBaibak\", \"jGaboardi\", \"vinodkkurmi\", \"adriancampos\", \"anuj1207\", \"BirkhoffLee\", \"AmaanC\", \"cako\", \"fatihbaltaci\", \"emptyr1\", \"strange-jiong\", \"jongoodnow\", \"curiousrohan\", \"smbeli\", \"RingoTC\", \"haraldschilly\", \"jhashanti\", \"naupaka\", \"wassimseif\", \"vattay\", \"cmacdonell\", \"mexeniz\", \"denisarnaud\", \"pmn4\", \"aoping\", \"simensen\", \"aosama\", \"cjpurackal\", \"moonboots\", \"nolith\", \"umstek\", \"brainstorm\", \"sudipbhandari126\", \"ReekenX\", \"libertatis\", \"Alex1996a\", \"jpvg10\", \"idear1203\", \"jldohmann\", \"thecjharries\", \"anzellai\", \"Soypete\", \"jakirkham\", \"cmutel\", \"CorcovadoMing\", \"okjake\", \"LecJackS\", \"itzamna314\", \"nashjain\", \"acabunoc\", \"jalateras\", \"ACharbonneau\", \"LiberiFatali\", \"ebuildy\", \"sdierauf\", \"srhrshr\", \"ehrenfeu\", \"SaumoPal97\", \"stnk20\", \"snurkabill\", \"justpic\", \"srayuws\", \"hwmrocker\", \"allardbrain\", \"kylegrover\", \"yakud\", \"adam-erickson\", \"vahtras\", \"cailurus\", \"EtienneBruines\", \"d4n1elchen\", \"ini\", \"ammarasmro\", \"shikharvaish28\", \"aaroncm\", \"autodataming\", \"Cugtyt\", \"phocks\", \"CSerxy\", \"jbencook\", \"ao-song\", \"jakubczakon\", \"LiEmail\", \"shashankgroovy\", \"luvegood\", \"davidlowjw\", \"mandar2812\", \"itsliupeng\", \"busterroni\", \"12wang3\", \"optixlab\", \"festline\", \"zyc1gq\", \"sshekh\", \"zahanm\", \"fanglinchen\", \"jasonbhart\", \"thezillion\", \"joybanerjee08\", \"adam2392\", \"nbsantos\", \"JanLauGe\", \"metrafonic\", \"Psimage\", \"Microsheep\", \"zh794390558\", \"kcrandall\", \"abought\", \"mindw\", \"rogerzanoni\", \"peterfabakker\", \"daanmichiels\", \"junxnone\", \"ahnt\", \"jogjayr\", \"mingzhang96\", \"jwsy\", \"wenyangfu\", \"shahules786\", \"vad4msiu\", \"triangeljs\", \"aniag\", \"gukoff\", \"Tirzono\", \"zdgriffith\", \"pw\", \"HaveF\", \"p1gd0g\", \"athiwatc\", \"douglatornell\", \"AnshulBasia\", \"juliangarcia\", \"curiousleo\", \"nathanhillyer\", \"daddou-ma\", \"kjappelbaum\", \"datamove\", \"acastrounis\", \"divik544\", \"TitouanT\", \"sourcesoft\", \"havk64\", \"kennethjmyers\", \"dbarbier\", \"niltonslf\", \"TaurusOlson\", \"victorhcm\", \"czenzel\", \"sebg\", \"rafaelsakurai\", \"appleJax\", \"ecolell\", \"tomhoover\", \"agusnavce\", \"RasPat1\", \"Gabriel-Azevedo-Ferreira\", \"itkinai\", \"Airatiki\", \"DanielMorales9\", \"AlexZhou1995\", \"brigham\", \"Alveona\", \"avinashsai\", \"sedge\", \"SarthakYadav\", \"mybaseball52\", \"cPolaris\", \"baogianghoangvu\", \"saiabishek1\", \"espoirMur\", \"brylie\", \"danielbogomazov\", \"tomahawk28\", \"JustroX\", \"koomar\", \"RequireSun\", \"eshizhan\", \"Pooch11\", \"jselmani\", \"sstarr\", \"kastman\", \"databaaz\", \"lupusomniator\", \"pkuphy\", \"ayushs136\", \"pfsq\", \"amar00k\", \"SentinelWarren\", \"buddhikajay\", \"nektor211\", \"hlkcrcck\", \"joyoyoyoyoyo\", \"willgroves\", \"jacksonlo\", \"UjjwalAryal\", \"dangsonbk\", \"Karl-EdwardFPJeanMehu\", \"mgoodfellow\", \"fchouteau\", \"p-s-vishnu\", \"DH-Diego\", \"nahumj\", \"dylandrop\", \"aggronerd\", \"bigwave\", \"koobs\", \"bryngo\", \"ilam\", \"finnigantime\", \"IgorKovr\", \"chneau\", \"Div44\", \"Domon\", \"harshavamsi\", \"taylan\", \"ulido\", \"proinsias\", \"PBarmby\", \"lzamparo\", \"HemuManju\", \"e173101\", \"sys0613\", \"mckays630\", \"wendingp\", \"alexlokotochek\", \"mgoldey\", \"samyag1\", \"pan-long\", \"PaulDebus\", \"Adrien-Jecker\", \"LizhangX\", \"pdkovacs\", \"jaymody\", \"anishthite\", \"KevinCooper\", \"gceboh\", \"AkshayVarik\", \"jkuchta\", \"credentiality\", \"Bachstelze\", \"RickEyre\", \"Frenchhorn\", \"cavestruz\", \"mikelogsdon\", \"YoungMStudio\", \"jamesmyatt\", \"sguada\", \"bobiechen-twilio\", \"sagardubey3\", \"silverstone1903\", \"adamwkraft\", \"irrationalRock\", \"jaksmid\", \"meghpatel\", \"SubrataSarkar32\", \"LeeMaria007\", \"MUSSONT\", \"pkayfire\", \"tychenjiajun\", \"MdScntst\", \"dear983604\", \"drlabratory\", \"Budddy\", \"mkotov13\", \"mollygibson\", \"benedictflorance\", \"rahmanhafeezul\", \"alishutc\", \"gliptak\", \"chess99\", \"daniel-kashin\", \"samedhaa\", \"tuanphuc\", \"elfelround\", \"yhx5768\", \"Amjad-H-Ali\", \"AselaDarshan\", \"YINCHENLI\", \"shrutibhutaiya\", \"amyrhoda\", \"njojic\", \"soumanpaul\", \"ktolstikhin\", \"hbaniecki\", \"jeffin07\", \"GageAmes\", \"beroe\", \"KeniMorri\", \"vilmacio22\", \"TusharShandilya\", \"2y2simple\", \"BernhardKonrad\", \"nmb10\", \"lukelafountaine\", \"giuliatondin\", \"gcoter\", \"IsakFalk\", \"poyuwu\", \"Asterisk14\", \"fndjjx\", \"chkoar\", \"lzcabrera\", \"Nebula83\", \"stieglma\", \"praveenmylavarapu\", \"Zzlongjuanfeng\", \"sohamM97\", \"jacarrico\", \"steven7851\", \"cogmission\", \"mapx\", \"npanti\", \"mikhailsergeevi4\", \"SumanthReddyKaliki\", \"mjschranz\", \"timfrostmann\", \"buddhiv\", \"thanhnguyentang\", \"adityahiran\", \"ismaeIfm\", \"ipcenas\", \"orionr\", \"cpdj\", \"flytomylife\", \"frannievas\", \"elesueur\", \"esztiorm\", \"zairah10\", \"mmBabol\", \"ronnierios\", \"peter-toth\", \"AnkurDedania\", \"hetii\", \"juholehtonen\", \"bkm009\", \"SumitBando\", \"MTietze\", \"Th30\", \"niklaskeerl\", \"slcott\", \"idelgado\", \"taoyudong\", \"Petemir\", \"louispotok\", \"kersov\", \"basickarl\", \"javierlorenzod\", \"Fatehsandhu\", \"digitalduke\", \"seIncorp\", \"willalways\", \"mzk912778163\", \"hugosoftdev\", \"olveirap\", \"justramgerry\", \"bon\", \"skervim\", \"agngrant\", \"wenphan\", \"thesimanjan\", \"K-LV\", \"wqiancheng\", \"allthroughthenight\", \"adyates\", \"omytryniuk\", \"borodenkov\", \"azillion\", \"LiLiu93\", \"Hefeweizen\", \"dombrno\", \"kreuvf\", \"GordianStapf\", \"tomraulet\", \"varan42\", \"joaoavf\", \"wayneadams\", \"wsbmxa198700\", \"jsgv\", \"K1t1k\", \"elwinarens\", \"kbagchiGWC\", \"engineeress\", \"kshs010239\", \"mkilavuz\", \"narisada014\", \"grayskripko\", \"An3bi\", \"mosew\", \"ankitkul\", \"matt-jay\", \"Pirikara\", \"creinders\", \"jovilius\", \"salehjg\", \"sailakshmi17\", \"sirius999999\", \"SoumyadeepJana\", \"Ouss4\", \"dsych\", \"JasonGitHub\", \"xkcao\", \"KirillPanin\", \"peter-parque\", \"imaness\", \"firebreath1001\", \"itsmeolivia\", \"matheusgmaia\", \"muhammadyaseen\", \"carlward\", \"Jurilz\", \"ThePhantomCoder\", \"CorreyL\", \"coderfive\", \"chrish42\", \"YongshanKe\", \"gideonthomas\", \"selay01\", \"BokaiLIAN\", \"maximkeremet\", \"hanpum\", \"deeper-learning\", \"gauravcharnalia\", \"sseidl88\", \"shenyyi\", \"dnn37\", \"4may\", \"ss52\", \"alcidesv\", \"jlar0che\", \"andrewd76\", \"qiagu\", \"rajasekharponakala\", \"liuliu5151\", \"pleabargain\", \"trpapp\", \"kevinkyyro\", \"ari-schaffel\", \"TwFlem\", \"sagunji\", \"Tom-Ren\", \"robot-c0der\", \"wtollett-usgs\", \"drskd\", \"rafalgrm\", \"TuanNguyen27\", \"mraje16\", \"yjh\", \"AndrewLiesinger\", \"binilj04\", \"jappre\", \"doppenhe\", \"voskresenskiy\", \"igorrocha\", \"McKenzyPG\", \"oussou-dev\", \"JsonAC\", \"qualityjacks\", \"JJLWHarrison\", \"jvanlangen\", \"alexobednikov\", \"hungphandinh92it\", \"JayJayBinks\", \"Owen-Mak\", \"codingcai\", \"ilbuono\", \"sagarcadet\", \"mzakariaCERN\", \"swlsw\", \"xcodeburpx\", \"Mintisma\", \"lacanlale\", \"moshejs\", \"nyoung85\", \"martijnvanbeers\", \"janismdhanbad\", \"AJDBenner\", \"scraggard\", \"jiangf13\", \"snowde\", \"malfple\", \"phillies\", \"derrg\", \"YJH1987\", \"Devinsuit\", \"maxnk\", \"kacper1095\", \"kzhk75\", \"clappis\", \"tairiUdacity\", \"jaywinhuang\", \"adpon\", \"yangyyt\", \"Minki-Kim95\", \"Liam-Yang\", \"apatsekin\", \"jgyllinsky\", \"eldaniz\", \"ptaiga\", \"ser-serege\", \"gsenseless\", \"individual8\", \"ivesn\", \"vicramr\", \"twigz20\", \"TocarIP\", \"cshan\", \"ecbc1\", \"mirjalil\", \"whughw\", \"nitin-tm\", \"Asmolovskij\", \"synapton\", \"Lincete\", \"toddrme2178\", \"harenbergsd\", \"liliuleo\", \"ReadmeCritic\", \"sdsk\", \"alexnich\", \"alexey-grigorev-sm\", \"m-maksyutin\", \"bkhaleghi\", \"wla80\", \"KaiNieRus\", \"gitbook-bot\", \"wang1211\", \"jmchen-g\", \"tuantp7\", \"chrissoulierserv\", \"TommyBark\", \"yonatanf\", \"tomassvensson\", \"163-0533\", \"imatiach-msft\", \"Bruce-Feldman\", \"CookieDom\", \"albertmolinermrf\", \"jared-weed\", \"mkeds\", \"fangweili\", \"guedalia\", \"ThatAndresV\", \"bvonboyen\", \"mikej888\", \"grp-bork\", \"awesome-bot\", \"rohduggal\", \"SeanPedersen\", \"lee709\", \"Charismatron\", \"testaccount553\", \"eddyzhd\", \"cswef\", \"zzincubus\", \"IMWP\", \"marsben\", \"GLevV\", \"sudoes\", \"cgcgcg\", \"aquinasCode\", \"serickso\", \"afromanF\", \"wrichert\", \"chrisadami\", \"josephmmisiti\", \"mahajani123\", \"acupofdata\", \"dnguneratne\", \"svntjng\", \"testbounty\", \"Zhi-lin\", \"qianguyizhe\", \"ExterminateWho\", \"egorpolusmak\", \"oleksii-trekhleb-epam\", \"rumi-naik\", \"SusieXu\", \"tushargt\", \"vargas\", \"ntache\", \"lisahdd007\", \"ShengKungYi\", \"ritabentodosreis\", \"APorterOReilly\", \"hfanahita\", \"monomagentaeggroll\", \"Digitalmobz\", \"bob7783\", \"jliddie\", \"elkfrawy-df\", \"Dr-Zhou\", \"twotabbies\", \"AlexanderKunkel\", \"jackkuipers\", \"bluewoodtree\", \"omrimendels\", \"aathauck\", \"Kacawi\", \"LukeArn\", \"windpls\", \"ivigamberdiev\", \"mrtnbrst\", \"miksago\"], \"xaxis\": \"x\", \"y\": [123514.0, 74060.0, 45243.0, 38070.0, 33777.0, 23893.0, 18842.0, 17632.0, 13367.0, 13268.0, 12707.0, 10865.0, 10618.0, 10402.0, 10014.0, 9595.0, 9451.0, 9436.0, 8974.0, 8782.0, 8540.0, 7324.0, 7315.0, 7249.0, 6993.0, 6889.0, 6496.0, 5607.0, 5492.0, 5353.0, 5319.0, 5229.0, 5193.0, 4975.0, 4852.0, 4809.0, 4728.0, 4645.0, 4529.0, 4465.0, 4274.0, 4097.0, 4044.0, 3966.0, 3811.0, 3652.0, 3605.0, 3482.0, 3394.0, 3367.0, 3358.0, 3234.0, 3171.0, 3170.0, 3139.0, 3085.0, 3075.0, 2909.0, 2760.0, 2755.0, 2611.0, 2586.0, 2435.0, 2373.0, 2360.0, 2285.0, 2222.0, 2191.0, 2108.0, 2104.0, 2100.0, 2092.0, 2045.0, 2020.0, 1921.0, 1887.0, 1828.0, 1750.0, 1728.0, 1726.0, 1723.0, 1638.0, 1624.0, 1607.0, 1533.0, 1488.0, 1442.0, 1434.0, 1401.0, 1349.0, 1341.0, 1337.0, 1257.0, 1257.0, 1228.0, 1220.0, 1217.0, 1209.0, 1141.0, 1131.0, 1112.0, 1077.0, 1052.0, 1041.0, 963.0, 961.0, 919.0, 911.0, 853.0, 852.0, 841.0, 836.0, 823.0, 760.0, 713.0, 711.0, 705.0, 701.0, 701.0, 694.0, 688.0, 682.0, 680.0, 679.0, 640.0, 638.0, 638.0, 593.0, 589.0, 587.0, 578.0, 576.0, 575.0, 567.0, 558.0, 526.0, 526.0, 514.0, 510.0, 509.0, 493.0, 488.0, 483.0, 471.0, 465.0, 460.0, 453.0, 449.0, 447.0, 429.0, 420.0, 414.0, 396.0, 388.0, 387.0, 384.0, 381.0, 376.0, 369.0, 361.0, 359.0, 357.0, 356.0, 351.0, 343.0, 337.0, 333.0, 332.0, 328.0, 323.0, 317.0, 317.0, 316.0, 315.0, 314.0, 309.0, 303.0, 302.0, 299.0, 297.0, 279.0, 271.0, 270.0, 268.0, 266.0, 265.0, 263.0, 260.0, 259.0, 252.0, 248.0, 248.0, 247.0, 242.0, 230.0, 230.0, 228.0, 227.0, 225.0, 225.0, 214.0, 207.0, 205.0, 204.0, 201.0, 200.0, 199.0, 195.0, 195.0, 192.0, 190.0, 189.0, 188.0, 185.0, 184.0, 182.0, 176.0, 176.0, 176.0, 175.0, 173.0, 170.0, 169.0, 168.0, 166.0, 165.0, 162.0, 161.0, 159.0, 156.0, 154.0, 153.0, 149.0, 148.0, 147.0, 146.0, 145.0, 144.0, 143.0, 140.0, 136.0, 134.0, 133.0, 132.0, 132.0, 131.0, 131.0, 130.0, 129.0, 126.0, 125.0, 123.0, 122.0, 122.0, 122.0, 121.0, 120.0, 119.0, 118.0, 116.0, 115.0, 114.0, 114.0, 113.0, 113.0, 113.0, 112.0, 111.0, 110.0, 110.0, 108.0, 107.0, 105.0, 104.0, 103.0, 99.0, 99.0, 99.0, 98.0, 95.0, 94.0, 94.0, 94.0, 92.0, 90.0, 89.0, 88.0, 88.0, 86.0, 86.0, 86.0, 86.0, 86.0, 85.0, 85.0, 85.0, 84.0, 83.0, 82.0, 82.0, 82.0, 81.0, 78.0, 77.0, 74.0, 74.0, 74.0, 73.0, 73.0, 72.0, 71.0, 71.0, 71.0, 70.0, 70.0, 68.0, 68.0, 67.0, 66.0, 65.0, 65.0, 64.0, 63.0, 61.0, 61.0, 60.0, 60.0, 60.0, 60.0, 59.0, 59.0, 59.0, 58.0, 58.0, 57.0, 57.0, 57.0, 56.0, 55.0, 55.0, 54.0, 54.0, 53.0, 53.0, 52.0, 51.0, 50.0, 50.0, 49.0, 49.0, 48.0, 48.0, 48.0, 48.0, 48.0, 47.0, 47.0, 47.0, 47.0, 47.0, 46.0, 45.0, 45.0, 45.0, 44.0, 44.0, 44.0, 44.0, 44.0, 43.0, 43.0, 43.0, 43.0, 43.0, 43.0, 43.0, 42.0, 42.0, 42.0, 42.0, 42.0, 42.0, 42.0, 41.0, 41.0, 41.0, 40.0, 40.0, 40.0, 40.0, 40.0, 39.0, 39.0, 39.0, 39.0, 38.0, 38.0, 38.0, 37.0, 37.0, 37.0, 37.0, 36.0, 35.0, 35.0, 35.0, 35.0, 35.0, 34.0, 34.0, 34.0, 34.0, 34.0, 33.0, 33.0, 33.0, 33.0, 33.0, 33.0, 33.0, 32.0, 32.0, 32.0, 31.0, 31.0, 29.0, 29.0, 29.0, 29.0, 29.0, 29.0, 29.0, 29.0, 29.0, 28.0, 28.0, 28.0, 28.0, 28.0, 28.0, 28.0, 28.0, 27.0, 27.0, 27.0, 27.0, 27.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 25.0, 25.0, 25.0, 25.0, 25.0, 24.0, 24.0, 24.0, 24.0, 24.0, 24.0, 24.0, 23.0, 23.0, 23.0, 23.0, 23.0, 23.0, 23.0, 23.0, 22.0, 22.0, 22.0, 22.0, 21.0, 21.0, 21.0, 21.0, 21.0, 21.0, 20.0, 20.0, 19.0, 19.0, 19.0, 19.0, 19.0, 19.0, 18.0, 18.0, 18.0, 18.0, 18.0, 18.0, 18.0, 18.0, 17.0, 17.0, 17.0, 17.0, 17.0, 17.0, 17.0, 17.0, 17.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 15.0, 15.0, 15.0, 15.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 13.0, 13.0, 13.0, 13.0, 13.0, 13.0, 13.0, 13.0, 13.0, 13.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 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, 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, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 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, 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, 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, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], \"yaxis\": \"y\"}], {\"barmode\": \"relative\", \"legend\": {\"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"plot_bgcolor\": \"rgba(36, 83, 97, 0.06)\", \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"autotypenumbers\": \"strict\", \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"user_name\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"max_star\"}, \"type\": \"log\"}}, {\"responsive\": true} ).then(function(){\n",
" \n",
"var gd = document.getElementById('20d1cd9d-3aa8-4e84-beae-214601582e8c');\n",
"var x = new MutationObserver(function (mutations, observer) {{\n",
" var display = window.getComputedStyle(gd).display;\n",
" if (!display || display === 'none') {{\n",
" console.log([gd, 'removed!']);\n",
" Plotly.purge(gd);\n",
" observer.disconnect();\n",
" }}\n",
"}});\n",
"\n",
"// Listen for the removal of the full notebook cells\n",
"var notebookContainer = gd.closest('#notebook-container');\n",
"if (notebookContainer) {{\n",
" x.observe(notebookContainer, {childList: true});\n",
"}}\n",
"\n",
"// Listen for the clearing of the current output cell\n",
"var outputEl = gd.closest('.output');\n",
"if (outputEl) {{\n",
" x.observe(outputEl, {childList: true});\n",
"}}\n",
"\n",
" }) }; </script> </div>\n",
"</body>\n",
"</html>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"text/html": [
"<html>\n",
"<head><meta charset=\"utf-8\" /></head>\n",
"<body>\n",
" <div> <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script> <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
" <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script> <div id=\"e10d50ef-f86f-4d8d-9be5-714531630817\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"e10d50ef-f86f-4d8d-9be5-714531630817\")) { Plotly.newPlot( \"e10d50ef-f86f-4d8d-9be5-714531630817\", [{\"alignmentgroup\": \"True\", \"hovertemplate\": \"user_name=%{x}<br>forks=%{y}<extra></extra>\", \"legendgroup\": \"\", \"marker\": {\"color\": \"#636efa\"}, \"name\": \"\", \"offsetgroup\": \"\", \"orientation\": \"v\", \"showlegend\": false, \"textposition\": \"auto\", \"type\": \"bar\", \"x\": [\"jwasham\", \"llSourcell\", \"fengdu78\", \"trekhleb\", \"rasbt\", \"aymericdamien\", \"josephmisiti\", \"vivienzou1\", \"Jack-Cherish\", \"justmarkham\", \"chiphuyen\", \"WillKoehrsen\", \"ZuzooVn\", \"ujjwalkarn\", \"susanli2016\", \"wepe\", \"Yorko\", \"lazyprogrammer\", \"soulmachine\", \"ty4z2008\", \"amitshekhariitbhu\", \"afshinea\", \"SamyPesse\", \"oldratlee\", \"jindongwang\", \"kailashahirwar\", \"titu1994\", \"imathis\", \"dipanjanS\", \"aleju\", \"rhiever\", \"benedekrozemberczki\", \"k88hudson\", \"ddbourgin\", \"tirthajyoti\", \"nfmcclure\", \"daviddao\", \"JWarmenhoven\", \"ljpzzz\", \"yuanxiaosc\", \"wkentaro\", \"firmai\", \"lawlite19\", \"polaris1119\", \"warmheartli\", \"Gaohaoyang\", \"hangtwenty\", \"pbharrin\", \"luispedro\", \"plusjade\", \"navdeep-G\", \"guillaume-chevalier\", \"xxg1413\", \"RedditSota\", \"layumi\", \"JustFollowUs\", \"zlotus\", \"dformoso\", \"TarrySingh\", \"Vay-keen\", \"timzhang642\", \"roboticcam\", \"hslatman\", \"shaoanlu\", \"haifengl\", \"tapaswenipathak\", \"meirwah\", \"RedstoneWill\", \"sjwhitworth\", \"stedy\", \"bamos\", \"Pomax\", \"Borye\", \"schmich\", \"swanson\", \"abhshkdz\", \"Lax\", \"JJ\", \"loveunk\", \"KaiyangZhou\", \"humphd\", \"shuhuai007\", \"Spandan-Madan\", \"csuldw\", \"reiinakano\", \"jphall663\", \"Sophia-11\", \"zotroneneis\", \"carefree0910\", \"demidovakatya\", \"lettier\", \"robertmartin8\", \"alexeygrigorev\", \"tdunning\", \"kevinlin311tw\", \"DeqianBai\", \"stephenturner\", \"kwhinnery\", \"robmarkcole\", \"atinesh-s\", \"scopatz\", \"shervinea\", \"zhunzhong07\", \"13o-bbr-bbq\", \"krishnakumarsekar\", \"shaqian\", \"xiaqunfeng\", \"karthik\", \"ethen8181\", \"MaxHalford\", \"yulequan\", \"jiffyclub\", \"jaraco\", \"masinoa\", \"yaph\", \"mappum\", \"ssusnic\", \"svaksha\", \"treyhunner\", \"JerryKurata\", \"frnsys\", \"albahnsen\", \"Naereen\", \"philips\", \"Metnew\", \"ilivans\", \"jeasonstudio\", \"Jasonnor\", \"jdblischak\", \"hamelsmu\", \"imhuay\", \"wilsonmar\", \"lefnire\", \"JohnMcLear\", \"tdhopper\", \"Mostafa-Samir\", \"parkr\", \"knathanieltucker\", \"pennyliang\", \"byrichardpowell\", \"martinwicke\", \"aaren\", \"NathanEpstein\", \"rhnvrm\", \"maxim5\", \"umpox\", \"yoavram\", \"ahmadia\", \"brandly\", \"art-programmer\", \"rieder91\", \"kinow\", \"Tomotoes\", \"gyoisamurai\", \"mcleonard\", \"liancheng\", \"zonca\", \"RaphaelMeudec\", \"wltrimbl\", \"sayakpaul\", \"sckott\", \"acabunoc\", \"myui\", \"geon\", \"kuixu\", \"rmarquis\", \"lorensr\", \"iamaziz\", \"wanzhenchn\", \"woliveiras\", \"glemaitre\", \"ecederstrand\", \"ranahanocka\", \"bigsnarfdude\", \"vict0rsch\", \"Bachmann1234\", \"ricardoamaro\", \"katzien\", \"wdm0006\", \"djoos\", \"ezefranca\", \"ColCarroll\", \"joaopedronardari\", \"rsbohn\", \"e9t\", \"timClicks\", \"abingham\", \"Tarrasch\", \"mtchavez\", \"andrewda\", \"msabramo\", \"cezannec\", \"terrytangyuan\", \"unode\", \"stefanv\", \"widdowquinn\", \"fperez\", \"SeanPrashad\", \"weakish\", \"synesthesiam\", \"re4lfl0w\", \"dribnet\", \"gumblex\", \"csinva\", \"zhigang1992\", \"ketanhwr\", \"penberg\", \"sinanuozdemir\", \"benmccann\", \"twitwi\", \"inejc\", \"jeff1evesque\", \"rdingwall\", \"egeriis\", \"Chandlercjy\", \"angeladai\", \"krother\", \"fhs\", \"Erotemic\", \"rachpt\", \"tranek\", \"ifesdjeen\", \"DiegoCatalano\", \"Philmod\", \"arnaldog12\", \"xuhdev\", \"juanpabloaj\", \"andreww\", \"ZYSzys\", \"rtlee9\", \"optas\", \"dubzzz\", \"ebenolson\", \"Sea-n\", \"gavinsimpson\", \"alphadl\", \"baldassarreFe\", \"JamesLuoau\", \"gaborvecsei\", \"gvwilson\", \"ptone\", \"sun254\", \"ProGamerGov\", \"secretrobotron\", \"Nukesor\", \"ethanwhite\", \"lexnederbragt\", \"anujgupta82\", \"iiSeymour\", \"mikl\", \"EdwardSmith1884\", \"lxieyang\", \"wking\", \"dhingratul\", \"nachocab\", \"kadirpekel\", \"magsol\", \"naupaka\", \"cratonica\", \"ooxi\", \"SiyuanQi\", \"YichenGong\", \"wojdyr\", \"crouchred\", \"Borda\", \"testrain\", \"axsaucedo\", \"CrazyBunQnQ\", \"gpailler\", \"dmcc\", \"rwdaigle\", \"Keiku\", \"apeeyush\", \"volker48\", \"BillMills\", \"dimpurr\", \"abarto\", \"cmacdonell\", \"zlu\", \"Diastro\", \"arfon\", \"daeyun\", \"idf\", \"matthewfeickert\", \"floydpink\", \"iglpdc\", \"antmarakis\", \"nashjain\", \"andresgottlieb\", \"eecn\", \"easezyc\", \"flipace\", \"jankrepl\", \"cbuckey-uda\", \"gaulinmp\", \"bboe\", \"KiranPanesar\", \"btbytes\", \"bertjiazheng\", \"adarsh0806\", \"run\", \"yoavz\", \"NeerajSarwan\", \"vmirly\", \"t-k-\", \"fish2000\", \"habi\", \"cmmalone\", \"harshnisar\", \"vishwajeetv\", \"jessitron\", \"leviding\", \"junlulocky\", \"vfdev-5\", \"orlitany\", \"pilif\", \"mogwai\", \"mysteriouspants\", \"rodgzilla\", \"pradeep1288\", \"lacava\", \"lazywei\", \"jgraving\", \"natowi\", \"girishkuniyal\", \"jakemcc\", \"bgreenwell\", \"adibis\", \"flyingpot\", \"hjlarry\", \"jackeylu\", \"init27\", \"piyushchauhan\", \"mjpieters\", \"mgschwan\", \"fhemberger\", \"willingc\", \"Finance-781\", \"xlfe\", \"lxj616\", \"iamBedant\", \"joaorafaelm\", \"teopost\", \"sebix\", \"GitHub30\", \"hsiaoyi0504\", \"Xyclade\", \"yarikoptic\", \"cmhungsteve\", \"lsvih\", \"jackmaney\", \"alicoding\", \"LarryBattle\", \"BetaPundit\", \"tommyblue\", \"MuminjonGuru\", \"ajmeese7\", \"gisikw\", \"herschel666\", \"jasonbhart\", \"gdevenyi\", \"njern\", \"zldeng\", \"maikelwever\", \"jrbourbeau\", \"tobyhodges\", \"lukearmstrong\", \"ffmpbgrnn\", \"raghavbali\", \"toaarnio\", \"beangoben\", \"DakshMiglani\", \"oneTaken\", \"gaodayue\", \"sudeepraja\", \"arc12\", \"fmichonneau\", \"dmoisset\", \"sivanWu0222\", \"havanagrawal\", \"NeroCube\", \"PatrickZH\", \"danyaljj\", \"drio\", \"AdityaSoni19031997\", \"zahanm\", \"kieranjol\", \"philippbayer\", \"BernhardKonrad\", \"pbanaszkiewicz\", \"nbsantos\", \"tgray\", \"cavestruz\", \"jpallen\", \"vrv\", \"LukasKnuth\", \"jakirkham\", \"kgashok\", \"prajjwal1\", \"thouis\", \"yeonjuan\", \"RockySJ\", \"kyranb\", \"iory\", \"nvh95\", \"hamiltont\", \"sergioburdisso\", \"wzell\", \"xiuluo\", \"vallentin\", \"justanhduc\", \"cjauvin\", \"koriroys\", \"cdeil\", \"polymeris\", \"clarle\", \"chi-hung\", \"meawoppl\", \"selimnairb\", \"Amir-Arsalan\", \"hanhdt\", \"RF-Nelson\", \"pipitone\", \"rajeshvaya\", \"vyper\", \"michaelaye\", \"Ir1d\", \"davidrhodus\", \"tvogels\", \"kno10\", \"dlebauer\", \"jaycode\", \"adamyala\", \"TehMillhouse\", \"robtaussig\", \"ArionMiles\", \"sdball\", \"whatrocks\", \"iamc\", \"Sentimentron\", \"daveredrum\", \"amitkgupta\", \"FlorisHoogenboom\", \"mrry\", \"DanBeard\", \"studiomohawk\", \"pjbull\", \"vattay\", \"chhh\", \"gvn\", \"lstolcman\", \"DamienIrving\", \"ZhengRui\", \"alimon808\", \"kwichmann\", \"keveman\", \"varshapaidi\", \"jayrav13\", \"nipunsadvilkar\", \"waterson\", \"vahtras\", \"hex108\", \"omo\", \"hmchuong\", \"caub\", \"douglatornell\", \"mangei\", \"SegFaultAX\", \"andrewschreiber\", \"divik544\", \"WuZhuoran\", \"rachtsingh\", \"adam2392\", \"mewben\", \"fmder\", \"cgohlke\", \"melzareix\", \"olivertomic\", \"itailang\", \"langner\", \"ajkl\", \"zylix666\", \"ambientlight\", \"espoirMur\", \"everping\", \"andsor\", \"graphaelli\", \"itsliupeng\", \"keppel\", \"mindw\", \"wenruimeng\", \"acusti\", \"erjanmx\", \"SylvainDe\", \"fchouteau\", \"jimthompson5802\", \"RandomArray\", \"danielsan\", \"PGijsbers\", \"BirkhoffLee\", \"jocelynlih\", \"Suraj520\", \"cloudyan\", \"planetceres\", \"simensen\", \"cailurus\", \"cbarrick\", \"ebuildy\", \"CorcovadoMing\", \"alg\", \"postBG\", \"PBarmby\", \"emptyr1\", \"avinashsai\", \"mkuhn\", \"el10savio\", \"anuj1207\", \"gideonthomas\", \"cjratcliff\", \"rozentill\", \"wogong\", \"QSCTech-Sange\", \"synapticarbors\", \"enjoyhot\", \"kid1412z\", \"umstek\", \"jboy\", \"code0100fun\", \"MarcelRobeer\", \"patricksnape\", \"tncardoso\", \"ccyanxyz\", \"ebigelow\", \"KodeWorker\", \"cjpurackal\", \"npbool\", \"brainstorm\", \"LoveMeWithoutAll\", \"dmnelson\", \"JustinJudd\", \"yurrriq\", \"Amir22010\", \"EtienneT\", \"Horaddrim\", \"digital-thinking\", \"ses4j\", \"hwmrocker\", \"songuke\", \"luvegood\", \"PrinzOwO\", \"jeffcore\", \"ericdill\", \"avn3r\", \"blokhin\", \"alexsavio\", \"juliangarcia\", \"aosama\", \"MadhumitaSushil\", \"dtchepak\", \"cmutel\", \"thezillion\", \"ammarasmro\", \"kilsenp\", \"jcn\", \"AmaanC\", \"asford\", \"bobiechen-twilio\", \"mexeniz\", \"rayeaster\", \"snurkabill\", \"daz\", \"mckays630\", \"DanilBaibak\", \"moutai\", \"sdierauf\", \"jongoodnow\", \"phocks\", \"allardbrain\", \"Ja1r0\", \"justpic\", \"eccstartup\", \"agusnavce\", \"LiEmail\", \"jGaboardi\", \"cameroncan\", \"brylie\", \"ACharbonneau\", \"RingoTC\", \"Cugtyt\", \"kastman\", \"jpvg10\", \"sjml\", \"maks-a\", \"jbencook\", \"liuluheng\", \"buddhikajay\", \"shashankgroovy\", \"RequireSun\", \"datamove\", \"yuanzhaoYZ\", \"ericbuehl\", \"guillermo-navas-palencia\", \"EtienneBruines\", \"Vincent-Vercruyssen\", \"shikharvaish28\", \"beckgael\", \"p-s-vishnu\", \"Vijayabhaskar96\", \"fleeting\", \"jsmith\", \"HapeMask\", \"srhrshr\", \"cako\", \"Alex1996a\", \"rafaelsakurai\", \"anzellai\", \"nolith\", \"cxxgtxy\", \"festline\", \"arteymix\", \"benedictflorance\", \"SwarShah\", \"jakubczakon\", \"albertstill\", \"alisezer\", \"JanLauGe\", \"ss8651twtw\", \"tommyjiang\", \"junxnone\", \"tiendq\", \"advancedxy\", \"timmartin19\", \"Microsheep\", \"strange-jiong\", \"stonebig\", \"kjappelbaum\", \"shahules786\", \"DrDavidS\", \"ghthor\", \"frankhjwx\", \"bendoerr\", \"sebg\", \"ayakubovich\", \"ReekenX\", \"jacarrico\", \"idear1203\", \"okjake\", \"BioGeek\", \"havk64\", \"poyuwu\", \"optixlab\", \"kennethjmyers\", \"sohamM97\", \"abought\", \"finnigantime\", \"SubrataSarkar32\", \"briansorahan\", \"dmmulroy\", \"zh794390558\", \"haraldschilly\", \"aoping\", \"chneau\", \"QuLogic\", \"phillies\", \"wenyangfu\", \"AJDBenner\", \"metrafonic\", \"filipefilardi\", \"thecjharries\", \"AlexZhou1995\", \"DanielMorales9\", \"vinodkkurmi\", \"SaumoPal97\", \"Karl-EdwardFPJeanMehu\", \"autodataming\", \"sedge\", \"mandar2812\", \"Psimage\", \"janismdhanbad\", \"libertatis\", \"fndjjx\", \"mingzhang96\", \"fanglinchen\", \"Tirzono\", \"TitouanT\", \"KevinCooper\", \"Soypete\", \"SnailSword\", \"tomhoover\", \"dangsonbk\", \"arimbr\", \"schneiderfelipe\", \"AnshulBasia\", \"vad4msiu\", \"0asa\", \"dogHere\", \"codedread\", \"ilam\", \"opie4624\", \"denisarnaud\", \"RasPat1\", \"curiousleo\", \"hlkcrcck\", \"kota7\", \"daniel-kashin\", \"mybaseball52\", \"curiousrohan\", \"CSerxy\", \"ackerleytng\", \"nitinagarwal\", \"victorhcm\", \"TaurusOlson\", \"AdilZouitine\", \"x1957\", \"Mrzhangxiaohua\", \"jhashanti\", \"kcrandall\", \"muhammadyaseen\", \"bobrosoft\", \"NJannasch\", \"UjjwalAryal\", \"wassimseif\", \"eeeeeric\", \"KeniMorri\", \"stromnov\", \"lzcabrera\", \"SarthakYadav\", \"digitalduke\", \"proinsias\", \"hugosoftdev\", \"dsych\", \"allthroughthenight\", \"Zzlongjuanfeng\", \"LizhangX\", \"NotAnyMike\", \"HaveF\", \"ahnt\", \"ocdtrekkie\", \"cPolaris\", \"skvrahul\", \"silverstone1903\", \"oussou-dev\", \"jalateras\", \"LiberiFatali\", \"meghpatel\", \"hanpum\", \"adriancampos\", \"jcsims\", \"mollygibson\", \"nschor\", \"itsmeolivia\", \"luntain\", \"eshizhan\", \"peterfabakker\", \"cogmission\", \"Tom-Ren\", \"samedhaa\", \"sguada\", \"ecolell\", \"HemuManju\", \"LecJackS\", \"qhfgva\", \"frozenkp\", \"CorreyL\", \"hyqskevin\", \"thesimanjan\", \"apatsekin\", \"aniag\", \"jogjayr\", \"RickEyre\", \"Owen-Mak\", \"mraje16\", \"ss18\", \"JasonGitHub\", \"daanmichiels\", \"firebreath1001\", \"pmn4\", \"zdgriffith\", \"rahmanhafeezul\", \"juholehtonen\", \"pan-long\", \"adyates\", \"alexlokotochek\", \"smbeli\", \"sagardubey3\", \"czenzel\", \"jsgv\", \"pfsq\", \"bryngo\", \"d4n1elchen\", \"pw\", \"ipcenas\", \"busterroni\", \"joyoyoyoyoyo\", \"Hefeweizen\", \"nahumj\", \"jselmani\", \"appleJax\", \"ayushs136\", \"koobs\", \"SumanthReddyKaliki\", \"sudipbhandari126\", \"niltonslf\", \"aggronerd\", \"Amjad-H-Ali\", \"buddhiv\", \"daddou-ma\", \"IgorKovr\", \"joybanerjee08\", \"kmscode\", \"adam-erickson\", \"nektor211\", \"jwsy\", \"snowde\", \"AkshayVarik\", \"mjschranz\", \"jacksonlo\", \"samyag1\", \"Mchristos\", \"irrationalRock\", \"ulido\", \"pkayfire\", \"jldohmann\", \"ktolstikhin\", \"sourcesoft\", \"robot-c0der\", \"Pooch11\", \"xcodeburpx\", \"jgyllinsky\", \"grayskripko\", \"qualityjacks\", \"zyc1gq\", \"ronnierios\", \"elfelround\", \"ehrenfeu\", \"idelgado\", \"mapx\", \"DH-Diego\", \"lukaszkaiser\", \"McKenzyPG\", \"azillion\", \"PeterShershov\", \"npanti\", \"yakud\", \"rafalgrm\", \"Alveona\", \"K1t1k\", \"n-kats\", \"giuliatondin\", \"gcoter\", \"brigham\", \"varan42\", \"kreuvf\", \"frannievas\", \"triangeljs\", \"bkm009\", \"jeffin07\", \"louispotok\", \"davidlowjw\", \"AselaDarshan\", \"taylan\", \"sagarcadet\", \"anishthite\", \"jaksmid\", \"calberti\", \"Fatehsandhu\", \"niklaskeerl\", \"athiwatc\", \"sstarr\", \"TuanNguyen27\", \"TwFlem\", \"sailakshmi17\", \"thanhnguyentang\", \"ao-song\", \"gliptak\", \"bigwave\", \"e173101\", \"timfrostmann\", \"fatihbaltaci\", \"mmBabol\", \"ismaeIfm\", \"JustroX\", \"binilj04\", \"SentinelWarren\", \"soumanpaul\", \"IamThilina\", \"Domon\", \"Gabriel-Azevedo-Ferreira\", \"lzamparo\", \"sshekh\", \"rajasekharponakala\", \"dylandrop\", \"Div44\", \"adityahiran\", \"jaymody\", \"beroe\", \"kshs010239\", \"dbarbier\", \"hbaniecki\", \"shrutibhutaiya\", \"mikelogsdon\", \"AnkurDedania\", \"chrish42\", \"moshejs\", \"2y2simple\", \"hetii\", \"chkoar\", \"Budddy\", \"alexobednikov\", \"jvanlangen\", \"seIncorp\", \"Adrien-Jecker\", \"aaroncm\", \"javierlorenzod\", \"ande765a\", \"Frenchhorn\", \"sys0613\", \"acastrounis\", \"twigz20\", \"codingcai\", \"joaoavf\", \"taoyudong\", \"K-LV\", \"Devinsuit\", \"tychenjiajun\", \"LiLiu93\", \"steven7851\", \"mzakariaCERN\", \"XiaoshuiHuang\", \"omytryniuk\", \"TusharShandilya\", \"borodenkov\", \"sirius999999\", \"tomahawk28\", \"justramgerry\", \"MTietze\", \"lacanlale\", \"chess99\", \"JsonAC\", \"dear983604\", \"ptaiga\", \"Minki-Kim95\", \"YJH1987\", \"drlabratory\", \"GordianStapf\", \"engineeress\", \"kbagchiGWC\", \"ss52\", \"lukelafountaine\", \"sagunji\", \"saiabishek1\", \"matt-jay\", \"drskd\", \"databaaz\", \"SumitBando\", \"thedadams\", \"slcott\", \"Th30\", \"itkinai\", \"LeeMaria007\", \"adamwkraft\", \"itzamna314\", \"kersov\", \"jkuchta\", \"bon\", \"agngrant\", \"peter-toth\", \"skervim\", \"zairah10\", \"Petemir\", \"tomraulet\", \"dombrno\", \"orionr\", \"wayneadams\", \"ini\", \"malfple\", \"gsenseless\", \"p1gd0g\", \"matheusgmaia\", \"JJLWHarrison\", \"Jurilz\", \"rogerzanoni\", \"ploth\", \"koomar\", \"derrg\", \"salehjg\", \"amyrhoda\", \"maximkeremet\", \"cpdj\", \"selay01\", \"Asterisk14\", \"imaness\", \"gauravcharnalia\", \"shenyyi\", \"ari-schaffel\", \"xkcao\", \"An3bi\", \"mgoodfellow\", \"basickarl\", \"baogianghoangvu\", \"nathanhillyer\", \"moonboots\", \"hungphandinh92it\", \"nyoung85\", \"pdkovacs\", \"swlsw\", \"igorrocha\", \"mzk912778163\", \"doppenhe\", \"YongshanKe\", \"wendingp\", \"eldaniz\", \"srayuws\", \"danielbogomazov\", \"tuanphuc\", \"credentiality\", \"wenphan\", \"mkilavuz\", \"vilmacio22\", \"flytomylife\", \"Mintisma\", \"tairiUdacity\", \"wtollett-usgs\", \"creinders\", \"Pirikara\", \"ankitkul\", \"wsbmxa198700\", \"MdScntst\", \"Airatiki\", \"Ouss4\", \"coderfive\", \"trpapp\", \"jovilius\", \"nmb10\", \"liuliu5151\", \"andrewd76\", \"12wang3\", \"BokaiLIAN\", \"wqiancheng\", \"gukoff\", \"olveirap\", \"YINCHENLI\", \"SoumyadeepJana\", \"ilbuono\", \"kacper1095\", \"elwinarens\", \"martijnvanbeers\", \"ivesn\", \"ser-serege\", \"jaywinhuang\", \"scraggard\", \"willalways\", \"clappis\", \"PaulDebus\", \"kylegrover\", \"lupusomniator\", \"jiangf13\", \"ThePhantomCoder\", \"yhx5768\", \"mikhailsergeevi4\", \"carlward\", \"praveenmylavarapu\", \"peter-parque\", \"harshavamsi\", \"deeper-learning\", \"sseidl88\", \"yjh\", \"willgroves\", \"yangyyt\", \"Bachstelze\", \"Liam-Yang\", \"mkotov13\", \"jlar0che\", \"vicramr\", \"adpon\", \"AndrewLiesinger\", \"dnn37\", \"stnk20\", \"jappre\", \"jamesmyatt\", \"voskresenskiy\", \"YoungMStudio\", \"alishutc\", \"JayJayBinks\", \"MUSSONT\", \"kzhk75\", \"maxnk\", \"mgoldey\", \"pkuphy\", \"4may\", \"njojic\", \"alcidesv\", \"elesueur\", \"kevinkyyro\", \"esztiorm\", \"qiagu\", \"pleabargain\", \"narisada014\", \"IsakFalk\", \"KirillPanin\", \"individual8\", \"Nebula83\", \"mosew\", \"stieglma\", \"GageAmes\", \"gceboh\", \"amar00k\", \"TocarIP\", \"cshan\", \"ecbc1\", \"mirjalil\", \"whughw\", \"nitin-tm\", \"Asmolovskij\", \"synapton\", \"Lincete\", \"toddrme2178\", \"harenbergsd\", \"liliuleo\", \"ReadmeCritic\", \"sdsk\", \"alexnich\", \"alexey-grigorev-sm\", \"m-maksyutin\", \"bkhaleghi\", \"wla80\", \"KaiNieRus\", \"gitbook-bot\", \"wang1211\", \"jmchen-g\", \"tuantp7\", \"chrissoulierserv\", \"TommyBark\", \"yonatanf\", \"tomassvensson\", \"163-0533\", \"imatiach-msft\", \"Bruce-Feldman\", \"CookieDom\", \"albertmolinermrf\", \"jared-weed\", \"mkeds\", \"fangweili\", \"guedalia\", \"ThatAndresV\", \"bvonboyen\", \"mikej888\", \"grp-bork\", \"awesome-bot\", \"rohduggal\", \"SeanPedersen\", \"lee709\", \"Charismatron\", \"testaccount553\", \"eddyzhd\", \"cswef\", \"zzincubus\", \"IMWP\", \"marsben\", \"GLevV\", \"sudoes\", \"cgcgcg\", \"aquinasCode\", \"serickso\", \"afromanF\", \"wrichert\", \"chrisadami\", \"josephmmisiti\", \"mahajani123\", \"acupofdata\", \"dnguneratne\", \"svntjng\", \"testbounty\", \"Zhi-lin\", \"qianguyizhe\", \"ExterminateWho\", \"egorpolusmak\", \"oleksii-trekhleb-epam\", \"rumi-naik\", \"SusieXu\", \"tushargt\", \"vargas\", \"ntache\", \"lisahdd007\", \"ShengKungYi\", \"ritabentodosreis\", \"APorterOReilly\", \"hfanahita\", \"monomagentaeggroll\", \"Digitalmobz\", \"bob7783\", \"jliddie\", \"elkfrawy-df\", \"Dr-Zhou\", \"twotabbies\", \"AlexanderKunkel\", \"jackkuipers\", \"bluewoodtree\", \"omrimendels\", \"aathauck\", \"Kacawi\", \"LukeArn\", \"windpls\", \"ivigamberdiev\", \"mrtnbrst\", \"miksago\"], \"xaxis\": \"x\", \"y\": [37828.0, 27168.0, 17562.0, 16723.0, 15633.0, 15395.0, 11857.0, 8498.0, 7738.0, 7694.0, 5998.0, 5843.0, 5644.0, 5471.0, 5169.0, 5091.0, 4985.0, 4985.0, 4808.0, 4717.0, 4069.0, 3937.0, 3855.0, 3783.0, 3389.0, 3274.0, 3044.0, 2981.0, 2909.0, 2748.0, 2732.0, 2652.0, 2634.0, 2507.0, 2493.0, 2429.0, 2368.0, 2361.0, 2335.0, 2215.0, 2184.0, 2136.0, 2109.0, 2105.0, 2088.0, 1996.0, 1952.0, 1937.0, 1936.0, 1858.0, 1673.0, 1650.0, 1426.0, 1396.0, 1338.0, 1313.0, 1306.0, 1254.0, 1249.0, 1228.0, 1223.0, 1211.0, 1145.0, 1131.0, 1129.0, 1118.0, 1112.0, 1069.0, 1054.0, 1031.0, 1003.0, 987.0, 966.0, 944.0, 930.0, 918.0, 915.0, 901.0, 896.0, 883.0, 807.0, 794.0, 793.0, 742.0, 706.0, 688.0, 683.0, 677.0, 647.0, 646.0, 630.0, 619.0, 619.0, 611.0, 601.0, 549.0, 534.0, 529.0, 516.0, 515.0, 512.0, 502.0, 496.0, 495.0, 493.0, 472.0, 462.0, 456.0, 439.0, 438.0, 431.0, 425.0, 411.0, 394.0, 393.0, 391.0, 368.0, 365.0, 351.0, 338.0, 336.0, 333.0, 333.0, 327.0, 321.0, 320.0, 308.0, 303.0, 292.0, 287.0, 278.0, 267.0, 264.0, 264.0, 254.0, 253.0, 250.0, 250.0, 249.0, 248.0, 247.0, 243.0, 241.0, 240.0, 238.0, 237.0, 236.0, 232.0, 231.0, 231.0, 226.0, 225.0, 224.0, 222.0, 219.0, 214.0, 210.0, 209.0, 209.0, 206.0, 204.0, 202.0, 199.0, 198.0, 198.0, 194.0, 192.0, 191.0, 187.0, 185.0, 181.0, 178.0, 176.0, 172.0, 171.0, 170.0, 169.0, 169.0, 167.0, 166.0, 165.0, 162.0, 161.0, 160.0, 159.0, 159.0, 159.0, 159.0, 155.0, 154.0, 150.0, 147.0, 147.0, 146.0, 145.0, 144.0, 144.0, 143.0, 142.0, 141.0, 138.0, 134.0, 134.0, 133.0, 132.0, 129.0, 129.0, 125.0, 124.0, 121.0, 121.0, 120.0, 120.0, 119.0, 119.0, 118.0, 115.0, 115.0, 112.0, 112.0, 111.0, 110.0, 109.0, 108.0, 108.0, 108.0, 103.0, 103.0, 103.0, 103.0, 102.0, 101.0, 97.0, 97.0, 97.0, 97.0, 97.0, 96.0, 96.0, 96.0, 95.0, 95.0, 93.0, 89.0, 88.0, 87.0, 86.0, 85.0, 85.0, 84.0, 83.0, 81.0, 81.0, 81.0, 80.0, 80.0, 78.0, 78.0, 78.0, 77.0, 77.0, 77.0, 77.0, 76.0, 76.0, 76.0, 74.0, 74.0, 74.0, 74.0, 73.0, 72.0, 72.0, 71.0, 71.0, 70.0, 69.0, 69.0, 68.0, 68.0, 67.0, 67.0, 67.0, 66.0, 66.0, 66.0, 65.0, 64.0, 61.0, 60.0, 60.0, 60.0, 60.0, 59.0, 59.0, 58.0, 58.0, 58.0, 57.0, 56.0, 56.0, 56.0, 56.0, 56.0, 55.0, 55.0, 55.0, 55.0, 55.0, 54.0, 54.0, 53.0, 53.0, 53.0, 53.0, 53.0, 52.0, 52.0, 51.0, 50.0, 50.0, 50.0, 50.0, 49.0, 49.0, 48.0, 48.0, 48.0, 47.0, 47.0, 47.0, 46.0, 46.0, 46.0, 46.0, 45.0, 45.0, 45.0, 45.0, 45.0, 44.0, 43.0, 43.0, 43.0, 43.0, 43.0, 43.0, 42.0, 41.0, 41.0, 41.0, 41.0, 41.0, 40.0, 40.0, 40.0, 40.0, 39.0, 39.0, 38.0, 38.0, 37.0, 37.0, 37.0, 36.0, 36.0, 36.0, 36.0, 36.0, 35.0, 35.0, 35.0, 35.0, 34.0, 34.0, 34.0, 34.0, 33.0, 32.0, 32.0, 32.0, 32.0, 31.0, 31.0, 31.0, 30.0, 30.0, 30.0, 30.0, 30.0, 29.0, 29.0, 29.0, 28.0, 28.0, 28.0, 28.0, 28.0, 28.0, 27.0, 27.0, 27.0, 27.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 25.0, 25.0, 25.0, 25.0, 25.0, 25.0, 25.0, 25.0, 24.0, 24.0, 24.0, 24.0, 24.0, 24.0, 24.0, 24.0, 24.0, 24.0, 24.0, 23.0, 23.0, 23.0, 23.0, 23.0, 23.0, 23.0, 23.0, 22.0, 22.0, 22.0, 22.0, 22.0, 21.0, 21.0, 21.0, 21.0, 21.0, 21.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 19.0, 19.0, 19.0, 19.0, 19.0, 19.0, 19.0, 19.0, 19.0, 19.0, 19.0, 19.0, 19.0, 18.0, 18.0, 18.0, 18.0, 18.0, 17.0, 17.0, 17.0, 17.0, 17.0, 17.0, 17.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 16.0, 15.0, 15.0, 15.0, 15.0, 15.0, 15.0, 15.0, 15.0, 15.0, 15.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 14.0, 13.0, 13.0, 13.0, 13.0, 13.0, 13.0, 13.0, 13.0, 13.0, 13.0, 13.0, 13.0, 13.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 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, 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, 8.0, 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, 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, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 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, 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, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], \"yaxis\": \"y\"}], {\"barmode\": \"relative\", \"legend\": {\"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"plot_bgcolor\": \"rgba(36, 83, 97, 0.06)\", \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"autotypenumbers\": \"strict\", \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"user_name\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"forks\"}, \"type\": \"log\"}}, {\"responsive\": true} ).then(function(){\n",
" \n",
"var gd = document.getElementById('e10d50ef-f86f-4d8d-9be5-714531630817');\n",
"var x = new MutationObserver(function (mutations, observer) {{\n",
" var display = window.getComputedStyle(gd).display;\n",
" if (!display || display === 'none') {{\n",
" console.log([gd, 'removed!']);\n",
" Plotly.purge(gd);\n",
" observer.disconnect();\n",
" }}\n",
"}});\n",
"\n",
"// Listen for the removal of the full notebook cells\n",
"var notebookContainer = gd.closest('#notebook-container');\n",
"if (notebookContainer) {{\n",
" x.observe(notebookContainer, {childList: true});\n",
"}}\n",
"\n",
"// Listen for the clearing of the current output cell\n",
"var outputEl = gd.closest('.output');\n",
"if (outputEl) {{\n",
" x.observe(outputEl, {childList: true});\n",
"}}\n",
"\n",
" }) }; </script> </div>\n",
"</body>\n",
"</html>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"text/html": [
"<html>\n",
"<head><meta charset=\"utf-8\" /></head>\n",
"<body>\n",
" <div> <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script> <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
" <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script> <div id=\"0f7651e6-fd0b-4733-ada1-23fca63c4264\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"0f7651e6-fd0b-4733-ada1-23fca63c4264\")) { Plotly.newPlot( \"0f7651e6-fd0b-4733-ada1-23fca63c4264\", [{\"alignmentgroup\": \"True\", \"hovertemplate\": \"user_name=%{x}<br>contribution=%{y}<extra></extra>\", \"legendgroup\": \"\", \"marker\": {\"color\": \"#636efa\"}, \"name\": \"\", \"offsetgroup\": \"\", \"orientation\": \"v\", \"showlegend\": false, \"textposition\": \"auto\", \"type\": \"bar\", \"x\": [\"CorcovadoMing\", \"stromnov\", \"brainstorm\", \"humphd\", \"chiphuyen\", \"jsgv\", \"bboe\", \"ande765a\", \"digitalduke\", \"hjlarry\", \"daveredrum\", \"Naereen\", \"tirthajyoti\", \"robtaussig\", \"kcrandall\", \"IsakFalk\", \"cmutel\", \"drio\", \"thecjharries\", \"CrazyBunQnQ\", \"tommyblue\", \"Philmod\", \"meirwah\", \"JustroX\", \"agusnavce\", \"pkayfire\", \"PeterShershov\", \"stefanv\", \"hslatman\", \"simensen\", \"bamos\", \"pbanaszkiewicz\", \"LoveMeWithoutAll\", \"MuminjonGuru\", \"oldratlee\", \"yoavram\", \"keveman\", \"sourcesoft\", \"LizhangX\", \"SeanPrashad\", \"gavinsimpson\", \"WillKoehrsen\", \"pjbull\", \"karthik\", \"pmn4\", \"cjratcliff\", \"cjauvin\", \"andrewschreiber\", \"WuZhuoran\", \"zh794390558\", \"dombrno\", \"rasbt\", \"ranahanocka\", \"woliveiras\", \"QSCTech-Sange\", \"natowi\", \"abought\", \"jiffyclub\", \"wojdyr\", \"abhshkdz\", \"dlebauer\", \"bobrosoft\", \"haifengl\", \"gliptak\", \"yakud\", \"ss18\", \"azillion\", \"sjml\", \"carefree0910\", \"gdevenyi\", \"imatiach-msft\", \"nipunsadvilkar\", \"cgohlke\", \"yaph\", \"michaelaye\", \"Hefeweizen\", \"arimbr\", \"brandly\", \"penberg\", \"synapticarbors\", \"DanielMorales9\", \"dylandrop\", \"luispedro\", \"junxnone\", \"TusharShandilya\", \"espoirMur\", \"ethanwhite\", \"shikharvaish28\", \"schneiderfelipe\", \"tomhoover\", \"aggronerd\", \"keppel\", \"tapaswenipathak\", \"amitshekhariitbhu\", \"jphall663\", \"alphadl\", \"graphaelli\", \"jimthompson5802\", \"adam2392\", \"loveunk\", \"rachpt\", \"ccyanxyz\", \"niltonslf\", \"sivanWu0222\", \"nahumj\", \"AselaDarshan\", \"silverstone1903\", \"naupaka\", \"ecederstrand\", \"vivienzou1\", \"xlfe\", \"jessitron\", \"lexnederbragt\", \"iamBedant\", \"tobyhodges\", \"lefnire\", \"guillermo-navas-palencia\", \"testrain\", \"Mostafa-Samir\", \"ajmeese7\", \"cloudyan\", \"qiagu\", \"cmhungsteve\", \"alexsavio\", \"ackerleytng\", \"tdhopper\", \"iiSeymour\", \"wogong\", \"floydpink\", \"Soypete\", \"planetceres\", \"fanglinchen\", \"Tomotoes\", \"ezefranca\", \"NotAnyMike\", \"alexlokotochek\", \"cjpurackal\", \"KiranPanesar\", \"dmoisset\", \"ayushs136\", \"cgcgcg\", \"SylvainDe\", \"xxg1413\", \"ZYSzys\", \"piyushchauhan\", \"danielbogomazov\", \"blokhin\", \"dmnelson\", \"wilsonmar\", \"abingham\", \"jgraving\", \"LukasKnuth\", \"vilmacio22\", \"jbencook\", \"layumi\", \"jakubczakon\", \"ColCarroll\", \"proinsias\", \"DrDavidS\", \"prajjwal1\", \"hwmrocker\", \"gaulinmp\", \"arteymix\", \"sstarr\", \"ocdtrekkie\", \"hangtwenty\", \"d4n1elchen\", \"el10savio\", \"BirkhoffLee\", \"mrry\", \"robertmartin8\", \"widdowquinn\", \"sergioburdisso\", \"egeriis\", \"plusjade\", \"titu1994\", \"jindongwang\", \"rozentill\", \"jaycode\", \"AdilZouitine\", \"myui\", \"dhingratul\", \"tychenjiajun\", \"ericdill\", \"koobs\", \"Ouss4\", \"ArionMiles\", \"RingoTC\", \"tiendq\", \"lettier\", \"chhh\", \"NJannasch\", \"daviddao\", \"anishthite\", \"ammarasmro\", \"Amjad-H-Ali\", \"reiinakano\", \"LecJackS\", \"lzamparo\", \"p-s-vishnu\", \"martijnvanbeers\", \"snurkabill\", \"BillMills\", \"tranek\", \"lzcabrera\", \"soumanpaul\", \"jcsims\", \"vahtras\", \"adriancampos\", \"gaborvecsei\", \"baldassarreFe\", \"jeffcore\", \"Sophia-11\", \"Jurilz\", \"orionr\", \"CorreyL\", \"dmmulroy\", \"RequireSun\", \"jankrepl\", \"Gaohaoyang\", \"lacava\", \"kastman\", \"lorensr\", \"byrichardpowell\", \"emptyr1\", \"fhemberger\", \"pkuphy\", \"13o-bbr-bbq\", \"IamThilina\", \"ZhengRui\", \"BetaPundit\", \"Chandlercjy\", \"kno10\", \"ty4z2008\", \"louispotok\", \"rhnvrm\", \"Yorko\", \"twitwi\", \"ilivans\", \"arnaldog12\", \"allthroughthenight\", \"stonebig\", \"shashankgroovy\", \"chess99\", \"timClicks\", \"JanLauGe\", \"mikej888\", \"ss8651twtw\", \"KaiyangZhou\", \"kylegrover\", \"joyoyoyoyoyo\", \"Pirikara\", \"avinashsai\", \"umstek\", \"AmaanC\", \"DakshMiglani\", \"bertjiazheng\", \"adam-erickson\", \"GitHub30\", \"carlward\", \"pipitone\", \"btbytes\", \"hex108\", \"patricksnape\", \"Suraj520\", \"alexeygrigorev\", \"liancheng\", \"ao-song\", \"magsol\", \"skvrahul\", \"ddbourgin\", \"orlitany\", \"kreuvf\", \"andreww\", \"asford\", \"gpailler\", \"SumitBando\", \"k88hudson\", \"havanagrawal\", \"whatrocks\", \"philips\", \"yuanxiaosc\", \"hamiltont\", \"cavestruz\", \"thedadams\", \"csuldw\", \"shervinea\", \"lukaszkaiser\", \"lukearmstrong\", \"wendingp\", \"bobiechen-twilio\", \"chkoar\", \"justmarkham\", \"code0100fun\", \"caub\", \"toddrme2178\", \"kieranjol\", \"lacanlale\", \"anujgupta82\", \"juanpabloaj\", \"gumblex\", \"nathanhillyer\", \"vmirly\", \"ipcenas\", \"Cugtyt\", \"moshejs\", \"Petemir\", \"ser-serege\", \"allardbrain\", \"juholehtonen\", \"KodeWorker\", \"Minki-Kim95\", \"geon\", \"zahanm\", \"ooxi\", \"langner\", \"joaorafaelm\", \"ProGamerGov\", \"clappis\", \"cshan\", \"adamwkraft\", \"frannievas\", \"FlorisHoogenboom\", \"cbarrick\", \"mogwai\", \"Alveona\", \"filipefilardi\", \"sudipbhandari126\", \"thanhnguyentang\", \"dipanjanS\", \"niklaskeerl\", \"roboticcam\", \"mgschwan\", \"jldohmann\", \"kilsenp\", \"cogmission\", \"gaodayue\", \"TarrySingh\", \"mcleonard\", \"taylan\", \"JerryKurata\", \"mybaseball52\", \"unode\", \"danielsan\", \"toaarnio\", \"HemuManju\", \"NeroCube\", \"mzakariaCERN\", \"basickarl\", \"gvn\", \"n-kats\", \"sagunji\", \"MTietze\", \"aaroncm\", \"alexobednikov\", \"bgreenwell\", \"BioGeek\", \"Jack-Cherish\", \"Amir-Arsalan\", \"tommyjiang\", \"fengdu78\", \"stedy\", \"kevinlin311tw\", \"fleeting\", \"jeffin07\", \"CSerxy\", \"Amir22010\", \"melzareix\", \"autodataming\", \"wassimseif\", \"SentinelWarren\", \"amyrhoda\", \"RasPat1\", \"Mintisma\", \"susanli2016\", \"pw\", \"ptone\", \"bryngo\", \"eecn\", \"jcn\", \"justanhduc\", \"imathis\", \"wdm0006\", \"msabramo\", \"ethen8181\", \"wenyangfu\", \"jamesmyatt\", \"mckays630\", \"Bachstelze\", \"jpvg10\", \"ini\", \"rafaelsakurai\", \"giuliatondin\", \"appleJax\", \"muhammadyaseen\", \"SnailSword\", \"idear1203\", \"meghpatel\", \"shahules786\", \"maikelwever\", \"javierlorenzod\", \"sdball\", \"oussou-dev\", \"afshinea\", \"adyates\", \"beangoben\", \"sohamM97\", \"wltrimbl\", \"ffmpbgrnn\", \"tdunning\", \"e9t\", \"divik544\", \"svaksha\", \"Zzlongjuanfeng\", \"teopost\", \"ebuildy\", \"TaurusOlson\", \"Mchristos\", \"taoyudong\", \"nashjain\", \"fchouteau\", \"kota7\", \"clarle\", \"gideonthomas\", \"AdityaSoni19031997\", \"ifesdjeen\", \"mapx\", \"raghavbali\", \"lawlite19\", \"dnguneratne\", \"harshavamsi\", \"vinodkkurmi\", \"hmchuong\", \"kbagchiGWC\", \"TehMillhouse\", \"dsych\", \"wayneadams\", \"KevinCooper\", \"dtchepak\", \"sebix\", \"LarryBattle\", \"mikl\", \"TuanNguyen27\", \"Sentimentron\", \"rtlee9\", \"sseidl88\", \"luntain\", \"bendoerr\", \"phillies\", \"SaumoPal97\", \"andresgottlieb\", \"buddhiv\", \"dribnet\", \"vrv\", \"dangsonbk\", \"ulido\", \"skervim\", \"XiaoshuiHuang\", \"martinwicke\", \"ricardoamaro\", \"DeqianBai\", \"ptaiga\", \"amitkgupta\", \"igorrocha\", \"vicramr\", \"salehjg\", \"yulequan\", \"nitinagarwal\", \"mexeniz\", \"joaoavf\", \"jaywinhuang\", \"jeasonstudio\", \"hyqskevin\", \"gceboh\", \"idf\", \"hugosoftdev\", \"ketanhwr\", \"Vincent-Vercruyssen\", \"mysteriouspants\", \"jpallen\", \"albahnsen\", \"advancedxy\", \"kailashahirwar\", \"xcodeburpx\", \"fperez\", \"justpic\", \"jselmani\", \"codedread\", \"ses4j\", \"alicoding\", \"cailurus\", \"EtienneBruines\", \"ZuzooVn\", \"jacksonlo\", \"shaoanlu\", \"sshekh\", \"luvegood\", \"acusti\", \"mingzhang96\", \"oneTaken\", \"Domon\", \"MarcelRobeer\", \"rsbohn\", \"idelgado\", \"dbarbier\", \"SubrataSarkar32\", \"fmder\", \"llSourcell\", \"peter-toth\", \"jgyllinsky\", \"rayeaster\", \"philippbayer\", \"alimon808\", \"Spandan-Madan\", \"sebg\", \"zhunzhong07\", \"zylix666\", \"vyper\", \"malfple\", \"joaopedronardari\", \"everping\", \"wtollett-usgs\", \"antmarakis\", \"xiaqunfeng\", \"bigsnarfdude\", \"McKenzyPG\", \"briansorahan\", \"bkm009\", \"tvogels\", \"rhiever\", \"hungphandinh92it\", \"kwichmann\", \"djoos\", \"sguada\", \"ari-schaffel\", \"Mrzhangxiaohua\", \"varan42\", \"SegFaultAX\", \"ebigelow\", \"PatrickZH\", \"volker48\", \"buddhikajay\", \"itzamna314\", \"optas\", \"angeladai\", \"UjjwalAryal\", \"jwasham\", \"yuanzhaoYZ\", \"matheusgmaia\", \"PBarmby\", \"shrutibhutaiya\", \"kwhinnery\", \"apatsekin\", \"GageAmes\", \"samedhaa\", \"xiuluo\", \"kyranb\", \"zlotus\", \"sagarcadet\", \"jwsy\", \"ismaeIfm\", \"knathanieltucker\", \"metrafonic\", \"praveenmylavarapu\", \"abarto\", \"srhrshr\", \"databaaz\", \"adpon\", \"Tirzono\", \"pdkovacs\", \"lupusomniator\", \"BokaiLIAN\", \"AlexZhou1995\", \"shaqian\", \"dimpurr\", \"beckgael\", \"libertatis\", \"curiousrohan\", \"benedictflorance\", \"optixlab\", \"voskresenskiy\", \"init27\", \"aymericdamien\", \"peter-parque\", \"victorhcm\", \"Dr-Zhou\", \"olivertomic\", \"elfelround\", \"katzien\", \"stephenturner\", \"DanBeard\", \"secretrobotron\", \"ghthor\", \"Vijayabhaskar96\", \"omo\", \"itailang\", \"cmacdonell\", \"gyoisamurai\", \"joybanerjee08\", \"gisikw\", \"elwinarens\", \"stnk20\", \"janismdhanbad\", \"timzhang642\", \"eccstartup\", \"RF-Nelson\", \"vishwajeetv\", \"ss52\", \"hetii\", \"mewben\", \"zldeng\", \"EdwardSmith1884\", \"MadhumitaSushil\", \"thesimanjan\", \"ReadmeCritic\", \"ktolstikhin\", \"DH-Diego\", \"flyingpot\", \"sailakshmi17\", \"Tarrasch\", \"RedstoneWill\", \"Metnew\", \"digital-thinking\", \"daz\", \"jackeylu\", \"gsenseless\", \"ecolell\", \"opie4624\", \"easezyc\", \"songuke\", \"K1t1k\", \"DanilBaibak\", \"thouis\", \"JustinJudd\", \"ssusnic\", \"twotabbies\", \"svntjng\", \"ploth\", \"zdgriffith\", \"nschor\", \"steven7851\", \"sedge\", \"nolith\", \"PrinzOwO\", \"Horaddrim\", \"lazywei\", \"kid1412z\", \"maximkeremet\", \"grayskripko\", \"jongoodnow\", \"jacarrico\", \"jiangf13\", \"imaness\", \"AJDBenner\", \"mkuhn\", \"HapeMask\", \"strange-jiong\", \"adityahiran\", \"sagardubey3\", \"jackmaney\", \"rieder91\", \"p1gd0g\", \"lukelafountaine\", \"art-programmer\", \"festline\", \"chrish42\", \"srayuws\", \"willalways\", \"nachocab\", \"maxnk\", \"Frenchhorn\", \"acabunoc\", \"qualityjacks\", \"habi\", \"TitouanT\", \"frozenkp\", \"pfsq\", \"AnshulBasia\", \"calberti\", \"PaulDebus\", \"agngrant\", \"mrtnbrst\", \"selimnairb\", \"tomraulet\", \"iamc\", \"trpapp\", \"EtienneT\", \"stieglma\", \"Diastro\", \"guedalia\", \"anuj1207\", \"cPolaris\", \"atinesh-s\", \"ivigamberdiev\", \"sdierauf\", \"itsliupeng\", \"krishnakumarsekar\", \"creinders\", \"vad4msiu\", \"koomar\", \"anzellai\", \"lisahdd007\", \"benedekrozemberczki\", \"jovilius\", \"avn3r\", \"selay01\", \"SarthakYadav\", \"zotroneneis\", \"mkeds\", \"DiegoCatalano\", \"tomassvensson\", \"ebenolson\", \"whughw\", \"pleabargain\", \"binilj04\", \"cako\", \"alg\", \"maxim5\", \"npbool\", \"JJ\", \"koriroys\", \"nektor211\", \"harenbergsd\", \"rogerzanoni\", \"nfmcclure\", \"jlar0che\", \"ilbuono\", \"hanpum\", \"ajkl\", \"LiberiFatali\", \"doppenhe\", \"gukoff\", \"kshs010239\", \"kadirpekel\", \"busterroni\", \"arc12\", \"timfrostmann\", \"rafalgrm\", \"AnkurDedania\", \"zhigang1992\", \"kevinkyyro\", \"Zhi-lin\", \"12wang3\", \"Microsheep\", \"mosew\", \"Gabriel-Azevedo-Ferreira\", \"shuhuai007\", \"hamelsmu\", \"czenzel\", \"marsben\", \"TwFlem\", \"TommyBark\", \"Karl-EdwardFPJeanMehu\", \"itsmeolivia\", \"alisezer\", \"omytryniuk\", \"daeyun\", \"drskd\", \"rachtsingh\", \"Borye\", \"KeniMorri\", \"rajasekharponakala\", \"derrg\", \"sinanuozdemir\", \"eeeeeric\", \"meawoppl\", \"Keiku\", \"daddou-ma\", \"mjschranz\", \"ujjwalkarn\", \"SeanPedersen\", \"cxxgtxy\", \"beroe\", \"aosama\", \"163-0533\", \"juliangarcia\", \"kinow\", \"wzell\", \"cezannec\", \"xkcao\", \"0asa\", \"Xyclade\", \"daanmichiels\", \"bon\", \"dmcc\", \"gcoter\", \"jaksmid\", \"mangei\", \"ReekenX\", \"zyc1gq\", \"jeff1evesque\", \"bkhaleghi\", \"JWarmenhoven\", \"havk64\", \"tncardoso\", \"triangeljs\", \"synapton\", \"wkentaro\", \"yhx5768\", \"scopatz\", \"iglpdc\", \"parkr\", \"Sea-n\", \"davidlowjw\", \"Nebula83\", \"kacper1095\", \"sckott\", \"bvonboyen\", \"JayJayBinks\", \"lxj616\", \"yarikoptic\", \"sys0613\", \"slcott\", \"zairah10\", \"demidovakatya\", \"Th30\", \"weakish\", \"elesueur\", \"Psimage\", \"willingc\", \"twigz20\", \"mgoldey\", \"TocarIP\", \"SumanthReddyKaliki\", \"JsonAC\", \"LiEmail\", \"harshnisar\", \"navdeep-G\", \"jvanlangen\", \"AkshayVarik\", \"flipace\", \"jakirkham\", \"Lax\", \"hanhdt\", \"finnigantime\", \"mgoodfellow\", \"jaraco\", \"daniel-kashin\", \"RandomArray\", \"acupofdata\", \"cameroncan\", \"hlkcrcck\", \"JasonGitHub\", \"rdingwall\", \"albertstill\", \"Ir1d\", \"mtchavez\", \"ThePhantomCoder\", \"HaveF\", \"eshizhan\", \"vargas\", \"liuluheng\", \"Kacawi\", \"jGaboardi\", \"josephmisiti\", \"Erotemic\", \"Liam-Yang\", \"An3bi\", \"axsaucedo\", \"fmichonneau\", \"frankhjwx\", \"rwdaigle\", \"NathanEpstein\", \"baogianghoangvu\", \"iory\", \"yangyyt\", \"crouchred\", \"girishkuniyal\", \"njern\", \"davidrhodus\", \"matt-jay\", \"saiabishek1\", \"gvwilson\", \"Airatiki\", \"eddyzhd\", \"pilif\", \"e173101\", \"jocelynlih\", \"adibis\", \"terrytangyuan\", \"lazyprogrammer\", \"thezillion\", \"leviding\", \"Borda\", \"ACharbonneau\", \"albertmolinermrf\", \"jakemcc\", \"chi-hung\", \"glemaitre\", \"waterson\", \"t-k-\", \"mandar2812\", \"synesthesiam\", \"drlabratory\", \"ambientlight\", \"tomahawk28\", \"herschel666\", \"DamienIrving\", \"vfdev-5\", \"pan-long\", \"MaxHalford\", \"fhs\", \"Adrien-Jecker\", \"m-maksyutin\", \"ivesn\", \"cpdj\", \"vallentin\", \"studiomohawk\", \"aoping\", \"polymeris\", \"individual8\", \"Nukesor\", \"nvh95\", \"QuLogic\", \"moutai\", \"vict0rsch\", \"ehrenfeu\", \"ericbuehl\", \"dubzzz\", \"mjpieters\", \"poyuwu\", \"csinva\", \"mikelogsdon\", \"samyag1\", \"BernhardKonrad\", \"umpox\", \"jdblischak\", \"kjappelbaum\", \"lxieyang\", \"Owen-Mak\", \"xuhdev\", \"rodgzilla\", \"jalateras\", \"robmarkcole\", \"jaymody\", \"gitbook-bot\", \"adamyala\", \"cdeil\", \"kuixu\", \"lstolcman\", \"Bachmann1234\", \"datamove\", \"timmartin19\", \"erjanmx\", \"swanson\", \"Jasonnor\", \"RaphaelMeudec\", \"JohnMcLear\", \"NeerajSarwan\", \"yurrriq\", \"credentiality\", \"yoavz\", \"monomagentaeggroll\", \"haraldschilly\", \"krother\", \"Digitalmobz\", \"x1957\", \"wking\", \"RickEyre\", \"benmccann\", \"kmscode\", \"apeeyush\", \"dogHere\", \"mappum\", \"kgashok\", \"fndjjx\", \"SamyPesse\", \"douglatornell\", \"fish2000\", \"okjake\", \"athiwatc\", \"schmich\", \"nbsantos\", \"brylie\", \"npanti\", \"zonca\", \"JamesLuoau\", \"hsiaoyi0504\", \"sudoes\", \"GLevV\", \"inejc\", \"IgorKovr\", \"iamaziz\", \"mindw\", \"arfon\", \"sjwhitworth\", \"polaris1119\", \"borodenkov\", \"warmheartli\", \"Alex1996a\", \"enjoyhot\", \"chneau\", \"4may\", \"hbaniecki\", \"aleju\", \"Pomax\", \"lsvih\", \"danyaljj\", \"rmarquis\", \"narisada014\", \"dnn37\", \"jsmith\", \"peterfabakker\", \"firebreath1001\", \"soulmachine\", \"phocks\", \"tgray\", \"PGijsbers\", \"curiousleo\", \"trekhleb\", \"guillaume-chevalier\", \"wqiancheng\", \"kersov\", \"matthewfeickert\", \"fatihbaltaci\", \"treyhunner\", \"denisarnaud\", \"postBG\", \"Ja1r0\", \"andrewda\", \"firmai\", \"ahnt\", \"masinoa\", \"frnsys\", \"dformoso\", \"sayakpaul\", \"MUSSONT\", \"SwarShah\", \"zzincubus\", \"ahmadia\", \"re4lfl0w\", \"jappre\", \"yeonjuan\", \"jrbourbeau\", \"pradeep1288\", \"Vay-keen\", \"ljpzzz\", \"robot-c0der\", \"sdsk\", \"Asterisk14\", \"LiLiu93\", \"RockySJ\", \"aaren\", \"shenyyi\", \"gauravcharnalia\", \"miksago\", \"YichenGong\", \"SiyuanQi\", \"JustFollowUs\", \"esztiorm\", \"pbharrin\", \"LukeArn\", \"jboy\", \"windpls\", \"jayrav13\", \"wsbmxa198700\", \"MdScntst\", \"nitin-tm\", \"junlulocky\", \"rahmanhafeezul\", \"tairiUdacity\", \"jasonbhart\", \"kennethjmyers\", \"seIncorp\", \"varshapaidi\", \"Asmolovskij\", \"JJLWHarrison\", \"ayakubovich\", \"Finance-781\", \"sudeepraja\", \"justramgerry\", \"pennyliang\", \"mollygibson\", \"K-LV\", \"RedditSota\", \"liliuleo\", \"omrimendels\", \"aathauck\", \"sirius999999\", \"Lincete\", \"eldaniz\", \"wenruimeng\", \"olveirap\", \"Budddy\", \"Devinsuit\", \"ecbc1\", \"mirjalil\", \"swlsw\", \"2y2simple\", \"acastrounis\", \"liuliu5151\", \"nyoung85\", \"alexnich\", \"cbuckey-uda\", \"oleksii-trekhleb-epam\", \"kzhk75\", \"willgroves\", \"rumi-naik\", \"vattay\", \"mkotov13\", \"yjh\", \"SusieXu\", \"AndrewLiesinger\", \"mikhailsergeevi4\", \"imhuay\", \"YoungMStudio\", \"alishutc\", \"IMWP\", \"mraje16\", \"flytomylife\", \"snowde\", \"itkinai\", \"jhashanti\", \"Pooch11\", \"tushargt\", \"LeeMaria007\", \"jogjayr\", \"cswef\", \"jkuchta\", \"wanzhenchn\", \"aquinasCode\", \"alexey-grigorev-sm\", \"amar00k\", \"bigwave\", \"nmb10\", \"testbounty\", \"andrewd76\", \"mahajani123\", \"Div44\", \"Tom-Ren\", \"josephmmisiti\", \"chrisadami\", \"coderfive\", \"wrichert\", \"deeper-learning\", \"afromanF\", \"qianguyizhe\", \"njojic\", \"alcidesv\", \"ankitkul\", \"serickso\", \"andsor\", \"adarsh0806\", \"YINCHENLI\", \"ExterminateWho\", \"SoumyadeepJana\", \"egorpolusmak\", \"KirillPanin\", \"Fatehsandhu\", \"testaccount553\", \"wepe\", \"Charismatron\", \"bob7783\", \"codingcai\", \"yonatanf\", \"chrissoulierserv\", \"maks-a\", \"mzk912778163\", \"jliddie\", \"brigham\", \"rajeshvaya\", \"tuantp7\", \"jmchen-g\", \"elkfrawy-df\", \"wang1211\", \"ilam\", \"YongshanKe\", \"KaiNieRus\", \"tuanphuc\", \"smbeli\", \"wla80\", \"AlexanderKunkel\", \"wenphan\", \"jackkuipers\", \"mkilavuz\", \"ronnierios\", \"bluewoodtree\", \"cmmalone\", \"moonboots\", \"zlu\", \"ntache\", \"lee709\", \"rohduggal\", \"scraggard\", \"awesome-bot\", \"grp-bork\", \"aniag\", \"run\", \"mmBabol\", \"ThatAndresV\", \"GordianStapf\", \"fangweili\", \"jared-weed\", \"hfanahita\", \"dear983604\", \"YJH1987\", \"qhfgva\", \"ShengKungYi\", \"irrationalRock\", \"engineeress\", \"ritabentodosreis\", \"APorterOReilly\", \"cratonica\", \"CookieDom\", \"Bruce-Feldman\", \"sun254\"], \"xaxis\": \"x\", \"y\": [999, 998, 995, 990, 977, 976, 975, 965, 965, 963, 953, 951, 949, 938, 937, 930, 925, 920, 920, 917, 915, 911, 901, 900, 873, 864, 859, 855, 853, 852, 851, 845, 842, 841, 826, 826, 824, 824, 820, 815, 797, 793, 784, 780, 780, 778, 775, 765, 761, 750, 746, 745, 744, 741, 737, 735, 733, 731, 724, 716, 715, 712, 708, 701, 699, 699, 691, 690, 689, 689, 680, 665, 664, 664, 659, 657, 657, 653, 648, 647, 629, 629, 627, 620, 618, 604, 601, 592, 592, 590, 588, 584, 581, 579, 578, 575, 570, 567, 564, 560, 553, 553, 553, 552, 547, 538, 538, 529, 524, 517, 517, 515, 515, 507, 504, 497, 495, 495, 494, 487, 485, 484, 482, 478, 477, 471, 468, 466, 465, 464, 460, 455, 455, 454, 453, 453, 451, 451, 444, 439, 438, 435, 431, 428, 425, 422, 422, 420, 416, 415, 414, 414, 411, 410, 405, 404, 404, 404, 403, 403, 402, 399, 398, 396, 393, 392, 392, 390, 390, 388, 388, 387, 385, 381, 378, 378, 377, 376, 373, 365, 364, 363, 363, 361, 360, 359, 358, 358, 357, 357, 355, 354, 352, 351, 347, 346, 344, 344, 342, 340, 337, 337, 333, 333, 331, 327, 327, 326, 322, 315, 314, 312, 311, 305, 304, 304, 303, 299, 299, 299, 298, 298, 295, 294, 293, 292, 289, 289, 288, 288, 287, 285, 282, 282, 280, 272, 270, 270, 268, 268, 266, 265, 264, 264, 262, 256, 254, 254, 251, 250, 248, 245, 241, 240, 239, 239, 239, 237, 231, 230, 227, 226, 226, 225, 225, 224, 223, 220, 219, 218, 216, 214, 213, 213, 212, 211, 211, 211, 210, 210, 209, 208, 199, 199, 198, 196, 196, 195, 195, 194, 190, 188, 188, 188, 186, 186, 186, 184, 183, 183, 182, 179, 179, 179, 177, 177, 177, 174, 173, 170, 168, 167, 166, 165, 164, 164, 164, 163, 163, 162, 161, 158, 158, 158, 157, 157, 156, 155, 154, 154, 154, 152, 152, 152, 151, 151, 151, 150, 149, 147, 147, 147, 145, 145, 144, 142, 142, 142, 142, 141, 141, 141, 140, 140, 137, 133, 132, 131, 130, 130, 130, 128, 128, 127, 125, 125, 123, 123, 123, 123, 121, 119, 119, 117, 116, 116, 115, 115, 114, 113, 113, 112, 111, 111, 108, 107, 107, 107, 107, 107, 106, 106, 105, 105, 105, 105, 105, 103, 102, 101, 101, 101, 100, 100, 99, 99, 97, 95, 94, 92, 91, 89, 89, 89, 89, 88, 88, 87, 85, 84, 83, 82, 82, 82, 82, 82, 82, 81, 79, 79, 79, 79, 79, 79, 79, 79, 78, 78, 77, 77, 77, 76, 76, 76, 76, 75, 73, 72, 72, 72, 71, 71, 70, 70, 68, 68, 68, 67, 67, 67, 67, 66, 66, 66, 66, 66, 65, 64, 64, 64, 63, 63, 63, 63, 63, 62, 62, 61, 61, 61, 60, 59, 58, 58, 58, 57, 57, 56, 56, 56, 56, 56, 55, 55, 54, 54, 54, 53, 53, 52, 52, 52, 52, 51, 51, 51, 49, 49, 49, 49, 49, 49, 49, 48, 48, 46, 46, 45, 45, 45, 45, 45, 44, 44, 44, 44, 44, 44, 43, 43, 42, 42, 42, 42, 42, 41, 41, 41, 41, 41, 41, 40, 40, 39, 38, 38, 38, 37, 36, 36, 36, 36, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 34, 34, 34, 33, 33, 33, 33, 33, 33, 33, 33, 32, 32, 32, 32, 31, 30, 30, 30, 29, 29, 28, 28, 28, 28, 27, 27, 27, 27, 27, 27, 27, 27, 27, 26, 26, 26, 26, 26, 26, 25, 25, 25, 25, 25, 25, 24, 24, 24, 24, 24, 23, 23, 22, 22, 22, 22, 21, 21, 21, 21, 21, 21, 21, 21, 20, 20, 20, 20, 19, 19, 19, 19, 19, 19, 18, 18, 18, 18, 18, 17, 17, 17, 17, 17, 17, 17, 16, 16, 16, 16, 16, 15, 15, 15, 15, 15, 15, 15, 14, 14, 14, 14, 14, 14, 14, 14, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 11, 11, 11, 11, 11, 11, 11, 11, 10, 10, 10, 10, 10, 10, 10, 10, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 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, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], \"yaxis\": \"y\"}], {\"barmode\": \"relative\", \"legend\": {\"tracegroupgap\": 0}, \"margin\": {\"t\": 60}, \"plot_bgcolor\": \"rgba(36, 83, 97, 0.06)\", \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"autotypenumbers\": \"strict\", \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"user_name\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"contribution\"}}}, {\"responsive\": true} ).then(function(){\n",
" \n",
"var gd = document.getElementById('0f7651e6-fd0b-4733-ada1-23fca63c4264');\n",
"var x = new MutationObserver(function (mutations, observer) {{\n",
" var display = window.getComputedStyle(gd).display;\n",
" if (!display || display === 'none') {{\n",
" console.log([gd, 'removed!']);\n",
" Plotly.purge(gd);\n",
" observer.disconnect();\n",
" }}\n",
"}});\n",
"\n",
"// Listen for the removal of the full notebook cells\n",
"var notebookContainer = gd.closest('#notebook-container');\n",
"if (notebookContainer) {{\n",
" x.observe(notebookContainer, {childList: true});\n",
"}}\n",
"\n",
"// Listen for the clearing of the current output cell\n",
"var outputEl = gd.closest('.output');\n",
"if (outputEl) {{\n",
" x.observe(outputEl, {childList: true});\n",
"}}\n",
"\n",
" }) }; </script> </div>\n",
"</body>\n",
"</html>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "kXk0bAbOWWiV"
},
"source": [
"## Correlation"
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:03:07.393790Z",
"start_time": "2020-08-14T21:03:07.337468Z"
},
"scrolled": true,
"colab": {
"base_uri": "https://localhost:8080/",
"height": 817
},
"id": "j8LAPpQGWWiV",
"outputId": "db44c26c-9605-4a8e-f64d-3c24808835b5"
},
"source": [
"correlation = px.scatter_matrix(new_profile, dimensions=['forks', 'total_stars', 'followers',\n",
" 'following', 'max_star','contribution'],\n",
" title='Correlation between datapoints',\n",
" width=800, height=800)\n",
"\n",
"correlation.show()\n",
"\n",
"figs.append(dp.Plot(correlation))"
],
"execution_count": 13,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<html>\n",
"<head><meta charset=\"utf-8\" /></head>\n",
"<body>\n",
" <div> <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script> <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
" <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script> <div id=\"de046e86-185c-4920-adf4-17018fdb5b3b\" class=\"plotly-graph-div\" style=\"height:800px; width:800px;\"></div> <script type=\"text/javascript\"> window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"de046e86-185c-4920-adf4-17018fdb5b3b\")) { Plotly.newPlot( \"de046e86-185c-4920-adf4-17018fdb5b3b\", [{\"dimensions\": [{\"axis\": {\"matches\": true}, \"label\": \"forks\", \"values\": [11857.0, 5091.0, 5644.0, 15633.0, 4985.0, 2109.0, 7738.0, 5471.0, 16723.0, 1228.0, 1952.0, 5169.0, 3937.0, 8498.0, 3389.0, 4985.0, 647.0, 742.0, 1313.0, 1223.0, 1069.0, 2507.0, 1211.0, 1249.0, 2136.0, 27168.0, 1254.0, 794.0, 4808.0, 5998.0, 4717.0, 677.0, 966.0, 2493.0, 2732.0, 2909.0, 1054.0, 439.0, 2335.0, 1426.0, 2088.0, 17562.0, 807.0, 619.0, 1936.0, 495.0, 394.0, 493.0, 1937.0, 462.0, 2361.0, 249.0, 338.0, 368.0, 683.0, 226.0, 549.0, 688.0, 793.0, 515.0, 1031.0, 3274.0, 1129.0, 1306.0, 5843.0, 1396.0, 2429.0, 2748.0, 3.0, 194.0, null, 1112.0, 58.0, 85.0, 73.0, 30.0, 6.0, 48.0, 27.0, 0.0, 496.0, 3.0, 18.0, null, 0.0, 2981.0, 19.0, 0.0, 97.0, 13.0, 0.0, 6.0, 5.0, null, 67.0, 97.0, 11.0, 144.0, 6.0, 159.0, 4.0, null, 0.0, 11.0, 169.0, 58.0, 6.0, 11.0, 209.0, 47.0, 287.0, 0.0, 191.0, 0.0, 2.0, 2105.0, 12.0, 21.0, 84.0, 34.0, null, 27.0, 1.0, 0.0, 0.0, 13.0, 50.0, 3.0, 23.0, 7.0, 0.0, 1.0, 1.0, 36.0, 11.0, 0.0, 142.0, 0.0, 0.0, 0.0, null, 38.0, 1.0, 5.0, 19.0, 17.0, null, 7.0, 83.0, 253.0, 0.0, 0.0, 124.0, 1.0, 5.0, 0.0, 5.0, 0.0, 0.0, 1.0, 10.0, 1.0, 45.0, 0.0, 78.0, 0.0, 37.0, 3.0, 0.0, 10.0, 6.0, 248.0, 0.0, 16.0, 1858.0, 1.0, 36.0, 7694.0, 10.0, 646.0, 74.0, 2.0, 47.0, 7.0, 0.0, 5.0, 1.0, 8.0, 24.0, 0.0, 12.0, 11.0, 7.0, 19.0, 5.0, 60.0, 141.0, 9.0, 0.0, 19.0, 6.0, 0.0, 35.0, 0.0, 176.0, 3.0, 0.0, 12.0, null, 10.0, 1338.0, 3.0, 4.0, 20.0, 34.0, 53.0, 7.0, 0.0, 1.0, 1.0, 0.0, 250.0, 5.0, 13.0, 81.0, 198.0, 1.0, 0.0, 0.0, 5.0, 26.0, 1.0, 0.0, 16.0, 19.0, 534.0, 4.0, 7.0, 45.0, null, 0.0, 185.0, 0.0, 2.0, 6.0, 0.0, null, 1.0, 0.0, 14.0, 0.0, 4.0, 0.0, 0.0, null, 22.0, null, 0.0, 630.0, 8.0, null, 143.0, 1.0, 0.0, 20.0, null, 10.0, 15.0, 425.0, 71.0, 74.0, 2.0, 3.0, 0.0, 0.0, 5.0, 706.0, 1.0, 2.0, 391.0, 1.0, 0.0, 0.0, 0.0, 36.0, 24.0, 243.0, 17.0, 1.0, 60.0, 12.0, 0.0, 77.0, 119.0, 2.0, 0.0, 56.0, 53.0, 8.0, 3.0, 49.0, 27.0, 8.0, 4.0, 22.0, 0.0, 0.0, 0.0, 222.0, 411.0, 25.0, 254.0, 21.0, 108.0, 1.0, 0.0, 6.0, 7.0, 112.0, 0.0, 0.0, null, 10.0, 0.0, 0.0, 3.0, 46.0, 12.0, 15.0, 102.0, 10.0, 3783.0, 13.0, null, 53.0, null, 30.0, 0.0, 6.0, 1.0, 1.0, 0.0, null, 58.0, 1.0, 0.0, 18.0, 33.0, 915.0, 0.0, 5.0, 6.0, null, 14.0, 2.0, 0.0, 72.0, 11.0, 0.0, 4.0, 7.0, 0.0, null, 5.0, 303.0, 0.0, 17.0, null, 44.0, null, 1.0, 61.0, 97.0, 4.0, 7.0, 8.0, 24.0, 6.0, 14.0, 170.0, 1.0, null, 12.0, 6.0, 150.0, 14.0, 0.0, 86.0, 21.0, 1.0, null, 24.0, 35.0, 25.0, 36.0, 23.0, 54.0, 120.0, 46.0, 1.0, 68.0, 49.0, 1.0, 0.0, 1145.0, 8.0, 4.0, null, 112.0, 45.0, null, 32.0, 12.0, 5.0, null, 219.0, 12.0, 108.0, 365.0, 81.0, 50.0, 22.0, 12.0, 14.0, null, 292.0, 55.0, null, 512.0, 19.0, 209.0, 393.0, 264.0, 0.0, 23.0, null, 4.0, 0.0, 0.0, 1.0, 3.0, 68.0, 2.0, 0.0, 8.0, 26.0, 56.0, 619.0, 76.0, null, 0.0, 1996.0, 59.0, 108.0, 0.0, 1.0, 4.0, 438.0, 0.0, 901.0, 16.0, 0.0, 3.0, 40.0, 166.0, 5.0, 0.0, 0.0, null, 39.0, 2.0, 167.0, 9.0, 0.0, 78.0, 0.0, 40.0, 39.0, 0.0, 12.0, 247.0, 14.0, 1.0, 26.0, 0.0, 3.0, 6.0, 1.0, 76.0, 96.0, 3.0, 43.0, 2634.0, 5.0, 71.0, 5.0, 2.0, 181.0, 25.0, 41.0, 4.0, 48.0, null, 2.0, 115.0, 0.0, 0.0, 0.0, 0.0, 159.0, 162.0, 0.0, null, null, 320.0, 8.0, 19.0, 0.0, 1.0, 15.0, 133.0, 0.0, 34.0, 2.0, 132.0, 2.0, 97.0, 42.0, 1.0, 76.0, 19.0, 0.0, 16.0, 10.0, 204.0, 1.0, 6.0, 3.0, 101.0, 18.0, 12.0, null, 0.0, 2.0, 26.0, 12.0, 4069.0, null, 4.0, 15.0, null, null, 1.0, 67.0, 0.0, 0.0, 103.0, 24.0, 0.0, 171.0, 6.0, 26.0, 81.0, 88.0, null, 2.0, 25.0, 28.0, 0.0, 6.0, 0.0, 80.0, 7.0, 0.0, 1.0, 14.0, 18.0, 40.0, 65.0, 3.0, 431.0, 0.0, 111.0, 47.0, null, 25.0, null, 40.0, 9.0, null, null, 9.0, 178.0, 8.0, 502.0, 5.0, 11.0, 13.0, 240.0, null, 0.0, null, 9.0, 0.0, 22.0, 4.0, 0.0, 25.0, 13.0, 214.0, null, 53.0, 9.0, 0.0, 46.0, 1131.0, 13.0, 17.0, null, 3.0, 1.0, 1.0, 0.0, 70.0, 0.0, 601.0, 66.0, 159.0, 2.0, 0.0, 5.0, 2.0, null, 351.0, 0.0, 4.0, 225.0, 0.0, 54.0, 0.0, 29.0, 0.0, 1.0, 0.0, null, 30.0, 7.0, 8.0, 1.0, 918.0, 32.0, 0.0, 8.0, 48.0, 24.0, null, 12.0, 14.0, 13.0, 146.0, 0.0, 0.0, 5.0, 0.0, 14.0, 4.0, 206.0, 66.0, 16.0, 0.0, 6.0, 0.0, 0.0, 0.0, 0.0, 0.0, 4.0, 0.0, 1.0, 0.0, 12.0, null, 3.0, 6.0, 121.0, 0.0, null, 45.0, 6.0, null, 0.0, 6.0, 110.0, 0.0, 24.0, 64.0, 55.0, 37.0, 29.0, 0.0, 17.0, 0.0, 69.0, 0.0, 0.0, null, 0.0, 5.0, 8.0, 0.0, 0.0, 3044.0, 55.0, 0.0, 187.0, 52.0, 4.0, 0.0, 59.0, 5.0, null, 1.0, 250.0, 6.0, 24.0, 25.0, 20.0, 78.0, 0.0, 129.0, 0.0, 7.0, 3.0, 0.0, 267.0, 241.0, 2652.0, 0.0, 28.0, 0.0, 6.0, 8.0, 34.0, 22.0, 14.0, 8.0, 333.0, 41.0, 2.0, 3.0, 8.0, 9.0, 1.0, 7.0, 74.0, 4.0, 23.0, 0.0, 3.0, 7.0, 896.0, 1.0, 5.0, 41.0, 5.0, 0.0, 0.0, 987.0, 56.0, 8.0, 5.0, 1.0, 16.0, 15.0, 8.0, 12.0, null, 15.0, 308.0, 129.0, 37828.0, 0.0, 8.0, 13.0, 31.0, 4.0, 0.0, 6.0, 0.0, 1.0, 0.0, 0.0, null, 0.0, 147.0, null, 1.0, 20.0, 1.0, 4.0, 883.0, null, 11.0, 10.0, 56.0, 77.0, 2.0, 0.0, 1.0, 20.0, 23.0, null, 11.0, 28.0, 52.0, 336.0, 1.0, null, 1.0, 10.0, 0.0, 8.0, null, 3.0, 6.0, 529.0, null, 8.0, 0.0, null, 6.0, 3.0, 10.0, 19.0, 95.0, 103.0, 0.0, 23.0, 7.0, 67.0, 7.0, 2.0, 66.0, 8.0, 14.0, 1.0, 15.0, 77.0, 15.0, 0.0, 14.0, null, 16.0, 28.0, 1.0, 0.0, 55.0, 1.0, 4.0, 0.0, 0.0, 43.0, 3.0, 2184.0, 26.0, 5.0, 327.0, 3.0, 4.0, 138.0, null, 0.0, 23.0, 0.0, 333.0, 96.0, 944.0, 57.0, 1.0, 60.0, 238.0, 231.0, null, 5.0, 456.0, 27.0, 17.0, 16.0, 32.0, 0.0, 8.0, 16.0, 0.0, 0.0, 3.0, 0.0, 11.0, 0.0, 31.0, null, 21.0, 93.0, 0.0, 5.0, 19.0, 3.0, 0.0, null, 60.0, 2.0, 85.0, 3.0, 0.0, 231.0, null, 1.0, 6.0, 50.0, null, 4.0, 14.0, 35.0, 20.0, 13.0, 1003.0, 1.0, 210.0, 1.0, 43.0, 24.0, 165.0, 0.0, 4.0, null, 0.0, 0.0, 278.0, 0.0, 1.0, 18.0, 43.0, 2.0, 50.0, 9.0, 2.0, 0.0, 1.0, 3.0, 20.0, 4.0, 1.0, null, 321.0, 472.0, 0.0, 2.0, 169.0, null, 3.0, 0.0, 5.0, 1.0, 1650.0, 224.0, 2.0, 0.0, 30.0, 0.0, 264.0, 45.0, 0.0, 0.0, 1.0, 24.0, 16.0, 20.0, 2.0, 2.0, 7.0, 1.0, 56.0, 15.0, 0.0, 1.0, 89.0, 14.0, 3.0, 7.0, 8.0, 5.0, 0.0, null, 8.0, 13.0, 35.0, 1.0, 9.0, 25.0, 9.0, 0.0, 119.0, null, null, 0.0, 1.0, 6.0, 1673.0, null, null, 16.0, 121.0, 0.0, 3.0, 2.0, 11.0, 30.0, 5.0, 0.0, 29.0, 72.0, null, 1.0, null, 3.0, 115.0, null, 21.0, 41.0, 2.0, 0.0, 1118.0, 0.0, 0.0, 1.0, 125.0, 7.0, 41.0, 2.0, 236.0, null, 0.0, 87.0, 15395.0, 1.0, 97.0, null, 0.0, 3.0, 516.0, 237.0, 2215.0, 155.0, 10.0, 46.0, 3.0, 202.0, null, 0.0, 1.0, null, 16.0, 2.0, 4.0, 69.0, 161.0, 0.0, 51.0, 1.0, 0.0, 36.0, 0.0, null, 1.0, 3.0, 31.0, 1.0, null, 12.0, null, 12.0, 159.0, 2.0, 0.0, 2.0, 103.0, null, 74.0, 11.0, 109.0, 96.0, 9.0, 3.0, 118.0, 11.0, 2.0, 1.0, 1.0, 17.0, 0.0, 28.0, 4.0, 147.0, 145.0, 12.0, 38.0, 8.0, 4.0, 0.0, 24.0, 8.0, 198.0, 0.0, 0.0, 1.0, null, null, null, 14.0, 160.0, 930.0, 4.0, 14.0, 37.0, 2.0, 21.0, 0.0, 0.0, 3.0, 43.0, null, 55.0, 19.0, 43.0, null, 134.0, 0.0, null, 3.0, 32.0, 12.0, 12.0, 3.0, 3855.0, 6.0, 19.0, 2368.0, 13.0, 0.0, 611.0, 15.0, 0.0, 11.0, 2.0, 0.0, 1.0, 53.0, 192.0, 0.0, 9.0, 134.0, 0.0, 232.0, 7.0, 4.0, 80.0, 2.0, null, 199.0, 28.0, 0.0, 1.0, 9.0, 3.0, 1.0, 1.0, 13.0, 1.0, 0.0, 0.0, 2.0, 1.0, 19.0, 16.0, 11.0, 2.0, 23.0, 1.0, 1.0, 0.0, 1.0, 172.0, 0.0, 77.0, 0.0, 1.0, 0.0, null, 103.0, 0.0, 154.0, 3.0, 120.0, 2.0, 144.0, 0.0, 95.0]}, {\"axis\": {\"matches\": true}, \"label\": \"total_stars\", \"values\": [46355.0, 7120.0, 23898.0, 47849.0, 5369.0, 3878.0, 15132.0, 16146.0, 96749.0, 4149.0, 10399.0, 4679.0, 16750.0, 125.0, 9633.0, 7777.0, 862.0, 1001.0, 4230.0, 5411.0, 2421.0, 8813.0, 4161.0, 2394.0, 10784.0, 56737.0, 6008.0, 3372.0, 14607.0, 20039.0, 13274.0, 3942.0, 1084.0, 4463.0, 7862.0, 4010.0, 7398.0, 1712.0, 4274.0, 2521.0, 6482.0, 45302.0, 5340.0, 1937.0, 4256.0, 1386.0, 616.0, 1607.0, 2401.0, 1446.0, 3590.0, 475.0, 219.0, 1505.0, 2780.0, 265.0, 1696.0, 2564.0, 5209.0, 585.0, 314.0, 13392.0, 5169.0, 3075.0, 8327.0, 8974.0, 5668.0, 13632.0, 2.0, 894.0, null, 4902.0, 326.0, 570.0, 234.0, 56.0, 8.0, 69.0, 130.0, 9.0, 1742.0, 1.0, 6.0, null, 2.0, 11023.0, 45.0, 0.0, 226.0, 16.0, 0.0, 0.0, 1.0, null, 105.0, 358.0, 24.0, 286.0, 17.0, 337.0, 5.0, null, 1.0, 44.0, 374.0, 269.0, 18.0, 29.0, 22.0, 144.0, 867.0, 3.0, 1248.0, 1.0, 0.0, 8476.0, 60.0, 57.0, 308.0, 80.0, null, 107.0, 4.0, 0.0, 0.0, 215.0, 68.0, 20.0, 107.0, 27.0, 1.0, 8.0, 0.0, 86.0, 11.0, 0.0, 205.0, 2.0, 3.0, 0.0, null, 4.0, 0.0, 7.0, 34.0, 98.0, null, 45.0, 352.0, 1015.0, 0.0, 0.0, 34.0, 13.0, 12.0, 0.0, 34.0, 0.0, 0.0, 1.0, 20.0, 1.0, 92.0, 0.0, 180.0, 1.0, 73.0, 0.0, 0.0, 20.0, 3.0, 346.0, 0.0, 16.0, 3581.0, 6.0, 19.0, 10176.0, 65.0, 1604.0, 80.0, 1.0, 67.0, 18.0, 0.0, 7.0, 9.0, 9.0, 27.0, 0.0, 16.0, 34.0, 11.0, 60.0, 4.0, 403.0, 1111.0, 11.0, 3.0, 70.0, 52.0, 0.0, 37.0, 1.0, 1155.0, 2.0, 0.0, 32.0, null, 13.0, 4420.0, 1.0, 9.0, 40.0, 58.0, 132.0, 9.0, 1.0, 1.0, 0.0, 0.0, 958.0, 4.0, 70.0, 175.0, 738.0, 17.0, 0.0, 0.0, 14.0, 62.0, 6.0, 0.0, 43.0, 95.0, 1504.0, 29.0, 17.0, 109.0, null, 0.0, 1419.0, 4.0, 7.0, 8.0, 0.0, null, 3.0, 0.0, 17.0, 0.0, 18.0, 0.0, 0.0, null, 98.0, null, 0.0, 8172.0, 15.0, null, 717.0, 0.0, 0.0, 54.0, null, 12.0, 65.0, 2276.0, 186.0, 175.0, 2.0, 35.0, 0.0, 0.0, 5.0, 5873.0, 5.0, 7.0, 2325.0, 78.0, 2.0, 0.0, 0.0, 40.0, 42.0, 1101.0, 37.0, 0.0, 131.0, 76.0, 1.0, 320.0, 394.0, 1.0, 0.0, 34.0, 123.0, 18.0, 9.0, 240.0, 85.0, 67.0, 3.0, 177.0, 0.0, 3.0, 19.0, 558.0, 2079.0, 154.0, 826.0, 109.0, 287.0, 0.0, 0.0, 1.0, 2.0, 725.0, 4.0, 0.0, null, 40.0, 0.0, 1.0, 7.0, 95.0, 6.0, 24.0, 362.0, 11.0, 11177.0, 30.0, null, 155.0, null, 3.0, 2.0, 5.0, 0.0, 1.0, 0.0, null, 266.0, 1.0, 0.0, 37.0, 61.0, 3489.0, 1.0, 0.0, 30.0, null, 58.0, 9.0, 1.0, 180.0, 22.0, 4.0, 19.0, 70.0, 8.0, null, 2.0, 1151.0, 0.0, 35.0, null, 204.0, null, 0.0, 693.0, 280.0, 6.0, 73.0, 7.0, 57.0, 9.0, 17.0, 481.0, 0.0, null, 27.0, 5.0, 565.0, 16.0, 5.0, 129.0, 98.0, 1.0, null, 56.0, 75.0, 50.0, 98.0, 146.0, 382.0, 283.0, 84.0, 2.0, 193.0, 39.0, 4.0, 0.0, 4405.0, 26.0, 5.0, null, 697.0, 194.0, null, 195.0, 28.0, 37.0, null, 604.0, 46.0, 782.0, 1818.0, 233.0, 76.0, 108.0, 36.0, 73.0, null, 681.0, 41.0, null, 2047.0, 37.0, 448.0, 841.0, 267.0, 0.0, 69.0, null, 13.0, 0.0, 10.0, 9.0, 0.0, 91.0, 12.0, 2.0, 12.0, 64.0, 271.0, 2349.0, 192.0, null, 0.0, 1796.0, 76.0, 306.0, 13.0, 1.0, 23.0, 2217.0, 0.0, 1048.0, 32.0, 0.0, 18.0, 84.0, 501.0, 16.0, 0.0, 2.0, null, 173.0, 4.0, 773.0, 54.0, 0.0, 319.0, 2.0, 80.0, 145.0, 0.0, 22.0, 567.0, 0.0, 3.0, 76.0, 0.0, 2.0, 55.0, 1.0, 235.0, 334.0, 12.0, 153.0, 33995.0, 14.0, 128.0, 18.0, 9.0, 251.0, 30.0, 196.0, 28.0, 444.0, null, 4.0, 313.0, 0.0, 0.0, 0.0, 1.0, 489.0, 836.0, 0.0, null, null, 757.0, 14.0, 70.0, 0.0, 7.0, 21.0, 519.0, 0.0, 35.0, 2.0, 819.0, 0.0, 498.0, 68.0, 4.0, 132.0, 138.0, 3.0, 58.0, 13.0, 904.0, 3.0, 2.0, 0.0, 1611.0, 44.0, 22.0, null, 0.0, 5.0, 83.0, 66.0, 22593.0, null, 38.0, 117.0, null, null, 0.0, 419.0, 0.0, 0.0, 604.0, 153.0, 10.0, 442.0, 12.0, 38.0, 126.0, 900.0, null, 0.0, 123.0, 24.0, 0.0, 11.0, 0.0, 353.0, 19.0, 0.0, 4.0, 40.0, 11.0, 135.0, 55.0, 0.0, 893.0, 0.0, 491.0, 119.0, null, 146.0, null, 122.0, 9.0, null, null, 6.0, 708.0, 9.0, 1080.0, 1.0, 67.0, 56.0, 560.0, null, 0.0, null, 19.0, 0.0, 41.0, 1.0, 0.0, 72.0, 64.0, 876.0, null, 293.0, 20.0, 0.0, 234.0, 4041.0, 30.0, 36.0, null, 0.0, 0.0, 1.0, 3.0, 292.0, 0.0, 1370.0, 111.0, 1163.0, 8.0, 9.0, 6.0, 1.0, null, 860.0, 1.0, 15.0, 300.0, 1.0, 71.0, 3.0, 113.0, 0.0, 4.0, 0.0, null, 53.0, 30.0, 39.0, 7.0, 4636.0, 94.0, 0.0, 7.0, 181.0, 28.0, null, 29.0, 4.0, 33.0, 703.0, 0.0, 2.0, 27.0, 0.0, 141.0, 12.0, 735.0, 171.0, 49.0, 1.0, 7.0, 1.0, 0.0, 1.0, 0.0, 12.0, 30.0, 0.0, 1.0, 0.0, 31.0, null, 7.0, 0.0, 575.0, 0.0, null, 57.0, 47.0, null, 0.0, 18.0, 576.0, 2.0, 49.0, 28.0, 149.0, 87.0, 9.0, 0.0, 56.0, 1.0, 9.0, 0.0, 2.0, null, 0.0, 12.0, 3.0, 0.0, 4.0, 9565.0, 283.0, 2.0, 805.0, 312.0, 14.0, 1.0, 19.0, 36.0, null, 0.0, 334.0, 10.0, 26.0, 120.0, 50.0, 33.0, 1.0, 696.0, 3.0, 8.0, 0.0, 1.0, 316.0, 2618.0, 14711.0, 0.0, 72.0, 2.0, 29.0, 30.0, 115.0, 88.0, 74.0, 32.0, 477.0, 254.0, 5.0, 4.0, 90.0, 6.0, 1.0, 8.0, 102.0, 2.0, 130.0, 0.0, 0.0, 24.0, 2309.0, 0.0, 12.0, 62.0, 4.0, 0.0, 0.0, 6732.0, 32.0, 18.0, 12.0, 10.0, 35.0, 18.0, 25.0, 37.0, null, 74.0, 1239.0, 202.0, 130077.0, 0.0, 14.0, 21.0, 162.0, 24.0, 1.0, 7.0, 0.0, 1.0, 0.0, 0.0, null, 0.0, 433.0, null, 7.0, 50.0, 3.0, 6.0, 3131.0, null, 7.0, 24.0, 124.0, 166.0, 1.0, 5.0, 0.0, 33.0, 14.0, null, 30.0, 104.0, 148.0, 1841.0, 2.0, null, 1.0, 10.0, 3.0, 29.0, null, 1.0, 1.0, 725.0, null, 46.0, 0.0, null, 17.0, 4.0, 17.0, 89.0, 441.0, 101.0, 6.0, 269.0, 4.0, 182.0, 14.0, 3.0, 51.0, 24.0, 144.0, 15.0, 43.0, 230.0, 4.0, 0.0, 143.0, null, 46.0, 50.0, 0.0, 0.0, 94.0, 5.0, 16.0, 1.0, 0.0, 92.0, 7.0, 7762.0, 160.0, 6.0, 1475.0, 0.0, 2.0, 137.0, null, 0.0, 99.0, 0.0, 1607.0, 123.0, 3766.0, 270.0, 17.0, 213.0, 523.0, 1000.0, null, 12.0, 2837.0, 53.0, 47.0, 7.0, 67.0, 0.0, 19.0, 10.0, 0.0, 0.0, 35.0, 1.0, 11.0, 0.0, 57.0, null, 30.0, 540.0, 0.0, 11.0, 36.0, 0.0, 7.0, null, 759.0, 0.0, 126.0, 19.0, 0.0, 672.0, null, 3.0, 3.0, 182.0, null, 3.0, 11.0, 142.0, 27.0, 16.0, 4147.0, 1.0, 301.0, 4.0, 161.0, 123.0, 954.0, 1.0, 0.0, null, 0.0, 1.0, 709.0, 0.0, 1.0, 56.0, 71.0, 44.0, 350.0, 11.0, 0.0, 0.0, 0.0, 2.0, 59.0, 8.0, 2.0, null, 1848.0, 1429.0, 2.0, 7.0, 1178.0, null, 38.0, 1.0, 6.0, 20.0, 6064.0, 1621.0, 10.0, 0.0, 37.0, 0.0, 771.0, 69.0, 0.0, 0.0, 44.0, 161.0, 117.0, 34.0, 3.0, 0.0, 11.0, 0.0, 53.0, 52.0, 0.0, 9.0, 200.0, 17.0, 31.0, 27.0, 11.0, 2.0, 0.0, null, 28.0, 69.0, 227.0, 6.0, 7.0, 39.0, 12.0, 0.0, 268.0, null, null, 5.0, 1.0, 4.0, 8074.0, null, null, 168.0, 244.0, 2.0, 2.0, 16.0, 30.0, 319.0, 9.0, 1.0, 2.0, 114.0, null, 0.0, null, 13.0, 250.0, null, 29.0, 163.0, 3.0, 3.0, 2751.0, 0.0, 0.0, 18.0, 94.0, 6.0, 39.0, 0.0, 592.0, null, 0.0, 86.0, 42975.0, 0.0, 361.0, null, 0.0, 16.0, 1848.0, 3428.0, 5915.0, 321.0, 4.0, 22.0, 11.0, 26.0, null, 0.0, 3.0, null, 104.0, 6.0, 3.0, 256.0, 348.0, 6.0, 107.0, 1.0, 0.0, 51.0, 0.0, null, 2.0, 4.0, 74.0, 5.0, null, 9.0, null, 17.0, 830.0, 0.0, 0.0, 5.0, 217.0, null, 209.0, 32.0, 262.0, 388.0, 7.0, 2.0, 509.0, 1.0, 1.0, 0.0, 0.0, 68.0, 0.0, 35.0, 14.0, 368.0, 369.0, 56.0, 32.0, 17.0, 18.0, 1.0, 49.0, 12.0, 649.0, 0.0, 0.0, 0.0, null, null, null, 30.0, 138.0, 4152.0, 19.0, 33.0, 41.0, 4.0, 50.0, 5.0, 1.0, 0.0, 58.0, null, 73.0, 178.0, 165.0, null, 596.0, 1.0, null, 1.0, 95.0, 22.0, 68.0, 2.0, 23371.0, 18.0, 9.0, 4405.0, 61.0, 29.0, 2289.0, 32.0, 3.0, 43.0, 8.0, 0.0, 9.0, 187.0, 322.0, 0.0, 15.0, 924.0, 18.0, 28.0, 42.0, 26.0, 852.0, 0.0, null, 665.0, 83.0, 0.0, 0.0, 7.0, 17.0, 6.0, 0.0, 30.0, 0.0, 0.0, 0.0, 0.0, 0.0, 9.0, 19.0, 42.0, 6.0, 49.0, 7.0, 5.0, 2.0, 3.0, 328.0, 1.0, 254.0, 1.0, 4.0, 6.0, null, 643.0, 0.0, 792.0, 11.0, 579.0, 2.0, 357.0, 1.0, 337.0]}, {\"axis\": {\"matches\": true}, \"label\": \"followers\", \"values\": [2495, 4508, 1192, 12725, 2809, 616, 2902, 1952, 4934, 192, 446, 2970, 1558, 45, 2355, 1222, 356, 247, 832, 389, 1083, 477, 3175, 1262, 840, 36270, 537, 985, 3046, 5884, 989, 493, 138, 1550, 5035, 1724, 291, 210, 1127, 602, 1470, 8184, 421, 315, 603, 287, 91, 235, 318, 119, 456, 362, 149, 62, 458, 45, 174, 529, 603, 74, 79, 658, 491, 544, 2859, 254, 381, 917, 6, 88, 18, 234, 138, 53, 69, 73, 21, 40, 10, 5, 354, 3, 11, 20, 4, 877, 16, 1, 94, 21, 21, 4, 18, 0, 563, 83, 21, 117, 41, 684, 9, 4, 4, 12, 58, 47, 27, 104, 22, 21, 707, 2, 112, 22, 6, 1311, 19, 13, 92, 36, 6, 53, 35, 14, 2, 16, 53, 9, 34, 16, 5, 3, 5, 64, 62, 5, 124, 0, 4, 5, 7, 0, 8, 2, 4, 10, 0, 95, 59, 175, 0, 5, 125, 3, 6, 0, 33, 14, 3, 5, 11, 6, 9, 14, 70, 31, 30, 2, 4, 9, 14, 54, 0, 20, 459, 1, 62, 5757, 16, 533, 67, 5, 10, 24, 8, 1, 28, 11, 25, 16, 24, 12, 5, 55, 2, 32, 54, 21, 7, 15, 51, 0, 71, 9, 174, 63, 20, 9, 0, 30, 1227, 4, 2, 92, 20, 70, 59, 0, 4, 13, 3, 1169, 15, 38, 111, 71, 12, 4, 16, 26, 29, 4, 0, 39, 22, 525, 11, 38, 17, 1, 4, 1521, 36, 31, 29, 20, 0, 3, 0, 162, 0, 7, 0, 2, 2, 68, 7, 24, 531, 44, 60, 96, 2, 1, 17, 0, 32, 94, 298, 73, 17, 71, 37, 5, 2, 63, 683, 13, 14, 433, 32, 2, 1, 0, 37, 30, 80, 50, 2, 21, 167, 16, 94, 43, 5, 12, 33, 308, 62, 16, 45, 35, 17, 3, 81, 9, 7, 14, 82, 238, 33, 463, 220, 287, 9, 0, 13, 36, 90, 9, 0, 1, 21, 11, 34, 18, 697, 23, 6, 50, 8, 5002, 26, 0, 120, 3, 40, 1, 20, 4, 8, 0, 0, 108, 11, 5, 66, 46, 286, 2, 4, 90, 0, 8, 2, 8, 37, 62, 5, 22, 59, 33, 0, 6, 154, 1, 19, 75, 44, 1, 1, 57, 292, 5, 22, 12, 73, 33, 5, 82, 0, 18, 23, 4, 143, 278, 15, 94, 522, 3, 0, 12, 67, 121, 99, 44, 529, 55, 159, 3, 40, 9, 3, 0, 439, 3, 26, 0, 50, 186, 1, 26, 29, 29, 1, 693, 194, 190, 185, 51, 41, 58, 3, 35, 1, 182, 62, 0, 410, 35, 103, 164, 189, 1, 32, 41, 12, 1, 12, 68, 3, 49, 37, 7, 21, 29, 94, 424, 6, 0, 0, 772, 21, 110, 0, 6, 3, 364, 7, 663, 2, 1, 13, 41, 36, 7, 1, 5, 1, 45, 12, 87, 22, 20, 7, 15, 36, 105, 0, 61, 451, 47, 1, 24, 2, 53, 12, 6, 192, 418, 0, 58, 858, 14, 116, 30, 9, 346, 35, 58, 92, 62, 0, 22, 55, 11, 12, 0, 1, 115, 243, 6, 13, 0, 54, 36, 90, 5, 84, 32, 137, 3, 66, 27, 200, 7, 61, 260, 12, 40, 29, 5, 30, 59, 737, 26, 3, 18, 105, 45, 2, 6, 1, 3, 26, 3, 5380, 0, 34, 32, 1, 0, 1, 541, 1, 4, 73, 29, 2, 97, 115, 9, 72, 62, 7, 1, 49, 159, 43, 20, 12, 99, 52, 1, 8, 20, 16, 26, 148, 0, 353, 10, 26, 19, 0, 27, 8, 53, 22, 3, 3, 12, 44, 9, 786, 2, 50, 130, 472, 0, 4, 0, 66, 1, 24, 4, 8, 23, 64, 870, 2, 39, 