量化分析/个股分析/yefei-concept-analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](https://fenc.wang/imgs/2020/08/3565654bfbe9ffa0.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tushare as ts\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from matplotlib.font_manager import FontProperties\n",
    "myfont=FontProperties(fname=r'C:\\Windows\\Fonts\\simhei.ttf',size=14)\n",
    "\n",
    "\n",
    "#设置完整显示数据\n",
    "pd.set_option('display.max_rows', 500)\n",
    "pd.set_option('display.max_columns', \n",
    "              500)\n",
    "pd.set_option('display.width', 1000)\n",
    "pd.set_option('display.float_format', '{:,.2f}'.format)\n",
    "\n",
    "pro = ts.pro_api('xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx')\n",
    "ts.set_token('xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx')\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "cn_en={\n",
    "    'symbol':'代码',\n",
    "    'name':'名称',\n",
    "    'trade_date':'交易日',\n",
    "    'total_mv':'总市值(亿)',\n",
    "    'circ_mv':'流通市值(亿)',\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#叶飞概念股票代码\n",
    "#tickers = ['002074','300185','002387','603680','000980','603377','605118','600552','300523','688033','002965','300503','601020','603557','002363','603929','603709','002464']\n",
    "tickers = ['维信诺', '龙腾光电', '京东方A', 'TCL科技', '深天马A']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>ts_code</th>\n",
       "      <th>symbol</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>000050.SZ</td>\n",
       "      <td>000050</td>\n",
       "      <td>深天马A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>000100.SZ</td>\n",
       "      <td>000100</td>\n",
       "      <td>TCL科技</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>000725.SZ</td>\n",
       "      <td>000725</td>\n",
       "      <td>京东方A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>838</th>\n",
       "      <td>002387.SZ</td>\n",
       "      <td>002387</td>\n",
       "      <td>维信诺</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4056</th>\n",
       "      <td>688055.SH</td>\n",
       "      <td>688055</td>\n",
       "      <td>龙腾光电</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        ts_code  symbol   name\n",
       "38    000050.SZ  000050   深天马A\n",
       "58    000100.SZ  000100  TCL科技\n",
       "264   000725.SZ  000725   京东方A\n",
       "838   002387.SZ  002387    维信诺\n",
       "4056  688055.SH  688055   龙腾光电"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_basic = pro.stock_basic(exchange='', list_status='L', fields='ts_code,symbol,name')\n",
    "\n",
    "if tickers[0].isnumeric():\n",
    "    stock_list = stock_basic[stock_basic['symbol'].isin(tickers)]\n",
    "else:\n",
    "    stock_list = stock_basic[stock_basic['name'].isin(tickers)]\n",
    "stock_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>ts_code</th>\n",
       "      <th>代码</th>\n",
       "      <th>名称</th>\n",
       "      <th>交易日</th>\n",
       "      <th>pe</th>\n",
       "      <th>pe_ttm</th>\n",
       "      <th>pb</th>\n",
       "      <th>总市值(亿)</th>\n",
       "      <th>流通市值(亿)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>002387.SZ</td>\n",
       "      <td>002387</td>\n",
       "      <td>维信诺</td>\n",
       "      <td>20210521</td>\n",
       "      <td>57.64</td>\n",
       "      <td>3,266.89</td>\n",
       "      <td>0.80</td>\n",
       "      <td>117.35</td>\n",
       "      <td>117.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>688055.SH</td>\n",
       "      <td>688055</td>\n",
       "      <td>龙腾光电</td>\n",
       "      <td>20210521</td>\n",
       "      <td>89.42</td>\n",
       "      <td>49.89</td>\n",
       "      <td>5.88</td>\n",
       "      <td>234.33</td>\n",
       "      <td>19.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>000050.SZ</td>\n",
       "      <td>000050</td>\n",
       "      <td>深天马A</td>\n",
       "      <td>20210521</td>\n",
       "      <td>22.50</td>\n",
       "      <td>19.61</td>\n",
       "      <td>0.97</td>\n",
       "      <td>331.80</td>\n",
       "      <td>281.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>000100.SZ</td>\n",
       "      <td>000100</td>\n",
       "      <td>TCL科技</td>\n",
       "      <td>20210521</td>\n",
       "      <td>27.15</td>\n",
       "      <td>18.66</td>\n",
       "      <td>3.55</td>\n",
       "      <td>1,191.21</td>\n",
       "      <td>1,095.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>000725.SZ</td>\n",
       "      <td>000725</td>\n",
       "      <td>京东方A</td>\n",
       "      <td>20210521</td>\n",
       "      <td>45.82</td>\n",
       "      <td>23.91</td>\n",
       "      <td>2.35</td>\n",
       "      <td>2,307.13</td>\n",
       "      <td>2,223.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ts_code      代码     名称       交易日    pe   pe_ttm   pb   总市值(亿)  流通市值(亿)\n",
       "3  002387.SZ  002387    维信诺  20210521 57.64 3,266.89 0.80   117.35   117.31\n",
       "4  688055.SH  688055   龙腾光电  20210521 89.42    49.89 5.88   234.33    19.92\n",
       "0  000050.SZ  000050   深天马A  20210521 22.50    19.61 0.97   331.80   281.57\n",
       "1  000100.SZ  000100  TCL科技  20210521 27.15    18.66 3.55 1,191.21 1,095.01\n",
       "2  000725.SZ  000725   京东方A  20210521 45.82    23.91 2.35 2,307.13 2,223.50"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily_basic = pro.daily_basic(ts_code='', trade_date='20210521', fields='ts_code,trade_date,pe,pe_ttm,pb,total_mv,circ_mv')\n",
    "daily_basic['total_mv'] = daily_basic['total_mv'].div(10000)\n",
    "daily_basic['circ_mv'] = daily_basic['circ_mv'].div(10000)\n",
    "stock_list = stock_list.merge(daily_basic, on=['ts_code'])\n",
    "stock_list.sort_values(by='total_mv').rename(columns=cn_en)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAv8AAAMNCAYAAAAP1huEAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAACY30lEQVR4nOzdd3xUVfrH8e+ZSW/0GiD0AaUKKthRLPhjbatrWdddRbCgCGIFsZd1rWsvKGJFRVfEhhUboPTO0HsnQHqbOb8/EgKhZCZhhmRyP29f80rm3Dl3nsuY5JlnnnuusdYKAAAAQM3nquoAAAAAABwZJP8AAACAQ5D8AwAAAA5B8g8AAAA4BMk/AAAA4BAk/wAAAIBDRFV1AAAAAIBTeTyesyS97PV621RwXh9JT0tqI+lbSQO9Xu/OQPOo/AMAAABVwOPxdJT0viR3BecdLelLSaskXSwpWtJ7wcwl+QcAAACOMI/Hc5yk3yStrMT0kZLWS/qb1+v9VtKVkk7yeDzHBppI8g8AAAAceadIGi7ppUrMPUPSx16vt0iSvF5vpqSfJPUNNJHkHwAAADjynvZ6vW9VdJLH44mS1FDS/P02rZLULtB8TvgFAAAAQsDj8dSWVPsgm3Z5vd5d+w54vV5/JZ8mfs8+9xvPUvHJv+Ui+QcAAEBEKdy+0lZ1DIfwgKT7DjF+f4ieI7/kq2+/cau9bwwOieQfAAAACI1nJb11kPFdoXoCr9db4PF4dktqut+mepKyA80n+QcAAABCoKS1Z9cReKq5kk6QNHafsR6SZgWayAm/AAAAiCx+X/W8HTnjJV3q8XjSpNJlQ4+T9H2giST/AAAAQDXi8XiaejyeruU8ZLSkdZKmejyetyRNkjRT0oRA+yb5BwAAAKqXQZJ+ONRGr9ebK+lkSZ9K6irpQ0ln7Vn3vzzG2up6sjQAAABwoMIt3mqZwEY38piqjiEQKv8AAACAQ5D8AwAAAA7BUp8AAACILP7KXhwXVP4BAAAAhyD5BwAAAByCth8AAABEFGtp+6ksKv8AAACAQ5D8AwAAAA5B2w8AAAAiC6v9VBqVfwAAAMAhSP4BAAAAh6DtBwAAAJGF1X4qjco/AAAA4BAk/wAAAIBD0PYDAACAyOL3VXUEEYvKPwAAAOAQJP8AAACAQ9D2AwAAgMjCaj+VRuUfAAAAcAiSfwAAAMAhaPsBAABAZPHT9lNZVP4BAAAAhyD5BwAAAByCth8AAABEFMtqP5VG5R8AAABwCJJ/AAAAwCFo+wEAAEBkYbWfSqPyDwAAADgEyT8AAADgELT9AAAAILKw2k+lUfkHAAAAHILkHwAAAHAI2n4AAAAQWfy+qo4gYlH5BwAAAByC5B8AAABwCNp+AAAAEFlY7afSqPwDAAAADkHyDwAAADgEbT8AAACILH7afiqLyj8AAADgECT/AAAAgEPQ9gMAAIDIwmo/lUblHwAAAHAIkn8AAADAIWj7AQAAQGRhtZ9Ko/IPAAAAOATJPwAAAOAQtP0AAAAgoljrq+oQIhaVfwAAAMAhSP4BAAAAh6DtBwAAAJGFi3xVGpV/AAAAwCFI/gEAAACHoO0HAAAAkYWLfFUalX8AAADAIUj+AQAAAIeg7QcAAACRhdV+Ko3KPwAAAOAQJP8AAACAQ9D2AwAAgMji91V1BBGLyj8AAADgEGGv/