Portfolio.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "import matplotlib.ticker as ticker\n",
    "import dataframe_image as dfi\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 台灣ESG電動車低排放投資組合建構"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 匯入資料 &　日期處理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_excel(\"price.xlsx\", header=0,engine='openpyxl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['年月'] = df['年月'].astype('str')\n",
    "df['年月'] = df['年月'].str.replace('-','')\n",
    "df['年月'] = df['年月'].str[0:6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "年月\n",
       "201701     9\n",
       "201702     9\n",
       "201703     9\n",
       "201704     9\n",
       "201705     9\n",
       "201706     9\n",
       "201707     9\n",
       "201708     9\n",
       "201709     9\n",
       "201710     9\n",
       "201711     9\n",
       "201712     9\n",
       "201801     9\n",
       "201802     9\n",
       "201803     9\n",
       "201804     9\n",
       "201805     9\n",
       "201806     9\n",
       "201807     9\n",
       "201808     9\n",
       "201809     9\n",
       "201810     9\n",
       "201811     9\n",
       "201812     9\n",
       "201901    10\n",
       "201902    10\n",
       "201903    10\n",
       "201904    10\n",
       "201905    10\n",
       "201906    10\n",
       "201907    10\n",
       "201908    10\n",
       "201909    10\n",
       "201910    10\n",
       "201911    10\n",
       "201912    10\n",
       "202001    11\n",
       "202002    11\n",
       "202003    11\n",
       "202004    11\n",
       "202005    11\n",
       "202006    11\n",
       "202007    11\n",
       "202008    11\n",
       "202009    11\n",
       "202010    11\n",
       "202011    11\n",
       "202012    11\n",
       "Name: 證券代碼, dtype: int64"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('年月')['證券代碼'].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 市值 & 平均加權"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df['年'] = df['年月'].str[0:4]\n",
    "# df['MktWeight'] = (df.groupby(['年','證券代碼'])['市值(百萬元)'].transform('sum').astype(int))/(df.groupby('年')['市值(百萬元)'].transform('sum').astype(int))\n",
    "# df.loc[df['年'] == '2017', 'EqWeight'] = 1/9\n",
    "# df.loc[df['年'] == '2018', 'EqWeight'] = 1/9\n",
    "# df.loc[df['年'] == '2019', 'EqWeight'] = 1/10\n",
    "# df.loc[df['年'] == '2020', 'EqWeight'] = 1/11"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 採用市值加權，權重過度集中於台積電\n",
    "- 採用等權重加權，無法凸顯投資組合的特色\n",
    "- 因此最後採用MSCI ESG Score加權"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MSCI ESG Score 加權"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['年'] = df['年月'].str[0:4]\n",
    "df[\"MSCI ESG Score\"] = df[\"MSCI ESG Score\"].map({6:12, 5:7.5, 4:4, 3:2, 2:1})\n",
    "df.dropna()\n",
    "df[\"Weight\"] = (df.groupby([\"年\",\"證券代碼\"])[\"MSCI ESG Score\"].transform('sum'))/(df.groupby('年')['MSCI ESG Score'].transform('sum'))\n",
    "df.drop(['流通在外股數(千股)','市值(百萬元)'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pd.reset_option(\"display.max_rows\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 報酬計算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "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",
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       "    }\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>證券代碼</th>\n",
       "      <th>公司</th>\n",
       "      <th>年月</th>\n",
       "      <th>收盤價(元)_月</th>\n",
       "      <th>MSCI ESG Score</th>\n",
       "      <th>年</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Return_M</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2002</td>\n",
       "      <td>中鋼</td>\n",
       "      <td>201702</td>\n",
       "      <td>22.53</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.125000</td>\n",
       "      <td>0.019457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2301</td>\n",
       "      <td>光寶科</td>\n",
       "      <td>201702</td>\n",
       "      <td>39.53</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.125000</td>\n",
       "      <td>0.091085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2308</td>\n",
       "      <td>台達電</td>\n",
       "      <td>201702</td>\n",
       "      <td>148.84</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.125000</td>\n",
       "      <td>-0.017233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2330</td>\n",
       "      <td>台積電</td>\n",
       "      <td>201702</td>\n",
       "      <td>162.97</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>0.018881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2382</td>\n",
       "      <td>廣達</td>\n",
       "      <td>201702</td>\n",
       "      <td>51.37</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>0.001560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462</th>\n",
       "      <td>2357</td>\n",
       "      <td>華碩</td>\n",
       "      <td>202012</td>\n",
       "      <td>250.50</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>0.077670</td>\n",
       "      <td>0.006024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464</th>\n",
       "      <td>2382</td>\n",
       "      <td>廣達</td>\n",
       "      <td>202012</td>\n",
       "      <td>80.90</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>0.077670</td>\n",
       "      <td>0.050649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>465</th>\n",
       "      <td>3481</td>\n",
       "      <td>群創</td>\n",
       "      <td>202012</td>\n",
       "      <td>14.10</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>0.038835</td>\n",
       "      <td>0.402985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>466</th>\n",
       "      <td>3711</td>\n",
       "      <td>日月光投控</td>\n",
       "      <td>202012</td>\n",
       "      <td>81.30</td>\n",
       "      <td>7.5</td>\n",
       "      <td>2020</td>\n",
       "      <td>0.145631</td>\n",
       "      <td>0.061358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>467</th>\n",
       "      <td>4938</td>\n",
       "      <td>和碩</td>\n",
       "      <td>202012</td>\n",
       "      <td>67.30</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>0.038835</td>\n",
       "      <td>0.030628</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>399 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     證券代碼     公司      年月  收盤價(元)_月  MSCI ESG Score     年    Weight  Return_M\n",
       "9    2002     中鋼  201702     22.53             4.0  2017  0.125000  0.019457\n",
       "10   2301    光寶科  201702     39.53             4.0  2017  0.125000  0.091085\n",
       "11   2308    台達電  201702    148.84             4.0  2017  0.125000 -0.017233\n",
       "13   2330    台積電  201702    162.97            12.0  2017  0.375000  0.018881\n",
       "15   2382     廣達  201702     51.37             2.0  2017  0.062500  0.001560\n",
       "..    ...    ...     ...       ...             ...   ...       ...       ...\n",
       "462  2357     華碩  202012    250.50             4.0  2020  0.077670  0.006024\n",
       "464  2382     廣達  202012     80.90             4.0  2020  0.077670  0.050649\n",
       "465  3481     群創  202012     14.10             2.0  2020  0.038835  0.402985\n",
       "466  3711  日月光投控  202012     81.30             7.5  2020  0.145631  0.061358\n",
       "467  4938     和碩  202012     67.30             2.0  2020  0.038835  0.030628\n",
       "\n",
       "[399 rows x 8 columns]"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Return_M'] = df.groupby('證券代碼')['收盤價(元)_月'].pct_change()\n",
    "df.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['WeightxReturn'] = df['Return_M']*df['Weight']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "Port_return = df.groupby('年月')['WeightxReturn'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "年月\n",
       "201701    0.000000\n",
       "201702    0.016820\n",
       "201703   -0.001044\n",
       "201704    0.027468\n",
       "201705    0.015998\n",
       "201706    0.047902\n",
       "201707    0.008146\n",
       "201708    0.004484\n",
       "201709   -0.028846\n",
       "201710    0.026744\n",
       "201711   -0.067589\n",
       "201712    0.023314\n",
       "201801    0.060812\n",
       "201802   -0.040800\n",
       "201803   -0.015014\n",
       "201804   -0.089340\n",
       "201805    0.000634\n",
       "201806   -0.017480\n",
       "201807    0.091060\n",
       "201808    0.033754\n",
       "201809    0.016085\n",
       "201810   -0.079302\n",
       "201811    0.018380\n",
       "201812   -0.002135\n",
       "201901    0.052683\n",
       "201902    0.029334\n",
       "201903    0.022888\n",
       "201904    0.029207\n",
       "201905   -0.090336\n",
       "201906    0.038575\n",
       "201907    0.048520\n",
       "201908    0.016642\n",
       "201909   -0.008104\n",
       "201910    0.059112\n",
       "201911    0.022945\n",
       "201912    0.065458\n",
       "202001   -0.044804\n",
       "202002   -0.034548\n",
       "202003   -0.118744\n",
       "202004    0.115666\n",
       "202005   -0.012886\n",
       "202006    0.094130\n",
       "202007    0.155521\n",
       "202008   -0.028353\n",
       "202009    0.005238\n",
       "202010    0.004719\n",
       "202011    0.109361\n",
       "202012    0.094655\n",
       "Name: WeightxReturn, dtype: float64"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Port_return"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 基金比較"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 0050 元大台灣50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_0050 = pd.read_excel(\"Fund.xlsx\", sheet_name = \"0050\", header=0,engine='openpyxl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_0050['年月日'] = df_0050['年月日'].astype('str')\n",
    "df_0050['年月日'] = df_0050['年月日'].str.replace('-','')\n",
    "df_0050['年月日'] = df_0050['年月日'].str[0:6]\n",
    "df_0050.set_index(\"年月日\", inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_0050['Return_M'] = df_0050['淨值(元)'].pct_change()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_0050['Return_M_Cum'] = ( df_0050['Return_M']+1).cumprod()\n",
    "df_0050.iloc[0,2] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "returns1 = pd.DataFrame(columns=[\"Port_return\",\"0050\"], index = Port_return.index)\n",
    "returns1['Port_return'] = Port_return \n",
    "returns1['0050'] = df_0050['Return_M_Cum']\n",
    "returns1['Port_return_Cum'] =  ( returns1['Port_return']+1).cumprod()\n",
    "# returns1.drop(['Port_return'], axis=1, inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
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     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
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    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,7))\n",
    "\n",
    "plt.plot(returns1['Port_return_Cum'],label='Portfolio', linewidth=3)\n",
    "plt.plot(returns1['0050'],label='0050' , linewidth=3)\n",
    "\n",
    "\n",
    "ax.xaxis.set_major_locator(ticker.MultipleLocator(12))\n",
    "\n",
    "plt.title('Portfolio V.S 0050',size = 18, color = 'mediumseagreen')\n",
    "plt.xlabel('Date', fontsize=16, color = \"mediumseagreen\")\n",
    "plt.ylabel('Cumulated Return', fontsize=16, color= \"mediumseagreen\")\n",
    "plt.grid(True)\n",
    "plt.legend(fontsize=\"x-large\")\n",
    "plt.xticks(fontsize=14 )\n",
    "plt.yticks(fontsize=14 )\n",
    "# plt.savefig(\"0050.png\",dpi=150)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "Geo_a_return = (returns1['Port_return_Cum']['202012'])**(12/len(returns1))-1\n",
    "Geo_a_return_0050 = (returns1['0050']['202012'])**(12/len(returns1))-1\n",
    "\n",
    "STD_return  = Port_return.std()*np.sqrt(12)\n",
    "STD_return_0050   = df_0050['Return_M'].std()*np.sqrt(12)\n",
    "\n",
    "Sharpe = Geo_a_return / STD_return \n",
    "Sharpe_0050 = Geo_a_return_0050 / STD_return_0050 \n",
    "\n",
    "#計算MDD\n",
    "D = returns1['Port_return_Cum'].cummax() - returns1['Port_return_Cum']\n",
    "MDD = D.max()*1\n",
    "d = D / (D + returns1['Port_return_Cum'])\n",
    "mdd = d.max()\n",
    "\n",
    "D = returns1['0050'].cummax() - returns1['0050']\n",
    "MDD = D.max()*1\n",
    "d = D / (D + returns1['0050'])\n",
    "mdd_0050 = d.max()\n",
    "\n",
    "#投組勝率\n",
    "Odd =sum(Port_return>0)/len(returns1)\n",
    "\n",
    "Odd_0050 =sum(df_0050['Return_M']>0)/len(returns1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_performance=pd.DataFrame([\n",
    "                  [Geo_a_return,STD_return ,Sharpe,mdd,Odd ],\n",
    "                  [Geo_a_return_0050,STD_return_0050 ,Sharpe_0050,mdd_0050,Odd_0050 ],\n",
    "                 ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_performance.columns = [ 'ER','STD','Sharpe','Mdd','Odd' ]\n",
    "df_performance.index =  ['Portfolio','0050']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "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>ER</th>\n",
       "      <th>STD</th>\n",
       "      <th>Sharpe</th>\n",
       "      <th>Mdd</th>\n",
       "      <th>Odd</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Portfolio</th>\n",
       "      <td>0.16</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0050</th>\n",
       "      <td>0.14</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.65</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ER   STD  Sharpe   Mdd   Odd\n",
       "Portfolio  0.16  0.19    0.85  0.19  0.65\n",
       "0050       0.14  0.18    0.77  0.21  0.65"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_performance.round(2)\n",
    "# dfi.export(df_performance.round(2), '0050_table.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 00850 元大臺灣ESG永續"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_00850 = pd.read_excel(\"Fund.xlsx\", sheet_name = \"00850\", header=0,engine='openpyxl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_00850['年月日'] = df_00850['年月日'].astype('str')\n",
    "df_00850['年月日'] = df_00850['年月日'].str.replace('-','')\n",
    "df_00850['年月日'] = df_00850['年月日'].str[0:6]\n",
    "df_00850.set_index(\"年月日\", inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_00850['Return_M'] = df_00850['淨值(元)'].pct_change()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_00850['Return_M_Cum'] = ( df_00850['Return_M']+1).cumprod()\n",
    "df_00850.iloc[0,2] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df[df[\"年月\"]>=\"201908\"]\n",
    "df2['Return_M'] = df2.groupby('證券代碼')['收盤價(元)_月'].pct_change()\n",
    "df2.dropna()\n",
    "df2['WeightxReturn'] = df2['Return_M']*df2['Weight']\n",
    "Port_return2 = df2.groupby('年月')['WeightxReturn'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "returns2 = pd.DataFrame(columns=[\"Port_return\",\"00850\"], index = Port_return2.index)\n",
    "returns2['Port_return'] = Port_return2\n",
    "returns2['00850'] = df_00850['Return_M_Cum']\n",
    "returns2['Port_return_Cum'] =  ( returns2['Port_return']+1).cumprod()\n",
    "# returns2.drop(['Port_return'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0.8, 0.9, 1. , 1.1, 1.2, 1.3, 1.4, 1.5, 1.6]),\n",
       " [Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, '')])"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,7))\n",
    "\n",
    "plt.plot(returns2['Port_return_Cum'],label='Portfolio', linewidth=3)\n",
    "plt.plot(returns2['00850'],label='00850' , linewidth=3)\n",
    "\n",
    "\n",
    "ax.xaxis.set_major_locator(ticker.MultipleLocator(12))\n",
    "\n",
    "plt.title('Portfolio V.S 00850',size = 18, color = 'mediumseagreen')\n",
    "plt.xlabel('Date', fontsize=16, color = \"mediumseagreen\")\n",
    "plt.ylabel('Cumulated Return', fontsize=16, color= \"mediumseagreen\")\n",
    "plt.grid(True)\n",
    "plt.legend(fontsize=\"x-large\")\n",
    "plt.xticks(fontsize=14 )\n",
    "plt.yticks(fontsize=14 )\n",
    "# plt.savefig(\"00850.png\",dpi=150)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "Geo_a_return = (returns2['Port_return_Cum']['202012'])**(12/len(returns2))-1\n",
    "Geo_a_return_00850 = (returns2['00850']['202012'])**(12/len(returns2))-1\n",
    "\n",
    "STD_return  = Port_return2.std()*np.sqrt(12)\n",
    "STD_return_00850   = df_00850['Return_M'].std()*np.sqrt(12)\n",
    "\n",
    "Sharpe = Geo_a_return / STD_return \n",
    "Sharpe_00850 = Geo_a_return_00850 / STD_return_00850 \n",
    "\n",
    "#計算MDD\n",
    "D = returns2['Port_return_Cum'].cummax() - returns2['Port_return_Cum']\n",
    "MDD = D.max()*1\n",
    "d = D / (D + returns2['Port_return_Cum'])\n",
    "mdd = d.max()\n",
    "\n",
    "D = returns2['00850'].cummax() - returns2['00850']\n",
    "MDD = D.max()*1\n",
    "d = D / (D + returns2['00850'])\n",
    "mdd_00850 = d.max()\n",
    "\n",
    "#投組勝率\n",
    "Odd =sum(Port_return2>0)/len(returns2)\n",
    "Odd_00850 =sum(df_00850['Return_M']>0)/len(returns2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_performance=pd.DataFrame([\n",
    "                  [Geo_a_return,STD_return ,Sharpe,mdd,Odd ],\n",
    "                  [Geo_a_return_00850,STD_return_00850 ,Sharpe_00850,mdd_00850,Odd_0050 ],\n",
    "                 ])\n",
    "df_performance.columns = [ 'ER','STD','Sharpe','Mdd','Odd' ]\n",
    "df_performance.index =  ['Portfolio','00850']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_performance.round(2)\n",
    "# dfi.export(df_performance.round(2), '00850_table.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 00878 國泰永續高股息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_00878 = pd.read_excel(\"Fund.xlsx\", sheet_name = \"00878\", header=0,engine='openpyxl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_00878['年月日'] = df_00878['年月日'].astype('str')\n",
    "df_00878['年月日'] = df_00878['年月日'].str.replace('-','')\n",
    "df_00878['年月日'] = df_00878['年月日'].str[0:6]\n",
    "df_00878.set_index(\"年月日\", inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_00878['Return_M'] = df_00878['淨值(元)'].pct_change()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_00878['Return_M_Cum'] = ( df_00878['Return_M']+1).cumprod()\n",