97, 4, 11, 460, 83, 20, 2, 4, 2, 29, 11, 556, 0, 281, 99, 244, 2, 5, 19, 3, 1, 624, 9, 72, 204, 1, 54, 0, 6, 0, 11, 4, 0, 48, 41, 5, 19, 1245, 12, 6, 22, 118, 26, 0, 61, 27, 3, 65, 1, 3, 42, 0, 50, 3, 383, 43, 21, 4, 21, 0, 8, 3, 21, 2, 49, 1, 2, 1, 37, 0, 10, 6, 92, 3, 0, 813, 21, 0, 1, 27, 346, 6, 80, 47, 36, 11, 10, 0, 14, 3, 20, 2, 0, 2, 2, 32, 22, 2, 5, 1657, 69, 39, 88, 37, 16, 0, 262, 48, 0, 12, 208, 33, 46, 218, 97, 123, 13, 351, 0, 3, 17, 2, 339, 201, 1742, 0, 54, 25, 26, 11, 197, 43, 17, 92, 273, 147, 15, 12, 25, 4, 8, 45, 143, 4, 54, 4, 8, 29, 191, 3, 25, 106, 12, 7, 0, 521, 204, 6, 12, 21, 15, 11, 24, 182, 0, 17, 185, 225, 9193, 3, 47, 39, 73, 28, 0, 17, 0, 2, 0, 1, 0, 0, 1938, 30, 13, 29, 1, 15, 417, 2, 6, 62, 140, 14, 9, 62, 2, 12, 58, 2, 47, 61, 31, 693, 5, 0, 5, 2, 12, 14, 0, 16, 9, 730, 33, 10, 3, 0, 53, 13, 5, 142, 180, 53, 10, 41, 4, 76, 19, 9, 36, 30, 19, 16, 19, 43, 9, 0, 14, 30, 28, 147, 6, 0, 52, 1, 34, 6, 6, 75, 4, 1235, 21, 33, 1287, 0, 5, 49, 3, 3, 47, 0, 244, 36, 174, 56, 18, 38, 97, 114, 0, 43, 928, 62, 64, 50, 50, 4, 18, 22, 0, 0, 54, 1, 35, 19, 61, 0, 193, 47, 9, 2, 42, 5, 0, 1, 45, 4, 58, 13, 0, 135, 0, 31, 34, 48, 0, 1, 19, 39, 6, 74, 2010, 4, 152, 34, 102, 49, 215, 22, 3, 7, 0, 0, 1631, 1, 21, 34, 37, 27, 172, 11, 5, 2, 0, 14, 37, 8, 3, 0, 241, 115, 3, 20, 449, 10, 12, 2, 10, 11, 863, 201, 3, 5, 14, 2, 430, 90, 0, 3, 388, 607, 121, 71, 2, 20, 47, 7, 62, 5, 0, 24, 100, 28, 41, 39, 24, 12, 0, 0, 19, 48, 29, 17, 12, 72, 1, 3, 55, 0, 34, 0, 4, 38, 188, 0, 0, 25, 62, 9, 363, 26, 44, 100, 24, 2, 6, 98, 0, 4, 1, 14, 170, 0, 8, 27, 53, 1, 1621, 0, 19, 6, 118, 21, 345, 3, 92, 5, 3, 235, 4589, 2, 216, 0, 6, 17, 257, 80, 612, 63, 6, 44, 39, 400, 3, 9, 3, 1, 25, 1, 11, 28, 94, 24, 66, 10, 22, 51, 7, 0, 29, 14, 80, 1, 1, 16, 1, 7, 118, 2, 2, 23, 55, 0, 20, 48, 78, 46, 43, 12, 252, 15, 3, 16, 0, 120, 2, 23, 51, 1348, 567, 14, 72, 20, 15, 23, 40, 23, 121, 4, 12, 4, 0, 0, 1, 24, 13, 406, 7, 17, 22, 10, 25, 52, 0, 7, 18, 2, 144, 221, 63, 17, 195, 4, 1, 10, 31, 20, 21, 5, 2461, 11, 21, 472, 27, 20, 606, 9, 30, 5, 82, 0, 5, 271, 172, 28, 42, 275, 16, 84, 8, 34, 157, 16, 0, 107, 532, 3, 1, 134, 3, 13, 5, 89, 25, 4, 3, 8, 16, 9, 7, 58, 33, 29, 58, 0, 4, 6, 254, 18, 71, 7, 5, 9, 1, 115, 17, 338, 6, 81, 1, 1104, 0, 33]}, {\"axis\": {\"matches\": true}, \"label\": \"following\", \"values\": [273, 47, 91, 33, 0, 48, 28, 224, 7, 0, 316, 68, 1, 86, 34, 19, 0, 7, 0, 26, 1, 10, 0, 44, 267, 4, 1, 20, 110, 35, 349, 3, 0, 5, 13, 0, 20, 0, 1, 13, 1, 17, 1, 2, 42, 0, 3, 13, 1, 22, 7, 0, 2, 0, 0, 11, 37, 9, 0, 9, 39, 19, 0, 5, 2, 0, 20, 0, 0, 136, 2, 4, 10, 60, 0, 98, 100, 30, 5, 1, 51, 0, 45, 38, 8, 7, 11, 3, 0, 20, 0, 6, 17, 0, 10, 234, 2, 26, 2, 9, 35, 0, 1, 21, 20, 17, 20, 258, 0, 12, 72, 3, 55, 0, 8, 25, 6, 6, 18, 11, 8, 25, 28, 17, 1, 20, 58, 20, 14, 15, 11, 14, 2, 8, 15, 5, 98, 1, 3, 3, 36, 0, 5, 1, 2, 0, 1, 157, 2, 0, 0, 7, 2, 3, 11, 0, 21, 5, 0, 23, 1, 9, 0, 42, 25, 14, 34, 2, 5, 2, 30, 16, 0, 57, 47, 0, 17, 0, 25, 53, 34, 0, 32, 14, 4, 2, 44, 7, 8, 53, 3, 1, 3, 56, 0, 45, 0, 4, 48, 0, 122, 0, 8, 13, 19, 646, 3, 5, 0, 30, 437, 0, 11, 0, 2, 0, 0, 2, 0, 27, 1, 269, 15, 10, 1, 1, 8, 3, 3, 14, 3, 2, 0, 25, 14, 2, 0, 57, 27, 0, 4, 714, 63, 77, 23, 13, 0, 2, 2, 67, 0, 10, 0, 1, 2, 171, 4, 79, 4, 47, 0, 1, 9, 1, 37, 0, 4, 8, 9, 62, 3, 70, 34, 3, 0, 60, 23, 15, 42, 248, 2, 14, 2, 5, 11, 13, 1, 33, 1, 18, 495, 0, 12, 27, 8, 86, 53, 138, 1, 25, 0, 26, 1, 1, 29, 10, 4, 3, 0, 4, 21, 111, 214, 26, 34, 0, 10, 33, 0, 23, 0, 0, 76, 6, 50, 9, 6, 0, 47, 1, 10, 415, 105, 0, 53, 0, 11, 5, 45, 1, 10, 0, 0, 628, 8, 3, 80, 0, 153, 0, 28, 84, 0, 0, 4, 27, 13, 76, 6, 79, 57, 36, 0, 2, 68, 1, 12, 0, 22, 0, 1, 78, 85, 7, 9, 0, 27, 21, 3, 25, 10, 1, 15, 11, 83, 5, 14, 0, 7, 1, 0, 2, 78, 1, 93, 70, 3, 0, 19, 4, 43, 4, 1, 1, 61, 3, 46, 0, 4, 0, 1, 98, 24, 105, 0, 0, 53, 55, 169, 60, 19, 4, 2, 10, 1, 0, 0, 0, 269, 59, 15, 73, 39, 2, 0, 21, 0, 1, 5, 424, 22, 1, 75, 62, 0, 10, 11, 0, 3, 0, 0, 144, 11, 179, 0, 1, 11, 110, 2, 48, 9, 0, 12, 7, 31, 1, 2, 7, 0, 53, 26, 34, 18, 19, 2, 19, 25, 39, 0, 93, 2, 4, 1, 2, 0, 44, 18, 7, 164, 0, 0, 52, 25, 153, 15, 371, 10, 145, 5, 12, 17, 12, 0, 39, 21, 10, 9, 4, 0, 47, 33, 13, 0, 0, 4, 0, 73, 13, 130, 391, 6, 1, 110, 4, 74, 6, 1, 10, 29, 90, 99, 9, 4, 61, 122, 10, 1, 0, 77, 102, 0, 0, 0, 2, 1, 0, 2, 0, 301, 61, 0, 0, 1, 164, 0, 0, 144, 36, 0, 12, 2, 1, 64, 6, 0, 0, 11, 50, 11, 67, 16, 25, 25, 7, 31, 85, 11, 5, 14, 0, 265, 5, 0, 6, 0, 0, 1, 62, 94, 27, 9, 25, 3, 39, 1, 1, 5, 42, 315, 0, 1, 0, 165, 1, 18, 7, 3, 32, 269, 12, 0, 6, 541, 0, 0, 11, 67, 8, 2, 8, 3, 2, 4, 222, 1, 38, 199, 80, 2, 3, 50, 6, 0, 74, 1, 212, 88, 0, 57, 0, 0, 0, 4, 0, 0, 29, 3, 0, 22, 99, 1, 2, 18, 3, 5, 0, 3, 7, 0, 22, 0, 7, 28, 0, 140, 6, 28, 5, 14, 7, 0, 0, 18, 2, 46, 1, 108, 0, 0, 0, 25, 0, 0, 12, 35, 0, 0, 275, 4, 0, 0, 45, 0, 4, 93, 3, 33, 3, 1, 0, 13, 5, 0, 15, 0, 0, 13, 45, 6, 5, 8, 18, 351, 66, 1, 35, 3, 0, 0, 191, 0, 26, 0, 36, 4, 94, 98, 66, 12, 48, 0, 19, 0, 0, 152, 0, 33, 4, 0, 61, 23, 26, 143, 49, 0, 215, 1, 242, 0, 6, 29, 26, 8, 61, 43, 6, 89, 2, 7, 0, 10, 2, 46, 42, 16, 7, 2, 0, 13, 0, 3, 0, 22, 9, 9, 367, 0, 8, 43, 133, 6, 4, 260, 4, 73, 37, 0, 79, 0, 0, 0, 1, 0, 0, 124, 2, 3, 6, 8, 16, 45, 0, 3, 112, 38, 10, 6, 5, 1, 8, 13, 0, 33, 61, 47, 28, 4, 0, 21, 15, 0, 11, 0, 13, 6, 29, 60, 0, 6, 5, 108, 37, 3, 2, 12, 0, 4, 32, 0, 19, 49, 11, 1, 4, 59, 41, 4, 0, 19, 0, 30, 0, 5, 390, 82, 1, 3, 1, 48, 0, 19, 106, 6, 329, 10, 48, 522, 1, 5, 20, 5, 3, 3, 1, 402, 2, 17, 9, 7, 15, 3, 250, 1, 20, 22, 14, 4, 35, 67, 16, 3, 0, 4, 0, 24, 1, 27, 74, 0, 0, 3, 1, 4, 2, 11, 0, 1, 0, 26, 14, 3, 9, 0, 3, 1, 31, 49, 15, 0, 2, 31, 2, 9, 6, 29, 1, 18, 268, 351, 220, 173, 27, 3, 3, 0, 0, 10, 5, 6, 5, 23, 28, 80, 5, 6, 10, 3, 32, 28, 32, 0, 0, 13, 10, 5, 21, 30, 16, 4, 0, 5, 23, 162, 23, 2, 2, 2, 7, 28, 16, 0, 3, 1, 1141, 155, 36, 0, 2, 29, 4, 200, 3, 0, 53, 32, 363, 46, 17, 170, 4, 0, 0, 4, 18, 120, 32, 2, 38, 2, 0, 5, 1, 0, 0, 7, 101, 52, 0, 0, 43, 17, 1, 0, 28, 76, 26, 47, 0, 0, 15, 0, 4, 0, 54, 25, 0, 5, 6, 16, 2, 0, 3, 34, 12, 0, 122, 31, 6, 9, 0, 30, 25, 28, 14, 9, 0, 19, 0, 545, 0, 16, 96, 0, 28, 251, 4, 0, 2, 2, 37, 4, 3, 8, 0, 230, 50, 70, 24, 9, 0, 3, 0, 10, 35, 93, 0, 1, 5, 0, 1, 4, 4, 0, 6, 21, 0, 25, 28, 21, 11, 13, 25, 1, 0, 3, 12, 0, 0, 0, 5, 95, 0, 7, 53, 72, 64, 27, 54, 87, 1, 146, 5, 3, 0, 0, 0, 3, 81, 13, 163, 18, 2, 15, 6, 5, 28, 8, 2, 30, 0, 1419, 16, 14, 60, 14, 4, 0, 8, 85, 27, 8, 0, 1, 7, 2, 57, 36, 0, 18, 0, 5, 16, 1032, 1, 7, 10, 9, 58, 83, 99, 15, 5, 10, 148, 46, 34, 0, 2, 3, 1, 0, 255, 1, 30, 0, 155, 53, 2, 4, 0, 0, 3, 3, 39, 39, 0, 279, 0, 1, 4, 265, 6, 35, 12, 12, 0, 0, 467, 28, 51, 0, 25, 5, 0, 0, 40]}, {\"axis\": {\"matches\": true}, \"label\": \"max_star\", \"values\": [45243.0, 3811.0, 23893.0, 12707.0, 5193.0, 3085.0, 10865.0, 10402.0, 74060.0, 4097.0, 10014.0, 2435.0, 10618.0, 120.0, 5492.0, 6993.0, 841.0, 694.0, 2755.0, 5319.0, 1921.0, 8782.0, 3966.0, 2373.0, 5229.0, 7315.0, 4465.0, 3358.0, 8540.0, 9595.0, 13268.0, 3139.0, 1077.0, 1337.0, 4728.0, 1533.0, 7249.0, 1624.0, 4274.0, 2020.0, 4645.0, 17632.0, 4852.0, 1141.0, 2092.0, 1341.0, 593.0, 1442.0, 2104.0, 1349.0, 2360.0, 460.0, 207.0, 1488.0, 1401.0, 225.0, 1220.0, 1723.0, 4044.0, 575.0, 297.0, 13367.0, 4809.0, 2045.0, 3170.0, 8974.0, 5607.0, 9436.0, 2.0, 823.0, null, 3482.0, 94.0, 309.0, 47.0, 41.0, 3.0, 34.0, 103.0, 5.0, 471.0, 1.0, 3.0, null, 1.0, 9451.0, 39.0, 0.0, 149.0, 9.0, 0.0, 0.0, 1.0, null, 58.0, 263.0, 14.0, 99.0, 6.0, 270.0, 3.0, null, 1.0, 43.0, 116.0, 199.0, 6.0, 8.0, 13.0, 50.0, 414.0, 1.0, 853.0, 1.0, 0.0, 6889.0, 27.0, 32.0, 85.0, 48.0, null, 60.0, 1.0, 0.0, 0.0, 201.0, 33.0, 8.0, 94.0, 23.0, 1.0, 6.0, 0.0, 34.0, 6.0, 0.0, 145.0, 1.0, 3.0, 0.0, null, 4.0, 0.0, 4.0, 34.0, 98.0, null, 18.0, 154.0, 589.0, 0.0, 0.0, 18.0, 12.0, 3.0, 0.0, 12.0, 0.0, 0.0, 1.0, 8.0, 1.0, 92.0, 0.0, 58.0, 1.0, 37.0, 0.0, 0.0, 11.0, 3.0, 166.0, 0.0, 4.0, 3367.0, 3.0, 11.0, 2909.0, 39.0, 1228.0, 56.0, 1.0, 53.0, 3.0, 0.0, 6.0, 4.0, 9.0, 23.0, 0.0, 15.0, 33.0, 9.0, 12.0, 3.0, 214.0, 836.0, 2.0, 1.0, 42.0, 16.0, 0.0, 12.0, 1.0, 852.0, 1.0, 0.0, 28.0, null, 6.0, 2100.0, 1.0, 8.0, 28.0, 38.0, 68.0, 4.0, 1.0, 1.0, 0.0, 0.0, 148.0, 3.0, 27.0, 60.0, 337.0, 11.0, 0.0, 0.0, 10.0, 23.0, 2.0, 0.0, 24.0, 28.0, 1112.0, 13.0, 4.0, 43.0, null, 0.0, 760.0, 4.0, 3.0, 3.0, 0.0, null, 2.0, 0.0, 5.0, 0.0, 9.0, 0.0, 0.0, null, 55.0, null, 0.0, 6496.0, 4.0, null, 705.0, 0.0, 0.0, 18.0, null, 5.0, 8.0, 1257.0, 123.0, 132.0, 2.0, 14.0, 0.0, 0.0, 4.0, 1887.0, 3.0, 6.0, 578.0, 78.0, 1.0, 0.0, 0.0, 26.0, 29.0, 711.0, 14.0, 0.0, 129.0, 17.0, 1.0, 200.0, 228.0, 1.0, 0.0, 28.0, 84.0, 3.0, 1.0, 126.0, 85.0, 35.0, 1.0, 43.0, 0.0, 2.0, 17.0, 558.0, 911.0, 48.0, 381.0, 42.0, 153.0, 0.0, 0.0, 1.0, 1.0, 526.0, 2.0, 0.0, null, 39.0, 0.0, 1.0, 3.0, 24.0, 4.0, 23.0, 328.0, 7.0, 5353.0, 29.0, null, 40.0, null, 1.0, 1.0, 2.0, 0.0, 1.0, 0.0, null, 59.0, 1.0, 0.0, 11.0, 26.0, 3234.0, 1.0, 0.0, 7.0, null, 20.0, 7.0, 1.0, 125.0, 4.0, 2.0, 16.0, 19.0, 5.0, null, 2.0, 323.0, 0.0, 9.0, null, 50.0, null, 0.0, 682.0, 86.0, 4.0, 59.0, 3.0, 25.0, 4.0, 8.0, 317.0, 0.0, null, 5.0, 4.0, 132.0, 7.0, 3.0, 35.0, 70.0, 1.0, null, 26.0, 17.0, 14.0, 26.0, 131.0, 108.0, 230.0, 48.0, 1.0, 112.0, 17.0, 2.0, 0.0, 3652.0, 24.0, 5.0, null, 488.0, 38.0, null, 81.0, 12.0, 33.0, null, 265.0, 16.0, 576.0, 961.0, 86.0, 40.0, 89.0, 36.0, 15.0, null, 465.0, 15.0, null, 1750.0, 11.0, 429.0, 176.0, 25.0, 0.0, 42.0, null, 9.0, 0.0, 7.0, 5.0, 0.0, 24.0, 5.0, 2.0, 5.0, 29.0, 190.0, 1726.0, 192.0, null, 0.0, 1607.0, 44.0, 77.0, 10.0, 1.0, 11.0, 680.0, 0.0, 204.0, 22.0, 0.0, 9.0, 47.0, 359.0, 6.0, 0.0, 2.0, null, 41.0, 3.0, 195.0, 19.0, 0.0, 248.0, 1.0, 60.0, 82.0, 0.0, 13.0, 343.0, 0.0, 2.0, 68.0, 0.0, 1.0, 32.0, 1.0, 168.0, 119.0, 12.0, 133.0, 33777.0, 3.0, 46.0, 5.0, 2.0, 99.0, 29.0, 113.0, 28.0, 332.0, null, 2.0, 99.0, 0.0, 0.0, 0.0, 1.0, 357.0, 260.0, 0.0, null, null, 713.0, 5.0, 33.0, 0.0, 2.0, 12.0, 279.0, 0.0, 22.0, 2.0, 271.0, 0.0, 351.0, 10.0, 2.0, 61.0, 136.0, 2.0, 29.0, 6.0, 205.0, 1.0, 1.0, 0.0, 1434.0, 29.0, 17.0, null, 0.0, 4.0, 42.0, 40.0, 7324.0, null, 3.0, 88.0, null, null, 0.0, 314.0, 0.0, 0.0, 169.0, 134.0, 5.0, 420.0, 11.0, 33.0, 94.0, 587.0, null, 0.0, 55.0, 6.0, 0.0, 7.0, 0.0, 259.0, 12.0, 0.0, 1.0, 22.0, 4.0, 35.0, 29.0, 0.0, 356.0, 0.0, 369.0, 115.0, null, 45.0, null, 31.0, 7.0, null, null, 4.0, 701.0, 2.0, 640.0, 1.0, 57.0, 17.0, 173.0, null, 0.0, null, 16.0, 0.0, 39.0, 1.0, 0.0, 31.0, 54.0, 388.0, null, 182.0, 5.0, 0.0, 122.0, 2760.0, 15.0, 32.0, null, 0.0, 0.0, 1.0, 1.0, 88.0, 0.0, 514.0, 38.0, 483.0, 3.0, 6.0, 2.0, 1.0, null, 302.0, 1.0, 7.0, 66.0, 1.0, 35.0, 3.0, 34.0, 0.0, 4.0, 0.0, null, 24.0, 28.0, 37.0, 2.0, 2586.0, 37.0, 0.0, 2.0, 71.0, 14.0, null, 24.0, 1.0, 26.0, 638.0, 0.0, 1.0, 11.0, 0.0, 104.0, 10.0, 333.0, 67.0, 23.0, 1.0, 3.0, 1.0, 0.0, 1.0, 0.0, 6.0, 14.0, 0.0, 1.0, 0.0, 21.0, null, 6.0, 0.0, 299.0, 0.0, null, 12.0, 21.0, null, 0.0, 14.0, 184.0, 1.0, 44.0, 6.0, 113.0, 63.0, 4.0, 0.0, 43.0, 1.0, 7.0, 0.0, 2.0, null, 0.0, 6.0, 2.0, 0.0, 1.0, 1728.0, 74.0, 2.0, 688.0, 247.0, 10.0, 1.0, 18.0, 17.0, null, 0.0, 86.0, 6.0, 11.0, 60.0, 21.0, 7.0, 1.0, 195.0, 2.0, 4.0, 0.0, 1.0, 82.0, 526.0, 3605.0, 0.0, 25.0, 1.0, 23.0, 26.0, 47.0, 42.0, 47.0, 10.0, 156.0, 175.0, 3.0, 4.0, 57.0, 3.0, 1.0, 8.0, 16.0, 2.0, 61.0, 0.0, 0.0, 13.0, 2108.0, 0.0, 3.0, 13.0, 3.0, 0.0, 0.0, 1638.0, 9.0, 6.0, 8.0, 10.0, 11.0, 11.0, 7.0, 6.0, null, 73.0, 919.0, 82.0, 123514.0, 0.0, 6.0, 12.0, 57.0, 11.0, 1.0, 2.0, 0.0, 1.0, 0.0, 0.0, null, 0.0, 162.0, null, 2.0, 26.0, 3.0, 3.0, 2191.0, null, 7.0, 5.0, 65.0, 86.0, 1.0, 2.0, 0.0, 28.0, 8.0, null, 21.0, 42.0, 144.0, 361.0, 2.0, null, 1.0, 9.0, 3.0, 8.0, null, 1.0, 1.0, 146.0, null, 35.0, 0.0, null, 8.0, 2.0, 8.0, 83.0, 189.0, 45.0, 4.0, 225.0, 4.0, 54.0, 8.0, 3.0, 26.0, 5.0, 130.0, 8.0, 12.0, 159.0, 2.0, 0.0, 71.0, null, 29.0, 23.0, 0.0, 0.0, 73.0, 2.0, 3.0, 1.0, 0.0, 25.0, 6.0, 4975.0, 131.0, 3.0, 493.0, 0.0, 2.0, 86.0, null, 0.0, 42.0, 0.0, 1131.0, 65.0, 2222.0, 140.0, 3.0, 170.0, 227.0, 510.0, null, 4.0, 1217.0, 11.0, 40.0, 2.0, 28.0, 0.0, 19.0, 4.0, 0.0, 0.0, 9.0, 1.0, 3.0, 0.0, 19.0, null, 21.0, 185.0, 0.0, 4.0, 26.0, 0.0, 5.0, null, 567.0, 0.0, 53.0, 10.0, 0.0, 303.0, null, 2.0, 1.0, 161.0, null, 2.0, 6.0, 114.0, 7.0, 13.0, 1257.0, 1.0, 95.0, 3.0, 147.0, 122.0, 176.0, 1.0, 0.0, null, 0.0, 1.0, 638.0, 0.0, 1.0, 21.0, 59.0, 40.0, 111.0, 6.0, 0.0, 0.0, 0.0, 2.0, 24.0, 7.0, 2.0, null, 963.0, 453.0, 2.0, 3.0, 1041.0, null, 34.0, 1.0, 3.0, 10.0, 2611.0, 1052.0, 4.0, 0.0, 4.0, 0.0, 679.0, 26.0, 0.0, 0.0, 44.0, 48.0, 43.0, 14.0, 3.0, 0.0, 4.0, 0.0, 45.0, 33.0, 0.0, 6.0, 71.0, 2.0, 9.0, 22.0, 6.0, 2.0, 0.0, null, 26.0, 18.0, 176.0, 4.0, 6.0, 19.0, 10.0, 0.0, 242.0, null, null, 3.0, 1.0, 4.0, 4529.0, null, null, 29.0, 107.0, 2.0, 1.0, 7.0, 5.0, 248.0, 6.0, 1.0, 1.0, 114.0, null, 0.0, null, 13.0, 43.0, null, 18.0, 74.0, 1.0, 1.0, 1828.0, 0.0, 0.0, 13.0, 23.0, 3.0, 16.0, 0.0, 317.0, null, 0.0, 44.0, 38070.0, 0.0, 85.0, null, 0.0, 6.0, 701.0, 2285.0, 3394.0, 90.0, 1.0, 10.0, 3.0, 6.0, null, 0.0, 1.0, null, 48.0, 2.0, 2.0, 52.0, 266.0, 1.0, 44.0, 1.0, 0.0, 16.0, 0.0, null, 2.0, 1.0, 72.0, 5.0, null, 7.0, null, 10.0, 376.0, 0.0, 0.0, 1.0, 118.0, null, 105.0, 18.0, 252.0, 113.0, 5.0, 1.0, 188.0, 1.0, 1.0, 0.0, 0.0, 25.0, 0.0, 17.0, 12.0, 268.0, 121.0, 51.0, 14.0, 10.0, 10.0, 1.0, 18.0, 10.0, 315.0, 0.0, 0.0, 0.0, null, null, null, 8.0, 110.0, 3171.0, 14.0, 6.0, 16.0, 2.0, 27.0, 3.0, 1.0, 0.0, 27.0, null, 47.0, 37.0, 165.0, null, 143.0, 1.0, null, 1.0, 70.0, 16.0, 43.0, 2.0, 18842.0, 13.0, 5.0, 3075.0, 49.0, 26.0, 1209.0, 27.0, 1.0, 33.0, 2.0, 0.0, 2.0, 49.0, 122.0, 0.0, 8.0, 384.0, 13.0, 12.0, 41.0, 7.0, 447.0, 0.0, null, 509.0, 64.0, 0.0, 0.0, 2.0, 17.0, 5.0, 0.0, 6.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.0, 19.0, 20.0, 2.0, 10.0, 3.0, 4.0, 1.0, 2.0, 74.0, 1.0, 230.0, 1.0, 2.0, 3.0, null, 449.0, 0.0, 396.0, 3.0, 387.0, 1.0, 110.0, 1.0, 316.0]}, {\"axis\": {\"matches\": true}, \"label\": \"contribution\", \"values\": [2, 0, 55, 745, 2, 79, 131, 6, 1, 0, 392, 116, 100, 517, 377, 270, 689, 196, 0, 25, 21, 216, 152, 150, 1, 49, 1, 7, 1, 977, 282, 10, 6, 949, 43, 154, 1, 108, 0, 431, 1, 130, 990, 388, 627, 289, 1, 11, 0, 44, 4, 0, 147, 19, 311, 15, 67, 578, 48, 12, 128, 58, 708, 35, 793, 0, 9, 1, 10, 1, 3, 901, 975, 468, 2, 186, 107, 2, 35, 140, 46, 142, 89, 162, 0, 112, 5, 3, 9, 553, 0, 72, 78, 0, 1, 575, 212, 387, 1, 91, 28, 0, 0, 24, 67, 451, 4, 239, 95, 963, 7, 618, 1, 18, 1, 1, 842, 158, 76, 0, 9, 1, 864, 26, 14, 0, 1, 322, 79, 1, 4, 152, 158, 1, 925, 0, 3, 0, 2, 359, 0, 0, 22, 3, 0, 27, 0, 254, 24, 494, 1, 0, 1, 288, 53, 3, 592, 8, 0, 154, 19, 2, 0, 1, 219, 35, 24, 9, 9, 1, 0, 294, 0, 11, 378, 4, 504, 188, 21, 3, 5, 0, 21, 102, 3, 32, 54, 1, 227, 78, 20, 10, 403, 0, 33, 299, 1, 298, 264, 1, 27, 0, 99, 1, 744, 538, 79, 17, 4, 337, 405, 0, 31, 1, 8, 214, 404, 33, 1, 58, 0, 4, 13, 188, 1, 166, 859, 66, 8, 5, 199, 157, 0, 570, 186, 27, 82, 256, 517, 0, 305, 741, 9, 553, 4, 36, 186, 9, 16, 56, 5, 6, 0, 8, 9, 210, 0, 2, 357, 264, 23, 815, 0, 42, 1, 0, 173, 390, 731, 41, 211, 360, 393, 0, 0, 1, 344, 35, 155, 1, 1, 0, 10, 17, 81, 25, 0, 164, 17, 114, 1, 119, 0, 381, 346, 66, 1, 2, 106, 331, 735, 0, 6, 3, 101, 6, 11, 18, 26, 3, 775, 471, 1, 268, 13, 0, 51, 30, 2, 3, 1, 0, 49, 142, 194, 21, 1, 54, 225, 39, 64, 826, 17, 0, 1, 1, 1, 411, 3, 0, 27, 0, 4, 226, 82, 0, 765, 444, 3, 1, 25, 1, 0, 778, 0, 0, 1, 2, 422, 354, 398, 14, 0, 7, 1, 0, 123, 1, 507, 0, 8, 71, 4, 937, 1, 1, 45, 733, 12, 1, 20, 0, 402, 30, 111, 852, 179, 515, 388, 105, 0, 0, 239, 1, 94, 1, 515, 4, 29, 5, 12, 2, 0, 0, 853, 0, 125, 0, 553, 292, 7, 142, 56, 105, 0, 149, 17, 1, 89, 1, 298, 76, 12, 9, 10, 1, 0, 5, 4, 41, 1, 664, 1, 0, 43, 680, 712, 42, 0, 237, 100, 0, 392, 2, 56, 2, 1, 224, 2, 0, 21, 299, 399, 911, 198, 3, 64, 1, 45, 9, 46, 7, 73, 487, 42, 920, 2, 2, 0, 1, 116, 111, 690, 141, 0, 14, 287, 26, 25, 361, 67, 82, 68, 35, 0, 151, 72, 22, 1, 2, 0, 231, 211, 590, 333, 123, 439, 1, 1, 77, 56, 1, 1, 57, 1, 0, 167, 66, 0, 262, 404, 3, 0, 10, 268, 592, 226, 184, 52, 485, 1, 140, 151, 547, 8, 657, 314, 3, 121, 495, 665, 33, 9, 12, 4, 35, 1, 266, 1, 761, 312, 0, 0, 8, 5, 19, 579, 12, 88, 435, 0, 4, 0, 63, 211, 49, 183, 3, 106, 1, 1, 1, 363, 1, 254, 179, 1, 3, 304, 1, 746, 14, 130, 13, 327, 460, 564, 915, 44, 23, 65, 177, 333, 22, 0, 1, 0, 841, 358, 0, 6, 3, 524, 299, 196, 1, 113, 376, 272, 0, 68, 0, 25, 13, 13, 6, 3, 113, 466, 223, 0, 2, 57, 5, 152, 54, 737, 28, 2, 965, 0, 701, 0, 32, 1, 128, 1, 21, 7, 40, 68, 15, 0, 1, 161, 1, 5, 0, 25, 0, 1, 3, 4, 0, 1, 845, 265, 15, 147, 716, 41, 117, 340, 133, 13, 0, 9, 36, 52, 145, 9, 1, 156, 4, 158, 41, 1, 465, 45, 0, 48, 0, 30, 107, 1, 26, 365, 0, 5, 0, 420, 7, 9, 16, 1, 33, 1, 3, 44, 1, 66, 303, 82, 0, 2, 84, 13, 2, 1, 2, 24, 107, 26, 2, 0, 438, 0, 464, 40, 13, 3, 378, 1, 289, 0, 61, 998, 63, 0, 657, 0, 76, 35, 105, 659, 82, 42, 529, 12, 648, 0, 620, 7, 4, 416, 2, 11, 0, 61, 930, 2, 495, 2, 953, 15, 127, 60, 482, 105, 1, 1, 873, 125, 59, 2, 147, 358, 1, 304, 357, 560, 7, 629, 1, 33, 9, 484, 1, 0, 11, 79, 13, 0, 145, 17, 995, 0, 2, 63, 62, 38, 0, 1, 1, 920, 20, 0, 1, 1, 538, 1, 75, 0, 0, 2, 0, 629, 355, 8, 119, 251, 0, 5, 1, 179, 164, 71, 79, 9, 49, 715, 0, 422, 403, 157, 1, 0, 0, 8, 1, 8, 9, 3, 89, 97, 36, 79, 61, 33, 19, 132, 404, 16, 824, 115, 213, 8, 938, 14, 7, 15, 18, 4, 410, 1, 1, 567, 724, 83, 0, 390, 0, 53, 1, 6, 0, 3, 0, 1, 0, 12, 164, 344, 4, 385, 13, 209, 0, 38, 1, 8, 45, 282, 0, 951, 1, 1, 239, 1, 20, 9, 653, 0, 455, 780, 19, 49, 604, 210, 0, 27, 1, 245, 11, 13, 0, 5, 10, 1, 0, 784, 163, 0, 34, 79, 79, 250, 0, 3, 2, 183, 453, 28, 14, 0, 900, 16, 414, 0, 2, 999, 144, 0, 225, 851, 1, 1, 824, 1, 130, 454, 34, 105, 0, 230, 0, 0, 2, 6, 7, 77, 699, 17, 107, 0, 16, 0, 12, 288, 0, 0, 0, 21, 32, 33, 0, 27, 2, 327, 13, 11, 141, 1, 455, 5, 4, 165, 163, 497, 4, 0, 63, 195, 2, 584, 141, 0, 35, 8, 49, 0, 3, 174, 1, 27, 241, 218, 2, 33, 18, 1, 0, 32, 647, 52, 26, 1, 9, 3, 337, 285, 11, 0, 14, 0, 750, 3, 0, 0, 1, 270, 1, 42, 780, 347, 49, 72, 1, 199, 6, 0, 44, 1, 63, 1, 1, 27, 15, 1, 13, 581, 3, 137, 87, 6, 1, 56, 1, 826, 0, 0, 601, 29, 35, 797, 0, 142, 1, 1, 1, 208, 2, 107, 425, 2, 13, 0, 177, 342, 28, 1, 588, 0, 34, 45, 1, 1, 351, 14, 195, 8, 19, 396, 35, 82, 220, 0, 451, 0, 168, 415, 170, 24, 1, 76, 0, 917, 478, 10, 315, 177, 103, 38, 190, 453, 154, 44, 664, 0, 414, 1, 5, 855, 41, 689, 2, 477, 363, 6, 37, 1, 0, 85, 280, 0, 0, 2, 293, 52, 1, 1, 88, 101, 13, 66, 0, 3, 62, 89, 0, 1, 27, 5, 0, 182, 1, 12, 820, 552, 123, 21, 2, 1, 0, 326, 352, 4, 67, 92, 1, 188, 151, 248, 0, 55, 0, 295, 101, 2, 70, 965, 1, 7, 123, 8, 976, 13, 364, 70, 64, 41, 1, 18, 699, 213, 240, 691, 1, 7, 99, 51, 1, 0, 77, 115, 373, 6, 4, 6, 22, 44, 1, 0, 36, 1, 51, 0, 428, 8, 1, 1, 2, 3, 58, 15, 0]}], \"hovertemplate\": \"%{xaxis.title.text}=%{x}<br>%{yaxis.title.text}=%{y}<extra></extra>\", \"legendgroup\": \"\", \"marker\": {\"color\": \"#636efa\", \"symbol\": \"circle\"}, \"name\": \"\", \"showlegend\": false, \"type\": \"splom\"}], {\"dragmode\": \"select\", \"height\": 800, \"legend\": {\"tracegroupgap\": 0}, \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"autotypenumbers\": \"strict\", \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Correlation between datapoints\"}, \"width\": 800}, {\"responsive\": true} ).then(function(){\n",
" \n",
"var gd = document.getElementById('de046e86-185c-4920-adf4-17018fdb5b3b');\n",
"var x = new MutationObserver(function (mutations, observer) {{\n",
" var display = window.getComputedStyle(gd).display;\n",
" if (!display || display === 'none') {{\n",
" console.log([gd, 'removed!']);\n",
" Plotly.purge(gd);\n",
" observer.disconnect();\n",
" }}\n",
"}});\n",
"\n",
"// Listen for the removal of the full notebook cells\n",
"var notebookContainer = gd.closest('#notebook-container');\n",
"if (notebookContainer) {{\n",
" x.observe(notebookContainer, {childList: true});\n",
"}}\n",
"\n",
"// Listen for the clearing of the current output cell\n",
"var outputEl = gd.closest('.output');\n",
"if (outputEl) {{\n",
" x.observe(outputEl, {childList: true});\n",
"}}\n",
"\n",
" }) }; </script> </div>\n",
"</body>\n",
"</html>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:03:10.483499Z",
"start_time": "2020-08-14T21:03:10.429898Z"
},
"id": "cD6TFevhWWiW"
},
"source": [
"corr = new_profile.corr()\n",
"figs.append(dp.Table(corr))"
],
"execution_count": 14,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "jS8eWvHJWWiW"
},
"source": [
"## Languages"
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:03:38.535467Z",
"start_time": "2020-08-14T21:03:38.529716Z"
},
"id": "cvet1sRuWWiX"
},
"source": [
"def isNaN(value):\n",
" return value != value"
],
"execution_count": 15,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:03:39.177421Z",
"start_time": "2020-08-14T21:03:39.159489Z"
},
"id": "iLne5OihWWiX"
},
"source": [
"from functools import reduce\n",
"\n",
"languages = new_profile['languages'].apply(lambda row: row.replace('[', '').replace(']', '').replace('\\'', '').split(',') if not isNaN(row) else ['None'])\n",
"languages = reduce(lambda x, y: x + y, languages)"
],
"execution_count": 16,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:03:39.730120Z",
"start_time": "2020-08-14T21:03:39.708658Z"
},
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "qhRP6jLeWWiY",
"outputId": "f00a21e4-0e67-457b-f3bb-72998aeb3b30"
},
"source": [
"from collections import Counter \n",
"\n",
"occ = dict(Counter(languages))\n",
"occ "
],
"execution_count": 17,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"{'': 29,\n",
" ' \"Capn Proto\"': 1,\n",
" ' AMPL': 1,\n",
" ' ANTLR': 2,\n",
" ' ASP': 1,\n",
" ' Agda': 2,\n",
" ' ApacheConf': 6,\n",
" ' AppleScript': 2,\n",
" ' Arduino': 19,\n",
" ' AspectJ': 1,\n",
" ' Assembly': 21,\n",
" ' AutoHotkey': 7,\n",
" ' Awk': 2,\n",
" ' Batchfile': 7,\n",
" ' BitBake': 1,\n",
" ' Brainfuck': 2,\n",
" ' C': 220,\n",
" ' C#': 57,\n",
" ' C++': 291,\n",
" ' CMake': 8,\n",
" ' CSS': 35,\n",
" ' Ceylon': 1,\n",
" ' Clarion': 1,\n",
" ' Clojure': 19,\n",
" ' CoffeeScript': 22,\n",
" ' Common Lisp': 8,\n",
" ' Common Workflow Language': 2,\n",
" ' Component Pascal': 1,\n",
" ' Coq': 1,\n",
" ' Cuda': 13,\n",
" ' D': 3,\n",
" ' DIGITAL Command Language': 6,\n",
" ' DOT': 1,\n",
" ' Dart': 15,\n",
" ' Dockerfile': 12,\n",
" ' Eagle': 1,\n",
" ' Eiffel': 1,\n",
" ' Elixir': 18,\n",
" ' Elm': 11,\n",
" ' Emacs Lisp': 38,\n",
" ' EmberScript': 1,\n",
" ' Erlang': 11,\n",
" ' F#': 4,\n",
" ' FORTRAN': 9,\n",
" ' Fortran': 1,\n",
" ' GAP': 3,\n",
" ' GDB': 1,\n",
" ' GDScript': 1,\n",
" ' GLSL': 1,\n",
" ' Game Maker Language': 1,\n",
" ' Gherkin': 1,\n",
" ' Go': 118,\n",
" ' Groff': 3,\n",
" ' Groovy': 4,\n",
" ' HCL': 2,\n",
" ' HTML': 460,\n",
" ' Hack': 2,\n",
" ' Haskell': 36,\n",
" ' IDL': 3,\n",
" ' Idris': 1,\n",
" ' Java': 312,\n",
" ' JavaScript': 482,\n",
" ' Julia': 15,\n",
" ' Jupyter Notebook': 344,\n",
" ' Kotlin': 14,\n",
" ' LilyPond': 1,\n",
" ' Liquid': 1,\n",
" ' Logos': 1,\n",
" ' Lua': 33,\n",
" ' M': 1,\n",
" ' M4': 1,\n",
" ' MATLAB': 11,\n",
" ' MQL5': 1,\n",
" ' Makefile': 48,\n",
" ' Mathematica': 6,\n",
" ' Matlab': 91,\n",
" ' NetLogo': 1,\n",
" ' Nginx': 2,\n",
" ' Nim': 1,\n",
" ' Nimrod': 1,\n",
" ' Nix': 3,\n",
" ' OCaml': 6,\n",
" ' Objective-C': 58,\n",
" ' Objective-C++': 1,\n",
" ' Objective-J': 1,\n",
" ' Open Policy Agent': 1,\n",
" ' OpenEdge ABL': 2,\n",
" ' OpenSCAD': 3,\n",
" ' PHP': 135,\n",
" ' PLSQL': 3,\n",
" ' PLpgSQL': 4,\n",
" ' Pascal': 5,\n",
" ' Pawn': 1,\n",
" ' Perl': 31,\n",
" ' Perl 6': 1,\n",
" ' Perl6': 1,\n",
" ' PostScript': 4,\n",
" ' PowerShell': 14,\n",
" ' Processing': 5,\n",
" ' Prolog': 8,\n",
" ' Puppet': 4,\n",
" ' Pure Data': 1,\n",
" ' PureScript': 1,\n",
" ' Python': 578,\n",
" ' QML': 1,\n",
" ' QMake': 1,\n",
" ' R': 95,\n",
" ' Racket': 3,\n",
" ' Raku': 1,\n",
" ' Rich Text Format': 1,\n",
" ' Roff': 8,\n",
" ' Ruby': 107,\n",
" ' Rust': 32,\n",
" ' SAS': 2,\n",
" ' SQLPL': 3,\n",
" ' SWIG': 1,\n",
" ' SaltStack': 2,\n",
" ' Scala': 61,\n",
" ' Scheme': 7,\n",
" ' ShaderLab': 2,\n",
" ' Shell': 322,\n",
" ' Shen': 1,\n",
" ' Slash': 1,\n",
" ' Smarty': 3,\n",
" ' Standard ML': 2,\n",
" ' Stata': 2,\n",
" ' SuperCollider': 2,\n",
" ' Swift': 38,\n",
" ' SystemVerilog': 2,\n",
" ' TSQL': 5,\n",
" ' Tcl': 4,\n",
" ' TeX': 124,\n",
" ' Terra': 1,\n",
" ' Turing': 1,\n",
" ' TypeScript': 94,\n",
" ' VBScript': 1,\n",
" ' VCL': 1,\n",
" ' VHDL': 2,\n",
" ' Vala': 2,\n",
" ' Verilog': 10,\n",
" ' Vim script': 63,\n",
" ' VimL': 47,\n",
" ' Visual Basic': 7,\n",
" ' Visual Basic .NET': 1,\n",
" ' Vue': 30,\n",
" ' Web Ontology Language': 1,\n",
" ' XSLT': 3,\n",
" ' YAML': 1,\n",
" ' Yacc': 1,\n",
" ' mcfunction': 1,\n",
" ' ooc': 1,\n",
" 'ASP': 3,\n",
" 'ActionScript': 2,\n",
" 'ApacheConf': 1,\n",
" 'Assembly': 1,\n",
" 'Batchfile': 1,\n",
" 'C': 25,\n",
" 'C#': 36,\n",
" 'C++': 15,\n",
" 'CSS': 291,\n",
" 'CoffeeScript': 4,\n",
" 'Coq': 1,\n",
" 'Cuda': 1,\n",
" 'Dockerfile': 60,\n",
" 'Emacs Lisp': 1,\n",
" 'GCC Machine Description': 1,\n",
" 'GDScript': 3,\n",
" 'Gherkin': 1,\n",
" 'Go': 15,\n",
" 'Groff': 2,\n",
" 'Groovy': 3,\n",
" 'HTML': 74,\n",
" 'IDL': 1,\n",
" 'Java': 21,\n",
" 'JavaScript': 90,\n",
" 'Jupyter Notebook': 49,\n",
" 'Lua': 3,\n",
" 'M': 1,\n",
" 'MATLAB': 2,\n",
" 'Makefile': 1,\n",
" 'Matlab': 11,\n",
" 'Nginx': 1,\n",
" 'Nimrod': 1,\n",
" 'None': 99,\n",
" 'Objective-C': 6,\n",
" 'OpenEdge ABL': 3,\n",
" 'PHP': 3,\n",
" 'PostScript': 3,\n",
" 'PowerShell': 2,\n",
" 'Processing': 1,\n",
" 'PureScript': 3,\n",
" 'Python': 209,\n",
" 'R': 13,\n",
" 'Reason': 1,\n",
" 'Ruby': 50,\n",
" 'Rust': 16,\n",
" 'Scala': 3,\n",
" 'Shell': 9,\n",
" 'Swift': 5,\n",
" 'TeX': 12,\n",
" 'TypeScript': 3,\n",
" 'VHDL': 7,\n",
" 'VimL': 3,\n",
" 'Visual Basic': 1,\n",
" 'Visual Basic .NET': 1,\n",
" 'Vue': 1,\n",
" 'nesC': 1}"
]
},
"metadata": {
"tags": []
},
"execution_count": 17
}
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:44:20.156677Z",
"start_time": "2020-08-14T21:44:20.133629Z"
},
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "BDg8xuanWWiZ",
"outputId": "3b27243b-ef83-4f0f-cad8-b7a769755080"
},
"source": [
"def isNaN(value):\n",
" return value != value\n",
"\n",
"from functools import reduce\n",
"\n",
"def string_to_list(string):\n",
" '''Change string to list'''\n",
" \n",
" return string.replace('[', '').replace(']', '').replace('\\'', '').split(',')\n",
"languages = new_profile['languages'].apply(lambda row: string_to_list(row) if not isNaN(row) else ['None'])\n",
"languages = reduce(lambda x, y: x + y, languages)\n",
"\n",
"from collections import Counter \n",
"\n",
"occ = dict(Counter(languages))\n",
"occ "
],
"execution_count": 18,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"{'': 29,\n",
" ' \"Capn Proto\"': 1,\n",
" ' AMPL': 1,\n",
" ' ANTLR': 2,\n",
" ' ASP': 1,\n",
" ' Agda': 2,\n",
" ' ApacheConf': 6,\n",
" ' AppleScript': 2,\n",
" ' Arduino': 19,\n",
" ' AspectJ': 1,\n",
" ' Assembly': 21,\n",
" ' AutoHotkey': 7,\n",
" ' Awk': 2,\n",
" ' Batchfile': 7,\n",
" ' BitBake': 1,\n",
" ' Brainfuck': 2,\n",
" ' C': 220,\n",
" ' C#': 57,\n",
" ' C++': 291,\n",
" ' CMake': 8,\n",
" ' CSS': 35,\n",
" ' Ceylon': 1,\n",
" ' Clarion': 1,\n",
" ' Clojure': 19,\n",
" ' CoffeeScript': 22,\n",
" ' Common Lisp': 8,\n",
" ' Common Workflow Language': 2,\n",
" ' Component Pascal': 1,\n",
" ' Coq': 1,\n",
" ' Cuda': 13,\n",
" ' D': 3,\n",
" ' DIGITAL Command Language': 6,\n",
" ' DOT': 1,\n",
" ' Dart': 15,\n",
" ' Dockerfile': 12,\n",
" ' Eagle': 1,\n",
" ' Eiffel': 1,\n",
" ' Elixir': 18,\n",
" ' Elm': 11,\n",
" ' Emacs Lisp': 38,\n",
" ' EmberScript': 1,\n",
" ' Erlang': 11,\n",
" ' F#': 4,\n",
" ' FORTRAN': 9,\n",
" ' Fortran': 1,\n",
" ' GAP': 3,\n",
" ' GDB': 1,\n",
" ' GDScript': 1,\n",
" ' GLSL': 1,\n",
" ' Game Maker Language': 1,\n",
" ' Gherkin': 1,\n",
" ' Go': 118,\n",
" ' Groff': 3,\n",
" ' Groovy': 4,\n",
" ' HCL': 2,\n",
" ' HTML': 460,\n",
" ' Hack': 2,\n",
" ' Haskell': 36,\n",
" ' IDL': 3,\n",
" ' Idris': 1,\n",
" ' Java': 312,\n",
" ' JavaScript': 482,\n",
" ' Julia': 15,\n",
" ' Jupyter Notebook': 344,\n",
" ' Kotlin': 14,\n",
" ' LilyPond': 1,\n",
" ' Liquid': 1,\n",
" ' Logos': 1,\n",
" ' Lua': 33,\n",
" ' M': 1,\n",
" ' M4': 1,\n",
" ' MATLAB': 11,\n",
" ' MQL5': 1,\n",
" ' Makefile': 48,\n",
" ' Mathematica': 6,\n",
" ' Matlab': 91,\n",
" ' NetLogo': 1,\n",
" ' Nginx': 2,\n",
" ' Nim': 1,\n",
" ' Nimrod': 1,\n",
" ' Nix': 3,\n",
" ' OCaml': 6,\n",
" ' Objective-C': 58,\n",
" ' Objective-C++': 1,\n",
" ' Objective-J': 1,\n",
" ' Open Policy Agent': 1,\n",
" ' OpenEdge ABL': 2,\n",
" ' OpenSCAD': 3,\n",
" ' PHP': 135,\n",
" ' PLSQL': 3,\n",
" ' PLpgSQL': 4,\n",
" ' Pascal': 5,\n",
" ' Pawn': 1,\n",
" ' Perl': 31,\n",
" ' Perl 6': 1,\n",
" ' Perl6': 1,\n",
" ' PostScript': 4,\n",
" ' PowerShell': 14,\n",
" ' Processing': 5,\n",
" ' Prolog': 8,\n",
" ' Puppet': 4,\n",
" ' Pure Data': 1,\n",
" ' PureScript': 1,\n",
" ' Python': 578,\n",
" ' QML': 1,\n",
" ' QMake': 1,\n",
" ' R': 95,\n",
" ' Racket': 3,\n",
" ' Raku': 1,\n",
" ' Rich Text Format': 1,\n",
" ' Roff': 8,\n",
" ' Ruby': 107,\n",
" ' Rust': 32,\n",
" ' SAS': 2,\n",
" ' SQLPL': 3,\n",
" ' SWIG': 1,\n",
" ' SaltStack': 2,\n",
" ' Scala': 61,\n",
" ' Scheme': 7,\n",
" ' ShaderLab': 2,\n",
" ' Shell': 322,\n",
" ' Shen': 1,\n",
" ' Slash': 1,\n",
" ' Smarty': 3,\n",
" ' Standard ML': 2,\n",
" ' Stata': 2,\n",
" ' SuperCollider': 2,\n",
" ' Swift': 38,\n",
" ' SystemVerilog': 2,\n",
" ' TSQL': 5,\n",
" ' Tcl': 4,\n",
" ' TeX': 124,\n",
" ' Terra': 1,\n",
" ' Turing': 1,\n",
" ' TypeScript': 94,\n",
" ' VBScript': 1,\n",
" ' VCL': 1,\n",
" ' VHDL': 2,\n",
" ' Vala': 2,\n",
" ' Verilog': 10,\n",
" ' Vim script': 63,\n",
" ' VimL': 47,\n",
" ' Visual Basic': 7,\n",
" ' Visual Basic .NET': 1,\n",
" ' Vue': 30,\n",
" ' Web Ontology Language': 1,\n",
" ' XSLT': 3,\n",
" ' YAML': 1,\n",
" ' Yacc': 1,\n",
" ' mcfunction': 1,\n",
" ' ooc': 1,\n",
" 'ASP': 3,\n",
" 'ActionScript': 2,\n",
" 'ApacheConf': 1,\n",
" 'Assembly': 1,\n",
" 'Batchfile': 1,\n",
" 'C': 25,\n",
" 'C#': 36,\n",
" 'C++': 15,\n",
" 'CSS': 291,\n",
" 'CoffeeScript': 4,\n",
" 'Coq': 1,\n",
" 'Cuda': 1,\n",
" 'Dockerfile': 60,\n",
" 'Emacs Lisp': 1,\n",
" 'GCC Machine Description': 1,\n",
" 'GDScript': 3,\n",
" 'Gherkin': 1,\n",
" 'Go': 15,\n",
" 'Groff': 2,\n",
" 'Groovy': 3,\n",
" 'HTML': 74,\n",
" 'IDL': 1,\n",
" 'Java': 21,\n",
" 'JavaScript': 90,\n",
" 'Jupyter Notebook': 49,\n",
" 'Lua': 3,\n",
" 'M': 1,\n",
" 'MATLAB': 2,\n",
" 'Makefile': 1,\n",
" 'Matlab': 11,\n",
" 'Nginx': 1,\n",
" 'Nimrod': 1,\n",
" 'None': 99,\n",
" 'Objective-C': 6,\n",
" 'OpenEdge ABL': 3,\n",
" 'PHP': 3,\n",
" 'PostScript': 3,\n",
" 'PowerShell': 2,\n",
" 'Processing': 1,\n",
" 'PureScript': 3,\n",
" 'Python': 209,\n",
" 'R': 13,\n",
" 'Reason': 1,\n",
" 'Ruby': 50,\n",
" 'Rust': 16,\n",
" 'Scala': 3,\n",
" 'Shell': 9,\n",
" 'Swift': 5,\n",
" 'TeX': 12,\n",
" 'TypeScript': 3,\n",
" 'VHDL': 7,\n",
" 'VimL': 3,\n",
" 'Visual Basic': 1,\n",
" 'Visual Basic .NET': 1,\n",
" 'Vue': 1,\n",
" 'nesC': 1}"
]
},
"metadata": {
"tags": []
},
"execution_count": 18
}
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:03:44.391685Z",
"start_time": "2020-08-14T21:03:44.360560Z"
},
"id": "OHD8QZBbWWia"
},
"source": [
"top_languages = [(language, frequency) for language, frequency in occ.items() if frequency > 10]\n",
"\n",
"top_languages = list(zip(*top_languages))\n",
"\n",
"language_df = pd.DataFrame(data = {'languages': top_languages[0],\n",
" 'frequency': top_languages[1]})\n",
"\n",
"#language_df.loc[language_df['frequency'] < 30, 'languages'] = 'Other languages'\n",
"\n",
"language_df.sort_values(by='frequency', axis=0, inplace=True, ascending=False)\n",
"\n",
"language = px.bar(language_df, y='frequency', x='languages',\n",
" title='Frequency of languages')\n",
"\n",
"figs.append(dp.Plot(language))"
],
"execution_count": 19,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:03:45.733124Z",
"start_time": "2020-08-14T21:03:45.724436Z"
},
"colab": {
"base_uri": "https://localhost:8080/",
"height": 542
},
"id": "uLOpe8zqWWia",
"outputId": "7b47a751-c324-458f-dcbd-c2b3ac46e5ba"
},
"source": [
"language.show()"
],
"execution_count": 20,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<html>\n",
"<head><meta charset=\"utf-8\" /></head>\n",
"<body>\n",
" <div> <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script> <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
" <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script> <div id=\"dc79b360-5eba-4b4b-89d9-ef68d1e1efd8\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"dc79b360-5eba-4b4b-89d9-ef68d1e1efd8\")) { Plotly.newPlot( \"dc79b360-5eba-4b4b-89d9-ef68d1e1efd8\", [{\"alignmentgroup\": \"True\", \"hovertemplate\": \"languages=%{x}<br>frequency=%{y}<extra></extra>\", \"legendgroup\": \"\", \"marker\": {\"color\": \"#636efa\"}, \"name\": \"\", \"offsetgroup\": \"\", \"orientation\": \"v\", \"showlegend\": false, \"textposition\": \"auto\", \"type\": \"bar\", \"x\": [\" Python\", \" JavaScript\", \" HTML\", \" Jupyter Notebook\", \" Shell\", \" Java\", \"CSS\", \" C++\", \" C\", \"Python\", \" PHP\", \" TeX\", \" Go\", \" Ruby\", \"None\", \" R\", \" TypeScript\", \" Matlab\", \"JavaScript\", \"HTML\", \" Vim script\", \" Scala\", \"Dockerfile\", \" Objective-C\", \" C#\", \"Ruby\", \"Jupyter Notebook\", \" Makefile\", \" VimL\", \" Emacs Lisp\", \" Swift\", \"C#\", \" Haskell\", \" CSS\", \" Lua\", \" Rust\", \" Perl\", \" Vue\", \"\", \"C\", \" CoffeeScript\", \" Assembly\", \"Java\", \" Arduino\", \" Clojure\", \" Elixir\", \"Rust\", \"Go\", \"C++\", \" Julia\", \" Dart\", \" Kotlin\", \" PowerShell\", \"R\", \" Cuda\", \"TeX\", \" Dockerfile\", \" MATLAB\", \" Elm\", \"Matlab\", \" Erlang\"], \"xaxis\": \"x\", \"y\": [578, 482, 460, 344, 322, 312, 291, 291, 220, 209, 135, 124, 118, 107, 99, 95, 94, 91, 90, 74, 63, 61, 60, 58, 57, 50, 49, 48, 47, 38, 38, 36, 36, 35, 33, 32, 31, 30, 29, 25, 22, 21, 21, 19, 19, 18, 16, 15, 15, 15, 15, 14, 14, 13, 13, 12, 12, 11, 11, 11, 11], \"yaxis\": \"y\"}], {\"barmode\": \"relative\", \"legend\": {\"tracegroupgap\": 0}, \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"autotypenumbers\": \"strict\", \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Frequency of languages\"}, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"languages\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"frequency\"}}}, {\"responsive\": true} ).then(function(){\n",
" \n",
"var gd = document.getElementById('dc79b360-5eba-4b4b-89d9-ef68d1e1efd8');\n",
"var x = new MutationObserver(function (mutations, observer) {{\n",
" var display = window.getComputedStyle(gd).display;\n",
" if (!display || display === 'none') {{\n",
" console.log([gd, 'removed!']);\n",
" Plotly.purge(gd);\n",
" observer.disconnect();\n",
" }}\n",
"}});\n",
"\n",
"// Listen for the removal of the full notebook cells\n",
"var notebookContainer = gd.closest('#notebook-container');\n",
"if (notebookContainer) {{\n",
" x.observe(notebookContainer, {childList: true});\n",
"}}\n",
"\n",
"// Listen for the clearing of the current output cell\n",
"var outputEl = gd.closest('.output');\n",
"if (outputEl) {{\n",
" x.observe(outputEl, {childList: true});\n",
"}}\n",
"\n",
" }) }; </script> </div>\n",
"</body>\n",
"</html>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "JuP0glCuWWib"
},
"source": [
"## Hireable"
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:04:04.608674Z",
"start_time": "2020-08-14T21:04:03.558805Z"
},
"id": "IZywscIPWWib"
},
"source": [
"import altair as alt\n",
"\n",
"hireable = alt.Chart(new_profile).transform_aggregate(\n",
" count='count()',\n",
" groupby=['hireable']\n",
").mark_bar().encode(\n",
" x='hireable:O',\n",
" y='count:Q')\n",
"\n",
"figs.append(dp.Plot(hireable))"
],
"execution_count": 21,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:04:06.057954Z",
"start_time": "2020-08-14T21:04:04.614050Z"
},
"id": "sWOS6ix9WWic"
},
"source": [
"hireable"
],
"execution_count": 22,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "p30M873FWWnB"
},
"source": [
"## Locations"
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:06:02.276026Z",
"start_time": "2020-08-14T21:06:00.657529Z"
},
"id": "DWOnpQ9TWWnI"
},
"source": [
"!pip install geopy"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:39:36.067318Z",
"start_time": "2020-08-14T21:29:24.300314Z"
},
"id": "dP5ZK4_VWWnJ"
},
"source": [
"from geopy.geocoders import Nominatim\n",
"import folium\n",
"\n",
"geolocator = Nominatim(user_agent='my_app')\n",
"\n",
"locations = list(new_profile['location'])\n",
"\n",
"lats = []\n",
"lons = []\n",
"exceptions = []\n",
"\n",
"for loc in locations:\n",
" try:\n",
" location = geolocator.geocode(loc)\n",
" lats.append(location.latitude)\n",
" lons.append(location.longitude)\n",
" except:\n",
" exceptions.append(loc)"
],
"execution_count": 23,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:39:36.608231Z",
"start_time": "2020-08-14T21:39:36.068489Z"
},
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "2-CVh18kWWnK",
"outputId": "5b2b5cb7-ef87-494e-bae8-5c88a5204b2b"
},
"source": [
"geolocator.geocode(locations[0])"
],
"execution_count": 24,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Location(Brooklyn, Kings County, New York, United States, (40.6501038, -73.9495823, 0.0))"
]
},
"metadata": {
"tags": []
},
"execution_count": 24
}
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:39:36.619793Z",
"start_time": "2020-08-14T21:39:36.610626Z"
},
"id": "eRmGr6yHWWnK"
},
"source": [
"location_df = new_profile[~new_profile.location.isin(exceptions)]"
],
"execution_count": 25,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:40:03.233907Z",
"start_time": "2020-08-14T21:40:03.229103Z"
},
"scrolled": true,
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "tdkJdh1TWWnK",
"outputId": "0808d1b0-b865-49d4-dc78-3658c75351d1"
},
"source": [
"location_df['latitude'] = lats\n",
"location_df['longitude'] = lons"
],
"execution_count": 26,
"outputs": [
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning:\n",
"\n",
"\n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning:\n",
"\n",
"\n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
"\n"
],
"name": "stderr"
}
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:40:19.293799Z",
"start_time": "2020-08-14T21:40:19.288819Z"
},
"id": "ib5JqP21WWnK"
},
"source": [
"location_df =location_df.dropna(axis=0, subset=['longitude'])"
],
"execution_count": 27,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:40:20.477792Z",
"start_time": "2020-08-14T21:40:20.297305Z"
},
"colab": {
"base_uri": "https://localhost:8080/",
"height": 542
},
"id": "7rhkuW0JWWnL",
"outputId": "29ee388b-999f-41b9-b78e-ffa774f22c35"
},
"source": [
"# Visualize with Plotly's scatter_geo\n",
"m = px.scatter_geo(location_df.fillna(0), lat='latitude', lon='longitude',\n",
" color='total_stars', \n",
" size='forks',\n",
" hover_data=['user_name','followers'],\n",
" title='Locations of Top Users')\n",
"m.show()\n",
"\n",
"figs.append(dp.Plot(m))"
],
"execution_count": 28,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<html>\n",
"<head><meta charset=\"utf-8\" /></head>\n",
"<body>\n",
" <div> <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script> <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
" <script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script> <div id=\"38d63b3a-e36a-47f8-b810-a08955c38cd1\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"38d63b3a-e36a-47f8-b810-a08955c38cd1\")) { Plotly.newPlot( \"38d63b3a-e36a-47f8-b810-a08955c38cd1\", [{\"customdata\": [[\"josephmisiti\", 2495], [\"wepe\", 4508], [\"ZuzooVn\", 1192], [\"rasbt\", 12725], [\"lazyprogrammer\", 2809], [\"lawlite19\", 616], [\"Jack-Cherish\", 2902], [\"ujjwalkarn\", 1952], [\"trekhleb\", 4934], [\"Vay-keen\", 192], [\"hangtwenty\", 446], [\"susanli2016\", 2970], [\"afshinea\", 1558], [\"vivienzou1\", 45], [\"jindongwang\", 2355], [\"Yorko\", 1222], [\"carefree0910\", 356], [\"csuldw\", 247], [\"JustFollowUs\", 832], [\"timzhang642\", 389], [\"RedstoneWill\", 1083], [\"ddbourgin\", 477], [\"roboticcam\", 3175], [\"TarrySingh\", 1262], [\"firmai\", 840], [\"llSourcell\", 36270], [\"dformoso\", 537], [\"shuhuai007\", 985], [\"soulmachine\", 3046], [\"chiphuyen\", 5884], [\"ty4z2008\", 989], [\"zotroneneis\", 493], [\"Borye\", 138], [\"tirthajyoti\", 1550], [\"rhiever\", 5035], [\"dipanjanS\", 1724], [\"sjwhitworth\", 291], [\"ethen8181\", 210], [\"ljpzzz\", 1127], [\"xxg1413\", 602], [\"warmheartli\", 1470], [\"fengdu78\", 8184], [\"humphd\", 421], [\"robertmartin8\", 315], [\"luispedro\", 603], [\"13o-bbr-bbq\", 287], [\"masinoa\", 91], [\"krishnakumarsekar\", 235], [\"xiaqunfeng\", 119], [\"JWarmenhoven\", 456], [\"pennyliang\", 362], [\"JerryKurata\", 149], [\"ssusnic\", 62], [\"Sophia-11\", 458], [\"rieder91\", 45], [\"DeqianBai\", 174], [\"jphall663\", 529], [\"Spandan-Madan\", 603], [\"atinesh-s\", 74], [\"stedy\", 79], [\"kailashahirwar\", 658], [\"haifengl\", 491], [\"zlotus\", 544], [\"WillKoehrsen\", 2859], [\"RedditSota\", 254], [\"nfmcclure\", 381], [\"aleju\", 917], [\"SarthakYadav\", 6], [\"rmarquis\", 88], [\"TocarIP\", 18], [\"meirwah\", 234], [\"bboe\", 138], [\"iiSeymour\", 53], [\"rwdaigle\", 69], [\"kieranjol\", 73], [\"wenyangfu\", 21], [\"adibis\", 40], [\"kyranb\", 10], [\"aaroncm\", 5], [\"zhunzhong07\", 354], [\"HemuManju\", 3], [\"divik544\", 11], [\"cshan\", 20], [\"Budddy\", 4], [\"imathis\", 877], [\"mangei\", 16], [\"twigz20\", 1], [\"ebenolson\", 94], [\"ccyanxyz\", 21], [\"Devinsuit\", 21], [\"phillies\", 4], [\"KevinCooper\", 18], [\"ecbc1\", 0], [\"arfon\", 563], [\"alphadl\", 83], [\"asford\", 21], [\"widdowquinn\", 117], [\"okjake\", 41], [\"e9t\", 684], [\"victorhcm\", 9], [\"mirjalil\", 4], [\"2y2simple\", 4], [\"MadhumitaSushil\", 12], [\"ricardoamaro\", 58], [\"KiranPanesar\", 47], [\"ReekenX\", 27], [\"AmaanC\", 104], [\"wltrimbl\", 22], [\"hjlarry\", 21], [\"hamelsmu\", 707], [\"TusharShandilya\", 2], [\"steven7851\", 22], [\"firebreath1001\", 6], [\"polaris1119\", 1311], [\"LoveMeWithoutAll\", 19], [\"FlorisHoogenboom\", 13], [\"mikl\", 92], [\"sudeepraja\", 36], [\"whughw\", 6], [\"yeonjuan\", 53], [\"pkayfire\", 35], [\"elwinarens\", 14], [\"willalways\", 2], [\"jboy\", 16], [\"pradeep1288\", 53], [\"adriancampos\", 9], [\"TehMillhouse\", 34], [\"SwarShah\", 16], [\"yhx5768\", 5], [\"jldohmann\", 3], [\"frannievas\", 5], [\"jrbourbeau\", 64], [\"cmutel\", 62], [\"wsbmxa198700\", 5], [\"weakish\", 124], [\"MdScntst\", 0], [\"Airatiki\", 4], [\"Ouss4\", 5], [\"nitin-tm\", 7], [\"jasonbhart\", 0], [\"sailakshmi17\", 8], [\"Psimage\", 2], [\"varshapaidi\", 4], [\"itailang\", 10], [\"Asmolovskij\", 0], [\"ss8651twtw\", 95], [\"EdwardSmith1884\", 59], [\"Mostafa-Samir\", 175], [\"wqiancheng\", 0], [\"olveirap\", 5], [\"benmccann\", 125], [\"IamThilina\", 3], [\"mingzhang96\", 6], [\"elesueur\", 0], [\"schneiderfelipe\", 33], [\"kevinkyyro\", 14], [\"esztiorm\", 3], [\"thanhnguyentang\", 5], [\"DanilBaibak\", 11], [\"e173101\", 6], [\"Finance-781\", 9], [\"individual8\", 14], [\"magsol\", 70], [\"GageAmes\", 31], [\"zldeng\", 30], [\"hanpum\", 2], [\"jlar0che\", 4], [\"moutai\", 9], [\"kennethjmyers\", 14], [\"byrichardpowell\", 54], [\"tairiUdacity\", 0], [\"itsliupeng\", 20], [\"plusjade\", 459], [\"triangeljs\", 1], [\"tobyhodges\", 62], [\"justmarkham\", 5757], [\"daz\", 16], [\"demidovakatya\", 533], [\"dmcc\", 67], [\"rahmanhafeezul\", 5], [\"jackeylu\", 10], [\"shahules786\", 24], [\"zairah10\", 8], [\"libertatis\", 1], [\"sshekh\", 28], [\"ericbuehl\", 11], [\"pipitone\", 25], [\"wayneadams\", 16], [\"songuke\", 24], [\"avn3r\", 12], [\"DrDavidS\", 5], [\"jayrav13\", 55], [\"Tirzono\", 2], [\"jankrepl\", 32], [\"synesthesiam\", 54], [\"kastman\", 21], [\"chess99\", 7], [\"waterson\", 15], [\"ghthor\", 51], [\"justramgerry\", 0], [\"beangoben\", 71], [\"drlabratory\", 9], [\"ranahanocka\", 174], [\"silverstone1903\", 63], [\"kbagchiGWC\", 20], [\"PrinzOwO\", 9], [\"synapton\", 0], [\"snurkabill\", 30], [\"layumi\", 1227], [\"mollygibson\", 4], [\"curiousrohan\", 2], [\"DamienIrving\", 92], [\"arc12\", 20], [\"orlitany\", 70], [\"jakubczakon\", 59], [\"pdkovacs\", 0], [\"samyag1\", 4], [\"xcodeburpx\", 13], [\"swlsw\", 3], [\"parkr\", 1169], [\"TitouanT\", 15], [\"code0100fun\", 38], [\"wking\", 111], [\"geon\", 71], [\"PeterShershov\", 12], [\"igorrocha\", 4], [\"doppenhe\", 16], [\"0asa\", 26], [\"hamiltont\", 29], [\"Alveona\", 4], [\"eldaniz\", 0], [\"graphaelli\", 39], [\"caub\", 22], [\"stephenturner\", 525], [\"kota7\", 11], [\"JanLauGe\", 38], [\"xlfe\", 17], [\"Lincete\", 1], [\"Jurilz\", 4], [\"woliveiras\", 1521], [\"rogerzanoni\", 36], [\"niltonslf\", 31], [\"havk64\", 29], [\"matheusgmaia\", 20], [\"toddrme2178\", 0], [\"nektor211\", 3], [\"imaness\", 0], [\"cailurus\", 162], [\"xkcao\", 0], [\"eeeeeric\", 7], [\"sirius999999\", 0], [\"mosew\", 2], [\"harenbergsd\", 2], [\"whatrocks\", 68], [\"liliuleo\", 7], [\"An3bi\", 24], [\"lettier\", 531], [\"shashankgroovy\", 44], [\"ReadmeCritic\", 60], [\"SeanPrashad\", 96], [\"robot-c0der\", 2], [\"ari-schaffel\", 1], [\"lstolcman\", 17], [\"sdsk\", 0], [\"allardbrain\", 32], [\"BirkhoffLee\", 94], [\"jiffyclub\", 298], [\"volker48\", 73], [\"gpailler\", 17], [\"koobs\", 71], [\"ocdtrekkie\", 37], [\"shenyyi\", 5], [\"gauravcharnalia\", 2], [\"mandar2812\", 63], [\"reiinakano\", 683], [\"jwsy\", 13], [\"sudipbhandari126\", 14], [\"mappum\", 433], [\"kmscode\", 32], [\"Asterisk14\", 2], [\"selay01\", 1], [\"maximkeremet\", 0], [\"raghavbali\", 37], [\"RF-Nelson\", 30], [\"aaren\", 80], [\"langner\", 50], [\"grayskripko\", 2], [\"eecn\", 21], [\"yurrriq\", 167], [\"amyrhoda\", 16], [\"SiyuanQi\", 94], [\"egeriis\", 43], [\"Amjad-H-Ali\", 5], [\"salehjg\", 12], [\"NeerajSarwan\", 33], [\"leviding\", 308], [\"rafaelsakurai\", 62], [\"lzcabrera\", 16], [\"natowi\", 45], [\"RockySJ\", 35], [\"cxxgtxy\", 17], [\"daniel-kashin\", 3], [\"sdball\", 81], [\"derrg\", 9], [\"koomar\", 7], [\"ploth\", 14], [\"gyoisamurai\", 82], [\"jaraco\", 238], [\"cjauvin\", 33], [\"tdhopper\", 463], [\"studiomohawk\", 220], [\"arnaldog12\", 287], [\"qualityjacks\", 9], [\"JJLWHarrison\", 0], [\"SubrataSarkar32\", 13], [\"benedictflorance\", 36], [\"Erotemic\", 90], [\"mgoodfellow\", 9], [\"cpdj\", 0], [\"alexnich\", 1], [\"rayeaster\", 21], [\"basickarl\", 11], [\"wendingp\", 34], [\"ecolell\", 18], [\"mjpieters\", 697], [\"luvegood\", 23], [\"Suraj520\", 6], [\"optas\", 50], [\"mexeniz\", 8], [\"oldratlee\", 5002], [\"kid1412z\", 26], [\"alexey-grigorev-sm\", 0], [\"vfdev-5\", 120], [\"m-maksyutin\", 3], [\"BernhardKonrad\", 40], [\"vilmacio22\", 1], [\"finnigantime\", 20], [\"ronnierios\", 4], [\"elfelround\", 8], [\"mkilavuz\", 0], [\"bkhaleghi\", 0], [\"btbytes\", 108], [\"mapx\", 11], [\"wenphan\", 5], [\"andrewschreiber\", 66], [\"dmoisset\", 46], [\"Lax\", 286], [\"credentiality\", 2], [\"janismdhanbad\", 4], [\"haraldschilly\", 90], [\"wla80\", 0], [\"cjratcliff\", 8], [\"smbeli\", 2], [\"tuanphuc\", 8], [\"apeeyush\", 37], [\"thezillion\", 62], [\"danielbogomazov\", 5], [\"NJannasch\", 22], [\"arteymix\", 59], [\"srayuws\", 33], [\"KaiNieRus\", 0], [\"Karl-EdwardFPJeanMehu\", 6], [\"Jasonnor\", 154], [\"YongshanKe\", 1], [\"melzareix\", 19], [\"gitbook-bot\", 75], [\"iamBedant\", 44], [\"wang1211\", 1], [\"rafalgrm\", 1], [\"andresgottlieb\", 57], [\"Sea-n\", 292], [\"kcrandall\", 5], [\"timmartin19\", 22], [\"datamove\", 12], [\"vyper\", 73], [\"abought\", 33], [\"anuj1207\", 5], [\"Bachmann1234\", 82], [\"K1t1k\", 0], [\"jmchen-g\", 18], [\"hwmrocker\", 23], [\"optixlab\", 4], [\"msabramo\", 143], [\"simensen\", 278], [\"nathanhillyer\", 15], [\"lexnederbragt\", 94], [\"mrry\", 522], [\"giuliatondin\", 3], [\"tuantp7\", 0], [\"rajeshvaya\", 12], [\"cdeil\", 121], [\"ffmpbgrnn\", 99], [\"adamyala\", 44], [\"jessitron\", 529], [\"jeff1evesque\", 55], [\"init27\", 159], [\"gcoter\", 3], [\"Diastro\", 40], [\"girishkuniyal\", 9], [\"brigham\", 3], [\"mzk912778163\", 0], [\"hslatman\", 439], [\"maks-a\", 3], [\"CSerxy\", 26], [\"chrissoulierserv\", 0], [\"fhemberger\", 186], [\"TommyBark\", 1], [\"NeroCube\", 26], [\"ses4j\", 29], [\"SnailSword\", 29], [\"yonatanf\", 1], [\"mcleonard\", 693], [\"Horaddrim\", 194], [\"xuhdev\", 190], [\"svaksha\", 185], [\"lxieyang\", 51], [\"lacava\", 41], [\"Sentimentron\", 58], [\"EtienneT\", 3], [\"alg\", 35], [\"tomassvensson\", 1], [\"jdblischak\", 182], [\"cmmalone\", 62], [\"163-0533\", 0], [\"scopatz\", 410], [\"SegFaultAX\", 35], [\"RaphaelMeudec\", 103], [\"yaph\", 164], [\"JohnMcLear\", 189], [\"nyoung85\", 1], [\"tvogels\", 32], [\"imatiach-msft\", 41], [\"bobrosoft\", 12], [\"hungphandinh92it\", 1], [\"moonboots\", 12], [\"adam-erickson\", 68], [\"oussou-dev\", 3], [\"zlu\", 49], [\"d4n1elchen\", 37], [\"baogianghoangvu\", 7], [\"EtienneBruines\", 21], [\"iory\", 29], [\"yoavz\", 94], [\"alexeygrigorev\", 424], [\"crouchred\", 6], [\"Bruce-Feldman\", 0], [\"gsenseless\", 0], [\"Gaohaoyang\", 772], [\"gaulinmp\", 21], [\"Philmod\", 110], [\"thedadams\", 0], [\"AkshayVarik\", 6], [\"nitinagarwal\", 3], [\"MaxHalford\", 364], [\"malfple\", 7], [\"zylix666\", 2], [\"drskd\", 1], [\"luntain\", 13], [\"ajmeese7\", 41], [\"djoos\", 36], [\"thecjharries\", 7], [\"matt-jay\", 1], [\"saiabishek1\", 5], [\"CookieDom\", 1], [\"herschel666\", 45], [\"pw\", 12], [\"wdm0006\", 87], [\"sjml\", 22], [\"sagunji\", 20], [\"cratonica\", 7], [\"lukelafountaine\", 15], [\"BetaPundit\", 36], [\"gisikw\", 105], [\"ss52\", 0], [\"ericdill\", 61], [\"martinwicke\", 451], [\"gideonthomas\", 47], [\"ulido\", 1], [\"xiuluo\", 24], [\"engineeress\", 2], [\"bendoerr\", 12], [\"ktolstikhin\", 6], [\"Borda\", 192], [\"gvwilson\", 418], [\"qhfgva\", 0], [\"GitHub30\", 58], [\"k88hudson\", 858], [\"tomhoover\", 14], [\"BillMills\", 116], [\"autodataming\", 30], [\"ayushs136\", 9], [\"glemaitre\", 346], [\"chi-hung\", 35], [\"LarryBattle\", 58], [\"codedread\", 92], [\"jakemcc\", 62], [\"albertmolinermrf\", 0], [\"jselmani\", 22], [\"fhs\", 55], [\"YJH1987\", 11], [\"Minki-Kim95\", 12], [\"ptaiga\", 0], [\"dear983604\", 1], [\"timClicks\", 115], [\"ColCarroll\", 243], [\"JsonAC\", 6], [\"jared-weed\", 13], [\"mkeds\", 0], [\"ilivans\", 54], [\"hex108\", 90], [\"lacanlale\", 5], [\"Domon\", 84], [\"cloudyan\", 32], [\"csinva\", 137], [\"MTietze\", 3], [\"gaodayue\", 66], [\"nahumj\", 27], [\"zhigang1992\", 200], [\"Hefeweizen\", 7], [\"baldassarreFe\", 61], [\"yarikoptic\", 260], [\"SentinelWarren\", 12], [\"testrain\", 40], [\"databaaz\", 5], [\"ajkl\", 30], [\"sdierauf\", 59], [\"sckott\", 737], [\"ismaeIfm\", 26], [\"poyuwu\", 3], [\"allthroughthenight\", 18], [\"dubzzz\", 105], [\"WuZhuoran\", 45], [\"jeffcore\", 2], [\"fangweili\", 6], [\"GordianStapf\", 1], [\"busterroni\", 3], [\"wzell\", 26], [\"JustinJudd\", 3], [\"amitshekhariitbhu\", 5380], [\"guedalia\", 0], [\"TaurusOlson\", 34], [\"SylvainDe\", 32], [\"ThatAndresV\", 1], [\"bvonboyen\", 0], [\"mmBabol\", 1], [\"idf\", 541], [\"SumitBando\", 1], [\"peter-toth\", 4], [\"juanpabloaj\", 73], [\"hanhdt\", 29], [\"ini\", 2], [\"vict0rsch\", 97], [\"QuLogic\", 115], [\"nvh95\", 9], [\"dhingratul\", 72], [\"Nukesor\", 62], [\"mikej888\", 7], [\"ipcenas\", 1], [\"polymeris\", 49], [\"jakirkham\", 159], [\"orionr\", 43], [\"aoping\", 20], [\"dombrno\", 12], [\"nachocab\", 99], [\"tommyjiang\", 52], [\"tomraulet\", 1], [\"soumanpaul\", 8], [\"planetceres\", 20], [\"adam2392\", 16], [\"tommyblue\", 26], [\"antmarakis\", 148], [\"thesimanjan\", 0], [\"yulequan\", 353], [\"Petemir\", 10], [\"tranek\", 26], [\"flyingpot\", 19], [\"grp-bork\", 0], [\"vallentin\", 27], [\"awesome-bot\", 8], [\"MuminjonGuru\", 53], [\"RingoTC\", 22], [\"rohduggal\", 3], [\"SeanPedersen\", 3], [\"LiEmail\", 12], [\"ecederstrand\", 44], [\"RequireSun\", 9], [\"shervinea\", 786], [\"fndjjx\", 2], [\"jcn\", 50], [\"rozentill\", 130], [\"rhnvrm\", 472], [\"lee709\", 0], [\"skervim\", 4], [\"Charismatron\", 0], [\"eccstartup\", 66], [\"agngrant\", 1], [\"iamc\", 24], [\"KeniMorri\", 4], [\"slcott\", 8], [\"justanhduc\", 23], [\"wogong\", 64], [\"liancheng\", 870], [\"testaccount553\", 2], [\"pilif\", 39], [\"justpic\", 97], [\"bon\", 4], [\"mgschwan\", 11], [\"shaoanlu\", 460], [\"QSCTech-Sange\", 83], [\"olivertomic\", 20], [\"eddyzhd\", 2], [\"digitalduke\", 4], [\"Fatehsandhu\", 2], [\"gliptak\", 29], [\"jkuchta\", 11], [\"kersov\", 0], [\"kevinlin311tw\", 281], [\"matthewfeickert\", 99], [\"Tarrasch\", 244], [\"czenzel\", 2], [\"itzamna314\", 5], [\"dangsonbk\", 19], [\"sagardubey3\", 3], [\"cswef\", 1], [\"treyhunner\", 624], [\"adamwkraft\", 9], [\"denisarnaud\", 72], [\"kinow\", 204], [\"LeeMaria007\", 1], [\"vishwajeetv\", 54], [\"itkinai\", 0], [\"tgray\", 6], [\"Th30\", 0], [\"davidlowjw\", 11], [\"flytomylife\", 4], [\"zzincubus\", 0], [\"pbanaszkiewicz\", 48], [\"stonebig\", 41], [\"HapeMask\", 5], [\"taylan\", 19], [\"abhshkdz\", 1245], [\"PatrickZH\", 12], [\"Mintisma\", 6], [\"p-s-vishnu\", 22], [\"bgreenwell\", 118], [\"selimnairb\", 26], [\"IMWP\", 0], [\"npbool\", 61], [\"PBarmby\", 27], [\"MarcelRobeer\", 3], [\"unode\", 65], [\"ilbuono\", 1], [\"MUSSONT\", 3], [\"filipefilardi\", 42], [\"JayJayBinks\", 0], [\"cbarrick\", 50], [\"Mrzhangxiaohua\", 3], [\"sayakpaul\", 383], [\"floydpink\", 43], [\"everping\", 21], [\"alishutc\", 4], [\"sebg\", 21], [\"YoungMStudio\", 0], [\"voskresenskiy\", 8], [\"jamesmyatt\", 3], [\"jappre\", 21], [\"stnk20\", 2], [\"AdilZouitine\", 49], [\"AndrewLiesinger\", 1], [\"jaksmid\", 2], [\"yjh\", 1], [\"dmnelson\", 37], [\"marsben\", 0], [\"LiberiFatali\", 10], [\"AJDBenner\", 6], [\"inejc\", 92], [\"adpon\", 3], [\"GLevV\", 0], [\"willingc\", 813], [\"briansorahan\", 21], [\"sudoes\", 0], [\"vicramr\", 1], [\"dmmulroy\", 27], [\"ifesdjeen\", 346], [\"mkotov13\", 6], [\"davidrhodus\", 80], [\"nashjain\", 47], [\"habi\", 36], [\"njern\", 11], [\"nbsantos\", 10], [\"Liam-Yang\", 0], [\"mewben\", 14], [\"Bachstelze\", 3], [\"cmacdonell\", 20], [\"yangyyt\", 2], [\"willgroves\", 0], [\"cgcgcg\", 2], [\"kzhk75\", 2], [\"Soypete\", 32], [\"buddhikajay\", 22], [\"maxnk\", 2], [\"mgoldey\", 5], [\"titu1994\", 1657], [\"fish2000\", 69], [\"pkuphy\", 39], [\"wanzhenchn\", 88], [\"mysteriouspants\", 37], [\"stromnov\", 16], [\"gceboh\", 0], [\"cbuckey-uda\", 262], [\"arimbr\", 48], [\"aquinasCode\", 0], [\"TuanNguyen27\", 12], [\"knathanieltucker\", 208], [\"idear1203\", 33], [\"michaelaye\", 46], [\"clarle\", 218], [\"kwichmann\", 97], [\"naupaka\", 123], [\"stieglma\", 13], [\"penberg\", 351], [\"amar00k\", 0], [\"junxnone\", 3], [\"itsmeolivia\", 17], [\"Nebula83\", 2], [\"NathanEpstein\", 201], [\"benedekrozemberczki\", 1742], [\"KirillPanin\", 0], [\"jpallen\", 54], [\"IsakFalk\", 25], [\"frankhjwx\", 26], [\"guillermo-navas-palencia\", 11], [\"fmichonneau\", 197], [\"daveredrum\", 43], [\"mkuhn\", 17], [\"fleeting\", 92], [\"albahnsen\", 273], [\"cmhungsteve\", 147], [\"appleJax\", 15], [\"peterfabakker\", 12], [\"jsmith\", 25], [\"agusnavce\", 4], [\"jeffin07\", 8], [\"advancedxy\", 45], [\"axsaucedo\", 143], [\"mybaseball52\", 4], [\"ArionMiles\", 54], [\"narisada014\", 4], [\"CorreyL\", 8], [\"tiendq\", 29], [\"loveunk\", 191], [\"TwFlem\", 3], [\"DanielMorales9\", 25], [\"lsvih\", 106], [\"AlexZhou1995\", 12], [\"pleabargain\", 7], [\"qiagu\", 0], [\"Pomax\", 521], [\"adarsh0806\", 204], [\"anzellai\", 6], [\"vinodkkurmi\", 12], [\"calberti\", 21], [\"andsor\", 15], [\"danielsan\", 11], [\"nolith\", 24], [\"brainstorm\", 182], [\"serickso\", 0], [\"jocelynlih\", 17], [\"jeasonstudio\", 185], [\"ketanhwr\", 225], [\"jwasham\", 9193], [\"alcidesv\", 3], [\"Alex1996a\", 47], [\"enjoyhot\", 39], [\"drio\", 73], [\"opie4624\", 28], [\"njojic\", 0], [\"chneau\", 17], [\"4may\", 0], [\"AselaDarshan\", 2], [\"dnn37\", 0], [\"sseidl88\", 1], [\"afromanF\", 0], [\"deeper-learning\", 0], [\"terrytangyuan\", 1938], [\"wrichert\", 30], [\"dylandrop\", 13], [\"chhh\", 29], [\"Gabriel-Azevedo-Ferreira\", 1], [\"RasPat1\", 15], [\"KaiyangZhou\", 417], [\"chrisadami\", 2], [\"aosama\", 6], [\"phocks\", 62], [\"vmirly\", 140], [\"ooxi\", 14], [\"buddhiv\", 9], [\"harshavamsi\", 62], [\"binilj04\", 2], [\"alimon808\", 12], [\"dlebauer\", 58], [\"josephmmisiti\", 2], [\"blokhin\", 47], [\"mogwai\", 31], [\"frnsys\", 693], [\"Div44\", 5], [\"mahajani123\", 0], [\"timfrostmann\", 5], [\"Ja1r0\", 2], [\"gukoff\", 12], [\"cako\", 14], [\"acupofdata\", 0], [\"Zzlongjuanfeng\", 16], [\"sohamM97\", 9], [\"kwhinnery\", 730], [\"dnguneratne\", 33], [\"Vincent-Vercruyssen\", 10], [\"BokaiLIAN\", 3], [\"svntjng\", 0], [\"BioGeek\", 53], [\"proinsias\", 13], [\"jongoodnow\", 5], [\"keveman\", 142], [\"ptone\", 180], [\"andreww\", 53], [\"12wang3\", 10], [\"robtaussig\", 41], [\"festline\", 4], [\"daeyun\", 76], [\"strange-jiong\", 19], [\"zdgriffith\", 9], [\"iglpdc\", 36], [\"jbencook\", 30], [\"postBG\", 19], [\"fatihbaltaci\", 16], [\"jimthompson5802\", 19], [\"wojdyr\", 43], [\"fchouteau\", 9], [\"andrewd76\", 0], [\"el10savio\", 14], [\"testbounty\", 30], [\"acusti\", 28], [\"kgashok\", 147], [\"rajasekharponakala\", 6], [\"liuliu5151\", 0], [\"harshnisar\", 52], [\"bigwave\", 1], [\"curiousleo\", 34], [\"nmb10\", 6], [\"trpapp\", 6], [\"joaorafaelm\", 75], [\"LecJackS\", 4], [\"wkentaro\", 1235], [\"AnshulBasia\", 33], [\"philips\", 1287], [\"Tom-Ren\", 0], [\"UjjwalAryal\", 5], [\"re4lfl0w\", 49], [\"Zhi-lin\", 3], [\"wtollett-usgs\", 3], [\"kno10\", 47], [\"coderfive\", 0], [\"Naereen\", 244], [\"JamesLuoau\", 36], [\"bertjiazheng\", 56], [\"athiwatc\", 18], [\"easezyc\", 38], [\"maxim5\", 97], [\"brandly\", 114], [\"qianguyizhe\", 0], [\"fanglinchen\", 43], [\"karthik\", 928], [\"thouis\", 62], [\"fmder\", 64], [\"espoirMur\", 50], [\"havanagrawal\", 50], [\"ankitkul\", 4], [\"Vijayabhaskar96\", 18], [\"mindw\", 22], [\"Pirikara\", 0], [\"creinders\", 0], [\"frozenkp\", 54], [\"YINCHENLI\", 1], [\"juliangarcia\", 35], [\"jovilius\", 19], [\"danyaljj\", 61], [\"ExterminateWho\", 0], [\"pjbull\", 193], [\"ProGamerGov\", 47], [\"SoumyadeepJana\", 9], [\"metrafonic\", 2], [\"hmchuong\", 42], [\"dsych\", 5], [\"kylegrover\", 0], [\"egorpolusmak\", 1], [\"flipace\", 45], [\"JasonGitHub\", 4], [\"anujgupta82\", 58], [\"NotAnyMike\", 13], [\"peter-parque\", 0], [\"art-programmer\", 135], [\"oleksii-trekhleb-epam\", 0], [\"JustroX\", 31], [\"jacarrico\", 34], [\"jgraving\", 48], [\"rumi-naik\", 0], [\"hlkcrcck\", 1], [\"CorcovadoMing\", 19], [\"toaarnio\", 39], [\"vattay\", 6], [\"patricksnape\", 74], [\"bamos\", 2010], [\"npanti\", 4], [\"zonca\", 152], [\"sourcesoft\", 34], [\"hsiaoyi0504\", 102], [\"Amir-Arsalan\", 49], [\"ezefranca\", 215], [\"praveenmylavarapu\", 22], [\"muhammadyaseen\", 3], [\"SusieXu\", 7], [\"carlward\", 0], [\"mikhailsergeevi4\", 0], [\"imhuay\", 1631], [\"ThePhantomCoder\", 1], [\"mjschranz\", 21], [\"rachtsingh\", 34], [\"sebix\", 37], [\"ss18\", 27], [\"lazywei\", 172], [\"jpvg10\", 11], [\"mraje16\", 5], [\"jiangf13\", 2], [\"snowde\", 0], [\"cPolaris\", 14], [\"ZhengRui\", 37], [\"jhashanti\", 8], [\"Pooch11\", 3], [\"tushargt\", 0], [\"Metnew\", 241], [\"shaqian\", 115], [\"lupusomniator\", 3], [\"jogjayr\", 20], [\"katzien\", 449], [\"vargas\", 10], [\"jcsims\", 12], [\"PaulDebus\", 2], [\"vad4msiu\", 10], [\"guillaume-chevalier\", 863], [\"daanmichiels\", 3], [\"kacper1095\", 5], [\"zahanm\", 14], [\"clappis\", 2], [\"lefnire\", 430], [\"lxj616\", 90], [\"scraggard\", 0], [\"jaywinhuang\", 3], [\"lukaszkaiser\", 388], [\"Ir1d\", 607], [\"keppel\", 121], [\"gvn\", 71], [\"aniag\", 2], [\"apatsekin\", 20], [\"Microsheep\", 47], [\"jgyllinsky\", 7], [\"run\", 62], [\"RandomArray\", 5], [\"ser-serege\", 0], [\"ehrenfeu\", 24], [\"secretrobotron\", 100], [\"avinashsai\", 28], [\"skvrahul\", 41], [\"albertstill\", 39], [\"sedge\", 12], [\"ivesn\", 0], [\"ntache\", 0], [\"beckgael\", 19], [\"synapticarbors\", 48], [\"oneTaken\", 29], [\"joybanerjee08\", 17], [\"ACharbonneau\", 12], [\"koriroys\", 72], [\"cameroncan\", 1], [\"martijnvanbeers\", 3], [\"Chandlercjy\", 55], [\"lisahdd007\", 0], [\"ShengKungYi\", 34], [\"p1gd0g\", 0], [\"irrationalRock\", 4], [\"zh794390558\", 38], [\"navdeep-G\", 188], [\"ritabentodosreis\", 0], [\"APorterOReilly\", 0], [\"ambientlight\", 25], [\"twitwi\", 62], [\"tomahawk28\", 9], [\"sguada\", 363], [\"pmn4\", 26], [\"ammarasmro\", 44], [\"philippbayer\", 100], [\"SaumoPal97\", 24], [\"mikelogsdon\", 2], [\"cavestruz\", 6], [\"Keiku\", 98], [\"hfanahita\", 0], [\"McKenzyPG\", 4], [\"monomagentaeggroll\", 1], [\"hyqskevin\", 14], [\"krother\", 170], [\"Digitalmobz\", 0], [\"DanBeard\", 8], [\"jackmaney\", 27], [\"RickEyre\", 53], [\"Frenchhorn\", 1], [\"tapaswenipathak\", 1621], [\"jvanlangen\", 0], [\"alexobednikov\", 19], [\"Mchristos\", 6], [\"sinanuozdemir\", 118], [\"kjappelbaum\", 21], [\"alicoding\", 345], [\"Owen-Mak\", 3], [\"yoavram\", 92], [\"bob7783\", 5], [\"codingcai\", 3], [\"ethanwhite\", 235], [\"aymericdamien\", 4589], [\"sagarcadet\", 2], [\"gavinsimpson\", 216], [\"jliddie\", 0], [\"mzakariaCERN\", 6], [\"jalateras\", 17], [\"robmarkcole\", 257], [\"umpox\", 80], [\"yuanxiaosc\", 612], [\"mtchavez\", 63], [\"mckays630\", 6], [\"piyushchauhan\", 44], [\"HaveF\", 39], [\"acabunoc\", 400], [\"elkfrawy-df\", 3], [\"moshejs\", 9], [\"lzamparo\", 3], [\"Dr-Zhou\", 1], [\"erjanmx\", 25], [\"aggronerd\", 1], [\"ilam\", 11], [\"abarto\", 28], [\"joaopedronardari\", 94], [\"jaymody\", 24], [\"rodgzilla\", 66], [\"anishthite\", 10], [\"chrish42\", 22], [\"lukearmstrong\", 51], [\"kshs010239\", 7], [\"twotabbies\", 0], [\"sstarr\", 29], [\"samedhaa\", 14], [\"AdityaSoni19031997\", 80], [\"ao-song\", 1], [\"AlexanderKunkel\", 1], [\"cjpurackal\", 16], [\"jackkuipers\", 1], [\"KodeWorker\", 7], [\"abingham\", 118], [\"juholehtonen\", 2], [\"hetii\", 2], [\"pan-long\", 23], [\"rtlee9\", 55], [\"bluewoodtree\", 0], [\"CrazyBunQnQ\", 20], [\"alexsavio\", 48], [\"DiegoCatalano\", 78], [\"gaborvecsei\", 46], [\"Cugtyt\", 43], [\"meghpatel\", 12], [\"angeladai\", 252], [\"bobiechen-twilio\", 15], [\"alexlokotochek\", 3], [\"niklaskeerl\", 16], [\"bkm009\", 0], [\"cgohlke\", 120], [\"LiLiu93\", 2], [\"LukasKnuth\", 23], [\"x1957\", 51], [\"cezannec\", 1348], [\"stefanv\", 567], [\"ebigelow\", 14], [\"gdevenyi\", 72], [\"liuluheng\", 20], [\"ackerleytng\", 15], [\"tychenjiajun\", 23], [\"meawoppl\", 40], [\"yuanzhaoYZ\", 23], [\"K-LV\", 4], [\"taoyudong\", 12], [\"louispotok\", 4], [\"omrimendels\", 0], [\"aathauck\", 0], [\"Kacawi\", 1], [\"emptyr1\", 24], [\"rsbohn\", 13], [\"swanson\", 406], [\"dogHere\", 7], [\"ebuildy\", 17], [\"maikelwever\", 22], [\"pfsq\", 10], [\"amitkgupta\", 25], [\"acastrounis\", 52], [\"sys0613\", 0], [\"hugosoftdev\", 7], [\"teopost\", 18], [\"LukeArn\", 2], [\"t-k-\", 144], [\"omo\", 221], [\"Xyclade\", 63], [\"windpls\", 17], [\"gumblex\", 195], [\"Adrien-Jecker\", 4], [\"ivigamberdiev\", 1], [\"LizhangX\", 10], [\"sivanWu0222\", 31], [\"Amir22010\", 20], [\"digital-thinking\", 21], [\"eshizhan\", 5], [\"SamyPesse\", 2461], [\"ayakubovich\", 11], [\"vahtras\", 21], [\"daviddao\", 472], [\"tncardoso\", 27], [\"XiaoshuiHuang\", 20], [\"tdunning\", 606], [\"PGijsbers\", 9], [\"chkoar\", 30], [\"kilsenp\", 5], [\"joyoyoyoyoyo\", 82], [\"seIncorp\", 0], [\"jacksonlo\", 5], [\"junlulocky\", 271], [\"lorensr\", 172], [\"javierlorenzod\", 28], [\"jGaboardi\", 42], [\"dribnet\", 275], [\"ande765a\", 16], [\"ahmadia\", 84], [\"alisezer\", 8], [\"wassimseif\", 34], [\"kadirpekel\", 157], [\"mrtnbrst\", 0], [\"myui\", 107], [\"vrv\", 532], [\"joaoavf\", 3], [\"varan42\", 1], [\"brylie\", 134], [\"nschor\", 3], [\"yakud\", 13], [\"kreuvf\", 5], [\"umstek\", 89], [\"azillion\", 25], [\"borodenkov\", 4], [\"omytryniuk\", 3], [\"adyates\", 8], [\"idelgado\", 16], [\"douglatornell\", 9], [\"wenruimeng\", 7], [\"dtchepak\", 58], [\"bryngo\", 33], [\"jaycode\", 29], [\"daddou-ma\", 58], [\"zyc1gq\", 0], [\"beroe\", 4], [\"DH-Diego\", 6], [\"bigsnarfdude\", 254], [\"hbaniecki\", 18], [\"YichenGong\", 71], [\"shrutibhutaiya\", 7], [\"IgorKovr\", 5], [\"dbarbier\", 9], [\"miksago\", 1], [\"ZYSzys\", 115], [\"AnkurDedania\", 17], [\"andrewda\", 338], [\"ahnt\", 6], [\"rdingwall\", 81], [\"SumanthReddyKaliki\", 1], [\"fperez\", 1104], [\"adityahiran\", 0], [\"sun254\", 33]], \"geo\": \"geo\", \"hovertemplate\": \"forks=%{marker.size}<br>latitude=%{lat}<br>longitude=%{lon}<br>user_name=%{customdata[0]}<br>followers=%{customdata[1]}<br>total_stars=%{marker.color}<extra></extra>\", \"lat\": [40.6501038, 30.2489634, 13.2904027, 43.074761, 46.3144754, 32.0609736, 35.000074, 46.3144754, 52.3727598, 22.5360142, 45.5202471, 43.6534817, 46.3144754, 40.4416941, 39.9065084, 52.3727598, 39.99171495, 22.555454, 46.3144754, 42.3602534, 46.3144754, 40.6501038, -33.8548157, 52.3727598, 52.2034823, 37.7790262, -33.8548157, 34.3430507, 37.3893889, 37.3893889, 22.555454, 50.938361, 46.3144754, 37.5482697, 45.5202471, 46.3144754, 51.5073219, 46.3144754, 23.1301964, 35.000074, 39.9065084, 36.0638034, 61.0666922, 52.2034823, 48.8489697, 35.6828387, 46.3144754, 46.3144754, 46.3144754, 59.6749712, 39.6566257, 46.3144754, 46.3144754, 39.9065084, 47.2000338, 31.2322758, 38.8949924, 42.3750997, 19.0759899, 46.3144754, 12.9791198, 40.7127281, 46.3144754, 48.6108441, 46.3144754, 47.6038321, 51.0834196, 28.4646148, 46.3144754, 46.3144754, 32.0852997, 34.4221319, 39.7852062, 35.7882893, 53.3497645, 46.3144754, 36.7014631, -37.8142176, 38.7604815, 46.3144754, 46.3144754, 46.3144754, 39.9065084, 46.3144754, 52.4459629, 46.3144754, 61.0666922, 41.298434349999994, 30.2489634, 59.938732, 50.1106444, 46.3144754, 46.3144754, 39.2908816, -33.8548157, 47.6038321, 55.8609825, 41.3828939, 37.5666791, 46.3144754, 46.3144754, 46.3144754, 46.3144754, 38.7077507, 41.8755616, 51.0, 19.0759899, 46.3144754, 31.3016935, 45.5202471, 46.3144754, 46.3144754, 46.3144754, 39.9065084, 36.638392, 52.3727598, 47.1486137, 42.3685658, 46.3144754, 36.638392, 37.7790262, 52.3727598, 46.3144754, -33.8548157, 37.3361905, 46.3144754, 49.0068705, 42.9746137, 46.3144754, 40.1117174, -34.9964963, 43.074761, 47.3744489, 46.3144754, 46.3144754, 55.7504461, 55.7504461, 28.0000272, 46.3144754, 37.4429964, 17.7231276, 49.4871968, 40.7127281, 32.0852997, 46.3144754, 23.9739374, 46.3144754, 26.2540493, 46.3144754, 46.3144754, 36.7014631, 6.7145129, 46.3144754, 46.3144754, -27.5973002, 40.6501038, 46.3144754, 46.3144754, 52.5170365, 35.000074, 46.3144754, 53.550341, 32.2105899, 46.3144754, 39.9065084, 46.3144754, 46.3144754, 46.3144754, 40.7127281, 45.421106, 46.3144754, 39.9065084, 37.7790262, 39.9065084, 49.4093582, 35.6009498, 46.3144754, 55.7504461, 19.37218875, 28.5442774, 30.5951051, 9.931308, 40.7127281, 23.1301964, 47.3744489, 46.3144754, 46.3144754, 46.3144754, 46.3144754, 37.7790262, 30.2489634, 40.0757384, 52.5001698, 46.2017559, 46.3144754, 42.3602534, 46.3144754, 46.3144754, 38.4758406, 46.3144754, 46.3144754, 38.6529545, 46.3144754, 46.3144754, 46.3144754, 46.3144754, 61.0666922, 46.3144754, -33.8548157, 46.3144754, 13.0836939, -42.8825088, 54.7023545, 46.3144754, 52.2319581, 46.3144754, 46.3144754, 49.65034, 46.3144754, 39.7837304, 46.3144754, 30.508235, 46.3144754, 57.7825634, 32.0852997, -22.9110137, 47.6038321, 50.6402809, 46.216411, 59.938732, 46.3144754, 39.9527237, 46.603354, 38.0360726, 35.6828387, 40.7127281, -24.7761086, 46.3144754, 46.3144754, 46.3144754, 48.7784485, -10.3333333, 37.7790262, -7.2246743, 46.3144754, 46.3144754, 46.3144754, 39.9065084, 46.3144754, 30.2711286, 46.3144754, 34.0536909, 46.3144754, 37.7790262, 46.3144754, 33.4484367, 40.7127281, 46.3144754, 46.3144754, 46.3144754, 55.001251, 46.3144754, 51.1263106, 46.3144754, 37.7790262, 25.0375198, 37.7884969, 39.9527237, 1.357107, -24.7761086, 41.47441105, 46.3144754, 22.3511148, 51.9228934, 37.7790262, 38.8949924, 12.9791198, 37.5164926, 39.7837304, 46.3144754, 46.3144754, 46.3144754, 22.3511148, 40.7127281, 46.3144754, 37.3893889, 54.710128, 34.3430507, 44.9772995, 43.6534817, 34.0536909, 40.7127281, 46.3144754, 46.3144754, 12.9791198, 30.5951051, -10.3333333, 49.2608724, 46.3144754, 35.000074, 39.9065084, 55.7504461, 35.996653, 46.3144754, 46.3144754, 53.550341, 46.3144754, 40.4416941, 45.4972159, 35.7803977, 35.6828387, -23.5506507, 46.3144754, 46.3144754, 22.9964948, 10.804973, 41.1018669, 51.5073219, 38.8339578, 46.3144754, 1.357107, 55.6052931, 46.3144754, -33.897495, 52.2034823, 47.6038321, 19.1914604, 37.4519671, 13.7544238, 30.2489634, 39.9065084, 46.3144754, 46.3144754, 55.7504461, 37.3893889, -7.0823544, 47.6038321, 12.1459907, 39.3262345, 46.3144754, 43.6534817, 39.9162861, 46.3144754, 46.3144754, 37.7790262, 51.5073219, 39.9065084, 46.3144754, 46.3144754, 48.2083537, 49.2608724, 51.5073219, 30.5951051, 46.3144754, 51.5073219, 22.3511148, 43.7941544, 51.5142273, 49.2608724, 46.3144754, 46.3144754, 27.7567667, 23.9739374, 46.3144754, 48.1371079, 46.3144754, 12.9791198, 46.3144754, 50.0469432, -33.4377756, 25.0375198, 38.8949924, 41.5051613, 55.7504461, -24.046329, 39.7837304, 28.6138954, 42.4184296, 46.3144754, 46.3144754, 51.2254018, 37.2333253, 37.3361905, 43.074761, 30.2711286, 60.5000209, 37.7790262, -29.8425284, 46.3144754, 25.0750095, 49.4093582, 46.3144754, 5.3428475, 38.6529545, 46.3144754, 13.0836939, 46.3144754, 47.6144219, 28.6517178, 46.3144754, 46.3144754, 46.3144754, 46.3144754, 42.2681569, 43.427043, 50.938361, 46.3144754, 24.8066333, 38.8949924, 46.3144754, 46.3144754, 37.7790262, 48.1808582, 37.7790262, 46.3144754, 40.4416941, 39.9527237, 52.2034823, 46.3144754, 46.3144754, 50.1106444, 41.083064, 46.3144754, 35.000074, 41.8755616, 37.7790262, 48.8566969, 52.5170365, 40.914854, 61.0666922, 46.5218269, 42.3750997, 64.6863136, 46.3144754, 46.3144754, 46.3144754, 46.3144754, 46.3144754, 22.9912348, 44.97208635, 51.0834196, 35.6828387, 37.7790262, 52.5170365, 46.3144754, 46.3144754, 46.3144754, 30.2489634, 40.7596198, 48.6108441, 33.4255056, 39.9670569, 33.6856969, 43.6044622, -2.4833826, 25.0375198, 46.3144754, 52.2319581, 30.421309, 51.5073219, 30.2711286, 52.5170365, 40.4416941, 48.2083537, 53.550341, 35.0841034, 33.7489924, 40.8466508, 27.708317, 5.76420625, 40.7127281, 22.55825, 44.811349, 59.938732, 35.6729639, 37.7790262, 43.6534817, 46.3144754, 46.3144754, 46.3144754, 38.0360726, 52.5170365, 50.0874654, 43.6534817, 46.3144754, 34.6198813, 43.6534817, 46.3144754, 46.3144754, 35.000074, 22.3511148, 48.758468050000005, 25.0375198, 31.8160381, 46.3144754, 41.8755616, 46.3144754, 43.6534817, 40.7127281, 46.3144754, 36.638392, 46.3144754, 46.3144754, -41.2887953, 42.3602534, 39.9065084, 42.3788774, 46.3144754, 55.7504461, 46.3144754, 34.2345615, -37.8142176, 46.3144754, 37.8753497, 27.7567667, 39.9065084, 42.7355416, 46.3144754, 46.3144754, 59.3251172, 41.1018669, -6.8160837, 46.3144754, 26.4609135, 46.3144754, 47.6487611, 43.9792797, 46.3144754, 46.3144754, 46.3144754, 48.8566969, 37.7790262, 30.2711286, 46.3144754, 46.3144754, 39.7837304, 47.2000338, 46.3144754, 28.6138954, 46.3144754, 44.5579391, 46.3144754, 1.357107, 46.3144754, 43.6534817, 37.4519671, 46.3144754, 46.3144754, 46.3144754, 35.021041, 46.3144754, 45.4972159, 43.6534817, 46.3144754, 37.3361905, 53.550341, 46.3144754, 46.3144754, -33.4377756, 46.3144754, 37.4519671, 46.3144754, 49.1922443, 41.3828939, 39.9065084, 46.3144754, 12.9791198, 37.7884969, 39.7837304, 43.7698712, 48.1371079, 64.6863136, 36.7014631, -34.9964963, 33.7489924, 46.3144754, 46.3144754, 55.3997225, 46.3144754, 41.32373, 35.000074, 46.3144754, 46.3144754, 39.9065084, 55.6867243, 46.3144754, 46.3144754, 46.3144754, 40.7127281, 49.2608724, 22.3511148, 46.3144754, 46.3144754, 46.3144754, 32.0609736, 46.3144754, 46.3144754, 43.6534817, 38.8949924, 37.5666791, 28.2302056, 37.7790262, 46.3144754, 47.3744489, 46.3144754, 52.3727598, 47.2000338, 35.6828387, 46.3144754, 59.67928085, 46.3144754, 19.37218875, 42.317099, 46.3144754, 34.395342, 46.3144754, 47.6038321, 40.1117174, 47.3744489, 28.5656649, 46.3144754, 21.0294498, 46.3144754, 46.3144754, 32.7174202, 46.3144754, 51.4582235, -36.852095, 46.3144754, 18.521428, 46.3144754, 41.5051613, 46.3144754, 1.357107, 46.3144754, 54.7023545, 50.0469432, 46.603354, 40.4416941, 52.3727598, 33.7489924, 46.3144754, 28.2302056, 12.9791198, 39.1014537, 46.3144754, 46.3144754, 39.9065084, 42.9836747, 46.3144754, 46.3144754, 46.3144754, 51.5073219, -23.5506507, 53.550341, 40.4416941, 46.3144754, 22.5414185, 49.1923042, 46.3144754, 51.5073219, 48.6108441, 46.3144754, 52.5170365, 51.9035099, 30.2489634, 46.3144754, 43.6044622, 46.3144754, 50.0874654, 46.3144754, -19.9227318, 46.3144754, 13.2904027, 43.451291, 46.0499803, 46.3144754, 53.902334, 32.7174202, 46.3144754, 46.3144754, 46.3144754, 39.5162234, 46.3144754, 39.7837304, 37.7790262, 22.3511148, 46.9482713, 60.4517531, 40.7127281, 46.3144754, 12.7503486, 46.3144754, 46.3144754, 35.000074, 46.3144754, 46.3144754, 46.3144754, 46.3144754, 6.9349969, 46.3144754, 41.8755616, 37.3361905, 39.2908816, 46.3144754, 14.854918, 47.6038321, 55.7504461, 46.3144754, 46.3144754, 48.8566969, -24.7761086, 37.7790262, 46.3144754, 46.3144754, 40.0149856, 37.3893889, 55.6867243, 37.7790262, 51.0834196, 63.2467777, 46.3144754, 46.3144754, 37.7790262, 46.3144754, 40.7127281, 55.9533456, 46.3144754, 50.725562, 51.5073219, 46.3144754, 40.4167047, 29.6519684, 48.1371079, 49.4093582, 30.2711286, 4.6533326, 37.3361905, 46.3144754, 46.3144754, 46.500283, 46.3144754, 46.3144754, 31.2322758, 51.5073219, 46.3144754, 19.0759899, 46.3144754, 49.2608724, 10.7758439, 22.555454, 46.3144754, 48.1371079, 39.9065084, 30.2489634, 46.3144754, 46.3144754, 49.592949450000006, 37.7790262, 54.7023545, 26.4609135, 46.3144754, 51.5328328, 25.7741728, 42.6384261, -37.8142176, 46.3144754, 37.3893889, 39.9065084, 29.865002099999998, 39.7837304, 59.6749712, 35.000074, 35.000074, 41.1018669, 37.496904, 46.3144754, 57.1482429, 36.5748441, 46.3144754, 55.7504461, 46.3144754, 46.3144754, 46.3144754, 40.4258686, 46.3144754, 40.7127281, 45.5202471, 46.3144754, 40.7127281, 46.3144754, 46.3144754, 46.3144754, -27.4689682, 42.7355416, 46.3144754, 7.5554942, 46.3144754, 46.3144754, 47.6038321, 32.2228765, 46.3144754, 48.9467562, 51.5073219, 40.6501038, 12.9791198, 46.3144754, 48.1371079, 46.3144754, 47.3744489, -22.9110137, 46.3144754, 30.2489634, 22.5414185, 44.07517895, 43.6534817, 46.3144754, 46.3144754, 46.3144754, 51.0538286, 30.8118989, 42.3756401, 46.3144754, 34.4221319, 46.3144754, 39.9065084, 48.6108441, 46.3144754, 33.6856969, 39.9065084, 43.074761, 46.3144754, 41.2587459, 37.5666791, 39.9207486, 38.9583737, 52.215933, 43.6044622, 46.3144754, 12.9791198, 46.3144754, 39.08854049999999, 11.0018115, 15.5075545, 37.2333253, 22.3511148, 56.7861112, 46.3144754, 43.1875572, 40.7127281, -25.4295963, -34.6075682, 51.5073219, 28.6517178, 37.7790262, 46.3144754, 46.3144754, 37.5666791, 31.2322758, 19.7073734, 51.5142273, 31.2322758, 48.1113387, -37.8142176, 31.2322758, 13.7544238, 39.9065084, 46.3144754, 42.3750997, 46.3144754, 39.7837304, 37.8708393, 42.3750997, 52.4760892, -1.7765835, 47.6038321, 46.3144754, 22.3511148, 31.5313113, 43.619776, 46.3144754, 23.9739374, 46.3144754, -37.8142176, 51.5073219, 46.3144754, 34.0922335, 42.3602534, 55.382525099999995, 20.2667774, 60.5000209, 13.2904027, 43.6534817, 37.050096, 55.7504461, 48.2083537, 37.4443293, 12.9791198, 46.3144754, 46.3144754, 46.3144754, 46.3144754, 46.3144754, 40.0332629, 47.659216, 46.3144754, 46.3144754, 46.3144754, 61.4980214, 46.3144754, 47.3744489, 40.7127281, 46.3144754, 32.7174202, 43.6534817, 23.9739374, 42.3750997, -23.5506507, 12.9791198, 49.234362, 47.6038321, 37.7790262, 56.839104, 22.555454, 46.3144754, 43.6534817, 52.2034823, 47.2000338, 52.5001698, 46.3144754, 6.2443382, 42.3750997, 46.3144754, 46.3144754, 39.7837304, 40.7127281, 12.9791198, 61.0666922, 46.3144754, 50.4500336, 46.3144754, 55.0282171, 46.3144754, 51.5073219, 46.3144754, 45.6306954, 46.3144754, 46.3144754, 61.0666922, 51.5073219, 46.3144754, 37.7790262, 46.3144754, 45.5202471, 35.000074, 46.3144754, 37.7884969, 37.3893889, 39.9065084, 37.5164926, 47.6038321, 46.3144754, 36.7014631, 23.9739374, 46.3144754, 37.3893889, 32.7174202, 46.3144754, 51.0, 40.7127281, 12.9791198, 13.3519723, -33.8548157, 46.3144754, 46.3144754, 46.3144754, 48.8566969, 40.4416941, 46.3144754, 22.5414185, 39.7837304, 41.8755616, 46.3144754, 46.3144754, 46.3144754, 46.3144754, 37.7884969, 22.555454, 46.3144754, 39.9065084, 37.130408, 46.3144754, 46.3144754, 46.3144754, 45.4401467, 52.5170365, 39.7837304, 10.7775391, 53.535411, -31.9527121, 22.3511148, 47.6038321, 42.2681569, 35.6828387, 32.6475314, 46.3144754, 46.3144754, 30.2489634, 52.5170365, 46.3144754, 33.6856969, 39.100105, 43.6534817, 46.3144754, 46.3144754, 52.5001698, 49.4871968, -33.928992, 37.7790262, 46.4602978, 43.6534817, 43.6534817, 31.5313113, 46.3144754, 46.3144754, 29.6519684, 37.7790262, 12.9405198, 50.44876, 46.3144754, 41.8755616, -37.8142176, 51.5073219, 53.7974185, 30.6335392, 46.3144754, 39.7837304, 25.5357691, 36.0620781, 43.6534817, 46.3144754, 40.6501038, 43.6534817, 35.000074, 52.5001698, 54.7023545, 40.7127281, 46.3144754, -23.5506507, 46.3144754, 46.603354, 46.3144754, 46.3144754, 52.3726682, 46.3144754, 46.3144754, 51.346715, 31.94696655, 12.9791198, 59.3251172, 49.9954978, 9.931308, 46.3144754, 25.0375198, 59.7862895, 63.2467777, 46.3144754, 1.357107, 37.4863239, 46.3144754, 39.9065084, 46.3144754, -10.3333333, 47.48138955, 35.000074, 22.3511148, 46.3144754, 37.3893889, 55.7504461, 46.3144754, 26.9154576, 33.6856969, 46.3144754, 51.0834196, 39.9065084, 46.3144754, 37.8708393, 37.7790262, 45.4972159, 46.3144754, 1.357107, 31.2322758, 37.7790262, 46.3144754, 43.6534817, 25.7741728, 46.3144754, 46.3144754, 46.3144754, 51.5073219, 39.7837304, 40.2971825, 39.9162861, 46.3144754, 43.1177238, 53.2190652, 41.3828939, 46.3144754, 46.3144754, 46.3144754, 46.3144754, 44.0925118, 46.3144754, 46.3144754, 37.3893889, 52.5001698, 30.2489634, 31.2322758, 46.7985624, 46.3144754, 32.7762719, 30.5951051, 22.3511148, 51.0834196, 39.9065084, 45.7578137, 37.7884969, 59.3251172, 34.2331373, 46.3144754, -33.8548157, 46.3144754, 46.3144754, 51.3210437, 46.3144754, 37.3361905, 45.8133113, 46.3144754, 46.3144754, 40.7127281, 46.3144754, 33.7489924, -41.2887953, 55.6867243, 32.701938999999996, 51.5073219, 48.8566969, 41.0096334, 51.0834196, 35.6828387, 46.3144754, 46.3144754, 46.3144754, 61.4980214, 46.3144754, 46.3144754, 51.0834196, 7.5554942, 43.411391, 56.866557, 43.6534817, 58.81895, 30.2711286, 49.2608724, 46.3144754, -33.8548157, 37.7884969, -7.2459717, 35.7032751, 39.9601488, 46.3144754, 46.3144754, 61.0666922, 52.2319581, 40.7127281, 18.521428, 46.3144754, 46.3144754, 46.3144754, 30.2489634, 41.8755616, 44.5645659, 46.3144754, 48.6108441, 51.0534234, 37.8708393, 43.6534817, 39.9065084], \"legendgroup\": \"\", \"lon\": [-73.9495823, 120.2052342, 108.4265113, -89.3837613, 11.0480288, 118.7916458, 104.999927, 11.0480288, 4.8936041, 113.9256222, -122.6741949, -79.3839347, 11.0480288, -79.9900861, 116.3912391, 4.8936041, 116.30393496863539, 114.0543297, 11.0480288, -71.0582912, 11.0480288, -73.9495823, 151.2164539, 4.8936041, 0.1235817, -122.4199061, 151.2164539, 108.9352154, -122.0832101, -122.0832101, 114.0543297, 6.959974, 11.0480288, -121.9885719, -122.6741949, 11.0480288, -0.1276474, 11.0480288, 113.2592945, 104.999927, 116.3912391, 120.3781372, -107.9917071, 0.1235817, 2.3255977, 139.7594549, 11.0480288, 11.0480288, 11.0480288, 14.5208584, -104.900937, 11.0480288, 11.0480288, 116.3912391, 13.199959, 121.4692071, -77.0365581, -71.1056157, 72.8773928, 11.0480288, 77.5912997, -74.0060152, 11.0480288, 22.2660066, 11.0480288, -122.3300624, 10.4234469, 77.0299194, 11.0480288, 11.0480288, 34.7818064, -119.7026673, -75.9790215, -78.7812081, -6.2602732, 11.0480288, -118.755997, 144.9631608, -92.5617875, 11.0480288, 11.0480288, 11.0480288, 116.3912391, 11.0480288, -1.8237251, 11.0480288, -107.9917071, -72.93102342707913, 120.2052342, 30.316229, 8.6820917, 11.0480288, 11.0480288, -76.610759, 151.2164539, -122.3300624, -4.2488787, 2.1774322, 126.9782914, 11.0480288, 11.0480288, 11.0480288, 11.0480288, -9.1365919, -87.6244212, 10.0, 72.8773928, 11.0480288, 120.5810725, -122.6741949, 11.0480288, 11.0480288, 11.0480288, 116.3912391, 127.6961188, 4.8936041, 8.5539378, -72.505714, 11.0480288, 127.6961188, -122.4199061, 