alpha-vantage-API.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://www.alphavantage.co/query?function=TIME_SERIES_INTRADAY_EXTENDED&symbol=IBM&interval=15min&slice=year1month1&apikey=demo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Alpha Vantage API \n",
    "This notebook presents a simplified model for utilizing the alpha vantage API."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "api_key = \"\" #you just have to put here your API key "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import requests\n",
    "import json\n",
    "import io"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "def getMarketdata(marketSymbol,interval,slice1=\"year1month1\") :\n",
    "    url_base = \"https://www.alphavantage.co/query?function=TIME_SERIES_INTRADAY_EXTENDED&\"\n",
    "    url = url_base+\"symbol=\"+marketSymbol+\"&interval=\"+interval+\"&slice=\"+slice1+\"&apikey=\"+api_key\n",
    "    r=requests.get(url,timeout=10)\n",
    "    s=r.content\n",
    "    c=pd.read_csv(io.StringIO(s.decode('utf-8')))\n",
    "    c = c.iloc[::-1].set_index('time')\n",
    "    return c "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "marketSymbol=\"ibm\"\n",
    "interval=\"1min\"\n",
    "month1 = getMarketdata(marketSymbol,interval,slice1=\"year1month1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "month2 = getMarketdata(marketSymbol,interval,slice1=\"year1month2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "month3=getMarketdata(marketSymbol,interval,slice1=\"year1month3\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "month4 = getMarketdata(marketSymbol,interval,slice1=\"year1month4\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "month5 = getMarketdata(marketSymbol,interval,slice1=\"year1month5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.concat([month5,month4,month3,month2,month1]).drop_duplicates()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "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>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-10-10 08:01:00</th>\n",
       "      <td>116.154878</td>\n",
       "      <td>116.154878</td>\n",
       "      <td>116.154878</td>\n",
       "      <td>116.154878</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-10 08:06:00</th>\n",
       "      <td>116.146874</td>\n",
       "      <td>116.154878</td>\n",
       "      <td>116.146874</td>\n",
       "      <td>116.154878</td>\n",
       "      <td>448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-10 08:13:00</th>\n",
       "      <td>115.666832</td>\n",
       "      <td>115.666832</td>\n",
       "      <td>115.666832</td>\n",
       "      <td>115.666832</td>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-10 08:30:00</th>\n",
       "      <td>116.154780</td>\n",
       "      <td>116.154878</td>\n",
       "      <td>116.154780</td>\n",
       "      <td>116.154878</td>\n",
       "      <td>2152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-10 08:33:00</th>\n",
       "      <td>115.970397</td>\n",
       "      <td>115.970397</td>\n",
       "      <td>115.970397</td>\n",
       "      <td>115.970397</td>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08 16:43:00</th>\n",
       "      <td>128.250000</td>\n",
       "      <td>128.250000</td>\n",
       "      <td>128.250000</td>\n",
       "      <td>128.250000</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08 17:21:00</th>\n",
       "      <td>128.050000</td>\n",
       "      <td>128.050000</td>\n",
       "      <td>128.050000</td>\n",
       "      <td>128.050000</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08 17:23:00</th>\n",
       "      <td>128.240000</td>\n",
       "      <td>128.240000</td>\n",
       "      <td>128.240000</td>\n",
       "      <td>128.240000</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08 17:39:00</th>\n",
       "      <td>128.050000</td>\n",
       "      <td>128.050000</td>\n",
       "      <td>128.050000</td>\n",
       "      <td>128.050000</td>\n",
       "      <td>765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-08 18:35:00</th>\n",
       "      <td>128.090000</td>\n",
       "      <td>128.090000</td>\n",
       "      <td>128.090000</td>\n",
       "      <td>128.090000</td>\n",
       "      <td>219</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>43137 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           open        high         low       close  volume\n",
       "date                                                                       \n",
       "2022-10-10 08:01:00  116.154878  116.154878  116.154878  116.154878     140\n",
       "2022-10-10 08:06:00  116.146874  116.154878  116.146874  116.154878     448\n",
       "2022-10-10 08:13:00  115.666832  115.666832  115.666832  115.666832     150\n",
       "2022-10-10 08:30:00  116.154780  116.154878  116.154780  116.154878    2152\n",
       "2022-10-10 08:33:00  115.970397  115.970397  115.970397  115.970397     150\n",
       "...                         ...         ...         ...         ...     ...\n",
       "2023-03-08 16:43:00  128.250000  128.250000  128.250000  128.250000     100\n",
       "2023-03-08 17:21:00  128.050000  128.050000  128.050000  128.050000     100\n",
       "2023-03-08 17:23:00  128.240000  128.240000  128.240000  128.240000    1000\n",
       "2023-03-08 17:39:00  128.050000  128.050000  128.050000  128.050000     765\n",
       "2023-03-08 18:35:00  128.090000  128.090000  128.090000  128.090000     219\n",
       "\n",
       "[43137 rows x 5 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "df.index = df.index.rename('date')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date'>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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+vIDO/9bcHc7lNhHsy+DKNfngf6v2R2UOrp74wbjZt1mpsV5tQpOdcLZLRolUk5Xxj18NlCQ1S43MTf8Vu49p3lbj7IdAMkYk8yCSZx8O11JlknRytxbO5SmrDziXPYMghwvL9Ov/LPY6f6S+R64cfWUym0QvKAMAAAAA9Q2BEQAAYMqs4Xpxec0N5m253uW1PPtbxDKLR2eR1XuPq6zSqmnrD+lLl9JKkdIyzbiEU0qicV+N2vZmuezEjm7rV5zcyW3dkWHSszp40DTZvTG7p+25hfrfqv2GmRRG7v96ja7490JZbe7jPcu1tU6vKRFmqz63xU9g5PKTOvncL0mTBrRza24vSTM35UqSCssqtc4lK6rCWnVdRw+SX7+1WHO2HPY6Z6cWqX6vG2oJ1f+fPL+PAAAAAABzBEYAAICpoZ2a+9y/52ixxj0zy2t7qceT+fXJeS/P06szt+nGd5fqjk9Xad/xkohe/4rhVTf1PTM4zNQ2MPLUrwZqxxPnONc9y1M5Yg+OgIyv/hySdMYzs3TbRyv049qqLCO73a6CUvNm5+8v3K0F249oqUfptXu/XOO2nlNQ5ly2BVhKq3/7TN8DJN02rqr01MAO7mO73DtF/R+a6rat0mbTX75ao25/+V67jxRr/QH3UnIOZsGrcHIEsBzBGwAAAACAfwRGAACAKX9PoZ/2j18Mt1fWo6fXjeIKz0/f4lx+7Lv1EZxNTVCpc5Z39oFRuaQkk8DIygfPlOS794TFYtHE/m3VrVWaTurSwm2fo/l6E2dgJLBg11++qgps3PjuMg14+Cet3HPc5/jdR4t97pek8sqqoIw9wFJaknRGn9Y+9/dumy5JevHyIX7PVVhWqQ8X7ZYkTX55rt/xkZQY78gY8R24AgAAAADUIDACAABMVfi42epZ8shVdrOafiH/nb9TS3ceVXF5ZUjnFirxfrqM/7DWu89KOJVWVgUgUhK8sw/ySrwzMP4wtrvheZqlJmnnk5N0+/hePq/36tXDNOOO072yHRyZCI7thWWV+mblPv32v0u0NafAbWxOQU2j+GPFVXOcvuGQJOOG567Bkrs/X+1zfpLU6/4f1OXeKdpwsCpTw1/GiCQ9cl4//4NU1Yj+wxtP9jlm+voc57LR/4Nocvx/qk/BSAAAAACINt/FogEAQKP2wcJdpvvGP+tdQsvhnz9t1gVD2qv3/T+6bZ951xh1yUoL2fxCYfeRIr9j7Ha7374WoeLoz9IkyX9ZpoX3jVPbzLo3rXd8bS1c+ptYPDJGJOn/Pl4pSZq+IUc7n5zk3L7vWE25sX7ZGV7n33e8RO2bNXGuP/LtulrN8x8/bnKbmy8dW6Rq3r1n6JQnf/ba9/xlg93Wm6ca93VxCCSo16F5E79jwiGhOrBXSSktAAAAAAgYGSMAAMBQTn6ppm/I8T/QQG5BmVdQRJLG/HNmHWcVep8v899gvbAsctku3VtVNTs/VlTuc9zb158UkqCIqzYZKXrpiiF6+7qTnNuSE43fLs7ZUtWo/Me1B/Xyz1ud29ftz9f09YfcxnoGJ1bsPm54TkfJLH9y8kv9D5LcgjGuPPuKdPUTrCsqMy4jtuz+8TqtZ5YkaertowOaU6iRMQIAAAAAwSMwAgAADOUWlvkf1ACc3ruV3zFztxyOwEyqOPq6OAIkrtJTapJ9x/b23UOjtiYPytZYl/4cyQnGbxeveWuxjhWV6/fvL9OMje4BtN++uzSoa36xbK/yiitUFGAAan9eYIERM908vrcpifHq1so8OPLc9M2G21s2TdZ7N5ysnU9OUlpydBKxE+gxAgAAAABBIzACAAAMlZQH1mw7WN+u2h+W89bWqO5Zfsd8uHh3BGZSxfHkf5xBI427z+otSbp6RKeIzcdX2aotPvrMBOPOz1bpd+8t1bsLakq3rX54QkjOHaif7xwT0euFSgIZIwAAAAAQNAIjAADAUHGYAiO3frQiLOetLZvd/w3lORHKGLHb7Vq7L09SzQ1vV9eM6Kzpd4zWI+f1j8h8/Ln1o+UBjy0ur5S9+ns9uGMzr/2Ldhx1y8zISEms8/yCdd6g7IDGNUmM17a/nxPm2QTGUX7s86X+S8IBAAAAAKoQGAEAAIaW7Dzqd8x1o7poTS2e7K+0xk7ZH5vLk/ZtMpINx1wwOLAb5nU1fUOOjlT3Fok3CIxYLBb1aJ1uuC+c3rr2RMPth/IDL7fW98GpuuS1BbLZ7GqeGrmgh9ncjbx4xRC3pvJmfrlrTMT/H5hxZNkURLAPDgAAAADUdwRGAACAoZdcGmqbefi8fkqvxZP9N38QeKZBuPVum+Fc/uymUYZjsk2aeIfa1yv2OZdj5ca7JI07oU1IzrN01zFNfGGOSirqlo3kqx+Ip1N61JRK++LmUVr1UN1LdLVKNw6gRUNZgA3rAQAAAAA1CIwAAAC/WrvcCL5ieCf1y87Q578fGfDxX9w8Sq73+aetPxTK6dXJyO4t9eIVQ/T9baepU8tUTfvTaC29f7zm/HmsWqYlSZJ2HSmO+LxiKTBSW3P+PNZr26ZDBSqt8H0z/6Ih7SVJp/bw3//Fn5TEeM28a4zm3jNWwzo3V2YT/4G8tKR4w+2TBrbTpsfObhD/bwA0LvmlFdoaor5QAAAADQGBEQAA4Nfgjs30wuWD9athHfTIef005bbTdGKXFgEfP6xzcyXEx+7bjvMGZatvdlXmSM826cpqmqyOLVJ1zcjOkqQpaw6oy71TDI99dtpmdbl3iuZvDW0fEqMeI/WNUQN5Sdp8qMDncV9WZ868d8NwvX/DyZp7j0eAJcg+412y0tSheWrA4yf0a2u4/fnLBis5wThoEi3JCbH7ewUgdgx/fLrGPztL6/fnR3sqAAAAMYFPUgAAwFC/7JoSU38Y20PnD26vf14ySEl+bsT+ePtpkqQz+7ZRSmKc/nZ+P0nSr4Z1cBs35G8/hXjGobfpoPsN/OJy9z4O5ZU2vThjiyTpyjcX1f2CLnGEH9cerPv5QmjuPWP1wuWDNf2O0QEfk5poHEQoLg+slJbFYtGpPbPU3qOU2V1n9Q54DrVhFGy4+6zeSozB4F6qSXYLADj8uPaAM1PvkyW7ozwbAACA2JAQ7QkAAIDYNP6ENlq3P19n9GmtwR2bBXxcn7YZzgbWFVab82byA5P66sNFNTdkjhVXOJd/e2rX0Ew6xDzLLi3ZeUyn92rlXL/toxUhvZ5rI/hOLQLPcIiEDs1T1aF5qsqD6GnRvLoUWbA++d0It3WLxaL1fztLFVa7yiqsap2RUqvzBmrnkSKvbRcNbR/Wa9ZWpS3I9BkAjc7v36/p6/XfBbv0yPn9ozgbAACA2BD0Y2+zZ8/W5MmTlZ2dLYvFoq+//tp07E033SSLxaLnn3/ebfuYMWNksVjc/l1++eXBTgUAAIRRQWlVdkS7zNrfhHZ9wr5JUrzWPGzc+NpfFkq0XD2is9v6/uMlbus/rgttVofrTe6uQTQYj6Rg/1/1aZse9DVO7tbSa1tqUoIymySGPSgiSZef1MlrW0aK/94k0XDlcO+5AgAAAAB8C/ouRFFRkQYNGqSXX37Z57ivv/5aixYtUnZ2tuH+G2+8UQcOHHD+e/3114OdCgAACKP/zNshSfpgUejKbqSb3FzeeNB3z4locW06L0n3fbkmrNdzzRhJisGyTQ53Tejld8xfzukjSfrvb4aHezohd8GQ9rpwSHtlNa36/981K01pybGZaH3dKV2iPQUAAAAAqHeC/oQ3ceJETZw40eeYffv26ZZbbtHUqVM1adIkwzGpqalq29a4sSUAAGi4djxxjgY+8pMzI0WSspuFPwugNlpnpOi1q4e6lSFxqLB6l5TamlOgHq2Dz5BwcM0Y6d8+s9bnCbdfj+qif/602eeY343uLklqk5GibX8/R3klFRr66LRITC8knrtscLSnEJAUl2bwVptd8SYN7wE0TocLy6I9BQAAgJgU8kcRbTabrrnmGt19993q16+f6bgPPvhAWVlZ6tevn+666y4VFJg/KVpWVqb8/Hy3fwAAIHy25xY6l28Z2yOk57ZYLOrY3L1/xjn924X0GqF0dv92Gl3dV2TSwJp53vP5aq+xX6/Y7/d8W3MKtWTnUcN9szbnOpezPRqOxxLXslKB9J+Jj7OoRS37jcC3RJfSZkbBOgCNm9FrFQAAAMIQGHnqqaeUkJCg2267zXTMVVddpY8++kgzZ87UAw88oC+++EIXXXSR6fgnnnhCmZmZzn8dO3YM9bQBAICLwrKabI7thwt9jKziCBh8cfPIgM6//oD7Qw5xMf6U+5kntJYkVbrceP5yxT6vcYE0wh7/7Cxd8toC7fPoV1LfnNYzS5L0z0sGObc1S60KmFjq8L9zSKdmdZlWo+Nacq2cwAgAD6v35XltKy6vNBgJAADQuIS0WPKyZcv0wgsvaPny5bL4+ER84403Opf79++vnj176sQTT9Ty5cs1dOhQr/H33Xef7rjjDud6fn4+wREAAMJk9d7j+tcv25zri3cc83vMy1cM0T8uHljrPgxNY7R/g0NGk6ob/lPXHfI5rlOLVJ/7V+057lzedaRI7WM4K8Sfd38zXCUVViW7lHL67KaRenXmNv3m1K6Gx0z702id+dxsTRrQTgM7ZOqJHzY69317y6n6Yvle3T6+Z9jn3pAkxte8566oJDACwJ3NIGBfWFqp1KTYft0FAAAIt5C+G5ozZ45ycnLUqVMn5zar1ao777xTzz//vHbu3Gl43NChQ5WYmKgtW7YYBkaSk5OVnJxscCQAAAi1816e57YeyNP/FoulTs2p+2Vn1PrYSNiaU5M1k19aoQSTDBfP7VsOFeiNOdt16xk91bFFqq59e7FzX3xd0ipigMVicd5Ym3X3GFXa7Oreqqme9dGbo2ebdO18sqb/nGtgZECHTA3oELt9VWKVxWJRYrxFFVa7Kqz+M5YAxD6bza5jxeV6bvpmjevTRmP7tK71ucgkAwAAMBbSUlrXXHONVq9erZUrVzr/ZWdn6+6779bUqVNNj1u3bp0qKirUrl3s1hcHAKCxSk2K9z8oSH895wS3dV+ZprFgWOfmzuVfvTrfrXG8qzKPG1BnPjdbny7dq3NenCNJOl5c4dy36ZB5f7X6pnPLNHVv1TTa02i0EqvLaZWTMQLUe9tzC9XtL99r2GPT9f7C3br+nSV1Op/R61VFAGUfAQAAGrqgH+0sLCzU1q1bnes7duzQypUr1aJFC3Xq1EktW7Z0G5+YmKi2bduqd+/ekqRt27bpgw8+0DnnnKOsrCytX79ed955p4YMGaJTTjmljl8OAACoC6Mbq89eOjjk12mTmRLyc4bT6J6tnMubDxWaZtGY3ZguKK3UofxSt20PfrNOvx7ZJVRTRCPmyD6y2rnZCdR3ZzwzK+zXKKuw+txfWmHVB4t2a1yf1uqSlRb2+QAAAERD0BkjS5cu1ZAhQzRkyBBJ0h133KEhQ4bowQcfDOj4pKQkzZgxQ2eddZZ69+6t2267TRMmTND06dMVHx/6J1IBAEDgNh30zmJwzZYIFdeG0fWBZ3N4i4wjI2WV5jeb8koqTPcBdeH4+bTyFDjQINlDHPQs85Nd9sKMLXr0u/Ua88+ZIb0uAABALAk6Y2TMmDFBvTHz7CvSsWNHzZoV/qdgAABA8N6ZvzMi1zm9Vyv/g2LYb99d6rYeZ5Fsdt+ljO79YnW4p4VGKr46MGIjYwSo1zYcyDfcXlphU5MQlLXMapqkw4XlfsvuLd5xtM7XAgAAiHX163FNAAAQVoM7NXNf79jMcFxdNUmK1zvXnxSWc4fLi1cMcS6v2nPcbd/kQdmSpM+W7nXbHu+SabJ8t/sxRoZUf///OLZ77SaJRinOQsYI0BBMfGGO4faCstBkHB4uLJckfbd6v89xsd31CwAAIDQIjAAAAKcHvl7rtt43OyNs1xrTu7W+u/VULbt/fNiuEUqTB7Yz3ffNyqqbTPuOl2jCczWZsYnx/m8vbTyYrwe+XqucglK1zajqveL4b2MxvEuLaE+hXnNUpiMwAtQ/drtdturf3eFdjf8W5haUhfSab8zZ4XO/WR8tAACAhoTACAAAMJUYF967I/3bZ6pl0+SwXiNULBaL2gXQNH7zoUJ1uXeKFm4/otIK3+VKbDa7zn5+jt5buEt//Wqtflh70HGxUEw55l03qosk6Z6JvaM7kXruUH7VTdNzX5qrXUeKojwbAMG45aMVOv2fv6ik3KqNJqW0XpyxJaJzMuujBQAA0JAQGAEAAKbmbDkc7SnElAX3jTPc/sLlg722Xf7vhX7Pd81/FjmXp60/5Fzeebhx3Nx++Lx+WvfIWRrWmYyRUDn96ZnRngKAIExZfUB7jpbo5405yi+tNBxzvDg0pbQczDJTnIiLAACARoDACAAAEZZXXKG35+0IeWmMcNjeSG7Q10Xnlqka1rl5rY6dt/WI4fa35vouc9KQpCUnRHsKABB1vhIFF+04Kru9bqXyTu2RpQfO7StJCnMyKAAAQL1AYAQAgBD7ad1BTXxhjjYdLDDcf9fnq/TIt+t13duLIzwzhEK2Rzmt4V1aKCvE5cCGVjdhB2qjPgRdAUjHisqdy3/4YLnPsUt3HQv6/F8s2+tcnjigrTMbceH2oz6PI24CAAAaAwIjAACE2O/eW6YNB/J11vOztfdYsdd+R8mkdfuNa4lHy5ZDxoEcuNufV+q2bpeUkhjv85hFfxmnHU+cE/A13rr2pNpMDZAkTd9wyP8gAFE35NFphtu7ZaV5bXt++uagz3/nZ6ucy11bpum9hbsCOq6RtLkCAACNHIERAADC6NSnfqlz+Ytw2XSwQFe9uVDLdlU9Obr5UKHXmNbp9aMxeiS9c7170MJW/f93+h2nq5XJ96tNRoosQdxpap6WVPsJotHbYvC7DKD+OLNfG69tZqUXPVltdtlsBu87LNKbvz6xrlMDAABoMCjqDABAmM3Zclije7WK9jS83Pz+Mm0/XKR5Wxfoi5tHatEO95sugzpk6omLBkZpdrFrTO/W6tYqTdtzq0qSOG5A9WjdVEv+Ol6zN+equNyqskqrZm3O1W1n9Azq/KO6twz5nNG4tEhLjPYUANTBrWf0VFFZpX5ce1CHC8v9H1Bt//ESjXryZ0ny6n1VabXrhOwMSVJSQpy25hSqRVqSWhgE4i0U0wIAAI0AgREAAMLs1/9ZrO1/P0dxMdbt9GB+TUmoi19d4LX/m1tOjeR06pXPbhqpkU/8rHKrTb89rZvbPtcg2PmD2wd97lvG9qjz/NC4FZRVRnsKAOqgaXKCHrtggG4Z21MjnpgR8HFfrdjnXF7m0ZOkrNKmJtVlH8srbRr/7CxJ0s4nJ4VgxgAAAPUPpbQAAIiAw0Wx1ww5KcH8bcBTFw+I4Ezqn5ZNk7XpsbO1+uEJ6t8+M6TnHtUjK6TnQ8Pn2Y/g9VnbozQTAKHUNjPFbf3Bb9bqP3N3mI53bebuqdJqU2qSdz8sq0HZLXqMAACAxoDACAAAEVBWYYv2FLwcL64w3XfZSZ0iOJP6yWKxKCMluJJFN53eTYM6mAdS2jdrUtdpoRF6+cqh0Z4CgBDZ8cQ5buuOLA9JenfBLv3tu/WmxybEm3+8L7falGzwQMTxYu9gCoERAADQGFBKCwCACCipsEqS9hwtjvJMqkxddzDaU2iU7pt4giSpwmpTz7/+IEm68uROemBSXy3ccUQndWkRzemhnurVpmm0pwCgFtpkJOtQfk1G6QWDs2XxiEq8d8Nw/eo173KXDgWlFbr+7SU6u39bw8CHQ6XV7nVuSfph7UFdPaKznp22WcVllbr/3L70GAEAAI0CgREAAELIbvcuSSFJxeVVgZE/fbIygrMxZrfbddN7y0z3v3jFkAjOpnFKjI/TnD+P1YG8Ug3vWhUMGdu7dZRnhfrK11PiAGLPhgP5+nL5Xud7A4d7q4Pnrnq1Tfd5rvcX7tbSXce0dNcx/eaUrqbjKm3Gmav3f71WvxrWQS/O2CKpqk8WGSMAAKAxIDACAEAIVRrU6pakjxbt1pq9x7XveEmEZ+Rt/rYjPvd3bpEaoZk0bh1bpKoj32sAaHQmvjDHcHtasncPkJQE722uSsorncv/mWfefySziXnpxz4P/Ohc/vV/FqtlWpLPawIAADQEBEYAAAihskr3JzK7tUrT9twifbJ0jz5ZGqVJebjqzUU+96ck+r4JAyD2PHXxAE1Zc1CzN+dGeyoAasno9Tcx3nf6hlF5rJZpSRrRraV+c2pX7T1WrOW7jmlC37YBz+OIjybuAAAADQV59wAAhFBphXtZjKy05CjNxFheiXfD9Td+faK6tUpzrh8zaMQKILZddlInPXJeP0lSegrPPgFGvlqxV58u2RPScx7KL9Xfvl2vnYeLDPeXlFu1dl+eaalNVwlx3kEOo8CHwydLduuDRbu8tr905RC9ctVQDevcXOcPbq9Hzu+vOINzAwAANGYERgAACKF1+/Ody+/+ZnjM1ek+mFfqte3Mvm306Pn9nes0AAfqJ8eT5RVW414CQGNVVmnVhOdm6U+frNKfv1itH9YcCNm5Rz4xQ/+Zt0PnvGhcHuv/Pl6hc1+aqx/XHvR7Ll9BEE9llVbd88UaHS70fphhZLeWpsddMDg74GsAAAA0ZARGAAAIoeembXYuj+7VSttyjZ8gjZZdR9zns+XxiZKkYZ2ba0D7TF0xvJPieaoUqJeSqpuwV1j9P5kONCZvzd2hzYcKnes3f7A8ZOd2tBbzbKTu8NP6Q5KkWz9aYXqOV64cqm1/P8d0//2T3Juy2+12lZYbB0B3PHGOzwDLI+f3142nddV3t55qOgYAAKAxIDACAEAIbcspdFs/XFgWpZkY2+FS6uPlK4cosfpGakpivL699VQ9cdGAaE0NQB05fp+tNrusNoIjgMPWQ4X+B4WZr/5dZ/dv6/OhhN+e1s1t/WhRue74dKXXuL7tMvxmnWQ2SdRfJ/VV//aZuuzEjr4nDQAA0IARGAEAIIQKyiqjPQWfCl3md07/dlGcCYBQS3Bp0kw5LaBGWQz8PvRs09R0XyCZmr8e2dm5POyx6ZqxMcdrzJTbgssC+d3pVQGXXw3rENRxAAAADQGBEQAA6mj/8RLd+O5STV3nXT88OSG2Xmpf+nmrc5lGrEDD4sgYkaTSCuOyPkBj1Do92WvbtPWHVBnmgInNJXMr3iSTo2dr84CJq7vP6u1z/2e/HxlUjxJJ6t6qqdb/7Sw9/auBOq1nVlDHAgAA1HexdbcGAIB66J4vVmva+kO66b1lzm3jT2gjSXr0gv5mh0mSutw7Re8t2Bn2mzMAGr4kl8DI67O3R3EmQGxJT0n02nbju0t17ktzw3rdDQfznctLdx0zHLMlJ7AyX3F+gh4ndWkR+MRcpCYlyGKx6K1rT9K3t9B3BAAANB4ERgAAqKO9x0q8thWWVUiSLj2xoxb/ZZzP4x/4Zp16/PWHsMzNTJ+26RG9HoDwc80Cm705N4ozAWLH0aJyvThji+G+jQcLwnrtDQdCd35fgZGF9/l+nxGIpIQ4DeiQqeG1DLAAAADUNwRGAACoI7vdu8nxwu1HncutM1ICOs+uI0X+B9XRhL5VmSzXuNQqB9DwUEoLqHLms7Oidu27Plvltl5htRm+ZwiEr4SRtpmBvc8IxMXD2ofsXAAAALGMwAgAAHVkNbjJkdnEu2yHP/sMMk8CZXQTdOamHK3cc9xtW3l1yS7XkjsAGp7SCsrzAZJ0pKjc537XPiAhvW5hmde2nn/9QY98u75W5/NXSitUfjWsoy49saoZe1ZT794sAAAADQV3RQAAqCObwf3H164eFvR5kmrZqP2/83eqzwM/6tMle5zb9hwt1nVvL9EFr8xzG1vhCIzEWFN4AKFVVknGCBCICqMX8RA47+V5htvfmb+zVueLjzMOjLxy5dBanc/Xda48uSqrNJn3CgAAoAHjnQ4AAHVkM8gYOaGdew+P727139D0E5fARjAe+t86SdKfv1jt3LbvuHH2SUVl1VwT4ngLADRkPOkNBGb/8dKwnNfsdbi2TOIimjSwXUivI0mRyU0BAACILu6KAABQR0aBEc+MjP7tM/2e57Nle033bTlUoBdnbFFRWaW+X3NAXe6dol825ZiON2oIL9U8GZsQz20PoCFKT0mQJP1qWIcozwSIDRcNremZkZ6c4LV/zpbcSE6n1iwGpbQePb9fmK5V9d/a9kMBAACoD7zfGQIAgKBYPapw/PWcE5SaFNqX2DOfmy1J2nmkSF8u3ydJuv7tJdrxxDlu444VlWvIo9NMz1NprbrJkUhgBGiQumWladXePNPgKNDYOHpq3TWhl/4wpoe6/eV7t/1tM0LXuNxh08GCgMee2bdNra5x+/ieumZkl1odCwAAADJGAACoM8+MkVE9WhqOu2ZE5zpfyxEUcdiWW+i2fv4rxjXNHRw9RiilBTRMq/bmSap9HwOgoSmrrHrdS06IV5xBPao0gyySujrqp+G7q5vHdK/VNa4b1aVWxwXCUl1Mi3wRAADQkHFXBACAOvIMjKQkxhuOS0n0/7J7pLAsqGuPf3a22/ruo8U+x1tt1T1GyBgBADQC+SUVksxfg8srQ998/fXZ29zWrxje0XTswABKbRoxe68RCjWltMJ2CQAAgKgjMAIAQB0dL65wW+/eqqnhuJV7jvs9V1kYbtBINXXCK22OUlq8BQAaOvoDoLGz2+2asdG9H9fU20frd6O7qWVakiQpr6TC6NA6mbnJvW/JYxcMMC2ZlVDL1+NIvI7byRkBAAANGHdFAACIkCU7j/kdU+HZsER1v7m5fPcx9XngR723cJd2HC6SJCUYlBMB0LDM33Yk2lMAoqq0ouY19eMleyRJvdum6y/nnKAj1eWu/vbd+lqfv7i80m29rNLqNeZfVw1VfJxFb/z6RK++YHURH8bXcc+MkWNF5YZfGwAAQH1GYAQAgAi5+6zeXtuaetQ2NwqMOLI8auuif81XWaVND3y91rmNjBGgYRrcsZlzebtHDyKgsbnf5XXPLCMzmH4gnuZvdQ8+nvviXNk8XrPPGdDOuWyxWPTub4bX+nqR4tpj5FB+qYY8Ok3jnpkV3UkBAACEGHdFAACIkB6tvUtsFZa5P21aXukdBPEs1RUK4Wg2CyD67pzQy7m8vTpDDGisvli+17n8yHn9Aj4u0ExNz2DLlpxCfbZsj3N98qBsr2NG92oV8DyixTVj5Me1ByVJe4+VRHFG9d+mgwVaszcv2tMAAAAuCIwAAFAHwZS5SjRpeL7x0bOdywu3e5e+OeOZmUHPy5/sZikhPyeA6EtyyQb7fs0B+owA1U7pkeW27ugxIknHi2uyRl6asUXDHpuuXUeMA4u5BWW6/u3Fmr05V20zk732f7Nyv3P5T+N7+pyTJUarWtbMy65Xftkazak0CDabXWc9P1uTX54blp42AACgdgiMAABQB8E0SzfKBjlvULZSEuOd6561zvcfL1FBaaXnYV7um9gn4HlIUnJCvP9BAOqdQwVlNcv5ZQH1NgIaotP+8bPP/Se0y3Auf7q0JsvjmWmbdbSoXE/9uNHrmPX783XS49P1y6Zc/fo/i916mDi4lqrs1so7U7Q+sdulHJe/Kagdq0uA+nAh308AAGIFdTQAAKiD0gr3ZqSf/X6k6dh1+91LKMz581h1bJHq8/wX/Wt+QPP47WndlJoUr9V785ScGKcR3Vrqlg9XBHQsgIYjJcH9uacj3IRDI/Pl8r3amlOoPUd9l346mF/qXK6wej+48P2ag27rdrtd57w4x23bA9+sladZm3ODmW5Mcu0xAgAA0FARGAEAoA5cnxbd+eQkn2NdM0Mk+Q2KSO43bnyJj7PompFdnOtWm12ScWBkbO/Yr28OoHYSPEr2WWK1Vg8QJnd8uiqgcVtzCp3LrdK9S2JJVY3ZW1SX3Op63/de+7fnNsw+Pq5/Nrq0TNXOI8XRmwwAAECYUEoLAIAALdl5VHd/tsqtFvncrYcDPt61nnkgbDbvZzVPD7Bpa5yPe6Eju7cMah4A6o/Terr/jSAugsbE6HUzED9vyDHsx1NpDbxcpqeLhrT3OyZWfz0d87Lb7bp4aIeozgUAACBcCIwAABCgS15boM+W7dWj321wbvto8e6Ajz+jT2vTfa4Nkx03Yj5a4n3uSltgN2l8PSVeh/s8AGJcYnyc7jm7j8t6rN56BUJvyKPTanXcj+sO6qWfDZqMu/z6pCWZ9+ZqbZBxsnx3/e3v43gLYZcU5+tJCwAAgHqMwAgAAEGav60mS6RbVlrAx7XOSNFNp3cz3PfTn0Y7l4ur+5b89Svv2uX9sjOdy0vvH6/Tembpi5uN+5qY3csoq7Qa7wDQINhcnnwnEIrGYs/RYuWVVBju69bK+7V6+QNnuq0/O22zDuS59yVxTSIpKjd/7TR68OHNa0/0Nd06SfURpAmN6h4jHkk0JT6+BwAAAPUNgREAAALw07qaJqwH8kr149oDkqQTuzSXFHiZrIyURMPtnVvW9BvZ4aNm+f+N66lbxvbQ97edpqymyXrvhpM1rHMLw7FmFUUO04wZaNBauPw9Kq8kMoKGp7zSps+X7XULZJz2j19Mxz94bl+vbS3SkpSe4t5yc+QTP7utV1a/kPorqXX7+F5e29o3899HLFiL/zJOr1w5VKsfmhDyc7tyZozY7W7l+JbuOhrW6zYGBhXbAABAlBAYAQAgAL97b5nb+u/fXy6p5qbj8K7GwQlPRjXMJffSV0/9uNH0+LTkBN11Vm/1zc4I6HpG/nqO9w0iAA3HRUNrehuUW3nCGw3Pv2Zu1V2frfIKZJgZ09u4lGVBaaXP46zWqtfsD13KZj5yXj/9ePtpbuNaGDwckZLo/6O2r7KXRlpnpGjSwHZKiA/vx3hnjxFJuw7XNF4vqyDQCgAAGg4CIwAA1FJBaYXKqgMjSQmBvaQG8qTg0aJy/4PqoEnYS3AAiKbkhHhnaR8yRtAQPT99S0jOM7JbS5/7HX29HvxmnXPbtaO6qE9b94cTjHr5BBv0iEl26ZOle5yr5dTmq7OG8GMBAEBDQWAEAIBauvWjFc6bBEkBPr1pVt7K1VgfTdrr6oXLB4ft3ABih+NvEoERwFyin4carNUv2o9e0N9r3/AuVZmifdtlNIwgiAvH1+P5lqVZqnE5UAAAgPqIwAgAALU0c1Ou86ZjoBkjNh8pI2N6t5IkdWjepO6T87D97+do/d/O0vmD2/sfDKDec/xNKiMwggbOs2/WlNtODfjYYZ2a+9x/47tLtWZvnqzVD0FMGtjOue+Tm0Zozp/HBnW9+sJZSsvjPUtcAwsARQM9RgAAiB0ERgAAqIOgS2n52Ddny2FJ0l+/WitJmjwou05zcxUXZ1FqUoL/gQAahOTqv0mUvkFDs2SnewPwF6ZvUYXLz3n7ZoE/XHDT6d1078Q+pvt3HinW5JfnavvhIklSSkJNKUqLxaKOLVLrlC0Sq2EGsy+pgr8ntUIwBACA2ERgBACAOgg2Y6Sjj2wQq0edLUd2yQntat9oHUDjlJJYdQO3lGbJiLCScquenrpRu48U+x9cC5e8tsBt/b2Fu3T3Z6uc602TA38IICUxXr8/vbvfce8u2CVJ+t+qfQGdt3urtIDnEIssMi6ldby4QvO2HqZEXx2QdAMAQOzg0VEAAPxwLSWRGG9RhbVm/ePFuyVVNTsOxEVDO2jvsRKd3LWFz3FFZZWqrH4ys21GsjYcCHbWABqzlMSqYG1phTXKM0Fjc8KDP0qSXvllm3Y+OSki1/x65X7nckKAPb9c9W2XofUH8v2Oc3399+XLP5wS9BxiiePmvWemw60frXAuR+r/LQAAQLiQMQIAgB/HiyucyzPuGOO2r6i86qZjboF7jXMz8XEW/enMXhrVI8tr34tXDHEubz5UoKnrDkmSJvRrqxtO7arnLhsU7NQBNFI1GSMERhA5nj0pQs1mC+z8vdukB3Xeb245RW9ff1JtpuSUnZniXM5IaRjPH9p9FgBFbVBWCwCA2EFgBAAAP178eYtzuX3zJoZlswJ50tSf81x6iny3uiZFZMOBfD1wbl9dOKRDna8BoHEgMIJoWLff/bWwMsQ9KUorA/t5/vbWmobogQRJEuPjNLZ3a7/jfPX++uH/RkuSRnVvGXDfkVgtq2SWMYLaIcAEAEBsIjACAIAfq/Ycdy7Hx1n06lVDvcacZpABUhtZTZMlSW/N3eHcVlTGjU0AwaHHCKJhW26h2/rJf5+h/NIKk9HBKwvw5zkpIU4z7jxdVwzvqDevPTFk179pdDfTfZmpidr55CR9eOOIkF0v2ridH3qxGgwDAKAxIjACAIAfrdKT3dbP6OP9VOm09YdCcq2EOO9PzNnNUgxGAoA5eowgGv7v45Vu60eKynWbS1+Kuipx+Xn+zSldfY7t3qqpnrhooDq2SA3Z9fu3zwzZuWKZI+OlIsQZPyALBwCAWEJgBAAAPxy9Pk5olyFJhiUyrh7ZOSTXSoj3PndSLRrJujq9V6s6HQ+g/klJqMoYWbzzaJRngsZkUAfvwMHMTbk6UhhYHy5/bv5guXM5OdH9tfGCwdla8tfxIblOY+d4J8JNfAAA0JARGAEAIEAbfPQROTVEpbSMMkbqWnaBsg1A4xNX/S7/eHGFissrozsZNBrnDjTuwfGvmdtCcn7X0pZ/HNvDbd/zlw/xyvCMdRbF5gt0IO8b7ERNAsa3CgCA2ERgBAAAH8zKSHRs0cRtPSUxNC+p8YaBkdi8cQKgfsgvITCCyHj8+w2G28srQ1+SqWlyQsjPGWk9WjeN9hQMBRKwqbRxt782eEsHAEDsIDACAIAPBaXGNxT3HC1xW3eUramrhDjvl+aspkm1Old69U2j3m3T6zQnAPWP0d8SIFpKwtTrZvvfz9HDk/vqf7ecEpbzS9JVJ3eSJH0Uwqbq3992mi4c0l6vXzMsZOcMpUBu3tN/pHbIHgEAIHbU/8dsAAAIo5/WHXQuz7xrjOm4pimheUn1zBhJio/ThUM61Opc7//2ZM3enKubTu8eiqkBqEdc773ZGuiduGW7jurBb9bppSuGqFur2HzyHlXySypCer7zB1eV7IqLs+g6P03Y6+qioe31+IUDQnrOvtkZeu6ywSE9ZygFktRQYW2Yf1cAAEDjwaNkAAD4cO+Xa5zLXbLSDMe0b9ZEiXVskO6w3qOPyRvXnqikhNqde1DHZrp1XM9aHw+g/rLabC7LVTcw35yzXU9P3RitKYXcxa8u0Lr9+frtu0ujPRVIKvWRFVIWolJaA9pXNXd3BEYioVFmXwUQGTlWVB7+eQAAAIRRI3yXBwBAYA7mlQY07rpRXcI2B6Nm7ADgj+vT3I6SN49N2aBXftmmLYcKojWtsNieWxTtKUDS3mMlpvt8BU0CUV5pU05BqbNXSXKIyld6SjJ4yCE5RD3EGpoZG3OiPQWftuUW6khhWbSn4YUeIwAAxA7e5QEAYOKFGVsCGhfKD7ldPbJSaG4KoDbsLuWzPIO8OQWxd7MQ9d9Ul9KTv9w1Rp//fqRzva6vk+e9PFfDH5+hTdVBvXBlQs6483Q9dkF/3X1Wb+e23m0aX58uo+brfz3nBLf1FmmJkZpO0PYeK9a4Z2Zp2GPTQ3rerTkFGvfMTH2zcl+tz9FAKxsCAFAvERgBAMDER4t3m+7r1qomgGEJYWSkVxv3Ovmu5XAAIFCuMdUr31zkVvamuDw8jbDRuBWVVTqXu2al6cQuLZzrF9WyV5bDxoPuWU5GmR2h0LFFqq4e0Vl/HNtDP95+mhb9ZVxIX+PrC6Mv+cbR3bTzyUnO9W5ZsdvXZ8Xu485lewgjEXd+ukrbcov0fx+vDNk5AQBA9BAYAQAgAK3Tk93WT+zc3LkcylsmnrXMezXCJ1UB1N3kQe49GA7m12SNFJaFthF2NFg9sun2HTcv44TI+NfMbV7bRnZrKUlKSQpt6atI9M7q0zZDbTJSwn6dWOTrfU3nlqmSpMoYfnDjkMvfO0d/G8+/GbVR26AyWSIAAMQmAiMAAATgljN6uK3HuwQwQvkwabxHT5EOzVNDd3IAjUbT5AS39cT4mr8t0zfEdm8AI6UVVu0+UuxcL/do5n3Kkz9HekpOlVab3l+4S1tzCp3bQvmUen3meH0M9fcjEoGRxsxXloyj95lrH6NY071VTTZLhdWmY0Xl6v6X73XS48altQrLKvXkDxu1dl+ez/PG7lcMAABqg3eUAACYaJNRkyUyqntLt33/N66nczm0GSONr2QHgPB7c84O5/KU1QeiOJPgzd1yWH0e+FGjn/5FX63YK8k7MCJJJVEqEfbO/J26/+u1Gv/sLEnS2n156nrf97rqzYXOMY9PWa8u907R6r3HozLHaAlXFapkAiNh5et/myOzNRQZGOHimtlRVmnTO/N3SpJyC8oM5/3kDxv02qxtOveluZGaIgAAiAG8owQAwERl9dOQ/7nuRPVo7V7Sqm1mTXmNUNYf98wYAYBQ+HjJnmhPodaufmuRc/lPn6ySJJVVegdBJr04J2JzcvXYlA1u646bq/O2HnFue6M6MHXey/MiN7EY4PgePD11kyQpJ79Ui3ccrfN5yRiJnoR4R8ZI7JbSKiqv6XdTXmnTwbya0lr/mLrRa/z7C817yrkiEwwAgIaFd5QAAJhw1KX212A0lE/EJsQTGAEAB7Obr2UGGSPbDxeFezp+PTdts9v6nqPFje5marpHGTdJ2nusqgfMdW8v0aWvL9Dy3cfqdI3k+ND2LIG74grz7KuE6sb3lTFcSsv170N5pU2929Y83PL6rO1e4/u0DW8/NztFuAAAiEkERgAAMFFYVvXEYXKi75fLjiHsA0LGCIBQaZdp3jg6lsvguPrLl2vc1k/rmSUptpqtD+7YzLn8wowtbvveX7hLo5/+JcIzio5Te1T9v7lnYh/TMesP5EuqKo9WF2SMhJfnO5F/XTXUuewo+VkZw39DXLOSyiptKvER6JGknUdqgqqVPjJhHO8Lq85bu9J94SovBwAAgsc7SgAADJS6fIhOTjB+MvW9G4br3ol9NKZ3q5BdNyGOl2YAofHtraea7qvtTb1I+2zZXrf1lmlJqrS6l