DCA_Crypto.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install yfinance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import yfinance as yf "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Ten cryptos to check "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "CryptoPar = ['BTC-USD', 'ETH-USD', 'BNB-USD', 'XRP-USD', 'ADA-USD', 'DOGE-USD', \n",
    "           'SOL-USD', 'DOT-USD', 'TRX-USD', 'LTC-USD']\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# Testing Bitcoin"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### We use '2020-12-31' as date to begin the analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    }
   ],
   "source": [
    "df = yf.download(CryptoPar[0], start='2020-12-31')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BTC-USD\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2020-12-31', '2021-01-31', '2021-02-28', '2021-03-31',\n",
       "               '2021-04-30', '2021-05-31', '2021-06-30', '2021-07-31',\n",
       "               '2021-08-31', '2021-09-30', '2021-10-31', '2021-11-30',\n",
       "               '2021-12-31', '2022-01-31', '2022-02-28', '2022-03-31',\n",
       "               '2022-04-30', '2022-05-31', '2022-06-30', '2022-07-31',\n",
       "               '2022-08-31', '2022-09-30', '2022-10-31'],\n",
       "              dtype='datetime64[ns]', freq='M')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# buydates took last day of month --> I supposedly bought bitcoin those days. \n",
    "print(CryptoPar[0])\n",
    "buydates = pd.date_range(start=df.index[0], end=df.index[-1], freq='1M')\n",
    "buydates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BTC-USD\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2020-12-31    29001.720703\n",
       "2021-01-31    33114.359375\n",
       "2021-02-28    45137.769531\n",
       "2021-03-31    58918.832031\n",
       "2021-04-30    57750.175781\n",
       "2021-05-31    37332.855469\n",
       "2021-06-30    35040.835938\n",
       "2021-07-31    41626.195312\n",
       "2021-08-31    47166.687500\n",
       "2021-09-30    43790.894531\n",
       "2021-10-31    61318.957031\n",
       "2021-11-30    57005.425781\n",
       "2021-12-31    46306.445312\n",
       "2022-01-31    38483.125000\n",
       "2022-02-28    43193.234375\n",
       "2022-03-31    45538.675781\n",
       "2022-04-30    37714.875000\n",
       "2022-05-31    31792.310547\n",
       "2022-06-30    19784.726562\n",
       "2022-07-31    23336.896484\n",
       "2022-08-31    20049.763672\n",
       "2022-09-30    19431.789062\n",
       "2022-10-31    20495.773438\n",
       "Name: Close, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract from df the records on last day of the month and just for Close column\n",
    "print(CryptoPar[0])\n",
    "buyprices = df[df.index.isin(buydates)].Close\n",
    "buyprices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BTC-USD\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2020-12-31    0.017240\n",
       "2021-01-31    0.015099\n",
       "2021-02-28    0.011077\n",
       "2021-03-31    0.008486\n",
       "2021-04-30    0.008658\n",
       "2021-05-31    0.013393\n",
       "2021-06-30    0.014269\n",
       "2021-07-31    0.012012\n",
       "2021-08-31    0.010601\n",
       "2021-09-30    0.011418\n",
       "2021-10-31    0.008154\n",
       "2021-11-30    0.008771\n",
       "2021-12-31    0.010798\n",
       "2022-01-31    0.012993\n",
       "2022-02-28    0.011576\n",
       "2022-03-31    0.010980\n",
       "2022-04-30    0.013257\n",
       "2022-05-31    0.015727\n",
       "2022-06-30    0.025272\n",
       "2022-07-31    0.021425\n",
       "2022-08-31    0.024938\n",
       "2022-09-30    0.025731\n",
       "2022-10-31    0.024395\n",
       "Name: Close, dtype: float64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How much bitcoin bought monthly: if a use us $ 500\n",
    "print(CryptoPar[0])\n",
    "btc_amt = 500/buyprices\n",
    "btc_amt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2020-12-31    0.017240\n",
       "2021-01-31    0.032340\n",
       "2021-02-28    0.043417\n",
       "2021-03-31    0.051903\n",
       "2021-04-30    0.060561\n",
       "2021-05-31    0.073954\n",
       "2021-06-30    0.088223\n",
       "2021-07-31    0.100235\n",
       "2021-08-31    0.110835\n",
       "2021-09-30    0.122253\n",
       "2021-10-31    0.130407\n",
       "2021-11-30    0.139179\n",
       "2021-12-31    0.149976\n",
       "2022-01-31    0.162969\n",
       "2022-02-28    0.174545\n",
       "2022-03-31    0.185524\n",
       "2022-04-30    0.198782\n",
       "2022-05-31    0.214509\n",
       "2022-06-30    0.239781\n",
       "2022-07-31    0.261206\n",
       "2022-08-31    0.286144\n",
       "2022-09-30    0.311875\n",
       "2022-10-31    0.336270\n",
       "Name: Close, dtype: float64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# seeing in a accummulating perspective\n",
    "btc_amt_sum =  btc_amt.cumsum()\n",
    "btc_amt_sum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# naming column\n",
    "btc_amt_sum.name = 'btc_amt_DCA'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BTC-USD\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.3362704431797148"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How much bitcoin would i have if I used DCA purchases?\n",
    "print(CryptoPar[0])\n",
    "btc_amt = 500/buyprices\n",
    "btc_dca = btc_amt.sum()\n",
    "btc_dca"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11500"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# if a bought BTC using us $ 500 monthly during the len of buyprice\n",
    "Total_USD = 500 * len(buyprices)\n",
    "Total_USD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "So, use USD $11500 to bought 0.3362704431797148 BTC using DCA Stategy\n"
     ]
    }
   ],
   "source": [
    "print(f'So, use USD ${Total_USD} to bought {btc_dca} BTC using DCA Stategy')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lump Sum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.39652819629977504"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# So if I were bought us $ 11000 on the first day (Lump Sum) I had btc_amt_LS bitcoins\n",
    "btc_amt_LS = 500 * len(buyprices) / buyprices[0]\n",
    "btc_amt_LS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.060257753120060265"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Then, the difference (in BTC) between the DCA and the Lump Sum strategy is\n",
    "diff = btc_dca - btc_amt_LS\n",
    "diff"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So, in this case, if you had used the DCA strategy you would have **LESS** bitcoins than if you had made the acquisition of the bitcoins in a single purchase at the beginning of the period."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>btc_amt_DCA</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>0.01724</td>\n",
       "      <td>28841.574219</td>\n",
       "      <td>29244.876953</td>\n",
       "      <td>28201.992188</td>\n",
       "      <td>29001.720703</td>\n",
       "      <td>29001.720703</td>\n",
       "      <td>46754964848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-01</th>\n",
       "      <td>0.01724</td>\n",
       "      <td>28994.009766</td>\n",
       "      <td>29600.626953</td>\n",
       "      <td>28803.585938</td>\n",
       "      <td>29374.152344</td>\n",
       "      <td>29374.152344</td>\n",
       "      <td>40730301359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-02</th>\n",
       "      <td>0.01724</td>\n",
       "      <td>29376.455078</td>\n",
       "      <td>33155.117188</td>\n",
       "      <td>29091.181641</td>\n",
       "      <td>32127.267578</td>\n",
       "      <td>32127.267578</td>\n",
       "      <td>67865420765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-03</th>\n",
       "      <td>0.01724</td>\n",
       "      <td>32129.408203</td>\n",
       "      <td>34608.558594</td>\n",
       "      <td>32052.316406</td>\n",
       "      <td>32782.023438</td>\n",
       "      <td>32782.023438</td>\n",
       "      <td>78665235202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-04</th>\n",
       "      <td>0.01724</td>\n",
       "      <td>32810.949219</td>\n",
       "      <td>33440.218750</td>\n",
       "      <td>28722.755859</td>\n",
       "      <td>31971.914062</td>\n",
       "      <td>31971.914062</td>\n",
       "      <td>81163475344</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-05</th>\n",
       "      <td>0.33627</td>\n",
       "      <td>21144.832031</td>\n",
       "      <td>21446.886719</td>\n",
       "      <td>21097.634766</td>\n",
       "      <td>21282.691406</td>\n",
       "      <td>21282.691406</td>\n",
       "      <td>37846047609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-06</th>\n",
       "      <td>0.33627</td>\n",
       "      <td>21285.056641</td>\n",
       "      <td>21345.376953</td>\n",
       "      <td>20920.191406</td>\n",
       "      <td>20926.486328</td>\n",
       "      <td>20926.486328</td>\n",
       "      <td>35082693210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-07</th>\n",
       "      <td>0.33627</td>\n",
       "      <td>20924.621094</td>\n",
       "      <td>21053.246094</td>\n",
       "      <td>20489.972656</td>\n",
       "      <td>20602.816406</td>\n",
       "      <td>20602.816406</td>\n",
       "      <td>53510852236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-08</th>\n",
       "      <td>0.33627</td>\n",
       "      <td>20600.671875</td>\n",
       "      <td>20664.607422</td>\n",
       "      <td>17603.544922</td>\n",
       "      <td>18541.271484</td>\n",
       "      <td>18541.271484</td>\n",
       "      <td>118992465607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-09</th>\n",
       "      <td>0.33627</td>\n",
       "      <td>18509.156250</td>\n",
       "      <td>18590.458984</td>\n",
       "      <td>17428.435547</td>\n",
       "      <td>17652.292969</td>\n",
       "      <td>17652.292969</td>\n",
       "      <td>126847909888</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>679 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            btc_amt_DCA          Open          High           Low  \\\n",
       "Date                                                                \n",
       "2020-12-31      0.01724  28841.574219  29244.876953  28201.992188   \n",
       "2021-01-01      0.01724  28994.009766  29600.626953  28803.585938   \n",
       "2021-01-02      0.01724  29376.455078  33155.117188  29091.181641   \n",
       "2021-01-03      0.01724  32129.408203  34608.558594  32052.316406   \n",
       "2021-01-04      0.01724  32810.949219  33440.218750  28722.755859   \n",
       "...                 ...           ...           ...           ...   \n",
       "2022-11-05      0.33627  21144.832031  21446.886719  21097.634766   \n",
       "2022-11-06      0.33627  21285.056641  21345.376953  20920.191406   \n",
       "2022-11-07      0.33627  20924.621094  21053.246094  20489.972656   \n",
       "2022-11-08      0.33627  20600.671875  20664.607422  17603.544922   \n",
       "2022-11-09      0.33627  18509.156250  18590.458984  17428.435547   \n",
       "\n",
       "                   Close     Adj Close        Volume  \n",
       "Date                                                  \n",
       "2020-12-31  29001.720703  29001.720703   46754964848  \n",
       "2021-01-01  29374.152344  29374.152344   40730301359  \n",
       "2021-01-02  32127.267578  32127.267578   67865420765  \n",
       "2021-01-03  32782.023438  32782.023438   78665235202  \n",
       "2021-01-04  31971.914062  31971.914062   81163475344  \n",
       "...                  ...           ...           ...  \n",
       "2022-11-05  21282.691406  21282.691406   37846047609  \n",
       "2022-11-06  20926.486328  20926.486328   35082693210  \n",
       "2022-11-07  20602.816406  20602.816406   53510852236  \n",
       "2022-11-08  18541.271484  18541.271484  118992465607  \n",
       "2022-11-09  17652.292969  17652.292969  126847909888  \n",
       "\n",
       "[679 rows x 7 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's concatenate btc_amt_sum with df\n",
    "df_tog = pd.concat([btc_amt_sum, df], axis=1).ffill()\n",
    "df_tog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>btc_amt_DCA</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>btc_amt_LS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>0.01724</td>\n",
       "      <td>28841.574219</td>\n",
       "      <td>29244.876953</td>\n",
       "      <td>28201.992188</td>\n",
       "      <td>29001.720703</td>\n",
       "      <td>29001.720703</td>\n",
       "      <td>46754964848</td>\n",
       "      <td>0.396528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-01</th>\n",
       "      <td>0.01724</td>\n",
       "      <td>28994.009766</td>\n",
       "      <td>29600.626953</td>\n",
       "      <td>28803.585938</td>\n",
       "      <td>29374.152344</td>\n",
       "      <td>29374.152344</td>\n",
       "      <td>40730301359</td>\n",
       "      <td>0.396528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-02</th>\n",
       "      <td>0.01724</td>\n",
       "      <td>29376.455078</td>\n",
       "      <td>33155.117188</td>\n",
       "      <td>29091.181641</td>\n",
       "      <td>32127.267578</td>\n",
       "      <td>32127.267578</td>\n",
       "      <td>67865420765</td>\n",
       "      <td>0.396528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-03</th>\n",
       "      <td>0.01724</td>\n",
       "      <td>32129.408203</td>\n",
       "      <td>34608.558594</td>\n",
       "      <td>32052.316406</td>\n",
       "      <td>32782.023438</td>\n",
       "      <td>32782.023438</td>\n",
       "      <td>78665235202</td>\n",
       "      <td>0.396528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-04</th>\n",
       "      <td>0.01724</td>\n",
       "      <td>32810.949219</td>\n",
       "      <td>33440.218750</td>\n",
       "      <td>28722.755859</td>\n",
       "      <td>31971.914062</td>\n",
       "      <td>31971.914062</td>\n",
       "      <td>81163475344</td>\n",
       "      <td>0.396528</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>2022-11-05</th>\n",
       "      <td>0.33627</td>\n",
       "      <td>21144.832031</td>\n",
       "      <td>21446.886719</td>\n",
       "      <td>21097.634766</td>\n",
       "      <td>21282.691406</td>\n",
       "      <td>21282.691406</td>\n",
       "      <td>37846047609</td>\n",
       "      <td>0.396528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-06</th>\n",
       "      <td>0.33627</td>\n",
       "      <td>21285.056641</td>\n",
       "      <td>21345.376953</td>\n",
       "      <td>20920.191406</td>\n",
       "      <td>20926.486328</td>\n",
       "      <td>20926.486328</td>\n",
       "      <td>35082693210</td>\n",
       "      <td>0.396528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-07</th>\n",
       "      <td>0.33627</td>\n",
       "      <td>20924.621094</td>\n",
       "      <td>21053.246094</td>\n",
       "      <td>20489.972656</td>\n",
       "      <td>20602.816406</td>\n",
       "      <td>20602.816406</td>\n",
       "      <td>53510852236</td>\n",
       "      <td>0.396528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-08</th>\n",
       "      <td>0.33627</td>\n",
       "      <td>20600.671875</td>\n",
       "      <td>20664.607422</td>\n",
       "      <td>17603.544922</td>\n",
       "      <td>18541.271484</td>\n",
       "      <td>18541.271484</td>\n",
       "      <td>118992465607</td>\n",
       "      <td>0.396528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-09</th>\n",
       "      <td>0.33627</td>\n",
       "      <td>18509.156250</td>\n",
       "      <td>18590.458984</td>\n",
       "      <td>17428.435547</td>\n",
       "      <td>17652.292969</td>\n",
       "      <td>17652.292969</td>\n",
       "      <td>126847909888</td>\n",
       "      <td>0.396528</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>679 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            btc_amt_DCA          Open          High           Low  \\\n",
       "Date                                                                \n",
       "2020-12-31      0.01724  28841.574219  29244.876953  28201.992188   \n",
       "2021-01-01      0.01724  28994.009766  29600.626953  28803.585938   \n",
       "2021-01-02      0.01724  29376.455078  33155.117188  29091.181641   \n",
       "2021-01-03      0.01724  32129.408203  34608.558594  32052.316406   \n",
       "2021-01-04      0.01724  32810.949219  33440.218750  28722.755859   \n",
       "...                 ...           ...           ...           ...   \n",
       "2022-11-05      0.33627  21144.832031  21446.886719  21097.634766   \n",
       "2022-11-06      0.33627  21285.056641  21345.376953  20920.191406   \n",
       "2022-11-07      0.33627  20924.621094  21053.246094  20489.972656   \n",
       "2022-11-08      0.33627  20600.671875  20664.607422  17603.544922   \n",
       "2022-11-09      0.33627  18509.156250  18590.458984  17428.435547   \n",
       "\n",
       "                   Close     Adj Close        Volume  btc_amt_LS  \n",
       "Date                                                              \n",
       "2020-12-31  29001.720703  29001.720703   46754964848    0.396528  \n",
       "2021-01-01  29374.152344  29374.152344   40730301359    0.396528  \n",
       "2021-01-02  32127.267578  32127.267578   67865420765    0.396528  \n",
       "2021-01-03  32782.023438  32782.023438   78665235202    0.396528  \n",
       "2021-01-04  31971.914062  31971.914062   81163475344    0.396528  \n",
       "...                  ...           ...           ...         ...  \n",
       "2022-11-05  21282.691406  21282.691406   37846047609    0.396528  \n",
       "2022-11-06  20926.486328  20926.486328   35082693210    0.396528  \n",
       "2022-11-07  20602.816406  20602.816406   53510852236    0.396528  \n",
       "2022-11-08  18541.271484  18541.271484  118992465607    0.396528  \n",
       "2022-11-09  17652.292969  17652.292969  126847909888    0.396528  \n",
       "\n",
       "[679 rows x 8 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# adding Lump Sum column to df_tog\n",
    "df_tog['btc_amt_LS'] = btc_amt_LS\n",
    "df_tog"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DCA Approach Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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cOKUKR16/4NqzYTv7AjR3GncIuw/24Q2EEt6NJIPVBWt2vSH6G/d3Rbb5guGo1w2GwzjzlJFFHAxFRN8f1PT4Q4TCmrKCkRP9BVMqWTAlutm8lSPRLhE8o4q1trN+X+eg4cSykCtkHWfPrKWhMt7yPlQmVRZy0Zw6fn3VPKDfvWPx1+W7ufI3S/nzOzujxtt7A1xz0mTOPaqWHn+Q5i7DLaM1UUI9XCzRt/zv6/f1W3ax6wyhkCYvT+FxOejzhyLur75AMOIOGEnRT0S+M4+ifAcHewcv+CYcHh19AVwOxcHeQKSPQiJE9IWs48wj47NDDweXI497rjgu0lwk1kJ/a4uxqNprq7wZCms6vQHKCvMpzHfS4wvS1uPn+EnlgBFyeagc6PbhyFMcNcGIlTdcSAZ9MaIfDGuceQq3y0GXNxgJM+3xhVh0x2vA6Is+QHlhPu19YumPBhv2dfHnZTvp8YeYN7kCgK0t3QPuL+4dISuwW7ieQcomjwT2+jN5qn/x0l6SucsbQGsjbNGoyhnCkQfzJ1eyv9PHqt2HHsK4t93L+FIP9eUFnDS1iiVbW2msKmR7a29ceYiwNnz6q3a1A7DfvNtot3UWs7ukRovyQldUPoAwctz65GreNoMD6swyGoPlkIilL2QFXbZiYicdMbqLhVai1w1nTI0S+g37OiPliV9Y1wwYYleU76DXH6TbG6TY46SmxB0lusNlZ1svDZUFKKX4/adP4NdXzeOmc6YDxOUAWJa+xVbzrmDj/m7yTTfV6TNG9s4oERWF+Ul/5k5vgK/9ddWgUUlCP/YLfY2ZZzFYDomIvpDR+INh/rxsZ0RQ7rp87oj68xNRVexm4/cu4BsXHEWJTfQfXLKDc3/2KtC/qOxxOShyO+n1h+jxhyh2OynxOOkcoOLlULT1+Fmx4yANFcZnLMh3cP7s8ZHF0lgLLxTSOPLyeOqLp0aN9wVC+INhrj996iEvKA+H4Vj6D7y5ncdW7OZ3tvpAwsAEw/0CP9E8L/wJ6jBZiOgLGc0flmznlr99wNcfN5pwl46BfxqIWMmxXbZiOaa+LBLqCUYZh1KPiy7voVmx979pCKG9xg30rzN4E1n6DsXs+jImVhi3/pNt4aVj4c8HKPG4kr7QWYEn4bCmxxfkFy9vHpEs5mzFykL/6nkzONO8axNLX8haLDFYubMdIFLga6woTvB+3kCIyqJ8rlo4iYbKQgptTdiL3U5KC5x09h2apW+5sa42s10trLITcZZ+WEdKL1iif+q0ai6eYzQ3Gavvy+3Mw59krSJlKwr3zOp9/PjZDdz2r7WjOLvMptcX4lPzJ/LFc6ZH2lkO1qlMRF/IaGIt+6MnHF4ZgeESG74JRmZke6+f8gLD5WK39Is9TkoOw9L3h8JUF+fH9aq1LP0+f7SFZ8XpAzRWGRm3VcXuSBG2sSLfmTeoy8GOtQShMTKKAV7beGDgA3KcHn8wkoxo3YEO1r9ARF/IaOxJKHddPjdODEebRJEvG/d3E9aGHxuIFDwD4wJQ4nbiC4bxmz/MXW29dCTp7/YFwgmbulsRRfaQTa01Yd0/xxvOOILJVYVcMrcuMqfuMWrwnu/Ii3zeobAyirXuTziKDUUVDLTW9PlDkaxxt4i+kO302sRgbkP5mL//aQk6RlnJUhWFhqVv78lb4nFG7k4sa/+0H73MRT9/I6n384fCEWvOTk2JG0eeYtuB/vhsq76OZelPqS7i1f86iyNqirn+9KmcNr2aT82fmNT7Hi75TqMHQaJGL7FY87bKRAD0Zkgj+rHGHwpH9UzId4joC1mOlRD1l+sXMrnq8AuGDZdrT5nCNy+cGdWO8c4XNgH9lr49mmh8WUGkzPPBXn/E+t3Z1pvU+/kCoYQupcJ8J5MqC/nFy1t426zAaZWBcDji70ZqSz08dN2JVB1Gn4HhYF2oknHxWAuT9762lXfNtZoefyiqVr9g0BdTSlwpZbjSRPSFbKXXDIM8MUWFvPKdeVx/+hHUl8f3lrXKJNgjZOrKPMyZWA7AqxsPRPWqvffVLRwcoj7NQJY+wI1nTAXgAzPxK9bSTyXWhSoZF0+fv1/c39jc78vfMkiWaa4RCmt+/tImvvqoERpsX6NxO/NkIVfIXvoCwTH34yfi3n+fx6dPbow8f+HmM6gt9UTtU12cj1KKqTXFTKku4p1tbZH6NwA/WLyenz6/YdD3MXz6iX+2n5rfQL4jL9Ka0LL081TqRT9/GKLfGxOeWVbgIt+Rx29fl7h9i9c3tfCT5zby4nojCdCenOh2OgZ170gZBiGj6fWHKEoD0a8rL+A7F8+itcfP/g5vXBz9qlsXRVnc40s9tPb4aOrwRu03VFtBfygc1xXMQilFZVE+bT0+tNY8sswoAJcOln4yvmaL3phF2+MmlRMKa3Yk6QIbDbYf6MHtymNCWfwd3VD87LkNHDOxnPOOHjdi84m9eJ5zVP9ru8W9I2QzPb4QBSNYO/9wueeK43j0xpPixsvMGjwWVcX5tHb72Xagv1jaOTNrWbmzneXbBy7G5guGBnTvgFHGuLXbzwd7Orh98XoAHI7U/8yTCSW0iE3E+vr5M6kpcXNgiDaAo8Xm5i7O/MkrLLrjtSFbEcaitebulzbz2T8sT2r/ZdvaolpODkSbzQ341i1nM8XWAMdw74joC1lKXyAY19kqE6gudnOg28eWlm4aKgvYfvuH+dDs8QB8/1/r4vYPhzW3Pb2W1Xs6B3TvgHkx6fGzo7XfKk4HS384Pv1ef5ATGit49sun89xXTueoCaXUlLhp6fINWid+tHhvl7FG0uUN8sBbw3MxtQ6jh0CvP8in7l3CZfcuGXJf+8VnQlm0GzF/iEQ4EX0ho+nxhTJS9KuK8un0Bnnq/SYmlBoug08cP5GTj6hiR2tvnLg9t3Y/vzF92oNZ+lVF+bT1+KOigVKgk3EMJ3qnz2/cvR05voQZ44zy0TXFbvyh8JgXYdNa8/d3d+N25nHWkTU8tmI34XDyX+ieg8l3SbOEfM3ezsgi/ID7mj0VHrvxpKhOaSCWvpDldPQFKC8cuS5ZY4W9fMO1pzYCRoeuD80ab6wLxDTBeH93e+Tx4Ja+m51tvfz42f4F4XSoVpnvMC7M/mAYrTUPvb1jQDdGrz9EYcy6hbUo3jyGLh6tNXc8v5E3N7cysaKAjxxbx/5OH2uGWHexs9XMm6hMopOb3XpfYvZoGIgD3T6m1RYzv7Eybpvb6YhrpmNHRF/IaIxyB2NTNGwkOfeocVx+QgOr/mcR58+eEBm3iqHtOhi9aGkvnzuUTz+Wg4dRxnmksOZ8oNvHW1ta+fY/VvO9pxLX0+n1x9+91Zcboj8cy/lweW3TAe5+aTMA3//oMcxvNBqUDNWD1s6vXtkCQF25Z4g9o0X/rS2Dl51o6fJRXZz4QlLkdtAzSKa1iL6QsYTDRsZmRWHmiX5DZSG3f/xYymLmbiVy7YqJVLEXUktUhsEikRAMFfs/Flii/59/XBkprXCgO/G8+gKhuDBc63tJNoltJLCL8OSqIurLC3DmKba19gxyVD9NHX1s3G9Y+sm42CyXTXmhK9KXYbC51ZQkvpCUF+YPeneXlOgrpcqVUo8ppdYrpdYppU5SSlUqpZ5XSm0y/6+w7f8NpdRmpdQGpdSHbOPzlFIfmNvuVrHOKEEYBl3eIGENZRno3hkIK8lrV1u0RWu/XR/c0u/PsJ03uYILZo/nK+fNGOFZDp98WwSR5W8eaIG5L4GlX1PsxuPKG1XR11rzx6U7WL2ngx5fMEp4q4vzcTrymFRZyPYDyYn+yh3tgNFjeTB3i0Vzp488BSc0VsaJ/pq9HTz9fhMAr2xoZntrb6SZTyxlBa5BG9Yka+nfBTyjtZ4JzAHWAbcAL2qtpwMvms9RSh0NXA7MAs4HfqmUsv6CvwKuB6ab/85P8v0FIQ6r52omuncGwuNyUF7oijQ/t7CLxmA+fXvOwvzGCn511TzqEmQLjzX2C5X12ZZtbyMQs7AbDmvT0o8Ow1VK0VBRyO6Doyf6u9r6+NbfV/ORe97gU/cu4devbolsc5oXrbkN5byyoSUqk3ogrPNzclXhkKGqd76wkefX7mdcqYf5kyvYeqCHzz28go7eAFtburnonjf4/J9W0ukN8On73wEYsFJqWcHgvQuGFH2lVClwOvA7AK21X2vdDlwCPGju9iBwqfn4EuDPWmuf1nobsBlYoJSaAJRqrZdoIzThD7ZjBGHYWJ2YyjPQvTMYHqcjLo3e7tO3N0GJxSrudsq0Kr563pGjM8FDwB6NZCWktfX4mf6txdz40Aq+/pjRBMdyYyWKyCovdI3qonSnrdy1fbF2qi0G/vIFk+gLhJLy61v5BmUFrrjexXb8wTB3vrCJDfu7mFDm4YoTJwGwePU+Lvr5G5z901cjfZhfMttwQvTdk52hfg/JWPpTgRbgfqXUu0qp3yqlioBxWusmAPP/WnP/emCX7fjd5li9+Th2XBAOCSuSI5nIiEzC7YoPufMGQuQpuO7UKVw8Z+CfzdSaYl77r7N46NoTB3UDjTVTa/ozlO05BADPrNnHX5YbkmGVYEgk+qUe1yE3n0mGRAXdbjpnOi997czIc8u6HkzELay/YXmhC98g7p1eW60hXzBMqcfFX65fCMSvYXz5L+8BcNLUKv7jtKkJX28kRN8JHA/8Smt9HNCD6coZgESOOj3IePwLKHW9Umq5Ump5S0tLElMUcpH1prU13Yzlzhbczry4dnfeQIiTjqji2x85OmENfzuTqgrJS4OELDuOPMWPP3EsYGS4DkRs1Ug7JR4nXb7Rs/StC844s7n4adOr+bLZcN7CalYzWEEzC28ghFLGxSq2o1mi9wUi7q5jzaJ8dq407wCOnlDK7z49f8CaU1bznoFIJn99N7Bba73UfP4YhujvV0pN0Fo3ma6bZtv+DbbjJwJ7zfGJCcbj0FrfB9wHMH/+/DRILRHSjXVNnTy+cjeNVYVRnamyAY/LEScS3kA4Up8/U7H+Tttbe1EqPqLlB4vXcYl5F1OYoLRGacHoWvpW3sBnTpnC7YvXc+aRtXEXz4joJ2HpewMhPE4HHpeDQEgTCuuEF2zL0m+sKuTOy44DjIb3j914Eu/v7uDkaUbC3hkzahhX4uFTJ0xM+P1Y1Ja6mdtQzo4Btg9p6Wut9wG7lFKWg/AcYC3wJHCNOXYN8IT5+EngcqWUWyk1BWPBdpnpAupSSi00o3auth0j5DhbWrrjFvUG44K7Xmd7a29KGqeMNgkt/WAoIjiZir320A2nHxG3/d5Xt/LXFYabZyD3Tpc3MGqlGCzxvWhOHX+5fiFXnzQ5bh9rEX0wy93CGwjjceVFupoNFMFjWfrf/sjRHF1XGhmf31jJtadOYeb4Uj40azwel4MvnTt9yKJvs+rK+MfnTxlwe7JOvy8Cf1RKvQ/MBb4P3A6cp5TaBJxnPkdrvQZ4FOPC8Azwea219Wk/B/wWY3F3C7A4yfcXspgtLd2c89NX+bmZCDMcLpmbfctC7gQLub5AGLcrfXz0h4Jd9K0m7bHc/+Z2wOgEFkuJx0lYGw1VRgOrdWRRvoMTp1bhSrBQal14kwnB9AaMC7V1TFNH4sQyK5FqrEqEJ3VfrLV+D5ifYNM5A+x/G3BbgvHlwOxhzE/IAZZtM6pK7kgy6QVgWm0xBS4HZ82sHXrnDMPjyqOtJ96nn+mWvt0Nd8aM/jaTdWUe9tpKTCsFR9REl6YGotpMjoZLz2rJOJjrxGNZ+gncOwd7/Dy3dh8fO34iLkce3mAYj8vBvMlGCtMdL2zi7CNr+fi86BaV1h1G0RhVi80uZ6iQkWzYZyzsTamO/6EPRJ8/xLETy0ZrSikl1tLf0tJNa48fzyCZuJmAZb1fPKcuqoXkm7eczZubW/lgTwc/fGY9ZQWuhFZviVmvqLMvyIQR/tNvbu7i/re2o9TgyW9ORx6OPJVwIffGh1ewdFsbT3+wjy+dMw2v2dpyVl0Zx08q5+n3m3j6/SZOOqIqKnfCcu8MFHc/0ojoCynHSnQJDcNX6w1kZnXNZHA786Isya+YYXr7u4ZOCEpnKovyef87iyj1GBb7jHHFbNzfjVKKU6dXRyxeq81kLFb5iWTKMw+Xe17aHFWjfjA8MX8fC6tsw2sbW3htYwunTa+O3J1Nripipdnvt7nLFyP6xuceq74QIvpCyrHi7ZMJg7PoC4QG7CCV6bhd/e3u+vwhVu8x6rnfcHriuOxMwhJ8gH9+8VTCNu08fUYNN509jWtPnZLwWJfZ4D0QHnnRbzXrAB0/qXzIfT0uB9sO9LB6Twcvr2+mobKQS4+rxxsIUV9ewB6zBebavZ1MH2fcvY631byPzebtsa0ljAWZvTIkZAX7TH9uMmFwYGR3ZrXo2xpbr97bQVjDb6+enzB2O5NxOx1RbhyPy8HNi44csFS2lYEaOExLPxAK89FfvskT7+2JjDV3eVl09Dge/9zJScw7j5fWN/ORe97gp89vjCRM9QVCnD2zloeuWwAYDVQsS/+cmbWRTOo7nt8Y9XpWUthYLeSK6AspZV+HN2IZJWvp+4JhtAZPlrp3PC4HvkCYPn+IX7xsRDTNycLQ1OFi1b8JhA4vZHN/p5d3d7bzpT+/Fyls1tLlo7bUHdeQJBGx+1ix91aIpj2fwlqHmd9YyUtfPROA9fu6+O4/17J8extaa556v4nptcUDllUYaUT0hZTyf7aa6sla+oNlbWYDbmce/lCYHyxexysbWljQWJkwhDHXiLh3hpHPkQh7I5bHV+7GHwxzsDdATfHQNe+BiJHy66vm8dHj6qkr96C1xhs07j7tZRBKC/o96I48xSRzAfv3b27jE79ewhPv7WXD/i6uWjg5qQvOSCCiL6SMcFizZGsr02qLk6pEaNEXyHLRN+PxH37byKn86afmpHI6aYMVN59My8XBsNfJX7O3M7KAW10yvIznE6dUUuJx0tkXjNx9ul2OKEv/szH1cX511fFRzy3X0AkJOmCNFiL6QspYuq2Nth4/Xzx7GsVuZ9LunYjoZ6l7p8SMQQ9r+OuNJ0WFN+YyVihl8DDdO5alf8aMGl7b2MI/VxnVYJKN/bcs+YqifEo8Trp9wUiyVoHLERVVFlsXqm6AbNojx49d/SgRfSFlPLtmHwUuBx+aNT4uTHEwLPdOpicrDYTdlTN/csUge+YWVtOVw3XvtHT5UAo+YSZJ3favdUDyov/K187k3W+fB0CJx0UorCN3Cx6XY1A3TaIKmM995fQhi+iNJBKyKaSMPe19TKosjKSq2y391Xs62NLSzVPvN/HfHz6KyVX9Nc0tqyp7Rb/ftyzN5foZKfdOR6+fUo+L844eFzVelLSl3+++sUJQLZeRVWfnmxfOjPjv7dj/npef0MCybW1MsdXrHwtE9IWU0dTRxwSzYbTbmRepcghw2b1LIjVW8h15/OLf+n2h1h2BJ43qxY8ktbJomxDLvXO4ln63L0Sx24nH5eDWi47mf/9pBBMcSmkHK0vYqhlkrTNdn6CgnP2YLm+Qm8+bQW1pcovHI0l2/mqEjGBfh5cJZZboO6Kid+xFtWIXeP0h82KQpaIvkTqJcY1QnH6PLxgpeWB3txyK6I8zRfuZNfuA5O4+/3rjSXzmlEaqB+hxO9pk569GSHt8wRAHuv2MLzUWttyuvEi5WnvbOoivTmil4Wer6HtcDiqL8vnKualvaJ5OWCGbwXDyC7n7Orw8ZwqyRY8/GHHllNn6Kyfr3rFz/KTyKPFOphLqzPGl3HrRrJQ1uhH3jpASuszGzRVFxo/O43RECk/tMlvEfeeio/nbu3s42BtdE8Wy/N0ZXoBsMFaaC4VCP4fi0//w3a/T2uPnwWsXRCp7dvuCEau+zNZl6lAsfacjj2m1RZFm732jVPZ5JMlOU0lIe2ITrKaPK6aly8cNDy2P1EGZVV/GrLrSuB+SPyL6cvrmEv3uneQs/T5/iFYzqubl9f0NxXt8wUgZY7t7x3OI/Qrs7QkHKhaXTsivRkgJ3phY+5OPqAbg2TX7ufr3ywCoLnZT4HLGi34ou907QmIceYo8lfxCrv0O0XIRHuzxs3F/d8SVY180P9RIqcsXGN1hX7j5jJQszA4Xce8IKaE3xtI/akIJCxorWba9LbJPdXE+hfkOegMhtNaRH2XEpz9GtUqE9MHlyEta9O2lkve2G0X9rvrdUvN1jHOpxOPiBx87hrV7Ow95TmceWcvW71+Yds3oB0JEX0gJsVm1SimuP31qlOgXu50U5DvQ2vDjW5ER2b6QKwyMIfrJuXcs0Z9WWxyx9NeY4r7d1qXtigWTDntemSL4IO4dYQwImxmLP352PeuajB9dovo5EyujU9SVUpGU9tsXr+d//7kGENHPZVwONWz3zuy6Ug50+6Pacdr98LmGWPrCqPPr17bwo2c2APD+7g6uWDApYmnZ+5FOry3hC2dN49Tp1RGxt/5/4K3tANx60Sz8oTBK9aflC7nDcNw7VkDA7Poy/vHeXts5dDSXzq0frSmmPSL6wqhjNT4HeH3TAV7fdCDy3G7pO/IUX/vQkVHHJmoh5w+GyXfkSYmCHMTlyEs6ZHPj/i7KClzMHF8KwGPLdzO5qpDPnJK4M1euIPfHwqhTXhBfZMrCkz/4KRhbPrnHZ5SxFddObpLvzONvK/dEhWAm4o1NB/jzO7uYN7mC+grDbdjlC7JgDEsYpyvyyxFGhVc3tkSaTbT2+JnTUE4iw7xwiGbQsc3PH1yynV5/UGL0cxTLpfeZB94ZdL83txh3k1ctnBQp9QEwc0Lp6E0uQ5BfjjAqXPP7ZZxy+0uAsaBWVZSf0I86VNG02Jr5P3pmA48u353V2bjCwBxRUzzo9l5/kJU7D3Kgy8f4Ug9nzxwXVQ9HitmJ6AujgL1E8pItrRzsCVBRmM/tHz8mbl/nELH2JQOkxot7Jzf57iWzgIEzX7/7z7V87Jdv8e6u9oSF60T0RfSFEUZrTWdff4nkR5btpLXHR0WhC7fTwU1nTwPg4etO5IYzpg70MhGqbMWs/nL9wshFQBKzcpPaUg/nHjVuwKJrVlTY5uZuqovjwzIzIWN2tJHoHWFEOfp/nuXoun6/6VtbWvEGwpEStDcvOpKbFxkROqdOrx7y9eyLwMdOLOfco8fx93f3iKWfwxTmO+jzB6PGmju9FHuc1JcXAka0mFj6iRHRF0aMcFjTFwixYsdBAOY0lLNqVzsA48sOzcKyZzp6XHkcUWN0GQrrw+uTKmQuRW5HVL8FfzDMgu+/yBkzamiwJfidMq3fqHj8cyfzzOqmQyqfnG3INyCMGB190XXw50+uOGzRt6OUityeT6xI3GBayH5ii/A9t9aol//qxhY+dlw91cX5PPGFU6kv7z9H5k2uYJ70GwbEpy+MIG0xde/nNpRHHo8fIV/qeUeN4/xZ4/nOxbNG5PWEzKMw30GvP4g27/bufGFTZFtLt4/qYneU4AvRiKUvjBjf/sfqqOf2CItxhyH693/6hEjxrIqifH797/MO+bWEzKfQ7SBsFuHr84fY3NzNsRPLeH93B69vOsDxk8pTPcW0RkRfGBG01ry1pRWAy+Y38Jfluxhf5uHxz51MVVH+YS28njWzdqSmKWQBhWbc/asbW7jhoRUAXHjMBHa29dLeGxC//RCIe0cYEVpttctvOnc622//MB6Xg3mTK2isLkrhzIRsw0rYswQfYFypm+MnGT77oiGyvHMdEX1hRNjXYTSpOPPIGvGnCqPKkePjSylUF7sja0jdvmDcdqEfEX1hRNhr1tm5+bwZKZ6JkO3MbShnwZTowmnFbmekzIfUZRocuQ8SRoQm09KfUCZWvjD6OMzqfadMq+KtLa1MrSmmrMDFE58/hTq50xwUEX1hRNjb0YfLoagqyt2ORMLYYVVsvXRuPX/8j4WR8Tm2MGEhMXIfJBwyO1t7+cpf3sMbCNHU7mV8mSejeoUKmYsl+mWD9GoQEiOWvnDIfP9f63hmzT4+NGsc+zq84toRxgyFofpul5TYHi5JW/pKKYdS6l2l1FPm80ql1PNKqU3m/xW2fb+hlNqslNqglPqQbXyeUuoDc9vdSvrdZTQlHsNmaOsJsKe9j7oRKLUgCMlgKYeWGkzDZjjunS8B62zPbwFe1FpPB140n6OUOhq4HJgFnA/8UillXY5/BVwPTDf/nX9YsxdSSoXpv991sJc97X1DNrgQhJHipnOmU17oiir1ISRHUqKvlJoIfBj4rW34EuBB8/GDwKW28T9rrX1a623AZmCBUmoCUKq1XqKNy/MfbMcIGUieaW5Z/UrtJZUFYTQ5obGS9/5nEeWFEjgwXJK19O8E/h9gb0M/TmvdBGD+b+XK1wO7bPvtNsfqzcex43Eopa5XSi1XSi1vaWlJcorCWNNr1jRfv68LgCPHl6RyOoIgJMGQoq+U+gjQrLVeMdS+1iEJxvQg4/GDWt+ntZ6vtZ5fU1OT5NsKY02PLxT1vE4WcgUh7UkmeucU4GKl1IWAByhVSj0M7FdKTdBaN5mum2Zz/91Ag+34icBec3xignEhQ+mN6V4k4ZqCkP4Maelrrb+htZ6otW7EWKB9SWt9FfAkcI252zXAE+bjJ4HLlVJupdQUjAXbZaYLqEsptdCM2rnadoyQgfT4Q5FOVoIgZAaHE6d/O/CoUuo6YCfwSQCt9Rql1KPAWiAIfF5rbfkBPgc8ABQAi81/QobS5w8yrtSDUopzjxqX6ukIgpAEwxJ9rfUrwCvm41bgnAH2uw24LcH4cmD2cCcppCc9vhB15fm8cPPCoXcWBCEtkDIMwiHT7QtS5JaMSEHIJET0hUNCa01zl5eaYneqpyIIwjAQ0RcOic6+IN5AmPFSekEQMgoR/TSlpcuX1h2A9nUa9fMPp+G5IAhjj4h+mnLGj1/m1B++RDicngWl/v7uHgCx9AUhwxDRTxPuf3Mbn7p3CQe6fSzd2kqvP0R7b4AN+7tSPbU4enxBHnhrG4AUWROEDEPq6acJ97y0mbYeP/O/90LU+JItrRw1Ib0Kmb22sQVvIMwjn11IpXTKEoSMQiz9NKGiMHEHoO8+tZb9pv88XdjZ1gvA7Pr0uhgJgjA0Ivppgj8UJt/R/+e487K5kcet3f4UzGhg9rb3UepxUuKRVnWCkGmI6KcJvkCYM47sryh66XH13HjGEQD0BdIrimdPu5e6cqmoKQiZiIj+GHCg28fpP3o5slCbCH8ozLjS6ESnc48yWhTEljBONXvb+0T0BSFDEdEfA9Y1dbKzrZdl29p4+v2mhPv4g2EKYpo8F+Yb6+y9/vQS/aaOPurKJVRTEDIREf0xoKm9fyF2+Y6DCffxBcPkO/PIU/0LpIX5xkUgtm59Kun1BznYG2CCNEwRhIxEQjbHgKYOQ/QvnlPHS+ub6fQGKLUtggZDYUJhjdvpYP3/XYDVi6TQLGbWk0aW/l7zAlYv7h1ByEjE0h9lNuzr4o4XNgJw5YmT6PYFWbq1LWoff8hoPZzvzCPfmYfTjOIpMt07fWNg6S/Z0sqL6/YPuV9TRx+A+PQFIUMRS38Eae/1c89Lm/EFQyycWsXZM2u57V/rALhoTh2TKgsBo66OHX/QEH23M/oabPn4R3Mh9/o/LGfZ9jbaewMAbL/9w4Puv77JyBCeUi0dswQhExHRH0F+9vxG/rBkBwAPv72TBY2VLNvexqdPbuQ7F8/CFzTEOzaCxxL9/BjRz8tTeFx5vLKhmStPnDQqxc2eWxtt3W/a38W02mJe23SA06ZVx/W9XbnzIA2VBdSUSEllQchExL0zghw0rWWLZdsNN86iWUYrQbfTQanHGSf6Pkv0HfF/Dm8gzKrdHfzomQ2HNKeO3gB3v7gp6aze8+54jXN/9irX/H4ZT6zaE7UtEAqzZGsrJzRWHtJcBEFIPSL6I0ifP8iU6iJOm17NpXPrADhjRg0nH1Ed2ae6xM3m5m7aevqzbC3Rd7viu1BNMKtY7mjtOaQ5/WDxOn72/Eb+unzXoPvZ7zK2tBjvtX5fdLG3ZdsMN9D5s8Yf0lwEQUg9IvojSF8gRFVRPg9ddyLnzzaE0Qq7tKgucvPWllYuvOv1yJh/EEv/hZvP4ILZ42kZIKnLzjOrm9jXEW3Rv721FeivlxOLtc7wzrfO5f3vLIradu+rW9nc3B15vmp3OwAnTq0aci6CIKQnIvojSK8/RIEp8mfMqOXSuXV888Kjova57IQGwGhCorXGFwzx0NvGOoDbFf/nKHI7aagspKnD2H8gOvoC3PjwSq578J3+sd4A21sNsd/Rmlj0+wIhrljQQFmBi1KPi2tOmszHjqvnBx87BoDPPbwisu+aPZ1MrCigrEBq7ghCpiILuSNInz8U6RlbkO/gzsuPi9vn4/Mm0tLt4/bF69nb4eX5Nft4ZNlOANwJLH2A8aUe/EHDtz+3oTzhPpvMuvt2cbfuDlwOxeo9HRzo9lEd09O21xeMZP4C/O8lswGjB+7fVu7mne0H2dnay75OL4tXN/GRY+uS+SoEQUhTxNIfQfoCoTh3TiKOn1QBwMZ9XSxevS8ybsXrx3LBMeNxO/P4w5LtCbcHQ2GWbDHcOEVmQtfe9j7W7+sE4ItnT6fHH+KJ9/ZGHRcOa3oDIYoSzFkpxefPmgbA6T826gaFNZEicIIgZCZi6Y8gdvfOYMwYZ3Sb2ri/i+YuH7PrSykrcHFcQ0XC/SeUFTBnYjl7DvYl3H7PS5u568VNAIQ1eAMhTr79pcj2s2fWcu+rW9gV49f3BkNoDYXuxKfB6dNrOG16Na9vOhAZm1oj8fmCkMmIpT+CeP0hClxDX0fLC/OpLXGzYX8Xrd0+5k2q4I//sZCyARqpANSVe9jbkVj0NzX3R9m0dPni/PeVRflMrChkT3v08VbSVyJLH4w8gYeuO5Ff/tvxkTFPgggjQRAyBxH9JHlnexvf/PsHAy6mam24Sgryk/tK5zaU8/ya/XR6g1QWDZ3oVFdeQFO7l1CCRunjS42SCD/95BwArn3gnajthugXsGRLK1ta+qNxrEJuRQNY+hbzGxPfgQiCkHmI6CfJF/60kj8t3RmJYY/FbxZNsy+KDsZN50yny2eIbmXR0NEwk6sKCYY17+1qj9vmCxqhomfPNOrvx1r0HpeDE6ZU0u0LcvXvlkXGrf1iF3djqS2RMsqCkC2I6CeJ1RrwxXX7Iwukdrx+YxE2tib+QMyuL4ss+lYk0Vz8w8fWUex28reVu+PfOxDG43JQUZQfSQoDePi6E3n8cycDcMPpU1kwpZI97X1s3N/FG5sO8MPF6wGYVTd0r9tnv3w6r3ztzGQ+miAIaYyIfhKEwpr2XiOD9geL13P+na9zxo9fZsWO/mqZm1sMv3pV8dACbnHlgklAfAJXIordTmpL3LT3BeK2eYOhSIz/FeZrAkwfV8y8yYZrRinFmWY7xkV3vMZVv1vKqt0d5pyHdi8dOb6ERimyJggZj4h+Etz72hYOxDQn39Hay3/99f3I88dX7qEo38E5R41L+nW/fsFM7rp8LmfMqE1q/xKPk437uuj2RZda9gVCeJzGhaO+or/kcWwSVXlB/AXpx584Nun5CoKQ+YjoJ8GTMfHtV544iW9cMJOtB3o42OPnQLePPy3dySnTqikeYlHUjsuRxyVz63HEVLIciBKPi03N3Vx275KoccO9Y/wpJ5QVUFfmYXJVYVykTXmC6KAzZtTEjQmCkL1InP4QNHUYPvCbzpmOLxji3le38oWzprHBLEa2uaWbHz9rVMC0FlJHC0vE1+w11hR6fEE8LgfeQCiyzZGneOPrZyc8vjxB+YShFnEFQcguRPSH4J+r9hLW8PHj65lQVsC1p0xhXKknEjr5yV8bVvenT27kU/MbRnUu9ozdNXs7+PDdb3DVwkl4gyFKbYIeWwPfIlEewED7CoKQnYh7Zwg+2NNJfXkBk6uKyHfmRRqZTKwooLGqMLLfoqPHjbqAegP9HbQ+fPcbgNGspccXiuu6lQir8YlVGvljx9ePwiwFQUhnxNIfgrV7Ozg6QUijUooHPrOAM3/yCgCTxyCyxaq7H8u2Az0DFmKzU1vi4fX/dxYTKwpYs7eToyYMHaopCEJ2IZb+IGxu7mJLS0+kQFosk22W/vhRaGUYiyfGmr/EFpPvSVCWORENlYUopZhdX5b0ArIgCNmDWPoJWL+vkz8t3UmJx4kjT0Vq4MeilGLxl05j4/6uMRHQn102l78s28ndL20GjFIOVuVMt1Nq4giCMDQi+jGs3tPBR+4x/OUeVx4zxpVQOUjG7FETSsfMTVJfXsDNi47k929up9sX5Jj6ssg2KYQmCEIyDOkTUEo1KKVeVkqtU0qtUUp9yRyvVEo9r5TaZP5fYTvmG0qpzUqpDUqpD9nG5ymlPjC33a2USjv/wi9e3hx57A2EmdtQNsjeqcESeHtNnGRKKQiCICTjCA4CX9VaHwUsBD6vlDoauAV4UWs9HXjRfI657XJgFnA+8EullGWG/gq4Hphu/jt/BD/LiGBPYLru1Cl88ezpKZxNYu6+Yi4nTqlkQrmHWy6YCcBZo5wjIAhCdjCke0dr3QQ0mY+7lFLrgHrgEuBMc7cHgVeAr5vjf9Za+4BtSqnNwAKl1HagVGu9BEAp9QfgUmDxyH2cw6e508dRE0pZ/KXTUj2VATn5iGpOPqIaMAqpXXvKFPKTCNkUBEEYllIopRqB44ClwDjzgmBdGCxTsx7YZTtstzlWbz6OHU8r9nV6mVCWOaWElVIi+IIgJE3SaqGUKgYeB76stY6vLWzbNcGYHmQ80Xtdr5RarpRa3tLSkuwUR4T9nT7GlUppAkEQspOkRF8p5cIQ/D9qrf9mDu9XSk0wt08Ams3x3YA9xnEisNccn5hgPA6t9X1a6/la6/k1NWNbEKzbF4jUzhcEQcg2koneUcDvgHVa65/ZNj0JXGM+vgZ4wjZ+uVLKrZSagrFgu8x0AXUppRaar3m17ZiUsXZvJzc8tBxvIEQorPEGwkk3QhEEQcg0konTPwX4d+ADpdR75tg3gduBR5VS1wE7gU8CaK3XKKUeBdZiRP58XmttFY35HPAAUICxgJvSRdy2Hj8X3v06AO/ubOeYiUZ4ZpFbRF8QhOwkmeidN0jsjwc4Z4BjbgNuSzC+HJg9nAmOJk9/0BR5vLapkyNqjfo5BUn2uRUEQcg0cjrsY0tzN0X5DqqL3axr6qTPb9yQFIp7RxCELCVnRf9At48H3tpOZXE+k6sK2XOwjx6fIfri3hEEIVvJWT/GYyuMlIETGisJhjTv7WqnL2D0nhX3jiAI2UpOWvpaa97b2U5FoYvvf/QYJpR72NnWG7kQFOWLpS8IQnaSUyZtKKx5bVMLd72wifd2tfPx4yficTkihcseWWYkEheI6AuCkKXkjKXvDYT44TPr+cz97/DernYAPnv6FACuWNDAjHHFkX0Lxb0jCEKWkjOi/59/XMl9r20F4BPzJrLqfxYxc7xRjrgw38kdl82N7FviEdEXBCE7yRl1W7O3A4B8Zx4/+eScuO2z6spY/KXT2H2wj+piqb0jCEJ2kjOi39kX5NRp1Xzv0oFzw8ayC5YgCEIqyAn3To8vSF8gxKnTq2msLkr1dARBEFJGToh+a7cfgKpBet0KgiDkAjkh+j98Zj0A1SXiqxcEIbfJap++1pqH394RKax25LiSFM9IEAQhtWS16P/rg318+4k1ALz77fOoEPeOIAg5Tla7d/5lWvgPX3eiCL4gCAJZLPpd3gAvrt/PVQsncer06lRPRxAEIS3IWtG/7el1eANhLp5Tn+qpCIIgpA1ZK/rr93UxZ2IZC6ZUpnoqgiAIaUPWin6fP8S4Uk+qpyEIgpBWZK3o9waCFEqJZEEQhCiyVvT7/CEK3VkdkSoIgjBsslb0e/0haXAuCIIQQ1aKvtaavkBI3DuCIAgxZKXoewNhtJYG54IgCLFklOhv3N9Fnz805H69/iCAWPqCIAgxZIzo/+uDJhbd8Rofvud1OnoD/OqVLTR3eRPu22teGKTBuSAIQjQZ4f8IhTU/Mssjb23p4eTbX6THH+LpD/ay6OjxnDKtmnmTKyL79wUM0RdLXxAEIZqMsPRfWLef7a29/PzK4zhxSiU9piW/rqmLnz2/kY//6i1e29gCGIu4Dy3ZAYjoC4IgxJL2lv6O1l5ueGgFDZUFnD9rPI1VRVxx39vccdlcjplYRpc3wLk/e42rf7+M6bXFbGruBqCmxM30WqmfLwiCYCftRb/TG6CxxM3tHzsWpyOP2fVlrLp1EXl5CoBxpR6OqCliS0tPlGX/5tfPJt+ZETcygiAIY4bSWqd6DoNSOfko3bJtLQ5T5BPR3OXFFwjTUFnIql3tBMNh5k2WQmuCIOQuSqkVWuv5seNpb+lPrSkaVPABakv6C6vNaSgf5RkJgiBkLuL/EARByCFE9AVBEHIIEX1BEIQcQkRfEAQhhxDRFwRByCFE9AVBEHIIEX1BEIQcQkRfEAQhh0j7jFyllBdYfRgvUQZ0jMExdqqBA4dw3OG+7+Ecf6hzPtz3lTmPzXvL9zw275tO58aRWuv4AmRa67T+B/Qc5vH3jcUxMccvH6u5jtTxhzrnEXhfmfMYvLd8z9k950TvPdDr5YJ7559jdMxIcLjvm4nzljmPzXvL9zw275v250YmuHd6tNZFqZ7HcFBKLdcJCh2lMzLnsUHmPDbInAd+vUyw9P+W6gkcAvelegKHgMx5bJA5jw0y5wFeL+0tfUEQBGHkyARLXxAEQRghRPQFQRByiLQRfaVUd6rnMByUUh9VSmml1MxUz2W4DPVdK6VeUUqlxSKYUmqiUuoJpdQmpdQWpdRdSqn8Qfb/slKqcCznOMA85HweI+R8Hh5pI/oZyBXAG8DlwzlIKeUYei8BQCmlMBby/6G1ng7MAIqB2wY57MtAykU/A5HzeZRJl/M5rURfKVWslHpRKbVSKfWBUuoSc7xRKbVOKfUbpdQapdRzSqmCVM4TOAW4DvNHopQ6Uyn1mlLq70qptUqpXyul8sxt3Uqp7yqllgInpWredsz5PmV7/nOl1KdTOKVEnA14tdb3A2itQ8BXgGuVUkVKqZ+Y58n7SqkvKqVuAuqAl5VSL6dw3oCcz2OJnM/Jk1aiD3iBj2qtjwfOAn5qXh0BpgO/0FrPAtqBj6dmigBcCjyjtd4ItCmljjfHFwBfBY4BjgA+Zo4XAau11idqrd8Y68lmMLOAFfYBrXUnsBP4D2AKcJzW+ljgj1rru4G9wFla67PGerIJkPNZsJMW53O6ib4Cvq+Ueh94AagHxpnbtmmt3zMfrwAax3x2/VwB/Nl8/GfzOcAyrfVW8wr+CHCqOR4CHh/bKWYFCkgUU6yA04Ffa62DAFrrtrGcWJLI+SzYSYvz2TlaL3yI/BtQA8zTWgeUUtsBj7nNZ9svBKTkdlgpVYVxmzZbKaUBB8Yf8l/E/0Gt517zh5NOBIm+6HsG2jGFrCHGAlZKlQINwFYS/4DSCTmfxw45n5Mk3Sz9MqDZ/IGcBUxO9YQS8AngD1rryVrrRq11A7ANwwpaoJSaYvo+L8NYGEtXdgBHK6XcSqky4JxUTygBLwKFSqmrIbJo+FPgAeA54EallNPcVmke0wXEVxZMDXI+jx1yPidJWoi++UF9wB+B+Uqp5RhW0vqUTiwxVwB/jxl7HLgSWALcjlEKeluC/VKO9V1rrXcBjwLvY3zv76Z0YgnQRrr4R4FPKqU2ARsx/OTfBH6L4Qt9Xym1CuP7ByP1fHEqF3LlfB475HwePmlRhkEpNQf4jdZ6Qarncqgopc4Evqa1/kiKpzIo2fBdpzvZ8B3L+Zy9pNzSV0rdiLFI9N+pnku2I9/16CPf8dgh3/WhkRaWviAIgjA2jLmlr5RqUEq9bCanrFFKfckcr1RKPa+M9OTnlVIV5vh5SqkVZtLCCqXU2bbXuk0ptUtlWMq7kD2M1PmslCpUSj2tlFpvvs7tqfxcQvYy5pa+UmoCMEFrvVIpVYIRo3wp8GmgTWt9u1LqFqBCa/11pdRxwH6t9V6l1GzgWa11vflaCzFW7TdprYvH9IMIAiN3PiujvsqJWuuXlVGL5UXg+1rrxSn5YELWknL3jlLqCeDn5r8ztdZN5g/pFa31kTH7KozGwXVaa59tvFtEX0gHRuJ8NrfdhZH1+psxmrqQI6R0IVcp1QgcBywFxmmtmwDM/2sTHPJx4N3YH4ggpAMjdT4rpcqBizCsfUEYUVKWkauMIk+PA1/WWnf2lyQZcP9ZwA+BRWMwPUEYFiN1Pptx548Ad2utt47SdIUcJiWWvlLKhfED+aPW2uqBu9+8Dbb8pM22/SdiJIZcrbXeMtbzFYTBGOHz+T6MNao7R33iQk6SiugdBfwOWKe1/plt05PANebja4AnzP3LgaeBb2it3xzDqQrCkIzk+ayU+h5G6YYvj+6shVwmFdE7pwKvAx8AYXP4mxh+0EeBSRjpyJ/UWrcppf4b+AawyfYyi7TWzUqpH2GkK9dhlCD9rdb6O2PyQQSBkTufgXxgF0apBsvH/3Ot9W9H/UMIOUXKo3cEQRCEsSPlZRgEQRCEsUNEXxAEIYcQ0RcEQcghRPQFQRByCBF9QRCEHEJEXxBsKKVCSqn3zEqXq5RSN5vtAgc7plEpdeVg+whCuiCiLwjR9Gmt52qtZwHnARcCtw5xTCP97e0EIa2ROH1BsBFbsVUpNRV4B6jGaGz+EFBkbv6C1votpdTbwFEYfWQfBO7G6C17JuAGfqG1vnfMPoQgDIKIviDYSFSmWyl1EJgJdAFhrbVXKTUdeERrPT+2n6xS6nqgVmv9PaWUG3gTIyN321h+FkFIRMqqbApCBmGVzHQBP1dKzQVCwIwB9l8EHKuU+oT5vAyYjnEnIAgpRURfEAbBdO+EMKpk3grsB+ZgrId5BzoM+KLW+tkxmaQgDANZyBWEAVBK1QC/xih8pjEs9iatdRj4d8Bh7toFlNgOfRb4nFlyGaXUDKVUEYKQBoilLwjRFCil3sNw5QQxFm6tksm/BB5XSn0SeBnoMcffB4JKqVXAA8BdGBE9K83Syy0YfXMFIeXIQq4gCEIOIe4dQRCEHEJEXxAEIYcQ0RcEQcghRPQFQRByCBF9QRCEHEJEXxAEIYcQ0RcEQcghRPQFQRByiP8PiJiwqIsetJkAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's plot the portfolio in USD\n",
    "(df_tog.btc_amt_DCA * df_tog.Close).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5935.944379739725"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# With DCA approach at the end we have in USD:\n",
    "(df_tog.btc_amt_DCA * df_tog.Close)[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6999.631891453639"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# With Lump Sum approach at the end we have in USD:\n",
    "btc_amt_LS*(df_tog.Close[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1063.6875117139134"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# difference in USD\n",
    "(df_tog.btc_amt_DCA * df_tog.Close)[-1] - btc_amt_LS*(df_tog.Close[-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "With DCA You invested USD $ 11500 and at the end you got USD$ 5935.94\n"
     ]
    }
   ],
   "source": [
    "print(f'With DCA You invested USD $ {Total_USD} and at the end you got USD\\\n",
    "$ {(df_tog.btc_amt_DCA * df_tog.Close)[-1]:.2f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "With Lump Sum You invested USD $ 11500 and at the end you got USD    $ 6999.63\n"
     ]
    }
   ],
   "source": [
    "print(f'With Lump Sum You invested USD $ {Total_USD} and at the end you got USD\\\n",
    "    $ {btc_amt_LS * (df_tog.Close)[-1]:.2f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## So, for this period of time and for bitcoin as asset we got losses with DCA and Lump Sum Strategy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# Testing ETHEREUM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n",
      "ETH-USD\n"
     ]
    }
   ],
   "source": [
    "df = yf.download(CryptoPar[1], start='2020-12-31')\n",
    "print(CryptoPar[1])\n",
    "buydates = pd.date_range(start=df.index[0], end=df.index[-1], freq='1M')\n",
    "buyprices = df[df.index.isin(buydates)].Close"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2020-12-31    0.677687\n",
       "2021-01-31    0.380232\n",
       "2021-02-28    0.353095\n",
       "2021-03-31    0.260639\n",
       "2021-04-30    0.180297\n",
       "2021-05-31    0.184166\n",
       "2021-06-30    0.219824\n",
       "2021-07-31    0.197145\n",
       "2021-08-31    0.145614\n",
       "2021-09-30    0.166573\n",
       "2021-10-31    0.116602\n",
       "2021-11-30    0.107957\n",
       "2021-12-31    0.135772\n",
       "2022-01-31    0.185993\n",
       "2022-02-28    0.171280\n",
       "2022-03-31    0.152363\n",
       "2022-04-30    0.183138\n",
       "2022-05-31    0.257423\n",
       "2022-06-30    0.468472\n",
       "2022-07-31    0.297350\n",
       "2022-08-31    0.321816\n",
       "2022-09-30    0.376512\n",
       "2022-10-31    0.317922\n",
       "Name: Close, dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How much ethereum bought monthly: if a use us $ 500\n",
    "eth_amt = 500/buyprices\n",
    "eth_amt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.8578717803030775"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How much ethereum would i have if I used DCA purchases?\n",
    "eth_amt_sum =  eth_amt.cumsum()\n",
    "eth_amt_sum.name = 'eth_amt_DCA'\n",
    "eth_amt = 500/buyprices\n",
    "eth_dca = eth_amt.sum()\n",
    "eth_dca"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11500"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# if a bought ETH using us $ 500 monthly during the len of buyprice\n",
    "Total_USD = 500 * len(buyprices)\n",
    "Total_USD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "So, use USD $11500 to bought 5.8578717803030775 ETH using DCA Stategy\n"
     ]
    }
   ],
   "source": [
    "print(f'So, use USD ${Total_USD} to bought {eth_dca} ETH using DCA Stategy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15.586807962925077"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# So if I were bought us $ 11000 on the first day (Lump Sum) I had eth_amt_LS eth\n",
    "eth_amt_LS = 500 * len(buyprices) / buyprices[0]\n",
    "eth_amt_LS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So, in this case, if you had used the DCA strategy you would have **LESS** ethereum than if you had made the acquisition of the ethereum in a single purchase at the beginning of the period."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_tog = pd.concat([eth_amt_sum, df], axis=1).ffill()\n",
    "df_tog['eth_amt_LS'] = eth_amt_LS\n",
    "(df_tog.eth_amt_DCA * df_tog.Close).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7535.792364023789"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# With DCA approach at the end we have in USD:\n",
    "(df_tog.eth_amt_DCA * df_tog.Close)[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20051.4713929841"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# With Lump Sum approach at the end we have in USD:\n",
    "eth_amt_LS*(df_tog.Close[-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "With DCA You invested USD $ 11500 and at the end you got USD$ 7535.79\n"
     ]
    }
   ],
   "source": [
    "print(f'With DCA You invested USD $ {Total_USD} and at the end you got USD\\\n",
    "$ {(df_tog.eth_amt_DCA * df_tog.Close)[-1]:.2f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "With Lump Sum You invested USD $ 11500 and at the end you got USD    $ 20051.47\n"
     ]
    }
   ],
   "source": [
    "print(f'With Lump Sum You invested USD $ {Total_USD} and at the end you got USD\\\n",
    "    $ {eth_amt_LS * (df_tog.Close)[-1]:.2f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## So, for this period of time for Ethereum as asset we got losses if we had used DCA, but we would have made significant profits using Lump Sum strategy."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# Come get some!\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n",
      "BTC-USD\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "ETH-USD\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "BNB-USD\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "XRP-USD\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "ADA-USD\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "DOGE-USD\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "SOL-USD\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "DOT-USD\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "TRX-USD\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "LTC-USD\n",
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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QW1vLU089RSKR4DOf+QyLFi1i8eLFnHHGGezYsSN3TVlZWZ/33Lp1K8uXL+9y7JprruHGG28E4Mknn+Stb30rtbW1LF26lGuuuQaA22+/nSlTprBq1SoWL17MySefzBNPPFHYT3gAAqP+RBERERkz2YDCO5ANKDIVFJWqoBARERktf/7zn7n33nt59tlnCYfDHDhwgEQiwb/8y7/Q3NzMyy+/jOu6fP/73+fMM8/kqaeewhgz7Oeee+653H333axcuRLP89iyZUvuvbPOOotbbrkFgEceeYQzzzyTRx55hKVLlw77uQOlCgoREZEiYT2P5Pbt6deJBAAmFAQ6t3gcHJO1iYiIFJPdu3czefJkwplWy8mTJ1NZWcn3v/99vva1r+G6LgDnn38+4XCYhx9+uCDP3bdvHzNmzADAdV2WLVuW97wTTjiBiy66iFtvvbUgzx2ofisojDHfA04F9llrl3d770rgBmCKtfZA5tjVwMcBD/i0tfZ3mePHArcDUeC3wD9Za60xJgz8ADgWqAfOstZuzVxzLvD/ZR7379baO4b12YqIiBSx5O492GQSjIHMdqJO5108UAWFiIgUlz3/8R/EN20u6D3DS49i+r/8S5/nnHTSSVx33XUceeSRnHjiiZx11llUVVUxd+5cJk2a1OXcNWvW8OKLL7J+/fphr+3yyy9nyZIlrFu3jlNOOYVzzz2XSCSS99zVq1fz7W9/e9jPHIyBVFDcDpzS/aAxZg7wXmB7p2PLgI8AR2eu+S9jjJt5+7+Bi4DFmf+y9/w40GitPQL4GvCfmXtVA18E3gqsBb5ojKka3KcnIiIiWYltWwEILVqYO5YdkmkiEUwohK+AQkREZMSVlZXxzDPPcOuttzJlyhTOOussHnnkkbxtHNbaAbd39HZe9vgXvvAFNmzYwEknncSPf/xjTjmlx7f6XZ472vqtoLDW/sEYMz/PW18D/hn4ZadjZwA/sdbGgTeMMa8Ca40xW4FJ1to/AxhjfgB8ALgvc801mevvAW4x6d+9k4EHrbUNmWseJB1q3DW4T1FEREQAkjt2AhBZtozEq68BHUMyjTG4FRWqoBARkaLSX6XDSHJdl3Xr1rFu3TpWrFjBt7/9bbZt20ZzczPl5eW585599llOO+20vPd48803c+9dfPHF/MM//AONjY1dzmloaGDBggW5jxctWsQnP/lJLrzwQqZMmUJ9Zmev7jZu3Diq8ydgiDMojDGnAzuttc91e2sW8Ganj3dkjs3KvO5+vMs11toU0ATU9HGvfOu5yBizwRizYf/+/UP5lERERCY8v70NgOD0Gblj2QoKSA/K1C4eIiIiI2/Lli288soruY/r6upYsmQJ5557LldccQWe5wHwgx/8gLa2Nt7znvfkvc+cOXOoq6ujrq6Oiy++mLKyMmbMmMFDDz0EpMOJ+++/n3e+850A/OY3v8lVRrzyyiu4rktlZWWP+z722GPceuutXHjhhYX8tPs16F08jDElwL8CJ+V7O88x28fxoV7T9aC1twK3AqxZs2b061BERETGAZtIAhCYXJM7ZoKh3GunlwqKbR87h8qzzqLi1L8Z+UWKiIgUgZaWFi677DIOHjxIIBDgiCOO4NZbb6W8vJwrr7ySI488EsdxOOqoo/j5z3+ea9Foa2tj9uzZuftcccUVXHHFFV3u/YMf/IBLLrmEz372swB88YtfZNGiRQD88Ic/5PLLL6ekpIRAIMCPfvSj3EDOn/70pzz++OO0tbWxYMECfvazn416BcVQthldBCwAnsv8Js0GnjXGrCVd5TCn07mzgV2Z47PzHKfTNTuMMQGgAmjIHF/X7ZpHh7BeERERAWw8DoBbVZ07lt3FA8CtqCS5Y0fXaxIJ2v7yF9zqagUUIiIiBXLsscfyxBNP5H3vm9/8Jt/85jfzvuf7fr/3XrZsGY888kje937yk5/kPX7eeedx3nnn9XvvkTboFg9r7fPW2qnW2vnW2vmkg4TV1to9wK+AjxhjwsaYBaSHYT5trd0NNBtjjsvMlziHjtkVvwLOzbz+EPCwTdec/A44yRhTlRmOeVLmmIiIiAyBTSQwwSBuRcd0cKdzi0eeCgqvtRWA2OZNo7NIERERKVoD2Wb0LtKVDJONMTuAL1prv5vvXGvti8aYu4GXgBRwibXWy7z9STq2Gb0v8x/Ad4EfZgZqNpDeBQRrbYMx5kvAXzLnXZcdmCkiIiKDZxMJTCiEU9YxeCs7JBPyBxS2LT23IrltO15LC25Z2egsVkRERIrOQHbx+Gg/78/v9vH1wPV5ztsALM9zPAZ8uJd7fw/4Xn9rFBERkf75iTgmFMItz4QMrosJdHwp4FZUYNvb8RMJnExw4WcCCoD45s2UrFkzqmsWERGR4jGkXTxERERk/MlVUGS2LutcPQHpXTwA/E5VFH6mxQMg9pLaPERERGTkKKAQEREpEjaRxITDuRaPHgFFZnhm6sCB3LHOFRSxTQooREREZOQooBARESkSNh7HhII4pSXgOLk2jqzgzBkAJHfvzh3LDsl0J0+m7ZlnsInE6C1YREREiooCChERkSKRbfEwxuCUl/eooAjOnAlAcueujmsyFRQ1559Pcvt29t30tdFbsIiIyATlui61tbUcffTRrFy5kptuuqnLFqKPP/44a9eu5aijjuKoo47i1ltv7XL9nXfeyTHHHJO7/h//8R85ePAgAOvWrWPJkiXU1tZSW1vLhz70obxrKOs2+Pr222/n0ksvBWDLli2sW7eO2tpali5dykUXXQTAo48+SkVFBatWrWLJkiUcf/zx3HvvvYX6bel/SKaIiIhMDDaRwAmltxV1y8ownbYYBXCrqzHhcN4KiorTTyO5cwcNt99O1Uc/QmjevNFbuIiIyAQTjUapq6sDYN++fZx99tk0NTVx7bXXsmfPHs4++2x+8YtfsHr1ag4cOMDJJ5/MrFmz+Ju/+Rvuv/9+vva1r3Hfffcxa9YsPM/jjjvuYO/evVRWVgLwox/9iDXDGGz96U9/mssvv5wzzjgDgOeffz733rve9a5cKFFXV8cHPvABotEo69evH/LzslRBISIiUiSyu3gAeSsojDEEZ8wguatnBYVTWkpZ5guPVH39KK1YRERk4ps6dSq33nort9xyC9ZavvWtb3HeeeexevVqACZPnsxXv/pVvvKVrwBw/fXXc+ONNzJr1iwgXY1xwQUXsGTJkoKtaffu3cyePTv38YoVK/KeV1tbyxe+8AVuueWWgjxXFRQiIiJFwiaSOJOiALjl5fiJeI9zgjNnkNzdEVB4ra1gDCYaxYlE0veJxUZnwSIiIiPsj3e/zIE3Wwp6z8lzynjX3x05qGsWLlyI7/vs27ePF198kXPPPbfL+2vWrOHFF18E4MUXX8yFF735+7//e6LR9L/5733ve7nhhhsGtZ7LL7+c97znPbz97W/npJNO4vzzz89VZ3S3evXqQd+/N6qgEBERKRI2kci1dUy+5FNMufSyHucEZs7sUUHhlJRgjMGE0wGFH+sZbIiIiMjwWGtzvxpjeryf79jzzz9PbW0tixYt4qc//Wnu+I9+9CPq6uqoq6sbVHiQfcb555/Ppk2b+PCHP8yjjz7KcccdRzye/9//7LoLQRUUIiIiRSK7iwdA6XHH5T0nOGMG3v4D+PE4TjiM19qKU1ICgBMJZ+6jCgoREZkYBlvpMFJef/11XNdl6tSpHH300WzYsIHTTz899/4zzzzDsmXLADj66KN59tlnOeGEE1ixYgV1dXVceumltLe393p/z/M49thjATj99NO57rrriEajJBIJQpmWz4aGBiZPnpy7ZubMmVxwwQVccMEFLF++nBdeeCHvvTdu3MjSpUuH/XsAqqAQEREpGukhmaE+zwnOTPezpvbsSV/T1oZTWgqAybR4+O2FDyjan3+e3ddeW9CfwoiIiIwH+/fv5+KLL+bSSy/FGMMll1zC7bffnhuiWV9fz+c//3n++Z//GYCrr76aK6+8kh07duTu0Vc4Aek5FdmKiuuuuw6Ad7/73dx555256++++25OOOEEAO6//36SySQAe/bsob6+PjfzorO//vWvfOlLX+KSSy4Z3m9ChiooREREikR6m9Fwn+dktxqNbdqEU1LStYIiPHIVFE2//jUH7/oJ0z73OUzmeSIiIhNVe3s7tbW1JJNJAoEAH/vYx7jiiisAmDFjBnfeeScXXnghzc3NWGv5zGc+w2mnnQbA+9//fvbv38/73vc+PM+jsrKS5cuXc/LJJ+fu33kGxeTJk/n973/fYw3f+MY3+MQnPsHNN9+MtZZzzjmH448/HoAHHniAf/qnfyKS+eHEDTfcwPTp09m8eTN//OMfWbVqFW1tbUydOpWbb765IDt4gAIKERGRouEnEj127uguOHMGADs/czmRFStwwuGeFRQjMIMi8cZWIB2ioIBCREQmOM/z+nz/+OOP5y9/+Uuv75977rk9BmlmPfroowNaw6xZs3LbhXZ30003cdNNN/U4vm7dOpqamgZ0/6FQi4eIiEiRsAMJKKZNw62shECAxGuv4bWNTgVF4vXXgXSIIiIiIsVJAYWIiEiRSO/i0XdAYUIhFj34AFM/80/4bW2k9uzNVVAQDILj4Bd4m1E/FsvtHGIVUIiIiBQtBRQiIiJFwKZS4Hn9VlAAuOXlBDODsLyGBpzSdAWFMQYTiWAL3OKR2LYNslurKaAQEREpWgooREREikD2G//+dvHICkyfnnvtlJR2vA6H8Qvc4pF4443cawUUIiIixUsBhYiISBHIfuPf3y4eWcEZM3KvsxUUQL8VFH5r66DXFs/MnwAFFCIiIsVMAYWIiEgR8OPZgGKAFRRTpoDrAnTMoCBdQdHbkMz4a6+x5S1rib388qDWlt3BA8DGC79DiIiIiIwPCihERESKgE0OLqAwrktg6lSA3C4ekK6g6G2b0cSbb4Lvk9y5c1BrS2zbhsk8Q7t4iIhIsfj5z3+OMYbNmzcDsHXrVqLRKKtWrWLp0qWsXbuWO+64o8d1K1eu5KMf/Wiv97399tu59NJLuxxbt24dGzZsAOB73/seK1as4JhjjmH58uX88pe/BOC8885jwYIFrFy5kiOPPJJzzjmHnYP8N324FFCIiIgUgVyLRz+7eHQWzMyh6FFB0csuHratLf3rIHf58FtaCFRXd1mniIjIRHfXXXfxzne+k5/85Ce5Y4sWLWLjxo1s2rSJn/zkJ3zta1/j+9//fu79TZs24fs+f/jDH2gdQlvljh07uP7663n88cf561//ypNPPskxxxyTe/+GG27gueeeY8uWLaxatYoTTjiBxCj+26yAQkREpAhkWycGWkEBEJyRCSi6V1D00obhZb5Q8tvaB702Z1J55rUCChERmfhaWlr405/+xHe/+90uAUVnCxcu5KabbuLmm2/OHfvxj3/Mxz72MU466SR+9atfDfq5+/bto7y8nLKyMgDKyspYsGBBj/OMMVx++eVMnz6d++67b9DPGarAqD1JRERExsxgd/EACExPD8rsUkERiZA6cCD/MzIVFH774AIKPxEnWJYJKJIKKEREZPQ8cvut7Nv2ev8nDsLUeQs54byL+jznF7/4BaeccgpHHnkk1dXVPPvss1Rnqgk7W716da4FBOCnP/0pDz74IFu2bOGWW27ps9Ujn5UrVzJt2jQWLFjA+vXrOfPMMznttNN6PT/7/DPOOGNQzxkqVVCIiIgUgY4Wj4Ht4gGdWjx6zKDI38KRraCwscFWUCRwysu7rFNERGQiu+uuu/jIRz4CwEc+8hHuuuuuvOdZa3Ov//KXvzBlyhTmzZvH+vXrefbZZ2lsbOxxjTEm772MMbiuy/33388999zDkUceyeWXX84111zT6zo7P380qIJCRESkCAx2Fw+AyPLlmHCY4MyZuWNOpP8ZFINu8UgkcDOlpgooRERkNPVX6TAS6uvrefjhh3nhhRcwxuB5HsYYPvWpT/U4d+PGjSxduhRIhxqbN29m/vz5ABw6dIif/exn1NTUcO211wJw2223UVNT0yO4aGhoYPLkyUA6qFi7di1r167lve99L+eff36vIcXGjRtZv359gT7z/imgEBERKQK5CorgwAOKktWrWLLxWYzTUXBpwgOYQTGIFg9rbXoGRaaCord7i4iITBT33HMP55xzDt/+9rdzx9797nezY8eOLudt3bqVK6+8kssuuwzf9/nf//1f/vrXvzJr1iwAHnnkEf793/+dhx56iL/927/NXbd3714uvfRS9uzZw/Tp09mwYQPxeJw5c+awa9cu9uzZw+rVqwGoq6tj3rx5PdZoreWb3/wmu3fv5pRTThmJ34a8FFCIiIgUgaHs4gF0CScAzEAqKAbT4pFMgrU45dkKiuSg1iciIjLe3HXXXVx11VVdjn3wgx/kP/7jP3jttddYtWoVsViM8vJyLrvsMs4//3weffRRZs2alQsnAI4//nheeukldu/ezYwZM3LHp02bxje+8Q3e//734/s+ZWVl3HXXXTiOQzKZ5Morr2TXrl1EIhGmTJnC//zP/+Su/dznPseXvvQl2traOO6443jkkUcIDaL6crgUUIiIiBQBm0hXJgxmSGY+zgAqKOwgWjz8THDilmkGhYiIFIdHH320x7FPf/rTfPrTn+71mnXr1vHkk092Oea6Lrt37857/hlnnJF3sOW8efN4+OGH815z++23977oUaIhmSIiIkUgV0ExzIDCRMKQTGI9r+czhrCLR27702gEAgEFFCIiIkVMAYWIiEgR8Iewi0c+TiQCkLfNIzeDYhAtHtmAwgmHcUKh3MciIiJSfBRQiIiIFAE7hF088jHhdECRr80jW0ExqBaPbAVFKIQJhbBJVVCIiIgUKwUUIiIiRaBQLR5OJF2B0WcFxWBaPDJDMU0ojAmFcpUeIiIiUnwUUIiIiBSBjm1Gg8O6T66CIpangqI1u4tH/l0+8q8rU0ERzlRQxBVQiIiIFCsFFCIiIkXAJuKYYLDHtqGDZbIVFPE8FRS5IZltA19XpxkUJhzWkEwREZEipoBCRESkCNhEYtjtHdAxJLN7lYRNJCCZbtcY0gyKcLrFQwGFiIgUgzfffJMFCxbQ0NAAQGNjIwsWLOCxxx4jGo1SW1vLsmXLOOecc0hm/n199NFHqaioYNWqVSxdupRrr702773Lysq6fHz77bdz6aWXArBlyxbWrVtHbW0tS5cu5aKLLupx7yVLlnD88cdz7733jtSn3ysFFCIiIkXAL1BAkd0FpPsMiuz8CRMKDa7FIze8M4wJBRVQiIhIUZgzZw6f/OQnueqqqwC46qqruOiii5g3bx6LFi2irq6O559/nh07dnD33XfnrnvXu97Fxo0b2bBhA3feeSfPPPPMoJ776U9/mssvv5y6ujo2bdrEZZdd1uPeW7Zs4eabb+bSSy/loYceKswnPEAKKERERIqAjSeGvcUo9F5B4WfmT7iTa7CxGNb3B7au7AyKUBAnFNY2oyIiUjQuv/xynnzySb7+9a/z+OOP89nPfrbL+67rsnbtWnbu3Nnj2tLSUo499lhee+21QT1z9+7dzJ49O/fxihUr8p5XW1vLF77wBW655ZZB3X+4AqP6NBERERkThWrxyA7J7B4k+G3pCopAzWRSu3bT/txzJF5/ncoPfrDfdUFmBkUohNfSPOw1ioiIDNTBX79GYldrQe8ZmllK5WmL+j0vGAxyww03cMopp/DAAw8Q6vbvdCwW46mnnuIb3/hGj2vr6+t58skn+bd/+7dBre3yyy/nPe95D29/+9s56aSTOP/886msrMx77urVq7nhhhsGdf/hUgWFiIhIEUgHFMPbwQM6thntWUGRCSgmTwag/rvfZfc11/ZbSdFzBkVy2GsUEREZL+677z5mzJjBCy+8kDv22muvUVtbS01NDXPnzuWYY47JvffHP/6RVatWcdJJJ3HVVVdx9NFHD+g5xhgAzj//fDZt2sSHP/xhHn30UY477jjivVQvWmuH8ZkNjSooREREioCNx3FCw2/xMJkWDxvrXkGRbvEITK4BIPHGVkgm8ZqaCFRV9bGuzAwKDckUEZExMJBKh5FSV1fHgw8+yJNPPsk73/lOPvKRjwDkZlDs3r2bdevW8atf/YrTTz8dSM+J6Dy80vM8jj32WABOP/10rrvuOqLRKIlEIleR0dDQwOTMDxAAZs6cyQUXXMAFF1zA8uXLu4QjnW3cuJGlS5eOyOfeG1VQiIiIFAGbLOwuHt23Gc1WULg1mYBi+3YAvAMH+l5XdpvRUAgTDmkGhYiIFAVrLZ/85Cf5+te/zty5c/nc5z7HlVde2eWcGTNm8JWvfIUvf/nLvd7HdV3q6uqoq6vjuuuuA+Dd7343d955JwDt7e3cfffdnHDCCQDcf//9uV1B9uzZQ319PbNmzepx37/+9a986Utf4pJLLinI5ztQCihERESKgB8v0AyK3JDMXiooajI/ocl88ZPqL6DIDckMqYJCRESKxne+8x3mzp3Le9/7XgA+9alPsXnzZrZt29blvA984AO0tbXxxz/+ccD3/sY3vsH//d//UVtby3HHHceHP/xhjj/+eAAeeOABli9fzsqVKzn55JO54YYbmD59OtDRPrJkyRIuueQSbr75ZtavX1+gz3hg1OIhIiJSBGwshtupvHOoTCgExvRaQZFt8cjqL6Dw43FwHAgEcBRQiIhIkbjooou46KKLch+7rpvbMrRzy4Uxhueeey738bp16/q996xZs7q0gXR20003cdNNN/U4vm7dOpqamga6/BGjCgoREZEi4MdimGh02PcxxuBWV3Pot/eR2Lq14/6ZCopsi0dWan9/FRTJ9PwJYzDBEL4CChERkaKlgEJERKQI2Pb23PyI4Zr1//4f3sGD7Lj8itwxv7UVHKfHQMx+WzzicZxM64kJh1VBISIiUsQUUIiIiBSBdAVFYQKK0uPeSvkpJ5Pau7fj/m1tOCUlOCUlHSc6DqkD+/u8l03EMeH07iImFIJUqt+tSUVERGRiUkAhIiJSBPxYDCcy/BaPrO4DLROvv0FwxvQubSShhQv63cXDj3cLKEBVFCIiIkVKAYWIiMgEZ61Nt3gUqIIC6DLQ0noe7Rs3Ej32WJxMQGFKSgjNn9//DIpOu4s44UxAoa1GRUREipICChERkQnOJhJgLWYEKiistcS3bMFvbaXk2DW5bUiDU6cSmDx5QDMoTCaYUAWFiIhIcVNAISIiMsHZ9nYAnEi4YPc0ocy9kknaNqS3RSs5dnV6N45olMD06QQmT8FrbMQmk72vLRHHCanFQ0REiovrutTW1rJy5UpWr17NE088AcDWrVsxxvDNb34zd+6ll17K7bffDsB5553HggULqK2t5aijjuLaa6/Ne/9HH32UU089tcux8847j3vuuQeAe++9l1WrVrFy5UqWLVvGt7/9bQCuueYaZs2aRW1tLYsXL+bMM8/kpZdeKvSn3ysFFCIiIhOcH4sB5KobCiEbJviJJG3PPktg5gyCM2cC4JSVEpw+ncDkyQCkGhp6X1si0WMGhR9XQCEiIhNbNBqlrq6O5557ji9/+ctcffXVufemTp3KN77xDRK9BPY33HADdXV11NXVcccdd/DGG28M6tnJZJKLLrqIX//61zz33HNs3LiRdevW5d6//PLLqaur45VXXuGss87iPe95D/v39z30ulAUUIiIiExwfraCIlrYFg8Am0zQ/txzlKxanXtv5le+wuSLP0FgSiag6GMOhY0nOrV4hHP3FBERKRaHDh2iqtM23VOmTGH9+vXccccdfV4Xy/wAorS0dFDPa25uJpVKUVNTA0A4HGbJkiV5zz3rrLM46aST+PGPfzyoZwxVYFSeIiIiImPGjkgFRTB973gc7+BBAlOn5t4re8c7APAOHgToc6tRG4/j5CooMvdUi4eIiIyS++67jz179hT0ntOnT+d973tfn+e0t7dTW1tLLBZj9+7dPPzww13ev+qqq3jf+97HBRdc0OPaz33uc/z7v/87r776Kp/+9KeZ2unf4IGorq7m9NNPZ968eaxfv55TTz2Vj370ozhO/vqF1atXs3nz5kE9Y6hUQSEiIjLB+e3pgKLQ24xCOkyw8Tgmz3wLN/PToGxQkY+NxzFBDckUEZHikm3x2Lx5M/fffz/nnHMO1trc+wsWLGDt2rV5KxeyLR579uzhoYceys2v6MwYk/e52eO33XYbDz30EGvXruXGG2/MG4RkdV7XSFMFhYiIyARnY9kWj8JuMwrgt7WB7+eqIDpzKyuBvgOKzjMosvfUNqMiIjJa+qt0GA1ve9vbOHDgQI85D//yL//Chz70IY4//vi815WVlbFu3Toef/xxXNflE5/4BADXXXcdCxcupLGxscv5DQ0NTM7MhwJYsWIFK1as4GMf+xgLFizIDeLsbuPGjaxZs2YYn+HAqYJCRERkgusYkln4Cgq/uTnzcc+AwikvB8fBazzY6326bDOaCSp8VVCIiEgR2bx5M57n5WZCZB111FEsW7aMe++9N+91qVSKp556ikWLFvHWt741Nzjz9NNPZ/HixezatYtNmzYBsG3bNp577jlqa2tpaWnh0Ucfzd2nrq6OefPm5X3Gz372Mx544AE++tGPFuaT7YcqKERERCa4jiGZBZxBkQkTvGxAkafFwzgObmVl3y0eiUSnGRRq8RARkeKQnUEB6RaKO+64A9d1e5z3r//6r6xatarLsewMikQiwfr16znzzDN7XBcOh7nzzjs5//zzicViBINBbrvtNioqKmhubuarX/0qn/jEJ4hGo5SWlnapnvja177GnXfeSWtrK8uXL+fhhx9mypQpBf38e6OAQkREZILLDsl0CjkkM9i1giJfiwfQf0ARj+eqLzoCimTB1ikiInI48jwv7/H58+fzwgsv5D5euXIlvu/nPu6tDSOfd7zjHTz55JM9jpeXl/Pb3/427zXXXHMN11xzzYCfUWhq8RAREZngskMyzQhsM+od6r3FA/oOKKzvY5PJ3L2yAYrf3lawdYqIiMj4oYBCRERkgssNySzoNqOZgKL5UPrjPC0e0E9AkWnlyA3JnDQJAL+5pWDrFBERkfFDAYWIiMgEl6ugKGhAEUzf+9DQWzyyu3U4mSGZTklJeqjmoaaCrVNERETGDwUUIiIiE5yNxzDhMMYp3D/72S1BvZZMi0c4f/jhVlbiNTbm3UPdzwQU2QoK4zi45eW50ENERESKiwIKERGRCc5vjxW0vQM6bzOabsfIVkF051ZWYhMJbGYnkc5yLR6d5lc4kybldgYRERGR4tJvQGGM+Z4xZp8x5oVOx24wxmw2xvzVGPNzY0xlp/euNsa8aozZYow5udPxY40xz2feu9kYYzLHw8aYn2aOP2WMmd/pmnONMa9k/ju3UJ+0iIjIRJA6cICWP/yh3/P8WHtBB2RCR9WDn51B0VuLR1UlQN42j2xo4XSaX+GWl6vFQ0REpEgNpILiduCUbsceBJZba48BXgauBjDGLAM+Ahyduea/jDHZzVz/G7gIWJz5L3vPjwON1tojgK8B/5m5VzXwReCtwFrgi8aYqsF/iiIiIhNTw49+xJuf/BQ22fe2nHYEKyi8TAVFXy0ekD+gSO7ZA0Bg+vTcMadiklo8RERkwnNdl9ra2tx/X/nKV/jbv/1bamtrOeKII6ioqMi998QTT7Bu3To2bNiQu37r1q0sX7487737OretrY2///u/Z8WKFSxfvpx3vvOdtLS0dFnT0UcfzcqVK7npppu6bHE6GgL9nWCt/UPnqobMsQc6ffgk8KHM6zOAn1hr48AbxphXgbXGmK3AJGvtnwGMMT8APgDcl7nmmsz19wC3ZKorTgYetNY2ZK55kHSocdegP0sREZEJKLV/P3geXksLgareM3w/Fit8BUW2xeNQuoKitxaPQF8Bxc5dAARnzswdc8snEd/3WgFXKiIicviJRqPU1dXlfe/RRx/lxhtv5N577y34c7/xjW8wbdo0nn/+eQC2bNlCMBjssaZ9+/Zx9tln09TUxLXXXlvwdfSmEDMoLiAdNADMAt7s9N6OzLFZmdfdj3e5xlqbApqAmj7uJSIiIoDX0AiA39R3S4SNtRe+giLzxUx2XkRvO4T0WUGxcycEgwSmTOk4v2JSLvQQERGRwtq9ezezZnV8W71kyRLCedo0p06dyq233sott9ySd9D1SOm3gqIvxph/BVLAj7KH8pxm+zg+1Gu6r+Mi0u0jzJ07t48Vi4iITBxefX36136GSvrtMZxogQMKx4FgsCOg6GObUYBUY2OP95I7dxKcMQPjurljTrmGZIqIyOh5+eUv0dyyqaD3LC9bypFH/luf57S3t1NbW5v7+Oqrr+ass87q85q///u/J5qpiEwkEjhD2J3rggsu4KSTTuKee+5h/fr1nHvuuSxevDjvuQsXLsT3ffbt28e0adMG/ayhGHJAkRlaeSqw3nZEKjuAOZ1Omw3syhyfned452t2GGMCQAXQkDm+rts1j+Zbi7X2VuBWgDVr1oxevCMiIjKGst/0e/1UHPixGG4fLSBD5QSD+G1t6dehXnbxqKgAeq+gCM6a2fX8SZOwsRh+ItHrPUVERMa7vlo8evOjH/2INWvWAOm5Eqeeemre8zL7UeQ9Vltby+uvv84DDzzA73//e97ylrfw5z//maVLl+a912hWT8AQAwpjzCnA54F3W2vbOr31K+DHxpibgJmkh2E+ba31jDHNxpjjgKeAc4BvdrrmXODPpGdZPGyttcaY3wH/0Wkw5klkhnGKiIhIRwWF30/FgW0vfIsHZOZQtLVBppqit3Oc0lK8gz3bUBK7dlL27nd3OeZMKgfSsy2cyZMLvmYREZHO+qt0GA/OP/98Nm7cyMyZM/ntb39LTU0NjZ0qFxsaGpjc6d/UsrIyzjzzTM4880wcx+G3v/1t3oDi9ddfx3Vdpk6dOiqfBwwgoDDG3EW6kmGyMWYH6Z01rgbCwIOZJOZJa+3F1toXjTF3Ay+Rbv24xFrrZW71SdI7gkRJz6zIzq34LvDDzEDNBtK7gGCtbTDGfAn4S+a867IDM0VERIqdH4/jt7YCA6ugMAVu8YCOtg4TDuf9aU2WW1GB13Sw65ricbz9B7oMyIT0kEwA71AzAQUUIiIi/fr+97/f5eN169Zx5513cuKJJ2KM4Y477uCEE04A4E9/+hPLli2jqqqKRCLBSy+9xLp163rcc//+/Vx88cVceumlff4bX2gD2cXjo3kOf7eP868Hrs9zfAPQYx8Ua20M+HAv9/oe8L3+1igiIlJsvIaOzL6/oZLpCorC7uIBHTt5OL3Mn8hySkuw7e1djiV3pTs9Q7O6zr92K9IBhX+o78GfIiIi41n3GRSnnHIKX/nKVwpy74suuojNmzezcuVKjDGsWbOGL3/5ywC89tprfPKTn8Rai+/7/M3f/A0f/OAHu6wpmUwSCAT42Mc+xhVXXFGQNQ3UsIZkioiIyNhIdQoovEP9DMmMFX5IJnQEFL0NyMydV1KC39YtoMhuMdotoHDK0y0eGpQpIiITmed5vb63bt26HlUNjz76aJeP58+fzwsvvJD3+lAoxC233JL3vXPOOYdzzjln0GsaLYXYZlRERERGWecKCq+59woK6/vYeBwTHruAwomW4HevoNi5E+gZUOSGajZpq1EREZFio4BCRERkHMoFFIEAfh8VFDYWAxihCor0YMx+Wzyi0dxuH1mJ7dswwSCBboO33EwFhd9H6CIiIiITkwIKERGRcShVnw4oQrNn91lB4bW0AGBGYAaFExxoBUUUv71rQBF/+RVCixZhXLfruZM6hmSKiIhIcVFAISIiMg55jQ0QDBKcOQO/j3aIxh//GIDoypUFX0OuxSMygCGZ3WZQxLdsIbLkyJ7nhsOYcBhPQzJFRESKjgIKERGRcShV30CguhpnUkWvAyUTO3bS8L3vM+m004iu6LGR1rBlKyecUD9DMru1eKQaG0nt20f4yCV5z3cmlffZtiIiIiITkwIKERGRcchraMCtrsadNKnXFo/m3/0Om0gw9fLPjMgaBjsk01oLpNs7AMJH9qygAHD7CF1ERERk4lJAISIiMg6lGtIVFG4f1Qap+npMJEJgxowRWcOAWzxKSsD3sYkEAPGXXwYgnKfFA8CtqsQ7cKCAKxURETm8uK5LbW0tK1euZPXq1TzxxBM8//zz1NbWUltbS3V1NQsWLKC2tpYTTzyRZDLJVVddxeLFi1m+fDlr167lvvvu63Hf22+/nUsvvbTLsXXr1rFhwwYAvve977FixQqOOeYYli9fzi9/+UsAzjvvPBYsWMDKlSs58sgjOeecc9iZ2XFrNAVG/YkiIiIybKm9ewkvWIBTPgkbj+PH4z120/Dq63GrqzDGjMgacrt49NPi4UTTAzr9tjaccJj4y1twKysJTJmS9/zQrFm0Pv2Xwi5WRETkMBKNRqmrqwPgd7/7HVdffTWPPfZY7th5553Hqaeeyoc+9CEArrrqKnbv3s0LL7xAOBxm7969PPbYY4N65o4dO7j++ut59tlnqaiooKWlhf379+fev+GGG/jQhz6EtZavf/3rnHDCCbzwwguEMj+QGA2qoBARERln/FiM1N69BOfNxZ2U2ZbzUM82j1RjA4Gq6hFbR0cFRd9bmDol6YDCZuZQxF5+mfCSJb0GJ8FZs0nt2ZOruBAREZnIDh06RFVVVa/vt7W18Z3vfIdvfvObhDM/jJg2bRp/93d/N6jn7Nu3j/LycsrKygAoKytjwYIFPc4zxnD55Zczffr0vFUaI0kVFCIiIuNM8s03AQjNnZc75jU396hI8BoacatHLqBwcjMo+v7JislWULSnd/JI7dpN6fHv6vX84Jw5YC3J3bsJzZvX63kiIiLD9W+v7OCFlvb+TxyE5WVRvrR4dp/ntLe3U1tbSywWY/fu3Tz88MO9nvvqq68yd+5cJmW24h6qlStXMm3aNBYsWMD69es588wzOe2003o9f/Xq1WzevJkzzjhjWM8dDFVQiIiIjDOJ7dsBCM2bi1uR/mIlXwWF19BAoLr3n8gMl8m0dnRvLenOKSkB0gGF9X1SjY0Eaib3en5o9iwAEm/uKNBKRUREDi/ZFo/Nmzdz//33c8455+SGSQ9Hb9WJxhhc1+X+++/nnnvu4cgjj+Tyyy/nmmuu6fVehVjPYKmCQkREZJxJbMsEFHPnkvA8gNyuF15TE6+deiqzbvx/pBobcUejxSPcT4tHNBNQtLWng5RUikBN7+sKzk7/1Cm5QwGFiIiMrP4qHUbD2972Ng4cOMD+/fuZOnVqj/ePOOIItm/fTnNzM+Xl5V3e+/nPf861114LwG233UZNTQ2NjY1dzmloaGDy5PQPBowxrF27lrVr1/Le976X888/v9eQYuPGjaxfv74An+HAqYJCRERknEm8uR23ogK3ogIn84WKl6mgiL/2Gt7+A7Q+/ji2vR23jyBguMwAWzyyMyj8tlZSDQ0AuNU1vZ4fmDoVEwyS3PFmgVbav8T27byy7gTir78+as8UEREB2Lx5M57nUVOT/9/GkpISPv7xj/PpT3+aRGY+0+7du7nzzjv527/9W+rq6qirq2PNmjW85S1v4U9/+hN79uwBYMOGDcTjcebMmcOuXbt49tlnc/etq6tjXp5WSmstN998M7t37+aUU04Zgc+4d6qgEBERGWeS27YTzHxBkd0hw2bmOyQzW4K1Z6aAB0ZwBkU2oBhoi4dtb8fLBBR9VVAY1yU4cyaJHaO3vVn7c38ltWcPzQ89RHjhwlF7roiIFKfsDApIBwJ33HEHruv2ev6///u/8//9f/8fy5YtIxKJUFpaynXXXdfjvGnTpvGNb3yD97///fi+T1lZGXfddReO45BMJrnyyivZtWsXkUiEKVOm8D//8z+5az/3uc/xpS99iba2No477jgeeeSRUd3BAxRQiIiIjDuJ7duJZr6o6RhAGQMguXMXAO0vvAAwwi0e6W1G+2/x6BiSmarPVFD08lOirODs2blhoKMhW63R9tTTcOGFo/ZcEREpTl6mRbM3t99+e5ePQ6EQX/3qV/nqV7/a773POOOMvIMt582b1+swzu7PGytq8RARERlHbCJBctcuQnPnAF2/+QdI7koHFNmKipEdkjnAXTxKOmZQeA31mXX1HZwE58we1RkU2YGcbc8+i00mR+25IiIi0kEBhYiIyDgSf+MN8H2Cc+cCYMJhMAYb69rikTUa24w6kQFWULS1dVRQ9LHfO0Bozly8piZS+/cXYKX9S775JjgOtq2N2IsvjsozRUREpCsFFCIiIuNIw/e+jwmHKX3724H0NG4TjXa0eOzaBcFg7vyRDChMZvZEdrvRPs9zHPz2NryGetzKSkyg7y7T0ne+E4Dmhx4qzGL7kdixg9J3vAOA1qeeHpVnioiISFcKKERERMaJ+Ouv0/TrX1N19tkEO21D5kQi+O1tWGtJ7tpFycqVQLoFwyktHbH1DLjFwxicaBSbmUHR3/wJgPCRiwnNn8+h3/2uIGvti00kSO3ZQ/SYYwhMnUpi+7YRf6aIiIwta+1YL2HCG8rvsQIKERGRcaLpF78Ex6HmHz/e5Xj6m/8YXn09Nh6n5LjjgHT1hDFmxNbjlJWlnzNpUr/nmpJoegZFff2AdhYxxlB+8sm0Pf0XUg0NtP75z7x+2un48fiw191dctcusJbgnNmYaAQbK/wzRETk8BGJRKivr1dIMYKstdTX1xPppw20O+3iISIiMk4kd+0iOH06gW4VCCYawW9vzw3IjCxbhlNejjuCAzIBStasYc53vkNk+fJ+z3VKStIzKBoaCC9ePKD7Tzr5JOq//W1aHvsD8ZdfJv7KK3gHDuDMmjXcpXeRHZAZmjMHJxzBj8cKen8RETm8zJ49mx07drB/lOYcFatIJMLs2bMHdY0CChERkXEitXcvgenTehx3oiX4sY6AIjhrJuElRxIYwS1GAYzjUPaudw7oXCdagt+eqaA47q0DuiZ81FGYaJTYppdIbEu3XXitrQT7uW6wsluMBmfPwURUQSEiMtEFg0EWLFgw1suQPBRQiIiIjBPJvXuJ5qlWcCIRbHuM5M5MQDFzJrO/8Q1wDp9OTicaxW9uxmtqwq3ufwYFpAOQ8JGLiW95Obc7iW1rK/jaEtvfxIRCBKZMTs/zyOyIIiIiIqPr8PnKRURERHplrU1XUEzrWUGRbfHwmpogEMApKyNQU0Ogn608R5MTjeZChkDNwCs7IkcuIfbSS7lr/REIKGIvvkh48WKM42AiYVVQiIiIjBEFFCIiIuOA39SEjccJ9tHi4bc045aVjehgzKFySktI7tkDgDt58oCvCy9Zgt/cDJlBZl5ra0HXZZNJ2p9/nujq1el1hiNYzaAQEREZEwooRERExoHk3r0AeSsonEgE29aO19yCU14+2ksbEBONgu/jlJRQ+ra3D/i6yJIju3xc6BaP2JaXse3tlKxelV5nJIKvCgoREZExoYBCRERkHEhlA4qpvbR4xGL4zc045WWjvbQBcaIlAEw67TTcstIBXxc+smtAUegKivaNGwGIrkoHFE4krBkUIiIiY0QBhYiIyDiQraDovcUjhtfSjFt2eFZQOCXpgKLqox8Z1HVuRQWB6dMJTJ0KFL6Con3jRgIzZhCcPh0AE4lqBoWIiMgY0S4eIiIi40Bqz14whsCUKT3ec6IRbHs7/qFmgnPmjMHq+lfxgQ8QnDGdyFFHDfrayg9+EFyHA9+8pWBDMv14nPpv30rLY49Revy7csedSBgb0wwKERGRsaCAQkREZBxI7duLW1ODCQZ7vGeiUbCWVH09kaVLx2B1/YssObLHPImBmnLZpQA03PZd/AK1eLQ9/TQH/uu/KFm7limXXZY7bsIRbDKJ9TyM6xbkWSIiIjIwavEQEREZB5J79hLMMyATwIlEAfAaGg7bIZmF4JSWFqyCwms6BMD0L36B8MKFHc+IhAGwcbV5iIiIjDYFFCIiIuNAau/evDt4QLrFAwBrD9shmYXglJQUrILCb2lJ37Os6++XCad/L321eYiIiIw6BRQiIjKuNT/8MPu+/vWxXsaI8w4exK2qzPueiUZzrw/XIZmF4JSW4rcWaAZFSzMAbveAIltBoYBCRERk1CmgEBGRca35dw9Qf+t38FoKu/3k4cZvb8cpzb89p9MpoJjwFRSFavFoaQHHwWR2F8k9I9Mu42snDxERkVGngEJERMY1Px4H3yf21+fGeikjxlqL39aGEy3J+37ngMKd6DMoCtbi0YpTVoYxpsvxXAVFXBUUIiIio00BhYiIjGu2vR2Atmc3jvFKRo5NJMDzcEryBxQmEsm9diZ0i0fhKij85macsp4VKU5EMyhERETGigIKEREZ1/zMbgvtzz47xisZOdlvyjtXSnTWtYJi4rZ4mEK2eLS25J3XYcKaQSEiIjJWFFCIiMi4lq2gaH/uOaznjfFqRobNBhSl/bd4TORtRt1Ctng0t/TYwQNUQSEiIjKWFFCIiMi45sfj4Dj4ra3EX311rJczIvxMCNN7i0engGICt3hkKyistcO+l9/SknegaLZdxsY1JFNERGS0KaAQEZFxzcZiBGfOBCC5e/cYr2ZkZNsaTG8tHiXF0eLhlpaCtbmqmeHwW1pwS1VBISIicjhRQCEiIuOaH4sRnDEDAK/x4NguZoTkZlD0UkGR/aYa1+01xJgIsluCFmIOhdfSkrcdxoQzFRTaZlRERGTUBcZ6ASIiIsORrqDIBhSNY7yakeG3ZVo8etlm1ASDEAjglpb22DZzInEKGFD4LS297OKRHpLpx4ZfpSEiIiKDowoKEREZ1/xYDLdmMgSDeI0NY72cEeH3MyQT0oMyJ/KATACnNB0oDHdQpk0ksPE4br4KiogqKERERMaKAgoRERm3rLXYWAwnEiFQWUlqwlZQpL8h763FA9JtHhM+oBhCBUXzww+T3Lu3yzEvE3A4eWZQmFAIjMGPawaFiIjIaFNAISIi45ZNJID0T73dqqoJO4MiOxTS6WO+hIlGcfNsmzmRuIOsoLDJJDsuvYwD//3fXY77zc0A+XfxMAYTiaiCQkREZAwooBARkXEr9417JJwJKCZqBUWmxaOPgCIwdUpuFsdENdghmamGRvB92p95tstxv6UFoNdAxwmHsaqgEBERGXUakikiIuOWH0//lNtEIrjVVcQ3bxnjFY0Mv60dgsF0+0EvZt98c3pY5gTWUUExsIDCqz8AQPyVV/AOHsStrEwfzwQUTln+lhgTieC3K6AQEREZbaqgEBGRcaujgiJCYIJXUPQ1fwIgUF2dd+jjRJKroBhgi0eqvj73um3jxtxrPxdQqIJCRETkcKKAQkRExq0uFRSVVXhNTVjPG+NVFd5AAopikNvFY6AtHp0CivZnnsm9zrV45JlBAZkKCs2gEBERGXVq8RARkXHLxtI/5XYyQzKxFq+piUB19RivrLD89vY+508UCycUgmBwwBUUXiagCC9eTFtmDsWe664juXNX+n69VVBEIrk/WyIiIjJ6VEEhIiLjVnZOgAlnAgqYkG0eflurKigynJKSQVRQNGDCYaKrVpHYtg2bSND447toeeyx9L16aYkxkUiuOifLWkvLH/6ATaWG9wmIiIhIrxRQiIjIuJWdE+BEI7hVlcDEDChsmyoospzSgQcUXv0BAjU1BKZOxWtoILl7d+49EwymKzLyMJFwbr5JVnzLFt686BM0/eIXQ167iIiI9E0BhYiIjFudKyiybR2pCRhQaAZFB6ekpM8WD6+lBWstkK6gcGtqCEydAkBs06aO+/TS3gHghHtWUKT27weg+eFHhrx2ERER6ZsCChERGbe6VlBM5BaPNpxSBRSQHpTZWwWF9TxeW38iB/77v4H0kMxsBQVA7IUXAKg+/3wqP3hmr88wkXCPGRTZP1etTzyBr/kUIiIiI0IBhYiIjFvZnRZMOIJbWQmA13hw7BY0Qvz2doxaPIC+KyhsPI7X1ETDHT/Ab23FO3AAt6aaYCagaH/hRQBq/vHjTL3yyt6fEYn2qKDIBhQ2FqP1z38uxKciIiIi3SigEBGRccvG0nMCnEgYJxLBlJSQ3LFjjFdVeOkWj9KxXsZhwSnpo4IikQDAb2ri4M9+RqqxkUDN5I4KihdfhEAgV23T6zOi0R7PSDU2guvilJTQ8oc/FOAzERERke4UUIiIyLiVq6DIVBdMeu+JHPz5z4lt2TKWyyooa622Ge2kryGZNpnMvT5w63cglSJQU41bXQ2ui9/cTGDyZIzT95c/bk0Ntq2ty3O8xoO4VVWEFy8msXVrQT4XERER6UoBhYiIjFt+rB2MwQSDAEy96ircigr2XHPtGK+scGwyCamUhmRm9NnikamgKDvhBLwDBwBwa9KBRGDyZIBcNUVfsuemMveAdItHoKqSwLRppPbuG9bnICIiIvkpoBARkXHLxuKYaBRjDACBqiqqzjqL9rq6CTPIMPvNuAKKtD6HZGYqKMpPPonQvHkABGrSu7tkg4nsjh59CUxJn9M9oHArsgHF3qF/AiIiItIrBRQiIjJu2XgMJxzuciy0cCFYS2Lb9jFaVWHZ9sycjRK1eEA6qLGxGDaV6vGen6mgcCIRai78RwCCs2cDHQFFcCAVFFMyFRT79ueOeQcbcauqCE6bmh7A2dL7VqciIiIyNAooRERk3PLbY5hIpMux0IL5ABNmTkC2WkAVFGlOaXpYqJ8JbjqziXQFhQkGqfjgB1n0+wcJzZkDdIQO2eqIvuSroEhlZlAEpk1Lf7xPVRQiIiKFpoBCRETGLRuP4XQPKObNByDxxhtjsKLCy34jrm1G07JBTb42D5tMV1CYUAhjDKFM9QR0bvHov4LCraoC1yW1P11BYa1Nt3hUVRGYmgko1OYhIiJScP0GFMaY7xlj9hljXuh0rNoY86Ax5pXMr1Wd3rvaGPOqMWaLMebkTsePNcY8n3nvZpNpGDbGhI0xP80cf8oYM7/TNedmnvGKMebcgn3WIiIyIfixeI8KCreslMDUqRMmoLCZWRrdg5hild1uNd+gzI4KilCP94KDCCiM4xCoqSF1IB1Q+IcOgefhVlUSnJa+PqmAQkREpOAGUkFxO3BKt2NXAQ9ZaxcDD2U+xhizDPgIcHTmmv8yxriZa/4buAhYnPkve8+PA43W2iOArwH/mblXNfBF4K3AWuCLnYMQERERG2vP+417aMEC4lsnRkCR20o1rIAC0tuMAvitbXgtLbz6nvW0PPYY0LGLhwkFe1wXWb4ct7KS8OLFA3pOYPLkXAWF19iYPta5xUM7eYiIiBRcvwGFtfYPQEO3w2cAd2Re3wF8oNPxn1hr49baN4BXgbXGmBnAJGvtn621FvhBt2uy97oHWJ+prjgZeNBa22CtbQQepGdQIiIiRSxdQRHucTy0YD6JN7aS/idnfLOJbEDRsyqgGOUqKNraOPi/95DctYuD9/wM6NjFI18FReSoozjyyT8TnD59QM8JTJlC6sABmn//e1r+9Ccg3frhRKM4kyapxUNERGQEBIZ43TRr7W4Aa+1uY0y2XnIW8GSn83ZkjiUzr7sfz17zZuZeKWNME1DT+Xiea0RERPBj7QQnTepxPDR/Pv6hQ3iNjQSqq8dgZYVj4+mAovtuJcUqNySzpZnGn9wFZHZuoe8KisFyp0ymva6OnZ+9Eut56WNV6ULO4LSpJDUkU0REpOAKPSTT5Dlm+zg+1Gu6PtSYi4wxG4wxG/bv35/vFBERmYBsLI6J9mx9CC9YAEyMQZm5Fg/NoAA6hmQ2P/h7kpmtZLNzOvqqoBiswJQpeE1N6YAos6VpNqAITJ2mFg8REZERMNSAYm+mbYPMr9l/pXcAczqdNxvYlTk+O8/xLtcYYwJABemWkt7u1YO19lZr7Rpr7ZopA9g+TEREJgYbi+Hkmc0QnDMXgOSOHT3eGympxsbcT9oLKdfiEVKLB3RUULT+6U9gDKakBD+eCSgSHbt4DFdgcnpbUqe8HJMJRdzKTEAxfZpaPEREREbAUAOKXwHZXTXOBX7Z6fhHMjtzLCA9DPPpTDtIszHmuMx8iXO6XZO914eAhzNzKn4HnGSMqcoMxzwpc0xERAQAPxbLO4MiOHMGAMldeXPtwq+jtZXXTnwvB//3noLfO9fioQoKoGNIZmr/foJz5uBWVmAzVSa5bUaDw2/xCGR+4FH27ndT+YEzcCsqcs8OTp9B6sCBvDuJiIiIyND1O4PCGHMXsA6YbIzZQXpnja8AdxtjPg5sBz4MYK190RhzN/ASkAIusdZmf5z0SdI7gkSB+zL/AXwX+KEx5lXSlRMfydyrwRjzJeAvmfOus9Z2H9YpIiJFzI/FcCLRHsedSAR3ymQSO3eOyjpiW17Gb20l/uqrBb93xy4emkEB4EQ7/vcOL1xIYtu2ThUUmRaPAsygCM1OF36Wn/Reyt79bmo+/nEyO6RTsuZY8H1a//IXytetG/azREREJK3fgMJa+9Fe3lrfy/nXA9fnOb4BWJ7neIxMwJHnve8B3+tvjSIiUnxsIoFta8Ot6DkkEyA0cxbJ0QooNm8CILlnd8Hvna2gUItHmnFdTDSKbW8nfMQiknv39qigcArwexVZtowF//czwkuXYozBmdUxpzu6ejUmHKb1T08ooBARESmgQg/JFBERGRWpgweBjsGF3QVnzSK5c3RaPOKbNqfXtKfwcwn8eAwTDud+ei8dgzJDCxfhhMPY7jMoCtDiAemQIt/vuxMOU/KWt6TnYIiIiEjBKKAQEZFxycsGFJWVed8PzppJcvfuERlc2V1sczqgSO7dU/B723hC7R3dZAdlho9YhIlEcm0w2V08KFBA0ZfSd7yDxOuvk9xd+KoZERGRYqWAQkRExqX+A4pZkEySGuHtp20qRfzll8F18Q7U536KX7D7x+OYsNo7OuuooFiYrqCIdVRQmFBoVKpNSta+BYD2554b8WeJiIgUCwUUIiIyLnmNB4F+AgoY8TkUiW3bsPE4JcceC9aS3FfYQMSP599KtZg5paUEpk/HLSvLVFBkAopksmDtHf0JVFcD4B06NCrPExERKQYKKEREZFwaUAUFIx9QZNs7yt79bgBSBR6UqRaPnkrf8XYqTv0bAJxIRwWFn6mgGA3ZNhO/tW1UniciIlIM+t3FQ0QEwEv5/P77L/GWUxdQPaN0rJcj0n9AMXMmMPIBRXYwZsmaY9PPK/CgTBuP4yig6GLKpz6Ve23CEfzMTic2kRi1Copsm4nf2joqzxMRESkGqqAQkQFpaYzz6jP72LmlcayXIgKkAwoTieBE8rc/OJEIbnU1yV09KxpS9fW8/K53Edu0adjrSDXUY0IhQosWpT8ucAVFdhcPyc90qqCwyeSoVVCYQCDdXtKmCgoREZFCUUAhIgPiez4AiVhqjFcikuYdPNhr9USWW1GB19zc43hy1y68/QeIv/ra8NdxoB53cg1uWRlOWdkIVFCoxaMvTpcKitELKCDd5qEKChERkcJRQCEiA+KlMgFF+8hv2SgyEAMJKJzycvw8AYXNfEPrx9qHvY5UQwOB6hoAgjOmkyz0DIpYTC0efTDRCKRS2FRqVFs8QAGFiIhIoSmgEJEB8VIWUAWFHD68xkbcqso+z3HLyvBa8gQUma1AbXts2OtI1R8gUJMOKAIzZpDcUdiZF34irgqKPmR3OPFj8VFt8YD0HAoFFCIiIoWjgEJEBiRXQaGAQg4TA6+gaOlx3M9VUAw/oPDqG3AzAUV0xTHEX345b1vJUNl4AhNRQNGb7O+NjcfSFRRq8RARERm3FFCIyID4avGQw8zAAoqyXlo8MhUUw2zxsNamWzwyAUXJ2rXg+7Q988yw7tvlGWrx6FN2SKqNxdIVFKPa4lGiIZkiIiIFpIBCRAYk2+KRVAWFHAas7+MdOtT/kMyycryWnhUUNpGpoBhmi4d/6BAkk7g11QBEVx6DCQZpe/ovw7pvl2ckEpiQAoremGyLRzyeqaDQDAoREZHxSgGFiAxIR4uHKihk7PmHDoHvExhABYVtb8cmk12vL9CQzFR9PQCBmsnp50UiRFeupO3pp4d1385sPK4Wjz442RaPmFo8RERExjsFFCIyIB27eKiCQsaed/AgQP8VFOXl6fO7VVEUakimlwsoqnPHStauJfbSSwWZQ2GtVYtHP0z3IZmj2OLhKqAQEREpKAUUIjIgvqddPOTwkWpsBPoPKJyydEDhdw8oMjMohjskM1tB4WYqKADCRx4Jvk9y165h3RvIVX6oxaN3HRUU7dhEAmcUKyhMSXoGhbV21J4pIiIykSmgEJEBUYuHHE78Q4cAcCsq+jzPKS9Ln9+tmiE7g8K2D7PF40DPCgq3YhIAXlPTsO4N6bYFQC0efTCRThUUiQSMcgUF1mI1KFNERKQgFFCIyIBkd/Hwkn4urBAZK34sHTCYaLTP83ItHt22Gs3NoBhmQOE11IMxuFVVuWPOpHRAkW/3kL4c/MUviG3a1OWYzaxTLR69M+FO24wmk6NaQeGUlgJoJw8REZECUUAhIgOS3cUDIKkqChlj2QqI/gYidrR4dK+gKFCLx4F63KoqjOvmjrmTshUUhwZ1r73/fj0Nt9/R5ZifaUXJzlmQnpxuFRQmOAYBheZQiIiIFERgrBcgIoe3B777IiWTQpRM6viiPxFLESkbvTJqke6yAUN/Py13My0e3QdWZmdQDLvFo6GeQE1N12dmA4pDA2/xsNbit7aS2Lmj2zozLR7h0fume7zJtnhkKyhGe5tRAE8BhYiISEEooBCRPjXsaqW9OUG4pDJ3TIMyZaxlWzRMP60PTqbFw2/uPiQzu83o8Coo/OaW3DO6PNMY/EMDb/GwbW1gLckdO/OuUy0evctVULRnAgpVUIiIiIxbavEQkT75no+X9HO7eAAk2tXiIWMrW0HRX4uHW5YZktmjxSMbUAyvgsLG47ldJLKM4+CUl+MdGniLR/Yn8Km9e/Ezn1t6fdkgRi0evckNyczs1NLfn4lCUkAhIiJSWAooRKRPXsonlUyHFFmJdlVQyNiyudkMfVcWmFAIEw7nGZKZbfEYZgVFIp53C1C3vHxQLR65b3CtJdVpe9LcrA21ePTKBINgDF7zoY6PR4lTUgJoSKaIiEihKKAQkT75niWV8PC8TgGFWjxkjOUqKAbwzahTXp5nm9HCDMm08UTekMSpmDSoFg+/teMb3PYXX2TX568i1dCgFo8BMMZgIpFcG48qKERERMYvzaAQkT55KR/HNV128UhoFw8ZYzYRxwSDGKf/nN0tK8Pr3uKR+cafVCozt2BoP3W38Xje6gZ3UkWXFg+bSmECvf+T2/kb3Ppbv0N8yxaitStxq9MDOLNtDJKfEw53VFCMSUChCgoREZFCUAWFiPQpXUHh46d8wiXpb7DU4iFjzSYSA/5G1Jk0qdchmTC8Kgobj+etbujc4tH2zDNsOXYNia1be71P54AivmULAK1/fnLA26kWOxOJ5CpWxqTFQxUUIiIiBaGAQkT65Hk2PYPCSwcUxqjFQ8aeH4/3O38iyy0rw2tq4tCDD2KTyfT1nQdRDmOrUT+RyDvA0qmYhN+U/ol+e91z2HicQ797oPf7ZL/BzVZZGEPbU0/l1uaogqJP6QqKTEAximGOcV1MNKqAQkREpEAUUIhIn/yUTyrp4SUtbsAhFA2oxUPGnE0kB15BUV5O7Pnn2XnZp2n54+Pp6ztVUNjhVFDEYr23eGS+YU68uR2Alocf7vU+2W9wwwsWAFBxxhl4TU20//WvQP/DQItduoJi9IdkQrrNQ0MyRURECkMBhYj0ylqL71n8lMVLejgBh2DEJakWDxljvc1+yMcpL8u9Tu3dk74+kQDXBcAf4k4e1treWzwmlWNjMfxEguT2dEDR/te/ktq/P++9sgFF5JgVOBUVTL70UgBaHn0MIO9OIdLBRMJ4uW1GRzugKFEFhYiISIEooBCRXvle18GYbsAhFFEFhYw9m0jgDPCb9tCsWbgVFeA4JPftS18fj6ePAbZ9aD/9zraL5AsPnEmTAPCbmkhs20548WKwluZHH817L781/c31tH/+Zxb8792EZs8ivGwp3oED6ftFFFD0xQl3qqAY5XkdbkUlXkPDqD5TRERkolJAISK98lIdW4vG21O4AUMo4moGhYw5PxEf8DeiNRddxKLfP4hbU52rYPATiVxAMdQhmdk2kXztF+6k9L1TDQ0kd++m/L0nYkpKSLz6Wt57+a2tOCUluBUVhObOBWDKpZfl3u9rBxDJDKu06UB1tFs8QrNnk3jzzVF9poiIyESlgEJEetWlgqI9hRtwCIRcUglVUMjYsonEgOcyGNfFLS8nMGVKLqDoXEEx1CGZHQFFvhkU5QDEXtoEvk9o3jzcygq8gwfz3strbc1tWZlVdsK6Ia2rGJWsXZt77YxyBUVw7hySu3blKmpERERk6BRQiEivugcUjpsOKJIJv4+rREaejQ98m9Gs4JSpHQFFpwqKoQ7JzAYU+WdQpFs8Ys8/n3723Lm4lZW9BhR+noDCGMMRjz3K3Nu/P6T1FZNJ7zsl93q0WzxCc+aC55HcvXtUnysiIjIRKaAQkV51bvFIZFo8giFHFRQy5tIVFIP7RjQwdQqpffs7hltWZOZEDHFIph9Pb1WafwZFOvxof/EFAEJz5xIYZEABEJw2jdLjjhvS+opJcMaM3OtRb/GYOweAxLbto/pcERGRiUgBhYj0yvc6AgprwQ1mWzxUQSFjy8bjgy7lD0yZgldfj820dLgVlQD4sSG2eCT6aPHIhB/xTZtxSktxq6v7qaBoyxtQyMBVfexjAKP++xicOw/o2E5WREREhk4BhYj0ykvZLh+7rkMgrBkUMvbSQzIHt7NFYOpUsDZXit+xi8cItHiUl0MwiE0kiK5ejTFm0C0eMjjT/uVqFv7mXoIzZ47qcwNTp2AiEZLbex+U6be20vrkk6O4KhERkfFJY8FFpFedKyiAXItHUgGFjDGbSA561kBgyhQAkjt2AHTaxWNoFRR+bkhmpMd7JhRi3g/uwARDRJYtTT+vshLv0CGs52Fct+u9FFAMmzGG8KJFY/Lc0Jy+d/Jo+vWv2XPNtSz+4x9yfw5FRESkJ1VQiEivuldQOJldPPyU7RFeiIwmG48PfgZF5hvDRCagcEqimFBo2EMye1tHyapVRJcfjXHS/9S6lZVgLd6hQ+l1bN+O39oKKKAY74Jz5pLcvq3X973GRgCSO3eO1pJERETGJQUUItKrzrt4AOltRoPpn/ymkgooZOzYxOB38QhMnQpAckf6m0QTCmGi0SEPyeyrxSMft7ISINfmsfWsj3Dgf74NKKAY70Jz5pB4cwfWz//3otfSAkByz57RXJaIiMi4o4BCRHrlp/K0eITTf20k42rzkLFj4/EBBwNZgZoaMCbX4mFCYZxIpAAtHoMPKPy2NrzGRuIvv4xNpdKfT2nJkNYhYy8wdSo2FsNvy/9nyW/OBBS7FVCIiIj0RQGFiPTK69bGkW3xALSTh4wZay02mcQEB1dBYYJB3KoqEjszAUU4hBOJYHv5prLfdWS3GR1CQJFqaAAgsW1brs1DFRTjl1MSBcBva837vp+poEjt2T1qaxIRERmPFFCISK/8fLt45AIKVVDI2LCJwQUDnQVnzCCxNT0rwAmHMZEIfma70MGvI1NBMcBWk46AogkvG1Ds3InX3JxejwKKccspSVe/ZLew7c5rVQWFiIjIQCigEJFeda+gcAMOgVD6rw1VUMhYyQUUg5xBARCcMwfb1pa+PhzGhMO5SohBr2MYMyiyFRQkk8RfeSX9vgKKcctkAgo/82eru1yLh2ZQiIiI9EnbjIpIr7pXUDgBQ1AVFDLG+ts9oy+hOXNyr00whDOMXTz8QbZ4OOXl4Lp4Bw/iNTTmjsdeein9vgKKccvpL6DItnjsTrd42GSS1qefxjt4kLJ3vxu3rGx0FioiInKYUwWFiPSq+1aibqcZFEkFFDJGshUUgx2SCRCcMzv32oRDmHB46C0e8cG1eBhjcCsq0gFFY0PueNtTTwPglE8a0jpk7DnRAQYUBw5gEwka7vwRb378H9n12Ss5ePf/jto6RUREDncKKESkV16PbUaNWjxkzPmDDAY6C82dm3udnUHRvcXDplIkMjt99MUm4phgEOMM/J9St7Iy3eJR35BuMSkpoe3ppwlMmUJ0xfKBfyJyWMnuwNLbLh5eSwsmGgVrSe7bx8G77yZyzDGYSITUvn2juVQREZHDmgIKEelVdptRN+DkftWQTBlrNpEE0tuEDlZwdqcWj3AYJxzKVUJkHfifb/P6aafjJ/qeTeHH45hIZFDPzwYUXkMDbnV1LjCp/PCHMcHgoO4lh4++WjystfgtLYQXLQLg0G9+S+KNN6g66yzc6iq8xsYe14iIiBQrBRQi0isvM4MiFE2HEo7beUimAgoZGx27Zwz+G/rg9GkQSI9fMuEwJhTGj3fMoLC+T9PPf45tb8c7eLDvdcTig95JJFdB0dhAoKqK0Lx54LpU/t2HB/25yOGjI6Douc2obW8H3ye8eDEA9d/5Dk5pKZPedwqByipSndp9REREip2GZIpIr7K7eISiAdqbk7hBh2A4M4MirhYPGRvDmUFhAgGCs2aS3LYdEwz12MWjfeNGkjt3AuA3N8PUqb2vIx7HGWSbSXDGDNqefBITCOBWV1Pzj/9I+XtOIDh9+qA/Fzl8ONEokH+bUS8zfyKy9Cjan1uIE4lQff55OCUluNXVXQamioiIFDsFFCLSq+wuHuFo+q8K1zUEgpkKiqQqKGRsDHY4ZXeh2XNIbtuOEw7hRMJdWjyafvXr3Gvv0KE+7+MnBl9BETn6aBp/9CNiW7Yw6f3vI7piuWZPTAAmEgFj8rZ4ZAdkutU1LPrtb7q851ZXkXj99VFZo4iIyHigFg8R6VV2F49gJF014QYcHNfBCRi1eMiYyc6GGGw4kBWcMxscBwIBTKhrQNFeV4dbVZV+TnNzn/ex8cSg15ALI1IpAlXVg1u4HLaM4+BEo/itvQcUTlnPbWQDVdWk+mklEhERKSaqoBCRXnmexXFNbjCmkxmWGQy5JLWLh4yRbEvGUCsoqs46i9DceRhj0i0eySTW9zGOg43HCUyfjtfYiHeov4AijgkPbg2hhQsx0Si2vR23pmZI65fDkykt6buCory8x3tudTW2rQ0/FsMZ5MBVERGRiUgVFCLSKz/l4wQcArldPAwAgZCrCgoZVcm9+9j1+c/jt7fnZlAMNaCILF1KzQXnp++RCRiyVRQ2kSCQCQ68Q0193ic9g2JwFRTGdYksWwZAoLpqUNfK4c2JluDnm0HRnK2gKOvxnltVmT6nQYMyRUREQAGFiPTB8yyua3BDHduMAgRCDqm4AgoZPW0b/kLTL39FbNPm3C4egx1QmU920GY2oPCTHQGF308FhZ8YfIsHQHR5us3DrVaLx0TilPRdQeGU9gwoApk/AykNyhQREQEUUIhIH/yUn27xCHbMoIB0BYVaPGQ02Vg6QPAa6jsqKIY4g6IzE06X1fuZthGbSOKUlWEiEbzmvodkpls8Br+GyDErAAhMmTLoa+XwlQ0ovKam3M4dAH5rtsUjTwVFJqDwGhVQiIiIgGZQiEgfPM/iBpzczh1OpsUjGHLU4iGjyo+lS+dTB+rxh7mLR2e5Fo9ER4uHCYVwy8v7raCw8TjOIGdQAEw6+WSccJjIcu3eMZE4JSV4hw6x49P/BI5h3ve/D4CXGbbqlPYckpkdyOo1qsVDREQEVEEhIn3wvUwFRY8WD5eUKihkFGUrKFIN9dhEEihMBUWuxSMWS/+aCSicSZMGuM3o4AcbmkCA8hNPxBgz+AXLYcuJRrHtbSRef522Pz9JYutWAPyWVkw0ign0/JlQrsXjQD2xLS+P5nJFREQOSwooRKRXfipdQeHmafFIJVVBIaMnW0HhHajPzYswweCw75sNOfx4Aut54HmYUDBdQdFfi0ds8Lt4yMSVrqBoJlVfD8DB//s5kJ5BkW+LUQCnvBxcl/rvfY83zjiDxI6do7ZeERGRw5ECChHplZfycVyHcEkAxzG4wew2ow5JDcmUUdRRQdGQrnIIBjHO8P8JywYUNhHvsjuIM6l8QNuMOgWo4pCJwSktIbV3L/g+BAI0/fznWM/Da2nGLeu5xSiAcRzcqiq8AwcASL65fTSXLCIicthRQCEivfI9ixswLH37DD5wxSqCoXQlhVo8ZLT5mRYM78ABbGJowynz6byLRzagcEIh3EkV/Q7J9BMJzCC3GZWJyykpyb0ue9e7SO3fT2rPHvyW1rxbjGYFqjq2m03u2Tuia5SBs4lE3m1jRURkZCmgEJFeeZldPEKRADOOqMwdTwcUqqCQ0ZOdEZFqaMgEA4Vpreho8ehaQeFO6ntIpvU8SCYLFpTI+Gei0dzrkjVrAEi8uQOvsRF30qRer3OrqzGR9CyT1N49I7tIGbA9X/4y2887f6yXISJSdBRQiEivfM/iuD3/mgiGHVVQyKjy45mAor4eG08ULBjIVkDYWLcWj/L0kExrbd7rOrY61QwKSXNKOuZMlKw5FoDkjjdJbN1KaN68Xq+rPvccpv/bv+FWVpLcrYDicBF74UXaX3opHUaKiMioUUAhIr3yPR830HOngUDIxUv5+H7+b95ECs22pwMKv6mJ5K5duBUVBbmvE+mYQeF3q6DA87BtbXmvy5Z+O0PYxUMmplyLRzBIZNkycF3a6urwW1oILVjQ63Xl73kPlR88k8CMGaT2KKA4XCS3b4dkkuTu3WO9FBGRojKsgMIYc7kx5kVjzAvGmLuMMRFjTLUx5kFjzCuZX6s6nX+1MeZVY8wWY8zJnY4fa4x5PvPezSaz95oxJmyM+Wnm+FPGmPnDWa+IDI6XsjiBnn9NBDK7eqjNQ0ZLtoICoG3DBqIrVhTkvl1bPDLblwbT24wCeM352zxS+9NDDQNTJhdkHTL+ZQOK4JQpmGCQ4MyZtP7xcYA+A4qs4LRpJBVQHBa8Q4fwmpoASGzdNsarEREpLkMOKIwxs4BPA2ustcsBF/gIcBXwkLV2MfBQ5mOMMcsy7x8NnAL8lzHGzdzuv4GLgMWZ/07JHP840GitPQL4GvCfQ12viAye7/m4eVo8AqH0MbV5yGjJVlAAkEoRra0tyH1zu3jEE11nUJRnAopD+QdlpvbvByAwZUpB1iHjn1OaDigC06YBEJw9K72rBxCaP7/f6wMzpquCYoxZa/FaWklsfzN3LLFt69gtSESkCA23xSMARI0xAaAE2AWcAdyRef8O4AOZ12cAP7HWxq21bwCvAmuNMTOASdbaP9t0s+8Pul2Tvdc9wPpsdYWIjLx0BUXP/8s5bvqY76nFQ0aHH4/jlHb0+EdX1Rbkvk5m2KaNx7DJbi0egN9bBcW+fQAEpk4tyDpk/HMyQzKzAUVo9hwgHYIFZ87o9/rgtOl4TU3aOWIMtT31NK+87W20Pv7H3LHENlVQiIiMpiEHFNbancCNwHZgN9BkrX0AmGat3Z05ZzeQ/eptFvBmp1vsyByblXnd/XiXa6y1KaAJqOm+FmPMRcaYDcaYDfszP9USkeHzPT8XRnSWHZzpe6qgkNFh29sJzkr/0+BUVAzoJ9IDkX8XjyBOtoKiSRUUMjC5Fo9p6S97gnPSAUVo3jyM0/+XW4Hp6WBDbR5jJ/HmdmwySeOPfgxAcO5cBRQiIqNsOC0eVaQrHBYAM4FSY8w/9HVJnmO2j+N9XdP1gLW3WmvXWGvXTNEXiyIF46Vs3hYPVVDIaPPj8VxAET3mmAF9wzcQJhCAQKBLi4cTCuFWZAKKgwfzXpfatw+nvDz3U3ORbEARmJqtoEj/eR3I/AmA4PR0lUW2LURGn9/aCqQDSHfyZCJLl5Lctn2MVyUiUlyG8xXeicAb1tr91tok8H/A24G9mbYNMr/uy5y/A5jT6frZpFtCdmRedz/e5ZpMG0kF0DCMNYvIIPien3dIpps55qV6VlC0NMY4dEAlylJYtr0dt6aa8JIllJ94YkHv7YRC2HjXbUaDM2ZgwmHiL7+c95rU/v2qnpAuAtOnE5g2jWjtSqBTBcWC+QO6PpitoNBWo2PGb2nNvQ7NmUNo3jwSO3ZgU6kxXJWISHEZTkCxHTjOGFOSmQuxHtgE/Ao4N3POucAvM69/BXwkszPHAtLDMJ/OtIE0G2OOy9znnG7XZO/1IeBh29um9CJScL5ncfO2ePReQfHHn77C729/acTXJsXFj8dxIlEW/vIXVJ31dwW9twmHsYmuAYUJBokcdRTtLzyf95rU/v2aPyFduOXlLH7sUUqOPRaA8MKFhI88krJ3vGNA1wemTwdUQTGW/JaW3OvQ3DmE5s2FVIrkrl19XCUiIoUUGOqF1tqnjDH3AM8CKWAjcCtQBtxtjPk46RDjw5nzXzTG3A28lDn/Emttdo/CTwK3A1Hgvsx/AN8FfmiMeZV05cRHhrpeERk8L5W/giIbUHh5ZlC0tyRob06O+NqkuNj2dpxoZETubSIR/Fgcv1NAARBZsYKD//d/WM/DuG6Xa1L79hFdvXpE1iMTg1NaysJf/bL/E7PnRyKYkhK8xsYRXJX0xW9txa2ogGCQyIpjCM5KF/gmd+4kNHfuGK9ORKQ4DDmgALDWfhH4YrfDcdLVFPnOvx64Ps/xDcDyPMdjZAIOERl9fip/BUW2xcNP9aygSCV8kjGVw0rhWM/DJpOY8MgEFPlaPAAiy4/G3nkniTfeIHzEER3rsTZTQaEWDykst7Ki17knMvL81hbcqioW/PIXmFCI5Pb0/Am13YiIjJ7CTBkTkQnH+hbft3l38XAD2RaPnhUUqaRPIu71OC4yVDYeBxi5Copci0e68icbUESXp3Pz9udfwKZS1H/3uyT37sNvasImEppBIQXnVlaSOqgKirHitbbilJXhhMMYY3JtN8k9u8d4ZSIixWNYFRQiMnFl50vkb/HIDMnMM4MilfBIxj2staTHyogMjx+LAYxYBYUJh7ttM5oOKEILFmBKSmh/rg6vsZF9N9wIGMqOfxegLUal8AKVlaqgGEN+SzqgyHLCYdzqalKqoBARGTUKKEQkr+x8icFuM5pKeGAhGfcIRfRXjAyfzQQUI1VB4YTD2FjPgMK4LqVvfxsHf3p3ejtS0r3oyX3pzamCGpIpBeZWVpHYuXOsl1G0/JYWgrNndzkWnD6d5B4FFCIio0UtHiKSV0cFRV8zKPK0eCTSx5IxtXlIYYxGBUWXGRTBYO69WV/9KpUf+hDu5MkEZs4gsXMHqf37AVVQSOG5lZV4B5vGehlFy29txS0r7XIsMGMGKbV4iIiMGgUUIpKXlwkf3EHs4mGtTVdQAAkNypQCyVVQRMIjcn8TDuMnEthkAhMMdmlNckpKmPGl6zji4YeILFtGcudOEtu2gesSmDFjRNYjxcutrMQ/dAjrKeAdC35LC05p14AiOH26hmSKiIwiBRQikleugiLPkMzsDIruLR6+Z7GZQ0kNypQCyVVQRKIjcn8T7tjFI9ve0eMcYwjNmk1y5y7iL79CaN48nPDIBCZSvNzKSrAW79ChsV5KUfJaW3FKy7ocC86Yjt/SgtfSMkarEhEpLgooRCSvXAVFX7t4dNtmNFs9AZBQi4cUyEhXUDihdIuH30dAARCcNQvb3k77hg2EFy8ekbVIcXOrqgDwGrWTx2jzEwlIJrsMyQQITE9XSqU0h0JEZFQooBCRvLIBRZ+7eHSbQZGdPwGQVIuHFMiIV1BEIrldPPoMKGbPAsBralJAISPCrawE0E4eY8DPVEj0aPGYkdlqVG0eIiKjQgGFiOSVrY7oawZF9xaPpCooZASM/AyKbItHsp8Kio7p/gooZCQooBg7uYCirOcMCoCkBmWKiIwKBRQikldfQzKzx7oPyexSQaEZFFIgfiwOjFwFhdNpF4++A4qZudcKKGQkuFWVAHiNB8d0HcXIb20FwO3e4jF1KhhDShUUIiKjQgGFiOTVEVDkG5KZv4IilexcQaEWDykMP9YOjGQFRQSbSODH2vsMKNyyMtyKCkwoRGjunBFZixQ3VVCMnd5aPEwwiFNWhtfcPBbLEhEpOoGxXoCIHJ4Gss2o3+cMClVQSGHYEa6gcCsqAPD2H8CEgn2eG5wzB+t5mID++ZTCc0pLIRhUQDEGvFyLR1mP95xoFL+9bbSXJCJSlPQVlojk5WVnUAR7BhTGGBzX4HWvoEiogkIKb6QrKNzq9M4Jyb17CS9Y0Oe5066+akTWIALpv1vdygoFFGPAb00HEN0rKACckhJsmwIKEZHRoIBCRPLykr1XUEC6iqJHi4cqKGQE2FgcgsERq1oIZLd2rK/HLFnS57klxx47ImsQyQpUVuId1Dajo62jxaNnBYUpieK3tY/2kkREipJmUIhIXn5mAGa2naM7N+DkafHwcu9pFw8pFD/WjhMemeoJALe6Ove6rxkUIqPBrajUkMwx4LemAwq3LH8Fha8KChGRUaGAQkTy6msGBZC/xSNTdRGdFCQZV4uHFIaNxTGRyIjd381UUIACChl7blUlXlPTWC+j6PitrWAMpqSkx3tOtAS/XRUUIiKjQQGFiOTV1wwKAMd1clUWWdkKipLykFo8pGD8WDuOAgopEk6JvhkeC15LC05pKcbk2blKFRQiIqNGAYWI5NXfDAo3YPBT+YdkRieF1OIhBZOuoBi5Fg8nFMpN7ldAIWPNRKIKKMaA39Kad0AmaBcPEZHRpIBCRPLqv8WjZwVFMuHjuIZIiVo8pHD8eAxnhLYYzcpWUfS3zajISEt/M6yAYrT5zYfybjEKmV08WhVQiIiMBgUUIpJXNqBwAvmHZPa2zWgg6BCMuMTbU/z5F69Rv7NlxNcqE5ttj41oBQV0bDWqCgoZa05JFNvejrW2/5OlYGKbNhNetCjve06JQiMRkdGigEJE8vI9CwYcZxC7eCR9AiGXUMQl3pri2fu38cpf9o7GcmUCG40KikBlOqBwFFDIGDPRKFiLjcXGeilFI7V/P8kdO4jW1uZ935SUYBMJbEqVgSIiI00BhYjk5SV93ICTd2AYpCso/HwVFCGHYDiQO9Z6KDGi65SJb3QqKNJbjaqCQsZaNozzFVCMmra6OgCiq2rzvu9E0zt7qIpCRGTkKaAQkby8lN/r/AnItnh038UjXUERjLi5Y21N8RFboxSH0Z1BoYBCxpZTkv6zbrVrxKhp31iHCQaJHH103vedzNaj2slDRGTkKaAQkbzSAUX+6gnItnjkn0FRMin9TV5ZVZjWJlVQyPCMRgVFIDuDIqiAQsaWE81UUOin9aOmva6OyNFH99ripYBCRGT0KKAQkbwGVkHRPaBIV1AsXDWFv/uXtzD36BpVUMiw+fE4Tjgyos9QBYUcLowCilFlPY/YCy/0On8COqpaFFCIiIw8BRQikpeXsjh9BhQ9txlNz6BwcV2HKXPLKakI0d6S7NEKIjIYtr0dJzrSAYVmUMjhITfvoE0BxWjwDh3CJhIEZ83q9ZxsBYVVaCQiMuIUUIhIXn4/FRRuwOB1b/FI+gRDHdeUVoTBQrsGZcoQWd/HJhKYEa+gqAQUUMjYy4ZxNqZvhkeDd/AgAG5lRa/nZNtukrt3s/uL16iSQkRkBCmgEJG8+ptB0VsFhdsloEh/s6c5FDJU2a0WR7qCIjRvHs6kSYTmzRvR54j0Ry0eo8tvagLAreg9oDCZCorm3z/EwZ/+lPa/Pj8qaxMRKUaB/k8RkWLU3wwK1zU9hmQmMzMoskoq0oMNNYdChsqPp//sjHQFRaC6miVPPzWizxAZiI6BjAooRoM3gIAi+79JYuvWLteIiEjhqYJCRPLyUrbvIZmBdAXFK3/Zy5an9gDpCopgsCOgUAWFDNdoVVCIHC46dvFQG8FoyLV4DCSg2LYtfc0hBRQiIiNFFRQikpeX8glF3F7fz+7i8ddH3gQMS946HS/hE+jU4hGdFAKjCgoZOr89HVCMdAWFyOEiG1BoIOPoyFZDOH0FFNn/TTKBqa8KChGREaMKChHJq/8WDwc/5RNv9/A9H8/z8X3bJaBwXYdoWZBWDcmUIbJxVVBIcTGR9J/1bDgnI8s7mGnxmDSp13NMJAKmYyaTWjxEREaOAgoRyav/Fg+D71kS7Sm8lCWVSA/MdINdqy5KKsK0qcVDhkgVFFJsjONgIhENyRwlXlMTzqRJGLf3ikFjTK6KAjpCDRERKTwFFCKSl5fycfoKKDItHon2FL7n46fSAUUg2PWa0ooQLY36SaAMTa6CIhIe45WIjB4nGh2xGRStTzzBrn/5V6y1/Z9cBLympj7nT2SZ0pIu14iIyMhQQCEiefkpHzfYR4tHwMH6lmTcw0v5eJmAwnG7bk1aM7OMhl2tpJLeiK5XJqZcBUUk2s+ZIhOHE41iR2gXj/rvfZ+m//s/Uvv3j8j9x5uBBhROVAGFiMhoUEAhInl5KR+3W9jQWecgwvcsXmbL0e6hxvRFFfieZf/2lpFZqExoqqCQYmSi0RFp8fBaWmh9Kr2dbvyVVwp+//FowAFFZicPHAfv0KERXpWISPFSQCEiefU7g8J1Op3bUUHhut0CioXpL/z2vKafOMng5SoooqqgkOLhRKP4scIHFK1//CMkkwAkXn214Pcfj7ymgwOsoEj/HRSaPx+v6eAIr0pEpHgpoBCRvPrdxSPQaaJ5yuJ7mRaPQNeqi5JJISZNjrDnDQUUMni5CoqwKiikeIxUi0fz7x/CrarCraoiroACAP9gE27lwCsowkceia8hmSIiI0YBhYj0YK1NBxR9zKDoXEHhp3y8ZKbFI0+oMX1RBXtea9JQNhk0PxYHVEEhxcWUFL7FI9XYSPPDD1N+4omEFy8m/rJaPKzv4x06hDOgFo8oOA7hhQvx29rwDh4kuWfPKKxSRKS4KKAQkR5834LtWiXRXecZFJ5n8bz8LR4A0xdU0HYoQUtjvPCLlQnNZsrcVUEhxcSJlhQ8oDj4059i29up+tg/ED7iCOKvvVb0obHf3AzWDqzFY9IkAtOm4U6uAWD3v32B108/QwMzRUQKTAGFiPTgJbM7cvS9i0eW9S1eIhNQBHuGGtHyEACJ9lQhlylFwI/FIRDABINjvRSRUeNEIgUNKPxEgoY7f0Tpu95F5MgjCR+5GL+lhd1XXU3Tvb8p2HPGm2y44FZU9nvulEsuYfbNN+fCjJY//Qn/0CHqb799BFcoIlJ8FFCISA++13u7Rlb37USTcS9zvOc12XN9v7h/WieDZ2Ptqp6QouOURLEFDChafv97vAMHqD73XADCRxwBQNMvf0nT//1fwZ4z3nQEFP1XUARnziS6YnkuzLBtbRAI0HjHD/AOHhzBVYqIFBcFFCLSQ25Hjj5mUHRv5UjE09UR+UKNXEDhKaCQwfFjcUwkMtbLEBlVhd5m9OAvfkFgxgxK3/42AKK1tUz5zGcIL11KqrGxYM8Zb7zMsMuBDMnMcism5V5X/d2H8dvaiL30UsHXJiJSrBRQiEgP2RaPPmdQdHsvGfPyHgcFFDJ0NtaOo4BCiowTLcHG41jPG/a9knv30fr4n6g4/XSMk/6yzwQCTL74E0SOOgqvoWHYzxivspUPA6mgyOp8buk73pG+T2trQdclIlLMFFCISA+5CopBtHgkYn1UUDjZgMIv1BKlSKiCQoqRk9m1xm+PDftezfffB75PxRln9HjPra7Ca2go2mGZqX17AQhMnTrga7IBhVtRQXjxYgB8BRQiIgWjgEJEevBS6S9W+xyS2e297AyK/C0e6WOaQSGD5auCQoqQiab/zNv2tmHfK7H9TZyKCsILF/R4L1BdjU0mi/Yb7OTOXTjl5bjl5QO+xikvB2OIHH00TmkpoIBCRKSQFFCISA/ZSoe+ZlA43YKIbIuHZlBIIVlVUEgRcqIlAAWZQ+E1H+r1G3C3qjp9TpG2eSR37SI4c+agrjGOQ3TVKspOOKFTQDH8IElERNICY70AETn8DGgGRa+7eGgGhRSOH2vHLRv4TzdFJoJCtnj4zS3pn/rn4VZXAZmAYu7cYT9rvEnu3j3ogAJg/o9/BJBujXFdVVCIiBSQKihEpIeBzKDIhhfZ8CGRraDIU3XREVBoBoUMjioopBiZSHprXRsffEDht7WR3LOn4+PmZtyysrznBqrTFRTFupNHctcugjNmDPl6YwxOaemAAwqvpYVt55xL/PXXh/xMEZGJTgGFiPSQnUHR95DM9HvRsiAAyew2o/kqKDKT41VBIYNlYzHNoJCik/0z78cGH1Ac+M532Pp3Z+U+9lr6qqDItngUX0DhNTfjNzcTnDX4CorOBhNQxLdsoe3pp2l+8PfDeqaIyESmgEJEehjMLh6R8hCQnkFhTP7BmmrxkKHyY7HcT5NFioUJZyoohhBQpHbtJrVvHzaRAMA/1PsMikBVpsWjsfhmUCR37QIYUotHZ05pyYADitT+/QDEXnhhWM8UEZnIFFCISA/ZgMLpYwZFNrzIVlAk4l6PwZlZCihkqNIVFNGxXobIqMrNoBhCQOG1tACQOngw93FvFRSmpAQTDpMqwgqK5M5CBRQDr6BI7UsHFO0vKqAQEemNAgoR6cEfRAVFNFdBkcrb3tH5XM2gkMFSBYUUo1wFRTw+6Gv9Q4cA8BoPYq3Fb2nBKc8/g8IYg1tdXXS7ePiJBMndhQko3MEEFJkKitSu3aTq64f1XBGRiUoBhYj0MJAZFCXlIVa+Zw6LVk0B0rt49LYtabbtQxUUMhg2mcTG46qgkKIznBkUXnNz+tfGxvT2l77f5044gaoqUkXU4uHHYrzyzndx4JZvYUIh3JqaYd1vUBUUmYAC1OYhItIbBRQi0sNAZlAYx/DOv1tM9cz0PvDJmJd3/gR0qqDwFVDIwLVnvoAPL148xisRGV3ZnWvsELYZzVVQHGzEb0mHFc6k3gMKt6qqqIZkJnfuxD90CK+xkeCMGRhneF8KOyWDCyhCixaBMbm/30REpKvAWC9ARA4/uYCil4qIzrIhRirpU9LLzArH0QwKGTibTGJTKdqeehqAkreuHeMViYyuXAXFELYZ7VxB4WXCit6GZEJ6J4/E1q2DX+Q4lR2OWXHmmUSPWTHs+3WvoEju2UNw+vS856b27yc0fz5YS+zFl4b9bBGRiUgVFCLSQy6g6GWmRGedqyZ6q7jQDAoZjJ1XXMGWVatpffxxwkcdldtpQKRYdOziMbgZFNb38bNDMhsbc6+dvlo8qqtINRZRBcWu3QBMuexSqj7ykWHfzyktwWtrA6DtL3/h1XUn0PbMM3nPTe3fT2DKZMKLFxN/9dVhP1tEZCJSQCEiPXjJ/ls8stxOVRPaxUMKofnB3wPQtmEDpW996xivRmT0GcfBhELYQVZQ+C0tYNN/z3qNB/Ez1RRuL0MyAdyqamxbG/4QBnKOR8ldu8B1CUydWpD7OaWlkEziJxIcvOceAGIvbepxnk0k8BobCUyZQnjxYpJvvonf3l6QNYiITCQKKESkh2TCJxB0MM4AKig6hRK9VVxk76MZFDIQ0ZUrc69LjlNAIcXJRKP4g5xB4R1q7njd0IDXnKmgKJ/U6zVuRfq97OyKiS65exfBadMwrluQ+zkl6TlMqX37OfTAgwAktm3rcV52147AlCmEjzgCrCX++usFWYOIyESigEJEekglPAKhgX3x1jmU6G1mhTEGxzGqoJAB8WMxQgsWUHHGGZQed9xYL0dkTDjh8KBnUPjNHSGD19iY+7ivCgpnUjqg8PIEFG3PbqT9uecGtYbDXXLXLgIzZxTsfk5pOqBo+vnPse3tOCUleWd6ZHfwSFdQHAFA/JVXCrYOEZGJQkMyRaSHVMIjEB5Yftm5gqK3XTzS7ymgkIHxY+1El69g5n9+ZayXIjJmTCQy6BkU2QoKU1JC6mBjpwqKPoZkZgOKpp4Bxd7//Ao2nmDhL34+qHUczlK7dhNdc2zB7pcNKJofegh3ymRK1qwh9sKLPZ+bCyimEpo7F4JBEppDISLSgyooRKSHZNwnOMAKCscxuRaOvmZWpAMKDcmU/tm2dpyS6FgvQ2RMOeHw4GdQZComQnPndsygCAZzQzfzyQYUnasvsryGRuIvv4yfGQI53lnPI7l3L8EZMwt2z2xAEX/lFSKLFxOaP5/kzp3YRAJrLa1PP431vC4VFCYYJDx/PvFXFFCIiHSngEJEekglB97iAR1tHm4v24xCurrCqoJCBsCPxTARBRRS3IYzgyI0Z056m9GWZtyyMozp4+/m8t5bPLzGRvB9Yi/2rAgYj1L79oHnEZxR+BYPPI/QgoWE588H3yexYycHf/ITtp9zLk2//BWJ7W+mh3PWVAMQXnyEdvIQEcljWAGFMabSGHOPMWazMWaTMeZtxphqY8yDxphXMr9WdTr/amPMq8aYLcaYkzsdP9YY83zmvZtN5l9SY0zYGPPTzPGnjDHzh7NeERmY9AyKgf/1kG3z6KuCwrgGr0BDMj3P5+l73yARSxXkfnJ48dvbcaIKKKS4OeEwNjbECop5c7GxGKl9+3Em9d7eAR1DMru3eNhkMrdN6XieQ2FTKXZd/S/EtmwhuTu9xWhwVuErKABCixYSmjcPgNYnnmDfDTcCcOg3v6H5d7+j9G1vwwTS3dXhpUtJ7tzZYw5FqrER66vaUESK13ArKL4B3G+tPQpYCWwCrgIestYuBh7KfIwxZhnwEeBo4BTgv4wx2R/R/jdwEbA4898pmeMfBxqttUcAXwP+c5jrFZEBSCUG3uIBHZUTTh8VFG4BZ1Ds39bMX+59g63PHyjI/eTwYZNJSKVwopGxXorImDKRyKC3/sxWUARnzwEguX07blk/AUVmPkX3Fg+vqSn3ejwHFMndu2n6+c85dO9vSO7cBTAyFRRAeOFCgpmAYu+XvwzGMOnUU2n9059I7txJxemn5c6t/NCHcMrK2Pe1r+O3t2NTKRI7dvLq8e+mObMbiIhIMRpyQGGMmQQcD3wXwFqbsNYeBM4A7sicdgfwgczrM4CfWGvj1to3gFeBtcaYGcAka+2frbUW+EG3a7L3ugdYb/qqUxSRgkjGB9fikR2O6fY7JLMwPxXKVk60NA7ui3c5/Pnt7UC6vF2kmDmRwVdQeM2HcMrKCEyZDEDizTf7HJAJYEIhTDTao4LCa2xMv19SQnvdc6S/RBt/UgfSQXb85ZeJv/wyBAIE58wp2P2d0pLc69DChQSqqnArK3EiEebc+m1qLjgfSP+dVr5+fe7cQFUVNRdeSMvDD7Pl2DXsvPwKmn//IDaZ1O4eIlLUhrOLx0JgP/B9Y8xK4Bngn4Bp1trdANba3caYqZnzZwFPdrp+R+ZYMvO6+/HsNW9m7pUyxjQBNUCXH5saYy4iXYHB3Llzh/EpiQgMbhcP6Kig6HtIZuFmUCTjHqCAYiLK9tw7mkEhRc5EoviDbfE41IwzqZzA1GkA2Fiszy1Gs9xJk/C6V1AcPAhA6VveQstjj+E1NhKorh7UerpL7NiJd2A/0draYd1nMLz6egBir7yMTSYIH7kYp4+hoYPlZioo0sHQFABm/r8bCU6dSnjxYqy1RJYtI7J8eZdqC4Dqcz5Gcs9uktu20fz73+eCieSe3QVb3//P3nnHSVLW+f9d1TlMT/fknHZmd9mcyFmQIFEQBVExop4Z03nGu9+peKfnKeYTJRgQEAQkKCxhYZfdZXMOszs555nO3VX1+6O6e3KOPfu8X6997Ux11VNP9XSo+tTn+/kKBAJBsjGdEg8jsAH4paZp6wEfsXKOURjJ+aCNsXysbQYv0LTfaJq2SdO0TZmxLweBQDB1omF1ciGZMWFirBIPSZ65Eo9IUBcofEKgWHRoAb1bgOjiITjTmZqDog9DigvrqpVk3nMPktWKaQI3bgyuFNQhIZnRmIPCUlGuj93ZOam5jETzv/879Z/57LTHmQzRDn3e0cYmAvv2Y1u5akbHl8xmJJMJ85KyRBip88ILsVRU6I9LEiV/eYScb39r2LayzUbut79N7ve/D7JMuLpan2uTECgEAsGZy3QEinqgXtO0HbHfH0cXLFpiZRvE/m8dsP5AT10B0BhbXjDC8kHbSJJkBFKB6X9DCgSCMYmEFUymKZR4jNNmVJlxB8XkTt4FC5/4HWPJKjIoBGc2kmXyGRRqby+GlBQkSSLj7o+xdNtWsj73uXG3k12pw0s8Yg4Kc2npoN+ngqZpKH19+LZvJ9rWNmlnyHSIdvSbblW/H+vqmRUoAAweT0KQGAnJZEIyjP6dasrOTpR/mIqLiDQ1z/gcBQKBIFmYskChaVozUCdJ0rLYoiuAI8DTwF2xZXcBT8V+fhq4PdaZoxQ9DHNnrBykT5Kk82L5Eh8Ysk18rHcBL2vJWgQpECQJmqbpDooZLvGYyZBMkUGxeFH9egaFbLOPs6ZAsLiZqoNCdrn6x7DbkczmcbczpKSg9PUNHqtbD8mcrkAROHyYk+edT9uP/xciEQAijY1jbzSDKO0dIPd/N9lWzbxAUfirX05ICBqLrHu+QOY995By2eVEmprQNC1pcz8EAoFgOky3i8dngD9KknQAWAd8D7gXeLskSSeBt8d+R9O0w8Cj6CLGC8CnNE1TYuN8EvgtenDmKeD52PL7gXRJkiqBexi7hEQgEMwAqqKhqdrUQjLHKfGYqdZpcQeFvy+MEhXt2BYTWjAuUAgHheDMRrLa0MJhNEUZf+UYcQfFZDGkulAHdO0APSRTsloxZet5FlMVKMLV1Sg9PXT96U+JZfFuGnNBtKMDc3ExckoKktmMpbx8xvdhXbEikT8xVcwlJWTc/TFM+XlowSDdf3mU42vXUfuRjxKuqZmhmQoEAsHCZzohmWiatg/YNMJDV4ywDE3Tvgt8d4Tlu4BhkramaUHgtunMUSAQTI74xf+U2oyO28VjZjMo0MDXHcKVIfIKFguii4dAoCNb9SBHLRRCsk/MUaR0d2Nwp05+X65UlN7hJR4GtxuD2534fSposfc0gPOKK/Bu3kykoWFKY00FpaMDY3o6ptwc1FB4Qo6S+cSYkwNA5x8eRjKZ8G3dSu9zz5HxyU/O88wEAoFgbpiWQCEQCBYf0bDuSDCaJ1PiMZEMChl1htwO4VD/HUVvlxAoFhOJLh5CoBCc4UgW3UXk370bLRIh5W1vG3N9NRBA9fsxpGdMel+GlBRUrxdNURJZCXGBQrLbkUymKQsU8bKt4j/+AUtFBScuvGhOBYpoRweWZcvI+cbXIQlKJky5uQCEK0+Rcu01BPbuI1RVNc+zEggEgrlDCBQCgWAQ0bB+8T+pEg/j+CUeBoNEJDRzDgpZllBVDW+3CMpcTKjxLh5CoBCc4UgxB0Xrj3+M0t09rkARjbXTNKZPvhWoIVXPrVD7+vodE11dGDxuJEnC4PEkunpMlrgryrpqFbLFgiknZ04zKKIdHTjS0jBmTF64mQ/iAgWAfdMmlO5uwtWixEMgEJw5TDeDQiAQLDKikSmUeBhiJR5jOCgkg4SqzFQGRZTULP0C1tspgjIXE5pwUAgEAMhW/T0QPl2F0tE5bmCiEhMoDOnpk99Xii5QDAzKjDsoAAxudyI0c7KoAT/IcqK0wpSfP2cOCi0c1nM5Mib/nMwXhrQ0JJMJAPumszGXlBCuqhKBmQKB4IxBCBQCgWAQkVCsxGMSXTzkiZR4yBKaOnNtRu2pZsxWA95uIVAsJkQGhUCgE3dQaMEgWig0KMthJPodFJO/GI87KAa2Gh0uUHRPelzQMyhkmw29URuY8vLmTKCIduqd6Y1TKHuZLyRZxpibi5yaiqWiHEtpKWpfH0rsWAQCgWCxIwQKgWCR0N3i5+FvbMPXM70L9qmUeMQdFONmUMxYm1EFk8WIw2PFJ1qNLiqG3m0VCM5UZOvgTjbRzrFLLKYlUMRak6q9uktCUxSUnh6MHo/++DQECtUfQLL3C46m/DyibW2o4fCUxpsM0fapl73MJ47zziP1uuuQZDnR5jUscigEAsEZghAoBIJFQmeTj972ID2t/mmNExcoJlPiEXdQyIbRMyhkg4SiaLTX91F3ZHp3giLBKCaLgRSPBW+XyKBYTGiBILLVmrjbKhCcqQwVKJSusT83p1XiERMoIk1N+li9vaBpM+KgUAMBZFt/FxJTfj4A0TnIoVA62oGpPSfzSe5//Ds53/omoLcfBb1dq0AgEJwJCIFCIFgkKLEOGUpkei6FSMJBMdNdPPQMil3P1fDqn49Pb44hBbPVgMNjwSscFIsKNRCYcEtFgWAxIw0VKMax+Ec7OpGdTmSLZdL7MhcVYcrPp+k7/07PM39PXAzHxQSD243S0zOlHAQ1VuIRx5Sjh0BGmlsmPdZkiXbESjySJCBzJEx5eUgmk+jkIRAIzhiEQCEQLBLiAkV0mq08+9uMTsZBES/xGNtBoSkakZBCyBeZ1hwjQQWT1YjTY8XfF04cuyD5UYOBYXeOBYIzEWmI0DBaF43g8eP0PvccSkf7lMo7QA+lLXn8MSzl5XT85tcEDx8BwLpyJQAGjweiUVSvd9JjawH/IIEiXm6hdHZMaa6TIdKsO0KMmZmzvq/ZQjIYMBUXEa6qnu+pCAQCwZwgBAqBYJGgRNRB/0+VqZR4GAyxEo/xMihUjWhYIRSITjkwU1U1ohEVk8WA02MBDXwiKHPRoA252yoQnKkkhLpYuZMySgZFx/330/jVfyXS2DStUgajx4Pr6qsInazEt20bhvR0jNnZAINaj04W1R9AHpBBEZ9j3N0wm0Rq6zBmZye96GnKzyfaMtxxokWjnL7xJnr/8c95mJVAIBDMDkKgEAgWCdGEQKFMaftwIMoTP9xNW63eZm5yXTwmEpIpoSq6QIEG4dDU5hmJbWe2xgQKEGUeiwg1EBQdPAQC+ks8TPn5YDKNmkERqatHi0QIHDw4ZQdFHPvGjQB4X3kF68oViSwYgzsVYEo5FGoggDQgg8LgdoMsE50DB0W4thZzYeGs72e2Mbo9I4pD0Y5OQidOEDx4YB5mJRAIBLODECgEgkVC3DkRnaKDorvVT1NlD6f3toE0ttgwlLiDYswSD1kPyYzPb6plHpFgFEB3ULj1E3hvtwjKXCwMrVcXCM5U4nf9TXl5GN1uol1d+HbuJNrWNmi9cH2d/oOiYJhmtwrrmjVIJhNoWqK8AwY4KKYoUAx8T0uyjCEtDWUOHBThulpMRUWzvp/ZxuDxEB3huY+HgI70mEAgECQrQqAQCBYJiZDM6NRKJyJB3ZkQDioYzYZJdVGYaEimFndQAKFAdGrzjDkoTFYDzrSYg6JTOCgWC1pAZFAIBDDAQZGXhyEtjWhjE7Uf+ShtP/1pYh01EEBpa0/8bkyfXhikbLFgXbMGANuMCRT+YaKjMS1t1h0Uqt+P0taOeZEIFJrfjxocLMbHW8sqXd3zMCuBQCCYHYRAIRAsEqLTzKCIDCi5ME2igwf0l3jIhvG7eERiIZwh/9QEinBMSDFZjJitRsxWA16RQZH0+Lbv4MRFFxNpbkayCweFQCCZTBjS0rAsW4YhzYN/926IRPDt2JlYJ9LQoK8bEzOm66AAsG/aBDDIQRHvghEZIQdhPLQhGRSgz1Npn1mBounb3xkk3oTr6gEwFyV/icdoAlE09hxOtQWsQCAQLESEQCEQLBISIZnRKWZQhPoFg8l08AC93GLg/yMhG2Q0rV8ICfmnWOIRz6CI7cuZZsXbKUo8kp3gsaMo7e0onZ3IViFQCASSJLHk+edIe//7MHrS0EK6EBuprSXSpHenCNfp5R3Oyy8Dpu+gAEj74F0U/Ow+TLm5iWWGlBSMebmEjh4bd/toezstP/gv1FAITdNiGRRDHRTpRMdpmzoZ1HCYnr/9jd5/9odFRupqATAVLgYHhRsYLkTESzymEl4qEAgECxUhUAgEi4TpZlDESzxg8gJF+cYsrv34auwu86jryLLusogmBIoplnjEMyisMYHCbRFdPBYBAy3KIoNCINAxpKYiGY0Y0nRnhGQyAeDbsQOASL3uoPDccQcGjwfrsqXT3qfR4yHlyiuHLbeetYLg0aPjbt/7/At0/v73+LZtQwuHQVWRB4RkQsxB0TFzDorgwYNooRDh6hp9n0C4RhcoFoODwujxALoQETx2DDV2jMJBIRAIFiNCoBAIFgnR6PyVeJitRsrWj91nXjYMzrSYfolHTKDwWOgTXTySnoF3AIfawQWCMx1Dmn6B6rjkEgxuN/5YmUekvg7JZsN+9tksfXMb5pKSWZuD9ayzCFdXo/T24t+7F00bOe8oeEwXMfzbt6P6/QDItsG5Msb0DFSfb1imwlTxv7VL/yEaJVyrCxPhuloMqakYUlNnZB/ziSEmUIRraqh612103n8/MCCDorsbTZ1ei3GBQCBYKAiBQiBYJPSXeEwxJDM0dQfFRBgqUISnGZJpthoBSC9IIdAbpubQ7LesE8weA+8ASqLEQyAYRPwOum3tWuxnn41/py5QhOsbMBfkTyrUeKpYz1oOmkbD579AzR3vpfXee0e8KI6Xgfi270ALBACGl3jEsjKUGSrz8L/1VmIfocpKAMLVNYuigwf0CxSBvfsgGqVv88tAf4kHqora1zdPsxMIBIKZRQgUAsEiIdHFIzK1DIpIUEE2SsgGaU4Eiqm3GR3soFh5cR6eXAev/ukYdUc7iYSndvyC+UXp6sK6ejWWpUv1CyGBQJDAEAuptK1Zjf2cc4g0NBCubyBSV4epYG5KGKxnnQWAb9s2DB4PnQ8+RM/TTw9aR4tECJ08iWS3Ezp+PBHiOazEIy0d0B0AozkxJooWjeLfuxfXNdeAJBE6WUm0qwv/rl2JwM9kJ+4CCRw4AEDw0CEira2JEg8QORQCgWDxIAQKgWCRkMigiE69xMNiM5JVnJJo3zmTDO3wEZxqBkUszNMYEygMRpnL71yGvzfM0z/Zx5Y/H5/eRAXzgtLdhSknm7KnnyLliivmezoCwYIi5dJLyfvv/8J+7rnYzz0HAO/LmwlXV89qWcdAjLm5iQvl/P/9XzAYCJ+uGrRO6HQVWiSC+9ZbAeh79VVgeNlW3EHR9K1vU/2u26Y1r8DevWh+P85LL8FUWEjo1Cn6XngBolFSb7pxWmMvFCSjETk1lXBV//Pt27KFaEcHxpwcQORQCASCxYMQKASCRcJMtBk1WQzc8Jl1XHxbxUxODZi5Eo9wSMFolhOhmwC55W7u+t6FpOc78Yo8iqQk2t2Nwe2Z72kIBAsSyWwm9YYbkCQJS0UFBo+Htvt+hhYO47r2mrmZgyRh27QJ27p12M85G4PHg9I1uEQjFMufcL/rViSLJZGVMTT41pCuOyhCR48SPHIkEWw5FXr/+SKS2YzjoouxLFlC6ORJep56GktFBZZly6Y87kLDGGs1aszMxJiXS99Lm1G6urCUlwMQFQ4KgUCwSBAChUCwSFBmSKAw24yzX+IhTb3NaNgfxWwzDltud5lxuC1TDt8UzB+apqF0dSfqrAUCwehIkoT9nHNQ+/qwVJRjXb16zvad/6MfUvT73yFJEkaPh2jn4Ivi4NFjSBYLliVLMBUWJPIghgoUxlhXEgA0jUhz85Tmo6kqfS++iOOiizA4HVjKywmfOkVg3z5Sb75pTrI55or456OpqIiUK6/Eu2ULqCqWJUsAULp75nN6AoFAMGMIgUIgWCQkMiimWOIRDkYTuQ6zwUDHgy3FPPUuHoEolhEECgCL3Uhois4Mwfyher0QjWKI3SEUCARjEy/zSL3l1jm9CJet1oTYYEhLGxZyGTpxAkt5OZLRiLmwCC3WpUMakkEh2+3IKSkJJ0U8qwIg0tTEybe9jdDp02POJXTyJJ0PPEi0uZmUq94OgPvWW0i76wPk/eBe0j74wWkd60Ij/vloLigg9YYbIBZQai6PCRTCQSEQCBYJI5/lCwSCpCNe4hGdhoPCbJ1FgWJABoXTbcHX3V+KoWkanU0+0vOc444TCozsoABdoAgLB0XSEa+dFg4KgWBiuK69lnBlJe5bb5m3ORjSPISOHB20LFxdjW3DBgDMAzpojNQ6uPA3v0aSJKpvv2OQQBE8coRoYxOBffuxlJWNuv+Ge+4hdLISyWYj5fLL9X2WlJD9ta9N67gWKv0OikKsq1ZhLinRM0iKi8FoFBkUAoFg0SAcFALBIiHevWN6JR6zp1kOLPFwpA52UDRVdvPIf+ykrW78NmkTcVBMNxVeMLfE7/wZPO75nYhAkCQYPR5yvvUtDC7XPM4hbVDugRoMEmlqSoR2mor6u4sMLfEAsK9fj3XlSpBlIo2NieXxco9IU+OwbeJoqkq4ppbUW29hyQvPJ8I7FzNxgcJcVIQkSbhuvAEAU3Y2BrdbCBQCgWDRIBwUAkESE+gLY0sxAwMyKKbRxcM0qw6KAQKF24ISVYlGFIwmA74ePSCts9FHZmHKmOOEgwqujOEnuwAWmwlN1WJuEPHxlizEBQqjKPEQCJIGQ1oaam8vWiSCZDIRrq0FTUsIFOai4sS6IwkUAJLJhDEne5CDItrSCjBItBhKtK0dLRzGunIlpuzsGTiahU9cwDUVFACQ/qEPYVlSjrm4GIM7VZR4CASCRYNwUAgESUpTZTe//8ob9HYEgP72olMu8Qgqc5ZB4XDrbUzjLopISHd/9LYHxh1nzBIPh3HQuILkQJR4CATJhyFNf7/GXRTh6mqAAQJFv4NCGkWgADDn5RMeJFC0AGMLFJGGen3b2MX6mYB1+VkY0tISXTtkmw3X1VcBYHR7hINCIBAsGoRAIRAkKb6eMJoG/pj7QIlqsf+n18VjthjqoAAI+XQhIRqOCRRt4wsU4bEECpsQKJKRaKLEQwgUAkGyEO/EEdi/n8av/ivBo3oehblEd06Y8vLAYECyWpHk0U83Tfl5g0s8WiciUDTEts2f3kEkEc6LL2Lptq0YUoa7DA2ZGUSamuZhVgKBQDDzCIFCIEhSNDUmSAxpLzqVDApFUVGi6iwLFP0fN+4sPdE97v6IOyh6xnFQKBEVJaKOmUEBU29hKpgflO5uMBiQRzjxFggECxODRxcouv/8Z3qeeoquh/+AITMDg1MPO5ZMJkx5eaOWd8Qx5ecTbW5Bi+if2/ESj2hTM5o68vdZpL4+sa0AbKtWEamvJ9rRMd9TEQgEgmkjBAqBIElRYwJFNKKiKuowwWIyRGMCwVw4KAwmmbRcBwDdLX5ALy+B8R0U8Raio3fxMOnrCQfFnLL5wSPseq56ytsrXd0Y3O45bZcoEAimhzFW4uHftRvQ2wVbiksGrWMuLJyQQIGqEomVdkRbWpAsFrRwGGWUC+5wfT2GzAxkq3WaR7E4sK1dC0Bg/4F5nolAIBBMHyFQCARJykBBIp47IclSIotiMoRjAsFsBkvGBQqT2YDVacLqNNEVFyhiJR6+njC7nqvi2V+MfJIVjgkUFtvIQkq/g0IIFHNJw/Fuao9M/c6d0tUlOngIBEmGIVbioYXDSDGhwFxaMmgdz53vJe2uD4w5jilfz5EIV1WheL2oPh/W1auA0cs8Ig2NmPPPnPyJ8bCuWgVGI4F9++Z7KgKBQDBthEAhECQpCQdFVEnkTphtBtSoNuk2m5E5dFAYzfrHjifHTnezf9D+AXY9V0PtoQ5UZbjQEg6O7aCIL48LGYK5IRyM0tcZnPL2Sm8vBtfibxMoECwmDG43xFxPae9/P6a8POxnnz1onZQrriDtrrvGHMe2Wr+49u/cmQjItK/fAIwhUNTXi/KOAchWK9bly4VAIRAIFgVCoBAIkhRViQkUYTVR1hHPZphsUOacCBSxkDSjWd+HO9tOV7Nv0P5Bn7uqaonWowMZt8TDZgQJgiKDYs7QNI1IUMHXHR5RVJoIqteL7HTM8MwEAsFsIhkMGFJ1YdG+aSNLNr9E6o03Tnoc2eHAtnYtvje3JwQK2/p1AEQahwc/atEokaamRLtNgY5t7VoChw6hRYVALxAIkhshUAgEScpIJR7xDIbJ5lDMi4Mi20GgL0LQFyEaUhKdPeL0dQzPowiPI1BIsoTZaiQcK/Go2t9Gw3HRG342iQtKmqrh7Q5NaQzV50N2CIFCIEg24mUeluVnTStDxnHeeQQPHyZ08qQ+Xnk5stOZ6NYxkEhTEygKpgLhoBiIbd06NL8/8RwKBAJBsiIECoEgSRkYkhkXJOIX7tHJChSx0gmTdfYFClPMQeHJ0Tt5dLf4iYQUXBlWrA4T+cvcAPR2DC8Z6M+gGD0rw2I3JjIoXn/0JDuePj1jxyAYTjjQ737xTrHMQwgUAkFyYkjzYEhPx5iVOa1xHOefB5pG99+eAsCYlYV1xQr8u3cPW9f7yqsA2Netm9Y+Fxtx14ko8xAIBMmOECgEgiRloIMiXtKRKPFIAgeFOyZQdDXrAoXJYuS2r23imrtXA9A3okARC/McT6AIRPVchI5gIohTMDtEQv124pH+ZhNB9fkwOJwzNSWBQDBHuN95C+kf/ei0O/DY1qxBttsJHT2KKT8f2WrFecnFhI4fT3T3iNPz7N+xLF+OpaJiWvtcbJjy8zFkZBDYt3++pyIQCATTYvYi+wUCwawSz6BQov0lHmb7dDMoZrOLx+AMCle6FVmW6G7VBYqUdAOuDL0dnSPVPKKDIhTLlhhXoPBH6IoFcAa9EYLeCFanaUaPR6Az0EExNChTVTX2vFDDWRfm4ki1DN0UAE1VhYNCIEhS3LfeMiPjSGYzRb+7H6W3N9Ey03HJJfDDH9H5wIME9uwh9/vfQzIYCO4/QNaXvzQj+11MSJKk51AIB4VAIEhyhEAhECQp8U4d0bAy3EExVYFiNks85LiDQt+HbJCxppgI9oVjDop+Q1dKum2UDAoFk8WQGGskLDYT3a1+Oht9iWVdLX5ynaJLxGwwloOi+XRPrMRGY9M7SkfcXvXrf2chUAgEZza2ISUblooKjLm5dP7+9wD0/fNFQP/ec1133RzPLjmwrVuLd/Nmol1dGD2e+Z6OQCAQTAlR4iEQJCkJB8WADAqLfWoZFOFgTKAwz95HQn8GRf8+bE4TAW8kUeIRJyXdOmK5QCgYHdM9AfpzEA5E6WzqFyi6W3xjbCGYDnEHhWyQhjkoGk906/9X9oy6verT/zZCoBAIBAORJAnnZZeCLGPwePDv2oX3tS1YV6/GlJMz39NbkMRzOQL7RZmHQCBIXoRAIRAkKWOFZE42gyLsj2K0GBJlGLNBfwZFv0vD6jAR9EWIhJVB+ReudCveztCwtpXhwPgChdluJOiP0tnoIy3PgWyQEuUecSJhhWfu20fdkc7pHtYZTzjmoPDkOOjrHNzFo/Gk3kGl+VTPqC1IEwKFU2RQCASCwWR9/vOUPv4Yrmuvwb97N4H9+3FefNF8T2vBYl21CmSZ4IED8z0VgUAgmDJCoBAIkhRN6RcoEm1GpyhQBH0RrI7ZrfgaUaBwmvD1hFGj2pASDyuqquHrCQ8aIxyIYrGNXYbidFuIhhQaK7tJz3eSmmWne0hQZs3BDmoPd/Li7w/j7w2PMpJgIsQdFGl5Dvo6g4nSI0VRaTrdiyPVTCSk0F7vHXF71acvlx32uZmwQCBIGgypqVhXrMC+aRNaIACqiuPii+d7WgsW2WbDXFREqPLUfE9FIBAIpowQKASCJCVxIRjt7+JhnmIGRdAXweY0z+wEhyDJEvnL3GSXuBLLrE4z3i69LGBgiYcrXQ/LHFrmoTsoxg67XHlxPml5DqIhhbRcB55s+zAHReWuFiwOI+GAwta/ip7x0yESKw9Kz3egRNSE4NNW20c0pLD+qmIAmip7UBSV/Zvr8PX0Oy2mUuJxclcLbz4pTsAFgjMF28ZNAMipqdhWr57n2SxszOVLCFVWzvc0BAKBYMoIgUIgSFLiGRTR8IAMCtvUMijmwkEhSRI3f2EDZeszE8tsThNqVD+OgSUeKelWgGFBmaEJOChMFgPXfnw1GYVOClek4c6x09sWIBrRL6TDwSjVhzpYenYOJWvSaa3um5HjO1MJB6MgQVquLjDEcyiaTuq5ExVnZ5OSbuXotiZeeegYbzx2kspdrYntpyJQHH69kT3/qKGjcWRXhkAgWFyYsrOwLF9OytvehmQU+e5jYSkvJ1xTgxYW7kCBQJCcCIFCIEhS4hkUSlSZdpvRoDeC1TH3bTgH7tM4sMQjTRcohrYaDXojWCYwT3e2nfd8/RyyS1wULPWgqhrVBzoAqD7YjhJRKd+UhSvdRm9HAC32XAomTySo54ekDHG9tNX14UyzYHeZuehdFfS0Bzi+oxkAf1//iXNcoDBMIoOiKxaAeuDl+hk5BoFAsPAp/sPD5Hzn2/M9jQWPZUk5KArhmpr5nopAIBBMCSFQCARJihbTIEZyUEwtg2IeBApn/z4HlngYTDKOVPOgEo9oRCHkj+JInVwpSv5yD45Uc+LiuOlkD2argdyyVFwZVtSoJnIopkE4GMVsNZKSZgH6HRTtdX1kFqYAULY+k/d8/Wwuf/9y7C4zgQECheKNZ1BMzEER9EXw94YxWQwc39FM0BeZycMRCAQLFIPTiWyxzPc0FjyW8iUAosxDIBAkLUKgEAiSlH4HRSyDQgKzdfIlHqqq6aUTzvkWKAaXbqSk2wY5KPyxwEx76uROUGVZYum5OdQe6sDfG6alupesEheSLCXu+ve2B8YZRTAa4aCC2WrAYjdhthrwdgSJhBS6WvxkFPS7ItxZdlZcmIc91Uygd7iDYqICRbx97PILclEiasJNIRAIBAIwl5aCLIugTIFAkLQIgUIgSFK0WNtGJdbFw2iUMZj0t/RkSjxC/ghozIuDwjZQoDAPFSisgzIo4i4Hu2vyYZ7Lzs1BVTWOvdlER72XrFhQpytj5FISwcSJBKOYYsJYSrqVvs4gHQ1e0CAj5qAYiC3FjL+v3/Wg+nwgy0hW64T219moCxI5ZfrfMBJWpnsIi4q6Y508c9++Udu6CgSCxY1stWIqLBAOCoFAkLQIgUIgSFLiDopoWHdQGEwyBqPeynMiJR6+7hC/+/Lr1B/rAuZHoBi4z+EOCivezlDiOOOdHxyTdFAApOc7ySxKYfcLNaiqlugkEs+6GBrGKZg4cQcF6M9nX2eQ9jo9eDSjcHiuhD1lcImH6vMjO51IkjSh/XU2+TBZDHhydMdFJCQEioE0VfZQe7iTriGtdQUCwZmDpWwJ4dOn53saAoFAMCWEQCEQJCmJDIqonkFhMMnIBhlZliYkUPS0+Qn0Raja3w4MLreYKwaVeFgHCxSudCuqquHr1oWJ/hKPqbVDXXZuDuFAFIDsUl2gMJoN2F1metuFg2KqRELRRGlRSpqVvo4gbfVeLHZjQgAaiC3FRKA3nGiTq3q9k+rg0dXkw5NjT4giUSFQDCIac5S01YruNALBmYohzYPS2zvf0xAIBIIpIQQKgSBJSWRQhBUiIQVjrLzDYJKJhscXKMJB/UKmpUpvBzkfDgqTxYAcc32MVOIB/V0hfD0hJEkvEZgKFWdnI8kSTo9lkAsjJd0qSjymQTigJMQlZ7qVcFCh9nBHoryj69FHB50o21LMRCNqwvmg+nzIDvuE9qUqKh0NXtLyHBhjrxfhoBhMXLARAoVAcOYiOxyJfB+BQCBINoRAIRAkKaoSK/GIqoQGdOFwZdrobB7/xCQSEyji7oH5ECgkScIW2+/QEg9Xom2lXn7h7wljc5mR5YmVAgzF7jKz5rICll+QO3g/GTZR4jENwkMcFADezhCrLsknXFVF87e+Tc/TzyTWjwtMgVgOherzYXBMrMXotidOEeiLULI6I/F6CQuBYhCRmHtKCBQCwZlLXKCIO9UEAoEgmTCOv4pAIFiIaDEHhRrVCHgjicDJ7FIXp3a3oqka0hgX8+FgdNDv81Hioe/XTKAvknBSxHEOaVvp6wlPKX9iIBe9u2LYMle6lcrdrUQjCkaTYYStBKOhaRqRAQ6KuOslf5mHJRsy8W07CUCkrjaxTTzkNNAXJjXTFnNQjF7i4e8N8+aTlVQf6CDoi7Dm8gKWbMhKvP5Ficdg4iUe7XXecT8DBALB4sTgcICmofn9SJMooRMIBIKFgHBQCARJSrzEA/TAS0vMiZBd4iLkj9LTNrYrIF7iAXorTrN1fi7OrU4jRothWEii0WQgJd1Ka41+J9jfG5py/sRYZJW40FSNP35ru959QjBhlKiKqmqJ105mQQqrLsnnsjuXIUkS0eZmAMJ19YltbCn66zTelUX1jZ5Boaoaj9+7ixM7WyhZk84lty/lgneVAyDJEkazLEo8hhAv74qEFLpbRVCmQHAmIjt1V5oiyjwEAkESIgQKgSBJ0QYIFP6+cMIBEe9Q0VI9dkBWZICDwuIwTriLwkxjdZiHlXfEKVmTQe2RTsLBqO6gmEKL0fEoXZvB9Z9ZS8Ab4eibTTM+/mImHNDFgXiJh8Ekc+l7l+HO0jMlIjGBIlJXl9imv8RDFygUnw/szsSd/4H0tgfo6wxy8XuWcsVdK1h9WQEGQ//XlsliEALFEKLh/q4q7XVCcBMIzkTioq/IoRAIBMmIECgEgiRloIMCrT9DwpPrwGgx0FI1tkAx0EExH/kTcdZcns+5N5aO+Fj5hkyUiEr1wXYCfWHs0yzxGAlJkihemU5GgZO2GlG3PxkiIV3kGs19k3BQ1NcnaqHtwzIo/OwJr+PZXxwYtn13s+4AyCgYOaNCCBTDiYYV0mPP13guqqHse6mWrX+tnI1pCQSCOSQhUHiFQCEQCJIPIVAIBEnKQAcF9IsMsiyRVZSS6M4xGpFgFEOs88d85U8A5FV4OOuCvBEfy1nixpZi4uArDaCBYxZKPOJkFaXQVtc37HkVjE78Dr3dPbJwFGluAUALBFA6OgAIvrUds9XAsTebePibbxIJROhVHNQf70q4KuLEw17d2SN3+TBZjEKgGEIkrGJ1mLC5zPR1BOho9PLGoycHC5qjcHxHMwdfqScygptFIBAkD3IseFg4KAQCQTIiBAqBIEmJd/GIY3X2Z96m5TroaR8/gyIlzYrZZpxXB8VYyLLE0nNzaD6tiy2z4aCIk1nsIhIUdfuT4fAbjTg9FvKXekZ8PNrcjGTVgzPDdXWEq6up/fBHsBCipy1Ab1uAgMlNUDWDBrVHOgdt393sx+Yyj/r6NFlEBsVQomEFo9mAK9Y+98SOFva/XEfrOCVfmqbR3RpAiao0neyem8kKBIJZIeGg8AuBQiAQJB9CoBAIkpTRHBQAZruRcEAZs8VYOKhgshjYeG0xy8/PHXW9+eb8dy7hmrtXsf7tRRQsH/lCeCbIKk4BSIRyCsamp81P3ZFOVlyUN2rr10hzM7b16/Sf6+vx794DgFXzJbYJWDMIRfUSkZpDHYO272r2kZYzsnsCRInHSETDKkaznBAoOpv0C5Shz+1QfN2hREeUoUKRQCBILmSH/rmpekUOjUAgSD6EQCEQJCmqqjEw13KgQGGxGdFULZHoPxKRUBSzzcCGq4opW5c5m1OdFgaDzJINWVxwa3kijHE28OTYMZpk2mqFQDERTr7VAhKjlucoXh9qXx/2jZsA3UER2LcXgDWhbdz4uXUA9KUUAWA0ydQe6UiUImiaRlezH3fO6C3yTBbjiOGaZwrhYJRoZPDxxx0UKek2vJ1BOhv1C5TxBIquFt05ZLYZhUAhECQ5Bqco8RAIBMmLECgEgiRFU7VB3S8GOShs+oV8OBAdtl2ccEDBZJm9C/5kQzbIZBSm0FTZPd9TSQp6WgM43RacnpHLbqKtev6EubgIY3Y2kbp6/Ht1gcLccIyc8lRAoze1BICl5+YQ8kU5vl0P1gz0RQj5o3hGyZ8AMJ7hJR7P/HQfWx45MWhZNKxiMsu4MqyoikZvexCzzUhbbR+bHzjCrueqRxwrHkh61gW5dDX58PWEZnv6AoFgloiXeCjCQSEQCJIQIVAIBEmKOqZAoS8PjSFQRELRUbsvnKks2ZBJa00f7fXipG48vN0hHKOEYwJEmvSWraacHKzLl9P38suEK08hmUyE6xuQZQmLFqAvVe/gsvLiPLJLXWx/6hSRkEJXLCDTkztWiceZHZLZ2eSn4UR34ndV1VCiasxBYU0sX3WJ7nI5tr2ZHU+fpv7YcIdEd4sfk8VA8ep0ALqaxJ1XgSBZkWw2kGXhoBAIBEmJECgEgiRFVTRMsZIHWZYwDRAb4qUQYzoogsqslkwkI8vPz8Vgkjn4Wv18T2XB4+0K4fRYR3xM0zRCx44BYMzJIeurX0UL6XfknZddpnf1aG/H4u8gIutjONwWLnxXBf6eMIdfb0iU2qTnjdxiFM7sDIpoWCEciNLbFiDoiySWARhNBlzptsS6FWfncM3dq7j9W+eQmmnjlT8cQ4kMLv/qbvHjzraTmqlvN9kWpQKBYOEgSRKyw4HqE6HPAoEg+RAChUCQpAws8bA4TUgDAiksEynxCEYHiRoC3YWy9OxsTuxoJuSPzPd0FiyapuHtCo5a3tFwzz20/vcPkVNTMWVnYykrJecbX8dUXITruncA4Nu+HYtfz0WQJLClmMldkkpanoPqg+3UH+vCnW0f06VhMstEw+qEWmguNnw9/S1Z2+p0MSeeOWM0y6SkWUHSn1t3to0lG7JIz3Ny8XuW0tse5NS+1kHjdcUECqfHimyQ6B2nC5BAIFjYyA6HCMkUCARJybQFCkmSDJIk7ZUk6e+x39MkSXpRkqSTsf89A9b9miRJlZIkHZck6eoByzdKknQw9thPpdiVliRJFkmS/hJbvkOSpJLpzlcgWCwMLPEY2oYxnkExWomHElVRo5oo8RiB1ZcVEA2rHHuzeb6nsmAJ+aNEw+qoAkXwwEEcF5xP+T9eQDKbAXC/612U/+MfWCoqAOh97nksoW4A7C5zoqtH8cp0mip7aDjZTcGysbu2xDNUzsSgTP+AjIi2mrhAEXNQmA0YTDKOVAuuDBtGU//7vGhFGq4MK0deb0ws8/WE6OsM4smxI8sSrgybcFAIBEmO7qAQJR4CgSD5mAkHxeeAowN+/1dgs6ZpFcDm2O9IkrQCuB1YCVwD/EKSpPhZ0y+Bu4GK2L9rYss/AnRpmlYO/Bj4wQzMVyBYFGiqlnBAWB2DSzXGC8mMBPULGZMo8RhGZlEK2aUuDm1pGLNN65mMtytWrjFKiYfS1YWlogKD2z3sMVN+vj7GK69gM+uvT3tqv9BRtDINVdGIhpRx28rGX/9nYplH3EEhyVKiNW4kIVDoX+15FW4KV6QN2k6SJVZclEfDie5EzsfOv1chSxIVm7IBRhUoImFlzFwbgUCwcBAChUAgSFamJVBIklQAXAf8dsDim4AHYz8/CNw8YPkjmqaFNE2rAiqBcyRJygVcmqa9qelXAw8N2SY+1uPAFdJAH7tAcAajKhom89gOinBw5Au3cFC/yBAOipFZfWk+3S1+6o91zfdUFiTeriDAiA4KNRRC9fsxeNKGPQYgW60YM/W2tpmXnQswqIwjt9yN0WIACfLHc1DELsTPRIHC36uLRLlLUmmr7QX6SzzizqqrPrKSS+9YNmzb5efnYjTLPPW/+9j+t1McfaORVZfm4451TEnNtNHbFiAcjBL0RtA0jb3/rOXBr23lse+/hXYGltQIBMmGwamXeDR+9V/xvvbafE9HIBAIJsx0HRT/C3wFGJi2la1pWhNA7P+s2PJ8oG7AevWxZfmxn4cuH7SNpmlRoAdIn+acBYJFgTZWiUfsAm80B0VcuBAhmSNTtl7/2Gqp7p3nmSxM+h0UwwUKpbsbAINndHHBXFaGqbCQrLdfCIA91Zx4zGCUKVubQV65e9jreijxEo8zUaDw9YSRZYniVen0tgfxdYcGlXiMhSPVwi1f2ojRLLP7HzVkFqWw6bqSxOOpmTbCQYWn/ncfD/7bVv5+3362PVGJ022hpzUghDuBIAmQHQ7CdXX0PPUUvm1vzvd0BAKBYMJM+epEkqTrgVZN03ZLknTZRDYZYZk2xvKxthk6l7vRS0QoKiqawFQEguRHVTVko4zVaRrUUhB0G7fZYhijxENfLkIyRyZukVei6jhrnpl4u4JIsjSoNCOO0qm3sDR43KNun/eDe0HT8BsdgH7BPJC33XXWCJ/0w4kLdNEzUKDw94SwucwUrkjjzSdPUXe0E1uKLvTEX79jkVmUwp3fOY9oVE04seK4Yp08Wqt7sbvM1B7pZNN1JWy8ppgHvrqVo9sah5WOCASChYVsdyQ+j9VQcJ5nIxAIBBNnOrdPLwRulCTpHYAVcEmS9AegRZKkXE3TmmLlG/Go8HqgcMD2BUBjbHnBCMsHblMvSZIRSAWGNXDXNO03wG8ANm3aJLyngjMCVdWQZYnb/nUTNpd52ONmm1E4KKaIJEnIRgk1Kj5ORsLXFcKR2h9sORClS7+7bkwb/QLWlJMDQIqiUr4xi+JVg41xBsPEzH1Gy5mbQeHvCeNINZOR78SWYqL2SCdL1uulM0MFh9GQZGnEdeOtRo0WA3d861yCvkii/GPpOTkceaORoC8yrsNFIBDMH7Kzv0WzFhAChUAgSB6mXOKhadrXNE0r0DStBD388mVN094HPA3cFVvtLuCp2M9PA7fHOnOUoodh7oyVgfRJknReLF/iA0O2iY/1rtg+xBWDQABoioYk64F2I11kmG3GUQPtwsJBMS4GgywcFEMI+SO8+LvDNFZ2j9r+MxoTKMYq8YgjG2Su/tgqsktcU5qP6QwWKHw9YeypFiRZonBFGnVHOxPPw0QcFGPhyrBiNMusvDAPq9OUECcAStdloETVRGtTgUCwMJEdjsTPalAIFAKBIHmYjdun9wKPSpL0EaAWuA1A07TDkiQ9ChwBosCnNE2Ln1V+EngAsAHPx/4B3A88LElSJbpz4vZZmK9AkJSoGiPewY5jsRkTQsRQ4hcywkExOgajECiGcnJXKyd2tgCMKioonRMXKKZLQqBYoG1Gu1v8OD2WcTMhpoK/N0ROmf43KDorjRM7Wmg61QOMn0ExHkaTgfd84xxS0oZ3aUnN0N0VfR3igkcgWMgMFCg0IVAIBIIkYkauTjRNexV4NfZzB3DFKOt9F/juCMt3AatGWB4kJnAIBILBaIqGbBhdoDDbjPh7wyM+Fi/9iF/gCYajl3icuQKFqmqoUXXQxe7pva2kZtm48F0VeHLsI26ndHWBJGFITZ31OSYEiqCCoqgTLg2ZC+qOdfLMT/Zx9vWlnH1d6bTGCgeibP1rJefeWIbdZUZRVAJ9kUQGSG6FG4DGk93A9AUKAHfWyH9fp0d3bQiBQiBY2MhO4aAQCATJycI5mxMIBJNCVTXG6ro7VolHv4NCCBSjoTsoztyKsj0vVPPo995K/B70RWg43s2S9ZmUrskY9QJW6e7CkJqKZJj911ZcoNjx9Gn+8v92JrpYzDferhD//L/DaBo0n+6Z9niVe1o58kYjp/e1ARCICY+OWPcTp8eKbJToafUD0y/xGAvZION0W+htD8zaPgQCwfQRDgqBQJCsCIFCIEhCNE1DUzWkcRwUcaeEElEJeiMAVB9s5/DrjdhSTMgL6I7zQsNglFGUsR0USkQdNYg02elpC9DV7CcSUmiv72P7306hqhpl67LG3C7a1TUn5R0ARpMMEoT8Ubqa/ex/uW78jeaAk7taCPoi5Jan0lbbx3Sjk2oOdgB6Vw2A9novQKJ7jyxLuNJtaLGyr9l2krgyrMJBIRAscMz5+SDLmMvKhINCIBAkFeLqRCBIQuLXO2NnUOhtRjVN463nqvjLd3eiaRovP3wMk8XAOz65Zo5mm5wYjBJKZLBAEegLD7pzvPWvlTx27y40VaOz0UfIH5nrac4akZB+7H0dQZ65bz+HX28ku9RFVnHKmNspnV0YxujgMZNIsoTDZaZkTQYlazLY/UINAe/IZU1zSUtVDynpVio2ZRPoi+DtCk15rGhEofao3ryqJSZQnN7bhslqIL+iXwhKdN6YRfdEnJR0q3BQCAQLHNumTVRseQ3r8uWoQfF+FQgEyYMQKASCJERTdIVivAwKVdFQIiodDT68XSH6OoIEesOcdUEuOWWznxGQzBiMMqoy+M731scree6XBxK/t9f10d3ip+pAO499/y02P3h0rqc5a8TLgNrq+vD3hDnv5jLe9dVNSGOIYqBnUBg87jmYoc67v34O1358FRuvLSYSVKg/pod0RkIK2586NWpQ7GzSfLqXnLJUsor1EMvWml5UVeOtZ6sm1f3ib/+zh8e+v4toSCGrOIXOJh9BX4TT+9soXZOBwdT/Fe5KCBSzX1rjyrDh6wkPE/AEAsHCQZIkjBkZSDYrWnDqIqlAIBDMNUKgEAiSEFXVL5zHzKCIdegIBaL0deh3T2qP6Hdi43dbBaMjj9BmtK8zSE9rIGHZ74ndRX75oaNEIypV+9sTd7mTnUhIv7Cvi71m0nIdY62eQOnqwjhHJR4AdpcZ2SCTWZiCbJRoq9UFgFN7Wtn9fA01hzoS62rq7GeKeLuC+Lr1DhvpBQ5kWaK1uo8tfz7OzmeqOPJ644TG6W0P0HCim84mH2argQ1XF4MG+16sJeSLsmTD4FKbeHeNuXJQgP5+EAgECxvZahMlHgKBIKkQAoVAkITEL7TGc1CA3gEgXi9ee1i/WHMJgWJcDCZpmEAR6AsTjaiEfFEiYQV/TziRgZBX4cbqMLHzmap5mvHMEg3rxx4vL3BnjxyKORBN04h2d2PwzE2Jx0AMRpn0PGdCoIiLcZ2NPgA6Gr385vOvUXesc1bn0XxaF6hyylIxmgyk5TvY+88aDr/eiCxLdMeCLMcj7gR55xc38O6vn01erFPH7hdqsDiMFK0Y/BynZs2hgyJd31dvh7CNCwQLHclqESGZAoEgqRAChUCQhCQcFGPY7eMCRV9nkHBQt+s3HNcveoSDYnwMhuFdPPx9er6BtztIX7t+wlexKRuAs68vZeUledQd6SDoS/4siniJR6A3jCRLExK1VK8XIpE5C8kcSmZxCm21faiqRv2xwQLF0W1NRMMqO58+Pe3QyrFoPt2DwSSTnu8EYMWFeRQs93DlB89iycasSQgUndhTzeQuSSU1044txUxmUQqeXAfvvGfDMCEi/p6ei9bBcQdF8+neUVsZCwSChYFstaGFQmiqKMkSCATJgXG+JyAQCCZPPBthrJDMeAvChhPdiWXhoIItxZQo/xCMjmwcXOKhKLpzAsDb2V/Pu+byAs5/5xJS0qzIBondz9fQeKKbsvWZcz7nmSQyILvBlWGdUGeISFMTAMa0+REosopSOPJ6I1X72gj0RTCYZDoavaiqxsmdLZhtRppP91J/vIvC5bPj8miv95JR4MRg1J+v1ZcVsPqyAgB6O4KcfKuFaFgZ0+mgqZo+xxVpg8q4bvnyBgwGeURh0pVuA2luSjwcbgsGk8xbf6/ixM5m3vcf58/6PgUCwdSQbbqgqAWDSPbxnXACgUAw3wgHhUCQhGgTcFCk5+sXSad2twJgseuihHBPTAyDUUIdIFDE27QCeLtDifwJV4aNlDT9BDC71IXJYqDu6OyWEcwFcQcFgGcC5R0AfS/8AyQJ+7nnzta0xiSzSO8wsvPvepnNsnNz6G0LUHOwHX9vmEtuX4rTY+GVh45RfaCdV/94DF/PzIbH9XUEcGWM/B6Ll2H0tI1eGtFc1cOzvzxAoC8yTEQxmgyjvucNJhmn24LRNPsOClmWuP5TayjfmEVPa2BegkgFAsHEkCz695MaEkGZAoEgORC3UQWCJESdQAaFwSiTUeikpUqvic9f6uH0vjaRPzFBDEMcFIG+fiu7tytIJKRgtBiwpZj6tzHI5C11U3esk1AgytGtjTRV9iDJEpfesRRbinlOj2GqaJpGJKwiGyXUqDax/AlVpeepp3Ccfx6mnJw5mOVw0vOcyAaJzkYfy87LofCsNI680ci2J05hsRtZsiETT46dp368l2d/oXdjcbgtnH1d6YzsX1VU+jpDVJxtHfFxd5b+PHa3+hMlIAPx94Z57pcHAd15Ub4xa9g6Y3HODaXYnHPzGitYnkbQF6Vydys9rQEOvd5AR72XnNJULnp3xZzMQSAQjE/CQREIwDyV3wkEAsFkEA4KgSAJSYRkjtPyMbtUb3NotBgSP6eOcndXMJihbUYDvQMcFF0hetuDpGbYhnVSKVyeRk9rgN99+XW2Pl5Je30fp/a0JkIbkwElqqKpGp5svXPHRAQK/65dRBoaSL355lme3egYTDJv//BKbvjMWq784ArS8vT5d7f4WXdlEUaTgaxiFzd9YT3n3VxGZlEK1QfaZ2z/3q4QmqqN6qBICBQtg3MoNE0j4A3z4u8OE/JHuOlz67jk9qWTDrw864I8StZkTG3yU8CTox9PS1UPR15vpKc1wP6X6+hq9s3ZHAQCwdgkHBRDWo2qPh8t9/4A1SferwKBYGEhHBQCQRISv3Aeq8QD+gWKlDRrorRDlHhMjKEZFPGATKvDhLcrhL83jDtr+HNZvjGL2sMdpOU5qDg7m/QCJ7/57Gt0NnrnbO7TJV7ekbfUTU97gJyy1HG38W/fAZJEypVXzvb0xmSg6yA1y4ZslLDYjKx5W0FieVaxi6xi/b2x/W+n8XWHcLgt0953b7zsJ31kB4XZZsTuMtNW00fl7lbK1mey8+nT7H2pFlmSUBWNS+5YOqK7YiGSmqnnXpx4qwWAi24rZ/ODRzm+o5nzbloyz7MTCAQwMINicGmZb8dOOh94APs555DytsvnY2oCgUAwIkKgEAiSkHgXgnEdFCX6haUr3UpuuZu8Cjd5S4XFcyIYjNKgLh7xEo/MIiedTX6C3ghFK4cHLTrcFm747LpByzw5djoakucuVSTW9SWz0MklP7l0QttEuzoxpKYiL6AQNoNBZtO1JaTnO0cMhi1Zk8H2v52m+mA7Ky/On/b+emPtfEdzUIDuRjm1t41Te9u49L3LOPhaA+l5TrJLXKy6ND9pxAnQW5qmpFlpquwB9Oez8Kw0ju9o5twbylA1jUhQweowjTOSQCCYLSSr/nmkDmk1Gm1rAyDS1DjncxIIBIKxECUeAkESMlEHhSvDiivDSnqBE7vLzDu/uCER6CgYG73N6MAMigiyLJGW58TXHUKJqokWo+ORluekI5kcFGFdoJhMiYHS1T1v7UXH4uzrSilbN3JHlbRcB840C/XHumZkX73tASRZwukZ3Y1RvCqdrOIU3Nl2Xn/0BOFAlAtuLefS9y5LKnEiTjxA1Z1tx2I3sey8HLydIRoru3nzyVP88VvbF0XbXYEgWZGt+ueRNppA0SgECoFAsLAQAoVAkISoE8ygkCSJ93z9HM65fmZCAM8kDCZdoIi7VQJ9YWwppoTAk7/MTXaJa0Jjpec78HaGCAWSo9tBvMTDZJmEQNHdjcHtnqUZzQ6SJJGaYcPXPTPp9r3tQZweC/IYLVk3XF3MbV87m7OvL0GNargybeRXuGdk//NBakygyCrWO6iUrsvEZDFwdGsTx7c3E/RF2Pti7XxOUSA4oxnXQdHYSOeDD1J9x3vnfG4CgUAwEkKgEAiSkESb0TG6eMQx24wYjOKtPllkgwRa/3Md6Atjc5kTrSI3XF084bHS8/Q747WHO2iq7J7xuc40cYHCbJ2Mg6JrQTooxsOeapmxVqN6i9GJOZTKN2RRsNzDxmuKx3VCLWQ8CYFCF+tMZgNLNmRyfEczQW8EV4aVAy/X4e8NjzWMQCCYJfozKEYXKLxbXiewbx+aogzbXiAQCOYacdUiECQhE3VQCKZOXNSJ51D4+yLYUswUr0zn9m+eQ9GK9AmPFe8m8c/7D/O3H+8lHFzYTopowkEx8ZiiZHRQANhdZvy94YRTZrLs31zHm387BegOClf6xEJoZYPMTZ9fz4oL86a034VCdqkLSZbIX9YvTi07LxcAi8PIOz65hmhE5eCr9fM1RYHgjCbRxSMwukARPHEcNA2lp2fO5ycQCARDESGZAkESoilCoJht+gUKFZPFQNAbxp1tQ5KlSWcFpKRbMVkNRMMqqqLRfKqHopUTFzjmmriDwmiemIataVrMQeGexVnNDvZUM9GwSiSoYLYZ2fbXSk7vbyM108Z1n1o77nvs2PYm2uu8yLKEvzeccNicKWQVu/jo/1w8KIQ0v8KNJ9dByap00vOdlK7J4NBrDWy4phjTkFwTRVGp3NVKWaw0RCAQzCxxB4U6pItHXKBQ2vpbLSsdHRjThoc/CwQCwVwiHBQCQRISd1BI4h08axiM+oVpPCgz7qCYCpIk8fYPreCd96xHliUaTnTP1DRnhcgkHRRaIIAWDielg8KRqgfIxcs8Tu5uoa8jSO3hTvo6AmNtiqZp9Lbp6+x6rpq0PAcrL5p+N5BkY2iHFEmWuP2b53D+LXqr0XVXFhL0RTi+vXnQepqm8dqfjvPS74+w6/nquZquQHBGEXdQaMH+UjZNVYm2t2PMyhq0brSjc07nJhAIBCMhLm8EgiQknosgTyCDQjA15JiDQlU0ohGFaGh67RJL12aSW+4mq8RFw4mZ6RoxWyQEiglmUChd+vEYkzGDwqWLTv7eMJqq4e8Ok7tEb8/b2eQfc9uQL0o4qLD03GzKN2Vx4+fWYXWKlpqgu7skSf98yi13k5ppo+ZQx6B1jm5r4ujWJmwpJg691rDgS58EgmQk3sVjoINC6e6GaBTb2rWD1lW6hEAhEAjmHyFQCARJSL+DQryFZ4tEiUdEJeTXL5ys9ulXxeUvc9Na07egL8YSAsUESzyi3d0ASemgsKfGBIqeMAFvBFXVKFiuW5y7mnxjbtsbc1gsWZ/F1R9dlXBjCAYjSRLpBU66WwYLPsfebCItz8F1/7KWcCDKsz8/wOuPnphyHohAIBiOZDQimUyDHBTx8g7bOl2gkCz6Z5dwUAgEgoWAuLoRCJIQVWRQzDoJgULpFyjMMyFQVHjQVI2W073THmu2iIQUDEZ5zHaZA1G6ugGSsovHwBIPb5ceIpeW68DhttA5jkDREyvvcGWcWbkTU8GTY6enLdBfMtUbpulUD0vWZ5Jd6qLi7Gw6Gr0ceLmernGcKwKBYHJIVuugNqPRVl2gsK5cBbKMbf16kCSUTiFQCASC+UcIFAJBEqKJDIpZJ14+o0Y1wgFdoLDYp2/fzyjUAzbHu/idTyIhZVKBhUoSOygsdiOyUQ+49HXrdxgdbgueHPu4Doq+Dv2Ef6KtRc9kPDkONFWjp1UXdar2t4EGZev1GvirPrKS2/51EwCNJxd2CZRAkGzIVivagBKPuIPClJeL46ILSbnySgxuN9HOjtGGEAgEgjlDXN4IBEmIpt+EFBkUs4jB1N/FI+6gsNim76CwOk1YHEa6mn2c3tfG33++H1VRpz3uTBKdrEARy6BIRgeFJEl6q9GewQJFWq6DzmZ/QgwciZ72ALYU07CQSMFwPDl2ALqafSiKyvEdzbgyrKTnOxLruDJsONwWGk52z9MsBYLFiWSzoY5Q4mHMzKToN78h7X13YkhPQ+kcLg72vvACgX375mqqAoFAIAQKgSAZ6c+gEALFbDGwzWgoEAH0u+3TRZIkPNkOupr9nNjZTM3BDqr2t4+/4RwSCSkYp+KgcLlmaUaziyPVopd4dIeQJLC7THhyHURDCt7u0Kjb9bYFRHnHBHFn6wJFe72X535xgKbKHtZdWZQI0gT9vZFX4abhRLfIoRAIZhDZYhnmoJCdTmRb/+eX0ZNGtLODwIEDRBobAdAiERr/7eu0/eIXcz5ngUBw5iIECoEgCVFV/Y67yKCYPQyG/jajId/MlXiAfje5q8VPS7WeQ7H3xVpe/eMxjm5rnJHxp8ukSzy6upBTU5GMyekksLvMiRIPu8uMbJBJy9Xv7B/Z2pgo8RlKb0cQV7oo75gIZqsRp8fCvs111B7u5NL3LmP1ZQXD1stf6ibQGx4WqCkQCKbOUAdFuLYGU8Hg958hPZ1oWxu1H/0YLff+AIDAwUNofj+hyso5na9AIDizEQKFQJCEaIpwUMw28RIPNaoRil2gmm0Tv2gfC3eOnUBvGG9niNRMGy1VvRx+vZGdz1QtiDvHU8mgMLhTZ3FGs4s91ZIo8XC49dDMjEIn7mw7u56t5sn/2ZMId4yjKirejqBwUEwCT46daEihaGUaqy7JH3GdvAo3AC1VCzdEViBINmSLBS3Q76AInzqNpaxs0DrGtDQiNbWovb34d+9G0zT8O3cAEG1sQvEu3NwkgUCwuBAChUCQhKjxDAohUMwa8Q4WSlQl7I9iMMkYTTMjUHhy+uvuL759KasuyWfN2wrwdoVore6bkX2Mhqqo7Hj6NM2ne0ZdJxKerEDRhdGdfPkTcVzpVoK+CO313oRAYbYaee93zuXtH1lBe52Xt/5eNWibtjovqqqRlucYaUjBCKTlOZEkuOCW8lHXcaXrgk9fZ3DUdQQCweSQbP1dPNRAgEhjI+byJYPWMaSlJX5WOjqI1Nbi27EDYmVY4VPCRSEQzCYBbxhlgWWSzRdCoBAIkpB4cJ8IyZw9DMZYiYeiEvJHZiR/Io4nVo8vyXrN/aXvXcbZ15UiyxKn9rTO2H6Gomkarz1ygl3PVfPCbw4lnCFDiQQnJ1BEu7uTsoNHnIqzs5EkCPRFcMYECtAzEZaencPyC3LZ84+aQZ1Xag51gASFK9JGGlIwAhuuLubme9aTnu8cdR2DScbmMuMVAoVAMGPIVhtaSH9PhauqQNOwlA0WKIzp+meZ7NTfn743txPYsxfnZZcBiDIPgWAW0VSNP31nB/tfqpvvqSwIhEAhECQhIiRz9kmEZEb0Eo+Z6OARx5VhRTZIpOU5MJl1IcDqMFFwlodTe1tnrczj6LYmjrzeSMWmLPw9IV76/RHaagc7NjRVP97JCBRqd09SCxQpaVZK1mQA4PBYhj1+wS1LMFoMbP/bqcSymkMdZJe4sDnNczbPZMfuMpNXMb7TJsVjwds1ejipQCCYHLLNiurTc11Cp/TPMcuSwSUeBo8uULiuvw7Z5aLtvvvQQiHc73k3ksVC6MTJuZ20QHAG4e8LE/RG6Gj0zvdUFgRCoBAIkpCEg0IIFLNGXKBQFb3N6Ew6KGSDTMnqDMo3ZA5avmR9Fr3tQdrrZ+YLqqmym9f/coIDr9TRVNnNticqyS1P5e0fXsm5N5VRe6iDx77/Fq01vWiahqKoHHi1nqA3Ql75xDMllJ6epM6gAFh9qR4YlzJC6KXNaWb924uo2t9OY2U3/t4wrTW9FK9Kn+tpnhE4PdY5L/HQNC0h/AoEiw1DRgbR9nY0TdMFCoMBc3HxoHVMOdkAOM6/ANv6dSgdHbiuuw7npZdiXlKG9/XXqb7jvQSPH5+PQxBMAS0cJnDo8HxPQzABvJ2hQf+f6SRn5LpAcIajipDMWUc2Duji4Y9id83snfJrP7F62LLSdRm8+ie9zCOzMGVa4+96rpodT59GNkiJ14ssS1z63mVIssTGa0o464I8Hvq3bZzY0cLx7c0ceq0BgOLV6Sw9N2dC+9EiEVSfDzlJW4zGKTjLw02fX0duuXvEx9deUciRrY1sfuAIxaszQEMIFLOE02Oh7mgnmqYNakM6m7z+6EmOvNFIfoWbi29fijvLPif7FQjmAlNOLlo4jNLZSfjUacyFhUjmwd9p1rVrKbz/tzjOPx8AyWAk9//9B5IkYSkvp/fpZwDofPAh8r733Tk/BsHkabvvPjr+77eUPfM0loqK+Z6OYAy8XbooL/KXdISDQiBIQtQkc1AoPT20/+rXaGryhP8MLfEwz2CJx2jYnGbyKtyc3ts2rXHCwSh7/llDyep0Pvo/l/CB713AZXcu4+q7V5Ge11//b3eZKVyRxom3mjn8eiNZJSmUn53F5e9bPuELQ6VPLxExpLqnNef5RpIkCpanJf7uQzFbjVz14ZX0dQQ5+Eo9Z12YS2bR9EQkwcg4PVYiIWXU9q4zTWtNLwdfrSerOIWWml6e/NEeuppnr2OBoqi89WwVT/xw95wdo2B67Hhm7GDhhY4pVxecI03NhE6fxrxkybB1JEnCeeGFSLKM6+qrKPzFz5HtulCXcuWV2Ddtwnn55fS98AKqX7QBXuhE29vp/MMfAeh+8m/zOxnBuMTLGn1dIeHmQwgUAkFSEi/xkJIkJLNv88u0/e//Ej51avyVFwgJgULRu3jMZInHWCxZn0lXs39aZR6Vu1uJBBU2XF2MyWIgJc3KyovzKVuXOWzd8o1ZBPoiKIrKFXet4O0fWokjdXgOw2go3fpJuyE1uR0UEyG33M2VH17B5e9fPikRRzA5nGn6628ucihC/giv/OEY9hQz139qLe/84gaiYZXdL9TM2j5f/cMxdj5TRVNlDzWHO2ZtP4KZQYmq7Hq2mhNvtcz3VKaMMTsmUNTXE66pGdZidDxcV11F8R8eJv3DH0L1++l78cXZmKZgBum4/3dooRDWlSvpeeZptKgQQxcycQeFqmr4e0SZhxAoBIIkJOkcFF1dAKjB5PnQjXdIUaKqHpI5VwLFhizMNiMv/OYgvkl+SWmaRku1fjfYk2MnZ8n4uRClazIwmGSWrMvEnT15W7vaGxcokjuDYqIsPTuHFRfmCXFiFklJ03NAZtvqGvJHeOKHe+hs9HH5+5ZjthlJz3OSU5Y6YzkwQ9E0jZrDnZRvzMLqMFF9sH1W9iOYOQJ9YQCC3sg8z2TqxB0U/rfegmgU85LJCRRxbBs3YszLpe+lzTM5PcEs0Pfiizgvv5z0T3wcpa0d7+uvz/eUBGMwUJDvEzkUQqAQCJKRZAvJVLo6ARJtzpIBSZKQjRIhbwRN1bDYTHOyX7vLzA2fWYuvJ8zrfzkx4e00VePVPxzj8Xt30V7nZf1VxRO6iDbbjNz6lY1c9r7lU5qv0nNmCRSC2cfpmRsHRdX+djobfVz78dWJLi4A6fkOupp8s9KP3tsVItAbJrfcTfGqdGoOdQg77wLH3xsTKHzJK1AY0tKQTCZ8W7cCYFlSPqVxJFnGumw54ZrhDiNN0+h67DEiDQ3Tmqtg+kRaWojU1+M452xSLr0UY24u7b/81ax1CBNMH29XEFss66yvMzDPs5l/hEAhECQhyRaSGU1CBwWAwSDjj909mysHBUBOWSpL1mXSVNkz4ROK1/9ygiNbm1j/9iLu+v4FnHVB7oT3l1mYgtUxNQFG6e0FSPqQTMHCwZ5qQZIlvJN0UGiaRvXBdjY/eISW6t5x12+p6sVkNVA0JOw0Pd+Jqmh0t8x8nX1rjT6vrJIUilenE/JFaUnibIMzgYRAkcQOCkmWMebkEK6uBsBSVjrlscxFRYTr6oZ9NwX27aP5m9+i+o73JlqZnqloqkrTN7+Fb9u2edl/YM8eAGwbNiCZzWR++tMEDxyg75+iNGeh4u0KkRtzvYpOHkKgEAiSElXVksY9AaB0dQPJ5aAAPYci0KeflM6lQAH6BYy/N4yve/wvqhNvNXPwtQbWXVnIBbeW4/QMb5U5WyQyKNzuOdunYHEjyxKOVHN/aFh3CFVR6WjwsucfNQkH2VBO723j2Z8f4Nibzez95/gZEi3VvWQVu4Z9lqbn60GyHQ0zX+bRWtOHLEtkFDgpWpmObJQ4uat1xvcjmDkWg4MCwJSjl3kYc3ORHY6pj1NUiBYIEG0bHObs27oNZBktHKbl3h9Ma67JTu9zz9P92GN0P/7Xedm/f/ceJJsN63LdGZl6802Yy5fQ8r3vEWlunpc5CUZHVVR83SE8OXYsDiN9Hcl1rjwbCIFCIEhCNFVLmoBM6M+g0ELJpQrLRilxcmqea4GiWHcktFb3jbqOrzvEP357iM0PHiW3PJXz3zk8mX22UeIZFCmio4Vg5nBn22mr66OnLcBDX9/G4z/YzZM/2sObT56irW7k90R3q+54qDg7m5rDnUTDyqjjR8MKHfVeskuHO388OXZkWaKjYXgnj+4WP//47SEOvlo/peNqre4lLd+B0WTAYjOyZH0Wx3c0ExljroL5JZFBkeQChTGWQzHZgMyhmIuKAYjU1g5a7nvjDayrV2E//7xhj51JaNEo7ffdB0DgwIEpjRHt7JxWOUZgzx5sa9YgmXRnpGQwkP/DH6J6vdTd/XG0cHjKYwtmHn9vGE3TO1ilpFnp6xIChRAoBIIkJOkcFJ16BkXSlXgY5YRAYZmDNqMDySh0IssSLTWjW9VP7GyhclcrKy7M45q7VyMb5v4jXenpQXY6kYxz+/wIFjclqzPobPSx54VqVEWjryOIyWIAoOFE94jb+LrDmG1Glp+XQzSkUHesa9Tx2+q8qKpGdslwgcJglHHn2Okc4qCo2t/Gn//fDip3tbL1r5WJ1PWJomkabbV9CfERYNUleYQDUSp3JW+HiMVO/DsgElRQosnTKnsoplgnj6kGZMYxFxUCEK6tSyxTensJHDiA88ILMWXnEGlpOWPzDnxbtxKuqcG2YQOR+nqisfOfiRI4eJCTF11M6733Tuk59O/eTfDYMewbNwxabl2+nJxvfZPQiRMEDh2a9LiC2SPuFnR6LDg9VnrbhUAhBAqBIAnRFC1p8icAot3dQHKWeIQDemuuybTenAmMJgNp+Q5aY7X0PW1+etsHByf1tgew2I1cescy7LFwpblG7ekVAZmCGad0rR5aeWRrE9mlLt7/3fN573fOw51tp/HEyMKDrzuEw20hf5kHs9XA6X1tI64HJN5XIzkoQC/zaK/3Ji4Qag938ML/HSKjIIVbv7oRTdN482+nJnUB0dMaIOSPklXc7zbKLXfjybFzaEvjhMcRzC2B3v67zcnsouh3UEzPaWfKywODgXBtfxmV99VXQVVxXHghptwctGAQJfa9f6YRDxBN++BdAHT96c+cvuGGcUsrFK8PLRKh9+9/B1Wl88GHaPne98f9jNE0jb5XX0UNBPC9+SY1d30QU2EB7ltvHbau44ILgKk7OwSzQ7ykIyXNSk6Zi64mH32dQXY9V03dkckJXIsFIVAIBEmIlkQOCi0aRY11ekg+B4X+HDtSzTjccytQAGSVuGir7UPTNP7528M8+aM9hAL9vcx7OwK4MmxzPq+BKD09yKkiIFMws7gybGQU6lkQ5RuzMFuNmCwG8pa6aTzZPWLnC293CKfbjMEoU7Yuk8rdrfS0BXj25/s5srVfAGip6mX3P2pIzbKNKjzmL3Xj7QrRWt1H/fEunvvVQdJyHdzwmbXklKay7opCTuxo4fF7dyXusI9H0yn9czB3iTuxTJIkVl6cT2t176ilKzPN6X1tPHPfftE9ZIIM/PvOdlCmpmrsfOb0hLKHJou5WC/NsC5fNq1xJJMJU14ekZiDwrtlC03f/BbmJUuwrVmDMebUiLacma6gSGMTks2G88ILQZZp//nPCZ2sxPfGG6Nuo2ka1e96Fw333EPviy/ivOwy0j74QboefpjWcfI8Anv2UP+JT9L50MN0P/5XDC4XpY8/jik/f9i6xsxMjHm5BIVAsaDobvWDBKmZNpZsyAL04PMdT5/m77/YT/3x0d2AixUhUAgESYiaRBkU8TaUkJwOCtCFgvkgu9hFyB+ls8lHe70Xb1eIbY+fTDze2x5cEAKFcFAIZoPyjVnIspQ4YQNdOAgHFdpjF/O+nhBHtzUS8IYTDgqAjdeWoEZUHr93F9UHO3j1D8eoPtiOtyvIUz/Zi8ks845PrBl935uyMZpkdr9QzQu/Pkhqpo0bP7cu0e3m3JuWcPn7l9Na08exN5smdDzNp3uw2I14cuyDli87LweDSebw63Pjoqjc3Urt4Q6aT3XPyf6SHX9vOBGSPNsOip62AG89W83JWSj5cVxwAcV//hO2deumPZa5sJBwLGei5d4fYCosoPjhh3TxIubUOFPDGCNNTZhycpAdDiwVFRBzQPh37xl9m4ZGwtXV9L34EtHGJlKuvpqsr34F92230fngg0RaRg/S7X7ySQB6n38e7xtv4LzkkjEzoWyr1xA4cHCKRyeYDbqa/aR4rBjNBtxZdjIKnVTtb8eWYiI1w8bmB4/M9xTnHCFQCARJiKpqJImBIpE/AaAGk0ugiGc6jGYDn22ySvSTjOPbm1EVDU+ugyNbm+htD6CqGr0dAVIz565jx0govb0YXEKgEMw8695exB3fPpeUtP7XeH6FB4Cq/e1U7W/jwa9t4+WHjrH/pTr8PaFEBxt3tp0VF+cR9EVYfXkBGYUpvPCbQzz/q4OoisaNn1tPWt7onQwsNiNl6zOp2t+OElW59hOrsTn7y6hkWWLFhXl4cuyjZmIMpelUD9mlqcPK86wOExUbszixo3lOWlm21erizqm9o5fACPrx94Xx5OivldkWKOJtrWfDQSFJEvb162dkLFOx3mpU9fsJV1XhuuZajGlpABhj3UKiZ7JAkau3+XZefhnWlStxXHpJovXnSAT27Ab0DisYjaS87XIkScLzvjsB8L3x+ojbqYEAfc+/gGy3Ezp2DLWnB+dll445P9uaNVPKxhDMHt0tftwDhOvyjboov/aKQs66MA9vZ4iA98wKNhUChUCQhGjKzDsoNEWh/de/GeR4mAmiXf3WNC2UXB+wBpP+HI8UpDcXpOU6MJrkxB3aeJeOmkMdeuvFqEZKunBQCBYnBoOMO3uw28DhtlC6NoODr9bzxuOVuLPtuDJtVB/qQNMYVIp1/s26y+HCW8u54TNrSct10FrTx9nXlZCaOf77ZsVFeQBccEs57iz7iOvkL/PQVNmNoowdnhj0Rehq8iX63A9l7ZVFKFGVzQ8eGbWN6kwQDkYT3U5O720jHIgmdfDjbKNEVUK+aELMmm0BKd4xxDsLAsVMYllSjtrTo2dPaNqgshFjRgYYDKM6KFr/58c0fec7sza3cH09Lff+gPrPfJbIPJSZRJoaMebpAkXW5z9PyeOP4TjnHMI1NUQ7Okbcxr97D3JKCiWP/Jmi392f+E61LF2KMTsb75Z+gUINBGj+j//Av3cvXY/8BdXnI/vrX9cfNBpxXHjhmPOzrVkNiByKhYKmaXS3+PEM+K5bcVEe695exOrLCkjP1z97RuoqtZgRAoVAkISo2sxnUAQPH6btxz+m+69PzOi4Sld34uekK/EwyCAxKHV/LpENMhmFKQT6IhhNMsWr0nFn26k+0J4IzEydxxIPTdNQe3owiAwKwRyy8ZoSQv4ovW0Bzr+5jNwlqXTU6x03BgoUZpuRFRfmYTDK2FLM3PyF9Vz1kZWse3vRhPaTv9TD+//zfFZfVjDmOpGQknAljEZLlR7KmTOKQJFR4OTCd1VQfbCDo9smVjIyFdrrvaDBkg1ZeLtC/PaeLWx+8Ois7S/ZiQsGablz46AI9Onj+7oWtkBhP3sTAJ0P/wEAy/LlicckgwFjVhbRppEFir7Nm+l99jk0dXaEsY7776fzwQfpe/FF+jZvnpV9jIYaDqO0tSccFKA7V2zr9Y4a/j178L/1FicuvCgRpgm6g8K2fh2m7Gwc55wzaFvnJRfj27oVLaK/NvpeeomuP/2Z2g/cResPfoDjootIfefN2NauxXH++eO2/LauXIlktdL9yF/O2E4rC4WmUz10NfuJhJRBYrzNaebCW8sxW42k5+tZTPHvuDMFIVAIBEmIOgtdPOJ3O3xbt87ouErcQWE0Jl1IpjXFRGZhCuY5bjE6kHiZR3qB3na0eHU69Se6Emq6a55KPLyvvUb9v3wKLRIRDgrBnJJd6qJkdTp5FW5K1mSQWdh/Qu4cI8zWbDNScXa2LjxOkPEyXvIq3ABse7ySlx8+OmrwZP3xLmSDNKYba/Vl+aTlOTi2ffYEiriQcu6NpZStzySjMIXT+9oIB6PjbHlmEg/ITEm3YjTJwxwU0bDCwVfrZ8yFknBQLHCBwlJRgSE1lcDevchO57BARlN29ojuBS0aJVxbi9rXN+gCfSYJV1VjW7MGQ3o6wTnOWogHg5py8wYtt67SRYGuhx6m6dvfQenoSDgYlO5uQicrsW/YOOKYjksuQfV68e/aBUDv8y9gzMrCft55uG68gYJf/BxJlin87f+R/+MfjztH2W4n6wufx/vqq/Q8MbM3pAQTR4mq/O1/9vDcL/TXgTtnZJeezWnE5jTR0SAECoFAsMCJhlWMZsPMjtmsf7H6d+2a0awIpUuvczRlZaElWQbFxe9eyvWfXjuvc4i7NzIKdBW9dHUGalTj0Gv1SBI40+ZHoOh97jm8r7wCgCwECsEcc+0n13DTF9YjSRKZRf0CxVx327G7zGQVp9B0uoejW5s4PUquQ+3hDvIq3Jgso39uS5JE+cYsmk71zEoGAUB7bR92lxlPjoNrP76aC28tR4mo1B4W9egjEe+8YneZsTpNwxwUh19vZMsjJ6g7OjPPX8JB0R2a1VKf6SLJMraYi8KyfBmSNPiGiTE3h0h9PZ0PPTwo6yBSXw8xJ0Dw0OFZmVu4qgpzaSm2VasIHJpbgSLSqIuLprzcQctls5mc73wb/+7dhE+f1ucZCxkNHtEDEG3rRj7XcF50EQaPh44HHkDp7cX3+uu4rr2Gov/7Dfn/9V/IZj0bx5CSgsE5eq7OQDzvfz/WtWvo+N3vJ3+QghkhElJQFY2eNt0N68keWaBo/9+fYO+sEgKFQCBY+ERCCqYZFigiLbqDQguF8O/ePSNjhuvrCTc0IDscyCkpqKGFfVdoKFaHCbvLPP6Ks0hOWapeZhK785pbnkp2qYuuZj/ONOuk7gbPJMETJ5Fd+pxMsVA0gWCukGUpUeYWb0cqGyRsTtOcz+XGz6/nI/99MamZNva+WDvMNt3XGaSz0UfRyvRxx1qyPgu02QuwbKnuHSTo5Fa4saWYOLV39C4BZyond7XwxmMnyV/qJqs4BYvDhK87xOm9baiKiqZqHHytHtBD7obi6wnReHJy7QHjDgpV1RKBmQsVx9lnA2BdtnzYY6ZsXaBo+d736PrDHxLLQ6erEj8HDx2a8TmpPh/RlhbMJSVY16wmfOo0inf2a/c1TaPxX79G92OPASN/J7pvvpmCn/2MrH/9Ksbs7ESb1lB1NQDm0rIRx5ZtNtLuugvfa1to/s530CIRXNdeO635SrKM49zzCFdXo4UX9utssRIJKYmfjRbDqOK6b8cO7K0n6Wz0nVGtoYVAIRAkIdGwgsk68w4KY2YmksmE97XXpj2e4vVy+vob6Hn8rxg8HiSLJekcFAuB1Ewb7/n6OSw/Tz/hkQ0y1396LekFzkEXGnOJFo0SPnUK97veRdnzz40byiVY+GiaRlNTE+3t7fM9lUljthpxZ9txpFpmvPRtIlhsRqxOE+uuLKS1upf6o4MvSmsP68F4xavGFyjS8hx4ch2cngXBoKPRS1ezf5BQIssSpWszqTnYQTSiDNtmxzOneePxk2dkrfqef9SQnufkuk+vRTbIWB0m6o528fyvD7L3xVpqj3bS06rf/eyO/R+nu8XP4/fu4skf7eXw6w0T3mdggCgxWy6amcJ+3vkAWFevGvaYuVjPeZGdTvx79iaWh6t0gcK8ZAmBw7pA4d+9G++WLTMyp3jZiLm0FNvq1aBpBA/PjlNjIKHjx+n529/o/fvfgf5OJkNJedvlpH/wg5iLihIOikhNDZLdjjErc9TxPXe+Fzklhd7nnifl2muwrp2+s9OypAwUJTGP+UCLRmn9nx/PS5jpfBMJ6p+37mw7JavTh7mQQA+vD504gcNbTzSi0tM6XAhdrAiBQiBIQqbioFDDYdp/+UtU/8gfcJGWZswlJaS8/e10/fkRAgenZ40MHTuGFgxiXb0a17XXIlssaEnmoFgoZBQ4Ey1PQXd23Pa1TVz90ZXzMp9wbS1aOIxlaQWW0lIkWXyVJDPBYJD777+fX//61/z+978nPOSOmqqqPP744/zkJz/hL39ZmMFqy8/PYcmG0U/w52YOuaRm2XjpwSP4evo/62oOdZCSZsUzSo3xUAqXe2ip6Zvxu2Un32pBkvpb2MVZsj6TSEihLiasaKqGryeEryfEnudr2P9SHTufqRppyEWLrztEe52XirOzEt+1cXeO02PhrWereel3R3C4LWQWpQxyUETCCk//ZB9KVCV/qZtX/3SchuOx51bTqD/eRTQ8XAwCCHgjiba6Cz2HwrpsKSWP/oXU668f9ljqLbdQ+tTfSL35ZgL79ycCHkNVpzGkp+O44AKCR46i9PVR/7nP0/SNb87InEJxAaSkBOtqvVtF8ODUulV4t2xJjDceiewugwFDejqydezSy3ibVtAdFOaiohEvUOMYUlIofvABSv76OAU//vGY604Uc5neFSwUKzmZDwL79tHxm9/Q+9zz8zaH+SLuoLjwXeVc/dHhIh/ogpsWDOLpPoEkwcFX6udyivOKOKsUCJKQSEjBaJnc29e/8y3afvJTev/5zxEfjza3YMzJIedb38SYmUHDPV9EU4afRKk+36gix0CCR/Rk+IKf/YysL96DZLUmXYnHQsZgkAeJFnNJ6MQJAKxLl87L/gUzywsvvEBDQwMXXHABPp+PnTt3Dnr81KlTHDp0CKvVytGjRzkSq5meKUKhEK+//joHpyGKbrymhAvfVTGDs5o8RrOBa+5eTdgf5dHvvcXuF6rRVI3Gym4KlnsmfFGRUegkGlLobQuMv/IECPSFObmrhZNvtVCw3DOsbC1/mQeL3cjpPbprY8czp3nwa9t47U/HUVWNopVp7HquGm/X4nDAqarG1sdPUnekk+5WP289W5UQA4K+CAdfref0Pr3EpmR1RmK7sy7M5dwby7j1KxsxGCRsLr0zTFqeY9Cdzb3/rKWvM8g1d6/iuk+vxem2sO3JU2iaxptPnOKpH+/liR/uGfH5DPSFE864he6gALCtWYNkHB4iLVssWJctw75hPVogQPDwYUKnThGuqsZcWoJ90yY0v5/q99yO0t5OtLV1Ru6ih6uqQZIwFxdh9Hgwl5TQ8/dn0aKTC4EN7N9P3d0f5/S176D69jvoeeaZMdf3vvEGlooKsv/ta7jffdu445sLi1Da21G8PiLVNZiLi8fdxrpiBbaVM3dTwlJWCpDIxJgP/Lv36HOonZ3A1IVMJKS/JsfKJQodOwaALdjJkhw/h99oTHRwW+wIgUIgSEKi4ck7KKKxjIngCL2vNVUl2tKCKScbg9tN5mc+S6SujlDlqWHr1n38E9Tc9cERxYuBBI8exZCenrAtylZR4pHsaIpC30svEdh/AGQZc9nINbOC5KGyspJ9+/Zx0UUXcdVVV1FeXs7WrVsJBoOoqoqiKOzYsQOn08mHP/xhsrOzefHFF4lO8oR/NNra2rjvvvvYvHkzf/3rX3n55ZdnZNz5IqPAyQ2fXYcnx872v53m5O4WQr4oueXuSYyhX6C21Y3dunSi7Px7Ff/87WF624MsPWe49dxglClZk0HVgXa8XSH2b65DUzWq9reTv9TNOTfo7/Pm070zMp/5pr2uj30v1fH3n+3nse+9xc5nqvjjt9/kxM5mXvvzcbY8coI3Hj2J02MhLa8/dLBoRTqb3lGC02Plzv84n/f829m4s+24s+x4u0JEQgrt9X3s/UcN5RuzyKvwYDIbOPu6Ulqre3niv/ew98VaStZk0N3q55+/PTzIjaSqGgFvBE+uHdko0XCim/0v16EqY3cIURR1QbqaAGwb9PaadZ/6NKevu57A3r1YSstIuertpH34w4RPn8Zcql8oB0Y4N5ks4epqTHl5CQdD5he+QOjYMToffHBS43T96c/IDgeZX7wHpa+Pxi9/Bf+ePSOuq/r9BHbtxnHRRaTdeSdZn/vcuOPHS2DC1dWEGxomJFDMNLLDgTE3l9CpeXRQxJ7TyCx1dFnIxB0UZuvoXeKCx46D0YhkNrPMVAkSHNoy8ZKxZEYIFAJBEhIJKWOqriNuE2sjGtg//CRA6epCi0QwZusnr/YN6/V19+6l4Ytfounf/x2AaHs7/l27CB48SHesPVWksZFIw/APzODRo1jPOitx11Cy6A4K346d9Dz99KTmLlgYdD78MPWf/gydv/895uLicW2sgoXPrl27cDgcXHrppQBcfvnlBAIBtm/fziOPPMK9995LZWUlmzZtwmQycfnll9Pd3U3VBK3PYxEIBHjkkUdQVZUPf/jDrF27li1bttDamtyBjXkVbq76yCqQYMdT+sl/bvnEO92k5TqQZYn2Gep731TZTe6SVG783DqWnjtybXzZukxC/ihP/mg3SkTlHZ9cjSfHzoZriskocGIwyrRU9czIfOab+li5RXaZC3e2nZvvWU9WsYuXfn+Eyl2t5JanoqoaJaszRnW92F1mDCb9FNodS98/vqOZJ3+4B4vDxAW3lifWXXZ+ju6yaA9w9nUlvOMTqzn/5iU0nepJlH4AhHwR0MDusuB0Wzi1p5U3Hj3J5oeOjtrRIxyI8sBXt3L49cYZeW5mGlNODqa8PJSODhwXXQSqinXVKiRJIuvLX6Lw17+i6MEHwGSakZag4aoqzCUlid9Trno7zre9jbaf/yJRZjIe0a4uep9/ntSbbiTjYx+j9LFHkV0uOh96eMR1W75/L1okMqksJnORLlD4t78J0ei8CBQAlrIywqf0G1HB48fxbd8+Z/vWVBX/vn0AhGvmLwdjvogLFGOdywePH8NSVoapsBBj0ymcHuuCL/2aKUaXbQQCwYJEUzW9zegkBYp4G9Hg8eOoweCgi8u4eGHKydb/LyrC4PHQt3kzvjfeACDt/e8nsHef/nhBAW0//l9c115L7cfuRjIYKHv6qcR4ajhMqLIS58UXJ5ZJFjNaMEjnQw8RPHCA1BtvnPzBC+aNSGsr7ff9DEtFOaHTVVjPGp7cLkgu/H4/J06c4JxzzsEYs2nn5+ezbNkyXnvtNTRNY8mSJUQiETZt0lsKlpaWIkkSdXV1VFRMvaRCVVX++te/0tXVxV133UVRURHp6ekcPHiQPXv2cM011wzbpq6uji1btvDud78bk2nuu3VMBrvLTHaJi5aqXmwuM6mZtglvazDJeHIdtNdNXqAIB6NU7WtDA5afl0vIH6Gj0cc515dSeFbaqNsVr0pnzeUF1B3rYt2VRZSuzaR0bX+mR2ZRCi1Vi8NB0XC8G3e2nVu+tBFN05Akies+lcKzPz9AJKRw0+fX01TZPeEQYne2/rfd8ufjpKRbufmeDYkcCdDL8d799bORpP7OM2ddmMuu56t5/dGTlK3LZNUl+QT9+gW0LcVEWp6eO1S8Op39L9Vhthi55I6lSJKEvzeM1WlCliWqDrQT9EY4+VYLqy7Jn+FnambI+NSnUHp7Sf/QB4m0tGLM0ENaJUnCGRNGrcuWTTv3StM0wlVVpN5yS2KZJEm4rnsH3pdfJnT6NNZly0bdtueJJ0m58gp6/vYUWjiM+/bbAZDtdty3vYvOBx4k0tSEKbe/hWjTN7+J9+VXcN92G47zzp3wXE0xgcL7un5+ZS6ZH4HCvKSM7sceR1MUGj7/BSKNjSz5xwuz3pkr2tZG8Ngx1J4eTPn5RJqaUMPhRMvUM4GJCBSho8ewn3cuak8v4bp6bAXDWx0vVoRAIRAkGZFYuNZkSzzibUSJRgkeOYIxM5P6f/kX8n74Q6Kx2k9jti5QSJKEbd06vK+8om9jMtH+q1+hBYIYc3LI/58fUf3u99Dw2c8l1PfQyZNYYhcsoZMnIRrFuuKsxP7lmINC6eoi2tY2K19GoZMnkR0OTHl5MzquADr+77do4TAFP/sZSp83cZIpSF4OHz6MqqqsHZIIf/nll3P8+HHKysq48847kQeEoFosFnJycqidZvL7Sy+9RGVlJddffz3FsbuHDoeD5cuXs3//fq688sqEaBLnzTff5OTJk9TU1FBeXj7SsAuK0rUZtFT1krckddKhdhmFTuqOdg5brioqjZU9yDLkVXiGPfb4vbvoatbzEHJKU+lpC4AGuUvGdnAYjDIXv2f0TJnsMheHXmtAiaq01fZxfHszF7yrfMbbXc82iqLSVNnNspiTJP53MVuN3HzPejRVQzbIFCwfXcwZSmqm7qDQNLjigysGiRNxhraDNpoMnHtjGVseOcHu56s5+VYLZ1+vlzrYUsxcc7fuwJFlCYNBYs8/arG5zJx1QS5//PZ2cspSuebuVZzcpX93N53qIeiLYHUsPOHOfWu/YGDKzhpxHdua1fQ89TSaqk45dDna1obq92MuLRm03LpiBQDBQ4dHFShCJ0/S9PWvEzpxHP9bu7CuWjUoYyntve+l8/7f0fvcc6R/5COAfiPG98ZWPHfcQc43vzGpuRqcTkwFBfh37ACYPwfFknK0QIDW//qvRIeVlnt/gPPSS3Gce86Mn0tpmkbXw3+g9Uc/SoSmp958M+0//zmRujosS5bM6P5Go+/lV+j+y18w5eeR8elPY0yb+Pt9phhPoIh2dRFtbcW6/CwijY34d+3CcqWRQO+ZIVCIEg+BIMmIhvV61MmWeESbmrGuXQPoZR4d999P6GQlPU/+LeGgiAsUALb1epmHuaSEtPe/n96nn6HvxRdxXnYptjVrcF56Kb5t2zC43SDL9D7/AqDnFHTefz9AIkUbQLJa0UIhlO7u2HyaJn/wY6BpGrUf/zjN//ldffyuLhq++CXafvrTGd3PmYgWidD77LM4r7gCc3ExtlUrZ/0Oi2D2OXLkCJmZmeQM+Vvm5OTwsY99jPe85z2DxIk4RUVF1NfXowzJoWloaGD37t0j7uvAgQMJUWPHjh1s27aNTZs2JZwZcTZs2EAgEOBYLBwMoLm5Ga/Xy/HjxwE9tDMZiDsQ8pZ6xllzOBkFTvw9Yfy9+r/uVj9KVOUv332Lp368l7/9z14qd7fSWtPLMz/dx6Pfe4sTb7XQ1ezn/FuWIBskDr5WT9OpbiRZIrt04iUmI5FTmooSUdm/uY5nfrqPQ1sakiZRPhpWePone2k82UVbTR+RkEL+suF/E0mSphQ8bLIYyF2SyvqrisibRNbIigvz+MR9l3HLlzfi7wvz8sN6sLQtxYTBKGMwyEiSxHk3L6Hi7Gx2v1DNzr9XoURVmk518+j33qLucCe55aloqjaioJUsWFevQfX5EhfJUyFcVQ0wqMQD9It/2W4nOEa4b+i4Hvzc9ZdHCR45QuoNgzuTmPLzMeblJsK/AQK7d6MFgzgumlqb7YKf/xxjdjaGtDQM6fMj+LuuuRpzWRmdDz6EqaCAtLvuou+FF2j62teo/dCH6Xv5FZr/87uogZkJZvRt2ULL976H/bxzyf63r5H5hS/gvER32s5VmYcWDtP8n/+PwL59dD32OI1f+tK4mWqzQVygGM0NHQ/ItC5fhrmoENXnw2qCoPfMECiEg0IgSDImYgsbcbuWFlKvvx61z0vH7+5H7dHtun0vv4xt3Vokmw3jgC9J2zr9rmrKVVeR+elPYcrPo+8f/8R9m55QnfHpT+N97TU873sf/rfeoveFF8j4zKdp/dH/0Pvc82R+8R7MBQWJ8eIhmUqXXnMbaWyc0bsGkZoaoo1NhJBQvF6qbrk1IYJYKipwXXvtsG3UYBA0Ddk2cfv1mUDz975HuLIS24aNZH76U/i2b0fp7Bx20iZIXlRVpbGxkdWrV494dz8/f3S7eGFhITt27KC5uTmxnqZpPP3007S0tJCTkzNo+56eHp588klcLhfXX389zz//PMuXL+faEd6TZWVlpKamsnfvXlatWkVbWxu/+tWvcDgcKIqC0+nk9Dymzk+GtFwHt31tE+n5zklvm1XiAqD5dA/HtzfTcKKLjdeW0Nno46J3V1C5q5V//N8hAMxWA+GgwisPH8OVYWXdlUV01Hs5tq0Je6qFzELnpL8vhpJTlgoSvPnkKVLSrGQUprDnHzWsuChvQnftVVWjtaaXlDQrjlTLtOYyWWoPd1J3tAtNA0+uA9kgkb/MPaP7uOXLG6e8bU5ZKjd+dh1P/2QfalTB5hzsLJQkiXNvLKNydyvHtjVRsiaDjdcU89IDR1BVjYtuq+CZn+7nyBuNOD1WMgqdSedsSbgcjhyZ0l10TVEIV1cDYImFbsaRZBnLirPGFihinam0YBBkGdc73jF8jsuWEzzeL5z6tm4FkwnHOedMer76eEspe+pvKD09M9I2dCoYUlMp+v3vaLjni6S9//04L70Ey9KlyDYrjV/9V+r/5V8AcF58UaIcZ6pomkbbfT/DVFBA4c9+hhQr04vftOr6yyP0PP00ed/7LrJ9Yi2ZB42vKAQOHMAeu7mmeH10/+URlJ5eUm+6MfG66nnmGaKNTRT+5tdEWlpo/ua3aPq3fyP7a1/Tb7jNEZGggtEkI0nQ+ac/0f3oY2R84hO4rrkaiAVkApbly1GDutvEpPgI+mYmoHqhIwQKgSDJSKiukzgBUX0+1N5ejDk5FPz0J9R84C60SIS0u+6i88EHidTVkfaBDyAZ+se0b9hA+ic/geeOO5DMZtLuvJO0O+9MPG5bvYrSp/6GpayM7sxMmr/9bbyvvELXn/6UCJcaiGTRba8DBYqZxLd9R2Jc72uvEW1qIv8nP6Hzd7+j6VvfxnnFFcNKSuo/+1nUPi/Ff/rjvJ0gLDTC9Q10PfQwhtRUfNvexHXdO+h55hlklwvHgEwRQXLT2dlJKBQaU4gYjaJY/fTp06cT21dVVdESKxV78cUXueuuu9i/fz/79u3D7XbrNd49Pfz5z38mLS2NW265BYNh+GeYLMusX7+eV199la6uLo4e1e9Y+v1+3G43GzduZPPmzfT19ZGSMrGMgPkkq9g1pe2yi10YjDL1x7uoO9ZJJKiw7a+VpOU5WHN5AcvOzeHYm01YnSaKV6Wz4+kqDm9pYPVlBciyxLorizi5qxVvV5DzX+IPBgABAABJREFUbp6+bdrpsfCur2xCiapkFDrpbQ/yl//cyZE3Gtlw9dhCc297gCd/tAdvVwhZllh1aT4Xvbtizj5zT+3TQ1frj3XRVNnD0nOyh4kA801OWSo3fX49VQfasKUMF3xSM20sOyebY9ubWXVpPjllqdz+jXPoavGTWZjCiovz2PNCDfXHdiPLEhffvnTBZlKMhKWsFMlsJnjkKKk33DDh7TRVpfGr/0ro2DEcF5yPZLViHMHdZ12xIpG1II3wuRM6cQJLRQWG1FTk1FSMmZnD1rEsX4Z3y5ZEhpd36zbs69cjOxzD1p0oBrd7Ti+KR8KUnU3JH/+Q+D1ekiM7HPj37aPjl78iVHlq2gKF95VXCB46RO53/zMhToD+HMipqfhe2wJA5/JlZHziE/Rt3kzzf36XsqefwjDCZ33g8GFa/vO7OC+5GM/7P0Dvc8/S/K1vU/CLn+O87DIav/xlvUxZkuh5+mlKn3wC2eGg/de/wbpiReJ8JtLYSMdv/g/v1m1kf+XL9G1+Gcd55+K5445pHe94hIMRDEqIU2+/ikh9PQa3m4bPf57oN79B2p13Ejp2DGNmJsa0NCzl+me40ddFJGRHiaiJkN7FihAoBIIkIxrPoLBOXKCItOgnaKbcHCzl5ZQ88mfC1dVYli2n88EHkcxm0j/6kUHbSEbjuO2y4vWcqTfeQNt999HwxS+hBYOkffCDw9aVLINPCCONM1vi4d+5I/Fzz1+fAFnGedGFaKEgjV/56rD6RsXrxbdNT9D2bd2Gc4o2zcWGd/NLABT8/GfUfOAu2u/7GX0vvUTqO995RgVYLXYaYwJh3hRqjF0uFyUlJbz22muUlpZSUFDAtm3bcDgcXHDBBbz44ovU1NSwfft2mmPlYytXriQYDHLq1CluuukmzGO8ltatW8err77Knj17EiLINddck8ik2Lx5MydOnGDjxo00Nzfz6quvctFFF1EwwLGV7BhMMtmlLo692UQkqODJsdPV7GfdlUVIkoTVYWLdlUWJ9S+8tZzMQifLztMvzjKLUrj7J5dgMMozJgRkl/aLLRkFTtLzndQe6RhXoIi3L738fctpOtXNgVfqySpxJXIgZhMlqlJ9oIOilWnUH+1Ciaqsv2p+6v3HI7vUNeg5Hsr5t5STVeKiKBZ2ajQbyCzUL9zOv3kJay4roKW6l/2b69j62EkKlntwZ03+TvR8IJlMWJYtI3j06PgrD6Dtxz+m95lnAFB6ejAXF4+YYWFdsQItENDPe0ZwaARPnsC+fgN53/8ejPJ+sS5bDopC6GQlptwcQkePkvmFL0xqvsmE89JLcV56Kd2PPU5ommV1qt9Py3e/h7m0dMSAdOvSpUSamjAXFdHxf7/FfdttdD74ENGmJgL7D4x4ftb+s58TOHSIwN69hKtrCMdalbbd9zP8O3bifeUVsr/xDWzr1lFzxx00fOEerCtXEKmtJee3v018LmZ97nO4rrqKhi9+icavfBXQxRTHRRdhLiyc1nGPhXffYSSfimXpUjI++UlSb7yBmvd/gK4//BHPe99L8NgxLMv1MHJTQQGS3Y7c2QyUEfRFcLjn1ok21yxu+UUgWIQkSjwm4aCItgzOmDAXFeG85BJM2Vmk3nwzGf/yLyPeMZgoss1G+oc+hBYIYFu/HutZZw1fZ0hLypl0UGiahm/HzkRuhu/NN7FUVOiBmbEvmPCQUD/ftm0QjSKZzbT/6pdo6ti95s8U+l58CcvSpdg3bcJ58cX0PvcckslERszqKVgcNDY2YjKZyMjImNL2t912GykpKTzxxBNEIhFOnTrFunXrOOecc7BYLLzyyis0NzezYsUKcnNzueSSS7j11lv50Ic+lAjFHA23281ZZ53F1q1baWhoYPny5RQWFpKbm0t2djbZ2dm88cYb7N+/n9/85jccO3aM/fv3T+k4RmLLli0LIucir8JNJKh/3l//6bVcducylp2bPeK6JouBlRfnYzT1fy8YTYZZdSkUrUijqbKHcDCKEhn987OzwYvFYeSsC3O5/P1nkVOWyut/OUGgLzxrc4vTcLyLcCDK6ksLWH1ZASsvySctd+p3vOcTu8vM6ssKkOSR/6YOt4WydZm8/cMrkQ0Sbzx2co5nOD2sZ51F8OhRNG3klqpDCZ44Qcdv79fLMQwGoq2tmIeUd8SxrdHzt3xbtw17TOnrI9rYhGXpUiSzedDd/cHz0y8WQ8eP4XvzTYBJtRZNVixLliTC0KdK289+TqShgdz/9x8jPr/5P/0JpU/8lexvfAM1FKLxy1/Bv3MnAMGDB/Dv3Ytvx87E+qHTVXhfeYWMj32MtA9+kJ5nniGwbx/W1asJHT1K54MP4rnzTjx3vhfbqpXk/Md/4N+1i877f0fKtdcMEzysZ51F6WOPkvOd71D6xF/BaKTl3h9M65jHwr97N/7TtZidVgp/8XPct96CZDLhvu1dhKuqCOzapXedWa7fBJRkGUtFOXKzfh4bOANyKIRAIRAkGVPJoIjEWoyOFGyYd+/3yfj43dOel+f292A/55xRL2TjJR6JOc2AQNH0zW/R8cADhE6cQOnoIPWWdyLZbKBpiROSeL/xSF3doG19r7+O7HSS9cV7COzaTc373k+ktXXac0pmoh0d+PfsIeXKKwFIfdetAGR85tOjpq8LkouTJ0/ywAMPcPLkSXJyckYss5gIDoeDc845h87OTk6ePImmaRQUFGAymVi9ejU1sbtZb3vb2/j4xz9OdnY2drt9XHEizo033kh6LBNn2YDkfVmWueKKK+jq6uLJJ5+koKCA3NxcmmYodPfo0aO8/PLLvPTSSzMy3nTIW+oG9I4ergwbKy/On1KI42xRuCINVdH45/2H+e2XXqettm/E9ToafaTnORNtNi9971JC/iiVu2f/8/bUvjZMFgMFZ3m46N0VXPbekbs4LCacHgsVZ2cnXVtY64qzUHt6iDQMPjcIna4adHEap+2nP0V2OMj+5jewb9QzQEZr12kpK8O6dg1df/4zitendxqLj3+yUl9nnLbJpsJCPWzz2HF8b2zF4PEM6lS2WLEsWULo1KkJC0cQc6hu345/717UUIjuRx7BdcMN2IeEIscxejwYXC4sZaVkfPIT+g0kwJCeTmD/ARq/8lW9JNfnA6DzId3567nzvaR/9CNIFgvIMgU/+V9c111H9r/9G9nf+HpCoHW/82ZK/vgHUm+6keyvfW3EOcgOB57b34N1xQoy7r4b7+bNBA4dnsxTNWG6/vgnFIsDW+Hgc/KUq69Bstlo/u73IBLBsqy/nbt16VKo01+rQe/si7vzjSjxEAiSjP4MiomfqEab9ZP3gV06ZhrZ4aD4oQdHf9zab0cz5edPW6DQNI3eZ59FdjhQ+7wgSaRcdhndjz5G8OBBbLGOJYa0NGSHg3CtLlBEmproeuQv9L38Co4LLsDzgQ8gp7ho+ta36HzwQbK//OVpzSsZ8L35Jpby8mGumd6//x1UlZSr9ZCmlCuvpPiPf0g4UwTJTW9vL0888QSBWCL7dFt1xksq3nrrLaC/XGT9+vXs2rWLjIyMKTs0bDYbd911F42NjWRlDRbHKioqKC0txev1cvvtt7NlyxZ27dqFoiiTElw6Ojp48cUXOffcc/H7/VRXV3P06FFkWaapqYn29vYR59/R0YHdbsc2y+G6OaWpGM0yRSsXZkvf3PJUjCaZmoMdALz25+Pc+uWNg+7wa6pGR6OPs87PTSzLKEjBk2Pn1N42Vl82e2U5qqpRta+N4tXpg5wlZwJOj5WgN0I0rEwqr2o+iTsvg0ePYC7oz89ou++n+HftYunrryeWBU+cwPvSZjI+82mMHg8pV7wN/86dwwIyB5J25500fuWrnL72WqIdHRT++td4X3st0U7dsnT0NrsQu4u9bBm+bdtQ+npxXHDBlFuiJhPm8iWoXi/R1lZMsXNIxetDtlqQjMMvI1W/n6qb30mkvh4MBnK++Q1Uv3/CIdsZd9+Nb8vryKkujJ40ep59FqJ6MGT3E0/ifvdt9D77HCnXXJ0Ids/68peINjVjyssj/0c/HHFc29q12Ia01B4Nz/vupOP+++n49a+wbdyIubiYlMsvH7SO4vXS/K1vkf7xj4/avnYgfa+8Qtt995F6w430vfQSXHoxZttgN4nB6SD1hhvofvRRDB4P9o0bEo9ZKpZieG4rwBkRlDnld5YkSYWSJL0iSdJRSZIOS5L0udjyNEmSXpQk6WTsf8+Abb4mSVKlJEnHJUm6esDyjZIkHYw99lMpJnlJkmSRJOkvseU7JEkqmcaxCgSLgkQGhWXi+mK4tg5DZgayZf5q1gY6KKwrVhBpbp5WWYXS3Y3q9xNta6PzgQewbdiAMTMzcRfEuloXKCRJwlRURLhWv6Pb+cCDdPz61ygdHbjecS2SJOG+5Z3Y16/H/+b2aRxhcqBFItTe/XHa7vvZ4OWqStef/qyX6CzTT9QkScK+ceMZcRK2mFFVlS1btnD//fcTiUS48847Wb58OWsneLI2Grm5uRgMBqqqqnA4HLhcev18Xl4eK1eu5LzzzpvW+E6nk6UjXDRIksSdd97JJz7xCex2O7m5uUSjUdrb29E0jeeee47qWKL/aKiqylNPPcWxY8d48MEHeeyxx9i/fz8Gg4F3v/vdgN4adSCBQICHHnqI++67j0ceeWRaxzYRTBYDt3/zHM5+R8ms72sqGE0Gilalk5pl46J3V9BS1cux7U2013v563/t4k//voO9L9USDSmk5w8uqyhbl0njyW42P3CEJ/57N4oy/RK7aFgZVGrSfKqHQF+EsnVTL19MVpxp+ne9tzs0zzOZOJZly8BgIDQkhyJSW4fS1o7i9SWW+bbogYqe2HvVdd11OC+9FPt55486fso112BIT0cNBjEVFFB39910/eEPmEtLSf/YRzHlj5/Hk373xwhXVaG0tZ8R5R0AljI9syNUqd+911SVqhtvpOk73yHa2UnDl75M5VVX0/DFLxFpaaXjd78nUl9P9te/DppGy/fvRXY4sE/w+0AymSj+w8MU/uIXWNeuSZTiWlesoPOBB+j75z9R+/pIvemmxDZp730vWV+8Z8aO2eB04rnjDvpefInWe39A/Wc+i/f1Nwat0/n7B+h97nlavvf9cd0lfS+/Qv0n/4Xw6Spaf/ADtHAYzZU24nl8zne+zdJdu6jYthVTbr+wa1m2DFNEfw8IB8XYRIEvapq2R5KkFGC3JEkvAh8ENmuadq8kSf8K/CvwVUmSVgC3AyuBPOAlSZKWapqmAL8E7ga2A88B1wDPAx8BujRNK5ck6XbgB8B7pjFngSDp6S/xmPhFY/DoUazL59eKODAk07pyBX0vvki0rS2hyE+WgTZQ1ecj5e16WULKlVcQqa9PpB4DmAsLCZ04gaZp9L36Co6LL6bw5z9DGhDUZz//PNrv+xnRri6MHg+zSbSjY1BL17kk0tQEkQi+HYPFGN+bbxKuqSHv05+al3kJZo/q6mpefvlliouLufHGG1myZAkV49iZJ4LRaCQnJ4eGhgby8vISdlpJkrgt1o54tjAOuHOXGzuJa2pqIhKJsHPnTo4ePcq//Mu/oGkaL7/8MjabjY0bN+J2uwmHw7z88svU1tbyjne8A6/Xi8fjYe3atcgxMa60tJQDBw5w2WWXJZa99NJLVFVVsWzZMo4fP05VVRWlY9yxnQlSMxd2yOHbP7wCTQWjSaZyVwtvPnkKh9uCtyuEyWJg+5N67frQVqtLNmSx+4Uajm3X85GObm2aVtcJVdX463/vxuY0cePndMfXqb2tGIwyxasWpgNlNnHGAvS8XaGkCcqUrVYsZaUEjwwRKBoaYv/XY4jdqfbt3Il5yZKEC9CYkUHhr3819vhmM8V/eBjZakX1+aj/zGdJu+sDeG6/fcJzTLn8crK++hXa7/sZzosvmszhJS3xcyn/9u04zj6b4PHjRBob6Xn8r4ROnCR09CiOiy+m78UX6X3uOZBlUq69hrT3vw//rl30/eMfpFzxtkmFbMdzKmyxG03OSy/F/e53U/exj9H4b1/HmJmJY5oC+HikffAuQidPknL1VXQ+8CD1n/0shb/8BY7zziPa2Unn73+PIS0N/44d+LZtwzmGYOV74w1ku50lm1+i9iMfQTKZiGIcsVRbkmUMzuE5OZalFf0ChU9kUIyKpmlNmqbtif3cBxwF8oGbgLjP+0Hg5tjPNwGPaJoW0jSt6v+zd97hUVXpH//cqZnJzKT33hNCIKH3KkUEBAXFteva1tXddatb9Le7bnV11S2uvSBipSO9lwQIKQTSSO+9zmT6zO+PG0YioYem+TyPj2Hm3nPPvXPnzjnf877fFygBxgiCEATonE5nulOUoD78xj6n2voCmHkqumKQQb6ruFI8LtCDwmE2Yy4pcdUZv6B9HA4sloFVaF0mmYLgCqW0XUbe+KlByylTLO1Ns8T/z5hBxIcf9CklpggPw1Jbi6W0FGtlFZrp0/qIEwDu48eD00nPoUNcSUz5+ZycNNlVFvVq4xrsVVaJYkUvHZ+KIYWn0jsG+faQk5ODUqnknnvuIaYfB/vL4VSax6VUAxkofH19kcvl1NfXk5+fj0QiQa/X88EHH/Dmm2+SlZXF/v37+fe//82mTZt49dVXycjIIDU1ldGjRzNjxgzS0tJcQgTAyJEj6ejooLCwEIDS0lKOHj3K2LFjWbJkCRqNhh07dqDX66/VaV8XyORS5EopgkRgyrIETHorLdV6piyLZ9rdCZxaWPQO7jvg9g3TEJniw6h5kQTFeHBkY7nrt62tzsDy3x6kqfLCPRSKDzfQUq2nuqCdmqJ22uoN5O+rI2q4Lwq37142s8ZL/L01tJuucU8uDmVSEqb8fNe/7XoD9o4O4Guja6fNhjHzKOoxoy++/ago5EFBKGNjidn01UWJE6fweeAB4g8fuixj8RsJqY8PiogIWt96m/I77kS/azcIAhIPD0zHjuH3zDOE/fc/RK9fh+8Pn8Rj/i0E/FKshuHz4ANi+u3NN1/Ssd0SE9DePBefhx9CM3kSAb/9LVit6BYs6Ldc7EAi8/Ym7PX/4rloEeFvv4UiNJTqRx+jc9066p59FofJRPi77yAPDqblGxGp38SYl4fb0KHIvLyI+vxzIt5/H6vZflHV+GReXsi9PJAJtkGTzAulN/UiDTgEBDidznoQRQzgVPJoCHC6S11N72shvX9/8/U++zidThvQCZwhhQuC8KggCJmCIGQ2NzcPxCkNMsh1i81iRyITkJ7HLM1cXk7xxEmir4DNdlECxZEjR3jllVewWs//EDx8+DCHLmBSfyrFQ6rTIfMXoyZsLS0X3KdvYq0RHxvBf/8bQX96oU/O6jeRh4WD1Ur7J58CoO2nnrcqJQWJu7tYevQScdpsOEznHhB2bdsmCiG9eftXG0vN149bQ+/nZmtvp3vXLjwWLhwsJfotw2w2U1BQwNChQ5GfxZ3+crgeBAqJREJgYCAnT57kxIkTxMTEMG/ePBwOByqVigceeIAf/ehHREREcOjQIXx9fXn44YdZtGjRWatcDBkyBC8vL/bu3cuaNWtYvnw5Xl5eTJ8+HblczsyZM6mpqeGVV15xlWz9ruMXrmXcohiSJwcTO9KfsCRvgmI98AxQnyESCILALU8OZ+zCaMYvjqGn08LRTRUAHN5QRleLicMbyi/ouDaLncPryvEN0+DuqWTvyiI2/S8PmVLKpDsuP1LoRsTdS4yg6G6/cVI8QEz/tDU1YWsVfU2stV//Xll7faRMJ07g6OnBfcyYa9JH4IpPjq8nBEEgau0aAn77W8yFhbS+8w5uQ4cS/Je/4H3/fXjffx8AiogI/J58kuC//c1lyK5KTSV29y6X8fZFH1suJ/Sf/0SVmgqA9z13E/n5Z/j96OkBObcLRebrS/iHH+CWnEzdL36JYc9eAp9/HrfERLwfeABjTg7GfipJOR0OHGYzpsJCly+aIJUiUalEgeIizO5B9JFTOE2YvgMCxWXLyoIgaIAvgR87nc6ucwQ49PeG8xyvn2ufvi84nW8CbwKMGjXqwm1mBxnkBsRqsl9QiVHT8RPYW1tp+vuLgJhWcaEUFxfT09NDU1MTISFnTvzr6uo4fvw406dPZ+fOnbi7uzN27NhztnnKJFPq6elaebgsgaK2FolOhyolBVVKyjm3VUSIlTw6Pv9czOPr55wEmQz3yZPp2rwZ/58+g9TD46L71PSPl9Dv2kX0pq/O6tug37MHEAdZ1wJrbS1IpUi1WnoyDuG5aBFdG78CqxWP2xZfkz6dj5r84+Tt3IITmPnQEyjVN0bI8vVAeno6Vqv1sv0mzkZSUhILFiy4bMPNy2XKlCmsXLkSh8PBtGnTSEtLY/Tovius99xzD21tbXh7e5+3/KZEImHixIls2LCB5uZmxo8fz9SpU1H2+vikpaURFhbG//73P3Jzcy9aoHE4HFRUVFBcXMzIkSPx+5asxo6Y07eKwrwnhrkiI85GUKwnieMCyd5WhbunktKsZjTeSirzWmmu7sYvTNvvfuYeKzarg4NfltDdbmLG/Wno203sXVmMSitn1kNDcPe4dr5L1xK5QoqbuxzDjSZQJInjFFN+AZrJk1wLEQCWajGC4lRFD/U1FCi+a0jc3PC6+3t0rlmD6fhxNJMnoZ0xHe2M6efd91LTeM/G+cZ7VwqZlxcRH7xPyxtvIg8KxHPJEgA8bruN5tdeo+2DDwh5+WXX9raWFkpvmS+aa1qtuJ3Wb4fdgd3qOK9AUV5ejk6nc1W0kvn7IbcavhMpHpclUAiCIEcUJ1Y4nc5VvS83CoIQ5HQ663vTN07VkaoBwk7bPRSo6309tJ/XT9+nRhAEGeABtF1OnwcZ5EbHarkw1dXaW7nD3tmJRKfrd1LeHw6Hg+rekpz19fV0dnYil8tdOevd3d18/PHH6PV6bDYbJpMJi8VyXgd9QXmaQOHjDYKArenSI56stbXIzxE1cTrKmBgEuRxFRARBL7xw1u18n3ic7i1baH37bfx/+tOL7lP39u1Ya2p6q4icOSG0NjZhzi8AmezaCRQ1tciDgnBLGYp+1y5sLS10fPEFyiFJF+REfbUxdnex9qU/4XQ6MBsMBEbHkjhxKkZ9Nz4hYedv4DuI2Wzmk08+weFwUFlZSXJyMmFhV+ZayWQyRvaW+LuWxMXFsWzZMjIzM0lMTOx3G0EQXAO9CyEtLQ2pVEp0dDQe/QiWvr6+REVFUVxczNy5c88rejidTgRBoKamho0bN7pKo3Z0dLDsEkLNbwTc3OW4uZ8/cmfC7bFUnmhl7yfFyN2kLPpJGp/96Qgb/3OMUfMiCU306uOlYLc6+PwvmXQ2ixVpxi6MIjRB9A5KHBfU7zEuBLvdTmVlJZGRkWzZsoXi4mJiY2OJj48nJiamTxrQ9Y67lxL9DZbi4ZYkfndNBX0FCnloKNbqGhxGI+0rV+I2bNg183H6riIIAv7P/ISqxx5HO2vWte7ONUFQKPB76od9XpNq3PG84w7aPvgA7xMnUCUnA9D+8UocnZ10rlkDgGrYMNc+Voto5nuusbzJZGL58uVIpVJuvfVWMQrS3x9ZWdd3IoLicqp4CMA7QIHT6Xz5tLfWAff3/n0/sPa015f1VuaIAuKAw71pIN2CIIzrbfO+b+xzqq0lwE7nxRTiHWSQbyFWs+OCyoad7u/glpR03sHzKRobG13+E7W1taxbt47PPvuM1tZWnE4nq1atwmw24+7uzuHD4kqGw+Ggvb39nO2eLlAIMhlSb+/Li6Coq0VxgaKLzM+P2J07iFq9ClXK0LNu55aQgG7BfFrfeZeTU6aiP62s2fmwVFe7BlPd23dgbWqi+skfUjx+AjVP/whbWxuGfaLzuMeiW7E1N2NtajpXk1cEa20t8pAQfB9/ArvBQNnixZgLC/F58MGr3pdTmAx6jPruft878OlyzD0G7vy/vxEUl0D2lg188n+/4qNnf0xrbXW/+3zXKSsro7y8nO7ubkaNGsVtt912wd//G5n4+Hi+973vDVj5T6lUSlpaWr/ixOnHbG9vp+U8z7ITJ07w8ssvU15ezooVKzAYDNx6662MGzeOoqIiOnrz7L+rqLQKvvf8OG7/xUiW/XYMHn5qFvwoFbVOwZ6Pi1jxXAZFhxroajFSmF5P7s5qOpuNpM4KZ9rdCYycGzkg/di3bx8ffvghK1eu5NChQ8jlcnJyclixYgW7d+8ekGNcLbReSvQdZuw2x3mrDFwvSHU65KGhLh8KS20tglqNalgKlupqWt99F1t9PQE//9k17ul3E/cJE0jIPOIqCTuIiO+jjyDz9qb+V7/CkHEI47FjtH/yCW5Dh4JMhszf35X2AmIkNJxboCgvL8fhcKDValm1ahW1tbXI/PyQ9bT3EShqi9o5sa8Wu+3yKyFdT1yOFDwRuBeYIQhCTu9/84C/ArMEQTgJzOr9N06n8wTwGZAPbAae7K3gAfAE8DaicWYpYgUPEAUQH0EQSoBnECuCDDLIdxrbhUZQ1DegjI9HPX7cReX/VfUaUfn4+JCXl4fJZMJms/Hll19y5MgRysvLmT17tiulQ6sVw29be3NGz8Ypk0yppycg5vT1J1DYWlowFRWdsy2n04mlphZ58IW7vsv8/C4obzTg2WfxeeQRbK2t9BzJvOD2Demid4U8LIzO9espX7QYw/79uI8fT/fOnbT8+9+0Lf8IRUQEnovFVIprEUVhralBHhKCW0I8Po98H3tzC94PPIDHggVX/NgOh52MLz+hq6Vv5Mzm//6Tj3/9DFZL33DkxrIScrdvJm3OfPzCI0mdM5+Ohnra62uRSmVsfO1F7LZv/0rCxVJaWopCoeDJJ59k/vz554xsGuTyOBVZlpWVhdFo7Hcbp9PJvn376O7u5oMPPsBsNnPPPfeQlpbmKsW6f/9+bLZvf237c+GmkRMY7YHOVxSYAqM8WPqrUSz73RgCo3Xs+6yY1S9lseODAtJXlxKW5MXE22NJnhyCILl8Ac5kMpGRkYGbmxsnT57Ex8eHRx55hF/84hfExMSQnZ1NY2MjH3zwAW1t138wr7uXG53NRj789UGO7aw5/w7XCW5DhmA6fhwQI/4UISHIw8Kx1tbS+sabaOfMQT364g0yBxkYrmW5+usVqacnQX96AfPJEqoeeICKO+7E3taG/89/TuBvf4PPY4/22d5qFp/15zLJLCkpQaFQ8NBDD+Hu7s6qVato0+mQW7owdJpdomPBwXoy1pYhkX67FiEuOcXD6XTup3+PCICZZ9nnT8Cf+nk9EzhjWdPpdJqAK1urbJBBbjAu1FjHWl+PPDiYsP+9ft5ta2trycnJITY2loKCAjw8PEhISODgwYPIZDIWLlzImjVr+OqrrwgMDGTkyJH09PSQnp7O1KlT2bBhw3kFCqE/gaIfU9vmV1+la+NXxO3fh+QsXgP29nacRuMFp61cDDIvL/x/8mM6vvwSe/uFD0IN6enIAgLwvv9+Gl94AXlwMBHLP0QZE4Pkd8/R/vFKAIL/8Q/cEhNBIqHtnXexVFbi88ADA34e/eEwmcTSrr2pMX5PPon7uPGoR12dEP364iIOfPYRph4D0+592PV6c2U5Xc1NZHyxkiFTZuAVFIIgCOx493XUOg8m3HE3APHjJpG9eT1xYyag9fbhq3+/RG1hPuFDr4y/wvXE+VKoTqe0tJSoqKhBYeIq4OnpSXBwMOnp6Rw7dowf/vCHZ0Rw1NXV0dDQQGpqKsePH2fKlCn4+/u79k9JSSEzM5OCggLuuusul/HoICBIBHxCNEy/J4lP/3wYp93JtLsTqDrRxrhF0QNyjObmZlatWkVPTw8mk4lHHnmEqqoqYmJiXMayqampfPnll6xcuZKOjg42b97MnDlzMBgMhIeHD0g/BhqNpxKryY7VZKe17sapNqMakUb31q1YGxtFQT00FEV4GNjtyAICCHz+uWvdxUEGOQPNlClErVuLva0de0cHTqsV9ZjRuI890yvllC+PXNn/NNzpdLp+xzUaDYsXL2bFihWsbG0lMNiK3ebE2G1FpZVTW9xOSLznty5K8rtXe2mQQW5wrGY7Ku35Ky3Y6utRpaVeUJv79u2jsLCQI72VJcaMGeMyfYuJiWHYsGH4+/uzd+9eJk2ahEQiQaPR8Itf/AJBENi5c+d5Q5wFuRz3CRNcpcFkfn6Yy8rO2M5SXoGjp4fu7dvxWLiw37YsFRWAmJd6pZB5eWE7T9rKKWwtLRj2H0A7cyYeixZhb2/H8447kAeIkxDfJx6nc80aFDEx6ObdjCCRoB4zhp7Dh+nJzESdltavZ8VAY60T035OpcYIMlm/P55XivIcMSKl7Ohhl0Bhs1rpamlGKpdzeO0XHF77BWMX34lPaBj1J4uY+4OfoFSLJQplcjl3/0nMKDR0iJ9NS3Xlt16gKCwsZNWqVdx9991EREScc9u2tjba29sZP378VerdIPfffz9FRUWsWrWKEydOMGrUqD7vZ2ZmIpfLmTt3LvPmzUPxjUo5ixYtYtiwYWzcuJEPP/yQ+++/v19z4u8y3sHuLHw6FTeNHJ9gDcmTL+/6mM1mTCYTpaWlbNu2DYlEgr+/P0lJSYSEhJxx/RMSEpDL5XR0dODv709xcTElJSU4HA4WLlzIiBEjAGhpaWHHjh1MmTKFoKAzvTBaWlrIzMwkIiKChISEK+ppofH+eqXb2DWwZcOvJOqR4venJyMDS00N6rFjUY8ciVtyMkEv/BGZt/c17uEgg/SPW3z8BW33tUDR/yJCa2srHR0dTJgwAYDo6GieeeYZtn7xBbmUo2tvprvVhNVsR99uZsQcr4E5geuIQYFikEFuMC4kxcPR04O9sxN54PnNwiwWCyUlJaSlpTF06FA8PT3x9vams7MTiURCSq/zcGBgIHfccUeffU8ptj4+Pq4IioaGBux2+xkDPEEQCH/3Hde/ZX5iiscp4zhXf2prAehcs/YMgeJUSJsxOxsA1bAr5+Ys9fLC3nZ+gcLpcFD37K9xWiz4PPwQUo37GSZK8uBgwt58A1lgoKu6R/h77+Iw9FAycyatb7+D57I7xfrs0QOzKtgflrJSsT/XaPJTnn0UBIH2+lra6mrxDg6hs7EBnE6m3P0gToeDsqzDZG9ej9rDA7/wSIZMPtMl3GQyYZdIcdPqaKmuvAZncnWw2+2Ul5ezatUqLBYLWVlZLoHCbDa7KkqcTmmp+BlHX8H7aJC+KJVKUlJS2LdvHzk5OX0ECqfTSXFxMQkJCbj1RpF9E4lEQmxsLA8++CBvvPEGu3bt4p577rla3b9hCIkfmEF4W1sbb775JqbektBBQUEsXboU73NMfBUKBcnJyZSVlfHggw/yySefoNPp6OnpYd26dfj7+6PRaPjwww/p6uqivLyc8PBwGhoakEqlLFiwgM7OTjZs2IDdbicjI4MhQ4awdOnSy175zM3NJTIy8gyvlPAhPgyfEUZjRSc9N5BA4ZaUiEStpvm1f+Hs6UEzaSKKyEiivvziWndtkEEGhG8KFHV1dXz++ecEBAQwduxYDhw4gEwmI+E043J3d3dunjWLir+/RLeulK5WoysyaqCejdcTgwLFIIPcYIgpHudedbE2NAAgDz6/QFFWVobNZmPo0KHExMS4Xvf09OSZZ57B3d39vG34+Pi4VpM+++wzbDYbP/nJT8458JL5+YHVir2jA5mX+HB1WizYGhqQuLtjyMjA2tjkikIAqLz7HtQjR2AuLUMREYHM1/e8fbtUpN7emM/jhQHQ/tFHGPbtI+C536HszUfvD/dvrGgLgoBU447XsmW0vvEG3du2oYiMJHrDegTZwD+anTYbzf/+D7LAQNx6XaavJvr2NpoqShl201yObd/MkXVfEJyQhEorDqqDYhMIiksgdEgKH/3qR1iMPSx45tkzyrXm5uayZcsWrFYrAaFR31qBwmw28/bbb9Pc3IxGoyE8PJzCwkJMJhP79u3jwIEDjB8/HofDQUlJCbNnzyYhIYHKykq0Wu1FVasY5PIRBIHU1FS2bdtGS0sLvr3PppaWFgwGA1FRUedtQ6fTMWrUKPbs2eMqh3olaG5uprKy8oxIj/5oaGjAaDQSGRn5rQghdjqdfPXVVzgcDm655RZ8fX0v+NxuueUWbDYbKpWKB3tNhc1mMy+++CI5OTno9XpMJhN33XUXu3btoqmpicjISGpra/nkk0+wWq1ERUWxaNEiMjMz2bt3L1lZWfj5+REcHIzsLM/9zs5OdDpdv32srq5m9erVpKWlceutt/Z5T61TMOmOOLa/n09t0YVFA14PCDIZqrQ0DAcOIAsOwn3SpGvdpUEGGVAsxl4Pil6BIjs7m66uLqxWK4WFhQDMmzfvDNFR6e9PSE0N+UO1dDTr6Wwwo9LK8Qr69pVeHxQoBhnkBqCnpwe73Y5WqxUFivNU8bD2VvA43TX4bBQWFqJUKomMjDzjPY1Gc0H98/X1JScnh2PHjrnMw+rq6s4ZpnxKXLA1N7sECmt9PTideCxaRPuKFRhzcpDPmQ2I4oUxJwfzyZMIEgmamf1a3QwYMm8ves5jhGYqLKTpxX+gmT4dr7vuuqTjeN93L6YTJ5AHBdLx+Rd0btiA56JFdKxZg1TncUF1xi+E9pWfYC4sJOTVV5EMUJWDi6EiNwuA4bPmUVdcyPFd28jbtY0hk6YB4BkkphQFRMUQO3oc3a2txI0eT2VlJZ6enmi1Wnbs2MGBAwcIDQ3F6XRSU1uLZ33FGVE4JZmHKDl8kOkPPOpKD7lecTgc1NfXu0I6Y2JiCAkJYfPmzbS0tHDrrbcyZMgQqqurKSkp4T//+Q/d3d0u3wMQJ7YrV65k2bJlVFZWEhER8a2YTN5oDBs2jJ07d7Jv3z7XinllpSig9fd87Y+RI0eyb98+jhw5wpw5cwa8j1arlU8//ZSWlhbCw8NdXhj94XQ6+fTTT2lvbyciIoJ77733rJPo65mOjg4OHTqEt7c3zc3NlJSUMHfuXEZfpNGiXC53eVKcQqlUkpiYSF5eHmazmcmTJ5OQkNBn5bOzs5O3334bf39/li1bhkKhYOrUqZSUlLB+/XoAvL29mTp1KhKJhIyMDGbPnk1ERAS1tbW8/fbbjB07lrlz5+JwODh8+DAGg4GIiAiye6MJ8/PzmTdv3hn9A1BrFfR0W854Tl7PqEeNxHDgAF5Ll16QufUgg9xINFV0I5VL0Pm64XA4KCgoID4+nsWLF7Nv3z4sFku/zydBJkMniNU6WhrbaSo2ExzndcN8ry+GG++XZpBBvoNs2LCB5uZmnnzySawWO7JzpHg4nU6sdXUAyPrJgT0dm81GUVER8fHxl2Wol5SUxJ49e1izZg1ubm6YzWYKCgrOLVD4+QFgb2mB3rw9S2+ZTs2UybSvWIGl/GuPCmtdHTgcOLrFcpTqkSMuub8XgtTTC3tXF06b7awRDc2vvoZEqyXoTy9c8g+EzMeH8Lffwul0Yjxxgpb/vo5uzhwa//gC8tDQARMoujZvxm3IELSzr0398rriAhTu7mTmFzLxwcepKC5m/9EsCo4cQumuwc39azFswU+exel00NbeznvvvYdMJsPd3Z3Ozk5GjRrFvHnzaGpq4n//+x8mJHS3NKPz+3qilb15PVV5OTRVlnPn83+5rkWKzZs3u8r1AuzevZuQkBCqq6uZPHkyaWlpAC6zLJvNxrJly0hISCA7Oxt3d3diYmJ49dVX2b17N93d3detad+3Ha1Wy9ixYzl48CANDQ00Njbi5+eHRqO54GgInU5HXFwcBQUFAy5Q2Gw2Nm3aREtLC4IgkJWVRVNTExKJhMWLF58RLdfY2Eh7ezvR0dGUlZVRXFzMkCFDLvnYa9asoba2Fi8vL+bPn3/FIkROYTAYyMjIICMjA5vN5koRHDVq1EWLE+ciJSWF48ePI5FI+m3Xw8ODp556CplM5vKckEqlLF26lIKCAtRqNXv37mX16tWufXbs2MGDDz7I5s2bcTqdHDp0iKFDh1JTU8PmzZsRBIF9vWWwQ0JCqK2t5eTJk/1+PiqdAofNicVoQ6k+U8C4HtHOnYvh0GE8lw765A8kTqcTk956QT5mg1w5aoraCYrxQCaXUl1djV6vJykpCYVCwczzLL5p3cQFptqKRsztKkbM8bwKPb76DAoUgwxyA1BbW0tnZyctzW04bE4UqrN/df/73/8SrTcQKQjIz7E6BmK+utFodPlMXCo+Pj7Mnz+f1atXk5qaSmNjIwUFBSQnJ+Pv79+v+CE9FUFxmrmmtUb0n1DGxSELCupjomnpLX+KTAY2G6oRV1ig8PYGpxN7Zyey3nD55v/8B1tDI0F//AMOgwHDgQN4LrtzQEy7BEHA99FHqf3xT2h6+Z84DAbMxcXYu7qQ6nSX1bbT4cBUUIDnokXXTGlvKCnGIyqew4cPYzKZ6OrqAqkMk4cPdi8fXn/9dW6//XYCAgKQSKWAlMzMTCQSCYmJifT09DB37lwSExMRBAGv3qgbh0JJS3UlOj9/nA4HTqeT+pNFBETH0lhWQuGBPQyfNe+anPP5MJlMZGdnk5SUxPTp01GpVGzYsIGamhpmzZrlKkEJ4oTmkUceQS6Xo+6tbjPitO/A0KFDXREV5zPSHOTKMXnyZLKysmhpaUGr1dLc3MzQoUMv6nsXHBxMUVERFovlDEPNS6W7u5v333+f1tZWxo8fT1tbGxkZGYDogfHWW2/x2GOP9alAUlBQgCAILF68mDfeeIPc3NxLFih2797N8ePHSUpKory8nP/973888cQTru/x5dLY2EhFRQVBQUGEh4dTV1fHxx9/jF6vJzk5mVmzZmEymZDJZK70m4EiNjYWrVZLTEwMurM8q/v7HL28vFwmeMOGDaO2tha9Xk97eztbt25l1apVVFdXM3v2bNLT0/nggw9wOBzExcVx5513snPnTk6cOMHSpUt5++232bhxI0ePHmXRokWu8t8gpnoA9HRZbhiBQhkVRcT7713rbnzrKM1qZtt7J7j7/8a5yvkOcnXp6bLQWqt3VSE6JW7GnSNF+HR0WnExp7OjCzdUhCR8+/wnYFCgGGSQ6x6j0UhnZycAxQUnAXD36DvYaX3vfbq3bsXzTy/Q3NyM0WgkLjwc4SyDW7vdjsViIS8vD5VK1cd74lIZPny4q+ReTk4OGzdu5I033mDWrFlMnDjxjO1lvSvetuZmnHY7hvQMrDXVIJcjCwhAGR2Npazctb2lqhoA30cfwXDgIIoLDJm+VKRenoBY0lTm44Px+Ala/vNfAPx/9lMMGYdwWixoZ940YMfUzpiB1Nub9uXLxRecTnqystBOm3ZZ7VoqKnH29FwT7wkAq9lES3UlgZMToKmFEydOYLfbkQgCVp9ArICto4O33nqLsWPHMnXqVEDMy0xMTGTJkiVntKlUKlGr1VjlSooO7qW2KJ/sTeuZdv8jWE1GRt6yiIOfr6DkSAbDZ83DpNeTsWolI+bdis733MLd1eLEiRNYrVYmTJjgCrW/6667zhqK/c181NNJSUkhPT0dNzc3/Hqjkwa5+qhUKu6//34kEglms5n333+f2NjYi2rj1OfX3Nw8YNU8tmzZQkdHB3fffTdxcXEUFhZSVFREcnIyY8aM4f3333dVn5DJZKhUKvLz8wkPD0er1ZKSksKhQ4fo6elxCWQXSkNDAwcOHHD5JLS0tPDvf/+b48ePM3ny5DO2PyXcjRgxol8j2NMxm81s3bqVo0ePAqLYMmrUKLKzs1GpVDz22GP9VtMYSKRSKU888cRliUkSiYSwsDBAPKe9e/eSl5fH8OHDGTduHPHx8ezfv5+GhgYWLFiATCZj9uzZzJ4tpkDOnDmTvLw8Kioq2LJlS59n5imBwthtwSvw+o0mG+Ty6e7uprW1lfDwcCwW0Rj1dHPe+pIOHDYnlcdbSZk2WM74WlBbLPrBhCR4UV1dzeHDh0lJSTmjPPXZ8OhdELNLRf8JhdZ5Sc/l651BgWKQQa5zmpqaXH+XlZUBAag9+g7aejIyMGZnU/34EzBhPHqVCvnvfnfWNnfu3MnBgwcRBIERI0ZcVnrH6ZxauR0xYgQ+Pj5s3LiR0tLSfgUKibsaQa3G1tSEYf9+qh97HIlGgzwoCEEqRREdTeeXX7oma9bqKgS1Gt+nnsLv6acHpL/n4lRUhK2tDYXTScMf/oAgl+M0mzGkZ9C9cwdST88BTTURFAo8Fi2i7d130Uybhv7AAYyZmZctUJjy8wFwS7601c/Lpam8DKfDgUUmRyaTYbOJBlEzJk1g+74D+Os03PvIY2zbto0DBw5gMpnw9/fHZDIxZszZy6B6e3vTZTWTv28XABKplN0fvAVASMIQYkePJ+urdZh7DGSs/pSjG9dSV1TInb//G9IrmEtvMplcEUTnmrRkZ2fj6+tL6DfK5V5KlEtQUBABAQH4+vpeVulCh8NOc0U5AdEXN6ke5GtOnxD/9Kc/veCB5ylOiVUDJVCUlZVx/Phxpk2b5lqli4+PZ+HChSQlJaFSqRg7diwZGRlkZmYik8nw8fGhubmZW265BRAF6PT0dN588038/f1RKBTceuut/Xoe9Hd8p9PpCl329fUlJCSEgoICxowZQ09PjyuSwul0smbNGgoLC7FarUyZMuWs7VZWVrJq1So6OzuZMGECqamprF27lsOHDxMbG8vChQvPGtEw0Azk5ECpVLJs2TKsVqvr8/L19WXRokVn3SctLY20tDR2797N7t27GTZsGPG9qZNfR1BY++zjsDtoKOskKNbzW5nD/l3AaDSSnZ1NdXU1JpOJqqoq7HY7gYGBrspqo0ePZvr06cjlclpqxKoPVScGBYprRU1hO3I3KVJ3Cx9/9DkeHh7Mm3fhUZ5KnQeyzm4cUjMhcV6u6lHPPPPMeQXdG4lBgWKQQa5zGhsbAXHyX1NXhZtchULddwJibW5CmZCA+bQJaJnVQn+B3jabjaysLNeAcOTIkQPeZ6lUSnR0NDExMWRlZWGz2c4wVxN6U1CsjU2u0qIOvd5VOlQZHYWjpwdbYyPywEAslVUowsKu2kBK2nt97G3t2OrrMR07hv/Pf0bL/96gc+1aeo4cQXvTTQNeccNz6RLaV6zA846l2Ds76ck8ekH7OQwG9Hv2YG1swuuOpUhOyyc35ecjyOUoByBS5mJxOhw0lBYD0GHoIS4uzlXCduL0mfTU1zBi2k1otVpuu+023NzcOHLkiMu49VzpCl5eXnR3d/O9P/8TY3cXlXk5HN2wGo23D1pfP2JHjydz/SoOr/mcnM3r8QuPpL6kiAOffcSU7z1wxc558+bN5OTksH//fmQyGR4eHtx111197t22tjZqamq46aabBuSeFgSBBx988LLECYBj2zaz493XueevrxIQdfXvl28bF1IF6Zt4eXkhlUr7iNOXw6FDh9BoNH2EYolE0idFaPr06ZjNZpcw0dDQwC233OL6fQgMDGTp0qXk5OTQ2dlJY2MjYWFhjB079rzHr6+vR6fT9TFdTkxMZMeOHbz11lt0dHSwZMkSioqKqK2tpampCTc3NzIzM5k4cWK/AnpnZycrVqxAo9Hw0EMPuXxX7rvvPhoaGggPD7+hJ90Xaqr6TSZNmkR+fj6rVq3ikUcewcfHx+U30NNl7rPtofXlZG2uZOYDSSSOu7JRJoMMPEajkQ8++ICGhga8vLxQq9Wkpqbi7+/PoUOHXOmQBw8eJD+vEC8fT+pbu3GTh1BTJMFmtSOTfzcNSLu6uqivrycyMvKqTuqtZjslR5vwS5DzXm8K07333nvWEtT9IdG449bYikVuxi9KxaZDWSQlJX2rxAkYFCgGGeS6p6mpCaVSyYgRI1i9ejUmnxxWfFnKvHk3u/KBbU3NaKdPxzphPPKsLIKDg8nPz2f69DMNFouKijAajdx+++0XHXp8sURGRnL48GHq6ur6Ne6TBQZia2zE1tAIggBOJ/JQMcxVESXm51nKykSBoroaZfT5S/UNFFKv3jC6jnaMx/IAUI8Zg3vuMbq3bkVQKPD5/sMDflxlVBTxGelIVCqM2dm0vv8Bdr0BqebsEx17dzcVd92FpaQUgI4vv0AZE4sgl6O7ZR6mY8dQJiQgXMBq50Bh7ulh38fvkbt3N1IcqH0DaOzsZNTo0SxYsAAAQSJh9j0P9tlvypQpZGdnYzKZmD179jknGd7e3uTl5eEbEYVMJsM7OJSsjWsJjk9CEASC4xLQ+PhyeO0XSOVyFv3yeTJWfcKRtV+g9fGlp7ODtDnzUXt4Xta5NjQ0kJ6eTn19Pb6+vuTn55OUlERzczNWi4Xi4mKKi4uJi41FkEgQBIH83qiW5AFMu7mYQc7ZyN+7E4CSI+mDAsU1QiqV4uvrS3Nz8yXtX1VVRUNDA2PGjMFsNlNSUsKoUaPOGe2gVCrPKFP5TZKTk13367vvvsuBAwcYOXLkeSt71NfXn5FmkZSUxI4dO2htbUWn0/HJJ58gkUiIiYlxeRd9+umn7NixA51Oh1QqZdiwYXR0dHD8+HGqq6txOBzcc889fcw2lUrld9qDRSaTsWzZMt566y3Wrl3LQw89hJtGjiCIue+nqMpvJWuLWGHm2M4aZHIprbV6xi6MvlZdH+QCsNvtZGRksG/fPsxmM4IguNK2Tud04TAqLI7169ZjMlgxy4yYfJpxtCdTX9JJWNKVNaq9HrFYLHz44Ye0tLQgl8tZunSpK9roSnN0dyFmk5kGewEADz/88EWXBJe6u6Pp7qAr3J92Z5UrTfTbxqBAMcgg1zmNjY0EBASIDt55eooya1AFtLF69Wqio6NRSqXYW1uR+fvT0tKCr68vQ4YMcbm1f9MQLCsrC51OR3T0lR+InBooVlRU9CtQyAP8MRw5gq2xAVlQIAE/+xnKpCQAFL1ihLm0DPW4cVirq9H0ehNcDWS9HhS2tjYsVdViBEJCApopk+neuhW/n/wE5RUSeE6VAdVMmULrW29j2LsH3VlCAJ0OB7U//SmWikpC/vUaEpWa+t/9DlN+Po7ubro2bADA8447rkhfz0bWprVk7dtDT3QycocdlacHdOkJDQ09Zzi0RqPh1ltvxWAwEBwcfM5jnIoC6ujowNfXFw//AG750S/wDRPvO0Ei4d6/vEJrTRVuWh06Xz+m3/8IdUUF7Hz3fwC0VFWw8Ke/6SOE1JcUUZxxgPFL7kLhdu7w/E/f+C8FdY1IBFBLBIpaWvDw8GD6+LGotTo+/t3PkOj8WfXpJzi7OkiMiea2J57i+PHjhISEDJhJ4EDQ3lBHfUkRCAKlmYeYeMc917pL31n8/Pyorq4+6/s2m438/Hyio6OxWq3YbDb8/Pyoqalh+fLlWK1WgoKC6OjowG63X7K55dmYPHkyK1asIC8vz1Vp5nTMZjMKhQKLxUJLSwtDhw7t876vry9jx44lODiYiIgI9u7dy5gxYwjsLY1tt9vx9vbm4MGDrn2KiopoamoSDXaBOXPmXPFKIDci3t7epKamcuTIERwOBxKJBDetAmOvQJH5VTmH15fjFaAmaWIwB78sYcvbx8EJieMD8fC79HSV6oI28nbXEBClY+TcyAE6o0FOsXnzZo4cOUJsbCyBgYHExsaeN9pG7fDDp1k0XNYIdpyJxbQ5ijh+KOqaCBQ9PT0cOXIEi8VCWFgYYWFhlxRpdqHY7XYEQUAQBJqamtixYwctLS3MmzeP7OxsPvvsMxYvXsyQIUOuWNSV0+nkwIEDbE/fjiRAiqPFzuLFiy9anACQaDS4G/S0S0xk5WQSExPjem5+mxgUKAYZ5DrG6XTS1NTEsGHDkEqlqJzeeCmdzFowkbfffpu8vDzifH1xgChQ1NUSHh5OYmIimzZt4sSJEzQ3NxMTE0NaWhotLS2UlpYybdq0yw4FvxDc3d3x9/cnKysLjUZDWlpanx8AWUAgtqZmrPUNyAMC+0zCZX5+SDw8MOYdQ9s4E6fFguIqlk8UFAokGg329g7MBQUohyQhUSjwWLgQqbcPmmlXXixRjRiB1MeHrq3bzipQdHz+BYa9+wh47nfoZoklRON2iavgTosF/f4D6HftvOrl2hrLShFColAoFGi1WupbW9FqtecVHYAzJjNn49Tkvr293SXEJYyf1GcbtYcnag9PamtrefHFFxk+fDgLfvob6osL6GpuIv2LjynOOODar7W2mlV/fh6TQU95diZOh4OguETm/uDHZxzfZDBQWF2LwukgxGHG2N6C3GLBNzyS5T//IRKpDIlUSlhwOJUWJ7jryKupR/vZShoaGpg9ezY2qxWLsQeAXe+/iXdIKGNuXYJU1ne1226znvHaQFO4fw8IAiNuXkjWV2vpbGrEwz/gih5zkP7x9/fn+PHjmM1mWltb6ejoIDExkX379hESEkJpaSnp6ekIgoDT6UQqlbJw4UI2b96MRqPBYrGwfft2JBIJGo3GZcA4UMTGxuLr68vRo0dxd3dn/fr13HLLLSQmJpKdnc3atWtRKBSu73J/RpU333yz6++FCxf2eU8qlfL444+7Km8cO3aMzZs3I5VKeeihh1Cr1Zc0uP+u4Ovri81mo7OzUwz/1yro6bbS1WLk0LpyYtL8mHFfEoJEIHtrJSqtgrY6A6VZzbh7KvHwVxEYJZrymgxWZArJedMBmqu6WfdqDhKJQNWJNoZMDB4sZzmA1NbWcuTIEcaMGXNRngWN5V0gAE6QIGXpsjv53xtvcLR0JxM7E9F5iKlXJ0+e5OTJkwQFBREcHIyfnx9dXV0UFBQwevTo80ZKXQhtbW28+eabmEwmJBIJBw4cQBAEV+nsgUav1/PGG29gNpuRyWT09PQgkUiYNWsWY8aMITk5mQ8//JDPP/+c0NBQ7rrrrisilmRkZLB9+3YUJh88A93wD/Vi2LBhl9SWxF2D2tiD2WLBbLH06/H2bWBQoBhkkOuY5uZmzGaza3DX02lBrVMQEhJCYGAgu3fvZlNPDwkpQwn08aazIF9cSfbwICQkhL1792K326msrGTYsGFkZGQglUoZNWrUVTuHGTNmsHnzZtatW0dYWFifCgOyAH+w2TAVFOA+qe9DVhAEdPNupvPLVSh6IzGUcVfXuE/q7Y2tpRnjiRN43n672C+FAu2MM1NnrgSCVIp21k10rltPy5tvYS4sROrlRcCvn0WQSrE1N9P00kuox47F6667zty/t69Xq7+nU19dhcE7mPEjRzJ79myX2elArlCcWj09laufl5fH7NmzXbnuZrMZpVKJ3W5n/fr1WCwWDh48SEtLC9/73vdw2O0Upe8je/M6l0Cx9X+vIZHJmPXoD8n48lNkSiUn9mwnfvxEotNG9zl+xtavcMrkTJo4nimz5tDd2sLHv3mG5pOFjLvtTlqqq0iZMZuotFF0trbQ3WPknXff4UB+ERKHgxBvT1b/9XmqTuShVKuxGI04HQ4K9u9h2Mw5DJs5B4VKTVn2Eda99GfGLrqDIVOmU5GbRXt9LSkz5+IdHIrNbEamVF7WtbWaTeRu+4rwocNJnT2PrK/Wsu7lP5M2dwHJU2fe0Pn8NyKnnvkVFRXs3LmTxsZGkpOTOXHihEuUSElJwcPDw+XXsHr1atzd3bn33nspKipiy5YtAFdEkBYEgbS0NLZt28b69evp7u7mk08+YfTo0eTm5hISEoJEIiErK6vP+VwMCoXCZTI7duxYnE4n3t7e/UbjDdKXU+JNa2urKFDo5PR0WShMrwcBJi6Nc5Urv+u5sShUMla9eJSc7VUYu60oVDKW/HIkLdV6dq0oxCdYw6KfpiGVnv0+yttdg0whYfbjCWz41zEOriqhu83MsOmhRA7zpbvViLuHktyd1QgSgbRZN7ZPyNXE6XTy1VdfodFomDFjxkXt21jeSUicJ/oOM1KZBL8AX+ZOW8DGHav55KPPePTJh3A4HGzYsMFVMQ5Aq9ViNpuxWCy4u7tf8oT6dLZt24bdbufxxx/Hx8eHuro61q5dy+7du4mPjx/Q+8Fut7NmzRqMRiOpqanYbDZCQ0NJSkpyiRDu7u48+uij5Obm8tVXX/HWW28hl8uJjIxk7ty55zSQP5U+5+/v32/lLLvdzrFjxxAEgR07dhAWFIkxO4xF3x9JcKznJZ+XxN0ddY+4qBEYGEhU1NVLfb6aDAoUgwxyHVNRUQGA4u23qTKZ6Yl5DHcPcSIyatQoNmzYgEwioSIyks5eg5xTD8qkpCRqa2vx9PSko6OD/fv3k5OTQ0pKSh+zsitNYmIiCoWCDz/8EIPB0OdBLu8NS3N0dyPvZ6XW++676Vj5CS3/+jfqMWNQjRi4ihkXgtTLk57MTJxGo8u882qjmz2bjk8+pfnll5H5+2NrakJ3yzzUI0bQuXYtjq4uAp9//roa6Jl7DLQ7BARg3LhxAy5MnEKj0eDm5sa2bdtcr8lkMhYuXEhGRgZbtmxh6dKldHR00NDQwNKlS2lvb2f79u3k5uYiCAI+Q4ZRsnMLVpMJQSKhobSYUQtuY9jMuQybORe7zcqHP3+Kne/+j5C/JaM8LT3lWHYWCApGTRRLJWp9fPnen1/GZrHgFdg3UsTT1w9PxND4orw8HIW5rPrDszjsdpKn3oS5R8+YRUsxdHRwePVn7Fn+DofXfM6QqTM5sXs7EqmMg5+v4ODnKwAQBAl5O7fi7uVDe10NCpWa23/9e4Ljk855zYrS93Pws4+47dnf94mOyNmyEUNHO/N/8iu8gkKY8dDj5G79ii2vv0LB/t0o3NzQePsSlTaSqOEjEa5CBNZ3mejoaNzd3dmxYwdNTU3I5XJOnDhBXFwcdrudrq4u5s+f7zJGi4uLY9u2bcycORNvb2/XimdYWNgVC/8dPnw427dvp7u7m9tuu43KykqOHDmCQqFgyZIlyOVyXn/9dUCc7FwOgiAwfvz4gej2d4LTBYrY2Fi0virq0hvoajESluSN1vtrv5pTUQ4xI/xJX12KV6Canm4LH//fIQA8A9Q0lHWy/vWj1JqO4+fry8x5E/Hx/zo9wGSwUnykkfCRGj7fsByCFRSkyxAQaCjtxDNQTWuNHolEwOFwAqBvNTFhSex31qjxYjhlILtw4cKL8hqyWey0VOtJnR3O5NEBOOzitR81KYWD245R11xCc3MzbW1tdHZ2smTJEgICAqipqaGwsBCJREJNTQ3Hjx/vV6BwOByUlZUhk8nw9PRErVZjMplob29Hq9W6FhE6OzvJycmhoKCA6dOnu55JERERTJw4kfXr13P06FE8PDxcfhpGo5Hm5uZLEiQPHjzI7t27sVgszJs375zVwKRSKSNGjMDb25tNmzahVCo5cuQItbW1+Pn54ebmhtlsxuFwEBcXR3BwMHl5eaSnp2M2i8azOp2O4OBghg4dikKhwGAwkJ2dTVVVFSD6QyUGjSEnuwGfkMsbf0s07mi7ugGYOHHidTX2G0gGBYpBBrkO6dy4EafZQoWxB7XZjGTvPgw2G93qO/ENC6Nr0yYi6+p5+OGHqdq4kW0OB9vz8pBIJK6ydMOHD6euro7Zs2fz4YcfsmvXLtzc3K5JONgpz4GeXtX3FLLTJkiyfgbRythY3CdMwJCRQcBvfn3VH8TygEBMucdAKkV9BaqdXAjqsWPx/9UvUaemooiOpnj8BPS796AeMQJjbi7y8PCrah7aH01NTRQVFWG1Wpk2bRpNFWVYdV4E+onRPFcKQRB45JFHKCkpQSqV0tDQwNGjR3E6nWRnZyORSNi4cSMmk4n4+HiGDBmC3W4nOzub1atXu9qR+4dQU3gCN40Gh91OYPTXhmNSmZxZjz3FZ79/li2vv8KCZ54Vc1kryuiwOvDx1fbx1NB69/V8+SYzZ97EzJk3iakkf/k/4saMZ9p93++zTeyosTSUFJP+5UqyN61HppBzz19eoaYgD4vRSMzIMUjlCra9+S9sFgtJk6aS8eWnlBzJOKdAYTH2sPO9/9HT2cHWN17ltmd/T03+CQoP7qHo4D4iU0cSmiiaIKbNmU/qrHkcWb+KoxvX4KbRUnksh5wtG/CLjGbpb19Apb06JRy/i5wyhUxPT0cikfDggw+Sk5PD1KlTUavVOByOPqt7AQEB3HPP154hMpmM0aNH99f0gKHRaBg6dChdXV2kpKQwbNgwxowZg8PhcKVf3XPPPfT09HxrB9HXKxqNBqVSSUtLC83NzaTODqG5spvmqm6SxvcfzZIwNpCq/DYm3xGHxWij5GgTAdE6dKECR7eWk1uQjkXZRnN3JZVvlPPz3z1Nc3U31fltFB1qwGa1UtKZ3vs730NcqoKUyZEc+ryani4L4xfHYOgwEzHUh+qCNnK2V1OW20JAlI7oVD8Sxn778ugvFpPJREdHB4GBgTQ0NNDU1ITD4eDAgQN4e3szfPjwC27L6XRSld+Gw+EkMErXZ2IsSARSkoezt6CUw4eO0NbeikajISkpCalUip+fn8tbZsuWLRw6dAij0YhKpcJut7Nu3Tp0Oh1dXV3k5uaetQ8RERHcfffdvPPOO3R1dREaGnqGoeOwYcPYuXMnG3r9subNm4ebmxtbt25Fr9dz7733ujzTTj1HTpw4wZEjR9Dr9Xh7exMQEIDD4aCtrY3AwEB27dpFTEwMY8eOPcNA9GxERkbyxBNPAHD06FEOHTpEeXk5ZrMZuVyOw+Hg2LFjru2TkpIYPXo0LS0tVFdXU1FRQWFhoet9uVzO4sWL0Wq1uLu7k7uhBa23G0rV5U29pRoN3m1t3JuSQvQFpsPeiAwKFIMMcp3RvnIlDb//A06g7PbbCGhoIPLDD2lbvhxzj4Css5H6157DaTYTd+edYDQisdupa2pi7NixrgmhVqvljl5jxLlz51JYWMj06dMveyXrUlD1mj5+U6CQBwb0+/fpBP7hD1gqKnC7AvmJ5yPgN7/Gc+lSlAnxyP39r/rxQUzz8HngAde/1SNGoN+zB/9nfoIx9xjqCyjzdyXIz89n57atdDXWY1F8bSSpVCqxNNTgVLgxNOXKR534+Pi4VgsNBgN5eXnk5uaSmppKamoq77//Pu7u7ixcuBBBEJDJZNx+++0UFBSQkJDAzh07KC+2UHU8Fw8/8R4MiOmbShSamMyUux9kz/J3yN22idTZ89i3+nMcShVpo8++MnPOfoeE8f1/vX3WiVtgbDyLf/k8FpMRm8WCWueBd3BIn21u//UfXH9X5GZTU3D8jHb07W2cPHQAv8hocrd+RU9nB8Nn3Uzutk28cvdiAJRqd6LSRjF26Wy6u/PRakVDRUEiYcytSxhz6xIA7DYbBft2seV/r3J893ZGL7jtks79m3R3n0ClCkcmu/rPpuuZtLQ00tPTSUhIIDg4uI9/y7lCj68mt90m3gOn7uOAgL7P8UtJ7Rjk8hEEAR8fH6qqqsjKymLcuHEsemY6NQXtRA3/WkS1WCyuNBp3TyWLfvK14WlQrCeHDx9m5ZubcDqd4Cb6hlTmN5Nfmcn2z45StFNMCfAL1xI61U5OUStLly5l7dq1VFuyyf18B0OGJLNk4a30GA14enoiCALhyT6ED/UhZ2sVTRVdlOe2EBCpwzPg0g06vw2sW7eO/Px8hgwZQkFBgXjdET/PpUuXnvd773Q46WjqwW5zsGt5IU2V3UhkAoHRZy4UxA4L5lC2L0cyDwNiOm5/7Q8dOpT09HS2bNnC0KFDKSkp6SNKTJ48mYiICDo6OjCZTCgUCjw9Rd+nPXv2sHLlSrq6uli2bBmJiYlntC+Xy7nrrrvo6OhwpVqA+OyQSqVs3rwZpVKJ1WrljjvuwG63s2rVKjw8PPD396e1tZWTJ08iCAIqlYqCggICAwNZtmzZWSsXGTrNtDf0EBLv2e9v8MiRI10llk/hcDioq6ujqakJX19fV2RHdHS0S5itqalBEATc3d3RarV9jt9aW4FP6OVHL0s0GgTA2+H4Vgu/gwLFIINcJzitVhr//iLty5ejmTqV1u4uTHI50UOSUY9Iw+4XgvNPxzGv+QSHXg+A4cABpM0tBHd20hQSzJQpU/ptOz4+/qqVUeqPUyvMRqOxz+tSHx+QycBmQxbQ/+qJIjQERWhIv+9daeQBAcgDri+TQM20qTS9+A+MOTnYmppQDUBe6MXicDjYsukrutrbkUplqDtb0FiNeI6fwY4dO9DIJOB0kjry6nmdgJhP+oMf/AC5XO6655YsWYK3t3eftKbTJ3vxCQmUlZdTdvwYQeGRqHQeaH3OzCcdecsiyrOPcOCTD/ENj6D45EnwDyX5MkSYCxlcKNxU560kAhCalEzm+lUY9d0U7NtF4cG9jFm4hKMb13wtXAgCIxfchjA1BqTlJCliiI5KJnbUOJCYyTh0M2ZzPYGBi4mPew69vhCzuR5//7lIJEqkMhlDp88ib+dWju/axqj5i/ucg76tFX17G4ExF7ZiBdDZmUPm0duRSJQEBd5GTMxPkcuvn8om1xJ/f38WLFhwXZfN/DYPkG90fHx8yMsTS2Q3NDSgcJMRnfb1s62wsJDPP/+cO+64g9jYWCwWCyqVylV+sbi4mK+++or4+HgSExMxmUyMGTOGhLhu8l/NIvNIJpEhaQxb5EGPuZvt23OIi4sjOTmZ8vJyMjMz8fPzIz//BKWlJZjNZleFkVGjRhGW6E1Yojc9XRaW/y6djLVlzH3027sifD5aWlrIz8/H09OT/Px84uPjuemmm5DJZCiVyj7mjd1tJtw9lUgkAnarg6r8VnzDtBz4ooTSLNGTSamWMWVZPJHDfPs1Kw2O9URjikDlA9NmTSQ5uf9rHxwcTGJiIjk5OeTk5AAwatQokpOT6ejoIDU1td/nQFxcHGVlZZSXl+Pv739OE8zQ0FBCQ0OJi4tj69atREREMHToUPLz8/niiy9QKBRIpVJef/11FAoFSqWShx56yPW7brPZcDqdSCQSTp48SUhIyDnLKu/7tJjSrGai0/yYelcCat35zVwlEomrn2d7/2zpKHarg/aGnj7i4KUi6b0PHAbDZbd1PTMoUAwyyHVC6zvv0r58OV733UvAz35G3oYNcOwYQ++7FwCzIE5SFHYDHrffRvf2Heh37cLW0sIEvR6//3v+ipZquhzkcrnLQfl0BIkEmb8ftrr6s0ZQnAtHr4L8XRoka6ZNo+nFf9Dwpz8DoBp+9QQKm83mGqB0duvRdjbzg7+8REd9HSt/93O89G2Eh4dTUVGBRnBek/vxmykl56sIcqq6QWNLK4amenSxSbz//vt0dXXx+OOPu3L8BUFg+gOP8eEvnuLT53+JPTIJXx+f66ZMaFjSUA6v+ZxPnvsFbbXVuLlrWPuPFwCYdt8jaH188I+K5d8n/86evS/RIJEQ5R7FJ6PvR5BKSc/5CUZTPYU2H4TG9bS27sVqbQWg+OSf0OmGolbH4Ok5iiHTZrD9zf+Qv3cnUWmjUOs86Gpp5pPnfoGho517/voKfuGRF9Tv+obVSCRKAgMXU1f/GS0tOxk3bisy2ZkrTU6nHYulBaXy+hINryTfXMUbZJAL5fQqJ6eMhE9htVrZvHkzdrudTZs24e7uTkdHB48//jhvvfUWVqsVp9NJXFwcy5Yt62Oy6umtI9gnkjrKMYcU8dmXpa73Zs6cCYir8WFhYaSkpLBt2zba29sJDw+nuLiYnTt3cvDgQaZPn05cXJyYgjfZk/ztTbTW6fEJvnoeWdcLTqeT/fv3I5VK+f73v49er0er8qTuZCcSqY3o1K9/Z05mNrL17RP4hmkITfSmPKeZzuavF39SZ4Wj9VYSNdyvj9fIN5EppIRHhdBe78nRj7o5YNiLZ4Ca4TPDsBhteAe747A5Kc1uYtGdt8MiO7W1tbS1tZGamnpOAQDE38wZM2bwwQcfXLBXglKpZMGCBa5/JycnYzabiYiIQCqVkpGRQX19PZMmTeqz6HB6hZH+ojROx2axU3m8FZ8QdyrzWvm4OIMpy+KJGxVwxcaSbQ0GnA7nZftPwGkChX5QoBhkkEGuMA6Dgbb330czdSqBv/41lZWVHD52jFGjRuHTu4Lf0ynWMI9+8Q8EjQjHabGi370bqY8P2sjIfl2EryfUavUZERQg+jzY6huQXWT/HQ4Hb775JuHh4RdVcutGRxkTg+6WW+jauBFBLkd5nh/jgeTQoUMuQ0qp00F4QAAqjRZVXAJpc+eTtXk9y/7vb3y8dQ3jb1921fp1OQQGBiKXy1H4B2EqzafLIUXa1ITRaKSgoIDU1FTXtr5hEcx48HFa6ms5UFHHkOTka9fxbxCckIQgSGirrWbSsvtInXML6176M+5e3oyYJ6a3rD1wC+MthYwPAkGdzH8qSrlv7SwmqtoYprKwr0fD6jYjz6U+SJhpNwEBt+DjM5WGhrUYDCW0tx+iuvpdNJpk3DzkbP7vP1HpPLjnL6+w6i/PY+4xoFCr2frGa9z1xxeRSM4djuxwWGhs3ICf7yySEv9EgP8tZOfcS33DKsJC7wPEgXtb+wFUbiGcLPkrra17GDd2M2p15FW4qoMMcuPi35uWGBERQWVlJT09PS7/kq1bt9LR0cGUKVPYu3cvXV1dOBwOVqxYgdlsJikpCYvFwu23395vBZhlDyxi01ebKSwqYNSoUYwdOxabzeYyP1Sr1S6/hDlz5rj2mzBhAg0NDWzevJlNmzaxadMm13tKTz9OHAhmytKB+03L3VGN1WIneXIwKs25V8mNegtu7nIEQaClRs+Wt44TOcyXlKkhSKQSNF7Kizq20+Gk+HAD9WVd6HzcGDY9FJnizGfiqWoTeXl5jBs3DjelirIj7axdcwib2Q7A6PlRjJkfRV1JBzs/LMAnVIO5x0berhp8QtyZ/f1kGko70fq4kXrThZtKhiV5U1PYjnewO8NmhHIys4k9HxedsV1AlI5h08OIiYkhJibmgtuPiorixz/+cZ+Fg+42E4Xp9ai0CpImBp2zMowgCH1E2tNLE18oZqMNmULiOk5Vfhs2i4OJS+Jw91Sy88MCtr2TT1FGI8mTgulsNhIU5+EqszsQ1Jd0AOA7ACkeglSKoFa7Iqm/rQwKFIMMch3Q/tnn2Ds68Hn8MUAsxeTh4cGsWbNc2+g7et2CIwMRpFJ0c+fQtX499o4O1GOurBnaQKBWq8+IoACQBwVirfVDOI8a/02KiopoaGigo6OD2bNnD0iN7huFwOefoyc7C3lwMBLF1akz39PTw969e4mKisLP15fjaz8jYOo01/sjb1lE1ub1bPrPS0jsNpLGT74q/bpcpFIpISEhGLp1SCxG9DY7ixfMZffu3eTk5PQRKABSZ88jNzcXZ/nqK1K3/VJRqNSEpwxHKpMx5tYlCBIJS3/3J9f7Wwr/g8ZcSLUQzbTopVRVvcUP/E1AA04EenQ388yEP1K35+e8kr+ezbdvRqsQPSF8faYBYgRDff2XFBQ+y6wfP42zcyQbX/s7Hz37Y4xdnSz+9e8wdjex+V9vsO/jD5h6z0Pn7HNL6y5stg4CAxcB4OU5Dq0mhZqaDwkNuQdBkFBX9wmFRb89bS+BuvrPiY35+QBevUEGOZPW1j20tu1DIfcmLOwBpNIbyx8hMTGRBx98ELPZTGVlpasiwueff05BQQFjx45lxowZ6HQ6fH192blzJ1VVVYSGhnLnnXees22dTsedy+7AarWedyX9mwQGBnL//fdTX19PfX09bm5u1NXVceDAAbKys5h0WzySc0xaL5TO5h72f3ESnHB8Ty33/nE8Unn/7ZZlN7P5zTxSpoUSPzaQDf/OxWF3krOtipxtVSDAnO8PJXbk+b2oHA4H2zft4XBmBoquQDzsERicLVSXNTBtSQrGbis+IRrkSlGsOHHiBHl5eQQo42nYo+G9zfuxmOyEDfFmzIIoTuyt5ciGcgoO1KFvN6P1dmPBU8PFtASnaHgJEDfq4iPLhk4JQSqTkDQxCIWbjJFzI2itM6D1cqOmqB27zUH21kpOHmlk2PSwC2qzs7mHqhNtYoRGsjeenp6u95qruvny70ex2xwApK8qwW53MvvhZKJTL26RytBpJmtLJTKFlCETg/DwO/P7adJbWfF/GSjVMibfEU/EUB/KcppRqmUEx3silUq47ecjyd1ezdEtFVSdEKMGVVo5dz0/FqlUgtxNesmRFYZOM3KllKzNlQRGD5zHisRdPZjiMcggg1xZnA4H7StWoB49GnVaGi0tLdTU1DBr1ixXeDmAvs0EAi4VXztzJqH//Q9dGzagm3vxqvLVwGTQo1CpkEikqFSqfgUK3x8+he0b4acXwsGDB5FKpZhMJsrKyq6px8bVRqrTEfXpp1f1mDt37sRisXDzzTcjGA0UfNiKX2S0632dnz/hQ4dTlZeDT2j4GYaO1zMRERHs3buXxNGTaCosJD4+no6ODnbt2kVzc/MZ0UmFhYVotdrrzgDw9md/D3BGCdBWQw0V5a8RopBzx6TPUCu8CAu9n5aWbdjsBny8J+PmJnpyPD3iae7+6m42lW/ijoQ7+rQjCFKCg++gtnYl7d1bGDPuaepLbuXohtWkLZhGk+l5TPY6hs9fROb6VUgU3USNCyUk7LYzBnhGYy1FRc+hcgvH23sSANlbNlJ0xEDwpHKqaz5ArYqgqPgPeHtNwst7Aiq3EBoa11Ff/yXRUT9GIrm4idH1itPhEPOnrxPjy+8yZnMzVVVvYTI30NS0EYlEicNhpr3jMMOHvYFEcnGr6NcSiURCREQEnZ2ikWVTUxMymYyCggKmTp3K9OnTAdFPAGDSpEl8/PHHF1XO9WLFiVMIgtDHCyg5OZmSogqaGysoy2siNvXyK3rk7qhBIhGYuCSOfZ8WU1XQhk+wOzaLA68gNQ67k6bKbmqL2sjcVIlCLePYrhrydtfg7qnk1p+n0dNloa3eQFFGA9veO4HWx42AyHNXL9q2cQ/pR/cgdbjRo63E3a+HruZmshvzOf7yQWQ2DQ5FD9+7/w4i4oM4diwPGW5QG0TISC9kMgmxowMITfBCEAT8w7UERHlQU9BG/Bg1I2+OQOHWO327zIwEhUrG8JlfCw8SqQS/MFGYPiXGGDrMpK8upavFiM5XTDW2We1IZRIEQaDuZDuHN1QgV0qRKSSUZH49nlO6y7jn9+Nx08hxOpzsWVmEQiVlyS/H0lZnoDyvher8Ng6tKyNqmC8IX/vaVJ5opeRoE1Pviu+3FO2hdWUUHKxHEASKDzVw+y9GnRHlkrmpArPBilItY8O/cwlP9hGv49gAV0SFRCKQNjuclOkhNJSK35X1/8rl0z8extBpQamW4R3kjk+ohpFzI9B4ueFwOCnNaiJ7axWCACEJXiSMDaQ0uxmJVMBqslFT2E5TZTcKlQyL0cash5MHLIVE6q7BYRiMoBhkkEGuAD3Z2bS9/wEet96KtaYGv6efAiAnJwdBEM6oOd3dbsZdp0Aq+3ryoZ0xA+2MGVe13xdKV0sz7//0B0y68x5GzLsVtVpNQ0PDGdspo6MuukxmXV0d1dXVzJ49mz179pCfn09MTAwNDQ14eHj0yU38tnKxKTEXi9PpxG63I5PJqKysJDMzk3HjxuHv78+JPTsA8I+I7rNPyvRZVOXlEDd2Qn9NXreMGTOGQ4cOUVBQQGRkJCqVitTUVPbv388bb7zBmDFjmDhxIu7u7litVkpKShg+fHi/oc/XklPChNPpoLl5G56eo2lsXEfxyT8Tq7SjDLgftULMZZZKlQQEzD+jjRTfFGI9Y1lbsvYMgeIUQcFLKSr6HVnZd+MxVMnNET+iXfoCZnMncpkHQsRGEqfNpd3+FpYSI/UNXyCTK/D3n0tIyF04HBaO5T2Gw2EmLe0jl9BQeHAPTSUKoqakcPKk6J/h7h7H0KGvuIwzJVIVLS07aG7Zjo/3JMor/k1T0yZiY58lwP/ihFqjsYqKitfx85+D3WbAZKpFpxuGTjfsqq6Wb/rvP9G3tnDH83+5asccpH8Ki35La+supFINoaH3ERf7Kxoa1lFQ+CvKyl+7ISN3dDodSqWSpqYm6uvrkcvl/YoQ8fHxPPXUU328K64ms2+ewfLly9m34yCxqZdXIai1Tk/BwTriRweQPDmYw+vLyN9fR0NZJya9FblSit3qwOEQq2QExXgw97EUDq0vw2F1MHFpHG7ucjwD1ATHeRI70p8Vz2WQs62KOY+c3dfIbrdzNPsISrsHP/zpYyz/+H1aW1tZsGABpXn1lNcXYLbU43A42LZpF98LXURpaSluhmDmfH9ov1EEEqmEoVNCGDrl2oj+saP8SV9dyqcvHMYvQseY+VFsfjOPoFhPoof7sv39Atw9lTgdTsxGGyPnRpA0MYjuNjNr/5lN5qYKWmv1NJZ3YTXbuenBIeh8Veh8VUQO86X4cAPb3s3nyxeP0t1mYvEzI2is6GLHBwU4HU5Ceyf/p9PVYqQovYGUaaEkjQ9i9UtZfPDsARQqGYHRHrhpZNitDsqPtZA4IYipyxI4sKqEvF01JI4LZOKSM42cZXIpoYneAEy4LZa83TWMmBuBqdtCR5ORggP1FByox91TQU+XBZvFgXewO2qdguxtVWRvFSNtcIJEKuAXrmXMgiiqTrSi81MREj9wflUSjQb7YIrHIIMMMtA4nU4a//JXTMeOod+zB4lajfamm1x1lmNiYs4oB6pvM6E5h+HR9cah1Z9iNRkpy85kxLxbzxpBcSkUFBQgCAKpqak0NjaSk5PDsWPHcDgcxMTEcO+99w7Icb6rOJ1OvvzySyorK7n77rtZs2YNnp6ezOgVw5ory5AplHidVvYQIG7sBMbdvozU2bdci25fMu7u7tx0001s2LDBlbbh4eHBE088wZ49ezh48CBHjx7l1ltvRS6XY7Var6v0jtNxOGwUFPyShsY1yGQe2GydGOQxvFtTy/KJPznv/oIgsCh2Ef/I/Af3b7oflUzFK9NfYWfVTiJ0EST7JhPgP5+Skr/Q2ZmF02klKNAXU0MNw4e9hVodzZHMxXgM243ZbKSr2gNH0FHkSjWdXdn4+c2ipmYFen0Bw1LeQOMuDhR7OjuoP1kEToH27DGkLJ4NSAgPf7DPqrWP91TU6mhKS1+koWE1ra27kUhU1FR/QID/zTidDopPvoCbWxAhwcuQybQ4HBYEQYogSDGbmygrfxWJRElz81bM5nrq6j/7xjWQEhvzS8LDHz7j+tjtPdQ3rEGh8MHPdzYWSzNK5aWXIHbY7ZRmHsJi7KG5quKCzUUHGRicTidWazsymY6GhjW0tGwnNuYXREQ85tomOHgprW17qa39mKjIJ13ildNpx+EwX5+pHzYz2K2g1CAIAn5+fpSXl9PZ2cnQoUNxc+t/LDEg4kRbGRhawTsK6rIhYgIozm+YHB0djbd7IFWdJ2htnI5PwKVN6E4eaWT7B/ko3GSMmBuBVCYhKtWPwoP1CAKMXxyDocOMTCnFP0JLcJyny59i+t39+1+4ucuJGx1A/v46zD1WlOq+kSMdzQY+/2gdDokJi6OHUYnT0XqqefDBB+np6cHHx4eRI8HhmIfdbufNf66gtq2EvXv24XQ6CPGNuugUh6uFzkfF5DvjaK3RU3y4kdUvZSFTSCjLbqYsu5mQeE9u+eFwJFIBh92JvNdnw8NPTcwIP3J3VCMIkDQhCHcvN+LH9E1FiR0VQOZXFbTWGZBIBNa8nIWh00JIvCfdbSby99cRneaHsduCu4cSiVQgY20ZSGDE7Ag0XkoW/3QEZTnNGLst1Jd20tFoRyqXEhLvxdiF0UjlEqbcGc+4W6O/jj45B8NnhvWJLAFRFDm2s8blVRIY40HMCH8kEoGmyi7qTnYQO9IfpbsciSC40olG33JxC3AXgsTd3WWS6TCZEBSKMyInb3QGBYpBBrkGGA4exHTsGMqkJMwFBahuuw2rVEpTbS1dXV3cdNNNZ+zT3WrCL1zbT2vXHx2NDRzftQ2ZXEFtUT52m9VlkmkwGLDZbGdUW7gYCgsLiYiIQK1WM2PGDHx8fDCZTLS1tVFUVITBYMDd3Z3u7m5kMhkqVf9lGk+vMT6IiMViYc+ePRw/fhyJRMIbb7yBRCLh/vvvR6FQYDEZqS3Mxzc84gwTRKlMzsQ77rlGPb88RowYgUql6pMq5O3tzeLFi5k4cSJr1qzhs88+w83NDYVCQVTUwA86LgWjsZbOzqP4+89DIpFRVfU2DY1rCA97mM6uHBQKP9Y2g0PlhlZ5Yc+PW6Jv4V/Z/6Kss4wOcwcL1yyk3lAPwM1RN/PnSX9mzOgNSGXuHDm8kPqGVajVUfj4TEMQJCQmvMDxE0+jcgsnfMgLrH/pr3hFqAmfk0VO7vfR6wsIDLgVP7+vn3NlWUfA6SQoPpHy7CzmPrkCueLMcHqJREZ83HPk5D6A0VhJXOxvsDuMlJW9jNFYi16fT03NBwBUVr5JUOBiautWIpGocHePRa8vwOEw9balZtSoVZiMNcjlnmg0iXR1HaOq+h1Ky14mIGBBH/GhuXk7BYW/dlU3kUo12O16hiS9SFDQpa34NpWXYjGKwu2J3duYdt8jl9TOIBeP3nCSkyf/RFvbPkACONBqkgkLO9M7JSz0fpqavqKw6Dls1k48PNKob1iN0VhDcPBS4mJ/g1R6jdI/cj6GqKmg9oYTqyH5Nlh5Jxg74LE9AMTExLBnzx4EQWD06CvoWWXuhndvBv1p0ZLR0+Huz0HaO6m3GqGrDuwW8EuE3t9fQRC4+eZ5rPj8Pdau+oqHnrj7gg5ZmtVEVUEb076XQHeriV0fFRIQoePmx1Nc5TVjR/pTeLCeodNCGTHn/GV77XY71dXVSKVS2traaG9vJ2HMMPJ211BytInkySEYOs3UFXdQeaKVnPzD6NUV4BSQ2d2ZsWAcACqVqs/4QyKRIJFImDhxAmu2VZBxKB252YPxCy+9XPXV4JT/RML4IA6vL2fiklgKDtRTW9zOnEeHukSJb2apjb4litqiDsbeGn3WCBCJROC2n4lGmE1VXWz4Vy5Rw32Z/f1kcndUk7GmjA+fPYjJYEWmkBCa4EVFXitjFkS5Ujr8wrUXND6+EHHibOh8VUy6o/8S2v4ROvwjzp36M5BINBqsNTUAtL71Nh2rVxHz1VdIziI83ogMChSDDHINaHv3PWSBgUR+tJyW119no0aD9YMPiImJQRAE4uL6PgSdDif6dvN1q7B/k+xN6wCBKfc8yM733qChtAS1Wlxl+uKLL+ju7uaHP/zhJbXd0tJCc3OzK2/Ww8ODKVOmAFBfX09hYSGFhYUMHTqUN954A3d3dx577DFXOL7dbqegoICamhry8vIIDg7m7rsvbCD0baGsrIz29nbUajWhoaFotVqqqqo4ePAgZWVlWCwWhg8fTlJSEqtXr2b+/PmEh4fT0VDPx7/9KcbuLiYtu+9an8aAIpFISD5LVQ5/f38eeughDh8+7BLHrqYpq8lUR37BLwgNuQd//7l0d58gJ/dh/HxvorllBxZLE1XV7zIs5b/U1X2Kl+c44uJ+7dr/xGczGRM05rzHMWQ1YmvqwWtyKGsXrcVL6cWKghW8lv0aP0j9AVa7lbfy3kLbUspv53+EoFARGnY/paV/Jyz0AQRB/I4FBNyC3W5Ao0lEpxvGsj+8yIZX/oahKgTCjxMQsIDY2N/RXFVB2dHDFB7ci6GjHa2PHxOWfI8v//wcFblZxI3uPxfex2cyISHfw2bTExb2ACZTLWVlL9PQuIbW1t24uYUyNPlVior/j6rqd/D2noxMpsNsrsfHZypRkU/h5haEw2FDLtfhoRvuatvXdzpqdTQZh2ZTXvFvEhP+AEB5+b8pK/8nGs0QUlL+g7GnnI6OTDq7ciiv+BcBAQuRSC7+nqg6cQyA0KSh5O/bzeTvPYBU9u3w1rhesduNHD/+NC2tO5FKNURGPonDYUGrTcbPd1a/3iYeHiPRapJpaFiNXO5NS+tOlMogAgPmU1u7ArU6ivCwB3E6nXTrT6DVDHF9H76JzWZAKlUPjDDeVQ9rnoCxT4B3NGz6Oez/J7QUAwKY9aDUMH36dCZOnIjD4Thr9MQFs+svIFfBhKfhm6u2u/8K+kaY82cxisPpgJ1/hOWLIWg45K+Fzuqvt4+YCLoQse+Tf0rc0HA8V4VS01iG3W5HKpVitztw2p39VsBwOp1krC2jo7GH0Hgvju+tBQFuemiIS5wACE/yZtZDQ4gafv4xVHFxMevXr6e7u7vP683JzXgGhpG1pRKnw8n+z0vQy2uwurdgVneSEJ/EiNgpCAKodecWq4aNi+XApmTM3Q4iQmOIukHGdsGxniz6SRoAfsu0OJ3Oc97HPiEaHnpxksvI82y4acTvXPgQH+7/60TUWgWCRCBxfBBZmyvxClQTPzaQ2qJ2So42ETvKn1HzIgfsvK453Y2Q8V8ISIb4ueCmA30TrH5M/I77xUPq3RA5GRRqpBp3zL0pHl1bNqMICf1WiRMwKFAMMshVx2E00nP4MF733ovE3R3ZQw9R+dprALS2thIeHn7Gir9Rb8Vuc9wQKR5Wk4kTe3YQN3YCiROnsvO9N6jJz0MVLYbEV1RU4HQ6MZlM/Q6Ujh07xsmTJ7nlllvOeN9ms7Fv3z6AfkPsAwMD8fLyIi8vj46ODvR6PXq9noKCAtfkc9u2bWRkZCCRSPDx8eHkyZPU1tYSEnLjmDpeDu3t7SxfvtwVPQIwevRocnNzUSgUpKSkkJKSQkREBIIg8Mtf/tIl7hxe+zkWk5Flv/87IYlDrtUpAOLA1NbYgzzw/KHDA4FMJmPChAlMmHD1/TUqKl+nvT2d9vZ0goPvpKszB7vdSG3dJygUvsTH/Y7SspfJyrobo6mKqKinXfs29TTRZGwi2efcJVGtjQbavzwJdieGww0EPJmKTKPikWGPcGfinegU4uqQrWgj73UXM+fo64wZ/wxhofchlaoJDl7ap73g4K/9K4LjExm/5C62vvUqt/36HTy9Y1nxy1/SXl8HiJNzN3cNCeMnE5Y8DLWHJwX7dp1VoABITPij62+VKgxPz7GUlb0MQHzcc3h4pDJq5BcYDMVoNEn9DqL786S022wc+mwL7jHTqK1dSUDAArq78igr/yeBAYtISvozEokSL8/RBAffQXPzdo7lPUZj41qCgm4/5zXuj6rjufiEhjP61ttZ/dffU5Z1hLgxN5aHy43GyZN/oqV1J1FRPyY05HsoFGdPa6gtzOf47m1MuONuhgx5Eb2+kICA+ZhMdSgUPkilanqMVVRXv09I8J0UFP6axsb1BAYsIjLyCbq6j2M0VhMUeCs2m56y8ldoadmBQuFPWOh9REQ8fllCha02nbwUHaGtO/DrrgepUhQn1D7Q0wqNxyFcXM1XDETFp/x1sOev4t/Vh2DBq2L6hiCFst1w6H8w4l4Y/+TX+yjc4eC/oPIAxM6CkfeLokRPm7h9eyXkfQalO+Duz4kIjyK3opqa6loiIsPZ/+lJ6ks7WPa7sWd0p6Gsi47GHqQyCdvePYHTCTc9OASpm6NPhRFBIhA/5uzGm3a7nb1792I2mzl8+DB+fn7MnTsXuVyOWq2moqKC7du3k5KkoO2wJ3tWFiOENqC3lRDgH0BAYAo333zzWaM1v4lEKuGx527D4XBe1qp+v/S0gbVHFIjU3qDyEqNp3Dxc0SoDxYXcu+cTJ76Ju4eyz98P/H0SMrloyDl0SggTbjfh7qm8NpGvhlbxmg7Esc16qM0EvyRY9QiUi9FOaAJg+DIoWA/dDWIEUsUBUdyTyGD2C0jcNTj0eswnT2IpKcXrue9dfn+uMwYFikEGucr0ZB7FabXi3mtSdeyYuIKmUqkwGo39Try728SQZK339e8gXnhwL+YeA6mz56HS6vALj+TEnu3Eu4sTnFMT44aGBiIjI/vs63Q62b17N21tbbS1tbnSCk6xYsUKysvLmTBhQp/SVac4ZS66Z88eKioqSEpKoqWlhR07duDr64tSqeTIkSMMGzaMhQsXYrPZ+Oc//8nWrVtxd3dnzJgxZ/Tp28ahQ4cQBIFHH30Um83GkSNHOHLkCB4eHjz88MPodH3DFE+JE/r2NvL37mTo9FnXXJwAMGTU07G2FP8fpqIIvTFSny4Fk7mBurovCAy8HYXCi6qqdwEHw4e9jZtbCEjUpDcX0Ow2kQDDVqRSDf7+c137n2g5AcBQX9HYzWGxYy7pQObjhsxfXMV1Opy0f3kSiVKK9/cSaV1eQPvqElTJPjhMNrSTQ8XGyvfxZHEGX4aF8EX5BoKSl9JsbGZE6Pk9XxInTWXvx++z692VGDs7ECQS5jzxY0ITk/EM7FsNJWnSVLI3b8TY3YVKe2FhsylD/0V9/Rf0GCtd4ohEIkOrPfu9qm9rZfeHbzPtvu+j0nnQVFFKzpaN5O/didbfg+S7QsnJuQ+Hw4Kf7yySkv6Gw+7EajKgUInXztd3JlptCsUn/4hGm4xW038Oe39YzSZqi/JJmT6byGEj0Hh5c3zXtqsqUDgcVgRBgiB8eyuIOBxWGhrWYrW109WVR1PTRsLDHyE66qkztnU6nRi7u1Cq1aR/sZLDa77A6XRQV1TAnf/3VwIDxd9nlerr/PTw8IfIy/sB+w9MwmbrxNd3Jg2Na2hoXOPaprLyDRwOM3K5B+FhD2MwnKS07B90defh738zOu0wVKpw9Pp8ik++QEz0T/H0HNXv+bS07KSxaSMKhR+2+n20eSnoUTXjc3wvkiELYcR9okDx+gSoz3UJFJdNTxtsfAYCh4kTqO3/B68OB5sJpApw2CAwBWb9se9+456AsY+Lk+ZvelFM6I2kPLEaVj0KK79HnOcT5AIFeScJDw+jNLsJY7eVzmYjHn6iAGC3OcjfX0f5sRbkSinT701k6zsnGLcomuKmI6x88WhvKsVEJk6ciEKhOKepcUZGBnv2iBPEiIgI7rrrrj4LJCEhIej1ejIyMhg7fQKmVgm55cUMHz6cW2+99ZIMk/uLCOlD4wk4+G8xXWbmcxCcJk6Qcz+Gos2g8hQjWbrqoLUUUu+CzhrI+7xvOyovMLaL0SqRk0SPkAlPQ9Cwfg97vSH/xnXSDsRCnaUHmgvF69JWJl5Hv0TwDIeOKvHaAwy7E+S9xyvaDJ/cBWn3wPxXwdINJTtAGyh+JxTu4ndE5XVmZJHNAsc+haPvgVIn+sNUHwKHVRT3nHa45SXwHwJbfysKel6RcO9q8ftrs4gCxsF/wfb/QyJ9HHtPD12bNoFEgm7WrMu/JtcZgwLFIINcZQzp6QhyOepRI12mmFFRUURFRbFz584zBAqb1U53qyhQXO8RFK211ez/5EN8wyMJSRRXbCfccQ/b3/kv6R+/D5FfD977Eyhqa2tpa2tjyJAh5Ofnc/z4cUaMGAFAZ2cn5eXlfcqj9RdeOGXKFPz9/amtrWXcuHG0tLTw6aef8vrrr7vKts6YMQOZTIZMJmPUqFEcOHAAEKM7Hn/8cVQqFdXV1YSEhPQp9Xq52O12jh49SlZWFvPnzyc0NNT1XldXF1KpFHf3KxcR0NPTQ1ZWFsnJya4SmaGhoaSkpODv73+GOHE6uds24bA7GDX/8tzVBwKH0UbXtkoALLX6b4VA0dy8nbLyfyIgxc0tGJvdQHjYQ9TULsfptPGTYzv43tCnmJ7yHgcq1/DTI+/z9IinWVHwP7ZVbgOc/D4mmbTQObRbDDy772kWxizk44KP0Sq0JHiLz5XOjWUYDon54eoR/njdHo8how5LVTdedybg5m/CI6mWjpxAzCUdABiONCJROBBaipArfsk9tlzespzgyOb76LZ0s2PpDow2I//N+S+ZjZn4qnz508Q/Eab7ehInVygZefNCMlZ9QsTwEUy77/t4BQZ/8zIAMGTKTI5uXEvhwb2kzppHUcZ+wocOR607u2+NQuHTx9jwQsjbuZWi9H3YbTbMPQaqe9MtotJGUZ6dibvlHgTlCkJC7iI87CHqiopY9dfnsRiNRI8cw8Jnfo1UJmNYyn/JPLqU3JyHGDduCzLZmfej1dpBe8ch/Hxnu55Z+fu3IVF0EzdmAhKplCFTZnBk/Sr07W1ovLwv6lwuBZOpjqzsu1G5hZOa+m6/IoVeX4zN3o2HbsQN6dWj1xdTUPgsXV05AMjl3oSFPkBM9DOA+Bti6GjHYbfRVlvDkXVfUnU8F5lcgc1qYej0WcSNncC6l/7MgU8/YtajZ6Ym+vnehE6XhiBIiY56Gm/vibS07MJiaUWnS0EqVXOy5K8oFX5ER/8EudwDp9NJReV/qaj4L83NWwCQyTxxOEw4HCaKT/6RkSNWUl2znPr6L4iM+AFBQYtdqUanDHABPLpsdOpk1HroCQsfD1FTwOkEdz+oPwYOx5kTposh52OQq6Fwgzihu3e1KETEzoL0f4EmECx6sBhg1h/EifM3EYRzG2UmLwaHHb58mPCyk0h5hIryCpqru2miAIeniZrCBDz8xEjH0qwm9n5SLO46JYS4UQGEJXlzsqyQo18eZdiwYTidTvbt28e+ffvQaDQsXbqUiIgIurq6KC0tJTExEb1eT0NDA7t37yYhIYE777wTQRDOuNcFQWD27Nn09PRwKPMgAOHh4SxcuPDKVHNqKoC3Z4nXTa6Ct2aI4f+tpaLQE5AChiZxoqvxF8WG/f8EQQITngKfOJApxXSa9kpxVT7zHag8CAoNHF8lphKMfQyipw58/+29E+/+rk13g9hXczeEjQGfWAifcHn36LmoTBevo9pXNG2tzoC8L8DU0e/mp4JLBQHY/RdRcPCOFiOA3Dwh60Mo3gKmTlGcE7cW73tju7i9T6x4DQzN4r5tZdBVC/7JovcKAoz/AYSPh6JN4mc86mHxoI/sFL8Lp3t8yRQQN0sUMP49GkndfrBa6Vy3HvXo0Ve8qtu1QDg9zPfbwKhRo5yZmZnXuhuDDHJWyhbfhlSnI+KD99m1axd79uxhyZIlDBkyhObmZgICvnY4tlrsYukkNxndrSYefmkybu7XZ36yzWrlnR89gsNm447n/4JPyNeTk/qTRXz0+2cxxA5DpVIhCALx8fEsWrQIEAeJ7e3t7N+/n9zcXH72s5/x5ptv4u3t7arIkZWVxbp163jiiScICAjAYjLyxR9/S3DiEKbde6bb/un09PSQnZ1NbW0tUVFRfUzCrFYrFRUVaLVa3nnnHZfoYbVamTFjhsvfYiBYv349R4+KKzunqmKUl5djNBopKChAKpUyevRopk2b5ioL19jYyNChQy9pcnDK6Mtms1FVVUVmZiZGo5FHHnnEVX/+QvngZ0+i0uquWSlES1c3jXlbCUibSd3WLXTXFuJmCMc3YTJet8Zekz4NFDW1H1NU9Dta7QocUh3hKh12Rw8WcwMgkGGL4dP6epw4kQgSHE4HWrkWk92E1WHlydQnSa9Lp93cztpb1/LEjic4UHvA1f4r015hZsRMLHV6mv6VjTrNH4lWgX5PDfIQDbbmHpRRHvjcEYTw/jycTUV0x7yHfORkEAT0+yqhLhOnDaxCEg6bk59HvEypeyUmp43vp3yfVSdX0W3pZkroFNLr0hkVOIoFMQvIbcrlxyN/jFKqxOl04rDbkV6Af8dHz/6E9vpaghOSqMg5is4vgOSpM+jp6mL6/d+/bJ8Gp9PJ+888QWdzI3arFYAp9zxEePIw/KNi+PDnP8TpdHLv315FKpNj1Hez/JdPI5FKiR01lqMb15IwfjLDZ91M6JAUurpyyTx6O1GRTxMd/aM+x7LZDGRlf4/u7uOEhNyDRCKntXUvBn0ZgsRJQMBCkoe8RHt9Pe/95DHG3X4XE++4Mr44druZkyV/prl5K06nDbtdj8NhITr6GaIin+yzrcNh4WD6dMzmBjw9x5A6/D2k0ksTyTs7s6mqfg+JIMfPfzb+fnMG4nQAsaxuU9NXmC3NeHqMQqdLwWYzUFL6V2prP0Em05CY8Ed8fKYhlapora5mz4r3UGm0dDQ1UF9c6GpL6e5O6uxbMHZ1ETVsJNHDRyNRydj42otU5Gbx+BvLL+j+vVAcDisGw0m6unLp6jqGw2nB3T2e0tK/o1QEYLY0olD4YrV24OU1nra2fQQGLiIp8W+0tx+gcefDxDtGkqtIp1MnI8RnPtHJvxfL8i6/DVpLxBlXxHhY+G9xonMxlO2GD2/9+t9TfwXTnx2w8z+D+lyc2Sv5x+4QTO6dRAcN4WSdKBwOD5jFjCVpuHso2b2iiMrjrSz51Ug0Xm5IZRJ6enp47bXX8PPz44EHHkAqlVJaWkpjYyNHjx6lvb2dBQsWcOjQoTNKnqtUKh577DE8NSrRN0OQwsmtYopM2R7oroMFr+GMmkJWVhb5+fksWrTo62prDjvkfiL6bEgVohhgMUDCPEicJ34GZ/sNd9jhyDviPg4b+Mb3CktWeHS3KA5lvA5V6eARJqbPBPQTGVa+F2Ru4qS/P8x6Me1DIoF9L4mTdGM7PLwVKvaLEQUSuShs1WZC6BgYshDaKyBuTv8CQuZ7sO15sbxmwFBxMt6QJ0YgKDXi+c97EWS9qS/lu+HTe8V+KLVgbBNfH3G/mC50+jUytEJbKYSOvvSUivK94v3rdHz9mkwF8bNh6O2iaOEdLYo+zUXYauppyYzBLdYDzxGdcOhNwAm1WeI2j+yCyv1QfVgUK4YsFIWKumwxksUnBpqLRTFCIhUjmZqLRE+JCT+C2JkXfC5Oh5PWjwqQ6hR4zI5AcqpyzK6/0Pb2azQe9QQg8Ad34hXVAfP/OeApPFcaQRCOOp3OfkPFBiMoBhnkKmAqLgaHA3tXF+aCAvx+/GNKSkrYs2cPqampJCcnIwhCH3ECoKG0E7PBhtlgQ66UolTLzmtKdK1ora5E39rCvKd/3kecAPAICESw2wFx1cFms/UZIFRWVvL+++8DkJSUhEqlIjk5mQMHDtDT04NaraakpAStVoufnx82q5Xtb/+X+pIiGspOMvymuXgFnd1DQq1WM3HixH7fk8vlLlPSe++9l/z8fOx2O4WFhdTX11/UNXA6nTidzj4rKnq9nsOHD6PT6Th69Chjx44lISGBDz/8kC+++AKlUolMJmPs2LGYTCbS09M5fvw4Hh4e1PS6NDc1NTFz5syL6kdbWxvr1q2jslKMNBAEgaioKGbMmHHR4kRnUyMt1ZVMPY8QdCVobzuCrdpCWck/0XtlU5wugM4JvcEesqo/48UFChSnVjeuEhZLCyZzA1KJGypVOHa7Cbm8b5TKnpLlWKr+QJsQyF/ru7E7jUglFiROK4+GxqFUx/FJ0W5+MfoXtJnEwdzi2MUopAoe3PwgUR5RPDrsUbzdvPljxh95dv+zHKg9wM9G/YwGQwN+Cl8my8biMNlo/7wAiZsEz/nRSNRyZN5uGDIbkWgUeC6IQvj8TmgrQ/CNRdf0Kyi7GTqrUdEMskJ4aA0Ov9E0/DOT39Tdgkn9G/7p483beW+jkChYectKErwTeD/vPV7Kepm9NXsBKO0o5R/T/oFOoTtjclenr+OpnU9xZ8Kd3JHwtW/Fwp8+y5q//5GKnKOk3byA4vT9pH+xEoDAmDiGTrsJfXsbOVs2ovXxYcjUmf1W/TgbzZXltNXVMP2BRynLOkLYkBRGL/g6Omjinfey9h8vsPvDt7HbbBQe2IvdamHZH/5OUGwCCpWYAlCUvo8pdz/IsJtuRqeeTFX1O4SE3OWq/uF0Ojh+4kd0d+ejr/Wilo8AKZa2ANoqvIkakUJj4zokEiVRkU8SP3YimRtWMWzmHLQ+vhd+s50Dp9OJ3lBES8sO6uu/wGiswsdnJgJOIiN/QHX1+5SXv4q313g8PEa49mtsXI/Z3EBQ4O3UN3xJQ8NqQkLuuujjt7cfJiv7LuRyLwRBSkPjGpIS/0Zw8JIBOb+y8lepqPg3AIIgIyhoCW1t+zCZ6ggLe4CoyCcxdtqQSFRU5GSz7qU/I3dzw03qjlzhxuS7HsDNTYNHYAA+6lDslT3gA4bt9dStz8B9dCBJCZMoPLCH7M3raa+vZeKd954zoudCkUjkaLVD0GqHuK6tw2Gjvv5LLJZWUoe/i06XxtGsO+jqyiE6+hkiIx5HEKT4KBLwOdEMc6Yy7HgdZaZaaoRNNKTvJ3nIS/gGDRd9HaQKMbzcaoQ7l8OeF8VV97R7+590VmWIK+5KHax5UlwNTrtXXNWf/NPLPudzEjQcwWrCf+cuyp02TtYdw13wxeBsobSimLrnTUQN86OhtJOQJA9auurJyCrB4XBgsVgwm83Mnz8faa/BTExMDDExMaSlpfHJJ5+wdu1aAObOnUt3dzfe3t4EBwXhba5Cufc5MbLAZhKjPUwdgCCuWktk8NHtCEvfZ+TI+YwcORJMXWLYf+tJKPwKqg6KEQwSmShwyN0gezm4+4u/PfFzxFQAqVycuA5fJkY57P4L7H1RnIhrAqCtXFyNv+Vl0PX+Vl+IKBR1nsUUpUb8D2D2C2Kax+sT4M1p4gTe3V8UDsyd4qS9ZDvs/rO4/bx/wJjTKgy1lcP250VfhMjJoqhSfViMsgkcJqb19LRC7koxzai7QUxjsBjEbe9cDp6R0FkligAZ/4GaTHEfrwhRKKnNFD+LiEnisSMmgqY3UsBqFMU3m1kURuT9CKfNRfDl98X7d/pvwNwFwSPEVA5p39+h7v216Pf64DB54LQ40GfpcZ82Fvld08QNHHZRoFBqwTcWRj7Q91jxAye4nsJS0YUpX6wYZSpqw//JVKQaBYy8H8kH/xI3EgS09f8CRZIolPQXvXSDMhhBMcggVxhbWxulN8/D3tlJc1AQbTExTH3ud6zauhW9Xs+TTz7pMnL6JofWlXF0UwUabzcUblIWzIuk86ty1MP98FgQfV0JFcd3bWPL/17lwX++gXdwX7HA6XTyrwfvwBqfypgxY2hoqKegrIJf//rXyGQy0tPT2bJlC3PnziUxMRFPT0/q6+t54403WLBgAampqbz44osoerqQlBUgIGCzWkidM5/ju7YRO3octzz98wE9n08//ZSmpiaeeurMPOWzsWHDBsrLy3n44YdRq9U0NDTw8ccf09XVBYgVR5588kkUCgXZ2dlIJBJSUlL6CBrV1dXs3r0bu91OWFgYer2e7OxsvLy8kEgkOBwOHnnkEVdVFBCjQLKysigsLKShoQGLxYLdbkcmkzFnzhz8/Pzw9/fvs8/FkLVpPbvef4OHXnnjDCHIUtONtd6AIlyLPGBg01MMLZVk5M4EQfydCpV/H2NFIxrveIKmzSUjYy4+1fMYfv8/z/1d0DeL7vYnVou5vFd4kG02N1F88gWamjYBjj7veRtvIjhsCTU97+Phm8rJyrcw2B28XePP3f4PkOCbyB7LQQSVjM+KP8NoMzLUeyhvxb+Ge4wPguzre8XqsCIVpEgECe2mdmZ8NgOb08bCmIW8MPEFBEGgY2MZ+n21CEopTrMFH8WfUSV6w03PiwO1U+z4A+x/GRa9Dl5R8N5ccaDtESbm5C59D4aIK6n6jHo61pSg9O2k3LCT70ds52XVb0lt9kXSU4q76Y88NGQo4QHDGREwghcyXsBL6cWLU19kdGDfEoe/2f8b1pWuA+DOhDv5+eifo+wt12g1m2ivr8M/Mhqr2YTVZOKLPz+HzWLhgZf+w94V73N0w2oA0uYuYMaDYopH5bEc/CKjzjqBdDocbPrPyxQe3Mvjbyw/63Zb/vcax3dtRSqTkTR5BsNmziEo7usUPKO+my2vv0JlbjY6P38MhlKGLKvGTRWCWh1Fd/dxdLrhtLRsp7MghfK9VkJGymguMaFWhROePJxpDzxKReU/qKp+DwA/71vZ81oRsSOmcfMPB+Y+rax8k5LSvwHg6TmG9oJQTmwqJTJ1BI1lpfhGBeE/YT+CALExv0SjSUAu9yIr+24EJIwZs5EjmYux2boZP27rRftVnDz5Z6prljNl8mEkEgW5xx6jre0Ao0d9iU536XnwRmM1VdXvUVPzAUFBS4mJ/gmFRb+jpWUHHtpRRPo/hdIZz8FPVtBaWI48XEtD1UnCA4Yy2ms2jg4xcgYB6GcorIjQIfNT0ZPdBHYnxYajZDdtByBp8nRmP/Y0NrMZN43mks/hbFit7YCAXO4JgN1uAhxIpeqvw79PrIbPH4AHN4lh4z1t6COTOZH/M4zGCkZ6P432y5+JkRMdVbD377DkXfiit4yqLkTMc5//ijiJLN4kTh53/1VMA9AGiikCD3wFoSMH/BzPfvJGDv7q5xyyzkBwSJl481COlO6gubkZJE7cDEG4mfzQBx7HarMglUrF6CyHgxEjRrBw4cL+m7Va+eqrr/D19mJigElcvZcqIOsDMVJEphJTTdx9xQoKKUshcqIYfm/sgI9uFyMDFr8OnbWw689gNYiNu3nATb8XDUqN7b2pLl5w+C2ozxEntvlrxZD/U6TeI6ZXrHoU0u6GW/9zRS7nORe1SnbAtudg+q8h8RYx0sNiEIWMynTxfI5/AXU5ED1NFBDiZsGev4v7T34GJj3TNx3hdI6vgtWPi+KJJkCMCpn7V9Fo8hQOB2z4kRh54B0t3nMOO/gniqkqe/8uXlMA3wQxSqVk+9fRF1IFaIPEybmbp/h/S4/4mSo14v3bX8RJ77UxFbXT+sEJFOHi9919ZAAt7x7HLfH/2XvL8LrKtP37t9Z2j7sntTRJ3Y22tLRFiw3uDgUGGBgchoFhcB3cXYq0pW7U3dKmcffsJNt9rfV+2KUltECZmWeeef4v53HkQ/Ze695Lb7mu8zrPOOLOH/ibRT7/WSiSDOKR8qKeLytxl1cTf04xjg8a0WZaiJ1bgDrRgOehk2n+rA5jcpDsq4bCue9Fn7H/Y/glBsXvAYrf8W9FW7WDsk1tqDUi4+bm//vVif8PovXue3AuXEjTeeexKRKdEFmtVlwuF3PmzGH06J+3//vqqZ1IYZnZ15UQKO8m8G0NqhgdkiOIZVomtpk5/7bjVBSFSKcPdaLxVzvk1spydi7+llk33Er1tmh9X3t1JftWLmXee58jHmOwev/OeVjiEwgHgzR1dOJOzODSSy8lNzeXhQsXUlZWxl133cXm+Z9Qs2Mb5/3lCV57/XUApk+fzqeffoq+uYZ+ebnEZ2SSXTyMnKEj2PDp+2z75gsGTpiCqFKRXTyUwsnT/uXrsWbNGtatW8c999xzOIC0fv16fD4fJ510dLS8traW999/H+BwxmbhwoVotVrOPvtsOjs7SU9P/83sBVmW2bFjB3V1dciyTEVFBRMmTGDGjBm0trayYMECenp6CIVCJCUlkZmZiV6vJzY2ltzcXOLjf16h/pfgsnfR29pCVvEQPv/L3XgdDq549tU+24RaPXS+sBsAdbye5NtGIKiOLKCDDS7c3zdjHp+KviAWJSITrHeiy7YhaH653lTyhin7+mE60z4hS38T1rwBJKfM6TPZ2rb2TEKOHsaesAx1zC9kz7+6FuXA1/Tm9sfUsB/d7BejSvP/JshyEHv3WjyeSgz6dOobXiEQaCMj4yJibCOIRNy46ipwV1fhzIgKsYlhA7LGj+RNJH/nXegCR7Llgl5FwmWDCaWJRKQILOvGu6UtqhlxTv+jJpuSJ0S41cs7nk+QBJkbht6AKIhI7hDtT2xHk6CA34XZ+yLG4TlQsTiaTRLV0Um0MQE6D0QnzGccmiQfXBhdrCT0j9YK661EJJmQJGMQRbreLEVyBpF6gwR01eiDBaiFRiJKOhpNK3Ha5/EnXEHIHUvXtDj+2BBlUHx+6ueHj7uip4JzF5zL3cpZhOQuXhA3kqfR8e7pX2G09BXOPLzP5vUseu7vzL7pdtZ/9A5JufloDUZqd23n2lffo7O2hs8e/jOp/Qdy3kN/R/yJVUckFGLJS09TuXUjo08/h3FzzvvZZyccCLB72SL6jR73swwtT08379x2PaBgsFjR2HrImdEIgoTJ1B+ncycxpumsfaaFzMISmspKScnvx7kPPd6H8REItNHQ+DotLR+hhM1ULkjksse/xGD+1yadiiKzceMkVEIi/fMf48DqbWz/9ktyBw0n29UfjCL7GtdgLpFJGLkFWf6hploEZIqLXiYpaRYdnYvZv38e/QruJSvrit90DNu2n4ZKZWbE8I8BiETcbNx0AjbbMIYOefOo7YPBDmpqnyEn+zqMxtxjthkM2dm6dTaRiIvk5FMZNPBRpM5ItI+xO3B+3gBy3/ltSA7gknpI0KahjjdgGpuKoBaRnEFEgxrF0YHYthajvASGXYwwYCqCJRk5rKL3m2p8+zopDWwkN6aYDVVfENaH8XvcZBcP5eRb7jzqXgWqevFubUMVZ8AyKR2VRYsclIj0BNAk//o4e0z4euClUdGSjabtoDXC9Zv7ZJCDwQ62b5+LWmNjTO6zCEkDowvuZwZFF3OKDLP+FqX1166NOn94OgAl+l3+9OhCtKsCLvg0ujD9D6PpyUtZUHMpQ0/MZNzcfHbu2sV33y1CpVIhR0ATtIHVy9lnn0VOTg4Oh4Ndu3YxadKkqI7Tj0sqqldGqf5FZ0ez7Z+eD5VLj/yY3gZT7oqKH+p/gRXj6YI3p4Mjykqk38yo3kNKyfE7ZMhSVJtg3ZOw/qnoZ+kj4NJF0Xv5b0Rr25c0Nb2D399MVtaVZGVeiVr9TyQRumuiTAtRE10Eu1shcwyc/Q7YjsP9TIocxVj4TZDC0QBJw4aom0XrLsgYjVJ8LpJPh9q1NWrFGXBEA0kBZ/R9SBsGU+9DEmJAUaLsg0OQAxHc65rxbm1H9oZRJxtJunEo4iFBTueKBtyrGtGkmhC0KlQxOjSJBvzlPWgzLRiLE1EnGJC8YTRJRgTVvxbE8B/opvvDMlAJmEalYD0hk+YXV1E79i4UVZAY9Xjil5+HKmzCNjsHsXsRjfe8QMqZA4l95PMoK+f/IH4PUPyO/xgWv7KPhv3dyJLClAsGUDT5/x/WjcdCsK6OjkcewbtpM3FXXcWnGjVms5lx48bxxRdfoNfr+eMf//iz1l+RkMQbt62jZGomE84qwLGoFs+WNtIfGkfPF5X4D9hJu38sou5fDwIpsoJzUS2eTa2Yp2QQM/vIpDBQ1UvE7keXZzus+v/Zw3+muWw/JdNncWDdKjR6A/HpmUiRMBc++swxf+PbJx+lu7UJb283wUCQyJBxZGZlceGFF/LOO+8gyzJXXHEFb867CldXBzOvvRkSU5k/fz4ajQadWgW7N3L50//oU0IiyxKbPv+YrV9/hiCKqDQarnj2NXQmE7uXLiI2NY3+Y45d3iFFIgiCcNQiBqCsrIzPP/+ca665hrS0NLZu3cqSJUsAuO6660hJOWJZ1tPTw3vvvXdYQ2LZsqjoWVxcHJdccskxHUf+WcyfP5/y8nJuueUWFixYQFNTE8XFxRQWFv7bHEh8Tgcf3Xs7rq4O4tIz6WlpYtIFlzH69L6UbNfaJlxL67GdnIfzu1piz+yH6ZCVm3dHB71fVkazk6KAYWAcwTonsi+CZWomtpN++VidqxvY57kIfXwSoybMP+Y2NXuep77nBYYmfo65fwY63Y9KpHw9sOxemPIneHUy9cOKqNFVgQJZXSoKzj6A8C/qGAA4nXsoO3gHPl/d4c9EwUCB56/YTMPRJJvQJBvp/uggsiTjPXkN7t4yshx/xL25nmBEQ7DIQF5Of9RJRpAUHAtqiDiC6AtikAMRQvUuNKkmwm1eNBnRbK3kDKFJMiD7IoTbolk826l5WCakI7lDeLe1E6xxEKztJUV7LWqxDfrPji44vN1Rez8pGFV9762P1gAPvfAXJ5JXvbeD/S1OFt08kQRzVFOi58WF+FtjMeh3EXfJMAKBgfR8VoUSjDJHBIIoaHAb7fw9/nPuu+BRCmILqHfWc/WKq5ncPJjL26P2nJLo5b34Feisa7nrgmXRTOZPIMsSH919Gz0tTUTCIU6+5U4s8Yl8+sCfmHLRFRzc+D2O9lZCfj9DZp7MkBNnUbF5PS57Fyq1mu7mRtqqKphy0ZXkS8V4t7QRf2khhkH/XCAPwN7UgFqrI+j18OmDdyGog+QNH0P/UdNIHmRh80fLqdi8mWtffY+mA/tIHzj4Z1kbTtde9uy+Bk+3i0zrs5ScOOuY2/0Smps/wuncyYABf8Hl2svuPZdQvzIdR020vKhw4lRGWWcRqOxFUIvIUoRl9W9TdNY0Bs8YjdO5i0CghdSUuTiXuJF7QyTM6Ee58090d68lIeFE4uOnkJ52HoJwdKAxEvHQ3PwBXl8NyUlz2LvvGnJzbybvR/a3dfUvU1v7DLGx41AUiZLif6DRxKIoMnv2XEZP70b0+gxKkt9GOihgGpuKJiFaxx4MdlB28C4cvdsojn0HI7kEa514t7cfZkJoc6yYRqfw/QdvYoyJZewF5+NYW4fskTAOTMA6NRPxxwmUoAdeHhNd3MRkRQN2AJY0OPd9JFsJ7U/uQAlHn+sgfpzabkz6WCrrtpA8p4jRc4/0j0pEpv2ZncjeMEpERh2jQ5Niwn+wG2TQ5dmIm5uBSmqJCk4eL3a9DwvmAUJUb+DqVVHxxJ+gpeVTyivuZdTIr4+wVD67KBp4HHJBlAUAUVr9O3OigciL5kcXf/mH6uQDzmO+g/8RLLyVwL5l6O8+AKKIJElUVlZiNBp5550o22j8+PHMnDkTOsqgeXu0/wp74ZsboroR/WZEg7ClR4KixOVHdQ2mPxhlhIW80ft9vNR4vyPKNtEYIWPkP1/zL8uw+pFo5n/kFf/aAv6opiM0Nr5BTe1TWCzF6HTJ2O0rUautpKedT0bGxej1xw4A/yy6a6LBbLU+GtQqOPG365n8CJ1dywgEWomJGYXVUvSb91cUhd4vq/Dt7MAyLRNDUQIqixaVpe8xBWoc2N85ABEZXf9YEi4pRHKHsL+9n0iXH31hPPp+MRiKE/oEMBRFwbe7M8o+1KsIt/tQ/BE06WbCHV6IHFk7a3OsxJ8/ENWP7FHlYIRwi4dwlx/9gDjUMTokdwj/ATvqBAMRewDf7k7U8XqMw5Jo/+57ujI/J2J2YKkcR0zLCbQXvoMrYyMZmRfT3Pwhek0q+s5+xLZPJ/uquTjefZ2Yi69EPE5r2/9G/B6g+B3/MXz88FZikgw4OnzozRrm3j4cRVYQVb+cLf1/DeGWFuovuBAlECD+2mtxTJzABx9/zJlnnklJSQkVFRWo1Wry8/MBWP7WARRF4aSrjnTUNbs7Wfrafk6+sYSc4gQ6X9kLQNL1QwjWOel6bR9x5w3AODTpXz5e9/oWnN/Vok40EOnyY52RjS7fhjbLSttjW5E9UeaHpJaQEhS27V1Ij9CG3+vu007x9JOYec3RJRG+PZ10fV7Gwrp/EJR9ACRPmUV1p53rrruODz74gH79+jFh2BDev3MeKo0Goy2Gy599jTfefJPOzk76GTV46qu45uV3jklXDHg8BDxu3r3jBuLSMvD09uB3OVFpNFz42LMkZuUA0Qxq5ZYNNOzbTfWOrSTl5HHug387qk273c5LL73E6aefTr9+/XjmmWfIzc2lqamJgQMHcsYZZ7B69WoqKipwu6PX4aKLLiIjIwO73Y7b7SY1NRW9Xk/A4/m30YDtdjv/+Mc/yMrKor6+nsmTJzNt2r/GGFFkmd72VtqrK2mrrqR+z048vT0MnjKd/WtXMP6cCxl12llHXaOut0qRXCGSbx1O1z/2IrlCpNwxEiUs0f7UDtRJRuLOG0Dv/CoinX60uVYkZ5Bwu4+U20YguUJo0814t7UTcQSwTs8+nImof/0Lagr+zMABf/3ZundX93627z0dFBEEhaSkOQwa+ChqtYXwhndp2fk1aXI7brGGPcUxxEgT0KnDdChbSTdORIzvT1rq2ZjNR1v7Htd1UyQ2bZyGHAmTa7wdbU0eYWsbkQMSKmcsSH3HV1PKImLG5iGMjZYifLHmQ16seYVvLlpInP4I5VVyh3CtaCDY4EJQg15fgdX5CK6ExwmFckGQUWn8hF1aBI2APtGFv0ZG0Vixzcyh57MKlIiMqJUwS59iHa0BW1Y0Q2j9+YlpbzhCiz9IS5ObJIuOHm+IjFgjA1IsrKvs4pK3twFwwoBE3r50FKIoILud+Bd9i3