4.8936041, 11.0480288, 151.2164539, -121.890583, 11.0480288, 8.4034195, -82.4065585, 11.0480288, -88.207301, -64.9672817, -89.3837613, 8.5410422, 11.0480288, 11.0480288, 37.6174943, 37.6174943, 2.9999825, 11.0480288, -122.1545229, 83.3012842, 31.2718321, -74.0060152, 34.7818064, 11.0480288, 120.9820179, 11.0480288, 29.2675469, 11.0480288, 11.0480288, -118.755997, 79.9889673, 11.0480288, 11.0480288, -48.5496098, -73.9495823, 11.0480288, 11.0480288, 13.3888599, 104.999927, 11.0480288, 10.000654, -95.8801625, 11.0480288, 116.3912391, 11.0480288, 11.0480288, 11.0480288, -74.0060152, -75.690308, 11.0480288, 116.3912391, -122.4199061, 116.3912391, 8.694724, -82.5540161, 11.0480288, 37.6174943, -72.33465445105234, 77.20046039098466, 114.2999353, 76.2674136, -74.0060152, 113.2592945, 8.5410422, 11.0480288, 11.0480288, 11.0480288, 11.0480288, -122.4199061, 120.2052342, -74.4041622, 5.7480821, 6.1466014, 11.0480288, -71.0582912, 11.0480288, 11.0480288, -80.8408415, 11.0480288, 11.0480288, -90.24111656024635, 11.0480288, 11.0480288, 11.0480288, 11.0480288, -107.9917071, 11.0480288, 151.2164539, 11.0480288, 80.270186, 147.3281233, -3.2765753, 11.0480288, 21.0067249, 11.0480288, 11.0480288, 20.15108, 11.0480288, -100.4458825, 11.0480288, -97.6788934, 11.0480288, 14.165719, 34.7818064, -43.2093727, -122.3300624, 4.6667145, -89.82872, 30.316229, 11.0480288, -75.1635262, 1.8883335, -78.49973472559668, 139.7594549, -74.0060152, 134.755, 11.0480288, 11.0480288, 11.0480288, 9.1800132, -53.2, -122.4199061, -35.8771292, 11.0480288, 11.0480288, 11.0480288, 116.3912391, 11.0480288, -97.7436995, 11.0480288, -118.242766, 11.0480288, -122.4199061, 11.0480288, -112.0741417, -74.0060152, 11.0480288, 11.0480288, 11.0480288, -125.002441, 11.0480288, 16.97819633051261, 11.0480288, -122.4199061, 121.5636796, -122.3558473, -75.1635262, 103.8194992, 134.755, -88.05876255177395, 11.0480288, 78.6677428, 4.4631786, -122.4199061, -77.0365581, 77.5912997, -122.2941914, -100.4458825, 11.0480288, 11.0480288, 11.0480288, 78.6677428, -74.0060152, 11.0480288, -122.0832101, 20.5105838, 108.9352154, -93.2654692, -79.3839347, -118.242766, -74.0060152, 11.0480288, 11.0480288, 77.5912997, 114.2999353, -53.2, -123.1139529, 11.0480288, 104.999927, 116.3912391, 37.6174943, -78.9018053, 11.0480288, 11.0480288, 10.000654, 11.0480288, -79.9900861, -73.6103642, -78.6390989, 139.7594549, -46.6333824, 11.0480288, 11.0480288, 87.6855882, 78.6870296, -81.1515962, -0.1276474, -104.8253485, 11.0480288, 103.8194992, 13.0001566, 11.0480288, -60.575046, 0.1235817, -122.3300624, 72.9775643, -122.1779927, 100.4930399, 120.2052342, 116.3912391, 11.0480288, 11.0480288, 37.6174943, -122.0832101, -41.4685053, -122.3300624, -86.2746665, -4.8380649, 11.0480288, -79.3839347, -86.05267778244621, 11.0480288, 11.0480288, -122.4199061, -0.1276474, 116.3912391, 11.0480288, 11.0480288, 16.3725042, -123.1139529, -0.1276474, 114.2999353, 11.0480288, -0.1276474, 78.6677428, -79.5268023, 7.4652789, -123.1139529, 11.0480288, 11.0480288, -81.4639835, 120.9820179, 11.0480288, 11.5753822, 11.0480288, 77.5912997, 11.0480288, 19.997153435836697, -70.6504502, 121.5636796, -77.0365581, -81.6934446, 37.6174943, -52.37802, -100.4458825, 77.2090057, -71.1061639, 11.0480288, 11.0480288, 6.7763137, -121.6846349, -121.890583, -89.3837613, -97.7436995, 9.0999715, -122.4199061, -53.7680577, 11.0480288, 55.18876088183319, 8.694724, 11.0480288, -72.3959849, -90.24111656024635, 11.0480288, 80.270186, 11.0480288, -122.1923372, 77.2219388, 11.0480288, 11.0480288, 11.0480288, 11.0480288, -83.7312291, 3.2983696, 6.959974, 11.0480288, 120.9686833, -77.0365581, 11.0480288, 11.0480288, -122.4199061, -1.6340044, -122.4199061, 11.0480288, -79.9900861, -75.1635262, 0.1235817, 11.0480288, 11.0480288, 8.6820917, -81.518485, 11.0480288, 104.999927, -87.6244212, -122.4199061, 2.3514616, 13.3888599, -4.2690384, -107.9917071, 6.6327025, -71.1056157, 97.7453061, 11.0480288, 11.0480288, 11.0480288, 11.0480288, 11.0480288, 120.184982, -93.26218935778115, 10.4234469, 139.7594549, -122.4199061, 13.3888599, 11.0480288, 11.0480288, 11.0480288, 120.2052342, -111.8867975, 22.2660066, -111.9400125, -74.9426677, -117.8259819, 1.4442469, 117.8902853, 121.5636796, 11.0480288, 21.0067249, -87.2169149, -0.1276474, -97.7436995, 13.3888599, -79.9900861, 16.3725042, 10.000654, -106.6509851, -84.3902644, -73.8785937, 85.3205817, -73.37509176653637, -74.0060152, 75.76073875510204, -91.4984941, 30.316229, -79.0392919, -122.4199061, -79.3839347, 11.0480288, 11.0480288, 11.0480288, -78.49973472559668, 13.3888599, 14.4212535, -79.3839347, 11.0480288, 135.490357, -79.3839347, 11.0480288, 11.0480288, 104.999927, 78.6677428, 2.1663459513667513, 121.5636796, -99.5120986, 11.0480288, -87.6244212, 11.0480288, -79.3839347, -74.0060152, 11.0480288, 127.6961188, 11.0480288, 11.0480288, 174.7772114, -71.0582912, 116.3912391, -72.032366, 11.0480288, 37.6174943, 11.0480288, -118.5369316, 144.9631608, 11.0480288, -122.23963364918777, -81.4639835, 116.3912391, -84.4852469, 11.0480288, 11.0480288, 18.0710935, -81.1515962, 39.2803583, 11.0480288, 80.3217588, 11.0480288, -122.3504466, -120.737257, 11.0480288, 11.0480288, 11.0480288, 2.3514616, -122.4199061, -97.7436995, 11.0480288, 11.0480288, -100.4458825, 13.199959, 11.0480288, 77.2090057, 11.0480288, 4.750318, 11.0480288, 103.8194992, 11.0480288, -79.3839347, -122.1779927, 11.0480288, 11.0480288, 11.0480288, 135.7556075, 11.0480288, -73.6103642, -79.3839347, 11.0480288, -121.890583, 10.000654, 11.0480288, 11.0480288, -70.6504502, 11.0480288, -122.1779927, 11.0480288, 16.6113382, 2.1774322, 116.3912391, 11.0480288, 77.5912997, -122.3558473, -100.4458825, 11.2555757, 11.5753822, 97.7453061, -118.755997, -64.9672817, -84.3902644, 11.0480288, 11.0480288, 10.3852104, 11.0480288, 63.9528098, 104.999927, 11.0480288, 11.0480288, 116.3912391, 12.5700724, 11.0480288, 11.0480288, 11.0480288, -74.0060152, -123.1139529, 78.6677428, 11.0480288, 11.0480288, 11.0480288, 118.7916458, 11.0480288, 11.0480288, -79.3839347, -77.0365581, 126.9782914, 112.9335861, -122.4199061, 11.0480288, 8.5410422, 11.0480288, 4.8936041, 13.199959, 139.7594549, 11.0480288, 10.774163640502413, 11.0480288, -72.33465445105234, -83.0353434, 11.0480288, -111.763275, 11.0480288, -122.3300624, -88.207301, 8.5410422, -81.5856742, 11.0480288, 105.8544441, 11.0480288, 11.0480288, -117.1627728, 11.0480288, 7.0158171, 174.7631803, 11.0480288, 73.8544541, 11.0480288, -81.6934446, 11.0480288, 103.8194992, 11.0480288, -3.2765753, 19.997153435836697, 1.8883335, -79.9900861, 4.8936041, -84.3902644, 11.0480288, 112.9335861, 77.5912997, -84.5124602, 11.0480288, 11.0480288, 116.3912391, -81.2496068, 11.0480288, 11.0480288, 11.0480288, -0.1276474, -46.6333824, 10.000654, -79.9900861, 11.0480288, 88.35769124388872, 2.46575, 11.0480288, -0.1276474, 22.2660066, 11.0480288, 13.3888599, -0.2013368, 120.2052342, 11.0480288, 1.4442469, 11.0480288, 14.4212535, 11.0480288, -43.9450948, 11.0480288, 108.4265113, -80.4927815, 14.5068602, 11.0480288, 27.5618791, -117.1627728, 11.0480288, 11.0480288, 11.0480288, -76.9382069, 11.0480288, -100.4458825, -122.4199061, 78.6677428, 7.4514512, 22.2670522, -74.0060152, 11.0480288, 122.7312101, 11.0480288, 11.0480288, 104.999927, 11.0480288, 11.0480288, 11.0480288, 11.0480288, 79.8538463, 11.0480288, -87.6244212, -121.890583, -76.610759, 11.0480288, -90.0696648, -122.3300624, 37.6174943, 11.0480288, 11.0480288, 2.3514616, 134.755, -122.4199061, 11.0480288, 11.0480288, -105.2705456, -122.0832101, 12.5700724, -122.4199061, 10.4234469, 25.9209164, 11.0480288, 11.0480288, -122.4199061, 11.0480288, -74.0060152, -3.1883749, 11.0480288, -3.5269108, -0.1276474, 11.0480288, -3.7035825, -82.3249846, 11.5753822, 8.694724, -97.7436995, -74.083652, -121.890583, 11.0480288, 11.0480288, -66.750183, 11.0480288, 11.0480288, 121.4692071, -0.1276474, 11.0480288, 72.8773928, 11.0480288, -123.1139529, 106.7017555, 114.0543297, 11.0480288, 11.5753822, 116.3912391, 120.2052342, 11.0480288, 11.0480288, -125.70255696124094, -122.4199061, -3.2765753, 80.3217588, 11.0480288, 9.9351811, -80.19362, 12.674297, 144.9631608, 11.0480288, -122.0832101, 116.3912391, 77.89284393558924, -100.4458825, 14.5208584, 104.999927, 104.999927, -81.1515962, -122.3330573, 11.0480288, -2.0928095, 139.2394179, 11.0480288, 37.6174943, 11.0480288, 11.0480288, 11.0480288, -86.9080655, 11.0480288, -74.0060152, -122.6741949, 11.0480288, -74.0060152, 11.0480288, 11.0480288, 11.0480288, 153.0234991, -84.4852469, 11.0480288, 80.7137847, 11.0480288, 11.0480288, -122.3300624, -110.9748477, 11.0480288, 11.4038717, -0.1276474, -73.9495823, 77.5912997, 11.0480288, 11.5753822, 11.0480288, 8.5410422, -43.2093727, 11.0480288, 120.2052342, 88.35769124388872, -95.66567459425735, -79.3839347, 11.0480288, 11.0480288, 11.0480288, 3.7250121, -93.740504, -71.2358004, 11.0480288, -119.7026673, 11.0480288, 116.3912391, 22.2660066, 11.0480288, -117.8259819, 116.3912391, -89.3837613, 11.0480288, -95.9383758, 126.9782914, 32.8540093, -77.3579805, 19.134422, 1.4442469, 11.0480288, 77.5912997, 11.0480288, -120.05035277301698, 76.9628425, 80.06080046754784, -121.6846349, 78.6677428, -4.1140518, 11.0480288, 44.5375689, -74.0060152, -49.2712724, -58.4370894, -0.1276474, 77.2219388, -122.4199061, 11.0480288, 11.0480288, 126.9782914, 121.4692071, -155.0815803, 7.4652789, 121.4692071, -1.6800198, 144.9631608, 121.4692071, 100.4930399, 116.3912391, 11.0480288, -71.1056157, 11.0480288, -100.4458825, -122.2728639, -71.1056157, -71.8258668, 29.2922122, -122.3300624, 11.0480288, 78.6677428, 34.8667654, 7.0477082, 11.0480288, 120.9820179, 11.0480288, 144.9631608, -0.1276474, 11.0480288, -117.435048, -71.0582912, -3.932652590941667, 85.8435592, 9.0999715, 108.4265113, -79.3839347, -121.9905908, 37.6174943, 16.3725042, -122.1598465, 77.5912997, 11.0480288, 11.0480288, 11.0480288, 11.0480288, 11.0480288, -7.8896263, 9.1750718, 11.0480288, 11.0480288, 11.0480288, 23.7603118, 11.0480288, 8.5410422, -74.0060152, 11.0480288, -117.1627728, -79.3839347, 120.9820179, -71.1056157, -46.6333824, 77.5912997, 6.996379, -122.3300624, -122.4199061, 60.60825, 114.0543297, 11.0480288, -79.3839347, 0.1235817, 13.199959, 5.7480821, 11.0480288, -75.573553, -71.1056157, 11.0480288, 11.0480288, -100.4458825, -74.0060152, 77.5912997, -107.9917071, 11.0480288, 30.5241361, 11.0480288, 82.9234509, 11.0480288, -0.1276474, 11.0480288, -122.6744557, 11.0480288, 11.0480288, -107.9917071, -0.1276474, 11.0480288, -122.4199061, 11.0480288, -122.6741949, 104.999927, 11.0480288, -122.3558473, -122.0832101, 116.3912391, -122.2941914, -122.3300624, 11.0480288, -118.755997, 120.9820179, 11.0480288, -122.0832101, -117.1627728, 11.0480288, 10.0, -74.0060152, 77.5912997, 74.7870308, 151.2164539, 11.0480288, 11.0480288, 11.0480288, 2.3514616, -79.9900861, 11.0480288, 88.35769124388872, -100.4458825, -87.6244212, 11.0480288, 11.0480288, 11.0480288, 11.0480288, -122.3558473, 114.0543297, 11.0480288, 116.3912391, -121.6544974, 11.0480288, 11.0480288, 11.0480288, 4.3873058, 13.3888599, -100.4458825, 106.7051633, -113.507996, 115.8604796, 78.6677428, -122.3300624, -83.7312291, 139.7594549, 54.5643516, 11.0480288, 11.0480288, 120.2052342, 13.3888599, 11.0480288, -117.8259819, -94.5781416, -79.3839347, 11.0480288, 11.0480288, 5.7480821, 31.2718321, 18.417396, -122.4199061, 6.8418655, -79.3839347, -79.3839347, 34.8667654, 11.0480288, 11.0480288, -82.3249846, -122.4199061, 77.5794387, -104.61731, 11.0480288, -87.6244212, 144.9631608, -0.1276474, -1.5437941, 104.08155875763552, 11.0480288, -100.4458825, 84.8511222, 103.8318566, -79.3839347, 11.0480288, -73.9495823, -79.3839347, 104.999927, 5.7480821, -3.2765753, -74.0060152, 11.0480288, -46.6333824, 11.0480288, 1.8883335, 11.0480288, 11.0480288, -1.2620038, 11.0480288, 11.0480288, -2.2504329, 35.27386547291496, 77.5912997, 18.0710935, 9.5733619, 76.2674136, 11.0480288, 121.5636796, 10.4382542, 25.9209164, 11.0480288, 103.8194992, -122.232523, 11.0480288, 116.3912391, 11.0480288, -53.2, 19.14607278448202, 104.999927, 78.6677428, 11.0480288, -122.0832101, 37.6174943, 11.0480288, 75.8189817, -117.8259819, 11.0480288, 10.4234469, 116.3912391, 11.0480288, -122.2728639, -122.4199061, -73.6103642, 11.0480288, 103.8194992, 121.4692071, -122.4199061, 11.0480288, -79.3839347, -80.19362, 11.0480288, 11.0480288, 11.0480288, -0.1276474, -100.4458825, -111.694943, -86.05267778244621, 11.0480288, 5.8008839, 6.5680077, 2.1774322, 11.0480288, 11.0480288, 11.0480288, 11.0480288, 12.3991309, 11.0480288, 11.0480288, -122.0832101, 5.7480821, 120.2052342, 121.4692071, 8.2319736, 11.0480288, -96.7968559, 114.2999353, 78.6677428, 10.4234469, 116.3912391, 4.8320114, -122.3558473, 18.0710935, -102.4107493, 11.0480288, 151.2164539, 11.0480288, 11.0480288, 4.9367415, 11.0480288, -121.890583, 14.4808369, 11.0480288, 11.0480288, -74.0060152, 11.0480288, -84.3902644, 174.7772114, 12.5700724, -97.10562379033699, -0.1276474, 2.3514616, 28.9651646, 10.4234469, 139.7594549, 11.0480288, 11.0480288, 11.0480288, 23.7603118, 11.0480288, 11.0480288, 10.4234469, 80.7137847, -106.280075, 53.2094166, -79.3839347, 16.507886, -97.7436995, -123.1139529, 11.0480288, 151.2164539, -122.3558473, 112.7378266, -0.6492976, 116.35193921040275, 11.0480288, 11.0480288, -107.9917071, 21.0067249, -74.0060152, 73.8544541, 11.0480288, 11.0480288, 11.0480288, 120.2052342, -87.6244212, -123.2620435, 11.0480288, 22.2660066, -114.0625892, -122.2728639, -79.3839347, 116.3912391], \"marker\": {\"color\": [46355.0, 7120.0, 23898.0, 47849.0, 5369.0, 3878.0, 15132.0, 16146.0, 96749.0, 4149.0, 10399.0, 4679.0, 16750.0, 125.0, 9633.0, 7777.0, 862.0, 1001.0, 4230.0, 5411.0, 2421.0, 8813.0, 4161.0, 2394.0, 10784.0, 56737.0, 6008.0, 3372.0, 14607.0, 20039.0, 13274.0, 3942.0, 1084.0, 4463.0, 7862.0, 4010.0, 7398.0, 1712.0, 4274.0, 2521.0, 6482.0, 45302.0, 5340.0, 1937.0, 4256.0, 1386.0, 616.0, 1607.0, 1446.0, 3590.0, 475.0, 219.0, 1505.0, 2780.0, 265.0, 1696.0, 2564.0, 5209.0, 585.0, 314.0, 13392.0, 5169.0, 3075.0, 8327.0, 8974.0, 5668.0, 13632.0, 2.0, 894.0, 0.0, 4902.0, 326.0, 570.0, 234.0, 56.0, 8.0, 69.0, 130.0, 9.0, 1742.0, 1.0, 6.0, 0.0, 2.0, 11023.0, 45.0, 0.0, 226.0, 16.0, 0.0, 0.0, 1.0, 0.0, 105.0, 358.0, 24.0, 286.0, 17.0, 337.0, 5.0, 0.0, 1.0, 44.0, 374.0, 269.0, 18.0, 29.0, 22.0, 144.0, 867.0, 3.0, 1.0, 0.0, 8476.0, 60.0, 57.0, 308.0, 80.0, 0.0, 107.0, 4.0, 0.0, 0.0, 215.0, 68.0, 20.0, 107.0, 27.0, 1.0, 8.0, 0.0, 86.0, 11.0, 0.0, 205.0, 2.0, 3.0, 0.0, 0.0, 4.0, 0.0, 7.0, 34.0, 98.0, 0.0, 45.0, 352.0, 1015.0, 0.0, 0.0, 34.0, 13.0, 12.0, 0.0, 34.0, 0.0, 0.0, 1.0, 20.0, 1.0, 92.0, 0.0, 180.0, 1.0, 73.0, 0.0, 0.0, 20.0, 3.0, 346.0, 0.0, 16.0, 3581.0, 6.0, 19.0, 10176.0, 65.0, 1604.0, 80.0, 1.0, 67.0, 18.0, 0.0, 7.0, 9.0, 9.0, 27.0, 0.0, 16.0, 34.0, 11.0, 60.0, 4.0, 403.0, 1111.0, 11.0, 3.0, 70.0, 52.0, 0.0, 37.0, 1.0, 1155.0, 2.0, 0.0, 32.0, 0.0, 13.0, 4420.0, 1.0, 9.0, 40.0, 58.0, 132.0, 9.0, 1.0, 1.0, 0.0, 0.0, 958.0, 4.0, 70.0, 175.0, 738.0, 17.0, 0.0, 0.0, 14.0, 62.0, 6.0, 0.0, 43.0, 95.0, 1504.0, 29.0, 17.0, 109.0, 0.0, 0.0, 1419.0, 4.0, 7.0, 8.0, 0.0, 0.0, 3.0, 0.0, 17.0, 0.0, 18.0, 0.0, 0.0, 0.0, 98.0, 0.0, 0.0, 8172.0, 15.0, 0.0, 717.0, 0.0, 0.0, 54.0, 0.0, 12.0, 65.0, 2276.0, 186.0, 175.0, 2.0, 35.0, 0.0, 0.0, 5.0, 5873.0, 5.0, 7.0, 2325.0, 78.0, 2.0, 0.0, 0.0, 40.0, 42.0, 1101.0, 37.0, 0.0, 131.0, 76.0, 1.0, 320.0, 394.0, 1.0, 0.0, 34.0, 123.0, 18.0, 9.0, 240.0, 85.0, 67.0, 3.0, 177.0, 0.0, 3.0, 19.0, 558.0, 2079.0, 154.0, 826.0, 109.0, 287.0, 0.0, 0.0, 1.0, 2.0, 725.0, 4.0, 0.0, 0.0, 40.0, 0.0, 1.0, 7.0, 95.0, 6.0, 24.0, 362.0, 11.0, 11177.0, 30.0, 0.0, 155.0, 0.0, 3.0, 2.0, 5.0, 0.0, 1.0, 0.0, 0.0, 266.0, 1.0, 0.0, 37.0, 61.0, 3489.0, 1.0, 0.0, 30.0, 0.0, 58.0, 9.0, 1.0, 180.0, 22.0, 4.0, 19.0, 70.0, 8.0, 0.0, 2.0, 1151.0, 0.0, 35.0, 0.0, 204.0, 0.0, 0.0, 693.0, 280.0, 6.0, 73.0, 7.0, 57.0, 9.0, 17.0, 481.0, 0.0, 0.0, 27.0, 5.0, 565.0, 16.0, 5.0, 129.0, 98.0, 1.0, 0.0, 56.0, 50.0, 98.0, 146.0, 382.0, 283.0, 84.0, 2.0, 193.0, 39.0, 4.0, 0.0, 4405.0, 26.0, 5.0, 0.0, 194.0, 0.0, 195.0, 28.0, 37.0, 0.0, 604.0, 46.0, 782.0, 1818.0, 233.0, 76.0, 108.0, 36.0, 73.0, 0.0, 681.0, 41.0, 0.0, 2047.0, 37.0, 448.0, 841.0, 267.0, 0.0, 69.0, 0.0, 13.0, 0.0, 10.0, 9.0, 0.0, 91.0, 12.0, 2.0, 12.0, 64.0, 271.0, 2349.0, 192.0, 0.0, 0.0, 1796.0, 76.0, 306.0, 13.0, 1.0, 23.0, 2217.0, 0.0, 32.0, 0.0, 18.0, 84.0, 501.0, 16.0, 0.0, 2.0, 0.0, 173.0, 4.0, 773.0, 54.0, 0.0, 319.0, 2.0, 80.0, 145.0, 0.0, 22.0, 567.0, 0.0, 3.0, 76.0, 0.0, 55.0, 1.0, 235.0, 334.0, 12.0, 153.0, 33995.0, 14.0, 128.0, 18.0, 9.0, 251.0, 30.0, 196.0, 28.0, 444.0, 0.0, 4.0, 313.0, 0.0, 0.0, 0.0, 1.0, 489.0, 836.0, 0.0, 0.0, 0.0, 757.0, 70.0, 0.0, 7.0, 21.0, 519.0, 0.0, 35.0, 2.0, 819.0, 0.0, 498.0, 68.0, 4.0, 132.0, 3.0, 58.0, 13.0, 904.0, 3.0, 2.0, 0.0, 1611.0, 44.0, 22.0, 0.0, 0.0, 5.0, 83.0, 66.0, 22593.0, 0.0, 38.0, 117.0, 0.0, 0.0, 0.0, 419.0, 0.0, 0.0, 604.0, 153.0, 10.0, 442.0, 12.0, 38.0, 126.0, 900.0, 0.0, 0.0, 123.0, 24.0, 0.0, 11.0, 0.0, 353.0, 19.0, 0.0, 4.0, 40.0, 11.0, 135.0, 55.0, 0.0, 893.0, 0.0, 491.0, 119.0, 0.0, 146.0, 0.0, 122.0, 9.0, 0.0, 0.0, 6.0, 708.0, 9.0, 1080.0, 1.0, 67.0, 56.0, 560.0, 0.0, 0.0, 0.0, 19.0, 0.0, 41.0, 1.0, 0.0, 72.0, 64.0, 876.0, 0.0, 293.0, 20.0, 0.0, 234.0, 4041.0, 30.0, 36.0, 0.0, 0.0, 0.0, 1.0, 3.0, 0.0, 1370.0, 111.0, 1163.0, 8.0, 9.0, 6.0, 1.0, 0.0, 860.0, 1.0, 15.0, 300.0, 1.0, 71.0, 3.0, 113.0, 0.0, 4.0, 0.0, 0.0, 53.0, 30.0, 39.0, 7.0, 4636.0, 94.0, 0.0, 7.0, 181.0, 28.0, 0.0, 29.0, 4.0, 33.0, 703.0, 0.0, 2.0, 27.0, 0.0, 141.0, 12.0, 735.0, 171.0, 49.0, 1.0, 7.0, 1.0, 0.0, 1.0, 0.0, 12.0, 30.0, 0.0, 1.0, 0.0, 31.0, 0.0, 7.0, 0.0, 575.0, 0.0, 0.0, 57.0, 47.0, 0.0, 0.0, 18.0, 576.0, 2.0, 49.0, 28.0, 149.0, 87.0, 9.0, 0.0, 56.0, 1.0, 9.0, 0.0, 2.0, 0.0, 0.0, 12.0, 3.0, 0.0, 4.0, 9565.0, 283.0, 2.0, 805.0, 312.0, 14.0, 1.0, 19.0, 36.0, 0.0, 0.0, 334.0, 10.0, 26.0, 120.0, 50.0, 33.0, 1.0, 696.0, 3.0, 8.0, 0.0, 1.0, 2618.0, 14711.0, 0.0, 72.0, 2.0, 29.0, 30.0, 115.0, 88.0, 74.0, 32.0, 477.0, 254.0, 5.0, 4.0, 90.0, 6.0, 1.0, 8.0, 102.0, 2.0, 130.0, 0.0, 0.0, 24.0, 2309.0, 0.0, 12.0, 62.0, 4.0, 0.0, 0.0, 6732.0, 32.0, 18.0, 12.0, 10.0, 35.0, 18.0, 25.0, 37.0, 0.0, 74.0, 1239.0, 202.0, 130077.0, 0.0, 14.0, 21.0, 162.0, 24.0, 1.0, 7.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 433.0, 0.0, 7.0, 50.0, 3.0, 6.0, 3131.0, 0.0, 7.0, 24.0, 124.0, 166.0, 1.0, 5.0, 0.0, 33.0, 14.0, 0.0, 30.0, 148.0, 1841.0, 2.0, 0.0, 1.0, 10.0, 3.0, 29.0, 0.0, 1.0, 1.0, 725.0, 0.0, 46.0, 0.0, 0.0, 17.0, 4.0, 17.0, 89.0, 441.0, 101.0, 6.0, 269.0, 4.0, 182.0, 14.0, 3.0, 51.0, 24.0, 144.0, 15.0, 43.0, 230.0, 4.0, 0.0, 143.0, 0.0, 46.0, 50.0, 0.0, 0.0, 94.0, 5.0, 16.0, 1.0, 0.0, 92.0, 7.0, 7762.0, 6.0, 1475.0, 0.0, 2.0, 137.0, 0.0, 0.0, 99.0, 0.0, 1607.0, 123.0, 270.0, 17.0, 213.0, 523.0, 1000.0, 0.0, 12.0, 2837.0, 53.0, 47.0, 7.0, 67.0, 0.0, 19.0, 10.0, 0.0, 0.0, 35.0, 1.0, 11.0, 0.0, 57.0, 0.0, 30.0, 540.0, 0.0, 11.0, 36.0, 0.0, 7.0, 0.0, 759.0, 0.0, 126.0, 19.0, 0.0, 672.0, 0.0, 3.0, 3.0, 182.0, 0.0, 3.0, 11.0, 142.0, 27.0, 16.0, 4147.0, 1.0, 301.0, 4.0, 161.0, 123.0, 954.0, 1.0, 0.0, 0.0, 0.0, 1.0, 709.0, 0.0, 1.0, 56.0, 71.0, 44.0, 350.0, 11.0, 0.0, 0.0, 0.0, 2.0, 59.0, 8.0, 2.0, 0.0, 1848.0, 1429.0, 2.0, 7.0, 1178.0, 0.0, 38.0, 1.0, 6.0, 6064.0, 10.0, 0.0, 37.0, 0.0, 771.0, 69.0, 0.0, 0.0, 44.0, 161.0, 117.0, 34.0, 3.0, 0.0, 11.0, 0.0, 53.0, 52.0, 0.0, 9.0, 200.0, 17.0, 31.0, 27.0, 2.0, 0.0, 0.0, 28.0, 69.0, 227.0, 6.0, 7.0, 39.0, 12.0, 0.0, 268.0, 0.0, 0.0, 5.0, 1.0, 4.0, 8074.0, 0.0, 0.0, 168.0, 244.0, 2.0, 2.0, 16.0, 30.0, 319.0, 9.0, 1.0, 2.0, 114.0, 0.0, 0.0, 0.0, 13.0, 250.0, 0.0, 29.0, 163.0, 3.0, 3.0, 2751.0, 0.0, 0.0, 18.0, 94.0, 6.0, 39.0, 0.0, 592.0, 0.0, 0.0, 86.0, 42975.0, 0.0, 361.0, 0.0, 0.0, 16.0, 1848.0, 3428.0, 5915.0, 321.0, 4.0, 22.0, 11.0, 26.0, 0.0, 0.0, 3.0, 0.0, 104.0, 6.0, 3.0, 256.0, 348.0, 6.0, 107.0, 1.0, 0.0, 51.0, 0.0, 0.0, 2.0, 4.0, 74.0, 5.0, 0.0, 9.0, 0.0, 17.0, 830.0, 0.0, 0.0, 5.0, 217.0, 0.0, 209.0, 32.0, 262.0, 388.0, 7.0, 2.0, 509.0, 1.0, 1.0, 0.0, 0.0, 68.0, 0.0, 35.0, 14.0, 368.0, 369.0, 56.0, 32.0, 17.0, 18.0, 1.0, 49.0, 12.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 30.0, 138.0, 4152.0, 19.0, 33.0, 41.0, 4.0, 50.0, 5.0, 1.0, 0.0, 58.0, 0.0, 73.0, 178.0, 165.0, 0.0, 596.0, 1.0, 0.0, 1.0, 95.0, 22.0, 68.0, 2.0, 23371.0, 18.0, 9.0, 4405.0, 61.0, 29.0, 2289.0, 32.0, 3.0, 43.0, 8.0, 0.0, 9.0, 187.0, 322.0, 0.0, 15.0, 924.0, 18.0, 28.0, 42.0, 26.0, 852.0, 0.0, 665.0, 83.0, 0.0, 0.0, 7.0, 17.0, 6.0, 0.0, 30.0, 0.0, 0.0, 0.0, 0.0, 0.0, 9.0, 19.0, 42.0, 6.0, 49.0, 7.0, 5.0, 2.0, 3.0, 328.0, 1.0, 254.0, 1.0, 4.0, 6.0, 0.0, 643.0, 0.0, 792.0, 11.0, 579.0, 2.0, 357.0, 1.0, 337.0], \"coloraxis\": \"coloraxis\", \"size\": [11857.0, 5091.0, 5644.0, 15633.0, 4985.0, 2109.0, 7738.0, 5471.0, 16723.0, 1228.0, 1952.0, 5169.0, 3937.0, 8498.0, 3389.0, 4985.0, 647.0, 742.0, 1313.0, 1223.0, 1069.0, 2507.0, 1211.0, 1249.0, 2136.0, 27168.0, 1254.0, 794.0, 4808.0, 5998.0, 4717.0, 677.0, 966.0, 2493.0, 2732.0, 2909.0, 1054.0, 439.0, 2335.0, 1426.0, 2088.0, 17562.0, 807.0, 619.0, 1936.0, 495.0, 394.0, 493.0, 462.0, 2361.0, 249.0, 338.0, 368.0, 683.0, 226.0, 549.0, 688.0, 793.0, 515.0, 1031.0, 3274.0, 1129.0, 1306.0, 5843.0, 1396.0, 2429.0, 2748.0, 3.0, 194.0, 0.0, 1112.0, 58.0, 85.0, 73.0, 30.0, 6.0, 48.0, 27.0, 0.0, 496.0, 3.0, 18.0, 0.0, 0.0, 2981.0, 19.0, 0.0, 97.0, 13.0, 0.0, 6.0, 5.0, 0.0, 67.0, 97.0, 11.0, 144.0, 6.0, 159.0, 4.0, 0.0, 0.0, 11.0, 169.0, 58.0, 6.0, 11.0, 209.0, 47.0, 287.0, 0.0, 0.0, 2.0, 2105.0, 12.0, 21.0, 84.0, 34.0, 0.0, 27.0, 1.0, 0.0, 0.0, 13.0, 50.0, 3.0, 23.0, 7.0, 0.0, 1.0, 1.0, 36.0, 11.0, 0.0, 142.0, 0.0, 0.0, 0.0, 0.0, 38.0, 1.0, 5.0, 19.0, 17.0, 0.0, 7.0, 83.0, 253.0, 0.0, 0.0, 124.0, 1.0, 5.0, 0.0, 5.0, 0.0, 0.0, 1.0, 10.0, 1.0, 45.0, 0.0, 78.0, 0.0, 37.0, 3.0, 0.0, 10.0, 6.0, 248.0, 0.0, 16.0, 1858.0, 1.0, 36.0, 7694.0, 10.0, 646.0, 74.0, 2.0, 47.0, 7.0, 0.0, 5.0, 1.0, 8.0, 24.0, 0.0, 12.0, 11.0, 7.0, 19.0, 5.0, 60.0, 141.0, 9.0, 0.0, 19.0, 6.0, 0.0, 35.0, 0.0, 176.0, 3.0, 0.0, 12.0, 0.0, 10.0, 1338.0, 3.0, 4.0, 20.0, 34.0, 53.0, 7.0, 0.0, 1.0, 1.0, 0.0, 250.0, 5.0, 13.0, 81.0, 198.0, 1.0, 0.0, 0.0, 5.0, 26.0, 1.0, 0.0, 16.0, 19.0, 534.0, 4.0, 7.0, 45.0, 0.0, 0.0, 185.0, 0.0, 2.0, 6.0, 0.0, 0.0, 1.0, 0.0, 14.0, 0.0, 4.0, 0.0, 0.0, 0.0, 22.0, 0.0, 0.0, 630.0, 8.0, 0.0, 143.0, 1.0, 0.0, 20.0, 0.0, 10.0, 15.0, 425.0, 71.0, 74.0, 2.0, 3.0, 0.0, 0.0, 5.0, 706.0, 1.0, 2.0, 391.0, 1.0, 0.0, 0.0, 0.0, 36.0, 24.0, 243.0, 17.0, 1.0, 60.0, 12.0, 0.0, 77.0, 119.0, 2.0, 0.0, 56.0, 53.0, 8.0, 3.0, 49.0, 27.0, 8.0, 4.0, 22.0, 0.0, 0.0, 0.0, 222.0, 411.0, 25.0, 254.0, 21.0, 108.0, 1.0, 0.0, 6.0, 7.0, 112.0, 0.0, 0.0, 0.0, 10.0, 0.0, 0.0, 3.0, 46.0, 12.0, 15.0, 102.0, 10.0, 3783.0, 13.0, 0.0, 53.0, 0.0, 30.0, 0.0, 6.0, 1.0, 1.0, 0.0, 0.0, 58.0, 1.0, 0.0, 18.0, 33.0, 915.0, 0.0, 5.0, 6.0, 0.0, 14.0, 2.0, 0.0, 72.0, 11.0, 0.0, 4.0, 7.0, 0.0, 0.0, 5.0, 303.0, 0.0, 17.0, 0.0, 44.0, 0.0, 1.0, 61.0, 97.0, 4.0, 7.0, 8.0, 24.0, 6.0, 14.0, 170.0, 1.0, 0.0, 12.0, 6.0, 150.0, 14.0, 0.0, 86.0, 21.0, 1.0, 0.0, 24.0, 25.0, 36.0, 23.0, 54.0, 120.0, 46.0, 1.0, 68.0, 49.0, 1.0, 0.0, 1145.0, 8.0, 4.0, 0.0, 45.0, 0.0, 32.0, 12.0, 5.0, 0.0, 219.0, 12.0, 108.0, 365.0, 81.0, 50.0, 22.0, 12.0, 14.0, 0.0, 292.0, 55.0, 0.0, 512.0, 19.0, 209.0, 393.0, 264.0, 0.0, 23.0, 0.0, 4.0, 0.0, 0.0, 1.0, 3.0, 68.0, 2.0, 0.0, 8.0, 26.0, 56.0, 619.0, 76.0, 0.0, 0.0, 1996.0, 59.0, 108.0, 0.0, 1.0, 4.0, 438.0, 0.0, 16.0, 0.0, 3.0, 40.0, 166.0, 5.0, 0.0, 0.0, 0.0, 39.0, 2.0, 167.0, 9.0, 0.0, 78.0, 0.0, 40.0, 39.0, 0.0, 12.0, 247.0, 14.0, 1.0, 26.0, 0.0, 6.0, 1.0, 76.0, 96.0, 3.0, 43.0, 2634.0, 5.0, 71.0, 5.0, 2.0, 181.0, 25.0, 41.0, 4.0, 48.0, 0.0, 2.0, 115.0, 0.0, 0.0, 0.0, 0.0, 159.0, 162.0, 0.0, 0.0, 0.0, 320.0, 19.0, 0.0, 1.0, 15.0, 133.0, 0.0, 34.0, 2.0, 132.0, 2.0, 97.0, 42.0, 1.0, 76.0, 0.0, 16.0, 10.0, 204.0, 1.0, 6.0, 3.0, 101.0, 18.0, 12.0, 0.0, 0.0, 2.0, 26.0, 12.0, 4069.0, 0.0, 4.0, 15.0, 0.0, 0.0, 1.0, 67.0, 0.0, 0.0, 103.0, 24.0, 0.0, 171.0, 6.0, 26.0, 81.0, 88.0, 0.0, 2.0, 25.0, 28.0, 0.0, 6.0, 0.0, 80.0, 7.0, 0.0, 1.0, 14.0, 18.0, 40.0, 65.0, 3.0, 431.0, 0.0, 111.0, 47.0, 0.0, 25.0, 0.0, 40.0, 9.0, 0.0, 0.0, 9.0, 178.0, 8.0, 502.0, 5.0, 11.0, 13.0, 240.0, 0.0, 0.0, 0.0, 9.0, 0.0, 22.0, 4.0, 0.0, 25.0, 13.0, 214.0, 0.0, 53.0, 9.0, 0.0, 46.0, 1131.0, 13.0, 17.0, 0.0, 3.0, 1.0, 1.0, 0.0, 0.0, 601.0, 66.0, 159.0, 2.0, 0.0, 5.0, 2.0, 0.0, 351.0, 0.0, 4.0, 225.0, 0.0, 54.0, 0.0, 29.0, 0.0, 1.0, 0.0, 0.0, 30.0, 7.0, 8.0, 1.0, 918.0, 32.0, 0.0, 8.0, 48.0, 24.0, 0.0, 12.0, 14.0, 13.0, 146.0, 0.0, 0.0, 5.0, 0.0, 14.0, 4.0, 206.0, 66.0, 16.0, 0.0, 6.0, 0.0, 0.0, 0.0, 0.0, 0.0, 4.0, 0.0, 1.0, 0.0, 12.0, 0.0, 3.0, 6.0, 121.0, 0.0, 0.0, 45.0, 6.0, 0.0, 0.0, 6.0, 110.0, 0.0, 24.0, 64.0, 55.0, 37.0, 29.0, 0.0, 17.0, 0.0, 69.0, 0.0, 0.0, 0.0, 0.0, 5.0, 8.0, 0.0, 0.0, 3044.0, 55.0, 0.0, 187.0, 52.0, 4.0, 0.0, 59.0, 5.0, 0.0, 1.0, 250.0, 6.0, 24.0, 25.0, 20.0, 78.0, 0.0, 129.0, 0.0, 7.0, 3.0, 0.0, 241.0, 2652.0, 0.0, 28.0, 0.0, 6.0, 8.0, 34.0, 22.0, 14.0, 8.0, 333.0, 41.0, 2.0, 3.0, 8.0, 9.0, 1.0, 7.0, 74.0, 4.0, 23.0, 0.0, 3.0, 7.0, 896.0, 1.0, 5.0, 41.0, 5.0, 0.0, 0.0, 987.0, 56.0, 8.0, 5.0, 1.0, 16.0, 15.0, 8.0, 12.0, 0.0, 15.0, 308.0, 129.0, 37828.0, 0.0, 8.0, 13.0, 31.0, 4.0, 0.0, 6.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 147.0, 0.0, 1.0, 20.0, 1.0, 4.0, 883.0, 0.0, 11.0, 10.0, 56.0, 77.0, 2.0, 0.0, 1.0, 20.0, 23.0, 0.0, 11.0, 52.0, 336.0, 1.0, 0.0, 1.0, 10.0, 0.0, 8.0, 0.0, 3.0, 6.0, 529.0, 0.0, 8.0, 0.0, 0.0, 6.0, 3.0, 10.0, 19.0, 95.0, 103.0, 0.0, 23.0, 7.0, 67.0, 7.0, 2.0, 66.0, 8.0, 14.0, 1.0, 15.0, 77.0, 15.0, 0.0, 14.0, 0.0, 16.0, 28.0, 1.0, 0.0, 55.0, 1.0, 4.0, 0.0, 0.0, 43.0, 3.0, 2184.0, 5.0, 327.0, 3.0, 4.0, 138.0, 0.0, 0.0, 23.0, 0.0, 333.0, 96.0, 57.0, 1.0, 60.0, 238.0, 231.0, 0.0, 5.0, 456.0, 27.0, 17.0, 16.0, 32.0, 0.0, 8.0, 16.0, 0.0, 0.0, 3.0, 0.0, 11.0, 0.0, 31.0, 0.0, 21.0, 93.0, 0.0, 5.0, 19.0, 3.0, 0.0, 0.0, 60.0, 2.0, 85.0, 3.0, 0.0, 231.0, 0.0, 1.0, 6.0, 50.0, 0.0, 4.0, 14.0, 35.0, 20.0, 13.0, 1003.0, 1.0, 210.0, 1.0, 43.0, 24.0, 165.0, 0.0, 4.0, 0.0, 0.0, 0.0, 278.0, 0.0, 1.0, 18.0, 43.0, 2.0, 50.0, 9.0, 2.0, 0.0, 1.0, 3.0, 20.0, 4.0, 1.0, 0.0, 321.0, 472.0, 0.0, 2.0, 169.0, 0.0, 3.0, 0.0, 5.0, 1650.0, 2.0, 0.0, 30.0, 0.0, 264.0, 45.0, 0.0, 0.0, 1.0, 24.0, 16.0, 20.0, 2.0, 2.0, 7.0, 1.0, 56.0, 15.0, 0.0, 1.0, 89.0, 14.0, 3.0, 7.0, 5.0, 0.0, 0.0, 8.0, 13.0, 35.0, 1.0, 9.0, 25.0, 9.0, 0.0, 119.0, 0.0, 0.0, 0.0, 1.0, 6.0, 1673.0, 0.0, 0.0, 16.0, 121.0, 0.0, 3.0, 2.0, 11.0, 30.0, 5.0, 0.0, 29.0, 72.0, 0.0, 1.0, 0.0, 3.0, 115.0, 0.0, 21.0, 41.0, 2.0, 0.0, 1118.0, 0.0, 0.0, 1.0, 125.0, 7.0, 41.0, 2.0, 236.0, 0.0, 0.0, 87.0, 15395.0, 1.0, 97.0, 0.0, 0.0, 3.0, 516.0, 237.0, 2215.0, 155.0, 10.0, 46.0, 3.0, 202.0, 0.0, 0.0, 1.0, 0.0, 16.0, 2.0, 4.0, 69.0, 161.0, 0.0, 51.0, 1.0, 0.0, 36.0, 0.0, 0.0, 1.0, 3.0, 31.0, 1.0, 0.0, 12.0, 0.0, 12.0, 159.0, 2.0, 0.0, 2.0, 103.0, 0.0, 74.0, 11.0, 109.0, 96.0, 9.0, 3.0, 118.0, 11.0, 2.0, 1.0, 1.0, 17.0, 0.0, 28.0, 4.0, 147.0, 145.0, 12.0, 38.0, 8.0, 4.0, 0.0, 24.0, 8.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 14.0, 160.0, 930.0, 4.0, 14.0, 37.0, 2.0, 21.0, 0.0, 0.0, 3.0, 43.0, 0.0, 55.0, 19.0, 43.0, 0.0, 134.0, 0.0, 0.0, 3.0, 32.0, 12.0, 12.0, 3.0, 3855.0, 6.0, 19.0, 2368.0, 13.0, 0.0, 611.0, 15.0, 0.0, 11.0, 2.0, 0.0, 1.0, 53.0, 192.0, 0.0, 9.0, 134.0, 0.0, 232.0, 7.0, 4.0, 80.0, 0.0, 199.0, 28.0, 0.0, 1.0, 9.0, 3.0, 1.0, 1.0, 13.0, 1.0, 0.0, 0.0, 2.0, 1.0, 19.0, 16.0, 11.0, 2.0, 23.0, 1.0, 1.0, 0.0, 1.0, 172.0, 0.0, 77.0, 0.0, 1.0, 0.0, 0.0, 103.0, 0.0, 154.0, 3.0, 120.0, 2.0, 144.0, 0.0, 95.0], \"sizemode\": \"area\", \"sizeref\": 94.57, \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"\", \"showlegend\": false, \"type\": \"scattergeo\"}], {\"coloraxis\": {\"colorbar\": {\"title\": {\"text\": \"total_stars\"}}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"geo\": {\"center\": {}, \"domain\": {\"x\": [0.0, 1.0], \"y\": [0.0, 1.0]}}, \"legend\": {\"itemsizing\": \"constant\", \"tracegroupgap\": 0}, \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"autotypenumbers\": \"strict\", \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Locations of Top Users\"}}, {\"responsive\": true} ).then(function(){\n",
" \n",
"var gd = document.getElementById('38d63b3a-e36a-47f8-b810-a08955c38cd1');\n",
"var x = new MutationObserver(function (mutations, observer) {{\n",
" var display = window.getComputedStyle(gd).display;\n",
" if (!display || display === 'none') {{\n",
" console.log([gd, 'removed!']);\n",
" Plotly.purge(gd);\n",
" observer.disconnect();\n",
" }}\n",
"}});\n",
"\n",
"// Listen for the removal of the full notebook cells\n",
"var notebookContainer = gd.closest('#notebook-container');\n",
"if (notebookContainer) {{\n",
" x.observe(notebookContainer, {childList: true});\n",
"}}\n",
"\n",
"// Listen for the clearing of the current output cell\n",
"var outputEl = gd.closest('.output');\n",
"if (outputEl) {{\n",
" x.observe(outputEl, {childList: true});\n",
"}}\n",
"\n",
" }) }; </script> </div>\n",
"</body>\n",
"</html>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:40:23.257343Z",
"start_time": "2020-08-14T21:40:23.246373Z"
},
"id": "15LXz2R4WWnL"
},
"source": [
"figs.append(dp.Plot(m))"
],
"execution_count": 29,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "yiRIhcPQWWnL"
},
"source": [
"## Word Clouds of Descriptions and Bios\n"
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2020-08-14T21:48:19.777664Z",
"start_time": "2020-08-14T21:48:17.256618Z"
},
"colab": {
"base_uri": "https://localhost:8080/",
"height": 713
},
"id": "ZqEUrA55WWnM",
"outputId": "c03abecd-cf35-45ae-cd06-8246fd66874d"
},
"source": [
"import string\n",
"import nltk\n",
"from nltk.corpus import stopwords\n",
"from nltk.tokenize import word_tokenize\n",
"from nltk.stem import WordNetLemmatizer\n",
"from nltk.tokenize import word_tokenize\n",
"from wordcloud import WordCloud, STOPWORDS \n",
"import matplotlib.pyplot as plt\n",
"\n",
"nltk.download('stopwords')\n",
"nltk.download('punkt')\n",
"nltk.download('wordnet')\n",
"\n",
" \n",
"def process_text(features):\n",
" '''Function to process texts'''\n",
" \n",
" features = [row for row in features if row != None]\n",
" \n",
" text = ' '.join(features)\n",
" \n",
" \n",
" \n",
" # lowercase\n",
" text = text.lower()\n",
"\n",
" #remove punctuation\n",
" text = text.translate(str.maketrans('', '', string.punctuation))\n",
"\n",
" #remove stopwords\n",
" stop_words = set(stopwords.words('english'))\n",
"\n",
" #tokenize\n",
" tokens = word_tokenize(text)\n",
" new_text = [i for i in tokens if not i in stop_words]\n",
" \n",
" new_text = ' '.join(new_text)\n",
" \n",
" return new_text\n",
"\n",
"def make_wordcloud(new_text):\n",
" '''Funciton to make wordcloud'''\n",
" \n",
" wordcloud = WordCloud(width = 800, height = 800, \n",
" background_color ='white', \n",
" min_font_size = 10).generate(new_text) \n",
"\n",
" \n",
" fig = plt.figure(figsize = (8, 8), facecolor = None) \n",
" plt.imshow(wordcloud) \n",
" plt.axis(\"off\") \n",
" plt.tight_layout(pad = 0) \n",
"\n",
" plt.show() \n",
" \n",
" return fig\n",
" \n",
"new_profile.descriptions= new_profile.descriptions.apply(lambda row: string_to_list(row) if not isNaN(row) else row)\n",
"descriptions = []\n",
"for desc in new_profile['descriptions']:\n",
" try:\n",
" descriptions += desc\n",
" \n",
" except:\n",
" pass\n",
"\n",
"descriptions = process_text(descriptions)\n",
"\n",
"cloud = make_wordcloud(descriptions)\n",
"\n",
"figs.append(dp.Plot(cloud))"
],
"execution_count": 30,
"outputs": [
{
"output_type": "stream",
"text": [
"[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
"[nltk_data] Unzipping corpora/stopwords.zip.\n",
"[nltk_data] Downloading package punkt to /root/nltk_data...\n",
"[nltk_data] Unzipping tokenizers/punkt.zip.\n",
"[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
"[nltk_data] Unzipping corpora/wordnet.zip.\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAk4AAAJOCAYAAABBWYj1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOydd3hcV533P/feudNnNOrF6rJkybJsufeaOHYaqQSSQEIJPbRdILDsCwvv7rJAeIEAoSQhkEBCEkKK0+zYce9VtmTJliWr9zIjTS/3vn+MPJasUbFjOyE7n+fxY3tuO7ed872/dgRVVYkRI0aMGDFixIgxMeJ73YAYMWLEiBEjRox/FmLCKUaMGDFixIgRY5LEhFOMGDFixIgRI8YkiQmnGDFixIgRI0aMSRITTjFixIgRI0aMGJMkJpxixIgRI0aMGDEmiWaC5bFaBTFixIgRhQ7nILV9vShjlHTJtMaRb4tHEISr3LIYMa48gUCIuoZuTEYtWVMS3uvmXAnGfHEnEk4xYsSIESMKOxob+PdtmwkoStTlD5TP4zvLVozd+8aI8U+M0+Xjsad2MH1aBp/+2LKo6yiqitcbQK+TEcWx3wSP14+skdBopCvV3MvKZRVO72w4xjO/34rRrOeHv/k4tkTz5dz9BwaPy8e/f/7P2HudI3632ox868d3kZ71gVTvVxxVVTm0q5bnHttOXlEq93xhDfGxZzDGFcKo1ZJmtuALBgmpCiFFxRXwjymkPig81/QyFY5KPpp1GzNtpVf8eC3uNp44+1dmx5exPm0NWlE7ah1n0MVzzS9TPXAaRVVQUSkw5fJA/sfQS/qLOt4Z51mePPsMpdZi7si8CZ2ku1yn8oHCatHz7a9ej1Y7tozo6XXy+NM7+dz9K0hMiN4XB4Ihfv3YVm68rozp0zKuVHMvK5dVOLkGvbQ29GK26gmFPtidx7tBEAWSUq2oiorX46e/10l/jxPXoJdAIPReN++floA/yKFdp6k83EBnaz/LrpsRE04xrhg3Ti1iTW4+Az4fAz4vdq+XX+zfw97W5ve6aVcUR2CATm833pDvqhyvx9dHs7uVNH0KQSWENkpkrizITLdOwygZ6fR2cdxRRa+/f0w36nj4FT+d3m6mGNJRY9EqYyJJIslJlnHXqahsprN7gNA4HxOtbf2cquvgWn/J5W7iFSPmqnsP0OllPv/tG/F6Avi8AfZsruKpX295r5v1T49GIzG1JIPEFCuFpVNIz4xZ7mJcOQRBwCjLGGWZNLMZRVVJMhrf62Z94JhmKeArhZ8lSZeAfgzrj07SsjhxHosT53HGeZYG9wdbvE4WVYU//203qclxrL+mFLfbz99eOojXG+Bzn1iBRiOxaWsV/Q43t94wm5raDo5UNPKh68vZf6ie41UtIMCiefksWVCAVtbg8wd55PdbGBj0oAKL5+Vz43Uzhx1T5eiJZvYcPMPhY0309jl5+Neb0A1Zph74+HKyMxPo6h5k0/aTHK9spqW1nz/+dTc26xEA5s3O5UPrZyEIAqqqMuj08taWKmrrO9FIInPLc1myoACDXgbCAu3oiWZWL5vGtt2naWrpxWzSs3r5NGZOz0SSLm8eXEw4vQcIgkD8kFJXVZUz1W3vcYs+GIiSyJqbZrFsbSmiJKLVxR7vGFebWETT5cagMTDTNv29bsY/LQODXhqaelm7ejoDTi9bd9Yw6PTy8bsWYbUa2LX/DBlpNmSNRHfPIDv31dLZPYDL5SMzI57uPie9fS4kMSw+NJLIiiWFNLf28+KGI6QmW0cdUxIFMlJtnLF04/MFmD4tA7MpLHpNQ3+rqorNaiQ91Ub16Q6m5qUwJd0GQGZGfGRfHV0DPPyrjbg8fooL0/D6Ajzxl52cONnClz69GlmW6Ooe5M3Nlew9WE/WlHiSEy3U1Hbw3z9/g289uI55s3Mva5JGbGSJ8YFC0kgY/kkCDGPE+GdFQEAQBFo9HVQ5ahgIDGKRTZRYisg0ZiAK57/w650NHLNXkm/Opdw2Y8R+BgNO9vcdxhvysTZ1ZSSeyBvy8XbnNlxBd2TdAnMus21laMTLM2ypqkq7t4tKRzWDwUFMGhOl1mkIHyDxKwhQmJ/CxneqGBjw0N0zSLzNhCiJ1DV2Uzotg67uQRbNy+ecrmhs7qW8NIuvfe5a9HoZRVEIhdSI1UaSRBbOzaeowM3WnTVRjikwa0YWs2Zk0dbhQFVVblg7g5SkkQIrLTWOm9fNZN+hevYdqmfFkkJml2WPWCcYDLFxaxUd3QP853dvJTcrkVBI4dW3jvOXF/ZyzYoSyqZPAaCze4BrV5bwyXuWIssSre12vvn9FzhyoonZM7Mva+D5RT2BqqqG43K8AQL+IKqqIokiOoOMPE6A2IUoiopvaB9KSEEQBCRZRK/XopEnPjlVVQkFFXzeAMFACFVVIxYGrU6DKI42y6mqis8TwOPxo9PLGE06lJCC1+MnMLQPSRLR6cPnMpE6VVUVj9OH1+PDYjMhigKhkDKpbS8XqqqGr6UnQDAQRFFUBFFAljXoDPKE5klVVQn4QwT8QYLBEKqiggCSJKHVSmiHzKDRzkdVVYKBEM5BL7IsYbKEAzBDISXcnuDQfRFFtFoNWv3I+6KEFBx2N5IoYI4zIgjhGCWfNzAUHyeg0YTvh0aWxrymiqIy0O8aFYkgSSImsx5JM/Y1UFUVR78LQRAwWw2IokAwEMLrOdcGFUmS0Ok1E97XC5/J8WIr9AYtBuPoANcYHwT+d8TEiILIyYFT/KPldRwBB0E1hKIqmDUmPpp9GwsS5kTEU6O7hdfb32ZNyvJRwskVdLOjew+OwCArkhdHhJOiKtQ5G2h2tzEYHGQw6GRNynLK4qajuQzf+4qqcMxeyfPNr9Dj60UURCRBYnv3HmbFlX6g7mJhQSovvHqY3n4nJ0+1UZCXjGPAw6naTpLizfgDQXKzEiPrC4LA2tXT0Q1Z7EVRJMqQelUYGPRSfaqdnKwErBYD/Y6wkM5Ij0MrazhR3RoRTnFWA4vn56MZ6vPjrHqyMhPo7XNxCaFu43JRT6DX7WfX21Vse6OCM9XteN1+EpIszFtexNrb5ow7SJ1jcMDD0b11bH+jgtNVrdj7XOh0GjKyE1m4qpgV68qYkpsYVfyco6muix0bKzmyu5bmsz34fQGsNiMl5TksXl3M4jUlGEwjfeGqovLSX/bw9K82c/2H5/Opf1nH3s0n2fzqUc6e7sTr8ZOUamXOkqlcf+d8cgtTEccRHm1nu3j6xxuo2lfLdx77DHGJFvZvOs7Nn1qFrJMnfU3fDX09TvZsOcmezVU01HbhHHBjNOnIm5bOkmums+SaEhJTrFEHfEe/i5qKZo7uq+PUiWZaGnrxuHxoZInktDiKZmSycv0MZi+ZiixHf0wqDzfwb595klkL8vmvxz5JX/cg296oYPfbJ2lt7MHvD2JLMDG9PIe7P7+K7PyUyLa93YPcv/anJKRY+fULX6S9uY8trx7j8O5a+roHkSSB1MwE5i0rZN3t85iSkxj1PAbsLu6/7mH8vsCI3/OmpfPQj+8iZ2rKqG3O4fMG+NT1/w+tVsNP/vQAwUCIra9XsG9bDd0dDlBVUjJszFpYwHW3zWFqScaYIrK1sZftbx7n4I7TNNd34/H4wkL0AiRJ5O7Pr+beL6wZs10AnkCARoedTpcTp9+PoqoYZJl0s5lsqw2zVjumkFNVFYfPx77WZjyB8HWZlphEcVIy4jjizx8KcrSjnbbBQQCsOh0rsnORpegfM6qq4g0GaXMO0ul04vB58YdCSIKAXqMhwWAk02olyWga97hHO9posNvJtFqZnZaOoqqc6u2l0W5HEgXybQkUJiZG9mH3eqjs7qLP48EoyxQlJJJljRt1PfyhEPtamun1uEk2mpifMQWdRoOiKjTY7TQPOBjw+cLCWdaSE2cj02od83yvNoqq0ufx0Oiw0+tx4w0G0YgiVp2OKRYrWdY4NO/RiOYKudnVs5/rUlexKHEesihzzF7J622beKrhedL1qeSYsi55/wZJz1cLPwvAyYFT/LjmV5er6UA44PypxudwBd3cnnkTs21lBNUge3sPsb17D+6Qe+Kd/JOQnhJ+N3r7XNSc6WBWaRaBQIia2nYyM2yIgkDOMOFkMesxGXXvi/pjPl+AgQEPTa19fPmhZ0YskyRxRL9iNuow6M/3iwICGklEUdTLHuQ/KeGkqmEL0ct/2cvfn9yJa9CLRiNijTcxOODmjecPcPJoI+WLC8bdj9vp5ZlH32Hzq0cZHPCg08vE2Yx4PX5qq9qoq27nyJ4zfO6hGyksHT1IqapKdUUzT/zsLaqPNaGqKlabEUucEUe/m50bT3BkTy1nazu55/Or0BsuGFzUsIWiqa6LV/6yl3/8eTc+bwCLzYAmKNHa2EtbUx+1VW189ls3UFKeNebDs/lveykZZt40mPWcPFDH9R9ffsWFk6qqdLb289SvNrPr7Sr8/iBGk464eDOuQQ/H9tdx8mgjh/fU8tXv30p8knnUeVQfa+I3/7mB7g4HggA6vRZbggmfL0jL2W6a67up2F/Hp/91HSuvnzVmDQ5VDQu4rjY7T/96Mzs2VhIKhhBFEUVR6Gyz4/MGuPtzq6KeR3/PIMf21fG3P2ynqb4LvV6LJc7AgN3N2VMdNJzuoKmum889dAPpWQmjzkOnl7npowux9zkZtHtoqu+io6UfVVWZzNe/qqo47G5qTrTw2rP7qatuQ9ZKmKwGXINemuq6aarr5szJNr7y/VvILUwd0QZVVenpHOBXP3iZysONaHUaps/OwWzV097cR11NO6GggtGsp2xeLrmFqcxePHXMtoRUlRNdnTxTWcGJrk66hoSTChg0GtLMFgoTEvloaRlLs3IQiG4RDCoKr52u4Y0ztaiolKem89hNt5BkNI157MquLr69ZRMNDjsaUeSB2XNZkZ0bdV2718vWxnq2NpyNCLwBnw9/KIR4TjjpDWTFxbEiO5d7y2Zh1MhR2/rCyUqerTrBypxcfnbt9Ww+W8cTxw7TYO9HEkWmxifypfkLWZtXQI/HzS/272HL2Xr6PG4MskxZcioPLljE4ikj31dvMMAjB/dyuL2NmSmpPHbTbciBAH+vruL1M6docjgY9PsQAJM2LJxWZOfysbJyko3GSxw43v1gc06QvnSqmrfqTtNgt9N3gXDKsFhZlpXDR0rLyLRE/zi6kiiqwgxrMTemX4dRYwDgmpTlOAIO3mzfwv6+w2QZp4xw2V0MI85HEC576NhR+3E6vd2sS13N2tSVyGK4z07SJtDr62Nnz77Le8D3EEkjkpxopqfXSWfXIDnrEkAQ2LW/llNnOklKNGM0nLeAi4LA+0AzAWFxpNVqmDUji3vuWDDqOR9e4kAQuGohhpMWTvu2VvPS07vxefwsXlPCPZ9fTeqUeBRF4di+ev72h21seHb/0IA1mlAwxIt/2s2rz+4jLt7EF79zE4vWlGAwagkGFGqON/PkLzZRdaSRX/3wFf7r9/djjTeNaENTXTeP/fRNTle2MHdZEXd8Yil5RWmIosCgw8Orz+xj00uH2fDMPuJsRm79+JKorr+Tx5poPNPFtbfM5ua7F2G1GfD7ghzYfopnfreVUyea+dMjm/g/P78Hiy16lkzb2S5W3b6AtrNdkd+C/tBVMfF6XH6e/MUmdm6sJHtqKvd8bhUz5uYgazX4fUH2bDnJM7/fxoHtp3j84bf48vc/hME40gKXNy2dgpIMllwznQUrp5E3LQ1ZllAUlROHzvLXR9+hobaTDc/uZ1pZFhnZiWO0BrrbHfztD9s4caiBD39qOcvWlpKQbME54KG2qo3ms91k5iVF3TYUVPjVD1/FlmDiy9+7hUWritHIEs4BLy89tZuNLx3m0M7TTCvL5K5Prxh1P/UGLZ/46loURUVRFF58chd//e07F3U9VUXldz96DZNFzye+tpbVN8xCZ5DxeQO88dwBXnlmHzXHm3n9uQM88I316Id1MqGQwot/2sWJQw2kZSXw9R/eFrZMiQJ+X5Atrx7l6d9sQQBWrC9jxboZSGP42r3BIM9UHufRw/vp94QzViRBQKfRIADuQIDavl7O9PWyt6WZT5XP4f6Zs0dZnwRBINFg4CsLFlNv76e6p5uKznYeObCX7yxbiUEzWtjbvV5+sncnDQ47oiBwbV4B98+cE9Wi0eNx89133mZnUyPeUDDyu1aSMGg0KGq4rU6/n6YBBwfbWqno7OA/Vqwh2RRduAE02O0cbG/lx3t24AkGEQUBbzBIZXcnP9+3mxSjiReqK3nhZCWyJCGJIk6/n72tzfj3hfj5dTeMKSKaBxw0Dzj4U8URNtWfIRAKodNo0Eka/KEQdq8Xu7eDqu4u9rY08bO110e1Yk3Mu+sBVFXlrL2fn+7dxbbGs3iD4eurkyT0GpmQqtDjdtPtdlPV3cWWhjq+v3wNC6dkXlXxJCIyPa4Yw7AaSbIoM8NawpbOnTS5W3EF3Vjk92c5kBOOagySIez6E84Pg3pJT4m1iP19h9/D1l1eNJJIbnYSxyqbURSFvNxkJFHA6w1SUdXCzNLMK3Zsg17GHwji949dZkeWJSRJwOXyj1pmtRooyEumorKFjHQb8XHGSKad1xeIZOpdbSZ1VLfLxzsbKhjod1NYOoXPfuuGEUUaV6wvQ2+Q+cX3X8bvDUTdR11NB2+9eBCdXua+L1/LdbfOGeEKW7S6GFkr8aNvPMfZ0x1se/MEH7pnUWS5oqhsfe0Y1RVNFE7P4Kv/cQtJqXGR5ZY4I/c9eA1up5e3XznKO69XsOTa6VEH/FBQYcHKadz34LUYzecFxfo756ECv/rBK5w42MDxQ2dZem30Am/Fc/PZ/Pw+etr6aahu49jOUySk2yYVo/VuObqvjl1vV2GxGfny9z5E6eycEcuv//B8Av4gf35kM0f3nuHEwQYWrJw2Yp3UDBvf/NGdGM2jTbJLry3F4/Lz6H9voKmum642+7jCyeP2cXRvHZ/51vUsvbY0ElsVn2QhK39sV9k5NBqRT319HYvXlESeCUuckXu/uIbms90c3VvH8QP13PiRBcTFjxx4BUEYEV93MbF2wwkGQtz7hTWsvWV2RNhY4uCOTy2ns93OOxuOcaqyhd6uAabknBeBvV2D1FQ0o6qwYl0ZJbOyI8+A3qBl7a1z2PbGcU6daKGuuo3l182Iar0LhEI8X13Jw/t24Q0GkUWRZdk5lKemk2oyIwjQ6XKxr6WZw+2t9Hs9/PbQATSiyGdmz0O64B4KgkBRYhJfXbCYb2x+C6ffz6una5idlsGHioojGTIAvmCQJyuOcLCtFYDsuDgenL+INHP0Qc+q0zEtKZmtjWeJ1+uZnpxCcWIyUyxWLDotgZBC6+AAO5oaONHViT8UYsvZOkqTU/jM7HljusLanYP87vABihKTWJdfiC8U5O/VVdT191Hb18tjRw+xp7mJZVk5rM7Lx+X38/zJShoddo51tFPV3UmmZXSGD0C/18svD+xlV1MDebZ4VufmkxMXh0Ej0+f1UNHZwZaz9fhCQQ63t/E/u3fyw1VrxrTQjc27Ey+9Hjc/2LGVnU0NqECa2cyK7FyKE5Ox6LR4gkHq+/vY3tjAWXs/NT09fHfrZh5ZfyOlyRO/a5cLrShj1oy2ysVrbciiBlfQhSfkfV8KJ0VV6PX1YZIMmC44B0EQiNfakIT3h7v2ciBJInk5SWzeXk1BbjI2q5FgMEicVc/J0+3c+aE5F7W/PruL3j4nPb1OXG4/Pb2DVNW0YdDLpKVYMQ77SC8pSmfDxgpe23ickmnpBIMh5s7KwRZ33iCRkRqHLc7I65uO4/MHEEWR1GQL06dloNfJXLe6lMrqVn7xu80snJOH0ail3+GmubWfT969BIv54gqcXg4mNco4HR5OHDqLIMCiVcWkZcaPWC6KAuWLCsjMSxpVDRvCX/QHttdg73NRMiub8oUFo+KHBEEgryiN/GlpnDjUQMX+OtbfMRftkNvL7wvwzusVoMLqG2eRmDK6gzSa9cxdWsj2N0/QeKaT9ua+qO4ds1XP/OVFGEwjA3QFQWDR6mKef2IHHc197NlSzZJrpkf9krv2I4t5/U/b6Wzq5dUntjJtdh63fGb1JQ/ck0UJKWx59QihoMLcJVPJn5Y2ah2NRqJ0dg5JqVbamvvCFrqlU0dZOs4FdF+IIAgUFKdjMOro73HidvlQVXXML1pBEJi9qICFq4ovqV5GfnE681YUjXom4uJNFM/M4tj+ero7HPh9wTH28O5Jy0xg5fVlo6+RWU9xWRY7N1Zi73Hido4s+ud0uHG7fMhaiaQ06yjhbLLoI0U4+7oHCQVDcEGZBFVVOdTeyh+PHsYbDKLXaPjK/MXcOb2UBL0hInIUVeWO4uk8WXGUp44fxR0M8PjRw6zMyaMkKTnqea3MyePeGbN44thhHD4fjx09xIyUVKbGh98LRVXZ0dTA8ycrUVQVvRQ+9vQx9gegkzRcX1CIWatlYUYm6WYLCQbDCEEUVBRuLirmhzu2sqelCV8oxI7GBu4sKSXFFH0w9YdCdLtdPH7TbUxLTEJRVcxaLT/avQN3IMDms3WUJCXzg5VryI6zEVQVVBV+eWAPAUXhSHs71+UXjilddjU1sCAjk28uWU5ZSgpaSRO5rg6fl5kplfx8/+5wW5vOsvlsPR8uKR0hMifm0i1OiqryxLEj7GpuRAWKEhL53orVlKemY5TlyJe2LxTijuJSHtqykZM93TQ4+vnjscP8n+WrsemvziAiCELU7LOway78XE0mrkRF5WqXSg4fU0EUxKiuxLAF6n3iq7osCKSlxCHLEtOnpSMI4YDv/Nxkauu7yM06/yGo0YgYjdpxp0fZurOGjVtP4vMFsDvcOF1efvabTZhNOj5xz1LmzDyfGVc+I4sbry1j3+F69hysI8FmojA/dYRwSk2x8sl7lvL4n3bw6GPvEGczcesN5ZEq4kUFqfzLF6/j+X8c5MUNRwiGFKwWPWXTMyNVyzUaCYPhgnYLoNfJ6HWay54pOalRvqmuC4/bjygJzFyQF3UA1ellCorTqTzcMGqZc9BDQ20noWA4U6m6omlE7SKBcHfjdfsJBsOvkb3PxYDdQ1KqHGlDX3c4aNXrCbB788nIdsP3097cF8lwamvqY86S0edjjTeRnjlaUAEYTTqmlU6ho7mPhtoO/L4gOv1o14ZGlrjrK+v58JfXoaph8SiIAspQxfSx3DHvlu5OB62NvUD43A/tPI0QpWPv7xkMB8UpKl3tDny+IMYL2nQuM66/14m914nH7SfgDxEKhuhqt0cyJ4MTVDPXyBJzlkwdt/T+eJTNy0M3RlxYfGLY2uJx+1Gu4FQWM+bmjnDBDceaYESSxEjG3HB0ei1arYZQSMHj8qEoyojEhmAghNsVFltGky5qh+QOBHihuoqmAQeSIHDX9Bl8fGY5JnlkTJAoCKSbLXxtwWIOt7dytKOdPo+bp08c44crr4nqVtNJEp+YNYcGh51NdbVU93Tz//bt5qfXrsckyzTY+3nkwF46XU60ksR9s2azrqBwQrdPSVIyxUnJY8ZYaUSRooRE7p81m+qebvq9Hmp6exjw+cYUTgDz0qdQnJiEIAiIgsCK7FwePXQAdyBASFG4vqCI7Dhb2NIoSCyYMgWtJBFQFM7ah2Lbxmi7VafjqwsXMyctfdR1ten03D2jjDP9vbxYXYUrEODV09VcX1BI3EWJkUvvoKu6u3j1VDWKqmLUyHx/5ZpRcVvCUPxYaXIK31i8jK9vegOHz8fWhrPcMq2E5Vk5V8VlF1CC+BT/qA8qV9BNSA2hk3Roh+KGzi2NJqQCSgD/VapAfg4REYNowBEYxK+Mdg95Qp73QM5dOQQBZk6fwl9+++nIvRJFgc/dv4LP3LcCSRQionzF4iKWLyocVzjdduNsbrlh9uhvBIFR24mAq7abB25dwPyVxQhEWUcUmTEtg0KDAd/JDj75sRUsXTtj2HKBZKsBfa+bh793B9YEU6TfOfforVo2jZVLi0bs22jQ8m9fvyHcrsv8TkxqpOsdEiwCQlRLD4RPIiHZErXb8Lj8OOwuACoPN1J5uHHCYwYD4TT5c3S22SPxU0/9avNkmo3X5SNaP6rTySNcdMMRRZH4pHDH7vcFcQ16owqn1/+8gzV3LkQQIC7JgiiKtNZ38tLvNqORNdz62WtIzY6eCfZusPe58HrC7tCtr1Ww9bWKCbfx+wIRQQdEruPpylY2v3KExjNd9HQO4HZ68fmCBANBgkElalZYNERRICnt0gNUk9PixlwmDL0Iqqpe0UzvcdswdF4qo7+ik1KtZGQncKa6jaN761hzUzkJyUPTEKhQdaSRtqZetDoNBSXpUS2S/V4P2xrOApBgMLImNx+zNrqIO1etem1eAUc72lGBqq5Out0u0s2jpz8QBIE0s5kvzVtIRUc7HS4n7zTU8/Kpk9w1vYzHjx6msjscpzc3LYOPl83CKE+c3BC2OEy8Tk6cjVSTiX6vh0G/D18oNK718pxoOkea2YJuyJIlCgJlqSOD85ONJqQhq4HD6x23Pbm2eOamR8+MFAQBizacRbip/gwDPh9HO9rp9bgvUjhdGoqqsqu5kW53uJ+ck57BrJS0ca28RQlJFCcms7+thX6vh+OdHSzJzEZzFYRTUA3S4e0ipIYiMUKqqtLqacev+EnQ2jBpwlaFc4HXrqAbRVUiVh5VVbEHHPT57ZF1rwaCIJBlnEKd6yzdvt5RbWr3dhJQrpx1OxqqqtLd2s+eN47R0dxLWk4Sy2+aQ0Lq5Qn8FwQBSRopwAVBQLxgnfChxj+eKIpclA1WDb+7mnG8EUaTjq/+8DZ+88NXoganm6wG1t85H7NVH3U/0dp94TlfTiYlnHye83FL0UTEOfR6LdEuejAYirhZUjJs5BWNdi9dyJScxBHH8rj8kYFz1oJ89JOog5OWnRD141MQhTHLHQgCyEOuFEVRCQSiv0DHtlez89XDSJLITZ9cxeo7F/D6kzvIyEvF5/Wz4YmtPPCDOyds48Xi9wYIhcJWj7yiNFIybBNuU1CSPsICFgyE2LLhGM/8bit93YNYrAayClLILSwkIdmC2WLAOdaRbMYAACAASURBVODh70/uxDkw/mAEQ9fsUl2UAujHeaauFnrDpbVBZ5C59b4lVFc0U3Ggnv948C8svXY6FquBloYedm85ib3PxcJVxSxcVRIRgsOp7Oqk3+sBIMVomlSsSllKauTfvR4PTQ5HVOF0jtLkFP518TK+v20L7mCAJ44e5mR3NxtqwwXsko1GvrNsJVPGiBG6VEyyjF5z3iXmD41vvUy74BxkUUSnOf9sXRjDpNdoIu+4NxgcV1vPSk1DFse2BAuCwPSkZBINRgZ8PrzBIDU9PeTHX8zUPZem7gd9Pqq7uyITBC/OzBpx3tGIN+jJGHY9TnR1ElKUq1KiQEBgb89B5sWXk2lIRxBEun097Ok9iIDAzLjpyEL4nUrRJaOX9Jx1NXLGeZYcYziQfSAwyDtdO3GHPBMLp8v80bQwcS7be/bwTtdOiq2FJGrjUVVo83Zw1H6CoHp1hZN70MuvHnqWit2nCfpDaLQSx3ef5ju///SYfavfF6C/10nAF0TWarAlmtHpZQL+IPY+F35vAINRS1yiGVSVQYcnUq9Pp5dxOX3YEs2RmoR+fxCTRY/P40eURBKSLSghJfyxPuRxikswYzTpCAZCDPS7EEQBtzMcqpCQbI2UJLL3Dg9ruJibF6XkTL+LAbubtKyEEeEcfd2DaGQJt9OLoqjExRsxmvUIghC5NsFACKNJhy3BHLXvvVQmNdrphg0q48WZjCUyJI0YufmzFuTz1f+49aKDqIcPbA98c/2YNXUmQygYGnMyXVUN1/eBsCVlrIdWo9Xw4I/vwRJv4o8//Aer71xAd2sfN35yJUazjl987amo1q53i6zTROKI1t0+lw/du3hcs+qFqKpKc303f/3tO/R0DDBnyVQ+9sU1FJWNnM+nobaDV5/ZB0wsnN4174Pc10ttgSAIlMzK5ovfvZnHH36T2qpW6mraUVUVg1FLemYCy6+bwW33LSEpNbooOWfxAXD4vPyj5uSEpuVztZYgLBic/vHdHaIgsL5gKpVDpQ4aHHYaHHYAzFotX1mwmNLklIt+p1RVxen30zY4SJfbiSvgxx0I4g+FCCqhSAbYZLHqRlqCBUGIWJQEQRi1fPh1Ck1Q5S47buKPjFSzBZN8/qOs3t434TYjubQnacDvo3lgIPL/mp5u/lRxZNxtQqpKg6M/8v8et/uSJrW9FKyyhQRtPI/W/ZESSxFaUctpZx0NzkaWJi9kbkJ55FnKNWUxy1bKtq7dPFb/NCXWQkRBpN7ZSEgNkWFII6Cc/zgPKiHqXGfp8HbhC/lo8bSjoNDkbmFz53aMkgGtJDMzrhSrbEFRw8sa3S34FT8dni7cQReqqrC5azsmyYgsykyzTCVFF7ZoFlryWZW8hG1de3jk9GMUW6eiqApnnGeJk63oxOgeiStFT7udw9uqI1b+gC/IsZ2n6GrpY0qUBJuAP8irf93LqYpmjBY9RpOW9XcuYEpeEjs3nuDgjlPIsoZQMMSaD80mZ2oqTz3yNjq9TGdbP+mZCfR2DTB3WREGo47tb1YgyxpkrYTRrKOz1c5DD3+UQCDI35/YgdcbwOf2kzolng9/ZiUD/S5+/t0XycxNIqQo9HYNcv2H57P4mul0tvbz+E/fGPLs6Glt6H1X1+bMyTZ2baqktbGHb/74rkhS2B8ffhNRCmsL16CHxFQrH/nMKnQGLVteOcKp482IokjAH+TW+5cydahQ5uVgUsIpcWguGhWVnk7HiIy6c4Rr8jij+rENRh1xQ2n9jj4nzgEPtouctT4lwxZWjCFoOdvD1JKMi9p+OD5vANegJ+qyUEihrys8KOkNMmaLIep6lngTpjgjBrMeR98gDSdb8bp9hIIhtHotyiTdXBeLLd6ETh/u2Dta+wgGgpEA+slSdbSJ7nYHOr3MRx5YQfGs0fWqwjFFH6T6uVcOVVXp7nTgHPSy5Jrp3PTRhRHLZVy8iZR027jz5vV5zj+LLYMD/Gj3jos6flAJ4ZvAkgNgkrV8qnwORzvaON7VCZwTVIXcVFg8adGkqiqKqtI04ODv1VUc7Wij2+UecsWFRVNIUQipKiFFuajvzfEsQpNZPh5W7cSDoVGW0Q4Lch+cQJBeLvyhEE7/+XibDbWn2FB76qL24Q4Erko5FI0okWlI596cD1PpqGZXzz56ff3Ea+O4NfMG1qQsRyuc75NkUeaOKTdj1Vg43H+M3T0HMGtMlMVN57q0VbzZvoVaZ30kgDegBtjVvY/9fUcIqkFCqoIkiDS5W2h2t6ERJDSihn+dljIknFQO9VewqWMrQTVESA0BKj7Fzz9aXkMSJDSChvtyP0KKLhwIrRVkbp9yE8m6JHZ072Vnzz5schzLkxaxOHE+/1PzyxFlCq40Hqd3VCkfVVVxDUQfp05XtrJ/aw0Pfv8WktNtBPxBDEYtbqePba9VcMt9Syiemc3B7TW89sw+Pv/dm3H0u7jnC2vY/sZx4hJMzF4ylRMHz5KZl4wt0cxNdy/i1z94ma/+39v58y820dnaT/bUFG6+dzFGsw5Hn4vHf/IG3W12dAaZQbubucuLmLWwgG2vH2PfO9UsvmY62984TlJKHPd86RrsvU4e/vYL7+razFlaSFZ+Mj/7zt9H/K4oKjqDhvu+shZHv5M//XwTXe12JEnk+IF6bv/kcpLS4tj04iHeeuEgX/repRtbLmRST0Z2QTJGkw6P28ex/fXMmDt6wjy/L0hdTXtUq5zFaiC/OJ1922qoP9VBw5lOZiWYLuokcgvTSEqx0tHaz86NJ1i6tvSSg5EdfS5aGnopmZU9ynzndno5VdkCQEFxBrI2eke98tZ5/PY7z6KqUDgrl7/94k1MVgOb/7YHS7yJtJykK2JIScmwkZWXRFNdF0f2nOH2+5eRkj7xl/RwujvClgZJI5JfnD7qPiiKSl11Ox731Q3a/Gelo6Wfpx7ZjNVm4FP/sm7MKudj4Q6cHzC1koRlEgP8cCxaLdpJCApBEDBrtSQYzrtFJEEk2WhCJ0mTspWoqsqg389fThzjyWNH6PN6UFQVWRRJMBhJMhgxyDKyKCKJIoGQQm1fL67A6CDcaEyYwfYu3qnJbCoIAtKwPsEXvDoum5Ci4B9WE8ui1Uay/iZLnE53VXLB7sv5CCqgESRyjJmsT1uDSvj6SoIUmcduOAlaGx/OuoU7Mm+KrCsKIiIin867FxU1IlT0oo77cz/Kx3PvGrcd59aXBJFbM27gQxnrxl1fGiaEBEEgTrZyY/raqO3/8czvISBctbIESVPiiUsw4xiWlR6XaCFtjDIwzXVdpGXGk10wZCUemimjs9VOMBAitzANk0VPYVkmLz+9B5fTi8GoJSHFgtmqJy0zHrPVEEm4sSWaSU6PQ2/QkpIRj96ow+f109nSz+t/28+gw43fF8TR78LnC6AzyCSn28iZmorJoiclI54ju89E2jZ7yVSsNiOyLDEld+xSNpNn9JMtaUSKZ2URl2ACIRxG5PcF8Xr8VB5uwNHnQtKIKCGVrPzky+oBmtSbaY4zMmNuLgd2nOLA9hquubl8RF0fVVWpOtJAU11X1O0FUWDhqmLeeP4gPZ0DbHh2P/nT0rGOUVzS4/ajGebeA9DqNKy5uZxnfr+VigNn2f12FcuvmxHV5RcKKfi94ZsbLZbJ4/azb2s1i9cUY7Yazgf/qiq73q6ip8OBIAosvqZkzAFwzupSEtJs+L1+8kqzEIRwqYB3/r6fnjY7N35i5dgX9F0giiJrb53Dvm01NNd388ZzB7j786ujxp6pqorH7Uer04yY4NBiDVvRlJBKV7sds9UwYpuutn52bqwcEdsWY2w6W+34fQH8fi1tTb2kpNuQtWPPr3chpmGB4NMSk/jKgsUXdXxZFCkep3zAOXzBIC+crOJAW0vkt4AS4h81J5mXMYXVOdEzZi/k2crj/PrgfjzBALIoMj9jCusLCimITyDZaMKi1aHXaJAliXbnIN94+80R7sj3iuHFOscipCgEhyVSGOWLnVPw0mw+0rBYLo0ocm9ZOXPTL86qbtZqR1jLrhTDJ9kVECZVHVwQBCTOu11H7O8Cy44gCBdl7QmvLwEXd+7nSipEa78sXN24y7gEM3d/7Xpe+9MOutv6yZyayu2fXYPFFr2OmMGkxTngQVHUEQHQWp2GkKJE+m730CwfeoN2RGntCw0Gw5M9hncBb75wEFkr8fnv3ISiqvzfL/8lskzSiBeEiYSfff1Q22CoCr57ch9Nl0K0UBqNRiKvKI0vfe+WSN0/URQuKqRlIib1dBpNOq69dTanK1uor+ng0f/awEc/u4r0rAQURaXqaCPPP7Z9RBbcheQVpXHnJ5fx5C82sW9rNU6Hm3W3z6NwxhR0OhmP20dzfTdVRxupOd7CN/77jhGFBkVR4NpbZlNzvJlj++r4/f+8zsmjjay6YSaJqXGgqvR1D3L2dAeH95xhSnYi93xhTdTJVCVJ5Ni+On77369x+/3LiE8y4/cF2b+thuef2AEIzFtaSOmcnFHbnkMQICMvOZz9N2yetHX3LA1PGKyJPnAqikowECQUVFAUlVBIwTuUrq4MmWYHBzyRGy1J0qhBuHxRAetun8uml47w8l/20trUy5qbysPz6w1VUW+o7aTqaCP9vU6+8r1bzmd6ASXl2RhMOrweP3/7w3bu+fxqbAkmFEWlpaGHp3+zhaYzXWg0YqQ8xPsRRVEJ+IOEQuEMQEVR8A7FpykhBdegF+fQtRREAY1GuiJ1tvKmpZKSYaO1oZef/duLGM3nyw6IoojZqqdkVjYrri9jaknGKLE/PD1fK0msyM65aGvDRKiqyoG2Fh4/egh3IEC83kC+LZ4TXZ10upz8ZM9OSpKSxw0wh3CRyicrjuAJBhAFgduKp/P1hUtIMZmjxmX1uEdPwPxe0e1yTbiO3esZIbASDReb7XVpnbNO0kTit4KKQp7NxjW5+Ve1GniM9w6NLHH9x5ey9MZy/L4AeoMWa6J5zMepbEE+m18+wt+f2MH0OTl4XD6y8pOJT7KQXZDCpn8cZObCAva8XcW85dOQJxVTPPpgeoOMvddJa2Mvh3aeGneMP8fCVSW89OddpE6JZ6DfTVvjxDFObqc3UjOwv9dJb+cA1ngTkiQyYHfR3R7+OO3pGECWNWEr0xhk5iUTF2/inQ3HKJufx2C/G2uCiRlzcydsx2SZVO8sCLBgxTQ6PtHHc4/t4NCuWo7sPYPVZiLgD+J1+ymemcUD37ieX37/paj7kCSRG+5agN8f5I3nDlBx4CwVB8Ip2KIojIiniYs3jSpYJQgC6VkJfPahG3jqkc0c2nWaDc/uZ8Oz+xFEYUTqvCAK3HTXgjG7sOyCFGYtzOftl4+w/a0TWKwG/P4gbqcPQRQonZPDfQ9ei2mciqQtZzp57Y/b6Ot0IGlEvG4/KZkJPPCDO8eNObL3Otn4j0M013fjdvvxuv10tYUDPF2DXn79n68SF2/CYNSiN+rIn5bG7fcvHbEPnV7mY1+8Br1By9svH2Hnxkp2bqyMpGQO95WXlGePqgOTNy2NG++az4Zn97PjrfD8fokpcXg9Pno6B0hMtvLAN9bz1t8PUXV04tIR7xX93YO88sxeutvteNwBPC4fbc29qGrYffbof71GXMK5a6mlZFY2N35kwWVtg6KoOPpclM7Ooa2pF0e/i8EBT6TG2LkyENUVzWx+9Sif//aNrLm5fMQ+5qSlnz8nj4cGu52ixOhT1FwqrYMD/M/uHfR43EiCwIenz+BTs+bwzS1vsbOpkdO9PTy8dxf/Z/kqbProcX0AB9tacfjCCQNGjcwX5y4cqmwe/W0b8PlwB94flsua3p4J12keGGDAd95FPVZh0ctNvF5Pvi2ew+3h+naVXZ3cUlQyYWZdjA8GgiCg1ckkTTLsIj7RzJe+dwvbXq9g51snSEmPI7cwDZ1e5p4vrGHXxkoObKuhsHQKy9aVoaoq5YsK0Bu0TC2dQnySGaNZT0l5DgkpVuKTzMhaDQtWFaPRSJQvKojEPW188RDbXq9g+pwcsgtSiIs3oTdqmbu0EOPQGJmcbmPO0iIA5i4txDng4dj+erLykvn4l9dOmP19urKFPZtPYokzcLamne52O+vumIc5zsg7G47R1thLblEam18+TEFJBtfftYCZC/LJyA7HW2u1GsoXFRCfZCY+ycwn/3U9O986wa63TmCxGVm+vuxd3J3RTFI4CegNWm6+ezGpGfG8s+EYtVVteDx+ElOsLFlTwrW3zMYSZ8Bg0oVT36P0ozq9zC33LqZsbi473jpB5ZFGOlv78XkDGIw60rMTKJqRyeyF+SRGyUASBIHcqal86d9v5vCuWg7uOs2pEy0M2N0IhP20mXlJzFqQz/zlRWMG5GpkifV3zKN4ZhZvv3yE+lPtqGpYUM1fUcT62+cxJXf8OJWNf92FLdnCQJ+TedfMoLOpB6fDPeH3pnPAw953qsPxYMM4l8bZUNs54veudju337d0xPU8VzPr3i+sYdaCfHZvrqLmeAs9nQ5CQQWzVU9mbjLTyjJZuHIalriRA6HRpOPOTy4nJSOeLa8epbWxh672fuITLaxYX8b62+dSUp5N89luak40j5nGKQgCkkYc07o2EedKJIy3qSCELUWSRhz1TA043OzcWElXu/2C/YoEgyHO1naM+N3j8o8STuf2Ha2I6PA2SBoJjTTyPFVF5fiBev78yNu0NPSw9pa5zF6cj94YjjVR1XApju52O5tfOUpdTTsvPLmTWQvzR9RDm5qQyBSLhdbBQTqcTg60tTA1PmHMkhkXw7mstz8cOcSpIeFQmpzCp8vnkGw08ZUFS6jt7aXD5eTt+jPMTsvgI9NnjDktSr/XE/nIMcgyGRbLmPdeUVXq7f10uUbPJvBeUNPTTZ/XM6YVSVFVqro76fWEswDj9QZybBcXP3iprjqjLFOanMqG2lN4g0G2NjTw4HwvKZr335QlMd57BEEgLTOBj35u9ahl8UkWbr53tLt//Z3zAViwsjjy23CvDsBt9y8DYN0d8yK/feSzq6K24ca7z0+JlluYSm5huESKIAmsvqmc1TeVR90uGuWLplK+KPrk53d8cnnU39feNjfyb4NJx7qh8wNITLFy631Lo212Wbiozxm9QWb5ujIWrykhFAxny4iCgEYrRVLZn97yLQAMY1Rh1hu0lJRnUzQjk2AwRJfHgT8UJMOYgCSGB6hzImIsEpItXHvrbFbdOItQKIQ65E0SxHDBK0kjhd0zY3XoioJOL7NiffhclNDQuYjnB+mJhEBncy/3fecWtr14gNziDBasLePR7/yNYCCEPI7FKTMviR8/+QDqJKtgi9JowXAOo1nHgpXTmLNkKqFQ2PXHUACcKIlhUSONPhdBELAlmrnxIwu47rY5kYEwLFJENHJYIHz8S9fw0c+sRDtGnaWyeXm8sPu7gDCiZMVkSEyx8vyufwMYc/8A6+6Yy5qbZsGQeB9OTkEKj7744JgTS1/IhdXcdXqZP7/9TVDVcV14i9eUMHdpYWSbcwwOeHj615upOdHCPZ9bzUc/uzLihhseN6cqKjlTU/nJQy/Q0+Ggrrp9hHBKNBi5s6SU3xw6gDsY4MmKoxQlJDEvY8q4ZQkUVcXu9WKQNVEn7oVwyvqL1VX8o6aKkKqSbjbzb8tWkmw0gSAwKzWVL85byE/27mTQ7+eRA3spSkxkfvqUqO+AWauLCF1fMIjd6yF5jErgTQ47z1RW4HqfWJw6XU6eqzrBp8rnRmpLnUNVVRoddl45VROZWPfavHzix7G+RefSXGuCIHBdwVReqK6kqruL1kEHD+/dxUNLVpBgMIzbH4Uz8nxYdfqrUsMpRoz/7VyUcDpXWVSrk2GMxB+jaeKMIEEQ0MgSGlliX9dpurwDPJh8/UW2Q0CrE7nIUwijhjtKURTGLeg5HqlZibTVdZGRl8KOVw5RMr+Agd7BCbcTRTFq3NWlcK4zlbUaLuUsJElEMmjD06ooXfQ5n4YAJIgfQ9akhfer1aCqKoFQK75ALSb9UkRBO2SFESKm2otFFCe3rSxrkOXo91iURAyTeN7GQhCEST2vGo00Irj+HIMON6cqWxEEgaVrp0cVX4IgIEgCFpsBk1WPvdeJzzdSSGgliZuLStjT0szBtlbq+/v4922buW9mOYumZJFri0cjiqhAcGg+t/r+fiq7OznR1ckX5i5gxrCCmMOp7OrkD0cP4goEMGhkPl42m/LU85mUsihxc1ExRzvaefnUSbrdLn62dze/Wn9j1KlRpiclo5UkfKEQ7mCAp09U8JnZ87AMq6/kD4Wo6OzgD0cOcqS9bdQ+3it8oRBPnziGRhS5o6Q0YnkKKQp19j5+dWAfh9vDEx2nmExcP7UIw1V0laWbLTwwey7f3boZdyDAq6drcAUC3FY8nTlpGcTrw8X9VMDl99M66KC2r4+KjnYkUeSzc+aTYLhYoRcjxgeHNxtP0eoaGHO5QdJwT1H5hIaRiXgfOND/OYMfr7t7KTqjFoNZz8mDdbzw642s+NDcca0n72ckIQ6LfjXt9h9gMaxDZmR192CoG3egApNu0T/rLbvsBIMKwWAISRTHdaupqkpPuwN7jxNZK0Um/R1Oni2ef1u6kn99+00aHHZq+3r50a4dJBgN2HR6zFodQUXBFfDjCQRw+v04hmJxPjFrdtRjdrvd/HTvTtqdYVfZsqxs7p4xc1TcjE2v52sLF3O0o40Gh50jHW08fvQQX12wJDK57DkKExJZlpXDW3W1BBWFPx47zIG2FuamTcGi0+Lw+TjR1UFtXy/9Hg/X5hXgCgTY29L0ngeJ3zathDfOnOaXB/byj5qTZMfZsOl0dLlcnLX30zI4gEp4fr87S0pZnJkdtYNVVBWH10ufx8OA38eg34fT52PA7xtRkPJkTycvnKzEotVi0emw6HSYZS0JBgPx+uhWpPUFhTQ7HJFJmd88c5q9Lc0kGAxYtTr0sgZ3IBD5M+j34fT7WZ6dQ0h9fyZyhIKhcAbYsGxFnV7GMFTl+WLweQO4L6jBZ7Ya0VxEFiuE34+AP4h70EvNkQbqTjTTVNuBo3cQj9OHIIDepMMcZyQjL5mMvBSmleeQlBGPTi8j6zQX3XZFUXAPeicVYA3hkBJznPFdDfKhkILL4SZ0bg5VScQSf74UkKIouAe8nK1u5fieWuqrWujvHiAYCGGyGohLMFM4K5sZC6cypSAFo8XwrrPTVEXF4/bR1dxH5f4znK5opK9zANeAG1GSiE+2UDgzmzmrSkhKs0043hhMOnSG8Me8K+DH4fMiCNDuGqS6v4vZSRnIkkRFTzuL07LH39kkmVA4nRpowyYbscoGKuyNFJjTMGv0VDmamZuQT49vkOqBFgJKiFxTMvnm8JfvQMBDs7sHvSTT4OomXmuizJaDLEq0u/upGWhFJ8m4r/IEj5eLrGHTxjz4k3uuSJXwq0XYgqdHJ09DFMZIf9WWY9BO3mf9vwGL1UBqho2uNjtvvXiIj35mJXHD6pOpqorH5eN0VSvP/H4bLqeXmfPzohZvFQWBWalp/O7GW3j00H52NDXQ5/HgHgjQQvQvKFkUybPFY9WNtty5An5+d/gAB9vCFpScOBsPLV1BnC66hS3TGse3lizn37dups/r4bmTlRTEJ3JnSSnSsAdbI4o8tHQ5nmCQPS1NuAIB9re2sL+1ZcT+jLLMDVOL+PbSFbx5ppYDbS0Er+AkzZPhpsJiihKTeOr4MU719kRivoaTZDRye3EpX1mweMzaWJ5AgB/seIdXT9dEfosmCve0NLOnpRkY2fcvzcrhjzffFjWOTCdp+NzcBeTa4vnjsSOc7Omi3+uJTMkTDYtWS54tflK1vN4L2hp6+N7HHqWz6fz1XnfPUj73wzvQGy/OYrzjlSP8/F+eDgcQDvG9P32ehcMmhZ2IUDBEXWULW/5+gH0bj9Pd2j8pd78kiUwpSKFscSHzrymleE4ucYnjZ6EOZ6DPxS+/8Qz7Nx2f1Pol8/L5yUtff1fzrXU09vCDT/yeljPheM/0vGR++cZDmKx6PE4vB7dUseHJHVQfqh+z4PH2Vw4jaSRmLCzg5k+tZM7KYgymS/M0eN1+ju06xRtP7+L47tP4PNFLFex+/Rh/+p9XJ/WNft9DN/PhL61F0kjcUXD+OfjO3o3896L1lCWGNckZRy+PnzwYqdn1bphQOB3qrcMqG5hmzeDP9du4PmM2JXGZvNZ6iBxTEk/Wb8Uo6TBotGzuOM4n8ldRZMmgzdvPw9WvsjS5GKNGizPopcSaicPv5vG6LcRpjcTJRvb31FIal/UuT+Pqo4QU9m88zvHdpwj4Q+TPyGTpTXPC8wK9121TPNjdL+H2H0MrTcFmuh1ZysQbqMQXOENQ6f3/7L13fB1Xnf7/PjNze7/q1ZKbXOXeexyXFFIJBBKyIbBAgF1Y6i4LLAtb+MLCBlh+Sy8JAdJ7c+IU27Hj3ptkyZKsXq50e52Z3x/3Wpas7tiJnc3jl1+S7tyZOTNz5pzP+ZTnIZasxmyYhNd2J5I0/EvgCz9AJL4Hq2k+HuttCGFB13W6Qr/FIBcQju9GCANu642YDdMAQSx5nJ7Io+h6HLt5FQ7z1YhR8L1cSbA7Laz9wBwe+d1WXnpsD42nO5gwtRCX14am6nR3Bmk+00XN8Rbam3vIznNy+6dWD9BZPDto68AEj5dvrVjDgbYWtjbUcbCtlTMBP8GMd8lpMlNgt1ORlcPcgkKmZecw3u0ZcLw36ut46uRxUpqGy2Ti0/MWUOZyD7l6lYRgRWkZN1ZM5cEjBwnG4/xy3y4WFBb102oTQlDidPO91Wt55XQNL9ZUc8rXRSAeR5YksixWKnPzWVNWztpMjtD03FwMkow6hOEkhEASIr34GHR7hjBxQK3tuf3ThIqDHr4XcTXF31TOoTI3n+eqT7K7pYnWUBBN18m22lhUVMz68RNZXFSCURrBgyGG/fOC8aXnBwAAIABJREFUIYTAKMtcP6mCaTm57Gw6w86mRg61teGLRYgmkxhlBa/FQrnbw7TsHObkFzIzN69fuPSygq6nc/36zcsX6n/URy0+PrAZOqmkytZn9vHI/7xM3YmxhZFVVaOhqpWGqlb2vX6cv/+vjzJ7ecWY2zBaVZzR5m6O5ZyxcJyW+g7GVRTw5/9+kZcf2kHANzJNh5pSOfhmFXUnmvnAx1dy62fXDcg5HakNkVCMp37zOs/+fgvdHUOH087tNMpe0udLfd/ZlkgApc+gIAQ0hf2jbvNwGNFwGm/PY193DXbFzHRXCScCTdgVM2X2XA711JNQU9w7aQNm2chTjbt44swuvjbtxvTBhcy6/EqKrWmyTFlI7OqqJqEm+cT4qzDJBtpjo7iBlyFe/NM2tj9/gLmrp2I0Gzn61ilO7jvN5394x5glUC42usL3E09W4bF9iEj8IK3+H1Lg/hZJtZW2wI/Jtn8Sj+1WOgO/RBJOvPbhGXrd1ptRpCwC0U24rTdnPtXxR57BIBfjtd9BNHGIjsDPKfJ+n6TaQXvgPjy225CFg87Qr9HRcVmGZ/a90mAwytx69zLMViMvPbaHEwfPcGj36V7voxACg0HG5jSzauNMbr57GZMG0Utqi4b4/45sZ29nEyldpczh5Tvz1rGsuDSt+aZrvYOolNFuM8gyRlkeMnn8qrLxLL6jpHcfu9E4YpWezWDgq0uW8/kFi3p139yDeLMkISh2uvjojFmohhTB02EeWvZhPCYLkpAwyjImWe5lAZ+bX8i2uz+JroPTPHBy/6dlq/jSonQFzPladAAP3nRb2lsl6KcjB5BttbH5znvQdR1Fkvp5x85HLJXCrCgsKS5hbkEhCTVFKjMJy0JgUpRh7+lZWA0G/m311Xxr+cCKptHAIMsjJnELIRjv9lDmcnNzxbS0jI2u0RprRNVTeI3ZuI1uDLKMQRq5mOV9pJ1Urz2+m1/9y2MDpEwUo4zFZsZoUpAkCU3TSCVV4tEE8WhigLHjynYwrmJsBKWSLOHKsuPNc5JKqKRSKqlk+n/fMOalRCycoOZII9tfOMjTv329N2wohMBsM2G2GnvZtmPhONFwvJ8B5+8K8defvoTT6+Dau5b30zcdDqmkypO/eo2HfvpSv1ClxW4mt8hDQVk27mwHakqjtaGL1oZOutvTIcO+SEtZGTBZjJjM6Z+ubDuDLV3WFk/gP/e+zvSsPCQEx7rbWZxXelEWOSMaTmX2HJ5s3EmOycUMdwkvtx6iOtjCZEchHfEAXpMds2zEIMmUWLPZ2VlNUktfbJbJjttoQ+njQg4mYziNVkyyAYOkUGjx0JMY2eJ9uxAizc/0kU+vxpvjGFCiP1Yc3HaSj33tA0yZPx6AxRsr+ck//IlUQn1XDSdNTxCMvkKe6+vYTPMxKuWEu3eSTKVDKUalDLftVmTJTtR8mHiqasRjSsKOLLkG+dyK07oBu3kpiuwlnNiJpieIxPeQUtuIJo4gkNC0COHYdpzm9e+pAV4Igc1h4bZ7VrD0qqmcOt5MR4ufWCyZSTw34s1xUjohh3ETcgdU9Z3FA1V7eb2lhtsnzqbE5s4YOiZMinJBPD5CCCwGAxbD2Prh2f3MisKBrmYCiTjLC8qG/L4iSczNLUrTEtidQ1b2KRk5lqFgNxqxG4devbrMQ3tEJSFGnRB9dvgXQmBWlAGVdaOFyDwf+8Wp8Rj2PLIQWCQJi8GAqqscDlVxxL+LStdiltk2joq1+32k0d7YxZ//+4V+RpNikJm7eiozF0+ksCwHV7YDg1EhmUgRDkbpavHTfLqDhqoWao810dncjRCCJRsq8eSMPkwHYHOY+dDfrWftBxcSDkSJhOLpn8EYAV+IzY/uIuA7j7rjIicGxqIJnv39G3S29PQaMHklWSzeMJMJM0rIKfRgtplIxJK0N/o4se80257d308KJpVQeex/X2HGogmUj1I499D2ah7/5eZ+RlNheQ4f/OzVLNk4C1fWOS44NaVSe6yJzY/s5PkHtpGMn9unbEoR6z+6hNwiD95cF1n5btzZDqRBwpm3T5rNOIeH490d6OjcOXk2S4cZz8aCEUeOXJOLmJqkKxFkpruUbKOD6mALa/JmkNRVqgLNJLQkAmiO+sgyOTBkKPklMdC5blNMBJNREpqKQNAZD2To8i8thCSoXFBO5YLyi3K84on5+LtDxKMJhBAEfWGyC92oqkoinr4finHsCYRvF7oeQ9fjyFL6pRYYkDCgk67kUqQcBFLvNvQL1+ISwogsnQ0TyZm8Ax1NDyFLHsyGKQghYTZOwSBfeeHY0UIIQXF5DsXlYydL1HWdPR2NzMku4u6K+ViVSzwbjwJJTWXTmSpkIbEsf9yQcShJCOZkFzEn++Kpjr+PoSELmeXZG4mpl36h+V6DruvseOEgnc3nkveNZgO3fHotH/j4Sjw5zkH56nRdR01pBHvC+NoDHNtZw57XjrH65vkDvjsSZEWmqDyXovLcAduC3WH2bz0x0HC6yNOHpmrUZLRYJVkwf810PvqlayifWjRowvuy62Yzd9VUfv2dx2htOMcA3tXaw5svHKB0cv6QC8KzCAeibPrrDqKhWO9nWfku/uYfb2DZtbMH0A/JisykylIKy3JIJlI8/8C2XgOypzPI3JVTKJ1cwEgwSBIL80qYnV2Iw2hE12FskuNDY0TDSZYkSm3ZtMX85JndFFq9nAg04zRYme0pY5+vhgdOb8Eqmzjqb+CeCWuHfdbTXSW83n6MP9a+hsdopyHc2ZtQfiUhu8DNb779KOXTi1EMCvUnmvHkOvn9955AABaHmU/8y63veLsk4cColBOK7UCRc4knq9D0JIqch6r5h8gSOQedtPEz2JaBEL1GWF+YlHJCbMFsmIwi56JpIYQYewXNexmBRIwjvjbCqTitkSAGSeb15lokBCV2F1PcuSQ1jUO+FhwGI1M9596RjmiI493tTPPmkWWycjroI5iMU2p3U9XTSSAZw6YYmeTKJtvcX0w7mkpyOuijNRJE1TWsipFSu5tCqxNV16gLdlMT6GJLSy2ldg8vZQwooyyzunACkhBous4pfye1AR+QZhBflFeK6TyZGE3XaY+GqA10EU4lcBhMTHbl4DGlK8pSmsqx7nasigGn0Uy1v5NIKoHbaGGKOwe7wXTF9BlfooO2WCOaruE0uCkwlyILhWCqh/Z4M3E1ik1xUmgZh0DQlWgjrsZQ9RR2xUV3soN8cyk22U5TtA6DZKQn2YlFtlNkKcMgGTPv7jm9sb6IqzFaYw2EUkEcBhcF5lIUYbhi7t+lhqbpHNlZg9pHQmrK3DKuu2s5nlznkPfpLHWOJ8eJO9vB+KlFXPs3Ky6q7hmkF/bv6JMSsGDtDD73Hx8iu9Az5PWbrUYWr59JyB/pF+JMJVWO7ayhuz1AdqFn0H3PoqGqleoD9b3hTiEJFl49g6XXVA7L2Wh1mLnhntUc3FZFU21a67K7I8ALf3qTT/3rrSP27WPd7fz88A72djTxyMY7CCUS7Oto4o7Jb7/IaVS+6uuL5hNKxXAZrSzLmUKxNQu30YZZNnDPhLUc6qknqaW4J/sqJjvSlmC+2c3NJYuwyP1X0LlmF5+csJZj/jNYZCP3Tt7QTxUc0mzLr798lKrjzeTkObnlw4tHJMUcDMePNNJ0xsfV11SOed+RUDIpn4/94w29fy/e2P8cw5FgXkoIIch2fIKO4G+IJHaBDk7regxyPvFkFf0H3XPVX/7I04TiW4inqukI/BSTYTLZjk+haUG6w48QTewnnjpNS893cZjX4rSsH7INVtNCYslTtPn/C4SMLBx47B9BkYd/wd4Ozsbhr5SJoj0a4rHaQ/gTMbrjERKaykOnDiCANUUTmejKxp+Ict+hrVS4c/iX+et69z3qa+M7ezbxbws3siR/HC82nGRry2mK7C6qezpRdY3OWISl+aV8Y+5ass3pSslAIsbvT+zm+YYTCARGWcGfiHJT+Qw+N30J4VSC15pOsaejkTMhP6FkgkgqgQCcRjOrCsZnSkd1aoM+nm84zomeDhKqyqMbPtbPcNJ1nWp/B9/f/xpN4QAWxUAkmWCqJ5evz1lDodVJNJXijyf3ENdUVE2jJRIkmkoQTiW4tnQKX5u9BuUKeJ6hVIBNrY/gNeYghERLTJBrKkQWMm2xRqpDhzEIEy2xBma5F1Num8Lr7U9jVRx0xluxK04kZJpMp5nvWcUTTb9jnHUiNsVFc7SO2e6lzHIvGdL7oOopDvRspzFSg8vg5ZC/lSmOWcx2Xzrm5CsN8Ug6X6cvXFkOXNlDM9+fD5GpUpDfSRPnEnF4WO0Wbv/7DeQUeYf93lkeuoVXz+C5P26l6sA5Ca7Whi78vvCwhpOu67Se6aSzj7qDYpCZvWIKyhD8fH3PnZXvYtKs0l7DCeDIzlPEwnEsI/AAPnzqEMsLyvAnYqCDw2DkjebaNI/TsHuOjFEZThXOc0lwxdas3mRvSBtCV+cPNEw8RhsLswZSqAshKLVlU2obWovrxNEmNr94iA/esRSLxTho/HI0aG7s5siBhktiOM1cOvmiH/NiwWyYQaHnu+haFCEMSJITSRixm1dgNS5AiHSHc9tuAdJGq8OyGqtpAbnOLwMgMgaPJFvx2u9E129Pfw5IUjoZr9j7o8zvYFLKKPb+CFlyI4RMluNuVM0Pupppw8AcqfOh6RqCoRnfh8NbnVW82XmSr0y9YeQvXwYoc3h7jaGPvPIgU9y5fGve1UhCYJTkMZeW7+lspNTh5perbsUgyWxpqeU7uzexpnAi14+bCsDjpw/z5+r9/H3lCjYUT0YSgnAqgabrGCQZl9HMnZPncU3pFD639QkW543j3ulLUCQpoyKffi4CwdqiiSzNG8cDVft4pGZgeXUkleR7ezdjkmR+tvwmcsw22qJBvrnrJe47tJVvzztnCL7eVMPnZizhXxesRwcerNrHn6r2cVPZDKZ5L39vdEKN0ZPsYq5nBXnmIkySBWOmUrXEOgG3MRtNV8EP9eFqymyTiWtxVniu45h/D4pkZJx1Egd6tpPUEkhCYrprAeNtUzkW2Mve7i1UuhchGLxPRFIhjvh3Mc+7ijxTEbXh4+z0vcYs99IRPcz/VyDJ0oBE5mBPmGBPGG/uyGPTu4ZL9PiWXlPJhJmjT59wZaX5nKoO1vcac11tfsKByLD7aZqOrzXQL7dJVmTKp40usd7msJBX3N+4C/VEaGvyUTZCcn5DsIdPTVvE1pa69HklibiqDrvPaHEZEGAORF1tB+PKc5i3cPy73ZQrEkJIKMINUn+dLUmYkeRzVrosneNskoVr0ARwgYwkD4zJAyjyOQNaCEO/vyVhGnK/oXCwu55Cq4c881j1wSCuJQkkhn+JLycokoTTmH4WspAwSDIOown5ApN9zbLCJ6YsJM+STrKcl1NMuTOLKn+aO0fVdR46dZDlheXcWDYNuyFdveblXNK2QGAzGImrKWQpHZ5zGk39ijsgUy0oZCRFYBpC025vRyMNwW7+ae5VVLjTuV9es5U7Js3hvw9t5WRPOxXudP/wmCzcNXl+b8Xcsvwynq47Rk2g64ownDymHFblXM/+njfRdY0K5ywqXYsA2NP9Bu2xJsyyjbZYI3bFhQ4YJSMmyYxBMmFV7ChS+tp1dMySFbviRJEMuA1ZhFOhYR0PKT1Fc6wBk38X1RmDrcgy7hJf9ZUFk8VIbrE3zbye8U6fOnSGN57cywfuXokyjOTSu4pL4HFSjDKL11f2ykONBkIISiflIxCZdA5IxJIkYkl0XR9ysatrGiF//3FZCIHdOXSxSL/vSulqP0mWeisPUymVaGhk/sepnlyeqTtGdyzKMV8bR33tTPHkvDNVde8kujqD/OUP2zh8oJ54LElzUzcLl0zk+lvmk0yqbHr2AAf31eFwWrjmxrlMmJSHpum88PR+Skqz2LerlqZGH6vXTWf56vQqG5FxFzb38OwTe9lw3WxKRhDwfR/noOs6qq71shLLQuqd3JO6iiwkUpqaToaXZCQhoek6KV1Ny9oI0S/5P6WraJmBS5Fk5Mz3k1qKpxt3c33xfFwGG4qQUCR5wPkVSUZC9D7XsxWcF4ny5IpFnsWB03guj0wREmZZIamlV3qhZJzOWJgyhxfbO5CA3hj2owPljv6rxSmeXHzxCF3xc5VNpXY35j5hPpOsoEhS77O97KHrTHZUUmqdSFusiZfbHiXPVIzXmMPBnrdYn3cb5bYKdvheoTV6JrNTH36Z8/xCcS1GVI2g6RohNYhJNg872EtCIsuYy/LsjRRayvod932kIYRg/lXTeOWRnSRi6UKZkD/CQz99ia6WHq67eyU5RZ5BtT3fa/Dmusgr9Y75Om0ua7rb9hlrzw9/no/0uHz+4KyjjtLzczY5vy8lgpTJOxsJH508m/tP7qMtGuJnh3cwMyufT09fOOJ+o8FlZTh5PDY+/pk1PPv4Xro6g3zsb1dhzMRBX3pmP0cONnDbHUtpbenh/l+9zj2fvYqS0mwaG7rYseUkH7pzKavXTcdoOndZQgjO1HXylz++yYqrplJUOnxM91IiEo5z/GADug4mk0LFzJJ+bb3Y6GoP0FTfhWKQKZ+Uh9lqHLMsQV24ncfP7KQp4kMIWJEzjRuLFxBVk/zD3t+zrqCS/d2nMcsG7ixbSakth71dNbzYcoBAMoLHaOe20iVMchTQlQjyu5pXM9xdOkuyK/hA8Xx6EmF+U7OZt7qqaIr6cBgsbCiYzfqCWQSSUR44/Qb14Q4MksLCrIlsKJiFLMm83HKQV1oPY1OMmCTjRZOciMeSVB9rJjYEq63DaWHitMJRc5i8ffQfeJKaOmAoMkr9My/OTyE+m/L/Tk0JZ88zYMgcxMA9P6l88PTnkdHe0kPLGR9Gk8L4igIUWWJ2XkGvJyvPNjgr/ttFe7yZE8EDWCQbcS2GRbZhkW1IQsahuKgLn6Q70U518DAuw8jjT1SNsL97G22xRk6FjjDTtQiBRCDZTUusgY54C2bJSk3oKPnmEqyyg6nOubzVtZkyWwUpPYFDcVPpWjziuf4vYf6a6cxdNYW3Nh3u7Zj+rhCP/+pVNj+2i2XXzmbVjfMonpCHK9tx0RPALwiXoAm5RR4c7rG/C4Ppdaoj8E/JsoQ7x9nP4NJUnfbGbrILRs55TcZT9HQG+pGeGkwGnJ6R219kc/K1Oav48uwV6LqOLEko4uIYxpeV4STJEja7GZNJwWCUcTjS/CyppMruHae4/pb5TJpSQHFpFrverKa+toPi0nR4aMbsUirnjut3U4SAjvYAv/vfV7n6mkqWrJj8rq4mWhp9fOuz96NpOnmFbn70x0+Rnee8JOcKh2L8+Vevs/mZ/ZjMBj7+xfVsuGnemI4R15I8cWYXVsXE16fflPb09JkSfYm0qPE/TLkeXddxGCz4ExFebDnAmrwZTHeX8FLzAR6u384/z7gVh2LhxuIF5JpdtES6+U3NZhZlT6LI4uXLUz5AU6SLT064mpnucxphr7QeQkXja9NupDsR5tenXmGCIx+3wcprbUe4fdwyymw5/L72NcKpi2M4dXUE+cm/PsmZ0x2Dbp85v4zv/s/HsIxRLmKskISEJAShZH9R4Mawf8zeGLvBiNdkpSHYTTiV6A3VDQYh0qs6VdcvOFJQ6khX6tQFfUz1nAvZnuxpx2uy4jVdXDHaUCDK7+57ie2vHsdmN/PZb1zPinUz+OaK1Rf1PIPBobjxGnMIJHswSibW538QjzEbXddZl/dB6iPVyELh6tyb0dCxSFbmupdjUxxMtE/HIBmxynYqXYswSEY8xmzKbFNIaHHmeJYzyT4TBMTUKF3xdkqtkwDoTLThMWbjMLhZkrWO+nAVnYlWjJKZPHPxJb/uKw2KUebOr1yPvyvMib2nzzH2azo9HUGe++NWtj2zn8lzxjF7eQUL1k6ncHzuO7hAGgSXwJNuc1kxjYH1++1ASIKC0mzsTmtvyC6VTHF0Vw3TFoycitPTFaTuREu/z7IKXHhzR543D3S2MCs7HyVDjxRXU5wKdDHR9fYjTpeV4TQUkimVRCKF2ZKuVBNSmpG5r4SDxzvQAtU0na6OINk5Dupq21m4bBLGyzWWfZHh94WpOtJILJokFk1ydG/9mA2nqJqkOerjzvJV5JpcAzqbXTEz11tOtindiXVdpz0VYGdXNQ3hDkyygaiawCBkdHTCapwdHVXUhtsJp2L0JCNE1TQPliLJCER6VZDJqdF1nd2+U9SFOqgKNKPpOr5EiFAqiiAdNpzkKMBrsjPLM443O05elHunKBI5+S6ikTiqqqGpOvF4klhkcA/UpYLLaKLA6uBAZxOHuloosjmpD/WwqbGKxBgNJ0VI3Da+kt+c2MVz9ce5qmgikhDE1BTRVJJxDg+GzH03SDIFVieHu1poj4R6iS3P0ghouk5MTZLUNOJqKh1SSiawyAYMUjpfa252EZNc2TxSc4gyh5dci522aJAHq/ezMLekN+/pYqGrPUD10WYS8RSJeIhjBxpYMQb9srcDq2JnZianqS+EEBRYSimwDBQWrXDOAqDYem7ycBjchFNBBFBkKRuwX665kFzz4AmxZtlChXMWFcwaVZt1XcMffYGu4J+QZRdFnn/DIA9dsPNegBCC8qmFfPVnd/HXn7zEm88fIBKM9WfG9oXYvfkoB7ed5Ilfv8b0heO57q4VjJ9ejNVuHpTr6dI2+uIf0mgyDOo9uhQQQlA6OZ9xFQUc3VUDgJrS2P78ARatm0nJpLwhjRhV1di/5QQn99edO54kWHT1zFFVrf/vkbf42cobMGUM30gqyS+P7uQHS699Z6rq3m2YzQYmTSlk9/ZTFBZ76eoM4vOFKCzy9sbxB7v3QggqphZyz71X8YufbuLl5w6y7rpZ/yeMJ5fXxsRphTTUdmC1mZi9aMKYj5H2LwnUISZpSUgYpYEduMSaxRcrrqfQmnbFShmVsQdPb0HVNb405Xo0XeNfDj88WPi7HxQhc0vJQjYWzun9zCKbqA42o2f+Ab0SIRcDOfku/v0Xf0MskiAYiBIKxti++Sh/+t/XLto5RgODJHPHpLmcDvq4d8vjeM1WTLLM/JwSWiPBMR1LCMGHJs4ikIzx2+O7+MPJPRglmaiaYn3xZD43Y2mv4WRVjNw6fiY/PriFe15/GLvBSJ7Fwc9XpOV22qMhfn5kO13xMNU9nXTEwnxnzybcRguL80q5bUIlZlnhm3PX8p/7X+WLbz6FOUNHUOHO4QszV+AwmAglL54h6s1xMn5KAR1tfhwuC7MuEtHtexcCl+VarMZZNHR98W0R4V5JkGSJ/HHZ/N0PP8LSa2bx2uO7M8ST/UlFE/EUnc3dvPHkXna8eIjZKypYf/sS5q6aisV2mWoCjhKKUUa6AHqfC0VeaRYrbphL1YH63uq6kwfq+d2/P8lH/+EaJswo7keiqes6YX+U3a8d5f7vP9OPOXzc5ALW3LpgyHPpuk4klcQXj9IVi9AU9mcIuXXOBP20RUJD7jsWXJYWhJCkfrpaQgiuv2Uef/3jNn7y/edQFIlFSydRPiEdApCkwUvYhRBIssDhsvChO5by4O+3UFDsYc788vd8AqDNbuajn1rDsrXTMJmNTBpl+WdfWGUTExz5vNC8H7fRhiwkYmqyHz1FXwghcBms5JndvNVVxVplJqFUjJSuMcNVQlRN4DHaSGopXmk9TDh5jklWQuA0WDjmP0Ou2YVVMeE0WFiZO40Xmvcz1VWMy2ClMx5kvD0Pj9GOrsOuzmomOQvY1VVN6iIlE5/tGxabCYvNRE6+Tv2ptoty7MHwjblX4TCYM6HQ/u2YlVXADxZfx5lQD6quU2B1UGhzsbKgnAp3DhKCa0qnMCe7CHef8JfHZOFLs1biMp6ronQZzdw7fQkbSypoj4bQdB2bwUiZw9svz0gSguX55RTbXDRHAmi6jtd0rgrGZjCypmhCWj/uPORbHb2UEmUOD/++cCM1AR/hZBy7wcREVxZekzUt76IofHzKAhKa2k8frszp5TsL1g9ILB8ODpeFe764nvU3zsVqNzF5+pXJZm6SLFyddyse49i8P2mviUofYRnopS/QMv8zUsn98jwGTqD9j3Vun/TnZ5/52ePJfSrVtD7byZz/8htnhRAoiszCdTOYtmA8J/fX8ebzB9nx4kEC3eEBIsKJWJJdLx/h5L46VnxgLh/87NW9FXqXHJcgVPdOPxEhBFfdsoCdmw6zf8sJIB0e3fnyYVrqOpgyt5zy6UW4s+yoKY22Rh8n9pzm5IG6fgatN9fJh/5+PU6vfdjz1Qe7+e3xPZzyd/GVN19Ii3/r6cX1dWUV772qurO49qa5A5Shc3KdfOaLG0glVYQkMBoVZDn9Mt/9qTWDJvKtXDuVZasrEEIwbnwOX/nmjRdEpHmlIiffRU7+hXOUGCSZj4xbxqaWg/z61CvIQmJ13nQqnIVImTCZSerfhZwGC5+etI7nm/bxs6oXsCtmNhakmVo/Mm4FD9S9wX0nnmOedwIbCmdjzlR4CSG4e/wa/lK3jcP+Bm4oXsCirEmsyZuBAB5p2EFSU5npLmW8PY88s5s7y1fyVONu9nWfZmHWJNpiPedfwhWBxXlDl44LIRjvzGK8M6vf50vzy3p/L3d6KXf2NzLMioEFuQN5WqyKkenefKaP0CajLDPZncPkQUJqDoOJq4oGcrQN1vYci50cy+ADnSLJzPDmD/jcZTSzrM/1jRYFxV4Kit+94o+LAUVSKLONjSNO11WCsa30RJ4kpXYSS9ZgMc6g2PtvCEx0BP+XaOIYQhhxWjbgsX4ASRo6xyylddDm/wmJVCNCSDgt6/HYbiWRaqDN/xMUOYt4shYhFPKcX8RqqkTVfLT67yOltpJINaIRp8D1tWGJci8EqcTF84wJIXB4bMxbM41Zyyu48yvXsuWpfex85Qj1J5vp6Qz2M1z8XSFAEqHUAAAgAElEQVSev38rVQfq+Or/3E3xhMufKuNygd1t5XP/+WF+8a1HOLDtJKmECnqaVfxMdRuSLCFJaaoDTdUHiB4XlOVwx5evZcX1c0dM2q9w5/DdhesIxOP82+J1GDJpIIokYblAfcrzcVkaToZBSg2FSBtL54fZhBBDVqYpitwbyxVCYDK/e+K7VyKEELiMNm4bt5Tbxi3tt80sG/jH6TcPuk+hxcsnJ149YFuJLYtvTL9lyPNNdhbyL5Uf6veZQZJZVzCLdQUDczdmecqY5Skb5dW8j/fx3oSmh/FHnsFluQa7eQlN3f+Ky3oNipRLZ/C3qFqAYu9/oGoBWv0/wqgU4DCvGPJ4snDitd2GQSnKGEs/xW5aAmhEE4fJdX6OXOe9dIX+THfkUaymSoLR19H1OKVZPyMU30F3+DHs5uWIiyxCPFL5+4VACIHBqJCV7+bmT1/F+o8s4cjOU+x8+Qg7Nx3G1+bv/a6m6VQdaOCBHz7H57//4QuqThtb4y7t4d8pCCEoLM/h89+/nZf+vJ2nf/dGr3xLmnJAZbB4gTNj2F5z5zJmLJ44opfvrDC2TTJy15Q5ZJttyNLFd5ZclobT+3gf7+N9vI/RQgKMpLRukmoHup5EFnZ0EkQS+3HbbsKolKDrSUzKRGKJKuympYghxNU1ooTibxELHkfVAqhaN5oeQQgFo1KKzbwIg5yHxTCNnshTAAjJiqaHSWmdpNQOZMmFEMNMLxcYgurqY8RcKticFhZePYPKpZO59mPLeeinL7Hz5cP9cm32vXGcfa+fYOWNc9/zaR8XE06PDdkgE4+l8xsVg0x2oQdJEsQiCYwmBYfbRkF5DhVzyqhcOon80ixsTsuY7/PSgnFEkklSfWhqBGmP9hVVVRePJdmzrYp4LEnlwvFk5zrp8YWoPtpEOBzH7bUzoaIAh+scDUHNiRZam7qRJEFhqZeS8bnDJnfruk48lqStuQdfR5BQMEoqqSJJEmZLmv+hsMSL020d8807e+z2lh462wJEwnGSiVSvN8vmMJOT5yIr14FxNFp1GRLHWDRBU30XXe1BopE4QghsdhM5BW4KS7woBnnEtrac8XH8UANDURlNqSymsHTkMkxd12lu6OLEoUYMRpmZ88vxZNnRdZ2gP0pjXSc9vhCJWArZIGF3Wsgv9JBfPLRQ5GDQNB1fR5DWJh/+7gjJRApZkXA4LeQWuskr9Ly7ZcCXEIl4ivaWHlqbuomG05V7JrMBt9dGYWnWmPqmrutEIwnam3vwdQYJB2OkkiqyImG2GHF50/3dPsqBp6mhi+qjTei6TuX8crIyZb+aptFyppu25m6C/giaqmPMtDm3wE1WrqNfXiJAd1eIfdtPIQRMmzOO/CJPOnkzHKepvgtfR5BYNIEkifS7k++mqNQ7oto6QENtO9XHmoecgGfMKyOvcGQGek3Taahtp+Z4CyaLgZnzynB5bOiaTqAnwpnTHQR6IsTjKQwGGYfLQkGJl5z8gVWmQ0HXdUKBKE31XXT7QsQiyQGhiPMhKxJL104bVSGLJGw4LWvoCj1ALHEUl/VqrKazQqYCXU9PUulSihRCmBjOldEe+F90PU6B51uATkPXF/qcy4LonTYEeianyWFZRXfoIVp7foDJMIFc5+cRpJOoJfn87D1IqRqaNjbrSdd1mmouXa5hXwghsNhMTJhRzBd/fAcP/3QTT/z61V7jKdQT4dCOKhatn4H5EtOSvBeg6zrhQJQHfvAsLz74JqmEitFs4IZ7VnHb59Zjd/dVMKBf97xQI2dbcx0PVh0gpZ8j0HQazdy3/Pq3cSVpvKOGUzgY45c/eJ7O9gBf+t6tVM4v43f3bWLv9moi4Tguj41la6dxx6fXYLGZ2PTUPp56cAetjd2IjOF0/YcWseHmeQPCc7quE+iOsHPLSfZsq6Kpoat3IkkmVWRJwmQx4HRbKS7LZtnaaay5dtaowne6rpNMqBw7UM+mp/bTUNNGV3uwn+FkNBuwO8xk5TopKs3i5o8tY8KU/OFVtxWZ+lPtPPS7LdQcb8bXESQaSZfnW+0mcvJdzJg7jlvvXkFO3tAK3gBH9tVx33eeHJKQ7O++dSOFpVmDbut/rXBw92l++t2nsNpMfOXfb2Xx6qns2nqSFx/bQ111G/7uMPFYEsUgY3dYyCvysGLddNbdOGfECVrXdULBGK89e4BtrxyjtambQE+ERCKJosjYnRZyC1zMWzqJjbfM7+W5ei+s6nRd50xtB88+vIsTh87Q2txNNJxAVdW04eSxUTohl1UbZ7L0qmmYzEOr2+u6TndniB2vHWfv9lO0NvnwdQQJh+J9DCcDLo+NkvIcVm6Ywcr1M0dk3D28+zS/+MHzJOJJvvnjj7BkzVTCoTgvPLqbba8cpa2pm2AgiqbqmMwKLo+N3EI3n/3H6ymf3D9f6czpDn74z48ihOAzX7+WGz6ymJNHmnjsj1s5XdWGrzNIPJpEnDWc8lzMXTqRmz66BE+2fdhnvvfNan75wxeG3P6N/7p9VIaTrmnsfOMEv//Jy3iy7Hz1Pz5I5YJy3nzlGJuf2U/dqTYCPVES8XR/d7gsFJZmsXpjJauvrcRqMw37jFIpjX3bq3nx8b3Un2qjxxcmFk2MaDSYLUbmLpk4ygpgjUSqAaflKrLsd9I3KdtuXoY/8hwmZQKq1kM8WYvbeh1pg0ojnQSuoaOh6xpCSGhaAEXOB3T8kefQtMDILdCC6OgUeL6NIvXPMzNZjANyS+OROGpqbMUcwe4wrQ1dY9rn7UIIgc1h4YZPrGLbc/tp7sPt1nbGRyySeN9wGiV2bjrMpofeIpExPpdfP4cP//0G7K7Rya+MFQ+fOsTVJROZ4c3rLT65UEmr8/GuhOp0Xef4gXqO7q9j+6vHMBgU0MHXEeT5R3bjybZTWJLFAz/fTCyadt9FownqT7Xzu59sonxSHtPPI7uMRhL8+NuPs39nTe+DEZLAbDZgNCloWtqzEw7GaDnj4+CuWmpPtvKJf9gwovHU3Rniz796jdeeP0QkFOtlP5YkgaykZUGi4bT6dkern6aGTm65awRlcgFH9tbxh5+9TFN9J0KSMJsNWGxGEvEUgZ4IgZ4Ip6taqTnZyuf+6XrKhuG8cHvtjJ9SQCKWJJVSSSZVerpCvffiQpBMpmioaaej1c/9P99MOBhDMciYzAYsNhPxaBJfZxBfZ5BTx5s5dbyZz3z9OpzuwV8EXdepq27jt/dt4uCu2rTRKQnMFgNWmxlV1ejuCuHrCFJ9rJm9b1bzyS9tZPrcK193KxFPsXPLCX71wxfoag+gaXr6XpoMCKGQSKRoaeympbGb/W/VcGj3aT7+hfW4hmDI7fGF+cE3HuHo/obeEl9JSns+TWYDmqoRDScIBWI01Xex/60aGus6uf2Tq0blDdU0nR5fmLbmHv7w0028ufk4yUSqt8+DluEI6yEaSWB3DK1Urus6p6ta2brpCL/58Yu0t/iR5fRCxmI1Eo+n8PvC+H1hTle1UnuihXv/8XoKh5GF8OY4mTClgGRSJZX57+sMkkpeeGVlNJLgzOkOThw+w8O/3UosmsBgVDCaFCyKiVg0QVd7kK72ICcPN1J7spVPfnnDkESoyYTK4/e/yaN/3EYoEMVgTBua3hxHegUeiuP3hXtXwyazgaxcZ9o4K8kaNNdzMOgZoe7u8NP4Iy8ghAGH+SqyHR/HY7sVUGn1/xBJWMh2fByrcTaqHqDd/zOiyWPoepIzvq9iM84lz/Ulsh2foD3wcxp938BuWoLLch2SMIOQMSolCJHuP7LkxCiXpnNUtB40PUR9570IZEyG8eQ4Po1RKcViN6EY+k817Y3dRIKxUecI6brO0V21dLePbMRdCnjzXOSXZvUznGLhsRt//1ehpjSe+NVrxDI5at5cJ2tuno/NeXGJcPudU9dZkFs8oHDmYuBdMpxgx+sncLqs3HrXMkrG53J0Xx0vPbmPVFLl2Yd24c12kJXjYN1Nc3G6rGx9+Qi7tpwkGo7z6nMHB0ymRpPCjHll7N1+iux8JxXTiymdkEt+kQeL1UgqqdLS1M3+Hac4ur+eRDzFy0/tY/qcUlZtrByyrT2+ML+97yU2P3MASK9AisZlMbWymKJx2VhsRtRUesJvPuPj1LEmJs8oJrdgeFe+3xfmwV++RlN9J1NnlTJn8QQKir0YTQo9vjAHdtawd/sp4rEkR/fV8dSf3+Kz/3TdkJPe/OWTmLtkItFInHAoTqAnwi/+37Mc3d9wAU8ojVRS5dXnDhLKhH8Wrqxg5rwycvJcIKCtqZtdW6s4cfgMyUSK1184xPQ547juQ4PrAfk6gvz8P57lyL46hBBMnFrInMUTKB2fg8lsJB5LUF/bzp6t1dTXtHPicCM//89n+Of/+gjFZVcuOZ+maezeepJf/L/n6WoPYLYYqVxQngmFpUNc/p4wNcdbeHPzUUKBGC8/vR+zxcid916FfZDBxWY3UzGzmMN768gv8jBpehHjJuSSW+DCYjURjydpafSxe0sVVUebiMeSPPfwbipmFLNo1ZRRtbutqZsH/r/NvPHiEbLznMxeNJ78Yi82u5lEPElHq5/qY83kF3uwDmM4Aex58xRH9tXT2R6gckE5sxaMp6DYg6zI+DqD7N1ezaHdp0nEU+zdfornH93NPV9cjywP/g6t3DCD5VdPIxJJL4YCPRF+9M3HqK9pH9W1DYZ4PMlLj++lo82PkARLr5rKjLllGUMHmhu62LXlBNXH0kSbLz2xl8oF5azaOHPQ4x3ac5q//vYNYhnD8sY7lrBgRQW5+S5UVaWhtoMXHt3Dzi0nSCZUvNl2vv79DzJxatGYwtSxZDXhxD5Ks37cW/HW1P1tvPbbkSUbWfY7M56oc1CEi0LPNwc9ntkwidKs+wbd1ncfu3kxdvNiVC1Ea8+PyXd9GbNxOroeo9X/30QS+zEqpVhtZnIKPdSfPMcAfeZUKy31naMu648EY+x48SBB/7sj5K2mVII9/c9ttplGFVZ+W3iPaHB2dwRoO3POW2i2mbBfQLrMWDAnu4DfH9/DqsLx2I3p6m2DJDMnu/DKynHqC393mHU3zuH2T63GaFRYuGIyJw43UnOiBV9Hmtzv3q9fx7K105BkiUnTCtn/VtqbdOzgQGNAliWWXjUVh8vCpGlFZOc5cTgtiD4cT6qqcdV1s7jvO09ycFct0UiCPduqWbRqCuZBKOhTSZVXnt7PtpeP9p7j6hvmcMtdy8jJc2LJuOl1PV0+GQrG6GoPYjIp2BzDW9LRSIK66jZWbazkb/7uanLz3b3ubF3XWbF+Bg/95g2efXgXqaTK1peP8NHPrCY3f/DwgxACWRHYnRbsTgvebDtW+/CT2UjQdWio7UBRJO68dy0bbpmHy2PrLQfVVI0VG2bws+89zf63atA0nU1P7uPqG+dgOs/ASyZSPPbHbRw7UA/AwpWT+dRXryGvwNMbPkqHNlSu/sAcfvStx6k+2kRddTtP/Gk79379ujGpeV9O6PGFuf/nm+lqD2C1mbj9b1ex7oY5uLPOhaPO5irNmDeOX//XiwR6Irz63EFmLSxn8eqpA150g1Fm9cZKikqzmDy9GG+uA7vDghD06+8r1s3gvn95ghOHGwn0hDmws5Y5iyeOSiNx87MHCPqjzF8+iY98ajVlE/OwZPQO0+HrFN2dIYQksFiHl3DozBgj1946n9v/djXeHEevcaDrOivWTef+n2/mlWcOoKkarz53gNs/uRLHEG78dH+XcTgtOJwWvNkOTJa3VzWrazq1Va2YzAbu+eJ6Vl9T2S/fTFU1Vm6cwX994zFOHmkklVJ5+el9LLlq6oCQmqpqPP/I7l62+Y23zudDn1jZ773IznNRVJpFd1eIo/vraWvu4UxtJ5Onj1UuRaBpIVQtrQEZTuxFlrxI4p2R1UjnOqmktC40LUg8VU9KbUOR06kBQhJMnV/OnteO9e4RCcZ4/v6tTJ1fjtE0dEga0uPwtucOsP2FgwM4lkaLYE+YVELF7raOKme0LzRN58hbp2hv9PX7PH9c1qUP0135GQpAZkzqcy2+Nj/H95xmXEVhOiVBEue+d5HQEPJzuKuV2oCvl9zXaTQzZ/nYOQ3Px7tmOLm9dmYvmoDRqGTiyGbmL59ETUaXZtz4XGYtHI+UGVwLSrzkF3lpqG0n6I8SCkT7DapCCApLs3rzeAZ7ALIskV/k4eY7l3LsQDrE0dLoo8cXJr+o/yCj6zptzT1semof8VgSWZZYd9McPvWVa3snj77nlhUZl8fWG6YaTQeYUlnMXZ9bS36RZ8Dx3F4bN3x0MTu3nKTljI9wKEb10aYhDadLiZUbZnLLXUsHeLskWaKg2MtHPrWag7tPo6kanW1+muo6GV9R0Ps9Xdc5eaSR7a8eR9N0isqy+dsvX0NhSdaA6zYYFMZNyOWeL6zj259/gGRCZd+OU1Qfa2LqrIHSFZc7dD1tTDbUpl38i9dM5da7liPJYsC1W6xGVqybQfXRZp55aCeBngivPHOAOYsnDjDshRCUTcqjbFJe79/nQ5Ylxo3P5boPLeTUiRZSSZUzdZ2Eg1GMJseIbe9sCzBzXhmf/8YHyC10D2iv0WQgr2hkoc6zmL1gPHd85qoB+UtCCLJynXzw7hXs3HISvy9M0B+l5kTLBTHev12sv3ku13940QCvjyxLFI/L5va/XcW/fuFBIO2Va2vqpqS8P99VW1N3r9ahYpDZcPO8AYsJIQR5RR4WLJ/MiUNn0hITO2tY+4HZjAVmwyS89g/TFf4Luh7FqJRT7Pke79TwLgkrBe5/xBf6K/7oyyjCRbb949hMi3qf89JrZvHYLzYTCZ4jvd3x4iH+9MPnuP7uleQUeQfw82iqRltjF9tfOMSffvjs25I8OvLWKX7z3SeoXDqJuaunUTQ+l7xi77AyKmcZrA9ur+Iv//0C/q5zrNN2t5XKxZPetrF+FpqqDRDA1rX0gvy9UCTjznGQW+QllPHaxSIJfv/vT3H4rVPMXDwRT44TwyD5fJIiYTAq2BxmPLkusvKco5JbAfjuwnUZh905efOLZZa9a4aT1WYiO7d/wnNeYXoQFiJN3ujoE6I4a0w01KZDH9FIYsBqdDTGihACT5Ydp9tKV3uAWDRJIp4c9Lu1VS2cyUx4uYVu1t84d4DRNNjxRwNFkZm/bBJ5RYNXowkhyC/ykJ3npOWMD3Rob770pbjnw2Y3s2rjzEE7NWT0nyblYXeYCfRESCZVurv609prms6JQ420t6YJKuctmTBsVZIQgpLyHApKvDTUdODrCHLmdAdTKkuuuCTxSDjOri0ne/NYNtw0d0gSViEEZouRyTOKsDxtJBKOc2x/A4l4alCP6Kj6uyTw5jixO8z0+MJEw3GSo8wDkiTBNbfOH5NxNBSMJoVFq6fgzrIN2d+LxmXhybKn8340nY7Wd76/O1wW1lxTOSTJnhCC8RX5WGwmouE48VgSf3d4gOEU8Ed6xxWX24ptiFCmEILcQld68lbTnrmxQhJG3NbrMknf7zyEEJgNE4cM/QHkj8th8fqZvPrY7t7PUkmVp3/3Bif31zF7xRTKphRid1nSOZ5dIWqONnJi72lOHT5DIpa+l0s2VrJz0+ELqMhLJ5e/+OB2Xn1sNwXjsimemEdusZei8hw8uS4sNhMGYzrf0N8VpLm2g9PHmji6qyZNhtkH0+aPZ/aKilGPR6ePN9HZ3JPJhY0RDaVzYqOhGNFwnHAgSmdLd799Wuo7+dnX/oLJYsRiN2WUDMxY7CbM1vTf2YVuSibmDzk+Xy6QZYlr71rOr779aG/ebTKRYscLB9nxwsGh91MkjCYDdreV3GIv5dOKWHXjfKYtGN/Puz4Y4prK06ePcczXzhdmLSOupuiJR/uJjl8o3rW7bTQpA3I3ziZZCknCm+vovxIQ9IYXzoYJhkKaUEsjFkuQiKVQVS0t1qpp6JpOZ58EQ3WYsthDe+p6J7yyiXlMmPL2Y6NnYbEZmTyjeNjVhCRJ/ZKDI+HYkN+9VCgo8VJQMnwegqykq40CPRE0NZ003BfxWJKqo41oqo6sSFhtZtpbhmf5DvqjWDP9IR5L0plJqB4q5+VyRWNdJ12Z0LPFZkJIotcTMRSSCbXXuOrpDhPwR4ZMuIdMiDOpEo8lScRTaTI5VUPTdXRNp7vPoK+q50pzR4LZYmTu0pEZwkcDl8fG+Ir8AZQFfSFJore/66SNzncapeNzyM4bPj/RYFCwO8xEw3FSKY14bPgCDE3Th73naupcJazBcHlPgBcKk8XAzZ9eS1NtRz/R1kQsyeEdpzi+5zRGkwEpowahplQS8SSamr5vsiyxcN1M7vzqtdQea6LtbVTXJWJJ6k+2UH+yJS0Yb1RQFLk3rUPXdVRVI5l5l/pCkgTjphTwyW/fjGOIwo3B8OCPnufAlpNoWnq+OTsXnf17sFwmf1eIlx96C0R6LpAkgZBEv9/nrpzCZ//zw3hynBd8P94prL5pPp3N3Tz569dG7T1UUxrRVKbwqqmb47tr2f7cATbesYwbP7kah2fwhRjAX6sPcLCjlSp/B+FkglgqyR+O7+X7S6+5ckV+05bk+Szg534OVqnSe4N0Brg1zyLoj3BkXz3VR5s4U9dJW3M34WAsTR0QT5FMqiQTqRFXLLoOjZkJTpIExWXZF5V53GgykDsKORS5j/E41lXWxYDbaxs0ObkvBPSu0HUYMEkkMxVjkH4R/vqbN/jrb94YUzsioTTf0ZXmtu5sC/SyHUfDcb52z2/HdoAMf9ZQ6PGFOLynjpoTLZw53UF7q59Ipr8nEimSiXSfv5DckLxC96CerguBxWokK2fk8GDf/j5aA+9iIivXOWK+Vnoi6zsWDWxndsaDAel8ztamHrIGmdw0VaP2ZGsvr9P5nqv3CoQQTJhRzCe/fTO//bcnObH3dL/tZysjB4OsyKy6cR53fPkaPLlOyioKx2w4mSyGQUM8uqaTiCVJMHjUoS/MViNLr53NrZ9ZS/HEoSucB0M0HCccHPo9HhZ6up8MJsUZDccvOO/rnURPZ5B9rx+no7knU2F5YWFXTdPxtQd4+H82EY3Eueefbxoy93VHawPfnH8V39+Xnms8ZivNYxRHHwrvmuEkhBh2EhyrZ0FTNY4eqOfRP2zjxKF0IqwOyJKUWUkApH/KioSWGDlcEcxQwgtJ4PRcXK4JWZauCP4Po0kZdVn0UNA0nUjonLdMCMFY6TTSq7LLf4A4H7FIot+EIEliTIF2IUQ/jwTQW4ywf2cNj9+/nepjTYQyfVUarL/L0gUJIFusQ3MUjRWKImO6SEbYpYTJbLgolVKebDvTZ5dSf6oNTdN5/P5tlJbfhM1xjrVY03ROHD7Dnu3VaJqO2WJg4Yqx6dRdSRBCMH3RBL74ozvY/MhONj+6i4AvlDYK9D5eF5EWmpYUmcKybK65czmrbpqHJ8dJMpGibGoh+7ee6D3uSNplABVzyvj892/n1cd2ceStU4QCEXRVT3tl9YEen7NhICFJmK1Gps4fz7oPL2L28ophvRxDwWBUMF4CyS+DURl2PDmbi9j33IpRuSCPiyRLaaqTPoaaNMJCVlM1ju2p5eGfbeLorpreHDfFIGN1mMkt8mJ1mAfmt+k6qYRKyB+lu91PNJJATaq9i5RUUmXTX3Ywf8005qycMujzMEoKgUQ87ZHXNeqC3TiNF2fOfRcNpxFyNMbYMffvrOWH33iEHl8YSRIUFHupmFnCzHllFJR48WTZsdpNmMwG6mva+f7XHsbXObz12deSly7SBHIWZye0yx1p8cW32U5d73W5G4wKy9ZOY+LUghF26o9J04qQ5Suvqq5vmMblsXL97YuwjMWAEIK8ooEFAW++epyffe9pgv4IsixRNC6bqbNKmT6nlIJiL27vuf5+dH89/z975x1mV3Wd/d+pt/fpvUkzkkbSqDdAIBASwlTTbDrBcfzFLcVJbMfJl+Y4sdP8JSaJ4xYbYlyw6cWAhEBdQr1LM5re587t7ZTvjztzNaOZUUdgh5eHB+bec/beZ999zll7rXe965/+/BeEhy8slXsq0uzFQBCF96Rm1OWGJImX5V6XJJG7HrmafbtO0d7cz5b1Rxjq/yFX39hIaUUATTM4fqiT15/bw0BvCNUic9NHF1E/+0Iz6n69IAgCFdOLePiLt3Ln71zPoR3NnNjXRn9XkFg4ga4buDx2iirzmLmwhoaF1VjH8EplReKBL9zMx37vplyb57Oxc3rsLF0zm0XXzyIRS9F2rJtTR7ro7wgy1BciFkmQTmkIZAU7sy91HxXTi5neVEmgyIMkSRd9T3z524+/JxEDURTOmm1cXJnHP734h+P2nJIkXNTmYPm6uSxZ/ffjbMyz9W2aJnveOco/fO6HuXp/qlVhzvJp3P6JVTTMrzq3MWmCltE4daSLF37wNptf2ksynvXgx8IJXn1qM41L6yaV6bm7rpF/27+Fo8P9/POedxhKxXmofsFlIYj/RgTUo+EET//XWwwPxQCYNa+Sxz6/hmkzSyb9YVVVxjwPgYxRUT/zHOGSD3F2iJKI3TlSfkEUmLuompvuWvQ+j+rKwGZXc2tQliVuvnsx/rxzh6zOhkgowY+/vYFIKI4gwILldTz4f66npqF4UmP8Uj2GH+LiUFjq5VN/fDM/euJNDu9r5/De7L9nwmZX+ci9S7j9/mWXLCEyFoZp0Jno5nD4OEPpILqpY5Us+FQvs9wNFFrfn7BgNtog4M1zsfymuSy/aWIB77OdO7Z4+4X2KysSLq+dWYtrmbX4ymVsvpfk7eF0iJe6X8fEZF3xDfjU0xstQRTOr/zXeUCSxAva7A/2hHjyH17KGU2iJLL8prk8/md34D8Hj3AsFIvMjIU1FFfmEwsn2Pba/tx33a0D9HcFKa2eSPi+qrgan8XO4WAfaV2nwZdP02XQcILfEMPp2MFO2pqzwneSLPLo55t/Sq8AACAASURBVG+kYU7ZpBNkmibplEYqcfaYtiBkidHZNHuT9lP9ZNLaBz574YMIWZEoLPFx8kh3ro6gpukX9fD7dYM/34XNrhIJJQgORhkejF6y4XTg3VP0jHDGLFaVx35vDZW1BVOu91HS+Ie4shAEgZlNFaz6yFyaj/YAJnmFHjRNR1Ek/PluGudVsuia6VTVFV42PhmAZmi80beRl7pfJ5QJY2IijKZkCyK/W/vY+2Y4fYjLi6gW47Xe9RimwdX5y8YZTu8XTNNkx5sHaT7YkfssUOTh9k9cd0FG01h48pw0XTWdXRsOoY1QbWLhBJFgDKonHj+cSjCUjGOXFaySTFcszGAyztqK6b++ApiXE4P9YVIjL4ZAgZvy6vyz1I+Ctpb+88rYmb2wmlee2QVA68k+Wo73Mm3m5cus+98Cq1WlYXYZWzdkdZwO7G4lFIxNSpb9TUNFTT6BfDd93SEMw2TTG4fGaVxdDPq7QzneVEFxVkRxqjWp6wZtLQMkExevgfMhLg6GYbLh5X3897++gSgKPPTp1ay5YwHWy6T9czZ0J3v5SfuzxPUEczwzmemuxy7bSGhJhjLD1DknedN8iA9xmZBJaZw80D4ue66g1E9t48VLygiCgNvvHKGOZJ9/ekbPGVFn4i93vIFFlimyuXLMH7t8eTYnvxGGkyicrr5taMaUJOKsOnOKN0fKp5wL02aWUFzup7t9iJ72IG++sIfy6nystrMr3Y5yWj40sLIQJYEZTRUUFHvp6Qxy7EAH2946yto7F56T2DlK3LycfJsrCYfLyuKV9RzZ34Fpmrz1yn6uWj2LqnNk5YzN1DrzOGEMwVzTppYXME2T8HCct8e4tj/ElUMqmeHn/72J8HCcWfMrWXvngsvqVTobDoWPEtcTBFQfD1fdR4ntdAFmwzRy3qcP8SHeC6QSacJn6Pn5C92XVP3BNE2iw/Fx3GNZlVGmqIJQ7vRS78tjUUE56gg/VrxM6/6Dz9Y8DxSV+bCOpBAPDkTYs715gv6GoRv0dAb59jde5sj+iTyDMyEIAkVlfm64ZR6KKqNpOs8/vY3//tdsUd5kIj3uhWUYBvFokq72QfbuaCEevfIaNB9UCILAjDnlXLOmEUkSSac0vvfPr/Hyz3bQ35MN242FrhlEQnHaW/rZ9tZRNr15aIqWP/gQBIGbPrqI6ulZhe/O1gH+3189x7tbThINJ8YRRk3TJJXKMNQfofloN796dvekmk9lVXm5kHF/zzAHdrWi6+Mz73TNoKttiCe+9iItx3rewyv8EFMhEU/TPZI2r6V1IqE46bR2RWQWepPZdVNmK8GvjhcwFQXxw03dh3hvMUnyVyKawjCMKU44NxLRFAe2nRyn4ejyOfBOEbmQRIHvHNrBH2x6kc++/Ryfffs5vrzt1Yvufyx+IzxO1dOLqKorZKg/gmmYfPefX6OrbYjahmKsNoVYJMmpE31se+sIxw52UlIRQNP0HE9kKqiqzNo7F9B8tJtNbxxC1wyefWoru7c10zC7jKIyP1argq4bhENxBnvDtJ7so6czyNe/+/iUasHvBXRNz1arT6ZJxjNEIwliY8ob9HUFaT3Rh8WqYLWrWK1KrkbQlXiIyorEnQ+t4NSJPrZvPEoknOA/v/EyG17Zx/RZpfgCLmRZJJXSiITi9HUN03qyj+6OIdbeuZCrbpj1no8RssbLKA8umciQjKdJJdPj1koilqblWA9urwOrTcVqU7DYlKyI3iRz6fbaeezzN/Ktr75AV/sQh/a08fUv/ZSmJbWUVgRwum2YmCTjaQb7I/R2Bjl1spd0UuOP//ZuKmrGEx+nN5ZRWhHg2MFOMmmd//jGS9x423yqpxehqjLRSIKTR3rYtvEIzUd7qKwtIBpJMtD7/lSWfy+gZXSSiTSpZIZEPE00khgnvNrdPsSpE71YR9a7ZXS9C1dmvQNYbQqFJT462wY5ebSbv//iz6iaVojdYcl5DAVBQFVl/PkuqqcXUVNfdMkimIZpkDKyIRJFVD70LX2IKw7VqkwQCO1uG6CnbZCSqgvn1um6wbbX9rN/6/HcZ4IgUD6tkEDh5IZTVyzMH867hgUFpaf5fZfpbviNMJzsDgsPfGoV7S39DPSG6W4f4kdPvInDaUGURLSMTnxEKKxqWiGf/vItPP/0tnMaTpDlTP3OH9+M1aaw+c3DueK8p473ZlOXxyjdjm4krTblihVnTCUzPPPDTWx89UBOMVrXDXTNIDSSZQjw4k+3s/7lfbnMCFESUVWZj9y7mLV3LrwiY/X4HHzqT27GG3Dwzq8OEo+m2L/zFPt3nsoV3jRGxj8KRZHOqyDt5cK+HS1875u/IhFLnVac141xnLjWE7189QtPI8sSkpydS0kSaZhTzqOfXT1O7R2ymYRNi2v5vb+8gye+9iJtzf0MD8XY8PI+RFHIqYTr2ngV+7xC96Q6KQ6nhQd/9wb+6c+fITgQofVEHz/419exO8as92gSE2iYU84nv7COHz3x5m+E4RSPpXj6v95i+8aj49a6rhsEB06HBn72/bd56afbc79NVjdN5aMPreCaNbOvyFitNpV7H1/Jf/1jtmjz/l2n2L/r1ITjRFFAtSo4XVbmLKrh4U9fT0Gx97wNPN3U2R86xLvBfQylggQzYXpT2WSZg+EjfOXA18a1tcjfxK0la1HF8WHDHUO7+XnH86wquIZVBVcT02LsCu5l9/A+QpkINslKqa2EZXkLqXNUj2vTME1iWozWeDt7hw/SGu8gpsVQRAW/6mWmu56FvibcigtxjIhbMD3MT9qfJaWn+O3ah3hnYBtbBnfgkl3cVHQ901w1dCZ6eK7rZfqSA9Q5q7m55EZ8ykSCsWEaDGdC7Bjaw+HwUYbSw8iCRIW9nKWBBdQ4K1EEJacOvnf4ID/peJY6RxWPVn88155m6PzjsW8xmA4yzVnDo1UfQxopEhvJRHmy7WcMpYe5p/y2HFfMNE2SRooTkRZ2BvfQHu8kY2bwKV7memfR5G3Ep/qmlLrYM7yfH7f9kmvyl7G68FoSeoLdwf3sCu5hOBPGKlkotRWzJLCAemfdBRn/cS3BLzpfZH/oEHmWAPeW3065vfS8z78YqBaF6pmlWOwqqRGeU2/bIM9+ez33fX4t3jzXOa9hVK8uGUvx9vO7+eE3XmC4/7SEkNWhcu3tC0cENSfCpVj4l32byLM6UEakUFyKhb9ZuuaSr+83wnCC7Aviy9+4j+d+vJXDe9sJDkQJBeOIkoDdYaGytoCmxTXc+vGlFBR72bez5bzjrXmFbj7zldu4+sZG3nxhL+2nsvXT4rGsuKEoCdidVpxuG4XFXqY3luILON/jK87CMEz6uobPGY6JhpNEw+NLtkiSeEVfpqP19z79pVtZtnIGb764l47WrLE7KhQpKyIOlx2v30FhiY/6OWWsWnf+6cqXinAoTsuxHlLJqbMuMxl90nlzuW1o2uSuaFmRaJxfxd888TC/em4Pe7adpKttkPBwnFQyg2maKKqMy2PDF3BSUhFg6bUNTJs5sZK3IAjMX1bLn3ztbl54ejtHD3QwPBQjFIyPlLSxUFNfzLyltdx+/zK8ASeVNQXsfOfYxU/MBwS6btDdEaTleO9Zj4uEEhMkRFRVHmdcvZfIZHSOHejgxOGurOEvgMWioKjyaYk6M3s9qVTWs5mMp1n/4h6Gh6J89iu3UXSeNQIN06Q93sWR8AlGlRwFc4wCOwaM/XuKSGHW8OmgNd5Oc6yFp9qe4XikGUWUERBIGWn2hQ6Rb/FT5xhPLk/qSb5x9Fscj54EwCZZsUoWMobG8UgzWwd3saFvE49U30ftGKNLM3V6k330pgZ4tvMVNg5sIW2kiWoxTsXauL/yLp7rfIXeVD9pI83xaDMhLcKjVR/DIZ8WJc4YGvtDh3iy9Wd0JXuwiBbssg3N0DgSOcFb/Zu4tuAqPlr2EZxydmOjiArD6RBHjOPE9USuvc5ENyeiLUS0KKFMmPsr78JG9l0xmB7iRLQFAQGXfPoZP5Ae4um2X7JtaCe6aeBSnEiCRFu8kx3B3ZTainmw8h4aPQ1IwsT3TkyL0xpvpzVWxqlYGz9u/wVHwseRRRlxZO73hw7jVdxMd9aO85ycLfAbyoR5puNFftW7gWJrIWuKVlFmm/hMudwQBIEF187glSeLOLGvDch6iZ///kY6W/pYfe8ySmsK8OW7sDosSJKEYRjZyEksRWQ4TrA/QsuhDja/vJdje1rHCQFLssiqjy6m6ar6KcdwT90cbtVnZscz8pl8mbTkrqjh5HBZ+Z0/uZlkIoPHa59guMyYW84f/e3diGK2kOZYSJLIXY9exXU3z0W1yBNSukVRoGFOOeU1+bQ39zM0ECWdymSNGruF/CIPxRUB1BFuyNWrGykq82Ozq+QVnr30yWjx1SUrG5izqIbeziBDAxESIy97URSw2FRcbhv5RR78ec5JBcYKir184at3YZpZ7RaX5+ylTABu/fgyllw7AwGomlY44XtVlVhz5wJmL