    "df_00878.iloc[0,2] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "df3 = df[df[\"年月\"]>=\"202007\"]\n",
    "df3['Return_M'] = df3.groupby('證券代碼')['收盤價(元)_月'].pct_change()\n",
    "df3.dropna()\n",
    "df3['WeightxReturn'] = df3['Return_M']*df3['Weight']\n",
    "Port_return3 = df3.groupby('年月')['WeightxReturn'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "returns3 = pd.DataFrame(columns=[\"Port_return\"], index = Port_return3.index)\n",
    "returns3['Port_return'] = Port_return3\n",
    "returns3['00878'] = df_00878['Return_M_Cum']\n",
    "returns3['Port_return_Cum'] =  ( returns3['Port_return']+1).cumprod()\n",
    "# returns3.drop(['Port_return'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0.9 , 0.95, 1.  , 1.05, 1.1 , 1.15, 1.2 , 1.25]),\n",
       " [Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, '')])"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,7))\n",
    "\n",
    "\n",
    "plt.plot(returns3['Port_return_Cum'],label='Portfolio', linewidth=3)\n",
    "plt.plot(returns3['00878'],label='00878' , linewidth=3)\n",
    "\n",
    "\n",
    "ax.xaxis.set_major_locator(ticker.MultipleLocator(6))\n",
    "\n",
    "plt.title('Portfolio V.S 00878',size = 18, color = 'mediumseagreen')\n",
    "plt.xlabel('Date', fontsize=16, color = \"mediumseagreen\")\n",
    "plt.ylabel('Cumulated Return', fontsize=16, color= \"mediumseagreen\")\n",
    "plt.grid(True)\n",
    "plt.legend(fontsize=\"x-large\")\n",
    "plt.xticks(fontsize=14 )\n",
    "plt.yticks(fontsize=14 )\n",
    "# plt.savefig(\"00878.png\",dpi=150)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "Geo_a_return = (returns3['Port_return_Cum']['202012'])**(12/len(returns3))-1\n",
    "Geo_a_return_00878 = (returns3['00878']['202012'])**(12/len(returns3))-1\n",
    "\n",
    "STD_return  = Port_return3.std()*np.sqrt(12)\n",
    "STD_return_00878   = df_00878['Return_M'].std()*np.sqrt(12)\n",
    "\n",
    "Sharpe = Geo_a_return / STD_return \n",
    "Sharpe_00878 = Geo_a_return_00878 / STD_return_00878 \n",
    "\n",
    "#計算MDD\n",
    "D = returns3['Port_return_Cum'].cummax() - returns3['Port_return_Cum']\n",
    "MDD = D.max()*1\n",
    "d = D / (D + returns3['Port_return_Cum'])\n",
    "mdd = d.max()\n",
    "\n",
    "D = returns3['00878'].cummax() - returns3['00878']\n",
    "MDD = D.max()*1\n",
    "d = D / (D + returns3['00878'])\n",
    "mdd_00878 = d.max()\n",
    "\n",
    "#投組勝率\n",
    "Odd =sum(Port_return3>0)/len(returns3)\n",
    "Odd_00878 =sum(df_00878['Return_M']>0)/len(returns3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_performance=pd.DataFrame([\n",
    "                  [Geo_a_return,STD_return ,Sharpe,mdd,Odd ],\n",
    "                  [Geo_a_return_00878,STD_return_00878 ,Sharpe_00878,mdd_00878,Odd_00878 ],\n",
    "                 ])\n",
    "df_performance.columns = [ 'ER','STD','Sharpe','Mdd','Odd' ]\n",
    "df_performance.index =  ['Portfolio','00878']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "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>ER</th>\n",
       "      <th>STD</th>\n",
       "      <th>Sharpe</th>\n",
       "      <th>Mdd</th>\n",
       "      <th>Odd</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Portfolio</th>\n",
       "      <td>0.42</td>\n",
       "      <td>0.20</td>\n",
       "      <td>2.14</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00878</th>\n",
       "      <td>0.17</td>\n",
       "      <td>0.14</td>\n",
       "      <td>1.19</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ER   STD  Sharpe   Mdd   Odd\n",
       "Portfolio  0.42  0.20    2.14  0.03  0.67\n",
       "00878      0.17  0.14    1.19  0.04  0.33"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_performance.round(2)\n",
    "# dfi.export(df_performance.round(2), '00878_table.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## T4812A 合庫AI車聯網Aa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_T4812A = pd.read_excel(\"Fund.xlsx\", sheet_name = \"T4812A\", header=0,engine='openpyxl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_T4812A['年月日'] = df_T4812A['年月日'].astype('str')\n",
    "df_T4812A['年月日'] = df_T4812A['年月日'].str.replace('-','')\n",
    "df_T4812A['年月日'] = df_T4812A['年月日'].str[0:6]\n",
    "df_T4812A.set_index(\"年月日\", inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_T4812A['Return_M'] = df_T4812A['淨值(元)'].pct_change()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "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>淨值(元)</th>\n",
       "      <th>Return_M</th>\n",
       "      <th>Return_M_Cum</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>年月日</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>201903</th>\n",
       "      <td>9.998962</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201904</th>\n",
       "      <td>10.459836</td>\n",
       "      <td>0.046092</td>\n",
       "      <td>1.046092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201905</th>\n",
       "      <td>9.207461</td>\n",
       "      <td>-0.119732</td>\n",
       "      <td>0.920842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201906</th>\n",
       "      <td>10.029019</td>\n",
       "      <td>0.089227</td>\n",
       "      <td>1.003006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201907</th>\n",
       "      <td>10.008981</td>\n",
       "      <td>-0.001998</td>\n",
       "      <td>1.001002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201908</th>\n",
       "      <td>9.598202</td>\n",
       "      <td>-0.041041</td>\n",
       "      <td>0.959920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201909</th>\n",
       "      <td>9.728449</td>\n",
       "      <td>0.013570</td>\n",
       "      <td>0.972946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201910</th>\n",
       "      <td>9.928829</td>\n",
       "      <td>0.020597</td>\n",
       "      <td>0.992986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201911</th>\n",
       "      <td>10.359646</td>\n",
       "      <td>0.043391</td>\n",
       "      <td>1.036072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201912</th>\n",
       "      <td>10.730349</td>\n",
       "      <td>0.035783</td>\n",
       "      <td>1.073146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202001</th>\n",
       "      <td>10.550007</td>\n",
       "      <td>-0.016807</td>\n",
       "      <td>1.055110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202002</th>\n",
       "      <td>9.928829</td>\n",
       "      <td>-0.058879</td>\n",
       "      <td>0.992986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202003</th>\n",
       "      <td>8.435998</td>\n",
       "      <td>-0.150353</td>\n",
       "      <td>0.843687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202004</th>\n",
       "      <td>9.548107</td>\n",
       "      <td>0.131829</td>\n",
       "      <td>0.954910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202005</th>\n",
       "      <td>10.550007</td>\n",
       "      <td>0.104932</td>\n",
       "      <td>1.055110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202006</th>\n",
       "      <td>10.980824</td>\n",
       "      <td>0.040836</td>\n",
       "      <td>1.098196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202007</th>\n",
       "      <td>11.692173</td>\n",
       "      <td>0.064781</td>\n",
       "      <td>1.169339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202008</th>\n",
       "      <td>12.423560</td>\n",
       "      <td>0.062554</td>\n",
       "      <td>1.242485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202009</th>\n",
       "      <td>11.882534</td>\n",
       "      <td>-0.043548</td>\n",
       "      <td>1.188377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202010</th>\n",
       "      <td>11.902572</td>\n",
       "      <td>0.001686</td>\n",
       "      <td>1.190381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202011</th>\n",
       "      <td>13.716011</td>\n",
       "      <td>0.152357</td>\n",
       "      <td>1.371743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202012</th>\n",
       "      <td>14.317151</td>\n",
       "      <td>0.043828</td>\n",
       "      <td>1.431864</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            淨值(元)  Return_M  Return_M_Cum\n",
       "年月日                                      \n",
       "201903   9.998962       NaN      1.000000\n",
       "201904  10.459836  0.046092      1.046092\n",
       "201905   9.207461 -0.119732      0.920842\n",
       "201906  10.029019  0.089227      1.003006\n",
       "201907  10.008981 -0.001998      1.001002\n",
       "201908   9.598202 -0.041041      0.959920\n",
       "201909   9.728449  0.013570      0.972946\n",
       "201910   9.928829  0.020597      0.992986\n",
       "201911  10.359646  0.043391      1.036072\n",
       "201912  10.730349  0.035783      1.073146\n",
       "202001  10.550007 -0.016807      1.055110\n",
       "202002   9.928829 -0.058879      0.992986\n",
       "202003   8.435998 -0.150353      0.843687\n",
       "202004   9.548107  0.131829      0.954910\n",
       "202005  10.550007  0.104932      1.055110\n",
       "202006  10.980824  0.040836      1.098196\n",
       "202007  11.692173  0.064781      1.169339\n",
       "202008  12.423560  0.062554      1.242485\n",
       "202009  11.882534 -0.043548      1.188377\n",
       "202010  11.902572  0.001686      1.190381\n",
       "202011  13.716011  0.152357      1.371743\n",
       "202012  14.317151  0.043828      1.431864"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_T4812A['Return_M_Cum'] = ( df_T4812A['Return_M']+1).cumprod()\n",
    "df_T4812A.iloc[0, 2] = 1\n",
    "df_T4812A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "df4 = df[df[\"年月\"]>=\"201903\"]\n",
    "df4['Return_M'] = df4.groupby('證券代碼')['收盤價(元)_月'].pct_change()\n",
    "df4.dropna()\n",
    "df4['WeightxReturn'] = df4['Return_M']*df4['Weight']\n",
    "Port_return4 = df4.groupby('年月')['WeightxReturn'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "returns4 = pd.DataFrame(columns=[\"Port_return\",\"T4812A\"], index = Port_return4.index)\n",
    "returns4['Port_return'] = Port_return4\n",
    "returns4['T4812A'] = df_T4812A['Return_M_Cum']\n",
    "returns4['Port_return_Cum'] =  ( returns4['Port_return']+1).cumprod()\n",
    "# returns4.drop(['Port_return'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0.8, 0.9, 1. , 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7]),\n",
       " [Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, '')])"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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oTnvsCazkYyzWh/N3XT8/Bvq5aqmdCW+9J7B6OXIW0jjtwjFYi87ciTWv6QqsEhPvYZW7mIO1tL8n5/GY0x67BSuBiMHqrfs31tDNx7EWcrndtS2vYKzes5zHK1i13P4NXFHc0v2uVUJ7AX847bHFzZH7CWtF1ttL/q7cHi4QZ95HsfXunPbYF7Hq9e3Dqgf4AVaJk2AKfCngtMd+hJXwb3Lte98V9zJgd55Dh2Ml+K9i/Y2fblXT4uI7jpXgvIWVoL6NVVOvFdbKmZ6eJxP43NXcilUfsOAx04HzsHoJb8H6XTyBNZw6llOHVJ+tm7G+HAoBnse6Dy7EWtCqWE577J1YiWQ28DTW7/h2rJ7Zp70cp4hUcoZpqhSNiIiIiIhIVaOeQRERERERkSpIyaCIiIiIiEgVpGRQRERERESkClIyKCIiIiIiUgVV6tISdevWNaOjo30dximSk5MJDw/3dRgilZruM5HSpXtMpPTpPhNvWLZs2RHTNOsVtq9SJ4PR0dEsXbrU12GcIi4ujoEDB/o6DJFKTfeZSOnSPSZS+nSfiTcYhrGzqH0aJioiIiIiIlIFKRkUERERERGpgpQMioiIiIiIVEFKBkVERERERKogJYMiIiIiIiJVUKVeTdQTCQkJHDp0iIyMjDK7Zo0aNVi/fn2ZXU+kNAUGBlK/fn2qV6/u61BEREREpASqdDKYkJDAwYMHadSoEaGhoRiGUSbXTUxMpFq1amVyLZHSZJomKSkp7N27F0AJoYiIiEgFUqWHiR46dIhGjRoRFhZWZomgSGViGAZhYWE0atSIQ4cO+TocERERESmBKp0MZmRkEBoa6uswRCq80NDQMh1qLSIiIiJnr0ong4B6BEW8QPeRiIiISMVT5ZNBERERERGRqkjJoIiIiIiISBVU5smgYRj9DcP4zTCMvYZhmIZhjPDgNYZhGI8ahrHBMIw0wzD2G4bxehmEKy5xcXF06tSJwMBABg4c6NFrJk6cSEBA7oK1cXFxGIbBnj17SilKERERERHxlC96BiOANcAjQIqHr3kbuB94CmgPXArMLZXoKogRI0ZgGAaGYRAQEECzZs249957OXr06FmdNyAggIkTJ56y/b777qNbt25s27aNn3/++YzO3adPH/bv30/Dhg3PKkYRERERkfJk19GT7Dp60tdhlFiZ1xk0TXMqMBXAMIyJpzveMIy2wENAZ9M081ZqX1EqAVYgNpuN77//nszMTJYtW8Zdd93F7t27+f3330t8rvT0dIKCgorcv3nzZp555hmaNGlyxvEGBQURFRV1xq8XERERESmPnv9tDX9vOcpIW3MeGNSKiOCKUc69IswZvBLYBlxiGMY2wzB2GIbxuWEY9X0dmK/lJFeNGzfmyiuv5NFHH+WPP/4gJSWF//73v7Ro0YKgoCBatmzJmDFj8r02OjqaZ599lvvvv586depgs9mIjo4mKyuLO+64w93rmDO0Mysri9tuuw3DMNw9hwsXLqR///6EhoZSq1Ytbr755mJrzRU2TLSk5xARERERKU9mbzxE3MbDpGdl8/Gcrew8muzrkDxWEVLWFkAz4EZgBGAC/wWmGIZxvmma2XkPNgxjFDAKIDIykri4uCJPXKNGDRITE93tc17x7cjT1f/u7/GxGRkZZGVl5Yvfz8+P7Oxs3n33XUaPHs0bb7yBzWZjzpw5/N///R+BgYHcdtttAJimybvvvssDDzzAn3/+SVZWFnXr1qV169a88sorXHPNNQDUqlWLzZs307p1a/773/9y5ZVXUr16dbZs2cJFF13ExRdfzOzZs0lISCAmJoarr76aP/74A4DU1FQAd4wnT1pd50lJSSQmJnLw4MHTnkMqjtTU1GLvt7KWlJRUruIRqWx0j4mUPt1n5V9mtslz83NnvtkaBXB40wriNvkwqBKoCMmgHxAM3Gqa5iYAwzBuBTYC5wGL8h5smuY4YBxAjx49zOIWO1m/fj3VqlUrnajPQEliCQwMxN/f3/2adevW8cknn9CrVy/ef/99HnroIR5++GEAunbtys6dO3n77bd54IEHAKsu3Hnnncdrr712yrkjIyNp1aqVu12nTp1Ttr/33ntUr16dr776yj289KuvvqJLly6sWLGC/v37ExISku99hYWFARAREUG1atV48803T3sOqThCQkLo2rWrr8Nwi4uL83ixIxEpOd1jIqVP91n599n87exPXgdARHAAb98+kHrVgn0clecqwjDR/UBmTiLoshnIApr6JqTyIS4ujoiICEJDQ+nUqRMtWrRg3Lhx7Nmz55REasCAAezYscPdOwfQs2fPM7722rVr6d27d755hueeey41atRg7dq1ZXYOERERERFfOJ6czpi/NrvbD17QqkIlglAxegbnAwGGYbQ0TXOra1sLwB/Y6c0L7Xj9Mm+erkiJiYle6ZHs1asXn3/+OQEBATRs2JCgoCASEhI8fn14ePhZxyAiIiIiUhWN+WsTJ1IyAGhWJ4w7+kb7NqAz4Is6gxGGYXQxDKOL6/pNXe2mrv2vGYYxM89L/gKWAxMMw+hqGEZXYALW8NClZRx+uRIaGkqrVq2Ijo52965Vr16dxo0bM3du/vmPc+bMoXnz5u6hmkUJCgoiKyvrtNfu2LEjCxcuJD093b1t1apVnDhxgk6dOnkUvzfOISIiIiJS1jYdTOTLRbvc7WcubU9wgL8PIzozvhgm2gOrLMQKIBR40fX8Jdf+BkDLnINdC8TYgUNYtQWnA3uAKwsuHiOWp59+mvfee4/x48ezefNmxo4dy0cffcQzzzxz2tc2b96c2bNns2/fPo4cOVLkcQ8++CAJCQmMGDGCNWvWMG/ePG699VZsNhs2m82jOL1xDhERERGRsmSaJi871pGVbQJwfos6XNQh0sdRnRlf1BmMA4xi9o8oZNt+4LrSi6pyue+++0hOTubVV1/l/vvvp0mTJrz++uuMHDnytK99++23eeyxx4iOjiYjIwPTNAs9LjIykhkzZvDkk09y3nnnERwczKWXXnpKCYvieOMcIiIiIiJlafbGQzg3W50mfgY8f3kHDKPI9KZcM4r6sF8Z9OjRw1y6tOiRpOvXr6d9+/ZlGJHFW3MGRcoTX91PRdEKbCKlS/eYSOnTfVb+pGdmc8mYuWw7YtUSvLlXU169+hwfR1U8wzCWmabZo7B9FWE1UREREREREZ/7YuFOdyJYLTiAmAvb+Diis6NkUERERERE5DSOJafzzl+51e4eHtyauhEVq5REQUoGRURERERETiP2z40kpGYCEF0njNv7RPs2IC9QMigiIiIiIlKMjQcS+TpPKYl/X9aBoICKn0pV/HcgIiIiIiJSSnJKSbgqSdCvVV2GtK/v26C8RMmgiIiIiIhIEWauP8S8LbmlJJ61t6+wpSQKUjIoIiIiIiJSiPTMbF6Zut7dvrlXU9pFVfdhRN6lZFBERERERKQQn/+9g+05pSRCAnhsSMUuJVGQkkEREREREZECjial8e7Mze72I4NbU6eCl5IoSMmgVAgjRoxgyJAhPrt+XFwchmGwZ88en8UAsGPHDgzDYN68ecUeFx0dzX/+8x+Pz1vS40VEREQqu7f/3ERimlVKokXdcG47P9q3AZUCJYMVkGEYxT6io6MBOHr0KE8++SRt27YlJCSE+vXr079/fyZNmkRmpvWHPWLEiHyvrVGjBueffz5Tp071OJ6hQ4fi7+/P77//fsq+iRMnEhAQUOzrC8aQ84iIiPD8l3IGWrVqxejRoz06tk+fPuzfv5+GDRue0bWuvPJKevbsWei+1NRUateuzbPPPntG5y7MkiVLeOyxx7x2PhEREZGqZP3+BL5dnLeURPtKUUqioMr3jqqA/fv3ux8//fQTAMuXL3dvW7JkCbt376Zbt2789NNPPP/88yxfvpz58+czcuRI/vvf/7JmzRr3+Ww2m/u1CxcupFu3blx11VVs3br1tLHs2LGDuLg4nnjiCcaNG3fG7ylvDDmPbdu2nfH5vCkjI4OgoCCioqLw8zuzW2bUqFEsWbKEVatWnbLvp59+4sSJE9x1111nG6pbvXr1CA8P99r5RERERKqKgqUkbK3rckG7ylFKoiAlgxVQVFSU+1G7dm3A+vCfs61evXrcf//9pKWlsXz5coYPH06HDh1o3bo1t99+O8uWLaN169bu8+UkOlFRUbRv357XX3+djIwM/vnnn9PG8sknn3DppZfyyCOPMH36dPbu3XtG7ylvDDmP+vWLv+m+/fZbunTpQkhICNHR0cTExJCcnJzvmA8++IAOHToQHBxM/fr1ueaaawAYOHAgW7du5cUXX3T3ROYktoZh8Pvvv9OvXz9CQkL45JNPCh0munXrVq699lpq165NWFgYnTt3xuFwFBrr0KFDadq0KePHjz9l3/jx47nooouIjo4mKSmJRx55hEaNGhEWFkbXrl35+eefT3nNvn37sNvthIWF0aJFCyZOnJhvf8Fhn5mZmbz44ou0bNmS4OBgGjVqxEMPPVTk7zYjI4PRo0fTvHlzQkJC6NixI2PHji3yeBEREZHKYsa6g/y99SgA/n4Gz9k7VJpSEgUVP36vqhldo0wuU63I65/wyvmPHTvG1KlTefHFF6lR49T3FBgYSGBgYKGvTU9PZ/z48QQHB9OtW7dir5OZmcmECRMYO3YsDRs2ZNCgQXz66ac8//zzXnkfxZk4cSKPPfYY7777Ln379mXPnj08+OCDHD58mC+++AKAF154gbfffpvXX3+diy66iKSkJKZNmwbAzz//TPfu3bnmmmt44oknACuh3rFjBwCPP/44b731Fp06dSIwMJAtW7bku/6BAwfo06cP55xzDr/99hsNGjRgzZo1RfYc+vn5MXLkSP73v//x1ltvERoaCsDmzZuZM2cOP//8M6Zpcvnll2OaJt999x0NGzbkr7/+4sYbb2TatGkMHjzYfb7/+7//4/XXX2fMmDFMmDCBu+66iz59+tCmTeErXI0cOZJp06bx9ttv06dPHw4fPsyCBQuK/P3efffdLF++nLFjx9K6dWsWL17MPffcQ0BAACNHjvTgX0hERESk4knLzOLVPKUkhvdqSpvIIj+9V3hKBiuhLVu2kJ2dTYcOHTw6Pi4uzj0/7+TJk4SFhfH111/TrFmzYl83ZcoUsrOzGTp0KAC33347Tz31FM8++2yJh1PmjSHHoEGDmDJlSqHHjx49mtdee41bb70VgBYtWvD+++8zYMAA3n33XYKCgnjzzTd5+eWXefDBB92vy0lwa9eujb+/PxEREURFRZ1y/n//+99cfvnl7nbBZPCDDz7AMAwmT57sHo7ZsmXLYt/jyJEjeemll/jhhx+47bbbAKtntUGDBlx++eXMmTOHBQsWcPDgQXcSP2rUKBYuXMh7772XLxl88MEHuf766wF4+eWXee+995g9e3ahyeCWLVuYNGkSP/zwA9dee6071t69exca5/bt25k0aRLr1q2jXbt2ADRv3pyNGzfy3nvvKRkUERGRSmvi/B3sPHoSgOqVsJREQUoGKyHTNEt0fK9evfj8888BSEhI4LvvvuO2226jadOm9OjRo8jXjRs3juHDh7sXiLnqqqu49957mTZtGpdddtkZx5AjLCys0GMPHz7Mzp07iYmJcffqQe773rJlC6ZpkpqaykUXXVSiOHIUtdhLjmXLltGnT58Szctr1KgRl112GePHj+e2224jIyODiRMncvfddxMQEMCSJUtIT0+nUaNG+V6Xnp6eb1gvQJcuXdzP/f39qV+/PgcPHiz0usuXLwfw+HexdOlSTNM85d8+MzMTf39/j84hIiIiUtEcTkzjvVm5HQCPDmlDrfAgH0ZU+pQM5uWlYZqnk5iYSLVqpdfd3Lp1a/z8/Fi3bh3Dhg077fGhoaG0atXK3e7WrRuTJ09mzJgxfPnll4W+ZseOHcyYMYMZM2bwzjvvuLdnZWUxbty4EieDBWMoTnZ2NgDvvPMOgwYNOmV/48aNPZrvWJzSWnxl1KhR2O121q9fz7p16zhy5Ih74Zjs7Gxq1KjBkiVLTnldUFBQsW3DMNy/l7OVc56///77lIS8so6XFxEREYn9cyNJrlISLeuFc+v5xY+SqwyUDFZCtWvXZujQobz//vs89NBDp8wbzMjIID09vdiEx9/fn5SUlCL3f/LJJ7Rv355vv/023/a1a9cyfPhw9u7de0oPl7dERkbSpEkTNm7cyN13313oMR06dCAkJIQZM2bQuXPnQo8JCgoiKyvrjGLo3r0748ePJzk5uUSJY96FZNavX+9eOAagR48exMfHk5qaSqdOnc4orsLkDI2dMWOGe5hocbp37w7Arl27sNvtXotDREREpLxau+8E3y7Z7W4/a+9AoH/lX2uz8r/DKurDDz8kMDCQ7t278/XXX7Nu3Tq2bNnCl19+SY8ePdi8ebP72PT0dA4cOMCBAwfYvHkzL7/8MuvWrePqq68u9Nw5C8fccMMNdOrUKd/j+uuvJyoqik8//bRE8eaNIe+jqCGvr7zyCu+++y6vvPIKa9asYePGjfz666/cc889AERERPD4448zevRoPvjgAzZt2sSqVat47bXX3Odo3rw58+fPZ9euXRw5cqREPWv3338/2dnZXHnllcyfP5/t27fjcDjcC9QUJWchmQkTJjBjxgxGjRrl3nfBBRcwZMgQhg0bxq+//sq2bdtYtmwZ7733XqGrkHqqVatWDB8+nPvvv58vv/ySrVu3smTJknw9ugWPv/POO7n77rv54osv2LJlC6tWrWLChAm88cYbZxyHiIiISHlkmiYvTVlHzsfOAW3qMaht5SwlUZCSwUqqadOmLF++nKuuuorRo0fTrVs3+vTpw/jx4/nXv/6Vr+fJ6XTSoEEDGjRo4K5NOH78eG655ZZCzz1lyhT279/vXsAkL8MwuO666/j0009LlFzljSHv4+jRo4Uef+utt/L999/jcDjo2bMn5513HqNHj87XG/nyyy+7k8ZOnTpx0UUXuefPAbz44ovEx8fTtm1b6tWrx65duwq7VKEaNGjAvHnzqFatGpdeeikdO3bk3//+t0fzNUeOHElSUhKRkZH5FqkxDIPffvuNYcOG8dhjj9GuXTsuu+wyfv/999MuTnM6n332Gffccw/PPvss7du35+qrr2b79u1FHj9u3Dgee+wxXnnlFTp06MDgwYP5/PPPadGixVnFISIiIlLeTF97gEXbjwE5pSTa+ziismOUdLGRiqRHjx7m0qVLi9y/fv162rcv+3/s0p4zKOILvrqfihIXF8fAgQN9HYZIpaV7TKT06T4rfakZWVz4vznsPmZNjxrRJ5rRV3T0cVTeZRjGMtM0C10VUj2DIiIiIiJSJX02f4c7EawZFsijQ1qf5hWVi5JBERERERGpcg4lpvL+