8aJBrvdrhemb9GU1Qe0cs9x03Gvz96uPUfdgziLth8xGV2/OW74piT6z+bwd6PaH3qMhFfz1CS39dbpNT3XHP19cgui+zvoy7er9juXSyqs+nL5Xh+jpdKKmmCIa/DDU36Ja2CkdqXEGlkCGQAAMY13lAAAGNhQ/VSrZF7e6rSerfT707vTYwRATMpqmmy6r6widvsD+GKxWHT+K/N0+ycrJUnDu7Rw2x+pslWr9ubpuemb9ccPl/scd3ov78D5Zf9eaDCyflu997jmVGeBJJq8Zo57ZqZz+dWZ2+p0vTheK8OqSZJ5cGvNvjxJ0gPfrIvUdOrkjx8s17bcwMvsfbNyv+k+SmIBANCwEBgBAMDAgy4f+DNSEqM4EwAIvSveiO2b8wfzSpVXUuG1/asV+7Ruf03gOqOJez+L4vLIZMIEmrEya3Ou4fbyWj5tHks2HsxXl3un6Ko3F7o1lTfLfAzm5rSrtdU34oFA5Je6/93wLLvnq8SgJD30v9AHfMgSAQAgNhEYAQDAwJoo3Yh5a+6OqFwXQOOy8WBBzPYZOVpUrhFPzNCgR37yO7ZdZhO3rJF+D00N59Sc6vq9K/fRx6C+OPv5OZKkeVvdS4OFuofCuS/NdVu/9MQOob0AGhR/2XAVBk3jHb2L/AlFgIMeIwAAxA4CIwAAAEAjVGmLzZvzG11KGfrTPDVRd07o5bYt3OW0/jl1k98SWh1bNPG5P5iMkQqrzWffg1hTWsf+If7cNaF3WM+PyCqvtKmg1Ds7rLb8VVkz6q8UaGnB2vYVAQAAsYnACAAA1dbszdPkl+aalj4BgPrmxM7NTffFbHmXIJ6oTkmK1/Cu7n1GKsOcCfPyL1v9jvFsuO4pmMDI+Gdnqf9DUw1Li8WicGciJcTzETbSEsP4Pe91/w8a8PBPWr33eEjOZ/Xzh80oCGIULAmXmP27CwBAI8S7SgAAJC3YdkSTX56rNfvydO1/FkdtHv3bZ0Tt2gAanvrYpDouiFoz87cekcVjfCz073jt6qE+98/anBPwuXYdKZYkLdt1tE5zipQJ/do6l5unhr5HVz38ka73+rfPdC5fN6qLJKlXm6YhvYZrn5q68BeYK7fatOuIe78bz0yQQLLOgvkxJBYCAEBsIjACAICkv3233nB7z9ah/eDvz5MXDXQuP3/Z4IheG0DDk+DjLnKsPrkczA1Ho7JN/p4Yj4Q+bX0Hue/5Yk1A51m4vaZ/hyWo70x0rHpwgjKb1ARDBnZoFvJr1MdgX30X7/I9H9KpmSSpZVpync8bjiBmIBlLZzwzy23dMzBSXB6+DBJ6jAAAEDsIjAAAICnfpESJ6w2eSGianOBcPn9wdkSvDaDhifdxE7mgLDZLMxnd+B5/QmvDsXecWdVfxDUAZItSU/mbx3R3LrdKr/tNY0m6/N8LQ3KeSElPSXBbf/LiAYbjJvRtE/A5h1bfiHeI585yVDkyuha4BO1qq8QlAOGvL0+gAgmMWG12Ldl5VKc8+bNW7D6mHYfdM0jqU08fAABQewRGAACQtO+4cT34l64cEtF5dMlK0/WndNGfxvfyKg8DAKH07vxd0Z6CIaO/fE9ePNBgq9Q3uyozw7WvSJTiIvq/cT116xk99PUfT1GaS5DbEbypq69X7gvJecLJM6jVOj3FcNxP6w8FfM7lu4+7X4PXxqhyLUNV194c78zf6Vz215cnUIH2uLnktQXad7xEF/5rvte+o0XlIZkLAACIbUEHRmbPnq3JkycrOztbFotFX3/9tenYm266SRaLRc8//7zb9rKyMt16663KyspSWlqazjvvPO3duzfYqQAAEFapSfFqlxmaJxiD8dDkfvq/8T0jfl0ADY+vUjXl1uj34giUWfZes9Qkr23hbv5tZNbdY5SSGK87J/TW4I7NJElrHzlLX9w8Uree0SMk1/hm5f6QnCcUjHowtG/m/XrpK2OpthLiCYxEU3pKze9iQWndMiuem765rtPxsm5/vuH2i4d2CPgcE1+YoxW7j+nh/61TfmlVZt2avXm1nlMgPUsAAEDkBR0YKSoq0qBBg/Tyyy/7HPf1119r0aJFys72LgNy++2366uvvtLHH3+suXPnqrCwUOeee66s1vDV8gQAIFjhrDENAJFw1YjOpvuiVXLKH6OEgMR43x9bWqTVBEjsYWp1vGL3MU1ZfcBt24huLbT97+eoc8s0r/FNkxM0rHOLWmf/HTN4an1bbqE+WbJblWEIagUTUDIaG6lEDl99cxB+p/TIci5vOlhQq3PY7XZ1uXdKqKbkxjXYMrZ3K+fyxUPb65Hz+gV8ngv/NV/vzN+pp37YqF1HijT55blu+2PzrycAAAhG0IGRiRMn6rHHHtNFF11kOmbfvn265ZZb9MEHHygx0f3prry8PL311lt65plnNH78eA0ZMkTvv/++1qxZo+nTpwf/FQAAUEc8yQegoZo8sJ0uHNLecN+bc3dEeDZ18/Dkvqb73v3NcOdyuP6kX/iv+frjh8vdtjVPTQqoGfgtY3vovEHB9Y36cPFur23jnpmle75Yo9dnbw/qXP5MW39IAx6e6hX4MWP0LQ5ldsiOw0U69amf9dnSPbry5E5u+ygzGV09Wjd1Lv/9+w21OsdbJn97apvt9Zt3lqjLvVO0/3iJerSqmd+vhnV0Lo/s3lJNEuODPveWnEKd/vRMr+1HCim3BQBAfRfyHiM2m03XXHON7r77bvXr5/1ExrJly1RRUaEJEyY4t2VnZ6t///6aP9+7vqdUVXorPz/f7R8AAKESjbIrABAJFotFAztkmu6vS3mY8DG+8T1xQDu39QsG1wQa+rfPVFJ1VoktgsHuBD+ZLA53ndVbL14xRO9cf5Jzm7+gfGmFedbi01M3BTbBAJRWWHXju0tVXG71CvyYMfoe7zpSHPA1u7RMNd1nt9t18/vLtPdYie7+fLXJTwPC7cbTukqSrhvVxXTMlpxC5/L23EJ1uXeKthzyn0Xy2BTjgEpBaYXySiq0dOfRoB5a+XljjiRp1JM/6+RuLSVJbTNSdHb/trpieEf985JBslgsSkyoxU+TyTQ2B/B1AgCA2BbywMhTTz2lhIQE3XbbbYb7Dx48qKSkJDVv3txte5s2bXTw4EHDY5544gllZmY6/3Xs2NFwHAAAtVFJYARAA+b6J+7us3q77bv3y9URno1/yQnuH1GGdGomSWqTkaJZd4/R8gfO1OK/jNOzlw52G+dIJIjkn/SkAAMjDkM61XwGOpBX6nNsXfs3BGrB9iNu63a73WdQpmpM3a5p9rprtdn1m3eWaKNLiaYyH31yED73TjxB3916qh441zxTy/XBkjOemSVJOvO52ZKqfo62HCpQhUvZt7JKqz5Z4p0J5bAtt1CDHvlJv3ptgaasCSx7ydOj362XJJ3WM0vxcRY9cdFA/WpYVX8Rfw3eHUGgRJc+Not3HjUcG0yIhXeZAADEppAGRpYtW6YXXnhB77zzTtApzna73fSY++67T3l5ec5/e/bsCcV0AQCQFNmniwEg0lx7ifz+9O5u+8waFUeT59/k7Myapt6dW6apRVqSWmekeJWwiqv+LBGO3imHC8sMtycF+QS6axP53Ud9Z1gEks34xbK9mvTiHO09Fni2hj+//e9SDXrkJx0x+Zrziiv05fJ9QZ83LSlefdqmSzL/2h78Zq1+2ZTrtu1Qfk0AyfX7h/CKj7Oof/tMnyXSzurXxnTfR4v36MznZuu2j1Y4tz0/fYvu+WKN6TF//36jc/l/K/fLbrfXutxpikHZrPSUBJ/HZFTvr7D6vybvHQEAqP9CGhiZM2eOcnJy1KlTJyUkJCghIUG7du3SnXfeqS5dukiS2rZtq/Lych07dszt2JycHLVpY/zGKjk5WRkZGW7/AAAIFTJGADRkI6pLy0hSfehb7Xm/0TODxIzjGatw3K/82KDfh+T/CXRf7v96rc/9CfG+/2d1uXeK7vxsldbtz9ffvl1f63l4XmXGxhyVVdr0vckT+zd/sEx/+cr85raZByf31XOXDZZkfuP5g0Xe3+c5Ww47lz+88eSgr4vQG39C1ed216Clp9dnb5Mk/bC2pirE1yt8B9RcfxZ/Wn9IXe/7Xl3v+175pRWmx5gF8FISvf9uNE32HRjZGEQzeSuJTAAA1HshDYxcc801Wr16tVauXOn8l52drbvvvltTp06VJA0bNkyJiYmaNm2a87gDBw5o7dq1GjVqVCinAwBAQGigCaAhG9AhU9/88RQt/us4rwztZqmx9wS+55PYF5g0j/fkyBixh6FwzT9/2my4fVMd+gxsdenPYGSJSQkfIz+tP6RfNuXUah5mWftm2+dvO2K43cxrVw/VdaO66OKhHZRQHZmz2oK/q/yXc/qoX7Z5vxxEzvQNhyRJb5o0Ubfb7c7fR4eDeaUqNymL1jo9WZK0dNcxw/0DH/7JdC77jxuXpEtO8M4YMcoicTW0c3PTfW0ykt3Wg/n9BAAAsSnowEhhYaEz6CFJO3bs0MqVK7V79261bNlS/fv3d/uXmJiotm3bqnfvqnrGmZmZuuGGG3TnnXdqxowZWrFiha6++moNGDBA48ePD+kXBwBAIMb+c6ZzedLAmua+jrr2AFDfDerYTK3TU7y2j+re0mB0dHmGNTq1MG/U7SoaPUZyC4yfVg/Utlzz4Mh5g6qaywf6/+j6t5fUaS6egqyMbOrs/u308Hn9lBAf5yzLdKzYPAPAjOeNdsQGq82u4nL3fjgnPjZdOw4XOdd/3nhII56YoSNFxg+i5NTh92j1vuOG240yRk7u2sLnuXw1mj+U7z7Hd+bv9Dc1J6puAQAQm4IOjCxdulRDhgzRkCFDJEl33HGHhgwZogcffDDgczz33HO64IILdOmll+qUU05Ramqqvv32W8XH+36CAwCAcEtwqTPzzCWDojgTAAg/o6eqo+2if813Ww/0hrizx0gE70IO7tisTsfnl5gHCBzlpjo0bxLwdY6Z3Hj2xey7WxlAn4VgJcTVvmABgZHYNH/bYW3PLXLb5hkAeX76FsNjx/RupZ6tmwZ0naUmGRofmZS5M8oOaZ2RokV/Gad1j5xlesxtZ/QIaD4AAKD+811k08CYMWOCaoC2c+dOr20pKSl66aWX9NJLLwV7eQAAwsoiafodp+toUbm6tQrswzoA1FeJfvpYRFpRWaXXtkDvpcc5e4yE9oa+0ZwcHM3Ea8tXEMfRoDw+Lk5HigJ7ov5v363X078aqIT4wAMQZvGGjCbBfVR88YohfsekJdfcrLbb7bJYLLLa7Jq1OUcbDvguS+arCTgi65JhHfTZsr2Sqvq0XfHGQp/jV+/NM9z+9nUnyW6XXvllq56ZZlyuzuFXry3QzicneW1PNPlZLzdpAtImwztzTpK+/ENVWe87JvTWiz9v9dr/zCWDdOdnq3zOEQAA1C8h7TECAEB99/XK/erRuqmG+ym3AAAIvTyDDIpAb4jXZIyEbj7zth7W0Eenme4368Phy5l92ziXc/LNAx6V1V9IQpxFLdKSTce5+mrFPp370tyg52TEqEH6ZoOeKlsen6iF941zlv7yxTVjxBH4+dcvW/Wbd5bq6ambnPvO6tfG69g4AiMxY+eRmgyR5Pg4FZSaBw99sVgsiouz6NZxPWs9l73HSgy3f14duAnU0E7e/UXumtDLuZzdzLzRPAAAqJ8IjAAAAACN1JfL90V7Cm5u+2iF17b4AIMPljCU0rrqzUUqc2kYfe3IzkpOqPkIVZuMm4cm93Uu3/zBcm0+VKC7P1ulPUeL3cbZnBkjFmWk1GRvdG7pu+fKxoMFOlJYt94nkty+bocJz812Wz+lR0slxsepbabxU/ieXLN/HIEfo0yBB87tqw7N3W9EExeJHe1dggS1DVj1y85wW/f3QMr1p3Qx3G7W52dEN9+9ec4fbB7I++7WU/XXc07Q70/v7tx2Qrs6ZIfRYwQAgJhEYAQAAABopCoj2ancj40H87V01zGv7YFmZTibrxtX0AmJh8/rp1UPTdDt43uqXWaK/jg2+H4EHZq7BzYmPDdbny3bq//72D0o5Jox0iw1ybn95zvHuI174fLBXtd4YYZxTwcjFpMuI0cKy/Sbd5bowW/WKq+kQje+u9RrzJMXDQz4OpJ7xoivAFZCXJxu88giCDRAhvC77pSuzuVygwCaP6f2yNK/f32i27aMlESfx7w9b6cqPcpjvb9wl+n4e87u4/N8vx7Z2XRf//aZunF0NyXEx2nJX8drzp/Huv0OAgCAhoHACACgUdt7zP0J3UBKgQAAQie/tEIl5Vad/fycOp3H2WOklo9nv79wl37736Wy2uyaseGQnvlpk9cYi8WilMR43T6+l+bfe4Zpv4LaWL77uNu6tTrCEx9n0V0Teik1KV6/OaWr4uMs2vHEOWrfrImuG9VF5w9u73WuQh99UTyZBSien75FP2/M0bsLdmnQIz9p2vpDbvuzmiarYwvf2SuejDJGjMTHWTS2d2u3bcF8TQivwR2bOTN6ckwyNnx5+Lx+blknknlPG9dMkts/Wem27/6v17qtX3ZiR+dyZhPfgRa5BASNSrc5tEqv+Tl/5cqhfs7p30tBBC0BAEB4Bd18HQCAhuRIYbnbelICzwwAaNiSEuKcT3kP7xLdfkol5VYNfPinkJzL0WOktpW0HDdZ35q7XX//fqPX/sEdm7mt16a/SDAcD8fHx1nUuWWaVj44wfkaZbFYNO/eM0yPPezx2ubLuwvMn7r3Zd69Y4M+xi1jxEdgJCHOouZp7k/oH8grDfp6CJ92mSnae6xEny7d49wWZwmsx0/3Vmle28wyRi4/qaMW7zgqSfpu9QG9fKXxOf/7m+FauP2I/4u7zNXhoqEdAjpm0sB2+uOHAV/C0Ncr9+v5y4fU7SQAACAkCIwAABq1onL3J1CpYQ6goUuMs8hx27xpSnQ/DszanGu4vXebdG2qbvTt/8nvKnG16DGy5VCBSitsykqvuQn/07pDhmND2bvEjNVmdzabd2SMJFSv+wrcn9GntX7emONcP3DcuCG1kekbjL9eX84Z0FbJCfFBH+f6GuszY8Sgd8vADplBXw/h4/h5LK2wOrd99vuRmrrukP49e7vPY42CihkGf4tevWqoyj3KZ73yy1at3ntc23KL3LY3TY7X70d315IdR3X+EO8sKk9xLnMId5m2skqr/0EAACDieCwWANCoXfnGIrf1oZ2aR2kmABAZl53Uybkc7R4jRuWqJOmME1rrl7vGaNbdYwLO5HP2GAnwS7Lb7Trzudma/PJct9cCoz4nkvTo+f0DO3EA/nnJIMPtx4prMj0c/28CaW79hke/hrTk8Aa8hnWuXaaR6w3x5wyarjs4gkEvXVHzZP0ZfVqbDUcUNEmsCoyt3pvn3JacEK9kP7+vy+4fb7h9UXVWiKuR3VtqSEf392VPT92kqesOaWtOodv2IR2bKzM1UZ/fPErXjDDvH+LgGgsxCsSZuWJ41d/PdD9B5Zz8Uj30zVq9OnObhv99RsDnBwAAkUNgBADQaBV7ZIs0S03UJS71qQGgIbr9zJ4a2qmZJN/ljDxtzy0MqlRNIK4xaYC85VCBumalqXNL75I7ZhxPgFsD/JrKXJpG7zhc5GNklUEepbTq4uKhxk+0vzGn5kl7