7zwLBlBEKiaVnDGZ9C0uIY/+tu7R8bsOWepGcUi8/jvryUWTaEoEvWN43czY8nyWSVbmaXXNTBncTV9XcMM9IVJJtLomoEsS9jsKh6/g4JiL0637byUgS8UU5Gv6xvL+P2/vDNX021TSxvbWzv45IpFONSzE3u9fkdO+2syCIKAL8/FXY+s4IZbm+jpCBIejpNIpHn96AnWN7eQcNvwVRXxyB3XU+QfXwS7Oxzhn9ZvQjdNLJLE7XNm8pmv3EZbcx+hYIx0SkOSsoZTYamXwhJfjgu1+vb51M4oxuW24fZOXWNrzqJqfu8v70DXDLx+xyWROcur83PryOW24XCdW7X3nt+6hhtum48gQN2MiQ94q03hto8vZem1DRc8HkkSqG0Y36Ygiiy9toH8omwKd0m5/5ySI7JVxnZdMaXJfB5alg2RjoWW0Xn7tf08+e/r6WwdpLw6n0c/eyPl1XnZMNyY5axrBslEmiP7O9jw8j6GB6Mc2HmKdzefYO2dC86pzAwgCxJX5S1hjmdm7rNfdr7E1qFd1Dgqubf8DlTx9D3slB3IwtTX2JXo4cm2nxPJRPlo2S2U20sQEAhlwpyItjDTPfFlpYgK+VY/sigyzzubElsxVslKxshwPHKSV3re5GTsFK/3vkVFdRmqMP5eCmXCHI4c457y21AFhWe7XqEj0cWPWn9KlaOCO8s+Qkeii2c7X+ZEpIXuRA91rhogey+fjLbwo9af0p8aYKGvieWBRXhUNxlD41jkJK/0vMHrvRtwyQ5uL12HKIj4VA9e1UNUizKQGswZTq3xdkxMAqqfUCZMT7KPakcFJibBdIhoJkqpvQS/6s0SlrUYz3S8wJbBHfhVL9cXXkONowpJlAilw7wzsJX9oUP8qPUnPFb9AA2uqT1GPck+nmr7OcH0MHeUrqPSUY6ASFiLcCLSzCzPjAnhpslaMk2TmB7nFx0v8lb/JspsxTxQeTcz3Zeein++KCwPcNenruef/+DJXHadaZjsWn+Yg9ubKSj14c0bNZxEDMMcMZzSRENxggNhQoPRCZahJIksvXEO93z6xrMmDVW4vPz85AEODPXwR/NXktQ0gqnLo8d4RQ0ni1Vh+aqZk34nCAKFJT4KSybfZYmiyNxFNefsw+G00jCn/JzHlVQEKKkInPO4M8dod1ionl404WF5PnC5bVx3gd6TWfMqmTWvcsrvJVmiYXY5DbPPfc3nA0EQLnhuZFliycrJX2SmabK/u5eagA+n5fSLUxAEHE7rRc/lpcA0TXoiUVKaRoXPO+7BU1DspaA4+xLVDYPkYRvREyor18zGbb08nDVRFPHnuXLGv2GalC0sZW7HdNYfb+bEYBBdmkiudFlUVtRUcqJ/kJ/vPcj88hIWV5addX2MoqImn4qac3MLLua+mAq+gJNVN1+YuGHTkrOLEiqKfM57YhSmaXK4t58SjwuvbfJNiigKVNYWUlk7cVMyFURFRK5145Aklq2agSqffoyapklbcx/f/+br9HUPUzejmM/92e3U1BdNqdZsmibLV83AF3DwoyfWk05r7H/3FNff0oTlPAwnQRDwqd5x+j3OEW+ITbJRYS/FIp1/qYljkZPUOKv43LRPUmYvRhzJITIxuTp/KbIgT1ibsiDxePUDmIAqKoiIuZDYLHc9Bia/6HyRvcOHSBuZCWFC0zSZ6a7nqrylCEBnooeORBeaqbGm6DpmuKYz013PpoHt9CR7Gc6c9vimjTTPdb1Cd7KXRb4mPln7CHbJlhvjTPd07LKNn7T/ko39W5jjmUmdqwaf6iWg+uhPDdCb7KfSUY5hGrTE2lBEhfneObwzuJXjkZNUOyrAhIH0IFE9TpW9HFmUs+rYw/vZMrgTl+Lk4ar7mOebPe76Gz31fKflKXYM7eal7l9Rbi/Jeb3OxIloCxX2Mj4//ZOU2UqRxoQ1r8pbPOncj9oVY7PLo1qMp9p+zjsD2yi1FfGp2kcpt5eOC5O+1xAEgeXrmsikNZ7+5qt0tvTnMuKSsRRtx3pou4DEFVES8eW7WH3vMu745HW4vGcvffOjY7s5FhzgyHAf8UyGpK7x/cM7+fqKmy+ZSXPJs2iaJslMM92hb9Id+iZ94e+QyrRNebxhJAjGniOc2HipXX+IXwMMJ5L8zasbaA9+cPg1umHyy32H+MW+Q2ctgyCJIjfPqufvb1t72YymySAKAtPyA9zVNIsllVOX3HBaLNw2ewa3NDZgvUQC8f8GRFJpvv7G2xzru7CCsJeKvdub6eseRhQF5i2to25myVlLXIzWE6usK8wVGI6E4u9LUW/IGkg3FV1PpaMMSZBynmJREFFFddKXryAIWCUrNsmaO2f0c1mUmefN8srCmQj6JHUTLZJKsbUQSRARBZF8awBFkMlX8wiofgRBwCKpeBQXaSNDykjnqj/0pQY5EDqCgMBNxTfgkO3jXqiKqDDLXU++JY/B9BDHos2YpolVslBozSdtpOlLDWBiEtGi9CR7sYgqs70zcEh2TkZPYZomGVOjO9GHYRpUOysREEgbGXYF95EyUtQ5q2nyzp5w/W7FzdqiVYiCyL7QIfpTg1NmVhoYrC1aRZWjAlk8PfeCIEw99yP/Hf0+mB7m6fZf8s7ANuqc1Xyy5mEq7GVX1GgahaLKXPfRxXzh3x7hpvtXUFQZuOAIgmpVqJtTzp2fXMWfPPEYD3zhZtw+5zk9Zzv6Ovjs3BVUuLLOGJ/FRm8idtZzzheX7elrmikSmaPE03uxKtOwKBWTHmeYSYYTr2KRa3DbrrmE/kw0ox9RcCKJl7cA7/9mmKZJWtfJjISqREFAkSQU6fQOKq3raIaBXTmtZ2UYBglNQxZFLLKMbhikNI13O7oYTiSJp9NEklmCtSpLqJKUa88wTVKajm4aiAiosoQsnu4vnsmgShJpbSQsKsukNA3dMLEqMtLIGE6PLZsZJ4oCqiShjGh4GKZJRtcZjifZ09lNtd9PJJUa6QscqjruGtMjMgmCIGBXlUmJnaNtnm2+MoZBRtcxDBNBAFmUUGXpstc/NEyTWDqNVZZz8zc6L6PzO/Y3OxdGf5u0pqONaP+oZ1xbShtZC2PmRzcMkhkNSRSxyBKGaZLUNCyyjKbrZIzs72yRZeQxHpVzrYWx1yIIoIgSKV1DG9OeJAq5MR/u6aM7HCWezuTWniJJWMZkP2b709ANAxBQJDG3NsfOa1rTyRg6IgKafvaU6u6RpBNREskvOj+VZNM0iUdTORkVh9PK+1XaTxUVZnmm5o6cDdmCqjqGqWOO/mOe9p6amBhMnD9JkMZxllRRQRBEbLIVq3jaWyYLSrYN08i6WgRojp1CMzVcihOP4iauTazJqIgKNsmKZuoMpobQTA1FUKgYIUkPpAfRDI1gOkR/apBCaz6V9jKcsoPeVD9RLYYoiHQnehAFMeuBAjRT41Qs6yiod9Uhi5MbyFWOchySnbAWoSXWSpV98giBIig0ei48DJ2dM5WUnubl7tfZ2L+VakcFj1V/nFJb8fsqPyFJItPmVFBWW8itnStpPtTJ0V2naD/Ry0B3kHgkSTKRRhCypHKH246/wE1BuZ+aWWVUzyghv8RHoMh7QYWS7ZLCUDKevX8Nnc5QGK/l8myAL4vhZJGrKfb8AZHUJloH//Csx0qil6rANy+5T9NM0j70FfJc9+O2XrwB9iHG41j/IN96ZxvH+gZIazqSKLKwvITPXLOMYo+LjG7wzY1b2NnWyXc+didOS3aH3BoM8cfPvcrqhlo+sWwRB7p7+c7WXRzs7qMnHOGPnnsVy8iu+6FF87h3fnYHGs9keGbPQZ4/eIThRBKrLLO0uoKHF8+j1OMmkclw3/efZtW0Gt5uPoVdVXh0yQJ+/O5+Tg0FeWBhEw8tagLgneY2/nvHbtqDITKGgUWWuGnGdB5ePA+PzUookeR/du3jrZMtHO7pZ09HN2+dbEEAvDYbP3zwLiQh++J9Zu9BfrL7AAOxOHZV4amH7iHgGG+gZ3SdTc1t/HzvQY71D2AYJrIksm5mPY8vXYBNVeiNRPn+9t1sam4lns6AANPz8/jEsoXMK7u8D7SBaIwHfvhT7m5q5LGlC3IGZUrT+bOX36AvEuWJe27Fppzfwyej6zx/8CjP7D1EXySKLIksqijlE8sWUu7zopsmT+7cw1Pv7uPvb13LgvISTNNkc0sbf/3qBu5fOJcHFzVxoLuXP33xde5pamRrawfH+wcQBYE75szkvvlz8NiyD7NERuO5/Yf5xf5DBOMJLLLM4spyHl7cRLk3a4CkNI2/fX0jFklmQXkJP9t7kLahYQC+dOO1XFNbSfNgkO9s2cnuzm7agyH+4pU3sY146G6aOZ1PX70UAE032NTSyg+276ZjOIQANBYX8siS+TQWZwVKdcNgT2c33968k+P9g3hsVpZWlpHKaFimKDrtdGevx9ANutoHR5Iezl4MdWggwuY3DxGLphBEgdqGYmT5/fEqOmQHFvHChDpN06Q/NcjxaDOHw0fpSHQxnA6T0BNkDI2MefaSPwICijjxeiVBGucpGcOrz2EwlTVUw5kIX9j7f6fsY9RgS+hJdFNHQaHKUYkkyPQlB4hrCQZSg/SnBlkaWEjA4sev+uhMdNOb7CPPEqAj0YVfyYb4YDSTL+tND6hTk/llQcatuAhrkdx4J4Ndtl1QWHUsBOD5rlfYNvQuJialtiL8qu998TRNGJuQTaCqmF5MxfRiVt62IJukMOJ5G/09hdMnIIycN5km1Pngnro5/OehbRwN9vMPuzcSyaR5bMbCD0aR39MXJHC2HPzxrsmpf8izicON7nIBUlorKa0tp7tz+qDLp9XwvxGablDp87KmoQ631cLhngF+uGM3BS4Hn792BZDN5MuGEcaINwK6aWCM/BblPg+PL1vIWyda+MnuA3xu5TKq/NkHS6E7y78wzGzI7Hvb3uXjC+fSUJhPfzTKkzv3Ekok+b83rcIEukIROkNhHlk8n3/ftJ1/XL+Jx5Yu4GB3Hz9+dx93NzViU2R002BeWTH3zJuNTZHZ1trBj9/dR5Xfy62zZ2BXFW5sqGNOaRFffW0Dc0qKuHf+bCRBRJbEnMdEFARumjGd+eWlPLP3IG8cOzlp5sq+rh7+6tX1zCou4A+uuwq7qjAYi2OVZdQRI1E3TRyKwuPLFuK32xiMxfnO1l3829tb+fd7b8t5wy4H3FYr19RW89KhY9y/sAm7mpXKODUU5HBPH3c1zTpvo8k0Td441swT72xj3cx6FpaXMBCL84Ptu/mXt7bwl+tuwK4q3NI4g90d3Tzxzja+fttaREHgPzbvoL4wj1sbG0bayhLbnztwhDvnzuK++bM52jvAd7ftwmO1cve8RgRB4MVDR/iPzdu5b/5cZhUXMBiL8z+79vKP6zfxtx+5EZuqYJJdN9ta2wkmEtza2IDPbqM3HKEub2R9uRw8sKiJGYX5/OfmHfz28kXMKsomQfgdttz1vdvRxd+9vpElVeU8uKiJRCbD0+/u56u/eot/v+c2PDYrwXiCb7z5Dook8cXV16BIEq8dOcGezm6uqa2adO4aZpcjySK6ZrB1/RHqG8u4enVjTnZiLDRN58Thbn75o81s33gUgJIyP3MWVSNK789z7EJftKZp0hrv4IetP+FEtBndNCi3lVDpKMc5YoQl9AQb+jeftR1hkvfC+czAqEGkiqPhvrPfU3kWf+4dUWjJxyZZGUoHielxuhI9pI00dc5qJEGi0lHO0cgJ+lODWCUrQ+nhLIdp0j7OPtrRPs9WYP5ijJzR1oKZEDuDeyi3lzKUHmbr4C5KbMWsKbouJ8PwfmNsCPO9xrKiCnxWG8eHB8gYBnWeALP8Z6/YcL64YlsakxQtA58lrbWjmxF89psp9X5x/DGmQVrvYDD6NJHkNgwzgSy5cVuvIeC4F1nyk9ZO0Rf5HtHUNpKZk7QHv4wkZIl2btsqSrxf4IqJKE0CzUiT0CM4ZO8UN9eFIanH0MwMTvnKFG6cUZTPtPxALhyzuKKcdzu6eLej+4IUj/12O367neaBIVRJYlp+HjOKxpOT24eGef7AEVZNr+HhxfNQpGxYx66q/N3rG9l2qp1FlWUIAiyuLOOG+jq2tXXQNjTMuhnT8dttbGpuZTAep8zj5uraKq6qqcyFdhZWlPLSoWMc6RvgFtPEIsvU5QcIOOzYVYUCl5PZxUXjwkWQvam9dhsuq4VC1+SyEqZp8t/bd1PkdvL7162g0ucdF3qURuIsJW4Xv71iUS78oxsGvZEY396yA90wuYSktQmwyBIr66p449hJdrZ3ck1tFaYJ+zp7GE4kubFh2nm3NZxI8tM9B2gsLuT/XL0EiyRhmlkv1H9s3sHezm6WVVeQ77TzuWuX83vPvMh3t+0ildFIZjQ+tWIxHpt1XEjs+vpa7p7XiCQILKkqZ09nN28cO8kN9bWkNJ3nTDAu5wAAIABJREFU9h9hRU0ljy2dn1sLLovKX7+2gXeaW1ndUJcbX084wt/eciMNhfmII17C0R2q22qlsdjKYCyOIkvU5vmZUzo+ASGeTvPCwSPYVYU/XHUV9hGD0irL/OWr69l48hQfmVXPns4emgeC/OMdN7G8ugJBEKjN87O5ZWoeZ/3sMq6+sZG3Xz1AT2eQb/7Vc/zyyS3UN5bi8We5Gcl4mv7eEKeO9zDQGyYaSWIaJt6Ak7sevZppM359amLGtBhPt/+Cw+GjVNjLeaDybirtZciihEh23bfHO85pOF0svIo799/PTHsct3z2ItqKKOfI6aqoUGkv43i0OSuBEG/HITkoH0nZn+as4XnjFXqSfSAIGBhUOypzpG1REPEoLvpSKYKZ4Sn71E2dkJb1TPnUs2dxXyhy5cZMg/sq7mRl/nLe7t/Czzqe59nOl/EqHlbkLf5f51CQRJFZ/kJm+rKbJkEQGEjECFjtl3xvXTHDSUClxPP7pLRWukP/hG6EJhyjG2G6hr9BWu/A77gdQbCQ1jvRjRgmWVevKLrx2K5HlvLpj3yPgONu7GpWVVqRit6TxaEbGQRBPC9DqC/VxpaBZ1hT/Amc8vnpsJwNh0Ob6U2dYm3xJy65rfNFW3CY5sEhgokkaU2nPxpDkcSz6oVcDHoiUXrCUR5dsiDneREFgXmlxeiGyZG+ARZVlmGRZdxWC5Io4FBU8p0OpBGukyAIZDQ9J555rH+A1qFhwskUGV0f4WtNXgTyvDDFckpmNA73DnBVTSUVXu+4nZQ05qYUBIFgPMHh3n4GY3GSGY1DvX3ohpHlaVxGCILAnNIi6gvzeHbfIZZVlZPWdd44fpJraqvw288tfzGKrlCEnnAEURB4aufe3OenhoJEU2k6Q+Fcn3V5fj511RL+5rUNaIbBVz+ymhlF42UuHKpKhc+T01FRRJE5pUX8ct8hIqk0oWSSzuEwdzU1jlsLs0uKEAWBQz194wyngMOeM5pGj70QhBIpmgeCmCY8/e7pWn7ZbEud5sEhAI729VPkdlLsPi3Y57ZaqAlMfm8LgoDH5+Dh370Bm11l4yv7iUVTHN3fwdH9HZOeA1l5khlNFdz00UVcdcPMXxujCaAz2UNnogdFVFlTdB2z3PUTxj+UntqouFSMeoeG0sMk9RSltgsrol3rrGb38H6C6WHa4h1UOcqxStlwa7WjAllQ6Ez0ENcTyIJEub0kl2moCDK1zmr6UgMcjZxgbdGqST1erbEOYlocWZCpdpw7I/RiIAsSTd5GPIqLtUWrGEoHea13A0+1/Ryv6qHR3fCBXVemadIzGKFvKMKs2uIJm9lLwdhr/tq7G/j75esu2Uq4coaTIGJTG1CkAmRxcu+JYSZIa+04rUsJOO9DQAFMTDOJIGQXsiIFUGwrQZAZjP4PdrUJj23lezZuE5MDobcpttVRYJ2c8P6bAsM0+cXeQzy5ay8eq4UKnxenRSWZ0VCkM9KHzzzZNKcU1psKmmGgGQY2dXz4yCLLQJa0C1ltqdyLUcjWIBq1aIQxbf3r21t560QLxR4XpR43NkVBuxSj6SxI6zqGmSWnT/UsMk2T7a0dPPHOdlKaRnXAh8dmJZZKX/BcnS/cViurptXw/W27Od4/iF1RONzTz5dunJkrdHk+SI+QuHvCEbaeGl/bcXFlGQXO8Z64Sr8XzTDQDZPqgA/TNMc9sASBcanVkPXuZPRseFfTDTKGMSGUaJElBASS2niOzKVmOWqmQUrXGE4k2XKqfdyDdG5JEeXerFcgldFRJCnnQcxei4DlHFmNxeV+fuvza1hx/Sz2bm/myL52ejqGiMfTmIaJxarg9NgoLQ9QNa2QOYuqqagtwJ937myhDxp0U8cYIfOfqQ9lmiYJI8nbA1vfs/6LrAXUu+o4GD7Ci92v8VvVD2CXspuEsfQOAwPdNJDP4E2NEr3bE130JQeY65mFMqJ75ZDtFFkL6Ev1E9WieBUPPuX0RkkRFeZ5G9kd3MeJSDMHQ0dp9DQgIOT6TuhJ3ujbiGEazHBPp8CSd1mDIpM9SiRB4paSNQxnQmwbfJen236Js/rjVDkq3tf1lUpnEzFslomhw46+YfYd76KhqvCiDaeW8BDRTHrS7wzTpDVyeQz4D1ROsyz68Niupz/6JLoRxGNbjU2ZmfUkXeKPnTFSDKW7EZGIakOooo0CayXyiBDbULqbcGYASZDJt5Rjk12kjSTdiZPsDr5OQo8QzgzgV4vxW4oxTZPhTC/D6T4kQSHPUopNyrqITWAg1UFfsg2H7CbfUoEoSJimwWC6i0hmEFm0kG8pxyplw4wJPcJAqgPNSONW8vCrxQjC+IyjtJFgINVBnqUMVbRd9hvg5MAQP9jxLk2lJfzx9Vdns+NMg9bgMIOxkUwVIesCzej6uJd/LJ0mnJxY2HhsNs2Z8FgtuK0W2oPjvY894QgCAgXOUa2Tc1/nu+1dPLP3IL+1dCEfWzAbWZLI6DovH55cLVtAuKDQ45mwqypOVaEvEiWpaZNyh4YTSX60cy+xdJr/vO92XBYVE/jB9t3sbOu86L7PBgFY2zCN727dxabmNjK6RoXfy5ySC7uHvDYrLovKsqoKPnft8gm/wFgjaDiR5J/Wb6KptJh4JsM/rN/EX627YRyZPqXpDCeS4wyqzlAYj82CRZZwWy14bdYJa6E3EsMwzQkh0/O5lFHz2pjkd7YpCn67jUKXk3+4/aYJHqvRvwtcDkKJBPFMZjSJK1veJZ7A5j57SMjptrFgeR3zltZiGAZZB+NpGqwwQnoVRAHxCtWMfC9QYMnDr3oZTA+xsX8zPtWDb0QcciA9xPq+d2iJtqIIMpp5+TcyFtHCHaXrGEoH2T60m+FMmGvyllFozUcURDRDYzAd5GS0hf7UII/XPIh/jOZVgSUPt+Ji59BuACodZSgjBqAoiEx31bJlcAeSIFFsLcCrnq6NJggC83xzWB45wYa+TXy35SnWFV9PjbMKSRCJZKJs6N/MzqE9BFQf64pvwCU7L2tkZLKWBEHAq3j4WPlHiWsJ9oUO8cPWn/LJ2ocptF54rbjLAdM02bj7JKmMxroVMyeMe0FDGfPqy0Y2xheHv9rxJkldG+f1z/UP9CYuT+WAD5ThJIpW8l0PYZGrCMafp33oK1iVOvKcD+K2XYsonH8q4pmIasO82PktCqyV2CQX/ak2ZrpXMNt7Lf2pNjb2P41HziNjplFFK8vy7kBEpD/VRlQbZCjdjW5qWEQbfksxw5leNvT+D27Fj2ZmkASZZXm3AzCU6uJIeCsiEgOpdlYW3EepvZ6uxAk2D/wCr1pAWk/gVHwsCdyCCWwdeI64FkKVbIQy/SzPu4MS22lOioHGjqEXSOhRlgXuQBXPP+xyvkhlNDKaQanHhcOiYpomB7v6OTkwhHdkhy8JAnkOO12hMJ2hMA3WfDTdYHNLGz3hyIQ2XRZL1g0bjjDzjPBNhc9LQ2E+rx89wer6WgpcThKZDK8cOY5FllhQfv71lGLpNJIoUuxxYlUUdCM7pmB8olKsJAq4rBY6Q+GRcNmF724USeTaaTU8d+Aw21s7uLq2Kse1iSRTOC0qumEST2cocDlxWy2IgkB/NMa21nb098rlRFbv6Yb6Ora3ttMXjXLttJopuVpTocTjorG4kG2t7ZwaDDItP5DjaHWGwhS7XYhIJDMaT+3aS1c4wtdvWwvA7//iJX625yCPLJk34j2EZCbD1tZ21syow2O10h+NsbmljdnFhfhsNrw2G43Fhbxx7CQ3z5pOkdtFMqPx+tETACytvHCBV7uqIksSHcMhYPz5XquV+WWl/HT3fg729NFUWpz7/TpDYQqdTkQpG/oMJ9PsaOugPj8PQRQ43NfPsb5BSs5hOMFI6FYSkC5j6OGDhoDq54bClXQkujkQPkJbohOf4sEwTQbSg3gVD3eX38bL3W/QGm8/d4MXCEEQqHfV8WDlPfy041kOh49xOHwMm2RDEkTSRob0SNHjac6acUa/IAjYJBuFlgJORJsJqD7yLXk5I1ZEpNpRyWu96wFo9DSM41AJCDhlB3eUriNtpNk6uIvvn/oxXtWDLMhEMhGSRoo81c+9FXcwx3PlwrCCIJBvDXBfxZ0MnBjicOQYz3S8wENV946TfnjhnYPkeRwcbOlBkSVWLZxGab4XwzB4ecthZtUUsfVAK8ORONcumEZDZQG9QxE27j5J31CUfJ+TlfNrKQpkDcpwLMkbO47R0TeMw2rhugV1VJX4+dmbe3lz53FM0+Roax81pQHWLZ+JRZV5/u2DnOwYoLG2mGsX1KGMJNdkNJ0DJ7vZebiddEajvrKAlfOz35/sGGDDrhNousGiWRXMm16KRZb5+op1WKWJpo2JyafeevayzO0HynACkEQ3XvvNuGxXk9G66Al/i87hr6LKpdjV06rjp5fe+b+AdDPDLM9VlNtncDC0iZPR3cz2XsvOoZepsM9gnu9GUnqc13q+Q0f8CNNdi5nnu4FDoXdo9Kyk3F6f63n30Gt41Txme68jqcfY2PdjepOtWCUHsqgyz7cav1rMrqFX2BN8nRLbdLYPvsA01wJmea4mpg3zWs936Uu2YmIymOpgddGj2GUP+4c3sH3wBW4r/RwgoJsam/p/jm5qXJ1/Dxbx7IqpF4uqgI+ZxQU8s+8QXeEIpmnSMRwmz2nPifGJI6TrCp+XP/jly8wsKiCcTBJNpSnxTHyRNJUVU+R28Y8bNvPakROIgsAN9XWsml6D06LyqRWL+eILv+IzP3+BmoCfgWiMlsEgn1yxmNo8/4QQzVSYU1JEwGHnPzfvYFd7VjtqOJGgehIuil1RWVlXzXe27OT3fvEyfrsNVZb40xuvRRAEQskk6481MxRPsKmllVAimc0sdDqZXhBgQXkpoiDwsQVzONLbz1+/up6GwnxcFgt90RjlPg9/cN0K3DYLS6rKeHLnXr70wq9wWy057ozbejrlOJ7O8NKho4STKTa3tDEUT/DUrr2UejxMLwgwv6wESRR560QLbUPDtAZDhJMp1h9vIZpKU+R2sbSqLKeOLQiwur6Wlw8dI55Os7Zh2rhQ0/nAIsv8zorFfPH51/jDX75MdZ4fqyTTHYngtlj42q03Iokibzef4md7DvLZlcuYWVSAaZo8vHg+396ygzklhSytyhosdlWlLTjM5595iUKXk+aBIQTgrqZG7COh2k8sW8iXXvgVn/35C9Tk+QnGEpwcGOLRpfOZVnDhaubTCwLMKMzn25t3sq21A1WSWFBewp1zZyFLInc3zeJ4/wB/+sLrVAW8uC1W+qJZ3adv3X0Lfoedujw/t8+Zwfe2vsuO1k5USaIzFKYuz3/B47mScMoO8lQ/bsXF+caFLJKFPNWPX/FekEdEEASWBRbhV72807+N5lgrKSONW3axrvgGlvgXkG8J0BbvIKbHEMe0LQkiHsVNQk+OkyOwiBYCqg/XGUWB3YqLPNWP9Qy5BFmUmeudRbm9hH2hQ+wdPkh3ope0kSagWimxFTHdVUOTd/a4GnOQlQCoc1YRTAepdJRnQ2ljUGYvptxWSspIUeWomKB6Dlnj8ZGqj7E0sJBtg7s4FW9HMzRqnFXM9sxgga+JEtvUGX8W0UKeGsCjusfNz/lAEiQCqh+DbBjyTFTay3iw8m6ebn+W49FmNg1sY1XB1cgj8/3a1iO4nVbWLG3gYHMPP3hxO5+55xpsFoVNe1vYebidq5pqKCvwYFFOGzSSKLJoZgXbD7Xy09f38Pjty9ANg3/72TvIosiKudUkkplcWZQlsypp7hzEosrctGwGTrsFeSTTdNnsKjKazo5DbVw1txpFlrJUh0NtPP3au9y4tAGfy5ZTR2/vCfJfz27hugXTsKgyT72yC8Mw+PKCa/FZbFNyHteU130w5AguJwwzjW6EkUU/suhBUtzkux7hRN/9E8jkgmBFEFQy+tmLfY6FS/HjVvKRRRWH7CZtJNHMFKF0HzM9V6GIFgREnLKfiDYEmCMpsqOaEqdLD/SmWknpcYbT2SrkNsmJZUSI0yl7sUtuFNFCwFLKyehuMkaScGaAQmsVimjBLrmxSU4iWhDT1LHJbmxy9pwCaxUHQhvJmGnApCN+BEyTNSWfeM+MJgCHqvDl1St57sAROofDuKwW7mmajWbo7O7syWUtzSoq4Ku33MivjpxgKJ6goSCP1fV1bD7VRonHPa5Nn83K3926hpcOHaUvGsOpquQ7s/MkCAJ1+QH+30c/wmtHj9MWDDGntIhPXbWEuaVFSKKILIrc1thAmdeDNEIcj6fTiKJAocvJTTOn47Ja8Ntt/MPtN/HqkeMMRGPUF+RxQ30tx/sHJwgWSqLA3U2zKHQ52NvZg6Yb4wysZFrjQHcfKU2jxO2mxO1mKJZgKJZAlSTml5WAkA0l/t2ta9jU3Mr+7l7Sus680mKWVVdgVRQkQeD+hXMpcbvY392LKAg8sKCJqoCPFw8eyRGl07rG/q4eDBOK3S6K3S4iyTRHkv0okkhTaTEScLx/kNYRzaKbZkwHsuHVUCLJ7OLCMYaTQLHbRaXfiygK1BdenGu+2O3iXz56MxuOt3CkdwDdNJhWEGBJZRl2VUU3DLpCER5YNJe1DdMQBQETuHnWdFKaxomBIZaMGE4WWeKhRfMwTJND3X1cXVvJ2hnTc54sgOqAj29+9GZeOXKctqFhit0uHl++iHmlxTnDTxZFFpWXZrMYzzF+l8XCV9ZcxwsHjtAZimCRpXHr02e38dc3r2b98WYOdveR1DJU+cuYU1qU05ayKQqfuWYpjcWF7OvqwWlReWzpfHqjMQZj8Q+ERs5kuKf8Nu4pv+2CzlnqX8hS/8KL6k8WJGa5G5jlnlq88f6Ku7i/4q5xn/kUL5+d9tsTjp3nnZ1TGx+LT9Q8OGX7oiASUP1cl38V1+VfNeVxZz4/raKFByvv4cHKeyY9ttZRxd/N+bMpzx/9zC7ZmO+dw3zvnPPqdywW+OaywHdxxcyLrAV8Y+5fnPWYOZ5ZzPHMmvQ7RZZYPruaq+bWUFOax9d/+CaDoRhlBdlwZtP0Uq5fOD4jN+BxUlnsZyAYRZYk2nqCpDMaLZ2DtPcE+dqnb8FlH19iq6zQi99lw25TmVaRP+7+zfM6KPA5Odral/vMME3W7zzONfNqJ4T2th9qIxpPE4mniCbS6LrB9oNtfKphxVnn4f7p8z4YcgSmaRJL70TTg8TTezCMBJHUFkwzhSIXY1WmIQoWUloHycxJMno3Gb0fExiOv4QourEpM1CkABm9h47gX6OIAVS5BMNME0ltwabMQJXGZ0pY5EoscgX9ke+T0bsQBBWLXI3Pvm7KsQpIEyZNEhSskoNIZiCbSo5G0oiO8JVGCcjZNNQcJ0YAh+Shwj6TRYGbs3wZTGRBoSfZQlKPoZvZivcxbRib5EISFVTJRjgzSJG1Fs3MkDaS2CQXhpkhlTvHQkQbwio5R/hXJnmWchrcS9k28BzOIh8BtfQ9MZ4EQcDvsPPIkvkTvmsqKxl3XH1BHvUF43dmFf6JpH9BECj3efjkisVT9lnscfHw4ol9Qtbz8YXrr879fdPM6bn/r83z89mVy3J/Vwd8/M4Z/YxqR53Zp11VWTtjOmtnTJ/wfaHbyZ+uuXbS8ZzZjsdmZd2setbNmlxp2aGqfKSxgY80jn+hfPqa0+P22mz8xbobztnf48vO76VmmibBRJLOUJjPXL3sondYgiDgtdm4fc7k9SVFSeLhxfMmPeexpQvOGBPYFYXVDXXcMUV7giBQ4HLy0KJ5k34PWeXvW2fPOO/x5zsdPHrGWMZ+b1Vkbpo5fdy6OvMYp8XCLY0N3DLmN5z8FfTBwcU8Hy7lmXKx50513oV+finjuFxtvh/zdz7nnut7URSwW7NkbUUWEQVyEQYBKPS5xrVhmiY/fX03vUMR5jeU4bJbRvQUIZ7KYLeqqPLEd+2FjgsT4sk0HqfttBjmSP/hWBJZyurvCQJct7COmtK8ce3GtQwvnDrMrv5OTNOkKa+Ej1TNwKWoHwQ5ApP+8PfQzGFM08CmTieW2k08vReb0kCh+1OIUj7R5FaC8WcxTQ1Z8gMG/ZEfIYoWClyfQJGWI4s+XNblxFI7iKRaEbHgsiwj4LwLVRrPUZDFAOW+v6Iv+l1iqT2IggVVmrrO11QQEJnnW822wefJGCniegTTNCizjaTUmlBoreLg8EbiWogCayUBSykL/Gt5q+9/UEQVq+RCM1LUubIvtrgeYU/wddxKPofDm1nkvxlJkFjgW8Oe4BvEtRChzAA2yUmhtRLDNFDFrWwffAGXHOB4ZCeLAutGdrMCDtnDDPdyNCPNpv6fsbLg43iU/F9bMumFwDRNuruGsdlUfP7JC2NeLHTd4NiRbjRNp7wigMd76foe7ycyuk77cIi0pvPdrbso9bhZfJbadx/iQ3yID5HRdJo7B1k4o4Ku/jAgYLWM8IkFcqG2sdhy4BT3r1nAwpkV/GrbUdKZLOk/3+cklkjT0j1EVbEfTTeQRAG7VUUAFEUiHEuRSmtIooAyxsAaL6mcNYBK870cbe1j0cwKVEUio+m4HFbKCrwcbull2ewqnHYLybSGRRlfAPlb+7dwMjTE1SVVCMCWnjaODQ/w54uuv+Q5uwzK4SLV+d8653EB510EnHed9RhJdFHgegRcj5xHvwIWpZJy39ldlKOwSU5me1fmMt8ClhJme68FoNKRVYLtSpzAJjm5puA+PGp+rp9lebdzNLydUKYfvyXreSmxTePawvvpiB8hpg2TZynDItoRZIHVRY+iGxkG050s8K+l1jUPEKj7/+y9d5gdZ332/3lm5szpbXvvq9WqrXqXXOQmbMA2BkzvgfALISFveElC6ptC3pfABQQCgYRAKLENuODeq2x1q3dpe989e3qbmef3x1ntarVFu7Yky8b3ddmX9kx7zpyZZ+75lvv2rkBT7PSlzuDXC1nmuQH3qLDlpqI7OR3bS8qMszr/ZqrduTB1qbMBn16AIhSa/euxKTqGnLrd8q0I07S49+4dzJtfyvVbpw6Bv1ZYpsWh/R089/QRbr1jJdfesOii7v/1wjQtLNNCs1347Q0gnErz1QefJJRMUuh28web11LgeXOTwTcznth7nJqiPBrLCy688tt4G28QBIJTXUP84N5t9IdirGyupMA/80vqqgVVPLztMHuPdxFLpAl4c2UCNaV53LhuPj95cAcBrxObprJl1TyWzstlSRbVlfHLx3fzvV+9yILaErasamQonOCZ3SfYf6Kbjr4R/vO321mzqIYV8yu4aX0zP3t4J9+++3kcukZFUYA7rm1h9cIqTnYO8G+/eQmHbsOha9y0rpmm6vEGpANDvfzVqi3U+3P1ketLq/mLVx4b6459XefsAi3Zb4w999t4G6MwDJMffOfJS0KcADIZgx9850kWLCrn2hsWXTEkQ0rJiaM9tLUOcs11C2f0OjsLwzRpC41gWhK/00GB2zXnovBLgWQmm+tU83rwOqb24TKtFKZMYlP8E2Q4rgRkTZNkJovXYZ/T9fHVnz7K5kW13LD8tRnmvo23cTnwv7/zANetbqKhsgBFCAqDHpz2XJlI71AUn9uB2zleEC+lJJHK0j8cRQJ+jwNLSvK8LlRVIWuY9A1HSaWzaKpKUZ4HlyO3fdYwGQjFSKSz+Fx2CgIe0lmDvqEomTHdPkGez0W+341lScKxJKFoAkuCz53bRhGCRCpDfyiGYZg47DYKAx7s+ngs6P/seppryutYWlAGSA4O9fHb1iP8+YprEOQanRzajJ36097sV1Rx+Nt4G5C7MU+f7KejbQi3x45pjBd3J+JpThzrJTQco6DQS+P8nFHuof0d1DcW4/O7kFLS0TZENmtSW19EMpHhxLEeRkJxCot8NM4vxTYaxRmX0pyI8EiC40d7iMdSlJQFaZhXjKapHDnYhdNlo6d7BNO0aGouo6DQS3dniOHhGNFIkvKKPPp6wwSCbubNL8WyJK2n++loH8LhsNHYVEowz014JEFfT5isYTLYH8EfcLFwSSW6rnHoQCfPP32Enu4QliXJL/CwaEklDuf05quaqlJfMPfus0sNp26joXD6cUkk0cxBRlK7qPR9HFVcHAfzi4Ujnf382+Ov8K1PvBN9zsa7VwYRfxtvYya4HDq1Zeffo4LSAt+kdYUQuJ06teVT39M2TR0rLJ9qWVnhRMsZp91GTdnUXaqKIgj6XAR9rknLXA6dmtLpu1tdmo2/2fEkTYECJHBiZJBaXx5/u/MpkJJyj58vtsxcTD4d3iZOb+OKQ2f7MD/+wTM0zCvJ6eYc6qR5UTnZrMnTjx/k9Kl+SkoD7HjlFMu6R7hqywKefeowgwNRrrtpMUbW5MH7dlNbV0RFZR5PPLKPzo5hior9vLLtBGvXN3LVlqkLlAHi8TT33bODSCRJfoGXF549yo03t7B6XQMPP7CHWCzN/IVlDPRFeHVXKx/+5CZe2XaCo4e6sDtsRMJJ6hqKOX2ily//5bsZ6A/zy5++RH1DMfF4mr27WrnzI+vp7BjmB99+guaF5eQVeHj8kf0kExnWb27CNCxSyQzZjIlhmJiG9aYI/0pp0h9/lJH0TkAhz7GWPOdVKEInZXbTG7uftNmLT19CsecWVOGgJ/pr+hMPkzJ6iWWP49JqqfB9AMOKMpzcRonnVjTFTTi1h1j2BOXe99MZ+Rl2rZhwag+gUOJ5N25b4yWLGM5kzDrTNq19w3zz3uexpOSW1QuYV16AJSW/3X6YxvJCth1upTcU5fpljaydX00ma/DwrmMcaO2h0O/m5lXNFPrd3P3Cfm5dt4jjXQMcauvltvWLONye69RcUlvGI7uOcqitF92msXFBDaubKlEVhbb+ER7YfohYMs2KhgquW5brfuwairDjWDt+t4NtR9qoLgryng2LcTumJ+a/Szg/EyMn/H+iS4IQAoU3r4CpGBVjfat712hMAAAgAElEQVRhXXEVLfmlTE6cjVon6VNHv2eDy0qcpJSkzBBJY2DSMoeWh1MteNNefK8XaTNCwhhAVzw4tYKLYhA8HXI2AEOkjCFUxYHHVooqrpwJ88Vnj1JZXcCHPrGJTMbg2OGcynY0kuSl549x3U2LKa/MR9MUHn3wVbbcuJhNV8/nwXv3cNW1C4hGk3S0DXHLrSsYGUmw4+VT3HBzCyWlARDw8AN7pyVOUkp6u0OcPtnP5754PYVFPrZvO8kDv97FitV1gKC2vojb37eGSDjBt7/+CK2nBzBNi8amEpavrOO/fvgs77p9Bd/82kMMD8X47W/2UFaex9KVNUQjKe7++TY62obGVKPf/d5VFJf4cbnt7N11hvWbm1i8tIqerhBOdz/Xb12C7WK6AV9CxDJH6I7dTU3gDwALKU0UoZK1hmkL/wCvvoA8xzq6Y7/CkDGqfB+nwLUFS2aIpF+lxv/7qIoXTQmQyLYRTu+l2P0OwE3S6CKS3ke59/0Mp7ahYKPc9yFimcO0hr9PY/DPsGsTpRcsKekejqBrKuFEClVVKPF7cOq5LqJQPMlgJA5Akd+D3+VASsgYBr0j0ZzieSI14UEZTqToj8QQQIHXjd/lmHLeMgyLg229fPja5bT2hvjho9v5X7dvpsDv4WBbH88dOM3t6xezsrECvzsXZfvNtoMcaOvl9nWLONE9yHcf3Mbn3rGO073D9IWivHjoDGd6h9mwoIZ9p3toqihk94kOXjh4mo9et5JEOoPboaMIQfdwhB888grXLKmj0O/hl8/uxbAs3rFyPpFEiv96chfv39zCresWYlryovqDvVkhpSRlpYlkI/Snh2iLd9Ca6GAoPUw4GyFlpjHkRG25WncVn6z90BumyP168dVP3TAhxfVWQYXHz56BLmLZzNiLj0O1cUf96y/JuLzECYtT0YfYO/jdScsWBT/GkvxPo/La1cHfrDBllmPhX3E49HMKHItZU/SneG2zV82eOyQnwvexf/hH5NsXsKnk7/DqV0731fBwjPKKvNF0GhQV50K72axJe+sgu3ee4ejhbgAWLqkEJItbqrjvnp0cP9pNZ/swFZX5lFUE6ekK0d42yK5XTuF06WPbSDm9bcdIKIHdYcPrdaJpKqXlQSKRJJmMgRBQWOjFZlNxOnUcDp1kMoOqKthsKg6nDd1uw+XSUTUFwzBzKTqnjUQiZ0lTU1eEL+AiGk5SVOzH43GgaSoej4NUMguMjk2Mvw2+WV4oVMWHIuxE0q+S51iPxz4fIVRSRjeR9AE04SVrDmPKBEOJZ6j0fgybEsCm+lEVN3atFFW5cKpOoJHn3EzQsRqXVk0ouZ2M2T+JOGUNk6/e9RjVBQHsNo3+cJwVdeV8YMNShmJxfvjkdgwrlwq22zQ+dc0q8r0unth/gif2n6DI7yGWzhBJpgAIxZP8+5PbR42lc/ZDH796JSWByeKvqqqwYUENq+dV0VBawMvH2ukJRSnw5wQYl9WXsXFhzdhvmzVMntl/it+7aQ0rGiuoK81n98lOuofDFAfc9IWjdA6GqS3JYzASZyAS45r8ejKGiWFJDrX1sq65hpqiIIoiON41QPtAiJM9Q7T1j5DKmmw73Mo7VuZkFUqCXrYsbaQkeGEF9N8FRLMx9oUPcTh8jGPRk/Sm+phNnDduJC66YfflhMf12iMvVzL+ec9zlLq9lLq8Ywnz8/0yXysuK3ESKJQ4V9CS95lc5Mkcoju+HUMmLucwrjhIaRDLdpO1EiSMPrJWfE7bmzJLb2IXmnBQ7JpeA+fNAn/AxeBABMMwyWZNQsO586FpCqXlQba+cynzmnJ+gZIcqdDtGi3Lq9mzq5Uzp/p593tWjpIZjbKyILfctpzauqKxEPxZHjLVtOj1OUmlssTjaZwunb6eEXx+J3a7hpQwMBDFNCzS6SypZBbnaN3R2ZvzfIpTVOyjpq6QW25bkTP+tCS6XeNIpAt1VIdkKiiKwDBMLFNiqfINI1BPP3+E+x9+FWO01qyyPMiXv7gVZYo2ZadWQX3wTwglt3Nm5F8JOtdS7r0TS2ZQ0PDojajCi9vWhKZc6IE9cf+WzIz9YAJljGAJoYJQkEztg5bKGiyoKObm5fPZdaqLe3ce5I61i3nqwElUReELWzcAkm8/so2nD57iXSubeXz/cW5Z0cyGeTU8uu8YZ/pyiu/PHjpNJmvyqS2rkFLynUe38fLxNm5dtXDSbyMAp567NnJirmKCGGuhf6KCddowSWcNPKPXk6Yq6JqKlFAc8HKsYwCX3UZNcZDu4QjD0QQlQS8uu85nt65hx/EOvnnv89ywfB5bV84nmc7itus0lBVgU1UaygooPKdbyuu043gLRhrmAiklaSvDgfBhHu19mrZ4B3Hz0j6P4kaCh3ueHLOBOQtFKKzJW0HtG2zE+1bBvEABRU4Pq4sr0EctWKbysHstuOx3Tb69mXx77o0nbUV5rOOzRLKtl3sYVxRU4aDBdwsClSLnYny2qjltH820s2fwXwnodW8J4rTxqvn84DtPcNfPtqFpKiMjuYnM53OyftM8HnlgLyebeslmTYqKfWNpt5VrG/jW/30Yh8PGoiWVCCEI5rtZuaae3967h4Z5xWQzJqVlATZePZ+e7hFOHOuhq3MYoQi8XieNzaWUVQSpring1//zCoXFfo4c7ORdt69EURSklBw+2Mm9v9rBQF+EYL6b6toCTp2cXsH+3e9Zxc9+/AKZjInLpSMUweZrLiziWFoW5IVnjvLwA3spr8xjydKqGYvDLxUGh2IcOtpNdlSrJZ3JwjRNvYYVxqYEKPXehte+iLbwDyhwbsGmBrGpQXS1GJ99EaaVi+CcdZBX0DGsKIYVBSSKsKMKO6ZMkDYHkZhEMvvHyJFFlmj6IEHHOhLZ1pw+3DREzO9y0FhagMdhp8DnImuYZAyT9sERmsoL8Tlzb9zzSgtoGwyNpedqC/NwO3RqC/PwOu1ICaf7hth9pou+e3NmoZaU2G1TT6OmJTnS0cfGhTV0D0dIZY2xlNzZ734u3HYbtcV57DjeQXHQS8fACIl0lpKgF0UInjlwinXzq6kqDPLbHYcJelx4nXaGogmKAh7eu3EJlQV+ntp3ik0LaynJ82HTVKoLA5Tn+0mks9i0c33afrdL1y0p6U31cV/Xw7w8tGtSCu5SQSBoT3SyK/TqpGXDmRCfrv0IdvXKKZ14vYim0hzs7CORztBQnE91wWRR4kuBpJHl3tMHearz5Ni95tPtfH399CLZs8XljTiJie/k4qJ6RL95IYSgyLmUIufSOW8rpSScaSNpDOLXay/B6C4/qmsL+PjvXU3bmUECQRfLVtTg8jiw6Rpb37mM40d76O0ZQdc16ueVALlzWFLq5/0fXofH40AdfUDY7TZuuW05x450098XwR7UqGssBiCbMUgmMmy6OkdiotEkpmERDLq54wNrOXygk2g0ye3vW8P8hTn9LlURrFpTT2Gxj/x8LwsWVxAIulm+sjbXAZLn5uZbl6PZVN552woKinx4PA4+8dmrOX2yH8uyKC0P4vbYKRuNnp0lQ/MX5Dr0zn6fec2lvO9D6+jpDqHr2pRCdFca4tmTdEfvQWIBgjznBnQ1HyEUit3vpCf2a3piv0IIG0WuG7Fr1+S6dPR6ZMLiROhr+PSFlHpux6GV47LVcWbk22iKD4HKWUNmgULa7OdU6OtkzGHynBuwn+cucBaKEBNkGSS539FltzEcGzeBDsWT+JwONEXBpqgkMzn1/1Q2i2HmCJvTbmNtYxV/uHXDGOuwqcqUEQJVEUgJ337gRYZjSVY1VlBZMN5tdP4WQgg+cPVSfvLUbg62Pg1CsHFhLeX5fgzTYiiSoKm8kPJ8H12DYa5pqUcIwcHWXh7bc3wscrmuuRq3Q2d+RSFXLa7jx0/syqmk6xrvXLOAZXXOaUaQw8nDXbz0xCGuu3U55dWz06CSUnJ4TxtP3r8XkPgCbra+bxUlFVemp58lLY5HT3FXx30ci558TcX/rxUO1c4S/wL2jRwkex5Ze3XkIFEjil298rpjXyu6QxH++cFnaR0M8cUbNvCJza/N1meuGMkk+WLLBpYXjjttXKwZ9Hc7TvsWgMQglD5B2oq80UO5aBBC0NRcRlNz2aRlTpdOy/JqWqievMyps27jZOsMl9vOspWTSWVVTQFVNVM/GPwBF+s2TWHDIQT+gGtSxKi2flx4bfmq3LFyxeTjy89dB3KkLi9/PF1TVpFH2TkPGrvdxuKlVSxeOrsIpJSSZCqLYZhomorrDYhO+ewtOLUaJCZCqNhGa54AitxbyXNuwJIZBOqECJFTq6Ep768xZRJV2EeXKdT6P49hxUAIVOFEyhyBEUKjwLWFgH0lILCpPpQ5NDgoQnDVgjp++NR2Ht6bG8fBjj4+f8NaHDaNxdUl3L/zEKF4kheOthJNZRACrlvUwL889AIP7z1KacBLKJ5kUWUxNUWTCcKX77gaTVVJprNIJD6XY1TOQPKFd21A1yYX/DeWFfC/77iaZCaLpih4XQ50TaW+NI/vfO7d+FwOVEXha594B85Rc+S186tYWF2MZUlsmorXacemqdg0ldvWLWJLSyOGaaKpuf2dPc5X79yC1zm5nqy3M8QLjx5gxYZ5syZOAIECL/XNpRza08bebftZt2XBFUmcLGlxLHqK7538D4YyoctKmiCXkmvw1lHkKKQr2TNhWcyIszu0nxtLrrlkx4+m0qRNk3yX8y2dEvTY7Hz91RcI6k5soy9OXt3O/7vcESeJxJJZopkOItkOksYwlsyiKjoONYhfr8Vnq7zkAnZSStJmiOH0CeJGD4aVGn3DPR+CgF5HmXvNlPtJGIMMp4+RNAYwZQab4sFnqyTPPg9Vmb5gzpIG7bFnyZgRSl1r8OrlmDJDONNKKH2SrBVHFTpOrYCAXo9bK5p0TtJmhNPRR8YeBGfh0gopc61DVyfWP5wLw0oSyXSQMPuJZDrojL8ISCKZNg6HfjFp/ULHEgock2swxk+TIGslGEodIZbtxpBJVOHAaysn39GMTZmooZG1EnTFt2HKDDWeLaTMED2JXUgMChwLCdobkBJGMicZTB0GBAWOhQT0mlw9ytu4JEgmM/z0rldo7xyioa6IT35oeqPTSwVF6JMKtMeXaejq1A9SIRRsqh8bEzVeVOFCVSZruCBBwYZdK5q87NztFYUtixoo9OVqewq8brYsakBTVVqqS/ncdWt5/sgZEPC569ewoKIYKSUf2riMJ/af4GBHL5uba1lYUYQiFOaVFfK/3rmZZw+dpnMoTFVhYEryAeB35yI7k1v8BX7X1NsIIfC5HPjOW66pKvm+8fqkPO/4OckpJ0/dVGPTVPKn0MCxaSoBj3OKLV4bhBCUV+dTXp2PP9/Dkb3tF23fFxNSSk7H2/iPMz9jMDP8ho2j3FFCubNkEnEC2BPax5aizWjKpZkrHz92kiN9/XzluqvQ3sLE6QONLdxeN9ENQrtIgsBzIk79yX0cG7mHkcxpUsYwWSuOxMq9WQoXLlsRDb530uB7J6qYukX39UJKSX9qH/uHfkg4007WimJJA4k1gTzlDH1VGnw3TyBOUubIX2fiRY6G7iaSbSdrxbCkiSp0HFoepc5VLAh+EK+tcsrvcLYLbiR9Crvqx676ODD8EzrjL5Aw+jFlGiE0dMVDnW8rS/M+O6ndP22GeXXw+5gyVy+SG7uk0LGEfMeCGYlTX3Ivewb/lbQZIWNFMWWuWyuUOcGewVOT1l+S/2kKHAuYKlAphEIi28++oX+nL/kqaTOMJbMoQsWuBilxrmBx3ifw2irGzkXGinE8/GsSxiBurYijI3fTk9iJhUme3sDKwi+hCJWX+/6BSLYDkATsjawq+CMKHFeOOvdrwe3vX43He2UJNJ5FJJbiocf2EYmmSKWyb/RwLikUYZsVCddUhTvWLh77uyTgnfD3oqoSFlWVTNhGCEGhz80HN06dOm8sKaCx5PLbqJw1UjUME1XJdWyqqjKm1oyUaDZtrGhfSollWpimhZS5ZoPz7XuklFiWxDRMpMx1Ap5/TNOwctEsfXxby5IYWRNFFWhTRM5m+g6MfgfLyjU8qKqCMk2682JCSkkoO8K9XQ/Rney94PoKCooQo52tAgWFlJW+KGPRVZ1GTz27Q/swz+vI60sN0J8eoMxZMs3Wb2M2OGu1ci7+8/AuGqf4fK6YE3EaSZ+mM/4SdtWHT6/CpRVhU9ykzTDhzBlG0qfZO/h9QGGe/1bERc8ESobSh3mp929JGAPkO5qo9tyJQ80nYfTRFnuaUPokqrDTFLidctcGfHrNeXswOTpyFwdCP8G0Uvj1OoocS7GpLpLGICOZ05yI3M9g6hAbS/6GgL1+2tEYVoq40cfuwW/RFnsGt1ZKoXMxIMhacRLGAF6tfEpNJpdWyNVl/5e0OULaDNMafZL+1ORiwang0oqp8V6PRGJaadpjzxDJthPQ66j2Xjdp/WLncqbL7qbNEXYPfptotjNXXO7M+epFsx2E0sc5HX2ElBlic+k/YBMT31wzZoQDwz/BIkuFexMDqf0Mpo9wMPRTMmYETXFR5bma/uR+hlKHOB7+DXmOJlTevIWP1bVXrlbLkWM9RKKpN3oYlwXzC/4Bwe+e7lDnmQG+87f3sWRVHS8+fpDqhmJueM8K7v7hc0RGEnzySzey+qr5SEvSfrqfh+7awYEdpzGyJgWlAW79yHqWrq3H7shFqBKxNPf/bBsvPHoAy5I0LiynpCI4lrwysiY//95THNrdxt/+28dweXKR+J72Ib751V+z9toF3PHJTbMev2lYvPLMER65eyd93SE0TWHJ6jpu+9hGSisvbVpPInm6/0X2hg5Mm55TUciz51HlqmC+t4FqVwUljiI8Ng8jmTBf2veXF208C3zzUIWGeZ73aNSI0xrvmBVxsqTkaN8AJT4v7cMjpAyD+oI8CtwuDvf1U+73EXA6SWQynBkO0VhQMLbdwZ4+kpksZX4fVUE/yazBiYFBmouL0DWVrGlyvH+QyqAfn+PKfFk8H/FsBgG4bDoj6STmOQJsEsnTXaf4ePOK113rNCdmU+25GsNKkOdoIqg3YFcDCCGwpMFw+jg7+r/OUPowbdEnqfXegF2dLNf+emBaGc5EHydh9JFnb2Jt0Z8R0OvHOnNKXCt5ue8fCWdaUYROoXMxipj4FQdSBzkU+jlZK0aD790sDH4Yj60MRagYVoq+5B72DP4rocwJ9g3/iHVFf46uTt2tY5HlVORBslaclrxPU+ZeP6q/JEibI4QzZ0ajVpOJk6Y4KHWtGvs7lu2aNXEK2usJjhK6tBkmlDlBJNuOX69jSd4nZ3k2c4hmO9GEi6X5n6HWexN2NVe8mjQHOTD8Y46Hf0NvYidDqaOUuJZP2DZthTFkkvXFX8Vrq+BY+NfsHfwe3fFtBOz1XFX6NTy2Eo6P3M/2ga/Rn3wVSxpXlNjmWwl79rW90UO4bFDE757eG4ymmo70UNNYwtb3ruI3P3mJ8HCM629bwctPHea3v3iFZesaSCUz/OCfHsI0Ld736atwuHWOvNrBD/7pQT77lZtZddV8FEXw1AN7eeTuHdx0xyrqF5TRdrKfFx87gJEdLyEwDGu0o1JOGEc2Y2KZc9Mv2vPySX78zcdYvbmJm+9czchwnIfv2kEk9Dh/9H9ux+G6dHNDX2qAp/temJY0uVQn1xZtYmVwKbWeanRl4jUWU+YmE3MhlDlLcKnOSbIEKTNFT6oPS1ooFyh7MUyLbz3/Mk2FBahqTu5C11Ty3S6+/fzLfHz1ctbVVNETifLt517m72++HoCDPX24dZ1kJktvNMZXrtuMW9f51vMv8ydXb2BhaTFd4QjfePYl/vqmay9InCwpOdjZy57WboZjCVx2nYbiPNbWV+VsrWYRTTQtizMDIXa3dtE7EsW0LPK9LhZVlLC4onhWdkd3ndiHIhQ+3ryC/7f3efoSsQnLO2PhC+5jNpgTcbKrQZqDd04iI4rQyLc30+C/haH+I4QyJ8bSRxcTKSvMSPo0EkmhcwkBvXa8Wl4I8uxN5NmbGMmcYiR9iowVw6GOd7GYMsOxkV+TtkYocCxkcd7HcWslY/vQFAdlrrVkglF2DHyd3sRuuhPbqfZsmfaHD2daWVHwhzQF3jNhMndq+Ti1N0NnhKDOdxMN/ndPqGVyaYU0Bz5IW+xp0maYvuTuScQJoNCxGK+tAkVolLpWc0D5MWlzhEr3ZtxaESAoca1AoJAwBjGt1KSaqbfx+pFMZdl/qOuNHsbbuAyQwMYbFlJZV8iuF48TyPOw5V3LyGYMHv/NLmKRJPu2n6a7fYgv/M2tLF/fgBCCJavq6G4b5JF7drJoZS2ZtMHzjx5g8apa3vvpzeh2Gys2NjLcH2H7s0cv+rhjkSSP/WoXFdUFfPSL1+Nw6khLoqoKv/y3pznyajvL1jdc9ONCriD82YGXCGenbqIpcRTzoar3sCSwAF25PC92NsVGubOMkezEh7mFRX96kLSVwanOLtITcDm4c9mS0Q7SC5MUj93Op9auQFc1vv70izx+7CQfX72clZXlvHSmnXlFBRzs6aPE56XQ4552P1JKRhIp/vulPdy3+zChRBLLkqiKgt2msrC8mDvXtmCbQZVeSoikUvzw2R08uv84I/EkhiXJyZII3HadVXWV/MnWTZQGctIc0+Gm6nFD7dPhYf569Zax3n2J5K+2P3HBczMbzIk45UxRp95ECJGLroymqSx58WssLGnk6odQ0BXPpEhOrovHDQgMmUKe1+oZybQRSh8HBOXujbi0wikIkaDI2UJAr6M/tY/exG4q3BvRpjEe9doqqfZeO4lMvlmgKz7KXOvQxORCUbvqxWerYsDcT2IKmxxF2HLnkNzv4FTzUUavj1yKM3ez5LqknBhWiqyV5M0R9H1z4eSpPkbCv9tCsr8rcLntOF12bDYNh1OnsNSPEIwREcOwOPxqO4Ulfiprx+c4p0tn0coa7vr350insgz1hYmMxNl0wyJso0KYNptGw8Iydr1w/KKPe7AvQm/nMHmFXp757b6xz7vaBkkmM3S3D10y4tSXHuBA+DDWFE1E+XoeH6+5k8X+BTM+lC82BIIqVxmHIkcmLRtKD5M0U7MiTgJoLi7EdU6DgHWe154lJ35W4ffh0e1oqkJVnp/ucBQBXN1Qyw9f3kVXOMIrrR2sq6nEPkOkx7QkP35hFz95cQ9IWFFbTnNZLtXXHYqw83QnX3/4edLG1OK0AKF4gm88+iL37zlMgdfF1c31VOX7EULQMTzC7jNdPH7wOKF4gr+6dQs1BcFpAxmlrvHs0M0182kKTCytWJBXPO045oK5ddVJCVikzBCDqcOEM2dImSNkrTimTBHPDowVaE/d5fb6YBNO7KoPiZkrwrbSKEIfS9UZMknSHAQkDjUwyWU9nu0lY0WwKS68tvIpyY4QAqdWgHO0WydmdJGxYmjT2EAE7HWjpOPNWfDsUIPTEEgAgTraSj5VBFFBxaa4xrY9W8slGCWwo7vMCe3llllcGpE5KSWmmXtLyR1TjBW6ni2AbW0fZO/+DlrbB4nEUqiKoCDfS0NdESuXVhMMuGelzn12f+cagQohUJTXZvQ51/2dXU/K3L8N0+LA4S4SycyEdYwZJqtxCFR1ruPO+cGcLVZOJjPsO9TJkWPd9A9ESaYy2O02/F4HdTVFLGwuo7wsiPoaz8/Z7yMlpFJZjpzo4cixHrp7R4jH07lONK+DivIgyxZXUV2ZP2rXM/tjSSkxLclZU7pzz//Z36enL8y+Ax2cbhtgOBTHsiQet538PA9NjSUsai7H63FccoV3RRETNL2Us2/zYx9JUokMmk1Fs53zpi8EDqdOOpXBsiTZUVV6u9M2Ybx2h37B6ezstTcXGBmDbMagp2OYFx8/OGFZ0+JKggXTN8S8Hkgp6Yh30Z8anHL5lqLNLPLPv6ykCXLEqdAxdZNB1IhNSuHNBG2KlJ5NUckYJlJKYuk00fT4/oYTSUxpoUjBUDyBz2FHCEFl0I/XrrOno5ueSJTm4sIZz8uJ3kF+vfMghmnxjpYmvnTTJop9HoSAZCbLy6fa+atfP8FIIjVl1MkwLR7Zf5zHDhynLODlS1s3sXFezRgJTGazvHS8jb9/4Bn2tHZz/57DfH7LuimlPGDifffhpsli0J9ZsOqiPKlnTZyklMSMbg6HfkF77OmxlntVcaKS63C5FOm5c2FX/ZS61tCT2EVX/GVOOx6nzLUaVegYMkVn/EX6knvRFQ9lrjWj0adxZKw4hkyjCQe6Mv1NKoSKXfWSq1WKzPi9dMWHeJNGmyCXnpwxdTbjVaacRz7HCdSoX/jFGOKsICV89o9/SnfPCELA5g1N/OkXbgTg+Mk+fnX/Ll7afpJs1sS0rDHTVkXJiSN6PXbeuXUpN123iNJi/4wPvmzW5Ic/fYGHH9+PZUkQsLylmr/801tw2Odee5NIZvjGdx9n2/bxjsgtVzXzJ39ww3nfUTIwGGVgKEZXT4hTZwY40zbI6TP9jISTuc6qUbx6oIN33vmdCx67vDTAd//lw3My+bRpOQ/BcCTJk88d4f6H9tLbF8Ywc91XZ6EIgaIKdJvG+jX13HrzMprnlc6pCwtyHVx9AxFe2Hac+x7ay8BQDNO0sM75HYUARVHQbSoNdUW899ZVrGipwu22z4rESAl/9JVfcurMAAhYv7qer/zxO1CE4EzbIPc+tJdnnj9KOpPFNMdJ7lmSpKkKBflebrpuITffsISC/DfW/624PEDr8V7i0RR5hblaU8uyGOgJk1/oQ9MU3B4Huq4x1B9BSjl2nsLD8QmkSFEUjKw5weg4lciQiM2tEcHldeD2OmhaXMEnvnTTpOVzvS5mC1OatCamtlIpcxSzpXgT6hskk1KgT13OEc3GyFivPWsjgAUlRTx0+BihZJJXu3qIZ8aJU08kyl17DmLqqhEAACAASURBVKAIwcGePr68ZTMAHl1nU30NP3x5Fy3lJVTnTa/yLaXkgb1HCCdTFHrd/P61aynxe8auI5ddZ9O8Wu5YtZj/eG7nlNsPxxPct/sQqazBHasXc/3CxglWTi5dZ8uCBradbOfu7fu5f89hPrphOXme11buUe7xX3ilWWDWs2XM6GbXwDdzXXWKjxrvjRQ5luDU8tEVL6qwM5Q+wiv9X2NqB7DXDyEUarzXM5w+yunIo+wa+Ab5jvnoipe0GWE4fRSJZH7gfVS4N08xYY6+UZ51UJ3uOIhzOnZm/i5CKG/SWFMOOYLz2rqTBDOfx8uNZCo7FnXp7hkhHEly5FgP3//xs7R3Tq3ZYlkSyzIZHknws7tf4cChTv7wc9dRO4Pwn65rLF1cySNPHCCRzJHq4yd7OXail5ZFlXMedyiUYOfu1rGxa6rCutWTuzmzhskvfrWDR588QPICcgOWJSdEoKZDMpWd8+3qcuoMDsX4r1+8xCNPHsScpkDYkhLLkBhGhiefPcLR47185mObuWrDvDlFZPYf6uQ/fvYCh490T/B6OxdSgmlaJEejbyfPDHDTlkV84D2rKSr0zup4qXOun56+MMOhOB2dw3z3R89wpnVgytN0NvKSsUy6e0f48c9forV9iE9/ZBPlZZfHWmIqrNw0j0fv2cW+7acpqypA1RSG+nK1S0vX1uN027E7dYrKAxzc1crwQJT8Ih/hUJz9O05jjvoSKqpCMN9Nf88IA71h3F4HhmGyb/spBnrnVmhbUOxn3qIKDu1po6d9iOrG4lxzkSUZ6Bkhv/jiNhOdRcbK0pGYuv5vRd5SXOrF07OaKzyaC4GYVLCeslIY1oWj86oiePfiZsoDk8/dncuX8NzJM4QSSa6f18DGuhrcuo2FJUX8xfVX0xWOMBCP8/mNa5hflJvvhBAsKC4iY5pc21g3o+5RIpPlcHc/UkJLVSkFXtek+8ymKiypLMFl18kYk79P13CEYz0DaIrCxnk1U/pfKopgcUUJd2/fz0AkTvdI5DUTp4uFWREnS5p0xl6gO74dXfHQkv8Z6nxb0cTEE5UwB6a8CC4mHGqARcFPkDAG6UvuIZrtQkoLXfVQ5b2WKvc1lLiWT4o2AWiKE1XoWDKDYSWn2HsOUlqjRrsSTXGN1e28jTcPhkfiPPvSMX513y66ekZyKViHDV3XcoraAuLxNKlUlnQmd0ObpsWe/e18+wdP8r+/uJXiIt+0D9zlS6qoKAty5HhOwG5wKMauvW0saCrDZpvb2+sru04Rjo5fj431xTTWTSHsKCEWS2FaEv28CJFpmLlU0yiEELMah82mzpn7WlLyi3u28+hTOdKkKAKH3YbdruF22ZFSEk9kSKWypNLjBK+zO8T3f/wsFWVB6munSw+fcxzLYs++dr71/ScnEN/zj2eaFolkhnTGIJ3OjqUPf/voq3T3hPjKH7+DYGDypD4TQqEEO3ad4Z77d9HWMQSAblOxnz2uUyeVNognc9fQWQNkKeG5l47jcup87pNX45llxOtio7aplK3vXcX9P9vGod1tuH0OTh3pwe2xs/X9q9HtGkIIbvvoRr7xF7/in//0Lqrqi+jtHEZRlLE0t6IIFiyrprDYx9e/cg/zFpUTGUkQGoyRXzT+sDZNi21PHCIaTnL41TbisRTPPbyP1hO9lFXnM7+lCt2ucfsnNtF2so+v/9k9VDcW43DqDPSGEULw5X9+H5r34kd+DGkwmB6a9Lmu6NS5a96waJMQAk1o6IqN9HlpuYyVxZIXLndRFYWtzZMdDoQQ5Lmc3LZkwaRl84tzdT/LKyc6M0gpMaXkxOAQxR4PyysmOzeci6FogmgyF3WsyvfjmMKzUQhBnsdF0OWgLxKbtPxY7wCmlFimyZfvemTaIvJocjzrMxC9uN2NrwWzYgSmTDOYPoxFFo8tpxWkKa5JqZhEtu+Sy9ebMsuxkbvpT75Kc+ADtOR96pxutpknKLdWil31E812EjN6sKQ5pcZSygyNFUN7tNIZxSivLFxe64ArGb19YX74X8+TSGbw+5ysW13PTVsW0lhfMmZFEo0leXnHaR558gAHD3eNRTP2Hezknvt38emPbsI5SfU5B4fDxs03LhkjTpYleXnnSW6+cTHFhdMTrvORSmd56rnx4lBVVVizso68oHvSPlRVYev1i1m6eHJU6/mXT7Bj9+mxdEpVRR7vu/XCnlBud65AdC44eqKHg4c7MQyLgnwPm9Y1cvXGJpoaSrHbc1NKJJZk77527n1wL4eOdo0Ri96+MHffu5M//vz1OGewhJFScvxUP9/90TMTSFN+npvN6+dx1YYmmptK0W05C5NINMXBI1088cxhdu1tJRZPYxgWO/ac4bs/eoYv/N61BPyzf0vtH4zw/f96lng8jaoIGuqL2XrdIlYuraG0JICi5mqf2juGeH7bCR56fD99/bmOLdO0eOLZw2xY28i6VXUXONLc4PY6WH/9Qrx+J5qusnhlLQUlufRDSXmQlZubsDt0bDaV9356M/OXVrHz+WOkEhk23biIq29uIVgwnk5ZvKqWr/zLnWx74hCJWJpr37mM5pZKHrlnJ4H83DU4b3EFX/rHO3j+kQOMDMeoby5j042L2P3iCUoqc1E1y7LYve0E2UxOiHP1VU1EwgkO7GolFk5S31yGrmsUlfr5i29+kG1PHebk4W5Mw6RpUQUta+pwui9NN5shTYYzI5M+99u8BPWZ0/KXGopQpiRulrSmLGS/lAglkjxw6Ch7Orp579JF6OrMhDKRzZIZ9XD0OhwT/CDPhV3TpjXCHozl0qeSHBGbCX5nrn5wjqV1lwSzIk65wskcI1bQ0IR9Amk6q8bdk9zJpX54x7KdtMefxakVUOW5OudPJZhVPY1Pr8RrqySSbacvuYcG3y3Y1Yk5TyklI5nThDNtqMJOnqNpyo6zKwcChRxxzFrJacng7xqyWZNs1sTl0vnw+9dy8w1LcDn1CZOk3+fihmsXsmhBOd/83uPs2pvTQTJNi6efP8rVG+ezqLlsyolVCMHKpdUUF3rpG4gCcKZtkBOn+ikunF3KQUrJsRO9dJ+T8sgLuGhZVDFlvYeqKqxYWg1T+PR194bZufvM2ItLQb6HW25qmdU45opEIjcXBPwu/vCz17F6RS1Ox8TaroDPxdUbm6ivLeKb33ucPftyFhxSwuFjPbR1DNHUWMp0zyzDtLjnvp2cbh3v5vR5HXzhs1tYu7L+vOMJAn4XG9Y0sHhBOb99dD///T8vkxqNPm3bfpLFC8q55aaWWZNEw7CIxdIoQrBmZR2f+simyVEyIaitLqSyPI+aqnz+6ZuPkBxN9aXTBk8/f4S1K2sv2oNZCEFBsZ/P/dktY5+9+yPrx/69YFk1C5aNXxs2XWP5+gaWz9CppiiC5pYqmlsm+iF+8k/Ga5CEENQ3l1F/nndkxTlisDabxh/93e0Tllsyw1DsJwRd16GNdocJIfAGXNz4npXc+J7ZfGuwrCS94b/HtCLkeT6KS185x8J/a0rFb6fqmHW7/6XEdM+uy1kjCrkSgTKflwUrl7KkrOSiXbeKmL4p5GwtnU1V+Lv3XD9jBx/kQiPzy954EeJZzSKq0HDbciqmKTPEcPo4Up4NTUuyVozjkXvpTey6dCMdxdnjJo0BTkUepD+5l+HUsbH/QumTOb81KzUp+qUJJ43+W7EpLrrjr3Ay8iBpMzq2T0saRLMdHAr9N0lzkIBeR6V70yX33ns9UIWOW8u1WMaN7lyd11iIV452I13eN5crCZvWNXLbzctxu6ZOmSiKoLw0wBc/dz35eePp3eFQnCeePTRj51BenofNG5rGHv6GYfHQY/snpMxmgmlKXtl5mug5abq6mkIWzp85RH4lwK5rfPbjV7FxbcMk0nQWQggqy4N87APrcZyzTk/fCB3dIWZ6ydp3oIMXtp0Y+9tht/GZj21m07p5Mx7P73Px/ttW8a53tIz9Lolkhnsf3MPAQGTOnWDVVfn8f5+5dsbUoqaprF1Zxzuun+iLtXd/O5nMbDob36qwMMxe4PWdAyHsFPq+gBA6GaNjzttLJMYUhdaa0NDe4MYeKS0MObn2R1O0y97l53M4uGF+I6urK6ZMu50Pp00bi0rF0ulp5720YZDJTl2vlTfq5yiEoKmkgE1NNTP+t7GphgLv9LpSlwuzumoUoVPiXE5r9DHiRi97Br9HjXcLDjVIxorTn3yVrvhL5DsW0JfYg8XUhatpM5wTQZQpDCtFygyRlbnwXCTbTk9iBzbFhSYcaIoLl1Y4qePLp1dT7bmOoyN3cTz8G46HfzNhec6ctoJy9zqa/Hfg0oomiGSWu9fR6L+NYyO/Zt/QDxlOHSXPMR+b4iRpDNEVf5mh9GEcaj5L8j6Fx3bxH2KmlSFm9GBYCQyZxrCSRLO54sWMGaEvsYe4rXdU/8iBQw1OK6apCjtFzhbORB8jkmln18C3qHBvQFf9WDJL1opT7FxKkXNq3623Mmw2ldtuWX7BWh8hBKXFfm64dhG//NX2sc9f3nGKT314E37f1BFH3aayanktTz9/hKHhXN794JEuWtsHaaid2XwWYGAowoHDnWMTjiIE126ej/01dOZdbixdXMnaVXWTvM3OhxCChfPLKSvxc7o11w5uGBadXSFM05oyspbNmjz65MGx2jOAJYsqWL+mYVYRI01TeNfWpbz0yim6ekIAtLYPsX33Gd79jrndB7fevIyKWRR567rG8pZqHnvqELF4LroRj6fp6QvP2GjwVoYiHJQGXr9FiRAKqpKH8poj/wJVqFjnEZSceMkbl/eRUpK2MlN2z9kV/Q2rvZot8j1uvM6cXE3HUJhU1pgkEyAljCRShJNTd2A2lebkDixL8mp7D5X5gSnXu9IwK+IkhKDEtYr5gTs5FPopg6kDDKePogo7UhpIoNKzmYXBj/Bi718ykjk95X5ao49zZORupDSwMDClQcbMpSm64tvoT+5HESoKGnbVz7KC36fUtRoYTQdi0BPfwWDqEIrQUIRj1L5DABJLGljSJJw5QyTTSjzby4aSv0Iw/iASqCwKfhRd8XF05H9oiz1De/xZBAqWNBFCIag3sjj/k5S5176ukzsdItl2Xu77R9LmCBYmljTIWrHRZR3sGfxXVKEjhIYiNGq817E0/7NT7ksIQZl7LY3+Wzk6cjeDqYMMpg6hChsSiUBgK/j87yRxqqsppKxkdu2nmqbQsrBizCQXIBxOcuJUHyuX1Uy5jRCC5nkl1NcWMTR8BshFN5578Th11YVTdoichZSStvZhTp7uH/ssGHSzesXFrYm5FLDZVJYtqSLgn92DTFEEdTVFY8QJIBJJTpAuOBfdvSOcOjN+Xmw2leUtVeQFZ/emKYSgMN/LquU1dD0UGvv8mReO8q6tS6dND56PYMDFmln+HkII8vM8BAOuMeJkSUk4Mn0TyuuBJTP0h7+OTSsnntqBorjIc38Ip94CWESSjxJOPggIAq7b8DquRco0/ZFvoamlJNLbURQv+Z6P4rAtBCyiqacZSdyHQOBz3YLPsQUxg7WNlCYjifuIJp9CYuC2ryHofj+q4iGaep6h6H+iKj5K/H+GTSslaw4QTtyHYQ4hMbBrtcTTO8j3fBybWspw/GcowkMiswu71kCB9zOoSt6MaZ60cYpQ/BdkjA6c+hLyPB9GUyYSXUUIdEUna04kTlkrS3YWnWuXEoOZ4SnJm0dzY1Ou7Bcot91Gc1kRu1u7eLW9m6FYHK9jYjmEYZkc7uojkkpP2aFXmRdgXkkBR3sGeGT/MTbOqyHgcsyoXweXVidtNph1nNKmOFgU/AjFzmV0xV8iZvQgUHBphZS6VlPkaAEhqPfdQn9y/zRK1AEC+vSmuRMGpjiwiXMnSsmZyKPsHvw2uuJlXdGfU+ZeO6F7To6Kc54I38+h0M/ojL/AQOoQxeeQBiEEuuJjUfAjVHuuoSP+ApFMG4ZM4VADFDgWUuZah654p601V4RKsXMZdiVAnn3emLjjbKEKO369hqx1YaVnATjVmd9YbYqLlvzfo8y9lu74K8SzPUghsSke/LZqylxrJu3Vr9dQ6b4an16Bpkz9AFSEjSJHC7pwk29vHvtcE3aKnEtxaUW4tXEjSgWVcvd6slYChzo+eanCToV7A4ZMX1a7lYbaQuz67CYfIQTlZQFKiwNEojnndMO0ZiROAF6Pgy2bm9mzrx3DMDFNi12vtnLTdQspL50+UmGaFs9vOz5BVuDazfPxed/4mosLwetxMK+hBGWGVuVzIQSTSFY8kZ42bdbaPsjg8HgHjsups3Rx1ZxSF3a7xoKmUh57+iDJZO4ct3cO09MXprx0dm+1zfNK8c7h93A4bBN0vKTMfc9LA0k09Qwu+2qK/H9INPUcg9F/pyL/G8RSLxCK30OR/49ASvoi3wQU3PY1RJKP43FcRZH/j4kkn2Ag+u9U5v0L8cxuQvG7KPL9EQB94a8j0PE5r512BBnjDEOxn1AW/HtU4SJrDaKMig577Btx6S2cGfgwlkyNno800eTTBD0fIpJ4BImJS19KNPUkftdtjCQeIN/zCYr9X2Yo+h8MxX5Cke+Ppz2+aQ0xGP0+bvs68twfZjj+MwYi36c08GcT1lOEis/mnaTjFDcTJKbQdrpckEhOx6b2lwzYfDgU+2Ue0dwghOBdy5p5YM8R+iNxvvfUK+cIYArS2Sy7Wru4e8eBKQu6hRDke1y8b/Vi/uXRF3n5ZDvffnwbH1jXQlV+ALumIqUkkckyFEvQNjRC0OVgYXnxm4c4Qa7Aq8i5hCLnkmnXWhD8IAuCH5xyWY33emq81891jECu/uho+G4yVpSFwQ9T471hypPn1oqp991Me+xpopkuIpnWCcQJzrJVgU+vYqH+oTmPRRX6tBGg2cCnV7Kh5K9e8/aTIcbIXLFzslrqpLWFoMZ7HTXe62Zcz6Y4acn/9KTP7ap/yu+vKnbWFf/5lOtvKPnrC47rYqNoVOhvtvD5nPh84w9Ky7Lo6ApNEAc8H0II1q6qIz/oGisSb20b5PjJPspKAtNuF09k2L57PDLr9TpYuazmgqmvKwFOh43iorlo7ghs54XwTcuaRhcpJ/J5NmoDuZTobMnO2BGFoLDAi9ftGCNOmYxBR+fQrPdVXhpEn4O0hKqI88iknFbj6mJAVQL4nDfgsDVhWQniqZeQMksivQuPYyNOW645wGNfRyK9A7d9JZqah895Iw7bPExrhER6BxKLeGobGaObodhPAUnG6CCdPYZ0XDPtNawq+ehqBaHYXXid1+J1bIbRl0ghFISc/NKiKE7c9jUkM/tx6UtRhItMugsw0dUKPI5NOGwNeJ03MhT70Yzf3zAHiad3Yskk8fR2skYnphVGSmtCXaomVPL0AD2pvgnbR7MxQpnwjPf3pYQlLY5FT0y5LF/PvyIK1y+EeSWF3L5yIf/90l4eP3CCwWiC+WWFOGwavSNR9rR2EXQ5sGsqveHopO01VeHGJfM4Mxji59te5de7DrC/o4e6ojw8dp2saRFLp+kLx2gdDPHRDctpLit6jcqDFw9vGoGirBUnksl15hQ6pidu42FPZbTb7srOE7+NSwef1zHrqAiAx+3A4x6frKTMqWNblkRVp59YfV4nW65ewC/uydVHJZIZnnvpOOtW10+rJP7KzlOERsbfdpsbS2mYhbbRlQBd16at+3q9MAxrzM7kLHw+J17P3B8iwYAbl2u8xT1rmPQPTp68p90+6Lqiiawi/n/2zjs8jvM6979vZnvBLrAAFr13kGBvYKdEkepUi61uucVxSexcx7Fvip2e2DdxHMe9xHGTZMkqVKUkUmyCxE6QYAVB9F4X2L47M/ePBVEIgAQpkCItvs+jgp32zezON2fOec/7mpDEOakUCVABBVULIsRotkII48i8KAkL0kiWXh7eBlTNh8U4jwTrRwFw2R5DJ1/Y10uWnKTF/yP+8D48/hcZCrxFivNryOJCQbV+RGA4Nsbh37sGiFG3ASH0aNqFSOUaGhF0Ujzx1gfQSa6Rcz2/VGCQ9KSbUzk2eGrc51EtyumhMyxOmIf+AiXJK4Va71nag10TPpeQSLOkYP4AhTmnC1kSfGL1IvSyxIuHTnC4qY2DDa3IkoRJr2NOVgpf3LCC77317qSBE4DTYuYL6ytJc9r5/b5jtPZ7ONPZi6KpCGKq/Ga9nkSblSzX1C+jVxPXTeAkDfN9FC2EL9ox9YoadAeq8UZakNDhNF77nJEbmHkIAUaj/oI8o/Ohk6UJGYZINEokolzwASpErHvv9bdq6OuPkcT3HjhLV/cgWRkTSf3BUISdVadHshF6vcz8udm4Eq4PvTBZkq4YgV1RVHz+8WKAFsvllSyMRt048rmiqAxdgk2IyaS/JibpC2Fiy7oes2E2Q8Ed2E2rAQ1/6ABxlg1wgZdIi2Ee/b5nEcKETnKhqH0IdBc8/6jai6oOYDEsxqDLoa3/r4ko7cjSucBJO++/5499PCLRNgLhI0iSDV+oCpO+ZMxSbTj400a2lqUEdFICijqIWV+BqvnQNGWierXQk23JRCd0EzrYDvQf4c60jSQaE6Y8zyuBoBJkR3cVkUmI4TadlTxr9jX/24NYZjfeauYL65ezpjSfQ41t9PsCWAx6ClMSWZKficWg57Y5JWQnxlOePnkwbjUaeHT5fDbMLuZwUxv13f34QmFkSSLeaiY70cmsDDcu66UJ2V4pXDeBkyyZSDJV0OZ/l+MDT2LTp5FgLB5NyWoaQaWfJt92TvQ/haKFSbMsw2m4Mm7bN3BtQ1xAO+RC0Ovl4VaDGJSoSiSqYGLqQEEIQUZaPHNmZfD2rthbrc8fZvvu0zz6kaXjxqFpGvWNPdQ3jSoZ260mKhflXxMTwnQgJNBdIAP3fjCZObHpEnz0xkKvk8cHvBrTND6OQSfL0yaSfxAQwsCIooyQEMIQI3abbyGitNPWH+tosxgXYTetHdnmnMVSLOsTy8jZTGuJRDvoGPiXYeJ2Ngm2x9HJUwcUUaWLnqEfEVX7kYSROPNGDHIWquqnZ+gn+MOHiERbaBv4a0z6cly2jw0fTwz7e8oIISPQgQCdlIAvtIcB/3MIYcHt+HMAhgLb6fM9STBynED4ML7Qbly2T2LSF5Ng+xgD/ufo9z2DJCw4rfdi1Oecd50EGZY0XIZ4OkPd45b1hvvY1fMed6dtRLpKsjOapnFs8BTVA8cmJYY7DQ7yrBO12q4GVFXjrR0nePudU+RkuXj4vsXjsvBTQZIEc7JSmZOVOunyjRVFbKyYqHA+FkII3A4bG2ZfeL1rAddN4CShoyLh4wSVPvpDtbzV+gUsOjcWXRIaGiGlH1+kE0ULIQsD6dblLHB9Ybjr7gY+bNA0DU3VLom/oGmxUtHYqUyWpWnxpOw2E5WLC9h7oH4kY7J990nu2FAxrhtMVTUOH22ms2tU9HJuRSZZmVf3jfdaxTnD3LEIRy5PByg6bAQ8unOQL6KGfL1AYCDT9YNY0AGY9eXDf+uRhCDJ/lk0e3R4XR1CxIi247YxzBndRjLisj9Bgv1RYq8N0sh6U8GkLyE94VvEyn1i3HES4/4ExilfSwj0ZCb8O6AfJqHH7kurcQkRpQ1ZcpBo/zR6XdrI+kIIbKYVWE1jO5xHjzW6bHQMkyHbkkGuNXtC4ATwZsd2ciyZVDjLrooEQJO/hd81v8hAZHKvv6Wuhdh1H0z2WQhYt7KErIwEfvqbXUSiH14NwAvhugmchBC4TGUsTf4a9UNb6AwcxBtpxxtpA2KdZTZ9Kg5DLimWRaRbKrHorg/OyA3MPDSNKUXXpoKqqRO20enkYVuPC0MIwYK52biTHSNq151dgxw60sRNq0c7Er2+EIeONI5YkEhCsH7NRD+pDytkWZpgxTIds+LJEA5HR64zgCRJWMzXdov3dCGEQGAY87d03t/yBH7n5Wxz4TGM336q44zHuc/H3lMy54IoIeSRzrzR/emmDIimGsP5MMpGlicu5kD/YSLnlev6IwP8rvlFzDoTxbaCK/bM0DSNZn8rv256liZ/y6TrOPRxLHNdmjL6TEIIgU4nMF5mlvfDguvq6khCxmUqwWHIJaIOoWhh1GECoRASsjCgE2b0kuWqqn0Ho1F8kTARRUHRNASgkySMsg6zXo9eki54I2iaRkiJ4g1HiCgKGho6Scai12PR66dswz7nyt7j82PQySSaY/XfiKIwFA4RVhRUTUMnSZh0eqx6/YifUFRV6PUHiKoqdqMBu2FqM1JN0xgMhfCGw0iSwG21TTomVdPwRcIEIhGiqjos/SBjNRgwyvKF9x+O7T/OYMRujBnFnruuYUVFEJPlt+gNmHTTU9UdHAxMKbI4Gfz+8IidyDlYLYZp86QS4q2sWlY4Ejh5fSH2Hqxn6cI8rNbYOXV2eaiuGZ00CwvcFBWkTLXLDx10OmnEp++cXMHgYIBgKDKlb+BUGBwKjJN70MkSCfHXB4/swwcZWXZxJR9JFc4ySuOKOOI5PmFZg7+J7535OR/N3MRc52wssnnGghdN0wgoQQ4P1PBC26u0+NsmXU9C4qbklSQaJmafVVWj5mQrr22tobNrkH6Pn5xMF1/45DrMZgPPvXyQI8daMJv13HbzbOZXZCFJgpqTbbzyxhH6BvyUFKZw7x3ziXdY8AfCPPncXurqu+nz+NA0jYfuXcLKpYVTznf+QJgXXz9MdU0LNquRW9aUMb8ia9rz6+VC0zR6fX5sRgODwRAa4DSb0Msy/f4AdpMRgywTjkYZCoVJsJjxhoatj6JRIqqK1aDHbpw5w+3rKnA6B51kRHcNaFwoqsqJnm5ePH2SquZGWoYG8YXD6CQJl8VCQXwCc9yp3FFYTJFrci0mVdPY19bCa3W1VDU30TI0iKqqJFmtzHOncmtBETfl5mGQJ/+qjnV1cd+zTzIvJZWn7v0IPX4fL5w6wZa6Who8A4SitvCO6gAAIABJREFUCglmM7OT3XxxSSWliTGfn4FgkE+/8gJHujp5sLyCv1m5BrN+8rdxVdP46+1v8XLtKYpdibzwRw9jOs9TaCgUYmdTAy/XnqK6s4PegB+9JJMRF8fyzCzuKS6jNDFpUiPIqKbywwN7+cnB/Xx+0VL+bPEyDnW08/uTx3ivtZn2oSEkIUix2dmQV8ATc+eTaLm4GGJn9yDR6PQDJ4/HP06wUJYlMjOmFuA7H0IIbl5bxu9fOjhCQj50pImOLg95ObHrvv2dUwSHH+aSJKhcnI8jbuYm6T8EJCfHYbMZGRoWIg2FI7S2DVCQd3E19rHo7hnCO4YMbjDIZKZfXAX8Bq4+9HIa6fH/dmWPIfTck347rYF2esP9E5b3hHr5Ud0vme0oZXniYgpsebiM8ZddvlM1le5QL3Xeevb1HWJf/2GUC3QKFtrzWJG4dNLjeX1BXn7jCGuWF1NalMp//OBN7t44h3inhedePkRTax+f++Ra+vp9/Pb3e7BajbjirTz9wn7Wry6lMM/N868e4qnn9/EnH1vNu/vO0tk9yN98+Xb2HW5kZ9VpFs/PuSCnb9uuk7S1e/jCJ9fR2T3I0y/uJ9FlIy/7ynrHhaIKn3/mJTaUFlLf24+ianx0wWxyXQl89cUt/NnaSmalujnW3sX3d+3he390J08eqKa2qxejXocvFEavk/mz1ZWkOy9FRmVqXBeBk6KobP79fpYuLyT1IhOfpmnsevsEkiyxYnXJBdd9P9A0jcOdHfzt9q2c7O1GEgKH0UR6XBxDoTBdPh/tQ152NzdR4U6ZNHBSNY0tdbX8W9Uumgc9yELgsliQhKDL6+XlwVO829JMy6CHRyrmYpKn7nLp8ftpGxrk23uq2FJXS1RVkSUJVdPo9HkJtEaQx2zrMltYmpHJ0a5OdjU1MBQOTRk49QYCvNcS84jakF+I8TyeSDAa5bv73uPZE8fwhIKYdTqSLFZC0Sh1fb3U9vXyXksLX12+kuWZ2VNmi1RNo8fvZ197K9/YsY1TvT1ICCRJEFYU6gf6Od3XO20hxMbmPsKR6DiftKmgaRrdvV66e0dbZmVZkJN1aXYZSS47ixfksnXHCQC6ugc5cqyVvJwkwmGFd/eOaje5EmxUlE9u6PthhRCCjNR44h2WkcApGIxwqrbjgn5x5yMSUahv7BnXoeeIs5CRdoNLdi3iarw4CCHIs2Vzs3s1L7S+SkidWAKOaBEODhzh5FAtqSY3qeYUCmw5pJoubHqraipBJYgnMkRvuI8mXysN/iZa/G20BzvxKxdWkDfLZu5M24DbNPVvXB3mbKpqjLcpSRLRqMrhmmZuWz+LrPQE3ElxpKU4qW/sIRpV0MkS82Zn4Ygzs25FMd//n+0EQxFULcblVNUYF1SWYiIRF6oKVO2to7ffyw//dwfRqMLZhi76BvzkZl15Haxzz7Mvrl2OJMCk0xG9iCdol9fHv9x1C0ZZxz+9sZ0jbR0frsAJIBAIT9ugs7mp94o/jKKqyo8O7OV4Txezk918fdVaihISkSWBqmm0D3nZ2VTP8Z5uFqelT9he1TSqmpv413d20uP3c39pOZ+Yu4B0e+yL7fB6+dnhAzx/6jjf27+HRIuFu4pKxwU/Y9Hl8/Ldfe9xsL2NP1m4mNsKiki22hgKhTje3cXJ3h7yE0YfGkIINhWX8asjh2kZGqSqpZlNxaWT7vvNs2fwhII4TSY25I3vUoyqKr+oPsj/VB8kwWTmr1as5s7CYiwGA4qqcby7i39/7x32t7fy12+/xW/ueYCMuMltUDTgQHsrJ3u6Met0fOvmjSxJz8CqN9Dj97G3tQW70US8aXr6JqfPdNDZNUic/eLrK6rGiVNt9I5TrDZSWjR5l8hUMBp1rFlRzJ79Z/H6QmgabNtxgjs2VHD0eAtd3YMj6xbmJVNalDojnVt6vYyQBCixeyQSUVBV9ZJ0rK4VZGe5KMhz09TSB0AwFGXvwXpWLS+alp6Tpmn0e/zsO9gwbs5YvqQAg+EPO0hVFZX2xh48vV4yCpKxO60MDfjp6/AQ8MUCUZPFiCvFgX24JDrlvlSVgZ4h+ruGCAfDIARmqxGX24HNOXlbeCQc5eyxFnR6HRn5yej0Mv3dQwz0DBEORpBkgd1hwZUaj9F8YbkHVVHp6xrE0+slFAwjhMBqN5GY6sRsm9yW42LQS3puTbmJ3nA/b3ftnjID5FcC1PkaqPM18G7vPiSkKe/TBn8zXz/2byiaioaKqmmoqKiaMi0nPJNk4t7025nnnD1lZ59tuPP2dy/uJzHBxsI52RTlu1FUFUVVR14mBYwLqsZCCAEi9iJauSift3ac4O//3ytkpDl5+IGlGI0XDgeiisIta8pZtmhU4me6NkjvF3pZZn5mGgmW0bn8XDnuHM6/1nPSU0iNs6NqGkk2K0PBmVPxvy4CJ1mWeOjxFR/0MMZB0TRqumNKtHcVlTA/JW3cjVzoMlLocqFoKtIk3i2+cJhnTtTQPDTIbfmFfHX5qnEBQX5CAl+pXEmDp593W5p56lgN6/MKsRkm53mEFIV3W5r5vytWsTG/aMQXyGE0kRHn4Jb8wgnb5DiczHWn8m5rM6/WnuLOomLk825cXzjMrqYGIqrKotR0Um32cedZ29fL747XYJRlPrNgMY/MnoN+TEZqaUYmf7NyDU9sfo7mQQ/PnjjGF5dUTnldT/X2MC8ljW/evIH8+FENJKfJREHC5EbHUyEcUXjtzaPk5yZflKc0OOjnjbePj7MGmFeRhSvh0iYGIQQlhTH/uuqaWJaurqGLto4BqmuaRzg3siyxYlnhBCL05cJmNSJLAmX4OeAPhOkf8F832lBjodfJbFhXzs6qUyOT/+GjzVQfbWb50umRd6veO8OpM6N6b3a7idUriq/YmK8VhIIRnvnvN9j+/H4+/28PklGQzAs/eZuTB+rp6xoEDZyJdsoW53PXx1dTsiBn0uA64A3yzqvV7Nx8gLqaFgb7vUiSRII7juK5OWx8uJLZywqRz3tB9fR6+edP/RSL3cyX/+sx6mpaePv5fdQfb8Xr8aMz6EjLTmTBunLu/vhqXKmTCxoGfCHefm4fu146SNPpdgb7fEiyRFJ6PBXLCtn4yHIKZmddkk4bxPrujLKRBzLuIqyEqerdN0Hb6XwomoKCMpUcFYqmTLBzmS6MkpENKWu4yb3qgnIImqbR0T3I+tVl3Hbz7JHz1jSYXZrOrvfOkJmeQL/HT0eXh5tXlRLvtBCORKk52UpBbjK79tRSXpSKQa/D6wshhOAvv7CReOdEGyxN04ZdkGMnLYRg4dwcjp9uY+G8bCxmAwOewFWjGQgEhvMqHQJGDIIBvKEQwejod2kcQyeZ6RFe1cBpoN/PU796h5bmXspmZeD3hblj03y6Oj0cPtDIRx5dhtGoZ8e243S1e3jg4WX0dA/ynW++xtBggM/9+QYKi2MZAE3TaGvp54Vn99HW0o/VZmTT/YsonZU+cpFUVeXQ/gbe3V3LI0+swDmD0bEA7AYT7Xg52N7GH5XNxmYwDHeUjOL8QOTc2Lv8PrY31qMTgntKyifNojhNJtZk5/JuSzOHO9vp8fumDJwEsDQ9k/W5BZOaKU4GgyyzsaCQPW0t1HR3UdfXN66kqGkap3p7ONnbg1GWqczMwmEaY0miaVS1NNEy6KHYlcjq7JxxQdM55DjjmZOSwtsN9VS1NPHp+YuwTFEWtOj1PDirglznzJRUtu48yayydFZWFqGTJ5L0NU0jFIrym2f20DBGW8lo1HHzmtLLmhQSh8t1x062Eo2qhMMKO6tOc+Zs14jopdNhpnLxzGmMpaU6MRr1I637Xd2DHD7azNqVJZf8cLkWMHd2JosX5FG15wwAAx4/P/3VLjLS48lMT5hUkFTTYhYnh44085tn94xMqJIkWLuimOxL4Ktd74hGFXa/fIiB3iHaznaRkp1Iblk6vR0eWuq62Ln5AG31XXzp24+QUzL+pS8civDbb7/Ga796h0g4SmKak7zyEpRIlJa6Lt559TAnDzbwyJdvZ809C9FNYkvT3z3I5v/Zwd63ahBCkF2ShslsoLW+m+YznTSf6aS3fYAvffsR9GM6uDRNw+vx89R/buH1376DElVxZyZQOCebgDdI0+kO3njqPY5U1fKV732MwjlZl/Wd2nU2Hsq+jzi9nbc6dxJUpy+MOlMwSkY2pd/KLe61mOSpObuapo00+bz8xhG27jqB2aRn/Zoy1lQWc8ctFTyzeT//8YM3MRr13LKmnKJ8N0IS3Hv7fF7bWsNzLx8iO9PFg/cuijUVhaP09fv4+jc3o9fLlBS4uef2+QD85vd7OHO2i55eL//w76+weH4uH71nEbfeNItwOMr3f74dTdMoK05j060fnHm8LEnEW0zsPFNPWIny5skzM5pVuhCuauD0ygsHCPjD/PHn11N9sIE3Xz3CLbdV4POF6O7yjLztD3oC9AxbI7gS7fztP9/P1//ydwQDox0yfb1efvhfbzJvUS73fmQJAX8Ih3M4MBq+kQ7uq2frlqPc+5ElOCaJqt8PdJLEppJSvrPnXd44ewZPKMTdxSUsTE0nM84xaQAxFse6uxgMxRyjGwf6ef7kxE4PgJbBWGknoig0eTzkOCfneMmSxIqsLAy66X+lkhDMT0kj1xlPy6CHnU0NFCS4RtK+iqZxoL2VlkEPWQ4nyzIyx/GL/JEIp3q6iagqEVVlb2sL1Z0TVd3DioIvHPvuPMEgvX4/Fsfk5bo0exylie9fRuLc5gMeP//9k220tvWzclkRKW7HcEpaEApHONvQzWtv1rBlW81IWUeSBGtWlDCnPPOyji1JgptWlfDc5gP09vuIKgo73zk9rq1+7YqZNfQtKUwhId4yQkofHAry69+9i8EgM292FlbraEeJpmkEgxECwTCKopGUaJ+xccwUjEYdH3uwkrb2/pGAtr6xh6//y4s8sGkRc2ZlkOJ2oB82Ag2Ho7R1eHh3Xx3Pv3RwnLVKcWEK99wxf1pctz8UKFGVPW8eJa88nb/5+acpX5yPkATRiMK+t2r4r794ktrqJqpeqya7KBUhj/42drxwgBd/uh2TxcCjX7mDOz62EuNwR+NA7xDP/2gbz/1oGz/7x+fJLHRTPIkJtqfXy5tPvcfNf7SEh/78NpIzEhACgv4wv/n3V3n+x9uoeq2a2x9fSfniUeN3TdV4+7n9vPyLndgcZj7xt/dSeescjGY9aNDW0M0P/up3HNxxkh9/4/f89U8/iTPx0nkrQgjidHYezLqXVHMKr7dvpTXQjsqV1y0SCLIs6dyWup7liYunRT6va+jm5JkOvvqnG3E6LNQ39fDjX+2iclEBNquRJx5cHnOtOXeM4Xt94dxsFs7NRtNG58RQOMqPfrmLxz+6jLKiVILhKP/7VBVHjrWwdkUxf/rJdeMy7+e2s1mNPHz/kjHa7VcHsiRYkZ+N3TQ+uDTqZD61fDGbj57gteO1VOZlU5iUiCQkCpMSUYY13IQQlKe6SbbPXOLkqgZOx2tauOOeBWRmu5Akwe7tJy+6jRiuyZ7/LTU19hKJKmy4fQ5W6+gF1TQNSQhOHW9j/56zfOZPbyavYObdlCUhuL+0HE8wyK+PHqaqpYmD7W0UuRKZn5rK7YXFsfIdkxMfW4cDoqiq8g+7t0/rmP7I1Ho2AmJltEs4ByEEOc54ypOSOdvfx4H2Nu4rKSfeHMt++SJhdjc3oWgaZYnJ5J2XBQpFo/QEYinqU709fO3tNy96TGVYemEqWPUG4ozG931TxtnNlBSmcPhoM719Pn7xZBU7qk6TkuwgLs6MJASewQANTT20tg+MM2NNSXZw921zsdkuv33Vnexg/txs3hwu/9U39oyeo9XIkkV5M5oJSoi3sqqymF89/e7IZ2cbevj299+iqCAZV7wNo1FPJBIlEIwQCITxB8JkpMXzfz6/YcbGMVMQQpCfm8QTD6/g299/kwFP7HfW0NTL936yjayMBFJTnNhtRlRVwzMUoKPDQ0NzL5ExgpnxTgsff2QFOdmJH5ps0znYnBbu/9x6ypfkj5Tj9AYdSzZUMPu5fex+5TAnD9THuHDDGbz+rkG2/X4v0YjC8tvncttjKzCNsbyJT4rjgc+t5/ThRqrfOc1Lv9hJ0dzJ7UFScxJ55C9uJzl9dN4wWQxsfLiSPW8coaOpl9OHG8cFTqFAmFd+uYtwKML6j65jzaYFI2NDQFpuEps+tY76E200nmyj+p1aVt01/7K+21h1QLA6aRl51iy2de1mV/e7BNUrl7UwSgaWuRaxIWUtmZb0aXfshUIRQuEIer2Mqmq0tg9gNcekUs6d+2RXYGTZmIUx66EABr2MTicz2DPEkDc48mIRc124wL6mf7ozAr0s89mVSyYdT35iAl9au3zCsrVFozwsAdw5e2Ybxa5q4DRWU0eSxUiKVyBiEe5wmOvzhqasJ5+DqqjoZGnSh08kouD3hzFbDFQfbCQzKxHDRYhvlwohBIlmC19aUsmtBYX8ovoQB9vbONnbTU13J8+dPM66nDw+OW8BpYnJEzrBvMNBkCwE6/MKpiR9jz2e23YhvoqYUrLgQrDq9azNyeOt+joOdrRRP9CP0xQjXrYODrKntQVZCO4uLpmQRYtq6khNOcVqY0Fq2kWP57bZsE5RboTY9dDNgAaXEII7Ns4hLzeJF185jD8Qpraui9q6rtiNLxj3VhXbBpKT4vjSZ9cPk7Yvf4oQAm6/pYJdVbUEQxEiY6w+ykvSyMueWXFWIQT33TWfuvou9h6sH+EG9fZ5eXevFyGG7zO0cecdVa5dZWCdTmblskIMBh3f+8k22joGUFUNfyDMydoOTtZ2xCZ4beJ0IUmC/NxkPvX4ShbMnbqT8w8Z2UWplC3Mm8BhkiRB3qwMdr9ymP7uoXG/h6bTHbSc6cQeb2HB2nLM1oklJKvDzOpNCzlSdZpje+ro7fSQmOKcsN6yjXNISB6fWRZCYI0zk5KVSFtDDwPnmS7XHWuhrb4Lg0nPmnsWxhoezts+s9BNSraL4/vOcuZIE8tvn/u+moFkIZNtyeSR7PtZm7yCt7t2UeM5SX94YEaCKL3Q49DbKYkrZF3yKvKs2RikS/NBLMxzs6Aimx/+704iEYW0FCef+8TaCSr704HFbODjDy5n8+vVPLP5IDabkXUrSpg/+/LKnh9GXNXAKb8whUP768nJS6L2ZDudHTHJeavNSH+/j472AXQ6mWNHmklNGy1JnSOqje2QSU2PJxpV2PvuGSrmZhEORdHpZRJcNiRZMG9hDmvXl/OT723DmWBl9bqyGXc6F0Jg1OmY407lWze7Odvfx/bGenY1NbKvrYUXTp3gRE83/7Xh9glyBNZhjo9OkvintTeTYJ7ZUuJ0IYRgZVY2iWYLTYMe9ra1MMedgiwEr9fVElKiZDucLE7PmLCtLCRMw8FaWVIy/7H+1ksqFU4+oPe3+TmEwhEUReXxB5eTkuTgpS3VnDkbcyLXRv41CoNex9JFedx313wqyjPedzZICEF2pouKWRnsPVA/8rleLzO/IuuKdKM4HRY+/6l1/H7zAd7acWKcJlXsFpr4NnKtT5OyLLF0YR6uBCuvbDnCjndOMeAZf17nI9FlY1VlEXffNpfsTNeH9mHgSLTjmKIMqx82aVYi40nPfV2DDA34iE92kJweP+m1kySJ5Ix4zFYTQV+IjsaeSQOnzAL3aLZo3PYCWS+DpsWOPwZNp9pRFQ2DQeatp9/D6pjI/Qz6w/QPE90H+3xEQpH33UUthMAgDORas8jJeYjOUDcnBk/T4Gum0d9MV7AHT8SDOq0+OTDLJpKMiWSa08m35VBszyfHmnVZfnhCCCxmA/feMZ9775h/ydtPtr+y4jTKii/+onsDk+OqBk633TWPX/xkO//+Ly+TkekiYbjjJ7cgmdLydH7831uxx5nJK0ge0ax449Uj7Hr7BE0NPfz8R9tJTXPy6c/fjDvFwYOPLeel5w/y6uZD2Owm7rl/EQkuGwaDDlknk5Qcx6b7F/L8M/vIL3CTnXvlhLp0kkSRK5H8+ATuLiplW+NZ/mHn25zq7eG3NUf4xup149bPGub4qJpGXX/fBxY4ASSYzKzKzuXXRw+zpa6WJ+bMJ6IqbGuIaQ6tzyvAopvIDzHpdCRZYwHAQDBIT8BPmn1mdDLeLyIRhXBEwWzSc8fGChbOy+FAdQP7DzVytrGbwcEAsiSRlGSnuCCFyiUFlBal4HTMnPu2w2Fm4dxsDh1pGikfOR0WFi/IvSKEbSEE6WnxfOKxlaxdWcKB6kZqTrTS1u7B5w+haSpmk4H4eCsZqfHkZLmYW5F10f2uW1VKeUka6nCUYjYZLukaCQGbbp/H8qWjZHinwzItKxuIPWiL8lPIeCKeDTfN4vCRJqqPtdDc0ofXF0SSJZx2M1mZCcyryGZWaTqZ6fGX1LEoBHz1S7cRCI6Ww9NTL00s050Ux1f+bOPIPiQhyEj/4HSjDEYdhku0zgiHIkTCCjqdhPEC109v0GEw6VEUlYBv8qyMxW6+ZKkNrycAmobfG+SFn77NhUJ7WSejKCqqMr1gZroQQpBiSsZtSiKiRhiMDOGPBvBEh+gO9eIJe/BEBgmrYSJaNNbxJekxy2biDU5chngSjS6sOgt2nW1GVchv4NrAVQ2c0jLi+erXN4EG3d2D/Pi7bwExzsdDj69AUzUQ52qpsZth/a2zuWnDrJF9nOM8CSGomJfNrDlZI0au5x5G9310CQyLeZXNzqCkPP2qdRbJkoTbZuPuolL2t7Xy3MnjHO5sH0fcA5iV5MZlttAfDPB6XS1z3KkT2i2vJjYVl/DsiRqO93RzqrcHbzhM+9AQCWYza3NyJ+3Us+r1zEpy86J8koaBfqo7O0ix2a+JsoiqaqjDZSidTiY9zUl62lzu2DhnXGknxkEbywWYwbFrw6WwMfP6rLL0ERXxKwWrxcissnTKS9NHsrTnEzrFcL1yOqeb6LLhSrDS3eslFIqQnjp5JmIqCCFIcTtIcU/eEDC9fcTOq6w4ldKiVD5632LgvPMSjOrZXOL3KIS4ZGXy82E06t/3PmYS53R7LgUGgw6dPhaQREKRKdeLRhQi4ViW3zRFgHV+mW06MJoNIATORBu3Procy0U02LIKU2achnEOsYDIQKLRBUbOu5cmD9bG9lTfCJb+cHFVAychBPJw94YkidFJ7xwZbdyNNjoBTtVdP3Z/539+sXXeL4LRKJqmjbMeGdu1BBqBaGzisRvG8wSEECRarKzLzeOZ4zVsqTvDisxsVmXlTBp0RFSViKJg0V9aXXy6EEKQ7XAyO9nNgfY2tjfWI4RgKBxiSXom+c7J27iFEFRmZpHpcHCmr5dfH61mjjuFVNvk5YFANIIkpAl2LVcKY6e2c+O/GJdsJjHg8bP/UOM4ftMta8qumkryueBopnD0RAtdPUM8cOcCJOmDCfKvxHndwCgcLhu2ODMBX4i+rsGRl9Kx0FSNgZ4hAr4QLrcD1yRlustFyjCJX9M0bvnoMtzXUKl1PDn62hjT9YDzhauvxPd5MXHsmT7mByaAKcsSiUl29JNogFwPqO/v5y+2vk5lRhbLM7PJinOgk6WYanEwyOZTJ9hafxa9JHFbQdGE28yq1/N4xTxO9/ZwpLODv9y6hftKylmXm0eCyUJEVej0eTna1cmOxgY25hfw+Jz56K7QJOI0mVmdncvB9nbeOHtmWFdKsCwjc6QcNxlynfF8fuES/mb7Vt5rbeZTL7/AQ7MqqHCnYtHrCUQiNHgG2NfWwr62Vr5180bKk66dt/IrBU3TOHO2i6PHxxj65rspLb40JfJrCcsXF6Aq6oxzBW/g2kFmUQqpuUmc2F9PzXtnmLuyGINxfJk+GAiz540aVEUls9CNO+vShGkvhJIFOThcVvq6Bjmw/QS3Prx8RCphLMY+KK+VwOoGJkdjax/f+dk2WjsHeHjTYu6+Zc6M7l/TNE6f7eRr//bihGULK7L43ONrcEzDPeJS8IEFTq5EO5/70rXXBj19xLhJx7q7+Mmh/Zh1OmwGI4qq4gmFUDQVu8HA3cWl3FU0sRVSCEF5UjJfX7WOb1XtYn97Gz88uI8fHtwXU0MdMzHoJIlb8mZOLHEy6CSJxWkZpNptnO7tRScJ4oxGbsrNu2DpTRKC2wuL8UXC/PzwQU70dPPX27eOLBt7Hla94Zoo410NKKrK5teqR7hNsiyxZkXxtCxDzkc4HOXoyVaaWvqId1qYU56JM85Mc2s/DS29LF8Uazffe6geR5yZ4nw3oXCUmhOtNLX1kxhvZU55JnF2E6qqsWtPLUX5bo4ebyUcUVg4J5tUt4NoVKGuoZtTdZ0oikp2hos5szKQJYltu0/R0zdEcUEKs0vTRzJ3Xl+Q6mMtdHQPYjEZqCjLIC3FgRCCxuZejhxvAQGzStLJuYayBzcwOZLS4ll332JOH2pk67N7ySlJY8Wd80fKYb7BAG8/t493t1Rjshq56xNrZjSQtjks3PGxVTz57dd5+jtbsMWZmbe6FPuwxYumaQS8Qdobe+ho7GXuymKscTP7ULyBmUU0qtA74KOrd2iclt1MwmQykJedSCAQwRcI0dE9iNcXYmAwMCKEO5O4LixXrkVkOZ3809r17G5q5FRvNx0+L/5IGJ0kk+uMZ3aym1sLClmUljGlSramacxNTuCbN63mneYmtjWc5VhPL4MhBZ0kk2SxUpaYxIqsbCozsiYtMwkhMOl06CV5UmuXS0FZYhIlriR6/H40oMLtHmd7MhV0ksT9peXMS0ljS10t7zQ30jTowRcOY9EbyIyLY15KGkszMslxTEzri+F9mHQ6DLJ8yYTSaw2apnHoSDOHjzaNfJaW6mTB3OxLfshomsaeg/Xs2nOGitJ0jp9q59SZTh77o2Xo9TJvbD+G2aTHbjPx3CsH+czjq9GAqr117DvcQHlxGtXHW6iAqIPTAAAgAElEQVQ928WjDywF4JnNBygtTCUrPR6EIBSKoGka1cda+N3m/cydlYnVbMAz5B/pWktzOzhxup3evjrKi9KQpVhwuKPqNCdqOygvTqPf48frDwIO2js9/OLpKmaVpCME/OLpd3n8gaVXnN/1QUHRVPpDAZwG87SV+69FCCFYs2kBJw/Us/XZvfz0759n18uHyMhPRlFUGk+2c/pwI5IkcdujK5hTWTSjx5ckwfqPLKPpdAfvvHKY7//VM2TkJ+POcmEw6gl4g/R2ePD0ejGa9RTNzb4RON0A6W4HX/vsRsKRKD5/iJ89XcWuvWeu2PFuBE6XCYtOz6bhbJKqxToAzxHAhQBJSMhiardpANRONM9XSYsc5b7EMJsSFDTjbRD3DYQwDe9HIAlpSiHNOe4UDn3qcwDTIpf3ev2c7e5DUVXK0pKxm0ZFHi16Pd+79c6RLJEsxCXYt+gocSVSlODiswuXnHc9BJIQU/KLZCHxZ4uX8bmFS5GEQH8dP3hUTaOuvotf/OYdvMPdRrIkWLOiOGaDcIlRoabB5i3VzCpJJ9FlQ1FUNr9Rzb23zyMlOY7HHljGD/53Bwa9zKZb55GT6UJRNV5+8wjzK7JIdNkIR6K8/OZR7r9zAWaTHkkSlJeksXpZIecI4oqi8uaOE1QuyueO9RUThPNKClM429RDY3PvmMExYvGSkRZP5aL8kYza9qpTsS6/VCeqqrHvUAMHjjaR+wcqRNnkHeAfD77JPy26lRTLtdFZerkw20x86hv3klnoZvvz+zn6bi37tx1DCIHZZiQl28XGh5Zz0wOLL9h5dzkQQuBKcfCn33yQ3NI0dm4+SOvZLmqrm1CiCrJOxmI34XDZKFuUj2UG1fdv4PqEEAKdTsY1LPESCkWwT6I/NpO4EThdJs550r2f0pOQHGD9BCjtSNETSIHnQNaQdDKIi38158YwXbK1LxTm57v2E4xEcZhNZMQ7sJuMMcuKqIJOlt5XZ58YDo4udQ9CCHRCRncdxUvBYAQhCQx6eaSEMDgU5NCRJp7dfIDjp9pG1s3MSODODXMuq6ShodHe6SHJZUMdthBYsbgAkynWKJCTlYgkCQY8gZHATNNU2js9tHd6RkqFK5cWjPAJJUmQ6naME0bUNA2vL4gr3jbtcUqSYM3yYmRZ4tW3jiLLEvfdPp+cLBe9/T48gwFOnG4HoCjfTeE11HE209jX3URAiUxT5efKQW/QsWrTQrJL0sgsSJkyeztneRGf/rv7cCTYkM678YQQ2J1W7vvMzSxZP5v6460MDviRJIEz0U5uaTqpOZMHwNY4Mw/9n9vwDwXJK0uf9Ngmi5GND1Uyd2UxBbMm2hrFAjQT9392PSvunE/jqXb6uwaJhKMYjDqcSXGkZrnIKEiZ1CfvBm7gSuNG4PRBQpgRxpWx/w+9gxZ49YoertPjpa6rj29suokEqxmdNPrQ/993DrK+vJDcpEvTrvmwYuuO4zzz4gH0OhmjUUcoHGVoKMiQNziSaQKIs5v4xKMrSU66PD84gSAzPZ7yknTWrSgGQFE0LGYDiqqys+o0dquJ9BQnW3ee4L47YvYTmenxzCnPYOXSwpFtzCb9cCAlJgT8QgicDgutHQMEQxFkSUJVVQwG3egDcpLOFbNRz/rVZVQuyueF1w6zbfdJPvbRSpIT7Xh9QR64awE6nUw0qo4EmZcLTdPoCAzxcuNxdnfWMxQOYdHpWebO5vGiRdj0RvzRMP+vejv5jkTKnG6erjtE7WAPdr2RL1esoTw+BYCAEmFHWx0vNh6jK+AlyWzlofx5LHPnjCjw94f8PHv2CFVdDfSHAlh1Bpa6s3kofx4JRgsasLX1NC81HedgTyuD4SCf3PG7kYzpPy++nVJnLFgMqwq7O+p5oaGGVp+HBJOF+3Jnsy6tEONlKP5PBZ1eZv6qEuavmtpiQghBYUUWhRfR8JJkiayiVLKKpt/QYLYa2fBg5QXXMZoNLN1QcdF9SbJEWk4SaX+g5d3LhaqqeIaCRKIKifFWoorK4FAQVdOwmg1YhrOAwVAUry+IBiOfT3X/Kao67F8ZQVHVmCCoXsZiNqDXXfy+1TSNQChm5RRVVCRJYDTosZoNTLcD8ZznpD8YIRJR0NDQyTJmkx6TUX9NmZXfCJyuQyiqytGWDhp6+pGERIHbRZE7EZ0s0TXo5VBTO/5QmPzkBGalpyBJgn31LbxX10THwBBbjtbidthYXphNIBxhz9lmXq4+SSgaJSXOzoLcdLzBMAlWM/FWM+/VNVGWlkyc2cSBhlaW5mdR19XLma5eFFUjNymeiozYA6nfH6Cuqw+LQc/pjh4S7VYW52Zg1OvoGvRyoKGVcFShwO2iNG2iFc31Ap8/TGtb/0ipajI4HRaeeGg5SxfmXXbAIATce9t8XnnrKG0dA8iyhDPOzK03zaKuoZu3dh7nsx9fi9mk5z9/vJWsjAQWz8th063zeGP7cZpa+5EkQYLTwm03z57yOLIssXFdOU+/sJ++fi9mk4GEeCu33TSLvgE/h2uaOFQT8/17bVsNs0vTyUyL561dJ2jv9GA06OjsHqRyUT5CCNYtL6auoZv/ebKKOHvMwmfl0kJysxKnHMPF0B308ZU9L9MT9LI+vZgUi52ugBd/NIJRik1lqqbRFfRSO9jD3q4mCuISKU9IpWGoD4chxoXRgF/XHuDpusOsTSug0p3DaU83/3ffa3xlzlruyCpDliRavB6O9rczKz4Ft9lO/VAfv6k9wFA4yNfm3oQA0q0Obs8sIxiN0uTt59GiBcQbYmK2qZbRYPmFhqP88Pi7rEjJZXFyJmcH+/iHg28yEAryQF4Fug9I3uEGrj94hoL86/e3cOJMB//59QfYV93AU5v3EwhGWDw3hz9+eCUWs4GfP13FtqpTKIpK5cI8Hr9/KVlpE6VlvL4QO/bUUnWgjmOn2/AMBTHoZTJS41lYkc0tK0vJy0qaMnsZjSqcONPBS28d5UBNI/0DfsxmA/lZSdyysoS8rKSLWsOoqkb1iRZ2vFfLgaONdHQNoqgqrngrZYVprK0sonJB3rRFc680pjUK1fsj0HwIy6OgNKIF3wS1C6QUhOkW0FcgzjMrjNmkDEFoF1r4XdC8ILkQxjVgWASMN1DVlFa0oe/E9mdcA5FDaKFtoHSAcCAMFWC6e/Q4moaGAuHdaKH3QO2IzYhyIkI/GwyVCClxlKShaTHLiWgdhF5HizaAkEFXGjumlDZ+PIHX0cJVCOvHAAkCL6Ep9YAM+tkI00aQxvuNaVoUItVo4T2gNIAaBMmJMCyInZOImxF+x9nuPn62cz9L87NiJTZJUJjsos/r56c792PUySRYzfx0534eWTaXxXmZGHU6rAYDOlnCZjJgNcY63GRJwqzXE44qWA0GbCYjelniYGMrNqOR8vRkfrn7IHfOK2VWhptXq0+xMDedoy0dBCJRoorKq9Un+b93riXb5aR9YIh/fXk768ryibeY6RnyoagqfT4/P96+D5fdjNVg4Cc79vHEigXMybo+2/PHimaO+5yY8F9WRgKPP7icysX5l6zePP44gnmzM0l02ejoGkSSBClJcRj0OhKcVp54cDkZqfFIkuCTD68Y2WbRvBxSkh10dse2SU12oJNlQOMTDy0nLWWih1hpYSqffnQlrR0DaJqGOylWztPrZJxxFlYvixGBZVnCaNAhSRJzyjNJctlRFJVF83LIHS4dJrrsfPqRldQ39RCOKDjjzLiTLp/7o2karzQdp8nbz9/Ov4XVqfnopJj8R1CJTvBRPDvYy2eXVrI4OQtZSERUBVlICCHoDnh5su4Qd2SV87mySoyyjkA0QntgkM2Nx1iekkuiyUppvJtvLNhAvCGm/OyPhhkMB9nZfjYWOAlBWXwKZfEp7O9uxhsJsTo1n9TzOE4DoQC/rD3AmrQCvlyxBotOT0iJ4gkH2Nx4jJWpuWRYZ04L6QY+HIhEorz6dg1vV52K3QehCDveO02C04LVYmTLzuOYjXr8gRBb3zlFvMPCpx9aiXF4PtI0DV8gzI9/u4stO4/jD4Qx6nUkOCyEwlFq67uore+i+ngLn3lkJXNKMyZqemkah4+38J2fb6OhpQ9JgN1uRi9L1Jxqpba+k5WLC8d1V58PVdPYuaeWH/x6J+1dHiRJEB9nQZIEPX0+tr1zkoM1TbTfvYh7Ns7FODYL/gFhejN6pBqiZ9A0L4R2grACGqjvoQV+B/avIsz3jPByNE0D5Sza4D9A5DjISbFDaTVogefBuAER95cgxkwWqhdCW9HkRFBawfez4eMAmg9NbUOY7oRhBo2mDYH3P9ECL4KUMLyuCtEatMBLCMtjYPvjkVPUCIP/aTTfj2P7kJyx9UO70Xy/Qjj+DgyVsWAKQKmH0JtoSBDeF1tXGGMBYHALWuAFRPz3QB7z4Pf/Cs37g9hYJBsgQfQYWvBFMCxFxP0dSO5LVvM9H4FwhHBUIScxngK3a7jsJnGqo4d+n5+v3b4Gh8VEiqOW375XzYKcdGZnuNHJEvsbWrm5vIA4U4w8ZzHoWV2Sy0937GNFUQ6F7lgXXaHbRdWZJuwmA/Oy06hp7cRqNFDgdmHS6VlTkkfXoI9wNMqBhhZOtneT7Yp9nya9ntvnlJCZEHs4S0LwTm0jHZ4h1pbmopdlznb38Ur1SSoyU2bmJhBQXJBCgjP2mzmXZblSmFeRzYP3h2hu6WfIFyQSiWI2G0h1x7rnZpWkYbebZyS9rNPJ5GYlTsjWpJ0nPDh2uV4nk5edSF72+RkeQUXZRN9BiAVEmekJZJ5nExLvtLB4fu6k22SmxZOZNnl515Vgw5VwIWPq6SOqqezpaiLNEsfKlFEleyEE5knsgNxmO0uSR8199WMyOod7WwlEo9j0Bo72d8Q+1DQSjVb2djcxEAqQaLIiC4GE4MxgD4FohKgW45jFuEzaOJXoC+FYfwcDoQBOo4njA50jn8cbLeztbqYr4L0ROF1DUDWVkBomokaIagqapk7q83glYZbNWHUXnr+8/hC79p7hTz++jrllGTz32iF+9dweXtlWQ5zNxN/9+R3MKc3gudcP86Pf7KRq/1keuWfJSOAUCkf5zfN7eXnrUcwmPQ/fs4R7N8zBbjOhKBpHTrbwm+f3cfRUK9/9n+381Rc2kps5nts2MBjgv37xNvXNvWSmxvMnj61iblkmOlmiu8/LU5v38cbOE4QjyqRC1KqmceBIE9//1Q76Bvzcuracj9y5kJTE2MtHd5+Xp1/az5Ydx/nl798j3mnhlpWl10ngBKC0QHArwv5lMCwAJAhXoXm/B74foulLEfpz1ightKFvQ/Q0wvpJMK1HCAua0o7m+zkEN6Pp8hC2TzK+/qlB8G2QHAj7l0BXBkIPSnssaBlLO44cRgtuAf0chO2LwwGMEstQRc+Cvmx8IBfeh+b9b5DTEfYvgq4ktn54L5r3B2hD/wqObyL05aPHUIcg8CKYNyEsHwHJBUobmu8HENqBFvg9wvb50fUNyxE2NTZuXRZgAKUVzffdWMAZ3oNmuut9a86WpiVz59xSth4/wyvVJ7mtopil+Vn0+fzYTEbMBj2yJJEeH8eAP0A4qmA2jD5cJu3QG/7z3Oe5iQk8+d4RUh12ZmWk8OqRU5zq6GF2hpuWfg+/rjqE3WTEZjLiCYSIKKMlK5fNgsNsQh5+uGmaRr8/SIdniKraJiRJYDcZKU2dObKwJARf/8s7Z2x/F0NBXvI1Za/xh46QohBQItj1phEO0oWQYDJPWQb2hIP4oiF+d7aal5uOj1uWY0sYyWRV97Xzy9P7aPcPYjeYMEgytZ6ei6oUT3Y8fzTCiw3HeKu1dtyyPHsCBunaKD/MFPz+59HrZ6PXX1ntuZlEWA3TFuig3tdEV7CH/sgA3qiPsBomqiqoqFd1PKuSlrEueeUF19E0KMpNZsHsLGwWI8sXFfDy1qN09gyxclEB88ozMRn13LS8mJ8+uZv2Lg/BYRsdTdM429TDGztPoGoad62v4LH7lmA2jXZJVi7Ix50Yx1f++XlOne3klW3H+Nxjq8e99+/ae4bG5l70eplPP7SClYsKRp4h2ekJfOaRVXT2DLH3cAOTcZ38gTCvvl1De9cga5cV8dlHV48Tq8xOT+AzD6+kpb2fgzXNvPzWUVYtLhzhcX1QuIQ7NgrmO8G0ESFiD2HNdCdEG8D3CwjtAF1pLGMT3hv7x3QbWB9FiNiFEFIyWB9Dix6LlcvMmxDyecQ/tQNh/3Mw3oQ45ySty5s4HM0HWhAh54C+BIE+lsmRU0B/vjKphub/FRBB2D4LhlWjgYPpDlCH0Ia+BcHX0XQFCHGulVEFQznC9gmElD6sM5AI5vvRItUQPgxaJBbcAUJXALr80awVoEmJCPPDaKFdaNETCO7kfcv1a3BzeQHLC7M50NDKcweOUZSSSILVgscfxBsKoZMl6nv6SbbbMF6kLiwN21iEo8oIMdDtsBFWFLqHfMzPTiM5zsqp9m5unV3EyfZuen1+/njtEkx6HXvPNo/bn5jEIstpMZHqsPPxlQuxmmLEZlmSPvA3h+sdqqoy2OtFUzWsDgt64wefxr4SMMoyZlnPQDhASIlelFB9oWyQ02AiTm/is2WVLEvOHrdMFhIJJgs9QR8/OlFFT9DH3y/ciMtoQSfJfLdmN1vbaifu9AKX3GEwYdUbeKJ4MTeljQ8mJCERb7x6OkSaFkRV/UiSc3R+nWEEg68hCds1HzipmopfCbCv7xDv9OylI9iFL+ojpIaveobpfJTGXVwfSxKClGTHMAEb3C47pmGV9+J890gXrd1qwmzSM+QL4fPHBChVTeNgTRNdvYPEO6zcunbWuKDpHHIzE1lbWcRTm/ezdff/Z++9w+S4qvT/z63QOUzWJI00o5xzsJVs2Rg5RzDgxRgHMgvLkndh+S0PYb9g2CVnkzHGNuCcgyTbyjlrRmE0OYeOVV11f39UT+4JkhWM8fs8sqcr3L5Vdbvuuee85z0Hed8tywmlJUdSls1r249h2ZIZU8Zl9GQH/R7WXjyNHf007XogpaS1PcprO46hKoK3r5mZUeE7FPSyfGEFO/adYv+Reto6ov9IhpOO0BcMOEUIHVzLkbHfIlOVDg9KBJHGVpBJkAlIPDNwCNotOGG+drDq0mG8/j2aAfrs0d3g2mTQJiITj4HidzhE2jSEEhg6a9utYO5LnzN14G6hgedyiNyLNHch7K5+fRKOEaYU9rUpBCgFIAIgY841Cr33eIkB5jGwm9PGnQnWyXQ/IqPc47Fh+8lathyrIeR109wVZUJuFj6XzvSifIrCQX758jbCPg8H65u5a/XiUQnYihDMKh7HA1v2MKO4gOWTyyjPy2ZibhaNnREKw0FKs8Psr20i5HUzLhQgaVo8tusg0aRJ3DQZaeYQQrC4vITtJ2r56UtbKAwHMFIWyyeNZ/6E4rNyT/5ZkYwZ/OYrf2HXS/u56+vvZsV1iy90l84JNKGwrKCM+w5vZUP9MS4pntzrGYpbDjlcHaP+1/zcEryazuGOZt5eOg2/5ryEDdsinjJRhUK3maQh1s3i/FKmhx3PYn28m+PdbRk9TiHdTTRlEE0NVUaelVNIjtvHwfZGri2bSdjlkOVN2yJiJgeEEc8tJIaxG8PYRCDwAeCfVzgyaRtsbdvJ0w0vUBU5ccENpTOBoorexAsAl0tFURztwJwsf7+C16DrGpDEMFOAQ8bec7AWKR1x2/FFmcPtQsDS+RO5/5FtdEeTHDnWyOK5zmKjrSNKc1s34Hi+/Bmy9oRw2s8K++joig1p/+jxJiJRZ6FfU9/OUy/vz9iPhqZOwCGi1zV2UjpMf88Xxm44Ca+TPj94ElZyAQXsrrSx5AOrGYhD4mFk4q+Z21OKgAzy60o2CM+oPCChlkPgU8jI9yD6S2TicdDngHsteN6OwN3Xht2U9gxlgfAxZJJXcgGXY9TJZL8v0UBkIwZrKgm1XxvpWtlSOsT56M/B3J82EC3ADWfZzTupIJe4kSJhmkwqyGVmcQGBNGfprtWL2VfbSNwwWTO9gumFfYZpSVaI969chDeDkvk9a5ayr7YBKcGfDuu9Y+kcogmDsM/DpTMq0nwqH7kBPx+8ZCm1HV3kB/1cOqOCkNdZhZRkh7h9xUJ8roErghy/jw+tXca+U41EkkmCHjcT8t680geWsQfb3Inuf985/R5vwMOH730vP/jEr4cr2P6mgBCCa8pm8kJdJd/a8xLbW2oo8AZoS8boNpN8YvYqst1j47Tlevy8f+oSfnl4C63JKNPDBZi2xbHuVmZlF3Lb5EXkefxMDOawvv44xb6taIrK9pYaWpPRjIbOkvwyfnNkGz/a/wpzc4oxbIvrJsyk0BcirHu4Z/oyvrt3PV/a9hRzcgqxpORkdxulgSzunr4cz2lKEkSjf0RRcjGNbUhp4PXdjK7PwTA2Y6Wq8fpuQAgXltVKNHofgcDdxONPkog/gmXVkTIPo2kV+PzvQ1HySKWOEo8/jG2343ZdhMd7DUJoWFYL8fhf0bQKEvFnUbUS/L7bEEo2UnYRiz1EytyPEF68vptwuRYCEtM8QNJ4DbDxeq9F1xecMw/X6UBKSdI2eKzuGZ5pfJHu1NlZzF4IKEIMyDLrcTaoqkBTB3rze2cr2fN/SXOrc+3j8kaWSskO+XDpKrYtaWrt7t0ejSZJGo4hFg750LShvwshBF6PC59Hp6NraNu9BpFl8/1fvzRiP3ouJJY4N2VbTgen8Wsd7q0sBu2XOERqH8L/EXAPE6cVOiiZvA39jZIRIDRwXYTIngnGdmT8ITB2IpMbIP4ohL7oGFdC9OubGKFtkR5V/a9TGZMQJeAYTZ3/AanD4LkG4b0+zXNSwTyAbL9jbO2MAT3GSibkBHysnpaZyBv2eVhSMdSd2hOaGxce6FqfMq6PWFySHaYkuy8Ta874QmaXjkPaEqH0KaRn+bwsmphZ+C7b52XVtIkjXtubBdKuwza2wTk2nEZCMm7QXNOKkTAJZPnIK85BURWMpElLTRuJaBLNpZJXkoMv6HVepjVt+ENeOpq6SCYMcouyCOeFaDzZjMuj09UWRUpJbmEWgWz/eQ0L5nn8fHv5tTx+8iCvNZ1gV2stIZeHlYUVeNNeI0UolPqzMO3hZSIE8I6K+UwO5/H3E/t5oa4St6oxOZzL4vzxaIpCUHF0n+47soUX6irxajrrSqdx48TZPHx8L4PfIwvzSvnyoit46tQhnqk9TIEnwJXj+7SUrhw/nRJ/mEdO7Oeluip0VWViMJuLCibgOgOlfMPYim21EAh+kFSqmkj3dwmFv4KihIgmnsPlvghVLSWReBrLqkeIEF7v20EmMcwdBIOfQIgQipKNZVXT3f1tPO5LUd2riUZ+iy0T+P3vQsoo0cjP8flvx+d/J8gUCDdSRujq+iYCBa/vXSDjKIpD6JUyhmHuIOC/i1TqBJHuHxLO+jqqWnja13k24XgnE/y19nGeaXwJw77wE/DrRcYyXGTgSgyGpJfv5B4h61cIgaIIdF0jaTg6Tz0wUxaW5TgFXLrKcHkwmqoMK6obTdeuUxTBqqWTR/caC8g/SwknrwdjN5xkAmTcMS76PxS7DbBBCYFwOYaGkg1IEC6EPp3XzekZBkIoILKdUJv7EkcKIPYAJJ5Axn4PgU8jhA+UfKdfssu5hsGwO4Bk2tt1BrFTKcHcAeYecK9FCX3e8Zql971ZHQGRjiiVO08wY/kUPL5zK3H/Fk4PRsLguT9u4Oi24+genUh7lGs/eDkzL5pKe0MHf/3+kwhF0N0epXz2eK7/8BWousb9//N3/Fk+pGUTiyZYum4+y69ayC/+40+4PC78IS/dbVFyirJ412evJ5guc3A+IIRgnDfIndOXcuf0pRmP8Wk6n5+/dtR2XKrKsoIJLBvEceqPEn+Y/1zwtiHb1xRNGrLNpapcN2EW102YNWRfjzL+wrxSFuZlzmg8XQgU3J5VuN0r0fVOksmXSKVO4HItRlHyMM3dKEqYZOJlfP5b096ebBQlGyH8qGoxQjjGcip1FCG8eLzXoChBpEwQjd6Hz3cTAIpSgNd7FVo/rqlp7MVKHScr+zuo6uAFsBuP53LcntWoqYkkk+uRMnpWrvv14pXWzTzX+PKbwmh6XRDg8zlzXSxuDnuYlBLLdoQpBWIAt0jX1V6DyDQtbAmZzB7LtocttOvzOtENTVX4zAffRlbo3GVCn02chsfJRKYOgHsNoifFX9oOSVpaoI5HCD8gEPocZPwBpLkL7OsRImugsdXj2TlT121/jkFvHFdzsv3UYmTyeUhVOjpS+BxCtzYFzENg1yJlPz0KaYOx2VlJaVNBOROFZ+mEKjEQ2oR0BmDPHgnm9jO7zjcwjIRJ7dEGXnzgVYoqxhHKDeD2uVEUgZlMIRSBZVpYloXu0tDTpMWUkcJMpkCAy+NC1RyXsm3ZGAkDy7LRdA1XuqTI+YaUEiv5Ira5E9uqQXVdjDT3I9RxaP4PIu0WUrFfY6eqQATRve9AcS0BwDZ3kIr9ERBOIkRvGDdJKvYQlrERoYTRvDej6AuGaJ+dTTScaGbXiwe44SNXMG5CPi/95TUe/+ULzFg+hZzCLG761ytx+93UHK7n7z96ms53dJOT5g0kokne+6Wb0XQVJf1itC2bcF6Qd3/uBlpqW/ntfz9EW0PHeTWc3kJ/CGdRCIDiJMeQQggfbs9qEvEnUJQCJAl0ff6ILdl2N0J46MlaFiKElElkWn5BKP70u70PEgNwpf8N6pnQUJUeb7UCiNPORDwXaDFaeaT2KRJ2cvSD01DS3puxSk+cLSgZTZCz2L4QlBZmcbiqkfqmziH+kP5obu3GTFm43RpFBX1Rh6Df00tGb+uIYprWEKFLKSEeN4YNrxWPy+o97mRt25vRcBIQexD0BUh9JqA4+k6JR0HJQbhX0ysX4FkL8Ych+QJES5Ge69O6SdLx+nFIhSAAACAASURBVFhNINyOMOQZQSJThxzSt1oGStj5bhkBYxOQSnuZegpAKgj/HciOzyAjP0IEA0i1FLCdMFr0V46YpWcd4owIk+lsO+FDmnvAqkUoBY7WlLEDGfszmW3xodf1j4LXHtvOs79bz7G91XQ0dTFuQj43fmwdhRPzefh7T5KMJ4l0xGg61cKSt8/j6rsvo7s9yp+/9Qj1x5pQNYUZy6bw9vetwe1zs/XpXWx4eAvxaIJAyMcNH1vHpHnDewPOJaRVjbQaUF0XY8Z+hyvwKczoT1A91yCUMIq+AM37TuzUQczoL3BpZYCNGfkpmudKhD4dM/J9HI4bWIknsM0d6IFPIq1azMiPcQU/j9CnnJv+S0l3e5QDrx0m2hlFd2nYNhROzEdKSdXukzzz25dJmTaxSJzu9iipfgro0xZXEBwUhtN0jakLywlm+zESBppLJZXmN7yFCwEb09iN5VmHbTdiyy4UJRchBG73amKx+4nH/oxLn4vSfzEoXEi7K20sSYRwo2kTiMcfxUodB7UII/kKuj6rN7tYZKA4KEo+CBvT3IkQy5yFJwJF7eEtvrEyOy3b4qn6F2gz2kc8TkEh25VFvjuXPHcOWXoYv+bDpbjOq/E0KTDxnLavKAoLZpXx0mtHaGjp4ujxJqZNGjfkOClh49ZKwOE6TelX/iYny0dhfoiDlQ0crGwgGkviGZTVK6WkpqGT9s6hxHCAaRXjyA776OiK8/KmI8ycUoSegSv1RsPYDSclG7QKZNeXnZR7NEgdcXSTAh9D6PP6maxeRPDfkV1fRUbvg+QGx7DAdrLp7HqE951pPagzge3oKEXvA22iI4BJOhRnHgElG+G9HiGcF4YQAulajvDfiYzeh+z8LKgTAAvMoyC7EIFPO4bcmXg5hADXfCcDz9iB7PgcUi0C2Qmpow5hPbl+wClSGo74prnXMfisk06Wnrkbu+trIEKg+BCeGxBqyesSzcy02nu93pyVNy4ltzibv37vST72vfcTygmgqArSlti2TeXOE3zg/91GMDvQ2/UND2/Btmw++r/vI9YV51df+jMVc8sonlTIhoe38Lb3rqZiznie/f0GHvnJs3zyR3edUT/HsroduV0FoVWgupZjJR5HdS0iFQ85HkyRDzJBKvYAUrYhZVdaoDUCSBT3ShS1ANu9Giu5EZCkEk8h7U5S0V8hSWKnDiPtRmAy52qC0TSVsumlfPS7d5Bb5KzqhKKgKAp/+9HTTFtUwbr3X0pLXRs//vffDTw3E+dBiMzb38I5w+BxPHDMCmzZRXfXN7HsFlyupWiaY4grig+P521EIz8mHP46Pa95IQS6NoUEkq7Or6Drc/H5b0XTpuF2ryQS+UG6aZ1g8N9G/I2oajE+33uJRf9CLPYwAjde3/V41EvP5i04a2hMNnOg6wj2CIvTLD3E2oLVzAxNo8RbSEgPorwBCO3nAkLA3OnFlJXkUF3XzuMv7qWkMAu/z8mM6xl7ByvreXX7MQDWrpg2QLJAURQuXlTB+s1HqapuZsvuE1x5yaz0uQ63OBpL8uJrh0mlbLQMxaRzsvxcvKiCx1/Yx/rNlSyZN5Gl8ydmzARPpWzMlIX3AkUj+uO0PE7CfwfY7U4xWrvWSf8PfgbcawZwg4QQSG0GIuv7kHwBmXjeKYmCcEJ63usc/aQBzbtAnQjqOAYIXaYhpQ12o2MU4QbPVQhspLnDkTWQFqjZ4LsJ4b3JaUs46cqdzd14/C7c/rsQrsXI2F/AqnS+x73G6Y8+p5+sAI6HTJ2IUMLp75d0NHUS6Yjh9UbJ8pWmV1dpBWOlBMJfR0Z/44TmUpWgTUQEvwz6DCQppwRM7wWlnFBm8nknXIgENU2qNralw5gKuFb2bT8DSKCqrY17N75CTWcnt86Zw61z5wwpUXG6UBSBqioIRaBqKmp6ldDD6Jq2ZBIlkwp7Qz1SSvZuPEjlzhNU7jqBlJJIe5RYd4Lutgg7XthHXVUjulvDiBsEsgMO8TyD2uxouH/PHn60acuwKcb3LFnC7Qvmj/DjU5xwtFAANZ0goCCxSUV/gUzVoPnfC9LCiNybDh3b6fN6FK29fStUO4bmvhTVtcL57LvLCemeBXS3R2iuaSPSEaW5ppX6Y03kFmVRVFFAUUUBT//6JeaumUmkPUpWfoj5l84imOWntb6dyl0nWP/wZqR9fsX93sLokFLy1wMH+fX2HeR4vXzhktVMy+8v3SJwuy/B47kMkChKuJ/+HKhqEapWgabPGjDOVa2CcNbXkTKOwI0QIYRQ8ftvw/ZeA1gI4UOIULqdErKyf4CiDMyAFULD47kcl2sJkAAUlPS7Mhz+JoriS59fSDjrfwZ6vc4zpJQcj1bTkGjKuF9BYUZoCu8qu4kJvvFO8fM3mMfsbEMIQVlpLrdctZCf/mEDjz+/j2jU4OYrF5AV9pKybHbtP8UDj+2gvTPGvBmlXHv53CHr99XLpvDIc3vZd6iWn/x+PYmEyaI5ZWiaSmt7lAef2MHBo/W4XRpWhveM16Nz85ULOVbdwqGqBr7xw6e48pLZXLy4gqyg04/mtgiHqxrYvOsEq5dN4ZarFqL1mxcsyyZppLAsG8u2iSfM3mw/w7To6Iw5KkKKgqo4mYg9GldnitMghzup9cJ7A8J7w6iHC6E4eki+Wx3V7dGO18oReQ+PcISJ7PwyIvBRcM13Jp7AR0cd3rYleeA7j7HobXNYdNkccC1FuDITSwf0x/duhO/dvZ+lLdn3yhE2PLwZCXziB98nkNUv7i8EQi1GhL6Qub3w1wd+VnyO0GfwU6P2pT+slIW0JeoYK83bts2jhw7zXGUVtpT8YNMmrpk+jSzvWdBwEWLY6KLHN5T7oLs0rrh9NVfdfVnfcV4X1YdqKZtezEfuvZ28Uqfki6KIXqPrdBE1TOq7u4ddW0aMMyeG2uYRVNciFHU8VuJFR10eEEo2kMJKHUBhCpaxA4mjb6W4L8JOVaF6rnRkPexOxpw9OgpO7K9hy5M7GTchn6bqFl68/xXWvmclReUF3P6lm3ntsR3sfvkAgbCP8tnjAXjnp6/j+T9tZMfz+1i2bgGLLpuDP+zUhlqwdhZFFUNd9kvXzaN4kpMV5fG7WXblAsL5F24yfLMjYVn87yuvUtvVhRDw+127+e/LLxuYYi50VLVPvd5Z6Sex7Xbi8UfxeN6OquYOaFcIxeGckjVou3tAW33bNVQ1c2FmIVRUNWfI9v7bnPOHHnM+kZIpTkRPkbATGfdPCVZwZ/ltFHsvbNbf+YamKlx56SziCYP7H9nG0+sP8Pwrhwj4PZipFNGY4WjwzSnjnvespLQwa8ic4/O6+Mjtq/n+fS9xsLKB7/ziefxeF7qu0h1NEg56uf2W5WzecZxdB2uG9EEIwdSKAj5511p++ocN7D1Uxx/+toU//G0LihADatypquIokw9qo+pkC397ZhcdXXESCYNo3KCmvgNwPGZf+8GTBPwePG4Nv8/NmuVTWL309dEk3vS+d0UVXHXXpYRyX99LXlEVVt64hOxxIf7+42fPUu9OD1JKDmw6SiKaZPHb5o5p3rWlJJJM9g7ArkSSYRIcThsen5vu9ggn959i3MR8svJDaMOolAshuPi6JTzy46eZuqiC7IIwrfXtTJw1npzCbHIKs9j8xE4uunYR3e1RhBDMXH5mg3vd1CmUhsN0JBK0x+K0xWM8cfgIDZExarYIFeenIXo9qQ75VkH33oQR/SWW8RqKWo6izwChINQSVM86UtFfggihqCWQJu/q3ndiRn+B0fUVABR9NprvdgSvnwg5Z+V05qycnnFfVkGYK+8cGjrJL83hXZ+5LuM5q25alnH7Ze9e2fu3P+Tj8ttGLgdxprClpCMeJ2qa5Pv9eLQ37itKSknEMGiPx8n2egm4hgoAnimMVIpo2sCXErqSgwjNQieTZz6Z3Eg0ch+qVobXe82Q/f+MMG2TukR9xn2a0Lip9BqKvEMXC29UCOHUonS7tCH131y65mwfpA3gcjnbxeDtusZN6xYwZWIB67dUsnXPCdo7YnjdOjMmF3HxogpWLplEUUE449gWQjBzchFf/Og6nnxpP69ur6KlLYrXo7NoThlXrZ3NvBmlVNe2caiqcVhZgplTivjCR9exfW81r2yr4ujxJrojCTRNJTfbz+SJ+SyZO4FFcyYMqf/Z3NrFhi2VxOIDF8Rul0YqZXP8VGvvNlVVKC3Ket2GkxiFDyIB7PaPgLENkfU9hHv50IOk4YSm7HZ6Qhbos5zsjNQBUIshdRKkAfpkhMhBys70tqiTyaZWIBQ/0qp3jrM7nX1qKUIrRUoD2f5RhO8dOEKWOmiTHJfyMC8rK2WxZ8NBrJRNxdwycsZlpbVqWom0x4h1x8kryaGtoYNwXpCSyYUc21uN1++mpb7dcWdOL07zdJy47/5Xj/D3Hz/DJ35wZ6/HybJs6qoaaK1rx+NzUzq1CF/QS9OpVmJdceKROLnF2bTWtZNbnEPhxHyslEVtZSNt9e14gx5KpxThC3lpb+wk1h0nHkkQ6YgSzgsxYWYpiiI4sv0Yz/xmPQhYfvVCsgpClM8uQxvB7Sil5G8HDvLNl9fTbRisnjiR71y1bohA5ZkgGUvy8oOb2PH8XoonFXL13ZeRXRjm5b9sQtNVVtywBKWfLodl2Wx7ahevPLKNZNxg2uIK1r57JeG8IM2nWnn29xs4vq+aYHaAy96zgtkrMhsEo6FnTMv037aU3PnQw7xa7ZSG+dTKFXxk2dKMLwLn3B6itAqYkM5Y6puozH77JaCmx4edPq5vnxB6vzZ72lWAN2dplNeLjniCLz7zDBtPnOSH11/LqokTL3SXhoVtS/5n/QZ+u3Mnn129ijsWLjhrz9SSko/8/RE2HD+B3+XiM6tX8Y45s/sJGZqAMiAzU/aGjE2c8ffWGAPoNLv46oF7qY0PNZ6W5izkw5Pej0c9+3IqzrsnhmnV4tbKEWKo8HAm2NIgaR7FstvQ1ALc2pQB4qFSSlKWk+LfXyNJSomZspASNE0ZUCvUNC0kjsGVqfC4lBLblli27WTYgUPDUBScEloiLU3QiiUjuNSyIX0acL5wMvd6+uaE0eSImk5SSqR0oiR2+m/oa0tRlYx1Vi3bJpUaO91AVZUh2X/DYNgfz+tezkkpIfkqMvksQit3+EzqOIRWDsKL7L7XKcSLgpPt5gUtB1LHIfEUCA/Sqka4VyM910HyRWTieYQ+GykjjgJ38HOOurfsQCaeRKjjkdYphDYD6b+rVx5hMGzL5tThep77/QZu+berWX3zMmxL8tIDmzi+rxrLtBCKILcoi9b6Dj7xw7v4/dcexut3U1CWR+PJFooqCrjlk1fjDXgyfgfAsT0n+ev3nySvJJdYV5ycwiyuvmctT/36Jdoa2ol2xHB5XYRyAyRjBh/61ns5tq+ax3/2HHklOUQ6Yowry+O6D1/B3o2HePwXz1MxpwxN1zix7xT/8p83MW3JJOqqGqk/4WSkHdtzkuJJ45gws5RMK88eCCF425TJ+F0uOhMJlpSWZFQOPxO4fW6uuH0NV9y+ZsD2S2+9OOPxqqqw7OqFLLt64ZB9BWV53PbFG89Kv3p+WML5gOglK4713P7jqcfA7H/PMr9knUkss3qu0+Yb13vyRoAEIkaS3fUNGJZ11jyj5wo2kteqqzEsC+ssp9srwBfWrOaySRWE3G7WlJcPGMGZJmFnnGUeg//MsKRNtznU26wgmBOegUs5O+/DTDCtWloj91EY/jyqCI96vJSSWHI7rZFf4dYm4dGn4dYGekcckn/m94wrg8dfCIFrlMQOIQSq6hg6UppIJIKhJOyosYOEeZD84IcRuDKenwmapo769hPpmqnKaZYgUhUF1XV+Sfxje5MrOU7xXDGMVW5uRegzwPsuhPCC1YJQ8nFWP9IhRftuThPu0jdFmwo+J/4ujPVIYyfCc6WzT+jgvxuBiuz+OjL5IsJ7CyAc2QPPVQhjGzL2BwTmsJehu3Wuvucyju44PrC7SZOpC8uZNH8iD3/vSW742JV8/1/vo73RkX8vm1HCDR9dR/2xRn71pT/TWN3CxAwFDHvw2M+ep2LOBJZdvYCm6lYeuPdRll21ACNhMGflDHxBD68+up0bPrqOn33uD3S2dvP4z59n8oJyllwxj9qqBh787hOsvmV5b//e8alrCGT5+dM3/8aul/YzbckkVt+8nFOH6/AFvdz48XWON2cM9kDA5eKKKW/sgptv4S0gJUdaWmmMRNDOQE37fKO6o5MTHR3npG0hBBOzs5mY/eYtS3S+IKVN3BrKbwrpIQo9484pEdylTWRc6N9RxNjVrqPJzXhd88gL3oNAcH5L1Ui64y+AgKDniiF7A+4V+N1L0tSFf16MyXASoa+O0spMZPIFx9AxjyDca3AMpJ6w3QzHoEpDShuSzyKNbQ5Z1qpNG2Vpd5s6HtJimqjjwWrs6QioExDCg1TCjnZIj19xuL5n6q6u4g/7CGT78QW9BLP9aLpKykyhagpF5QW4vS7C+SFUTSURHV4wTUpJ5a7jNJ5spmrPSQByCrPQPTq6SyMQ9uENeQlk+fCHvCiqIwx5dMcx2ho6OJJO9cwrye5N9x4/zQkPujw6obwgHU2djjWupFeV6QyBwfHqt/AW/tGx8cTJfxg1sy2nTmGk3tKyeqNDIrHk0OfkU7341Qz1V88SYsZ2kuZhdLUEv2c5Iu00iCQ2oCpZJE3n3e91zcellZGyGogkNxFLbkFVc+iIPoTXtQCvawa2TBJLbsewTqEpufjci9GULKS0iCQ24NanEjd2Y8sofvcSFOEnYR7GsrvQ1QJsmcCyIwS9lwCChHGAZMrRZ/Lo0/HoswBJd+JZ2mMPoggvptWESysj4F6BEBrdiRcwrXo8+jR8rgX0mA+WHSFmbMe06tHVYnyuhahKgIRxEEkK02ogZbfj1ibhc80/p8K/5wtjM5xGGFgCkPpUR+xSyXY4SNpkJ5Vbpo8YcqNsZPxBhO8OcK+GxDPI5Av9drfQa3TZbaD2V6E9Gze9r5bP4EuzLZuO5i6kLTESJlbKUb4eCblF2ay4YQlr0h4jelVYRa/lNvge5pXkcvl7VnLx9Yt7z3Gl5edVTc1o8fXEnW1LOiHS3hjwQMExyx5erUQIgSrEmF4WVjrWrAjRq6thpzlDAqeGUf+Ys5QSSzp9E+lzMsWkBx/X05/eGDfpfU6Hh23nQkGmy+j0///p9NVOP6OeawfnUdrpe9L/fvfcl/73vSfmP5b70cP3sjP1Nd3WaO2M+Lz69Rvo7Z8Y5T5Ip+EBfUuYKTbX9GXeWLaNaWWuOScgzb8Yve+DnxX9+jXWsTWYN2dYFltqakmlU6xt2+79OxO0Efra//kOB1WIAXzB00GmMQB9z2gsY6nn/vWklKuKgtJP7+f1tH3uIVCEij3IeHKpLvRzGKZThR9bxmmL/A6vaw6K6tA9Wrp/gRAufK7FmFYDkeQrFIa/AEJDVfwI4UYRHhQliCJcSCnpij9NV/wpfK4FdCf3EDd2kx/8MAiN1sivcWllaSFegWV3kpKtNHZ9F79rMa3GTnyuBSTMA7i0YlxaBTHDqWZhywSdsUcpzv4aulqMoyBvORmbSgiln8NDVUJEk6+QNA/h1ecghIaUFh3RvxAz9+DVZ9GZ+DtJ8wi5gTuIJF+hM/YEAc8qFOGlKfYo40Kfxueed87u+fnC2SFdWM2O90eEQJpgtSDV4hEcQcIRxEwdBGkgE085nqcepCohdj9gQ+oownvzGXWrta6duqpG2hs7OHmwhkNbcimdWjTypaRstj2zB7fXTfXBGvJLc8kfn0s8mqD2aANVu0/Q2dzFwc2VlE4toqi8gGs+cDmP//x5zISJ2+vCtmyWXjlymYOr776M5/6wwSm06taQtmTVTaPIJAgomVLI+gc3s+GvWygYn8uUhRUDyOEHmpr5+KOP0RLLrNQ6r6iQH19/HYExkMM/+9TTPFtZxfUzpvPFS9ZwtLWVn2/dxpZTNfh0naumTeNf5s+jMBggZpo8U1nJ73buoqazkwJ/gBtmzeTGmTPI8Q5c1XUmk9zxl4c41t7Oigll3HvVlahCcKSlhUcOHmJLTS31XV3oqkphMMCa8nIuqShnen4++hgmy3OJlG1T1drK5poa1h8/wfH2djoTSfy6Tmk4zLLx41k7qZxJOTl4tMzk3OcqK/nqCy+R7fXyjbdfQVEwwO937eaxQ4fpSiaZM24c71+0kOVl40FK9jY2ct/2HWw+VYNLVVlYUsydixYyq6BgVAOtrquLTadOsfHESQ41t9AWj6MrCkWhIAuKirlsUgWzxhWMmBEWM03e+8CDVLa1saSkhO9dezW6qlLV2soTh4+ypaaGkx3tpCyboNvNtPx8VpdPZOWEMsaHM2fjICVHW1vZXlvH4ZYWDjQ2cby9nfa4U0vStG0+/uhjwxb9zPF6eer97xs2686WkpZojJrOTjadOsXehkaq2troSCSwpSTkdlMcCjKvsIi1k8qZmpc34j2oj0TYVH2KIy0tHGxq5khLC62xWO8C5buvvMoPNm3OeK4AHrn9X5iQlZVxvwR+vnUbP9q8JeN+XVH4+MUXccfCBRn3jwQpJa2xGLsbGth44iTb6+pojcawbJtcv48ZBQVcPqmCBcXF5Pv9GYUHe7DlVA0f+Nvf0RWFT69awbvmzqUzkWRLTQ3PV1Wxs66e1lgMl6qS7/czu3Ac10ybxuzCcQTPYsbh6UIRAo/qJjLIO3iuF2Nu3UluiSZeG/S9Cn73MnIDd2Ckqmno/AaW3YFLm0jQcznR5GZcWhnh3qxIm7bIHykIfQy/+yKM1EnqOr7seHi08YDAo08l2/+unqsibuxCFQHyQh+kuuUesv3vpD16P0bqJB59FiHvlaSsJiQG0cQrJM2j6GoJAfdKIomNuLRSwt5r6b+Cdwy9emLJvnFqywSd8ScoDP8HXtcc4sY+6ju/Spb/FgA0NZf80EcRKJhWHXFz31uGE4DERpr7QfE7StgkwG5HBP8TlCxHjFIZaKwIFAh8HJKvguxA+N/vGFw9cVPXMlACYLchAh9D6FOQ0kJ4bwQ13ZYyzvk8QqZCa307B7ccZdbF0xACDm2pJLc4mzmrpuPxu8kZl8Wqm5ahuzTWvnsFWflhdLfOzOVTMA2T4smFLLp8LsFsPx3NXVTuPE48kmDB2tkc21uNpqsUlRew8LI5+IJeju48jmmkmDirFG/Aw6LL55BTlIXu1lm6bj5un5tLb11BMCfAsivnE8rxU7nrBMmEQcWcMnS3Tvns8fiC3l6S3ayLpvaGCoUQLFu3AE1TaapuIRD2MVhIyZaSmGn0pjIPRtw0e1f6oyGRTok+0tLKsbY2/uu559nT0Ni7/xfbttESi/KZVat4/PBh/u/VV+lMOH1tjcU5tmEjrdEY/3rx8gGEdCklMdMkahgcbWmlO5nk2aOV/GzrNmq7ugb0oSESYVd9Aw/vP8Cdixbynvnz0C7QCzhqGPz1wEF+u2MnVW1tA/a1x+PUpI2UB/ft4+bZs7hr8aKMBmrKtokYBoZlUd/dzSMHD/Kr7Tt6PQ4vHDvG0dZWvnft1Xh1nS8+/SwHm5t7zz/V2cmx1ja+c/WVVORk1sgxLIsXq45x344dbKupHeKBbIhE2FlXz8P793PdjOnctXgxJaHgiMZT1DA42tpK1DB46fgJfrJ5CycHcXzaEwmqOzt5vqqKxSXFfHrVShYWFw/1OgI/3bKVvx04mPH7wBl/w8E9goCrlJLnK6v44+497KqvH5rKj/O8TnZ08Fr1Kf68dy/XTJ/Gv624mLAncxLIYwcP8a0NG4f1ChmWhTGMdwwY0ZsEjqE43G9WU5RhPW8jQUrJnoYGfrJ5KxtOnnR++/3QHItxqLmFJw4dZun4Uj64dAnLx48fdgxY0umjIgRVre00RaJ895VXeezw4SFtN0Wj7G9q4snDR7hx1kw+ftFysjyeC2I8qUIlpAWIpAYWGjbtFKZ9/kOtQujo6niE0BDChWOcWGkvbu9RvffKsiPYMoKuFjnaWUoYgQvL7k7PmAKXVo4QA6dzRfGjpGsQOufo2DJFMnWU1siv0ZR8FOHHlt1IjPT3D0hBGPV52bILKU00NQ8hVDQ1F6SNbTsLd5dW3suHUoQPKcdeJ/CNjNfvcbKbwViPCH8boWSB3Yzs+m+QbSByEd6rh54jBEKblC7dMhDOuHGB57oBpDghNPBe1fdZLRjwOROmLqpg6qKKIdvzS/tE4ZanM7xW3eh4ewQwriyPi69bPOCc7IIw694/VBMHHM7U7BXTmL1i2oDtc1fP6P17XJkTblx5w5LebXNWzWDOqhkDzimbXkLZ9D6l8GmLB94jX8g7rNYOwOTcHH5x0400R6K0JxK0xWK8Wl3NxhMnzzjz51hbG3/cvYeT7R0sKi4mZppUtrZi2jZPHD7CvKIifrJ5C1LC0tISupIGla2tJC2Lv+zdy82zZzIpJyfjj7C2q4u/7T/AT7ZsJZlKURgIUBoO4dNdNEQi1Hd3051Mcqqzk/979TU0ReGdc+ecV/Jwj6H30y1b+e2OnXQbBrqiEHS7KcvKIuzx0JVIcKqzk85EgtquLn66ZSutsRifX7Ma3zBZjF3JJI8fPsy2mloqcnLI8/nY39RId9KgpquLX23bgSIEJ9rbmZaXR7bXw77GJiKGwcHmZh49eIiPXbR8iFfGsm3+fuAg396wkZZYDFUI/C4XpeEweX4fyVSKE+0ddMTjdCQS/Gn3Hqra2vjfa64mZxRh1IZIhMcOHeaHmzbTlUwS9ngoDAQYFwgQNU1OdXTQFo+Tsm221tTyrQ0b+doVb6MiO3vA8xfApRXlFPj7RGQNy+KBvfuImSaKELx9yhTGh0MZ++FzuUYcA11Gko0nTyKlxKNpuDWNPJ+PwmAAVSjUd3dT391NNK3D9Kfde/BpOv++LUtJ8QAAIABJREFUakVGL9e8okLuWbK4NxSVsm2eqaykptMx9JePH8/cwuG0gARZwxhkPffi1jlzWFZaSls8TlssTnsizh927aZxrNpjg2BLyabqU3ztpZc53NyMBHy6Tq7PR2kohBCChu5umqJRoobBhhMnOdnRwZcuvZQ15ROH9fT1tL2/qYlvb9zIIwcPoQpBvt/HxKxsvLpOUzRKTWcnUcOgK5l07q2u86mVKy6IHrcmNPLdudQlGgdsj6VixKzMnvlzC3FaPB9F+FGVEEaq2uFC2a1AClXp82CKUSksfXc+ltyKlCZ5wbsBQXfiuYF9Q8W2k4CVNqT6e/kHziGKCCKEnuY3jcO0GhDChZpWih8u4/0fHa//qpQsUAqR8QdAyUFap0ApAOUfR1DszQSvrjOroAD6iQC7NY3Np2qwzpDI2haP8+Kx43xz3dtZO6mCqGHwjZfX89C+/cRMk/95eT35fj/3Xn0ly0pLiRgGX3z6WZ4+epT2RIKtNbVMGsEzcu/GVygKBblz0cXcOHMmAbcLgTM57aqv596Nr7CtppaORIJfbt/OjIJ85hcVndfV62OHDvPzrdswLIs8n493z5vLrXPmMC4YSFdlgqZIhD/t3stvdu6kO5nkr/sPUJGdzW3z52UscWNYFo8ePMRt8+fxudWr8Og6zxyt5IvPPEtnIsHTR4+iCMGHli3l7sWLcKkqfztwkP9+4UUihsGehkba4nHy/QMr12+vq+ObL6+nI5HAo2ncMnsW75k3j8m5OQ4vBehKJHji8BF+vHkLdd3dvFZ9iu+9+hqfW71qRLkKy7b55voNuBSF62fO4J4li5mUk4OabrctFudnW7fy5z17iRgG22pqebayinsWL+rlc/Xg6mnTuHpa32KjO5nkicNHiJkmqhC8Y84sVp+BjpMQglUTJrB2UgVeTeeSinIWlxRTFAz2hqJM22ZXXT3/9+prbDp1ipRt89jhw1w9fRqzxg1V0F5aWsrS0r7M2ngqRWVrW6/hdGlFOXcuXnRGhoFIGx75/j5BVCnhxapjZ2w41XZ28o2XXuZQczOKEMwvLOTuJYtYU16OOx3eNC2LPQ0N/HjTFl6prqa6o5Nvrd9Ajs/LvMLCEX9fW2tq2FYrKA4FuXvxYq6aNpVsr9fxnUjJjro6vvfqa2yqPoVhWdy/Zy83zpo57HtgKCQpqwPTakGSwqNXoAyX1T0KXIrOeF8puzsPDNjemeqmNdnWy907m7DsLmLJbcTNvRhWLZ3xx/Hqs/G5h0qxjA6VHP97aY/9hbi5FzNVi8+9DF09sznWpZXRlXiB9uiDWHYbgwm1XtdsOqIP0yoU3PoUAu4VmFY7seQ2oslNJM3jdMYfxeuah1ubRJbvetoifyCqbyJpVhH2XTOAG/VmxFlYtrsRwU8itJkgshCuFYjAx+kpsHvacF2M8F7DWHV3zjau+8gVTFlYfkG++2xBpAmZPf/OBuYVFrKmfCKaohD2eLh2+rRefkncNLl88iSWlpaipvevnVTRO0kdaWkZsW2vrnP34sW8e95cQh53L6FUV1UWl5Tw2dWrmJzreAlPtnfwbGXViETcs42maJRfbd+OYVmoQvCBpUv40NIlFIWCvX1VhKAwGORDy5Zwy+xZKEIQM00eOXiIxkhk2MLDYY+H2+bNw6vrKEKwsLiYeYVO6QfDsigOBnnX3Dl4dR1VUZhfVNSbot4YidCVGOj67kwk+PX2HXQmnPTrG2bO4NOrVjItP6+XTK0IQZbXy61z5zoeK+GUNnih6hh7GxpHLZIspWTd1Cl8cc1qpubm9hKfFSHI9fv48LKlrC6f2GtQbjh+AtMa+LwGj9HMYzXzMWMZ2zk+H/+19lK+dsXlXD9jOqXhcO/1CyFwqSpLx5fy+TWresNz7fE4+5saM7Y35LuHHtDLmTndvmZq//W8/qSUPLh/PwfS4d0JWVl85bK1XDFlSu84U4TArWksLinhvy5by7LxjlF4tLWV+3fvwRzl9yUBl6ryudWruG3+PHJ9vt7fgqYoLCkt5QtrVhNwO8ZO1DB47WT1mPpu2RGaI3/mWOunONb6SY63fgrTakrvt4kkd9HYfR+W3TVKaw40oTHBX4pbGWh4WdLiaOQYqQwZd2cHCi61jPzgB1GVED3TbW7wTrz6bKdvSg55wbvQ+hlBWb4bCbj7lPqFEAS9l5EXuBuXVk7Ydy25gX9BUbwIVPKCH8CtD5SbcWkTyQ3cgUCnIPRxFMVPyHc1fvcifO6l5Ac/jKbmE/RcSlHWl/Hqc/u+y7OW3ODdaGohmpID9IxtFb9rKTn+W3HqIjqesyzfTeQE3oNLm0hO4N1k+W5ECI2g5xLCvj71+rDvWoKegZp/I0Gmk07GUrS9/7FjOf714nV7nIQQThHa11GIdkB72sSz0s6ZYvbF00Y/6J8MAlhYUtS7UgWYNW4cLlUlZproqsrFZWUDQieT0t4NS0oaukdeNZdnZ3PdjOm4MnhlhBDMKyzkymlTObFpM6Zt8/ihw3x42dLXXah4LJBS8sThI5zqcDS+ZhYU8O65c/AM45XxaBrXTJ/GS8eOc7y9nb2NjexrbKIklDnkNDUvl1y/r3dizfJ6KM/JZv2JEwAsKS0l5O574Wd5Pb2eic5Egniqj1sipWR7bR3bauuQQGkoxPsXLRw2EUARcOmkChbsL2JbbR11XV28Wl3NguKiEe9tcTDIHYsWOh6GQQaBALI8HtZWVPDy8RNEDYMDTU2kbIvzKQCqKQrFw9zz/qjIyWFJSQnPVVWRSKVojETPiQfifKK2q4snDh8BnOdx56KFzBqXOZFACEFZVpj3L1rI/sYmOhIJHj98hDsXL2JqXuYadT24Zvo01pSXZySUC2Bafj5LS0t4vuoYpmVxqLl51HsrZZKajm/TEv0zivADKVJ2t1OdIt2yaTVT1/kDVCVEnn/0xCEhBBX+iRR7CzkePTlg39a2XVxb9HbyPSNf6+lCVULp1P+h8Lv7qBaK4hvwWQiB1zV7yDmKcOFzL8THQI+VECoBz9BqHpqag5auERjwOEaY1zWzXx+WDDmnf58CnoEixpqaT8g7VNep7xqGJjYNNua8rlnDfmcm3F+1i9poJzdMnM3k8OjPZ0dLLa82nmBt8WRm5ZzbuoNvfJW5t3DBIYSgNDRQ9TbocvVOrqoQTMgemDEUcrt7X5D9J/dMmF9UNCwpF5zU56WlJb2r1/rubk51dp72dZwJYqbJjro6kmly7mWTKwYYkIMhhGB8OExxyPG42lKyI23IZMK4QGCAwagripPdlf5clhUewDdxq2pfqMW2BnjeUrbNvsZGWtMZlYtKihkXCAw7UQkhCLpczChwQlMSJyszZo78vKbk5TIjP3/EdseHw3jS6sYx0ySZOn1y8/mAY2D1Pau4af7D6EgNh70NjbRGnTEQ8ri5dFLFiMaKEIKlpaUUBp37EE+ZrD9+YsTv8Ok6K8rKhuXvgZPN1uMplkC3YYzKs+xObqUl+gBB90WU536L/MB7h/TVpRWjK7l0DcpWGwmFngLmhGegDJryOsxOnml8GUu+McfnPzNeqqviwWN7qIuN7lkUQnCoo4kf7X+VZ2qOnPO+vWU4nSFMI8XP/r+HqT7ScNrnWimL+775KK0NfZO/aaT44Rf/wudv/T7PP7QVe1Bo43y5IDNB4Hg6BmwTAj2d+SeEINszMKbdf7IfHKYZjMm5o/MeyrOz8aYNBgkcaR45/He20ByNUtcv068sHCZqmHQlk8P+s6XErfYZV6c6O4d9dgG3e8C96gl19HqgPJ4BK/qekBiAZQ8cE8lUisP9wqIFgQCWbY/Y10Qqhb/f5NcYiYyYHQYwq2DciORhcDxvPf2UQMK6MEKRPb+blGWRSKV6swMjhkEkmSRqGAOSTC/k7+xsQErJsfZ2IukMvYqcHIJjkB7xu1xMzUsbORJ21dePeB9yfD6K0yTzkdDfsEqNonUF0BF/Fl3Npyj0YcKeS3Bl4PFoShaqGiaZOjViW/2hCIXLC1aT4xoqCbGxZRM72vdgSxv5D282//PCr+noikJN5Nyo+ffHWalV19IeZX+lU0AxK+Rl1uSijLV0+p+z48ApuqNJFEUwdWIBhXkju9VTlkVDSzdtHVEi8SRmykYRTnVnv9dFdshHfk4gY62e4WDbkrbOKI2t3XRFE5imhaapBH1u8nMCFOQEMxZEBJC2pPpoA/ERVMWHgwQCIS+q3jf5aLrKPf91Aw/95AVa6zuG/HxPVTbi9bnJL7kwJRg8WobaWPSINIJn0H0fa6BDALk+36jH5fp8vZ4ZKeWwOlVnG91Jo5cvBPDpJ58e07X1Tz/vSMSHPc6lqigMDnf1fXbr2sAaZQx/b03bprFfWPQXW7fxq23bR+9rv9EWSSZHndxKw2PgL4re/zi4APORYVlUd3RwuLmFg83NVLW20RSN0JVMEjNMkpZFMpUaUfbgHw0p26Y9Hu/17BQHg6MauT3orzPVFIliSTms9EfQ5SLsGZ2sfbohz2SqFk3Jxq1PGN6jiepkfp1manueO5dbxl/H7048QLRfNl2H2ckfTj6IRLIoex7qP5iytUwLBttSog2q82ZLSYfRTdRKkqX7CWjnTin9QkMVCgJBpzm0vM7ZxlkhHeyvrOML//soAItmjedr/3ot4eDwrHrLlvzwT+s5eKwRt0vjs3dexlWrh8Z1wZkkT9S18cT6/ew+VEtjaxedEcfIEYrA49II+j0U5AQoL8llwYxSLlk6FfcIat9SSiKxJM+8cpD126uoaeigvTuGYaTQNZVw0EtJQZiLF0xi3coZ5ISdiT0TeRXBsCuz/oraPZ+llKiqwi0fvmzIsaqqogwqkthz7osPb2PG4nLyirMGnHO+oI1Y3kVk5DmMFa4RQl+936+qAypajxZOOlswLYtEvzDTaHo8mTCSIaIKp/r4cFDGoKXSA1tKov3ui4TTlqBISXtET4MAvProHowLCSkl7fEEv925kxerjnGktXVUL9qbBZZtkzD7DEGPNrRQ63Don01p2hZx0yTozmwcaYpyTjiGquLFtK1+nKaBkFKSsjux7M60UvbYIYRgSfYCamJ1PN3wIqbs+600Jpv53YkHaDc6WJm3HN85LMVy1iFhV0cV29uOclPpSnJcjh5byrZ4rfUAT9RtpsOIUuTN4baJl1HhP3sZyYOV+C8UbClpTcZIWin082D4vqFFFqSUbNl7ku/85gVqGzuwbImqOBWgvR4dW0oSRopovIuGli72Hq3jwLEGViycNKzhJKXkWE0LP75/I9v2V5M0UgghcLs03G4d27JpauumsbWbfZX1vLb7GB+/bQ1TJwxNUTYNkxf/uo0//u9T+IIebrz7UqbMHc8z92+iqyPGLR9aC8BffvQ8WXkBrrh1OYd2nuSP332SaFeCT333NkorhrbbH/Fokp9+5WF2vHyIzc/t4+Gfvciyy2dx/V2XjDjhnm2cy0KYY5nUnGybvgn9fBDDwfGm9RiFqiJYOWHCkPT/0TAhK2sEPtDr7uIA9KT8KwLmFhb2ckzGihyvF98ohtFgWYE3GtricT7z5FO8erIa07bxahoVOdnMKyxkRn4+44IBsrxefLqOKgS/3r6TRw4dutDdPitQFGXAAiNlW2MWvE31+x0qQkEfwVN1NjN2+yPgXkpX4jW6E5tw+a8ftFdiywgd8WeIp46TH7jttNv3qh5uKr0aIeDZhpdJ2H1eqxajjT9WP8SrLVtZV7SWacHJ+FUfLuXCqZ6PBTaSZ+q3sau9iiuLlgBBpJQcjdTygyN/I24lCWg+qmONNCc7+NrcOwnpp/cOGw4n69ooyA3i8wx9Z0gJ3dEE3dEEqqqQm+UfNhIlpSSWMomm+gzmpJXCkjYdyThN8eETjGwpqY6089CxPaSkPSYi+evFG9pwau2I8v0/vEx1fTtCwMKZ45k3rYTCvBBul4ZpWjS1dVPT2MGxUy0cr21lxYKKEb1NzW0R/t8vn2PPkToUIZg6oYAFM0uZWJKLx6URT5hUnWphy96TnGpoZ/v+U3zrV8/z1Y9fQ1H+wHBid0eMULafG+++lA3/P3vnHZ7VdaX73ylfr/rUewEJhOi9GgPGvcV2bMdxmtMmfW4myWQmN5nJ5N5MksnMxPGkF08cO3biOI4btnFswAZM7yCQhHpF/evlnLPvH58kEKqAwHhu3ufh4dF32j5l7732Wu9614sHef7X2/j89+4nEooRDpwNz4QCESwDdejKFxbxjV99nC/f/TD6JAizNoeFT3/rHv7ji0+w5tYFLLtuNrIiXVGj6XJCAIHYxK7VZAgp+bwkSRqWaXY5YVXVszwNAQ8tWsSqwoKrciBVJBn3QPhEILFx+nQ+uXTJVdnWy4WErvPYgYNDRpPLYuHzK5Zze/lMUu32Ec8ipmm4JhFyerdAPSe5QMBQiZnJoPuc8LfdZBo3CeJywWe/ma7g07T0/4C43k5cawEEgdg+QvGjBKK76Q7/GbtpBin2Gy/4/JIkYVNsvDfvDnwmH692vEF79MzQ9riRoCp4mprqOnJtWZS5plPkyCfdkorX5MGpOrEO1LiTUS7bOCwhIUuTC7EKITgVaKLYmTUUihNC8FzzDoJahE9Nv41rMubxx6ZtvNiyi/091azLHL8k2GTxX7/dxo3XzCLd5yIaS5CfnUJWmhtZlujqDfKT373FrsN1uOwW3nfbYm5bN2eoKsawe0DwctNJHq/aN/RbfaCXsJbg4aNv8euTo5czAojqOi2hfkJanBSLjRvyy6bk3sbDVW04HTrZQmtnkkBdXpLFP378erLT3cOKXQohiMQSdPUEaWzvpTDbN2zFdS4Sms4TL+3jaHUrACvnF/OZB64hN9M7ZAkLAfGExummTr71k1eob+2hsradZ/9yiE/cu3rYud1eB7OXTSMz38e8VaXs/ssx9MQoxtB549aFdDZJklDNKpIsoaoKJstV/couCpPJkGsLBodlZuWNoSg91fBYraTabVR3J8NejX19rCwseIdUxsaHWVXI93jY3dSMGJCBiGnamNIJ/xPRHgyyq6l5SIfozlnlvH/+vDGNAEOIMUudvBshSxJ5bjdWk4lIIkFjX/+EmkyQHEcHywhJQIkv5R0xuFXZR0HK12nq+w5t/h8NtMague97CBHHEFHs5gryvf8woDE0OSSLFAsMYWAgCOthsmzpZFsz6Yh2jiCFGxg0RVppirRiklQcqgO7YsOiWDBJKoo8yE28PM9oddoyrs1YNen9e+NB5nqnYVWSnp+OaC97e04xx1vCyvTZuE12VqfP4aXW3TSFOyc42+Sh6QY///2OZGhQ08lIdfGxe1eycFY+e47Uc7K2na9+4nqqGzr50+bDVEzPprRotCiLRJbdhddi51B3K+FEHF0k2Zf1gd4J50wZiXSrg09VrGSm9/KLb1/Vs3B3XxB9ICOrJD+NzDT3iArhkiRht5rJz04hPztl6LfzIYTgaFUrb+6rQQgoyE7hCx9cR27G8CKkkgQWs0p5SRafvG81X3/kRTTNYPuBWjasmMGMorMvJVkNfGS7JVnC0MXQTsH+ML7Mi5/ok91T+h+b8XGwtY24po3JdRJCcKi1bShTyGYyUZ4+fohzqpDhdFKWlsae5hYMIXj9dC13z654R1bjE8GqqszPzuL5ypPEdZ39ra10hsNDJTaudiQFFM/+bYgLFznti0ToCoWGzre+pGRUfbBBxDSNUxeRoSmd39YrKMg6EWZnZZJitRJJJGgYIMcvzc8b95i6nl5qupOGkyxJrCy4MP7QVEGSZJyWJZRlPEpf+DX80R0k9E4EBqqSituyDJ/91mTttQv4plsibezpOUBDuJnmcCvd8R40oU8qky4hNPoS/fQlrowECkCpa2SpsPEgS9IQncIQgjc7jxA3NFaklpNicgKQYk4mdYT1qSVPu51WHrhtCSluG5u3V/LE8/uomJ5N25l+ivPTWL1oGisWFHPgWCPHq9tGNZwkYGVmEcsyCgjEY+zpbOKHR9+iKdjHxrwyCl1jJ0WpkkyW3cXSjAJyHO4RyTaXA1ff6H8OfB5H0q2X0DlU2Uxdczelhemj7jtRJ9INweGqFs70BABYtaCE9JTxNW6m56eRneahqb2X9i4/TW29lBWeFZIL9IY4uquGrPxUDm2vIjPPh2JSSElzcWh7Fe2N3QT6wlQdbqSg7Kwg1+B8MJKEKxCGQAz62QfbIkvY3VYaq9opX1yMyaxid74zBTMvB2p7ejnc3s6SvNEH975olB3nFCldlJMzFJK63FBlmfXTpvHsiUoCsRi7m5vY3tDAhmkj6yy+05AlifnZORR6vVR3d3Oqs5NNp6r4xJLFEx98FcCqqkNZQQbiosqNCM52ncn4A/Y0t1DT3X3B1zGfo6cFSU/X1YLS1FTmZGXSGghgCMGTR44wNytzTM9jXNfZVFVFTyRJL8jzeFiUOzWCxhcDSZJQJQ9pzntIc96NIRKAQJLMF821PBmo5unm56e2oVcJJCDT6qM10kVEj+FPhNnVVYnX5GSRr2xonojryfFTmWQIcDJQZImb11awfnkyPGa3mfn+r15HNwSabmBSk+FMVZHJyfTQ6x89G3pQjV+WFHxWOzfkz2B7Wx29sQh3Fs/mmuwLMyQvN65qHafFswvIyUgKLzZ39PGPDz/Pz/6wg4bWHkKROIYxeQ9MJBqnuv4MhiFQVRmv205Pf4j2Lv+Y//qDUZz25AQdiSXo7DmndIYE0+fmYzIr/PjrT1NX2cIdH12LyayycO1MCsqy+NHXnublJ3ay8sa52B1WEnGNpx7ZzD995GcE+yP8+Gt/5OEvP4mW0Dm2+zTf+fRv2L7pEDs2HeLbf/NrDm4/lbyUJHHTAyupPtrEf37xd+x+7fg7kt59udAZCvGzPfs43d0zLANNDIRRnj1+gi21dQjAZlK5Y9boKuOXC8vz87i2OFlCJJLQ+Netb7LpVBX90SiacTYLTZDMoAsnEvSEwxxsbWVzdfUVywCEpDjlbQMq7LoQ/HzPXh47eIiuUJiErg9razIDK0FvJEJNdzd/PnGCnisk8zAaZEka0hLSDcFr1afpDIVGLDAEyVX1aNl/HqsVnz2Z0asLwY7GRmLnyQ0IIYhqGrsam/j+W9snFcoara3TfL6hxIEtp2tp8ftHjEnjtfVywaKqfGTRoiEe4OunT/PogQP0RiLD+E6D/euVqioeP3SYuK5jURTeP38uKbaxBWmnCskU+sQE/zSSpoGMENqwbeKylUp5d0GSZFalVXC0r47vn3ya71Y+xQl/A+sy55NjO5sc0hLpQiDwDnigpgJOh5VoTEPTkmNLNKYRicbp6g0SjibQz+lbsiwPS/AZ956AGd70qzYR5ar2OHldNr7w/mt5+PGt1DV309zex3//eRfPvHaQ5XOLWVSRJIvnZXpRx9GNAojGNVrOJF2tmmbwk6fe4idPvXVB7QmEY+iGQJbBZFb5X99/YNT9HG4bH/77W0fddt9nN3LfZzeO+L1iaQkVS8e2qqfNzuNrP3to6O+xwpFxXSemJfVpYro2UEYiODRgRhIJanp68FqtWAaqxg+qUY9Xbf5yosSXwpbaWlr9fu6cVU6+14NVVemLRNnV1MxzJ06QMAxkSeKG0lLWFBWNuu4UJEMm8QGxw7imE9U1ookE4cRZHktnKMTpnh4siopFTd77oAdhNFkFVZb50po1dARD7Gtpoa63l7/b9DIrCvJZkpdLmt2BKsvEDZ3ecIS63l5OdnZysrOLG0qnsyw/H64Qz0iVZR5atJCarm42VVXRF43y7a3beL6yklWFheS63ZhVBU1PCmM29fdx4kwnlWc6KU5JYVFOLr6JZbUuG26ZMYM36+vRDcHOxkb+92t/4cbSUlJsNgSCmKYRiicN0bsqZo04PtvpZGFODkfa2tGF4LcHD2FWFJbk5eK2WNEMne5whN1NTbx0qopALMa8rCyOdnRcsNTEddOn8fihQwRicZr8fr646WXuKC8nx5VMB4/rOqF4nIiW4I7ychxjCFHqhjGkKTXYd6NaYkhxXwjBmVCImu7uYf118Lsd7Zudn53FZ1cs57/e3oU/FuPhHW+zv6WV9dOmke5I1pXrCUfY39LKCydPEtU0FFnmtvKZ3DFr1iXJi0wWgjht/p+cdcFfIExKBhmuB6e4Ve8+SBJcn7WYhlAH+3qqUCSZFWmzuCtv9RDBXBcGR/pqkZEpcWZP2bWXzSvisWd3E40ncDus7DxQi0lV+Nefvoo/GMVmMdHrD6MqCs3tvWNGjEbD3NRsKnxZuExXX/LGVW04SZLEwln5fOPTN/HKWyd4cdsxguEYgVCM194+yZv7aijM8bGgPI/b18+hKCcVSRrdqNB1g1Dk7OR5vj7fZKAbxpCn50qHySa6niEEb9XX89iBQ8R1nbiukxj4vzuc9DYA1Pf28dVXNmNRVUyKjFlRMMkKmU4nX16zinTn1K1GJgMJ+NSyZTx24CBH2tv5t7e2YzeZhurgDYoTSiQLDX962TJ8o9RIg2Tm3W8OHGR/S+uw+4/r+jAC+qZTVexrbsGkKJiVpB6NSVZYWVjAQ4sWjhAMlKRkFfhvrF/Hv2/fzpt19cR1nW119Wyrq0eRJRRJRjOMEZPvOxFOtaoqX7pmNQ6ziT+fqCSiaRxqa+dQWzvygDK5bhgjNJ5kSXqnamsP4ZriIq4tLuGN2lrius5fak6zo74Bu9kMiKQxrGnkezy8p2LWiOaaVZX3zZvLzoZGKjs7iWoaP929hz8cteM0m9EGlNT7o1FMssxHFi9kXlYWX3/t9aFQ1WRRkZHB3RUVPHbwEMZAncCj7R3JrDZJGtAA07AoChtKpo1qOAVjcX66Zw/HOjpI6Maw77ahL6mArAvB8ycqebuhceCbVYb67sbp07l7dsUID6xJUXjv7Ap0w+CRt3cRTiTYUlvHW/UNA+1jSAQUku8iMuyMAAAgAElEQVT+ptJSPr9yRTL78IKexMXBEDHa+n+MYDTP0aAxdX7AdfB3GYd53l8NJ5L813SLh09Nv42mcGcyQcCejuccyQEhBAt9pRQ7syh3Tx1/7Zol02ls7WXT1uOEIjEWVhTwkXtW0NTaSyyhceRUC//08EvIskxPf4jZZTmTPvdMbwb/e+F1pFrfwZXcGHjHDCdtgjIcg1AUmdKCdIrvX8PdG+fz+u4qth84TXN7L/2BKFUNZ6hp7OTVHZW87+ZF3L5uLh7X6PyfQQKnxayyZtF0inMvTONm7owcZOXqdB0CNPf72VpXN+4+UU2jehROR7bLRTgxslDjlUCuy8UPb7uFn+/Zx1sN9fSEI0m1bknCaTaT4XSwprCITyxdQqbTMaYxktB1jrR3DBXIHQvd4fCw1OtBuK2WMSOgsiQxMz2Nh2+9hecrT/LCyZM09fXTF40OTXayLONQVZwWM16rjdmZmbx3zuwxPQ2XC5IkkeNy8fX161g/LekVqevtpSccIaZpybZKEjZVxWE247VaKUxJ4Z7ZFWRcoEbVVLfbZ7PxL9dtoHCfhzdqa+kOR4gMhD4VWcaiKKTYbOR7PGOep8jr5ZHbbuHht3dxsKWV7kiE7nCYrlAIs6LgtJhZkJ3N++bN5eYZZbT6A+S4XRdsOKmyzBdWriTL5eK5E5W0BQKE4nF6IxFkWcYsy7gtFjKdzjHVu+OGzoHWNnY3jV8+pCscHlUtv8DrTS7oRgldu61WHlq8iLlZmfx6/0FOdXXSE44QiCW1i8yKQqbTQYHXy10Vs7i5rAzHOXUSLzdkyUZx2n8My7CRgL7oNvyRN3FY5uK0LMEkp4Kkouk9hOKHCcb247VdR47nc1eopVc/JEnCZ3Hjs4yehKRIMgu80xFMrXacw2bmY+9dwYfesxQhQFVlTKpCxfRsQLB26XSefHEf3X1hPnDHUspGzagbHRZFJd85skTO1YB3zHAKRyafAixJEiZVITfTywdvX8od6+dw5FQrB0408ea+Glo7++kLRPj1s7vwB6N84t5VI0qvKLKE3ZacwGRJYtWCYm5cPdLV/26FBMzLzuLvVk8+hfVcOC1mvLbhau+3l8+kIiMDWZLIPM8TJQEfX7KYQCyGRR0ZLvBYrfztqpXohkHuBFXqw1qCPI+Hr6+/lpOdXdR0d9M7MIl5bTYqMjIo8aVMKHppM5m4c1Y587MvrjJ2aWrquCEKSZJwmM3cP3cON88oo6qri1Nd1dT2bcYfayfbuZpCzzKyXS4KvC4keQeZdueIEGhZWhqfXbGcmKYxPzt7xKS6oiAfVZERQlCeMdy1bVIUbp05k5np6dhMJrJdoz9bSZKwqCrrSopZnp9PbW8PNd099EejRBMJVEVJGqUOB0UpKeR53GM+X5Oi8OGFC+iJRJAG2j8RMp1O/mbZEsLxBLIkDZH5+3uCPPvYTs4n6WXkpLD25rk4nFayXE6+eu1a3lMxi5rubrrDYeK6gUVRsKsmmg62EDzq57GmzcOcEcvXlTNjbj6SJFHs8/Gv12/kZGcX1d1d9EeTNQQdZhPZThezszKHvulsl5OPLl5Mc38/C3Imr6osDdzXxxYv4vrS6RzvOENnKERU0zDJMnazmUyng1y3e0Stx0HYVJX75sxmdeHFeQHmZGUOCVVWHmrk8O7TlM3JY+6SElSTgirLLC8oYE5WFtVd3VR3dxMYqKfosljI9biZlZ4xxAsbDwVe79D4kuF04h2nMDckX83y/LyhY6b5fMP6giyZSLUPpzSEYknDKNP9EJmuDyFJ1mGEcCE0ukLP0B74Ob7ETZiUyS1+ixwF3JFz06T2vRpQ7ppaLaLBb3qqjWJJSsrknE+VkQZCOj6Pg8+8f+0UX/WdhzQBaXHCoL8Qgm37aviH/0xmLCyalc//+fyteN1ju9f8wSh3/+0vCYZjE5ZcGQ+xeIKmtj7+8OoBXt1RSTyhY7ea+Nk/v4/pBcMnnP5AhG/+5GXePlSHJMEn713Ng7cuGVWM66+4vOiNRLjvyd9zuqcHCfj5e+5k/bRLz5oQQhCJJtB1A6fDctnDZIaIc7rv1ySMflKtS3GYCnCYkpXodRHneNe/UJbyOazqpemKGCJBwghglj1I77I6Wuejpb6LL9z3Y3TdwDAEWkLH0A1mLSzkH/79ftIyx/YkAWgJncd++BovPrUbYRjouiART4Z6Pv3127n1/mXvumxTIQTxmIaiyhNyNcdCOBjl3//xj+zacpJZ8wv4++/fN+GzvBrR2PstAtHdTEv7EVZT4aj7xLV2arv/FrOaR0nq9yd13ndbAd8LEcCcLIQQ1IXasSgmcm1To65tCEFnd4Dj1W109YZGUBWsFpU7Nsy9pD6pC4NgIkZ1fxdHuttoCfUT0RLYVBO5Dg9zU7MpdafhNFumNGOQcezMKfE4Oc6RW4/GNcKxBOM52E6cbiOeuPSMCIvZxLSCNL7w4LU0tvVy+FQL4WiCI1WtIwwnu81MeXEmuw7XDxUZvmP9XLzj1NT7K64eJBI6kpQM3Y7VCWNxjUef3EF9czff+dpdKJc5rKqLGGGtkVzn7aRalwFnV3YyJuakfeuSryEQhLUWmgPPUuL5CGbl6nRdTxbp2V6+9bMPE/RH6OsOsuXFwxx8u2bSxyuqzG0PLGfxmjL8fWE62/v5zQ82E4teuczFqUZPZ4AnfvQ6qzZWsGj1xXkaZEXG7rSiqjIur/2iDbB3GjGtAUkyochjL7wlyYIkWYgm6id93qk2Qt6teKTqWUpdeXy69PYpOV9NQydf/8GLhCIxfB7HCI+922nljg1zL/r8YS3O683V/KZqH4e6WocVJB+EDMxNzeHDM5awIbcUxxWopTklhpPbacViVonFNbp6g7R19pOdNlJ0TwhBPKGzdW81CW18jtO5nrDxrFVJSobg0lPOhpL0UfhTqiIzd0YuaV4Hnb1BjlS1sOdoAxtXzJjQGp6okGFfvJtj/v14TalU+g/iM2ewMm0DVtlOZ6yNPT3biOphpjlnMc+7FFlSiOlRDvTuoClSi1m2MMu9kGnOcmRkmiN17O/djmYkmOVZQLlrAQBbO1+k3L2ALGse/YkeDvTuYHnqesyyhW1nNjHDPZfDfbuJ6GGW+a4l11aELjRqgic44T9IQsQpspeyKGUNiqQMXUcXOrPcC5jhmntVDjBCCDZvO0F2hpsFc8YOaZhUhY1rZxGOxJHHLUp86eiK7KI1uIme6H5iWiftpr+Q77oLj2UWfdEjNAT+gEl2U+L5CFY1acTrIk5t369Js62gPbwZCZV8113Y1QKiejutwU2EEg1YFB85zttxmorpCL9OS+glArFKwlozdjWHAtd92E3jCxperTBbVMrnJ99hIq5RX91xQYaTJEmkZ3tJz04akL3dQX734zfe1YbT8f31bH3pMAXTMy7acLLazNz3ibUsX1dOXnEabu/VR6idDFTZSzh+kkjiNKqcNvocojUS15qxmorfoVa+exHSokylls2mrcewWUx87gNryUp3j5APuJSIjiEET58+wiPHttMTCyMBDtVMlt2FRVaIGjod4QBhLc6h7lb+Zf9muqIhPlS2eExO4VThkg0nSZLwuGxMy0/jxOl2zvQEeGHLMfKzUoYJTAoh8IeivLK9kq17qifUNUloOm8fqiPFYycn3YPLYcVsUoZ1JCEECU3nVP0ZKmvbAVBkmZK8kXFvSZJYMDOP1QtLeO6No0RjGo88sRUhBEtmF+Bx2oa9ZF03iMQS+ENRmtt70XXBivmjd9SoEWbLmRdZlbaRpb616MJAkVR6Ep282v4MczyLcZtSeKvrFQyhszBlFacCR6gKHmNt+s1E9BBWxYaEREuknlfbn2GJ7xqsio23Ol/FEAYV7oXUBCvJtRWTZc0jokeoCVayKGUNqmTmZOAIXfEO5nuXo0gqdjVpSB73H+Dt7tdZmboRl8mNIQwkSaI92sxrHc8OGV5bz7wECMrdCy7o/V8J9Psj7Nhdw+pl08fdT1FkyqZdfrl9AK9lDhYljYTRT47jJlKsCzDJydCIyzKTMvWzHOj4WzTXe4Gk4SSETmvoJXQRJtOeLACtSg4MEjQGnkZCotB9H2GtBXVgxZ1qW4YkKTQaMaZ7PoFZ8WFW3n0hmL9idBiGweE9tWiTqFs5EfKK0skrmny699WIFPuN9IZfobH3m2S7P4XdXIEsmQEJIeJEE6dp9f8Xcb2FHM9n3+nmviMwhEFYj2GSVMxycgqPGvEJ7SEBBKdYNbztjJ+lcwtZtbBkykPk1f2d/PDoW/gTMRan5/GxmcuZl5qNVTUN1WKMagkOd7fx61N72N/ZzA+PbWd5ZiGzUi7vPDAlHiefx8GqBSVUN3SS0HQ276wkFImxfF4xqV4HhmHQ3RfmSFULOw7UYjGrFOX6qG/pGfOcum7w2tun2HmwlpklmUwvSCc/y4vXZcdqVtENQSAcpa65mx0Ha2kd0GiaNzOHmcWjPzSzWeUj71lOQ1svB0400dUb4ru/eo25ZblUTM8ixe1AVSSicQ1/MErrmX5qGjtp7ujjvTcsGNNwAvCaUpjnWUaq5WzWQGukga54O23RJs7E2kgYcSoDh1iYsgqn6iZhxGkKn2amax5plkxAoiFcTboli9meRSiSSn+ilyP9e5npmjfuO5AlmZmueZS55gz9ZgiDE/6DzPUsZY5n8bAP+3SwkpAWoDlcC0jEjAingyeZ6Zp/1XBEAsEoRytbOHayhZM17cnCkT1Jheb0NBc3rqtI8ol0g7d2V9PYnPye0lNd3LCuYsjrJITgjbdOkpvtpf2MH38gyqql0+jo9HP8VBvlpVmUl2WjDBCyA8EYB4420NbRj8WsMrM0mxnTMocZ1qrswKpkoEhWzIpvGI9JkcxYlNFrfSmSlQz7OnzWswaqITSsSia90YOEEo34rIuxKMnVtooTs+xDka1Y1cx3fajurxiOvq4gDdUdiAsQ8/2fDLd1LRmuD3Im+AS13V/ApGSiyl5AQjf6iesdyJKNNMe9eG03vNPNfUfQGunm8fq/UOjI5P6CdRgIflGzibgxvtdVAL2xwJS2JSPNRTSuIcTUZusBbG6uwp+Isig9j+8tv5V8h3fEmOoxW9loc1Lhy+Qru15kd0cjLzeefHcYTmaTwq1rZ3OsupU9RxvQDcH2A7XsPdqI1aoiBERjCeIJHa/LxkfvXkFnT5D6lj3jnFVCUSQisQQHK5s5WNmMSVWwmtWhCS6u6UQGXPSKLDGjOJNP3rsam23sGGdaipO/+/B6fvnMTnYerCMSTbD7SD17jtYPyMMnJ+Jz5RJMqjJm4eBBWBU7ZvmsUJdAENdjWGQr2bYCFEkl21aA25Sc+Aoc09mY9R6qA8d4tvUxFqesYa5nCVE9gkWxMshLsykONCOBQAxXMxE6uji7SpVg6NxnIYgbMWyK/bxfBVEjjFN1k20rACSybQWkma+Mt2ayCEfi1DV20dreRySaoD8Qof2MH0h6lwTD2Xv9/gj7DjfgsJu5/tpZQ1uFgJffOIZpQPjxdEMn+w7XAxJnuvy8suUY3/r7O8jO9OAPRPn3n7xGfVMXaalOgsEYf3rpIB++fyUb1sy8ZKNSlkyY5eHvSZIUcpy34DQV0RHeQmvwRUpTPovbPDO5/ZKuOBxCCBJxnea6TvbvqKbmeAv9vcnabh6fk7yiNOYsKaJiYREm88jhQQhBsD/Cod2nObCjho7W3qT8QUEqy9fNZOb8AuxXgJh/qTAMQaA/zIEdNRzYWU1XRz+KopBbmMqSa8qYs6QEs0Ud9z6EEETDcWpPtrF/RzX11e2EAlEUVSEl1UVRaSYLVk6jqCxriHMkhKC5rotj++upPdnG6cpWak+1oekGf35sJ2++cnTEdT79v29n2syR2X5VR5v5xb9tGkFNqFhQyH2fuBane2L+pjAE/b0hDu2q4cCOGro6/MiKTH5xOsvWzWTG3HysNtOIaxuG4A+/3MbBndXcfN8yVl8/m+a6TrZvPs7pylZCgSjuFDtzl5SwYkM5vnT3mBp750JCJdv9aZyWpfSEnicY309cawUEiuwlxX4jqfY7cFmXIUv/f/JTu+N+dnadoCnSyf0F6xBC8Gr7XmJGAnWC5JHYBMbVheKG1eX84L+3sH3/aRZW5Cc5qOftYzGP34/GQp2/B0WS2ZBbSq5j7NqEkiSRbXdzfd4MDnQ2c9p/4SWULhRTJkeQ7nPyz5+5hcee383+4020d/kJRmIEgjEsFhWfx0FJXir337SIBeX5bNlTNe75zGaFm9dUoGkGTe299PkjBMMxwrEEhm4gyxJmk0pmqosMn4tFFfncvXE+qd6xdX4g+ZCLc1P5xt/cxLZ9Nby6o5LWjj66+8NE4wl0TUdVFNwOK163jXSfkzmlOdyydqKsv5FVlFLMaSiSSro5C58lg7gRRZGSjzysBUgxpbIq7Xq8plRO+Q9T7p5HhjWHA7076It3Y5YtnA5WkmsrRJVMWBU73fEzhLUQbZFGAoneCVogkWnNoS5URYljJmbFQsJI4FTdZFhyqQ9VkW0twKG6iOkRzPLVNeFlpLl433uWcrq+k+q6Tm5cV8FNGwbfw9m7lWWJtSvKWLawmISmU1N3ZsS5dEMgNJ1vfvk2/vTSQf7w/H6+9rc3k5nu4hvffZ7m1l4y0lw8+eweGlu6+dr/upnpRRlEYwl++cR2Hn1yBzNLs8jLHrvY5LkQYtBzPloV6POesTDQjCAucyku8wxO9/+CrsjbZw0nyYRuREkYfmTJgiKZLyq7TghBW1MPzzy6ndefO0A8lkhK6JxTG1GS4KXfO/jGIw8ya8HwrCZdMzh5pJFf/tvLnDraDAIsVhNCCA7urOGVP+5lwYrpfPRLN1IwLeOq+pbOhTAEB3ZU89gjr3G6sg0Ai0XFMAQHdlSx6fe7Wb5hFg9+5joKStKRRuHLGYZB7al2fvODzRzedXqg5ETy+YlznuX2zbl8+bv3klecPnCcYNumw2x+dj9CgJbQ0OJ6shi4PzJqyC4RGzuRRksYRMIx4tEEPZ0BYtEELo99VJ7nyGN1juyt5Zffe5n6mo7kc7CaBp5PFS8+tYuV183iQ1+4nux83/D3KQStDd0c3VtHUWkWsWiCX3//FQL9YcwWE4ZhkIhr7Nh8nE2/381nvn47FYuKJmyTJEkokhOPdS0e6xqSyzwNBEiSymD5lav127oSKHPm8fWKB0k9R7NJQuKm7KVsyFw45kJLIPiX449PaVsqT3cQjiX42n+8QHaGG6/bPmx4czusfO8rd17UuWVJwqyo+Cz2CbPlZEnCZ7FhUdQrokM2ZYaTJEm4nVY+ee9q2jr9NLX34g9G0XUDm9WUNJzyU3E7ktof82fm8tWPbUSRZWaXjiwoqcgyS+cUMm9GLm2dfrr6gviDUWJxDU03UGQJi9mEz2MnN8NDum/sgr2jtdVqMXH9ypmsmF9MS0cfHV0BIrEEmp40nBw2M2kpDnIyPLidtgsuQSAhkWsrYrZnMa+feR5JkjBLZpb41lLsmEFd6BRH+vcOTf+z3AswyxamOcppjzTzYtuTANgVB4t91wAwx7OE3T1bOR08gVWx4VBdw644WhsWeVezpfNFnm39DapkIttawDXpN1LqquBMrIWX2p5ClmTsioNlvvVD3KirAYMV6AdDbsm/pRHveUijZBzla0mC7AwPToeVwjwfaT4HGWkubFYzbpeVQChKV0+IYydbmVOeS1lJ0vtmt5lZuqCIt3ZVU1nVPorhNPyCuojTHHiW/thxIolmqvp+hNtcxjTPx4ftdy7HzxAJ2kOv0h87MTTzZntuHLonq5KBRUnlVM8PcJlLyXfdNULiYDTO4Pl8wN6uIL/6/ivs3loJAkpn57FoVSlpWZ5kWY/WPmqOtwAwfdZwhV8hBDWVrfz02y9yurKN3KI0rr1lHnlFaQghqK9u543nD7H3rVMIIfjUP95GdoHvqpvghBBUn2jhp//6Ii0NXcxZXMzq62fjTXWiJXTqTrXxl+cOsvO148QiCb70nfeOIFoLIag92c6P/+/zVB5qRFUVFq4qZc7iYtwpDhJxjfamHqqONTOtPIesPN/QsbIsse7W+cxenAz7tzZ28/ufb6W7w8+6W+ezamPFiDbnl4zOWyoqy+Qr33svkXCcaDjOf/9gM0f3ji+Ae+49HD/YwE+//SLNdZ0UlWZx7S3zyMpLQdcNqo+3sG3TEba/egzDEHz8KzeTnjVy1S8E7Nl2irc2H8Ob6uDOD64kO9+HrguqjzXz8tN7qa/u4Dc/fI3/8/OPYLFOrvSQJEkIkZwsJZRh3exq+6auNGyqhSWpM87+IECRFYodWcxPGbv4uBACtzq1SQOKIrF0TiFL54wuHWGzXnyG23R3Ki8bBv54FCHEhN7f3niEuKEz3TM1UgvjYcoFME2qQkF2CgUTrMzTfS7uWD9+muKggVOcl0rxKITvcxHSetjf/QRLUj+ITZ0ceVaSJNwOK+6SLMpLkqKJ/YEIjz61k6bWXkoK0vjkB66Z0GhKt2TzvoK/wa4MNzosipVlvnXM9SxFFxqypGBXksrM5e4FFDlmIISBKqtYZQeKpGJTHFyTdjNREQYEFtmGRU4am7M9iyhxzEQXOmbZgsDApjiQkHh/4WewysNd15IkkWbJ4vacB4kZEYQAs2xBlUyYZDNr028hoocwhJ4klCtXRjXaY7Xy+L3vRTMMJCBlEuJ7lwqJswKoiqpgNqlDlbtlSULXBf5ABH8gwptvV3PkRMvQsfGEhq4bhKOxYedUZSezUr+Kcs5zl1HJdlxPhn0tpSmfAiRkkitlRbKyKPMRTLIHTWj8tuFRrsu4nnx7IXmuu8h23AQIZMmCSXYldWcEmBUf5alfQTfCSJIJkzxS9FIXOk82/pb6cB1r0q7hmvT1wz2QAl58che7tlSiKDJ3P7SG2x5YjstjR1WTE5SW0IlFEwghRoTpIuE4f/jFNk5XtlFUlskX/+89FJVmogwcuypRwbxl0/jRt57n4M4aXnxqFx/8/Eas44TN3wn4e8P87sdv0NbUw7U3z+OhL95AaqYbWU6G/1ffMJvZi4v59hefZP/2Kra+dIjb379y2DkioRhP/+pNTh5uwpvi4AOf28iaG2djd1iQFRkEJBIasWgCRZFRTWe9g5IkkVuURm5RcnB3uW1YbckSKLlFqcxfPvbEdz7MFhPZ+WfHRU/K5PqvEMnw3NO/2EZzXRflCwr53D/dQX5xerL9wKqNFcxbVsJ/ffM53n79BIXTM7n/E9cOu5dBtDf3UFSWydd+8ABZeb4hLuCqjRW4fQ5++8hfOF3ZxvH99SxcVTqp9umGn1D8KP7YdmJaMyAwK9m4LMtwWhahyl6kqzAD+J1Cni1tTNXwc+FUp3asvW39nBGFrc/Fpdi4NxbM5PHqA+xor+fG/Jlk2V1j1mhtDfvZ0lKDUzVza2H5xV90kriqa9VdCFTJTKZ1Fqp8aQP1waON9PaH+fKnr0dV5KFJZTwokopTHf2jVWUVlzzSkDNLlmGcqEG0dfTT748wY3om8nkplQoqLtPoRuFY1096LGxYlZEdxiSbMMlXnmwsSxIZzitf2mNYnzu/BBYCWZaQZZn5s/NZs3z4AC/LEtOLh5cLkCR5BFk7+dvYiwbLgNKxLhIEtQCa0JLK+JILk3zWg5gwEtQEqyhyFGNT7CO2nw9VVnmg8IO82r6JiD4y5djfF+L15w5i6AYLV07n/k9cO2L1bzKro/KaIClcOehNuuPBlSM8Uiazyvzl07j2lnk8+ZM32LbpCLfcv4ycgtSrxkMghKDyUAOVhxvxpTm54Z7FQ7IGkOwrZrPK/GUlVCwo5ODbNWx54TA33bsU0zmVCFobutm9pRKEYMMdC7n+7kXDdZOkpFFjtlyZws4Xg7pT7RzeU4usSNz1odUUlQ5X2zdbTCxdO5OVG0/z/OM7ee3Z/dxy/zJSUkd6pFWTwj0PXUNuQdqwsKbFamLZtTPZ9NRu+npC1Fd3TGg4CSGIJKpo7X+YvshfEMSBwWer0xF4FLd1FTmeL+A0L/ir8USynMq/zvsYVmXiuW9l+izSLVM35pvG0QuLxBI0tvRcUJmVc1HgTOEr89fxn0fe5LuHtnB7UQWFrhS8ZiuqNFBUPRahPtDLn+uPUdl3hs/OXk2mzYU/Pnr2oEM1T4lUwbvGcBJCYAgNgQFIyJI6pDlkCA1FMjHdtQZZurjByjCS0gbNbX1kZbjxum1DhHAhBJpuYOgCSQJVVZBlaeh3WU4SyoUhUAcJ5oYxzL0oDIFqUpBI8m0GOQiyLKEOiDomEjpHTrbQfsZPQZ4Pk0kZIqz//wxJklBkaULtr0tFaoqDNF+SI3ftyrIhsU0hxISu4ouFIQziRhwJCUVSkJAwMAhqAbZ3bcNnTkWRVNQBbtygArIsyQiRlINTpbPky7FaWH28FX9fstbZxjsXYrZcWNc/ureOREzDZreMOflJksTydeX8/udb6ekMUHuyjZyCC6sHeTmh60lekr8vTElZFtn5vlH1nzTNIKcglYNv19DTFaCvKzjMwDp2oIFYNIGqKmx8z8J3pdjkkT21aAkdT4qDeUtHV+2XJImVG2bx/BM76Wzro6G6Y1TDKSPbS3FZ1qhcMKvNjDfVSW9XkIB/4lqAhgjT2PsvhOIHSLFfj8e2AbOSnuSDGV30R9+kN/wyjT3/TFnGo5iUyxOWGQx9Gxhoho5fC9AUbuFMrIu+eB9BLUTcSKAJHVVSMMkmnKoDr8lDqiWFfFsuKWYvqqQgS8lx/3KN45Ik4TZNLgR3V96aC6adXCzazvTzy6d38t0v33lRvKPXW6p5u6OBqK7xQsNxdnbUk2qxY1NNySiBEIS1ON3REL2xCG6zlRcaTvBSY+UIBfNB/NuKWyly+UbddiF41xhOIa2LvV2PEdJ6kCSJIudKZno2okgmTge2U9n/Ks8wBjMAACAASURBVGCwIevLOEwX3pnOdPl54k97OHSiGU0zqG/q5pplpdxy3Rw6ugL89o+76ezyY7GYuGZ5KdcsL0VRZH706Fbyc1KoaeikuyfEjesqKM5P5bfP7EZRZHTdIDXFwemGTj7x/jUU5aXyytbj7DvcQCyhkZri5FMfuAaP28ZTz+1ly84qItE4J6ramFaUzvvuXILbOX5NqP/pcDktZKS72bm3hhnTMlAUBbNZoXAgfBsfkI8IhWKEQnFicY22jn7MZhWnw4J1kit/r8fOjetn8+vfbeeJZ/aweH4hJlUhGI7R1NLD9ddWYJskR2MyiOkxdnS/yeaOl9GExvLUVSxOWUql/zhvdW6lOniKQCKA1+xlY+aN+BMBtndtRRc6KWYfmqHTn+jloeJPYp+Au9BYewZN0/Gk2IfCRBeCuqqkTlpWXgp2x0hP6SByi1IxW0xoCZ3ayjZWX3/hpZQuFxIxjeb6LhDJ+/n4zf85aihBCND1JElb1wyC/sgww6n2ZJJQnpblJiPn3SkPMfg+cwp9WGxjf9P5JemYTCqJuEbtybZRQ4lpme4xM/hkWUJRkxmw+iQWPj3hFwjHj5Hj+SKZzgeRpOFjX4r9JpzmRTT3f4+u4B/J9vzNhOe8UCSMBGdiXTSEmjkROMWxvkp64n0YJBfDydItwwu4DC5bJJIcTBkJl8nJDFcps90zKXIUkG3LxKa8c2N5Mvpw5ULnwXCMzu4gI9KfJ4k/1R5lc/OpoefcFQ3RFQ2NuX9/PMr+ruZxzxnWpiar8F1jOFkVF7NTbsepptMbb+Rgz9PkOxbiNmVR6r6WLNssXm/77kXXI8pMd/OFj63nqef3EY7Eeei+lUOk5GdfPojXbePD9y6nraOf3/15L0X5qRTnp6HpBpXV7Xz4vpXYrCZURaa7N0TbmX6+8NB6fv677SxbUITNaqa67gzTi9JZMDufFYuTgmE//OUbHDvVwqol03nfnUuwWEz09IX48L0rUFUF5TIrYL8b4PM6uOOGefz2j7v41n+8hNmssnBuAZ/7aFJE8tTpDp54Zjf+QISW9j6i0QTffngTFrPKjetns3Ht5Is5r11ZRjgS57VtJ9i87URy4Jdl5s7KnXKdkqgRwWdO446cu6n0H2d/z17mexcyyz2bLGs2/13/Cz5Y9BFSzD5kFI7GD6MJjRuybuGpxt9yb/4DvH5mMx2xdorV8Wv9hQNRhCGwOayYLiI9OBRIegtsDvO4xyqyjM1uJhyMTsrDcCVhGIJwMOnCV00qHt/E4eKUVOeIkHlw4L5cXvu71hscCiSfg91hHf99qjJWm5lEXBu67/NhtppQTVMTMgvE9mBWc/DaNiDLI40xCQse21q6Q88SiO0hm6kznAxhUBdqYFf3fo72V9IcbkFncl7uwQzaQV6iDvTE+3i7ey+7uveRbklllnsGi33zmeuZhSqro2RBX/1o7ehn3/FGNq6cic1qYtueajq6RteGamrvJRyNX/S1bsyfMeVE7zTr1FBE3jWGU8wIURd8m75YEzEjQNwIoxlnybqX+gkOVnlO8lykIfd7NJbgZE0Hn3hwDempLhx2Cx6XjZb2PooHiJnzKvLIPSfjpLs3hNtppbggFYfNTNm0LMKRBNFYgoRmUNfUzZ6D9fQHItQ2dNLXnxyQFEVGkSXkwYrTY2hHCSFIGD0YIoFZSUGWxvYATBWEEGiGH10ER2xTZS+KdPkmEUWRWbFkGrPKsonGkisGh/3sPU8rSuezD60bNbPM7bIhSfDVz984FI9fNLeA0uIMfCkOJOAbX7p16HyqInPLdXNYvWw6kUGitKrgdFiwjMH/uVg4VRdlzhl4zSlk23LY27sbIQxkWUZGGQrfDUpYSJKE15RCni0Pi2whz5aPU3ER1Sc2UGRFBimZRn8xYovqAMcn6TUY+3jB2ZJHoxGJ32kMGkFFpZn8w3+8b8KSELIijTCwBgnUk/GgXK0YHN80bbTqX2chxFlawVghyWS/n5q+rxn9yJINdRRe6CAUyYkiO9GMvku+niAZhu+K9bC5Yws7unbjTwQxJmkwTfYaZ2JddHZ2s7fnIDNc07kr71YK7LnDwuwXfX4hCGgRAokwmdYUFOksxcCfCHOwt4b2aA9lrjxmeQovyevUeqaPZ149yKqFJdisJl7YcoyTp9tH9erH4tolfRa3FM6assLMmqET1iOARk88KZatSAoe08Vlkb9rDKf9XU+gyjauyfosCSPGlvZ/vyLXlUiKa8YGJmxjgJ907odiHyXlUpFlGEinV5Xk/wg4UdXKC5uP8KkPXUNRfhrf+/Hm4Z/GoA7MON9L3OjiUPtDxPQ2pqf8Azmuu6fiVseFQKOu7xGaA78dsa3M9w1yXQ9c1uurikyqb/SP3G4zD2XMjYX01LPEapvVPCxNNiNtOLFeUSR83stPXlcGuBFJnC+xkPz//M9AZnCiP7d6+sSDi9eX9JwE+sJEwvEL5mylZyYnsp6uILo+9vUioRiRUHJBk5Y5cZbPlYSiyngHjCBdN7BYTfjSxybcj4XUgWN6zvjREjq8C3UY07OS77P7jP+s8NQoCAejRCPJ95l6Bd6nWckilqgnrrdhUkbnxyWMThJ6F1ZT0SVfzzAMdvfs5/nWV2kIN13y+caDQBDSwxzoO0JtqIGNmWu5PmsdTvXSxhqB4Nnm7bzato/vzPso+faMZHp+IsDDp55lR9cxdGGgSgrvL9zAg0XXocoXt6iZXZbD9758J15X8qM3DMEH37OMtUtGlsM6Vt3Go8+8fdH3pU5RvTlDCN7q2cuu7kMDQ2Xye8+ypvNQyT0X17YpadkEEEInGD+FZgTwWpdelIWdEFHsciqakaDK/zpxIzxwboHAQBMJhDAwhIYhdOTzBAKFMAhrdUQTrfhsKyctIGg2m1g8v5BXt53A47bR2NJLJBonNytZBuBCoWkG0oB458GjjdQ2dDJ35lkdK4fdwqHjzbR39mO3mvG4bSNWxQm9l3CiFoFGMF55wW24GEjI+GyrAUHC6COud9MX3ZsUp/srphyqpKIJjdZICxISjgkGVyEM9CE1eWno/0HjqnB6BqpJIRKKUXWsmRlz8i7o8y0b2L+3009nWx8uz0hrQQhB9fGWpIijBNNnjdRneydhNqvkT8tAliX6e0I01HSQkjZ5/bdBTCtPZhQG+iOcrmxj7tLii/canGMgC8FlS0I4HzPm5PPanw/Q1dFPV4ef7PyRhFkhBFVHmzH0ZMbp+ZmUlwMe6zV0h/5MZ/B3mD1fGvA8DT4PgS7CdAafJKrVkuX++HinGhdCCGJGjDfObOf51lfoT/inpP2TRV+inz+3vEx3vJe7cm/FZx5ZTmSyEMDhvlpcJitWxTzkbdrZdYK3u06wxDeDVWkVvNK+j5fb9rAibRYz3PkXdS2rxTTMaaAqMnmZXjLTRhrVXb2hcbPuphpJWyCJcwnwAoOdXQfYkLmSPFvmUIj07KL1wnFFDKe43k1t3w+J690szv7DRZ1joe9+DvQ8xfYzPybPsZBS1zpUyUJE7+NQzx/pjp0GCbZ1PEK2bTaL04Z7QHQRpqHvF/TF9rA89+WkqNooSE91DXmXILnyv+umBbz42lEefWonXo+ND9yznNxsL8IQ5GZ58Zw3iVgtKoX5qciSREFuKhazSmqKA00zmFWWzZLmQn7++FsUF6Rx8/rZpA2sgiVJYtmCYtrP+PnJY28ypzyX2zfOHeFNsakF5LkfJKq1kuN670U9zwuHTKptDT7bKkAQ17vY03oHmnH5BhwhBPXBHjJtLuzqldcDEkLQn4gQ1hJk2dxTmo0iIZFjzR2SibDKFnKsuUPp1XbVwbXpG9jR9SZuk4cNGdfjUBykWzOQJZk8ez4yMhnWTGyKg9PBGrZ2vo5/YAJojbRwTfo6ZrqTmials/PIL06n6lgzzz/+NotWl44pFTAY8jx329xlJeTkp9La2M2m3+/m439/M5bzPK2hQJTNz+5H1w1mzM6jYNrFpSFfLkiyRMWCQnIK02ip7+KNFw5RMjMb9xhcJV1LGp/KeZIkc5eWkJbppqvDzzOPvkl+SfqYBthoz/JcmK0mTGYVXTPo6wqia8YVCXEuWDWdjBwvXe39vPrHvTzw6fUj5BMC/RFefWY/ABWLikY1rqYaHtu1pNivpzv0Z/zRnbitqzAr2YBEXG8jEN1FXG8lxX4DXtuGi75OWI/w55ZNvNaxlZhx8TycS0FCJNh6Zgd9iX4+UHgvmZb0izKehBA0hc+wMKUUx4BOU8xI8GzzdnLtqXxy+q0U2DNJs3j43sk/cLSv7qINp/Pxj5+6AfsYCTM+r51FswumnBs6FoKJOH+qO4JVNXHftPlnNwgwSSrTHPlkWKcmy/eKGE4xvZNQogp1HB2aiZBiKWBD9ldG3bYyY+KVh2YE8cePYIjxO8nGNSPFs6wWE/fcupB7bl04fIMi8b47l4zYPyfLyycfXAPAxx5YBQwPB913+2Luu33xqNdP8dj58L0rxm2jIlsp9f3DuPtMNZIdWhkyOJO8qsvbI3Rh8POqt/jgtOWUe7MmPuAy4EB3E6f6O/ho6UrMytnukjCSWVeqdHHlH1RZ5Z78+4f+zrLlDPtbkRSWpa5kWepZ8cUMMilxJl3i7yv4AAA3ZN08tH26q2zM65nMCu/54Eoe+eZztDZ288g3n+PW+5cxe3ExnhQ7COjvDdHW1ENTbScLV00nLfMsz8TlsXHL/cv47X/9hW0vHyUjN4WNdy7EO5Ce3tXh54Un3ubAjhrsDivXvWcR7pSrizwtSRLFM7K49pa5PPmTLbz1ylGsVhPX372Y/JJ0LNZkNmBvV5CGmg6qjjWzauNsikqHq7T70l1cf9di/vjrNzm8u5affedFbrp3KWUVedgcZgzdoLc7SHNdF73dQRavKsXlHT3r0ZfmIiUt+Qz376hi+fpyZs7LH/IaaAkdWZEn5GJd6HNIy3Sz8c5FPP2rbWx+9gDeNCfrb1sw5Elsa+rhucffpvJQI26vnRvvWXJFxEwlzOR5/h6zkk136Dk6g08M225Wcsl0PUSG8wFk+eJCXJqh8Wr7G7zS/gaauDCPuUOx41Dt2BTrAP9QQRcGutCI6FFCWpiwHpk0N8fA4EDvEVRJ5eMlH7josF1MT+BUrUO16o721dER6eXmnKVkW5OL+EJHJhLQk5i6Qr+DIbvRkJ3u4bMPrp2ya02E3niYp2uPkGp1DDOcJEkix5bBC61bmOMtwzKg9WhXrJS6ii7qWpfdcBJCENHqiWptOM0XbzhdahtiWiuRRD0m5fKvmv6KqYEiyXy+fB0plqktE3AhWJJWyNyUXEzncAKEEGxtr8KumFiZMXml53cay9aV09zQzfOP7+TI7lpqK1vx+JxYBgpxx2MJIqE4siJRMjN7mOGkKDLX3bmQM629vPrMPp786Rb+8twBMnNSEOL/sXee8XFc19n/35nZne272EXvAEkQ7CIhkSJFFVLdlGRbki3bsWM79munOG9ipxen9x7HqXasRHZi2ZYsS1a1KlUoNrF3ECDR+wLb28zc98OCAMFdkABESk5ePfzxA6bcuXd25s655zznOZKh3nGGByMIYNtHNrBl25oCMnEknOD4gW4mwnGS8QzRiSSH9+ZLhAz1jvPdr71KaYUPl0fH7XXQuKSCpqVVU+fnS50M0HV6mGQ8TTyaYnw0PqXFtOP5o0TG4rg8DtxeB/6gmxXrGmeEFW12jfd/fBPD/RO88vQhnnlkD7teOYHL48CmqxhZk2zGIBFLk0ykWX5VQ4HhZLOrbPvIBkaHIrwyWZbk8J4zeP0u7Hree5TN5EgmMlQ3hFi2pm5Ww8nl0bnxfas5+tZZOk8O8me/9DBV9SFcbjuJeJpMKscv/uG9NLbMXDhMhBMc3tNJPJomEUuRiKWnJAa6Tw/znX99hZJSz9S9WLS8mrqm6dItNrvGto9sYLh/nFeePsRDX3mBZx/ZS3lVANMwGegNMzoYxWZXuecnNrJx67IpUvyVhBACu1ZJle/nKXXfTyrXQc4cQAJ2tRqHrQldrS6acTcXmNLkjbHdlzSaBAJd0QnYfazwLaXZ3UCNsxqP5kZVVLRJzbUpnTckhjQxpEnSSNKb7Kcz0cXx2CnGsxNkzAwXo+HvGz/ID/vLubdmG7o6/2Qfr81JwkhjSBNhwfaRgzhUO1cHl2JX8p95ddKosuTlI76bpsVENMVIOEYineXCpjVNYU1rzTuygEobxtSC9nxIYCgzxng2Qn96CHVy8V/pKP3xMpwsmSNjDJIxR8iaIwzGfwBY5MwIQ4knCo53aDX49bZpsUgpSZv9RNJ7UYSDEscGbGqhXoqUkmhmPymjB5tSQtB5/VQbljTImsNkjGGy1hjDiWeQmFgyzWD8SRQxc+g2NUjQcd2sSrSWzJIyeknlujFlAoGCTQ3isjVjV0KznidlPqw1nt6BXS2nxHEtAIYVJZE7RdYMIzFQhRuHVoVTa0BVCrU+Iun9pIzugu1e+yrc9ounokOeQGjJLGmjj4wxQM6KIqUxWd7Dj8vWhF0ruyIpsntGu6hzl1Dp9JE0shyd6KfVX0nCyDKWSZA0Moyk45Q5vKwN1qIpKvFchu2Dp5DAxvJmHKoNU1qcjAzhUG00efJhpnAmQXt0mLXBOhBwIjJEX2KcgN3F8kAVPpsDC8me0S6aPaUcjwyQMQ1Wl9RS6fKRNnIcnRhgKB1FVzRa/BXUuvJ8g50jZxhJx2nyhijRXagITGnxxlAHj3cfpNThYSyToNoVYHVJDUcnBqh0+qh05r2LA6kIw+kYKwPVCyZjXi4IIXC47Hz08zfR1FLJc9/fS2/nCKNDEbLpHAiB05UXK1y0rDrvhbrgfK/fyWd++U6q6kO8+uxh+s6O0t81NrWvdXUdm29fyZ33X1MQ3gLoODHA3//uY0yMFWZmjg1H+eF/TxNJFUXwvgc28HNfvmdqm7QkTz68i2e/t6foGA/s7ODAzo6pv0tCHn7nq5+gdc3MsITb6+Dzv3EXy9c2sP2ZQ/R0DDPQM0Yua6LZFNxeJ+XVARoWl1NVX7jQEkJQUurh5758D82tVbz50nH6zo4y2BsmlzNRVQWnWydY5mXZmvqL6l4Jka9dFx1P8vKTBxjoCXN4TydCyf8epZX+onUrOo738xe/+t08Of0CDPaGeeyhN2bcy5/42Zv52M9unXHdQMjNz375HmqbynjzpWP0d43Re2YERRH4Am5WrGvg5nvWsvXuq4qKW15JqIoTRTSha00F+xbMBZKSs4keHu97hphR+AxC3mAK6UHW+FdwbaiNJZ5F2M/jwszl2lJKlnia2cJmDGlwKtbJ3vH9HJg4wlB6pKg3ypAmLw+/TqOrjg2htvMSPy4NIQQrfI0cnOhk5+gx4kaa3WMnWOKtZXWgearP4WwUCbgWYJjNhh37O/m7/3gZRVFw6IUZgn6Pg698+Z2hk6TNXFHDSUHwSy0/BUDOMlCEcsmiwZfCFTGcEtnTnB7/C1JGNzkzjCnzRO6MOcCx0cJwW4X7Lvz6WjiPdxTNHODY6K9iV8tZU/6vRQ0nsOiLfZfBxGN47asnycv5Hy5t9NAx/rfEs8fJmuGpNHrDinFi7DcLWvLr6whWbgRm3tB8Gn6E7ui/E07tIGX0YFoJIF9aw21bTLX3AcpctwKFBWgBErl2jo3+Kn69jZLKa4hlT9AV+TeimUPkrHGkNFAVFy5bMy3B38KnF9bw649/j4H497kwg6ol+OU5GU7jqTcZTDxBIttO2hjAsKJITBRhx6YEcNsWU+P9CCHXTQjefors+fivzl28v+4qKp0+JrJJvtmxm19cvpWu+Bj/euo11oXqCdicfL/rAJ9ZsomN5fnxSOAb7TuodPoI6XkX9qFwL13xMF9aeQsaCi8NnOTYxABrg3XsHjnLkz2HWeIr562xbg6Ee/n0ko0oCL528nVaA5UE7S4kUOsuocLp5c2RMzzXd5RWfyUxI4PbplPjCkxVZDk43suh8V6W+MqnwiVZyyRp5F/SnGVhTi6zdo2eBSn5/NJ8mPbx7kNIJCsDPx4k6YFUlJf723n/TatYeXUjA91jjI/FyaYNpJAcjA9QWurn7rVripK/hRDY7Bp3ffRaNtzUSn/3GPFoGiHA43dS21BKsNw3a1ipcUkFP/c795DLzC08UtMwU8NFKILb77ua1dcUfkyLwa5rVM9i+LjcOrfd20bb5iX0d48Ri6TIZQ00TcXtdVBa4ae8OjCrwroQArtu4+6PXst1t65goCdMdDxJLmfkDSdX3nCqqg/hdF08xKWqCvf8xEauuaGFgZ4wqUQGoSg4nDZKQp6i3KKmlgp+6U/uLyrBUQxNLYWhbiEEDqedez+9mc23r6S/e4xkPI2iKHgDLmoaSgmWFepYQf63uPPD17B24yJC5T7c3uLCjv6gm0984RZikdSsxYrPh5xKKZ7MRL5gIXdOxX/6mLnPUxaS5wZfYiA9VHS/gsL64DpuqbiRFm/zgsnD5/fJJmys8C9lqXcx14au5uXh19kxuoecLBRijBlxnh18iTWBlbjmUVNOQXBL5Vr2hE/y1fbHMaWJheT+uhumpAeklHTGBwBJuePidWTngxd2nGDZokoe2NaGs4gkwWySOufDkpKe+ASKENS4/VNc0rSRm5pb54JINk3WLDScABJGipdHdnEydgab0FgTaGVz6bqpigzzxRUxnFTFhU9fhce+BCktxtM7SeTasSlBKj13Fxzvta/gcvNlFOHAa2/FoU0W780cIJo5iCKcVHvuK8iqc2i1FDOa0mY/p8b+gHDqdVThxKHVousVSJkjZfQwkd5DNHuEjDFItfcBVDG7MmzGHGIi/Rbt4T8hYw5jU0uwq0EsmcWwEhhmBF2rKnpure8TBBzryZnjZMxheqP/iaT4Q1IM4fQOhuJPoile7GoIj70FVXGTNUdJ53oIp98gnj1Jq7ATct4w53bfLlSh8FOLNxGwOxEIdo2cZWN5Mx6bzh01K3ii59CMY9tKG3hh4CSRbAqPTeelgZP85OJr0RSV75x5i7ZQPetC9XQnwnyrYxf3NawlYHeCgCZPiPfXrwGmsy7Gs0lURWF9WSNVTj8emz71JG4oayKcTbJvbNrTpyDYUtnCjuFOVpZU8cH66Vj61qoW/uzQczzQdDU2RWX36Fl+cfnWOafVjvaHmRieJtt7SzxUNFw+AbhoNs3+sV7urFtOsMQ9oyisJSWZPju6assLO16kHVVVqKwNUlk7v7B3sMzL5lsXriQuhKB1dR2tqy8PsTXP9fHPCEnOF4qqvO02IK95VddcTl3z3Aj1wTIfN21b87auOXVtTaW6PjSv8jhCCJatqWfZmvqLHud06bRtnp17dyGimR2Mxr9Dpe9zuO0rih4Ty+xgMPpvVPm+gNdRyDGdDSdj7ewJ7y/eT9XBnZW3cHf1beiKftlDS5qi0uJZRJOrnkZXHY/0/pCEmSw47nS8kz3hfdxYft3cGxewtmQJv77sIzw/9BaaULm5ch1rAtMLakOaDKTDNLorWelvvAwjymPtsjoOt/fjcep43PqUaPQ5zCWh5oXedv5w3/NoQuH3rr6NG6vz9Iff2v0Mr/R3XOLsaRjSIpHLsugC0UyJ5IcDLxHORLiudB2GZbBz7CAZK8PtldfPuf3zcUUMJ5etgUUlXwLyIbNTY79PIteOrpWzuOQ33pF4p0OrojHws8CkizbyVaKZg2iKh8XBX52TaKQpE/REHiSceh27Wkaj//NUuLehqT6klCSNs/RGH2Ig/ihd0a/hsNVR6rxp1rBdxhymc+IrqIqHpYEvEHBcjU3xY8okyVwXGXMAu1L8Q+m1L8NrzxPXDStGX+y/kHLuhlO15z4EKgG9DZ++atKDJ7BkhvHUbk6O/S5ps4+B+Pfzcg1cmQKlUs6Msde5S3BpdjRFxWPTGc0Ud6GfQ5MnRJ27hDeGO6h25T9Wa4N1SCSnY8NoikJfMi+Mt6qkZorQrSBo9pYWcJW2VLYQy6X5VscuvDYH9zaspcU3+8dLCIFAzqgRfO55Xuwtp8lbysuDJ/HZHPhtTpb5505qf+wfnuP7X3lmqtr4LT+xmV/5+udJGzmOTAzQn4iiKQpem85QKs7tta1kTYPtgx2MpRNUOr1sqV6Cx6aTMQ32j/VydHwQVShsrmxCAhnT5IW+k0RzaZYHKrmmrB4pJS/0n6InPsF1FU1T43qpv52A3cGR8UE0RWFr1RIqXflw62uDHfQkIizxlbK+rAGn9uNb0PY9/M9BLP0m0fQbBF134bYXGtlCCITQSeU6GU89N2fDKWvlM9iKZdDpip07K2/mrurbcFzBkihCCOyqnZsrbsRC8v3eJwuMJwvJKyM7WB9qm3N5FoHApmhsKF3GhtLC5CbI85s+1rAVS0pc2uUL1bWtrOfJl4/wy3/+fSpKvWjqTIeE163zR18sdJacj/FMcqqUynB6ev6PG1nGs2+/+oAlJafj3Xyu+QEqJrPq6l3VfLv7yR8vw+l/A/JVursYSjwFQI33Aaq896GIvOtTCIHb1kRz4P8Sz54kknmL/tjDBB2bZvU6SZnFtGIsLf0DfPbVUwaWJjz49BVA8RXW5YBTa6Qp8IWCIsiK0Ak6N1PuvpPu6NeJZg7AZVTNBdAVjaSRwZQWsVyacGZ6slCFMi9fo6ao3FLVyve69tHsKWVjeTN2RZ0Kv22tauWWqlYgPwk5VRvGZNy7WFzbY9P5SNPVjGUSPNFzkMe7D/ILy7eiqxd7NfLq7lnLnFQezhtRihDcVbuKhzp2Tnmm7BdtZ25ImTkePXOIRb5Sdg6fZUVJJeOZFCV2J62Bcgxp0eIv48X+dhJGlgea17Jz+CyPnjnErbUtk+POs9eOTQyyPFBJtdvHN07tosrlo95dwhJfGbuHuzgU7mdlMO/1fK73OJFsmvc3rOJkZJgHT+3iS6u28HTPrX0z8AAAIABJREFUcTqio1xdVseL/e1Es2m21S+fFy/jPbyHYsgYPWhqEF2b3atoU0LY1BDp3Ny9Ef2pQc4kuoryi5b5Wrij8uZ3rI6cTdG4qew6epJ9bB/ZUdCnwfQwnfGzrPC3zqm9S0leQH5ucl5GbtM5PPrcASZiKW7etJSKkK/A4zSXags3Vi/iS7kbEAhuqJxJO/HZHTywaA2LfJf2hnZGw3y342DB9nw+uELKTE9+C/JCpDZl4XPze4bTRTCWeo2cFUZT/FR5PjhlNJ0PTQlQ5bmfSOYtwqkdpM1+3MpsnCOVkGsLPvuadzxNO+8pmd0r4LbnK97nrIlJAdHLd+31pU0823eMsUySnkSYrHVxjouUktOxETpjo4ym4+wZPUvSzHJNqBGnZuOa0ga+duoNdqfP8gdr86sZAXy06Rqe6D7ISCqGoig4VRv31K1GneVeS+D5/uP0Jibw2nT6k1Fa/RWok6TzoxMDHAz30pUI88rgKVr9lTR6QghgeaCKlwdPIRA0eUtZF6pDRdDiK0cgOBUd5jdX33nZ7qFD1dhQVk88l2apv4KUmaMvGWFzZTOt/nImsinKHR6OTQxhSskzvSe4s24Zd9ROT74nI8M0eILc07CSKpePt0Z7OB0dpckbotkXotI1U8ROCMH1lYu4o7aVttI6fmPvDxnPJPn+2YPcXN1CzjLx2nReHzrD1poW3FdIayttGBwbH6IlUIrHtrDJfzSVoDs+wdrS6h8riYT3MBOmjKGgoyqzl8JQhBNFOOZcckVKyZlEF0PpkYJ9DkXn3pq73rZ693zhVB3cU30n+ycOF4hvRnMxTsZOs8zXMqfFiAR2jh2jzlVOlSM4VXLlnYBNU7huXTOfuX8T9gXqj1U4PXymdQNQSNjx2XRur2tlbejS4qsHxvp5tudkwXYhFK4OruTh7qeoc1WSs0x6kgPcXbO1SCtzw3uG06yQxLLHAHBqNdjV4sRGIQQ+fRUgkJjEM8dw24obTorQ8Omr35WJ+9yqJGeNEcscJWX0krMmMK0EFlkS2dPnjuRye5zurF1BUHcTySW5I7CC22uWU+rw4FA1PDbHVPhsfWnjlF5T2swRy6X5aPPVgCCaTU/Vj7IpKj/begNJM0uVc7pG4PUViylzeOiMjaIIQZMnH5oTAj6xaAO1rpmkSAEs9VdgSUnOMrmtehmrgzVoioph5b1ji31lLPaVkTSyZMy8wSeE4NbqZZToLiaySRyqNvXC21WNRk8Iv9254I98MdgUFVUo6IqGTVHJWDksKXmq5xiHw/2sDlaTMnNY0sqXdshlKNGdBc9awO7AqWr5eoiKWjQL5XxUOL0IIVBF3mOVsQzCmSRJI8toOkGVy8c1ZfUzQqBvB5aUZE0D+2QfASLZFP90+E1+o20LHv/C7umx8DAPnXyLr2258uWJ3sPCoQoPGdmNYcWwF1VRl1gyhSVTqGJudcZy0qAn2UeuiPxAq28Jda53Jl3+fAghqHCUclVgJdtHdszYZ2HRnx4ibWbmRBK3pMVfn/ge5Y4AK/yNXF+2ilZv/ZQMwZUc2+rWGr779D6+8tDLlId8BcaTQ7fxgVsKk53OhxCz53LbFBWPdvHC4lPXUjVsRfikihDcWLaeCkcpPckBANaHVrHUO7ckk2J4z3C6CDLmMMCsRtM5aIoHVbgwZZK0WTxjIw8Fu3J5lEvngzzJvY+eyIOMpl6eVPsWk9lz57Q9Mhdv5G3ApdnZUlVIEPXZHFS7prMlF/mm7/OqkhpWlRTPRhNCsL6ssWC7TVFnPe+GyiVF21nkLWORt/D3LXd6eV/t7ERmj03npsrpMeWzLy0i2RRdiTD31K3GfkUkCKYnGVNavNB3kgea17GxvIFvdewlkk0hEJQ5PHTFw6wL1U6elj9LEaJoevtsuNBbpwmVZm8pK0uquK6iGVNaKEJguwxhOiklo6kEj3Qe5iOL1xB0XEb9rvecTP8j4LavZiL1EvH0Tpy2JSBnZvhKaZHIHiRtnKXM/dE5tZmzsvQm+wu2CwRXBVbOkBt4JyEQXF1yFa+OvFkQrhtOj5Awk3MynIQQbAgt48BEB88O7OFHA3updpZyW2UbV4eWErL7cKmXn/AOsOdwNxPRFKMTCTRFKZhafF7nJQ2n2VDu8GBYJj773BZLDtU26wJOV+2sCbSyyp+fswWCiVyMEvvC6i/+jzec5pNZNu+2J1co4pK3SeT5ShJkkTTTGUfOsUbe5UTKOMuJ0d9hIrMbm1JCqfNmvPpyHGoVmupHETrh1BucmfjKO963/y3IWibbh9rZOdxJucPDVcHaK76KVYXC2lAtz/Ue52RkiDOxMJqioAjB3fUr+NbpvfQnotgUlU0VTbMSuAeSEd4cOsu+0V4cmg2HZuOmqsKinZA3vB5oXsvTPUc5Mj4ISDaVN7GutHbqmKSR4+jYIJFsmoxpUuP2cWpilPUVdTT6SohlM+wZ7qE3HqHG42dDRT1uzcahsUFe7u3ghd52cqZJpcvLTTX5DBtLSg6NDbBjsAu/3cH11U0E7HlOyoHRAY6GB7GrGpsqG6j1+JHAcDLOjsGzZEzzkp619/DjgYDzNoZi32Ag9jVA4HNej00pBaFgmGHimb30R/8RgKB725zazEmTkexYwXaP5qbSUfGucfOEEJTppQTtAcay4zP2TeQiZMy5LWZVofDLrR9mJDPBW+FT7Btv50S0h6+2P05Jl5d1JUtYH1rKcl8DVc7gZR3vL35yC6ZlkUhmyObMAnmMYlIWc8Vvt92ClPISfNNpeO06V4Wq8V7E0Do3dkta/MfZ7/PFlk8tqG9zNpwMy0AIUFCn1FIzVn51q6vvXnnwcxpRVwI2JW+NXqoem8TAtNKAQFN+vCrCWzLHUPxJIpl92JQgzSW/QIX7LrTzOARSyvNCde9hIVCFQrOnlKDdRZO3FL/98r0THpvORxeto8zh4a76Fbi0vBioYVl4bDqnIsNI4O76lSSNLAJYFaziCyuuZygVQxUK9Z4SHKrG51o34Z0MIX58URs+uwNNUWnyhvhky3oE+ZWbrmh8puVaQo4898Nnd/DFlVsI6i42VTRS7fIxmkmgKyqN3ple1EQuwzdP7afeE6B9YhS3zU6Z001fIsLnVmzgsc4jdETDLC8p54WedrqiE3xqWRs+u06p04WqKNR5A1Q4PeiqSsY06IlP8MZAF23lNbzYe5r+RJTPr9jAwbEB/unIm2yqbGAiE+dvDrzGF6/aTFB38eCJvUSzaVaUVPB6/1kSuXenJtl7mDt0rZYq/8/TN/GX9Eb+Cj3x8GRITmDKBFmjD5BU+j6H07Z0Tm1a0iRmJAq2ezT3O85tuhAOVcdv8xUYTnEjWVTraTYoQlDhKOHOqvXcUL6awdQ4RyJneGX4IG+MHmHX2HEqHAHWBJrZWrGOZk8VdkWbDJMtfIE3NBbla9/dwcBwBNOS+bTp8+DzOPjLX/vggtqeq8F0DiV2J19cfcPUgrU72Y9bdRK0BzgR68Q6r2+WNBnPRhbUL5iH4dQeP0jSjHFV4HpUVCZyI7w28kNafW20eK+6dAPzxLSXRyIpTiaWmKRyXXNucb498NpXEE6/QdI4iylTaLPE1BPZ00hygIrHPreX+Z1CzooQzR5GYuDTV1HuuhO1SI2njDn4LvTufw80RWGx79ICfwuBbdKwAYrypq4uK9TS0UT+nKYLjJoW/7TUQrNvWvpi7Xkeo3NY4j+vRIeisqKkcsa+Jcw+XsOy+EDzcp7rPoVLs7GmtJrHOo8ylk7yVNcJ7mxYSoXLQ70nwA/OHOETrWtp9JaQNg1e6evkhuomQpOldoZTcTw2nQeWrKGtrIZyp4dHTh/GkpLvth/i5trFfHjxKjKmyR/ufZGdg91sqKjneHiY37p6C4v9pdgUhSe7ThTtq5QWKTNG1BglayYwpYEQCjah41R9eGxBbMIxqwfRsLJEjRESxjiGlUMVGg7Vi99Wjl0p5JnlrynpTR4lJzP4bRUE7cV5NikjynDmLFJalDoa8GgzeXqWNOlNHicvbNiMQ3VjSoNobpi4EcawcmjChkP14LWVoivuWceRMqJEjREy5+4BCpqi41S9eLTgrGM5/z4mzRjR3DAZKwnSwqY48diCeLUQypy87YIy94dwaE0Mx79JOtdJzhoFJIpw4NGvpsz7MfyOG+YsmWJJScZMF2zXVX2qbtm7BZvQcBZxPOSsLKY1f66pEAKP5mSRx0Gzp5Jt1RvoTY7yw/43eX3kMI/1vsEP+3fS7Knizqr1tAVbqHIs3Av1n4/torN7lJs3LSXgc3JhjrR9Dll1lwuqolDmnP5Gbx/eTa2rkutLr+Er7Q9R45wunSSlJGMufCE151GV6lW8MrwTXXFSqlexffgHVDjqqXVeulaXmEyBN60UEvOSoS8hBIrQUYQDS2amuEYXIpk7S9oojF0XbXPyJTNlGmuy1MilEHCspyf2nxhWlPH0LspchdW4pZSMJl8AwKFW4rb9eNUuk9LAnOQvqcKJKhwFKwwps4yndr4b3XsP/0vhUFVsSv6/x6ZPSiLkSfh9iShnouOMZ/Ifszsalk49k1PaWMwktZboTgJ2B4oQOFSNnGVOEdWrXF4UoaApkqDuIpJNT4bmJG7NjiIEIae7KP/BsDIcibxCR3wPw+kzeeNHZlGEiq648dvKafKs45rg+3FpM0UupZREcsMcGH+Gs8kDhDN95Kw0mmLHq5VR61pGW/BuKhxNXLhwszB5auDvGM/2syF0HzeWfxK1yLw4lO7gh/1/TdZKsa36i7T6Ns/Yn7MyPNX/Nxgyywdqf4NSvZ6D489xMraDsUwPOSuNTXHgtYVoK7mbtSV3FvTFlAZdiUMcmvgRg6l24pP3QKDgUN34bOWU6nVcVfI+6lzLi/7elrQ4GX2DY9HtDKZPkzDGkUicqoeQvZ4W70auKrkDm3LxeTf/m2v4HNfi0deSNfoms+ckquLDrtagiIsbcIWQM7wN56Ag3nUJjfy3rrAP5mSSx9tp17QsziQG2TV2nN7kCFKCS3PQ5K6kLzXKP5z6AUu9tXy88VY2hFoXRC1w2DVWtFTxsbuuvqyFqC8HPtZwD4K84dzgquFXln5m6tG3pMWfnfjagtueu+Fkr+LWig/z1MBDTORGuTZ0B6v9G7FdwmIXCJxanqxrWBFimUP49DVTXJ9z8vkXikba1VJ0tZKU0c1o8hX8ehs2JTAZJrTImqN0R76OKecmkOW05VfUlpVmIr2XkPM6xKTc+mx98OrLKHFsYiy1nZ7If+DU6nDbmhFCQ0qJJTOMpbYzknwJgUaV976LptG+G1CFA7uSX6WmzUFSZh8u0TQVbjVlgoHYI8SyR9+V/kkpSScyjA9HOLG7g2M7T9HfMczESJRcJodm03D7XZTWBKldUknr+kXUtVThDXpwuPQ5Fx49V2k+Ohbn+K52DrxyjN5TA0yMRLFMC0+Jm/rWGlZe18KaG5YRKPOh2RdeeubcuHpODbD3uYMcfbOdscFxLFMSKPPStLKea7etZfFVDbj9bhRF5MciBBeW1ZnvNYd7xtj7o0Oc3NvB4NkRUvE0mk2jtDbIotX1tN2yisYVdbh9znemcOt5H2qbotLgDXBTTTMbKuon3yM5RUJXhYIpLTKmiWFZU5l1ihAFKsS6olHlyvOnNlTWkzZyDCZjtJaUoav5324snaTU6WYgESN3XjkGiSRlxNg+/B8cjW7HsNLYFRe66sYlAljSwJQ5RjNdlDka0S6QIpFSMp7r58m+v2YgdRpNseHRSnCpDWSsBLFcmMMTLzCQOsWWip+i0b32in6kM1aSlBFhe+Q/OBZ5FVVo6KobXXVhWDkiuWF01UWxEiad8b08N/BPJIxxnJqPoF6DrrhIm3GSZpRwtpeRzFlW+W8pem3DyrF//CleH/02hpXBqfqocDQjUIjmRuhPnWAgdYrxbD/Xl38ch+KZ03ulCB3HLBnK80FeINJGxprJGTKlhTkPEeErAUtaGEXkWVShLmjuyVkG0VySE9FunurfxclYD1nLIGDzsLXiKm6tbCOk+0gaGV4Y2sdT/Tv5avsPKNV/ksXe+ZeGeuB9bfzDt7bz5b97kqa6EHbbTJPCqdv40J1rFzSWuehTXQzndPsEks8tegD1vIWTgsKm0NoFtQuXMJyiuTCn44en/hYIapzNxI0J0maCw5E3aXQvI2i/WJkABZ++FrtaQdYc5lT4T6j03I1dLQdpYsokDq16ss7cNFy2JoLOjfTFehhKPIElUwSdm1GETs4cYyT5ArHsMTz2pcSzxy85UK99FQ6tjrTRw+nxPyORuw+HVgNYmFYKTfFS7r59eqxCYFNCNPj/D2mjl4nMHo6N/goVrrtw2KqR0iCaOcxw4hly1gRlrluo8tyL4PKSv8/VystZ45gygyUz5Mxx5KT6djJ3lkh6H0LYUYUDRejoWtVUEWNN8VHi2MBYajuxzBE6x/+WcvedaMJDzooSTr3KaPIlPPZlRDIHLtKHiUmNpwymzJA1R6bI88ncWSKZfSjCgSp0FMWJrpYV1b06H5lUlhO7T/Ojb77G7mcOEA1fXDX8HHwhD5vubuNjv/5+KhrmFh4b7Qvz/Lde58X/foO+04NFa3wd3XGKZ77xMpWNZdz6ieu55WPXUdFQNu8X17IkXcd7efTvnuH1H+whFZ8ZJugCDm4/zpNfe5GV1y3lvv97J223rMLlc84n4W3mNU2LozvbefrrL7HrmQMkIoXcv87D3ex+5gDf+asnueqm5dz+yRvZdNc67M53Llzhsdn5YNNKHu88yoGRASQWDd4SPti8EkUIAroDl2bnweN7WRIoZUvN7B5cIQQfWbKGfzi0g/GDr5MxTTw2Oxsq6vHY7LSV1fDvx/ewyB+iJz4xYwWfszLsDj/G4ciLCASLPRtYF9xGlbMFh+LGkFnGswMMpE4R1GuxXVB4O2lO8PLQg/SlThKy13Bd2cdo8W5EE3YsTPqTJ3h99NucTeznxaGvc1/tbxPUr1zNwpyVZt/4U4xmemgL3s1y3w0E9TqktIjkBulPnaLBVagfZ0mDPeHHiRmjNLnXcVvlz1Bir+KcgZUwJuhNHWU000O1q1CQ0ZIW7fGd7Bj9LgK4NnQ/a0veh3sypJg0I+wff4ZdY49ycOJHBPUa1pVsu+zz5MWgCAWHqhcYTmkzTXqOBOwrhayVI16Ef6UrdtQ5JhJJKUmaGdpjvewfP82rI4fpTgxRYveywt/I+mArm8tW4LflF/VCCAI2D59ovIVqZ4ivtj/OG6NHF2Q47dh/hgPHe6mrKiFrmAXzl8e1cEmWwWSM/WP9NHuDLPKHFix5IoQgaPcXbNtafu2C+3ZRwyltJulLdc7YpgiFKmcTY9lBBIJyvfaihpMQAq+9lVrfx+ma+Bdi2SPEw8dQhAOJhZQ5qr0fLjCcNMVNne+TJHIdTKT3MpR4ipHE8wihYckMquKm1vdxdLWCk2O/e9FBCiFwaJU0+D9L5/hXSObO0DH+16jCSd6Nm51Uz7694Dy/fhUtwS9zevzPiWWPE8/+Depk3y2ZQaBR7rqd5pJfRFcrL3smlSRHf/xRhhJPImUOS2axZGaSUwWDiccZTb2CImwowo4qnKwo+1sckzXvhFAoc99BNHuYgfgPGEk+Tzj1JqqiT4ZODcpdd1DtfYCjI79EzgoX7UVf7LuMJJ/FOq8P54j5g4kfMJp6Od8H7NjVUhYHfx2PvVACACY9I8kMj/zN0/zoW68y3DM2LydLdCzOmaO96Jd4Kc8ZR2cO9/DQHz7KnucOFq0mfyEGz47w8J8/waFXT/Azf/VxGlfMPUNOSsnJPR187Te/zbGd7Uhr9oEZWYMDLx9loHOIT/3eh3B55xuCmDRqswbbH9nFw3/xBD2nBi55jmVa7HvxCB0Hu+g+3scDv3o3dt122Z5dn93Bp5ddQ5nDzW11LZPhOjsfW7IWr13nrsZlLAuWM5iMTfK3Sqb8IEHdxZeuup7u2AQemx2nltet+rlVG6l0eQFoLSnn51ZtRAAtgVJ+ae31nI2NowmF1pJyypxupJR8fOk6TowPY1gW2xpaieUyU/dsPNvPscgrmNJgifdabqv8abxa6dQ9sAkH5Y4myh2FWi9SSroSh+lKHERX3KwP3UurbzPq5GJFRaPOvZKb1c/y7a7fYjTTxZHIS1xf9vErmmnZlTjElopPs7Zk23RITKiE9DpCenElbolkLNMLQLOnjRL7TIFQj62EVtvmyYWaKDg3YyU4GnmJlBlhdeA2NoTuw34eZ8etBVgf+gADqZOcju/m8MQLrPLfjK6+c6RsVagEbP5CoUkjTsyII4vqRV155A2eFOELiOEAXptnzjIJFpI/P/4wp2I9jGVihHQf99XdwKbSFTR5KvFproLxnSOFr/I34VRsRHOFxttccPBELxuvauKn7t+Iy2kvYBKLt6Gk/OpAJ3924CU2VTTy+9fcTqljYc+MJS0OR06xyj8tKJo2M/SlhljkuXitxdlwUcOpTK/mzspPXLBVYmGioMIcY8Sq4qTe92kCehvDyWdJ5c5iySya4sWp1VPqKq7g6dQaWVX2VcZSLxNO7SRjDqIIO27bYsrdd+Kxt5LInSagr8dla+RiBHBF2Kj23I9PX8NQ/EkSudNThO9iHq9zEEIl4FjPmoqvM57eyVjqVbLGEELYcdmaKXXehE9fjXIR8qim+PDrbShCL0rMvhQESt7IE9MTkkObTeNI48L7YFcDtAR/m5DzRsZS20kb/SjChkOro8y1Fb/ehkWOcvdtxLOnEBT+pkKok4q9l+6DIuwXzdSIhRP8+28/zPPfeh3TmGnIeEvc+EJenB4dzablBRGTWRLRJNGxOJlUFqEIrv/gevyl3lmvcQ6dh7r5m5/+Oh0Hu6YMKc2mUl4XoqQiQEmFH6EIIiMxxgbGGe0Lk0llyWUNDm4/xl9+9l/5wt99ktb1i+aUWjt4doS///lvcOZIz5QxKBRBRX0poeoSQpUBDMNkYiTKaG+YscEJhrpG+fpvPczK6+afWGCZFs/+53b+4/ceIT4+PfkFynyU1gYJVvhx+52k4lnG+scZ6R0jMhrL83NGYzzyd09jWRYf+ZV7cLgvj2CnrmqsCuWJ5I22aW+WX897bWwKrAhWsCJYUXCuqigs8odY5J9Jal9bNv2shRwuQudpPDX5gjT5ZhYcFkJQojvZWNlQcA0pLboSB4nkhrArLjaE7p1hNF0KOZnhTOItMlaCKkcLLd6NU0bT+Qjaa2n1bWbf+JMcj77KNaEP4FQv/cwuFEG9hjWB2y/JI5oJgc9WRtwYoz22k0WeawjYKybHM30/itbflBDNjXAmvh9FqKz0b51hNJ2DXXHS7Lma0/HdDKU7ieZGKXsHDSdNaJTrIbqSPTO2p8wUZxLdrAmsQH0HPWDn40yiq2ix35A9WJQ0Xgx5Q36IWmc5n2i8lc1lq3CrjjkpiCtCIaj7KNUXVqT6lk2tPPXKEfqGJgj4XKgXGEqqouBzL6yUzZHwINFsmqDD9baqElhS8mT/y6zwLZ6yV5JGmsf7XuRLSz+9oDYvajgJoaCd98IMp/s4EnmThBnDpwVZ5b+WoF44+RVpCUXYCDjaCDja5tw5IQQ21U+l5wNUej5Q9BivfRnrqr45pz4IoeWL5QaLF0I8H1JKeoYn+OEbR7FpKh+7ZR0V7vdR4X7fnPt/bgw+fSVtVf89r/POQRF26v2fpt6/sB94sheoioty9+0FXrVzUHGyJPibxc8WCg3+z9Lg/+zb6EMe6USGx//5R7z8nTdnGE3eoJtrt61j/e1rqFtaTUm5H4dbxzItouEYI71huo73cXJvJ2eP9XL9B6+55KQQG0/w4O9+j9MHzk5t85d5ueNTN3HDveupW1qN3ZH3tJiGSfeJPt564QhP/PPzDHWPAtBxsIsHf+e7/PpDP0eoMjDLlfIwciaP/cOznDk8PUHbdBs33r+euz93K02r6tAnw2KZVJb2fWd49fu7ee4/tzPWP86rj+66qIeqGI7tbOdbf/zYlNGkagrrbl7Fts9uYdn6JfhLvQglz2eLjsU5trOdp//9ZXY/e2CqH8984xWaVzdw/QeueVsrxP8pkEgGUqcAcKt+qhwt8/I4GFaGkUw+mzeo1xSQxs9BFRrVzhb2jUPGTBDO9FLjuvTcs1BUO1sLuFiXgiJUVgVuZjTTRU/yKI/3/RmLPOtZ7FlPhaMZ7RIc1uH0mSki+fHoa3Qm3ip63FimG8jf+6gxQhmFBu2Vgl2xUeuqZs94IRVh3/gh7qzciku7jGKrc4QpTd4c21t0X5WjArc6tz4pQuGLS+9nibcGtzY/I8Vrc/HTi++mbIGG05FT/RzrGGTXX/wAn8dRUOQ34HPy9T/5iQUJHkRyaYQQ1Lj9OBZQ81NKSdRIMJ6dIGEk6U0Noop8XdOuRHEl+blizr0ZyfTzwtB3KdUrqdBrGcsO8aOhh7m14gFC+twrwP9PQt9IhAef3o3LYef9m1e+rXjte8g/yCf2dPDkv71IJjWdClq9qILP/vFHuGrLClzeQs+dy+eksrGcldctZetHNpGIJAlVl1zY/AyYpsWPHnqVg9uPTW0LlPv59B98iC0f3jhlMJ2Dqqk0raynbmk1TSvr+MrPP8jg2XxtqyNvnOTxf/oRn/rd+2clU0spOfLGSV5/fO95bSrc8rHr+OTv3U+gzDfjerrTzopNLSxa00CgzMu3/vgxTGN+6cfjwxG+/RdPMDGcD0EoqsKWD2/ik793P2W1wRnXE0LgL/VOEdL//gsPsudHB0HCxEiU7/zVD7nmttU4Pe9ModN3GzEjL4jos5cX9RZdDBYmSSMCCLzaRSoBCHCqPlRhw5QGCWNutdUWCo9WMi9VeMjzVlf4tiClZOfoI4ykuxhJd3F44nnK9EZWBW5lkadtUoqg8NmP5vLviMTiwPgzF73WuSh1C3o2AAAgAElEQVSFYb2zvCJVqNQ6a3CqDlIXyBJ0JXs4MHGUjaGr39FwnZSSI5HjdMTPFuzTFTsN7to5h+oUIbiq5NLZ3FJOs/zOJVo4VTurAwsn4N+9dRU3b5zdU66q8yvifj68Nh1ViBnOm/lAIulJDvDMwHa6kwP84+n/nuqLTbFxb81tC+zZPAynnmQ7Vc4Gbii7BwUVUxq8NPwoA+mu/7WG03u4vDANk0e/8gwTI9Ncg0CZjy/982dZuXnpJScuIQQurxOX99Iu7N72AV7+zptk03kumKIItn1mC7d+/HoURcx6LVVTWbtlBR/7tffzL7/2XySjKSxL8sJ/vc6N921g0ZriK+VcxmDXM/sJD05/HOuWVvPhX767wGg6fzxOj4N7fvo2Tu7pZOfT+y85rnOwTItdT+/n2M726eu1VPGp37+f0prgrOMTQlBaE+SBX7mbrmO9eX4ZcOZID28+uY+tH9k05z78T8a5j/d8PTTAZDZqfrWqXMToEpMVBRRUJNPnzOtak//mAgVt3mKGQgjsipN1JdtY7F3P4Ynn6UocYijdQWfiLc4k9lPnWsGG0H00e9oKtJjO3UcFlfWhD170fkD+ngTthZphVxJCCJrc9VQ6yjmT6J6xz5QmP+h7mnpXDTXOqnfEeJJSMpge5rH+pwsI6wAl9gArfAuTB7gUdowewWdzvy1j6XzUXuCFL5Jzs2CsCVXzSOch+pMRMpY5b69TflGwmKXeJr56+lv89KKPogkFMUkxejvCn/PryWW8Ke/h/z/0nhrkyBvT1auFIrjj0zfSumHxZZ0kLMui/a0zdB3vndrmL/Nx50/ddEmtESEEQhVce9c6nnnwFY7vziuqR0ai7HxqH40r64q2ER6c4Piu0zNCbRvet5aqpktn5bl8DjbevY79rxwlk5ybKFsyluatFw6Tik2voLd+dNNFjabzx9i0so6WtuYpw8nMmex8ah83fujaHzs9lisBu5IPg6TN+ZNiFaFgV/KJJRlr9vPzBlYOU+bQFBt2Zf7ePEPmpjJorxTOPS9+WzmbSj/K6sCt9KdO0R7byanoDrqTh5nIDfHB2t+g2jnTu2CfDCcpQuWa0AcLBDp/XFCmh1jkbuRsoqfAEO1PD/BI7w/5ZOMDBGz+K2o8SSlJmEke7XuSziLeJoBl3hYqHFdGTPd73a+y1Fd72QwnS0pe39vBroNnSaSyBTaCx63zy58p1D+cC7ZUL6LOHWDH4FkGEhEavZee287HuWM1VO6p3oqu2C6bJMicW6l1LmIgfZaXhh5lz/iLvDD0XcLZIaodjZelI+/hfz92P3uATHJ6hVWzuJJNd1+NZru8xEwja7L3hcPkMtMr/KtvXU1JxcU5SufDF/KwYdu0/oiRMzn6ZjvjQ4Uy/VJKxocmOHt02lBTNYXN75+b+19RFBatbqC8bm4FoPPE7iiHXp1WwnZ6HGy8a92czgdw+5w0r66fce/7O4YY7S2s6TUfSCmJRJJ0d43OKYPx3YEgqOe9HhPZAdJmbF5nq8JO0F4NQDjTP6snSWIxnunHwkQTOn77tGdeML3itWbREpJSkjDC5KxC1esrBUUo+GzlLPVexx1VP8+9dV/GrQaI5obZG36i4PhSPZ+VZEmLodSPb9kmTdG4ueKGokVzTWmxJ7yff+p4kL7UQFFdpcsBwzLpSw3wzx0P8uboHowiv7tbdXNn1c1XTPMrbs5N93Cu2HngLH/x9Rc4cKKPgZEoOw+epXdoguMdgxzrGKA8tPBkiFKHmz+45naEEPzhW89zYmKYSDZFzjIxLWvW/9YFCw0hBI3uWuJGknA2MvU/kpub/E0xzNnjVO6o5dbKBzgS2cVQugevFuCW4IfnSA5/D/+/w8gZnHqrcwaPp2FZDfWt1Zd9hWfkDE7smjmJr7lx2bw8KUII1t60nIcUgTTzy6iek/2MD01QWoRfNXBmZIZeU0llgKrmub8bZXUhSsr99Jy8tJwAQPeJ/hkhz7ql1XhL5iYsCPnxVTSUotm1KQMnGo4z0heeszZWMUgJb7x2iid+8BZ/9KcfprSs+MSZyeRQVQVNe+ezmQSCetdKDo4/S8ZKcDK2gzWB24pnjhWBTdGpcS6jM/4WE9l+RjJdVDoKOSaGzNKRyHPeSuxVlJxnOClCQZ/MsI3mRvJeJXHh+RmG0mfIyQx28c7WAxVCYBM6ta7lLPZu4ODEc4Sz+Tpx53e0TG/AZysnmhvhZGwH9e7V88zqe+dQ76plU+ganh/aXrDPwuJI5Dh/2/6v3Fi2iY2hNsr00iKtzB8SSTgzzptje9k+soO+VH/R4I0qVLaWb6bScfF5w7BM0tb8y4XkDfHLa4S/uqedpY3l/Prnb8OSkj/9lx/x65+7lZxh8uD3d1LxNgyn9sgoCSPLteUNPNJ5iP+z/XusLa2h2u3DfhFNp0ZvkPuaV0/9LaVkb/gwO8cOEMnFsSs20maGtSXLeX/Nwrxh8wrVBe2VrA/eSsqM49a86MrsL7NhWjz++hGe3Xmc+7es4ea2Fjr6Rnl21wk6+seQUtJUGeTW9UtZVl9edAKVUpLJGfSPRtl9vJujZwYZnYgjgRKvkyW1ZdzctoSasgDaRT6KUkriqSyHOvrZc7ybrsFxEuksdptKZdDHktpSrlvVRE3Z3N20UkrSWYNHtx9i+/7TuBx2PnH71bQtrZ1S5bakJJnOsr+9n30ne+geGieeyqLbVGrLA6xfVk/b0jq8Ln3W62YNk5NdQ2w/0El77wiJVIZiiVeaqvALH7qBFU3Tk/O5PgyPx3ntYCf7TvUyEU/hcthZUlvKzW0tNFUFsb0DH6/oWJzx4ekPvaIq1C6pumwp8OcjEUkx2jetR6W79Lw3Z572WVVzOXaHjXQi7yUbG5wgOlao+yKlpPvEzNI/lY1lqNrcDTVviRtPYO4p2meOzORqBMp85LJGUeHL2aCqM9OVs+lcgVjnfCEEbNy0hNZl1fgDxbOCTNPi4f96k7XrGll91cJ0VN4uqpwtVDoX0586yd7wE5TYq6lxLptBFM9rtZlILFRhn/ICKKg0eq7iSOQlxrMDHBx/Dn/Zx3Go3ul3H4Pj0dfoSx5HoLAmcDuqmEn2rXA0M5A+RU/yCBO5QUL2c3NH/tr9qXbaY1e2FFLGTJGzUjhUD4rQJnlZ+WdCSknOShPN5TNM3erMBYMQArdWQqv3OvaEH6c9tota13JafddjE3bOvXASiSVNclYKCwuXemXDYbNBILil/EZOxTroSvYWPaY/NcCjvU+wY3QXq/wraCtZTb2rFk1RUVBmcGMunAPg3FgtLPKq5N3JPvaGD3A0eoK+1CDZixg8SzzNbCnfjHYJ4cuTsR6+cuqx+Q4fgLHMxQvWzxfhSJLWRZWUh7wMj+U9tznDpK6qhLYV9Ty/4wS3X7+wTNJvnNzNi73tZEyDpJElYWTp7750/6+vap5hOFlYvDKym+tK1/H84BvcV7uNN8cOoKsLlziYs+GUNlPsCb/I8ehuJBJFaKzyb2Rt4Hr0InoTUkoGx6IcON1HbXmAeCrDPz+2g1Q2h27TyGRz7Dxylh+8dphPb9vAh7asweOc+RG1pOSvvv0yz+w8QdYwUISCy5GffJLpHC/sPcXDL+7np9+/ibs2LS+Qe4f8j3ioo59/euwNDncOIK38R09VFUzTwpISRQgOdw7w+5+5Y6r0wyXvR9bgoWf38K3n9uLQbfzMB65j9aKqGccc6ujnT7/5ImcHw0hLots1dJtG1jDZeayLR185RNvSWr78qduoLi1MB02kMnzzub1887m9CCGoCvmwaSqRRJqhcP4h1W0aTdVBnLqzwHg0TIundx7j35/cxeBYDE1TcNptZHIGrx3s4OEX9vOTd1zN/Tetwe+5siva2HiCZHTaTazZVGoWV1yRCXS0P4xpTnu2fEH3gsQlbbqNYFWA/tNDQJ4HNNY/fuGiG2SeA3U+SqtL5uXhUlQFX8gz9eG9FAbOjMz4e89zB/jU8kPzSqqSlsQ6zwo3sgbpxMILX8KkflLQTUlwdiNwZCTK/v1dLGl5d5JK8srJlWwMfZjnB/+FkcxZvt/zRyzz30C1cyn6pHJ4NDdMf+okdsXF1orP4NYCU+dXOVrYUHo/Lw1+jf3jTxMzRlnuuxGn6iNnpTmT2M/RyMtIJKsDt7LEW6hSvMK/lePR10iaEZ7o/UvWBbfht5VjSoPhdCf7xp9GEWqBavnlxHi2j+/1/B41zmXUuVYSsFeiCTsSSdKY4GTsDc4k9mFXnKwO3MqFqw9N2GkL3k0428/p+G6eG/hHOuJ7aXKvxan6sKRB3AgznD5DV/IwawK3cm3ph4rW5bvSEEJQ66rm3tq7ePDMfzORK/4Rzlo5upK9dCV7eXrgeUrsARpctVQ5KynXQ3g0D7pqR+X/sffe4XGc1/X/Z9r2CmAXvTcSjSTYi9hUSDVKoqxqR7aURI5L7DixEyfx1/k5xUlcEseRbcW2HFu2ZLmoS1SjSLH33sACgETvWCwW22fm98cCIEEABECCku3oPI8eSdidujPve997zz1HRBBEdF1DRSOiRvDHA3RHemgOtdIQbKI31jeqdDQWvMYUHspZT5rJO+E4NRAPc6a/iUxzCoo4lfs4+UaDycJmNuLzh9B1HVkS0XSdbt8A2eluLGYD3b0Do4bLySLFZB2l5zYZzHCNzJjrOkS1KJXOEvZ2HyXd7OWOjFU8Vfcb1qbdcBVnNoXAqSF4mvZwA7elfxyb7MQf62F399t4jVkU2MY2fhw66R3H6tl3qoGFZTksqczHZjbg6w+xcf8Z9p5q5Odv7cfrsrF20QykS0QGRUHAYTXhtptZMDOHioJ03IMTYFNnQmOptrmb/92wl9lFmeRnJI1aBRyra+Xfn9lEXUs3LpuZZVX5VBakYzYaiMRinG/r5XhdK7fMLx1x7PGvRycaU/nte4f5xdsHkGWJx9ct4c6l5SMyN4IgYDYakCSR6pIs5pZkkZ3qwmI0EI7G2XuqgQ27T7L/dBPPvnOQL9y/YsREq+s6W4/U8dy7hzEbDTx44xyWVuVjMsh0+gb41aZDbDlUi8Nm4vMfWU5xlgfHJdkbXdfZdqSOJ57fTn8wwo3zSlhWmY/NYiQYjrLvVAPv7D/D02/uR5ElHrypGsN1zDxFQhFikdjw/4uiiMVxfYK1gb7giPYOxaggXQWPShAEzJdJUAR8wUTG6ZKhQAeCl2VqjGbjlFrDBUFIZN8maVXX3zuSlKzroKvXRiLWVA0tPpp3oes6He1+Nm86SXtb34igNL/Awx3rqpEkkb27z7FzR6LLz+E088CDi7Bf8hv39ATYteMsRw83cL6uk5dfPMDuXYmSalFxKnfeVf2+ZSIEQaDQNg8t9U/Y2vkM3dFGDvVu4FDvBgSEERNMkW3hmNuXO1YQU4Ps7n6es/27qe3fhyKaUPUYcT2KJCjMcq1hUcpHBsnkI5FuLmZe0jr297xMe6SWN1ufwCCaUfU4cT1CmqmYxSn3sb3zGfpiYxudXytEQSKsDnC6fwen+3cgCQqKYERDI6aF0dEwS07mJd1JgW20Bp8gCLgMaaxOfQxFNHK2fw81/m3U+LeNuo+SIKOI5mvqZrpWiIJItauKzoxunmt4kfgEnY4aGt3RHrqjPeA7Ovx3WZATApMIaIMZtbE4S5OBU3Fwf/ZdFNsKJv38i4LIp4rXkWqcPG8T4MtHfnw1pzguZhSmsnVfLb3+ICajQrLLyq83HKSty8/WfbU47aar/rX/dOYiPl4yb8rbGS7TkhIEcCp2uiK9ZJq9vNm6FYdiu7pobhCTDpz6Yt2kmXLJMOcjCiJ2xYVnIIPAJLRJfP0h7l5eyafuXorLltDp0XSdpVUFfPWpN9h7soFnNx5k2awCnJepjD5220LuXz0Hp9WEadB0VdcTnVNzirP49H/8ltZuP4drm8nPGKkeHAxH+dEru6hr6SbL4+Tv/uhmKgvTL9mPTiyuEorGsBgnMCsWExNIKBLjlxsP8fO39mMzG/nkXYu5bdHMMUuFRZkpfOfP78ZkVLCaFCRRHD7uovJcZEnk+S1HOHyumbbefjIvyTr5gxG2HaljIBzltkUz+Ogtc4fPOy8tCbNR4XxrD52+AO29/cyfObLk0dDu4+m39hMIRXnwpjk8eusCHFbT8PFXzinC7bDw9Bv7eObtA6yqLibbO7WXcCrQ4hraJROuIAqJ4OI6QL2MlCwr0qRUvy+HIAgoxpHllXhsjIFW14mGRmZqDMapGwTLijzZuIlYODbi/0VJHCwNXv1ooBiVMXWqWlt9fOPrr2IyG5g1K4fac+3s3HGGVTeWU1SShiQJCAJ4vQ4KCr0c3F/PwQP1rLt77ojAKRZTiUbjGIyJYcfuMJGcnPDPstvff/0oSVQocSwlwzKDhoFj1AX20xtrI6qGUEQjDiWFTMtMimyLMEuO0dsLCnOSbifPNofT/p1cCB4hFPdjlKx4TfmU2peSbi5BEY1jBguyYGBxyv3kWRNlv87IBeJaBLuSTLalknLnKqyyizP+XUiCMmbwNRS4iIKMWR59jhMh2ZjNQ7lfpz5wkI5IHf2xLmJaBFGQsSlJZJhLmWFfituQMarUeCmSDFncmv45qt21nO3fTVv4HCG1H0mQsclJpJoKKbDNxWvKH9OZYDQSJuraYPAmi06ESXq3TQRZlLnJuxxV13i15c0xveImQlyPE5+G5E2q0cN92XexMGnyjR0AVslIgTWNdPPkMzK6ruMwTK9i+42LS3HazJiNBkxGmdtXlvODZ7fx41/vxGRU+MzHVlz1vp2G6RkTRETWZ96C2+BgtXcxP7/wMkE1xL1ZY4tBTwaTDpycSgqHB7bRHKrFJrvoi3XREW4i3zpx/TLZaWF1dRHuS/R3REEgxWnloRur2XuygTONndQ1dzGn5KLGhyAI2CzGUcKTgpDgZ5TmeMlLS+JEfRtNHaO7nU43dnLwTKKW/ehtC1hQlnPZfgQMijxmiW/E9wCzQSEaV/nlxkP8ZMMebCYDn7/vBm6eVzpuSUaWRFKTRpPjhMFM2pySTN7cc4qBUBRff2hE4BQIRmjp7kOWREqyvZgvmcATZTs76ckOGjt8NHeOvHZN1zl0tomzjZ2kJzu4Y0n5iFJcIhumcO+KKn717iG6/UF2Hj/PA6tnX/E+XAsEURyhSq3rOrHItZWFxoNsHPl7xmPqiCzJZKHrOpHwyHOUDfLo2EQQRhnlxqIqU9Xv0FRt0ltIyshnbsaCQhbdVo1suPrJxWBUyK8Y7Wm2d3ctbW19fOeJR0hLc9LTE6A/EMZolCkvzxwOSguKUskr8CJJInV1ozMkqalO7rl3PsePNXLo4AVW31jOkmUlV32+04FEF5mHCtdqKlxjWz+NB0EQkJBJMeaQ4slhKQ9OeXtFMJJjrSTHWjnu99ZlfWnczwyimYdyvz6l414KSZDJsswk6xoVzQVBwChZJryWyUDTw/RH9tEX2kIkVo9OnLykf8UgZ6DrGpH4BcLxOhzGJYhX4NleCUbJyNrUVbgVB79peoXOyLV1k04VAgIF1lwezLlnyppNSQY7K72zsUhTX3japOldoKS4baxdfrHiNK8ih3/+wp00t/vI9LpIG0fD7v1EokSboAVYZctV26xcikkHTrmWErqjrWxo/QWaHkcSZGa7biDDPLEehNtuIdMztqT7jFwvVrOBgVCUk+fbRwROQxgiOWuaflH9VAdV07AOWVjEYqO2O3i6CU3XSXZaWVh29RL/kpggBb7w3lF+8fZ+7GYjn1m/jJvmlUzIYxniq6ha4hr0BPMTfXC/siShahpxdWSWRBC4hITIaCPKIR+0MY4Zi6mcaewkEouTZDeT6rYTjo6+PyaDgttuobXbz7nGzjH2NH0wmpUR2RtN0wn2X582a7vbNlgmS9ykaDiGOlamaALouk44MFKgzu62jsoeCIDlMsXtSCjCVOV3QgORScdaNufIlWNmURp3fvLGSYmDThWBwd8pJSWRHTIaFNxuKz09A9MqePchPoSux+kM/JpW/w+Iq13oJF4iTR/iRwqEYjU09P4LuUn/hMu86qqPZZAMLElZSJIxiZebN3DKf3bC0t10wCgaWZaygDVpq8kyT72rOM+axuOFt2ORpx443Z6xCLfBNuXtxsPQ/DZ0DYIgkOF1kuG9OguX6wFN19jbc5QyR1GiRDcNmHTgZJTMLEy6hbmulYS1IEbJjCIYJ6U3YTIo2C1jR7pGRcbrslEf6qG9d6SeylBp7GxjJ4fPtXCivpXW7n76BsKEozGisTjBoZLFGAN4Y4cPXYfcVDcW09Uz6I1Gmdd2nuBHr+0mFIlx9w2V3Dy/ZEJOlKZptPcGOF7XysEzzZxv7aarb4CBcJRINE4oGiMaU7GYlFETkM1sJNPj5ER9GyfPtxMMR7EOlrZ0Xaex00dThw+TUSEvfWSJMhpXaelKEB+P1Law5q+eHPsE9QR5HqA3MPlurKuBzWUdYeehxuK01LZfF2dyT2YSikEetnXxd/czMEhgnMqxIqEo3W0XnctlRSI53TVGxinhgXcpult7UdXJcx40TSPgG5gUMRwSXXuXwtfRd910k/LyPUiSyI5tZ5hRlkFLcy/n6ztZtbrsA19Nfog/LAxET9Lk+yZGOYsMx2cIx2tp7396+HNBAEXKQBQM+ELvXlPgBInKR5m9hIKSXHZ37+fdjm00h1oJq9O/qHPIdgpseaxJXUmlqwyRiU14x4IsStiuMtN2c1o110TuuQxHaprRdZ2q0sxpF84dSpKI1zjGaLrOO207KLbnTct5wRQCJx2d7mgrp/z7CcYD2GQnMxzzSDamTkj2EwVh3IsXBIZJ1ZHoyIF/IBzlJ6/vYcOuU3T1DWC3GMlJdVOYmYzVZECRJXafOE+nb+wadWiQjDzEDbpaBAYiPPX6HgKhCJqms+1ILctnFzC7KHPcbTRN58CZJn66YR8HTjei6ToZyQ4yUpwUWIyYDAqdvgCHzzaPub3dYmT57EJ2HKtn94kLPPX6HlbOKcJqMtDS1cevNx+hucvPrKIM5s0YWYLUdZ3IYIbJYlRIdk5c1052XF+3ckeKHWfKxeBCjWs0n2sjGo4NG99OF0xWI+n5Xs6fTJRpo+EY7ec70fWpWXm11LYTv+SZTEpzYU8arZUkCALZpRkj/tZ2vmtK3nMD/hD9PZMXZMu7rKTWdLYtIS6aNH2rySHMmZvHshtK+cETG8nOSSIe1yidkc7qm8qnao32IaaIwECYN7adwmo2sHpRCSbj5PzLfl/RG9qAJNrIcn0Jp2klnYHLzdEFFCkJWXQTjtVd8/EEhEFPQRMrPUupcM7kpP80h3uPc9J/Gn98auKoY+3fY0yhwjmDOa5KSu1F2GTrByPHIAjTTsx/ddNx4qpKZUnGxF+eIvyxML84c5DFqblUJqejXEG7yR8N82L9MeK6xsNF1ZjlS6ktkGRwElGnjxoy6cCpJVTPO23PkWxMx6G46Y628XrrT1mT9jBppitrscQ1dTizcTk0/WKAMyQ1AAmtl99sPsKvNx1GEAQ+enM196yowm42osgSopggiX/huy+NGzgN7S8UiaFdQ00hHItRlp/KgzdW84u393O0toVvPbuZb31mHWnJY9dwe/xBvvHMJs639VCc5eGTdy2hNNuDyaAgSSKiKLD1cC01F8bulhEEgRWzC2nr9vOjV3fzy42HeH3nSURRJK6qxFWN6pJMvvjgKpLsllHbDg2wVUWZfOWRmye8RqPh+rYHKwaZojl57Hnj8DBJ/PyJJhpPt1A4K3daBxJZkahYVjocOAEc3Hycmz62DHGS7bu6rnNg47ERFirZpRnjqo+nF3gx20zDOkjdLT201ndgd+dP6nhdTT34Oic/SBdUZuNItuHvTgRb7Re6uHCqeVKWK1OFALS29nLzmgpuXlOJwSjjcJgxmw1XdSxJEpEkkVBodPn4Q4xEQ2svv3njIG6HharSDLLSfjctTaYL4VgdBsmDRZk5riCpgAFBMKDp05slFwQBjzGZ5SmLme+ejT8W4EKwkeP+U1wYaKI72ktci6PqKgk2oj6cxR7yP5MEEVlQSDN5ybNmU+mcSZY5A6tsxShe3fsyWei6TlSLE9PjV8xcG0QFozQ9AXgwHKUwO+W6CNnu62jkyZO72NxSy3eX3k2Gdfzmh5im8k7zWQ53NVPoSGFlxkVBWgGRUnsBzze9RYWzBPMgN8wqWah0XR3HctKzZWvoPNmWElZ670FERNXjbOz4DR3hpgkDp2A4Rm8gNGbmIxSO0ulLDP4ZKRdvTIcvwK4T5wlH49y2aCZ/um4xVtPIBy+uagyEx3fazva6EAS40N5LMBwd1bE3WZgNCl955GayvC4yPU7+34/f4ExTJ9967j3++uHVYxLA99U0UN/agySJ/M3Dq6kqSkTkl56/puvErlDOMSoys4syyUxxouk61SVZCAI4rCbK89KYU5KFzWwYteo3yBIZyYkac38wgsVkwG75YNV8BUFgwdrZ/PY/Xyc0yBtqOtvGnjcOk1eehTwBQX8qkA0yc2+q5N1f7hj2cju06QSdjd2TVvP2dfSx762jwwOQpEjMWFCE2zv65RUEgaRUF7llmdTsrQUSGbUdL++jeE7ehIOlruvUH2+ko2FyPDNBEHB5HMxaUca2F/YCCWL56z/eRNUNMzGYpjcrERiI4OsNYrUGOHzoAqIoYjIp5OYlU1SchiAIxOMq7e1+wqEo7e19xKIq5+s6CQWj2O0m3EkXV9nJyTY8HjubNh7HZjMiySIOu5mSGekTnMn/PWSlubn7plk4bCY8Y4wzf2gQkJiolKTqAVQ9gCJeHz83QRCwyBbMkplUk4cFgx1vA2oQX7SP/niAoBoipsXRdBVJkFBEBYtkxqnYcRlcmC5RT38/sktRNcYRXx27u0/SGuq5ojTCDZ5K7sxcPC3HLc330trZR6D2wkYAACAASURBVCyuTruQ8tGeVsJqjBybC7ty5fnLqhgocXrY3XaB/R2NIwInHZ3aQXPn431nhv/uMSZdn8ApUWNMTBxmyUYg3oemqwk5AVQUQcEsTVwa6O4boKG9l8KM5FE6S0dqWwhH44iiQFneRUG8YDhGIBhBFATSUxyjgqYhgc22nvFX6XNKshBFgV5/kJ3H6lm/ourqHuLB7jtBECjMSOaT6xbzrec2s/vEBZ595wCP37UE62UcqiG+ltkgk5s2Wl8qFlepb+keJG2PXa/u8Qf5/ks78AfDfOmhVayYXTiptnqDIjEzL9GJ19bt51hdK4vLx8/qXE7wu17IK8+iZF4hR947CYAaV3nth+8y/5Yqiqvzp+34giBQNDuPkup8jmw5BSR0j1794bs89o/3IynSFe+FpmrseOUAjacvqoE7k+0svHUW0jiDQ1Kai7KFxZzeXzecpdrz+iHWPLKC9IIri9oF+8Ps3nBwSmR5i8PMgrWzOLjxGAODwqJHtpxix8v7WXHfwsQqeAoq+EO4fBtN02hp7iUSidFwoYvurn50Hfr9IQRR4FOfvYmqWTn09g7wnW+9QX9/CJ8vSCAQ5snvv4vJpDB3Xh6PPLocZVBLKznFzv0PLeKZp3fw/SfewWCQWbmq7MPAaQw4bCYevnPqWja/rzArpQxEDxOKnUGRLhdI1dF1lYHIISKx87gcE2fSrwWXvws22YpNvr6UhquBrusc66vn26d/Q2fYhyiIqLoG6MMcZE3XkUWJMkcOtjH8+q4Wa28o4/vPbuPt7adYvah0+B0fggCI4uTHokvRGkyMNXl2NxblyotBgyiTYXGAAE0DIyWSRAT+OP++Udtcy2xzxcCpK9rC3p6NCAjEtTjnB07RFKzFrrjoi3UTUUNUOEcr4l6OvoEwL207TkFGMjmpbkRBQNU0LrT18ou3DgBQXZJFXtpFkrPZKGM1GdB0naaOPvqDkWFrEm0waHry5Z0JR+ZxMDM3lcVleew4Vs+PX9uNw2ZiXmk2TpsZcVDPKByN4x8Io2ramOrdl0OSRFbMKaQ/FOE/nnuPX206TIrLxoM3zhkRcXsGs2sD4Rh1rd3MtmUO87yiMZU9py7w6s4TV+xKqmvpor6lG7fDgsdlm3QHkyAIzJ+Rw+ziTHafOM9Tr+3GYlIozfYO8700TScUjdHjD9IXCFGS7cUwzWa7l0MxyNz3hdupO9owzOfpafPxjcee5E++/hBVy2dgHtT5Gg9qXKWvq59gf4iMgtQxdYcAPFlJ3PbHqzl3+AIDfUF0Teftp7fiyUxizSdWYraNbXMTj6nse+sIv/z3V4bLboIAqx5YTHH1+GU3xSiz6I5qtj6/h66WBKH8Qk0Lz/7byzz6tftISneNebxwMMKmX+5gx0v7x79xY0AURRbfMZc9bxxm+0v7QE8Ifz71leeIRmIsXTcP2ziWJ0PQNZ1AX5DOpm4aT7ew7O75owLDluZenvzeRu5eP49VN17kNIXDMb7y5d+w9b0aqmblkJxs52v/cu+Yz6gsiciX2M9Iksi8+QVUzcpB0xJl2+lYrbZ09NHZEyAz1UmyazSPJB5XqWvqJhyJMbMwbcQxozGV9i4//kAYTdMxmxQ8ybZh7bNL0dcfoqGll7ysJCxmAz2+IN2+ALGYhsEgkeyykuK+uKAc0p3r7A3g84eIxuLD5XS3w4zLbkaSpOF7q6oaDa29+PsvKu1bLUZyM69sjxQMRWnv8ifGRAHsVhOpyXaMl3E8O3v66ewJkJORhCSJtHX0EQhFEUgEaqkpDgxXWFxcTyRb19M18DxNvm+S4YwSVROq/ZF4E5oexh/eRav/+0iiixTrPe/7+f0uQkPn1eZdDMTDfLp4HSu9s/nBuVeJqFG+NPN+fNEBNncc4q3W/azwzmKZp2Lajr39QEL88js/3cyTv9xGktOKeInsjMNm4jt//5Gr2vdALIokCNgVI+IkeNQWWUESRPpjo6tQjaHWUQruRtEwLFMwVVwxcFIEIymGi6vAVNNFqYCh8tyl3k7jwWU3U9vUxdef3siCmTm47WZ6+oPsPHaeM40dJDut3L969gitohSnlYqCdI7WtrLzeD1PvLCdOcWZKLJEa7ef7UfrOd/azcw8Lyfq28c8rskg84nbFtDW08+55i7+7efvMqckk4KMFMxGhWgsTqcvQGOHj7z0JP72YzdNeC2QkBG4bdFMGtp6+eXGg/z0jb1kpDhYOadouNNuVlEmXreNjt4A//nrLdy6cCapbhvBwS7BTQfPkmS3XFFfKNlhxWwycKGtlyde2E7pJcGNKApYTQby05OZU5I5yq4mNcnOH9++kMYOH0fOtfAPT73J/Bk5eN02ZEkkGI7S1TfAueYuREHgvz5/DwblyhPttUIQBMoXF7Pm48t5+ftvE4skWn8bz7Tync88xaLb5zD3xkpyZmbi8jgwWgyoMZUBf5CeVh8tdR2cP9FI3bFGBAG+8uznxiWWC4LAkjurObLlJBue2gwksk7P/OtLtNZ3sOqBJeRXZmMc5OmocZXzJ5rY++ZhXv/xphFed6XzCrnr07dcMduXuLYSlqybxytPvgMkymfv/WY30XCUdX92M0Vz8jANlkxjkRjnjlxg5ysH2PDUJuIxFaPFQCQ4eQKj3W3l4b+5i7qjDbTUJt6BzqYe/uevn+H49tNU31hBQVUO7lQnBpNCPKYSDoTxdfhpb+ii6WwrtUcbEuVFARbfMXdU4BQKRenq7MfjcWA0XhSO7ekeIBaLYxzUzBJFAcsUysGiKGCa5pLivqMX+OZTG3nk7oU8un7RqNVvt2+Av/73FzEYZJ76l4+i2BKf9/QFef2942zcWUNjq494XCXZZaWiNIOP3jmPGQUjB9fDp5r46ndf5+t/uQ5REPjVhgPU1CU6X+0WI+tWV/HJh5YNf1/TNF5/7zhvbD3J+eZu+gciSKKIy2EmPyuZT6xfxKwZmQytgaOxOM++uo8t+84RDEXRNJ3ZM7P4p7+4g+Qx/Ax1XaehpZcX3j7MrsP1dHT3D7eFL5yVx0fXzR+x3cadp/nlawf45INLaWrz8e6u07R39yMikJnmYvWiEj521/wJ9e2uB4xyFlmuv6a579vUdn0WUbQAKg29X0PVA8TULoxS4jsGafoJyb+P0HWdM4FmZrsKuSltLk7FilkyMBAP4VCsOBQrD+feiEUy8VLTDiqc+RTbx29smgokUaQoJ4WinLENka+lm90sy2johNWJJSIS/C4VTddGGQBr6LzWsomImuBUBtUw7eEubvDM48Gc26/q3K74ZrgMKSxMvmX4xOJ6jIgWQhYUjKKZuB6bVOBUkJ7MumXl/PCVXfzsjX0gJFZ/DIpg/tndS1lakT8iUjUoMg/fVE19aw/7axp4Zftx3t57GkkSUFWdJIeFz923nFhc5UT9O2MeVxAEKgrS+YfH1vC9F7ZzrLaV7Ufr2XqkbjjjlBDBlChIn5onjiyJfPSWuXT7B3hjTw0/eGknLpuF6pJMBEEgLdnBp+9eyg9f3cW5pi6+37IdoyKjkxhIF5Xn8cja+Xzj2U30+EeT23Vdx+u2ceeSMp58eScHaho5ePoi2TmhAyVgMxupLsnis/cuG+R0XbyHVYUZfO2xtfz4td0cq23ltREZLh1RFDEqMnNLs65okjydMNtM3PeF2+lu6WXrC3uHVb572/t483+3sO3FfVgdZgxGBVEW0TWdeEwlGooSCoQJBsLoms6MBYUTtu4rRoWHv3wXvk4/ezYcQo1rwyW77S/vx5lsx+V1IMkifZ39+Dr99Hb4R1jD5Fdk89g/348nK+kKR0pAViQ+8he3cmLXGeqONgyKfMbY+sJeju04jdvrxJ3qRNd1+jr9+Dr8+Dr9xGMquTMzWXLXPH77n68PB5STQX5lNp/8xkf54Zefpflc23Dm6Z1ntrHjlf3YXBYMJgOiJKJrGmpcIxqOEh6IEAqEhyUMvNljP//JKXYqZ2Xzo//ZxP59eVhtRnw9QU6fbkUUBNbcOmvS53q9saS6AMevTOw8VMd9a+fgdo5cCBw61URnb4CH75yP+ZLGkZ+9sJs3tp5kTlkW961NZI4PnWpm8+7TNLf5+Ic/v42cdPeIdysWUzl4opF9xy6Qne7mj+9bgqZpnK7vIDNtZOZ679EL/OjXO3HazfzRXQvJTHUyEIpSU9dObUPniHEPEjpZjz+wjIfvnE9DSw/f+dnmK153t2+Abz61kZq6dlYuKGJBVR66rrNl3zle3XSMju5+/vpPb8ZxiRxIMBTlZy/sQZQE7lhVQVaaiwstvbz49mF+8co+stJc3LLs2kQxrwaCIOK2rMWsFNE98CJ94S3EEIlrPmTRjdu2Fo/tIUxK4bQpif8hIBAL4TG5MImJQMUiGQnEQ2i6hiiIKKLMck8Vzzdt43DvuWkLnO5YXTGigWYUriFpmW5J8EnP9/cwEI9iuwLPKaLGOd/fi6aD1zKSCygi8Ee5dzNkw6zqGod6T9ITHS2aPVlMekkRUgPs6n6Tk/79FNkqWeW9lyO+beRaSkkzTyQuqbNqThGzizPZcqiWho6EUWq218Xy2YWjJvwhpLisfP3x29lxvJ7jda34B8JYjAoFGcksrsgbVs5et7ScsvyxU26yJDIjx8t/fPYujte1cbS2hbaefsLRGEaDTJrbTnGWh+rS0cKbHpeVWxfNxKjIo9qABUHAbTfz6fXLsFmM+ANhTp5vo6owHUWWkESB25eUUV6QztbDtTR2+AAdj8tGRUE682dko8gSt8wvpb3Hj9txcZDXdZ3GDh9PvbaHrUdqqS7JIsvjGuwSFAb98uL09oc4UtvCpoNnMRllvvqJNciScMk5QlVhOt/+zDqO1rZy5FwzHb0BonEVq9lARrKDqqIMijM9171Md+l9c6bY+fPvPkpyRhKbn9tJd2vv8HUHegcI9E7dAmG8Y6VkJvGZ/3iE5HQ3G5/ZTigQRlM1ult6E4a940BWJMoWFfOn//rQlPhX3pwUPvffj/Ljv3uO4ztPo2s6uqbT0+qjp3Vse6Lcskwe/7eHyS/PHpGJm+w1Llw7G0eyjV/8y4sc2XKKeDSOrukM9AUTvn2TQKJEOvrvbreVz31hLTu2nebc2Xb8/hA2m4nb7pjNosVFVzTzfb/htJtYPq+IVzcf4+yFThZUXRyX4qrG29tO4bJbWDQ7b1hz5tjpZl7aeJTbVpTxF59YNZxluXFxKanJNn7+8l5e23ycxx9YOqpM9uLGI/zVo6tZe0PZqODnUhw/20IkGuf+W+dw5+qLqtq3Li9D0/SE2O0lN18UBTxJNjxJNtD1CT0kX3znKEdqmnn4znn8yX1LhhdBN8wr4n+e286GLSd4Y+sJPrJmzvB1x9REp/NXHl9LdXlC2kLXdTxuG9/56WY27qjhpiUzrnhd1wuioGBWZpDl+luy+DKaHgE0RMEEg3YtH+qHjYRNNjEQDxPXVYwoJBsdBOJh2sK9ZAzasthkE6qu0Ru9NomFEdAHLa2uw++xwJvDU6f2sqW1jru6W1mcOjZPV9d1Tvd1sqn5LJIgsMAz2iHEZRjZ1FPpKuUndb+96nObgsnvGQbi/SxMvpnuSBuiIBBUA3RF2yYMnDQ98U+Wx8VHbxltFDkeBEHAYlK4eV4JN88bm/2ek+rmq49e2XNmyFqlujRrzABpvG2Ksjz805/cesXveF02vvjgaBG2oR84Pz2J/PTxsxUP3zzao0jTdf53w17e2H2KNQtn8Nn1y/C4bCMGsSFx0Be3HeM/f7WFncfOE4urIzJHQ+dgUGTmzchm3ozRdhofBARBwOow87G/u5vq1eW8+dMt7H/nKMH+0JWVs4VEajirJJ1VDyxBmYSEwlDw9In/7yMUzsrljZ9s5tzh8+NqLAkCeHM9rHlkOavuXzwhsXus45XMzedz3/0Ez3/3DbY8v2e4s+9yGMwKc2+q5COfv43yxSWoqoonK4mGUy0gTG5yEISEDk3ZwmI+/8RjbHthL5ue20n9sQa0CVaCAgKpuSnMv2UWC26dPaYRsiAIuN1W7lg3NS+tDwKKLLFwVh7v7Khh8+7TzK/MGb6HF5p7qG3sojjPQ+6gGbiu62zefRaTUWHp3EIUWRrOyIqiyOyZWTz3+gHqGrrw94dJdo8MEotyPKxaOLF7QLLLiqbrHDzZyIKqPFIH9cwEQUCSrm3CiUTjbN9/Dm+SjRvmFSJLF0UVLWYDa26YyetbTnD4VBNrlpXhusQ7sGpGJqUFqSNUn/OykkhyWejxB4lEY5ivodRyLRj6fUAYDJg+xHgQBIE8axoNAx0MxMNYJCMFtgz8sQF2dp5gXdYSZEHiuP88US2GYZqkCACefW0/KxYUk5sxUiZj6Pfbc+QCe47U47CZuHN15Zjcw/EwJzmDImcyJ3rb+ffDm/mrWStY6M1BEaVhT09V0zjS3cK3j26haaCPXJubRakjAydN19nXc3SQMJ9QEj/VX0vyFA2SL8WkA6dAvI8UYzophnS6I20A6LqGPlVfiQ8xIYKhKO8dOoem69y7ogqve2zRRbNRYVZhIuUaisaIxdURPLHfdZhtJqpvrKB8SQk9bT5O7jrLqb21dFzoxN87gKaqGIwGrC4L3uxkcmZkULa4hNScFMw247jE8LFgdVq45ZHlLF+/gNMH6jj47nEaalro6/Sj6zp2t5Xs0gzKFhVTdcNMbC7LFbvvrgRRFMmekcGn/+MR7v7sGva/fZRTu8/R0+5D03ScKXYKKrNZfHs1ueVZmAabHiRB4tsb/x/qoObZVGUFvNnJ3PPZNaz9xApqjzZwfHsNF041093SSyQcw2BSsNjNeLKSyJ2ZSXF1Ptkl6ZisJpSrMCX+INETCBJTNVKdF0nYgiBQku+lKM/D/uMNdHT3k5riQNN0dh2uIxiKMq8iZ5jvo+k6NfXtBIJh/vGJN0YQ2CFB0g4EI/QHw2NaFs0sSB3FoxoLNy4uZfehenYerOfgySZuXFTC8vlF5GUl47Kbr+m+t3X5Ez6Xqa4xJ6WiHA9GRaKpzUf/QHg4cJJEgcxU17Bl1RBMBgWDIqFpOrG4Nk6/7/WFrmvENR+R+AWC0ZPEtIRMhyJ6MBtKMcn5yKJ7XJ2n/2sQEVjqKecndW/RE/XjMTqpcOaRbk7mJ/VvsrP7BCZR4XR/E4ogU+HMm7ZjH6lpwucPomo6/kCY6rJsViwowmEzcfhUE//1s81YTAqhSIwT59r46mduHVEyvhJsipEvzlrJ3+7dwPGeVj6z7QWybU5mulOxK0aC8Rg1vg4u9PcSiEVIMlr4wqzluI0jS/Q6Ovt7jxPVYsP3K8WYxNq0G676uicdOCUb0tjfu5m4HqM/3stJ/z7awg2UOn73V6K/b4hrGqqqIcAoD7vLse/UBQC8Lhum6yxieT0gCAImi5GMglQyClK56aPLJt7oKrC1/RxpZjulzjSqV1dQvXrizpKBeJTn6vYR1VRuz6ogx5bIHGq6zu7OOo72NpNnTWZlegkmaXQp12g2kF+eTX755DJ9giBgd1996UsQBCRZwuayMmv5TGYtf/85Ku8X3jh8mra+AH91+8jBLzXFQVVJBq9sOsaB4w3ctrKCvv4QR041YzDILKkuGA4uYjGVaCyO1WxkfmXOKE7UENI9TixjNCGYTcqkgh6HzcTffXotG3fUsPNQPS+/e4xX3j3GvMoc7rl5FnPLcyYVgI2FcCSGpukYFGnMjjtZllAUmXAkNqIRRRTEa3ZUuB7QdY1AZD9t/T/CH95+iUddAgJGHKalpDoew2Fc/CHPCRKNHSlluBQbWeaEtpVRVHi88HZ+VPs6x3z1qLqGx+Ti7swlzHIVTrDDyUNVdV7dfJyK4nRsFiPPvb6f9m4/j65fxImzrSS5LHz7y+tpavfxtf/ewJFTTdwwv2hylyUILE7N5R/m3sKTJ3dxtLuFGl8nNb7RenclTg+Pz1zIzZklo8qGIgKP5N6NXRk5tiYI5TFkQZqUddylmPRMm2UpIqj2s7d7I13RVgLxPhYm3UKq8Xej/POHBJvZSF56EifPt/OzN/fjddvxuGzDHBRN1+kLhHl732mee/cQkiiwduGMafcK+kPC5rbTzHJnUeqcfPupQZSoSsrkBzXbKHelDwdOApBjTaIl2MerTcdY5M0fFTh9iA8GsiSyeE4Br24+zqFTTaxYWEJzu4+aunZmFKSSm3GxbK7IEookYTEbuPvmWVSVjk2YFQVhVDYqgckFHYIg4LKbueeWWaxaVEJtQxfv7Kxhy56z1DV28eXHb6G6PPuqghiTUUEUBWKxsd0Z4qpKLBbHarGMHB8EpuY/9D4hqrZwvufviMQbsBoqcZiWIEteAGJqB/2RvfjDOwjHzlHs/QlmZXKT8B8yBASSDA6WXiYzUO7M4+/LPkZnpJeYruJSbGSaU1Am6Z4wGYiiwK3Ly/j4PQtRFIm9R87zwttH+Ni6+QyEoqS4bRgNMgVZKWSluWhsG59XOhYMksxNmcWUujzsaW9gT0cDdf5uBuJRTJJCrs3FPG8OS9PyyLe7kcewZdHQeK7xdW5JW4ZJNOIxuhEQ2N51gI3tO/EYk/h43t3Yp2AAPOk7qIgGyhwLmOmYh47OoMj879yK5Q8BsiTyZ3cv4ZvPbmbPiQv80T89Q06qG5fdjKpq9PYHaezoIxKLYbcYWb+iintXzrouBL3/y1BEiUp3JknG0ZY2WVY3M6IhNredGWfr309E43HOtnXT4Q8giSLFqcmkux2omsbZti7afAGsRoXSdA82s5Gm7j76QmH6QxEy3Q5aff14nTY8disN3T5C0RhWYyJb4w9FqMpJQ5Ekmnp8NHb3JTwc3Q6KUhME1mONbdhMRlp7/QmeYVoyHrsVEGjr6+dsWxdGWSI4RulsCFWlGeRkuDl6uoXmNh+Ha5rp7Qty24ryETxBURQozvPw9vYaWjv9zC3Pua5kaEkUSXJaSKrMYV5FNlUlGfzr/7zNe3vPUjUj86q0rNI9DpKcFtq7++nxBUlLGWkBda6hi0hMJSvVhc36wboHTAadgeeIqe1kOD9Pqv3RQX7T0PXo6MToDDxDc99/0dH/NLlJ/zjt56DpGkE1RESNENPjaLo2LAT9fsEu23Ao16YULwkiaWY3qaZBLs8gr3E6YVAkZhamDeuWFWR7iMbixFVtsPFhiD8HLrvlirqL40ESRXJtbnJtbj5SWAX6RSqsMHhNiXXAeKLGsKf7CM2hdkREbk9fyRz3TDZ37uHerDWc8J9lY/tu7smanBwRTCFw6ol2IAkSDjlpuJXfF+vCIBqxyuN7yHyIqWNIwPIfHl3DO/tOc+BME02dPk43diCJIlaTgYKMJIqzPCyuyGPBzBwcV2kn84cEXdcJqTE2t57mcG8TkiCyMq2ERZ58dKAl6OP7NVsYiEdZmVZMdXIOmq5zuKeRnR11DMQjlLkyuC2rYpQWyGQR01S2tJ1hf9cF3EYrazLLyLUmUdffxRl/B/3xMOf8HeRak1mfOwezrBBWY7zaeIwzfe1EtDiyIHJv3hzKnOk0DvTyauNRAvEIc5NzWZVegnSduB1xVWXD4dNsOVlPUVoymq5jlCXS3Q4O1Dfzy51HKPQm0TsQYl9dEw8tmc3rh2to6u4jqqpomk5mkoOOvgD3LariBxt3U5qewrm2bgpTk2no9vGJ5XMpz0pl99lGegYSPKVf7z7K3961iky3g++9vQuHxUS+x017X4Adpw186ubFhGMxnty4G6Ms47KY2FffREXW2PY5kiSyelEp33tmK+caOtl9qI6MVCflRSOVyQVB4MbFM3hr2yle23ychVW5eJNHTlaqphOLxa+aJK1pCcNto0EZkeARBIGM1IRswXg+npOBQZFZubCYH/9mF9sP1FKa7x3OLIUjcd7Zfgpd16ksycD+ezBGhGKnMcrZJFluRxIvL50KCBhxm9fSG3yTYOzUNR9vSNIkqkW5EGzmbH8tbeF2fDH/oK1K7BJvuvcPqzzLuCVt5aS/f6k0S1iLElFj4wZ7RtGARZ6eIDrN42DfsQssnJWH3Wri2Jlm2rv6eW3zceqbuofPSyfha5cqX10wOBQUSYOmzFNFhjmVvyj+OL1RP5s7djPHPZOYFqfQlo3b4ODFpo1T2t+kA6fawDHMkpVyx0IAdDTO9h/GrriZ6RhtCSBLIo+snc+9K2dhkKVRliQf4spQZIlZRRnMyPUSisSGI3iEROlAkaWETMLvIE/hg0JUU3n63G7O9XdyT+5sVE3DNjhAaJrGrs56HilaSDge58dndvKlCiu5tiRC8RiV7kyMkszT53aTYrSyLPXqSgBb287xVvNJ7smdQ+NAD0+ceo8vVtxEe7if757axEfyqlmVVsqzdfswSjIfyavmreaTnOht4ZGiRbxw4RBRLU6uNZnWkJ8nat5jqbcQr8nOc/X7iWkqt2aVT+dtG0arr583j5zhUzctYmamF13XEcWEUv+zOw5z66xSVpUX0t7Xzzdf28qFzl6icZU5eRlkuh28uP8EDy+ZzT+/tInegRC6rvPYyvn8/a/eYs2sEvaea6Shy0d1XiY3VhQRiESIqxp17d2cau4g0+1A16EyO40HFlVR19nDD97ZTSAc4URTO/2hCH957w0YFZmO/itLViyZk88vXtnLxh01nDjXyrrVVbgco4nYs2Zmcu+a2byy6Rhf/PcXWb2olHSvg1A4RmNrLzV1bay/ZTY3LZlxVfc0GovzvWe20tU7QHV5NhleJ4Ig0NDSw6ubjuGwmVhYdVEeQdd1BoLRYTeDlo4+YnGNcCRGc5uPUDiKKIo47WYsgxyrO1ZWcuhkE8+/dRifP8TCWQkdp/f2nWXnwXpmzcjk1hXl75tW27VAFEyIgglJHJ/rJwpmRMGMzrU1Jqmaii/Wx67ufezo2kdXtJuwGiGuT14O5Hqh1zW2dMlYGDL33dN9ipebd9Iw0H7FQO/OxtAeOwAAIABJREFUzMV8Iv/KneiTxZ2rKvnqf73O4195NtFJh84dqyrYtr+WeFwlEouzbX8tRoPM2fMdLJ8kv2k6IQjgUuz4Yn764v20hjs51HsKVVMJq1F0nSlXayYMnDRdoy/WjT/WQ0QL0x1NdNSpepy2cAOWcbJNgiBgtxgnbS6r6zoH2psxyQoVKZMzYv0gEVVVtjbVszgjB6tyfYJCQRAwGRRMhg/5M5NBd2SAw71NfHbGSspd6SMmSUEQWJpayC0ZZfijIba1n6MnMkCBPYVCu4djvmbaQ340Xac+0H3VgdNLDYexygbO9LUTiEc43ddOe6gf0MmwuFifMwe30ULDQA+n+xJq3+2hflJMNrKtboocXmp8bSiixClfK42BXjrs/fRGgujAe21nWJtZdl2C5f5wwhsyzWUfoR00EInSHQiS73VjkCVcVjNWo4HegRCKJGE1GrCaDIl/Gw1Iokhc1bAajdiMBmRJJMVmwSBLxFSVtr5+ntt1BFXTMMgybX0BwrHEZGVSJPJSXBgVGavBAHoi69MXCuO2mjEbFAyyRE6yi96BsTWqBEEg2WVlfmUub2+vwWEzMbciB+MY75HZqPDovYtI9zh4Z+dpnnt9PwOhKLIk4XaaKc1PJd0zsRXTeJAkkaw0N0dONXPwRCPBcKJUYbMYyctK5qE757Fodt7wwK1qOhu2nuDpl/YSCkeJROIJi6kuP5/+2q8wGRXMRoVPPXwDa28oQxAgyWXhrx67kd++dYidB+vYsOUEggBpKQ5uXlLKx+9ZOKbi+O8iHKZltPp/QDh2HllMGfWc67pOON5AJN6Mx/bQVR8nrEbY1rmLdzu20hBsft9LcdON7V3H+c7p54moMXKsXqyyadyynGsKXJ6JUJiTwtc+dxt7jp4nFIpRVpRGdXkOkVicWEzl6OlmvveLLQSCEZbNK2JeRc7EO51miIjMS6rg141vIgoC1e5yDvtOMtNRyIvN7xCIB6l0Ts3sd8LASdXjHOrdwhHfTlQ9zhHfdoYqpcmGNNJNE4lfTh6bG+tJMpsnDJw0XScQi2KVlWGLk/cbETXOK3U1VHnSrlvg9EFD13U6QruIa2EyrCtHtP++X8bAU0FcU0EH8xhEbUEQ8Jou6ueIQoI02Brq479PbabMlU6Rw4vLaBnW+5gqdF2nJzpAnj0Zj8mGBxt/VnoD2VY3NX3tJButyIPPqyJKww7mK9KK+caxt/nSvhewKUbW585GESWCahRFkvCY7SiCyJqMmaSar19Z3KQoxFWNQDiCx2EdJhIYZRmr0UCbr5+i1BRCkRjhaAynZbD0c+kjMKIcdSkX4eIHJ5raaerx87frVuIwGznX3j1io7HeaYvBQCAcJa5pSJpATyB4RW6z2WTgsY8s5tblZRgNCoXZKeN+32Ezc++aOSypLqSnb4BINI4kiljMBlLcVpKcI4OOqtJMvvP395LhdSJNwImSJYl1N1aycFYe/kCY2GCAaDQoJLutpCbbR5C2JVFgaXUBeZlXVqpPaFEl/lvXQzisz/Lo+kXcsXId/oEwAgIOm4kMr3NYJX0IqxaWUJLnJd07OiDM8Dr5m8dvSXh/TbMlzuVImMiP5Lw4TSvxhd6mxf9fpDs+jdUwC2HQnULXYwSjx2nxfx9FSiXJMnW7DF3XCaohnm96jS2dOwiqoYk3+h2Hhs6brfvQdI1PF6+j2l2EQRy/49MiTR/XTRAEivO8FOd5R/x96JlbPr+InHQ3kWiczDQXTvvkBS50Xccfi2CRFWRhNJ86pqrU9HVwtq+LZKOFOSmZ2JXRHqSCILA4eQ6l9nwkQSLZ4CKuq0S1GEf7agCBWc6pZZQnDJxkQWGF927sihtFNDLDnpAfEBCRRRmRaWwHneQc3BMO8cNj+/iTirl4LdMXPU8FNsXAt5ffOjwR/uFCQByj5Xcg1oAkmjHL3jG2+WBgU4xYZAPHfS14zfaEvY2u4TJYEi7dYzxgXeEAvdEgq9NnYBClBDfgEr6Aftm/L8XwZ5d8WOnORERgsbcAWZQIxWPYlESAMZ5RpUmS8Zjs/GXFjbgNFuTBADXN7MAkKZS70kk3OwmrMWTx+jVkZCU5WFySww827mZhUTaappPncbOgMIcHFlXx4v4TNPf6aentJzPJSa7Hze7axivuc6wzdVvNRGNxdpw5T08gSG8gOOGrX5WTxjvHzvLTLftJslo409ZFafrY/liQIH5np7nJTnOP+51LkcgMuchKm1gUz+20sKAqb1L7FYSEX1d+1uQsnQQhoa+UmToVcb440VgNNmvlqAlsLKR5HKR5xg7ALWYDlSXvjwecpg9wqn09OkMcLwEBCV2PEYk30h/egyhakMVEgBdX+9D0RJbRblyIP7yTFNv6SR9P13UC6gC/aniRLZ07hxcuv+/QdZ3aQDMLk2dyY+ocbPK1aYNNFZqm0dMXpL2rn3AkhixLeJJseJPtKLI0qWdyLPiiYR5452lmJWfwN3NWk2K6uIDxR8M8cXwHPz97gLimIQow05XK31ffxDxP1qjrV0SZVNPF8UJGoi3ayaKk2Vd1bhMGToIgICFTYC1HEiSM4vT9KDqwu7WBbU3nSTFbCcZiJJnMaLrO2d5utjbX0x0Kkud0sya3GLfJzJ7WRjbUn+G9pnr6ImHSrTbuLiojx+6ipqeT7c0X6AkHKXAmsTa/GIfhyoTIjmCAty+co7G/D5fRxK15JeQ6EoNWQ7+Pty+cozM4QKbdydq8YlItNva1NfHW+bN4LTbuK6nAbUpE0bqus7u1kZ2tDZgkmZtziyh2JdMVCrKrtQFREDjR3UGqxcY9RWU4jSZ0Xeecr5t3G+voCYfIc7hYm1dMkslC20A/b54/S0cwQFmyl1tyizFI759uiSAIpFoWj/q7js6FwOskGSt/pwInp8HMvblzeP7CIXZ31iMLIou9hdx2BU6Q12QnyWjl+zVbcBhMSII4HLjs6qhjc9sZTvhaCakxjvuaWZ8zB0WUeLXxGMd9LZzpa+e7pzazyJPHmsxyHsiby4/P7uAbx95BEUWyrG7uz7uyWn5UU6nt7+TJmm1YZIUqdybL04opc6WzzFvIj85sRxElDKLMHVmVzE25PulugyzzwOJZHKhroqmnD0WSSHXaEQS4YUY+VpOBuo4eyjK9zCvIwm0xs6wkF4fZhM1kYE1VCUZZ5p555eR53JgUGUkSuXdBBQ6zkfmF2ciiQE6Km4/dMIfznb0UpaYwOzcDtzXxDq2fX0G+N5FtcVvNrF9QjtNixGo08OmbF3HwfAtWg8Ln1i4hGvvDmPimB787md+pQNOj6GMEMIp0UTZkaCEjiQ4kEgFfOH6BntDrUwucgG2du9jWtecPJmgagoiIU7GgiO8v51XTdPYevcBv3zrE6boOAsEwRoNCflYyt6+s4OalpWOWyCeDg11NNAR8mGSF6CV6hqqmsaGhhudqDxPTVLwmG0E1ytGeVr515D2eWnn/FX3tIDGH/arxDb5Y+thVnZswgVHqiA9jWoT+eB8RNYhZsmGVHSji1Zepjne186/7tnBvcTno8IOje3mwtJJHy+dypLOVs75uUi02Xq2toSIllUfKZtMbDnO0q43/PrSLv5y7jFSLlUybA5OscKC9mQt+H/8/e+8dJ9dZnv1/T50+s7M72/tqV71bkmUVW5Z7x9imBQOhBXghEAgvBAIkhJcAgSS81PgHAUIcINjGNi64CNmyLataxera3vvs9JlTf3/MarWrnV2t1ivZ5s31x34+O6c95znPec793Pd1X3fI5eZ3jce4orSKty1YNiXxSzMNfnRoDynTYHN5NZ2xKBvKKqnwBhhMJfn080+wtqSClYWlJHSNy4rLKHJ7iWbStMZG+MrObXx3yy1UjRpaB/q7+dGhPdzVsIS4rvFsWyOfvmwTYPORbY9wTeU81pdV8UjjMRblF/KRFZfTGYvw2Rf+wFXltSwuKCRlGKwrqUAA/vXATsq9furzCni06QRrS8p518K5K6pq2zZxvZXmyG+J6+0okpda/z2EnKsRBIEDA19nJHOCSu8N1AXegShI6FaCw4Pfpj/1MqroR5WClLqvZF7gndiYdMSfpDvxHAIi5Z5rKfNuRRIuXSjTtCzCWpKEoSEIEFTd+BQnQ+k4DknGqzixbIuhTBKv7MAhyUS0FDE9jSrJOEQZSRDxq04iWooRLTn2EkiCSJEza0gMphNo1lkSqU92UOD0jrqX00T1NLZt41Ec5KkuNNMgbmgUONyIgkhMT6OZBj7VydcOPcnivFIafEVE9BQPtr3CJxZdzQJ/MZplMpzJXksRJfIdnv/RjJoCtm2jG43EEr/AMJoRhQA+73twqOsBjVjiN6TSzyIg43Hfidt1A5adIhz5BwLej6Io88hoB4kl7qcg7xvYts5g+FN43LeRTP4eBIWA72Mo8kJMq5944jdktD0AuJ234PW8A9CJJ35DMr0NQVDxuG7H7boOQZh6Irdtk1T6j8STD2FZYVS5Ab/vw0hSGRltH7HEr7CsAVRlBX7vB5CkAiwrTiT6r2T0oyjyPEyzG5/3fTgdm9D0Q8QS92OafajKEvzeDyJJU3vnXi/YtoVu9s6aXSQKCopUOOP9u1M9fPXYd4jo0RntLyAgCSKiIM55Gv/5cFvZjdxVceuM9jVti7979RdkLJ3PLXoH+arvkhlPTe0DfOGff099VYhrNiykMN9LPJnhxX2NvHywlU+8+yq2XN4wq/b8y+Ed/PDoS7yrfjWfX7UVl6xg2zY9yRiffOlhDg51cU/dCj60aD3DmSRf2PMEbbEw3990J9dWzOdotJGA7KXMVcyeoUMTjGXLtni67yW+tuxT0zVhykZfUJHfnYN/oCVxLBu6sW3qfctZm38NLml2xMOXe9pZEAxx57zF2MCLXW1jra325xHTNAZTCWRRpHFkCMuGfKeLGn8Qj6rSECygyHX22rWBIElDZzCVRBElTo8M5b7wKAQEvKqD7nAMzTS5tmoe+c6sR217RzMBh5OPrbgc6ZyH7nc4qRHyJvXqQ43HcEoyg6kEmmXSnYhxMjzAgmCIAqebty9YTl0gSNrQear1NABPtzVS7cvjQ8vWTDDwXh3q49BALyVuH93xKA5J4vHmk7xzwfI59PiZdMWfRRQUVhd+ibQ5hFM+OxGtDH2epshv0KxhztjQsuBmRehz7O//ChXe6yhxbx5V7xXoT+6iL7mTpfmfwMLg6ND3USU/xe4Nc9LemUASRUJOL+d+JgqcZ0O6oiBSOO7/oMM9SaYfsh6sgJo7Jl/mzk0YFgQh53EuWcUlnzUgfYoTFBhKJ2iMDvCBhg0UOf10JMOIiGTMUS6MJFM6xbX+B+fCJJl6DAGVgrxvY1oDSKOei0TqCdKZFwgGvohta4xEv4UguHCoqzHNXmwyQJYvZJo9ZMe7jaYfRdUXkBf4HACSWABkiMV/gmlFyA/8HQgS2Nl3Mpn+I+nMLvIDf4tlpxiJfgtJDOJ0bpyy1Zp+lEjsuwR8n0RVlmDZUUQxiGl2E43/Gx7XW1HVpcTiPyca+xHBvL8lkXwQw+ykIO8f0I0mhkf+PtsDZg/R2L/jcd+KoiwmlvgZ0fh9BANfuFidPmsIgogqX5qwoGEZPNW7nag+fYFbEZEiZ4hyVylFjhABxY9Lck3LGboYqHLPrKYqZCkAd1Rs5LunHuLRrp3cVLqOQmfeRZMtGY/Hth+hrrKAv/nIDRPK96xeXInX/TKP/vEwWy5vmNW5uxIRJEGk1p+PUzprqhwa6uLgUBclbj+fXLaZIpeXSm+AW6sX871XX2RXXzvXVsznVLSFElchJc5C/qPtERb7540ZwBbWa8qenLHh1JY4RVQf5vay9+OSvMSNCDsHn6A71cw877LznyAHkro+FkoTgHxX9uOlmSbfP7gLVZRYWViKV1VJ6jpgT6pPdGYwJ3WN7x3YhVdRxwjblm2RnQBzD3hZFLmzfjG7ejp4pq2RB08f4ZOrNlCfV8BIJk3I5UYShBm9MLZtM5RK4lcdyKKILIq8a+FylhYUo1smQacLp5x1oyqihG5lCcjhTIqQ24M47jrZzBEDzTRQJQlZFFlVVMrVlXUz6td/3v0SJwYHKPJ4+dKmLTjk3I9ZQCTPuYimyK9pjj1AhecGHFL+hD3OZdQKgoCIgiCICIKMJGZX0jY2A+n9RLVmjg3/EBubmNZCXO+gyLYn9WFcy/DDfXuIZNL8xep1VAX+3zQO8lQXN5Yv5l+O/RHLtpAFiRX5FdT5JmcUzQamZWFhIwnitCJxbwZYto1pW4gIE96XsxBR1eXEYv9OLPFLPO47kMQQYJLR9uFybEGR5wM2DvUyNP0gDnV6D64oeHA5r0aRa8d+M81hNP0Ufu+HkeV549phk07vQDNOEo5+E2wTXT+NbrbjsDdM2feZzC5UZSku5zWj81sZtm1jmMcAGadjA5KUj8d9G8Mj/4BlJUlre3E5t6Io9YhSAYrSMNq2PjLaHix7BEFwYpq9gIxtW7Oq7ZYlcJMzYWLq5zB76OYQtp2Z0b7CBXicetP9nIg1Tps9F1Lzuan0Whb6Gih0FOCR3RdciuP1gA1E9QSFjgC/7XievcMnKXIG8cmunMbTqmADVxUtn5Nr9wxEqa8K4T0ne96hytRVhth5oHmaL/D0SBoaqijhH0f4toHftx3DtG1uqJhPoStbx1UWJMrdARySTE8y61G8o/waIDtv1Hoq+Gj9u8baYdkW3zzx/83uprkAwylmhCl0lBFylCEKIm7ZS75aRMKY3oKfDuVePy90tTKSSWNj0zQyRKnHi2aZHOzv4YuXb6EhGOLVoT6imbMvkzya7hzXMgRUJ4ookjIMjgz18eX1V1PjD7Kvr4u0MbW6MGSzEWzbZmNZFZeXVPCjw7vZ1tFMfV4BDcECdnS10hmPUuByo5kmLlnGccbytZn0Ci7KL6Q/FefaqnockkTKNPApDjpiI2PqpudifjDEI43H6UnEyHO40CwDt6yS53AScnlYXljCovzCsRjvTCapfT3dvNzZTnUgb/oMMUGg2HUFeepCehLPcXjon6j1v5Vyz3XMbKhP7AHTylDi3kit/66x31Qxt0H0Qnsb9x3Yiw14VJUvbLxqBtf704Mkiryrbh1316zGsm1EQUAVpTlZLeqWydd2befp1kbeuXA5H1lx+SXlyM0lTMvip6/u4+dHX+Ha6nr+es0m/I6J/MVs4estqMoykqk/MDzyZXyeP8PluhHbNmBcnwqI2IiACAhjDH/LTmX3HdtRQhDPFe2zR43QyX1p2xnczhvxeu4Z+00Sp8+QszEQkDn3nbNtbfS3M7+Lo/cpAda4+xEQBGX0XCayXEXA/+mx6wqCOuncM4UN/PrEYb6++7lJ296zeBWfvGzD2TlxDtA6/Dmi6Z0z2tetLmZR8QPn3c+2bZoTbfSl+3NulwSJVXnLeEfVnZQ6ixGEqWbrNyYs2+KnzU8S11NIgkh7sp+O5MCUd+CT3XNmOAX9WdX6jGbgGFcr1TBMegej+L2uWfekU1JGjfaz35nW2DC7+trwK05urlo04dwOKTtvpszRYr6j74eAzV823DthThUQuK54ai/w+TDjER9Uitgb30Zr4jh+JZ+w1k9vpoM67/mLpU6FzeU17Oxp5x92bafA5R57AVVRYmmomF8eP0iR20N/MkFw3CTpVx2U+/x8/+BuGoL5vGVelmi9IBjiF8cOEHK56U/GKfFMn3GnmSaPNB2ncWQISRSJZNLcUJ1dua0vqWRXTwff3LuDPIeTPIeTuxqWUuz28njLCU4MD9IVj3Lfq3tZGirm7fOXcXfDUr57YCff2LsDhyQRcrm5u2H6/rmqopZ9vV18Y+8O/KqDkMvN2+Yvo8oX4IaaBu4/fgiPoiAgsKWylmuq5q5AI7ZFVG9GEpyUeraQNHqJZhop81zLmH2fo9yAgIgieohprWScI4iCjCx4KHStpjX2KIaVxCHlkzaHkUV3TmMvbRpjL4R2nkLGU6E3HmN7WwsLCkKsLrk0Lv+LgayHcu55YNFMhhc62+hJxHihq433L13zpjWc0qbBi91tdCdi7OxuI6KtmWQ42baFbpxCEFx4XDdiml1o+gncrltwqqtJpZ/D6bg8m7WlHcTreSeCoCAgo+knEMUAmcxOLHviYvDc0SsIbiS5mmTqKWSpHJCw7TSyXIvTsYFE6lFs6xZEKR/LHMQWfNOWcnGoawmnvkZG24Ui12NZUSSpEFmuxLYzZLS9qMoSkqk/4FQvQxAcqMoqUukdONS1GEY7ut4IgCQVIwhuDKMVxVGOZcWwbB1Zmr0hUOULcGVFDVEtQyST5nR4iLRpkDHN3OmmrwEuZWFOsriNiWlFSetNWHYKv3Mjea6ZiTgatkF7spOMlbvcxyJfA++uvodi58z5Um8kiILIh+pumTHhvcozdwk9V62r59s/3cb9j+7l8hU1+L1O0hmdQye6eOalE9x53ewNtFK3L0t5SUYxRiM0j7YeJa5rXFlWR5UvOOHbkjYNDNscq/pgWGbW0y4IOKSJ86sgCKwrmH3bZmw4VXsWEDPCPNv3W3QrjSq5WJd/LeWumYWPcqHI7eEL665iKJXEIcl4FDW74pYk/mr1RgZSiVGirgN7NNwA4FMdfH7tlQylUqiSRL7TjUOS+Os1mxhIJVFEEd8oq366lYNDkrm1bgEjmTSWbeNTHRS7s64/pyzziVVX0JeIo1kmblmhxO1FEkUuL6lkSUFxltQOuJXsaq/E4+Vza69kMJXAHD1fkcuDZdt88fItFI7ysdaXVrIoP/uS+hSVz6zZRH8yjm5ZeBWVkMuDKknc1bCETWXVJAwdRRQpnmPpBRub4dRhepI7sG0dt1JGnf8dCIgMp4/QOPJLYnobNiZRrYla392UeDYiCALVvjs4OfLvDPUfoMJ7I5XeGylxb0azohwb/iGmreFX65kXeNs54b8s1pdXsqGikoSuc9fCxRfedttmT3cX392zk3uXrXpTG04XCwGHk+ur63mmrZFb6xbgmEUttDcKXLLCNVXz6IhG2Fo1jzxHLu6ZTUbbTzL1NNg6klyJ3/vngITbdSumFWF45EvZ/53X43RuRkDB476HePK/SaYeQ1GXjIblsp4eScyDcyRXBMGJ3/t+YvH/ZHDkswjIuJ0345VrcbtuwrIjhKPfAFtDVZfg87wPmNrr5FBX4vO8m2jsPiw7iaLMJ+D9ELJUjt/758QTvyFm/wxFbsDv/SgAXs9dhCONDIX/N4qyEKdjA4KgIktlBHwfI574NfHErxFFPz7Pu2GWxXAFYF1pJUsLS9BNk5FMio9v+z0nw4OzOt/5UOL/MLadK1JgY9s6utlPd+T/Ylgj5Lmvm9E5NUunM9WTc5sqqtxdeTtFzrklz9u2STL+ExT1MlTH5MoacwlRENhSPHdJQxeC1Usqecu1y3lk22H+8MIxJFHEsm0sy2LLuvlct3HRrM+9tqiKn53cy+Ntx1iUV8xwJsGDLa/ikGS2ljVMqCFq2RYDqTgZ0xj7/Zdtj3B72VaCqp9n+nZybfGGOeN9XVBWnW3bWJhkzDSq5ERCelNzJv5U8a6HfzsWqnviHffinkKg8+yzH5MpzP4drUU4eTk5kYd19tipjjv7e65rj9/rQseRbpp86+UX+MXhg3x8zeX85brJsgn/g7P9fKZ338zv6/nuZbrxfHb72W1nx+vkY8adlfHj/nzXmnjc5DZMdV9THTPV+5Tr/cu9jZztny2imTTvevw3HBnq5wNL1/C/126ekkN5MWDbNkn9KC1DnybffQdlgf913mMiepSvHv023eneSds2htbxodr3TPJIvPZ2WqRTj6Aoi5GVBXN67ksN3crQlWqiyFGJ+5xac7ZtY9vQ2Rvm0IkuRqIp3C6V5QvLmFdZmC3CO8uxlzENPvrCgzzX3TTh96vL5vHtK26bkNAT1dL87Z4/8GTHcf5m1TW8f+E6vnr0B/zFvLdToAb5+vEf8YVFH0EWL2isvvasOtM2aYkfozVxHN0+6/JckbeRMlftNEfODXIZeG/mj8ClwPl652z/Td4zu23qM0x17PmOG7/fbJ+ebduE0ylODQ+96UslXGy8ln5+o+F89zLdeD67Pdd4nfqY6c914cdd6Lmmep/Of8yFteHNAkEQUKUyFKmEWGYPcH7DybQtYkZ80u8iIov9C1DE2cl7TLW4PAOn646x/8/9fk00isc/p/HG7nhx3fHH5zbkDdukNdFLT2oYfZqwXZW7kAZfBZqZ5nT8AM3xV5EEiQX+tdR6lk4ixKfNJLuHnuDKwrdOMpyy9wJVZflUlU3P5btQqKLEZ1dswS2ro8aTzRXF1Xx6+VUTjCbbtoloaQ4MdqKIEpcXZXXuqjxl/KL1d5Q4C+lODfDr9scnJEjkqwFuKr1yVm2bseHUEj/K8wOPUOtZjF8+q8arXGSNHtu20VIagz0jdDX2MtA1jJ7RWbS2ngVrzoYJTcNEzxgIkoDquPipo5ZlcXJ4CNO2qPQH8KsTpd67YlHC6RQCUO7zk+c8G1qwbZveeJyhdBK/6qTS75/UXtOyiGkZwuk0GcPABlRJyvKtnM4ZlZrJloMQMCyL4VSKSCaNbpkoooRPVSlwuWekRG3bNrplEU6niGsammlg29nzOyQZn+rA73SgiFOHgpK6TlcskuVFjIMAlHh9FLgmywGc24aErpPQNBK6xpGBPo4N9mfLwiQTHBnom3SMV1Gp9Aem7au56Oe5hmYaDKdTxLTMWPalLIq4ZYWAwzkW0s6FcDpFdzw6aTrPczgp8/rPW8zStCyaIsNgQ4UvgFtRsuMnnRwdPxayKOKRFYJONy55suDemfEyksneg2aa2KP34JGVMT7jlFlmpkFHLELayJ0uLIsitf7gRfV0WLZNdzxKVMtQ6vERHBXmjWTShNMpMqaRJaPLCkGHC686+ZnYto1p20S1NNFMhpS22cRbAAAgAElEQVSZrTsnCwJOWSHf6cKrqDlLSXTGoyR0jaDTRanHN+1zG0wl6E3EEQWBhrwClHE8Ntu2sWybqJYhqmVIGTqmbSMJAk5JJs/hJOBwvqkWobadwbYzWDlDepNh2RZpMz3p94Dip8RRNCvz0rYNMulnSad+j2X1YRodqI7N+Px/gyC4GAl/AsM4jc//RZyuGwCbdOp3GHoTXv9fAk4M4wTx6D8TCP4T2BaJxH0Y+hEEwY/TdTsO51Z0bT/p1O8BMatNJgbx+T+PJFeOa4tNXybMfY2Ps2/4JLpl5lxQioKAR3bxlvKNNPgqiBlhBjKdLPSvQ7OS/LHvV9xZ8XFCjvIZ98PJln4kUWBeVQhxjudKQRBYmFfEt9bfStrQsbFxSQouebKh65FV/vay63BJMgvyshyueypu5NXISXrTgyiijFt2T5AWcknTi2NPhxnPPCP6IPN9q9gYuilnCY6LAdu2GewO8+iPn+HFR/fT3ZT9OMqKxL1fvHOC4TTcO8Kv/ukxPAEXf/a5O3B65q4eTy5kTJMPPvY7uuMx/vHq63n74rMkcBv46gvbebo5S9j80qYtvH/lRPXob768g0dOneDti5fxtS3XIo97oEld54nGU2xraeLIQB+DqSSWbZPvdLEwVMjWmjreMn8RPsf096hKMjEtwzMtTTzZeIpjg/0kNB2vqjAvmM+1tfW8bdFSgq7p6wd1xqI8ePwou7o6aBkJE06nMW0LlywTcnuozQuysriEW+oXMC+Yn3MSPjE0wKefeZK2yOSq339/5Vbes3zVtG2IZNJ8b+8ujgz00RmN0puIY40ux+4/coj7jxyadMzmymq+f+Otk0jEZzBX/TxXsG2bzliEB04f5cWuVppHwsS0DAhZI7DE42NJQRFXV9ZxfU1uFfmnWk/zxRefnpCJAnB3wxK+tuk6nDkmnfFIGToffOohMqbJD665nQX52azPJ1pOcnxoIFsjUlEo9/p575LV3D1/6YQPj2XbvNTVxsvd7bzS301LJEw4k8KybLyqSoXXz8byau6av5SGvIKcY6U7HuXj237PieGBnG0MOlz89vZ3Up83szIms4Fumnx77ws81XaaL15+Ne9atJynWht5pPE4Bwe6GU6nkAWRUo+Pm+sW8OHla/GpE8fJieEBtrU3c7C/m1PhQfpTCXTTxCUrFLu9rCoq5e4Fy1hTXD6hdFPKNPjGnud5qvU011bX883NN0y7sPjegZf5xdEDlHv9PHbnvQSls/u2RUd4tr2Jfb1dnA4P0pOIkTENHJJMkdvD4oIi7pq/lM3lNW+KxAHLTjOS2kZKb8Tv3DTDo2zMHB4Yt+zCNcvyJJbZTzr1MG7vh5GkSiLhT+H2vg9Ryo7JvPz7iI78NYzW4hMEEVlZSDr1GJYVRpJKyKQeR1EWI4p5JGL3YdsG/sC3MIxmkvGfIMv12USGzAv4/F/C4/sY8dj3SKV+h9f3l+PuDp7u2c/z/YdYmlfDIn81e4dOYtoWGwuXkDDSHI200pUa4s6KTVxdlC0zUuAoZUtRNvtTtzIcCG8nqg8RcpRj2DqnovsZ1nrxyIGcER+AB586SDqj8eWP38zFWGMKgoBbVnBPM28JgkC+080NlRNDoh7ZxfqClZi2SXeqj9vLrr7QUN2UmPFZfEqQIa2XjJVCHudlkgT5omldxEcS/ODT/8Hepw9jmRaqU8E0crsgFYfCweeO0tc+yPqbV7Fk/exEt2YKSRRZGCqkOx7jxNDECT6cStEyEh77/2BfD/Y4LSMbODGUJVcuCRWNrSZt22YkneYH+3fzwPEjxDQtq+MkiCDASCbNjvZW9nZ3cmJogE+t3UDInTtrDbIr8x/v38NDJ4+hmSayIOKQJJK6zv6ebo4M9NMaCfOZyzdR4Jo8gdi2TWN4mK+/9DwvdrQBWfepQ5bAlrCw6YnHaI+McKivlyWFxcwL5nbXFrk93D5/IY3Dw4TTKfoS8Ql9dD6kDYNjgwMMpVK4FIVSr4/ueAzbtgk6XeTnMP5KfblX6nPdz3OFkUyaz73wFPt6uxCELLm7PlhAxjQYTiVpjYQ5HR4k4HBybXVusu+qolL+6rKNDKaShNMptnc0E9VmposzHnFdI6Kl+cHBXfzq+CE0y0QWJZyyTMY0OTVKDj63RwzL4t+P7OeFrtZRr4ZCqceHKkoMpZOcCA9yYniQ/X3d/Pi6txDKYRAUON18aPlaOmMRkrpGXNeIaxrNkWGODE72LF5M6KbFUDrJ75tO8PXdzxPJpJFFEackY1gWHbEI4XQqJ+n0iZZT/NvhPdi2jUOSKXC68Soq4XSKjliE5kiYgwO9fH3TdawtOVtfy6eobC6vZntHMwf6uumOR8eEec/FcCo5Jhx8bdW8SaUmXuhq41/2v4RmZpXnAw4nftVBVMvQk4jRFh3h8EAvf7v+aq6vaTivR/JiozvyPZL6idwbbRPdHCRtNGNZSQo8d8zwrAKSKGNZEz1UqqigzjJMl5WCELCtOLYQHZWbOXeBNbEvJakGUcxH1w6BKqBrB/EFvgzYZNLPYtlhDP0Y2DqG2YZtRQCQ5QZUxzpEMQ9FWYauH5lwXhuLXUPHqPOW8fGGO6nzlhLVk8T0FB+ouxndMuhKDfLzlqc4FmnjjvKzgsS6pTGi99MUO4wkKBQ7awBojB1g//AzLA5cwUCmi75Ma85uiCXSzKsMobyBE09ERO6puAlpDh0+MzacXJKXxthh2hKnyFeLxrxOa/O3UumeeyNFz+j89l+fZO/Th8kr9LPx9jWs3LKYbb96iV1PHJjcPq+TpRvm09XUxyvbjlx8w0kQWFFUwh9bmzk6MFEf5PTwIJF0mkK3O1t3b3iIqJYhMOr56InFGEomccsK9fkFY69XxjT58St7+I/DB1AkiTsXLOLuRUtZWFCIKMDxwUF+c+wwf2g6zX8fO4JbVvjM+k04pwhZnB4aoik8zDU1dbx98TKWFBZhA6/0dPOzQ6+wu7uTh44fo8zj4y8uWzdpxamZJr89foTn21rIczp53/LV3DivgTKfP+seTsQ5NtjP7u4uTMtiaWHRlMZFuc/Pp9ZtGFu5HOrr5e4HfzVjhlKxx8t/3nH32P6H+3t576MPkjYM3rN8JR9fs37SMQLk/BDMdT/PFR44dYQ9vZ2EnG6+sH4L11fXI4+GP+NahsODvezsbueaqnk4pvAOzA+GaAhmM4RsbN7y8H/y6iyMjaSu8esThzk80MOdDUu4s2ExC4IhTNumLTrCnt5ONpVXTzpOFkXumb+UQpeHa6rnsbakfEzkNqqluf/YIb5/cBf7+7p46PRRPrx87aRz+FQHb61fPG5sZAMPD546yhdffPqC7+W1wLAt/tjeRFTLsLaknHvmL2NVcSmqKNGfTLC7t4NqXxBXjrFxS90CWiNhNpRXs7m8mhJPlh+SMQ2ebWvkH3c/T+PIEL88fpAVRaVjciyCIHBdTQPfP7CL3mSc7R0tLAkV5wwpvdDVRl8iTsDh5Jrq+klFx6+urGVfbyeri8vYVF5NlT8PYTR8/0JXK9/as4PTI0Pcf+IQ60oryXfOvHr9xUBSP04svXuKrQKioOCQawh57pyxx0kUBJyiA92aWWhvRucUi1Adm0nEf4wsV+HyvBNpnEhqLgiCG9V5NZn0k4CFKJUgyaN1JwURt/v9OJzXjrtGHlrmZQTBxxkNr2yG50RtPtuG7tQwmwuXUuEOIQkiTkmlLx1GABySQq2nhLdXbeFrR+9n5+BRrivJRkAi+gAvDTxC2kpS4qzGHtX9OzzyAkvzNrEybwthrY/OZG5jdl5ViHAkiWFayNIbVyzUI7s4HW8jbabH5hWX5GS+r2ZW55vxl8Aj+bmycLKF75NnVn38QtHXPsTB546hOhXe+dnbuf7ezahOhUPPH8u5v6xIVM4vBaD1eNdFadN4iILA/IIQoiDQHYsS1zR8Dke2UnV4mKShs6mymr5EnL54nNaREVYUZ8s/tETCaKZJqc9H/jhPT+PwEL85dgTDsnjrwsV8fsOVE7hRl5dXUJ+fT0zTeLaliQeOH+WuhUtYGMqtP5I2DbZU1PLlzVcTcp8tTbO1po6qQICP/+ExTg0P8cCJo7xtyTKKz9G9SpsGJwYHsIGFBYV8ePXaCcaDz+GgPr+AW+oXEMlkyHNOHTMeI/aO3uuFrmwFQZgQnx6/whcRJn0wpsNc9/Nc4fTIEKZlsbywhM3lNRPCanlOF1dW1LK5vCZLJ52i/yYSqGfvPbCBP7Y388nVV/CBZWvwjMvMXFxQxOKC3FowoiBwfU0D11bPQz1HGDHf6ea9S1bxck87O7vb2d3TwYeWrZl0L2f+P/c+xNeJ7Hx4oJcbahv4+w3XTgiZVfnzxupU5sKCYIhvXXXjJE6GLKrcNm8Rhwd6+emR/ezv7cKwLBzjbOFCl4f1ZVU83HiMp1pP8ZEVayf1Z8rQ2d3TQULXWF9ayby8yWHycq+ff9x8/aTMWlkUuaZqHi2RMN/Y8zxHB/tI6NrrbjiV+D5MyHP3FFsFRMGJQ65AlUoRhJl9viRBwq94JxHEdUt/DcaUiWk04/a8B4dzop7UWdK3hY01tlgUBAGHuoFk/GeQfgbVcQWQFSd1OLeiZV5AUVchCm5MaxBBmPmzEGC0OkD2+XtlF3EjRdrUcMlZ/m2NpwTLtuhMno2QhBzl3FH+MRJmhGd67+dY9GXWFdxEyozjkQNZVW5RwSVNJoUD3HzlEn786xfZsbeRzWvm5TSeXqun/jyZ/zkx/po2Nk/07uBEtAmffPY7WOQouPiGU4GjmAJH8awuMhsMdA7R1dRHqCyfre+4AtU5vUtVlETyirIq1cO9k3k0FwMlXi+Fbg8pw6A1EmZZUQm6ZXJ6OPsBvLKymhc72zk9PETj8NCY4XR6eIiMaVDpDxAcN1E9cOIokUwat6zwF6vXTfiYn0GBy83bFy3lj63NjGTSbG9tnvKDLgoCb1+8dILRBNlBVR8s4C0LFvFPL79IRzTCvu4ubmmYGCMWEMYIuOF0iu5YlJq84CSjRxLFnKGyNyrmup/nCgXObDjw+PAAp8KDrCwsRZXlCebCpcySq/D5uXfxqglG00yQNWJzG7IOWWZRfhE7u9sZSMZnXY7hUiLodPHeJasv2Kg4Qx7PBVEQWFGUXegNppKY1kQvggC8pX4xjzefoCUS5pX+HtaXTiQEd8Qi7O/rQhJF1pdWUerJlfEkTClHIgoCy0MlSIJAOJ0aTfqYXB7pUsLrWDnn55QFmSJHIV2piXIEcSNJwkhe8PmyKfgaCE4S8R+SiP8EUXDidL8Np+s2Muk/kErcj2kNYBgtpFNP4PN9BlmZjygGcTivRtcOoSirx/ra5X4nIBKPfgOwUdX12XI+ohtJKuLM+ySKPiRx4jwkAMXOIH3pMGlTwympVLhDbOtNcSzaxupgNvoS0eIYtolum6OJCzq6raEIDhRBRRYV0lYKgIBSyGCmi1rPEhJGlJiRm1Zx6GQXybTGd376LPf9+kVCQe94gX58Hif/569um/WYMiyT7kSUg0PdNEezwqvnM6Rq/QW8o/7sOLJsm2ORRt5dfTvFzhACWbP2tVCMLp0AxwUincyQiqcoWFWD2zezCUsUR7VZrIufon6GkFbh83N8aIDmkazhFE6naQoPI4sSy4pK6EnEeaa5kaaRYQzLQgBaRsLoVjYb74yXJmMY7OnqBGB+QWha1fNFhWczQQ72T9YmOQNZFKcUhhQEgY0V1XxHeAnTtjnY3zPJcHIrCleUV/FiRxunh4f4/B+f5q6FS9hQWUWZ1/e6ZJy9VlyMfp4r3Fy7gN81HqUjFuFT2x/nLfWLuaKsitVFpXjVS0NQH4+1JeUXbDSdgQ0MJOO0RUcYSiVJ6BoZ0yRtGBwfzoa2DdvGsq1LlmwyW8zLy6fCG5jV5G8DMS1Na2SEvmScuKaRNnR0yxrja1m2jXFOaSRBEJgfLGBpqJhDA7081XKKtcXlY++cDRwZ7KNpZBi/w8HW6ropvbg22dBrW3SEnniMmJ4ZrYVp0hoNY43qYxnWNOWZ3sRQRZUqdzkHRl6d8HvMiDOYGZ6VsahldmNZA+QFf4ggejG0o8Rj/4zTdQNO1004XTflPlAQ8Po+PulnUfTh8X4Qj/eDE9uurkFVzwpoOl03g+vmc04psCI4j2d79zOkRQkoHpYFatFsg/tbtxHW4jglhRcHjqBZBqXOLA+1P9PJgfA2HKIbzUqRMmJsKLgVgNXBq3lu4AEi+iBCtiphztsJR5IE/W6uWJVbCHt84d8LhWXbPNVxkn85vIOW2PCMaR1by+onGE6CAF7ZjUNU8chzs8B/wxpOkiwhyRKGNrNVkGVahPuj2LaNvyC3W3GuEXQ6KfP5ONTfS+vIyBjpuDUygkuRqc0LsiA/hCSKtI6MENcygEBPPIYiitQE8sZSh4dS2XRvgLZImA8+/vCUE6FummNZU0PJqVdMPtUx5WoToMKfTU83bZvu2OSag7Ioctv8BbSMDPPb40fY29PFscF+avOCrCgu5c4Fi1haWIwiSbMSsXw9cDH6ea6wuKCQL1+xlf+7fyeNI8Pcd3gPD50+ysL8EDfVzuf6mgbyHK5LRuAtcnuZplJITti2TU8izq9PHubFzlb6kwlSho5umRiWhWXbaNbsSuy8Xgiozpwcpulg2zZJw+DB00d4quU03fEoMT2DbloYVnZcnWssnYuQy8P60ioODfRycKCX7kSMSl/Wq25aFs+2NWLYFguCIRYGJ3tDz8hCPN5ykodPH6MzHiGayaCNPgvTtjAta1IG5uuJkdQ2AALOq5mqKLFpJUhoB5HFAtzqwvOeUxYkqtwVuCQnqXGyBKZtcjJ2mitCa1AvWFbHyBLD7Qy2ZaDrBxGlYs5Vmb8UEBDYGFpCT2oIxyjZvdgZ5IaSNfym/Tka412IgkjSSDPPW8blBVk17wK1lBV5W9CsFLKgEFAL8cvZrMAK93yuL7mXpBHDKwdYHdxKQJmcxXr3jauwpnFUvJapaiAV59uHnqctHsYhydT58gmoLvYNdOBTHVR5gyQNjd5kjLieYX6gkHvmLWd9cc2k/ily5vPLtodZGpg/JkPgkz2zLrvyhjWc/Ple8ovz6GsfpK99kJLq6cMkiUiSPU9lU9IXXz6H9dymgVdVqckLYts2bZERMqZJdyxKVyzKpspqXIrCsqJiVEmiKTw0lsbfG4/jVlQaxhHDY5o2NpGG02l2drbPqA3n6iKNh1uRpx24siihShK6ZRHXctdxCrncfHnz1VxZVcN/Hz/C0YE+jg70c3SgnwdPHGVlcSnvXraCKytrLlna/mvBxejnuYIoCNxYM5/1JZX8vvkEjzWdpDk6zI7OVl7sauPfDu/lk6s3ZLOnLoEHKqvLdWEzX+PIEJ/c/jgnhgcIOpwsDZWwID9EtS+PgMOJKkk83HiMJ1pOXZxGXwRIonjBbv3BVJJ/2PVHnmg+hUOWWJhfxOaKGmr8eYRcHtyKwsGBHr5/YNeU51BEkU3l1Tx0+iiNI0Mc6u+hwpvVfOtNxtnR2YoA3DV/aU6OXyST5ruv7OS/ThxCGNV4ury0klp/kEKXB4+i0Bod4Rt7nn/DGE99sf8AIODcMuU+ph2nJ/ojFKmYuoLvnPecgiAwz1tLuauMxnjzhG37woe4tewGylwlF9RO1XEFljVAPPavgIks1+MLfGXGvKs5hQBLA7Us9lePcT8FBN5VvZUSZz4vDx5Fs01qPSW8tXIzhY7AaP02FxVTJHaJgkTJaIbddBhf2Heu8WzXabqTEaq8Qb665gbWF1dhA1se/SErQ+V8dc0NBFQnfakY3z/6Etu7mlAlmQV5E20Fm2zZnYDiozPVO8YDCzmCrONPzHAqrS2idlkl+599lSf+/Tne8de3ThmyS8XTPPbT7Rx9+RRun4t1N1yauj2CIFCbF8QlKwymEoykUxwbHMCybVYVlyIApV4fhS4PHdEoI+kUhmUxkEzgVmTq8s6m7svi2YrcSwqLuK1+wYxCYefyl8bDsOzzFuE8456fSsNFEAQUSeK6unrWl1dyuL+Xlzrb2dHeyvHBAXZ1dXBkoI97l63kQ6vWTOBsvRFxMfp5rnCGv5TvcvOexau4pW4BB/t72d7RzDNtp2mJhPm7nduIaxpvX7hsWsHR1wOaaXLf4b0cH+qnwOXmb9Zt4cbahgnhvoxpsLun43Vs5cWHOerleaatEYcs894lq3jfktUUnVNrMmlMT0wWBIHlhSVU+/PY09vJ7t5Orq2eh1NW2NbeRMrQKfX6WFtSMelYy7Z5qbudB08fBeDuhqV8ePlaKn0TQ44vd7ePeZ3fGDizQJm6PaLgREBBMzpnfNZCRwHLA4tpjrdijctKixlxnu57jndX3T1jjR9BEBAEH27Pn+H2/NmM23CxIIyqjJ8b8nbLTm4tX8/NZeuwbBtJPEsen0uYpkVX3winWweIpzI4VJnaigLqXqNMwamRAWwbbq1exPrialRJwrJtnFJWlDdb11amwpPHXy/fQn8yzg+P7mRDcQ11/rPeMUkQeX9tNuEgbWaQBek16zm9YQ0nf76Xm/98Cyf2NvHIj56h9Vgn175rYzYcB8TCCZoOtXFiXxMvPLyPY7tPA3Dje6+koqH0krWzIViAS1EYTCYJp9McHehDAFaXZrlFkiiyoriEppFhGoeH8TkcDKWSLC0spsR7diINOl1jKeYFLjfvXbFqLD15toik02PK07kwmEyMGU75zumVuyGbRbehooq1ZeW8b/kqdrS38pOD+zk9PMQvDh2g0h/gbYuWvqG5Txejny8GBEEg5PJwTVUdG8qqePuCZfzdzm280t/Nz4++wk2188+rtn6p0RGL8OpgHzZwY818bqqdPynEZdk2I5nJKs5/SojpGvt6O0kZBmuKy7l30aqxAt/jMZxKnfdcXtXB9TUN7O3t5PmOZj6+cj02sL29Gcu2ubKilpBrssaYbprs7ukgqmWo8efxwWVrJhlNACPpFG8Ym2mGsG0dGx3Lzu0lzwVRELm2+CpeHtpLT3qiPMfOwT3UearZGFqHKFwc4+L1hCiIFxxynylSGZ1fPryHZ3eewDStMXNXEgRWL63kg/dsJBT0zIrGEdaSOCSZam9wghq+S1ZIGfrYt0sQBAqcHq6vXMD+gU6e7TzNhxefNZyyyupDPNq1jZZEJ5IgsiQwn9tKt+BVZrcgfuN9MUYhiAJrr1/O+75yF//1jUfZ/eRBdj95cGz7A999kge+++TY/4oqc8O9V3LXX96E4rh0t1WbF8TnUBlMJhhOJTk2OECxx0ulf3SSsm0uKy3joZPHONjXQ00giGFZLCsqnmBgBJ0u6oL5tEcjHBvoJ5LJUOyZpTjbKDKmQePwEGvKckvoH+7vHRvoS4pmljEmjFr5RR4vdy1cQn1+AZ/4w2N0xqK83NnB7Q0L8agXtwzPWFtGJzjrAmb+i9HPFxPZrCiFZaFi3rtkNQcHemiODJMxc5cjeT2R0LWxMimlHh8OaXIR8LimcbA/d6X6PxXopkk0kxUd9TscEyRHxvaxTF7uOX+YWABurGngewdepj0W4WB/D0UeD63RMD7Vwaby6pyqyuZoPUcAp6xQ7PFOaoNhWezu7cQ8D9fqYsK2LQxrGMvKcggtO2tUZ4wOhBx8IQuNaPolUvopfI4LK+ydp/i5p+J2ft76K6LjpAliRpz/7ngYyBb9nUuhxD91bNt5kse2v8pNVy5hzbIqAl4nybTOq6e6eWz7q/z68X18/N1Xzerc46f18SM36HARziRJj5sDRUGgzO3HragcDU9M5LGxebRrG37Fywfr7sGwDV4Y2M8TPTt4W9UUJP7zYMYWxkCmm5QZp8JVf9GUwnPhmndspKS6kGfuf4mXHt1HJqWd1cUgK0NQ0VDKTX++hS13X05eof+StQ3Ao6rUBoLsaG+jdWSEwWSSlcUleMcZDwtDhaiSxImhwbF6PksLJ+rgCILAbQ0Lea6thaFUkodOHOPDq9YgCjkKOgKMqxQ/lTVv2TZPNp9mVWnZBA0k27bJmCZPNTVmXZ+yzNrSye5++zzXEASBecF88pxOOmNRMqaBNePch9cGWRRwSBJxLcNQKjnjzJiL0c9zAd00SRgaXsWRbcu49p55DkPp7H0GHM6cStWvNzyKmlWVBzrjEdKmgUfMvgdn6rb99tSrtERnrhj/ZoQiSWN8v5F0msFUkjKPb+xZWrbNc+3N7O2dWagp5PKwobSKJ1tP8Wx7I6uKyuhLxKnPK2BFqCTnuJQEYSxsnjJ0uuMx6gLBCeNpX28n29ubX9cy2ZadoS/2M6LplwCbtN4EQPPQJ3Pub9sGmtmDaSUpcM9UOTwLQRBYFVxOV6qHx3qeJmOd9VgNaWF+1f4QQ5kwW4s345cnG5pvVKRMHQlhks7XpcCew62sX1nL++9ej0M9a8AvbchSVZ7ZeWLWkiMhp4eMaTCYTmDZ9lhSTLk7wJHhXsKZJFXevLExbdjZ5JOEMdETadk2PelB7qq4ngJHVnfSK3v4ecvvZnnXF2A4tSVOkjYTVLguDfEaRvk1qsyKKxexZH0DH/jqPbQe72Kwaxgto+PxuaheWE5pXRGqS0W8WP7I82BlSSnbWpvZ3taCbposKAjhHyXvZkMubqoDeZweHsQhSUiCwPKiyWTEq2tquaqqhhc62rjvlb3olsnN87IhGWU0vpsxDWKZDB2xCKeHhnjHkmXTEoV/f+o49cF8rq2ZNyZ9MJxK8eCJo7zY2YaIwA11DVT6A5OOjWQy3H/kEGvLyin3+fGrDpyyjCSK6KbJSCbNtpZmumOxrCBofsElC3v5HU4q/AEGU0n29nTxclcHK4tLccgSlmWPkbk9yuSCzxejn18rRjJpPrvjSWRBZFN5DQvyQ2MFYBO6xq7uDn55/ACiIHJjzXx8Obx6mmlkye+WNZbFpo32Q0zXaH5YxHIAACAASURBVI9F8MgKsighiyJeVZ3T51XpC7C0oJhTw4M81nyC+rwCNpRVIQkiw+kkjzYd54mWU5R7/XTGInN23TcafIrKmuJytrU1cXSojx8d3MXd85fhVhTShsH2jmb+6/ghAg7nmFdoOqiSxE118/ljRxM7OluIZNJolskVZZVU+Ca/t5A13taVVvC7xqN0xaN895WXuHfxKgIOJ5ppsq+3k58c2YcsiEjTcJzShkFc1zBGx9NIJj32bkW0NO2xEdyyiiyKKJKEV1EvqOadKDjId9+CKDiIZfaMGnEWlj1VmSARt7qEkOdu/K6Z1qo7C4eockf5TSiiwmM9TxM3EmPbRvQID3Q+ys6hPVxfsoVFvvkE1Tzc0uzq2V0K2LbNfzXtZVmwjHWFNZf8+pIkEvS7URV50u8Bv+s1kceX5GcXBcfCfcT0DAHViQCsKizngZbD/Lb5MLX+AvyKg5Sh88pAFxEtTZ46kWcrCOCRnbQkulBFFQuLxlgbBY7c785McAElV9ykzcTrsjoRBAHFoZBfkkd+ydRKva8XlhVmhUF3d3cgiQJ1wfwJk4fP4aAuL5/G4SFeHeijxOujwD2Zn5LncPLp9RtJ6jr7err47p6Xefz0SeqC+XhGq9RHMhm6YzFaI2Eq/QHuXLAY7xSRsdUlZUS1DF9/6Xmebm6kNi9rbTcND7O3p4uUoTM/P8R7lq/Eo0x29yd1ne/t3YVDklhQEKLC7yfP6UIRxazo58gIh/p6iGoZFoUKub6uHiUHvymp67zS003K0EnqOilDpyl8VpdjV1cHsijikhVcioJLlpkXzKcihzF3BoVuD5