Stock Portfolio.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tushare as ts\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']    # 用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus'] = False      # 用来正常显示负号"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "TOKEN=\"ab8cda03b983bbe19fb5e50cd01c23581fbac2870eac95465b253777\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "ts.set_token(TOKEN)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 设置股票列表\n",
    "code_dict = {\n",
    "    \"600009.SH\": \"上海机场\",\n",
    "    \"600036.SH\": \"招商银行\",\n",
    "    \"600519.SH\": \"贵州茅台\",\n",
    "    \"000002.SZ\": \"万科A\",\n",
    "    \"002594.SZ\": \"比亚迪\"\n",
    "}\n",
    "code_str = \",\".join(code_dict.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.DataFrame(columns=[\"trade_date\"])\n",
    "col_list = [\"日期\"]\n",
    "start_date = \"20190101\"\n",
    "end_date = \"20201231\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             上海机场     招商银行      贵州茅台      万科A      比亚迪\n",
      "日期                                                    \n",
      "20190102  49.4780  23.2058  583.4473  22.1556  48.9292\n",
      "20190103  48.8102  23.4986  574.7002  22.3132  47.8246\n",
      "20190104  48.9280  24.0936  586.3890  23.1104  50.4020\n",
      "20190107  48.8888  24.1031  589.7885  23.2216  51.1383\n",
      "20190108  48.9477  23.8197  589.1066  23.1753  52.6210\n"
     ]
    }
   ],
   "source": [
    "for code_item in code_dict.keys():\n",
    "    df_item = ts.pro_bar(\n",
    "        ts_code=code_item,  # 股票标准代码\n",
    "        asset=\"E\",          # 资产类别：E股票\n",
    "        adj=\"qfq\",          # 复权类型\n",
    "        start_date=start_date,\n",
    "        end_date=end_date\n",
    "    )\n",
    "    # 根据日期合并每只标的的收盘信息\n",
    "    data = pd.merge(data, df_item[[\"trade_date\", \"close\"]], how=\"outer\", on=\"trade_date\")\n",
    "    col_list.append(code_dict[code_item])\n",
    "\n",
    "data.columns = col_list     # 重置列名 \n",
    "data.sort_values(by=col_list[0], inplace=True)  # 按照日期升序排列\n",
    "data.fillna(method='ffill', inplace=True)       # 根据前值替换NaN值\n",
    "data.set_index(col_list[0], inplace=True, drop=True)    # 重新设置索引\n",
    "\n",
    "print(data.head())  # 查看前5行数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='日期'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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XorCw0JmS9PTTT/PEE08432dkZDjHzZw5s1Zesd1udzZtSE9PZ9u2bfz7778MHjyYHTt2sHHjRjp27MiOHTvYvn07mZmZLsdv2rSJyZMnCzEWCAQXLPZKgVSrFXmqWXjDgcVoQ6vXoNVrMFc0vu6C3SqjVrtavVpdpRC3YJ1pEEJci927d/Ptt99itVpRqVSoVCqsVivr1q1jwYIFznGSJOHh4QHA6NGjAVCpVM7I6dTUVLZs2cKBAwcoKytjx44d7N27F6PRyI4dO9i2bZtLSczCwkIefvhh3nrrLSRJ4rHHHiMhIaEF71wgEAjcj8MiVmkUkazLIrZZ7NhtMjpPtbPwR6OvY6uyiB041qVb2iIWa8Q18PPzIzk5mTfeeIOTJ08iyzLbtm1DlmUeffRR5zhJkpxrCN7e3i7bAYYNG4avry8PPPAAJpOJBQsWIMsyRqORP/74g19++YXw8HBAEeFrr72Wd955h969ewMwbdo0rr/+eubPn09cXFzL3LxAIBC4GSVqWnK6puuyiB2uaK2HBp2nhvIiU60xp72O1Y5aU8MirnRNt2R5S2ilQvx/2/6PhIKmtQa7BHXh6UFPn3LMihUr2LlzJ1dccQWgWLWyLBMbGwsovYPnz5/Pl19+yejRo1mwYAElJUp90pdeeoknn3zS5Xw9e/Zk3bp1LFu2jPz8fPr378+TTz7JtGnTCAsLc46bNGkSycnJvP3223zwwQeo1UqgQLt27Zg8eTJr164lODi4KT8OgUAgaJXYLJUWsbp+i9hRg1qnV6PTayg0Ghp/HavsdH870Dhc0y2YQwytVIjdxbhx4xg4cCBTpkxx2X748GEAvvzyS2dnJlmWGTRoEHPmzAFgwIABzJo1y3nM5s2beeGFF5AkCbvdzvr165EkiZ49e/LJJ5/wySef8OabbzJ48GC++eYbAgMDCQ8PrxWpt2XLFlEIRCAQXDDYbDIqTcMsYp1esYjPxDVtt9bhmvYQQuzkdJZrcyJJEhqNhiVLljB//ny6dOlCp06duOOOOzCZTCQnJ9OvXz9OnjzJpZdeit1u5+eff2bSpEnMnTvXeZ7BgwezbNky1Go1v//+O76+vmRmZrJ9+3ZkWWbIkCH06tULgLy8PEaOHOm0vB2kpaXx008/oVa37C+FQCAQuAO7XUa2y64WcR0VsBxFPrR6ZY34TIK1bDa5ftd0CxbzABGsVQuLxYKnpyc2m43333+fnJwcEhMT6dmzJ3q9nvbt2zNz5kwOHTpE586dmTp1KqCUsHS8BiVwy2Kx8MILL7Bs2TLmzp3rFFRJkti8ebMzsEur1XLllVeyY8cOl3833nijs0SmQCAQnO84imxUT1+y2U6xRlzpmrZZ7djqaA5hNlrJzyyr91qqGq5ptUZFTPcg2rQPOJvbaDRCiKths9koLy9n2rRpTJkyheuvvx5fX19eeeUVli5dytGjRwFlrTgoKMgpknWlGy1dupRBgwbRrl07/ve//5GRkeFsewiKUDtQq9X8888/DBgwwOXfb7/91qJJ5QKBQOBOHG5olVqqZhHXFliLc41Y40w1qiuXeOFn+5j92jbs9rpazdYO1gK4/KE+xPcNPfObOANapWvaXZSWlvLUU0/Rv39/PvnkE2JiYgD47bffOH78OLNnz+aSSy7hscce47333nMeFxkZCShCbjAoQQN9+/Zl+fLlhIeHYzabeeyxx3jggQfqvK7FYuHKK6/k66+/dtn+6KOPOlsuCgQCwfmOozWhWqNCkhQxttUZrOVYI1Y7U43MRiuevq5dmjKTigClx3HNDk42i4xG1zpsUSHE1QgICGD27Nl17ouPj+e5554DYO7cuXh5VbXHcgioWq1m06ZNAC5R0Tqdjr///rve6w4ePJj+/fvX2v7RRx819hYEAoHgnMVWzTUNoNKo6rSIzS4WcaUQV9iY//FuinIquO3NYS7jDSXmWkJst9lRqVuHBLaOWZxjVBfhpkCtVouALIFAcMFjtzmEWHEZqystYmO5BbtNdoqpxZlHrHZpl5h2uNB5LqulKoCroo6mEI6a1q2B1mGXCwQCgeCCx2ZR3NCqGhbx2l8TWfrVAec4i9mORqtCUkl4eCmxOsYyi8u5inMqnK8NpbWF2GKyOvOG3Y2wiAUCgUDQKrDZXF3TDou4tMDo0urQZrGjrmxTGBDhhUotkZNS4twvyzKF2VVFPmq2SZRlGUOxGW9/V3e1uxAWsUAgEAhaBdWjpqHKIjZXWDGVV1m8NovNKcRanZrQGF9SDxU491vNdkryqyxih2s6N7WU75/ZSHFOBVaLHe8Aj2a/p4YghLgGNlv9ieE2mw2z2cyOHTv4/PPPmTRpEhs2bMBkUuqcPvnkk6xcubKlpioQCATnFc48Ym01i9gqYzRYMRttTotZWd+tkq/I9v7kpVXlC5sMVkrzjXh4afAJ8nC6pncvS6G8yMShDUrnO2//1iHEwjVdjYKCAq6++mq0Wi3p6elIkkTbtm2d+61WK6+//joLFixg06ZNfPbZZ/Tq1YuHHnqIMWPG1Aq6KigoICYmhry8PPR6vTtuSSAQCM4ZnOlL6qo1YpvVjsmgWMOmcitefjqsFmWN2EFkhwD2rEhzvjdXKELsG6xHpZKcFrEjwrogqxwA74DW4ZoWQlyNoKAg1q5dCyipQ2FhYdx0000uY2w2G0OHDmXGjBn4+flhs9l4++23mTRpEn369HEZu3z5ckwmE+vWreOSSy5pqdsQCASCc5Ka6UtqtYTFaHWWuTSWK/nANmvVGjFARLy/y3lMFVZK8o0EhnthtytrzACOjOTMo0UAePmdQxaxJElBQH9gtyzLec07Jch+6y1Mh5u2+5JH1y5EVOYBN4Tc3Fy+/vprPv/8cwCKiorYuXMnGzdu5MUXX+TQoUMcOHCAm266CZVKxapVq3j++eddzrFkyRIeeOABlixZIoRYIBAIToNDcB29iNUalUuglbFyndjRs9iBl5+OgHAvik4qAVomg4XSAiMx3YKwWuxkHysGwFCsnMtRmcvrXAnWkiQpElgIDAJWS5JUq/aXJEkaSZJSJUlaU/mvZzPMtUU5ePAgq1evZsOGDWzYsAEPDw88PDwYM2YMCxcuxGq1MmbMGEaPHk1mZiYzZsyodQ5HByaxbiwQCASnp3ZBD8kl9cgRsOVolVidiPZVVnFJXgVWkw3fID0+gR4Yyy1YzDYXUVdrVc6qXO6mIbPoDjwmy/IWSZICgX7A0hpjegG/ybLcJG2TGmO5NgelpaXk5+cTGlr1zFF97fezzz4jLCyMq666itmzZ/Pss88yZ84c5s+fz8GDB0lMTGTo0KHk5eVx7bXXkpycTFpaGtHR0e64HYFAIDgnsNUq6KHCVF5VQ7q6Rayr0SGp/8RYAiO82DzvGEd35AAQGOFFRaWQlxUYMRSbnOMDI5q2MNPZcFqLWJblFZUiPBLFKt5cx7AhwNWSJG2QJOkXSZJax2PGGfLWW29xyy23uGxzNF/YtWsX27ZtY/To0YSFhWE0Grn77rvJz89HpVJx7733cu+997J06VKee+451qxZw8MPP8zSpTWfXQQCgUBQHUcHpeolLqtjrBRlax0WcUCYFz1HRQGQdayY0BhforsG4ROkBMqWFZgwlJjpe0kMU18axOQHejfrvTSGBqUvSYoK3QBYgLrye7YDF8uyPAIoAi6r4xzTJUnaIUnSjtzc3DOfcTPz77//snbtWu6++25ASfw+fvw4vr6+AISEhPDxxx87x7///vv8/vvvPPXUU3Tu3BkfHx9A6b40ZswYAMaMGcOSJUta+E4EAoHg3MJe2eDB0Z5QrXYtQemwiO3W2kIMuERS95sQi6SS8AlUhDgvvQy7Tcbb34PgNj6tJocYGhisJSt9/h6QJOl1YDLwe40h+2RZdtj8CUDHOs4xC5gFMGDAgNrtNFoBBQUFfP755/z5559OV/T333/P999/z6uvvgrg7MhkNptd2hqC0kXJkVO8YsUK5/bRo0czevTolrgFgUAgOGex1cgjrm4Rq1SSU4hrpi85qN42NrZHMAA+lYJ7MlmpvFWz+UNr4LRCLEnS00CWLMs/AgEoFm9NfpIk6U3gAHA18FYTzrHFCAoKYvHixS7b7rzzTu68885aY3/88cda295///1mm5tAIBCc7ziFWC25/ASllGV5ock5Tl2HEDvQeWrQeijGlFqrwstPR2aS0hDCN7j11XRoiEU8C5gjSdLdKEKbLknSG7Isv1BtzGvAr4AEzJdleUUd5xEIBAKBoF5s1tpNHwC0ejWBEV7kZyiFOOqKmnZwx/8NR1ujmYN/qCdZlSlMfiGezTL3s+G0QizLciEwvsbmF2qMOYASOS0QCAQCwRlht9qRVBIqlatF7Omrwz/MixN78rDb7C5NH2pSV9nKwDbeZB0rRuOhxtNX23w3cIac09HNAoFAIDj3MVdYWf1LAmq1ysUd7bCIvXy1+Id6OqtkKQU9Gt5LOLiNN6AEc1VfR64PWZYbNK6pEE0fBAKBQOBWjmzL5uiOHBK3ZqP3qbJYHWLr6asjIExxKRdmG5Bl6gzWqo+gSEWIrZXpUadjXfo6hvw6hMSCxAZf42wQFnENevXqxb59+5zvu3XrxqFDh1zGONKS7HY7KpXK+VOWZbp27eosi3nXXXfx0EMP0bdvXwCysrK46667agWECQQCwYWMxqNqTbd6WpEjjcnTR4t/qFKAY+FnyvdzzRzjUxHURkkr9fRumFu6yFREuaUcb613g69xNgghroGnp+tCviMv2Gaz8e2333L33XezatUqAF555RWGDBnCli1bGDJkCBMnTnQ59tlnn2X9+vUcOHCAb775BovFQkJCAqNGjSIoKIh58+a1zE0JBAJBK6a6G9gnsLoQK9v1Plq8/HV0GBDmrJrVGIvYy0/HsCkdiO0e3KDxRaYiAAL1gQ2+xtkgXNM1qLkuoFKpOHz4MJdccgnr16+nvLycRYsW1cohBigrK2P16tXO9x07duSuu+4iMzOTZ555hn/++YehQ4eyZs0aioqKmvtWBAKB4JzAYqwqY1ndIraYlPpROk8NkiQxcmon5776oqbro+/4GILaNMzCLTQWolVp8dK0TBnMVmkRr59zxKXJc1MQEu3DRdd3Ou24iooKRowYQUVFBXfeeSdZWVk88cQTvP322wwaNAhQuioVFxfXOvaPP/4gISGB0aNH88EHHzB79myef/55VKravzB1bRMIBIILEbOxqmCjT0BVnq+pQhFoDy+ty0/glHnEZ0uRqYhAj8AWC9hqlULsTjw9PdmwYYPz/c8//8zChQtdxjz44INMnz6dUaNGuWz/8ssv+ffffwG499578fT0pLCwEEmSePbZZ/Hz8+PQoUOMGzeOzMzMZr8XgUAgOBdwWL7g6po2GxQh1nkqa8iOtCZovEXcGAqNhfjr/U8/sIlolULcEMvVnXTq1AmVSkVOTo5z29KlS+nVqxchISEAeHt7O9ebZVnm7bffZsCAAdxxxx0sWLCAsWPHumXuAoFA0NowV9TtmnZaxJ61g6yaU4gdFnFL0SqF2N1YrVZ++OEHSktLXbZnZ2cTFhaGSqVi0aJFvPPOO85948aNY8SIES7jLRYLFosFs9nMU089ha+vrzNYKy0trUXuRSAQCFo7ZodFLIFfSJVresS1Hdn4RxJtOgU4t0kSjU5faiyFpkI6BtRqmdBsiIXKalitVlJTUxk4cCAnTpzgtttuo6KiArPZjN1u5+6772bJkiXYbDb0etd6pWq1Gn9/f6xWK3a7nZMnT/Lxxx/z/vvv07dvX/bs2cPGjRvJz89nzZo1HDt2zE13KRAIBK0LS4UV/1BPpjzZ39ktCSCojTeXP9zHpWSlVq/Yj81qERuLWixiGoRF7IJGo+E///kPt956K2FhYQBcddVVjB07FlmWiY+Pp6KigqFDh6LTKR08HF2WVqxYweuvv47ZbOadd96hpKSEt956i+HDh/P2228zc+ZMrFYrRqMRq9VKQUEB9913H88++6zb7lcgEAhaA2aTDb2Ploj406/L6vRqzBXWZgvWstltFJuLCfAIaJbz14UQ4hr85z//cXn/6quvOlsgOpgyZUqjzvnee++5vLfZbEiSJCKnBQKBACV9SadXn34gVHVVaiaLuNRcil22t6hF3KqUQGl7fP6jVqvPSoQvlM9JIBBcGJiNNqfL+XQ4xjlaJjY1hSalXWJLWsStRoj1ej35+flCZE6DLMvk5+fXWqMWCASCcxWz0YrOo2EWcadB4QB4+euaZS7OqloXYtR0VFQU6enp5ObmunsqrR69Xk9UVJS7pyEQCARNgsVoQ+vZMDnqNTqKLkMiXIp7NCVFxiKACzOPWKvV0q5dO3dPQyAQCAQtiCzLmI22BlvEkiQ1mwiDeyziVuOaFggEAsGFh9ViR7bLaBsYrNXcXNBrxAKBQCC48Dh5ogSAwIiWaTl4OoqMRXioPfDUeJ5+cBMhhFggEAgEbiN5fx4qjURUl5ZzBZ+KQlMhAR4BLdbwAYQQCwQCgcCNpB4soG2nQHQNTF9qblq6qhYIIRYIBAKBGykvNBIY0TJ9f2titBp5ceOLZJdnO7c5LOKWRAixQCAQCNyC3a5ETHs0MHWpqTmYf5C/j/7N2rS1AOzP3c/e3L0tLsStwxcgEAgEggsOR/vD5kxHqosKawUWu4WMsgwA58+bFt0EgF1unqpd9SGEWCAQCARuwWRQhFjXwhbx65tfJ6koidHRowFIL0t3qeo4tM3QFp2PEGKBQCAQuIUqi7hlpWj7ye1kl2c7XdAZZRnkG/MBeHrg01zb6doWnY9YIxYIBAKBWzAZLEDzCXFCQQJf7v3SxdrNq8hzBmdtydoCKELs2NbGp02zzOVUCItYIBAIBG7B1MwW8Tvb3mHnyZ10C+7GRVEXAXAo/1CtccWmYpIKkwD3CLGwiAUCgUDgFpp7jVirUoLAPtr1EWabGYADeQeQkHi036NISIyMGgnA0uSlAER6RzbLXE6FEGKBQCAQuIXmjprOLs9Gp9JxpPAIX+77kuzybA7kHSDeP55pPaex7/Z9fDDqA4L0QWzM3IhercdP59csczkVQogFAoFA4BZMBitINLjzUmOw2W1klGVwc7ebGR87nln7ZjH+j/Gsz1hP95DuznEeag9m9J4BQJegLi1a2tKBWCMWCAQCgVswVVjx8NQgqZpe/HIMOVjsFqJ9oxkSOYTlKcud+3qE9HAZe2OXG5kYNxEvrXsqfAmLWCAQCARuwWSwNNv6cHpZOgBRPlEMiRzCNR2vIdYvFoCuQV1rjQ/UB+Kh9miWuZwOYRELBAKBwC2YDdZmTV0CaOffDpWk4tVhr2K2mdmYsZHeob2b5ZpnirCIBQKB4AJHlmXe2PKGi/u2JTAbbWibYX0YYGvWVmL9YonwjnBu06l1jI4Z7ZZ14FMhhFggEAgucI4VHeP3xN95fM3jLEte1mLXtVrsaHVNL8QWu4Xt2dsZHDG4yc/dHAghFggEggschyXsq/XlP2v/w56cPS1yXavZhuYMhXh2wmw+2fVJnfuOFh7FYDUwMGLg2UyvxRBCLBAIBK2IFSkryKvIa9Frrk1fS9+wviy6ZhEAO07uaJHrWi12NLozk6E3t77JV/u/cilf6SCzPBOAaL/os5pfSyGEWCAQCFoJRquRx9Y8xk0Lb2qxa1rtVpIKk+gd2psAfQCxfrHsy93XMtc229Boz06Gssqzam1z1I2O8Iqota81IoRYIBAIWglFpiKgbnFpLpKLkzHbzXQK7ARA79De7M3dW6el2dRYzfYzdk07OFxwuNY2R0WtIH3QWZ27pWiQEEuSFCRJ0nhJkkKae0ICgUBwoeIQYoD8ivwWuWZiYSKAU4i7BXejwFhAgbHAOWZ79nbuWnoXuYbcJr221XLma8QOEgsSa23LLs8mwjui1UVH18dphViSpEhgITAIWC1JUmg9476RJGmTJEkvNPEcBQKB4IKguhC3VCpRYmEiGpWGeP94AGe6z0nDSeeYxScWsz17O0+vf7rJrmu32bFb5TNaIzZajc7Xjq5J1ckqz3JL84YzpSGfQHfgMVmW3wSWAv1qDpAk6RpALcvyMKCNJEkdm3aaAoFAcP7jEGJfnS9f7vsSk83U7Nc8UnCE9v7t0aqVxguOddWT5VVCnGPIAWDXyV1Y7JbTnjOzLJOMsoxTjrFa7ABotI23iKs/sKSVptXan12eTbh3eKPP6y5OK8SyLK+QZXmLJEkjUazizXUMGwXMqXy9ChhRc4AkSdMlSdohSdKO3NymdW8IBALB+UCxsRiAe3vdS15FHqklqc1+zcTCRDoHdXa+dwhYdYv4RPEJAGyyjcyyzNOe86VNL3H30rux2q31jrGaK4W4Hou42FTMkuQldQp/sUn5nMK9wkktTXVZzy42FZNbkXveWcRIiqP9BsAC2OoY4g04Hn9KgFqPIrIsz5JleYAsywNCQ+v0bgsEAsEFjcPSi/KJAmh2izi/Ip+8ijzn+jBAkD4IjaRxCrHFZiGjLMNZHCOlJOW0580uzya9LN3Z49dBjiGHi2ZfxMrUlVjNipTUJcRmm5kr/r6CJ9c+yV9Jf9Xa7xDiniE9qbBWcNJwkrTSNCx2C98e+Ba7bGd87PgGfgrup0FCLCs8AGwCJtcxpAzwrHzt09DzCgQCgaCKIlMR3lpvfHQ+AFRYK5r1eo5AreoWsUpSEeoV6nRNp5WmYZNtXBx9MUCDrHRHHvQ3B75xWqtr09YydcFUikxFzEuaV80iru2azijLcAaLvb7ldT7e9bHL/mKzIsSOLkrj/xjPZfMu464ld/HtgW8ZFT3K5Z5aOw0J1npakqTbKt8GAEV1DNtJlTu6N5DcBHMTCASCC4oiUxEBHgHOLkDNZRHLssyfR/7km/3fICHROdBVtMK9wp0W8dGiowD0C+uHr9aX5JLkU57bYDFQbimnQ0AHkgqTmHtkLgCf7fmM3AplWbLIVITVUmkR15FHnFWmpG+NiR4DwNf7v+bupXc7K2k5PAc9Q3q6HLcndw9dg7oyc+TMBn0OrYWGWK6zgFslSVoHqIF0SZLeqDHm78oxHwDXo0RZCwQCgaARFJmK8Pfwx1OjOBirRwc3JUeLjvLK5lfYlr2NF4e+SKA+0GV/uHc4GWUZyLJMYmEiaklN+4D2xPjFkF6afspz5xuVtKubu97MoIhBvL7ldbZmbSWlJIWbutzELV1vIakwCbNJWfutaRGvS1/HD4d+AOCJgU8wo/cMALZmb+Wr/V9hsBj4O+lvALoGdyXEM4S7etyFj1bxIlzV4Srn53eu0JBgrUJZlsfLsjxSluX7ZVk+KMvyCzXGlKAEbG0BRsuyXNw80xUIBILzl2JTsYtFbLQ1nxAD/D75d67rdF2t/YMiBpFRlsHe3L0kFiTSzr8deo2eMK8wp1VbH4785wjvCD4f9zn+Hv58sfcLDFYDMX4xxJZ0w2q0k1WsWNw1hfjDnR+yKXMTaklNpHckV7a/0mX/8xueZ1/ePny0PvjqfFl13Soe6/8Y3UO6A9A7rHW1OGwITbaWWynYc2RZzm6qcwoEAsGFQo4hh2NFxwj3Ckev0QNgsjaPa/po0VFUkor2Ae3r3D85fjI+Wh/mHplLQkECXYK6ABDiGXLaOtiO/SGeIXioPbg8/nJ2ntwJQFtNDPl/eNMldwjZJUpKVHXXdIm5xPmQYJNtaFQa2vi0cbFwV6SuAGDB1QsAnEU7BkcMJkgf5BJ4dq4ggqoEAoGgFfDZns+wyTam9ZyGXq0IcVNZxCeKT3DHkjuc1urxouPE+MY4Le+aeGm9GNF2BEtOLOGk4aRzDTnEM4RCY+Ep05KqCzHANR2vce4Ll9oo5zf7UW4wAK5R03XVuFZJKjoEdCDcK5xBEYMAGBgxkGDPYJdxd/a4k3+v/hetSnuKT6J1IoRYIBAIWgHbsrYxMmoksX6xeGgqXdNNtEY898hcdp7cyaq0VYBiETsqadVHr9BemO1mAPqH9wcgWB+MjExiQSJ22V7ncfnGfFSSikAPZd25Y2BHeoX2QiNp8EXZ5mnxwWBU7s3hmrbarcxLmodaUt5H+1Z1Trq/z/08OfBJ+oT1AaBrUNda19WoNPjp/E7/YbRCNO6egEAgEFzo5Ffkk16WzrWdrgVo0jViu2x35vNuSN/ApXGXklqaysR2E095XK/QXs7XjvVXh5U7deFU3hrxFpe3v7zWcZllmQTrg1GrqtZ+nxn4DAmFCVgrFPHWW32oMCpud4dF/O+xf1mespz7+9zPhNgJ+Hv4O48f0VZJyvHWegM4XeXnC8IiFggEAjeyPXs7o+aMAqryYlWSCg+1R5OsEScVJpFjyCFIH8SWrC1sz96OXbY7rdz6cFidkd6RqCRFKqq7g/fk7Kn3eh0DXasc9wztyXWdrsNkUFzaPlZ/jE4hVgR7c9ZmQj1DmdFrBvEB8bVczwBDI4fy6rBXuSTukgbc+bmDEGKBQCBwIwkFCc7X3YK7OV/rNXqnRWyX7Sw+sZi0kqq6ykXGIh5f8zjfH/gem72ugocKjqId13e+HoPVwK8Jv6JRaegdeuroYp1ax/cTv+eXy35xbnNYxABHCo/UOsZit3C06Gi9xTQcQuxp9cVkVtKXZJUNWZbZeXIn/cP7n7Jjklql5pqO19S7tn2uIlzTAoFA4EbMNmUd9pWhr+Cr83Vu91B7ONeIFx5fyHMbngNg+bXL8dH68MbWN1iespzlKcvx8/BjUvykOgUqsSARD7UHV8Rfwf/2/o8tWVvoF9avQbm2Na3m6lZqUlESdtnutJZBCQqz2C21CoQ4MBkU8fUwe1FRkYtaq+L6Bdfj7+FPjiHntFb6+YqwiAUCgcCNlFvKUUtql+hiAL1asYhlWWbWvlnO7ScNJ3lg5QMsTV7KjN4z6BLUhZc3vcyI30bw99G/a50/sSCRDgEdiPKNcm6bFD/pjOZaXbzLLeXMTZzrst9h3de1hrvoi31s+1dpHqGx6Qg52hFNuIVjxcfYlbOLSO9IxsWOO6N5nesIIRYIBAI3UmouxUfnU8slq9foMVqN5FbkklySzGXtLnOOP1p0lKs6XMX9ve/n+cHPc2X7K4n0iWRO4hyXczgqY3UJ6oIkScT5xQFKnvCZsuiaRcyZPAeNpOGNrW9wvOg4dtnOf3f/l18P/0qQPsh5neqc2Fs7/3hn/7+J9Yvl60u+Zu7lc11c3xcSQogFAoHAjZRZypzlGaujV+sx2UwcKzoGKLWeAXINuZSYS4jxjUGSJPqE9eGNEW8wNHIox4qOubQEzDHkUGQqcha5+GbCN8y7Yh5eWq8znm+0bzRdg7uyZMoSAJanLCepMIkv933JwfyDXBx1sUvEdH3k+aaTbDhOt+BuDI4c7BIlfaEh1ogFAoHAjZSZy1zWhh3oNXp25+x2Fqhw5NA6Kk/VbHzfPqA9BquBrPIs2vgohTMcgVoOV3GYVxhhXmFNMu9w73D6hPZhReoKl7mMiRnToOO3RP1LZnnmadOoLgSEEAsEAoEbKbWUOvNjq+Oh9qDCWsHa9LUAxPrFAlVCXFNQHSlDR4uOYrQaWZe+DotdCY5qrrKPF0dfzMe7PmZTxia8NF58N/G7OottAKhUEna7Yq37PJhO+s4EkKGtT9tmmdu5hBBigUAgcCNl5jIivSNrbXfUm67+XqfScbSw0iL2qm0Rg5Lf+8DKBwCI94+nrU9bZ3/jpmZA+AAAFicvpl9YP5f0q5p4eGuoKLXgF+pJtH+Mc7sQYiHEAoFA4FbKLGWnFco3hiudZ/08/MipUJol1BRiP50fI6NG8tX+r5zbjhcf59K4S5t4xlV0D+7ufN0vvN8px1otdqK7BjLuzu7InhbndiHEIlhLIBAI3Ep9wVq5BqXd4P9d9H9c2UFpBehYS/bV+tYZcPXasNcYGzOWN0e86XRd39/n/uaaOlq1lvGx4+kW3I3pvaafcqzNbCcs1g8vP52LK74ub8CFhrCIBQKBwE3IslxvsFa2QekoG+sf69zmGFczUMtBsGcwH43+CIBeIb3Iq8gjzj+uaSddg/cvfh8Z2aWwR01sNjt2u+zSaemLcV+wLXsbWvW51y2pqRFCLBAIBG6iwlqBTbbVGazlaIVYPSfXIcQNCb6K849rdhEGpR+wRP1lKUGxhgHU2qq0phFtRzibOVzoCCEWCAQCN1FmKQOo0yL+fOzn7MrZ5SLSjhzh+mo5t1asFkWINVqxGloXQogFAoHATZSZFSGua4042i+aaL9ol22ZZZkAdAk8t9oAWs1KUwpHpyWBK+LxRCAQCNxEibkEUKKhG0OnoObJC24unBaxTkhOXQiLWCAQCNxEfkU+AMH62r136+Kj0R+xIWPDOVeT2WkRC9d0nQghFggEAjeRb1SEOEgf1KDx7QPaOwt3nEtUrREL13RdiMcTgUAgcBMFxgKg4UJ8ruKMmhau6ToRFrFAIBC4ifyKfPx0fudtLq3NZidp20m0esUSFq7puhGfikAgELiJAmPBeW0NJ27JZuUPh0nep/QiFlHTdSOEWCAQCNxEgbGAYM+GBWqdiyRszgKgMNsACIu4PsSnIhAIBG4i35h/3lrERScNZB0tdr4GYRHXhxBigUAgcAP7c/dzovjEeSvECZuzkCTQeWowGayAsIjrQ3wqAoFA4AbuX6l0RarZzvB8wGqxkbA5i+huwQRFVpXoFFHTdSM+FYFAIGhh7LKdIlMR7f3bc33n6909nSZn/+oMyovN9L0kBp8gDwBUKgm1WkhOXYhPRSAQCFoYR/7wDV1uwN/D382zaXpO7MslLNaXqM6B+AQoQqwWbul6EZ+MQCAQtDC5hlwAwjzD3DyT5sFcYcO7UoADwr0AiOl2fq6FNwWioIdAIBC0MLkVihCHeoW6eSbNg9loRadX5KXL0EgCI72JbH/+Wf5NhRBigUAgaGFyDDkAhHmdnxaxxWhzVtNSa1S06RDg3gm1coRrWiAQCFoYhxCfr8U8zCYrOr3IGW4oQogFAoGghckx5BCkD0KrOv9qTNssduxWGa1eOFwbihBigUAgaGGyDdnnZf4wKNYwICziRiCEWCAQCFqY5OJk4vzj3D2NZsFitAGg9RAWcUMRQiwQCAQtiMFiIKMsg3j/eHdPpVkwGystYk9hETeU0z6ySJLkD8yuHFsG3CDLsrnGGA1wvPIfwEOyLO9v4rkKBALBOc+JkhMAtA9o7+aZNA/mSotYJyziBtMQi/hm4ANZlscD2cDEOsb0An6TZXlU5T8hwgKBQFADWZZZk7YGgPb+56kQVygWsVasETeY0z6yyLL8ebW3oUBOHcOGAFdLkjQcSAFul2XZ2jRTFAgEgnOf3Tm7mbltJgfyD6BVaYn2i3b3lJoFi6nSIhZR0w2mwZ+UJElDgUBZlrfUsXs7cLEsy1mSJH0GXAbMr3H8dGA6QExMzJnPWCAQCM4xDBYD05dNx9/Dn6cHPk33kO7nZeoSVAvWEhZxg2mQEEuSFAR8CkypZ8g+WZZNla8TgI41B8iyPAuYBTBgwAC58VMVCASCc5PU0lSMNiNvDnyTS+Iucfd0mpWqYC1hETeU064RS5KkA+YAz8qynFLPsJ8kSeotSZIauBrY24RzFAgEgnOalBLlqzPWL9bNM2l+zM70JWERN5SGPLJMA/oDz0uS9DywGtDKsvxCtTGvAb8CEjBfluUVTT5TgUAgOEdxCHG07/m5Llwdi9GKRqdCpZLcPZVzhoYEa30BfHGaMQdQIqcFAoFAUIOUkhTCPMPw0nq5eyrNjrHcgofX+bn+3VyIgh4CgUDQjKxLX8f8Y/OJ8bswglTLi83OXsSChiGEWCAQCJqR/+7+LwCDIwe7eSYtQ3mRCW9/nbuncU4hhFggEAjOguzybKz2ussmWOwWjhUd4/ZutzOj94wWnpl7KC8y4SMs4kYhhFggEAgagdlm5mDeQQDyKvKY/Ndkfkv4jQ93fsj1/16PLFdlZ54oPoHZbqZLcBd3TbdFsZptmAxWvIQQNwqR6CUQCASN4PfE35m5fSYfjf6IElMJJpuJ93a8h122A/Dw6oeZGDeRSfGTSChIAKBrUFd3TrnFKCtSykkIi7hxCCEWCASCRpBXkQfAhzs/pJ1fOwCnCAOsSVvDmrQ1XNbuMpacWIK31ps4v7iWn6gbMBQrQiyCtRqHcE0LBAJBIyg2FQNKStKa9DV0DFQKCd7f+36XcTctvIn1Geu5r/d9qFUXRnELh0Xs7S+EuDEIi1ggEAgaQV5FHh0COmCwGCi1lPL1JV9zovgEfcP68kfSH+QYlL44B/IPcHPXm7ml6y1unnHTsuCzvQSEezF8SgckybVoR0WJBQAvPxE13RiEEAsEAkEjyK3IJcI7gkf7PYrFbiFIH0SQPgiAeVfMY+Hxhby97W0Anhr4FCrp/HI8puzPJ2V/Pm06BBDfJ9Rln8VU2QLR88LwADQVQogFAoGgEeQZ8ugU2InOQZ1r7fP38Kd/eH/n+/NNhGV7VUR4ab6x1n6z0YZao0KtPr/uu7kRn5ZAIBA0EJvdRr4xn1DP0HrHOBo7PNrv0RaaVcthtVQFpTms3+qYjTbR/vAMEBaxQCAQNJBCUyE22UaIZ0i9Y/QaPXtv24vE+df0wGq2OV9bTPZa+y1GKzohxI1GWMQCgUBQB6XmUmZun0mxqZhySzlQlboU6lW/RQyKS7pmINP5gMVUTYiribIDs9GG1kPYd41FfGICgUBQB5/t+YxfDv/CwuMLKTAW8NOlP5FWmgZAjO+F0cChJlZzlRVsNdUWYovJik4EajUaYRELBAJBHWzL3gZAgbEAgDe2vMGenD34aH3oENDBnVNzG1ZLddd0HUIsLOIzQnxiAoFAUI3D+YdZkryEpMIkl+2JhYnkG/PpFdrrginQUZOGuKb9Qi7Mz+ZsEBaxQCAQVOONrW/w7YFvuTjqYjoFdgJgaORQQFkj7hPWx42zcy8O17RKI9XtmjZaRdT0GSCEWCAQXPCsTl3NI6seIassixNFJ5gUP4lPx3xK+4D2AFwWf5lz7PWdrnfXNN2OwyL28tVhMdmQZdml25TZZEMnXNONRnxiAoHgguZA3gEeXv0wAOWWckotpfQM6YkkSUT5RAHQ3r89v172K6FeoQR7Brtzum7FsUbsWSnEOxYlc2JvHtc/NxBZlrGYRB7xmSAsYoFAcMEiyzKf7PqEAI8AbupyE1uztwLQzl/pqjQkcgjt/dvTPqA9PUN7EuEd4c7puh2Ha9rTR4vFbCMnuYS8tFLsNrtiLcsIIT4DhBALBIILlhWpK9ictZl7et7DtJ7TnNsd7Q0HRQ7i76v+xkvr5a4ptiocrmlPXx1Wk53SAhOyDIYSi3OfTi8crY1FfGICgeCCZHbCbN7a+hadAjtxY9cb0aq0zn3h3uFunFnrxVFZS++rWMRlhUq96bIiIx6eipxoPYRF3FiEEAsEggsOs83MF3u/oF94Pz4e/bFThJdNWUZ6Wfp516yhqbCabag0Ejq9BpvFjq2y9nR5kQmVSqkkpvMUstJYxCcmEAguOFalraLAWMDbI97G38PfuT3SJ5JIn0g3zqx1YzHb0erUtaze8iITao3y8OIhhLjRiE9MIBBccBzKO4RWpWVw5GB3T+Wcwmq2oalDiMsKTRTlVKDRqgiN9XXT7M5dhBALBIILjuSSZGJ8Yy7YCllnitVkQ6NTodVVue41OhVlhSayjxUT1TUIrU58po1FLIQIBIILApPNxC+Hf2FPzh6SS5KJ849z95TOOSxmO1oPNZpqFnFYrB9phwsoLTDSrnf97SEF9SMsYoFAcEHw3PrnWJayDAkJGZnR0aPdPaVzDqvZhkardrZ47DMuGr2PlsykIpAgrqcQ4jNBWMQCgeC8xy7b2ZS5iUvjLnVGREf5Rrl5VuceZqNSOSuuZzDj7uzGkKvb075vGADhcX54+encPMNzEyHEAoHgvCetNI0ySxlD2gzhnYveAaB3aG83z+rcw1BswttPh0qtovPgCNRqFQHhXvQcFUXfSy7MHs1NgXBNCwSC8xq7bGd5ynIAugd3p3NQZ0ZFj0Kv0bt5ZucWsl3GUGzGO8Cj1r6RUzu5YUbnD0KIBQLBec0HOz7gh0M/ABAfEA8gRPgMMJSasdvlOoVYcHYIIRYIBOctx4qO8eOhH2nr05aH+z7sUsZS0DjKi0wAQoibASHEAkErwWg1UmQquuA7/DQlh/IPISPz+djPndaw4MwoLzYDQoibAyHEAoEbWZa8DJ1ah9lm5oWNL1BhrWBq56k8P+R5d0/tnKfYVExmWSaAeLhpApwWsb8Q4qZGCLFA4CbWpq3libVPICMDShSvv4c/85Lm8ezgZ0XjgbPg1c2v8seRPwDw9/AXbQybgPIiE5IEXn7Cvd/UCCEWCNzErwm/0tanLcPaDCPEM4Tbu9/OguMLWJe+jhxDjrDizoJVqaucryO9RROHpsBQbMLTV0ldEjQtQogFgkYiyzL/HPuHS2IvOWNLy2a3sTd3L5PaTeLFoS86t8f4KbmYaaVpQojPkLyKPAqMBc73EV7ic2wKzCabaHHYTIhHG4GgkWzO2syLG1/kk92fNPpYg8XAz4d+ZkvWFsot5fQJ6+OyP9o3GoDUktSmmOoFSVJhEgCXxF7i5pmcX1iMtlpdlwRNg3i8EQgaSXZ5NgC5htwGjU8qTOKnQz/RO7Q3Px/+maNFR537agpxhFcEGpWGtNK0JpvvhcaRwiMAjIsdx7KUZRhtRjfP6PzAYhJC3FwIIRYIGklycTIAaqn+L6WVKSvx1HoyrM0wvtr3FYuTF/PX0b8AmN5rOotPLObaTtc6LWAHapWaKJ8oUksVi9hmt4lWfY3AZrexPGU54V7hjIsZx+XxlzOt5zR3T+u8wGKy4e1/DtSSNpeDSguac2CulZxWiCVJ8gdmV44tA26QZdlcx7hvgK7AIlmW32jqiQoELYUsyxhtRjw1nnXuP1Z8DICThpN17jfbzDy65lEAll+7nNVpq5nScQpGm5EwzzAe6vsQD/V9qN7r9wnrw9LkpXy6+1N+PvQz3038jm7B3c7upoDNmZtp59/uvF17tst23t72Nntz9/LWiLfQqrW8ddFb7p7WeYPZaCUgrO6/iVaDLMMXw8EzEO5ZBZVdolo7DVkjvhn4QJbl8UA2MLHmAEmSrgHUsiwPA9pIktSxaacpELQcPxz8gUG/DKLQWFhrnyzLHCtShHhXzi4m/DGBHEOOy5j1Geudr29YcANGm5GrOlzFOxe9w+MDHj/t9ad2mUqFtYJZ+2ZhsBqYlzTvLO8IssqymL58OuP/GE9ayfnp9l6Xvo7fE3/ntm63MTl+srunc8akHsrHWGZx9zRqcU64prP2QOEJyNwFB/5092wazGmFWJblz2VZXl75NhTIqWPYKGBO5etVwIiaAyRJmi5J0g5Jknbk5jZsbU0gcAeLkxcD8M3+b/h6/9fO4B+A7w5+R0ZZBkH6IAAyyzN5edPLyLKSC2yxW/j2wLcE6YN4bdhr2GU7j/V/rNZa8KnoHtydh/o+xItDXmRC3AQWn1iMxX52X8x7cvc4X+/P239W52qt7Dq5C61Ky8P9Hnb2yz3XsFnt/PvJXua8td3dU6mFxWRDq2/lq5kH/wJJDR5+cODsH2BbigZHTUuSNBQIlGV5Sx27vYGMytclQHjNAbIsz5JleYAsywNCQ0PPaLICQUvgWPv94dAPfLzrY2Zun8nmzM3Y7Da+3v81I6NGcmu3WwGI8Y1hQ8YGev3Yi98TfuePI3+wL3cfzwx6hqs7Xs26G9ZxV4+7Gj2H6b2mc33n6xneZjgl5hJngBjA3ty9zFgxA4PF4HLMkhNLuHvp3WzK2FTrfHty9jhf51a490F4xvIZPLXuqSY9pyzL7M3dS7fgbnioz93KTxajDYDSAiOyXXbzbKqQZbl1W8SyDEWpkLkH2vSFntfB8TVgNbl7Zg2iQUIsSVIQ8ClQ3zdKGeBYPPBp6HkFgtaGLMsklyQzKX4ScX5xAGzJ2sL05dOZnTibUnMpl7W7jGs7XstdPe5i7uVzuaL9FQDM2j+LtelrifWL5dJ2lwKctWUW7q08054sr1qP/uXQL2zM2MjgXwfz+JrHyavI4+VNLzNr/yy2Zm/lyXVP1hLpPbl7GBgxEA+1B3kVeWc1p7NlY+ZGFp9YjNlWK9SkUVjsFg7mH2Rf7j7G/TGOXTm7zvkew2aT1fn6ZEqJG2fiitVsB5nWK8QbPoCPekL6DvBrAx3Hg6Uc0ra6e2YN4rSCKUmSDsXt/Kwsyyn1DNtJlTu6N5DcJLMTCFqQImMRNy28iVJzKd2Du/PnFX+6WLOf7FLyhgdHDiZAH8Bj/R/DS+vFmyPe5L9j/kuOIYeNGRsZED6gyebkKEZRPTCsehT18pTlTJk/hXlJ80gqTKJHcA9KzCXMPTLXOcZis3Ck8Ag9Q3oS4hniVou43FLufL0iZQUPrnyQKfOnnJHr/dfDvzJ1wVRuXnQzOYYc2ni3YWJcrRCWcwqLyeZ8nZVU7MaZuOKYl07fioS4MBlyE5XX275WflrKwTcS2lb+DZ485JapNZaGOPynAf2B5yVJeh5YDWhlWX6h2pi/gfWSJLUBLgWGNPVEBYLmJKEggR8P/siB/AMAxPrFolPr6BrU1TnGYDXQNagrIZ4htY6/KOoifHW+lJpL6Rfer8nm5bSIqwlxZlkmkd6RvDjkRb47+B3bs6vWE2/vcTtzE+fy0c6PkGWZfuH98FB7YLVb6RzYmV0ndzU4/7k5cDRhAPi/7f/nrIB1MO9go9bRATZkbEAtqXl60NN0DOjIgIimewByFw7XNEBOK7KIzUbFUm81FrHVBB9Xej9ezIPSqt8rfCPAOwQ8/CH/aN3HtzJOK8SyLH8BfHGaMSWSJI0CxgMzZVluPY9ygguazLJMdGodIZ4hHM4/zILjC7i03aX0COnhMu72xbdjsCruXI1K4xTgoW2G0ju0N0arkcTCRJ4c+GSd11FJKr6b8B0zt8/korYXNdn8vbXe+Gp9XVzT6WXpDIkcwkVRF7End4+LEPcL64e/zp/p2dN5f+f7qCSV06rvHNSZUK9Ql4IiLU1WeZbzdfUylFuztjZYiE02E4+tfowtWVu4uevN3NjlxqaepttwWJ5efjq3CnFJfgWGYjMR8f4u82oVwVp2Oyx9rur9phoV7nwjlbSl4PbnjxA3FFmWC6mKnBYIWgW3Lb6Nk4aTBHgEEOIZwtGio/ye+DvfTfiOnqE9AWVd2CHCsyfNpmtwV2fnI38Pf36+7GeKjEUkFCYwMGJgvdfqHNSZbyZ80+T3EO4d7rSIzTYzuYZconyiAEV4Aa7vdD1397ybMK8wQj1DeeeidwjzCuOeZffw9f6v8VB7EOsXS6hnKFsy64q3bBkyypSYzk6BnThSeIRQz1CCPYPZlr2Ne3vf26BzHC066kwRO9X/x7mIQ/Dadg4kaftJKsrMePq0TGEKu83OnhVpdB4SwS8vb8FulXngf2OUeVVa6m63iE1l8PM1ytrvwHvg4DxY+RoggVoHNhP4VsYKB7eH1PNkjVggOJfYk7PHuQ5ZbCp2CliRqYijRUcZ0XYEgfpA3tn+jvMYhwg/3v9xuod0r7P9YIA+gCGR7llx8dX5sjJ1JV/v/5rMskxkZNr6tgWU4h+xfrGMih5FpI/SZUiSJCbFT2JgxEDnnDsHdkaj0hDqFUqppZQKa4Vb7iWrLAutSkvPEOUhKNInkr5hfdmftx+7bG/wOQCu63QdF0dd3GxzdQeWShdwSJQPAOVFZxfQ1hgOrs9k81/H2Lk4BbtVidi2WhQBdlrE7hbioysUEb7sPbjsXRhQWTVN7w9RlUsTvpXdtoI7QHEaWKr9rlcUub5vJQghFpw3FBgLuH3J7fx06Cegqvj/52M/Z1L8JAAua3cZt3W7jX25+0goSABwRhHXtfbbGnC4yT/e9THzj80HIN4/HlBc1wuuXsBFUXW7w58c+CRPDHiCd0YqDx6Oe8wzuEZO5xhy2Ja1rVnmX50TxSdo69OWKF/Fom/r3ZZuwd2osFaQUlJfLKgrDqv6kX6PoFG1AldpE1LdNV39fUuwe7lSVrUgq8y5razQ5DIPbUsHayUth5ntoawyriFtK2j00O92xf08aLqyfcRj4F9ZLta3snJcZG9Ahl+ug99vgU2fwsx4eKsNZOxq2fs4DUKIBecNh/MPY5ftHMw/CFQV/+8U2ImpnafSIaADI9qOcKYbrU5bDVQJcbBnsBtmfXoe6vsQrw17DYCv9n/FhLgJdA/u3qBj2we05/butztrWod5hgG1c4lvXHAj05ZNo9h0duEdsiyzKXNTrfQpUDpPbcnawtA2Q2nj3QZQLGLHg8bh/MMNukZWeRbeWm/8dH5nNdfWiLmGEFtbSIhlWaa0QGmOkX28am26rHKb24K19vwKhjw4rvytkroF2vavqiPtEwrPZcKwhyF6IAS2A32Asq/TRJjwFhSnw+F/YcWrINtAtivu7RWv1H/dkkzY8R2U5zfn3TkRQiw4bziUr6QqJBYoKQ1HCo/g7+FPmFcYfcL68NeVfxGoD8Tfw59Aj0CnVdjaLWIfnQ9XtL+CeP94hkQO4eWhL59xfnKIl3KP1YU4pSSFnAqlYN7M7TM5WnjmAS57c/dy7/J7uWb+NbVSkjZmbsRoMzIuZhxtfBQhbuPdhviAeHQqndNDcSpyDDkcyj9EpHfkOVs961RYjDaQwNO3ZS1ii8kGMkTE+2GzVC0ROCxiY7nyf6lryWAtq1lxRQMcXwtmA2Tvg+jBruN03qBSwcC74ZE9VfWlJQmGPqBs6341OH4fp/4KplLY+iXYrNTJ8bWw4FEoq7uefFNzfvl1BBc0hwsUiyqrPIvRc0aTV5HHxVEX1/mFHewZ7BSj1i7EoOQOz7ti3ll3Ygr1VKraVU9hmrVvFlqVFovdwvxj81mVuoqhbYbyzKBnCPMKa9T5HRHcGWUZ7M3Z65JStD17O14aL/qF98Mu27m207VcHH0xWpWW9gHtSSpKqu+0Tq779zoKjAVuW69vbiwmG1qd2ukCtpjqEYpmuC5AZPsAV4u4ULGIUw/mExjhhd5b2yLzASBlA5hKwCsETqyFjJ1gt0LM0MafKyBG+anSKJbyVV/AvHsgNwEietQen7ZVKZMZ2uXs7qGBCItYcN6QUJDgrAHtENerO15d59hQz1Cyy7NZlbqKNWlrUEtqAjwCWmimZ0ZTtEMM8AhAo9I4H0JSS1JZcHwBN3W5iReHvMhNXW4iPiCe5SnL+efoP6c8V4GxoJYre+fJnQR6BAJVHgoHiQWJdArshEalQafW8fLQl52doCK9I13KeNaFLMvOlCed+txpcdcYHGUkHS5gi7lhAWxnfd3KqOigtt4u20sLTRhKzGQeKaJ9v8Y9lJ01CYtA46lYtcVpcKjy9zH6DCLlA2KVn35tQKVW3NsAGTvqHp+2TQn+UrWMRAqLWHBeYLFbyCzL5I7udxDqFUqBsYD16esZGTWyzvEhniFsztrMI6sfcW6rK1r6fEOSJEI9Q8mryGPR8UXMOzoPWZa5rfttLtbvzYtuZkXqCu7pdU+d5zHZTFw27zLKLeW8MfwNOgV2otBUyJ7cPUxqN4k16Ws4VFAlxLIsk1SYxGXxl9V5vgjvCLZlnzpYrMSsWGq9QnrxzKBnGnvr5wS1hNjYgq5parueywpMnDxRjCxDbI8WiKGwWcBqBJ0PJC6G9mOqLODtX0FoV6XFYWNxCLF/pWUcFK+sJScuhr63VQnunl/BboOcQ9DtirO+nYYihFhwXpBVloVNthHnH8dVHa4COGXP3+pu6JFRI/HWetc79nwj1DOU40XHnRHY3YO713JBj4sZxwc7PyCzLNO5nlud5OJkZ5rYCxtfcNk3NnYsuRW5Tot4Q8YG/HX+lFpK6RTYqc45RXhHUGYpo8xcho/Op84x6aXpAEzrOc0ZfHa+YTFa0erVaHQOi7hlhNgRjFW9hKVfqCcVpWbKi5R1Yt9gffNPZONHsOoN6HMLlKTDmOchomfV/nZ1P1iflsBKIQ6o/L2RJBj6IKx+A3Z+q6wvp22Hv+9T9qt10GXSGd9GYzn/TQDBBYHjS9pR6OJ0OCKk2/q05bOxnzFz5Mxmm1trI8QzxFnKE+p+YBkbMxaAlakr6zyHoyfz9xO/Z3L8ZOeDTIxvDEMih9A7tDcnik+wKXMT9624j5sW3QQoRU/qItJbyf2syz19vPg4dtlOWpnSR7mtT9sG3ee5iMMiVqkkNFpVywVrOQp26DV06K88lIW09aGi1ExZkQlJJTkDyJqVtMoqcXt+Vn52vRw8qj2YDZlxZuf1jwa1BwS1r9o28gklyvrYajixDn6eAl7B0Gsq3PCL6wNAMyMsYsF5QVqp8iXdUEvJEbTkWM+8kHBYv0H6IFZdt6rOtecYvxg6BXZi5vaZtPdvz7C2w5z71qat5X/7/odKUtEzpCf9w5X1tgXHFxDuFY5KUnF5+8v5dPen3Lu8qlqWhETHgI51zsmxVpxVnkWHwA7O7SeKT3Dl31dyTcdr2JqlVEly5CCfj1hMNvSVlbS0enWj0pdkWT7jSHJH1yeth5qxd3Sl/6WxHNl6kpQD+ZQXmfDy06FStUCUenmO0sYwcw/0uh48fJXtV34GhnzFpXwmaPVwz0oIjKvaJknQth8c+BOS1yvrxzfNdh3TQgiLWHDOk1CQwBtb3wAg1Kthva4d4hOov/CE+Lbut3FPz3t4ddirpwwAu6bjNQC8vPll57bVqat5cNWDnCg+gUpSuQRNTY6f7Cw5GeYV5szXdhDjF4OX1qvOazmEONvgahHvy90HwLykec5CHufzMoLZWNXzV+uhdrGIk/fn8dmMVZQX1+6xu2neUX5+cTOJW7MpyWt85SiHRazTq9Fo1YRE+eLpq8NmtVOYbcDbv4WC44rTIaIXPJ0MV3xatb3vLTD8kXoPaxARPauE3UGbygYtxmK48Te3iDAIIRacB7y19S0AvDReDQ646h/en0CPQO7rfV9zTq1VEu0bzcP9HmZU9KhTjru56808PfBpssuznS7jv4/+jUZSHGkOd3J9vDz0ZeZePpc7u98JUO/6MCjuco2kcS4xONift9/5untwdz4f+/kpr3muU1FqxtNXSRHS6NTONeLiXAMb5irpXYXZtYul7F6WSkmekRXfHWLL38cafd26mjp4+inzyEsvwzvAo9HnbPwkKqA8V1nH9QwATQtcs01f5WeHcRDUrvmvVw/CNS04p0ksSGRPzh4GhA/g4X4PN/i4EM8Q1k1d14wzOz/oG6Z8Ue3N3UuYVxg7c3Yyuf1kpnSc4kwVqw+1Sk2XoC5kl2fz3cHv6BxY9/owKB2vOgd1dlrADvbn7adDQAf6hfXjkf6PnJfVtBzYLHZMBquzqpbDIi4tMPLbq9uwWZVUJmuNAC5ZltHq1U6r9kxSnsx1NHVwrAnbLPaWEeLiyocw/xYMxIsZqtSt7nldy12zDoRFLDhn2ZG9gxsW3IBOreO1Ya85RUPQdHQK6oRerWdPzh6OFR2j2FTMgPAB9AnrQ4xfTIPO0Su0FzG+MYxoO+KU4xzNHyw2pQKS1W7lSOERLoq6iBeHvnheizCAoVRp8ODtr4ie1kMR170r05wiDGAqd61YVlFqwWK0MfSa9sT2CHYW4WgMFqMVjU7lsg7s6VNVvKNJhdhuA0NB7e1FSq3rFhVilQoG3aNY4G5ECLHgnCS5OJmZ22cS4hnC31f+TbTf+ZnO4m60Ki1x/nGklqY6I6gb23owSB/EwmsW0j3k1PWx+4X3w2QzOWuFZ5VnYbVbaefnPpdhS2IoVoTYxSI220jel0dItA9qjfJ1bSy3Ittlvnt6A/tWp1F0UnFVB7f1wS9YT0le44XYbLLV6jVcPUo6IKzutf1GU5YLH3aHme0geaPrvsLkyotdeH/LQogF5xyyLDN9+XQOFxzmyYFPntdRtK2BMK8wMssymZM4h+Fth9eZV9wUOFojOmqFp5U0LhL+XMdQogRhefm7uqYryixEdgjg3k8uBkmp+1xebMZQbGb970lOIQ4I88I32BNzhRWTwVLvderCYrShq9HQwbFWDRDXs4mKeWz4EEqVNpbsm+26L2uvUmSjJS3iVoIQYkGTkV6a3iKt9E4aTpJVnsV/+v+HCXETXPbZ7TLJeeW8vuAQZmvLlAc83wn1DOVo0VFyK3K5tuO1zXadMK8wPNQepJWm8d/d/+XeFUrq04UjxK4WscZDjdlgxVxhxdNHi6SS8PDSYCq3UJxTFbB1ZHs2eh8tvsF6/EKUohsl+Q2ziu02O/kZZZQXmWq1ONRolfdRXQKdBUbOCpsVdv0IvW6AntcrHZGqu6gzdyvBU+dhM4/TIYK1BE3GK5tfYWvWVr6d8G2j3ZeN4WCe4rrsF97PZXuZycqY99aQU6pYFuO6hjO0fetsbXguEe4V7nxdX0GOpkAlqYj2jSatNI1Vaauc2xuaknau4xBih0tY66F2dj1yNFvQe2kxGqwU51alKGUkFjHi+o6oVJKz+lVpnpHQ6BqpOnWwf02GMxrb8QBQnbs/HIlG10T2WvY+MJdCpwng1xYO/Q3fT4Lpa0CWlbKSwxoecHk+ISxiQZNRblZKHn6598tmu0aZuYwfD/2ISlLVSodZfyTXKcIAO1PqCAgRNJrq5S8dfYSbiyjfKFJLU122XQg1wEFZI9Z7a51rwdXrPusrA6c8vLUYyy0U51ZZxGGxvvQYqVQb8wvxBKAkv2G5xFlHiwDFCI3uVjsK3sNTg1rdRJ//ibXKz9jhEDMErv9REd83wuCfB5TOSm37nfoc5ynCIhY0GUWmUgBOlJxotmt8vf9rduXsoltwN/Qa19q3yw+fJMBLy5Znx3L5pxvYkVJY6/jftqWSXWzksfH157QKXKkuxE3RAepUxPjGsCF9AxISMnKzelZaDVYzpG6itDAQ74Aqq9QnsCpS2SHEem8txjIzxTkVBEZ4MemBXvgG6VFViqWHlwatXk1pA13TOSmldBgQxrg7ujWfR9hmhX/uh32/K5WxfJXiLXS+VHFR758DB/5Qyku2H9tMk2jdXBiPmoJmR5ZlssqUog85hhyM1sZHbjaEzLJMAD4c9aHLdqvNzuqEHEZ3DkOvVTMgLoidyYUYLTZ2JBdQalRcfM/O28/HK5NIyS9vlvmdjzS2J/HZEO0bjVW2IiPz4pAX+XJ883lXWg07vkX+4Sqyk/IJi6tK0areZMHpmvbWkJNSSubRIvzDvPAP9XKKMCjdtfyCPRu0RlxRaqa0wEhYjB9qjcrlPE3K7p8UEe57K0z+yHXflK/gwZ1KHegh94OuiaKzzzGEEAuahFJLKTZM2CoUF1l6aTqpJamnOarx5Bvz6RvWt1bk7q7UIgoNFsZ1VdYzJ/eKpNRkZda641z35WY+WuEqvp+vbnz1oQsVxxpxnF9cs1+ra3BX5+t2/u3QqlqwEb2bkA/N51DFOExGaNupquSqXzUhduT0yjLOn4Mm153W5Rusp7SGa7qu5hE5qYoHKyz29GvJZ8XRFRAQo5SsjL+49v6QDvDofhjxePPOoxUjhFjQJGSVKtawzaB8Ocw9MpdJf01iS9aWBp/jz53pPDF3Lwczi+sdk1+R72xhKMsyW4/ns/lYPssPZaNVS4zspOwb1j6Y+FBvPlh+BFmGBfsyWbRfmeO4rmH8viONDUl5Z3SvFxoB+gBeHPIi/xv/v2a/Vq+QXs7XF0S0dHkeRxI1rCm5H4A27Tydu3wCa1vEoTGKaE5+sLfzdU38QpRcYrlStQsyy5n1yFp2L3N9MM5JLnE5Z7NgtykNFdpdfOpoaN/wqp7AFyAX7p0LmpT9J5U/cocQ/5rwKwALji1wjnF8MdRFucnKy/MP8sfOdKb/uBOD2VrnuDxjnrO04r70Ym6YtYUbv9rCL1tTuahjKL565QtLkiReubyqgMTJEhP/tySBofHB/PemfvjqNSw6kHUWd3xhcX3n61uk/aAkSXw29jNGtB3Roi5xt1FwnGyzEok+2OcXfHOrosUdQVuAM32o99ho7npvBOFx9VcZ8wv2xGKyUXTSQF56KXsXHwaUxhDlRVUu65yUUgLCvdB5NjJUyFwOs0ZB0vLTj83aqzRUiB/VuGtcYAghFpw1siyzKmU9AP6aWFT2qi+Jlakr2Za1jZ8O/cS4ueNYkrykznP8vSeDMpOVpyd2IaOogt+2pdUaY7FbKDYVO3sJH84qce4zmG3cOiTWZfzITqHMu38Yq/5zMfeNas/0kfHMuq0/eq2aHm382ZtWxNbj+djt9T8gCFqekVEj+WLcFxdGtLSxhBxrB9rGqhgQuRH2zTnlcJVKwtPn1J2Q/MMUq/qvD3bz+xvbObS9hGCNEkB5cqMSuZx5tIjkfXmExZ2BNZy1V8n5/eVaxeI9Fek7lJ8xQxp/nQuIC+A3XdDcrExdyfqceVjL23PrgN6UZ14OwKVxl1JmKWPasmnM3D6TnIoc3tv+nrOWcHU2JOURE+RF5/gUgjvMYl5CbcEuqFDSkYL1ihAfyy3DQ6Pi3Wt7Ma5rGBd3qp1v2i8mkPhQH56e2IXnLuvqtJh7RvlzMLOEG2Zt4eHZu5m/N5PtySLdSdCy2Awl5FniCIvyhPZjFIGrRu9x0bTrHdKoc0Z3DcLLX0dFiZmAcC9G9TvClUGvAFCwfzcWk42/3tsFQFiMHxxbBVu+aPgFTh6sen1sVf3jADJ2gk+4kjfcTFhtdr7feKJeL9q5gBBiwRnzya5PeHPLm8w/Nh8tvgSXPchlPdtiLe3JPfFf8OZFb3Jdp+sI8wrj60u+5uPRH3PScJIfDv1Q61wHM0vo1EbmibVPYNYeJ0X9FQdzqgKqyi3l/GftfwCca8RHc8poF+LNdQOi+fr2gY1qXN41ssoSWLAvi4d/2839v+yiwnyaJ/zzgeNrYdGTUFE7vUvQsuRlGrGjJTTWT2nDV5oF5qoc4RHXduSy+3qd4gy1UWtU9B0fg95by5Sn+tPdcxmekbH4ehkpyDZxMkHpctS+Xxhdh0fCT1fDkmfAVHb6k9ttikWs0Sv/jq449fiMndC2f7NWy1qflMcr/x5i/p7MZrtGcyOEWHBGHC86zlf7v2J24mxWp61Ga+xJ5zB/Oob5EOytIy3bF61Ky4tDXmTJNUsYHDmYMTFjGB87ns/3fO5sIABQYrSQWlhIocdfWO1Wnuv7CUg2/m/jd84x69PXszd3L4DTNX00t4wOYT5nNP9h7UOI9Nfzy92D6d7GDx8PDbmlJr7d2Hw50K0CWYaF/4Fts+CTvpCwCCxG2Ps77PnV3bO74EhLUQSqbdcwCKyMgnY0PzgLeo+N5o53hqP30ijCGdmLoEgvCqxRZO9JAGDUzZ1dioaQuvnUJ81Lgs8GKelIQe0hbsSphTj7AOQnNWmRjvwyE9d+sYmkk6XObVuO5wOwK7XqwTK90MBlH6/nUGZJrXO0RoQQn4MUGYu4c8mdrExRxGxv7l6eWf9MrV6uzcXGjI1MXTgVvVrPuxe/y/A2Iyg8OZCO4b5IkkR8qDcpBcpTvSRJaNVaLDY7/5mzl+tiH6VzYGeeXf8sO9NTGfrhV/R69V88whdyxLCGqV2mcmOv0QTSh10FK3h1obLGlFSU5Lx+uFc4KfnlpBdWnLEQh/vp2fzsWIZ3COG36UNY9Z+LmdA9nE9WJnEi7zzOMc7cpXw59rtdKbC/7HmYdTH8NR3+vg8O/uXuGV5QpKZ7Eqo5hldwoFLsAqDg+FmfVwLUy5+Gj3qCIQ9ihhIUF0GhNYr0nQkE+paj11rIKjKAVFmkpaab2WyA9J2w6k0ozoDFT0N5ZaZBl8ug00TIPwqpW2tPoCwXfrsRfNtA39vO+n4cbDiax46UQh76rcqFv+WEsqS0O7XIue29pYkcyirhu3PkwVoI8TnItuxt7Di5g0fXPEpaaRpPrX2KhccXsiLlNG6iJmJr9lYqrBV8M+EbJsZN5IneMzEbIukUrohibLA3u1IKeWT2bgrLzXy/8QT/mbOXP3elc9e3h3i438NUWCu4Y+UkyoI+wbfj++gCtzEm6hKeG/wcAC+PvA9JbeT3tJcwmC0czj9MjG8MT/f+kNmbS3jg11346bVc2//sOy/56bWE+el57coe6DQqnp23j41H8/hla4pLIJfBbCW/rKqEpizLGC3nmCv7xDrl5/hXleL7BcchN0EpNxjZG1a8WpWsKmhWbFY7J/N9iPJKUFJ3ghwWcROIx97fFK9HcWXQY6cJRHcPw46WDHNPYm3L4a1Ifnz3MZArf4d3fOe6/vvr9fD1GFg3E/59GI6vVnr3PpsOFz8NfW4C7zBY+Wrt6y9+CspzYOovSmpSE5GcpzzgJ2SXsjetiNf+PcTetCICvbQk5ZRxPLeMJQey+HefkhGx5UT+KbM1WgtCiM9BHP1aAeYlzSOzXFkbKTIVtcj1s8qyiPGNoVeosnZ1KEtxE3WOUNZd44K9sNpl/tmTyS9bU3hrcQLz9ypzrLDYUJk6OM91S4fHQK24jy5tP965fVz8EKbEPozaM41HVj7B+oz1+EodmPm3jY9WJHEgo4S3ru5JVGDTVeIJ99Pz3GVd2XK8gJu/3srzfx3gvl92OsX2pX8O0v+NFXxf+ZT95brjdHlxCcUVjWs551Zyj4BvJHgGQodxyjatN3S7UrGSC09AbiJYTcpasqDZMBms2GUVPh6Va8Kegcq667IX4MC8qoErXoVtXzXu5Nu+qrKwkcAnjKgugfhWJjT0GKYs7zyh+R2AZe2fB70//HIdFKeDqRRSNkH0EOh6ueKClu3Qayp4+IJaCzpvuOhxSNmoLHfMvQNOHlIukLEDukxu8trRR3JKUUkQFejJlZ9t5NuNJ7iufxQfT+0LwBX/3ciMn3fhpVPz1MTOpBVUsPVE6w/CFEJ8jmCz28ivyCelJIU1aWvoGtSVDgEd+Hr/184xhaaWCb7JLM8k0ifS+X5vWhF6rYpO4ZVCHOLt3PfesiMu7QhVEtzw5TaM2VdxRdR9PD38Lj4a9RFdg7pyUduLXK4ztetVyLLElhzFZbYzIZASoxIZecOAaC7rGdHk9zZ1YDRD4pU85av7tmXpwZMMfXslR3NK2XRUccu9v+wIZSYrv2xNAWD+noyGnXzTp/DdJEhc3OTzdmK3uVq0xhLlC/XYauV9bgKEVNbZbtsPBt4Ndy5S3neaqPzcPxf+fQR+vEI5VtAsmCuU32WdR7WNFz+t/Nw/V/kpy4plu/xlKM8/9QllGf5+ADZ+rCxBDLwHpq+FB5XlHUklMXxqDwZf0Q7/a1/mybAvsVdKwHuH/JBvnqMI8E9Xw6F/FEt51DMw4S3oOAGu/0mpglWdfreBpILtXyvLGvtmKw9xRWkQ3KHmDM+aI9mljOkSxrz7h+Gn1xDio+P1q3owrH0wgV5aykxWAr20fHXbAO4c1o5Ifz1vLzrc5PNoakTTh1bKzpM7KTWXMip6FAAzt8/k14Rf8dJ4YbAauKbjNQTrgzladBSArkFdKTIWtcjcssqyGNF2hPP9nrQierTxR1tZqza6hpU6qVck64/kcvOQWJYezOZ4bjnXdryON8cqFvXY2LGMja1d7L1jWCCWjHsY3c2bQKkbvx3ORadWsfrJUbQN8Kw1vimQJIkvbxlAUk4pA+KCuK5/FDd/s5W5O9PJKjEytksYKxNymLsjDXvl88XcnencOjTu1CcuPalYNnYLFKcq1qi6aco3Wmx2Vh4+yajOYej/vA25OI1fO3/KpdpdBC1/VLGybBa46D/KF/Sg6cqBKjVMer/qRP5tFTFe/17VtnnTYeqvENm4yF3B6TFXPlR66KtFFF/0uBKsdfBv5aGqJAPMldHMWz6HsS/WfbKiNEjbCnt+Vt5rvaDX9eDtmvrUvp9SJGXbiQLmpvoyOfp6huT/TZocSo53Z8JvnK1Yxf88oAhs9GCl/vPN9eQ367zh1r+VCPyNHytrygUnABmC25/R51Ifc7ancTyvnHHdwgnz1bPxmTGYrXb0lX2TR3cOY97uDOY/OILoIOU76PZhcbyzOIH8MhPBPh6nOr1bEULcSrljyR0A7LttH6WWUmelKoPVwMiokdzQ+QaifKP4ar/isorxiyGxILHZ52W2mcmtyCXSJ9JZivJARrFLMY3OEb4MjQ9mbNcwtp0o4K2re+Kn1yBJEqE+Hry24BD3jjz9H6laJdHBtw/p6bCzpIwRHcL45o4BeGiatwOQv5eWAXGKVTysQwgdw3yYvS0NWYapg2IoqrDwwfIjlBqt+Oo17EsvpqDcTJB3/YUWtv7xHoPtFpL6PkvH3W8rhRv63lw1oCxXqUBU0+I4BV+uPcbx3HL8PDX8sv4wXfRFzGMBEtAlYxrlOhNBoBTUb9NXWesDcj1iqLfD7/U/wbYvlSAcYwkcnAd/3AUP7WjwvAQNw+SwiD1r/D63Gwm7flCinR3BUYFximU87CHwDKh9sp+nQF61v//BM2qJcF6ZiR3JhUgS3PvTTgAqRr7EbvlhKn49wYm8csLjh1N+87+Urf+C8I4DGtaEwVE/OmWTElHtmEcTCrHdLvPqvwfpHO7LHcPiAJw1ARw8fkknLuke7hRhgO5tFF/8kZNlDBVCLDhT0svS2ZOzB4DPxn5Gh4AOLg0PFl2zCIPFwNwjc1tkjTi7XKnXnLphHZPSolHiM2FEx6o/er1WzW/TlUo6d18U73L8ncPjuLpvWwJripbNAuW5yvpltZzDO4e344m5StrSXcPbNbsI10Xf6EB+36EEvXRr48ddw9vxwK9KQYR7R8bz3rIjbD6Wz6RekXUeX2EwEJ/8O6vsfbhrcw+2BHUmdO27qHtcA1pPJSL1w27K4HtWKXmXp8FgtvLxyiQMZhvdpWQO6Z8jXwrCKOt41XIrb2u/ASsc6HgfHSY/jt0ziB++/pi7Tr7FvLxo7q3vxBqd8mUPiotRpVHa1FUU1S0AgjPG6Zr2rOEZaXcxICklJDWV4jH5I/jpKsVl3P/22icrqlZH+qa5ipjX4PovN3M8t5wgbx3dIv345o4BRPp7klYQAJwgJb+cIfHBzEry5eODV7PtyrE0qsho1ADlIc5RHSyo6YQ4vbCCcrONW4fGEu6nr3NMVKBXrZiRzpXLZUdOljK0fXCTzaepEWvErRC7XLWmuidnD0eLjqJRaRjWZlitrkPRvtF0DupMgEcAxaZibDVKzsmyzF9Jf/HJrk+aJHowpURZF72mdCW9JaXgxujOoXVWtaoLSZJqizAokZcfdIU5t7psvrZ/FH/eN4z/3dKPO4fHndXcz5R+sQEA9Iryp42/nok9InhxcjeeuKQTdw9ti4+HhuWHsmsd99jve1hyIJsDK34kVComdOzD3DgolueKLkdddIKS9/oqwVMJC6sOSt5w2vksO5hNt5eWYjDb+OiGPvyni7J2GCwXYL/0XQZOeZyMq+ay1XMk9xzsyZCP93DJh+t4N60LXUzf81WSDyXGBgSYaTyg91Tlddae048XNAqHEHt417DUfEIVl3DCAsjerzycxo8Cr5D6c321lUs1U3+FTpeA1lWsUvMNHM9V0vIKys1c2z+KSH/lmEh/PVq1RHK+EjTmyMt96s99/LEzveE31GGcEvCVsEDpttSED26Hs5WAzi4RjSvJGerrQYCXloTs0tMPdiPCIm6F5Bpyna+3ZW+jyFRErG8sGlX9/12B+kBkZErNpQToA5zbN2Zu5KVNLwFwdcerz7qjzcrUlejtEj1MZv7xeInSfveivfRtpLOtnJNUmXp1+F/Y+b3Su7SyCX3/2MD6j2sBru4bhY+HlnHdwpAkCfWJtUzrHAkrXob/bufmfnP4cnMmkiTx2pXd8dVrMVps/LU7g792Z7AwcA6ZUhg9Rl7F2yo1O/q15aNlEdyc8TrWr8eh8QpUAqhsZkjfftr5fLFWeQDqHO7LFb3boEo5qUTc3rMKr6B4rgEgCp/Ooxm7NIGVh3NIL6wgKtCTGwfF8O7SRMa+v5atz449fTWyNko0Khm7ROH+JsZcoTw0r08roUd+ObHBVUGOdLkMlr8E2fuUvwVJgtihSoRyrROVQ0UBjHkRukyq81pbT7gGeg3rUGUdatQqogO9OJBRjMlqY3daEQBrEnNZk5jb8BRBryC46gtY9y5c/knDjmkgCVmlSFJVZkZDkSSJTuG+JGSXYLXZ+XtPJuO6hiHLUGayurix3YmwiFshWeVKDlyoZyhLTixh18ldxAfEn/IYfw9/oHbk9JHCI87Xu3Nc69g2FoPFwIqUFfQrl/CstK59d33pDJY4Y8pyIfcwjHoWQrsoEbtzblPc1a0AnUbFpF6Rilu8MFmJJv5sICQugvJcnupWxO1DY/lrdwZ/blbWx06WKF1uQimki2EXSWGXIlU+WAyIC+LOW+9gmv0F7Gajcs4+N2GOHIA5eQvYrHBsFYVJW7D8ejO5fzzuLK6fdLKU3alFvDCpK0sevUgR0uy9imAGuf6O+HtqeeOqnmx+diy/3TOE3+4ZwvSR8dwyJIbcUhOHqjXNqBevIMW6OXmgyT5PgYKpXPkdOVxg5sV/Drru7FvNMzToHuVn7HDFBV1cI0q/uNJqDYip91ppBQZUktICNMTHg05hroJ2dd+2rE/K46k/9rlkOQDYGtMUpcskmL6mSYP7ZFlmy/F84oK98dI13nYcGBfIvvRivtuYzBNz9zLli02M/3AtF81czd7Kh46apOYb+HzNUXJKjHXub2oaJMSSJIVLkrT+FPvbSpKULknSmsp/DfNTCuoko0z5Q3tu8HMYbUZKzCWnbcoe6KFYjdXXiWVZJqM0A1+dL75aX3ad3FXrOFmWeWb9Myw8vrDWvjJzGR/u/JBlycu4/t/rGfzrYEotZUwtKabQr4sSmVnN+m4027+BBY/Bxo+U9x3Gwb3rYPxrinurMYXonZPOVYSsuXCUgQztCtd+C5IadeoGXr2yB9f4HOSOtcPhtxvJy1O8GiNUB1BLMj79r3M5jb+nln4Dh3ON6SU2jfyJl/LG8fLhKHQVuZjfjIKfribwlwlojywg9MA3bF7xJ+VfjMM2714+1H7GLakvIuUmKjmn2fsh4tRffEPbBxMd5IVWreKhMR0B2HxMsZJySoz8d1VS/W7IgNiqL3tBnRRXWPh5Swrrk3JduoKdisz0bLRSBRkEcyCjmNxSE2mVFenwClLSjq76n1JoBSBqoPIzY6friYoqi3b41+/tSikw0CbAk7eu6cns6YNreULuH92BUZ1D+WdPJt0i/YgNrrIUnXNyEwv2ZbH5eD43Dar/QeNUjO8Wgc0u82ZlGtOx3HLyyswAvLes7gDX7ckFzFyS6EyXbG5O+3ghSVIg8APgfYphg4E3ZVk+g29OQU0cKUnD2gzj6g5X89fRv4j1iz3lMQ53tKND0c0LbyZAH4DNbiPaN5ogfZAz6Ks62eXZLDy+kIXHF9IhoAOdgzo7961JX8O3B74FoI13GybHT0ZT0pnRxx8hv98M8PGAFa8ouYcejWynZjXBoieUIgEAMUMVq06lhuGPQPJGWDsT+t6ifCk1BGMxvNdBCTa65I3GzaehHPpHCaa5fb7yfssXsP59SFzMB1almIE9cTFxR7cxSXUTt7crwZatp1//obVO9fTELkxNLeSmZcVAKhO7X8G3pV7clfOWc0ySvS1tpTyGblKsoi5ApMYPfZoEXwxVPr+QztD96gbfQrifnvhQb/7Zm8HAdkHM+Gkn2ZVP/iM7hRDmWyMYxj8aTpymuMf2r6EkE8a+pOSznmqpYtYo8I+CG35u8JxbOz9tTua9ZYr3KdBLy6ZnxuKpO7WnaG9COrGSmmQ5goJyM+M/XEuRwcLMa3tx/YBoCOmo/HMQ3l0JnsvcrRTLWPyk8v9eXBmoFVC/EKcWGIgJ8iLMV1/7/xclQ+HLW/szZ0c6E7qHo5YkViXk8OQf+ziaU0ZciDdpBQbyy81sOZ7PnO1pvHZlD5cgzebiu40n6BDmw10j2p3R8b3a+hPq60FuqYnf7hmCh1bFwcwSjmSXMm9XOlabHY3a1SZNyC7BQ6MiLrhlXNcNsYhtwA3AqR7zhgD3S5K0WZKkD5tkZhcou3N2883+bxjWZhheWi9eHPoib414iwlxE055XDu/dujVerZmK3Vf9+XtY136Oo4WHaWtT1v6hfXjWPExl/VngL15e52v5x6Z67ovS6l5e3e3h/n7qr95+6K3yUtQvmCDoztXPYE7XGV7Z8NfMxpWIjHnkCIikz5QCgbc9LtzTRiAca+AubRxFYUcvU/3/1H/mISFsLN296cGYamAvCNKII2DUc/CgLuc9zzTcgO3mp9BYzXwlGY2PVTJqCO6I6lrP/N66tR8ddsAOob58ODoDvzv1v5cNOV+rjS9xhMWJa654/hprFQpIj7XNoqxpnf5YcgieGCb8mU84C54YCu06dOoW3lkbEcSskq56rONmG12PrxBsbpWHs6pPdg/SukKZLMo92mp4a6zGGHl67D+A6VYyQfdXAPQqiPLipAc/ve8KqW54WgeHhoV914cT6HBwq/bUk85vsxkxQ8LOpWByy4eTtsAT4oMylLMN+vrKXGp9YSwrsrnd2Kt8vCz5Fklf9c7TAnqqoHdLjPhw3XsTi1ysXLrwkOj5tYhsYT56gn28WBCD6VgTkJ2CZuO5TH+w7Vc9dlG3lmcwPG88mZvkFJkMDP6vTXsSi1iSr8o1I3orlYdlUrir/uHse35sQxtH0y/mEBuHRLLwHZBlJttdQZyJWSX0inct5ZANxentYhlWS4BTheMsxh4XZblUkmSFkqS1EuWZZcOBJIkTQemA8TEnJmL4UJgR/YOZGTevfhdALQqLZe3v/y0x3lpvRjedjgrUlbwaL9HndtPGk4S5RNF3zAl6GbM3DHc0PkGXhjyAgD7cvfhofZgWJth/J74O8H6YGb0noEkSWxMOYLd4outcCSeGk/m7EjDK/8Q6FCCi0yVv8DF6UrO4M7vlajO9mOh13VKJSDvelIGMvcoP9uPqaqxW53wbkpxiW1fwohHq9I4ToUj0ElXj/OmNBv+vAesFUqj8tDOdY+rj9xE5eEhvFvVtg5jlX82K6m7FrN8jSfjekbx3vosXtd+D2k50P/Oek8Z5qdn2WMjnX9fHcN9kaIG8EdaB26ZOJI+Q8bRKe4m1qSncOXAQegPZjOmSxh4aOCGnxo3/2pc2actHcJ8+H17Gtf2j6JnW38+XJ7E4gPZ3FjTBRgQrdx3aZZSj3j3z8oSQm6C4ib18ANHMZnfKqOsF/5HCe6q+X9RVk3o85IgtNMZ34O72JtWxLtLE3lnilJiddPu/UxLe47irlO59tJLWX7oJNtO5DPtFBZccl45nrKMVmXizvH9CQjJYM6ONEZ2DOX95UfILjYS4V9Hmk6bvnBovlLcA5RgLq234qFR1bbA0woNJFZ2KvKrmSZ1Gvz0WvpEB/C/tceJDvIi0EvHgLggfDw0+Hlq+Hr9CXJLTYT6Nk9+7p60ImcDlqv7nl0/47pK4Q6MU5bztp4ooEdbf5d9h7NKGd255VZYm0ruN8my7HisSAA61hwgy/IsWZYHyLI8IDRULCHXR3JJMmFeYfjp/Bp97MS4ieRW5PLaltdctkd4R9AjpIfz/e+Jv7M1ayt22c6WrC10C+7GlI5TAPh87+ckFirrJiWWbOyWIPZnFGO02Hhl/kGu8U9E9g5V1kj9K6MpD/8Dr1dLrVjxMuz4Ft6Nr7JSrSYlCGvz55C4BNK2KakOgXH139DAe8CQrwRFWU2w4UPYN1fpAuOwpswGxQL+9QZY87ayrSQLZ9mr6mz+L9hMytr22v9TAqByj9QeVx85lXV0w3vU3qfWEDPwcpY/OY4p/aJYY+9dtc8ReVwPNR9yf7hrEPteuYQ+F00GrZ7O0ZGMGjoEnUbF5b3b4O3RNMkO3dv489qVPegVFYAkSVzZpw3rk3JJL6yxJuj4f/7nAdjwgVLMf86tSl7rqtcVF2lIZ5j4fwAUBvdTRPvwgtoXLajqMU3yuia5j5Zm8YFsNhzN46avtnIgo5gjf77GePUurk16CjZ+TFSgF5lFpw7y2b8hE5slGrVOg0at4roB0cydMYyxXZUGCeuTcus+sOsVykNP0jKlQlqH8UpjhagBdQ4/WK0N4CXdGl8S9otb+uHjoeFwVgk3DIzm0xv78vY1PRnbJRybXXYW9WkOHAGP658aXfdDyVkS6e9JfKg3C/ZlujR42XaigLwyE10jG/8dfKY0VfrSUkmSbgSKgQnArCY67wVHSkkKcb411oPtdqU0Ydv+SrccD1/wqZ1qPyFuAqvSVjkDr94a8RZbsrZwcfTF6DV6JsZNRKvSsujEIhYeX8gfR/4gqTCJ14e/zsXRF/PH5X9w3b/XsSp1FV2CulBizUG2xLExI5/n/tpPhdnCQM+9SB3HK91ifCKUFmq7fqyaxNAHFcFb8Jjy/tgq5Uti72+KxVydbleeei2x/Wjwi1Lc03absh7toM9NSl7lD5crX+76APCPAbsVSjOhJN01ilSWlbKB7ccqNXC3fKaI/PE1cM3XigVfk1+nKnm9V3wCap3SJhBqRSfXJD7EmzQ5nP9ZJzNjXC9lro3Av5GWS1MxdVAM/119lJEzV/Pg6A48PLaj4ppzLEGcWKfce8cJsPUL5TPpdYNSTemSN6DTJezUD2bq7FS2+z1FwP65GKPGo/phPLoxT0CfGyG/mhA7vCItTc5h5aGxzy1KAZNGsj+jiHhfmTfLXyB4Via3qItIj7mCKC87rHiVdt0WcSizos5jS/IqsJrtFKxWMiM8PF2v3zXSlxAfD9Yl5XHdgDrWfDuMU5Yk8pKUoEZH/nA9HMwsRq2SOPjqhDPKboj09+T7uwby31VHuXlw1fdSRGVRjdxSU32HnjXZxcq56yvg0RSM6xrOrHXH2Z1axLxdGRgtNpLzyokK9GRij6avZV8fjRZiSZLGAN1kWf5vtc2vAqsBM/A/WZabv9bieUpKwRHGFxco667+le6Y/XOVfrHtxyjCFtIZ7lqiuAgHz3B+mUiSxJXtr2TxCaWpQPeQ7lze/nJ2phTw+fL9zLxqJpIkcbjgMH8dVfrOjooexRXtrwCgc1Bn+ob15c+kP+kXMhy7uohe4fFYNX7M25XBGNUedKYC6HiJMi+1RonozKwWjT3iMcXK3fe74ipO26aI4Kb/QmQfJdI4N1Gxqnpef+oPwxG4tfhJKDvpum/x02AqU9zNN/8J7S5S3NepW+HbS5SgKkeFKFDyYIvTYPRzyhrvls8UEfYKgQWPKjm8nS+tCgwzlcKRyuYMf96t5OkC9L6pThegy7RVEs9e2oUg73egri/TVkrbAE9emNSN1Qk5fLLqKFFBXkrQkF/l72HUQLh7hRKVnp8EUYNg5JPK/1FlUNG6XG8saJhnHcZtRxfwzfN7aKu7jas2fADdr4KCY9hQc9K/F21yE1r+Jsty4fOhgKw83KVuUX5Xxr3s+vvioEbgmSzLHE/PYo7n/9HWcoTVtl6kygO5bspHkLsHEhbQRzrKD2WBGC02F/FL2nGSZV8fxDvAA1RWJvq9T8hVz7hcTpIkRnYMYd7uDAbFBXLz4FjWJuXy2aqj3DMyngndI5QypHbLaZdrbHaZ7ScK6Rjmc1Yphl0i/PjvTa5dlBzu6JzmFOISI8HeOnSa5lunHd9NEWKAnSlVqZ9f3daLNs1Uz74uGnyHsiyPqvy5qoYII8vyalmWu8iy3KvmPkHDKSo8QZGtgliT0TXYxSF0jsbdeYmKa3X5i4qgVKNbcNX6ZbiX4uZS2hGmkl6oPKV3CeoCKCL86ZhPUUlVvwaPD3gcm93GI2tnIEkyAyI78O0dA9Fh4SntXEVku11ZdcGulevXcRfBI/uU+raD7lG+sPvfoRSiz01Qvrj73qKsJXe5TNnXkDq2A6cpAp5/VGnJNvU3GDBNqcNryIMr/wsdx1V9KUUNhE6XKt1qqjc6P7JYKWLf+VJlDncsgntWw4wN4BMO/9wPX41W+rHKsjJvUB50ZJtyrbuWwdUNSwy49+L2dVs0rZxpI9rx07RBRAd5srCypys6L3h4N9xZ+WCi1sAtf7Iy/A5m/LKbB5aWklWs/G5trqzK9IVhLAmG0QBkmHtizz0Kb0Zg3/Y1R+xtWVccpjyo/TxFse5aiqy9QOWyxqIn4cAfiqitfB2OLKsaZy6HbybAmxEuPXpT8g1callJdMVhToz9nGmWJ3nVejs+/sEQPQgkFT3LNiJhZ8mBbGc1O7vNzoY5yn2WF5kI1O0lwC8N/36jak1xZGWVuhf/OcjutCIe/m03O1IKeXdponI+lapBMRMfLE9kW3IBl/duc9qxjcVTp8bXQ9OsFvHJEmOzWsMAA2ID+eGuQXhWe1Dx9dA4a823FKKgRysgoyyDlJIUkg78BkA7iwUSqwnxyYOKW7r9mKpt+5Q+oqz/UGmvd+gfQKmw5eCT5UrkpiPgYX+Gsp7jq1NSjfqE9qk1l96hvXl9+OsYrGVozb48svphAv68gd3tv6KLlKJEOFfvGuQQ4k4TILCGS73r5WAqgc+VutN0qN1h6bSo1DD5Q0VEu05WRHzyB/B8FvwnAXpcU2O8CqZ8pRQG+WOa4grd+YPiFo8aVGXZxg1X2gD6RcKM9UoXosJk+GIYHPhTKWAvqZVqRTf/oQhRzOCaszsvkSSJy3pGsvFoHsWVkbwExYNai8WmCMzKwye5+8cd7E0vYk1iDtf9bzMHMorZk1rE8A7B5BLIAd0NznPmWeMAKPCM5VHL/ey3VFrZR1fAD1eAoYV6xjoKk1z7HU5BnrYc9H7w63VKfWdQfmfStoDV6FJ29EReOX1URzF5tyVuuHJ/faIDlJ0evhDRiw7Jv/KS5ice/X0Pc3akIcsyJflGDCVmfIMUYenjuRSP9iPqXJoZ2zWMbpXrkz9tTqbUaOXKPm04mlPG6sQ6otrrYd2RPIbEB3H/qKbtguQg1M+jmV3T9QSsNSGSJHFxp1B6VgvWuqxnZLNa4XUhhNjNJBQkMPHPiVz191WsSlmOSpbp02+64jad/5DSPi97P0T0hFvmwXWVqTcVhdB5EpiKlaIO66va2XUK7ASyxNKDSv1jR43ZA5VCfGu3WxkZNZJrO11b55xGtB3ByOC7uTk7AJ1aB7lH8M7br4hVzRJ6IR3h0QMw5IHaJ+owTnFVg7KeeJq11Xpp2w8e2gmD6m1V4IqHL0x4Uyn792k/+PdhpaFEfQ8COm+lL+89q0DnC39OU9al40aAhw90HH/mcz9HuaRbBFa7zPqjrkFD7y1NZMbPO5n2ww5kGb67cyCzpw+lzGRl8qcbMNvsPDJWiYTOs4UREu0DQIa5B3S9nGeDP6YisAt5Hsr6vSyplP+bRU826/0466yfPKi42ntco1j413ylWLKP7APPIOUB12pWHm5jRyhLF9mVCSCmMgb8M5or1JuxR/ZBrZLY9MwYfpo2qOpCkz8AYIJ6O//VfsyIZZfz1q/LefxbpQjHqJs7k9TWQFfddnzi6g6w8tVr+fO+YQD8vScTf08tb1/Tk+ggT95fdsQZVHQqLDY7idml9K4MxGsOwnxPLcQGs5VHZu9mX3rRGZ2/MRax5WQOOe+/j2w5s2p8XSIV42TTM2N4+5qeZ3SOs0EIsZv588ifAFhlKz/b8uis8cVv9IvKetWeX+GDLkqUZHgP5enZUWUHlOIJDrL3k5uXw4t/H+Db8T9jSHqN5HwD2cVGMivdhgcqIyijfaP5bOxnzrKYNZEkiXD7WG6zHlQKyD+6H54+oYhVXQREK5ZoXYx9WVkXvun3Rn0utQiKb1xgTfXuM1O+gR5TTh801bY/TKyMvFbr4IpPGz/PVo4x8QiZzzyL3XRqS6Z3lD9+eg0P/rqbR2crpVHtdpl/9mS6jOsc7kvPKH++vUOp+uSn1zCoXRBtAzyxGqyERPmg81RT2mYyXP4JJ/LK6RLhS0jXkXxpncR4+XMKu9+meHRMZc1yz0sPZtPr1WUcyChGzt6PLbQbs7elUhE5WOnZC4r7vevlSqT3V2OUgL+LHlMegLMqhThlE74VSoUxj7bKl3WbAE/Xdnxt+2Md9TxtpAImq7fS1pLM1YlPEJqjrIfv+usZgo2LFEO4+t9yDTx1aiIrrcGLOobgpdPwwKgOHMwsaVBp0qM5ZZhtdrq1ab7I31BfPTmldUeHf7vhBAPeWME/ezJ5ZX6Va1+W5QY1nzFZbeSXm51BYacj+6WXyP/qa8q3bWvY5Gtw8+BYnprYmUh//enrrzcDoumDm8k2ZNMxsCPj7Hq+KN5Pr4iByKiwD30add9blaAkm6UqQCogVlmj7XOLksur81UKX8h2/pk/j5+ORBMb7IXNpnw5/LMnA1kGX71G+SKS5VM/IVvNoNGhydlPqFSkWN31iWxDkCRFBFsalRpu+EWJjO55rfKvIfS9RVlnDow9bUTquYYsy6Tdcw/WnBy8hw/H//LJAJhTU9FGR7v8XmjUKjqF+7IjpZC/92Ty7nW92ZdeTHaJkQ9v6M3fuzPpG1NlbfWLCWTOvUMJ8VEeluJDvFCnGPDy88DLz4MKn+7Y9IGojx3hyoOH8B89ilusN4MVfi7sxkN2CySvV9bwm5hNR/MoNVqZ9+PH9DAd5pO8gXx8cD9/7Exn7oyhVfc94lElRS19e+VS0FglUnzz58rfxfE1znOqOtVfYEcTO8T5+gHzw7ys/ZFJUgIHpBiutMzhKq3iCZDCuzdo/o72ff0qm58cyy2rlfdak0OVD93dm1GI67OId6YU8tqCQ873e9KKmLXuGH56LS/PP8i9I+N5/JJT5/A70r/aBtb/N2ivqEC2WlH7+mJKUtbfTQkJ2EvL0ISG4NX/9O1EHXSO8G10Q4mmRAixmzlZfpIIXSD37VxMt/iB9B/5JifffofCX36h8769qG772/UAlQqur5YuFNmL0rR96GxGtMdXAHc6/wgB5u1Sql5d2iOCOTvSySo2EurrgbayYozpx+tQl59EExIPpjLkjB2Y71lHZEHlk6Wj6fe5SNfJjT9GkiCsS9PPpRVQsXs31hxljbH4r3n4Xz6Z0tWrSb/vftp+9BF+E13F5Y2re/DCXwfYkVJIQlapsz3e6M5hXN23dkeeQe2UAJeKMjMdArxRyQY8fDR4+moxlJjJLKrg5gOLiD+ZgN6Yy9P3vMqx3DI+3WnhPm9PNEdXNosQF1auc19b8QcHiOO/5vEA7EgpJCmnjE6VPWsJileCDMvzQKNXfhdihimVq767FDJ2cMCjD6/5vcqctv3qu1xVP+mxL/Fk1xkkZ1xP6XdLCVKnI0lQGDaYwBH3KMsep8BoURp9DI1XhDg22AuVBMdyFM9BRlEFoT4eda5n7k4rxFunpl3Iqa9xNoT5elButvH6gkP0iQ7AQ6NyVt1q469n6WMjqbDYuO/nXby1qCpCfunBk6cV4tTK+tYxdXRHMiYkUDRvHmWrVmM3GQn7z3+wZCqemuKFCzEdUmpKt/v7L/Rdzo2/ZeGadjMny7MJz01CspkZdckH+Op8KVmoBGoZtp2+JR7jX+dp+SEW2wdylXojekxsS1YCXyQJEk+WolOruKaf8sX5ycoker3y/+2dd3RU1RaHvzN9Mum999AJvXekKIoNFBXsvesTu8+uT+y9i12sCKhIE+m9h57ee5nUybT7/rhhkkACAQMBvN9aWUnunHPLmZm779ln799ewtK9hVCaij5tCZrCnTgy1kHKUkRdOXvevZIBtSsp0keBx6nLpVNoP1py/1X+/gfCYMD3hhuoWb8B82+/U/DscwBUr1mN5Ghey7pLsCdvXtEbkG/sO7MriPE34e3W+hJBZWkds2euISJZvpHm1dtw89RTW2ll964idD79kABbSgq3jYrl+Yt7MDA+hB32SCx5J6fCU15FHW4qG51ENiucvXCgJsJXnmkt21foqs3sGjOTPwv2V8piFYfiCnK34PSN53MxhQDvY8wydSZ4ohiG/4dofxMDEntQpu+Ll7EKpn6Ozx1LWs5bP4wPZ/RjxuBIYvxldTK9Rk2krxupxTVYbA6GvbScu+fIGRULdubxwYrGHO2NaWX0j/Y9YVnItnBh71AuSAzh87Xp3D1nO7d8vZW0hsDQ5y/pgYdBS6CHgZ9vG8LUfuGEeRu5enAUyUVV1NQfvZhCa4bYlptLxhVXUv7td0h2OwJB/iOPogkKwtinj8sIA1T8dBSp29MMxRB3IPWOesrqywkqzYAJz8lpNYAuSo4+rl6xosV+NoeT15cepKzGSn1wbxbW9WCO/Ry8RC3PaL50KSP1CvcGYGRQHb2NJagE/Lo5FYvNxmdr0qjf8AlOSTDE8g5xpa/T3/YJzzuvp4sjmR6kYo0c2eLxFU5vHGYzyYOHYP6tUdlKcjioXLIE91Gj8J1+FUgSeQ8+iD1fTlEy//wLKePHYy9tXrc2zNuIv7uOXTlmduWYSQw/uku0qlR2KdZlyjfkLQUVuHnqqDbXs+bHA5QGD6UmsjcOsxl7cTEGrZpXL+tFPgHUFLWjdvGBP+X87+Sl5JfXcG1cDRrhZLdTlp2c0jcck07Ny4vk2szfbMgk5tGF7MuvxGJzcM+c7Zz/9ho5Q2Dsf8nVRtGr4HF+qYhzrd0eFY3OFRGdl1xBpRmiLr78yCj/ozAo1o/nL+7ZbMkgLsCd1OJql6LV4j2F1NTbuWfOdmYt2o/F5qC0up7komoGxZ7cFJwQLyPvXtWXFTPH8MIlPfA0aHjygm78esdQxnYJcrUTQvDqZb1Y8eBoxnULwinRavnBQ2SX1aLTqAg8TD6zevVqJIuF2PnziP97ObF/LiRy9mfELphPwD134z56NGHvvI3bgAHU7drVyt5PPxTXdAdSVCu7CYPdgmDw7djLy1F7e+Mwy1+ymrUtFAEH1qaU8PZfySQXVnHfODlCdaPUhffsF3KnZgF/OAdxl2YeniKeZ1W9+LTsRfhIcEXAizxY9RJ2vS9Ls6LR5/3NXOdw8pFdX9UqD4ZPf4xc98cwFW0nvMvAFo+vcHpTvXoNDrMZ8/z5rnXg2s2bcZSU4HneeWjDwvAYP47abdsJuO9e7AWFlLz3Hva8fApfmkXYKy+79iWEINTbyO5ceX340MNda9TXNp/p/JVeyoTBvtgtDkKR4xY2xd5MYvX7RKakoA0MJNjLgMo7Ei/zellk43DBlN2/wPy75cpDg26FsY/L2yVJzh44JMJStA/mXAmXfS5rXVfmQtJPrAVoqBToCErkhcE9OLd7MOtTS9mYXobTKfHEPHk2/ufuAkZ1aqwoVFNvxzRyJsMWdnVti/I/WiG65lQU1bJyzkH0Jg2dBgQdu8MxiAt0Z3VKCRvSGtO9bvyy0XO2OaOM5ELZdT04thWd93Ym0s+N6X5RTOsfcdQiCVq1ij6R3ug0Kt5ZnoKXm5bOQR4IIY6YuWeV1hLhYzwicKp20yY0QUHo4uLkfu7umIbKEeamIUMwDZELpFh27qT0y69wWq2odMevnnaqUQzxKWBu8lyGhw0n0K25LGVBjZxeFOQRjq2wiJRRo3Afdw62QllFypqejr28HI2PT7N+2Q3CHH/uLuDP3fI+Ogd58lbhFGZolnO5egUDVQeg6ABDVYciOiVerHxU/stay1WadOY6hvOg/TYeOa8LozsH0CnQo/GDH3b0ak8Kpy/Vq+SShTUbN+KorqZqyVLyH3sMNBrcR8lejrDXXweVCqFWIzkcuI8eTcWPP1K5aBGS04loEqDnZ9Lx9wE5jcm1ntoK9bXN00eKbXa+2Z7NobAkL3MqZq84DiZcTrcDB103UZVPBBqzA7s5D41PEyGUqgKYe6scYWzyh1UvyznglfmyTOXO72Hym3Kq2d75UJ4uG+OqfF62TWOcVw47K925XrMYCcGD08bTKVh2Lb8xrTfZZbVUWezc9JWsib4714xHEy3vudtyOD9RFsQYkeDP1YOj5KIbbWTHsmyqSuo499aeaFopi1iXlIShR482pRmNSPDn41VpvLbkAIEeerqFerLiQDHn9Qhm2b5Cvt+UzYoDRYxI8KfPofzmU0RbKhV5GrTcNSae15ce5Py31xAbYCLEy8C3NzUGuH27MZNFewoYfVjRBUmSqNm8GdOgwcccK0NiIths1O/di7F37xO6nlOJ4pr+p5RnHrWcW0FNAU+te4rblt12xGt5lbLgRkBVAJlXyak11cv+Qqqrw32sLN5Rt3PnEf1SCo8s29U7whsrWpL9x3OBeqNr+63em5ECu8GMX2SN4PNfR8w8yOK4J3jEdjP9o/25bVQcXYI9OyRsX6F9kRwOalatRhcdDTYbNWvWUPjCCwB4nT8JlVFeGxVaLUItGwahVmPs2QNj3744q6qwpqY226evqdE9GOR5pKKTvazMlTZiqZFnxL3HRaAzaugT58t+s7xUIpx2Bop19BgVhsXoT+Gy9dSsW4ckSZgCZZdxYXZK851nbZCVrya9DJd9IetefzMF5t0G276Ui3jMux0+HC7rmbv5ywUngPmOoVxadifP2K9l/aUbEXdvdRlhkFOPBsX6Ma5bEN/eNIiLe4eyOaOMzRllhHgZ6BvpzX/n7+HHLfJ0+uYRsUzoHnxcpfHK8qoJiPIgqkfLs9O6pCQyLruckg/aptg2NM4fg1aFU4IRCQF8fHV/frl9CO9P78uEbsH8kZSPWiV48ZKeJy1/+J9y++g4nrtIfjRLK65hbUqpS+MA4Ov1mYAcYFqflk7O3fdQ/N57WNMzcBSX4DZwwDGP4davHwhB9eo1x2x7OqAY4n9CzhZ4KxF+vqFVY5xmlnVMk8uTjwig2ZS1Ai+HA/WCNGy5ua7ZAYDHOeeAWk3d9h1H7DOluJruoZ7894JGOcs+kd4AFEWe26yttjoXEdpHFteY/qMsGenmy7jpM1n56ETm3DwYhbOHul27cFRU4H/nHah9fCj/5lucNTX4Xn89wU8+edS+xt5yXmvp519gL2/U3T2UkgS0WFQ+/79PknXNtVgOHKS+xoZQCYZOiefmN0by3S2D6RIhryt7m1NI+OYzeo2VZ7y5+RJZN9xI1aJF+IfHy8fOPcwQ526Rc7qDesrpZFfPk2e/g++EbhfLOuOTXpXr8ZZnQN9rqB90F2sc3QmOaiyx2KtLvCsGoyWGxfszpksgVRY7f+0vYmicP59fJy/NfNpQH/hE0lvKC2rxCW7dle0ok13M5nnzqfh1HuVz5hx1f2qVYNaURG4YFsMzF3VHp1HRL8rXtQ573dBoPpjRj4gWoo1PF7RqFVcPiebbmwYxY3AkOrWKC95Zw7K9hTicEmklNTwWWsvg954i/dJLqVq6lJJ33qVy4UIA3AYc2xBr/Pxw69+fqiWLT/bltAuKIT5eDi6RdYwBsjeSr1bDnrmtFqNPNzcGoFy/+HoeWvkgT6x+HKfkZE3+BobWWbCVVGHolUjY66+hcpfTDXRRkRi6daN20ybq09LIvusuHNU1LN2azsaDhXQO9uCaIY2Skv0bamvqYoc3Hjx6hPy7hbJ9apUgxOvINRiFM5fyn34i80rZs+I+ciTuo0dTu0V2uXpdOBmV6ehrm7roaNQ+PpjnziVl9Bgse+VcUF+TbIj1GhWexiNXsyz75HYl775Lfa0dvZvGNRsTQhDf1Q9V2Q4iC/5EqFR4B7mh0QrqTPKaacknnxAWJRvixI0z5dzdQ+Rug+DERjEX/3i4Zj6c+yJc/qWsMz7wZrhxCZaBd/Fe9WhWRN7NDNvj3DwilnvGxrPsPyNx0x17FW5kQgAqIRdLGJHgj5eblk5B7pRU1+Pvrj8icOhY1FVZsVTb8A1pfdwPPfDYsrLIf/RRCp55ttW2h7iodxhPTu6G+2HlMI06NU9f2J1h8f6t9GwfJIeD4nfe/cfBUMPi/Xn+4p58e7MsHbs+rZTsslq65+1n+EfPULthA5LF4jK8Je++iyYgQPb2tAGPcydSn5xC1bJl/+g8TwWKIT5evrsM1r4JlkqSctczITKMTyK6yLV2WzDGaSXyTWooRrYWbuXPjEXMT1vA1l1fU+a0MFIdgaOiEs8JE1F7exP0qFyNRRcVhWnYUOp27aL0s8+oXvYX1cv/Inz6JJ5ZP5uB0b6uXGCA+EAPFt4zgrHdwiBmlCzjd9WPMO5p6HXFqRgZhQ7GPFeuqGUaNRK1lxc+V10JgNrfH32nTkfrCshGM+LTTwh7520AKn6dR92uXURkyikhgZ76I9ydjupq7AVyTEP1ypVYqiwYTI1KU9WrV9OzJpfQrD+x+TTOKA0eOtwumUbIC89Tv3cf6l17+EZ9ifzigUXyb6dTLpUYdnRhhu82ZnHbL+ncnH8hr2yo5tavZTnJHmGe/GdCZ+ID2zaT9THp6BMpP9AOjZddyYckFq8YEHFcrl5Jkti6WHax+gS3Pjt1lB6psX0s1bOOpj4llZL33iPzmmvbxcgNiPalS7AHGSU1JBdVc9WBpUhBIcT+uRCfa64m7PVG+V7T0CFtfh+8p0zB0LMneY88iqO65h+f58lEMcQnSv4O9pXL1R7f1tTyelAI/NX8aTatIo0f0xbQ21LPR+kHeL64FN+GXM3n9nyMRpIY1L3B8MbIa2TeU6bQZXcSmoAA3EeMAIcD8y9zASj6XNaZ7lt8kCsGylq9/72gG7eOknWQu4U2rPNe/ausnatzk7We3U5uGsOJItntFL/9Dtbs7I4+lTMeSZKoT0vDa+oUIt6RpTmNPXvSeesWYufPc60HHwtj9+54jh+PafhwqpYupeC554mY/SYAQS24pet27ASnE98bbkCyWqnJK0Vjq0GyWpGcTrJvvoXwx+4ktr6cuJ4Jrn4Gk5Z6ixOvyZPRBAVR+umnrI6+i52qbnKxBYtZdkvbapACux5x3EM4nRIvL97Poj0FrE4uafZa2AmUsbt1ZCw3DY9xueBvHhFLlJ8b1w2LPq795B4oZ+cy+XPtH9H6g4CjvAyh05Gwdg2hDdHqtpyc4z7vU4k1XV5u0/j7k3PvfS6vyz8hxt/E/oIqPludSow5H4/hw9DHxBD82GNoAgIIuPcePMaPI/Chh9q8T5XBQNCjj+CsrqZqyRKsmZkcHDSY6tWrqVy8hLLvvmu1ryRJ1Ke3Yzrdsc71lB3pbEHXoFTzw9Vk1snpR+Mix/G51sqe2nw5mrOBJ9fJa3Ld7BKMmMlFw55gaVYubk4n6bZKBjk0aIvlvEt9bIyrn9DILidjYiLacFmIQ+3tjX1fo2zcIW4cHsOj5x12o1Kp5VJ1pzkVP/9CyfvvU/Le+x19Kmc8tpwcnGYzxp6JiCbpGiqTCY3f8aexeIwfh72gAEtSEpqCXAz2egJbCNSq27YNVCr8broRoddTnZyJlLyX8jlzqN/fqKakqavBFB3p+t9g0mKptiF0OnxmTKd240YGqSpZa41Hyt8JH4+Gz2QFrBt+r+DnrS0bp735lVTU2rhhmPz9eXNab+bfOYxvbhx0QsFKE7oH80ST2IuRnQJY+eAY/N1bdktLksS2xZmU5jbXyc7eJ890r3lxKG6erafP2EvLUPv5ofHzQxchr51bs7KO+7xPJdYGAxX9/Ry04WHkPfoYktP5j/YZ428it6KOtD2pmOwWPLo1v6f533474e+8c9yfZWOfPmijIuUZ/LXX4TCbyb75FnLvv5/CZ5+jLinpiD51u/dQ8eNPpJ1/AbVbt/6j62oriiE+HpwOuSwagKWCDHdfOrlH8Nyw5zCpDXzj5SE/zQNWh5U9JUmMqanlP/GXwTn/hSF3oLt5ObOKSkm01HONTyLWjAzQaFwGtylCqyVm3jyCn3uW6B++b3xBr2+TcPrpjOR0UvLxRwA4mgQGKZwYlj2ysL6he9v0i4+Fx+jRoGl8mIuqLGgxUKt22zb0XTqj8fUl6NFHcJi80dhrqFyylJoNcvS+Li7uiHPTu2ldqU7el14KWi2Ju1ay3RmPcNqhLM3VNskSxMyfdlLdghrT2hR5FnzbqFj2PDORi3qH0ivCm+EJJ3ed9BDV5fWs/zWV75/bREVRLVsWprPmp2Sy95UTmuDtKnvYGvayUjS+ssdKGyk/qNhOAw9R6ezPybz6GmrWr+fgkKFULm6s1Vyflo4mNASNvz/+t9+OLTubuu3byXv4Ycq+/RbJ6cSamSnf29pIlJ/svh/glO8FbVlKaQtCCEKefhqh12MvKJDHWAjc+vdH7e9P4Qsvuu6lkiSR++BDZEydSsFTT2Ho0uWUpT4phvh4qC4Cp10uCjDhBTK8Q4n264q7zp0J0RNZ6WbEkbaSvaV72Z+7AbvkZLJbJPpznm7cR0BXRtfV8W1+IUP73IytIB9tUJBrFnw4ancTPpddRp1bIAuuepVNkb2hvh6n2dxi+zOFuh07sOflg0qFpcnMSeHEqD+YDCoV+oT4dtmf2tsb08BGQZcutUXEBjQPOqpPTaV2wwbc+spruD5XXIHDww/P7gnUbd1KxS+/oIuJIe6P3+m0ZQumwY0R+gZ3LZYa2RBr/PwwDRyI197tFOqOfCAtQU45OmR0AeqsDj5elcpLi/aTGO5FoKcBk17T5llwVZmFbUsy//EDbWVxnevvzX+ks3FBOjv/yqY4q4qIrj5H6SnjKC1D3WCI1T4+CL2ewhf/R83GE6si1BL2khJSzz2vzZWJbAUFFL38MrWbN5N1/Q04yssp/fRTAAr/9z8qf/sNbaicW+0xZgxoNBS9/Arm+QsofO55Cp55lowrriRjxtU4KluvFNV07OMDPVBJTqbZ5XV1faeE1rodN6YhQ4hdMJ+wN14n+rtv6bJrJ1FffUng/fdTt2MHJe+8g2S3U7VoEZW//Yb3tGm4jxpFyAvPt3lJ55+iGOLjoVIuoMCIB7AOuoXc6lyivaIBGBo2nCqVio8z/mDa79N4YpW8lpF4zgvNy/fp3ORKSgNvhZgR2AsK0QQfW8953hvbcM8zUjlQLsJgK2x7gfDTiZoNGyl49lkyr5qO0Grxv/127IWFVPzyC+Xf/4DT0nJZNYWjY81IRxsWhkp/fJG9R8P/9tvwu+UWVG5u3BsruHJgo2vZmpNL2vmyatehvE6Hw0l9nR2PHp0QRiPW1FR8rmwIGHNvbsQNbhosNXbXzdjYuzf2lBSmDe2LU2puTI1aDTq1im2ZjZ6TD1ak8OLC/UgSPD6p9TXk1tizOpf1c1Mpz6897r5NMTcY4tg+ARzcVNjstU6Djv29dpSVuWbEQgi8LrkYgJy778aWn3+Unsdxjgt+w5qRQdlXXx2zreR0kv/kkwitlpD//c+13ZKUROHLr1D2pbyPQw9pai8vTEOHuPQO3IYMpuKHH3DW1OAoLaXg2eewFxdj/u03nFYr9pISUsaeQ9oll5I8bDj2EvnhKlFnYeHmtwhYsRDPyZNRu7dvsQqh0eB53nlo/P0RWjmY0OuSi/E471xK3v+Ag0OGkvvgQxi6dyf4v08Q8dGHGLoe/+fqRDn9FxJPJ8wN61SeYazOXY1DctDLP5HCWS8Tv30rqokS7zdEWaY7aohTuREUMfTI/Uz/yfWnrbAAY/cj04u2ZpZRZbEzurOs4lNdYQWgT/fO8DPYiwqhc/u4b04V5gULyHvoYYTRiC4uDveRIzENHkTJe++R//gTAJR99RU+V1yB5+QLjlAU+zdRs349uqgo18zjWNSnpaNrEmfQHrgNGIDbgAFUr1iBtqy4WZR+4cef4RRqIt54FY9x4wCoKKwFCXxjAvC/5x7Kv5+D99SWS2Aa3LVITgmrxYHeqJFdgJLEUMwU4EMoZexxRrHM9wq66z1xShJbGwxxRa2V2Wsz6BPpzWOTujIg+viDEYszZVGcoqxKfEPbLll5CGudndoqK+biOlQqwYjLO5G5uxSHTV4r9Q014el39GAxSZKwl8lrxIcIefppfK+9lrTzJmH+7Xf8b7n5uM/tENUrV1K7ZQtVS+XI5uoVK7Hl56MNCWnWzmmxIFksqL29KZ8zh5pVqwn67xN4X3IxQqNGFxNLzj13UzZ7Nrq4OKK+/qqZofSeOpWaVasBiPjgA6pXr0YfF0fVkiUUv/kWVYsXI9ls6D//HENCglwpqaFaUuXChfhecw0lH30ExUWEvfO26/N0shEqFeFvvEFRVBSlH36Ex8SJhDz3bKveyZOJYoiPQW61PAsOcw+D3K2sN7qxM+9v9phT8Df6k7jPQv7nnwNwZWI834ZluPr+Z9Cjrr8lm43KJUtQe3rK0dA0fBELCnGMGoPTKbFkbyGvLjnAO1f24dG5SRRX1bPlifHsy6+kRnJiQhAYGIIDKPv8c2rWrcf/9ttQe568mqMngiRJVC9fjr5zF3ThYQA4a2oofPkVDL0SifryS1QGg6tt5Fdf4qyqwmmxkPfATApffBFHZSUBd93ZkZfRYUiSRNb1NwDIpTCPoZUrOZ1YMzIwDRp0Us5H7eeLo7SMwoxKFn+8m8BoT1KLhuM7pjvdz20UkCnLlVNE/MJM+A26Dr/rr2t1n3o3eVZiqbbJhjixJwCmfbvIFMGEUsYL9unsMffhvB7ueBg0fLk+E6vdyaer06mx2nnp0sQTEtmQJInCTNllWpRZRZfBIcfocSRLPttD5u5SIrr64OFvwN1HT6+x4SRvLuKSmX3Rt5BvfThVf/6JZLGgi45qtl0fE4O+a1dqVq36R4a46M23qN+3D6HTEfjIwxS/9TYpEybiOXEigf+53/WQl//YY1Qu/JPon3+m6LXXMQ0fjk+D0p/X5MkAhL/5JuVzvidw5gOuGfwhPMaMQej1+MyYjspgwHO8HGSnu/VWtCEhVC37C2PfvhTNmkX93n34zJhB8BOPk37pFMwLZDd3xS9z8b70UlffU0nAvffic9VVaAPbLl3a3iiGuAXq7HX8b+P/yKzMpMxSRr2jnvlBEzGue5sPYruwffenqIWaa7pdQ/3SbQi9Hk1gIOftEHwbBqM8Yrm2790MiB6H5HRS+OL/sCQludw3Mb/OxdC1K06zGam+nte3lbPjtRVklMpusteXHuRgg3D71sxyFuzMRa8CkwPMtRpMRhM169ZTs249ddu24TV1CrrIKEyDTo8iDdV//03OnXcBEPnFF5gGD6L8x59wlJQQ/s7bLiMMsjuu6Vqk2sOD7FtudYlJ/BtxNKmAVDZ7Nv63HSmPasvPx5qVjWnQQOz5+fINPTb2pJyP2tsXy97dFKSZqSqzUFUmLx+UOZt7LEpzqxEqgU/QsWeYBnfZEC+dvYeL7u+D1ssL04gRVPz4I1Xnh4F1L7mSP+Y6G/GB7gR6GrDa01m/p5A5q9OZ1DOkRSNsLq5jz+pc4vsFEhjV8gNqVamF+gYpzoJUM5JTQhynsE3mbvk9yt5XTmR32TANviiOgZNjUbdQH/hwbLm55D/1NMZeveRgtcNwHzGC0s8+w1FVRf5jj6Py8CD0xRfafH7Oujrqk5PxuugiAh96EI2fH9rAQEo+/oSq5cupXrUKn2mX43n++VQu/BOAjKlTUbm5EfLsM0estRsTEzEmJrZ4LKHV0nnrFjhsPVUIgddFF+F10UUAqNxNOM1mfK+/HgDPCydT9NIscv/zAIYuXQi8/742X197IoToUCMMiiFukT9Sf+fXlF+bbfti65tMVavYIclrQg7JwcXxF2N59zn0nTvj1rcv9u++47EnHmJM3HiCTfL6kC07m/JvvgHk9RPL7j0Uv/kWER996CruUGL0orrezstTE/l+U5ZcKxjQqAS/78pj8Z5CrtRpoM7Jpj+yiL/pA0aO0GPNyiZv5kyXge+StMu1/tFROK1Wil55FeHmhsbPj5w77kDl6Ym9qAi3QYNw69PnqP3dR47E88LJ1LZjsMqZxqEi52i1lHz8CZ7nnkvJhx9Rt2sXAXfdifu4cWTdfDPWlFT0CQlINjnoydCjfSKmm2K12FlmO4cgnQZvs/WI12vM9Zi85HXp0rwavIPcUGuPbYgMbvKtpzC9kvSdxXQaEIzfjTeQdd31qMzdKDO4ky/JLtu4QHfCG3KCd3+wj+vQcu45LQfz7F2Ty/YlWexZlcv1Lw/HbnVSU1mPX2ijK7WowS0d3z+QlC1FrPh2P2Oubvt6oKW6eWGL6J5yhLZQHVlFqDWK334bHA5CX32lRVeo+8gRlH78MdUrV1G1dCkgK5/53XRjs4IcrVG3cyfY7XieP8mV8uM5aRKekyZRt3sPmTNmUPrJp5R+IgdheZ5/PvaSErynTm3zckhT2uLO9bmseQ1mz0mTKHr5FSSrleCnnkLt7X3cxz1bUAzxYVz757VsK9pGqM2Ol9PJAZ2WQRYLs3182RI/HKl0N5Eekfgb/YnxiiF5/348xo/D2LcPZV98wcXOnhhNjUEa9alyGoaxd2/CXnmFkvffxzx/AfXp6aRfdDEACd3j+Oj+MZj0Gsy1NrZlVXDlwAisdomvGgTQjU4thzL1UpKqmHjnAIyJiViSkij7Uhb6qFq2DM/zzjtlY9USxW++hTU9nYhPPkYbHEzpp5+BRo02KAjvaW1T+DJ060blgt+wl5Sg8T95aSj1aWkUzXqZ0Fde/kfufXtZGUKrRe1x/G7SljhkiMPfepP8x58g9dzG9zT3Pw8g3NyQamvRBARgy83F0KMHAffdh7GdUpeasnF+GjV2A7l+A9DklR7x+pePrmPGc4MxeeopSDMT2a1t67XuTdJ6MpNK6TQgGGNP2T0dHpLIxzG3Yl0vVxZLCHQn2LOxvQpBQitVoA4ZWavFwdqfU9i9OhckuOi+3oR38W1oU4lKIxh3bTeMHjqS/s6htspGTC9/ug4Ncc0Gs/aUEhzrhe4wN3NeSgUAE2/ugX+EO96Bx6/rXJ+egbFvX1fu8OEYe/dG5eHh+m4DFL/+OiqDAd9rrj6iffWqVdjy8vC54gosBw6Qc8edCKMRYwsPvsYe3YlbshjJaqXkvfex7N1LyPPPuQqCnCq0gYG4jxmDs6oK40l4iDyTUAxxE6pKk9lWtA2AfpZ6rqysIkWnZdCAu7ks73c2le7myi5Xcl/f+wCwFxfjqKhA36mza6ZXu217s9wza5pcySbi449Qe3pi6N6D8u/mNBOxCO3ZGVODbux1w6LpFOzBiHjZLbe/oJLRnfxxzs9HCLm2hEotcNidqDUqgh59hMCHH+JA/wHU7djRoYa4cuFCymbPxvvKK1zr4KGzXjru/RxygVUuXozv9Olt6uOsq0NyOI4r2rLkww+pXrkS86+/4nvttcd9niCvN6ZfcimOqio6rV/XLlHLtlw5LsFtwACivvqS/CefQqqvJ+KzTyl5/wMkmxWPsWNx69cPSToyIrk9yDlQzrpfUlwpRgZLGSUrC3DXelDjHookZDek5JRI3lyIyVuPpdpGlyFtW2/18DVw9fND2Px7Oum7SnA6JVQmEypPT9yrKnjggj58vOFP9Bo1oQ2a6JommUZ2mwONtrkrVJIkirOr6DI0hMzdpexelYuHn4GqUgvz39xBl8HBnHNdN4oyq/APc0etVdH/vGh2r8wlY1cJGbtK0Bs1xPUNJGtvKb+9s5NeYyMYfnnz2Xd+SgUqjSA60e+Ic2gr9sJC9PGtp5oJjQbT0KFULZaLFsT+/hsFL7xAyXvv4XXJxc0e+iSbjfwnn8JeUIAuMpKa9etx1tcT/eMPrT4cHnLFhv7vxRM6//Yi/K03j1q97t+Ckr50iG1fk/aJXDAhxG7npsRb6OnbmUuqawhNvIrFUxYze+Js7qwZROVrb+OmdaN2k1yQ29C9G5qAALRhYdQlNRdCr09NQx3g75pxvZcnu44rf/8dR7dEzrvoFeLiGm9eWrWKUZ0CUKkEPiYdf9wzgruHx4MEw6YmMP6GbjgdEuUFtZTmyevIQqVCGxKCLa990h0O4aiuofTzL45IKapctIiDw0dgnj+/2fby739AFxtL8GOP/aPjGvv0wW3wYIrfertZFaDWsJeXk37pFNImnY81J/eY7SWbjbKvvqJuq/zQVbXsr+M6P6lBprR09ufs79ETe2EhUm0tZbNnH9d+WsOWm4fK0xO1hwf6hASi53xHzNxf0Pj4EPz4Y4Q8/TTuI0eiMplOihGWnBLz39hOcVYVVaXye2/XmrDqPPFOCMPd4EQtnNzxwRj8wkzk7C9n//oCvIPcCO/S9kh3T38jEd19qa+1U5Itz2S1QUHYCgvQqlUEexqICzS5CpNc1q3xe2Jukr97iMJFq6mvseNnqmfiTd0ZflkCUx7qR8IAubjE/g0F1FVZKc6sdK0fu3nqmPb4AK55cShGDy07/8qmJKeKjfNlT1ZJg2LW8q/38ds7OwDISzETEKSl+rcFxzOsLiSHQ/b2BAYctZ13E1euLiaGwP/8B4fZjHme/L07lPpVuXgJ9oICEIKsG26k9JNPMfbseVI8JO2N0Gg6fDntdEAxxIfY/AlpvnKe5CcTZxM7/CEYchf0ngE+Ubjr3OkX2J+8O+6i/IsvqVm/ntw33qTQ6MMCq+zy0nfpIgsrNKE+LRV9rKwsJEkSn2U3Pv1l9hkOQtAl+OhuUdesxF2LX5g841vy6W6+f3YTJTnyjUIbEoItP98lbl6fkkLFzz9jKyyi7KuvKHjxxeMWLyj74guKZs2i+I03mm2vmDsXR0kJeQ8/QvH78szeabFQt3077qNGnfAXq6ainorCWoQQBD32KM6qKso+/+KofSRJIm/mg9jy8nBaLGTdcIMrN7ElnLW1ZN91F4Uv/s8186zdvBnzb79jKzp2bra9pISU8ePJe/hhil5/HRqMsjY0FPO8+dhLSjD/9jvO2ub5qZLd3mYZQGtuzgmt07UXRVnN612rNWDTmqjXeeIZH05QjzD8o70RQhDe2Zec/eXkHignOtH/uGUlwxJkw52XXAGAJjgYe77skr5iYCTT+je6bm8f0BhdXJ5XTdXy5WRMn0H1mrXYCgs5OOtjAAwpWwjr5EOvcyIweekZNjWe+H7yDHDr4kysFgfBcV6uffmFuePhayCmdwD5qWZ+eH6zy8Vdkl2F0+Fk39p8svaUsfbnZIoyKjHtWUX+Y49R16BodjzYS0vB4UBzjAAh9+HD8L5cDqiSa0b3xNCzJ+Xff481O5vUceMpeu01yj7/HF1MDJGfz3ZVJjJ063bUfSucXvy7XdPFB2DlLLDW4MzeRX7cWLSqDEJD+lOfno4ucRqiSeWiX7fnEqoz4W2tIev6GxDA0s7j+XbeHib0DEXfKYHqFStw1tfjqKjAsns39fv2Uz7hQqbPWs6DEzvjFGpe6zON56ck8qM5jNiKOkKPIU5fV91oiL2D3dAZ1JQXyDf6wnQz/uHuaENCqFmzhoP9+xPz61xy77sfa2Ymam9vHBUVgJzvZ2ijdJzkdLpmvGVffU3N+g04zGZ8rryCmjVr8bnqSpw1tZS8/Q6O8grqdu5EstkwDT6xFBqnw8m8N7ZTUVhLSJwXY6/tisfEiZTPmUPAvfe4FG4c1dXYi4vRNxTJqFq0iJq1awl+6kkMXbuSefU1lLz/AcFP/rf59VitVK9bR8kHH2BJ2o37uHOoXvYXQY8/TuHLL5P34IMIvR7TsGEEP/4Y2rCw5u/Bjh1UzJuHPb8Ae14+5vkL0AQFoYuJwVFWhs+M6RQ8+RTJw2WXvDY8nPB33kZyOMl78EGsWVnoIiOJnP0ZNRs24nHO2Gbr0pLVStXyv3HW1VGzeg0+V3RcxaxDs+BDBEcYyU2THyLcvHQMvTQOh11+qIvp7c/O5bIkY1uUpA7H5K3HK9BI7sEKeo+LRBscjGWfXO3pnsMCsmoqGqsSHXzyNWxpvwOQffvtaHx8qPIejpAcqDcspi5pEEKjwdC1KyYvPeOu60b6rhJ2LstG46hD+/7j2Du92ixXve+ESCzVNtK2FwMw8opOrPr+IMlbGh/QdjQUcvDK3wFA/hP/Jey1V9EfR8S6vUjevzYo6JhtQ559ptn/vtdeS97MmaSOnwAqlSvYKvjppzENHkzUnO/If+xxfKZf1ebzUeh4/r2G2G6FL84HhxUsZrK2eTPm530MMKnJX3UnNatXE/z0U/hccQWS1UrBc8+THDyQWIeVCq84HP6BbB0ygp/M8hf5+81ZzOjcGRwO6g8epODpZ1z6v8+ag8nR1HHv9zuYUKclxGc4aT0S2fDNVq4aFHm0swSazIhNWtRqFX0mRLFxgew6K0yvpOuwUDZZ++Hvk4Rv+X7Kvvoaa6Yc5OWoqEAbGYktK4uadesQajWaoCDXWmr5nDmovbzwnDSp2THrduzElp1N8DPPULt5M5b9+9BFR1P85lsAuI89B9OggUgOhxwVrlKh9vPD2K//Cb0d+zcUUFFYS9dhISRvKWLLwgz6jxpF1aJFWNPTEQYDRbNm4aiqpm7HDuKXLUXj7495wW9ogoPxnjYNoVLJxvu773DW1qIJCnKlRJj/WEj+o3Jed/h77+JxzjnUJe2WlxWCAqnbsZOKH36gevlyyjt3IvDee13nJkkS+U89Tf0BudqW3223UrdtO/533Ylbv34gSThrayn58EPsefl4nHcuNatWk36JnJaiCQjA7/rrKPv2O1LGTwC7ndqLLyb0pf8h2WxU/f035d98S22DBKG+a1cCH/jPCY1je1BdLhvimF7+pO8qISTBl9x02RVs8tK7coABwjr5ENbZm9wDFYTEe5/Q8cI7+3BwUyEOmxNNcBCOkhIkqxWh0yFJEub581F7eJC/IBWIx6suh8ywsYQbSoh65G6KHpkJdgf2IZPwKq7Gvm83GZddDmo1oS/Pwuv881FrVUT18CNtezFhOSupT19HxY8/4X/rLXLUuVqNV4Ab593akwMbC1zntfqHg6yaI7/v467vhoevAU1VCaVXJWEaOhTLnj2kTTofXVwc/nfcjtf55x/1WiWnE3uD5+VYM+KW8Jx0HmVff4Vl5y4iv/gca2YmttxclyKXxseHiA+UIipnGv8qQ7wgdQG/Jv/KrJGzCMxLgppiai77gj8Lkuj88xwkNRATQc1qWSWm6NXX8Jo8mZqNm6j46ScSIvdhcNj4O/FWDD5e/OkOQ8MMWO1OvlqXyfQp8lNxxmWXNztuSWQ8M4fE8OrSZHpZ5SFfPOcA9XYnY7sc+8tYa5ZnAoequPSZEIlWryZ1WxGFGZXkJ1eQY/agPH4qgzY/j/lXOfUq9NVXKf/6a4Ief4y8hx+h6KVZFL00C214OFFffYnay8tViNx99GhUbo3Rn9V//w0aDZ7nnYvPNPl6JLsd84LfUBkNmIYNRQhB2KuvEPzUk66i821JrWhKXZWV5V/tI3tfOSHxXoyZ3gWhEhzcWEC/G+WUkrqduzDPn+8yVADF776LNSOT2g0b8L32Wtdxfa68gsrff8c8bx4AXpMvQB8fT90uOcUrYfUqNAHy2pyxp6xo5jlhAp4TJhD4n/vJuu56qpf9ReC992LNzERlMmHNyqb+wAE8J0/Gc+KEFpV/1J6exP3xB3VJSbgNGIAtJ4fqlasw//orgQ/OxDR4MB4Tz6X8m2+o2bAB8/z5qEwm6nbscD2wuQ0ciO8N1+M+bFiHrptVl9ej0akYckkccX0DcdgbXeotVRKafE9v6iptaHUnFrgU0yuAPavzyDlQjleD3KutqAhdeDjWlBTyH5EfoCo6z0AfGUOPde+zbtgLbIm/kdWzK7jmqx8xeulZ/ewOohIjCOr/X+z5+VSvWk3pp5+5jOPEG7txcNJF6AO9Eb79MM+bh6FrF3IfmIn3ZZcR9NCDAMTFa3HWWdB56wlN8Cb3YAV+Ye50bpCsrPhlOQCBjzyMvbCQ7JtvwZqaSt4DM1G5ucn6yy1gzcgg9dzzcB87FjgxQyxUKiI/+wxnbS3awMBmOfgKZy7/GkOcVZnF42seB+CPtD+4Nn0X7/j588W2Zzl/rZXudlj57GRumfwMxe+8izYkhMIXXiD1gsnYGzRfu2Xtpl7nhV5tQqq0k6uyMK5rECM7BXD5R+v5KNXOFVdfw9acSjoNTGRRnTuLduVxX3AwVfPymD2uM/sWySXOPIqsxMa6MSyu5fQch8OJ5JDQ6NRUltShUgtM3nJErlqjotc5EdhtDjbMS2Pd3BQA3Gqba926jxqJ1wXyTcj3mqspeO55dBERWHNyKP/+BwxdOrvaln39Df633gLIaT2VCxfKFUqauE+FRoP3pZccca7/JG0neUshGUmlRHb3ZfwN3REqQY8RYexbm8+vXxcx0NOf/Mfl9800bBi1W7bg1q8fFd//AMizTa8pjYIIbv36Ebd4EUKnI+WccVQuXEjAPfdg2b0Ht0GDXEa4JYRGg/s551A0axbJY8fiKCtH7e2N2tMTlZcXIc883exh5XBURqPrxqiLiMB3xnR8ZzRGfRt79sA46yVZZeyllyj/8UcEEPrKK6i9vXEbOKBdtaJPlOryetx9DPgEm/AJNrlctQC+IUcGh6nVKtx9Tvy8wzv7oNWrSdtZzMD4hlKA6RmyIW6ozSsBZT6d8cjfjd5qJiBYR1G+nNf81fO76DkqjLoqGwFRnviOkd2ymsAgCl94gX09Ewl69BF0EZFIWan43vMqOOzkPfwI2bffAQ4HZbNn43PVlejCw8m5517qtm4l6NFHGHDBhdh/TWX8Dd2wZmSQfeddWDMz0QQEoE9IwNCpE1Fff4UuOpqsW24l/5FHMcyfh7aJfryjogJUKqpXrpTHd/lyUKlOqDwlgNrdvd21mBU6ln+NId5RvAMAvVrP0owlSFk7+NTTDd8KG1PWOtmcIBg7/iZURiNBDz2Io7qawhdecBlha0gYuvxcyr0b161CrILBsX4MjPFlSt9wPlmbQWb3ifxRlQ8HAAnu9e1GxdZSjB5alxFOD9EQk2/n+thgV0QogMPuZN/aPBIGBvP7Ozuoq7Zx2aMDMBdb8PQ3NmsL0GNkGBsXpLsCSyTvAGLmzyP75luQ7PZmBtLnyitxHzMGldFIzn33Ufrxx2gjItAEBmLslUjxW2+hT4jHY+xYcu66G0d5+RHrrP+UqjILq384yOCL41w39IykUryD3Jh8d29Xu4BIDybf04sFb+7A3Os8fFd/jWn4cCI++Riptha0WopmvYwxsadLtacpuig5qMc0ZAilX3yJef4CbLm5+N5wwzHP0fuyqbK7eOlS1B6e2HJysBcU4HfzzUc1wseDymQi5Lnn8L/rLpw1Nce1vngqqKmwNDOsBvfG24RnQPvnmqq1KsI6+5B7oBxDQy3gih9/RKq3YCuQHy693/+G+h/NRGfKKlCRvUMoym+s25u0Ug68i+7ZaNw8z59E6ezZqIxGCp99Tj6Wry8eE8YjNBrMC36jLimJkOeeI/fee0kdN56wd96mrqEGbemnnxE/fTpTH+5PxS+/kPHa6zjK5DrDpuHDXYFpbgPkohdhr79G+pSp5Nx5F6GvvkLF998j2WyUf/8D2uBgdDGNWuC+V8/oEE1jhdOTf80nYVfxLtw0Rm717s0bJevZY1Iz3rsrd9hHYLO9T+fHn6eTT2MgU9MnTr8PP2H84jKuLNlOn/ihkCOw2pwkWjUMiPIG4NFJXVi2t5A/duXTL8qHAwVVhFY50ZltjJjWiehEP757eiNCwIuPDOX7Zzfh3FKG5VwbWr2aAxsLOLChgLzkCrYvzaKyxIIQsG5uCpUldXj6H1nXVO+mZdJtPSnLryH3YDk1Fe4YOncmbtGfLrWlphx6SvecOJHa9RtwlJcT8cnHGLp0IfOaa8n9zwOEPP881rQ0gh5/HPdRo/7xuO9elUv6jmIuuLsXO5dlk76zhMKMSsbM6EJwrBe5B8tJHHOkqEF4Zx/cffWUB02gzx3nYezRAyEEosEFHvzfJ4557JAXXyTvgQeoz8wAwNir1zH7qN3d8b/lZvxvuVnWAi8upmrxErwuPtLg/1PaEqzTEVSX1xPeuTGIqema8OEPg+1FaLw3GbtKsGBAGxpK1dKlVC1dKssh6vXsyzaCMONfKrvxEwaGkL6rlHHXd6csr5qls/cSHOuJp3/jg4LG15eEv5cjWa2kTJiIvaCAwJkzXdrdER9+gKO6Wg7Yeustcu+/n9y77wHA7+abKP3kU7JvuYXAhx+m4Jln0Xftgsf48VT88AOmIYOPuAZ9TAxhr75K7r33knZeY8yFoUF4x5aXh/vo0Xhffjnuo//5d0vh7OGsN8R7Svbwzb5v+D3tdwY41Fy9+Qf2BPiRqtPx9OjXqHziFaTQEAYOOtLl6jN9OhU//8xO/zjMkpkxj95F4e/Z+IdYmVNcxvg6HdsXZtJzTDgrPkziv74B7InRMX1QFL4mHX++sxOp1k6PUWGoVIKbXhtBfa0dnV7D+Bu6M/eVraTtKCZrTymp2xrdf5UlFgKjPQmO8SRpZS6SU6LnqLAjzg8gOtGf6ER/zMV1FGfLqUzHmrl5T5mC2s8P05ChrjzUiA/eJ2PaFeTNnAnIEnvtwcrv5ECXjF0l7N+Qj5unDpVK8OeHSfQeF4nTLtF50JEGSQhBTGIAe9fmob9rJEJ9/Jl22qBAor75GsnpxLJrF4Y2GOLDz0EbGIjv1TOO+9hnKg6bkxqzFVPTGbHp5K9XhyZ4A5CfYkY0cc9bkpKoih3C/vUF9Ds3irhpL6F2d8ctxMQV/5Uj9P3CTBSkVxLVvWVXr9DpiP7uW6zZOc302IVW64qa9pw4Aeu991L8xhuo/fzwv+su7CWlmH/9lfSLLkbodIS/8QaakBA8z5+EW/+WgxI9xo4h6rvvKP30UzzGyzNvjwnjqVm7lsIXXsR76hQ8xra8hqzw7+WsN8SfbX2LpQXrUQMjzCVo1TpeKy7FOfJhKn6TdVy9Lr74iPxHc3Edmb2uYsAjj/DLkoPoNCp6RXjzU/FBAqM8+PDORHb8nML2pVkc2FhAdbkcUHXP5YPwCZSNW32phehEf9csQqNTo2kIaAmO8UTvpnHNgnuNi8DTz8CBjYUUZVQS1cOP7iNC2fW3vEbWVBKwJYweWixVVlmh6BizFqHVHlHlROPvT+Rnn5Jz990Ig9Hl3v2nGD201FXZWPhBEgAX3d8HvVHDjy9uZtviTMI6e+Mf3vIac0icF0krcijLrSEg8sTXoYVK1UztTKFlCtLNrJpzEMkpNZsRHzLErT0Mtgf+ke7ojBqSNxfSu39/rOnpANRu2YJ55O0IlaDfedFo9XFH9BVCMHLa0dPytKGhx8zN9rvxBkxDh6AJCECl1xP6vxexl5RQs3o1/nfc7up/rAApY88esmJUE9xHjMB90Z9H7afw7+XsNsQWMxl5mxhdV8tbRSXYq9VIT6ciqrJwasMovEOe9XmMPzIKdu/aPLYtyiS+XyCb0svoHeGNTiWoLrWQ0C+QYC8Doy7vhKPeSU1FPaOnd2HhB7vYty6foZfGU1dlpa7K1mJwC8gC8UExnmTtKUOtUdF3QhRunjqEEBRlVBLd0w+Tl55RV3Vm5XcHjmmI3Dx1SBLkJ1cQ1vn48zlBFpWP/e03l3LUiZC8pZA1Pyajd9NgMMlG2MPX4KrYE9bJG5Bv7pYaGyMub/0GGhQjB4oVZlT+I0Os0DZWfneAkuxqIrv7unSZQV7Dven1EWgNJ+92oVar6DU2nM1/ZND3gXuImDCe7Jvl4MEKYyi+ASa0+hOLym4rQqNx6V0fIuT55+Wauf8ir4jCqeesM8S/vrYNzwAj5wzLx/n1JWRFhTM0sBf2tBWk/h6EatW5RP/wPXXr5AjGmLm/tKhCU9ygLrQ/qZg9OWbuGZdAdXk9TqfkClgxeug4/47G0mCBUR4Upst1TsvyZYWroxUd9wkykbWnjMQx4a60kG7DQvEOdHNJ8PUYGUZML/8W00aaYvSQX5/3xnamPNyP4Bivo7Y/GkJ9Yjc8h8PJqjkHMXnr0RnV5KeYARh+eQI5B8oJ7+zj8jxc9qjs2mu6pnc4Hn4GDO5aCjMq6THy5M3GFOQqS6W5NSQMCGL09M5HvN50nfhk0eucCHb9ncOWpXl0GdyJ7PAxhOf8TYXTh/jojqm5rQ0KPGpdZQWF9uCsMsSWGht5yRXkJVfQvfw9vqoNxC4JBq8ykLm1K1CGs7KS7JvkCFhNSAj6rkeWP5MkieKGSOQd89KZodLjvqyYv3bKa7BerRgP/wgPdq/M5fOH1rhqkrY2IwboOSYcp8PJgMmN0ZRqrYqIwyrYHCozdzSM7o03yv3r8snYWYK7r+GUGrDsvWVYamyMvaYLMb0C+OLhNdSYrfiFmYjt3Txt6GgG+BBCCELivMjaXeoqcnE4eckVrP05mUm3J7rSuxSOn8KMSiSnROfBwehO4sz3aOjdtPQeF8HGBelk7CqB+KkEa4ux2gSBUYpHROHs5azSmk5fsc/1d8lHKUxeoGHOyw78lmzHXloGQhA15zuEToe9pISgB2e2qI1bVWpxqVkBBDhV1JnrXXq4Xq2UPfMPlyOtayutVJVZMHrqjmocvAKMjLyy8wkLITTFu6EYu95Nw57VeWxdlMnm39NxOiXqa21UFNUeYw9H4rA5yUiSK+O0heQthejdNER2k4Nmpj7Sn+GXJ7TJ6LZGt+Gh1FZaXbmsTocTm7XRdb5ubgpFmVV88chaln+1r7XdNGPFt/tZ/2sqUsN1Ha8G99lIQaoZBATHnrgnpT1IHBuB3tT4IOD2jKzk5heu5M0qnL2cNTPiqj/nsevzdPCXI2PTo4Kx2rPolg3aiWOxLV6OsXdv3Pr0Ie7PhUfd14q/ZXnIjXobJqegd1d/zhsVhdMp4XRIrYoX+Ec0PrVf/vgA15rvqcDdR89t742mLK+GH1+Qq0LVVlrZuSybdXNTUKkF1/5v2DFd3E1Z92sKu5bnMOqqzsecWdusDtJ3lJDQP9BVGN7dx0CvsS3XW20rUd398Al2Y+WcAxRmVHJwUwFqjYqrXxhKRWEthemVmLz11FTUy+vzU+KPGuVbll/DntVyvd9dK3IIiHCnpqKeK58adMIl7c4GqkotmDx16I0de0vQGTQMvCCW1T8cBCA3VfZMHc2zpKBwpnPWGOK0b+dR4n8N8WIFKdJovhobScLAPlicIVw1+h7qtmxB24ZIYIfNSdbGIvLVTnIi9aSX1PDMjG4Eeh49ahnAP8ydkHgvBkyKISDi1LvS1GoVAREe9D03CnNhLdn7ylyqW06HROq2InqODm/WpyyvBo1OdcSstbKkjl1/56BSCzb9nk5cnwDXOjTIxdU3/Z6OX5g7/SdFs+anZGz1DlfJufZCqISc6vXaNnYtz3aVLj2woYADG/NRaQSXPzaAqlILP8/aQmZSCZ0Ht1wTV3JKbFuciUolGDo1npx9ZWQkycXuM3aVEprgjd6ocT1I/JuorbRiPI6HtJNJ4phw3H30/PlhEjn7y/HwNXSYu1xB4VRwVny6JbuN7KpQVCYbkfFz2Zs2mO7Oftw36Aq8Dd5Ao/rNsVj0yW5EtZ2MEDWvTO3FvvzKNhlhkNd3L53Z70Qvo90YcrGc4rFhfipb/8wkYUAQJTnVJG8pPMIQz3l2IwB3vD8G0STtKXN3KUiy0P1fX+xj6ed7mXx3L4QQ7F2bx99f70cIyEwqJX1HMeWFtXQZEkxopxOL2D4aAZEeXD9rGEII6mvtfPlooxu6y+Bg3Dx1GN21mLx0pO2UDbG5uI6qMgvhnX3kZQJ3LVsXZXJgQwG9x0fSa2wEiWPCqauy8cPzm1j8yW4AdAY1o2d0QXJKdBoYfLTTOquorbQel7fkZHMoLqKisJaoHicmBamgcKbQJkMshAgCfpYkqUWVByGEFvgV8AU+lSSpfSqkt5G65Z9TpQtBaMq5PEBwfmk6Xap6uYxws7ZWB8ZW1mTrqq1k7Cphp4dEUFdf+kX50C+q/Q3LqaLvhChqzVb6T4rm4KYCNi5IJz+lgsBoT9QaFZWljcXV03eVNAuoytpbhqe/gfh+gdSaraz5KZncgxV4+hlY+1MyoQnejJnRhR9e2ER5QS3DL0/4x27oo3FoRtQ0haXP+Eh6jZOPKVSCmF4B7N+QT/KWQpZ8KiswBUR6UJxVhdagxmaRZ+xDL5UfVIQQuHnqGHxxLGnbiwmK8SRpRa6rr7uPntCEM/f9Px7qquSgutMFN6/Gh4LT6bwUFE4Gx/TBCSF8gC+Bo30b7ga2SJI0FLhACHHK/LLL5y9gzjc6yvy6k27Koptvb9JVampKrKybm4K5uJbCjEqqy+v5an0GXZ9cxIGCSpwOJ8u/3kfqtsZaowVpcurRHsnKgGjf1g55xqAzahh7TVc8/Y3E95ddxnNf3cZvb+/AbnOQe6DC1XbvWnndVHJKFKSZyd5bRmR3P4QQdB8ZipuXjiWf7eHnWVsQKsGYGV3wDnJj2uMDuebFoSfVCB/OhJu6M2ZGF4ZOiW8WUR7T2x+71cmST/fgHSQH1BVnVdFzVBih8d54B7kx5JK4I9btuw4N5fw7e9F/Ugx9JshlKTVaFevmpmKpsZG8pRBrnZ3dq3JZ+d0B9q7Nw1xcx9mCJEmn3Yy46bmcDC+LgsLpRFtmxA5gGjD/KG1GA480/L0O6A/83bSBEOIW4BaAyMhj1+BtK53jg9lnlG+6FV5qMpOuw2atZySwfUkW25fIwvABMZ48WS4LyK/8MZlle+Uc19RtxYTEe+PmqWPrlnwcSAzqG8zUfuEtHu9MxTvQjageftSY68k9WMGqOQfJ2luG0UNL58Eh7PormxXfHSB5cyFIEiZvHQPOl9OqNFo1F9zViw3zUlGpVQy6MNZl6A79PpUk9G95HTqskw/hXXwwumsZdlkCdVVW6mvthB3HjbzXORFEdvejNKeaJZ/t4bMH5JKYPsFulBc0Rp4HRHpw2aP9T1kwXnshOSUqimqpr7XjdDgJifdu+FtqFgPQ0TRNVTskf6mgcLZyTEMsSVIlcKwbjgnIbfi7EjjiTilJ0sfAxwD9+/dvt3yRsO4DcfotRlWmok6KxN9Tx9RRsXy/KIUALwMz+0WzZ2UuxemVhLmrGF+rxVYhG+GoHn5k7ytj9kubKOznhWNbIQa9ihcvS0R7AtrGpzvn3ymLj3z39Eb2rcvH6Knj3Ft7ojNo2LE0iz2r5LfQP8KdSbcnNpuVBER4NKuQdDqi1qi46L4+rv/bkn99OEIIfENM+IaYqK2yUlVqwTfUxPpfUwG5uk9JTjXFWVWk7yghtk/rZRVPN6rLLWz6LZ196/Jd2/pOjHSlmzV1B59OtEd6n4LC6Ux7BWtVA0bADLg3/H/KmHHPcJZ9vYePbh+O0V2+mbgbtMz8aSfXBesYd303fvrfFi6s0eEuyQ8Ul87sizrQwOezVjO2VCJtTR6DnVoSBoVgOEvTWA49TIUmeFNRWEv34aGExnsDMOWhfhRlVtF9eOi/Mmq4JZq62yO7+VKeX0tEN1/sNgdzX9nGoo+T8I/w4MJ7emNoIqiSc6Acc1EtcX0DT0nBhLZgqbbxzX834LA7CevkTXz/IPJTK9i2OItti2WvkdtpNCMGuPqFIS2KuCgonG20lyHeCgwHfgZ6ARvaab9twifYxGUPNhdiv7BXKM//sZcbv9zCiHg/+hpUuFucYFSziDqG6SS+W3KAXdi4rJMvw1LMSE6I73b2R2j2OzcKS42tmaEJjvXqcDGH0xl3HwPuPnL0/CFX/ZY/M0j6O4e/vtxLVA8/3H0MZO0rI6mhUEf23jLOvbXn0XZ70qittKLWqti+OBOdUYOHnwGH3cmwqfH0OicCIQSxvQPITza7dMBPl/SlQ3j6tX/tYwWF05HjNsRCiLFAN0mS3m2y+UtgoRBiBNAN2NhO53fC6DQqxnUN4uetOaxOKSVHrWIqevqOj+SbnWlc/P46AG4eEcOEvlF835DGExJ39hsjT38j53WQgThbcPPUMXJaJ3yC3Fj1w0FXPjJA4thwKgrrKCs4fjWz9qCuyirLrGpVOGxOQA7c0xrUJI4Jbyxo76nj6heGUJ5fy86/sjpkvV9BQeE4DLEkSaMbfi8Hlh/2WqYQYjzyrPhJSZJOvHxPO/Lk5G6M6xrEq0sOkFJUTei0GAaNjOLNLp5M+1ietN81NgEvo5aeY8LJS65Q9IoVjoueo8Pxj/BACFnr3M1TR2CUJ2t/Tib3YDmSU2qWn30qyDlQDsjiNJHd/QiO9WTTb+lE9fRDdVjsgxAC31ATY64+UnNdQUHh1NBugh6SJOUBP7bX/toDT4OWc3sEMzjWF6cEvibZ9TYo1o8fbhmMXqvGyyiv4Q2/LKEjT1XhDKYlL4qnvxGHzUltpfWUPdxJkoTklFyGGCBhQCBdBofgF+qOT4gy41VQOB05K5S1joW325FrX4Nim68Fn2lpKAqnN4dKZZpL6poZ4vSdxexdm8+gC2PwD2893X7tz8kYPXT0HhdxxCy2NdbPTWXfejkiOqqHH12HhhDTyx/gjIruVlD4t/GvMMQKCqeaQ6UyK4vrCI33RnJKbJifxrbFckERa53dJYpyOIUZlexYli23s9gZfFFc42vplejdNK5+lSV1GD102OodbF8qRz97BhgZdGEsAZFK6UAFhTMBxRArKJwEPPwMCAHlBbWUF9SwfUkW+9bl031EKEYPHVsWZvDtUxu4/LEB+IaacNidHNhQQGR3PzbOT0WjVxPe2YftS7PoMjgEr0Ajq78/SNJKOdc7cUw4PUeH88MLmwiI9HCtU1/51CC8A91O+bq0goLCiSM6ohZr//79pS1btpzy4yoonErmvbGd3CbrtX3PjWLwRbHY6h1sWZjhUn3zDTUREOnBgQ0FAKhUgsEXx9FpUBDfPbUBq8WBWqPCYXfSc4ys+Jb0dw4qjUBy4qqr3G14KGNmdDnFV6mgoNBWhBBbJUnqf/h2ZUasoHCS6Do0xGWIh1+W4Eod0hk0DL00Hq8AI+k7S8hLrqAsrwaQjfDke3oR3kXWOh86JZ61P6eg1avxCjQy/LIEVCpBeCcfMneXEN8/iKoyC4XplQy+KLbDrlVBQeHEUWbECgonCbvNwbpfUkkcG453YOsRyxWFtWxdnEmf8ZEYPbQudbhDSJIk12GWpDYHbikoKJx+tDYjVgyxgoKCgoLCKaA1Q6w8XisoKCgoKHQgiiFWUFBQUFDoQBRDrKCgoKCg0IEohlhBQUFBQaEDUQyxgoKCgoJCB6IYYgUFBQUFhQ5EMcQKCgoKCgodiGKIFRQUFBQUOhDFECsoKCgoKHQgiiFWUFBQUFDoQBRDrKCgoKCg0IEohlhBQUFBQaEDUQyxgoKCgoJCB9Ih1ZeEEMVAZjvv1h8oaed9/ltRxrJ9Ucaz/VDGsn1RxrP9aMtYRkmSFHD4xg4xxCcDIcSWlspLKRw/yli2L8p4th/KWLYvyni2H/9kLBXXtIKCgoKCQgeiGGIFBQUFBYUO5GwyxB939AmcRShj2b4o49l+KGPZvijj2X6c8FieNWvECgoKCgoKZyJn04xYQUFBQUHhjEMxxAoKpwlCiFghxFghhL6jz+VMQgjhK4QYL4TwP9o2BYXTlQ4zxEIILyHEn0KIpUKIX4UQOiHEZ0KIdUKIJ5q0CxJCrG7yf18hxLKGdg80bNMKIX5v2HZDk7ZdhRDzm/zvLYRYJYRYK4Q4r2Fbn4b/Vwkhnjo1V9/+nIrxbHhtgRCiTxva9RBCLDm5V31yaM+xbNjels/hBOADYDywsEnbUUKIT07yJZ802jKWLbVp2N7SmB/eNwT4AxgI/C2ECGhpW2v7O9M4BePpI4RYKIRYLYT48CjH1AghsoQQKxp+enbEeJwtdOSMeDrwuiRJ44EC4ApALUnSUCBUCJEghPABvgRMTfq9A1wPDAOmCCFigLuBLQ19LxBCeAgh4oBXAK8mfZ8FZgMjgXuEEAK4DbhEkqSRwOVCiKbtzyRO6ngCCCGmA2mSJG1v6NtaOwG8DuhO7iWfNNptLI/jc9gJuFySpEcBLyGEXggxGHgK0J7Miz3JHHMsW2hzrhDi0sPbtbQN6A7cL0nSC8BioG9L21rpeyZyssfzauAbSZJGAB5CiP4t7Q9IBOZIkjS64SfpVA7C2UaHGWJJkt6XJGlpw78BwAzgx4b/lwPDAQcwDahs0tVXkqRsSY4yKwU8gdFN+q4D+gNVwJTDDjsS+FmSJAeQCkRLknSrJElFQggtoAFq2+8qTx0nezyFEL7Aa0C5EGJMw2tHtGv4+3rg73a7uFNMO49lWz+H7wJWIcRVQLokSfVANnBTu1/gKaQtY9lCmyKaf7YOjfkR2yRJWiZJ0gYhxEjkGfD6lra1sr8zjpM9nsif285CCG8gAshqZX+DgUuEEGuEEN8KITTtfa3/Jjp8jVgIMQTwQb7p5DZsrgSCJEmqlCTJfFiXtUKIuxpuWNHALuRZyeF9ixpuZk2xS5JU3bRdk9f+A3wnSZKtPa6rozhZ4wncD/wEfARcI4S4sKV2Qgg/5JvDqyfh8k4p7TGWx/k5DAKmHjqWJEm5gLM9r6mjONpYHt5GkqQNtPwZbGnbIQ/MNMCG/IDU0rYW+56pnMTxXAMkAPcA+4HyVva3GRglSdJwoAKY1O4X+S+iQw1xwyzrHeAGoBowNrzkTuvndivyB+QuYFbD7KOtfR1N/na1E0IMQv4gvXhCF3KacJLHsw/wniRJBchP0aNbafcS8OhZ8EDTXmPZEi1+DiVJypAk6VKgnxAi+J9dwelDW8bysDa00q7FvpLMnchemQta2dbW9/C05ySP54vAbZIkPYv8Wb6+lf3tkiQpv+Hv/cjGW+EE6chgLR3yDf1RSZIyga00uot6ARkt9Wtw5x1o+Pfbht9t6gvsaVjzAHmNI1MIEQ28D1x1JhuPUzCeKUBsw7b+yEU7Wmo3CpglhFgB9BZCPP+PLqwDaOexbImWPofzhRDxQggVYABq/tlVnB60ZSxbaENL7Vrp+7AQ4pqGbd5ARUvbWtnfGcfJHk/ADegphFADgwCplf19LYTo1dDuEmDnSbjcfw+SJHXID3A7sttjRcPPtchv5uvAPsCrSdsVh/X9EhjR5P8oYA/wFrLLRN1SX2BAwzE+Bn5v2PYDkN7kPDp31JiczuMJhCJH864FlgIeRxv3lo5zpvy051gex+dwALCpYXxvbNI2Gviio8fkZI5lC22mIa+vH96upW0+DZ/HVcgP1KKVbUf07eixOU3Hc2DDd7q6YQzdW9lfD+RlrCTghY4elzP957RS1mqIRB0PrJJkF+jx9A1FfrpbLB25dte0XTzQG/hNOnLt7qziFI1nm9qd6fyTsWxlf/+az+HhtHUsW2r3Dz/T7foeni501HgqtB+nlSFWUFBQUFD4t3HGBiwoKCgoKCicDSiGWEFBQUFBoQNRDLGCwlmGEKKmQWih6U+mEOL2Jm2eE0JMFLJM6faGbWYhyxVmNOSJKygonAIUNRQFhbOPTEkWWnAhZC1he8Pf5wDXAZORU3vihRA3AwckSRothHgasJ7KE1ZQ+DejzIgVFM4+HEfbLknSX8gKafdJkjQa2CNJ0iecJSpeCgpnGsqMWEHh7CO0QVClKVHAM4dte1MIUdHk/7iGftHAhpN1cgoKCs1RDLGCwtlHdsNM14VoufTfUmQlsEOFJYqRq5HddVLPTkFBoRmKIVZQOPsQR31RiLuBK4ESZI3gGCHEnciVovyRZQ4VFBROEYohVlA4+2jNEB8qkvCOEMKGXB7QA/BFljFdLknSGiHEuFNzmgoKCqAYYgWFs5GoVtaIXwQQQoxFLu7+MfI94FOgJ3CFEMKEXId27Sk7WwWFfzmKIVZQOPsobGWN+ND3fRdwnSRJTsAqhHgKmChJ0oGGgvB1KMFaCgqnDEVrWkFBQUFBoQNR8ogVFBQUFBQ6EMUQKygoKCgodCCKIVZQUFBQUOhAFEOsoKCgoKDQgSiGWEFBQUFBoQNRDLGCgoKCgkIH8n+tIfJ/5htjGAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(data/data.iloc[0]).plot(figsize=(8, 6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "R = np.log(data/data.shift(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "R.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>上海机场</th>\n",
       "      <th>招商银行</th>\n",
       "      <th>贵州茅台</th>\n",
       "      <th>万科A</th>\n",
       "      <th>比亚迪</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>486.000000</td>\n",
       "      <td>486.000000</td>\n",
       "      <td>486.000000</td>\n",
       "      <td>486.000000</td>\n",
       "      <td>486.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.000874</td>\n",
       "      <td>0.001314</td>\n",
       "      <td>0.002533</td>\n",
       "      <td>0.000533</td>\n",
       "      <td>0.002838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.020815</td>\n",
       "      <td>0.017098</td>\n",
       "      <td>0.018691</td>\n",
       "      <td>0.018943</td>\n",
       "      <td>0.030058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-0.078063</td>\n",
       "      <td>-0.053487</td>\n",
       "      <td>-0.082345</td>\n",
       "      <td>-0.084568</td>\n",
       "      <td>-0.105360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.011450</td>\n",
       "      <td>-0.008850</td>\n",
       "      <td>-0.007831</td>\n",
       "      <td>-0.010071</td>\n",
       "      <td>-0.014553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-0.000570</td>\n",
       "      <td>0.000264</td>\n",
       "      <td>0.001224</td>\n",
       "      <td>-0.000733</td>\n",
       "      <td>0.002545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.012218</td>\n",
       "      <td>0.010733</td>\n",
       "      <td>0.013105</td>\n",
       "      <td>0.010287</td>\n",
       "      <td>0.016757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.072245</td>\n",
       "      <td>0.095209</td>\n",
       "      <td>0.057168</td>\n",
       "      <td>0.079476</td>\n",
       "      <td>0.095310</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             上海机场        招商银行        贵州茅台         万科A         比亚迪\n",
       "count  486.000000  486.000000  486.000000  486.000000  486.000000\n",
       "mean     0.000874    0.001314    0.002533    0.000533    0.002838\n",
       "std      0.020815    0.017098    0.018691    0.018943    0.030058\n",
       "min     -0.078063   -0.053487   -0.082345   -0.084568   -0.105360\n",
       "25%     -0.011450   -0.008850   -0.007831   -0.010071   -0.014553\n",
       "50%     -0.000570    0.000264    0.001224   -0.000733    0.002545\n",
       "75%      0.012218    0.010733    0.013105    0.010287    0.016757\n",
       "max      0.072245    0.095209    0.057168    0.079476    0.095310"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "R.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:title={'center':'上海机场'}>,\n",
       "        <AxesSubplot:title={'center':'招商银行'}>],\n",
       "       [<AxesSubplot:title={'center':'贵州茅台'}>,\n",
       "        <AxesSubplot:title={'center':'万科A'}>],\n",
       "       [<AxesSubplot:title={'center':'比亚迪'}>, <AxesSubplot:>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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I2uHqQzUlt34MT3ez3CHrJrw382nKvhuESc6tB2cCZ0TEy4DHAw8Hvg7cBGwEbh1daJKaoHROUwDPB34EBIsMWTtcfaim5NaP4eluljtk3dThamjOvhuESc5tqTLzSbOPI6INPAO4ISLWAWcDp44oNEkNUTTcnJWXATupOg6HrCVNrMxsZeYBqsngNwGbM3P/aKOSNGqLFjwR8aqIeGH99IFUk8BPq59vBPYOJDJJGrHMvD0zr8zM20Ydi6TRKzmesh24MiJeAnye6qyS6x2yliRJK0nJRPDbgbM6l0VEq152iUPWkiRpJehp5m5dSF25aENJkqQJ4SRuSZKkAhZNkiRJBSyaJEmSCizvBjpSn6yf56Kbe7edM+RIJEnqzpEmSZKkAhZNkiRJBSyaJEmSClg0SZIkFbBokiRJKmDRJEmSVMCiSZIkqYBFkyRJUgGLJkmSpAIWTZIkSQUsmiRJkgpYNEmSJBVYtGiKiKMj4iMR8fGI+EBEHBkROyJiZ0RcOIwgJUmSRq1kpOk84A2ZeRZwG/ACYFVmbgLWRcRJgwxQkiSpCQ5frEFmvq3j6fHALwNvrJ9fB5wGfLHvkUmSJDXIokXTrIh4InAMsBfYVy8+AJzYpe0WYAvA1NQU7Xa76HfMzMwUtx03w85tz779XZdv3TCY3ze1GrZuONj37b75vR88ZNmGE47u++9ZiH+XkiQoLJoi4ljgzcAvAK8EVtcvraXLIb7M3A5sB5iens5Wq1UUTLvdprTtuBl2budf8OGh/S6oCqZL9xTX4Muy97zWUH7PLP8uJUlQUDRFxJHAlcDvZOZXI2I31SG5m4CNwK2DDVG6r/XzFIR7t50z5EgkSStJyUTwFwOnAK+OiDYQwK9ExBuA5wHDHdKQJEkagZKJ4G8H3t65LCKuAc4CLsnM7pNnJEmSJkhPk1Ay83aqQ3aSJEkrglcElyRJKjCc050kSRLQ/WQWT2QZD440SZIkFXCkSZKo7rMJXEHVL84Az6c6CebRwLWZefEIw9MSzXdpkqbyUirjwZEmSap4n01JC3KkSZLo/T6b3jbqUE3IbRC3dYLB3TJqPsN8H5uw3walX7lZNElSh6XcZxO8bVQ3TchtULeSGuYto2C4t41qwn4blH7l5uE5Sap13GfzRVTzmha8z6aklcVOQJI49D6bwOx9NqG6z+beEYUmqSE8PDcBxu0sEamhOu+z+Wrgz6jus7kOOBs4dZTBSRo9iyZJwvtsSlqcRZMkzcP7bErq5JwmSZKkAhZNkiRJBTw8p4nhTTAlSYPkSJMkSVIBiyZJkqQCRYfnImIKuCozT4+II4APAMcCf5qZ7xxkgJIkzWfSr1PntINmWXSkKSKOAS4H1tSLXgHsqu/8/fSIOGqA8UmSJDVCyeG5u4HnU92wEqDFvdct2QlM9z8sSZKkZln08FxmHgCIiNlFa7jvnb+n5q4TEVuALQBTU1O02+2iYGZmZorbjptB5rZ1w8GBbHcpplY3I465+vGe+3cpSYLeLjkwe+fv/VR3/p6Z2yAztwPbAaanp7PVahVtuN1uU9p23Awyt/MbcEx/64aDXLqneVew2Htea9nb8O9SkgS9FU2zd/6+iurO3zf1NSLNa9InPEqS1GS9FE2XA9dGxOnAY4BP9TckSZIO5RdHjVrxdZoys1X/+1Wqu37/L+DMzLx7MKFJkiQ1R0+TUDLzm3jnb40xr30iaVzNN+JmHzZ4XhFckiSpQPNOdxLgsXtJkprGkSZJkqQCFk2SJEkFPDynieZhTklSv1g0SZI0oTzTrr8smkbMkRBJksaDRZMkaWS8ZprGiRPBJUmSCjjSJNXmO1T6rqeuGXIk0srmtIXe+L4NniNNkiRJBRxpknrgGSmStPI40iRJklTAokmSJKmAh+cGoNuhm60bDnK+k/TG0p59+4v3nadPS9LksmiSJPVkvrl93b4k+uVhfPll8F4enpMkSSrQ80hTROwAHg1cm5kX9y+k/uvHmU5e/0K9Wsrfzkr99tZk49TXSaW69UuTck26QebW00hTRJwLrMrMTcC6iDipL9FIUoPY10nqFJm59JUi3gR8NDOvjYjnAEdl5p91vL4F2FI//Sng1sJNHwd8d8kBjYdJzg0mOz9zqzwiM48fZDBNs1hfV7exvzuUuY0nc6vM29f1enhuDbCvfnwAOLHzxczcDmxf6kYjYldmTvcYU6NNcm4w2fmZ24q2YF8H9nfdmNt4MrfF9ToRfAZYXT9eu4ztSFKT2ddJukevHcBu4LT68UZgb1+ikaRmsa+TdI9eD89dDdwQEeuAs4FT+xTPkoe4x8gk5waTnZ+5rVxXM5i+Dib7vTe38WRui+hpIjhARBwDnAVcn5m39SMYSWoa+zpJs3oumiRJklYSJzVKkiQVGHrRFBE7ImJnRFy4SLupiLih4/kREfGhet0XDT7SpVtCbvdpFxGHR8TXIqJd/2wYTsRlSvLq1qb0/RilXnJr+v6aVZjb2H3Oxon93Xh9fuzrxmdfzTWs/m6oRVPp1XXrOQSXU10jZdYrgF31uk+PiKMGHvASLCG3bu0eB7wvM1v1z57hRb6wkry6tSl9P0ap19xo8P6aVZjb2H3Oxon93Xh9fuzrxmdfzTXM/m7YI00t4Mr68XXceyrvXHcDz6e6mFy3dXcCTbsAV4uy3Lq1OxV4dkTcGBHvjYie7wk4AC0Wz6tbm5L1Rq1Fb7k1eX/NarF4buP4ORsnLezvurVr6uenhX3duOyruVoMqb8baNEUEe/oGNZrU1V1nVfXneq2XmYeyMz9cxbPvTJv13WHpdfc6J7Hp4EnZ+ZpwB3A0wYVdw9K3vdubRq1v+bRa25N3l+zFs1tHD5n48T+rqtx+vzY143PvppraP3dQKvGzHxp5/OIuIzer647e2Xe/fW6M/2IsVfLyK3bFYZvzswf1MtuAZo0vFtyReRubcbhSsq95tbk/TWr1/e/UZ+zcWJ/19U4fX7s68ZnX801tP5u2Dt3OVfXbfqVeUvj69bu3RGxMSJWAc8GPje4MJesJK9ubZq+v6D33Jq8v2b1+v6Pw34bF/Z34/X5sa8bn3011/D6u8wc2g/wAKo3/Q3APwFHA48BLp6nfbvj8SOALwCXUQ0Zrhpm7P3KbZ52Pw3cDOwBXjfqXBaJd2NhTocsG3UufcytsftrKbl1tG13PG7052ycfuzvxuvzY183Pvuql/w62rY7Hi/5czb0i1vGMq6uG9WtDE4DPpaHHpscudLclvMejEJJvN3ajEOeveY2DnqNu+mfs3Fifzdenx/7uubnMZ9h9XdeEVySJKlAEyesSZIkNY5FkyRJUgGLJkmSpAIWTZIkSQUsmiRJkgpYNEmSJBWwaJIkSSpg0SRJklTAokmSJKmARZMkSVIBiyZJkqQCFk2SJEkFLJokSZIKWDStYBHx0oi4pM/b/MOIuKjj+T9FxMmLrPPciNgeEdHPWCSpnyLiIRHxSxHxoYh40Jzle0cYmobk8FEHoOGKiL8D7q6fPghYHRGb6udHA0/NzH112wC+lpkPq5//M/D4zPx+RLwaOJiZfxARzwUuAg4ADwfujoin1Nt8GPCnEfF9YDXwmsz8q454jgf+CPiNzMyI2AD8KDNvGdibIElARNwC3EXVJ64GfgD8uKPJKuAo4OeAvwaOBb4LvBY4WPeDHwW+Chzssv33Ardl5tYBpqEhsmhaeR6RmesAIuJ84MTMvLB+3gZytmFdxPygY90f1j9QdS6zncRfAlfV7V8D3JGZb6y3uQv41cz8zNxAIuL+wAeAP8zMq+rFPw38j4g4IzO/vPx0Jam7zHzU7OOI2Am8PDP/oVvb+svlvwcuzMz31cs+BfxP4Cnd1gHOAG7ra9AaKYumleczEXFj/fhBwP0jotXx+o8BIuLpwL9QfZt6KnB9/fpJEfG9zg1m5t31Oh+h+lZ2MCKeVb88A7wjIm7OzJfMrhMR64ArgL8B3hoRRwMPBP6pXvaJiNiUmXY4koZhDXBHtxci4jDgex3PA1iVmZ+IiGuBp3ZZ57HA14AHRcRxmfndgUStobJoWiEi4vHAqVQjO7M2URVOV3cse2ZEfB7YAvxBvew/Ug1dAzweeCJVZ3AfmXl2/bueDuzMzH+LiF8HfhV485zmFwCnA48FXgD8W/1ze/3zGeDaiHhCZh4y7C1JffZQ4GMRcXfHsqvqkfhTgR1U/eAxwGeBt9Sj5a+k+sL3yjnbOwNoAw8BNgN/McDYNSQWTSvHDLAP+FHHsiu7tDsc2A88CvhCvewq4GX14/cDvwt8kOrYfue3rtniZgPwuoj4MHAacFpm7p/ze/4HcElmfqNbsPU3u5+1YJI0aBHxEGAmM0/qWPYyqsNxZOZO4NERsZ2qCLoeuBzYTtWPvrzLZn+ufv0hVAWURdMEsGhaITLzS8CXIuJq4DFUk7Y7HQkckZmPjojVVMfhZydI3kQ1AfJxVIfvfh04s2Pd9cDVETFbkB1Rt30c1YjRJ+sT406mmkP15cz8VkTcFBEPnSfk72TmgmfdSVKfPIV7pyDMOppq1BuAiDgOOBe4EXgA1ej5i6hOgjkGODIizqbqO28GnkQ1Kn9Y53Y03rzkwMrzQ+DXM3Oaarj5t+vHz6AehcrMuzLzSVTfsr6ZmXd3nvGWmX9DRyeQmV/JzI31djYBXwTeRjWy9aR6+SuBG+ZM7v53QCszH9r5QzUUftzA3gFJqtUj5S8D3j3npQdSTRmY9UfAO+vHF1H1b5dRTTN4d93+Z6i+WJ4MfCUzpzLzeGBtRDxsQCloiCyaVp4j4J6O4leBH0bEI6gKprmTrn8BuKF0wxFxEnAdcCtzhqsz83qq4/qd7mZ+P17gNUnql5dQXVrg43OWHw/8b4CIOAtYR32ILTMT+DrVdIVnUI1UfSczX5uZn6M6NPepjm19iuoQncach+dWnv8M/ATwx8AtVPOXPkJVML0pIqK+dMBxwCuovjnNOpyqc7nPPKOIeDBVkXQ+8Guzo1JzL1aZmXMLocOAG+ZMvKT+HT9EkgYoIp5MdcLLk+pCiIg4luoEmWng7QCZ+fGI+DRw4uy6mflnHdtZA3T2dz8HvKfj+afqZZcPJhMNi0XTChERRwDvpZpnNEPVGbyz7igeExE/SzXkfA7VCNTvATsy8+sdm3k1944A3Z97C5uHUB1qOzkzvxMRPwO8ierv664FwjocOL2eb9UZ60OBT/eaqyQtpi50Xge8IDM/3/HSGfXyq4Bdswsz846IOJJq/udc96t/Ztue1fliZm7rY+gaoaiLa60A9XVDvr3Q9UIi4pjMvD0iVgGHZeaP5mu7wDbuT3Vpgpsz8/sLtPsJ4K70j1CSNAYsmiRJkgo4EVySJKmARZMkSVIBiyZJkqQCAz977rjjjsv169cXtb3zzjtZs2bNYAMakUnODSY7P3Or7N69+7v1hfo0D/u7irmNJ3OrLNTXDbxoWr9+Pbt27Vq8IdBut2m1WoMNaEQmOTeY7PzMrRIRXx1sNOPP/q5ibuPJ3CoL9XUenpMkSSpg0SRJklTAokmSJKmARZMkSVIBiyZJkqQC3rBXfbFn337Ov+DD91m2d9s5I4pGkpZv/Zw+DeBdT53MU/JVxpEmSZKkAhZNkiRJBSyaJEmSClg0SZIkFbBokiRJKmDRJEmSVMCiSZIkqYDXadKSdLtuCcDWDUMORJKkIXOkSZIkqYAjTZIkFep29wPwDggrhSNNkiRJBSyaJEmSClg0SZIkFbBokiRJKmDRJEmSVMCiSZIkqYBFkyRJUgGLJknqEBFvi4ifrx/viIidEXHhqOOSNHrFRZMdiaRJFxGnAw/OzL+KiHOBVZm5CVgXESeNODxJI1Z0RfD5OpK6kDopM7842DAlabAi4gjgT4BrI+KZQAu4sn75OuA04JC+LiK2AFsApqamaLfbRb9vZmamuO24mZTctm44eMiyqdXdl09CvpOy37rpV26LFk29diSSNGZeCPwjcAnwCuBlwI76tQPAid1WysztwHaA6enpbLVaRb+s3W5T2nbcTEpu3W6XsnXDQS7dc+h/nXvPaw0hosGalP3WTb9yKxlpWnJH4jevQ01Kbt2+YUH3b1+TkC9Mzr7rZpJz68F/ALZn5m0R8R5gE7C6fm0tzgGVVrySomnJHYnfvA41Kbl1++YF3b99TcI3L5icfdfNJOfWgy8Bj6wfTwPrqUbSbwI2AreOJixJTVFSNNmRrFDr5ymQpAm1A3hnRLwAOIJqKsI1EbEOOBs4dYSxSWqAkqLJjkTSxMvM7wHP7VwWES3gLOCSzNw/grAkNciiRZMdiaSVKjNv594TXyStcEWXHJjLjkSSJK00ng0iSZJUwKJJkiSpgEWTJElSAYsmSZKkAhZNkiRJBXo6e06SpEnhhXxVypEmSZKkAhZNkiRJBSyaJEmSClg0SZIkFbBokiRJKuDZc5IkLVO3M/D2bjtnBJFokBxpkiRJKmDRJEmSVMCiSZIkqYBFkyRJUgGLJkmSpAIWTZIkSQUsmiRJkgpYNEmSJBWwaJIkSSrgFcElSStCt6t2S0vhSJMkSVIBiyZJkqQCFk2SJEkFLJokSZIKWDRJkiQV8Ow5SZIGYL6z9fZuO2fIkahfHGmSJEkqYNEkSZJUwKJJkiSpgEWTJHWIiKmI+Ez9eEdE7IyIC0cdl6TRKyqa7EQkrSCvB1ZHxLnAqszcBKyLiJNGHJekESs9e+6QTiQi3hYRJ2XmFwcYnyQNTUScAdwJ3Aa0gCvrl64DTgMO6e8iYguwBWBqaop2u130u2ZmZorbjpum5rZ1w8Flb2Nq9fK308T3Bpq73/qhX7lFZi7coOpEngc8CrgZ+GhmXhsRzwGOysw/67JOZydyyhVXXFEUzMzMDGvXrl1aBmNiHHPbs29/cdup1fDtu+67bMMJRxdvd762TTCO+67UUnLbvHnz7sycHnBIIxMRRwJ/DTwLuBr4F+BNmfm5iHgKcHJmbltoG9PT07lr166i39dut2m1WssJubGamls/bti7dcNBLt2zvKv1NPWSA03db/2wlNwiYt6+bsE9X3ciF3FvJ7IG2Fe/fAA4sdt6mbkd2A5VJ1IaqDusWc5fQgfTrSPZe16reLvztW2Ccdx3pSY5tx5cALw1M++ICIAZYHX92lqcAyqteIuVy3YiklaKM4EzIuJlwOOBhwNfB24CNgK3ji40SU2wWNFkJyJpRcjMJ80+jog28AzghohYB5wNnDqi0CQ1xIJFk52IpJUoM1sAEdECzgIuyczySX6SJlLxbDY7kcnVj8mR0iTKzNu59ww6SSvckk8BsBORJEkr0fLOm5QW4AiWJGmSePabJElSAYsmSZKkAhZNkiRJBSyaJEmSClg0SZIkFbBokiRJKmDRJEmSVMDrNKkR5rum095t5ww5EkmSunOkSZIkqYBFkyRJUgGLJkmSpAIWTZIkSQUsmiRJkgpYNEmSJBWwaJIkSSpg0SRJklTAi1tKksaWF8bVMDnSJEmSVMCiSZIkqYBFkyRJUgHnNEmSJs58c52k5bBoUqN16/ic4ClJGgUPz0mSJBWwaJIkSSpg0SRJklTAOU0rjJMjJUnqjSNNkiRJBSyaJEmSClg0SZIkFbBokiRJKrBo0RQRR0fERyLi4xHxgYg4MiJ2RMTOiLhwGEFK0qDZ10laTMlI03nAGzLzLOA24AXAqszcBKyLiJMGGaAkDYl9naQFLXrJgcx8W8fT44FfBt5YP78OOA34Yt8jk6Qh6rWvi4gtwBaAqakp2u120e+bmZkpbjtuhpnb1g0Hh/J7Zk2tXv7vbOp+929yccXXaYqIJwLHAHuBffXiA8CJXdraiczRlNwG1cH0oyMpNez3sSn7bhAmObdeLaWvA8jM7cB2gOnp6Wy1WkW/p91uU9p23Awzt/OHfO25rRsOcume5V3icO95rf4E02f+TS6uaM9HxLHAm4FfAF4JrK5fWkuXQ3x2IodqSm6D6mD60ZGUGnaH05R9NwiTnFsvltrXSb3wRuTjq2Qi+JHAlcDvZOZXgd1Uw9QAG6m+jUnSWLOvk7SYkm9OLwZOAV4dEW0ggF+JiDcAzwO8L4ekSWBfJ2lBJRPB3w68vXNZRFwDnAVckpn7BxSbJA2NfZ2kxfQ0CSUzb6caxpakiWVfJ6nTcGbuaui6TTSUJI0XJ403i2eDSJIkFbBokiRJKmDRJEmSVMCiSZIkqYBFkyRJUgHPntPYme/MwG5nlCylrSSNimc8jwdHmiRJkgpYNEmSJBWwaJIkSSpg0SRJklTAokmSJKmARZMkSVIBiyZJkqQCFk2SJEkFLJokSZIKeEVwSZImQLerinv3g/5ypEmSJKmAI02aGN67SdJKYF83Oo40SZIkFbBokiRJKmDRJEmSVMA5TRPA49uSxtVSzviyr9OoOdIkSZJUwJGmIdmzbz/new2NxljKN9Z3PXXNACORJI0LR5okSZIKONI0RjyeL0nS6DjSJEmSVMCRphFz9Gg8zbffnKMmLZ/9Yv/YV/WXI02SJEkFHGmSFjHfmY/SJOrHyISfmebrtp+3bji47P026SNYjjRJkiQV6HmkKSJ2AI