21_SimpleStockSignalsRSI.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Simple Stock Signals RSI"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "This simple tutorial, we will add buy and sell signals for RSI."
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "# fix_yahoo_finance is used to fetch data \n",
        "import fix_yahoo_finance as yf\n",
        "yf.pdr_override()"
      ],
      "outputs": [],
      "execution_count": 1,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# input\n",
        "symbol = 'AMD'\n",
        "start = '2018-01-01'\n",
        "end = '2018-12-31'\n",
        "\n",
        "# Read data \n",
        "df = yf.download(symbol,start,end)\n",
        "\n",
        "# View Columns\n",
        "df.head()"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[*********************100%***********************]  1 of 1 downloaded\n"
          ]
        },
        {
          "output_type": "execute_result",
          "execution_count": 2,
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2018-01-02</th>\n",
              "      <td>10.42</td>\n",
              "      <td>11.02</td>\n",
              "      <td>10.34</td>\n",
              "      <td>10.98</td>\n",
              "      <td>10.98</td>\n",
              "      <td>44146300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-03</th>\n",
              "      <td>11.61</td>\n",
              "      <td>12.14</td>\n",
              "      <td>11.36</td>\n",
              "      <td>11.55</td>\n",
              "      <td>11.55</td>\n",
              "      <td>154066700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-04</th>\n",
              "      <td>12.10</td>\n",
              "      <td>12.43</td>\n",
              "      <td>11.97</td>\n",
              "      <td>12.12</td>\n",
              "      <td>12.12</td>\n",
              "      <td>109503000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-05</th>\n",
              "      <td>12.19</td>\n",
              "      <td>12.22</td>\n",
              "      <td>11.66</td>\n",
              "      <td>11.88</td>\n",
              "      <td>11.88</td>\n",
              "      <td>63808900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-08</th>\n",
              "      <td>12.01</td>\n",
              "      <td>12.30</td>\n",
              "      <td>11.85</td>\n",
              "      <td>12.28</td>\n",
              "      <td>12.28</td>\n",
              "      <td>63346000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             Open   High    Low  Close  Adj Close     Volume\n",
              "Date                                                        \n",
              "2018-01-02  10.42  11.02  10.34  10.98      10.98   44146300\n",
              "2018-01-03  11.61  12.14  11.36  11.55      11.55  154066700\n",
              "2018-01-04  12.10  12.43  11.97  12.12      12.12  109503000\n",
              "2018-01-05  12.19  12.22  11.66  11.88      11.88   63808900\n",
              "2018-01-08  12.01  12.30  11.85  12.28      12.28   63346000"
            ]
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      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 3,
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>251.000000</td>\n",
              "      <td>251.000000</td>\n",
              "      <td>251.000000</td>\n",
              "      <td>251.000000</td>\n",
              "      <td>251.000000</td>\n",
              "      <td>2.510000e+02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>17.209681</td>\n",
              "      <td>17.667610</td>\n",
              "      <td>16.729880</td>\n",
              "      <td>17.214502</td>\n",
              "      <td>17.214502</td>\n",
              "      <td>8.460868e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>6.202684</td>\n",
              "      <td>6.430476</td>\n",
              "      <td>5.912749</td>\n",
              "      <td>6.182515</td>\n",
              "      <td>6.182515</td>\n",
              "      <td>4.636185e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>9.080000</td>\n",
              "      <td>9.770000</td>\n",
              "      <td>9.040000</td>\n",
              "      <td>9.530000</td>\n",
              "      <td>9.530000</td>\n",
              "      <td>2.887510e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>12.005000</td>\n",
              "      <td>12.185000</td>\n",
              "      <td>11.710000</td>\n",
              "      <td>11.955000</td>\n",
              "      <td>11.955000</td>\n",
              "      <td>4.869910e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>16.180000</td>\n",
              "      <td>16.530001</td>\n",
              "      <td>15.780000</td>\n",
              "      <td>16.270000</td>\n",
              "      <td>16.270000</td>\n",
              "      <td>7.434780e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>20.150001</td>\n",
              "      <td>20.895001</td>\n",
              "      <td>19.574999</td>\n",
              "      <td>20.149999</td>\n",
              "      <td>20.149999</td>\n",
              "      <td>1.071805e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>33.180000</td>\n",
              "      <td>34.139999</td>\n",
              "      <td>32.189999</td>\n",
              "      <td>32.720001</td>\n",
              "      <td>32.720001</td>\n",
              "      <td>3.250584e+08</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             Open        High         Low       Close   Adj Close  \\\n",
              "count  251.000000  251.000000  251.000000  251.000000  251.000000   \n",
              "mean    17.209681   17.667610   16.729880   17.214502   17.214502   \n",
              "std      6.202684    6.430476    5.912749    6.182515    6.182515   \n",
              "min      9.080000    9.770000    9.040000    9.530000    9.530000   \n",
              "25%     12.005000   12.185000   11.710000   11.955000   11.955000   \n",
              "50%     16.180000   16.530001   15.780000   16.270000   16.270000   \n",
              "75%     20.150001   20.895001   19.574999   20.149999   20.149999   \n",
              "max     33.180000   34.139999   32.189999   32.720001   32.720001   \n",
              "\n",
              "             Volume  \n",
              "count  2.510000e+02  \n",
              "mean   8.460868e+07  \n",
              "std    4.636185e+07  \n",
              "min    2.887510e+07  \n",
              "25%    4.869910e+07  \n",
              "50%    7.434780e+07  \n",
              "75%    1.071805e+08  \n",
              "max    3.250584e+08  "
            ]
          },
          "metadata": {}
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      ],
      "execution_count": 3,
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        "collapsed": false,
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        "inputHidden": false
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    },
    {
      "cell_type": "code",
      "source": [
        "import talib as ta"
      ],
      "outputs": [],
      "execution_count": 4,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df['RSI'] = ta.RSI(df['Adj Close'], timeperiod=14)"
      ],
      "outputs": [],
      "execution_count": 5,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.dropna()\n",
        "df.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 6,
          "data": {
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              "      <th></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>RSI</th>\n",
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              "      <th>Date</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2018-01-23</th>\n",
              "      <td>12.82</td>\n",
              "      <td>13.00</td>\n",
              "      <td>12.76</td>\n",
              "      <td>12.94</td>\n",
              "      <td>12.94</td>\n",
              "      <td>46417200</td>\n",
              "      <td>75.654450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-24</th>\n",
              "      <td>13.02</td>\n",
              "      <td>13.05</td>\n",
              "      <td>12.60</td>\n",
              "      <td>12.71</td>\n",
              "      <td>12.71</td>\n",
              "      <td>41956400</td>\n",
              "      <td>71.047655</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-25</th>\n",
              "      <td>12.78</td>\n",
              "      <td>12.94</td>\n",
              "      <td>12.32</td>\n",
              "      <td>12.41</td>\n",
              "      <td>12.41</td>\n",
              "      <td>42966600</td>\n",
              "      <td>65.449453</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-26</th>\n",
              "      <td>12.70</td>\n",
              "      <td>12.95</td>\n",
              "      <td>12.62</td>\n",
              "      <td>12.95</td>\n",
              "      <td>12.95</td>\n",
              "      <td>44239000</td>\n",
              "      <td>70.027488</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-29</th>\n",
              "      <td>13.13</td>\n",
              "      <td>13.47</td>\n",
              "      <td>13.05</td>\n",
              "      <td>13.32</td>\n",
              "      <td>13.32</td>\n",
              "      <td>66645400</td>\n",
              "      <td>72.696974</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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            ],
            "text/plain": [
              "             Open   High    Low  Close  Adj Close    Volume        RSI\n",
              "Date                                                                  \n",
              "2018-01-23  12.82  13.00  12.76  12.94      12.94  46417200  75.654450\n",
              "2018-01-24  13.02  13.05  12.60  12.71      12.71  41956400  71.047655\n",
              "2018-01-25  12.78  12.94  12.32  12.41      12.41  42966600  65.449453\n",
              "2018-01-26  12.70  12.95  12.62  12.95      12.95  44239000  70.027488\n",
              "2018-01-29  13.13  13.47  13.05  13.32      13.32  66645400  72.696974"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 6,
      "metadata": {
        "collapsed": false,
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      }
    },
    {
      "cell_type": "code",
      "source": [
        "df['Positions'] = 0\n",
        "\n",
        "df['Positions'] = np.select([df['RSI']<30, df['RSI']>70], [1,-1], default=0)\n",
        "df['Signals'] = df['Positions'].diff()"
      ],
      "outputs": [],
      "execution_count": 7,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.dropna()\n",
        "df.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 8,
          "data": {
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              "      <th></th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
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              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "    <tr>\n",
              "      <th>2018-01-24</th>\n",
              "      <td>13.02</td>\n",
              "      <td>13.05</td>\n",
              "      <td>12.60</td>\n",
              "      <td>12.71</td>\n",
              "      <td>12.71</td>\n",
              "      <td>41956400</td>\n",
              "      <td>71.047655</td>\n",
              "      <td>-1</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-25</th>\n",
              "      <td>12.78</td>\n",
              "      <td>12.94</td>\n",
              "      <td>12.32</td>\n",
              "      <td>12.41</td>\n",
              "      <td>12.41</td>\n",
              "      <td>42966600</td>\n",
              "      <td>65.449453</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-26</th>\n",
              "      <td>12.70</td>\n",
              "      <td>12.95</td>\n",
              "      <td>12.62</td>\n",
              "      <td>12.95</td>\n",
              "      <td>12.95</td>\n",
              "      <td>44239000</td>\n",
              "      <td>70.027488</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-29</th>\n",
              "      <td>13.13</td>\n",
              "      <td>13.47</td>\n",
              "      <td>13.05</td>\n",
              "      <td>13.32</td>\n",
              "      <td>13.32</td>\n",
              "      <td>66645400</td>\n",
              "      <td>72.696974</td>\n",
              "      <td>-1</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-30</th>\n",
              "      <td>13.12</td>\n",
              "      <td>13.27</td>\n",
              "      <td>12.69</td>\n",
              "      <td>12.87</td>\n",
              "      <td>12.87</td>\n",
              "      <td>91236400</td>\n",
              "      <td>65.102501</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             Open   High    Low  Close  Adj Close    Volume        RSI  \\\n",
              "Date                                                                     \n",
              "2018-01-24  13.02  13.05  12.60  12.71      12.71  41956400  71.047655   \n",
              "2018-01-25  12.78  12.94  12.32  12.41      12.41  42966600  65.449453   \n",
              "2018-01-26  12.70  12.95  12.62  12.95      12.95  44239000  70.027488   \n",
              "2018-01-29  13.13  13.47  13.05  13.32      13.32  66645400  72.696974   \n",
              "2018-01-30  13.12  13.27  12.69  12.87      12.87  91236400  65.102501   \n",
              "\n",
              "            Positions  Signals  \n",
              "Date                            \n",
              "2018-01-24         -1      0.0  \n",
              "2018-01-25          0      1.0  \n",
              "2018-01-26         -1     -1.0  \n",
              "2018-01-29         -1      0.0  \n",
              "2018-01-30          0      1.0  "
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 8,
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    {
      "cell_type": "code",
      "source": [
        "buys = df.ix[df['Signals'] == 1]\n",
        "sells = df.ix[df['Signals'] == -1]"
      ],
      "outputs": [],
      "execution_count": 9,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(16,8))\n",
        "plt.plot(df.index, df['Adj Close'], label='Closing')\n",
        "plt.plot(sells.index, df.ix[sells.index]['Adj Close'],'go', markersize=10, color='g', label='Long')\n",
        "plt.plot(buys.index, df.ix[buys.index]['Adj Close'], 'ro', markersize=10, color='r', label='Short')\n",
        "plt.title(symbol + ' signals')\n",
        "plt.ylabel('Price')\n",
        "plt.xlabel('Date')\n",
        "plt.legend(loc='best')\n",
        "plt.show()"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1152x576 with 1 Axes>"
            ],
            "image/png": [
              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\n"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 10,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## RSI Subplots"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "fig = plt.figure(figsize=(14,10))\n",
        "ax1 = plt.subplot(2, 1, 1)\n",
        "ax1.plot(df['Adj Close'])\n",
        "ax1.plot(sells.index, df.ix[sells.index]['Adj Close'],'go', markersize=10, color='g', label='Long')\n",
        "ax1.plot(buys.index, df.ix[buys.index]['Adj Close'], 'ro', markersize=10, color='r', label='Short')\n",
        "ax1.set_title('Stock '+ symbol +' Closing Price')\n",
        "ax1.set_ylabel('Price')\n",
        "ax1.grid()\n",
        "ax1.legend()\n",
        "\n",
        "ax2 = plt.subplot(2, 1, 2)\n",
        "ax2.plot(df['RSI'], label='Relative Strengths Index')\n",
        "ax2.text(s='Overbought', x=df.RSI.index[30], y=70, fontsize=14)\n",
        "ax2.text(s='Oversold', x=df.RSI.index[30], y=30, fontsize=14)\n",
        "ax2.plot(sells.index, df.ix[sells.index]['RSI'],'go', markersize=10, color='g', label='Long')\n",
        "ax2.plot(buys.index, df.ix[buys.index]['RSI'], 'ro', markersize=10, color='r', label='Short')\n",
        "ax2.axhline(y=70, color='red')\n",
        "ax2.axhline(y=30, color='red')\n",
        "ax2.grid()\n",
        "ax2.set_ylabel('RSI')\n",
        "ax2.set_xlabel('Date')\n",
        "ax2.legend()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 11,
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x194335ffac8>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1008x720 with 2 Axes>"
            ],
            "image/png": [
              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ee5k2bVqN4+qqDj3++OMkJiYyYsQIRo0axXXXXUdiYmKNY84991zuvPNOJk6cyKRJk7j77rsZN24cW7duZeLEiYwdO5YnnniCn/3sZ4SEhLBs2TIeeughxowZw9ixY1m3bl2LvgYaAiciIiLtXqZvyFv68VLAWwHqFh1a7/E3TziHpz7cw4vrDvC72ckNXnvJxkP0jurPm9+6C8f33gA/WvjaqCiuGHxFE56BSPuwatWqWtvuu+++6p8XLlxY53m5ubnEx9duLBISEsLvf//76iF0pzpw4ED1zw888AAPPPBAjf2XXXYZl112Wa3zxo4dy+rVq+t7Cs2mCpCIiIi0e5kF3qYHVQlQVkEZiQ0kQLERTq5K7sn72zJwNdAMIf14CZ/syuKW8/riDHLAnDngrD2srgank6C5dzT9SYh0UJdccgmjR49mwIABbR1Ki1ACJCIiIu3eyQqQdyhcdmE5iac0QKjLxcO7U1hWyRcH8uo9ZunnhzHAzRPP8W548EG/EiDu19wf6Tw+/PBDXn755bYOo8UoARIREZF2r6rt9ZHjpbjcHvJKKhqsAAFMdeTzxId/Y/zo/uBwQEwMzJ8PaWkAuNweln5xmBlDu9E7Ltx7UlISLFsGERG1EiGXI4jykDDv/iTN/RHpqJQAiYiISLtXNQSusLyS/TnFWEuDc4BYsYKI887l5q//TWhpMVjrnduzaBEkJ8OKFXy4I5OconJuO/+cmudecQWkpMC8ed6kyZc8rZp2Hfc98qJ3v4h0WEqAREREpN3LLDjZ9ODLQ8eBBhKgtDSYPRtKSgh2V9bc53JBSQnMns1H766jd1w404Z0q32NpCRYuBDy88Hthvx8Vn7/f9gc3KXWodZaXtpwkHfT/GwhJyJtSgmQiIiItGtlLjf5pS7OPcebfGw5eAKg/iFwCxZ4E50G2AoXY5Y9z60T+xJURyvtWtLS+NaLv+OTX30De8pwuvJdu/nvZSk8+vY2/nOw4ccUaaq0vDTmL59PzG9icPzCQcxvYpi/fD5peWltHVqHpgRIRERE2rWq4W/j+/kSoKoKUEw9TRAWL240ATKVLr65/RNumtC38QBWrIDkZEa+/xrRFaUY33A6u2gRNnkM2a+9zcDESIoqoLKBjnMiTbFizwqSn0lm0ZZFFFYUYrEUVhSyaMsikp9JZsWeFWd87aioqBaMtONRAiQiIiLtWlUHuKE9ookMCWJvdhEACVEhdZ9QVOTXdSNdpfUnUVVOGU7nqKw5nM64XIRVlLHovd/xg3MMFsgr0TA4ab60vDRmvz6bElcJLk/NZN7lcVHiKmH267NVCTpDSoBERESkXauqAPWIDaNPlwishbgIJ6HBQXWf4Oen255IP47zYzhdsLuSc994AYCcQiVA0nwL1i/A5W74787ldvHUhqda7DEPHjzIrFmzSE5OZtasWRw6dAiAO++8k/vuu4/JkyczcOBAli1bBoDH42H+/PmMHDmSq6++miuvvLJ6X3unBEhERETataoEqHt0GL27eNtVN9gBzo/FTN1BwQTNvb3xB/djOB0uF72XvwFATlF549cUacTilMW1Kj+nc3lcvJTyUos95ve//33mzp1LSkoKt912G/fdd1/1voyMDNauXct7773Hww8/DMCbb77JgQMH2Lp1K4sWLWL9+vUtFkugKQESERGRdi2rsJzQYAcx4cH08SVADa4B5MdipkGhIZgHHmj8wf0cThdU7D1OCZC0hKIK//7u/D3OH+vXr+db3/oWALfffjtr166t3nfdddfhcDgYMWIEmZmZAKxdu5Ybb7wRh8NBjx49mDFjRovFEmhKgERERKRdyywoo3tMGMaY6gSoW3QDc3caWMwUp9O73d/FTP2dLB4dDSgBkpYRFeLf352/x50JY052RwwNPfmBg7W2xveOSAmQiIiItGveBMj7BqxPlwigkQoQ1LuYKfPmebf7u5ipH8PpcDphzhycDsgp0hwgab45yXNwOhr+u3M6nNye7McwTj9NnjyZpUuXArBkyRKmTJnS4PFTpkzhjTfewOPxkJmZyapVq1oslkBTAiQiIiLtWlZBeXW3tt5xfswBqlLHYqYsXOhf5aeKH8PpcDoxDzxATIghp1AVIGm+By94EGdQIwlQkJP7z7//jK5fUlJCnz59qr+efPJJ/vznP/P888+TnJzMSy+9xJ/+9KcGr3HDDTfQp08fRo0axXe/+10mTZpEbGzsGcXT2oLbOgARERGRhmQWlDF9aDcAhnSP5sJBXbkgqWvrPHjVcLrZs73NEE5tiOB0er98w+liQneTrSFw0gKS4pNYduMyZr8+G5fbVaMhgtPhxBnkZNmNy0iKb0IyfwqPp+71qlauXFlr2wsvvFDj9yLfvDiHw8Ef/vAHoqKiyM3NZeLEiYwePfqM4mltqgCJiIhIu1VUXklxhbt6CFx4SBBL7j6fkb1a8ZNmP4fTxYQYDYGTFnPF4CtIuSeFeePnERMag8M4iAmNYd74eaTck8IVg/0cxhlAV199NWPHjuWiiy7i0UcfpUePHm0dkl8CVgEyxoQBq4FQ3+Mss9b+3BgzAFgKxANbgNuttfrXQkRERGqpboHd2IKlgVY1nG7hwnoPiQ01pOarAiQtJyk+iYVXLmThlfX/3bWljjTv51SBrACVAzOttWOAscDlxpjzgd8BT1lrBwPHgW8HMAYRERHpwDYdyAOgW4wfc37aWEyIIa+4Ao+n43bHEukMApYAWa+q5uRO35cFZgJVy8S+CFwXqBhERESk43ov5Sg/eWsb486JY3y/Lm0dTqNiQwxuj+V4iQa2iLRnJpA9vI0xQcBmYBDwF+B/gQ3W2kG+/X2BFdbaUXWcOw+YB9C9e/fxVW35zgZFRUVE+buugHRoutedl+5956V73zL2HHfz641lDO7i4P7xYYQHm8ZPamOf7i/i+V2Gxy8Mp0+0pll3Jk357z42NpZBgwYFOKKz3969e8nPz6+xbcaMGZuttRMaOzegXeCstW5grDEmDngLGF7XYfWc+yzwLMCECRPs9OnTAxVmq1u1ahVn0/OR+uled166952X7n3LWP3uDkKCD/Lmjy4hKrRjNK1Nzf0YKGPA8GQuHJTQ1uFIK2rKf/epqalE+xbObVRaGixYAIsXQ1GRd2HeOXO87dmb0s79LBQWFsa4cePO6NxW+XjCWnsCWAWcD8QZY6r+JesDHG2NGERERKTjWJeWw3n94ztM8gPeJggAOWqFLS1hxQpIToZFi6CwEKz1fl+0yLt9xYozvvQTTzzByJEjSU5OZuzYsWzcuJH+/fuTk5Nzxtf86quveP/998/4/NYUsATIGJPoq/xgjAkHLgZSgU+A2b7D7gDeCVQMIiIi0vHkFpWz81hh663100JiQqoSIM0BkmZKS/OuPVVSUnPtKfD+XlLi3Z+W1uRLr1+/nvfee48tW7aQkpLCRx99RN++fZsVbmVlZYdKgAL5sUpP4EXfPCAH8Jq19j1jzA5gqTHmceBL4O8BjEFEREQ6mA37vJ3fOloCFOkEZ5BRBUiab8GC2onP6VwueOqpBluz1yUjI4OEhARCQ72dFRMSTg7XfPrpp3n33XdxuVy8/vrrDBs2jLy8PO666y727dtHREQEzz77LMnJyTz22GMcPXqUAwcOkJCQwNq1ayktLWXt2rU88sgj3HzzzU1+2q0lkF3gUqy146y1ydbaUdbaX/q277PWTrTWDrLW3mit1b8SIiIiUm39vhyiQoNJ7t2Ki522AGMMXSNDySnUWxtppsWL/UuAXnqpyZe+9NJLOXz4MEOGDGH+/Pl8+umn1fsSEhLYsmUL9957L3/4wx8A+PnPf864ceNISUnh17/+NXPnzq0+fvPmzbzzzju8/PLL/PKXv+Tmm2/mq6++atfJD7TSHCARERERf61Ly2XigHiCgzre25SE6BBVgKT5iooaP6Ypx50iKiqKzZs38+yzz5KYmMjNN9/MCy+8AMA3v/lNAMaPH8+BAwcAWLt2LbfffjsAM2fOJDc3t7r72rXXXkt4eHiTY2hrHWdmoYiIiJz1juWXsS+7mG9NPKetQzkjCVGhmgMkzRcV5W144M9xZyAoKIjp06czffp0Ro8ezYsvvghQPSwuKCiIyspKAOpaMscY73y3yMjIM3r8ttbxPloRERGRs9b6fd4uVOcP7Fjzf6p4EyBVgKSZ5swBp7PhY5xO8FVmmmLXrl3s2bOn+vevvvqKfv361Xv81KlTWbJkCeBt952QkEBMTEyt46Kjoyn0J2lrB5QAiYiISLuxbm8useFORvSs/QarI+gXH8GxgjKyCsraOhTpyB580L8E6P77m3zpoqIi7rjjDkaMGEFycjI7duzgscceq/f4xx57jE2bNpGcnMzDDz9cXS063YwZM9ixYwdjx47l1VdfbXJcrUlD4ERERKTdWL8vlwsGdsXhMG0dyhm5KrknCz7czTtfHeU7Uwe2dTjSUSUlwbJl3lbXLlfNhghOp/dr2bIzWgx1/PjxrFu3rtb2qjk/ABMmTGDVqlUAxMfH8847tVetOT1pio+P54svvmhyPG1BFSARERFpFw7nlZB+vJTJgzrm8DeAgYlRjOkbx5tfHmnrUKSju+IKSEmBefMgJgYcDu/3efO826+4oq0j7LCUAImIiEi7sC7NO//ngg46/6fKN8f1JjWjgJ3HCto6FOnokpK86/zk54Pb7f2+cOEZVX7kJCVAIiIi0mpW787m8/15de5bl5ZLQlQog7qdWWer9uKaMb0Idhje2qIqkNStrs5q4r/mvn5KgERERKRV5Je6+N6SLfz3sq9rvYGx1rIuLZfJSV2rW+x2VPGRIUwf2o23vjyC26M3ulJTWFgYubm5SoLOkLWW3NxcwsLCzvgaaoIgIiIireKl9QcoLK+ksLyS3ZlFDO0RXb0vLbuI7MJyJid17OFvVa4b14uPUjPZdCCPSR18SJ+0rD59+pCenk52dnZbh9JhhYWF0adPnzM+XwmQiIiIBFxJRSX/+OwAY/vG8XX6CT7YdqxGArQ+LReAyUkJbRVii5oxtBthTgfvb80IeAJUUekhNaOAMX3jAvo40jKcTicDBgxo6zA6NQ2BExERkYBb+vlh8oor+NlVw5nQrwsfbD9WY/+6tFx6x4XTNz68jSJsWZGhwUwf0o0V247hCfAwuLe/PMI3/vIZ+7KLAvo4ImcLJUAiIiISUNZanl+3n4kD4pnQP57LRvYgNaOAg7nFAHg81rv+z1kw/+dUVyb3JKuwnM2Hjgf0cQ7meV/HDfvqbi4hIjUpARIREZGA2p1ZxOG8Ur45rjcAl43sAcAH27xVoNRjBZwocZ0183+qzBzWjZBgB8tTMgL6OBknygDYuD83oI8jcrZQAiQiIiIB9fHOTABmDOsGQN/4CEb1juHdlKNYa6vn/1xwliVAUaHBTB+SyIptGQEdBnc0vxSAjfvy1FlMxA9KgERERCSgVqZmMbp3LN1jTratvXXiOWw7UsD6fbmsT8tlYEIkPWPPjvk/p7p2bC8yC8r5MDUzYI9xLL+MIIfhWEEZ6cdLA/Y4ImcLJUAiIiISMHnFFWw5dJyZvupPlRvO7UNCVCgLV+5l4/48zj/Lqj9VLh/Zg4EJkfzpoz0Bqc5Ya8nIL2PKIG/3vA37NAxOpDFKgERERCRgVu3KwmNh1vCaCVCYM4i7pvRnXVouReWVZ938nyrBQQ5+MGsQOzIK+M+Olq8C5RVXUF7pYeqQRLpEOPl8vxohiDRGCZCIiIgEzMc7s+gWHcqoXrG19s05vx/Rod4lCc8/ixcLvSa5V8CqQBn53gYIvePCOK9/PBuVAIk0SgmQiIiIBITL7WH1rmxmDuuGw1G7vXVMmJMfXTKEb4ztRUJUaBtE2DpOrQIt3nCw3uOyCsooc7mbdO2qBKhHbDiTBnblUF4JR09oHpBIQ5QAiYiISEB8cSCPwvLKWvN/TvXtKQP40y3jWjGqtnHd2N5MH5rIr5ansvNYQa39ZS43Fz/5KYvW7GvSdTN8HeB6xYZx0WDvPKCVO7OaH7DIWUwJkIiIiATEytQsQoIdXOiboN+ZGWP4w41jiAlzct8rX1JaUbPS8/n+PArKKtmXU9yk62bklxHsMCREhTLYHvvFAAAgAElEQVS4WxQDEiL59/ZjLRm6yFlHCZCIiIgExMc7s7hgYFciffN8OruEqFCevGkMuzOLeHz5jhr71uzJBiC7sLxJ18w4UUr3mDAcDoMxhktHdmd9Wi75pa4Wi1vkbKMESERERFrcvuwi9ucU1+r+1tlNHZLIvKkDWbLxEB9sO1mpWb07B2h6AnQ0v4xecSfXV7psZA8qPZaVOwO37pBIR6cESERERFpc1TyUhub/dFY/vnQoo3vH8tAbKRw9UUpmQRm7MgtxBpkmJ0DH8stqLCA7tk8c3aJD+fc2JUAi9VECJCIiIi3u49QshvWIpk+XiLYOpd0JCXbw51vH4XJ7+NGrX7Fq18lkMbe4Apfb49d1PB7rTYBOqQA5HN5hcJ/uzm5yRzmRzkIJkIiIiLSo/FIXXxzIU/WnAQMSIvnVN0bx+f48Hl+eSkJUKBcNTgQgp8i/KlBeSQUVbg89Y8JqbL94eHdKXW62HDze4nGLnA2UAImIiEiLWr07m0qP1fyfRnzz3N58Y2wvCssqmTo4ge6+RMbfYXAZJ7xrAPWMC6+xvarqlu1nIiXS2agti4iIiLSolTuz6BLhZGzfLm0dSrtmjOHx60ZRUuHmlonnEBLs/Vw6q6Bm4rL5YB6f7z9O7y7h9OkSTp+4cBKiQjlavQZQzQQoLsIJwIkSdYITqYsSIBEREWkxbo/lk11ZzBzajSCHaetw2r3oMCfPzZ0AwNET3oTm9MrNY//awdYj+TW2hQQ7iAwJAqBHbM0hcHHhSoBEGqIESERERFrMl4eOc6LExazh3ds6lA4nISoUqFkBKq90s/NYAXdO7s9tk84h/Xgp6cdLfN9LiQ4LJiEqpMZ1goMcRIcFc7ykolXjF+kolACJiIhIi/l4ZxbBDsNFQxLaOpQOJyTYQZcIJ9lFZdXbUjMKcbktEwfEM7h7NIO7R/t1rbgIpxZDFamHmiCIiIhIi1mZmsXEAfHEhDnbOpQOqVt0WI0KUEr6CQCS+8Q26TpdIkJUARKphxIgERERaRGH80rYlVmo9tfNkBgdWmMO0NeH8+kaGULv0zq9NSY23MlxzQESqZMSIBEREWkRK3d6F/TU/J8z1y06tEYFaOuREyT3icWYpjWU6BIRQr4qQCJ1UgIkIiIiLeLjnVkMTIhkQEJkW4fSYSVGh5JdWI61luLySvZmFZHcJ67J14mLUAVIpD5KgERERKTZissr2ZCWq8VPmykxOpQKt4eC0kq2HcnHY2FM36bN/wGIiwihoMyF22MDEKVIx6YESERERJpt7d4cKtweZg7T8Lfm6BbjXdMnq7CMlHTv2j9nUgHqEuHEWihQJziRWpQAiYiISKM8jVQSPk7NJDosmAn9u7RSRGenRN9aQNmF5XydfoLeceHV6wM1RVyEtwufOsGJ1BawBMgY09cY84kxJtUYs90Y80Pf9seMMUeMMV/5vq4MVAwiIiLSfH9blcYFv/2Y7Ue9FYmsgjLe3JJePbzK47Gs3JnNtCGJOIP02WpzdIvxJjvr0nL5KDWTSQPjz+g6cRHexVFPqAIkUksgF0KtBB601m4xxkQDm40xH/r2PWWt/UMAH1tERERaQF5xBQtX7qG4ws23ntvI92cM4i+r9nKixEVWYTn3TEvi3ZSj5BSVc7G6vzVbYrQ3AfrLqr10iQjh4cuHndF14sK9FaATDVSACspcbNyXx5DuUfTrqsYV0nkELAGy1mYAGb6fC40xqUDvQD2eiIiItLzn1uyjxOXmH3dO4H/e2c4T76eS3CeWMX1CWPCfXfSKC+eRN7cyoV8Xrkru2dbhdnjRocGEOR2UuTz87+zk6jlBTdWlqgJURyc4ay3/tSyFt748gttjuWREd56bO6FZcYt0JMbawHcHMcb0B1YDo4AHgDuBAmAT3irR8TrOmQfMA+jevfv4pUuXBjzO1lJUVERUVFRbhyGtQPe689K977zOpntfUGH5r09LGJsYxL1jwzhe5mFHrptJPYMprYSffVZKfrklOgR+OTmcLmGde/hbS937P20po3eUg9lDQs48lgrL91eWcOuwEC7r76yxLzXXze++KOPCXsGkF3kwwGOTm7bQqtR0Nv1335HNmDFjs7W20Ww+4AmQMSYK+BR4wlr7pjGmO5ADWOBXQE9r7V0NXWPChAl206ZNAY2zNa1atYrp06e3dRjSCnSvOy/d+87rbLr3v1mRyrOr9/Hh/VMZ1C261v5Pd2fzX69/zVM3j+XCQQltEGH70p7uvcdjGfTT9/nejEE8eOnQGvtu//tGUjMKWfvQDB59extr9uSw4Sez2ijSs0N7uvedmTHGrwQokHOAMMY4gTeAJdbaNwGstZmn7H8OeC+QMYiIiEjT5RSV8891B7l2TK86kx+AaUMS2fiTWRhjWjk6aYzDYYgNd9YaArftSD5r9uTw35cPJcwZRGJ0KDlF5Xg8FodD91E6h0B2gTPA34FUa+2Tp2w/dYDw9cC2QMUgIiIiZ+bZ1fsor3Rz36zBDR6n5Kf9iosIqdUG+2+r0ogODWbO+f0Ab9OFSo9VtzjpVAJZAboQuB3Yaoz5yrftJ8CtxpixeIfAHQC+G8AYREREpImyC8v55/oDfGNsb5ISNa+ho4qLcJJ/SmKzP6eY97dlcM+0JGLCvPOCqrrOZReWEx955nOORDqSQHaBWwvU9bHQ+4F6TBEREWm+//s0jYpKDz+YOaitQ5FmiAt3kl1UXv37/32ahjPIwV0XDqjedurCq0N71D3UUeRs07nbtYiIiEgNWYVlLN54kOvG9Wagqj8dWpeIkOo5QMfyy3hjSzo3TehTXfWBUypARWVtEqNIW1ACJCIiItWeWbUPl9ty38yG5/5I+xcbcbIJwt/X7sNj4btTk2occ+oQOJHOQgmQiIiIAJBVUMaSjQe5flxv+idEtnU40kxdIkIoKq8ku7Cclzce4urknvSNj6hxTJRv4VUlQNKZKAESERERAJ75dB+VHqu5P2eJLhHeRgdPr9xDcYWbe6cn1TrGGENidKgSIOlUlACJiIgIAGv2ZDNtSCL9uqr6czaIjfB2dXt54yFmDuvGsB4xdR6XGBVao1mCyNlOCZCIiIhgrSX9eCkDNPTtrFFVAar0WObXUf2pogqQdDZKgERERITc4gpKXW76dAlv61CkhcSFeytA5/XvwoT+8fUelxgdSk5RRb37pWk+2JbB+b/+mNIKd1uHIvVQAiQiIiIczisBoG+XiEaOlI6if0IEw3pE8+NLhzZ4XGJUGHnFFbjcnlaK7Oz27tcZHCso41iBWou3V0qAREREhPTjpQC1uoRJxxUd5uSDH01l0sCuDR5X1Qo7V1WgZnN7LJ+l5QCQV6xhhe2VEiARERHh8HFvBUhD4DofrQXUcnYcLahee0nDCtsvJUAiIiJC+vFS4iNDiAwNbutQpJVVJ0BFGrLVXGv2Zlf/nFesBKi9UgIkIiIiHM4rUfWnk0qI8jZLUAWo+T7bm1PdSVEJUPulBEhEREQ4crxUDRA6qYQoDYFrCWUuN18cOM7MYd2ICg3WnKp2TAmQiIhIJ+fxeNcAUgWocwpzBhETFqwEqJm+OJBHRaWHKYMTiI8MUROEdkwJkIiISCeXXVROhdtDH3WA67QSo0PJLtIb9uZYuycHZ5Bh0oB44iNDyNUQuHZLCZCIiEgnV7UGkCpAnVdidKgqQM20dm8O557ThYiQYLpGhmgIXDumBEhERKSTq14DSHOAOq3YcCcFpZVtHUaHVVBh2X60gIsGJwD4hsApAWqvlACJiIh0cqoASUyYk4IyV1uH0WGl5roBuHCQNwHqGhVKXnEF1tq2DEvqoQRIRESkk0s/XkpidChhzqC2DkXaSHSYk4JSJUBnanuum+iwYJL7xAHQNTKECreHwnJV1dojJUAiIiKd3OHjJfRV9adTiwkPprjCTaXb09ahdDjWWrbnuJmc1JUghwG8Q+AA8jQPqF1SAiQiItLJHcoroY/m/3RqMWFOAIpUsWiyA7kl5JZZpgxOrN4W71tcVp3g2iclQCIiIp1YmcvNkROlDEyMbOtQpA1FhwUDqBHCGVi7NweAKb75P+AdAgeoEUI71aQEyBijfx1FRETOIvtzirEWkhKj2joUaUMx4d4KkBohNN3aPdl0DTP073qyito1KhSAXK2t1C75lQAZYyYbY3YAqb7fxxhj/hrQyERERCTg9mUXA0qAOruqIXBKgJrG7bGsS8tlZEIQxpjq7VUVIA2Ba5/8rQA9BVwG5AJYa78GpgYqKBEREWkdadlFAAxI0CCPzqwthsC99sVh7nrhiw7dKjol/QSFZZWM7Fqzg2KYM4iIkCANgWun/B4CZ609fNomdwvHIiIiIq0sLbuI3nHhhIeoBXZnFusbAlfYihWg5VszWLkzi+1HC1rtMVvaZ775P8O71v7vR4uhtl/+JkCHjTGTAWuMCTHG/BjfcDgRERHpuPZlF5PUTcPfOrvqClBZ61WAUjO8ic97KRmt9pgtbc2eHEb2iiEmxNTa1zUqlBzNAWqX/E2A7gG+B/QG0oGxvt9FRESkg7LWkpZdxEANf+v0okK9CVBrVYByisrJKizHGFi+9egZD4NbsTWD3ZmFLRydf0oqKtly6HiN7m+n6qoKULsV7M9B1toc4LYAxyIiIiKt6FhBGSUVblWAhOAgB1Ghwa02B6iq+nPd2N689eURth7JJ7lPXJOukV/i4gevfMn0od1YdMeEQIRZQ0lFJW9/eZRXPj9EZGgQ04Z0w+W2TBmcgPtIZq3j4yNDqp+ntC/+doF70RgTd8rvXYwx/whcWCIiIhIoaXlpzF8+n0ELu3Ew7Bru+XgU85fPJy0vra1DkzYUHRbcal3gqhKDH84ajDPIsPwMhsGt3JVJpceycX8ubk9gGykUlVdyzdNr+clbW6n0WPZmFfG7D3YSEuzgvP7xdZ7TNTKE3OIKrLVUuj18sO0YDy1LIauwLKCxSuP8qgABydbaE1W/WGuPG2PGBSgmERERCZAVe1Yw+/XZuNwuXB4XGCipLGLRlkW8+PWLLLtxGVcMvqKtw5Q2EBPmbLUhcDuOFtAzNoz+CZFMGZTAv74+yrypA6vXz/HHv7d5qy6FZZVsO5LPmL5NqyD5y1rLT97cyv6cYhbNncCs4d0oKKvk6Y/3EB3mJMxZdwOR+MgQKio9PPXhbpZtTudovjfxGd+vCzed1zcgsYp//J0D5DDGdKn6xRgTj//Jk4iIiLQDaXlpzH59NiWuEm/ycwqXx0WJq4TZr89WJaiTiglvzSFwhQzvGQPAdy4aSG5xBdcu/Iyt6fl+nV/mcvPp7mwuH9kDgHVpuQGL9bVNh/nX10d54JIhXDyiO8YYYsOd/OzqEfzw4sH1npfgS+b+vHIvAxOj+Ott52IMHM0vDVis4h9/E6AFwDpjzK+MMb8C1gG/D1xYIiIi0tIWrF+Ay93wJ/wut4unNjzVShFJexId5myVIXBlLjd7s4sY4UuAJg9K4I17JgNw0/+tJ7uw8c5pa/bkUOpyc9v55zC0ezTr0nICEqvHY/n1+zs5f2A8904f1KRzLxvVg59eOZyPH5zG4rsnceXonnSLDuXoCSVAbc2vBMha+0/gBiATyAK+aa19KZCBiYiISMtanLK4VuXndC6Pi5dS9L/4zigmLJjCVmiDvTerCLfHVleAAEb3ieW5uRModbn5z45jjV7j39uPERMWzPkDu3JBUle+OJBHRaWn5WPNLiK/1MXs8X0JctRudd2QqNBgvjN1IEmJJ5uM9IoL5+gJzQFqaw0mQMaYGN/3eOAY8DKwBDjm2yYiIiIdRFFFUYseJ2eX1qoA7fAtfDqiV0yN7cN7RtO/awQfbGs4AfJ4LB+nZjJreHecQQ4mJ3WlzOXhy0PHWzzWLQe91zz3nJaZX+RNgFQBamuNVYBe9n3fDGw65avqdxEREekgokL8a3ft73FydokJ91aAznRNHn/tyCggIiSIfvERNbYbY7hsVA/Wp+WSX1J/IpZ+vJTjJS4mDfB+Fj9pYFccJjDzgLYcOk6XCCcDWmitrF6xYRw5URrw11ga1mACZK292hhjgGnW2oGnfA2w1g5spRhFRESkBcxJnoPT4WzwGKfDye3Jt7dSRNKexIQ5cXssJRXugD7O5/vzGN07FkcdQ8quGNWTSo/lo9Ta6+pUST3mrSAN8w2hiw13Mu6cLizfmtHiicWWQycYd04XvG+Hm69XXDjllR4tkNrGGp0DZL1/SW+1QiwiIiISQA9e8CDOoEYSoCAn959/fytFJO1JdJj3byOQw+CyC8vZkVHA1CGJde5P7h1Lz9gwVjQwDG5nRiHGwJDuJyuVt048h71ZRWzYl9diseaXutibVcS4Fmyv3SsuHMDveUCvbzrM31apK2NL87cL3AZjzHkBjUREREQCKik+iX9+YymGUMxpq1k4HU4inBEsu3EZSfFJbRShtKWYcO/fRCAbIazdmw3A1MF1J0AOh+GykT1YvSebovK649iVWUD/rpFEhJz8G746uSdxEU5e2nCgxWL96rB3Ccxz+3Vp5Ej/9fYlQEf8mAdUWuHm8eWpPPnhrgaHBErT+ZsAzcCbBKUZY1KMMVuNMSmBDExERERa3pFjw+hZtpCbht9BTGgMDuMgJjSGeePnkXJPihZB7cRiqipApWf2ZntvVhGrdmXxwbYMsgrrrnCs3p1DfGQII09rgHCqK0b1oKLSw6pdWXXu35lRyLAe0TW2hTmDuHlCX/69PZNj+S3TZW3LweMYQ4susHqyAtR4AvT2V0fIL3Xhcls+2J7RYjGI/4uZNvlfQ2NMX+CfQA/AAzxrrf2Tr3vcq0B/4ABwk7W25dt2iIiISA35JS6eW7OPK4eP5bmb7gYWtXVI0o5Eh3nfFp7JELiCMheX/3E1lR7vHJwwp4O5F/Tnu1MH0tW3IKjHY1mzJ4cpgxLqnP9TZUL/eBKiQlix7RhXJ/eqsa+0ws3+3GKuHdur1nm3TerHs2v28crnh7j/kiFNfg6n23LoOEO7RxMV6u/b5cZ1iXAS5nQ0mgBZa3nhswOM6BlDSUUl//r6KDefd06LxdHZNdYGO8wY8yPgv4DLgSPW2oNVX41cuxJ40Fo7HDgf+J4xZgTwMPCxtXYw8LHvdxEREWmCovJKDueVNOmcRWv3UVhWyQMt8OZQzj4x4d4K0JkMgTtyvJRKj+Why4fxxr2TuXJUTxat2cdFv/+E//33Tk6UVJB6rICcovJ65/9UCXIYLhnRg092ZlHmqtmQYXdmIdbCsB61K0jndI1g+pBEXvn8EC5389YEyikq5ytfA4SWZIyhV1w4GfVUqay1WGtZn5bLrsxC7rywP9eM6cX6tNx6q2rSdI0NgXsRmABsxVsFWuDvha21GdbaLb6fC4FUoDfwDd91q65/XRNjFhER6dTKK93c+uwGLn1qNQdzixs8ttLtYd3eHB59exvPrdnHVaN71liAUqRKdQXoDIbAHSvwvjmfOCCe8f268OTNY/nP/dOYOawbf/kkjYt+9wm/+NcOAC4anNDo9S4f1YOSCjdr9uTU2L7T1wFueM/ouk7j9gv6kVVYzn+2199FrjEFZS7u+MfnuDwevjWx5asuvePC65wDtC+7iCv+tIZBP13BHc9/TnxkCNeO6cW1Y3rhsbA8JYMyl5v8MxyiKCeZhtoFGmO2WmtH+34OBj631p7b5Acxpj+wGhgFHLLWxp2y77i1tlZ6bYyZB8wD6N69+/ilS5c29WHbraKiIqKitMZCZ6B73Xnp3nderXHvl6SW8+HBSkIc0D/WwcMTw3Cc0qa30mPZketmU6abLzMrKXRBiAOSE4P41vAQ4sP8nQIsTdHR/7uvcFvmfVjCDYOdXJMU0qRzVx128cL2ChZMC6dreM2/r8OFHt7eW8HmTDd9ox386sLwRq9X6bHct7KEcd2C+U5yaPX2JanlrE6v5G8XR9T4m6/isZaHVpcSH2Z4ZFLjj3O6CrdlwaYy9p7w8MNzQ0lO9G/4W1Pu/T+2lZOS7eaPM06ug7Qtp5K/flWOw8DUPk5cHsvIrkGM7eZ9/Ec/KyWz2EOlhbAgeGJKOF3033EtM2bM2GytndDYcY3d1eoU01pbeSY90I0xUcAbwI+stQX+XsNa+yzwLMCECRPs9OnTm/zY7dWqVas4m56P1E/3uvPSve+8An3v/739GB9+sJk7J/dnVO9Yfvz61xxw9ueuKQMAb+eqO5//nBMlLiJDgpg1ohdXjOrBtKGJNbpmScs7G/67D/lkBQm9+jJ9+vAmnfflh7sxO/Zw7aXTcQbVfmN+O97ha2HBQZzTNaL2Bepwec5XfJyaxYUXTa2+5jO71zO8l4eZMy6s97xvO9L47Yqd9Bw2nqE96q4U1aXS7eHeJVvYfaKEP948lm+M7e33uU25919X7mF1+m4umHIRIUEO/vHZAZ7cvIMh3aN5bu4E+sbXfn0eTTzGss3pDEyM4h+f7eeT4134863j/I5PamrsX8IxxpgC388GCPf9bvAuEdRgDd0Y48Sb/Cyx1r7p25xpjOlprc0wxvQE6m7xISIi0om4PZagBiaGA2zYl8sPl35Jcp9YHrlyGCFBDlZszeD3/97JZaN60DsunN+uSMUZ5GDR3AlMGZxAmDOolZ6BdGhpabBgAVv+8SKRvy6FqCiYMwcefBCSGm+Lfiy/jISo0DqTnypDuvufjABcPrIHb245woZ9uVw0OBFrLbuOFXL5qB4NnnfThL48+eFuFm84yK+uG+XXY1lrefjNrXy4I5NfXDuySclPU/WKCwPgcF4Jz67ex2ub0rlsZHeevGkskfU0XLh0ZA8uHel93iHBDv788R5umdiXyUmNDyeU2hqsnVlrg6y1Mb6vaGtt8Ck/N5b8GODvQKq19slTdv0LuMP38x3AO815AiIiIh2RtZYVWzO48k9rGP3Yvxn00/d556sj9R6/+eBx7nrhC/p2ieD5O88jNDgIYwy/vG4U1sJv3k/liwN5bNiXx3enDuTiEd2V/Ih/VqyA5GRYtIio8hKMtVBYCIsWebevWNHoJY4VlNEzNqxFw5o6JJGIkKDqRVHTsos4XuJiRK/YBs+Ljwzh6uSevLklnUI/OtpZa/n1+6ks25zOD2cN5o7J/Vsi/HpVrQU09++f89qmdO6bOYi/3Ta+3uTndPOnJ9E3Ppz/eWd7nc0e0rKLaGiKi/i/DtCZuBBvxXOmMeYr39eVwG+BS4wxe4BLfL+LiIh0OKt2ZbE3q7DJ5+WXuLjz+S+4d8kW3B7LDef2oV98BAtX7q3zjcu2I/nc+fzndIsOZcndk6rbCoP3zdQ905J4LyWDh5alkBAVwm2T+jXreUknkpYGs2dDSQm4TksWXC7v9tmzvcc1ILOgjO4xLZsAhTmDmDG0G//ZnonbY3ljyxGCHIbLRzZcAQKYe0F/iivcvP1l/R8qVHnm0308t2Y/cy/ox48uHtwSoTeoai2gvJIKFn5rHA9cOrTBtuCnC3MG8dg1I9mbVcTzn+2vse+rwyeYteBTPqlnDSXxClgCZK1da6011tpka+1Y39f71tpca+0sa+1g3/e8QMUgIiLSHGl5acxfPp+Y38Tg+IWDmN/EMH/5fLZl7uLB177mzue/4JfvpTb5uo++s43P9ubwP1ePYPl9U3js2pH8YOZg9mQV8enu7BrH7jpWyJy/byQmzMmS75xPtzreZN4zLYlesWHsyynm7osGEh6iyo/4acGC2onP6VwueOqpBg/JyC+jRwsnQODtBpdTVM7n+/N4a8sRpg1JJDE6tNHzxvSJZXTvWP65/mCD1ZCPdmTyuw92cu2YXjx2zUjOZL57U/XrGsFPrxzOG/dOrrXOkb9mDe/OxcO78ceP9pCRf7Kj3HtfHwVg25GC+k4VAlsBEhER6bBW7FlB8jPJLNqyiMKKQiyWwopCntu8iDHPjGXx12/Tp0s4W9NPNGm4ybtfH+VfXx/lh7MGc9eUAQT75kxcM6YX3aJDWbTm5Ce6adlF3LZoI6HBDl7+zqTqoTOnCw8J4rc3JDN9aCJzzlf1R5pg8WL/EqCXXqp3d1Vr5h4tPAQOYMawboQEO/jVezs4VlDGDef28es8Ywy3X9CPPVlFbNyfx/aj+XycWrM19omSCh55ayvDekTzhxvHNKkK0xzGGL4zdSAjGxnK15ifXzMSt8fy+HLvhzDWWj7Y7h0uuDerqNlxns2UAImIiJwmLS+N2a/PpsRVgstT881hpXXhoYyC8N9x3YQgjpe4OFrPooanyyoo49F3tjGmbxz3Tq85sTwk2MEdk/uzdm8O76UcZduRfG57biNgWXL3+fTrGtngtacOSeSF/zexRVetl06gyM83yg0cd8z39x+IClBUaDBTByewI6OAmLBgZg3v5ve51yT3Ijbcyb2LN3PVn9fy7Rc3sevYySGrv3xvB3nFFfzhxjGEBHe8t8R94yOYP30Qy1MyWLsnh+1HC0g/Xkqww7BHCVCDOt7dFhERCbAF6xfgcjf8qbjbVvJFjvdT8a3p+Y1e01rLQ2+kUOZy8+RNY6orP6e6bdI5JESF8P2Xv+Tqp9dSVunmpW9PYlC3jru2jLRz/q5b1MBxGb4EqKWbIFS5fFRPwFslbUpjj/CQIL5z0QDCnEHcf/EQwpwO/r52HwArd2by5pYj3DstiVG9m1eJaUvfnTaQfl0j+J9/bePdlKM4DFw7phf7sotwe9QIoT5KgERERE6zOGVxrcrP6VweFx/sf50gh2H70cYToKVfHOaTXdk8fPkwkhLrfjMZFxHCxw9OZ8ndk3jsmhEsu2cyw3s22HRVpHnmzAGns+FjnE64/fZ6d2cWeBOg7gFKgC4b2Z3LR/aoXuuqKb4/czDrH5nFDy8ezOzxfXj7y6OkZRfxkze3MaR7FD+YNSgAEbeeMGcQj107kn3ZxTy3eh8TB8QzcUA85ZUejhwvbfwCnbeMUjAAACAASURBVJQSIBERkdMUVfg3fKSooojB3aLYdqRmApRTVF6jKnQot4RfvbeDyUldmXtB/wavGRvu5MJBCdx54QBVfiTwHnzQvwTo/vvr3Z0RwCFwANFhTp65fXy9Hxz469tTBuLyeLjpmfVkFZbxv7PHEBrc8RuGzBjajUtHdMdj4YpRPav/3dib3fQOlZ2FEiAREZHTRIX490ZrdGEEj65YyNP3zsA6HBATQ9KTT/Ffv32T6//6GSnpJ3B7LD9+/WuCjOF/W3GitYhfkpJg2TKIiKidCDmd3u3LljW4GGpmQRnRYcF+r2PTVgYkRHLx8O7kFlfw3WlJjOkb19YhtZhffGMkN5zbh2vH9DqZAGkeUL2UAImIiJxmTvIcnI6GPxW/em8QG58u4/yVb9VYPLLn+8v5y+/+H5cd/pL7XvmSP3+8h88P5PHYtSPr7eIm0qauuAJSUmDePIiJwWMMpeGR3t9TUrz76/D/2bvv+Kiq9I/jnzuTSU8IafQaeglBUEERKaKCqOhGxIK6rou9LetvcVfXXlZFXEXXVZZFgZWm2EEUQboIEULohBJ6QkJ6m8zc3x8TIoFUSDJJ5vt+veaV5M4tz52TwDxzznnOqTLxL2+6mARjZEmZ+MS0itcMcqe/jurOvYM78ujw2l/vpy61aOLH5LF9aBrgTYi/N+GB3kqAKqAESERE5AwTB07EZi0/AeqYBnPmOvApKMJaVFTqOS+HA/+iAt7+9CXMxET+uXQ3V/Zoxo0XtKrtsEXOXVQUTJ0KGRmMfXcVd0353vVzOT0/p5eJt5s5UFwmflrcNKLfj2bR7kV1G38VdQgP4MlR3atVTKEhiooIrJME6Oe9qQ2y2IISIBERkTNEhUax4KYFWPHFoPSwHpvFxl9+tuJnVvwGylpUxDvHltMxPICXb+xdJwssitSENqH+HKpgAn1FZeLtTju59lxi58fW656gxq5TpCsBqs4aZdU1b8NBxn24jumr9lW+cz2jBEhERKQMPUMvp1n+OwxpNY5gn2AshoVgn2Am9JvAPVt9sRQ5Kj6B3U70sq9YOvFywgMrX7lepL5oE+rPkYw8CoucZT5flTLxdoedKeum1EZ4UgWdIgPJzC8iJbugVs4/95ck/vJpPIM6hTN+YMNbfLl+z1YTERFxk0PpudjMFrw4dAqXRM0s/WTOe1U7SXa2en6kwWnT1A/ThMPpeXQIP3sB3qqWiZ8ZP5Opo6bWVphSgdMLIUQG1Wx1vk/WJ/HkZ1u4vEsE/x7fr0EOJ1QPkIiISBlSslyfnEYGldF7UwOLR4rUV21D/QE4mJZb5vPVKRMv7tGteTAWA/79014KKuutrob//exKfoZ0bbjJDygBEhERKdOpBCgisIxPT2tg8UiR+qpNcQKUVE4CVNUy8VXdT2peRJAPL47pzU+7Unhw9q/lDmesjlnrDvDXhVsY1i2yQSc/oARIRESkTCnZBXhbLQT7lTFavAYWjxSpr5oF++JttXDwZNkJUFXKxNssNsZH6wMAd7r14rY8f31Pfth+nI/X7q/ycat2n+CvC7fgPK2628y1+3nq8wSGd4vkX7df0OAXkFUCJCIiUoaUrAIignzKnsNTweKRTqu1SotHitRXVotB66Z+5Q6Bq6xMPIDNauPxAfoAwN3uGNiejuEBrNubVuVjpi7bzf9+TuLrLUcBWLTlKE9/sZUrujfjvUaQ/IASIBERkTKlZBUQXtb8n1POWDwSiwWCgzkyenSFi0eKNAStQ/05mFZ2KexTZeL9vPzhjHLwNosNf5s/C25aQFSoPgCoD2LahLDpYHqVSmIfz8zn532uZOnNJTtJzsrnqc8TiG7dhPduaxzJDygBEhERKVNKVgERlZWvPm3xSBwOyMhgz2OPqedHGrwOYf7sTs5ib0rZhQxGdh7Jm0OWEOi4mkBbUKky8fH3xTOysz4AqC9i2oZwIruAIxn5le77TfxRTBOeHNmN/am53PjeGjLz7bwWG423V+NJGxrPnYiIiNSgE9mFRFTUAyTSiN1zWUf8vb245+MNZOSVXfI6Oa0prXiQtL+k4/i7g4xJGUwdNVU9P/VMn9YhAGw+mF7pvl/FH6FHi2AmDO5I37YhHDqZxwNDOtGteXBth1mnlACJiIicweE0ScspUAIkHqtNqD//uu0CklJzefiTXylynF1FbNPBk/Rq2QSbVW8n67PuLYLxtlrYVEkCdDAtl1+T0rm2T0sMw+CVG3szYXBHHhzaqY4irTv6jRURETlDak4BThMlQOLRLu4YxotjerFiVwovf7uj1HN2h5OEI5nEtAlxU3RSVd5eFnq0DK40Afo63lX0YHR0C8C1ltBfR3VvVEPfTml8dyQiIqXU5CJ4nuK3NYCUAIlnG3dRW35/aXumr97H3F+SSrb/sj+NwiInfZQANQgxbULYciijzJ68U77afIS+bUNK1oFqzJQAiYg0YjPX7qfv899X+smflFaSAKkHSIS/jerOZZ3DeerzBNbvS6PI4eTFr7fTLNiHod0i3R2eVEFMmxDy7A52J5dd1GJPcjbbjmZybXTLOo7MPZQAiYg0Uj/tSuGZL7eSW+hg8pKd7g6nQTmVAEUqARLBy2ph6i0X0KapP/fN2sg/Fu9g29FM/j66J4E+ZSwULPXOqaGKv+wvez2gr+OPYBhwTfHwt8ZOCZCISCO0JzmLh2bH0bV5MI9f0YWVu0+wfl/VF8JrqBxOk2e+SOC2aet4bM6vfLHpcJXWvjhTSrYrAQrXEDgRAJr425h2Z3+KHE4+XLmPy7tEMKp3c3eHJVXULsyfdmH+/P2Lrfz+v+tZsSul5N9G0zT5avMRLu4QSrNgXzdHWjeUAImINDJpOYXcPWMDPjYr0+7sz4TBHYkI8mHykp3nlAw0JFN/3MNHaw+QkWdn3d40Hp2zid/P+IUj6WUv6FielKwCgny88PNuHIv+idSEjhGB/Ov2flzQNoTnr++JYRjuDkmqyDAMPr3/Eh6/ogtbDmdyx/T1jJiyglnrDhCXdJLElByu7eMZw98A1G8pItKIFBY5uW/WRo5l5jNnwgBahfgB8OCQKJ79ahvv/LiHh4Z2wmKpn29cTmQXcDwzn27Ng7FWM8a1ian8c+kubuzbijdvjsHpNPl47X5e+24n101dzSd/vJjOzYJKXWv9vjR+3ptKep6df/wuGl+bK+FJyVIJbJGyXNopnEs7hbs7DDkH4YE+PHpFZ+4b0pFv4o/y39X7eerzBAwDrBaDkb08Y/gbKAESEWk0TNPkqc+3sH5fGv8cF8MFbZuWPHfbgHb8ejCdN7/fxZbDGbw9rm+96d1wOE1W7Eph7i8H+WH7cYqcJk39bVwT3YJnru2JzWph25FM3l2+h7+P7nHWEI3sgiJmrTvA+z8l0j4sgBfG9ALAYjG469IODOoczq0f/sy4D9bx56u6su1IJuv2ppZMBvbxslBQ5GRgxzDGXdQWcCVAGv4mIo2Rj5eVGy9ozQ19W7HxwEk+WnuAViF+hAZ4uzu0OqMESESkkZi2ch/zNhzikWGduD6mVannbFYLb90cQ+9WTXjxm+0s2HiQ8QPbuyfQYkmpuczbcJAFGw9xLDOfsABvfn9pe7q3COanXSnMWpeEv7cXDw/rxAOzN7I/NZfU7AJm3zMAq8UgPbeQ/67ez4w1+8nIs3NZ53Ceu64nAWdMyu4UGcTcewdyywfrePKzLfh7W+nfPpQbLmjFgI5h9G7VhDHvruaDlXsZ278NFotBSnYB3RvZyuciIqczDIP+7UPp3z7U3aHUOSVAIiINUMLhDPadyGFI1whM4JOfk3h18Q5G9W7OY1d0KfMYwzD4w6AOTF+1j3V709yaAL349TamrdqHxYDLu0Tw7HU9GNatWcmCezde0JpgXxsfrNjL2sRUDp7M465L2jNjzX5e+XY7VovBrHUHyCl0cGWPZjw4tFOF65F0CA/gu8cGk5SWS7cWQWetXD9hcEcenbOJpTuSGdGjGSeyCojorB4gEZHGSAmQiEgDY3c4uXfmRg6n5+FttWC1GOTZHVzWOZzJN8VUOL/HMAwu7hjGyt2uCkDumMScb3cwc90BrujejBfG9KRFE78y93tqdHfiD6Wz+VAGT1zVlQeHdiIz316SOF3bpyUPDOlE1+ZBZR5/pib+Nnr7NynzuWt6t+C1xTv5YEUil3UOJzO/SHOAREQaKSVAIiINzLdbjnI4PY9JI7uRklVAvt3BuAvb0rt12W/uz3Rxh1AW/nqYxJQcOkUG1nK0Z9t8MJ2CIifjLmxTbvIDrnHqH97Zn2U7krmpXxsAXhzTi54tmzC8WyTtwwNqLCYvq4V7LuvAc19t475ZGwGI0BwgEZFGSQmQiEgDYpom7/+0l6iIACZc1vGcqrldamTwwpL3aPvOOMjLgcBAuP12mDgRoqJqIerS1u1NwzDgwg6VjzuPDPLl5gvblvzs7+3FHwZ1qJW4xg9oR0aenXeX7QEgPMhzJgSLiHgSrQMkItKArNpzgu1HM7l3cNS5lbJetIjWQwYwbvN3eOdmg2lCVhZMmwbR0bBoUc0HfYZ1e1Pp2TKYJn62Wr9WdXhZLTx2RRe+fvgy7r28IwM7qtSviEhjpARIRKSBiEs6yfNfbSMyyIfr+57DgnWJiRAbi5Gbi83pKP2c3Q65uRAb69qvluTbHcQlnWRAh7Bau8b56to8iCdHdq83ZcJFRKRmKQESEXGj9NzCSvfJzLfz+NxN3PjeGtLz7Lz6u974eJ3Dm/PJk12JTkXsdpgypfrnrqJT838GdKy/CZCIiDRuSoBERNxk9Z4TXPDC92w/mlnuPvGH0hn99iq+3HyEh4Z2YvmfhzCsW7Nzu+CsWVVLgGbOPLfzV0F15v+IiIjUBhVBEBFxk++3HcdpwtLtx+neovSim6ZpMmPNfl7+djsRgT7Mu3cA/dqdZ9KQnV2l3cysbE6fXbTlUAYnsgsY2i3y/K4PrEk8US/n/4iIiOdQD5CIiJusSTwBwIpdJ0ptT88tZMLMjTz31TYu7xLJt49edv7JD7iqvVVBno8f+XbXHKF8u4P7Zm3k/tkbycirpPeoEvM3HOTnfWlc0f0ce7BERERqgBIgERE3SM7MZ9fxbEL8bcQlnSQr35VcxCWd5Jq3V7F8ZzJPj+7Bh3f0I8S/hsox33472CrueXF6eTG/+xAe/uRXihxOPlqzn8PpeeTbnSyMOwRAwuEMJi/ZicNpVvnSa/ac4MnPtnBZ53AeHNrpvG5DRETkfNRaAmQYxnTDMJINw0g4bduzhmEcNgxjU/FjVG1dX0SkPluTmArAg0M6UeQ0Wbc3jW1HMrn532uxWGDBfZfwh0EdMIxzKHVdnokTK02ALN7eBE16gu+3HefRuZuYumwPQ7pG0Kd1E2b/nEReoYMH/xfHOz/uYdrKvWWew+5wsjcluyRB2pOcxb2zNtIxIoB3b7sAm1WfvYmIiPvU5hygGcBU4OMztk8xTfONWryuiEi9t3rPCZr42Rg/sB1TftjFT7uS2XksiyBfG188OIjQgFpYhDMqChYscJW6tttLF0Sw2VyPBQu4ceTlHA7bzeTvd2Ex4MmR3dl8MJ3/+zSeCTM3cCA1l54tg5n8/S6GdYukU2QgO49nsXpPKmv2nODnfWlkFxRxaacwnrqmB3/8eAM+Xlam33Uhwb6a+yMiIu5VawmQaZorDMNoX1vnFxFpqEzTZE1iKgM7huFrszKwYxjzfjlEocPJP37Xu3aSn1NGjoT4eFep65kzXYURAgNh/Hh4/HFXkgQ8NKwTPjYLFsOga/Mg2oT68cI321i5+wSx/VozaWQ3rpyygjunr6fQYXIiuwCA9mH+XB/TkmbBvry3fA8j/7kSX5uFuRMG0rqpf+3dl4iISBUZpln1MdzVPrkrAfraNM1exT8/C9wFZAIbgImmaZ4s59gJwASAZs2a9ZszZ06txVnXsrOzCaziZGRp2NTWnqusti9ymiRlOkkvMHn71wLG9/BmeFsb3x+wM3t7IR2bWHhqgC+Wmhz2VoPm7ixk7ZEiXrzUj0Bvg7jjRXyyo5CoEAs9wqz0CLMS7vfb8LZDWU7m7ixkeFsvYiI9p+io/u49l9rec6nt64ehQ4duNE2zf2X71XUC1Aw4AZjAC0AL0zTvruw8/fv3Nzds2FBrcda15cuXM2TIEHeHIXVAbe25zmz7HccyeWzOJnYcyyrZtuzPQ+gQHsCxjHzunbmBl2/sTc+WTdwQbdU4nSaFDie+tnNYhNWD6O/ec6ntPZfavn4wDKNKCVCdfiRnmubxU98bhvEh8HVdXl9EpK45nSbTV+/jtcU7Cfaz8cZNfYgI8iHU35sO4QEANG/iyxcPDXJzpJWzWAx8LUp+RESkYavTBMgwjBamaR4t/vEGIKGi/UVEGrIj6XlMnLeZtXtTGdGjGa/e2JuwQB93hyUiIuLRai0BMgzjE2AIEG4YxiHgGWCIYRgxuIbA7Qfura3ri4i409