rNx1NB4b0oaaYZW7lERBSgZFRERERKTKeXv6JpLTrZXlW9WP4OZeTX0cUdlTMigiIiIiIlXKmr0n+H5ZbimJ56pIKYmCqt47LqAyL6AjUlZ0H4mIiEhFUbCUxKC29RjQpp5vg/KRKp0MBgYGFltYXUQ8k5KSQmBgoK/DEBERETmtaWsOsHiHVUoiwM/gWXsHH0fkO1U6Gaxfvz579+7l5MmT6tkQOQOmaXLy5En27t1L/fpVoziriIiIVFypGVm8OnW9u33b+dG0rBfhw4h8K8DXAfhS9erVAdi3bx8ZGRlldt3U1FRCQkLK7HoipSkwMJDIyEj3/SQiIiJSXn06bzt7jlsjA2uFBfLI4KpVSqKgKp0MgpUQlvWH2Li4OLp27Vqm1xQRERERqcoOJaTywewt7nbMhW2oEVa1p7lU6WGiIiIiIiJSNbw5fSMnXaUk2kRGcFPPqldKoiAlgyIiIiIiUqmt3nOCH5ftcbefs3cgoAqWkihIvwEREREREam0TNPkxSlr3e0h7etja101S0kUpGRQREREREQqrd9X72fpzuMABPobPHNpex9HVH6UeTJoGEZ/wzB+Mwxjr2EYpmEYI05zfLTruIKPS8ooZBERERERqYBSM7J4beoGd/v286NpUYVLSRTki9VEI4A1wCTXw1OXAKvytI95MygREREREalcxs/dxt54q5RE7fAgHqripSQKKvNk0DTNqcBUAMMwJpbgpUdN0zxQKkGJiIiIiEilcjAhlQ/jtrrbMRe2oUZo1S4lUVBFqjP4s2EYIcBm4H+maf5Y2EGGYYwCRgFERkYSFxdXdhF6KCkpqVzGJVKZ6D4TKV26x0RKn+6zszP+nzRSMqxSEo0jDBqc3EZc3HYfR1W+VIRkMAl4ApgPZAJXAN8ZhnG7aZpfFjzYNM1xwDiAHj16mAMHDizDUD0TFxdHeYxLpDLRfSZSunSPiZQ+3WdnbtXueOb/Md/dfuPGnvRtVdeHEZVP5T4ZNE3zCPB2nk1LDcOoCzwJnJIMioiIiIhI1WWaJi851rnbF3aIVCJYhIpaWmIRoNmfIiIiIiKSz2+r9rEsTymJf6uURJEqajLYBdjv6yBERERERKT8SEnP4o1puaUk7ujbnOi64T6MqHwr82GihmFEAK1cTT+gqWEYXYBjpmnuMgzjNaCnaZqDXcffDmQAK4Bs4HLgAeCpso5dRERERETKr3Fzt7HvRCoAdcKDePCCVqd5RdXmizmDPYDZedovuh6fAyOABkDLAq95FmgGZAGbgDsLWzxGRERERESqpv0nUvh4Tm4piccvakv1EJWSKI4v6gzGAUYx+0cUaH+OlSiKiIiIiIgU6s0/NrpLSbRvUJ0bzmvi44jKv4o6Z1BERERERASA5buO88uKve72c/b2+PsV2f8kLkoGRURERESkwjJNk5em5JaSuLhjJH1aqpSEJ5QMioiIiIhIhTV55T5W7o4HIMjfj2dUSsJjSgZFRERERKRCOpmeyet5S0n0i6ZZHZWS8JSSQRERERERqZDGztnGgQSrlETdiGAeHKRSEiWhZFBERERERCqcffEpjJ2bW0riXxe3oZpKSZSIkkEREREREalw3vhjA6kZ2QB0aFCda7urlERJKRkUEREREZEKZdnO40xeuc/dfuHyDiolcQaUDIqIiIiISIWRnW3ykiO3lMSl50TRq0UdH0ZUcSkZFBERERGRCuO3VftYlVNKIsCPp4eqlMSZUjIoIiIiIiIVQmpGFm9N3+huj+zXnCa1w3wYUcWmZFBERERERCqESQt2sDc+BYDa4UHcN7CljyOq2JQMioiIiIhIuRd/Mp33Z21xtx8Z3JrqKiVxVpQMioiIiIhIufferC0kpGYCEF0njJt6NvVxRBWfkkERERERESnXdh09yaQFO9ztpy5pR1CAUpmzpd+giIiIiIiUa29O30BGlglA92a1uKRTlI8jqhyUDIqIiIiISLm1cnc8jn/2u9vPXNoOw1CBeW9QMigiIiIiIuWSaZq8OnW9uz20UxTdm9X2YUSVi5JBEREREREpl/5af4jF248BEOBn8OQl7XwcUeWiZFBERERERMqdzKxsXp+W2ys4vFdTmtcN92FElY+SQRERERERKXe+XbKbrYeTAagWHMDDg1v7OKLKR8mgiIiIiIiUK0lpmYz5a5O7fe/AltSJCPZhRB7YFgem6esoSkTJoIiIiIiIlCvj5m7jSFI6AA1qhDCyX3MfR1SMjBT47SGYdCX8/Z6voykRJYMiIiIiIlJuHExIZfzcbe52zIVtCAn092FExTi6FT65EJZPstp/jYbdS3waUkkE+DoAERERERGRHP/7cxMpGVkAtIuqxrBujX0cURHW/gKTH4L0xNxtHa+C+hVnxVMlgyIiIiIiUi5sOpjI90t3u9vPXNoef79yVmA+Mx1mPAuLx+Zu8w+CS16HHneCUc7iLYaSQRERERERKRden7aBbNcaLLbWdenfpp5vAyro+E748Q7Yuyx3W81mcP0kaNjFZ2GdKSWDIiIiIiLic39vPcKsDYcAq3Pt6aHtfRxRARv/gF/ugdT43G3t7HDlBxBa01dRnRUlgyIiIiIi4lPZ2SavTs0tMD+sa2M6NKzuw4jyyMqAWS/D/Hdyt/kFwIUvQe/7K9Sw0IKUDIqIiIiIiE/9tmofa/YmABAc4McTF7fxcUQuCfvgxzth14LcbdUbwXUToUlPn4XlLUoGRURERETEZ1Izsnhr+kZ3e2S/5jSoEerDiFy2zoKf7oaTR3K3tboQrh4L4XV8F5cXKRkUERERERGfmbRgB3vjUwCoHR7EvQNb+jag7CyY8ybMeQNwrWZj+MEFz0Lfx8Cv8pRqVzIoIiIiIiI+EX8ynfdnbXG3Hxncmuohgb4LKOkQ/HQXbJ+Tuy0iEq75FJrbfBdXKVEyKCIiIiIiPvHerC0kpGYCEF0njJt6NvVdMDvmW/MDkw7kbou2WYlgtUjfxVWKlAyKiIiIiEiZ23X0JJMW7HC3n7qkHUEBPhiCmZ0Nf78DM18GM8u10YD+T8DAp8HPv+xjKiNl/ts2DKO/YRi/GYax1zAM0zCMESV4bWvDMBINw0gqxRBFRERERKSUvTVjIxlZ1py87s1qcUmnqLIP4uQx+OZG+Gt0biIYWhuG/2jNEazEiSD4IBkEIoA1wCNAiqcvMgwjCPgWmFtKcYmIiIiISBlYtTueKav2udvPXNoOo6zr9e1ZCmP7w+bpudua9IJ7ndB6SNnG4iNlPkzUNM2pwFQAwzAmluClbwD/AHOAAd6PTERERERESptpmrySp8D80E5RdG9WuywDgEUfw4znIDsjd/v5D8KQ0eDvwwVsyliFmDNoGMZlgB3oClx7mmNHAaMAIiMjiYuLK/X4SiopKalcxiVSmeg+EyldusdESl9lvc9WHMpk8fY0APwNGFDrRJm9T//MZNpteI96R3KLyGcEhLOh3SMcDe4FzvllEkd5Ue6TQcMwGgLjgatN00w6XfexaZrjgHEAPXr0MAcOHFjqMZZUXFwc5TEukcpE95lI6dI9JlL6KuN9lpmVzctj5gJWMnhL72bceFmnsrn4/lXw/aNwfHvutgZdCLz+c86pFV02MZQz5T4ZBL4APjJNc5GvAxERERERkTP33dLdbD2cDEC14AAeHty69C9qmrBsIkx7CrLScrefdzdc/AoEBJd+DOVURUgGLwAGGIbxgqttAH6GYWQC97t6AkVEREREpBxLSsvkf39udrfvHdiSOhGlnIilJcHvMfDPd7nbgiLgineh0zWle+0KoCIkg+cUaF8J/BvoCewt+3BERERERKSkxs3dxpEkq2euQY0QRvZrXroXPLQBvr8NjmzM3Va/I1z/OdQtgx7JCqDMk0HDMCKAVq6mH9DUMIwuwDHTNHcZhvEa0NM0zcEApmmuKfD6HkB2we0iIiIiIlI+HUxIZfzcbe52zIVtCAksxRp+q74Fx2OQcTJ3W9dbYOhbEBRWetetYHzRM9gDmJ2n/aLr8TkwAmgAtCz7sEREREREpDSM+WsTKRlWUfd2UdUY1q1x6VwoIwWmPQnLJ+VuCwiFy96GrsNL55oVmC/qDMZhzfsrav+I07x+IjDRmzGJiIiIiEjp2HQwke+W7Ha3n7m0Pf5+pVBg/uhW+P52OLg6d1ud1nD9JIjs4P3rVQIVYc6giIiIiIhUUK9P20C2aT23ta5L/zb1vH+Rtb/A5IcgPTF3W6dr4fIxEFzN+9erJJQMioiIiIhIqfh76xFmbTgEgGHA00Pbe/cCmWkw4zlYPDZ3m38QXPI69LjTuqgUScmgiIiIiIh4XXa2yatT17vbw7o2pkPD6t67wPGd8MMI2Lc8d1utaLjuc2jYxXvXqcRKlAzaHDFRQFMgpOA+pz12rreCEhERERGRim3KP/tYszcBgOAAP564uI33Tr7xD/jlHkiNz93Wzg5XfgChNb13nUrOo2TQ5ohpBHwBDChktwGYQCmuDSsiIiIiIhVFakYWb/6RW99vZL/mNKgR6p2T71sJ3w2H7Eyr7RcAF74Mve/TsNAS8rRn8COs4u9PAquBtFKLSEREREREKrRJC3awNz4FgNrhQdw70IuV4/5+NzcRrN4IrpsITXp67/xViKfJoA142GmP/aI0gxERERERkYot/mQ678/a4m4/Mrg11UMCvXPyE3th3eTc9k3fQINzvXPuKsjPw+NSgEOlGYiIiIiIiFR878/aQkKq1XMXXSeMm3o29d7Jl3yS2yvYrK8SwbPkaTI4Hri1NAMREREREZGKbfexk0xasNPdfuqSdgQFeJpynEb6SVj2WW67933eOW8V5ukw0b3ArTZHzExgGnCs4AFOe+wEbwYmIiIiIiIVy5vTN5KelQ1A92a1uKRTlPdO/s93kHLcel6zKbS91HvnrqI8TQY/dv2MBgYVst8ElAyKiIiIiFRRq3bHM2XVPnf7mUvbYXhrdU/ThIUf5bZ73Qt+KmZwtjxNBpuXahQiIiIiIlJhmabJK3kKzA/tFEX3ZrW9d4Gts+CIq1RFUAR0vcV7567CTpsM2hwxQcCjwNdOe+ySUo9IREREREQqlJnrD7F4uzWTLMDP4MlL2nn3Anl7BbveAiE1vHv+Kuq0szmd9th04B7AS1UiRURERESkssjMyua1abm9gsN7NaV53XDvXeDwJtjyp6thQM9R3jt3Fefp0j4rsIrOi4iIiIiIuH23dDdbDycDUC04gIcHt/buBRaPzX3edijU8WIB+yrO02TwceAJmyPGbnPEeGkWqIiIiIiIVGRJaZn878/N7va9A1tSJyLYexdIOQ4rv85t97rXe+cWjxeQ+QGoAUwGMmyOmMNYK4jmMJ322GbeDk5EREREKp+T6ZkcSkijWZ0w7602KT4xbu42jiSlAdCgRggj+3l53cnlkyDjpPW8fkdo3t+756/iPE0GZ5I/+RMRERERKbGjSWlc+q6TgwlpdGlSkwcHtWJw+/pKCiugQwmpjJ+7zd2OubANIYFeLPeQlQmLxuW2e98H+jvxKo+SQac9dkQpxyEiIiIiVcCkBTs5mGD1JK3cHc9dk5bSLqoaDwxqxaXnNMDfTx/2K4r//bWJlIwsANpFVWNYt8bevcCGKZCwx3oeVgfOuc675xeP5wyKiIiIiJyV1Iwsvlq085TtGw4k8tA3KxgSO4fvl+wmPTPbB9FJSWw6mMh3S3a7289c2t77iXzechI9RkJgiHfPL571DNocMbed7hinPXbS2YcjIiIiIpXVb6v2cSQpHYCGNUK49JwGfLVol7t3afuRZJ786R/embmZewa04PoeTbw77FC85vVpG8h2TSKzta5L/zb1vHuBPctg9yLruV8gnDfSu+cXwPM5gxOL2J53HqGSQREREREplGmaTJi33d2+vU809wxoyf2DWjFh3nY+X7CDxNRMAPbGp/D85LW8O3MLd9uaM7x3MyKCPf3YKqXt761HmLXhEGBN4Xt6aHvvX2RRnl7BTtdAtSjvX0M8HibavJBHD+BFYDPQq1SiExEREZFKYcG2o2w4kAhAaKA/N57XFIDa4UE8cXFb5v/fBfzr4rbUDg9yv+ZIUhqvTdtA39dnMeavTcSfTPdJ7JIrO9vktakb3O1hXRvToWF1714kYT+s/SW33VvlJEqLpwvInDq4G3YCy111B2OAm70ZmIiIiIhUHhPm7XA/v7Z7Y2qEBebbXz0kkAcGteLOvs35ZvEuxs3dxoGEVABOpGQw5q/NjJ+7jVvOb8Zd/VpQr5oXa9mJx6b8s4/Ve08AEBzgxxMXt/H+RZZ8AtlWLzFNz4eGXb1/DQG8s4CME7jMC+cRERERkUpox5FkZm446G6P6Btd5LGhQf7c2a85c54cyGvDzqFp7TD3vuT0LMbO2Ua/N2bxwuQ17I1PKc2wpYDUjCze/GOjuz2yX3Ma1Aj17kUyUmDphNx27/u8e37JxxvJYG8gyQvnEREREZFKaOLfOzBdK01c0K4+LetFnPY1wQH+3NSzKbMeH8CYG7rQun7ua9Iys/l8wU4GvDmbf/2wim2H9VG0LExasMOdgNcOD+LegS29f5F/voeUY9bzGk2hrfqcSpOnq4k+X8jmIKATVq/g+94MSkREREQqhxMpGXy/NLcEwZ19m5fo9QH+flzVtRFXnNuQGesO8sHsLe5hipnZJj8s28NPy/dwWeeGPDCoJe2ivDx/TQCIP5nO+7O2uNuPDG5N9ZDAYl5xBkwzfzmJXqPAXwsHlSZPf7ujC9mWhjVv8BXgNW8FJCIiIiKVxw9Ld3My3Sod0SYygr6t6pzRefz8DC7pFMXFHSOZu/kIH8zawuIdVg9StglTVu1jyqp9DGkfyYMXtKJLk5reegsCvD9rCwmu1V6j64RxU8+m3r/Itjg4vN56HhgOXW/1/jUkH08XkFFxehEREREpkcysbD6bv8PdvrNvcwzj7AqTG4bBgDb1GNCmHou3H+P92VuYu+mwe/9f6w/y1/qD9GtVlwcGtaJ3i9pnfc3KLiU9i+Mn0zmWnJ77MzmdYyczXD/T+XNt7pzPpy5pR1BAKaQHeXsFuw6H0Jrev4bk4+kw0f7Acqc99pQB2TZHTATQzWmPnevt4ERERESk4vpz3cF8c8yu6trIq+fv2bw2k5r35J898XwwewvT8yQs87YcYd6WI3RvVosHB7ViYNt6VSIpTMvMIv5kRp6EzvUzOaPQhO/4yQxSMrI8Pn/3ZrW4pFMp1Pw7uhU2T89t91I5ibLg6TDR2cD5wOJC9rV17ff3VlAiIiIiUvFNmJ9bZH54r6aEBJbOx8XOjWsy9tYebDqYyIezt/Dbqn1kuxasWbbzOHdMXEKHBtV5YFArLukUhb9fxUgKs7JNjiSluZK5nCQuo0DvXd6fGSSlZZZaPMEBfrxweYfSSaoXfZz7vPXFUKcUFqeRU3iaDBb3Lx4MeP51goiIiIhUev/siWfJjuMABPob3NK7Walfs01kNcbc2JXHLmzDx3O28uOyPWRkWVnhuv0JPPD1clrWC+e+ga24sktDAv3LdiaUaZokpGRyJDmNo0npHE1K40iy9fNoUjpHcn669p9IyYAZf5V6XEH+ftQKD6RWWBC1w4OoFR5E7bCcn4HWz/Ag2kVVL536jinxsOKr3LbKSZSZIpNBmyMmGmiRZ1MP15DQvEKBO4Fd3g9NRERERCqqCfNyewXtnRsSWT2kzK7drE44rw3rzMODWzNu7ja+WbyL1IxsALYeTuaJH1Yx5q9N3DugJdd2b3xWPZapGVkcLZjQJadzJNH107X9aHIax5LT3clpafH3M6gVZiV2+ZK6QpK9nOfhQf6+HUK74gvISLae12sPLQb6LpYqpriewduBFwDT9XiP/D2EpqudCTxQWgGKiIiISMVyMCEVxz/73e2SlpPwlgY1Qnnh8o48MKgVE+Zt54sFO0l0DaPcczyFZ39dw7szNzOqfwtu7tWUsKAAsrJN4k+muxO5I0m5id7R5Dzt5HSOJqWX6rBMgJphge6EzkrmAgv03AW5e+5qhwVRLSQAvwoyDBaArExYNC633fs+qAJzO8uL4pLBiUAcVsI3CyvhW1fgmDRgk9Mee8zTCxqG0R94AugONATuME1zYjHHdwA+ADoANYB9wLfAaNM00z29roiIiIiUjS8W7CTTNWmvZ3Rtzmlcw6fx1I0I5slL2nHPgJZM+nsHE+Zv5/jJDAAOJabxn9/X885fmwkO9ONYcrp7vmFpiAgOoE5EEHXCg6gTEUzdiCDqhAdb2yKCqevaXjs8iH+W/M3gCwaVXjDlwcbf4YRrkGFobeh8vW/jqWKKTAad9tidWHUEsTliBmGtJprohWtGAGuASa7H6aQDnwMrgHjgXGA8VuxPeiEeEREREfGS1Iwsvlq0092+s1+074IpoEZoIA8Nbs2d/ZrzzeJdjJu7jUOJaQAkpmXieloiAX6GK7mzErq6EcH5Er26EbmJXp3woBINSa0oC92clbzlJHrcCYGhvoulCvK0zuAcAJsjpjPQH6gDjHXaYw/YHDGtgIOeJoqmaU4FpgIYhjHRg+O3AFvybNppGMZAwObJ9URERESk7PyyYq+7161xrVAu7FAKZQjOUnhwAHfZWnBL72b8uGwPH8/Zyp7jKe79NcMCT9tzVyciiLrhwVQPDagSJStKxb4VsGuB9dwvAM67y7fxVEGe1hkMBr4EhmENGzWBKcAB4E1gE/B/pRRjPoZhtAIuAX4ri+uJiIiIiGdM08y3cMyIPtHluncrJNCfW3o346aeTdl97CShQf7UCgsqnYLqcqqFecpJdBwG1Rv4LpYqytPSEq8AQ4BbgT+Bg3n2TQPup5STQcMw/ga6YZWyGA88U8Rxo4BRAJGRkcTFxZVmWGckKSmpXMYlUpnoPhMpXbrHpDBrjmSx+VAqACH+0DB1J3FxWnT+TFXm+ywo7Ri9V/9ITtq9LLAniZX0vZZnniaDNwHPOu2xX9scMQUHOm8Hor0aVeFuAKphzRl8C3gKeK3gQaZpjgPGAfTo0cMcOHBgGYRWMnFxcZTHuEQqE91nIqVL95gUZuJniwErGbyxVzSXXtjRtwFVcJX6Ppv1CpiulVib9KL7FXf7Np4qytNksA6wvoh9fli9daXKNM3drqfrDMPwBz4xDOMt0zRLdz1fERERETmtLYeSiNt4GLAqA9zRN9q3AUn5lZEKSz/NbavIvM94OiB6O3B+Eft6Ahu9E47H/LAS2TOvECoiIiIiXjPx79y5gkPaR9KsTrgPo5FybfUPcPKo9bx6Y2h3uW/jqcI87RmcBDxjc8TsAH5ybTNdJSceA0Z7ekHDMCKAVq6mH9DUMIwuwDHTNHcZhvEa0NM0zcGu42/FGm+wGqvMRA+s4aE/mqZ5BgsAi4iIiIg3xZ9M56dle91tXxWZlwrANPOXk+g1Cvw9TUnE2zz9zb+JNVfvC+AT17Z5QAjwrdMe+14JrtkDmJ2n/aLr8TkwAmgAtMyzPxN4GmiNtZLpTqwi9P8rwTVFREREpJR8s3g3KRlZALRvUJ3eLWr7OCIpt7bPhUNrreeBYdDtNt/GU8V5WmcwC7jR5oj5ALgYqA8cBf7IqUHoKdM047CSuqL2jyjQ/gb4piTXEBEREZGykZGVzaQFO9ztO/tGq+6eFG1RnnISXW6G0Fq+i0U87hkEwGmPdQLOvNtsjpgo4CmnPfYxbwYmIiIiIuXfH2sOsP+EtYJo3YggrujS0McRSbl1dCtsnJbb7nWv72IRwINk0OaIqQ80BXY47bFH8mxvhFVbcCQQiDV3UERERESqkAnzcxeOuaV3M4IDtL6fFGHxOMC0nre6EOq29mk4UsxqojZHTE2bI2YysB9YBOyzOWLecO17DtiEVWzeAZxTBrGKiIiISDmyfNdxVuyKByDI34/hvZr5NiApv1JPwIovc9sqJ1EuFNcz+ApwKfApsBxoDtxrc8S0B+xAHPCY0x67qrSDFBEREZHyZ8K83F7BK7o0pF61Ui89LRXVii8hPcl6XrcttLzAt/EIUHwyaAded9pjn8vZYHPELAB+xlpB9ObSDk5EREREyqd98SlMW3PA3VY5CSlSdlb+hWN63wdaZKhcKK7ofENgZoFtf7l+ji+dcERERESkIpi0YCdZ2db8r/Nb1KFDw+o+jkjKrY1TIX6X9Ty0FnS+wbfxiFtxyaA/cLLAthTXzxOlE46IiIiIlHcn0zP5ZvEud/vOfuoVlGLkLTLf/Q4ICvNdLJLP6VYT7WFzxETkafthLQF0ns0RUzPvgU577CwvxyYiIiIi5dBPy/dyIiUDgGZ1wrigXX0fRyTl1v5VsHO+9dwvAM67y7fxSD6nSwbfo/AC8Tnpvenab2L1JIqIiIhIJZadbfJZnnISd/SJxt9P87+kCAvzzBXscBXUaOSzUORUxSWDg8osChERERGpEOZsPsy2w8kAVAsO4NoeTXwckZRbiQdhzY+5bZWTKHeKTAad9tg5ZRmIiIiIiJR/ectJ3HBeEyKCTzfQTKqspRMgK9163vg8aNzDt/HIKYpbQEZERERExG3TwUScm48A4GfA7X2ifRuQlF8ZqbD009y2egXLJSWDIiIiIuKRvHMFL+4YRZPaWhVSirDmJ0g+bD2v3gjaX+HbeKRQSgZFRERE5LSOJafz8/K97rbKSUiRTDN/OYmed4N/oO/ikSIpGRQRERGR0/p60U7SMrMBOKdRDXo0q+XjiKTc2jEPDq62ngeEQrfbfRuPFEnJoIiIiIgUKz0zm0kLdrrbI/s1xzBUTkKKsChPOYkuN0FYbd/FIsVSMigiIiIixZq6ej+HEtMAqF8tmEvPaeDjiKTcOrYdNvye2+51r+9ikdMqci1gmyPm+RKcx3TaY1/2QjwiIiIiUo6YpsmEPAvH3HZ+M4ICKll/QkYq7FsBDbtAYKivo6nYFo8DTOt5y8FQr61Pw5HiFVcYZnSBtgkUNh7A9a+NkkERERGRSmbpzuP8s+cEAMEBftzcq5mPI/Kyo1vhi6shfifUaAJXfgAtBvg6qoopNQGWf5Hb7n2/72IRjxT5tY7THuuX8wA6AduB/wOigVDXz6dd2zuWeqQiIiIiUubyFpkf1q0RtcODfBiNl+1fBRMuthJBgBO7YdIVMPVJSD/p29gqopVfQXqi9bxuG2h5gW/jkdMqrmcwr/eBT5z22DfzbNsFvGFzxPgBHwCDvR2ciIiIiPjO7mMnmb72gLt9R99KVE5ix3z45kZISzh13+KxsHUmXPUxNDmv7GOriLKz8i8c0+te8Ktkw4krIU//hXoBS4vYtwTo7Z1wRERERKS8+PzvHWS7JgTZWtelTWQ13wbkLRunwZfDchPBkBpww1fQ5pLcY45ugQkXwcyXIDPdN3FWJJv+gOM7rOchNeHcG30ZjXjI02TwBHBhEfsucu0XERERkUoiKS2T75bsdrfvrCy9giu/gW+HQ2aq1Y6IhBFTob0dbvoWrngfglxJr5kNzrdh/CA4sNp3MVcEeYvMdx8BQeE+C0U85+kw0QnA0zZHTATwA3AQiASuB0YBr5ZOeCIiIiLiCz8u3U1iWiYALeqFM6BNPR9H5AULPoTpT+e2a0XDrb9A7RZW2zCg263WAjK/3g87nNb2g2tg3CAY+H/Q91Hw9/QjdBVxYHXu78rwh553+zYe8ZinPYPPYyV8twEzgTXALOBW1/bRpRGciIiIiJS97GyTz/7e4W7f0bc5fn4VuMi8acKs/+RPBOt3hDun5yaCedVsCrf9Bpe8AQEh1rbsDJj1Mnx2CRzZUjZxVxQL88wV7HAl1Gjsu1ikRDz6WsNpj80GnrM5Yt4GOgNRwH7gH6c9VkNERURERCqRmRsOsfOotZpm9ZAArunWyMcRnYXsLJj6BCydkLutSW+4+VsIrVX06/z8oPe90Gow/HIv7HUtn7FnCXzcDy58Ec67W4ukJB2G1d/ntnvf57tYpMRK1MfttMfGA3NLJxQRERERKQ/ylpO4qVdTwoIq6LDIzHT45R5Y+3PutlYXwvWTICjMs3PUbW31IM4fA3GvWz2EmSkw7UnY4LDqEtZsWirhVwhLJ0CWa4GdRt2hsVZfrUg8vrNtjphGwONAf6A2cIXTHrvG5oh5FFjgtMcuKp0QRURERKSsrNuXwIJtRwHw9zO4/fxo3wZ0ptKT4btbYOus3G3nXAdXfQT+gSU7l38A9H8C2lwMP98Dh9Za27fPhQ/7wNDXoctwa85hVZKZBks+yW33vr/q/Q4qOI/6tW2OmI7Aaqw5gvuAZkBOxdFmwCOlEp2IiIiIlKnP5uf2Cg7tFEXDmqE+jOYMnTwGk67Mnwj2HAVXjyt5IphX1Dkwajb0iwHD9TE6PREmPwDf3ASJB88u7opmzc+QfMh6Xq2BNV9QKhRPBzm/DawHmgPDgLwp/9+ozqCIiIhIhXc4MY3JK/e523f2q4DlJBL2wWeXWnP7cgx8Goa+6Z35fQHBMOSFUxef2TQNPuwNa385+2tUBKYJCz/Mbfe8++wSbfEJT++IfsDrTntsEmAW2HcQa0EZEREREanAvlq0k/SsbAC6NKlJt6bFLLBSHh3dChMuhsPrc7cNfcsqCeHt4YtNesK986wexxwpx+CHEfDjSKt3sjLbtQAO/GM9DwiB7nf4Nh45I54mg9nF7KsLpHghFhERERHxkbTMLL5cuNPdHlnRegX3r7ISwfhdVtsvAIZ9Ar1GFf+6sxEUDpe+Bbf+CtXzlFNY8yN8eD5s/rP0ru1reXsFz70Rwmr7LhY5Y54mg4uBotL964H53glHRERERHxhyqr9HEmyVoVsUCOESzpVoIFfO+bDRDskH7baAaFw4zfQ+bqyuX7LQXD/33Duzbnbkg7AV9fCbw9DWmLZxFFWju+ADb/ntnvd67NQ5Ox4mgy+DFxuc8TMwFpExgSG2BwxnwNXA6+UUnwiIiIiUspM0+TTPOUkbjs/mkD/ClI/b+M0+HIYpCVY7ZAacNuv0Oaiso0jpAZc/RHc+DWE18vdvvxz+KivlbBWFovHg+kaONhiENRv79t45Ix5dJc77bFzgKuwFpCZgLWAzOuADbhKZSVEREREKq6F246xfr+VTIUG+nNTzyY+jshDK7+Bb4dDZqrVjoiEEVOhqQ/XNmx3Gdy/ENpfkbstfidMvAz+eAYyKvjsqrREWD4pt937ft/FImfN4698nPbY35322NZAG6wFZdo77bEtnPbYaSW5oGEY/Q3D+M0wjL2GYZiGYYw4zfEDDcOYbBjGfsMwThqG8Y9hGHeW5JoiIiIiUrQJecpJXNO9ETXDgoo5upxY8CH8ei+YWVa7VrS1wmdUJ5+GBUB4Xauw/bDxVo8hACYs/ADGDoC9y30a3llZ+XVuL2ydVtBqiG/jkbPiUdF5myPmeeATpz12n9MeuwXYkmdfA+Bupz32JQ+vGQGsASa5HqfTB6vG4ZvAfuBiYJxhGKmmaX7t4TVFREREpBA7jybz1/rc+ngj+pTzhWNME2a/AnPfyt1WvyPc+jNUK0fzHA0DOl8P0f1g8oOwdaa1/chG+GSIVcS+/78qVjmG7GxY9HFuu9e93inXIT7j6b/eC0DjIvY1dO33iGmaU03TfMY0zR8pfpXSnONfNU3zWdM055umuc00zY+An4FrPL2miIiIiBTus/k7MF2Fwwa2rUer+hG+Dag42Vnwe0z+RLBJb7jj9/KVCOZVvSHc8hPY/weB4dY2MwvmvAHjL4CD63wbX0lsngHHtlnPQ2rAuTf5Nh45a54mg8UVZqkFpHkhlpKoDhwv42uKiIiIVCoJqRn8sHS3u31n33LcK5iZDj/dBUsn5G5rfRHc+guElvN6iIYBPe6E++ZB0/Nztx/4B8YNgPnvWIlueZe3nES32yG4HH9xIB4xTLNgDXmLzREzELjA1XwW+AzYW+CwUOAyINlpjz2vxBc3jCTgQdM0J5bgNXbgF6CvaZqLC9k/ChgFEBkZ2f3bb78taVilLikpiYgI3TwipUn3mUjp0j1WOUzfkcE3G6xyEg0jDF7pG4rh7eLsXuCXlUqnNa9R+/hK97aD9fuzod0jmH4ezXoqP8wsGu+ZQottX+JnZrg3x9fowIZ2D5Ma2sC9rTzdZ+FJOzhv6SMAmPixsPc40kLqneZVUh4MGjRomWmaPQrbV9zdMwArCQSrlERhdQbTgXXAw2cVoYcMw+gLfA08XFgiCGCa5jhgHECPHj3MgQMHlkVoJRIXF0d5jEukMtF9JlK6dI9VfFnZJs8umu1uP3RRJwb1bOrDiIpw8hh8fT3kSQTpOYrIS94gssLOVxsMh+6BX+6B/asAqHliHb2Xx8BFL0OPkWAY5es+m/yg+6nR4XLOv6SMajhKqSoyGXTaY18EXgSwOWKygd5Oe2yhCVhZMAyjHzAVeN41b1BEREREztCf6w6w57hV5qBWWCBXd23k44gKkbAPvhgGh9fnbhv4DAx40hp6WZHVbw93zYS5/7XmQJpZkHESfn/cKuh+xftnf43sLMhMg6z03EdmGmRlQJbrZ5H7825LhX++zz2vyklUGh71qzvtsT792sUwjP7A78ALpmmO8WUsIiIiIpXBhHk73M9v7tWUkEB/3wVTmKNb4YurIH5X7rahb0GvUT4Lyev8A2HQ09D2EvjlXji8wdq+dRZ8eD5ta/WAY98Uk7jlPM+7PyfRS88tDO9NDbtCk17eP6/4RIkHWdscMfWBkILbnfbYXYUcfgrDMCKAVq6mH9DUMIwuwDHTNHcZhvEa0NM0zcGu4wdiJYIfAl8bhpGzVFSWaZqHSxq/iIiUL45/9jHp7530alGbBwa1Kn8fSEUqodV7TrB4xzEAAvwMbjs/2rcBFbR/FXx5DSS7Pur5BcBVH0PnSjo0sWFXGDUHZr0MCz4ATEg7QYMDM+GAr4MroN9jFb9XVtw8rTPoB/wHuAeoWcRhnv7fuwcwO087Zzjq58AIoAHQMs/+EUAY8ITrkWMnEO3hNUVEpBwaO2crr02zvglfvOMYv6/ez3+vO5duTcv5yoAiFdxneYrM2zs3ILL6Kd/z+86O+fDNjbmFzQNC4YYvoPWFvo2rtAWGwMWvQNtL4df7IH6nF05qQEAw+AflPgJyngdbPZMBrp/+OccVsi3nNQ26QHu7F+KS8sLTnsFHgQeAN7CSwlewagQOd/183dMLmqYZRzGlKkzTHFFIe0Rhx4qISMVkmiavT9vA2Lnb8m3fdjiZaz/6m7v7t+CxIW3USyhSCg4lpDLln33u9p39ylE5iY3T4IcR1hw1sGrZ3fw9NO3t07DKVHRfuH8BbJ7BxlVLaNvhnDwJWlDhSZo70SuY2FWwlValzHn6F3IH8BIwBisZ/MVpj11uc8T8B5gBlMOlp0REpDzKzMrmmV9W8/3SPe5tHRtWZ+fRkySlZZJtwtg525i5/hBvX3cu5zap6btgRSqhLxbuJCPLKi3Wo1ktOjeu6duAcqz8BiY/YC2kAhARCbf8DFGdfBuXLwSFQ8er2X+4Fm27DPR1NFKJebowTAtgqdMemwVkYtUXxGmPzcBKEO8slehERKRSSc3I4v6vludLBIe0j+Sn+/rwx6M2+raq496+5VASwz76m7embyAtswIUYxapAFIzsvhqUe4yDyPLS6/ggg/h13tzE8Fa0XDn9KqZCIqUIU+TwRPkLhqzD2ibZ18AUNubQYmISOWTmJrBiM8WM2PdQfe2a7s35uNbuhES6E/jWmF8ObIX/7mqE2FB1vDQrGyTD2Zv5Yr35rN6zwlfhS5SaUxeuZdjyVaR+UY1Q7mwQ6RvAzJNmPkyTH86d1v9jlYiWLucJKoilZinw0RXAB2A6a7HizZHTApWL+ErwPLSCU9ERCqDI0lp3D5hMWv3Jbi3jerfgqeHtsPIsyqdYRjc0rsZA9rU418/rmLhNmu1w40HE7nqw/k8MLAlD17QmqCAilpoWsR3TNPk03m5C8eM6BNNgL8P76XsLJj6BCydkLutSW+4+VsI1SJSImXB0/8CjAFOup6/gLXI7VfAd0Ag8KDXIxMRkUph97GTXPfxgnyJ4P8Nbcczl7bPlwjm1aR2GF/f1ZsXr+hIaGBuL+G7s7ZwxfvzWLtPvYQiJTV/y1E2HUwCIDzInxt6NvFdMJnp8NPI/Ilg64vg1l+UCIqUIY+SQac99k+nPXas6/kBoCfQBugCtHHaY/8ptQhFRKTC2nQwkWs//pvtR5IB8DPgjWvO4d4BLU/zSvDzM7i9TzR/PGqjZ3TubIQNBxK58v35jPlrExlZpVBQWaSSmpCnnMR1PZpQPSTQN4GkJcE3N8DaX3K3nXM93Pg1BIX5JiaRKuqM1pt12mNNYIuXYxERkUpk2c7j3DlxCSdSMgAI8vfj3Zu6ckmnqBKdp1mdcL4d1ZvPF+zgjT82kJqRTWa2yZi/NvPnuoP897pzad+gemm8BZFKY+vhJGZtOARY9cJv7xPtm0CSDsPX18G+Fbnbet4Dl7wOfhr+LVLWikwGbY6Y/iU5kdMeO/fswxERkcogbuMh7vtyOSkZ1sqAEcEBjLutO31a1j2j8/n5GdzRtzkD29bnXz+sYunO4wCs3ZfAFe/P45HBrbl3QEvfzn8SKccmzt/hfj64XX2a1w0v+yCObYMvhsHx3B5KBj4NA56yMlQRKXPF9QzGAaYH5zBcx6kysIiIMHnlXh7/fhWZ2db/QmqHB/H5HT05p3GNsz5387rhfHfP+Xw2fztvTd9IWmY2GVkm/52xielrrV7CtlHVzvo6IpXJiZMZ/Lgst5yLT4rM71sBX10HyYettuEHl70NPVSdTMSXiksGB5VZFCIiUilMWrCDF35bi+n6KrFRzVC+GNmTFvUivHYNfz+Du2wtGNSuPk/8sIoVu+IBWL33BJe/N49HhrTmnv4t1Eso4vLG9A3uXvp2UdU4v0Wd07zCy7bMhO9vg3Rr8RoCQuDaCdDusrKNQ0ROUWQy6LTHzinLQEREpOIyTZN3Zm5mzF+b3dta149g0sieNKgRWirXbFkvgh/v7cMnzm28/ecm0jOzSc/K5q3pG5mx9gBvX38ureqrl1Cqtu+X7ObrPEXm7xnQoshVfEvFqu9g8v2QnWm1Q2rCzd9B095lF4OIFElfm4qIyFnJzjYZ/dvafIlglyY1+f6e80stEczh72dwz4CW/P5QP87NMwx11Z4TXPruPMbO2UpWticzHkQqn1W743n21zXu9uXnNuSqLo3K5uKmCfPfhV9G5SaC1RtbxeSVCIqUGx6tJmpzxMw6zSGm0x472AvxiIhIBZKemc0TP6zit1X73Ntsrevy8S3dCQ8+owWrz0jryGr8dF8fxjm3MebPzaRnZZOemc1r0zbwx9oD/Pe6c2npxaGqIuXdkaQ07v1yGemu8ivtoqrxxjXnlE2vYHY2zHgWFn6Qu61+Bxj+I9Qoo2RURDziac+gH9ZCMXkfdYG+WPUGtQSUiEgVczI9k7snLc2XCNo7N+DT288r00QwR4C/H/cPbMWUh/pxTqPcXsIVu+K59B0nnzi3qZdQqoTMrGwe/Ho5+0+kAlA9JICxt3YnLKgM7svMNPj5rvyJYLO+cMc0JYIi5ZBH/1Vw2mMHFrbd5ohpCfwKvOq9kEREpLyLP5nOnROXsNy1eAvArb2bMfqKjvj7+fb7wbZR1fj5/j58HLeVd2dtJiPLJC0zm//8vp4/1hzgrevO9c2y+iJl5LVpG1i47RhgVWx456auNKtTBn/zqQnw3XDYnqfaWPsrYNh4CAwp/euLSImd1ZxBpz12K/A68JZ3whERkfLuwIlUrh+7IF8i+PDg1rx0pe8TwRyB/n48NLg1vz3Yjw55CtIv3Xmcoe/MZcK87WSrl1Aqockr9/LpvNw6fjFD2jCobf3Sv3DiAfjs0vyJ4Hl3w3UTlQiKlGPeWEDmMNZQURERqeS2H0nmmo/+ZtPBJPe20Zd3IObCNmW7QqGH2jeozuQH+/LokNYEuBLV1IxsXnKs48bxC9l5NNnHEYp4z7p9CTz10z/u9oUdInlgUKvSv/CRzfDphXBwde62C56DS98CP5WhFinPzioZtDli6gAxwFbvhCMiIuXVmr0nuPajv9kbnwJAgJ/BOzd2YURfHxSwLoFAfz8eHdKGXx/oS7s8BekXbz/GJWOcTFqwQ72EUuHFn0znni+XkpphLRjTol44sdefi19p99bvWQqfXgTxrvIVhj9c+QH0f8Iaoyoi5Zqnq4luBwr+nzIIiHQ9v8abQYmISPmyYOtR7p60lKQ0a4n4kEA/Prqle9kMP/OSTo1q8NuD/Xhv1mY+jLNKTqRkZPH85LVMXb2ft649lya1w3wdpkiJZWWbPPztSnYfs76oCQ/yZ9yt3akWEli6F940HX4YARknrXZgmDUstM3FpXtdEfEaT5eVmsOpyWAqsBP4wTV3UEREKqHpaw/w0DcrSM+0ehyqhwTw2R3n0b1ZbR9HVnJBAX48flFbLuwQyRM/rHIPd1247RgXj5nL05e2Z3jPpqXfmyLiRf/7cxNzNx12t9++vgut6lcr5hVesOJL+O1hMLOsdmhtGP4DNO5RutcVEa/ydDXREaUch4iIlEPfL93N//30DzmjKOtXC2bSyJ60i6pe/AvLuc6NazLloX6889dmPp6zlWwTTqZn8dyva/hjzX7euKYzjWupl1DKv+lrD/D+7C3u9gODWnJJp6jSu6BpgvO/MOs/udtqNoVbfoG6ZTA/UUS8yhsLyIiISCU0ds5WnvwxNxGMrhPGT/f1qfCJYI7gAH+evKQdP9/fl5b1cpfdn7/lKJeMcfLFwp1kuAp2i5RHWw4l8fj3q9zt/m3qEXNh29K7YHYWTH0ifyIYdQ6M/FOJoEgF5XH1UZsjpj1wLdAEKLhGsOm0x97uzcBERMQ3TNPk9T82MHbONve2Dg2q8/mdPalXLdiHkZWOLk1q8vvDNv731ybGz91GtglJaZk89+saxs7ZygODWnFNt8YEBej7Uyk/ElMzGPVF7jzeJrVDeffGLqVX3iUj1Somv35K7rbm/eGGryCkcnxBJFIVebqAzG3ABKx5g4eA9AKHaBk2EZFKIDMrm3//sobvlu52b+vZvDaf3N6D6qW9GIUPhQT68/TQ9lzUIYp//bCKbUeskhN7jqfw9M+reX/WFu4b2JLrejQmOEBL5YtvZWebPP79KrYdtv5OQwL9GHtLD2qGBZXOBVPi4dubYef83G2droGrPoKAyvcFkUhV4mnP4HPAZGCk0x4bX3rhiIiIr6RmZPHwNyuYse6ge9uQ9pG8f3NXQgKrRgLUvVktpj5i49N52/nEuY3jJzMA2BufwrO/ruGD2VZSeH2PJlXmdyLlz4dxW/Ldp29c05kODUupd+7EXvjqWji0Lndb7wfgov+An3rLRSo6T+/iKOBDJYIiIpVTYmoGIz5bnO8D5rXdG/PxLd2qXNITEujPA4NaMe+pC/i/oe2oE57b27L/RCrPT17LgLdmM3H+dlIzsnwYqVRFszce4u0/N7nbd/ZtzpVdGpXOxQ5tsIrJ500EL/oPXPKqEkGRSsLTO3k+0L40AxEREd84kpTGTeMXsnDbMfe2Uf1b8Na1nQnwr7of+MKDA7h3QEucTw3i35e2p25EblJ4MCGN0VPWYXtzNp/O205KupJCKX07jybzyDcrMF2Tc3o1r83Tl7YrnYvtWggTLoaEvVbbLwCGjYc+D5XO9UTEJzwdJvog8LPNEXMUmAEcL3iA0x6rJddERCqYPcdPcuuni9numiMH8H9D23HvgJY+jKp8CQsK4O7+LbildzO+XryLj+ds5XBiGgCHE9N42bGOj+K2ck//Fgzv3ZSwII/XZhPx2Mn0TO75YhkJqdaCMQ1qhPDB8G4ElsYXNusd8NNIyEy12kERcP0kaDXY+9cSEZ/y9L8ge4AVwJdYC8hkFHgUXFBGRETKuU0HE7nmo7/diaCfAa8PO0eJYBFCg/wZ2a85zicHMfryDkRWz10440hSGq9MXY/tjdl8PGcrya4VHkW8wTRNnvppNRsOJAIQ5O/HR7d0p25EKSzesnQCfH9rbiIYXg9GOJQIilRSnn59OR64AfgV2ICSPxGRCm3ZzuPcOXEJJ1KsBVKC/P1496YuXNKpgY8jK/9CAv0Z0bc5N/Zsyg9Ld/Nh3Fb2n7A+OB9NTuf1aRsYO2crd9lacNv5zahWiVdhlbLx6bztTFm1z91++aqOdGlS07sXMU2Iew3mvJG7rXYLuOUn66eIVEqeJoNXAv9y2mPfKc1gRESkdKWkZ/HH2v088/MaUlyLn0QEBzDutu70aVnXx9FVLCGB/tx6fjTXn9eEH5ft4cPZW9kbnwLA8ZMZvDV9I+PmbuOufs25vW90pS7NIaXn761HeG3aBnf75l5NueG8pt69SFYm/P4YLJ+Uu61hV7j5B4io591riUi54mkymAysO+1RIiJS7sSfTGfm+kNMX3uAuZsPk5qRO8W7dngQn9/Rk3Ma1/BhhBVbcIA/w3s147ruTfh5+R7en72FPcetpPBESgZv/7mJ8c5t3NmvOXf0aU6NMCWF4pm98Sk8+PUKsrKtFWO6Nq3JC5d38O5F0k/Cj3fCpmm521oOtuYIBkd491oiUu54mgx+BtwM/FmKsYiIiJfsP5HCjLUHmb72AIu2H3N/mMyrUc1QJo3sSct6+sDnDUEBftzYsynXdG/MLyv28sHsLew8ehKAhNRMxvy1mU+d2xnRN5qR/ZqXXoFwqRRSM7K478tlHEu2ZubUjQjm41u6ExzgxVIvJ4/B1zfAnsW52zrfCFe+D/760kKkKvA0GdwJ3GRzxPwJ/EHhq4lO8GZgIiJSMlsOJTLdlQD+s+dEkce1rh/BxR2jGNE3unQWoKjiAv39uL5HE4Z1bcTklft4f/YW9yI9iWmZvDdrCxPmbef2PtHcZWtB7XAlhZKfaZo8P3mN+z4O8DP4cHg3IquHeO8i8bvgy2vgSG7NQvo+CkNGg2F47zoiUq55mgx+5PrZDChsOSkTUDIoIlKGsrNNVu2JZ/rag8xYd4Bth5OLPLZr05pc3DGKizpE0kI9gWUiwN+Pa7o35souDZnyzz7em7XF/W+UnJ7Fh3Fbmfj3Dm49vxmjbC2oo8RcXL5atIvvl+5xt5+9rD09m9f23gUOrIGvroXE/a4NBlzyOvS+13vXEJEKwdNksLm3LmgYRn/gCaA70BC4wzTNicUcHwJ8DHTDKnw/3zTNgd6KR0SkIknPzGbR9qNMX3uAP9cd5GBCWqHHBfgZnN+yDhe5EkCv9ihIiQT4+3F118ZccW4jHK6kcMuhJABOpmcxds42Jv29k1t6N2VU/5bUq6aksCpbtvM4L05Z624P69qI2/tEe+8C253w7c2QlmC1/YPg6rHQaZj3riEiFYZHyaDTHrvTi9eMANYAk1yP0/EHUoH3gUuBml6MRUSk3DuZnsmcjYeZvvYAMzccIjG18Bp2YUH+DGxbj4s6RDGoXX1qhGrOT3ni72dwZZdGXN65IVPX7Oe9mVvYeNCqG5eSkcV453a+WLiTm3s2494BLaivBL7KOZSQyn1fLiMjy5rj27FhdV4ddg6Gt4Ztrv0Ffh4FWa4KYcHV4cavoHl/75xfRCocT3sGvcY0zanAVADDMCZ6cHwycK/r+M4oGRSRKuBYcjp/rT/IjLUHcG4+QlpmdqHH1Q4PYkj7+lzUIYp+resSEujFxSWkVPj5Gdg7N+TSTg2YvvYA78zc7C4mnpqRzYT52/ly0U5u7tmUewe0JKqGksKqID0zm/u/Ws6hRKu3v1ZYIB/f0t0797RpwuJxMO0prJk9QEQU3PIjRJ1z9ucXkQrLMM1TV5gryOaI2Y77vx6Fc9pjS1yR1DCMJODB4oaJFjj+faBTccNEDcMYBYwCiIyM7P7tt9+WNKxSl5SURESE5uyIlKaKeJ8dSclm+cEslh3MZNPx7CL/o1snxKBbpD/dIwNoXdMPfz8t9lCRZZsmKw5l8dvWDHYm5E/6Awzo3ySAy5oHUifUz0cRFq4i3mPl2Rfr0pi5y+r1N4AneoTQse7ZJ4LVEjbRcuvn1Dyxxr3tZGgj/un8AqmhkWd9fildus/EGwYNGrTMNM0ehe3ztGdwDqcmg3WAPkASMOvMw/Mu0zTHAeMAevToYQ4cONC3ARUiLi6O8hiXSGVSEe4z0zTZdDCJ6WsPMH3tAdbuK3oBmHZR1bioQyQXdYyiY8Pq3hs2JuXCBUCMaTJz/SHenbXZvYpkpgmzdmXi3JvFTT2b8syl7ctN729FuMcqih+X7WHmrlXu9lND23HvgJZnd9KjW2HmS7Du1/zbG59H2M3f0zvMiwvSSKnRfSalzdM5gyMK225zxNTEKjXxl/dCEhGpvLKzTVbsPu4uAZFTh64gw4BuTWtxccdILuoQRXTd8DKOVMqaYRgM6RDJ4Pb1idt4mDEzN7NqdzwAGVkmkxbsJCPL5LVhGtZXmazec4Jnflntbl92TgPu6V/iwVa5kg7D3Ddh6QTIzjO/2C8Aut8BF74EQWFnEbGIVCZnNWfQaY+Ntzli3gJeAb72TkgiIpVLemY2f289wvS1B/lz3UGOJBW+Amigv0GflnW5uGMUQzrUp341zRWrigzDYFC7+gxsW4+5m4/wzl+bWL4rHoBvl+ziuh6N6da0lm+DFK84mpTGvV8uI901J7hNZARvXtv5zHr+05NhwQcw/x1IT8q/r8OVMPgFqHOWvY0iUul4YwGZVKCxF84jIlLpLNx2lMe+W8n+E6mF7g8P8mdgu/pc3DGKQW3rUS1EK4CKxTAMBrSpR//Wdbnr86XM3HAI04Tnfl3D5Af6EuBfvuYQSslkZmXz0Dcr2BufAkC1kADG3tqD8OASfjTLyoQVkyDudUg6mH9f0z5WT2CT87wUtYhUNmecDNocMQFAJ2A0sLb4o3MZhhEBtHI1/YCmhmF0AY6ZprnLMIzXgJ6maQ7O85oOQBBQF4hwHY9pmivPNH4RkdKUnW0ydu423pq+gewCM67rhAdxYYdILu4Yxfkt65SbOWBSPhmGwegrOjJvi7Wq7Np9CXy5cCcj+nqtBLD4wJvTN/L31qPu9pgbutC8JMPBTRM2/A4zX4Qjm/Lvq9cOhoyGNpdYY85FRIrgUTJoc8RkU/RqognAZSW4Zg9gdp72i67H58AIoAFQcBzDVKBZnvYK10/9F05Eyp0TJzN4/IdV/LU+91v6WmGBXNOtMRd3iqJb01paAVRKpEntMB66oBX/nWF96H97xiYuPaeBahFWUFNW7WPc3G3u9qNDWjO4fQlW9ty1CP58DnYvyr+9WgMY9AycezP4l3n1MBGpgDz9L8VLnJoMpgI7gWlOe+wJTy9ommYcxSRxpmmOKGRbtKfnFxHxpTV7T3DfV8vYfSzFva1Hs1q8f3M31YuTs3J3/xb8vHwv244kk5iWyStT1/POjV19HZaU0MYDiTz54z/u9pD29Xn4gtaevfjwJqsncIMj//bg6tD3Eeh9vxaHEZES8XQ10dGlHIeISIVmmibfLN7N6Clr3YtBANzVrzlPDW1HoOZ3yVkKDvDnpSs7ccunVm/Q5JX7uKFHE/q0quvjyMRTJ1IyuOeLpaRkZAHQvG44sTd0we90IwUSD0Dca7D8CzCzcrf7BcJ5d0H/f0F4nVKMXEQqqyKTQZsjxg9r+Od2pz12TRHHnANEO+2xU0opPhGRci8lPYt//7Kan1fsdW+rFhzAW9d15pJODXwYmVQ2/VrX5fJzGzJl1T4Anp28hj8e6U9QQNX+siEr22T7kSTqhAdTKzzI1+EUKjvb5NFvV7DDVU4mLMifsbd2p3pxi0alJcL8d2HB+5BRoAxNp2vhgmehtuaOisiZK65n8BbgQ6C4gkaJwDc2R8zdTnvsN16NTESkAth2OIn7vlzOxoOJ7m3toqrx0S3dS7YYhIiHnrusPbM3HCIpLZNth5MZ79zGA4Nanf6FlVRWtsk9Xyzlr/WHAKhfLZi2UdVoG1mNtlHVaBdVndaRET5fqGnMzM3M3njY3X7r2nNpE1mt8IOzMmDZRGuF0JNH8u9r3t9aIbShhgiLyNk7XTL4mdMeu72oA5z22B02R8ynwO2AkkERqVJ+/2c/T/30D0lpuYWdr+3emJev7ERokFYI9UjCPqs22tbZ1jC3Jr2hSS9o3ANCa/o6unKpfvUQHr+oDS9OWQfAuzM3c8W5DWlSu2rOFRvv3OZOBAEOJaZxKDEN5+bcJMrPgGZ1wvMkiNVoE1WN6DrhZbKY05/rDvLuzM3u9j0DWnBZ50JGDZgmrPsVZr4Ex7bl3xfZCYa8CK0Ga4VQEfGa4pLBbsB7HpzjL2C4d8IRESn/0jOzeW3aej6bv8O9LTjAj5ev7MT15zXxXWAVyeFN8Pc7sOo7yM7I3b59ruuJAfXbQ5OeVnLYpBfUbqEPwS639m7GD0v3sG5/AmmZ2bw4ZS2f3F71asmt3nOCt2dsdLcD/AwyC9ZyAbJN2H4kme1Hkvlj7QH39uAAP1pHRtA2sjptoyJoG1WddlHVqF8t+MwKvxdi6+EkYr5b6W73a1WXf13U9tQDd8yDP5+Hvcvyb6/e2BoO2vl68NOXTCLiXcUlg9WA4x6c47jrWBGRSm9ffAoPfL2cFbvi3dua1Qnjw+Hd6Niwhu8Cqyj2LIP5/4P1DoquWIS179A667FsorUprK4rMXQliA27QmDVXKE1wN+P/1zdiWEf/g3AX+sP8ee6g1zYoQTlCSq4k+mZPPLdCjKyrL+jrk1r8u2o3uw9nsLGA4lsPJho/TyQyI6jyafU+wRIy8xmzd4E1uxNyLe9ZlggbSKtHkR3T2JkNaoVN7+vEElpmdzzxTISXaMHGtUM5b2buhKQd0Gpg+vgr9GweXr+F4fUANsT0HNUlf07F5HSV1wyeASrtt+805yjqetYEZFKbe6mwzz63UqOJae7t13UIZK3rjuXGqEl+5BYpZgmbJ0F8/4HO5yn7m/SC85/0Ooh3L0Ydi2EA6vzr5oI1typjb9bD7BWUmzYJX+CWC2q1N9OedGtaS1u6tmEbxbvBmD0b2vp26oOYUFVo77cf35fz7bDyQCEB/kz5oYuBAf406JeBC3qRTD0nNxhmKkZWWw+mORKEBPY4EoSDyWmFXru+JMZLN5+jMXbj+Xb3qhmqDUfMSo3UWxRN6LQBXxM0+RfP6xiy6EkwOqFHHtr99wFbk7shbhXYeXXYOauQIx/MPQaBf1iIKz22fyKREROq7j/Y8zDmgv41WnOMYLTJ4wiIhVWVrbJe7M2887MzZiu3gV/P4OnLmnL3bYWXhtOVulkZ1nzn+aNgQP/nLq/9cXQ7zFodn7utk7XWD/Tk2Hvcti90EoQdy+G1PgC58+APUusxwLXtprNcpPDpr2hfodKPbTuyYvb8ceaAxw/mcHe+BTen7WFJy9p5+uwSt2MtQf4etEud3v0FR1pVqfoBZtCAv05p3ENzmmcv/f+eHK6uwfRShAT2HQwKd884Lz2xqewNz6FWRty5ygG+Bm0qBfuHmKa06P426p9TFuTOyT1tWHn0KlRDUiJh/ljYOFHkJma5+wGnHsjDPo31NRwcxEpG8Ulg2OAeTZHzP+Ap5z22PS8O22OmEDgLeACoF+pRSgi4kPHktN55NsV+RajqF8tmPdv7kbP5vrWvlAZqbDqa2tJ/OMF1iAz/OGca60C2ZEdiz5HUDg0t1kPgOxsOLrZ6jXcvRh2L7LaBcXvtB6rv3edJ8JajKZJbytBbNzDGn5XSdQKD+Lpoe158icr2R7v3Mawbo1oVb/yzt44lJDKUz/lfrlw2TkNuLZ74zM6V63wIHq3qEPvFrk1+kzTZG98Sp4EMZFNBxPZejjJPSQ1r8xsk00Hk9h0MIkpqwq/zog+0QzrXA8WfAhz34SUArNwWg2BIaMhqrgF3EVEvK/IZNBpj11gc8Q8DrwNDLc5YmYAO127mwEXAnWAx5322IWlHqmISBlbvus4D3y1nP0ncr+9P79FHd65qQv1q2kOzylST8DSCdYH3uRD+fcFhEK3W63hoLWalfzcfn5Qr6316H67tS35KOxxJYa7F1sLb+TraQHSk2BbnPUArIVpOkDTXrk9iLWaV+iFaa7t3pjvlu5m2c7jZGSZPPfrWr6+u1el7LHOzjZ5/IdVHD9pLTrUoEYIr1zdyavv1TAMGtcKo3GtMAa3z52DmZ6ZzfYjyWw4kOBOEDccSGTP8ZRiz9erWU2ebboG3r8R4nfl39ngXKtMRIuBXotfRKQkip1Y4LTHjrE5YpYDTwFXA6GuXSlAHPC60x5byAQQEZGKyzRNPv97B69MXZ+vJ+CBQS15bEib/Is/CCQehIUfWolgWv6FOAipaS2A0eseCK/r3euG14G2Q60HQGY6HFwNuxa5EsRFkLi/wItMOLTWeiyd4DpP/fyrljbsAgHB3o21FPn5Gfznqk7Y35tHVrbJgm1HmbxyH1d1beTr0Lxu4t873L30hgFvX38uNcPKpsh8UICfe75gXompGa6ewZzhplayePxkBtfX3sIr5o8E/FpgmHTNZjD4eeg4zPqiQ0TER047y9xpj50LzLU5YvyAnP+TH3XaY7OKeZmISIWUlJbJUz/9w+//5CYRNUID+d8N53JBu6qzUqNHjm6Fv9+Fld9AVoGFOKo1hPMfsHrxgstoyGJAEDTqbj3Ov99auObEntzEcPciOLDm1IVpkg/BBof1APAPslYqbX859LoP/Mv/giztG1Tnjj7RfDLPGpb7n9/XM6hd/Uq1sNH6/Qm8Pm2Du31P/5b0aenlLxjOQLWQQLo3q0X3ZrXc28z43WROfpjA7bPgZJ6DQ2vDgCehx50V6gsHEam8PP4/nNMemw0cOu2BIiIV1MYDidz31TL3CoUAnRvX4IObu1XZgt6F2rfSWgBj3eT8qyAC1GkN/R6Fc663kjNfMgxrIY6aTax5igBpSdZw0px5h3sWW8Nb88pKz00eN02Haz+DiHplH38JPXphG6b8s4+DCWkcSUojdsZGXryyk6/D8orUjCwe/XYl6VnW31unRtWJubCNj6MqQloSxlfXEng4N3ElIBR632fdG5VozqqIVHzl/+tOEZEy8PPyPTzzy2pSM3KTm+G9mvL85R0IDqi8q1F6zDStgvDzx1hlIgpq1N1aGbTtZeV72FtwBLQYYD3AWpjmyMbceYe7F8HRLbnH73DCuAFw/SRr8ZlyLCI4gOftHXng6+UAfLFwJ9d2b3LKCpoV0evTNrDxYCIAIYF+jLmha6HlHHzONGHy/ZCTCBp+0GU4DHoGqjf0bWwiIoVQMigiVVpqRhYvOdblW6Y+NNCfV4d14uquZ7ZCYaWSnQUbfrdqBO5bfur+loOtJDC6X8VchMXPD+q3tx7dR1jbko/Akk8g7nXAhIS98NlQGPoGdL+jXL/PS8+Jwta6Ls7NR8g24dlfV/Pz/X3x9yu/MZ/O7I2HmPj3Dnf7OXsHWtWP8F1Axfn7XavHPMeVH0CXm30Xj4jIaZTDr9WkTCXshyWfwp5lvo5EpMztPnaSaz/+O18i2KJeOJMf7KtEMDMNlk+CD3rC97fmTwQNP2vhi3vmwq0/W+UfynGCVGLhdWHg/8HwH6wFcMAaOup4DCY/ABnFrx7pS4Zh8NKVnQhyLXK0as8Jvl2y6zSvKr+OJKXxrx9yF18Z0j6Sm3s29WFExdg6G/4ands+724lgiJS7qlnsKrKSIWFH8DctyEjGfwC4I4/oMl5vo5MpEz8te4gMd+vJCE1t7i0vXMDXr+mMxHBVfg/jWmJsGwiLPjg1JU4/YOh63Do8xDUbuGT8MpU6wthVJyVDB9YbW1b+ZX1/IYvoFa0L6MrUvO64dw7sCXvzrTqML75x0Yu7hhF3YiKtWCJaZo89eM/HEmyFieqVy2YN645p3yWzIjfBT/emTuHtklvuPhV38YkIuIB9QxWNaYJ6x3wYS+Y+ZKVCAJkZ8KUhyErw7fxiZSyzKxs3vhjA3dNWupOBAP9DV68oiPv3dS16iaCSYdh5svwv44w49n8iWBwdegXA4+uBvv/qkYimKN2cxj5J5ybp4fnwD8wbiBs+ctnYZ3O/QNb0tS16NGJlIx8q3BWFF8u2sXMDbnr1v33unOpUx4T2owU+O4WSDlmtSMi4frPfb+AkoiIB5QMViWHNsAXV8N3w+H4jkL2r7PmO4hUUocSU7nl00V8FLfVva1hjRC+v+d8bu8TXT57HErb8R3w+xMwphM4/5t/Zc2ISBjyIjy2Boa8ANWqaGmNwFC46kO4LBb8XKUaUo7Dl9fCnLesRWjKmZBAf168sqO7/eOyPSzefsyHEZXMlkOJvPL7Onf7zr7NGdCmHK7oaprgiIH9q6y2X4C12FC1KN/GJSLiISWDVUHKcZj2FHzUB7bNzt0eWgsu/a/1YS9H3BtW7TARD5mmyf4TKcSfTMc0zdO/wEcWbTvKZe/OY+G23A/EA9rU4/eHbXRtWquYV1ZSB9bAT3fBu91gyXjITM3dV7sF2MfAI/9oKfwchgHnjYQ7plk1FAEwYfZ/4NubISXel9EValDb+gztlJuUPPfrGjKyyl/iWlBaZhYPf7PSvbJvu6hqPHlJWx9HVYQln8Cqr3Pbl7wOTXv7Lh4RkRKqouOhqojsLFj+uTX0KyXPN8KGH/QYaS11HVYbsjJh7c/WN5tZaeB4FG77rXItCCFecyw5nVW741mxO56Vu+NZtTueEynW8OKQQD+iqocQWT2EqBoh+Z+72vWqBRPoX3bfQ5mmydi523hr+kaysq1k1TDgsSFteHBQK/wq8CqLZ+TQBpj5Imyceuq+BudaK4O2vwL8VE6jUE3Og3vmWPPDdjitbZumwfhBcMOXENmx+NeXsefsHZiz6TAn07PYeDCRz+ZvZ1T/lr4Oq1ixMzaxbn8CAEEBfrxzY1dCAsvh3+OuRfDH/+W2z70ZzrvLd/GIiJwBJYOV1Y758MdTuYse5Ii2Wcuj5/3A4h8Al79rfZgxs61aYqu+0SpoQmpGFuv2J7Byl5X4rdwdz65jJ4s5PpsdR0+y42jRxxgG1I0IzpMoWs+jaoS6fgYTWT2EaiGBZx3/iZQMHv9+FX+tP+jeVjs8iHdu7IKtdTkcclaaEvbB7FetBVAKFopvPsBKAlsM1JdAnoioD7f+CjNHw9/vWduObYPxg+GK96Dzdb6MLp+GNUN5dEhrXp1qzRkc89dm7J0b0rBmqI8jK9z8LUcYO3ebu/300Ha0jarmw4iKkHjAWlgo27UAVYNzwR6r+0dEKhwlg5VN/G748zlY+0v+7TWawsX/sb7xL+x/Vg27QO/7YcH7Vnv6M9D6ImuJdakSTNNk+5Fkd9K3cnc86/cnkJF1+qGf1UMCyMw2OZme5cF14HBiGocT01i990SRx4UH+RPp6k2MyvMzsnru87oRwUXWT9txIovn3nOy+1huGYBuTWvywfBuNKhRPj8Il4rUEzD/HVjwIWTmLYlgQHu7lQQ26u6z8Cos/wC46D/W7+7XB6zFuDJT4Oe7YO9Sa5//2X+h4Q139G3Oj8v2sOlgEifTs3jZsY6Pbil//+bHk9N5/PtV7vaANvUY0SfadwEVJTMdvr8dklxfMoXWtnqFA6vQf1dEpNJQMlhZpJ+0Fn+ZNyb/B77AMGsVwD4PnvI/qgMnUvllxV7mbzlC16Y1eWzA0/it+w1O7LLmGU5/BoaNK9v3IWXmaFIaq/bEs3KXNeTznz0n3MM9ixPk70eHhtXp0qQmXZvWpEuTmu5VCxPTMjl4IpUDCakcOJHKwYSc52kcSEjhwIk0jian4cnUwuT0LLYdTmbb4eQij/H3M6hfLThfghhZPYTMrGzeWZRKZp4OsJH9mvN/Q9uV6RBVn8pMh6Wfwpw38w8TB2h5gTVXuEFn38RWmXS8Guq1t1aTPGqVcmDRx9aw++smlouFRAL9/fjPVedw/dgFAExbc4DZGw8xqG19H0eWyzRNnvllNQcSrLmrtcODeOu6zuVzUacZ/4bdC63nhh9cOwFqltPahyIip6FksKIzTVj3K8x4Dk7szr+v07Vw4YtQI7d49sn0TKavPcDPy/cyb8sR94fyeVuOkJ6ZzdP2WPjqWmvjP99B5xug1eCyeS9SalIzsli7LyFPr9/xfD1mxWleN5wuTWq6H+0bVCcooPCEqnpIINVDAmkdWfSwroysbA4lpuUmi3mSxwMJudvSMk+/0EVWtsn+E6nsP5Fa5DERwQG8dW1nhp7T4PRvtjLIzrbmAM98CeJ35t8X1dn6b0LLC3wTW2VVvx3cPQsm3w/rp1jbdi2Asf3hus+h2fm+jQ/o2bw213RrzE/L9wDwwuS1nP9YnXIzF++HpXuYtuaAu/3mNZ2pXy3EhxEVYeU3sDjPl6SDX4CWg3wXj4jIWVIyWJEdWGOtErpzXv7tUZ1h6JvuDyDZ2SYLtx/l5+V7mbZ6P8lFDOUbO3cb0XXP4aZO18KaH62Njsfg/oUQFFaa70S8KDvbZPvR5Hzz/NbvTyAz+/TdcbXCAl1JXy26NK3JuY1rUDPMu7WyAv39aFQzlEbFzFkyTZMTKRnsz0kQCySKBxLSOJiQyrHk9GKv1S6qGh8O70aLehFefQ/l1rY58OfzsH9l/u01m8IFz1lfEPlVkZ7RshZSHa7/AuaPsRJxM9saRvi5HS56BXrd4/P5ZE9f2o6/1h/kREoGu46d5KO4rTx2YRufxgSw/Ugyo6esdbdv6d2UIR3KYRmTfSutBdZydLgS+j7iq2hERLxCyWBFlHzUWs582cT8C0GE1YHBz0PXW8HPn22Hk/h5+V5+WbGXvfGn9gIZBpzfog7Zpulebv+5X9fQ4sZ/0WvLX5Aab/UszHkdLnypbN6blNjRpLR88/xW7Y53F1MvTlCAHx1dwz27NKlJ1ya1aFI7tFwMyzIMg5phQdQMC6J9g+pFHpeakcWhhDSrZzFP0ng4MY2glMO8fEtfQoPKR89HqTqwBv564dQi6KG1oP+/rBUOA8phse7KxjCsOZgNu1qrjZ48ai0w8sdT1jzCy9+BoHCfhVc3IpgnL2nLv39ZA8BHc7ZyVddGNK/ru5gysrJ59NsV7vnGLeuF8+9LO/gsniIlH4Xvbs0twVKvHVz5gc8TfBGRs6VksCLJyrTmAM1+JX9haL8A6DkKBjxFvBnGlMV7+Hn5Hlbsii/0NC3qhXNNt8Zc1bURjWqGkpyWyfVjF7B2n9V7dNfPO/lr4LNExj1hveDv960eBc0vKhf2n0hh6uoDrNh1nFV74j0e7tkiZ7ina55fu6iih3tWFCGB/jStE0bTOqf2XMfFxVX+RDB+t7VC6KpvgDw9vwEh0Ps+6PsohNb0UXBVWIuBMGoOfH8b7FtubVv9AxxcBzd8AXV8V9rhxvOa8v3SPazaHU96ZjbPT17DpDt7+uxLoHdnbmbVHuv/Z4H+Bu/c2LX83bfZWfDTndZ8eoDg6nDDVxBcDlc5FREpISWDFcW2OJj2f3B4ff7tLQeTceErxB2rzc8/bWXm+kOkF1JUuGZYIFec25Bh3RpzbuMa+f7HHx4cwKe3n8eVH8zjYEIaiamZXLuoBTOb9CVo93wws2DKw3DXTNUe86HUjCzGzd3Gh3Fb3MWYi1I7PMjd43duk5p0aVyTGmHlY2VD8YKU4+CMhUVjrdqgbgZ0GW7VEK3RyGfhCVCziVWg/o+nrFEcAIfWwrhBMGwstB3qk7D8/Qz+c2UnrvxgHtkmODcfYerqA1zWuezn1C7efowPZm9xt5+4qC2dGtUo8zhOa+ZL1v+Dc1w9Fuq28lk4IiLepGSwvDu+A6b/GzY48m02azVnZ49nmXikHb+N38Ox5G2nvDTAz+CCdvUZ1q0xg9rVIzig6EQuqkYIn95+HtePXcDJ9Cx2H0/lsdDbed9/KUZWGuxbYU2a732ft9+heGDm+oO8OGVdoTX+ggL86NSwOl2a1OLcJjXK1XBP8bKMVOs+dL5tDePOq/XFMGQ0RJbDIXZVVWCINTS0UQ/4/XErcU87Ad/caA3fHfi0T75gO6dxDW7t3YzPF1gLDL3kWMuAtvWICC67jwQnUjJ47LuV5Exl7tOyDnfbWpTZ9T22brI1DzTHgKeg3aU+C0dExNuUDJZXaUkwL9Yaopnnm//swHAWNxnJy0cGsHZKGrDzlJee27gGw7o15vJzG1I73PPFPzo1qsG7N3bl7i+WYprw+74IhjYejv3IBOuAmS9DO7v1jbeUiZ1Hk3lpyjpmbjiUb3vHhtW54bwmlWa4p5xGdjas/h5m/efUVYMbdrPm9Da3+SY2Ob1ut0JkR2vYaM6/39y3YO9yuOYTCKtd5iHFXNSW31cf4EhSGgcT0hjz5yaetZfdFwnPT17jnsteIzSQt68/F78iaob6zKEN8Ov9ue3WF8GA//NdPCIipUDJYHljmtbckj+fh8T9+XY5w4bwxPGrObiuFpCWb19U9RCu7taIYV0bFbus/+kM6RDJs5d14GXHOgAe2zOQ3rVmUzdlu1VU+ffH4ebvNGm+lKWkZ/FR3BY+nruN9DwlFmqEBvKvi9tyU8+mRRZbl0rENGHrTPhzNBxcnX9frebWglEdr9b9WBE06mbNI/xpJGybbW3bOhPGDbBWIW3YpUzDqREayLOXtefR71YC8NnfO7ime+NiF2zyll9X7GXyyn3u9uvDzqFBjXJWsD31BHw3HNKTrHat5lbdXa3GKyKVjJLB8mTfCqtUxO5F+Tb/Y7bi+fTbWJmaf45CaKA/QztFMaxbY85vWcdrycGdfaPZfiSJLxfuIoMARsXfzs/Bo62dm6dbdQ07Xu2Va0l+pmkyfe0BXnasz7cCrGFYCz/86+K2JertlQps30rrS6Htc/JvD6trDVXrPgIC9LdQoYTXgVt+shYBc75tbYvfBRMuhstioevwMg3nyi4N+XbJLhZuO0ZWtsmzv67hh3vOL9Ueut3HTvLcr2vc7et7NC5/NUCzs+GXe+Goaz5jYBjc+JW1Oq+ISCWjZLA8SDoMM1+EFV+Sd0XAQ2ZN3si4kZ+z+2FifRuZUw5iWLfGDO0URXgpzPEwDIPRl3dk59GTODcfYbnZhq+yhjDc37Vs/dQnrdXy9D9Gr9p6OIn/b+++46Oo1j+Of046EHpHCEVBelE6RLoCgqCo4M96FXuP/SIK14pXUfSKV7Fgx4YNvYINCQpSFFC6IkV676Se3x9nk90ECGmb2STf9+s1r+yZmZ15dmXcffacOc+Yz5aSuHpHlvVt6lXiX+e0oE29St4EJkVr91o3HPS3D7KujywLXW6Crje7mnZSPIWFux7dk053CUfSPleu4NMb4O/5MGBckZUBMcbw8NCWDJiQSEqaZeG63Xz4y99c2D44twKkpqVz+3uL2J/kSt80qFqWBwe3CMq5CiTxKVj5pb99znNumK+ISAlU5OMdjDFnGGM+M8ZsNMZYY8wVuXhOK2PMD8aYw77nPWBKwuwYqcnw03PYZ9vBr2+SkQgm23D+mzqY3klP8lH6GVjCaFS9HHeddSqz7+nNO1d35vzT6wYlEcwQER7G8xefRpOarlj34ykj2IYv+Tu4Db4ZE7RzlzYHk1J5/H8r6P/MrCyJYJVyUYwb1oqPr++qRLA0OLQLvroP/tMhayJowl0v4C2/Qu9RSgRLiqZnw9XfQ/Vm/nULX4PXBsLejUUWxik1ymeZuOWxL5ez+2ByUM41ceafLFi3G3Czmj4zol1QP8fyZfXXruc2Q5eboNX53sUjIhJkXvxfOBb4HXjDt+TIGFMB+BqYBXQAmgKvAQeBp4IXZnClrpxO0rR7KLf/LwKz2m/S2vFw6iWstbWpVDaSy45TDqIoVIiJ5NUrOjD0+R/ZcQBGJ1/Oi1HPuI0LJ0Pr4VC/a5HGVORSDvuG7s6D8AgIj4bwKDc8LzxgiYiG8Mg8bbdhkcxdf5A3521iy8F0TiWCZBNJmong7HYNGNnjVCrElnP3akZEu3qSJeA3EMkm+RD8/ALMfsb1EgVqOgj6PAjVm3gSmgRZtVNg5Dfw2c2wdKpbt3EBvHgGXPAaNDyjSMK4uXdjPl20iY17DrP7UApPTF/JY+e1KtRz/LJ+NxO+XZ3Zvq1PY9qG2o9cu9a4ezozRug0iIe+Yz0NSUQk2Io8GbTWfgl8CWCMmZyLp1wMlAUut9YeBn43xjQFEowx4621Nuenhw5rLauXL6bKT2OJSP4ly5v/Z3pt/pV6GT/Slt7NanBvLspBFIW6lcsy6bL2jHhpLtNTOzAj7XTODF/oNn5+K1w3u8iGNBW51GQ3+9/qGUE5vAG6+Bayv4VLfUt24VEuoYypAM2HQvfbIbZ6UOKTIEtPg0XvuKLx+zdl3Vavk5shNK6zN7FJ0YmOhfNfhbodYMb9rq7roR3wxhBXKqTrLUH/EahMVDhjzmnB1W8sAODdeeu5oH1dTosrnFsBDiSlctuURaT56kh0aFCZG3qFWJ2+5IMw5RI3cQxAhZPg/Nfcj4AiIiVYcZgWqwuQ6EsEM0wH6gANPIkon5bNfJ8G7/WmdfIvmev22TI8lHIxd1V/gd6D/o95o/ry0mXt6d+ylueJYIZ2cZUZf2FbwPBAyhUcsDFuw45VMPtpL0MLnrQU+PAfQUsE8y0tGZL3w76NMPd5mNDGFUQ+vNvryCS3rIVV0+GFbvDZTVkTwaqNYfjbcOV0JYKliTHQ5Qa4/HMoV8Ots+luAqH3L4Ok/UEPoV/zmvRtViOzff/Hv5Oalp7DM3Jv7GdLM2uklo+OYPyFbUNrNmRr4bNbYJvvF7jwKBj+pn5oE5FSwXjZsWaMOQDcZK2dnMM+M4C/rbVXBqyLwxXY62qtnZNt/2uAawBq1qx5+pQpU4IRev4k76fVjzdQ1ewj3Ro+oSc/17yY1nFVOSk29PPyaX8m8+HqFC4Ln86/Il8HIN1EsKD9MxwqV4JqD9o0mi1/mprbEjNXrYsbxvbq3QhLT8HYVMLSUwhLT8XYjL9Hrwvcl/QUdhxIZv3eZEx6CpGkEkUqUSaVmtGpVI9JJ8Jmfc5Rx7Rpxw05NbwcG+oN5e+6g0iLKFsU71LIO3DgALGxsV6HkUX5fas4+c/XqbT39yzrk6Iqs7bBCLbU6of1oAi5hI6opJ20WPoEFfetyFx3sGxdlra4j0Pl6gb13NsPpTNq9mGSfTngxU2j6Ncg8rj75+Yam7cllYmL/KWQrm0dTZc6odXbVnfDZ5zy5yuZ7RWn3sSW2v08jEjELxQ/y6T46dWr10JrbftjbStxyWCg9u3b2wULFhRixAX31euP03DDVA71HUfrjj1D69fRE7DWcveHS/ho4Xo+ihpDuzDftNtxXeGKL0pG/aX0dNdbs+ht/7quN0O/h/I9VGvppr088OlSFq7L2nvXpVFVxg5pQZPc1oVMT3c9g2nJsDbRDS/cmjWpoGxV6J4AHa6CyBCr21XEZs6cSc+ePb0Ow/U6bF8BMx93ZVkCRcVCt1uhy40QVc6T8CQEpSbDjFEw7yX/uqhYGDoRmg8J6qmf//4P/j19JQCx0RF8d0cPalSIOea+J7rGNu05TP9nZrHviJs9dGjbOjwzol2hx1wgfyW6IbkZP7adfgUMnuBpSCKBQuazTIo1Y8xxk8Hi8O19C1Az27qaAduKlf6X3s3mbuNo17lXsUoEwU1D/si5rejYqBr3pYwkxfp6MNb/BL+ecC6g0GctfHln1kSw4zX5TgT3HEpm9Ce/M/i52VkSwVoVYnjuona8c3Wn3CeC4JLtyBh3v2DTs+HaRBj2ClQNuPfm0E73JfLZdjD/ZfelUoqWtbDrL/jlDZh6DYxvDhM7Z00EwyLcv61bFkGPu5UISlYRUTDw33DuSxDh+1En+YAbMrr0k6CeemR8QxpVd/8eDySl8vAXy/N1nLR0S8L7izITwZMqleFfQ1sWWpyFYu9G+OAKfyJ4UnsY8ISnIYmIFLXikAzOAeKNMYE/TfYDNgFrPYmoIMLCivWMkFERYfz3ktNJrtqMl9LOzlyfPn007C92ubmftTB9FCzwDxXitMug/7g8//dKT7dMmbee3k/9wJtz1+GbM4HIcMN1PU7m2zt6MLhNnYLPDhsW5qY8v+FnGPI8VIzzb9u/Gb64A/5zOvz6NqSlFuxckrM96937/PH18EwreLatmyFyyXtHTw7TfCjcOM992dc9SZKTNsNh5NdQuYF/3YzRkJp03KcUVHREOA8P8Sdtny3exI9/7MjhGcc2KXENc9fsAiDMwDMj2lIh5vhDTotcahK8f6mbrAegXHW48I2SOyGaiMhxeFFnMNYY09YY09Z3/jhfO863/TFjzLcBT3kHOARMNsa0NMacB9wLFKuZREuSSmWjePWKDrwReSFr010nbVjyPlK+uNvjyArgu4fchCwZWl0Ig57J89DXxRv2cO7EH