BduX2nD/RyovLndbq3qEFCO9mdnV3UIKIfnkw1VHQLKcVvKMVUdAspxzbHrqzoEBFDnk8mmqmNA6NH2AwAAgMjCaj+VRtsPAAAA4BAk/wAAAIBD0PYDAACAyOKn7aeyqPwDAAAADkHyDwAAADgEbT8AAACILKz2U2lU/gEAAACHIPkHAAAAHIK2HwAAAEQWVvupNCr/AAAAgEOQ/AMAAAAOQdsPAAAAIgttP5VG5R8AAABwCCr/AAAAiCjW+qo6hIhF5R8AAABwCJJ/AAAAwCFo+wEAAEBk4YTfSqPyDwAAADgEyT8AAADgELT9AAAAILJY2n4qi8o/AAAA4BAk/wAAAIBD0PYDAACAyMJqP5VG5R8AAABwCJJ/AAAAwCFo+wEAAEBkYbWfSqPyDwAAADgEyT8AAADgELT9AAAAILKw2k+lUfkHAAAAHILkHwAAAHAI2n4AAAAQWVjtp9Ko/AMAAAAOQfIPAAAAOARtPwAAAIgsrPZTaVT+AQAAAIcg+QcAAAAcgrYfAAAARBbafiqNyj8AAADgECT/AAAAgEPQ9gMAAIDIwkW+Ko3KPwAAAOAQJP8AAACAQ9D2AwAAgMjCaj+VRuUfQLVj6jSQu81RUkJSVYcCAECN4vjk3+fz6Ybho/TZl98FPWfJ0hW6YuBQHdf3Ig25+0Htzsgss/29jyfo9POv1Cn9L9fb4/4X6pAdw10rUa1fvUPdF7+vjl89pfiOaRXeR+ObLpbn44cPui22ZWN1XzpOMc0aHm6ozpSQpPgbRin5hc+UOOpFuZq1qtB0V4u2Sn7pc7maln1d464YrKQHXlHclUOU/NQ4RZ9wZiijdqTzLjxHU2d/o4Urp2jEfcNkjAnp3KapjbVkzTSd2ueEUIZdo8XWStBfXhmimxa+riu/fEj1OzQPal7DTi11xecPaOjyt3TjvFd0/E3nlW679vdnNHztuwfcjr745HAdRo1mEpOUeNsDqv3Ol0r+z6typ7UOal7cxf9QnU8ml7lF9+hdvDE+QQnX3apar3yoWm/+TwmDhslQ5MAR5ujkPz+/QHc9+IR+nTYj6DmZWdm6bvgotUprrk/GvqjUxo1072PPlm7/6vvJeuqlN3T7zQM15oXH9fHnX+unX6eFIfqar/WLwxXbopEWn3+ntrw+QW3fGCFXQlzQ8+M8LdR02KUH32iMWj41RO4K7A9lJQwaIVeDJsp+9Bblf/uJEm56QIoN8t/THaX4AXeoYNJ4+TeuKR2O6n6C3J2OVeadVyn7geuV994Lirv8RqkCySrKOvb47nrx9f/otZfe1v+dcZl6HtdN1wz6e0jnPv38Q5r01Y/6+acpoQ6/xvq/529SreYN9cGF92vG61/rgtHDFJ0QW+6cmKR4XfjWbVr983y91vsWfXv7aPUedpHSTu4kSXr77BF6odOg0tvYs+5Wfmau1k1bfCQOqcZJHHavXI2aKGPEYOVP/FiJdz4ixcUHnBfV/ijlvPm8dv2jf+mtcPafxfscMkLuFq2U+cBwZd43TO42HiXe+VC4D6Vmsv7qeYsAjk7+H3ryBcXHxalb56OCnvPFpB9VVFSke24brOapTTT0+qs1Y858bd66TZI09oNPdX6/M9Wv76lq07KFBg+4Uu+NnxCuQ6ix4to3V63TjtHaka8qb+k6pf/vF+UtX6/a5xwf3A7cLrV6eojyV2086OZGA/orqlZiCCN2FlfTNEV1PlZ57z4v/8Y1KvrjR/k2rVN09xODmh97/lWSy6X8L94vM25zspX31lNSbrYkybd6aXFVzM3pSZU18Iar9OvkqRrz+vtavWqtHhz1ZNDJfzBz//Gvv+nozh10/4jHwxF+jVSvfapandZFP9wzRjuWbtCSz6Zox/KNant2z/LntWuqxZ/+pilPjVfOtt1aPmmGti1aqybd20qSCrJylZ+RU3o79vr/09x3vlfG+u1H4rBqFFfzlorufpxyXntW/nWrVfDr9/JvWKOY404KONfd/igVzp0hm5NVepPfJ5NSW9E9T1DO6P/Kv2m9/OtWK/f90Yru1F0mKfkIHBVQrFLJvzEm1RgzwBjzUagDOpIG/fMyPXj3UEVFuYOes2jpcvXo2knxccUVztjYGHVo11rzFi6RtVbeZSt1Uq8epY/v2qmj5i30hjz2mi6hcxsV7cpS9qylpWNZM71KOqZ9UPOb3HSxrM+nLaMnHrAttlVTNbn1Mq0a+t+Qxes07rR2stmZ8q3cW1H0rVgkd+uOAee6WnkUc87fVDR7iqKP7yNTr9HefXjnyrd0fvGdmFjF9r9ChTN/k4oKQ34MTtG5a0f99MNvpffnzVmoZs2bqm7d2oc9t1nzprr3ods16eufdGa/PmrvaRPq8Gukhp1aKm93tjbNXlE6tmnWcjXpXv6/36bZK/TLo+NK77tjolS7ZSOlr9x0wGPrtU9V6zO6648XPw9d4A4S1bqd/FmZ8i1bVDpW5F0od/vyi4Wu1BYyCUlKHDZKtT/4Vin/HavoE0+XJJlatWVcLvm3bt47weeTJNmSr8CREFTyb4yJMcb0NcY8aYyZI2mBpBaSXgpncOHWolnTCs/JyspW89QmZcaSk5K0ZdsO5ebmqcjnK7M9JSlRObm5yszKPux4ncSdnKD8tVvKjPkyshXduF7AufEd09Ro0PlaNfS/sr79PoIzRq2eGaItr05QzoKVoQzZWeIT5d9WNuGwOVkydYJ4fa4cIpuTKRkjV1o7Jd33kqJPPKvMY6J6nKzkZz6Su10n5Y19OqSh10Qvv/GklqyZdsBtrvcXpaQka/WqdaWP9fv9ysrKVuOmjcrZY7FAcx987C65XEbZWdlq1761xk8co6G3XRf6A6xhYpMTtHvt1jJj+RnZSmpct0L76TGwn/J2Z2v5pANbV3sO+j8tGDdZBZm5hxWrU5mEJPm3lP3k2GZnyVW3frnz3Gmt5d+4TrljXtTuGy9X/vdfKvGWkXKltpB/y0b5MzMUfUKf0sfHnvkXFS6aK+XmhOU4ajS/v3reIkCwn6XvkBQj6UVJZ0gab62971APNsYMkjRIkl566mFde9XlhxtnteF2uxUTE11mLC4uVjm5uXK7iz9BiI2JKbNNknJyc5WcRJtJ0Ip8svkFZYb8ufkBe/RNlFutnrlFG598X/krNyqpR4cy2xsNOk9yu7Tp+fEhD9lRfD7Zwv2q8QX5MrHl98O62x4td8v2yn7mbvkWFCcs/jXLFPf3m1X452SpsPg1L5r9u3Ke3q7YSwYp/sZ7lfPE7eE4ihrjnjsfVfzBfjas9OX345Sfl19mODcnV4mJCQH3W1TkO+TcpqmN1a9/X9057AG9PeZDSdKP3/2i8RPf0vgPJ2r9uoO33EHy+3wqyi/781OYW6CYxPJ7/vfVsFNL9brlQk0Y8LT8hWWrxgn1U+Q5r5fGnHpbSOJ1Iuvzlf4+Kh0ryJcJ0PNfOGWyCqdMLr2fP/EjRR93omJO7qu8cW8q5/nHlDD4TsUcd6JMrTqKauNR1qN3h+MQgEMKNvlvIeksSWdL+k1SfWPMUEk/Wmvn7f9ga+1rkl6TpMLtK21oQq0e6tSqpe3pO8uMZWVlKyY6WrGxMYqPj9P2HTuV1jy1eFt28bv5mOjoA/aFQyvamaGoBnXKjLmTE+QvKL/9o8mQS1S0M1Nbx3x5wLa4NqlqctNftfj8uyLm3Xl1ZbN2y1Wr7OtjEhJlA7TnmHoNZQsLShN/SfKt8srExctVp4H8WzcUD/r98q1YrNzXHlXyE+/L1bi5/JvXHWKv2LE9/ZDb0nfsVMNGZauVyclJKtjvzXVF5zZNbSxJmvT1j6Xb5sxaIJfLpdZt0kj+y5GbnqnEBrXKjMUmJ6iooCio+fF1kvSXV4Zo+stfaM2vCw7Y3vHCE7Vp5jJlbjr0/xcon83YLVO77CcxJiHxwKJHMPtK3yFXw+KOgMKZU7V70MVyNWmuxOuHq3DBbBXOnBqSmIFgBdX2Y63daa390Fp7jbW2o6TTVfzG4cmwRlcNde3UQbPnLiy9b63VIu9yNW7YoHj70R01a97e7QsWL1V8XKxqpXAyT0VkzVqq2GYNFL3Px+AJXduqYGP5J67Vu7iPEnt2ULeF76nbwvfU4tHrlHRsR3Vb+J7qnHeS3MmJ6jjxidLtknT0d8+q8eCLwno8NY1v5WKZeo1kau9t83GntZdN31buPLtjq2RcUvTeT8dc9RvL+nzyZ6Qr9oJ/Kur4vR+Jl/bD+umHrayZ0+fouH3OQ2rdJk0ptZK1ceOWcmYFnrsnuU9I2PsJQvMWxUWPzZvKtrSgrE2zVigltb6SGu19A92oSytlbtwRcG5UXIzOHz1MWxes1tRnPj3oY4666CQt+ZyE8nAULV0kV4PGMvu0+US18RT/DitH/FXXK7bfhXsHXG6523WUf/s+P29FRTIxMXK37aDcN58PdejOUdWr+jhttR9r7Xxr7ZPW2rMCPzry5OcXKCfn4H2SfU7qpa3b0/XxhK8kSR999pV2ZWSo97HdJUn9z+qj98ZP0KbNW5WfX6DR73ykk3sfK5fL0QsrVVjhph3Kmr5YqXf9Q3K5FN+xpeqc00u7v58huV1ypxy8hWrJX0doYZ+btejsYVp09jBtfPJ9Zc9brkVnD9O2t77S/JNuKN226OxhkqRlVz2kbe9MOpKHF/Hszu3yLVug2L8OkIxLrmatFdXjJBXNmya5XFL8wV8f38rF8m/dqLh/3CJTr5FcLdsr9uJrVTTjFykvV/4tGxR3+WC5O/WUqddQcZdeL9/KxbJbqSJX1icff6GLLumvTl06yhij4XcO1pxZ87Vta/Eb6YTEBMXGxlR47uZNW/XzT1P08OMj1LpNmtp3aKvHnhql6X/M1lLvioPuD8WyNqdrw/SlOumuv8m4jBp0bKF25/TUyh/myLhdik05dEtW/5dvVnRinL4fMUbRCbGKToiVO2bvh/jJTeup4dFpWv3z/CNxKDWWTd+mosXzFf/3gZLLJXdaG0Uff4oKZkyVXO5Drs1ftHyJ4i65SlHH9JK7jUcJN90lV1Ky8r8q+0Yt/qoblD9pgnxrOPcMR16F188zxuxZyNknaYukF621P4U0qio2+t2P9PPvf+qjN587YFtiYoIeGjFM9zzylF58413t2pWhkcNvVO1aKZKk8/qdod//nKn+lw9UbGyMEhLi9fDIW4/0IdQIa+5+Re3evVdd57wld1K80j//Tbt/nKnk3p3k+fhhzWp/mfw5eWXmFG4qWzkrSs+UzS9UwfqSas3Oshdkk6SCTTvky+CE7IrKe/c5JQx7VEnPfCQTn6DCPyeraN6fcnu6KPGOp5Rx41+k/LKvj/x+5Txzl+IuvV5J970kGbeK5v+p3LeflSQVTv1eJqWO4v85TCYuQUULZyrn+UOeXoQgTP1tusa+OU5f/TBOu3dlyOV264q/Dird/s6HL2nu7IV6cNQTFZ573b9u1b0P364J37yrhIR4TZsyU4MH3nFEjivSfT9yjP769h26YdZLikmK15KJU7Xqxzlq1qujLv1opJ7rMECFOWXPt6jfobnanFFcaLpxzsul4ws+/kWThr8mSWp5amftXrs1qE8RUL6c155W0qj/qNYb/5OJT1DB7z+qaNY0RR3dTckPPqudf+8n5ZUtFBZOmay8Bo2VeOMdMvHxKvIuVOaoW2R37W3Bij7hNLmbtVDW4yOP9CEBkiRjbfkt+caYRyWtkbRO0lZJ/7XWnmiM6SVpl6T/lbQCHVRN6/nfY3v6Ts1buERtW6UddNWgRd7l2rYjXT27dgrqxLqqMrdb9X5j4oqLUVLvTvLtylT27GVVHc4R1/7sav6mJCZWUe27FC/7uWpJVUdzxHk+2VDVIQStbbtWatOulaZPm6X09F1HbG5Vui3lmKoOoVxRcTFq1quD8nZla/Mc531acs2x66s6hMBiYhV1dFfZrEz5ljnvYml1Pplcba+wmDv+4WqZX8ZffE+1/TfbI5jK/18kPS2pq6RGkvY0wP3bWntayTKgxgZ6F1HD1K9bR6ef3PuQ24/ytD2C0dRc/rwCZfw0q6rDwKEU5KtowfSqjgJBWL5slZYvW3XE5+LQivIKtHryAWtmoDopyFdRydV5gZoimOR/u7V2zJ47xpguJd/uOeW9u9MSfwAAACASBZP8l5vYW2szQhQLAAAAEBhLdldaMMm/McacKSlR0iZJwV+FBAAAAMABPB6PS9IDkgaqeCGdx71e74GrzRx6/oOSrpZUT5JX0giv1/t1oHnlrj9pjHGVPMYlqbOkyyTtaVCk1QcAAAConPsl3SnpcUk3SbrH4/FcGsxEj8dzrYrfNAyXdK6kWZI+93g8nQPNDVT5d0uabK2dJGn/hdAPci15AAAAIMwi/HRTj8eTIul2SQ97vd5n9hm7V9KHQeziH5Ke9Xq9H5Xcn+zxeM6W1F9SuRf6KLfyb60ttNYeapHtW4IIDAAAAEBZJ6q4kP7BPmMTJR3l8XgOXEP+QA0llS4r6vF4jKRoSQe/Su0+KnSRL2NMZ2vtfEmy1s42xqRJqmetZS1GAAAAOJrH46ktqfZBNu3yer279rmfKilP0vI9A16vN93j8eyW1FZSoEvb/yDpJo/H823JPm6VlCzp40Axlpv8G2Pcks6z1v6vZOhdFa/3v8dASZkq7jMCAAAAwq/6rvYzVNLBumYeUHGP/x7xknZ7vd79+5eyJDUI4nlul3SypJkl932S+nu93oBXnyy37Wefne9RsOcbY0wPFV8A7Pkg9gEAAADUdM9KanWQ27P7PS5fxQn7/qyK3xgEMkxSMxWf8HuZpO8lfeDxeLqWO0sBKv/WWp8xZt/ArCQZYy6UNELSxdbanCACBAAAAGq0ktaeXUE8dKukhh6Px+31evfNtetKyi5vosfjiZJ0h6QBXq/3k5KxjyVNlXS3it8MHFIwPf+NjDHXqPikgobGmB9U/BHDmdbaXUHMBwAAAEKn+rb9BGuuivPw41SctMvj8XSUlKDA/f4NJNWStGDPgNfr9Xs8nnmSugR64mDafvZXKOloFX+EAQAAAKACvF7vKhWfM3vHPsM3SdqpvX38h7Jdxd04x+4Z8Hg8cZL6SArY8x9M5X+ztfZNSTLGXG+tPccY00XSB8aYEdbaCUHsAwAAAMBet0n61uPxTFZxq8+5km71er1FJct9NvB6vXP3n+T1egs9Hs83kl7yeDwnqXjxnXMltZF0XaAnDeYKv9H7DFlJstbOk3S6pCeMMXwCAAAAgCPH+qvnrQK8Xu9Pkk5R8ZKf9SVdu+eCX5IGqXg5z0O5QsWrcJ6j4mtvxUu60ev1ljdHUuDKv5H03D73S6/qa63dYowZKekxBTixAAAAAEBZXq93qooT+P3H71fZpUH3375L0o2Vec5AV/j1Sfqz5GJektTHGNN3n4csk/RGZZ4YAAAAwJEVTM//ZEljjTFLVXzJ4GslfW+MaStptKQzwxceAAAAsJ/IX+2nygSz2s8SSUsl9ZX0uSSfMWaQpNckXWqt3RnG+AAAAACESDCVf0n6VtI4Fff3Hy2phaSvJQ0wxsRba4eFKT4AAAAAIRJs8n+8pEWSPlHxWcmxkn5V8Vqi0eXMAwAAAELL2qqOIGIF0/ZjJf0h6QVJ6ZJ2SLpaxcsKNbPWTgtfeAAAAABCJdjk/w0Vn+jbSdIf1tqZKr6YwEBjzGlhiw4AAABAyJTb9mOMMZJ2Sbpb0kZJW6219xlj3pb0u6SBKv4kAAAAADgyWO2n0gJV/k+W9Lm1dqWkf0tqVDJ+raRCSd9IujN84QEAAAAIlXIr/9baX/a5+7O19ouS8QJJb5Z8AtAyfOEBAAAACJVgV/vRnsR/v7EiSctDGhEAAABQHtp+Ki2YE34BAAAA1AAk/wAAAIBDBN32AwAAAFQLlrafyqLyDwAAADgEyT8AAADgELT9AAAAIKJYv63qECIWlX8AAADAIUj+AQAAAIeg7QcAAACRhYt8VRqVfwAAAMAhSP4BAAAAh6DtBwAAAJGFi3xVGpV/AAAAwCFI/gEAAACHoO0HAAAAkYWLfFUalX8AAADAIUj+AQAAAIeg7QcAAACRhYt8VVrYk/+53W4N91PgMHSd83RVh4BybOh7XVWHAESs3S56gquzZ2am6kJ/VlWHgXLUqeoAEBa0/QAAgCOOxB+oGrT9AAAAILLQ9lNpVP4BAAAAhyD5BwAAAByCth8AAABEFssJ/ZVF5R8AAABwCJJ/AAAAwCFo+wEAAEBkYbWfSqPyDwAAADgEyT8AAADgELT9AAAAILL4We2nsqj8AwAAAA5B8g8AAAA4BG0/AAAAiCyW1X4qi8o/AAAA4BAk/wAAAIBD0PYDAACAyMJqP5VG5R8AAABwCJJ/AAAAwCFo+wEAAEBEsX5W+6ksKv8AAACAQ1D5BwAAQGThhN9Ko/IPAAAAOATJPwAAAOAQtP0AAAAgslhO+K0sKv8AAACAQ5D8AwAAAA5B2w8AAAAiC6v9VBqVfwAAAMAhSP4BAAAAh6DtBwAAAJHFz2o/lUXlHwAAAHAIkn8AAADAIWj7AQAAQGRhtZ9Ko/IPAAAAOATJPwAAAOAQtP0AAAAgslhW+6ksKv8AAACAQ5D8AwAAAA5B2w8AAAAiC6v9VBqVfwAAAMAhSP4BAAAAh6DtBwAAABHF+lntp7Ko/AMAAAAOQfIPAAAAOARtPwAAAIgsrPZTaVT+AQCoQeqmNVLzY9oqOj62qkMBUA05Ovl310pU61fvUPfF76vjV08pvmNahffR+KaL5fn44YNui23ZWN2XjlNMs4aHG6pj+Xw+3TB8lD778rug5yxZukJXDByq4/pepCF3P6jdGZlltr/38QSdfv6VOqX/5Xp73P9CHbJjuJKT1OCJUWrx22dq8v6Lim7XKqh5tQb+XS3nfFfmFn/y8WUeE9uji1I/ezMcYTvSeReeo6mzv9HClVM04r5hMsaEdG7T1MZasmaaTu1zQijDrtHiUhJ06Uu3aMT80bp+4sNq1KF5UPOaHN1Sgz57UPcuHau75ryqUwafX7rN5XbpsleGasD4e3XeY9fq9j9eUJuTO4frEGo8d61EtXzlTnVZ+IE8Xz6luA4VzxEaDb5YbT/cmyNEN6mv7msnlLm1fOXOUIYNBOTo5L/1i8MV26KRFp9/p7a8PkFt3xghV0Jc0PPjPC3UdNilB99ojFo+NUTuCuwPZeXnF+iuB5/Qr9NmBD0nMytb1w0fpVZpzfXJ2BeV2riR7n3s2dLtX30/WU+99IZuv3mgxrzwuD7+/Gv99Ou0MERf8zX49whFNWuiTf+8RRnvfqKGzz4gEx/4//fYLh214z8vae3JF5TecqdML90e17OLGj59n0xMdDjDd4xjj++uF1//j1576W393xmXqedx3XTNoL+HdO7Tzz+kSV/9qJ9/mhLq8GusS56/SXVaNNDrF92nKaO/0hWv36qYhPIr9bFJ8bpyzG1a/ss8PX3iEE2483X1GXpRaYJ//D/PUlL9Wnr6xFv04tl3adpbk3T2iCuOxOHUSC2fv02xzRtp6YV3aOvrn6v16JEVyxHat1DjoZeVGUs8pr2yZy/VvE5XlN7WDH0m1KE7g99Wz1sEcGzyH9e+uWqddozWjnxVeUvXKf1/vyhv+XrVPuf4wJMlye1Sq6eHKH/VxoNubjSgv6JqJYYwYud56MkXFB8Xp26djwp6zheTflRRUZHuuW2wmqc20dDrr9aMOfO1ees2SdLYDz7V+f3OVL++p6pNyxYaPOBKvTd+QrgOocaKbpOm+BOPVfqjz6twxRplf/WjCletU0KfEwPOje3cUXnTZsqfmV16k694ybaoZk1U/6E7lfH2+HAfgmMMvOEq/Tp5qsa8/r5Wr1qrB0c9GXTyH8zcf/zrbzq6cwfdP+LxcIRfIzVol6p2p3bVF6Pe0rZlGzRvwhRtW75RHc7qGXDe3E9/149Pj1fWtt1aPGmGNi9ao2bd2kiSdq7fpomjxshXUCRJ2jh/lRLrJYf9eGqiuPbNlXLaMVp3zyvKW7pOOz/7WXnL16nW2cHnCGlP36L81WVzhMQeHZX1xwL5MrJLbzavIAxHABxaUMm/Mea0Q4w3MMZcdrBt1V1C5zYq2pWl7FlLS8eyZnqVdEz7oOY3ueliWZ9PW0ZPPGBbbKumanLrZVo19L8hi9eJBv3zMj1491BFRbmDnrNo6XL16NpJ8XHF1ZnY2Bh1aNda8xYukbVW3mUrdVKvHqWP79qpo+Yt9IY89poupkM7+TIylT9/celY/txFiu3Ssdx50a1ayJWcqAaPjVDaH1+q6advKPHs00q3+zOytPHS65U/d2G4Qneczl076qcffiu9P2/OQjVr3lR169Y+7LnNmjfVvQ/drklf/6Qz+/VRe0+bUIdfIzXt1Eq5u7O1fvby0rF1s5apefe25c5bP3u5vv33B6X33TFRqtuysbav3CRJWvLtTG1ZvFaSFF8rUSdce67mfz41DEdQ88V3aqOi3VnKmb03R8ie5VVid09Q8xsNvli2yKetoz8vM57Yo4Nq9T1OXRZ+oM5z31Gzh6+TiY0JaexAIMFW/kdKkjFmrDHmSWPMnubeSyXVCktkYeZOTlD+2i1lxnwZ2YpuXC/g3PiOaWo06HytGvpfWd9+F5kwRq2eGaItr05QzoKVoQzZcVo0a1rhOVlZ2Wqe2qTMWHJSkrZs26Hc3DwV+XxltqckJSonN1eZWdmHHa+TuJISVbR+U5kxf2aW3A3L//mJbtdShavXK/3JV7S+/1XK+t/Xqv/IXYpu1aJ4HxmZ8u93jgYCe/mNJ7VkzbQDbnO9vyglJVmrV60rfazf71dWVrYaN20UcL+B5j742F1yuYyys7LVrn1rjZ84RkNvuy70B1jDxCbHa+farWXG8jJylNy4ToX2c8K15yp3d7aWfFu2NbLX1Wfrtj9eUHytRH33nw8PO14ncicnqGDt5jJjweYIcR3S1HDg+Vpz639LP9WUJBMdpZim9bXjw++1+PTBWnnto6p1xrFqPPQQ7cMon/VXz1sECLjUpzEmRtKeJqa6kl6U9G9jzBJJp0o68yBzBkkaJEl31+6qixJbhire0CnyyeaX/ajNn5sfsEffRLnV6plbtPHJ95W/cqOSenQos73RoPMkt0ubnqdtoSq43W7F7NcrHhcXq5zcXLndxZ8gxMbElNkmSTm5uUpOok0raD6fbEFhmSGbly9XQny503K+/UU53/5Sej/jnfFKOK23Evv10a6XxoYlVCe4585HFX+w311W+vL7ccrPyy8znJuTq8TEhID7LSryHXJu09TG6te/r+4c9oDeHlOcYP743S8aP/Etjf9wotavO3hLJCS/z6+i/LI/P4W5+YqtQD95k6Nb6rQhF+r9gU/LV+grs23G+z9q69L1Ove+q3TeowP0v9teDUncTmJ9fvn3e438uflyJQZ4jaLcSnt6qDY99b7yV25Q4jF7PymwhUVacOzVpfcLt6Rr0zMfqMmtV2jT4++ENH6gPMFU/r+XdIwx5jtJ3ay1f0q6X9JVkn611hbuP8Fa+5q1tqe1tme1TPwlFe3MUFSDslUWd3KC/AUHHE4ZTYZcoqKdmdo65ssDtsW1SVWTm/6qVbc8K3HZ6SpRp1YtbU/fWWYsKytbMdHRio2NUXx8nLbv2Ls9KztHkhQTzcmlFeHbtVvuemV/flxJiQe8IQhqX9t2KCq1cahCc6Qd29O1fu3GA2/rNip9x041bFS/zOOTk5NUkB+4z7i8uU1LXrNJX/9Yum3OrAVyuVxq3abiq6I4SU56ppIalP3QPC45QUUlvfqBJNRJ0qUv36LfXpmoFb/OP2B7UX6hVv6+UBPvGaOuF57Ekp+V4EvPUHSD2mXG3MkJAX/HNb75Evl2ZWr7WwfmCAdTuCVdMU3rS27HnoKJKhDw/zZr7SmSZltrz5S00BjzmaTbJZ0iqY8xpmKfU1YTWbOWKrZZA0U3rls6ltC1rQo2bi93Xr2L+yixZwd1W/ieui18Ty0evU5Jx3ZUt4Xvqc55J8mdnKiOE58o3S5JR3/3rBoPviisx4NiXTt10Ox9+sWttVrkXa7GDRsUbz+6o2bN27t9weKlio+LVa0UToqriPx5ixXVpFGZNp+Yo9uraPO2cufVGTZQyZfuXZpQbpdiOncIOA+VN3P6HB23z3kurdukKaVWsjZu3FLOrMBz91T2ExL2foLQvEWqJGnzprItLShr/ezlqpVaX8mN9v75bNqltXZv2hFwbnRcjC5/7VZtWrhaPz37aZlt5z8+UK16710gwV9UJOv3y1KMqrDsWV7FpDZUdKN9coQugXOEun89XYk9Oqjz/PfUef57av7I9Uo69ih1nv+eko4/Wm0/eKjM45N6dlThlvQy7UEIUlWv6uOA1X5WG2NckhZK+oe19hpr7TpJr0kaGLbowqhw0w5lTV+s1Lv+Iblciu/YUnXO6aXd38+Q3C65Uw7eArLkryO0sM/NWnT2MC06e5g2Pvm+suct16Kzh2nbW19p/kk3lG5bdPYwSdKyqx7StncmHcnDq9Hy8wuUk5N70G19TuqlrdvT9fGEryRJH332lXZlZKj3sd0lSf3P6qP3xk/Qps1blZ9foNHvfKSTex8rl4uqS0X4tm5X/pwFqnPzAMnlUnT71ko8/STl/jpNcrvkSj74z0/+Qq9qX/d3xZ98nGKObq/6D94ud0qKMj/47MgegIN88vEXuuiS/urUpaOMMRp+52DNmTVf27YWJzEJiQmKPcQJh+XN3bxpq37+aYoefnyEWrdJU/sObfXYU6M0/Y/ZWupdcSQPMeJkbE7X2hlenXnHpTIuo0YdW6jjOT219IfZcrldiks5dEvW314cotikOE0c+aZiEmIVkxArd0xxB+/uDdt1/r+vVYse7VWnRUP1vf1SLZo044AWIwRWuHmHsqYvUtO7rirNEWqf01sZP0wvN0dYdvHdWnzGTfL2GyZvv2Ha9NT7ypm3XN5+w5SzaJXiPC3UZPgViu/YUvWuOEsNB12gzc9/fISPDk4XsOe/xMOS/iJpkaSukvYs//CNpIi9gsiau19Ru3fvVdc5b8mdFK/0z3/T7h9nKrl3J3k+fliz2l8mf05emTmF+1VmitIzZfMLVbC+pNK188CTFQs27ZAvgxNKQ2X0ux/p59//1EdvPnfAtsTEBD00YpjueeQpvfjGu9q1K0Mjh9+o2rVSJEnn9TtDv/85U/0vH6jY2BglJMTr4ZG3HulDqBF2PPKcGr34qJr/8JFcSQnK/maycn/9U3E9u6jx6Ke0pvdfZHPL/vzkfPuLopo2Vv37hsskxit/7iJtGnCrfNvTq+goar6pv03X2DfH6asfxmn3rgy53G5d8ddBpdvf+fAlzZ29UA+OeqLCc6/716269+HbNeGbd5WQEK9pU2Zq8MA7jshxRbqJI8foqrF36o4ZLys2KV4LJk7V0p/mqGWvjrpm3D16+KhrVJBT9nyLRh2ay3NGcSHjrlmvlI7PHv+L/nfbq/r5hc8Ukxiny14ZKuN2afE30/XNI+8d0eOqSdaNfEVt375PnWeNlSspXrsm/qaMH2cqqVcntfvoEc3tcOmBOcLm/XOEDPnzC0pzhJVXP6zmj1yvhtdfpIKN27T+wTe04z2KgziyjLXlf0RhjPlBkpFUT9IOSS0lLSgZi5I0wlo7+1DzZzS7oFp/BuKKi1FS707y7cpU9uxlVR3OEdd1ztNVHUJYbE/fqXkLl6htq7SDrhq0yLtc23akq2fXTkGd+FhVNvSt3iunmLhYxfXoIt/uTBUsWFLV4RxxvVdvqOoQgta2XSu1addK06fNUnr6riM2tyoNrN29qkMoV3RcjFr26qjcXVlaP8d5n5Zc6M+q6hACMnExSu7VSUW7spQzZ2ngCTVM97UTgr8c+BGWOfQv1TK/TH52YrX9N9sjYOXfWnuGMaadpL7W2peNMY9J+t5a+4Mxpq+kiyQdMvmv7vx5Bcr4aVZVh4EQq1+3jk4/ufchtx/lKX89bQTH5uUr9/fpgR+IKrd82SotX7bqiM/FoRXmFWjZ5LlVHQbKYfMKlDGZHAE1S7BtP5slfVvy/SuSapd8/6O19vtQBwUAAAAg9IJK/q21mZIyS75fY4w5S9JcayPkagYAAACoOSJkZZ3qKJiLfPWRtO8VRIyk/saYDZKyJMVaa78LU3wAAAAAQiSYyn8/SUWS4iXlqfhqv1bSAElLS/ZB8g8AAABUc8Gc8HuHMeYCSbdIOkPFPf+fS6prrX0yvOEBAAAA++HidZUW8MpGxpgYSadL6i/pBklbJX0kqUd58wAAAABUL8G0/fS01g4pucKvkTRO0l2SImeBawAAAABBJf8jjDF3qvjk3iskNZL0maStxpgWkqKttc67OgkAAACqBqv9VFowyf+Xkl5S8cm9HSR1knSZpJ9U/ElAtKR/hSk+AAAAACESsOdf0p+Spkq6XtIiSc0lvSWpoaSHrLX/CldwAAAAAEInmMr/PEnLVby85yhr7W5JjxhjukviVGsAAAAcWbT9VFrAyr+1ttBau9ta67fW/rTP+GxJ54U1OgAAAAAhE0zbT3n+FYogAAAAAIRfMG0/AAAAQLVhLW0/lRVU8m+MueJgw5LqhjYcAAAAAOESbOW/nYpP+DUl9/d8/044ggIAAAAQesEm/09KGiRpqbX2S2PMbZJyJI0JW2QAAADAwbDaT6UFe8Lv2ypO9heW3P9ZUoKkD8IRFAAAAIDQC7by39ha++qeO9ba6ZKmG2MuDE9YAAAAAEIt2OT/B2PMj5K+kpQuKUnSmZJmhCswAAAA4KBo+6m0YJP/mZK+lnS2pDaSMiS9bq39PFyBAQAAAAitYJP/W6y1p0uaGs5gAAAAAIRPsMl/L2PM0v3GjCRrrW0f4pgAAACAQ7K0/VRasMn/H9baPmGNBAAAAEBYBbvU5/iwRgEAAAAg7IKq/FtrXwx3IAAAAEBQaPuptGAr/wAAAAAiHMk/AAAA4BDBnvALAAAAVA/+qg4gclH5BwAAAByC5B8AAABwCNp+AAAAEFG4yFflkfwDAAAAR5jH43FJekDSQEk+SY97vd7nKrGfWyTdL6m91+vdFujxtP0AAAAAR979ku6U9LikmyTd4/F4Lq3IDjweT1NJD0m6P5jEX6LyDwAAgEgT4W0/Ho8nRdLtkh72er3P7DN2r6QPK7Cr/0paLynoC/JS+QcAAACOrBMlxUn6YJ+xiZKOKqnmB+TxePpJuljSLV6vtyjYJ6byDwAAAISAx+OpLan2QTbt8nq9u/a5nyopT9LyPQNerzfd4/HsltRW0sYAzxMj6XlJ2yRdWtIuNNbr9f4aKEYq/wAAAIgs/mp6k4ZKWnWQ29D9jiBe0m6v17t//1KWpAZB/AtcL6mNpFhJzSWdKWmyx+P5V6CJJP8AAABAaDwrqdVBbs/u97h8Fa/wsz+r4jcGgQyUtEPSUV6v92wVvxH4XtKTHo+n3M4e2n4AAACAEChp7dkVxEO3Smro8XjcXq933zcBdSVlBzG/vaTXvV7vhpLnLfJ4PG9KOktSC0krDzWR5B8AAAARpQZc5GuuivPw4yRNlSSPx9NRUoIC9PuXyFZxO9G+8kq+FpQ3kbYfAAAA4Ajyer2rJM2SdMc+wzdJ2ilpZhC7mC6p635jp0ra4PV615c3kco/AAAAcOTdJulbj8czWcWV/HMl3VrSwtNUUgOv1zv3EHOflPSlx+NZIWmypJNU/ObhtkBPSuUfAAAAkaWqV/U59Go/QfN6vT9JOkXF7Tr1JV2754JfkgZJ+qGcud9JulBSP0lfSbpR0oNer/e5QM9L5R8AAACoAl6vd6qkcw4yfr+k+wPM/VLSlxV9zrAn/+3PDuaEZVSVDX2vq+oQUI7U71+t6hBQjtpHXVbVIaAcm8o/5w1VrE7dnKoOAXAkKv8AAACIKDVgtZ8qQ88/AAAA4BAk/wAAAIBD0PYDAACAyFLBlXWwF5V/AAAAwCFI/gEAAACHoO0HAAAAEcXS9lNpVP4BAAAAhyD5BwAAAByCth8AAABEFtp+Ko3KPwAAAOAQJP8AAACAQ9D2AwAAgIjCaj+VR+UfAAAAcAiSfwAAAMAhaPsBAABAZKHtp9Ko/AMAAAAOQfIPAAAAOARtPwAAAIgorPZTeVT+AQAAAIcg+QcAAAAcgrYfAAAARBTafiqPyj8AAADgECT/AAAAgEPQ9gMAAICIQttP5VH5BwAAAByCyj8AAAAiizVVHUHEovIPAAAAOATJPwAAAOAQtP0AAAAgonDCb+VR+QcAAAAcguQfAAAAcAjafgAAABBRrJ/VfiqLyj8AAADgECT/AAAAgEPQ9gMAAICIwmo/lUflHwAAAHAIkn8AAADAIWj7AQAAQESxltV+KovKPwAAAOAQJP8AAACAQ9D2AwAAgIjCaj+VR+UfAAAAcAiSfwAAAMAhaPsBAABARLF+VvupLCr/YWLqNJC7zVFSQlJVhwIAAABIcnryn5Ck+BtGKfmFz5Q46kW5mrWq0HRXi7ZKfulzuZqmlRmPu2Kwkh54RXFXDlHyU+MUfcKZoYzaMVzJSWrwxCi1+O0zNXn/RUW3C+71qTXw72o557syt/iTjy/zmNgeXZT62ZvhCNtRfD6fbhg+Sp99+V3Qc5YsXaErBg7VcX0v0pC7H9TujMwy29/7eIJOP/9KndL/cr097n+hDtmR+p3fV5P+/FRTl3ynW+8ZLGOCr5gFM/f+J+/S4NsHhjLkGi8hJVHXvzRcz80fq3smPq7UDi2CnmtcLg0Zc7dOuPi0Q24f8dljuuC2y0MUrTOF629QwlmnKnXiWDWf/InqDBkgVeDnEQgFRyf/CYNGyNWgibIfvUX5336ihJsekGLjgpvsjlL8gDtUMGm8/BvXlA5HdT9B7k7HKvPOq5T9wPXKe+8FxV1+Iz/cldDg3yMU1ayJNv3zFmW8+4kaPvuATHzg1ye2S0ft+M9LWnvyBaW33CnTS7fH9eyihk/fJxMTHc7wa7z8/ALd9eAT+nXajKDnZGZl67rho9Qqrbk+GfuiUhs30r2PPVu6/avvJ+upl97Q7TcP1JgXHtfHn3+tn36dFobonaP7cV30n5cf1NhXPtCl/a5Wt56d9fcBl4RkrjFGt98/RJdedVG4wq+xBj4/VPVbNNS/Lxqp70ZP1E2v36nYhMC/36Jio3Xtszerc59jDvmYfjdcoPjkBH3x3MehDNlxwvE3KLbb0Wrw6N3KePdTbfrHzYrtcpSSLzs/3IdSI1lbPW+RwLHJv6tpmqI6H6u8d5+Xf+MaFf3xo3yb1im6+4lBzY89/yrJ5VL+F++XGbc52cp76ykpN1uS5Fu9VCYhSXJzekVFRLdJU/yJxyr90edVuGKNsr/6UYWr1imhT+DXJ7ZzR+VNmyl/ZnbpTb7iNcGimjVR/YfuVMbb48N9CDXeQ0++oPi4OHXrfFTQc76Y9KOKiop0z22D1Ty1iYZef7VmzJmvzVu3SZLGfvCpzu93pvr1PVVtWrbQ4AFX6r3xE8J1CI5w1aDLNfWX6Xr/zY+1dtV6PfHAc7ry2r+FZO4NwweoVZs0ffvFj+EKv0Zq2q6ZOp3aTe+PGq2Ny9brjwm/adPy9ep21rEB51758EDl5+Rr+YwlB92e6mmh/kP+qrfvfkVFBUWhDt0xwvU3KOXvFynvj1nK/HCCitZtVPqzrynl8gvCfDRAWZVK/o0xqcaYAcaYj0Id0JHiTmsnm50p38rFpWO+FYvkbt0x4FxXK49izvmbimZPUfTxfWTqNdq7D+9c+ZbOL74TE6vY/leocOZvUlFhyI+hJovp0E6+jEzlz9/7+uTPXaTYLuW/PtGtWsiVnKgGj41Q2h9fqumnbyjx7NNKt/szsrTx0uuVP3dhuEJ3jEH/vEwP3j1UUVHuoOcsWrpcPbp2UnxccfUsNjZGHdq11ryFS2StlXfZSp3Uq0fp47t26qh5C70hj91Jjuri0W8/Ti29v3DuEjVp1kS169Y67LlffPKNbvzHcGVn5YQ+8BqsRafWyt6dpZWzl5WOrZi1VK27tw8498sXPtXbd70iX5HvgG0ut0tXPzVYaxasUv3mDdXuuMB/z3Bw4fobFNOhbZlPogsWLVNUk4Zy1U4J+TEAhxJUOdoYEyPpFEnnSOorKU3Sc5JeCl9oYRafKP+2TWWGbE6WTFrbwFOvHCKbkykZI1daOyVddr3yPnxVhb9/W/qYqB4nK/6a22TzcpV9L72wFeVKSlTR+rKvjz8zSzEdy399otu1VOHq9Up/8hUVrl6nxHP6qP4jd6lg6UoVrlor/3795ai8Fs2aVnhOVla2mqc2KTOWnJSkLdt2KDc3T0U+X5ntKUmJysnNVWZWtpKTEg875prqqVcf1kmn9z5gPD+/QFFut9auXl865vf7lZOVo0ZNGmpX+u5y95ucnFTu3LWr1pczG4cSn5yg7Wu3lhnLzchWWqfWAeduW7P5kNv6XHWO0jq11h8TflP9Zg109qDzlL5xu1649nH5fVwRqSLC9TfIlZSownX77Nfvlz87V+6G9eXflRGOQ6mxWO2n8oLtRdkhKUbSi5LOkDTeWnvfoR5sjBkkaZAkPXtCB13dodnhxhl6Pp9s4X7V+IJ8mdj4cqe52x4td8v2yn7mbvkWFPc6+9csU9zfb1bhn5OlwgJJUtHs35Xz9HbFXjJI8Tfeq5wnbg/HUdRcPp9sQdnXx+bly5VQ/uuT8+0vyvn2l9L7Ge+MV8JpvZXYr492vTQ2LKEieG63WzH7nWsRFxernNxcud3FnyDExsSU2SZJObm5JP/leGTkU4o7WC+ytRr3zRgV5BeUGc7NzVNCYvk/S5JU5PNVei4Oze/zqXC/f9eC3IKgev7Lc/o/++nPib9r9C3/lSR9P+YrPfbrizruvJM07X+/BJiNMsL1N8jnky0o+9rbvLyA+wVCKdi2nxaSrpJUW9JvkjoZY4YaY7oc7MHW2testT2ttT2rZeIvyWbtlqtWnTJjJiFRNkB7jqnXULawoDTxlyTfKq9MXLxcdRrsfaDfL9+Kxcp97VFFdegmV+PmIY2/pvPt2i13vbKvjysp8YBfxkHta9sORaU2DlVoOAx1atXS9vSdZcaysrIVEx2t2NgYxcfHafuOvduzsovbSWKiOTm7POnbd2rjuk0H3tZv1q4du1S/Yb0yj09KTlRBfuCfpcOZi0PLTM9USoPaZcbikxNUVInfb/uq27S+5n63929TbkaOtq7arMZtUg9rv04Urr9BxfutW3a/iZXbL1BZQSX/1tqd1toPrbXXWGs7SjpdxZ8aPBnW6MLIt3KxTL1GMrX3/mFzp7WXTd9W7jy7Y6tkXFL03uqkq35jWZ9P/ox0xV7wT0Ud32efJyruy7T+A/szcWj58xYrqkkjufdJPGKObq+izeW/PnWGDVTypfusnOB2KaZzh4DzcGR07dRBs/c538Jaq0Xe5WrcsPiNc9ejO2rWvL3bFyxeqvi4WNVKST7isdYUc2bM1zHHdy2937J1CyWnJGnLpq3lzDr8uTi0VbOXql5qA9VutDcJTOvSRumbdhzWfnds2KbYhNjS+8blUp2m9bRr8+Ht14nC9Tcof95ixXU/unRzVItUuZIT5dvC36iKsn5TLW+RIKjk3xjjMsacsee+tXa+tfZJa+1Z4QstvOzO7fItW6DYvw6QjEuuZq0V1eMkFc2bJrlcUvzBWwx8KxfLv3Wj4v5xi0y9RnK1bK/Yi69V0YxfpLxc+bdsUNzlg+Xu1FOmXkPFXXq9fCsXy27deISPMLL5tm5X/pwFqnPzAMnlUnT71ko8/STl/jpNcrvkSj7465O/0Kva1/1d8Scfp5ij26v+g7fLnZKizA8+O7IH4GD5+QXKyck96LY+J/XS1u3p+njCV5Kkjz77SrsyMtT72O6SpP5n9dF74ydo0+atys8v0Oh3PtLJvY+Vy+XYhckO28RPvlH/v56jjp3ayxijG2+/VvNnL9L2rcUJYUJivGJiYyo1F5Wzc3O6ls9YoovuuELG5VKzjmk65pzjNO+HmXK5XYpPSajUfqeMn6x+N16oNj08qptaX5eO+qdi4mI182uWy62ocP0Nyv7qByWee4ZiPG0kY1T7+n8of6FXvh07D7o/IByC7fm3kh6Q9IMxppOkrdbaiC/95L37nBKGPaqkZz6SiU9Q4Z+TVTTvT7k9XZR4x1PKuPEvUn5e2Ul+v3KeuUtxl16vpPtekoxbRfP/VO7bz0qSCqd+L5NSR/H/HCYTl6CihTOV8/whT49AOXY88pwavfiomv/wkVxJCcr+ZrJyf/1TcT27qPHop7Sm919kc8u+Pjnf/qKopo1V/77hMonxyp+7SJsG3Crf9vQqOgrnGf3uR/r59z/10ZvPHbAtMTFBD40YpnseeUovvvGudu3K0MjhN6p2reKVLs7rd4Z+/3Om+l8+ULGxMUpIiNfDI2890odQo0yfMkvj3vpEH056Sxm7MuR2uzXwsiGl219+92ktmLtYT9x/4OsVaC4q792Rr2vo2JF6asbrik9K0PSJv2v+T7PUvtdRun3cA7rpqH8oPycv8I728fVLxRfFG/DMzardqI42r9io5695TJk7OJG0MsLxNyhvxjxlfjxRTd59Qf7MTMnl1pbBd1fF4cHBjA3yigTGmF+stacYY1ZJmi+pvqRYSS9Ya8ccal7GgDOr9yUPYmIV1b5L8bKfqw6+bnJNlj6zqiMon4mLVVyPLvLtzlTBAue9Pqnfv1rVIYTF9vSdmrdwidq2SjvoqkGLvMu1bUe6enbtpMTEylVBj4QuR11W1SEErVXbNLVqm6ZZf84NuMpPKOdWpZMS0gI/qArFxMWofa+jlL0rS6vmLK/qcI64kbV3VXUIAYXrb1B0y+aKatlM+XMWVutVflrO+a7a9rGs6lo988tWc6vvv9kelUn+f7XWnlwyliJpsrX2kJcarPbJv8NV9+Tf6Wpq8l9TRFLy70TVPfl3ukhI/p2O5L/iIiH5D9j2Y4xpKOmgl/C01mYYY6YebBsAAACA6iWYnv93Jb22z/0y77SstYNDGhEAAABQjkhZWac6CriEhrX2LGvteEldjTG/SWpjjPncGHONMcYd/hABAAAAhEJF1s+bZ609yVqbKuk6FV/463djTIMA8wAAAABUA0Et9VlS4S99o2Ct3STpfmPMJEnjjTF9rLX+MMUIAAAAlLKWtp/KCrbybyU9eMCgtVMl/YPEHwAAAKj+gqr8lyT3k/YfN8bUtdauDXlUAAAAAEIuqMq/MeYFY0xUyfejSr62lDTFGOMJX3gAAABAWdZfPW+RINi2n07W2qKS708uubjX55Kus9Z6wxMaAAAAgFAKqu1HZdf2Lyq5uNeF1toV4QgKAAAAQOiVm/wbY2KstQWSrDHmKElPSDrGGPN5yXa/pHestZ+EP1QAAABA8rPaT6UFqvyfZ4y5WVIjSSslDZE0WtINJdtrq/gKwCT/AAAAQDVXbs9/yZV9B6r4TcL/JPkk5UraLOl4a+1CSVeGO0gAAAAAhy9gz7+1dqkxZp2kuyV9oOIr+9aWdLMxpqm19oXwhggAAADsxUW+Ki/Y1X4kaZ6ksyWNk7RL0lmS+hpjLg5DXAAAAABCLGDl3xjTWNJNJRf6ypA0vGSTzxhziSr2BgIAAABAFQlmqc92krpJWniQbY9L2ijpyRDGBAAAAByS9dP2U1nBJP9+SX5jzJeS6paMpUt6X1JLa+2t4QoOAAAAQOgEk/zvucBXvLW2tyQZY36SVCBW+gEAAAAiRqCLfKVIukLS4v02tZLUWVJnY8xma+1LYYoPAAAAKMPawI/BwQU6WfdcFbf97G+XpMmSfpZ0rjGmW0ijAgAAABBy5Vb+rbXjStb477bfpp2Smqm47z9P0pqwRAcAAAAgZILp+d9jjTFmqoo/LVgkqY6kDyVdUrIMKAAAABB2rPZTecEk/9GSoq21V++/wRgTL+nfku4IdWAAAAAAQiuY5H+RitfyP4C19t/GmHqhDQkAAABAOARM/q21WyVtLWf7jpBGBAAAAJTDb2n7qaxAq/0AAAAAqCFI/gEAAACHqMhqPwAAAECVs7T9VBqVfwAAAMAhSP4BAAAAh6DtBwAAABHF2qqOIHJR+QcAAAAcguQfAAAAcAjafgAAABBRuMhX5VH5BwAAAByC5B8AAABwCNp+AAAAEFG4yFflUfkHAAAAHILkHwAAAHAI2n4AAAAQUbjIV+VR+QcAAAAcguQfAAAAcAjafgAAABBRuMhX5VH5BwAAABwi7JV/zycbwv0UQI1V+6jLqjoElGPeonFVHQLKEd/05KoOAeVItadVdQgI4P6qDgBhQdsPAAAAIgoX+ao82n4AAAAAhyD5BwAAAByCth8AAABEFFb7qTwq/wAAAIBDkPwDAAAADkHbDwAAACKKreoAIhiVfwAAAMAhSP4BAAAAh6DtBwAAABGF1X4qj8o/AAAA4BAk/wAAAIBD0PYDAACAiGJp+6k0Kv8AAACAQ5D8AwAAAA5B2w8AAAAiir+qA4hgJP8AAADAEebxeFySHpA0UJJP0uNer/e5Su5rqKShXq+3ZaDH0vYDAAAAHHn3S7pT0uOSbpJ0j8fjubSiO/F4PG0kPRLs46n8AwAAIKJYRfZqPx6PJ0XS7ZIe9nq9z+wzdq+kDyuwHyNptKSiYOdQ+QcAAACOrBMlxUn6YJ+xiZKO8ng8TSuwnxskdZb0aLATSP4BAACAIytVUp6k5XsGvF5vuqTdktoGswOPx5Om4pahwZK2BPvEtP0AAAAgovhtVUdwcB6Pp7ak2gfZtMvr9e7a5368pN1er3f/I8mS1CDIp3td0tder/dDj8fzr2BjpPIPAAAAhMZQSasOchu63+PyVbzCz/6sit8YlMvj8QyQ1FXSjRUNkMo/AAAAEBrPSnrrIOO79ru/VVJDj8fj9nq9+74JqCspu7wn8Hg8qZKeknSN1+vdXtEASf4BAAAQUfzVdLWfktaeXUE8dK6K8/DjJE2VJI/H01FSgqSNAeaeKamWpE88Hk+ZDR6Px0q62uv1vnWoybT9AAAAAEeQ1+tdJWmWpDv2Gb5J0k5JMwNM/1xS9/1u90naVPL95+VNpvIPAAAAHHm3SfrW4/FMVnGrz7mSbvV6vUUly3028Hq9c/efVLIqUPq+Yx6Pp5ukAq/XOyfQk1L5BwAAQESxMtXyVhFer/cnSaeoeMnP+pKu3XPBL0mDJP0Q0n+0ElT+AQAAgCrg9XqnSjrnIOP3S7q/Avt5Swc/0fgAVP4BAAAAh6DyDwAAgIjir+oAIhiVfwAAAMAhqPwDAAAgolT05FrsReUfAAAAcAiSfwAAAMAhaPsBAABAROGE38qj8g8AAAA4BMk/AAAA4BC0/QAAACCi0PZTeVT+AQAAAIcg+QcAAAAcgrYfAAAARBQu8lV5VP4BAAAAhyD5BwAAAByCth8AAABEFD9dP5VG5R8AgBosJSVZvXv1VFpas6oOBSXqpjVSs2PaKjo+tqpDgQOR/Jc478JzNHX2N1q4copG3DdMxgT/ljKYuU1TG2vJmmk6tc8JoQzbMXh9qrd+5/fVpD8/1dQl3+nWewZX6PUJZu79T96lwbcPDGXIjuDz+XTD8FH67Mvvgp6zZOkKXTFwqI7re5GG3P2gdmdkltn+3scTdPr5V+qU/pfr7XH/C3XIjnXJJefJu/h3bdm0QI8+cneFfoYk6ZSTe2nhgl8OGL/ssgu0asWfevbZhzR/7mS9+MK/QxVyjReXkqC/vXyL7l4wWoO+eFiNOjQPal6TTi01cMKDGrVsrO6c+6pOvun80m0ut0uXvjpU14y/V+f9+1oN//MFtTm5c7gOATgokn9Jxx7fXS++/h+99tLb+r8zLlPP47rpmkF/D+ncp59/SJO++lE//zQl1OHXeLw+1Vv347roPy8/qLGvfKBL+12tbj076+8DLgnJXGOMbr9/iC696qJwhV9j5ecX6K4Hn9Cv02YEPSczK1vXDR+lVmnN9cnYF5XauJHufezZ0u1ffT9ZT730hm6/eaDGvPC4Pv78a/3067QwRO8sJ/TuqXfGPq//Pve6Tjipv3od30ODb7w66PmnntJb4z8erdiYmDLjjRs31AvPPaq+Z16i43v1U49jz9K1A65Q926dQn0INdLFz9+kOi0aaPSF92nq6K902ehbFZNQfqU+NileV4y5Tct/madnThiiCXe8rtOGXlSa4B/3z7OUWL+WnjnxFr101l36461JOmvkFUficGocv0y1vEUCkn9JA2+4Sr9Onqoxr7+v1avW6sFRTwadXAYz9x//+puO7txB9494PBzh13i8PtXbVYMu19Rfpuv9Nz/W2lXr9cQDz+nKa/8Wkrk3DB+gVm3S9O0XP4Yr/BrroSdfUHxcnLp1PiroOV9M+lFFRUW657bBap7aREOvv1oz5szX5q3bJEljP/hU5/c7U/36nqo2LVto8IAr9d74CeE6BMcYMmSgfvjhV7308ltasWK17rzrYQ2+8Zqg5rZunaYxb/5XTz/z6gHbEhMTdPMtIzV7zgJJ0rJlK5WRkakGDeqFNP6aqEG7VLU9rau+vOctbVu2QfM/m6Ltyzeqw9k9A86b9+nv+ump8cratltLJs3Q5kVrlNq9jSRp1/pt+vKeMfIVFEmSNs5bpYR6yWE/HmBfJP+SOnftqJ9++K30/rw5C9WseVPVrVv7sOc2a95U9z50uyZ9/ZPO7NdH7T1tQh1+jcfrU70d1cWj336cWnp/4dwlatKsiWrXrXXYc7/45Bvd+I/hys7KCX3gNdygf16mB+8eqqgod9BzFi1drh5dOyk+Lk6SFBsbow7tWmvewiWy1sq7bKVO6tWj9PFdO3XUvIXekMfuNN27ddKkbyeX3p85a57S0lJVr16dgHN37tytHseepalTD/yEZ8WK1frgg72tWcOGXqfs7Fz98usfIYm7JmvSqZVyd2dr/ezlpWPrZi1Ts+5ty523fvZyfffYB6X33TFRqtuysXas2CRJWvLtTG1ZvFaSFF8rUScMPFcLPp960H0B4RLUaj/GmFOstb8YYxIkpVprl4U5rpB7+Y0n1afvSQeM5+cVKCrKrdWr1pWO+f1+ZWVlq3HTRkpP31XuflNSksud++Bjd8nlMsrOyla79q11z/236s3X3tOzTx5YpXEyXp/q7alXH9ZJp/c+YDw/v0BRbrfWrl5fOub3+5WTlaNGTRpqV/rucvebnJxU7ty1q9aXMxvladGsaYXnZGVlq3lqkzJjyUlJ2rJth3Jz81Tk85XZnpKUqJzcXGVmZSs5KfGwY67J3nv3JZ191mkHjOfl5SsqKkorV64pHfP7/crMzFZqahPt2LGz3P3u3Lkr4HO3aJGqKb99oQYN6umMvhcrLy+vouE7TlxKvHau3VpmLC8jR02Oblmh/fS+9lzl7c7Wkm/Lvjk7/uqz1feuy5S+eou+f/zDww3XkWxVBxDBgl3qc6ikXyTVknSyMeZ2SbUlGUkx1trz932wMWaQpEGSlBLfWAkxgasX4XbPnY8qPiHuwA1W+vL7ccrPyy8znJuTq8TEhID7LSryHXJu09TG6te/r+4c9oDeHlP8w/3jd79o/MS3NP7DiVq/bmPlD6iG4fWp3h4Z+ZTi4g/2+liN+2aMCvILygzn5uYpITE+4H6LfL5Kz0Xoud1uxcRElxmLi4tVTm6u3O7iTxD27SuPiyvuf87JzSX5D2DosFFKSDjw/2trrab89sUBCXlOTq6SgvgdF4y1azfo9L4X69Zh12ncB6/qmJ5nauvW7SHZd03lL/KrKL+wzFhhbr5iEg/ye/AQmnRqqVNvuVDjrn1avkJfmW0z3/9R25au1zn3X6W/PDpAn91GwQlHTsDk3xjzraSjjTHvSBouySeplaT+kr6SdO7+c6y1r0l6TZKa1D6qWrw527E9/ZDb0nfsVMNG9cuMJScnHZCUVHRu09TGkqRJX+/tV54za4FcLpdat0kjudwHr0/1lr790NXHXTt2qX7Dsj3EScmJKtjvD2eo5yL06tSqpe3pZV/rrKxsxURHKzY2RvHxcdq+Y6fSmqcWb8subseKiY4+YF8oa9u2HYfctn1Huho1blhmLCUlSflB/I4L1tKlK3T9DXfIu/h3XXB+P732+jsh23dNlLMzU0kNyrYuxiUnlPbqB5JQJ0l/e/kW/f7yRK34df4B24vyC7Xy94X6cuQY/XPcSH056i0V5uYfZE9A6AXs+bfWniVplqT7JJ2zd9jmS/KXfI1oM6fP0XH79LG2bpOmlFrJ2rhxy2HN3ZM8JiTsrd40b1H8R3PzprIfJ+LQeH2qtzkz5uuY47uW3m/ZuoWSU5K0JYh/w8OZi9Dr2qmDZs9dWHrfWqtF3uVq3LBB8fajO2rWvL3bFyxeqvi4WNVK4YTFwzFt2kydeMJxpffbtWutWrVStH7DpsPa7wUX9NPjj91TZqzI51NRUXAJrJOtn7VctVPrK7nR3s6Fpl1aa/fGQ7+J2yM6LkaXvX6rNi1crcnPflpm23n/GaiWvfeehO8rKpL1+2X9/tAF7xD+anqLBAGTf2NMJ0mJkjpIOkrF1f86Jf3/bmNMxH8+/8nHX+iiS/qrU5eOMsZo+J2DNWfWfG0r+Vg0ITFBsbExFZ67edNW/fzTFD38+Ai1bpOm9h3a6rGnRmn6H7O11LviSB5iROP1qd4mfvKN+v/1HHXs1F7GGN14+7WaP3uRtm8t/iOZkBivmEO8PoHmIvTy8wuUk5N70G19TuqlrdvT9fGEryRJH332lXZlZKj3sd0lSf3P6qP3xk/Qps1blZ9foNHvfKSTex8rl4u1Iw7HBx/8T1dcfqG6dTtaxhiNumeYps+Yoy1bildZSkxMUGxsxS8GtXChVzfc8C8NvvFqpaY20dBbBqlRw/r66usfQn0INU7G5nStne5V3zsvlXEZNerYQh3P7qmlP86Wy+1SXMqhW7IueWmIYhLj9MWINxWTEKuYhFi5Y4obLXav367zHr9WzXu2V50WDXXGHZdq8TczDmgxAsIpmJ7/AZJaSOol6RlJmyUdK2m1pJ8kvWuMudxaG7rPJ4+wqb9N19g3x+mrH8Zp964MudxuXfHXQaXb3/nwJc2dvVAPjnqiwnOv+9etuvfh2zXhm3eVkBCvaVNmavDAO47IcdUUvD7V2/QpszTurU/04aS3lLErQ263WwMvG1K6/eV3n9aCuYv1xP3PVXguQm/0ux/p59//1EdvHvh6JCYm6KERw3TPI0/pxTfe1a5dGRo5/EbVrpUiSTqv3xn6/c+Z6n/5QMXGxighIV4Pj7z1SB9CjfPzL1P16qtva+rvX2rnzt1yu936v/57lyT+/LOxmjlznu6466EK7XfZspX626UD9eijI/ToIyM0d+5C9Tv3Cm3ezCdrwfjinjG6cuydun3my4pNiteCiVO17Mc5atmro/714T16tOM1Ksgp2/zQqENztT+j+M3yHbNfKR2f8/Ev+uy2V/XLC58pJilOl74yVC63S4u/ma5JD793RI8LMNYGbsk3xoy31l5sjEmVdK619nVjzLuSnrTWzilvbnXp+Q9G23at1KZdK02fNivgKjKhnIvgOPH1qR2TVNUhBK1V2zS1apumWX/ODbjKTyjnVqV5i8ZVdQhhsT19p+YtXKK2rdIOumrQIu9ybduRrp5dOwV14n1ViW96clWHUCEeTxu1b99GU6ZMD7jKT01wT5PTqjqEgKLjYpTWq6Nyd2VpwxznfSJ8/5r3qu1Vq8Y3+Xu1zC8v3lR9/832CJj8G2NqSzrPWvu2MSZOkstam2OM+UHS/dbaX8ubH0nJP1DdRFLy70Q1NfmvKSIt+XeaSEj+nY7kv+IiIfkPplHzVUl7GnBXSxpnjPlcUo6k+40xwS4XCgAAAKAKBUzcrbWXSlJJkv+UtfbAxmoAAADgCKmWZf8IEcxqPw2NMSdYa4tI/AEAAIDIFUzLThNJvY0xt0p6TlJDFa/331jFV/nNstaec+jpAAAAAKqDYJJ/q+Kr+u55bJSk1tba040x35H4AwAA4EiKlAtqVUfltv0YY46VNETFbwD2/DvTZgUAAABEoEA9/5slvS3J7PPYfZcw4o0AAAAAECHKbfux1q4zxtRVceKfWPJ4tyRjjPlOUndjzLfW2rPCHyoAAAAg+av9avrVV7nJvzGmlqQ8Fa/v/3dJu0rmfCSpyFprjTHRYY4RAAAAQAgEOuH3BEmPSPpT0mn7bzTGSFKMpOtDHRgAAACA0ArU9vO1pK+NMf8n6W5JKyX9W1J2yUPckpLDGiEAAACwD7/o+6msgBf5KjHDWnuSpO8kbbXWrrHWrpF0qrV2bvjCAwAAABAqwSb/H5V8Pcdau90Y837J/YvDEBMAAACAMAh0wm9DSTdKyjPGXCSpY8nXNiVfax2BGAEAAIBSrDVfeYEq/1EqbvWRinv73Qf5CgAAACACBEr+20s6VcWJ/k+S0ku+7ij5mmGMaRHWCAEAAACERKDkf66kpZLWlXyNknRbyfe3SVouaWQ4AwQAAAD25TfV8xYJAi31uVPSeGNMgaTPJHWTNELSFZJ+kHSjtfaeMMcIAAAAIATKrfwbY9oZYwZIWijpWEkdJHWVdK2kTZJ6hz1CAAAAACER6Aq/OyTVlfRfSeslLZN0jqTOkjpKqm2MaWqt3RjWKAEAAIAS/qoOIIIFavtJl/SEpCeMMedLirLWfmKMGS9ptaTHJPnCHiUAAACAwxao8l/KWjthn++Xlnw7PuQRAQAAAAiLoJN/AAAAoDrgIl+VF2ipTwAAAAA1BMk/AAAA4BC0/QAAACCiRMoFtaojKv8AAACAQ5D8AwAAAA5B2w8AAAAiChf5qjwq/wAAAIBDkPwDAAAADkHbDwAAACIKbT+VR+UfAAAAcAiSfwAAAMAhaPsBAABARLFc5KvSqPwDAAAADkHyDwAAADgEbT8AAACIKKz2U3lU/gEAAACHIPkHAAAAHIK2HwAAAEQU2n4qj8o/AAAA4BAk/wAAAIBD0PYDAACAiGKrOoAIRuUfAAAAcIiwV/5vSzkm3E+Bw7DbxXvn6myTCqo6BJQjvunJVR0CypG78deqDgHlmNbpjqoOAXAk2n4AAAAQUfymqiOIXLT9AAAAAA5B8g8AAAA4BG0/AAAAiChc5KvyqPwDAAAADkHyDwAAADgEbT8AAACIKLT9VB6VfwAAAMAhSP4BAAAAh6DtBwAAABHFVnUAEYzKPwAAAOAQJP8AAACAQ9D2AwAAgIjiN1UdQeSi8g8AAAA4BMk/AAAA4BC0/QAAACCicJGvyqPyDwAAADgEyT8AAADgELT9AAAAIKJwka/Ko/IPAAAAOATJPwAAAOAQtP0AAAAgovhp/Kk0Kv8AAACAQ5D8AwAAAA5B2w8AAAAiChf5qjwq/wAAAIBDkPwDAAAADkHbDwAAACIKa/1UHpV/AAAAwCFI/gEAAACHoO0HAAAAEYXVfiqPyj8AAADgECT/AAAAgEPQ9gMAAICI4jdVHUHkovIPAAAAOATJPwAAAOAQtP0AAAAgovi5zFelUfkHAAAAHILKPwAAACIKdf/Ko/IPAAAAOATJPwAAAOAQtP0AAAAgovirOoAIRuUfAAAAcAiSfwAAAMAhaPsBAABARGGd/8qj8g8AAAA4BMk/HKluWiM1P6atouNjqzoUIKKlpCSrd6+eSktrVtWhAACC4OjkP7ZWgv7yyhDdtPB1XfnlQ6rfoXlQ8xp2aqkrPn9AQ5e/pRvnvaLjbzqvdNu1vz+j4WvfPeB29MUnh+swaqy4lARd+tItGjF/tK6f+LAaBfn6NDm6pQZ99qDuXTpWd815VacMPr90m8vt0mWvDNWA8ffqvMeu1e1/vKA2J3cO1yHUaAkpibr+peF6bv5Y3TPxcaV2aBH0XONyaciYu3XCxacdcvuIzx7TBbddHqJone2SS86Td/Hv2rJpgR595G4ZYyo0/5STe2nhgl8OGL/ssgu0asWfevbZhzR/7mS9+MK/QxWyI/h8Pt0wfJQ++/K7oOcsWbpCVwwcquP6XqQhdz+o3RmZZba/9/EEnX7+lTql/+V6e9z/Qh2yo0TVSlTH0cPVe9nb6jbpcSV0TKvwPpoPuUidP33ggPEGF56kzp/cH4IonctW01tFeDwel8fjecjj8Wz2eDwbPB7PkArOv9Xj8az3eDyFHo9nmcfj6RfMPEcn///3/E2q1byhPrjwfs14/WtdMHqYohPKrwTHJMXrwrdu0+qf5+u13rfo29tHq/ewi5R2cidJ0ttnj9ALnQaV3saedbfyM3O1btriI3FINcolz9+kOi0a6PWL7tOU0V/pitdvVUyA1yc2KV5XjrlNy3+Zp6dPHKIJd76uPkMvKk3wj//nWUqqX0tPn3iLXjz7Lk17a5LOHnHFkTicGmfg80NVv0VD/fuikfpu9ETd9Pqdik2ICzgvKjZa1z57szr3OeaQj+l3wwWKT07QF899HMqQHemE3j31ztjn9d/nXtcJJ/VXr+N7aPCNVwc9/9RTemv8x6MVGxNTZrxx44Z64blH1ffMS3R8r37qcexZunbAFererVOoD6FGys8v0F0PPqFfp80Iek5mVrauGz5KrdKa65OxLyq1cSPd+9izpdu/+n6ynnrpDd1+80CNeeFxffz51/rp12lhiN4ZPC8PVVyLRprbf4Q2vPqFjh57h1xB/I7bI6FDc7UYfskB4/XP6632z9woVfBNOGqk+yXdKelxSTdJusfj8VwazESPx3N1ybxPJV0jabukTz0eT8BKqWOT/3rtU9XqtC764Z4x2rF0g5Z8NkU7lm9U27N7lj+vXVMt/vQ3TXlqvHK27dbySTO0bdFaNeneVpJUkJWr/Iyc0tux1/+f5r7zvTLWbz8Sh1VjNGiXqnandtUXo97StmUbNG/CFG1bvlEdzir/9WnQLlVzP/1dPz49XlnbdmvxpBnavGiNmnVrI0nauX6bJo4aI19BkSRp4/xVSqyXHPbjqWmatmumTqd20/ujRmvjsvX6Y8Jv2rR8vbqddWzAuVc+PFD5OflaPmPJQbenelqo/5C/6u27X1FRyeuEyhsyZKB++OFXvfTyW1qxYrXuvOthDb7xmqDmtm6dpjFv/ldPP/PqAdsSExN08y0jNXvOAknSsmUrlZGRqQYN6oU0/prqoSdfUHxcnLp1PiroOV9M+lFFRUW657bBap7aREOvv1oz5szX5q3bJEljP/hU5/c7U/36nqo2LVto8IAr9d74CeE6hBotwdNMdU/vruV3va4c73pt+/RX5SzboHr9Av+OkyS5XWr/35uUu2pTmeFavY9S2u2XacPrX4YhakQSj8eTIul2SQ97vd5nvF7v/0ru3xvEXFfJ4273er1DvF7vO5LOkxQjqX+g+YeV/BtjLjfGtD2cfVSVhp1aKm93tjbNXlE6tmnWcjXp3qbceZtmr9Avj44rve+OiVLtlo2UvnLTAY+t1z5Vrc/orj9e/Dx0gTtE006tlLs7W+tnLy8dWzdrmZp3L/9/t/Wzl+vbf39Qet8dE6W6LRtre8nrs+TbmdqyeK0kKb5Wok649lzN/3xqGI6gZmvRqbWyd2dp5exlpWMrZi1V6+7tA8798oVP9fZdr8hX5Dtgm8vt0tVPDdaaBatUv3lDtTuuY0jjdqLu3Tpp0reTS+/PnDVPaWmpqlevTsC5O3fuVo9jz9LUqQdWp1esWK0PPtjbVjJs6HXKzs7VL7/+EZK4a7pB/7xMD949VFFR7qDnLFq6XD26dlJ8XHH1OTY2Rh3atda8hUtkrZV32Uqd1KtH6eO7duqoeQu9IY/dCZI6t1bhrixlztr7Oy5jxlKl9Aj8O04qbvexRT5tePWLMuO5Kzdp9lm3K2f5hpDG60T+anqrgBMlxUn6YJ+xiZKO8ng8TYOYf6Gkl/a5ny7Jp+I3AOUKaqlPY0y8io9pTzuTS5KRVFvSl5I8weynOolNTtDutVvLjOVnZKthp5YV2k+Pgf2Utztbyycd+Mex56D/04Jxk1WQmXs4oTpSbHK8du73+uRl5KhJBV+fE649V7m7s7Xk27KvT6+rz9aZd16m9NVb9N1/PjzccB0nPjlB2/d7fXIzspXWqXXAudvWbD7ktj5XnaO0Tq31x4TfVL9ZA5096Dylb9yuF659XH4f13M8lPfefUlnn3XaAeN5efmKiorSypVrSsf8fr8yM7OVmtpEO3bsLHe/O3fuCvjcLVqkaspvX6hBg3o6o+/FysvLq2j4jtSiWTB/28vKyspW89QmZcaSk5K0ZdsO5ebmqcjnK7M9JSlRObm5yszKVnJS4mHH7CTulATlrdlSZsyXka2Yzq0Czk3omKZm1/9Fc869W8k9y75ZKNhS/s8cIp/H46mt4vx4f7u8Xu+ufe6nSsqTVFrl9Hq96R6PZ7ektpI2Huo5vF6vX9Kc/YZPlxQtaUqgGIOt/H8p6RtJm0q+fi3pC2vty5LW7f9gY8wgY8wMY8yMaVnL9t9cLfh9PhXlF5YZK8wtUExi8Ku/NOzUUr1uuVDf3/2m/IVlq5gJ9VPkOa+XZr05KSTxOo3f5z/I65MfVE/5Hk2ObqnThlyoiSPflG+/12fG+z/qvQFPyriMznt0QEhidhK/z6fC/IIyYwW5BRV6fQ7m9H/2058Tf9foW/6rif8dr8cvGaXWx7TXceeddFj7remGDhulHseedcDthJP6q6io6ICEPCcnV0mJCSF57rVrN+j0vhdrzFvjNO6DV9WwYf2Q7BcHcrvdiomJLjMWFxernNxcud3FnyDse25GXFzx37OcXApQFWWL/PLv9zfIl5Mvd2L5v+NMlFue527Smv+MU+6KQ+ZuqNmGSlp1kNvQ/R4XL2m31+vd/zzhLEkNKvKEHo/HSHpA0u9er3d6oMcH3fZjre0jaZa19vSS7/ecqXJAOc5a+5q1tqe1tmevpHbBPsURlZueqcQGtcqMxSYnBN1jHF8nSX95ZYimv/yF1vy64IDtHS88UZtmLlPmpvSQxOs0OemZStrv9YmrwOuTUCdJl758i357ZaJW/Dr/gO1F+YVa+ftCTbxnjLpeeBJLflZQZnqmUhrULjMWn5ygooLCg08IUt2m9TX3u72f0uRm5Gjrqs1q3Cb1sPZb023btkNr1qw/4LZ27QZt35GuRo0blnl8SkqS8vd783Y4li5doetvuEPZ2Tm64PygFptAJdSpVUvb08tWjrOyshUTHa3Y2BjFx8dp+z6f5mRl50iSYqLLvmFAYEXpGYppWLvMWFRKgvwB/gY1H/pXFe7M1MY3vg5jdJCKL/JVHW+SnpXU6iC3Z/c7hHwVt+nsz6r4jUFF3CTpeEnDg3lwRXv+y7w7McXrxdWt4D6qhU2zVigltb6SGu3te23UpZUyN+4IODcqLkbnjx6mrQtWa+oznx70MUdddJKW0EteaetnL1et1PpK3uf1adqltXZvCvz6RMfF6PLXbtWmhav107NlX5/zHx+oVr33nmDnLyqS9ftl/bSUVMSq2UtVL7WBajfa++Of1qWN0oN4fcqzY8M2xe6zopNxuVSnaT3t2nx4+3WyadNm6sQTjiu9365da9WqlaL1Gw48T6kiLrignx5/7J4yY0U+n4qKOEk7XLp26qDZcxeW3rfWapF3uRo3LC4Sdj26o2bN27t9weKlio+LVa0UFjWoqIyZSxXXrIFiGu/9HZfUtY0KNpa/eEejv52qlJ4e9faOVW/vWLV9bKBqHddBvb1jFZvKp2JO4PV6d3m93tUHue3a76FbJTX0eDz7n/hTV1J2sM/n8XiOkvRvSY95vd6gTroKmPwbY2ZLOsYYM1XSccaYKSXf95A0TdLsYAOsTrI2p2vD9KU66a6/ybiMGnRsoXbn9NTKH+bIuF2KTTn0R+L9X75Z0Ylx+n7EGEUnxCo6IVbumL2nTyQ3raeGR6dp9c8HVpwRnIzN6Vo7w6sz77hUxmXUqGMLdTynp5b+MFsut0tx5bw+f3txiGKT4jRx5JuKSYhVzD6vz+4N23X+v69Vix7tVadFQ/W9/VItmjTjgBYjlG/n5nQtn7FEF91xhYzLpWYd03TMOcdp3g8z5XK7FF/O61OeKeMnq9+NF6pND4/qptbXpaP+qZi4WM38muUKK+uDD/6nKy6/UN26HS1jjEbdM0zTZ8zRli3FK8QkJiYoNrbin3wtXOjVDTf8S4NvvFqpqU009JZBatSwvr76+odQH4Kj5OcXKCfn4G06fU7qpa3b0/XxhK8kSR999pV2ZWSo97HdJUn9z+qj98ZP0KbNW5WfX6DR73ykk3sfK5fLsQv7VVrBpnTt/nOJWo78u+RyKfGoNNU/93jt+G6m5HbJfYjfcXPPH6WZpw7VrL63aVbf27TmiQ+VOXeFZvW9Tfmb6QRAGXNVfO5taXXG4/F0lJSgcvr99+XxeJIlfaLiXPz+YJ844Am/1truxpgfrbWnG2O+s9aeKUnGmJ9K2n8i1vcjx+ivb9+hG2a9pJikeC2ZOFWrfpyjZr066tKPRuq5DgNUmJNfZk79Ds3V5oziX7Q3znm5dHzBx79o0vDXJEktT+2s3Wu3BvUpAg5t4sgxumrsnbpjxsuKTYrXgolTtfSnOWrZq6OuGXePHj7qGhXs9/o06tBcnpLX565Zr5SOzx7/i/5326v6+YXPFJMYp8teGSrjdmnxN9P1zSPvHdHjqineHfm6ho4dqadmvK74pARNn/i75v80S+17HaXbxz2gm476h/JzKnby59cvFa8eM+CZm1W7UR1tXrFRz1/zmDJ3ZITjEBzh51+m6tVX39bU37/Uzp275Xa79X/9/166/fPPxmrmzHm6466HKrTfZctW6m+XDtSjj47Qo4+M0Ny5C9Xv3Cu0efPWwJNxSKPf/Ug///6nPnrzuQO2JSYm6KERw3TPI0/pxTfe1a5dGRo5/EbVrpUiSTqv3xn6/c+Z6n/5QMXGxighIV4Pj7z1SB9CjbH8ztfU6YN71Gv+aLmT47VtwhTt/H6Wap1wtLp8+oB+b32l/Pv9jivYr9W3MD1D/vxC5a/bdiRDd4SKXlCruvF6vas8Hs8sSXeoeOUeqbh9Z6ekmYHmezyeKEnjVfxJQV+v1xv0x67G2sD/fPsk/99aa8/adyzQ3KdaXFmtX5+ouBg169VBebuytXnOisATapjdrmr98ig6LkYte3VU7q4srXfg67NJoevLDoeYuBi173WUsndladWc5YEn1DBjNgZcVKHa8HjaqH37NpoyZXrAVX5qityNv1Z1CGGxPX2n5i1corat0g66atAi73Jt25Gunl07KTFEJ3aHw7ROd1R1CAG54mNUq/fRKtqZpczZ1XMBk3A6efP4anslsmEtL6uWCcwzq8cF/W/m8Xj6SPpW0u8qbvU5V9KtXq/3mZLlPht4vd65h5g7StKDkm6T9PM+m7Z7vd7V5T1vUEt9SvIbY1ZKqmWMWaridqEGxpg4a21Er+tWlFeg1ZPnVXUYOITCvAItm3zQ/+9RDRTkFWjB5DlVHQaC4PWukNfrvDfQNVH9unV0+sm9D7n9KE9EXn6nWvLnFmjnjxHZ3YwI4PV6f/J4PKdIuk9SfUnXer3eN0o2D1LxJwGHOllkz+Wjn9xvfKykf5X3vEEl/9bavsE8DgAAAAi3mrJMh9frnSrpnIOM369y+vi9Xm+Xyj5nhc4CMsa4jTED9rl/tTGG09cBAACACBBU8m+MOc8YE22t9Un6e8lYlKQ0SaPDGB8AAACAEAm28n+apGnGmNIF0q21Rdba+yWlhCEuAAAA4KBsNf0vEgTb83+rMaazpN2SmhpjrinZVFdSRJ/wCwAAADhFwOTfGPOQpD1XHDHau7SqkZQuaWhYIgMAAAAQUsFU/peobHW/UNIySXOttVx5BwAAAEdUTVntpyoE7Pm31r5nrf1E0nZJ81V82eG/SppsjLkuzPEBAAAACJFgV/t5UNJ/JSVLWmutHSrpREmXGGP6hy88AAAAAKES7BV+31LxJYR9KnnDYK3NNcYMkzRG0hdhiQ4AAADYjz9CVtapjoKq/FtrV1pri1R8ku8z+4zPl/RCmGIDAAAAEEJBX+HXGOOW1F/SPGNMD2NMoiRZa98KU2wAAAAAQqjcth9jTJqkRpIukvS2pMGSVkl6X9IXxpjdkupL6m+t3RXeUAEAAADR9HMYAvX8+yRdIym25PuekuqoOOFfIOlHSf0ktZI0O3xhAgAAADhcgdp+LlVxst9V0tmS/pQ0zlp7saQdkq6z1g6y1pL4AwAAANVcoMr/Kyq+yNflkuIlHScpzxhTW1ItcY0FAAAAHGGs9lN5gSr/zSX1kbRT0peSZkiaquIr/j4hKS6s0QEAAAAImXKTf2vtEkmFknapuPqfLylFxW1AgyQtMcZcEuYYAQAAAIRAMEt99pH0jor7/beWfJ8q6d2S7/8TtugAAACA/fir6S0SBHOF30aS7peUvM/3TUu+Lpb0f+EJDQAAAEAoBUz+rbWtJMkY08da+9OecWNMkqS/SLpQ0qKwRQgAAAAgJIK+wq+kByXJGPNXSbLWZklaKulfoQ8LAAAAODhbTf+LBAGTf2NML2PMK5IyjTEuSecZYz43xtS11s6UtDrcQQIAAAA4fMFU/rtKekiSrLV+a+0/JT0s6RNjTGsVr/8PAAAAoJoLpuf/VUkyxiQYY34sGTYlX+dImhie0AAAAIADRcrKOtVRucm/MaatpO8lLZPkUfHSnr9J+tpaW2iMGaTiC4EBAAAAqOYCtf2skNRWUj9JCyT9LOkESbOMMTdLelPFy38CAAAAqObKrfxba62kIkkyxhRaa7+U9KUx5mFJj0r6WsVLfQIAAABHRKSsrFMdVWSpz5Q931hrs6y1QyT9JGlCyKMCAAAAEHLBXOF3j8v2H7DWPmqM+S6E8QAAAAAIk6CTf2vt+kOMTw9dOAAAAED5WO2n8irS9gMAAAAggpH8AwAAAA5RkZ5/AAAAoMr5Lav9VBaVfwAAAMAhSP4BAAAAh6DtBwAAABGFpp/Ko/IPAAAAOATJPwAAAOAQtP0AAAAgovhp/Kk0Kv8AAACAQ5D8AwAAAA5B2w8AAAAiiqXtp9Ko/AMAAAAOEfbK/zXHrg/3U+AwrJ5eq6pDQDnq1M2p6hBQjlR7WlWHgHJM63RHVYeAcvRa8J+qDgFwJNp+AAAAEFH8VR1ABKPtBwAAAHAIkn8AAADAIWj7AQAAQEThIl+VR+UfAAAAcAiSfwAAAMAhaPsBAABAROEiX5VH5R8AAABwCJJ/AAAAwCFo+wEAAEBE4SJflUflHwAAAHAIkn8AAADAIWj7AQAAQESxltV+KovKPwAAAOAQJP8AAACAQ9D2AwAAgIji5yJflUblHwAAAHAIkn8AAADAIWj7AQAAQEThIl+VR+UfAAAAcAiSfwAAAMAhaPsBAABARLGs9lNpVP4BAAAAhyD5BwAAAByCth8AAABEFC7yVXlU/gEAAACHIPkHAAAAHIK2HwAAAEQUa2n7qSwq/wAAAIBDkPwDAAAADkHbDwAAACKKv6oDiGBU/gEAAACHIPkHAAAAHIK2HwAAAEQUy0W+Ko3KPwAAAOAQJP8AAACAQ9D2AwAAgIjip+2n0qj8AwAAAA5B8g8AAAA4BG0/AAAAiCjW0vZTWVT+AQAAAIeg8g8AAICIwgm/lUflHwAAAHAIkn8AAADAIWj7AQAAQESxtP1UGpV/AAAAwCFI/gEAFVI3rZGaHdNW0fGxVR0KAKCCHN32YxKTlHDD7Yru2lO+TeuV8+Lj8q1ZGXBe3MX/UPzlA8qMZT16twpnTpXiE5Rw1fWK7n68FBOjwmm/KPfd12VzssJ1GDWWu1aimj9+k1JO7qb81Ru1ZvhzyluypkL7aDT4YiWf0k3LL71HkhTdpL46/fFGmcfs/GqKVl//eMjidgpXcpLq3TtM8b17qHDtBm2/70kVLlsVcF6tgX9XncH/KjO25eZ7lPvrH5KkhLNOVZ2br5ErOUlZn36lnc+/KbGec4XFpSTovMcHqs3JnbVj9WZNuO1VbVmyLuC8Jp1aqv8j16jxUWkqyMnTlNe/0q8vTJAkudwuXfLSEDU/pp1ydmYqpUk9fXzjc1rx6/xwH06NFFUrUe2eul61T+2q3JWbtHToS8pZXLHfcc2HXKTap3XV/IvuKzPe4MKT1PjKvpr/1/tDGLGz+Hw+3XTH/Tr79FN0wf+dGdScJUtX6MEnntfyVWvV69hueujuYaqVkly6/b2PJ+iNdz9Wkc+na6/8m6667MJwhV/j+fm7UGmOrvwnDrtXrkZNlDFisPInfqzEOx+R4uIDzotqf5Ry3nxeu/7Rv/RWOPvP4n0OGSF3i1bKfGC4Mu8bJncbjxLvfCjch1IjtXz+NsU2b6SlF96hra9/rtajR8qVEBf0/Lj2LdR46GVlxhKPaa/s2Us1r9MVpbc1Q58JdeiO0ODfIxTVrIk2/fMWZbz7iRo++4BMfODXJ7ZLR+34z0tae/IFpbfcKdOLt3U7Wg0evVsZ736qTf+4WbFdjlLyZeeH+1BqpIufv0l1WjTQ6Avv09TRX+my0bcqJqH8Sn1sUryuGHOblv8yT8+cMEQT7nhdpw29SG1O7ixJOu6fZymxfi09c+Iteumsu/THW5N01sgrjsTh1Eiel4cqrkUjze0/Qhte/UJHj72jQr/jEjo0V4vhlxwwXv+83mr/zI2SMaEM11Hy8wt014NP6NdpM4Kek5mVreuGj1KrtOb6ZOyLSm3cSPc+9mzp9q++n6ynXnpDt988UGNeeFwff/61fvp1WhiiB8rn2OTf1bylorsfp5zXnpV/3WoV/Pq9/BvWKOa4kwLOdbc/SoVzZ8jmZJXe5PfJpNRWdM8TlDP6v/JvWi//utXKfX+0ojt1l0lKDrhf7BXXvrlSTjtG6+55RXlL12nnZz8rb/k61Tr7+OB24HYp7elblL96Y5nhxB4dlfXHAvkysktvNq8gDEdQs0W3SVP8iccq/dHnVbhijbK/+lGFq9Ypoc+JAefGdu6ovGkz5c/MLr3J55ckpfz9IuX9MUuZH05Q0bqNSn/2NaVcfkGYj6bmadAuVW1P66ov73lL25Zt0PzPpmj78o3qcHbPgPPmffq7fnpqvLK27daSSTO0edEapXZvI0natX6bvrxnjHwFRZKkjfNWKaEev9sqI8HTTHVP767ld72uHO96bfv0V+Us26B6/Y4Nbgdul9r/9yblrtpUZrhW76OUdvtl2vD6l2GI2jkeevIFxcfFqVvno4Ke88WkH1VUVKR7bhus5qlNNPT6qzVjznxt3rpNkjT2g091fr8z1a/vqWrTsoUGD7hS742fEK5DAA4pYPJvjHEZYxLL2fa30IcVflGt28mflSnfskWlY0XehXK3L/8H3ZXaQiYhSYnDRqn2B98q5b9jFX3i6ZIkU6u2jMsl/9bNeyf4fJIkW/IVwYnv1EZFu7OUM3tp6Vj2LK8Su3uCmt9o8MWyRT5tHf15mfHEHh1Uq+9x6rLwA3We+46aPXydTGxMSGN3gpgO7eTLyFT+/MWlY/lzFym2S8dy50W3aiFXcqIaPDZCaX98qaafvqHEs0/bZ79tSz8FkKSCRcsU1aShXLVTQn4MNVmTTq2Uuztb62cvLx1bN2uZmnVvW+689bOX67vHPii9746JUt2WjbVjRXGCueTbmdqyeK0kKb5Wok4YeK4WfD41DEdQ8yV1bq3CXVnKnLWsdCxjxlKl9Ggf1PzmQy6SLfJpw6tflBnPXblJs8+6XTnLN4Q0XqcZ9M/L9ODdQxUV5Q56zqKly9WjayfFxxV/ehMbG6MO7Vpr3sIlstbKu2ylTurVo/TxXTt11LyF3pDH7hS2mt4iQTA9/y0lXWyMmS6pzn7bjKR/SPooxHGFnUlIkn9L2aqwzc6Su3X5v3jdaa3l37hOuWNelG/DWsWcdIYSbxmpjNXL5d+yUf7MDEWf0EcF302UJMWe+RcVLpor5eaE7VhqIndyggrWbi4z5svIVkKnNgHnxnVIU8OB52vp+Xco8Zi9bxZMdJRimtbX1tGfa+dnPyumRSO1fG64fJk52vT4OyE/hprMlZSoovVlK47+zCzFdCw/uYxu11KFq9cr/clXVLh6nRLP6aP6j9ylgqUrVbhqrVxJiSpct89+/X75s3Plblhf/l0Z4TiUGikuJV47124tM5aXkaMmR7es0H56X3uu8nZna8m3ZVsfjr/6bPW96zKlr96i7x//8HDDdSR3SoLy1mwpM+bLyFZM51YB5yZ0TFOz6/+iOefereSeZf9mFWzZGdI4napFs6YVnpOVla3mqU3KjCUnJWnLth3Kzc1Tkc9XZntKUqJycnOVmZWt5KSD1liBsAim7adIkk/SKEldJZ0l6WFJF0nqpIO80THGDDLGzDDGzHhr1cb9N1cL1ueTCsu2e9iCfJkAPf+FUyYrY+i/VLRgtuzOHcqf+JGKvAsUc3JfqaBAOc8/pvjLByhp5L+V/J9XFXPS6cr/bFw4D6VGsj6//PmFZcb8uflyJQboh41yK+3podr01PvKX1m28mULi7Tg2Ku19dX/qXBLurKnL9amZz5Q3QtPC23wTuDzyRaUfX1sXr5cCeX//OR8+4s2/vVa5U2fI9+2Hcp4Z7zy5y5UYr8+++x3v5/LvLyA+0VZ/iK/ivb7+SnMzVdMoJ+ffTTp1FKn3nKhvhjxpnyFZT+5nPn+j/rgmidlXEZ/eXTAIfaA8tiiA3/H+XLy5Q7wGpkotzzP3aQ1/xmn3BXV8++rU7ndbsXERJcZi4uLVU5urtzu4k8QYmNiymyTpJzc3CMXJKAAyf//t3fn8VHV1//HX2dCQhKC7Isii4AOiIALKFgXLLhWsT+rxf1r60atVq3UpeKCVVttbW211q/iQt3RKn5Rq4hKtYhfFQQUcZSKu6gQ9iUh5Pz++NyBSQjZviRkuO8njzySuXM/N3dyuTPnns/5fK6ZNSME+gcAOwLPAq8B3wBvAs9U1c7d73L3Qe4+6Ixd6n713Bh8xXKsddsKy6ywBb5+/RZaVLOt4iUkOoar+fUzZ7D8nONZ8/f/hvXrWf/eO2EWIKmTDcUryO3QusKynJaFmwWclXW+4AQ2LFvJ4vtrV++6/pti8nZqDzmxHf5SLxuWLSenXcWOwERRixqPT5Xb+m4Jzbp0zthuxfMy0aJ+242zNUtXUtShVYVl+S0LN9bq16SwTRE//tuFTP/b5Cpn8ikrWc/H0+fx7JX3MeC4AzTlZz2UFa8gr2PrCsua7VBIeQ3HqOtFP2L90pV8dc8/G3DvpD7atGrF4uKKPS+rVq0mLzeX5s3zKCjIZ/GSTc+vWh0qAvJyK14wSO2U403yKxvUJuJ5DSittK5X+p51yj58n0SHzljb9huXNeuVxJd8W00rKDh9NM2PzJiaK5FDzq59KV+c0X1bVobl5ZHTuw9r771ta+96LKyelSKvS0dyO20KBAsH9Kb0q8XVtmv7o+/TYp8+9H/3Ifq/+xBdbxhN0eDd6f/uQxTt14/ej1ScealoUF/Wf1O8ccCp1E7J3Pk027ETOR3bbVyW1283yhZ9V227NhefTctRGbP35CTI699nY7uSufPJ36vfxqebdetComULNnxT/Xaloi9mLaB1l/a07LTpAm2nAT1Z/tWSGtvm5udx4t2/5Ot5nzDt1icrPDfy5rPpMXTTuKgNZWV4eTlervOnrlbM/JD8nTuQ13nTe1zRwF41vsd1+vHB7DAoydDUBIamJtD7t2fTat8+DE1NoHmX9tW2lYY1cI8+vDNn3sbH7s77qQV07tghPN+vL7Pmbnr+vfkfUpDfvMJUoCKNodrg393LgCnAW8CXwG3AZUB/4GfAHQ29gw3Fi7+jbP67FJxyNiQS5HTvRe5+B1H69gxI5GCFRVW2K1vwAfknnE6zvYeQ0ytJ4fmXkyhqSclzFT8kC07/GSUvPF2r+wbI5tYvWsKqt95np8tPh0SCgr49aH3EUFa89BbkJMjZoer6yI+Ov4L5w88ndeTFpI68mK9veZg1cxeQOvJi1ry/kPxkN3a85GQK+vag3cmH0fGcH7Lotscb+dVlvw3fLqZk9nu0ueBMSCTI3a0nLb5/AGtfewNyEiRaVn18SualaH3uKRQcuC95/Xaj/XW/ImeHHVj5yCQAVj/3Ei2OGk5esheY0Xr0aZTMS7FhieqY62LFomI+eyvFiMtGYQmjU99u9D18EB++/A6JnAT5OxRuse0Jd/yCvBb5PPPre8krbE5eYXNy8sLwsOVfLGbkTWfRddButOnWkeGXjmL+829vVmIkNSv9upjlb35AjytPgUSCFrt3p/1R+7HkxZnRe1zVx2jOsVcx8+CLmDViDLNGjOHT3z/Gyjn/YdaIMZQsKm7kVxE/JSWlrFlTdZnOIQcM4dvFxTz+9HMATJz0HMtWrGDo4L0AOPqwQ3joiaf5etG3lJSUMv6BiRw4dDCJhHqepXHVZsBvV2C2u/+h8hNmliCUAmWlNXf9kaKrbqbVPU9hBYWUTn+Zsllv0KzfnrS87laWnnIkrKt4kq9/fRrrOnSmxXmXYgUFlKXmsfKqC/Flm950c/cfRs7O3Vh105WN/ZK2K59feSe9/34N/WdNIFFUwLLJ/2bFyzMpGrIHu068gTl9RlG+Zl2FNusXVcxslhWvoLyklNIvQo/Oxz+5nq43jKbj6OMo/eo7vrjuHpY89EKjvabtyZIb/kKnv95I15cmkigqZPXz01j72pvkDxpA5/G38OnQY/C1FY/Pmimv0mynzrS/5hKsRQElc97n6zN/yYbF4fxZ9/ZcVj4+mR0fvJ3ylSshkcM3P79iW7y8rPfM2Ps4dcJl/Grm32heVMB7k2fw0cuz6TGkL2c8NpYb+/6U0jUlFdp06tOV3YaHQOXSd+7cuHz2468yacx/8+rtk8grymfUnReRyEkw//m3eOH6hxr1dW1PFlx2F3s8MpYh744np2UB3z39OkunzqLV/v0Y8OQ4pvc8dbP3uNKvKwb464tXUF6ynpLP1TvWGMY/OJF/TX+Tiff+ZbPnWrQo5De/vpixN9zCX+95kGXLVnDlJefRulWYrWzkkcOZ/uZMjj7pbJo3z6OwsIDrr/xlY7+E7Ua2lNg0RebV3CHNzJoDk4B1wPwqVkkA7d39rC1tY+mPhjXto5PXnGb9BuKrVrLho6pe4vbtk7da1bzSNmT5ebQcsgdly1axZvaHNTfYzrRp27RnibL85uTvM4ANy1dS+t4HW227uT260qzHzpTMntekZ/m5f2nHbb0L1crNz6P7kL6sXbaKL2f/Z1vvTqMbXlJS80rbWKIgj1ZD+1G2dBUr3/mo5gbbkSHv3bytd6FBLC5eytx5H9B7l+5Vzhr0fmoB3y0pZtDAPWjRYsu9cE1BbvueTfZOcUO7HNIk48sZX77SZP9madUG/xtXMusJ3AgMAC4C0ulVA5q7+/QttW3ywX/MNfXgP+6aevAfd009+I+7bAj+42x7Df63Jwr+6y4bgv/alP3g7h8DJ5rZ8cBn7r71UnwiIiIiInVQm+S1VK1Wwb+ZdQU6Ax8AZWbWhVAKtNrd11XbWEREREREmoRaBf/AOUB3oATIjb7ygA5m9pG7n91A+yciIiIiIltJbYN/gKvc/VMzKwIucfdxZmbAFw20byIiIiIim9FsP/VX4+SyZtaHcDMvN7PjgBsIpT+neii4OqaB91FERERERLaCajP/ZlYI/AHYC1gWfV1KuOPvv8xsrrvPauB9FBERERGRraCmO/yucfejgV2BVYS7+uZHGf+fAbrtpoiIiIg0Km+i/7JBre4p7e5rgJOAA919uZnlAuPc/fMG3TsREREREdlqahzwa2bTCWU+ewLPhTG+GNDfzHZy968adA9FRERERGSrqM1sP4cBG4CXgR8A5dHyk4EzCHf+FRERERFpFLrJV/3VGPy7+2oAMxtHuLGXAaOAKYSBwCIiIiIikgWqrfk3s4SZ/cLMBgLvRgN9HTjL3b9092caZS9FREREROT/rNrMv7uXm9lIYBHwiJn9HbiFTaU/IiIiIiKNSjf5qr/azPZT7u4TCQN+C4GBoL+4iIiIiEi2qc2A313M7NfRzyXA4UCPaJkBzd396obaQRERERER2TpqE/yvAVLRz04I+NdGywxo3jC7JiIiIiKyOc32U3+1Cf6/cfd/mNmuwO+AMcC37v6Pht01ERERERHZmmpT858ws2OAScCD7r4Q1fyLiIiIiGSdajP/ZpYAJgPTgH3dfbWFW/zmNMK+iYiIiIhsZnuY7SeZTCaAccDZhBvq3pRKpf5Sh/aHAH8EehHuv3V2KpVaWlO7ajP/7l7u7n9295Xpm31FflfbHRMRERERkc1cC1wG3AScD4xNJpOjatMwmUz2A54FFgLHA7nAQ7VpW5uynwo8eLGu7UREREREBJLJ5A7Ar4DrU6nUn1Kp1FPR49rOoHkl8AXw41QqNQU4FTggmUwOrqlhnYN/EREREZFtyZvovzr4HpAPPJKxbDKwezKZ3KkW7YcDj6dSqTKAVCq1EngFGFFTQwX/IiIiIiKNqwuwDliQXpBKpYqB5UDv6homk8lmQEfg3UpPLQR2rekX12aqTxERERERqUEymWwNtK7iqWWpVGpZxuMCYHkqlarcXbAK6FDDrylIb7OKtr1q2kcF/yIiIiKSVcqb7k2+LgKuqWL5OMIA37QSwgw/lTmbgvstKYm+V25fm7Yq+xERERER2UpuBXap4uvWSut9C3RMJpOVp89vC6ymGqlUqpRQHlR5bEC7