ojRTy8fAVOp8lrv4vmpv6ta7aktYiIiJyT2qwCd0sZm/9TW9cTEakvJi/Zyb/jC+jXrilTxsbQNkzVz0REROoLzynLIyJSB+wOJx+t2U/fSCvz7h2I1aJeHxERkfpECVAtS0xLZPLaycyKn0V2YTaB3oEMDRtKm+g2RIVGuTs8Ealh6/amkplfxOAePkp+RERE6iFL5bvIuVq0exHR70czLW4aWYVZmJhkFWbxzdFviH4/mkW7F7k7RBGpYYsTjuHvbaVnmKqliYiI1EdKgGpJYloisfNjybXnYnfaSz3nwEGuPZfY+bEkpiW6KUIRqWkOp8l3W48ztGsk3lb1/oiIiNRHSoBqyeS1k7E77BXuY3fYmbJuSh1FJCK1JTkzn5M5hfyadJIT2QVc1au5u0MSERGRcigBqiWz4med1fNzJrvTzsz4mXUUkYjUhrxCB6PeXsnFryzliQXxeFstDO0a4e6wREREpBwqglBLsguzS/3cMQ3+tAZuj4egQsjyhlnR8NalWW6KUERqwtxfkjiRXcjo6BYs25HMiJ7NCPK1uTssERERKYcSoFoS6B1IVqErubl6NyyYBzYHeDtdzzcphD/GwV2bTbhqEYwc6cZoReRMB9Ny+Sr+CO1CA4hu3YTWTf3OWsjU7nDy4cp99G/XlKm3XkC+3aHKbyIiIvWcEqBacnv07UyLm0abE3YWzIOAMkbDeTuLE6LYWIiPhyiVxRZxN7vDyQcr9vLOj7vJtztLtocFeBPdugl92oS4Hq1DWLErhcPpeTx/fU8AfG2q/CYiIlLfKQE6R2Wt73N79O1MHDiRjk07Mqz13czY9BF/WmPH5qjkZHY7TJkCU6fWSewiUr5XF+3gP6v2MbJXcyaN7EZmXhGbDqWz+WA68YfSWb4rBdN07WuzGnRpFsjQrpHuDVpERESqTAnQOVi0exGx82OxO+wlhQ6yCrOYFjeNGZs+4uImL+LYEsTMhD7cuGEtlQ6Isdth5kwlQCJutmbPCf6zah/jB7TjhTG9Srb3bt2E8QPaAZBdUETC4Qw2H0xn29FMbu7fBouGvYmIiDQYSoCq6fT1fc5kd7oSIr91/8dn861YiooqT35Oyc6ufB8RqTUZuXb+PH8zHcMD+Ouo7uXuF+jjxYCOYQzoGFaH0YmIiEhNUQJUTZWt79MxDebPK8LXXlS9EwcGnmdkIlKWvSnZHEjNxWa1YLMa2LwseFst2KwWvKwG3lYLaxNTeWPJTlJzCvns/kvw89ZcHhERkcZKCVA1Vba+z5/WUPmcnzPZbDB+/PkFJiJnmbfhIH9buAW7w6x0375tQ3h/fD/6tAmpg8hERETEXZQAVVPksSxeKWM9nzcvgb2hru3ezsrPU4rNBo8/XivxijR2ZxYk8bEG0LvpaLoGjGPlDi8u6xzOY1d0wWma2IucFDqcFDlM7A7X93aHSVigN0O6RJxV5lpEREQaHyVA1ZD52Zds/ld56/lA7FhXUlRVps2GYbPBggUqgS1yDsoqSJLvyOaXlPlsSFnIrb3e4r+3jMTLanFzpCIiIlJf6F1BVSUmEnD7OALsZ/fweDtd6/wsmAc5VVwA3gQSx9zqWv9Hi6CKVNvpBUnOGpZqODCNAhYmTeRAxj73BCgiIiL1khKgqpo8GWtRxYUNbA7YHwKFlbyqTquVeRddy7u/e6xR9Pzk2x1MW7mXvy7cQpGjuuP/RM5NZQVJAOwOO1PWTamjiERERKQhUAJUVbNmudbrqYC3E9pngMXHp8L9TJuNnbfcw0+7UsjIq/ic9ZnDaTJ/w0GGT/6JF7/Zzv9+TuKLTUfcHZZ4iMoKkoCrNP3M+Jl1FJGIiIg0BEqAqqqK6/QE2g28Pl0I/v6u4gans9nA35+tzz7Ldb8bTEaenb9+tgXTrLxCVX1imibfbzvOyH+u4IkF8YQFejPrDxfTs2Uw/1y6G7t6gaQOZBdW7W+yqvuJiIiIZ1ACVFVVXKfHCApyzemJj4cJEyA4GCwW19cJEyA+nrSLLyamTQh/vrIr32w5ypxfDtZKyNuPZvLKou289cMuvtt6rEbO+cv+NG56fy1//HgDdofJu7dewBcPXsqgzuH8aUQXktJy+XTjoXM698R5m3n2y60NLiEU9wj0rtrfZFX3ExEREc+gKnBVdfvtMG1axcPgTl/PJyoKpk51Pc500JXw3Du4I2sST/Dsl1vp164pXZoF1Vi4pmnyxILNbD2Syal8YtYfLmZQ5/BzOt+e5Cxe+XYHS3ckExnkw0s39GJs/zbYTquuNaxbJDFtQnh76W5G9m5BE78qVoQA4g+l82mcK3FqG+rP3YM6nFOc0ng4nSbvLtvDun2p/ON30bRu6g+4fhf/u3o/1vzBYCwGo/yFt2wWG+OjtcaWiIiI/EY9QFU1ceLZQ9rOVM31fCwWg8lj+xDk68VD/4sj317dFVTL993W4yQczuSN2D7seOFq2ob68/zXW8ssUpCclc+iLUd54ettjP33WlbsSin1fMLhDG54dw3r96fxf1d35acnhnLbxe1KJT8AhmHw11HdScku4LZp60jPrXpN8A9X7iPIx4th3SJ56dvtrE1MPbcbl0Yhr9DBw3N+ZfL3u1i/L40x765m1roDjP/Pz1zx5grmbzxEbNf78LVVPN/OZrXx+ACtsSUiIiK/UQJUVVFRrvV6Kpjbcy7r+UQG+fLm2Bh2Hc/m+a+31UioTqfJlO930TE8gOtjWuJrs/LUNd3ZdTybmesOsCc5iznrk5g4bzNDXl/GRS8t5f7Zccxad4Ddx7N4bO4mkjPzAdiTnM0d09cT7Gfju8cG88CQTvh5W8u99kUdQvlgfH92Hc9m3AfrWLk7BdM0MU2T5Mx81iamMmvdAZ7/ahv3fLSBOeuTOHQyl2+3HGXcRW3457gY2of589D/4jicnlcjr4c0PH+at4lvtxzlb6O6s+jRwQT4ePHU5wnsOp7Fn6/swtpJw/jw1tF8NnYB/jZ/bJbSf5M2iw1/mz8LblpAVGjDr7QoIiIiNUdD4Krj1NyeKVNg5kxXYYTAQNewt8cfP+eS1oO7RHDf5VG8/1Mil0aFc010i3MO0TRNZv98gJ3Hs/jnuJiSBSBH9GjGoE7hPPfVb0lWaIA3/ds15daL29K/fSi9WjYhKS2H0e+sYuL8zVzRvRlv/bALq8XCrHsupmWIX5ViGNotkml39OfxuZsY/5/1NA/2JaegiKyC38qI+9mshAZ488P240QEuT7Fv+vSDgT52vjgjv5cP3U1983cyPz7BuJrKz/hksbnu63HWJRwjP+7uit/HNwRgC8fHETcwZMM6hRequdxZOeRxN8Xz5R1U5gZP5PswmwCvQMZHz2exwc8ruRHREREzqIEqLoqmttzHiZe2YV1e1OZ9Fk80a2b0DLEjz3J2bQJ9cPfu/JmMk2TxQnHePvHPWw/mkmfNiGMjm5Z8rxhGLx8Q2+mr95HjxbB9G/flA7hARiGUeo8nSKD+Pvonvx14RZW7j7BwI5hvDCmFx3CA6p1P4O7RLB60jC+3XKUJVuPExnsQ8fwAKIiA4mKCKR5sC8AM9bs59XFO7g+piWtihOsqIhAptwcwx8/3sAfPvqFsf3bMKhTOGGBpYc7maZJTqGDQB/9GjcWWfl2nvliK92aB/HHyzqWbG/ib2No18gyj4kKjWLqqKlMHVWzf5MiIiLSOOmdYz1hs1p455a+jPrnSu6cvp48u4OjGflYLQa9WzXh9dhoOpdTJCHhcAbPf7WN9fvT6BQZyOux0Vwf0wqrpXRy0zbMn2ev61lpLLdc1IZ8u4N2Yf4M6xZ5VpJUVb42Kzde0JobL2hd7j53D+rAmL6tCPAp3cszokcz/j66B+/8uJtH52zCMKB3qyZc3iWCwV0i8LNZ+cfiHaxJTGXanf3LfXMs9d/JnEJmrjvA5oPp7D2Rw/GsfN4f3++sOWYiIiIiNUEJUD3SJtSf12KjeXTOJi7tFMajwztz6GQes34+wN8+T2DuhAGlkpHkrHze+G4n8zceItTfm5dv6M3NF7Y5K/GpLsMw6rQKW2iAd5nb7x7UgTsvac+Wwxms2JXCT7tSeHfZHt75cQ8ATfxstArx4/G5m/j64UGEBfjw/fbjpGYXkFvowM9mJdjPRpCvF8G+NoL9XF9bhfhhOc/XSM5fclY+01buY9a6A+QWOujWPIi2of7cO7gjMW1C3B2eiIiINFJKgOqZkb1bcFXP5qXeoDdv4stTnyfw3dZjXN2rBQVFDqav2s+7y/ZQUOTgnkEdeHh4Z4J9q152uqGwWgxi2oQQ0yaER4Z3JiPXzurEExxJzyO2X2vSc+1c+84qxv9nPem5hZzMraBMebERPZrxwfh+59yzJefn0Mlc/v3TXuZuOEiRw8m1fVrywJBOdG1ec2XgRURERMqjBKgeOrN3YtyFbfh47X5e/nYH+1Nzmbn2AIfT87iieyR/u6ZHS50RFQAAIABJREFUtefnNGRN/G2M6v1bkYgQf2/eGNuHh/4Xx+VdIvjjZR3p2jwIX5uVfLuDzLwiMvPtZObZycwvYsP+NKat2sfcXw4y7qK2JBzOIN/uoH/7UDfelWdwOk2e+XIrn6xPwjDgdxe05r7Lo2jvQb+/IiIi4n5KgBoAL6uFp67pwR3T1/Pqoh0M6BjKKzf2ZnCXCHeHVi9c1bM5W5+7Gm+v0nNGfG1WQvxLD6+7skczth3N5MVvtrMnOZvpq/dhs1r44U+X0ybUvy7DbtSSs/KJDPIttW3OLweZue4At1zUloeHdapyVUERERGRmqQEqIEY3CWCD8b3o11YgIYKleHM5Kc8FovBP34XzdVvrWDaqn1c16clP2w/zjNfbuU/d/bXsLgKHEnPY+4vB1mccIyMPDsjezdnTEwrols3KfW6/Wt5Iv9YvIOb+7fh2et64udt5UR2Af9YvIOBHcN4+YZeep1FRETEbZQANSBX9mzu7hAahTah/sy4+yJyCooY0jWSaSv38uI32/lu63Gu7qXXuDxPf57AjzuTubB9KO3C/Jm9Lon/rt5fvOBuK8b0bUnC4Uz+sXgH3ZoHMW/jQTYmnWRMTEs2Hcwgt7CIF8Yo+RERERH3UgIkHunC0+b83HVJexZsPMQzXyZwYfumZ603JC47jmUxOrol79zSF4CMXDuLEo7y+abDvLV0F1N+2IXVYtCvXVNm33Mxv+xP49kvt/LGkl0APDg0ik6Rge68BRERERElQCJeVgtv3NSHG/+1hsfmbmLG7y8671LijU1uYRGH0/O4+cI2Jdua+NsYd1Fbxl3UliPpeXy1+Qjbjmby99E98LVZuaxzBEsnDiEr387+E7n0aBnsxjsQERERcdFKgyJAr1ZNeP66nqzcfYJ/LN5BbmGRu0OqVxKTcwDoXE4PTssQP+69PIp/jut7Vg9akK+N3q2bKKkUERGRekE9QCLFbr6wDXFJJ/lgxV5mrNnPgI5hDO8WybBukQ22QlyRw8m+Ezl0bnZ+hTP2pGQBaAibiIiINHjqARIpZhgGr94Yzex7Lmb8gHYcSsvlmS+3ctlryxjx5k+88d1O8u2Okv0T0xJ54JsHCH4lGMtzFoJfCeaBbx4gMS3RjXdR2htLdjFiygqe+nxLqdira09yNlaLQbswrdkjIiIiDZsSIJHTWCwGl3YK5+nRPfjxz0NY9uchPD26B5HBPnz52Ur23HQnBAdjWixEtOxE9HPvE3EsCxOTrMIspsVNI/r9aBbtXuTuWyE1u4CP1uynbag/s9YlceN7a0jNLjinc+1JzqZ9mH+Vy42LiIiI1Fd6NyNSgQ7hAfxhUAdmtzrJ9zMeputXcyArC8M0CS6AuzeaxP8Lrt7t2t/utJNrzyV2fqzbe4I+WLmXgiIH0++6kOl39ScxJZs/frzhnHqCdidna/ibiIiINAq1lgAZhjHdMIxkwzASTtsWahjG94Zh7C7+2rS2ri9SYxITITYWn8J8bM7SyYO3EwLssGAedEz7bbvdYWfKuimlT1ODQ+ZM06zw+dTsAj5ec4Dr+rSkU2Qgw7o1462bY4hLSmfi/M0UOZyVXiO3sIgih5PCIicHUnPpHKkFeEVERKThq80iCDOAqcDHp22bBCw1TfNVwzAmFf/8l1qMQeT8TZ4MdnuFu9gc8PhaePga1892p52Z8TOJHRALwKLdi4idH4vdYcfudJ0rqzCLDzZ+yEebP2LBTQsY2Xlkuec3TbNkAdGsfDu3TfsZf28rr8f2oU2oP3aHk4TDGfy8L411e1PZsP8kBUUOHhrWueQcI3u34MmR3Xhl0Q52Hsviz1d2JSLIh5M5haTlFpZ8Tc0uZOuRTHYcy2RUrxY8dkVnHE5TPUAiIiLSKNRaAmSa5grDMNqfsfl6YEjx9x8By1ECJPXdrFmVJkDeThgf/1sCBBB5LIvOU6bgvHY0V2XncMQbZkXDm5fA3uJ1WB1mEbn2ImLnxxJ/XzxRoVFnnTsz387It1YS0yaEl27oxcR5m9l6JBM/m5WR/1xJ37YhxB04SU6hq3cqKiKA62Nack3vFmclLfdeHkX78ABeXbSD+2ZtPPs+rBZC/G10aRbE8G6RfLPlKGGB3oAqwImIiEjjYFQ2lOa8Tu5KgL42TbNX8c/ppmmGnPb8SdM0yxwGZxjGBGACQLNmzfrNmTOn1uKsa9nZ2QQG6s1kQ3H5sGEYVfg7cRjg9Yzr+6t3u4bF+TmtWBy/DZsrtIDdCrFjYfFvnTNYsTK65Wge6/zYWef9KrGQT3fbsRjgbYF8B4zv4U2fCCsfby0kNd9J11Ar3Zpa6RpqpYlP5evtFDlNEk44sBgQ5G0QaDMI9DbwtVLS01ToMHlyZR6p+SYG8P4If3ysWsunqvR37rnU9p5Lbe+51Pb1w9ChQzeaptm/sv3qbQJ0uv79+5sbNmyotTjr2vLlyxkyZIi7w5CqCg6GrKxKd8vwgZAnXXOB4v/lmhtUnhwbRN//W08QQLBPMBmTMkrtl1fo4NJ//Eh06yY8PKwzf56/mWHdInl6dI9zvZtq+WLTYR6ds4nWTf1Y9ZdhdXLNxkJ/555Lbe+51PaeS21fPxiGUaUEqK6rwB03DKMFQPHX5Dq+vkj13X472GwV7lJogZnRru//tMY1J6gip+YMnS6rIItNB9NJySooKXIw55ck0nIKeXBoJ/q1a1pSlruuXNenJZdEhXFxh7A6u6aIiIhIbarNIghl+RK4E3i1+OsXdXx9keqbOBE++qjCeUB2K0wZCDaLjfFb7HhXUmStrDlDmH6MeXc1AL42C61C/EjOKuCiDqFc2D607BPVMsMwmPWHizE08k1EREQaiVpLgAzD+ARXwYNwwzAOAc/gSnzmGYbxByAJuKm2ri9SY6KiYMECiI11JUGnJUJFVoMCi8nYmw1OtAhiQvR4ggrfAyofWhpY+Nv3NouNm7rfxt09+3PoZB6HTuZy6GQeTf29+cvV3WrhpqrOYlH2IyIiIo1HbVaBu6Wcp4bX1jVFas3IkRAfD1OmwMyZkJ0NgYF4jR+P1+OP803UadXbAj+u0pyhbO/fvrdZbTw/7C9EhTarheBFRERE5JS6ngMk0nBFRcHUqZCRAQ6H6+vUqa7tp6vGnCGbxYa/zZ8FNy0oswS2iIiIiNQsJUAiNW3ixEoTILsVpl0eyIR+E4i/L77CRVBFREREpObUdREEkcbvtDlDzoKCUusAYbOBzUbAggVsGqmkR0RERKSuqQdIpDYUzxk6Mnq0ax0hi8X1dcIE11wiJT8iIiIibqEeIJHaEhXFnsceo/Xnn7s7EhEREREpph4gERERERHxGEqARERERETEYygBEhERERERj6EESEREREREPIZhmqa7Y6iUYRgpwAF3x1GDwoET7g5C6oTa2nOp7T2X2t5zqe09l9q+fmhnmmZEZTs1iASosTEMY4Npmv3dHYfUPrW151Lbey61vedS23sutX3DoiFwIiIiIiLiMZQAiYiIiIiIx1AC5B4fuDsAqTNqa8+ltvdcanvPpbb3XGr7BkRzgERERERExGOoB0hERERERDyGEiAREREREfEYSoCqwDCMNoZhLDMMY7thGFsNw3i0eHuoYRjfG4axu/hr0+Lt3QzDWGsYRoFhGH8+41yPF58jwTCMTwzD8C3nmncWn3e3YRh3Fm/zNwzjG8MwdhSf49XavndPU1/a+oznvzQMI6E27ld+U5/a3jAMb8MwPjAMY1fx3/vvavPePV09a/tbDMPYYhhGvGEYiw3DCK/Ne/d0bmr7xYZhpBuG8fUZ2zsYhvFz8TXnGobhXVv3LfWu7WcbhrGz+PjphmHYauu+pZhpmnpU8gBaABcUfx8E7AJ6AK8Bk4q3TwL+Ufx9JHAh8BLw59PO0wrYB/gV/zwPuKuM64UCe4u/Ni3+vingDwwt3scbWAmMdPfr05ge9aWtT3v+RuB/QIK7X5vG/qhPbQ88B7xY/L0FCHf369OYH/Wl7QEvIPlUexdf/1l3vz6N+VHXbV/83HDgWuDrM7bPA8YVf/8+cL+7X5/G/KhnbT8KMIofn6jta/+hHqAqME3zqGmaccXfZwHbcf3CXw98VLzbR8CY4n2STdP8BbCXcTovwM8wDC9cCc2RMva5CvjeNM000zRPAt8DV5ummWua5rLiaxQCcUDrGrpNof60NYBhGIHAn4AXa+j2pAL1qe2Bu4FXiq/jNE1Tq4vXonrU9qfeAAUYhmEAweUcLzXEDW2PaZpLgazTtxW39zBgwZnXlNpRX9q+ePu3ZjFgPXpvV+uUAFWTYRjtgb7Az0Az0zSPgusPCdenA+UyTfMw8AaQBBwFMkzTXFLGrq2Ag6f9fKh42+lxhOD6FGHpudyHVK4etPULwGQg95xvQs6JO9u++G8b4AXDMOIMw5hvGEaz87gdqQZ3tr1pmnbgfmALrjdQPYD/nMftSDXUUduXJwxIN02zqPjns/7fl9rj5rY/PQ4bMB5YfC7HS9UpAaqG4k/kPwUeM00z8xyOb4rrk4UOQEtcn/LdXtauZWwrqVde/AnDJ8DbpmnurW4cUjl3t7VhGDFAJ9M0F1b32nJ+3N32uD5JbA2sNk3zAmAtrv9cpZa5u+2L3/zcj+uNWEsgHniyunFI9dVh25d7ijK2aZ2SOlAP2v507wErTNNceY7HSxUpAaqi4v+YPgVmm6b5WfHm44ZhtCh+vgWusdsVuQLYZ5pmSvEnfZ8BlxiGcbFhGJuKH9fh+uSnzWnHtaZ0d+oHwG7TNN86/zuTM9WTth4I9DMMYz+wCuhiGMbymrlDKU89aftUXL1+p5Lf+cAFNXB7UoF60vYxAKZpJhYPhZkHXFJDtyjlqOO2L88JIKT4A044+/99qQX1pO1PxfIMEIFr6LvUMiVAVVA8Nvc/wHbTNN887akvgVPVe+4EvqjkVEnAAMNVzc3ANRluu2maP5umGVP8+BL4DrjSMIymxZ8sXFm8DcMwXgSaAI/V1P3Jb+pLW5um+S/TNFuaptkeGATsMk1zSE3dp5ytHrW9CXwFDCk+33BgWw3copSjvrQ9cBjoYRhGRPH5RuCalyC1xA1tX6biv/tlQGw1rinnob60fXEs9+CaG3iLaZrOc7kfqSazHlRiqO8PXG9ATVzDETYVP0bhGrO7FNhd/DW0eP/muD7hywTSi78PLn7uOWAHkADMBHzKuebdwJ7ix++Lt7UujmP7aXHc4+7XpzE96ktbn/F8e1QFzqPaHmgHrCiOZSnQ1t2vT2N+1LO2v6/43/h4XIlwmLtfn8b8cFPbrwRSgLzi468q3t4R1wT4Pbh6fss8Xo9G2fZFQOJpcfzd3a9PY38YxS+8iIiIiIhIo6chcCIiIiIi4jGUAImIiIiIiMdQAiQiIiIiIh5DCZCIiIiIiHgMJUAiIiIiIuIxlACJiIiIiIjHUAIkIiIiIiIeQwmQiIiIiIh4DCVAIiIiIiLiMZQAiYiIiIiIx1ACJCIiIiIiHkMJkIiIiIiIeAwlQCIiIiIi4jGUAImIiIiIiMdQAiQiIiIiIh5DCZCIiIiIiHgMJUAiIiIiIuIxlACJiIiIiIjHUAIkIiIiIiIeQwmQiIiIiIh4DCVAIiIiIiLiMZQAiYiIiIiIx1ACJCIiIiIiHkMJkIiIiIiIeAwlQCIiIiIi4jGUAImIiIiIiMdQAiQiIiIiIh5DCZCIiIiIiHgMJUAiIiIiIuIxlACJiIiIiIjHUAIkIiIiIiIeQwmQiIiIiIh4DCVAIiIiIiLiMbzcHUBVhIeHm+3bt3d3GDUmJyeHgIAAd4chdUBt7bnU9p5Lbe+51PaeS21fP2zcuPGEaZoRle3XIBKg9u3bs2HDBneHUWOWL1/OkCFD3B2G1AG1tedS23sutb3nUtt7LrV9/WAYxoGq7KchcCIiIiIi4jGUAImIiIiIiMdQAiQiIiIiIh6jQcwBEhEREZH6x263c+jQIfLz890dils1adKE7du3uzsMj+Hr60vr1q2x2WzndLwSIBERERE5J4cOHSIoKIj27dtjGIa7w3GbrKwsgoKC3B2GRzBNk9TUVA4dOkSHDh3O6RwaAiciIiIi5yQ/P5+wsDCPTn6kbhmGQVhY2Hn1OioBEhEREZFzpuRH6tr5/s4pARIREREREY+hBEhERETqhGmavPTNNmas3ufuUKQRsVqtxMTE0KtXL6699lrS09MrPSYwMLDC59PT03nvvfdKfj5y5AixsbHnHavT6eSRRx6hV69e9O7dmwsvvJB9+1x/Dy+//PJ5n78qzry35cuXM3r06HM614wZM3jooYeqdcxdd93FggULzul6NUUJkIiImxxIzeF3/1pDem6hu0MRqRNvL93Dhyv38cXmI+4ORRoRPz8/Nm3aREJCAqGhobz77rvnfc4zk4SWLVvWyJv2uXPncuTIEeLj49myZQsLFy4kJCQEKD8BMk0Tp9N53tc+5cx780SqAici4iYrdqWw8cBJElNy6NfO293hiNSqLzYdZsoPu/CyGJzILnB3OFILnvtqK9uOZNboOXu0DOaZa3tWef+BAwcSHx9f8vPrr7/OvHnzKCgo4IYbbuC5554rtX92djbXX389J0+exG638+KLL3L99dczadIkEhMTiYmJYcSIETz44IOMHj2ahIQELr74YqZPn07Pnq64hgwZwvPPP0+/fv14+OGH2bJlC0VFRTz77LNcf/31pa539OhRWrRogcXi6oNo3bo1AJMmTSIvL4+YmBh69uzJSy+9xMiRIxk6dChr167l888/Z+fOnTzzzDMUFBQQFRXFf//7XwIDA2nfvj133nknX331FXa7nfnz59OtWzdSUlK49dZbSU1N5cILL2Tx4sVs3LjxrHu75ppryM7OJjY2loSEBPr168esWbMwDINJkybx5Zdf4uXlxZVXXskbb7xR7mt/1113ERwczIYNGzh27BivvfYasbGxmKbJww8/zI8//kiHDh0wTbPkmI0bN/KnP/2J7OxswsPDmTFjBhEREQwcOJDXX3+dIUOG8OSTT2KxWHjppZeq/HtQGfUAiYi4SWJKDgD5doebIxGpXfl2B3//Yiv92zXltovbkpJVUOpNkEhNcDgcLF26lOuuuw6AJUuWsHv3btavX8+mTZvYuHEjK1asKHWMr68vCxcuJC4ujmXLljFx4kRM0+TVV18lKiqKTZs28frrr5c6Zty4ccybNw9wJTRHjhyhb9++vPTSSwwbNoxffvmFZcuW8cQTT5CTk1Pq2LFjx/LVV18RExPDxIkT+fXXXwF49dVXS3qyZs+eDcDOnTu54447+PXXXwkICODFF1/khx9+IC4ujv79+/Pmm2+WnDc8PJy4uDjuv//+kiTlueeeY9iwYcTFxXHDDTeQlJRUcq0z7+3XX3/lrbfeYtu2bezdu5fVq1eTlpbGwoUL2bp1K/Hx8Tz11FOVtsHRo0dZtWoVX3/9NZMmTQJg4cKF7Ny5ky1btvDhhx+yZs0awLWG1MMPP8yCBQvYuHEjd999N3/729/w8vJixowZ3H///Xz//fcsXryYZ555ptJrV4d6gERE3GRPcjagBEgavx+2Hycjz86jV3Rm25FM8u1OcgodBProbUhjUp2empp0qudk//799OvXjxEjRgCuBGjJkiX07dsXcPX27N69m8GDB5cca5omf/3rX1mxYgUWi4XDhw9z/PjxCq83duxYRowYwXPPPce8efO46aabSq735ZdfliQg+fn5JCUl0b1795JjW7duzc6dO/nxxx/58ccfGT58OPPnz2f48OFnXaddu3YMGDAAgHXr1rFt2zYuvfRSAAoLCxk4cGDJvjfeeCMA/fr147PPPgNg1apVLFy4EICrr76apk2blntPF110UUlv1KnXcsCAAfj6+nLPPfdwzTXXVGme0JgxY7BYLPTo0aPkdVyxYgW33HILVquVli1bMmzYMMCV4CUkJJS0l8PhoEWLFgD07NmT8ePHc+2117J27Vq8vWt2lIT+5RERcZPEFFcClKcESBq5+RsO0bKJL5dEhZOc6Rr+lpJVUK0E6GhGHrH/WsuM319I52ZacFJ+c6rnJCMjg9GjR/Puu+/yyCOPYJomTz75JPfee2+5x86ePZuUlBQ2btyIzWajffv2la4v06pVK8LCwoiPj2fu3Ln8+9//BlzJ1KeffkrXrl0rPN7Hx4eRI0cycuRImjVrxueff15mAhQQEFDyvWmajBgxgk8++aTcc4KrIERRUVHJMVV16vjTz+Hl5cX69etZunQpc+bMYerUqfz4449VPs/p1y+rbLVpmvTs2ZO1a9eWea4tW7YQEhJSaUJ6LjQETkTEDbILijia4fpPNt9ec5NbReqboxl5rNidwu/6tcZqMYgIcr1BSsmq3jyg9fvSOJyex45jWbURpjQCTZo04e233+aNN97Abrdz1VVXMX36dLKzXR82HT58mOTk5FLHZGRkEBkZic1mY9myZRw4cACAoKAgsrLK/10bN24cr732GhkZGfTu3RuAq666infeeafkjf+p4W2ni4uL48gRVxEQp9NJfHw87dq1A8Bms2G328u83oABA1i9ejV79uwBIDc3l127dlX4egwaNKhkqN6SJUs4efJkle7tlOzsbDIyMhg1ahRvvfUWmzZtqvSYsgwePJg5c+bgcDg4evQoy5YtA6Br166kpKSUJEB2u52tW7cC8Nlnn5GamsqKFSt45JFHqlTZrzqUAImIuMHe4t4fUA+QNG6fxR3GNCG2n2t4zakEqLqFEE4lPrmFRTUboDQqffv2pU+fPsyZM4crr7ySW2+9lYEDB9K7d29iY2PPeuN/2223sWHDBvr378/s2bPp1q0bAGFhYVx66aX06tWLJ5544qzrxMbGMmfOHMaOHVuy7emnn8ZutxMdHU2vXr14+umnzzouOTmZa6+9ll69ehEdHY2Xl1dJGekJEyYQHR3NbbfddtZxERERzJgxg1tuuYXo6GgGDBjAjh07KnwtnnnmGZYsWcIFF1zAokWLaNGiBUFBQZXe2ylZWVmMHj2a6OhoLr/8cqZMmVLh9cpzww030LlzZ3r37s3999/P5ZdfDoC3tzcLFizgL3/5C3369CEmJoY1a9Zw4sQJJk2axH/+8x+6dOnCQw89xKOPPnpO1y6P0RAmIfbv39/csGGDu8OoMcuXL2fIkCHuDkPqgNrac1XW9p/FHeJP8zYD8NQ13bnnso51FJnUtsb4d7/tSCa/7E/jzkvaV+s40zQZ+sZyIoN9mXeva75CSlYBF770A89d17Na5/v9f9ezbGcKT4/uwR8GdahWHHWlMbZ9ZbZv315qjounysrKIiiofg3NLCgowGq14uXlxdq1a7n//vvPuRenPirrd88wjI2mafav7FjNARIRcYPElGysFgOH0ySvUD1AUn/l2x08+L849p3IYWSv5kQG+1b52A0HTrI/NZcHh3Yq2RYa4I3FOI8eoAL1AIlURVJSEmPHjsXpdOLt7c2HH37o7pDqDSVAIiJukJicQ7swf5JSczUETuq195Ynsu+Eq5TvmsRUxvRtVeVj5284iL+3lVG9W5Rss1oMQgN8qjUHKD23sGTOXLaGwIlUSefOncuchySaAyQi4hZ7UrLpFBGIn82qIghSb+1JzuZfy/cwOroFIf42Vu05UeVjcwuL+Cb+KNf0bkHAGdXeIoKqlwCdXvggt0AfGIjI+VECJCJSx+wOJwdSc4iKDMTHZlUPkNRLpmnyt4Vb8LNZeebangzsGMaaPSeqXFr32y3HyCl0MPbCNmc9FxHkU60hcDuOZgLgZ7OSoyFwInKelACJiNSxpLRc7A6TqIhA/LwtFCgBknpowcZD/LwvjSdHdSciyIdLO4VzJCOf/am5VTp+/oaDdAgPoH+7sxdfDA/0rnYPUFN/G21D/clWAtRgJaYl8sA3DxD8SjCW5ywEvxLMA988QGJaortDEw+jOUAiInXk16STvLtsT8kbv06Rgfh6qQdI6p+0nEJe/nY7/ds15eb+rh6cSzuFA7B6zwk6hAdUdDhJqbn8vC+NJ67qWuYCiK4eoEJM0yzz+TNtP5ZFt+bBFBQ5yFXRkAZp0e5FxM6Pxe6wY3e61rrJKsxiWtw0Ptr8EQtuWsDIziPdHKV4CvUAiYjUgYxcO/fPiiMuKR0Mg+HdIunWPAg/byv5SoCknnnpm+1k5Rfx8o29sVhcCUr7MH9aNvFl2Y5kJi/ZyfVTV5GZX/aijQs2HsRiwI0XlF0wISLQh0KHk8y8yntzHE6TXcey6NYiiAAfL/UANUCJaYnEzo8l155bkvycYnfaybXnEjs/9px7ggIDA2siTPEg6gESEakDz3yZQEp2AQsfuITo1iEl2+uiB8jpNEvexIpUZk3iCT6NO8SDQ6Po0uy3dU0Mw+CSTuEs2HiIpTuSAYg/mMGgzuGljnc6TT6NO8ygzhG0aOJX5jVOLYaakp1PE39bhfEcSM0hz+6ge/Ngjqbnczwz/3xuT9xg8trJ2B1lJ8un2B12pqybwtRRU+soKvFk6gESEall38Qf5fNNR3h4WKdSyQ+Ar3ftVoFbuTuF6OeWcDQjr9auIY1Hvt3BUwsTaBvqz8PDOp/1/C0XtWVwlwim3toXgF3Hs87aZ01iKofT87ipX+tyrxMRWJwAZRVWGM+KXSncMX09FgMuaNeUAB8vclQFrsGZFT/rrJ6fM9mddmbGz6yxax44cIDhw4cTHR3N8OHDSUpKAuCuu+7ikUce4ZJLLqFjx44sWLAAAKfTyQMPPEDPnj0ZPXo0o0aNKnlOGh8lQCIitSg5M5+/fb6FPq2blFoM8hRfL0utDYEzTZMp3+8iu6CIfSk5tXINaVz+/dNe9p7I4cUxvfC1Wc96vl+7pnx890Vc09tVFnt3cvZZ+8zfeJBgXy9G9GhW7nXCS3qAyi+E8OOO49wxfT3eXhbmTBhIp8hAAnzsXRboAAAgAElEQVSs5GgdoAYnu/Ds35Pz2a8qHnroIe644w7i4+O57bbbeOSRR0qeO3r0KKtWreLrr79m0qRJAHz22Wfs37+fLVu2MG3aNNauXVtjsUj9owRIRKSWmKbJ/30aT77dwZs3x2Cznv1Prp937Q2BW78vzTXnCEjLrfiTdhGARQlHuSQqjMFdIirczzAMukQGsfuMHqCMPDuLE45xfUyrMhOoU071AJ2ooBLcp3GHCQ/04dtHLuOiDqEAxT1ASoAamkDvqs3Rqep+VbF27VpuvfVWAMaPH8+qVatKnhszZgwWi4UePXpw/PhxAFatWsVNN92ExWKhefPmDB06tMZikfpHCZCISC2Z/XMSy3em8OTI7kRFlP0fu2sh1NpJgN5bnoi/t+tN6MncioefiAAczcgv93f1TJ2bBbLreFapdYG+jj9CQZGTm/qXP/wNoImfDS+LUW4PUL7dwfIdyVzZs1mpRCrA24rdYVJQpGFwDcnt0bdjs1Q818tmsTE+enytxXB6tUEfH5+S70/9/lZ1fStpHJQAiYjUgmM5Tl76ZjuXdQ5n/IB25e7na7OSVwtlfbceyeCnXSlMGNwRgJM56gGSiuUWFpGRZ6dFiG+V9u8cGUhmflGp9XzmbzhE12ZB9G7VpMJjLRaD8ECfctcCWr3nBDmFDq7u2bzU9gAfV+2mXM0DalAmDpyIzVpJAmS18fiAx2vsmpdccglz5swB4P/ZO/PwKMtz/3/e2TMz2TdCAgSSsBNAEaRiBXdaXFoBW4tarcW6tKceTu1irdpz7HKq8rOl2lqtWlGr4lFqFRdUVBTZIYQ1BEIIZCH7JJPM+vz+eGcmezITMslM8nyuK9dk3m2emTfz5v0+931/7xdffJEFCxb0uv2CBQt4/fXX8Xq9VFZWsmnTpgEbiyTyCKsAUhTlHkVR9iuKUqgoysuKopgURRmvKMpWRVGKFEV5RVEUQzjHIJFIJION2+PlbwUO9FqFPyyd2asDm0mvpdU98CYIT24qxmrUccsF44k16qiVAkjSB6frVXe10T04t3XG7xB3pFKt2zhaZWPPyXqWzckKqreP2guoewH0bmEFsSYd509I7rDcYlAFkLTCji5yknJYt2wdZr25SyRIr9Fj1ptZt2wdOUk5/Tq+3W4nKysr8PPYY4/xxz/+kWeffZb8/HxeeOEFHn/88V6Pcd1115GVlcX06dO5/fbbmTdvHvHxvQt5SfQSNhtsRVEygR8BU4UQLYqivAp8C/gasFoI8U9FUf4CfA94MlzjkEgkksHm6c3HKW7w8vi38hkV3/tsukmvwen24vEKtANkVV1S3cw7+8pZ+dUc4mP0JFoM1MkaIEkf+J0CM/r4m/WTFxBANhbkpfDajjJ0GoVrZ3ff+6czqbFGyhu6Wlq7PV42Hqzk0inpGHQd52kDESDZDDXqWJy3mIIfFLD6y9W8UPACTc4mrAYrN+bfyD3n39Nv8QOqg1t3fPTRR12WPffccx2eNzWpAl6j0fDII49gtVqpqalh7ty5zJgxo99jkkQ24e4DpANiFEVxAWagHLgYuMG3/nngQaQAkkgkw4gPDlQyIV7DNbP6vhGM8dU3ONwezIaBuST/9dNj6LQabl2QDeATQLIGSNI75f4IUEJwEaAUqyHgBOf2ePm/3adYNDmNFKux752BsUlmth2vRQjRIWK0raSWOruLKzqlvwFYjOr3RUaAopOcpBzWfG1NxPb6WbJkCfX19TidTu6//35Gjer6NygZHoRNAAkhTimK8ghQCrQA7wM7gXohhP/KVQZ0e4egKMpKYCVAenr6sMrFbGpqGlbvR9Iz8lyPTI5X2smL8wZ17k+eUIXJxk2fEWc4+whQXauX17a3cGGWjgM7v+QAIFpbKW0Q8m9xkIjW7/0XR50owOE9WykOMhqZZvSw40gZv/hHOWdsLqaZ6oN+765aF00ON/96fxPxxrbXe+GAA4MGlMqDbKo+1GGfI3Vq5GfL9l3YjvfsMjdUROu5Pxvi4+Ox2br2g4pG3nrrrQ7PQ3lfHo9n2HwO0UJra2u/v2/hTIFLBK4BxgP1wGvA4m427dZ2QwjxFPAUwJw5c8TChQvDM9AhYNOmTQyn9yPpGXmuRx5uj5f69zaQHmsI6txXbT8JBws4d+75ZAY5894bv3nnIF6O8eC3FjAu2QLAv6r2sPVYrfxbHCSi9Xu/obqAlNgqLr04ePvfD+r28fquMkqOurly2ij+Y9k5QdX/AIhDVbx4aDuZk2YyJ1u1ufZ6BT/74iMWTUnmikvmdNkn7XQjbP2M3MlTWTg9I+hxDhbReu7PhoMHDxIbGzvUwxhybDab/BwGGZPJxOzZs/u1bzhNEC4FjgshzgghXMD/AV8BEhRF8QuvLOB0GMcgkUgkg0qlzYFXQJIpuJtAo169DIfqBLduZxnPf1HSYVmD3cWLX55gSf7ogPgBSDTLGiBJ35xuaAm6/sdPXpqVVpeXRLOB335zRtDiByA7Rf0bLamxB5YVnGqgorGVK6d3n3rUlgIna4AkEkn/CacAKgXOVxTFrKhXxEuAA8DHwFLfNjcD68M4BolEIukXhacaWPz4Z5ystfe9cTtO16uF5MlBCiB/DVCovYD+9FERD799kCpbWxH5P7aU0Oz0cMfCjsXESRYDdqcnbP2GJMOD8obWkAXQnOwkzAYtjy6fSaIlNFPXzIQYtBqFEzXNgWXvFlag0yhcPCm9233aTBBkDVBUUlwMd94JcXGg0aiPd96pLpdIBpGwCSAhxFZgHbAL2Od7raeAnwL/qSjKUSAZeCZcY5BIJJL+IITgwX/t52B5I89sPh7SvgEBFBPc5TXGELoAqmxs5USNHafHy9otJwA1gvTsFyUsmpTKlIy4DtsnmtUb03pphCDpASEE5fUtZARpge1nemY8hQ9ewYV5qSG/pkGnITMhJhABEkLw3v4K5uckE2/uvmeMtMGOYjZsgPx8ePppsNlACPXx6afV5Rs2DPUIJSOIsPYBEkI8IISYLISYLoS4UQjhEEIcE0LMFULkCiGWCSG6bwIgkUgkQ8R7+yvYcaKOjHgTr+44SUNL8MLhlE8ABZsC5+9y3xKCANp2vBaAcclm1m4tpdXl4U8fFVHb7OTORbldtk+yqDeTsheQpCcaW900Oz2MDrIJant663PVF+OSzZRUqxGgoqomjlc395j+BqptvEaRjVCjjuJiWLoU7HZwdbqeulzq8qVLzyoS9PDDDzNt2jTy8/OZNWsWW7duJTs7m+rq6n4fc8+ePbzzzjv93l8SuYRVAEkkEkm04XR7+d2GQ0xMt/LUjXOwOz38c1tp0Pufrm8hwazHpAs1BS74ZqjbS2oxG7Q8fO0MapudLP3LFzyxqZhvzM7kPF8xeXsSfBEgWQck6Ym2HkBnb8QRCtnJFkpqmhFC8G5hBYoCl03tPv0NQFEULEadjABFG48+2lX4dMblgtWr+3X4LVu28O9//5tdu3ZRUFDAxo0bGTNmTL+O5cftdksBNIyRAkgikUjasaGwnJIaOz9bPJkZWfGcPyGJ578oweXpWaC8sbuMnSfUqMzp+lZGh3ATafKbIIQYATp3XCIX5CYzNSOOwlON3L0ol0eXzex2+ySLFECS3mnrARR6BOhsyE6xYGt1U2d38W5hBeeOTSQttvcxWAw67E43bo+X6/+6hRe+PDFIo5X0m7VrgxNAL7zQr8OXl5eTkpKC0aj2oEpJSWH06NEA/OlPf+Kcc85hxowZHDqk2qrX1tZy7bXXkp+fz/nnn09BQQEADz74ICtXruTyyy/npptu4le/+hWvvPIKs2bN4pVXXunX2CSRiRRAEolE0o4dJXVYjToWTkwD4LYFEzjd0MqGwoputxdC8Ks39/P/NhYBagQo2EaS0JYCF2wNUIPdxeFKG+dlJ6EoCmtumM3a783jv66Y1GMqkr8GqE6mwEl64PSQRYDMAHxWdIYD5Y29pr/5sRi1NDs8nK5vZevxWu5/szDkWj3JINPUNLDbdeLyyy/n5MmTTJw4kTvvvJNPPvkksC4lJYVdu3Zxxx138MgjjwDwwAMPMHv2bAoKCvjNb37DTTfdFNh+586drF+/npdeeolf//rXXH/99ezZs4frr7++X2OTRCZSAEkkEkk79pbVk58VHxATF09OY3yKhWc2H0eIrm3Lapqd2Bxudp2ow+3x+gRQ8LPooQqgHSdqEQLmjldT3SakWlmQl9LrPglmfw2QNEGQdE95fSsaBdJijYP6un679qc+PQbAFdOCEUBqCtyJWrV2aFJ6LP/97wP8zXcMSQRitQ7sdl12s7Jz506eeuopUlNTuf7663nuuecA+OY3vwnAueeeS0lJCQCbN2/mxhtvBODiiy+mpqaGhoYGAK6++mpiYgZ3IkAy+EgBJJFIJD5aXR4Oljcya0xCYJlGo3DrBdnsPVnPrtK6Lvv4C7ibnR62ldTS2OoOKQIUqg32tpJa9Fqlwxj7Qq/VEGvSyRQ4SY+cbmghPc6ETju4twVjkmJQFNh/upGpGXGMSTL3uY8/Be6Ezz3u6Zvn8PUZGTz8zkH+8om0U45IVqwAfffOfgH0evCJkv6g1WpZuHAhDz30EGvWrOH1118HCKTFabVa3G61dqy7ySx/DyuLxdJlnWT4IQWQRCKR+DhQ3ojLI5jZSVxcd24W8TF6nv6sa5pN+yaO/9qj9nXuTwpci7NvEwRbq4v3CivIz0oI7BcsSRbZDFXSM+X1ofcAGgiMOm2gZi6Y9DdQU+CaHB5Ka+0BK+3HvzWLq2aO5ncbDvHEpqPhHLKkP6xaFZwAuueefh3+8OHDFBUVBZ7v2bOHcePG9bj9V7/6VV588UUANm3aREpKCnFxcV22i42NxWaz9WtMkshGCiCJRCLxsae0HqBLdMVs0PHtuWN5b39Fl8aoJdXNaDUKGfEm3tlXDkBmCClwWo2CQavp0wTB5fFy54u7KKtr4Z5LJwZ9fD+JZoO0wZb0SEVj66DX//gZn6LOuAeT/gZqCpzd6aa0xs7YJDMajYJOq2H18plcM2s0//vuYdZ8VNT3gSSDR04OrFsHZnNXIaTXq8vXrVO36wdNTU3cfPPNTJ06lfz8fA4cOMCDDz7Y4/YPPvggO3bsID8/n5/97Gc8//zz3W63aNEiDhw4IE0QhiG6oR6ARCKRRAp7y+rJiDeRHtdVwNz8lXE8/dkxnvuihPuXTA0sP17TTFZiDOeMTeSN3acANQJ0OITXNek1fabA/fKNQj4rquYPS/P7rPnpjiSLgSpba8j7SUYGZ2wO0iYNbv2Pn/k5yTjcHiamB1f/YTHqaHa4OVGrCiA/Oq2Gx5bPQqMoPPL+ESxGHbdcMD5cw5aEyuLFUFCgWl2/8IJqeGC1qmlv99zTb/EDan3PF1980WW5v+YHYM6cOWzatAmApKQk1q9f32X7zqIpKSmJ7du393tckshFRoAkEonEx96T9czM6r62JiM+hq/nZ/DK9pPYWtvMBE7UNJOdbAn039FqlD5tfDtj0mt7FUCbDlfxyo6T3LEwh2Vz+tfbIsGsp06aIEi6ocXpocnhJsU6NALorkW5vPaDrwRqMPrCYtDS5HBTWtPcQQCB+v17ZNlMzhmbwCvbT4ZjuJKzIScH1qyBhgbweNTHNWvOSvxIJP1BCiCJRCJBtYguqbF3qf9pz/cWjKfJ4Q7cWAkhKKm2Mz7FwtzxiQCMijOh7cGOuidiDD0LoFaXh/vXFzIh1cKPL80L6bjtSTLLGiBJ91Q3OQBIHWQHuP5iMepodXlpdnoYl9zVNEGrUTh/QjJHq5pwuIPvryWRSEYOUgBJJBIJavobdK3/aU9+VgJzs5N47osS3B4v1U1OmhxuxiWbyUm1kmjW96uRpEmn7bEG6E8fFXGytoWHr52BURea8UF7Ei0G7E5P0G5zkpHDGb8AGqIIUKhYDG3Z+90JIIDpmfG4vYIjFf3rKyMJje5c1SSScHK2f3NSAEkkEgnw3v5K9FqFGVnxvW5364LxlNW18P6BSkpqVAvs7BQLiqLws8WTubUfNQcmg5ZWV1cXuKJKG099eoxvnpPJ/JzkkI/bniSLrxmqjAJJOnHGpgqgoUqBCxWLsU0AjU3q3rJ42mjV0avwdMOgjGkkYzKZqKmpkSJIMmgIIaipqcFk6r9zpTRBkEgkwxqPVyCE6LW/SVmdnXU7T3L9eWOwGnu/LF42NZ2xSWae2Xycb52n1uOM9zVzvP68sf0ao0nX1QVOCMF9bxZiMeq472tT+nXc9iQGmqE6h8ztazhyxubApNcQa+rD4jeCib4UODUSqihqH6HuGJtkJtakY78UQGEnKyuLsrIyzpw5M9RDGVJaW1vP6oZcEhomk4msrKx+7y8FkEQiGbYIIVjyp80crbIxJtFMdoqF7GQL41PU36dmxJFsNfLnj4+ioHDXotw+j6nVKNxyQTYPvXWAGL0WrUYhM/HsBEWMQUtdJ4vq13aWse14Lb+/bgbJAzAzn2RRj1HdJCNAA0VpjZ2r/7yZy6ak84dlM4d6OP3GHwFKthqGeCTB4U+By4gz9ZgWqigKUzPiKDzVOJhDG5Ho9XrGj5due5s2bWL27NlDPQxJkEgBJJFIhi3bS+o4WN7IYl+DxePVzWwprglEWwxaDUvyM/jX3tPcMG9s0JGRZXPG8NgHR9h8tJrsZDP6XqJLwRCj13K6XQSottnJb985yJxxiSw7t3+ub53JTVMthg+VN3LRxNQBOeZIptnh5vv/2EG93RWooYlWqpscJJr1Z/13PFiYfRGgMUnd1//4mTY6npe2ncDjFSEbk0gkkuGNFEASiWTY8uqOk1iNOh5dPhOzb9ZYCEFlo4Pj1c28s6+cV3ecRKNRuGNh8DasVqPaGPWpT4+RndJ9DUIoqDbYbTVAv33nILZWN7/55gw0A3TjlmQxkJUYQ8EpmRJ0tni9gv98dQ9FVTZSrEaaHe6hHtJZccbmiJr6HyCQptqTAYKf6ZlxtLq8HDvTRF567GAMTSKRRAlSAEkkkmFJk8PN2wXlXDt7dED8gJoaMyrexKh4E/NzkvnxpXnUt7hCrou5+SvZPLP5ODmpwTVv7A2Tvs0FbuuxGl7bWcYdC3OYOMA3bflZ8ewrkwIoFIpri3l0y6OsLVhLk7MJq8HKjMQllJy4mF9//RK2FFdzuj66G8xWNzmjpv4H2kwQxiX3PvkwbbRqaFJ4ukEKIIlE0gEpgCQSybDk7YLTtLg8fTYOTbYa+1Vjk5kQw6u3n9/nTVgwmPQaWp0eXB4v971ZSFZiDD+6uP89f3piRmYC7+yroN7uJMEcHfUeQ8mGog0sfW0pLo8Ll1dtImtz2vii4lV0MW+QkfY65pMZNDujPwLUm/17pJGZEMPc8Ul9pnLmpFow6jTsP9XIN2RphkQiaYcUQBKJZNgghGD1B0coq2thW0ktuWlWZofxxu7ccUkDcpwYvZZWt4ddJ+o4WtXE49+aRYyh/z1/emJGpjojvu9UAxfmyTqg3iiuLWbpa0uxu+xdVyoe3MLDsnXLuHH8azQ7oltMVjc5oioCZNJrefX2+X1up9NqmJwRF7QVdnfRvhX5K1g1fxU5ScGnyEokksgnOioeJRKJJAhO1bfwx4+O8smRM2gUhbsX5aIokV/8bNJrcXkEXxTXoCiEzaSgvQCS9M6jWx7F5XH1uo3L42J33VrsURwBana4sTs9UVUDFAq5qVaOVzf3ud2Gog3k/yWfp3c9jc1pQyCwOW08vetp8v+Sz4aiDYMwWolEMlhIARQGPF7BHWt38uLWE0M9FIlkRHGw3AbAUzfN4dN7F3Ht7MwhHlFwxOjVaM8nR84wKT02bOlp8WY945LNsg4oCNYWrA2kvfWEy+uioPYt7E4PXm90NoGMth5AoZKdbKay0UFrpz5b7Wkf7et8zl1eF3aXnaWvLaW4tjjcw5VIJIOEFEBh4NnPj7OhsILNRdUU1xZz59t3EvfbODQPaYj7bRyrj6yWF9IooaSkBEVR2LFjx1APBYDs7GweeeSRoR5GxHKwXO35MWlUdBU8m/TqpXhvWT3zxg9MWl1PzMiMp0AKoD5pcjYFtZ3Do0YX7L3cYEcy/h5AKVHSAyhUxvqc4kpru0ll9BFstG/1l6sHdGwSiWTokAJogDlZa+fR948AsL/2k25D6m+Xvy1D6iFw6tQpVq5cSVZWFgaDgczMTL7//e9TVlY21EOLSBRFYd26dUM9jCHhUEUj45LNAZvcaMHkiwAJAfMmJIf1tWZkxnOqvoWaKO9dE26shuDc/Uw61QQjWq2wh3sEyG9ScqKmZwEUbLTvhYIXBnRsEolk6JACaAARQvCLN/ah1SjkZjTxed193YbUPXhkSD1Ijh8/zpw5cygsLOT555/n6NGjrF27lv3793PeeedRUlISttd2Op1hO7YkPBwstzFlVNxQDyNk2hsezA13BChL1gEFw4r8Feg1+l630Wv0LMy6DoheAeSPAKUO0xqgcb5mqSdqeq4DCjbaF+x2Eokk8pECaAB5fdcpPiuq5qdXTqJG+T+8yJD62XLXXXeh0WjYuHEjl1xyCWPHjmXRokVs3LgRjUbDXXfdxV//+lfS09NxuzvegNxwww1cc801gedvvfUW5557LiaTifHjx3Pfffd1EDnZ2dk8+OCD3HrrrSQkJPCd73wnsO7IkSMsWLAAk8nE5MmTef/99zu81qeffsq8efMwmUykp6dzzz33dDj2woULufvuuzvs893vfpclS5YEnjc3N3PTTTdhtVpJT0/nt7/9LUuWLOG73/1uh/1aW1u5/fbbiYuLIysriz/84Q8d3gPAsmXLUBQl8HwkYHe6KalpZkpG9Akgk04VQDmplrAXo4/13RBW2WQEqDdWzV+FXtuHANLqWT75BwDYndGVAudPz/7+h9M5YbqK3D+ncefbdw67SbkEs55Yk67XFLhgo31e4Q2ksg/Hz0oiGUlIATRAnLE5+O9/H2DOuES+M28cBxveBnr/hyhD6r1TW1vLu+++y1133YXZ3LHjt9ls5s4772TDhg0sX76c+vp6Nm7cGFjf3NzM+vXrWbFiBQDvvfce3/nOd7j77rvZv38/f//731m3bh2/+MUvOhz3scceY/LkyezYsYPf/OY3geX33nsvP/rRj9izZw+XXXYZ11xzDadOnQLUFL3Fixcze/Zsdu/ezTPPPMPLL7/Mz3/+85De76pVq/jkk0944403+Oijj9i7dy+fffZZl+1Wr17NjBkz2LVrFz/96U+599572bJlCwDbt28H4G9/+xvl5eWB5yOBQxU2hIApGdFV/wNtEaBwp78BWHxNYe1RGrEYLHKScli3bB1mvRlER0tyvUaPWW9m3bJ15CXnAmrj3WihveOZw9MMyvB1PFMUhexkCyW9pMAFE+3zI93hJJLhgRRAIfDpkTPM+Z+NHK6wdTE3yFydTInnj9xxqQWNRsHh7fli2x4ZUu+ZoqIihBBMmTKl2/VTp05FCEFRURFf+9rXePHFFwPr3njjDXQ6HVdddRUADz/8MD/5yU+45ZZbyMnJYdGiRfz+97/nL3/5C0K0uTdddNFF3HvvveTm5pKX19aI8o477mD58uVMnjyZxx9/nDFjxvDkk08C8MQTT5CRkcETTzzBlClTWLJkCb/73e9Ys2YNra3BdYhvamri73//O7///e+57LLLmDZtGs888wwaTdev6OWXX87dd99Nbm4uP/zhD8nNzeXDDz8EIDVVtU9OSEhg1KhRgefDGf938YJ/jOWE6SquWz8x6mZnY02qKAm3AQK0ia3mKItYDAWL8xbzr6VfYPVcSYzOikbREGeMY+W5Kyn4QQGL8xZj8dWbRYsV9kh0PBubbKa0lxS4YKJ9nRmun5VEMlKQAigEzAYt1U0O1h96u4u5gUs006R9j6tf+wobijYQowuuO3ywofeRTE99XPzCRVEUVqxYwZtvvondrgrPF198kaVLl2IymQDYuXMnDz/8MFarNfBzww030NzcTEVFReCYc+bM6fa15s9va7qn0WiYN28eBw4cAODgwYPMnz+/g1hZsGABTqczECXqi+LiYlwuF3Pnzg0ss1gsTJ8+vcu2+fn5HZ6PHj2aqqqqoF5nuNF+JrvV0wSKoMkVfbOzMzLjefI75/D1GRlhfy2jToNWo0TNDftQ09CUTLLrDvbcdhrPrzw0/KyBNV9bE2iMafEJyiZHdAjKkeh4Ni7JTFldC26Pt9v1OUk5/H7hcyjCiFbpZKDSh7v5cPusJJKRQtgEkKIokxRF2dPup1FRlB8ripKkKMoHiqIU+R4TwzWGgSY9zoRLKedXm2/tdvbMizswIzQ/4/IuaROd0Wv03Jh/YziHHNXk5eWhKAr79+/vdv3BgwdRFIWcnByWLFmCTqdj/fr1VFVVsXHjxkD6G4DX6+WBBx5gz549gZ+CggKKioo6REksluCEa3uEED2KNP9yjUbTIdIE4HK1/f20F3N9odd3nKlUFAWvt/t/7MOZ4TSTrSgKi2dkoNOGf05KURTMBi3NUXLDPtTsO9WASa8hJ7X7yapABChKUuBGouPZuGQzbq+gvKHniHzp6YlM8D7BrbNuI84Yh0bRMKEW1rwN9b8Bz4Pq45p/w4Tatv2G22clkYwUwvbfVghxWAgxSwgxCzgXsANvAD8DPhRC5AEf+p5HBamxRhp1bwQ1e2bQaVHo3YpXr9Vzz/n3DOQQhxVJSUlcccUVPPHEE4HIjh+73c6f//xnFi9eTFJSEkajkaVLl/Liiy/yyiuvMGrUKC666KLA9ueccw6HDh0iNze3y49O17dl8pdffhn4XQjBtm3bAql5U6dOZcuWLR1EyObNmzEYDIwePRpQU9PKy8s7HHPv3r2B33Nzc9Hr9Wzbtq3DeywsLAzmo+qAXq/H4xn+N7cjcSZ7oLAYdDICFCSFpxqYmhGHVtP95IS/pkXICOgAACAASURBVCpaUgpHnONZcTEXPf4g+1YvIyvFCnFxcOedUNw2MdLY6uKtveUsnTmHp65+koafNeA5798UPAnf3wXxTvVmKd6pPi94Eq4sanuJYfNZSSQjCKXzrHRYXkRRLgceEEJcoCjKYWChEKJcUZQMYJMQYlJv+8+JjRU7zj037OMMhk0lnwF9z7ZrNVo0niw8mpMIRIfZfwVQNBqmpU4jOSb8Of/RTHFLC1/ZvZucmBj+JzubvJgYiltbue/4cY61tvLFrFmMj4kB4JP6ei4tKGBiTAxLkpP5/YQJgeO8V1vLksJCfj5mDMvT0tApCoXNzWxrbOR/c9RUluwvv+TuzEz+a8yYwH4lra2M37qVLKOR1Tk5zLBYeOL0af56+jRH580jy2jklMPBxG3buDE9nf/IzORYayvfO3yY76Snc39yMgkJCfz19Gl+XFzMK1OmMMls5q+nT/NMRQUXxsfz7xkzAPjBkSO8W1vLM5MmkWEw8D+lpbxdU8M3U1J4dvLkHse4cM8eplssrPHVLE3cto2FCQn8Ojsbo6KQqA8ttz1a+Kx0Mx5v3zedWo2WC8cuGIQRdaS+vp6EhIRBf91g2HOyHotRR16aTMHtDQFsL6kl1WpkfEr30WGvgG3Ha8hKNJOVqF6LIvncR/r3ZkCprYX9+9Uofft7HUVRf6ZNg6QkKhpbKaluZnpmvNpDrKUFduyAXiLrHgW2j4ZWXcfPKpLPvSS8yHMfGSiffLJTCNF9PUM7Bqtb4LeAl32/pwshygF8Iiitux0URVkJrASYrtdTX18/KAPtm+BSjTxeD3oRS6ohD7u3mnpXHeBFo2hI1CeQZkpD69BQ74iU9xWZJAMf5ubyh8pKVhw4wBm3mxSdjsvi4ngqJ4dEh4N6h2rnmy8EGTodB+x2nsrK6vA3M0+j4ZXx4/lDZSWPnDyJTlHIMRr5dlJSYDuv10tLS0uH/Rp9Vtb3p6fzvyUlFLS0MMZg4IXsbKwtLdS3tGABXh0/ngfKy5lVUUG8VsvShATuTUzE4/FQX1/PN2Ni2J6YyC2HDgHwvZQUvh4XR43LFXi9XyYnU9faytWFhVg0Gu5ISWFWTAyK293rGN1uNw6HI7DsofR0fnn6NM+Wl5Oh11MwdWp4Ts4QE8xNnH+7obh++M99RCK8tDqckTu+CMHpAa9XoHic1Nf3HG1UFLC3tFKvqNeiSD73CfoEah01vZa2KECiPiFi30MwaBwOYg8fRhGCLrE7IUAIRGEhjZMmUd6qx6hTcLU0Ud8CMWVlGLzervu1QxEwphGOJnX8rCL53EvCizz30UXYI0CKohiA08A0IUSloij1QoiEduvrhBC91gHNmTNH7NixI6zjDBbDr624RM9uMn7ijHEkNbzEjy7OIy/dyt0v7QbgT9+eTWzdERYuXBjmkUoigU2bNvX7XDscDsaNG8dPfvITVq1aNbADGwbE/TYOm9PW93bGOBp+NvhNP8/m3Ieb5X/dggK8cvv8Prcdyewra+CqNZv5201zuGxqeo/bzf71+yzJH81/X6ualkTyuS+uLSb/L/nYXT07lZr1Zgp+UBAweohK7rwTnn4aXL2kyer1nPn2TZyX8Q0e/sZ0vjNvnLo8Lg5sfV9bGoww+lcdP6tIPveS8CLPfWSgKEpQEaDBcIFbDOwSQlT6nlf6Ut/wPUaVfdW0hK8BwZkbxJn01NmdVLdrOFjb7OxlT8lIZvfu3bz00kscPXqU3bt3c/PNN2Oz2bj++uuHemgRSTC9O6TRSPdYDNqoa9w5FDjc6mdk1PX+r9Js0NEcJSYI7fsbda5Tbd/fKKrFD8Datb2LHwCXC+tr/8Rs0HL1zNFty5uCq+mJdTI8PiuJZAQyGALo27SlvwH8C7jZ9/vNwPpBGMOAccW476OI4MwNEs166uwuzjQ50PhSjmukAJL0wmOPPcbs2bO5+OKLqays5NNPPyUrK2uohzVk7Ctr4G+fHut2XTC9O6TRSPeYjTqapQlCnzjdasqzoQ8BZI2yz3Nx3mJ2fn8PcZ4rMWq6728U9QQpYowtdq6ZNZpYU7triTW42jhhtQ6Pz0oiGYGEtQZIURQzcBlwe7vFvwNeVRTle0ApsCycYxhopqXlker8OTbL/9LqdiJo+6en1+jRa/WBGaFESwX1didmvZYUqxGXx0ttswNkjZykG2bPnk2kpHpGCo9+cJhNh89ww7yxAbthP/6Z7Gv++U3VDU5pi2h0/i5KOmIxaLFLG+w+cfgEUJ8RIOPZ24q7PV7KG1rJTIhB04PjXGcaWlzUNTvJ7sGgoTeEO50E5w94/Jt/4ZpZmSHvH/FYrUGlsTUbYvj23LEdF65YEVT6nPamm3teL5FIIpqwRoCEEHYhRLIQoqHdshohxCVCiDzfY21vx4g00uNMxHjnsO4bn5Om+ToGjaXH2bNEs4E6u5MzTQ5SrEaSLAaZAieRBEmD3cXmomoAjp3pvu5ucd5i5lueJcd8baB3x7CbyQ4DZmmDHRRtKXC9pz2fTQSorM7O8r9sYeoD73Hh/37MWwWng973/jcLuf6pLf163X2n1H/L0zPj+7V/xLNiBfThgOnSaPlk7hXkZ3WalVy1qs990evhHhldlkiilcFygRs2pMeZANB4R2FpWclPFv6eVZd37+KdYNZzuMKGRlFIjTXS4vRQ0yQFkEQSDO8dqMDtVU1ais80MSOr641aRUMrJ6piuffK33HnwnWDPcSoxeyrAeqtia+kXQRI31cNkJaqRkev23RHQ4uLW57dTkVjKzfPH8czm49TXBVc6lazw837BypodXmptztJMBtCeu39pxqwGLSMTw49ehQVrFoFzz/faxTHpdHh+fGPu67IyYF162DpUnX/dsdwarToTUaUdevU7SQSSVQyGDVAwwq/ANpbVo/HKwJ9H7ojEAGyyQiQRBIqbxeUk5kQg1ajUHym+5vCP7x3GL1W4WvTMwZ5dNGNxajD7RU4PcHZ+o9UHK7gUuAsBh1NIZoguDxe7li7k5KaZv5647nc9/WppFiNVDS2BrX/h4eqaPWN73h1386kndl3qoFpo+ODTreLOvwixmzuGs3R63GbYvjVjQ9wyZKvdL//4sVQUAArV6qucBoNTouVl2deSeOXO9T1EokkapECKERSrAYUBXaeqAMgK9Hc47ZJFgN2p4cqm4OUWANJVimAJJJgqGt28vnRaq6aOZpxSeZuBdD2klpe31XG9y+c0K8aiJGM2aCmdMk6oN4JNgXOYgw9pfCdfeV8UVzDw9+YwVdyUgAYFW+iIshI0lt7TweEWagCyO3xcqC8kWmZcSHtF3V0I2KIi4OVK9EV7uORv/9cbXzaEzk5sGYNNDSAx8P6TQd44PI7aMwcN3jvQSKRhAUpgEJEp9WQYjWy96Ta7Kq3CFCCWZ118ngFqVYjyRY1IuQNc+8liSTaed+X/rYkP4MJqVaOdkoLcnu83P9mIZkJMdx9ce4QjTJ6sRjUm75oci4bCoJOgeuHCcKGfRWkxRpZek6by2N6nImqICJAja0uPjl8huVzxqBRQhdARVVNtLq8zOxc+zIc6SRiaGhQn/cjfS3WpH5vQo32SSSSyEMKoH6QHmfE4faiKJAR33sKnJ/UWDUFziuguY/WBBLJSOezomoy4k1MGx1HbpqVkmo77nbpWs99UcKhChu/umoqZoMsZQwVs1GNaLTIXkC9EqwLnNWgw+nxBmyz+8LudLPpSBVXTh/VIQVtVJwpqBS4D/ZX4vR4+cY5mYxJMnMsRAHkn8CbNWYECKABxO9EKQWQRBL9SAEUKsXFrHrzcfatXkbx767CkJSgdpwuLu6yqT8CBJDqqwECsDllBEgi6Y2jVU1MzYhDURRyUi04PV7K6loAqGxs5f9tLGLRpFQun5o+xCONTtoiQFIA9YbDpX4+Bm1fESD18wxWUG46fIZWl5crp4/qsDw9zki93UWrq/fjvLnnFJkJMcwek8D4FAvHe3BJ7Ik9J+uJj9EzLrnnFG5JV/zpck2tUgBJJNGOFEChsGED5Odz4SfriXW2oEGofQaefhry89X1foqLmfLfP2Pf6mUc+/1VzJs9gfP+cD9j68qlAJJIesHt8XLsTDO56Wozwpw09dFfB/Q/bx/E6fHy4NXTpINZP4kJ1ADJG7necLi9GHWaPv/OLL7PsynIlMINhRUkWwzMzU7qsNxvslPZSxSotMbOZ0XVLJ8zBkVRGJ9ioaSmGRFCavWek/XMHJMgvz8hIlPgJJLhgxRAwVJcrFpi2u3oPJ0ufi4X2O3q+uLigFBKeOkfAaGkbbKR8epa3v373SRv2zo070EiiQJKa+04PV7y0mIByElVBdDRqiY+P1rNW3tPc8dFOYwbrva9g4CMAAWHXwD1hT81KhhB2ery8NHBSi6flo6uU2RpVLxfAPVshPDy9lI0Ciw/T60dmpBiCZjtBEOzw82RSptMf+sHVqOa1SEFkEQS/UgBFCyPPtp7V2hQ1z/4YEAoKZ22V9wuzG4HV6/+dbcpcxKJRC3QBsjzRX7iY/SkxhrVmp/1hYxNMnPHQtl/42zw1wDJZqi943B7MfThAAdg8X2ewdwYf1ZUTbPTw+JurNtH+SJAPdUBOd1eXttxkosnpwfqT/0OiD01C+5M4akGvAJmjRmmDVDDSOA8yxQ4iSTqkQIoWNauDU4AvfJKn9vpnQ6YMqXH2iGJZCTjd3zzp74B5KRaWL/nFMVnmnno6mmY9H3flEp6JhABkjbYveJwe4KLAPk+T3u7iNonR86w5qOiLttu2FdOfIye+TnJXdal+yNADd0LoI0HK6lucvKdeWMDy8b7BFCwTnB7fAYII8IBboDxn2ebjABJJFGPFEDB0hRcd+7OXaO7Q/Fv113tkEQywimqtJGZENOhP0dOqhWvgMunprNoctoQjm54ICNAweFwe/u0wIa2FLjmdjfGj31whNUbiwK9hECN4HxwsJLLpqaj78ZYIdaoI0av7TEC9NLWUjITYvjqxNTAstHxMRh0Go5XB/c/am9ZPWOSYki2GoPaXtKGRqNgNeo6nGeJRBKdSAEULFZr39uESufaIYlEQlFVE7lpHb9v52UnkWDW86urpg7RqIYXZr1fAMkIUG84XN4+m6BCW2NZf1+lmhYve0/W4/EKiirbhMnnxdXYWt18bcaobo+jKIqvGWpXAVRS3czmo9Vcf94YtO2sszUahfHJluAjQKX1MvpzFliNOpkCJ5EMA6QACpYVK0Cv730bvb7vbbrD5YLVq/s3LolkGOHxCo5WNQXqf/xcOzuTHfddSlaitO0dCHRaDQadRjZC7YNgU+Csxo4phTsr24TloQpb4Pd391UQa9RxQW5Kj8dKjzN22wz1n9tPotUoLJ8zpsu68SmWoHoBrf3yBKcbWjlnbGKf20q6x2rSSRMEiWQYIAVQsKxaFZwAWr48dBHkcsELL/R/bBLJMOFUXQsOt5e89K4R186OWZKzw2LQYpc1QL0SrAucuVMK3I5KNxPTrRh1Gg6WNwKqvfv7Byq4ZEpar1Gl7pqhOt1e1u08ycWT0wJOce3JTrFQWtOxWXB7XB4vv3xzH798s5CFk1K5/ryuIkoSHBajTtYASSTDAHlHESw5ObBuHZjNXQWOXq8uX7cOHnqof1GgYGuMJJJhTFGVOlue67PAloQPs0EXkRGgjw9V8ccPi0LqaxMu1BqgIFLg9P4UOA9VtlaK6rx8fcZoJo2K5VCFKoC2Hq+lzu7iym7c39qTHm+istHR4f2/f6CC6iYnN7QzP2jPuGQzbq+gvBvzhNpmJzc+s5W1X5Zy+0UTeObm8wI1S5LQiZU1QBLJsEAKoFBYvBgKCmDlSoiLA41GfVy5Ul2+eHHvQqk3wlFjJJFEGX4L7M41QJKBx2KMvAjQu4UV3PaPHTz2wRGe/bxkqIeDwxVEClxxMZq776Jw9XLuuWIyCaNS+fX7T3B1rJ0po+I4WG5DCME7+8oxG7QsnJTa6+HSY0043V7q7G1mOi9v85kf5HW/77gkNTW0tNbeYfnB8kauXrOZXaX1rL5+Jj9fPKVD/ZAkdGQNkEQyPJACKFRycmDNGmhoAI9HfVyzRl3up71QCkYE6fVw443hG7NEEuEIIdhzsp53CytIjzMSH9OPKKokJMwGHXZX5AigDw9W8sOXd5GfFc/Fk9P47YaD7PVZNodKQVk9R6tsfW/YB86+UuB8Ta95+mmsTjuKEBjsTXxr73tkX/wVLinZSW2zk4rGVt7bX8miSWl9Wrj7U9wqfNGckupmPj9aw7fnjulRvIzpRgC9W1jBdU9+gdPt5dXb5/ON2VmhvHVJD8gaIIlkeCAFULjwC6WDB9VoUG/o9XDPPYMzLokkArn75d1c++fPOVjeyPcWjB/q4YwIzAYt9gi5kdt0uIo71u5iSkYcz90yl8eWzyQt1sSP/rkbrze0VDiXx8sNf9vKZas/5e6XdlFWZ+97px5Qa4B6ECzFxYGm151bH+i9HhS7nUt+dRdj68pZ++UJqpscLO7B/a096b5mqJU2VQC9vK0UrUZhWTfmB35GJ8Sg0yicqFHf69ZjNfxg7U7y0mN564cLmDVGur4NFFajDltrHz0BJRJJxCMFULgJtnYoR3a2l4xMth2v5e2Ccm69YDzbf3kpK78qvwuDgVoDNPQRoM1F1ax8YSe5aVb+cetc4mP0JJgN3LkohxM1dk43tIR0vP2nG2lyuFk4MZUPD1bxizcK+z02h9uLoacI0KOP9tnzTeN2873tb/Ls5yUYdRoWTeq7h9Wods1QHW4Pr+0s49IpaQFh1B1ajUJWYgwnfRGgz4tr0Cjw4m3zet1PEjpWoxoBioQaNYlE0n+kABoM2qXEuayxeFHwxMZ2rB2SSEYgQggeef8wqbFGfnLFJOJMMvVtsLAYtUPeCPXLYzXc9o/tTEixsPa2eSSYDYF1eT4jjKNVoRnEbDteA8Dvl+Zzw7yxfHmshtZ+pvr1aoO9dm3fTa9dLq478DF2p4eLJqYGZT6QFmvEYtDy9Obj/O3TY9Q2O7lh3rg+9xubbOFErWqFfbC8kfEplg7NhCUDg9Wkwyug1dW9455EIokOpAAaLHwpcdv3HGPCT99i6+5jXWuHJJIRxudHa9h2vJa7FuYQY+jbbUsycJgNukDfmqFgR0kttz63naxEM2tvm0eSxdBhvd8II3QBVMf4FAtpsSa+OjEVp9vL1uO1/Rqj6gLXw7/JIJ07zU41ghVM+huAXqvhqZvmUNvs5JH3j5CVGMOFvfQN8jM2KYZSXwrcgdONTB0dH9TrSULDLyptDpkGJ5FEM1IADTL+GW6bdJGRjHCEEDz6wWEy4k18a2739r6S8GExaGkZwgjQQ28dINlq4KXb5pFiNXZZn2QxkGQxUHxGFRpNDjfPfn4cTy81QV6vYHtJLXOzkwCYm52EQafhsyNnQh6fEMJngtCDMA/SudMVY8Fs0HLJlPSgX/uC3BTe+uECLp2Sxn9dPglNEM5t45IsNLa6Ka2xc6q+hSkZ0ko+HPgFkHSCk0iiGymABhm/AGpskbNHkpHNpsNn2F1az90X5/bpjCUZeMxG1QUuVJOBgaK8oYUFuamk9VKjkptqDUSAXt9ZxkNvHWB3aV2P2x+pstHQ4mLueFUAxRi0zM1O4rOi6pDH53CrKU49psCtWBFUc2ztzTey8T8vCjm9MzMhhqdvPo9rZ2cGtb3fCe69/RUATM2IC+n1JMEREEDdGIgcrbJxsGbo6+okEknfSAE0yMTF+MLncvZIMoIRQvDYB0cYkxTDsnNlV/qhwGzQIgS0ugf/hs3rFdTZXSR3SnvrTE5amwDaVqKmsR0709zj9tt9qW5+AQTw1YkpHK60BWylg6VPAbRqVVACSLdqFaMTYkJ67f4wLlkVQO/6BdBoKYDCgdXUvQAqPtPE0r9s4ZlCx1AMSyKRhIgUQIOMf/aoUdpoSkYw7x+oZN+pBn50cV7PLluSsGLx1VwNRR1QQ4sLj1d0qfvpTG6alTq7i5omR0Dc+FPiumPr8Voy4k1kJbYJjgt9zUM/KwotDc7hE4bGnqKTvTh8erXaQXf49EeAdpXWkWI1kBYr3d/CQXcpcFW2Vm7++zbq7S5a3NIdTiKJBuSdxyCj02owaWUESDJy8XoFqz84woQUC98IMr1HMvCYDeqN3FA4wdU0OwFItvYRAUq1APDhoSqqbOrMenEPESC3x8u247XMHZ+EorTVzEweFUtqrDHkNDiHq48IEHRseh0XBxoNxMVxesmSQXf4tBp1pFgNCAFTZPpbeCguZuz9/8W+1cu4bMZoiIvDefsP+MUf3qSmyclXJ6bS6kZaZEskUYAUQENAjE6RNUCSEcs7heUcqrDxH5fmodPKS9BQYTG2RYAqGlr7bRXdH2p9AiiYCBCozUBBFUTHqruPAP398+NU2Rx8fUZGh+WKojA3O4k9J+tDGmOfKXB+/E2vGxrA44GGBo7++MdD4vDpjwLJ+p8wsGED5OcTu/Z5Yp0tKEKAzYbmmWf44+++yz/H1DFvfBIeAU6PtMiWSCKdsN59KIqSoCjKOkVRDimKclBRlPmKoiQpivKBoihFvsfEcI4hEjHrZQRIMjLx+KI/eWlWluSPHurhjFyKi8n/zS/Yt3oZU7ISsKYlc+i6G6G4eFBevrZZjeb0JYBGx8cQo9eyu7SeRLOey6eNorTGjqvTDWZpjZ3HPjjCZVPTuWxqV7e1qaPjKK21Ywsh9dgZEEDRY9Axzi+AZP3PwFJcDEuXgt2O0qn3k87jxuxyMPOe20g/UwaAfQjt5SUSSXCEe/r1ceBdIcRkYCZwEPgZ8KEQIg/40Pd8RGHWKbIGSDIiWb/nFMVnmrnnsolog7D2lYQB30z2qNdeDMxkW512pr/zGuTnq+vDTCAFztLV/ro9Go1CTpqaBjcnO4ncVCtur6C01h7YRgjBL97Yh16j4b+vmd4h/c2P3xL6UIUt6DG21QBFT5RyrE8AyRS4AebRR/tseovLxczXngW6d4iTjCzK6uz88cMimQ4ZwYTtyq4oShzwVeAZACGEUwhRD1wDPO/b7Hng2nCNIVKJ0SsyAiQZcQgh+OOHRUzJiOPKacE1hZQMMO1msjXurjPZ2O3q+jBHgmqbVAGUaOnbGjo3VU2Dmzc+iQm+mqD2TnCv7zrF5qPV3Lt4MqPiuy/8n5qhNgU9WN4Y9BgDKXBRlKZ51czR3HJBNjmpwfUokgTJ2rVBCaDsDW8AYHfKCNBI59XtJ3nsgyOcsUlXwEhFF8ZjTwDOAM8qijIT2An8B5AuhCgHEEKUK4qS1t3OiqKsBFYCpKens2nTpjAOdXAx4Ka0rnFYvSdJ9zQ1NQ278yyEwOkFoza0CE5dq5eSmhZWTDHw6aefhGl0kUMknvu81avJcDh6nfnyOhycXrVKrWMJEwVHHMToYMvmz/rcVuOLFmlqj3O69QQAH2zdi77KQKND8MBmO3kJGjJbjrFp0/FujyGEwKqHjTsPM9ZR0mX9KZuXHZVurs7RByJI+86ok1T79+3FWRZaGtxQnvuLYuGzEfD9GkwuamoimKudzq7Wp322ZRvlidGTOikZGNp/7zcXqrb7H332BaMs0TOJMpIIpwDSAecAPxRCbFUU5XFCSHcTQjwFPAUwZ84csXDhwrAMcij4x/73cNs1DKf3JOmeTZs2Davz7PEKbnt+O8Vnmnn/ngtDamC67XgtbNrC5fNn8dWJqWEcZWQQkef+6qvVQv1e0Hg8ZH38MVlvvhm2Yfxf+W7SmuqD+nwmzmph/M4yvrsoF41G4YGtH0BsGgsXzuRHL+/G5W3lyVsXkJsW2+txZhZ/SUOrm4ULF3RYXniqgR8/s5V6u4v/Wnohmb6ePc79FbBzJ/PnzmF6ZnxI7y8iz72k/1itYOs7fdJjUSNvk6bnB+zXJSOH9t/7B7Z/DNiZNvNcZmSFdv2QDA7hlKVlQJkQYqvv+TpUQVSpKEoGgO+xKoxjiEjMetUFTuaGSqKNR98/zMeHz1Baa+fVHSdD2vdEjZq25K9TkAwBTT330OnXdv2kttnZpwGCn9EJMfzwkjw0vpqxCSlWjp1p5qNDlfxr72nuWpTbp/gBmDIqjkMVNtztDBT2nKznhr99GShar2lqS1cJ2gVOMvxZsSKopreN110PQLOsARrR2J3uQJ2irAeLXMJ2ZRdCVAAnFUWZ5Ft0CXAA+Bdws2/ZzcD6cI0hUonRgdsraBlE21mJ5Gx5f38FT2wq5ttzxzA3O4knNxUHCsXbU9fs5L439nVx3CqttaNRILNdk0rJIGMNsjYk2O36SU2zk+QgBVBnJqRaKKpq4pdvFDIx3codC4Ozm56SEYfD7aXEJ8R3lNSy4umtJJgNPLp8pjouX20StBdAMpVpxLNqVVACqOXuHwFD01xYEjkcqWzCP78txXDkEu6prR8CLyqKUgDMAn4D/A64TFGUIuAy3/MRhVmnzmRKIwRJNPHqjjIyE2J48Opp/OiSPMobWlm3s6zLdh8cqOTFraV8dKhjcLe01s7ohBj0UVRUPuwIYiZb6PVw441hHUZtsyPoCFBnclKtNLS4KG9s5bffzMcQZITGbw29/3QjW4pruOnv20iLNfLq7fOZmZUAQHWHCFD0ucBJwkRODqxbB2Zz1++PXq8uX7cOw6SJADQPQXNhSeRwuKLNbEX+LUQuYb2yCyH2CCHmCCHyhRDXCiHqhBA1QohLhBB5vsfacI4hEonRqwJINkOVRBOtLg/pcUaMOi0X5CZzztgEnvi4ONAvxU/BKbXh5M4TdR2Wn6ixMy5Zpr8NKUHMZHt1OrjnnrANQQjhS4Hr3QK7J/y22DedP45zxwXfRi4n1Ypeq/DytlJueW4bmQkx/PP28xkVbyLZqooxvz03gMMlU+Ak7Vi8GAoKYOVKiIsDjUZ9XLlSXb54MVajWlYtI0Ajm/Z2+zIFLnKRK4DkVAAAIABJREFUV/YhwOyznmiUESBJFOF0ewPpQIqi8KNL8jhV38IbuztGgfaVNQCwo6SjADpZa5f1P0NNLzPZQq/HrjPywUNr1O3ChM3hxuUR/U6BW5CbykNXT+OniyeHtJ9BpyEvLZYvj9UyPsXKP1eeT1qsapttNmgx6TU91ADJFDiJj5wcWLMGGhpUM5GGBvW57/ti0mtQUGtAJCOXQ+U2JqaracQyBS5ykQJoCPCnwA2nZqhv7T3N0ie/wOuVxg7DFYfb0yEd6KKJqczMimfNx0dx+QrLnW4vB8ttGHUaDlU0Bma/mhxuapqdjE2yDMnYJe3oYSZbWbmS7/74af6dOSusL+/vAdTfFDiDTsPNX8nGbAjdxHTJzAwuzEvh5e/PI9naFoFSFIVki7FDBMgf2Qw2xU4iURQFk07O+o9khBAcrrQxa0wCigJNMhoYscgr+xBg1g+vGiCXx8vvNhxix4m6DjcQkuGFw+3F0K5+xx8FOlnbwvo9pwE4UmnD6fFy7axMvAL2lKrpcKU1qiOOjABFCD3MZKfMmsLesvqwvrT/GpFk7Z8AOhvuXJjLC9+bR4K562unWA2dTBA86LUKWk1o/a4kIxujVgm4CkpGHmeaHNQ2O5k8Kg6LQUfTMLnPG45IATQExPhT4IZJDdCbu09xqr4FgCpb6xCPRhIuHG4vxk59fy6enMa00XH8+eOjuD3ewM3zTV8Zh6LAjhNqiV9preq8JWuAIptZYxI4WdvSIRVsoKn1CaD+psCFi2SrkZrmjilwBmnYIQkRkw6aZArciOWwr/5n8qhYLEatTIGLYHq9uiuKktTbz2ANcrgxnCJAHq/gyU+KsRjUG+MqW/hunCRDi1oD1PGS4Y8CHa9u5t8F5ewrayDBrGdqRhyT0mMDRgj+nghjZAQoovG7oYUzClTrExn9TYELF8mWrhGgzoJfIukLk1bBLm96Ryx+ATRpVCwWo06K4Qimr+mtncAO32Pnnx3hHdrwxaABnUYZFjVA7xZWcOxMM3dfnAfAGSmAhi0Ot6fbeojLpqQzeVQsf/yoiD0n65mRGY+iKMzJTmR3aT0er+BEjZ0Es574mD56aUiGlOmZ8WgU2HOyIWyvUROIAPXPBS5cJFuN1DQ5Aw2qHa6ugl8i6QujVrrAjWQOVdhIsRpJthqxGnUyAhTB9Hp1F0KMF0JM8D12/pkwWIMcbiiKQlyMvkujyGjkb58dY3yKhZvmjwOkABrO9HRDqNGoUaBjZ5o5VGEjPysegDnjkmhyuCk81UBprZ1xMvoT8ViMOiamx7L3ZBgjQE1OzAYtMYbIiq6kWA04PV5svhsWRzcRT4mkL0w6RfZ+GcEcrrAxeVQsABaDFECRTF8pcOMURYlv93yRoiiPK4pyj6IokZW/EGXEmnQ0tkT3F2NXaR17Ttbz3a9kYzHqiDXpqGqUNUDDFYfH26Ml8JXTRpGXptp+zshU06guyE0h1qTjP1/dQ1Flk0x/ixJmjUlgb1l9IBICsPFAJc9+fnxAjq/2AIq8fx+BXkC+NDiH2yMtsCUhY9JK6+ORilcIjlS2E0BGnXSBi2D6mt56FbAAKIoyC3gNKAVmAU+Ed2jDmzhT9EeAnv28hFijjuvOzQIgLdYoa4CGKUKIbmuA/Gg0Cj+5YhIJZn2gOWVqrJG/3TSHk3UtVDS2SgOEKGHmmATq7S5O+Jz7AJ794jh//rh4QI5f0+yMOAMEaEvJ8xtAqKYfMgIkCQ01AiRvekciVXaBw+1lkk8AWaUJQkTT19U9Rghx2vf7CuDvQohHgVuAuWEd2TAn1qSL6kaoFQ2tbNhXzvLzxgS6X6fFmqQAGqY4guiJcvm0Uey+/zJSY9tqO86fkMwfvzULjQKTRsWFfZySs2fWmK5GCEWVTdQ0OwL9ns6GSI8AVfsjQLIGSNIPTFqkCcII5aRNvT5O9v2vs8gaoIimr6t7+wYIFwMfAgghzv6/4Agn2iNAL3xZgkcIbp6fHViWFmeUNtjDFL8A6uuGUFG69ky5cnoG2++7lKvyM8IyNsnAkpdmJUavZY+vDqix1UWVzYEQA1PjV9PkICnCDBAAUnyNUf1W2DIFTtIf/BEg2RR85FFm86JRIC9dTQe3mnSyKW4E05cA+khRlFcVRXkcSAQ+AlAUJQOQHS/PgmiuAWp1eXhpaymXTklnbLu0prRYI1WNjg61A5LhgdMvgPppC5xsNXYrjiSRh06rYUZmfMAI4WhVU2Bd5VnW+NU0OTjd0Equr14skkg0d6wBcnpkBEgSOr6ECFpcMg1upFHW5CU72YLJ93/SatDhcHsHJHIuGXj6urr/GPg/oARYIITwhyxGAfeFcVzDngSznjq7E08UzhKt33OKOruLWy7I7rA8LdaEw93moiQZPjjc6j9zo2wMOSKYOSaewtONON3eTgLo7CJA/r5Qc7ITz+o44cCg0xAfo2+rAXLJGiBJ6Ji06kSPTH0aeZTZ2up/QE2BA/m3EKn0ZYMthBD/FEKsFkKcareqAEgJ79CGN1My4nC4vRSfaep74whCCMGzn5cweVQs8yckd1iXFqemkFSd5U2SJPIIpMDJG8IRwawxiTjdXg5X2CgewAjQzhN1GHwRpkgk2WqgutnvAtez66FE0hMmnU8ASSOEEYXd6abKLjoIIH99tEyDi0z6ssGOUxTl54qirFEU5XJF5YfAMWD54AxxeDLTV2i8J4z9Nt4trOC6J7/g/jcL2XigckCOueVYDYcqbNxyQXaXlKZUXw59f+uAqhpbqbfLzMpIxBlkDZBkeDBzjCpQ9pTVU1TVRF6aFZ1GOWsBtONEHdMz4wIpIpFGisVIbTsbbIOMeEpCxOj705az/iOLosomBAQssKF9BEiK4Uikr6v7C8AkYB9wG/A+sBS4RghxTZjHNqwZn2wh1qQLa8PBDYXl7Ctr4P92lfH9F3YMyCzEs5+XkGjWc82szC7r/BGg