7l36m/sCqjVFd+4Gl/ddgb3Dmha+HW1wiOg3SVw8wIY+CTEBnSk71nvillP7Ay/T3VDTaXg9m6ExVPgkxvhmdYuAfz0Blj8DuzdcPT+0RVcmYiR38GFr0PVk4s+ZimearVy9QjLVnXtvethwWtBPWXXU6oxpG2dzPboT38nKfX49yxn99vfe3lqxsrM9o29TqFDgyqFGmOBfXkXbPTNjG3C4YLXoeJJ3sYkIuIBL+7ibg98H9Ae61teB64AagOZ35SstXuNMf2A54EFwG5cfcHxRRSvHEODauV47rJuPPjKSF4PcwV6I1d8StryLwlvNtDj6PLoh39DYkDJyuZDYOgLkIeJPHYdTOaJr1bw3oINBP5EcVKlMowe1JyzWtQMfp3IiGjoeDW0vdgNEZ39NBx2v8yzc7WbHbXmeFe4vEn/Yt1DXeT2b3H3Fq2dBWtnu3pkOYmKhbgu0DDe1Sqr3SZP/55EsihbBeLvhOn3ufasf0O7iyE6D8PM82jUwGZ8t3wb+5NSWbP9IC8n/sWNuSgHcSg5lVvf+5WUNPc/wjb1KnFLn8ZBizNfFk6GX173t896BBp08ywcEREveVFncCZw3G+h1torjrHuN6Boqu9KrnVsWIWNw/6PD6cmcn74LAD2T72VinfGY4L4JaVQ/fQcfP+wv91kAJz3cq5rS6WlW975eR1PzljF3sMpmeujIsK47oxGXN/zFMpEFXESEFUWut3iJkL4+b/uNWYUM9/6G7w7wt0b02c0NOpZtLEVFwe2uUl6/kp0yd/O1TnvH1nWlYJoEO8KhdduA+EhNCROir/2V8Lcia7n+dAOmPuCu980SGpUiOGOM5sw5vNlADz77WrOaVOHelVynq344S+Ws2b7QQDKRoUzYXhbIsND6I6Uvxe4XsEMrS6ETtd5F4+IiMdCa35nKXbObVeXiZtHs/Pn86hq9lMpZRu/vXUPra6a6HVoJzZvkivynKFRL7hgspu8IRcWrtvF6E+Wsmzzvizr+zStwQODm1O/qseTgsRUcF8WO4yEn56Fn1+EFFfri40L3Ax6DeKh92iI6+RtrF47uMMlfRkJ4I6VOe8fEeMKwzeMhwZnQJ12uf53I5IvkTHQ8z43HBngx2eh/VVQrmrQTnlJ5/p8sPBvlm7aR1JqOg9+tpRXLm9/3FEOM5Zu4Z2f12e2x5zTggbVQmhypAPb4L1L3YzMADVbuZlDNUpCREoxJYNSYNcP6MCb62/msi2PAtB8/Tv8PPtcOnUP4TpNv7zpZg7NUL8bjHjHfeE6gW37j/D4/1Yw9ZeNWdbHVSnLg4Ob06dZ9slvPVa2CvQdA52ud0NHF7zi/zK0NhFePRManwm9RkGdtl5GWnQO7YJ1P/p6/hJh27Kc9w+PhnodfT1/8XDS6ZpoQopemxHuh53tKyB5P8we74Y4BklEeBgPD23JeS/8hLXw3YptfL1sK2e2qHXUvtv2HeHeqb9ltge2qsUFpwe3LmKepKXAB//wT+gUU8kVlo9SXVYRKd2UDEqBGWO48Mo7WPTk/2ib/CvhxlLh6zv4vf53tKxXzevwjrbkAzfTY4a6HeD/3jvhl4KUtHTemLOOZ75exf4k/+ycMZFh3NjzFK4+oxExkSF8X1j5mjDgceh6E/zwBPz6ln9K9dUz3NLsHJcU1mjqbayF7fBuWDfH3/O39Xcgh/mnwiLdv4uMe/7qdsjVDwUiQRUW7nry37vYtedNckMcK9UL2inbxVVmRIc43p3nevzGfr6M7o2rUTbK//UhPd1yxweLMyfNqlUhhkfPbRX8+6Tz4usHYN1sX8O4sjxVGnoakohIKFAyKIUiJiqC+pe9yJGXuxNDMs3MOp6bPIZqtzxJrYoh9CV62afw8bVkJgK128DFH55wIoY5f+5kzGdLWbl1f5b1/VvU4v5BzahbuRj9ulyxLpzzrCt2/sM4WPI+me/H8s9g+efQ+kLoeS9UaeRpqPl2eA9Vd8yH6V+7BHDzEnJO/iJcb19Gz1/djuoxkNDU9Gx3z+/GBZCWBD887krLBNHdZ53K9KVb2HUwmY17DvPcd39wT3//D0aTf1pL4mpXosEYGD+8DZXKhtCw6SUfuPstM/S+Hxr39S4eEZEQomRQCk3luqeyo8udxMxxw0VHpr7HTa/24Nkbzi38cgr5sWo6fHiVvzesRnO49BMoU+m4T/l9414mzvyDL3/LWkOxUfVyjBncgjOaFOM6cVVPhvNegu63w/ePukQQAOvq4/3+kStZccZdLoEMRYd3w/ZVbtjc9pWwfbn7u28jrXJ6ngmHk06DBt1dAhjXWYXfpXgwBvo+CK8Pdu1F70DXW6D6qUE7ZeVyUdw7oCl3f7gEgEmz1nBeO1eGYfnmfTz+vxWZ+14T34iuJ4fQiJAtv2UdCdJ0EHRP8C4eEZEQEwLf0KUkqdY3gQMrPiZ293LKmGQu3zWBW9+tz4uXdSA8zMMhQ39+7yYOSPfN+Fm1MVz2qbufLhtrLTNXbeelH9YwZ83OLNvKRoVzS5/GXNmtIVERITRDXkHUaObundn0K3z3CPzxtVufnuqmYF/0rpvJMD4BYmt4E+PBnb6ELyPp8/09sOXEzwUwYa4XOGO2z7jOQZ2WXySoGp4BJ/eGP78Dm+7qpA5/K6inPP+0unywYAPz1+4mNd0y+tPfufJky21TFpGc5uqXtqhTgYQzmwQ1jjw5tAumXAyph127amNf2aAS8v9uEZFCoGRQCld4JLHnP4+d1AeD5Yzw3/ho1cc8+mUsowc19yamtT/Cuxe5IVUAlRvA5Z8dldgkp6bz6aKNTEpcw6qtB446zOA2dfjnwKbUrlimCIL2QJ12cMmH7t667x7231+TlgQ/v+DqcnW61vVCHCOJLjBr4eB2l+hty5b4HdqRt2OFRbK/bD3KtxroEsD6XSCmYuHHLOKVPg+4ZBDc0O6/F0Ld04N2urAww0NDW3L2s7NJS7fMXbOLLTvCWLvPJYIxkWFMGNGW6IgQuW86PQ2mXg171rl2VCyMeNvNsiwiIpmUDErhO+l0TKfrXAIBPBD5Jn1mt6FBtXJc2rl+0cayYT68c6H/l+EKdeHyz6FCncxd9h5O4d1563ntx7/Yui8py9PDwwxnt6rNNWc0ouVJpSSZqN8FrpgGa2a6HoeNC936lENuNtL5r0DXm6Hz9fnrXbMW9m8+updv+wo37DMvwqOhWhM3RK56U//fKg1ZmPgjPXv2zHt8IsVBnXbQ4lxY+rFrfzvG/b8tiJrWqsCV3RowKfEvgMxEEOD+s5tzSo0Q6m2f+Rj88Y2/fe5/gzqUVkSkuFIyKMHRexR2+eeYfX9T1exnVMTb3PtZBeKqlKVHUd1nt2kRvDUMkn29fLG1XI9gpTi3ec9hXp39F1Pmb+BAwOyg4IaDjugQx5XdGxSvyWEKizFwci9XlH7l/+D7R3wzcOIK2H//iCt63f126Hg1RB6jtzQ9Hfb9HZDwZSR9K90x8iKiDFRvkjXhq97U9fKGhUhPhEhR63U/LPvM3Qf91yw3HP7kXkE95a19m/D54s1s2Xckc13fZjW4uFNcUM+bJyu+gFn/9re7J0Czwd7FIyISwpQMSnBEl8ec/SS8OwKACyJmMTU5nhvfDuej67tyaq0g/4K8dRm8eS4k7XXtstVcIlj1ZJZu2sukWWuYtmQzqelZZ5isXj6af3RrwMUd61OxbGRwYywOjIGmA6FJf1j2sZtoZucfbtvhXfD1aJjzPJxxJ1Ssd3RvX8rBvJ0vKvboXr7qp0LFON3nI5JdtVPgtEvdvb0A34xxP+AEsaRDbHQEDwxuzg1v/+JCiI1m3LDWoVNGYsdqmHqtv31ybzd7qIiIHJOSQQmeUwdA86Gw7BMAHo14mf5J47hy8nw+vrErNcoHqeTEjtXwxjkuWQGIqYS99GMSd1fhpU9/ZvYfR99/dkqNWK6Jb8SQdnVC556XUBIWBi2HQbMhsGQKzBwHe13dMQ5sgS/vzNvxoiv6kr1T3QQ2GYlfhZOC+kVWpMTpcQ8sngKpR2DzIlc+p8XQoJ5yQMta3H92M76cv4qHRnSgamx0UM+Xa0n73YQxyb4SQJXiXD1BjR4QETkuJYMSXAPGuaFLSXtpGLaVmyM+5sk9w7n6jYW8d03nwi/SvusveP0cNxEJYKPL833HF3nivT2s2LLhqN07NazCtT0a0bNJDcK8nO20uAiPcOUmWl3oJpSZ9WTOM3qWqQzVmx3d21e+lpI+kcJQoY6b2OnHCa793UOufEJ48D7ejTGMjG/EKWnraVEnRO6lthY+uQF2rHTtiBgY/nZwJrsSESlBlAxKcJWvBf3GwrTbALg2fBqfp3Vh8Qa44/3FPHdRu8JLwvZscIng/k0ApISX4ab0e5k+Iw3wF4sPMzCgVW2uiW9Em3qVCufcpU1ElLtXsO3FMP9l1xsRWeboe/rKVVPSJxJs3W6DBZPdsPidf8Cit+H0y72Oqmj9+ExArVRg8LNQu7Vn4YiIFBdKBiX4TrvcFTFfP4dIk8bjkS8zLHkMX/y2mfpVy3J3/6YFP8e+zW5oqG/o4hEbyT8OJzAnvWHmLmUiwxneoR5XdW9IvSqlcFKYYIgqC91ucYuIeKNsFXcNfveQa898HFpfeOyJnUqiDfPh24f87U7XQZvh3sUjIlKMaEYGCb6wMBg8AcLchCztwv7g4nA35ffEmX/y/oKjh2/myYHtJL02GHatASDJRnBtSgJz0lsAUC02ijv6NeGne3sz5pwWSgRFpOTpfD2U89VO3b8J5k3yNp6ikrQfpo50M6oC1OsMZz7sbUwiIsWIkkEpGtVPhfg7Mpv/jHqfWux0j6f+xk9/5rGoOGCt5eelf7B+wplE714NQIoN56aUW/ghvQ2NqpfjsfNaMfue3tzcpzGVy0UVzmsREQk1UeWgx93+duJTcHiPZ+EUmS/vht1r3ePoCjBsEoRrJmgRkdxSMihFJz4BqjYGoIw9xFPl3wYgNd1y/Vu/8Of2A7k6TGpaOp8u2sjwZ6cT894FxKW4HsE0a7gt5Ub2xPVj0mXt+eb2HlzUMa7wJ6kREQlFp13uam8CHNkDPz3nZTTB9/tHsPgdf3vQ05l1ZEVEJHeUDErRiYh2w0V9uqXM5YJyiwDYeziFKyfPZ9fB5OM+/UBSKq/M/ose/57JfVPmctfO0bQJc4lgujW8WfMerrougQ+u60q/5jU1O6iIlC4RUa4QfYa5E2H/Vu/iCaY9G+Dz2/3t1iOg1fnexSMiUkwpGZSi1aCb+/Xa59Ho16kWeQSAdTsPce2bC0hKTcvylG37jjDuqxV0fexbHpq2jB179vJy5JN0CFuVuc+uXuO44ob7OC2uctG8DhGRUNRyGNRs6R6nHILEJ72NJxjS0+Dja93sqQCV6sPAf3sbk4hIMaVkUIpev7GZEx1EHtrKR02+yaw+MH/tbu796Destazeup+7PlhM93Hf88LMP9l3JJUoUngx8mm6hi/zH6//OKr1vNaDFyIiEmLCwqDPg/72gtdc/dWS5MdnYN2P7rEJh/MmQUwFT0MSESmulAxK0StT2RWj96n/57s83SUps/3xrxsZ+Oxs+j09iw8W/k1yWjoAEaTyarnn6Rm+2H+svmOg83VFFbmISOhr3A/iurrH6Skw8zFv4ylMGxfC94/62z3uhrhO3sUjIlLMKRkUb7Q4Fxqf5WtYhmx4gotPr5W5efnmfVl2b1+vPImnTKF72jz/yh73QvfbERGRAMZA34DewSXvw5bfvYunsCQdgI9GQnqqa9frBPF3ehuTiEgxp2RQvGEMnP0kRJZzze3L+Vf1b+l2StUsu5zZvCYfXtuJD+u8Q+2/v/Q/v9ut0PPeoo5aRKR4iOsMTQb4GtZfkL44++qezHqyRJWH816C8AhvYxIRKeb0f1HxTqU46H0/TL8PgPDEJ3nxqsE8v6QS6emWCzvU4+Rq5WDa7bD4Xf/zOl4LfceSeaOhiIgcrc9oWPUVYN3fdXOgfhevo8qfpZ/Ar2/522c/5S+jISIi+aaeQfFWp2uhTjv3OC2J2Bl3cc9Zp3LfwGYuEfzqPlj4mn//0y6D/o8rERQROZGaLaD1hf72N2PAWs/Cybe9G+HzW/3tludnfV0iIpJvSgbFW2Hhrvag8RWGX5sIi952X1i+HQs/v+Dft/VwGPSMmy1PREROrOd9EBbpHm+YC6tneBtPXmWUkTiyx7UrxrleQf0gKCJSKPStWrxXuw10ucHfnj4KZtwPs5/2r2s+FIZMdMmjiIjkTpWG0P4f/vY3YyE93bt48uqn59yPhAAmzN0nWKaSpyGJiJQkSgYlNPS8z91DCO4X4Dn/8W9rMgCGvayJAkRE8uOMuzIn62LbUvj9Q2/jya1Nv2ad+Cb+zuJ7z6OISIhSMiihIaocnP300etP7g0XTIbwyCIPSUSkRIitkXX0xXcPQ2qyd/HkRvLBrGUkTmrvagqKiEihUjIooaNxX2h1gb/dIB6Gvw2RMd7FJCJSEnS9GcpUdo/3rINfXvc2nhP56j7Y+Yd7HBULwybpR0ERkSBQMiihZdDTrnREl5vgoikQVdbriEREir+YihB/h7/9wxOu9y0ULf88a7I68N9QpZF38YiIlGBKBiW0RJeHgU/AWY9AdKzX0YiIlBwdRkKFk9zjg9tg7gs57++FfZvhs5v97RbnQpuLvItHRKSEUzIoIiJSGkSWgZ73+ts/ToBDu7yLJ7v0dFdG4vBu165Q140WURkJEZGgUTIoIiJSWrT5P6ja2D1O2pe1hI/X5j4Pf/3gaxg470X/fY4iIhIUSgZFRERKi/AI6H2/vz3vJdi70bt4Mmxe7GogZuh+OzTo7l08IiKlhCfJoDHmBmPMX8aYI8aYhcaY+BPsf6MxZrkx5rAxZqUx5rKiilVERKREaT4Eard1j1OPwA/jPA2H5EO+MhIprl2nHfT6p7cxiYiUEkWeDBpjhgMTgEeBdsBPwP+MMXHH2f96YBzwL6AF8CDwvDFmcNFELCIiUoIYA33H+Nu/vgU7VnsWDjNGwY5V7nFkORj2ispIiIgUES96BhOAydbaSdba5dbam4HNwPXH2f9SYJK19l1r7Rpr7RTgJeCeIopXRESkZDm5FzTs4R7bNFeI3gsrvoQFr/rbA8ZB1ZO9iUVEpBQq0mTQGBMFnA7MyLZpBtD1OE+LBo5kW3cY6GiM0U+HIiIi+dH3Qf/jZZ/Apl+L9vz7t8BnN/nbzc6BdpcUbQwiIqVcRBGfrxoQDmzNtn4r0Pc4z5kOXGWMmQoswCWTI4FI3/E2B+5sjLkGuAagZs2azJw5s7BiLzQHDhwIybhEShJdZyIn1qJaF6rvmAPArg9uY0mbsSd4hl+BrjGbTuslY6lyaCcASVFVmV/lQlJ/+OEETxQpXfRZJsFW1MlgfjwE1MLdW2hwiePrwN1AevadrbUv4YaR0r59e9uzZ88iCzS3Zs6cSSjGJVKS6DoTyYUWdWBiJ7DpVNm9iJ5xBhr1yNVTC3SNzZkIuxf5GoboiybTveEZ+TuWSAmmzzIJtqK+Z3AHkAbUzLa+JrDlWE+w1h621l4JlAUaAHHAWmA/sD1YgYqIiJR41ZtA24v97W/HgrXBPeeW3+CbgCGq3W4BJYIiIp4o0mTQWpsMLAT6ZdvUD9fzl9NzU6y1f1tr04ARwDRr7VE9gyIiIpIHPe+F8Gj3eONCWDEteOdKOezKSKQlu3btNtDr/pyfIyIiQePFbKLjgSuMMSONMc2MMROAOsB/AYwxbxhj3sjY2RjTxBhzqTGmsTGmozFmCtASUBEiERGRgqpYFzpe7W9/+xCkpQbnXDNGw/YV7nFkWVdGIiIqOOcSEZETKvJk0Fr7HnAbcD+wCOgODLTWrvPtEudbMoTjylEsBr4GYoCu1tq1RROxiIhICdc9AaLKu8c7VsKSKYV/jpVfwfxJ/nb/x6Ba48I/j4iI5JoXPYNYaydaaxtYa6Ottadba2cFbOtpre0Z0F5urW1nrS1rra1orR1qrV3pRdwiIiIlUrmq7t69DN8/BinZqzoVwIFt8OmN/nbTQXDa5YV3fBERyRdPkkEREREJMZ1vgLLV3ON9f8OCVwrnuNbCJzfAoR2uHVsLBj8LxhTO8UVEJN+UDIqIiAhEx0KPu/3tWU/CkX0FP+68l+CPr/3tc//reiJFRMRzSgZFRETEOf0KqOS7bf/wLpjzn4Idb+tSN2lMhi43wcm9CnZMEREpNEoGRURExImIhl6j/O05z8OBfJb0TTniKyOR5Nq1WkGfBwoeo4iIFBolgyIiIuLX6gKo0dw9Tj4AiU/l7zjfPAjblrnHETG+MhLRhROjiIgUCiWDIiIi4hcWnrUHb8ErsHvd8fc/ltVfw8//9bfPegSqn1o48YmISKFRMigiIiJZNekP9Tq5x2nJMPPx3D/3wHY3e2jmsQZA+6sKNz4RESkUSgZFREQkK2Ogz4P+9uJ3YeuyEz/PWvjsJji4zbVja8KQ/6iMhIhIiFIyKCIiIkdr0A1O6edrWPju4RM/Z/7LsOorf3voRChXLSjhiYhIwSkZFBERkWMLvHdw5RewYd7x9922HGbc7293vgFO6Ru82EREpMCUDIqIiMix1W4NLc/3t78Z44aCZpea5MpIpB5x7Zotsw4zFRGRkKRkUERERI6v1z8hLMI9Xvcj/PHt0ft8Mxa2/u4eR8TAsJchMqboYhQRkXxRMigiIiLHV/VkOO1yf/vbMZCe7m//8S3Mfd7f7vcQ1GhWZOGJiEj+KRkUERGRnPW4GyLKuMdbfoOlU93jgzvhk+v9+zU+EzpeXfTxiYhIvigZFBERkZyVrwWdA5K+7x/BpKe6MhIHtrp15arDkOdVRkJEpBhRMigiIiIn1u1WiKnkHu9aQ+slY2Hll/7tQyZCbA1PQhMRkfxRMigiIiInVqYSdL89s1l5zxL/to7XQpMziz4mEREpECWDIiIikjsdr4HYWlnX1WgO/cZ6E4+IiBSIkkERERHJnaiy0PMefzs82ldGoox3MYmISL4pGRQREZHca3cptBxGUlRlGDoRarbwOiIREcknJYMiIiKSe+GRcP6rzOk6GVqd73U0IiJSAEoGRURERERESiElgyIiIiIiIqWQkkEREREREZFSSMmgiIiIiIhIKaRkUEREREREpBRSMigiIiIiIlIKKRkUEREREREphZQMioiIiIiIlEJKBkVEREREREohJYMiIiIiIiKlkJJBERERERGRUkjJoIiIiIiISCmkZFBERERERKQUUjIoIiIiIiJSCikZFBERERERKYWMtdbrGILGGLMdWOd1HMdQDdjhdRAiJZyuM5Hg0jUmEny6zqQw1LfWVj/WhhKdDIYqY8wCa217r+MQKcl0nYkEl64xkeDTdSbBpmGiIiIiIiIipZCSQRERERERkVJIyaA3XvI6AJFSQNeZSHDpGhMJPl1nElS6Z1BERERERKQUUs+giIiIiIhIKaRkUEREREREpBRSMigiIiIiIlIKKRnMxhhznzFmvjFmnzFmuzHmc2NMy2z7GGPMGGPMJmPMYWPMTGNMi2z7jDLG/GiMOWiMOeaNmcaYPsaYn4wx+40xW4wx44wxEdn2aWWM+cF3no3GmAeMMSZg+wXGmAXGmD2+cy0yxlxemO+JSGEqhtdYpG/dn8aYI8aYxcaY/oX5nogUtsK4zowxDYwxrxhj1vi2rzHGPGaMKZPtOHG+4x80xuwwxjxrjInKtk8PY8xC3zW0xhhzXbbtNxpjlvji3WeMmWOMOTsY741IYSiG11h5Y8wzxph1vnP9ZIzpEIz3RooXJYNH6wlMBLoCvYFU4BtjTJWAfe4G7gBuBjoA24CvjTHlA/aJBqYCzxzrJMaYNsCXwNdAO2A4cA7weMA+FXzbt/rOcytwF5AQcKidwMNAZ6A18BrwijFmYF5fuEgR6UnxusYeBq4HbgGaA/8FPjbGtMvrCxcpQj0p+HXWFAjH/ftv4dvvMmBCxgGMMeHAF0B5IB64CDgfeCpgn4a4a/En3LX4GPCcMWZYQCx/A/cApwHtge+AT4wxrQv2NogETU+K1zX2MnAWcDnQCpjhi/ekgr0NUuxZa7XksACxQBow2Nc2wGZgVMA+ZYD9wLXHeP757m0+av2jwK/Z1g0GDgPlfe3rgX1AmYB97gc24psJ9jgx/wI85vV7p0VLbpZQv8aATcCt2Y7zEfCW1++dFi25XQp6nQXscwOwM6A9AEgH6gWsuwQ4AlTwtccBq7Md52Vgzgli3pVTLFq0hNISyteY77ypwJBs+ywEHvb6vdPi7aKewRMrj+tB3e1rNwRq4X5RAcBaexiYhft1KLeicRdyoMNADHC6r90FSPQdP8N0oA7QIPsBfcMR+gCn+uIRKQ5C/Ro73nG65yEWEa8V1nVWIeAY4K6h5dbaDQHrpuOum8DrbAZZTQfaG2Mis5/AGBNujBmB+3L9U84vSyRkhPI1FoHrgdRnmRxFyeCJTQAWAXN87Vq+v1uz7bc1YFtuTAc6GWMuMcZE+LrpH/Btqx1wrmOdJzAOjDEVjTEHgGTcUIJbrLX/y0MsIl4K9WtsOnCbMeZUY0yYMaYfcF7AMUSKgwJfZ8aY+sCduKFxGY51De3A9ZDUymGfrbgvqNUCjt/K91mWhBuOfa619recXpRICAnZa8xau98X1/3GmJN8P7hcgksi9VlWyikZzIExZjzuF5Nh1tq0wjy2tXYG7oJ/HvdLzSrceG9wwwHyYj/QFjcefRQw3tdDKBLSisk1diuwEliG+8HlP7h7c/N6nYp4ojCuM2NMTeAr3D22TxdieIFW4j7LOgEvAK9nn5BDJBQVk2vsUtzn1t+4H1xuAd5Fn2WlnpLB4zDGPI27Sbe3tXZNwKYtvr81sz2lZsC2XLHWjgcqAXG4X0c/9W3KON+W45wnMA6stenW2j+stYustU8BHwD/zEssIkWtuFxj1trt1tqhQDmgPu6G/wMBxxAJWYVxnRljagHfA78Dl1prA2fvPdY1VA03JG1LDvvUxN3DtCNjhbU22fdZttBaex+ul+X2E71GES8Vl2vMWvuntbYHbvh1PWttRyASfZaVekoGj8EYMwH/hb0i2+a/cBddv4D9Y3AzPOX53gbrbPKNI78I2ICbAAZcl3687/gZ+uEmtFibw2HDcGPJRUJScbzGrLVHrLUbccNuhuFPLEVCUmFcZ8aY2sBMYDlwkbU2Ndtx5gDNjDF1A9b1w/U8LAzYp1+25/UDFlhrU3J4Cfosk5BWHK8xa+1Ba+1mY0xl3Oyi+iwr7byewSbUFtyQsn24aYJrBSyxAfvcA+zF3TfUEpiC+/JYPmCfONxwlzsB63vcNttx7sJN79sCGI0bgjY0YHtF3P9IpvjOc54vtjsC9hkF9AUaAc1wUxinANd5/V5q0XKspRheY5186xvhPsS/xf2SWsnr91KLluMthXGd4SZSWoX7olov23HCffuEA7/hSkG0830ebQSeCzhPQ+AgrgxMM2Ck71ocFrDP477rq4Hvmn0MN3xtgNfvpRYtx1qK4TV2Fm5m0oa4RHERMBeI9Pq91OLt4nkAobbgvlQeaxkTsI8BxuCmDD4C/AC0zHacycc5Ts+Afb4D9uBmc5p7rA8934fiLN95NgMPElBWwveBudp3jF24X5su8vp91KLleEsxvMZ64O4XPIIbbvMGUMfr91GLlpyWwrjOgCtyOE6DgP3igGnAIVzt22eB6Gzx9MD1yCfhekyuy7Z9MrDOt30b8A1wltfvoxYtx1uK4TV2IfCnb/tm3P3vFb1+H7V4v2TU0RIREREREZFSRPcMioiIiIiIlEJKBkVEREREREohJYMiIiIiIiKlkJJBERERERGRUkjJoIiIiIiISCmkZFBERERERKQUivA6ABERkVAUPy3hCuC1gFWHgO3Ar8C7wAeJg8bnqT5T/LSEtsBQ4NnEQeN3FUqgIiIi+aSeQRERkZxdAHQBBgKjcUWb3wW+jp+WUCaPx2oLPAhUKcwARURE8kM9gyIiIjlblDho/B8B7TfjpyV8AHwAPAHc7E1YIiIiBWOszdMIFxERkVIhYJho42zJYMb2j4EBQJXEQeMPxU9LGAsMBk4BkoElwD8TB42fm+142TVMHDR+bfy0hAjgLuByoCGwE9cDOSpx0PgjhfzyRERENExUREQkn74EooH2vvZJwNPAEOAKYBswK35aQivf9i+Ah32PM4aedgE2+9a9BdwPvAOcDTwGXAW8HcwXISIipZeGiYqIiOTPet/f2gCJg8aPzNgQPy0hHPgKWAqMBG5NHDR+e/y0hD99u2QZeho/LSEeGA5cnjho/Bu+1d/ET0vYBbwVPy2hbeKg8YuC+mpERKTUUTIoIiKSP8b31wLET0voC4wCWpN1gpi/cnGs/rihpR/6hotmmOH7ewawqCDBioiIZKdkUEREJH/q+f5ujp+WcBpu2Oh03NDOzUAa8DIQk4tj1QCigIPH2V61YKGKiIgcTcmgiIhI/pwNHAEW4noEU4HzEgeNT8nYIX5aQmVgTy6OtdN3rPjjbN9UoEhFRESOQcmgiIhIHsVPSxgGnANM8M0kWhbXE2gD9ukNxJF1mGiS72/2+oRfAfcAFRMHjf82aIGLiIgEUDIoIiKSs7bx0xKq4YZxxgGDcLOBfg3c59vnK+A2YHL8tITXgCa4AvUbsx1rme/vjfHTEl4HUoAliYPGz4yflvAu7p7B8cA8IB1ogCt2f0/ioPGrgvPyRESktFJpCRERkZx9AMzB3Q/4CK6cxAigf0b9v8RB46cDtwDdgGnAlcBlQJb6hImDxi8GxuDqEc4G5gN1fJsv8W07H/gU+BC4CVgNbA3SaxMRkVJMRedFRERERERKIfUMioiIiIiIlEJKBkVEREREREohJYMiIiIiIiKlkJJBERERERGRUkjJoIiIiIiISCmkZFBERERERKQUUjIoIiIiIiJSCikZFBERERERKYX+H8KMheIkHLUwAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,7))\n",
    "\n",
    "plt.plot(returns4['Port_return_Cum'],label='Portfolio', linewidth=3)\n",
    "plt.plot(returns4['T4812A'],label='TCB AI Electric Vehicle' , linewidth=3)\n",
    "\n",
    "\n",
    "ax.xaxis.set_major_locator(ticker.MultipleLocator(6))\n",
    "\n",
    "plt.title('Portfolio V.S TCB AI Electric Vehicle',size = 18, color = 'mediumseagreen')\n",
    "plt.xlabel('Date', fontsize=16, color = \"mediumseagreen\")\n",
    "plt.ylabel('Cumulated Return', fontsize=16, color= \"mediumseagreen\")\n",
    "plt.grid(True)\n",
    "plt.legend(fontsize=\"x-large\")\n",
    "plt.xticks(fontsize=14 )\n",
    "plt.yticks(fontsize=14 )\n",
    "# plt.savefig(\"T4812A.png\",dpi=150)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "Geo_a_return = (returns4['Port_return_Cum']['202012'])**(12/len(returns4))-1\n",
    "Geo_a_return_T4812A = (returns4['T4812A']['202012'])**(12/len(returns4))-1\n",
    "\n",
    "STD_return  = Port_return4.std()*np.sqrt(12)\n",
    "STD_return_T4812A  = df_T4812A['Return_M'].std()*np.sqrt(12)\n",
    "\n",
    "Sharpe = Geo_a_return / STD_return \n",
    "Sharpe_T4812A = Geo_a_return_T4812A / STD_return_T4812A \n",
    "\n",
    "#計算MDD\n",
    "D = returns4['Port_return_Cum'].cummax() - returns4['Port_return_Cum']\n",
    "MDD = D.max()*1\n",
    "d = D / (D + returns4['Port_return_Cum'])\n",
    "mdd = d.max()\n",
    "\n",
    "D = returns4['T4812A'].cummax() - returns4['T4812A']\n",
    "MDD = D.max()*1\n",
    "d = D / (D + returns4['T4812A'])\n",
    "mdd_T4812A = d.max()\n",
    "\n",
    "#投組勝率\n",
    "Odd =sum(Port_return4>0)/len(returns4)\n",
    "Odd_T4812A =sum(df_T4812A['Return_M']>0)/len(returns4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_performance=pd.DataFrame([\n",
    "                  [Geo_a_return,STD_return ,Sharpe,mdd,Odd ],\n",
    "                  [Geo_a_return_T4812A,STD_return_T4812A ,Sharpe_T4812A,mdd_T4812A,Odd_T4812A ],\n",
    "                 ])\n",
    "df_performance.columns = [ 'ER','STD','Sharpe','Mdd','Odd' ]\n",
    "df_performance.index =  ['Portfolio','T4812A']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "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>ER</th>\n",
       "      <th>STD</th>\n",
       "      <th>Sharpe</th>\n",
       "      <th>Mdd</th>\n",
       "      <th>Odd</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Portfolio</th>\n",
       "      <td>0.29</td>\n",
       "      <td>0.23</td>\n",
       "      <td>1.26</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T4812A</th>\n",
       "      <td>0.22</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ER   STD  Sharpe   Mdd   Odd\n",
       "Portfolio  0.29  0.23    1.26  0.19  0.64\n",
       "T4812A     0.22  0.26    0.83  0.21  0.64"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_performance.round(2)\n",
    "# dfi.export(df_performance.round(2), 'T4812A_table.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 大盤比較"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "TAIEX = pd.read_excel(\"TAIEX.xlsx\", header=0,engine='openpyxl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "TAIEX['年月'] = TAIEX['年月'].astype('str')\n",
    "TAIEX['年月'] = TAIEX['年月'].str.replace('-','')\n",
    "TAIEX['年月'] = TAIEX['年月'].str[0:6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [],
   "source": [
    "TAIEX.set_index(\"年月\", inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [],
   "source": [
    "TAIEX['Return_M'] = TAIEX['收盤價(元)_月'].pct_change()\n",
    "TAIEX['Return_M_Cum'] = ( TAIEX['Return_M']+1).cumprod()\n",
    "TAIEX.iloc[0,2] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0.8, 1. , 1.2, 1.4, 1.6, 1.8, 2. ]),\n",