q0vzdX/i4yxuN5xTEsP7MS+QOfnzwaLd+m71fsN9jmyUyYOytfXxiVr/t7OU7qc5NyJr5Z7jXttSEuOVkmieSXTlyZ3Usmmy4b4B7b0zghLj49SpZWpAgY5AAohu42uZMXJqjyxJVaXEfLnj01X674JdeupH77J8AAAgNhAYAQA0aBVWm5bsPOqsp+9q1JM/u61fdlJHZwkTAGioMlISdf0pXSVJlTbvv41mznhmli7/90JtqS5xFQprXJ42d3W8uCLoc9X8+Q4sMFJSHlh5m25Zafr89yODno8vZv1JXp/lHRiJjwvsI1vLpska2a2lpKrG6IHq1aZpwGMdmiQFX0bLyC0frjDc7vpanBAfp9QkKkDHGqP3VSmJcT4zRkb3bGW670SDfkeJ8VXnGlH9cx1Krr+CwQT68kur/jZtPlToc9ySnd4ZMAAAILYQGAEANGiPfrdel7y2QI9+t95rn+eNN4sIigBoHBw3AoOIizitP5Afkjks2XlUny3ba7ivm0FzZn9qMkYCG19YVul/kKRPbhppeNM2XJ6eulEH8kpcAiOBH3vOwHaSpB/WHpQ9wJ4oTWtRdis1RIERV6O6V938bpUeeFAH0WMUHMvObKJkHxkjBaXmAU+jWGFidYmrNhnmPxMdmjfRpsfO9jFTY64ZI8FkmyzdaVxqz5NnbxS3fZU27TriP0sNAACEF4ERAECD9u6CXZKk9xbuivJMACB2OG4EBpMx4hBoqSp/HpuywXRfMCW0HBxfU6BN0mduyvE/SFJW0yT/g0LolV+26dr/LHb2GAk0Y0SSjhZW9Six2uz6wwfLlZNf6veY5buPO5dP65kVUGAi1IGRpIQ4fXjjCK144EzNvntsSM+N8DDK4omLsyjFR8aIr8wfo6wNR2bVsM7m/d/+fc2JztJrwahtxkggY9fuy5OvP0NXvLFQpz89U79sDOxvEAAACA8CIwAAVAuixDQA1GuOm3vWWsQ4KmtzkIFVBj0KHG44tWvQ53P8CQ90fl+u2Od3zGk9s0zLXoXSfRP7uK1vPlQoqz3wHiMO7y3c6Vz+Ye3BoJs+v3fDyVp03zjDfU9dPMC53CQxtKWtHOWXmqclhaxMF8LLrC+PURN1hwn92pju81XK1GKxmAbM+mZnmB4XqGCCvYFkl5z70lyf+5ftqso6+Wjx7oCvCwAAQo/ACACgUTIqMUJcBEBj4bi5Z61FxkhliDJGjFw8tIO+uHmkzwbOZrbkVNX8f+h/awMa3zLNdyZIm4xkvXfDyUHPozYuObGj1zar1ZExEvirU6JB3a05W3J9HuMoU/T8ZYMled/47ZedoW9vOVXjT6i5qR3q5u6++lKgfnAE90b66Adi9PPp4O/nvGOLJl7bHji3b4Cz8+baI2Wxj2COJ3+Byn3HS2o9JwAAEFm8AwUANFh5Jca1rLfmFKr3Az9GeDYAEDscN/eKywJrQO6qNuW3jLTwCExcN6qLnrl0kIZ1rls/j225gdXu99c35O8XDvC5v67Ore4HInl/LyS5lNKqW2DkmrcWS6p6wv9IYZnX/oyURElSa5M+DlNuO00DOmS6lUGKC3EWTUIQ5cIQG5qnJrqtp1f/HPVo3bRW54v38zPlmbk17U+j9ZtTutTqWpLcSl21yUwJ+Dh/v4/7CYwAAFBvhDYHGgCAKLPZ7Fq197jmbzuil3/eajhm/LOznMspiXEqrai6yZcQTIdbAKjHHDf3th8u0pZDBerZJj3gYwNs4eHnHHYdLSp3rl84pL0emlz7p79ro9KjOXLr9GRdf0pXPfXjRt07sY/GnWBe9icUnrl0kH7emKOrR3Q23L9sV9VT7ElBvDYNaJ+p3UeLvbZ3uXeKc3nnk5Pc9jma0Ls2YT+tZ5bmbDnsNs41qyOYYE0gQn0+hN/sP4/VvV+s0ZQ1ByRJCdWN0pM8sn/ev+Fk5RaWqlML332DgmmAfsXwTkH9zTLi2ovIVw8TT64Zx3a7XRaLRQfzSvW/Vft0eq/WsoUxow4AAIQWgREAQINy68crNGX1AcN9+4+XKLuZeykGq82uP43vpe9W79cNpwRf0x4A6iPXJ/RfnbVNz146OOBjjUoRBuvJHze6rT88uV9Eenk4WG12/fOnzW7bEuPjdPOY7rp5TPeIzCE5IV7r/3a26f5jxVVZj8Fk6JzVv63zRrWZT5bs1mUndXKuOwIjaS6BkdevGaYLXpmna0Z2cW6Li7PogsHZOpBXqhPa1b2vgysCI/VPekqiXrlqqBY8Ok1Hi8p1So8sSd79OiwW6cIhHfyer0Nz9/dnz102yGvM1NtHa8qaA7ppdLc6zLyK6zS7tvQdtHFVXG51W954sEAXvzpfkvT37zfq7etOqvPcAABAZPBoLACgQTELikjSs9M2e22rsNr1f+N7atodpyvToywEADRUrjeig2k8LPlurhyIn9Yd1OuztjvX594zNmx/fyusNsOa/0ZZFbF6cz6rqXGJKyPHi8v9jrnnizXOZbvdriKDjJHUpAT99KfTdY1HNsvzlw/RJzeNrNP3as6fvZtoB9NgHrFl7j1jtegv49S++sETz5+NQP/Pdmie6rZuFEzp3TZdd5zZyy2IV1uuAd5gslVcg4JllTZ9uMi9gboj0AgAAGIfgREAQKPx+bK9KqsMvp4+ADQ0ifE1NwJX7D4e1LE/rD1Yp2v/7r1lbuvtMr2bKofKFf9eqFOe/FlLd7oHc4yCQQnx0b05/+lNIw23BxOEMOpV4ktphc355HwobjYHomOLVK9t2w8H1hcGsSc1KUFtMmp6dLgux7LaVrxy/X202e3KL3XvZ+fo4zOuT2tdPaIqM+v+SSeY/n4DAIDoITACAGgwdh3xf2Nl2c5jEZgJAMQ215t7rr0+jMzanOvWoyKccwm1pbuq/uZ/unSP2/bicu+nurcH2LQ9XIZ3beHV/0OSSsoDD+gnJ8QHNM6RWVJQVnVT12KRUhMDOxbwxSs4F6PJQJ1begfoAuFa8e+Gd5aorNK91N1ny/ZKqgo0PnbBAO18cpJ+e1q3oDPzAABA+BEYAQA0GKc/PdPvGM8n+y4a0j5MswGA2OXaY6R/e9/9Iq79z+JwTyfk8ksrVO5yw/J/q/a77T/v5XmRnlKtfbF8X8BjA40xbcstlCQdr+5jYrcHV04ICJQlRiMjbTJS9L9bTtHPd54e1HGuX82qvXmavTnXbb8jkOmZgWULQW8mAAAQWgRGAACNxu9Gd/MqnRCpJrsAEEuOufSiWLi9bj1DAmW32/XXr9b4HxgCAx/+SaP/8YtzvbQi8Abm0da2DqWIAu9fXzXw1Znban2tUDp/cHa0p4AwCfxnskakYnQDOzRTt1ZNgzpmQr+2Pvc7vt6mye4ZWBXW+vM3CACAxoLACACgwTurXxtJVR9KSyvcS5K0zawftbABIJSSEgL7GGAP4VPO2w8X6QOPRsXb/35OyM7vmQF4ML80ZOeOpF/uGuO2Hkxj8mapNWWMPJ+En3r7aOeyo9/WVysCz0YJp0tP7BjtKSBMahPjSE2KTL+b2vDXQ6XYJGOEUloAAMQeAiMAgAavT9uqMjGlFVaVuARG2makqGmEms0CQCwZ0rFZQOOe/HFjyK5p9MR0KMs3/e70biE7VzQ1SXJ/0jw+iKbwQzo20x/GdNc/Lh7o9SR877bp6pdd9Xro6IuQGOWG8xcP7aCf7zxdp/TIiuo8ED6WIFJGxp9Q9SDLjafV39/lA3lVAVnP95eZTRKjMR0AAOADgREAQIOR1TTJ5/6PFu9x1n4e16e1Zv15TFAf2AGgofD827f3WLHhuNdnbQ/J9ex2u3YeNr5GqASTWVGfxAfxOmWxWPTns/vo0pOMMzAcmUKzNlX1RaiwVj3F3r1VWh1nWTsdmjcJupQRYt/jF/Z3LgfzNuvlK4fo05tG6pYzeoRhVpHlmfUyrHPzKM0EAACYITACAGgwzJ7G23WkyLn82JQNkqSfN+UoOSHecDwANDanPvWL/0F18OSPG/X795eF9RrxceYfbVxv/NvqWUmbi4a29z/IxPOXDZYkjejWQpK0YvdxSdI783e6vTZuyy3yPDSsXrlyqCYNbKffja6/mQEw17F5aq2OS0mM1/CuLRTfAIKcTZLc/x5ZLBale2SR8GwOAADRRWAEANBglJs0tvxm1X6vbSEsmw8ADcLafXkBjx33zMygzm2UedImIzmoc/jjK2PE9cb/xoMFhmMeu6C/4fZo+OLmUc7lzi1rn81xwZD2WvPwBH104wivfac/PbPW562rSQPb6ZUrh3r1YUDDkOBSoq22QZL6rqTc4D2px58o3osCABBdBEYAAA1GWYVxYIQPngDg379nB142a1tukY4UltXpeucMaFen4z0F+pR5SmLNR6A/ju3uXPZXjjGSerdNdy7X9aHy9JREv2UjU5PIoEToJMXX/I6FOgBaX3yzcl+0pwAAAPwgMAIAaDAqDcqj9Gmb7iwlIkmO+2b3TzohQrMCgNjUpaX7k9z/M8iu88XRZNif8krjoHWL1NAGIgLtMbLGJTPmT+N7hXQOoRKuCjtm8ZEF940L0xXRGCXEc5vhWZf3ng5UzgIAILbwjgUA0GCMP6G123pW0yS9d8PJumBIe68bZp1aNM7SDgDgcO7A7Dodn5wQ2EcJszKHp/TMqtP1Pfm7GWutDp7/38crAz4mWlwDGKHsQ2CUQdkyLcm0RxdQG67vufxlK9VHTRLNM6ziLNKC+85Q+2ZNvPY1xO8FEIyiskodLSqP9jQAwCk2PwkAAFALnjd2/m9cT7VKryrh4MgmcSSVpCZR1xxA42aUZefLukfOclsvLrcGdFyFScZIq6ahLbHjr5TWvmMlPvfHUk92i8uz5XHcTEU90zq9YZfP2vDo2Vr14ATDfS9fOVTtMr2DIhLN1oH+D0/V0EenKb+0ItpTAQBJEneFAAAN1sjuLU33udaYB4DGqNIkk8OMZ6PsovLKgI6rMLmONcSRCH+ltD5btkd3Tuhtuj+WeiHYFbkojY1GXAix1hkpevWqoWrSgHvXZKa6P4xz+UkddddZvZUV4oAv0JA4Xm62HCrUsM7NozsZABCBEQBAA+J5b6dDc/NyWbH0ZDAARIO/jJFnftrkXH720kFe+3ccLtKo7v7LYZmV0urcMrQlDf1ljHy3+oBO7uodMH/r2hO1PbdIwzq3COl86sL19SzcT5kfK+bJXYTexAHtoj2FiKqw2v0GRTx/lckgQWPFzz6AWMHjsgCABsPzFp+v8iOJ8bwjB9C4Vdq8AxZllVa9PW+HHv1uvV76eatzu1EA5K9frQ3oOmbN10Ndbz/RT7+Q7q2a6uq3FnltH3dCG904ultI5xJKofw+XTikvSRpQt82ITsnAPPMOFeev8ska6Exsbv8wK/cfTx6EwEAFwRGAAANhucHTF9PD/t7shgAGroerZp6bbvj01V65Nv1emvuDrftdSk/WGGNzN0/o7/rV57cyRkIn77hUETmEQquX0tKgE3uA/H4hf316lVD9dxlg0N2TgCBlaTjnScaM9ck1R/XHozeRADABYERAECD4VmT3Vfso5vBDUEAaEwuO6mTrhvVRX8Y0925bcrqA4ZjUxKregXcP+kE57aTugRWH3zXkaI6zLL21jw8QX+/cIBaphmXt+nYwrhBcixISYzXoxf014Pn9lXLEPYsSE1K0MQB7ZSWnKCJ/dtKku48s1fIzg80JpMG1pQL89W/yIHyQWjM3PqK8bsAIEbQYwQA0GC5liw4sXNzLd11TFLVzbymybwEAmjcmiTF6+Hz+iknv1T/mrnN59jk6qyFG07tqg0HCvTF8r3q0zYjoOus2ZfnXB7aqZmWR6iERnpKVXNksxI3/7pyWETmUVvXjOgc1vP/66qhOpBXquxmsRsgAmLZhL5tnMHkrllpUZ4NENtW7D7mXCYuAiBWcFcIANBg+Kpi8NiF/XX283MkSZef1ClCMwKA2NckKd7vGEeg2WKxqGtWVdP0QGrqS9JJXaqamsfHWdQiLamWs6y9I0XlhtsHdMiM8Exii8ViISgC1MHkgdmy2e0a3DGw7DluB6MxKyitjPYUAMALgREAQEQVlVVqyuoD+t+q/Zq79bAkaen945UVwlIhRpok1tz4SwphvXYAqO9c/z4GwtHkvDzAwIijyXu/7IyYaTa86qEJ0Z4CgHouLs6iC4d0CHi8ZyktSmuhseJnH0Cs4M4QACCi+j00VX/+YrUzKCJJ5788LyTntvu443a4sMy5XFphDcn1AKAhSIj3/ZFg2p9Gu607AiOBNlWvrB6XEGdRahTKGJ7eq5XXtswmiRGfB4DGjXvBaMziXN5qxMpDEgBAYAQA0CgMaN/MuVxCYAQAAtazTbrbemJ11l1FZWAZI46Gqwlxcbrn7N7q3z5Dz146KLSTrDbtT6PVNDlBX/5hlHPb29ed5Dbm7H5tw3JtAPCFp+TRmHVonupcTojnlwFAbKCUFgAgYnILygy3X3lyaHp++Hr4yLV8VhyfTAEgIB//boTXtqTqGxqB9hiprA6MxMdZ1KF5qr679bTQTdBDzzbpWvvIWW7b4uLc/+Y3SyVbBED08dQ8GoJp6w/pzTnb9exlg9XepW9VeaVNhWWVzt5iBaUVzn22wN4+AEDYkTECAIiYe75Y7XeM48ni2gj0AyaBEQDw7+3rTtKIbi29tgfbY2TOllxJsfOEaCaBEQBRYKGYFhqgG99dqkU7jurif83Xd6v3y263q7TCqkteX6Chj07T2n15kqSLX13gPCYrPby9JQEgUARGAAARs/dYseH28upyLIVller+l+81/PHptTq/3WfOiPT707vrhHYZumBIdq3ODwAN1VvXnqhTerTUiG4tJEnnDcrW2D6tDcc6epLM2XLYcL+r5buP6dOle6uOi4uNm4ILtx2J9hQANEI8l4OG7GB+qW75cIW63ve9+jzwo1btOS5JOveluV5jJw9sF+HZAYAxSmkBACLGLBvE8dTxf+fvlCTlFJSp0mrz2xDYk7+MkXsn9tG9E/sEdU4AaAzGndBG405oI0my2exe5adcLdt51LlcXmlzK1XoaeamXOdyfFxsPJO1am9etKcAoBEy+qu6/3iJNh7M19jerWUhcoIGKq+kwm39p/WH1K1VU/Vo3TRKMwKAKrHx6QQA0Chsyy0y3H6ksKr3iGsPku2Hi/TR4t3qcu8U00wTAEDo+QqKSO43OL5Yvtfn2BdnbHEux0rGyB1n9or2FAA0Qp6BD4tFGvXkz/rNO0s1bf2hKM0KCL9Bj/zktv75sr0a/+ysKM0GAGoQGAEARMTWnALTfY4yKxlNauq+P/H9Bt335RpJ0qlP/RLQNehhCQDh55ohcqy43HSco0yiQ5Ok+LDNyZ9HzuvnXHY0ggWAWLFgOyX+AACINAIjAICIWLPPvXTJzLvGeI3pn53hXPZMuQ5EoM3XAQC11yQxsABHTkGp+3FRDIyc2beNc9kzYAMA0cZ7WAAAIo/ACAAgIjxvRHXJStOfxruXM3H0GpGkTJfskcDxqRIAwq1/+0zncqXV/O9uaYXVbT2aN/6ymzVxLpcRGAEQBZ4tRAiGoL5bU8eeXWb9JwEgUgiMAAAi4p4v1jiXe7dJlyR1yUp1bvt+zQGVVdTcrBrZvWXkJgcACNivhnVwLqf6yAIpKXcPQHy0eHfY5hQMO0F0AFHgq7c6fddRH01+eW5Q44d1bu62XuLxAEUoFZdXhu3cABoOAiMAgIh7cHJfSVK8SyPeP3yw3O0pXtcMk/SUBOfyjsNF+nHtAdkNHrPjyTsACD+LxaIrhneUJH29cp/puHDe8KiNW8/ooW6t0nTV8M7RngqARmjP0RLTfRYRGUH9UlJu/Bo//Y7R+uLmkfri5lHq0rLmIbhpfxqt5qnuFQHCFbyYsvqA+j44Va/O3BaW8wNoOBL8DwEAoG48gxjJ1Y17E+LcPwTO33bYubz9cJFz2XXU2H/OlFTVSPfaUV08rlP3uQIA/FtdXT5j7b580zGxFhi5c0Jv3Tmhd7SnAQCSyBJB/fbF8r1u6/2yM9S3XYZ6tE53bvvx9tH618xtumRYB3VskaoDee69x4rKrFK6Qu6uz1ZJkp76caNuHtM99BcA0GAQGAEAhF1+qfvTQEnVgZH4OPfExe9WH3Auf7m85ilki8Enx4f+t06XD++o5ISaMi6URwGAyMgvrfA7ZtmuY27r/7nuxHBNBwDqNYIkqG9+XHvQuZyenKApt53mNSYlMV53nNnLa7sD5a4ARBultAAAYfeXr9a4rTdJrApmHCsqr9N5H/x6nds6GSMAEBlNkxP9jnlxxha39TP6tAnXdACgXiMugvqm0lZT9nhCv7YBHXO4sMxt3bWMcigRaAQQKAIjAICwstrsmuKSCSJJXbPSJEllle5lVlx7ibjKK6nQt6v2O8toOXyydI/pdQd3bBb8ZAEAAWmaXJOtZ7P5j0p3a5UWzukAQL3GjVzUN9YAXvs9Hcr3CIxUhCcwAgCBIjACAPWIzWbX1pxCw8bjsers52e7rd8/6QQlxFe9/Li+oW6VnqyCUvN06ls/WqEdLn1HjDjOdt6gbH38uxG1mzAAwK/UpJpA9vES47Ja7Zs1cS5P+9PpYZ8TANQnrm/njcrGArGsY4uaxuqt0pNrdQ7Ph+RChd8mAIEiMAIA9cT23EJ1+8v3Gv/sLL0xZ3u0pxOwLTmFbuvnD27vXD5nQDvncm6B+xNEteH4gNk3O0MpifG+BwMAau3XIzs7lx+bsl5/+GCZHvh6rduYi4ZW/b0/b1C24uO4TQEAZiqt9eehJ0CSOrg8/HDLGT1qdY5wldICgEARGAGAeuKMZ2Y5l//+/cYozqRuXJ8oap2Ror7tMkJ2bkfzdW6/AUB4ndGntXP5y+X79P2ag3pv4S79sjHHub3cWnXDo7ZPkgJAY/GfeTuiPQUgKCUVVdkeN43upqbJxuWQ/QlfjxE+DQIIDIERAEBU1eUp4rYZKYbbeS8MAOFldtPhw8W7ncvl1Tc8khL4yAEAQEORX1qhN+ZUBfOCydK/blQXt/WyCvNSWpVWm44WlQfUx8wTHwUBBKp2YV0AAELkpC4ttGZfXq2OzfOsa08VAgCIqkKXXlFvz9spKTSlEgGgobHVo56BgKs359RkODVJCjww0iw10W3dLGPkkyW7dc8Xa5zr6/92lltvM38Kysz7VgKAKx7fAgBE1Y2ju9b62JIKqyqsNW+oHR8vLTwnBABh51pOy2Fgx0yvbZ8v2xuJ6QBAvTJ9Q47bejn9FlBP5BaUOpeT4gO/rfjb07ppnMt7h+Jy4wCGa1BEkn791uIgZwgAgSEwAgCImC4tU722ZaQkGow0Nqxzc0nSkr+Od257fdY2/d/HK3TpawuUU/0mnVJaABB+Rn9qW6cblzgEAPjW6/4foj0FICDj+rRxLq8NIvO/aXKC3rruJF1+UkdJUoXVO2vqg0W7vLYt3XWsFrMEAP8opQUAiJiz+rX12uZZl/bqEZ30/sLdXuMk6fPfj3TWtW+SGK+SCqv++dPm0E8UAODXjI05XtvKKs3rhQMAfPtp3UF9vXKfnrhwoDJTA394CIik+PiaRyMSg8gYcYir7jFZaRAY+etXa2s/MQAIEhkjAFAPndSlebSnUCtGZVc8m69fM6KL6fGuzX7TU8xj+2ZNgQEA4fWPHzfJbreryKW+970T+0RxRgBQf/zuvWX6fs1BvTZ7W7SnApiyugQ0WmckB318QvXnP6uN8nEAoouMEQCoh5bsrJ/pxC2b+n/jnJwQWMy+0kbDSgCIRV+v3KfCsprMkfMGZUdxNgBQ/xSW0jwascv1c1ibjOBLaDoejHvx563KK6nQI+f393uM3W7n4TcAIUfGCACE2PdrDmjzoYJoTyMm9Wjd1O+YJIPAyKMX9NeXfxjltu1oUbnpOXjLDADh18ykzMufPlmlB76uKYVRm5smANCYtanFU/hApFhdAiOXVfcLCUaCS8WA/y6o6Slit7s/+PbtLac6l0srAssuySupCHo+ABovMkYAIITmbzusP3ywXJK088lJUZ5NbLnp9G4BjUuIdw9rZDVN0jUjOodjSgCAOoh3eXLT0ffJcFwc4WoACEaH5qnRngJgylodwBjVvWWdeow4z2ezKz7OonX7892298vOcC7vOlqkPm0z5M+783cGPR8AjRcZIwAQQutd3sy51ldvrFyf+klJiDcdd/0pXZzLaUnuMfuXrhhqeEy3Vmmm5yPLGgDCz7WkxStXDYniTACgYeG9LGKZozdIbR98SPA4rqTCqhW7j+ncl+a6bXcNoJz9/Byf55y1OVczNhzSM9M2O7d1aek/wFhQWqHzX5mnL5fvDWTqABoYMkYAIIRcs3/3HCsO6KmWQHVs0UR7jpaE7HyR4NoGJCXRPDBi9zFuZPeWhsdkZzbR9tyiOs0PAFB7rvc1TuvZKnoTAYAGxk4rPcSwyurm654BjkDFx7k/o11cXqk35mx325aaZP7Z0VNhWaWu/c9ir+3+fo0OF5bpxMemS5Lu2HNcFw3tEPA1ATQMZIwAQD3RJr3+1Wh3rT/rK8vaZncdZwnoTfbcrYdN9wVagxYAUHt/v3CAJOmOM3vV+uYIADRmp/XMMtxuIzKCGOb4jOcZ4AiU53uG0nKbvl9z0G1bMP3JTn3qZ8Pt/n6NfvvfpQFfA0DDRGAEAEIoXGnvVptdS3cdC8/Jw8j1Q934E9qYjnMNoEj+n+7x1CItyW39pZ+3BHkGAECwxvdto7WPnKXbxvV0K6vlih5RAGDuZZOSscRFECsO5Zdq5Z7jbtsqrFUPodX2oYhdR4rd1osrvEtQ/+nMXl7b7Ha77v5slbrcO0VnPTdb+aVVjdaPFxs3XLebfKr8dMkeXfr6Aq+vy2bjFw9obAiMAEAINQki5TcYy+phUERyD4y0zTR/6sfzPag9gE+D/7h4oHP5u1tPddtXXG7cABgAEFpNk31X5h3QPjNCMwGA+uWd609SZmqi4T5uzyIWHC0q18l/n6ELXpmnWZtzJUnT1h/SA9+skyTFx9cuMPKFRz+Pez5f7bbeu026zhuU7XXcj2sP6rNlVcduOlSgWz5c4fM6+4+XGm7/8xertXjHUa/tny7d4/N8ABoeAiMAEEKujcMrKkP3keaJHzaE7FyRVOkS8YjzkU4zZ0uu2/rLV1Y9Pffw5L6mx/xqWAf99zfDtez+8Ur0VacLABA1X66gmSkAGMloYhwUkQJ7SAgwsvdYccgyH275cLlz+dr/LJbNZteN79aUn4qvZbmEU3u4l5BbtTfPudy3XYa+ueUUw+Nu/mC523pOfqlyC8q8xvVpmy7JuyqB4xgzT/yw0XzSABok7iQBQAi5PvWVnuL7Kdpg5OR7v+GrD1buPu5c9hUY2XvMvan8OQPaaeOjZ+u6U7qaHhMXZ9HpvVqpZdNkNTd52g4AEF2dWqRGewoAEBO6tHT/e+j6QJUn4iKojW9W7tOpT/2iuz5fFZLzzd92xG2921++d1uvbSmtgR3Ms0kfv7C/UhIDq8Kw8WCBTnp8unP94qEd9Na1J+qK4Z2c2zyDjBOen216vrwS45JcABouAiMAoKqnSbbmFNT56SzXm//xIWpEeyi/VPuOl/gfGIN2H62pH+vr+/HhjSd7bQv0DbEkJZAxAgBRl2pQTvLaUV0iPxEAiEEdPQLFjo8N71x/ktdYs94IgC8vzqjqs/jl8n21Ot5ms+u1Wdu0bJd3mSkj2w8X1eo6Fw3tYLqvLpUArjy5k8ad0EYJLiW+PJNGzPqRSNLoXq1qfW0A9RN3kgBA0qWvL9D4Z2frkW/X1+k8rj01QvWk18l/nxGaE0XB01M3OZd9xYlGdc/S1scnaueTkyIwKwBAOAzr3Ny5/L9bTtG3t5yqftn0GAEASfrHrwbqdJcbr46n7ZMMbgSTMYLaqGu/y8+W7dGTP2zUxa8u0P4AHszzbF4eqB6tm5ruS0qo/W3Kvu0yJLn//qzfn+9cLq+0eR3jGpicvTnXaz+Aho3ACACoprn5O/N3asOBfF32+gKtcal16s/8rYe9Mk540ss9HdnipwYtWR8AUL/985JBuvTEDvru1lM1sEMzDfBRKgMAGpt2mU30398M19UjOuncge3UNStNkvF7ZD5FoDbW7sv3P8iHaesPOZfPe3leXafj0xl9Whtu98wYeeHywV5jHrugv+GxKYlVx7o+rFhhqwmGfLbMu7n6mN7e8ygsq9RtH63Qj2sPGl4HQMPBXSgA8DDxhTlatOOoJr88V5Nfmqsjhb77e2w+VKAr31yk8c/Olsv7Lq+03VA7WlQe3gvUUnF5pY4Ulqms0hrtqQAAIqhNRor+8atB6t+egAgAmHnsggF6+cqhzoCIUblZGykjiILpG3Kcy4f9fAauq7euPVEDDN4vJMa7/z4Y9akc0a2l17arR3Ry/k5VWmt+fxyN6P+3ar/++tVat2Om/Wm0pJrgS2aTqr6Vb8/dof+t2q/fv78s0C8HQD1FYARAo3a0qFx//GC56f41+/L0r5nbfJ7ju1X7ncuuH2EO5ZfWdXqSpA7Nmxhuv/7txSE5f13tOlKkLvdO0ZM/bJQkjf7HTA17bLoGPzItanN64Ny+Ubs2AAAAECijcrPERVBXde2dGW4Wi0Vr9nlXaPAsLWcUGPEMnqx6aIIeu2CAc93q8oRihdWuCqtNt320wu2YL24epZ5t0iVVZXNJNUHKAyH6HA8g9hEYAdAo5RaU6XhxuYY+Ok1T1hzwOba0wnfmw2GXzI0b313qXL7lwxVGw00ZvXm12uzae8y4vuuqIEp9hcPTUzfqpveWOr/m12ZtU3F5pfPpohI/37dQu21cT+dyi7TEiF4bAAAAqA1KacWuwrJKXfLafE1Z7fvzYiyotLr3z5i6LnRloD66cUTIzuVPcoJ7nxTP8tQ3je7mDGQ4ODI9HJql1qzb7HbDz/NDOzVzuWbVrdGjReUqrbD67I0JoGEhMAKg0Zi39bC+XbVfRWWVOunx6Rr8t8AyGpbuPGa6b9/xEn24aLfhvkDTj/NKKnTbRyvU9b7v9ekS97qnoco6CYdXftmmqesOafOhQue2fSZBnEj4P5fASH+a/QIAAKAeMLwJG+NP+9dXVps9qEyKP3ywXEt2HtMfPzSvMBALbDa7+j881W3bP3/aHJJzf/PHU9StVZpz/ZHz+jmX05MTQnINh/snnaDMVPcgR1mFe8AnNSnBb4P203q2ci6XW236ZZN3U3XXgGSlSz3sQ/mlWrT9aFDzBlB/BR0YmT17tiZPnqzs7GxZLBZ9/fXXbvsffvhh9enTR2lpaWrevLnGjx+vRYsWuY0ZM2aMLBaL27/LL7+8Tl8IAPhz1ZuLdOtHKzRny+Ggjtt0qMB030PfrKvrtHTfl6v1v+pyXH/+YrVz+2uztmnUkz87140az0WL2QeKD0yCRJEQH2fR7LvH6vPfj3SmRQMAAACxzChjJNy9Chuj0gqrRv/jF/3mnSUBHzN7s/cN9Vi08WCBSj0CCKHqU5PZJFFtMlL01rUn6qMbR+jaUV2c+1o2TQrJNSRp7SNn6bendfPavm6/e0P5+ADuYjZNqQnY/Hf+Tq8yWp5aNU1xOb9FW3IKfYwG0JAEHRgpKirSoEGD9PLLLxvu79Wrl15++WWtWbNGc+fOVZcuXTRhwgTl5rq/oNx44406cOCA89/rr79eu68AAIIUqiyMw4Vlmr7hUJ3P8/0a4zRnR88OSerUIlXnD25f52uFSoXV+I32O/N3RnYiHjq1TNWJXVpEdQ4AAABAoFKT4r22xXp/iPpowbYj2ne8xDB7oL6btt77M+n23CK3XhuBMMoASU2u+vkcd0Ibjezu3vQ8IZAoRYCammSf/GfeDrf1Hq39PwDneq6ZBv+/377+JLf1Ti1TnctzA3iIsqisUl3unaIu907xOxZAbAv6r9jEiRP12GOP6aKLLjLcf+WVV2r8+PHq1q2b+vXrp2effVb5+flavXq127jU1FS1bdvW+S8zk7InACLjof/VZHl41iMNxj2fr/Y7Zv/x2pWWOubSt0SSdh8tliTdekaPWp0v1JbtMi8vZqSzy5tNAAAAAFXSDG4IExapm+PF5Zq39bBsLoEBx+cpSUEHDKLpSGGZ3/kaJB1JkhZtPxLwdSqtNhWUVXptT00yL5eVEKJmHAPam98PvGWs++ffrllVZb3+fmFVs/VPbxoZ1LU+/t0Ije3d2nT/vV+ucVs/6vG5XJL6PVRTtuyVX7bqz5+vCmoOAGJHaAsCeigvL9e///1vZWZmatCgQW77PvjgA73//vtq06aNJk6cqIceekjp6caR37KyMpWV1dTqz8/PNxwHAGZsJm8m80oqgj7XPZ+v1voD+Vqzz3/z8+Jy7zeXrj5a7F166pdNObr+beMU76tHdNZLP28NbKJh9LbHkzv+7DpS7H8QAAAA0MgkGTx1T8JI3Vz86nxtyy3S078aqEtO7CjJPRhitdkVH+RNfbvdblj2LByW7Tqq3UeLtW5fvt6cu0On9czSezecHPR5/jNvp0b1yApo7MPfGpeIbpLondHkkFjHjJGOLZpoz9ESTRrYznTM707vpqW7jio7s4nO7NtGvdtW3Te88uROuvLkTkFfc0S3lv4HuRj6aE1f0h1PnOP1M/D01E2Sqn5nn77E/b4ngNgXlsDId999p8svv1zFxcVq166dpk2bpqysmj/GV111lbp27aq2bdtq7dq1uu+++7Rq1SpNm2bcCPmJJ57QI488Eo6pAmgkrCH6dHH7xyv09cr9AY83KznlcJ/HEymSTIMikvnTQJF2xODJGQAAAADByWqapK5ZadpxuEijurfU/G1HQtYforHallskSfpm5X5nYKRfdoZzf3F5pZISfPfHWLXnuNu6zS7FR+iz2MWvLnBb99cj06wKQjBln99f6P3AXnpKgmEA6fpTuujteTt1z9l9Aj6/kW/+eKqW7jyqM/qYZ3BkpCTq498FlxVi5orhHet0/Btztus3p3Q13PfZsr0ERoB6KHQFAV2MHTtWK1eu1Pz583X22Wfr0ksvVU5OjnP/jTfeqPHjx6t///66/PLL9fnnn2v69Olavny54fnuu+8+5eXlOf/t2bMnHNMG0ID5Sz/+2/n91L5ZE+f65783fvMVTFBEkiqsNv+DgmBRbERGOregNBYAAABQVxaLRb/cNUY7n5ykVunJ0Z5OgzJ3a01AwfUG/9R1xj0eXV3+74Vu67FQfqu0wqob3lmi/3r0dWxi0KcmFP58Vm/D7Q+e21drHp6gU3sGlo1ipkVakib0axvSXiUOfdq6V6QZ0a2FHj2/f53O+fHiPXp73k7DfRcMzq7TuQFER1gCI2lpaerRo4dGjBiht956SwkJCXrrrbdMxw8dOlSJiYnasmWL4f7k5GRlZGS4/QOAYPh7I9unbYam3TFaZ/Vro4cm9w1ZA29/GSOBumZEZ0lSiMq41skrv2zVlyv2+Rzz1MUD9NgFdXvjCQAAADQmcdXp4SSMhN6GAzUl2T1LQN392Spd/u8Fbp8ZSyqsbmOCzeKZv+2wdh4uCnqedpPrLNx+RN+u2q8ZG3PcemZKUnml8cN4Z/ZtE/T1XVWafIa2WCxKT6l9r85I+Ms5J7itv37NiT4DMIH0xNx+uEiPf7/BcF9GHXqXAoiesPYYcbDb7W49QjytW7dOFRUVatfOvK4gANSFv1JaTRLjlZqUoNevOTGk1zV7kyqZv+n1NOvuMercsqrJXKTq2vriqKPqS4XVrqtHdNb9X6+VJCVGKu8cAAAAqKcc75jttF8PuQe+qQkmZFdXCpi+/pDSkhP02bK9kqQlO49qRLeWmrMl1+v4YDJG1u/P15VvLJIk7XxyUsDHfbZ0j/YcKzHcd/m/F5r2+/D8zHnbGT304s9bNW194KW0jDRNjsgtw7BISnAPgvj7PPrspYO8SpgFg2AmUD8F/VeusLBQW7fWNP7dsWOHVq5cqRYtWqhly5Z6/PHHdd5556ldu3Y6cuSI/vWvf2nv3r265JJLJEnbtm3TBx98oHPOOUdZWVlav3697rzzTg0ZMkSnnHJK6L4yAHBh9ZO50STJfwKdWVmsT28aqUtfN34TVVZpNdwuSdtyC/1e88fbT3MGRaTYyBgJRGuPMgCxENABAAAAYlr1W+YYqNpUbxWWVbqtHy8u1+C/ufezXbM3T6lJ8frtu0vdtl/+74X67tZTdc1bi73OG0zPyvUu2SnBuPvz1T73u2axHC8uV7PUqj4p5R6fU4+XVDiXdx0pUtPkBLVsGniZtvsnnaA1+/J0wZD2AR8Tazw/uyfE+f683y87s07XC1VPUwCRFXRgZOnSpRo7dqxz/Y477pAkXXvttXrttde0ceNG/fe//9Xhw4fVsmVLnXTSSZozZ4769esnSUpKStKMGTP0wgsvqLCwUB07dtSkSZP00EMPKT4+PHURAcDfG5UUk6dvXBV5vMl2aJFm3rivtMI8MFJQanw+h+FdW6hPW/fSgdHsMfLv2dv09YrAeqyMP8E9bTstTHVvAQAAgIbC8V6fe6y11/+hqW7rZzwzy2vM499v0JjerQyP35JTYLjd34N2riLxiW3w36bpzjN76dZxPb1+Xo4UljuXT396pqTgMleuHdXFq9xYfdOztXuPEX8ZI0ZN5n154qIBuu/LNc71QKtBAIgtQQdGxowZ4/MX/ssvv/R5fMeOHTVrlvcLEwCEk83PY1fJCd437if0baOf1h9yphC/v3CX4bHNUxN18dAO+mL5Xq99nrVpjfZ1b5Wmbbne9WfvObuP1zZLFN+f/v37jQGPjat+Y/nva4bpsSkb9MLlg8M0KwAAAKBhcNybpZRW8MoqrdpyyDsj/2hRucFoafZm73JZkpSaZHybzPNBu0qrTdtyi9SrTVOv7HhfyQnllTZd8Mo8tW/eRG/8um5lnJ+Ztlnzth1WXknVA3ct05L0/m9PVmmFVf/P3n2HR1Wm/x//THohCYQAIfTeQYpIkaYUAcWOir27a107Vtb1u7jq6u5i/9m7q6KyVjqIFOlVeui9JSEh/fz+CDOZXpLJzGTm/bquXHvKc57zTDYe5pz7PPf9w9r9Nm33njilJqdTiHlS24MikpSZlmCz7imDQbSb/VEmx1lcv2cf0+qnR+rlGZv1/sIdKnedQRtACKv9VzsA8IKrwnFmKQmOX4AHtcuw+d/lO487PTY1MVbPX9Zdz1/WXbMfGGLz9tFfvljttM6IYRiWGSOuvnzHOflCGsoJqb66o7+kipy2ZiO7ZGr+w8PUs3m9YA0LAAAAqBXMz2Z5+dx3HZ74WedPWeB1e2e3hxf3bOJyxr/9i3YPfbVGo/41Xx85eXlu3ibnQRepIs3Whv25mrHhoM25PL3I58ri7ccsheWP5herU+NUp2mhZv9RvXojtdElp1OB/ePSbh7bRjmZMXLTwFYa3TVT2yc7zra5+qzmSkuMVaPUigAMqbSA2onACICIYF8s770bzrRZd5pKy2Q7lb1NgzpO+46NjlJ0lEnj+zRT6wZ19O71tn3/aPe2zpGTRRrw3Gzd/tFySa5TdJU6ee0kKoRrdfRpma4/njlP94/sEOyhAAAAALVOMNPmouJlus9+3+V03+LsYzbr36zcK0maMruiBq9hGJbsKt+ucp1+2Pr/4fcX7rAsL91xzKFtVTlLGxXvJnW0sxf5wsHzl3XXrAeGaHyfZj4f2zw9SU9d0FmvX9Pb6f7eLSpe/DO/y1hOYASolQiMAIgI9l9UWmUkK8lD3Qvz10nzVPaMFMeCdfWd1Bexf9vkXzM326y//Wu29ucUWta3H3FMoyU5/4IawnERSVIitUQAAACAKjF/16/q7IFIs+togX7PPqa8whLPjb3w29YjWrzdeYDins9WSqpIoXTnpyss2w/nFemf0zep1cQf1eaxHx2Kv9uzftFtxobKWRxvL8iuztBtOEsb5a7GhvWYNz872m/jCLaY6Ci1aeCY6swbu44VuN1v7jPK7mVKALWLzzVGAKA2sk+llRQXrTev7a07Plquv13U1ekx9t+fck85fuG+fkBLp8e2bpCs7afrhhy1ymtbVm7ojXnbvBrzGc3rOo6Jt8gAAACAsGRJpRXcYdQag1+YI0m6b3g7v/Tnqh6JtfFvLnLYZp41Um5In9vNOCkvN2xenCuxygqQUafyJTv7DAf+drLQdcDmy2W7LctxMbw/7QtzgIQZI0DtxBUPQESwf+uqblKcBrVroDWTRumSXk3dHmv+jmOuCfKnoW0s+1x9gU1NiLUsW78V9OkS5wXcHxjR3mGbs4Lw9sGalbuc1z3x1jsLsnXp6wt13IubAHv/uLSbpf6KuUA9AAAAgKqq+LL/0ozNlrRMgXQ8v1jT1x9QSVntSq20YMuRYA/B4p/TbbMF2L+gV2KVFaBbk8paILM3HnLoa2TnRn4b18ki57VTpMq0YKh0t1XdTEna/vcxGti2viTpmz8PsGw3x7xqOrAFoGYQGAEQEeyLoZnfhIl2UmTNzDw7w3zknuMV02mt02e5Ks63avcJy/INA1pq2up9uv7d3/Xkd+sd2r46oZfuPrdqbzld/NrCKh0nVeTB/dv3G7R853H9e9YWn48f0r6h/jm+h24+u5W+u2tglccBAAAAwLb24OGTRQE//3n/nq/bPlquZ7/fEPBze2vOxkO69PWF2nb4pGXbsp3Ve1nMlfkPDfP5mBF2wQz7upF7jp+yLJeUVdxp7nCRWvk/V/VUupPUzXMfHKoVT47Q6qdHalyPLMv2q/o2dzmuEwXFWrz9qIpKHe9fNx7Ic3lcpLrf7sXFqCiTPrmln3Y8N1Y9m9ezbDc/T2DCCFA7ERgBEBFKy3z/pmKuLbJmzwlJ0pxNhyVJB3Mr64OcKPCczzYlIUb3fLZS8zYfdtj3n6t6amz3xpKkHk0r3xh67epeTvvyZ42RHKvUYNY3Ft6KiTapYUqCnjy/s8vC9AAAAAC8Y7hcCYyDuRXBmA8WOZ/lHgpufH+plu88rns/X+myzcU9m+inewdV6zyf39ZPzesn2Ww7lFfoonWlaattC6/bzxiZ/NMfluWSsnIVlpRp6ItzHfppUjdRCbHRmvPgUP18n+1nyUiJV3pynNISY/XvK8+wbB/fx3UmhDfnb9eVby3WpGmOL+rBkbd1SUilBdRuBEYARISqfFH5dXPFlOyDuUVq+egPlu1r9+aobcOKQMB53TKdHrvsieGW5SInRdQl6ZHzOtq84fPhTWfp1Qm9tPFv52lMt8ZOj4mPidY9VZxdYq+6s31j3My2AQAAAOAbm/RZIf5V2zAMTf7xD01dsSco5z+e7/wFtR3PjdXLV5yhdg2r9+LWWa3SHbaZ7w99Yf+C3uiulfd5JWXlynVRON6cmiktMVYdM1Nt9iXHVaZcNplM+tuFXXTL2a10RrO6lu29nNSrlKTPft9ts559JF+ju1bc0958div3HwYuLd1xLNhDAFAFJIUHEBGqkvOzblKs0+09m9fTn4a2UfbhfHW3muVhLaNOvK7p11wfL96lYheBkfX7cmzW05JiLbNH3Ll/RHv9pwqpr+z9a2Zl/ttGqQk+Hx8TTWwdAAAA8JeCYqs0RyH+AvpvW4/qzfnbJcljzUZ/KCots6nBeMRDqjFv71Wu6ddc/VrX112fVs5Aeef6Pk5nDDzw5WovR1vJPpVWVt1Ey3JJmVGl/5/tx3Zt/5YObab+uSLV8eVvLNTSHc5TjS3cekQT3l5iWW+UGu/7YCLc96dnCB056XvNTgDBx1MtABGhKoGRek7yuUrShL7NlZoQqx7N6rqdYhsXXfHFvdhF8cJg3+t8aDVF/ud1B3w+nhkjAAAAgP9YF+C2r5EYak6cqnwQXFrDxdrX78tRl6d+0T+nb7JsczYrf+WTI3zu+9mLuumsVvVttq22qhdp5uzWZ8Mzo/TLfYOVPXmM5jw41Gn/v221nWViXaPyy2W7ddKqroy1A7me03Z5IyXB8WU/873xV3azfawDT/COdc0YALUPgREAEeGHtfsty9/ffXa1+oqJ9i4gYC7wXlTi/Ebh8TGdqjUOf7Kedu2tWGaMAAAAADWiKi92+VO5h/NHW70gNnXl3hody99//EOl5YamzN7qtp39i22rnx6px8Z0dNn+r+O6SJJi7e7vzulUWUD9kp5NJDmmId7x3FglxcWoQ2aKTCaTWtrVIzH7arlt8MH6/9f84jKd8895LsdnM6aODSVJV/Rp5lV7s36tHVOC3f7RckmOBcNdZTqAa3XiKxPx7DpaEMSRAKgKnmoBiAjv/bbDsty1ifP0V/bSk5zPGEl3MZPEnjkwcqrE8S2g5y/tbjONOtjsCwt6I5oZIwAAAECNWLnrRFDPv9/DjAXrmfOH/DS7wZWN+/OqdFxaYqxuG9zG6b5f7hus6we0lCTVtbvv62GVLnn+Fse6IoPaZThsc5VJIMpue0m5d8GHWwfZ1vv415VnaMpVPTXpdDDHW9f2a6mMOrafb+YfB3XLB0v1jV1Aa/H2oz71HW4+uKmvmqcnablVvVBPUhIqAyP/79ftNTEsADWIwAiAiDC8U0Ofj7mst/Ncud5OMY4/HRixL3Dnru9g2XroZLCHAAAAAOA0+4fWgTbwudmav/mwy/3WL0nVdNavo/me6zcseGSYxzZ14mP06OiOemhUB3XITLHZN/fBoWpZP0l/u6irTZDjeIHjuV2lFP7bRV0dtg3tYHsfWlbm3S8r1S4FVmpCrC7okaXEON/SXSXGRWvZEyPUxO6lvJl/HHJoGx8b2Y8Ih7RvoPkPD1P9Ot7XWqljFRjhxUGg9onsqx6AiHFOx4rp0APa1PfQslJSfPVyrP6xP9fp9tev7qUoP35p8kdO39+zj/lhJAAAAAD8wbreiL2i0jK9MnuL1u3NqdExXPfu75IqZoT86ePl+mLpLhWVVtTIsL6dqemkX9Zv5Tvz39v7q2k972bA3zGkje4c1tZhe8uMZM19aJiu7dfCZnsDJw/J7x/RwWnf9sdK0t++36BDeYV65Ks1WrPnhErdpCj75b7BlmU3pSyr5PPb+nlsM6ZbY/+eNALEWaWX9jVoBSD4CIwAiAjm4oVpiY7F51yJiareJfL7Nfudbu/byjHPa3Ws8dMNkRHiBR4BAAAASO8u2KEXp2/W+VMW6I7T9SI8OZRXqCVuUiW5uxe489MV+mndAT3y9Vrd+N5SSbYpomq6HkpmaoLb/Z7urzo1TpUkje6a6ZfxtGtUx+U+65oTZn3/b5a+WLZb4175TXtPOC/WvXjiuTazWFyl5qqqZulJ6tOints253Xxz+8nksTHVgZDWmUkB3EkAKqCwAiAiFB2elaFLzM1nDV9+oLO1R6LL1NzXRnZubIgYF6hYw2TqihxM63b/kapXpL3ASYAAAAAvissKXO6feOBypnpP68/oO/X7PPYV9//m6Ur3lqseS7SYxU5Kbx91umAw9Idxy3bFm6rCK58smSXZVuov1718c199fyl3X2uzyFJzdId60ImxLqeGfDdXQN1w+naJc7M2HDQ6XZzGuaa5CzVl7WYaB4R+urhUZWzh2o6QAjA/7jqAYgI5hy9P7iYxeGM/Vs6P907SDcObOWitaOHRjlOsb6kVxOvj3fnyfMrAzT+SKUlSaVuCgH+Z9ZWm3V/BHcAAAAAuPbx4p1Ot9vXMth1rMDrPq9/93cdPVnksH3LQceag/Xtinabzd10SDP/cP6APxTVrxOv8Wc2U7KT2RyedMxMtVm3L2Rur02DOpo0rosm+fhCnX2wxd+ptCTns1lQPc3Skywzbfx1Xw4gcAiMAIgIq/dUP92UeQq2t67r75hj9oXLelR7HJLtzJd1e53XMnHH2VR5VzNGSsvK9fLMzTbb4nibCAAAAKhRx1wUHf953QGb9Y52hcTt2b/J3vvZmXrup4022yb8v8UOx50qdj5j5YbT6bS8PX9NSk92H6jwt/gY7+pI5JzybVa/uT5FtyZpkqSxNVDvo5GHlGSompjointzd/VjAIQmnmwBiAjjemRJklo3CFzez+Q4xzdy7N/uqirrXuyDFt5w9p2txMUbLlNX7HXYNrY7hfkAAACAmuTqMWui/ewCub/HOOkk9e4b87bZrOcVObaZt/mwfs8+5n6Qcp6COFDaNnRd78MfJpzV3GbdVY0Qe18u3+31Oa62Osc3fx6gVU+NUIv6/r9vjQtAuq5IFHv6pcFSN6mpAYQmrooAIkLL+kmSpEFtMwJ2Tl/qmfjKXV5bbzjLf+rqi9xhJ1PtbxvculrnBwAAAODefhcP4UfZFRE3PFT5yCsqcbr9v8t2q6jU+awQqeJlqvFvLvIwSslN3Xa/yD6S73Lfsx7qZlSXr1kDzDo08n4WzaB2lfeoMdFRqptUc7Ngtv19TI31HanMLz+WuElNDSA0ERgBEBHMcQD7uiE17c1re9dIv9WdMl7u5O7laL5jAMSVWFJpAQAAADXq21XOi6rP22RbQN06Je7/Vu/TT2tt6yoWuEiJ9fBXa9TzmRlO0+z64qST2Sb+5KrWiSS19yEAEUj/d3E3r9vGRAXu3io6yqQZfxnssH3KVT0DNoZwE2tOpcWMEaDW4ckWgIhgDgREBTgwMqpLphY8MkxntUrXrAeG+LXv6ae/0NZLivX5WGczRi6YssBp2/+tdn5DBgAAACDw7NM5mVPinigo1t2frdSfPlmhwpLKYIj1sr2C4jLN/ONQtcZT04XYva3rUVNirDIBNEqN9+qYzDTHeh4rnhyhC8/I0k/3DrLZHh0d2HvUdnbBpM6NU3U+qZKrzBzYosYIUPsQGAEQEczfUYKR/7ZpvSR9cXt/tWng3/y35iCPsyCHJ2VO3gpz1c3GA3k+9w8AAACgZtjf0xSXVgRG8qxqiVjfIxSWuE/xs+3wyWqN55f1NRsYCbZLejWxLDdMqVoB85vPbqX05Dj9+8qeDmm2YoJZpEXSj/cOCnhmhXBiKb7uomYngNBFYARARDBPD/e17sfwTo1qYjh+Yc5lWpWZ7+VeBlNcFWQHAAAAEBy32tX7c/ad/fcdlUXTreuIPD6mk8f+uzbxva7GD2v2a+kOz4Xaq8JTDZWa9twl3S3L53ZqWKU+7h3ezrJsf08aHYTAiLk2y53D2gT83OHGUnydGSNArUNgBEBEML8x5euLMM9d2k3X9W+hH+8Z5LlxgJm/Pzub/eGJt7NM3pq/3ee+AQAAAPiuX+t0j222HspzqDFinjFy+GRlzcAb31tqWX74qzWWZfugijNf3THAYdtjYzq6PebOT1fo8jcWKa/QeaH3mvDxzWcF5DxRUSYtmniOnr+su/401PtAwqe3nqX+retr5v1DlJrgOv1xIGuMmF3Tr4UWPnqOHhzZIeDnDjdLth+VxL0zUBsRGAEQEcxxgGgfIyMZdeL1zIVd1TnL97emapo5ldYpNzmDXSmz1Fxx3+6FXzb53DcAAAAA3706oZfHNsNfmu+Q6rb4dNHnK99a7PSY/TmFNuvPXNjFZn1pduVMj9uHtFZCbLR6Nq8rSbqkZxNlTx6j2wa30eKJ53oc3ytztrrd/+3Kvbrw1d+0z65Oii8u7tlEX93RX2e3y6hyH75qnJao8X2a+VTvZECbDH12Wz+1beg+pXJibHBqqGTVTSSFlh+s3pMT7CEAqCICIwAiQrCKr9ck61Rany7Z5dOxpadvnmKionTDgJaSpKS44BY1BAAAACJZ/TrxSnbzndxwMVP81y2HZRiGZeaItRMFxZZlc7Djuv4tteCRYZbtszYeUpO6iZKkMV0rinBP/dMA/XjPIP3jsu6Wh+eZaQla+Og5+vTWs3TroFZOx3LALghj774vVmn17hN69ocNbttZK7KrkfLyFWeoT0vPs2tqi0Tuw8LGFW8u8jptNYDgIzACICIYXs6QqE2sgzyPfbPWp2PNqbSio0wa2LbiTat2dkUAAQAAAATWI6Ndp6zadDDP6fa5mw7r/v+udth+sqhU/561xbJuXT+xab0km7bFp+uUmOslmEwmdc5KtaybZdVN1IA2GXp8bGenY1m47ajL8eecqkyz9ePaAy7bWTMMQ4fyKlOEndmynlfH1Sa8oFa7/dkqvdqS7GP6eb13f9sAgo/ACIBapbzc0O/Zx5TrY+5a80sb4TRVuDqpaM2F4WKiTTLf6+w8mu+HUQEAAACoKneFuM2zvp35ZuVeh23P/G+93vtth2Xdfvb8E2MrC7EfPh18iIvx/n7pPquC4pVjdJy1Ynaq2DYFsDdv1s/ZdMjr8dRWBEZqt9kbbf9G46J51ArUFvzXCqBW+Wr5Ho1/c5EueW2hT8eFYyqt6nyWy9+o+P1FR5mUe6pUknSioEQldjcy5i913999tto3qsiNO/P+wVU+LwAAAADXfK2J6M6sP2wf2CbE2j4Ccja7w36GiDvWM1DMBrRxXfdjyyHbGS89npnuNpAiSc9+/4fX46mtSKVVu9nX8EkIUs0YAL4jMAKgVpm2ep8kaeuhk3rsm7XadbTAq+PMLyOFUyqtqt40Hc4r0pGTFbmGTxSUaK9V4cPcU7YzccxT6uslx+mX+wYre/IYtW1Iyi0AAACgJlinm2qdkWyzr6i0zL65W/ZBjsv7NLNZX7nruMMxMT4ERjpmOt4XdGuaZrO+P+eUPvt9l9btzdE9n6202ZdXWKrPlu52e47tR8J/VjszDGo3c+0eM0PUGAFqC66+AGoV61jAp0t2afALc7w6zlJjJIwiI1X9LEdOFrncV2o1nb2guNSybBiGTCZTWKUiAwAAAELNq3O2WpbNs96zj+SrrNzQ+n25Nm09fTWPt5shUic+xmZ90rguDsfERnv/fd9ZEMW+AHz/ybM1cepanT9lgY4XOKZD3rg/12FbpOEeq3Z7YEQHm3X7LAwAQheBEQARwXxTEU7fOf0V4xnSvoFl2fpL3Jo9OZbljDrx/jkZAAAAAJcKSyq/jx8vKNGXy3Zr2Itzdf9/V+mp79bbtH396l5u+9rpYXZ903qJDtuqO3vBPjDiibsyI9sOn6zWWIBAyEiJs1mft+lwkEYCwFcERgDUKhv2Ve2NIvPz/nCqMeKuMKM7ZXZ3H12bVE53L7Eq6Hj9u79blsmTCgAAANS8R0d3tCznnCrRQ1+tkSR9t2qfQ9vWDepU61zJdjNIJN9qjDhT7PPb8q4jIwftajeEkx/vGaT6yXF69qKuwR4Kqsn+vvyDRTuDNBIAviIwAqBWyS10nH7tDUsqrfCJi1Q5yPPw6Zsra/WSYiXJpvhhkY9vewEAAAConsy0BJf7Lu/d1Ga9bmKs1/22bpDssC0lwfH4GB9SaTnzhYeaIfYMNzNGStxNJ6nlOmelatkTw3VNvxbBHgqqKSaKR6tAbcV/vQBqFesZDWZLth/1eFy5JTASPpGRqn6WDU7y+JrzA5t/v3M3Har6wAAAAABUibvv+Fl1bVNf1U2Kc9HSUVKc4wzwjDqOx8dW8yFvzqkSywx1w13U47SCYtcF5QtLHPfddU67qg8uxFBbJDxUNZMDgOAjMAIgpHyxdJdGvjxPR90UCLd3xVuLPbYxv2wUToGRGD9+AYuzBEbKtWDLEd3w3lLLPme5hwEAAAAE1r9nbbFZj4vx/pHOsA4NHbbFx0Trn5f3sNkW5Yd7jOd++kOSNPY/Czy2PeAmXZZ1Ifir+jbXiidH2NRHBEKBs7o8c3jREKgVCIwACBmFJWV65Ou12nzwpPr+fZYkKftIvh79eo1PgRJnysMxlZYfP4x5yvxN7y/VNe8ssdnHzQcAAAAQGGe3y/CqXcv6ST71e9c5bZ1u75CZ4lM/3vh/v2ZLsp2pflXfZk7buiuwnp4cb1mOiTIpPdn7GTJAoDgLUN743lKV+FxvB0CgERgBEBI+WLhDHZ/82bJeVm6o5aM/aNiLc/X50t3q838zveon+0i+fl6332HatnnVn8GEcJJ4urj60fxih327jhUEejgAAABARKoTH6PXr+7lsd2M+4dIkmY/MMRj29YZyYqPcUylJVV/Rv17N56pXs3rasJZzd22a1LX+Sx0Z/cfZmXlPFhG6HOVSuup79a5nREFIPgIjAAICU9PW+92vxfpaWUYhoa9OFd3fLxCv221rTtinjESbnlcp901UJKU5aZIozfqxMe43HdBj6xq9Q0AAADAewO9mDUSezp9T6sMx6Lq9t66ro/LfdWtjzCsQ0NN/fNAPT6mk8323MISy/KkCzqr2EmtSEk6v3tjl31b15e8fkDLao0TCLTPft+tfpNnaX/OqWAPBYALBEYAhI35W45Ylmf+cdBmXzim0pKkmNPFEUvLvYgcuVEnwXVgxDq3LwAAAICalZoQq2QnxdLNrGsamEwmDfIQSGnbsI7Lff4qHJ1s96JV90nTLcu9W6TrZGGp0+NKywwVlZZp6Y5jKrVLPVR6OjDSLD3R7WcAQln/ybN1KI+ZI0AoIjACoFZIS4z12Ka4tPKLtH3O3XAsvi5V1gY5lFfkcCPhC3czRk4WlVW5XwAAAAC+c/fi0sKJ59is331OO8ty83Tfao/4KzDiTr3kWJ3RvK5l/R6reicFJWV66Ms1uvyNRRr2z7k2x5WeTqWVmuD5XhAIZU9+uy7YQwDgBIERALXCGc3qut3/wi8bNW/zIct6QqztG1ZGmM4YsQ70XP32Ejct3XMXGFm241iV+wUAAADgu4O5RS73pdgFTfq2StdP9w7S13/qrx/vHaQx3TIt+359eJjb80T78cUxVyl442KitO1QZZH1czo10hvXVNRROVVcqmmr90mSdh87pZxTlSm4zDNGYqJ5dIXQ9tL4HrqgR5b+cWk3p/t/WX/Q6XYAwcW/LgCCrjozHcxenbNNHy/eZVnPL7ad5VBWHp41Ro6crLxhWpJd9QCGfSDJmrugCQAAAIDAinMSKOjUOFW9W6SrTnyMBrVrYNnezMMMkig/PhV6eXwPp9tjo6Jknfi3Sd1EJcZV3GPsPFpg07bHXytTcJnTBceE29ttCDuX9GqqKVf11BVnNveY2g5A6CAwAiDonvl+g8c25mnU3iooss1ha06l5c83okJBi/q+TZW399rVFW9qbTmU57JNLG9oAQAAACHD08teGXXive4rxo+RkZjoKGVPHuOwvW5SrG4d1MqyHh8bZXk57lCe65kx5ntAAiOoTa4+q3mwhwDASzztAhB0mw64fihvtvvYKRWWeF/rwn7GiKX4ephd9eyLHPpqTLfGkqTfth512JcQW/HLurxP02qdAwAAAEDgnNuxoW4a2Er/vvIMj239XWPEZDLpuzsHWtZ7Na8rk8mklIRYvXfDmXrjmt5KTYjViYISN71UMM/650Ut1CajumTqrWt7a+Gj5+iKPs0s27cfPqmPFu1QbqHnv30AgcG/LgCCbkAb26mmfx3XxaHNrmMFluCGN04V284YMcK0+Lqzz1NYUqZLX1+o53/eWK2+P7r5LC19fLi6ZKVVqx8AAAAAgRMVZdJTF3TWhWc08djWejbG57f188v5ezSrq/kPDdNdw9rqrev6WLYP69hQ53WtqH8ytntjl8eb60OWnK4xEogC8YC/mEwmjeySqay6iZa6Ox0apeicf87Tk9+tV/dJ0z30ACBQCIwACLpvVu6xWR/nomjf73Y1NPq1TnfZp6sZI+FWY8T+HsEwDM3645CW7zyu1+Zuq3bfDVK8n4YPAAAAwD8u7lkZ1GiVkWxZHtWlkV/PE2V1Q1HdNL3WmtdP0oOjOrhM6+WuxmFZuaEDOYV68MvVkqTY6PC6h0PkSEmoyPCw6aDnLBkAAo/ACICgsw5ifHBTX9VLjtMNA1o6tLvhvaU26+6+TJvTc5WXG9pyMM9SuC/cvlLbzxh5be42m3osRaXepR9zFi9qUCehWmMDAAAAUDWbrR6kTuhbWbNgdFfXMy2qIhTfG1u0/aju+WylZZ0ZI6it6iQ4T3391/+t12E39XUABAaBEQBBN7Zb5Zf7Hk0r0jZNGtdFr0zoqUt7ua5vER/j+hK2dm+OJOlfMzdrxMvzLbNNwi0/rf2NzAu/bNK/Zm6xrG85eNKrfn66d5DN+sjOjdTcj2+MAQAAAPBeSVnly07WMybc3QNVRZzV/VFSbPXqF/rLte/8rt93VGYLiAmzezhEjhQXNUHf+22Hzvy/mT7VUQXgf/zrAiDoPly0Q1LFdPG6SXGW7ed3z9I/x/dwedxtg9vonev7uNwvSf+ZvdVmPdymYTurMZJ9JN+y7G5WjbW8QtuaLJf2puA6AAAAECzW3+PrJMRaluP8HBhJiI3WG9f00pSreiotKdbzAUEQw4wR1FKuUsmZHS8o9rqvTQfydN27v2vV7hPVHJV3ThaVquWjP+jxb9YG5HxAMBAYARB0p7NcaeaGgz4d17tFPZ3byXWO3dzCEodtUWH2pdrTp7F+A6WwpEz7c045bVdSWm6z7kOdewAAAAB+Zj3TPcUqHY+/AyOSdF7XxpYi0aGIVFqorTw9f/h18xGv+7r67SWav/mwLn7tt+oOyyujXp4vSfpkya6AnA8IBgIjAELGhT29/zL+2tW9LMs7nhvrtE33SdMdtkWHYhLdanA2Y8SadY2Rjk/+rP6TZztt17eVbSH7lhmk0QIAAACCxVwjUbKd9R4XRmmlHh3d0at2U1fsreGRAMGx+3iB122PnKyoSRKolxj3nnD+UiUQTsLnX1QAtV5pmfN/4f9zVU+b9b4t0zWmm23RwSHtG3h1jnB728hTnOeat393ue+JsZ0syzHRUdr87Gh9dUd/vXFNb3XMTPXXEAEAAABUQ0xU5aObgjCqSdCnRT3Lcv3kODctgdrrh3vOtizfNLCVzb4ps7fWijojpWXlnhsBtRCBEQAhY2QX52mxxtlN6/7vHf0d2rx9fR89MbaTQxFxe55mWNQ2Jg+f59TpL1n3fb7SYZ99/ZG4mCj1aZmu87pm+m+AAAAAAKrlUF6RZTmnwDFdcG3VrWmaZblj4xSteHJEEEcD1Iw2DepYlp88v5M+v62fzf5PQzBVlWE3LaWwlMAIwhOBEQBBVW41RbxH07ou200c3VGpCTFa99dRTvfHRkfplkGt1amx+5kO4TZjxFvfrtrnsC3MYkQAAABA2LD+qm79kLK31SyL2i4+pvJFrZT4WKUnx2nHc2N1y9m2b9UnxPLoCrVXQmy0Vj89UhueGSWTyaR+revb7N8Xgimrdh2zTfFVG2a1AFUR47kJANScnVb/4CbGRbtsd/uQNrp9SJtqny+MUvJ6zf5tD7MjecUBHgkAAAAAb1i/xNQwNcGy3Cw9vGoB1k2K1YmCEo07ozJLwEGrGTJS+M36R+RJS4x1ua84BNNU5RfZBkJOFpYqo058kEYD1JwIfEQIIJQs2X7Usmz9xlBNicQv1QdyC51un/nHwQCPBAAAAICvBrfL0J3D2uiVCT09N65lfrp3kN69oY9GW6XznXRBZ5s2kXgPh8jx4aKdwR6Cg9V7TtisH3TxTAGo7ZgxAiCooqxSWwUizVU4p9JKjotWfrHjFNf3f9vhtH0Y/yoAAACAsGEymfTQqI7BHkaNaJyWqMZpiTbb6vNmOhA0p4rLNHHqWptt9s9R5mw6pF83H9Gfh7VhJglqNWaMAAiqTKtp4f5ySc8mluUXLutusy+c3zYqKXeeMmuvi5ylp8gTCgAAAISka/u1kCT1a50e5JEEx5pJI4M9BCBgWj76g75btVdSRSrs1+du09xNh1y2tw9c+NOxAseU20VWxdcP5RbqxveW6t3fstXn2Zk65eTlTKC2IDACIKjMD+d7Na/rtz77t6ksZnZ5n2Y2+8J5xkjDFOdvany/Zr9l+aq+zS3LB3KYDgsAAACEoot7NtGP9wzS+zf2DfZQgiI1obImg6uaiUBtdW7Hhg7b7v18ldbvy9GtHy7XP37eqBveW6ruk37RCSeBis9+31VjY3P239v09Qcsy+PfXGSz78NFO2psLEBNIzACIGi+W7VXt3+0XJL7wuu+cve1OZxnjNw3vL3b/Q1T4tWmQbJlPS3JdQE4AAAAAMFjMpnUOStVCbE1X4cx1MXG8OgK4eWl8Wc43b5y1wmbWqC5haXq/ezMoAcHP7Cqg7LjaIHNvv28cIlajH9dAATNvZ+vsiz7M2BxXtdMpSfHaVSXRg77osP4qje4XYbb/Qmx0TJZ/Z7Pbuu+PQAAAAAEy6sTeikzNUHvXH9msIcC+JWrlxSf+Hadw7aycsNleuya4CkGk2z3UmubhnVqcDRAzaL4OoCQ8OuWI37rKzUhVosnnqvYaMdgiykMZ4ysfmqk8opK1NBDvZbE2Gg5+ZUAAAAAQMgZ272xxnZvHOxhADUiMTba67qfpWWBmzES5Sb9+KniMuXb1RS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\n",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['open'].plot(figsize=(20,10))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}