8Grs3Mi/sX0vIs9+qyk14lS1qacerrYGl9mHOHNAxL+Ttr+v/BPY00RcS5wKrM3ASsi4iT+huWJI2efZ2kTr0enmsBV9aPrwNO60s0ktQsLezrJNUiM5e+UjVc/abM/FxEPAU4OTO3dby+BdhSP/0p4NbCTR8HfHfJAY2HSc4NJjs/c6s8IjOPH2QwTbNYX1e3sb87lLmNJ3OrzNvX9TqnaQZYXT9ey5wRq8zcDmxf6kYjYldmTvcYU6NNcm4w2fmZ24q2YF8H9nfdmNt4MrfF9Xp4bjf3DlNvBPYuNxBJaiD7Okn36HWk6WrghohYB5wNnNq3iCSpOa7Gvk5SraeRpsw8QDVB8iZgc2bu71M8Sx7iHiOTnBtMdn7mtkINsK+DyX7vzW08mdsiepoILkmStNJ4RXBJkqQCQy+aImJHROyMiAsXaTcVETd0PD8iIj5Ur/uiwUe6dEvI7T7tIuLwiPhaRLTrnw3DibhMSV7d2pS+H6PUS25N31+zCnMbu8/ZOLG/G6/Pj33d+OyruYbV3w21aCq9um5EHANcDqzpWPwKYFe97tMj4qiBB7wES8itW7vHAe/LzFb9s2d4kS+sJK9ubUrfj1HqNTcavL9mFeY2dp+zcWJ/N16fH/u68dlXcw2zvxv2SFOLsqvr3g08Hzgwz7o7gaZdS6JFWW7d2p0KPDsiboyI90ZEz/cEHIAWi+fVrU3JeqPWorfcmry/ZrVYPLdx/JyNkxb2d93aNfXz08K+blz21VwthtTfDbRoioh3dAzrtamqun31yweAqW7rZeaBLmeprClZd1h6zY3ueXwaeHJmngbcATxtUHH3oOR979amUftrHr3m1uT9NWvR3MbhczZO7O+6GqfPj33d+OyruYbW3w20aszMl3Y+j4jLWOTquguYvTLv/nrdmX7E2Ktl5NbtCsM3Z+YP6mW3AE0a3l30isjztClZb9R6za3J+2tWr+9/oz5n48T+rqtx+vzY143PvppraP3dsHfucq6u2/Qr85bG163duyNiY0SsAp4NfG5wYS5ZSV7d2jR9f0HvuTV5f83q9f0fh/02LuzvxuvzY183PvtqruH1d5k5tB/gAVRv+huAfwKOBh4DXDxP+3bH40cAXwAuoxoyXDXM2PuV2zztfhq4GdgDvG7UuSwS78bCnA5ZNupc+phbY/fXUnLraNvueNzoz9k4/djfjdfnx75ufPZVL/l1tG13PF7y52zoF7esZ7CfBVyfmbctcd11VFXhx7K/V+bti9LclvMejEJJvN3ajEOeveY2DnqNu+mfs3Fifzdenx/7uubnMZ9h9XdeEVySJKlAEyesSZIkNY5FkyRJUgGLJkmSpAIWTZIkSQUsmiRJkgpYNEmSJBWwaJIkSSpg0SRJklTAokmSJKmARZMkSVIBiyZJkqQCFk2SJEkFLJokSZIKWDSpq4j4QUSs7sN2XhMRJ89ZNhUR31rutiVJGiaLJhER2yPiRXMW/wj4YZe2OyLiCxGxKyK+ExF7IuKWiNhXL/vHiPhvHat8FrgyIo5ebNuSJDXZ4aMOQI3QrYg5mJl3A0TEI4FTMvMvMvPFsw0iog38BrAeeFZmnj93w5l5dUQ8FPhxRPw58BhgFfCQiPhs3ezjmflb/UxIkqR+c6RJANltYUSsiYjfAa4HHlkvOyoifnK+DUXEI+eMKpGZb8nM79XbeBZwOvDNzHw8VdH10D7kIEnSQFk0adab6kNs+yPiV+plNwNrgMdl5h/Uy54JvH2B7VwMvAQgIrZExMcj4s31a3fPs858yyVJagwPz2nWr2fme2af1IXO4zLzzjnt/iewLSI2zN1ARJwA/Cx10QRcA/wL8Pv186yX3U11eG4XcBTw6X4mIknSIDjSpHl1KZjIzB8Bfwz8apdVfht4e2Z+v257G1XR9OP69QCeAWwGvpWZ08BLBxC6JEl9Z9Gk+4iIVRHx7xZp9i6qAqjTYcBjqQqq+cz39+bfoSSp8fzPSveIiGdQzWP6+S6vPS8ifgIgM7+Rma+Y0+THmXlmZt4xZ/mxwIMi4v7APuCDQBu4qz577k3Ad/qZhyRJg+CcJgH8JPCLwG7gJZn5dxFxaUQ8ODNvi4j/C3gP8NCIuBv4YWbOd8bdYcARwEHgQcDlVHOWPgFcBPx9Zs7MWWdVRKzOzLsGlaAkScsV8/zfpxWkvrDlNzPzox3L/jvV5QEOo5qTdDnwSeCjVNd0+vGhW4K6/ZHA86kO4Z2YmX9cXxX814BTqCZ/34+qaL8/8EDguZn5/n7nJklSv1g0aWQiYhVVkXV3Zs5XhEmS1AgWTZIkSQWcCC5JklTAokmSJKmARZMkSVKBgV9y4Ljjjsv169cXtb3zzjtZs2bNYAMakUnODSY7P3Or7N69+7uZefyAQ5Kkxhp40bR+/Xp27dpV1LbdbtNqtQYb0IhMcm4w2fmZWyUivjrYaCSp2Tw8J0mSVMCiSZIkqYBFkyRJUgGLJkmSpAIWTZIkSQUGfvacVoY9+/Zz/gUfvs+yvdvOGVE0kiT1nyNNkiRJBSyaJEmSClg0SZIkFbBokiRJKmDRJEmSVMCiSZIkqYBFkyRJUoEFr9MUEYcDX65/AF4BPAd4GvCpzHz5YMOTJElqhsVGmh4HvC8zW5nZAu4HnAY8AfhGRJw54PgkSZIaYbGi6VTg2RFxY0S8FzgDeH9mJvAJ4PRBByhJktQEUdU/87wY8TPANzLzWxHxVuA7wGcz84MR8ZPAKzPzP3VZbwuwBWBqauqUK664oiiYmZkZ1q5d20MazTfJuQF859/28+277rtswwlHjyaYPpvkfbeU3DZv3rw7M6cHHJIkNdZi9567OTN/UD++BTgSWF0/X8s8I1WZuR3YDjA9PZ2tVqsomHa7TWnbcTPJuQG8+b0f5NI99/1z2nteazTB9Nkk77tJzk2S+m2xw3PvjoiNEbEKeDawhmpOE8BGYO8AY5MkSWqMxUaaXgv8ORDANcDFwA0RcRnw1PpHkiRp4i1YNGXm56nOoLtHfcbcOcBlmfmVAcYmSZLUGIuNNB0iM+8CrhpALJIkSY3lFcElSZIKWDRJkiQVsGiSJEkqYNEkSZJUwKJJkiSpgEWTJElSAYsmSZKkAku+TpNUav0FH+66fO+2c4YciSRJy+dIkyRJUgGLJkmSpAIWTZIkSQUsmiRJkgpYNEmSJBWwaJIkSSpg0SRJklTAokmSJKmARZMkSVIBiyZJkqQCRUVTRExFxGfqxzsiYmdEXDjY0CRJkpqjdKTp9cDqiDgXWJWZm4B1EXHS4EKTJElqjsjMhRtEnAE8D3gUcDPw0cy8NiKeAxyVmX/WZZ0twBaAqampU6644oqiYGZmZli7du3SMhgTk5wbwHf+bT/fvqus7YYTjh5sMH02yftuKblt3rx5d2ZODzgkSWqswxd6MSKOBC4CngVcDawB9tUvHwBO7LZeZm4HtgNMT09nq9UqCqbdblPadtxMcm4Ab37vB7l0z4J/TvfYe15rsMH02STvu0nOTZL6bbHDcxcAb83MO+rnM8Dq+vHagvUlSZImwmJDA2cCZ0TEy4DHAw8Hvg7cBGwEbh1odJIkSQ2xYNGUmU+afRwRbeAZwA0RsQ44Gzh1oNFJkiQ1RPHhtcxsZeYBoEU10rQ5M/cPKjBJkqQmKZu52yEzbweuHEAskiRJjeVEbkmSpAJLHmnSeFt/wYcPWbZ32zkjiESSpPHiSJMkSVIBiyZJkqQCHp7TknQ7vAewdcPytuEhQklS0znSJEmSVMCiSZIkqYBFkyRJUgGLJkmSpAJOBNe8k7udnC1J0r0caZIkSSpg0SRJklTAw3Oa13yH7SRJWokcaZIkSSpg0SRJklTAokmSJKlAUdEUEcdGxFkRcdygA5IkSWqiRYumiHgI8GHgCcDfRMTxEbEjInZGxIUDj1CSJKkBSkaaHgv8Zma+DvgYcAawKjM3Aesi4qRBBihJktQEi15yIDM/ARART6IabToWuLJ++TrgNOCLgwpQkiSpCSIzF28UEcBbgEcBXwPemJmfi4inACdn5rY57bcAWwCmpqZOueKKK4qCmZmZYe3atUvLYEw0Jbc9+/YPZLtTq+Hbd/W+/oYTju5fMH3WlH03CEvJbfPmzbszc3rAIUlSYxVd3DKryuplEfH7wHOA1fVLa+lyiC8ztwPbAaanp7PVahUF0263KW07bpqS2/kDumDl1g0HuXRP79dK3Xteq3/B9FlT9t0gTHJuktRvJRPBXxURL6yfPhDYRnVIDmAjsHcgkUmSJDVIydDAduDKiHgJ8HngauD6iFgHnA2cOrjwJEmSmqFkIvjtwFmdyyKiVS+7JDMHM0lGkiSpQXqahFIXUlcu2lCSJGlCeBsVSZKkAhZNkiRJBSyaJEmSClg0SZIkFbBokiRJKmDRJEmSVMCiSZIkqUDvNwuT+mj9PPfE27vtnCFHIklSd440SZIkFbBokiRJKuDhuQk13+EuSZLUG0eaJEmSClg0SZIkFfDwnBqt22FGz6iTJI2CI02SJEkFLJokSZIKWDRJkiQVsGiSJEkqsGjRFBFHR8RHIuLjEfGBiDgyInZExM6IuHAYQUqSJI1ayUjTecAbMvMs4DbgBcCqzNwErIuIkwYZoCRJUhMsesmBzHxbx9PjgV8G3lg/vw44Dfhi3yOTJElqkMjMsoYRTwQuBvYCb8rMz0XEU4CTM3PbnLZbgC0AU1NTp1xxxRVFv2NmZoa1a9eWRz9Ghp3bnn37h/a7AKZWw7fvGs7v2nDC0cP5RTX/LiubN2/enZnTAw5Jkhqr6OKWEXEs8GbgF4BXAqvrl9bS5RBfZm4HtgNMT09nq9UqCqbdblPadtwMO7fzh3zvua0bDnLpnuFcK3Xvea2h/J5Z/l1KkqBsIviRwJXA72TmV4HdVIfkADZSjTxJkiRNtJKJ4C8GTgFeHRFtIIBfiYg3AM8DhjukIUmSNAIlE8HfDry9c1lEXAOcBVySmcOdPCNJkjQCPU1CyczbqQ7ZSZIkrQheEVySJKmARZMkSVIBiyZJkqQCFk2SJEkFhnM1QqmP1s9z4c69284ZciSSpJXEkSZJkqQCFk2SJEkFLJokSZIKWDRJkiQVsGiSJEkqYNEkSZJUwKJJkiSpgNdpGiNen0iSpNFxpEmSJKmARZMkSVIBD89NgPkO26003d4HD11KkvrFkSZJkqQCFk2SJEkFig7PRcQUcFVmnh4RRwAfAI4F/jQz3znIAKXl8IxDSVK/LDrSFBHHAJcDa+pFrwB2ZeYm4OkRcdQA45MkSWqEyMyFG0Q8AAjgg5nZiohrgAsy8x8j4r8AuzPzb+asswXYAjA1NXXKFVdcURTMzMwMa9eu7SGN5utHbnv27e9TNP03tRq+fdeooyi34YSji9v6d1nZvHnz7sycHnBIktRYix6ey8wDABExu2gNsK9+fACY6rLOdmA7wPT0dLZaraJg2u02pW3HTT9yO7/BZ8lt3XCQS/eMz8mYe89rFbf171KSBL1NBJ8BVteP1/a4DUmSpLHSy9DAbuA04CpgI3BTXyOShmClXdNpvgnx73rqmq7LJUmH6qVouhy4NiJOBx4DfKq/IUmSJDVPcdGUma36369GxFlUo00XZebdA4ptRfCUeEmSxkNPM3cz85vAlX2ORZIkqbGcxC1JklRgfM4RX2G8Ce/wOVlakrQQR5okSZIKWDRJkiQVsGiSJEkqYNEkSZJUwIng0iL27Nt/yH3/vI6WJK08jjRJkiQVsGiSJEkq4OE5acC8VY4kTQZHmiRJkgpYNEmSJBUY28NzTT7k0S22rRsOHnIGliRJGh+ONEmSJBUY25GmQWnyCJaaY1B/J0vZrn+rkjRcjjRJkiQVsGiSJEkq0PPhuYjYATwauDYzL+5fSIea7zDEqLc7qLg0vpbyN9HUv2tJUnc9jTRFxLnAqszcBKyLiJP6G5YkSVKz9Hp4rgVcWT++DjitL9FIkiQ1VGTm0leqDs29KTM/FxFPAU7OzG0dr28BttRPfwq4tXDTxwHfXXJA42GSc4PJzs/cKo/IzOMHGYwkNVmvc5pmgNX147XMGbHKzO3A9qVuNCJ2ZeZ0jzE12iTnBpOdn7lJkqD3w3O7ufeQ3EZgb1+ikSRJaqheR5quBm6IiHXA2cCpfYtIkiSpgXoaacrMA1STwW8CNmfm/j7Fs+RDemNkknODyc7P3CRJvU0ElyRJWmm8IrgkSVIBiyZJkqQCQy+aImJHROyMiAsXaTcVETd0PD8iIj5Ur/uiwUe6dEvI7T7tIuLwiPhaRLTrnw3DibhMSV7d2pS+H6PUS25N31+zCnMbu8+ZJI3KUIum0tuvRMQxwOXAmo7FrwB21es+PSKOGnjAS7CE3Lq1exzwvsxs1T97hhf5wkry6tZmHG6102tuNHh/zSrMbew+Z5I0SsMeaWpRdvuVu4HnAwfmWXcn0LQL8rUoy61bu1OBZ0fEjRHx3ojo+UbKA9Bi8by6tSlZb9Ra9JZbk/fXrBaL5zaOnzNJGpmBFk0R8Y6OQxhtqm+x++qXDwBT3dbLzANdLmOwpmTdYek1N7rn8WngyZl5GnAH8LRBxd2Dkve9W5tG7a959Jpbk/fXrEVzG4fPmSQ1yUC/IWfmSzufR8RlLHD7lUXM3rplf73uTD9i7NUycut2C5qbM/MH9bJbgCYdylrwljkLtClZb9R6za3J+2tWr+9/oz5nktQkw/6PbDm3X2n6rVtK4+vW7t0RsTEiVgHPBj43uDCXrCSvbm2avr+g99yavL9m9fr+j8N+k6SRGOrFLSPiAcANwCe59/YrJwC/lJmHnOETEe3MbNWPHwFcC3wC2AScmpl3Dyn0RZXmNk+7hwF/DgRwTWa+erjRz69LvC8AnluQU85d1scrx/fFMnJr7P6aVZJbR9ux+ZxJ0igN/Yrg9Rk7ZwHXZ+ZtS1x3HdW34I817T9gKM9tOe/BKJTE263NOOTZa27joNe4m/45k6RR8TYqkiRJBZo4OVeSJKlxLJokSZIKWDRJkiQVsGiSJEkqYNEkSZJU4P8H1xiqNwJdxQkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x720 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "R.hist(bins=np.linspace(-0.1, 0.1, 41, endpoint=True), figsize=(10, 10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "上海机场    0.220226\n",
      "招商银行    0.331152\n",
      "贵州茅台    0.638269\n",
      "万科A     0.134196\n",
      "比亚迪     0.715052\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "R_mean = R.mean() * 252\n",
    "print(R_mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          上海机场      招商银行      贵州茅台       万科A       比亚迪\n",
      "上海机场  0.109177  0.039231  0.046936  0.041095  0.034059\n",
      "招商银行  0.039231  0.073669  0.037998  0.047372  0.030378\n",
      "贵州茅台  0.046936  0.037998  0.088034  0.031465  0.042686\n",
      "万科A   0.041095  0.047372  0.031465  0.090423  0.039524\n",
      "比亚迪   0.034059  0.030378  0.042686  0.039524  0.227678\n"
     ]
    }
   ],
   "source": [
    "R_cov = R.cov() * 252\n",
    "print(R_cov)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          上海机场      招商银行      贵州茅台       万科A       比亚迪\n",
      "上海机场  1.000000  0.437445  0.478754  0.413606  0.216027\n",
      "招商银行  0.437445  1.000000  0.471840  0.580415  0.234557\n",
      "贵州茅台  0.478754  0.471840  1.000000  0.352663  0.301510\n",
      "万科A   0.413606  0.580415  0.352663  1.000000  0.275459\n",
      "比亚迪   0.216027  0.234557  0.301510  0.275459  1.000000\n"
     ]
    }
   ],
   "source": [
    "R_corr = R.corr()\n",
    "print(R_corr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "上海机场    0.330420\n",
      "招商银行    0.271421\n",
      "贵州茅台    0.296705\n",
      "万科A     0.300705\n",
      "比亚迪     0.477157\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "R_vol = R.std() * np.sqrt(252)\n",
    "print(R_vol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "weights = np.array([0.10220201, 0.27353176, 0.1263887,  0.32700943, 0.1708681 ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "投资组合的预期收益率：35.98%\n"
     ]
    }
   ],
   "source": [
    "R_port = np.sum(weights * R_mean)\n",
    "print(\"投资组合的预期收益率：{:.2%}\".format(R_port))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "投资组合的收益波动率：23.35%\n"
     ]
    }
   ],
   "source": [
    "vol_port = np.sqrt(np.dot(weights, np.dot(R_cov, weights.T)))\n",
    "print(\"投资组合的收益波动率：{:.2%}\".format(vol_port))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "Rp_list = list()    # 建立一个初始的投资组合收益率数列\n",
    "Vp_list = list()    # 建立一个初始的投资组合收益波动率数列\n",
    "for i in np.arange(1000):\n",
    "    # 生成1000个不同权重的预期收益率与收益波动率\n",
    "    x = np.random.random(5)\n",
    "    weights = x / sum(x)\n",
    "    Rp_list.append(np.sum(weights*R_mean))\n",
    "    Vp_list.append(np.sqrt(np.dot(weights, np.dot(R_cov, weights.T))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
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       " 0.24820110708428111,\n",
       " 0.27866094330069524,\n",
       " 0.23182650022623918,\n",
       " 0.24558809439707385,\n",
       " 0.23824366476404565,\n",
       " 0.2568894328515582,\n",
       " 0.23927003844397418,\n",
       " 0.24600243754338127,\n",
       " 0.2374325609840604,\n",
       " 0.25426729298871814,\n",
       " 0.23927579848517122,\n",
       " 0.2289449533020286,\n",
       " 0.2357388804565784,\n",
       " 0.22737328416604483,\n",
       " 0.23243054318429296,\n",
       " 0.23361197379978582,\n",
       " 0.23297775635017856,\n",
       " 0.22958428238920628,\n",
       " 0.25721580234281016,\n",
       " 0.23138301841590053,\n",
       " 0.2539615153649777,\n",
       " 0.22965982085725561,\n",
       " 0.22871616632639166,\n",
       " 0.24322244065281068,\n",
       " 0.2509732411648474,\n",
       " 0.2369090375579229,\n",
       " 0.2609616329528226,\n",
       " 0.23093683885381094,\n",
       " 0.23633234547928555,\n",
       " 0.23172648428421752,\n",
       " 0.23288933631266306,\n",
       " 0.23705054373667198,\n",
       " 0.23882868294809814,\n",
       " 0.23760551314073877,\n",
       " 0.25024494939054254,\n",
       " 0.25368951044810045,\n",
       " 0.23672106131045703,\n",
       " 0.2456842252398551,\n",
       " 0.2792775793903938,\n",
       " 0.23474884991079606,\n",
       " 0.247947280565178,\n",
       " 0.2509760981989796,\n",
       " 0.23187225090783434,\n",
       " 0.24482831894599255]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Vp_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(Vp_list, Rp_list)\n",
    "plt.xlabel(u'波动率', fontsize=13)\n",
    "plt.ylabel(u'收益率', fontsize=13, rotation=0)\n",
    "plt.xticks(fontsize=13)\n",
    "plt.yticks(fontsize=13)\n",
    "plt.xlim(max(0, round(min(Vp_list) -0.05, 1)), round(max(Vp_list) + 0.05, 1))\n",
    "plt.ylim(round(min(Rp_list) - 0.05, 1), round(max(Rp_list) + 0.05, 1))\n",
    "plt.title(u'投资组合收益率与波动率的关系', fontsize=13)\n",
    "plt.grid('True')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "投资组合预期收益率50%时上海机场的权重: 0.0420\n",
      "投资组合预期收益率50%时招商银行的权重: 0.3208\n",
      "投资组合预期收益率50%时贵州茅台的权重: 0.4369\n",
      "投资组合预期收益率50%时万科A的权重: 0.0647\n",
      "投资组合预期收益率50%时比亚迪的权重: 0.1356\n"
     ]
    }
   ],
   "source": [
    "import scipy.optimize as sco\n",
    "\n",
    "def f(w):\n",
    "    # 定义一个需要求解最优化的函数\n",
    "    w = np.array(w)              # 设置投资组合中每只股票的权重\n",
    "    Rp_opt = np.sum(w * R_mean)  # 计算最优化投资组合的预期收益率\n",
    "    Vp_opt = np.sqrt(np.dot(w, np.dot(R_cov, w.T)))     # 计算优化投资组合的收益波动率\n",
    "    return np.array([Rp_opt, Vp_opt])                              # 以数组的格式输出\n",
    "\n",
    "def Vmin_f(w):\n",
    "    # 定义一个得到最小波动率的权重函数\n",
    "    # 输出前面定义的函数f(w)结果的第二个元素\n",
    "    return f(w)[1]\n",
    "\n",
    "p_pct = 0.5      # 预期收益率等于50%\n",
    "# 以字典格式依次输入权重的约束条件\n",
    "cons = (\n",
    "    {\n",
    "        'type': 'eq',\n",
    "        'fun': lambda x: np.sum(x) - 1\n",
    "    },\n",
    "    {\n",
    "        'type': 'eq',\n",
    "        'fun': lambda x: f(x)[0] - p_pct\n",
    "    }\n",
    ")\n",
    "# 以元组格式输入权重的边界条件\n",
    "bnds = tuple((0, 1) for x in range(len(R_mean)))\n",
    "\n",
    "weights0 = len(R_mean) * [1.0 / len(R_mean), ]  # 用于生成一个权重相等的数组\n",
    "result = sco.minimize(Vmin_f, weights0, method=\"SLSQP\", bounds=bnds, constraints=cons)\n",
    "\n",
    "for stock_item, idx in zip(R_mean.index, range(len(R_mean))):\n",
    "    print(\"投资组合预期收益率{:.0%}时{}的权重: {:.4f}\".format(p_pct, stock_item, result['x'][idx]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "波动率在可行集是全局最小值时的投资组合预期收益率: 0.3821\n",
      "在可行集是全局最小的波动率: 0.2257\n"
     ]
    }
   ],
   "source": [
    "# 仅设置权重和等于1的约束条件\n",
    "cons = (\n",
    "    {\n",
    "        'type': 'eq',\n",
    "        'fun': lambda x: np.sum(x) - 1\n",
    "    }\n",
    ")\n",
    "\n",
    "result_vmin = sco.minimize(Vmin_f, weights0, method=\"SLSQP\", bounds=bnds, constraints=cons)\n",
    "Rp_vmin = np.sum(R_mean * result_vmin['x'])\n",
    "Vp_vmin = result_vmin['fun']\n",
    "\n",
    "print(\"波动率在可行集是全局最小值时的投资组合预期收益率: {:.4f}\".format(Rp_vmin))\n",
    "print(\"在可行集是全局最小的波动率: {:.4f}\".format(Vp_vmin))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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FBaxfb/9vRUXzuw2KitjVsSPtDjgAevSA7t3rv8KDgq5dtXVA5RwNHrLImWeeyeLFi/F4PBhjqKiooGvXrjz77LOhpE9jDDt37mTu3LmsXr2aNm3acNppp7Fo0SK++OILBgwYgMfjobCwkFNOOQUAv9+PMYYHH3yQhx9+mPz8/ND+fve73wFQW1vL119/zfXXX8/111+Pz+fjkksu4cYbb+S4445jwYIFXH311YwZM4b8/Hzcbjcff/wx3bp1Y+rUqVldR0NlkJoaqzXAKSBYvx42bGh6ISK327rpd+9uBQTBoCD83x49rHUKCvg4x2edVMqJBg9Z5IUXXgi9vvvuu1m4cCGvvfaabR2Ezz77jE8//RSfz8eAAQMwxvDDDz/g9Xp59tlnqa6uZsiQIaxYsYK+fftyySWXcMUVV/Db3/6WgoKCmCNQtoc9ta1fv56DDjqI+fPnh5Zt3bqVTp06JenKVatRVQVr1sB33zX8d80aWLfOSjY0JvH9ulzWTb+4uP6rZ8/GQcHee1sBhFIqKg0eIl1zDSxd2nLHGzQI7r8/oU0+++wzJk2aRJcuXejfvz91dXUNhhO+8cYbHH744fTt25cBAwawaNEinnrqKaqqqjjssMM444wzKC8vp2fPnhx88MHMnz8/VADp448/Zvr06Q2Od/HFFzNixAiqq6vp2LEjo0ePZuLEiRx77LFs2bKFI488kp/97Gfcfffd9OzZk4ULF3LIIYeEciXcbjevvvoq7dq148gjj2TkyJHN+papLGWMVZXQKTj47rumzWGQnw/77msFBOH/hr/u1k0LECmVRPrXFGnpUnjnnXSfhaO1a9cyevRoBg4cyOLFi4GGFRiLiopwB56crrvuOk4//XT23XdfrrzySgYOHEh1dTVt27bls88+o2fPnmzdupV99tkntP9NmzaxceNG7r77bgCmT5/Od999x6uvvsrf/vY35s2bx65du0ItE127duWrr77iD3/4A3PmzKGkpITzzjuPadOmhfZ54YUX4na7qampaXAslYP8fli7Fr76yvr63/8Y8OGH1hwI331nJSkmIj8feveGvn2hVy/7IGGvvXJmpkKlsoUGD5EGDcrY45WXl3Pqqady4okn8vzzz4eSHcNbHnbs2IHb7Wbx4sV88MEHzJs3D4B33nmHiRMnMnLkSPr168ebb77JkUceSadOnUItBAAej4eqqiqWBlpffvjhB9xuN4WFhRQ4jA/v2LEjTz75JADffvstd911FxdffHHo827dunHdddfFfZ0qw9XVWfkFwQAhLFDg228b5RvsHW1f7dpBnz5WcNCnT8PXfftaCYdaZ0CpjKPBQ6QEuxBayhdffMHQoUO55JJLGDNmDKtWrXJseQAYOnQoCxcuZNiwYdx+++1MmzaNhx56iIMOOgi3280DDzzACSecwLHHHtvoWG3atKF9+/aAFUzEY/fu3Tz77LP85je/YePGjRQWFlJYWBj63Ov1cuWVVzZokVAZzu+Hr7+Gzz6zvr74wgoSvv4avN749lFQwM4ePWjfv799gLD33tpqoFQW0uAhSxx22GE88MADXHbZZbz55ptxbdO1a1cWLFjASSedxJ49e/jJT34CwP7774/H42HSpEnccMMNjbarq6ujtrY29DoeTz31FB988AG/+c1v8Hg83HDDDUyaNCn0+b333su2bdvi2pdKg61bYflyWLasPlj4/PP4ih7l5cEBB8BBBzX+Ki7mk3ff1REJSuUYDR6yyBVXXBF6/dlnnzl2W4TbtWsXVVVVFBUVMW7cuNCT//HHH8/f//53Tj/99EbHMcY0Ch52797Nbof+6h07djB16lQWLFgAOM8FoXOIZIitW+H99+GDD+oDhYqK6Nu4XLD//nDwwQ2Dg4MPtnIRdISCUq2KBg9ZqK6ujsMPP9y226JDhw60CWSVv/HGG1x66aU89thjHHXUUdx5553s3LmTO++8k//85z+ceOKJXHrppTz66KOhbgqfz0efPn34zW9+A8Cnn34KwBlnnMEZZ5wBWDUfwgOB8ePHM3LkSA480JrA1+/3c8899/DQQw+F1vF6vfzhD39I5bdFOdm4Ed59t/7r88+jr9+5MwwcCIcfXv/Vr59VNlkppdDgISvV2BTA+eyzzzjjjDMYM2YMRUVFfPPNN1x11VU8/fTToQqRhx9+OP379+eoo45i8eLFtGvXjnPOOYdDDjmEOXPmMHTo0AYtF3/605/47LPPQi0edXV1nH322bRt25aSkhLACiS6d+/OeeedF9quoKCAyZMnN0iSvPfee9m0aVNKvh8qwo4d8NJLsHChFSx89ZX9em43lJTUBwjBgKG4WPMQlFJRiWlKwZUsU1JSYlatWmX72Zdffsmhhx7awmeUXMGWB2NMgxaByPfvv/8+Xq+Xk08+ucH2L774IqWlpRnbrWBXBKulpfL3ZGEyqhTW1VmBwpNPwpw59kMi8/PhmGPg+OPhhBNg6FAItDilUlKuL0Pl8rWBXl+2E5Elxpghqdi3tjzkkMibf+T7n/70p7bb2eU9qCyxfj38/e/w1FOwenXDz