mtqCMv8iIiIiIltFVNqzrBarziHE4fsCMwCSyWRfoBD4qpbt9wcmZCzbB5hVU0Nl/kVEREQkq2zrWX3+r7P9pFKphYRA/dKMxecDS4GZtdjEE8CoZDLZHSCZTO5LuJCYWlNDZf5FRERERBrfGGBKMpmcRijXOQr4ZSqVKoum++yQSqXmbKHteOAcYEYymZwCHEu4aHi6pl+qzL+IiIiISCNLpVKvAAcRpvxsD5yVSqX+FD19DvBSNW3XAgcCTwIDgceAw9Lz/ldHmX8RERERySpNeLafOkmlUjOAI6pYfi0VZweqqu0yQqlQnSjzLyIiIiISEwr+RURERERiQmU/IiIiIpJV6jKzjlSkzL+IiIiISEwo+BcRERERiQmV/YiIiIhIVtleZvvZFpT5FxERERGJCQX/IiIiIiIxobIfEREREckqmu2n/pT5FxERERGJCQX/IiIiIiIxobIfEREREckqmu2n/pT5FxERERGJCQX/IiIiIiIxYa5ukzoxs3Pc/a5tvR9SNR2fpk/HqGnT8WnadHyaNh2fxtOz/V5NMoD9ePE7tq33oSbK/NfdOdt6B6RaOj5Nn45R06bj07Tp+DRtOj7S5Cn4FxERERGJCc32IyIiIiJZxb18W+9C1lLmv+5Uy9e06fg0fTpGTZuOT9Om49O06fhIk6cBvyIiIiKSVXZpN7BJBrALl8xp8gN+VfYjIiIiUomZ5QDlXilLamYGJNx9QxVtWrj76i1sL9/d10U/5wK4+/qtv+fxUE6TjP2zQuzKfszsYDOr9nWbWbPopK9qebOMx3lVrSeNKzoOg8zsPDN71swOMLPm0XO/N7PhldZ/udLj19LrS92Y2Ulm1qqGdU4ws/xabKvJZ0uyiZm1M7Pdop/bmtkhZrazmXWqtN5RZtYm+rmbme27LfY3DswsYWa71mK9vmZWZGZjzKyrmfVohN2TzV0ATDWzqWY218wWmNlU4KXoOaLj9HpGm4lmtvsWtjfJzA6KjudPgHvNrIeZ9cqMLUQaWhz/s3UFHjWz1mx+8dMXGAYMBn5hZmVA+oPyG8Lf6/fAP6JlY4FhZpY56qQ98Iy7X94ge78dM7PzgeOB/YD/Bf4M7A0MJ/z9TwPGAAvc/cGMpoXACcD+wM/dfa6Z3RYF+RuiL8xsB6AzkIjefMcCPYB+wLNR8HmDu1e4OJBNosBxdyCdrdofONDMHo4eJwjH56to/d0IH5JP1GLzU8zsNHdftJV3O67OBJYCHxLOod0Ix+1Q4BrYeMF1A3CymXUHWgH/ZWal0TYWufsiM5sIjHb3YjO7Fbg3Os9edPdDG/VVZbccYCrQ3cxGA3PcfQaAmX0CfAu8DOQCrwD7ArsC9wGfVN6YmZ0K9HH3sdX9UjOb7e57brVXER/3AQvd/WkzO57wt77ezEYRziuAMqAUQtYf2ItwPqW3cbe7f2pmvYASIJ/weTUYaE74zGsG/BVY2TgvS+IudsG/uz9oZjOA24Ez2BRoHgokgTJ3fxh4GMDMzoraja9iW1eb2ZGEbsEXovXPBPIy1zOztsBnQPt0l59szt1vB243swXuPszM9gcOBL4HjGbL8yevBK4E7gRWRL0xVwDPArMz1usIjADaEd6gR7t7mZlNdfcRUSCk7HP1WhP+dungMBV93zP6ngMUZ1wMdCVcfL0SfRgmgPfc/bzoOJm7l0Xr3kW4AF8EIUsaPb9B51C9HAxcZGbHEoKNboTkBmb2GvBjYB/gLcIFcHegHJgLHEI4lm8QjscDwDFmNpJw/Pc0s1VAPzObBNzq7tMa64VlMQcWRD8/A1wFzIgevwFcC5wKtAROIlywzQGOi54nCiLPcPergHXRF2b2J+Bf7j4pevwS4RgC9DSzaRn78YMtlaZIBRuA35rZ/PSCqJf4WuBQMzuCcCG9u5n9ixA3/JFNyY7fEBJOnwI3AvMJF39XADsTzrdWwG/cXYF/HWnMav3FKvg3s2MIH4hXAOcC9xOykksIwf9Ud19Yx80OBt7LeNyJ8OGZ6VDCFf5BwJQ673h8HQ485+5uZi8QApR9qljvYMKb7O7AHoQ34HLg+4SsJgDuvgBYYGYnEHpobjazfkBfM3sGKHb30xvyBWU7d08BKTO7n9Brkmmtux8JYGYjgP7A74D/B/R09/ei59IXx4cCV0c9ZwOIzpuMjFmC8MH6IjqH6sTMfgh8AZxHCO5/SAgkhwGr3P2JaL0rgHeAfxMusNcQzp0EIRHyBzPLdffJ0aYnmNn1hEB0PnCdu5/SSC8rK5lZV+BRQpKiGbBHFCiujZ6fTrgIKAL6EP72dwI/IBy754EcM2sWXSh/BhybWb5oZgMIxzazx7mnu+8SPf+Guw+Lfp5GOMZSA3dfZWZXATcBD0WLxwIPuvsXZvY18CrwHHBU9POdwD7u/g8zKwHWRp85Awm9COVRD8Fp0fZ+ALRpvFclErPg390nm1khIZPcAbiIEASeC5wFjDSz9oTu1pKoWQeAqIsWQgByqrvPiR63Bb7K+DWdCCUqmY4gdOkdgQKXuugEvA3g7h8DH5vZZsG/u79sZrOAzwld5q8QsmZ3Ei7sAIhKfUYDuxAy1o8R3sS7mNl+wKgGfTXblz7uPiRzgZn9b8bDQuBvwMnAjsDNhA9H3L00+v48IbDBzF539wOq+X06h+qmGbCKEPCXEYLICYT3qw1m9iPgn0A62bGMcKFWttmW4GIzu4Rw3rQl9JpeTHjvvMTMdgKWK5NcNXf/nPCZg5kdTUhWDHb3I8wsJz1o1MxuAkYSPnMGRV9vAlcT3gfvMLPJhGz0TwkXE+2iX1NM6DEozbhIaBXVp0NIcKR/HggaKVkT2zQ28EnCBfLe0ePJwOyM58sB3H2NmR1KuKj7vZlNIZRvrQPmEeKNYVGbAqB39HPHhnsVIlWLVfAP4O6PReUd4wgBfzvCydeX8PdY5u790+tHGec8dz9kC5ssAP4UXeEDdAH2NTPcfWi0bChwAGGQkNTeCkI2DAuDEA+uZt2fE+plJwEnAr8llDWMJJQmJAkfpFOBPdz91Wi7xdHgrEsIPUJSO1UNdM8MKK4llJHcQahx3d3MniecY6+5+7hKbXuY2b8zHu8MjHT3dC+azqE6cPcnov/z4wilb7cCfyAj829mHYGZwM8Ix6UzIbB0QvlbWbStm83sIEJG+iigRfR9PuFiLIfQc5AuAZMtOxCYTugxBrjPzCa7++PAfwgXyacRAvu1wGuEi6xPgHeBYwgXXk4oqVtLCDBPA76OtvkQcDehJ3MEbMz8p3+e1qCvcPsxgtCTku4l6UhIagyLHucA44nGAJpZnrsvjS4KviF8puQRekQ/jxKPaTsS4g8I592LDfg6tlua7af+Yhf8R/V64939NDMbRBjQswp42t3vrLTuAMKJP9PMjnP3Jytvz93P3cLvSddnDiC8eT9BCHC6Rpkgqdl0Qp3/rYTAfy0h8KjAzPYmDIx7hXABkE94U55JOH53u/szGetflNH8akJX7QPu/p+GeBHbqXlRENGGMA5gIWFwadplhAuwZYQenDvd/Wgza+XuyzM3FGWOZ7n70RnLniEcS51D9RAF/mMIwXl6vNJdhL/jBjM73t1PzAhIStkUjKR9DDye8Xi1u98VjecoJWSajVDKcE8DvZTthpkVAUcT3nMuinob20aBP4TxZ/cCXxLq/N8FbiFc+D4crTuJkODAzP5MyErvClWOS6tu/FLsZvqrK3efQkYvo2UM+M1YtjOhd3MAYSKRqwk9nuPdfYKZPUE0JqOSxUTHkfDZJdKoYhf8Ez6wXrcw9eDNhFrLA4ATzewld/8INs5q8ihwOiEjM9XMPnP3t6Pn9ybMRlNSaft5hMAnPf/v4cCN7v5HM/tN9HizwcNSpf8BRliYRm0xoZTnV8B1GQH8/dF6FxJqMXH3S9IbMLPfES7u0nM2HwLkmllnwrE4h5ApO9jMfgE86u7fNvgry36zgWmEuvJhhEAlr9I6jxNKRNIXwr2Bp8xsZKWxNeey6YMwrR1R8I/Oofr4hJBlnk/ILA4m/F8fRkbNf4YyQo3/iPQCM3u20jovm9lXwGFAj6geOh94EKmN3xISESXRuJabCTO9YGYtCRNPXEv4jJpAeK+7lpDRH0e4cCBav4CQELmGKPiPludmzBvfMSPLv3uljL8mNqi7qiaE2AvYCRgQjQHoBlzg7rOjCoMOwOqM9onoc2g5obcMQvKEzBIwkYYWq+Dfwk01LgSOJHTV3UYIXsqAs4HHLMzu04swMv+yjGD/JOCJKCN5t7vPIny4VvV7+rCp7v9wQgYOQj36z1HgUi137x19d6K5lDNcG31tJhpImltpcS5hnAbRrDGHAL8mDAzekVBasiTqEfopoav3YWSLokGi+xLGSBwULX4WeCAak3EpIfB/Kiov6UeYEWuBmV0AvGBm+7v7YjMbSjgfv5ex/R2AfHdPd7frHKq7kYQytuWE2WQShMx/K0Lm/0xCT8q0aH0H9sqoC4dQ4pDWghCAriCcU5PNbEO03cweH6kkCgKvIExIcImZnUOo59/T3b+LeqB3I1yotSVc+D5AyBinB/92S88GY2b9Cb2hd7n7MjNzNtX+j42SVPcAndx9TdTmLWB4xviC88xsubunB7FKzZpHXxtFA+EnZzz+DPgseh+cDDyfPgZR2/aEwcHfUfFzbDAhHnu0oXZ+e6TZfurP4vTHs3BzlZMJI/f3jwaKDgVOdPcLzawdYTaZs4BfR7PDZLYvIgSjL6YvCio934owMGg9cJ67qz5ZtisWBsRfHn0NIQQ1/3T326Na1zGEi+pj3H2ime1B6Fm5wd0nRtvo6+7zLcwr/yBwgkdz+5vZHYR7B9xeRRmD1JKZ7QjkuPsX0eO7Ccfgk0rr7UmYEeh8wsxamZn/Ke5+WPRzXnqgtpk9BZyWkfl/3N2PaYSXlZWi8Uo3AccSyni+BXoSxsSsIQykvp9QwvMscLm7P5rR/m6gn7vvb2Y/IXwGjXP3p6Pnk4SLgQLCxdlZlXsvzWw8IUu9lJCB7kaY7vNDRLJUlzb9mmQA++XSeU2+Zy1WwX9jUNedxEV0sdwdeMfr+UZim2YmkSxhZvmuey3UiZlZbc6RqtaLssgLPdxgrVbbEYkDBf/1F6uyn8agwF/iwt2XkDGVaj23ocA/yyjwr7vaBuxVrefuM+u6HZE4KNfpUG8a8S8iIiIiEhMK/kVEREREYkJlPyIiIiKSVVw3+ao3Zf5FRERERGJCwb+IiIiISEyo7EdEREREsoomv6o/Zf5FRERERGJCwb+IiIiISEyo7EdEREREskq5ZvupN2X+RURERERiQsG/iIiIiEhMqOxHRERERLKKZvupP2X+RURERERiQsG/iIiIiEhMqOxHRERERLJKucp+6k2ZfxERERGRmFDwLyIiIiISEyr7EREREZGsotl+6k+ZfxERERGRmFDwLyIiIiISEyr7EREREZGsUo7KfupLmX8RERERkZhQ8C8iIiIiEhMq+xERERGRrKLZfupPmX8RERERkZhQ8C8iIiIiEhMq+xERERGRrFKusp96U+ZfRERERCQmlPkXERERkazimue/3pT5FxERERGJCQX/IiIiIiIxobIfEREREckqGvBbf8r8i4iIiIjEhIJ/EREREZGYUNmPiIiIiGQVV9lPvSnzLyIiIiISEwr+RURERERiQmU/IiIiIpJVdJOv+lPmX0REREQkJhT8i4iIiIjEhMp+RERERCSraLaf+lPmX0REREQkJhT8i4iIiIjEhMp+RERERCSrqOyn/pT5FxERERGJCQX/IiIiIiIxobIfEREREckqKvqpP2X+RURERERiQsG/iIiIiEhMmEZLi4iIiIjEgzL/IiIiIiIxoeBfRERERCQmFPyLiIiIiMSEgn8RERERkZhQ8C8iIiIiEhMK/kVEREREYuL/AyvB+1Q4u536AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1008x1008 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_names = stock_list['name']\n",
    "all_data ={}\n",
    "\n",
    "#遍历list里面的股票，可以写入多个股票\n",
    "for name,ts_code in zip(stock_list['name'],stock_list['ts_code']):\n",
    "    #获取各股票某时段的价格\n",
    "    all_data[name] = ts.pro_bar(ts_code=ts_code, adj='qfq', start_date='20200521', end_date='20210521')\n",
    "#用for循环遍历股票价格并转换为dataframe的形式\n",
    "p_data = pd.DataFrame({tic: data['close']\n",
    "                    for tic, data in all_data.items()})\n",
    "p_data['平均值']= p_data.mean(axis=1)\n",
    "#计算股票价格每日变化\n",
    "returns = p_data.pct_change()[1:]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(14,14)) \n",
    "cm = np.corrcoef(returns.values.T)\n",
    "sns.set(font_scale=1.5,font=myfont.get_name())\n",
    "sns.set_style('whitegrid',{'font.sans-serif':['simhei','Arial']}) \n",
    "\n",
    "hm = sns.heatmap(cm,\n",
    "                 cbar=True,\n",
    "                 annot=True,\n",
    "                 square=True,\n",
    "                 fmt='.2f',\n",
    "                 annot_kws={'size': 15},\n",
    "                 yticklabels=returns.columns,\n",
    "                 xticklabels=returns.columns,\n",
    "                 ax=ax)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](https://fenc.wang/imgs/2020/08/3565654bfbe9ffa0.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.8.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}