H2LISYaF8kecN41tahSTahy1Dwzl+EuzmeDpWGL07cgiTIrGxcyYBAGk/U3ILe1o35jBl4t7QRqOjlzcT5nJXTQ/FZ7x85OHdH1Nawdi0dE/7OR8+/iUaj4bqTY1FbE/lglYOupiYA5sy7g+aD+9m3MpolFUQRS3wiUjhEJBxizvgbMTqNRLr8oBbRpESzZ/+OkjlXVyfbvv2Sqm2b8Dkd5AwdQf2enYw4+QxOuOSq42qjsek9qqr+QvfWWZx792+jfdfUPkd9fbQ+2WIuJhKS8LjLkeuvISGzgKyiIZidFno+Kcd2ci6G4kQ6X96D3+ticdPrnHr27cTFpGMsTqSnrJ7Qoi5kRUIQROKuG0Bb5D3a2r4hFO4gJ+sG8guOLkPZf+CPh3U1FEVCUSLkVD+Eob0AbY4N64lZiEkKmzZHdXUkyY3J2I/Bg5+ltfWzqI5H4oW0dX8FYQVD90BkjZ9E20y8xnK6AysASKq4hNiGQ32fCOaxaUfGsFk5dDXX8eHdtzLz2pspnjbzly/c0rthyz/gyhVRLYDatdHA3YZno4J3Q87HE3MzwVYZ85gU7O+XgaygsuqI2P1USLuY/Oh1lK5cStXmzUwcdi7KNi/aU5PQxZjxfNkIioJpdAqyVsH/fTvIQazCe5iumIeYd2xL0aPw/hnQWwfnvBet6U8fQdOBfSTm5KE3HRljwmEX6zeMITX1TFSinqSk2cT0+qJlClcuj2aXf0BPXTQQ8d9EEd/1ASy4CW7cFg0e9dZBcTQA9Oabb9La2sqtt96KVSPBKxOi9yguP1oKEHRFyxUat0RFJweeDCfcAwe+gp3vRkUkT3vp/5yg4PHA4dhB6f6bCIW6SEo6mcGFTyOKGpyuvTQ2vkln51IEQSQpaTaioMViGUxm5qX/seOT5QgVlQ/Q2vrZ4c9SU89hQP8HouVLxwnXmiZcy+rRpJkIt0YD9IJeRdKNQ9EkRtsJd3jpfHkvqhgdhsHxuNc0YSiKJ9jgQgnLJFxSiC4v5rh+TwnLyP4wKqsO2R8hWOck0hsAGVwr6hE0IrFz+6FOMuJYVEuwqvdwsFQ0qdHm2Agc7OnL6koP0ZL6CmpPHJ6k3WCMoDek4vFWYGUULnaSmXkp/fvdR2/vFqqqH8PjrsLYWciIaR+gSfr3Mm7+N/C7SObv+I9AlhVcXX5yiuJJyraydUEt3z67G2eXn9P/OIyY/wdepuOBIss0zZuH7PeT/cH7kJ3Nos8+Q6fV0bFLRBok97ESbSzrpmp7BwBDpjnpbvFgb/JQtqkVW6KBtH4xKJJMqMWDeWx0caHNtiJatPj22f8tAYpAeTeaVBNJNwyh643SqIXjSog7fyCyJ0xHXCv1FbtJ1meTEsxlYvJcsKlYUPEyI04/nS1ff0YkGCQx+2g6bqQnQO/X1ahkFTHaRDoCDRisNoSORjRaG+vWrcPr9ZKQkEDNjq0gCMy8Zh5LXn6G/WuWc/bZZ9PW1sqG5x8nf9TYn11E6M1m9GYzY+aey5b5n5E7bCQl009i2avPs/jFp7jwsWcRVSILn3uc2p3b0FuspBT0p7F0D+Ub1jJo0tQ+7cXFxaFWq+ns7MTv9yPLMrNmzWLHjh1s376dzs7Ow1ap8fHxTJ8+ncRDVk8JCQkkJCQgyxLrPnqH7QvmM+LkMyiedhJBn5eknDzUP8Oc+TUkJCRw4oknsnz5cgRBiIp1/Ub8uEyit62Frx5/CEd7VBBUo9OTnFfAtCuuI3foCKZdfu0xGSZKRCZU78I0KgVBELCelIP9zVI8W9uI2P3I/ggxp+WjjtGTeOWRDGGwwUXXK3uj2ciQRPxlg3EsqkEJyQTrnOgLYtHmWOnRrEJAQ1LSnKNPoGkbdOzHkn8iltBI6BHQBJPoVJYgBLTkxd9Jadt8PMVltLiSCJri0LpTSdx2EYKsJTCsjZaEDeDdQEvTexQOeork1GPXLf8SurpWEQg1k7b3RuhIImIOovitaC1aEv9YjGjREO7wEWl14d30FmdZvmPMTh+PqXUI/WawRtpEbKyVuLpN0Uxa/TrwdKKSwsRqZSiJjSrDdzdDbC62+kui5Rj+nigVW2eLsiA6AqgiM+mN3Ez3pxVoElTEC39D3bseckbByUt+lQIalGXm7q6m3BuAkIymwoHY7kcriDx0WiFvra8jLdnEWcMzeHFJBeur7Uzpn4hosWE6/5I+balMGmwn9z/8v/XG69AsnI+yMR5HaSv1xjqebD2VAd4TEMUwsVedhDoxFv3AODo/3M/lB+ayhEcp7iiL1g7XrI6KnQXdYIgjefX1nDhmNkrTNjS1Dgj7OD1nJE1zbkOl0TCwXzKDRg5nyIw5tJQfoGDUuMOCk969nfR+UoEqT4t5YjoI4Piqms6X9yC7Qwg6NbInhHl8GtYTs/ucl6IohFs8eKu7qdO14M2UmZg+sU+fZE1M4sSrbmDaFdey+u1X2btiCVnFQ5l0wWXH/VzFx02kCvAF99BWVUHZ+tX0trVy+u33otH/vIuGx1NFXd2L9FZZcdZbyJlejqAK46pP5/TL5x3et/ujg6hsOswT0hFEgbjzBmB/o5RhiScibPLjEupxLalHUWTcUi/eURESdsZS/8FWBtx4M4bPJ9OW8Rr1/IOI7EGRw9jtq0lInIFK1NHRsYDc3FtJTDiR7TvORFC0aBoy0A+Nx3/ATucL3egHxzPm9CVEGoPYm9ZTx1/ZsjUaREjSno7poxPJLxhJh/5zQuktEBZoFF8En4q4+lOwto/BmlSE7cZcBK2IOs5wVNlY1bZNCKJI/sgxv3zBK5ZEXRJGXkF1fAlb23rIiRtJlb6YshmTiLTu5uL9zzEs9WHM538EQOqdoxA0KgSNSN3f15DV1Z+1f36RVCWX8do5KNu89EgdrHghqv0xevbZpA8qZNPyt2jcv5eMjEGM1gzAyVW43ujFmDkfU6EGzaRT+pTJ9YHXHi1VmHALpA0FwN1t5/NH7mXYSacc1mAB0GisJCRMo7X10+h2njJGDP8E/twY1VT4MeKOXUbzv4ofykrKF0HZgqiOgzkJMsdwRqEBh6YL6yenRhkQng448aHofcwYBSMvh6yxR7c57sbo3/9jkOUIHR0LiYufREXlQ4iChpLiV0lImH6Y4WSzDqG46EX8/maamt+ltfULFCVMR+d3pKWd85uCA/8sFEWhsuphWls/Izv7ejIzLqap+QMaGl5Fo7bSr989x92Wb1cHunwbCVcV4y+1o4RknItr6X6/jMTrhiAa1TgW1CCoBRKvKjocWPBuaUOdZCD+qkG/STNL0IioNFGGhGhQYyg8wrjTD4il5+ODdH94MLqtVoVlaibabCsqo4be+ZWE6pwYxyfQmvo6VnkEJv1AKj0PEwi2osRKiOgZMfIzTMYCKqsepqd7A8m2U8jNibLOYmPHMnrUAsr23UN75Ft8ZR3Ykv4L39t/I35nUPyOfxtcdj8f3LeZqRcNJGNgLB/ctxlBFNDoVKjUAqYYHYPGp1EyNeMX2/lvdak4XriWLKHlj7eR9uQTaKZP57XXXsPlcpFtG4K33MroU3MZdXK0YwkFIsx/YieRkETILyFFZMJBCY1eRcaAWKZdMgi9SUOo2U3nS3uIO38gxiGJUL0Sx9J2PG3ZGIoSMY9PQ5dt/ZUjOzaUiEzrw5sxjU4h5tR8FFkh0uWj47ldiAY1sj/CorbXyBmUztSb7qd01XLiwilot0uYT8pEpdawf/1KNu39gj88/HcyBg7GX9aNc1k9hqIEfLs7kZxBkBS2dy2hWapmyIzZ7PzuGzLOuJADZWUADMlMxb57K6aYWM5/5Ck+e+jPODrauPKFN+isq+XTB/7EnHl3MGjiCb98PoqCFImgPqQbUbtrO1///WGGzTqVcDDI/jXLmXrp1QybdSoAH917O86ONpJy8xl1+tnklBzJLL322muIokg4HEatVnPNNdfg9XpZvnw5nZ2dFBcXM27cuMPPa2d9LV0NdfQbM55Vb71C7a7tBDxuUvL70V5TdbhdtU7HKbfcRf6In9cf+bVzXLRoEVqt9ph6GL+EgMfDh3ffQsDjwRQbh8/pQBAEJp5/CWn9BhKXkXlMDZGfIljroOv1UuIvLsQwODpYd71ZSrDOCZKCeXwaMaflH3PfrjdLiXT5USISSkhGCcuYJ2fg29WB7AmjCBFqpvyR2MSxDBlxSPei40A0q9lTF7VjU+Qo3fS6DQR9yfj3dlHveInu9AWoglYkrZukniK6YirQ+BLx9FxI8cyTMO+WcW+qJ6J1IsgaWoY/gWJ0MGHGnj509ePph7avOxefu57h0uNo89PRhnZDbAHYDyDs+wQsqUQ0RuTatbyg9vCeLfqOnuXykCJFeD0mhrkeL/fbu480qrUcCSb4e6L1zbMej064N78UPX9LSlRMrO570JhgwGzk1U/TVnsrqHUkm+5CLXbAjIdh8JmHa5ud4QitwTDpei1Wdd97/NeaVl5q7CTbHqZLL+AzR/MXqoiC0htE1KuQLBrUgoCm1s1ci5mnzxn6q8/J4espyTQ9tJBIRINW0QFqTMV6rKcORWX9MTVWouKxlbQL7UyKfwl1/5mw+WVIGgTnvBut9f76OmjYFFVnv2h+1Kng2xujGhq99dFaZWMCzP774awrgByS6Hh6J6JRTdK8YQiigBKR6XxpD4qsIKTpqO+sJTZsxdijJuWOkahjo4v6UKsHx7c1hBpch9tbY92OpSiZ00++4Jg1yIqi0LB3F2kDC9Hqj5+GqygKGzZMoKdeon5ZOpFwCID8kWOYfePt7F+zgt72ViadfylagwFvbw8IAvv2zMMT2oo1eB8hD2z/9gvM8bHMufFOMgeXHG677dGt6AtiiDvviEhq1+v7CNY6UUSFg4YdKN0R4g1ppM4dQvroYkqf+hZbVwyoQNSoURcYaFZewpkRFdeMjRlHr2MbihIixjqWAt+jmIek0ulfSteSbcgHS9ji+o7cwuEMz5lJcGsP2jQzoTYPRBSEPBlnv5WYtP1RL8tH0KuQXSHUyUaSbxmOgkLX3u9RYyOmXxGRngDadPPPLubdPXbe/9M8kvMKOPveR/p+GQmibHiBbq+DGkWPvXkfCQYzz5XczRqHr8+mBiGMKGrxSgp31L/NHSdfH33ufhTwc5e143w/2r/LcQL6AXHsXLsAh9ZO8ayTaKk4yP41ywEwx8UzcMIUGndvprO5jX4JGeRp+2PTDkEQtAiiH1nnI+EPxRgG/qj/VBT47vZo33fdRkiJsi33LFtM21d7sAutXPDSc31ccnp6NrJ339VYrUNwOLYxftz3GAx951//1fOtN6ZHS9A87dFSDZ0lWhoRdEYdJ1KKomUoIy7/t2oK/bcjEnFTWfVX4mInEBc3gcrKv9DRuQi1OoZIxEFh4dOkppzxi20oioLDsZVduy+kqOhFko+VCDgEWQ4hir+cUPlhLfnDs6QoCt3da/F4K8lIv4DKykfo7d1MINhKdta1FBTceXjfsoN/pr39WzIzLsbp2svQIW+hVv8841Tyhml7ZAvWk3KwTj1S7vtDOYc6Tod+QBye9S3EnJ6PeVxU90uJyPgPdKMfFHdYa+LfBSUsE6jsJdIbwFAYjzqubyBZkRVq656hvuEfAAiCCpXKzJCS1zEac5CVCHpdyrGa7oPOrmWUlt5AXuNfyb3stzsq/bfh9xKP3/EfQWNZNwtf2MsZtw0jvX8spWubiUkyojdr2Di/moAnTHeLh1nXFJE//NhZ/507d7J+/XrmzZt32Cbq34W6vV14eoMMmpiC+keDuCwrLHt9P9lF8RRO/G0Chj+FIknUnnY6CJD37bds3b6dpUuXcsEFF7L25VakiIwgCJz5p+HoTRqWvFZKd7OH2deX0NvmZfPXNYw/q4BhM7L6tOvZ0orjmxpS7hwV7fhemUC4zU13+G4kIRl1soWkm0f+UxONHzLa8RcNwlB0pN7U/u4BAuU9hM0+vip9kfNz9pA2aGhU8TuhgM7X9hFu86AEJNAJrAt/zTkPPAqu6IQfUUAJRFDF64k7qz9db+yjrHcTznQXky64jI/uvY2UkeOp8gQBMNWUYjWZmHzh5QyaNJXmsv189vCfmXTBZfS0NlO5ZSPXvfoeWsNvj/SvfPNl9q6I6keMPuMcJp1/hNLY1VjP+o/eobulCa+jl1k3/JGU/P7sWbaQSGI6G7ZGae2/Jmga8vt49/YbcXd3obdYCXo8FE6eRt6IUfQfM4Gq7ZsJeNzoTWa2fPUZva0t9BszHre9i7j0TNzdXcSmpjH69HMw2mJ+8zkeL5a9+jwHvl9F8bSZ+F0upEiYyRdeQXxG5q/v/CPULnuLNu9npBTNwheqJ8Y2giRlLl2v7sM0MpmYMwqISG5a2z7HbBqA2TKI3p6NtLR8QkbaxSQlz8GzsRXnd7XI/d1o54QxGLLQ+pNpXryQxpwnKCl+jcS4KfDV1VHF+h9Qcl7U5uudWXDS32DcDQCEvV52b74UUVHI2r+Z0uHXkGeYzl/LXmCbUI5G1HDewPO4KuVSdO0Kgl5F4/ev0VL4DkMLXyE+ZSaOjS9R3fMhPr2L0eOWoDdnoygy4XAPWu2R98PtOsi2HaeQXDWTwa2fIAg/GUsTB+KPBLjOFKFcrSIsiszOOxmdoOaL6q8AOEHW8lDsKOKHXQrutmgQwvqjPigSBJWWhkCIL9t7uSw9gXjtzxAfS7/E//krUR0zYzNcuhAS+xOQZLY6vfSGI9xT1UxPWEIjCFyYFs+0OAuyAgu6HHzV0cvcBBtLPy5j3vQCsooSaQmEOej2saXbTY5Fz8Q4K9W+AN90OjA0ejl4wVj0muPvp31bq3Gva0bXLxXTxKzDmgKOcIS2YJgErZpErYZti1eRtk5LT+xLlPiXwpDzeSY9D209nNoyEYPBhO2kTHQ5UeFVJSwjfnFWNGBjy4KRl0Wzqa27o771qSVRT/mPDhIo6ybx2hJ0Obao6N3Od6IUcEsqf9/+dz6sX0xCOJZ3av+CpSSFuD8MQOoO0PnKXiQk3rZ+wR7zXh5yn4G1sxiNrKGj0M+IS365hEDyhgk1uNAPikMQhF9dGJYd/DOdHUs58NEg+o0cS0J2DmveeQOVWo0UiQBgsNpQ6b1Y81owJfsxJvnxNRVw6qVLUBSFml3byC4a0qfPDNv9dDy1g5i5BZjHHCn3+SHgaJmehW1G9lHHE+zx0vrUFjrdDeztXYtPdnN2yZ9QzB4SrhyMwZCOJEUX964lbXg3tIJaxDQqGe/mNrbbl6ItiaF622ZEtZrTTrsd1bYQKqsWy7RMnEvqUYJRK2rRqCbp5mGEW72oEwy/mcosRSJ89bcHaa0q5+LHnycu7UeL8pCX2q/+yAXW06j/yWLdrBK5OTuZhEgVL+z/FKenAo3UiVZtIzvvUTb6LVzRvghTyMlF8TrSAu2E3J2YxlxF895UtPFmEmcMRBAEZFk6HOhVFIWD69cgqFT0H5CBatc7KG2l7NlVzQH9NJyd7cgBhTRTPgnaNNJNA0B0kn95DELV4qhYZSQY1YcYdxOc9CiyPwICbP3bB2QGC3CGujBcmEHeT4LeshwmGGxn0+YTyM+7nZycGw5/19r6OdU1T1JY+CQxthGEwy4Mhn9dN+yni9V/GptehOX3RYMT530Cqx6OMkcGnwl5U49tkfr/CGQ5zMHyP6NSmcjNvRmtJv7w9ayoeIjmlg/6bJ+efiEdHQvQ6VIZM3rRcTntKIrE+g3jiI0dQ3HRi4c/lyQfbW1fEZG8OBzbDjvuWCxHa538oHfR1Pw+kuTDZMrHainB6dqF2x3VcVGpjEiSn6SkOVitJWRlXtEnGRAItLF5y3RkOToX7N/vfjIzL/vZ4/aXdUeZEteUoMvrq+UTrHVgf68MJSihzbWReFXxvyxg+e+A21PO9u2nk5x0CnpDBuFQN3l5t/aZUxwPwmEX69aNIL7uZEouegpRrybSG0DqDRx3ucp/E34PUPyO/whK1zaz7tNKLvv7BEw/Eov5AZGwxDfP7Ka7xcOZd4wgMevoescFCxawa9curr/+epKTk/t85y8tRdDp0Pfvf9R+x4OPH9pCR08L7oQyTj/9NHoqKwm63QwcdRrfvbwPURSYe8dwUvJs0UCCKCCKR6LBLrsfReEXS1Vcy5bTcsstpD/7DNbZs3n11VcRBIGZ485i8T/2Me2SQWz5toaAJ3y4/ZlXDSanOCHqVd8bxBJ3NIW3+6ODBOucpN47BsHRAM8PiapOi2o8q/biCF1H4jXF/1QH9YPQYep9Y/qIBP0wCNR6V1Pn3sAll81A2PxS1Jd6wCz80mi69w4hYnGihCTSrpyK1BvE8W01iAJJ84ZBWEZl0yJoVLT9fRt1rXsRJpkZd/b5bP36c9Z/+gGh4jGEImEyelu58rnX+0xqvn7iLzSW7gVFoXDKNGZcfdNvPj+IqvGv//Q98keMIbt46DG38XvcfPnIfXTW1xz+rHjaTNInTmffvn2cccYZaDUapHDoqCCJoiiseusf7F25lOGzTqV80zqmXnYNA8cf25fc09vDJ/ffQcDjITY1nd62ZsxxCfS2taDVG5hz8x3kDRt1zH1/C0J+H21VlQT9XsKBAE1lpRxYu5JRp5/N5F+hnAeDHfh89cTGjqGrazmBYAcaTQzhsIP42Cls23A6iiqMLPpRq61EIi6ys68jN+UWRKMGl2svpftvJBhs79OuSmVCkvxYLIMJBTuJ7zqFjphPkRRvn+006lgmTtiI+O082PdZ9HkfeQUYE3CEPeyz7yP+m3kMjh8M53/c9+C/f5KF25/hnsQEVIIKAYEXp7/IioYVfFP9DUMSh/DUlKd4cfeLnNtWgt38CHHafIpGvsSGDaegiDKyKkRsJJ0hJ33H/v23YO9ezcABfyUt7VwAStffQldgOf12DGDDqH44Aj1oYrOZqY4jy5xOR/ZYHtj8EJtbNzMtaxoNrgZenv4yaeY0XCEXPf4esq3ZvziJlxSF5xs6eK6+g5CiMC7GxOdDCtD8SP3fE5FoCYYZoBPg2cFRxfMrlkLSIMKywoX7aljX6wFggEnPvKwktjq9fNzWfVgiQyMI3JSVRFJHkIe/PcCyWyczIOXY9eiKonDp9mqWe73EygJDY4y8MzQfnSiwottFhSfA7CQbBcafL0X4MRZ3Obj2QAPhQ3ORcTEmXuiXTOsTK4jBQuaJehpaRL5rXsLcnml0aXpJ16aiVmswDk/CvaYJFLCPijD05BHIogn32ia08aBfPRNFbcMdOZeAvz9hXxy2k3Ow9HdDbx3+5fexNNTBiV4fPSoVZ2SkcqrHi0FWUAfP5/zuORhKEqLMgqCPv6U8zB5DF5/YvWTKCpLfzVfaeYxzz0AZYMSgMWAenYquX0yf+xpq8dDx/j4Ep4SuKI7lkXUE29wkh+MIqsOkDMlj7IwT+2T1OjuXUrr/RvLz7sTh3I7XW02K9Y9UbyklPjeGmMRMDm5ciaHfCgRBQghl4O6UGDXxBdLyh/7s9fZub6d3fhXJc31oYoVoTT4KDL+EkGkimlTzL07o7U0N2Jsa2PDp+6SpcinRTcY8MR3JFcQ6PQvRrKX98W3oCmIACBzsQUFmo2op8X/8M36ng7Y3n8dbX83ZFz1A6qhCNElGFEVBCUnI3giiUd1XwPI4EA4E+OrvDxEJhdCbzNTv3cXMq6+nOEsN+7+iqWYze9Kn0iqpeDN+Bl5jArfmZ5Nv1BOvUdMQCJKn8fNh6fMsrltMQUwB9465l0RjIvdsuIe9XQdISf8L+1VZiIqMRokgKjIhUcNYx15eyNCSPupCKP8O9n4SLVFo2hZ1zEGAEZeCIBLe/hb7DDmo5Aj9Mgsx/eFdpEiYis0bsDfWI6pUyAc6yQuPQZZrUIQYgmIHiUlriS0ZhC/nBuo/2UMopMciKXRo4O7hei6sizCqrQFbXioZZ49EG9eXvr5j5x8IBloZNepbwuEeGhvforXtc0RRiyjqUYkGIpKHcWNXIMtBVCozWm0cshymqekd9Po0kpNP+dX74PPVsX//LWi0cQwpeRNR/BcqyR2N8FzxEXHf/4chy2Gqqh/F5SpFo7EhCBrs9pUIggpFkQARgz4DozGH7p71ZKRfRGzsOALBVszmgcTFjiMY7EIQRLTa4xf8La+4n7a2rxlS8hrdPetxOLbj9zccsrkFtToGWQ6QnHwKhYP+ftT+DY1vUl39N+LiJmE05uF278fl2ofFMpjUlDPRaOOorX2G3Jx5pKT8fBllV9dKZCVEU9O7BIOdjB+36phBFjkQwb22Cfe6FtIfHodwjAC5HJJAVhB0qv8KdpCiKOzafQFebxXjxq5Ao4n9Tft7ghG8wQjJ1uiYum3DXMJdHoYXfoa+fyz2t/YTanKT+ufRiIb/W8oNvwcofsd/BOs/q+Tgpjaufm7yz3YKXmeQLx+P3p9z7xmF4SeKux9++CHV1dWcccYZDB069PDnSihE1dRpaDMzyfn0k998bD+Un3hsVfgNbX2+G2gci73Lg0FjQ/bryBuSQPXuLjQ6FZkDY1FrRBoO9OB1BEGAwglpTDirAO0xOoL6Cy4k0tlJ/rKlNLe28tZbbzFnzhxcZWbq9tq54smJhPwRNnwRpYOOm5uPOfbnJ/JKWCLY6Mb+RinmSenEDHNC4xa8i+5HuHoVxuwhKCv+RtuqYjTZ8SRcNxapN4jKojlmxw2gSAr+0i4kZxDjiGS6PzyI7IuQcltfLQNFVuhauoNP3v8b4ydkM2res+Buj3pmN25B6W2ka9RzHDQ8AQEzAzteI1zpwVO8Bd1wK7mDru3TXtfr+wj7gyRdPwS1Vosiy3z28N00eQMEBRWThhQx5aK+9nXuHjvv3nYDIb+Pix5/nuTcY5cM/LsQCYep2bEVe2MdzeUHcNu7uOrFtw5dD5kvHrkXR2c7lzzxInqTmbL1a6jYtI6gz0tLeRnDZ5/G1MuuOa7fCoeCiKKI6kdOEj2tzSx6/gm66mvRGoxkDi5m6qXXYEtK/oWWjiDk99FaVYGAwP61K6jatgkpHD78vUanp3DyNKZccmUfi8OfQlFkduw8G5drLwnx07B3r+7zvaBoUIQwJfHvElNYglptpqLiQVpaPyEj41IS4qew/8CtqNU2Bhc+RTDUSSjYhdGYh802nANltxEItIAi4/FWoNOlUFz0IqFwL35/I5Lkw2YdRlz1AapW3E3a+NtoHXoO7+x/h3MGnMN9G+6j0d0IwMd2D8UT7oT1Tx+xyNs/n0tz8mk3xZFhyWByxmQuHRxlzSyoWcC9G+4lRheDI+jAFjHzvDgER9YqUkNDadPtItl1K357Fa687xBlDbIYxiDn4hfryM25mfTk89m4aTIxbUU8pOmmLmQ/fG0MagPDk4ezs30nkiJx75h7Oav/Wb967xRF4YWGTvyyTKJWzUFPgG1OL5W+AGckxTDSZuK+qhYmxZo5KzmWWl8Qi1rFe612WgJhHi5I4xpdN0FRx/t+C2+1dBGUFdqCYR7KT2OASc+YGDPGQ5T47lCEBn+0Tysw6rGqVZz76mbsniCrbp/yixM7f1hi+JfbcYoKcpKBKTFmXBGJ3R7/4W1uyUxisNVISyDEnEQbpW4/g8x68g8FLjb2ullmd/FOi51kRSDPJaOJ0bGBEANMeua61zN5ZRo2yUJYiKBR1BCn4dLkuzkjdg5zN48FBfYn1OHzexnhLST+1AK829sJt0cz+SqLDN5eJDkWrboSI2swmzZEKeLAA8kpfG3UkqQ2EZAjRFD4ruhmlOYdzLKv5dGu8ynqmYRK08h7ca/zUVwPz/a/hBNH3Ry13OuuomnxXZTVn0pqKBmVoMIWMaNONqJJNiIHJLQZZtzrW+gVnKw2b2Vuz3REBHy6IH5zGLwS8QEbikbA2D8OfWE8huIEBI3AvtLrsNtXRd9dTRzhcM9P7oSAwZDNsKHvH1/mW5bpeWsNgdogqdrzoxqBxgRQ66Iig+d/BgN+5BoiRWD7G9BVHnWaGHHF4ax1S8VBPn/wbs4omIcmoo26kooC6lg9kS4/hoszsean4lrbyMolC3nupGHUGaITc6sIJ+1YRVHVXrKKh+JzOTl53p8OCwnLskTTgVIyBg3u0z/+FErADYqCq6OFla8/T11dCyajDp8nwLQpAyjwr2CDNpMvU+fwXfwRJ6c4UWa4tIDhViuCILC6cTVhOUyLpwW1qOaa4mu4qvgqNIfKOIJSkKuXX02Dq5EvTluEXxH4R00TKpUGk1bPOw1NDPTU8rh7Je8KuSxKOoEzO1aQFeyiKuMEYiQ3k6s+YYttCO9lnkOPGGUOmUSBM1PiuCgtnmKzAVEQaA6E+LiuhaL3t1AQttITbMNqzEatSHQNMPKaQc+aJA1hlYAhFEYng0OvwRKR+XKdh9iQTIQI4mgT2XPHHrYydTh3snv3RWg0cQSDHYiilrS088jMuJgdO89Fo4nD72/EZhuKy7UXQdCQnHwKLtcePJ5yAGJsoxBVemJjxpCWdu5RC+FAoI2t2+agKBKS5CU19WyslmISEqah16ehKAqhUCe1dS8gSV6yMq/AYin+5UXk7g8hYzQk/nOJqf8LUBSZsoN/or39G2JjxuIPtBAINJGTcyPJSadgt69Gkrz4/PX4vDUIoprhwz5Crf7XRU3dnnJ27bqQSMQBCMTEjEanSyYj4yIs5kIEQUVF5cO0t3/DxAmb0GiijIWm5vdRFIna2ueIiRnJ0CFv/cvHAkcCs+npF6FWW3C59lBc9A80GmtUGHN5PaJJgypWT/KNQ4+rzZ8yemQ5RHPLRzidu9Dr0xBFPSZjHrGx49HpEn/T8UqSH1HUH/MZ9vtbqKt7HlkO0tG5iAEDHiEj/YLf1P7i0jYe+HY/3d4QMwYlMzQrhvEJ39Dd8SpDQvPRxyVh/24nulkaUsf/tnLf/wb8HqD4Hf8RLHxxLz5XkD/c+8t19V2Nbr54fAfFJ6Qz6dwjg46j08eHn72NvdvOmDFjSE5Oxmg0MnDgQFxLl9Fy662gVjNg+7Y+tjpKKETHk09hO+1UDMXHtuv6gd0RyNtD2AmEjRh84IrpRBZEFFUETUQixzYBR42WvGEJtHjK6XF2YvblkJBlJjZDh7vXR0NpN3GyiSnj1eScd6RD8JeWsv/Sy9l/7rlICXG0trai0Wg466RLWPFGBUWT05ly/vG7BfjLe+h+9wCIAqpYHcnjd2Nf+BDru/Ko99jQ6Ayccutd5A0qwP33P+MMXIRxeBK+vV1oMywkXl2MoD6aAtn1VinBKkf0HwFQQB4UYlvpuwhaI1mjptLTWEN3cz2pKTHs2naQq++/HWtRVESyu3s97W1fEahdiNugICgyEbVI0sELsQZGUzP8DgDGj1vTx8qq58tKAhW9pN17RLCsqayUzx++G+CwfsVPUb19C62VB5l84eXHfe3+Hdi9dCGr33mNK194k5jkFHYvW8Tqt6N6CIWTpzFg3CS+eeIRTDExCCoVo08/hyEnzkL4F2mn4WCA3UsX4erqpGxdNDAw64Zb6T92Il5HL7IsYYk7QguMhMM0H9hH9Y6tlG/8nqAvykTQ6A0UTT2RvOGjMVptaPUGTLGxaHS/ntlua/uasoN3YDYNwOOtIDnpFAoK7sKxqRLX9mrail7D5C5hxDlvIohAwIGitVJV8xhNze8CoNOlMGL457+4cJIkP01N75GUdBJG408EnzrL+frDmTwYbyPLko0/4qfT3xk9N1HDw+Mf5t4N93Bjr4NrHe6oMrs1DQ4upDp9CHPVXdw+4nYuK7qsT7OKonDT6pvY2LKRJ6c8yYdlH3LuvmGYi98noneic2fwF68a2RvmcWUoosaHoWcg5u7htA96H1f6elBUgIyucjDXG2t5dOKjzMmdg91v57Gtj1Hvqmd0ymguG3wZGZZf1tz5AR+3dnNbRdMPryRxGhWFJgPnp8ZxVkrU4ePt5i6erGunNyIhAjKQZ9CRZ9SxstvFSQlWGv0hDnoDjIsxEadRc0KchYvTfp1GWt7uYtZz67l79kCunfLrgcCIJLO1roc/rD5ApJ8NbVBCqHUzVKdnh05CSj9agCxepWLNmIF82t7DY7Vt6ESBdEmkZXUTiXotdk+QuFwrHf0tXJgWzwzXPlq3VbEhdR83DL+RIalDeXLvU3xS/gmfJr3G/qZ9/EXzIpMTJ3Ll5lkkRmIRzGq2jKihUD+ApBYTsi+C9cRsdDkWOPhtVHAvZyJLxRB/2v8PTss/jXpXA/H6OG4ceiP9Y/sjCAKPfHs+X/SUclWvmcWxAdpFhRuH3cyQrD9gUasoMOqjTBZfDwfenMJWqZc3bXGcFzqJc0Pno/gjIAhIPQHa4xzcFv84Y/LHsqN6OyPSRvDk5HsRalbStvdj7nULTHONZpx/FLqQAdGgEDN3EJpBOkr330hi4gySk06mvf0b1GorOn0qwUAbDsd28vJuRa//5dJEpX4zwWVf4WtLwRcYgWw5SPlphbRGVLSbM0nR6Th56WUkOiqjYoPudmjdjdxTzxvawdRZ8pjdsYopRSfApNvBXglBF6vXlNGwdicDh06iumE7I9JOIsaQRIenntV730elVpOc359v9LF8P242L5Q/RlqwkydyrmCbrYRTV31BUW0piiITn5LEaTfchLXyE97d1MBzQy7lgvJl3NHfgUoORcVSbRnQ2wCtu3C11PFi1zBqTVn49EbKC0qwJ6SQHOrm9JYV2EQ/r2RfRK/KiEmEmbYAF2XmMdgaxxNbHuS7ukUICCgojE8bj0VjoX9cf2ZmzyTLmnXUNdzbtZeLFl9EQUzUIveBcQ8wOWMyvoiPXd0hrq2LOjlpkZkQa2VtrxsFgXiNGndEInRorj0nwcYZybGoBVhmd7Ggsxe/rKARBCxqEVdEIqJAjgpOltws18dSFYgwrDtMo0mFTyUzR6dQnJrIhtYODkgi9w3O49byZkZYDMx2OSle2UKWFI/b6GLQAycfPofOzmWUV9xPauqZZGddg1Yb7VciETeiaKCm9kkaG9/EZOqHQZ9Jr2MrBkMmOTk34fPW0Nm5GACPtwKTqT+jRn6DSnUk0H3w4N20tX/D2DGLaWx6l5aWD4Eoa85s6o/LXYqiRBAELaKoRZI8qNU2tNpEEhKmUpB/139FxvtfhSxH6OlZT0zMaNRqE7IcxOUqxWIpRqXS0du7jbb2ryjIvwOtNoHOzmWU7r+BvNxbyc2dh6LI+P0NGAw5//L1kGWJ2l07qN+zk9xhI8kbNpJIONRnHhCJeLHbV2I2Dzymo5XbXca27adis40kNeUMdLpk9u67GgBB0DB2zJKjx+9fQSQcRpGko0R/FUWivOLHLh8K2dnXk6a6BPub+1BpTCj+COaJ6cSckvervxMMdrJj59koikxCwlQS4qdRVf04Pl81Ol0q4XDP4dISAIMhB1kOYjb3JyP9IkymArzemsM6HKGQHattKMFAO80tH2C3r8ZgyCY5+WQS4qehUhlwew7idO6io2MhshxCUSTM5gGMGvnVcZXe/IADrU5OeWUj2bkxlKTZ2LSzDbs7yEXDXUxNuI+MmlsxNQ+lefRTBMz1TBi/Ho3mn9Oi+9/C7wGK3/EfwQf3byYpy8JJV/+6p/GaDw5SvrWdi/4yDkucHkVWeO+eTTTq1yATITExkZ6eHtRqNfPmzaPn5lvwbt0KkkTWu+9gGntEodn53XcceOSvxOi05L3yCqhU6Af07WQXvrgXe2c3Dap1lOwpRRfIIxiTTmemmXZTM7kuH91EcFssFFmt+BITqamtRSUISMd4R9RhHbpAKgkGOH3eXGITrXz3x1fYbXEiixG0shUdFnSeVMSQntg0E2fdOQLNT4V5IiHY/mbUj9vWdyHnWFSLZ0srxiFJmMckU/vGbBZXxqJTRRg6NI/aHi2d9bXkDRvJ5P6gbDcTkEejjtcT6Q5gGptK7BkFfdqU/RFaH96MeUIaxqFJeHe0oxsUx6dPXk7AH8SkDmEPmlAJUa93SRFJN3k4781VIKoIh51s3DQZUdRiiugxtNWS3SZzICcNrymM0ZiHT65EUSJkZl5Ov4K7D/+2a1UjrhUNpD8yvg+744tH7qG7uYlrXnn3uMQZ/1Pobm7i3duvZ8Y1N5FdPIz37riR9IGFJOXkse3bLwGIS8vgwsee+ad0MY4HLnsni577O21VFVFLNEUBQWDOTbczaOIJNOzbw4JnHiPk96HR6ckfOYbCyVHbvZSC/hjMvy3DEgzZqat7gba2rzCb+zNi+Oc4nbuw2YYjimo6X96DIsloss3oMiyYwt/Cmkejtm6Jg1DmvkavwXeIATEULYaoA0PGKLAkR4+/qxzi+/2q7/uuD0/mskgDwxJLaPC0EpJCPDXlKb6p+YaZ2TM5MftEzv3mDCztB3irNwjzdkRV3r3d3LvrKRbXL2XVOav62Hf+gEAkQLu3nRxbDp+Vf8b8NR/zV/cptAx5Hm/TTB4zbSHLkkWju5EvJz1D2tonkap24JLOoTnVRNjYQWpnG7fnBXGoRBaesRDVb3h213S7eLq+nTmJMdT5g+x1+aj0BRhpNfFucS4eSSZZqz7m5NQTkWgKhCgw6nFGJGLUKkQBXmnq4qm6dsxqkacHZDIzwXaMX4YNVXa+r+xkQkECEwoS0BxiVNzzdSnzdzaz5e7pxJqO32HmrFc2sb3LjTYo8f7loxlfkMALqyp58kAzhBU0AYlQvA4hKBEuikWjEgkrCqcnxXC5ycLFb2xlVlEqL54/jPVVXVzx7nZSxqVSbRJ4aVAWHaEIn7R10xmKoBIgSyfSU3sn/kAjCmpmFD2EYhjMnh1/ZYo6ie3aUhq9LWgEFXePuZtzB5x71DE3uVs5d+G5aOLPoEk/A7+sEKtWYVSJtAXDGFUil6fF4mx5kSX1S+gX24/zhzzAa50G9h9iicSqVcxKtDE+xsxpVhU6ezlfr3uQB6QWJopWcpJKqPV1Mjb+JJ6vfZkrDFnMq9zC+gHTGObswNKyO3owMdlsyxnFcz072C8qXNSTwcVd5yKTRer9kxCNv+y+ciwosgIK0VINTxc9T76BLziJiCrE90NE/pZswSFH378fAl1aAc7rWEZJ7z5Mkp+ILYPFMaNZYipCLwoEZIX3S//MzJ4t/OCfFzRn887BgXg9PlLNQdq9On4YLofNPpVIKETp6uXMP/liVIlW1s84ETztRHa8w6nefjRoU3j2wGMoQQ2V+2QUwKoL8ezJt9OZmIYu6OfyVW8zVa5B9PcgK7Bfncv2lOF49SY2DD0B5VBAuEgdYWJCDHvcfrZ4o1oWIy06YtwL2dP4CQIR4vRxDIofxMaWjVw35DrO6X8OsiKTYvp1cTqA29fezrrmdWRbs6norUAlqJAUiamZUxmWdQMarYWZyUkk6TTU+4OIQJZBh0+SWdfjJk2vocRixO63U95TTkFMAXptAovtTmp8QTwRiRiNmkEmPfMONhJWFIZbjYyxmfi0pRudIvNhSQ5FcTFHHdtPg5cnt/Vyd6mapKsHYs47vqxwJOKhqeld0tL+8IuZZLt9NXv3XU1m5hX073cvAC73frZvn0tmxiXkFdyHgEIw0IgsB6mtfZZgqJOYmFFo1LEkJc1Cq42ns3Mp3fZtBEPNOF3bGDTo76Slnv2zv/t/Bc0tH1NRcT9qtYXEhJm43fvxeCvQahPRahPweKJuD+npFzBwwCPs3HUBgUAL48et/k0L2B8j6POhPZS48zp6MdpstFVVsva912mvqYqWDkkSWoOBcDDIuLPPZ8wZ5x7ToetYqK17kfb2b/D76xEEDQZD9qGSDxmbbXifbWVZYveShbi77WQOLukjBu73uPn+/beo3LqRcMCPwWojb9hIJpx3cZ/Ei89XT8Tuo6byORyqDQghPYIiUFjyDIaGfmgG6vEJNYiCCr0+E602AUny0N29DlHUIUleIpKXtrYv8XqriIubTHf3amQ5hE6XwsABfyUhIZp0UxQJt7uMnp6NuFx7UKlMdPesJxzu5peg0cSTknwqHm8Fvb1bifakUahUZmJjx9Kv4B50uiRA7BPM+ylCssyKbhdBWaHQrKe/Qcf0j7ZTnqJBOZRojNOoiPfKdO5q49XRd2JpGYFastGdvZD8fo+Tk3nOcd3L/yb8HqD4Hf/jCHjCvP2n9Yw65YhDxS/B3RPgwwc2k94/ljnXF2Nv9vDFE1vpTt6EgIhy+EUXKEpIYPBLL3Fwzl+R66qYMt1C4k1HrKL2XX4FX2VlEuvwMWx7FYqoJ/ePV5J+xnScHX52L6mmYlsXZuN+am0OzvR4MezYQfzVV2E780waFy0i67TTcO/ezaLPPqfaZkUfDjOwvJycqmqaMjMx+P3oAwFERSaYnc2ukiG4Q9GoqyCrSIkU0UUdssbDpGGnoLgMyJKC3hydXA6Znnm0tkQkBF9cGq1RzTsBLv6mjy931+v7UMIySTcOpWvdx3z8jw9ISk9l7p0PoE/IIByOsH3hfHYvWYjRZuOCtD2EwmMxxR7EpboeT20CSbcMR5t6JJMZqO7F/uZ+4i4vpMNfT/2enSiRILtXLOO0ySn0m3MpvStfRmeJoXbPDpbVpXDiEC0ld3+JIIjU1r1IXd1zjB79HRZVMrw9C064G/eq+zhQoMWrd5LbJuLTgz1WTXryXLIKbkWnS8K7q4PezysxT0hD0Kiwzco59Ox4CPo82JKOb5L4n4KiKLx2/aXEpWUgCAJt1ZVc9tTLmOPjqd25HU9PNwWjxmKOO/56z38GkXCY0lVL8TocGCxWqndspqW8jNk33c7mL6KWdydccjVZRUP+aetSiCq+7z9wC5GIl5TkU8nNvaUP+0FyhWh7bCvWmdlYT0iHr66B/V9C/jTIngDb3oh60J/zLgyYHaXmrnwIfHZQGyBrTNRhobceBs+F8TdD/QYYfQ1seiFqJxcOgByGtGE807KKD2Ji2HjBZsJymEAkQLKpb6nLk9uf5NOyD9g47F48/abzxr43sGgtvLbvNa4uvpqbh9/8q+fd4mlh1vxZPJR3D2PK8rieBzh9/DlMy5zGed+dh4DATUNv5HzLANQ73iK8ZxOgsKeomCv8B7h/7P3HXATbQxEuKa2lwKjjjKRY2kNhVnW7oouVXjcWlQpHREIvCoyLMROjVvFgQToput++IP0BXaEwOlE8yqHDFQjz2bYmlpe1s72+93CsK9aoYXxBAhpRYHFpO6cNTeOpc4b8pt9cWdbB1R/s4K9nFHHhmKi4oqIovL2xnlSbnuFZsSza10q8WcvN31eSUZTAH5JjaanoZv7OFhItOhbfPIl4c3Ty9uKqKp5aXYVxZga9cnQcGGszUWg2EFEUvunsJVYtMkXfwAZ/ErXB6PUy4iem7T6SYkdRbfwDeqmdcOe7nJVewLaO7WRbs7hpyE00KincVFZLGD0IIlPjLAy3GukKRfBKMuk6DRW+AMvsLu7KTWGayU5Ak8XFpfWYVSr+lJuCThRZYXeyqseFKyIzKdbMO0W5mAT4ZMm1PNu1hYgAVlmmR6VimKzixaZ2WvudysCqrxES+kHRWZA7BTJGRvt9KcynO57n8YoPmRgu4M9Vt2AdGcJ69vTfdD+c7y3GWxkNPsQOa0Kqr+A93VxeH6THqYoQQIMq1IDZ8SlGqZNI2E5B8nRysufxRYeTyI+mhFpB4E+5KVydkcjsHRX0+Fx8JOwiIyEDjSJh2vgUnfW1BCU1mRlxeDpbqHAnoBUliouywZRAo5TC5JQ/cJHBw18nnHi47YOdTczc30X4kFheieAjtamaGnMy1THJPJSfynM1LTgQUUfCKAj0bzhIfVZ//Ifs/qaZNDwwOA+tIJJn1CHJEqIg4pVkOgIebl15Mc3uJq4qvorihGLeKn2LLn8XM7NncuOwG9GIR79roYhMm9OPwxfm9XW1OP1hbjmxHyOzY4nIEQJSAK1Ky5Pbn8SoMaJX6Xll7ytcU3IN84bNQ1EUGt2NpJnSqHPVsbx+OdWOai4pvISihCJe3fsqb+1/C1mRsWgs3Df2PoJSkIW1C7FpbVxedDlp5jQqAjr8ssL0OAuCIOCVJFDApP75BaWkKOxx+fi8vYf3WrsZYw/zTI+f1LGD0OZYUR9DG+yfRXnFg7S0fEha2h9Q5AjtHd+iVlsYOmoJp21rQkRg4fgStKKIWjhCr4/ICk/Xt7Oj14W1s5W0r98l1tNDyQVO1BYHo0ctxGg8WqT1/xKiAYdWYmzDsXevRRR15ORcT0/PRhQlQoxtBH5/E23t8xk08G+UHbyTgvy7yM7uWx7qdfTi6enGlpyC3nTE1UJRFDrrazFabdTu2s7upQvpbm6k35jxhPx+GvbtRlSpkaUIBquNEy65in6jxrF72SKcHe0EPG4qt24ku2QYp9xy1+HSql+Doig0Nb1NQ+PrFBf/gxjb0Rbn4WCA7154kpodW1FpNEjhMKffcR+iSkV3SxOlq5ejd+rIGzwSQ7wNh70dV3UbbquLcRdcQE9LM4OnTCfY6sbxXgWStof6cfej82QgJEr4w/UUFNxFc/NHBAJNh3/XaMwjHHYeFVQQBDWDC58jOXk2gUArXV3LSUk5A7XKehST5MeQpCBO5078/kaMxjzUahOSHECjjqXXsQW1ykxS0kmIYvSdCobsuJy7kOQgJmMBZnP/4w42KYrCjWUNfNXp+PGHIAikdLUycetygjo9nqmnsFltJugM8b7lJVTSThR1ALt8Ei/sOJslt07Cqv/n5w//G/g9QPE7/sfQUtmLyx5AVAmsfKeMs+8aSXLu8VGMyja2suaDcrIGxxOfbmLHmnJ64negCcYS1vWiCVtRh8z4ja2c3GRnq/YMQGBKaBHFbz8LgK+8gg+f/IjWTPFQUkdAUETMrn4YQ0nIMsiiG491NyGtjFaSuPOBBxC12p+lznUtXUrPgw+hGtAf2+1/JC6/Hz+khQStFlGnQ5ZlpEiEXa+8x5rWFgJ6QIBTp0xhxNSpx3fxtrwKS++CghkEK1bD3FfRDT8XZAkFkdaHN2JMaKQxoZN1C5ejEWUueu49zAl9F2n1+3Yz/9H7GTammGmuV2hRsrBEPLhV76EriCf29HxEkwZBLR4WxNyl/46qg/sRRBFFlknWu7nwkScRsqKR7nDYgXP3MwgLXqN2egEewYFen0Eg0Exc3ESGlLzW91yW3AVbXyWoFdFmTCYQ6uBgbAsOmwarksCIUfMJ7t6DfVlMdHsBUv88GtVvnDA5VzQgCGAanUKo2YN/vx1dfgymEcen0fBbsemLj9j8ZVTzZNoV1zHspF8XCfufRijgZ/5jD9JaEbVnnXvXg+QN/22CmtFaYDu9ji14PRUkJs5k957L0ekSKS56CZOp4Kjt3aubcK1oIHlGA5r2b6FqOUy9DybfEV1gebvh43OizgnmFHC3QtZ4GH9TVDjOXgmGuGgZxs53jjRuTY/Wv2eOjbIspDBULeeStFSklGI+OuVozZkVZR0cbHNRXNDCzWvn8cqJr/D6vtfZ3RnNShfGF/Lh7A8P15D/Gs745gwSjAlMzZzK49seZ8EZC8i15dLkauLRbY+ysWUjA2IHcP+4+xni84KicF3VBxzsOciys5ahV/ed5ERkhfP21rDd5UUAAnK0/0jXaYjXqMk36nhiQCZtwTDxGvXPO3McgsMX4oVV1VwwJpOCpN/GitlYbefGj3fh8IUpTLVyxrA0zh+dxeaabr4rbWN3owNXIMzMwmTunDWQBPNvX8Q4fCFijL8eHLv2gx0sO9ABgF4j8oeRmfxxRv8++4YlmclPrCE9zczNpxaSptf0Edzc7vRywd4a3JKMWSXy9MBM8g06Tt1VjawohBWFPKMOT0SiPRRBFW5DUScgc2iyKIioQ43MToxjYvJALk6LR/zJWCApCtceqGdRlxOjSsQnyWTptXw1rIAM/ZFjlRWFz9p7uONQaU6x2cjDBWkk+GpwuOwo9npW7/8AT/yJfJE4mx5FxSirAZ2oojMUQUFBFARGWo0MsURZWOpgNS9uvY1Hqi6nMJhK6gOzkCMKij+C+pDryVEuCbIEIS/+zTtoXKmhOa4OU8hChjMBjxpOn2wiLHYj+w8w0hThlgHjSTYm8HnF52hEDZ+Uf8KolFE8PfVlvDJ4JRlFgWyDFpQIsiJT5Zc5ZVcVwUPPslYQuC83iatr3kKIBGH6g+BoQAm62VSzl5WddvQRH7Gueh4omMeZul0M1HvoF9uPcanjiNHHsMvlxRmWqPUH+bSthwpvgHS9hovTErghKwl7KMIyu5NKbwCPJDG/o5dsg45XCrMRgTXV79MTsJNtzWaffR/rmteRbEzmhqE3sLh2MWub1/L6jNcZk3qkrPAHeIMRdGqRYERmb5ODyg43i/a1sbvJgXToHE1aFSadmk53kHiTlgdPG8xpQ44up7lt7W1sbt3MTcNu4pPyT2hwNaAVtYTkEKIgYtaY8UV8mDVmHEEHp+efzqzcWTy942mqHdUAZFmy6An04AlHBW3vGnUXFxVe9KvvVFgK87dtf+PU/FMZlnTEIvuVhnYerm3npR0+xnZLGIcnEXfu8ZeY/hpkOUJ1zd9panoblcpMaspccnJv4qFaH++09SDIMhkGHa3BMEUWAxNjLbgjEgc8fna6fCR0t+OwxqGo1SSGAsS1VnBtzvvkW+MZPvzTf01c838RgWA7GzdOJDf3ZvJybz4kcCn0ca0ACAa72LxlOpLkRRT1TJywoY94Ynt1FRXPL8WqSiCk+NEOtKHYVMiRMI7aViJtPjzhXvySl7S0/iRbcjhYswGTxkZq1jjcoszuZBNdsSY0GhXxgkiKWk26JJLrjuBrbKeiejPeBA9nPfLX31RK8lMHoh80Y8KBADsWfU1rxUGmXnY1xdNn8ekDf6KzrhZFkdGrTAxPmkGm/shzWGMSWZqqZkp1PdUN89GrTITUIaYnnI+ASLlzK8VJ47FMzMU4MY6K6tvo6d2IKBhQuU5FDovE55oJi2WIgprs7GtRqYyoVGbUahN+l59vHn8Cv9tFar8B9Bs9nraqcraWHaRebyZNiVBgMpCakkJMcirGmFikSJiMQUXEpvxrrn4/xcpuFy82dJBj0NHPqGOXy8cepweNSqQhEGbcjjUMrNnHvuyRtKcNoNBZzfDS9fzhT/ez7dsvqdmxhQP9hrB4+jmc7NnDBaZH0OgHcs3iazi5JIenz/1tyYX/BvweoPgd/2P49rndtFQ6SM6x4uzycfnfJx4WZToe7F/XwvcfVyCIAuacILW+LUyfPIvV65Zx8pxTcX60ivUxXuJUOTiDnYiKitwaPXn5eqwjS9i7qJya5A70FhVjRk+kvbOFrs5mOh12TB4ZY0DCZZZRWcwMGT6c7MxMBhb9egmKHAjw2WP301lXy+XPvoI5Nh5BFI/ZiXdu2sRHX31Fol7PhY88csxtFFkmHAoiiCIBjxtzTBx8eBY9be1U5t3Ejq8/Rq+WOPOu+6l7+1b0KROI6T6LKud8dvVUk2V2M/OmP2MbNvuYx7v63dfYvWQheUOHU7tnF3q1xKm5wxEjUcEz49BE4s4biP2DMhxljXxb+xInJNdQEtNBRzgeW6wFy592HmZwHCi7g/b2rzGI8fjlblJTzyEScYMikZd/O2ZTv74H4GyJ+rMXnUW5RoU/5GFYIEhb+XOUaXdh9EUI6FTkbHgGjZQAEQXrrBysJxy/taXkDdP21y0/sIujODTmJ1xRhL7gtykjHy96Wlvoaqil/5gJ/7K+xL8LQZ+Pb5/6KzqjkdNuv/c3TS4kyceOnX/A4ynr87ko6hg9aiEmU1R/wF/RQ7DagWVSOo6FtfhL7egSPSS4zkMwxcPoa+GEu35yYB7Y8Cw4GqLCZqOuOrYV3OaXwdcNcfnw3W0w7CKY89Th5y/UU8e4787i/IEXcMeoO/rsWt3p4ZQX1xMIy0wZaGGveAuyIqGg8NjEx0gxpZBryyXBcPz2Xc/ufJb3DrxHiikFnUrHt2d8e/g7RVFY0bCCv2//O52+Tq4fcj1DEodw3crruHnYzVxdcnWftrpCYW4qa+T7XjfPD8xiWryFal+QOI2a/kbdP1VTfPMnu1mwtxWLTs1f5xYxMieO1eWdjMuLlq+sreiiudfPNZPzSIsx4PCFWFzaTkGSmRs+2oXNoOa5PwyjOOPYZR//KTh8ITbVdKPXiIzKicPyM9meF1dV8fSKSlbfPoW8xKOze15JotoXJFWrIekQ42Sbw8NiuxODKHJ9VhJaQeCjVjvz29sZbotDL8qU2g/Q7tzP30qmMT716OzfjyErCiu7XSy1OxlkMnBGcgyJ2kOiiREJrerIeLDN4WFlt4v5Hb20BMNHtSUAJ8ZbGWMz8WFbNzFqNel6DQIQkhU2Ojx4pSP04FR1iMT6b3n7wCx0cXYikVQkVxhtlgUlJBHpCSKoBfQD4lA8DqSGSoSIm251CueOy6JTr0ZA4SZBTYdWw+fBAOn2v/Hi+FsYnz4eXyhCVYeHnAQTTywtp11exzbPq9ww5AauH3r94eNwh9xcsuQSGl2NTM6YzI2jHmK3R6InHGFjr4fl3S7G2kwk6TR83+PmxHgr+z1+KrwBNIfKI2VARCa26Vo0hJEUCb1Kz/mDzuemoTehVR0J+Pyw8FEUhYreCvrHRjWqtrRuYUfHDqbnnEa+LRNXsJtPyj/hzdI30YgawnKYeH08E9InsKN9B63eVgBuG3EblxddTmO3j4+2NZAVZyQ3wcTaii7e2Vh3+LfCh+xsCpLMzCxMJjfBhE6jYmxeHGadmoV7W/lwSyO1XR6W3joZk05N3I/KoCp6Kjh7YbQ0oTihmFPyTqHZ00yKMYXT8k+jyx3i3YrnCUkhzup/FiOSRqNRifjCPvZ27SXeEE9BTAHOoJPNrZtZULOAre1buWXYLTS6GwlJIc4ZcA5DEocgKzKL6xbTL6YfA+IG8Ma+N3lh9/OkGbNYdNY3h1khIVlm2Irt2AICmb4Is+xw2Y3jDs/PwrLCK02dvNti5/acFEbYjAgIDDDpaQqEsKhEYjTRIEFzIIT5R///GH5/M1ptIiqVjq86ermhrIERezeS2NPBrnEzSa8poz1vEHaDBRMK+pCfks3LuTwnDduwMSw2JVDvD7KsvRtZFBgnbOD6JB/TBt/1T5c7/G9AUSSqqv+Gx32QXscWxoxehr3aSXxmNpb4I2NRT2sz9Xt3E5OSQkr/RNzegxj06UjeeBwd7TTu30tndTWZvfnUZg2iLEWFyRVmmEMgyytjiYBTI7AmWU1yQEYrwdYEFctTNZT0SnTpBHbEH7lPoqKgAMqPxh2drDDVqTCwI0RJh4PC05LIGd63TON40Vlfx87nP8UajkMlqAgpATKGDiE2PgXZHyEsh9hbvpIBuhGovSpCArw1I5HNBoXmUBjXIZbc6O4IL+3wISIQVAfQRnToz0mjum47W774FBkJtUZL/uiRqJN2UrfRga/TcLh0RWc0YUlIRBAEYlPTScjKxhwXz97lS9gflLAMG02odCdiVxu7h01m++CxSD+am6Ta28itP4jFExVQjgv5ufyssykaPhK/olDtC9IZDJOh15Jl0OKKSOx1Rfu6JJ2agSYDBUYdZpVIRAFnRKLBH2Sjw0OMWsXKbhfLu12kCDJuQYVXVkgK+YlrrEI2mIhvb2S6x01DQEti3SZUh1jkp9z6ZwaMm3hIwH0LzZXl3GrMwG2w8ln657yycyp7Wwx8d91I0pL/Z9m8/xP4PUDxO/5HoCgKb92+nqAv6sk+cGwK0y8r/M3trHr/IOWb2siYpLC7aj233HILKpUKi8VC5cRJLJh8Jl6d6/D2Bm86Znd+dGLhX4Yz14De0cX0E09k5ClzkSSJjStXUrZpE17AkpjImeedR2Li8avzHvh+FUv/EWVppA8cjKO9lYzCYk6ed8cxF6lyKASCgKg5esLtd7v44pF76WqoO/yZKSYWwdOBJxKd5IzOn46zy06Fay8AmaaBjE86nbX2Dxky2kbR6ZcjJA/62eOVZYnFLz5NxaZ1FIwaR29DFc4uB9MLZ2CKKULTKpJ4XQmd75fS2HkAjfZNRs97Bpq2QNteKDwDiqMTrFComw0bJ6LXp+L3N5CVdVUfLQmALbXdvL2hjkfnFhOSZEQBUm0GFEXhtG9Oo8PXwfzT5pNhSqd03WwckXrCYoS0iivIKLwUf1k3sj9C8h+HH7Vg8+3uJNzhxTojp4/dnW93Jz2fVRBzWj5KREaTbsap24xvkRttWwaxcwuQgxKaFBO67P9bQkH/LH6ayTge1Na9QF3d8+Tl3UZs7Fi0mjiqqh4jKWkOqalzAYh0++l4YRdKUI6urgSwTk3GsnMWQlrxUeVIP4eeQA8v734ZBYVUUyo2nQ1P2MNp+acdCSCEA6Dpy0DY07mHi5dczHMnPMf07CjFvazVxR8/20OXJ4gkwqgx6Syts3Nd/04slhbyY/I5Je+fY7i4Qi6uWnYVB3sO/mxpiDfs5bGtj7GgZgEAaaY0Pj/1c77oCrG+102sWk21L8Butw+1IPBYvwwuTDv+CYMvFOHVtTUEJZmhGTH0S7bQ4QqwuryTtzbUcem4bHY1Oihtcf5sG+Py4jl3VAYPfHsAdyDaL2tUAt/eOJHCtP8770SnO8CEx1czc3AKd540gC93NtPpCnKgzUmHK8hn14w9HLiwe4J0e0L0Tzb/5ndha203r35fQ2qMgcn9EjhhQBL6n3E/6nQHeHl1NV/tbsEdiJBo0TGxIIGidBvnjcrEpFPjiUh82t6DpCjEatQYRZGIojAmxkSq7siCNhCWWHWwk73NDsw6NR9vb0RjUPPcBcMoD4d5ramDSq+Xu6tWcFbdJES6MenWEzCehEoTQK3uQfILBF1JCHIvbr0Xlz6T19LjWZSmwtz9KiHDcIKmqFaTzrOej4cPZ0L6BAJhiYvf2sr2+l40KgFJji5gYrK+RDbuYkL6BMwaMypRRYOrgbLuMkYlzGBr1zLO6n8WD457EIj2PR+39fBobSsBWeGEWAtre90UGHVcnp7AGUmxhGSZp+vb+abyc8ZoDvLKia9Q1l3Gp+WfsrB2IbNzZzMpfRINrgYmpE9gaOJQAlKABzc9yJK6JUxKn4Qr5GJvV3RctGgtJBuTD7MO5hbM5b6x9+EIOkg0RBcnvrCPsu4y9EICj3xzhBEhKwo/nu6eOTydeJMWlSgyLj+efklmUm3HVuMHaOrxMeu5dQQiMpKsMC4vHrVKwOELMzInloK8MhJNNialTWNtRRfDsmKp7fLw/Koqttb1cEpJKmPy4lm8r42tdd1kxRk5d1Qm10zKQ63qO6dwBBycueBMuvxdWLVWFEXBL/m5suhKmtxNLK6LilWm6PPpDDQRCVoRdXZuGDKPq0uuQH2IffD0xq08GdKhliQUQeSBpER0cXpaA6HDwbTEQICuQ0KFAnBxWjyftfdgEEXOTYmjxhdkVY+LGLWKs1Ni2e/2IwiQqtNSaNIzM8GGAHzf6+aRmlayXd08ubYds87I6rqPiE/OoKOjFlmWDp/f0JmnMPmUi5HcIbQZFkS9ml0HDnD/95vY378YnRjgqcRtnFZ85+F9FFn+r0kQHAv19a9QU/sUKpURs6kQ9+opBGoceEUXSeMGEGh3kjSkPxs/e5+AN8qS+cHu+8D3q1jxyoukxo0ipDfSz5RLaUIy95cYjvodEwIRAYI/ephFYHyMmV1OL3pB4KrsJBI0akbYTBSa9MhATzhCWyBEnT/EJoeHbzsdOCIS5rDCi5v2M3DKAHq21IJLQhBFxJCIWqtFLWgQwgLWcRnEjs1FNigYbTZc9k56mpuofW8DYvxIOiwCRrWKFI9MrFfCaVZj0KmxdgchJCNaNFimZPKSOcLzvb0MENXEKSJDEszEmrX8ra6dC0MahsgqxmzoInlCBv7p6TR7A/iWzEdvNOHq6qRm1zakSIRBE6Yw8byLURSo3r6Z1sqD+JwOZEmiu6UJZ0fU3rwudxDzT7oAhSPvtQCckxLL5emJNAdClHv9rLC72PcjF6rD11aWkX/Dc6cW6FMm9wP0isTorSsYuW8zaosVRatHsHfQb8qJOJvqqevx8651FpKo5k/j4pmRIpGQmU1cWl+RbVmSuPOVV/lw8ARyKntpr/VycWYrtYLMW5dedNzlOv8t+D1A8Tv+R+Dq9vPBvZsxWLX4XSFOurqIghFJv7mdcEiidE0zPWINGzau47777kOtVhOsraV2zsm0XHcPGxw1ZCb2IzU3lm3btjG430C6D5TSKYeR9Ub66aB9zw6ScvNJLejPlIuuPEodGECKhOmorSa138CfnYhIkTBv3HgF1qRksouHsWX+JxhtMficDoqmzqBo6kzS+h+9f0dtNZVbN1I4eRqKLNPT0kRvWysVWzbQ09LE6NPPQaVWo9EbaNm5Fuo3kD31XLJPuBDPa7UoIT8Heh9ncPo8BMWAEtCS+vB4VNrjo6nLkkRr5UHSBxQSDgVZds8FVLaEUQkaTs68Gq3BiCqkoqx3GdOuL0E99Oi6ea+3mpbWT2lqeoexY5YhCBpkMQ1vSCLepEWtEvGHJGY8+z3NvX5yE0y0OvzkJZpZcsukw0rnAMOThvPQ+IfIseaAHOH71QNIUfIZOHMFnm1tOL6qjjIf+scS7vLR80k5oklz2GHEMDSRuHMHHM74dH9aTk/nRuIuHITFMoDauudoafkYQdCS3ngDhvLBeBP3oVESyLnyHJSITO8XlYhGNXHnDjjsD60oCuE2L5EuP4igzbSijvn31eb+N8Ph2MHuPZdicY8kP3wfmjQzEbsf44hkiMiEWtxIziD+nY1I7gCx2tfxGi/EYliE3rkQ5Ahcux5Sfp2F1Opp5erlV9PmbcOkMeEIOg5/NzljMi9NewmI0tR3deyiwdXACZknEKuP5Z397/DMzmdYc+4aDNpYKrwB7llRTqXbT2qckQ6bGs+hzMsgt8Ka04Yd6xB+E3oDvbxR+gaXDb6MJOOx+zFFUfi4/GN8YR8XDrqQXR6Jc/bUkKzVIKOQY9AxPsbMmcmxmMMK3+5ppdcXItaoJSvOyI6GHrLijCSYdexvdXL28AzcwQhryztZtK+Num4vGlEk9KNsuijAjMJkXrpgOKIgsLi0jepODzMKk1lfZUerFjm5OJW1FZ38+atSAEbnxPGnWQPYUtNNToKJU49BS/9vx9PLK3hxdXQhqhIFEszRa1jd6SHJoufjq8fwj7U1vLUhGvg9b1Qmj59VQkSS+a60jYxYA8OzYg9nybfV9VDR4UaSFQ60uuhwBdhU002sUUswIuEORNCoBLLijBi0Ks4Zkcml43OAqIbHOa9sptbu4eTiVPITzVR0uNla10OXO8ikfgm8fdmow4Kjx8Luxl4+2dbIjMIUHlt8kDq7F5UYDRCUZNio6fSQbNPzt7nF5KRbGblpL6rAATY62rHFqCi3l1PvdtCoT0XSmghrLdQas9hi6o+dI/2XwbmA+eNOocPbyTP7vyUs+7m0YCqXF11KtyfIHV/sZU1FFzdNLcDuCXL2iAzUKpHL31uPEP8NelMHEkEEQSKiBHC1nkTIMZLknJX4DCuZkjGFFFMKZo2ZK4qvQKMyIyvKUdoITa4mXi99HUmWWFi7kIvz7mVq5kwKU62YdGreLH2T53c932efQXGDsPvt2P12ZuXOYkX9CowaI3eMvIMhiUN4ePPDhOUws3Nnkx+Tz5iUMYfFactaXTy3spIeb4gUm57t9T04/WHOG5WFVa/mwrHZ9PpCdHtC5CSYSI85evH3a1i6v5015Z0kW3XM39WCQasiyaJjW10P4/LjuX3mAO77ppT9La7DOi9JFh1TByTxxc4mZAXyE01MHZDEwXYXG6u7GZhiYWxePFa9GptRS6JFh1YlMDBdJoSXfjH9sPscPLTlPtY1rwMg2DUdRdajthxAVDuYbLmftT2voDZVo8HMjLQLuKrkIjJjLexubiKwcxcPanOotEavlQCMETSctaODyXYNn6b6iIgy2xNtbEk2MtpiRCeKbHJ5SNNpOd1sZkvAzy6PnyEWIzpRoDkYojnQly00xKTjyo++Y7xhDAiHAugIEKsmmBDCoDEjBATk1gBK4FDAQgBBq0KTZkY7PYG3Pn6VN8eegEodYcu4Ikz6VJa98hxdDfWc/9enUB8jCfTvgN/tombnNpJy8ohNSaN818e0dLyNRmNGCVnx2mXy+l/B4Ekn9RGWlOUwbe1fUVHxIPHmqRTmPk3Za0twySm8ka/FoxawhmXiQ1Dc5SHf4SArIY1ej4NdVV+QNq6I1p2V1I+5gPdzzQTUR+aV42JMfFKSjzMisdPlpdEfojkYAuDclDhcEQlJgUEmPUk6DX5JRkDBF3YSp48jLIWRkdEdQ5xRURTKvQFmbi1nrF2iyCmxL0ZFr1bBHJZxagV0ERkZhYAo8OcKmaEOCb/kxRPnRtMlIskRtuRm8mDJz4uExyHwtNpKIMtMvSLxdF07xu4goR1HrLltRg2mCSnUitFxzyAIGNQiPeHoMzLMYiTLoCVdp+XazESStGoWdTnZ4/aRqtMwPsZMP6Oe9lCYnU4vRpVIudPDfqeH1e4gOUYdT/bPoC4Qos4XJD8isOegnXZngMI0KxP7JVCSbiMCdIUjtPb6aQn62V5VQV19HbK9gxhXD4ki2EZPxJeUjuDzkNjaQJKzC0vRMEIDimkISbgiEnqViE2tIkmjJtHrR02IpX+9mzYS2WUtYbJ3D7Fahcq8Gazu0qBVRcf8+08p5MIxWYeD5IFIgLvW3UWrt5WCmIKojs7+t5hjnMorymQET5g0v4uK7GzipQibThiO7Rgsp/9m/B6g+B3/I6jd08WSV0s5+cYSOupcjJidjfpnsk/HgwULFlBRUcEdf/wjglpN76ef0v7Qw+Qu/o6tlXZGTSxGb9SxatUqNm7cCIqCWaNm0oyZjBo1it1LFlCzcxtNZaX0Gz0OjVaH3+2icMp0tAYD5th41n/yHvV7dpI3YjSjTjmTxJw8dMa+nWvllg0sfPZxzvzzQ2QWDaFqywbyR45h4+cfsWtxlPo9bPapTL7gchSUw7/z/p3z8PQcrfprjotn+pU3UDDyR3WwKx6EzS8h31lL09YmVEt6AVAbnUR8NgSNiCbDTNK1/3xNmdLbSOf7N0BXObu7xpNsmI1FE0tA/RpFj34JP3IdUBSZmpqnaGiMakvExU5k2LD3kGWF2S+spsa7A63ewcj4kwiFdGyp7WHetAJeWVtDvFlLhyvIytum8HHNMyysWcjtI2/nsa2PoaBw49AbubbkWnYsLkIRFUbN2o8UCmJ/8QCKopBy63CcKxrxbGhGtGpxlCwjoK8l7vszsRYOIPacKM235bG1VI67EUUI8oM/ambmFTidu3C59iCgQiE6oMW2n4ileTye5J2o/FYSHKdgGpaCvn8s7nXN+Ms7CVqacKVuRhNOpt+0WxFNGjRJBoRfWGT86jX/aW04UQs3u301CQknEgp1Yu9ei1YTT1LSLETxnxe1PB7IchCXez9SxENT03t093yPWooja9M9aMJJEJEPW83+aC80Qg222OXoM4DKJZAwAAbMior6Ffy6aF9EjnDpkkupc9bxjxP/wdCkofgjftwhN9/VfsczO5+hKL6IJk8T94+9nwc3PYg3HLVHtWqtuENu0ix5jC/5B++22vEdWrALUd0opsZZuTUnmZu3VFGnUvhuRD+G2EwEZBnzMUTkWgIhXq3rYEWHg2S9hiFxZhQBdjh9FFsMXJGRwEDTb1uweCWJSVvL0YsC91vjONjiotMVIDveRFWnm292tyArUa2FQDh6/D9MRH4KUYBBqVbunTOIETmxlLe5qer0kGLVU5xuw3YcTg6KovCnL/ehVYs8eGohul8Q0/u/go3VdrbWdnPOyEwy46L99PqqLi59exuHZAI4b1S0TOzT7U1cNyWfbXXd7Gp0ADAkM4YTByaxaF8bFR3uw+3Gm7RkxBooTLNxz5yBGDQqNtd2s6mmm7ouL21OP3ubnZwzIoNUm57lZR1Ud3p4/4qoS8mP8fmOJu78ch8mrYoYo5ZrJudxwoAoWy8iK+Qnmtnf4uT8N7YcZrXEmbQ8dU4JU/on4Q6EsRk0bK/v5aaPd9HpDnJKSSpxQ3W83hHGHGkirIonKPQdp1RAokYhS+NBCVQhSF6avZ0MVrfwwey3+2y7pryTF1dXUdnhIRiReODUwVw8tq8Q4f4WJzd+vItgOMqIs3tDhCIyc4pTmFmYwp3zd5FZsAqDrRpH0IEn5CHDksETk59gUNwg3GE3Vm2UpbO0bin3b7wfgIAUwKCy0nngTlDUaFQCSRY9YVninBNaGJ6eyajUUSyvX85HBz8i0ZDI1SVXk6AuRFF3YNPZiDfEI8sK4qFgtSsQZlN1N8+uqKTLE0SrEml3BbDq1fRLttDpDlCQaObm6f0YlvU/U/r3Y3y2vZG75keDgxa9mgdPHUxjt5dEq55zRmSg16io6fIQkZQ+TJ9v97Tw7qZ6ytvc+MNSnzZLMmxcOi6HJfvbWVPRSf9kC429HYjqANdNGMuc4lQEwBOMUJRu47V15XxcupRe1QYUQwVyKI7k8AWsuv4aHO2tVD25AWdaKgNOK0R+7yBqCdzhXiKZCtY2KxISMiLbUjWM6VLQIiAk6JF7/IhhgYgooRuXjsYfRm3Wo8u2Yc8x873Tg14UKLIYCH+zBus+A+o8EwmzBuLb1YEqVo9vezuR7gCiUY1o1qLNtKDLt6Eyawk2uFD8Eby7O0GSUU2L5a/r3uLLSRfzRFIZwzoSWP7aCwCMP/dC8oaPJiY5Fa3BQGddDa1V5dgSk8kZMhxRpSISCrFr0QJ6dtchqFSYChJIKsgjPiOb+IxoX7Hp848oX/E9iYNycXS043M7CbicWNJchCMy8QU+YgfaaQwU0U0KaN0kiq2kervwN05k9hXPojUYcfU2sX/fdfilcrTeHLK23YEqbGZpqpoHi/WY1CqyFRFHRKJTVAj+6P6KisKVNQGm79vNR6OHszBDzyyDkRNTY3BHJNCouCA17mcXnE5/GItOjSgKOAIOntj2PCdkjWdp/RJWNKxgZPJIDnZXEJSCpGiLmZBwDleOmkaqre8497eKZp5vjQYL+mk1pJmi7lCxGhX+Q2NVo9dHVyDEiQ0tjPCZKXQbWJiuYFVp+ThFw8BYE3ndEb7a14olVof7kCuSLEJ3gg7FdOQcBF+E7INu/nbqYAamWNhc082yA+0sPdABKgHFrCG7JIGSzBgi7hCdvQE6EjQoQGMghABk63XU+IOoBDhUnXX0NIao5lOWVkPnxla67X76J1uIN2lZU9GFTi2SatPT0ONDUaJjc1qMnlBEptUZQBBgSEYMhakWVPZG4nztmO01uKpKj5yLzoCi0oDPhWgwkzV+OtYhE+hobKCrvg57XRWx3VUIQERQUX/CPEYW5fP/tXffYW5V18KHf/uo9+l9PO64d9wAU01vgYSQkAAphAshvX4JgVxII7khhZAAKfQSIPTuUI2NjXvvM57emzTq0tnfHxo3bMAG47Gt9T4PDx6NNLOlNUf7aJ21135xTTPVHWHyPXbOGl9KVziO3RnCnvcWx5Ycy5zyOdgsNm565yYe2/wYx5Ufx+r21YQSIVxWF0kzyajIdbw+cipok9N7W7j93NPxHWHJCZAEhfgYtkt2/5UAAEj8SURBVCxtJRFNMfaE8r2+t/iZapa9uJ2r/nTi3ttnfgT3338/ofp6TnvxRYY+8wytN/+CyNKlDH/zjT0+8NWsXMbj//dLxh53Imdefd1eW1MufvJR3n7kPiw2Gy6vj77url3fVIqxc05l44I3SKdSeHJyOedbP2TFS8+SV1bBtPMu4vk//46O+lqu+ss/9/rZkd4eFj/5KMtfzJR52xxOJsw9i8aN62irqeaCH/yUnpZmXD4/eWUV5JaVY3e+54NPuAPuOJ438kr5tc/OD9d+Ab/hpcRTimpP4hyTT94lmQ/lhnPPN5xIMoLD4mBLzxbsFjtDAx++DzSRLvTDl9GzbTl9SQcVl/wcdeyX97jLli2/oq7+n5SVXUpx0dn4fOOw2QI8u6qRHy28Gou7NvPymS5UqgC3K06e28ktx/8Zu/Jy+h/e4lunjOLRtq8x1HMsXz3mekZXmvx+6e95efvLTC6aTHlsMaf6E+TlHU8s1sTEggfp+udmfCdVEFnZTnxQDaEJb9PW9gJKWbBoP5Vv/4ic0RNxVPmpXXg/zRPuoGrQ1ShloTj/dLyrXiKdW0F7sZfe3mXk5R5H25ZXaYn+B5TJjmnLG55E0fIvYo0FaB/xOD2D5+1MZgCUr/gW3vbJ2Mq95H32GGxFH23b0C1bfk17xzwmTfwXDkcRTU2PUrP9rySTnbhcg4jH2zHNTBlhSfEFjBnz+8zrepD2fo/H2+nufod0OkwwuJr2jnkkk5nklyXlJbf6bHLrTyX3pAo8U/JIhyJYghvo2+bFUv0MjuB/sJSPRM34Eow+D2wu6GsFb/EHLumIpWLcsuQW3m58m8vHXM7Wnq08seUJbjnhd1j8szAAi1J0JFP0JJK8tO6XtIc2gLWAntBaHI4Krph8Pa3hBnpjbRzjsrGI2bzaYzI0oejbHiTcEWXBN+ZQ7N9VGfXkhhauaWgC666k0jSXk2KLhRXdYdowKUgr2u2QVqCCycxJkNuKoRQ5SU2fXeG3WXn12GModtjQWvNOT5i6WJwLi3Jxvk/C6va6Nm7e1sSwLWEaq3swFOS67XSGEzisBpfPquLyWYOpzHPTFU5Q2xlmTJmf2s4IwWiSwQUeHl5cR4HPwbkTSt+3H4PY2/qmIC+tbaYiz81nplaQTGs+c8dCVjX0kuu2cf05Y4gkUvxrwXZqOsKMLfNzxazBmcSBgkLvB/cCSZuaG55ey0Pv1qE1jCn1c90pwzl7fOk+7//0ykZW1PWwvinIu9u79vjemFI/m1tDFPoc/OvKY1lU3clpo4t3Jlx2F0umufPNam57bQtDC73MPt3F35t6cZgd5EUXEA5vwpLqADKJDtV/Sp7nzKz/bo+287sTbmXZhnI2toS45eIJ9ESSXPy3hRT7Hcwcms+Xjx/CyOIPb7SaNjVd4QQF3kxD6XsW1PDzZ9eT77HjdljAXkOq8F4i6V7ynfm0R9uZUzEHj83DizUvMqVoCr+d81siqQj/88BSSBTz47NGsai6k9ZgjGV13cSTJjOH5tPUE+WCyeVcMKkMu8Xgf59dx8Pv1jOxIkCB18HK+h56oknOHFtCd38fE4ChBR5mDM0jmkgzqTKHCyeX71ez1k/Cf5Y1YGrNaaOLD2ib3h201vREknT0xdnYEuKHj68mmkxT6HNw1rgSVtb3kOO28+uLxn9g9Ufa1Ny/8hXuWncrwWQXd8x5huOHl/LCD3/DeDU7syNIqpe3u59k8OxjOeXLVxNrC2LzOnnrj/9gUM8wmiLbMHUKry2PSKqXiK2PQl1BsauKWDqCzXBgURYsATvuaSUoBamuGKFlTURVmJE3nLHH9rhaazDZY8nme6V643Tev55kYx89hSE+PcHFIOr43Jv/omikG6Vz2PB8JsmYU1xK2TGjWf/Wazsf7ysoZOLcs1n72jwm5A9HD19F0tWBu2US8YZiOnu6iRaZeIsL8a1zUukdRXVsDSl/ilxvDsmKV+kteReNot0sYV74Wl7x79lUdHRqKxer+6ha46bAeRKh0ofY7vXR3vwFtqlhrPWnyInFWJefw7E5Xv4xfigF/Q2Q46bJkt4w6/ui9KTSbOmJ8GxPCKupSRmK75QW8KNRe5bzP7P+XVqDJhOLRzKpMge71aCuM8Jv5i3htba/49UjKPcOYrt+GNPWvPNxKjyFtK2WdLQcnfZh9a/CsPahk7l4LAWYppVp3i8wumA0s4bnkw7YOcbjJPd9PuC2J5JcvXobS/riJPs/M+5YyuAwFHPbNf9d2sjnZwzipvPHYiiFYShSaZML7nqH1TqJCiWpsloZX66oHLyUaDqIz+6j0ldJnjOPQsskYgkLy2q7+L9XNu/x++eOKeY3F42nw0zzn/YelgcjHOtxQU2QxY29lA7LIZDvIsdhZbBpIdfvIAdFsCfOH/67mZr2MJ+ZVsn6piBb2/v44swqrj5xKG67lZ5Igre2dLCusZem3hgA06pyM+8zWzvZ3BbCaig6wwm0BncqQiDVS8xw0N3f1LQi1sjE4BqGRLaz+194zObBN24mvbE0juJKvn/1JTuTrLuLp+Nc/uLlrO/M9AUrdhdT5a/i3ZZ3+dK4L/Hdqd8lkoywqXsTpZ5Szn/qfObEZ7AmMp7zXIqvf+krh/Xypw8iCQrxkd3/s3dIJ02u/M1xe33v+dtXEeyM8bkb9u6QfaC01vz5z3/GW13NjFdeoX7qBCy1dRRNn8HQ//dT/AWZK1Kmmeb+H36TVCLBlbf+FYt175N6rTXr3vgvpSNHkVNcQmv1NgB6WpsJFBZTPmoMfV2dtFRv5ZU7/kQ0FNy5HZLV7iCVTDDzoks57pLL3nesa1+fR7Cjjc76Ora8uxBvXj4nfO4Kxsw5Zd9PsHFZ5rFFY3nroXNZEqzmfr+XWa7pXL/8Cu4re460YXJl0/lsuiiEWWAllo6xrWcbHpuH0Xmjea3+NR7f/PjOH6lQzKmYQ12ojstGXcZnR332/V9gMw0tayDUAiPm7qyeiCc66OlezNp13wT/iTS7TsZj99IV6yKWTPHvRSG6PffyvanfZ0bpdB7c8CCdsU58dh8LmxYSsAfojncTi7nQoamkAi8S3n4NxKr4y+encPLoHD7//OfZ3rudkY44XyvcdQ1hWNW38C87g8jyNvoKV9A4+U8YhoOqqv+hqPBMli2/BFdyGKXzvoVC0XzcX4n7NnGc46uoVCyzjWVXJrZM/HzmCn/zKiifSnzINDo73yLXM46u3nfZXP07QKO0hbQOU1pyEXl5J5CTO51VK75KX2QTBg5yGk6mYPPFeCaUkgrF8Z80COewnPd/XXcTjdaxcOFpoNJYDA+aJKaZwMc4cjqPp7XoCdy+wYwa+Sta25+jpuaPWK1+TDOBxzOMRLwDj3ckI0f8bGejyv0Vj7eydesttLY91981HKxWX+Y5RucQeb0Lf84EfOOrsDp6cbw4F5UM7flDnAE463cw4ZK9khGbwjFipslwlwOroXAYBr/YuJJHm9uwp9sJxdpJx7cz0tZFfXdmJ43Thl9BjesCFvWG9xqvAdgMRdzU+NJNRC2lpHab2vNsFrqSafx1YfTmXk4cWcinp1Zw5rg9PyAm0yYz/vgGbU4Dw2lBGYp4qQssCkssTREG7VZwxU0udnr46pRBVLf38eC7daxu7MVpMWhMp0jNKmJKjodfj6zgx5sbWBaMAFDltDPZ76Y3lSacNjk5z8fZhTkU2q0cv3gD6e44elE7v79kInPHFOO0WWgPxbEa6iN9SBEfXTSRpieaoNjn3HkSaJqalmDsA3sLfBDT1CRNc7+rUbTWrG7oZVNrCAV0RxI8taKJ6UPyuPakYRT5972l3Xu9vK6Fq+9fxvXnjObCaX58dh/JdJJ3mt+hyl9FKBGiPdqO1+al0ldJpa8SU5ts6tzGjx5pY21jEKfNwKIUibRJnsfOs984niLf/v3+93tuD79bz+qGHuIpk+r2PlY1tTDimHcozo0RifhpTL2Nw2Kj2DaBtpqzyfd4mD4knzve3MbPzxvDlcft2oJ8Y0uQT92+EIuhKMtxsrm1D6fNwNSZrT4vmlLOuzVdKAWzhxZgtxo8uaIRj8PCpccOYlJlDsePKPjAZTVHssaeKJ19ccaVBfb5oebDzK9fxLWvXcUYy//w6zOuoG/9Ejbe+zzjc+ewOjGfC359Iyk7LG9bzuyy2VgNK50NdTzz+18x6cxzySkqoaupkcqx4ymsGsLWJe9QveRdcsrK6KirJbSyifHlJxJIZfrspG1pWnqqCXxqKENPzCRC9rWN6wcxE2l6n60mvLSFP01q4f6iEQzW2+ghDz89/KxuNeVFk3jniX8TCwWZcc55jDxuOl3VTWx67V1a6rYxccIIwlMeIWopIGodhj+1ECtpVNqOt24OsXUjqD02yMvFbsan1+MzOtFKsY5xPM+niavMh3QD+PqgIs4ryiGlNUu6+vjrtmZaDZiklzLUrOMl4wwiKrONe76hmJDjpTaaIM9m4aGJw/ba7nl3WmuebuthTV+UQU47XyzN47FlDfidNs4YW8LrW6v51oJLgDSJjtOwhmdT7HdSH2zEUfo4hrOZHTUDBk5Oyf0+L23cRDrp5qxhpzIoz83wIi8TK3Io8MF9a//DExveIJjoIWm0kaKPRNdMCJ7AU1efx+hSP4mUyWsb23hrSztWQ1Hsd+J1WDEUfHpqJTarwepQhDV9UWZ53VgtBvcsruW+eVu4+pRcxg7tpLGvEVRmiWc0FcVjFLFgyWTOmuTGkbuCRzY9QjgRJs+VR2+8l3g6c044sXAiPzz2h1iUhWSkjE2tIcpz3GxqDXHzc7saepcGnIwtC/DWlnZSaZPBBR6q2/c+x9jBbjH462WTOXV08c45oCXcwpKWJXRGOyl0F1LkLqLIXUS+M5+0TrOoeREFrgKmFO3qkdYdTlDdkamCWt8cxGWzMH1IHiUBJ3aLwfbOCBu3bCexZTklg4cwftpUfN5dSehoKsrrda8TToUZ4h+S+br+ddZ2rKUt0kZnrJNbT7oVh8XB3WvvpiPawfnDzufKcVfudRzdvvJ27lh5B7eP+TXHTz2Ltlg7azrWMLdq7v4daIcRSVCIjyTYEeX+698B4Mu/O541bzRQVOVn8IQCtNbc++MFlI/KZe6Xxn7s37V582Yeeughjl38Lg6SrPLvWjNnsdn4wq//SG9bK8uef4r6dat3drb9uNq2V/PuU48x86LPkk6nWfv6PNprazjnWz/Al7d/uwBEgr24vL4PzmD+aSL01HN72RDusGfK1E6uPIUbXd8l8nQdiauK+MLiL2GLGnRZdzXBsygLab3rSv8lIy8hx5lDlb+KzV2bebb6WRwWB12xLp48/0kq/R++K4bWmvb2l6mr+we9wcyHyRBebmpIk9R7nwgVOat45TNP71zru8OCxgVc++q1DA0M3dm0zKdH83/H/5Xfz9vMstpu/E4rF0zOpzgHHqr9MjdXhPEHk9iTJt15HsaP+RfxvxvUjfodqbIWZh37ApaXroemFTTOOo2NXQ9Qbn4JX+NMNg26joqGECO3ZRpMUToJTrkets+Hd/4K5m7rYWddB9EeWPs4WOxEp32G2jIbyuoi3zeVgs44hNsh0kkst4QGazXR2pdoc/diT5di7y4hnLuW0p4rGf2ZH3/oa2qacVYvuI6u2FuUr/g6vRULscVdeFuOw9V7DIoYJlYMWwrSNmz5EYKz1xB3tKNSDmKqDqsZoCv6NqaOUlZ2KclkFzZbHlWDvoLLNWify0d6epexefP/0te3CaUMKsq/mNnj2xrAYS8mUdNH10MbsOS7KPqfiSidhPs/BS2r4YTvgmGF8mkQ6cj8359JAMTSJn+p2cLmSAq/3c+DzZ17lE8WW2O0ppxYEs2YhgetHNC/znW4EwI2BytCcawa7Jt7KTWstPfFifQlwISCMXmMG5SDPQ1rjRSjnA4maStWq0HCgLcTMTbU9+Ja3c0DX5nxgQ0eI4kUKVPjc1iJJtM8t6qJgNvOiSML37fh4Q5aax5YXMdPFm3DnJhHGrBpKKyPYE2Y+MflE1Yan8WCoRQrQ5E9Hm9f1M5tZ43hgkl7V5gJ8XF8+Z4lLK7u5I+XTiaRMukMx5lWlceQAg+u3SoWu8IJNreGSKZNXlrbwoOL67jjC1MYXuTjr69vpcjv5JJpFfvcDeXj0Fpz94Lt/OL59Zh67+VLxw3PJxhNsaaxF7vVYMlPTttrqVJTTxSv04rPYWV1Qy9PLG/AajE4dXQRs4ftPf8mUpnlJ+9tKin2ZmqTWQ+cRijsxIwXckLpmXw94Gf+w/dw/vd+ymL7Zv647I+EkiG+MPoLfGX8V+hL9DE4MHi/fv6qeS/y+j134rT5iCfCpNIJKseM5/Qf/JBPP/tFQPHQef9kc/dmRueNJt+1/w2DE/Uhqv+xkr9PSLLV6sQXM3it0Mak9GZODYY5IVaClRoeLtlCSPmI48SXTjClxc/95SVs5RjiKpMg9hgw1hmlIrGNqsTzOHWcPxnf25lY2N15hTmM87ootFuZnetlsGvP3g2RtMkdW5v4e3Mj3drBiT7N5VVDmORzU+aw7Zybk2mT1Q29FHjtO6tdeqNJ8vu3cE6bmubeKOU5LpTK9KG5/qm1PPxuHQAlfidhzxMQmM+kghms7Fy0xzgsysJtp9y2s+n0uIJx+O1+GrojKKU+tL9KV6yL3y75LS/XvEwq5cDd8W1G5g9hZV0PoXgKn1OhXNsJxxNo0wmmncmlo/jizCraQ3HWNvXy3OpmSvxO2uPbCQx+gBjte/yOAlcBXpuX7cHtlHvLaQ43o7VmVtksfjT9RwwNDMXUJl2xLhY1L+KGBTeQ7D+HG5M/hjH5Y6gN1tISbuGSyp9BooRQLMXG1hAraruZ2d/zpTzHxbb2PpbUdBFLpqnMc9PYE8VjtzK4wIPP08f35l9LU18Tpd5SClwFLG9djt5rQcjeyr3lDMsZhtPixO/wU+4tp9RTikVZ2NKzhbUda2kNt5LnymOQbxAjckdw9pCzyXXuWlYWTAQxTZNvv/FtlrUu2+Pne21exheMp9BdyIzSGZw/7PwPHRNkGnaf/cTZlHnKqPRV8krtK9gtdt645A3cto9W/TtQJEEhPpJ18xt548FNAJzw2ZHM/3em7GrKGVUUDvLx8t/XcuqVoxk1c99lr5DZrjO8cCGJmu2YkQieWTNxT9vzb1FrzT/+8Q+Czc2c8ci/WXzyDFQwyJlXXUfc7+OFP/8Ol99PT0sL/sJCxp50GjMvuvSglcV/4vraePzOSfw7kMtGm8GFeZO4/ux/4LA46Hx4I/HqHkp/MoNlrcu4b/19XHrMpeQ6c7EYFobnDCeejrO8dTkBR4BxBeMIhdbR1PQYvZFelrROR7mHc1/9NxmeO2znpGX077mdTsex7NYgKZUKs3btdXR2vYXbPZTSkovZGGrnxpX/ptL2aZLdsyjLNXhlbQ/DKttI5jzFL47/OceV711BA5lMdIGrgJ8v/F+e3vYUd59xN9NKphGMJXl8aQMr63t4dnUTWoN3yJ/4rLea71vGg9PLCtvbRF0Gpa6LaI4+RVWskuHVIejYDL5SdKiZtSfNos3cAigMrTh2ZRDvZa+CpxB8xbsGEu+D1rWZbSuf/RZseh7sXhh3ESTCsO5JcPhh8PFQuxCiXe95JgosNtpyoHFQLhGXBW16SJJg9ow3cOTmEY+3Ed6+HVuiAN/4zNIa00zS2PQINVv/TNLsorBmJmNyqujb4CBtq8Ka58RVlcLq6CX4RidmUmGoKNHUZNK6ZK/XM2UL0jHiMXor5mOJBzBtYbSRwmrJwTSjmDqOzZpDecVl5ASmsm7997FY3BS6zyDQehLW7rydPTRim7sxQwkMW4rCY1dg650PdYswk1FuP+NhiofM4MKiHOy7JdbaE0nuqtnCnQ1dJAwvyoygDTe+8HyIrsS0FKKVi4RzFNZoPbN7xzG2aBDFfidvNvXwem8Ia5Ebn8tGpC1MakuQM4YXEk2myXHbuXhKOV3hBP/viTXEU5kPM4U+Bx198T067HsdVvriKf7w2Yl8avKeZa8Hm9aaax5Yzgs1HfjH5BLc1MOJJQGq28N0huOMLw/gc9oo9juZPbaIDo9BTzLF/c9vplJZeera2UfOe5E4YjR0R/jS3UvY0ta31/fyPXYKvA6SprnX1cMvHTeYG8/7+BcN9teCrR20hWKcM76MrnCCtY295HrsTK3KRWvNy+ta0Vpz1vssjxGfnN8uvo37N94FgBmr4NVLn6TIa+PONXfx11V/ZXLBdHTaz8ru/2JgQWHhP+c/yZItkOO2c8bYYtpCceZtqKPI52XOiGJqOrsZXpiHzWLQ2VDHu089hje/gGFTZ+CpKuVrL32Pdd1LQBsYhonGxGF4GROYRV88gc8eoDXcgmlaGe6bylemnoHdEcRr9zIksKvCJrykhe4ntuAcmYv/jMH8sfo1bk0OAsCrQ+TrLmqNKhQaFyZRFBoDP2E+U1ZKldtLwGplWTDMmlCUDeEosf7GNXlGgmemTaA9mSJumlhQFNitjPZ+8NIZS38lS8I0aYon90pgLKruZG1jL48sqWdrWx+Qxmpk+kQkUiYTKgIMynOzvLabpt4YF0+p4KfnjOYXz63niRWNXDknhw71BivalxHSNZxcfgZ/Ou03bOzayGt1r+GxeSj2FDMqd9R+J5I+yPbe7Vz63GXEEzZcyfFYXA2Yli5QKYKJ4B73TXXOJdo+B5SJz25n3Oj11HWkCTleJdeb4n8mXc2UoikMy8nssGezZJKRr9a9yq8W/4q5VXP5yrivUOje9256W7u3UhOsoTvWzeObH6ct0ka+K5+uWOZc7bLRl1Hhq2Bs/ljKPGXMq5vHxs6NuG1uphZP5ZjcY5jfOJ/nq59nTP4Ychw5xNIxntn6DK2RVi4acRENoQYa+ho4qfIkTq86nVJvKR3RDtoibbRF2uiKdpHSKSYXTaYuWMf8xvnUBetImAm6Y917NPo2lMExucdQ6imlK9ZFXaiOrlgXNsPGIN8gnFYnPfGeTEVJ//1vmn0T00ums6FrA4YymF02e49tlg/Eo5se5eZFN+O1ebl4xMV8bvTnKPceeRdKJEEhPpKX7lpLw8Yu4pEUgUIXve1Rhk0uZNuKdqw2A3+hi89eP/19yw+11iy98otsbmlAaY2hNe54isqqIeTbXSSbm3FNmUzks5/lgf/8h+HbtuBKxdhuxjnnmz9g1HEnArD61ZeZd9dtlI4cxWd++ot97s6xv5JmktXtqylyF1HuLd/5Qf7DbOraREqnGJU7aq9Kgg/TsuohzlrxK4Z6Kzlr6Dl8adI1WAwLWmuaf7UYx7Ac8i8d9eFjT/awZeuvaW5+HI2daMqK2xqhPZrHytBo3kitwW44meXuYZzHQalNo8w+HPZiSksvorj4PDZuup7e3lU0u45nedSH1xHg2W3PYksPonfb1xhTlsO6piDjywPc++XpeB3713QnkU6wpXsLYwv2PjHe0BykK5zgqhd+iDewjsWXvoZKRUm/8F02pV6nuTjzBj1raRB38UyYckWm/8ETV6HXP03T7DMJeRRVC17DNfrzcN4fSZpJ7l57N09seYIROSO4+bibyXHmZH6h1pnqCHcB7Pjw3bIW5v8+UzmQOxjm/BAKRmSSFmseg63z4LSfw/a3YdML0FVDV7ibFVPi5KvTcVeUU19/L2BiSfgY1XctLo+Ndcm7iXobcXWNpKhmFlWjDGznXf/BL5bW6Ka1RJ5+HBIJLAELqW6NxRlFhWpJhSzELKUYKTd9tqH0FNWS8DZhpFwYaQdxXz19RcsBsCgvQzf+AqM2B5TG4ohCKoU2wa424jZew2kswVBxKBwNg4/nluIL+UMoczXVpUym+p3MzM3hkbq1NKQLQBm4Els4zZ4g3LOS1aHXSIeqSIVHYjH9jMuZzZqODUwoHsxDXz5jjxLrpdu7+O3Lm6jvijCi2McPTj+G8RWBvV6Cmo4wTT1RUqbmrre2Ma4swHkTy4in0rSH4jy4uI5ct50/XTrpkHz4jyRS/Om/W7h74Xa+ftJwvnnqcDr6Etzy0kYau6OE4klqOyKE4inKAk7s1kxJ5/1fmc4JI/Z/+2IhDkQiZfLMqiYKfQ6GFnhYXtdNQ3eUhu5M+b8GJlXmML48gMVQ1HdFuHBy+YdWDonsEEwEeWTjI7SEenls633Mcf+acycW8sN3voorPoP2mvPRGvyVzxJPKGyBZVhT5cRTBpg2LOkSTOdGDEcrmE7MZA4WZzMkSpiRfyG3nXs1LruVtR1reWrrUzyz9Tmi6TA5kUsp95azsvcFbNHJpNxLMJwtYFpQ1gik/BiWONqya5mhwuAr477G1ydfvXObVJ1Mo2wWUmaKSDJCS18DHSmD69bX0kmA20bkcl75SJRSVPd181L9Ij49eDZFrgCRRIr5WzqYWJFDScBJLG2yOhShKZ6kblsPTy2s5YrZg5k1LB8FVHeEWdfYy/EjCplWlcvGlhAvrKvGbXMzf3MX727v4NRRJXz7tJF7VPTVdIRZVd/Dy+taeHFtZmvLitImbMVP0hlvJNc6mHL7NGxWk8aWUuJxJ4WBNEU+By8t9QEGyt5O1agn6EzWoFBMLppMsaeYH0z7wft+oD9YVrSt4JeLfkldqI4hgSGMysuci84pn0PAESCSivBizYs8V/0cBgZKKXKduXREO/rjprhz7p3MKpv1iYxvW882rv3vtTSFm3be5rA4iKfjWJWVlE7tcf9CVyEd0Y6dFRI+m49bT76VmaUzP/ZYwskwreFWTG1mdjKy71mVtrV7K09ve5r6UD3xdByvzcsxeZk+JuMKxh2UMexgapPFzYuZUDgBj23vaqAjhSQoxAHTpuafP5jPkPEF1G/oItybwJvn4PJfzub1BzayYUEz531jIoPG7l22p02TyJKlhN99l6fmPU3M58GbX0gqmSDUv8tFhbZgdTjo6emiZcRYUm4vnq2rsVosVE2YzAXfv37nVk7aNNm6bDGDxk7A4d77QEyZKV6vf50NnRtY37We1nAr5w49l0+P/DQBR+bDUU1vDZFUhD8s/QOLWxYD4LK6GJU3ikpfJctbl2Oz2JhaPJWrxl9FfaieNR1rCCfDhBIh/r3p30DmjbHKX8XsstmcXHkyEwsnfmjC4nePf4oH+7bw/AXPUOIvp7n5MXJypmPtK6D+X8/iPikX63AbHs9wvJ4RxOOtmGaKWLyJ3p5lJBLtKMNGU/MzJBIdvFJ7Ms9Vn0Z5bg63nt9DW8u/UckVJEw7cSz4jChNSSe18SQ9aYMRbifDbf0nAsrOI10u3g2nKXSV0BFt5diC03llwTT+56wpnD2xjFKrFZ/VgmHJ9BpImCZJU+OyGFRH46wJRYmaJlVOOzNzvFj28wPkKXf9gnbHv7loxEVEkhFumXMLatGdbN/wvyStBiPzPwfn/H7XA9JJeO47sPJB0CYUjSVx6YOonAp+t+R3PLzxYaYWTWN1xypyHblcNuYyDAymFk9lfOH4Dx2PqU3+sOwPhJNhvjv1u3tNNrz8U5a1r6OnLNO1OdAwh5xuaBqxnKQ9CmgM00ZV/TnkRifiP3MMluFT9uu1eF9aQ28DdNeA3YNuWE5y8TzS7UFSugQwSOlCeqzTiQfqsYcqcMc1XuNx3Ja3MawJKJkAuVXgL0MXjKa28gRq8BFD8WJHL4+2dDPKDNLe+S/CzvEknaNI28oxUp0MStVSmgiSaBjJuvr+ucES5oShVdz2ucnYrQZuu5VwPIXdahx1679TafN9y8djyTTz1rfy1IpGkqbmov6mflI9IYQ4nPXGe5nzyMnEe8ahbL1YHK1Ms/yWyRWljC3zc+u8zUwelEOf43Vea/87biMPi6HoS3VT7hzHjLIp1PQ00BhqYqh/DGu7Mlf4rYnhlPr91MeWY2AnERxNkXkWD11xEWUBJx19mSarDd3RneX3wViSPLcdw4CF9au4f+WrNHU62BJcgi1nBUN9Y7jttN8xyJ+plkiZKa565SrqQnU8dcFT+Ow+grEuOqOdtHbnEfBGsdsMCpwFWA2D295Yy4LWZ6kLbyAWd5MOH8NQzwSmVJby9ZOH094X59J7HsOZu4q+zvGAQlmiGI4mbIFVpCOD0PEqDPdmrP6V6LQXAzuGNYTuPZ5I2wl8btooBuW5eX5NMyvru1DWIA5fDWWDljEyv5wV7UsodBdyyqBTeK3uNWqDtSjUXssKphQcz2jnJbzc/lvShLly3JXMHTR3v5bqHkppM8296+8lnAyTNtNs7N7IF0d/EbvFTjQVZU7FnE98DJFkhJpgDes61rG5ezPTSqZxetXphJNhlrYspbq3mkJ3IecMOYdIKkLSTOK0OHFanft9IVIcepKgEAcs1BXjvp8s5MTPH0PNqg7q1nUyalYJp14xBm1qQl0x/AX7Lodrv+0vdNx+Oz1uBwtGVHDSlVcz7uS5zJs3j1gkQqilkaa6OjzpOAGXizq7j6p4lNMvuIDSGTOJpmPcuepOtge3MzgwmM+P+jwlnr3L4SFT2fD9N7/P9uB2DGUwNDAUn93HirYVuKwuZpTOIBgPsrwtc8XZalj5/rTv47Q42dKzhTUda9jeu50pxVMwMJjfOH/nOjhgZ4b2MyM/w7TiaazrzLw5Lm1dSspMMdg/mL+f/ndKPCVs69nGq3WvUujKNN15oeYF3m58m2C0i3O0nW+e80uqq28jHNkIKJS2oVVit2djITd3Ot3di9h9w6RY2ondSLIxNpp/dnyFwcWDGV8WYFyBl5m5Xiqcdl5a9l9Wb3mIXHs9z9eczpqO0RjOJgoLG/DkriPX2MiZZWN5qqWFroSFZMPVdPT4ARMwcEzMp7dkV2WKAtwWgy+W5fOf1m7aEymchtpZIrlDgc2KUjArx8tfR1dh/YBmXt99+knm9dyw8+sbZt3AZ4ZdCH+dCT118M2VENhHiVrnNgg1k6qYzomPnEtfuhOTBHnJuTTXzGVIeSf+8hfZ2LMaALth51cn/AqbYeOOVXfQHe9mavFUvj3l25R4SmiLtDG/YT6Lmhfx0vaXUCjynHlMKZ7C3Kq5nFZ1WqYpUVcN8T9eTIvlBnTaglu3UVh0F9Ev3Evtyj9iWP2UjbkSX/6Y933OB0339kzCxuqEjk2k5t1JsH4MSiUIjG7AGH8ulIzLLHGxOdFaM68zyJ9rW1ka3NU3wWEoJpsptmy/Gp3IJd56HoazAUvOFtK9w0l2ngTAuHI/n51WyYyh+Syq7uTiKRV49rOaRgghxOHlxgU/54mt/wHg2vHf45opV+51H1ObvFW/gBll07AbduLp+D7XtJva5MY3/8YLNU8RS8VJ9k6mhDM5YVgFPzprFP6PsCPRstournv6bkLef2O3an5w7He5aORF3L7idu5edzcAnx/1eS4YfgGFrkL+79WlPF17D1bvBpTSmMkARmwE2r0WZYnh0EUoa5hYOrMESicDxDtPJBUag2/oHWhLz15jGJk7im09W0nrFFbl4PxhF9IT7yKtUzitdl7e/jIGdpK9E0mEqyjIawPPGsLpzE5ZQwNDCSaCeG1e/nXGvyh0F6K1Jp6Oo9Esa11GIp0gx5HDmo41/H7p79ForMrKXaffxbElxx7w6ybEkUwSFOKANW7q5qk/rOD8b02iYVM3y1+qfd9+E4naWuLbtuE9/niiq1dTe8WVeE4/nRUBB2v7oqT9ebjdbiKRCG63m2g0isvloq8vs7bWMAy+853v4PP5CCfDXPPfa1jdvprB/sFsD27Hali5fub1nD/s/D0yoX2JPi557hJiqRg/nfFT5lTM2bnubVPXJh7Y8ABrO9ZiapMLh19Iha+CKn8VI3NHvu/zrgvW8ULNC4zKG8Xkosm4bW5CiRB5zrw97hdKhHiz4U1+segXFLmLOGfIOfxr7b+IpHZ9GLQbNubmT8Ja+xbuoWeyzDaCpOnG2jeYQelmHCpKb+5I2mxOtjeHGG9bxiz/MpaY5xBTeaztNgi7S1A2K9F4mpTbss+tHm1KcUFRDt8ZVERzR4SGvji2lKa1J8rCrZ28va0FX+XDKM96vAyhZdsFzBo0hnMnlBFJpKmNxPinLc45RTlcWJTDlnBmK6nlwTCvdYUY53VxTmGAnmSa0V4nE3xuPBaDNaEoz7f3kNCa59t7uaQkl2MDHoKpTHXFWYWBPaornluznR8vuwBig1BY8PhaufesezgGO4Saqc+rpNRTyvWv/5kV7UuYVDSJnxz3PzurYO5c+hR/WfczzL5xpJN+RtouY1JFLs+vbqEznKCsIEIwmsJVcR8xowEAj1GEh6F06ZVYlMGwwEg296wnoZwkbUNIRabjihYwvOgNOhJbCKY6KHIVcfrg04mmonyufj2D1zUQSn2KXP/DWL7wd6iY+r5/Pz9dspVXO3o4p6QAn9PKup4I60JROtNpJrmcDPO5aE90o3QLXx45DYfdS2MsgcNQ1MYS+K0Wpgc8lDoyf8d2pfZ9hV5rqF0Ahg0GzUBrzdZInEW9fawMRljUE2ZbNE6F08blJfm4I2nq28M0NIdY2P5nbIHV3HHio8TjARSwqSVEScDJlEG55Hrs+720RwghxOEvZaZY0baCxr5Gzh167s5lFB9XTySBy27Z751uPkhvNMk3Hn2NJeG/YfVsw2bYSJpJ0r3HYpoGttzFe9zfiodJgbNwW3KoiSynIbaKKQXH8f0Z1zCuYBxJM8ni5sVs69nGyzWvsqYz0xTcqqzcMfcOWiOteGwech255LvyqfJX7ew1UOopxWndcznx5u7NPLD+AV7Z/grhVBinxcnsstnMLpvN0JyhTC3OnBuY2tyv13ddxzpqgjUMDQxlzKG40CHEYUYSFOKArV/QxOv3b+QLN88i1BXjpTvX8LkbZ+AJ7GoKlO4L0/TjH9H331cBMIcOoSYSpD3PT6/LQczjJ1Y2hBEjRpBKpZgzZw6DBw/euRtBTU0NfX19uAIutrMdr83LrctuZWvPVm6ZcwtnDD6DhlADNyy8gSUtS3BanBxXfhxXTbiKSDLC31b9jWWty7j7jLuZUrx/pfWmmSKdDmOz7VoXr7VmU9tCXBY7lXkTMAzH3g/sqoFNL8K21zJ9DEbMhRGns9RI892Vf6Q73s1oHPyhvhoTaLFaqUymKEmneWDkBfyg5NvkppO4k1Z6NERcBqZS2NOaZDyNclgw37NHuCVlMj3PR6HTRsrUVLrsfK2ikFyblbTW1McSLA9GWNsX5cGmzp37UwN4LAZz8/2cWRDAEUtz76vbWLS5BWW1Mf7UKiJeC53JNE5DoYGWeJJ3Zo6m1LGrYY/Wmg3hGCPcTmwfss3ZjVsbubN+zy7OFU4blU47p+b5+WxpHkbCZPrv/0mOtYKEDmEp/xs2W4LbTv0zG9vr+f2KmzC0E1PFSMcLMewdOHQxvznhd8wdPolZ93yaDlcVX57yXTxWC+sjMV7tDFJgszI2YRBrDhNw2nhjdQ1xywZM00E6MB53rpu+SDdGoAFrcgsJ92SSeXv2ylCRFMRSOEINlNjfIKg3oXSa0b5iHht8IappBcy+DgLv37Dxni3N/Li+mcyG79YdLyJGshuLGSTpGAQHWGroMGGU08Hw/m7f4XSmi/1kn5vpAQ/v9oZ5sq2bzkSalkSm8setFKUYFPamCW3rpbq9D63TWNy15BZsJu55k88fczn/b+b3D2gsQgghxCdJa80db27j1gVPYvNtIBEcxYySE0iaUVYGn8NJMbn+PvI8Nv7xqW+S787Z47Hvt+ROa83K9pW8WPMiEwsncs7Qcz7yGOPpOHXBOgYHBh/wVqpCiF0kQSEO2KKnt7H8pVqu/stJWPaxJrtvwQLafvMb4tU1FFx7DUGPi+ee/w8pQ1E8eCjFo8fxbkMbpaWlXPmlL2EYBqvaV9GX6GNk7kgKXAV0xbq4e+3dPLr5UaKpKJBpaHPLnFs4oeKEnb8rZaZ4oeYF1nas5emtT++sUvDZfXxv6ve4eOTFez8BrXdWG8QTHXS1vUpj/QN0RbdQw2BarBOoo5I+PPSk3azWmaqKoaqGEx01JNImm1OFdGs/BfSRSsdJYc10eybMnJZqRnTayIlFGeNcQNDmJNg1hoVVM+j2AtpKnSPMFqeVFcZY8lJRet9IYrMajC8PsLi+O9OcymrhO3NH8sWZg1jdF+Xtpl4+VZWPDwOPw4J9P69KVEfivNUdIpw2ybVaWBGK8EJ7L53JXQ2E/BYDi1L0ptKcmOej2G4jnDapjsa4qDiPrw8q2q/f9X5qo3HshsJnsfBqV5AnW7tpjidZFcrENs9m4ZuBXEpzXKxtD3HPU4uwVfwDtzNC2lQkkn68qoTRRbO4btalvLjmLR7d/gu0EcFhlhN2OekpuXHn7yu2Wzkpz8+GcJTV/b8DwGcxGGVaCGqTTezaolWRWThjAFdVFHJWYYACu5VF3X0839pDUzzJplh8j+dkj67khmHDCATGMr+jhWU9YfKsDn49djgpDXfVtfFuVx/BRJKgRWFJ1DIr8SzrQq0YOoFXJSj35FHuK2NByzq8tjxOLp1LUlfwTNvbpNO9OM0gUd2HNd1L2nCTtA/BMEqxmkX0mRUkHXlgt2JosGiNshrE7buOydyYSbIvRryrDWuoEUuqBcPWi8vVh9fTh7IGiZqdJMwYNsPGnIo53Hzczfjsvo8VbyGEEOKT8M62Tu5eUMNFUyo4fUwx8ZTJK+tbOOmYIgIuSQoIcTSQBIU4YK/8cx0t1b1c/svZe9xuxuO03HwzvY//B1tZGSU33USsqoJ//+//w+ZwcNGPf05BZRUvvfQSixcv5pprrsGT6+HOVXdy97q7MbTCoi1Y7TaiqSiGMjh7yNlcPOJiIqkII7yVFKSiWPNGoYy9EyPtkXYWNS/CbXMzs3QmHpuHcNNi/rNtHh6Lh2AiwdZojOE9rQTMEEF/jAaPk42Moc0sZxvDCVsyayqdZpSADqIVnNv1Os50nJdzT2CbPbOFZGmqhWKzg26LD6UNbNograDVkkN4tz20A2aIknQX263FxNWeJYFF6V4q4kGiqzQ/vmA6Jx9ThN1qsKU1RHckyYSKwCfWcT1latb0RamLxWmMJamNxulKprm6spBpgUPX9XdVKMLinj4eaOpiWzRGuv8tp9xuIxwOE4u8AYaFmPeUPZaw2JXilBwnNdWv0B2rIVx0AT5XPvOOPQarUuTa+jt99y9vWBoMo4B5nUHe7AphKPh6ZTFXVxbSlzbxWw0WdPdR5LAx9n22E1vXF2VDXxQTeLuxi0d7e3ZVQ5hxrMk60rYytNH/+plJbJGtKCOMLb6JYx0JHj77j6TMFFbDusfVnJSZwqIsO2/b8d6rlCKZTmI1rDSHm3m78W3mN85ncfNioqkoDsPJUOepJFNWgqkm+hJx2lpOJuUagqHbyfM+T9q5Br1bMsbAoNBdSLGnmGJ35r/JRZM5rvy4I7rjsxBCCCGEOPJJgkIcsMdvWYrVbuHC70wGMh+muu+7j8577iXV3IzzyivQp51MMpng9XvuxOaNc963fkVBxTAWb3ybRfMeQOcFaSvooi3cQqk2mJsahiflxki6iViShPPtFA8dhl8laWxbhyW1jYjupM0oImna6VZ5FMYTHGefTNUpN2DsY03fG/+9kW8bM2lRH7zHujuVZmifZlifyayONKODaUqjmpQKY7fFIZmLtqQJq25aLIqyRB5uc88ESTsmD5EgrTRryrpI+qIMdseJ+W20WXLwpROkWjVmxMBhhKludROMZLaj+tGZo7jmpGEHKTpHps5Eih9urmeC180Qt4NHmjuJm5qF3SE08IWyfMqcdvJsVlyGwfJgmMdau4mkTQAsCu4eN4TTC/betvKT8s1XXuPF9rew6KWUxMdwzrCTeLPzFTYCygzjjG1muLeC4yumMa1kCrPLZu/sg/JxJdIJlrct54ktT/BSzUtYlIUKXwXBRJDuWDe5tkp6ko147G4+NfxTTCqatDMZke/KP2hrjIUQQgghhDiYJEEhDti/fjCfIRMKOPmLowHofuwxWm9/nIZKF7W5YZyVdeSO6EWnFcqucXgy699jcTdWSxJlTZPEhoM4aaw0UIE14cauY8Qt0GkN4CBODCcNVFKTHoNKudlkHUy3dc+u0Xm6g7OS88k1YuSpNLMLR5Jvz6GndR2XmCdi0YovbOzFayZwKYMAg3jWk8KlEwRSdqxWG+Nz3OTkuigq9jK+IodkbS+p9iiprhhmOImt2IMZSZLqjKLTGseQAPYKH4bHijY1CrCVeYkZUN0e5p1tnXRHErT0xninupPm3hgFXjszhubjsGaWUlTlu5k2OI8Sv5PBBXLV+v20xJPETZMq1969P8LpNBv7YgRTacZ4XRQ7Dn1pZ9rUdEcSFHgz49Na0xxuJmWmKPWUHrSExAcJJoK4rC5sho2+RB8Pb3yY5W3LKfWU8o3J3yDXmfuJj0EIIYQQQoiDQRIUWSzV0UGqsxPD5cJWUoJOJlEu117LJ7TWmL29hBctIpnUPPK8g2nHB5gw0UF0zWpa7nmW+GcLCOasIxmoA6XpChbiTvno0ylae0dgcflIO3tZ6pjI6+7jSBkGjrQJaOKWD17GUB5PYsGgFCvHWRw4G8M4DYP5Ok5TbifrfPvYfhJw6DjX1vXwlU+ftPMD5ECIJdPYLAaWD2kmKYQQQgghhBDZ7IMSFFIDfBgxTc2Cx7agTU1uqQczrUmnTfq64qSTafLKvCQ3rydR30gqGEJHIxQNz8Ndu4r46lWovAISw6eg84ohEadr63qCLXWYysQwTSw6jUZTEPAw4vIr6F6xnFDNVlKtbeieHhyxJFZT0+cphWOvp++u37OxaxVJhx3z2om8NCRMdewM2qPFNKpKOn05aAWgMAv3THic1dSAJZakISefqM1FkbYwrMDL6IoAAaeVcqeduGniMgyqXA4K7Pv+U/wa8NamNl58+S1M7cdnUaS8HcQsafoMKwWxfL575Vxs+2jkeSh9Un0khBBCCCGEECJbSAXFYWTZS9tZ9FQ1FitghLC4OrE6t2N1rMbm6sbqD9Br86OsEdyWXpwJTbyllEhHHhYiGL4OVE6CtAJrMoLNFcSwapShsTpTuAriGBZNrMtBT3U+dn8YZTFx5cVx5iZIRi0oBWbKQiLoxOqKYfcmMWyaVziTe9VVWMw0/kScykiQyngPLjpRmHgdORSngyS0gcuWz+mzzmBkif99t3z6uFJpE0MpDKlYEEIIIYQQQogjxhFfQaGUOhP4E2AB/qG1/s0AD+mguvGuX9Hq95AwHHSf5SDpSmFaIYGNFMcQ5Fi6ySeq3Hs91l0eJocu7CTpoIA+lWnKaNVJ3ESwaBOFRmkNpoFKQV6gg9JpdfSZOWhtoNIGhO1oI43WBg5LDGd+H52qkJjpIh2zsN1ZxvDOWv553EmU53nwOgb2T8c6wBUTQgghhBBCCCEOrsM+QaGUsgC3A3OBBmCJUuoZrfX6gR3ZwbO8opQlrsxuGQHdjcuMYcQVhgmWNPjiKUqiLVhSvTiSEUCTsNpJGU5SDjsxl52UYWFwtIVAuBYLELU6SFptKKVQKLRSpNCYStHlzKPeVYk7EccATJX5vtKZZpAJi5WExYo/HsWRSmHoNGOCNdwybSrHlB66HRSEEEIIIYQQQmSPwz5BAUwHtmqtqwGUUo8AFwBHTYLid/kT6XV2k7TFKPeUU14yErvDSdpMYyhj5zIJrTVJM4lFWTCUQSQVoSfeQ2+8F6fFydCcoQdlPMm0STxl4rFbPrElGkIIIYQQQgghxO6OhARFOVC/29cNwIzd76CU+hqZfooMGjTo0I3sIBk1Y8o+b7cYezZeVEpht9h3fu2xefDYPJR7973DxUdlsxgD3nRSCCGEEEIIIUR2ORI+he7rEv4enT211ndpradpracVFhYeomEJIYQQQgghhBDiYDkSEhQNQOVuX1cATQM0FiGEEEIIIYQQQnwCjoQExRJghFJqiFLKDlwKPDPAYxJCCCGEEEIIIcRBdNj3oNBap5RS1wEvk9lm9F9a63UDPCwhhBBCCCGEEEIcRId9ggJAa/0C8MJAj0MIIYQQQgghhBCfjCNhiYcQQgghhBBCCCGOcpKgEEIIIYQQQgghxICTBIUQQgghhBBCCCEGnCQohBBCCCGEEEIIMeAkQSGEEEIIIYQQQogBJwkKIYQQQgghhBBCDDhJUAghhBBCCCGEEGLASYJCCCGEEEIIIYQQA04SFEIIIYQQQgghhBhwkqAQQgghhBBCCCHEgJMEhRBCCCGEEEIIIQacJCiEEEIIIYQQQggx4CRBIYQQQgghhBBCiAEnCQohhBBCCCGEEEIMOElQCCGEEEIIIYQQYsBJgkIIIYQQQgghhBADThIUQgghhBBCCCGEGHCSoBBCCCGEEEIIIcSAkwSFEEIIIYQQQgghBpzSWg/0GA4qpVQ7UDvQ4/iICoCOgR6E+ERJjLODxDm7SLyzi8T76CbxzR4S6+whsT78VGmtC/f1jaMuQXEkU0ot1VpPG+hxiE+OxDg7SJyzi8Q7u0i8j24S3+whsc4eEusjiyzxEEIIIYQQQgghxICTBIUQQgghhBBCCCEGnCQoDi93DfQAxCdOYpwdJM7ZReKdXSTeRzeJb/aQWGcPifURRHpQCCGEEEIIIYQQYsBJBYUQQgghhBBCCCEGnCQohBBCCCGEEEIIMeAkQSGEEEIIIYQQQogBJwmKQ0wppQZ6DOKTpZQaPdBjEJ88pdT3lFKn9/9bjuujnFIqsNu/Jd5HMYnv0U/m6ewg83R2kXn66CEJikNEKXWBUupeYOJAj0V8cpRStwEvKKUGD/RYxCdDKXW6Uupl4EfA5QBaug0ftZRSpyilVgJ/U0r9BCTeRyuZp7ODzNNHP5mns4vM00cf60AP4GimlFJaa62UOhm4GUgCs5RStVrr7gEenjgIdsR4t5vygG7gNKXU/Vrr+AANTRxE/Zl4G3ADcCLwa8AOHKuUsgEpmQyPPkopL/ATMu/f7wL3KqXcWuvrB3Zk4mCRefroJ/N0dpB5OjvJPH10kgqKT8h7JsQa4AzgB8AMYMKADUwcNLvHWCll6b95EfA34DJgxECNTRw8O+KstU4AT2utT9Bav0DmBPdSrXVSTnqOPkopA/AC9cAKrXU98FXgs0qpUQM6OHFQyDx99JN5OjvIPJ2dZJ4+ekmC4hOglLoOeEIp9R2lVInWervWullr/RrQCpyolCof4GGKj2G3GH9bKVWmtU4rpezAmcCTwOvApUqpi5RShQM6WPGRvedYLtVaL+m/3aa1fhOoVkqdNbCjFAeLUupapdTFAFprE9BAIZkTILTW1WSO75v67y9rXI9QMk8f/WSezg4yT2cXmaezgyQoDjKl1KeAK4A/k7kCc71SatJud3kQGEnmCs3uj5MD6AjxnhhPBH6ilJran7lfqrXuALYA3wR+CUhsj0D7OJZ/qpTasTY9pZTKA2qB9AANURwkSimfUuoOMqXB9yqlrABa61ZgPfDt3e7+Y2CGUmqsXJE7Msk8ffSTeTo7yDydPWSezi6SoDj4ZgB/01q/DvycTNnoN3d8U2u9GlgCjOtv6vKj/tvlADpy7CvG1/R/7xyl1HwyjZmeIlNKGhyAMYqPb19x/hZkjletdRfgAk6GnaWG4giktQ4Bb2qtS4DngNt3+/ZNwCSl1NlKKUf/FZvnyKx1FkcmmaePfjJPZweZp7OEzNPZRQ7Ug2S3KyvVwOcBtNa1wPOARyl1/m53f5jMGql/AwXvebw4TH1IjHOUUrOAPwELtdaTtNaXAyWAbGd2BDnAY/kBYLpSytk/IYojzG7xfqb//98GPqeUGgGgte4DfgtcSuYq7E3ACUDzIR6qOEDvnVdlnj76HGCMZZ4+Qn3MY1nm6SPMB8Rb5uksIQmKj2G3hku7X1l5HIgopS7o/7oZeAMYozK8ZCbHNcAErfUP3vN4cRg5gBi/BswBHtRa/2i3H/EprfWKQzJY8ZF9lGO5/zYX8AhSPnpE2Ve8tdZhpZShtW4B/gr8Y7f7PAL8ikwZeCFwVn9ZqTi87XGOI/P0UelAYizz9JHrIx3L/bfJPH3k2We8ZZ7OHpKgOEBKqVn9mTm01undbt/xRthNpjnLNUoppbXuJdO4xdl/gMWAb2mtz9FaS2bvMPQRY+whE2NTKWXZUUaotY4d4uGL/fQxjmXHbidHT2ut/661Th7KsYsD90Hxfm/Zr9b6x8CQ/seUKKVmaK03Ajdqra/RWjce2tGLA6GUmq6UegD4tVJq/I747paYknn6CPcRYyzz9BHmYxzLMk8fgT4g3obM09lFEhQHQCl1BXAvmYZal/TftqNJy443QhfwMpks7l1KqTJgMpm91dFap7TWbYd67GL/fMwYp/rvl5YywsPbwYhz/33liswR4MPi3f+BxQsEdnvYLcAC4C3AueO+h3Tg4oD0n8TeSOaq2ouAFfg6mSaJux+vMk8foQ5CjGWePgIcrDi/577iMLUf8TZlns4ukqA4MI3AKWS2qPo/yJzI7MjkKqV+TiaTWwx8j8xWZQ8BPcBvDv1wxUcgMc4OEufs8mHxvpFMqfC4/q/PAr4B3AqM1Zmt6sRhrv8DZwNwpdb6QTK7M1QBO5f0yLF9ZJMYZweJc3bZz3jLPJ1FlCSa3p9S6kJgDLBaa/1c/8msobVOKqXeBl7XWv+s/75FwB+Bn2mtt+32M9xa68ihH73YHxLj7CBxzi4fN95KqTFASGtdPyBPQOy33WK9Smv9vFLKDcQBq9Y6rpR6FLhfa/2sHNtHJolxdpA4Z5ePG2+Zp49ukqDYB6VUIfB3II9MNvYm4Gqt9ZNKKbvWOqGUGgssBEbq9zRhUZkGLlI6eBiTGGcHiXN2OQjxtkg58JHhg2K9231swJtkrsptfs/j5dg+zEmMs4PEObschHjLPJ0FZInHvg0DFmit52it7yBTOraji3ei/+BYBzxGfxlZf6kR/feRN8rDn8Q4O0ics8vHjbec9Bw53jfWuxkFtGqtNyulfEqp6ZBpjCrH9hFBYpwdJM7Z5ePGW+bpLCAJin5KqcuVUif1lxgtA+7rv90CrCez3diODv87trv5KnCFUqobmKje02FWHF4kxtlB4pxdJN7Z4wBibe1/SD6ZLQivJFM1M77/BFdKRw9TEuPsIHHOLhJvcaCsH36Xo1f/CWsJmRIjE9gGXEVme7HWHWVESqnRQC7s7A6rlVJVwB+A+cDXtdZrB+RJiA8kMc4OEufsIvHOHh8x1js6+J8BfI7MuubLtNarD/kTEB9KYpwdJM7ZReItPo6svWrUf2BowAc0aq1PBa4FuoC73nP308l0jt2xdgqgF/iN1vpEOcE9PEmMs4PEObtIvLPHx4h1cf9tzwGf01p/WU5wD08S4+wgcc4uEm/xcWVdBUV/+dBNgEUp9QLgB9Kwc9u5bwJNSqkT9a4ta/qAGqXUTcBFSqmztdZ1wLsD8BTEh5AYZweJc3aReGePgxTrs7TWCwZi/OLDSYyzg8Q5u0i8xcGSVRUUSqkTyax9ygW2AjcDSeBk1d+ApT/jdxPw8/7HWIAvk8nu+YGT+09wxWFIYpwdJM7ZReKdPQ5irGXrucOUxDg7SJyzi8RbHEzZVkFhAv+ntb4fQCk1GRgC3AD8DZiqMs3SniRzQFWReY3uAO7TWi8fmGGLAyAxzg4S5+wi8c4eEuujn8Q4O0ics4vEWxw0WVVBQSaz92h/xg5gATBIa30PmXKkb+jMdkUVgKm1rtVab9Naf1sOnCOGxDg7SJyzi8Q7e0isj34S4+wgcc4uEm9x0GRVgkJrHdFax/WuPXTnAu39//4SMFop9RzwMJkDbUcXWnGEkBhnB4lzdpF4Zw+J9dFPYpwdJM7ZReItDqZsW+IB7FzzpIFi4Jn+m0PAT4BxQI3WuhF2rpcSRxiJcXaQOGcXiXf2kFgf/STG2UHinF0k3uJgyKoKit2YgA3oACb0Z/R+Rqbk6O0dB444okmMs4PEObtIvLOHxProJzHODhLn7CLxFh+bytbklVJqJrCw/7+7tdb/HOAhiYNMYpwdJM7ZReKdPSTWRz+JcXaQOGcXibf4uLI5QVEBfBG4VWsdH+jxiINPYpwdJM7ZReKdPSTWRz+JcXaQOGcXibf4uLI2QSGEEEIIIYQQQojDR7b2oBBCCCGEEEIIIcRhRBIUQgghhBBCCCGEGHCSoBBCCCGEEEIIIcSAkwSFEEIIIYQQQgghBpwkKIQQQghxyCml0kqplUqpdUqpVUqp7yqlPvC8RCk1WCn1+UM1RiGEEEIcWpKgEEIIIcRAiGqtJ2mtxwJzgbOBGz/kMYMBSVAIIYQQRynZZlQIIYQQh5xSqk9r7d3t66HAEqAAqALuBzz9375Oa71QKbUIGA3UAPcCfwZ+A5wEOIDbtdZ3HrInIYQQQoiDShIUQgghhDjk3pug6L+tGxgFhABTax1TSo0AHtZaT1NKnQR8X2t9bv/9vwYUaa1/oZRyAAuAz2itaw7lcxFCCCHEwWEd6AEIIYQQQvRT/f+3AX9RSk0C0sDI97n/6cAEpdSn+78OACPIVFgIIYQQ4ggjCQohhBBCDLj+JR5poI1ML4pWYCKZflmx93sY8A2t9cuHZJBCCCGE+ERJk0whhBBCDCilVCFwB/AXnVl7GgCatdYm8EXA0n/XEODb7aEvA9copWz9P2ekUsqDEEIIIY5IUkEhhBBCiIHgUkqtJLOcI0WmKeat/d/7K/AfpdRngNeBcP/tq4GUUmoVcA/wJzI7eyxXSimgHbjw0AxfCCGEEAebNMkUQgghhBBCCCHEgJMlHkIIIYQQQgghhBhwkqAQQgghhBBCCCHEgJMEhRBCCCGEEEIIIQacJCiEEEIIIYQQQggx4CRBIYQQQgghhBBCiAEnCQohhBBCCCGEEEIMOElQCCGEEEIIIYQQYsBJgkIIIYQQQgghhBAD7v8D+/EfS1c/6ocAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1296x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "initial_date = '2020-12-31'\n",
    "initial_amount = 500\n",
    "# bucket_df store all the Cryptopar coins with the cummulate crypto value by date\n",
    "bucket_df = yf.download(CryptoPar[0], start=initial_date)\n",
    "bucket_df = bucket_df.drop(['Open', 'High', 'Low', 'Adj Close', 'Volume'] , axis=1)\n",
    "for pair in CryptoPar: \n",
    "    print(pair)\n",
    "    df = yf.download(pair, start=initial_date)\n",
    "    df = df.drop(['Open', 'High', 'Low', 'Adj Close', 'Volume'] , axis=1)\n",
    "    buydates = pd.date_range(start=df.index[0], end=df.index[-1], freq='1M')\n",
    "    buyprices = df[df.index.isin(buydates)].Close\n",
    "    crypto_amt = initial_amount / buyprices\n",
    "    crypto_amt_sum = crypto_amt.cumsum()\n",
    "    crypto_amt_sum.name = pair\n",
    "    bucket_df.drop(columns='Close', inplace=True)\n",
    "    bucket_df = pd.concat([crypto_amt_sum, bucket_df], axis=1).ffill()\n",
    "    bucket_df = pd.concat([bucket_df, df], axis=1)\n",
    "    bucket_df[pair] = bucket_df[pair] * bucket_df['Close']\n",
    "\n",
    "bucket_df.drop(columns='Close', inplace=True)\n",
    "bucket_df.plot(figsize=(18,12))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Surprise, Surprice\n",
    "\n",
    "Let's look at Solana or Doge-coin! \n",
    "\n",
    "\n",
    "but most of the coins would have caused losses ..."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.13 ('base')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.13"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "6575615a8e4bf2bce2073070fa9afe345e3f6bb4481a529180704a6478cdcccb"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}