9q1g2HDrGDh+OPhqKMgbFiuUko1lQYPSmWjPXvg3nth8uSGIyI8HhgzBi6+GE4+WSdkUkqlhAYPSmWbBQvgyishvCtu8GArYDj3XKt2glJKpZAGD0pliy1b4Prr4Z//rF/Wvz88/LDVLaGUUi1E674mgc+3lWXLTsHn25ruU1G5yBgrp+GQQ+oDh3btYNo0+PRTDRyUUi1Og4ck2LTpKbZtm8+mTf9I96moXPP113DSSVaXxI8/WstOPdUqFf3HP2pOg1IqLTR4aCZjDOvWzQBg/foZtOTQ123btvH3v//dsfJjOrnd7qh1Hb7//nt27drVaHl5eXmojHYi3nrrLZYtWxZzPZ/Ph9Ow3Yzi88HUqTBggJXjANCjhzUM86WXrJkmlVIqTTR4aKaqqvfw+6sAqK2tpKrq/RY79rhx4/j973/Pa6+95rjOGWecQZcuXejbt6/tV9u2bVmyZEmDbf7xj39QXFzM8OHDG311796df/wjdgtLfn4++fn5jp/fd999DaYVD9/OaTIuv9/f4P2ePXtCr59//nneeuutRttUV1fj8/lC77/++muOOOIIdu7cGVpWU1ODN96JnlrCkiVw9NEwYUL9SIr/+z/48ks480wt4KSUSjtNmGym9evvx++3nqD9/l2sXz+DoqLjUn7cf/7zn7z77rt88sknnHLKKQwcOJDBgwc3Wi8vL497772Xiy66yHY/w4cPJy8vr8Gy/Px8/H4/1TaTIvn9/qhBQZDL5YpadOquu+6iW7du3HzzzUydOpVzzjkHsFoGvv/++1Cp66FDh/KXv/wFgLPOOotPP/0Uj8eDz+ejtraWisCcDG3atLEtJHXNNdfw4YcfUlhYiIjw/fffM3jwYE455ZTQOrt376Z///48/fTTMa8rpbxemDQJpk+3ZrQEK8/h8cfBoUaHUkqlgwYPCVi+fAxbt77cYJlIHhDsqjBs3TqPhQsb3jT33vs0Bgx4KWnn8dBDD3HHHXewYMECDjnkEP785z/zs5/9jHvvvZcLL7ywwU3b7XZz4403MnnyZNt9bdq0qVG569raWgYPHsyll17aaP2HH364UQsAWDfgq6++mvvuuy80LTjAV199xRNPPMHdd9/dYP0vvviCa6+9lj/84Q8sXbqUfffdl4ULF7Jy5UquuOIKFi5cyHXXXUdBQUFomxdffLHRcadOncrq1atZtGgRn3/+eagV5ZZbbqG4uJjf//73fP3115x22mns3LmTQYMGMWHCBLp160b//v1p27Yt9913H6eeeqrt96fFvPceXHppfSnpNm3gppusrziCNaWUakkaPCRg//3vYufOpdTUfI8x1lO5MQ1vvOHvXa62eDzd2H//u5Jy/PLycm688UbWr1/PBx98wAEHHADAiBEjeO2117jkkkuYMWMGF110Eeeeey777LMPIsLdd9/t2PJg56c//SltHSoRXnXVVQwZ0rja6Ztvvsnbb79Np06dGizfZ599+Nvf/saYMWNCuQzr1q3j1FNP5dhjj+W+++5zbKG47rrrQq0ctbW1uFyuBjN21tbWcsQRR1BSUsKaNWsoKSlhxIgR/P73vw9NNe52u7nllluorKxk5syZ/PKXv0REKC0tZebMmbz00kusWLGCs88+O+7vT1Lt3MlBDzwAZWX1y446Cv72NyvfQSmlMpAGDwlo164fRx/9BStXXsLWra9SV+ecqOhyFbL33qdyyCF/w+1u1+xjf/vttxx33HFcffXVrFy5kpNOOgm32822bdvo2LEjLpeLqqoqrrvuOh577DHGjh0LWDfYv/zlL7z++utR9//II49QXV3NKaec0qgbI1JdXR3V1dUsX74cd2Aq5tmzZ3Peeec1CgQ6derETTfdxE033cTChQsB6NWrF19++SW33XYbPp8Pv9/P4sWL6du3Lz6fj61bt9K3b19EhP/+978APPnkk/z5z39m165doW4Nn8/H5MmTOf3003nhhRcYPnw4paWlXHvttXTs2BGAkpISFi1aRF1dHTNnzmTlypX89a9/5bXXXuPwww+nXbt2DBo0yDHPIqXeegsuvZTiNWus923bWhUjr7lGp7hWSmU0DR4S5Ha3o1+/WVRUPMrXX1+DMXsarSOSzwEHTKe4+IqkHXf//fdn/fr1FBUVMXXq1NDyfffdl1deeYX+/fuHlt10002h11u3buXXv/511BEMw4YN46GHHqJHjx58/PHHjBo1ihtuuIF99tmHyZMnc+GFF7LPPvuEWiNcLhclJSWhwGHbtm28+OKLLF261Hb/V111FXfffTfvvPMOJ5xwAgBt27bl9ttv54svvmD79u2ceeaZtGnThtNPP53S0lLee+89rrzySnr06MGOHTu47LLLuOyyy/jTn/5EdXU1d955Z4OJvzZv3sw+++wDWBNptWtnBWw1NTVMnz6dgoIC7rvvPq6++moWLlzI66+/zqOPPsqhhx7KhAkTePrpp+nZs2eiP5am2bEDbrgBHn20ftnxx8MTT8BBB7XMOSilVDNo8NBEHTocgcuVj9/fOHhwufLp0OHIpB+zqKiI2tpa3G63Y1O/z+dr8BS9ceNGjj/+eKZMmcKHH37YYN2PPvqIvfbaC7/fT0FBASIS6ib44IMP6NSpExs3bmT79u1ce+21/N///R+bN2/myy+/bNCS8ec//5mjjz6agw8+2Pac8vPzueSSS7jvvvtCwQPAtGnT+OSTT/j5z39O7969Oe6443j44YcpLS3lgQce4PLLL2+wH2MMzzzzDK+99hr/+te/+PTTT7nnnnsAWLFiRagbx+v1hnIlRowYwbHHHsuFF17IYYcdxsCBAznxxBMZPnw47777LhdccAEFBQVMnz6d6dOnx/VzaJYFC+CSSyDY2tCuHf+79FIOnjEDXDr4SSmVHTR4aKIdOz7BmOAQQMHlKqCuzgsYjPGxY8cndOx4VNKPe8cddzBnzpxQ3//mzZs5/fTTyc/PxxjDYYcdxvPPPw/Azp07Wb16NQcddBBbtmzhiSeeCE0/27dv39A+fT5fg8REgP/85z/k5+ezdu1a+vbty/nnn8/hhx/O8uXLGRDRF799+3bGjRsX9byvvPJKPv3009D7pUuX8tBDD7FkyRLOO+88br31VkaMGMGECRP44x//yCeffMLMmTMb7GP27NkMGTKE/fbbj86dO3PNNdfwu9/9DoB27drRvXt3fD4fbdpYv9Z+v59Zs2ZRXFyMiFBZWcm2bdvo378/s2fPZsuWLXTt2pURI0ZQU1OD3+8PtaYk3a5dcOONVinpoOHD4e9/Z8OaNRysgYNSKoto8NBElZXvUVfnDSVFHnjg/Xz99R+oqfmeujovVVXvUVz8f0k/7h133MEdd9wRer/vvvvy4osvNui2CHr55Zc5+uijyc/Pt70pigh+vx+Px9MgERHg6aefxufzMW7cOB577DFmzJjB6aefzp49e0J5CEHxPLH36tWLXr16AVbAc9ZZZ3H33Xezfv16KioqGD58OC6Xi8svv5yrr76aRx55pEHS5qZNm7jyyispKSnhJz/5CZs3b8bj8XDnnXfSuXNnzj//fMAKmIJdFq+++iqTJk0iLy8v1FLj8/moqqpi6NChDc6vtraW22+/ndGjR8e8loQtWgS//jV88431vrAQ7rnHqt3gctW3QiilVJbQ4KGJduz4EHCz995jQkmRe+11MitXXsKWLS+wffuHMfeRSj6fjylTpjBx4kQAunbtytVXXx36vH379hhj+P7772nfvn1o+TnnnMOXX37JZZddxpAhQ9i2bRvnnnsuxhj8fj+FhYVMnz6dSy65hO7duzc67rvvvsu8efPw+XwN9htuxYoVHHrooZx11lkMHjyYqVOnsmPHDqZPn86//vUv7r33Xu666y4WLFjAOeecw5AhQ+jVqxcTJkygX79+9OvXj169erFp0yaee+45Hn74YcrLywHYsGFDaMTHmDFjGDNmTINjb9q0if79+zcqTpUSe/bArbdac1AEK48edxw8+SQEuliUUiobafDQRIWFh9Knz0R69LgktCyYTLlx49/ZsuWFpB/zqquu4u23324wGqK6uppf/vKX5OXlUVtbS1VVFaeffjrnn38+hx56aGgIol0BpAceeICHH36Ya6+9NrTs7rvvpmfPnqGm//PPPx+/38/YsWN59NFH6d+/Pw8++CATJ07kiSeeaLTPoqIiKisrKSsrC+0j0siRIznhhBNwu9385z//4aOPPuKYY47hwgsvpLy8nPbt2/Pb3/6Wp556igceeIAnn3wSEeGPf/xjg/1s2bKFe++9l9mzZ9OxY0fOOuss3nrrLa677jrH76HP52tQmTJlli2DCy6A5cut9/n5cNdd8Ic/6EgKpVT2M8bk/NfBBx9snHzxxReOn2WL7du3h17X1dWZ3bt3p/Fsmqa2ttbxs/DrC+f3+81HH30Uer9y5UqzcePGpJ+bMQn8ntTWGnPPPcZ4PMZY7Q3GHHmkMStWOG7y9ttvJ+ckM1QuX18uX5sxen3ZDvjEpOi+qi0POUZEGiU/ZoOmJCq6XC6OOqo+KbWkpCSZp5S4tWvhwgvhnXes9263VSHyllt09kulVE7R4AEa1AtQKpKJZ6bUf/0LrrgCqqxJ0jjwQJg5E445JrUnp5RSadDqx4e53e4Gsy4qFcnr9TpXoNy+3WptOOec+sDh8suhvFwDB6VUzmr1wUNRURGbN2+mrq4u3aeiMowxht27d1NRURGqXtnAhx/C4MHwz39a7/fe25qj4q9/BYeRJkoplQtafbdFly5dWL9+PatWrUr3qTRZdXW140RWuSCd1+fxeOjWrVtorgwA6uqsOg233AK1tdayk0+Gf/wDevRIy3kqpVRLavXBg8vlonfv3uk+jWZZuHAhgwcPTvdppExGXd+mTXD++dakVmAlQk6ZAtdeq+WllVKtRqsPHpSK2xtvWLUbvv/een/QQfDcc3Bk8ucxUUqpTKaPSkrFUltrDbkcNao+cLjgAliyRAMHpVSrpC0PSkVTUWGNpHjvPet9u3bwyCPWCAullGqlNHhQysmbb8J558GWLdb7/v3h+efhkEPSe15KKZVm2m2hVKS6OrjjDqubIhg4/OY31tBMDRyUUkpbHpRqYOtWq7Vh/nzrfWEhPPqoleOglFIK0OBBqXpLlsCZZ8KaNdb7khKYM8fqrlBKKRWi3RZKATz5JAwbVh84nH02fPyxBg5KKWVDgwfVutXUwJVXwiWXwJ491kyY994Ls2ZBhw7pPjullMpI2m2hWq/Nm+Gss+D99633XbvC7NkwfHhaT0sppTKdBg+qdVqyBEpLYf166/2QITB3LvTqldbTSoay8gqmzV/FhkovPYsKGDeqhNLBxek+LaVUDkl7t4WIDBeRL0Vko4jcEuc2LhFZLCKaAq8S99xz8NOf1gcOv/61VQQqRwKHCXOXU1HpxQAVlV4mzF1OWXlFuk+t1Ssrr2DY1AXsN34ew6Yu0J+JymppDR5EpDPwInAz0BsYISKnxLHp74FqY8w/U3l+KsfU1cHEiXDuuVBdbU1kNWOGlSyZI7OSTpu/Cq/P32CZ1+dn2vzsnTU2F6QyqNOgRKVDurstfg58a4yZCyAiDwLnAq87bSAi+wG3AcNa5AxVbti1yyopPXeu9b6oyMpvOPnktJ5Wsm2o9Ca0PFPlWtdLtKCuOdcVDEqC+w4GJUBWf79U5hNjTPoOLjIB2M8Yc3ng/UDgMWPMMVG2eRUYBHwKrALuMsZss1nvcuBygK5dux45e/bs5F9Ahti5cyft27dP92mkTHOvL++HHxhw8810+N//ANjdqxfL77wTb4Z0UyTz57dq0w5q/HWNlue5XZR0T8/okUSvr9Lro2Kbl7qw/5tcIhR3LqCowJOKU2yyeK9teUWV42cDijs1+fip/nnr/y3ZbcSIEUuMMUNSse90Bw83A52MMTcE3h8IzDPGlDisfyzwX2BK4N+rgUJjzPHRjlNSUmJWrcrdZtuFCxcyPIdHCDTr+j77DEaPrs9vOPFEa36Kzp2Tdn7NlcyfX+STKECBx82UMwak7Uk00esbNnUBFTYtJcVFBSwaPzKJZ9Z88V5bqq5pv/HzsPsfXIDVU0c3eb9B6fi/pSVbnXL9/04RSVnwkO6Eya1AUdj7QsBvvyoAJwAfGWNuMsa8ClwAHCciXVJ3iiprvfFGw8TIyy+H117LqMAh2UoHFzPljAEUFxUgWDendAYOTZErXS/hxo0qocDjbrCswONm3Cjb56S49SwqSGh5ptOE3+yR7pyHRcA1Ye+PAdZEWX8n8F3Yey9WsLEj2Semstzf/24FC34/iMA998D111uvc1zp4OKkBQvpyD3oWVRg+5SerTdEqM8/SPb3ctyoEtuWpuYGJemSqtwQlXxpDR6MMctFZJuI3APMByZijbxwMh+4WUT2B1YDfwQWGWP2pP5sVVYwBv70J7jtNut9fj7MnGkVg1IJSSQZL5lBRq7dEIOSGdSF7xOSH5SkSy62OuWqdLc8AJwOTAOmA48YY2aKyFhgrDHmjPAVjTFficjVwMtAd6yEyfNb+oRVhvL74aqr4K9/td7vtRe8/LI1Z4VKWLxPgcnO+M+1G2KqpSIoSZdcbHXKVWkPHowxm7ByF8KXzQJmOaz/AvBCC5yayibV1XDOOVBWZr3v08eaVrsku59W0ynep8BUNDXn0g1RxS9XW51yUdqDB6WaraoKxoyBd96x3g8cCP/+N/Tsmd7zynLxPgVqU7NKFm11yh4aPKjstmULnHIKfPqp9f6EE+Cll6BT08fOp1MmFUeK9ylQm5pVMmmrU3ZI91BNpZquogKOP74+cDjtNHj99awOHDJpmFq8wz5TNQxRKZW5tOVBZafVq62CT6tXW+8vvBD+9jdok72/0pkyTC3R1g9talaq9cne/2lV6/X11zBiRH3xpyuvhAcftCa6ymKZkDvQ1JET2tSsVOuS3f/bqtZn5UqrqyIYONxwAzz0UNYHDpAZ1QJ1Vk6lVDyy/39c1XqsXGm1OGzcaL2/5RaYOjVnqkZmQu5AJrR+KKUyn3ZbqOywapUVOGzaZL2/4w4reMghmZA7oCMnVC7KpFFMuUKDB5Xx2lZUwHnnpTVwaKn/fNKdO6BFelSuiZbHU5TG88p22m2hMtvatQy6/nrYsMF6P2lSWgKHTBpCmUq5MCunUuE0jyc1tOVBZa7Nm+Gkk2i7ebP1fsIEuPXWFj+NTBlC2VLS3fqhVDJFz+Np17Ink0O05UFlpm3b4Gc/g6++st5fcw3ceWdakiM1iVCp7JUJo5hykQYPKvPs3g2nngqffQbAxp//HO67L22jKvQ/H6WyVyaMYspFGjyozFJbC7/6FSxaZL0/6yxWXXddWodjZut/PmXlFQybuoD9xs9j2NQFOZmjoVQsmseTGprzoDKHMVa1yFdesd6PHAkzZ8IHH0TdLNUjITJhCGWimlopUqlcpHk8yafBg8ocU6bA449brwcNghdfhPz8qJu01E0y2/7zSXaSp46TV0qF024LlRmefRZuvhmA9R334dSf30zZNztibqbDsOwlM8mzNQ1VVUrFR4MHlX7//S/+iy4GoCq/HRedPYnl/oK4blA6EsJeMpM8NUBTSkXS4EGl15o1UFqK21eDz+XmitNv4usuvYH4blDZNBKiJRMYk5nkqQGaUiqSBg8qfXbvhtJS2LIFgFtP/j8+6DOwwSqxblDZMhKipZv+k5lhnk0BmlKqZWjCpEoPY+DSS2HpUgCeP/Z0nht0SqPVYt2g0jUSItEEwmhN/3cOTU0Mn6wkT53vQikVSYMHlR4PPAD/+pf1esQI8qbeR8ErK+1vUFVfRd1VS4+EsBvhce2spVwzayluEfzGUBwRUGRzidxsHKqqlEotDR5Uy3v/fRg3znrduzfMns2YLl0wHo/tDWrhwujBQ0uza0UwgX/9xnoVOWS0pae6TvbQymwbqqqUSi0NHlTL2rIFxo61Kknm5cGcOdClC5A9N6h4EwXD6ypEbfqP0bKSKC0QpZRKNU2YVC2nrg4uvLB+eu3774ejjmq0WuSohEqvr2XPM4ZEWguCgUZLlsjVoZVKqVTTlgfVcqZPh9dft16PHQtXXNFoFbun5opt/tCohEzod7drRXASHmi0VMuKDq1USqWaBg+qZXz8Mdx0k/V6//3hscdsJ7uye2quM4bbX1lBta8uI5riwxMIKyq9CPU5D+HSNSKhpfMrYqn0+hg2dUHagz6lVPJot4VKvR074JxzrDwHjwdmzYKOHW1XdXo63rbbl1FN8aWDi1k0fiTfTR3NjLGDKA7cmN2BgCidM/dlUu2LsvIKKrZ5tbS1UjlGWx5U6l19NXzzjfX6rrtgyBDHVZ2emp1kQlN8piV6ZtLQymnzV/GrXg3bZZozQZdSKjNo8KBS61//gqeftl6ffDJcd13U1e3yCVwiFBV4bBMnYzXFt9bZIDMloNlQ6YVejZdXVHrZb/y8VvUzUSqXaLeFSp21a+uTIrt0gX/8A1zRf+XsRiUUdy5g0mn9Em6Kz4bZIMvKK1i1aUeLzHeRDtGCu0z9mSilYtOWB5UadXVw0UVQVWW9f+IJ6NEjrk0jm903V9XRrTtMOWNA1FaEyFaGXXtqHfMkMuFJNxjcXHlIHQZXTtZjGDeqhIovl0RdJ/Jn0lpbi5TKJtryoFLj/vvh7bet17/5DYwZE/emkS0GNf46Jsxdzidrfox7m4pKr2N9iHjzJFI9C2ZrqMdQOriY4s4FoZYkJ8GfSTa0FimlNHhQqbBiBUyYYL0+4ACYMSOhzZ1uqs8sXut4U7HbxkmnAk/MdVriJuYUxFRUenOqC6OowMOi8SNZPXV0aFRKpGD3RmsIqJTKBRo8qOTy+eCCC6CmxspvePppaN8+oV043VQjaymE31QSGXWxq6Y25o25JW5i0fIBcvWJO9YwUi1wpVR20OBBJdedd0J5ufX6hhvgJz9JeBdNKf/stI3Lpq3c5zcxg4Bk3MRidXuMOKRr1O1z8Yk7Vplup59jugpcKaXsafCgkqe83AoeAAYMgEmTmrQbu6dTp/7y4E3F6Ym2zq70I7GDgObexOLp9nh75ZaY+8nFJ+5gga3VU0ezaPzIBsmQmVTgSinlTIMHlRw1NdboitpaaNPGGpaZn9+kXUU+nea5XfzkgL0aBRDhN5XIbYoKPLT1OP96xwoCxo0qweNueESPW+K+icXT7RFPYNDanrhbcgIxpVTT6VBNlRxTpsBnn1mvb7oJBg9u1u7CixyVvfYmn66oapDzIMCZR9oXQjJAlddnO98EJPAkG7kDpx3aiKfbI1Y1zdb6xJ0pBa6UUs605UE13/LlMHmy9XrAALj55qTufnNVdaOneEPDZv/wboLg53bifZKdNn8Vvog+D19d7FyJIOccDAl1XUTrntEnbqVUJtOWB9U8fj9ceqnVXeF2w5NPQl5eUg9R46/DLs4Nf4qPZ6imAIvGj4zrmM1NmHSatttvTKNCUJtXfYqAFkRSSmUNDR5U8/z5z9Z02wDXXw9HHpn0Q+S57RvIwp/uk50/0MlhLo14akRAfWBw/exl+I3zxFClg4tZWPUVq6cOj/vclFIq3bTbQjXdd9/BxInW6wMPbPLoili6dWrbqHkfYEOVl4ll1lN8rMAg0fwBcRje4bTcTungYuqMfQdKLo6iUEq1Hho8qISVlVcwbMpbLDjxbNi921r42GNQkJqRAUUFHqacMYDCiNETxsDMxWs57/EP2F1T22i7WPkD0eowVO62L23ttNyJ1i1QSuUi7bZQCQkmJo5Y/g4jv/0EgLmHn4yr6GBKU3jc0sHFXD97me1ni75pPOdFUYGHSaf1c8wfCF5HMCchclIqp5EQid707XIfMnkURaxJqXTSKqUUaMuDStC0+atw79zBbW89BsCPBR350wkXtUglxMjcgWhErHN1qu4Yqw5DPMWK4pk4K5vqFsQqbKWTVimlgrTlQSVkQ6WXW96bSbed1tP+XSMuYVthJypboA/fLRJ3ALFtt49tgS4Gu6muY42miJwWPPIpO1bLRbh46xak+6k+VkAVK/lTKdV6aPCgEnK8dwO//vRVAD7s1Z85/U8E6usXJHoTSeSGec4xvZi5eG2TzjvyJhdPt0S0m77TjXbC3M+aFAAkEoxE20dzgo9os3xOmLvcMXCLJ/kz3YGRUiq5NHhQ8TOG+959HLepo1Zc3HLyFaHhB3b1C8LZ3TyAhG6Yk0sHsHrLTtsch3hUVHrZb/w8ehYVMOKQrrywpKLJuQhON0yvry4UlCQSAER76m+p4MMpoHKLRK2hESsPpNLrY8JbzTs3pVRm0ZwHFb+ZM9l7qVXT4akhY/hf174NPnaaBdKpr3zSyysSnvb6u63N6x4JHt9qwTB0LvTEnYsQnuPginPMZrwzYza3KFUyphB3yvOI1lUUT8BlVyE0F2cMVao10ZYHFZ8dO6wptgG6d+eBYefYrlZR6WXY1AUNWhicbmxOT7PRbpjR5oIIKvS4MER/WrbOoQ4QZowdFPMJOPLJPpHkTbvvSeTxmju6IxlTiDvleUybv8qxRSKe5E+nCqHB74t2YSiVfTR4UPG56y7YtMl6fffddNywNztsbigCjZrtY93EIzndMMvKKxCiz0/lcQl3nXE4UH8TjLZ++BNwtD75eMpfO7H7nkDDJvtoQzrjyRdI1tBSpzwPu3OLd9SIU4VQ0C4MpbKVdluo2L79Fu67z3p9zDFw/vmOkzpF3qij3XBFiDkcMty0+auiBgLFRQVMO3tg6Aa4aPxIVk8dTXGMG2jwBhZtCGJTK0I6fU8im+ydhnQCcQ2PjGdoaVM1d7ipU4XQIO3CUCr7aMuDiqni8t9RXFMDwGVHXMDoZRttm7jj6VIIZwzkt3GFAozOhR5uO9W5sFO0G/j9UboenCapCrJLCIx3dEakdnluigrzYn5PwpvsiwLL7J76h01dEFciZayhpc3VnGmyrQqhhzl2f0DrK9eto09UttPgQUX13t/mctxb/wbgxcOG82bHvrwf1swc/h/esKkLHPvG7XIEBBpMPlXtq+OTNT82+k+1KPC502RVQOhmGu0/5dtfWRGq/RBU4HHHlXsRKwAJ2l3jZ8Ud9TN3On1PoL4VYcpPnJ/KE8llaM4NPtWC5+b0/WhN5bqTMTJGqXRLe7eFiAwXkS9FZKOI3BLH+m+IyBYR2RT4urglzrNVqqtj70k3AVDdJo97Tvg14NzM7NR0fs4xveLu4nhm8dpGTfTBgCHaAIcNld6oFRBLBxdTfuvPuH/soEbN707dGpE1H8Kb7t0OJxN5ExxxSFeijcvw+vxsrqp2/DzX5sZIZfdKtkjGyBil0i2tLQ8i0hl4EbgUeAWYLyIfG2Nej7LZIKCPMWZ3C5xi6zZ7Noett/5De/yo09nYsWvoI6cnX7BvOh/SZ6+4ujjsAorNVVbwEG1SKkN8FRATSQiMvKGFbxv59Gi3TVl5BS8sqYiapwHB0Qj2sm1ujFhS3b2SDZIxMkapdEt3t8XPgW+NMXMBRORB4FzANngQkf2BzRo4tICaGrj5ZgB+KOzEX485s8HHBR4Xg+94I9QNED4RVXj3wbWzljJt/irGjSph0XirOb+svML2Ru94KoGba6y8g6ZWQGzKDS2ebeIdoRFtNEIu3mwzuXulJSRrZIxS6ZTu4KE3sCTs/bdAtEeqo4FuIrIeKABmAb83xjSej1k1z2OPWaMsgAeGncPO/MIGH+/21bHbV//EXOn1cc2spVwzaylFBR521dTi81s38/A+XcCx1LHTMMzgzTXevINIRYWemOvEuqE55VJE2yaeJ8kCj5tunfKadW4qu+Raa5JqncQkUOwm6QcXuRnoZIy5IfD+QGCeMcb2r0hEzgL6AH8GOgDzgb8aY56wWfdy4HKArl27Hjl79uzUXEQG2LlzJ+3bt0/a/txeL8ecdx5527ZR1a07M+9+kLo2sW/AsQSDgGjN9JFcIhS3F/C0ZXNVNTX+OgTBxOwMqCcI++5VQFFB7Guo9PpCx3G7BAFq6xofyyVCcefo+1y1aYfttQbPP8/toluntrTx70nqzy/TJPv3M5M09drCf8+Cvwfx/H62tFz+2UHuX9+IESOWGGOGpGLf6W552IoVDAQVAo6PlcaYOWFvfxSRp4BTgEbBgzHmMeAxgJKSEjN8+PAknG5mWrhwIUm9vrvugm3bALjl6PN5+cvkNKcGEwdNjDzdYAtE50IPxsClB3q5b3lNYDtXo/XiUVzkZtH44VHXKSuvCMzB0PA4Td1npUNeRGSNhHh+ftk8tC/pv58ZJJevDfT6lLN0Bw+LgGvC3h8DrHFaWUR+BSwwxnwfWLQvUYIN1QSVlTBtGgAru/bllUOPT9qug326seolBAOHal9d6MZrFyQk0mYWPilW8MZbVl5hO3wzXvHkUnyy5kee+3AdfmNwi3DmkYl3QejQPqVUpklr8GCMWS4i20TkHqwuiInAzVE2OQYYKSLXYeVGXAxclfozbUXuu88KIIAnT7kUI8kZzRvepzvu+WX4bLoCwjXlhh5sqXCqBRE+fPOTNT8y6+N1obyMpoiV4BYcbRHM7/AbwwtLKhjSZ6+4Z8p0KqyUyIybSimVbGmv8wCcDvQApgOPGGNmishYEZlrs+5tQDdgM/AscIcx5oWWO9Uc9+OPcP/91uujjuLYay6yLSvcudDD+UN70zlKIqLHJc4zVsY3IWXCKnf7+MXAHlFLIYN1433uw+YFDuHzTgRn2hw2dUGDstHNGc8fXrPCiQ7tU0qlS7q7LTDGbAIuiFg2C2skReS624ExLXRqrc+MGdbsmQC3307pEfuCiGNf++TSAaFN4+2TnzZ/VbNu2tEYYNZH6xh7dC/eXrkl6qRYicyKGRTMsSgOXB8QtTuhOeP54xnmmatD+7I5v0Op1iLtwYPKEJWV8Oc/W6+POgpOOQWIf5hg5Hpl5RUMuv2NUBdCcN6KVD8t++oMry7bSLt861fbKalSxJpbIxYJ7MDuJhZr3onmjOeP9X3K1aF9mt+hVHbQ4EFZHnwQtm+3Xt96a/Ra0DGUlVc0ymvYttvHuDnLKCr0NDlBMV6VXp9j3kNQQRsXvjoTtRUk1rTTsVoWmjOeP1pBrOIcfhqP1tWTi9erVLbS4EHBzp31uQ6DBsHo0Y1WcWpKtls+bf4q24RIn99gTPTJqJx43JLU7o7dvjruHzuI62YvxS530y0Sc9rpWC0LiVaHDP9edirwNLrmyGAmU5v3G53XwPh/1lq6WansoMGDgscft5IlwSpJHdHqYNeUPG7OMibM/QxvWJXJikov185aGnUIZZXXx4yxgxIqTw2Asbo+Knf7Ehqi6SRUc8JhZ3WBD4ZNXeB4c46nZSHebp/I73Gl1xdKOq3c7Wt0/Ext3rc7r4pt/tDkZLFo6WalskMmjLZQafTSR6v5ftJdAKztsi9lfY9uNILg9ldWNGop8PlNg8AhKNaNvWdRAaWDixNOWPTVGbZ7a5kRmBWzuQxWi4BT6erCPHejGTqvnbWUiWX1ZbYjZ9psNKokAXbN9b46Q2FeG1ZPHc2i8SNjzpuRCTMz2p1XnTFxn5fOuqlUdtCWh1asrLyCD+58hDHbfwDgoSFn8OKLn4Mh1O0Qq6BTIlxC6CbgFkk4gPAbw4S5yznzyGJmLl7b7PMJdg/Y2VXTuKndAM8sXtugTkOy5p1ItLk+U5v3m3teuTgRmFK5SIOHVmza6yt54gOr4veWdkWU9RuRsmGUYN18g7NsNmWoJFhP12+v3ML5Q3s3O4DoWVSQ8M022GKR7JtZos31Tut3KvBE7WpJtWR0O+hEYEplPu22aMX6LlvMoVu+A+CpI06lJgmTX0VjTH2Vx+bYUOllcukAzh/au8n1poJN4U3pS48n4Ijs+plYttyxmBQk3lxvt77HJeyqqW3Q1TJh7vJGx0olu/NyiWi3g1I5RlseWrGrlr4CgLdNPjMH/zzm+m4R6oyhqNDDzuramCWmU6Wo0Hq6bmoQEhxJAbC7JvHZ3IPHd3q6t0saDG8lsUtuTLS5Pnz9ikovbhHbn0eyhznGGuFhdx3Fnf3akqBUjtHgobX66it+supDAF7oP5Kqgg4xN/EbQ3Ggqb8oMI9ElddHW4/LNnkyFTxuYWd1bZNrRQSHOwKNRkrEa9tuX+j4doFAPNUh7W7qds310W7WwX9jXUeiXTPRhuXGM8Ij8joWLlyY0PGVUplPuy1aq4cfDr3894izEawn8liCTeLbdvvYVWONfshvE30uiWQIjmZol9cmoRaP4HaRoyGcbvCR3wGPS2iXF3uujPDRBPHerGOtFz6/hVM3RDyBitOIkkSPmakjPJRSLU+Dh9Zo50548knr9Ukn8ex9F3Pe0N6JD5/0G25/ZUXMao7NEbyZu0SoqPQmfCwDLBo/stFwR6cbd3DuimCwMe3sgRQV5sU8Tvj+4s2jiLVePDfreAKVKq8v7ryHaMfM1BEeSqmWp90WrdGzz9aXor76aiaWLW/yyIVUlpoOn5eiqaMznGb+dBoVUFxUwKLxIxssu3bW0pjHCc+DsKsOGSme2gXx3KyjlbEOqjNw+ysr4so7iHZMLeCklApqVsuDiHRK1omoFmIMPPqo9XrffXmp56BmD3mMNjU3WDfkAk9iv2pukaRUknSKORIZ3RDr5hjMwwg29Vd6faGKmMEWjPOH9k64mJRTDYrw87G7DjvxBnnRhoZqASelVFBCLQ8icj3QxRgzIbDoPyIy2xgzzWH9dkAvY8zKsGVDgFXGmB0xjuUB9jfGaIdqMi1ZAuXlAHx56q8Y//KXzd7l6MN7MOvjdbZP2gUeNyMO6ZpQgNKUuS+cOHVzxDO6IdjPX1HpbTQ7Z/j03Lv21DY6TrA6ZPmtP2vSeZeVV7DLZiSIxyWNyl+HX0dzA65oJbe1gJNSKijRbgsvsAdARLoBRwCXRll/FDBdREqMMTUikge8BlwEzAtfUUTaAn5jTPB/4QOBT0SkmzFmZ2CdPMBtjNFO1qZ6/HHrX5eL8Z2GJOUm/fbKLUw7a2CDYYPBkRnjRpVw+ysr4t5XcJvgvporWhJotGJEkSMLDA0DhvCb5n7j59nuozm5ANPmr7INxtq3bdPonMOvI3wa9HBFDq0YkWIFCFrASSkFcQQPItIFmGSMuRoIH493DvC5MeazsHXzsP5/dQG1xpi5IjIW2B9YCZQCy4wx80TEBeQZY6oDm98PHCMiuwP72AcoB16X+htAIfA5cGHTLreV270bnnvOev3//h+fmfZRV89zCzVxVJzcUOmNelO5Jo6cgaDwfINxc5Y1u+JlU3Ml7BIHg4FDZE5EKnIBnAKPyojuh8hhlb8Y2INZH61rMCLF4xImndYv7mNrgKCUiiWejug8rJt+pMuAfUTkOxFZLyJ7gNXANcD7wLci8i1wJPCqiHwN3AX0Dbz+JrB+0J+B24wxw4BTAuc2JbC/k4wxPwVmAn9K9CJVwAsvwI5Ab9Gll8a8ucUTOIDzUMBglcWm8iehVHZTJ9FKZGRBU3MBgt+f5RVVjapORss9CN8+cljlC0sqGHt0r0YjRjQYUEolUzzdFnVAg85XERkF9ASGGmNWichRwBRjzEmBVaaFrXsF8JIxZqOIHIAVTJQZY2oijuMH/iQiRcD5wGysh70y4HwRGQP0A55P7BJVyD/+Yf3bpQuMHs0IWZWUCaaqbbo+Ipv94zHsgL1Crye9vIJYZadiTa4VmR+QiERaEyKrPQrW8MZrZi3l9ldWcNup/RrlUkx6OWyIa6/GBZfime7baVjl2yu3NGodUUqpZGrKaAvBakH4N/BUYNn+wHcNVhIpFpFXgMuBQwOLu2B1d6wRkftEpH9w/UBi5DCsYAHgEOCfwBnAYuBZYLQxZl0TzlmtWwcLAq0A555L2YotzPo4Od9Kr6+uUR2BeIoXRVr0zY/sN34efcfPi6ueQ50xUfvyxx7di2nzVznOJxFNoq0JwRu+x9VwlMi23T7GzVkWOnYwqLK7vvAaDvFM9611F5RS6dLUOg+3Am8BG0SkM3AM8AGAiLiBu4GxwGTgcWNMHYAx5kPgdBHpC4wDrgauCGyXB1yPlZR5HfAQMByrC+MK4EtgiohcaIzZ0MTzbr2ee65+3OKFFzom5DVV8KbX3Kz/RLbrWVTgODeFx2VNnx3cX/iTffA8w1sW3CKcc0wvJpdapaubMrJg2vxVttUvfX4TKkUdK6gKv/HHyj3QugtKqXSJJ3goBNqIyPHAUOA7Y8w8ABF5GSt5cQxwL4Axxi8i7wCHATcBfwyMzFgL9AK2YLV4fG6MOS3sOG9jBSBPA18Ay7AClIXA8VitEF6sAOP6pl9y61NWXkG/GX/lIGBN116USzc2VG5K6jEqKr0JJUY2V7AVwKmAk91UG16fn9tfWUG1r67RDdxvTKgLZ0ifvRoEDTPGDoprzoloT/wVlV72Gz8vZnCUyI0/nq4NpZRKhXiChyFYD4S/onHp/0exbu7/Dm8NMMa8IiKlwGPA18BUY8wvRGQOVmtEe6xESCDUWjEWqDDGmEDeQ2esAOOXItLVGLMFeFtE8kTEbYxJTiGAHFdWXsHjj81j3qZvAXih5Hgef/Fzigo9Ka0OmUqdA5NyXTtrKa4YeQ+RYl3zM4vX8sKSiqiTP9lNEHXtrKUUeFzsjjJBWKyzTPTGr3UXlFLpEjN4MMbMFpEXAi0KVwDdwz4eFNiHEZE2xpjwNuREWqB/AUwCakQkuJ0H6CQiiwHChmu2AW4jok6Esjdt/irOXr4w9P6VQ4/H6/OTnPqNLSfYrTCkz14NbtxNHYrpxIDj3A7RZs00wG5fHS6