       " [Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, '')])"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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RERF/cZ8VHNW1OYEBlh9HU3UKBuuh++67j//973+88cYbbNq0iddee41XXnmF+++/v9LndunShT/++IO9e/eSnJxc7nG33XYbaWlpTJ06ldWrV/Pnn38yZcoUYmNjiY2N9Wic3jiHiIiIiIi/zKvD6wVBwWC9dPPNN/Poo4/y+OOP07dvX5566imefPLJEsVjyvPss8+yZMkSOnfuTMuWLcs9rnXr1vz888/s3r2bESNGEBcXR//+/fniiy88Hqc3ziEiIiIi4g8Oh838rSnF23VtvSCAZdt2zV7QssYBdwHDgLbANbZtT6vkOacBDwP9gVxgDnC3bdsbK3re8OHD7cWLF5f7+Lp16+jTp09Vhu8V3loz2JD563sn3jVz5kwmTJjg72GI+JXeByJ6H0jdtG5fGmc8nwRA88gQFv1zEgHHmSbqi/eCZVlLbNseXtZj/pgZbASsBv4KZFd2sGVZXYDpQBIwBJgEhAPf+3CMIiIiIiIi5SqxXrBb8+MOBP2hxquJ2rb9Pc5AzrKsaR48ZRgQDNxn23ah83lPAL9bltXCtu3yF7aJiIiIiIj4gPt6wdFd616KKNSN1hKLgHzgL5ZlvQlEAFcDi8oKBC3LugG4AcyatJkzZ5Z74ujoaNLT030x5goVFhb65br1SU5OToXfW6kbMjIy9H2UBk/vAxG9D6TuKXTYzNnk6t8ddHgLM2duO+7z1vR7odYHg7Zt77As6xTgc+AlTGrrMuCMco5/HXgdzJrBinJu161b55e1e1ozePzCwsIYMmSIv4chx0lrRET0PhABvQ+k7lmx6yjZP88BoE3jMC45cyKWdfxpojX9Xqj11UQty2oDvAW8B4wAJgDpwGeWZdX68YuIiIiISP3ivl5wTLfmXgkE/aHWzwwCtwKZtm3fU7TDsqwrgV3AGOBPfw1MREREREQannlbSxaPqavqwsxaBFBYal/Rdl0Yv4iIiIiI1BN5BQ4WbXP1F6yLzeaL1HgwZVlWI8uyBluWNdh5/Y7O7Y7Ox5+wLOs3t6d8Bwy1LOtflmX1sCxrKPAOZmZwSU2PX0REREREGq4Vu4+SnW/mpjo2i6B90wg/j6j6/DGzNhxTAGYZpl/gI877jzofjwG6FR1s2/bvwOXAZOdxP2Gqi55u23ZmzQ1bREREREQaunlu6wXrakuJIv7oMzgTKHeFpW3bU8vY9wnwie9GJSIiIiIiUrm5bv0Fx3Sv28Gg1tzVQZZlVXjr3Llz8bGffvopgYGBXHTRReWe64MPPije7ty5c5nnjIuLA+DQoUO0adOGf/7znyXOc/ToUTp16sQdd9zh/RcsIiIiIlIL5OQXsnTH0eJtzQxKjdu3b1/x/blz53LBBRewdOlSYmJiAAgMDCx+/LXXXuPee+/l//7v/zh48CCtWrWq9Pz33nsvd955Z4l9YWFhALRs2ZK33nqLyZMnc8YZZzB27FgAbr75Zho1asTTTz99vC9PRERERKRWWrLjCHmFDgC6t2pEq8Zhfh7R8VEwWAe1adOm+H6zZs0AE6S57wfYtGkTc+fO5fPPP2fZsmW888473HvvvZWev1GjRsecy91ZZ53F9ddfz1VXXcWKFSuYPn06X375JQsWLCgOGkVERERE6pv6tF4QFAyW9HB0jVwmqtzrp3r1Oq+//jpnnXUWzZs3Z+rUqfzzn//knnvu8UpTzGeffZbff/+dK6+8kpkzZ/Loo48yZMgQL4xaRERERKR2KrFesA63lCiiNYP1VF5eHu+++y5Tp04FYPLkySQnJ/Pbb79V/ETg3//+N40aNSpxK53+GRERwYsvvsi3335L7969ueeee3zxMkREREREaoWM3AJW7HZN3ozSzKDUVl9//TUBAQGcccYZgFnzd8kll/Daa68xadKkCp976623csstt5TY17z5sT/sr7/+OpGRkWzcuJG9e/fSvn17770AEREREZFaZNH2FAodNgB9YhrTNDLEzyM6fgoG3Xk5TbM86enpREWVmyzqFa+99hoHDx4ssYbPtm0CAwMrLSTTrFkzunfvXuH5p02bxowZM5g3bx433ngj11xzDT///LNXUlBFRERERGob9/WC9SFFFJQmWi9t2rSJmTNn8tVXX7F8+fLi24oVK+jUqRPvvPPOcZ1/+/bt3HHHHTz++OMMGTKE999/n7lz5/Liiy966RWIiIiIiNQu9W29IGhmsF56/fXX6dq1K+eee+4xj1100UW88cYbFRaSycjIYP/+/SX2BQcH07x5cxwOB1OmTGHEiBH87W9/A6BXr148/fTT3H333Zx66qn06tXL669JRERERMRfUrPyWbM3DYDAAIuRXZr5eUTeoZnBeqaocEx5TeYvueQStmzZUmEhmaeeeoqYmJgSt/HjxwPw5JNPsnr1aqZNm1YimLz11lsZN24cU6ZMoaCgwLsvSkRERETEj+ZvO4xtlgvSv100UWHB/h2Ql2hmsI6bMGECdtFPJhASEsLBgwfLPX7QoEEljne/DyYFtCL3338/999/f5mP/fjjjx6MWERERESkbqmP6wVBM4MiIiIiIiIVqo/rBUHBoIiIiIiISLkOpeey8UAGAMGBFsM71Y/1gqBgUEREREREpFzzt7pSRId0aEp4SKAfR+NdCgZFRERERETKMddtveDoepQiCgoGjymgIrWfvmciIiIiUlPcZwbr03pBaODBYHBwMNnZ2f4ehlRRdnY2wcH1o5yviIiIiNRee49msy05E4DQoAAGd2zi3wF5WYMOBlu1asWePXvIysrSbFMdYNs2WVlZ7Nmzh1atWvl7OCIiIiJSz7m3lBjRuRmhQfVnvSA08D6DjRs3BmDv3r3k5+fX2HVzcnIICwursevVJ8HBwbRu3br4eyciIiIi4ivzttbf9YLQwINBMAFhTQcWM2fOZMiQITV6TRERERER8Zxt2yVmButjMNig00RFRERERETKsjMliz1HTX2RRqFBDGwX7ecReZ+CQRERERERkVLcZwVHdmlGUGD9C53q3ysSERERERE5Tu79BetbS4kiCgZFRERERETc2LZdIhgc1VXBoIiIiIiISL23+WAGyRm5AESHB9M3pn5WslcwKCIiIiIi4qZES4muzQkIsPw4Gt9RMCgiIiIiIuJm7ub63VKiiIJBERERERERJ4fDZv62+l88BhQMioiIiIiIFFu3P42jWfkAtGgUSvdWjfw8It9RMCgiIiIiIuI0r1RLCcuqn+sFQcGgiIiIiIhIMfeWEvV5vSAoGBQREREREQGgoNDBwm0pxdv1eb0gKBgUEREREREBYNWeVDJyCwBo1yScjs0i/Dwi31IwKCIiIiIiQskU0VFd6/d6QVAwKCIiIiIiAhxbPKa+UzAoIiIiIiINXm5BIYt3uNYL1vfiMaBgUEREREREhOU7j5KT7wCgS4tI2jYJ9/OIfE/BoIiIiIiINHil1ws2BAoGRURERESkwZu3tWGtFwQFgyIiIiIi0sBl5xWybOeR4m3NDIqIiIiIiDQAi3ekkF9oA9CzdSNaRoX6eUQ1Q8GgiIiIiIg0aCVbSrTw40hqloJBERERERFp0NyLxzSElhJFFAyKiIiIiEiDlZaTz8rdRwGwLBjVRcGgiIiIiIhIvbd4ewoOs1yQfm0bEx0R7N8B1SAFgyIiIiIi0mAt2JpSfL8hzQqCgkEREREREWnA5m9zBYMnNJCWEkUUDIqIiIiISIOUkVvA6j2pgFkvOLJzMz+PqGYpGBQRERERkQZp8fYUCp0LBvu0aVjrBUHBoIiIiIiINFALSqSINqxZQVAwKCIiIiIiDdSCra7+gic0sOIxoGBQREREREQaoKy8AlbuTi3eHtlFM4MiIiIiIiL13tIdRylwrhfs1TqKZpEhfh5RzVMwKCIiIiIiDc6CbW4pog1wvSAoGBQRERERkQbIvdl8Q1wvCAoGRURERESkgcnJL2T5rqPF2w1xvSAoGBQRERERkQZm2c6j5BU6AOjWMpKWUaF+HpF/KBgUEREREZEGpeR6wYaZIgoKBkVEREREpIGZX6K/YMNMEQUFgyIiIiIi0oDkFhSybOfR4u1RmhkUERERERGp/1bsSiW3wKwX7NIiktaNw/w8Iv9RMCgiIiIiIg3GAqWIFlMwKCIiIiIiDcaCbW79BRtos/kiCgZFRERERKRByC90sGTHkeLthtpsvoiCQRERERERaRBW7k4lO78QgA7NwmnbJNzPI/IvBYMiIiIiItIglOgv2MBnBUHBoIiIiIiINBALtrqtF2zgxWNAwaCIiIiIiDQABYUOFm93BYMNub9gEQWDIiIiIiJS763Zm0Zmnlkv2DY6jPZNG/Z6QfBDMGhZ1jjLsr61LGuPZVm2ZVlTPXiOZVnWnZZlrbcsK9eyrH2WZT1ZA8MVEREREZF6oMR6wa7NsSzLj6OpHYL8cM1GwGrgPefNE88CccDdwCogGojxyehERERERKTemb/VPUVU6wXBD8GgbdvfA98DWJY1rbLjLcvqBdwODLRte53bQ8t8MkAREREREalXCh02i9ybzauSKOCfmcGqmgxsBU63LOs7TGrrLOBu27YPlj7YsqwbgBsAWrduzcyZM2twqJ7JyMioleMSqWl6L4jofSACeh+I721PLSQ9twCAJqEW21YtZHstTBOt6fdCXQgGuwKdgEuBqYANPAPMsCxrtG3bDveDbdt+HXgdYPjw4faECRNqdLCemDlzJrVxXCI1Te8FEb0PREDvA/G9N5O2AibJcFzvGCZOHOLfAZWjpt8LdSEYDABCgSm2bW8EsCxrCrABGAEs8OPYRERERESkllvgniKq9YLF6kJriX1AQVEg6LQJKAQ6+mdIIiIiIiJSFzgcNou2a71gWepCMDgHCLIsq5vbvq5AILDDP0MSEREREZG6YMOBdI5m5QPQolEo3VpG+nlEtYc/+gw2sixrsGVZg53X7+jc7uh8/AnLsn5ze8qvwFLgbcuyhliWNQR4G5MeuriGhy8iIiIiInXIgq1u/QW7NFN/QTf+mBkcjmkLsQwIBx5x3n/U+XgMUDwL6CwQEwccBGYDPwG7gcmli8eIiIiIiIi403rB8vmjz+BMoNxw3LbtqWXs2wdc5LtRiYiIiIhIfWPbNgvVX7BcdWHNoIiIiIiISJVtPpjB4cw8AJpGBNOjVSM/j6h2UTAoIiIiIiL10ny39YIjuzQjIEDrBd0pGBQRERERkXppvluK6KiuShEtTcGgiIiIiIjUO7Zts2Cr1gtWpEoFZGIT49tgGr2HlX4sKS5htrcGJSIiIiIicjy2JmeSnJELQHR4ML3bRPl5RLWPR8FgbGJ8O+B9YHwZD1uAjWkCLyIiIiIi4nfus4IjOmu9YFk8nRl8BRgA3AOsAnJ9NiIREREREZHjtGCbq3jMKF/3F9w5H6JioGkn317HyzwNBmOBO5LiEt735WBERERERESOV42uF7Rt+PZ2SN4IXcbB2S9Asy6+u54XeVpAJhs46MuBiIiIiIiIeMPOlCz2p+UAEBUaRN+2jX13sd2LTSAIsGcpNGrlu2t5mafB4BvAFF8ORERERERExBvcZwWHd25KoC/XCy7/wHW/37kQEum7a3mZp2mie4ApsYnxvwE/ACmlD0iKS3jbmwMTERERERGpjvlu6wVP8GV/wbwsWPWla3tI3Zo/8zQYfNX5tTMwsYzHbUDBoIiIiIiI+F3J9YI+LB6zbgbkpZv7zbtDhxN8dy0f8DQYrBsrIEVEREREpEHblZLFnqPZAESEBNK/XbTvLuaeIjr4crDqVvuKSoPB2MT4EOBO4KOkuIRFPh+RiIiIiIhINS3Y5r5esBnBgZ6WSamiIztg22xz3wqAQZf55jo+VOm/TFJcQh5wIxDu++GIiIiIiIhU34KtbusFfZkiuuJj1/1uJ0Hjtr67lo94GiYvwzSdFxERERERqbXcZwZ91mze4YDlH7q2B1/hm+v4mKfB4N+Bu2IT4+NiE+PrViKsiIiIiIg0CPtSs9mZkgVAWHAAA9o18c2FdvwJR3ea+2FNoNeZvrmOj3laQOZzIBqYDuTHJsYfwlQQLWInxSV08vbgRERERETEt9bvT+O3dQc5e2BbOjaP8Pdwjot7FdFhnZoSEuSj9YLL3GYFB14MwWG+uY6PeRoM/kbJ4E9EREREROq4/EIH176ziL2pObw2awuf3jiaPjGN/T2salvg3l+wi4/6C+akwtrpru06miIKHgaDSXEJU308DhERERERqWEbD6SzNzUHgLScAqa8tZAvbhpN5xaRfh5Z9dRIf8E1X0OBaV1B6/4QM8g316kBPpo3FRERERGR2m7NnrQS28kZuVz51gL2OwPEuuRgWg5bkzMBCAkKYFCHJr650LJShWPqWG9Bdx7NDMYmxl9V2TFJcQnvHf9wRERERESkpqzem3rMvt1Hspny1gI+u3E0TSND/DCq6nGvIjqkQxPCggO9f5FDG2H3QnM/IMisF6zDPF0zOK2c/e7rCBUMioiIiIjUIav2uILBqWM688H8HRQ4bDYdzGDqOwv58PpRNAr1NGTwrxLrBbv6aL2gezuJnqdDZAvfXKeGeJom2qWM23DgEWATcIJPRiciIiIiIj5RUOhg3T5XmuitE7uTcMng4qzHFbtTuf7dxeTkF/pphFUz32294ChfrBcsLIAVn7i2h1zp/WvUME8LyOwoY/cOYKmz72A8cLk3ByYiIiIiIr6zNTmTnHwHAG0ah9EyKpRzBrUlPSeff369GoB5Ww9z+8fLeOWKoQQF1t5yI8kZuWw+mAFAcKDFkI5NvX+RLb9Dxn5zP7IVdD/F+9eoYd74jiYBZ3nhPCIiIiIiUkNW7XaliPZv52onccUJnbjn9F7F27+sPcA9X6zE4ai9neYWuq0XHNyhCeEhPlgvuOx91/1Bl0Jg3UifrYg3gsFRQIYXziMiIiIiIjXEvXhM/3bRJR67ZUJ3bhzftXj7q2V7eDRxLbZdOwPCBVt93F8w8zBs+MG1XQ9SRMHzaqL/KmN3CNAfMyv4ojcHJSIiIiIivuXeVqJ/2+hjHv/H6b1Jy87n44W7AJg2dzvR4cH87ZSeNTZGT7lXEj2hqw/WC676HBz55n674dCyV8XH1xGezm0+XMa+XMy6wceAJ7w1IBERERER8S2Hw2ZNBTODAJZl8Z9zB5CWU8B3K/cB8Pxvm4gOD+basV1qbKyVOZKZx/r96QAEBVgM6+SD9YLLP3DdH3KF98/vJ54WkKm9q0VFRERERKRKth3OJDPPVAlt0SiU1o1DyzwuMMDi/y4eTEZOAbM2HgLg0cS1RIUFcdHwDjU23iKZuQVsPJDOxgPprN+fzgbnrciA9tFEhHh5Ld++lbB/lbkfFAb9L/Du+f3I0zTRccDSpLiEY9YGxibGNwKGJsUlzPb24ERERERExPtW7ylZPMYq6idRhpCgAF69chhT3lrA4h1HALj3y5VEhQVzev82PhlffqGDbcmZrN+fzsb9zsDvQBq7UrIrfN6Ybj5YL+jeW7DP2RB27CxqXeVp2PwHMBpYWMZjvZyP+6Bkj4iIiIiIeFuJYLCM9YKlhYcE8tbUEVz2+nzW7kvDYcMdHy/jnWtGcGL36jdet22bg+m5rNmbWmKmb8uhDPILPS9WEx4cyKiuzbj2RC+nrxbkwcrPXNuD60+KKHgeDJb/UQGEAnWjE6WIiIiIiLDavXhMGesFyxIdHsy7147k4tfmsS05k7xCB9e/t5gP/3KCR339HA6bnSlZrN6bypq9aazZm8bavakkZ+R5PO7AAIuuLSLp2SaK3q2jzNc2UXRoGkFAQEUhSzVt/AGyncVpojtAl/Hev4YflRsMxibGdwa6uu0a7kwJdRcOXAvs9P7QRERERETE22zbLtVWonEFR5fUMiqU968byUWvzmNfag5ZeYVMfWcRn904ml5tooqPyy90sPlghjPoS2XNnjTW7ksjI7fA42u1axJOrzZR9GxtAr5ebaLo2jKS0KAaTEhc5lY4ZvDlEFC/SqlUNDN4NfAQYDtv/6PkDKHt3C4AbvXVAEVERERExHt2pWSTnmOCsiYRwbRrEl6l57dvGsH7153Axa/NIyUzj9TsfKa8tYCbJ3Rj44F01uxNY/3+dPIKHB6dLzIkkL5tG9MnpjG9nDN9PVpH0TgsuMqvzavS9sHmX13bgy/331h8pKJgcBowExPw/Y4J+NaWOiYX2JgUl5CCiIiIiIjUeqtKrResqHhMebq3asS714zksjfmk5FbwMH0XB6ZUTpUOFbzyBD6tm1Mv7bR9G9nvnZq5qMUz+O18hOwnQFt51ho2tmvw/GFcoPBpLiEHZg+gsQmxk/EVBNNL+94ERERERGp/VZX0l/QUwPaR/PW1cO56u2F5JYxC9iuSTj9nIFfv7aN6deuMW0ah1Ur+Kxxtg3L3KqI1rPCMUU87TM4CyA2MX4gMA5oDryWFJewPzYxvjtwQIGiiIiIiEjtV7qtxPE4oWtzpl0zkpdnbqZpREjxbF/fmMY0jQw53qH6z+5FcHiTuR8SBX3P8e94fMTTPoOhwAfA+Zi0URuYAewHngY2Av/w0RhFRERERMQLbNuucluJyozu1pzRvujv50/uhWP6nQshkX4bii95Wg7nMWASMAVoTclCMj8Ap3l5XCIiIiIi4mV7U3M4kpUPQFRYEJ2aR/h5RLVQXhas/sq1PWSK/8biY54Gg5cBDyTFJXwElC4Wsw3o7M1BiYiIiIiI97nPCvZr27hurN+raetmQJ5zBVzzHtBhpH/H40OeBoPNgXUVnCPUO8MRERERERFf8XaKaL207H3X/cGXQz0OmD0NBrcBo8t5bCSwwTvDERERERERX3EPBge0VzB4jCPbYXuSuW8FwKDL/DocX/M0GHwP+EdsYvwVQFH3R9vZcuJvwNu+GJyIiIiIiHjP6r1pxff7aWbwWMs/dt3vdjI0jvHfWGqAp8Hg08B3wPvAEee+P4FfgR+T4hL+54OxiYiIiIiIlxxIy+FQei4AESGBdGlRPytkVpvDAcs/cm0PqZ+9Bd152mewELg0NjH+JUzl0FbAYUwgOMuH4xMRERERES8oXTwmMKD+roWrlu1JkLrT3A9vCr3O9O94aoBHwWCRpLiEJCDJfV9sYnwb4N6kuIS/eXNgIiIiIiLiPav3KEW0Qss/dN0fcDEE1f8amZUGg7GJ8a2AjsD2pLiEZLf97TCN5q/DrCNUMCgiIiIiUkut3utWSbSdgsESclJh7beu7QaQIgoVrBmMTYxvEpsYPx3YBywA9sYmxj/lfOxBYCNwC5AIDKiBsYqIiIiISDWVqCSqYLCk1V9BQba533oAxAzy73hqSEUzg48BZwJvAUuBLsBNsYnxfYA4YCbwt6S4hBW+HqSIiIiIiFRfckYu+1JzAAgNCqBbSxWPKcE9RbSBzApCxcFgHPBkUlzCg0U7YhPj5wFfAZ8kxSVc7uvBiYiIiIjI8Vvj1lKiT0xjggI9bSrQACRvgt2LzP2AYLNesIGo6KegLfBbqX2/Or++4ZvhiIiIiIiIt7mniPZv19iPI6mF1nztut/zNIhs7r+x1LCKgsFAIKvUPmciLamIiIiIiEidoPWCFXAvHNPvPP+Nww8qqyY6PDYxvpHbdgBgAyNiE+ObuB+YFJfwu5fHJiIiIiIiXuBeSVRtJdwc3gIHVpn7gaFmZrABqSwY/B9QVjfKV5xfbefjNmYmUUREREREapGjWXnsSjEJfiGBAfRsHeXnEdUi69xmBbufDKEN69+momBwYo2NQkREREREfMK9eEyvNlGEBKl4TDH3FNE+5/hvHH5SbjCYFJcwqyYHIiIiIiIi3qfiMeU4uhP2LjX3A4Kh1+n+HY8f6GMBEREREZF6bLXbzKDWC7pZN8N1v+t4CG/qv7H4iYJBEREREZF6TJVEy9HAU0RBwaCIiIiISL2VnpPPtuRMAAIDLHq1aVgFUsqVtg92zTf3rUDoHeff8fiJgkERERERkXpqrVuKaI9WjQgLVgMAANYnuu53PrFBNZp3p2BQRERERKSeWqUU0bKtne6630BTREHBoIiIiIhIveXeVqK/gkEjMxl2zHFuWNDnbL8Ox5/KbS0Rmxj/ryqcx06KS/i3F8YjIiIiIiJeorYSZVifCLbD3O84CqLa+Hc8flRR0/mHS23bgFXGcbbzq4JBEREREZFaIiuvgC2HMgAIsKBPjIJBoGQV0b6T/TeOWqCipvPFKaSxifF9gW+B14FPgANAa+Ay4HqgYZbfERERERGppdbtS8PhnLbp1rIRESEVzQM1ENlHYNss13YDThGFimcG3b0IvJkUl/C0276dwFOxifEBwEvAyd4enIiIiIiIVM/qPVoveIwNP4CjwNxvNwyi2/t3PH7maQGZE4DF5Ty2CBjlneGIiIiIiIg3uFcS7ddWKaKAUkRL8TQYTAVOKeexU52Pe8SyrHGWZX1rWdYey7Jsy7KmVuG5PSzLSrcsK8PT54iIiIiINESr1VaipJw02PKba7sBt5Qo4mma6NvAfbGJ8Y2Az3GtGbwYuAF4vArXbASsBt5z3jxiWVYIZr3ibGB8Fa4nIiIiItKg5OQXsumga/6kr2YGYdPPUJhn7rcZAM26+Hc8tYCnweC/MFVD7wRucu6zgExMIPiwpxe0bft74HsAy7Kmefo84ClgJTALBYMiIiIiIuXasD+dQmf1mC4tIokKC/bziGoB90bzShEFPAwGk+ISHMCDsYnxzwIDgTbAPmBlUlyCxymi1WVZ1lmYiqVDgAt9fT0RERERkbpsVYn+gkoRJS8TNv3i2u6jYBA8nxkEICku4SgmTbPGWJbVFngDOM+27QzLKqvVYYnjb8CkrtK6dWtmzpzp8zFWVUZGRq0cl0hN03tBRO8DEdD7wBd+WZ1bfD8851CD//dtcWgu/QuyAciM6MCiNXuBvf4dVBlq+r3gcTAYmxjfDvg7MA5oBpyTFJewOjYx/k5gXlJcwgLfDJH3gVds2/bo/LZtv47ph8jw4cPtCRMm+GhY1Tdz5kxq47hEapreCyJ6H4iA3ge+8OyqPymq8Tg5digndm/h3wH52xeuUiWRIy6vtT9vNf1e8KiaaGxifD9gFTAFE0J3AkKcD3cC/uqT0RknAQ9ZllVgWVYB8BYQ6dy+wYfXFRERERGpc/IKHGzYn1683b9tA08Tzc+BjT+5tlVFtJinM4PPAuuA04AcIM/tsbmY4i6+MqDU9mTgn8BIYI8PrysiIiIiUudsPJBOXqEDgA7NwomOaODFY7b+AXnOyqrNukLrfv4dTy3iaZ/BscCTSXEJGZiqou4OYArKeMSyrEaWZQ22LGuw8/odndsdnY8/YVlWcQMQ27ZXu98wAaDDuX3E0+uKiIiIiDQEa/a6FY9p6LOCcGwV0UpqkDQkngaDjgoeawFkV+Gaw4Flzls48Ijz/qPOx2OAblU4n4iIiIiIOKmSqJuCPNjwvWtbKaIleBoMLgSuKeexi4E5nl7Qtu2Ztm1bZdymOh+fatt25wqeP8227UaeXk9EREREpCFZvSet+H6DDwa3z4YcZ3Ac3RHaDvHveGoZT9cM/hv4NTYx/mfgI0yq6KTYxPi/AudhKoyKiIiIiIgfFRQ6WLfPFQz2a9vYj6OpBUqkiJ6jFNFSPJoZTIpLmAWcC3QB3gYs4EkgFjjXh20lRERERETEQ5sPZZBbYFZ4xUSH0aJRqJ9H5EeFBbD+O9e2UkSP4XGfwaS4hO+A72IT47sDrYDDSXEJG3w2MhERERERqRKliLrZOReyDpv7UTHQfoR/x1MLeRQMxibG/wt4MykuYW9SXMJmYLPbYzHA9UlxCY+WewIREREREfG51XtUSbSYe4pon7MhwNNyKQ2Hp/8iDwHty3msrfNxERERERHxoxJtJdo14PWCDgesS3RtK0W0TJ4GgxWttGwK5HphLCIiIiIiUk2FDps1e11pogMacpro7oWQsd/cj2gBncb4dzy1VLlporGJ8ROAk9x23RibGB9X6rBw4CxgjfeHJiIiIiIintqWnElWXiEALaNCadU4zM8j8qMSKaJxEBDov7HUYhWtGRwPPOC8b1N2n8E8YC1wh5fHJSIiIiIiVVAiRbQht5SwbVg3w7WtFNFylRsMJsUlPAI8AhCbGO8ARiXFJSysqYGJiIiIiIjnVu12BYMNOkV071JI3WXuhzWBLmqJXh6PqokmxSWo9I6IiIiIHGPt3jSOZOUxpltzLDX09qvVbjOD/RpyMOieItr7LAgM9t9YajmP+wwWiU2MbwUck4CcFJew0ysjEhEREZE6YcmOFC59fT75hTa3TezOXaf18veQGiyHw2aNegyaFNG137q2lSJaIU/7DAYA/wFuBJqUc5hWZYqIiIg0IM/+vJH8QhuAl2du5qQ+rRjasamfR9Uw7UzJIj23AIBmkSG0jW6gxWP2r4Ij28z9kCjoNtG/46nlPE3/vBO4FXgW02bicUxwuA3YAlzvi8GJiIiISO20ZEcKc7ccLt522HDX5yvIyS/046garhIpom0bN9yU3XVus4K9ToegUP+NpQ7wNBi8BngUeMq5/XVSXMJDQB9gD9DRB2MTERERkVrqhd82H7Nv66FMEn7Z6IfRyGqliBpKEa0ST4PBrsDipLiEQqAA01+QpLiEfOA54FqfjE5EREREap2Vu48ya+MhACwLro/tUvzYG0lbWbLjiL+G1mC5t5VosJVED66H5A3mfnAEdJ/k3/HUAZ4Gg6m4isbsBdxXBwcBzbw5KBERERGpvf73u2tWMG5gW+4/sw9ju7cATP2Ou5UuWqNs22bVHvceg1UMBnfMg8R4mPkkrP8eUnebb2Rd454i2uMUCInw31jqCE+riS4D+gI/OW+PxCbGZ2NmCR8DlvpmeCIiIiJSm6zbl8Yvaw8Ub986sRuWZfHkBQM4/bkkMnIL2JqcybM/b+CfZ/X140gbjj1HszmalQ9AVFgQHZqFe/7knFT46GLITSu5P6I5tBkIMQOdXwdBs24QUIs7zilFtMo8DQafw6SKAjwEDAU+dG7vAG7z7rBEREREpDZ60W1W8LR+rendpjEA7ZtGcP+Zfbj/61UAvPnnNk7v34ZhnZRA5msl1gu2ja5a8Zi1048NBAGyDsPWP8ytSHAktOlfMkhs1ad2FGk5vAUOmJ89AkOh52n+HU8d4WnT+V/c7u+PTYwfCXQDIoB1zrWDIiIiIlKPbT6Yzver9xVv335SjxKPXzayAz+s3kfSpmRnuuhKvv9rLGHB6kDmS6vdUkQHtK9iiuiKT1z3u4yDwgLTniEv/dhj8zNh1wJzKxIQBC37mOAwZhDEDDYBY0hk1cZxvNxTRLufDKFRNXv9OqrKTecBkuISbODYElIiIiIiUm+99MeW4qVkE3u1PKZqpUkXHchp/zdb6aI1qHRbCY8d2Q475pj7ViCc/yZEtQaHw/Tq278S9q10fc08eOw5HAVmRu7AKljuTBy0AqBFTxMYxgyCtoOhzQDfBmhKEa2WcoPB2MT4cVU5UVJcwuzjH46IiIiI1EbbkzOZvnxP8fbtJ/co87h2TcL551l9uO8rpYvWBNu2S8wMVqmtxMrPXPe7n2wCQTDrApt3M7d+57mOSd/vDA5XuILEI9vLGJQDDq03t5VFM48WNO9uAsOiIDFmIIR5OF7bNumsmcmQlQJZySaVNTMZMg7CXmcJk4Ag019QPFLRzOBMwJMyQpbzOM3/i4iIiNRTr8zcgsP5l+HY7i0Y2rFpucdeOqID369SumhNOJCWS3JGHgCRIYF0ae5heqZtw4qPXduDLq38OVFtzK3nqa59OakmrXTfCtcteaMJCEteEA5vMrdVn7t2N+vmmj0MCjcBnnugl5Xi3HcYHB6sTOs6AcLL/9mUkioKBifW2ChEREREpNbafSSLL5fuLt6+/aTuFR5fVrroMz9t4IE4pYt62x8bXKmb/dpFExDgYfGY3YsgZau5H9oYep1ZvQGERUPnseZWJC/TFSDuXQ77lptZwmMCRCBli7mt+ap61y9txF+8c54GotxgMCkuYVZNDkREREREaqdXZ22hwDktOLJzM07o2rzS57RrEs4DZ/XhH8500bfmmHTR4Z2VLupN3yxzpe6e1q+N5090nxXsdy4EV6EdRWVCIqHjKHMrkpcFB9aYwHDfcti7Ag6tM2sOPT5vI4hoBhEtTOuLSOfXolvRDKN4rFoFZERERESkYTiQlsNni9xmBU+ueFbQ3SUjOvD96v3M3njIpIt+sZLv74glPETpot6w92g2C7alABBgwdmDYjx7YkEurP7StT3oMh+MrpSQCOgwwtyK5OfAwTVm9vDAapO6WhzgtTCBn3vA582AVQAPg8HYxPjfKznETopLONkL4xERERGRWuS1WVvJKzTpfYM7NGFs9xYeP9eyLJ48fwCn/d9s0nML2JacyTM/b+BBpYt6xbcr9hbfP7F7C1pFhXn2xI0/mrV+AE06QYdRFR/vK8Fh0G6YuYlfBFThOKvUrQVwItDTuS0iIiIi9UhyRi4fLdxRvH37Sd2r1tAcaNsknAfi+hRvvz1nG4u2p3htjA2Ze4ro5MHtPH+ie2/BgZeY6qHSIHnadH5CWftjE+O7Ad8Aj3tvSCIiIiJSG7yRtJWcfDMr2K9tY07q3apa57l4eAe+X7WfWUXpop+v4Ie/jlO66HHYsD+d9ftNY/jQoABO69fasydmJsOmn13bnlQRlXrruD4GSIpL2AI8CfzXO8MRERERkdrgSGYeH8w7vlnBIqa66ACiQs08xPbDWfz3pw1eGWdD5d7zcVKf1kSFBXv2xNVfuoq2tB9peglKg+WNOeFDmFRREREREakn3pmzjcy8QgB6tm7EqX2rUKmyDDHR4SXWCr4zdxsLtyldtDocDpvpy13rBScPbuv5k6vaW1DqteMKBmMT45sD8cAW7wxHRERERPwtLSefd+ZuL96+dWJ3z/vXVeCi4e2Z0KslYApH3vPFCrKdAad4bsnOI+w5mg1AdHgwE3p5mL57cD3sXWbuB4ZAv/N8NEKpKzytJroNsEvtDgGKkpMv8OagRERERMR/3pu7nfQck0rYtUUkcQOrMPNUAcuyeOL8AZz6f7NJzylg++Esnv5pPeOjvHL6BsO9cMyZA2IICfJwfmelW+GYnqeb1g3SoHnaZ3AWxwaDOcAO4HPn2kERERERqeMycwt4689txdu3TOxOoBdmBYsUpYve88VKAKbN3U6bEWFM8NoV6re8AgffrdpXvH2upymijkJY+ZlruyZ6C0qt52k10ak+HoeIiIiI1AIfzN/Bkax8ANo3Da/aejQPXTSsPT+s2scfG0x10bdW5zIlroCIEE/nKRqu2RsPcdT5/WkbHcaIzh7O7m1PgjTnjGJEc+g+yUcjlLpETUVEREREBICc/ELeSNpavH3LhO4EB3r/z0WTLjqQqDAT/B3Msnnk27XYdulENCntG7cqoucMbuf5Wk733oL9L4SgEC+PTOoijz9+iU2M7wNcCHQAwko9bCfFJVztzYGJiIiISM36eOFOkjPyAIiJDuOCYVVoZF5FbaLDSqSLfrp4FzFNwrhzkorUlycjt4Bf1x0o3j53iIeztrkZsPZb17aqiIqTpwVkrgLexqwbPAjklTpEH+OIiIiI1GG5BYW8Nss1K3jT+G6EBvm2KfxFw9ozd3My3zjbJDz36yZaNArlylGdfHrduuqn1fvJyXcA0LtNFL3bNPbsiesTIT/T3G/RC9oO8dEIpa7xdGbwQWA6cF1SXMJR3w1HRERERPzh88W72Z+WA0CLRqFcMqKDz69pWRZPXziIzbsOsPqwaTHx4PTVNI8M4YwBMT6/fl3jniI6eXAVZm3dU0QHXQqW9woCSd3maRJ4G+BlBYIiIiIi9U9+oYNXZrqKw984rithwb6dFSwSEhTAbUNCGdQ+GjD9B//6yXLmbTlcI9evKw6m5zBnc3Lx9jmeFvZJ2wtbZzo3LBh4sdfHJnWXp8HgHKCPLwciIiIiIv7x9bI9xU3Mm0YEc8WojjV6/bAgi7enjqBLi0gA8god3PDeYtbuTavRcdRmiSv24XAuzBrZpRntmoR79sSVn1G8oqvLOIhu75PxSd3kaZrobcBXsYnxh4GfgSOlD0iKS3B4c2AiIiIi4nsFhQ5e/mNz8fZfYrv6pcVD80ahvHftSC54ZS4H03NJzy3g6ncW8uVNY+jYPKLGx1PbTF+xt/j+uZ6miNo2rPjYta3eglKKpzODu4FlwAeYAjL5pW6lC8qIiIiISB3w3ap9bD+cBUDjsCCuGu2/4i0dmkXw7rUji1tOHErP5aq3F5Cckeu3MdUG25IzWbHrKADBgRZnDmjj2RP3rYBD68394Ajoc7ZvBih1lqcf+7wBXAJ8A6xHwZ+IiIhInedw2Lz4u2tW8JoTuxAVFuzHEUGfmMa8edVwpry9kLwCB9sPZ3HNO4v4+IZRNAptmE3pp7sVjhnfsxVNIjzsEeheOKbPORDayMsjk7rO03fUZODupLiE5305GBERERGpGQWFDp79ZSObDmYA0Cg0iGtO7Fz1E+1cABkHoHccBHinQf0JXZvzv8uGcPMHS3DYsGpPKje9v4S3p44gJMg716grbNtm+nK3FFFPewsW5sOqz13b6i0oZfD03ZQJrPXlQERERESkZuw4nMlFr80rUUF0yuhOns84FVn9Fbx9Knw2Bb7/u1fHeFq/Nvzn3AHF239uTubvn6/A4WhY7a1X7k5lW7LpEdgoNIhJfVp79sTNv0GWs/poVFtTPEakFE+DwXeAy305EBERERHxLdu2+WzRLs54PollO48W7x/ZpRm3TexetZMd3gLf3uHaXvw2rPjUOwN1uvyEjsSf0rN4e8aKvTyauBbbbjgBoXtvwdP6tfG85Yd74ZiBF0NAzbQKkbrF0zTRHcBlsYnxvwA/UnY10be9OTARERER8Z6UzDzu+2olP605ULwvKMDib6f05Kbx3QgMqEIj8vxs+OxqyEsvuT/xTogZCK2815Hs9pO6k5yRy3vzdgAwbe52WkaFcmtVg9c6qKDQwYwV+4q3PU4RzT4CG35wbStFVMrhaTD4ivNrJ+DkMh63AQWDIiIiIrXQrI2HuOvzFRxKd1Xl7NoykucvGcIAZ7P3KvnxH3BglbkfGAJRMXB0B+RnwWdXwfV/eK1YiWVZPHR2Pw5n5PHdKhMY/fenDbRoFMIlI2q2H2JNm7vlcHEl1ZZRoYzp1sKzJ675Bgqd3+uYwV4NzqV+8TQY7OLTUYiIiIiI1+XkF/LkD+uZNnd7if1TRnXi/jP7EB5SjdTBlZ/Bkmmu7dOfhI6j4Y2ToCAbkjfCjL/CBW+CVYXZxgoEBlgkXDKII1l5zN1yGID7vlpFs8hQTunr4Rq6Osg9RfTsgW09n711ryKq3oJSAY+CwaS4hB2+HoiIiIiIeM/qPanc+elyNjurhQK0aBTC0xcO5KTe1QygDm2EGXe6tvtfAMOvNUFf3P/BNzc5L/4FdBoNI/5S/RdQSmhQIK9NGcYlr81n7b40HDbc9tFSPvzLCQzv3Mxr16ktsvMK+Wn1/uJtj1NEU7bCrvnmfkCQ+R6JlKNh1eYVERERqecKHTavztrCeS/PKREITurTih/vHFf9QDAvCz6/GvJNZUuad4ezn3fN/g2+DIZe5Tr+x/tgz9JqvoqyRYUFM+3aEXRsFgFAboGDa6ctYuOB9EqeWff8uu4AmXmFAHRtEcmAdh6m87oX8el+CjRq6YPRSX3h0cxgbGL8Nsy6wHIlxSV09cqIRERERKRa9hzNJv7T5SzYllK8Lzw4kAfj+nLZyA5Yx5O2+f3dcNDZaSwoDC56F0KjSh5zxtOwdxnsXwWFeSZ4vHE2hDet/nVLaRUVxnvXjuTCV+eSnJFHWk4BV721kC9vGUO7JuFeu46/uTeanzy4nWffO9suWUVUhWOkEp7ODM4q47YaaOw8x0xfDE5EREREPDN9+R5Of252iUBwUPtovrtjLJef0PH4AsFlH8LyD1zbZ/4X2vQ/9rjgcLj4PQhtbLaP7oSvbwaHo/rXLkPnFpFMu2YkjULNvMb+tBxu+WBJvWk5cSQzj5kbDhVvTx7sYYrozvmmkA9AWDT0PN0Ho5P6xNM1g1PL2h+bGN8E02riV+8NSUREREQ8lZqdz7+mr2b68r3F+wIsuG1id24/uQfBgce5KujAWvjOraH8wEthyJTyj2/WFc59GT690mxv/AHmvgBj7zy+cZTSv100r08ZxtXvLCS/0GaFszl715beqWLqT9+v3keBwwS2gzs0oXOLSM+e6D4r2O98CA7zweikPjmu3w5JcQlHgf8C//LKaERERETEY2v3pnHGc7NLBIIdmoXz+U2jiT+11/EHgrkZJtWzINtst+gFcQmVVwntczaMvs21/dujsH3O8Y2lDGO6t2BCr1bF20mbkr1+DX+Yvsz1/TzX01nB/GzTUqKIqoiKB7xRQCYHaO+F84iIiIiIh/IKHNz28VL2puYU77toWHt++Os4hnXyQnVN24bv4k2rCIDgCLj4XQjxcJZq0sPQ4QTnuQrhi2sh4+Dxj6uUcT1cvfeSNh2q4Mi6YfeRLBZuN6m+gQEWZw30MBjc8APkppr7TbtAh5E+GqHUJ572GTxGbGJ8ENAfeBhY460BiYiIiEjl3pu3na2HTGXPyJBAnrloEGcMiPHeBZa+ByvdKlOe9WzVmpcHBsOF78BrsZB1GDL2m4DwqukQUI3+huWI7eGqljlvy2HyChyEBNXdgvnfrnDNCp7YvQUto0I9e2Lp3oJe6vEo9Zun1UQdlF9NNA04y2sjEhEREZEKHUrP5flfNxVv3zmpp3cDwf2rTPXQIkOuhMGXV/080e1M8/n3zwds2J4EfzwOJz/otaF2ah5Bh2bh7ErJJjOvkGU7j3BC1+ZeO39Nq1aKaMZB2OxWwmPgxV4eldRXns4MPsqxwWAOsAP4ISkuIdWroxIRERGRcv33p/Wk5xYA0LVlJFeP6ey9k+ekwWdXQ2Gu2W7VF874b/XP1+0kGH8vzHrSbCc9Ax1HQY9Tjn+sgGVZjO3eko8X7jSn35RcZ4PBdfvS2ODsmRgWHMCp/dp49sRVX5hUXICOY6BZFx+NUOobT6uJPuzjcYiIiIiIB1bsOspni3cXb/8rrq/30iJtG2b8FVK2mO3gSNNPMCTi+M47/h7YtQC2/mG2v7oebkyCJh2O77xO43q0cAsGD3HXab28ct6a9o1bb8FT+rYpbp1RKfUWlGoq9zdHbGJ8QGxi/NmxifFlNJEpPmZAbGL82b4ZmoiIiIi4czhsHp7hKtUwqU+rEtU0j9vit2DNV67ts5+Hlj2P/7wBgSZdNMqZ9ph9BD6fCgV5x39uYEy3FgQ4l8it3JPKkUzvnNcTmw6kc+bzSZz/8hzen7+DtJz8ap3H4bCZsbwaKaK7FsH+leZ+YCj0O7da15eGqaKPka4EPgYyKzgmHfg4NjFetWtFREREfOzrZXtYtvMoACGBATxwVl/vnXzvcvjxPtf2sGtg4EXeO39kC7joHQhwznbtWQy/eGftYHREMIM6NAHM5OacLTXXYuK5Xzexdl8aS3ce5cFvVjPysV+J/2w5C7elYNvlldw41sLtKcWVYZtGBDOuZ8tKnoF5sT//07Xdd7JpNi/iocqCwXeS4hK2lXdAUlzCduAt4Govj0tERERE3GTkFvDkj+uLt6+L7eJ5M/LK5KSafoKFzhm1NgPg9Ce9c253HUfBpEdc2wtehTVfe+XU7lVFkzbWTDCYk1/IHxsOltrn4Kule7j4tXmc/OwsXpu1hUPpuZWea7pbiuhZA2M86xG55muTfgsQGAIT76v4eJFSKvopGwr87ME5fgWGe2c4IiIiIlKW//2+qTioaN04lNsmdvfOiW0bpt8KR7ab7ZAos04wOMw75y9t9K3QO861Pf12wrP2lH+8h0r3G6zKrFx1JW1KJivPFG5pFRVKn5jGJR7fmpzJEz+sZ/QTv3HT+0v4Y8NBCh3Hjiu3oJDvVu4r3j53cLvKL56fA78+5No+4UZo1rV6L0QarIqCwSjgiAfnOOI8VkRERER8YOuhDN7+05Wsdd8ZfYj0tLhIZRa8ButmuLYn/w+ad/POuctiWTD5JdMYHSAvnX5rnoK8rOM67aAOTYhy/pvsTc1hy6GKVjp5x09r9hffv2BYe76/YywzbhvLFSd0LFH8pcBh8+Oa/VzzziLGPvU7Cb9sZFeK6/XO3HCItBxTHbZ903CGdWpa+cUXvAJHTdEcIppD7F3eeVHSoFQUDCYDnTw4R0fnsSIiIiLiA//5bh35hWZGaVinpkz2tLhIeRyFsC0JZtwJPz/g2j/yBuh33vGd2xPhTeDi90zBE6BR5g54+zTTK6+aM3rBgQGM7uZqKZG06ZA3RlqugkIHv647ULx9Wr82WJbFgPbRPHbeABb+82SeuWgQIzqXDOz2pebwwm+bGPffP5jy1gISV+7lyyWu6rCTB7fFqqxhfMYhmP2sa3vCfebfVKSKKvpI6U/MWsAPKznHVOexIiIiIuJlf6w/yO/rzbo0y4KHz+5XebBQFocDdi8y1ULXfA0ZB0o+3nYInPofL4zYQzED4cynTSsLMBUxP7gAOsfCyQ9BhxFVPmVsz5b8vNa8rqRNyVxzou/67S3clsLRLFM5NCY6jIHtShZuiQgJ4sJh7blwWHs2H8zgs8W7+HLJbg47K53athlj0qaScyoepYj+8RjkmX6EtOhliv2IVENFweBzwJ+xifH/B9ybFJdQokZvbGJ8MPBf4CRgrM9GKCIiItJA5RU4eDRxbfH2pSM6MKB9FapF2jbsXeYMAL+B1F1lH9eyj1knGBR6fAOuqqFXQ1YKhX88QaDD+afm9iR4axL0OgtOfhBa9fH4dO7rBudtOUxuQSGhQYHeHjUAP7qliJ7atzUBAeUH6N1bNeL+M/tw16m9+G3dAT5ZtIvZmw4dMwnaN6YxPVpXsvrqwFpY+q5r+9T/QKCXUoalwSn3JycpLmFebGL834FngStiE+N/BnY4H+4EnAI0B/6eFJcw3+cjFREREWlg3pmzjW3JZu1bVFgQd53qQTN124YDa0wAuPorOFJOYfjIltD3XOh/PnQYBQFealxfFZYFsfEsyOrEmPw/Ycm7YJuCLGz4DjZ8D4Mugwn/gKaVr17q1DySjs0i2JmSRXZ+IUt3HC2ROuotDofNz2vcUkT7t/HoeSFBAZwxIIYzBsSw52g2ny/exeeLd7PnaDYAV42u5DUWtZKwHWa720nQ45RqvQYRqHhmkKS4hOdiE+OXAvcC5wHhzoeygZnAk0lxCUlVuaBlWeOAu4BhQFvgGtu2p1Vw/ATgb8BIIBrYDDxn2/bbVbmuiIiISF1yMM2sLSvyt0k9ad6ogpm7QxtdAWDyhrKPCW8Kfc6G/hdAp7G1ZkYpL7Q5nPZ/MPo2kwK5+kvnIzas+AhWfQ4jrjNFUhpV3H8vtkcLPlxgCqskbTrkk2Bwxe6j7E9z9QQc2blZlc/Rrkk4d07qye0n9WDR9hQKHTZjKhvr5l9hy+/mvhUApz5mAmqRaqr0N0BSXMJsYHZsYnwAUDT3fjgpLqGwmtdsBKwG3nPeKjMGWAU8DewDTgNetywrx7btj6o5BhEREZFa7akfN5DpbFvQo1UjppQ1a1SQa3r1rfwcDqwq+0QhUdAnDvqdD10nQFCI7wZ9vJp3gwvfhhP/Cr/9Gzb/YvY78s3rXPq+aU0x5rZym6vH9mjpFgwmc8/p3h/mT26zgpP6tCbIk56A5QgMsBjV1YOAtTAffnJrMD/0amjdt9rXFQEPgsEiSXEJDuBgpQdWwrbt74HvASzLmubB8Y+X2vWKZVkTgQsABYMiIiJS7yzbeYQvl7oqTP7r7L7HNiF3OODTK2FTGW2hgyOg5+lmBrD7JN/1DPSVmEFw5RewfQ789oirsXp+Jsx+Gha9CbHxMOL6Y17b6G7NCQywKHTYrN6byuGM3IpnVKvItu0SLSVO6+dZiuhxWzLNNeMbEgUT76+Z60q95ofkcK9ojGc9EEVERETqFIfD5uFv1xRvn9avNbE9ykiNnP9yyUAwMNQ0c7/wbbh7M1z0jpkRrGuBoLvOJ8K1P8Fln0Art1mw7BTTEuN/Q2Hpe1BYUPxQdHgwgzs0AcwSuzlbDnt1SJsOZhSv44wICWSsW9Ean8k+CjOfcG2P+zs0auX760q9Z9nV7OXilYtbVgZwW0VrBst4ThzwNXCibdsLy3j8BuAGgNatWw/75JNPvDRa78nIyKBRo0b+HoaI3+m9IKL3gRwraXc+b602lTWDAuCJseG0jCj5+X2j9C0MXXoPAbYJgva0PZ2tXa+mMCiixsfrDR69D+xCWh9IovP2DwnPKZmslhXejo09b+Zo0wEAfLM5j282m7YPse2CuG6A92YGp2/O42vnuUe0CeTWwb4PtrtueYeOu74BICe0FQtHvoQjsBan+0q1+eL/hIkTJy6xbXt4WY/VqWDQsqwTgR+Ae23bfqWy44cPH24vXrz4+AbpAzNnzmTChAn+HoaI3+m9IKL3gZSUlpPPSc/MJDnDBIO3n9Sdv5euIJqbAa+Ph8ObzXbMYLjul9q9FrASVXofFOSZ1gqznoZMt6AwvCnctQkCg1my4wgXvDIXMD0A5/7jpOr1ZizDWS8ksWZvGgAvXDaEcwa19cp5y5WyFV46AQqdrTcufNuk/0q95Iv/EyzLKjcYrDNpopZljcUEgv/yJBAUERERqWv+99um4kAwJjqMmyd0O/agH+51BYLBkSY4qMOBYJUFhcDI6+GOZXDSA2Z9JED2Edi3EoBB7aOJCjOlMfal5rDlUIZXLr0rJas4EAwJDGBir4orm3rFLw+5AsH2I00hIBEvqRPBoLMdxQ/Aw7ZtP+fn4YiIiIh43eaDGbwzZ3vx9n1n9iEipFStv9VfwvIPXNtnPWMqcDZEoY1g3N2mVUaRHXMACAoM4MRurrV8szcme+WS7oVjTuzenKiwYK+ct1w75sK6b13bpz+hVhLiVTUeDFqW1ciyrMGWZQ12Xr+jc7uj8/EnLMv6ze34CZhA8FXgI8uy2jhvNfBRjIiIiIjv2bbNo4lrKXCY5TsjOzfj7IExJQ86sh1m3OnaHnCRacje0HUa47q/Y27x3diermAwadMhr1yqRquIOhzwk1vF0AEXQfsyM/1Eqs0fnUaHA3+4bT/ivL0LTAViAPePuKYCEZhG9Xe57d8BdPbdMEVERETKt3ZvGq/N3sLavWl0aRHJiM7NGNGlGf3aNj62DUQlflt3kNkbTcASYMFD5/QtucatsAC+vB5yTYoiTTrBWQmaJQLodKLr/s65JogKCGCcWwXW+VtTyC0oJDQosNqXOZSey+Idpph9gAWT+rau9rk8suoz2LvM3A8Kg5Mf8u31pEGq8WDQtu2ZQLm/uWzbnlrG9tSyjhURERGpaUt2HOGlPzbz+3pX8ZJNBzP4ea1pRB4eHMiQjk0Y3rkZIzs3Y0jHJkSGlv8nV25BIf/+bm3x9mUjO9KvbamG6rOehN3OIuoBQWadYFhj772ouqx5d4hsCZmHICcVDq6FNv3p0CyCzs0j2H44i+z8QpbsOMKYbtVvA/HL2gMU1V0c3rkZLbzYu/AYeVnw6yOu7dG3QZMOvrueNFj+mBkUERERqVNs2+bPzcm89Mdm5m9NqfDY7PxC5m45zFxnf7vAAIt+bRubmcPOTY8JJN76cxs7DmcBpkfeMdVDtyXB7Gdc2xPvV7qgO8syqaJrp5vtnfOgTX8AxvZowfbDOwFI2pR8XMGge4ro6b5OEZ37P0jfa+5HtoKxd/r2etJgKRgUkZqXugfmvkDbFBsKx0KgfhWJ1EXbkjP5etkexvdswbBOzfw9HJ9wOGx+WXeAl//YzIrdqSUesyw4o38bLhvZkV0p2SzensLC7SnsPpJd4rhCh83K3ams3J3KW39uA6CrM610YIdoXvx9c/Gx8af0pFmkW2XQrBT46gbAOSXVORZOvNMXL7Vu63SiKxjcMcdUGwVie7Tkg/lFweAh7j29d7VOn5aTz9wtriI0p/bzYYpo2j6Y85xr+6QHIDTKd9eTBk1/gYlIzcpKgWlnwZFt9AR4bzVc8BY0jqnsmVLbFOVLac1Sg/TL2gPc+ckyMvMKeStpK7PumejbtLkaVlDoIHHlPl6euZmNB0q2JQgMsDh3cDtuntCN7q1czaEvP6EjAPtSs1m0/QiLtqWwaHsKGw6kU7qt89bkTLYmZ/Lp4l3F+3q1juIK5zkA8x779nbXDFF4Mzj/dQio/rq3eqt0ERnbBstidLfmBAZYFDpsVu9J43BGLs2r8XP6x/qD5Beab+KAdtG0bxrhrZEf6/d/Q76ZKaZ1fxhype+uJQ2egkERqTmF+fDZVXBkm2vfjjnw6ljzB073k/03tobmwBqThnR0FzjywVHgvBWa75P7dnmP24UQFG7K2jfvBs17mLU7LXqY7fCm/n6V4gO2bfPyzC088/OG4gAnM6+Qb5bt4S+xXf07OC/IyS/ky6W7eXXWFnallJzhCwkK4NIRHbg+tisdmpUfDMREh3POoPDiZuSpWfks3XmEhdtTWLw9hRW7UskrdBzzvIfO6UuQe+GZxW/B+kTX9rkvQ2MfNzivq1r1hbBos2Yw44Bp1N68G43DghnSoUlx4Zc/NyczeXC7Kp/+x9XuVUR9OCu4dzks/8i1fdpjCv7FpxQMikjNsG344R7YnuTaRQAWDshKhg8ugHF3wYT79B+fL2Uehj8egyXvgH3sH6NVVpANB1abW2kRLZzBYXfztShYbNYFgurPDFJDkpNfyD1frOTbFXuPeeyzxbu4bmyXkhUw65DM3AI+XriT12dv5WB6bonHIkMCuXJ0J64b24VWUWFVPnd0RDATe7diYu9WgPl3XLUnlYXOmcOdh7M4f2i7kuvZDqyFn/7p2h55A/Q6o1qvrUEICISOo2Hjj2Z7x5zi/ouxPVoWB4NJm6oeDObkFzJzg6s1xen9fbRe0Lbh5wcoTgnueQZ0neCba4k4KRgUkZqx8A1Y/LZr+6QHWJ4SzpDN/4OM/YANs/8LO+fDBW9ClI8X5zc0hfmw6E2Y+YT55LwmZCWb2675JfdbAdCkowkM2wyAUbdAo1Y1Myaptv2pOVz/3mJW7XH9/Izs0oxVu1PJzi9k44EMVu5OZVCHJv4bZDWkZuUzbe523pm7jaNZ+SUeaxIRzLUnduHq0Z2JjvBec/Gw4EBnMZly1lnmZ8OX10FBjtlu1Q9O+bfXrl9vdRrjFgzOhaFXAabf4P/9uhEw6wZt267ShxazNx4iO78QgK4tI+neykfr99Z/5/rANCAITtX3XHxPwaCI+N6W3+HHf7i2+18IsXeROmsW3JQEX10PW2eax7YnmbTRC97UJ6LesulX+Ok+SN5Ycn/XCaZceUgkBASbT9YDgiAw2HwNCHTuD3Lud34NcHs8+wgc3gKHN8PhTeZr8mZI2eL6Q7Y022GaZx/ZDpt/hUMb4bKPyj5WaoVlO49ww/tLOOQ2Y3b5CR15+Ox+3PfVKr5cuhsws4N1KRjccTiTi16dd8xMYKuoUG4Y15XLRnassCWEz/z8gGmPAKa/3IVvQ3DVZyQbnI7u6wbnFN8d2C6axmFBpOUUcCAtl00HM+jZ2vOA7qc1B4rvl9lo/tBG+GwKZB2Gpp1ND8imndzud4bG7SoullaQB7886Noe8ReTci/iYwoGRcS3kjfBZ1PN+jKAtkNh8ouuoiONWsGVX5my6TOfAGzTK+q9c2H8vTD+HqWNVlfyJvjpftj0c8n9zbrCqY+ZlLPjTemLaGZuHUaU3O9wQNpuV3DoHiwe3UVxGhTApp9MUKk1hrXSV0t384+vVpFXYNKKAwMsHj6nH1NO6AjzXuLxHS/TP6g/jxZM4dsVe3kwri9hwbX/PZuTX8itHy0tEQh2bBbBTeO7ccGwdsfVnPy4rP/OzOIXOf0JaFW9CpgNTswgCI4wxVeO7jS/a5p0ICgwgBO7t+AH57q/2RsPeRwM5hc6+HWdKxgss6XE7/+GQ+vN/cxDsHvRscdYgRDd3gSGTTu5gsSi28pPzTpHMGsfx9/r8csWOR4KBkXEd7KPwEeXQK4zrSyqLVz2MQSHlzwuIBAm3AsdR8GXf4HMg4BtmizvnAvnvwlRPlywX99kH4VZT8PC10yhlyIhUTD+bjjhJt+v2QtwpoI26QjdTir5WH42pGwz5fIPrDJj3PgzDLrEt2OSKil02Dz943pem721eF+TiGBevmIoYzo1hum3wfIPCAWuCdpDGpH8X86F/LRmf7UKdNS0x75bx+o9aQCEBAbw+PkDOHdw25IFXGpa2l6Yfqtru8/ZMOwa/42nrgkKgfYjYNsss71zXnGj9tgeLYuDwaRNyR4XO1q4LYXUbJM+HBMdxsD20SUPKMg12S+VsQvh6A5z21bJsePvNR+yidQAP/7GE5F6rTAfPp9q0gXBVJ287KOK1wJ2HQ83/Wn6aBXZNhteizVfj1dBHmyfA7//B96cZNJR139//OetLRyFZl3m/4bC/JfcAkHLrJ25Yymc+Ff/F28JDofWfaH/ea59677133jkGGk5+fzl3UUlAsEerRox/dYTGRMTAB+cD8s/KPGcvwZ9xekBC/nMrVVCbZW4ci/vz99RvP3Ps/pw4bD2/g0EHYXmA5JsU+iExu3g7BfUuqWqOp3ouu+WKhrbw1WcZ8G2w+Q41wBWpmQV0TbHrjXcMQfynK1HmnSCqxNh8ksw7m4YcDF0OAEaVeHDzGZdYcT1nh8vcpw0MygivvHjfa51gADnvQJth1T+vKjWcNV0mPWUmd3CNmXC35tsKo3G/t3ztFHbNqmSW36HrX/AtiTIzyx5zCeXweArTCpWWHTZ5/EVZx8sr9g22/ybl67q2XGMeW1tB3vnOt7U5xz47VFzf/NvkJcFIT7s3SUe2ZacyV/eXcSWQ673yqQ+rfi/SwYTlbkT3rrYpPsWiWzlnM2HhOBXuGBLa3alDKyw9YI/bUvO5B9frirePnNAG64a3cmPI3L68/9cxUOsADj/Dc0OVUfpfoNOHZpF0KVFJNuSM8nJd7BkxxFO7N6ijBO4OBw2P691BYNlNprf+JPrfq8zoEssEHvscXlFqas74MgOs2ba/X5eulkfevbzZoZTpIYoGBQR71v0Jix6w7U94T7od175x5cWEAgT7zdlwr+63qzBsB2mJcKOOSZttFHLsp+bedgEflv/gC1/QNqeyq+3/EMTTE1+ycxO+lrKNvjtEdjwAwSGmtnSqNYQFWM+QY6KMduN2jgfa2OKvJTlyHZTbGLdjJL7ozvAKY+af/faOrPQoge06AXJG0yLii2/mbQ48Zs/NyVz60dLi9PiAG6Z0I2/n9qLwF3z4ZPLITvF9YSTHoTh18KbJ0PKViKsXN4IeZbE+cO46cwT/PAKKpaTX8itHy4lI9fMmndqHsGTFwz0fzuMXQvhj8dd27F3QecTyz9eytd+uCly5cg3RbMyDhX/fxHbowXbks2HHLM3Hao0GFy++ygH0sya0qYRwYwsXf3Vts3v8SI9Ty//ZCERZu1nWes/bdvMCAeHH7uMQsTHFAyKiHdtnQXf3+Pa7nde9RfCd5sINyaZdYQ7/nSef6ZJ77zwLeg81qzX2DnfGfz9DvtWUqI4SWlNOpk1bF3Hw7pEWP2F2Z+6C947B0beCJMe9s0MVU4aJD0D81+BwjyzryDHrKlM3lDxc0MbOwNFtwCxIA+WTINCt0qIwREwNh7G3FY3/qjoczYkOV/7ukQFg35i2zbT5m7nP9+to9Bh3j+hQQE8feFAs/5v5WdmLVvRz21gKJz3KvQ/32xf9gn5r00kuCCT9lYyIxf9DccpMwkIrl0zHP9OXMvafa51gi9dPpTGYd5rGVEtOammjURRka0OJ6h4yPEIDod2w1wtbXbOg77nAGbd4HvzTHpw0sZk7qukbeNPa1yzgpP6tD42jfjQBjO7BxDSqGSKalVYlmaBxW8UDIqI9xzeAp9d5fqjJmYwTH75+GamGseYtNGZT0DSs5i00f3w7tkmBXLvUlM5rjyhjaHLOBNYdjvJrMco0u886BMHifGu2Y6Fr5kZqnNfPbZCZnUVFsCy9+D3x0zfverITTO3w5vKP2bgJXDyQxBd+4t3FOsTZwJkgI0/mLWmgX7+47yByStw8K/pq/lkkWutX+vGobw+ZTiD2kfDH0+YYk5FIlvCpR+XfH+07AUXvInj08sJwGaovYZ9n99JzOUv1+Arqdj05Xv4cMFOAMLI5X9jCui/8WX4dS5gmXTxAReZ4kc1Ze9y+P5ukz4IEBpt2upU1IJAKtdpjCsY3DG3OBgc1bUZQQEWBQ6btfvSOJSeS8uostdQ27bNT27rBctsNL/RbVaw20lK75Q6Sb9tROoa2zYpgckbYdBltecP/+yjpnJozlGz3aiNqRzqjRm2wCA4+UHoNNoUWMg6bNJGi2YL3VmBpppcUfDXdmjFf1j1O88ElTPucDUrPrwZ3j4Vxv4Nxv/j+P6D3/I7/PRPV8+wIu2Gw2mPm8br6ftMgJvuvGUcMPvSDzi397tmZMrSbhic/pT3gteaFDPYpLSm7jIzJNuTjq0+Kj6TnJHLzR8sYdH2I8X7BnVowutThtE6HJOmvepz1xNa9obLPzOl8UsJ7nMmv7a9kUl7XwUgZuOHsHi4SSP1s2279/L9V+9xb9AaRgasZ1DANoIWFZQ6aBbM/R9Megi6T/JtevXRXaYdwcpPS+4/53lTgVeOT6cT4c8Ec9+tiExUWDBDOzZl4Xbz4d+czcmcO6Ts/0M3Hshg+2HzQWNkSGDZKaWl1wuK1EEKBkXqmqRnzR8RAEkJMPE+0yrAn7MphQXwxTWuWaugMFM5tHFb716n+yRTbfSL60zLiSLNurmCv85jq14IJqo1XPYJLPvAFGHJSzfBZtKz5j/7816DNv2rds7kTWYtX1GAWaRxezjlEeh/geuPzcjmQAXnL1pPkr7fGTg6g8XsIyao7HNOzc5meJNlQe84WPCK2V6XqGCwBti2TeLKfTwyYy3JGa404/OGtOOJ8wcQlncE3rvCNbsC0HUiXPxuhe+vtmfdz7evruCcwHnmOt/fjdWiV82vf8s8bH5H7JiLY/scOu5fxWsBjsprqB9YBR9eaCoaT3rYrD/zppxU83t7/isl07utQJjwj6qtrZbydRhpivDYDti/yvy7O39uY3u0KA4GZ286VG4w6F5FdELvVsf2zsxKgV0LnBsWdD/F6y9DpCYoGBSpSxa96QoEwVTG/PkBWP4RnPVsySpqNennB0r2WZr8kpmt8oXGbeHqGWatX2G+SQEtY5aiyiwLhk4x55t+q6uq34HV8PoEE3SP+Wvl6VtZKaYS6qI3S/b4C46E2L/B6Gqs5StaTxLRzLRkqG/6nO0KBtd/B2c+U3eD2zpgV0oWD05fzcwNh4r3WRbce3pvbhzXFSt5E3x0kSlOVGTYNXDmfyv90Klvu2geaPF3uhy+iwEB27EcBfDZFLhhpm9nvNL2mRmgHXPN16IG4FQQ/7XsY35ndhpjjp/3kivlfHuSKYrT52yTet2ix/GNryAPlrwDM58sWYAHoNdZJvBs2fP4riEuYY2hzUDYtxywYecC6HkqALE9W/LsLxsB02/Qtu0yCwi5rxc8raxG85t+McEmmA8NyitqJlLLKRgUqStWfg7f3eXaDgo3FRjBpCC+cwYMutxUkKzJ/5SWTHP9IQ8w7h4YcGGFT1mx6yiPzFhDY0cuo8cWEhrkYauIIoFBMOjSqo/VE007wVXfwsLX4deHTIEXR75pgbDhBzNL2Lzbsc8rzDcB4MwnXamyQPFapJMfrLjHYkPWcRREtDDrKTP2w57F5pN98aqCQgfvzNlOwi8byXbrsda6cShPXjCQib1amQJQn00xMykAWHDqf2D0rR6nTU4e0YMbvv0734b+k5ZWmknr/vhyuO6n8qviVtemX+CXh+DgmgoPK7Qt1tqdCO46lt4nnG4qFUeWSvsb8RfTzmbpu64PctbNML1Ih04xKeONY6o2Pts2PTR/fRhStpZ8rO1Q82+rqqG+0WmMMxjEfEDgDAYHtIsmOjyY1Ox8DqXnsuFAOr3bNC7x1F0pWSUKDU3sVcb/qe5ZHxVVERWp5fTRq0hdsOEH+PpGiqtkthsGf18Hp/zbzDgVWfERvDgMFr1lGhj72rYk+O7vru0+55g2EhXIzC3g5g+WsHTnUWbuLuCuz1ficFRQ/dMfAgJg1E2mkqn7DOfuRfDKibDgdXA4PxEuKi3+8ij48R8lA8FOY82MyLkvKRCsSEBgyfU2akDvdSt3H2XyS3N47Pt1xYGgZcFVozvxS/x4Ewgufd80ky8KBIMj4NIPTWXaKqyfmzy4LYcDW3JT3t/Is50f9BxYBd/cYt4v3nB0F3xyhUnpLCsQDAgiu/Uw3rAnMzXvbgbnvsEbfabR6+oXzWxf6UAQzHs0LgFuXVgyXdMuNB96vTAEfn3ErI/2xK5F8PZppqiWeyDYpCNc8Bb85TcFgr5UTr/BwACLsW7r/5I2HlvUy31W8MTuzYkqXXG2MN/0Ri2iYFDqMAWDIrXdtiT47GpXhc6WfeCKLyC8KZx4B9y20ARhRXJS4bt4eHMS7F3mu3GlbDUzCEWfoLcZaErNV5Le99yvG9mbmlO8PWPFXv77cyVtFfylZU+49mc46QEIcCZSFGTDD3fD++eaPwbemwwfX1qyCXfTLnDJBzA1sXY2e6+N3H+G1yV6L2ho4DJzC3h0xlrOfWkOa/amFe/v1TqKL28ew6OT+9M4JNDMrn17m+v9HBUD1/wAvc+q8jWbRIRwar/WLLF78WCBW/GYtd/A7GeO7wUV5Jnm7C+NhPWJrv2BoWad3/h74apvyY7fxrk5D/NY7iXMdAyhZYuWPH7+AM/6CTbvBhdNg+v/MGnjxdfONkVJnh8Ec16A/Jyyn5+y1fzOfmuS25oyzJq1U/8Dty022RNKhfatjqNd9/cuNU3fnWJ7uILB2ZsOUdqPlVUR3TnPtAQCUwCrdb/jH6+InyhNVKQ227PUBBpFhQaadoYpX5fsRxTdHi5536RLfX+Xa53P3qXw+kST+nTSAxDexHvjyj4CH11qvgJEtnJWDq04BWzN3lTenrP9mP2vzNxCuybhXDnKC2v/vC0wCMbdDT1OM7OzRVVBt80yN3eh0TD+bhh5AwSVXa5cytF1PIREmeI9R7aZf2f9gXVcfl17gH9NX13iw5fQoAD+OqkH18d2JTgwwPyB/PWNJWdjWw+Ayz89rkrFFw/vQOLKfXxaOJEhIbu51HaW4P/jP2bdazWCTLbNNqnypXtyDr4CJj1SIj3+oS9WsOFAOmBe80tXDKVRaBX/5Gk31KSMb/ndpHnuX2n25xyFXx6EBa+ZtcSDLjOz21kpMPu/sPANk1peJCDY/E4Yd5d6ydWkyBam+u2h9eZDjt2LzO8ZYKxbMLhwWwo5+YXFBWIOpuewZKf5vy3AMv0Fj+FeRbTnab6tPCviYwoGRSpg2zap2fnsPpLtvGWx+0g2+1Nz6NkmitsmdickyEef7h5cDx9cAHkZZrtRG5jyTflrVnqcArfMhz+fM59eF+YBNix6w3wif+pjMPDiqv+n5XCYKqG7F5u1XLsXw4E1rpnKwFATCEa3r/A0hQ6b+79eXdzQenTX5mSnH2X5IXOef01fTUx0GCeX9R9vbRAz0KR8/vE4zH3BVTgATNW6YdfAxPvLTj+TygWFmjU9q7802+tmKBispgNpOTz87Rp+cJvdADMb8p9z+9OpufNDm30r4JtbTQpnkZ6nmxTG0EbHNYYTu7cgJjqMfak5PJB9Gad0SKH5Iecs2Vc3wHW/eF4MKX2/KVLl3uICoFU/Z+Gs0SV2f7lkN58t3l28/cg5/egTU3JNmMcsC7qfbCqprvnKFPAq+sAtbbcpNjX3Reh1Oix62zVbVKTfeXDyv0r2N5WaU1QcCEyqqDMYbN80gq4tI9l6KJPcAgeLtx8pDhB/WXugODFhROdmNG9Uxgd7Wi8o9YiCQWnQbNvmSFZ+cZC3xy3g230kmz1Hs8nILSjzuT+u2c+czcm8csVQWjUO8+7Ajmw3aYhFVefCm8JV30CzLgCs3pPKzpQsTu3bmqBAt2A0ONx8Uj3wYjNLWFThM/MQfH0DLH3P/PHUqnf518445Ar69iyGPcuO/QPH3eQXPSq//uGCHazYdRQwC/L/c15/Nq9YxEvrg1m5OxWHDbd9tIxPbxzFwPZNKj2fXwSFmrYQvc6E6beY1NBuJ8Npj0GrPv4eXd3XO84tGEw0pfbFYw6HzYcLd/L0D+tJd/u91SwyhAfj+nDu4HYmTbIg1xRK+fP/XB/qAJxws/lZDqhiQacyBAZYXDisPf/7fTMFBPFI2D280CQeju4wH3B9cplJw6xopqywwHyY9cfjkOtKcSUkyvyeG3njMdV9Nx1I54FvVhdvnzekHZeM6HDcr4eAAJPa2eccs35w1lOm4BHAoXXm5q7DKJMSWhd7f9YnnU6ExW+b++7tiIBxPVqy9VAmAEmbDhUHgz+tOVB8TJlVRJM3u5YFBEeY9GSROkzBoDQYaTn5LN95lKU7j7Bqtwmmdh/JLlFVrzJh5HJ24DzODpjHXrs5L++cTNz/snjlymEM69TUOwNN3w/vnWv6yAGENIIrvoRWfcgtKOS/P27gzT+3ATB1TGcePqeM2ZPm3eDKr2DtdNM3L32v2b/jT3j1RNPeYPw9prfV/pVus36L4OhOz8bZoqdpyj7w4koPPZCWw39/dKV23TKxG91aNmJXkMVbV4/gvJfnFH8vrp22mK9vGUOHZl5oVu8rHU+AWxeZdDGlfXlPj1PMTHNhrpmtStlW/AGIVGzD/nTu+2olS3ceLbH/omHtuf/MPjSNDDE7di8xH2S4tV4gKAxOexxGXOfVMRUFgwCJm3N56C/TaP5JnGmJc2Q7fD7V/J4qq13LroWQGF9y1hJMf85THyszQyIrr4BbPlxa/Du9W8tI/nNuf8/WCXoqKAROuAEGX2ZaUcz9nyt7A8wM4KRHTJEapQ76n/u6wV2LzJrTIPNeGNu9BdPmbgdg9qZk7gNSs/OZu9lVUOa0stYLus8Kdp0IwV7+MFikhikYlHrJ4bDZmpzJ0p1HWLbzCEt2HGHTwYxq1aSICAlkZFQKlwX8SmzWz0QUphc/dkFgEp9mT+CO18/ntsnjuGzkcfbRykqB9883a6bA/GF86UfQfhhbDmVwx8fLShSBeH/+Dq4a3YmuLctI6bIs6HeuSXGa+aRpcmwXmrUTc54zn27nZZZc21KeiBZm9q/dcGg/zJREr8IaxEcT1xbPVHRtEcnNE1ytGVpGhTLtmpFc8MpcUrPzSc7IZeo7C/nq5hOJjqi4p5lfBQQoEPS20CjoNtH1x9b6RBhzu3/HVMvl5Bfyv9838dqsrRS4VeXt0iKSx87rz5huzrTl/GwzwzbvxZIpzh3HmNn9stqlHKdOzSMZ1bUZ87em4LDhs13R3Hz+a/DpleaAbbPg53/CGU+5npR5GH79Fyz7oOTJmveAs56BrhPKvd6D36xh00ETmIUFB/DyFcOIrOo6QU+FRpmZ6+HXmRnWPYtNoDrsmuJgQ2qB6HZmrf2R7aYA0L7lxW1rRnVrTlCARYHDZt2+NA6m5zB38+Hi99GAdtG0a1JGT9gSKaKn+fwliPiagkGpF9Jz8lmxK5WlO484A8CjpGZ7EOQAjUKDaN80nPZNw2nXJJz2TSPM/ehguqT8SaOVb2Bt/aPM5wZbhVwZ9BsX2Em8++1p/HvHzdx73ujqrSPMzYCPLnaVSbcC4aJ3sLuM49OFO3lkxtpjZjELHTbP/ryRl64YWv55Q6NM6tfgy80n7bvmm/0leuG5CQyFmEHO4G+Y+dqkU7U/5f5jw0G+W7mvePs/5/U/pq9g91aNeOOq4Vz55gLyCh1sOZTJ9e8v5v3rRla9B6HUbb3jXH9srZuhYLACG/anc/OHS4pT3QCCAy1uHt+NWyZ2Ly6IwY55Zm1byhbXk4MjTaPzEX/xaVXLi4d3YP5Wk+7++eJd3PT3OKwJ98HMJ8wBC16F1v1NEZil78Jvj7gKU4Hppzr+bhh9e4VB1meLd/HlUtc6wUcn96dXmyhfvKSSGrWE0x/3/XWk+jqd6FrnuWNOcTDYKDSIoZ2asnCb+fmcszmZn1a7UkTLrCKafbREmwoFg1IfKBiUOmlbciZLdpjAb+mOI2w4kF7prF9ggEXvNlEM69SUIR2b0KNVFO2bhhMdHlwyjSh9v1lb98s0SNtz7ImadjF/uGydadIugXArj5uCZpC2+le+2H4Rp1zzMC1bNPf8BRXkwqdXmDTNIue+QmrHU7nvo6V8v8pVCCIkMIArR3Xi7Tlm9vC7Vfu4cffRytfZte5nSsWv+NhUwss6bPY37+6c8XMGf637e+2T7ey8Qh50W79z/tB2rpmKUkZ2acazFw/i9o9NO4yF21K46/OVPH/JYAIClG7VYPQ60xTksR0mVTB9v3o0lmHGir3c88XKEh8QDe/UlCfOH0CP1s4gKC/T9MVb+DrFPUoBuoyHc14wMyY+dkb/GP41fQ0ZuQXF2RrDxt1jilAVVTBN/JtZG7hvRckn946D058wffkqsGF/Ov+a7vo9c8HQ9lw83AvrBKV+6DQGln9o7u+Ya5Y3OI3r0aI4GPx5zQFmbXS1mTitXxnFzLb85lpn23aIfjdJvaBgUOqUgkIHd366nES3mabyNIsMYWjHJgzp2JShHZsyqEM0ESHl/MjbtvnEcNGbZjbCUapojBVgKoaNuA66nmQ+SR93F2z5DcevjxKw3/wR09jK5vLM90h5cTq7TriTDqfcWnmLgcIC+OJaE1wWOeO/LGx8Cnc+P7tEWfjurRrxwqVD6Nu2MftSs4urBT7143o+/MuoSv9NCAiAIVdA//PNAvjG7Xya6vj8b5vYfSQbgCYRwfzzzIqLrJw9qC17j2bzxA9mPdOMFXtp3zSce0+voOCN1C+Rzc0n+duTABvWf+f1tWx1WX6hgyd/WM9bznXDYFLZ/3lWHy4b0dH1wcnWWfDt7aZgS5HQxqaoydCramw9W3hIIGcPiuHjhbsA+GzRboZ1agbnvmL68R1YbVLV3QPBJp3gzP96NOuSmVvALR8uISffpL72aNWIf5+rKrTixr35/M754CgsLpIU26Mlz/y8EaBE9d1uLSPp3qqMmeUN7imiZ/hkuCI1TcGg1ClP/LC+zEAwwIJebRoztGMThnZsyrBOTenUPKLywgE5abDyUxMEuhdUKBLRAoZdDcOmHvvptGVB90kEdD0Je+10Ur9/mCZZ2wFoRirNFjxC5so3iDz1ARh0adkV+hwOmHFHiebJhePv5/nU8bz4zTzclgBxxQkdeeCsvoSHmPPcdVovfl57gEKHzZzNh/lzU3KJ3kkVCg6HNgM8O7aaNuxP582krcXb95/Rp+wS3aXcMK4ru49k8/5880dsre5BKL7R52xnMIh5bygYBEz/s9s+WlY8kwFmbeBrU4bRs2g2MCfNzPwvmVbyyd1PgbOfq7QFjC9cNLxDcTCYuHIv/zq7L5GhjeDSD00v1KKqyYGhMPZOM3MTXMZarVKy8gq4dtoitjjTZMODA3n5iqHlf+gnDVPTLhAVY4qy5aaZDyBiBgHQv100TSKCOZpVcllJmVVECwtg8y+ubaWISj2h35hSZ3y9bHeJT8NHdW3G2O4tGNqxKQM7NPG8oXBBnikDvmQarPjUVLYrreNos5amz9mVz+wFBGD1P48mfc5m4y+vEzX/GWIwKZiR2Xth+i3Yc57HOumBkhXmbNsUTyhKXwHSh9zI1WtPZOmuzcX7mkQE8+T5A49Zv9CtZSMuGtaeTxaZP7Ke+nE9Y7qdWCtSKh0Om/u/XlW8EH9k52ZcNNyzP0Ity+Khs/uyLzWbX9cdBOpAD0Lxrt5nwQ/3mPvbZpt1OlUoWFQfLdmRwi0fLuVAWm7xvlP6tubZiwfROMxZaGnTLzDjryXT28Oi4fSnzAdSfqpuOaRDE7q3asTmgxlk5hXy/ap9XDS8g0lTvfIL+OmfJkth4v0eF7LJyS/kL+8uZoFbYPyfc/u7UmRFiliW+T99zVdme8fc4mAwMMDixO4tSqxrh3LWC+5e5FrPGhVTfA6Ruk7BoNQJq/ek8o8vXSXGT+3bmlevHGYCn8ICs/7tyCHT9ymz6FbGdmZy+T3zgiNh0CWmOlyb/lUfZGAQPU+/hV1DL+XVtx/jouxPaW6ZyqNW8gb4bIqpwnnyv0zFxFlPw/yXi5++o9P5xC09iXS38Y3q2oz/u2QwMdFlf0p+56SefL1sD7kFDlbtSeX71fuIG9i26mP3sk8W7WLJDvOfZnCgxWPnVa28e1BgAC9cNoRLX59fd3oQivdEtzfvlb1LTcr2xp/Me7MBsm2b9+fv4N+Ja8kvNB+uBFjw91N7cfP4buZ3YPYR+PF+WPFRySf3jjN9Rf28rsmyLC4a1r44/fvzxbtNMAhmnfK1P1bw7GPl5Bdy/XuLmbvlcPG++8/szQXDan7WU+qITmPcgsE5MOrm4ofG9SgZDLaNDmNAu+hjz7HxB9f9nqepdYjUGwoGpdZLyczjxveXkFtg1oRc22QZ9xfOJ+DlAybAc688Vx0te5tZwIGXQFjj4x5vh1bNuCr+Kf71+fm0Xfs21wd9R5Rl1s2xd6lpJt96QIn+WSuixnPehvNxYBamBwZYxJ/Sk5vGdyOwgpm+NtFhTD2xM6/NMumYz/y0gdP6tSE40HfVAStzKD2XJ39wNWC+cVy3an1aHxESxFtXj+D8V+awK6UO9SCUSuXkFzJjxV4+WLCTg2k5PHZef07qXWrWt0+ceb8ArJ/RIIPB7LxC7v96FV8vc830NY0I5oXLhhDbo6XZseFHk2qe4aqCSERzs+au3/m15g/W84a24+mfNlDosFm4PYVtyZl0aRFZ5fPkFhRy0wdLSNrk6gV392m9uGGc91tjSD3S6UTX/R1zTWaO870xtui95HRqvzZlf3i58SfX/Z6n+2KUIn7hv78YRTxQUOjgto+WsudoNmBzd+g3/CvnvwTtSILkjdULBK0AiGxp/lCa+j3cMh9GXu+VQLBIREgQ/718DI1Ou58Jef/H6wVnkWu79cxzCwQXBg7mokPX4nC+HTs2i+CLm0Zz68TuFQaCRW4Z353GYeZzne2Hs/jUmTbqL//5bi1pOaYAT6fmEdx2Uvdqn6uoB2ETZ7/Boh6EqaXWd0jdsD81h2d+2sCYJ3/n7i9WsmLXUfal5nD35yvJKdU2hT7nuO5v+hXysmp2sH6283AW578yt0QgOKBdNDNuH+sKBNd/Bx9fWjIQ7Hc+3LrQ9LyrJYEgQKuoMCb2alW8/cWSqv+eyitwcMsHS5m5wVXxMf6Untw6sfq/Y6SBaNkbwpua+1mHzd8PTu2ahNO9latXb5kpoinbXHUFgsJMRV6RekIzg1KrPfXjeuZuOYyFg38Fvc811k9lHxjezAR4kS3MLaJFye3Ilq594U3KLubiZZZlccO4bvSJacztHzfn7azTuSPoKy4OnEWQZWY5lzh6cnXOHeRhgp3zhrTj0cn9iAoLrujUJURHBHPzhO489aP5j+r53zZx/tB2fimikLTpENOX