sqqzk60M+poUG+/Pw21paW43c40C2LaCbbpj9bumJSqZS57ue5gCgIaKbJc90tPNvehCxkDRtREIjrGpppIgkC11XX84Fll+UUVnylr4efHtlHytBJGQZpQ6ctmhWDfbm7nU9tfxy3rOCUZTyKyvuWrOaKsqo5uwdVkvjAsjUcG+rn+PAA/2f3cxS5PaiixGAqiWFZ3NmwmDXF5Xx11/Y5u+4bDZIocmPtfPb1dfF480n+8/ghnmw5hVd1EM2kiWoZLi+t5KMrLuczzz9xXq6TKAgszi+iIRji2FA/L3a1oYgiN9cumPKDLgoCV5RWcWf9Ev7r+CEebTrB852t5DmcxDWNkUyKZaESPrNmE19+6dkpvYA7Olv471NHSBvZ9zah67SPGr3b2ho5PtQ/OqYUgk4X71m8kjU5yOpTQRBE3Opi3OpiLCtN4+D/wrSj1OZ/ByFHyExAQpbyEIXZVbYXBAFFULi59DoCip/He56hM9U9tt3CojPVzc9bfkWxs5BaTzVV7gpKnEXkq0ECih+X5EQV1QlK3XMNQRDGIju2bXN0pIed/c1IgsjGonksCBSRNDV+23KA33e8ytGRHl7sb2Z1QSVXFWfrWHYlIzzfe5rhTIISd4AtJQ0UOqfWrZsNtqxr4JFtr9I9EKGsMDDm/RmOJDlwrJNNl82bdQ+tL6rCLSvsH+ikLxnDP1qHcXWonFK3j4daXiVt6tT68ulJxniq4ySWbbOmcOL4ExG5MrSWZ/pe4rn+3Zijau73VN446/ueseFU7qrjdOwQOwefoNBRNqaxUeqsxq/kLuz6/wrOfHDjmkaJx0ttXnDChOZTHdQH83maLMdjbVl5zpW+IAgsLSzm29fdyPf37mJbazNtkREaw8NYtj1We+3Mym55UQnqNFkLN85rYFVJGd/Z9SJ7ujvZ0d465vJUJYllhcV8afMWlhfldverkkhdMEh7JMLBvh7293aP8YkEsjpPDknmivJKPrdhM4tCuWvV9cZj/NUzT2DaVlY/xrInkNafaWniubYWJFHMroBFkY+uXssHVq2ZdK4zcMoy9y5bSVcsytPNjbRFRmgKD8NoH8litkBHLv7GXPfzXCDgcPKVK7byh5bTHBrooSMWIaZnV9117nwW5ofYWjWPDWXVFExR8LVtcJgXmppxexxj2z2KOpbV1pc4y+uQRIFb6xZMOoeAgEdUUDLgmIUmzaL8Qv716lt4pOk4z3e2MpxKIosSWyrruKm2gc0VNfTEYywIhkYXF2/MlTxClphd4HTjVx1TyP9NjRKPj69csZWVhaU829ZIRzwKwOKCYq6vqee66no8o56p/X3d59XmqvLncUVpJX2JOJZtszA/xKKC6XmJ+S43n75sI4sKCnms+SRtkREs22ZeXj5XVdZyW91Cit1eriirJKplckoa9CRiHOzvnsA38Soq3tEx1TtuTHlVlaHU/Jl20SSIohO3uoiEdhiHXDanqf2WbWHaJoZtYlgGcTOBQ1LJV/PoSvWMVkMctz82Pel+etL97B5+BafowCGpKIKCJEhjJPKL5YjaWrSZG0q2AtAUG+TfTr7I9WWLsLD4wYnn+djCK6n3F7I2VM22npOsyK9gRbB8zDAKa0m+duhJFgVKWBosI2Xqsypdcj4oskQ0nuKz3/wd/z975x0nx1Xl+2+lznF6enLOynmUZSVLsi0csMEJbIPJmF1Y3i4LPHgfHrv7loUFFlgwLMYE44BzthyVrJzzaKTJOXTPdPd0rqr3R49GM5qRNBpLDuDfPxpV1b11q7rq1rnn/M7vVBRl4LCaCEfjnGzoJhyJI4kC//WHs4uk6ulFLJo9tljmuciyOLiucBLoKV4TpObuQpubj5XM4H9O7OTp+iNDHlNREJjhyWFN/jkVMASB2e4pFFlz6Y33oaOTYfSQZpi4E0a4yM0c2lkbPMRu3+tnmg0dsCj9GoqsFxchuxzQdZ14NEEsHEfTNBSDjNlmQnyPiwsG4zF+uWcXHQNBsqx27p05e0T6uq7rbG9t5tma48Q1laX5RXykvHJEpsBwnOGDNPT72dnawmm/j1A8hiSKeEwWilxu5mbnkO9wjsnN+eXendT7/dwzYzaT072E4nG2tTSxp72NQDyKw2BkakYmywuKcRiN51216rpOKB7ncHcnR7o66RxIKR+ruo5Zlsl3OJmRmc2MzKwxicBn0BEK8oPtWy7pnl5TWs6akgsXatZ1naSmsaOthb3trXSEQui6jt1oJM/uYHZ2DlPSM86b5Xcp9zkeTVB7tJWyyblYrFcmZDf8XTz3rTy37MpY+NH3niEQiPAP//t6HK6LZ9yNxdvSdZ0tbx7ngZ+/xjf/9WYqJ+decpjizHUMv4Zze9CHbR9v/0/UHOGbWzdgMxh5/CO3U+YaLch3uTD8GobzzSbax3CMdS8udh/Od08vNqZ3OoYzfKjx4p1yAQPRnQzE95Nl/9x5BTAngvqBJrZ276Al0kZbpANfvG+ELMH7DTfmXsut+TcC8PNjGzkd7GFFdgWqrvFs0yGuyZ3MrcVz0HSdv9/5OLeVzGFxxlkazTNNB9nccYofzrtpBB/ycoccf/HQJk7Ujb+I+Lqlk1i/Ytq4jj0zPw/n557xaA0k4zxyaj+vt9TSH49ilmWmpWXzqcpqiuwjHReprLoeXIoD4yDnMpgcIKbF8Rov6PQ5780at0lfaptKsXXyqO1Xmiiu6zqRgRhHt59k7xtH6GruJTYQQ9M0ZIOMO8NJ6YxCqtfOIKswVRX+3Y5H2w1GvrFo6Xn3C4LAorwCFuWNLywiCAKykKonV+a+9I/Dl+bMHzk+o5G1peWsLT1riIxn9SEIwpAEwXjHPhaybHZ+cvW1Fz/wEnFGY2ppfiFL8wsn1H6897nfN8Azf9rGZ//xmitmOA1/bif6BAv6GTf/xHoYqoWnp0YxkXdpdJHeMY6ZwNjOCJcqonjFC/6O5xouVx/jOcdEx/NOx/Bu1kYEsBursRvnXVajCeB0qJ6XOl6/+IHvM+i6Tm8sxcMKJlIZh1fnVDEjbXQ4dPi76o9FSDfZUuHEK/g9/MQN1SQS48/wtZjGz3c4Mz+Ptd2mGPl01XyuKZhEMB7FJClkW+wjCqOfgYbGs61vcn3OSrLNKS9tb6yPLT17uKvoxnGPZzjGbTgJCCS0KP2JXkySDYfiJqqGMYimK2Y8aarGke0n+eP3n6L2QAPxSHy0vLsAymMyj/7weT765bWsuWspjrQPTkbEuw1d1+lLBOmK9ZLUVNIMDjxGNwbx/ZuS/yE+REJTqe3rRdV10kyWSyIgf4iJI5yM0xLqJ8fqwKZc+oJB03U6wkF8sZTcgFlWKLK7L5AVmkRHG6e2lIgo/PXPW8V2Dyf7u7gubypGSSamJjHLypBRq4gSgXiUmJpM0RQEkSJ7Gtu76+iKBnEZzCQ0DYMkYXiHwo/nwjXOOrJXApIgkGd1gvXCJG9dh45oNxbpLC/OplhoDLddoNWFMe67GEr2s7n7ORrDNRRbJ7Ei42YO9G2m0FJFrmV8MctLxdHtJ/nxFx+gvb4LQRTIKckkqygdq8OCKInEInF62/y01Hbg6+jjj//6FN2tvXzmX27FcAmW7d8SumK9PNz4AjEtjixKJLQk1WnTWOatRrnML9X5kEyqbHrpEFXT8zmwqw5V1aheWklWnptwKMqBnXW0NfWSmeNm1sJSrHYTgiBw8mgrR/c1oiZV8ku8zJxfitGkEApGOLijjvYWH9l5acxaWIrZaiQWSXBg52laG3uRZYkZ80soKs9E13VqDrcgyxIdLT7aW3yUTsph1oKUq7u7vZ99208R8IfxZDqYsyhFttQ0nSN7G3n79eM40ywsWF6FzWE+xy0MjXVdHDnQxJr1MzEYZU4caeXowSYWLK0gt8BDZ0cfu7fWsnztVGx2M/3+AfbtqqOnK4DJZKBqWh4lZZlIcurjoiY1DuypB6Bicg6H9jbQ1uLDZDIwY14R+YXpYy4UdF1n747TtDb5WLCsgoysFHkzFIhwYE8DXR19aJqOO81GaWUWhSXesx4KQSAyEGPTa0fobO/HZFaYOrOQolLvkKSGrut0tPo5vL+JPv8ADqeZabMKyclPQxAEkkmV/bvqkSSBrBw3B/bUMxCKUVCUzrTZhaM8d7qu0xVOra7TzZahEGs0mWBDwylebahF13VmZWS/7xXqrwR0XSeiJjCK8rsmMnuir5v/te0F/m3+OhZkXrpXN6mpvNl6ileaazjd34vXbOXPq+7Afp4M1e7QY0STdWPuOxcGKZssx2cveUwfJAiCwLV5U6gL9vKTY29ikQxYZQPr86dRbPcgCgKLM0t5oeUoJwKdLPSWsMBbxAJvMbu6G/jRkTfwGK3YFCPr86dSZLty4e3Ljdr+HrIsduwTMNiHQxDAICq0RDpwKDZ0oH6gBbs88WoQ4/5SNoVPIgoSi9OvpS1SjyiIxLUYvnjXFTGc+roDPPOr1+ho7Car0MtN961l9orJWF1WDEZ5aGKOhKJ0Nvbw7P2vseOlA2z44xYWXDuL2SunXvYx/TVgU/duyuwFLEmfiyxINEc6eLl9E3Pc03AZ3p3iyKqq8eyft3PqRDsllSliuqqqqEmNN144SNPpLibPLODwnnqa67u59bNX4e8O8Odfvsmi1ZNRZInezhTZNplQee3pfXS29VE5LY9920/R1tzLzfcsJZlUaa7vIT3Tgb8nxEO/fIMvfnM97nQ7x/Y3sXtLDQtWTCLN60Af9GQG+yPc/+8vklPgoXRSNsm4SjKZSr9uaejh+IEmpswpZPfmkwR8YT56z+JR19fdGeDxP77NkhWTUAwSb75yiA3P7cfuMJGTn8apEx08/ehOVqybTmd7H7/6z1dob/HjzXQwEIzywpO7uf3Ty1i2egqiKKCqGrversXfG2L3tlrqajsxGhW6OvpIz3CQPxiiPvce795Wyx9+9RaLlldhs6dWW4H+CPf/+BVO13SQkeUgHk/S2x1i3uIyPnPf1UhyynCKx5M8+uBW4vEEVpuJ1uZeXn/xEF/8+jqqpqYEVU+d6ODnP3iRZFLFk27H1xvixaf28uV/vIbKKbmoSY2dW2poauhBEFOrYzWp8dxfdrH62unc/ullGM4Rq33u9HGerD2Ky2jCNVjbrmMgxOk+H75omBJnGjeXTxkh+qgPFg7WBjWSZFEkoakYJRlZEFF1jZiqopHiS5gkOTV/qUl0UgkEqq5jFCUUSX6/0tVJ6hrf3/s6n5+8kCK7+105Z4UznZ8vuYGCCZ5PESVuKp7K8pxSfnV0O4d9FxY/7Yu8QSC2bfQOHVKU7SSgI2DEapz5V284AaQbbXx18grawv0kdRW7YiLHclav8Lq8qUxxZZPQVLLMqe1mSeFLk66idaCPmJrEphjJNL27GofvFL87sZP6oI9VuRWsy68kw2xDEaVLDh+LiMxLm8bDTc9TZM1D1VXqQy3cVrh+wmMbt+EUUQdwyC7scoqJnqq8Hb9iWQUttR0c33UKm8vCl370CeatnYEgjOYvudIdZBV6KZ9ZxH987jfseHE/Gx/f+Z4ZTlE1Qt3AKbKM2bgNnvddyLAn5md5RjVuQ+olyidr8OPx7lasFyWRmdUlVF91NgMiEo6z8cWDVF9ViWKQcKfb2fzKYW6+Z0mKpDqYOVE6KYfcQg+SLBLsj7Dl1SMsWjUZxSCRlm5n40uHuOmTi7FYjVQvq6Snsx/FILFjY5jujn7c6SkD0Zvl4ppb5qIM0xrZvbkGURK5++9WIyvSEGu2s9WPw2Xh2o9XUzopG5PZwKaXD4+6LkGA9Aw7FpuR9lYfZouBhtNdTJ1VSP2pLuKxJF3tfWRkOdF1ncf/tI3Otj6++x8fJyvXTTyW4ImHtvPgL9+gpDyTguKzmVN7d9Zxy50L+N5/3o7BKBOPJZGVkZ4HQUyp1W/beIKHH9jM0lWTufWeJYhiiq906kQbxw4284Wvr2PeoCdtIBQlmdQQpbPPam93kOlzCvnKN67DZDbQ3urnG1/8I9s2nqCsKptIOM7//Ow10r12vvxP1+JKsxIKRLj/Jxv47c9f55+//1HsjpRX6NjBZr7x/Y+y6KoqVE3jhSd28/ADm5m/rJKqKSNV7WVRpD8WpTnYnxJU1XUMkoTXbGVWRilfmb2Q6eeIPgYSMe4/to3+eJT2cIBKl5f6oI9qbwF3VcxlT3cLT9QfZCARRxZE7iifzYKMQv58aj+1/d3o6HRGQpQ50vnylMU4DRNLdb/SOObv5EBPG7GL1Li7nLApRqakXVoB3OEQBAGrYkARxaFMvAshx3kfXvWOUdt1EiRVHwPxAwSiO3Cal5Pn+scJj+uDBEEQcBstuI1jJ3yYZYVJrtG/kUMx4Rhj+wcFgXiMXV3N7O5q5hdHtrIyt4wVOWVM82STZ3VeUq3O5d5q8sxZnAimJB3WZC6hyDp2RY3xYNyGU4Yxl7d7XyKihuhLdLPX/xYd0SamOS9N9n68CPUN0N8bomhyLrNWTL6guKUgCFjsZpZcP5c9rx2mta7jvMdeafjjPh5t+gPXZt/I/LTR3oj3GuW2Qt7o3I6AiEUycaT/JLIgYpTe3dCmJIl4s0bWztJUjd6uAP2+AURRQFZErr5xFpIkkp7l5LbPLWf35hp2ba5h6uwirv34PNSkhq87SF9vKqPOYJK5+obZCKLAwd31vP7MPiqn5WEwyqiqNoIj5812IkkjyZP+3hCeDAeyMpglOOyxc7gsWGypLESDUSF5HlKk22PDnWajsa4bs9VIeCDGutVT2PV2LQOhKJ3tfRSWePH1BDlxpIUFyyqGwltmi5ElKyfz1oYj7N52aoThJIoC19w0B7Ml9Vud+Xc4ZFni8P4mHvndFhavqOKm2+YPGU2psdlRDBJb3zyGO81KWVX2kIEz/D6YLQZWrJ02JG3gSbdTVplFd2c/mqpRV9tBV3sf135xBR5vyhB1uq1cfd1MfvS9Z6g90c7s6pQnOj3TwZwFpUiyiITIjLnFbHjuAAd3148ynNaXVFGV5sUXjRBJJgaLespk2+yUuz0pEbwxFiPd0RArc8qpC/bSHg7y6cpqnqg7RCgRp8KZzn1TluAymHmq/hCb2k8zz5uPrus0hfz8e/V1IAj8y77X2N7ZwLr8d5YlrOs6b7adIppMIggC+3taWV8wGaMk8XzjcYrsbq4trMIqG0hoKkd9nbzd0UBnJIgiSEzzZLE8p3ToWusCvbzafJKdXc20DQT46eGtuAaNu+sKJ7E4q2go26g7GmJD80lO9/diU4wsyipifkb+UGgvpiZ5su4weVYn5a50NjSfpD7gw2U0cWPR1CFPVk1fN3+o2QOkJC1uLZtJuXOkZzOqJtnZ2cje7lb8sQg2xcBsby7LsksmLKxqM8654H5N/zg9oUfpCD5AOH4NDtP45thyWwl3FtwyoTG9Fyi3Xxn6ywcJnyifjcNgYnN7HR3hAM82HOWV5homuTKY481jRU4Z87z5QzIa53NSpEjmMlWOEqocl+e+jl/HyVLKQtayvWcDvfEOdF1nqfcjZJgmbrVdCKIoIooCDrdtXHwlQRSwuSwYjAqy/L4twfeeY5l3HhE1ysONz5HQk+SYMrg+ZxVW6d3njAjn8DQkWSS3KJ3JMwuYs6QCXdNRVQ1JFknEVQrLMigsy6Cns59f/usLTJ1bREa2i5xCD1PnFjOzugRNSxlHoiiwe3MNOYXprL15Lv6eIC8/sWfE+VJcnZEvW3a+h4O76un3DWC1m0gmNRRFGjx+fLotDqeFzGwnDae7sNpM2Owmissyef3Fg/T7w7Q1+1h29RQikTj9/vCoUJs304Esi3S0jhQl9HjtQ0bO+dBwuos//3YTalJj6crJmCyGERNKQXE6n//aWh5+YDM/+M5T5OSnce1Nc5gxtxiL9eyxdocZh/Ns8VhBAINRGSrk6e8NEY8nyckfyZnIK/QQCcfo853V90nz2JCGSYbY7Kl70tU5Uj1cEAS8Fitey6VzD0ySQr7NRSQZRxElMs2pEicJTaUp5Ofl5hN0RoK0DQQotqcN6ZFNcWeRO0gurXCmUxfsveRzj4Wjvk7eaDlFlsVOezjAW62nmZWeQziZ4Jn6IxglmY8UTqIx6Oe/j2wjmIiRa3MSiAd5oek4+7pb+dacVZgkeciAlAezJT0mC55B78PwkGVTqI+vb3+BuJqk3JlOXdDHMw1H+NKURdxaNgNJSIUw3+5oQBFFdCChadhkA8f8nVwzzGB0GU1M9WRx3N/FM/VHuSqndJThdKi3nZ8dfhurYiDLbOd0oJcn6g7z5SmLuLtyzhXxtouCAad5Nb3hF+gZeHLchlOBJY98y+X/Vv34N6+zpLqM6plFl7Xfv7ZCwxPBgsxCZqbn0hePsKOzkWcajnKyr4uj/k4O+9p5vO4QpQ4P6wsmsTynDK/ZikU2TDij+FIwbgtDEiSKrJMosk4aEgu7kj+uM92OJ8uFvztALBzDaLkwQUzTNPxdAWKROCXT86/YuD7oSOpJ1ues4Nrsq4hpiaFMA22wzs+7RRAfC0ajwrqPzuXtN45Rc6QFAYGcQg9X3zib1sYe3nzhIJIkkognyS9Kx5PhwGI1cPX1s9n88mGO7WtEBwpKvKy6fhZV0/N568WDPPn7rQwEozjTLv5Bnr2olAM7TvPb/3wFT4YDk9nAsnXTkKTxP+uiKFBYmsG+Hadxe2zkF6WT7rVjMMg0NfQQ6I+QnetGkkQkWSQeHxkmPcOpkpWRrmhZvjghOBpNsHzNFLZvruHR32/lC19fh8N5lsAuSSJzFpQyaVoeh/c3sn1TDb/6z1dYsXYad39xxdB1iqKQCvsNg8DZwpvSoG5XIj7S65aIJxFEEWlY1lsioY7QAtI0PaXDply+Z23oIy0IIzK24prKfx3ezM0lM/jHvOW80lLD9s6Gof3D61pF1CQOw+VbQLSHAzy48uMc8XXwv7a9QIXTyycrZvPZTU9S299NUq+k0O7mO3NXkW1xoIgScVXlvw5v4eHaA3xtxjJMksyUtCympGXx2KkDnAr08sny2VS6R9a6jKlJ7j+2A03X+dmSGyi0uYmoSX58cBO/O7Gb+RkFlDrPGrnbO5v41qyVXFtYhSJKRNUkBvGsFluWxcGd5bPZ293CK801Y17fDE82P170EfJtLkRBoC8W4Zs7X+aJukPcXXlhz9E7gSSYEQUz0WTjuNukeDGX/3sVDMWIx7V3tX7r+w3aoJ6eIl5e6QNBEFLVJGSFm4qnsb5wMrX9PWxsO83uriYO9bazv6eV/T2t/Pr4DpZmlbAgs4AFmYVDi6ErhXHPXF3RFiRBJs2QOegW1uiOtWGQzDivgHJ4blkmk+aXsef1I+x76yjz181MEUzPkz0U8ofZ8vQuDCaFq26eP0aPY0PXdV5sf5psUy6dsQ66Y52sylhHd6yLff5dTHJMY27afAyigaga5WDfXmqCxwkmA5glM5X2ycxxz8coji0kqes6vngPL3c8h1vxsC77I4iIaGg0hRvY49tBT6wLh+KkOm0xpbbyK/oSvtyxmflpMxAFkYxB8a+2SCePNb+MqmvckLuKclvhFeVmKYrE579xLVm5I5VbRUlkwYoqCssz8HeHkGSRjGwXoiiQledm6ZophEMxZEUip8CDa9AQWnz1FEqqsvH3BpFlicxcN4IA85dXkZXnJhKOp8JJgoDLY0UQUm00dSSvB8BkNvDJ+1bR2tBDLJrA6jCR5rUjigJ3fmkVaYNFpCum5uLxrjrvNRaVZPDa8wdoPN3NjLlFuDxWvJlOjh9pQRQF7E4zZrOBzCwXJ4+1suYjMxGE1PPS0tBDPJ6ksCTjvP2fD8WlGVz30blUTs7l/p9s4JlHd/KJz141ZBBpWkoZ3WI1Mn9JBdNnF/Hn327ijZcPDh43vmcvO8+F2WLg1MkOJk/PRxBToaKTx9uw2014s85OXJ1tfUTDcYyDRHBfTxC/b4C8wncjw0cnoWsYRInGkJ/XW0+OSMne39vKjq5GREHkmL+T1bkTV74+F1kWOw7FRPZgZlCxIw1JFPGarQwkE6iDYcg8q4ukphFTk+i6TpkznaiaGFP1/nxoGwhw1NfB/IwCMs12omoSAZjjzePFxhMc93eO7Y2L9QAAIABJREFUMJzcRjNr8iuGeCKmCYTWDKJEntVJUlPRAKMkU2BzcdTfOeHCrheDruvE1XYSaheKeOmEdU3TUQerFmiqjiCm1K8FQSCRUBFFAUkSU+K6SQ1JEtD1QWNf15EkMTVviALyYDUBXdeJDS4gFFlEEEQEIdUmmUwtGqTBfgVBSI1B1VJJMZqGIJwdwwcNuq7T3N/PwfZ21pSVYRqjdNflgiJKTHZnUunyckvJdBqCPra01/NW2ylOB3p5uuEwG1pqWF84iX+rvvy6gcMx7relfuA4ZslCmiFVl01H51ToMHbFjdM5fkPlXGiaRn9PcMQ2gRS35COfW03LyXZ+/c+P0NXUy5SF5dhcVhSTgiCkMnTCgQidTT288D9vcOpAI5/89o2UTr+UtFmd5nAjxwJHyLMU0BJu4oH6/6bAUoxBNPB82xNkm3MospTQGmlmR+9WXAY3+eYCumKdPN36GP54L9dl3zRm773xHh5uehBZUFiXlTKaAA727eXp1r+Qa84nx5xHZ7SDB+t/xUfzbmO2u/qKGU/N4Q529R7GJBmY4azipryrebN7J5McpZgkI690bKGkNA/5MpY7OBeiKFIxdex6VopBpqAkg4JzjAazxXjeNgajPBTGGw6jSTlvm8ycseX2BUHA4bLgmDla8LO0Knvob6fbitN9fg9WcXkmwWCUutoObrxtPgaDTFGZlzdfPkx2nhuny4rdYWbF2qk8+vstvPLsPiom5RAKRnn6kR2ke+0sXn7pXBtRFBAlkdkLSrnj3mX88f638GY6uPq6GSgGmZqjrbQ1+8jJd2MwKAwMRGlr8ePNdHIpj1xJeRbzl1TwyrP7cLmt5Bak0d0Z4Mk/b2dWdckI7lI8nuSPv36L1etngA7PD4ZMq5dcWBl+vJAFkXJHOnbFSKbZjkU2YJYUKpxerLKRL01ezHONR9jR1cjq3HKSmjbkzp+Xns+m9tO0h4PcWTabed7L5622yEqqfA8p2sEZ40QkZWSi6/iiYV5rqeXN1lMEEzESmkpvNExCUy+pREZfPEIwEePJ+sO82nJyaLum65hkeUg89AyyzfYx6x2OF7qu0x4O8kz9EfZ2txBWEyRUjdaBfiRRgAmaTuF4DaoeOM9JNZJaH12hh4gkTuJxfv2S+z/V0MWfn96F026moyuAIMC9ty+moiSTn/zPG8ydUcjKxZUEglF+8fuNXL9mOidPd1JzupMe/wDlxV66uoO4nBa+dPdVaKrOtt2neXPrCcKROCsXV7J66SQAtuw6xaYdJ4nFkmSk27nzpmoyvQ6aWn3c/6fNTK3M4ejJNrIznNz1sQW4HGOTv3Vdp6m/n7ZAgISmIQB5TieFLhexZJI6v5/+aJQ0s5mStDQUUaShrw9ZFOkJh4kmEuQ5neQ6HIiCQDiRoM7nIxCL4bFYKHG7kUURVdc51tVFhtVKY18fBkmiPD0di6LQFQrREggQV1U8FgulaWnIokid38+bdXXsbW3FrCh4LBaq0tOxGAz0R6PU+XxEkkkybTaKXS5EUSSWTFLb20ua2Uxjfz8WWaYiPR3zOI0uSRDJMNvwmqzMSc/jC5MXsrm9jsdOH2BnVxOtA+d5fi4jLvp11HSVnngH/YleomqYjlgTAEktQVuknqp36G0KByL89L7fjRI8E0UBSZEQZZH2+i7u/8afySz0kpblwmwzIooCiVgSf3eAzsYeIqEo6bluAr4Bju86xfQll/bRMYpGbsm7g529b/Nc2xPMS1tIlimHpnADvlgPRZYSCi3F3FX0WVxKStI9ooZ5uPFB9vftHWU4iYj0xLt4quVRZEHm5rzb8Bi8Q+02dLxAua2KW/JuxyxbiKlRft/wG97u2UiprQK3Yez7mkyqdLT10dbiJxKOISkSLpeF/ML0ESGZ80FE5DMlt5Bh9PDbusfR0QkmBljomUWm0cOO3gNo76CUs67r+Dv62PnyftpOd2K2Gpm5YiqTFpR/IFdUE0WKI2RG18HuSJF8C0sz6O4MMGNuMTabCVEUuGrtVMKROC89vZenH9mBIAgUFKfz2a+uweaYeHaXJIksXTWZzrY+Hv/TNryZTuYsKCUSjvH8E7vp8w8MepcEsnNd3P2FFciXICopSSIfu2sRuq7z6INbSCZTq/XJ0/O5/VNLMVsMxKKp7K8z2k///R8vEx6I4nBauPe+1XjSL4/8hVUxcFdFqq5hkf3se/OZqtSCbll2CcuyxyaFOo1mvjp16RV6Ni/cZ0LTeLzuEL8/sYfPTq5msjsLh2JkW2cjPzyw8ZLOJAsSiiixJq+CawtHzn2SIFJiHzmfvFMdqGAixn8f3cbOziY+P3kBxfY0rIqBP9bsYWtHw4T7be3/McHY9rF36hqqHgZ0bMZ5pFlvuOT+dR1ON3TzmTuWML0ql6de3s9rm49TUZJJUlXRBr1ROimPk6bpBEJRMr0OFswu5vnXD/OFTy7l1w9tpccfQtU0TEaZe+9YTH1TD0+/fIDpk/KIxhJs2VnL7TfMw+ux85fn9/D8a4f4zB2pDOHGVh/rVkzhutXTUJMatgtQUVoDAX62fTtVXi+nens53NnJ/1mxgmy7nZdOnmRfWxtpZjPtoRArS0q4prycvxw+TL3fT7HbTUxV8Uci/MPixWTabDx/4gSHOztxm0y0BoNcW1HBqpISwokE39iwgXUVFWiahkGW8VqtGCSJPa2tHO3uRgBO9fZy34IFTM/KoiMYpM7nozMUoqanh2y7nWK3GzUW448HDtARDGI3GmkLBrln1ixm5+Tgj0T4pw0bWFtWhqrrWA0Gsh2OcRtOZxBOJtjR1ciuziYO9rZRG+ghro5fxfyd4KKGk6qrHO3fydH+nST1BEcCO4CUVyjPXEa+pewdDSART7Lz5QMXVYrVNJ32+i7a67vOe0xPq58n/utlju2o5Ycvf/OSxpFm8GAQDaQZPNgVB07FhSzImCULUS1VvVwSJKyyjVAyiKon0dCxynaiagQdfUQMPa7F+EvzQyS1JJ8oupc0g2dof3O4iUCin+q0fCJqhIia6j/HlMdO31b6Er4RhpOu60SjCfbsOM0LT+2lubGHWCw55O5VFBGzxcDCpZWsXT+TgqL0EZlUw+FS7MS1BBE1SigZ5lBfDYFEiKgauyw8gKAvxG+/9Qi6plE0JZ9Q3wAPfucxPvb19VRfM+sd9f1BgiDA//nhbYCO25MqvDljThE/+8NnsNpMQ+KWZrOB62+Zx7JVk4nHkoiSgM1uxjqsUK9ikLj900uJxxIXzC799H2r0TRtSLPJYJD56J0LuWrNVJwuM4IA02YV8t3/+DjRaAJd0xElEavNiM1mGuI0zV1YSnlVNmnDDBuDUeHzX1871C+A02Xh7i+s4Kbb5xOPJ1FkCbvTgsk8cgJUFJlPfn450UgcNalhthhwOM3jDgteUVz+uqfjRlRNsLe7hQpXOreVzcQymGX3VtspktroMJ1BktGBqDb645BrdZBtsRNKxJnrzcMsKUOZdnFNxXAJqdvjQU90gCO9HSzLLubmkmkIQCgRIzIoITFRWAxVnO9HERCQRAc24zycpqUo0sRS7fOy3UypyCbNbaWk0Mu2PafHPO4Ml1eRJdwuCwV5HtKcFvKy3ZiMMrFYElmWmFqVS4bHniosLggEQlF8fQMcPNpCd28QURQZCMcoLkgfujfZXgdTKnJwOy9eU/JIV+qbd8+sWbQFg3z7tdco83gIxeO8euoUH508mQqPh+3NzTx2+DDrylOeXJvRyJcXLCChqvzft96itrcXWRR5q66Oj02dSonbzebGRh45dIhVJamFharrzMjKYkF+Pug6iiQhCgKLCguZnpWFpuv8bu9e9rW1MT0ri4UFBUSSqRDzPbNmYTEYEIBDnZ0c7+riG8uWkWmz8WJNDX/Yv5+Z2SmvvappLMjPZ2Z2NvrgeS4EnRQPN5yI0xoOsKG5htdaTtI60E8oEUMRJTwmKytzyrmz/Mp/Zy5qOMmCwnLvTTiVdAyikUmOFOlPQLwsZDuDycDVn1h6WSs3ZxaMFgS8GOTBkiOCICAiIQpSqmAlZwmxHdE2tvS8RWukefDaBbpjnehjFIvc2P06fQk/kx3TMIuWEfcqlAwQ1aK81vkim7tH1k9yKi6EYbXYdR18vSH+8tA2nn9qL8lEijgsSSKKIqFpOgMDSfr8YZ56dCc7tpzkU19cybKVk8a8zqXeuTzV+ipxLcFUVwX7/cdIN7rZ0r2bvf6jpBmcQ+HEiSDgC6EmVL7007txeFIf3q1P7WLf64cnZDjpuk5zMMCWloYx95skmevLqi764l0MDf1+9nW2YVOMLMsvwjSOzMyEqrK9rZnmYD8mSWZ+Th559hS3RxAEvJkjBeeMRoWcvNGeRFmRSM84vzidIAi4LhAWPIO0QQNtOEwmhdz8s+dUDPIIg2gsmC1GzOesgEVRGOUhEgQBo0nBa7pIyYPBcTjHUXj43USly0vkXVqhjgWDKFFgc/N6ay1b2utxGczU9vfwclPNmOn85c50VE3jqboj9Mei6OiUODzk21y4jWbuLJ/F/9v/Fj86sJmFmYUokogvGqYjHOTuyrlYx6GjBKl3rnWgn3AyQV2gl6Sm0RD0kWm2YVeMeM02HAYTGRYbRwalFCRBYFdXM0d9HSO8WVE1SftAgFAiRnd0gEgywYm+LtxGMx6jBZdxpJc8x/HVcd+/iXoJjQZ5SP1eHDQuIeWFU9XUXK6qGqGBWOo8g8cJDIbCxTMLzJS2XHxQlkQ7ozU3mKxbXpLJ1z67EuvguyRJZyssKoo0rmQPgHKPh6eOHuXhQ4fwRyLMzc3FYTTSNTDA4c7OFGdx0FtT6HINXU9Vejo2g4FYMolFUYglk0QSiVQbQcA8OMcVuVxDpqrdaKTY7R4x/wViMR4/coS2QABFkjje3U2mzTZ0bwQGyfeDWZ+6rtM9MIDdaMRjsWCSZarS0/nL4cNEEwkQBNxmM/kuF8ZxzLMxNcmp/h72dLfwdkc9b3c0EFETCEC2xcH8jAKWZZewIqeMLMu7I+J80VGfeTjLbFMRBQmRy0tis9hN/P3P7rls/QFMRJXzYkZgKBnilY7naY00c2PurUMeqlc7X+Ro/8FRxxdaS1hhLWNDxwts6n6dtVnXIQqpj7tBNGISTazIWEOVY8qIdiIi6cazXJ1EPMnTj+3ipWf2IQgpr0X1ojLy8j1DhlMgEOHk8Ta2vHmMtlY/D97/Jt4MB5Omjq5sX2zN4+6im4ipcTJMHkREdHSOBmrpiPYwzVlxgTpSF4fBqOD02knGVXQtNZEkE0k8OW60wUlJEEZnbF0Ix3o6+fbm18bcl2Yys664/B0ZTglN40e7tvJqwyksssKPV17DysLSi7aLqkkePnaQV+prSTOZ+cHytUOG04d4/2NxVvEV61sUhBH6MvIgYRgGicKCgEGSuaV0Gl2RID86sAmjJFPuTOeuyjk8cHzXqHe30uXl3qpq/nL6IJvb63AYTNw3dRH5NheCILAit4yErvHk6cNsbEt5URwGI6tyy4fGAqlzSxeYI1Vd51/3vUnLQD/BeIxoMsFvj+/iL6cPMcWdyT/MWEa6ycK9VdX8/PBW/u+e17DIBqoz87mtbCZP1x8Z6qs+4OPbu14mmkzSHQ0RSSb5zq4NGCWZG4uncHfl3BEz77lV7UHjrAcqxRg797jLhewMJweOtlBVns3h4620tvddtE0yqbL7QAOVJZmcrO9CFAXcTgsWsxFN19h/tJnpk/Lo6w9jNCqUFXkv2ue5KHK5MMkyRklifl4ekzIyUCQJSRQpdDr5/Lx5VHmH6b2d8VSPMSfKokiR282X58+nNC21oDpj/Jz5+9x0/o5gkO1NTfzzsmWUpqXxgy1bRtx/URBSRiNni8fbDAYGEokho61zYACHyZQylGIxROHihchDiRhvtZ7izbZTHPV10BjqI6GpKKJIlSuDa/KrWJxdRIn9/PpuVwrjZgDH1AiBpJ8MYy5W2XnZyMuCICBfxrTkK4WQGqQj2kalfTJTHNMACCYDBBJ9Qy7d4SizVlDtWYSAwMsdz2GXHSzwLEEWZQosRZgkM/2JPjKMWUMZeaquktASGMWzq/3TtR08+8RuJFnii19Zzco1U1EM8lAo7syDunzVZNbfNJvf/Px19u6s49nHd1FQdO1Q2OYMdHQ0XSOuJWgOny1/MMVRznRnJQJjh/jGC6PFQHdzLz+45xcUTMoj6Atxan89M1dM5bff/DMA89bNYtYlKLvn2p18pKyKvmiEUCJOLKlywtf9jkICwxFOxKnx9RBXVeKqyuk+37gMpw9xYQiiQHZeWiob9hIM5b8GfG7SfD5dVY0oCBTZ3Tyx5i6MkowkCHxv7pqUiKooUen08sOF60loKQNBESVkQWR9waRRld5lQeSTFbP5eNl0ND1FDTAO+zjKgsg1+VWsyikbIoOLgjDUJ4BVVvjBgusuOHZJEPjRwvVjch1TJWsUREGgOiOfB5Z/jKSuISAMyRncXj5zaCFa4UznjytvGzP4ZhClMZeruq6RULsJxnYRiL5NXG0FdAxSNjbjPBymRRikbATh0hdLZpNCQV4ayqC3x+kwk5+TMiCuXzOdh57axW8e2kJlaSbXr5mO1WLEm27HYTdhMink56QhCgKF+WkYjQoVJZnkZLl4/IV96OjccWM16YOe9i/dfRXPv3qIzTtOkeaycMPaGQCYjApF+R7kcYaqQ/E4naEQ6VYriiTRFQphkmXcJhNLCgt57PBhFhQUEE0kcJlMrC0/f9KF12plXm4ujxw6RHVeHuFEgnSLhdWl55/vjLKMIoocaG9nf3s7x7q6WFJ4NgEr3WqlJxzmpZoaClwupmVmUu7xkGY284f9+8lzOtlYV8ft06dfErfuf+9+hVeaTpDQVEySQqHNzXRPNjcVT2WmJwejpCAJ7+x7NVGM22IZUAPs8r2GpmvkmUsptU0jx1z8N6NfYZPtpBnSqQ2dYLdvO6IgcSpUQ1e0E5HRL3Aq5Ccy37OIrlgnr3W9hMfopco+GbvsYEXG1bze+TKarlJgKUJHpyfeg1Wyscy7EmWw6vfWjSeIRRNcc/0sVq+bPqq215mHRlYkCoq83PmppZw80c7JE+20t/opH5YJBnAiWMczra9jOKeq+OdKb8WhjA71XCokWWLO1dNHbJt2DlHfPo6w0xkIgsA0byY/X71+iK/RHQ6z5rEHCV+m0hM2xcDSvCLaggEyrDYW5HyoA3Y5YDDI3Hznlaks8H6GMOhNOhMYE2BEmOxcg8goyRjPmUIs4uiwmjDoKRpr35n9whj9n3vMxbLpzpRJuRhEQRjzXPKw8UmiiE0cf5FWXdcJJ47S2vdjAtGt6CQQkAcNryQ9A09iN84lx/n32I0LES7x+1OQm8a9t50VzZw1NZ9ZU1Pvu8tp4b5PLR/VZriX6K6PLQDgc3cuBeBTty4CYO1Vk0e1K85P5+/uXTlqe3amky/eddW4xqvrOgc7Osh3udjT0oIOdIZC3DBpEsuLi7lr1ix2tbRQ5/djlmUK3SmJhmVFRVgNqd9BEkWuLisj3+nErCh8evZsdra00NDXh0VRKHSlMoyNksQd06fjNI1cbOfY7Xxu3jwOd3bisVj46qJFQwa7IAhUeDx8evZsTvT00BeNouk6HouFL8+fz5bGRvqjUW6fPp2FBalMZZvRyK3TpmEzXPgZiyQTWGUD1ZkFLM4sYmFWEYU29zDv6XuHcRtOBZYK0o059MTaqQnu48X2P2CVHUxzLqDMNh2TZEWawArgfEjEk0SC0Qm1lWQR6zhId2dgliyYxNTDIgsyVtmKREqPwyJbUUQFq2TluuwbeaXjOV7rfAmjZGKacyZrsq5je+/mob5EQcQq24cMHxGJVRlrCSb6ebXjBfLM+dhkOws8S3EoTnb2buNk18uIyKQb01mYvmyEMXq6tgPFIDFrbhGK4eL3t6Iqh4xMB00NPfT3h0ft395zgAWemcx0TRoRnrTJl4d/YnNZWf/5q0ds01SNeCyB6SIipheDIAgYJRmX8fK6ZSVR5O/nLuS2SdMwyTK5tg9WMcwPceWh6zr9/vCQh1dWJKxWI+L7geD+VwRV66fR9x2iiTrSbR/HbV6DIqUMl4TaQ3/0LXoGnqLR910qM/6EQc55j0d8ZTGQSPD0sWPcPn06M7KySGgafzpwgJqeHpYVFWE3GllVWsq5inJnjBRIheeWF58NSztMJq4uG53UZZRlPjplyqjtiiQxLy+PeXljS7sYZZnFhYUsHuaFAsi02bhljP5sBgM3TBqbgzsct5fO4qvTlpJtceAwmN4VRfDxYtyGkyhIWCUHismYym4QFOpCR9jr28iBvq1McVQz3bUYwyWsLi6EAxuP8dOvPDihtsVT8viXp8ar8SFwd9Hnhv5Xbqviq+X/PPT/z5X83dDfueZ87i3+8qgehtekyzBm8U+V3z3buyBgk+18ovDeEdsUFGY45zDDeWGF3fBAHEWRMZkN4zIWJFnEajWRiKtDRPLhUEQZt+IgzfDucXH8nf289MAbfPI7799aUU6jCafx/Vnc9UO894jHknzm+p8yEExlwE6fV8zXv38zGdlj64F9iImhN/wc0WQDua5/xGu7DWHYJ8qsgMO0CIthGs3+79Mz8AQ5zr+7QG8ffJhkmSkZGbxSW8up3l6C8Tg13d3cOXPm+8qQuBK4KieV6fd+lLG5JI7T6YEjHO7bTlJPUGipZH3OPTiUNDqjTezqfZ08SxlZptHCgRNBLBqnp9V3ye0EQSA9Z/yKsuf+KO/0Rxqr/Xi3jQWH00wsmiAQiKDr+kXbxWIJ/P4BjCZlKG18OKocJbzQ/hZtkS5cBseQ12mOe8qEC/1qqkZLbft5U7t7Wn34Oi5OtPwg4/33an+Iyw1d14cybC9jEvCHGIaB2D6MUi5O01JEYayQoozduACTUk4otu9dH5+qhegNPYQsekmz3XzFzyeLIrdOm8ahjg780SjpFgsrS0oocbvflwbF5cT7+frGbTjVhg5xqO9tZrmvotBSiUkypyQJBAGTpYqW8Gn0SygRcDEUVuVy93fP/2BqqkY0HKPtdCfNJ9vpbOwhtyyTT3zrJqYuvHxlE95rTJ9VyK5tp9j8xjGqF5ZdMC09mVTZvvkkPV0B8vLTRqXDA/hifRhFAyeCdYMrltTDOc1ZMWHDKRKK8u31/47nPAZrIpqgYs77p9p3QlU51deLqo3x9ROg2Oked+r22XZnU3FjqoovGiYUjw/VcHIYTbhN5nHVc9J0nbo+H9FkknSLhQyLbajvvliUvmiUqJpA10ERRawGAy6jGbMsn7dvXU+VjAjEYwTjMSLJBKqWMsQVUcSiKLhNZkyDatcXgq7rdIUH6A4PYFEU8uxODIOch3AiQU9kgEgiQVLXkcUUD8ZlNGE3GIdWybquE00mqe/3o+k61sF+xpMd6Y9GaA8F0XQdh9FInt35V7/6/ltBUg8iCEYk8fxp5ZJgQRIsqFrwvMdcOagk1HYEYWJz5URgNxpHhcH+lqDpOuFkfKjY9cVgkCTcxisrfTJuw6nCPoNK+yyUMYiJkiAzL231ZQvTAeRXZHPHP11/0eN0Taenzc+GP23m6V9sYMeL+5lzCRlb73csXFLB04/tZM+O0/zhfzZx7Q2zKC7JGFUAtr8vzLbNNTz5yA6ikQRz5peQOUYYYV32MtZlL7usY9R1nYq5JXzt/s+N+eHuaurh+V+PLSfwXqAnEubWZx8jEI+N2icAD19/KwsvkSAuDaafNwb6eOTYIba3NdPY7yecTGJTFMrT0lmSW8jHqqaSbbuw1khcVfnSq89z0t/DXVNm8e1FV6HrsLGpjqdrj3G0p4uugQFUXcNhMFLodLOioJh7p8/BZhj9DsbUJMd7u9na0sihrg7q+nx0DISIJBPIoojdYCTH5mBuVi7rSsqZnZlzQQKmpuv86egBfrFvB9O9Wfx89Xry7A6O9nTxVO0x3m5ppC0UIJJMYpEVMq025mTl8Jnpc6lIO6ux1hYK8IVXn6Up0E9lWjo/XXUdkzwXTtdWNY1Hjx/mJ7vfJq6p3D11Ft9aeNWYukd/yzhxuIVQf5jsAg85g5mNHwQYpVxiiXpiyRYUaexahnG1k7jaiVl59xfIkugk1/29d/28f6sIJmK83nKSHZ2NtIeDxNXkRTVrZ3hy+Nbs89cRvRwY92wjCwqN4Rr2+TYSUgM4ZDez05aTby5DFCQs8jvPyJoIBFHAm5fGTV9aQ3NtOxuf2MGSG+cyf93M92Q8lxvZeW5uuWMhD/1uM688v599u06TnZtGXoEHq9VAIqHR0x2grcVHW4ufgVCMqTPy+cjNc8cM1SU1laOBk7RHetB0DR0dURBZnjEfszQxw9dsM/HJ79yCzTW2Nywt203lvPdPer9BkqhMS6c1FCAYj6ENej/UdxB/EQWBhn4/v9y3k70dbSAwmCoL/fEYu9pbONDZzr7OVr6/9Gry7I5xuaJ7Bz1XT9Qc4bcH99AdCSMNaaAI9MWi+LvayXc4xpxQdF1nS3MD/7J9Iy2BAEk9VadNEkRkUUQn5cHpiYQ50tPJhoZavrd4FasKS8Y1vkgyQTAeY2d7C9/d+jr1fX70wfshCgIDiQSn+3yousY9U2cPtRMEgWybnaV5Rfz52EHq+/3s7Wilwu25YMqyLxphd3sLcU3FZTSxJK/wsqtif9ARCkR44Cev0NLQw813LebGTyxC/oDcI5d5JT0DT9EVfBBF+qdB4+nM86ChqgE6g78jlmwk1zl+scyxkAq9RtHREAXL0POuo4OuoelhRMHEmc+kpg/AoNixgAFRNI3qD1R0PY6OOnichCAYx5ROSGUQpoo9WxRlSFsrqWkkVHVoPhIFAUWSkEXxvJ7VMx7lhKaR1LQhWoc02PZCafsD8TiqrmOW5aE5Ia6qQ/2cOf94vOVnxnKm/RkPkTTsGsbD0QYdAAAgAElEQVQbgktqGr8+tp2HTu4lkBjUfkIYlL8YFC+FEecwSjLZliuf3HNJRX43dT3DJMdcnIY0fLEu3uh8nFUZH6PQWnklxzguWBxmqtfMYOszu9ny9O6/GsNJkkTW3zQHk8nAU4/uoLXFR3trH/t21SEIg7SiwS+mw2lmxZop3PP5FeetA7axeyfbevaR0JKkGVyEkmEssoll3nkTHqMoiRROHplxkSpimjJsHR4bV39yfOm37wbSTGYevf5WdFJhu/5YlK+9+RLb25on3GcgFuNX+3cRiMVYUVjMgpx88uxO4qrKwa4ONtTX0hzsZ1NzA/9vxya+v3Q1HvPF3cmdAyEeP3GE/9q7jTSThetKKihzpzRSgvE4dX0+Tvf5WJJbdN7wYoHDhVUxkG6xUOpKo8rjpTLNS5rJTExNcqy3m41NdRzr6aI1GOBftr/FVG8GWdaLq/CG4nF2tDXzx6P76Y9Fqc7OY7o3i0yrDU3XaQj4Oe33kWm1UeYe6UEwywqrC0vZUF9LTyTMi6dr+EhZ1XlJ+vpgCHNPRysAU9IzmO7Nel9zId4LnD7RTkt9D/7eEJFw/L0eziXBblpMuvUmegaeJBDdjt00H0XKRADiaheh2B6Smp9060dxmt6557wz8HOCkTcp8j6IQR6UbtEhHD9EffenyU/7IQ7zKnRiNPd+nViyjniyDbf1BvLS/m1EX5oewT/wOP6BZ0iq3YCGLGWQbr8Hp2XdoBF2Fqqu87FHHuGUz8cDN93EwoICTvb08Ozx42xtbKQ9GEQHMqxW5ufn8+nZsylyj6ZD6LpOWzDIpvp63qyr42hXF8F4HIuiUOJ2c1VREWvLyylyu8c0vO558kkOdnTw72vWsLq0lE0NDTx/4gQHOzoIJxKp8+flsb6qivl5eedd2Oi6TiAWY09bGy/V1HCwo4PugQFEQSDbbmdJYSFry8uZmpExLsXw4/5Ofl+zm5iqMis9l3nefBwGE788+jZ5Vhcrc8tIaCr1QR97u1vItTr41uzVVHsvD8/6Qhi34eSLd1Fqn8Z8z9WIgoSqJ4lqYfoTvVdyfJcEq8OMwWSgvaH7ip9reImYKzlxnylrcc0Nsygpz2D/ngaOH2mhtcVHJBxP1VHy2Cgpy2DugjKmzcjHfoFiv7WhBm7OW8upUBOV9mLSDE6ea3uTpD46A+9SxngGuq7TUd/Fxr9sR5JFbrzvGpprWrG7bWRMoBTOlcCZlRikyJdmRXlHleIhVXAykkzwhZnVfH7mPFwm89C+a0sqqM7O5d92bKKhv49NzfVsb23i2tLKi3Jzav291PX5mJKeyVdmL2BBTv6ISUfVNFqCAawGw5h9CYJAsdPN1+YuxiTLTPZ4cZtGPh/XlFRwbUkFX3nteer6/XQNDPB2SxM3V45OJT4XvmiE3xzcDcA35i9jTXE5nmH9a7qOLxomGIsP8aCGj212Vg4lrjR6ImH2d7Zzyu9jTtbYKeY6sKWlkUA8hiyKVGfn4bWMXxPsbwG6rlNX00FoglIu7zWE/8/ee0fHdV7n3r9TplcMei8ESZAEeyclNkmkrN6s5nptOU5cktw4vrHjJG7xtf3lOvGNu69txZZky7Z6sQpVWMQidhIkARAgiN7LANPntO+PAUCCaINCkXb8rMW1OIPT3pk579nv3s9+HmRyPH+DScqmO/RbesMvjPi7RS4kx/PXpDnuRRBn1gUrCAJu2zb6Qs8Qih3GJN0+/LsdiOzEIudjNZUm3jPM5KT8E3G1hVb/v45pszWUjUpx3IFZLgQMeoNP0tH/XaymMmzm0cbzmmGgGQZtwSAHGhv59t69VHV1jcgeD8RiBGIxHl6yZNT+hmFwvreXb+zezbtNTcS0xDwuCgIRRaEnHOZoSwu76uv5uw0bWJ2XN2qeGLqGur4+fnz4ML+tqMAfjQ5zHev9fur9fvY1NvL3113HLfPmjRk8DcRi/Mf+/bxYVYU/mvj9CZf87Vx3N6/X1vLxlSv5wNKlk859+zvqiWsaK9Pz+Prqmyl1p2IAT9Qco8Tt4xML1pJisROIx3ix4QzfrdjLa03V11bg5DWl0RfvpF/pxSRaiGlh4noUs2glpA4AzLqW01QR7A+jRJVZ9b0bD5FQjJ99/Tk+9LlbSJnAZ2y2IIoCZYtymVuWTSyqoCgaum4gCCBJEmaLjMUyPjl4CFbRgmqouE0OmsJtpFlSCKhB1DGMQ6eDQG+QJ7/9PGariYbKZm775E201LTT3tDF/Z+7fVbOca1ieWYOH1y0bFTGRBJFthXOobq3h+8dPUBIUXim5iw7iuciTkKG7o9FKXR7+acNW1iSnjVqsknYLkzcEm+SJLYVlgx7Sl0OURAo86Vxf9livvXuHqKayrnebgwm7xaMaSo9EZ1vbLqR++aXj+JGiYJAms1Bmm3sAMdttnDX3AUcaW8hqqk8VX2a5ZnZY06qYUXhpdqq4f1uKZn3Z1L4ZQiHYpyvbkWJXz0PvplAEARMUhpZ7kdIc95HTGkgrrUCYJZzsMiFyKIXcZbI2XbzUsxSDsHoPty2G5AEB7oRYiD8Oi7bNsxy7uB1iZjlfETBgSSM/VsWBQc+50MISAyVF2Upg9r2u1D17lFG8JfiUHMzJ9vaiGkan1yzhlU5OXhtNrpDIU60tdERClGaOjJjaxgGTf39fO3ttznY1ESu280DixezpbgYt8VCfyzG7gsXeLKigqMtLXz5rbf4yZ13DgteXo7fVVSgGwabi4u5d+FCilJSiKoqO2trefzECVoGBvjPAwfIdDpZnTvSziumqvzH/v385tQpREFge2kpDyxezByfD0XTONvZyaPHj1PR0cG/79uH02zmjrKyCcvy5wd6EAWBG3LnMsedOuyUYZVkYpeUMp0mM3cVl1Pd38UzdRXsyJvPhqyicY87G0ie4yTKVAeO0RCqwi47Car9RLQQ/UoPJ/wJAcgbM+8nzXJ1BMn6OvvZ88whlLhKVuGVz2zIssTCVcVYbO9dd4UgCMiyhOycfnC63LsQ3TAoc5XwROOLHOo9hcvkwDrNjrrLEegLYRgGD/7DXfyfR34EgDfDQ8U7VbNy/GsZq7NySbc7xgxOZFFkR3Epj1YcHebpBJQ4Psk2xpFG4qaiUpZlZE+63USYLMAQBYH5qWkIMNx9l4z8BUB5egY7iudOS9FXEARuKirl+8cO0hoMsLe5nqaB/jGDwQMtjbSGEp1UK7JymJMyNnn4vzP8vSHqqtuv9mVMG4ahADKiYMYsZWCWMibdZ2aQSXHcTVfg5yhaG5I4h2D0HXSiuG1bEMaURBgbgiCg61HC8bPE1WZ0I4yidQDC4LjGxwtVVSzNzORftm5lUWbmiPv1xjlzhnmDl0LRdZ6trOTd5mayXS6+uX07ay7JKOUAC9LTWZCezqdffJGanh6eOHmSf9w8Nm2iNxLhoSVL+OKmTdgvUfUuWrWKPI+Hr7z1FnV9fbxYVcXizExspoufzd6GBl6orEQ3DO5dtIh/3rJlxN+LU1JYkZPDP+7cyTsNDfzsyBEWZmQwP238Z3VITWSpUy32EWN3mMyE1BjKYHZNEATsspnV6fm8WH+G3W11107glGbO5vacj024jUtOXj9pMvR19nP+VOOk22mKRkdTD+/+4Tgndp9FFAXWDHoCXSloqoZhGGy6YwWmS3z2DMNAU3U0LUFek03SjJWFh7RjNE1HU3WikTjRmIKhTy79kOJzYr0ssFvkmTtIrJN4qOA2+uL9ZFhSsSXxAE8Goihg6DqxSAxDN9AUjYazTXjfg6zc1YRFkshzezBNEDwUe1JwWyz0RiNEVY0L/l58WbkTHlcANuXPTivyUCZWGySSJkiwQxQ5Y5gIOpS61wdfT4ZVWbnYZ1Dq9FqsvK94Hj+vOEp3JMyupgt82L1sRNCm6Bo7G2pRNA0BuKt0wYy1s3TdIByKcmx/LWdPNtHe0oum6Lg8NkrKslm5oZS8wrThDlZxioGhYRgYuoGq6bQ39VJV0UzD+Q66OwKEQ1EkScTusJCW6aF0QTYLlhaQkuZEkpIn4Q6NQ9d1dN2gsa6TloaL9AlN1YlFFTR5/PlCEAVMpsnN2w3DQNcNVEWj4XwntZWt1Nd00NcTJBqOYzJL2B0WsvJ8lC7MoWxxHi6PfdhXMxm09H8Xk5SG13bTILdp8iz6TOGwrKEz8GMi8QrMcj6B6F5kKR27eXnSxzAMA1Vro9X/TWJqLVZ5LpKYik4UxizrjYRFkvj4ypWjgia4aKVzOQZiMV6tqUHTda4rLGRVbu6Y9+uq3FwWZmRwtLWVvfX1BNevH9PuRBJFHl6yZETQNPT+1uJinkxL40BTE3sbGgjF48OBUURReLuujoFYjEKvl/vLy7HKo63Bslwu7l20iFMdHZzv7eVQczOlPt+4WSezKKHpBjFdHbGI81nsNIf6iWjKiPfdZisWSaY5eOU1A2fcw5tmycYpz74K9dl3a/nGh3+Q1LaGbqBrOiaLievvuPIddcf2VPGHx/Yx0Bvk89//CFn5iZWvvzvAk//5Om313ZjMEmtuLGfznStmZDUSj6ns3VXJ7jfOUnWmhXA4Nq7Q5OX4p2/cx/rrR7bsmsSLX3muLZNcW+a0r20spGR6yC7J4rGvPUVLbTvf++wviAQj/NW/f2RWz3OtwSpPbgUjiyLZDhf1/Qlj6I5wKKljF3pmviBRNI26/j6qe7s53dVBTV83vZEI/fEoEVUlpqoJbadplLlznO6k9JfGgyyKbC+ey0vnq+kIB3m7oY73Fc8lw3GxU7emt4cTHW0YJEjhyzOnn9k2DINIOM6+N8/wu5/vpbWpB10zRpT4d71yisd+8Cabdizmvo9eR2aOF4fTQmAMG6OxEIsqNNd3c+Sdc+x/u5IL5zrQ1ER5/XIqgSAmOhAdLisbbljIPR/aQF5h2oSLLl3XqTrVTEdrH/U1HVyoaaehtoueroERjgG/f3QvT/9q34RB5pI1xfzLdz8wZhfuECLhGHXV7Rx+5xwH3q6kpaEnMRZdHyUGKg6aOntSHOy4eyU3372S9GwvYhKSCFG1nvaBn9LS/1081s347LdgM83HLOeNI4g5MwiCgEnOxWnZQF/oOaymBYRjx/E5HxzVNTcZ+kLPEYq9S0Ha93CYVwACUaWavuCTk+7rs9nYWlIypdJzeyBATXc3ADaTif2NYycaFE0b5hf2x2K0Dgwwb4xMT47LRcE4ZTy7ycSavDwONjXR3N9PZyhEmiNRsuwOh6np6cEA5qenjyvOKQoCK3NyyHA4qIlGOdbayj0LFw576l2OfIeXuK7RFPSjGjomIWEKPdeTxoGOeuoGeih2JQyaDcOgPx4lqqnE9enzdZNF0oFTR7SJI31vA6AbGv1qL7qhcWfOI1ckcBrKVkwKAWwOK3lzs9hw+0pueGgDVsfs6UmNhdXbFrFgZTH/8uEfj5AQfu03BxBFkc9++wEGeoM8/p1XyClOZ/G60b5AyWLfnmq+92+vDHfHmEwJPlMyqzBRSmyj6CqaoWERzfQrASLa2PpFTpMDhzQ+sTwZWB1W7vzMDs7uP0fZmrmYrDKLr19AdsnsBmjXGkRBTKot3j6UvjYgrCTX8WSboUZRdyTM76sqeLamkjp/L+pl2UqzKGGRZSyD3IGpwiKN7XKfLARBYJ4vlWWZ2bx2oYYTnW3U+nuHy566YVDR1UFjoB8B2JBbQKrNPu3fqabpPPXoXl548iDBgbFJ1LpuEIsqvPnicVoauvnY327H6bZBS19S52ht7OH733iBypOTd2oauoGGwYA/zGvPHKWprotP/q9bmLswZ9wxqorGv33pKdqaJnZX0LREBnwiKPHJv/Payja+889P0948+fh13QDdoLcrwO9/sYe6qjY+/aXbSc/yTPqdZbk+gc00l4HoPvrCr9IXeR27aR4uy3o81k04rSsT7f2zqNUvCg4clnW093+HYGw/mu7HZd3EVP0ANGMASfRgEjMQBBO6oeAPv4rB5HyzHPfUFx8Nfv/wGvrRY8d49NjkSuqarhNWxi4bpjkc4wZugiCQ43YP348doRBDtsbBeJzeSMKKyGez4bSM//xNdziG58DWQABlgsrJktRsJEHgTG87/fEoadZEoLYyLY9fVB3i51WHKPWkUehMoSsaYmdTNUElTrZ98m7gmSLpGbnQUUa2bcgo0CCqhTnY8xraJLXb6WL51kX85NA3Jt1OlERMZhmLzYwrxYHJMvurkrFw+QQQjymcO9HAbR/dRHpOCp5UJ1kFqTTVdrBozZykVltj4Y1XThGNxFm6opD7P7iBnDxf4lhJHC5lUGV8f/cxTvqr+OzcD/H75lc5F6gfYSQ8BFmQ2JF5Hdelrxzz78nAMAxkk0zpimJKliQ6S0AgNBDG6fnT7YAyjMTDbzIMTxQCSXOCZhLIBuIxvnVwNy/WVhHXNNxmCyuzctmUX8ScFB8ZdgcWSUYUBA63tfC5t1+Z8jlm4xHmtVi5sXAOe5rq8ceivFp3jjXZeciCQEiJs6vpAlFVJd3uYENuwbA7+1ShaTqvP3uUZx/fP7wYkSQRj8/BklXF5BSkYugGLY3dnDvTQnfHAJUnG/nB/35xTO/H8ZCZm4LNlniACKKAzW7G6bKRne+juDQTl9eOpum0NfVQfbqZzlY/qprQzTl7opHHfvgmX/j2/Tic42c9LBYTKWkj9fOUuDoiGLTazdjsE/MX3V77pN9h4ZyM4TlBHCwxOl1WCuZkkFeUitNtJxZVaGnopupUE73dAXTNQFV1Dr9zjid/tptP/+PtSNLEZ3KYl2I3LyLD+SGiygV6ws8zEH2HruBv6A49hUUuINVxNx7r9ZikjBH6S9OFIAg4reuQAx66B36Bw7IGWRopxBqJnyEcO4GitRNXm9D0IJ0DP0ESPbisGzFJebism+gLPU9L35exmOYSVxsBBZM0uZiuzTS5Yv/lCMQvLryynM4RnKLx4LPZxg3QTKI44TXYLzl+9JLgS9V1YqqKQGIRNVHWTBbFiy4D8fiESuBrMgrIsDmp9nfSFQmSOqgGXu7LYklqDoe7mvjQW7/BZ7Hjj0VojwQwixLbcqefqEgWSQdOJtE8QjXcKtlxyG76lan7ySUDu8tK4YKJ+R9DuFZ0XERJJBZJ/KAMAxRFw2ozMZPL01Qds8XEXfevYdW6hIjkVMe72reYxd6E1lZYjfC5+R/Dc5lgqQHUhRp5oeUt1qctm3bgFA3FeO77r1D5bg3GJZYmq29exh1/tWNax/xjgKLrSWWQ+gZXZgK8J6bCu5vqeebcWXTDIN/l5ssbb2BzftGIoG2oW6W278rcy8lAEARuLJrDj08c4ry/l1fqzvGZlevJsDvoCAXZ19wAQKnXx8rM3Gnd84ZhUF/TzvO/PngxaJJFtt2ylPs/vom8opHli76eIM89foCXfvcuF851TOlcNruZ2x9ay0B/mLIl+azcUMqi5YW4PKO5hH09QX77sz289uwRopEEb+PovhqqK5pZsX7sh4DJLPOvP/7I8D02VP47ur+W//vV54a3e989q7jj4XXIsjRKQmXotdkij3IiuBwuj407H17H2384SfnKIlZtnMu8RbnYxsjutzT08NgP3mT/22dR4ony5N7XT3PHQ+soKp0485zg85gQpVRk0YfTshJN76c/uptA9AAh5TTN/m/SKnwXj20rbuv1OM3LscgFM3oOmKQcUl0fIhI/jdd+B6IwUmMtrrYSUc5goOO0JfSjYuoFREzYTGWY5XwcltUUpP47gehedCOM27YFt+0G/OGXMckTl5anc+WOwUBGFAT+eetWdpTOLGCIqhOrcocuCdQuDdJMoohFljGAmKZNyI1UdJ34YFbbPo6EyhCcJgufW7oZSRApdCXoCoIgkO1w88mF6/nW8TdpDPppCfUPbm/mvpKlbMwqHveYs4WkA6fuWBvN4drh1xE9xIXQWfLtc6/IhV0rwdDlMIwEn0qJqwnip6KhqRoms8yKzQvY/fxRMvJS6OscoKulj8KHN8xoLJtvXMjpU41cON/J6vWlmEwXJ8Bkj2uXbdhJTNhm0YxdsmKTRz+0i+y56OjJUqjGhL9rgHNH6rj7s7eM8K4bT1X8TwVRVaEnEp6wE20gHqM7kuA1iYJAgWtiGYHZwBv1tcOruttKy9haUDwuGbM/dnW1f7wWKzuKS/nh8UP0RaPsaqzj/fPLh7WbBAS2FpTgnqAUMBFURWP/m5U013cPv7d4ZREf+587SEkd7XyQkurkob/YjKpqvPCbg1PKOAmCwIr1peQWppKVm4J5gkx44jxb6O0OsPf100Ci3HXsQO24gZMgCKRd1nBhGAYe78gHvt1pIT3LgyzPXCbmhtuXseq6eWTmeic8Xm5hKh/965vobPcPlyqjEYXTxxomDZwuxdB9JIkefPbb8dq24Y+8RVfw1wRjx+kJPYs//DpWUwk+++2kOu5BFqdnfisIAqnOh8f9u8d+Ex77TZMcw4TTuh6ndf2I99NdH5/y9SSDPE+CImMYBnW9vYPXMP1nTWcoNG4GaEhk0zAMBBKinENwmM2k2u1c6OujLxIhGIvhto69KOwOJXwsIZElm6iZRgBuL1w0WoJFENmWM4dUq503mmtoDfXjtdhYl1HIxqwi5Gku+qeCpAOnfqWH2mDF8GuTaGatbzuF9quvGv5eIhyI8vRP3qK2ogmTReanX3mG4oW5fPQLt3PT/WsRBXjy/76G3Wnl/s/cSPHCmckz3HDzYqIRhReePkxjfTcrVpeQme1JSrMpryAVl3vkCvfBgltxyGMrViuGRokjn4kTthPD0A08aW5KlxXh8l0dG56rAW2QhzMQj42ZSTKAQ23Nw+n1LIeLXNeV7zRsCSY01gRgaXr2uEGTquscaJm8i/VK4665C3mysoLeaIRX6s6xo3guL59PSFl4LBZuLx0tIpgsAgMR9r15dpjzY7ObeegTW/D6xg7qBUHAajNzy/tXc/JQHeer2qZ0PovVREHJ5O30giDgSbGzaUc5xw+eJziQyErWVrZO6XxXEoIg4HTbEjyvJLbNykth047FnDvTgqbqiU682qll7RI2IhHiWiuB6EF6ws8RiVchCnYclsV4rFtQtG4CsXdp6f93+qN7KPJ9E4ucXKXijx15bjdzfD7O9/ayu76eBxcvxmefvrltVyhETU8Py7JHS59EVJXDzc0YQL7HQ/olgVO6w0FZWhrHWlup7u7mQl8fS7JGK/rrhsGJtjY6QyFkUWRpVtao7rtLMV43IYBZklmVlsey1JxEhgsBaQJLmtlG0oHTHGc5c5zvnXmuPtgpJ4rCjFv6ZxMOt40Pf/7WMf9mMsvc/IGN3PyBjbN2PlEQcbosWG1mdu08w66dZ4BBqYNJeFNf+td7WX/dyK66FPP4D2uv2cVDBbdN+RpVRaNib2WiWykQIdQf4vkfvsa8VSXIg3INabk+Csr+tCe0A61NVPZ0sTY7b9Sk4Y9GeOl89TAxc0dx6YSrrdmCQ06U1w0Svnfj4WRXO280nL/i1zMRhvzrNucX8WxNJQ39fl67UEPjQCIVv6WgmFTb9GUz2pp6aKzrHH5dtiSfgpKMCRcggiCQW5DKvPJc6qrbRnWQzRYEQaCgOAOH0zIcOIUC0cQceA3Nf8lCEATmLcxFkkS0Qe5WKBhD142k+J6qPkAw+i7+6C4CsUNElfOYpWx89tvx2LbitKxCFlNAgJhST0fgUbpDv6c7+CS53s+9ByO8+vBYrdwybx4/OnSIys5OfnniBH+xahV2s3lUwGEYBp2hEFZZxjNONkjTdZ44eZISn29EVlfTdd6uq6N6sIPv+sLCEXIGVlnmptJSXq6upsHv53enTzMvLW1EOc8wDDqCQZ4+c4b+aJQSn481E9i3JANBEDBdJcHtCQMnY1DrRUDAwEA3xmbAi4KAQPLmfcng5O6z/OQLv+b6u9fwgS/cOen2um5w4KWjPPuD17ntE9vYct+6WbuWq4k9b53lR999nXAohtVmwmRKZJqS+aiHfpR7u45wqPcUkDCwjOsKsiAPGiZqSILIX855CJfJMa1iuxpXeP77r6APtibHwjGOv1lB1aGa4Uly1Y5lMw6cEr9H0AydSzUZhjSHxlPGnux4Q7/zIeiGjqbrw6uXZI4pkAiOvrbvLb68cRsLUjMwDRpmhpU4Pz15mJ0XatExKHR7ed97pHq9IiuHXU0XAHju3Fk25haQ5XAhDXbHRDWVQ23N/MfhfQzEE0aaExE2rzScJjNbCkp4s6GOznCI52oqCcTj2GSZ7UVzMc3ArPbcmdZEx9cgShfk4ByDc3Q5BEFg8cpiXn/22KQdajOBy2MbwTXSNB1V1TH/EQZOAN5U54ggSVW0wcXw+N9hXG2nJ/wcfeHXian16EYci5xHfso/4bFswixnjyKEW+QiMl2PEFYq6Y/uJZf/HoGTSRS5b9EiTra18U5jI48ePUpFRwe3z59PcUoKJkmiPxqlwe/ncHMzZ7u6+PLWrawvGNuSxCrL7KytRdF1HigvZ47PR0zTeOP8ef7r2DH6IhGKvF5umz9/VKZoTV4e7y8v5xfHjvFsZeKevb+8nNLUVDRdp7Kzk18cO8bR1lZsJhMPL1kyofjltY4JA6cBtZeawEnKPevoirVwtv/wmNtZJQclzkXk2IpnzXIlNBDhwplmFqxNjkMlCKDEVM4eqiWnJPNPJnDa+cpJwqEYi5cVcs+DaymZm4nDYUlq1WaxJiL+IkcuZjHx/8ZwKzXBBpZ6y3DINuqCTUS1GNIM6sIWu4UvP/X3E280zRjhXG83DQN+YqpKVFMJKQp90QjxwQdYRFV4tOIoXosVh9mMVZIxSxK5Lg+L0kaXSbrCIc50dxJS4sQ1jbASJ6goNAwkRNMM4IWaKqp7unGYzNjkxPE8FiursnLH7UjJdbpZm5PHH+rO8dE/PE1ZajoFLi+KrnGmu3P4+G6zhU8sXX8QhNcAACAASURBVEV5WuZ7wuO7e+4Cnjl3lvr+Po60t/CRl59mQ24BPpuNYDzOme5OTnS2YZdNPLxgCftaGjnvv7ok8fU5+czzpXG0vYVDbc2ous7qrFwWp89MRfrSUpvZIpOZm4IsJ/e7zy9ORxAFuIISMeJlwpcJn+yrF8TOFJIsMvLGn3w09b1fYCD6DmY5F491Cz77rbis64bJ2mPdM4IgIEteTGIqca1l1q7/WocgCOS63Xztxhv51p49vNPQwO4LF9h94cJln3oCNnliesfWkhJcFgsvV1fzUlXVCL9JSOg8/fX69azKHd2cYZYkPrVuHZph8OzZs7xcXc0fqqtHHEMAMp1OPrB0KR9ctmxaTgPXCiYMnHRDJ6ZHMTBoiVwgpAXIGZYkuIiQ2s873S9xc9bDpJivtET+2BAEAYvNjNlqoqv52jEenikkUcJiMXHbPStZf/28aT1s8+3Z5NsTdeuzA+e5PWcbiz2JEt4Sz3wea3iemB4fJpCPh/GMjQUhOXmE6eDp6jP8uvIkUVUdU/Mjoqr8x5H9w69Ng+2ut86Zz/+35eZR25/sbOdf3nmD7kgYRRtbQOC3VRe5fJIgYJYkij0+nrj9/aSMo7Be4k3hC+s2U+D28v9OHuF4RxvHO0ZyYtJsdj61fC33zFs0I8HIqSDH6eaL6zbxb+/u5by/l4YB/3AQd3EbF59ctoYbC+fQHBi4qoETQLrdweb8Io51tKLqOpIgsDIrhyyna0bBZm9XYPj/FqsJjzf5VvbUdNe0umOH7hnDMAgFYrQ0dNPa1EOgP0JwIEI0ohCPqcRjCuFgbMQ1XosYHo9uMNAfprGui85WP4GBxHhi0aHxqAT6w1P2zLOaSnFZ1+OyrMFuKkMQJhaVHYKAgM00D6upZFrjuloQLvk3rf0FgTy3m69u28a+xkZ219dzoq2N7lCIuKbhNJvJcbtZmpXFypwcFqSnj3usiKryT1u2sDw7m5eqqznd0UFEUUh3OFiTl8dt8+ezsbBw3PKay2zms+vWsS4/nxeqqjjZ1kZXKIQkimQ6nazLz2d7aSmrcnL+qIMmmCRw8prSWJe6AxEREYEy13IWuFeN2i6ux9jZ8VuCav9VC5wAEAQEBEKByNW7hlnGXfev5kJdB82NPQQDUZyu5CaS8SAKAvWhFnKsGUiCRFu0E388ucm6O95BQOmn0FGKxHvz4PdYrRS6U6a88vZZxyZJWmWZPJeHFOvUuDJZDucY3R0C+W4P5WkZbCkoId3u4K+Wr+GGojm8fqGGk53tBOJxvFYrq7NyubGolCKPd9JykygIlKb4MEkiAsKMJhlJFLmxcA5LM7J4+Xw1h9pa6AgFEQTIsDtYlZXL9qK55LrcCMCq7Fw6wkFyna4JJ/MMu2M4o5cyzmc9XQiCwB1zF/CDYweJahpui3XGZTqA4CXzgixLWGzJa77ZHOYp33e6rtPZ1s/po/Xseb2C6tMtKDEVVdUSbgeDliwGwKC10rWKITup9pY+jh2oZc9rFTRe6EKJqWiaPqgibgxbRA3Z+UwVeZ7PIQgmBGFqoq+i4CTb/ampn/AqQhIEnnzwQTRdH9Y2mg4EQSDN4eD2sjK2l5YSHzLAHezwHdJOMk2isRRTFDxWK/csXMgt8+YR1xLWYpIoYpESIrmT3QMui4WtxcWsz88fvg5hcKyWwez95ccwDIOIpiAgYJUuniMQjxGfgfm8KIhYJXlYp242MeGvUxCE4QdkprUAi2RDGKOkIwwGLLOp5jpVaJpOe30X0VAUm+PK6+O8V5i3MId7H1zHqy+eoLmhh8KSdNweOxaLjCiKE66Cy5cVkH5Zy/KW9LU81fwqFf5qREFEMzSWeOeP22l3Kc70H+NQ7x7+dt5XZ60kOxk+tXwtn1q+dtaOd11eIdflzY73m91k5kvrt4x4zyzJlKdlUp42faV0syTxw+13zPDqLkISRbIcLj6+ZBUfXzJ64XMpkvm8JVHkw+XL+XB58l5eU0V3OMwQHWl+ShqL02euPB+PXpyEBVGYUou+KIrIskQ8ltxErigq+944y7OP7aOmsg19DG6UKApY7WbMFhmz2YQoCnR3DKCqV94yYqqIx1T+8NRhXnnqME0XukfZxkCiNGezWwbHk3i0dLb5pxQQiuL0yP8J3ucf17wvCALecYja04EoCNhMpqSEMMfC0NckiSIOs5npCsgIU7yO8wM9PFl7HEEQeKh0OSXuhIXZL88d5nj39DtLTaJIutXJktRsbs4vw2WePUeRpMP6fHsp4yUUZcHEutQdOOXp69JoqkYsEh/+9mKRRNu2qqiEBybOIKmqxtl3a3jpZ2+i6wbF5ZMrtY6HYDjGz188yL1bl5KXMXOdndN1bew+dp5P33fdtPb//v95hdqqdnp6AjRc6EIUBUwmGUkeCprGj5y+8JW7RgVOBfZs/kfxvfTF+9EMHYdkI82SMsLDbjxEtQip5gxMwsRKxH/GnzET6IbBS+erUPSEoe8dcxfMSmrfbLnMkHuKRO9kn/+qorHz+eM89sM36esOAolAzemyMndRLktXl5BXlIY31ZG4lyURSRLp7wvxnX9+hs62K29SOhVEo3GeevQdnvnVPsKhhF2TKIm4PTbKVxaxcFkBuQWpuL12ZJOEJImIkkhHSx/f+Psnkw42/4z/njjc1cTjNQm7mFJ32nDgVNHbztuttYNPuOkkZRLZ3OcbzBzvbuHzy7bgNc/MUmwISQdO4gQZBkEQ8ZlntiI8tbeKf/+rnxMNJ27Modr42787yMGXj0+4bzyqEI/G0XUDb7qbGx/aMO3r0HSdC629RGKzYyUTCMeob5s+Z8RkkvF47aOE7ZKBfQyrBUEQ8Jk9+MxT9xdMs2RyIVSDaih/UsGTpscIqi1E1U5UI4oxTvcoQJp1GVbZN+I9wzBQjTBhtZ2Y1ouqhzEwkAQzZtGNXc7GIvnG0DVR8ceqiGp9pFmXIAlW+uJVxLUBLJIHj3kesmhBMxQG4ueJqF3Iog23qWTM4116PWG1nYjagaIHMNCRBCs2OROHKQfpGv/uzvf1sK+5AQMo9qSwOb9oVo57qX2JpurEosnf4/GYkpQApmEYnK9q4zc/3TUcNMkmic03L+aBj28itzBtRFfspd9hZ5t/UgXv9xq6bnBozzle+M3B4aDJZjdz2wNruO2BdaRluhNlkDHGM9Uu18vROODnbE8nCwYbLa5VUeQ/Y2YodvlYmZ6X+L975Nxqk0xsyCokyzZ1zTvV0GkM+qnobeXZ+tMUOFP4+II1syJhMDP30EEIzJwcnFWUzrpbl1Oxr5qm6tbhSUqJKShJBjHZxRnc/3e3UrQoL6ntx0o3GxP8/VKbgmTfn+h8yUwEj3z6hikpFl+K6QRbE2G+awm1wUoO9uxite86LOOk1f9YJjjDMIioHdQO/JaO8LuE1NbBoGf8z3tT9g+wyhc7NuNagPbwPlpDewgo9YTVDhQ9COhIggWL5MNlLqbEdTfZjo0IXKzha0aUc/1P0B4+wJqMrxJSWjnX/zhRtRernMpcz4OUuO+jIfAS5/p/TVhpRRYdZNjWsDzt8+MEcEGagjtpDLxGUGkgpvdjGBqyaMdpyifDtppS9/3Y5Pemq2+qiGkqf6g7R8OAH0kQuLl4LmkzMPS9FJf6usWiCgH/xErvl2LAHybZmtO+N8/Q1d4//HrVxrk88nc3j6lOfilURRthU3QtIB5T2PfGmcT4B3HjHcv5wF9uw2qbOABPxjx4IuxqquNf9r/JlzfcwIcXLmNmVtKJRfFAPIbLbPmjJSeruk4gHsNttsxIA+lawur0fL619lYEINs+MkDyWqw8UraWtZlTp1cYhkFvLMwvqg7z08qD7G47zz0li8mwzVyYeVYCp9lAVlE6j3z9fqLhOL3tfl762Vu89PO3KFs1h+vunJiXYTLLZBSkMW95Ed4MN1IS3AVd1zlS1czzeyrwByNkpbh4aMdK0rwOYorK83tO09zpx2qWeWj7CpaU5hBXVF7ad5Z9J+sQRZHNy+dw45p5WEwynX1Bnt9zmtPn2xAE2LpyLnduuigYahgGDe19/PIPh7jz+sUsnZucorhvksn2vURbtBFVj/Nq+9O81fkSXlPqKK7TR4o+i8s09WzW1UBcH+Bw11fpihxDFu34LOW4zEWoeoje6GkCSiMGKk5TAXmObbhMxXjMIwVFw2or1f5f0R+vQRYdmEQHFsmLgIBqxIhpfYTCLfhjVSw1/o58501cvsrQjBgXBl4gpLYgCRbMkpuw2sE5/6/RDIXzA79HRMYmZxJR22kOvUGKpYyylI9cNp5+Knr+k8bg6xjoWEQvdjkbARHNiDIQr8MfO0dX5AhrM7+BQx4t1PleYughkOBGJjSldtaf5xcVR4lpGgtS07m9tGxGxNlLUTI/i7dePgkkAqfOtn50TU9qvmiq705K38owEn5xQ3A4rWy7dem46uSXItAfQVGurbJWPKZy+mj98GtvqpOb7lwxLHUyEfp6AiN0s642Dne08P3jB/jXjTdR5EmZfIdrEAdaG/lZxRG+ft2N74ll03sBSRTJd449FlkQsUjTC1MEQSDV6uCRBWv5/fkTnOvvIhCP/mkFToIgYLFbsNgteNJcbLxjJW///iAliwt4/9/eMuvna2jv46fP7ueD71vFopIsguEYaV4Hmm7Q7Q+xsiyfD9y8kjcPn+OZXacon5PNwTMNHK9u5m8e3Iyq6fzgqb2kuO2sKsvntzuPE1VUPv/BrQnS9iXnEkWB6oZOnnzjONvXzmdJac60H1iqojEwECESjiGKIhlZHqT3SCAvrIYQBJGF7mXjbjNRSfdaQ33gRboiR5FEK0tS/4Zi1+0IgoSBQVhp51j3N2kP7wN0Sj0PYJNHd4y6zMXkODaTbltBmnU5Xst87HIWAhJRrZuW0C4q+35GVOumPvA8WfYNmCXXiGPoRpzu6DEWpHyCEve9+OPVvNvxRcJqO5V9PyffuZ3Fvk8jCDKHO79CW3gPreHdzPd+aLhZwzB0avy/4ULgecyih/neD5Pr2IrDlAsIRNVumkKvcc7/a3pjZznd8wOWp38Bi3T1Jt/OcJBvv7uXiKKgGTrNgQFq+3rQDAOnycwnlq5mQWr6rAV3cxfljsgO11S2EBiI4E3CGqjqZFNSQYChG/R2X+xSdafYSc/yTDoGwzCor+0gFJiZX+DlKuO6Nr3utiGoqoa/LzT8OiPbgzsJGQfDMKg61YymXTtE9wOtjXSGQ6gTlOKvdbzTUk93JIR2DQWkVxKJjr6ZhSkuk4Vch4fTfe1jStpMB9dM4HQ53KkufJlXLnNx9kIHGT4nm5bNQRQF0r2JydMfjJDqsbOuvJDsVDdlhZkcrWoGA45VN1Pd2Ml3n9ydmOja+mjt7iccy6S+vZcP7FhJXsboWrw/EOEnz+1nx7oy1i0qSkq88lIYhkE8rvLOrireebuK7q4B4nEVX6qTL371btyeRElO03S6OgYIh2Kkprtwe2aHCDeEcs9KFriXTriNWZxe58KQKr2A8J5kQVQ9TFfkCAYaqZbF5Ng3IQwGfQICDlM2Je57aA8fIKi00B+vGzNwkgQzcz0PI4mWUdwhm5xOifsu+uO11A08RW/sLJoRBVyjjpMIwDYhixZSLeWkWBYSVtvRDYV53oexyqkYhk6O43rawnuIqj0oehCzlEht98draQi+DIjM8dzPXO/DI67Hbsqk1P0AcW2Aav9jdEaO0Bs9TZZ941XLOsVUjeMdrcOWKpDoDEq12fnk0tXcWjI93bLxkFeYRk6hj5b6hM5b1ckmWhp68KQ4JuSL9feGOH2sPrkymsCo7uLJ9jIMg0B/hOPvnicaiU+y9cSw2c0MJvAAGOgPzyjrM51uacMw6Gzzc/JwXSJwS2J7zTBQ9YQjgCgIyONITwxJN2iGgabrwzIlgiAgCwmvsqHv0hh0FNAMg2A8xsmuNlRdJ6apRNSL9A+TKI0o3V26n36Je4Y02No/1m9laAyaoV80YUdAFAUkQRzTd80wDBRdH8xkGpOOYSAe42RXO5phTDqGqeDLW7cSiMfxWK3viQ3UVDCTjNOl0AxjBBdvprhmAydfpoey1XPwZV2p4MkYd0Kwmk1YBj3WRFEYtuZQVZ3Ny0t5/w0XgwenzUJc0SYkQgYjMcoKM9h/qp41CwvxuZPnHhmGQVtLH7/40Vsc2HsO5RK+UygYQ1P1Edu+9OwRXnj6CLfcsYKPf/oGTLNINpVFGfkK/WSO+ysAgRXexVfk+JcjrgeI64kHttOUhzwGX8trnjdoN6QTVsZvi708g3QpRMFEiqUMEFD0AJoRG3M7u5yJRUpwlgRBxGVK1PQdphxs0lDAJiRI4UgYqCh6CLPkTjiXh/cQVbtwmvLItW9CZHQpRRTMpNtWUB94gajWQ1+skkz7OoSrNA14rVbun7+Yqt4uQoqCTZZZmJbBjuJSSjy+WddecXnsbNi6kKd/+Q66bhAMRHny/+3m779xL56UsUtpqqKx84Xj1FYmZ/ArCAKZOd7hrJO/N0hrYw9li/PHXTApisabL53gwFuVM9ZysjuteLwO+gezRGeO1RMMRPBZxv+NTgTJJJKW6aa9pQ+A9uY+ejoHyMwZn6wdCkZ57okDVFU0T3p8wzCoH/DzX6eP8mbjeQJKnFJvKu+fVz4YSI2Eqmvsaa7nzYbzHGpvpiMUQBQFitwpbMufw/1li8l2JMZqAC+er+J35yqo7u2mLxrBwODu5564SM5H4HOrruMTS1YPn6M5OMDLddXsbqrjvL+XkBrHY7GxPCObh8uWsiord8TD3DAMGgJ+flN1it2NdbSGAhgkBG+Xpmfz/vnlrMsuQLrk8wrGY+xvbeTXVSc5091JXNMo8ni5uWge98xdRKbDOTyGp2vO8EzNGc71JcYAcMezjw2PQRQEvrhmCx9eND15kKVjmPpeC8i0OdENY9hvc7owMPDHIzhkC/IMHDIuxazNmEPBxUw7KYbgSXPxwS/ehXSFukzKijJ5ZlcF+05dYEFRJsFIDLfDOu7kJgAry/J4ZtcpevvDpHoc9AwkVFEdNjN5GSm8faSGTJ8TSRSJxlQKsxN19Jw0D395z0Yef/UIj796hI/dthanPbnMTCyq8NjP97BvdzWiKLCgPJe0dBfv7Koata0sS8xbkIMkidRUt9HTHSAre3ZLMYah0xVrpyF8nrgeY56rnDRzJnE9Nmi6OHWhQIDWSDs+83tXNhKREQY1ynRDGVNgMxHkJN4XxYk5HbqhEVbbGIjXEVE7UfQQmhFFM+L4Y9XDxzGMsUsXsmBHFi7+JqTB/1uklIuZsGFPSJHEOlgdvM4IwXgDOiqqHqJm4LeYxbEflBG1G1VPTL5hrRPdUBGnKDY4W0ix2vjMyvfOGslklth440L2v11JS33CsPT4wVr+63tvcN9HryMnf2SnYigYZefzx3j28f1JZ4IEAZasLqbyVBMAkVCc1589xqJlhWTnjybz93UH2fnCMZ7+5b4pdfmNfW4Bj89OQUk6FUcTgVPD+S5e+PVB7vvodTjdU9dIMptlypbkDwdOA/4wLz75LgXF6bguaz4xDIOOFj/PPbGfV585klRTS3NwgK8ffIv9LY2sysqlzJdOTyTMT04dIsM2OpiNqSr/dfoo5/29rMjMYWt+MVFN41B7E/95fD/t4QBf33hTIjMEpNntbM4vZmVmLs/WnCGiqtw7bxGptkELF2B11shmoqMdLfz01CFKvancVFSK3WSmacDPrqY6znR38J3Nt7Ai8yLdoi0U4H8f3MW+1kbWZ+dzfV4RmmHQHOjnSHszpV4f67LyGYp0YprKb6pO8aOT75Jld7GjaC6SKHC6u4P/OLaPWn8PX1q7BZ/NnrApsTvYWlDCqsxcnqo5jW4Y3DN30bCIr4DA8ozkOLN/TPh42VoUXRtXzDhZ9EbD+GMRch0erNL0NK4ux6zNmE+/dZIuf5BP3r1xlChjbXM3T7xyhM/cfz2pnuRktSRZIqtofHn4maIo28cn7lzH83tO8+Qbx8hJ8/DQTStI8zpIcdsxDRJGzbJEitsOAmxcUkwoGufnL75LNK5SmpfG+7ctxee28+BNy3l+TwXf+tWbSJLItlVzKcxOwWKSSXHZsFlMPHDjcn72wkH2nqxj+5r5SXGTTp9qYs+bZ7HZTHzm87ewfFURiqKxb0/1mNuXlGZis5lpb/XT2x2c1cBJMzQO9+5lZ/tzqIaKgYFL9uAzp3Og52164p3clv0AFmnqom55tmxaIx2EtcigplTiRyQLEuJlqwTDMAiqcUJKHAMDiyTjNlmRLuOWTQSz5MFpyqM7eoK+WDVRtQvZVHCJt5JKe3g/BgYiZrzm+eN8JnH6omeo8v8Kf6wa1YgAOheNFAx0Y/IHoijIcOk4BweSKLddOqrRI1T1CLHB7FlU66Eh8NKY242EgKZHB6/1vwcEQWDughxuff9qfvm9N4hFFVRV5/XnjnJ0Xw1L1xSTU5CKgEB7ax/VFc20NfUQi6osWJoPBsMB0US4fns5b718criz7vSxer7yN49z3U3llMzLxGwxMeAPc+5MC8cP1NLe0oeqaCxbW4JhwMlDddMeY2qamzWb5lN9upl4TMUwDJ55bB/HD9ZSvrKY1HQXum4QCkbx9wbp7QpSMi+Lj3z2xjGPZ7GY2LS9nGMHaoc76/buPE1Hq591W8ooLM1AFAX8PSEqjtZz5ngDHa2JIGvjjQvpaOkbN1un6jp/qKtmT3M9d5Uu5B/XbsYhm1F0jQOtTfzjO6+P2sdmMvGv190EJBTrLZKEbhic6+vmn/e9wa6mC9T5e5nnS8g+bMwpZENOIZ3hIAdaG+mLRXj/vHLmeFOHj3n5nbKtoIQyXzrpNgc22YQkCkRVlcfPnuDfjuxlV/MFlmZkIw/OFdW93Rxqb+amwlK+suEGbLKcMDvXVILxOHaTaUQHXFVPF98/cZCVGTl8beONw0GcPxbl24f28Gp9DUvTs/ngwmWIgsCmvGKuzyumPRRgd/MFVF3ngfmLKXRfJLhfe/2xM0eha3YI/HFd5eG5yyl0+kixTE9g9XLMWuA0EIrSOxCG4bzTRei6TnVDJ+GoQuo10nAliSJrFxWydtHoNsd/+dj24f8vKsliUUlWQkVdFLl1w0Ju3bBwxPaCIJCV6uKTd28Y9f7yebksn5cLgMtu4X8+uHlK17lvVxWKonH3A2u4fusCTCaJYCA6bpkxPdONySzT0x0gFJwZ0fRyNIRq2dn+HIu9q5jnLOep5kcx0BERybBkcah3F3E9Nq3AyS7bOdR7jHPB86SYvcPjuylzMzm2rBHb1gf7+NHZ/bSHBzAAu2zm1oIF3JJfNi434nIISBS77qItvA9/vIrTvT+k2HUnFtmHbsTpjZ3lnP9xBEQKXDtwmkZLXOiGQmPgD1T0/oCY1oddziLLug63ZQ5WKRWT6EQSLHRGDlHT/yQTs13Ecb7TyadEA204k2WTM8m0rR2z9Hg5UiwLp2xt8ccOSZa4/cG1dHcM8OrTRwiHEuXuzjY/O58frRcnigLlKwv55OdvYe/O05MGToIgUDgngwcf2cwvv/8GA/4Ex6ihtpOG2rfG2QlWb5zHx/7nduprOmYUOImSwE13LqfmbCt7X6/AMBKdcdWnW6g+PbYBrm0MvbdLr235+jnc/uBafv/oXuIxFU3VqTzZSOXJxjF3kU0SW963hA99ahtvTFDmjGsarzXUIAsijyxeRYo1kWGxIHND4RyWVGfxZuP5keNDGO4muzQ7uCg1g3neVJoG+mkPB5jnSxveJrGEGemtOVEZ2GWyMD/FMuL4FklmR9Fc/u3IXhoDfjRDRyYRDMmiiCyK+GMRQkocjzmxr1WWcY+hVv1UzWk0XefDi5aT63QPn8cqydxZuoDX62s41N7EHaUL8FqsY44BJh7De43OYJBjbW0EojE8VivrCvJxWyyous7x1lYa/H7cVisrc3JItdtpDwS40OdnZW4OZkmirreXnnCY1Xl59EejnO3sxGO1UtnZhc9uY11+PjaTibCicLSlhfZAEIsssSInhzyPB0XTONXeQX1fH16blWXZ2fhsCY5vnsPLPyzbNqvjndGsOWz4yKDEiUHCJuHSQr0BsbhGTNGmZJJp6Any33QgQFItxkmZR162zXj7JPP+dEpYzY09mC0y8xbkJOXkbjbLmEwSSlyddeuGC6FzuExe3pd1HybRPCxFIAgCNsmBoito45SiJoNdsrE9c8uY71+O39WdoMDp5RNlazGJEpX+Dp66UMHm7Dl4zEkGToKAz7qYhSmfoLLvZzSH3qQ7ehyT6MYwFCJaD7qhkOvYSpn3o0jC6OuIaX6q/P9FTOvFbZ7DstTP4bOWIwsju44iamfyH8Q0IAqm4dKeQ85mYcojg910f8ZYkGWJh/9iCzn5Pp7+5T46WvtGEagFQcBklthy8xLu+x/XkVuYRktDD7Kc6LqcKFtsMstsu20pNruZx370Fh0tfQkC8GVxsyAIOFxWNt+8mHs/vJGcglRsdjMOp4VoVEFK4n6/HIIg4PU5+djfbsftsbHr1VOEArFxdOZAEMUJm1UEQcBmt3D3BzdgtZt57vED9HYHxiTKi6KA22vntgfWcst9q0lJc7JwWQFWmxlFUUd1/GmGTm1fDzlOF+k2x8hOZEFgUWrGqMBpaL+6/j4OtjbRGPAzEI8SUVVOdLYlCtiz0Dk1EI/xblsTlb1ddIaDhBUFfyyxEFUuU5wv86WzKjOX3c0X+Nu3X+KGglJuLZlPjsM1gugNiWfm8c42FF3nhyfe5YnKkyOO1R+LEtNUuiNhIqqC13Lt28iE4nF+efw4siiS4XByprOTFTnZYLHwTkMDv6s4zcqcHKq7uznW0spfrV3D+d5enj1bSXlmBmZJ4lhrGyfb21idl0dnKMTX397F9rmlpNrs6OHEdxpTVX51/DiVnV2stYiHJgAAIABJREFUyMnGH9XpjUTIdbs51NzM02fOsjQrk3M93RxvbeMv167BaZ4edWQyzChwUjWd/acu0Njex8maFgLhGL9+9ciIC1VUnYOn60n12LFbkid5Hd99lh//wxPTuq7Csly+9KtPT2vfaw2xmIpJljCbJzdYhITonKpqmMzylLy4koGix7FLDsyiZQQnKCG8qM6k65k8Ww55tuTq9IF4jPfllzHXkyjlukwWXm86N+bDYSIIiGTbr6c7eoK28Ds4TPmIyEiihSx5I1mOjWRYVyGOw9vyx6oJKk2AQIn7bjJsa8bcLqJd2cDJJDqxy9mAQEhtJ6J2YZenL3nxp46hgOV9963m+u3lHNp7jsqTjbQ396GqGm6vndIFOay6bi4FxWkgtRNTD7Piep1fvXEbFlMZkmzBbBmfL2GzW9hyyxKWry/l9NF6Th6+QEdrH7GIgtkq40tzUbogh5UbSsnI8Q7fq5k5KTy2838lDFpFcdjzbarIzPHyyX+4lbs+uIEj75zjfFUbfb0hlJiKzWHG5bGTlZtC0dxM5pdPLhjscFm550Mb2XzzYk4crOP08Xp6OwPEYypWu5m0TDdli1MpW66Rmb0QsylBbl6yuoRfv/UPYBhIsjRi8RfTNEKKwhyvbczsiXeMskpPNMx3jrzDa/U1pFhs+Kw2PFYrTpN5VkQtFU1jT0s933x3NwOxKBkOJykWG26LBas89neRZrPzzet38OiZo7x6oYYfnjjIT08d4vq8Ij6ycAWL0zIxDWqRRTWVgXiCO9kXjYzojBvCwtQMCt3eWSMyX2louk5/NEaJL4V1BflkOBw4zWY0XeeJEyd4cMkSthQX0xkK8bW33qaut3fSZ4VFlrl13nxKfIlynSgInO3sZG99A9/esZ1slwsDGPqEHj9xkvLMTMrS03FbrTx2/AT3Ly7HYTJde4GTQOJDq2vpoaG9j3AkzmsHR3JvJEkkL93DXVsW43EmHz2HByI0nB07tTwZrLbZM/O72khNc1FT1cZAfyQplePGhi6iEQWPx47DObufQ7olixP+d2mNNJJtu+gHqBoq1YFTeE0+zOL0OyDqQvWc8p+lzD2XEmcR7dFOMi1pWC8r/a1Oz+d350/SEQ5iFiUq+towSSKnelsxizKSILIqPRlxR50q/6M0B3dS+v+zd97xVZ33/X8/Z9w9JF3tPQEhENPsYRsb49hJvBLHdlK72cNJ2oxmtP21aZqmbdqkmU7aJs4e3jaeYDvGmGXA7CEQCCGhfSXdvc74/XGFkLgSCBCOSf3xy68Xes6zzrnnPM/3+Y7P13snDTmfQJUmntoyZZzm6xHYZN+Y4yX0AH2x3VwSmc55IAkVn72RE+G1xLQeumKbybHN+JNFy10JEEIgywJvtpPr3zWH6981dkSSaWqEojsIRp8gmTqKkOyUeX+Lco5IytOQJIlsn4vlq2ewfPWM89Y/PS+Hc+LfrWHGSRuw1AzttqrKlFbmUlqZO+H+zjUvWRbkF2ax+pa5rL5lbkadeHIfHX0fIaH9LRb15uE2492PLASSYFwNkTHGN/O7w3v5Q9M+VlfU8vFZC5mak4tNVjCBL7/6POtamzM7ugAcC/Tzre0bGUzE+JurVrCitJJ8hwtJCE4EBniu5UhGGyEE2TY7n52zhFtrG9jScZKXTh7jpdZj7Ozq4B+WXMOq8lokkaYmkIACh4uvLb2O6b6x/XgVIeFQ39qpkU7DbbVy39w5PN3UxA+3bqPE4+ajV12FQBCIJyjxeJAlCZfFgsOiEkwkMljPNUMftUTm2O1k2+2j6oUSaX8xr802qtw0TU4MDmJXFCLJdNTyorJSnJbL9/wuaWVVFJlr5tWxsKGC36/bRVvPAB+9ZcmoD1gSArtNxWW3XhB/UVFVHjd/ZNW41w3dIB6J03G8m86WXsKDEcqnFnPb/WuoX1BzKbf1lkLjnAo2v3qYra8dYcmKqbjcYwufpmkSiyZ56fn9BANRGudUkJc/uQ5l0zyzeGNgC79q/SFVzilEtDC7Brayo38TnfE2bii8FZt8cREQLZGTPHnqeUxMFEmm3FHC6/6dzM+eTZVrtB9aRzRI02AvbeFBJCGIaSkUSeaXR3YCYFdU5uaWjAr/HQtJI0B7eD0mJsWOlSjCNuEUHOlxCjjtAO6P76XYeTXS0AZmmgZJI0Rz4A8MJA5dzCO5IBQ5lpJtqac3voPmwEM4lVJKXdciCSti6FxmomOYKTQjSijVSo51Ooo0uWl5/vwg47LfiMO2nIHQ/xKOr/9TT2gYpqkzEPofLGodLtsNf+rpXDBUSSLf4aI7GiahZzKmd4aDo/7WDYP1rc34bA7umjaLWXmFw99qJJkknLq0qETTNGkJ9HN0oI8bq6ZyW13DKC1WbyxyjtZpv9kqbzaVnizWVNaxvrWZr2/9I48cOcDc/BJ8dgeqJFHmzmJXTwcJXcNrsV2kRuStQ4BpAqVeLx+dP5+ucJj/eG0TW9raWFVdTbbdzomBQWpycgjE40STKXLsdqKpFEldJ6HrWDWd1sHBUVaMkfkcT8NtsxJLpeiPxbCr6rCFQZEkKrK8LCwv453Tpg0rdByXyUwHk+AcLoTAabfSUFOIw2ah0Oe5YILHsVA9s5z7v/2B89YzDJOuE7088cA6XvrdZo7vP8nKOxZe8vhvFSy7ehprH9vOpg1NFBR5WbWmEbfbNvyK6YZJIBCl89QALz2/jxee3o2syKxYNZ3c/IvjbhkPDtnJ+8o/wss9T9MaacateumOd5Bl8fHO4ruY4Z17wWR5p9EUamZudiN22UZPohdFKBimQUSPZdT9eP1iPla/+Jz9TWQWAgVZ2IAg+wceoDS5CovsGRY0BHLaDKYW4VYrMsL2PZZqcqwN9Cf2c2Ioks1na0QSFhK6n1ORV+iLvYHPNovu2DYu52KnCCezc7/A6z1/TyDZzBt9/0JL6ElybbOxylmYpk5c9xNKtjCQOITHUsOigm++LTidB+kF3I4wLUjSWyf9EYBu9BFNbEGRM4lZrwSosszCwjIeaz7Alo6T3FLXMPzdDsRjbO0czQN1miRTEmJUGh7TNDno7+agv3vcsSyyjCpJJDSNQGL8oBltiJDSIsujDl5xTeOJ5oMZ9c0RczqtBRFCkGN3cF1FLf+54zX6R5jkhBDcVD2VTadaeezIAebmF+Md4cdkkiYD1g0zI9WQRU6TXIaSSULJsfng/hToj8Z46vAhElraj9nEpMzjRZIkPjB7Nr/bu5fm/n76IhGm5PqozM4mmEigSBI/27ETp0WlpX8An/Pca1FtTg4rq6r49mubmJ6fhwnMKy5mfkkJfzFnDr/ZvYeecBhVlnGqFm5tmI7rMmmdJk2X31hbTF1Z3gU5gJ8LE5UUZVlQUlPAB75yC92tfTz/i1dZfPNcZi2vn5yJ/ImRk+virvuW878/fJEnHt7Ojq3HyM3zYBgGwUCU73/rWVJJja7OAKfa+zENk6uvb2D5tfWTLm0LIXCrXm4qupOgNkhUCyMJCY+ahVN2X9J4khDDjuUmkDRSRPToEDXBaDx+Yj9Hg31nCoa0RPc3LMVxAWRpquRiStb7OTjwP/jje/DHRztqpgUnJw6liDLXauq870OSrMPCoSq5qc/+EHv83yGcOsnRwG85HnwUgYJuxpGESqX7XdR472DDqY+RMAYu/MFMEEIIvJZq5uV9labBX9ER2YA/vht/fHdmXSRsSi6SmBxOk/MhqbUSCP8Gj/N24oldxJI7EULBYVuJy7YKMTQP0zTRDT+h6JMkUocRwobTthyHbSWSsGKaJpH4H4klNpPt/gSKnA4p140gg+Ffosj5eBx3AIJk6jCh2HNkud5PLPE60cRmMHXstqW4bNcjSXYMI04suZVofBOa3ock2bFbr8Jpux5JjM8mfjEwzATByKNIwo5FrSUUfQbd6EFVKnA73o0qV4xIB6MTS+4kHHsB3RjEolTgcdyGIqfNz5ruJxx7nmhiM/HkbgwjRCS+EQCLUo3P+1f4g9/FqtThdtyEbgQYDKUjYH2evwYEoehjGGYMj/O9AMQS24jEXsYwg6hKJR7HHSjyGY2Org/SH/oBHuedGEaQUHQthhnCok7B63wfspSp3TZNE03vYCD8M1S5mCzXfcOcZJBmu15TVccr7cf50e5tqLJMY24h/niMR4/spzsaGtWfKstM9+XzZPNB1h47TJnbi0u1sLeviwd2b6MvFkUdJ6rWbbEOaXo6efTIARyKBY/FSjAZx2d3ku9wghAUON3kO1xs72pn46kTzMoroi8W5anmQ6xvbc4QZkxgQ3sLr3e2s6i4jEpPNlZFpjsS5pnjTYRSCaq92aP8tVaV17CouIx1rc3YFZU1VXUUOt1EtRRtwUEO9vewqqyGRcXlo8byWm2Uub0c7u/l0SMHsMoqTtVCKBknz+4k1zFxN4PJhNtqYV5xCR2hIALBsooKpublIoDF5WV4bVbaAkEaCwuYWVCA22rFabHwmcWLaOrrwyrL3FBXR3RIY1jgcvGR+fMyhB6ronDP7Fns7eqiLxLFpiiUZ6WJWBeUlpIzpN1CQLnXO65P2mRg0np22CzYrSrReJJEUhuTATfLbb9sedXc2S6WvmseO9bvZcMj2/5sBCdZlrjm+ga8XgcP/uSPnGrz09qSFhrisRRbNqZt7kIIcnwull87jbvuXY7rAvzJLhSKpJBjySXHcum+E6cx01vPo+1PkzI14nqC1kgbLtVFsa0wo26WxUbBUKLGmJZij7+DXJvzgrRdmhGlM7qJ1tCzADiV0rM4k0xMdJJGmECymfBAGwJBXdY9wyH8kpApdCzFa6nhROhp+uP7SRoBVMmNW62kxHUtPmvat6XYuZKBxCGkEWlQBBJOpZgsyzQcSsGo+dnkXLIs03CpZcMaMABVcpJlmYpF9iAxemERQibHOpMF+V+jP3GIruhmAslmkvrgsLDktdSSZ59HtrUeRbw52ibdGCAYfYRY4nUkyY6qVJNMtRCOfRXd8zm8zrsQQialt9Hl/2tMYljV6Wh6J90Df4fX+T58ns8AEkntGOHYS2S57gXSgpNpxonGX8Oi1g4JTqDpPYRiT6EZ3WjaKVSlAt0IkkwdQdjXAJBINdEf/BFCWFGVUjS9g56BfyTLeQSf94tMKjuOqRFP7iKR2g/IWNQaQCYQeYhw7AVK836DLLIBjcHwLxkM/xyLWocs5RKOvUQ4to78rG9gs8wCNBASipybFu7lIqxqmmdMkYsBgaa1o2kncdlvRNP7CEQfxTCjZLs/hiScBGNrsanTEQj6Qw8QiPwemzoTWfYRif2RcOwFCrK/gVVtRAiBYcYIxZ5FN4JoegeKUoqJSSyxkyzn2JYB3eiie+CrQJIs593A6LX/NEfRp2Yv4sH9O/nqxnXIQsKmKFR5s/nSVSv44qvPD9cXwCdmLaSpv5dnjjfxbEsTqiRjlRWWlZSztKQiI0rtNBQpTXlwwN/D08cP88zxw8iShCrJ/O2iq3lXTT0CmJlbwN31s/jNod3c/9JaFEnCIslk2+x86aoV/Org6IOIOeTkvfb44WFySjiTAmZRUTkfn7UQp3rmkJJrd/D1pdfzvTc2s6G9hXWtRzGGDn+nzZdLizNpchRJ4mONC2nq7+Px5oM80XwIWRJYZYV/WHItayqnZLR5M2BVFGYVFTKrKHOtliWJmYWFzCwcfU0SgsrsbCqzM7maPFYrC8vKMsoBHKrKojGuKZLEtLw8puVdPu7HUeNNVke6YbB57wle3n4Ef2DsJIT/8OEbyM+ZXPPRaQhJ4MlxY3VYaTsysfQIVwoUReaqxTVU1uSxY9sxmpu66O4MEI8nkSUJt8dOSVkO8xZWU99QisV6eSTtqBamO9FBqb0SVbJgmDpt0RMcjzThVbOY5m7EoVycOaPYXsSdZbeya3AvwVSYXGsOc7MbcauZ/V1bUjfq745IkP/a/ypJQ8c+RqqRs2GYKVqCT3Fg4MeokpNG36fJsy/AKnlH+AMZaGacYPI4hwd+Rm98Jx3R1yh1rcapnklRIAkZp1pCQ87Hzjnm/Py/zyhTJAczfZ9mpu/TGdeqPbdS7bk1ozzPPpdVpb8Yd5z0gu0g3z6PfPu8c87pXBhMBtnq30etq4xad/n5G5wHuhHAZvFRkP1vyJIP04zS3ncPkfgG3PabkCQng6GfY5iDFPt+gkWtSfNpBR8gEPktLvtqrOr08w80AslUC1a1gSLfD5ElL6ZpYJJEDAmvNks9BTn/gSqXIoSEYYTpGfxHgtHH8Xk/z9kb/WQgkTxEse/HOO1prrhQ9Al6Bv+BWHI3Lts1pPQO+kM/wet8Dz7PZxHCQkprp733HoLRh7CqU1HkArKcd5FIHiQSexmnfRUex3tH8w6pM4nE16Mbg2j6KVS5EE3vJplqwmppQNM6sNjfSTLVzGD4F2S7PkS2+8MIYUHTe+no+ygDoZ+Rn/11ZJHOh2gYAZKpIxRk/yuWIUHNNONIZ3GGCWQ0/SS9g/8CmORlfQ2LWs1YgqhNUfjLGfOYlVfIrp5OYppGicvN0pIKbLLKZ+YEmJVbOHwoqvZm86NV72Jzx0k6I2FsikyNN4dlpZX0RCPYFGUUMeRI1GX7+NF16bbd0RCykMix2UexbtsVlU/MWsisvEIO+ntJGTr5DicLCssocbmxyDImIA9FvElCYk3VFErdXo4M9DGYiKObBi7VSpUnm4XFZRlcTkIIarJy+LcVa3i9q42jA36CyQRWWSbf4WJmbgG1Iwg6R2K6L48fX3/LUMLiMIok4bM5aMzNFFrexuXDpO2wB4938cOHNyKAGbXF2CxKxmeiTnJ4/EiYpkkynkRLamipTEfD8aAbBsmUjm4YKLKEVU2H/SdSGoI05YJJmkFckWWESBN6Js5qA5DU9OE2BiYWRUGVx04KeaEQQpBf4OXGd84huVojEkmgazpCCCxWBYfTijxJY42HE5GjrO9+knsrP4NXzaYn0clDbT9lMNWPhGBl/o1cnXcjynnSk4yFpJHEZ81mdcE1w0lKQ1qYuJ7AJo9eeFKGPnyyAzAwCCbjo8rOPVaIltDjpIwwNZ73UOl+95hpRyx4sMt5BJJH8Sf2Edf7SBnhC763KxEDySDPdLzKjUXLJkVwkoQdp20lsnQ6+tCBVW0kkTqEYcYx9Ajx1B6s6kxkOR99KGLRZmkgEDGIJ3dfsOAE4HHcgjS08QshITijiRXCgioXY5rxIaHKRFXKMMwwJsZlYWNWlTIcthWIoY1XVauRpRw0rQuAWGIHYGKzzEtHzJlxhLBhtcwklngD04wB5yc3tVlmEoj8Ht3oI57YjVWdiSS5iKf2D5nVdCxKDdHEa0jCg8O2fFiglCUfbsdNDIT+F13vR5Y8w/3abYuxqHXD64wYg9/MNBP0DH4DwxigIOffsSiVnEt7JwnB/MJS5hdm0iJ8bv6yUX8LISjzZHGnJzMjQoUniw/PvCqjfGTbCk8WFWO0HQmLLHN1WTVXl1VnXHtnzWhLhiBtBlxcXM7i4gv7TmyKworSKlaUVk24jRCCKm82Vd7JYdU+H0zT5MT+k/zqnx7FV5LNR755Dxb7lRHtdzkxaYLT/mOdmKbJA19+7xDtQOaHcjlpZUIDEbY88wbJeIq80rGl9bOh6QYb9h1n3c4mEikNr9PGnStmU1+ez4+f2UIskSKaTNEfjDK7ppi7rp6DTVXYcriVF3Y0EUkkcdmt3LliFtPLC/j+k5vQdJ1wPEkwGqe60Md9188nyzU5NO+Q/nCsNhWr7c3xTxmJrng7JuBR0wvPpr4Xsco2/qryHzkS3s9rvetZmLMS9xj+DufD6/5dSEJikW8ewhS0xzp4pvNFritYQa1r9MLyh2O7OTSY5kYyMemPRylyeLBNMIu2YSQJJVsBgddSe55cbSaGmQDTQBbWP1letysdQliRpdG54NJmSwMwMYwwhjFIOHWIWPe2Mw1NEyGsXExqGFlyZ4w5omNSWifB6KPEElswzCSgk9I6ME2Ny+XIL8sFo9ja05QRMpD279O0dnS9l+6BLw4LMunpGihy0YRnpSqVgIam9xJP7cNpuwZZ9pJI7kWRchHCikWtIRh7CkmyI0sjN2KBIpeiGX2YxEeUWlCk/FF+SmNhIPxTkqlmPM7bUKTTkadv40rFpid38NoTr2Nz2rj+AyuZMi9ToPy/hknbBTTdoCQvC4/LhjQJRGShgQgdx7rOP65m4O8Y4PUX9rDpqZ0gYO61E+NMCUbjrN16gFuXzGBmVRHrdjbx6z++wTfuXYNhmPSHonzu9pVEYkn+64lXmV1dTFVhDi/sPMIN86fSUFHI8zsO8/sNu/mnD9yAbhj0DIb5/O0rSeo6//X4Ro51+ZlXe36CuSsBCSOBV/UiEET0ME3B/SzJXYXPmk+xVk7KTKKbE9f2jUSls5ynOp7DLttwK06e7lzHDG89JfbMzN3Tswvw2c44QrpUC/VZ+RMWnISQUGQnST1AIHkU07weOMPwa3KG5TmUOkFndDMGGk61BKt8eRMRjyTxPJtx+OzycxF+Xkid89WbHAjOZfoSQkFgwWm7hizn+8++iCqP9GsYPVfT1DHNsSKlJMbbtA0jwkD4vwnHXiDX83lUpRpJchGMPMxg5OKIdycCcR7znyQ5kOU8fJ7PYlFG06qkhc+JmcKFsCBLeWh6N5reiUWpxjALiMa3Ek/uRZGLkCQ3knBimhqmOTqJsWlGkIQNkEd2OqwpOxcsSi1u+00MRn6BVa3H67xnQu3exlsTlQ2leHPd+Ipz8BXnnL/B/wFMmuBUVeLjlZ3N+AMRcrNcl5xH5+DWo3zrY/99/oomaCmdeDSBJAlmr5zOkpszydnGgj8YRTdMGioLyXE7uGpqOc9sP0w4nl5EZlQWUpjtJunSyM9y0TUQIi/LxZZDJ2jt7seqKiRSGjaLimmmNWpzaksoyfUSTSTJctqITjDjeWAwOum55XJ8LmyTqFZ1yC6iWoSYHmH3wFZkSabe04gkJExMDPPiUx2U2Au5vfSd/Lr1YfzJAd5b9m5meKahjBFVN8dXwkAiRlcshG4a5NqceC32CZspFclJoX0JbeHnOR58HIBS53WoshtB2vSX1Afoje2kJfQkkdQpbHIuFa4bsVyENu1CENXj/PLEWnTT4FO1dw7fU3O4jZ+1PM6tJatY4JuBaZr0JPp5qXsb+wJHiekJnLKNWdnTWF2wmCxL2pdQM3XeGDjEyz3b6Ir5cSl2lufNZWX+VdiHTKC6qdMUOsGjbS/iTw5SbM+n0TtlFK/K5YYs56Oq1eh6N1bLdCThGY4yM834kNZJIEtudGMQ3QihDAl7mt5JUmvBapnYgQnSPlfx5D7sloW4HbcCEqYZQTeCcAnv8aXCZpmPaX4fIazYrQsQQh4Sak9rwUZomoUCqBhjmI+FsGBRa4gltgACi1qX5vEygsQSr+OwLQfAYV1IIPIHEqmDqEolQkiYJIjEN2JV68eMljsfnPZrcNvXAAb9of9Glny47DecV1P1Nt6aWHjTXH78xr8jKzLe3Mvjo3ylYdIEp9rSXHxZTr7xs3WsnFuLz+vMEJ7m15dht01sI08lNUL95yYcOw2r3UJpXSHzVs3gnR9ZhTt7YmGZsiTQDWM4p1s8qaV9loZ8sSKJtNBjkvZfUoYiAivys/nC7SspzTuTbFKIdBJGe0YaholtPo/8dgvPPPHGhOpOFF/6x1tYuKTu/BUniCrnFDb1vcjv2/6H9ugJ5mUvId9WjGmahLUgspCRLmBx7Ix1czA4mmm+2F5IKBWmI9aFP9HPnKyZ5FhH2/PbIgG+s3cDodQZBtqby+u5sax+QmkXFOFgatZfkDJCdEU3cXjwQZoGf4lFTjuHa0YMzUy/ewIJt1rFlKz3U+y8+rKfnA3TJJSKoJ2V808zNAaSQRJGWqiP6Ql+d/I5Tka6uLZgAVZJpS8xSFxPoI3Q+m3u282vW59mTnY9c7On0x3384eT6wilotxSei2qpNAcauMHR35HmaOQGwuXEdZivNzzOr2Jwct6ryMhSx6ynPfQPfBVege/hsO6HCHZ0XU/Ke0kPs/9COHCok5DCIn+0AO47TdimjGC0Se5UNOaJLlQ5VLiqf2E4+uRsBJL7iKW3D5MjwBgmkmS2gkMM0pKa8c0osST+1HkARTZhyzlTapfoVWdhsv+DgZCP8EwAunoNTNBMnUcm2UGTtu1nNYCyVIOFrWKYPRJFLkAIaxIwonDtgSBilWdij/4fWyWRhTZh2FE035OyX3keO4HwGa9Crv1KvpDP0kLo1IO8dQBYokt5Hq/iCxNzO1hNCTAQpb7wyS1k/iD30aRi7BZZk/CszKJav2ciu4AoMQxD4cyedG9b2M00jkbVXxFb45P1ZWCSROctu1vpam1h77BCPuau7Db1AzB6cdfeS8lExScpi+q5Z8e+dw4V01Oq+BlWcJiU3HnuCisyMV+AWH4uV4nXqeNF3cf5aop5Ty3/RDz6kpRhxJ5bm9qY/G0CoLROL2BCJUFOWS77JT4PLy6v4Xr59YRjiXRDYPZ1RPLszYeUimdWDQ59kWRZko/bU1JJ+cUw5Em6VO5OXxdVtI5ribbs6DEUc6NRXewZ3Ab83OWsSz3egQCHZ2BZB917gYs0sTTRcSNBN3x3lFlkpCodVczmAwADAsKI/F4yz4afUXcWFaPKkkcHOjm4eN7WFlUg8dy/t8/zXlUy9zcL9MZ20R3dAuBZDMJfQDTNFAkOy65FLdaSb5jAT7rTNyWTALMPyWSRoruuJ/pnipWFy5GFcoQ/1USy5BzfjgV5enOV5nhreW+yndhV2xohk5CT7KpbxcLc2dSZMtj+8B+YkaSD1ffRp4tB900cCg2ft7y5KTMVSAQwpZhpkqnCTlDAWG3LiQ/++sEwr/GH/wuoCNJWThty4E0C7BVmUqu90sMhh6kN7kDWcrF43g3spwod+NLAAAgAElEQVQ7SuBByAhhg3EEXUm4yXZ/CH/wu/QF/hUh7DgsC8h2fYjB8M+BoYATrZvWjvsxSSLJASBK7+DXEcKGy74Gn+d+mEAkZ9oUPPp+T5dLwsppYUgIGz73X9MffJhg5Al0cwBJ2FCVShzWxaPaylIOOe6P0xf8Ln2Bf0MIFYft2rTgJASqXAro2Cyz0+2EikWtIZ7ah0WtGxrdQp73KwyGf81g+EFMM4Ys55Hr/Qou+/XDWqLTv+Eo013mUx36neXhvn2e++kZ+Hv8wf+kyPcDZHFppm7D1DkWWsfOvgcRCOb47mVG9p0XdGB7G2PDNE30lI4+XnJ4IVAsyjkphUzTxDRMdN3ANEbuWQJJlpCVzAAmwzDRkilMw0RWlTHrjOw/lRiqq8jIqpzhcmDoRvp/w+S0rCBJ6fGlyQrWOo9vw4SPcd39Ibr9oXPWmVqRj3WCSSsvxOfiYh+EaZq09wV4cssB2voGmV5ewC2LZ+BxWPmvxzcihCClaQSiCW5aUM/CqeUIAT2DYZ55/RCH23tx2y2smT+N+XWlPPLaXoqyPSybUUUipfHQq3uYU1PCjMrzh4oePnCK1pbejHJZlvD7wzzz+E7CoTjVtQVU1eRTVJKN3WHBNE2CgRjtJ/0cOdRBR/sAN982j/fcs5jsHOek+Jud/cwMdATS0GIqhsrS5g2Jib+YI9uNh7H6+/zWp7h3ynwac9LCan8iyt9uf5Z/ueodZFsnzk2UfsdMTAxMDEaRjwkxdI9pP5k3K2FuKBXlgeY/oJk6X6n/0PC4hwLH+e7R33BPxU0sz5tLytB4uuNV1na8wuysqSz0NVLtKiXXkjXc5kDgGN9u+iWLfI3My67n9Ka7J3CEP3a/zmem3MNUdyXfO/obMOFL9R9EGSIQPBxs4TtHfs27i6/mHcXLL+me0hFrKQTK8EZ8tvnpDPkjgJb+PYbSeKY34tPvgTncNl1HDDlYn36PTq8vBibakHA29jdwph99qB8ZEEPt0ge87o4BfvydtRxr6uL/fetOaqae+ZbT9cdOvm0MbRqSJEbc2+j7Hf1s5GGn8RPHenjwR+v5/P+7GZfHOjQ3CYbml+mbdvoeGOrnNKGoPnQv6b5H1hVYz/KDSz8vMIfGUkY9N9M001QOI+aZ+TzH/53TUYqXngJDMxJs6/0+hwJpob7eewsL8+5HuYAD29sYG4Zu8NO//R1P/vD5Ma9bbBa+/Mv7WXDj2HkdU4kUx/ed5NDWo+xct4fWw6cI+kPIikxOQRbTl0xhxR2LmLF0GtYRLiR9p/r55ge+z5Edx7j9r2/mnq/eijpOAu3wYITPLPk7etr6uOvLt3LXV25BkiRM0yTUH+b43pPsWLebg1uP0tHcRSwSx2q3UFJbxOxrZrD89gVUzSif6Hs4bqVJO0IX5LgpmESOpjdjoxJCUJaXxf3vWjrGRSjKcXPnytkZlwqy3XzwhgUZ5e9ZPmv431ZV4QOrJs6jM62hhGkNJRnl4VCcf/va40QjCT78qVUsu3oabk+mP49hmJxs6eV3v9zExpcPMXNWOUtWTp3w+BOFEAL5rNcmXXbhJ76R7XoTflJGiiJbQVpgNVK0RU9RYMvHqYwWhhpzinjk+F5MExyKhS3dJ3AoVixj+EOdb/wzmxJv6eAfk9GHCVVSuKFwMYU2H6/27uS/jz1CsT2PG4uWc1VOA6qkENPjJI0U2/sPcCh4fFR/5c4ibLIFA4O4niTH4hl1XZUU1Ek6xadpADK5bM7W1Jx5p9Vz/BSnBQfLWXXOnqs8rPkYf15iaKyz5jGiXWFJDn/ztffxT3/zEGAdcpg+P1qOdpOIa9Q3lo4aK3MOmc/GNE00Le2ndL7xxruH9LXRz2Dc+xWC8z0vIUTGPCdyL2fGnBxIQqHAPovW8CYkoVDkmIv8JjHg/7lDCEH9ojqiwRiJaIJ4LEEyliTQF6J5VwvJeHJIizM2QgMRvvuJ/+HY3lZMw8TmtOLxudGSGm1HO2g91M62Z9/gQ9+4i+vuWYEYSs3mK8pm6vxq9m86zM71e3jXJ1aTUzi2ZnL3KwfoPeXHarcw6+qGUfvgvo2H+MFnHsTfmc7Q4PG58fo8RAIRDmxu4sDmJnas283n/vtjVM24NIqVSbU9RONJdhxqY+u+E4RiCW67upHZU0ro7g9hGCaFPvdFa0BOq+ASsRS6pmOaJpIksNhUVIs6/CNMJt4KaRQ3b2xix7bjvPuOq1i1ZibWcSRxSRJUVOfx/g+u4Muf/TVrH9tB3bQi8gsnz5n5aOggLZHM7OAjsSJv9UUl+t07eABJSBTZ0gzahmmwc2APs7NmUuceHf56e1UjP2t6nW/ufomUoVPpzuG+KVdhV678BXRIlsM4K2N8VI9l+D05FDuLfI00Zk2hLzHAE6de5hcnniTXmsUUdwUuxYFNtrKmaCnX5I/mtxEIHIqNpJHCIdsIpsKMfOOTRorURUZIvlWhpXQikQSKIhGNJFBUGY/XgSxLJJMaoUAMwzCwO6w4XWc0MmOd4QzDJBZJEIslMU1zuA3AYH+ErUOM/jl5bmw2FU+WA0kSJBIpQsEYpgEOpwWHM61RMgyDUCBGKqURjYxjsn8bSEKm0rWCAvvMtE+pkn1Z/A7T2nCTlJEiZaTQTR19iOvLMI1Re4MqKXhUN8qVbi4UsOimucy/fhaGcdrcZXDy4Cn+363/TvI8gU52l42GpVMprM7n6vcuoXpmORabBcM0OXmonf/50m9oPdjOr//5MRbdPH/YF1lIgqvft5S1P15P864TtOw/SXaBN0M5kIyn2Lp2J8lYitlXz6CktnDENyooqSuiqrGca+9exlU3zKKgIg9ZldFSOq89to2H/uMpjuw8zlMPrOOT3753XK3WRDBpglMknuSnT25l7cb9lORl0dkXYNmsakwTNu1p4dU3jvG1j91IlvvCOY0S0QTNe1vZu7GJ1oPtDPQE0FI6dpeN0tpCamdXMmPJFAoqcidNUzWzsogs5+VLWzJRbH3tCLIs0dBYhuU8Zk4hBKXlOeTle2g+0k1nx8CkCk7d8VPsD+wY/tsEdFMjmBokaSSocNSyJHfVRfUd0aL4rGdCXSUhoZk6CSMzmaVLtfLphmV8vH4xcV3DraY3rDfLnHY5oQoFl+zgQOQYYS2KS3WQ0FPsDxwjpEWH62mGTkiL4FVdOBU7DtnGO4uvZmPvLgKpdJRVuaOIApuPptAJrs6fT7aajlTTTZ1gKoIiZCRJospVwnOdr9EV91PqKEAzdI6ETjKQDI43zSsS7W1+fvjvzzFrXiWd7f348j3c8f7FWCwKL6zdTdOBU0CaqPe99y2lpGx8x+h4LMlzT75BS3MPqZSGqip89K9W4/HaefGZPWzdeAQhoKtjkOq6At5x6zx03eDpR3Zw4lg3CIHdYeG99y4jv8DD7u0tPPXQ6zicVhRVJjQYHXfs/+tQJCtu6fIwZRumwWAqyMloO23RU5yKddIR6yaQChDSwiSNJPpZUZc1zio+VftBiuwF4/R6ZUAIgaIqKOrofcaVPbG8jTanlY996y/S5mnpjEBjmiYF5bkIBF97z3/S3znAsd0nmH1Nw3DbqoYypi2sZc8rB3npN68xd9XMjP7bmk7RtOMYqlVl7qqZePNGa8krppfytUe/gDJinzw9/rs/tYb+rkGe+MHznNh/En/nAIWVF58ce9IEp71HT/HKzmb++u6raagu5AvffXJo4lBTmssjL+0mlkhdkOB02m750Hee4bUnd9B5ojdDDbR93V5sTis1syq4+4vvYs41DUjypfukXDdn8qLRLgX+3hCyLKEoEz9VqapCJBIf39n8IjE7exFT3KNDvnVTJ6gNsqHnOSqdtdikixM2sy1ZHA4dYV52I6qkEkgF6U34scuZ78u2nlaKHR7KXNlYJsjddKXAIqlM91azxb+HHzT/nmpnCZ3xPk5Fe7COYGQPpML85NjDeFQnedYcdFPnQKCZckcRhbb0hu9QbNxRej0/PvYQ3zvyW+rc5UgIuuJ+3IqT91fejE22sCBnJlv69vCj5t8z01tHSItyLNyOVfrzYwge7A9TP6OEW963EMMwcLpsNB04xaG9bdz9oRW4vXYe++1W1j+9h3s/fs2464jVprLsmnpW3diIYZh875tP03y4k7kLq7n17kVEY0kcDgu3vm/R8Eayc+sxThzr4S8+dg0Wm8pvf/oqG188wK13LWL9M7uZv6SWq6+fwdbXmjh6qONNfjL/d5H23zLxJwfY0LOJA8EmOuPdBFOhCVJyXJht4rQ2a6x20pDbwJV4CEwLXplat9P3UlRTQE5RNv6OAQZ6RkfsyqrMitsXsXfDIfZtPIS/Y4DckjMHacMwaN51go5j3fiKsmhcOR3pLCuTEGJMLZIQAqvdQsX0Mix2C9FQnFjo0qh/Jm3XOdbupyDHzeoFU5FlaThMXIh0iL5mmGj6ON764yA0EOG7n/05m9e+gazIlNQU4vW5cGU5UVSZaDhO0B/C3znIwa1H+fanfspHvvE+Vt62ACFfeS/eWHC5bMRjSVpb+liwuA5ZOfd9+XtDdHcNYrEoqOrkChUuxY1LyfRjKzRL0E2N5zsfYbHv2otiDp+TNZMjoWb+o+lHuBQnwVSQRm/DmASYj7bs4/21cylz/fmFyAohWJY3F1UovNr7BgeDx6l1lfPO4pU81/kanqHcfQ7FxuysqRwIHmN/4CiKpDDVXcl1hYsptJ0Jz27MquMr9R/m1d4dNIfakISgwJbL4txZwz5hVc5ivjDtXtae2kBTqJUSez4frr6NV3q2k32W79OVjvzCLKrqCnC50wK+aZr0dAbYt/skP/j3Z5GEIKXp1M8sG+ZmGwvhYIzNGw5z/Eg3yaRGe6ufSDiejh6SJCSRPrzJsoSQ0qfeUyf97N/dyne+sRZBOpI2N9+DYaTncMudRbi9diprCsjKefMz3RumRkwfJKmHSBmxoSAQgSKsqLITh+w7pxO2ZiQIJE+SMmO4lUKcaj6maZA0wkS0PjQjlk5rI9mxyznYZO95zWymaTKYPEFCH0P7KcTwOBcL0zTpTfTxWt82Xup+lcFU8LwBK5eKsB7hlyf+QCg1mn9LEhLXFaxkdtaM4YjpKxGGbhDoCxEJREnE0mnQDN2gt90/HJCjJUe7AQghaFg6jdKpxfSc7GXbs7t4x4evHRa6EtEkm5/cTiqRYtrCOqpmjJ0E+HTUXaAvRDQUIxlPoaf09PhtfTAi6u5SMGk7qyxJmKaRsdKYpkk0ngTMYWFqItBSOs//YgPbnttDToGXG//yapa+cx7FNQVYbENROIaJv2uQIzuP88yDr7Bj3V5+869PMHPJlFHS6pWM+pmlbN96jOef2sXU+mJmzavMkLQh/ZwDg1Ee/u1W/H0hSspyyPG9OYuvEAK75CCshS+aOdylOrm74g6aw8eJaFGy1SyqXBXDofUjkW9zEdUmRix6JUIRMkvz5rA0b3T0yv11dw3/2y5beUfx8vNGvElCosJZxAec7xy3jhCCMkchn6y7c1R53STkqHurQZbTYcmjyhSJKfXFfPpLN2Gzq0P1pDG/s9PYveME+3ef5OOfW4Mv180/f/mh4WtCpP83zZHEKaCoMg2zyvnkF28cDulWlHT+S0WViQ/5kGgpHU1780g4NSNBT/wAp6Lb6YsfJpjqIKb1o5tJJKFgkVy41AIK7I3Uulfjs9aOKfBEtB42dv8b/kQzs3LuYZ7vw7RHX+do8AV64weIav2AiU3OwmedQrX7Gqrc15zHudtke99POBnZlHFFQmF+7kdozLn7ou7bMA0OBY/y+KmnORg88qYRvqpDUYl7AgcyrgkhmO6ZmpGf80qAYRi0H+lk85M7OLCliZ7WXoL9YeLhOKmUPixAqVYlQ9kmhKCoKp/pi+poP9LBnlcOsPI9i3Blpfewvo5+9rx6ECEE1961LOMbhjT348HNTbz2xHZaD7bR2+4nMhglEU+iJTS0lD4cYHOpv/TkEWCW5fLEhr28+HoTSxqrMEyTZErDH4jy5Ib9VBX7cDkm/jL0tPWx5eldKKrMnZ+/mTX3rUS1jA79FZIgtzgbX9FcqmaU8a9/+QBNO1vY9sIebvrgNZN1a39SXLt6Buue2UPHqQH+45+fYvb8KuYvrKa0wofTaUXXDQb6Ixw93MmrLx/k+NFuMGHR0imUlF8Med34SBlJNDNTYNFNnSPh/ZgYl8SnIguZElsRCSOJS3EMq63PxurSKTzYtJ22yAB5NtdQxA8sKqjEIr15Dpq6YRBNpXBaLCQ0Dc0wcFosxDUNWQgkIUjo6cTPcU1DlWVclrT5K5ZKkdA1TNIZ2e1K+lMMJRPIQiKha0hCwmWxIEsScS2VPk3pBpphYFdV7Go6WskwTSLJJEldR5UlHKoFeeg7CSYS2FWFSDKFCbgsFizyFe7EOokQQlA7tZCXntvLa388xNTpxQz0R/DluqidVkQsmmRwIEIqqREcjBIcjOJy25Akga4bBAej7N15gq7O0aaHbJ+LvTtbOdbUidNtp6DIy4zZ5Wx+5TCbX2mioiaPAX+YwuJsKqpzmd5YxoZ1+5FliR2bmxmcIPnvpcI0TTqib7Cp51tENf/QN6wioaBIdjBNEnqQmN5PX7yJjsgOlhZ8gXxbw7jmJBOdUKqLo8Hn2OH/X+LaQLpPoWCaOlGtj4jWQ3dsL6FUJzOz70QZ18QvyLVNJaYPkNADpIwoKSOGNmaKnYlDMzS2+HfwaPtauhOZNDCXE1bJSqO3gR39u4mf5cO5P3CYvoSfUsel8QK+2TBNk4NbjvC9+3/KqaOdWB1WSuuKWLhoCr7ibBwuG7FIgqceeIFIIDpmBLPNaWXedY1sfGwbTTuO0X60k6nz02mHtjy1g2gwRnl9CfUL6zLGTiVSrP3xeh773rMMdA3iznFRO6eKsqnFeHxuHC4bR3e18MrDWyblfidNcJoztYQbF9fzg4c28uvndtLtD/H7dbt4cO3reFw2PnPnCtwXIDh1n/TTdqSDvJIcVr1vCZZzeMALISgoz+W6e5ZxZNcJdr184M9GcCosyuKTf30DP//JH2k51sP6Z/ew/tk9aT67oToj6YdsNpVrVjdwx92LUMewN18KtvlfYVv/q2eVmsT0KGEtxMq8NdgvIqIOIKxFeLbzRZpCRxFIKEJmQc5cluYuwHrW6ev13pPopsHGrpbhMgnB3NzSN1Vw6otG+dbmjXxhyXL+cGAvR/v9/P3ya3jo4D6m5+Xjtlj52a6dTPHlcnywnypvNh+fvwDDNPnV3t00+ftI6jo+u52/Wboch2rhk8+upS7Hx0AsRiSV5Lb6BlZX1/LYoYPs7DyFQ1HpiUTIdzr53OJlZNts7Orq4KED+4mkklhkmTU1dayqqiFlGHxk7RPcVDeFg3296IbBBxpnM6sw0/z5fwEul41Z86sygiwKS7L5+OfW8OIze3j28Z34ct2sekcjAFs2NLF7ewsFRVm8/Pxedr1+nDvvXcbchTWEgjGeeXwH1XWF3HnvMvKLzmQSWL5qOom4xrOPv0HDrDLy8hsor8rjE59fw4vP7OXg3pMUFGVRXZum37jlzoWsW7uLV9btp2FWOdk+15j+IpcDXksZLqUQVXLgs07BZ60j21qJRXKhGXG64wdoCb3MQPIE/clj7Oz7X24o/RbyOYg/O6I7aI9sxaH4mJrzDvJsDVhkJ3F9kJPhzbSGN5Iwguwb+D0O2Ued98axD10C5uTcx5yc+wAT3Uyxf+AhdvgnkI5rHGimzqa+1/n5id9lCC5vBoQQ1LgqKbQXcCJyctS1pJFka/9O7rjCBKdIIMpPvvArTuxvo2ZWJfd/7y+ZtqB2lGboVHMX63+5IS04jaHyEUIw97qZFJTn0nKgjQObmqibW00immDjY9vS39VtC3F6Mv1ej+1p5df//CjRUIzV917NPV+9lfzy0cFiLzz4Cq89/vqk3O+kCU6KLHPn6rlUFvt4o6mNQp8LWZapKfGxcm4ttWUXFvEWjySIhuLUNFbg9J5/M5ZkCV9RNlaHBX/3m5cq4nJDkiXmL6rBl+vm+ad3s2XjEfx9oVFM4UKkTQvTZ5Zx9fUN43I9XSp81gLqXNPPKhVYJAtF9jJqXPUoY5jWJoJ9gUNEtCgfrLoHu2ynN9HHyz0bqXZVUOkcbTK6b8pVo4TF01CGiNDeLMdKqyLjslroj0VpCwRQhMRAPEYwkSDX4SCh6bQFA9w3ey4fmjMPzTCwKWmG7xtrp3Bnw0xShsFXX1rHob5e5hWVEE2mKPV4+fSCRWxsPcFTTYdYXl6JaUJnKMS3rl+DKkn888ZX2NDaws11U3n04AEWlJRybWU1W9pP8tDB/Swvr0QIQVLXSBkGX1yyLB2+rV58CK55OppIiAwfDNM0McwoQihDTNhvPeTme7j9nsUZ5UIICouzeP9HVmZcW/WOxmEh6my849Z5wNhcbR6vg9vuXpRRXlqRy32fvDajPCvHyXvvXXaeO5h8CCFwq4UsyPsUslDIslRkaH+KHHMpts9hfcdXSRhBehOHCKU6yLJUjNtvTO/HoeSxrOCL5NmmDwtFpmlS4piPWy1kT/9vSRphDgfXUuFejk3O9I0UI0+ICGTUtCbsImGaJvsCB3m4/ak/idB0GvnWXEpshRmCE8CBwGHeXbwG9SLX0j8FTuxvo7u1F0mWeNcnV1O/qG4U9ZBppv2awoFzR4t6fG7m3zCLlv1tbFm7k5s/eh3Nu1robfOTVeBl5rJ65DEOFPs2HiISiOJw23n/395GQUXeqOumaRIORDJ8qy4Wk+o9bLeqrJxbw5LGSnQ97e+kyBLKRdCcy4qEosokEykM3RjTpjkSp38YQzPOG7Z/pUFRZGqnFvKxquv5iw+vpLtrkI72AWLRJIoikZXtpLTchzfLgdWmIknSuE6tl4Kp7hnUuRoyyoUACfmSBJa+hJ8aVyXFtjQ3h0tx4FHcRLTMD21vfyf1WQVIQmCR0uNGtSSHBroxTKjz5OJQ1MsuQNkUhSyrjVPBIDEtRaU3m65wmGAiQaHTTWtgkMqsbKbl5uK1ndmMBmIxNpxsYV93FzFNozUwSCiRXsRdVgvTc/PIsTuYnpfP7/bvIzUUVDEtN49itxuBYFpuHscH+tFNg1daWzjQ28Ojhw6gGQZJTUM3DRQhY5EVFpSUkuu4dH+3YGIHKb0fn+N6GKEdME2ThN7BycEfUuC6Fa/tqnP08jbeapCEQr4tfSAa65uRhEy+fSYlzgUcD72IYWoMJlvPKTiBoN777lFC0+n+VeGgPus22iOv0x3fR1/8EL2xQ5S5MgXNyYRpmrTHOni47Sn8yf5z1pWQcCh27LINi2RBEQpg0hptn5S5KJLCdM9UtvXvzOBn60v4aYt2UO061/N9ayESjKHrBrIik52fycFkGia7Xt5HaCCMep79+dq7lvPUA+s5tO0I7Uc72bvxEEF/iHmrZ1Ezu2LMdzTUn3a0t9jVjETEpmkS6A1ycMsRUm9FwQnSH4ZFVUaR5KY0neOn/FQUZmObIOmUO8uJN9dNb5ufU81dlE09t+pSS2o07TxOIpakfFomA/eVDiEEFquCxargzXIwZdqbr8qVhMxl4BkFoMCWzxsDeyixF+FSnHTGuxhIDeJWM6P4fn5kBwU2Fwi4pWIG07MLeK7tMOvamzCBFYXV3F0797LHpVhkhVyHkx2dp6jL8VHmyeJAbzcCyLHbaQ0MosoS0lmOtK+caGH7qXb+bvk15DmdfPzpJ4c115phENfSH3dS15GlM9Qa4WRyONIrmkrhUFVME4pcbj67cDFzCs+8E07VkvavEgwnrb5UaEaI1sHvI4QFn+MaIB0tFkk10TrwbRJ6FyXSX47bvjPWxzb/XhJGknJHEVflzBhO8fI2JgdRLc42/156Ev14VRcLfY0Tiow83yFDIIYFJROTpH5uHyyL5CLf3jBu1JxN9lDsnE93fD8mJp2xXZdfcMLkha4/0hJpHbeOKhSqnBU0eKdR5aygwJZHjiULu2yjPznIZ3Z9ZdLmM8VTgyzkDMEpokdpi526ogSn/DIfqlUl1B9m18v7mXPtDKxDrjnxaIKd6/byyLefmZBXdkFFLo0r6tmxbg8v/WYjbU0dCEkw99oZeHPHfpdL6tLuB+GBCLtfOcCCNXOGlS2BvhCPf/85dqzbMzk3y2UQnMZCMBLnV89u5xO3L6Ukf2JJHgsr86icXsobL+/nsR++wAe+eitZeZ4MzVNa06Sze8Mh1v92E4oqs+TmuZfjNt7GZcRMbz3+hJ9ftz6EZurYZRvX5i8fZhIfCc3QybLaKbC7+N2xXXx9/hq297bx4akLsSsWfnJoC++rmZORZHqyIQlBkdvN2iOH+cjc+fjsDp4+2sTCklKUc0SQmqTNrNFUkmeOtNMROpPjMZRI8NKJ4+TY7aw/3kxlVvaw4LO3u4tXW09gkWV2d3Xy6QWLUWWZxaXlPN98FK/VjmbqRJJJlpRN/qLrtS7A57iOk4PfRRIKXtsiAvHttA5+B0lYmeL7Jg61atz2nbFeHmlfTyAVZkXuXOZm16NcRKqetzE+onqM9d1b2Rc4SrmjkCnuyglTSpzmMzLRhvLOpf/DzOQcMs8Tsm9XcrBKnnOG1fustQgEJiYDyZZx600Wjkda2erfOeY1AfgsPm4vvZkG7zRyLFnIl5kJPN+ai0d105vwjyqP6wm6Yj0YppFx6HqronRqMY0r6tnw8Bae//krdLZ0UzWjfJh/qWX/SQor8sgr83H0jePn7Mvhtv9/9s47PI7zvPa/b9r2xaL3QgIk2EmxiKJESVTvxZYlW5ITO3YcJ851HMeJnXqT+HFcoiTOdUscJ467LcmWrd4rKYmS2JtIggUEiN63l5n57h8DgAR3AS5YQMrSeR49ImZnvv1mdso773vec1h1/TK2vbCL9b9+Eytj4Q16ueiWlZNusyMAtS4AACAASURBVPjS+dTOq+bovk6+/ZkfsP6yNyhvKGWkL8KBbYfpPtzLimuWsGvD3jOyvzMSOKUzJr1DUawpfG5ORKgsyE0fv4L9Ww7z5P++zKGdbVx9z1pqmipw+5yulkzaZLBnmK0v7OblX71BKpHmqrsvZsHqprOyHw6PI1tWIZnO4NJzm32eS0iZQGZ2Iu0oQi1HaPPGzTfPN3hUN9dXXMVV5ZeRMJN4NQ+ayH1MvZrOnbOXEjI8PH10H8PpBAkzTcjlodpXQMzMn7sgpYU09yHNbK7B8RDCjTBWIhT/hOVNhcUsKitnWUUVLlVlbnExq2scf7JCt4clZRVZQdRVsxoZTib5j81vsrisgo8vX0GZzymlFXm8VPr93L97F0UeN59ccSHuUZHP1dU1bOvuojMa4d7FS7mwugYB/MGKlTx5oIWf7NyGS1W5rL4BAahCcGF1DX7jzHCOVMVPXejTCKHQOvQvhNyX0hd7jALPamaFPo+uFp9318B7yA8ZO85g6iB9yb0Mpg4wkj5Kyh4hbcewZBrbzmDK/K8rXbhParzrVY/pjSXMoVOeez7I2Bme73mFuJVd+ldQmBecw0caPkitp3rGzmFVaNR5a7ICJ4mkN9VHwkpm+XSer9ANjU/e9ztousrO9XvZ/OwO3npqG4bboLiqiItuWsGH//b9/ObbT3Ng69RBslAEi9fOo6qpgiN7nNLoVfeupeIE3tL4+kJQObuM//P/fo8H7nuElq2HeeHnryIUgTfgoay2mHv/5g4uff+F/OUNXz5tDSc4jcApmcrw8Cu7WLO4gbqKQna0dLJtf+7670g0SVf/9OwbhBCsvHoxd332Jn76tYfZ+9Yh9m0+jL/AizfgQVEV0sk0IwNRzLSJoipccssKPvi5WzA8Z0/x+Nlt+7lm2dzxbMZAJM5Dr+/iE9dmm/6eS0hpYyd+hRn5FtgjCG0WWsEXEcbkUftM40isnTcGt0y5zmWla6hwTxS4W1BYwbd3byCgu0laJl/a8hyHwoO8PdyLLcGtTodUmcGK/xw7/tOpV1Mq0It/iFAmtsLWh0L83WXHOjj/au0xgvGc4mLmFGdLQhS43XzsgmxSsWnbKEKwurqWlauyy81ew+AzF12clUkLutx8cOFiPrhwok2BCnxuzakTjmUOBr5ApTr4MQA6wz+iyHsVswq/gK4UjW/zXvD0zoGUkkimk51D99MWe42Y2TPhc0240BQPhhpAsTVSdmSSkSbCyTRNfR6o4tjjx5Jn15+vO9nLwVhrTq2mCncZ99Z9YEaDJnCOTpWngs1D2SWkocwISSv1jgmcAIoqQnzq6x/l8M42etr6sTIWbp+Lilll1M2rxu1zceXdl1DbXMX8NXMnHUcIQW1zFb//lXsY6HQC6vmr50x5OimKwrIrFlIzt5KD21sJ90ccgdRCP9VN5dQ0VyGE4KNf/CBmKkPZFHZK+eCUA6dUxuTJ1/ZQV1FIXUUhW/Yd5adPbaLAn93xYJoWQ5Hpey+pusotn7yK+gXV/OY7z3BwxxGSsRRDPSOOya+m4At4KKoo4Kq7L+GGj67DV3Dmu8mOx9ZDnYQTKW5dtYAjfcP84PlNzK89deXaswY5jJV4Cuxe509zP3byaZTzKHBShYp31FIlbiXYMbybRn8DISNEb7KPmBnPqeX0ocZlPHZkD8PpJF9ceR0Ali359p5X+UnLZu6avXQaZTqBwADcgAlYnFt75/PBWnoMkoH4s0hOJFQq+PRmijzrSGQOMZR4ebyTrsB9IYaa+83wPZx/SNlhXun5Cj2JXYCkwKin1ruaat8qAnoVuhi7nwp2DT3AjqGf5TWuhYk8iRhuxj6mxaSfRqfcySClpDXWRk8yW69JFQq3V99Ig69uxgN+gaDMVZLzs3AmQto+38yexZRNR0II/CEfiy+dT7bTnIPZi+uZvfjkNALDbbD6xulRboQQlNYUU1ozeVC05ubcXbDTxSkHTgGvi/v+5DYCPueGads261Y08fu3rck6AbsHwvzLT16c9nc4hGidlVcvZtnlCzi44whH93cxMhjFGjX5rW4sZ/biOoLF/hk58T9x7Wr+59k3+f5zb9HSNcC6xbO5YXnz+feWLTMwIbUukXbinE0nF2q8VeNCby/2buCKsrVcWXYpQgiSVopHOp8ibEYoY+LNxasZ3NW4bMIyKSVfvfAmYpk0IZd7GoGThuK5CaHVIe0wyChSRsEexk69CnLmjG4FcG3jHMp9/qzP5peWUBnIXn42IbFpG/4mlpz6padt+Fvj/55b8s/vBU7vIBwIP0NPYicSmzL3Ii6v+GsKjBpOfL2XUqKI/B8XaSs6ITDKhajZw9iLglfLHUCcCZjS5Ej8aM5ApMFXz4rC6bxonVkUGblto2JmjLR97t0RHHFJk3Qqg1DA4z/3xvfnA045cFIUhdLCYzdyVVWoKimgtNCfdRJKW+I/zfKZpqs0r5hN84rZpzXOqSBtHpNq97tdfPDSZfznUxtprCjiqsVNjrXC+VaiUAoR2ixkZhtggfCiGGcm2j4bSFgJbCkxpYmCginNab11CSFwqRquaZr+CqEijOVgOG83zu+cAauXjPkJpDlzgZOqKNy9KLdm0IrKme8UFag0l/4rkvw9Jt1anjYt59Gl8m6FRI4HTQDNBTcT1LODprG1I5muvMdOWIPEzf5J74tSSvqSb4+XzopdZ4eXCpC2M3Qkcs99eWgxLvXcmVl7VQ8KSpY/XtJKnbJ91anA0QV0fqux30uO+rptfWEnqXgaf8hLVWPFjM3pfMYZI4ffdbXjq5XrkvN6DC5a3IDXnf8Jats2SE6q3zQT+PrDr3Cw+5jux1iL+Gt9Q+xo7aYo4OUrv3P9OZxhNoTQ0QJ/hqUUIK1uFNclKJ6bz/W0JsXC4Dx+efRR2uMdeDUvw+kR3Kori990tuHcNAyk4oN3eceXEAKf0XxWxh4rwVq2xWB6hP70MCkrgyoUfJqHElchAc2b18uIlJKElWIoHSZsRklbGWwkmlBxqy4KjSAhI4CWZ2OElJKUnWYgNULYjJKyHbsbVSi4FIOA7qVQD+JWXXnPL2Yl6E8NEzPjZGzTKVNrHkpdIfyaL++Mhy1tRjJR+lPDxK0kIPGobkpdhRTo089IZuxj2USvOlmJQzKSOUpXfGo+4vGwZJrW6MvU+FajZQmiSiKZDjrjmwBQhUGN9+xxRE1pZhGwATyqhwZf3aTWTmcbQgg0RcNQ9CwxzrSdwZIz51fY29bPtpd2U1QewhNwo+kaqUSanev38OC/PoaiKlx+5xqKKvLriv9txxkLnDxT6DMFvC5+98bpieId3tXO5ud2ceF1S6mbXz2l4ebZxocuW0YyPXnaVDsvvb8EQq1AC/7NuZ5IXqjz1XBv/QdoiRwkaaVoDjQxL9BEQZ6t1O/h3EJKi3jmEIZaiq6e/OaqKxoJK8X6vi1sHNhOa7yLuJlAFSpFRpDZ/hpuqLyURQVNqFO0ZA+nI7wxsIPd4YO0x7vpTQ0RN5PY0sJQdAK6jypPGUtCc7mufA1BfeqSvkSyN3KY57o3cijWQV9qkJiZwJI2uqLh1zwUGyFqvRXMC87iqvLVOY2ox5CxTXaNHOCFnjc4GDvKYGqEpJ1CFxohI0ijv4aLipewtmT5STWtLNvitYHtvNj7Jq2xToYzEZAQ1P00+mu4rHQFCwsa0ZX8busCgV+vwHndlXTE36Tad+EECQEpJSOZNjb1f4+ENb3Ot9boeiq9F9AYuGa8w84JSkfYMfQLwhmnmajSs5wC4+wZSlvSIpzJJrUHNT8BbWYoHpNBIHJKDtjYM2Y6DNDfMcjPvvwQve0DeP1uDLdBMp4iHo6jaCqrb7yAD3z2ZsQ5eg53JXrpTvZPCCbnBWfjP0fk+RmRI7ClJJU2cela3gFQ1+E+fvRPD/Hwd59j3srZXHHXGhaumYOvwJtl9nu2UV/q1KGllMRTjvSAdh5kwn6bIBBUuMtmPMP0Hs4MLJmgM/xDSv23EFJXn3R9Cfyg9WFe7duKjcRQdDyqG1OadCcH6Er20xJp4976G7msdGXOoCJtZfhF21M83/MGSTuFgsBQDdyqgUBgSYuB1Ah9qSH2jBxkf7iVz8z9MAE9983Wkjav9m3lx0ceoyfZjxAKbsXAozq8DlvaRMw4g+kwLdE22uJdXFE2+Qth0krxcMdLPNb5MiOZCKpQcSkGPtWDhU1/aojuZD9bh/bSGuvkztpr8WrunNpHKSvN413r+dXR5whnoigI3KoLVVFJWim2DL3N7vBBrq+4JO/MGsAs/zoOhp8hIxPsCz9BRiap9V2ESwmStEboTe6mNfoySWuYGu9q2uMb8xrXyV4pvNH3bQ5FXqTKuxyPGiJuDXIkuoHB1AEsmSGgV7Kw8APoSvZvIqVNyo5gS9ORDcEmYyfGO/8kkpjZx1CqFV3xIBAIoaAIHUPxT7B5SVrZfCu36satnp+cHQVlSg2sM43yhlJu+NiVbH95D0M9IySiSYIlAarnVLD2fatZcfUSgkXnJsjcEz7AA+1PkrGd0qVpWwR0H3Xeyt/uwCkaT/Hgc9u49bJFE3hRUyFQ5KO4spCetn42PLyJDY9somFBDRdet5Sll81n7gWzCBT5ZvyH/K+n3+DOtUuoKc72VXoP7+HdCilN0lYfUuZHaN00uJu4lWReoIE1JUuZ5atGFSo9yQFe69/OlqE99KYG+WHrI1R5ymgONGRd67qisTQ0l9cHtjPHU0ejv5Ymfy3FrhCGojOUDrNzZD/P97xJ1IyzZehtnu/ZyK3VV2TzMKWkLznIA+3P0J3sJ6QHuKx0BYtDcygygoAgnInSmejjYLSdQ7GjXFa6YtLsjiUtnup6lZ8deQIbm1pvOWtLltMcaCCg+4ibCfZGWnm5dxNHEz081vkKbtXF+6qvwnWCnIYtbd4c3MUv258lYsbwa17WFC9hdfESQnqAuJVkb/gwr/Zv5bHOl6flcVbpvYBFhXexZ/jXpOww+0YeZd/IoxPW8ahFLCm8mzrfWgY6WkjaIycdt9A1m8bgNewaeoCO+Ft0xLPNVQv0OlaUfJwa76qcCuNpO8r6nq/Rn9xH2o5j2okJfDuJxe7hX7J7+JcIVDThRlc9FLmaWFP6mVGSuxNgWTKbp6cKdcps5kzAljZmDi6TpmgzKn5ZXFnIBz9/Gx/8/G2TrnOuMnN7wge4rHTVeGZ3fqCRx7temtFS5omYkcApkcywaW8716zOny8xd/ks/vqHn2L3xhbW//otDmw/wpE9HbTuOcpzP3uVWYtquWDdAi6/YzXFVYXjmayz/eO2dPWhT6M055CNLbB7sNNbkJm9SLsPZBwQILyOOKVag9AXIrQmnJ8lf38/x3w1HwKvOqkFwuRzt0f/E4Ay+v80dmojdvIZkGGEVo/ivgWhzRlvXZbSRpot2MnHkWYrQgki9KUo7htA5A54J34fo9/nHAcpJcg4dvo1ZGY70mwHTBBBFL0Z4boEoc5CoHJWjPrOMJx9TSEz+7DTbyDNw6MdfCpCKURoc1CMNaDVO8vOwT5JadER/j52HsGQLRPEMwfyHns4E2FJwRw+PeceytzF44FMc6CBpaFmftj6MM/3vMlgOszjXetpDjRkjSGE4ILCeXyu+SNUekooMgqyHoQXFM7Dr/n4+ZEnyUiTPeFDXFW+moCe7d3XmxqkPd6NguCSkmX8bsMtOYnDKSs9GlwFc/JjpJS0RNp4omsDNjYV7hI+1fRB5gcbJ8xvcWgus301fO/Qr+hO9vNM92tcXLyUWm/FhN87bWd4sms9ETOGoejcWHkp76+5Cq/qHl9vScEcLiicz1fe/m8G0ycPbMaPIQqLC++m2DWHg5Hn6E3uIWmNoKDg0Uoo9yykMXAN5Z7FZOwYIVc9vYk9iJPwgkw7RYV7CUXljbRGX6E99jqRTCcSSUCroNq3igb/5ZS65096T5LSJp7pI24e4yeJKXiHpkximkniSt+Ec1YgUBUN+4QuNYmdU6tspuBw85JkcnTPuRTjrCuXH4/J7i9SSixboigzmf86cRLgUVxoispAahiv5kERChEzRiXnpoP3lAMny7Jp6xnKS3amZzBCJDZ1a+qJ8PjczF0+i6ZlDdz4e+voONDNCw9sZOf6vXS19rLl+Z1se2kPD3z9cZatW8C6D1xE45I6iitCaGexlLd6bh07WjtZ0VgzXq5ThMDnNrKNDWUKmdmPFfsedmrDaLBk4hy0sQM3FpAoIDRQylFc61C9dyD0bEPdXLATD2FGvgpTicgJN1rBF1Hd0yGxp7Ei/44V/ykoIbTg36MYa7Ci33SWydjofqhY8V+jBT6L4rkdkNjJZzHDfw/2ME5QJ4AHEYlH0IJ/j9AacwQ4FlbsP7Ci3wNAcV+PFvw7pFSwUy9iRb+DNA/hHMOx4EpgJ1QQLhT3LWj+j4E667xVSHdkIaLY6Y1Y0e8iM28DGSbqRwlAHe2EvAjV/0nQFyLEzHb/SGyOjvw3qhJAFVPr7EhMMlZ/3mMrKNxVdx3l7olq40IIQkaAu+tu5I2BXUTMGNuH9tGR6KXGm22/41IMFhc0TXq960JjTfES1vdtoS3exWB6hIgZzxk4pe0MNjYKAl3RJs1GuFSDet/kXpEZafJa/3a6k/0YisZt1VdkBU3gaAitLFrAjpH9PNrxEn2pIV7t38qH6m6YsN7haAd7wo5NRZWnlNuq12WV9FRFZW6gjlur1/GDww9POrcTIYTAUH3U+y+l1rcGG9MJJoQTVClCQ8G5n2rCzbVVX8WWFqoy9bloYyKxKXbNocg1m2VFHx7vHBMIVKEjTvJC4FILuLH2G6MvhvlDCGUCId0pubqyApSUlSZ1jrWSupO9OR+hQT2A6yTHeCbQNRLhT+9/jI+sWc5NS+adkznM9tfSlxpiccEcNvRv4Ui8k8H0CFeUnZwScLZwyoFTJJ7i8994JK+IPWPZDAxPbQqZC0IIVFWgel00Lqln9uI6hnvD7H6jhe2vvM2uV/dxePdRXvnVm7z2yGbmXDCLhRfPZdU1i2leORuP78zXr3uGo/x6427qSkN4DCd1WOjz8IU71k1YT8oMduJRrOi3kdbkppLOw9Jy/pMZsFqx4z9ECDdKnoETZMCOAlPdBCyYdnurRMoUyChYKaTZhi3jWPEfgjw+ELbA7sKM/D90fRnIIczIfWAPTBgLMsj0RqzY9xHBv0KIEw18pRP8ScfpWpqHkHYfduIJrNj3QQ7nnCOYIE3sxANkzP1owb8Ffen5JQ8BICVSDmNFv4MVf3AKjaixfQpjp57BNveg+T+N4rkFIWaWk6GrhdSH/hSfsWDK9Uw7zOHBr+Q9bqERZJavZtLfqMgIMj84izcHd5GwUxyMtucMnE5qTisEPs1DSA/QRhdpO4Np574OSl2FFBpBhtJhXu/fQYW7lMtKl+cMsqZCOBNjX+QwEkmpq4jmQMOkQZgiFBYGG3micz22NNk5coAPnbDO7vBB7NH77OKCOQQn6Z4TCBYGG/GpHmLW9DTbhFBQhYHK5A/rseApP8jxbQTatDSgjv8+/SQBez5QhUJQDxIxoxOWx6x4TguWmYJE0jqJ4XCBHjynMgljCLhd3LliMc0V506bbWFwDnKUB3lj5eXsjxzmkpLllLtOT/37dHDKgZNt2yTTJrdetoiyk/CWBsNxHn5556l+1TiEEBSWF3DJLStYdc0ShvvCHNh2hNce28zWF3ezb/Mh9m0+xPM/e5WauRVcetsqLn3fKoLFflTtzJQ7blo5j2uWTbTdMLTswygzOzDDXwU5JmOggQgg9GaEWgvCBzIBdg/SPDAqvpjECX5cKJ5b856TUGtRXGuRVg/SHgYSIO3RjNCZElHLIDPbsRMto5mQtaAEsdNvgNUJSLA7sOM/RsoIWB2gNqAYK5AyhkxtGA2ILOzk00jf74KYWjhUWkexYj/FTvzS2Vb4nZKmNgeUENhD2JmdYHXhHDcbmdmKGf4H9ML/AvX8IppLUpjh+7ATD3EsyHWDWoqiLwKlBGQKabUizRawRwAbrKOYka+iCTeK+6ZplVtPF7paikdvxKNP3fVkWmF0NbeYXy5UekrQp8gKCqHQ4KvmzcFdZGyTruTU2SwpJaa0MKWJJZ0SjD1qUBsx4+MdSuPGtVnfJyh3l3B12Woe6XyZntTAaLlwI2tLl7O6aDHFrgIMRT8p9yRuJjiacAjMPs2DJlSG05PrgenKaIZcOkbIEjkhm3Qk3jU+50Z/7aTjCCHwa16KXQXE4ueX2O25hCY0SoxCOhKdE5ZHMlH6U4PnTIMvY2fYHd6f87NyVyle9dzbrQTcLu5cOZkO+Mxg7HoTCJoDs2gOTG4kPlM4LY5TScjHtRc1U1c+9Q2zayDMxl2tp/NVEyCEwOUxKKspRtoSVVMoKA7w4oMbGeweZqh3hKHeEXa9uo+Hvv001/3uZVxzz1pKa4pO+3sX1DpvvRnLQhEKag5ulZQZrOh/HBc0uVG8d6D6ft8JmrKqxWmkedDhuqReB6UEoeV/cgjjEjTjEsZLPTIBcgQz/CXs5NPHlp8m7OTjoBShh76OMC5xviqzjczwn4HlmORaiV+NzmkNeug+UEoBEyv2E6zov4zObQiZ2YLQTsJ5s3ux4/8LqAhjFarvUyiui5mgrySjWPEHsOLfHw2gJDKzGyv236iBP5vxDM1kkDKDHf8FduI3jAVNQpuP6vsIiucm4PibpESaB7Fi/zHKI4uDPYQZ+Sq6Nhehnx1tpRMh0JhX+u/oyskbIRRhEPKsxcgzWPWfRKNJAIWGk5G0pU3UzJ0ZkFLSmxqkJdLGgWgbR+JdDKSGiZkJklaKjDTJ2CZmDnLwiXApOnfWXUfICPBM9+scTfTSEm2jJdrGz9ueZGXhAlYVLWJRQROlrsJJeXopO0M048x3f+QIf7L1q1PyQ46/OtPSJG1ncKvHSk3hzLFMSbEx9W+hK9q4jdF7cGAoOnXeGraP7J6w3MZm58jbrCledU6yO9uHdzOUzpZ40IRGtbcSl2IgpWR3Zw+9kRiXzmmYwK+NpzO8tO8QC6vKqSsqwLIl7UPDtA4ME0ulMVSVmsIgTWUlGJqznW3b7O3uJ2NZzCkvZm93P90jEQxNZV5FKdWhIEIIoqkUL+w9BBJUVbCoqpz64uznfCKdYVdnD/2RGKqqMLukiPri0Pg8e8IRdhztYXldFcV+5x5n2Tbbj3ZjWhYX1FWhqypSSvqjcVp6+xmOJ1EVhUKvh6ayInbFd+PVPKwI5VuBOfs45cDJ4za4+9rlFAdP3tlmaOqUOk/5YqwsaFs2h3a18+ojm9nxytsc2ddJdDiGoijMWlTLxbcsZ6gnzMbHt9Dd2sdPv/IbWra28gdf/hAVDaWn9XaRSGd47K232XKwA0VRWNlUww0rmsfLdgBYXdjmMaKs0JvR/H+KmFRgzoXQF6Bo85Ge949apeR/IR/bn9H/Cx/gg6xS2OnCQnFfhTAuGc96CH0pinEJdsIJnJBxECFU38dAGTvWOorrYuxEHdLc56yWeRvyvL8LrRkt+A8ILUeGSgRQfR9GKH7MkX8EkoCFlXzWIaLry855yU5KiTRbsOI/H50foJSjFXwRRb8AsjIYAqE3IQJ/hSktJ2DFBqsHK/4TRPDvZoTv5PBf8kuHK4qbysCJRabJ4RBfp/pdxDg5NldXlERiS8nmwd38uuMFDkbbSVip0S0dDpVbc+FR3QQ0hZGMI2Q5FYQQeFQXN1ddzqKCOWwf3scrfZs5FD1K0kqxoX8rm4b2MNdfz81Vl7GyaAGayOZTmtJ0sl0T5psfBE6geDwyx5UWtZNoNClCOake1LsNmtCo8VZhKEaWE8HOkT0MZoaoVLPLwGcLjiBqnFcH3iCTgz7h13w0eOvGm2K2H+3mR69vpToUnFAy29nRzZefeIkvv+9a6ooKONA7wH3PvELncISA20UkmUJVBJ9adxE3LJqLEALTljy5ax+dwxHmlBez4cARbCnpj8b49JVrqAoFnfYf02LzkQ56w1G2tHXyuWsvnRA4SSkJJ1N8/9VNPPf2QfyGQca2UBWFj6xZzg2L5qIqCm939fHVJ1/ia3fcMB44mbbNA2/tIJJKs6CyDF1V6YvG+IdHnqdzOIzPZRBNpUmZJp+6/CISRX00+GbeOWEqnHLg5DY0rr5wbl4PpaKgjy/94U143KcePKVTGQY6h9i/5TDP/nQDeza2kIynHDJpWQFL1s7jho9ezryVs/EGPdiWzb1fuI0nf/AST/3oZTY+sZVAoY8/+Mrd+AtOLQUqpeTBV3ewv6OfK5c0IYGXdx1iJJ7ko1euOCZVb/dxvE+c0GYj1DyyXUIgxPktc6C4rmHCA0+oo0HR/YwRtoW+0Ol0O570q1aNZp+cwMm22vLU5dZQfb+XO2gaG1u4UDzvQ0k+i516wVlotWOnXkPVFwGnH7SfHkbLk+PBtI7m/zRCX5YjaBqDQKglqP4/Hm0sGAJs7NSryMwehLFsku1mBlNxG/O5J6StNFOHE5Kk5TzkFEQWUVZKyRsDO/ivg79iID2MR3WxLDSPtSXLmO2vocRViCocLZzB9Aj/ceABdocP5rNrKEJhlr+ael8lV5ev4VC0nZf7NrN9eB+D6RF2jOznUOwod9Vey63V61BPOJMNRUdFwcJmtq+GO2qvnlIk83joQsvKfriP+ztlTU1mtqWNaedvkfNugBCCBl8d5e5S2uMdEz6LmFEe63yGjzR8EGOGyNg2Nq/3v8XOkb05Py93l9LobwCcuV85r5Efb9zKKy2tzCkrQVGcgOrR7XuZV1lKc4XzglpTWMAnLr2QOeXFGKrKcDzBV558me+tf4vrFs5BPe66fP1QG8V+L//ygRvwuQzi6Qw+lz5+Zy/0evjrG9ZxdHiEj//woaw5Wrbk4W17eGTb23zp9mtZUlNBxrL4+Zvb+bdnNzCnrHhavKgX9x6i5hsPcAAAIABJREFUfWiEf7jlKuaWl2BLSW84Ssjrpi1j057oYiQTGb2OnFm6VOOcyUmccuB0vKfNyaAoAr/3RNn9k0NKSTKWYs8oGfzNp7bTtq8Ty7TRXTpNyxpYff1SVly1mKal9WjGcbujQ0m1wT1fuJXqpgq+8ZkfsO2lPXQf7qVpWcO05zKGN1va+fz71lFf5kTf86pL+eeHXuKjVx7vA3fsxwWQVhdSJhDi3NesTwvCh1Crs5rhhFbP8fsr1BqHg3T8OsKHEL5jj0prCOfBeZJzSClEcV+Rx7mmo3g/iJ16iTFJAzu9HlV+GM51MCpjWIlHGCfM6s0I10V5dP4JhNaE0Bci0xucRVYH0tyH1JfMKNdpDCmzk8HEK2SsgZzdTmX+207KhwIYyoSzMivHQyLpTzllDFWoWXYiSSvNE10bGEgP41J0bq66nA/UXINHc2UJB8ZziB+eDGI04xXQvSwtbGZJaC6HYx281PsWT3W/StSM88v2Z1ldvIQqz7EHhBACQ9EpMAIMpkdwqQYLgo2UuE7dqqLouPJcX2pq9e6MbRKbpKz5bkaVu5xG3yyOxjuzOG5vDGxmjn82a0tWnzSjdyawJ7yPR7qeIjEJgX9tyeoJpdqKoJ8LaqvYfKSD912wgBK/j55wlK3tndy6ZB6lAad5we82uGj2MQ6c32WwvL6a/9mwCVvKCeF9yjT5yMXLqShwqhIB98TnsxACl67hysHfBYgkU7zS0sqqhhpWz6od7zC/cfE8Xtx3mMd37ptW4FTs9xJNpth+tIuawgLKAj4KPA7Non0IXu57i53D+wjqgfFnwZ0111PpeYfJEZyISCxJIpWhJOSfoA4upWQwHCeVNikvDqAq+d3sI0MxXn9sCy/c/xpH9nYy3OeQK91eg6WXzeeaey+lcWkdpdVFqNrkDyBVU7nk1hX85Cu/obetn1j49EiTuqoSTabIWM5bXSSRwtAnHkahViOUANLuBnA4N/EHUD13OATn863bK1+I0GiJ6MTI6XhbFAWhFCM4IVAWCkzwrJrozTQZFH1hXiVHAY7EgVoNVjsAMrPX4VRxbgMnaR4E6+j430Kbh1Ar89xaoBhLscYCJzJIcz8OT2pm+Vsps5fDQ/cxlNiAIjRMO4wqfEgsbJmhwL2SUnljXmN1JPqIWUm8Wu56rSVt9kecjiNd0ajxTCylZKRJy+jnhUYBV5RdiFfLPh5jWjkjmWjWZ9OBEILZ/hoqPaVEzDjP9WwkYsbZF2mdEDiBw9+q81YymB5hIDVMV7KPYqPglK/7Wb5qBGLcDua6iosn5VdFMjH607m6T88+BAJd8aArPnThmVHl65NBUzTWlV3MxoG3snzhYlacB48+gks1WFV4AaqinvG5S+mUm3eH9/HjIw/QnxrMuV65q4wVhUuzlt+0pJm//vUztA2MUOzzsvFwOxnL4rK5s1BGS3qmbbO9vYuX9x+mOxwllkpzZGAY287Wqyrxeyn1n/qLfMo06RqJsKqhZsKLdGnAR8jj4lBf7v0bw4m55jWz67h56Xwe3LSTp3e3cHFjPbcunUddUYgKdykfqb89a4zgNLtdzyTOWOD01p42/us3r/Otv/gAJaGJO7R1fwf3P7OFr/7xLRSH8tvZHev38m9//D9IW+Lxu2laWs/yqxZx+R2rqWuunFaXnOHWKSj2093ai7RPjyh9/fJmvvv0GzRWFCElHOga4PbVJ5DWlCIU941Y0W/gtNhHsMJfxk6tR/PeDfoiUMrOScbgdCAUP7lOmYl8Gw2UgtwilEJjzBeLPBWmhTYX8jHhFAIhAgi1HjkaOCHDSKsdoZ5bR287vZljulMaQq1nOkGPUCbOX1odjrTEDD+XYuk9hJObmVP8ZYq869jT+0mqAh8h4FrC0ZH/QZLB0PIjhyesJOv7tnB79RVZXWoSyd7wYQ5End+x0AjSHGyYuI60SY9yljSh4pvEOkMi2T68n65k35TzkdLptjtZx5xHdVF7nCxCLvHCoO5jeeF89oQP0psa5MWet5jtq8E3SZA4BltK5wXghGtnaagZt+oiYSXZMbyf9kQ3dd7swNtG8urAtnGu10wjoFdzQ82/M5ZJPplI5kyjyT+bi4pX8VLfhqzPBtND/OfBH9JW2cHaktVUusvPmHK3JS16k/2s73+d53peyZJFGINLMbip8mqCerY/Z3O5Q9xe39JKY1kRrx04QmNpMfNGszoZy+Inb2zjxxu3cWXzbC5urKPI6+XF/Yd4ald2555Lm1gVORUoAuwTnqfOdUQO02o54Z9pa2I52WvofPaqi7lrxSKe2t3CC3sP8tj2t/m/t1zF2qZ6Kt3nTg4hF85Y4NQzFCXgdREKTLw5CCGoKAowEkuSTOevIySlxOUxWHn1YtbcvJz5qxqpml1+yiaD8UgSb8CDcRo8KyEEVy5pojjg5UDXAJZtc/H8BpbNqsoS8VO9d2Kn1iMzY47iJjL1Ipn0ZoS+CMV1OYr7GoRaB+Rf9jynEC7Ip7x0JonLSil5X+DCjVBLJ7zNSKsDmJ7B9JmGNFs4duOQ2KkXkMdloE66vXV44t92hPyU4s8sTDuCrhYS8lyEInQU4caWSTQlREXgLloG/pJE5ggB16K8xnuqawP13kqWhponcBWOxLv4RdtT41YUl5QsI6BNfOFShUqJK0R3coCwGWN/9AirjYlt05a0eWtwFw93vJiXPcOr/duQUrIkNIcCPXeWszvZz8YBR1pFQVDvzSatqkJlTfESNvRvYX/kCK/0bcanubmlah2lruzOpJSdpiXSxqHYUS4vXUnImPjdZe4iVhTOZ0P/VgbTIzzY/iwfabh1Qofd2L6+1PvWSffzbMHRbDp/iekKgmsr1tESPUhHoivr87Sd5tHOp9k+vIvlhUtZUbiUWk9V3greJ2Z1bGyOxNrZMryDHcN7OBhtHRcBzYX5wbmsKFqaxdsRQhDyuFkzu44X9h3iyvmz2dPVyx9efkwAciieZH1LK0uqy/nC9ZdjaCqmZbO1vfOsqKO7dZ3awhAtvf3jZUApJb2RKMPxJEtqnJc9Q9NIWxZpyxqdh8CSNu0Dw5QXTDzPhRDUFoX4+NqVXLdwDn/zm2d4cPNO1jbV05nopTPZO+E6XhhsmrbG2pnCGQucMhkLv9eVM9Gga6oj8zMNBdh5qxr512f+hqpZZbj97rzNgSfD5//7k0hpU9106tkHKSX/9MDzhHweGsoLaawopiToI55Kox9nfwCAUokW+ipW5JsO70aOunPLMDL9GlZ6E1bsf1CMC1G994A+D0TwPM9CnawTitFM05m7eQplGp2BQkOIEy6kPHy1zjrs49PWFjKzFZnZeurjySTkuAFLKYlbcSJmGE1oFBpFZ9S2QQgNKS1HIwzQlSISmSOARFU8ICWWne1CnwvNgQY6E738674fsrCgiQXB2eiKTke8h7cGd9GXGkIgmB+cxfUVl2Rt71YNLilZxm86XiScifK9g7/iQKRt3NOuJznApsE97I0cpsgI0uiv5eBoBmsy7Bxp4cWet/BpHmb5HHJ4sVGArujErSStsQ72jByiNzWIKhQuKl5Cgy93ybXcXcwnZt/BfXt/QF9qiEc7X2FD/zbqvZVUe0pRFZWEmaInOUBXss9RM9d8rCpaRIiJ57wuNG6tvoK2eDdt8S7W923hUKSd1cVLKHGFiFtJdo8cYG+klaDmo8go4HCsI+e83s0QQlDnreb26hv4ceuDhM3sc9WSFodjbbTFO3i6+wUKjRBz/Y3UeCrRJyGPZ6RJX6qftJ1mODNCb2qA1lgbh6JHGEgPErcSOb3yjkeJUcxdtbdTqOfmwmmqwoWzanl85z4e3b4XIQTL646p12uKgtdwutEGY3FURbCvu5+X9h/OOd7JkEhnyFgW4WQKW0ri6TQjiSSaouDWNYJuF9cumMM3X3yNZ/e0sLyumrRl8cvNuwgnU9yyZD4AdUUFZCybl/YdorYwhKoIntnTQtvgxMDpjcPt+F0uinweVEUhkkiRMS38LoNd4RYebH8KW9oIwJQ2Ps3NbF/NOz9wCgU99AxEGIkmKQoeq51KKekeCAMSbRoebyVVhZRU5S+oNxWEEDQuOTlhNR/8wXWrOdI7RGvfED99eSt9I1EqCgP804cnWpkIMUrsDX0NO/E4duIR7PQmYIxjlXZ0ipKPYaeeQzEuRvHcgeJah1DOVx2WfIJXkbtMd8pfmYNTNSnU0fWPQcrpK9afWUhHEPQMjzkZOhMdvDH4Oodjh/njpk9TZJw5dV2XWoZNhqTZgV8twO9aTE/kATx6A6Y9RNoeQFFOXoL0qC7uqLmaoXSYhzqeZ+PADjYO7JiwjkCwvHA+99bfREkOzSRd0bmuYi09yUFe699Ob2qQ+9ufzhqjKVDHx2bdzoFIG22x7CzD8QhoPjIyw0A6xUB6mE1Du3Ou51ZdrC25gDtrr520W04IwdxAA38+76P8+ujzbBl6m