/hZKr3xhJ798s/CsxicJD20mCJF54yoZWDITYkixGth7sp6jVU1MHBVLWqzxrFLgWl0e9pU1cF520gCOdGBJthramSDIFDhJ6MToZArcSORwhQ3o6Hb6/9m77/C4qmvhw789VWXUm9VtS664VzqyaaGFnlBTb7gESCEh7UtyU0lCCiQkIUBIcrmYQAgECBADbjIYDO64ypZlW1bvfYqmnO+PKZasLs1II896n0ePpZkzZ/boWDNnnb3W2rG+aFhmgMLTUO/u0zVN+4ymaU8AtwLLgKs1TdsT+qGd2XQ6xcKcxF6tZoOtotnK0vwkHrppAZrm/XksTjZZWX+ojttW5vV7BTctLgoYfQpcRbOVQzXtYxqjCA2Hr6B3sDbY4syhlGJRbiIfHm+iosVKYZqF9PiowAzQ63urueJ37+IaQXHvvqo2ut2ewDpR4SjFYjq1EKq0wRaj4J8BskoKXEQpqe3ApIe8Hgt+W6QGKKwN9e4e6NOsaZobOK5pWkdohxQ5FuYmUFLTgT1E3WJONtvIS44J/EGONQB6eusJ9Epx59lT+70/PsqA2aAbVQqc26PRbO3mZLN1RCdVYnwMtw22OHMszEmkotmGpkFhuoUpPQKgjSX1HKpp50RT17D3t+OEtwFCWAdAsWaafc1ppA22GA1/DZBc9Y8sh+vaybbo0OtOlQZIE4TwNtTZzEKlVLvvqwNY4P9eKSWX6sdoYU4iLo/Ggerg/ypt3W4aOx3kJkeTm+QLgFpso95fp8PFC9sruGJ+JlMSovrdRinlWwto5DNArdZuNA2cbo2q1tGPU4RGt6TARRx/nSJ4A6CMeHMgADpU470OVlI7/OthO8ubmZ4aS4ol/NYA8ku1mALrHXk0CfjFyEUFZoDkpDeSHK7tIMfS+/1CmiCEt6G6wOk1TYv3fcVpmmbo8b0s6z5Gi0LYCKGixTvbk5scQ2KMEYvZMKYZoJd2VtLhcPVpfX269LioUaXANXWdan5wrHH4V5XF+JAucJFnYY73/UmnYFpqLOnxUbTbXbTbnRyt9wY+R4YZAGmaxs7ylrCe/QHIiPde3Cmp9V6Ukv/vYqROzQBJClykaOx00NjZTU5c7/cLmQEKb/LuPoHS46PITIgKSSMEf7CTmxyDUoqcpOgxBUAv7KhgYU4CS/IGP4FJjzPT0DnyAKixx2NOSAAUdvzrAElXrMiREGNkemosuckxRBn1TPEFB1vLmnC6veuXDXcGqKyhixarMyzX/+lp5fQUDDrFf/bVADLjKUYuUAMkJ70Rw98AIbdPAOT9zyAt0cOTYaIHEOlC1QjBH+z4639yk2MoH0G+fk+2bjcltR3cU1Qw5LbpcWbeO9o44ufwFx4DHJcAKOzIDFBk+tLFhYH0R//sSPHhBgAK0mI5XDdwAGR3ugPNUnaWNwOwND98O8ABJEQbOacghTf31wKSAidGzqBTmPQ6OiUFLmL4mzedngJnNugx6pWkwIUpeXefYAtzEylvstLSFdz1b04224g26kmJNQGQmxTjK2jWBnyMw+XmDxtL+8wUHaxpw+3RWJCTOMAjT/GnyYy0sYN/9fXc5GgJgMKQ1ABFpusX5/DJ5XkAZPja3L9zpAGjXnHl/ExONlv7rXV4YUcF837wFm8f8AYSO060kBRjpCAtdvwGP0qXzc2g3e59TRLwi9GINeuxSgpcxDhc20GqxUS8WfW5L9ZsoNMuAVA4knf3CeZfcDDYs0AVLVbyfOlv4A0sbE53r1qbnhwuN/es2cWv3z7CP3dW9rrvo4o2ABbkDL16e3ZiNMCIukOBtwZIp2BxbhLHGiQACjeBFDi5Ih6xMnzNT6pabRSmx3FWVgKa5l0AsKdnPyznmy/uxeXReNH3XrLDV/9z+uLJ4eiSuRmB7yXgF6MRYzJI3UcEOVzXwaweC6D2ZDHL/4VwJWczE2x+dgJKnQoygqWi2UpucnTg50AnuH7qgBwuN19cs4sNJfVEGXWU1fc+odlX1UZGvDmQAjOY+b4gae8IX09jZzfJsWYK0ixUt9lC1hpcjI7DKW2wI12c2UC0L6VtTmZcYMXzwz3qgP723nG++/J+Vs9O57aVeRQfaeBkk5XjjV1hn/7ml5kQHbjYIzVvYjQsZgNd45wCV9tm55F1R3B7Bs7yEMHn9mgcqetgVkb/fcEsZoOkwIUpeXefYHFRRgrTLEGdAdI0jYpmKzlJpxbkyvXVAp08LQDyBz8bS+p58Pp5nF+YSml977z+jypbmZ89dPobwLSUWOKiDOwZ4etp6nSQajExLS0WTYPyprGtWSS8jtZ38KPXDoz5Q7Hb7UGnvPntIjIppQJpcHOmxPuaI+gCjRCe2FzGj147yOVnZfD4HUu5fnE23S4Pv3yrBCDsGyD0dJlvFkhS4MRoxJj1474Q6tsHa/ndhtJeFyRE6HxwrIldJ1s42WzF7vQwO7P/GaDYCQiGxfDIu3sYWJibyEcVrYPW54xEc1c3Xd3uXisS+2eDKnusBdQz+PnZ9fO5fWU+helxHG/sCixG2mF3cqyhi4XDSH8D0OmUt7HDCDvbNXV1k2IxMT3VWyNwvLFziEeI4XjrQB1/e+8EB8e41pTD5cFs0E+KFCYROv5Z4NmZceh1ipkZcRyua+fRDaX8fG0J1yzM4g+3LcFk0LE0L4mMeDOv763BpNcxP3t47yHh4PolOayYmjxgWosQg5mIq/6tVu+69adfwBTB1eVw8Z1/7eOWJz/g1ic/YM0H5QCBGfHTxZoN0hI9TIU0AFJKnVBK7VNK7VFK7fDdlqyUWqeUKvX9O3kuC4bIwtxEmrq6ewUnY+Ff8DS3RwAUYzKQajEFUuAcLjd3P7MzEPzcttJb6FyYbsHp1gIzRfuqvKls84cZAHlfTwIltR3YRnAFrKnTQUqsmam+AEjWAgoOf3vxbSeax7Qfh9Mt9T8iEADNyfSme8zKiGNrWRMPrzvCDYuz+e0nF2H0pY3pdIor5mUC3vcPf0e4ySA7MZoX7j6H9Lih036FOF2MafybILTZvAHQ6SnsIng0TeOOv3zI89tP8l/nTyM7KZq/bDmOUjAjfaAaIL3UAIWp8TijWaVp2iJN05b5fv42sEHTtBnABt/PEW2xb0HUYKXBnTytBbZfTlIMFS1W7E5v8LPpcEOv4Ae8ARDAUd+b6L5KfwOE4aXAASzKTcLt0ThQPfw6oKZO7wyQxWwgPc7McWmEEBTNvqYX24+PMQByeaT+R7B8ahJL85NItXhT4WZnxuPR4Jblufzq5oXoT0uRvHK+NwBaFuYLoAoRTLETMAPkD4CONkgAFCrFRxrYfbKVn143j+9dPZdnPr+SKfFRFKRZiDb1f4EnVhpihK2JWAfoWqDI9/3TQDHwrQkYR9iYNSUOk0HHRxWtXL0ga8z788/y5CRF97o9NzmGXeUtfHGNN/j5+Q3zuXVFXq9t/G1qS+s7uews2FvZRk5SNMm+dtrD4U+X21PRyrKpQxc+251uOhyuwEnVtNRYmQEKEv/6SttPNKNp2qhT2LpdHqmHENx5zlTuPGdq4OdPLMshOzGKy+ZOQddPfdiy/CQeuGwmH1+YPY6jFGJixZoM/baHDyV/AHR6V0YRPH8qLiMzIYqbl+YC3pnif9933qD1XhMRDIvhCXUApAFvK6U04AlN054EMjRNqwHQNK1GKZXe3wOVUncBdwFkZGRQXFwc4qGOn87Ozj6vJ88Cm/eXc15s/Zj3/94+B3Em2L51S6/btY5uqlqdVLXa+MxZJjKtxyguPtbn8UlmxXv7yphDBVtLbUxP0I34958cpVi38wiF7pNDbttk89YbNVYep7i4kmiXg+21LjZt2jTpa076O9bjqbzOhsJbY/XcG5vIsowuiKmoseNyeM6ov8NQm+hjP16igHfeOTzg/fN0cGxfFX3fac5ckXLsRV+dnZ1Ym7ppsTp5/e1NWEzj8xl2ssab+n6soZMNGzf1mY0VY1Pa4mbbcTu3zjbx/pZ3+tx/gv7/7ptqu+m0nzqfsbk0dte7WTFFL02FJlioA6DzNE2r9gU565RSJcN9oC9YehJg2bJlWlFRUYiGOP6Ki4s5/fVs7jjA89sqOP+CCzGMofVqZYuVHes2c8OSXIqKFvS6ry2xiteP7eEXN8znltNmfno66+iHtNudROXNptn+Id+/dh5Fi3NGNI6VlTvZX93W53X6OVxu/vbeCS6Zk05Ktwc2b+HcpQsompvBMcNxiisOMn/5uYFZocmqv2M9nhzvrWfZ1Bi2n2hBpRdSNMhxH8ya8u10KTtFRRcEeYRnrok+9mLiyLGPXMXFxdw8dz4vlX5AVM5cinqsKxVKP9/9Dkp14NZg6vzlFKRZxuV5I8Wap3eQGOPm+7etIsbU/6lzf3/3hyjjtWMlrDzvAjaW1POT1w9S1+5g4bwlXLIgcxxGLgYS0pwWTdOqff/WAy8DK4A6pVQmgO/fsU95nAEW5SZic7opHWMB42/Xl4KCr1wyo8991yzIYut3Vg8a/IC3DuhofSf/2F5BXJQhUMg8EotyE6lotgWK8Huq77Bz65Mf8Iu1Jfxh41Eau7zbpFhMgeeHU3VIYnQ0TaPF2s3S/GRSLaYx1QE5JAVOCCGGZVFuIka9YvsYm8+MRJvNyawMbyG+pMEFl9uj8c6RBq5fnD1g8DMQi9lbG/Spv2zjvr/vJiHaCEBduz3o4xQjE7IzGqVUrFIqzv89cBmwH/g38GnfZp8GXg3VGCaThb4mAyNtH91TaV0H/9pVyafPySczIbrP/Tqd6vf20xWmW7B2u3l9bw3XLcoeVfemC2akAfD8tt4pcPur2rj2D+9xqKaD2VPieLe0kYYObwCUGmsOPD9IADRW7XYXTrdGqsXEsvzkMXWCkyYIQggxPFFGPQtyEsfcfXMk2mxOlviajZRJI4Sgqmu30+32BM5NRiIuyhvwHK7t4EcfP4s3vnwBBp2iqavvxWExvkJ5RpMBbFFKfQRsA97QNO1N4BfApUqpUuBS388RLz8lhoRo45g6wf12QykxJgNfLCoc01j8f+Ruj8Ynl+eOah9zs+JZPTudp7YcDxQAvr63mpsefx8FvPjFc/jCBdNp6upmS2kjcGoGKDMhihiTXgKgMWrqPDWztnxaMpUtNmrbRnfVyeHyYDJMnjbGQggxkZZPTWZfZduIloMYrW6XB5vTTVZCFFkJUfLZGWT+hdlP76w7HJfMzeA7V8xmwwMX8elzp2LU60iONdHY0R3sYYoRClkNkKZpx4CF/dzeBFwcquedrJRSLMxNZE/F8FtH91TTZuPN/bX81/nTRtSxrT/+AOisrHjmjWHxwq9cPINr//geT79/AofTzaMbj7I0P4nH71hKWpyZNF99z9sHa4ky6ojxtZFUSlGQZpGrWGPkb4GdHGsOzPwdrutgSsLI1zZxON2Y4yZ3PZYQQoyXFdOSeHyzxu6KFs4tSA3pc/k7wCVEGylIt8hiqEF2stnblTY/OXbEj7WYDfz3RQW9bkuxmGUGKAxITksYWZSTwJG6jlG1z/z7hyfxaBp3nJ0/5nGkxJq4blEWX71k5pj2szA3kaJZafz67cM8uvEon1iWw9+/sJI034l0enwUs6fEYXd6SIk19+r45q9DEqPX6GuBnRJrGnNaYbdbUuCEEGK4luYnoxTsONES8ufyB0Dx0UZmpMdRVt+Fx6OF/HkjRXmTFYNOkZUYnIWRUy0mGjplBmiiyRlNGFmYm+hbQLR9RI/rdnl4blsFq2elkzuKKdrTKaX47S2LuTQI3Wu+fukskmNMfP/quTx04wLMp6VRXTjTWyuUauk9a1WYbqGmzS7988fAPwOUYjGREmsiMcY46gDI4fT0OXZCCCH6lxBtZFZG3Lg0QmizdQeeszDdgs3ppqrVFvLnjRTlzVayk6LH1KG3p1SLOZCiLiaOBEBhZEGPRghuj8a7pQ3YnUPnD6/dX0Njp4M7zxn77E+wzc9JYMf3LuHz50/rd02fC2Z4UwNSTmt37W/heUzS4EbN/wabHGtCKUVhmoWy0QZALg8mmQESQohhWzEtmZ3lLbjcnpA+T88UuLlZ8YC34VCkuPuZnTy3beg1B0frZJN1VPU/A0m1mAKLlA/HC9sr+P2G0qA9v/CSM5owkhZnJjsxmj0VrTy6oZQ7/7KNTz6xleohruQ8s7WcqSkxXOjrvBZuBlvMdPnUZMwGXaAeyK8w3ZtrK2lwo9fU1U2c2RCYuSkcQ264w+WWFDghhBiBpflJWLvdlNSGtibHHwAlxpiYmxmPyaBj9xg6yk4mTZ0O3jxQy2sfVYfsOcqbushPCV4AlGIxY3O66Rpmhsvjm8v40+aykAfSkUbOaMLMotxEig838OjGUs6ZnkJZQxfX/H4LJxq7+t3+YHU7O8pbuOPsfHSTcFXhKKOev35mOfes6l0kmJ8Si0GnJAAag6aubpJ7pBYWpltosTpHNfXeLesACSHEiCzJ87al3n0ytHVAbdZTM0Amg455WfHsKg997VE42OML9PZVtaFpwa97arV20253jaoBwkD8C7wPZxaots3OscaucQmkI42c0YSZhbkJdDpcFKZZ+MtnlvHSF8+lqaubtw7U9rv9Mx+cIMqo4+alo2tXHQ7OK0wlP6X3m4tRryM/JUYCoDFo7nKQEts7AIKRz6ppmuZdByhI+c9CCBEJcpKiSYszs+tkaGdj2mzemYT4KG9j3yV5SeyraqPbdebPGPgDoA67K9CuOpgCLbCDOgPk/VxuGMbFyK3HGgPfj+fCupFAzmjCzOrZGSzISeCx25cQYzIwa0oc6XFmjvSzsnObzckru6u5dmE2CTHGCRhtaM2aEseO8hYpFhylps5ukmNPpRYGAqAR1lV1+6bdzaNYEFcIISKVUooleYnsCvUMkM2JxWwIFOkvzkvC4fJwqGZkDZUmoz0VrcT6ltDYG4K6p5PN3gAomClwaYEZoGEEQGVNJEQbyUqIYkeEzOqNFwmAwkxhuoV/33c+MzLiArfNzIjrt3bjxZ2V2JzusGx+EAz3riqk0+Hi/hc+6relZ3WrjW+++NG4LDQ3GTV1dffqrpeVEE20ceQLzDp8VxGlBkgIIUZmSV4S5U1WGkN4Ia/V1k1C9KmLoEvyvQ2VQp16N9E8Ho09Fa1ctSATk0EXksYP/gAomE0Q/DNAjcNIgXu/rImzpyezbGoyO0+0hCTNL1LJGc0kMCPDQmldZ68gwOPRWPNBOUvyEse0WGk4OysrgR9cM5d3jjTwWPHRPvc/v+0kL+yoDPnVtcnI49Fo6erutSiuTqcoSI8dcQDULQGQEEKMypJ8fx1Q6NLg2m1O4nsEQJkJ0UyJjwp56l0wfHisiT9u6vv5PhzHGjvpsLtYNjWZOZnx7K0M/ustb+oiLc5MjMkQtH36P5eHmgGqaLZS2WLjnOkpLJuaRG27XdqbB5Gc0UwCMzPi+vT1f/doI8cbu/jUOVMnbmDj4LYVeXx8YRYPrzvC1rKmXvetO1QPQJm0yu6j3e7E5dH6tBcfTSts/wyQtMEWQoiRmZ+dgFGvQnqhrs3mJCG69wn6kvxEdleE/8XB57dX8Ku3DlPfYR/xY/1B5eLcROZnx3Ogqj3oC8CWB7kFNoDZoCc+yjDkrKD/nOfcwlSW+gLp8VhYd6R2lrdMyoV35YxmEpiZ4a3dOFJ3Kg3uma0nSIk1ccX8KRM0qvGhlOJnN8xnamosX35+Nw0d3jeMqlZbIL95tGvbnMma/IugxvZdYLa6zT6s9pu/W1/Km/trcPjWopKFUIUQYmSijHrmZiWwM4T1G94AqHcd8OLcJCqabYHPzHBV4Usxe+dI4xBb9rWnopU4s4GCNAsLshPpcLg40dR/x9zROtlsJT/IARB4O8E1dvVNgfN4NB584yCfeHwrj24sJdViYka6hdlT4rGYDbxf1si6g3W8uqcq6GMajdK6Dm780/v89b3jEz2UEZMAaBIoTPfWA/kbIVQ0W9lQUs8tK3JWgDduAAAgAElEQVQj4qTUYjbw2O1L6LA7+eo/duP2aGw4VAd430RGWtQfCfztNVMsfQMgYMh2msWH63lk/RFe2FF5qgmCzAAJIcSILclLZG9lK84QrePSZnOSGN37vX5+jjc1PtwbIVS2eDNbNh9pGPFj91S0sjA3EZ1OBV7vviDWAR2t76CmzU6h7yJ0MKVazDT2E5w+8c4x/vzucewuN3FRRj57nncReb1OsTgvkRd2VPKF/9vBV57fExbZL48VlxFt1HPDkpyJHsqIyRnNJJAQbWRKfBSlvhmgZz88iQJuW3lmNj/oz+wp8fz44/N472gTv99YyrqDdUxPjeXCmamU1Qf3is+ZoLnL+8aafNoM0MppKRh0ircHaKsOYHe6+cG/DwBQ127H4ZQUOCGEGK2V05KxOz1sPx6aNsZtNmefTrD+Bjj+RVLDkcPlpq7DjlLwbmkD7hGkUTndHkpqO1jgC3xmpFswG3TsqwxeAPTrt45gMRu4ZXle0Pbpl2IxBTI1/N4va+RXb5Vw1YJMXr33PNZ+5QLuXVUYuP+uC6dz64o8fn/rYox6xXMfngz6uEbiZJOVf39Uze0r8/qca0wGckYzSczIsHCkvoMOu5N/bD/JJXMyyE6Mnuhhjaubl+Vww5JsfrehlPfLmrhkbgaF6RZq2+102E+9yTvdHvZUtIb1G3+o+bvLpJ5WA5QUa+LCmWm89lH1gDm7fyouo7zJSmG6hbp2R48ucGf+bKMQQgTbRTPTiTHpeW1vTdD3bXe6sTs9fVLg4qO8P7fbw/dzsLrVjqZB0cw0Wq3OwJo+w1HXbsft0QL1OQa9zruQ/JGGoHRK232yhTcP1HLXhdNDcnKfajH3qgGqbbPz5ed2My01loduXIBSfRe2v2BGGj+/YT7XLMzisrlTeHFXJXZn3y64XQ4XX31+N7VtI6+rGok/bS5DrxRfuHB6SJ8nVCQAmiRmZsRxtL6TP2w6SovVyX2rC4d+0BlGKcVPr5tHYZoFt0fjkjkZFKR5p6aPNXThcLn59kt7WfKTdVz3x/dY/tP1/NfTO/j3R9VYu4eueTmT+BtmJMX0feP++MIsqtvs7DytKPdAdRuf/ds2frehlKsXZHLV/EyauhyBeiGzUd4uhBBipKJNei6dm8Ha/TVBT4Nr913oiz89APL93G4L388+f/3PLSvy0KmRpcHV+E7us3pcCP74oiyO1ndyoHpsaX+apvHQmyWkxJr4/PnTxrSvgaRYTLRanTjdHpxuD/f+fRfWbjeP37EUi3nojnO3r8yj1epk7f6+QfWO8hZe2VPNO6UjTyscrto2Oy/trOTmZTlkxEeF7HlCSc5oJomZGRbsTg9/fucYNyzOZkFO4kQPaULEmAz8+VPL+OolM1ianxSoaSlr6GTdwTqe317Bqlnp/O6WRXzqnHz2V7Xx5ed2s/Qn6/nSc7t5+0DtGb86dn2HnTVby7loZlq/aWuXzs0gyqjjtY+qATje2MWXntvNVY9uYdfJVr59xWx+ffNCMuKj0DSo9AVTUgMkhBCjc82CLFqtTrYcHbjYX9M0rv79u7ywvWLY+/VnOpw+A2Q26DDpdWE9A+Sv/5mXncCi3EQ2H64f9mOrfZ9LWYmnTr6vmp+JUa/G3CDg3dJGPjjWzJdWFxI7jGBkNPzZGc1d3fz8PyXsLG/hoRsX9FoDcjDnFKQwLTWWv/eTBucvl6hpDd0M0J/fPYZb07j7ooKQPUeoyRnNJOH/ozDqdTxw+awJHs3Empoay1cvmYlep8hLjsGgUxyt7+T1j2pIjzPzyCcXce2ibL539Vze//Zqnr/rbG5Yks2W0gbuemYn//Pq/ol+CSH1szcO4XB5+OHHz+r3/lizgYtnZ/DG3hq+8699XPLwZtYfrOO+VYW8881V3H1RAVFGPRnx3jdo/1U6qQESQojRuWBmKvFRhsCFp/40dnazv6qdj0awns1AAZBSivhoQ2CGKBxVtlgx6BRT4qO47KwpfFTZNuw1gap9J/eZCadmgBJjTBTNSufVPdUjqifqyePR+OVbJeQkRXPryuDX/vj5a7Sefv8Ef33vOJ89byrXLMwa9uOVUty6IpftJ1p6dQgGAmv91bSFZs2g5q5u/v7hSa5dmEVuCDrkjRc5o5kkZmbEEWPSc/dFBb2mfCOdUa9jamosH1W2svFwPVfOz0SvO5U7q9Mpzp6ewoPXz2fbdy9h+dQkDg3RAW0yeO2jaj441tTn9vfLGnllTzV3FxUwLTV2wMdfszCLpq5uXtxZwR0r89j8zSIeuHxWrw9R/7R2ua+tqNQACSHE6JgNej42bwpvH6jrt24DTr3XtlqHH7QMFACBtw6o3R7GKXAtNrISo9HrFJ8/fxrXLsriV28d5ldvlQz52OpWGwnRxj4zNNcvzqa+w9Hv5+Nw/Gd/Dfur2vnapTND+pnnX6PvseIyluYn8Z0r5ox4HzctzcWk1/WZBSr1BUDVIaoB+usWb5e6e1ZN3tkfkABo0rCYDbz3rdV89ZIZEz2UsFOQFst7R5vodnm4ZmHmgNsZ9ToK0y1UtVjHcXSh8ZPXD/LgG4d63dbt8vA/rx4gNzmae4oGf2O6dG4GD904n41fL+JH184jPa5vDq8/ADrZLClwQggxVtctyqbT4eLFnZX93n+80RsANfezPsy6g3X84NX9PPNBOduON9PmC5L8AVBiPwFQXLQx7GeAcpO9F3SNeh0Pf2IRNy/N4Y+byjhaP/iFypo2G5kJfT+3Vs9OJ85s4OXdI0+Dc7o9/Pqtw8yeEse1i7JH/PiR8KfApcSa+ONtS0aVYZHsWwvypV2V2Lq9QbWmaT1S4II/A9Rud/L01hN87KwpgSVaJqvQJDeKkEiahG0Gx4O3EUIdWQlRLM5NGnTbnKQYGju7sXa7iDFNzv/+dqeb+g4H9R0O6trtgUDlL1uOc7S+k799ZjlRxsGvXOl1ik8O0dozJdaEQaeo9KXASQAkhBCjd05BCkvzk/j9xlJuWprT533av4hni7VvAPSn4qPsOtk7NS4j3ky0bx/9zwAZwroGqKLZxsWz0wM/63WK+y+dyT93VrKxpH7QE+yqVnu/nXCjjHqumD+F/+yr5afXzRvys7CnF3ZUcKLJyl8+vaxXJkko5CRFc83CLD51Tj5T+gnkhuu2FXm8uqea1/dWc/OyXBo6HLTbXUQZdYFGEcH0zNZyOuyuXu25Jys5oxGTnr8RwtULs9AN8aaVk+R9w6xqCU1u7Hio6nFVZ1NJfeC2RzeUctncDFb1+EAZC51OkR5npsPXBU5qgIQQYvSUUjxw2Szq2h2s+aC8z/0nmrwXm/pLgatts3PDkmy2fmc1//vZ5fy/K2dzfmEacVFGluUn9ekCB95OcOE6A2R3umnsdARmgPyyEqOZPSWOjSWDN0SoabORmdh/4OCfaVvvWzB9OGzdbn63vpRl+UmsDtJn6GCMeh2/v3Uxy6cmj2k/K6YlU5hu4e/bvGlw/vS3ldNS6HS4ghoA27rd/GXLcS6amca87ISg7XeiyBmNmPSWT01mWmosn1g29ErEOUnegr0KXxrc3spWNo2g80w48HfOUQo2+D4kfvyad+HS/7lmblCfK71He0upARJCiLE5pyCF8wtTeay4jE5H7/qcE/4UOGt3r7Vs3B6Nug4HWQnRZCZEUzQrnbsuLOA3n1jIa186nxe/eG6/MxbDrQFyuNyjbhowWv7PMf9nck+rZqez40TLgCfv1m4XrVbngPXQK6enMCU+ildGkAb3v++foL7DwbeumN3vGjzhytsMIY/dJ1s5WN0eaIBw4cw0gKCuBfTctpM0d3WfMcuwSAAkJr3c5Bg2PVA0rHzUXN8MkP/N96E3S/jey5OrK1ylL3i7eHYGW0obWbuvhrcO1PHli2f0+2EyFlN8AZBSYNRPng8FIYQIVw9cPovmrm7+tuV44DZN0yhvsqJT3npOW49GCfUd3kU/B5rxGMhQXeAqmq388N8HWPLjdXzvlfH9HPRfhDx9Bgi8dTwuj8aW0v5bhvs7wGUl9B8A6XWKjy/KovhwQ7/1VKdrszr5U/FRVs9OH/OMzES4cUk2ZoOOv28rp7S+g/goAwtzvDM01UGqA3K43Dz5zjFWTEuelL+j/kgAJCJKWpwZs0FHZYsNTdPYX9VObbsdV5AXpwulimYbRr3itpW52Jxu7n9hD4XplpAs2OZvhW3S6ybVVTEhhAhXi3ITuWROBk++eyzQzKCxs5tOh4uZviUvWnqkwflrOfor+h9MfJQRh8vTb9c5j0fjlic/4NkPy9HpVJ9WyqE22AzQ4txEEqKNA6bB+ds7D9YR97pF2bg8Gm/s67tQ6Ole3l1Ju93F1y6dOZyhh53EGBNXLcjkld3VfFTRxoyMODJ9v5tg1QG9ub+W2nb7GVH74ycBkIgoSimyk6KpaLZS3WanzebE7dFCUiwYKpUtVrISozm3IJVoox6708OPrz0rJDU6Gb4PXGmAIIQQwfP1y2bS6XDx5LtlwKkW2EvyvY18WnrMXNT0s+bNcMRHeRv9dPSTBre3qo2qVhsP3biAVbPSaex0jPxFjEFlsxWTQUearxtaTwa9jgtnplF8uAFPP6l5/lmNwQLCOZlxzMyw8Oow0uBe2lXFWVnxk7qu5faVeXQ6XOyramNGuoX0ODNKjb4T3Mu7K7n+sfcCF4ffPlBHepyZCwpTgznsCSVnNSLi5CbFUNli40BVW+C2qhC0iwyVyhYbuUkxRBn1fOa8qXzhgmmcWxCaN6UMX3ts8wg66QghhBjcnMx4rl6Qxd/eO0FjpyPQAntRbiLQuxOcf8ZjxDNAvsYI/dXSbCypR6dg1ax0Ui1mGjvGNwAqb7KSkxQ9YOOiVbPSaOx0sL+6rc991a12lGLQ7mlKKa5bnM2O8pbAYt79OVLXwb6qNm5YMnQNcThbkpfELN/sYWG6BaNeR3qcedRrAW0qaWD3yVbeLW3E4XKz+UgDF89JH7LR1GQiAZCIODlJ0VS0WDlQ3R64bTJ1hatssQW62X3rY7P57lXBbXzQk7/FtswACSFEcN1/yQwcLg+PbSrjRFMXep1ivm8W4vQUuGijvt9W14OJj/IFQP3UAW0sqWNJXhJJsSZS40x0dbsDa8mMhyN1HYET9v5cNDMNpeg3Da661UZ6nBmjfvDPJf9aPq/uGXgW6KVdleh1imsXZQ1z5OFJKcXtZ3uXtvCnUWYmRAeC55Eqa/A2U3hpVyUfHmum0+HikjkZwRlsmJCzGhFxcpJiaLU62Xa8OVCAGc4zQJqm8am/bmPdwTps3d7Wof4AKNSmJPhqgCQAEkKIoJqeZuHGJdms+bCcD481k5sUTVqc9z23Vwqcr+XzSOsw46O9KXCnd4Krb7ezv6o9sGSCf1HO8UqDs3W7Od7UxawpAwdAKRYzi3IT2XS4oc99NW32YaUDZidGs2JaMi/vrurVVc/P7dF4ZXcVRTPTAr+DyeyW5Xn85uaFnOdLU8tKjAqkT46Ex6NR1tCJXqdYd7COV3ZXEWXUBfZ7pgj5WY1SSq+U2q2Uet338zSl1IdKqVKl1D+UUrK6pxhX/qBn24lmFucmkRZnDnRWC0cdDhfvHGng/7aeoKrVO85gd3sbSHpgBkhS4IQQIti+tHoGmqaxo7yF/JRYEn2zPL1T4OwjTn+DgWeA/Es/+Ne78dfhNIxTAFRa34Gmwewp8YNut2pWOnsrW/sEZtWttn4XQe3P9YuzKWvo4kB1O2v31fCLtSWBYOj9skbq2h2TPv3Nz2TQcePSnEBL9MyEaKrbbP0Gf4OpbrNhd3q4eWkODpeHf+2u4vzCtBEtKjsZjMdl3a8Ah3r8/BDwiKZpM4AW4PPjMAYhAvzBg9ujcVZWPNmJ0WE9A+TvEvTBsSYO1Xg79fTXOjQU4swGoo16SYETQogQyE2O4dYV3tSlaamxGPQ64qMMfZogjLQBAgxcA7SxpJ7MhChm+2ZgAjNA41QHVOL7HJs9yAwQeAM0TYPiHrNAmqZR3WYbdkB45bxMTHod9/59F198dhePby5jR3kLAC/trCQ+ysDFc0K/8OlEyEyIwu700DbCxXD9awndsCSH6amxAFw698z7HYX0rEYplQNcBTzl+1kBq4EXfZs8DVwXyjEIcbrcHuljZ2UlkJMUHdY1QP43L6db4+8feld7Hq8ZIKUUUxKiJAASQogQuW9VISmxJhbneRsgJMWaAjVALreH+g47WWOaATqVAudwudlS2siq2emBlLoUizcRp7Fz6DVzgqGktoNoo5685ME/x+ZmxpMWZ+61WHlDpwO70zNoC+yeEmKMrJ6dTnmTlU+dk0+sSc8L2yvodLh480AtVy/MOuNmNvz8v6PqEabBlTV4G3IUplv45PJcTAZdIF3yTGII8f5/C3wT8If5KUCrpmn+v8ZKILu/Byql7gLuAsjIyKC4uDi0Ix1HnZ2dZ9TrmWw0TcOkh243tBzfh6fDSWWzk42bNqEL8lo3wTjWB5tOFaZuPdaEQcGBnVs5NE7r8kyPcWCmW/7PjpD8nUcuOfaRa7TH/lfnG9C1llJcXIreZedYZR3FxcU02Tx4NGivO0lx8dBr2vSkaRp6BfsPl1FMBQAHGt10dbtJc9ZRXNwEgNPXanr7vhKybMdGPPaR2nrIRmYMvPPO5iG3nR3vZuPBGtZv3IRBp9hV5z19dDcco7i4fFjPd2W6xlJLFDMSGjmRrvj3nkpMXfXYnR6mUx+0v9Vw+7uvafWeO7y9ZRv16cM/3X93vwOLEfZuf58ZmsYvzjdzcOcHHAzVQCdIyAIgpdTVQL2maTuVUkX+m/vZtN/kRE3TngSeBFi2bJlWVFTU32aTUnFxMWfS65mM8ndvptPh4prLVtG69QT/OX6As5aeE+h6FizBONbWfTWwfRdnZcVzoLqd3JRYVq8a2z5HQv6rjo78nUcuOfaRKxjH/unj22jodFBUdAE7y5th81YuWrGQolkjvwqfuGUdielTKCqaD8Dm1w5gMpzkv68rIsZ06hQw/p23iEvLoqho3pjGPhRN0/jau+u5dE4GRUULhtzenlrDu2t2YZm6gLOnp/DB2hKM+mPceXXRqGZu4qa1cOOf3uelMhfTUmP5/HUXBW2R73D7u1/Q1c2DH66jXEvlq0WLhv24xw5vZU62RlHRuSEc3cQLZV7LecDHlVIngOfxpr79FkhUSvn/6nKA6hCOQYh+3bAkh9tXevOus30pcZVhmgbnT4G70VeoOV4d4IQQQoy/pBgTLV3e931/+lLWKGqAwFsH1LML3KaSes4tSOkV/ACkxpmD0gXuhe0V/Ow/h/jOv/bx6p4q3KctZNrQ6aC5q5vZmYPX//idV5iKUa8CaXC7yls4Kyth1GlrS/ISKUy3YHd6uGFxdtCCn3CUHGviS6tn8PLuKl7aWTnsx5XVd1KQZgnhyMJDyAIgTdO+o2lajqZpU4FbgI2apt0ObAJu8m32aeDVUI1BiIF8saiA+1bPACA70ZuHHK6NEPwB0DULszAZdOSnjE/9jxBCiPGXFGui1dcFrta3kOVgi34OJj7KEOgCd6yhkxNN1kD3t568i6GOrQaoqdPBN1/ay/++f4I39lbzlef3cOnDm/nXrkpcbg8Ah2u9DRAGa4HdU1yUkeVTk9lUUk+3y8NHla0szU8a9RiVUty+Mg+TXsd1i/utwDijfGl1ISumJfP9V/cHFtsdTEtXN01d3RIAhci3gK8ppY7irQn6ywSMQYgA/wxQuDZCaLU6MeoVqRYTz31hJV/yBW5CCCHOPEkxRrq63ThcbqrbbMSa9MRHja5iIT7aSIevC5x/UdFV/aTSpVnGPgPkb93965sXsud/LuOx25dgMuj42gsfccnDm/nnjgr2V3kXIB+qBXZPq2enc6Suk/WH6nC4PGMKgAA+fc5U3v3WKnKHaMJwJjDodfzulkU43R7+sb1iyO39C6AWpp/5AVComyAAoGlaMVDs+/4YsGI8nleI4bCYDSTGGANr7ISbNpuThGgjSimW5idP9HCEEEKEUGKMtytbq9VJTaudKQkjXwTVLz7KSI1vFmnT4XpmpFv6PfFPtZjGvA6Qv3NdYrQRnU5x5fxMPnbWFNYdquPRDaV848W9KAXpcWaSY4e/BGTRrHR++sYhHll3BIAleWMLgHQ6FfR633CWmRDNtNRYjtZ3DLmtvwV2JMwAjUsAJES4y06MDtsaoHabM7CegxBCiDObPzhosXZT3mwddsvn/sRHe1PgOh0uth1v5nPnTet3u1SLmQ67C7vTPer6mlZfAJQUcyq40ekUl581hcvmZrCxpJ4/FZcxPydhRPstSIslLzmG0vpOshOjR50OGMlmZMSxr7JtyO3KGjoxG3SBzJgzmSzuIQTeAChcU+D8M0BCCCHOfIkx3vf7XeWtHKpp57zC1FHvKz7KSLvdyZbSBpxubcD1XFLjvIuhNnWNvg7IX7fkH39PSikunpPBi188lx9cc9aI9quUYtWsNACWjDH9LVLNSLdQ0WLF1u0edLuj9Z1MS41Frztzm0P4SQAkBJCXHMPJZmufjjWh1NDh4LltJ4fcrtXWTaIEQEIIERH8Myh/2XIMnYLrx1CsHx9txO708Ob+WuKiDAPWz6RavAFQY8fo0+D8DXsS+gmAxsofuC3xLRYrRmZmRhyadqrGZyBlDV0RUf8DEgAJAcDMKXE4XB7Km4bukhIsL+6s5Dv/2kdly+C1RzIDJIQQkcOfAlfW0MWFM9PGVK/ib57w9sE6LpyZhlHf/2lfqsX7nGNphNBi7UavU8SZg19dccGMNH5wzVxuXJoT9H1Hghm+oOZI3cB1QHanm4oWa0TU/4AEQEIAMNvXknOwN4dgq/a13T7ZPEQAZJUASAghIkXPFDL/+m+j5a8ftXa7WT3IQqqBGaAxBECtVieJvoY9wabXKT573jTio+SzcDSmpsZi1CtK6weeATre2IWmRUYHOJAASAgAZqTHoRSU1I5fAFTT5g2AKgYJgDwejQ6HSwIgIYSIEGaDnhiTnrgoA5fOzRjTvvwBg1JQ5Kuj6U9anD8AGkMNkM0ZkvQ3MXZGvY5pqbGUDnKRN5I6wIF0gRMCgGiTnvzkmMAibePBv8L3YDNAHXYXmoZ0gRNCiAgyLyuBJflJo+7I5hcf7T3NW5SbSIpvlqc/UUY9FrOBhjHUALVapV41nM1Ij2N/9cCd4MoaOlEKpqfFjuOoJo4EQEL4zJoSN64B0KkZoIG7z7Xa/F11hr9mghBCiMntH/99dlD2488eGCz9zS/VYhpzClwkra8z2czIsPCf/TXYut1Em/oG1kfrO8lJih5z0D1ZSAqcED6zMuI40dSF3Tl4m8hgsHW7A4vGDTYDFOiqI1fVhBAiYiilglJLU5Bm4XtXzeHOc/KH3DbVYh57DZCkwIWtoTrBHa3vpDBC0t9AAiAhAmZNicejncqDDaVq3+yPxWwYtAZIAiAhhBCjpZTivy6YPqwsghSLieYxrAPUZnOSGC3ZCuHK3wmutL5vpovbo3G8sSti6n9AAiAhAmb5OsGNRyOEGl/9z9L8JJq6uul0uPrdTgIgIYQQ4yE51kRzl3NUj+12eeh0uGQGKIz5O8E9s7WcQzXtve6rarHhcHkipgMcSAAkRMDUlBhMBt24tML2zwCtnJ4MDNwJrtUqAZAQQojQS4410WLtxjOKBcH9F+skAApfRr2On1w7j6P1nVz56Lt89fndnGzynnv40+IKIigAkiYIQvgY9DoK0yzjNgOkFKyYeioAmpMZ32c7+VARQggxHpJiTLg9Gh1214jbWbdJw55J4ZYVeVwxL5PH3ynjb+8d5419Ndy6Ii/QFCGSaoAkABKih9lT4thytBFN00KymJtfdauNVIs5kG87UCOEdpsTk0EXMV1ZhBBCTIwUizd4aepyjDgA8jf1kTbY4S8hxsi3Pjabz5w7lUc3lPLshydxezSSY00kxUZOACspcEL0cF5hKvUdDh7dcDSkz1PdZiMrIYrEGCNxgzRCaLM5Jf1NCCFEyCX5Zm9arCNvhOBP15ZshckjIz6KB6+fz/qvXcQNi7O5fWXeRA9pXMkMkBA93LAkm/fKGnlk/REK0y1ctSAzJM9T02anMM2CUorc5JgBZ4AkABJCCDEeUmK9C6U2dY4mAPI+JklS4CadaamxPPzJRRM9jHEnAZAQPSil+PkN8znZZOXr/9xDbnI0C3ISg7LvsuYyfrP1N6zZu4YORyfvdsWge+NTJMRdTkVL/8/RapUASAghROglxXo/a0YzAxToWCozQGKSkBQ4IU5jNuh5/M6lpMSa+cL/7aC2zT7mfa4tXcuCxxfw1K6n6OjuAKXR7eniqV1P8VLVLZS0bO638453XQX5QBFCCBFagRmgUawF1GLtRq9TxJnlurqYHCQAEqIfqRYzT316GZ12F3c9swNbt3vU+yprLuOmf96E1WnF6em9xoLT48TpsVOt/xm/f2cLTren1/2SAieEEGI8RJv0RBl1tIwiAPJnK4SyeZAQwSQBkBADmJMZz+9uWcy+qjYe+OdHfWZoyprLuOeNe4j/eTy6H+mI/3k897xxD2XNZb22+83W3+B0D7G4nHLxvQ0PcdEvN/HUu8cCC6O225zESwAkhBBiHKTEmkc1A9Rqc0oDBDGpSAAkxCAumZvBtz82mzf21fC7DaWB209PadPQ6Oju4KldT7Hg8QWsLV0LQG1tLX+6+k84KwYJgKpA+6Ebl62YnOQYfvrGIc75+QZ+sbaEDodLZoCEEEKMi6RY4yhngLolXVtMKhIAibBXVVXFXXfdRU5ODiaTiezsbL7whS9QWVk5Ls9/14XTuWlpDr/bUMrB6vYhU9qsTis3/fOmPjNBQ3G4rbzw3+fwyr3nccGMVJ58x/t4uaomhBBiPCTHmmkeQQDkz4R4oepiXm64YMBMCCHCjQRAIqwdP36cZcuWsbCYE9kAABTjSURBVH//fp5++mmOHj3KmjVrOHDgAMuXL+fEiRMhe+7ubu+HgFKKe4oKADhU0z6slDan28kjHzwyoueLNcUCsCg3kcduX8qmB4r4xuWzuHpB1ihGL4QQQoxMcoyR5mF2geuZCeHCCgNkQggRjiQAEmHt3nvvRafTsX79ei6++GLy8vJYtWoV69evR6fTce+99/LEE0+QkZGBy+Xq9djbbruNa6+9NvDza6+9xtKlS4mKimLatGl897vfDQQ5AFOnTuWHP/whn/vc50hMTOT2228H4Mc//jGrlp1F+a+v47OXLubP3//zqZkfF7AW+BXwE+DPQLl3JuiZvc8E9q3X6U8NrBT4vW/7vwJN3puvn319r/Hnp8Ry76pC0uLMY/gNCiGEEMOTHGumeRjrAIUqE0KI8SIBkAhbzc3NvPnmm9x7773ExMT0ui8mJoZ77rmHtWvX8olPfILW1lbWr18fuL+rq4tXX32VO+64A4C33nqL22+/nfvuu48DBw7w17/+lRdffJH/9//+X6/9Pvzww8yePZsdO3bws5/9jJdeeolf//rXPPbYYyx94P+46uu/xTWlR6C1DjgAXAvcDWQAa4AO6OzuDGxm0Plag7YBzwMFvu1X+PYBfH7x58f6KxNCCCFGLTnWSFe3G7tz8M6nocqEEGK8SAAkwlZpaSmapjFnzpx+7587dy6aplFaWsqVV17Js88+G7jv5ZdfxmAwcM011wDw4IMP8o1vfIPPfvazFBQUsGrVKh566CEef/xxNO1Ud7eLLrqIb37zmxQWFjJjxgzKy8vJzMzksssuY2bBNOxJU4m7IM67cTewHbgEmAmkAVcDFmAbWEyWwH4fuuQhYowx6HboIAG4wru9cYER40pvjU9+Yn6QfnNCCCHEyCX71gIaajHUNXvX9Jn5Od3pmRBChBMJgETYG2hdAX/gopTijjvu4JVXXsFqtQLw7LPPctNNNxEVFQXAzp07efDBB7FYLIGv2267ja6uLmprawP7XLZsWa/nuPnmm7Hb7UybNo0Dzz/ER5vf5NY5t2LUGaEZ8AB5PR6gA3JANSruXHBn4Obz8s5j7917yXbkQY4epRTx5njuWnoXf7nnL2P+HQkhhBBjlRzrvSA3VCOEnhkOwdhOiPEWsgBIKRWllNqmlPpIKXVAKfUj3+3TlFIfKqVKlVL/UEqZQjUGMbnNmDEDpRQHDhzo9/5Dhw6hlKKgoICrr74ag8HAq6++Sn19PevXrw+kvwF4PB5+8IMfsGfPnsDX3r17KS0tJS0tLbBdbGxsr+fIzc3l8OHDPPHEE6QmJ3Jy7RNs+PYmDO7BV7vW6XTcf/b9vW4rSC5gavwcYt0X8s5t9bR9u40/XPkHsuKlyYEQQoiJ558BGioA6pnhEIzthBhvoZwBcgCrNU1bCCwCPqaUOht4CHhE07QZQAsghQ+iX8nJyVx++eU89thjgZkdP6vVyh//+EeuuOIKkpOTMZvN3HTTTTz77LP84x//YMqUKVx00UWB7ZcsWUJJSQmFhYV9vgyGwYOZqKgorrrqKr7+Pz8j89MPU3a4lO/mf5fojGjQAyd7bOzWoSoVN190MwXJBX32lZo7HUfNEbISowK3ffDBB6P6/QghhBDBNNwZoDsW3OHNhBiEUWfslQkhRDhRPesfQvYkSsUAW4AvAm8AUzRNcymlzgF+qGna5YM9fllcnLZj6dKQj3O8tLa2kpiYONHDmBTKbDbO3b2bguhofjp1KjOioymz2/nu8eMcs9t5f9EipkVHA7C5tZVL9u5lZnQ0V6ek8ND06YH9vNXczNX79/Od3Fw+kZ6OQSn2d3Wxrb2dXxZ4A5WpH3zAfdnZPJCbG3jc/9bW4tI0VsbFoXPDH49X8lR7PYeXL2eKET63fx/rOm08kALZRh3/bDWywerk6MoVZJrN7K2vZ+GhQ2xfsoRlcXF8WNfKBSV7uTsrk3uzs9nX1cX9ZWVUOhwcX7mSqVFRiDOD/J1HLjn2kWuyH3unW2NneTP5KbFkJgz8eWRz2dhevQOPxzPgNjqdjuVZy4g2RIdiqGFnsh/7M4XavHmnpmnLhtpu8EvfYx2EUnpgJ1AI/BEoA1o1TfO30aoEsgd47F3AXQDzjEZaW1tDOdRx5Xa7z6jXE0opwIbCQn5VV8cdBw/S4HKRajBwaXw8TxYUkORw0OpwALBA08g0GDhotfJkTk6v3/FKnY5/TJvGr+rq+HVFBQalKDCbuTU5ObCdx+PBZrP1epzR4eCx+nq+brfj0iDfYOaPWfkkORw4HPC1pOnotFoebm6jze1mtknHw2n5GLtstNpsuN3eTjodHR20ut3Euzw8lJbHY021PFlTw8LoaL6fkcF/nzxJe3s7rXb7+P1yRUjJ33nkkmMfuSbzsdc5HJgbGljW3IK+woOm09GdlIQjLQ2Pue9yDFOj8zlhPYHntAvpCm9t7tTofBydDhw4xukVTKzJfOwjUUgDIE3T3MAipVQi8DLQXzuvfqegNE17EngSYNmyZVrijh0hG+d4Ky4upqioaKKHMWkkAk8Pc9uTg9x3g+9rJI+93fflt/jHb3NsXiaJN8wH4Gu/3MjSvCTqb1kMwInGLi5+eDMN507le1fPpa24GK3Hsb7vqQ/pdLgovfe8Xs9z1yDjEpOT/J1HLjn2kWvSHvu1a+Gmm8DpBM03q+PxYG5vx2yzwYsvwhVX9HpIIuBsLmP1k9+gpvtt3NiwmCzcueBO7j/7fvL6SQM/k03aY3+mGaBx1ulCGgD5aZrWqpQqBs4GEpVSBt8sUA5QPR5jEGLMysp4cP3jFP38LXDY0CwW7p5xIR33fjmwydTUWK5blM2aD8u566LpfXZR1Wpjblb8eI5aCCGEGFhZmTf4Oa3WFvAGRE6n9/69e6Ggd1BTkFxAouNu7lz4I3563fxxGrAQYxfKLnBpvpkflFLReFdLOQRsAm7ybfZp4NVQjUGIoFm7FhYs4LL3XyPGbgVNQ3V0cPOeN/n8vdd57/f50upCnG6NJzYf67ULj0ejqtVGTmJk5EMLIYSYBH7zG2+QMxinEx7pu6hpu91Jm81JblJMPw8SInyFsgtcJrBJKbUX73KR6zRNex34FvA1pdRRvCUesgiKCG89ro4Z3K5ed5k8box2m/f+sjLAOwt0/eJs1nxQTqvjVIFoY5eDbpeH7CQJgIQQQoSJNWuGFwA903dR08pmGwA5EgCJSSZkAZCmaXs1TVusadoCTdPmaZr2Y9/txzRNW6FpWqGmaTdrmhYZ1XFi8hrF1bH7VhWS1VRN4s8egfh40OlIyUrjJ28/RmF7XYgHLIQQQgxT5zAXK+1nu4oWb9pcbrJc2BOTSyhngIQ4M4zi6tjU7e/w1t/u49wta6GjAzQNfWcnn/zoLc6+fnWvlDkhhBBiwliGuVhpP9tVtsgMkJicJAASYigjvTrmS5kzOeyYPO5em5g8bnQ2a6+UOSGEEGLC3HEHGAdf1BSjEe7su6hpRbOVWJOepJghHi9EmJEASIihjPTq2BgKSoUQQohx9fWvDy8Auv/+PjdXttjISYpBDbP1sBDhQgIgIYYy0qtjYygoFUIIIcZVQYF3nZ+YmL6fdUaj9/YXX+zTAhugssUq9T9iUpIASIihjPTq2BgKSoUQQohxd8UV3nV+7roL4uPRlKLDFEPnpz7nvf20RVABNE0LzAAJMdlIACTEUAa5OubWG/peHRtDQakQQggxIQoK4A9/gLY29pY3M//+F9j85R/0O/MD0GZz0ulwkSNLO4hJSAIgIYZjgKtjJR+/pe/VsTEUlAohhBATbU5mPCaDjt0nWwbc5kSTtwW2zACJyUgCICGGq8fVMdxu1m4pYcr/PdX36tgYCkqFEEKIiWYy6JifncCO8hY0Tet3m7cO1KLXKZbmJ43z6IQYOwmAhBgFpRSfWJ5LisXc984eKXMevb73fUMUlAohhBDh4MIZaeypaOXuNTtp7Oy9Zr3Ho/Hq7iounJFKWlw/n4NChDkJgIQIBV/KXPXVV0N8POh03n/vumvAglIhhBAiXNy3upBvXzGbTSUNXPbIO/xnX03gvg+ON1HdZuf6JTkTOEIhRk8CICFCpaCAo1/9aiBljrY2bwqdzPwIIYQIc3qd4u6LCnj9y+eTnRjNPc/u4svP7aalq5uXd1VhMRu4dE7GRA9TiFExTPQAhBBCCCFEeJqZEce/7jmXPxWX8eiGUrYea8LqcHHF/EyiTfqhdyBEGJIZICGEEEIIMSCjXseXL57BK/eeR0qsia5uNzdK+puYxGQGSAghhBBCDGledgKv3nceR2o7mZ+TMNHDEWLUZAZICCGEEEIMi9mgl+BHTHoSAAkhhBBCCCEihgRAQgghhBBCiIghAZAQQgghhBAiYkgAJIQQQgghhIgYEgAJIYQQQgghIoYEQEIIIYQQQoiIIQGQEEIIIYQQImJIACSEEEIIIYSIGBIACSGEEEIIISKG0jRtoscwJKVUA1A+0eMIolSgcaIHIcaFHOvIJcc+csmxj1xy7COXHPvwkK9pWtpQG02KAOhMo5TaoWnasokehwg9OdaRS4595JJjH7nk2EcuOfaTi6TACSGEEEIIISKGBEBCCCGEEEKIiCEB0MR4cqIHIMaNHOvIJcc+csmxj1xy7COXHPtJRGqAhBBCCCGEEBFDZoCEEEIIIYQQEUMCICGEEEIIIUTEkABoGJRSuUqpTUqpQ0qpA0qpr/huT1ZKrVNKlfr+TfLdPlsptVUp5VBKPXDavu737WO/Uuo5pVTUAM/5ad9+S5VSn/bdFqOUekMpVeLbxy9C/dojTbgc69Pu/7dSan8oXq84JZyOvVLKpJR6Uil1xPf3fmMoX3ukC7Njf6tSap9Saq9S6k2lVGooX3ukm6Bj/6ZSqlUp9fppt09TSn3oe85/KKVMoXrdIuyO/bNKqcO+x/9VKWUM1esWPpqmydcQX0AmsMT3fRxwBJgL/BL4tu/2bwMP+b5PB5YDDwIP9NhPNnAciPb9/ALwmX6eLxk45vs3yfd9EhADrPJtYwLeBa6Y6N/PmfQVLse6x/03AH8H9k/07+ZM/wqnYw/8CPip73sdkDrRv58z+Stcjj1gAOr9x9v3/D+c6N/Pmfw13sfed9/FwDXA66fd/gJwi+/7x4EvTvTv50z+CrNjfyWgfF/PybEP/ZfMAA2Dpmk1mqbt8n3fARzC+x/+WuBp32ZPA9f5tqnXNG074OxndwYgWillwBvQVPezzeXAOk3TmjVNawHWAR/TNM2qadom33N0A7uAnCC9TEH4HGsApZQF+Brw0yC9PDGIcDr2wOeAn/uex6NpmqwuHkJhdOz9J0CxSikFxA/weBEkE3Ds0TRtA9DR8zbf8V4NvHj6c4rQCJdj77v9P5oPsA05tws5CYBGSP3/9u4s1KoqDOD4/6NEosEmM83qFiVlUDZAAz0IlUFE9FAPRRJFREKBRC+9JKEPPZSUNENQRASFRvaSgRTNEYjaYKRlNCBlkWkTpH49rGWd9B7vPXc4Z3fP/weLc8+ezlr749x9vrXX3jtiADgb+ACYlplboHyRKL0DbWXmd8D9wNfAFuCXzHxtkEWPA75pef9tndZaj8MpvQirR9IODa0BsV4MPAD8PuJGaER6Gfv63QZYHBFrIuLFiJg2iuaoA72MfWb+BSwAPqL8gJoNPDWK5qgDXYp9O0cB2zJzZ32/z3Ff46fHsW+txyRgPvDqSNbX8JkAdaD2yC8HFmbm9hGsfwSlZ+EkYAall++GwRYdZNo/9yuvPQzPA8sy88tO66Gh9TrWETEHOCUzX+r0szU6vY49pSdxJvBOZp4DvEc5uGqc9Tr29cfPAsoPsRnAeuDuTuuhznUx9m03Mcg0n1PSBQ2IfatHgTcz860Rrq9hMgEapnpgWg48l5kr6uTvI2J6nT+dMnZ7fy4FNmfm1trTtwK4KCLOj4i1tVxF6fk5vmW9mfz3dOqTwMbMfHD0LdPeGhLrC4FzI+Ir4G1gVkS8MTYtVDsNif1PlLN+e5LfF4FzxqB52o+GxH4OQGZ+UYfCvABcNEZNVBtdjn07PwKH1w5O2Pe4r3HQkNjvqcsiYCpl6LvGmQnQMNSxuU8BGzJzacuslcCeu/fcCLw8xKa+Bi6Icje3oFwMtyEzP8jMObWsBFYB8yLiiNqzMK9OIyKWAFOAhWPVPv2rKbHOzMcyc0ZmDgAXA59n5tyxaqf21aDYJ/AKMLdu7xLg0zFootpoSuyB74DZETG1bu8yynUJGic9iP2g6vf+deCaDj5To9CU2Ne63EK5NvC6zNw9kvaoQ9mAOzE0vVB+gCZlOMLaWq6gjNldDWysr0fW5Y+l9PBtB7bVvw+r8+4FPgM+Bp4FJrf5zJuBTbXcVKfNrPXY0FKPW3q9fyZSaUqs95o/gHeB66vYAycCb9a6rAZO6PX+mcilYbG/rf6PX09JhI/q9f6ZyKVHsX8L2Ar8Ude/vE4/mXIB/CbKmd9B17dMyNjvBL5oqcc9vd4/E71E3fGSJEmSNOE5BE6SJElS3zABkiRJktQ3TIAkSZIk9Q0TIEmSJEl9wwRIkiRJUt8wAZIkNUZE7KoPDvwkItZFxJ0Rsd9jVUQMRMT13aqjJOn/zQRIktQkf2R5cOAZlAeBXgEsGmKdAcAESJI0LD4HSJLUGBHxa2Ye0vL+ZOBD4GjKA2KfBQ6us2/PzHcj4n3gdGAz8AywDLgPmAtMBh7JzCe61ghJUqOZAEmSGmPvBKhO+xk4DdgB7M7MPyPiVOD5zDwvIuYCd2XmlXX5W4FjMnNJREwG3gGuzczNXW2MJKmRDux1BSRJGkLU10nAwxExB9gFzGqz/DzgzIi4pr6fApxKOUMkSepzJkCSpMaqQ+B2AT9QrgX6HjiLcg3rn+1WA+7IzFVdqaQk6X/FmyBIkhopIqYCjwMPZxmvPQXYkpm7gfnAAXXRHcChLauuAhZExKS6nVkRcTCSJOEZIElSsxwUEWspw912Um56sLTOexRYHhHXAq8Dv9Xp64GdEbEOeBp4iHJnuDUREcBW4OpuNUCS1GzeBEGSJElS33AInCRJkqS+YQIkSZIkqW+YAEmSJEnqGyZAkiRJkvqGCZAkSZKkvmECJEmSJKlvmABJkiRJ6ht/A6imO9vDtCuQAAAAAElFTkSuQmCC\n"
            ]
          },
          "metadata": {}
        }
      ],
      "execution_count": 11,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    }
  ],
  "metadata": {
    "kernel_info": {
      "name": "python3"
    },
    "language_info": {
      "pygments_lexer": "ipython3",
      "codemirror_mode": {
        "version": 3,
        "name": "ipython"
      },
      "mimetype": "text/x-python",
      "file_extension": ".py",
      "name": "python",
      "nbconvert_exporter": "python",
      "version": "3.5.5"
    },
    "kernelspec": {
      "name": "python3",
      "language": "python",
      "display_name": "Python 3"
    },
    "nteract": {
      "version": "0.14.2"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 4
}