Imehpp12eG4/bxbWzljJt/qq4gwCnro1YU2crpVRzxJXzEPaULxAqEHU7VhGoIcD/AR+IyG3Am2GFnuJijHkJeCl8mYh0x2p5GJrIvlRDGyq9/L9ViwD4vNsBrN7LuoFEe0JOlVijI6LxG8Osj9bx6rKNUXMGgqWyk92qEt4lEa14VadAq0g8CZ+C1U2xd7s91IVt4zTVdbzinTo7k2iwo1R2STRhsi1Wy8NC4L/AIGNMFfBbETkPK1FyoIiMw8prGIP1UJYnIpsC2x8f2FeeiFQBfzXG3GBzLA+Qn+D5qQhDa7ZQ8oPVl//vkmHpPZf9O7Pomx+bvL2vzsS8KaeqK8YAw6YuYMQhXRuVqg5XudvH6qmjQ+/7OlSfBELr/fVfr+D1NRz4FNnakYhoM2Nm4g05G4MdpVq7hIIHY8wMsEZGRNZpMMY8AzwTeDuluScWGJLZobn7ae0u3lIeev36wT9J45nA4m+3pfX48Sgq8LCrptZ2JEpFpbfBCA47kQmPnR1yS8InE6vx12E3arqpQy6zbQhntgU7SqkmzqppU+BJZajihW8A8NXevfh2733Tei5OXRbOs0+0rAKPm18M7BE1Wyda4GBXlOq2U/vhcTe8Qo9buO3U+nLReW77P8OmDrmMpzplJsm2YEcp1cwpuVWG27SJfuutCU3fPOiYNJ+MveKiAs4b2jvtAYRbBK/Pz3MfrrOt1RCPvDauRkWpSgcXM+2sgQ3LRZ/VsFx0t05tHQtSBUtYJ1LoKtumzs62YEcp1fQiUSobzKvvb//PgZkXPAj1E2Gt3rKzWfkQzRE+BXhzRm/sqvGzq8Z6Wo7st4/W/F5U4GHKGYc1ShgEmpQLkG1DOLVehVLZR4OHXPbvfwPwY0FHlvY4OM0n01inQGnpsvIKPl1blZZzCLY4xKvA40YwcY1W8fr8XD97GRA78c8uwBg2dUGTcwGyaWbMbAt2lFIaPOQunw/+8x8A1h51HHUud4wNUsclYNcTsL3ax+A73khbsSqPW+Iq0R0cXVHs0CIQjd+YJo8caE25ANkU7CilNHjIXYsXw/btAAy67Fd0/tY+69/pxp5MTvuvM8kdWlngcdPW44q6T7eINaFWoYed1fbzYoSvF+0pOPxJedeeWsdhpE0dOaBzVyilMpUGD7kq0OoAwMknM/qD722n30514NCSzjyymGdiTDEenPxq2NQFjkFGgcfdaAbLSJFPyrGmIG9Ka4HmAiilMpUGD7kqGDwcfjh068bbK1ek93xawNsrtzg+rYevU1ZeEXWdYOCQSNXD4PLrZy+zTbpsSmuB5gIopTKVBg+5aOdO+Ogj6/WJJwIt30/enFLUTbWh0suMsYOitgBETs0dqbioIBQ4JDrSIbg8ntaC8MBk/KA6KgPDOu32qcGCUirTaJ2HXPTf/0JtoD9/+HCg5fvJh+7fuUWPB9Y1lg4uZsoZA3CLfeWIaKMrwm/y0aoeRhM8fnhdh8gukGBgUlHpxWBVmJwwd3lcNRyUUioTaMtDLnr3XetfEeZ1OoC7pi6I2kyfCv9t4ZoN4dUdnVoAPC6JWgAqv019LN2ckQ6xWgu0HLNSKttpy0Mueu89AKoOKOGP/1nX4oEDJDYfezLUAZNeXhGqxAg0aAEoKvDErINd6fWFWgBSWfWwNQ3BVErlJg0eco3PBx9/DMD8ogMSKoCUzfyBGTcNVn7CtbOWcs2spQDMGDuIdvlt4qrpEGwBGDeqBI8rYk4Km7kr4hVeZtrl0KWiQzCVUtlCuy1yzbJl4LWeYD/o1nqH9AXDhGCiYyJBVKgFIPIeH/Y+kZEYkcmXdomkOgRTKZVNNHjINcFRFkB5T70ZgdWakMjoj55FBUybv6pRS4XPb0IJk4mMxLDLcYD6QlR5blfMuhJKKZVJtNsix6x5/R0AqvLb8V3nnmk+m8zhN6bRTJMetzTqmgi2ADjliVRUehMeieGUy1BnDKunjqakewcNHJRSWUWDhxzjC+Q7fNb9IHDoW89Gsa4kMgiw2z7YAgH1U2NPO3ug7bDKaEM9E0141CmnlVK5Rrstckl1NX03rwFgRfcD0nwyyRWtwyE4YdW0+ascWwyC2wdbIMJzFOye+p26OPzG0LnQfp6QokKP7TZaZloplWu05SGXfPEFbYw1VfQX++yf5pNpGQKhQCDem3E8xZ6KHVoFiosKcEqdcFoeT+GoeIWP2hg2dYEWllJKpYW2POSSzz4Lvfxin/3SeCItxwC3v7IiNCwzXrFqKow4pCvPLF7boMUj2FpwrcOxqhxm1YTklJluSslspZRKBW15yCFfv/UBAHvcbVpVsmRTpvWOlm9QVl7BC0sqGgQOgjVrZ+ng4rTlMDS1ZLZSSiWbtjzkiLLyCvb64FMOBFZ3LqbWnXk/Wo8LautavvpkpFj5BnY3aQM89+E6hvTZK+4chkRqQcSjOZUpk30uSqnWTVsecsS0+avY74d1AHy9d6/Q8kwacOGrg8I8d+wVUyiefAOnm7HfmFA3QaKTXwW7GJqTo9DUFo9UnItSqnXT4CFH/PBDFcVV3wPw7V71N7EWnhU7pl016SuXXVxUwKLxI2M+cUe7GXt9fm5/ZUXMp/hUdDGMG1XSqFZFPKM2bn9lhXZ3KKWSSoOHHNHP+wOuQIfAd3tlT75DcVEB948d1OApvrPDkMfm8Ljjn5fC7iYdbttun+NTfHA0hNOQ0eZMftWUURtl5RWOOSE6EZdSqqkyr2NcNcm+lRtDr78ryp7gIXiTXTR+ZKhffttuH0LTcyMKPC7y27ipDIx+6Fzo4bZT+8Xdxx9c7/rZy+IqaR3+FB9rHo3mJlUmOmojWuuCFqlSSjWVBg85Yu/N9f3X64q6p/FMEjduzjI+WfMjLyypCN14DTQpgBBgyhmHNzsZMLh9vJNqbXAoWx0uHYWhorUuaJEqpVRTabdFjjioZhsAe9wetrQrSu/JJMjnNzz74VrbEQ4Fnvh/RQU4b2jvpI0isOsmKCqw71LpWVQQ9UbdnMJQzeHUulBU4NHRFkqpJkt78CAiw0XkSxHZKCK3JLDdPiLyvYj0TeHpZY0T2lo3rg0du2TWEIs41Tk0MXh9dY7bFHpcdC70hG7sM8YOYnLpgKSeV+ngYhaNH8nqqaNZNH4kk07r55i06HSjjjdRMxWckiwnndavxc9FKZU70tptISKdgReBS4FXgPki8rEx5vU4Nv8r0DWV55dNinf9CMDGDq3jW3L/2EFpuRkHj+k02iLT5rCIdb5KKdUU6c55+DnwrTFmLoCIPAicC0QNHkTkIqATsDbVJ5g1NmwA4PsOe6X5RFpGc25+zS2Y5JS0mKk36mSUxlZKqXDpDh56A0vC3n8LRH1ME5HewCTgOOC9lJ1ZNjEGNm0C4IfCovSeSwtwmi47lrLyCia9vCI0CgOc54doaoChN2qlVGsgJo1VhETkZqCTMeaGwPsDgXnGGNsAQkQEeAt43BjznIh8Bww3xnxns+7lwOUAXbt2PXL27NmpuYgM4P3+e/7f2LEALPrVhXz6izPSfEbJ1a0ANoflIu7dLo/C/DZsrPRSG0iWcLuEnlESGiu9Piq2ealz+H3Pc7so6d7BcV2XCMWdnfffHDt37qR9+/ZJ32+myOXry+VrA72+bDdixIglxpghqdh3ulsetgJ9wt4XAtHGxf0B2GiMeS7Wjo0xjwGPAZSUlJjhw4c34zQz2+Ln6r8dZVVFPL883T/W5Lp+QC3TA9d0/tDe9OqzF+PmLMPnb5gI6HH5mHb2YbZP/lbhJufCTwLMGHsQ0+avoqKyBmi8bnGRm0XjhzfnUmwtXLiQXP79zOXry+VrA70+5Szdd5lFwDVh748B1kRZ/5fAQSKyKfC+K/CxiPzGGPNSak4x83m2bw+9rizomMYzSVxxUYFjNcZIAkwuHcCwqQvw+Ru3IPjqDNPmr6J0cHGjbodYx+hU4IlZ00ErMiqllCWtwYMxZrmIbBORe4D5wETg5ijr/yT8fbRui9akzY4doddVbbOrCW7Xntq41w0OhYx2E6+o9NJ3/LwGBaYqKr1RC04VeNyIELMYlFZkVEopS9rrPACnAz2A6cAjxpiZIjJWROam+byyxp5t9S0PO/IL03IOwXoLiQpPXowmfMhjPDfxyEAhWLEyUudCD1POGEClw/wPdsdXSqnWLu3BgzFmkzHmAmPMIGPM3YFls4wxMbP+jDF9W3urA8CuH7fj6wjL7gZ/e+eiSqm0bbePokIP7ZI45XawsmOe29WgOuO4USV43ImHKiZsn8EJucpv/Rmlg4ujBiTpqg6plFKZKt05DyoJxOtl0yjYdhT0y/+I/208MC3n4TR7Y1MEqzJCIKkpLI+hotLbpCKa4fuMNG5UiW2BJw0alFKqsbS3PKjmy6utYd3ZgMDxB79O0+ejzAwCjDikYaXMsvIKJsxdHkp8THSEcbRuh2BQ4vX5QzUktLVBKaWcafCQA/K6bcTfznpd4NnNwZ1XpPeEwria0EJggBeWVFBWXj9TaKwZK+0EDx0tEIgMSvzGhAINDRyUUsqedlvkAO9hn+Nva73Oc+3hZ31e4n/b+qf3pAKcJryKxevzc/3sZQAUkfgwSbcIfmMoDqsOaVc10i4o8fr8oSGfSimlGtPgIcssXz6GrVtfbriwryvUhuRyGQbt8zFPnfKLBqt8uvkY/lwe96SlGcFvDBPmLmfKT9xx1WoArERKY9V8gPry05+s+ZEXllSEAoXgcqfWDK3poJRSzrTbIsvsv/9d5Of3RqRt/UJ3wxEWbVz1tRNq/Hn8sHsf5nx1YUudYiPNmSDc6/OzuaradmrpyP13LvRQ6zehwCF8H899uM62hcFpngyt6aCUUs40eMgy7dr14+ijv6BLl9NwuaLXdKiuzefT74/hpkWPsGFnn6jrptJ5Q3vHXCfaL2KN3wqO8ts0XquowMOMsYO4f+wgqn11jqmifocMy2COQziPS9hdU8t+4+cxbOqCBrkXSimlNHjISm53O/r1m8UBB0xHJN92HZ/fw79WXsqjy26kxt/Wdp2WIGKVlI7lvrGDHFsB2riECXOX2xaU2lNrBRaxEiqd9h1MpgzWfygq8IBYw04N9d0bTgFEWXkFw6Yu0EBDKdWqaPCQxTp0OAKXyyF4qPOwZnt66j2Ey3O7Yt5Qi4sKKB1czDnH9GrUxVHgcWNwLh0dTG6MlqNQ4HFzzjG9GrUwhI+qWDR+JKunjqZdfptG82YEjxEpfKRGPIGGUkrlCg0estiOHZ9gjPU0XmeEPf586ox1+3VLLX07fZ3O0wOsloFxc5ZR4HH+VdtdU8vEsuW8sKSiQbeDAGceWYw/xpCN4OgJO24RppwxgMmlAxq0MDgN33RKyrQLTqKN1FBKqVymoy2yWGXle9TVeTEmjx+9RTy78jLOPfQxOuZVkt+mhoM7r+DtdT9P92ni8xva57exTWYEq4vgmcVrbeejeHvlFs7rEz3lMjjsMlaFyNLBxVGHX5aVVzhOoGUXnDi1duhIDaVUrtOWhyy2Y8eHgJsd1Udz06JH+PT7Y7np/b9Q/v0x+OtcHFCUOU/Albt9TDt7IMUOLQRObQsVld6oLQ8uIdT1EE/LQjTT5q+yPQ8B2+qUTq0dOlJDKZXrtOUhixUWHkqfPhOZs2BvavzWj7LG35a/LBvPT4vf5Khui1J+DsFiTLH0DOQ1lA4uZr/x8+IuoB1rmGd4XBGrZSEWpxYDE9h3JKfWDp19UymV67TlIYsdfvg8evS4hDY2NaDfrziZGZ9OSvk52A11jORxS+iGWlZegcth5EPkUqcuhEjXzFqalJEOTi0GTq0lyWjtUEqpbKQtD1murLwCf3pm4Q4588hi3l65hQ2VXjoVeKip9bPbZ51U50IPow/vwbT5q7hm1lLHgKDA4+aI3p1Y/O02/MbE3aIRFBzpAPatBPFoSktCc1s7lFIqG2nwkOWmzV/Fr3qldxbNZz5cC6Y+cTH8Zhoczhi8IdudqVuEM48s5oUlFaGAwW9M3C0PQc2dkyK4XeT8FxocKKVUQxo8ZLkNlV7old5zCDYQVFR6Gfe8NZlV8IY76eUVMWfD9BvDcx+ua9TSYEi8tHVzRzpoS4JSSsWmOQ9ZLtMy+311hkkvW1OCl5VX2FaFtOPURWGwCk0FcwrOH9rbqgLpIBnfD60aqZRS0WnwkOXGjSpxTEBMl2DAkIxiScVFBZR078DqqaNZNH4kQ/rsFSpJHSkZIx20aqRSSsWmwUOWKx1cTOdC5yfxdIpnCu1o7IIBpzksgpUkm9vloFUjlVIqNg0ecsCO6trYK0WI1vSfDOc9/oFjvkLnQo/j8Ee3SNRhj045DXXGJCVXQatGKqVUbJowmQOsKasTiwMnndaP62cvS2g4ZCIWffOj42eH9ejAig07Gi2PLCdtp2dRgW2LRrJyP1K9f6WUygXa8pAD8tyJ/xhvf2VFygKHWP77zY+2iZRen5/bX1kRNb9g3KgSx9kxIzUl8TGR/SulVGulLQ85oFuntgg1CdVE2LY7vlEQqRDtPLft9jFuTsPhnuHircUQWV8i3iJSWutBKaVi0+AhBxQVePjJAe2jdhUkW7s8NzW1fnwpqG7p85uoxZ7iqcUQLfExuG1ZeYVtkKC1HpRSKjoNHnLEd1tbNqGvpraOuoRrQMY/X0VzExRjJT42tWVCKaWU5jzkjJYeDeCrM1GnynZy3tDeeGwm8orU3ATFWNNl65BMpZRqOg0eckQ2jAZwizCkz160bxu9wSt8Fs6mipX4qEMylVKq6TR4yBHjRpVk/A/TbwzXzloaNVnTJTDtrIHN7jqINV12rJYJpZRSzjTnIUeUDi7mutlLE01BaHGxTq/O1Je1jpydM9ERENESH5sy/bZSSimLBg85pAkpCA0UOxRIammRyYuVXh8T3kpucqMOyVRKqabT4CGHuEWaXPhJsPr7iwo8bK/2NTsQSYTdeYcPq9xcVY3X53L8vKl0SKZSSjVNpneTqwQM3b9zk7c1ga9Kb8sGDsVFBdQ5BDzB5EWr/Lbz50oppVqWBg85pKVrPYQr8LjwuBObGrzA42bEIV0dpxQPJi86ld/W5EallEoPDR5ySHqfxIWxR/UKjW4o9LgIxgRuEc4f2pv7xw5qMPrhzCOLeWFJhW1Xi0sIJS9269RW55toAU2ZC0Qp1Tpp8JBD0vkk7vX5eXvlFhaNH8mMsYMwCMGYwG8MLyyxbkTjRpXQs6iADZVenvtwXaNCTUF1Bj5ZY5XbLirwRB12aXfT0xthYoIVNysqvRjqk1L1+6aUsqMJkzlk3KgSxs1Zhs+fnvGawZYPp+qNk15ewZ7autBnsZI7n/twHZNLBwDOyY12ZabHzVkGxqqCGVympaeji2cuEKWUCtKWhxxSOriYaWcNpF2eO+a6nhT85IMtH07dJ5Ven2NLg514Ro7Y3fR8fhMKHIK09HR0WnFTKZUIDR5yTOngYlbccQqdCz1R10v2bJjhOQjJ6j5xOyRShkvk5qY3QmdacVMplQgNHnLUbaf2a5RkmCpukQY5CONGlZDIuAundfPaSMw+90RubnojdBZrLhCllAqnwUNOS33uQ4HHzfRfNpyLonRwcdxH9riFGWMHcf7Q3kROtun11TFh7nIqvc5zYdjd9JzOU2+EzmLNBaKUUuE0YTIHlZVXMO75ZY36/ZNJIGpJ53hLXbfLaxNKhnx75ZZG23h9ftb9uIeJZctDyZPhwstMRzue3ghj04qbSql4actDDpo2f1VKA4fiogJWTx3NovEjo048FU+LQHirQrSchJmL1zKxbLntZ6WDi1k0fiTFDt0SxUUFelNUSqkk0uAhB6UyMVCAEYd0tf0svLbCtPmrOPPI4lAzuJPwpMhYOQnPfbgu6ufab6+UUi1Dg4cclMrEQAO8sKSiUSKjXZGhmYvXsmtPLTPGDnLcX/hwzFitFbGGbmq/vVJKtQwNHnLQuFEleCKzD5PI6/NzzaylDSo32tVbAKtbYsLc5Y5DR8O7GoI3fyexhm6WlVfoFNtKKdUCNHjIQaWDi5l29kCKCqLXemiuYOXGiWXLoyYren1+jCGuLoXSwcWcP7S37X7OOaaX4zHsWj6umbWUQbe/YTvcU8tXK6VU02nwkKNKBxez9Lafcf/YQSmt9+D1+Xlm8dqY61V6fXF3KUwuHcD5Q3uHWhoEa2Itu9EWQbFaPsKDA53HQSmlmkeHaua4eIcyNkc84zqCHQ6Lxo+Ma5+TSweEgoWFCxdy9XDnwAGiJ4lGztGg8zgopVTzaMtDKxAcyhhNtBSJAo/LcRhkvAykdG6JWEmi4cFFrHkctEtDKaWi0+ChFYmWbhitLMSZR+7LovEjm90FksohpLFGaoQHF9HmcdAuDaWUik2Dh1akqWWjXliyPvQ6v039r0y7PHdCv0BFMSbrihRsAVheURWzBSA4UsNuVEdkYma0ehDRujSUUkpZNHhoJZyqM8bD66tjYtnyRvNM7Krxk8jknHHMsB0S3gIA8bUAlA4upvxWK0k0WmJmtHoQOjW1UkrFpgmTrUBZeUVcIyKiefbDtVG7NuJRFWWCq0jNSWqMZ44Gp3V6OszJoTNyKqVUPW15aAWmzV/V7Pk1kzFVRiI34HS1AGiJa6WUii3twYOIDBeRL0Vko4jcEsf6fUVkpogsFJFJIpLfEueZzTKhyT3RG3C0pMZU0hLXSikVW1q7LUSkM/AicCnwCjBfRD42xrzusL4HeA24C/gQeBTYA0xpmTPOTk5N8ankcQvt8tpQ5fU1qVT0uFElTJi7vEHXRUu1AOjU1EopFV26cx5+DnxrjJkLICIPAucCtsED0B142Bjzz8D6LwJHt8SJZrNxo0q4dtbSZnddxOIWoc6YpMwrEV7QCXZQ3IR96lwXSimVGukOHnoDS8Lefws4PloaY9YBDwGIyMFYLRY3pfIEc0Hp4GI+WfMjzyxem9IAos4YVk8dnbT9BVsAFi5cyO/OG57QtsHRGsGWi+BojeB+lVJKNZ2YRMbPJfvgIjcDnYwxNwTeHwjMM8ZEbZsWkROBfwGrgFHGmF0261wOXA7QtWvXI2fPnp3s088YO3fupH379jHXq/T62FxVTY0/kQGW8WvjEg7t0THp+433+sKt2rTD9jrz3C5KundI1qklRVOuL5vk8vXl8rWBXl+2GzFixBJjzJBU7DvdLQ9bgT5h7wuBxrMbRTDGvCUixcA/gLuBq23WeQx4DKCkpMQMHz48GeebkRYuXEii1zexbDkzmzl8M1JRgYel5yR2HvGIdn1OXRMXj5+HsckHFmD11OSfY3M05eeXTXL5+nL52kCvTzlLd/CwCLgm7P0xwBqnlUWkN9DTGLPYGFMjIrOA61J7irlpcukAhvTZi+tnL8OfpNanKq8v4TyD5uQlROua0HoNSimVOmkdqmmMWQ5sE5F7Al0RE4FnomzSAZgrIgeJiBv4JVYAopqgdHAx5xzTK+qcF4lo63Fx7aylcc8L0dx5JKIVktJ6DUoplTppr/MAnA70AKYDjxhjZorIWBGZG7miMWYFVoLkm8A6YBcwqQXPNWeUlVcw+I43mNnEJMrIXxyPS/D66hrtK9q8EM2dRyJaISmt16CUUqmT7m4LjDGbgAsils0CZjms/xTwVMpPLIdFNvc3RR1WjkOwjsPumlq27bYvP51otch4i1rF6prQeg1KKZUamdDyoFqY3RN/U+yorg29dgocIPFqkfHmJWjXhFJKpYcGD61QsspV+40J5So4EXC8mTf35q9dE0oplR5p77ZQLa8ly1WfN7S34808vIpkU6tAateEUkq1PA0eWiG7eSNSZXLpgKif681fKaWyjwYPrVD4E39FpReBlJStLtaaCkoplZM0eGilwp/4wws1uUSSUjQqWq6DUkqp7KbBg2oQSOw3fl7c2xVHyZ0w2E9ApTNdKqVU9tPgQTXQqcBDpdd52GVQcVEBi8aPZNjUBbYBRHiXRTBgiOwi0ZkulVIqO+lQTdWAxFGrOnw4ZazhlhPLlodKVkPj3IpEKkoqpZTKDNryoBqojFLsCaBzoYfbTu0XaimINtyyrLyCZ+Iof52suhNKKaVahgYPqoFYNSCqfXWNljkNt5w2f1Vcozh0pkullMou2m2hGhg3qgSPy7nvIt5uhrLyirgKUWk5aaWUyj4aPKgGSgcXM+3sgRQVeBzXqaj0MmzqgphTbcdDy0krpVT20eBBNVI6uJilt/0sapGn4EgJuwAi3om3igo8GjgopVQW0uBBObIbSRHOqQsj3gTIXTW1jq0XTVFWXsGwqQvYb/y8qC0jSimlmkeDB+UofNZKJ3aBQrwJkD6/SdowzWBXSUWlNzTTp1PLiFJKqebR4EFFVTq4mEXjRzoGEJ1sciNitViES9YwTbuuEq0hoZRSqaHBg4qL0ygMu66HYIuFO46KU8kapukUhGgNCaWUSj4NHlRcSgcX075t47Igwa6HyHwDgOm/HBh12Gcyh2k6BSFaQ0IppZJPgwcVt20O1SeD+QWR+QZAo2GfwViiuKggqcM0Y5XJVkoplTxaYVLFpay8osGkVuHcIo75BovGj2yR4ZjRymQrpZRKLg0eVFycSk0L4Df2RajjqTCZTE5lspVSSiWXdluouDglHhpwHIkhoEMllVIqB2nwoOLilHhYHOgesEuLNKBDJZVSKgdp8KDiEi0hsXRwsePsmTpUUimlco8GDyou4dUmhcajJZy6LnSopFJK5R5NmFRxi5aQOG5UCRPmLm8w6kKHSiqlVG7S4EElhQ6VVEqp1kODB5U0OlRSKaVaB815UEoppVRCNHhQSimlVEI0eFBKKaVUQjTnQSVNWXlFkxImm7qdUkqp9NDgQSVFWXlFg6Ga4TNrRgsEmrqdUkqp9NFuC5UU0+avcpxZMxXbKaWUSh8NHlRSOJWhjlWeuqnbKaWUSh/ttlBJ0bOowHYK7ljlqYsKPWzb7Yu5neZFKKVU5tCWB5UU0SbOclJWXsHO6tpGyz1uabBdpdfHhLnLqaj0YqjPi9DpvpVSKj00eFBJEWviLDvT5q/CV9d4Ps52eW0abLe5qlrzIpRSKoNot4VKmkTLUzvlNVR5G3Zj1PjrsItzNS9CKaXSQ1seVNo45UNELs9z2/+a6nTfSimVHho8qLSJN0+iW6e2CedTKKWUSh0NHlTaxJsnUVTgSTifQimlVOpozoNKq3jzJHS6b6WUyhwaPKi00xoOSimVXTR4UGmlc1sopVT20eBBpVW0uS10Rk6llMpMGjyotGrO3BbaaqGUUumhwYNKq3jnxLBrYWhuq4VSSqmm0aGaKq3iqfXgNLeFXdABWnlSKaVSTVseVFoFWwii5S1Yc1s0jHO9Pj9uEfym8dwYWnlSKaVSS4MHlXaxajg4zW3hN4YCj7tB14VWnlRKqdTTbguV8ZzmtghWmtTKk0op1bK05UFlPGtuC79tC4NWnlRKqZanLQ8q4+ncFkoplVm05UFlBW1hUEqpzJH2lgcRGS4iX4rIRhG5JY71fysim0WkRkTmiEj7ljhPpZRSSlnSGjyISGfgReBmoDcwQkROibL+0cB44P8BPYB9gd+3wKkqpZRSKiDdLQ8/B741xsw1xviAB4Fzo6xfA5xtjPnUGLMVeBPom/rTVEoppVRQunMeegNLwt5/CzgO0jfGLA2+FhEBRgMz7NYVkcuBywNv94jI58092QzWBfgh3SeRQnp92S2Xry+Xrw30+rJdyorepDt4cAGVYe93AUVxbnsx0BZ4zu5DY8xjwGMAIvKJMWZIk88yw+n1ZTe9vuyVy9cGen3ZTkQ+SdW+0x08bAX6hL0vBPwO64aISAlwDzDKGFObonNTSimllI105zwsAo4Pe38MsCbaBoEky5eAm4wxS6Ktq5RSSqnkS2vwYIxZDmwTkXtE5ERgIvCM0/oi4gHmAW8FuiXilci62UivL7vp9WWvXL420OvLdim7PjE2sxK2JBHpDkwDBgDPGWPuFpGxwFhjzBkR656G1erwA/XdG/+NXE8ppZRSqZP24EEppZRS2SXdOQ9KKaWUyjJZEzwkq4y1iHhE5AkR2SIiH4rIgWHbDBCRT0TkexF5RERa7PuTxOvrISJvicgeEVkrImeEbfNG4Lo3Bb4uTuU1RZxvsq7vJyLiDbuGFU09RjIl8fpWhV3bJhHZLSK3Bj7Lpp9fXxGZKSILRWSSiOQHlufK35/T9WXc318Sry1X/vacri8n/vbCttsn8LfUN2zZnYFlK8Sq2Bxcvq+IvB24xtkiUhjzAMaYjP8COgPbgDMAD7AAOCXK+kcDq4EjgL2BxVijMwBuB/4LtAdOBBYHlrcBvgauwwqq/gFckYXX9yowFeiAVa1zO9A28Nn3QGGW//x+B0xp7jEy9foi1msDrAQOy7Kfnwf4ErgAODiw/oTAZ7nw9xft+jLq7y/J15YLf3uO1xexXlb+7UVs+yJggL6B9xcDXwH7AIcFXnsCn70D3B/42/sTMDXm/lv6m9HEb+B5wJKw96cDT0dZfxAwJOz9n4DHAq+/Ak4N+2wpsD8wLPAL4g4sHwy8m03XB0jgFySYy9Im8MvTM3CNy3Pg5/c0cGZzj5Gp1xex3uXA3wOvs+nn1wu4Ouz974B/Bl7nwt+f7fVl4t9fkn92ufC353h9Eetl5d9e2HoXYQUaa6gPHt4Efhe2zkvASKAYawBCUWD5XsCaWMfIlm6LhMtYG2M+gQZlrN9z2NfqwL56A0uNMcFRHFGPkWRJuT5jedIEfgMCy78xxmzAetrtJiLrRWRroFm4pYqEJfPndzQwNXANy0Tkp005RpIl8/oILHcBN2A9xUJ2/fzWGWMeAhCRg4FLqa8Emwt/f7bXl6F/f8n82eXC31606yOwPGv/9gBEpDcwCfg1VvAaa1+9sX5PKwGMMT8CHWJ1XWRL8JDMMtZO+2rOMZor6WW6RaQAuBu4NbCoNvB+P+Ag4Cis6LQlJOX6An+wi4FfGGP2Bu4FnhERdzOP0VypKLN+GrDKGPO/wPus+/mJVbtlEbATq1k02r6y7ufncH3BzzLl7y8p15Zrf3vRfnZk8d9e4GHkKayumHVx7ityOcBuoFOsE8sGW2n4DUu0jPUFpr6MtdO+mnSMJEnm9QU9AHxujHkWwBgzxxgz3RjjC0SWTwGO058nWVKuL/B1kTFmFYAx5p+BfR3a1GMkSSp+fr8Bngy+ycafnzHmLawm0XVY//lG21fW/fwcri8oU/7+knJtufa3F+Nnl81/e38ANhpj7OZ8ivdvL57jZE3wkMwy1qF9BZqnhgT29REwSETaxnuMJEpqmW4RuTKwv0vClv1KRPYJW21fWu4PPCnXJyLFInJm2DqFWP1z/qYcI4mS/fPbGysHYF7Ysqz5+YlIbxEZCmCMqQFmAYdH7itb//5iXF+m/f0l5dpy5W8vjp9dVv/tAb8EfhYcFYKV4/GxiIyJsq+vgPYiUgwgIgcBeVhBhbNkJ3ik6gv4AOsp7cTABZ8fZV0PVkb3wzafjQK+C+xnGvA/wBX47DmsxKefAuXAxCy8vtOwKnAeHLF8BlZSZXvgSGATNslPmXx9WFnCW7CS6TpgPd0tC/v5xX2MTLy+sM8vBP6dxT+/fsAGrCZeN/AsgSz9HPn7i3Z9Gff3l4xry6G/PcefXeDzrP7bs9n2O+oTJvtjJSWfijWq6QfqkySnAPOxAqc3gCdi7rulvgFJ+AZ2D/zHshS4MbBsLDDXZt3TsBJFtgR+0JvC18MapvMRVnRZEra8A/BQ4I9iGoFhLNl0fcCngDds+SbgJ0BHrCfdXcAq4Mps/PlhRdZrgR8D17NftGNk2/UFPn+aiKGb2fTzC3x2EdZ/XBuAx4H8sM+y+u8v2vVl4t9fEq8t6//24vjdzPq/vYhtvyMQPATenwK8D7wNDA1b7gEmB47xONAx1r61PLVSSimlEpItOQ9KKaWUyhAaPCillFIqIRo8KKWUUiohGjwopZRSKiEaPCillFIqIRo8KKUaCUzn285m+WAR+W+C+zpRRAbGsZ4nUHVTKZXhNHhQStm5DlgWrMYXZg/gi1w5MMdB+Pv8sLdnYxW4idymrYh4whYdCHwqIu3D1skLzBOhlMogLTUzmFIqu9wEbAbuFJHx1E/c5QH2EZGvA+8XG2POB+aIyBFYgYUH6/+W4sA6tcAOm2PcDxwjIruximbtg1VZ8nVrfh/AqrH/OVblP6VUhtAiUUqpRkSkvzHm88D8E4OA+4wxw0XkEODRwOv7AK8x5maHfYzHmolwGFYp3JWBj/5kjKkQkcOAA40xLwdaG5ZiTeyzGWtSqWoRuQ54xRjzVQovVymVIO22UEo1ICK9gFdE5Fms1gCnJ4z7gPtFpE0gyAjfRxusUs2vA+uxSk6/DvwcCHZp+IE/iciFwFxgduBYZcBQEZmBVU63OnlXp5RKBg0elFINGGPWYU21vA6rC8KNdTP/Dngr7PV7WN0TF2PlR3wrIjtFZClWsNDOGPMiVqvDQmNMGVbAsD1wnFVYrRJlgUMfglXD/wxgMdakRaMD56OUyiDabaGUshWYHvswoAi4FCt34UVjTJmIHAc8YowZELb+LUBbY8zNIiIm8J+LiLwJTDLGLBKRH4BexhiviOQBE7Amkvo31qRYv8NqbTgU+BJrFs4LjTEbWuaqlVLx0JYHpZSTccBtWNMXrwVmAZcFPvsD1jTFAIiV4Xge8ISI/Aq4O2w//YBvAq8LjDHewOu3sWbSfB74GGiL1bJxFFb3xidYrRLXJ/m6lFLNpC0PSqlGRGQQMB84EngGuAPrZl8OvAmcBRxijKkOrD8WONUYc76IFGElRx4V2N0CY8xBgWGZPxhjOgWGdvYAKowxJjC0szNWomQXEelqjNkS2Hce4DfG+Fvk4pVSMelQTaVUAyLSDZgD3AjsizXkcqExpk5EHsPqXrgyLHDoDjwCrAoUkOqGNWTzZmAbMDOw6/bArsDrXwCTgBoRCT7BeIBOIrI4sN/gKbXBagGZl4rrVUolToMHpVSkflj5BnOwWhrGAx1E5HrgV8AfgZtEZCRW/Ye3gSnAisDXOqA7cA5wFTA4sN+eQBWAMeYl4KXwgwaCkM+NMZGFqZRSGUZzHpRSDRhjFgClxpidwEmAAB9iDZkcbIyZjpXQ+A5W7oPHGHOvMeY1Y8zaQKJkV6wg49fGmO0iMgd4H2sEhRMP9cM4lVIZTHMelFIxiYg7kZyDQN2HI40xHwfelwBVxphNqTpHpVTL0eBBKaWUUgnRbgullFJKJUSDB6WUUkolRIMHpZRSSiVEgwellFJKJUSDB6WUUkol5P8Dv3IGx8iZEJEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Rp_target = np.linspace(Rp_vmin, max(Rp_list) + 0.1, 100)   # 生成投资组合的目标收益率数组\n",
    "Vp_target = list()\n",
    "for r in Rp_target:\n",
    "    # 以字典格式依次输入预期收益率等于目标收益率的约束条件和权重的约束条件\n",
    "    cons_new = (\n",
    "        {\n",
    "            'type': 'eq',\n",
    "            'fun': lambda x: np.sum(x) - 1\n",
    "        },\n",
    "        {\n",
    "            'type': 'eq',\n",
    "            'fun': lambda x: f(x)[0] - r\n",
    "        }\n",
    "    )\n",
    "    result_new = sco.minimize(Vmin_f, weights0, method=\"SLSQP\", bounds=bnds, constraints=cons_new)\n",
    "    Vp_target.append(result_new['fun'])\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(Vp_list, Rp_list)\n",
    "plt.plot(Vp_target, Rp_target, 'r-', label=u'有效前沿', lw=2.5)\n",
    "plt.plot(Vp_vmin, Rp_vmin, 'y*', label=u'全局最小波动率', markersize=14)\n",
    "plt.xlabel(u'波动率', fontsize=13)\n",
    "plt.ylabel(u'收益率', fontsize=13, rotation=0)\n",
    "plt.xticks(fontsize=13)\n",
    "plt.yticks(fontsize=13)\n",
    "plt.xlim(max(0, round(min(Vp_list) -0.05, 1)), round(max(Vp_list) + 0.05, 1))\n",
    "plt.ylim(round(min(Rp_list) - 0.05, 1), round(max(Rp_list) + 0.05, 1))\n",
    "plt.title(u'投资组合的有效前沿', fontsize=13)\n",
    "plt.legend(fontsize=13)\n",
    "plt.grid('True')\n",
    "plt.show()"
   ]
  },
  {
   "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": "3.8.5"
  }
 },
 "nbformat": 4,
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