/7UEP2pITbn4HcrKDR4qzBykJOFEDQH6vnYrNv5ceujHIwdpS3RTdvR7gn7Ottfw0dn3cbWwbffC5wmgZMNXMVQephfHn0sS55gDJa0iJoxomYsqxPvRLTHO/ja3m9OmU2aCiG9gLvr3k+Dt3aKzmHBoupyGopD/Gbbbt53wUKKfMe00EJeN7ctnc9/vvIG/+fnj+AzDPwug4sb63j+7fw9JMfwkze2saujm6F4kpF4kl9t3s1brR3UFRVw94VLqSsKce3COYwkknxv/SZgE1JKAm4Xf3HdpdQXOwFgWcDH769dyYObd7LhQBseXaOmMMi1C+cwFD/WtPF2Vx+/eGsHmqpgqCpp06K6MMhHL17BjvAmrihbPW6ovSDYxOOdL540GJ0MYxm406nynLHAadHsSiTwnV9u4N7rVlBZEsSWkr1HevnBY28yr6GcwCl01p1vODowwp72Xg71DOA1dJbNrqKpsmTS9YVwO63yrrXYme1Y8QeQ6bdGVb1HLzSZxE69gJ3ZjuK+Fc3/CVDK3xnlu7MNaZNX952zMmSlpc91Bk8y0epGRxjLR0u0pwZHRDX7WhJCMCcwlzJXGd85+K1THn8yePUmyv13oIyKihZ5rqA7cj8HB78ISELuNXi0+km3V0Y7zoqMAkrdRawsWkCDv5rX+rexdehthtLhUSJ4BauKFrKmZCllrqJJr4MKdzEfn/1+FgYbeX1gB0cT3cStFG7FoNpTxsqihVxYvIhaTwVpO0NQ92Eo+qTjXV95CbXecnaNHKQ1dpSBdJiEmcSSNi7VoMxVRJO/hpVFi5gXbCCgTa1hpwjBvEADf9R0F3vDh9k8tIeWSBsD6WEytolLMShxFVLnq2BJwRya/HWEcvBbnLEULiicR5GrgNf7t7Nl6G26k/0gnVLeRcVLWF28mFpvJUfjPfg0D7qin1cE7fMFqlC5unwdKSvNE93PkTiFrsvjMZkafT4Ian7eV30jq4pOrjfndxn8+XWX0ReJ0lBciOu4pihVUbhi3mxmlxYxEIujCEFlQQC/y+Ca+U3jSQtNVbhjxSKumt843gmXCxc31rGgMpuv6NE1Cr3Oi73X0Ln7wqWsaaxjKJ5AFYKKggAVwWNNYLqqcs/qpVzSVM9IIomhadQWFpCxLEYSSdyj+ofvu2ABqxqqiaUy2FLiMXQqCwKUBXzsPCpwKTq6otOXGsStGCAEETNOvi02ALa0aIm8zt7wyywIXkmdbwndyRYq3HNwqdPLXImT1D/zPhuklLy0+QDf/fVr9A5GMHQNy7aREhY3VfJHd1zCnNrTE58815BS8qf//Qi6pnLR3DoaK51SXUnQh1s/ubGwc6wzSKsNO/EwdvJlpHXIEY0ch4LiuhIt9DWEcnoZt8zwFxy7EiQID1rB11A9N+e9vZRJzPA/Y8d/AIDQl6MXfiuLbC2tbtK9lwKW8z3Bv0b13ptjPn+Onfg1IBFqA3rpcxNKk47i+jewot8eX6YVfAnF86G8SpjSjmNGvowd/9lx238R1fvhvPf52FhDZAZ+B2nucRYoFejFP0TR5ky9YfZIpAd+B5l+zflTeNGCf4vi+cC053QMjsTjZOfbSHqY7xz8Fp9s/KPxjJOUkr5UHwPpflShUumuIjDK44mbcbqTXSSsxKgnlEGDb1aWro1z/trj3y2lJGP1MpLchKr4CbpXoIrJgwlb2pjSGm/1H+sGsrGx5bGHj/O5o8GUzzXliGHaE0QnTxwj13fnGgvIms/xYypCoExx7Ceb42TjOhRqgSLyG3Nsfy1pT3q8LGljScuxihZazn19t0NKOWrG/AYPdTxBXyp/g+ozhTJXCffU3cGqogtG+WHv/U65sG34bfqTQywsmMP97U+gKSpRM87v1t9OlSd/W62DkTfZPfIchuKj1DWLBaEreL3v5ywKXU2Ze3auTSb9Qc5YxkkIweXLm6gsCbLncDcDI06dtbw4yMp5tZQXn2kV63ODP3/f5bT1DdM5OMJbLUfpC0fxuQw+c8vak27r3BgNp4Tn/yyK505k+lWs+M+RmV2ja9lO9inxMKrvo2dzV94RkNYw+cfvGbBP8AQTud/gZw4CoRxHWJcm0o4iTsH09HTQnezmkc7fUGgUYkoTVahcX3EjXtXDq/3rGc4M41JdvDm4kdVFF1Przc6IiRP4a0IIDK2cUv9Nec1BEQpGDuKriop6is+MsQfOyTqgcn13rrGA05rP2R43n/1VhXLOhAHfKRBCYAidy0svodAI8XjXc+wJ7zvl8s90oKCwqGAeN1ddx8Jg8xnr3vttxYJAI3bAMfm9ueoKDkbbqPNWUuaanoVab/IgzcHLMO0USSuGKpxslzlJuXYqnNG7t6II5jWU01xfhmU7rbWKMjMdY5O18p5ptPePcLBrgCN9Q7T3D+Nzu6isn/7DWQgFodUh1RoU42LM6LdHfcxMwMZKPIriue20s07vdDhdcXkGTjKBtHuOWyAQ6rk3hBTaHMZlGEgjrTakTM+IbQo4b9fr+1+m3lfPlaVXkZJpHmj/Bfsie5kXmM+ReCuXl15Bnbee/lQ/9b563Dm4SpYdw5JxdKU4KwMopUnGHkZTgigztF/vYWpIKUknM0gpcf8W0CTOBoQQLC5YwCxfPa8PbOLp7hcYSA+OS12cSWhCo8go5Jryy7msdA1+zfde0JQHdFUnZaUZTocJ6QFWFy3Fp3lQp2kt5FL9RDJ9aIqBJTOE0z0krQjGKXCKz8prrxAC7Uy+suWBrQNHqfWFKPOc3czW2+09FAd83LZ6IY0VxXhHPfhONWATQkGqdWiBz5FJb3FKd4C0+5HmEYTxLg+czN3k6iDLXlEi7RGkeejYMqUEMYMeVJNBca3CiiqMSQhIcz/YfY5Y5wwgIzP0p/tZEFyIobpQpUaRUcRweghDMSh1lbFleDNtiTZAUuHKzRzojz9Lf+xJ5pV+HfUEFfy01ce+vs/RUPR5gq6Zs4OxpM3Wof0sCDbkFMB8NyMRTfLwd59H2jb3fP7Wcz2d8xaKUAhofq4tX8eFRct5a3Ar20d2cTh6hOFM+JT5S2PwqV7qvDUsK1zE6qIVlLkcTuw7mbYykxhMDfNI54sciXVgIzEUjeWFC7mibDWeSfTbcmFO4CJe77+fgVQbGTtJW2wbdb5lFBjTf0bkHTg5yqdOfV3gnGwCR3Rt7G8pHeNNJ53sZIEYXUcZ5QeM1eCdMYFR0bmxbY7/HodPIMb5FJZ0ljmyBmLce8eUNj8/uIV7m1ZQ6PKiipOn7k8VC2rLWT23FmWU/JZMZzjYPcCC2lMncwshQC13MlCjgRPSnOB3926FNA+B1Q3a1GRqCU6587jWf0d1/Nw/TIU2F6HWjesxycxu7MxeFKVqRm6eqlDxql6GMkPjCsYxM0q5qxyX4qLMVUZboo0yVxkLAgsodhWfwrwULJnEtk9PmX+6sGyLJ7s2Uuctfy9wOgE9bf288tCbFJQEuOfz53o2p4fOg928+vAmbvjYFfjzFFEeQz5dVGOfFRoFXFN+OauLl9OV7OFovJM94f20x4/Sk+wfLeVNHko5PDMIaH5qvTU0B5qY659NhaecEmPyRod3OqQ0se0BFKXwjGfS3xzciSVNfm/W+zEUg97UAE93r2dBsGla5r9+rYRLSj9Mf6qVtJ3AqxZQ6mpAEy7kaNySL/IKnGwpebPvCL86vJ2BVByfZvCJeWtYXFjJN3evp8zj557GFaRti3/e8TwXlTUwP1TOP+94nkpPkJZwP0HdzZ8svIxZgSLu2/ECmqLQGQszlIpzTU0z729YiioEL3Ud4NG2XUQyKep9RXy8eTW1/kKG0wk+u/HXXFU1l9d6WykyvPzh/IsB+Oae9bzcdYAj0UECupu7Zi3j+tr5eR+E6eBHL25mRVMNxmhclkhn+N/nN3HfR/PjeUwGKVNI+zirBOGC6WgY/bZCxrHi96MGPjP1BSkjWPEfc6yspyNcV8CJuk7nAsKH4r0TK/JvgOl410W/6QR2Z1DV3JIWXYkuelM9JKwEh2OHSFgJqtzVXFKylqe7n8S2LRJ2kqSVZG6gGRubgfQALsWFS3GRsBLEzBgBLTD+wmLLBLZMYdsxJBlMexh7QlAvSZitWHYEIWbWUFlXND4/7x70PE103y2QUnL0QA/dR/ooKHnn30eiw3H2bz7E1feenEt6Itr3dVJUEco74BJCUKAHCeoB5vobubz0Yixpk7SS9KcHGU6PMJIJk7YzZGwTRQh0Rcejuik0QhQbhRQaBahCdRoRptlM8E5EJrOD8PDfUBC6D93ITwA3XySsJAuCc6jzOi+ahUaQrUN7ps1H60keJKAXU+mZhy6czjzTTtOV3EfailPqno1Xzc8aKa/AKW2bPN/ZQmOwhL+ctYyBVIwKT3D8s8xxbtwpy8Qc9cZpGenn6qpmfm/uan5yYBO/OLSFv1p6NUkzw2A6zl8suZKBZJxv7H6FhYUVFBpeHmrdzodmL6e5oIz7D23lf/e/wf9dfj0SSWt0CENV+cfl12NJSaHLg6FofHH5DXwkOsRfLrmKRUWVZ7yLREpJOJGiPxwjkkhxuGdwvJWztWeQRGpiPdxObwOZQhgX5BV9S2lhJ19AmsfEyoRSjJihUs75DRsr8RuEsRTFdWVOUrWUcaz4j5GZt8eXCW02irEqDyPdsw8hNFT3tdjJZ5CZbQDIzE7MyNfQ/H+CUBtOqn0lZQqZ2Q0yheJak3MdS1p0JNoZSA+wuvgiepI9mLZFlbuaJt8clAqFQ7GDuBUXt1bdTrFRQtSMErdipO0MO0a2ETPjaELj7rp7R/3RTPpiTzCUeImk2UHa6uHg4BcnKERLbBKZw7i0KlxaFa2xLobSERJWmoPRDuq85awtXczecBtJK83ywrkAbB7ah1d1MSdQy/q+7QR0LwciR/FqHi4uXkSJq4CdIweRwNF4L8PpKPOC9SwrnIMqFA5FO3mlbzs+zc015asIGY4R8Jah/WhCoS3Ww4gZZ2GwgcWhRlSh0J8a4Y2BPfSlhrClxKe5uaHyonPqe3U2YGYsDmw/QiL625a1nt69XUrJL7/+OLd96rppZ6rGuhQVoaDj6HeFjHNsGH6ewkxvw7b7yYtWMU00+ut4pfdNwNGA60r2MZQeoSc5QNx0pCSag7Mm1VQbQ0vkNcKZXlShMzdwMQ3+5bTFtrNz+Bk0YRDUy1hT+iH0PKoUeQVOhqKxtnw2P2p5i4FkjBtq5+P2557k8SnMKm+QxUWVVHiDXFTWwHf3Oi3ZQgiWF9dS6yuk2OWj2OWlKx4mZZkYisbS4mpChocrq+bypa1PEzcd1nuxy8uFpfVZPCZNccqGmqKgT5Mwli+O9g/zk5e20to7xD/+4lmndVSArip8aO1EToed2oAV/ylCm4XiWoPiugyh1gA6jq7QGFHYAvv/s3fegVVcZ9r/nSm3F/Uu1AGJJnovxgaMC7jbuCV2EsdJ1tl4N9kku/vF2SSbtimbnmyKE3fHduICtiGmmWYwvSMEEuq96/aZ8/1xLwIhUYQBl+T5gzJzZubMuTNn3vO+z/u83Rj+v2L4ngd5MiNMRbEtRijnJp1LKUH2RM+DGYt9hpBmT/RcZhN9v4g0kJGyqFGneGIK21q0+G509BCKkyteAO2ciGVxmQ1EOh9Dc1ag2JeAcBEdRxPMdgzf4xi+vwAnDVgLiv1WhFZ4zrNLGYnpacXS7KUJMoCUXdHw4OnimTKIDO2NelqEGyEc0T4IJfa3BSHOQTJUc1CdDxPp+g8wWwGJ6V9BOHwA1X4bwnoVQk3klO6UCWYPMlKJGdqGGXoXadSg2hae1XCyKBamJg6+D6DAVUiB69SYSCmp9lXhM/zclnUHFsVCY6CBp6ueJGSGsKk2BCrx9pkoQqex52VCRjMCvZ/hpAiVZOf1JDmvx6qmUu3bz3NVq7k6dSL5zow+4boj3VV0hnr6DKc9HeUkWjzkOtN5vmo1he4spiaUsKejnHp/C5/Kv5GDXZVsbN7LorSppNkSeKF6DTbVwihvHinWeKYnjuInZS8wLbGkz3Da33GM7e1HWJg6hWSrl+erVmNXreQ403i1dgMe3cXYuEKePfE3FqZNwR6rRC+lJOgPUbazgk2v7aT6SD3dHb2omkpCqpf8MdmMmz2SgrHDsLtOVQporm3jF//6FE3VrSz++Byue2DeWQuPGxGDZ//nNTYv30XKsES++oeHsdpPLa6klISDESoP1rDxlR0c319NV1s3iqLgTXKTU5xJ6dxiikpzccU5+q2OO1u62bpyL8f3VXF8fzUV+6NK6Ye3H+ezMx8b0Jd5t0/lts9f20c7OB2mYdLe3MW7q/axY/U+WuraUTWVzIJUpiway/h5Jf3GAKKF2Z/67itUHa7jy797iNrjjbz0k5X0dvuYeeNEFt0/G1VV2PTaTlY9tZFIOMLcW6Yw77apA841GIL+EC/8eDlVh+rIKclk2ZeX4opz4uv288ovVnFoaxmgzpuSAAAgAElEQVTeJA+LP3EVIycXUlvewDPfeZl3V+6h8kANTq+dJQ8vYPqNk855nY8CpJTReQwQwgWEkdKPlEa0hqCwIoRj0DGXMoKUfpAholI2emy+O11yR8baBZCym1BoJ1L6MM0ODONUXUgh7IgzJErkye+U9CNlJPYttcT6M/C96Qh1UR9oZlXDRlRFIWiEAcmapi2c/F593nnfeQ0niYld9TLMOZrD3RvIdJTQHKykyD2DTEcxm5qfJmj60C9AxPeCDCcBzEnLZ3xiJqvryvjJ/re5u3AiCzOjNaaMWKE/U0o6Qqc4DmHTxIjFlyPSRDuNdxQ0TokCGlKioiBl9N8nuVFh00BTVHRFJWCE0RQVqzpYl0WfKXK5UJKdyrfuXcRXn3iDx+5agK4qIASqcoq7dQoGmE3IUCNG6B2M7v8FxRsVLhRx0TCcDILZjIxUAafrOGko1rmojjs5rxEjuwm3fw6M6qhCttkDnJ5aefqIhDB6fn6aRpKI8n+EM/pga0XoCb86/zWvJIQLxb4E078czEYi3d+Dnt8gtLxoIWHZgwwfOVXOBgAFxTYP1bHsvCn/MrybSOc3kGY70AtmL9GsRhjwNMl2Ip1f4tT4KCAcfeOn2JeguR85+60IFcW2AE12Eun+EZiNQAQZKSfS/V3o/kH0GRFeZCych9lO/xVc1AN0KZFoTSRoBNnUsgFN0aj11VDsLsGqWGP9VrCoaSQ7l6AqLpp736Ao8b9QxLkrqydZvSxInYzrPIVtT8KuWpmfMpEJ8cOJs7h5sXptny5TjjONGzJmYCI51H2CGl8zo7x5uHQ7eWrGIKn3gnxXJtdnTCciDQ52VVIXaCHTnkRzsJMxcYWUeHLItCfj0GxoQkVKSVtjJ3/65l9Y99JWQoEwFquObtUJB8Mc3h5m8/KdPP29V/nM9+7mxk/NP3WvGfG4E5y888ZuXn98PfNum4o73jXoffZ2+Vn51Eaaa9oonVcyoHamrzvAU995mZVPbsTX7Ue3aFjsFiKhCKFAmK1v7uGFn7zBHV9YzP3/eQvqaUk4x/dX8+cfryAcDGOaklDME25GTHo6fZyJkH/wzDHTlGx9cw9PfudlKg7UIITA5rBgGCb7N5fxt2c2MXXROO77j5vIK8nqqx9qRAwaTrRwbG8V61/axvI/rKW5po2gL8TBrccIByPEJbv5+RefwjRMQoEwh989jr8nyNKHr0HTz73orT5Sx5zbpnHtx6/iue+/wpt/XMdtX7ieV3+1iqbqFj713XuoLqvnue+9yie/s4ysonQe+dkDfGXxd/jsj+4nb/QwNMv774G+MpB0tH0aZASX54sE/K8RDKzBMOsRwoPFMgWX6zPolgl93u6osdVJwP8aft/LRML7gQiqmo/Nfj12xx0oanoshA/BwGp6e35NJFLWRzNpb13WrxcO5wO4vd/st80wKvD1Pk0w8BaGUY3AiqYX43Deg9W2EOUMisqc5MnMSX7v9UZVoVPgmUqavYiyri30RNoJmwEsig2XlohAwbzA8N8FGU5h02Bfez0e3cbk5Gx2tFRT74tasxkOD1uaTlDR3UZldytlnc2QHT2uztfJ5sYKFCFYU1fGuMRo6ElKyTvNlcxJL6Al0ENbsJcsVxwe3YYhTTY2HGd0QjrLqw4wNWXYeb1IqhC4dCsH2htItbtxaBbc+qVLvz1pFCnAx+dPwm7R+yIrg6+SBPQz5SSYHf05TINCR7HdgOr+XPSjfF5EogVkzaYLuY1TfTn5t/SB9CFp5v1X2B4EMohqW4DQcjF6fh311MiOc9R501Cs89Dc/3ZB4yfNrlgB3qGEM06OnxE12GR3dItx/hIXQggU+1I04cLo+WVMXPPk+SJgtiJpPccZFODSEaCFECRZk7k+/Qaago0Y0iQzIYscZ+6AdgB2LZc421SEOLvY60kiboLFg64MbHe6ORo5LcTv0Gy4NHs0I1coMYHHKFJihXEFoAn1grgNqbEyLUKK6DGmiU21Mtqbz2u1G9nQvAddaBS5svqOeeuZTax+bgsWm84dX1hAUWkOVruFUDBCS20bezce4fj+aoqnFAwYn2uWzWT1c1uoOlJH2a5KJs4fyPOQUrJ/cxltDZ1YbDozb5wwoM2WFTtZ/ru1SOCGT85nzMzh2J1WwiGDtsYODm0t59C7xymeUjigfmfhuBz+5RcPImNG03M/XMGetw+RU5zBw9+9e8C1EtLjBv4+UnJkx3H+7z+eo6GyhdJ5xcy9dSpxSW6MsMGxfVW8+cQGtq7cQ9Af4su/e2gAh8rX7eeNP73N5GvGMHJKAWue38K2N/ew4g9rUXWV6x6Yx6iphax+bjObXtvJ5uU7WHjvzLMamyeRUZDGuLklJGcmMO36Cax5bhNLP7OQPesPsuzLN5E9IoOEtDg2/mUbNUcbyB6RgcVmQVEEulXH6vh7k8mQRCLH6Or8JlL2YLUvRggn4dBWgoG3kGYHnvgfoGm5sfYmPd0/xd/7FKqWh8P1IEJYCQXfpafnZ4TD+/HG/xghor+3quVid9yNlD78vucwIsdwuj6Dop56pzS9v4fbMKro7vwvQsGtWKyzsdmXImUXwcBbdHV+DZfZhsN5P0Kc+n5fKn5YkjWH3e0rcHUn0mu0s6n5STrDjWhCJ8mWiykjKBdYZ/WCDCcJHO1s5u2GYxjSZGRcKtcPKwHghuxRVPd28p3df6PAk8Sd+aV4LNHJPccVT6O/m+/ufoscdwL3FE4EogNR6EnmT2Xb6AoHua9oMsO9yQgEny2exfPHd7G8+gBj4zO4ryjqVlWFQp4rAX0QV54QgoeLZ/J42TY2NhznvqJJTEvJvaABGCqGZyZT395Ftz9IQVoiEdPEMEycNsspoTvHMhB2zMAbSLMl5skIgAwT9SBE1ZejoTI7KG4ULR/FfgeK7Srg/G7rKDSENhzMs5d8uVCI0x72U1AQahpCi/7WQssjGm4cpB96CUgj5sUaXEJBqJmxc0mEmjFom/4IIWUI1XE/ij4Wo+c3mOEDMYPlZKFbPer1UZJQHLejOm4HcWEEP6G4EXpxzCX9XiDggu4HhLCg2BaiWKZg+F+I8p6MumjIVQaJhl2joVOEFYQNIbwIvRDFdh2Kdd577Gt/qEIly5FNliP7vG3teh42fRjiAqaNwVSQHaqVqnAjASNEWEao9DWQaovva3+23+zcYo7ytD9PYTCeoyoUNKFS4s1jUdoUbKoFmxJ9b03TZOMr2zEiBgvvuYp7v7IU3ar1EeSlKbn2/jkE/aEBITKAgrHDGDWtiH2bjrDyyY2Mm108wIMSCRusf2kbhmEwbs5IsooGJgZsfHUH4VCEOTdP5uNfuwWnx96vDwvvnkXAH8IxSGjLHe+kZGr0QxXoDfYZNE6vg1HTL0zxvqO5m6e/9ypN1a1cs2wGDzx2K3EpXhQl2oepi8cxesZwvnH3z9m1/iCrn9vMLf+0aMB9JqbHccsji0hMi8Ob4OLIjgrqjjcx4aoS7vqX63HFOUjJTmTL67s5tq+agC+E+zzKK4p66qnSNAXTMImEDYyw0TfWQohouwG//+WMR3xwYZqNKEoC8YlPoKrpgECaXXR2/Auh4CbCwW2oag5CCIKB1fh7n8JimYon7r9RYu0djm56en6Ov/cJfD2/w+n+PEKoaNoING0E0uwgFNyIYdRgtV2Dpo/p14dTP0UQX+8ThIJbcHu/gd2+BIQOmDicD9Decie93b/Aap2HqhVeckJ9oXsaqtBpD9Uy1/sgDtVD2Aywt2Mlb9T+iEL3NGzquY33k7ggw8mqatxVMIG7CgaukNwWG/82dv6A7dU97VhUjbvyx5PtGvhGFHmSuCN//IDtYxLSGZMwUEfGa7Hz3Sk3nrWPE5OymZh0/sn/vWLb0Wqe37CbQzVNPPnoMlq6enn3aDUfmz+xr41Qk9Fcn0Q670NGTiCNKjBaosVeZRCIxGK6TlBSEFoBQsvtZ2VfCITiwZL4xCW+w9POLyxorofA9dC526lJWJJeOe/5NPej4H50aJ2QPkCLEr3jxyHD+5CRo0ijmWiJFydCG4aijwUlbUgvm2KZjCXpL0PrzyWAECqoiWiuh5GOu5GRw8hIBdJsixmEKgg7QklAqKlRpXk1lfc7jCqEEuVHXCSKPblsbT3I7ytWoAt10EXQhSJsRtjSeoDK3npagp0sr91MniudRWlTz3qMicRvBCjrqiZiGthUC6VxhRS4op7wcDjqyfL1+FG0U5lQQgiEKrA5rdicg7+jdpeNWUsncmhbOUe2H+PEodoBhcWrDtdxbF8Vmq4x6erRuLwDDbBIKNoHf2+wn3jwyT5YHZbL5jmRUkb7v+M48alerrl7JglpcX37hRBousaoqUWMmlbIjjUHWP+Xbdz4qfnoVv20dpBZkEpCanQBkzU8HYfbRntjJ6NnjsDujhp9aTnJWO06/p4gvu7z14trON7E0Z0VmKZk55oDDJ+Qj81pZcTkAja/up2krETqjzfS09FLWm5yzIhSsNgs1JY3kpydhNWmY/07EwN1OO9DVbP7RGuFmojFOrcvdAcmUpoE/K8BKjbHzahqdp/FI9R47I5bCfrfIBhci91xB6qW2fdsyjOmpbPNwYbRRCiwFkXNxO64ud/3TlUzsdoW4Ov9PeHQDtTz8FMvBqrQKHQPnB9mp3yMgNGDTXWhXOCcdHnrPnwEjfzXtx/itpljeWrdTgDiXXZ2HKvpZzhFIRDChtBHgD7iynf0AhAORXjliU0UjsqkdPrFP6i9XX5eenwDN90/C0/8hYQYh4JTHB8hLAjLRLCcOdYfXgjFg7BMAcuU97srlwzjYsaIRek/vWQ7Uvl0wVI6wj1YVQsu1Y4iBFbVwkMFS0iJeZ9ynek8VLAETahcnTrplA4PgpsyZ2NVLVEPtDONRIuHifHR98umWhDAtelT+zxOqlC4NWsedtVKR6ib8p5aJiQMJ1530xBs40+Vb/LYqI+jCpVxs0dy4mAtm5fvJCE1jkX3zSYpMx7dcv46lIoiGDWtiMyCVOoqmti19iB5o7JQYtm30pQc3n6cpuo2UrISKJlWNCiBfNzskexcs5+9Gw7z+8deZMlDV5OWm4TFovdxiS4XjIjB8f3VdLf1kjQ6geTMBHoH4UZFwgapOVEvd3tTF+1NXaRkJ/btV1QVb5K7j3Rud9r67jU5MwE1NiZCEVjtVvw9QQK+c4fLFVVh5NQi9qw/yCu/WkV8ipc7vnQjQghu+ty1/PmHr/G/n/ktNpeNq++eRdbw6OJbUQTXPjCPFb9bzdrnN3PLI4sZM3vkex+sDw0saPoozlx0KUo8IJAyCJiYZjuGUYOixKFp+QOyfDUtH0WJxzQaMYwaVG1oGd8yJlAciRxHCCttLbcPaGPE6A6GUTOkc18oTGlQ5z9CS7ASM1Z4XaAw3DMTpzY0oenLZjjZNZ3SxEzs2sDQTnFcKpnOuEGO+uCjvcdPYVoiVi06dKHwpSXrXklIKamvaiUl4z2qkwuBy2NH1T5AxPJ/4H2BEAKP7hw0vV8RgjR7Imn2xAH7cpynwlYOzUaOFv1/srX/PHH6sdmOwRV/TxpgJ/uTHjtmf8dxAkaIWUljsakWyrtr2NS8j5AZwa6q3PzZhTRUNrNr3UH+/OMVrPjDOqYtHsf068dTMHYYqcOSzmpACSHILc5kzKwRVJXV8+5be5l3+1SSYu9WT6eP7av3EQqGKBqfO8AbdRLXfmwO5XtOsG3VXlb8YS1rX3iH0rnFzLl5MoXjckjPS+kzPC41wsEIteXRkkUV+6v55KR/H1wlQ0YJ5BA1tno7fdDPcBLYXdZ+/xdCoGpqvwxCAX3GoDTOncZeMC6HR3/1yWhbKUGIPo5XQnocn/7+vX0GtqL210266s4ZzL19WnTfIBmEH2VEs9oGo36cWTLJF/V2C0ssC+9MRLPwoll0A43pC4Epu4EQQsTFsvTONM6GgzYcdVDayHvHse5t7Gpfjir0WL1HFVNGKHAPfdF62QynJJuLT8cEKs/EYCG6DwtGDUvjuY17aOnu5Z0jJ9hxrIbSvAvjt3wQcHJyudB9J/kVg+HkPofLys0f7y9Md67rnO1cH1S0dPTw1Ovb8Z2WhTRrfD4zS/NQ3+eJ2JSS3Ydr2bD7GEvnjiYn/aOrTvxekelIxq07+O2xVwGISIMFqZOwq1aEEKQOS+RzP7iXTa/t4M0n3qbqSD1vPRslMBeMHca826Yy99Ypg4bYADSLxowbJvLWs5sp21lJzdF6EtOjhl97UycHthxFVVVmXD8B3TL41OuKc/Dw95ZROq+EN//0Nkd3VbD5tZ1sf2sfeSVZzLhhAovum403yX3Jf2fTMPF1R7OidatOfMr5a3DGJ3v6vGonIRADtkGsbulF1i49Gaoc6j6IGmdDrWv20cHJRKXztdJAqGAaSAbLtjRj21Uu1mw4qWmo62PwJvwMzkLEvlw1PJuDFYyJWxjTp5PkOEt5t+2vhM3zh4nPxJUt0f4RwLI5pby67SA2XePVbQeZNmIYt84Yc/4DPyAI+EM8/+u1lO2rIT07ga726OrBNCXlB2pZ+cI2muo6yMpLZun9M0jNSiAUjPDS79dzZG8NUkomzCzi2tunYHNY2LhyH288txWbw8pnH1tKUmpUIM7XE+T536yhqryJtqZuTNNk2WevJn1YAitfeBeLTaficD1ur4N7/3kBmTnvneB+uWCa0Nrho7a5k6a2bprbe0iKdzJjXO773TVMU7Jmexkvr93HsNQ4ctKHVjH87wlxuotP5t+I3wgikehC6yeXIIQgJTuRJQ9dzdxbpnBwWzmrntpI2a5KDm4tp2xXJTvW7Oez37+HpIz4QQ2AMTOHkzcqi0PbjrH2ha2MnTUSoQi2rtxDV2sPaTlJTLzm7MrKQgjiU7wsvHcW068vpWxnJauf3cz+zWWU763i+L5qdq0/xMPfWUZO8SUu2RPzCgHklWTytaf/CfU8EgFCUXB5zwjPi8GTA/6BDy4UNQlFScGIVGNG6kAb2S9cZxoNSLMTRUlAUZPPOPp04+xsi2xQhBdFSSMSKQc0FOXCiNiXCppixZQGDs1LY+AYERnCMIOELqJM1D8MpyFACEG8y87H5k/k/qsm9G37MGHzqv1UH2vms/9vKe2t3fzsa39lNtDd6WPFM1sYP7OI0ZPy+NtftvPC79bzT1+/maryRnZuPMrnv3kLFluUzGmxRh+d2deOZfSkPL79+acxT3O3b1t3mI7WXr7y47vZvbmct9/Yy4SZRdRUNrNjQxl3PnwVN94zg1ee2MSqF97lgS8ufp9G5PxISXDxzc9eB8Drmw7yrd+ufJ97dAqqIlg4bSRxbjtTx+S+3935QEMIgVOz4TxPTTtVU0lIi2PWkklMWzyesp0VrH5+CyuffJsty3cxbHg6H//arYMeq+kqi+6bzeHtx9m6cg9tjZ14Elxs+Ot2AObcPBm76/ySEqqqEJfkYcrCsUy6ZjTH91Wz7qWtvP6Hdexed5AXf/oGX/jZA+fVPhoKVE0hLjmaiReJGAhVIT7l708p2zANuiM9+Aw/QTOEYRqYl0ER+1xIsMSTZL1yiyAhbFht8wkG1xEMrkG3TkOJlauSMkIwuBbDaMBmW4im5pxxtB4lessIptk88OTRK6CoyVis0wj43yDgewm7c9kZ3iWJNE+GCy+9hzDTXkJPpJUkaw5lXZt4q/6XaIoVhzp02tBHynDq6ehl5ZMbCAfD3PXFs2fgXSyklDR29LB8+yEaO3owzejL5HXYeOSGmR8KI+rInmrGTc0nKz+Z5Iw48kZEuSS9XX52bSmnsbaddct309XeSzAQQUpJWlYCSWlenvvVGqYvGMWUucX9iKqD3beiCIyIQSgYIRQMo1u0Pk5C+rBESqcXkpwex4ixWWxbd/jK3PxHEEIIxhZlMLbowxMu/jBB01VKphaSPSKdtoYOtqzYxdY395zVcAIYPb2IjPwUmqpa2fHWPoaNzKC+ogl3vJMJ80cP0F86HxRFoXBcDllFafi6/Lz++Hq2v7U/ulA5m+EkTjkMzFgJrPPNTxarTs7ITBRVoaO5m8oDNX2ZcR9VSCkxMfFF/JT3VHCg6zC1/nq6w72EzBARGcGU5jnK+l4eLEy7iuvTF1zRa9rs1xPwv4rf/1cQFmz2pTEdp434ev6AEFYcrgcQSn9RWyHsaFoBAfk6vt4nQdhRlVRM2YWixKOqudFwqvDgcNxNOLSTnu6fEDEqsVrnIoQT02wlHN6DNDtwub+EUC+90ZhmL0LKAoRQmJJ0O12hRlx6Im596NGOIRtOhmnSEe4lYIQHPEwKgnT74C7sK4Hu9l42vvwu4VDkshhOAL94fRNWXWfUsNS+zB2H9UNWYPS0n0dVoxOvaUqS073c/4WFfWTxk6ROl9fOF759G0f31bD6lV3s3HiUB7+0GPeZLvrTMOWqkax5ZSf/++8vkJmbzF0PX9WnkuxwWftCAoqq9BFNrwTqW7qob+6kcFgymqpQVd9Oty+IpiqkJXlIiXe9J/JtxDA4cKyBiGEyrigD7bTMKSkldc2dVDV0UJidRFLcqVIEUkraunzUNXfiC4SRZv+3S1EEo/LTcDmilby7egMcPN7Y79ojcpKJ9wzk33R2+ymvaSE7NY44t5265i5aOnoxTROXw0pWShxup/Uj/YE8H4xINCVb0wefEh0uG+l5KQD9PKtnQghBclYiU68t5eVf/Y1tq/ZSe6wRf0+AideMPmd4zTSimnCarg7axmq3kFWY1tf2XB9zoQicnuj72dXaS2+Xf2BIbZBjSqYVklWURnWM31UwdthZ+VSRmHzDpfR6XUmEzDC1/no2NG9hW9tOOsJd74uRNBh6Ir3nb3SJIUQc3rj/obvrhwT8y/H3RoumC+FE1QpxuR9F08cOcpyC3bmMcPgAodA7BFvvi5VRseFy/TMO16f62unWGXjjf0J31/cJ+F7G3/tktAyM0BFKHBbL1AEZfZcK/kgXlb076Y20n/IgBmC09+ohG09DMpxCZoQ/n9jCjrbjdIf9Ax4vh2rhfyd9HPV9im+Hg9GyBJfz8i1dPr525zWkJ5yfOPlBxPCx2WxZfZAJs4bT1d5LxZF6pl1dgttrJyHZQ/mBOlIzE/D1BoiEDOKT3DTWttPbFSArP5n5S8fz/K/X0NMV6DOcpJRIJKfzwQO9IRCCz3/zVuISr2ws+1xYv6OcJ5Zv49O3zqS6sYO3th6hpaMHi6YxIi+FOxdOYHZp/kUbT75AmO/+8S26ewM88+2P4Tkj5fxv7xzhVy9u4rGHrmXxzGIgarTuK6/nmTe3s/doHf5gmGAo0mdQ2qwaGUlevvW563HFNGiq6tv51u9W0uMLEghFMzu/+/kbmTdxoKzEkRNNfP03b3Lz/LF4nDaWb9jPifp2DMMk0etk2phcHlg6lbTES084/rCgvbGD5b9fy/AJeRSNzyUpPb7Pqxr0Bdm76QhbVkQV64unnlu6w2q3MH5uMWv+vIWKAzXUHW9CKILR04cPUNk+HV1tPSz//VqGjUinqDSX1GFJfSTrcDDMkZ0VrHnhHQBGTMo/Z2KCpmtkD09DUQQtdW2se/EdFtw9C6vd0iemGYkYWPrpLwlyS7KYf8c0nvz2y2x6bQcWm851D8wlZ2QmVke09EtrQwcV+2s4vP04826dQt7oy6+fd6nhi/h5s2E1G1reoSEwlMoLHxYIHM6PYdpbUNWBQqu6Phq39zF0fRwnM+yimY85eOK+RTi0G8OoBGmiqKnolnEoSvrZRWrVNDxx3yUc2oZhNMUyJj3olv6JYEIo6JYpxCX8mnB4L6ZRh5ShmHGWha6NRIg4Dh6pIxSKMHZU9pA9tGfDka4NtASryLCP6NO0gqi+01AxpCPeqt/HUxUbGOnJYGJCfl/xzpOwKNr7SgkMBcOEQ+F+YmyXGvlpiRyoasRu1fsmLiHAabV8KD46MxeNpvpYE7/8xisMK0hm6vxibHYdd5yTuz4zn1UvvssPv/JnHC4bVy8dT+6INHo6/bz0+/V0tftwee1cf/d0UtK9dLX38sJv13N0fw2drb38+KsvUFw6jPsfXUTAH6KzrYf//vxTaLpK/sgMbvrYTHRdwxPvRIllwVht+mXQfjo3/MEwf3xtG6nxLj5x0zQSvA4OlDfwwurdfP+Pb5HxxVsYnpNyxfrT0e3np8+up6q+jUeWzWX8iEx6/EF+//I7bNpTwb2LJ7F03hjiPafGaURuCr/72jLCEYNn39zBX9bsPec1JJLX3t6PrqrMnVTIp2+ZSWePnxdX72H5xgNYLCqP3j2vX+2zDwN6I50oQsOuDpQ/GAr8vUFWPL6O5b9bi8Njw53gxpPgQpombQ2dtDd30tvpJ7ckk5s/c/4QyugZw8kZmcG+TWUAJKbFMXnBmHOmw4cCYda+8A4dTV3Y3Tbc8S7iktwgoL2xk/amLrrbe8ksSOXWRxadk7itKIJxc4opLM3l6K5K/vD1l1jx+3UkpHkJBsL0tPey8J5ZA1S/dYvGkoeuoaWundXPbeGtZzexbeUebE4rukUjHDKIhCL4ewMEfCFK53y4NJGklLSHOniq6kW2t+0mLAev1/dhhxACm/26s+7X9AI0vWDQfYriwWqbA8zpt900JS2t3Xg9diyDZIWqahLqOa55et9UNRlVvXrQ/VJKGpu6CAbDjBmVxaXyhMRbM+gKNxNvzUA/LdyoXUBR3zMxJMNpW2s5pfE5fH3sHViVwQ8dqvFgGiZtDeer4XZhaKltI9AbuqyGkwB+snwjeSkJuO3R1X+c08YXb5572a55KWGzW/j4v147YLsQgvyR6Tz8n0sGbC8oyeDffrhswHZ3nIMHvzSQ1B30h/njj97k3kcWMHxMFsFAmKd//hYHdlYy97pxfPZrS/vaTpozgklzTgqEKgh9LIrj1LWEmnvxN3sWRAwTh03ni/fPpyA76qKdOsiP20cAACAASURBVDoXj9PKL1/YxNNv7OCxh669ZCud86GirpX9x+pZMnc0i2cWo8W8DPcsnkTZiWb2HK3lkzdP76cibdE10pM8GIaJ13VhhXR7fEH+6c45LJk7GjV2byPzUnnkey+xZttRPnf7bOyXSSPockAiebdtFRn2fIa735soqjfJzeybJlO2s4LW+g6qDtcSCRkxTSIbSRnxzL15Ctd/Yh45xZnnnedsTitX3zmDvRuPIE3JyMn55Iw8t2ig02tn1pJJ7F5/kJa6dmrLG6g8GC2ya3daSUiLY9I1Y7jhE1cxYlLeOc8lhCBvVBYPfftOXvjfNyjfc4LqsnpOHK7DatOJT/VisQ+e9u1w2/jEN+6gZEoh6/6yjcoDNbQ1dhIKhNF0DXe8g+zh6eSNyiajYHAtrQ8ipJR0hLt48sSf2da264oTvj/sCATD/OnZzdxzxzTSUy9v0sC8WZdeNDpk+GkOVtDb3t6vAsKM5GVYLEPjiA7JcJJIMh0JWAcp3nmx6O3y8e2P/xJ5CXguvp4AbY0duBPe2+rzXLh6XCGzR/WftE6KYX4YcK7f7VzifkPZbkqJrzcYI6VCa1MXnW29OGPZRKcf1//fKqptAart8pIiBYIROSlkp5/i42mqoHREFulJHspONNHe7SPRe/meo9PR3hWVhEhLdKOIUzo3TrsFp8NCZ0+AiGGiD6I0PRQkxbmYPT6/zzADSPA4yMtMYO/ROnr9Qey297bokFJS4yujPdxI0AhwwneQTHshUxKvRUGlyneYPR3rkZgUe6ZR6CpFAHX+Y+zv3Ex3pJ1kaxYT4q/GpUWzXdpC9exoX01nqAWvJYkJ8Vfj0RJY3fQMR7q2c7R7JzvbVlPgLmVS/DX93PAXCne8k4f++06aa9robOnG1xPAiBgIRWCzW/EmuUnPS8Z2geU6omGvqIElkcy7fdp5lb+dHgf3fmUJC+6ZGe1Dd4BIOIIQAqvdgifBRVpuMk7PhRnKQkTVzDN+mkp9RRM9nT6kKdEtGq44J2nnkACxO61cdcc0SueV0FTVQk+nj3Aogqap2N12ElK9JGXEo1tPzX1Oj51l/3o9iz82h5yRpz5EukXnM9+7m0BvkKLxpzKyLHYL//rLBwkFwmQWDgwnXWpIJKsb17O9fc/ftdEkpeRoeSOvv7WPUDDC1En5zJ5RhJTwzAtbGTMqi3Gjsyg/3sSGLUdZdusUjhxtYMXf9rF9ZyVNzd0kxDu4ZclEivJT6OoO8Na6gxw52sCwrEQWzi8hOcnNlm3HCAQiVFa10NDURemYLBZcVYKmqbS29bJqzQGOVzbjcdtYcNUoRg6Plsz6zePrqa3vYM7M4cyfPRJVjeoFNjV38+bq/dTUtjGiMI2FV4/C7bKx5u3DqIpC2bFG2tp7mDwhjzkzhqOf4ZENmX7yXZMYG7fojFDd0HWjhvTFn5iQz5qG/bQGu0m0Xho+RCRscPCdowxRL/F9gRCC8flDk5r/e4TdYeFjjy7i9ee28sbz23B77Sy4ZSJjpxZ8IMKZqipISXBjOcMQSfA6SPA6qGvupLmt54oZTpkpXqy6xuHKJnr8QbwuO6YpOdHQTnunj/Ejs/oZOxeLpDgnSXH970lVFBy26MQRipF93yu6Im283fwXZiXdxMykpUhMBAr1/uNsbH6ZGUk3ogqNt5tfAqDINR5V6OQ6R+HVE3m3bRW72tcyK/kmusNtvFL7a4o9UxjrnY3f6MGmONAVC7OTb6E91ESJZyqF7vHowsrFuvWFENgcVrKHp5M9fGCtzKFCSsmm5TuRpkneqCxGnYcXdRK6VSerMK2PBP5eIYQgIdVLwkV4CIZ6rG7VGTl5YPhH1RRK5xYP2K7pKpOuuXIaeBW9J3i9YTUReWHVHlShoAsdTdFQ3kONxouBTbl89fQqT7Tw5PNbWHJdKU6nlWf+vBWAOTOHUzwinVdf343VovHK67uYPCEPq1WjeEQ68fFOqmva+MR9s0hN8eB0WDBNycvLdxEKR7j9pkls3V7B409v4tHPLqCuvoPlK/fyiftmMWVSHo8/tYn4OCdTJuaxas0B2tp7uPv2qTQ1R8N/J3H/shm8snwXJ6pb+3jUgUCYPz6ziYy0OG5dOonV6w7x1PPv8PCDc6mqbmXztmM8eO8s7DadJ57bQmK8k9Iz1PntmocDrWs43rMdTVj6poq5KQ+SaB0aT29IhtMITwav1GznOwdeZlJiAXEWZ79pShcqV6WNHrQy+fmQnJnAzCWT0CwXv6purW9n25t7Lvr4f+DSQAhBYUkmn//GLe93VwaFQKBrAzOXNFVFjWX5hSKXxog4E4Mpqg9LS2D+lCLWbi/np8+9TUFWEj5/iLXbj6KpKrddU3pJDE67Vb9ihmuSNZORnsnYTuMeHe/dh8/oorxnNwC9kS5qfUcpco3HqXloDFbR0F1Jb6STWLoBVb5D2FQHUxMXDyjA6VA9aMKCVXX2eac+KGipbWf7W/sQQjD9+vE4z5PR9g9cXoTNMKsbNxAwzq0SrQqVLHsGBa5c0m2puHUXVsU6gM97uZFuu3wh0INH6mlq6WbnniqEEHT3BNhzoIY5M4czpiSLsvJGHn96I4X5KUyfUoCiKFitCh63DU1T8HjsxMWe52AowtubyyjITWbthiO0tfWwa1913yJsRFEas6YXAVCQn0xjUxdCQGqKh8Nl9Rw4VMvkiXmkJnv65ia7Tcdi1egNhPr63NUdoKGxi/vumk5GWhyqIvjxL/+GPxDlqI0pyWT6lAIiEYPMjHha2noG3HemvYSE9IHlXDz60PmsQ3oaltfupDHQSWVPEwe7atFF//w5h2ZlXuqoi0onzCnJ5N5/v+ms1ccvBGU7KyjbUXHRx3/YYZg9NHT+lK7ABhKcN5Hq+fT73aUPJEwpCYTCA7RtwpEI4YiBoipYz1IS40IhJYOK6PoCA8moDpvOJ5ZOo6mtm7d3HGPXoRosFpVR+elcP3sU4y6BRpMArhBlCwCH6u5n6EgkQdNHvCWVfOcYEJDvGkOcnkJEhljV8BSJlnQK3aUAdIZbAAiZAayKvR8n4YMMKSUBX5DVz2+mpqyBjPxUJi8c+6FN2f+ooMZXR1l3+VmlBhQUhjkyWZp5HYWuXFyaC6vy4Uj4GQqklPj9IZIS3YwfOwxFEUwYN4zkWLanpit4PXZq69qZMC7njHlw4FhIGc3OHFWcQWZMxmbB/FHYYjzjxIRTGdWaqmKYJkIIZk0rJDM9nk1bj/LDn63irlsnM2FczlnH2x8IIQRYYu+R1apHJVtiP2fiaZnb6lkkbhyaF4fW33t6pGsDIEi0Dq0+3pC+DstyZ3Bj5tlJmKoQF+VtAvAkuLHY9LPWcLoQOFy2Pq2gv0dITIKRGvzhg4SNae9PH6SkI3SC1mAZVtVDur20X9ZCNKulAl1x4NJSL3piklLSFiynPVSBXUsg1TYWTbmwWLVpmjS2dhMIRbCflkjQ0uGjrbMXp81CavzFSSgIARZNxRcIY5j9eRRSQnlNy4BjDMPk7V3HqKxr5/v/vIRxI6Lh4NPYXxfVl/cTYpAaWam2XBoClcRZUnBobgKGD6tix5AGraE6JiUsIM6SQk+kEyMWTkmx5bCrfS11/uMkWtMIm0F0xYZNdSAQWBQrXeEWAoYPVaho4sp/7MLBMLvXHyISNohEDPZuOMzq57dgRAwW3DOT4eNzP3If4MuBSMRAStA05ZKOl5SSCl8VTcGB7x6ALnRmJk3h9uylxOvej3zJmGHZiWzbWUFykpukRBc+XwhrjKt2tLyRrTuO88inr+H1v+1l194qJozLQVFEn0HS3t6L123HYlFRFYXC/BRCYYPC/BRMUxIMhvsSawb7HaWE9g4fyUkubr9pEn99bSc7dp+gdMywU1m9Zyw8E+JdWHSVQ0fqGTtaZe/+atLTvH2czLM9L2EzSNgMYFc9hEzfGeVVJPX+o7i0yyyAmWFPQNpk7JKncLLLF/uwC0XBHe88L3nyfNCtGrpV71P0/gfeHwggaHRxqONlEjIKz0j3lFT1bsKrZ+Ny9XdHR8wgilBRztDVMKWBKcOo4kyRRkFvpJmjXSuZl1ZwwYaTBA5VNHK8poWS/CiXJGKY7DxcTUNrN4umj8RzgZlqZ0JVFFIS3Bw50cT+Y/XMKs3v23eoooHDlY0DjgmGo6KZRkyQ0jRMFEXpe8eEiK6sPiwf38GMJoGg0DWOtlA9qxqeQCBwafFMTlxIoiWDPOcoNjT/BZcWhxAqdjVquKbb8hgTN4t1Tc+jCBWXFsfkhEWk2aPGSLF3Ku+0vE5V72GKPVMZ5R28sPjlhL83yO8fe5HGqpaoWn4gjKIqzLttCos/PrdP7PUfODuklGzdXkE4bDBn5vBLqoEYlhGqfbWEz8JtGhtXwh3ZS4m3fLDCvZcDQghGl2RSXdvG409vAilxu+0sWTwOm03n5RW7mDw+jwnjhhEIhHh91T6KClLxeuzYrBqjSzL507ObyUiL4+YbJ5CdGc/NN0xgxaq9/PDnq9BUhTGjsliyeBwI0e93FCI6K5imyTvvHmfX3ioQoGsqN147DkURHD3eyIo393LwSD3hcIS29l4WXlXCmFFZXL9oLGs3HGHlmgPYrDo33zAhaqAJ0c/QPXkdgFrfQQ50rmZh+iMc7nqbQ53r+o1HZ7iRIvfQnQxDy6qTkpZgN2sa9rOu6QBNgS6cmpVJiQVclzGePGfKkKvFexJc/Hb7t3HHO9+TtwnA6oim7IZOi43+A1cWQgjirLloioOKnnWDtWB03O0DMp8kkv3tz5PpnEKybWS/7e2hCup8OxjpXYIu7H3XSbQVogiVet+uIfVRVRT8wTDf++NqrptVQkq8iwPHG/jr2r0keBzcs3hS34opYpi0dvTSGwhhGCb1zV1IoKWjl6NVLVh0FU1VyEz2omkqNovGnAmFbD9YzQ+eXMvRqhaGpcdzoq6VNe8eJcHtoK3T168/Fl1lZG4KG3cd5+Fv/7mPCK4qCknxThZOHcn1s0uIc9sRQhAxDOpbugmHo6HFlo6oynBtUwfl1S2oisBm1UlJcF8SUvlQMdw9kQLXOPQzslVsqpMZiUsIxQeQSFShYlFsCBTmpdxJ2AwgUFBjfBIFBaGoTEpYyFjvHExMFKFgOU2Dpcg1nmH2kZiY6JeRUHsuWKw64+cVU7azgkjEjPI1bxjP5IVj/8FtukAEAmE2by0nNcVDdGlz6SynkBmixlc36D6n6uDO7JuIs/z91ORz2C0sva6UBVeNwjRNVFXBbregKoLPfWo+NquOrqvMml7ExPG5OB3R91jXVT5x7ywCwQhCRM8jhKBkZAb5ecmEQrEMUIuGqirceO1YzNM4nffeOQ1FRD1X1y4YzVVzRiKlRNdV7LYo/zI3O4kH7p2FacroEyCI9k1VmDG1kPHjcohEjNgx0evfdeuUPgNNVRU+9bE5ffNepqOYJGsOmrDQFW5iatIdJFlPZXZub3uZi3nWhmSpdEf8/ODQa5R3NzDKm02hO52gEWZnWwXvth7jyyVLGeXNGtLKWNVUsoreexYLRLVY7vnqUszIPzxOH0RIaXKg4yXCpo9s53QSrVHSYMDo5Hj3ao51r6Yn0khN71bS7aWkOcZR2/sulT3raQseI2R049LTyHHOwnYOMrApDRr9+2kJHsaiOMhwTMKlp/WtSjRVYeH0kWiqwvOrdtHc3o1V1xhTmM6dCycwLD2+71wd3T5++ux6th2sIhAI95HGX1m3jxUbD2Cz6DhtFv7v/91JWqIHRVGYO6GA9q5eVmw4yOOvRJWeM1K8zJtYyNiiDP7lRy/36295dTOHK5vIzUwgI8mLzaIhgXDEoLqhnf/762Y6un184ubp2K06bZ0+vvrT12ho7SIQChOOPe8/e24Dv9E2Y7NqjMxL4+ufvvaKZQaehBACTehoDB4y1xQdTRm4TxcW9LN4DFWhYdcGD50qQj3rvisFm9PKp7+z7PwNLxKmKamqbmXfgRo6u/z9PkalY4YxuiQTRRGEwwa791ZRWdWCaUoK8lIYVZyBPabXVN/Qya69VUwan0NZeSM1tW3ousao4gyGF6b2iXNKKens8rN7bxX1jZ3YrDrFI9L7tQmHDbZsLScx0UVGehw791TR1NSF02Fl6uR8UmLFgjs6/Rw6UkdtXQfhcASvx8G4sdlkxfgwfn+IA4frOHyknp27T5CeFhfzroLTYeWWJRP6vieGYXK4rJ7DZQ2EQhGyMuMpHTsM93mKJhumQWuofdB9kxPGk2pL/lCE5qKe9+iC4716nzVNxeMe6Ak9fSw1TcXtOtVGCIHVqmM9QydRUQQOuwXHGbpgZ7az207tt1n1Ph7U6dB1Fa8+uLdfVRVcg3CgT5dQEUL064eu2NBjEY8cZymJ1mE4tVPze4o1D6sy9MXNkAynNQ0HqPW185+jb6XQnYZN1YiYJg2BDn5bvpoXq7ZSMibzfXsILVad4ePPLQw3GKSUmDLKwleEo68yc7SMSAgpg4CCImyIWBgpWmYkjJQBhLAg6B9GktJEEkLKCCdXUAI12vYclZ+lNDGlH5AowkHMuRntByddzUq0tg9Dz5KSMowpA0RrEA3s9+WFIMU2igMdL2BT4/oMJ01YSbAUoAiVOEse8ZZcnFoyAC49DZeWRk+4iWRbCTY1DvU8noXmwCEOdrxItnMGAaOdXa1PMDHxQZx69JymlHgcVu5cNIFrZxTj84dQVYWkOCcJXkc/r6nHaefBm6Zxx8LxZ7scQoh+qt4el407F05g7sRCun1BANwOK6kJbiTw2/93F9mpUcOvqyfAT555m2AozBfunkd+ZmLfaskwTTq6/Tz6g7+y7UAVN80fS1ZKtN7cv39iAeFzZP7ZrToeZ3TCKM5P4weP3oRjEP6fw27hc3fM5v4bJpMUf2WNrPcL2w5Wse9YHZ+48dwu+tMzIM98R0wpeWdfJa9vPkjElHzu1llkpUS9FlUN7WzeW8FN88Zit+qxGoVd/OjZdfhDYb5833xy0i68iGlFZTPf/dEbJMQ7SE+LY/e+ampq2lh6w/ioVo2IGiDPvbSNdW8fIS7OAVLy6uu7mT+3mHvvnI7VqlFX38GTz25m8ztHae/w4XbZqK3v4I1V+3j4k/OYWBol53Z0+PjBz1ZSW9tBUpKL7i4/f31tJ5/82BxmzyhCCEE4HGHN+sO43TakhPqGDlRNoaGxkxHD00hJdiMlvL5yLytX78fjjoZ66uo7+Nvagzz6uQXkDEskGIxwoqqVmtp2en0henoCNDZ2IoTA47b1+Z5C4QhvrNrHK8t343BYsFg0lr+5h4mlOTxw32zivPazzmMGBt2RgVlWqlAp9gxHFx98Xmw0w7SMnkgXJZ7JF/2NlVJiGCYRw8QwZTRBhujzrSgCXVfPGTUyDDNa4klKrFYdVRFIorJCESNaTBoh0FQFXVPPKSIcDhsEwxFURWC16AgRfa/CYQMjVg9SCIGmqeiXgPc2zDluwLZC97TLr+O0q72S8Qm5lMafYr/rCuQ6k5mbUsLjx9dhSnlFs3cuBSRhDjVcR8RoY3jqi9j1kdH7kwYNXT+nsfOXaGoiOQn/g8d+UiHcpLn7D9R2fI80zyOkex/tO1/E6KQ7uIn23pfxhfYTNltRhQO7Xkyc8wa8tqvR1ZRBH4Rg5ASVrf+MKf3kJ/0GRThp971Mh28VgUg5UkbQ1RTiHItIcT+Irl54KqVhdtPc8xQNnT9BVeLI8P4LCc7buFLkYyEEybaROLX+fVaFlRT7KKyKm2TbSFJso/r2efVsEqz5dIdrSXeUoonzc48Od76CXUuMyepL2kPr6QxX4ziNBGhKid2qk5+ZeM5zWXSVgqyhkwetFo2c9ME/jmNPy5I7cqKJirpWrpkynNIRmQOSK9wOGykJblo6eojEPEsWXevjZl0I3A7rWdtrqkJuxqWvRP5BRke3n+rGC6tWcKiykcxk7wB19oaWLp5ZtYMHbphKSryLlPj+WT1Oh7Xfb5mR7OGxTy7iK794DX9waGU+Xnp1J06HhS99YTEJ8U4OHKrl+z9+gxFFaYwcnoaUsOmdcl5fuZfPf+Yapk8tRJqSN/+2j9/+8W1Kx2YzsTQXgMamLvJyk/nW127G47bT3tHLP//bc7y9sYzRxZmomsJTz79DU3M3//nlG8jLScLvD/GbP6zn8ac2UliQQkZa1OiXwJZtx7h/2QweeXg+mqYSCIax9cleSBZdM5r5c4tJTnYjgCNHG/j3r7/EO9uPkTMsEa/Xzs03TqC1rYdjFc3MnF7IPXdMi31wo+aBlJKyo408++et3HLTRG65MeqF2rn7BN/+wQoKC1K5cfHAj+JJmFISMIIDtsfpXlKsp95tKSXdkXYaAzWEzSAuzUuaPQeLYqU30kW9/wRhGSTekkKqNQshFGp85VhVOx2hFkxMUq3ZePQEWkMNSGmSbM1ACIWA4aPeX0m2owhFKDQFa2gPNWNV7KTZhmFXXUgktf5jxOnJNAdrCJpB0m05ePVEqnxH2NW+kZDpR0oTtx5Hlr1wUO/t2cago9PH0Yom9hys4eDReipr2ujpDaIoAo/LRnZGPDMm5jNtQj6Zad5BywMdPtbAf/14Bf5AmK/+07VMGJ3NOzsrWLP5CAfL6uns9uO0WygZnsHcaUVMn5iH22kb9Fu3fPU+fvXEevKGJfGfn78Ou01nw7Zy1m4u43h1M6GQQVK8k7ElWVwzayTjirMGiFq+V1gvslTTkAwnBTibUqWJ/FC4OweDQMWuF9EZeYtQpAa7HuXYGGYPgdBRJGHCRjPBSDVSmjF+jok/dAQwcFhKgJg1b3bQ0PULWnuew/j/7J13YFzHde5/c+t2LHoHSBDsVWyiCkVKpHqxLLnJTXHsuHen+T3HSZzEzpMTO47jxErcY8tNtiSrmmqUKEqU2EmwdxJEr7vYdtu8P3axBIhCgCJVEn9/SMTee+fOzt47c+ac73xHxtCUYnzaFByvn3jmJQasLcR9z1NT+NfoWsUoYyaR0sHzkqTtw/QlH6Un+XBWVVtEkDJNxjlCIrMNwh+a8Hf0ZIbO+I9oj/8XighQVfAFCoO3npfK8oWGEAIpR1cTH+3c8SCRJOxOgrogZmd5DVNCqwjpF1+Z+PyQfZ+SucK+vrN4fsdbujnV3kt9ZVFeqPIPmByyU9bo89ZoulrZ5zGbuP6LJ7fz/puW5r13g8d64yk0VWX2lPJ8ZubgserSAqpLC4a1B1kjdfQso9H7MIiOjn4iET9FhUEURVBSHCYQMOnsjiOEIJOx2bH7FCXFYZYunpotp6MI5s6ppqw0wuatx/OGk8/UWX3lTKIFgSwfsSDA7JmVdPUMYNkOA70Z9u5vYdH8WqZNzXpog0GT5Usb2LT5KIcOt+cNp8Fja1bPzodlgkOU1YUQFJ9VxWHm9Ar8PoN4PJ2XAxGCYf9XFDFs0fY8ya6mZnRD48oV0/MFuBumltIwtZQt245x8w0LUMecGySeHOmd9akmPvWMxz3hxni89b8xFB8RvQhT8VNklON4Fhs6f0fGy+BXg2zrfY6VpbdSF5jBc50PAVBm1pBwYuxjM2sr3snp1FGODezlpsr3Yygmhwd209T/EjWBRk6njrKx6zFKzEqSzgBHBppYWXormjB4vvN3RPVi/GoIDw+/GqBALybhxhlw+nClQ8zpRRXamNIKoyGRyHDfg5t59Jkm4gMjtaySKYu2zhjbm07x3KZDfP7Da5laWzzieZUy+3skUxanWno4eqKT+x7aTCx+ps1U2ub5lw+xddcJrl01m4+/b1WewzS8LYnjSTp7Bmjr7Od363bx4tajZKwzJP6TKYuTLb1s3nGcu99xGTeuyiqPv96JMpMynBYUTuE3Jzexvfc4jeEKdKHi4dGRjrG+fQ/zorXnLUdwLuQnl4k8K2KyGUiCgLGI/tRTpKwmCvxrAXC9flL2AYLmchKZraTsfUiZQQg/Eo+UvQdFBPHpM3LteHQO/JjO+A9RlTA1BX9DNHA9ivAh8UhaOznd91X6Ur9HCJW6oq+jjhFfdb0+Wvu/gSuT1BR+mYhvFaoSREqblL0Pz0uhKRPzFLheko7492iPfQdViVBb9FUKfKsRF9VFLc/6/2jHzkAgEELD9hK40kag5HWAhFBxpI0rbRTpoHDmxZFn560CUaMOnxZldsFtCKHiSRtdCbzuL9tomDWlnCmVRWzYfoSgz2D10kZCfpNYMs2ugy08+fIBPE9y3WUzKY7+gWh8PnA9jw3bj/Dwxj34DI2CkD8/n/TGkvz0ia0cau6kMBzgtpVzuWRGDUdbuvnRI6/wUtNxTrb3EvKb3HXdYq5YMJUfPfoKL+w8yom2Xj73Lw9SV1HIx+64gqJIgJ8/uY1ntx6msaaEj995JeFzlGhxXJeXmk7w6Ma9ZCyH+dMqecfaRYT8Z65rmFJG077THDvRSVlJhCNHO0gkM9TVZN9/23Fp7+jnxMluPvqZnwzjBMXjKRKJM96WQMAgGh3+LvhMjYGBNEjo608SH0jz9Pp9bN52PH+ObTl5DaBBCKCsNExwDO09KSUnT/Xw/MYDHDrawUA8jWW7dPcOTLJShKS5pYeOzhh/8eX784aT9CSxeCpr4I3TnkCgKTqWNzxpyFAM9CEem6b+l0Eo3FD5Xgxh4uGhCo1jib30WB3cXHU3QTXCjr4XeLHrcWpqG5FIKnx1rCq9nX67mydaf8qA00+Nfxo7ejcw4PZTIIpo6n+ZeQUr0BWDTd2/p9JXz4zwJfTbXTzX+TsWRK+g2Mhu7oJalCtKbsrNidnfaVZ4CR3p07jSZkXx9ZNWMg/4DYIBE01VaKgrYd7MKubOrKS0KIzreRw62sEzLx7gyIlOdu5t5vu/2MhXvnDrmEW/Ldvh/ke3k8rY1FQUsvqtM5haW4wnJXsPtfL4s3vo6Irz2NNNRMN+3v+2FRj66OZGT2+Cb/9wPR3dDxPxlAAAIABJREFUcZYuqGfl8kbKSsIkUxYbXjnMxi1HaO+K8/2fbyQa9nPlssYLmnV5PpiU4XRtxXxe6TrE3+z6NbMiVRSaIdKOxYF4K2HNx4cb11xQr5OUkkzK4sDWo7QcaScRS02I+F1YXsC177lyEncSBIx5gELK3pe/t+22YzknKQq+FcftImk14ck0Cn5cL0bGOYlPn4aqhLI7P+c0nfGfIHEoj3yU0vAHhk1QEd8aRFTnRM+fEkutJ5Z6msLgraP2yJVxbLeT+uJ/IuJbPawdQztX2ReByJFzXS9Ge+y/6Ih/D0Otpqrw/1Dgu3pcntWrge2lOZV4kZ7MURJ2B/v7HqbEN5264JX0WSdoSW6hM72PmN2CxKM2eClhPevOrg4s4UD/I3Sk91ETWEaZfy5CCMJaBZ7MsLPnpxQaDdSHrgAUmhOb6MocIG63sr//IUp9s6kJXsrs6B1s7/kRW7t/gCZMTDVMY+R6Atr4YbnXA+Ggjy+872p+9PArbNx5jAfX78ZxXQxdo7ggwJTKYv74tku5ZvmMSWes/gFZNHf08dCGJt6+ZhE1ZVHufeDFPPfivnXbQMAX717L4VNd/HzddsqLwkyrLuFLH7iOj97za/7y/WtoqC7JF0Z+343LWDSjhh8/+gp/++EbCZh6npd217WLmddQyc+f3DaqJ+lsHDzZyaMv7OHum5dTEPLxvYc28djGvbxj7RlO3VtuWcSe/S187Z8fo6oySm9vgmWLp7JsSZbPKUTWm1VbU8Qdty1G04Y+J4KKskj+r6w3Z+w5WlUEqqKweFE9ly1vOOuYwvTG4RIi2jhSCx2dcf7unoeJhHysuXoOleUFmKbGX//DQ+ccl7OhaSqlJWHuvG0J4fBwQy0S8Y/7nYRQ8CnmCMPpbI9Nj9VGqVGFPxe+URkM3/URUEP41RCaolPmq2Zb73ocaaEKjVKzBl0xMBQfilDxpEuhWU2Zr4aDse3UBqaTcgdoDC1AImlNnSThxOiy2gAoMSsxhvA2K311IxMl5CChQgwzqCYKVVW48eq5zGosZ96MqhGE+ssWN3DNFTP5y689yPHmbrY1naK1o5+aIYkyw7ojobWjn8uXTuOLn7iewiHZo5cvaWDJ/Hq+/t11nGrpZd3z+1ixuIG5M6pGNXgc1+N4czcffNcVvOOWJcPI3pcvaeCRp3dz78820N2b4JcPb2XJ/Pp8pt/rhUkZTkHN5HOzb+aFjv1s6j7MoVgrQc3khqqFXF0+l5rASNfe+UJKSaI/yfe//Cs2r9tNf2cMawLcACEEMxZPmZThJAToajm6WkLKPgB4gELS2oXEJaDPJWXsJ5ZajyeTQCFp+zBS2pjaNJQc7yae3ojr9WOoNRT4RxaqFUIQMBflvFvriGdeosB/LYoyelZIxHcVIXPpeYypgqIE8KRNe+xeOuI/QlOKqS36h1x7r95okjlpbEl2N5slmWe9RGG9ClMJU+FfiAB8ata1b6ohCs2pFBj1OSVrDX2Ix21WwW2U+ecjpUNQPzNBR4walpR8mKTThalGUIUJSMJ6FT61gOrAcgQibxhFjXqWl3yUuN2GRBLQijDV7OKxekkjjbUlVJa8cdKPp9eV8hd/tIa27jjxRAZPemiqQtBvUlyQJaxfLE/uZCBlmnTqt9jp9ei+q/H534oQ42c0vRHQ3ZfAZ2jMa6igIORnyawadh1uIWM57D7SyqfesZKqkgJCfpPfv7yf05391JRFc4TUrOLx0LqGmqqgqwqKEBiaOqL48kR/Kiklx1p62H+iI2/MtXXHUFVlmKq9z6ejawqXLZ/JrJmVhIImNdVFeVVnQ9eoqy2hpe0Il13aSDhkngk3yskVcigpCRONBtA0hVVXZgusnmlLTmou2neglVgsxd3vvjxfdqOvL4k9Sk1EIbKLu2O7I7xRQggaG8rY9MoRFsyvYWp9yaS+nyoUCowIMSc+7HPLs4cZUyEtSnemDcezUYWaT+nxq0FSXgLby6AJnT6ri6CWLfcz2P7Ie6rMCi9mQ+fDuLjU+KfljaOoUczsyFIWRgfXKIkmDDyZdQooY9AnhFDwPDeXtCTzYzNRVJRGqCiNjHm8qjzKVZc2cry5G8dxaW7tG9NwgmwG3p03LiJ6VtFpIQTzZ1ax9srZ/PdvN9HWGWPHnmZmNVaMKY9SWVbA7dctHFFk3DA0blg9l+c2HWLr7pM5blYXc2e8+moKrwaTMpyEEJSaEW6vXc5tNUtzFntWLVw5Dyt4PDiWw6+++RjrfvoC0pOUVBcSLgzSdbqXWM8A1dPKMXw6mZRFT1s/yXiKwvICLr1hEctvWDDJuwk0pRBTm0rKPoDlnsZQa4hnNmGoVehaFQFjIX3JR0haezG0apLWbkDi12fmst8gaTUhcXJeqIJRx0MVEXz6VPpTgoxzHMfrxVBGk2NQ8RuzUMTkU60Hy1O0x75Le+xeNLWYKcXfJHheRtjYsJ2j9MS+imXtoaLkJxj6TFShD9NhGoqAVjKMoH02DDVEhX9k0U9FaESNOqLG8KKNZf45o7YjhMhm443Ca6ooiVBRMvbk8XpACEFByD+CgPxGg2MfIDVwL65zGNveja4vQcuHqScOKW2kHEBgIJTXPpNv0HPn5soy5FkAuX/kvSiDQnoXsQK543rMnlLOJ99+Zd4AO5vn1tLaR1fPAKqqZMNvA2mOHe+kuqqQwmgQXVe56soZbNtxgv/8wXNct2Yufr9OKmVx9HgnKy+fMaz0xXgoKgxy47Xz+e9fvMQvf/MKlyysQ9MUBhIZWlr6WHv1HHwTrM5QXBzE8yTHT3RTU11IMmHx5Pq9o5bDME2d6qpCtmw/wfKlDfh82SyrhilZntWyxVN49vn9fO9HG3j7HUsJBUwylsPJ5m7mzKyivm5sb7IudMrNUk4lTw/7fMAeYMBO5P9eUHA5D57+L57q+FU+bDYrvIQq31T2qVt4ofMRwnohhwd2c2XJTWMaOIOoD87iuc6H2NP/CtdX3EVuleSy4ht4qfsJMm4q51kSLIhenitSPTZKjEo29z7N9t7nKDLKqQvMQLuAdAshoHqQ+C8lA4nx6/o11BZTV1006pqiaSpL5tfyuyd30t2bYPf+09x50yI0dXRP0bKF9aNKDUBWxmDlpY1s3X0S23bZ3nTqzWU4QY7EByMKbiadDPtjLSwqnHJBdsftJ7vZvn4vSMlVdyzn5g9eTWl1Eb/850fY8OBmPvC3b2fq3BoS/SmO723mke89TX9XnEtvWMiKm8ZOHR8LqhLB0OpIWk2k7aPoSikpaw+GVoemRPFpDSjCT9LaTjRwLWn7AIoIYGi1eQ+O6/UDEkUJjckfEkKgiggCFc9LIOXoYp1CaDlphPMZS0l/6hkyzkkkFkgXR04si2iiEEJg6I2UFX6Ltq73X9TF5Q94o8CFvPqyx8QIhyPh2HtJJf4L3VyJP/DOC9a7sVBUECCVsdlztI3a8kK2HWhG5rIq502r5OktBymOBDjc3IVlu1QUhXMkZQVd1zje1kNxNIjP0IeV6BkLgzW0zh6dQcL5UG/BtJpi1uW8XA1VJfTGk9g+nUgwa0S7rkdvbwLbdnnymb0YhoqUkmTKZu7sKj7w3myl+lnTK/jIB1fxmwe38vVvPZH34JSXRvLenolACME1q2aRSlk88/x+nniqCUUINC0bvpvMdDRjWjlrVs/mqfV72fDiQQJ+g8WL6lm8qG7EuQG/wc3Xz+dHP3uRf/zGYxiGls22+otbEEJQXlbAR/54Fb95aCvf/Ld1IEFRFYoKgzQ2jJ9ZbCg6dYFqtvTuGPb5gJOg0+rOZYILCvRibq66m5PJA2TcNEVGGYZiYqp+rim7kyMDe8h4SVaW3EJ9MLs5XFy4Km9k+VQ/iwtXE9Gz3DMFhVWlbyFm91Luq83P5Q2heZiKn9b0CQDKzGp0YaAIhSWFV1NijqRiCCGYFpqPIlR6rY5Rye4TRSqdJVyfaumlP5YikcpgWS6243L4WAeQI4GfY04vjAYJ+kc3hISAqvIzJVFOt/XhumO3V10RHXOtEwIa60vzf5843TNuv14LXLCSz62prJbTt5d+YIRRdT7obu2l/UQnxZWFvP9Ld1A5tTSr7VESRlEVQtEAVQ3ZcM60hXXMWjaNv3vPt/nuX95Hw/w6KqaUnuMOw6GIIKY2BZBknKPoagmOFyOiN6IphRhaBbpaRSKzHdcbIOOcQlOLMLXafBtZY0lkFxc5Nhcrq8ckQWgw5q5FnFex5Gz7Nmn7AAFjAYoSIpZaz+ner2CUVODX5046ky6b5deX1bMSKoqInhVePDtbwsOTcaSX3c1lDclwzr3u5tpK59qKIERWg8XzkniyH6SHED4UJXrRuFh/wOShatMxA3dgpX6PGbgdVa0990VnQUoXx9pCJvUQinLxKsAPRW15lNuums/9z+wk4DeYWVdGd38CIeA91y/hvnVb+dpPnqIw5OcdaxZRWZz1SArgXWsv4aHnd7Pu5QO878ZlzJ+W9Q7rmkphxD/syW/u6OOnT2zhcHMX8USGL/3Ho6xe0sgdqxdw/zM7eW77ETp7B/jmz5+jurSAT7/zKmbVl/H+m5bxu+eb6BtIU1oY4l1D+E07dp3ix/e9yGc+tpYZ0ytQhEAi6eyK88W//g3LFk+lvCyCqiosWVTP9GnlJJMZXFeiaVlF6EE+y9zZVfzLPXdRFD3j5VNVhT9+/0pc1yMYyu74dV3l1psWsmrlTFJpC2T2s1DQxMh5w3w+g099dM24mV2GofGB917JHbctxnY8DF2loCBAKmmNmNoURbBgXi1/83/eQjKVAckwz5aiCGZOr+AzH7+WgYE0jpNTvPbphMLjh4tVoTIlWEdICzLgnPEweXg09e/jiuLlmLnsulKzilJzpDcjohdxSeHKEZ/PDJ/5rQzFx6zI4vzfQggaQnNHXKMKlbrgDOqCI721Q68/G6bqG/f4ePBklkj/+Pq9PPncXrp6E2QsO6+XNDiHn/n73PDnFMbHQijoy3tvYwOpcUuhRUK+cVVxogWBrDQF0B9LjX3iODiR2ImKRnVgzquOvFwwwynlZojZyXOfOEEk42kG+pPUzqzKG00Aps9ASkgNSX9UFIWqaeXc/MGrufeLP2f9/Zt415+OTroeC0IIfPo0hDDJ2MdQRRghFPz6dIQw0dUKDK2GjH2UpL0Xx+tDU4owhhhOhloDKNhuB54cqRsCWSPEdtuRuGhKIaq4OJlSBf411BZ+FU8mOCm/RCy9nlM9f01d0dfw6TMm/OBI6ZBIPcZA8iGy4p0GkeB78JnLx7kmQWzgx9jOYaS0UESAouiXUSggY20nlvgRWQNTEgq8Bb/vGjwvRV/82zhuK+ChKiVEI59DFW8cLtL/dggRIhD6PIHQ58+/EZnBsl4m67F6baAqCtcsaeSaJY0jjhWG/XzizuF8yMF3QwjB1UsauXqU62bUlfKlD1w37LPq0gL+4n1rRpwrhOBt1yzkbdeM1BoSQrB8Th3L54z0wgCcbu2lrz/J7NlVeQKuzGnyCEWMEOksiPgpiIwe8vX59GFSAoPXFJ0lfDooOpj9fPRQqqKIYRXpR4MQAp9Px+cb/g6bY5TWUlWFwmiAwjGyR4UQhILmmCGd8frREJxCjb+K/fFDw47t7NtDW7qD+uDkNwFvFkgpOXW6h3/9wbNs3nkimwlYVsDcGZWUFoUoiPgJBkwMXWXPwVZ+/9zeiTV8jiVEUc6kio3nbZoI1CHcKGcSxt1QNCebhpVbeTUY13A6lejmybZdvK32UiJGgMdOb+PoQMeo57an+4nZ52cJjgYpJdKT+R3OIPwhE6Skv2s40U9VFaobKwgVBDiw9eh53dPUpqCIALbbQdLajSL8mHpjdiJRCjG1WlLWXhLpzXheAr+Z9UYNIku81knZh7DdVnS1fJiBIqXEcttI24cBBZ/WiKpcDMNAoKvlaGoUKQuoiv4ZdncLCWsHLf3/RH3RP6OpE+P52M4x4on/Jhr+LIYxL28IjXt34ScUuA1FhJDYdPb8GZa1F5+5goy9CyGCFEa+ALgIEQAUXK+bdGYTxdGvoGl1eN7AefG7/oCLhwvBj5MyhWNNrrbgq8Wr0QUbO3ww8vPzvc94x6ZOKcXvN/jXf3+KeXOq0XWV9o4YO3adZGp9CXNnv75cjzcLCo0CLimcz6GBo7hDwlxJN8VjrU/xwYb3oivam1aLcDzYjsuvH93G5l0nEIpg9YoZvO2mxUypLSYUMPMZiVJKFEVM2HDKKnyPbRBlMk6ezzaajtNQpDPOuCUKk0NkMM4u7TJRFOjlZNxE1ksqh99ssnPbuIZTzE6yufswN1cvJgI817GP/bHTRPWRu5Ckm8HyRq8+fT4wfTq+gEFvZwzHdvMFgIvKo0gpObH/NK7jDqs8rmoKqqrQ2xE7r3v6tKloShTLbcVyW1GVCH59JpDlHAX0OfTxOAOZV/BkgoCxYFgoKeRbQchYQjyzkdbYt6gr/FrOeMqRUWWMnsT9JDLbMdRKooEbL3ooSgiBX59NXdH/41jXx+lPPUlL/z9SHf0iqhI+5/WO04wQAUzjEpQJ1vRxvV4Sqcew7P1ImcFxj+PJOCAI+NZiWXvo7vsSfvMqAv7rQICm1hAKvove/q+j6w0E/behqdlFQUob1zmK9PpR1ApUrS7/ued24HndQAbQEMKHUApRlBIGy+OMDpkNDXrtSC8OWLnrQyhqOYoSZqy3WHpJHOcwYKGq9ShqKVK6SK8Hz+tAyhTZsjhhFLUCIUITejGz3oM0ntuJ5/XnvpOCEEEUpRShRCccZpXSQ8oYntuFlAMg7VzoV0eIAIpSmGtv7DGSMoNj74ZR+BRCCaFqjYhzEFqldJAyjvRieF4Mx96G57UC4Lmt2JmXR71O1WcgxNi8ByklyCSeNzhWNqDmfr9ShBg9OWNYG14SxzkI2KjqNBS1KNd2GtdtQXqx3LjlxkwtRYhI/p2V0sGxd2ZD88JE0xec8/eR0sN1DiG9PhAaqjYj96yNjrmzKvmrP7+Fx59qYvPWY3iepCAaYO3Vc7hm1Wwi5whT/QFZKEJhTdlVvNK9jSOJ48OObe7dTl1bNddWrEZX9P9xxlMyZfP0C/vxPEl1RQGfuHsVZcXhEe+HlAwTsjwXevuTJFPWmB7Aju446VwmfFmOYjMWWtr7cvPf6GN/6nRPPihcWXZ+zoYyXwPPd/yIrsxJInppnos9I7KSkDa56gnjGk7TI5X8/cK7iBpnFsx31V/BdZUjXc57+5v5zsEnJnXz8RAuDlFYXkC8Z4CWI+3Uz84S5mpmVKCbGnteOkjrsU6qG7NeHc/1aDnSQbwvSe0ECJyjQVH8+PRGYqlnAQj5lqMpZ7LAfMZsAJLWLjyZwm/MG3a9wKCi4LNYPW3EUs9xwvsCYd+V6Fo5njdAwtpJX/JRQFAavjunHXXxX1IhsjpVVdE/53TfP9CTeABDraEs/AEUZfxMLiHMXG27iRvFqfSzZKwdFBd8BVUtob37j8jWxhPoWh0lhV8lYzURT/4c1+sgGv4kQhiEA+8iYK4ildlIb+weiqP/gKFPR3p9JGJ/j5V5Fn/wA4QiX8HzekmnfoWVXodjH0DKOEKYCKUITZuOP/QJDPOyUfsnpYNtbSGT+h22tRnPPY2UiSyvSi1H0xfj878V3VwxqmHguieJ930G1zlJqOBL+ALvJZN6iEzqdzj2HjyvJ0vuV6vQjeX4Au9E05eMu5BnF9R9pJO/wra24ronsgad0FCUMjR9Lqbvekz/zYhzlJ2R0iaTehQrsw7H3ofntuSMOZE1wtQSVG0amjYX038rWm5zcDY8t4O+7rtAjgzBa/oSIoX/jqrVjNcTbOsV0okf47onc8ZIN4O06Uz6ITLp0TV9IkU/xDBHSnpkv5+HY20hnfoNjr0T1zmJlEkQBqpSkR0r/1swfNcgxqlD5bonifV+BM9tI1z4r/h8t+G4x0gn78NKr8dzTyFlKmdolqCbl+IPfgxNz4XupM1A/5dw7F0IpZhoyQNo2rRxxgOQKWK9H8V1DqIoFURLfgvjGE6KojBzRiUzZ1yYQuj/mxFQ/dxRcwvfP/pTeuwzyTIpN83DretQhMK15avRlAvGYHlDID6QIpHz2JSXRigfI6tY5sQrJ4rmtj56+5OUFodHcNaklBw+3kk8J77aOKUMXRvbcNpzsBXXk6ij+BGklGzbcyr/9+zG86sCkXT6qfANFpY/E7E6H6L9uE+IoWgUm2fCJUHNpC5QPOyzQZT5IpgTrJszEZTVFFPTWMmO5/ey64X91M2qQghB3cwqqqdVsPeVw9z7l/fxjs/fTGF5AQe3HuP+bz2GnbFpXHj+ccygsZDe5O9y/x6+2Pn1GQjhw3ZPo4hgvjTLIIQQhMzF1BV9jZa+e0hYWxmwtiLQABeJh66WUhb+IMXBd76mxGchNKKBG3G8Xlr67qE9fi+GVkVh4NZx+2Hos1DVYvri/07Afy3SS6GqJejaTKQcwHW7kFi4Xjeu24OiREGoSOnget0kM+tzvKXsgpfKbABcFKUYRYnmswpt5ySWtRtVq0JVy5B4wNkPtMTzYnheNwOxL5NJr8t5BAwQZtbr47Zged0E+PSo3ydrVPyWROwePK+DrEfHzIUMPVznBK5zFCvzHIHQJ/AH7x4zQxIsHPsIqYH/JJn4D6SXyLXlQ2LjOkdybb1IOHoPunHZqB4JKR2s9OMk4t/EdXIcDOHLGUgSz23Fck9gZzZi2zsIhj6LUEbXTJMyRXLgO6QGfoiUfYCR46YFyepuWbjOcVznCBbr0YwFYxpOQgQwzTW4blvOm9aLlDEmY0R77kks68UhbYaQcnDS8iHG8GIKRho82R2pRTp5P8mB7+C5J8n+foNj5eUMtCNY1kv4nffiD/5Jzks03gbFQXp9OM5+Bvr/L7a1jWxyhpZ7rjK47nGEFUAMqRaPMDH9b8exdyO9GJnUo6ihT47rdbLtLbjOcQB0cwXKeRDs/4DzgxCC+QWzua36Bu5vfngYUbzfjnF/88O0pju4sWINpWbx/xgDytA1FEXkS6XYjjtCe8x1PbY3nWLHnuYJt9vZFWfDK4eZWlc8TBVcSkl3b4IXNh8mmbII+A0umVsz4p5Dceh4B9ubTrJsYf2wcjtSSg4e62DrrpMAlBSFmD/7XALQo6M+uJC64EipIjFJFXaYJDn8z+fchjaGa7/EDHNt5YILJtRXUBJm0eo5NB9qxUpZOJaDbupohsbbPnMj9/zJf/LK73fyyrqduUKQ2euKqwpZOynV8OEI+66kKPBWACL+q4cdU0SIktC7ydiHsxwiJTrieiF0QualNJb9N7HUMyStJhyvG0UJ4NOmE/Ffg6GOzUtQlRAF/msIuHPxaVMn1XcFnZBvOYpiEDBGPiCKMCkNvR9PZkhb+0hauyjwr0EV4+14Cykp+FviiV8ST9yHokQJB94BwEDqEdKZl9G1qcSTv0RVyykMf5qAby3SixNL/BhTn080/Klc2E0gUEmkn0bKJLo2nVDgLWTDRz5s9xTJ9LMIxU80/Gl0beSC7rmtDMT+jkz6KXR9Ibp5BZo2E4SB53bkPD6daMZIr6iUDpnUIwz0/w1SxlDVqZj+29HN5QilGOn1ZD0kyfvx3JMkYl9DUUow/beNsRh6WY+JdNH0OZi+m9H0eSB8uO4JMqkHsNLP4rnHGej/WyKF30LTZ3G2l9HOvEi874tI2YtQijF9N2H4rkZRq0BmsK0dZNKP4Fg7SCd+AtIiFPlrEMND5lJKrPR6UokfI2U/mj4P0/82dH0hQgkjZQrXbcG192DnQky6PnaWjlCKCBf+B4MeItc9Rrz30zj2jjGvORum/w4M3835v63MeuK9HwXAF3w3wfCfj37vUb1qkkzqYRKxv0fKGIpalR0rczVCLcmG3qxXyKQfw7GbSMb/DSk9guHPc66pzrH3kU49iGsfxPBdg25cjqrWAALXPYVjN6GopSjqUBK3wDCvIq014jqHsDPr8fx3oo6h7C+lQyb5ENmwooYv8NoV2H61iMVS7Nx9iumN5VSUjx0qyVgOr2w+SiplIYSgvq6YGdPfOHUiNaFxbflqDEXn/uZH6LF688eSboon29ezrXcnV5VexryC2VT6yonq5w77vpERCfuYVlfKgaPtNLf28shTu1m1YjoFYT+O69HdO8CWXSe578FX8KSccDK3ogh++fAW/H6dSxdNyWdrdnYP8NC6nbzwymGEgCXz61gwu5rxnnXPlXzrB8/w/jtXMHdGFeGQiW17HDnRwc8e3ExLex+6pnLr2vkjBDcnDCHozZymI32UMl8DBXo5CaeHoFY8aT2sSRlOvjHEqwCKzTDvnToyXfN8IYRg9dsuZfbyadTPrkYfUkjzkqvn8q4/vYXffPsJ+jpjWU6ZIqieVs67/+I26madP2HSb8xiSsm/jNmnyoJPTajvqghSGLx1zJIqgxjUdhG563S1jKron55Hz7OhxrLwH52jbyoVkY/m7w3ZVNXB+488X6CqpUQjnxxxLBK8i0jwrlHvEwmN3g+/70r8vpGGraaWEQ1/dNy+Azj2DqS9HX/gPfiDH0JRq4YZNVI6SK8XzvJYSClx3VOkEj/MLbpTCEb+CsO3dpjHTTeyhli8/4tIr4dU8sfoxuI8r+psSK8HTV9AqOAf0fRpDE4OmpyHbiwlwVfIpH+H6xwgk34cVZs2LHzkeXGSA99Cyl5AIxj+S3z+24d5YjR9MYbv6qw3JLOBdOoBDPMaTP/1DJ+MHBx7D9LrQShF+EOfwPTdPPz7sRjpuxnpdePJGGIU438QZ56HwWIPKkxqdybymZhn2vQPOWqMy+85G9LrJTnwbaSMIUSYUOQrGL6rGaperhtLMXxriPd9FsfeQzrxE0zfNejGEsabuDPpRwEIhD+HL3DnCH6VlJmsaOeQsRRCoGpV6MbluM5hHHt/zsCqGvVdct3Q5nuoAAAgAElEQVQT2PYuQKLpM1G12RNepF5vtLX3853vPs1HPrR6XMPJdTwOHGrj2PFOmvac5sbr5r+hDKesDqFgZenlhLUwD55+bATnqdvq5cHTj/Nc50tU+sqo9ldSE6ii3CyjyIgS1AKYqonGxSs2qwgF9QJFJAxd45Y18zjZ0sNAIsP3f7GR5zYdHGY4HT3Zjc/UeM/ty/jVo9tIp8ev0iGAS+bV0hdL8f1fbOT36/dSFA0Agq6eAU6c7kFKSUVZhHffvoyiaHDMZ11RBDevmce65/fxL99/htqqQsJBH7bt0tzWS2f3AEIIli6s56Zr5o2pPn4u9GROsbHzZ8TtLmZFVjG7YBV7+p9hdsEqCo3JebEmZTidj8z7q0FRRZSiipETu+HTeesnrueqO5az96VDJGIpSqoLmbVsGpGi0LgktDca1nfs4b7jG/jCrFuZVTAeX2QkpJS40kMVo1ddPxdc6fHT48+zrecof7/wLiL6G7+IrJQJdGMlgfDnUZSRsXohNIQ6moaXxM68kPOW6PgCd2L41owIUwoh0M3VGL7ryCR/gWPvxrY2o6i1Y4yxjj/4x6haA2dnaShKOb7g3dj2Zjy3hUzqMfyBuxHqGZVjK/M0jr0HANN/M77AW0d4W4RQUNUGguEv0pfZAjJJKvE9DN9qhpc88bJcH0Cg5cJzI98FIQRCLUFhbBX3NyIyqQfzYS5f4F0YvutG+f1UVG02gfCfEev5E6TsI5X4cY64PfbGT3o9+IMfHTM0mw3BjkaC9WP6riWTfgTpdZNJP4bhWwUMJ21L6WFbL+O5JwAFw7wWRSnizeJxmij8fp33v+dy2ttj/OPXH329u5OHK10yboaUmybtZei3Y3RmuvJk8LP1qCSSHquXHquXvbGDaEJFFSqKUPK14i4mifymyrXcXn3TBWlLUQTXr56L7Xg88PsddPUMsK3pFFKCpimEAiazp1dw950rqCiLsGn7cQ4ebR+3TQnUVBbyybtXc+/PNrD/SBunWntz+lqCaMRP45QyPviuy5kzvXLc9cnzJEsX1LNsQT33PbSZk6d7SKZtPE9i6CqlxSEuXTSVD911BcWFwfO2P44ObKU+mNXdcjwLTTFIuwOk3YFJtzUpw+nptiYq/FHmRUfG5Q/H2ziR6OLq8rkXva6WEALd0KioL6WifnJCl280WJ5DzE7hjCOYORYk8FDzZlaVz6XEnPjOfSjSrk3cTg3Tg3ljQ8t5BCYrVeBgpZ8mK4EQwTCvHiOjTKAoQXRtLhkMkCkcey+m/xZg5MKpqNWo2oxRQ3nZ53Q+qlqD57bgOgfxvC6UnOEkpY1jbc5mvaFjmNdx9oI7tC1Nm45mLMSxNuE6R3DsA+jDQpJ6zoAz8bwu0okfI0QI3bgw9QlfT0iZznGlHMDE9N3MWN4vIQSaPh9Vm4nrNOHYe3GdE2j6eAraPnyBu8bhs40OIQSasRxNm4FtvYSVeRrPbUfVhvMspUxgZ15EyiSKUoFurBjXkHtDQuT/M/YpQmDoGqahIcYpvPta41D8KE91PEd7upPOTDcxOz6ueOdQSCS2dLDlhcsaPxcy3ugVJc4Xfp/O229ZzLKF9ew52Ep3XwLPkwQDBrVVhUybVkJZQYR0xubOGxdxsqWXhrrxN1a27VJTVcjffP4W9hxs4dipbhLJDD5TZ2pdCXOmV2aFLScAy3JYu3I2c2dWsXv/aU6392PbbtYAm1rGzIZyjHHENicCV1oYSiGedHGwcD0bx8tcfI7TurZdLC6aOqrhdHygk58f38jqsjnnrXg9FK+1d+vNiNZULw+f3sKiwinnbTi92aAoxahq/TnTvkfCw7F3ASCEgaKU4nnjyFYIEyEMpLRyWWn2qB4HRSlBGUeLS4gAijYVrFcAF9c5kidjS68P12kmW6anBFWrGf95Fxq6Ph/H2oSUSVzn0DDDSQgFw1yJbizBtjZhZZ7FcQ6gGyuyXC5jac6bdfFCDBcLntuB52Z3wapaiaKWjfsdhAii6dNxnSY8rxvXPTWu4aRqdSjq+KU7xoKiBDH9t2Nbm5BeL5n0E/iDH873L6tJ14mVeSF7L70RbRQO4mRw+Eg7v3lwK7fctJBXNh9l/4FWIhE/t960iLlzqvOCgX19Cb5z7zPceftS+vqTPPn0HgYG0jRMLeWud6wgEvFnBTX7kjzxZBO7m04hgUXz61i7Zg5FQ3b4AkF/LMlPf/4iTXtOEwiY3HjdPBZfMmWYQOG5IKUknbbZsPEgG186RCplM21aGTffsICqykKEgPsf2IJp6gwMpNm3v4U7bl+CZbk89sQuZs+s5JabFhKa4KIM0JxqYWPXK5Ma4/8psDyHp9t3cV3FIqbUFjN1iEHkeh6bew7zVO9O3l2wEp+ps3bl7Am16+UKPwf8BssWTmHZwinn3UfXy3KrSopCXH356MkqrxY1gXls7v4tRi6TvNc6jSNtwvrkPe8XLG1AAnEnPWEr/lzobO7m5P4Wpsytpbgi+obavZwvpJR0ZPo5PtCJ7blU+qO4Z3maXOnRlY7RnOom4WRQUCjzRagLluJTs7vhPivB0YF2NnUdojsTZ3P3YU4muwBoDFVQE8hmXNmeS3Oyi450jLRrYao6Vf5CagLFwwpUKkKh305xKN5KyrUoNsNMDZbj14x8v5NuhlOJbrqtOK70CKgmU0NlFA8x2KSUDDhpjiU6iFnJbJah5qMmUEyRcUbLyJMezckempPduNKl2IwwNVSGfxwO3SCEEh4zE2vcsfdSeF42Bdnz2unpuPxcVzCobp3VoBrdIygUP5xDy0hRSiFXMCCrOZW7g0zhyViunUgus288qChqRe5aa1hb+XupdYSj3yARvwc7swHPPU0mdT+Z1G9RtZn4/Leim1eh6XPGCD29MSFlHCmzWVBCKc5mUo4DIXSUQSkRmULK/nHPz557/iF+03dDPtMvk3oQX+AdCHFGHDeTfhrpdQIqpu9GhHh1haYTSYtNLx/h+IkupjWUMW9uDYcOt/G1rz/CZz91PcuXTs3OAY7Lnr2ncRwPKSUNU0txXY/+WAqfT0dKSVt7P9/813UkkxmWLskmpDy/8QBbdxznC5+5nrLSbF8zGZuHH91B47Qy5s2t5tjxTu75xuN88mNrWXnFjLyQ4kT6/v0fPs/2nSdYvqyBYMBk5+6TbNt+nD/73I00TC2jtbWPXU2nmD+3lmTS4h+//iiLFtZTXh7hNw9uobIyylVXTrwCwv9mONLlp8eeJ2GneUvtpRhCQ0pJws3wWMtWfn58A++sP/+EqjcLqv1z0EtMmvqfIuH0EtAiLI/eSUAdm+c5Fs5pODmey8lEF7Z0GbBTdKT7ORBrGXZOwsnwfMdeIrr/gj3Ih7Yf55uf/CHTF01hwZUzWXbdAhoWnCky+WZ8YVpSPXx930OcSnRTaAQxFJ0yX2RYmKw11ct/HnqSfbFm/KpJ2rNQUHhn/eXcWr0UTVE5kejk0dNbORhvJW6neKa9iYCWXQRvr1lOTSAbCmrqO8m/HXycuJ3CrxnE7RRRI8jnZt3K/OgZsnPGs/mPQ7+nLdWLI13SrsNba5ZzR90KfKqOBB49vY0Hm19BSommqMTsFIsK6/nY9Buo8GcfvIST5jsHH6ep/xSmopN2bTKezR21l3JX7sV0PY+NXfv52bENxJwUGgq2dLm+ciFvr7+cYK5m1NiYLEE5i6yO0VCjfjLaHe5Z1w6F4JzhC4aGf4aW4vEYLJqbJV5PwBWdDy9KGKVAtBACRa0hVPBVbOtlrPTjZFLrkLIH19lHIr4fNflrTP9t+ILvQ1Eq3hTvkpQOg79ZNsR6rmdAyY+VxM3KVowH8eqED4USwfTdSCpxL65zCjuzCcN3Q25sHTKpR3N9D+cSEl79mCdTGRbMq+GP716JYWj09yf5i//7a57bsJ/5c6sJBLJzQiKRIR5P8dlPXUd1VdaYs20Xw9DwPI8XXzpM8+ke/uqLtzFrZlYvatmSqdzzjcd5bsMB3n7HMgAs22XmjEo+8ZFrCAQMEokMf/WVB3jmuX0sWlBHQcG5s52klBw50s6GjQf5yJ+sZu3VcwA4fmIGX/67B1j//AGm5OgXriv5yIdWs33nCb7+zcdZvKieKy5r5MDBNtra+vA8iaq+8Z/d1xumovOWmmU80Pwyfs3k5qolJN0M3zvyFM+37+GO2hXcUr309e7mRYfEo8w3jTX+xpx6ONheGg8XdZI+pHOenfEcfnD0WY7E22lJ9XIo3sYzbU0jGxIqH5m+FuUCEeY0Q8OxHLY928SuF/bxwHfWMWPxVFa/fQVzL59BYVkE02+8KSZ9yBqg3z/yDL1Wgi/Pfzv1wVJOJbv4xr5H8IZ4nYqMEDdXL+Gj06/Dr5mkXYv/OLSOnx57nrUVCwgrfmYX1NAQKufxlu388sRGPjXzRqYEs2EGUz2zSE8JlvKhaWtpDJejKxqnkt38076H+OWJF5gffXf+vOMDnVxVOoc/nX0bAnj49FZ+cuw55hfWMa+gDgEsK57GzEg1NYEiFKGwvecYX9/3IAui+7mzbgUAW3uOsqX7CJ+ZdQvzo3V4UtKViRMY4rk6mmjnu4fWsaJkBu+uX4mqCF7sPMC/HXycumAp15QPFxW9UMh6qbKLraKUEyr4f0yUmKuoRWN7g6SdN37GgmRoKaKhEgJ63usjscimqY/fkvQG21LG7JMQIrtAm2swjMvxhz6BlV5PJvVrXOcornuM5MC/Y1vbCBd+E1V944srZknwg89RmnMbvi7Sy6ogi5zcxcWFjuG7hkzqd3heG1bmGXTzKoQIYlvb8/pchu+aC1bcOBgwmTO7CsPQEEIQiQS45JJ6duw4yUAikzechBDMn1ebC4Nln/nBUlauK9my/TizZlRSW1uUPz6lvoRZMyp44cVDecPJ59OZM7uSQCA77waDJsuWTOWpZ/bQ25eYkOEEsH3XSfx+nWjEz6nmbKX7dNqmrDTC7j3N+WKwpSVhTFOjuDhMKOijvCyMqipEwj5SaftNxMt8faEKhbfWrsCvGvzixAv0Wgn2x5o5kejkY9NvYFXZXHTlzc2BnAgOxDYQ0cup8mf1F+NOF1u6H2B+9FpKfZOT/jmn4RTUTL48720cHmjj2weeoNxXwKUlw7kCpqIxNVRGXbDkghkys5ZO4xPfeB871u9l38uHaTveyeYnd7H5yV1UTi1j6bXzmX/5TOZeNp3iqsI3vAHVmuplf+w0K0tnsyBajxCCqBHk0pLpPN22O39eQDOHja+UAa4sncX69iacnMKpoWgYioap6ihCEFBNwvrISavQDHFZ6ZkK3AV6gOnhKo7EW4dNOmHdx+21y/Nht9Xlc3m6bTcbO/dnDSchmBoaPtmvKp/Dtw48SlcmhpRZVfCQ7sORHkcG2pgWqqDSH6VoiFiqJyVbu4+Sdm3eWrOcYjMbvru0eDqPhraxvr2J1eVzUS9CtkpWFbwYzz0NCHRz+bjcpInC8+L5TLYxz3FaGPRYKeqZcRRKMJdZBZ7Xh+edK7vDy/U/y9MaPXvwDIQQIAJoSgNqcCq+wNux0r8nlfgBjr0T29pAOnEfwcgXznHf1x+KEkVRwriA53XmjKexkQ1lZjlRQgQRQ2pKXgwMEtI14xKs9GNYmY343WaEmIaVeTqXAODLkdovDENC01VMc3gNsIKIn2TKwnW8YedFIv5RQ2lSSvr7kpRNL0cbIttsGBrBoElvbyKvkaeqCn7f8M1qQYGfdNrGtifuwe3tSdDZFedf//2pEdyo+trifFTBMLL9UURWbmawvJYQZ3T7/oBzQwiBITRurc4awP95+Ek0ReVv578rvxb9b0BYL2F7z8OoxSqqMNjcfT+FRjURffLcxgm9wYaqMaeghoXRekp8EW6sWjTpG00WBSVh1t51BVfcuoS2450c2n6c9b/exP4tR2g/2cXD//U0z/5qEzXTK5h/xUxW3bmcKXNqUHU1t+N+Yz0MPdYAludQGxyu+FztL8oHHaSUeEiOD3SwoXMfLckeEk6GllQvrvTwJjFbSClxpMe2niNs6zlGZ6aflGuxP9ZCRPMP46IVm2GMISq5Qc1HkRmiJdWbbytmp9jUdZC9sWZ6rQEyrk3MTg7r09yCOm6vXcYjzVt5vmMvy4obuaHyEuqCJSi5lN/jiQ767QRf2/MAhpq9p+O5nBjoQAbPr+r1xKCi6Yuw3NPZQrP2npyS96t7TqTXjud1543Hs+F5fbjuidxfBprWkD8mRDiXBacivR5c5wjSWD4m8V1KC9venrs2hKbNGPW80TDohTL9d6BqU+nreieQwso8TZDP89qlxQ+9z8SfZ6GUoKr12GzGc9txnROo6tRRxzxLxo7j2vuBwYSCi6/QrSgRTN8arPTTeO4pHGsbQgnliho7WcNKn3XB5ibH8chknGHP3kAig2lqwyRZBIyZ6SyEIBT2kUxauEOqzjuOSzptEw758oaM53pkMvbw+w1kMAwNbZxyGmcjGPJRUV7Axz9yDaUlw5NaDEM7Y0wN6fKrHbH5BXP49PQPv8pWXjvU+F+dF7g52U3MOmtDJ6AxXMlba1fwVNtOkm6Gff1ZpfBCM0Sl/+JuLl5vVPvnIAslGzvvw/ZSzItey4zIFXmy+GQwqa3PjVWLLhD1e2IQQhAI+2mYX8eUubVc887LaD/ZxQsPbWHLU7tpPdrBga1HObD1KA9990lmLm1g5VuWsXDVbKbMmZwm0muGswZw6ITmIXmydSf3Hn6S+dE6FkTrKTJC7I+1cDg+8RpCkJUZ+N6Rp3i2fQ9XlM7kksIGCowAademxzrLszHiR83Gfwd71mcn+T87fkbCybCybDZzIjX4NYOmvlPDrjIVjfdNXc11FYtY37GHZ9ubWNeyk4/NuI5rKxbmv2NED7AgWkdQOxM+ubR4OiW+8EXURlHx+W/BSj+DlHHSyV/mCNIFjD8tDw7O6Od4Xid25gV0Yxlnv05SetiZjbhudpx0Y+kwwUkhVAzfWtLJX+J5HaRTv8b034gQIwtOSimxMxtw7X0AaMZCVO3sLLHx+5q9p4KqNaIoUTwvhZSZ3HWvjeGkiAhniPJdWdfBBAwJIVQM/22k04+ATJFO/hTDvBQYLVwpsTJP4bpHAYFmLn+NSpsIDN9NKOq/4bnHSKd+h6JW4Dh7ARXdvBxFPb9yEaMhkUhz8FAbKy6dhqGrJJIZduw8yZT6EoKBiUkdqKpg6SVTeOSJnbS199MwNevFbD7dy8HD7Vx5+ZlnLJ22OXCwjatXzcbn00mnbbZtP051dSHRgoknbFyyoJZ1T+4mlbKprytGURSklGQy9pib3le77pSZJZSZby7dsleDX554gec79o56TJLV//vant/k59sbqi7hY9NvOGe7oaDJojk19PQnaagrmXBCwGgoL4mwbEE9tuNSUjRZeZmJIW5302udHvKJpDowm5OJ3fjVCG2pQ5T7pmGqwTHbGA2TMpzqQ6+fZpKiCBRTp2Z6Je/8wi3c+IHVHNl5gr0vH6bpxYPs33yE3S8cYPfGAyy9dgH/8Ns3Vvih0AhhKBrNqR4kMv/AtqR685NC2rV4vmMfJWaEP5v9FsK6H09K+u0k3ihTh5rPUht57HSqm5e7DrG6fC4fn349mqJiuQ7rWnfQkxluOHVmYqTdM/yaATvN/2fvvePsuMr7//eZcvvdu733KmnVuyzJsiwLdxu30DElJnQSCPnmm0oIyTeEACHhyy8Y+BIwJhRjG1suuBcVq9dVW+1qe2+3l2m/P+7uSut7d6WVV7IN/vhlv7wzc86cO3NmzjPP83k+z3AiyHxf8iV/ZLSNrsgwn2+4iS2FybI6IS01g1IIgYyg2JXN+yo2cG3BIr598nF+2b6TrYVLEAiq3PnsH27hppIVlLnS11u7HBBCQrGtxma/ikT8BRKx3xGRsnF6Po2cJuRlWTF07RSG0YbNvjmt2OYEYpFfoNpWjXNapPH2FqZxNln+xBwlqT10fYr+lKIuwea4lljkF+iJ/URC38fl+STSeaElyzLQtQNEQt8hqUPlxen+SIo2k2VGicefRZYrUdTGtDpVybp4zyeNFhiXRrhygrGSXATCCVYEXTuMrrecK5p7Adjs67DZ1o3fv5eJhh/A4foAknTumlqWjhbfQST0fSDpqUrqM10ZDkfSq3cr0dB/oGuHScR3YZmjCCkbm/3qWetEzQRVVdi1+wyWZVFcnMXp030MDAR4z92rJ/lNFx6vYP1Vdeza08L9P3qJq9bWIQTsfO0MdpvCtdecS01XbQrHT/byo5+8SmVFLmfPDnKmZYBPfHzTJL9pcCjIwECA3r4xQqEYvX1+Dh7uwOWyUVqchdttZ15DMWvX1PLAgztoax8iL9dLOBynrWOILZsXsHRxepX+N4K3WgTicuOWkpWsyZlJt2wqCi/S21RZmsPffGFuhDnXr6ph/aoLFMV+gxhJdHJs7LnJv5PeVwWn7OVk4GVA4M193+U1nCzLIqzHCRtxdDM1pi0JQaEj87JPUiEEvhwvyzY3smjDPN71QT89Lf08/dNX2LXtAGMDM6cevxkodmYxL6OEXUOnWJdbT7k7l67wMLuHTk8aPgKBQ1YxTIOwHsMcly94uudg2j7z7T5006DJ30muI+nydso2HLINVVJQJZm4oREal4k4MNLKyUA3bnkqUTaix3moYxfvqViPJAQv9jcxGAuwPi9JopsotRM1EgS1KHFT48meA0SNqVldJ/xdSEIi1+5FEhIJM0mato+HAZMk81qe7DnA/7Rt58PVm8Z/r0lXdIQCh++yzh9Jysfl/RKG0YWhnyYa/m8S8RdQ1BXISuW4blMoWQRXO41pDiAr9ai21UB6w0mS8rDQCY59EdW+MSlsKLkx9NZxpetWAGz29dicN6cs4EKouDx/iq6dQdcOEg39AC3xGnb7dUhKxXituj0k4i9iGv0I4cLp/sS4h2sqLCtGNPzfmPpZJLkc1bYMWakbN8LGiwUndqEl9gAaQvhwuD6U9ndZVgLLDAH6ZMFlw+ie5BZZVizJtxKCiUxHgYSQvCQLC6e/h5KUhd2+mXjsSQz9LMGxz2N33oYsV2ChYZmjmOYwDucdyCm1Gh24vF/GNPrR9ROEg/9GIvY8Nsd1SHIhlhlGS2wnEd+BZQ4hRAZu7xeTtQyvIOzOm4hFfo5ljhCP/hoAWa5GVec2c8njtnPzjUtoax/i8ScO4nbZ+fxntrJmVfWkJ0CSJHJzvTid6Q02IQRFhZn8xZ/dyKPbDvK7545iWbBwQQk337iE0pKscfFVmbraAu6+YyW797aw7clD2O0Kf/LH17Dp6nmThVlffvUkz79wHF030TSDs22D/NcPXsTpVPnYvRtZvLAMj8fOJz62iZdeOckr20/hD0Rxu+3U1RRQkOfFNAzMuIYWjBH2R1AUmdxsDzZVJhaOo4XixPwRTPMdotN0aMgooSFj7rybb1eUOBspcMz8YXYpoTpxgcyEKTuHYgG+dfIJdg2eRrMMNNNAFhK6ZeCUbdR6C7l/zSeQZy1OOHvomkF/+yAn97XStOs0h189SVdzL1gwb1UN33nx7y77GGaLrsgw3zjxW7rCw/hUFw7FxkJfGS8PHOdvF97NAl8Ze4ab+X7zs1hYeBUnCIs6bzEv9h/jh2s+NUU3KWZofOvEY+wfacWrOrFLKu+r3MA1BY3opsGvO3bxSOdufDY3dknBZ3PhVZycCfZy/5pPYloWP2x5njPBXlyync7IEJplEjc07ihbzV1la7HLKlE9zr8cf5ST/i5yHBlgQZUnn97oCHXeYj5Z9y6EEGzr2sdPz76MJCQcclKOIEN18onarazIrkYIgWGZ7Bs+w4Nt2+mPjeGUbWimgSJJfHHerWnJiqYxSHDsiyTiLyArDWRkfRdFXXBJ98CyrGRafuBf0RK7xkm700HC7rgZj++fJtW+AXTtJIHRT2Hop7E5bsZmX08k9F+YRkeaPhRU21o8mf+ELNdMy8kx9GYioe8Qjz4NpCc+S3IpTvfHcLo+ACK19IBpjhEY+RRa4lVmDm4IZKUWp/uTOFx3kk7BOhHfRTj4r5hGL5YVxjLDTJVSmIAdIVwIyYMQbjwZf49q3zit4WRZFrp2kJD/K+jagWnGaceX8zNs9lStrWT7w0SC3yQRf5XpMhFlpQ6X50+wO+8YH2PqeHTtJP6RezGNLlT7JnxZP0BIs/vyTAfTDBD2/y2x6EOT2zy+f8bp+vCciAMDHD7ayT9/fRtf/EJSs+l8TK2xZ6Xd/npMtw6cL+I5HaY7HyTf07IsTerwXUx/h185yeM/fAGbQ2X55gVsee9VCCGIhmL891cfZmwoiMNl476vvQdv1hu/X38oSJg6zYFeemIjaKaOT3VR7SmkwOGbouv3+4qQloz2eJRk9qhhavi1AbxqLqqU1kM77QMzu5Ir/cc4OtbBx2o2k+/w8ZPWl3hP5XpG4iFeHmjiQ1Ub50yO4PWwxlVKEzGNYztOsf23+zlzqI2uM31EQzEkSZBdmMmqrYvZfM/ayzKGN4oSZzZ/teBO2iOD6KZBoTOLXLuXVTm1SQK1EKzIruHvFvnojSbFGgscPvIcGazPbUgaUufBLil8uv4GWkP9RPQ4Nkmh2pvM2lIkmTvKVrMws4yAFkUVMhWePASCnugIAoEkBNcXLWVr4WKy7R5aQwNE9TjZdi9VnvxJaQOHbOMLDTdzNpzc71WdVHnyGYgFJsOFAFcXNFLhySegRTAsE6dso8iZRZHzXNajLCRW59RR7s6jKzJMzNCwywo5Nu+k/lR6KIAyrneU3viAZNhSmiE5IFmYdT6ezK+jJ/YSjz2Hrh3GNAawrBhCciLLpSjKPBTbalTbKsRM2XdWArvjRmSlnnh0G1p8O6bZB0JFUeqxOa7H7rgBSS6fcUyKWocn4yvY7JuJx55F1w5jmSMgbMhyOar9Kmz2Lai25dMKVwrhweH9c/mSdCAAACAASURBVNTEevTEHgyjLUlcN6OAjCT5kJUaVPs67I7rxkvFpOfCWFYAQ2/FGhcNTSLd68JIilMawcl2MyH5W5fgzfwGsehv0OKvYOid49fejSwVIKuNk0Kf6dqrtiV4Mv8PidiLJGIvoOtHsUx/MoNQrkpeK8f14xy2mUJjgqnzam4ghBfVvoF47HdYVnAyTDdXRlPq+WbitF3cOS903KX0YxomL/xiJ8u3LCSvJHva486HoRscevkEC1bXcsO9G5FledKb1dXcR+fpXv7iB/eh2lRcGbP3FPwhYiK551cdO3i+/wjD8SC6ZeKW7ZS6srm3+lrW5vz+i4m2hPZgkxzMy9gEgG4lOBF4kYaMq8m1zy48PCvDqcnfxZqcOt5ftYGAFuHRrr0syaqgxJmNKslsHzjFxvz5c5ZOnsyOsRgdCNDXPshrTx5k1xMH6G8fQovrSLJEbkkWizY0sOH2lay5YSlunwvlDda0uVwQQlDgzKTAOVWpdFXOOVeiKslUeQpS0v9X5KTGgickDZZnV6fsg6TBsyizImV7viNpCAiSnqPJc0xD0BNCkG33TJEWAFKKAmeozinCmtNBCDFpUKWDZVmY45k7khAIKYeMrO9hoSfrCk2jyXNibIDH2pr47ML1eNTpOR5CCGS5AMlxEzbHu8CaCEclSdJiUjxRSf4905c6GhYWqm0tqm0lWNp4X4yH5WwkNZcu9EwIhJSL3Xknduet42OaCOHKk+OZqZ+ucJj7jw3xpWUfwef5Y7DM1/0uAUIe/10zl12x2beQnb+D2dJyL0YvKVmItx6398vg+dM0114GZjZ4JKkEh+v9OFz3gGWcu1aTbS9cVkZWasnOewYLE4Ey7byaLQSM95V8D9kd182ZdtNbDYZu0Nc2SGAkhKTI5BVnkZnvIzQWput0L08/8Co2p42C8lxKagrIyPHQcaqHnKIsPD4XsUic/vYhimsKiASjdJ/pp/1kN9ULy2g/0UNRVR52l422490c23kaLaHT1dyH2+eiYn4JVy4b9O0LwzJ5uOs1nu8/wl1l61iRXY1dttETGeF3vQf5zslt5C15P7Xet76e2xtBUBukwHlurZWFQtyIkDBmlpNJh1kZToZp4rbbkScqRANRPY4qyVS683i290jyy38O5nI8luDs0U4OvtTE0e2nOLW/ldBY8gfanTaWbV7A4o3zWLppAdWLyrE732YFM9/BjHipt4WFWYUUuLxJwrVwXnBa5TrcbCismiKtMBOSRG4bCNsbmLLn11RUxxWoLw3JPgRgB2GfdT8Zqp3NpbU4ZEeSGC4u/VEUQkkhss8l3uj1EpPcKvmSf6cQcjLkeQltZ4JFHD2xD8vykyyyfPWcGWUTKCzw8d4/WkNpyZuXQm5ZFi1HOnj4e8+QW5SFltBZvKGBtTcuZWwoyNGdpxnsGuHEnhb62odwZzjxZrv5f3//EHd8+l0s3TSfgc5h/t9XHuIL//ERQqNhmnafYahnFEmWUGwKdoeKL9fLmcPttB7rwj8U5NDLJ8gvy6GsrnBWNfL+UJEwdV7uP8Z7ytdzW+nqSSpNiTOb+Rml/OXhB9gxePL33nByKZn0Rk9T7VmFZMlEjSARfQxFmr3tMCvDqciZydnQwDgnRUaVFE4Eeihz5TIUD6bUXXsjOLbjNN/61A8ZGwxg6CY2h0pRVT5rbljC1Xespri2gIxsD5J8MV/z7+BywrIsEqZBRNcwLRNVknGrNmQhoZkGIS2BaZk4ZBWXkhTsCybiyJIgbuhYgEuxYZdkdMskkIjx8+aD3Dd/DbIk4VFsOBQV3TQI6wl000QWEm7VNql4G9YTSEKwJKcIRTqX2RbU4iiSRMzQEePnsUlvvyK3umkSMzQMMxmKlIQgYRp4VTuKJBHWEmimwYr8EmznCRkapklYT6BKMhFdQxESHpsNCUFIS2CXk9sNy8KtqDgUFdOyCGsJEqaBMn6dlfGU8aCWwHF+G9WGQ56zkpdveySzKftJxHcCFrJSi2JbOq0216WiID+DO25bPqd9Xgr62ofAghvuvRpvphubU0WSJcrqCsn9xBZ2bjvArfddS0ltAUKIGblNZQ1FFFbl0ds6wKKr6tl09+rJ53TLe9eRmZdBJBjl/X9xK0KSLlfk8/cOpmUSMeKUuHJS+Mce1UGxM4vhePBNGt2VQ413Nc/1fo9tXV/HrWYzEu8iz16JT529N3hWb7wN+fPojY0xkgiRY/OwLreOH515nmd7j9AZGeaa/AXTCq3NFtFQjNEBPyU1hdSvqGLFloWsvn4p7vG017fbwvf7jLCe4P4Tuzk9NoAsJMo9mXxk3iq8qp3ftB7ltf52LCwybA4+tWAdFd5s/mbvU2TYHET0BIFEnIXZhXx83mr6IkEeOL2fQ8Pd3H/iNTJtTv6oZglrCyo4GxzhByd2E9U1dNNka2k9t1YuQJVknuo4yVMdJ/Godv5x1fX47Ml58qVdj1Pk8hLU4gS1OGvyy/lQ3QocytylhV8JtAVH+fahV3GrNvzxOCWeDJrHhvjUwrWsKyznpe5WHms7QdzQ+cZVN5HnTJJmu8MB/nzHE1xdUsWp0SEKXB7+pHENmXYHX9n7HPWZubQHxxiLR7mzeiHXldVycnSA+5v2EDN0VElic2ktN1c0IBD81a6nWZpXRIt/hEAizh/VLmJTSfpQ8R8q4vHnMfQTgIzNcS2yXPlmD+myYfnmRtpPdPOTrz1CWV0h19y1hrL6IoQkJtcCIcQkT+n1hpNlWpPZccnjkqFxIZ1rM7FPiGSUQ5Kk34ui71cKkpBwKw46I0OsyK6ZYjwFtAjdkRHW5V7ZzNM3AxlKPjcWf5HW0F6iRoAq93LK3UtQLqHY+awMp0ZfKbl1W8m1eZEliXcVLUG3TI77u1ieXcXNxcvnTMCwpLaAT379A8xfU0tZfRGOi9QluZywLIuEYXCot4+m/n46/X7CmoYkBBl2O9kuJ/Pz8pifl0eu233RRmRM13m+pYVdHZ1UZWXx7gXzyXbOrmCyZVkcHxjgh/v2T3uMXVH44NIlLCyYW77Fjr42jo308pdLr6XA5SGm62TbXJwY62dH31k+u3ADRS4vDzYf4IHT+/nr5deRMAwsy+IvlmymNxLke0076I8Eqc7I4S+XXcuRkV7+fMk11PtyJzM+il0+PrlgHdl2F3sHO3m68yTXlNSQbXdxd/ViajJy+PGpvVPGFtU1XIqNzy3cwGn/ED85tZfbKhrfdoYTFgxEw3x18VV869CrNGYXUOjycnJskLWFZdxcOY8F2fl8Zc/zr2/GQDRMnS+XD9Yvw7AsMmz2yZ1dIT+fW3QVdllGkWQsy+LHJ/azJLeI26sWcGpskB8e38uKvGKKXBlYQF8kxBeWrMcmyX8QNa6mQ6r3xMLQmoiGfgRYSFIeDufdv7cfeUII3D4n7/vyLfR3DPPSb3bzxI9f4iN/eydOj2PcuBGTiT3jrZAVGV1LKp5HwzEigehMp3nTkc5LZp333yTSr3xvhXtvkxTW587joY5dJAydRZkV2GWF/ugYLw00MZoIsSFv/oU7ehMxcQ9mytZ9PV5/rBACp5zBvIyrMSwNVXImKUeXcI9mZTipkjIl8ynL5ua9FVehWQaKkFHE3IXNKuaXUDGvBCG9NcqnJAyDAz09fPPV7ZwaGiJhmhjmuTIokhDIQmCTZT68fBmfW7sWu3Lhy2tZFsf6+/nqCy8yHImgjrug7122bErG2sWgLxTisZMnp93vUlWuq6mZc8Pp0HAPS3OKqfMlaxX6bMnf1RX2k+twU52RjUuxsaGwim8eeZmooaPKMivzyyhweUGAXVaImwaSEChSMjdTFgLlvIW5IzTKQ61HGIyGGYlHUCQJ3TwXHk43T5yKyoq8UvKcHsJ6AiEEmnk5S7tcPmTY7FR4s/CodhoyczkxOsBQLJKs2zXDVCl0e1mcU0im/VwWkjauw7Yqv4wi9zmJi7CWoCUwzB83riLb4WJeVj52WaE3HKTIldSyWlNQRqFraqmMP0xYxCIPklxATXTtOInYC5hmLwgnLu8XrpBi+ZsDy7LY9/wxRnrH8OV5iUcSON32SW+QospkFWSw/bF9NKyopmpBKZn5GVQ1lvLKo3uJheMc2X6SsH8W5NwrtBRYloVhGYSNCAEtxHBihI5wF/3xQUYTY4T0MAkzgT6+9qmSikdxk6VmkmvPptxVSp49F6/qxqO4UYX6pq1jspC4q3wdMVPjt917+GXHDizLQpFkcu1evjT/dsrdlyZufbFyF28cOgntJIpcgCTlTgl9W5aFYXQRjb+CprWiKKU47BtQleopunmaGePw2NOc8m/HRMetZLMs62bK3UuQ04gFz4RZC2DCuQskhEgaTHOYyjuB8920bzZMy2JvVxd/8+xzdPjTi2ua45lgNlmmKisL20UYTRMYjkQYiiRfHgnTpG10FNOyZn1VC71ebqqvJ5RIEEokCCcSjEajDITDs+xpdnDKCiEtkVK4Q5VkYoaOMe6KD2pxnLKa5BghJrkxr3/cJr7dXv8R8Z/HtrM6v5w/W3w1zf4h/qtp1wXHJgmBfZrzvN1wvgdzNlppipCQp3meHK+bp7IQKEIilEiKm2qmgW6auNVzBEr7O5ymcZhEwz/C0JunbhYunO6PYnfePufcpkuBYRkcD5yiJdRKvj2PVdnLUaW58bjmFGbSfqKboZ4RSmsLWXndwsnogCRLfPiv3s3+55toO95FSU3yg+3W+65l57YDdDX3sXLrYhZe1YDTPd5Gkli1dREF5anSJEVVeWy4feVlf5BjRozTwRZOBE7TGu7gbLidoH6hAtypcMoOylyl1LgrqPVU0+hrwKdOX4HgckEIQZbNw6fqbmBr4RLaw4Nopk623cu8jBIy1VRNuIuFYZg8/dA+1mxqIK8oM2X/npdP4c10Mn/JG1OD17TT9A+9D4dtLbnZ30GIc/pdutHB8OiXicVfndymKvXkZP0Ldtvayd/WGtrPQLSVawo+jlP2MhA/y7GxZ8lUC8myz04sdFZvwO81P0NDRjHXFS5K2ffaUDP7R1r5VN3WyyKmdQGhzhTMpfWb0HV+evDQpNGkyjIbKyq4qaGeIm/yy9sfi9ETCDIQDrG0sHBWz3a200m208loNIoqy9Tk5MyeKyYEDbm5/ON1W0iYJpphoI2HFb/89NOzKhA8W2wuruWr+59lW/tx6n15+BNRGjLzqfXl8pvWIzzXfZpyTxYPnz3K9WUNk+Tt6SALQYbNwd7BTlRZIsfuJtPuxLSS86AvEuThs0cnlckN0yRm6AQTcRKmQVBLYFeUScXyuYeMEG6E8CKEizfbJDOxiGkJgok4umUQ1OJ4VBvOSwhH2hWVTSXV/LrlKLIkODzUi0tVKXrHw5QGAkVdjGXFscwgQnKjKA3YXX+Ezb5xxjI9VxKmZXJ47ChP9T3HIt8ClmYunhPDSQhB9cIyqhem96oJIaheVE71oqmLZmZeBjd99Jq0bSRZYu1N6YvIl9QUTBpfcw3LsoibCY6MNfHC4Hbaw534tUBKWanZIGrEOB08w+ngGdzyLoqdhazNWcGG3LV4FPcVF52UEFS68yl15QIWEtIbDrUbusljD+6iqr4wreG099VTqDblDRtO0fj2pCYdOue/b00rSiD0I2LxXQjhRlXrMPR+NL2Z0cC/UpDzs0kjayjeRrV3FcXOZKFtr5pLV6SJqBlitrmps1pZ2sNDU5Srz0dEj7Nz8DR/Unsdc8XbsyxrXLejl+HeMWKh+JQK3tPBm+lixXWpxt2loj8c5uW2NiC5qN/T2MiXN27Ea5+axnjhEqupEEKwsKCAv9l8DTva21mQl8/t8+bN2nASgCJJZDqnisJNeLIuJxZkF/DlpdfwVMdJXuppoTGrgPrMPCo9WXxpySYeajnCzv52NhZVc3tlIwBLcooocCbnkl1SWJJTjPc87aUvLr6aX7Uc5tTYAO+rXUam3cmfLt7Iz5sP0OwfYn1hJbGc4mQYKRLgweYDdIbHkIXg3w6/yNVF1dxRtYhluSXkOpIPjlOxsSynBOcsvIHpICu1ZOY+Ov6X4ErUenOrNpbnliALweKcQrw2OyVuH16bg+FYhAdPHaI1MIJXtfPtQ9tZlV/Kh+ctx6WorMovTTEiBYJFOYXkO92v2w4fm7+Sh1uO8cCpgxS7MvjC4vXkOFwYlsXS3CJyHRdf0PX3GxLezG/zeq7Lxel2vYNLhWlZ9PmDdI8G0Ixzpb9q8nIo8M1OQsPCQjd1TgVbeLL3WQ6PNWEy96H8sBGhOdTKmdBZXhjYzu3FN7IsaxFu2XVF5krc0Dg81sajnbtpCnQSMxIUOrK4KreBm0tWUuLMvizjME2LSChdxYHZIZ44CAic9g2TAsCWZZFIHCUSfQohHGRn/gMe111oWitDo58nkThOLL4Tl3MrABlqHr3RUxQ6alElB2OJXuJG6JJKrlxwBUlLjEuzLW7qk/XrJva/vvD5bMnO8UiCX/37E+z47T762oeIhS/uBtQurZhTw6l5aAhjnBfjsdvZVFVFhiOVrH6p086pqtw+fz63z39rE/SmgywkVueXszo/9auizpfH/16+JWX7x+atnvx/n93JH89fM/m3EILFOcUszime0mZeZj5fXZVawdtnc/C/ll2bdmyfXLBu8v/znR4+2bgu7XGzQXIeT3102vyj3H9kb4pnr8jt5YMLlpLjnJ2xoRkGT509zaGBXt5VWcuaojI+tSipiP/R+cmaZ6Wec4rmX1q2MW0/eU43X1iyPmW7Ikl8ZP6KtG2cisoHGpbxgYZlU9sIwX2Nq9O2uZzY29vFU2dPszC3gNtq51/QY3mlcE5L6h1cDkzHn2kfGuX/e3E3hmlhO0/H6Y4VjbMynCzLQrd0nuh9juf7X2EoMTw3A5/pnFh0R3v5SdsvOBY4wXvK7iBL9V1W48m0LPaNnOHfT22jwpXHbSWrsEsqAzE/Lw4cozXUz1813o3PdnHvKMuyiEYS9HQMo8V1Egmd7vYh7OfXQ7QshvqDnDzcydpr3/i6Zhh9COFEUUrPC38bxOI7MIxuHPZ1uJ23IYQdVa3FbluLpjWT0E5OGk7VnlUMxtp5pvc/kYSMhUWtd93lkSPQLINX+08QNuL0RUc5Nibjks/ztFgQ1GM823eECncuumHy8qEWHn3pKPXledz37nXsPNpGdXEOlcXZ05/odTANk8e+/xy/+c7TJGIJ3D4XHp+LcCBKLBLHl+OdzM6IBGNocQ23z8mCNXVcdcvc6psMhiOT35QORaHMN0MJjnfwBwl/PMbz7S0kDAPdMojqOrppsiAnj3fXzZ+14RTSEnzttRcZjIQ5PjzAz295z9ueo3Wp+Nb+HbzW04nPbue6ihoy7HMrJvkO3prQTZNXW9qozM6iOvfc2tHcP0yhz8u965djU84Zrq/n680Ey7IYSYzxcPc2tg/tJmEmLtxoDhE2Imwf3M1AbIgPVtxDlbv8soXuEqbGL9t3sCm/kQ9WbsKjOBBCoJsGt0dW8w/HfsnLA03cVppaOHw69HWN8r2vPU7AH2Goz89/f+dZbPap19+yIDvPy5Zb04deZwPLiiKEEyGcTLgoTCtMOPIYAB7Xe5GkpNEshIqiJFXlTXNwsg+3ksWG/A8S0f3EzTBuOROnnIF8CWHrC84007JoCw9yeKyd7sgIA7EApwO9U45RJYVyVw4frt5Ea9cwrxxoYf2SKlq7khb84GiISDQxK8Opv2OInU8cQEtorHzXYm766GZKagp46DtPsuPxA3z6Gx+kfH4JgeEgp/a38vz/7MS0TO783A0s3TS3npuYrk0ylaXxzLl38A7OR11WDv+19XYCiTj+eIxfnTrKju72S+5PFhKlXh+BeJyazIt/bt5KiBs6hwf6KPVmUOT2XvJXdXlGJgf7e6j2ZU9Lcn8HFwvxthGOTBgGTzWd5vr5dVMMJ7sq41QVvA77FMNpNhjT/Pys/VfsGTl4WUJzFwMTk5PBZn509md8tPL91HqqLovnSTdN+mJjvL9yI5m2c6F5WZao8RZS5y2iNdR/0f0JIaiqL+AfvvchTh3t4v9+7XGuvWUJJZW55x0DLo+D+oWlZGa/8ULMkuQFXcOyzhX1jsf3oenNKHIZDsdUj3uyhBIMx8/SPfrMjH1Xe1fjVlL5WTPhgoaTQ1b5SM01jMRDfPPE45S5c7m+aMnUToREps1NhupiR2sr5YVZrJxfljScBNhVhVgifRXz6TDcM0Zf2yCZ+T4++nd3U7WoLJkdUOBDViSyCn1UNZYCsHB9A43r6vmXj/0XP/jrX/BPj3yJ7ILZXQg4lxlnWUlKoGVZaIZBIH4uRGhZFnFDJ6ql/z2qLM8YSjBME800ZyS722R5xkK1byYsyyKq65wYGGR7exutI6ME43HcNhv5bjcrSkpYXVpCltP5lv0NlwMu1caygnOhxQP9Pezs7rjk/tw2lW9supHBSJjqzKw5E5a9kugM+Pnii0/w6WVreU/DolnLa0zgz1ZcxR2188l3eS6J8P5mwbIsTodaeLR7G3n2XD5a+YHJ58HC4rfdT3IicApVUvlM7X045XOetD0j+3lpYDuLfY1sKdiEKqmT74yAFuRY4ARN/hME9CA2yUapq5jlmUsoc5Ugi+mNCQkBFpwNt7NnZD+90T4QghJHEWtyVlLqLL6spGXLspJyIBfBuY5rOqF4qieoODODX+45wr8/s52qvOzJ9+2yimIqc2em+SZJ4HF+3fnYRRtNEhKSSP7rU71kKF48qhtVKMhCxrBMNFMjZITxa0GCWrKKhmmZF9X/2XAHD7T/ii/UfYJsW9acvzOFSHJzE2ZSO29KIWbLImZoZNtmZ4AKIfD6XCxeXU3tgmJWrK9jwbLUuqhzBUWuJGbtQtfPYllJAyoU+R/AxOnciiSdW++TtU5DWJZJzIgxEG8FwLB0OsJHyLWX45J9jGm9SChUeGbvEbso36YsJPIcGazMqcGtOKj1pq9cDuDzOBkaC9PZP0YknqC1a5hjLT1cu6p+VgMLByIER8PUL6+aNJoAbA4blgWxUOzc+GSJeSurue0TW/jxV37NSw/t5s7PXD+r8wEc6Onhd83N9AaDDIYj9IWCjESixHV98jnvC4W448Gfpw2bSELwvzZdzYeWTn8jdnd18cUnnyIQi017zL/ecAM3N8zuel0JxHWdPV1d/N/XdnOkrw/tPB0rSDpQf3b4MEVeL+9bvJi7FzaS43qHSHwpkIVETWb229bbBPBqdxtdoQBh7Y2FQQrdXgrdb9esPovOSDe9sX78WoBMWzLMr5k6u4b30hXtRkKiI9JJg7cu2cKyOB44SVPgJA3eOpRxjRmTZHbcLzsfoTfajxACm6RiWAZ7R/bzRM/vuLFoK9cXbMGrpuf66JbOCwOv8Nvep9BMDUXIJEyNfdZBnht4iTtLbmNT3noc8uURHLaAL/x6G8HYhfmqumXROjTCXUsbp2yPJnTyvR4iCY3jPQOT2ytyMi9oOCVMjW29z7JjePeMRo0qFPIdeRQ7C2nMaKDSVU6xs3D8upwvdimYKodpETPi9ET7aIt0cjLYTFekh4H40IzhwDOhszzY8Rs+UvleMtS5neuqkJmfUcq27n3k2r0UODKRhUREj3No9CwtoT5uK7k07qKiSNz90Y3kF8/eUTEbuJzXE4r8Cn/o+1iYaNoporEXUORS3M5bEJybrxZxdL0TgDLP1TR67wPg6Ngz5NkrWZx1PSCIGSH2DT9Cwpx+LZ4Os0ovurZg4QXTM2vLcqkty+XxV5to7hhk2B9hdWM5i+uKZ2z3epimhWmYOFz2KRay02MHy8I/PFVXQ1ZkKheU4s5wcXxX8yUZTvu6u/npwUNTRBXTIXFeJsf5kISYJJFPB9OyiOs68Wn6AOa05t9cIaZpPHL8BP+xa9e0ulAWSbdwp9/PN3fsoH1sjM+uXUtxxtt10XsHbwRvxOP2+wAhBBlKBlm2TIYTIwzEhyYNp75YP2E9jEt2opk6raH2ScMpasQYio9gl2wUOPIm338nA6f5SfsvGE2M0eibx/KsJXgUDwkjwcngafaNHuTJ3meQkLi56Hrscmrx0rZwJ93RXhZmzKMxYz4uxUVAC7Bn5ACng2d4tHsbWTYfK7OWXTbP04m+QRoKcinwzkzk1gyDPn9qDbXFZYUsLivEME3imo5DVZEuIpXbsizOhFp5of9VEmb6iIFAUOEu4+rcdTT6Gih2FKLMUtZElVQa1FrqM2q4ruBqeqJ9nAqe4ZXBXbSE2tIabBYWh8aOsnekgWvyN8xKp+3C41G4u/wqvn3ycf7h6K8odWWjSAr+RJje6Ai3lKxiWXbVJfUtSRINi0rnbKzTwWFfg9NxDdHYs4z6vzK+VcblvA2bumSqF80YRNNbEcKGqtYgiYl6pqN41VwklHENSpWYEUQzZ69cP6sZkW33jLv2EumNCwFuu51bNy5kw9Jq4gkdRZbI9rlw2GbnYldtCjaHin84iGEYyOO8Il9uRlKV+kwfpmlOEcpU7QqqXWG4b2xW55pAeWYmm6oqU35blz9Ay8gIAHZZZklREU419dJJQlCaMTNxfN641tJAOMxIJMpoLErH2Bj7u3tmNKbeTJiWxXMtLXxj+6v4Y8miuRWZmdzZuIDlRcVkuZyE4nFODA7y62NNnBgYQDNNHm5qQpUl/nzDBjw224xy+TFDJ6prJAwDw7Im5RUciopHtU0bqhqIhNBNkyyHE4esoJsmQS0x7iW0UCUZjy1ZiDbd+eOGzlAkjCLJ5LuSsfiIrhHWknN8QkDTa7Nf9myusXiMcCLB6+MYTtVGtuPiU2at8ZBzRNfGSeoGFskwjSpLOGQFp6pO+3LWTIOIphE39MlnYeI6JAsrp6bbT4RgYoZOXNfpCwdpGk7yJvzxGN2hQEqoLsPuwGtL9WxEtARj8VhKOFuRZPJcF1/KaOIaRMbv67lJyQAAIABJREFUpSApyupSbTiV9PMBYDASJmEaZNkdOBUVwzIJJRLEDB3TShZZnpiX8gXC0T7VS44tm55oH/3xAeq9NQB0RrowLIP53nraIh20hFsnwyh+zY9fC+CUnRQ6khk/w/FRnuh9htHEKOtz1nFP2e1kqZmThXNX56wgz5HLo93beG7gJZZnLaHCVZYytogR4ZrsDdxT9m4ylCTvzLRMlmct5bvN93Mm3MpTvc+x2NeIQ748JHyf08FH1i5nSUnRjMeFEwn+bttzKdt1w2TnmXYefO0QgWgMn8vJ+9csYV1tOeoM/FPN0nik+0lGtfTrg1t2cX3htVyTv55sW9YbNl4EAlnIlLlKKHEWsSxrMTuH9vBk77OMaYGU46NGjG09z7A8awlZtrlLQBJC0JBRwj8t+QCvDDRxzN9BzNBo9JVxX+1WGn1lqDOEd2dCUjLIoP1MPyePdhFOUz6nsq6AtZvfGO9YCC/ZmV8lGKoiEnsWIey4nbeT4fkY0nlyApZloRu9GGYvilKOw3aO8F7ims9rQ79iLNGHU85gJNFJ1AjiVmar4jRLw0k3DV7sb2LfSAsj8XCK98khq3xl4T30jwQ42zNCQtMn99WX51NeePEDzMjxkJXvIzAUpPfsIKW1yfBgWX0Rik3h2M7TDHQMU1CRLPNhmiYDHcOExiIU11zahL+xro4b6+pStv/4wAH++aWXsYBsl4t/3rqVyqxLc03muFzc3DC1oOLR/n4+/djj9AbfmhWqO/1+vrVjJ/5YHFkIbp03jy+uv2pS/HMCS4uKuKm+nq+/+iqPHj9BwjD45ZGjrC0r44Y01xWSi9Tu3k5293ZxZLCXtsAo4UQCRZbJdbqYl53PzdX1bC6vITNNNtVHn/oNp0eH+OY1N7GmqJSHm4/zu7ZmzowOo1smRW4vm8qquKN2AYvzClMWkiODffzRY/9DqdfHM/d8lKahfn5+4gi7ezsZjIZxKzbqsnK4rXYeN1fPI2sWBsxs8Z39O/lJ04EUSYM76hbw7c03X3Q/veEgz7W3sL27jePDgwxHwyQMA5dqo8jtpS4rh1tr5rG1snbK4hDVNY4O9vNabye7eztpHRthOBbBsiy8Njs1mTmsLS7jzroFVPmmhhAThsFjLSf5XdtpzowO0xMKkhiXJ/nuwdf47sHXUsb5l6uv5pNL16Rsf7qtmb/d/lxKiK8hO5dHbv8gLnXmjzBr3GB6vr2F5zta2NfXzVA0giwExZ4MVhQUc0fdApYXlKRN9Pj884+zp6+Lr23Yyrsq6/jtmRM809bMyZFBwloCt2pjQU4+11XUcFf9QnwzZPk5ZScFjjwOjun0xwbG+ZMW7ZEuTEyWZC5kRBujN9pPSA/hVb2MaX7GND9exUOBIx/LsmiLtHMq2IxX8XJdwaZJowkmanA52JK/id/1PY9fC3Bo7AgVrlRhykybj7U5qyaNJkgWgc21ZXND0XV898z9nAm10hPto9pTOeN1vlRsqq2kPCsT1wU/pi18ztRre7xngEcONPGeVYspzfbRMxbg4f1NuO02VlROrwB9YPQIp4Jn0u7LsWVxT9ntXJ2blCuZa56RJCSy1UxuKXoXxc5CHmj7Nf3xgZTj+uIDvDK4k9tLbpzT88tCIs+ewV1l67irLFWS5VJ/r2VZPPPIfh747nN4Mpy4vY6UvjTNmAPDSaDIFWT5vkKW7+8ntqYdt6rUkJd9P5LkQZLOEdbLXUux5btpCe7Gr/WTbStjTe46vMrsy83MynDaPXyGb598Ap/qotZbMBl7n4BDVukcGOMHD+9CVWSc9nMPhs/jnJXhlFucRVFVHif2tHD8tWZKagoQQlA+r5jc4ixO72/lwX/5Lff82U1k5nk5c7iDx+5/jng0QXnD7MKCE5jN5LnUifZ2I0ublsVDx47RNa6aXpmVxZc2rE8xmibgczq5b+VKjvT1cXJwCM00efDwEa6rqUWVU3/7rp4O/mHnC4zEIsmHQ5Lw2u0kDJOeUJCuYIA9vZ10BgPct3hlWnKwZpq0jI3wTNsZnu9owTCTRoKum7T7x/ip/yCv9XTyjU03sDC3IO09CMTjbGs5xQ+P7KXFP4JdlnHICoFEjD19XTQN99MeGOMzS9fis6e+HOYC64rLiOoao7EoI7EIx4b6ier6hRuOw7Isjg318+39O9jR3UHc0JME/fF/IlqCM2PDtI6NUOnL4l2VU43Z3lCQf9v7Kvv6u4HkF7NLVZGFIJiIs6+vi/393Rwd7OMfN2yl1JMxeR0My6QjMEZ/OIzX5qDKp9DqH0Ezk8Zr7uuFNgXkudJn29Rl5vCehkX0R0L44zGODw8wErs4d/pE8sK39+3godPH8MdjyJKES1ExLIuz/hFaxoZ5rbeTTy5ZzZ31jckSQK+7n8ljR/n6nlfY1nKSuKHjUm04FIVgIs7Ong4O9PfQHw7xxZUbpq1LKYSg2FmILCRG4qMkzASapTEQG0QRCvMzGjgwdoTuaC/98SE8ige/FiCoBan1VOOQ7ZiWSVu4g5gZJ9uWTbGzCMMyUgjWTtmBT/UR0sN0RLrSjidZSy0nbQHUGncldslOwkxwNtx+WQwnAXzq6jUXVcfTrijcu2YZue6p86R71M/8onyubqhEkWVq8rM5OzRK54h/WsMpZsTYNbwP3Up9nlyyi9uKb+SqnFWX9f080ffSzIXEyuI82P5QWu/XnpGDXJu/cVqe2qXAsiyiRoJDo2dpDfeTMHVybF4WZVZQ7spFuUSPk66ZPP2bfazcWM9t71uLOyP1w9LlmRu+3Ll7M/09EkIgyznIcmrJHiEERc56ipxvnD88K8Pppf4m6ryFfGXRPbjV1C8BAew+0kFxbgYfuXUNNvXczZDl2XmBsgsyWbxxHu0nuunvGEKL69gcKnanjTs/cz3//vkf89zPt/Pyw7uRJIGhmyRiGt4sN1s/uGFW53oH06NtdJRX2towxr0gH1q2lELP9A+0AKqysthQUcGpoWEsy+LU4CDNw0MsyM9POX51YSn1WTlUZ9ZxbXkNi/IKcCk2DMvkYH8P3z34Gvv6u/nhkb1srahhXnZe2pfbD47sxWd38Pnl67i1Zh6ZdicRPcFvz5zg+4f3cHJkkP+z+2W+vfkmCtIQjQOJGP+46wXm5+Tz31fdxaLcQiQhaB4d5odH9/LM2TP8tOkg5d5MPrBg6WXRVNpSXsM1ZdVYloU/EePeJx/ixMjghRuOozPo56+3P8vRwT48tqTm0S3VDSzILcAhKwxEwhwZ7GVvXxfvrl2QEvIqdHtYXlBMht3O1opaVhSWUODyIBD0hYP86Og+Hj1znB3d7TzS3MSnl65FGe/Dqah8bvk6Pj3uQTobGOWjT/2G/kiIDy1Yyocbl08N1QmmDX025hYwLzsPEwvLgr94+Skea5m+ePX5iBsG3z+8hweOH0KRBHfVN/LxRSsp8/owLYum4QF+0nSA59pa+OfdL+OzO7ixKv2L9GfHDyEEXF9Vx4cWLKMuKwcLODzQy7/tfZUjg338prmJVUWlbCmvmXbRLXOVokoqQ4lhQnqYqBGjL9aPT82g0FFAqbOY5mALvdE+qtzl9Mb60Sw9mZ6OwLBM+mLJsGdvrI/PHvjy9L/fTJKuA1p677VDduCW0yds2CQbmaqPgfggw4mRac/xRiCEwHkBj+EEZElifmHqO8PrsNMfCNHrD+JzOgjE4vSOBajMmf7DvC3cydlwenmQtTkr2Jy/AfWylWiaClnIrM1ZQV+sn4e7nkjhPA3EBzkZbGZV9rJpepgdkskGXXz39JP0REdwy3YkIRE3NSJ6nFtLVnFv1WacSion7mL6DgdjrN/SSP2i0redY+BSMauZEjM0aryFZNmnXziddhVZllBkCVsaHtDFQkiCzfespXpROQvW1GJzJB82IQTrblnO2eNdPPnjlwiNniMq55flcNfnb6B2SeUln/cdTEXz8DCdY0lvk9tmY0Xxhb15QggW5OUnyfKWRUzXOTmY3nAqcHv4jy23kuN0pSzk15RX47M7eM+2XxBIxDk00Me87PRu1Yiu8acrruLji1ZOav14bDbubVyOZpr854GdHB7s49Xudu6sa0w5lwUUebz87bpraMw555VaXlDM33u20BUMcGSwj582HeSO+kY86uxfMheCLEmTOtR2Q5m1BMEvTx3lyGAfshB8eukaPrRgGR7buXEWuD0syivgffMXT8kLmoBLtfHJJatxqSrq67wwtbYc/mzlejqCfnZ0t3N8aIBgIj4ZuhQT+mbjoa8kpyzZVpVlnIpy0RpMkhBI54XQLradZVmcGBnkkeYmdNPgjrqF/OWaTWTaz30Frysupz4rl2BiGzu62/nPA7tYX1KRNtwW0TVurKrn76/aMiVMvKGkAs00+N+vPMNAJMShgV42lVVNyxMpchTikOyMJsaIGBECWojB+BBrc1YhEFS6y0mYGn2xAeJGgp5oHwCV7on0bmvSIFIl9QJZV8l90xWTlRDTkr6FEKiSgoU1LXn6SsIwTTpH/ficDrJc5+5hY0kBBzt6+foTL+OwqUQTGnUFOSwtT8+ZMi2Tzkg3I4lU745HcXNj4ZYrZjRNQBYy1+Zv5OXBnQzGpyqWh/UIZ8PtLM9aPKO0xMUiYer89OyLWBZ8vv5mKtz5qJLEWCLCgdFWHu3aTZ23iC2Fi2fdtxCCnHwvsdiVFRB9szGr2VKfUUTTWBdRPYFDVtNal7mZHk53DPL1nz5PdUkOyvgLcPm8UhoqUhfOmVBYmU9hZWobh9vO+/7iNtbfuoKj208RDkTILclm0foGiqryUNR3BCrnAoZp0j42NqljledyoZsmwxdR/06RpcmlWTMMBqfJxBNCTBuyAZiXk0eWw0l/OERvOJVQOYEsh5PbauenLLI2WWZrRQ2PNjdxenSY/X3d3FhVj/t1ho8kBKsLS5mXnZ8yr/Ndbu6sW8CRwT7ag2McHxpgddHlzySZDUZiEZ4+exqAFYUlvH/+kilG0/mYKVsqcwYOV57TTbUvm53dHYzGo8RmEUa8EjAsi9d6OugKBsh2Orm7fhE+W6pBlO1wcm/jMvb0dtEWGOWVrjZurZmXcpwsBB9ftCKFWyeEYEFOPmVeH/2REP3hEHHdQJ1GC8ch2SlyFnImdJaQHqEv1k/MjE8SxStdSdXovlgfYSNMb6wPh2Sn2DEh+yKwSclwR6mzmM/W3nfBazFdEV8DMxnmSwPLShpMApE2I+9KI6Eb/HzfYTbUVHJ1beXk9iy3k49tXEH3aICRcBSf005Ztg9PmjJYAJqp0RbpTPu7l/gaybPnpml1+eFTM1idvYIneqcKNCbLsvQR0aNzEq7TLIOWYB+frLuBzQWLJj/IKtww31fKyUA3Tf7OSzKcFFVi4w2LeO63BympzKW4LIfk6+XcO1RRJBzON38+zSVmZTitz23g+b5j/PupJ1mfW49bdUz5cpWFhNtwU1OanIiB87SWZiuAOROEELg8DhpWVtOwsjpl3zuYGyQMg06/f5JK0TY2xp0P/vyi2p5PvzAti2B8Zt2WhKHTFw4xEAkT1pIZTLp5rnQJMGPWYV1mDh41/Yuz0pdFodvL6dFhmseGiepaiuGkShLzsvOmDR+tKSpDFhKGaXJsqP8tZzidHB5idJwHdGNV/bRG08XAtCyGoxH6wyHG4lFiho5mGGimSVfQD1gpGl5vBeimwf7+HkwschyutMkAE6jJzKYiI5NW/wj7+7u5pboh5dhKX1YKCX4CXtU+GXKK6NoFJUSq3VUc9R9nODFCW6QDVahUuysByHPkkmXLpCfWR0AL0h8boNRZMqmlJAuJAnv++LmieBQPbuXS9NGiepSQHk7rtYqZccbGvTK5tlSOyJWGYZn0BUIk0hjobruNuoJzYxwKRQjE4hRnpnraNFOjJ9qbsl0WEgt987FdQsmNuYBAsDSzkd/1vZDCvRqMDxEx5sZwEoBbcSSdHa/bpwoZm6TgvERD2TAsTh/povVUH3/+wfspLMvG6bJNOc/KjQ186LOp9UrfzpiV4fRkz0EGYn5O+Lt5vu8oTtk2xXByK3Z+dtXn+Mw9GzBMi2g8kQzdpUlfngu8YyRdXpiWlaLceylL5YS+U8r2cYX213o7+W3zcZpHhxmMJg2nuGGgmwa6aU7yq2ZClsM5bWhLlWSyHcmFZjQWTTsWSUjTZswJIXCpNrw2G4FEnKFoeu/Zm4nB8cw5RZIo9fiQZsnCmkj97w4F+PWpY+zt62IgEsYfjyUNp4l7YZqXNAeuBEzLoi+c5PbkudzTlkYSQuBUVLIdTs6MWQxGwmimmXJ8ntM9vQSFOPdNbXHh56LSnSyAPRAbpCvSQ4EjD7fiRgiBZElUucs5NHqUwfgQUSNGiat4MkwjIVHlqcAh2QnqQU4ETrMia8m077+Je5lu/6g2xmB8kCLH1CQJy7I4E2whYWnIQqZqMkw4t7Asi//Zf4SYdmFvZVzXOTM4PNluJjR19+OPxrh92YKUfbplTBOm85Brz37T1hEhBD41qfM1GB+ass+vBd9Q/byJdyskdZxW59Sxa/AUSzMrcSlJD6qFxdGxdvqio7y34tJ4wQLIK85k67un52OV11x81trr7/Ok0v4cfqTNxf2eleF0XeGiGYWyFCFhGCYvHzrLIy8eIRiN47Kr3LKxkWtX1c1ay+kdvLkwLYuofs5T6FZVyny+WesZSUKkzcKLGToPNB3ie4deI6QlyHO6qfRlUZOZTb7LTYbNjirJ/OveV/BfwGOlSNKMNbj+f/beO76Oq07/f5+Zuf3qXvXeuy337thOYqc4TiOddEo2hCUksCyw7LJfyrIBXpQFlsACgZAQagohIZ0UO04c994lq1i9t9vvnTm/P0aSJetKtmyZJD/y/CN77pQzZ9rnfM7zeR67piIws1bxMiXDulETngMCi6IOVW29+/yPkxGMRTGkxKqoWNXxVWKng82tTXzjndep7u3CabGS4/awKreAbLcHr82O22LludojbDoLD75zCcmQryRgP4U1iyqUkUApqutEdX1c4OTQtLhcsDNBriMLm2KjJdRKY7CZBYlzcCjmB0wgKHOX8E73Nvb1HwSgwJk7UrUshKDUVcQs70x29O7mr60v4tZcFLnysSrWES2nYdsPX8xPhi097nRbf3SADZ1vk+PIJsWaPKLj1B7q4IW2vwFQmVBGln3qjvGnAwn84q1tKIo4pSmvISXtA6bQcW8gyJbaJlaUFtDjD7D52Fhx1YMtHczOje9ooUuDwdj4wY5bc+HSzt5H7WxgU2wkWjzjAqdALED0LHhmjx9/mz199YB5f4X0CEcGmtncfWSI46TSHRrkeKCL8oQsYsaZaQiqmsJt/7x60nWmwtU0jG6CofUoihe77TyEMK/PoP836PrpF8qMa4PiQNMKsVpmoql5CHF2nLYpbV3pnVgjYxiH6tp5Y3s1N69dQG66l+5+P0+v30eyx8my2YWnfaxoJEbLsXa8qQkkpsUnOn6AcwtT6O/ELVKZlsaPr7qSjEmq6k4XUkq2tTXzy33bGIiEuSC3iHvnL2NeetaYACYUi/GjnZuAyQOnUCw26agkEI0iMUnL8R5kiZyUs2NIU9xxOPv0XsPweYX0GBF9vCfVqRCMxfjetjc52N1BliuBLy29gAvzivBYxyr3H+zueM8GTgJGpmADp7B5iQ2JdYLJg5tMOPGs2yXEkJhlOocHqgnrYXKd2VhHBTb5zlwsQmNP334cqp10W9oYLlqi1ctV2etoC3VQ46vl/479krmJs0mzpaApGmE9TF9kgIZAIxEjwmfKPkm6On6kn2ZL4chgDQ/XPcYs70zcmou+6AA7enfTGGgi0eJlbeZFWJVzd4+7bFY+uXIJs7MnD878kQjffXUjYPKdmnr6ieo6exvbePNIHaWjpup6/BPLVZhk9/H3g1WxvGvTdMPQFBVbnL6OGqee/p0MihAonLh/HKqNeUljaS2ZjiQyHWYlYoO/g7lJhVM+jhACi0UjHIpSfbCFjpZevEku5i0rMTlz4diU+E2D/t/TN/A9FOEkLeWXOOwrh5b/hmj04JTbdzIsWjlez7/gcqxDiDOXSZhS4CSlJKCH2dVTz86eOhQhuCZvMVmOJLrDPhyqhc4+H3kZiSypyseiqeRlJFHb3ENzR/+UGtbZ1MOvvvI4A92D3Pz5q1h2+fSUZn6A04cixBhl54FwmOg0qZvHDIPtQ9NB6U4X/zRnEQszsseLpw2pWJ8K7QHfhFN6oViMrqBJaE9zuLAo4z+SMUPS7vfFDTiklKaqdzSCADKd7z0LmQyXG6uq4otGaBjow5BySqa6x/q62d9llrzfUDGLq0oqxwWYumHgi0bes1N1qlAo8CSyp7ON9oCPQDQaVyxTSok/GqEz4EcRgkxXApZzrApvU6xk2TNoCDTiUp1k2jNGAiMhBB5LAqm2FFpD7WTbM0esWUajxFXI3cV38mTTMxwdPMYbHRtHtpfSAASaolHiKoprE6IKlQvTVpGguXmq+VkODVajCoWoEUNi4LF4uDH3GmZ7Z57T6atEh53StORJ5QMA/OEIyS5zij3D4+auVYsQAuxWjWsWVnHxzNKRdd84dOwU/nfxssxi2jKKZ474Io5nOyF+ZfYi1mad/jdzsqpCwzCIRHSsVm2ctY2Uku6OAX7/szfYvbkW32CQmXPzmb2okN4uH7/+4Stce8cKKuacHidUCBtCOBCKEzGuotCCqmaeWcAjw+hGD9FYNX3930JV0oYyWmd2/acUOA3Ggnzn4F/Z3n2MRKuTiBHjgoyZpFgTeKR2PapQWOOcR3vPIHXN3aQmuhkMhKht7mJJ1dTmzDubujm87RhCESQkvbvp1H9UWFWVPK93xMayaWCA/nCYnClmM+JBl5KOgJk+d1msFHriu4Jvb2seyQxMhprebtr9vrgWHkd6OmnxmRV5lSmpcT+mUUNnX1c7oVgsrs7M+sY6DCmxqxrz0ic2uX63UJmcRqrDRU8oyPO1h7m+vGpKKuejA8+qlPS4n5Nm3wANA6dnZ6QqyshHKTTKJPtcQlMVlmXl82LdUXqCQba1NXF+bmHc++pAdztNg/3YVY0lWedef8am2pifNJeY1Em0eMl35I75aHstXs5LWUpDoJFcR3Z8craAElcRnyu/l2O+eg4MHKIr3E3EiOJQ7aTaUihPKKXYVYhdsY3aTCHPmcuS5AUsSJpLniOHCk8Z23t20hrqQADZjkwWJy0g0x5fIHa6IIAfXn8Fic5T27lYVIXF+TmkJ7gRQoxMxQ8HTKMD+5nZGRN6iAoEVmElKMeaucaMGDHj3a0M1aUeV/rBomhn5RXo0GxMl8dB4/EeHnvkTe751MWkpY+d/TF0yZ8f3cT+HQ1cdetSWo730FTbhZSQlunFNxBkx6bq0w6cPO47sVqqUBQPVstYtXGLVkRq8v9itVRNsPVkMIhEj9LT9zXCkbfxB57EZluI4MxshaYUOG1oP8iR/mY+U7mOdLuXB/b/GTAVw4vd6bzcspu751xEcU4qDz6xEUUIYrrB7NJs5leceppvNIL+EP6BIGk5SeRXTm3bDzA9UBWFwqQkPHY7/aEQwWiUva2tzEybukT9yVCEwGszX+7BWIy2wCDZbjOTM8zZaAv4eOzgqU2XweRL/eHwHr645HysozJKYT3GK/U1tPgG8VhtzE/Pxq7Gv+13djSzs6OF5dn5YwKH44P9PDckwFialEJJ4rtfcXQyEu0O1haWcbS3i72dbTx6YCd3z1mMcwKuz8lk6ESbY+Sc6/p7AUayb1JKYobB87VHONx9ejwDr9U2ksU50NWObhgjvm6jp1Sn8yOtCoVFmTmUJqVwpKeLJ47sY2ZKOqmOsRVo7QEfj+7fhS4lhd4klmWNtyaZbqhCZWXqMlamLov7u1tzcV3uVZPuQwwx0q3CSmVCGZpMpo5uVmeXxs2itgUGeanxMDeVzOOCtBVckLZi5LdcRza5OWfmsHA2EEKQlnB6A2GrpnHLornj9zH0d/T9memdmD6gCIFDsxOMjA2cgkaIoBGaYKu/DyJGBF8c/pVNsU2LhtP0QGIYJxusmdB1nZ2bqrn61mWsu3ExLz25jaZak6+lqAppWYl0tZ/+bJMQjpHpufG/WRHCfsb8JJt1FkneL9DWuYVQZBvIMIi/Q+C0s6eO+clFXJo1l/7ICS0fIQSJVhf90SBOu5UbL57LJUvL6fOFcNmtpCRO3eRXEQqKIrDYLLi8584f7ANMjsq0VIqTktjVapbzPrH/AFdWVpJgOzsZfYuiMC89mwSrjY6Aj5/t3sK985eT6nAipeRobzcP7d3GoZ5OkuyOkVL7ieC2WHniyH4GIxFuKJ9FmtNFIBrhz9UH+cOhPUQNnYtySibMQAjMqcj/2PgK98xdwqKMHDRF4WhvF7/at51j/T0kWG3cM2fxOFJrzDAIRCPoUqJLA92QBGIR5FDZflcggFMzjYpVRWBVNOzaCa6VlJKwrhPWY+hDVYT94RDRIcJmMBaj3e9DFQJFUVCHqsJGBz4CuH3mPLa1NbGtrYmf7d7K1tYmriipYEZyGhZFpTccpLq3m+1tzZQlpfC5RSdeUBXJqeQmeKnr7+U3B3ZR5E1iZoopYtobCvJU9QGerj6Iy2I9Lf0mr83O/Ixsjg/280ZjLT/dvYV1xeXYVQ1dSgYiITKcbrLdJ0awUkpi0iAQNYnuw30xTMaPGgYdAR+uIXNdRVFGrHGGr2lJYjL/NHsR/715PS/XV9MXDnHX7EUUehLRkezvbOexg7vY29VGit3JFxavipulfD9gIBqkNTAwoSxEfyTIm621XFs4C05Bln8vYDKO4uhn9lBrJ4ZhUJVjcqQkcLi1E5umUpI+flCjCY1ka9K4yrr+6CC9kf4p8wGnC1JKfDE/XScJYIKp8TTMfZJS4hsMMTAQREpwuax4vU4UVSEa1env8xMKxXBkXfA1AAAgAElEQVQ4LCQmuVAUgWFIenv9hIJRFEWQmOTE6bQhpWRgIIimKgSCEcKhKO4EB96hb2w4FKWvL0A0pmOzWUhKcg61Afr7AkTCMSxWlZQUN5qmIqXJR05JS4g7jReL6Fjt0yQuKqwIcXbcO4tWhqZmocdakBPomZ0OpnhGAlUo40qdpZQMRoPYVIuZFrWopCcnkJ585lwQd5KLxDQP0XAUX18AT/L0+fZ8gNNHntfLJaWl7GtvJ2YYHOrs5JGdO/n4woW4TkMrSEqJPsS3Gf1yEkKwLCuP68ur+N3B3fyt4RgbmxpIcTiJ6DrdwQDpLhf3L1hO40A/jxzYOelx1hWXoxuSvx47xBNH9mHXLET1GLGhYy/JyuXzi1ZOKPDotFi5Z+4SXqw7ypc3voKmKGiKMuIV57XZ+cScxazOLx7H/Tnc08kv9mxlIBImEI0SiEZp8pn6Vw0DfXzxzZfw2uw4VA2nxcqiIYHK4Q92TBq8UHuEl+ur8UcjBGNRfNEI9UPTYm83N/Dxl57CqVlwWCw4LRZuLJ/NRQUlY9qR7nTxtRUX8ZNdm3mlvoZNLcfZ1DK2+gjMEXiGa+zz5LJY+cyC8/jWlg20+gf59Kt/JcnuwKIqdAcDGBJuKK8yldTffm3SawHm9b17zmIOdndQ3dvNj3Zu4ie7N2NXNUJDAeK3z1/LhyvHiu7t72znF3u3EYhFCUQjBGIxjg/1Q9NAP/f87RlcFgtOzeyH87ILuHXG3JEgUlUUPlQ6E380yi/2bOWt5gbeam7ArmoYyJHpnLKkFD41bxkrcvLfl7ImQggWpuaxMPUU2bL3wal1DPrYXN9Ity8QNwi8uLKEguQTfKia9m6ihj4SOCElB5rbsU4UOCka6bZUanx1Y5ZHjAjHfHUsTJqL5SyrrM4EEjgyWEM4DnE9xZaMQzWzIb7BEL/8han8LaUkMyuR665fjNWmsXlTNVveqUFRBJGIzkWXVLFoSTGDg0Ee/8NmQqEooVCUzEwvN9+2HLvdwnPP7KS3x4/FqjE4EGTWnDzWrptDOBzl949torm5B4fTSmKiiyuvNnlSXZ0D/OXP21EEdHX5uOb6RSxdVoqiCNIyvRzc08j880rHnENzfRf1NW2su2HxtPSXwILgLAcAQgGhITk7ru6U7paqxFyeadzOwf4mUm0JI/o8raE+3uw4xOzEvElLwqeCnJIMSuYWcOCdoxzedozFl855X77gRsOQ8oS+xtBfCUR1Y8xoK2YYRHR95AMthMmGEMP/jkNelif9hfj6ScP7HrFLPMW+hRBcXzWTl6ur2dPWRkTXeWTnLoLRGHctWojHZjONZIdS5sPHjxoGhzo6+FvNMVYU5LOyYDzHLcnu4L75yynyJPFc7WFq+3rwRSIkOxysKSjm6pIZLMjI5uW6auyHtUkJvIaUfH7xSpZn5/FszWEO93QQU1XyPIlcVljOuuJyCj2Jk1wdyYyUNC4uKOXxI3vZ2NRAu99HsttJVWo6N5bPZnl2flxhyY6Aj/WNdeM4FsNTgs2DAzQPnlA9tygKN5TPOtF2Q3K0t4sNjWNf7AoCu6oR1XWO9Y31DlucOZ4zIISgIimVryxfw9rCMl4/Xsu+zjY6g35ihkGC1Ua+J5GFGdlcUzpW70YRgsuKyki2O3j86H52tDUzGAljUW0sy87nssIyLi0sQyL53ra3sKnqKZ/1GclpfO+CdTxz7BAbG+tpD/gQQpDn9FLoSaQ0afxHrs3v443jteOWD/dlw9A04jASLDb0ytnAKIsWIbi5cg4zU9L5W30N65tqhzJ2CvkpiSzPzuOqkkpKE1PiVtNZVQ27qmEdZRszrq8xOYB2VTNNgifviimjPTjILw5t5r6qlSTaHPijEX51ZAuX5pZTmZjB/x3cxM6uJpZnFHJr6QLsqoaUko6Qj8eqd9Dk66PYk4I+9PwbUrKjq4mn6vYSM3QuyinjkpwKVCFoD/p4onYPR/o7qEzM4IaiOWQ43H+X922PP8iPN2zmlUPVgFn9alc1YtLUDJuXm82yIlMDK6YbHG7tpLazh5hhsLW2CQREYzrb65tZM6M47jGsioVcZw50bxv3247evVyVvRaL8vcv+IjKKJu7t8f9LdueMSKV0NPjo762k89+fh0pKQlmNshuYXAgyJvrD3HRJbOoqMxm86Zqnnt2J4sWF+N22/nQdQtxOW309QX4+U9fo71tgIJC85nr6hrk3vsvxek6kW3du/s4R460ct9nLyU5xU00ouN02Whp7iEcjnHB6hlUzcrllRf38s5bR1m6rBRVU7nkmgX89qev09XWTyQco7tzgD89tIE9W2uxWDSWr5kR9xynAoFmksbPMuOENDAMP4ri4mxGFVMKnC7Pns/27mN8affvyXYk0Rv28/OaV+kI9pFm93Bj/vJpq1LwpLi58TPraK5p4+kHXyY1O4miWXnv6+BpfV0d+9ra8EUiDIYjDIbD+CIROv3+MTYmD76zmT8fOIjbasVttZJgs+GyWslKSODyinKSHWOzJhJ44chRqru78IUjDEYi+Ib23eH3jYziQrEY33vrLX63Z8/Ivt02829WQgLXVVXF1VZJcTr5yprVfOnlV6jp7qYvFOKh7dt59vBhluflUZSchMtqJRyL0R0IUt/by6HOTjp8PmJSUpoSX30ZTPuLO6rmc8uMuSOBlxAmX2W4KuyqkkouKypHU+JXoICpcp5kd3B9+SyuKZ05cs5CCHNaJ05QOKYPpflxKU9K4d+XXsi/LTEwpNkWBTGkExV/+wtyi9h6+6cm3PfJUIQYEwRaVZV/XbySzy5cMclWYzGR5pQQglSHkyuKK7isqNwsaZaM9KvgRH+cDLtmYVVuIctz8oeC/BPnb5K9Tbx5891DvmaTk1dVRWFOWiZVqRkYQ/0JY/d5Mi4tLGX3R+477X5QhRjXF8O+eQszspmfnsW/Ll6BlCd+O9X98NDaazGkHHedRsOhWfjpxR8aqV6cqrbZqZBqd9EZ8rG5o4G1uRXUDHRxsLedW0sXAHBXxVIK3UlsbK/DGCpbN5A8fGQrMUPnnhnLeaHxEM1+k19ysLeNXx7ewt2VS3GoFv73wFsoKKzJKeXBA2+RandxX9VKXm46wg/3vcnXF63FNgEXcDpR3dnFW8fq+fdLL+CymWX8y1MvcO3cKhbkZfObLTsJRmPkJZkVhoaUHGrtYHt9E/5whJr2IS6NIpibl83S4vjZNwWFAmcOCZqbwZhvzG9toXbWd77NFVmXop4FGXuq0KXBW52baQy0jPvNqToocRehDXGc8vJSuHDNTB7+xXpy8pJZfdFMEhOdhMNRdu9soKtrEJvNgjQkdqfVFIJt7eevz+xgYCBINKKb02yj3DvKK7JISXWjjLpva6rbKS5JJyd3SBR0FDUwM9NLQUEKLpeNjEwv+/c1AuazvOqy2WhWjRef2EZXWz+xmM47rx+iuDKLW+65kMSUs58tSvT8G0LYUZTx1aZTgWH0Yxg9WCwVcar2Th9TejIcqpXPzbiK9e372dN7HMWrYFcsXJYzj4syZlPgiu9cfyYQQjBzWRmf/Pat/OabT/Pjzz7K+dctoWROPp7kBBRt4pvcarOQWXj2BObpxl8PHebZw6d2eT/e38/x/vGEulyPh0U52eMCJ90w+OPevbzT2Djpfg0pqevtpa63d9xveV4vl5WXxw2chBDMysjgq2tW87233mZ3ayuGlLQODvLng2enrTGc8ZpI5RnMj+OZGsSeSXs0IYDTf4mqinLa7ZvomBahYpmm9/bwM6gJgTaF8xjdlslgO4Vw4cn7O93+HA5qTu5LafRC+G2EbQ0op281MrK/KfZBvHtRRvchw2+A1BHOOxBKyqT37NlCQXBhVinbOhtZlVnMvp5Wyr2peIZshSyKgvWkwEZKyf6eVu6btYoZSRmE9CjbOs13ws6uZtoDA7zQeAiBoDPoY09PC0vT86nu7+RjFYsp8aSiKSr/sfUFBiIh0hznnh7hC0dIsNs4v7QQu8Wcio7qOqluJ7csnssXnn6Jms5uFuRlY9VUblg0i2SXk6iuc/HMEhAChfjZ8mEIIch35pJpT2fQNzZwkkheb99IRUIp5e6Sv8vAXEpJvf84r7S/Mc5qBSDJmkhlQulIWxRV4UPXLWL5yjJ272zgsUfe4t7PXIqmKuTkJfOJf76IgsLUkXNVFMELz+3CYlG59/5LkYbkq//55JhjaHG+n2Z2qTcu50uzqAhlWD7jxHIhBFarxgWXzWb+0mJam3qJRmIkeB1k5iZjs08Pt87pWDMt+9GNXmzWxdhty84qezWlwEkIQbrdw/X5y7g8ewFRqaMgcGrWaXeXPrqrjsf/53k6m3toPNKKvz9AzZ4GHG77kInvxDd4UVUuD/zl89PWFpfVSo7HgyEl6W73GY8ukx0OcjyeM5aPz3C741bPCCFIcTrJjqPOPZV9T6bwqikKS/PyePCqK/nj3n28cPQInT4/oSEvOYl5RVRFwaKq2FWVdLebi0tK4k7TfYAPcNqQQWTsIMJ2/umtLiUYHaB4EOLsC0uk3o70PYiwXw5KMkzDPk8H81NzWN9SQ4Ovl51dzVxbNCvu8z/STsypeNvQu9iimNOIEgjEIhQlpHB53gwEgsvzZpDucBPSTakI69A2VsWcgv17aXUpwiQyD2eIk5wOjvf0IaXEoWkoAvqDJyrfhBCcV5qPhClZeSVbk5jlncExXz0GY+kLHeEuftfwJB8ruoVC57nlvEkpaQm18VjD43GzTQBLkheQbD3B6aqv66T2WAfp6R7sdosZ2AAJHjuVM7J47ZX9rDy/gmAwgqIqLFlagt1uobfXT3NTD1s3HyMaPTWnZ9nyUt5cf4inn9pOWXkmAX+YsvLJpVeklIRDUbra++lqGyASiYGEgC9Me7PJTUzJ8FBSmXX6nXQOYbNWkZ7yC4SwA38nAcxhqELBbTmzMr7TRcfxbjY+PXZOOhKKEgmdWgwxKWN6lcZvmjWLm2bNOvWKp8B/rr6Q/1x94dk36CSoQvDDKy6f9v2eDEUIMt1uPnvecj66YD47Wlqo6e6myx8goutYVBWv3UZOgoeSlGRmpKWNjMrfz1OsH+BdhpKFcH9hSptI34MI5x1gKT/74+utgAH2yxAMjVLP8f0shCDTkUCGM4E3WmoIxiLMTsoa6y83PAc7BAVBnjuRXV1N5LkTOdjbTncogADKE9PZ2nkcr9VOmt3NQDSEU7PitlhJsTvZ2nkcp2Zhe2cjKTYXCRMYZk83Ut1mFW1z3wCpbhezsjP43bY9VGamEYhE6fT5cVjGfqYccSq02wd8RGM6ucnxp3IUobA6fQUbOt8eV10nkVT7avlJzcPcnH8dszyVIwbL04mwHuHAwGGeaHyG+kD82YE0awpr0leNuc4ul42O9gEOHmjC5bLx0bvOJyPTPM9b71jJpreO8vbGozicVpYsMwtGrr5mIS8+v5vXXz3ArNl5FBSmkpjoBASl5ZmoqjKOVpOR6eW+z65l45tH2PDGIfLyU6iYkY07wc6CRUU4hrJH6RleFiwyrdcM3eC3P3mdN57fg9vjwGIdz/dbfH7FeyZwEsKGOg3XVpwi+zHmx6ZAN3W+DhanlGJTNEJGlNfb9rOlq5qZ3lyuyFmAW7NPy0ey/XgXe948dEbbepLdHyiN/4Pgiqce5UB3B1eVVPKdCy7DMcWy621tTdz07B9waBb+96IrubigNO5650p7aDogpaRmTwN/+91GAv1Brv7kJZTOLWDDn7ew6dkd5M/I4bp71+Lynv4013sFMvhXZPhV0MoQzjsRijkoMvyPINQMZGQHyCjCsQ4si0GvQ/ofg/CroJWD4kU4PoywLUfKEISeR0a2gZKOcFwNagkCHel/BKxLkeFXQO9EOK8HyyIIPIwMvwWxo2CZj9AKwHUPQliQ4TeQ4U1ADGFdAfYrEAgkUYi8gwy9BjKIsMwD5/WADWIHkcGnQIbNDJrt4gm5FlJKXmk6yk8Pvs01hbP4aPlihBDUDnTzu5od7OtpoyvkZ1ZyJpfnzWBtbgVbO4/zq8NbUYQZRFX3d/Gj8z6EJlSeqtvL5o4GYoZBmsPF7aULqUhMZ2vHcR6v3cNgNITbYuPGorksyyiYksfYmaI/GOKPO/ZyfmkRMzLT6PL5+eQfn6Vj0JxSm5OTyVfWrSbNPVb76eSv1obDtQyEwnFNfodhSIOnm5/nqabniK9KBIkWL/MSZ7E2czV5zpwR25IzeeaH3xkGBi3BNl5qe51dvfvojcYXkbUICzflXc26rIvfQxpOkyMcivLpGx5kzVXzWXZh5dBs0Fg43TZS0qcnmXHiPSxhTObwzPw5T4EJdziljNP6toNs6jrC3KRCrIrKa637+HnNq2Q5Etnd20BU6txWuGpa6OHpeSlccuuZOTZ/gA8w3YiGo7Q1dJFZkIZ1mubtpwsD3T6e/OELLLpkDiVzC0jLSUYoghVXLyKzII3fPvA00bsverebeWawX4rQipGDPwDHh08sj2xDEkW47gK9Hel/GJGQA2oBwn0vMroX4f5n0EoA86Mrg89DdBfCeRtEjyJ9P0Yk/AcoScjoXogdRjhuNKfi1KGpEseNCLUIGfgtwvNlEE4QbiAK2Mz1iSIHf4hQC5GWWRB+01zfeSeoGSAjgAqxaqTvpwjnLaAkIH2/QCDBflncUxdCcFFOGSszi8YYNxe4k/jc7AvHfPyHRV8Xp+UzJzkbXRpYFHVE7V4Iwa2lC7iheM4Qod00OVaEYEl6PvNSsolJA1Uo2CbwczwX8NhtfHz5whFeW4rLyYM3XcmW+kbsFgvLCvPw2G10+wO8dbSB1TOK6Rr08+bR+jH7OdLaycLCyYWSBYIL0lZQPVjH3v4DcYOnvmg/Gzo3saVnB+UJpSxMnEOxuxC35sKh2rErNjTFNH8ek/2Tcki3LUbYCBPUg/hiAer8DWzv2U21r46gHpwwYBMIFifPZ1Xa8jEec+91qJrCwhVlSEOiaIrJaTrp1rFYp4/GI6WPcGQ3wdAbRKOH0Y1eNC2HlKTvoYpEpJQYcgBdb0URLlT13LgCTOmM6v0dZDmS8Fgc+GMhnm/ZxYq0Cj5dfhlPHH+HDe2HuLVwJdMhHiLMEqAP8AEmxUeq5tMZDFCWlHJG3LNct4fPL16FRVEmVASXUtLb3s9ff/Eat33pQ++5wMnfHyASijBnVSUZ+akjy602C063/X39HAlhQ4o4StPCgrCeh7AuRertEHoNpN/MBClJIDQQiQhl1DUNPQfCjQy9AtIH0QNg9IKSBAhzf7alJx3Hg1Q8IKygpJwglEoN1KyhjNcgEASjBahChjcgbGsQtgtN3ZghyOhe0NuQkc2AANmPjGxH2Ncy0UUy9cTGklhVRcE1gQmvgAmzrvH2BcNm3u/OPS2GKhL9kQiDocgQ10myKN8MgnzhMFZNRTckA8EQumFwoKWD3cdbqMgcLgCSRGKn5vAIIUixJnFNzjpaQ210hLvirieRBPUQe/r2s6dvP27VRZo9lRRrEl6LB6fqwK7a0ISKEIop1ipjhPQQfj3IQHSQ7kgvHeFO/LFA3GOcjAJXLtfnXonX8v4ytFcUhRnzC3j4+y/xxgt78CQ6xwXdC1aUcss9q8/6WLFYKwO+n+Hz/xFDnpB3MaQfRpHso9HDdPf9O5qSRVrqLxHTZj5zAlMKnCJGjAy7qYVT5+ugNdjLx4ovxKXZyHel8kLLLjOV9j57UUspaQ0O8Ej1Zup8PZyfUcKtxYtQFeU9PUXzXsZwv53rPrvpJAHFqSLL7eHe+fFtMIbx5p+38tIjG6jbf5y6/cfJyE/lps9dSX5lNk3Vbbz0yHoaq1spnJnHVXevITUnmb/89BU0i8axvQ30dQyw+NI5XHzbSqx2C7V7j/Pioxtor+/Em5rADZ+9nIIZOURCUZ7/5evs2XgIZ4KDyz5yAbPOK0cIwV9/+RopmUkc3FxN45EWzr9+KZfctpIXf72e9U9upm5/I9+562dkFaVz8xeuJrdsYlJnYDDIMz/7G4e21uBN8bDuYxdSMjuPX33lcW7+wtVU76xjy4u7uf0/ruHQ1hrCwQhrPnzeWfXz9EOBkaBIDHGOJqMdSJA+