7y3e/vfk/q5eZ9XUraXpQXjFmwvIK1APwrrGtm2W7jzCO3O28+Pq/SUaoxc5nJnH50t2M8W9SFCLHtCiFyRvMM2it/xuZgsbgD/WH+Svnywr/lAF4OLh7XnU/f20byV8+ReKW0Y0am1SQvucXfMD9tDFw9vz6zoTuH6xZDfxp/Ty6AMvMFVUb/1oKb+tP1i8746Te3DHyT18MlapZwICoOMY2PCd2d4xF1r2Kn74obP78u/EtYzp1oITupRRYdt9VrDLeAhRdorUHwoGpdaavnwPbyRtI4gCng5+nfMD/3Q92HWiKZHeqJUJBANr749ybI+WfHvrWG54fzH377+e1wvjuDrwZwoJ4IWC88kmjEahQfz73H6cN6R6a16mjunMtLnbOJCWy6H0XN6Zs73GPy3PyS/kAbeegucMasu4ni0reIbnRnRuRsLFg7jtI/UgrCtyCwpJXLGPaXO3s2rPset02zUJp09MVHGRoDdmb+WyER0Ick9x7hMHSRvM/XUz6n0w6HDYvPD7Jp7/bVNx39SQwAAePqcfl43s4EpdSz9gZgTznbOlTTvDdb+aBui12MTerWjRKITkjDwOpOUye9OhErOF5ckvdHDHx8v4Za1rBvTWid342yQFglIFnUoFg8OvKX4otkdLfv5bBbN9G91bSqiKqNQvShOVWmnN3lTu/XIloeTxavD/lQwE+54Ll39qirw0alWrA8EiHZtH8NUtY4gbGMN2O4ZHCq7mPwVTSCOSQR2a8N0dY6sdCILp5XXnpJ7F26/O3MKRzDxvDN1jL/2xmR2HzR+nUWFBPBBXcU/Bqoob2Jb7z3T1G5yxYi9P/bgeRxkzTeI/B9JySPh5Ayc++Tt//3zFMYHgCV2a8eqVQ5l19wSev3QI0eFmFnxnSlaJPl9AyVmujT9AYf1ND07Nyue6dxfx3K+uQDAmOozPbhrN5Sd0dAWC+dnwyWWuiqGhjeGyT2t9IAgQHBjAeUPaFW9/sXh3pc8pKHTwt0+Xl/jZuHFcV+46tVeVilKJlOg3uGMOxW+0yuSkwXa3v0G0XlDqGQWDUusccRaMCclP572QJ5kUuMz14LCpcOHblbd7qIUiQoL432VDuP/M3gQGWFiW+XT7i5tG06l51QsplHbRsPZ0dRZkSM8t4JVZW477nJ7afDCdV92u948zetMqKszr17k+titXjXalEr42eyvjn/mDl/7YzKH03AqeKb62bOcR/vrJMk588nde+H0zyRmuDyNCgwK4ZHgHvr8jlk9vHM3p/WMICgwgMjSoxPfz1VlbsN3/QIsZDNHOqpM5qa7eg/XMzrRCzn7xT/5wWws3pltzEm8fy+AOTVwH2jZMvxX2LDHbVgBc9A606k1dUVxFFPh57X5SKvjQqtBh8/fPV5ToLXvd2C7844zeCgSl6toMhBDn2sC0PXB0p2fP2/oHOJwfRLUZANHtKj5epI5RMCi1SkGhg9s/XkbOkf18HPIfTghwawQ/Nh7inquR9X6+UrSOcP59J7Pw/kncfVpvr1X+DAoM4K7TXGsgps3dzt6j2V45d0Vs2+b+r1cXl70f2rEJl43o6JNrmR6E/ZjUx5Vatislm//+tIHRT/zGrR8uZc7mZM0W1pC8AgffLNvD5JfmcN7Lc5m+fG+JNYEx0WHcc3ov5t13Mk9dOJC+bY8t0nT1mM6EBpn3wJq9afy52VUlEssy7RGKrEv02Wvxl6+X7eY/83PYmeIqkHPj+K68d+1Imjcq9aHXrKdh9Zeu7dOfhO6Tamik3tGzdVRxgJtfaDN9+Z4yjyt02Nz9+YoSa5CnjunMA2f1USAo1RMYBB1OcG3vmOvZ81RFVOo5BYNSq/z3pw1s37KOz0Mepl/ADtcDp/4HJj1Uq6rjHY+WUaG0jPL+7OYZ/dswqL3pj5RX4OC5XzdW8ozj9/mS3Sx0Nn4OCrB4/PwBPl3HFxhg8eLlQ7lpfLfiFEOAAofNd6v2ccWbCzjp2Zm8NmsLhzM0W+grq3anMvGZmdz56XJW7Dpa4rERnZvy0uVDmX3PRG6Z0J1mkSHlnqdFo1AudpstKmqTUsx9neD678Dh8Mbwa4Wvl+3mb5+uIM/5kiJDAnnliqHcd0afkmsnAVZ/BTMfd20Pvw5G3lBzg/Ui9+/3p4t2lZwNxqyd/MeXK/nKrZLqlaM68tDZfRUIyvEpnSpaGUdhqWDwDO+PScTPFAxKrTFjxV5+T5rNFyEP0yXAWSjACoDJL8GY2/07uDrCsizuPd2VMvbFkt1sOpDus+sdzsjl8e9dPQWvi+1C7zbea9FRnrDgQP5xRm8W3H8yCRcPYninpiUe3344iyd+WM/oJ37njo+XMX/r4WP+4JTq+339AS5+bZ6z5YsREhjAhcPak3j7WD6/aQxnDYzxeNb7+tiuFH1+8OfmZFbtdltn2HG0qQQMkLEf9iz21svwq80H07n/K1fBpW4tI5l+24mcMSDm2IN3L4FvXE2y6TIezniqzn44FjcohrBg87Oxfn86a/amFT/mcNj885tVfL7EtZ7wspEdePSc/goE5fiV7jdYmT1LIcuZrRDZEtoO8c24RPxIwaDUCuv2pfHBF1/yWcijtLFM70A7MAQufg+GXOnn0dUtY7q3ILaH+ePZYZvZVl95/Pv1HHX2/GvXJJy/1nCZ97DgQM4f2p4vbh7DT3eO4+rRnYgKcxUUyit08O2KvVz6+nwmJczirT+3cTSrZgvr1Dfvz9/BX95dTLazL2BUWBB3ndqTufedxDMXDaJ/u+gqn7Nj8wjOGti2ePvV2W7rXQMCoZfbp/HrZlR77LVFdl4ht364rPjfsE2kxde3nkj3VlHHHpy6xxSMKcgx2827w8XvQqDn7Wdqm8ZhwZzR3xX0fr7Y9By0bZt/fbuajxe6ehBeNKw9j53r22wDaUDaDYVAZ1ZOyhZI31/x8e5VRHucZlpUiNQz+qkWvzualcfr097k7YB/09TKAMAOicS68sta3TOrNnOfHfx57QGW7Dji9WvM23KYL5e6Pr3/z7n9/dLbsEivNlE8Mrk/C+4/macvHMgg98IbwJZDmfw7cS0nPP4b8Z8uZ/H2FM0WVoHDYfPED+t48JvVFC0LbN80nK9vGcNtJ/WgRen1bVV047iuxfd/WLWPHYczXQ+6N6BfN8PzKoC11CMz1rDBOWMfGhTArYPDaFxWb9G8zJJN5cOawOWfuZpn12EXDXdVT/5m+V5y8gt5ZMZaPpjvKupx/tB2PHnBQAWC4j1BodB+uGu7stlB92Cwl9YLSv2kYFD8qtBh895bz/NUzn+ItMz6roKwZlhXJ0KXcX4eXd3Vv100Zw9yzbQ89eN6rwY+uQWF/PPrVcXbZw5ow8TelfcLqwkRIUFcPLwD0289ke/uGMsVJ3QkMsRVdCi3wMFXy/Zw4avzOPvFP9mfmuPH0dYNOfmF3PHJshLr+Qa0i+arW8aUPZtVDf3bRZeY0X59ttvawa7jIcR5nSPb4OBar1zTH75ZtodPFrlmvh46ux8dosr4r9jhgK9ugP0rzXZAEFzyPjTvVkMj9a1RXZrToVk4AKnZ+Vz+xnymzd1e/PjkwW3574WDPG5KL+KxEusGKwgGj+6CA85U7sAQ099YpB5SMCh+9cv7T3Fb8mOEWCZdKju8DUHX/WRSOeS4/P2UngQ5/5BauC2FmRsPVfIMz+TkF/LvxLVsTTYzN41Cg3jo7H5eObe39WsbzWPnDWDhPyfxxPkD6N+u5HrG1XvS+MdXK/00urrhSGYeU95aUKK8/6Q+rfj0xlFebx9y83hXoPP5kt2udiFBodDjFNeBdTRVdMuhDO53+xDl7EFtuWxkh7IP/v3fsN6teupZz9arD8gCAiwuGuZ67Ut3Hi2+HzcwhmcvUiAoPuJpMLjJrXBM51gIbeS7MYn4kYJB8Q/bZv3nj3D6ticIsMyMVUp4J8Jv/BVa9qzkyeKJzi0iudTtD82nf9xw3C0X/thwkNOem10ilevu03rRurH3ewp6U2RoEJeN7Eji7bF8e9uJXDqiQ3HtjZkbDrE9ObPiEzRQOw9nccErc1m03ZVmPGVUJ16bMtwnKcGjuzVnoFs13Glzt7kedE8Zr4MtJnLyC7n1w6Vk5ZkPvrq0iOTx88opirL8Y/gzwbU96lbTY7WeuWBY+2Nq4JzRvw3/d8ngY6upinhL+5FgObNFDq6FrJSyj9vgliKqlhJSj+m3rdQ82+bwN/fSe43rj51tIT2IvuU3aFLOp+RSLXec3IPwYPOf3rp9aXy7Ym8lzyjbrpQsbnhvMde8s4gdh1390Mb1bMmVozpV8MzaZ2D7Jjx5wUBO6uVKa31v3o4KntEwLd91lPNenlM8Awxw/5m9eXRyP5/N2FiWxU1us4Pvz9tBRm6B2ehxiqvww4FVkLKtjDPUXo8mrmX9frNOMCQogBcvH0JUWesEd8yDGXe4tnucCqf+u4ZGWbPaNQkntkfL4u1T+7bmhcuGeK33qkiZQhtB28HODRt2LTj2mLxM2Dbbtd3ztJoYmYhf6Deu1KzDW8j7dCrNV7xWvGtZQH+a3fIzgVEtK3iiVEerqDCuG9ulePvZXzb8f3t3Hh9Vdf9//HWykBAgARJIIJCEsIPsa8AIUnENWlEREUGtCnXpr421WtuvtdVvtbWmamsrWBRRUUG/1TYuoCAhyCYIKrJDwr6FNQkJSWbu7487mUxCAgkkmUzm/Xw87mPm3nvm3jOTOZP7uWejqKT687SdKXHw98XbGPvXDBZuPOTeHh4axFM39Ob1O4f4bFOuKSMS3M/nr91DfmnQISz84SATZ67gaL498mqToABenjSQ+y7rXOfD+1/VO4aEyDAAThWW8O5qVy10SAvo7NFnZ7Pv1A7+59v9zF1VVpv+Pym96N2+klFXj++C924Hh2vE2zY94aZZ9oiqjdT//vgSruodzU9Hd+bvkwYqEJT6cb75BncuAYermXrbXtDKt256itSEfnWl7lkW7MzAmjsB62+DaLL5Q/euRdZgmv/kQyJatvZe/hq5+0Yl0irMroHYc6yAuauqVwuWsfUIV7+QyV8WbqWwuCyAvGVQBxb/cjR3JCX4bCAIkNwlik5RzQDILSzhw/X7zvMK/zD7qyymvbXW/TdvFRbM3HuGcV3fSua/qwOBAYZ7PUYW/VdmVtkNjB4eE9D7SFPRrJx8fv1BWb/U6/q2Y/KwuLMTFp6CubfC6aP2elgkTHoXQut+3k5v6tg6jBl3DObRq3vQJEiXJFJPzjffoOcooqoVlEZOv7xSd4oLYd1bOP85EuZcj9m6AENZn7V5JaMoHj+brrGqEaxL4aHBPHB5F/f63xZvL2t6V4l9JwqY/uZapr62miyPJoK92oXzwU+TeO6Wfhc9jUBDEBBgmJJUdrf3jeXZfj3VhNNp8VT6Rp7870b3zA1xrcP44KcjGJxQvzdrbhrYwf0dO3iqkI9KA/Xu14Jx/dvaswpyD1VxhIahtJ9gvqufYHxkGM+O73N27arlgA9+Akc22euBTWDiXGiVUL8ZFvEXccMBVzncvx7O5JXtczph68Ky9W7XINKYKRiU2pd3GJY8S0lab/joAQIO/1Bu9yLHACYVPc7B0X/h6n7qI1gfJg+Pp32EPcjL0fwiZmWe3d/qTImDl7/czhXPZ/DZD2UT8bYIDeL31/fmPw+OZFB846rBvWlQB8Jc005sPZTHyp1VDCTQyBUWO7j/7W+YtazsezEgriX/vn8EiW3qfwS90OBA7hqZ4F6fsXSnPfhRs0iPO/oWbPm43vNWE09/vJGNB04B0CTQbmpbWT/BzjtmwzaPi89xL7kuVkWkTjRtBdGuUbAtB+xdXbbvwHrIc/0PbNq6/LyEIo2QgkGpPYd+wPHv+3Gk9YIlzxBUkOPeddoKYU7JWK4qSWNBvxd57P5p/OwKjRpaX0KDA/nF2LLPe+bSHRzNO+Nez9x2hGteyOS5BVsoKHa4t980sAOLHx7N1BEJjXJ0v/DQYMYPjHWvz1mR7b3MeMnRvDNMenVluRsAV/WO5p17hxPpxRrgycPjaR5ij1i6/XAeizYftneUayracKeYSP9uf7lRd39zXU8uia2kn+Da2XTc+5+y9Ut/Af1vq4ccivi5qqaY2OoxpUTXKxt1n10RUDAoF8vphC2fcWZWCvxzBIHfvk2gs9i9+4DVmmeLJ3Jb81kUX/0c8x6fwp9v7kffDi29l2c/NX5gB7q2tWt58osc/P3L7ew/UcD9b6/ljlmry40a2SOmBfOnJ/H8hH60aeH7TULPZUpSgvv5wo2H2H+iwHuZqWdZOfnc9M/l5eZ4u3tkJ/5x+yBCg717ARTRNJhJHn3rXsnYYT/p6REMZi2FghP1m7FqyM7J57EPyuYTvOaSmHJNkgHIz4FPH4P01LJtPVJgzBP1lEsRPxeXVPa8XDDo0V+wu6aUkMav9ieKEv9QlI9z3VwKl71MWG4WFcOF9c7OvO68lpLu45iU1JlHO0fW+SiEcm6BAYZHrurOfW+uBeCtlbt47+s97nnPAFqEBJF6ZTfuGB7fKGsCK9MtugUjOkeyfMdRHE6Lt1ft4pGreng7W3Vu26FcJsxYwfHT9s0bY+CJlF7cNbLTeV5Zf+4e2YnXv8qi2GGxdtdxvs4+xpCEDtB+AOxfB84S+y5+v1sv7AS5hyBnK0R2gfDaGSDnTImDB9/5xt0vt2Prpvzp5r5lv39ncmHFy7D8b1Dk0U8ppg+MnwkB/lHuRLzOs2Zw7xp7nIOC43YzUYCAIOg8xitZE6lPCgbl/CwL8lwXTUe2cGbfBvjhA0JKcgnzSOawDJ86h/JhyPX0HjqWXw+LJyaiYU9G7m/G9opmUHwr1u46TrHDothRFgiOHxDLY9f2oG0L//ubTUlKYPkOexTHd1bv4aExXb1eM1bXnv54kzsQDA0O4MWJA7iqd4yXc1VeTEQoNw6IZd6avQC8smQHQ+5sbU9Av3+dnWjzf6sXDDpK4NAG2LPa7h+0ZxWccDXjNIHQ41oYci90uoyzZkKvgT9+vIkN++x+gsGBhpcnDSQ8NBhKimDt65DxZzidU+41J8N7EjFpHjRpdsHnFZEaahEDrTvDsR32NBL7v7Gvc0rFj4DQSpp2izQyCgaljKMEjmdDzhZX4LfVfszZBmdOupNVrAU8ZTXlXccYfuhwK1ePHMo/e0VrrqgGyhjDo1f3YMKMFe5tPWJa8PvrezMsMdKLOfOuK3q2pX1EKPtPFnIsv4iPvzvATYM6eDtbdWbTgVNkbD0C2HHP2/cMa7CDA913WWfmr92LZcGizYfZeiiXbj3GwaI/2Am2L4Ki09AkrPwL84+6gj7Xsv8bKD5d+Uksh93/cNN/Iao7DL0X+k205zasgU+/P8AbK8qmbnn82p70bR8O382DxU/DiQrTurTpAT96gnUHwhgd3r5G5xKRWhA/wg4GwZ5vcN83Zfs0iqj4CQWD/uhMHhzd5hHsbbEDvqM7wKO/3/lkO6N5J+BazIDbuWVkT+7zwqiDUnNDO7XmsWt68NmGg1zfrz1TkvynSWhVggIDmJwUz58/2wLYA8k05mBwRmn/O+z+bA01EATo0rY5Y3tGs3CjPY3EjIydPD+hnx205WyxA7ztX0DrxPLB37Ed5zkyEBRqT99wZHPZtpwt8Mkv4Ysnod9tMOQeaHv+ZsO7j57mVx7zCV7Vqy13ttkKMybbNZKewjvA5b+2jx8QCAeXnD+vIlL74kfCujft5zu+rBAMan5B8Q8KBhsry7IHKMjZAke2uJt4krMNTu2t8eHyaMp2Z3u2W7HscLYnp0VPho75MT/v35GmTRp3c7rGaPqozkwf1dnb2WhQbh3ckRe+2EZRiZNv955k/Z4T9O/Y0tvZqnV7jp3mv98dcK/7wvdg2qjO7mDwo/X7ePjKbrTvmQKZdvDOvDuqd6CIjtBhCHQcai/RfSCoCRzeBF//C759t6wfX1EefP2qvSQk27WF3a+DwLP/bZb2E8wttPsJXhWxm5eL/oaZu6J8wqatIPlhuzlqsP81xxZpcMqNKPpV2fOobhDZ8H8bRWqDgkFf53TCyd2uWj6PwC9nq90RuqZatIeortCmOwXhnXltSzBvbAvhMC0pnaD17pGdeOrq7o2+T5X4l8jmIYzr254PvrFvlsxZnk3/W/t7N1N1YNayLBxOe1b5EZ0jfWJk30HxrRia0JrV2ccocVrMWpbF/wwcB5nPV/2igGBo3x86DC0L/qpqitm2J1z3PPzod3ZA+PWr5fsOZWfaS3gsDLoLBk2F5m3du5/9dDPf7T1JZ7OPR4Pf48oza8DznltwGAy/H0b+TH2QRBqSlnF2TX3Fm+SqFRQ/omDQ1+Tn2E0aDn5vB4BHt0FJYc2OERBkN6mK6mYvbbrbAWBkVwgNB+x55x6Z/x0HT5UdO7ZlU567pS8jOkfV5jsSaTCmjoh3B4Pp3x3g8et6EuXFufZq2/H8It77eo97fZoP1AqWmj46kdWzjwHwzurdPHT55bSMvxR2LbMTNI92BX3D7ACwXb/z1r59u+cEn244iMPppHlIMM1Dg2gRcg3NL0uhw4k1dNzxNi13L8RYTvsFp/bBl09Dxp+g949hyL0sOBXHZ1+t5U9BH3BzYAaBxio7QUAQDJwKo35lD1YhIg2LMXbt4Pfzym/vpiklxH8oGPQle1bDvCmQe+D8aQGCm0GbbhWCvu7QuhMEBlf6ktNFJTz76WbmrCg/0MHNgzrwxLhe9qh4Io1U3w4tGRDXknW7T1DkcPLu6t08OKart7NVa95YkU1BsT2CbK924VzW1Xdu7FzevS3do1uw5VAup4scvLlyNw/dPg8ObrADrZZx1RoF1LIslmw9woyMHazceewcKQOBKbTjOiYFLWJi4GLaGHuUUJzF8P18+H4+iVZHloQcJMRU6G/dezyM+a2amok0dBWDwdAI6Djce/kRqWcKBn2BZdlDkn/yq8oHeGnWxg7yKgZ+4bE1GiL9m93HeXjet2R5TD4e2awJfxzfp8ENOS9SV6YmJbBu93oA3lq5m+mjOjeKAXYKihy8sTzbvT5tVKJPzf1pjGHaqERS530LwOzl2dx7WSKhccOq9fqiEif//XY/M5fuZMuh3Gqf9wCRPF8ygb+V3Mg1AauYEvQ5gwK2ufd3NXvKvyDxcrjid/ZciCLS8MWPLL/eZWylfYNFGit92xu64kL45GFY91bZttCW9h3nmL52886wixsJsKjEyUuLtvGPJdtxerRwGtsrmmfG92lUzeREzueaPjE8/XETcvKKOHiqkIUbD3Ftn9qZkNyb5q3Z455XsEOrplzng+9pXL/2PL9wK/tOFHA0v4j5a/ZwR1LCOV+TW1jMu6v3MGtZVrlm7wCBAYZxfdvRs104eWdKyC0sIe9MCXmux9wzJeQVFpN/xkHemSA+OnMpHxVdSm+TxZTAz7kh8CtCXTWC+VF9aXbtU5A4uo7evYjUiaiuEBZVNv+nmoiKn1Ew2JCd2GOPklc6uTJATB+49S17OPRasOVgLr94bz0bD5xyb2seEsTvxvXi5kEdfKrmQKQ2hAQFMmloHC8t3g7AG8uzfT4YLHE4eTVzp3v93uREn6ztDA4M4CeXduIP6RsBmJm5k9uGxlX6Xg6fKuS1r7J5e9Uu9yifpcKaBHLb0DjuvrQTsS2bVvv8TqdFflFpwDiVLadyaLr9EyJj4ojsn3JRk9WLiJcYAwMmw1cvQEQcdFcwKP5FwWBDtXMJvH83nD5atq3vREj569mTK18Ah9Ni1rKd/GXBVoocTvf24Ymt+cst/ejQ6uLPIeKrJg2L5+UlO3A4LVZlHWPzwVP0iAn3drYu2MffH2Dv8QIAWoUFM2FwRy/n6MJNHNqRlxZv48TpYvYcK+DTDQcZ169slNDth3OZuXQnH67bX+63DSCqeQh3jUxg8rB4IsJq3v85IMDQIjSYFqHBEAFEt4CuD1zsWxIRb7viSbhkPLTqBCEtvJ0bkXqlYLChsSxY/pI94XHpCHYBQXDVMzD0Xo7kFfHlt3s4U+KgSVAATYICCA4MoEmg/dz9WGFfSOnzoABy8s7wyPvfsTqrbPCEJkEBPHp1D+4akUBAgO5ui3+LiQjl6t4xfPy9PVjTG8t38cz4Pl7O1YWxLItXMspqBaeOSPDpuUHDmgQxJSmBlxbZ/fZeydhBSt92rNl1nBkZO/hi0+GzXpMY1Yx7L0vkxgGxmhJHRM5mjD0CsYgfUjDYkJzJg48egI0flm1rHo11y2y+dvbgzXfX89mGAxQ7rCoPcSEuiQ3nrxP60zVad8NESk1JincHgx+u28djV/e4oNokb1u6LYdNrmbgTYMDmXqePna+4M4RCcxcuoPCYic/7D/FVS8sZeuhvLPSDYxrybRRnRnbM1o3uURERCqhYLChyNkO790ORza7Nzlih/Jh1z/y6r8L2HxwRa2fMjDA8MDlXXhoTBeCfbD/kEhdGtqpNT1iWrD5YC4FxQ7mr93DPcmJ3s5Wjc3I2OF+fuuQjrRq1sSLuakdrZs14dbBHXnDNQVOxUDwip7RTB+VyOCEixtcS0REpLFTMNgQbP4E/j0NzpQN4rIqajzT9t7MiR1nN3kaFN+Knu1aUFTitBeHk6ISy/XooKjESbHD8tjn8VjipNjh5JLYCJ68vjf9O7asxzcq4juMMUwdkcCv/+97AN5cuYu7R3byqRqm7/aeYPkOu99xYIDhJ5d28nKOas89yYm8tWo3DtcQyE0CA7hxQCz3XtaJLm3VykFERKQ6FAx6k9MJGc9Cxp/cm4oI5vHiu3l/76hyScOaBPLjAbFMHhZPr/a+O5CFiC+5oX97nvlkE6cKS9h19DQZW49weY+23s5Wtb3iUSs4rm87OrZuPANDdWwdRtqEfsxbs4c+sS25a2QC0eGh3s6WiIiIT6n3YNAYcxnwS2AQ0B64y7Ks2ed5TR/g78BQ4BgwA3jKsqza7TxXnwqOw//dB9sWujfttaKYVvQLfrDK7t53aducO4bHc+PAWMJDfa+/kogvC2sSxITBHfnXsiwA3liR7TPBYHZOPp9uOOhenzaqsxdzUzdu6B/LDf1jvZ0NERERn+WNmsHmwAZgjms5J2NMOPA5sBQYAvQAXgfygefrLpt1Jyw3i4KXH6Jp3m73tkzHJfys+EGOE05ggOGq3tFMHh5PUmKk5voT8aI7kuKZ9VUWlgVLthwhOyefhKhm3s7Wec3M3Enp7bJR3drQs51aFIiIiEh59R4MWpb1CfAJgDFmdjVecjsQBky1LKsA2GCM6QGkGmPSfKl28FRhMevSZzJsw5OEUuTe/s+ScTxXcitRLZry82FxTBwSR0yEmjuJNATxkc24vHtbFm+2++/OWbGLJ8b18nKuzu1wbiHvr93rXp/eCGsFRURE5OL5Qp/BJCDTFQiWWgA8BSQAWd7I1IU4tOxNRm143L2eZ4Xyy+LpnEy4hr8nxTO2V7RG9RRpgKYkxbuDwflr9/Dwld1oFtJwfz7fWJ5NUYk9T2m/ji0ZnqhRNUVERORsDfdqpkwMsLfCtkMe+8oFg8aY+4D7AKKjo1myZEld56/aDO2BOLqym51WO16PfITkxE7ENi+Eo1v4KnOLt7MoUq/y8vIaVBmtitOyiA4zHDptkVtYwp/f+5LL4xpmH96CEovXM0+71y+NLCAjI8OLOZLz8ZVyIFKXVA5EbPVdFnwhGKwRy7JmAjMBBg8ebI0ePdq7GapgcbPW5H/1NF3vm81T4bpbL/5tyZIlNLQyWpVpwVn8IX0jACuONuHJOy5rkP15X126k9MlmwDoFNWM1AmjCPSh6TD8kS+VA5G6onIgYqvvsuALbRIPAtEVtkV77PMpY5KGcmJwKs0UCIr4lJsGdSCsSSBgT3K+cucxL+fobEUlTmYtK2sscW9yogJBERERqZIvBIMrgGRjjOeIKmOB/UC2V3IkIn4nomkwNw4om8Zgzops72WmCh+t38fBU4UARDUPYfxATbsgIiIiVav3YNAY09wY098Y0991/jjXepxr/zPGmEUeL5kLnAZmG2MuMcaMBx4DfGokURHxfVNHJLifL9x4iP0nCqpOXM+cTosZS3e61+++NIHQ4EAv5khEREQaOm/UDA4G1rmWpsDvXc//4NrfDnCPg25Z1knsmsD2wBrgZez5BdPqL8siItAtugVJiZEAOJwWb6/a5eUclVm8+TDbD+cB0DwkiNuHxXs5RyIiItLQeWOewSVAlZ1YLMu6s5Jt3wOX1V2uRESqZ+qIeFbsPArAO6v38NCYrg2iBu6VjB3u55OGxRHRtGGOdioiIiINR6MbTVREpC5d0TOa9hGh7D9ZyLH8Ih6c+w2RzUIocVo4nE7Xo0WJ08LperTXne7tDqdFicMiMMAwonMkk4fH07F12AXnaU32MdbsOg5AcKDh7pGdauvtioiISCOmYFBEpAaCAgO4fXg8zy2w5wX9YtPhizre9/tOMjNzJz/q0ZY7khJI7hJFQA1HAPWsFfxx/1hiIkLPkVpERETE5gujiYqINCgTh3SkVVjtNcO0LDuonPraan6UlsFry7I4VVhcrdduO5RbLiCdNiqx1vIlIiIijZtqBkVEaiiyeQgfPjCSzG05AAQFGAIDDEGBhsCAAAKNaz3AEBhoyvYHBJRtDzDsP1HA26t2k7H1iPvYWTn5/CF9I39ZuIUbB8QyJSmB7jEtqsyL5wiiY3tF06Vt1WlFREREPCkYFBG5APGRzYiPbHZRx7gkNoIre8ew80geb63czfy1e8gtLAHgdJGDt1ft5u1Vuxme2JqpSQmM7RVNUGBZg44DJwv4aP0+9/p01QqKiIhIDSgYFBHxssQ2zXliXC8evrIbH67fx5zlu9hyKNe9f+XOY6zceYx2EaHcPiyOiUPjiGoewmvLsih22NOtDkloxaD41t56CyIiIuKDFAyKiDQQzVzzA04aGseqrGPMWZHNgh8O4XDaAd+Bk4X8ZeFWXlq0nWv7xPD5xkPu104f1bmqw4qIiIhUSsGgiEgDY4xheGIkwxMjOXCygLmrdvPO6t3k5BUBUORw8uH6/e70Xds25/Lubb2VXREREfFRGk1URKQBaxfRlIev7M5Xj43hxYn9GRjX8qw000Z1rvF0FCIiIiKqGRQR8QEhQYHc0D+WG/rH8v3ek8xZkU3mthyGJbbmhv7tvZ09ERER8UEKBkVEfEyfDhE8d0s/b2dDREREfJyaiYqIiIiIiPghBYMiIiIiIiJ+SMGgiIiIiIiIH1IwKCIiIiIi4ocUDIqIiIiIiPghBYMiIiIiIiJ+SMGgiIiIiIiIH1IwKCIiIiIi4ocUDIqIiIiIiPghBYMiIiIiIiJ+SMGgiIiIiIiIH1IwKCIiIiIi4ocUDIqIiIiIiPghBYMiIiIiIiJ+SMGgiIiIiIiIHzKWZXk7D3XGGHME2OXtfFQiCsjxdiZEGgCVBRGVAxFQORApVRdlId6yrDaV7WjUwWBDZYxZY1nWYG/nQ8TbVBZEVA5EQOVApFR9lwU1ExUREREREfFDCgZFRERERET8kIJB75jp7QyINBAqCyIqByKgciBSql7LgvoMioiIiIiI+CHVDIqIiIiIiPghBYMiIiIiIiJ+SMGgiIiIiIiIH1IwWIEx5tfGmK+NMaeMMUeMMf81xlxSIY0xxjxpjNlvjCkwxiwxxvSukOY3xpivjDH5xpizOmYaY+40xlhVLEM80sW58pBvjMkxxrxkjGnisb+dMWauMWazMcZhjJldBx+L+Jn6KgeuNEOMMV8YY064lkXGmKEV0vQxxmS4zrPPGPOEMcZ47O9tjHnfGLPTVYaerMWPQ/xYPZeFHxljlhtjco0xB40xfzLGBFVIo7Ig9a42yoExJsEYM8v13SxwPT5jjGla4TjnvO5xpRlljFlrjCl0HWd6hf2XGWP+4yojljHmzjr4WEQaBQWDZxsN/AMYAYwBSoAvjDGtPdL8CngYeAgYAhwGPjfGtPBIEwL8H/BCFed5D2hXYXkL2AmsATDGBAIfAy2AZOA24Gbg+QrnyQGeBVbV/O2KVGo09VAOjDHNgc+A/cBwIAk4ACwoPY4xJhz4HDjkOs//Ax4BUj0OFQZkA78Fsi7oHYtUbjT1Uxb6AZ9gf9cHALcC12P/tpemUVkQbxnNxZeDHkAg8FOgtyvdFODF0gNU57rHGNMJu6wsxy4rzwB/M8bc5JGX5sAG7DJScLFvXqRRsyxLyzkW7B8UBzDOtW6wL1Z/45GmKZALTKvk9TfbH/N5zxMGnAAe99h2DeAEOnpsmwwUAuGVHCMdmO3tz0xL41vqqhwAgwEL6OSxrZNr22DX+k+BU0BTjzS/BfbhGhG5wjE3AE96+zPT0jiXOiwLfwTWVdg2DvtCtoVrXWVBS4NYLrYceKS5HzjqsX7e6x7gT8C2Csf5F7CiinPkAXd6+zPToqWhLqoZPL8W2DWox13rnYAYYGFpAsuyCoCl2HfMLtQEoBnwmse2JGCTZVl7PLYtwL7DPOgiziVSU3VVDrYAR4CfGGNCjDEhwL3AbuAHV5okINN1/FILgPZAQo3ficjFqauyEIJ9weupAAil7PdeZUEaitoqB+Eex4DqXfckeZ7HI81gY0xwzd6GiCgYPL8XgfXACtd6jOvxUIV0hzz2XYj7gHTLsg56bIup5Dw52HfjLuZcIjVVJ+XAsqxc7OZHE4DTruVWYKzHBW9l5eCQxz6R+lRX/xMWAMOMMZONMUHGmFjgCde+dh7nUlmQhuCiy4ExJh74JXbz01LVue6pqhwEAVHVyr2IuCkYPAdjTBpwKXCTZVmOOjxPb+w7Xa/W1TlELlRdlgPXwAGvASux+wyOBNYBHxljmtXmuUQuVl2WBcuyFmJfGL+MXUO4FbtfFNjN5kQahNooB8aYaOz+4p8Df63F7IlIDSkYrIIx5q/YHZfHWJa102NXac1ddIWXRHvsq6n7gD3YP4yeDlZynijsDtgXei6RaquHcjAJ6AzcZVnW15ZlrXRtiwNu9DhXZefxzIdInaqP/wmWZaUBLbG//1HAR65dpedTWRCvqo1yYIyJAb7E7tN6h2VZnqPrVue6p6pyUIJdiygiNaBgsBLGmBcp+7HbXGF3FvYP0ViP9KHYo14tv4BzhQJ3AK9ZllXx7u8KoKcxpoPHtrHAGWBtTc8lUhP1VA7CsAeL8fzuO13bSn+fVgDJruOXGos9Aml2Dc4lckHq83+CZdvvaiZ9G/aNwm9cu1UWxGtqoxwYY9oBS4BNwG2WZZVUOE51rntWeJ7HI80ay7KKa/7ORPxb0PmT+BdjzMvYwdmPgeOuO1gAeZZl5VmWZRljXgAeN8Zsxm7K81vs0armehwnDmiNq1O/Maa/a9d2y7LyPE55MxBB+YFjSi3EHkRjjjHmYSASeA541bKsUx7nKj12OOB0rRdZlrWx5p+ASL2Wg8+xv9P/MMa8hB0APobdP2SxK+1c4HfAbGPM00A3V5rfl95Rds1B1cuVPhSIcZ0rz7Ks7bXzqYg/qs//CcaYR7BbiDiB8djf8wkeTfFUFsQraqMcGGPaYweC+4GfA1GmbIrMI67veXWue14BHnSdbwZ294I7sQPV0vw2B7q4VgOAOFc5OGZZ1u7a+ExEGg1vD2fa0BbsGonKlic90hjgSexhlAuBDOCSCseZXcVxRldIlwF8co78xGFPGXEaOAq8BIRUI8/Z3v4stfjuUp/lAPuO7jLsqVWOYzcfGlHhOH2wR6UrdJ3vd3gMpY99gV3ZeZZ4+7PU4ttLPZeFxa5yUIDdj/aaSvKjsqCl3pfaKAfYAVtVx0nwSFed655R2DXmZ7BrJadX2D+6ivPM9vZnqUVLQ1uMZXk21RYRERERERF/oD6DIiIiIiIifkjBoIiIiIiIiB9SMCgiIiIiIuKHFAyKiIiIiIj4IQWDIiIiIiIifkjBoIiIiIiIiB/SpPMiIiKVSE5PvRN43WPTaeAIsA54B5ifmZJWo/mZktNT+2NP3P1SZkrasVrJqIiIyAVSzaCIiMi53QIkAdcC/4M90fU7wOfJ6alNa3is/tgTxbeuzQyKiIhcCNUMioiInNv6zJS07R7rbyanp84H5gN/Bh7yTrZEREQujrGsGrVwERER8QsezUS7VggGS/f/G7gGaJ2ZknY6OT3198A4oAtQBHwHPJ6ZkraywvEq6pSZkpadnJ4aBDwCTAU6AUexayB/k5mSVljLb09ERETNREVERC7QJ0AIMNi1Hgv8FbgBuBM4DCxNTk/t49r/MfC063lp09Mk4IBr21vAb4G5wHXAM8BPgLfr8k2IiIj/UjNRERGRC7Pb9dgOIDMl7Z7SHcnpqYHAZ8APwD3A/8tMSTuSnJ66w5WkXNPT5PTUZOBWYGpmStoc1+YvktNTjwFvJaen9s9MSVtfp+9GRET8joJBERGRC2NcjxZAcnrqFcBvgL6UHyAmqxrHuhq7aen7ruaipRa6Hi8D1l9MZkVERCpSMCgiInJhOroeDySnpw7Ebja6ALtp5wHAAfwLCK3GsdoCTYD8KvZHXlxWRUREzqZgUERE5MJcBxQCa7FrBEuA8ZkpacWlCZLTU1sBJ6pxrKOuYyVXsX//ReVURESkEgoGRUREaig5PfUm4HrgRddIomHYNYGWR5oxQBzlm4mecT1WnJ/wM+BRICIzJW1RnWVcRETEg4JBERGRc+ufnJ4ahd2MMw5IwR4N9HPg1640nwE/B2Ynp6e+DnTDnqB+X4VjbXQ9PpCcnvoGUAx8l5mStiQ5PfUd7D6DacBqwAkkYE92/2hmStrWunl7IiLirzS1hIiIyLnNB1Zg9wf8X+zpJCYCV5fO/5eZkrYA+BkwEkgH7gamAOXmJ8xMSfsWeBJ7PsJlwNdAe9fuya59NwMfAe8DDwLbgEN19N5ERMSPadJ5ERERERERP6SaQRERERERET+kYFBERERERMQPKRgUERERERHxQwoGRURERERE/JCCQRERERERET+kYFBERERERMQPKRgUERERERHxQwoGRURERERE/ND/B31ga+M2h0p1AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,7))\n",
    "\n",
    "plt.plot(returns1['Port_return_Cum'],label='Portfolio', linewidth=3)\n",
    "plt.plot(TAIEX['Return_M_Cum'],label='TAIEX', linewidth=3)\n",
    "\n",
    "ax.xaxis.set_major_locator(ticker.MultipleLocator(12))\n",
    "\n",
    "plt.title('Portfolio V.S TAIEX',size = 18, color = 'mediumseagreen')\n",
    "plt.xlabel('Date', fontsize=16, color = \"mediumseagreen\")\n",
    "plt.ylabel('Cumulated Return', fontsize=16, color= \"mediumseagreen\")\n",
    "plt.grid(True)\n",
    "plt.legend(fontsize=\"x-large\")\n",
    "plt.xticks(fontsize=14 )\n",
    "plt.yticks(fontsize=14 )\n",
    "# plt.savefig(\"TAIEX.png\",dpi=150)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "14d4fbff62c0e9dc96a00571d36e862ff94d0b95e5af95c3927533226faba3a4"
  },
  "kernelspec": {
   "display_name": "Python 3.9.0 64-bit",
   "name": "python3"
  },
  "language_info": {
   "name": "python",
   "version": ""
  },
  "metadata": {
   "interpreter": {
    "hash": "14d4fbff62c0e9dc96a00571d36e862ff94d0b95e5af95c3927533226faba3a4"
   }
  },
  "orig_nbformat": 3
 },
 "nbformat": 4,
 "nbformat_minor": 2
}