hPU8GPa6sl0C6ig9LPX0K3FldCfS/2uE41pQF5lB0dDUgZDBoazU6HtfgvSDmoGwLgVUsC43M1L/wBgIhfnN1l28caR2SHNu/DX890svZGlhLrefNx8BuKwWrp43k9WjdJvWH649hcmvCSEE5Qkl3F5wEw/V/macPEE8+HQ/Pr+fOn/DyDJlJOM0rP5vnJExrwByHNl8tPAWsuzvv3shFtX500MbSM9J4rw1M0nw2sfx/zJzJ5ajOV0YRoD+wR8w6P8TAgVVzUZVUolE945ZTwiBqqQhsBGO7iIS2Y/dNj0CnKMxpcAp05FEva+D4/4unji+mQpPNhUe09E+osf+fqUY0wwJvNh0CAl8dd46bEMpbIBGfx8RQ6ck4b3nT/ZexsG+NlLtLjIc768RVDysuHohmYVp/PabT3PfDz5CYroHzaoRGAzx9IMvUzI3n6s+cTGv/eFtfv+dZ7n/Rx+lu7WXg5urufuBm1EtGr/+6hPkVWRTvqCIlx7dQGZBKh/+3BW0N3SRkmUORl55bCM1exr4+Ndvoqe9jyd+8Dx2p43S+YX0tvWz+bld3PHla0lM96CoZibjkttWUrG4mEe//hR3f/Nm0vNS0U6RGn/256/S0djN3Q/cQtPRVv743Wf5yFduQI/qdBzvYt9bh+nr6qezuYe6/Y0Uz8k/5308OYalYk/GRBlGFdDAaAcj28wWCQtYFoDsB63UzEgZfvO3EUwhyNebzGk76xLQO8EYts0QoFUiozvAtgREAsggKGmgFUN4IyiZJj9L+oa8sv5xB2R7m9t4atd+rptXRUlqclxZj+LUpBHZEoA1M0wC9OhBWdUkJr8nQxEKC5LmcFfx7fzp+NO0htqn3G4DCWdYHT0aFQll3JJ/HWXu+OKd73UIASlpCVywbjZrrpyHUM7NvRyO7GDQ/0cUxUOi54u4nR9CImlsGV+0parpWLRiotFDRCJ73/3A6fz0GbzYsouv7n2c9lA/X5z5ITwWB7o01cMTra53PSszosw9hGFF7MmWG9KgLdhPqSeNbKd35AE1pGRTRy2GlBS5k0cUtodL7znp34xaNtHxR4+LJ2sbTJ6tGa0OPnqbyY5/8u8TtVuYBzfbOkHbJtuXgeTJ+t2sy51Jmj3hlH0wvJ94673b9xOAqqlYbBYURcHqsGK1mx/b4GCQna/vp6ulh/2bjtLbbgYbhm4AgjmrZjBjaRmRUIT0/BQGenxoVo2y+YW89ewOFFXhvCsX4va60KM6ezYc5JLbV1IwI4fMojTefmY7dQcaKZlryjlULS+jcknJGNE6zaphtVlRVAWrzXLKacRoOMreNw9x8xevJq88i+RMLxv/so3WunbS8lLobO6hta6DkjkF9LT10dncw3lXLTxnfTsZpN4JwT8howcgdhQ58N9gW45w3sz4oEmM+bewXYL0/xqpPo9w3oqwzEE4b0H6fw0D/2UGTlqFyXcSw6Pkye61k37Tqkwu08DXQEkFNc88LiAdlyP8DyMHvjl0nEqE86Nm4GarR/p+bHJdFK95LsrZj8jfr7BbNNLcLq6dM5OcxKkNskab/KZ7Ts84eBiqUFiYOIcE1cVvGv5EQ6BpStufLRShMD9xFh/Ou5ZcR/Z74j13JlAUhYo5ubz67G6O7GsmMdllDupGnU5hWQbLV5+dengg+CIQxe28iQTXzQhhxTDimwcL4URVU5HE0I3WszruRJhS4DTDm8NXZ9/A7t4GZifmszC5CCEE4VgEq6LxobzF06YcfiaIGTqvNB/mxeZD+GNhMh0e/qVqNak2F43+Ph6ufocGXy9pdjfXF85lUUo++/paeKxmG9u7jvN2ey2vthzhluKFrM4s47v7XuX11mokkpdbDjM3KYer8qr4U/0uPlW5kifqdtMWHOC+mRfweN1O5iXnYlM1/lC7g66Qj2Sbk9tKFjEvOZeIofO5rX/m8rwq3mg9SjAW5eNly1mQkkvtYDd/qN1Ona+HTIeH6wvnMS85Z8KeNK0VBnm8bjd7epqRSFZmFHNnyRIGY2F+Xb2Zg31tAKzKKOHmogVoisozx/fSFhxkIBriSH87y9OKuKt8OQ8d3URIj9Ls76cr5GN1Vhk3Fi3Aqqjs723hifrdtAb6yXElcnvJYkoTUvnp4Y3oUtLo76UnHGBhSh53lC4mrOt8d/+rvNl2jN09zXitdq7IreKGwnn4YmE+t/VpLs2pZH1rNR6LnU9UrKAp0Mf61mo+W7WaBIuNBl8P3973N7658CqSbVN7IZ4rjFyLUVGkoRskJLm46u6LyCgwuUWKqoxkg7xpnpGtFUVBGgaqprD6w+dRdV4FG57czPc/+RAf/eoNlMwtIBqNoQ6VXgsEqqaO4fp5UhLO+vmKRXViMR1NOyEToaoKqqaSXZzOoS01eFISyK/MobWuk972fjKL0s/qmGcMJRmcdyKIcSK0NoNW4fnaiWyRkorwfINhp3MBSNftCOd15nbDHCm1AOH5EshhXSDbSMZHeP4bxARlypa5CO93YJRPltBKwfMNIDLUJmWIVyUQShYy4fPmlB1y6DiOITXmm8FxNaADmpm1+gdGVWY6l80s574nnmNGZhoeu21cEHHt3JmUp5/g7u1vbseQkjm55nS0BA40t2PTNMozUzldaIrGDE85n6+4l+da/8bW7p0TVrxNFxQU0u2prM1YzcrUpbi0dz/ZcDbQDYN92+rx+0Ic2nPcNPo96XxiEf2sA6do7DBCJGC3LYVT+NUJoSCGnivDOD2O2VQxpcBJFQqLUkpYlDLWXNSp2bi9aNW0NuxM0BMO8FTDHj5WtpRKbwatgQESrSYx7FdH3yHTmcA9FSvZ1d3Io3G7XAMAACAASURBVNVbKHKnMCcpmwcWXsl39r1KhTeD6wrmjkjv/0vVamyqBZdm5c7SJahC0BMOoBsGPeEAxwa7CBsxesMBeiNBEiw20uxuPlK6hHRHAs8e38cLTQeZmWhqWHSH/Rzpa+f+GRegKSouzUpMGvyxbgcF7mQ+UbGCN9uP8euj7/DdxddMSNjUpcET9WbQ9h9zL8Ux5DivCIFDtXBhZim3Fi+iPxLkv/e8zJLUAsq96YT1GOtbq/m3ORfz0dKlGENCasFYhD29LXxl7mWE9Cjf3f8a5d50Zngz+VPdTpamFbIsrZDnGg/wqyOb+NaiqwnEIuzrbeXLcy9FEYLv7HuN+b25LEsr5OvzLufezU9wV9kyFqXmj/SnBI4NdhGKRfl/cy9DlwZJNid2VeOJul00+Xup9GbwRms1+a7k90zQBGZmJ+QP09Xai2ZVsTttOBLsZBSk0tbQSem8QkLBMNHQCZJivNdhLKLTfKwNZ4KDtXeeT0djN8f2HmfmsjJmLill8/M7ySvPor9zgPbjXZx//dKRF+uZvF8Nw7ROGQ747C4blYtK2PTcTlJzk2mt7WCwz09mYRrBwRC1+9az7PL5ZOSnsuWFXSRleE2C+bsAIVQQ8bMQQnGPWk8Z4hSNLDD1lk5SBjb70UE8AUshJlbJFsJiTvWNbcDE2wiBwD4SyI3f19nZRvz/CXXdvTy9+wA2i0YwGiWqG+PWOZn4XdfZS9TQRwInpORwaydWTZ1S4ATmPZFqS+H2/BtYmDiHN7veYV//Qfqjg2d8ThMh057BgqQ5rExdSqHz/W0fNgyLReVbv/o4k/F0puM8pYwghAUhxgfW49eVSBkGxJDQ5fRjynWCptu9QVSaN7NV0VDMotrTmmI6l0i0OliVUcIj1VtZmlbAutyZqEIhpMc43N/OrSULyXJ60JQCnjm+j47QIGl2U41bEQJNKGOUebWh5erQckWYKulOzUpnyEdIj5Jsc9Id9hOMRUmxufDHIrzeepR6Xw8tgX4yHAkY0kARCppQWZFRTL77RGo+pEd5reUoKXYX69tqCMQitAYHiBo69gki66ihc7ivnWsL5phTiKP625AGdYM9PFG/G180TG84wGD0hPLuzKRMqhKzxvlQzU/OpSghhZihk+9KosHXQ4ErmTfbj1E72M0zx/cxGA0RiEXQpXm1F6fmU+HNIKzHyLAnMBANDVXJmCJomqKOs4VItDpYll5EpvPEB9GiqFR4M9jcUU+a3c327uN8rCw+YVtKiUGMmGEKoarCgiq0c3rPCSFIzkykYlExv/p/fyK/IptrP72W9NwUrr9/Ha88tpF3nt+J3Wlj1bVLyKvIwmq3jCnDtdotqBaVWDTGtpf3sHejab2TmpvM4rUmwf2yj13Ikz98gf+9/9dY7RZWXrOYsnnmNJ3FbpmQu6QoApvTOoZf0N3Wx5M/eJ6aPQ20NXTynbt/xqKL53DdfZfxoU9ewuM/fJ4fffph7C47F92ygtyyLDoau0BKSuYWkJGfQmAwxII1VeeqW/8ukFKix3TCgQiqpmJzmsFUNBwlFtWRUqIoCppFRbNOfh/JIZPuWERHj+kYhukDKBQza2exWRBx/BSllBiGJOQLoagK9iFj1VgkRjQSG5ly0iwaFtvp3cvSkEQjQ+dgmNsrmoLFqqFqk6iLS0kkGCEW07HarVispjlwLKoTi8QwDAOBQFEVNKt6Iut5jtDlDyAUwdcuv4i8JG9cGYRhAcyYrrO/uYOj7V3EdIO3jjYwbPK7pbaRtbPKzrgdmqIxyzuDYnchbaEOdvTsYWvvTrrDPURlDEMaE0oJxIPpCamaBsOObJamLGSOdyZptlSsiuVd+UZKeaL6UFOVU/p3joZhSHTDQIjxiu3SkLQ393L0QDP+wRAnB1E5BanMW1bC2UBV0ggb+9D1nriWMGPaKgeI6U0IVDR1comKM8WUAicpJdWDrbzcuoc9vQ04NBv3la+l0JXOrt56Eq1OyhMmVgiNRGIc2N9EYVEaiYnO03tBSEk4HKOn20csppOQYMeb6DJTgifBoqjcWbqENdnlvNh4kC9ue4YHFl5Jmt0cGerDvKAhDs3p2MSYfJwTN4JDs5BodbCju5HihFSSbU729bagCPBaHXxly/Osyijlq/OW8k5nHa+1HDnB5xHg1sZOB0gJiTYH985YxazEE33nmlS5V0xoi/BE/W529zTz+VlrSLQ6uPedx8es59ZscV9OMcN8oCQMZaIEBpIsh4fPz1pDwVCwpwz5f4F5viMtEqMq6cwWxn3RaELFoVpOWqawOquMHx1YT547CU1RKfXEr3AK6P1s7nqa/f1vYEid8oSlXJhxJy4tcYK+mh44E+x89Ks3jJyjopovj8rFJVQsLD5x7kP35e3/fs3ISMJi07jn27eamQgB19+/juvuM7V7hBAjH1tPspuPfe3GE8dQFIRicjhu+fxVwx07DlnF6XzhoXvGPBPJGV7+6YGbx/BXh39Pzkrknm/dOu5csoszeOCZL4xMNX75sU/zd/Q9PWfY8sJuHrjtR8y7oIqvPvk5Dmw6wosPv8HBzdX4+gIkZyUye0UF6z6+mvKFxXEDD2lI6g80cmT7MXa+vp+a3fX0tvWj6zoJiS7yKnNYcfUill25gNSc5HHvtto9DXzm/K9QMCOX77/+Fer2Hefl37zJrtf3M9Dtw5vqZubyci65fRVzL5iJZpn43eTr87PnzUOs/+Mmju6spbdzALvTSl55NuddvYgVVy8ivSAt7jsyGo7yv/c9zKa/7uAT376NtR+9kMNbqtnw5GZ2vLqP7pZeNKtGdkkGF964jMs+thrHOcw4FqcmUZKazNb6RgZCISzq+ECtJDWZJKcDKaGus4f9TW34I1Fa+sySdFURzM3LYskEJr+nCyEELs1JsauAIlc+1+ZeTmuwnUOD1TQHW+gMdxPQg4T1CFEjioExMihWhIJVWLCrNpyqk0x7BnnObCo9ZaTZUhm2yH63s0zffuoNev1Bbjt/PotKc0+9wRCOtnTywo7DeJx2rllaReoQp0xKyevP7+bXP3gFi0XF4bKNe0ctvaDyrAMnh301gdDL+IPP4LBfgKpOJB1jEAq/RTi8GUXxYLMtOavjToQpBU5toT6+feAZ+qMBitzpHBtsJ2zEQMDW7mq6w4N8ZfYNE/Iw+vsCfOPrT/Opey9mzcWzOPnTH2+k1tLSy+N/3EJdbQfRqI430cmSJSVcfsVcbPaxkXt/NET9YDfpjgQuzalkU0ctbcEBCt3JzErK4qWmgyRoNrZ1H8ehaqTahuaXJ6iOEJiBxrHBLrrCPqyKhsdiJ8vp4c/1e7ilZCEu1cpjx7axICUPi6IwGA2T6UzAFwuzse0YIf0kE8eTzRMVhTlJ2WztbKDEnUpMGgxEQyTZnExEVrUoCjO8mbzSfJgCdzJO1YIvFqbMk05/JEiS1YFDtbCx/RhdIX/cfZyM7d3HOdzXTkiP0uDr4er82bgtNvJcSezobiTL6SUQixDSoyRZJ+dlKELgttg43NdOSUIqNtWCW7OO9Om4fhaCMk8ayTYnT9TtYmFK3sj6oyGlpM63i529LxAxggDs63+DdHshi1KuOqf8OiEEQh2//wmXj1p28jrx1j+TY4z+XT3pdyHEhJmHyY4zehtVe3de8keOtuL1OsnMmJ4pLWlI9JhBU3Ur6x/fxG8feJrulh7cSS4sVpWWmjZaato4tLWGu791K4sumTMSPA4jFtP5zX89yZaXdqNHdRRVweV1YnNa6esapOv1/RzYdITdGw7yuZ/fjcsz9hmREvSYQVt9B1tf2s1j33iKlmPtuBNdWO0W2o930d7Qxf63jnDXAx/m/OuXjbt+UkoCA0F+/62/8MpjGxjs8WNzWHElOgn6Qux/+wiHtx1j28t7+Ofv30F+ZU7cD7WhG0SCEfq7B9mz4QA/+eyjNB4xfdOEIpCDkoHuQfIqspHGuS2Vbukb5HBbJ68cqsFptWDTtHFT0t+86lJWlRZi0VSuWTATr9NOJKZz8cxSTAqgOSCZToN5gUARCvmuXPJdZoAR0sP4YwFCeoiwEUGXOgamaKiZXbLiVB24NCcW8e5klU6Ftw/X097nY82c+A4JE6HXH+T5HYexWTQWluSOBE6xmMFzf9jCzHn5XHHzUjxex7hvXILn7HWUHPbVaGohwdDr9PZ/kwT37WijpUSQ6Ho3gdBrDAw+iG504nJcj9VydtyqiTClwOmF5l0oQuH7C+5AU1Tu3/5rACxCpdCVzvbuY8h4ZWZDMAxJf3+QmmMd5OS2cORIKwF/hLz8ZCors0lJTRgzSvL7w3z/Oy+wb18jVpuGRVOpq+tk375GuroGuf3OlTidJz6wUUNnQ1sN+3tb0BSVVZmlLEgxRyH3VKzgsWPb+PruF8lyevmn8vOGghOzuSk2F+6TsjxCCC7JqaDhaC//ueM5VqQX8+HiBRS5TWf0OUk5qEKgCEFVUhaKULizdAlP1e/mRfUgc5KziRi6mRIFshxebCeZdGpC4RMVK3iqfjf/teclbIrGhVllVCVmTdiPqlD4cNEC/nJ8L9/d9yoguCCzlFJPGlfnz+bnR97mS9ufZV5KLmtzKrEPTZclWOwk26Jxd1vmSec3NVvpDPu4pmAOc5Nz0ITCvTNW8VT9bv7fzudxaVauzKuiKjGLZJsTr+UEGTfV5sY1lE0TQvCxsqU8dPQd3ums58bCeazJKkdBkO30xhWqtCgqV+TN4oE9L/OJihUjvKgx9w86PZHWkaAJQJdR2kN18TvqA5w2TvY9g3M3OtZ1g9gEgoUS2LOvkdKSjGkLnIbR2dTNr778R2YuL+fLv7uftNxkDN1gz4ZD/Om7z9B4uIXHvvEU2cUZ5JRljjl/VVWYe2EVAz0+zrt6EfPXzMKbkoBQBP2dAzz94Eu8+ruNvPPX7WxcO5fLPnph3DYEBkP89F8epWh2Pp/+0cfIr8wG4Oj2Wn73raep2V3P7771FzIK0pmxtHTsNLxu8NSPXuCZ/3uFhCQXn/zeHSy5bB4Ot51oJMb+tw7z6NefZPcbB3jws4/wtSc+Ny6AG0YsprP3zYO8/ZdtuLwO7n/w48xeWYnFZqG7uYcdr+2jdF4hjoRzy2+bnZ3BL2+7dtJ1kl0nzkEIwYrSgiGT379vFseu2s6Jh937AR6HDZum0u8P0j14YjAuDclAb4AbP76KeUuLz9m1UNVskrz/QW//N/AFHicQehEhXICOHmuiresmDKMPwxhAyjA26yISvf+KKU0y/ZhS4FTn72CmN4dCdzo94RPCYUIIHKqVgB49rXngN147yLPP7CQ8ZNgrhKCiMov7P3MpFUMvEoCtm49x9GgrWdmJXHvdYjIzvRw92sozT+/g5Zf2Mn9BIYsWF41crDS7m89UXRj3mOmOBP511pq4vylC4Z8r45Pbc11JfG3+ujHLqpKy+Nl5N4/8/yfLbxr597rcmazLje+X9J3FHxq3TAgzmLhv5gVxt4kHIQQpdhd3lS/nrvLlY34rcCfzzYVXxd3uiryJ+Sr5rqRx+wIoTkjlC7MvHrd89LpWVRvX73OSc/jxshvGLHNbbPxg6XUTtiEQi1DhTafSmx73ATR5AyfzvgSasP4DK+FMD6SUHBl4h/5oO1bFwZzEi9HG9fX0oLqmnZdf3T9BQ6D6WDvFhacvRnm6MAxJ0ax8PvU/d5Ked4JEfNGtK0hIcvHNO37M0R21bH5hJ9fff/mYgYuiKlxx90Ws+9iF2JxjP57JmYnc/a1baTjUzOGtNWx7afeEgRNAclYSn/qfj1Aw4wT/YtmVC0hIdvHNOx6k8XALG/+8hbL5hVhsJ65Bze56nnvoVax2C3c9cAsX3bpijDRF+i0rsDmtfP/uX3B4Sw1vPb2VtR+ZoB0Sdr66nzkXzOALD32StLwTUx9ZRenMWll5it6cHjisFnKsUwuQrZrK8f+PvfcOj+M8z71/U7bvYnfRe2cDewPFJhZVSpbVXCRZttzt2I4dHyfni+PknCSfT2L7xI4TH7ccf+7dstWoTkoiJVGFHewkQILoHdvrzLzfHwssuEQHwSJZty5dgnZmZ96ZnXK/z3M/9zPg582zrZRlu1lZWULrgJ88lwOX9c+T2FxuWM0mVEUmltSIJpLpzyVJwpvnRNNGi/pnE5KkYLfdiixn4Q99n3h8L4YxCIAgSjKZ0ozKkgeH/S6yXJ9EVSovG5GbFnFyqlaCySi6kXmSDGHQE/OTZbJNaaB9fUHMZpXy8hxcLisdHT5Onezkpz/ZzVf+4S6cQzn1s2d7SCR0Vq2q5l13LMNkUlm1ugrDEPzy569yYH8zy1dUpEur38FbD0IIwlqClvAgj7U08O7yxePquyRkCqxVuNQcglrKcNAi26hwLmFiD553MBl0keTFnp8ymOjEpeZQ574edZKy35mipa0fIQSLF42hsRAQDMUuy8+pmlVW3LCI3JJM3yRJkli+dRGVdaWc3NvEa9sPcPfnbkW5KDpsMqswjkDfYrcwb1U1J99spLd9fAGrJEss2TifsrmZWlBJkphfX8u8VTXseXwf+3cc4QNfuSdNnIQh2PPEfkKDYRatn8/STXUZpGl4G7XLqihfUMLJvY0c3nWCrfetzyBfF8LmtHL3524ldxacnWcKfzTGnrMtrCgrpiDLiSEE+1va+f2BI1hUlQ+tWc6cvJyMc9k+GOCHL71BMBqnyONiSWkhu0+dY15hLmtrK67asbydMawL1g0D7YLKR1WVWX9jHS89dZjaBcXkl3hG3bqyPL5sYDqQJBWrZSMm0xwSyZMkEg1oWjOGiCJLTkxqDWbzUszmOhT58mpep22A+a0TT/KHlteodRWiGQYdkUF6Yn6e6jjItuJlU9KZ2B0WvvTX21i7bg6yLNPfF+R7393BsaNtHD7UwvoNcwEIBlNVWnn5rjQ5MplUbrl1CX96eC9Hj7aiacY7xOkSUeHMxjaGpuhK4bivi9+c28/6/GpuKJo37nqSJFHlXMa24s9ywv8KBjpzXPXMc03cMuUdTI7e2HkCyd4rsq+8XBebN85n6ZKxxbzxuIbFPPukzWIzU72kfBThgJSAf9HG+Zzc20TzsVZi4TgO9+g0lxCCcCCKr8dPNBgjEUugJXUS8SSDPSlDPi2hoWvGmJ3iZVlm7srqURoqANWksuT6Bex5fB9tpzsJ+8I4h8YQGAhx7khLertNh5tpOdE+ahth/1AaRcBAl4+QL4y3YOyXSPmCEirqpi4Qvhxo7h/kP3e9xjfuvIWCLCddgSB/v30HWVYLQgi+9twu/tcdN1PkdqW/c7Kzl7JsN2uqy3jmyGlkWcakKHQFJm+f8g6mDyEELb0+gtE4ZlXFekHhgmEIOloGOHOsg798/3cprczDZjdnyJyWr63lvk9unpWxSJKEqhShyIXYLNcz0lVguHJGviKp22kRp9U5NdxctIRfnnsZk6IykAjxX407iGhx1ufN45biZVOaKC5eXMbadXOxWFK7LyzycOu2JRw+1EJH+2B6PcMQSBKoF5XE2u0Wiou9dHf5L7t48c8Bd1csvWr7liSJ+rwK6vOmNlNUJJU5rnrmuC5PtcSfK1oixzDE5Q23D2Pp4hRhGu8Bt2plJdbL0EhZUWWysl3jLs8bikTpSR1/XzCDOAkhCPnC7Hl8PwdfOEr7mS78fQEioRjJWBItqaElp9JoFjz546em8kqyQUrpmQZ7AhRUpFKWkUCE4ECKGOzfcYT9O45Muq9kPEkyro273J3rwua0XlURsy8aQ5ZIE6PtR05hN5v42p23oOkGX3h4Oy2DvgziNFz1O9yexTAMBsIRsh3vtMWabRhCcLKth4dfO4IvHCM/y0G264L7glQae83m8Se83rzx77mZInXNXr2AybSIkyopfKh6E5sK6jg40Ex3zIddsbA8u5L5WSU41EnMqYYqH8rKskdVARUVeQBBOJJq1CgucO27eIuKIuHKstHWNjAtb4138A7ewWjoQqM1chTBlSFOF0Z8ItEEkUhi1HLrOOmlS4EkSShjRIGGYbalUsRCCOLRzDENdvv59md+xOHdxxG6IKfYS/XSCkpqC3F5HZhtZvY+e5gDkxGaIb+mcceQLnYRxCMjTWuTCY1EPKUtyS/LoWSCJs7DqFxYNm6aDkA1KWNG364kdMPAYTajyDJ9oTC7m5rZVFtFVY4XXySK3WwmFM/8LeYX5bHzRBOdviDN/YP8+3Ov0hcKc/eKt7bn2GxCCMEf9jTwyOuZWsL+YMpJ+wdPv8Zvdh+cdDsJTccXjjEQiiCEoLY4lznFI/pAVZX56F/dnNHh4GIoY0RXxx93AiHGJ/vThSSpSNLsZ1OmRZwkScKqmJjrKhrl1zSVWYssyzidFnp7gxgXRYr6+0PoRsqzSdN0jKG/gVHrQqqSzRCjK4HewTt4B9PDYKKTwUTXVdn3G2828fzOY0DqPvf5IiiqzJe+cCvVVbMrEDcMQSKWHHd5PJwiKpIkpY0yIdWm5rffeIw3nzmEI8vG+798J9s+uhmnZ8TZPpnQ6G3tn5w4CUEiGh93cTwcH8o8SBkidEVV0oRrzW0r+PS/fRBFnQXSc5WlgVlWK3FNo7G3n9M9fXQHgtyxaF76+R7XtFG+c2XZbr5483qeOnwKVZHJdtp4aP0KSrxv/YbiswkhBN2+0BDpyVzWPhCgfSAwre2V5rh5aMsqvI4RewFdN3j9pRPUb5qPYwy/L03TOX6whb5uP/nFHuYtKs0wBr4Y4ehTxGIvT2tcE8FqWYvT8Z7JV5wmpkWcBuIhzLKCQ51ZeNdsVigpyebQofOcOd3F/AXFSFLKdmD3rpPEY0n2vHKampp8srJsNDX1oOsGwVAsQ2ypazo+XzglIr9KYeaUWC4VFbsw6iUN/ZMyqby8Yxtp9Dv2OEiP5dJKdic61tnax7WEK3Vex93/kDXAWPsfGcPwX5cyjlQ7lv54GyFtcPLVLwNWLKugZqgXniEEPb0BXtlzBnU2SMFF0DUdf9/4L4u+jgEgFYlx54ykF/ra+zm65zTCEKy+dRm3f3wr9qzMQhhhCKKh2KhtXgwhBAPdYzcnTe0r9TvIiow3f4QI2LNsuLwpojbY4ycSjJKVPX6bmLcKKnM8lHk9/PPTLxCKJ9gyp5qKbC+QSuPFkhpOy8XFIhL5WU4+tH4FglTaLmVj8/Z4/swWblo6l9qiXJo6+9nb2Mqhc530+kOp9NoUXcMlwOO0sWZuGXfWL2R1baY3mK4ZPPzjVxACwqE4iiyxfG0thaVeJEli/6tn+P6/bCcSiuP22rn/01vYvG20T9ow4on9hCK/nqUzICNJpqtPnH7d/Arnwr38r6X3YVWmH0p3OCxs3DSPn/3kZf7hK3+gbmEpHo+dpsZumpp6KCh0k5+fxb9/82kMQ5BMarjddo4eaeV8cx8VlbmpsulTnZw/38fSZRWjUn6zgbgeYSDRTtJIhYidqhevuYjhTtwR3U9XtIkzoTfoiDYSTPahiQQW2U6OpZRy+yKqHMvIs5ZjkmfmgxLXI/TEzqVfmV5zIU51xJHYEAZhbZCO6GmaQvvpjp0lMDQOk2TBZcoh21xCmX0hhbZqci3lmKbQ5+dCGELHl+imJ36Oc6FDdMfPEUz0kRAxZFSyTDnkWSupdCymxLYAtykfVZ5ZiiVhROmLt6EZiclXvgg2xUmOpRRZuvScty40fIluumKNnA8foSvaREgbICniqJIZp+qlwFpNhWMxxba5eMyFKNK0OxeNCSEEcSOCP9lDV7SR1shxBhJtBJL9ae8qk2TBqjpxmwrIsZRSZK0hx1yK05SNXcka+n3H/42FECRFjJgeJq5HiOoBTgVeI6qPEApdJGmPnJzStWtTXORaSpFmaDHudttxX6AlKi7ycLihlf6BMOVls6tZSUQTnD18njXblo96cCfjKR8kSKW4htuiAAT6Q8SGSFFlXemYuqB4JE7jweZJx2DoglN7m7jpwY2jKo20pM6Rl08AUDq3CId7JKLlznVRubCM/TuO0HjwHO2NXbhW11zWyUooGKOrfYBEQqekLJusoW4PmqbT0TpAUWk2pglSn2Mh4Ivg90Uoq0yle3Icdv5h2xaeP9GIx25lY01l2p9pIBzlnmV1VOV4M7YRTSR5/vgZnjlymkA0jtNq5paFc7hl8VwclqtX5HItQZIksl12sl12lleVcNeahYTjSe7/5q/oHAzypbuu58YlcyaNO5hUBYua8lA0KWMLr9ua+/jh157Cm+dEGIJHfrGHv/3f76dmfhHP/Wk/K9fN4UN/eQPbf/cmz/5xP4tXVpJXNHbBgkmtxWbdPNYSQBBPHMAwAihKIYrsRZIcSJIFIeIIEUY3BtD1TkxqLQ7HvdgsY23r0jFN53A/JTbvjEgTpETeN9ywkNaWfp5/7giv7TmTXpZfkMUnP72Vyoo8/vTHvZw+1UlhkZv6NTX84Hs7+e7/eZ6lS8vRDYOXXjyBEFC/puayVNT1xVt5rP3fGEx0AjDPtZZ7yr4MAlojx3ij/xHOhQ+TNDJnmDE9hD/Zw9nQAfarT7LIs4UV3m24TWP7Ek2Enngzv2j+clp3sjn/Q6zNvRcJBUPonAnu5cDAU5yPNKBflBOOESKo9dMRPc1R/4u4TDncV/5P5FmmXqob0QI0+HZyzP8SPfHzGGPknSO6j65YE0d8L5BvqWB+1jqWZ2/DqXrH2OLEGIh38Ejr1/Elp58yqnWu4t2lX8KmzFyEmLJF8HHU/xJHfS/QEz8/puYnpA3QFWuiwbeDPEsFizxbWOzeikP1XNJLTBcabZETHPbt4Hy4gUCyj7Hy0FGCBLQ+emLNnAm+AYBLzaHQVsvNhZ/AbSoY82EY16M0Bt9kINGBP9mDL9lNINlHINmLLjLTVxE9wG9b/ueUxl3rrOfesi+jzpA4dXb56Ogc6UjvD0Rpae1nw/q5M9reRNCSOgdeEjshtgAAIABJREFUOMrW+9dTWDVyTwohOPTiUZqHqtTW3rEyQ/tjsZnTfQIHuvwkExoW28gL2hiyCjh75PykYxBCcHTPKc4fb6NqcXnGGE7ubeTkviYAVt60BItt5DkryzLr71rNcz/fRdf5Xrb/cAfl84vHNbiMheMoJmXCtMhESMQ1nnl0P81NPXi8Dq6/aSFZntS+QsEYv/yvl/iLv96GN2d6Ua8jB5rZveM4X/6XVBRAkiQKXE4erF82at36ylLqK0dX/TW0dbLzeBPvXbWY3CwH/cEwjx44Tq7LwfXzqmZwtJnQDA1/MkhICxE3EmiGhnGF9H/DyLPkUmCdnVS1LEuY5RT5qcjPpnMwSJbdSoHHOSvE22Izse09q9h6xzI0TeeRX+zh2T/u4zNfuYPB/hBL19SQ5XVw/a2Lef2FEwR80XGJU5bzIbKcD4363BAxfIFvEk8cwOX8KA7b7ZjUGmTZiyTJCGFgGD6S2mmC4V8Rj7+JqpRgNi2+5OMbC9O6q3ItLjRDxxBizH5nU9pGnotPfnorq+urOXyohVA4TlVlHqvrq6muyUeWZT75qS2EwnFsNhOyLHPyZCfPPt3AoYOpB5MsS6xaXcWGDXPH7Mc02+iJnUMXSc6FDrGj+0dpQjURglo/b/Y/SkfkFLeXfAGPqeCSLtKQNpBuNNng28lL3T8noo8f8r8QNtmFWbZPKZIthKAv3sJLPb/gbOgAmphKBEjQE2+mv6+dlsgxbir8BLmWcuS3SKMzIQSDiQ6e7fwBLZHjaGJ8DUr6O0PHvLvnV5wLHWJb8Wdn/BtH9SBv9j/G4cEdBLW+aX8/qPVjSTgmjPoEtX52dv+EkDZwxUTgU8HJU508v/N4+v+tVhNr19RQWTH7FVKSBE0N5/nel37Og1+5h8LKfAzD4MjuE/zqXx8lHo4zZ3kV9bcuy7hXCiryKKrK5/zxNl559E2Wbalj8Yb5SJJEJBjlpd+/zmPfexaL3UIkEB1/AEPobe1PjeHv7qZqcWoyc+bAWX7x1T8x2OWjdG4RG+5aPaqp89wVVdzx6Zv47TceZ9fDrxHyhbnloU3ULksZZUZDUVpOdnD8tdOcPnCOv/rexymcoZFoMBDh9LF27n1wHZVzClAv6CHnctn42OdvwuW+9FYaM4EvEmNJWSHXz6tCVWR0w6BlwM9gZPJzfzGEECSMJAEtwKlgE0f8x2mPdBLWI2iGhi4MBMYVl9JuK7yBO0u2Tb7iNDGvJJfXT01O8KeD7DwXa7bMp7wmlXJft7WOp37/Zqq5tW6gqqlIldVqwmwxkUxMX/wdj+8lGPoJDtvteLL+G4qcWZkqSTKKko0sr0FVSukb/Bt8gW9hMa/EpFbOxmFmYFrEaVvxMn7UuJMjvvMsdJehytOP9kiSRFaWjU2bF7Bp84JRyyDl82R3jFS4fPSj11NWlkPD4RaEENTUFvCudy0jO2d2GPNkCGk+jvh28nr/o2nSZJZteM1F2BQXimQiacQJaf0MJrrSLyZdaJyPHOHpju/yrpIvkGXKnWg3EyKYHEATcU769/Bi90+J6kEgpXKxK26sihNVNmMInZgeIqz701GiEvsC7GrWlDy2+uItPN7+LbpiTRmfq5IZj6kAu+rBJFvQRZKIFsCX7EqnkXSRpDl8mMfbv8UtRZ+m1LZgyr+PRbFT7liEO5mPITQ0kUQXWupfI5H+WxNJkkZs1l7+QqQI0Pb2/6Ar1pixzCo78JgLsSpOFMmEJhJEND+Dia40udJEgnPhgzze/i1uK/ocuZayaV2TIW2QF7t/RoNvx5jLTZIVx9A5lyUFzUgQM8JEtQAGqfJ3CZm5rjU4lAmiXkJgoI+ZVjSEnt7WMNQpVqKoU2iUPWp/xnATY4nN189n8/VXxqXa5XVy28dv4Lmf7+KLm/8JV7YTYRj4+4MgoGxeMR/8h3spqc1st2Kxm3nPF2+n+VgrXc29fPX+/6SoKh+LzUR3az+xUIyVNy1h1c1L+PHf/27CMagmhfd88Xae+/kuvvyur+PyOpAUGX9vAGEIcku8PPC3dzF/de2o31JRFe79wm0YuuDZn77E608e4PWnDiBJKY2PoQ+94AXkjDOjnwrOnu7iyIHzdLYP0nDgPH29QRYuK8fjdXD+bA9Np7rIcttwe+zpiP/Jo21YbWa6O3wkExqVtfkUl+UgSTDYH+LUsXaEgMGBqfXOnAil2W72nmtjb3MbHpsVfzRGU08/a6rLON2VmniUeLMmTdvF9ThNoWZ2973GgcEGgtq14wMVMyafvM0EdaUFKLI048DHxZAksNnNtJ7ro7auGF0zaD7Tha8/RMPec0QjiZEiL5GyjpiJFC0ceQQwsNluRpbGLwJI9e0swWpZhT+4j2hsJybnx2Z4dONjWk+9pKHhUK387+NPMMdVSK4lK+MHMMsqH6nZPGmkYTovFkmSyHLbuefeVdx2e8pvyGq9sg0UNRHn5d7fEtIGkFGodC5jiecG8i0VI8RJxAlq/ZwN7mf/wJOEL4gGtUSOcnDwGdblvheTPLOWAGFtgK7YWfb0/oGoHkRGocg2h4Xu68m1lGNVHKjSEHEywviT3bRFTtEcPkShtRqTNPF+hRCEtEF29fxqFGkqsFZTn30n+dZK7Ko7RZyMJBE9SF+8hQbfTppC+xlOLXXHzvJC90+4t+zvcKoepnKnuE353Fj4MTQjiZ4mTRf/V0Mz4rzS9zs6o2cm3eZkGD7ml3t+TXfsbPpzVTJT61rFQvdmci2lWBUXCmqKOOkBOqONHBx8ms7ombRwuyNyitf6/8hNhR/HKk9O6FMz3Shv9j3KMf+uUcuzTHkscm+m0FqLy5SNSbYiI6OJJDE9RCDZR0f0FOfDDSSMGOWOxSgT6MtcphxuL/5LDJFJkAyhcyLwMicCr6Y/sykubi781JSuVYfqRZmmtuz0mS4GBsOsWV1NY1M32dlOcq/AJEhWZTbctYr59TU885OXOLWviUgoTkF5HovWzWXbx7ZSd92cUfonSZJYuHYuf/mdj/L8L3bT8PJJult6sdgslM0ron7bcrbevx5/b4CcYu+ExyFJEkuvX0Dd2rk89/NdNOw+QXAgTE6hlwXX1XLTg9ez8qbF41bM2V023veld7F443x2/eE1TrzZSG9rP4loAqfHQVF1AbXLK1mxdRHecXr9SXJKGCxJY0+ldN1A13WESFVF6ZqeLpiQJIlIOM72h/fyt1+9F+tQyvKZRw8w0B9iXl0JsWiCV188wUc+ewMOp5U//eo1QsEYRaVejh1quWR5RTSR5HBLB8c7unFYzITjCcLxJF3+YHpy+IWb11NXnD/m94UQhPUIj7Y/zev9++hPDFzSeN5KWD2nlH/94DYWVUxuZzEVKKrC0jU1/P5Hu9j78ikMTXDmWBt1yyv47lefIBFPcvpoG77+EC2N3cSiyfQ1Mx0ktSYkyYYsOSbVZaUaPrsAHU1rmdmBTYJpEaedXUdpDHaRFDrHA+3IdGREMeyqmQ/XbJ7tMQJD/fBmcMJnAwJBSBtAQmaZ92a2FHwYi2zLSI3YcKW0JtYaCm21PNv5A/zJHiAViTk8+DxzXPUUWefM6AUxkOhkR+ePGEx24lA9bMi9j4XuTVgUx5hEVYiF1GVdT8KIoUjqpPvUhcbhwedoDO1NfyajsMizmY15D+A25WWmghRwmrLJs5RT7VzO632P8Gb/YyRFSvfVHjnFK72/48aCj6BO4QUsS0pKozTJM9UQOod8z026valAIDg0+Byng2+kI1gmycLG/AdY6b0NkzxaBJw65gqqnct4pvMHaZ2Rgc4x/y6qHEtZ5N4ypb2fCb7J/sGnMjRGZtnGYvcWrsu9F5cpBxll1BiGX2IL3deTFHH8iV6yzUUTRhQtin1M01BdaHTHM5skp4jjaqyKY9T6s4GOTh89vQHWrK5m/8Hz1M0vIneaWpmZQBgCRVVYc9sKlm1eSDKhIQwDWZExW0yYbeZx7xNZkVlxw2IWrZ9HIpZEGEbaF8piM6OoCnkl2Xx71z8CjEt8ht3plm9ZSN11c0jGkhiGkXK/tpiw2MxIk8gPbE4ry7csZOHauSTjSXTdAEMgDbW2MFlUTGbTmPMVk8XE5779ET759QcxWVRsY5SQ184vwpll49ihVjZsraP0grRpeVUeWW47Lz4z2nahrCKH9z20nlAwxvf/7Wm6u/zY7VFazvXy6S9tI7/QjSRJnD7WMeHxTYalZUV8/6G7iSe1lCXN8HkxmzApqQeIYxz/KiEE3bEeftr8W44GTqBfIdPXawGSJJHjcnDL8vHNKqcLWZa450Pr8XgdvLHrJCaTwkOfv4n6TfNpOduD1WbmDz/ezRfu/wG6prPh5kXkF82gebekIowQut4zbjujYQihoeudQ35Q10CT34/VbuVD1eM3ox0yPL/UMV2zKLbNY2P+B8Z9oUiShIJKrXM1vpxunuv6YXpZUOvnuH83RdZaZhKrjOh+Irofm+JiS/5DLPHcOMnMVkaVzKjy5GRTCIE/2c1h3/MZL/Fi21w2538Il2l8vUnK28vJmty7CGuDHPbtGNIEGJwOvMZcVz1VjuXXpFWBP9nNgcEn06RJQmaJ50ZWZ98x7nmThmwmskx5bMl/iN5YM75kNwCG0Njb/zjzstZhliauSIsZEV7v/1M6zTm87TU5d7Em524sytiiXxiJ2KqSGRUzNtvsO/NeTmR7Hex+5RSPbT/IiZMd+AMR2i8QiAPUr6omL3f2j0uI1MPe5rQyXYWOLEtY7Ras9rEnAoqq4PJOTgCHH/wTbWsySJKExWbOEKlP9Xv2LBv2CY4+FY1iyLB4jAzBGLeyJEuUVuRiMquYzCqqKqMldeJxDdWkYHdaUE0K+YUeGk9OrhGdCP2hCI8dPE5PMJRRP/GuZfNZUVEy7veEEAwkBvnF+T9wxH/8KiiX3n6QJIksj527PriOuz64LmPZwuUVCCH4yBdu5sBrjZhMKis3zME+BlmfDGZTHfH4HkKR32G1XIeqlo+5nhCpyrto7EUkScWkVs/ouCbDtJv8XiqEECQSOieOt3P4cAv9fUGSk7QqWL26mq03Xl1XWEUyscSzBbsyucmaJEkscG/gkO85emIjs/mTgdfYmPcBLMrMRJUyMgvdm1ng3jDrROR08I00AQBQUFmbey9OdWoNQG2Ki9U57+ZMaC/hIU+gkDbA6eAblNrrJiUSVxpCCI76XiKsjaRUs80lLPHeiCJNrWrUay5iftYGXu//Y/qz/kQ77ZETVDmXT/jdc6GD9MYyw8iVjmWszn73hKTp7YD584q4JbqIYyfaGRgMI8sSupb5Elu88Or2UHsHE2AcvjFWlM1sVtGSBrFIAj3LxuDAaPPj6eJ4Rzd9oTB3LF2A+YK0X7Fn4mezgcHTXTs57D/2Dmm6QhCGICc/i23vWX1J23Ha7yEU/h2x+Bv0DnwOh/29WC1rUZV8QEKgo+vtRGO7CIZ/jaadxaTWYLNunZ0DuQjTVnYaQuBPRuiJ+YnrSVRZIdvsJM+ahTKJtkkIQW9vkJ/+eBc7dxxD141RjqZjISvLdtWJk9dcSLFt3pRFdTbFxXzXugziFNYGaY+eoNq5YkZjcJlyWeK5AdMskxBdaKN0NiX2BZTY50+LoOVZKqhxrkwLnQWCM4E3uS7nHkym6XlIXW6EtAHOhQ9eIDKXKHMsoMBaNeVxKpJKmb2Ow77n0z5ISSPOufBhKh3Lxt2ObiQ5HtiNwUh1iU1xcV3O3ViVt76p4WSwWk1ct6aGNfU1PPL4AebW5rOwLjNScC1dK1cD8YTG/oPNaJrBgnlFM9KAJZIaJ0934fNFMj6XFYnVy6vSvUKnPKZ4kjPHO2hv6cc/GGbvnkaqavOpWzr27B+goNhDcZmXP/ziVcoqcjnR0HbJ/UXLczy8cKKJgy0duG3WdADMbjZluFpfjNPBJnZ070IXk/cUhFSLMYtswSSbht5tV+6adLxNJk8nDrdy5lj7qGjUdGE2LcLr/jL+wH8QT+wlnthPymTaiiSZh3yc4jD0PFeVMrzu/4GiFE243ZliWneOEILdPcfZ3naAlkgfUT2BSVYotHrYVFDHu0pWYFfGf0FqmsFzzx7hxRdOYBiC0tIcKqpyJ72B58ydHSHbpcCpZuM2pdjtVCCjUGCtwiI7iBupShJD6HRFm2ZMnLLNxeRbK2f9pTKQaB/yDRpBmX3BjDQuc1xrMirEAlovffGWoXN37WAg0Y4/2Zv+f1UyUWybNy0zS0mS0saTw8RJYDAQ7yAp4uNG2fzJHgbjmemKQmsNedbyPxvCMJwOuq6+Gqdz5Jnx53L8kyEUjPEv33qKYCjGP3/5Tq6fga9VOBznZ79+lX2HMsvPrVYTv/zhx8mzjJ8KzXLbuf3eVXgvcCcXhiASjmMYgnseXIckQSScsiu54bYleIaczS1WlVvuXEFpRQ5Ol5V7H1zHiYZWAN7/4Q2EApM7rE+EnmAYfzSGphuE4hf089PH1ysljAQv9rxKwhi/5Q6AKqlUOsqZ76qlxF6EQ7Fjkc0zqh69FOSaL0/DYiFEhp3QWPebEALNMDjV3ktfIEyOy86cojwsQ2an07lH25p7OXOs/ZLHLUkmnPb3oyolBEM/JhZ/A0EMIcIIEb5gPSd22804HfdjNa+5bM+TaV0NBwbO8c0T26lw5HFX6WpyLC4iepwDA+f42dldJAyND1RuHJdahMNxXtl9imRS5z3vXc173rcGm808qRfT5Wi/MF041expRQOGX6oO1UM8MUSc0OmNt0wqbhsPJbb5s+ZSfSF6Yucy/JpMkpVsSwny9AOS5FnKMcu2DO1OW+QENc5VszLW2YAQAl+iO51ShFT0KM8y/sx5PFhlxyiH7ageJKaHMI/jvD2Y6CJygVO3hES+tXLKadG3E4qLPITDcdraB8lyWXG6rMRiSawW07Sag76D0XA6rHz0wQ3ctGUh/mCUoyfa2f3q6Sl91+6wsGJNTcZnVpuZ+g1jE7hFy0bMdU0mlaWrRowo8wrc5N00A0HwODArChU5XjbNq8JqUtNz2WzH+FGa8+E2zoSaxm0Kb5JUap3V3FN6OxX2MqyKBXUKRTVvJQgh6AuE+cYjL1Ge5+U96xZTdFF/PyEErX0+/uOJV9jb2IZmGKiyzNziXD572zqWVRUT9EfQkgbeXGcqi9TlHzd929PhG3vBDCDLdmzWG7Fa1qDp3SSTJ9H0doSII0sOVLUMk2keipw35Ch++X67ab0Zn+9qYI6riH9c/B6yzCMX6e3FK/jZuV0803GYByo2jNs/LpnQaGsbwOu1c98Da/F4Lk/VzmxDQsZ1QbuTqcKmuEa5WUf0AEkRwyxNX+eUbSme9nemgsFEF/oFMzGr4pjR8UqShEm24Dbl0xsfmeVe+Pe1AAMdf7Inw3FdH3Jjb4+cnNa2YnqI6EVGpEkRIzmBD0tIGyCmj8ySVMlMrqV8xm1L3sroHwjxm9+9QcPRNrZuXsDt25bw3I6jXFdfQ2nJ7BDJ4toC7vn8NqwOK+68qyOk9xZkcc/nt6EoMnkllyeacDFMJoWFC0pYuCCVBs3NcfLynku38bjacFrMDISj/PClN7GY1PRE/e6VC1ldNVobZwiD85FW+uJj2w6YZTNb8zdwV8ltZKmutw1ZisaSHDzawoI5RXiH2ho19wyysyHlV+dx2Pjg5szsR38wwrcee5mXjp1NV+8C7G1s459++zzf+ti72fPHQzSf7uLvv/0AyYTGVz7xExKJsdOf4WCM+k2zV8UnSTKS5MYsuzGbZr+7wFQxLeIU1RNUOHJxmTJf+iZZodKRl3a2Hg9CCDRNp6AgF6v1rdNTSELCPIOcs0m2jvLC0Yw4SSOOWZ4+cbJchvLw4d57F7YUUGVzyml8BlAkdRRZDCb7L2mMsw1D6IS1zJmQJuLs6fv9rGxfCAPB2A8SIQQxPZwR4ZMl9c8y2gRw4OB5nE4rt926hFgsiaoqDA5E6O8PzQpxkiSJ6sXlfOobD87CaGc+hrzSnKs6hrcTqvOy+eLN64knNcKJJE6LGbOqkGUbO8KrCY2WSDvaGG2jAFZ6l3JPybtwmd5e+sJINM4zLx0nN9uZJk77m9rRDYHFpLBhQWXG+kIIXj5+jj0nmxFCUJbr5rp5FbT2+dh7ppXzvT5+/8phttVXUVmbP/QdiEWTbHnXUgpKMlttScCBPZmmwsP70UQc9YLeqYbQiWg+nBNUcI+FC8ndlSS80yJOK7OrebnnBP5kBLfJnm56G9OTnAl2ssRbPqF4WlEVvNlOwuF4xgFf+5DGTbtMBAV1VGpt2P16JmOYzMRyZhBD0ZGR30OW1CnZGIwFCXkUWbwwunItQAiDuBGZfMWZbh8x7vUtMIbSmBeeb/ltX0k3HgZ9EUpLvFgsKu0dvlQTYl1/p+bpArxdIiCzBUMIdp06x/bDJ0nqOhZVZdviebxr6diRjYSRpD06tndUlurifWXvxml6a2Q/po2LLp3jranK6eqCHEpyMtN0kXiSX+8+SFzTKfK6+OZH7qCmMIdQLM43H9vNE3tPcOBsO+9dt4QlKyrT38vy2tm0bQlVY2iRDUNw4lBm9XBSxHi19xfU57wXu+IhaUQ5FXyV3tg5thZ+ctJDGvZp0vRuDMOfStXJdmTZPdT8t/Cy3zPTIk5zXcU80bafbxx/nMWecpyqlbiR5Eygi8O+Zjbl1/F0x6H0+lXOfOrcI6FTm83EwoUlvPrKaZqb+1iw4PKknq4VSJKMxMXpF4GYsena7F8MAjGqfYmMjDxD4zBJkpAvJovjRF+uFgRiVGPkK7nvi9ubgIQ6RQuEtxtqqvJ4bucx8nKdhMJxnn3+KP39ocvi4fRWhaxIxBMap850cfREO8FQHLvNzML5xdTNL8ZmvXzXjhCCQDDG0RPtNJ3rJRKJY7WaqCzPZenCUjwe+4QvKV03aG0foOFYG13dfhJJfcxJhcNu4Y5bl07pdz/e0cP+8+184cZ15Gc56Q2F+f2bRyjLcbO2ZrROUTN0BhJja21W5ywn25w9pXZUlwOGIXh1byNFBR6OnGyjuzdI/fJKViwqR9cN9jWc5/CJdpx2Cxvraykt8qDpBsdPd3DoWBuxhMbcqnyuXzMHRZFJJHVeePUkza395OdljbJ+6PKlWnXNKcodZZx84Gw7zT0p3ecdq+uYW5yLJEm47TbWz6/kxSNN9AbCdPoC1BSlIkOKKnPnB9aSV+geU6uc5XVkNKuGVFbCKmexv/9Rlme/mwbf0/gT3dTnvnfS86UbPoKhXxCNvUhSO41hDJCahCooSh4mdR4O+7tx2O5Ali/fM2RaxOnJjgP0xPy0Rvo44mtBkeSU4ZShIUsSz3U2ZKz/7tKVFxEnM9tuW0pTYzf/9YMX+PRnbqCsLAeLRZ1UIH51Z10CYwZkZ6weYBLyNdX8NjWeTJJkCD3d5266SFVkZEbULoeg/dIgjSKGFtnBXaV/Mytjtcg23OaCcfY8et8gZhiFfOtj6ZIykkmdx586RG9PgFAozj13rqRwnHYhf46IJzS+88OdvPpGI7FYEk03EELgsFtYtbyST31kE/m5s6/N0TSdgw0t/N+fv0xHp494/AKHe7NKUYGbjzy4gfqVVZjGaKMST2g8/Og+Hnv6EOFwHFmWECL1eWKo0auqytjtFvJzXWzeOG9KxKk7EKImL5slZUWoikyRx0VDaxdd/uCY6xvoBJKj+9CpksoC1xxMV/H5JITg0PE2nnzhKDdsmE9+bhb2IRnLwWOtPLnzKLdsWkDfQIgf/34Pn3xgA7leJ/5gjPKSHBRF4pFnDpHtcbC0rpTdr5/mxT2nuP2GxTSd7+PMuZ6M/YViKYlAnjuzdYmm6zx/6DRJTScvy8HNy0b0Q5IEJTlZuGwW+gJh/OGRqkhFkbnxzvENjldvnMuS1ZUZn8morMh+NwcHn2B7+9fJtVSwIf9DuNTxe7mmZD7nGAx8lWj0BQTJVAsWeaillzAwDD+x+G7iiX3E4/vxur+MLOdcFu4wrSvmgcr13Fk69eoojzkz/aBpBlaridVranj0T/v4yt/+nhUrK6mozMPhMI+b5quuLWDRoqtriHdhldhUMdxj7UIokjrlBqpXBBJYZDsSUlqfpguN5AUanOnAQE+3XRmG7RrzJpIlCctFGjNZkim01eBQZt4cdSoYK5VpCGNG19fbASaTynVrarjuogqud9JTI/jDo/vo7g6wfEk5leW5SBI0t/Tz2t4mdu46gabp/O1fbcM+QxfysaDrBnveaOTfv7+DQDDKnOoCFi8sxeO2EQrFOXaynROnO/navz/N5z91A1s2zsvoQSeEYMeLx/nJr17BZrNw+y1LWL28EpNJ4VRjN9ufOUxL2wC1Vfl88sObqCzPweuZWro612nnldPNnOjsIc/loC8U4UxXH7eNk6ozhCAxRrGGx+S+bGX/08Xcqnxu3JDZ7PrJnUewWk30DYSJxJI0t/bT0e2nIC+LuVUFnGnuIRSOIcsSzW39LK0rZdfrZ7hhw3w21tcypyqfQ8daM7apDgUoFDlz8n62a4BjLd0IYM3ccoq8mUTcYTFjUmSSuk5CGwkGDPc8HA82uxmb3YwQglOBV9DT7xUJp5qDIpmQUGgNN+BUc6hwLhtzO0KEGQx8jUj0GVSlDJv1JiyWFahKGZJkwhARNO0csfheotHnCEV+gyJn43F/mcuRqZkWcSqyeSdfaQL4/RG+9q9PEArG0HWDwcEwO3ccm/R773lv/VUlTgKDqB6cto1AwoiNeiGqsmVU+frVhISEQ/UiS0qa5CVFnLg+s07hhtCIaJlVZhPNJK4GZEnBrmYSJCEMIloAp3pp1/hkSLWoSTVkHhaIG0K75gT0VwqhcOqF5rCbicWSHDnWRllpNoUF7kn6UV1ZUejVEqECNJ3r4QufvpEtG+Zjt6f66YXCcR7Zvp+f/+Y19h5o5vV9Z9mycXqGteOPsvyNAAAgAElEQVRBCEF3b4DfPrIXnz/CuvpaPvHQRspLs5HlVJahs9vPL3/3Os/sPMqvH36D2up8KstHZvc+f4Sdu0+g6YKt18/nIw+sTzdnX1RXisNm5vs/folAMIbFrJKTPfXJ1cKSAhp7+vnWs6+gGwYSElvralhaNp7Z4dgZA6tiwaKM35/wSiI/N6U3Gh6LEIIBX4SqshwURcblsHLvtuWUFXvp7Pbzsz+8Rk1FPiVFHixmNZ2Si0QTZDltSJKEqso4LiLTXqed870+BkKRtPm0YRgcbu6ktd+Pw2JmVW1pOuo1DN0QCMGolKYQIr2d4fY8QggMPSUCkeURYtUTbyJpjEyqJWRyLRXoIklX7Aw55hgVjE2cYol9RKPPocgF5Hi/gdVyHdLFml/LOhy2uwiZl+Hzf51Q9E84HO/BbJq9qr5hXNEYpSRJ2O1m7HYz+QWTty4ZRu5VKiEehkAQTPZhoKNM45RF9QBRLXDBJxIuU861FXECciylKJI5TZxieoiA1j9toiiEIK5H082Nh5FvrRrnG1cHMipecyGKpKaPWRMaPbFz5FsrJvn2pcOp5mBRHGhaYmjfCfriLRjCuKbSuFcCe14/w+BghHffvoyf/vJVWlv7sVpNfOzD11NSPD6JTcaTnN53ljkrqrDMYqRlPBi6wbE9p5izonrMxriXEwsXlHDL1kWYTCMRHYfdzC03LOZgQyv7D53n1dcbuW5VDXb77Dxb9h86z/GTHWS5bHz0wfVUlI2QIkmSKCpw89EHN3Cg4Txnm3t58eWTPHT/OhQltU5XT4Ce3gAOu5nFC0vSpAlAVWQW1ZXg8djp7Q3S1eNnUd34PeYuhsNi5n31S7hj2QIC0ThOixmHxYw6ju+XhIQqm0gYmVF0k2zCNMMimNnGWLf93Op8FFlmY30tqioTT2i4HFYaTrYTCMfYsn4uiiyzfUdDmtiXFHk4c66bxfOL6ekL0juQmb6cV5LHoXMdHGhqJxiN43Xa6PGHeWLfceJJjZqyfNbMHV3kFYzGSWg6qiJntLkxDMEzD+/DmWVl/U0LURSZU0fa+OHXn6Kvy88Ndy7nvk9swmI1sT7vQcY1fGI0KbsQkeh2BElczo9gtaxHGie9Kkl2nPZ7iSf2E4luJxZ/9a1PnDweO//69fum/T2r9eprZMK6j7DmI8s0teiJEIJAsi+j7F1GJtdcdk3McC5EgaUak2whMVRpposkfbEWdJGcNsnrijVlNAoGKLFfPb+NsSBJEm5zPg7Vk3ZM10WSzugZ6twbR2m+ZhsecwF2JSttwCkQ9MZbCGs+XKY/L1uCgYEwBflZtLUP0t8f4i8/cyNPPHmIvr7ghMSp5UQ7P/+n3/M3P/4MeVeAOHWf7+XHf/dr/vvPPofNeWU7GSxdWDrKDFSSJHK8Dmoq8zhwuIWOLj8DvvCsECfDEBw4dB4hoLw0m6qKvFHPLEmSyMl2sHhBKZ1dfvYeaOaD71+LMnTr6LqBbggURcZsGm0kaTIpKLKMbhjo+vRqKPtDEXyRKJW5XlxWC7ph0NjTT67TQY5zdLpPkmSssmUUcRKXVKhzeSFJEnfevJSfPfw63//lbkyqQl62k9tvWExBrgurxcwv/vgGNqsJWZbSGuFtWxbx49+9Ske3H7vNjM2SeT2sn1/Bw3saaO4Z5P889SqLK4rY19hKQ3MnkgRbFtdS5B0dqOj2BQnHE9gtJpwXRKMM3WDnE4dYu3UBkiThGwjz6x+8iMmksOX2pby4/RDzFpWyduuCdNBBCEFQ66M1coSYFkxLRNymfOZkjd2aJZlsRJIcmE0LxiVNw+dNklyY1LkgQNNax133UnBFGYmiyGRnX56yz2Er+Ytzt0KkfhaJSwuxB5J9DCQ6cKlTE5vpQqMjepqkGMmtK5JK8TVGIgBcphyKrDU0hvalP2uJHCWqB3FKUzfCFAhOBV/L+MxjKiDHXDar450N5FrK8ZqK0sRJYNAWPclgootsc/FlJbceUyFec2GGMWhn9Aw98XM4Ve8VJdZjidUFAmOK/bwuFXa7mf7+ED29QWqq83Bnpaq0xmoEK4QgEUsSj8R546kDxKMJ/H1BVHPqMebyOlFMSjpdoCV1YqEYuqYjKzI2pxXVnHqJG7pBJBBFCIHTO+IynIgniQaiWB0WzDYzybhGLBxj7zOHiEXiBPqC6YiTw+3AZLn87tIF+e4xPYUVRSYv14VJlQkEo4Qj45uuTgcCaGlPmUUOa6rGQ3VlaiLZ0t6PYRgwdC15smy4nFZ6+4J0dvsxDAN56NkshKCzy084EsfltOJxT8/T7mh7N6e7evnw+pUocspL6M2zrRR5srixrnbU+qqk4DW7CWiZ0ZeEnpi0BcvlhixL3Hfn6nQ7kwtRUujhMx/ahC+QSqs5HRbcWTY8bhufe2gT/mAUm9WE2aymxfnzqvP5b5+4kUg0gdNhQULC7RqJkC6qKGTN3HJeO3WeR14/ylP7TxJLaAgBNYU53H3dolHXs6brNHX3E4rFKc/1kuMaeYcbhiDgC1NU5kWWJU4caqH5dDf/8J8PUDmnkM7WARr2nmPt1gUj2xMJXun5ObpI4jYXpiNNE7f40pEkFUlSIP1GHw8iTa4El6d6+uqHcmYJUU3j1dbz1BeXYlVVLKqKIQTHe3to6Omi3O3hupJSVHlm0YRgso+W8BHK7AtQmLz8N6wNcjKwJ+Mzt7mAIuvoG/tqQ0JiqecmzoYPpavpumJnaQrtZ6nnpilvpz1ygpbwkYztznHV41Czrrkom0PxMMdVT2vkeLrysTt2lpOBV7gu995ppWSnC0VSqXNfT2NwX3rfUT3Im/2PUmybO8pA9HJCQh5lxmoInYjux65OPZ0+U6xaUcWvfpsi2/e9dw1CCGxWE54xhMJCwKuPvMHOX7/C6f1NxEIx/uWBb6OYUr/Vf//pZ6ldXpWK9vYFefz7z7Ln8b1E/FFUi8r6O+u5+/O34S1wEw1F+en/+C1HXjnJ//zjX1NcXUAyofHkD5/n0e88zee/93FW3LiE/c8d5qkf7aDx4DkCAyG+/tB3UM2p+/8vvvUQy29YfNnPkXWCXp7WoYhDMqmjabMUPREiTcIck0SwhjU0iYROPKFjsaTOTVGRh9XLKznT1M1TzzVQkJfFvNoCFEWms9vPH5/Yz8BgmLX1NcypGbsCdTyEYnEUWUaSh1OHqeKOQHRs4miSVAqs+ZyPtGV8HtRChLSZaTlnC5IkkTeOvkuSJLxue9q88kLkZjvJHeN7sixTlD92RaokSWQ77Xz2tnUIYH9jG5F4ElWRWVxWyGdvW0eOa/S+BkJRDp7tQAgozcmiNDdz+4qioKoK8ViSvS+fpraumIqafEwmBU+uk5A/0zPPEBoxPcjNRZ/HMUVNqaqUEE8cQtPaJpWQCJFA084DAlW5PNHha5o4DQvPhkVnEyGSTPKvr+6ixptNWZaHT6+sx2k2838P7qPQ6WTX+Wasisqq4qnn0jPGguCI70Xq3BvJmTDdljI/POzbgT/ZnbFkQdbGa7A0P4VS+wJKbHNpjRwf+kTwZv9jlNsX4p0kAiOEIKz72DewndgFonKnmk2NaxXqZTHuvDRIkkSd+3r2DWzHN/Q76SLJ3oHtFNvmUulYll5vMozlSzPR9yRJosqxnBxLCb3xEXO45lADe/sf57qcezHJ4zfLnmj/M2mTY1NcmCRLOjqaFHG6ok3kmEsvO+EtLvLwqY9vBgEulxVdN7j5pkV4xnhZSBIs3riA8rpSHv7mE7ScbOcjX70f75B1QUntiDj4ke88zSuPvMGdn72V8vkldJ7t5pf/78OYzArv/3/uxuF2cNfnb+Pkm4388VtP8NF/eYDOpm62/+A5tj6wgWVbFgEwd1UNeeU5PP3/7eTQC8f4+Nc/QF5pqhKrsPLKNK6eiBAlNR0hUtEnZRJLlylDkrAMRfESyYkjj8PLZUnCdEFPUUWWuev25TSe7eGN/Wf59vefp6TIi6JI9PaH6Or2U1OVxwffvxbvNFtveexWXj7TTCgWJ8tmJZJIcrKrl83zqsdc3ySbKbeX8ObAgYzPw1qYnnj/n5W2UJIkFpYV8PfvuYGG8530B8N4HTYWlhdSnucZpW0SQhBPauS47GxaVM1NS+fgto9EsGRZIrcwi4a950gmdA6+1siHPncjqklNpeR8ERwu60VjkLEpWcSNMA6mRpwslusIRx8jFHkYm+3WoX50cGHkSSBAQDzRQDT+MpJsw2JePuNzNRGuzbf4EAb6Q/zzPz3CdWvncP8DaydZW5Bjs/PZVddxpKeb5882csfc+YQTCT69sp7X21p5vb11xsQJwJfs4sn277Ct+LNDgurM0yeEICliHPPtYv/AkxnLci1lLHCv53KURl4qJEnCoXpYnXMnA/EOwnpKl9Ubb+GZzh+wKf9BCm21KGNofwxhEEz28UrvbzkZ2JPOV0vILHBvoNK+5JqLNg3DqWazMf9+nu38Ybr6MawNsr3jP9mQdx+1ztU4VM+4D1UhBAkjRswI4U90cTLwGnmWCpZ5b5503zbFyfq89/N0x3fTLuYGOq/3/YlAso/VOe8m21yMKo1d9ZNqW5AgrocJJPsIaL1UO1ZgVqbfyifHUoJD9eJLdgGQNGI0+HZSbJszKWm+VPj9EXxDM9JB34jDvGsMAbYkSeSV5ZJXlosnP4vetn4q60rJK8vUHXY19/LCr1/m1o9t5baP34CsyCzeuIDzx9vY88Q+rn/vOirqSimpLeTjX/sA3/z49ymdV8ybTx2ganE5d3z6ZmRFTul4ir3kFHvJLvRisZupWFBKcc2V1Tj19AXTE8gLYRiC/oEwSU3H6bBgs82O0FkCSoq8NLf009YxOOa+h9HakUrp5ee5UC5qxp6b4+R9d6+mo8tHNJrAMAwMA+ZU53P/vfWsq68lJ9sx7rbHw5KyIvY0tvDF3zxJrstBfyhCdZ6XlZVjGyorkkyVo4Is1ZWRrjMQHPYdYUPuGqzKtTe5u1yQJImSnCxKcrIwhEiTpfHu8+LsLP7xvlTmwawqGeupqsK2e1fxs+/s4LUXTrC0vprl62qRJAgFovR0+ti8bEnG9mQUJEnmqY5vUmSbl454e83FLPaM/ex02G4jGP4Z8cR+evs/idv1F5hMc5AkOyCD0DBEmERiP77At9H0Nhy2O7GY6y/1dI2Ja5o4hcJxWlsHmD9/8pYdkiRR5clmQW4emmHw7NkzDEQjCMAsKxQ6XRzu7prhSCRsipOoHqQtepJH2r7BwqzrKXMsJEvNHRJWxxhMdHI6+DrH/S8TM0YiLybZyjLPzWSbiq5ZEiFJMrXOVfRkb+PV3t8NuYkLzoUP4mvvYonnBopt83Cb8jHLNnSRIKgN0Blt5GTglQsiVSmU2OdzXc49KPK164gtSRJzXWvpjjWzf+DJtKg9kOzl2c7vc9y+m0rHErLNJdgUF6qcqjxMGnGieoCg1s9AvJ2eWAu98WY0kWBT3genuG+ZGudKlnpvzth3UsQ57Hue8+EGal2rybNUkGXKxTzktaWJBDE9lNp3opO+eAud0UbyLGWU2uswM33ilGepIN9amSZOAM3hwzzb9UOWeW4h31qBVXECKXPThBElpoeJ6iEcqpsS+8yrVg41tPLCS6lrR9cF/f8/e+8dHtd1nXv/9ikzZ/oMMCiDDoIE2AtIsIvVkqhuNUey4yY3XV8ntuPcxImf3DiJ8yVx8qXYzmfHLW6yZEuWXNRlNUqiSLF3EiAJovcyvZ/9/TEgQBAASbBJcvw+j0Ryztln71P2Puus9a53DUbQNZU/+eyNVFVemoxFy+FW4tEEzQdaeOQffzn6e/vxToa6hwkP5eamEIJ5a2az5aObePj/eRxXnpMv/viPyQtcXUmK6eLw0Y4Rr+I5mU6ROC2tA5impKjQfdE6SBeCUAT1iyp5Y8cJTjb30T8QoXCSzOZ4PCcfAbB4QfkEfulwMMZ3friVeCLN//nsFpbXV1+R9c9lWPmj96xib2sXfeEoeXYb9ZWl2K2TrzU5D28lZfYSjoSOj9t2KHicjngXNc6qyx7Xuwln7oN6gfshhEAVArt1cqNcKIIVG2dTVOojHIwxa14ZrhHOWjZjctv9K5lff26msqDQmEGBdXy2tXEepW9Fycfn/iKDw18mmdpB78BuNLUUVS1GCB0p42Qy7WTNPkBgWFfh9fwpXGIFjAvhHW04xeMp5CQk0clgqBqKEPzfV19kKB5HEYIvvfwCVlXjSH8vB3t7KHRcGjFdEzpL827hcPBVhkZeVq/1PYJjyItVsaEIjaxMkzCjI1l0Z4VOUKh1rWCh9/p3tBEBoCtWluffTiQ9wIHhF0f5N0OpLl7rfRi75sGq2FGFhjlScy2WCY4rWAuCgDGTzUUPvCsK1xqqgzX+e0llYxwYfglzhEyYlRlOR/fTEj2IVXWgCwuKUDGliUmGtJkibSYmlKuZXt9OVvvvJZ4JcTj46jiV+eF0D7sGn0QXViyKLefdFAJTZsnINGkzfsXKxlhVO/W+m2iO7hvVWZGYnIrsoSt+ArvqRht5dk1pkpVpMjJN1kwzz7vhsgynZfVVzKkLjBxbMjAQ4bcvH7lAq/MjGU9hZkz62gfJnBVq0qwaDTcuxuUbWwdUVSG/xEcynsJn0fAWeqYtw3G1cfBIB4eOdTB/dumoLk42a3LwSAcHj7Sj6yrz55bidFwZmQQBLFlYTnlpHl09w/zyqT384ftWYrNZRon36XSW5148RHvnEC6nwXWraidUfzh0tIMTzb3UL6xgZvWVDWsauj5peZWp4NXdNOQtoTF8gsxZiQ8JM8FvOp/jwZoPY1Wtb1vplXczdF1j1ryJkRxvvpONtyya8Lum6NTn3T7uNynlWeKYEyGEis3YiD/Py3DoqyRTe8lkO8hk2xgji6sowoXDfjdu18fR1MqrNo/f2YZTLDWSqXFh2HWdP1m5mu0d7RTaHSwNlBBMJmkPBfnu3l24rFY+u/xC4b6pUWKrpdQ2m5d7fkBv8jQmGcKZfiYX+c9BVwxqXSu4ofhTF8gYeOfAUJxsKn4Aj6WQ3YNPE8nkXPEmWSKZQSIMTtlWExZqnEvZUPSha8KPuVKwqW5uCHwKn6WEfcPPMZTq5ozxKzFJZMMkzn8IIHf+073PdtXNlsCD+KwBDgy9OM7rAzkPVDp7ZbKlzodq52LWF/4h2/oeJZYdEzCNZ0PEs6FJ2wgEGfPSFObPwOGw4nCMhUnyfA7e2H6CoeHoeT1OQlFAwiT0MgrK/BhOgxs/upEbPrR+Yir9WS/4liPtPPZvT7Lp/Ws5sq2RR//l13zk7+7D7jpHWV4RI/1d2/LDuZIkFv7x357hjpsXM7O6EEURNLf089NHdxAMxZk3u4QbN80bZ7hIKYlGkySSadLpLOl0lt6+MCCRpqStY5BEMo2mqVh0FZvNgm1Ea0kIQWWFn/vvXs63/vtVHvv1bnr7wmy4rg6H3UoymWbHrmaef+UwUsJ7b13CgrmlnOsRMwwLqiI4dKyTnz2+k7pZxbnsrxHOqmHVKCp0EyjyoOtX91UkhGBDwRreGtjD0XDjuG37hg/yZNcL3Bq4/vfG09uErEzzUs93uCHwmSn3EcKC1bKcQv9DpFIHSaZ2jZDFkyiKC12vwbCuRlMrAeWqvn+uytMqpWT3rmZ27TzF4iWVLF8xE0URxGJJnnvmwIUPMILTp/tJpS4+LbrA7uC2WWNfv/k2G/k2G/+4+UZ0RcGqXdrpSiSJbJT5ng0YqpPdg0/SGN5x3jIZXkuAhrzbmOu5Dpt65etIXS3kyMJOVubfRZExgz1Dz9IS2T9OVmFCGwTFtpnM92xgrmfdVVffvtIQQqALK8vz76DCMY+Dwy/TGN4+ajReCDbVRYVjPjMc9dQ4l067b4tqZ1X+3VTaF3Io+BJN4beIjGg8XQgKKqX2OuZ7NmFVLj1UowiVJb4bcag+dg3+mo748Qs3IhdyvBy0tQ/S2jammj4cjNF8uo/1a88v2+HxuwgNRggPRigoHyubIYSgekE5gepCtj+5i6XXLxwlc6cSaYa6hykoz0dRFaLBGA/9/S/wl+Zx35/fybG3TvC9v3iIeavrWHfvqnFz1p3vIhaOM9wbGsdxutrzurgwJzT56C938a3vv4rTaUWQozGYpqSmuoBPfmT9BDJ9MpXhp4/t4HhT92htuKFgLq09lc7w79/8LXabBV1XsVo01qycyS03LMQyQgrXVIVN62eTTKX50SNv8sIrR9i6rRGbzUIylSYeT2MYOnfdtoS7b6ufwK+SUjKvroRVy2t4+bXj/OyJneO2K0Jgs1koL/Wx8brZ3HnrktGMvKsFq2LhztKb6T81QF9q7JlLmime634JFYVbS25EE+q7Zr2+HJz7EZDJmqSzWVRFmcBlmgqmKTlxpBNNV6iaVYQQgmg4wTOP7mSwP8LKjbNZ2JALyQXT3VhVJ1bFzkCydZQPC5AxU0QyF66eIIRAYGBYGzCsDdM84yuHq2bmf/+7r9LY1M0brzdRv7Qai0UjEk7w7f96+aKPYZrmRafYmlLyWttpnjnRxHAiMfopuiRQwoNLL5cgJkmZsRypzlZHYaCSlfl30RTZSVe8iVC6j6xMY1Hs+K3lVDoWUumYj0PzXXIWXcCYxWdqvzfuN7t67QqfaoqFmc4Gyu3zGE71cCqym65EE8F0H2kzgSYsuPR8CqxVVDkWUmTMwFAdl/0ifTuhKTqlttkUGTNY7b+HrngTrbHDDKY6iWaGyMg0mtCxKnZcej75ljKKbTMpsFZgqE50xbjk7BxNsVBun0vAVsPagvvojDXSHj/KYKqTcHqQjEyhoKCrBnbVjc8SoNBaRYmtFqeeh0WxTVI8eHqwKDbmetZS7VxM98i5dydOEs+GSZsJVKFjqE7cegH5llKKjBmU2GZd1LGzMks4HcSpuUbDfgDNp/t46ZWjo/+22yxsuX4+1VUF5z3eqtuW8cz3XuJfP/UtKmaXks2afOj/3ktZbQlWu5VPfvWD/Odnv89fv/efCNQUg5T0tg6weON8PvTX95LNZPnNN5/jxN5TfPFHf0xhhR+330XjrpP86Ms/Z8aiSspqx4jxDVsW88TXn+brf/RdquaWI6Xkrs/dSt2ymvOO81KhqgplJT5mzihk6eJK5s8p5Y0dJ9i24wRDwRg11QYrG2awbnUtxYUTy9NIU9I3EKGnf8wnbrXqlJflwuemlETO0n0aDsYmvEhthoXbb1rMogUVvLatkb0H2wiH4zjsVubUBVi3qpaZNYUY5xg8Z0q2/OLXe9h/qJ2iAhc+rwPLiKyCNCGRTBOOJDjZ3Mepln6cDiu3bpkY1rmSEEIwx13HPeW380jrEwylx8SJI5kov+x8hrZ4J7cGrqfUFsD6O0wYl1IyEI6xr7mTVw+f4khrD5FEiqw02bxwFn98yxocRq7GXDqbZSCcS+Dw2m3Yzrrf2azJI99+hZlzSyifUYg0s/z4Gy/yxotHsNkt7HjlGF/6t/uZUVfMtr6HqXLWU+Ns4Im2r+DQPJzxUpqYIzzKdweumuE0d14p4UiCOXNKRl3IUkIqlcHjsVNa6hvnMp8MoVCcjvaL++oPp1L8YP9eNlRWU+0d83j47ZcfIpMyt/DDGQ+BjSLbDIpsk6e/Xgloio5bOf/LYzrIZk0OH2onnclSXpbPwUNthIZjeLx2Fiwox18w5hUzTUlX5xBHjnQQCSfweO0sWrSF1eX3kkikefG3h1i6rJriYi+9vSF2vXKKSGWQBQvcJBJptr95gqpqP5WV/nfdl9sZ75PHUojHUshsz5pr3LeBrhi4PQXXtO8zUISKQ/NQ41pGjWtZjtMlTdTL/AqPZEI83v4jbgrcQ8A2Vndy3do61q2dPkeqvK6Uv3zos+x7+RDhwQieAjeOEa+LEIJZS2fwpYc/z57fHqDjRDeqptBwUz2L189Dt+qEBnLCmR/+mz+gbvnMnKfVYXDH/96C02un80Q3ZbVjWVoF5X7+8qHPsfv5/QT7Q7jzXXj8V09vy+u1861/G59ocNdt9dx1W/1FtbfZLHzpC7dc9jg0TaWmqoCaqgI+cpFt4vEU3/nBVl5+7RjXb5rHh+9bTXGRZ0Iosa8/zDe//wovbT3GM789xM03Lpyy0PuVgqaorPWvQFNUftb6K3qTfaPbUmaKNwd2cjR0nOV5S1nomUOlo5x8y8WLAL8bkDVN9pzs4JvPvsn+5i4y59BhQrEE5llGdMdAiC899CzhWJIPbqznfWvGDFxpmrQ393HdDbmSQId2t7Hr9UY+9vkbWHZdHV/5/E/Z9uIRZtQVc2PJHyMQpMwEAVstN5d+YfQ4aTPJM53/esGx5yQHMmTNQaSMTx6rPwuK4kJVr3yt1KtmOH3ww2u56eZF+PIcE8oFLKmv5CMfXTeumvZkOHCglW987fmL6i8rTRy6hTtq5+CzTT+z6Hcdpmmy/c0THD/ehUXXiMWTCCHo6hymbnaAP/2zW3C7bUgpOXiwjf/+3qtEozll38HBCBWV+Xzik5vweO089uhOnE6DoiIPRw61893vvsKKFTXMm1dGOBzn4Z9u44GPbaDyErOiLg2/OwvbOwUSyXB6kJORoyz0NGBV3znFqRVVoa5hJnUNkwvKCiEorPCz5YFNk273FLi59wu3T/i9sMLP/X9x16THm7GwkhkLr34tw3c7BodjvL69CYTg/fesoCTgnbCPEIICv4vlS6t5aesxhoMxMpkslqvMdYKcWOaKvKW4NRePtf+G4+ET47YPp0O80PMK2wd2kW/1UWwUUmkvJ2AUkW/14dQcGKqRC+ldpXUnV0fvyocupZTsPtHOV594laauXNUEVREoQpAxzQl2iBACj90gz2nncGsPrx85zc31s3HarCPHy/3ncFnJZLIc3tOCzW6lYV0dTreN8uoC+ruDuey8EXPDohisKrhvfDRGkVTYx8sWnDtuKYj6ppoAACAASURBVCPE4i8QjT9BNtsPpMeF+yaDw3YbXvfnpn+hLoCr8pQKIfB47HgmEbEDKCx0EyjxXtBwGhgMTzC6poJV1fAZNl5tbWZBYfFomqVdt1xyNt350JcI0RbrQwJz3WVYVQsnw10MpCIUGh4qHQWolxi2kVLSHhtAV1SKbVeWL3RgfysPfGw9d97dgKIIXtt6nK/9+3McPNDGmrW1RKNJvvWfv6Wi0s//+vRmHE6D3t4QX/riz3j8Fzv50Eeuo6Iyn46OIdLpLKdb+pkzp4Tu7iCDgxGi0SSZTJb8fCdXw5g54wE5G4rQ37HCohMgTWS2BbIjKsbCDvp8JlT6fgegL9HNsfABjob2Y1GsuDQPJbYKLIqVUHqYwVQvGZnBqbkpMkpRhZrzJCS7GU4PIgCvJZ88y3jPqZSS/mQPGZmm2Ci94uHd7kQvCgqFxuSGuylNWmIdlNqKsbwNma7BRILOSJiZvjx09eLDq1JKYpk0HeEQ1V4f+kgVhFg6ze7uTqSULC4qxm2d3MDtioSJplLMzMsfPd7xwX5KXW5cliv3/EVjSRLJDLqu4nROfdxM1qSlNcdr8Xrso2VDrgYyZoZoNkYkEyWSiTKcCtIW6yArswjEhBewRBLKhAllwjRHW9kxsHuEXyM4fznaK4PbS2/inrLbrugxpZT0BiN845ltNHX147BaWDyjhHVzq5lRlMc3n93OnlMdE9q57QZzy4t4/Wgzrf3DtPUPM6c8p/YuhMDltdHVPkTbyT5ef+EwG25eiG0k4SOVTI+W2jkDRaj4reM/QBQ0luTdep6xRxkMfplo9BdIzoSYL6L0mWXZBfe5FLwtbxuny7go16fNsExIcZ0KUkraQkF2drZT4nKjj9ys+uISHlx2ZUWwwuk4/33qRXRFxaEZVDsKsao6vckQr/QcRFVUPlt3Kzb10gTpJJJnOnfjszi5t/LKhmvcbhs3bFmAYeReGDNqCikqctPZmSMjn2jqYWAgwgc+tAaPN1c3LBDwUL+0miOH24nHUlRV+mlvGyQcitPeNsiatbU8+eu99PWGGBqK4fXYcbuNaQvbXQwSZmQCKd+iWM9fjFgmyWXJWadW8rtmMCF9FJl4CjJNgAWR9z1Qp1d2YhxkBmQahHFFzy+YHqIn0UkwPURXvI24JUaBtRhN6JyKHqM9dhqAnmQnNxbfSYW9hqFUP093PYrfWoQpTQqsRSzLWwucWeYknfFWXu59ikXe5RQZpZf1EsqYGRCgnWU4b+3bgVWxckfp5GJ6KTPN4+1P8ZGqPyDfeu0TGRoH+/nJ4QN8+bqN+KYpWNoZDvHDg/v485Vr0a05QyOdzXKsv4+fHzvEP228gfriyYUgX25ppnGgny+vy3nhstLkO3t38bHFS5nrv3JyAR63DY/bRiic4OnnD3L3bfXYzyrELKUkFE6wdVsjz710GIB1a2Zd1XDYsXATz3S/yEBykMHUMJFM9ILeirNhTpXCeZWQvUq1Ivec6uDg6W4UIfjA+iV8YP0SPHYbQsBPt+6btI2mKpTkubFZdIYicfpCUc5UnlM1hfpVM3ny4R1sffYgUkqWXZeTpkglM3R3DDG/vuqC45KYNEd2U+Oa/F2dSL5JJPookMZqacCwrkVVfHCBjy5dm33Bvi8F19Rw8njt/O1X7qF6RsFFGUR2hxWHwxjN9DjvvrrO3298z4TfbdqV/6LsjA/SGR/ibxfeh6Fa0ISKIgSr/XWkzQzbBxovfJC3CQUFboyzqltrqoKmq6Mk/Pb2QSKRBN/+5kv8+Iev53aSEAzFsNksSKCi0s+BA20MD8cYHo5SUZGP22OjpydIW+sgxQEv7mkW7rwYSCnpS7QQTPeO/qag4rUEzqPubUL8CaTMIuz3vwNSjVUwNiOsq5HRH0Dit5d1NCklpHYgU28hHA8ixJW77jOdczClSTwbZV3BFmzqmAe51jWfCnsNUkpe7nua5kgjFfYawtkQsWyYhd5b8en5WBQLmsjNQVWo9CW72Tu0nWV5a5njXnhZpS4kktf636LI6meu5+KLZ1sUCw9U34dbv3Y1Aa8UKj0+Pt+wGqdlbA57DIP3z1/Ito7W87ScCFUofHH1OjzWK+vt9Hkd3LZlEY/9ajc/+fl2tm5rpKaqAKfTGJFFCNHaMcjAYATTlGxYW8cNG+dd0TGci+5EL3uGLj6j+3cVWw83Y0rJzEA+H9xQj9t+ceH3PKcNQ9eJJJKEz6oJqCiCW+9bgctrp78nyLobF1A+owAhBIN9IYpL81i6ZtaITlMGpjBWMzLF4eBLUxpOsfhTQBqb8R7yvf+AqhYBV7/A9lS4poaT1aqxes3FZeEA5OU5+MwfX09B4YWLjaqKQpl7fNZZOpvlUF8P+fYro6grpeStgSZ2DZ6kPxni+a79+K0uVvprMUa8S+e+mKWUDKYiHA62EUzH8FkcLPBU4LHkwocdsUEOB1tJmRn8VjeLfVVYFG1c++7EECfDPSzLrxnt51KhnVMW4Vw7QlEFdoeVdRtmU1Y+XsDSZljweu0UFLiIx1MMDUVzhSjzHJSX59PePsSpU73MmlV8VVKL49kQe4eeJZQeI3RqioUqx3kKrcooMvUWqDVMNWmvKYRAYEWi5TxElw0TmXoTzEG4DDHOqXAmMHFG3wcgno2xfeAVhlL9qEKjM96CV895bspsVSzwNPBy71M4VBf1vlVUOXJzPkOG1/qex6E5qbDPQHDpRlPaTLNr8ABb+7ZTZgvQkeimzBZgtivHeUpkE7w1uI94Jk65vYQqRzmKUOiMd3M0dAK7amORdy52LWdoNoWb0RWN3kQ/8WySSkcpFfZSFKEQTIVojJwilI5gYmJXbdT7FmC7DM6XlJK3OtsJJpOUuz0sD5SiKgpvtLdQ4fZS7vYQHwnBzfMX4rPZ2NPdyfHBAUpdblaUlGGcO5fP7QNoCw6zu7sTq6oRTIypkYWSSZ452YhEsqmyhkJHbs1pCQ4zlIgTTCTojUUpGelLUxTi6TQ7uzroioTJmCaaorC+oopi53gD1KKr3H/Pcvx+Jy9vPU5H1xCnWwdIpzMoioLN0PF57SyaV87qFTVsWDsbt+udw5/7XcbJ7lxodGlN2ZRq4JPB0HU0VZDOmqQyY94wIQSePAe3v3/luN8Aikp9fP7v7hz9fXv/z0jLyRXxsjJDyoxNug0gnTmJEAYO+z2oaunbTta/pobTdE/WatVZsXJy8idM1KE497UYy6R5+NBBlkzhur4UGKoF24iXyakZ2FTLBb0YA8kwjaEOfBYnr/Ycpi3azz0Vq4hmkvz3qRepchZiKBaOhdpZ6D0T+xUgBEOpKD889Qq17sA18ZZUVxeCzP25afPcUaXgs5GX50TXVY4f78Lvd+H12JlRU8j+fS10dQ2zYeOci7rXaTNBKN2PS/ePeCXOnOHZbSUSSTDdx+t9j9AY3j7uGEXGDAKTpMRLMwTJ3yKTb0JyGyhHkZkjSAQoPoT7b3LcGimRpCD5MjL5Gsg4Qp8Hxq2gFCIEyNhDIPLAHEBmjiPs7wcziEw8idCXgO2WHHcp/jBCLQfhRSafBTMKlgaEsQWEc1rPvzQHIfE8Mn0YZAiUPIR1I1jWIoSClMmRMb8JyVcABWl+YcQgUxCef8zVcZISSQbSu5CJ58EcRqiVYLsL1PMVq85BCCV3B6QcfQ6GUwM0hQ9ze+n7KTZK+XXHw6P3TEFhtX8zCzzLaIocYWvfs+RZcl+gpjRZ7d9Ec7SRNwdeZlPhLaPeqOlCILCqFrIyi1WxYFdt4/hKB4JH0BUdRQh2tO/lvoo7qLCXois6dtXg153PUe0oHzWcdgzu5XS0jXmeWqSU7Bzcx/2V78VvyeOFntcQAny6h9/2bOU9RetQLsPoAzg20Ee5243bYvBk0zG0hlU0BEr5+ZFD3FQzi3K3h1AqySNHDvDp+hX4bDYcFgvxdJqfHNrP/IJCjAvo0vVFI3xt13bybXb8NjuvtjZTl5/jm6mKwGsYfGPXDmZ480Z5oAd7u/nu/t2sKaskz7Dxm6a3EMCq0nJePH2KNzvaWFlaxuPHjxBwuthcNTGzWAiB02Fwx01LWLWshr6BMNFYikwmi6IIrBYdl9PAn+/EN0IH+D2uDeLJXGknj316VIqsNDFl7rnRzuEdn7l/Z9aHyUViJScjO1jiu4XJuEkZmSKY6jrPCARC2FGVidIbbwfeJYzaySGBXx8/xpyCAircHh46tH/c9lg6TSR9ZVWXF3orkUiOhtrYVLRglKB5PpQ7/GwsWkAsmyQtszSGOkmZGdJmlnA6QYHVzVxPOX6rG0PRkeQKLw4mw/zH8SdZXVDH5qKFl0w2vzjkHvaamkKW1FfyxOM7cTisFAc8mKakrzeExaKxcFEF+X4neXlOXn+tkXXrZ2N3WCkp8fLM0/uJRhJUXUCD5wwimSGe7vwGg6kO8q3l5FtKcesF2FQnmmIFJLFsmI7YMdpiR4hlhsfxEuyql7UF96FP6rmRIGwIrRqZ2gFaGcLSACggHIwybmQEGfkGJLeCZQkoecj4k5B8FeH+O1DLkekjOT6SNgPSJ5DDfwL6fBA6MvI1hFqc+3f6ADLxTI7wrc0CoULkP5GZowjXXwDTMBKSbyDjT4BWCUoAMkeRiecQ7i+DcYa7Yxk7P8WN0JeBsHCm/EDuKmQg9kNk7Oe5MSoFyNQuSL6cO5a++Ly8KKfmIp6Nsnf4TQqsAcrt1eiKBVVotERPcjraRHu8mTpXLiPmdLSJ1tgp3LqHYHoAu+ZEU3SyMoOCSrFRTrWjlie7fsaeoW0szVtzScR+Vags8s7ltb4d1LlrWOYbrwFUagtwe8kNmGTpTvTREeumwl5KgTUft+bkqa4Xx+0vgCKjgNsCN5CWab7f/DO64j04NQediR6uL1pHtaOcY+GT+C15l00qz7fZ+cC8RRQ5nBiaxi+OHaYhcP4C5HV5fiSwvbP9ovo41NdLLJ3mr9Yux6Fb6ItFSWZz3gKHbmFzVQ0PH54YvrJrOp9a0oBD14mNeJlWlZZzoLeH2rx8bqqZxXAiQV8simcKIjrkwjjFRR6Ki66d/tzvcX54HAb0w1AkftGULSkl/aEo8VQau1XHaYz3VKVTGXo6hwkORclOorvozXdQXu2nyrFkyiK+GZmiN3FqyjFoWiWp9CFMM/SOKIn0rjacAMKpJIlMmmg6xRPHjnBDzcxRv0U8nb6i0ZkJN0tcnBft2c49NIW7CNh8dMWHSZpppAS/1cWHqjfwYs8BtvUfZ467lLvKV6EJhaw02TV4krSZ4f7KtWgXYaBdHnLnoesqD3xsPb94bCff/c7LmFmJUHLlEd57Vy5DwTAslJR4OXKkg/LyvJFwnZNsJovFqlMcuLiFUkpJRqaIZIaIZIZoiV48B8Gmuriu4D4q7PMmvQdC8YBxEzLbC4kXQFsM9g8ixFnXUUpIH4TE0wjX/wHjNgQg0/uRw5+H5PNI+wMj+6ZQXH+NTL6CDP8twroerGuQmSbItoA+N7dfthPh+wFCr0XKNER/iIz9AGz3gj7n3GFODetmhGUFQikAIZDZbuTQJ5GJlxDGDbksPGMTUqZyRp9aDPb7Eco5GaTZTmT0J2C/F+H4BEJYkNnO3LHiT4A+GzFFYWAhBAXWYjYW3kpH/DTRTG7R8lny2Vx0G62xU7g0NzcV3zuaOu215NOVaGMw1Y9Dc1PvW41Tc5HMxlmatxqX7sapubmh6E5aYyfJyuwlGU5CCIQ8458UE56BgFGIpqhkTLAInfRF1PU708Y0TXShkZFZbKpBpb2Ul3vfYL/FiypUyuyBaY/3XPgMG4amoyoKAaeT19tbJuwjJWTPqdU5nddFNJ3CabFgVVU0RaHE5eL08PAF25W7PVhVFVVRcOg6ffFcCKWhpJRfHDtEfzxGfyzGrTNr0ZR3r+Dt/0TMKM7nYEs3e5s7SaYzaBdB/UimMxxt7yWWTFFdmEexb4w6Y5qSna818qOv/5aOln5AYJomAshkTPzFHm67bwXlH1/H2sIPTZlBq2I5b1ad3dhCNPYE8cQr2Gw3IHh7Q7vX1HA614V3uVajAD6wYBECGEokWF1eyR81jNWjCyeT/P3rr1xWH9PFxLRWeL5rPx+oXkdD3ky29h7mpZ5DQC5TY6armEpnAT3xYf6j8UnmeSqY5ykHYJW/jmpnIT8+/SqfmnkD5fZLF5TUNJW772ng5lsXY7ONfS0XFXn4yy/dgWMkbVgIQXHAywMf38DQUJRkIo2iCGx2C16PfaTIKLzvD1ay5aZFo/yzQMDLX/7VHUiTafKbpnc+qtDx6kVsKv4o1Y7FaMqlc74kMsd/Upw5b5I5kLt7wgFaeY5wbf/oSMcloNhBDYDw5P6NBooPzBijFro2M+dtQuSMFEsDxB+F9L7pGU7CBkJByhDILKCD8IIMM1bU8iKQ3gNIhDYHzNDIKAVotZA+ADKR62sKaIpOrWseta7x5N0a52xqnBMzVnyWfFb7N0/43araWOQdI34WGgEKjcs3QFShkjLTZKU5LlFcEdP/0JjMo6sLDZfmpNDIZ3neElyaE48+dQklKSU98TBfP/Q6J0MDbKmYzX0zFmOck6TSH4sRSSdxWSy0hoIU2XOqyYauE0olyZhZgskcz2jc8adxPk6LlXAySSydQREKXZHIRbXXFGXSx6vU5cJjNdhUOYNCh4NCu+Nt//K/WNT7FhEwii+84zsEBdb8C+90CVg3t5ondx7hdO8gj715kPvWLjpveZWsaXKwpZsX9jWBhJkBP5UFY7pc2UyWX/3kTfIL3Xzmr25n346TdLUNcut9K9jxynGaDnew6dZF43ScJoMiFIqMqVX4bcZaHPY7iMWfQtPKcTn+ECGcCKFx/rVQjP9YvkK4poZTIpHmlZePEgh4WbCwHFU9/6RrauympyfInDkl5E+i0pvT1cjBZxj85Zp14x4Au65z//ypRbWuJIZSEQ4Ot7Jn6BSt0X5e7D7AHHcZM5xF1LiK2N7fSFd8kIPDrRhqbhHtig/yYvdBNEUhbWZxaTYKrDlvjQBcmsF1BXMZSIZ56PRWHpx1Iz7LpcnSCyEmvYYWizaBBC6EwG63YLdPbZT48hz48sa8G7quUlqaN+X+k8FQncx0LcOiGEQzwySyYZJmnIxMY47oq6hCx6IYODQfXksRNc56al2rcGq+K7BoSzC7IdOBHP4jGFeyRII2d/RfYjQcqIzsd2bqCMaRsoWXcRNZcYPQwby42nOjfaf3IeOPjeg9yVwfmeNgWc60DKdsV84gDP1Nbhxn96FcOe7flUbOG2miCmVKNWmBoM5Vw46BPQTTIaodFdS5pl58M2aG4+GTdCf6CKXD7BzaR3mylEWeuVO2MTEJZcIEU2FOR9uwKDrVjkoKrflTPn8vdZ7gkVO51O7eRIRFeSUs8Y8Pw2XMLA8fPohVVdnT3cnnl68GYG1ZBU8cP8pALE5vLEp2RLMslEyyp7uTg309dIZDPHOykXkFRSwpCnCor4dDfb10RcK80tJMXyzKmrJK5hcU8qzVytd3bafI4aB5eIiA04WUkiP9vRwb6Kc7GuHV1tMMxGOsr6ia8jpA7uO0LxalabCf9nCQaq+POfkFqO8Cr5NP9+DTL+wJjyRTHOnoZVFF8Wht0/5wlP5IjNpi/4Rn8XT/EI3d/QgE62ZXjbaJJlMcbO9hKBqnpjCP2uJrKQY8OYQQLK0pY2VtBW8ca+Hbz22nYyDI9YtmUeb3kBoJ45qmJBxP0jMc5lBrN996dge9wQgeu8G9axZis4ytI6Yp6e0a5oE/uZF59ZV0tg0yPBBl5pwSZs4t4at//ijbXznGbfevnGpYF4V0pg3DuoZk6gDDoX8hEnsMq2UZmlo2ooE3+Vy0WOZjNzZeVt+T4ZoaTqFgnH/56lNs2DiHufNKLyhuuXXrMZ5+ch+f/sx72Pye+RfVx9lS8aqisLho+l+1PkuA9xR9fFQvSAhB8VnWcKWjgPsr16GJc4W9BPM85czzlKMKZZQ68qHqjRwNtSOApTNqyJgmVlUnT7hY5KtiIBlGFQobiuZTZOQm98bihVgUDU1RuTGwhHJ7AepVsJzfTtg1N2v8f8Bi743EssMksjmNpoyZxiQLCLQRw8mueXFrfgx1eiTrC0LYQStHOP8ElHMMP+GA6ZKA5Rnv08gYZSLnMZqGTIDMdiHD/5zjaDk+BkoxCCsy+MXpjQVy56D6EY7PgHaOUSEsIN6Z9aGy0uSlnn0sy5tFvnXyrFohBGv8DRQY+SSyCZxaLnt2RV79qPdIEQrrC1fh0nJG/hlS+fvKb8+F2kfu02p/A9aRcKMmVDYVrsZr8RBKRxhIDuHR3UQzMdpTQXYPHeDBmg+jXoTxqgoxKsZ7BjN8efzt+s0kMhl6ohHWVVSxsDDnDbm+eiZ5NhvDiQQrS8u5o3Y2pS73yPlChdvDJ5YsQzkrVUQgsGs6D9YvR8Doy91vs/NHy1ZxqK8Hq6axuaqGeCY9eu10RT2njWBJcQllbs/o2ra+sppkJkNWSra1tTDTl080naYrGuE3Tcf5yvrNFDremc/Q2bjYNaMvFOWHr+/mb+66HsOlI6WkqWeAPac7qC7IwzhL2XwwEuPrL2yjpjAfp9VC1sxxb7KmyUtHTvJGUwuzA4XkOW3TGsOVQDKdyZUHO0dU1GM3+MimZbT2B2nrH+bnb+zn1UOnKMlz09ybK2+2t7mDv3nkBYaicVr7homn0qiK4H1rFrFkRsmE8xBCjIpcWg2d8EjdQ4tFp7TKT3Njz2Wfz3DoH0gkdyJlBJBkMqfIZKbmRJ2By/HBd7/hNF24XAbJZIauruAF981KyUunT/LsiSZCyTFCeH2ghE8vWzGtfu2am1r31G18Fie+POeE39YWTB6KKTQ8FBoTv3Z0RWWxr3rSNrNcYwafS7exwn/xMg7vJihCwaXn4dKn562aRg8grEBk0m1CX5bLNlOcoC8an2mHkuM8Tae7TBOY/aAW5DSkMsdARkGbRpgu2wZmN8LxvxCW6wCQZkcuu45zBRtFziiTMSaVI7Asheh/5f6uL8i5ts9k2mEirsESEMnE6U+ERjhDFooMH5qikpUmA8kQoXQMQ7Xgt7qxKjqRTJyO+ABPdr6FUzMoMnwUGz6c+kTj067ZWOwdH0asdIx5dxQhqHGOqRRPpfdU7Sg/q43CTFd1rvxQ8CgpM82WwAZ0Ract2smPWx4jbaZRpygCu7lkFkdqemgOD3Jn1Xzm+MaLm+bb7OTbJpdIMTSNNWWTl3VZXzH5WjGvoJB5BZMLWJa53ZS5Jxqec/2Fk4pe2nV91FADqPHl5mVnOMyu7k6+dsMteK0GXZEw+3u6CCYT7wrD6XLQUF3GksoSrOcYIaf6BomnMnxiQwOKUFBHtAmzpsnB9m6uq6tmy4JaxEVyYa8UpJQ8vusQ1QV5rJxZMW6bogiWzizjKx+4kX9+4hWaugboHg7TPTxWDLpnOELP8Nh6WeR1cu/qhdx33eIJnDZFEeQXuuhuG8Q0Jf5CN52tAzQe6qAg4KH9VB+Fk5TcmS6EsKGp0/eQq+rVCc++ow0ni0XDNE1isQtnxkVSKR4+dJD3VNdQ5fWOfo/l/b5u3f9sCHuOz5N4BbSZSOEEFLC+Jye1YGkAyzJk+P9FGLcj1XwwI8jMCYRxM+jn0YiaFBIZ/kewrgOZyGWzaXVgyWV9SZmCTHPO0Mm2AzFIH0Sa/aD4EUphLoQmnMjkqzkvmIwjU9ty3qsJXg4FoS9Exh6G+C+QaklORdy4ASH0HOfKuAkZ+wHCHESqZSCTyGwzQl8I1o2MD1FeWcQySR5p2UooHc29XITgw9XX4xI2jgZb+U3nDgzVQjKbZra7jJtLltOTGOb1vsN0xPrZ1n+UPKuLTYWLJzWcrjaKjSIkJr/seA4FwXA6yIr8JVin4NYJISiyu/hKw03XeKRXF/k2G7V5fr655y0cuoXhRJyZvnwCzgtr7L2TISXEUim2Hm+meziMx26M4+I+f6iJ0/1DzA4UsHpWJbqqYkrJU/uOseNkGx1DQb6/dRcBj5ubFtXR0j/E642n2dfSRTCWoDcU4braKmYV+4klU+w41c7pvkECXhcrayrw2A2ypuTpA8dZWF7MWyfbyJom19VVU5bnIZJIsuNUG639w5T43KyaWYHLsLKvtQukpHUwyFA0ztySQuqrS8lkTX695wi/2XuU8nwv+1q7mFtayHW1VaPGm6ooLKoK8C8fvZUX959ge2MrJ7r6GQjHSGWyCMBm1anwe5lTXsiWJXUsnVk2aXkgVVXYcPMiEvEU2UyWqllFVM0q4p/+7Oe4vXaCQ1G23NNw2ffJ7/sP5CXo1IlLlDu5EN6xhpNpSoLBOKYpJ9S6mQxZaeKwWLh5Zu07rshvKBjj8Z+/xXu2LKCs/OqQ/n6PySGEDRwfRMoEMvL9nAClvgCsOZV5ofjB9efI+C9yWWYyOkIWnwXKiJdQGIz6nYQKiiP35xlvz9nlXvR5CK0OGfspmGGwLMqF285kgZh9yOBfAmkwgznjKvyvICwIYzPS8SBCLQHn55Cx7yEj/57TcDK25IyeTPP480NB2m4Hsw8z/jhCZkErRRibAB2BFRyfBq0aGX86J5QpDNCqwbqBybgBZ784LvdLOZKJcyzUyn2VG5jlLCEjszg1Awk81bmTue4KVvvncjLSxc/btrKuYAE1zgCFhpddg03cV7meUlv+26L4LoTAb/XxvvLbCaZDmNLEptooNP7nzWGLqvK55avoDIdJm1lsmk6Jy4VDv/a1/q4sJM/sP84bTS2sn13NofYe2gbHIhyzivy0DQZ56chJGmbkjAcB1BTm0xuK0jIwzKKKEtyGFVUR+Bw25pQUsuNkO1UFeSwoK8bnsGGaJs8caORwRw/1VaXsa+2iqWeABzetwDQlD23by7GqUuoCBQhy4b5M1uTJvcc42TvA4soSdjW309w3/bxWYwAAIABJREFUxCc2NLCruZ2Xj5xky8I6nFYL3311J5+xaMwtKWRWsR/DolPl97G4IkChZ6JHUAhBwOfm/nWL2VJfx3A0TiyZJpHOoAiBzaLhHinua7fqU64DQhFsum0R2YyJbtGwWHU+9Jn3UFKxj3AwxuIVM1i0fHJP6XSgnJst/DbjqhpOOeMnRiadI50NDObcf8lkhv7+8JRFHTNZk5bTfWx7oxFVVSgquvBXjVXV8BoGzzefYFFh8ahL0WGxEHC+vaUVMhmT9tZBEvH02zqO/5EQAqHOBM8/MBZ0Oyt9XQiEUpwzLhwPnt2QM/wm4frS2M/aPETew5zx0gjPv+b2laGRHazg+PiIsTR2nNH+lBJE/s+mGmyuTyHAujEneTDKlzpjOpxDDB8Zf4f2SRTtkwRseePGntueh7S9H2G7f9w1mIq/lZYZmiM9VDoKL1upvsDq4Z7y6/hV+5u4dBsr82ez2j8XRcC+4ZO0xnp5c+AYINGEOirxoQjlzJW7rLIslwtFKPitefitVyuU/O6AEOK8IcZ3KyTwwuET3L9yEetnVzOjII9jXWMlnaoLfNQM5NE2MF7GYU5JAYPRGAfaulhRUz46I/OddpyGlYL9x6kt9rOsOhc2TmWy/GrvEdbMrMSqqfhdDp7ce4yPXrcUfUT6YXlNOevrxoyMWCrNUweOs76uGstIm2cPNPKR65YCUOn38YdrlmCakmNdfZzsHWRBWTELy4vJd9qpCxSwoqac80FVFPxuB36345I+mIQQ2OzjQ9b+Yg9/8Inc2vVuybqcLq6q4ZRIpPjJj9/gdHOuREY6ldNSOXq0g3/56lNTXtRMJkt3d5D+vjDFxR4WLqyYdL+zIaWkZXiInR3tFDudo8KU9cUlfLrhwhynydVOmVQ5+3y/X2jb+fqaCr+rD981gxCI84WjRqueT/6CPrtt7l6cPW1GhCbH3VJl6i+0kfbne6bGtinjfj8zmtxfx7ff2neEQquHgG28+OjZ7Sb1Lk0cPKF0nF91bOeBGTeMEqYv5xlckV/HbHc5R0Ot/Lx1K0WGl1muUgqsHu4uX8Py/DFZA+NMfyP/l2edwztxHlzsXL7Q2CeTapnqGTlfv+frZzrrzrRU7i+x+O10r8kkB7gifshYMjWipC2wWy04LlCKZFLduPPO91zSUm8wwlAsTttAEAXBHfVzR8NfqiIo9oyXuciaJr3BCIPRGMoImf+99fNGuVSlPnduVguwaCqZrJlrf4ke4ys1v3LlmeCiM3/fhZiW4ZTOZNHUqV8K50JVFfLznRzY38rwUIxoNFenJjgc41Co/TyCxQJdVyku9vDxT26kvOLCrnGHxcK/Xn/zBCKvdZK47GQwTcnDP3qDQImXQwfb6eoY4vqbFrD5hgX09oT42Y/foLs7iGHo3HDzIhpW1nCisZuXnj+EoiqcPtWL12vnw5/YQHHAy9BQjB9/71W6OocpK88b5Wll0lne2n6CF587SDyeZu78Mt57bwP9fWF+8/huEokUTqeBYbPQ0tzHJ//3ZgKlVyL1/vd4p8CUksZwO4+3v0F/MoRbs3NvxTrmustpjfXxePsbtMf6CdjyuK1kBbNcpfy2ey/t8X4GkyG6E0NUO4v5YNVmbKqVrzf+ih0Dx7GoGk92vsUSXw0fqNyYK8Dbu59Xeg4ikSzPr2NLYClI+PfGX1Js5HE81IauaNxZtpolvhpe6zvErzp20BhupyXaQ6Hh5QOVG5npujTpgt7kMHuHTuHVHaTNXBhAFSoCwfXF9bzYsx/IZZ4lzQxr/HMxVAu6ouLQrGzrP8psdxmV9sLR+o7vJPTGI/zd3hfYN9Ax5gw8axGanxfgy0tvpNh+fq93U6ifP93+G5LZDP+84lZmeQp4uu0oj57az2AixiJ/Ce+vqWdhfi5p5GRogP868iYHBjuxa1auL53FndULKLG7J6wVUkrSpslQMsaJUD9v9bVyaLCbzliIWCaNTdPItzqo8xayIVDDPF8RedYLl0KRUpIyszSHB9nadYrtvafpjIaIZlJjRs+Z63HWnwoKD8xezkdqJ+e+mFISTMXZN9DJS50naBzuYyAZRRUKRXYnKwoqWFs8g1keP3bt8jyiAPkuB20Dw8wpKaQvHCEYm7ye2uVAUQTVBXksKC9m4+wZSHKRFYumjtR+ExOkDjRFoarAy+LKEtbOqsKUkqw0R6MpU8lACCHQFIVoMkU6k81pKCkTRWJ/j0vHtAynZ948imHVWVAToMjnQlHOfyOsVp3737+Ku+5uoOV0P7t3neL733uVquoC1q2fM2o5nwtFVfD57MydV0ZZWd4F+4Gcdd4fj1Hl9WLTLi3uHokkePXlo3z4Y+txuQyUEbkEp9PKxuvnUVKWR+OxLp5/ej+z6opJp7Ps2HaCD398PXfe28CjP93O80/v50MfW8+zv9mLNCWf/dObOHqkk91v5VInT57o4dkn93HP/Svx+138/Kdv8tSv9rB0+QxONHbxwIOb+OF3XuXGWxeRTKY5dqSTQOm5mVTXFqZMEY6/SDrbh80yD7ul/veT8FwIa66W3EWgJzHEt08+w43FS6n3zSSWTeLRHZhIHmp5mWpHEe+v3MCO/uP85PRL/MXc95HIJtnae5AvzL6LfKub/6/pSbb3H+P64iV8ZtZtSKDWVcqNgaUoCFShsGfoBG/0HeVTM29GFQr/dfIZ3LqdVfmzORZqo8Dq4XN17+WN/iP8umMHC7zVrCmYR4WjkK81/oo/m30P+Vb3Zclg2FQrAjgwfApN0Xh/5UZqnAGEENxQXI/f6uZwsAVVKMz1VOTCdeSEJx+YcSM7Bo5xcPg0hVYPHt55hpOJZCgZpysWnnR7ccI9qsV0PqTNLD3xMJF0kmPDvewZ6OCr+14iaeZoDifDA+zua+cba+4iZWb40s5nODY8FlI6NNTF3oEO/n31e3Hp40Mn4XSSR07u5cnWIxwd6sWcJE+0iX6297bw0IndrCyo5AuL1rMw7/zGciyT5odNu/hR4076EtHz7ns2XLp1gpfzDEwpeaO7mf9ufIttPadJm+Ov3YlQP290n+a7x97i7uoFfKS2gVLHpdcvE8Bti2fz+O7DNPUM5MjRI8fqDUV4o6mF3c3tnOgd5JHtB1haVcqiiulL3Oiqyr3LF/DswUaOdfYhhKDM5+bOZfOmbGPVNe5aNp8XD5/gUFs3CKjM9/HepVPrjkEuk3RFTTnPH2yibWCYJVWlrLxAyO73mB6mZTgV+Jw88+ZRnnj1AHOrirl+eS3VgXx0TZ3SuBFCYBg6dbMD5Oc7efwXO6ms9HPf/SuxWK5cpDCSSvGD/Xv4s1XXXbLhBLBwcQUzZhaOm4imlJxs6uGFZw8SHI4RjSZJJnJ8pbKKPBYvrcSX56RuToCD+1oBOHq4gy23LCZQ6kPVFEpKfUgp6WgbxF/opm52CVZDZ+362fzysZ0sXFyB22Nn9twSHE4r8xaUEw7GLyqj8GojmthO++CXyJhDGHotNYUPo6n/szkf50IIG9juvPCOQEu0F12obChciFUde1Yj6TjtsT4+ULmRIsNHQ34tL/buYzideynVucuZ56lEIKh2FDOYCo98XaojnhwFXaijYZ6joTZORDr55omnAEl7rJ8aZzEr82fj1Z005NVSbMuj1lXKWwPHkUhUoaIJFQWBpmjoyuXNUbdu58bA0km3WVWdVf45rPJPlGoQQjDXU8Fcz4XD9G8n8qx2vrh4E53RIIPJOMFUnOPBPn7dcviSjpcxTZ7vaKQjGqTY7qbI5uTYcC+hdJKWyBDfPvommqLSHBpkrrcIq6pxdLiHRDbD693NbOs5zY1ldeOOmTazvNXbxuGhHhRyIR+XbqXS6cNlsRJNp2iJDDGUjJExTV7vacbcL/mH5bdQ5phcNDKdzfLTk3v41pFtRDMprKrGppKZLMkvxaFbaI8GeamjiaZgPyYSXVG5u3oBa4qrKTAcVDgnfgxKKXmt+xR/ves52qLDKAgcmoUKpxe/4SBlZjkdHmIgESWUTvCTE7vpiUf40pLNFNmmVnO/ENbWVRHwuokkkhS4HdzdMA+PzSCRzlDl91HkzpGrFSHId45xvOaVFuHf7JgQkLKoKh9eW4/PMZakpAjBdbVVVBf46AtFURRBwOtCVRRUAX9+yzpKfeO5vKqisHFODbOK/PSFo2iKQsDrQhGCmxbWjVapUITgfcsXYjvrfXrjglpmFOSRSGdGjyul5Dc7jxJLplhRW0lVofeir1nPcIRjHb3YLTrzKoqxT6s6xOVDSkkmnUXTp1Y5v5aY1qq4cl4ly2aX///snXdgHNd17n93Zna2Y9F7IwiisHeKEiWqUKS6JVmyJbmXOM8vjuPEjhM7yXuJ47yX5yR27Dhx3Gskd9mqVqUosYu9gCQKCYDofXuZct8fi0IIAAFIlEQ5+v4Bdmfmzp3ZmXvPPec736F7MMT2g03844+exak7uHFdLatqSygvyJqR8A2gOzXKyl8/BVXLlq85rOrzTa2B86PvvIjmUHnfh68hGk3ynf94bnzN5vW6xoU8FUXBvrC21Dj/WIx7r0zLBjnhzZcyfZyiKOPtCAEOTRmdAF/b9VwKJM1zWPYIYGKYXZj20GVnOKXM8xhWD7pajkMrmP2ANxGvLMszBkuO+QImbx/zwgQuSMdXhcCe4smYfJxpW6zNquY9ldePU8s9WtoD5FS0ceK3QExbKuhtzA6nqrE0q5ClWYVpPhaSl/vOv3rDSdq82H2WW8vr+d+rt+LRdPb2tfJHu35NzDR4/PwpMhxO/nT5Nbyveg2KUPhh48v849HnMaXNsx2NUwynbKeH2ysWEzWTrMktZXPxQhZnFY4a2ekxKGom+VnLUb55ajchI8nB/vM803GGD9SsmxJCklLSMNLLQ82HiZopMnUXn1+1hdvLF4+GkdKG+0dq1/O5/U/wTGcjpm1h2jbXFVXjUrVpw4nHh3r4P4ef5Xx0BJ+mc1flMj5Uu54iT9ookkDKsnii/RTfPr2Xs+FBnjx/imynm79ZvRXtVUyoQgicmsbikqmaVrqmsqpiZq9bltc9yTgag6IIqgum0kscmsqCvGwW5L1SaBeWlk6vN6RrKlX52VTlTz6mNHuyQVuZN9kQdesOlr/CMyal5Bu/20PvSJi/u38rlflz11dq7h7giz9/Dr/byd8/sI0l5W/sGDvUM8IP/v5hPvqFewlMUwHjjca8DCchBKqqoCoKLt1BbqYPj0unpXOAvSdb2bKuhm0b6ma0CJ1OjbXrFmCZ9oxlFF4tPA4Hi/PyeLK5kXVFJeOkO69Dp8A3d4G26fo+OBBmxepKdKfGi9tPEY3O7gWqXVzMy3ubqarOp+l0D12dwwghqKjM5cXnT9F4qoucPD87d5xmxaoKVE25bKl0Xud6nI4qUmYHGe7r0NWLV3F/oyGlRX/oO4zEH6Mo8Fmyfe9+s7t0UVR480naJi/1n2BlVhUJK4VT0cl2+ih157JroAGnqrN/6AzZuh+fdnF5DYHAq7loi/YzYkTRhIpPc7E4UM5DbTsYSIbId2UylAqDAO8Mwo1jcCgqScugJz6EQ6i4NSf6qOdJSsnvHj5EW0vftMeqmsL9H92Mz//GFOGUUnJ05DSKUFieWTvt9q5EH93xflZm1r8uxbLHxgzB6ELoNY5tWU43dy9YRkBPE5bX5ZWzIruYPX1t2FJSl1nArWWLx+vfbSur5esndxIxU7RHhklZFro6OaHh+uJFbCyoJM81fX05XfXwgZq1dMWC/FfzIZK2xamRXmJmCt8rQn8SyYmhbtoj6UyzjQWV3FC8CF29YDoRgkzdzQdr17G/v51gKsGpkT46o0GqA1MXz3HL4FfnjnI2NIQmFN65YDmfXn4tHm1yKryuqLyzahk+h85n9z1K3DJ5vP0U9y1cNUVo9G1MhWXbWPZMS7eZ4XPpqIpgMBxjIDz3sOylgsfvZvPd63B5Lz52vVGYl+HUdL6fR3eepLljgKULi/jYnRspygmgqQpn2vv44RP7uXFd7Yw16HRd46671yGlRNUubYpxwjR5pPE0McPgl6dOjg9eV5SU8dkrr55TGz6/C5d7qgvyrnvX8/MH93BwfwuLl5WlDR1VweFQCWS6EaNhSpfLgT+QnuRuuX0VP/ruDr76T0+yqK6IVWsr0TSVygV53H7Xan77qwPE4ynql5Rw0+0rGegLEchKEzIDmV4UVcHj1XFcwnDmq4XLUUtV3k+wSaIpmRfUbbs8YFi9xI2TWHYYW17+kg+Friw+tvBmft2xiye6XybT4ePesqvJdWbwvsobeLhjN/906pcUurK5v/xa3KqOW3Pi1ybCBF7NPW7MCCG4sWAVP2l7nv/b8DM25S7mluL1rMpaSMxM8lDbC8SsJGWePO4uvQqf6iJTn8g8dSgamQ7fuOGe6fBxVd5ifnDuGYrdOby7/BpKPKOTnYS9L55h744z016brmvc9cDGN8xwAmiKtKEJdVrDCSBohOmM945uv/zLFhV7MijxTPB2NEVhcVYBe/raEEBdZj757onFoEfTKfD4iYQGiVsmESNJtjpZNsCvO/Fz8UnHpWqszyvnt60niJgp+uJREpY5xXAybUlTaBCJRBMKNYE8AvrU31sIQbEng3JfFseHuhlIRBhIRKcYTlJKemJhftdxBhtJlT+be6tWTDGaxqAKhRtKFrEwI5cTwz2EjSTPdzVRl5l/WYRxfh/hceo4VJXBZIxoIgWks+QjI1GMlImqqWRkedFG56t4JEE0FEdRFHyZHnRXel6NhuJoDpVENImRNPH4Xbh8LkKDYfxZPjSHipRy9FiB2+ciFooTDcVZuLwczTHx/kopScZTRINxLMtCdznwZ3pRNRUjZRIejmKZFi6PE1/m7MkO88G8ZuU9J1opK8jkPdvWkJ+VfnHHOlNTlsfiysKLhsrGise+HshwOnnorndN+X6uBSgVRfCeD2wCpnqdlq4oY+mKqeS6gsIANXUT7tCNV9ew8ep0SYesbC9/8ue3TDlGCMH6jdWs31g96fvyytzx/f/sL28F4KbbVk7bnzcaQig4tMu3snjKbCNltr1p5x/LIJKSOZVXUIRCfUYZf7X4vknfCyEo8+TyyZo7pny/pWDV+P8A95RtmrRPpbeAv158/5TjNucvY3P+VPXzzy2e8MrV+EsmfdYVjfvKN3Nf+eapnRewflMNGZkeEvEUiViK4EiM5tPdWOb8lX3fCNT7F1J/keK/lxsydNckQ0QgyHKmDSGHolLkyZhU/04RYjy7zJI2Sdt8VecVQuB16DhVjYiZIm4Z0xLbJZKIkbzg3DMLJGpCwTXqiTJsC2OU7P5KHBvqZmCUYF7uy2JRIPei75GuqNRn5nNiuAdT2pwc7sWS8lWF697G7Ehn5YFh2SQNE8u02PXoQV5++hhj6ij3/slNVC4uJTgQ5sEvPUokGEuT4BcVctuHr8UT8PDLr/0O27JJxlMEB8Ks3bKMjbes5Kuf/CF3/9FWll9dRzKe4kdffJia1ZVc/+6NnNzbzI5f7WOga5g//9YfkFucDkvGQnF+9uUn6Drbi8PpIL8sh3f84Q34Mr1s/8Veju06AzKtJfXOP76JBUtKL9n9mJfhdO/1K3GOWnzjxXSlRBECl+7g/q2rL3kIbq4QQuDStEm6L2Pfz/X4V7Ntpv0uRXtvY3ZIaZMwWjCsfoR4fYzy2fsg+fVP9nD8UBsf+eSNlC24+KAPs+u+zPb9bJ9n+/7VtDW27ZZ3rmHbnatIJU1SSZPW5l6++NmfEw7GZz1XzIzzu56dbCu8ilOhs7THuthWuImTwWY8mosqbxnP9+2lOdJOoSuX6/KvIN+ZjSVtftP5LCsz69g9eJiQEWFLwZXU+icEA6WUtETb2T90nNuKriXD4eO3Xc/RGG5lWaCGGwo2ogsH9mhbOc5MGoLN6IrOdfkbWOBND6yHR06xZ/AwMTOOjWRFZi3X5V2B8zWKgc4VLlXDeUHYS8B40V1VKPgc+uSxBsYNKSnlpELnF0JKiSltemJhTgf7aI8ME0wmCBkJEpZJ0jLpjAYJjxpFMxEsFSHGDTtT2oykEtij88Arz5e0TEKpxOh1OWZM3Dk+1DX+f8NwL5/Y9fAMd2e0bSRnRvrHP0fNFHEzhX8az9d8IaWkMdLAoeEDbC24lRzn68fLne7c56LN7B/aw7bCW8nS33yVeiklI7EEScNCVQSqomAkTU7uaaJ6ZSVb7ruSeCQxzj3a8av96G6dj376VmLhBN/721/SdKSNFZvTSSA9rf38wRffjcvnTBvrAQ+rr1vC7scPs+yqWiIjMXrbB7jlQ5tRFIX125ZTuaSEf/n49yb169D2k7Sd6eIP/v5dZBVkkEqY+LM8dDT1cPiFBu7+xDbyS7N58ocv8uQPdvDxLz1wyebeeRlOiaTBwzuO0TUQBCkwLAu/x8lHbr8Ct9OBz31p4o+vRvDOsm0O93Sz83wbg/EYqhBYUrK+uJTba+pmb2DGvliY9hCWNYQt40gM0mtAB4riQVUCqEoWgqmEx4u3a2PLCKY1hGWHR4vK2oCGIpyoSgaqkoUiZnYxSilJGKex7DCq4sflqEUIZXTwjGFafVh2ECkNEAqK8KIqARxqLjPV8JHSJmk0YdrTF1ZWhI5bXzGna5XSIGmew7RG0NRMnFoVQmhIaWJY/Zj2QLp2Gwqq4kNT81HFVB2aV/ZPygSWHcKSYUxrgFD8acACaZMyW4kk9k97rKpk4HLUIC6xErWRsnj8Vwfoah/i3g9umv2AtziEEGiaiqapeLxOsnNnlyYZg0TSk+hjMDXCkZEGBpIjrMteTlOkjSUZ1TzS9TwhI8JtRdfSEGrmwfZH+ciCe3CrLs6Ez9Kd6Of6/A3oioOAnh6ox87cHGnn0a7nubHgKnyjYc2bC68hR8/keLBxnEwvkewePEy5p4hthVdzKtTCw53P8D+r30N3vI/Hu7fzB1XvYjAV5EetD7MhewW68sZlEWlCGTeUXglFiPEQ7VwhpWQwGWNHdws/aznCmWA/KcvElhKJxB51GcyV96IKhZU5xTgVjaRtcrC/g/ORYcp9k/XmJHBksIuz4SEAKv3ZM2bpXSjn0BMP09M5vbzDTDBsi9QM3qxXg6HUIKdDJ7g69/pL1uZcYUqTpJ24LBI0pJQMhmM8e6SJgXAUv9tJls+N06Nz/bs28vA3nubs8fOsvWEp67YtB6BhfzOtDR00H20DKUklDCzLGjfE69ZVkVucNU5xAdj0jrX888e/TefZXk7ta6awMo+S6okox3RSp42HW6lZXUlJdUHaAMtI93e4N8jxXWcY7B5BdahYhknpoiKkvHRK5vN6A3/70gk6B4IMh2LUlOczFIoRjM5PLKy/P0wsmqSsPGfSYCulJB5LsXdvM+1tA/j8btasqaSiMm9Og3LUMPjekYPU5eZxtKebd9Yv5YW2c6x/dbp96dWZ1cdI7BEiid0kzCZMaxBbxkmLlXlwqHnoWhkuRz1+92a8+moUZfY6eZYdJBh/lnB8B0mziZTZhW1HkRgowjVq3JTgcizE776OgPuWGX/wzuH/RTS5F7e+nOqChxHoJIyTDEYeJJo8SMpsx5YxBA40NQ+nVkGO7wEyvXdM257EpGvkHwgntk+73aGWUF+8m7mkL1p2iO6RfyQUfwa/azNl2f+CEA6Gor8kFH+OhHEG2w4hhI5DLcStLyfHdx9e57oZDbuk2cxg5EESxhkMs4uU2YUkMdr3JP3hb9If/ua0x/pcm6jK+xEzKYS/WpxvHWCwb34D/X9XaEIj4PAznAoxmBoh35lD0AgRMiIEHH6OjZzhwwveSbW/gkw9g6PBMwylgpS4XQgEqzLrWBJYNN7e2GDYFuvieLCRe8q2Ue9fOP6+6IoD1zRkeI/q4orsFdT6F+AQGieDTVjSIm4lEAgyNB8gUNJFX95QL3FaefkiXr95tCWl5Hx0hC8d3c7znU3julC5Ti/VgVwK3D4ydBdu1YFT1WiLDPN0xxkS1szhPkUIVuWUsCq3mL197Rwe7OBrJ3fygUVrqQ7k4lQ0BpMx9vW18fWTuzBsC6eicVNZ7SRu1oWImqnx//NcXgrd88ucqvLnoL6JpXkuFYQQ1PjrqfFPleiYD6SUHGzp4PDZrgsMMDnOT9px4iw9wyEmNPrH9pgMw7Ro6hpgb2M7pmVTnJVBRV7aQK5fv5DKJR/ixK5GHv/+CwghuPqutbg8Tq5/95Xc/tEJXTvdpTOmeO2YRsogI8dHWU0xp/a38PIzx9n6nk2z8nvdXheRYHSKQaRoKguWlPGJf3kvGTmjUhKqMqeat3PFvAync12DPLBtDbuPnWPDkgoKsv3858O7MUwL9xx0HUzT4vnnTvDobw9z591ruefe9Rdss/n2t7bz3LMnicWSaJrKo4UBPvPnt7J0WemsA5dhpYXL3rdsJWcGB7h/6TKW5hfwdEvTvD1OUkpSZivnhz5LLHUEKROkq2Y50hO6lNgyStIMkTRbCCdeJGWdx5VVi8LMhlPaQ3SKnuCXiSR2Y8uxyVaQnswVbJnAtmIYVjex1AEcWgkB91Su1NTr7wNpEk7spWvkCySMxtEtKqAgSWFYHRhWJ5neO2dsRyBwqAVoSv6od81GSgNbxuZ282bsXz8pq42+0LcIJ15EyhRCaCDS15w0W0iaLUSTL1MQ+GOyvPegTBN6S5mdhOLPYFrpVWzag6UB5uhnJ4Lpn0VFXPriz1JKjh1oxTQv3Wr39xmaopGlB2iJtOPXfBR78umO9xO1YvgcHixpjYfENKGhCmVCdkFApj61bqVpW/QnhxAI+hND1PoXoM5CAtcVB95Rr5QiJuQYFvrKyXfm8KXT38Gnebip8GoyHJef8OZcYUmbLx/fwVMdZ7ClJN/l4/7qVdxUVkeW7salajiUdK00RQie62xiR3fLRQ0ngGJvBp9YsomO6ON0RoM80nZj7epAAAAgAElEQVSSvb1t+B1OVKGQtE0GEzHCRgKXqvGuqpXcWbFsxrqDHnWi1M41RQv51NJr5nWdTlXFr1/qjCuBxCZqRrGlhSJUXKprkiCsLW1SdhJTmuPhSl1x4hCTeV+2tEnaCcxR/pkiVByKY3w/KSWGNEhY6XC3goJb80wrPptWbE9hyNS40eAQDnTFOemch8528p2n92PaE5KnY3I5zx1r5vnjzRe/fJn2Q45FbN26g1vW1FGSk0EiluTIjlO4vE68mR5cHh3DSF/bte/cwM/+9QnKFhWSlZ/BcF+ImtULyCqY3tsI6Wzc1dct4Ynvv0AykWLZVelED8uyiYXijPSHMFIGwYEwbq8Tb8DDhptX8B+f+S+efXAXFfWlRIMxqldWULKwAF+mhxd/8zIrrq4jNBjBG/CweEP1jOefL+ZlOGUHvAyMRCnI8bO/oZ21dWUMhaJzrlUUjxscOthGb2+QnJyJlYeUkhd3nOap3x1D01RWrKwgFktxtqWXb/7nc/zf/3cf/lmydFQlzXGKGCmyXW52tLViSUkwOX8BScseoTv4JaLJfQC4HEvwuTbi1CpRhBdbxjGsHpJGE0mzDcPqxKOvQFMuHo9OGGdoG/gjkmb6gVWEG5ejDpdjEZqajxA6ljWCYXWRNFux7BAB941z67M1QiS5l67hL5Iy2/Doq0bbLUSgYFi9JM2zGFYvftfFsgw1SrO/BJhYdhjLHiGafJmOoc+PhhNfHQyri86hvyNhNuJy1OBzbsDpWAgopIxWwsmXiKdOYVgddA3/PQ61iAz3VCVuj76K8pyvp8OPgJRJekP/RjS5B4GTXN8HyXBvnbYPqpLBpc6qSiZNjh9uu2yJ0ZcbFAR5ziye7tnFuuxlFLnz2d63lyw9QK6eRaE7j+PBRgIOP+ei5xEIAo4J78N0LntFKKzNWsoVOSv5YevDeDQ3a7KWjE/S6fFpmrpvM7Q1YoT4SNW9lLrT6e1vZU7isaFunu9sxpYSXVH5y5XXc3vFktEaZ1Ovy7TtOSmdK0LhivwKvrLxHfzl/sdpCQ3SG4/Qn4hiS4lL1chyulmZW8ytZYu5tbx+nCQ+HQpGS9JIIGqkKHD75pzY83pBYnNweB+N4dOEzSC64uS6/K2sy7oCp5qej85Gm3my+xH6k73YMi2zU+NfzO1FdxPQ0zpJpm1wZOQgL/Y/T9gMYUkLXdFZnbWerQW3oon0fWkIHeOpnscIGUFsJJ+o/gwl7smEZlvanAk3sHPgBTri7enalkjq/Et4Z+l9uNSJxeF1y6qxbTjT2U9b/zDdwyFiybFxc8Igmg0uXaM8N5ObV9fx7k0rUBUFS1FIxlMcfO4EtmWz8prFXHVbuqLEys31KKrC3iePkIynqF5Zge5yIAQsXFaGL9M7rdu0emUFVcvKqagrRh/Nbo+MRHnyBy/S0dRNYUUev/nGMyxaVckdH7uBBUtK+ejf38uuxw7RsL+FqqVlVK+sIKcok4984V62/3wvT/5gBxk5fq571xXz+u1nw7wMp+vXVOPQVBaV5fL1X+7kpaMtrKguxqXPLf5vpEw6OgZx6BpLl008EKFQnBe2N2Dbkq03LeO++zcyNBjha199is6OYU41dLJ+w8WzYtyag1sX1eLSNK5fUMW3Dr2MLeF/rJm+HtLFkDRbiCePAhKXo56S7C/g1ddO4saM8YhSVgcpoxW3vviiA6xlh+gN/uu40aQpOeQHPkmG6zp0rSztfUm3jGXHSJntWPbIKC9oDnwiUnSP/COG1U1B4E/I9NyBrpWOtyuljWH1YljdONSpYm9jmDiXA03NRlOzMe0hEMprUkW07BHi9ggZ7m0UZf7F6HWNFci1yDLfSdfwFwgndmDLCH2hb+B1rhk1diagqZlo6qoL2o2hKaPicEJB1yrxudbzesE0LbrPD3G+dYC2ln7ONfdy8vBERt9/ffMFAlnTV5BfUF3AO+7fgMs9Pcl4bAFimTbnmns5frCNvu4RIpEEbrdOXmGAlesWUFldgEOfm4LuWJuGYdF4spNTR8/T3xsiFkvi8TopLs1mxbpKSivz0LTXPyQlhCBLDzCUClLlLSNTz6A3Mch1+en3+/bi63i86wWOjZzBITSuzl1LwOFHIqc1dGCifHGBK4ethVfxbO9uit35CATP9O6iKdzGUGqEb7b8lCtyVrI2e+kr2hLjn20pMW2LB9sewak6KXDlsKXgSnL1t2a9yIbh3vFMtny3jy2lNTMm8NhSMpyMETfnJukhgUMDnYSNJF5N5w/rN1Lpzxo1nBxkOd1U+LLInUE76kIsy57ITu6MjdCbCFPsmdlD8UZgxBjmXLSFbYW34VJdnAwe47GuX5Ot51DvX5oWNkZhoW8Rm/NuwKW6aI2e5bm+35HvLGBrYTo7ujvRxe96HmFxxnKWBlZgS5uh1CBu1T3pvtT5l1DkKuXYyCGe63uK6QbcnkQXPzv/Y/Kc+dxV8i68qo+YFSNlJ9GViXFFCMGiolwWFeUSSSTpGAzS1jfCF3/xLKFYkjvWL2Z5ReF4+GwmOFSVDLeTsrxMKvMmBK51l4PNd69n891Tx1qhCFZcU8eKa6ZGeq6+c/r5WAhBTmEmH/jrydUXAjl+7vv0rdMeoygK9eurqV8/1ZOUV5LNu/509kjNq8W8DKclC4pApAepv3zfDaRMC5euoTvmtoo3LZuhwSjFxZn4RxW6pZQ0NfZw+lQXBYUB7rhjNTk5PrKzfSxfUc7Zln7Oneuf1XDSVZXN5ZVpafvySlYVpslNfn3+mTCWPYI1So52OaqnJRQLIVCFF7dSi0uruWh7UkpC8ReIJHcBaU9TSfY/EHBvu8BgGm8ZVfHi1uuZn6WSJkYXBD5Fru/D6ZDVpCw/BV0rQtfmX2fpUkFVsinO/Ct0R+WkiUsIFae2iOLMv6G57wiWHSSRaiCS2EXAc/Ob1t/p8Ouf7OHnP9iJkTQxTGuKp+nQ3pYZjw1eEePWe9fOuN22JA1H2/nlj3dz4nAbibiBbdnYdtodr2oKP3U5qF9eyv0fuYa6ZaVoF1Hqh7TBdGTfWX71k900NnSRSppYpp128SsCTVVwunVWb6ji/o9eQ0VV/iXXWHslFnhL+bulf5yeOBB8rv4PcSrpkMVCbzkfW/huDNtEFQou1Ykq0toun1z0fpzTkLRvL04TeBWhsCKznlr/ApxKOmxzd8lWbMZ+I4FTcaCg8KmaD+IcnWjKPIV8quaDuFSdp3t2UeEt5src1Sgo7B08wu+6X+I9FbfPaLhdzggbyfEsuyynB9dFiOURI8mevjasOboinu1s5BsNuwkbCT6/cgsPVK+eJLw5H6zOLSXP5aU/EeVcaIiXus9yz4IVb6rXSQJbCm5maUY6GabQVUxj+BSHhw9Q46tHExqV3ioqvAvSXDghqPJWczR4iLbYufEwmmGnMGyTHD2PEncZHtXLGBl/7JkSQuBS3TgVF9kzZNJJKXmpfzua0Lir5N0UuUrGw3wSOWMY1OdyUleST01xHj/ecYjjrd2srS7ltrX1s2f/jv19Cy4aXk/My3C6kKTtcel4gCNNnSyuLEB3zN6UlBLLsvD6XOM/hGnaHDt6nqGhKBs2VlNWnjNKjoS8vAxAEppDmjPAcCLBS+2txE2De+qX0B2JEDcNinzzIxoqwouieLGsEPFUA0mjEVVf96pTvm0ZI5LYNVq2BDLcW/G7rp3GaJrS8rz67XLUkem5E0W5vAQqx+B3XYVDK552AhJCoDsq8buuZST2WywZIpo8QIb7xjncpzcOOXl+6paWjHMFUimTs429RMNpgnrt0pIZxR8X1RejzjCxmIbFS8818O2vPDVONFc1hew8P16vk3g8xVB/hGg4wYFdzbQ29fHhT27h6i2L0WfgF6ZSJk/86gA/+c8XCIfS75DDoZJfmIHTrROPJRnsCxMJxXnxmZO0NqfbXLdp0awG2WuBKlR82gRvyHeBsKcQArfqwv2K0wsh8E6joC6EmCQToAplnLsE4Fem5ydd2JYqVLyaG8M26EkMUOzKo9CVS9JKjZ9j/lrLlwdynB5UITAl9MXChIzEuCbUhbClzdMdZ9jeNQvvZRTWaGmYYCpOQHezPKfoVRtNQggK3X5uLV/Mj5sOEDFTfP/My1T4stmQX37R8TVhmfTEQlT4Lr1HMEPLIOCYqOfmUlwUuUvoSXRdYIxDZ/w83fEuImYYUxpEjDB+zQ+jplGxu5TVWet4uvcxzoQbqM9YyuLAMrIdOfPqsyENuhIdZOs5FLqKx48VQszJqBdATXEux1u7096yWZIQ3sbMmHVGsm15UQ7TE7sbqCzKnpPhpCgCl0snHk+Nr4JisSS7dp5BUQTXXz853DXmUrbt2WPuScvi+0cP0hkO0zo8zO2L6jg7PMzpwX4+vmZ+oRunoxqXox7D6iZpnuX84GfJ8T1AwHMrmpo3ShKfj1RCkIRxGgAhXPhd17wORGWBW1+OQ718hSrd+jLERR45gYZHX81I7LeAJGWex7LDaOrUgqBvFq68ro5VG6rGnYGD/WG++g+P0tSQ1qG5/yPXULtk+pI0mq7idE01cqSUHDlwjh/++3MM9oVRFMHSVRXc9d6NFJVk4dBVTMOivyfEb3+6j8P7zzLQF+J7//YsgUwPa66snvI82rbN7u2neOg7LxIOxVFVhQ1X13DzO9eSX5iBpqkYhkVH2wC/eWgfp46ep/1cP9/68lPkFQZYWFv4325Q1YTGptzVPN27i5fPnEBBUOTO4+aia6Yl6cIF4qejaf0SiXnBeCVJayeZtpUOCArxhq7iV+QU49IcJFMWg8kY3z69j4/UrsfnSNcstKVkJJXg163H+XHTAUzbRkFgz2IoXpiFFTYS/LjpIJpQKPEGxhXpgfHr1YSCrqozekVcqsZ9C1dyaKCDY0PdNIUG+KuXn+CdVcu5saSWQo8fZbSmYtIy6YgG2d/Xzt6+NlyqxteuvGuSKOilgCKUV3jGBarQMKUJSGxp8Uzvk+wf2k22nkO+sxCX6p5iZLtUN1sLb6PGX8/B4X081fsYewZf4qbC21kaWDHjPXklLGlhSQuHor9q72dt8RunSfX7jFmtnZdPtdNwrmfabRI4ebZnzuRw3aFRUppNW2s/nZ3DVFTksv35BtraBqhfXEJt3WTtgFAojpTgnEPGXsxIcT4Y5PObNvOnTz8JQIHPx6ONp+fUtwuhKbkUBD6FaQ8QT50gabbQNfJFekP/QcB9I373Dbgd9aPcpNkfeltGSZkdo23noGvll1xLCJTXRaPoUsKhFnNxKQAlzcvCgcTAtAexZQS4fAwnt8eJ2zORvWNa9iTvjD/TQ1aub16TYmgkxoPf3kF3xzCqqrB521L+x2duIuMVZQIqFuZTt7yUB7+9g0d+tp+B3hDf/srT1CwpISNzwosgpaSrfYiff38nI0NRHA6VW+5Zy4f/eAtO14TRL6Wksjqfpasq+PZXnub5J47SdX6Ib335Kb7w1Qdm5GL9vkIIQbWvgoW+8vHJTzDzaj6YSrC/r52wkSRiJImYKaJGkrPhwfF9OqJBvnFyF/luPz6HjlfT8Tmc5Lq8rMkruyhh+lJgUSCPd1Qs5cHmQ5jS5tun9vJUx2mWZqU9RIOJGMeHuhlOxsh1efnk0k0829nEsaHui7YrENxYWsML3S10x0I80naSx9obXpHcnlb4znK6qQnksbW0hmuKFlLo9k8rulqdkcvfrd3G/zrwFCeHe2iNDPPlYzv41+MvkuV041Z1kpZJ0Ehg2NZoiApWZL9KzZlZEDNjJO3keMjNtC1GUkNpLxQK52Pt7BzYztqsjdxSdAeq0LCkxZlww5S2XKqLOv8Sav2LGU4N8suOB/lVx0PU+uvHieazwak48Wk+QkaQuBXHo03PpbwYVi8s5abVtVOKBL8WSCk5d7aPrs5hsnN8LKopwjFH+s5bFbO+tTuPnkVTFbIypv5I8xWUcnt0Vqwsp6mxh3/716coKc3mwIGzOBwaW7YsxXXBatxImfT0jCAEBDLn9oBMDHZpdISCZDjnn6IqhMCjr6Q0+0sMR3/OcPQ3WPYQlj3IUPSnjMQexeWoJ8N9A1ned+BQLy6XIKWJLdPlBBThRpkhfPDaIFCVN79q9MwQKMJ1US5iOkSrI4Q+KoGQGM+e+33G6eMdnD6eNqzziwLc9Z4rCGRNfUaEEPgz3Nzzvit5eWcT51sHON86wJ4dp9l6x6qJZ1DC0QPnaG1OF+JdUFPAHe9eP8UQGts/K8fHAx+9hgO7mwkOR2k+1cWRl8+x4eqa/3Zep7mGPQDaI8P86Z7fErdmfkYHElF+ce7YlO+rM3L54bX3U+h5fd9ZAXys/gqiZorH2htIWiat4WFaw8OT9qv0ZfFHSzZxU1ktp0b6Lmo4jS2U6zMLWJNbyuPtDUguqCZxgcclbtnEYwZdsRB7+tq4sqCJL669edrrFkKwLKuIf1x/Kz9tOcwjbScJphJYUjKQiAFTJVFyXR42FlS8Ls9pzIpyfOQwCzxVKKj0JDppj51ja+FtqELFkAZSSjIdmWjCgUTSEmlkMNmPT5vIGg8ZQSSSDC2AQJCpZ1PmqaQ5cmZ8zprJ+XDh94pQWBpYwaNdv+boyAHWZV857gmNWhHc6vTyBWMYI4z/v/dfWtK0lJBIGDSe6aH1XD+f+YtbcQTmb9S9lTCr4ZSX5eOGtTUU5kzzgkvoHgzPucyKw6Gy5calnGro5FRDJydOdOBwqGy6uoZN19RM4lD19YVoaxvA5dKpqJjdveh16FRl5fDV/XvoioT5yr7dnB7o58/nWOD3lRBC4HYsxpX5OXJ872c48nNCiedJmZ3YMkIsdYB46hhD0Z9TkPEJMj13XIRbJJGjOkOItKDe64PL19vE+ABx8USOSSvWuebLvsWxa/vpcZJ5/bIyFtZenMCfnedn0w2Leei7L2JZNru3n+b6W1aMr/JsKdnzwmksy0ZRFVauq6K4LPuibRaWZrHh6kU8/cgRYtEkB3c3s+7KatTXkev0VoeuqFT6s0jOonk0HUq8AbQLxjunolHpyyLD4aTA7Z9svAkIOF1U+bPxjHqsLoQyGiILpRKUejPRLiBUj/GH/vfqrdxZuZTH2xtoDg4QNBK4VAfFngyuKqjkmqKFFHsyUIRgfV45zcEBir2BaRXMU7bFo20NfPfMPrqiQXJcXvJcPvLc3kn7W9ImbCQZTMQYTESJmCl2dLXwtRMv8YW1N03q54X9rQ3k8Rcrrue91WvY2XOOw4OddMVCRIwkuqKS4/JS6ctiXX45y7OLyHZ6XhfafoGrkLPRFr7e/GXcmpvOeDsLvNWszFyDQFDiLqPEXc72/mdoj7ViSIOoGSHPWTCpnXPRFh7vehivw49P8xEzo/QmutmUez2O0WQHUxrsG9pNxAjTGmshbsV4oe9Z8pz5FLqKWZyxDE1orMvaSGv0LI93/4b9w3vwaxmEzRBuxc0DFR/Cp73xi2dFESxeUoqqKbSe65/9gN8DzGo4PbB1zWiBv+kfzTs2LcHtnJtLXwhBdXUBf/rpm3n+2QZGRqKUlGSzZevSKbpO4UiCQMBDaWk2tXWzZ4I5NY2PrlzDS+2tZLvdOBSVz2zcxMqCV8/5Sa8+XbgcCynK+hx51h8SSewklNhOJLELw+omZZ6jc/hvsGWcbN/904o2CqGhCC+WTCJlElvOT2399wWziWhKJDYppExrbwnFCZcRMfz1gGmmZQIg/bzVryhDVWc3gJetqeCh76b/7+8J0t8THDeOjJRJ06m0x0B3qCxaXDyraq6iKCxeWc7TjxxBSuhsH2RkOEZO3uXsxXxzUZuZz2M3ffSStFUdyOVnW94/7TZVKLyraiXvqlo57faA7uJrV9417TaYKN57ZUElVxZUztqX99es5f01M2d/PtF+ir89+BRxy2BT4QI+ufRqlmVNTw6XUhIyEjxx/jRfPPQMCctkT28rbeEhFgamXxALIXBrDqoDuVQHcvmAXMvxw+20nu3D43Vy3aalc3pHXguKXKVsK7ydWt9ijocOM5QapMZXx8rMtWTqaeqAW3XzQMUHOTS8nxFjBJ/mY0nGcqJmlIFkL2MLwCpvNTcW3kJ3ogvDTlHgLOL6/G1U+2pRR8c3W9oMJgdI2Uly9Dw25V4LQNAYwaW6x8noTtXFvaXvpSlymrbYOZJWkiJXCVW+atzqm+vlmc5CCAXjHDncxvBQBK/PxYqV5eTlZ9DbE6Sne4REwqCne4TcPD/rNixE1zWMlMnhQ610dY1gGhaqqrBuw0IURdDVNczKVRVomkpLcy+RcILlK8sZHo5y7Eg7IyMxAgEPK1aVk52dtinOtw9y/Fg78VgKCZSUZLN6bSVCCE4e76C9fYCsLB/LV5QRyJy5xNmFmHVW0tTJ2kWWLbGs9I+oKIK6yoJ5E9UqKnL54IevxjRtHI7p9WgqK3L55Ke2oTs0vN65hdv8Tie3LKrl5uoJeQBT2jgu4r6cDzQ1m4Dndvzu60gYjfQGv0o48QK2jDEUeQifcyMufao0gcCJpmSPhvtGMK3+S1o3560Cw+ojXY9vht9DSkxrYFSxHDQReF3Uvi8nxCJJYtFRQ1FAQdHcuAe5BRkoisC2JfF4Kl1gtyy9LRxKkIin76GiKeTmT1XbfiWEgNz8DIQikLYkEkoQjyWBtw2ntzGBwUSUB1sOEbcMvJrOp5dvZvlFOEZCCAK6m1vK6vnF2aMcHewiZqVDdzMZTq9EV8cwD/3gJTZeU4tQXpsohGlaJBMmbo8+YykvIQSV3ioqvVUAbM7bMmN7AUcm1+VPFdxd5K8d/9/vyGBd9saL9supunhHyT1zuQScqpOlgRUsDayY0/5vJmLxJG2t/eTlZ9DU2MPZll7e+4Gr6egY4tvfeI6166ooLMrk8UcOI6Vk0zV1HDxwjp0vnmbT1XVsf/4kiqpwzbV1NJ7pYdfOMyxdVoamqTSc6KDj/BDLV5YTDsXp7BgiJ9fPsSNtdHYMcu99GwkFYzz4k12sW1eFkbL47cMH+PRf3IaiKOzf28yulxpZuryUUw0dNJ7p5r3vv2pO3M55Lef7R6L811MHONPWh2nbFGT5ue2qJaxfUj6vOkFjtZh0ffpjhBC43PqrJqeOGSTRVIp/P7CPz77KcN1MbavCj0dfTUnW39E++GfEUgdIGI2kzHacjkVTDCJVCeDS60iazVh2kGjyAH73dQgudYmAyxvx1HEkJmIGw0liEEseGf0k0LVyVCXzom2+koz6mlQ63wTEY6lxaQNgEvF8JowV2XXoGsmEgZmySCYmeDbxaHJSoWyXe/bkCiEEDoeKQ1NJpUySSQMj9XYZmbcxGa3hIXpGC/IuCuRS5p1b4oYqBF7t1Y3nLY3dZOf5ue3utBfs1a43pZR0tA+yc/sp7nr3Bry+y1O25fcJOTk+rtxUQzicwLYl+/Y0E42kIy4ej5O7711PZpYXy7I5fuw8m66po6W5l6LiLNZdsZB4IsXJEx0zSryMobAokw0bq4lEEkSjSU43dJJMGgwMhImGE6zdsBDblmx/roGcHB+qqvDYI4dZsrSE3Fw/liV5/JFDvOPuNZfecPrNjmNICR+/+yp0h0rDuV5+8fwRli4swj+HAf9SQ0pJZzh0ASlxMsKpJO2h4OtybiEEmpqLrpUQSx1AYiGZfqJRFR9efTWh+DNImWQk9hhZ3rtw60tel75drogm9mJag+ja9CtU0xoknHgRAEV4cDuXocxQ7HcCYtwrlSaURy6qMn25Ia0APvF5rjXv0ppoo55fVZkkWjmpzQv2mw22LbFGU+lVVZlTce238d8LprTHx1t7hlI20yGYStAUHADS0gN57tkTZGKxJI/9+iBHDpxjoD/MN7/6NNW1hWy5eTlSSk4eO8/BfWdxOFSu2FTDgup8bFvSfKaHIwfPEQklqKjKY9N19bhcDvbtauLF5xpobuxhaDBCQVEmN9y0HEURvLynmas21+Hzu2ht6aPxdBdbb11JPJbiud8do6q6gAP7WvBnuLl2yxKycnwM9IfZ+cIphgbCLFxUyJWba3HMQZbnvxNefOE0hw+2UlmVRzSSxDDM8UVdXr4f3amNyhQ5SCXTXMEVKyv46YO7+fZ/Pk8sluTKq2qmva+mOSGa8cxTx2lq7KG8IpfBgTCGkc66LC7OIjfPz/e+9QKaQ2Hx0pI0LUjK0RChD2t04XrlphrcrrkZ9/P6lXuGwtxz/UoWV6bJb4U5AQ6cOj8nnaWZYI+G/qSUKIqYl/CeJW0+9vhvZ0zpNaVNiX/2MMWFkNIiYTQhUHBohSjCA0KdMhGP7Temz6QpOahK5rThNyE0Mtw3Mhz9NXHjBIbVScfQX1OS9be4HIsQYrL0vpQ2UiawZAyBQFWyfy/CeobdR1/o3ygM/PnovZqoJWbLEH2hr2NYaT0kXSvF75q90KcQGrpjNEaFSSx5ENPsG639d/nfM6/PNakK+PBgZNZjpEyH0kwjbWTpuobHM/HC+wPucQ6IbUuCw9E5thkfJ6m7Pfq0mlNvNYxN8nNNYHkbF0e+y4fXoUMcGoP9HB/qZmNB5STtpjFImdaw6otH+OdjL9CfSD/bCzNyqfLPHqbTdY2NV9dgGiYtTb1svW0Ffn96kdR8podfPriHLTevIJU0+PF3d/C+j2ymoiqPSCRBXn4GlVX5/O7RwzidGpuuq2dRbREjQ1FCwTg33LScQKYHf4aLnq4R9u9qYvW6Bfj8Lrq7htm/u5mtt64kmTT42Y93s+Wm5SxeXpqep1SFUDDOz3+8i/yCAMtWVLD9meNEI0luuXP1pb3hbyFM5794/tmTXL9lCZuuqaXhZCcNJzvGtymKMu3yNndU9Pf6G5aQnesjM9ODoqQ94slE2hsuSHOXtNEF4wvPNXDXPetYu76KfXuaOd+elgTx+dNi22vWVlJdW0ggw43mUJESSsuyWbKklM3XLwbSBYU9c0YIJagAACAASURBVHQAzctwWlVTynMvN5JMGWiqQmN7Px63g9aeYZxaCEVRWFSWO+uEJaUkHjdoauzm3Ll+BgciJFMGy1dUsGlTTbr6c8okFkuh6zNznKSEAq+Pr2y9eVoPQzCZ4J/27JzPJQI2wdhj9Ie/j8+1AY++GqdWjqpmo+BEYmPJEEnjHMPRn5MwzgAKPtdGXI6Zqy/rWgUFmX/G+cHPYNlDxFIHONf/ITLcW/A4V6MqAQQKtkxg2oMkUg1Ek4fI8t5FfsYn5nkNrwVytABkEpsk0k5gWL3jb4XExLA6EMI1Ki/gRKDPQbrfiaL4GIr+gpTZTabnFnStFFAwrT5G4k8Qij0LSAQu8jM+jqbMXFNvAhoefRWakotpDxCKP4+ifIlM982oSgApJNJOYMkompKFz3Vpiz2+VuhOjYqFeXS2DabLD53q5oZbZ+cuNJ3qGv8/kOUh94LK4263k7IFeZw+3oFhWJxr6mPtlYsu2p5tS1rOTOi15RYE5iwDcrkhGEvQ2DNA90iIcCKt/u1z6hRl+qkpyiXgdr/qcM9/d5T7s7iqoJKzoUESlsnn9j/Be6pXszS7kGynB01RsaRNzEwxlIxzariXpzvOjHub8lxePl6/EcccSqmoqkJpeQ65+QH6e0NUVU8UXd7+zAk0VSU4HMU0LYYHIzQ39rCgOp/KqjxaGi2CwzFUVaHtXD+brqsnO9dHQXEmPr+Lyqo8PHPkzvp8TjZdV0fVoolsuabT3Zxp6CI3z09fbxDd6WDHcye5+R2r3hILtkuJcDjBkUOtnDndRU/3CE8/dZzauiKWLS+nfnEJL+9rYWgwwvn2QXxzCI9Go0n6+8OcPNGBy+2grDyH2rpiSsuyURT46X/twenUGByIUFCYdozU1BWxZ1cTnR1DnDvbP24AGYbFyEiM1tZ+gqEYfr+LFSsrCGR6eMfda/nd40fo6hpBVRUCmR5uumXFJFmkmTAvw2kgGGHn0RZOnO1GVQTBSAKnrvHdR/YAArfTwf/5+K0XVXCVUjI0GOG739nB4cOtDPSHL+B4CDZtSpOrW1r6+NEPXqKwMMAf/8m2abMoVEXhf67dQKZregKxQ1VZll8w7baLQ2DLEKH4M4Tiz6AIL6qSgcAB2FgyNlrLzgIELkcdeRkfR1VmTvkWQpDhupbizM/RG/wqKasT0+5nKPoQw9FfpsNNQrkg627MUHnjeCaG2UN/5LskjbNImULKFLZMYdlBJOkJyLKGaBv4o7TeEjpCOFCEE7e+nFz/h1AV37Rtq4qPvIw/ZDD8Y8KJ54gkd6MpWYCCZQexZZo3IYSLHN97yXBvm9MAJITA61xNwHMTg5GfIjEYjv6cUPxZVOEjXeM8ibST+N3XXXLDSVHEpEnYmmOo7cL+r96wkN3Pn0ZKOHOig+BwdIr45YWQtmTfS42jx0PlogJ8GRMDklBg5boFnD7egWlYnD7eQTScwONzztimaVgc3DNagNqhsmBRAS7PW0sA07Jt9jWf56G9Rznd1cdAOEbKSv8eDlUl1++hpjCXd21YzqaaykmJL29jblCFwkdqN9AY7GdfXzs98TD/euIlsp1uMnQXqlCwpU3CMgmlkoSMNJ9FAOW+TD659GpW5V5c924M04lkQnoOGRmO4nI7UFUFVVW46fZV1C8pIRSM85PvvkhOnp+q6gLcbh3LeqUrRE7b/hhMw56kn+Ry6/gyXJPOn0qaGIaJQ9dQVYW6xSWs3/iKhbOUSOscMvzPU0/iWIrwvA9xWWvvTQ8pJcQeRBpHEe47UdXVZGS4qV9cQv3idP28McPljrvW0HSmG8uyuWLjIizbJhDwoOsaGfesG/dqr1xTSXVNIbZls/PFMyxeUoru0ohGkvzyZ/v48B9cS2lZDh/48GY6zg+hOzVu3LaMVCod3rv3vitoaepFSsnGq2rS3iO3TsPJTrw+13i23IljHbS3DfKe929i5aoKcnP99PYEURRBQWFgzsKd8zKcHti6hnffsGrG7WP1b2aClJLe3hD/+uUnOXjgHC63TnFxFsmUSX9f6MKW8PtdhEJxzrb0ccttq6ipmSorIIC1RTNndLg1jQ+tmK/rVMXruhL/qGJ4elKPXZARlhZp1JRMNDUfn2sTef6P4lCL5jAYaGR578XjXMNA+PtEEnvTmXYygiUjICUCDUX40ZQADq0Yj/7GZU5YMkQovp2kcWbGfSQGsdSRKd9bdogc3wPA9IaTLeO4HPUsyPsevaF/J5o8gGkPImUSgYqqZKGrxeT4P5DWxBJz93Yowk9R5udRFT/B2FOY1gCWHcRiGIGGEDqq4kdTL325gXQSw8QK5WxjL8vXVM6rjY2b6/jNg3vpaBvkbGMvTz9yhDvv3zAphDcG07DY+VwDJ4+0A+DxubjpztWTnj0hBFffuITnnzxGX3eQoy+fY9f2U9xw6wpUdeozmkqZPPWbQ5xt6gXS9fiuuXHJW2rlnDJNfnuwgX9+4iUiyRRep06u34OuaePbg/EEO06fY//ZDj617SruXb8M59uclHmjxBvgKxvv5Jdnj/JUxxl642EiRoqhZAxLSlQh0ISCU3VQ4gmQ6/JyZUElDyxaRYHbP+cSIxdD1cJ8zrcPcsWmGnRXOknC43Ey0B+i8/wg77h3PVnZXvbubJxEJdE0hVTSJB5L4XBoaA4FTVOwLJvgSAy3x8nZ5h4M44IFkGBKRMOf4SYr20tNfTFV1QUYRnoCn/LOyCSYLYCR/t8OAUnSi+53v+b7MC9Imc5YtkdAyURMI50zJ9gDyOg3we5FyhDuzHWsWFUx7a4ZGW7WrKua8r3T5SDzApHfgoIABQUBhgYjHD7Yyuf/151kZnkYHIhw+lQnoVAcIaC4JIvikqkJCVlZXtaun3we07Q4eqSNqoX5bLtpObYt2etpYv/eFizTwqFrVC7Io3JB3rxvwbxGDcO0cDo0HJpKJJ6krXuYisIsfHOMC5qmzbPPnODI4TYqKnK5+5511NUVc+RwK//+9WfH9xMCcnP9FBZm0t42yNmWvukNp9nCQ0LguEjhyUPDL2HYSZYFriBkDHE22kDUDOHTAizw/w2FahzDPI9pDWLJKP+fvfeOr+O4zr+/s7u3F/ReSQAsYO+dFIskiurFapYsO26SndhJHJe4JL/YTnXimrhJkSxLsmyrk+oUxd57JwGSAAgQvd9eduf9Yy9RCIAESVBhXuf5fFju3dndmblbzpzznOdIGaMxXMdx3zHmZNxPpmMeTdEwOzr2EtHDODU3Rc4x5DtL+s+bEeVssJJzoSrCehCn6qLA+QmKPZ8mEjtNTG9KKIvLRAjMS10kQGNc5VRnI5IX+x3PrjpYknGnqULr+hhnIw5ao02UWcYS1gOc8h+lKVyHxCDZkk6JewIpVvPikEh0I059qJqGcA3dsXYkEreWTK49lVT3J5CGSaiPGhF2t68j31mKQ3VzvHsvNsXO5OS5WISNw1076Iy2ku8socC96qLGjiGjSOLYreMoSP1XQrFjhGMV6IYPIaxY1Gyc1omXVGEf6ndWhYfspK+R4rqXUPQEcb0ZSQwh7KjCg0XNvmgo9UrhdNnIKUhD7DSrob//+j6mzCymuDRrALnaMCRCDLxuk1Nd3H7/bJ79xYcE/RFee2E7mqaw4rapeJJ6vamhYJSN7x/hpWe3EvRHUBTB8lsnM6q0v1dVCEF+URo33j6Vl57diq87xAu/3oiiKMy7YWxPNpGUEl93iHVvHeLl325Fj5uCmavunUFO/vVT5uZSkFKy+0wdv1i3k7hhsLS8hOXlJRSnp+BxWM16aqEI1a0drDt6mu2nzvLUht0UpCWzeGzxdWUg1vq6WH3mOHOzC5iWmXvV3CwpJS9VHqYx4OeBsZPJcg6+sLkcCCHIdLh5onw+94yazBtVR3nuxH5yvR6WFZSgKQp2VSPZ5iDH4WW0N5Vkq2PE5lkIwdKbJ/HCf2/iv3++DqtNw5vk5MZVk3F7HGRmJ/Pqi9vxJDkJBiJkJsLYQggyMpOwWDWee2ojo0oyueHGiSSnuCgclc5LL2wnKdlBKBS7aGKEEILsvGQWLBnHW6/txeGwgoBZ80qZu/ACORptNCL5P0EGwOhABp+F6LYRmYfLhQSIHUT6n0R4/hos467sQMIJWjHEfAhtPCMpvOxNcjBpagEvPLcFh8NCKBgjI9NLQcHlFUQGM9Q7cVIBH6w9QmNDJ4Zu0N0dYsVNkwZdlF4OLmvvNZuPkJeZzNwJRfz0j5uoaehgcmkOn7lz3rBWbsFghB3bK5FS8sQXVjBtRhGKonD6dNOAtna7hfQMD/G4TnPztcmMO9y1g7ZIIyE9wL6OTQTjPuIyjsTApXm5K+/PKHPf3M9FW29sYX+gismZ49jesZ897euJGCF0aYbt5qbd2M9wCsUDvN3wPCd8+4kbMc5XzLapdmalLmNB+i14ld6HSlgPsb75VfZ1bEMisSo2gnEfYT0ICNJtWRQ4zZtTCIHXcQcdopOjoW3cYHhY3/gMp/1HiRoRJAZ21YVNdfQYTkhYXf8bTnbvJyajJhE9scGmOFiYsYoF6R9HESr+eBfVzfUo+gSagnU0RgqIGzGELQen6uFA8DRB3UFV3EJBcjmpysU0l4wenpSiOHHZZuKyDS2ydyUQQsNuGYvdMvbSjUcIiiJYtnISG949TMAXpupUM9/9yh8oG59DRnYSum7g7w7R1uJj/KR8Hvj04gExdM2isuL2KdTXtvPOq3tpa/Hx7H99yNo1BygcnUFyqpuAL0TVqWbqa9sJ+MKoqsLsRWO495H5KIN4kewOK3c+OIfaqla2fnicxnMd/Pzf3uaNF3dQWJKJx+vA1xnkdEUjjec6CAWjaBaVpSsnccvdMwYdqx43CPjDBPxhgv4IAX8Evz9EXXVbT0aMbhhsWXeMzJwkXG47Lo8dp8uK02XH7bGjXYMaVr5whNX7jtPmD3Lf7Il8YcU8Ul0DX9TTinJZMm40P/9gOy/tOsJbB04wrSgHr+P6SUvfdK6KH+/bysPjpjAxPQvbRWrZxQ2Dc/4uPFYbKbbBDRMJvHH6OEfamlheWDIihtN5CCHIdnrIcSTRHYyxKCuTx8svrld0JZi3aAzTZo7q911qmptPPbGM9jY/hm7gdNtITXOjqiqf/sIyujqCWKyaqdfUZ14ys7x87ks30t0Vwm634PLY0DSV+x9ZQHubDxB4vPae69njcfA3376TlLT+82azWVixagrTZo0mFIqiaSpp6ReE3YQwJWcsCX6hDCMj7434/FwOZPgDiO4A2X3pxkNBOBFJ/waGD9SsEa2EoWkqDz48n7ZWH/G4jsWikZLqGraWY79uCsHkqYXkF6QS8EdAgNtt7ye2fcX9vJzGJ8+2MGNcAXtP1hGMxPh/n1nJz17aTDgSG5bhFI3GqaluJTc3hfKJeRdVMxZC4HJae4jk1wotkXo2t7zJ4ozbGeedjoLCke5dbGl5izfO/YbHiv+GTHt+v30MdHa2fYA/3s2ijNvId5ZgSJ3GcC059l6XZUQP8X7THzjQuYUJSbOZnbqcZEsG7dEmtra+w7qmV1CEypKMOxAIpJQc797L9ra1jHaVc2fup0iyptEWbWL1uac5F6piVc6jjPcOfLFFjBDvN/6BmIxyW+4nSLNmETKCtITrybUX92s7yjUOq2KlxD2RTFseBpLT/iOsb3qNtY0vMd47k3Rbr4dvX8dmVuY8xC05H+e1uifZ3f4huY5RPFT0ZepD1bzf+AcOdm2jyD32EjIA/7s0loaL8qkFPPyZxbzy3DbaW/001LXTUNc+oF1Kmhs5RAaqy23nM391E95kB2vXHKSpvpPTJxv7EbbPIznVxcLl5TzyuRtITnMNuRLzJjv58nfuIC3Tw+a1x2ht7qbiWD0Vx+oHtM3I8nLjHdO4++G5eJIGfwmfrWrh377zKlUVjeYvOcjPqccNfvGDd3q/EGZIPSM7ia9+757LDmMOB+3+EPtr6nHbrXz2htmDGk1gPlNSXQ4+t3Q27xys4GBNPZ3B8HVlOM3JLuDhcVO4uahs0Ey1vmgK+vja5ne5p3QC94+Z9BH18KOHx+vA4+2/KDtft/HC7wFSUt2kpA7+clRUhbR0zwAjx+2xD6oVpGoKeUOUK7JaNXIGCRtdv4hDdPtVH0UIAWq2+ecawOWyXZGhNBg0TTU9jldCdb7YcS+nsdWi0h2IsPvYWRZNGY3bYUWXxrBLikkpicV0XG77Jd1uUkriupEQ5rt2JE5dxhnvncmC9FvQEnWDFlhvoTPayp6ODRzv3k+GLbcndf48qgMn+NSov6XQ2St4WezqdX1KKakPVXO0azeZtnxW5Xwcr8W8AVOs6XgtKbRFG9jW+i4zUpbgtaSgyzj1oSoieogZKYtJsZleogxbDhOSZnMmcJz6cDXjvTMGzJ+BgT/exQOFXyTZktGzvdQ9ccCYJyfPZ3Ly/H4FIZMtaTSH69jW9h4N4ep+hpNNtTMtZSEO1cUYzxTOhc4wzjOdQmcpbi2Jba3v0BFtxZB6TwmBPyUIIbjtY7MoGp3J5nVHOXqglvaWbqJRHYfDijfZQUFxOtPnjh5SbuO8AOX9n1zI1Nmj2b2lkv27ztB0rpNAIILDaSU908PkmcVMn1PCpBnFl8wKEkLgctt47AvLmLN4LDs2nODI/rM0N3QRCkXNMGN+CpNnFDN97mgmTC3Eahs6o0RKiTRMj6mAwWssDLkviX1HHuF4nFZfgFEZqWR4hzYkwZyTNLeL7GQP1S3tRGKXX2fuWqI0OY1/mDe0UvV5SClpCgY43dXeUyj2/zA45JB6U33kcy/2PpI9pXgH7H/Jfa8C/fs9dNmzIdvJvleGNLlWelPvNjnYIm7w81xyDoc7B1cyl1L2ucbNdv8Tv0dfXNZbbvnMMfz6jW1kp3l5aGw+3cEIyW7HsLNTVEUhKclBa4uPaDR+0bS/SCROU2MniqqQfqELdAShoDDWM6XfC9+q2Bjnmcbejg00hKuJGGHsF9QBKnNPJt85euiLGcm5UBVdsTZmpy3Ho/WuTIQQpFgzKPNMYWvLO5zxH2VqykKzFLA0vWsXns+m2EFKYkZ0UIFHBYXJyfP6GU2DQQiBIhXiMoY/3kVUD6PLOAZGD2kzGO+vJZRiTe+ZnyRLGqrQSLVlIlCwqXZUoaHLGHEZ/5M1nOwOKzMXlDJ5VjGxSNwUVUuU1RHKeaVv9aI1toQQWG0WJkwtZOzEfO7/1EL0uJnh01zfyc+/+wYd5zoYOyFv2KnUQggcThtTZ41iwtRCs28J3TQhBKqmYLVpaNrgpY/6omh0Jj948lPDFtTsC0URWG2aWXj4IrUvrxzmMS/HhBi+fOPlQUpJMB6jNRQgEIsNEOgVAnJcHlLt5j0e03UqO9v6tct0ushw9DcCpZToUtIS9OOPRdl0rorWUIBzfh9H25p72rksFvI9SQM8VlJCZyRMWyhARNfRFIVkm510h6tfOKsp6KctFCTb5e7p43kEYzHq/F1YVZUCdxJqn6iBKiCix2kOBvDHIggEKXYH6XZnv3YfGaSBNNqQ0U0QXgd6lUnOFhZQssBSjrDOQVpmIdS0wQ8h4xCvgMh6ZGQLGA2AZnKXbCuQtoWgDCcx6ApgdCLbbgN0hPfvwL5q8HbhNUjfv4HwIFJ+CZoZ9ZBEIbIVGd0KsaOgV4PsBCSy8wvABe9foSLS3wIxSLWG4PPIwM8HijU5H0C4v8SQZbTOQ0okYbMf4bXI6E6QHYATLOMQtpuRtrkIkcTAFZmObH8MjGaE9x+QlvEQ2YwMvwPxU0AUlGyEbQnSfjOoowY4OkYal/WWm11eSEFWMk67lSSXHX8oyoMrpuMYplCe3W5hzNgctm87xeZNJ1h5y5RBXyRSSioqGjh+rAG3y8a48XmX083LglWxY1cHpn4nWdNQUAjEfcSM6ABDJt2Wc9HYriF1OqItSGTCY9X/+JqwkGwxb9aWiFmQVRUaWfYCLIqFY117KHCWYlMdBON+Kn2H0BQLmba8QbNShFDMPg3Dk1cfqmJ/5xZqg6foiLagyzgCQdSIXGDd987ReUNNFSqq0NCExTQKEt+boZs/7ZWvEAKbzYLtIl6b4R7HYlH7pca2NXUTCkbwd4WIRS/fS2KWONKwXgUpUtWUfmT1y0E4GGXT24fILUpjwgiH6+yaRprHSWOXjzZfgKykiy+0WnwBGjt9ZHhc2Ec4q05KSUPAx68P72bDuTM0BfzEDJ1YIkSrKQpZTjffmLmEO0rGA9AeCfH5da/TEgoQjseQwJenzecvps4bUGezPtDNl9avoc7fTUvIFDb96YFt/PRAL+F4dnY+/7n0jn58Jk1ROdXVxi8P72RXYx1toSAui5WJaZl8fvIcFuf1kuSfO76fp4/s4Zuzl/LI+P6FhSs6W/jih6sZlZTKL5bdicdqGvBCQEiP8+yxfbxceYSq7g40oTAlI4dPjJ/GisLSQYsAXzNIidTPIH3/ApGtgG6SmoUddD/o9RDbjwy+iEj6ITgGMUpkBMLvIP0/Bb0OUEB4zGNFziIjm8A6B+H5G7BM5LJcsMOCAUa7eT4ZvchYI2B0gKKbbXu+D5l9jO5MfGHr7aPwmnPRF0JjSKK3mguWqSB9YARMY5IYyCDDWX5IGYLAU8jQ7xJj0kC4TUNOP40Mvw+O28H1BEIrZMBcym7Qa5HxSgivgdAac36EG4iA3oCM7Yfw+4ikfwJL+SX7dDW4rKeGEILc9F6hPY/ThtWiDjvzw+G0snDRWA4dPMtzz26hqyvEihsnEk3UxNLjBsFglIqKBp781XoaGztZtqycUVeQLjhc9H3594UZxhIYGIO6wi/lWZFIdOIXbaugIgA94WVShMJ47wxOdh9gb8dG6sPVJFnS6Iy10hw+R7l35qD8puH2CaAlco4/1v6czlgrE5PmsCTjDtyWJFRU9nVsZmvr2wP2udBAvH5ykP50UDA6g2/8x0NYrBqpwyjae72ho83PWy/uYPld00fccEpy2hmfm8HG41X8btsBPrt0Ni7bQFFWKSX+SJTnt+7HH4kwv6yQpBHmN0ngx/u3svrMce4rm8RdJeUY0uD3Jw/x6qmj3FRYyl9MnU+eu/c3TLU7eHLF3UT0OBvqqvjhvqFFe9PtTr4+awmGlLxddZLnTxzgc5Nms6ygNxXbmyCL90UoHuNH+7aQanfyuUmzcFtsbD5XzbraU/zHvi3kuDyMSblyuQ5DSrbU13CktYmVxWMo8iZzqqON3504yP/bsY50h5NZWZefMXulkOjI4HMQ2QJKBsL9RdDGm94mGQP9HDK6GWInwDpQskZKAyIbkL4fgtEK1nkI58dBzQMMiB5EBp+H6E7T2+P9e4Ra8pGEiYYN4UG4Hwf5mPk5uss0JGUc4flLsEweZJ8hSuHYFiKsU00DTsaQ7Y+AMZB/ORikjCNDL0LwaZBxsN+OcNwLSpJp9EW2IEN/hNAapIyB99sIkTzIXBrmMQwf2Jabx1DTzP5E3oPACxA/jgw8BUn/hLjQMBxBXPVy65evbuVTt83B67p0J4VQWLR4HHW17bz6ym6efmoDLzy3FUdCB2fjxuPs3HGKlhYfUkrGl+fyZ5+5YdiiVFeCmBE1w1+J0MV5BOM+MytNsaNdQfhJEQpuzTQyfbHOAdslBiHd3yMFcB5eLYWFGas4FzqDJiwY6OTYi5ifvpIJ3llol6zdNjSklOxsX0dLpIElmXewLPNu83jC3Ob07R90v+voUfAnC4tVo3gQSY7/DZBS0nyug5pTA7NnRwLJTju3Tytnf3U9z23dT01bF7dNG0d2kgdHwqMUisVp6Oxmzb7jbK6oJsPj5q6ZE/A6RrbGZlPQz7s1lUzNyOWLU+aSnfD65LuTONzayIGWBkYnpWLXep8pFkVlXKq5ODzrG/isOA8hBA7NwtzsAgwkR9vM+SxJSmFudsGQ+wEEYlHGpaTz1I33kGxzIIA7S8bz9c3v8m5NJXubzlGWfPkp3/0gJd+cfQOL8ooRmMZUaXIa39z6Pv95YAfP3HTvRcWRRxY6RDYDBjgfBccDffgvEiknI+w3m+0uDFlJCUYLMvBrMJrAtgzh/S4oiaoYUiK1iQjrVGTnVyC6C4IvID3fuK4Ktwuh9iNwS/0spkdJgJqD0EYNue/AY9lAmGOTUpoG6HAgJcQOQvB3psHqfBTh/nMQrt65tExFWCYhu74C4TfBOgPpeGjw947eAI6HEd6vA/YevpOwjEFKHYK/hdghiJ2Ea6iBeEmLoKM7SDgaJzvNQ0NbN/5QH5ehlFQ3tvcUBr0UhACn08oDD87F47Xz1poDnDvXTjhR2b2j3XQ9W60ay1ZM4O57ZpFxjVfXcRmjJVrPWKb1hp2kpD5cgy51ki0ZWJXLt1wVVDJt+dgUB9XBk8yVN/Z7KEX0MPXhGoRQyHf2rhZ98Q42Nr9Bpi2Ph4q+hFP1jNgqzUCnK9qGRbGQZctHUyw9Y44Y4Z6Q4bXD1Y1D1w1OH6vnwPZTtDZ2YbVbKB2fy+xl43E4ez0Mvs4gv/v5h4Dkgc8vJblP+qmUkh3rjrFrwwmmzCth0crJqKrCu3/cRVdHgJvvm0V7cze7Np6gvdlHaoaHmYvHMnpcDsoFYWUpJZFwjCN7qjmy+wwBfwRvspMpc0sYN7UQi6U/b6ituZvXfrOFSbNGM3vJWM6cqGfvlkpam7pwue0Uj81m4U0TURME8mgkxrsv7abqRO/vkleczi0PzMF1QQbQ4d1V7NtSwW0fn8ehXWc4daSOyXNKmDa/lNrTLWx+9zBWm8aSW6eQW9T7gpRSEglFObSriqN7qggGoySluJg2v5Qxk/LR+ozh7Klm3n9lN3NXlFNcls3ezRWcPFxLPKqTnZ/K7KXjyCs2vRZCCMLBKDvXH+dcdSuHdp0hEoqx4c0D/caTU5jGyvtn472K8i5CCBaOKeKRBdP45bqdrD1SyZaKajI98FooDgAAIABJREFULpw2KyAJRGI0d/sJx+K4bFY+u3QWs0aPvAekNRRANwwynS5cFkvP8e2aRpbLw9nGOqKGjv0K16x9ib9DbhsCD4yZ3E+2wKFZmJWdz5tVJ2gJBdClRLuK+Sj2pjC9j/aUKgQzs/IoS0njSFsTLaEA2a6PUik7cb/q56CHGZpIbhBg8nIGqbEHEDtm/kFDOB9GqH2iHiLx1LRMMDk1gV8iw+8iXE+AOpwyUX86kOjI6C7zN1ByEI67EH2rSyQiPtK2AKxzILIOGXoF4bgPGESgU7gRrk8gRK9H1bzanKbBFXrN9EgZLdd0XJe8ezcfPMPRqka+8ehyfv36dmoaO/qIg0lqm4ZeIQ0Fl9vGPffOYvnyCZw61UTFyQa6ukNYLRrZOclMnJRPTk4ydrtlxB9sg2F323rGeaaRbM1AIGiJ1HOwcxt21UmJe8IVEZ6FEBQ6SylyjeG07zCHu3YwxjMFTViIySjHuvdQ4TvIaFc5eY5eyz+kB+iOdSCEoD5Ug9eSgkgQXy3CikvzoIlL14YbDAoqLs1D3IjRFm0kZkTRhEbUiHLSt5/j3XsYSf+SqiRTkPrviRIyoF2kJM2lEAlHef03W1n9/LYesrVhGKx9ZQ/rVu/n01+9haKyLJOo7bTi8th46clNGIbkM19bhcWqIaWkuqKRp37wDpqmcNO9M3uu5YM7T1N55BzhYJSta48Sj+kYukEoGGH189v59
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment