ES_ML_Capítulo_07_SVR_para_predecir_stocks.ipynb

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    "colab": {
      "name": "EN - ML Chapter 07: SVM to predict stock prices.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oGTFBnE2jZ7l"
      },
      "source": [
        " <p><img alt=\"Colaboratory logo\" height=\"45px\" src=\"https://www.quantreo.com/wp-content/uploads/2021/10/Original-on-Transparent.png\" align=\"left\" hspace=\"10px\" vspace=\"0px\"></p>\n",
        "\n",
        "\n",
        "# Support vector machine to predict stock prices\n",
        "\n",
        "</br>\n",
        "\n",
        "In this chapter, we will explain how the SVM works theorically. Then, we will apply this algorithm to predict stock price and create a trading strategy\n",
        "\n",
        "### Summary\n",
        "* How a SVM works theorically\n",
        "* Predict stock price using a SVM\n",
        "* Create trading strategy \n",
        "\n",
        "</br>\n",
        "\n",
        "💰 Únete a la comunidad de [Discord](https://discord.gg/z3dx5XpkX4)\n",
        "\n",
        "📚 Puedes leer nuestro libro en [Amazon](https://www.amazon.es/Python-para-finanzas-trading-algor%C3%ADtmico-ebook/dp/B0BT4ZS9Q3/)\n",
        "\n",
        "🖥️ El canal de [YouTube de Quantreo's](https://www.youtube.com/channel/UCp7jckfiEglNf_Gj62VR0pw) (en inglés) y el de [Frogames](https://www.youtube.com/channel/UCMUxXNYrVCv6-bQakhomvBg) en español\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KCTZot8bjZXu",
        "outputId": "00bcd380-6161-48e6-ebd6-64a41ede2671"
      },
      "source": [
        "! pip install yfinance\n",
        "! pip install ta"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: yfinance in /usr/local/lib/python3.7/dist-packages (0.1.66)\n",
            "Requirement already satisfied: multitasking>=0.0.7 in /usr/local/lib/python3.7/dist-packages (from yfinance) (0.0.9)\n",
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            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20->yfinance) (2.10)\n",
            "Requirement already satisfied: ta in /usr/local/lib/python3.7/dist-packages (0.7.0)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from ta) (1.19.5)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from ta) (1.1.5)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas->ta) (2018.9)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas->ta) (2.8.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas->ta) (1.15.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V0OnBCXkj5v5"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "plt.style.use('seaborn')\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "import yfinance as yf\n",
        "import ta"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ONfw5f_ckiUB"
      },
      "source": [
        "import matplotlib as mpl\n",
        "from matplotlib import cycler\n",
        "\n",
        "colors = cycler('color',\n",
        "                ['#669FEE', '#66EE91', '#9988DD',\n",
        "                 '#EECC55', '#88BB44', '#FFBBBB'])\n",
        "plt.rc('figure', facecolor='#313233')\n",
        "plt.rc('axes', facecolor=\"#313233\", edgecolor='none',\n",
        "       axisbelow=True, grid=True, prop_cycle=colors,\n",
        "       labelcolor='gray')\n",
        "plt.rc('grid', color='474A4A', linestyle='solid')\n",
        "plt.rc('xtick', color='gray')\n",
        "plt.rc('ytick', direction='out', color='gray')\n",
        "plt.rc('legend', facecolor=\"#313233\", edgecolor=\"#313233\")\n",
        "plt.rc(\"text\", color=\"#C9C9C9\")\n",
        "plt.rc('figure', facecolor='#313233')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BXBodaMWkloH"
      },
      "source": [
        "# How a SVM algorithm works theorically\n",
        "Look the video and the attached PDF."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "49Zxaw3wkqxZ"
      },
      "source": [
        "# Predict stock prices using a SVR (SVM regressor)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OEi6a4qQk1aO"
      },
      "source": [
        "\n",
        "### Import the data from Yahoo (esiest choice)\n",
        "**IMPORTANT**: You can import the data from Yahoo or from MT5. But you need to have a Windows device to use MT5. To avoid this problem, you can see the video introduction video of the chapter MetaTrader 5 Live Trading! \n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G_upH5VIkpI0",
        "outputId": "009effc7-2ab0-4317-a546-f6b732c90178"
      },
      "source": [
        "# Import the data\n",
        "df = yf.download(\"GOOG\")[[\"Open\", \"High\", \"Low\", \"Adj Close\", \"Volume\"]]\n",
        "\n",
        "df.columns = [\"open\", \"high\", \"low\", \"close\", \"volume\"]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PTC7w6EslL2N"
      },
      "source": [
        "### Features Engineering\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P3Dkxmqtk-0I"
      },
      "source": [
        "def feature_engineering(df):\n",
        "  \"\"\" Create new variables\"\"\"\n",
        "  \n",
        "  # We copy the dataframe to avoid interferences in the data\n",
        "  df_copy = df.dropna().copy()\n",
        "  \n",
        "  # Create the returns\n",
        "  df_copy[\"returns\"] = df_copy[\"close\"].pct_change(1)\n",
        "\n",
        "  # Create the SMAs\n",
        "  df_indicators = ta.add_all_ta_features(\n",
        "  df, open=\"open\", high=\"high\", low=\"low\", close=\"close\", volume=\"volume\", fillna=True).shift(1)\n",
        "  \n",
        "  dfc = pd.concat((df_indicators, df_copy), axis=1)\n",
        "\n",
        "  return dfc.dropna()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b_QxoQ8YCVB_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 640
        },
        "outputId": "86cc5f5b-9dbe-4521-8264-625d5db82b3b"
      },
      "source": [
        "dfc = feature_engineering(df)\n",
        "dfc"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <th>volatility_dcw</th>\n",
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              "      <th>trend_macd</th>\n",
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              "      <th>trend_visual_ichimoku_b</th>\n",
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              "      <th>trend_psar_down</th>\n",
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              "      <th>trend_psar_down_indicator</th>\n",
              "      <th>trend_stc</th>\n",
              "      <th>momentum_rsi</th>\n",
              "      <th>momentum_stoch_rsi</th>\n",
              "      <th>momentum_stoch_rsi_k</th>\n",
              "      <th>momentum_stoch_rsi_d</th>\n",
              "      <th>momentum_tsi</th>\n",
              "      <th>momentum_uo</th>\n",
              "      <th>momentum_stoch</th>\n",
              "      <th>momentum_stoch_signal</th>\n",
              "      <th>momentum_wr</th>\n",
              "      <th>momentum_ao</th>\n",
              "      <th>momentum_kama</th>\n",
              "      <th>momentum_roc</th>\n",
              "      <th>momentum_ppo</th>\n",
              "      <th>momentum_ppo_signal</th>\n",
              "      <th>momentum_ppo_hist</th>\n",
              "      <th>others_dr</th>\n",
              "      <th>others_dlr</th>\n",
              "      <th>others_cr</th>\n",
              "      <th>returns</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2004-08-20</th>\n",
              "      <td>49.813290</td>\n",
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              "      <td>49.982655</td>\n",
              "      <td>44871361.0</td>\n",
              "      <td>3.656206e+06</td>\n",
              "      <td>4.487136e+07</td>\n",
              "      <td>0.081482</td>\n",
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              "      <td>50.000000</td>\n",
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              "      <td>-4.140941e+07</td>\n",
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              "      <td>53.907942</td>\n",
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              "      <td>16.180589</td>\n",
              "      <td>0.513580</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>51.835709</td>\n",
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              "      <td>...</td>\n",
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              "      <td>631.172755</td>\n",
              "      <td>8.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
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              "      <td>94.131072</td>\n",
              "      <td>74.102585</td>\n",
              "      <td>-5.868928</td>\n",
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              "      <td>51.709669</td>\n",
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              "      <td>-0.808972</td>\n",
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              "      <td>7.942987</td>\n",
              "      <td>7.643300</td>\n",
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              "      <td>0.079430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2004-08-23</th>\n",
              "      <td>50.316402</td>\n",
              "      <td>54.336334</td>\n",
              "      <td>50.062355</td>\n",
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              "      <td>44.356538</td>\n",
              "      <td>44.356538</td>\n",
              "      <td>-3.959039e+07</td>\n",
              "      <td>1079.429868</td>\n",
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              "      <td>51.967712</td>\n",
              "      <td>55.937828</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>51.328442</td>\n",
              "      <td>55.482871</td>\n",
              "      <td>47.174014</td>\n",
              "      <td>16.187627</td>\n",
              "      <td>0.815847</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>47.800831</td>\n",
              "      <td>54.336334</td>\n",
              "      <td>51.068583</td>\n",
              "      <td>12.576084</td>\n",
              "      <td>0.941311</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.316704</td>\n",
              "      <td>0.063341</td>\n",
              "      <td>0.253364</td>\n",
              "      <td>51.967712</td>\n",
              "      <td>...</td>\n",
              "      <td>0.042838</td>\n",
              "      <td>2.941683</td>\n",
              "      <td>92.892055</td>\n",
              "      <td>595.653649</td>\n",
              "      <td>-918.560809</td>\n",
              "      <td>-920.447527</td>\n",
              "      <td>1.886718</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>642.061120</td>\n",
              "      <td>631.172755</td>\n",
              "      <td>12.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>47.800831</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>41.163075</td>\n",
              "      <td>76.712317</td>\n",
              "      <td>74.972495</td>\n",
              "      <td>-23.287683</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>52.919278</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-8.373489</td>\n",
              "      <td>-2.321875</td>\n",
              "      <td>-6.051614</td>\n",
              "      <td>1.006371</td>\n",
              "      <td>1.001341</td>\n",
              "      <td>9.029294</td>\n",
              "      <td>0.010064</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2004-08-24</th>\n",
              "      <td>55.168217</td>\n",
              "      <td>56.528118</td>\n",
              "      <td>54.321388</td>\n",
              "      <td>54.495735</td>\n",
              "      <td>18342897.0</td>\n",
              "      <td>7.036644e+06</td>\n",
              "      <td>8.615713e+07</td>\n",
              "      <td>0.081672</td>\n",
              "      <td>7.949639e+07</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>38.803061</td>\n",
              "      <td>41.579799</td>\n",
              "      <td>2.006947e+06</td>\n",
              "      <td>1090.292935</td>\n",
              "      <td>51.764201</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>52.810387</td>\n",
              "      <td>56.833902</td>\n",
              "      <td>48.786871</td>\n",
              "      <td>15.237592</td>\n",
              "      <td>0.709437</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>52.590655</td>\n",
              "      <td>56.095851</td>\n",
              "      <td>49.085459</td>\n",
              "      <td>13.330108</td>\n",
              "      <td>0.771751</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>47.800831</td>\n",
              "      <td>56.528118</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>16.525702</td>\n",
              "      <td>0.767123</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.604539</td>\n",
              "      <td>0.171580</td>\n",
              "      <td>0.432958</td>\n",
              "      <td>52.810387</td>\n",
              "      <td>...</td>\n",
              "      <td>0.067978</td>\n",
              "      <td>3.898774</td>\n",
              "      <td>19.269197</td>\n",
              "      <td>595.796446</td>\n",
              "      <td>-918.781017</td>\n",
              "      <td>-920.030899</td>\n",
              "      <td>1.249882</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>642.061120</td>\n",
              "      <td>631.172755</td>\n",
              "      <td>12.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>48.149922</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>63.509651</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>98.723193</td>\n",
              "      <td>34.487343</td>\n",
              "      <td>50.856191</td>\n",
              "      <td>73.899860</td>\n",
              "      <td>-49.143809</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>52.633457</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-12.703524</td>\n",
              "      <td>-4.398205</td>\n",
              "      <td>-8.305319</td>\n",
              "      <td>-4.140761</td>\n",
              "      <td>-4.228934</td>\n",
              "      <td>4.514651</td>\n",
              "      <td>-0.041408</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2004-08-25</th>\n",
              "      <td>55.412300</td>\n",
              "      <td>55.591629</td>\n",
              "      <td>51.591621</td>\n",
              "      <td>52.239197</td>\n",
              "      <td>15319808.0</td>\n",
              "      <td>-3.322809e+06</td>\n",
              "      <td>7.083732e+07</td>\n",
              "      <td>-0.032744</td>\n",
              "      <td>6.320123e+07</td>\n",
              "      <td>73.185672</td>\n",
              "      <td>-47.863040</td>\n",
              "      <td>11.765519</td>\n",
              "      <td>-4.497591e+05</td>\n",
              "      <td>1045.146506</td>\n",
              "      <td>51.972026</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>52.667589</td>\n",
              "      <td>56.186993</td>\n",
              "      <td>49.148186</td>\n",
              "      <td>13.364590</td>\n",
              "      <td>0.439138</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>52.728195</td>\n",
              "      <td>56.357094</td>\n",
              "      <td>49.099297</td>\n",
              "      <td>13.764547</td>\n",
              "      <td>0.432624</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>47.800831</td>\n",
              "      <td>56.528118</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>16.570508</td>\n",
              "      <td>0.508562</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.643152</td>\n",
              "      <td>0.265895</td>\n",
              "      <td>0.377257</td>\n",
              "      <td>52.667589</td>\n",
              "      <td>...</td>\n",
              "      <td>0.092612</td>\n",
              "      <td>4.791987</td>\n",
              "      <td>2.510662</td>\n",
              "      <td>595.769547</td>\n",
              "      <td>-918.739536</td>\n",
              "      <td>-919.772627</td>\n",
              "      <td>1.033091</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>642.061120</td>\n",
              "      <td>631.172755</td>\n",
              "      <td>12.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>48.485050</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>66.767328</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>97.682465</td>\n",
              "      <td>36.533952</td>\n",
              "      <td>57.305952</td>\n",
              "      <td>61.624820</td>\n",
              "      <td>-42.694048</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>52.704386</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-17.874792</td>\n",
              "      <td>-7.093522</td>\n",
              "      <td>-10.781270</td>\n",
              "      <td>1.077523</td>\n",
              "      <td>1.071759</td>\n",
              "      <td>5.640819</td>\n",
              "      <td>0.010775</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2004-08-26</th>\n",
              "      <td>52.284027</td>\n",
              "      <td>53.798351</td>\n",
              "      <td>51.746044</td>\n",
              "      <td>52.802086</td>\n",
              "      <td>9232276.0</td>\n",
              "      <td>-3.053906e+06</td>\n",
              "      <td>8.006960e+07</td>\n",
              "      <td>-0.027585</td>\n",
              "      <td>5.491487e+07</td>\n",
              "      <td>63.063788</td>\n",
              "      <td>-18.215626</td>\n",
              "      <td>4.270233</td>\n",
              "      <td>-5.348769e+05</td>\n",
              "      <td>1056.408195</td>\n",
              "      <td>52.039585</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>52.694489</td>\n",
              "      <td>55.844177</td>\n",
              "      <td>49.544800</td>\n",
              "      <td>11.954528</td>\n",
              "      <td>0.517081</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>52.738988</td>\n",
              "      <td>56.052569</td>\n",
              "      <td>49.425408</td>\n",
              "      <td>12.565961</td>\n",
              "      <td>0.509521</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>47.800831</td>\n",
              "      <td>56.528118</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>16.562050</td>\n",
              "      <td>0.573060</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.710978</td>\n",
              "      <td>0.354911</td>\n",
              "      <td>0.356067</td>\n",
              "      <td>52.694489</td>\n",
              "      <td>...</td>\n",
              "      <td>0.119345</td>\n",
              "      <td>5.625402</td>\n",
              "      <td>26.585978</td>\n",
              "      <td>595.593042</td>\n",
              "      <td>-918.467347</td>\n",
              "      <td>-919.555080</td>\n",
              "      <td>1.087733</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>52.164474</td>\n",
              "      <td>642.061120</td>\n",
              "      <td>631.172755</td>\n",
              "      <td>12.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>48.806773</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>71.412902</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>96.828990</td>\n",
              "      <td>42.002655</td>\n",
              "      <td>68.207750</td>\n",
              "      <td>58.789964</td>\n",
              "      <td>-31.792250</td>\n",
              "      <td>0.595020</td>\n",
              "      <td>53.161271</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-22.949050</td>\n",
              "      <td>-10.264628</td>\n",
              "      <td>-12.684422</td>\n",
              "      <td>1.801882</td>\n",
              "      <td>1.785841</td>\n",
              "      <td>7.544342</td>\n",
              "      <td>0.018019</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-11-12</th>\n",
              "      <td>2942.139893</td>\n",
              "      <td>2970.044922</td>\n",
              "      <td>2933.889893</td>\n",
              "      <td>2934.959961</td>\n",
              "      <td>623200.0</td>\n",
              "      <td>4.704680e+08</td>\n",
              "      <td>1.386930e+09</td>\n",
              "      <td>0.057071</td>\n",
              "      <td>3.937262e+06</td>\n",
              "      <td>73.590487</td>\n",
              "      <td>67978.690879</td>\n",
              "      <td>54648.068474</td>\n",
              "      <td>-1.943199e+04</td>\n",
              "      <td>8027.143835</td>\n",
              "      <td>2915.785007</td>\n",
              "      <td>58.768128</td>\n",
              "      <td>2897.875000</td>\n",
              "      <td>3033.369657</td>\n",
              "      <td>2762.380343</td>\n",
              "      <td>9.351311</td>\n",
              "      <td>0.636850</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2951.299325</td>\n",
              "      <td>3006.510311</td>\n",
              "      <td>2896.088338</td>\n",
              "      <td>3.741470</td>\n",
              "      <td>0.352028</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2734.969971</td>\n",
              "      <td>3020.689941</td>\n",
              "      <td>2877.829956</td>\n",
              "      <td>9.859638</td>\n",
              "      <td>0.699951</td>\n",
              "      <td>1.688111</td>\n",
              "      <td>41.729046</td>\n",
              "      <td>38.176665</td>\n",
              "      <td>3.552381</td>\n",
              "      <td>2945.253337</td>\n",
              "      <td>...</td>\n",
              "      <td>0.200739</td>\n",
              "      <td>25.099159</td>\n",
              "      <td>82.249049</td>\n",
              "      <td>16.734583</td>\n",
              "      <td>51.001968</td>\n",
              "      <td>39.047592</td>\n",
              "      <td>11.954376</td>\n",
              "      <td>2956.755005</td>\n",
              "      <td>2872.844971</td>\n",
              "      <td>2914.799988</td>\n",
              "      <td>2822.010010</td>\n",
              "      <td>2758.267517</td>\n",
              "      <td>2779.869995</td>\n",
              "      <td>100.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>92.0</td>\n",
              "      <td>2853.254123</td>\n",
              "      <td>2876.238007</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>85.593629</td>\n",
              "      <td>61.484916</td>\n",
              "      <td>0.787685</td>\n",
              "      <td>0.597338</td>\n",
              "      <td>0.664658</td>\n",
              "      <td>18.251233</td>\n",
              "      <td>50.830141</td>\n",
              "      <td>88.452885</td>\n",
              "      <td>75.863044</td>\n",
              "      <td>-11.547115</td>\n",
              "      <td>126.919216</td>\n",
              "      <td>2902.012794</td>\n",
              "      <td>2.197670</td>\n",
              "      <td>-7.405755</td>\n",
              "      <td>-1.838274</td>\n",
              "      <td>-5.567481</td>\n",
              "      <td>1.974472</td>\n",
              "      <td>1.955232</td>\n",
              "      <td>5887.897077</td>\n",
              "      <td>0.019745</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-11-15</th>\n",
              "      <td>2956.629883</td>\n",
              "      <td>2997.189941</td>\n",
              "      <td>2929.080078</td>\n",
              "      <td>2992.909912</td>\n",
              "      <td>852000.0</td>\n",
              "      <td>4.712129e+08</td>\n",
              "      <td>1.387782e+09</td>\n",
              "      <td>0.086420</td>\n",
              "      <td>1.042813e+07</td>\n",
              "      <td>79.155859</td>\n",
              "      <td>89275.103535</td>\n",
              "      <td>70265.319997</td>\n",
              "      <td>1.734102e+04</td>\n",
              "      <td>8027.143835</td>\n",
              "      <td>2927.824705</td>\n",
              "      <td>59.702302</td>\n",
              "      <td>2905.845496</td>\n",
              "      <td>3043.983780</td>\n",
              "      <td>2767.707211</td>\n",
              "      <td>9.507614</td>\n",
              "      <td>0.815135</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2953.905322</td>\n",
              "      <td>3009.034302</td>\n",
              "      <td>2898.776343</td>\n",
              "      <td>3.732617</td>\n",
              "      <td>0.853758</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2734.969971</td>\n",
              "      <td>3020.689941</td>\n",
              "      <td>2877.829956</td>\n",
              "      <td>9.832593</td>\n",
              "      <td>0.902772</td>\n",
              "      <td>1.403358</td>\n",
              "      <td>43.558950</td>\n",
              "      <td>39.253122</td>\n",
              "      <td>4.305828</td>\n",
              "      <td>2950.616659</td>\n",
              "      <td>...</td>\n",
              "      <td>0.206967</td>\n",
              "      <td>25.134248</td>\n",
              "      <td>94.154888</td>\n",
              "      <td>53.136914</td>\n",
              "      <td>55.246436</td>\n",
              "      <td>42.736290</td>\n",
              "      <td>12.510146</td>\n",
              "      <td>2960.880005</td>\n",
              "      <td>2872.844971</td>\n",
              "      <td>2916.862488</td>\n",
              "      <td>2822.010010</td>\n",
              "      <td>2744.875061</td>\n",
              "      <td>2779.869995</td>\n",
              "      <td>96.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>92.0</td>\n",
              "      <td>2866.648989</td>\n",
              "      <td>2876.238007</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>84.184070</td>\n",
              "      <td>60.752275</td>\n",
              "      <td>0.614397</td>\n",
              "      <td>0.635376</td>\n",
              "      <td>0.621357</td>\n",
              "      <td>18.753480</td>\n",
              "      <td>48.654285</td>\n",
              "      <td>85.209330</td>\n",
              "      <td>81.219106</td>\n",
              "      <td>-14.790670</td>\n",
              "      <td>117.862473</td>\n",
              "      <td>2912.906921</td>\n",
              "      <td>2.230219</td>\n",
              "      <td>-8.570740</td>\n",
              "      <td>-3.184767</td>\n",
              "      <td>-5.385973</td>\n",
              "      <td>-0.172070</td>\n",
              "      <td>-0.172218</td>\n",
              "      <td>5877.593698</td>\n",
              "      <td>-0.001721</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-11-16</th>\n",
              "      <td>3000.000000</td>\n",
              "      <td>3009.540039</td>\n",
              "      <td>2973.050049</td>\n",
              "      <td>2987.760010</td>\n",
              "      <td>812400.0</td>\n",
              "      <td>4.710555e+08</td>\n",
              "      <td>1.386970e+09</td>\n",
              "      <td>0.045258</td>\n",
              "      <td>8.340717e+06</td>\n",
              "      <td>78.508707</td>\n",
              "      <td>126484.413124</td>\n",
              "      <td>72085.226066</td>\n",
              "      <td>1.542460e+04</td>\n",
              "      <td>8013.331523</td>\n",
              "      <td>2941.969625</td>\n",
              "      <td>57.381070</td>\n",
              "      <td>2912.272998</td>\n",
              "      <td>3053.070574</td>\n",
              "      <td>2771.475422</td>\n",
              "      <td>9.669257</td>\n",
              "      <td>0.768069</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2962.414990</td>\n",
              "      <td>3011.552979</td>\n",
              "      <td>2913.277002</td>\n",
              "      <td>3.317428</td>\n",
              "      <td>0.757896</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2734.969971</td>\n",
              "      <td>3020.689941</td>\n",
              "      <td>2877.829956</td>\n",
              "      <td>9.810892</td>\n",
              "      <td>0.884748</td>\n",
              "      <td>1.173372</td>\n",
              "      <td>44.085419</td>\n",
              "      <td>40.219582</td>\n",
              "      <td>3.865838</td>\n",
              "      <td>2956.048319</td>\n",
              "      <td>...</td>\n",
              "      <td>0.211445</td>\n",
              "      <td>25.030917</td>\n",
              "      <td>77.593969</td>\n",
              "      <td>-42.047021</td>\n",
              "      <td>57.515187</td>\n",
              "      <td>46.199900</td>\n",
              "      <td>11.315287</td>\n",
              "      <td>2963.594971</td>\n",
              "      <td>2872.844971</td>\n",
              "      <td>2918.219971</td>\n",
              "      <td>2822.010010</td>\n",
              "      <td>2745.578247</td>\n",
              "      <td>2779.869995</td>\n",
              "      <td>92.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>88.0</td>\n",
              "      <td>2878.972265</td>\n",
              "      <td>2876.238007</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>87.638041</td>\n",
              "      <td>59.822123</td>\n",
              "      <td>0.525747</td>\n",
              "      <td>0.642610</td>\n",
              "      <td>0.625108</td>\n",
              "      <td>18.917809</td>\n",
              "      <td>48.409011</td>\n",
              "      <td>73.729067</td>\n",
              "      <td>82.463761</td>\n",
              "      <td>-26.270933</td>\n",
              "      <td>110.652350</td>\n",
              "      <td>2917.612316</td>\n",
              "      <td>0.543267</td>\n",
              "      <td>-9.037648</td>\n",
              "      <td>-4.355343</td>\n",
              "      <td>-4.682305</td>\n",
              "      <td>-0.208852</td>\n",
              "      <td>-0.209070</td>\n",
              "      <td>5865.109387</td>\n",
              "      <td>-0.002089</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-11-17</th>\n",
              "      <td>2983.409912</td>\n",
              "      <td>2996.649902</td>\n",
              "      <td>2967.000000</td>\n",
              "      <td>2981.520020</td>\n",
              "      <td>862700.0</td>\n",
              "      <td>4.710378e+08</td>\n",
              "      <td>1.386107e+09</td>\n",
              "      <td>0.029870</td>\n",
              "      <td>6.380151e+06</td>\n",
              "      <td>70.258187</td>\n",
              "      <td>-32547.505033</td>\n",
              "      <td>23166.189300</td>\n",
              "      <td>-3.199662e+03</td>\n",
              "      <td>8013.331523</td>\n",
              "      <td>2951.031231</td>\n",
              "      <td>54.607954</td>\n",
              "      <td>2917.527002</td>\n",
              "      <td>3060.410757</td>\n",
              "      <td>2774.643247</td>\n",
              "      <td>9.794854</td>\n",
              "      <td>0.723934</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2968.970988</td>\n",
              "      <td>3016.514982</td>\n",
              "      <td>2921.426994</td>\n",
              "      <td>3.202725</td>\n",
              "      <td>0.631973</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2734.969971</td>\n",
              "      <td>3020.689941</td>\n",
              "      <td>2877.829956</td>\n",
              "      <td>9.793225</td>\n",
              "      <td>0.862908</td>\n",
              "      <td>1.177772</td>\n",
              "      <td>43.497720</td>\n",
              "      <td>40.875209</td>\n",
              "      <td>2.622511</td>\n",
              "      <td>2957.390828</td>\n",
              "      <td>...</td>\n",
              "      <td>0.214110</td>\n",
              "      <td>24.925674</td>\n",
              "      <td>72.065012</td>\n",
              "      <td>-6.913989</td>\n",
              "      <td>57.821243</td>\n",
              "      <td>49.286410</td>\n",
              "      <td>8.534833</td>\n",
              "      <td>2963.594971</td>\n",
              "      <td>2877.829956</td>\n",
              "      <td>2920.712463</td>\n",
              "      <td>2822.010010</td>\n",
              "      <td>2745.578247</td>\n",
              "      <td>2779.869995</td>\n",
              "      <td>88.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>2890.309679</td>\n",
              "      <td>2876.238007</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>92.618313</td>\n",
              "      <td>59.777891</td>\n",
              "      <td>0.521532</td>\n",
              "      <td>0.553892</td>\n",
              "      <td>0.610626</td>\n",
              "      <td>19.042857</td>\n",
              "      <td>50.599254</td>\n",
              "      <td>73.541254</td>\n",
              "      <td>77.493217</td>\n",
              "      <td>-26.458746</td>\n",
              "      <td>110.274765</td>\n",
              "      <td>2920.647446</td>\n",
              "      <td>3.677995</td>\n",
              "      <td>-10.142678</td>\n",
              "      <td>-5.512810</td>\n",
              "      <td>-4.629868</td>\n",
              "      <td>-0.009392</td>\n",
              "      <td>-0.009393</td>\n",
              "      <td>5864.549134</td>\n",
              "      <td>-0.000094</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-11-18</th>\n",
              "      <td>2984.580078</td>\n",
              "      <td>2992.520020</td>\n",
              "      <td>2971.260010</td>\n",
              "      <td>2981.239990</td>\n",
              "      <td>764500.0</td>\n",
              "      <td>4.709910e+08</td>\n",
              "      <td>1.385342e+09</td>\n",
              "      <td>0.050200</td>\n",
              "      <td>5.438118e+06</td>\n",
              "      <td>63.026280</td>\n",
              "      <td>180.935271</td>\n",
              "      <td>15750.530036</td>\n",
              "      <td>-1.873567e+03</td>\n",
              "      <td>8012.578897</td>\n",
              "      <td>2956.023622</td>\n",
              "      <td>51.273159</td>\n",
              "      <td>2924.173999</td>\n",
              "      <td>3065.921775</td>\n",
              "      <td>2782.426223</td>\n",
              "      <td>9.694893</td>\n",
              "      <td>0.701294</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2974.635653</td>\n",
              "      <td>3020.591659</td>\n",
              "      <td>2928.679647</td>\n",
              "      <td>3.089858</td>\n",
              "      <td>0.571855</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2734.969971</td>\n",
              "      <td>3020.689941</td>\n",
              "      <td>2877.829956</td>\n",
              "      <td>9.770963</td>\n",
              "      <td>0.861928</td>\n",
              "      <td>1.181118</td>\n",
              "      <td>42.519233</td>\n",
              "      <td>41.204014</td>\n",
              "      <td>1.315219</td>\n",
              "      <td>2966.204163</td>\n",
              "      <td>...</td>\n",
              "      <td>0.217265</td>\n",
              "      <td>24.874136</td>\n",
              "      <td>97.692652</td>\n",
              "      <td>3.697559</td>\n",
              "      <td>58.644944</td>\n",
              "      <td>51.782734</td>\n",
              "      <td>6.862210</td>\n",
              "      <td>2969.349976</td>\n",
              "      <td>2883.584961</td>\n",
              "      <td>2926.467468</td>\n",
              "      <td>2827.765015</td>\n",
              "      <td>2745.578247</td>\n",
              "      <td>2779.869995</td>\n",
              "      <td>100.0</td>\n",
              "      <td>24.0</td>\n",
              "      <td>76.0</td>\n",
              "      <td>2900.740100</td>\n",
              "      <td>2876.238007</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>96.309156</td>\n",
              "      <td>63.222650</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.682426</td>\n",
              "      <td>0.626309</td>\n",
              "      <td>20.082248</td>\n",
              "      <td>50.419364</td>\n",
              "      <td>88.780253</td>\n",
              "      <td>78.683525</td>\n",
              "      <td>-11.219747</td>\n",
              "      <td>112.227688</td>\n",
              "      <td>2924.603102</td>\n",
              "      <td>3.322293</td>\n",
              "      <td>-6.286032</td>\n",
              "      <td>-5.667455</td>\n",
              "      <td>-0.618577</td>\n",
              "      <td>1.104907</td>\n",
              "      <td>1.098848</td>\n",
              "      <td>5930.451879</td>\n",
              "      <td>0.011049</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>4344 rows × 177 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                   open         high  ...    others_cr   returns\n",
              "Date                                  ...                       \n",
              "2004-08-20    49.813290    51.835709  ...     7.942987  0.079430\n",
              "2004-08-23    50.316402    54.336334  ...     9.029294  0.010064\n",
              "2004-08-24    55.168217    56.528118  ...     4.514651 -0.041408\n",
              "2004-08-25    55.412300    55.591629  ...     5.640819  0.010775\n",
              "2004-08-26    52.284027    53.798351  ...     7.544342  0.018019\n",
              "...                 ...          ...  ...          ...       ...\n",
              "2021-11-12  2942.139893  2970.044922  ...  5887.897077  0.019745\n",
              "2021-11-15  2956.629883  2997.189941  ...  5877.593698 -0.001721\n",
              "2021-11-16  3000.000000  3009.540039  ...  5865.109387 -0.002089\n",
              "2021-11-17  2983.409912  2996.649902  ...  5864.549134 -0.000094\n",
              "2021-11-18  2984.580078  2992.520020  ...  5930.451879  0.011049\n",
              "\n",
              "[4344 rows x 177 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F4XQhr9NlQ6L"
      },
      "source": [
        "### Create different sets of data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xs3iL2LPlQQB"
      },
      "source": [
        "# Percentage train set\n",
        "split = int(0.80*len(dfc))\n",
        "\n",
        "# Train set creation\n",
        "X_train = dfc.iloc[:split,6:dfc.shape[1]-1]\n",
        "y_train = dfc[[\"returns\"]].iloc[:split]\n",
        "\n",
        "\n",
        "# Test set creation\n",
        "X_test = dfc.iloc[split:,6:dfc.shape[1]-1]\n",
        "y_test = dfc[[\"returns\"]].iloc[split:]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lEstoP03B18p"
      },
      "source": [
        "### Standardisation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0Ntn7T7nBuM2"
      },
      "source": [
        "# STANDARDISATION\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "\n",
        "sc = StandardScaler()\n",
        "\n",
        "X_train_sc = sc.fit_transform(X_train)\n",
        "X_test = sc.transform(X_test)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 362
        },
        "id": "u_-CxrGwCBsZ",
        "outputId": "ca890d70-52fa-4790-8a76-e324ec7f422f"
      },
      "source": [
        "plt.plot(X_train.values[:,0:15])\n",
        "plt.title(\"WITHOUT Standardisation\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x396 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 362
        },
        "id": "gh5YSyy8CwZh",
        "outputId": "3a8d631f-917f-4685-c517-758cd0515258"
      },
      "source": [
        "plt.plot(X_train_sc[:,0:15], alpha=0.5)\n",
        "plt.title(\"WITH Standardisation\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x396 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zvxKYGMfB4Do"
      },
      "source": [
        "### PCA\n",
        "\n",
        "Principal Component Analysis (PCA) is a statistical procedure that uses an orthogonal transformation that converts a set of correlated variables to a set of uncorrelated variables. PCA is the most widely used tool in exploratory data analysis and in machine learning for predictive models. Moreover, PCA is an unsupervised statistical technique used to examine the interrelations among a set of variables. (source: GeeksforGeeks)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eJRJIM6JBRbW"
      },
      "source": [
        "# DIMENSION REDUCTION\n",
        "from sklearn.decomposition import PCA\n",
        "pca = PCA(n_components=6)\n",
        "\n",
        "X_train_pca = pca.fit_transform(X_train_sc)\n",
        "X_test_pca = pca.transform(X_test_sc)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1tFhGuvuE235",
        "outputId": "99a3ceec-a388-40c9-c3a9-4ac92bda4c66"
      },
      "source": [
        "print(f\"Without PCA: {np.shape(X_train)} \\nWith PCA: {np.shape(X_train_pca)}\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Without PCA: (3475, 94) \n",
            "With PCA: (3475, 6)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TmtBa64HlVUC"
      },
      "source": [
        "### SVR training\n",
        "\n",
        "scikit-learn documentation: https://scikit-learn.org/stable/"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4CgRR0hVlVuJ",
        "outputId": "d4ca9e5e-c497-424c-8039-256fa8ae3e24"
      },
      "source": [
        "# Import the class\n",
        "from sklearn.svm import SVR\n",
        "\n",
        "# Initialize the class\n",
        "reg = SVR()\n",
        "\n",
        "# Fit the model\n",
        "reg.fit(X_train_pca, y_train)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SVR()"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sUzRnTA6luad"
      },
      "source": [
        "### SVR variation predictions"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 358
        },
        "id": "mfiQlgR7lyfr",
        "outputId": "944185c4-704b-4c5e-fd31-7a5c1dd64467"
      },
      "source": [
        "# Create predictions for the whole dataset\n",
        "X = np.concatenate((X_train_pca, X_test_pca), axis=0)\n",
        "\n",
        "dfc[\"prediction\"] = reg.predict(X)\n",
        "\n",
        "# We verify that the algorithm doesn't predict only way (positive or negative)\n",
        "dfc[\"prediction\"].plot()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f26f213f590>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Lm2n3XfIKQI/BPHtnQMsLj3YekjUJ7EKTtC94MKTI7m3PBwDMnrhPbgjKW9u/BGms78Hgfa+c4h81xqkLvdX9fWee9Bc68qI4c5oxnzuPyqqmsJxoXkk7RLIHTY8vr6RN2NEuxIIha699N9YeeueK0tC99XmIJXMNHPE8JcupB5qOlsHdoe2sywmfZEu8r9tf8Qnn77XXvoc7BsnU2MVi3DlsLVS4TTb5DfE3ksz9scARzY4xX5ryVyokv+GoBUsUFGRw4XGI84RQi0AsTnz6y7DIX4CMOhIaLGjHPZmxegIrsYWAJscMMt3rV6xkY/+lt2LHrZ9Cx65bV2R+JjzvKk9T0XfJy/lDkJtUhn173XXvQSLbVftVmy9MjXkN7mZMqLnyf3einO/Ou8L6XnWCabf1SRCpoBANFwm3CA87x7MMNO382bQvREl7pbDuue+nD4RZuAPgSoz859k2fBl2/+oXsOGGDzZsXmmYJlprefHTfbvP//wcaDrN1GIRKmqR0jrP/jt8za/X5gsvaUPT5QoCMRi6MOTLzguv+xm7ThxjnVdQaBSal0OEVY8vo71WMWo2kl7P30ZumJwMd3xmsOnFvw8A6N52fePm5WDDDb+Nnp0eTYKUtFgfYulWawo9hsEDtyFV8wDnwfeuRnl3iT68THdOKlNnsxxmw6bB3oyJwq+Y351H0o6n2zB88B2IJXPOu6Kx1gKKaYs1Mx0brkK6a52wjYICD03LLUKpx3XSEW2Z1eOrmIEzFzNvGz2G/O6biEpOoj70vTYbyLSdBZszZsvALir2djmhx1Po2fFCJyYZAIxKEaFrvofE8KFfx/63fw+53q3o2no91lz5Jmx7xZ9TbeLZTiRbCXWv5/2MFJMsIWnbz8dWV3OfPUta1jTi1RHQJyFpr7nyLejf/yuWtqXmDMcKPyM3ACKmrcUS2HLTH2HP67/Ip0tBQYDVyyHqRJiqQ5oed7/vZVGPE7v7C9B7vJHI774Z65/3G9h0oyXFiq7Xv1A3XtLmjdlYpzcxWAypOHfWFbSXad7+fZatvHXoUsQz1iYq5bHH7rj1U7jkzV/Hztd+3qLFt6kMTx3F4HjhUZoOPZF2vg3+Jps1v0ZI5pzzYF2L/1iqfQAAkMh2OjTkd70YeoIOfdMk1eMqW5pCvWhaph1G3UZK2ssRIkQtYqsobAqAR/IKpt1eBLO9W5DIdaP/0ldy2/oW6oZumGq2Um4o0fn0KufNZR1Pdq4PVFvXTwKbhnTHGgBALr/ZOtBg9bhI0h64/FcJ+tibbJakr2maqxETbYJZfb301NokW3uRbOlxDqc8aXVJRt299Xn8KWPK3q1QH5qWaYeTtGPOB0smiWgYQkja2Z5NaBve33gaIiKsPV4jbJTbbvkzDItCyTyMpJGmCS2CrTTZ2of8npsbRgNBTeCxvW/6u4bOqCeIzadpUPdBpGXwOWpF0o4TIV1xtk1b03TKp4GvHmfZpV31uFh97z/XtflaT4sa0/aGcXk3e5JheSLvdAUFGTQv0w6xWHduuU6YDrF/36+gdc1eAECqfQ26t90QihZmMokaXNuvhV2v+ytse/nHQ42/nCAljJ6dL5LpYP1rWuFUQiyjpO2oXTkbARaTuOTNX8f6574fbWsvr2vuzk2HsOcNX0U8bTlb8aTF5US2Z4Pztwn6eoWOVF6bdiSuHSxpQ9Pob4Hz7Nn3yXVEo0Efq+cee9cP/3Vwkr6sUPigwsWD5mXaISTt3j03Y+7UL5jnYskchg+9A9tf+UkAwNab/wQbX/g7oRZ2nno817cd+97+XQwf+nXpsZYX4opKwwffLj1GJKl5ORhZhI1AItsR3EiAzS/5CNIda5xMYnxJe/lU9Btf+GH3h2lSc4nyfIuSq8iCkrS56nGPRBrGpq0R906oHvfTXl6YYozFgknN7b2OdNdaAECubwdiqVZiSiVpK9SHpmXa4RZrjWLy22/9S+ic+NR05xAAIMMtJcganu09bqvBbYehFQfLcSfkIhQmSY1XmlkW1SLvPRC8Hxtf8Du+Yx0brmps8pcAGuoF5XBmGlTFq0t/7Vv8jg15BhKe1pIlMllx1RqCvMdtRzRx6Ba/f+3dJDcfjOtItQ1g56s/jV2v+ZywnYJCGDQv0w4htWkaLfW0Du5C56ZrxJ1CMDO+Xbhxi3b7+iudmNzIkPC2DR4jRJIaT5uwtY5loHNsqmGx5aY/wobn/1ZwQwKmyD1cA9qG93H7tg5dKvQH6NpyndhfwINEriu4EdznbW9io+QYkEkmJK265ti0TalwObfv7Mn7sTj+JL0J1RPcdcJbqYzFjJOtlh3cdr602pHZ4JQnuUJ4NC3TDrPYFOdGfDzGNGql+LiLTgiJhFgXKLoaJGm1De/D1pv/GNtuoW3hmp5A9/YbuFoDL5j3LKy6L1RmOa8NMoZM13qsv/6DvpCbqOBLPufDe1zEWDShQ9j2V/y/6N/3Km6Sjk03/j76971K6j6ZpoGhq35Ngl6X4ToZBaNYLChGyBlA8vtkJ0hxQ77EfmikzdyAaVad8QaveAPW3foVZHs2Mbtm85s9md3o98hi6u75bM8mKoQNYFdMU1AIQvMy7RDMZvSBf4Qv0Uetfi5PIghVno9SjxNzNIhxpNqs8JRc7xbq+MCB12HjC35HWNyBAlPSDqsujW7TNqolbHvlnyO/80XI73pp6P5sckQ2y/OFYO9xbs+A97hry3PDkyOeEAAZKheFa7Pfd2oa73vFe05M5k6ox4nzpGajbe3liBOaJxMmTKPq3M81z3kjACCeYm+cLE0D36atx5PU3Lte91fY9KLfpZ6XHRuvoBAGimlLwKq7Sy/iRlUsaa+58k1hqCEJIyYOMYQAJthOPNluy4PYy8x5YCajkFRZp9rX1MawJW2pbhSKs2eQqKW3bJRDT2H6FPO483zPA+ryrwvQWHRvfb7wfFi4meQExTMCx5CRtCU3LSzPe8qJz38+mevGtlv+FOuue6970DStjYjkJtSKfCBt2nQ/PZ7yXULHhqsozU6UvO0KCpGZ9u5du3DNoYO45tBBdHS0U+fyPT249ppDuObQQWzdSjMEXddxw/XPx/DwUNSpG4Mwi42m+WOGqxX3XL2kEGPYjLSh4K3rEkUz6PbRJO3evS/H3jd+1arL7Sx0EYp/EPfJqBSRzW/G/nf+AK1Dl4Yfyx7Hfo7e45VS5DGlYfIZi7RNN8jMILG5aV93hdxcgCtp1+aN9PaT0RKc65Q3X7G8xwlNjiyBpgnTrAbU33YxePnr0L3DDe30mlksKZ6efO7ZB5VNW6FuRGLa3d3dyOVyuPPwXfjlAw9iz266CtGePbvx83vvw52H70JvPo/WFjeH87atW1EqnT8phgd6Zxz0ZfvPW9J3NEcc0fgbX/ghcpYGjC0aR0bq5WgBbEhI2p2bDtb+PeQw3mh5xEmmXcLggdcjlsxg7TXvijBWbUQec2xgRTEeRFm7fBXOgsbgQGZT1bHez7STrb2c8WxJ27ZpL4+kLZ0ulfn+uZts2Thy0zSJIkKaVEho+7Ab1ullwFZpUe/cJm3TVkxbIQIicZx8Tw/OjowAAObn55FIJBGPWzvNbDaLUqmMQsEKIRkdHUNPvpZNrKUFra0tGB0bbQTtdUGU0ITTgfO7sZJ2vdDjaWS61tMHuQxSwr5MhbX4GYDXUYdZtYlM3BFQqEMMImCsWgqvKYg4V7huIT4pwT2Q9moPuI9RPe4TGXYsui8XeKSCIRI0yTqisZYwGfW7D6ZbxUuPhSsFCve9rhTmAAB6Msu8N6REzqtwpqAgQqQvOpVKoVQqOr9LpSJSqRTzXLFURDpleUnu2rUTxx56qB56G4fQ3t3e6kZ2FaIGMNwGSnvbX/lJ7H79FxwbstS0goU/aHPjLVs5cPnrpOj0FqaQAXmvrUXV+p3t2eRPMyk/qNxxaW/mSO7UzKOlc2MSfYMk7YiaIM734TCdOtTjGsfxkp5H8vvkZUQLW9bUNNwwNj0W+tuzvwPbrOINCbPpYknaqfZBDD7nTSrxioIUGhTpL4yrAAAMDw1hemoai4tLoUbu6u5GPOEns7c//KJPIpV2nUCCxmpra0cqTYdndHR1IV3uQyzrFhHwjtPb3w/Wouptl+zqZp7PtbZw+6y95HoURo/5xs71bQUA9K3ficKopcLPtblesuQ4ydpmKp6I8+8BUZVI03Rfu1SSVvF1Dm5DxXt9KWsBSyRT0DLyzjfJ2kbQRnunK/21d3RQz2TLjf8Xxg/TZSW9YF1jW3s7dMbxZKfnmQzQBSJ49yvfPwAYcuaf1rY2aP190JPsEqB6jGa4rDm7e3pQTtH291TezY+fSKYifStdPT3IaX0wKgUnNKm3vw+ZnEWrplm/k109omGYaOvoQNx+x9vZEr0e05Emnm9LawvzOuKa/153dnU6a0YylXT6ZbL8dy+VSjn2/3z/gBTTTqXd99MurKKZ1jfX0t6JWKGTap9MJdFB3K+uwY1oa0mj6/K3ItHSh7RewPzTdwTOGwb1rpMriWamfWyEr42OxLQLxQJSKfeDSqdTKNbU4YVCwZG6ASCTTqNQKKCvrxfZbA59fX3IZNIwDAOFpQLGJyaEc01NTvqO9fb3CS9KBuv69zh/j4+OQVSS/tzcOcTyZZD1vWZn5jA7MopUmwbbpW5sZJQaZ2q2gMrSTCDtOXRhgPhtn9cG5tHlOWaPn7/6N3H/52+ixomlW53zs7OzmK316e6YQY9nHABoL5WQBVAplbn3U4+n3GvSdH+7J3+GdUMHnJ9VPe1r01ksIQ2gXC6hWChCtkp1qVgCuczOzsyil/g73lt0nknFYNBGwHvf7Ws6N3cO44x+ObODeiYTYxPUs/XOtY5oZ1QKEMGdew7jI6OIp5fAyp9nVGnGwaJ/anIaS1M0Let3vcH5u2KYzPsiet8BYGZmFudGRrG2tmkzqhWMjYwiV3t+RtWwfpv0uyuDc3PnMOm8m3NgsX2jWkWhUHDelfn5Bcwu6sj1bcPU43c47VLjp5AbvpKmfXoG2VLtnStVnOvPLC6Cl16oUChA0zRkAUyMT2LQqAaqIYuFIrwBYeXCAhKtQKFQxuzMLMilu1wqY27unPMOd+9/M02D4f926kEj1smVgqKdj0i6s7GxcQwOWp9qe3s7CoUiKlVLtbS0tIR4PIFMJgNN09DX14ex8XHcd/8v8JM778Sdhw/jxMmTeOz48UCGvVywnERIiFVoejzpt53ZajeB+nHo6rdJ0cN1lhHaPFO+Y5S9jFRvcoeRsAkHlN4szJymfrcO7vG1oYYLoz72tPUVbWmwE6DwuHSGLvnrW/+830Ai1yOgIeJ8hJSo15hu15bn4tK3/QPSkul1NT0GPZF1VLa2bdx5fvY/kWzahJ8E1zTkfyf3vulvsenG30O6g4g8YfXXdIT2c7BDvmBplORqE/jnsDdsVvUylk2brwKPNShhkMLFjUir3vT0NGZnZnDNoYPYs3s3jhw9iuHhIQz0WzV/jxw5gssv249DB6/G6TOnsbCw0FCi64W/mId44Vl77bt9i4Nr06ZvIfmx2yqzQES0i3dvux4byDzY3IWGV9bQPiuyaUdx6qGRcu6DFmoMbxjNep9H9TL6E4D9vIOHC/dJrXvu+7k0yLCdoPnsXPibbvw9JDId8uFxWgzxtKsTcefRav93uLbceBSC75Ho2skCHPwBQtq0YRJZ3rRI/iQAUK1Y/jzWppqx8RP40qgMaQoyiGzTfviRR6nfc3Nzzt+TU1O48/Bd3L6PPXY86rQNwdpr6KpZMg4gvsWx9rtlYBd1ePbk/U4IjXRIR0RHNDs87Nm7v4jygseMwFvMNd1N8ehwbZGkTdb6FpLDRaoWPpTp3oDS/Lh0P5Hns6ZpDeHZ/Al8xMj1C+mtHUtmgxuJwKSLfp7rrnufe4YTl+4fVvc7U2k6oWEK1jQBQHHyCaS6N9PDkO87591PtfYitf0FbrMwmz1NI2uWSfYyne+gb+8tRMY34Uy+I0a5xrRjCYYWQRNusup+FxSaAs2ZEc3zMdlxxGH62B/fhhs+SLczXWlXNnkCM2wlEthqRzJ8Jb/zxcz21CjEYh0kyYVRj/JSQgpGF55tG9ovbNm29vLAsqbcgod0VVQAACAASURBVBU+SVvuOhv3LOXAossbA9+792XuOclMb5oW8zFkTdN98+249S+E4xjlJd9Gjf4ulmPnFd573DTdkK/BK25zpW4B4pl23zFbPc4yXwGakB63VKuCAh9NybS9C4+UWsonabNVvSSDJBen9vXPwZ43fBV6yv+hN2zdIq6LKjZBrOHJ1l7oiTSy+c1ue2KR79x8LS5/97+ia8t11pCBSWjCER9KfRygafBmr0rkepDffZND07Zb/hT9+25Fqn2Q0dshSI6WZZK0AVOgaZFQkDPUrR3rDjAa2kPKqX01PebXQGk6wi8Zpu86KA1U3e8+y6Zdm9d7VnQ7TZN+3yRs2m1Dl/iOGZUiquUC4ul2jgZvOdVDCs2ApmTa/g8neHFkSTQtAzv9DYkFilyctt78J0h3rEHLhusYg7MfQ+sQvzSjZwCbSOcIrQGgr2/rzR/Drtd+nkiZ6p7v3W15pPfuvcVHG3O5Cb0GyXcQMxj/ONte8XGsf95voHMzXTZV02NI9WwLlzaSo1kBgIUxvnkndFy0afJVvxIbCu97menZxM1mZrWXrVPtZ9qarru3vY78BJTDpOz7EGq6CHHatYIhzq+oGfFMA+XFKctp0qepkNXYaMq+rcBFkzJtGnIVp7wfoBYofWmxBNrXHaA8djMD/t354IHXM/t3brxKgi53IeAvgPT1ta7ZC8CtoUwKQm6dZNtrmLRpBy84Ja9t3Uds4BAuLaKFkzFOpnMtANeGbqNz87Xof94fYP3z/ld0gohnnevdivWc2tmRkpnUk6BHs0p4WvXdNSRbAuKmZafSYoxr0X0OaYXZM1I00sOIIxKCxwtuIFdPm4BpgvxOpJ1IfcOYMMoF6PEEO4WsxLNec+Wbcdm7/plbdlWhudGkTDv8QuHfIeswK0VmWxuxRBpbX/b/YM9tX3aOpXu2YfutnyJCaWJoq6PghYdI5mHaxsnaoLjHbFueLQ3RC3ewejyIabFtfRwInYEE83gkRDtbVRej4hVX8vFJ2vTv/K4Xg4mGhKHVICHtaVoMm1/yEWx+yf+Nrq3PQ/C7LWmb13XffSQdA+0N4tzJX4gHMk3fnOHLufqhx9M48L7b0b/vVt85jSjwI+uLYJXmbEC++Zpt3NJUMPKnS9AzeOBXAQB9e19ePz0KFx2ak2mHlGwWxp/w99Gs+s7CaXS2OrZ1cDey+c3QE1lc/p5/D0WLGFElNoJp24VQ7AU70EYb0qatywcsiCRt0WKc7d6Ajg2uliLjaDoYGxbJkC+ZalnWcFE+qfok7bZhy4xih3eJm8uGrjHU45rubkocNXnQSC7TdtTPEt7jDIqoX7Lx5lEl7cgwDcseTnraO6Roobzgw0RaKDQPGpTGdHXBt+ALvlXTqFrqLp89VGNXqgoosOGMa5rISCyyXpSXZvzFHILyoAdJbCbJtIn8ywiWinxzNrD4CUQevALm073tel9O9NqArIHYw3ulQ2k1erjr15MZ7nNLtfVLzEfWXzcj5j5nDRvzP3tNR1jNiglAryUNcd+pBpgQRNep6RFs2kBdm6caTBCSNlM9Ln/t1dJi3fQoXHxoTkk7pDOUZb/2L1bsBVKOacM0pKU3D0GMKf2OaKGGpMiqMUpPJizp8SNV72JD7FAV4VqZt46nHvf8lvYKD0cX5eUfAaEZoOx9Y6h3LUbkFbEDxjNNX6hf6Ap7IWHRaD3sWCoHPREc/2yaRmhaygtTjIEMmIbBDJmTwSVv+XuCJpmsbArNhiZl2l6IRG2zpuryhnw5/4s2o2lGVKX64XUOikCM+6fhtWmHqTsu4XUbYmH0lv2kx4ly7+Qlbe/xzo0Ssfyi4TiQTXbCn4+cUCZETNKmrcXgDSfTWMlVAsHaKflt4xIUSbajkelci8t+/ft8WmxE+B6XZp5ljGMxW02PwfD6vGji5CoAkGxxU/XqIUxJCs2D5mTavogv/sdsmtWaVM1yKmHdPlkbWjVaKb4Iknaw/U9k0w6g0WdqWKZSkUHzSiDInCE6Pnzw7aHnk8HMM/fUJW36nJ0CxpJlkpqu+97P9g1XEnm/7Xcu/PMUaW/setTC/poecBWaZESIb+Bw7Rnvk2nbtOFXb2uSjmhOe1WqU4GB5mTaYS7bkbTl1OPS5XtN07H18TDyi38AYFVYcvoxFiMnPIuzlA1d9WvO30zvbaFNO0iV6dsBMWlwh2i0dkEeTkEGKfVsNEYaxtEIQC39bB1MO7QntjXXuTP+sq7ecb33eP1z3++WoHT2iVFCtvjP7uRPPh/IuAMjEAjvcXmSWCFuUeBmVvMm/7HufQimHSavgELToCmZdpiFxrJpW5K2XeCeGCkyDUaliFhCbM90VM2kypmp4Q2jsuS36dx0yAk/I0PShKN55mRKs1SHxqdsDd1TIrlHZOG3zqpXobuSz8cE4uk2qbkC09OyMqLRLeQIZLwP4jBCk/kOka0S2c7gexaSaeuJdIR3ky1p27boZEuePqlpodYeJWkrsNCUTFsWp+76AmKJDLL5TdDjaRhE3uaWgV2BjmhCGFXEkpmARnILTxibNmuxtqX3zS/5iCNJxRI12kLaHxuZq1w4Tuh0oS7oNJqNlbTD9wsrm3u70/eB1Kqw20tu8GSZdiRPcOKd8m36jMBoB6u0Lp9+0hHNRs+OFwnH1BPpxrybpumox9de+27PHKmQ6nElaSv4oZi2APMjjzgLV6qtj/KCze96MTo3X+vvJJ3LWpNQf8mOFRDyRSCeYUhiDKnEVkGG3e37KkN50TCbdvRx5ApWNN6rmTlLnYyCVI+bMC0pVNQetqQdpEHRnVSaBqvIiEb9I0CQpB3Y3AfrGkUza75XesMNHxR+m7F4OmBM9jx+mFxnTGsjrCRthfrQlEzb+zHwVbr+46VzY87fA5e9ppFkCUDQwfjmnUVQggGw45f5CGvTrhTPBQ0Yan7uMHWpxyVSs0rQyfRJiHR9DboWqQ58SXvu9BFqXDt/vbDEbITrFb9TBpvpaRoVjije7PglbWsIwb1ihHUGgtHeNOkc5iT0RDacelzZtBUYaEqmLQ0GMz9z37cCOjVOQmNJJCxm5Y+dDQnOpiXXtz24ypdnESovTgunqlMZTAxE3xs7n7pU10ghR36w7Mehx4vCLMjulE2bfo4nfvw5Vo9aP/+7dc7DtANmthvKkElDYNowTTNQ2tY0f4pVTwOwBuGmnrUmDu3Ux3xqAvW+Hk/yerHHVyFfCgwopg2gIekLbUh/kxINWQsia4G3F5vIiz/7+lsHd0dYlBuvVn76v/01m6OoledO/dL6Q0LSlhm/d8/NjI5hqQrnUdy29nIceN/t7gEBAyzO+Yt5uNel+9TeZK3tRuQH50HoiGaaAFhMj2jHDMF0EU+1hE/ycx4kbXDDRNnwe58rKCimXUOID7xB6t21174L6657r/N7fuQRAMDixNPEVLJ5omvSU0SGyYtp1WLJ0GEwgbcnyv1jFXKIIOHZale5jFz0cfK52FgYezw0DRJTCbHmyjfRXQXMVVQAwyqqQZ+ncunrMYw/9EMAwPRTP2X3h8TmJiiVp6+/v/62047wfBc5IiZy3dxzIiRb88GNCKRrVeUomBz1vo0Qz1pJ2gosKKYNgPslRUjJKcs4vRm2qsUFGNUSjEoBAJDqWIP29VdITirtFcQG5zKtxVEslYaReEcf+MeIzDZMoQ/ROHbZUYnSkJ7D504/yB1328s/ETweDyGLSPi6B6TK9TEQ+9p13S8RGlUc++bba2S598hOuMOG+Hmee/J23zHaPOEh2eSEfBHZxHr33OTbDMyeuNelKJ6KVA+7pW97qPaJTDvjqEjSlt+IA4ppK7DRlEz77C++Q/3mfUjMRCaBC2wdkjgx3d43fNUJv6IWMSbjtNXjwY/Tl1rROzGB/O6XBo7nv14/fXZymGp5qWE27Wi5x+0iEvyQI2IGz3wM/4LaMbvKVu1gKJK0kH10TxgQybQ7Nx2izlnhU55n62hldB8zNmt5s73jsm204o2iUSni3s++CIWRI/6TQvW4AZl0s15J+9m7v4Snbv9E7VwsvMWrQTnzLZs8e8NgvWvKpq1QH5qSaVtZqFyE8sBdhgIHFmQXDZEzWDBtrMpBvDCtZEuPZ8xg7/HA+xPp/rHzV889y5d+WTDKSzUSJCRt33Wx/AvqSGNLtZfvk83T+dhJ9Xiudwvd2DBw/AcfZlPHkLRNo+rJiGe1Zntz+/6gxxIyL7F5Qkaz4jULmGYVC6OP1WiPI4qfSqW4ELqPD2ZAXW6J9995BjEV8qXgR1Mybe9i27v3Zex2rLUjKAwjcqWtWj3fCLmjbalDZmaW6k5UaUpPuAlgGpMYpTGbnmz3BrQNXRKqT2l+wvpDonKZ91pZNlTWZi+8H1oDvcc9MM2qP12pE9Ov+5iLaVbdylJk/DdT3Rtk0+YzTfpe0v15yVW8mg7Wddt0Wl7a4Zn2g195LSYe9avzQ4HIiMaCjKbJ8b1QyVUUGGhKpu3dpfOrSfk//FhcnC+8HpimyfmoxepxOwmGjHqctQCXl2a47a0FUIDQJtzGSNpeVXA4GmTU495O7Hub693qHTwsNfWZDIRM24BZLeP0z76GsSM/cOYDLKZnVj1peQ232EWwetweLgLtlKTto5rXCcW5UfYYtW42s+zZ8UIkW/tCkWQCMMoFPH37J1CcPRuqLzWOabIdJ23I3C+TYaIAMPicN1J5FpKtfbjkLd+s61tQWH1oTqZdR6ahoCIfkWHa/wtQQTOYx5ab/qh2zm23MHacPQ3DqagwdYJLVrBdLVg9TjLGKHa6ehZRFkimncz1sBd4RoEYRiPkd9/kOxaOGP9c3KYMySuwZjuAMz//Oqaf/ilFnqbFYPhs2lVCyos5dIkkbe71CgRdYZy8yc4oRhboKc1PsJ8HQWdL/w4+ASyaSBJC9fTCFNfBllGP18wD3sx9a654Aza+8EPOGtC/71VItuSx/vm/VQ/BCqsMTcq0ZS/7PJT3CzmdSDKkFh6eB2tIT2zLrs2agU2PWGo0oUWIPa0UArKsScPmWC6j695+Ay5589f5bZ2fLEc0zZ8tLLQjmrx6vGPDcxg0CBKVMCQ+u72mx/2OaEbV837wmXZwyJf/PbNDyEQhXxbD4oV8ETn2WTn0CTqjeI8TA9XVl/vtSUYK2M9IJzZkZGWzeLoN2175SfRd8vLa79bo9CqsOjQn05ZNHMFgcCMez3PPyNEIsiYTDCFWj1vHdSn1eFimQqZqTfftDtWXOT1H0h5/6N8EnRrr/CezaSOZUbW0xGVOdaeaDBHyNXDZ6/zdA9TjxA+7h/WPHvMzFyJETCMqUgklxxDvvB2WFZhchVMZzE3Xy96skJsQk5UvXYBGpVcyOZoCwKK5Y8NVwYM4Gyv33dLi7t/JljzaQmQAVLi40JRMm2cHPHX4b/DYP31I2LVSmKNtayTqjLnlq8ddxBLsymD9l76S7st1sOJ5PAfT3bHrldATGfTserFrR5cI+fIQwDwsim31lTisF3VWpqIOe5h2+KcvL2nn+rb6jgnNDRSzpdmSpuuUOhnwStrE9QpttLx76WeDTl144aaJEaZmz0MmEfLyek98dGCJWAHqltIF77LX+58Fx7GU8B7XY66knWrrj06fwqpHUzJtnkpR02OYO3W/85v32c89+0vOuPWoxvne4za9ovzaub5tNM/mPVpealRJ2ocPvRMbnv9bWHPVW+yJPGOJ+/M3NfxFdmH0USnaAiGbxctq5enKvm/1qsetPsvzGZLqccdOSqnHPUzbNGDaKUSJ62BK2qHupUOQ1UfwkliCdoB6nBPvTNJZX6RDnVZtoWYiGBpD0ibV48yN2jK9QwoXHprySfNUih0brqQP8Hbr3F18PbfThGlyFrTaBymSRs1qxRP/ym7HWsw0aNxFrrw0S/3Odm8AAGS61okn4oG3mAokI6NS4p6LBBnzCEUnPxTPrx6PJGtTeOz7H2a2k+ldJKrQ0bZZ2vyi6TGGTdtwmxEbObZN22agvHeewVTtcURx2pzkKpR6PGj8elGnlC6M0+Zg8vj/UFndAFvDZF0nGcXBit8WhW0qXFyInHJn965d6OzsAAAcPXYMMzPu4p7v6cGOHdthmiZGx8Zw/LiVo3nnzh3o7uqCpul4/InHcfbsSJ3kRwOPact+9Fz1WZ0xt7wdvk0vO5uZBcNHO5drO2M5u3eN375anPeka/TSGFLUjgBxGk15uLWkw26uTK5ZIZbM+o6FI8rvVFUtzIXoTvedfuIn6N/3KgB27H8NlE1bq8Vpe98ZIkaaHFegLg5zL90YcCKawHe/RLnHA0L1KDqjv4fuhtSPU3d9EcMH38bvbAZ4j3NgVEowE3S/WDKDRK4L5YVJmmkzNp3xVA7VoLK4ChcFIomG3d3dyOVyuPPwXfjlAw9iz27aQWnPnt34+b334c7Dd6E3n0drSwt6urvR1tqKOw/fhZ/ecw9276rfqSkyOJKWfxHjSdqiTE/RFguvnxAbArWiUaEWw2pxnjOEqx6lxg1lA+dDT6T4J02+xNrAOmuBCOuIZppg060x7O2hI778qt5Q9ljPfOTGjmKITgpXzXn2rM2n6WHuQMBmVjINLDkORZfPDy045Is5p7e6VuP3jijMnsH4sX8RtjFNQ+wDwIH13PzP3S7/Stq0WepxJWk3DyIx7XxPD86OWFLy/Pw8Eokk4nHrRcpmsyiVyigUrMIXo6Nj6Mn3YGJyEvfeZ9mLy+Uy4vGVS9HHW7RZi8XD33kfox23wkZddNW4g+9weWE6eHyjStmxeWFSrr3MWwiEM7buTRfpHY/ul+4Y4tOoaXxb+/lk2xIbEb/am90nke2k+0WI0/ZLjWHuhYfhc5yxbKlbg+Y8e7YGg/Aed8aJ4IgmkoSFam7ZkK+g+7wMXNs0feVMWW14krZo82OUl5gKBptpa6SkzdAUxpnFSxQuRkRSj6dSKczMulm0SqUiUqkUKpUKUqkUSiV3t18sFZHLWrvAatV6adetW4vR0THIoKu7G/GEn8ze/nAZj0h0DLPTXyYTcWrczu4ulGdO+ObNZNjSZL6vD8lUQAYxDlKpJDRdQzyR8F2bHtPR29+HZCe/5GA6k0JHd5c7XibNvEc6wx6WzWa59zMWp+99Imkxs2Qqid7+PuTa26jzmqajt78frDC1XEsLN59yJsP2igeA3r5e3zHTqIZOkpPJWdeZ6erynfNef2u366Gra0Aq7U+q09bmXygHdl4Hbc8NmDn6bS4dpmk4m6dcSyti3TQ9nV2dvj6lmRNIdvjVtpkcrZ7Ptboxu+1ZA8hY15WqjZlraUG+37q2ZJLemLR3dCBdtu51Kp1GVbe+11zOawKw0Nvfj2SK/S1ouu67p51dnTBNA8mU+27mWlo8bbocAYBEOpOFrtvxyzra2ul7393TjXKqCKO0AD2ZQ3VpCnqL/BqRZHx3XsTiceTz/neHRGtbKz8M0KwC4Lz/6Thz7egeWItMdQSZHpe21o4OX7ueNZuRLp/2Ha9nnVxpNDPtYyOcCCXUYdOmIdrV0uf6+/uwbu1a3P3Te6RGnpqc9B3r7e8TXlQQ1rUPM48XS0WMjYzCXhqnJiaxNOH+BqybmVpYQBuj/8T4BDpLZUTJmVYsFpCsGqhUKhQNAGAYBsZGRpEzOzFAHF8YfwK5/GYAwOK5OcxMTcNmNcVC0blH5Fi2sLMw+pjlcQ5gaXEJ42PjYFQH9lkCyrXrK5XKGBsZRU/XOfR4+oyPjVNSxVrLww4LC4vIcVSHS4vsewrAdz8Avl+CCEuLixgbGUVn7hy82wD7XnVsPIhNN/4eph6/wzlnGAZKpTK8rOvc3Dl4t1Edu14JAHjmnr9H6Rx7Y2rfDwBYWFjA3PQMyCCeqYkJDNb+nn7yMNqG96FSqYK1HSwsFqj7triwCHtJHzvrZpJr0XrQD+sZTNSedbGwRF3T7PQM5kZGsBbW860UCmgBMD83Cz+bAMZGx9BVqjDfdz2WxNjIKLV4TU9OodcwUC5XnPsdX7dIjT09NYWWcgnerUCxWEIW1m0zTRNzc3PUvZ+cmERhehTJIz/AwOWvQ7VSQZgI+lKpxPxeSFQrFYyNjHDPA8Dc7Cy0WBws1m5C566U56Yn0ZLp971jCwUT4yOj6GpbdN7ZhflF3/gFM+NbE+tdJ1cSinY+IqnHC8UCUin3U02nUyjW1OGFQgEpYvedSacdVXk+n8fWLVvw03t+hkqlMc5FUcCLs5ZPuiJwRINYnVicfIJ5PNU+yCwF6pmA+jVBJCQxjYrHWYXniGb9c/In/x9O3f1Fgm52+1jay0qDVbedm65Fz64XE3MGx4+Tw547zSjn2BA4rtPcFhtu+CD0WAI921/gHCsvTEYIIRK0p8Zi3Xv3ZsyPPgrhPffSVbu20/d8zTOkHfIVoFoOadMOFfFlZfim7iWzO6eeNtm6USVeQ0HG14Bh066WFmAaVeiCbICmUWGOn6lFa1CV+BgbVjpzocLFjEhMe2xsHIODlszX3t6OQqGISk31vbS0hHg8gUwmA03T0NfXh7HxccTjcezatRP3/OznKJfDZStqNArTJ5nH/U5X7I+Ux5T1WJK5ihWmn3X+tstDemGHUmnQqMpa9jGLPv5CZRhV2hmFy7StD75aXsLMUz91ZuAxGdFC4/alsenG38UGRj5kDeJrsLE0fcpzpLH2brFznZ++TPd6hxke+9Y7qc1OkSNNWxs7DelOv/6Czr3tZ0CUz4RJtgym176/s0S+AWpMyivce18tplobiNiENiYjmmWu9jgjcpzK/CCdPPnvq3u7Gh/NGrypZjvSPfHDP8b8iDjXgGkaTF+ZPrsCYUD+flV7u3kQ6UlPT09jdmYG1xw6CNMEjhw9iuHhIVTKFZwdGcGRI0dw+WX7AQCnz5zGwsIC1q1bi1QyiQOXX+aM84tfPoClJTYTW1bIOs9w47TZTHvbLX9m1eQl1J9eZPr3CAizFrT87pfK0UfCqHrCj3je4I57EcjY3bCSpMNownQTSPRt6y4jfskz6XNnHkLr4C7n91O3fwKAho0v+G0BHVEyoll0L00+gwzBiJcmnkSqlWFzN00MXPYaDF39Vjxzx6cxfvSf6fO2TZ4l+VJM2xC+T/7jmn8MAKZhbZSDFndvEharLy9aQsYhjCaNtOdT9BK/eclVKO/xgHj/xpSRpZHpZJvVaBiM5YEde07C0ma4bYpzI07ms7a1l9MbPcYzTLcPWu91PdncFFYFIm/PHn6E3jnOzbmxpZNTU7jz8F3U+RMnTuLECbaEe95RZ3gTz3s8070e82cfshYmwuFEZodeGxgAP8tW2/A+T3OD+psO++BJ2vaiDlCqUOlFzpMOU8C1NV9+az7TJhlhGMF6cfxximnr8RSMcoFDUE1jIQj54lsVSGboL6rhh4mOTQcBAB3rr/Qxbao/M8GIO44IvneW2pQRo9RSiFpOUhwplcz7TdLEZQQRGKMg7M8aUYMj7ZPHfSYF7gS1Jucvb1Rx9ixS7QPE9N465SaV0YwF06zSj4xYY/I7b8Tcsw84v3WGerxlYCcOvPc/cO9nXuA7p3BxoTkzookWLaohZ3EQxq3qqEudK1iP1jznTdTv8oLrpKfpOnRC0naEEk7GLrP2n9WWZhzzZx/m0tA6KNIU0OjZcSP1u2Vgl+Q6779/584c4zSl2/bueRmzPwmx7wKPa9ufiscrnhd3bkvInCFNgjl6pUI6VMseQlI9zpG07VClYHMHMaMgI5rVJJykrdlSNMFQBw/8qrcRW8NF5h7XEDjv+bJ4z599GEszrjnHZFT5iiUyyPVuEQ9kGEh3ssMlu7ZcR19vHaWFFVY/mpJp83bhJ3/8WfoAR8IILCjAtBVKQC7DCkyjiuknD2Nx8mnnmKbFmGrHVPsg1deRMk2Tspfai/3C6HE88n9+A8e+9U4pkkXFPJwY5tp1tQ7ultJmsDQZM0/dzW7rubfnnn1A8HyCHdFEZgV7XEeFLNAckO8AzXDtv0XZuzzqcZih43B9byCpHg/gaJYKW6N+s6BpsfAOYZ6x2fOzHdE0Ik6bmUnN6lxrEj7rXRSY1Hdkze/1AZApEuItixrzlNskN5pBDrPpzrXnVdOgcH7RlE9W03XmQlSYoeMcuUlUBF6kmqbXVWFIRkY4c+838MQPP0rT4d19cws6kBKjX81bnJNMLVsbd/CK27hNWGkrZa5v+snDjPk4r6rnXk8e/1Hg+svaODghZFxBO8aRADmTUCUmWaI2ccZLj6ekZizV5kviQhDm+c2R/Cn1uD204P0msvsJJe3QTNuEeNnRwHyAstdJjXM+YNDPy/cbGH/o3wNHMY0qRXI8Rcevk1K4nuAHlbYO7cOe276Edc/1J4VSuDjQdEw717cNrYN75OzXnEVNLGlr/n6ygjZMtuTCyZhVXphyjqRae+l2tb+TLbSTlMPEvfZLry00YOMhJTGzHJgk1lKWd79Z5RUN8TpcVcGyiVJg2LTb1z9H2EXT40zzCVfS5HlIe8MCGcwnzKaPK7V61eOEpB0kHZumSYdYcbzHNU0Pxxs1DSYCJG2N8f3A+75JTHqeeLblLU6YM4yqb5NTXpiQGKcKEdHkM+vlOaoC6N76vFqbmwLnVFidaDqmvfba9wjOyqq1g+JmI0raJmo2zoDHYvNVo4yHv21dTzzb6VHCWr+Gr6HV3E4KS0rS1vzMJAAyyU3YoUISqylj0R4nYtJFbU2jSi2iC6OPOTZ6e2bW/bWd/3j1yi1NhsGYk389yTYrsQjzXhFSuCjUMHxtZ7EjGu3kaOKp2z/OoMkKV3N4Ni+XdpRc+x6bNmNQtuMmlXbX+R9rAquJYI5wVdQCYBogN4nW+xeh2lgtRNDG+EM/pE5zs6x5kMjxsyYqXBxoOqYtssH6FjrOglktLfKH0DghK1Kw+mV7N3sH5dK1MGZVUGsf3s9UQ+txjiqNMMVpMhsFv6HKmAAAIABJREFUL0UycaF2/WSqOpOEhM5gWkaF7RHufUZe2+DD33kvnv7RJ6k2bBrEdGmazlGPC5h2bQFtG7qUaM6wafsUKfLvT8+OF7Lp8W5mGOpxAJh89L/8g3o8vHlMSCOcw2ThD/liNmLMRW58GKVk7T4s73fv8HWW8KTMaJQZBIhamtOrHveOkSeTFQkQ5KVuI9e3w+fvorA60IRMO0TmIM7HN3X8f7hdNKakXY+NmzEH5QHMGdtZvDkLCOndTB2XpFXGgzXk5uXR734AT/3nx0P3o+cMjoll0h7AeyxfBfteyjkMiuAK2hq8n6HpsWmHga1h8feSL1vpMtaAd0jXwzmiaZo1lijki+M9TobpiR3ZbCfB5Vvajv7dW9zZPElRrE1j+E2BaVSpe8lLwhSEtiGirgLHYW340Dux89Wfxt43fi3SHADQseEqtK+/MnJ/hehoOqYtgl9CZi+YRtVNwerftWv8RS6YAkDTqApdS1MnfAtjPM3zJA5jHyXU45T9Uo72WDyNjS/6XWEbXpIMHs6dOYLJx/4rJKNiqcdF6lyOI1qQ9Md1RAvLuOn7rLGkRgIy6nFb/T9/9iHiFfBqjRhqY9/lmO4/WnDIF8umPfrAPwpp9YZ8MUaFyYzT9ti0g9LhSpRf5aE4ezagBendT0vaMKt1SNruNY0d/UHoMbzIDl3hO9YysMuptw7IS+Yk4pkObLnpj7D15j9GkpFYSGF50dRMe+yI+MOIpObWNIagHSbki1ZVsxeAAOma+Fto+aPsql4JTUxzunPIcXrhI8ihyMXpn/0t0Ute0vQ+I5OhQbDVu7a0xqQhKO5XjzlzuQxQ0hGNPmET5bbzxWmHW/RteoxKyT++20iCNhu0fVWoHveaboK0HIEhX2xHND+j53iP18qNin0uxBqmh7/zPjz+r38o6E+ORGt2hJtG0ThGGfY1TT1+B6pEXfSoyF/p99/J5mnTW+sadsVDFlIda9C19flUzHmma110AhUioamZ9omffC6gRTCzHX+YdpDStFg0R5TabMwQIKHjDTk3mdO61l4iVMoaPpyk3WgsTjzp/gglaNONS/Pj/s2WvfGx7wXzngQwbS3m3hvS8ztiukyauXHss+RcsuBkRHO1Krr/mLelaUpsHO25vLSLIysCJW2u97jHEc270aldi60VqCcXd6Uwi7lTv/Ad9/pGWBPSucatTaP4mbEK4pQXpoj9lolqYT4c0Rx474PXp4EbSsjA3jd8FZte9GGk2txag1yfGYVlQ1MzbaE0wvj91H9+HF547du07dNCpnt9KHpYkojMIkRJF2SeZuZchC1O0wJUlhER1TYdhlER13fuzDGmTdt+HjYjYqUxDVKPa7rriEYX32Df3/xOjuOQw1MN5wDXqQoSkis1NmnmELXhwQlLoDckDQr50mqmI/J6S/PjKMyeoalgvTc6rR7napAMlpe8t5HMPfW3Ic1WxIT082KEfHnx2Pc/5DtWWpgApd0wyrjvcy/Bsz/9sgStfKQ76Cxrumcd2XDDB0OPGSNiyO0ICYXzh+Zm2gEOY/Zi/+h3P4Czv/iOZW/1taOXj2Rbb33Sqo+B1hg56XzGW3Q8HrZ+6rwg1OPO0I1zmrMZzuLEUxKNSQ9ceRrI6ztuL4aMMDCA2NSwHHSC1ONajFDb285OfEl76Kq3MI+zn4hXaiTNA0KyPI2I58jo6M10xh28ZtN2fnIlbX9GNKFqWAPSHWuQbMkjke1yD0r4kvjjtHnq8fo8w92BWCp0/7VZGdGI4zLqcdNwaq1PP3U3yovTMMoF917am0Oj7Hj9R0WmZwP6970Ku173N1ZYKCONbe/eW0KN2bHetZWvPfROYbIXAOjZ9WKse+77Q82hwIeq5yZC7eM5d+YIzp1h13hOttI7TT2WjOSIUpsQgIaiJzMboHkkbfZiSy1sAZI2xRhZjmgN4N3Vgl1EJqwKOax0acGo2QF9i4hJq8ej2LQtRzRPnLYWvqqz4zsgUrGTlx9W68AJ+XKP8ffpTtQUDJApWvk2bRbtcs9u8MDrceLHn4H33dBsD3NqSDpMTFRdzJa0xQimkbVxZN4H0/A8ruBNg2maOPJ3b0YskUGl4BZaYps26vsQE9lODB+ycjXse+t3cObeb/jarLvuvRg78n3pMVsGdlG/s90bMT/CrleQ693qlOk9e/+3UTo3Kj2PAhtNLmmLYUg5g7AlGhunDv+N/IS1+Fg7p/ipu77gjC+TzIQKi2H85ZmMXmCXQT1eLS2JSSBBVZUKs1AxTAkcxy7bLspUjwfZtPWYM46Q4crC5vtM9Xi0TV+QbsVifuDS7IaQG7WwOLH3eKTkKnZXUn0d5GxoVBlheuyNTlhJu7I0xz7BYtqMzbhX0jZNOUnbrJZphs2Zu0cQn/34v34ER//uLZjm5OUHgESmg/qdliovGg59+27Fpht/n3lu52tcv6E1z3ljw+duRiimzcDRr78VT/zwo6iWFiRai9VoS1MnpOe1HdHsRdxJ4uJhDu3r/KEcVju/pL00+YxgPsKGrrlHGwZb2A/pREfSEE1d72XatPc4c4MSZNPW/CFfLO9pWdocqY1gji69dVy/8DnSTmD+sa1zhlGx0p06TDyETTsoxa/9l820fbdP8zE906j6tSNcV41w6uQqJ2lP0HftHjOpjYJpGJG8xwE43yw5s11Tm4WZp+5GYeZZPPlvf4wjX3sDs026ay31O9vDLl6S69uGlhAV/Eh0bb4WXVuuCwz/iqfbIo2vQKNpmbYoFrMwfZJdtIKFQDVaKFdoAEBfLY4yket2JTJi0Up3rGH2ZuVnnj15L3smyoHGDV2KvOCwKbIJk2hKMpNojmissQD4vMejhXzphHrcdSILzbRrze0Mb3oswZibfGfC3osg9Th/E2VvasxqmSrh6X0e4w/XCmDojJAvyU2GHk86tFD2dw0MVxMP0xaE2mm1cYUI5SfgwmDmvzeojYJVFzuipqRmAiM3AZWl2cB+plFBsWYj98JbeyCR7WC22/nqz2LHrX/BZaxeMyAL62tqcB46NqhkLI1A0zHtQo1ZP/q9D9QxSoAkZBji8yJoGlr6tgMA2tdeZh8MTv4Bmhm5KleeSOJxprP7OnbN+iXuri3X1dLGykjahPozjEmbpR73qL+93uNMlXoQjZo/TttKQCJPKzm3Ua7Z3+MpBj0m88+gMS2SbGmNtZk0xe9R7ZxpVmsMxL+RMyolVIsLtbl0/3hCRzSXTidUiJlB0CtpG5R6XJQ+tX14P39+FrhFgfzHWWFYpkfShhEtuQrA/kpO3PEZuc6mgXNnHvId9maAjCVzwmFaiZS7JC5589cDSYgFOKQBtOe5QjQ0HdPWNA3FuRGU5scbNKLYph1uKCdS2/ntLL4yNmfd7z0u5CoO8yGPNU7S7tn+Aux63V+Ht2lTi3YA12KFx3m9w+1rctTj/j7VsiCfPGBJnh5Jm6qEFRJWIhRL4vQzPu6PAJCSNuO0/X5xbdpErXXCJOOzE3sc++SpJZk2IRGbdBtWwhzvM/Un9aDjtEWQ2pAymHalyA75oiRtoyrFvFiwE6qQ94YnQbMwdsTNRjd78n4Y5aVQcdgAkCOSr+iJNHI1AcJHK8N06HVQY8EqOaohkQuRTlqBQvMxbT3WuLAQgG36qovxEaE2Tty2Z5Hj9dT8cdpcCdI04RLvSvL1yNcsk0I83QopSVsn1eN1SvleSdugHdFYKM5ZXq2LE09Tx+dHHnHHce4OsZGKmMbUUY/HU75KbLQmx+9JHTS2dwzqmMjhz34HDANU7m6T3kRRmgvP9cveDSd9pk/S9oeAJTLtSLbQ1au6t13PHjjku7M0faL27ynvQL621WKwpG2ahnxNeg+KM89a8xDx4P5IEj6qZdc+f/z7H8L80z8OTUMs3er8vfcNX8POV38GbQztxfRTd+P+z9/spNC1se2Vn8TQ1W8DAGgx/5rVOrQPB973n7j0176F3r23SFcvU3DRdCFfVl3kaMn42WAsogL1mFEtQWe8zABqEg75261Y1bnpUCAlLK9onoROxgI3whFt4pH/5DJbucAoHjMJ6hssaTuOaLZNW6AejyWz9AlG8Q6T8AUICzdfiSVpa/GUz8OXLhjiGcD7jnjHFoR8mZ7qXf7+jucZZR+nN7lESBZD0yAT5QCAWKz9TLoebU/Yt/fUnX+F2ad/holHbxe2O3f6CDuaxDQ8jmhVSgr1bwb4ePq/P4WB/adx5r5vOse81e2MSpGbL9yslqnf5Xl387A0fQqZmud4ZWkOR7/5NsRTLUi29GDbyz/htIslc0i1DSCeaUciZ8XSs5i2aRgwKgXMnPg5WgZ2Osfb1uxF25q9GH3wH5mOaRuud+3e6657L9Zd914AwL2ffVFDtXwXM5pP0tZiMKt1StqkyTHIES0o6xqBdOeQU86RHluzikHUsDD6GNVvwi6vyPAe5+Z5JgXt2hzWcVbN6GDMnfqld0AfLWKwpURxnmr4VctgMA6vOpc1ZO2YMFGEE8hMqMejpjGtSWhMGzN1G2UWMnIToXmO0e2E99Oxade8zJ1Xgv5eyOIj3tFEmfuYPoMeRzRN0yjKWXHF9cOdoVpaxNjRHwirap07fYTrA2M9R48jGoFH/kE+qUhlcRqnDv81JWkDwNM/+gtifJFAQDNto+iGlBWIzUOlMIfK4jQK06dq362LdPsg9r7pb7Hz1a4tnfVN2Lby0Qe+i0f/8bdx8vBfU+cHr7gN/ZfeCgA48ePPYn70US7dANC+9nLheQUXTce0oUfPDS4NU2STDcEMiZScRqVMHGbbGNm5x3mLNMG1ySxsETXT008dDs3oRVgYPQ5AXnIjwWKEpmkQmgg+1xZW3PIyUC1kaUrG3K2Du5kzOX/57Luse+yngdUqnmrxhPx4Q9hq97qWOU3zbuRgmWnsFKEbbvht//sVdhNT044vjD8BoBbVQcx39v7vyI3j3Jdw76CMKat1zV7BALSkbYfH2SpyJ2yzDhRnXRV5eWEKAG22cUjxaAKqRBx4oaZ6D0Kub5vvWB8jY5qtkTLKBZx79gGU5yep8727b0LXlusAWOlfT9/zNeG8W1/2MaQ7hpDuXMttk+5ciwPvux373/lPgddxMaPpmLamx7hxp5HGYyxSjQqbcscRhQQR7Tz5mcl/qYIcqNl5qZAv75xhiRWck1jIvfexUggOdbE6+g9NP/1TAMDJOz/vHvRk1fKPY53zhryUF6eJMWz1uF1Wk0OAkF5XEuZvSOibOX3k77nnvGMHaSZqDcW0edTo3nciWYsdtkIPfbK2xPzkG2dx7Ue/+wE8/J33YmnqGU/LkBtBmY0jVZCl3o2m36YNAMe+8Tb88kuvdjYgXu1YGCzWNjQAcOKOT2Pu9BE89R9/6mu3MP4Epp+6G0/++8cA0JJ2eX7C+ZunTaoUxXkpnrnj05h87L8B+L8Te1PACourFucxd/I+4dgAsOcNX8Ge276EA++7Hbm1V8P7Lq258s0ALBV+rndr4HgXK5rKpp3f9RLEEunGOqKxpBxDJGmHgGk63fWEoO6tJ+NX7UftHzv21nvNBtw9GyFpR6bXp28PxKPf+wC2v5JROQlhNg/++1+aG8G9n3mBZ0CDUI+z7ODs0cuLMyRR9L8hC2ZQ9AqYBSVNmwaKE+SCL3mPwzIvuD4RbtpQjvc41clj02ZsjB7/148gv+sldHUr6lmYMMqLDmMzhZqqBkPiPRM5lhmVIqW5s++VUSlSNvDHvv9h7H/H9yKRSErrc6d+waxAVpscT/zrR4h+ruMcmWbUW+To+D//AdrXXoaTP/kcLnvXv3Bt5uNH/wWxeArd256PxfHHqXOL44/jke/+JqqlRex+Ha0qryxZ39ADX34t1lz5FphGBRMP/xt2vvqz1vEvvQaXvvXbVJ+e57wb2U03ojBz2kp9apro2nyNc37naz6H4rkx6LEEliafQWlhEkalYPkUFOd9pgL3Hi3P+zT1xI9DOQ3Wg6Zi2nZKwKnH72jgqJplmySlJsFCEKaUnaOO1YBtL/dXGHPaMdTjzmJa+/fsL76NzS/+A7KTawklHZjqAN/rmz320tRJwWCSTFsy/SodNiQwahMozU9QdDjMROCItewIWnS4pTmD4arHxSFfpDTvu3rG7Zh56m7MeFJtUqYKlrPdeYJMpMIj//Ab3HNGpURp7ngbnCorXCwEjn79rUK7O5M2QtJeGHscZ+79BvoueQVO3f1Fqt3sM/dg9pl7AADHvvkOdG15LrI9G1GaH0eubztaB3fjmf/+FAATIw98D9VyATM1bRaJ+TPHAADlpVkkMu3u3DVNQXlhEs/86M+tg5qOsSM/wPRTh1FenMKxb74DW2/5U0w+9iMM7H81ACDbsxHZno3UHE//6JMwykXk99yEtprZImxY23Igke3EycBSz41BUzHtx//5DxBL5RqwI6I/9FOH/xprr323e5Za6OuYxnBt2lR9Y18uCls9TiSgcGzaVj9vZiW6CEP96nHT5EvaLLZ25r5vOTtw/ngNhGk65gMmm2XZwatlOqbXVo/bXaKEfMk096QxlU5rGpQRzWkmVo+b3sIiIh8Q31iS94NUv4v8PqRfA69nf7h+LIzc8TEUzBaUF6e4bTQ9hhSZoVDw/SxNnWSGjcmgMC3Y4ApAapxO3/NVnL7nq8L2xdkzOEt4r/tgGhg/9i/CMR744quCCTONWsEYC0uTT+PBL78WAPDsXV9Ab38fJqfmocdTSHUMAoaB8tKsY9+fevx/oMUSSLb21pyLS9BiCWh6HLFUDpruDyVrgFzCvhTTxMKI2NGukWgqpl1ZmhEyikjQgPGH/83DtKOmMaXBCy068T9/SbdjMHaHZztjeRYTsu405YhWh3qcK2j7v5bT3jrBEYtmyNlwPZsU2T5G1cNAvWlM5ed32oNkjNyZSSJAP39/P5KEMNR4R3LfH7qEJ2nuKcyeRaqdTKPrfW5y749TvIVBcBT1uMn4S64j/z0rjj+C8RFxVSo9kZG+5mPfeGso0pod1dICqqUF7qbJrJbPm0r6QkJTMe3lAUO954nTnj1xL9rXHYgwtsHM3rTk3XWz1OMeSdtf7tCEZpJt69yGCtet8GPXY9NmDyh2RGM6FBoVptOSm8ZUrmAIbQaIoL42gyRP2yWOUGlH2XwRIV+aHiPGor2jsz0bfHPbmB95CInHuwLjnqGR6nFvWCTxp+x1eP0NZNpKNhch271erl68gkKDEJlp7961C52dVlKIo8eOYWbGVb/me3qwY8d2mKaJ0bExHD/+eGCf1QqNkTuZTo5h4vgPfhft669ALJHhlrBjwomHFTMGRxJieI/76je7nVy6qfDeejzfGxWnDeTyW6RmLC9Z3t2UlzcLpkHcHzmbtmnQZRbdkC/yuVj9nvnvT2H983+TPXcdejk/03J/zzzzM3Ssfw45EUSbgsWJJz2FH7whX/QGjxXy5Q9781BnVPHkv/+J/0I8oPPAe5l2hHew1mfikf9AXlDO0kbp3BiSrb2h7cQ2FieeRrZnAyqlhfNqg1dQiMS0u7u7kcvlcOfhu9DS0oJ9l16COw/f5Zzfs2c37v7pPSgUCjh08GqcPXMWyVRK2Gc1w7ewMhad2Wd+DgChmLZpGDCrVWHCilpLAGz1OBl/bTvMuXWha/2YaUwj2Aa5GdFkutP3LNU+IDXr3Mn7UZ6fwGxASAnliMbk2f6DhlGGR+zz0KoBmpVhau7ZB7lzMx0EpW+vAZhs9bjj9OQ4HUK8QTBtmnk2bY+JpOYjQb3fHi2SxnLElIBG0swXtP0nA2DHMYtgwsTRb7y9lho4GsMtTJ9EtmcDSnOjy+3frqBAIRLTzvf04OyIFQYxPz+PRCKJeDyOSqWCbDaLUqmMQsFKvzc6OoaefA9SyRS3z2oDzaQDJG3JT9qoVqhyiLWjloNFwIJoL96atxKSZyyCQA9txCIeWdIWlGGQ8PD2pmsMg/GHfhjciAz5kpS04bFpw7PZsZOrmNaOiDt1iVn0QVbtS79PVOge5cUO0M/RP77vCfnqg9NaGWaSGu8YWjSmDcqTX7DpldaOe99pMYzyIoyAIjEinLjjM1iaOoHRB76HoYNvjzyOgkJYRGLaqVQKM7OuQ1epVEQqlUKlUkEqlUKp5MYnFktF5LI5JJNJbh8Rurq7EU/4yeztD67vGhayY5KeiW3tbYj10Tl2Uyk3t3hHZycy1eBxNcZik0qloMf9C2dvXy/IxSmbs7ITxRPuvPF4HL39fci2WKXwOrs6iT6mda01CT6ZSqGzu7s2Vg69/X2It9IFGoKQ7+tFJssOZ4vF/Z6c3nvd2taCOOf+i55LZ1cnsqbEczMNxOMJ9Pb3IZPNAACWRo4g02+FjXR0diJVoMeJJ+JOW/u3dW+snMzZXBaxRAK6rqE7z79f5uIZ5xr0lJWUIpXmx92T19ve2Y4q5TzpMu1k7T1LJOx/E0DGorc73wOjSN/3RDwOXdfRnbdSUKYzGWqulvZ2mP19SCYTtfEtGnuJ9zsei2H8ns8hf+V7rOvRdZDe5W0d7Uh4nhfr+cVq76em6859tZFOu3Tn+/K+viz05HtQbY0hLlE9qrOrCznIfeuid69y8j/R3dWC6ujPgd0vDWy/ErjQ6AmDZqZ9TOAA2SBHNJEClHdOzs43NTnpO9bb3ye8qDBYR/wtO6YWS8JOtjc3N4epkVFqnMLSEuyqtTNT0zhHjEu2I2HC9N2RwtIi9IqBjOe4RafLtBMb5tEOoFp1j1WqVYyNjCK1uYB2AFMTE+gzDUuuMQyMjYxC0+NYB6BUKmFmagb9ABbm5zE2Mop0MYk1kMfYyCjSC4toY5zzX5l7r+37MTs9jRnOffK2JTE1OYkFiec2aBowoWNsZBTZpQJaAUydfBBrakx7dnYWM57nWC4Wsbhg3Vv7N3lvlpYKiFeq0OJVTIxPcO/X0uKScw3xbAnDAIqFAniVjccIOmamptGadp9rtVRAvPZC2GNUKlWkAJQrFRQLReQATIyN+SIlesplxEwTk+OTGIL1npJzLcwvYmxkFO2FAjIAyuUKUgDGRkacNpVyGc/c+0/IX/kenDtzDOnOIWjVCux97Oz0DPUcvd+qPY5hmhgbGcWwCZRLJapNbGjMuefjo2Pcb4bExNgYyotTSLZpge/t9OQUFkaD3xnpdWZkFAO1omONWpcagUauk+cbinY+IqUxLRQLSKVcqSqdTqFYU4cXCgWkUq4UkUmnUSgUhH1WNxjqPQJStXudcTx9TdNXuccelYKtHmd4jztZroyq0831BiZDvuxD/oIhY0d+IHkN7Gv1pjxk9hRURrPBSpEofXul1OP0cRO0KcT+2/TYtGsHBZOTyUhCend72hlEcQr38ZHVy0SbYZN5/sy9Vlyu4xfAyrDnkGOdM6plxxEvSi5/m2ZWyVmyAIfsAzbdlzs0LY3A0z/6C5y44zPBDRUU6kQkpj02No7BQctRqL29HYVCEZWarW1paQnxeAKZTAaapqGvrw9j4+PCPqsPXpt2tBhjGqyAVYOfjo+ixnYc8hcMsRdek/QW94QuaQFpTBc8KQvZRAjitKUQfM8e+PJrcfTrEWNdWSFfxAKfautnx4pT9lV6Q+Ok+jTFNm06kDqsJzlNA3MTVxsym98k3kQ4Lgw0Dafv+Qru//zNWKqFLjkbClapVzK0yi6YEiVtr6Zj+OA7AAAt/TvoKaqC4jg8hGLWjWfsEw//G8aOym5uFRSiI5J6fHp6GrMzM7jm0EGYJnDk6FEMDw+hUq7g7MgIjhw5gssvs2qwnj5zGgsLC1hYWPD1uVhASwbwLCDyC8T0U3ehc+NBYhgDMCT6G5zc45ru1rQ1qoSk6PGCJvNMMxd7mWswQ2gVXJy+52tYc+WbMH/WX7XIi2rhnK9sobQkZhrQHe9xP+Nce82vU6kXa52oa3elOdcBzFtakgVmyJ4kk/HuhWimbZ9xmWuyJe855yWGHNttQzsCEqVHvfTAdsarbYI0RJa0+/f/CvOc4f2eQkH5citc3Ihs0374ETpt29ycm+d2cmqKGc7l7XMxgL2whV84NE2jGLY1kOnfEDDgePvqdGjR5pf8ITo2XOm2cZi1P5e0cx3M+uCSmoMIqskz934dZ+79euh+xKSSzQyG5Ej37d5+A2N0f8iXK7DW0piaYnW3nsgi3TEkXR7RRyMZccVg2uQ7aJdMZL+Dlno8UNanksdwzpkG7LSpMqYNL2w6mdNX6Xd+9Mj3meUh6U5h6sArxq6wetF0pTnPCxpU+s80q0JmQLS0/vHYtDs3XuW2MKpOO8pOa1TByuzFYlb1YHHy6brHqAemaXoSevhheJiFyVWPe5mUCREjyO98Efa84SuIZzqIuUNsNlix2SCeI0v9ztSOm55NJpsGk7Bps5Py1OaubVooX4MGvCumQZsACqLCMnafEIy4sVX+FBTOLxTTrhfMetoRFi6eClVCyrUlnWTODTtKe5OTUDZtunKVRlR0Ys0nn1KUf91GeZmcDqUdutxYYo3D2Fj2YmaxDqo0p9gRkUSCeD7ydHvaMp5FumPI+ds1kfz/7Z1pcCPbdd//jYXYCJIAuJMzQ3LIWd9sWqKnxYksWZFjV8qJkziuSiVxKuVKnDiOs9iJy4ntJC5Xynal4pKjWJZl2fGqxZIt2bJk2VqeZtNb5s17b0jODDkzHBIcLiAIECB2oDsfsHU3erndANjo4fl9IYC+y+lm9z197j33HLPLHM1yHOdoqSNeWqmv6QtlBQfBNpBb2kwKWel0+Qoe/PF/wvp1aarITuW7JwgrIKVtBtEAIc+e1VLASLOywSTx+CbTQOuLzOi3LVrTFrfpcLrRP3Gx6WXezmCvQbeUNrNkEu9xtSJy3wReUWE2HPjqYUwFgUkRjFz4sOEEI9X/h3bbksAmGssctQLQ224piNbsW47VrpFQmx6vrg6w3x8Pv/DTumXk/4cuzrRtAAAgAElEQVTwwvsZWlaeRUpt3Gm990xM5xNEr0BKu02ST263/mhyepwvFSTfMzv3mZSB0raZFpFE0b2U2hyarU2lK4rb/po2z+t7wZuC2aFLebuTpIyihadgaYsiyXEcV/2dQY6h2feI2pbCq1mrAi8pLI9rL4fTm36XzI6rlJF4x0tpxHhvhIVVSPihQY5hmUS+YyIwMq/fcO26KL5EtyTLIaVN2BdS2m2j5vBjDI5zqHih67fFskYnqEyP12nspVacHmdUjFr71Tu4ve/+53/SVL1mvGu12NvyLV/yAb7pOV0vzzmcTM6C1Yq8qA/ptSocPFOvpvrSpHC9G5m6lIrXXlwYrX2l+O+bt3+72VYjYQr7/c4S7lT+8sQUT7xxa5dEWdWUHepoTZuwM6S0u4A0M5QRBd66ftgpq0BQ2vIlIjz/16UySPYZtW9py52L9KhoZF/KbIu3h7FeX3G52vY2Wd3AqCyzWMv0uHR5geMcNWetiua5NyVQn4FRfTFq2fOlbWlrK2S2axU5+4FmczIlWy6kal03t3xJT0u7j+Jha4TDFilllrb4XjjYuKNWq/Gpr7/qO+BwVYM8VYqyGOMmtqgRRK9ASrsbCCqfARST6p6wimkYTawnK1oSIktb60VAadA15VgnQ3X6V4XNW5/UOGpi+UFAQ6GxrypLr3/juom8tjmHqzaLwOIspTVFr/w/cfnFMeP1XwI99X35quX017Q14ZsR0RxON1otbW35WF7etJZS1Gckmv06+6QBYhOr38TWa59qlqTpccLGkNI2hc4ArTEolDMxA+2yeY/LKShklRKvaWu3qeiGy9iz1vR459a0zQ26oi1fDeWt55ClbB03p6s5wOFk35rXmFJWFE8RT3BUZu3rVlE9Kgh81eGQUy+jR317l1AuwOHyVtf0O7w9UD49vnH91xqfyy3BdfT7FfgKojd/Q/SdlDZhX0hpdwFB45t2RaHle4saV1BYLR7JiuvSTaXdF9TInNSOpa01cHZySlISpYy5UutPSmE6JchCiLaEMeWqSpBns7QF8KIoowKe/OUvi45p1W/1YG/5XaNKnUoxB45zNKaNzVB/+RL4Si3fttwRrQNKW2ZpS6LlqdxjRmaDOnovEsQRQ0q7KzAOwHqtKO3TZlk7VbJERU5QDqe6t7lyXmIeq1/67/r9agulW58VM/nKpcXqcdl1bn+5V7hsTdvh9lWnx/ky2/nJlNve8leaywaaLzwqSlGzz9ZjlWIGQOv0sRkEviyz2usidUJpS5WqRMmqrtkb6JcsbcLGdCg1JyFBrFSM7MtVWNM2OghKvMRNoTQ9LqBSPGyjTRODOet1ayeQjd6+bUF2/WX7tAdPvr32M5vlVv3fyM9L+iKgUlMiE1tfSkq76pDl8vQbakuxfb4CrpaPvZMvZIrtib6r3hWGJrRIaRP2hZS2KfTWtJsfHS6vermWaq2DVUsGJMUBUpIFok2dbXx6PP7ga6p1Ra0YFERDaZtc05a3qxfohJNFO2t+kvbv9AYZRRBt+VJyOlQWgn1KXKc9obYezTndjG1otM6Xa9vdZC+JHVDg+WQU23c+g+RaPQaCqE3V/5mBe4KmxwkbQ0q7C4jf5J1udqWt0FLDmhP/pt23Oee1ZutKlrb2INc8X3XZGNJUmMSgEuM49PUP1z5rW9q+4TnZFiNlq9gfmTUkguSnhnObcb8BzZcpRX/CWt51h0aoUxXe/O1/LOlP4CvV5YWWSKedsbo3bvy6yhHl+8jYmjZZ2oR9IaXdFUTTefJgEhqDi3yNlX0gEg9kvMG94TIUQp02t/eo1RF5U6shug7JtW/ry8E8Pc5YrFbO2RdAcPJSrQttpe0dnJQqSV46PW6U6v9Fel6NlzqtsKMSZzhWpy8FS7tFabNTSG1L22okFXHI+urwVHkNvlxoy4FOQndEJIgjgRzRukD/xEXRN43sWTJaMyopmkvanWtNj9cUYWb3oXZ9+U8627UUs021FGrKXSm0tz5ujqqMbn+o+ZOO0s4nN2WOaBrpH1leMviK+nYrFaXNV4rquxEMLkeIs3epFGFGmlpTbP2bb1ML8T32xm/9I4UC+tZz8unLACDNSkYQNoOUdhdohAQFDDmitURuUhhVxduElBAEQTNXMSCKH63cQssvfKWkORgzJcEwOJqzXjX2WYXWFws9S1sQKpCGEK331aogWv93Su3xjWUCxUA6CiQf35K9OJh3REMblrYcia9Fh7d8KbFdC46SfHIbRYU4BCysfOGn8er/+e62lo8IwmpIaXcDk+aG0rrv2td/RfJ9f+UbShUlfXsGxrQ70oqIpujAxGZptx9AU0xnvccdLl/1r3i7m96WL1n7gqA8PZ7Zechm6UmWBapt5BNReTey7uV7wNvw+K77JnRAaUvalXzpjkJ89srv4s7Hvg+Hz95qqx2KO07YHVLaXUBsnenuBdahUmhGgFIbcGKLfy76xpB/W3NWtX5Quqat3aDRgZpBIRtMYamHJ1LNFDX17h8SdaG3TxvKVq7sAh6sv8Ikg1AutpxXM9mIxjVUdT7TckRTWtOWTY93yipWidjWaVhmMwDg0Vd+oXtCEITFkNLuEFt3Pt38Ihm4WqJPGGpXUB2wm6Q339QtI2tV9Yh/eK61dKWkWadOdu8JW58dVshGGDr115pi6EZEkyZsUQ48Y8wxbepd/0TSRKWcrzeiIoL62rd2vxqOaE5t/1Pt5RPtvtpyguwQ7b4oE0QvQ3d3h9h98wuib2IF1cFOVC1ag2ueona2735Ockj8AtAoXtFOPVlXbOWCSlxoGSyDKl8uSP5q9M7Up6IcGpHhqk0LUlnVrj/jTEP/5EWEF95frwSgaT1qrTMLFfE1aGOqvDY93nREU66/8qc/a7Dd7q9pG4Lr7PQ/QfQStOWrY6gpTjatXc6nlC1QpdjXmmIYGzRLWWmu4szOg9Ymdafca2vamt7jxiztvaUvIzB6puWlQrNdg7C8PIy88L26fbHu+3W6Wx0E+ZrSdrh9mnXrqTDbjWIG6Dui1cOdmuvEeqXNOUlpE88vZGl3CpXBisWzOv7w67j/+Z8AX8orNCtaW1azOiVLiixr2qIyLI45zONw51zR+HIBT/7yl5Dbe2SonhHK+QPN4wIEeIemmt9VLW0TiqpWpx57XG8PcjMzlfn148aWr9qyQKfUay9MiYspHGzrFyIIm0JKu4beVio9JGvPEJCNVZWNPCiF0lD5+Cu/gNzeYzz68s8rNNxUFPpTxWCcHm9+PNy5L6suKEip02ZjDy1bn530MGZVGOXcfuuPetOognxpQG3d2fj5CAqftCso7RE36B9Re0FzeQZ0ShrExJa0bpKOvm61CATRNUhp12h68ZpuQfLx/ud/Ag/++D/jcGuRuYV8MoqN6x9TPc6XWy3x1r5ZBk2RkmHZLywI2i8MLJnHxGqqg1mW6skv9Chn9lp+qzCswW/c+Hjjs5qlzTxlLZmWrtdhWz6pb9cSOqAgx67+Xb3eTLVbrWm8LtPLqEHe+p1/hjd/54c63i5BWA2taZtAcZAWZyLiOFQKaaQ2XtMsp4xsS5DY0i7pD24sCsT4wC8gs72scdSYAtLdQmaARqYpE2y99ik4XB6MX/v7KiUEFA9joq9qljbb3l/FNXTVBCJSnLU1b7HHu390ganfOu5ARPaLcp9OnfX1FsQvMyb0/fJn/53xSjrkk9GOt0kQvQAp7RqGHHwEHtHbv4Xc3uPmT6LRShIRzSgta+AiC1U1/KJYdnUr1u0bqnYhUnQslpHupWGakhdQzMTRF4hA4DuntFmDZSj5FvClHDauf0xTacs6Uy7FeO9IZJDVYbVQxVvy5Bng9GCdTXL5h4y1y3j/qZGNrRiuk3h8C97QFDZv/zZyca2thgTxfEFKu4ExE2Hrld+TVRcpbYODnhT1fd2sVvTTb3wEp97/b1TLhOe/Aw33LrUmBSMDMYulLTSSjuhtITNGl/d8s1x/1i1f4pj0Cm09/uovMoQYNX++23c+g+kXf0hTBua27n4O41e/v9aO6IDBNpc/++Om+l/9s58xVY8g7A6taddp139GNFiJ10GNIrcIWSJgyae7ja0rsmwjYzuum5/aUVfanbO0u6qzBZk3vqqlbcIRTaFO/P5Xsbf0Zc16/uE5LP7Bv8Sb/++fGu+zUkSllG94rGsIp9tW7N6fNT6L/+9G7rzVL/03Qz4fBEGYtLQ5jsO1a1fh9/khCAJev3sX2aw0xOD01BTm5uYACFh7+hTr6xvgOA5Xr15BwB8Ax3FYXFrC/r6CV68FqDt5sdIcruIP/oqpnPJRsxGw6oV4SdQv/fJsa9raRxmnh2uWNt+205+oTcboV2b2NwsQpNdf7aXJ1MyBfG87u3zZdrbBCQLgMN6nQkONT8Hpq9L2GSlleuPZJwg7YcrSnp6eQrlUwvUbN/BwZQUXzp+THHc6nTh79gxu3rqF6zdu4vTcHNxuN05MT6NSruD6jRu4+8ZdvHDxQkdOohOkN99oq75kQG8nAIaWAmD00g6MnWXvj6WMXr91q1HH0nbUwmd21tJmM7WZMpEpoZSaU17ExEtIaxpWw02YhNfPbsbg3S8uI821buBELAxnSxB2xZTSHhkextZWdf9xLBZDOByWHA+FhpBIJlEul8HzPPb3EwiHw9iIRnFvsTodVigU0denE0byCGkn0lStgY7I0ZLrVzKwsTl8GZKFaZ1Wuz2Xb5ChG1Fkt04q7W7Oj8uWGtTuEVOZoxptHa3iEgRBd92cybGrk4FmCIJgxpTS9ni8KBSlykVsyXg8XhQLzeOFQgFerweCIICvvaGfnptDNLpppvvehHUblc6gJpTVrytTUglBaLXitHtUaVLQK9Jg+NyHap/Ywph2Yno8Vlv7ze2vMZXPPjMTcENgcrIy5w3PsD9eRLamSM3mkm52o789Sx7aVrEZtfvGiCyU2IMgDKO7pn3y5EmcOnlS8ls4HMLikoFeZGP57MwMBocG8e1vv6xbNRyJwOVuFXN0XCdntEFGxkYhtLGuzbmae1uHR4fBF72K5ZQGNfG5+Pt9kt/7/E2raODENZXzbl5gp8upOBbK69W/uwdDkt+HR0ZQCbrg9DY94EfGRwEdRTs6PgZfSN1rfmCkeQ8F/J62/3/Zxd/F0+U/RGTID6A1prec1P0vom9wGoGT75HIrIXL7UYo3DynQL9fsU546gxc6fstv2vh91fb8nir94nT5VJse3h0BHwhhfL+ChCZhdMTYLp2amXE2xF9AeXzYWnL6Q8rlATCkTBKrkMmWUKRCPx8Z5/jTtPpceaosbP8x1n23e0d1WO6Snt9fR3r6+uS365dvQqPpxoruW4Jii2zfD7fOA4APq8XiUQ13d/JkycwNj6Gl19+hWlKej8eb/ltdHxM86SMcKr2N7azC76UM92Ow+1DXS3FdndRyStH24ooqG3xuYQCexgR/769g4nvUi4rpn4eFV4A+FLLP3Z3e6dRRtyOrxzApOj3vVgMpUwcLl8B0/Xz2d6BwJcl9ZXOIRQ4wGhdjlIeTnfzxcV/4l2Nz6nEPvY69P9jZXR8DPsbSw2lvb/yjcY1UDuvcrGE/XgcE7Xvh6m0Yh3eMyK5vulnbyE4eUlTnmwuj93tHQTzBQQAVEolyf+23tbebgzhQQ8OD+IYAOBweRvlnDc/gen3/HPF9vXuEwDIZjJM5ZTK9PXzjftDzP7eHnLxZnmlZ7XednI/gfQR3wdG6OQ4YwV2lp9kV8fU/NRuLIapyepQNj4+hj2ZYk0kEhgKDcHlcsHpdCIcDiMe34ff78fMqRm88sqrjWny3qHtPV9MTaVXvwoAiD/4muLxStH8iwNQS7toZHqcYcrdVIhXWbsc52ikL1VK/3k0NGXSzv0tKs/giCb/nWNIDenyBGuFGcRAMxuYeD36cMvIdFdnaSd5SmzpKwCAXHytgxIRxPHA1Javzc1NjI4M433vfS94voI7r98FACzMz2MvHkcikcDS0jLe8+4XIQjAgwcPUS6XsTA/j74+N158V3NL0s1bt9t3AusFGBM5FPcf4ZWPfAih0+9D5OwHWo6n2kx2wDkc4CtGHKPU1ibNvFRpO809/eZHsHHzE+BL2ZZjR0Hk7AcbnwXG0KOS1Khq10rmiMbyklN3xvOGTkj+qlFRmAUy9z8SN9DGc6e6vq9/7mt/9ct4+o1f6bBDIkEcD0xHRHv9busWqZXV1cbnra0tbG1tSY4v37+P5fvG1v7sgsBikYlo8RI3UFeLqqVtxHtc7ffWA6mVr4B3D2Fo5l0KFSDxdFd7EbNKYQPSEKAs18gzNCXbyqf8v8nKvK0Tj28iOHUZQDW++cTb/2FLnbqi90dmAejnuN5b/guEF/4Gtl79A0Pn0C1Uk6cwetKTwiYIc5D7Zp22xz/x1iD90qVsst0OlXE4DG1BUp/mbP09cfd3sPLF/8LU7vadTzPLYAUsHvZ8Mcu0KyD56Ia0bZG1qRa0x2gUNb6Uw/0/+vc4ePqKqJ92l5i6YGmzzmAQBGEKUtqdwmCe43yi6tyXfHKro2JwnMNUWE05RtqoKxLx9rStV38fd369mQJy/aWPti1TR2E4P87VJ13bZw1jKvEHUOunE1aydX4h7VraBEGYg5R2xzCmtPlSHq/937+NlT/92Y70XsodAKhNs3Zgn7aRqdf1b/0aACCffAYAyMSqyySVQnPrTyG1bUCm7iNWpo+/+ouSY+ln1QBADqcHhbRIbvFec/H0rsb17qbl2bal3daaNiltgrACUtodwkgwkjrVqdPOrEsmHn2rJocxK1letpRNKP6u2UZtoM7GVrD82R/Hg8/9B+a61iHyJJelhqxPaTtcfeBLzelt8TURRw2Tr99Lrp2KEuvEbEi7/g/GEsvI6tL0OEFYAintBr0RxtR8/6LPOhaYoBIVq5xLNRWBofNplj3cWkSlaJ2zGSsSi1B2qpntZQBAcu22rJKq1556PyxR7EzSjtLVk6HuKLkryuYlK6FWsT2ZCILQhPJpdwzRAGhFHgTx1qSOhDE1b63bAo216sTjG0hF7yKz+0BaRaKoxJ7y0vrByReapboZqrOLsQ44R3VoqM+8tKC65cuG9wJB2AhS2l3h6LW2NLGFzsDJEiedQRE/e+X34ezzodhj69UsaF0jQeCVs76Jr5U4JrxMUaU332zsCS/nU23JqUnbt5m6pV1/2VDbmqXuiNa5tKsEQbRC0+M1OhnghS8XOtYWMwzrqM2i4uPmzzv55Ba7V3ivpWGULBHIFJCatSi6RzixpS2bKi6LHPAEQcDDL/5XpcYk3/aW/0JbXiUYIq9pwpLqVW0/dScznhEEwQwp7W5gwXSxoDHdm9qQRlkTW0NtvazYcVq8hiRVqEyBqm/tUlkC0byGvHIu71qdQi1rl5n/g+kc4XURWMqoWM7qMxXPQXRDguhhSGl3kOJhHPsr37RaDGy//tnG56VP/Wus/OnPSI5LB1zzgyxv56hWWt7+RhWS1suLAMVZhnpL8Qd/BQBIrb+m3oYa7a6Xs1jajDHG5S+GBEF0B1rT7iBvfPIHrRYBQNP7GQAyuw9bjks9p8070BnyErfaux7V/eOBkXkAsq1JMsXEZkWKLpam8hSUndFq12Pz1iext/wVFJLGc8u3v+DAoLRVp7uldR/88U9SfmyCOALoKWtgvVLpFLqOaKoDsTE1ULEwjrgZojd+o/lFK4KdqnUp/tK8VpVCRrVP9WlvofHXjMKuiqD8/4re+k22+iwvUoYyxtl3uYQg7AIp7eeEpmOUoDsYi63Mdta0+TbTiB41YqcqyZq2VnAU6ZHmx9rl3l99CVovfEOn3onA+HmFprSv++qf/w/svvVFlHPqMeqLh3uKv2d2VxR/bxFB41h9iSUVVfCiJwjCMmh6/HmhbnUJvG5UKr4k9m5vIyoWw/aeQmoHnoExVQVzlEi8vLXW9Zm8qsu1ZrSvdWDiAtw1ZzOpLNokVl9CYvUlzTKlTFzzuD7qUmxc/xg2b/+WNTshCIJQhZS2DaiU8nC6vUg8Vk8u4nB5AAB8uag7TZnde9xs24S1HL31SXgGxpjKLn36RxEYO9MSKtQS1DzsGS1tsUX++C/+J058x79A9MbHtfvkeZW13i4ux3TIf4AUNkH0HqS06/TwkrbT7QUA5BNPVcs4XH0AqgOt2pR3PrkJ79CUNHVkKYvMzgMExs4y76XeevX3WUVHOZfEwdrLzOW7iZqiNjM9nk+sY+ULP63fJwTNLV/dgbHtHnAOJAjCGLSmbSMGTr5D9VjT0i6oWtqNKFey6fP01qJi+aVP/xju/d4PmxG1N1Hdyy5TXirBVUyFJBUEKD9m9leYscUvWS0CQRw7SGn3IK//xj/Aa7/2fS2/awXTkChtNRrr3moKQ9p+ZmcZuf01LVHthdqUuNzSVkmG4fINGu6SrxSVJzA6rLPXvv4rJhpvT4itV/8AAHDw9NW22iEIgh1S2g16x/Ip55LgRduplj79oyhlE7j/uf+oWodNadctbem5eoKjAACXJ2BWZFsgqGzzasmWpWJpj13+O4b7jN78BJS20rWdoUuG2NHvqGa9C6lt3P3NH8TDL+ovExAE0RloTbtBj8XGFpHZeYC7n/gBzTISRzQVGmcomz4PnX5fO+LZB7VtXi1r2spaj3O6DXdZTO8o+wr0wHqyf2Sh7Tba92AnCMIIpLTr9K7OZoJrOKLlAQCvf/zvoeWkjnnEKol1q+E9ruoT4DCeoEPgK91Nz6ncK1Op+oseQRD2gZT2c4LDVfUwr1vaiikhaxafLfNfdwJV5zM273HORFYtQeBVvPI7a2mbSR5i5iWEIAhrOd6m13OEQ2ZpK9Gw+HpgatYKBJVtXi3T4WovNWaUHF+B4jRON/8HjG1zDnpnJwi7QUq7gb3nxx3OqtJWzX8s5tha2mrr2KyWtvHHRW16vNOOaPLW1Vj72v9ufCZLmyDsByntOna3PhvbudSLxB9+HQCQ2jym8aRVt3zx6uVEmF3TVnZEM9xURyjnDxqfSWkThP049vNji3/4I/AOTUPgbZwbWoSWBbdx/WOI3fsz5BPrRyhR7yCZEhdv+WJUoOlnb5nos4LD7SX4h+fkRwy3xQpfUl8iEUPT4wRhP469pZ2NrWJ/5RtWi3E0CLyiwt554/MAqmFOn2sE/YQhd379+1uqFWoJP4qHMc3m91e/BQDIxh6JuuGRWL2uIEvnlfbiH/4Iorc+qZhDXQmytAnCftCr9nOD+TX56K1PopiJP/dhKVVnIUQKtFJItxxef+mjWPjen8Pum1/QbP/Rl38eT32DKGcTorYrSG/eVZSmo3AcsrFVZGOr7FXI0iYI20FP7fOGCQuOL+Ww/dqnuiBMjyEJrtL8rOVxDwDJxzfwykc+xNS+RGGjuqYt8BWkoncxMH21+TujyN2ELG2CsB+mlDbHcbh27Sr8Pj8EQcDrd+8im81KykxPTWFubg6AgLWnT7G+vtE45vH04QPf+Z14+ZVXEY9TRKVOYGKb7vFD4nx2VF2qeOpb5PgoXtcnS5sg7IepNe3p6SmUSyVcv3EDD1dWcOH8Oclxp9OJs2fP4OatW7h+4yZOz83B7W6GgLx44UKLkieIbiNVoFJlWil26X5kSPPZGdje2sRBWMjSJgj7YepVe2R4GBsbUQBALBbDtatXJMdDoSEkkkmUy9W8zfv7CYTDYezs7GB4OIJyuYxUqnXtkCC6ika88buf+IFGKNiu990jkNImCPthSml7PF4UitLEFBzHNabePB4vioXm8UKhAK/XA47jcPbMWXz75Zdx6YUXmPoKRyJwuVvFHB0fMyN6T9AN2esBPPwBf1evjZ2ve2Qk0vgcCocQcCidi7+jfdavl7tP+kLQ398PwcC11Lvug0ND6GNozzfYTC/qcLqP5P9p53vGzrID9pb/OMu+u72jekxXaZ88eRKnTp6U/BYOh7C4ZECC2ozcwsI8nq4/bVjgLOwrrHmPjo9pnlQv0y3Zp2vTsNlMpmvXxu7XfW9nBydq3/fjcWRj3TuXU7W/9etVeu2PMP89FxvH06kU87XUuu7+xT/HyMW/ha2HL+tuSQMAT/YORt9b/bzz5he6/v+0+z1jV9kBe8tPsqujq7TX19exvi7d23vt6lV4PNUMQVwjCUVz+i+fzzeOA4DP60UikcCJEyfAgcPszCwCAT9CoSG88uqrSKcPO3IyxxvyRNNDM954l0k8+hZe/ej34B3/6ku1/isdaXfta/8L6y99VNcDvk4htdX4vHP3cx2RgSCIo8PU9PhuLIapyQnEYjGMj49hT2YNJxIJXL16BS6XC4IgIBwO4617i9jZudEoc+3qVaxvbJDCJo4O1SxfR9S9KC68wLPPNunBqrAJgrA/ppT25uYmRkeG8b73vhc8X8Gd16vBIxbm57EXjyORSGBpaRnvefeLEATgwYOHhqbECTOQpa2HoBVv/IgoZRNw+0MoZRL6hQmCIGSY3qj5+t3WpBMrq81oTFtbW9ja2mop06yvFCWKaJse9FLuHcRhTK2RYOkzP4bQ7LtxsHbbGgEIgrA1xz72+HMDGdr6SNa0rbG0i6ntRqx3q+luelCCILoBKe3nDBqI1REraoHvjCMYQRDEUUJK+zmDI5NbHYml3V2lfbi1hHIu1dU+2oaWUgjCdlDw4eeEh3/yUzjx3h/G1uufsVqUnkViaVe66xi5/Nl/i15ds9h5808QOftBlPM9/lJBEEQLpLSfEw63FrH82R+3Wgzb0G1Lu9bLEfRhnPVv/irWv/mrVotBEIQJaHqcOD5I1rRpCyJBEPaDlDZxPCFHNIIgbAgpbeJYQt7jBEHYEVLaxLGElDZBEHaElDZxLCGlTRCEHSGlTRxTetOzmyAIQgtS2gRBEARhE0hpEwRBEIRNIKVNEARBEDaBlDZBEARB2ARS2gRBEARhE0hpEwRBEIRNIKVNEC2zAdAAAA2BSURBVARBEDaBlDZBEARB2ARKzUkcKx78yU9BKBetFoMgCMIUpLSJY0Vq/VWrRSAIgjANTY8TBEEQhE0gpU0QBEEQNoGUNkEQBEHYBFLaBEEQBGETSGkTBEEQhE0gpU0QBEEQNoGUNkEQBEHYBFLaBEEQBGETSGkTBEEQhE0gpU0QBEEQNoG79ra3C1YLQRAEQRCEPmRpEwRBEIRNIKVNEARBEDaBlDZBEARB2ARS2gRBEARhE0hpEwRBEIRNIKVNEARBEDaBlDZBEARB2ARS2gRBEARhE5wTE5M/Z7UQci5fegHgOGQyGatFMYTb7caZhQVwDg7FYhE8z1stEjMulwvz86fhcDhQKpVsJbvb7cbpuTlUKhVUKhXbyX5mYQEulwvFUgmVSsVqkQxBz6o10PNqDb3wvPak0j5//hycTidSqTTK5bLV4jDh8/nwtmvXwPMVoBZjLpfLWSsUI+PjY7j0wiUUC0UE/AFMTkxge3vbarGYiITDuHLlMsrlCoLBfkxPTWNra8tqsZgIhUK4cvky8vk8/AE/ZmdmEY1GrRbLEPSsHj30vFpDONwbz2vPTY+73W4Ui0W4XS6EQkNwOp1Wi8SEz+cFALz51j08WVvD/v6+xRKx4/f5sRHdwNLyMjY2NmxlNfV5+pA8OMC9xUUsLS1jYGAAkxMTVovFRMDvRzqdwvL9+1haWobT6UAwGLRaLGbs+qx6vfZ9VgHA5/XZ7nl1OKqqps/jsd3zWpfd7w8gnU5b/rxaamkHg0EsLMwj2N+Pg1QKglB97e3z9CGZPMDwcASJRKInp08asgf7cXCQavxWqVRw7tw5jI+PIxwOIRbbs1jSVuTXfXR0FO4+N9wuNy5cOA+32wWny4WDgwOrRW3B7/djbGwUqVQaABAKDYHjOKTTafA8j3w+h7PnzmJt7anFkrYil93r82F/P4FCoQCvx4OhoRA2o1HwQu+lA5DLXqevr/rS1MvPqlx2p9OJYDCIcrmM8+d7+1kFWuWfmBhHn7sPLpcLF3v8eQ0G+3Hu7FlEIhGk02kE+/tt87zKZXe5XIjH45Y/r5ZZ2oFAAJcvXUIqlcLAQBAXL1xAIBCAw+HAyPAwNjc3UalU8M53vgOnT89ZJaYiEtmDAzh/7hwGBwbBV3hMTkwiFovh3r1FhEIhnDmzYLW4EsSyDw4O4MzCAhLJBHZ3Yzh//jw2nz3D4tISpiYnsDA/b7W4LVy8cB5zs7MYGR4GAGQzWQwNDqGvzw0A2N7eQSGft4Xsu7u7jYHW5XbD4/EAHGeliKrUZR8ejjR+c7vdGB7p7WcVEMteve4cx0EQBExNTvT0s1qncd+MVOVfX1/HXnwPF86f6+nn1efz4fKlS4jH4+A4DnNzsyiXyxga6v3nVS77mYV5JJNJpFJVA83K5/XIlXZ9qiEYDKJYLGBjI4p7i0sol8uYGB+Hz+dFLLaH2ZkZDEeG4Xa5kEwmj1pMRZRlXwTP8/B4POD5CjweD9LpNEqlEt64+wYmJyYa9axESfa37i2C4zgE+4PI5/PY3tlGNLqJTCaLpeX7GB0d6QnZudqDEQgEwPMCNjaimD4xDQCI7++jWCxianIKLpcLAPBwZRUDgwONelaiJbv4eCg0hEzmsLEu3KvX/cSJE43jgiBgf38fMzOneu5ZVZa9et0PDw+RyWTg9/uRSvXeswqo3DfTVfkzmSwS+wnEYnvY2Ij23PNalyESCaNcqWDz2TPcf/AAI8PDiO/vI5vLYmqqN59XNdlDoRDcbnejnJXP65FNjw9HIrh48SLC4RBKpRLS6TTGx8dwkEohn89DEAQMBINw97lx6tRJABzuvvEGBEFAMBhEKpW2zLNWT3ZAwMDAADLZHDgODcecgYEBcA4Ou7u7lsjNIrsgCBgYCKKvrw/hUAiHmQxyuRzC4TB4gbd0yrApexjlchmpVAqpVArpw0OEQ2F4vR4cHBwgk8lgamoSDqcDBwcpjAwPo1wuW7pWqSe7p68PB7W3dqDqXLS1vQO32413vvMdAITGskvPye7pw8FBCh6PBxfOn0dvPqsq94ynes/kcjkE+gM99ayyyF+/bzxeL6anp3v0ea2ONXt7e0inUigUCuB5HsPDw9jd3cVhOt3Dz6uy7JFIBPF4HKVSCYC1z+uRKG2Px4OrVy7j0eMnKBYLGB8fRyDgb0zR7u8nkMvlMByJIF/IY2VlFRvRKMrlMrLZLPL5PLLZbLfFNC17NptDZDiCcqmEZ1tbGBgYwNzsDMbHx7G+vtHTsjeuey6HfD6P0dFRzMycwtDQEKIbUWQt8qqVyz4xMQ5PXx/29vYgCAIEAJMT47Xrn0WxVMLQ4BAW5k9jcHAA0eimZR7BTLJPTmA/vo9yTblNTkzizJkFDAwE8ejxEzx7Zo1HLdt1n2jcO7uxGNY3NnryWdW6Z/L5PHK5HPr7g5ibnbX8WWWWf3KiIb/H04fhSASzszM9+LxOwO12YTcWA9Dc5rWxEUU+n0ehWERoqFef11bZ50/P4cnaWsNnY3JiwrLntatK++zZMxgIBhEMBpHJZLERjSKTyaBYLGF2dgYHByn4vF7wgoBcLgfO4cDC/Gk8evwYQHWKqFwuo1AodEvEjsnucDhw+vQcHj16jEQigVQ6jdVHjywZBMxc97nTc3jr3r2Go8WDBw8tGQDUZC+VSpg/fRrbOzsol8uoVCoIBPzw+X1IJKpTsltbW8gcZrCyumrJAGBYdp8fiWQS/YEA/AE/drZ3sLS8bIk3sHHZfUgkk3C73Q3ro1Kp9NSzqie7y+XC7u4uUqmUZc+qKflr93ypWML2zi7y+V59XuexvbODSqWCqalJcJwDz2rbu1xOJzafPcNhzz6vrbJvbW1VlxODQfj8Psue164oba/Hg2vXrlW9Awt5XLl8GR6PBxvRaM1jMI9AwI+BYD/24vuYnz+NaHQTQ4OD4AUBe3vxTot0JLILgoB4fB+CIKBYLNpKdgCIx/dRqVQsURp6sudyOQwMDCAUCiG2t4dyuYxiqYTz585hdmYGuWwWqXS6tlxhH9nnZmdwkEphfX3DEu/fdq97JpNBOp3W76gHZc9ms0in0yjWXjrsJn8mm0Uymezt57XmlT80OIhEMonBgQFcvXIFxWJRtLxoI9mvXkEmm8H6+gaSFnnrd0Vp+wMBTEyM47U7d3BwkEIgEEAkEoHH48HOTnXNqFQqIRQO4cmTNfh9fpw4MY3hkWGsPFxBwQKF1zHZLbA0jovshWIRoyPDSCQScLpcuHrlCvL5HO4tLiJWm8qynez3FrEXt+4ltR3ZFxcXEduzbg3VzveM3eVnl30E2zs7mJ2ZwflzZ8HzPB48XLHUd6Bd2evLFVbRtenxw8NDZLNZcByHgYEgVh6uYGFhHnu16VeXy4VwKIRnW1vY29tDbG8PT5+uW2Khkuz2kT00VJWd47jqNP7Dh5a+bLQre55kt0T2XrhnAHvLzzbWDFW3dRWL2IvHsbK6SrK3SVeUdqVSaawPcRyHs2fP4vHjJyiXypiZnUE+X8BwJIJgsB/bOzsQBKFngjKQ7NZgSPbt6hrf4eGhtULXINmtwc6yA/aW3+hYU1+K6AXsLDsAuLrdwUAtzFupVMKTtTVUKhWMDA/D4/HgjTff6ukECSS7NZDs1kCyW4ed5SfZj5auK22vz4vNzU14PB5cuXwZyWQSy/fvd7vbjkCyWwPJbg0ku3XYWX6S/WjputLu6+vDCxcvYmJ8AusbG9jc3Ox2lx2DZLcGkt0aSHbrsLP8JPvRwl1729u76gYXiUQwODiAJ0/WLPW4MwPJbg0kuzWQ7NZhZ/lJ9qOl60qbIAiCIIjOYH10eYIgCIIgmCClTRAEQRA2gZQ2QRAEQdgEUtoEQRAEYRO6vuWLIIjewefz4YMf+E4kEgkAAOdwYD8ex4OHK5qBJKanpxCN9v52GIJ43iFLmyCOGcViETdu3sKNm7dw8+YtuFwuvP1tb9Osc/bMmSOSjiAILcjSJohjDM/zeOveIr7rgx9AMNiPc2fPwd3nhtvlwuazZ1hdfYRr167C5/Ph3S++iFu3b2NycgJzs7MAOBSLBbx+941GTm2CILoLKW2COOYIgoBkMomxsTFsbW8jGo3C4XDguz/8N7G29hT37z/AyPAwbt2+Da/XizMLC3jpW9fB8zzmZmdx5swCFheXrD4NgjgWkNImCAIutxuFQgGRcBizM6fA8zwcDgfcbrekXDgcgtfrxbtffBcAwOFwNDImEQTRfUhpE8Qxx+l0YnBgAHGvDw6nA9+6fgMA8N0f/nBLWZ7nkUgk8e2XXz5qMQmCADmiEcSxhuM4XHrhImKxGDyevkbe4PGxMTidTjgd1SGCq/1NJpIIhYbg8XgAAJMTExgfH7NGeII4hjgnJiZ/zmohCII4GtxuNxbm5zEyMoxTJ0/i9Nwc0oeHeOveInK5PM6fO4eJiQkUCgUUigXMzc7i0ePHmJ6awqlTJ7H29Cmy2SwuX7qE6elpDAwM4MmTJz2Zd5ggnkcoYQhBEARB2ASaHicIgiAIm0BKmyAIgiBsAiltgiAIgrAJpLQJgiAIwiaQ0iYIgiAIm0BKmyAIgiBsAiltgiAIgrAJpLQJgiAIwib8f+As19tAs3mrAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 576x396 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3Yr_sm865iSz"
      },
      "source": [
        "### Backtest function"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4wGSbstJ_FMF"
      },
      "source": [
        "def BackTest(serie, annualiazed_scalar=252):\n",
        "  def drawdown_function(serie):\n",
        "\n",
        "    # We compute Cumsum of the returns\n",
        "    cum = serie.dropna().cumsum() + 1\n",
        "\n",
        "    # We compute max of the cumsum on the period (accumulate max) # (1,3,5,3,1) --> (1,3,5,5,5)\n",
        "    running_max = np.maximum.accumulate(cum)\n",
        "\n",
        "    # We compute drawdown\n",
        "    drawdown = cum/running_max - 1\n",
        "    return drawdown\n",
        "\n",
        "  # Import the benchmark\n",
        "  sp500 = yf.download(\"^GSPC\")[\"Adj Close\"].pct_change(1)\n",
        "  \n",
        "  # Change the name\n",
        "  sp500.name = \"SP500\"\n",
        "\n",
        "  # Concat the returns and the sp500\n",
        "  val = pd.concat((serie,sp500), axis=1).dropna()\n",
        "  # Compute the drawdown\n",
        "  drawdown = drawdown_function(serie)*100\n",
        "  \n",
        "  # Compute max drawdown\n",
        "  max_drawdown = -np.min(drawdown)\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "  # Put a subplots\n",
        "  fig, (cum, dra) = plt.subplots(1,2, figsize=(20,6))\n",
        "  \n",
        "  # Put a Suptitle\n",
        "  fig.suptitle(\"Backtesting\", size=20)\n",
        "\n",
        "  # Returns cumsum chart\n",
        "  cum.plot(serie.cumsum()*100, color=\"#39B3C7\")\n",
        "\n",
        "  # SP500 cumsum chart\n",
        "  cum.plot(val[\"SP500\"].cumsum()*100, color=\"#B85A0F\")\n",
        "\n",
        "  # Put a legend\n",
        "  cum.legend([\"Portfolio\", \"SP500\"])\n",
        "  \n",
        "  # Set individual title\n",
        "  cum.set_title(\"Cumulative Return\", size=13)\n",
        "\n",
        "  cum.set_ylabel(\"Cumulative Return %\", size=11)\n",
        "\n",
        "  # Put the drawdown\n",
        "  dra.fill_between(drawdown.index,0,drawdown, color=\"#C73954\", alpha=0.65)\n",
        "\n",
        "  # Set individual title\n",
        "  dra.set_title(\"Drawdown\", size=13)\n",
        "\n",
        "  dra.set_ylabel(\"drawdown in %\", size=11)\n",
        "\n",
        "  # Plot the graph\n",
        "  plt.show()\n",
        "\n",
        "\n",
        "  # Compute the sortino\n",
        "  sortino = np.sqrt(annualiazed_scalar) * serie.mean()/serie.loc[serie<0].std()\n",
        "\n",
        "  # Compute the beta\n",
        "  beta = np.cov(val[[\"return\", \"SP500\"]].values,rowvar=False)[0][1] / np.var(val[\"SP500\"].values)\n",
        "\n",
        "  # Compute the alpha\n",
        "  alpha = annualiazed_scalar * (serie.mean() - beta*serie.mean())\n",
        "\n",
        "  # Print the statistics\n",
        "  print(f\"Sortino: {np.round(sortino,3)}\")\n",
        "  print(f\"Beta: {np.round(beta,3)}\")\n",
        "  print(f\"Alpha: {np.round(alpha*100,3)} %\")\n",
        "  print(f\"MaxDrawdown: {np.round(max_drawdown,3)} %\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GVgVgP7Lfi1q"
      },
      "source": [
        "### BACKTEST"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 502
        },
        "id": "GLCxo93mHcYG",
        "outputId": "1aa36f4a-9966-4d78-809d-7a9adb49a09d"
      },
      "source": [
        "# Compute the position\n",
        "dfc[\"position\"] = np.sign(dfc[\"prediction\"])\n",
        "\n",
        "# Compute the returns\n",
        "dfc[\"strategy\"] = dfc[\"returns\"] * dfc[\"position\"].shift(1)\n",
        "\n",
        "dfc[\"return\"] = dfc[\"strategy\"]\n",
        "BackTest(dfc[\"return\"].iloc[split:])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x432 with 2 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sortino: 1.472\n",
            "Beta: 1.047\n",
            "Alpha: -1.542 %\n",
            "MaxDrawdown: 25.001 %\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dJWs54jwAy_w"
      },
      "source": [
        "# APPLICATION"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KlIZCzDR_LFS"
      },
      "source": [
        "### FUNCTION"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dDekRv1R5jFx"
      },
      "source": [
        "def svm_reg_trading(symbol):\n",
        "\n",
        "  def feature_engineering(df):\n",
        "    \"\"\" Create new variables\"\"\"\n",
        "    \n",
        "    # We copy the dataframe to avoid interferences in the data\n",
        "    df_copy = df.dropna().copy()\n",
        "    \n",
        "    # Create the returns\n",
        "    df_copy[\"returns\"] = df_copy[\"close\"].pct_change(1)\n",
        "\n",
        "    # Create the SMAs\n",
        "    df_indicators = ta.add_all_ta_features(\n",
        "    df, open=\"open\", high=\"high\", low=\"low\", close=\"close\", volume=\"volume\", fillna=True).shift(1)\n",
        "    \n",
        "    dfc = pd.concat((df_indicators, df_copy), axis=1)\n",
        "\n",
        "    return dfc.dropna()\n",
        "  \n",
        "\n",
        "  # Import the data\n",
        "  df = yf.download(symbol)[[\"Open\", \"High\", \"Low\", \"Adj Close\", \"Volume\"]]\n",
        "\n",
        "  df.columns = [\"open\", \"high\", \"low\", \"close\", \"volume\"]\n",
        "\n",
        "  dfc = feature_engineering(df)\n",
        "\n",
        "  # Percentage train set\n",
        "  split = int(0.80*len(dfc))\n",
        "\n",
        "  # Train set creation\n",
        "  X_train = dfc.iloc[:split,6:dfc.shape[1]-1]\n",
        "  y_train = dfc[[\"returns\"]].iloc[:split]\n",
        "\n",
        "\n",
        "  # Test set creation\n",
        "  X_test = dfc.iloc[split:,6:dfc.shape[1]-1]\n",
        "  y_test = dfc[[\"returns\"]].iloc[split:]\n",
        "\n",
        "\n",
        "  # What you need to remind about this chapter\n",
        "  from sklearn.preprocessing import StandardScaler\n",
        "  sc = StandardScaler()\n",
        "\n",
        "  X_train_sc = sc.fit_transform(X_train)\n",
        "  X_test_sc = sc.transform(X_test)\n",
        "\n",
        "\n",
        "  from sklearn.decomposition import PCA\n",
        "  pca = PCA(n_components=6)\n",
        "  X_train_pca = pca.fit_transform(X_train_sc)\n",
        "  X_test_pca = pca.transform(X_test_sc)\n",
        "\n",
        "  # Import the class\n",
        "  from sklearn.svm import SVR\n",
        "\n",
        "  # Initialize the class\n",
        "  reg = SVR()\n",
        "\n",
        "  # Fit the model\n",
        "  reg.fit(X_train_pca, y_train)\n",
        "\n",
        "  # Create predictions for the whole dataset\n",
        "  X = np.concatenate((X_train_pca, X_test_pca), axis=0)\n",
        "\n",
        "  dfc[\"prediction\"] = reg.predict(X)\n",
        "\n",
        "  # Compute the position\n",
        "  dfc[\"position\"] = np.sign(dfc[\"prediction\"])\n",
        "\n",
        "  # Compute the returns\n",
        "  dfc[\"strategy\"] = dfc[\"returns\"] * dfc[\"position\"].shift(1)\n",
        "\n",
        "  dfc[\"return\"] = dfc[\"strategy\"]\n",
        "  BackTest(dfc[\"return\"].iloc[split:])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "OpCblMBJ6dGp",
        "outputId": "2493daba-398a-41cd-a6a2-0f6f38fa7d89"
      },
      "source": [
        "svm_reg_trading(\"BTC-USD\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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osWN4vV4+fPddTJkyhRkzphMKhpg9ezZXXHkFhw8f4Vvf/AarV68hHA4DcN6sWXz6U59k1QsvcMYZZ3DXhz7EO97+Ni6//HI8bndif9q7fPlydu3aRVV1deK1lpYWZs2cRTAQ5MCBAxQUFHDTTTfy7nfdwpVXXMHkcyeze/dujDHcd++9lJWVsWjRQvbu28fdd30o499v2bKLuPjii5k5YzpHjhzhu9/5NlXVVdx+221ce+0Kxp8xni1bt+b+ABAREZFBqf21TDAYZMuWLVxw/hKKiou4aOlSpk+bxjXXXM3oUaPZ9eabLFu2jA/efhuXLb+MZcuWcerUSWpra/nsZz6Dbdscr6wE4Jvf+DojRoxg586dAPzbv32M4uISGr1ePvqxj3LtihXMmzePUCjE6NGjE9d2V1x+Obfe+gEuu/RSFi9ZTFVVNc3Nzfzg+99j7dq1BIJBxowZw3e+/S2OHjvGiRMnsCyL73/vu2zZspUv/Pd/EQ5HuPmmG7n22hXMnz+P7dt3KBgm0k+pBpLIIHP22WdhjElcACQ7ePAgNTU1Wa1n9uzz+Mc//8m9930Jn8/Hxz/+bzz+h8e570tfJhQOs/SipV1q18yZM7jk4ov5xje/xZe+vJI3d7/J+973XgB+8cuHAPj5L37Jy6+0Dierqanh6NFjzJkzJ/HawoUL2bDhNTweD5/8xD1s2ryJL6+8n29/+ztcfvlypk6dknWbJk+ezKRJE9kTC7Td+M53csYZZ/DA1/6He+/7Ei2+Fm6+6SbC4TCPPPIooVCIlfd/hePHj3e67lmzZvG73/2e/334EQBcLhcTJ0zkG9/8Fl994GvMnz+PyZMnZ91WERERkVS2bNnKjOnTAZg9ezY/ffBBnvjLXxgzZgzvuuVmfvTjn7By5f28+OJq7vjgBwHYtWsX504+F4Bx48Zy6tSpxHWJZVlMPvdcdu7YwQ3vvIHGxka+eO99/PSnDzJr1qzEdufMns3lly/nB//vh6y8/yusWrWKj37kwwDs37+fc2PrmzZ1Kvv3H2DKlOjziRMn0tLSwokTJwBYMH8eP/rxT/jivfdhuVwsW3ZR/v9oItItCiCJDDJlpWU0Njb2eD3Hjh9PBJsqKys5ePAQDV4vxhgqKyupGFHRpfXt2LGTL3zx3sQY/d279zDq9NM7/dyG1zawYMF8AAoKCpg9+zzWrV/P5MmTcbvdrFnzEgCNjY1seO01Fi5YmHZd73rXLaz88pdY+eUv8f3vfZebb76Jhx76FYcPHwZg/vx5/Ov5fxEOhzHG8K9/rWLBgvlYltWlfQWoqqrqEKx79dVXAWhubqauro6KESO6vF4RERGRZM0tzZSWlgLRwE1TUzMA1dXVfOaz/059fT0Au3fvZsiQIZSWlrJz1y6mxAI8U6dOZdu27bjdbkpLS5k0cSJer5dTdXVMmzqVDes3AOD3+9m0aVNiu3PnzuG1jRvxer0AbNwYfe+sM8/ssP7nnn8+EaCaOmUKO3fuSqxn48ZNiWuvY0ePdfkaU0R6j2ogiQwyzc3NDB8+HMuyMMZ0ez1+vz/x2DgOgUDb566CrgVVSktLuOnGmzjnnLPBsigsKMgqMPPaaxu54frrKSsrY8qUyZw4UUN1dTXjx4+nqKiIlV/+UmLZgoICDsRqPqWSXDfghuuv56yzzmLb9u1JbSzlPe95NzeFb4y+YFkEg0HKysq6tK8AzS0tHV5r8fkSj23HweVSDF9ERER6ZsTwEXi90ZuHLUnXHx6Phxuuv54ZM6bjcrtxx647LMviyJEjlJWVUV5ezrSpU/nns88xomIEkydPZvSoUeyIZbKXlZXR4mtdZ1NzU+Lx0KFDqapqLQ0Q3b6P8qFD2blzF3d96EIsy2LSpEn88qGHuP666ygtLWXKlMm8lDSBiS/p+shxbAoK1EUV6a90dooMMgcOHsRxHObNndumYDTArJkzKSouZtOmTTiOg+VqDeDE71x1leMYrKRASLr13HLzzQwbNpyvf+ObBINBZs2cyV13fajT9Tc1NbF33z7mzJ7NzJkzWL8hWgC8oaGelpYWVt7/lW61++//+AdfuX8lixYt5LXXNsbW2cDvfvd7du7a1cmnydnfT0RERKS7PB4PS5Ys5rnnn+esM89s897b3/Y2pk2byvd/8AOampoZO2YMX47deDPG8Obu3UybNpWJEydy6NAhThs5kimTz2X0mDGsWvUCEA3ulBSXJNY5dOjQxGOvt5Hy8vI22xwypAyv18vx48cpKSlm5owZVFVX4TgO+/fvY9rUqZx55pn88qFf5ekvIiL5pNvfIoNMIBDg//7vb7z73e9qUw9o6tQp3Hb7bdi2DUB9fT0TJ0wEoneX5syZ3a3t1dfXM/6M8ViWRUFBAQsXpR5CVlJSQnV1NcFgkJKSEi5ceiEejyeRhROJRNJm+mxYv4G5c+cybfr0RLDn0KHD2LbNwoXR7blcLm65+SamTp2aVbuDwSBP/vWv3HTjjRQVFQGwafNmLr30UtxuNxCtA/XOG26Its+28Xg8FBYWJvY7F38/ERERke4oLx/CnXfeQUtLC6++urbD+yUlxZw8eYqmpmY8Hg+XXHoJAMWx655dO3dx6SWXUFlZieM47N23jylTpjBh/PjERCx79+5j0eJFsfWVsGDBgsT6X9+yhUWLFiaCSEsWLyYcjiRKA7z55m7e8Y63syc20+3evfu47LJLqaysVJFskQFKGUgig9CqF17A29jIO2+4gbKyMiIRm4aGeh765UOJgtHPPvc8H7rzTr5y/0pqampYv+E1Zs6Y3uVtvfTyy0yfPp0HvvoVTp06xaZNm7nqqis7LPePfz7LB2+/jZUrv0x9fT1//OOfGDd2LF/47//mga99jQ0bXuOjH/kwzz33fIfPbtm6lfe+9z3s3rOH5ubouP5IJMJPH/wZ737XLaxYcQ0W0QuV/fv3Z932tWvXcekll3DtihX86c9/5umnn+HGd76T++79IsZEs5/+8PjjABw7doyqqiq+8fX/4aFf/W/O/n4iIiIi2XrXu27huuuuxeOJduM2v/46jz76ayKRSIdlX3hxNXfffRdfuX9l7Jrmj5xxxhl89rOf4Wv/8z/s3LWL2267lb/85UkgenOsuKSEY8eOJWa/feIvf+GOD97O1x74Kg0NXjZt2pQIIm3bto3nnjudz3z6U7hcLpqam3nwZz9LfHbnzp3ceecd/OnPfwZg77593HHHBxPbE5GBx5o3f0H3i6SIiIiIiIiIiMigpyFsIiIiIiIiIiKSkQJIIiIiIiIiIiKSkQJIIiIiIiIiIiKSkQJIIiIiIiIiIiKSkQJIIiIiIiIiIiKSUV4DSOXl5Vxx+XLOOvNMAIqLi1l64QVctPRCFi5YgMsV3fz4M87g4mXLuHjZRUycOCGfTeo1FSNH9nUT8kL7NXAMtn0abPsDg3OfQPs10AzW/ZK3rsF6TA/G/RqM+wSDb78G2/7A4Nwn0H4NJAN1n/IWQHK73Zx33ixqa08mXps+bSoHDx7i5VdepaWlhYkTJ+B2u5k6dQqvrl3Ly6+8yjlnn01BQUG+mtVrPAWevm5CXmi/Bo7Btk+DbX9gcO4TaL8GmsG6X/LWNViP6cG4X4Nxn2Dw7ddg2x8YnPsE2q+BZKDuU94CSI7jsG7degLBQOK1kSNPo/rECQCqT5zg9NNOZ8SI4dQ3NBCJRHAch7q6eioqKvLVLBERERERERER6aK8hb2MMRhj2m7M48ZxHACCwSDFxUUUFRUTCoYSy8Rfz6Ri5MgBEbEbNWZ0XzchL7RfA8dg26fBtj8wOPcJtF8DTX/dr5rqE33dBBERERGJ6bMojGWle6Pzz9adOpXTtuTDqDGjB+WFr/Zr4Bhs+zTY9gcG5z6B9mugGaz7JSIiIiK51auzsEUikUTh7OLiEgKBAIFAgKKi1oyjkuJiAoFAulWIiIiIiIiIiEgv69UAUm3tScaNGwvAuLFjOFFTS319PcNHDMfj8eB2u6moqODUqbrebJaIiIiIiIiIiGSQtyFsw4YNY9bMGZSWluI4DuPGjWXT5teZN28uZ06ahM/v5+jRoxhj2LlzFxdecD7GwO7de4hEIvlqloiIiIiIiIiIdFHeAkher5dXXl3b4fW1a9d1eK2qqoqqqqp8NUVERERERERERHqg/09lNoCMrKjgvvvu5ciRIxQWFuIYw7P/fJYtW7d2+tlzzz2XEyeqaWpq5qorr2TJ+Uv4+c9+Tk1tbYdlb7/tVjZvfh3bcTjttJGsWfNSPnZHRERERERERARQACnnTpw4wfe+/wNGjRlNc2MTX/zCf7Nj507C4XDGzy298AKee/55mpqamTFzBg8//EjK4FGynTt35rLpIiIiIiIiIiIpKYCURz6fD29jI5MmTeTqd1yNx+PGMYbHHvsNGMMdd3yQYDDIi6vXMGfOHMaOHceLq19k4oQJfOD97+fhRx5m5oyZLFy4AIAtW7fy7LPPJdZ/wfnnM27cOP78xBMsv+yytMuJiIiIpDNr5kxGjBgOwLbt22lo8PZxi0RERKQ/GpQBJM9VN+CeMS+n67R3vk7k2Se79JmRFRUMKSvjggsu4JVXX2XTpk3MnzePFSuu4am/PcWECRP4whfvpaWlhWPHjvH7P/yBysoqLrzgAn7/hz8Qidicf8H5fOMb3wTgv/7z82ze/HrH7YwcmXK5kydP9nzHRUREZNAaOXIkZWVlvPTyKwwZMoR5c+fw0suv9HWzREREpB9y9XUDBpvRo0fz2c98mjtvv533vf99PPzIo0yaOIk9e/YAsHvPHiaMnwBAbe1JWlpa0q5rwoQJHDx4EMdxcByH/fsPMH78+G4vJyIikg1r3ESsESP7uhnSC04/7TSqqqsBaG5upqCgEI9nUN5fFBERkR4alFcIkWef7HK2UK4k10CqqT4Re9VgWRYAbrcbYxwAbDuSeWXGYGElnro9bowx3V9OREQkC0Uf+TwAgfs/CY7Tx62RfCoqKqLB25B4HgoFKSoqIhJJfY1SMXIknoL8XD4WO1BqrJTvuQ3Y7d5ymejyNuB3JV332FBx+pict89lwBC9eC6KtTNoGcKpm5x7edqvPjUY9wn6xX65DRQaC7/LJM4fy4BF9L8iY+FzGYodCw/gt0yHcyyhk/2JnxsuOp6n+eI2YAN0d3v94DvKC+1XzrkMOEnHWfK/R/FzyhD998gCQhhC2aTpZNinVP/mpfg4Xnd++vytcYyOBmUAqb85dPgwU6ZMYePGjUyZMpnDR450WMYxBpfL3ea1o0ePsmLFNbhc0SPwrDPP5B//+Cdz58zOajkREZEuKyxMPHTNmIezfVMfNkZ6X+Yr1rpTp/K25QtdQ5jpKkn5XvxGmQU4RC+Ym4zDKqeRmVYJC11FiWWLiooJBgM5b58Va0WNCfOK0wzAcvdQynspoT9f+9WXBuM+Qf/YrxCG406Is1xFFOIihIMbCwdoweGQE2CBq5R9jp8dJsA17uFpO4ad7U+EWMDKsgjTOzexwxg8xsJtWYnfhK7oD99RPmi/8rBtXARpvZlWQPQ4bzI2DcZmjKsAG3jRbiSI4QJXGaOsgs7Xm2afXLHzlE6O64AxPGb3fskaBZB6wd/+9hS33voBLrpoKXYkwmOP/Qa3u22waO/evXz47rt48Gc/T7x2qq6Ol15+mX//7GewLItXXnmVurq6DuvPdjkREZFOFbV24N0zFUAa7ALBAEVFxYnnxcVFBAN9c5HuwyFdbvZex8e5rmKCGIpxYQE7jY8aE2YILs6iKHGp7bFIrMeDRSRHHVrbODRhc9SEqDHR2XV9jk2Jq3cCSPH9cgGDJS8w+bsaTPrDfgWMwykiTKCIRhOm1HITNA7BWMd3k9PCTFcp2xwfJ7HxG4cSK/Wx3Nn+HDNBCnFRaCyGW/nvXrqASidMGMMI3Azrxjb7w3eUD9qv3HIRDbhC6+2VWhNmhOVhm+NjhwnwNmsYIRyOmhAAXmNTkUUAKd0+eYADToCJSTdGUsnVv21dpQBSDp2qq+PrsULWybxeLz/+8U86vJ687NNPP8PTTz8DwPe+/4PE66tXr2H16jVtPvforx/rsK5Uy4mIiHSVVdwaQLIqTuvDlkhvqKmpZdq0qViqSkUAACAASURBVBw+fJhhw4YRCASJ2HaftMVn0m+33tj8y45mG411FeLG4oATBKDahKNDZ5KWN8Z0OzMhnRAGr7E55LQG2PriL1WIi8CgCSFJvthAOFbS4pAJMdMqwYdDwDi0YBPAcMpEOBk7iu0enCtVTvQc9OFwiXtoXo9OA5wyEU4RZrPjY6ZVwiL3kDxuUd7KXECjsRkSC8C6gD2On6Xuck7F/s2qNWECpvWo72kWno1hm+PjLFdxj87LfFEASURERFoVlyYeWiNO78OGSG+or6/H29DAsouWYgy8sW1bn7Wlwdi4iXZ8PbTemXVjUWlC1GMzxYpmS9mYxEW6Dwe/MRRarcPvDpggYykkiMOIHGVERHB4zWmmKal73BdhnP7YoZD+x2AI4GABzSZCvYkQMIYAdiKj4nnbm1i+u9kMHiyOmRAN2AzFHRt+k79jtMqE2G77Cca20hzbR50Vkg8GaMJmCG68xuZfjpcSXLixaIj9K7XbCRBKOgJ7emMhZAx1RPrtb70CSCIiIpLQJgOpqAiGlENzUx+2SPJt5643+7oJADTGLpddgM84FMaG04SMQ0O7LAnHmDZ3eZtMhJGxIQMuYKfjw3ZFs5pGuHNzuRsypk3wKLk9vUm5R5INB2g20bpHfgy1JoIbCOLQFMuc8CZ1dW1julWQOoKhOXZU+nHyfk5UmxDHCSWe15sI7hwOVRVJZgPNxgYLmrHxY4jgEMIQiB1zLe1+lXuagRSMDecOGoeiNMNK+1L/a5GIiIh0mzW8Atf0ud1fQSyAZPy+6PoqollIrjlL8Kx4d4/bJ5JOAEPYGAzRDKI4r2ntGsY7pzZtAymNlo1F9MI2jOEUNq84TfizDLeYLC74Qyle64sAkm0UQpLOOcbQgo0Hi2bjUGVCBDE0G4fqWA2vZN3NmggYJxG8CcfO4XyxgJZ2x7+vF4JW8tZlG5MIEMUDpWEMvgy/wz0NZgZj6+6vQ5UVQBIRERlECj+1ksL33IU1onv1i+IZSE7VUQBcE86KrvfGW/EsWgblw3LTUJEU4tkRB5wg8elG6pLKjEYS/297gX7YCeEYw1ETwu9qHc7ijw1vycQF/NP2UmvCGZcNp7iYz+dQnXRC6ixLFgzRY8Vg8GFz2IQ4ZoLsNgEaU4SLutvp9bfrSOfz+HQDdaZt2eEwhlAeg1by1hbC4DfRf0cak469ugwlvSM9PB6DsXPI30+PawWQREREBhErPiNUcXHmBdOJZyAdPwxAwVXvxH3+pa3rV2FtyaOAcWg0NjWECRiDBZxMumiPZxq07+weMkGqCFNvIrRYre/5Y0VPM2k2NlUmzFN2AzUmnDYbKdWwhL64P6wAkmTDIXqs2BhCGCIYjpnozGWpjqBuB5DanQXBHmbIWUC6frNNx+FC0H8zNWTgi+DQYGwKsdpk7u1y/Gk/E+rh8RgknoHUNxNadEYBJBERkcEiqYiwVVLWvVXEAkj27u1E1r0IQME7bk6876pQYW3JnzpsDpno/df43d6DScPZImkCSAZ4zvZSbyIEkwNIOFid5CDV0topeMluYq3dnPICOVXgprfrrli0di5EMnGInhfhdvXC0unuMLD2AaSeBjhrTRhv7Nxvfx6GjUlkZyQLaFin5EnIGLzYbHf8NCYd60dNqkHNUX46v3GRSWsAqe2x3l+KV/eXdgwal1xyMUuWLMEVu4h/8q9/5dxzzmXx4kU0NDQAFqFQkMd+81u8Xi9fe+Cr1NXXY5zogfK///swDV4vt9x8E2eddRbGwON//COHDx9mxIgR3PHB27FcLhq9Xh5+5FEikfTpcyIi8tZiDatofVJSmn7BTOJFtP0tRP7+J9zTZmMNb12vpQCS5NFLTmvB9iZs3MZqcxGdqLWSIkXBASpNmPFJV+5hTMZhZhZw1GkNIHmxcRtSziTVXzKQsq3rJG9t8eM3mFWFr+4HQ33tM5C6eXxaRDMGX7IbucA1FACvsRlueRLBrXSZRspAknwJE/3NfdnJfjIRXyzztbtHZTDN8d5fev0KIOXQyIoKLlq6lK9/45ucNup0sB0+8IEPsGfPHlateoEXV68G4Pzzl3DttSv4zW9+C8CPf/wTgsHWu2uTJ0/m9FGj+Na3v8OYMWO47dYP8K1vf4drV6zgxdWr2bz5da6//jouvPAC1qx5qU/2VURE+h/rtFGtj0t7loFkAtEi2pGNL1NwxXVENr6MZ+FFCiBJr2nAJtyuT2ub1iLaqfhw2O1pfTcaQEovbAz7TaDDOlIFncIpshx6u9sarcPh4LI0G5tkFj8+sg2u9KSIdrLuDt85bkI8a3sxRINQbmCd08Ry1zDcsRvz6YbHtZ8dUSRXUtW+60y2QdsoQ/vpD+N1xU6aCCFjKLQs3MBxJ8QYV2GX25NrGsKWQ8UlJRQUFODxRONyNbW1fO/73++w3MGDhxh1+qgOr8dNmzqVrVu3AlBdXU1paSnFxcVMmTKZN97YBsAbb2xj2rRpedgLEREZqKzTRrc+6eYQNopiGUiBaKfafuV5gg9+nchTf8CEQqqBJL2mxoQ5mjR8DVqHx2S6qLeTrm5tokEnd9L70ewlQ5Ox2WLa509EL/6dFBlOqYbO9MXU4Y0mgqs7863LW0o8CJqqZlAq3R3C1j4zL/mc6MpR2mJaWxDEIWIMlSZMk2kNbbUf0hNX10kBfJHuymb4Z3uhTm5cJAsYw36n9SaGG6iPHfNHTYgXHS9uollNJ/tJDtKgzEB6x+knOW9oc07Xua1xCH+vzXzRfPz4cQ4dOswDD3yV/fv3s/G1jby+ZUuH5Wafdx6HDh9KPH/fe9/LyJEV7Nu/nyef/CtDhw7lyJEjifebmpsZOnQohUVFiSFrTU1NDBuqmXBERKSVNWJk6+NuDmGzikswkTBEYsN6HAdTfRwA03AKa/jIDJ8WyZ3jKaYaD8RqS3QlcBPBUISL+NxsB02A4Xh40/GxP0Udi2gGhKEoqUvqAlpS5Gj09ixsFtGAgKYtl87Ej5CTTsfzKJXuZCC5yDzMpgAr65pIyYGuACaWCRjNRByOh5Bx0g7fPBYLIOmskFzrTk2vCAbbmERJm6LYeZBqTUEcTpgw59A68UnyLImVJjqhhBcbXz+p9TUoA0h96ZFHH2XMmDEsWbKYq666kosvvpi9+/ayfPllzJ8/D7CoqTnBn/78BAD/97en2LlzBy0tPj760Y8wf968DutMFVG3LMXZRUSkreQaSFkV0Xa7CSy6BGvdGkxtdfS1ktJE9lEHvmY4bXS0WHc/nV5WBrdgbGa2rgSQbAwB41BgWRxxgmxxfBg61m5JFsJQlPTchUVzyiFsfRBAMk6bzolIKvEg4+EMxX6TdSebLl63KNV6LKJZE54sjlML2mQahYyTOD+bYp3pYybUpkZaMj8OLcahxNLgGsmt7pwXhmhANn40BnDwYKUM0oaModaEcWNhYwgb0yZQaogGlHY4PmxMj2or5cqgDCD9vfa0TrOF8sXj8VBdXc3a9ev5v//7G/ev/DIVIyra1EBKtn79+sTjHdt3MO6McXi9XoYOHZp4fdjw4Xi9XoLBIAUFBYTDYYYPH47X29Ar+yQiIgODNXRE65OkAJI1ahzm1Amw216+uCadS2jhxRQtvJjgD76MaajDGjYCU1Odcv3G14LL5YoGmXwtedkHkUwCGCysLiXyW5ZFrRNmglXEZqclqyE9YeOA1TrwzcakrCVj93IcNbrvhgjQ95UwpD+LH5qnsjxbIt24KWBhdcgKine43UC1CTPGKgQMJsMgMzcWtaa1nS04BGKzKcZrLHWWCdJsbAWQJOe6M4QNoudBQeyY9xuHoZaHVDlyQQyN2EmF4jtmKr1oe2nEYQiufhFA0lmWQ0uXXsgH3v/+xPOSkhIsy6KpKXW0vLi4mE984h7c7ugFyuTJk6msrGTnrl2xbCWYMGEC3oYGgsEgb+56k3mxDKV58+ayY+fOPO+RiIgMJNaw4Th1tRjbTgxhc50znaKPfwHP22/quHzS7GquGfOgfBhWQSGmrjbl+o0vOjzcKh2Sh9aLdC4+q1pX7go7xnCSCDYm62K77XM27DTTh/f2UDJDNOupO4Vd5a2lq8dmd47l6LHY9nPxQvcGqIsNu3nObmxTh6y9sHESmUYADSaSCGj5cbDovCPf3SLgMjAVYPVK3atUM35mI5L0G91+2HFyu0M4RGjN5AuYjkdyY2xdPpxutyeXBmUGUl959dW1jBk9hv/6z8/jGINt2/zh8T9y5qRJKZcPBALs2L6D//z85wiHwxw9epTNm18H4PCRI3zuP/4DYxx+9/s/APC3p57ijg/ezrJlF1F3qo61a9f12r6JiEg/5/ZgDRmKc3APVmExxGZhc50zNfr2gqVEnn48umxsCFpyxpJr1FhMbIa1dAGkRNZRdwt0i/RQOHZ3tisBJD+GZmMTMh07u+m0n0kqnOKucPz13mRixVl7e7sy8HT1CAnGcoS68jmHjudiPFMoYgxVJkS55abShAhnGHbpb1d02IfDyVgNtKbYlOidB5B0TryVhGPDufL9rXd3VsGgMZTHDvcWYxPBk5hNcLvtY6orOmFJ/MaEL5ZBl65QPETPtyCG4j4uGa8AUg4ZY/jzE9HaRqPGjKam+gQA27dvT/uZVS+8wKoXXujw+pNP/rXDa42Njfy/H/4oR60VEZHBxBo6PPrAW48ZMrS1iLYrdt83NnzNc/UtuM6dQehX34Vhw1s/P2psYoa19BlI0QCSVVqmS3XpE3asOGlXhttUmxBeYxOxsu8IBNt1GtINnwnHOt0hHEpw5X2OnGgGUuyuuEogSQZd7fb6Y4GarmTy2MZ0OOaDsUL3QaDKhHEcg020jsvwNF3PYLs6SgEMu020Fp8POzp0s5MCwrkKIKkY98DgMzblVqa8tp5zQdrC7Z1J/lwwlqnnxsIFVBJiGG7OpSTxb40Ph5FZbC+EQ3EfDyLTEDYREZFBwBoWzSYy3nrwt0SzhFwuKIqVArajl/meJZfgGnk6Bdd/IJGB5NRWY50+Buu00dHnnQ1hK9MQNukbhvgsadlf1O90/DRidyno1H7eqlCazmvQRDsFe+wgvRHRiQ9h605hV3lr6Wq3N4jT5UFBqY5Dv2kNqoYwHI1lEjWkGJrTuu2O64lnHAVjw1Z9vZiBpA5y/9do7Lz/4rqwuj3zWUu7AFI8k8kC6o3NESeEZVr/bWkguj/VKWYfTdYfhrDp/BARERkE4sEf01iPOVWL5XZjjTitdZiaY4On9e6ve+os3OdOxwr4MMcPYxUU4po8M7oODWGTfqyaMPtMMOvlW4hO/51paEB7gXZ5GOnmsQrj4AEOEei1Gdk0hE2y0dXjMZQIz2YvVQApHohqn7XXlCG3KdMwofix3pIhAAW5CyCdMpF+M126pOfFJv9B+9S177LhTwoYBYxDKBb4CRuDD4e9JkDI1VqXb4vTwikTYY9JMwtuTL6zXLOhAJKIiMgA5po2G2vcRNwXLsfYNs7+N3FqqwDwXPJ23OdOjy5YVIw1chQApqEu8XmruQnn2KHoukaNxampgubUkz+0FtFWAEn6zrO2t8uX9A5wopM7u8majNOma5KuaHWY6JAfr7F7pax1tIuffS0neevq6vFot6tDlI1UAaQIseLa7TIlMgWJOssojBDtdGeSqyLaAeNQ2yEHUfoTN137Pe+uCJ3P/pdOo7FxAU3GpiWWjQfRwFJ8KPKOQpuG2OyDEeCvdn2n6+0Pv/2qgSQiIjJQeTwUvvfDiaeRDWsw9acwNdEAknvO4sR7lqcA14SzosutfxH3nCW4xpwBHg/2pldwz1qANfHs1kLbqcQzkDQLmwxA2x1/1svWmQhurEQHOV0HN4IhGO8cGBMtUJ9PJlpPpj90IqR/62oGkk3Xa/+kGhYaLzjf/pzJNIS0s056OM0siMlyFUDy49BiHCaoxli/ZYgOiUw9tUHuOF2YeKG9kyZMi3HY7wRoMBHCViyAlJTdtr/AScywlq3+MAOnAkgiIiIDVVFxm6f2uhcBollEKbjOnAyAqa0m9JufUvjuuyjetw2f4xD69Y+xho1IP3wNMP5oAMkz/wLMsYPYm17NwU6I9I6uFENtbjftcrp73TYGv4nPDJf/C+v4ICMFkKQzXe1mOt3ojqcaThOJFbpvf4yGMszy1mkAKYusu1wNYfPjtJmCXfof25hEJk8+9WS4WDMOVSbEZuMDWgOq3S3KHdcffvs1hE1ERGSAsopK2jw3p2qiD7ytadD2wT04lUcBcE2a3Lpck5fQQ9+l8M2tsQUjGYNHAARaMzjc8y7oYetF+q8IhkDSneJ0w2/sWAZS/HG+xVvRHzoR0r+ZLhbbdbrxmXTF3G06BoX8OGkr1gQ6qTmUTac7V+dfwDgE+0GhYkkvQvQ3MN9hvp4EEh3gVac58by1KHzPWq0aSCIiItJ9SRlIwZ9/q81b4b/+NvrfIz/E3vgSANbQYQAYb0O3Nxn686PRB7rAlkEukHShH0pzvNtEpxmPP863eIs6m9JcpKtHSLwuS1ekCyClqlnkNw6uFCEkF5kLbEN0SGlncpGPYgGN2Phw1Enux4KJDNH8Xof0NFCf/PlgIoDUs3X2hxk4dW6IiIgMUFYsgBR54RlM5ZE279mb12JvXgu0LZptmhrB7v49LOeN1zDNjaBC2jLI+WNBIxdQn6YDa4BaJ/peb2Qgxbfgjw0HEkmnOwGVXAWQLAtOOm0HfgYxKQfJubBo7GSGtUqTbh7EpLZ0YXcN0ORqu7fuWFvqTYTmWAFk6Z9CxsEBnDz/5Gaq29VV8Sy7ngaQ+kMNJJ0bIiIiA1UsgGSCmad9NfUnWx83dj7LR2eM34dVUtrj9Yj0Z4GkrIj6DBkSe2PTLvfGneF4UMBnWjMkChVKkhS6083satAp7TFvoKbdYJtIiiFH8SM30Ml2D2URQOpKADdoHPYXtG2NC4uwcWjGIZD38szSE/GjId/fUS7neas3Nh6ix15PtJ/dsC8ogCQiIjJQxYewBTPPLmWSaiKZxu4PX0vwtUBJWf5nnBLpQydMBIvoBXumGiwt8RpIaS7s3TlsU3wLzdhYse53k7IlJIXuBDS72rVNN8THh5OyiHb7GksGw58jp3JS0yvUhaw8G0O9yyTOTYvosKhmbByiNc96Y0iqdE+8Jl2+c3Fyme3ThJ1Vtl1nAv0g+7TXZ2Fzu93Mnz+PgoIC3C4Xb+7eQzAYZM7s8zBAY2Mjb7yxrbebJSIiMuBYxdEi2p1lIGG3XrAkB5O6y/h9uFyuaAArkP3U6CIDyV4TYDFlHWq5pJOqW+AGbAO5uuKPZ4i04OA3DgWWxQkTZpJVlJsNyKBg0b1iu13NQPKlyaY4boIdXovOHggFSa81G4e6HIVqQrEi3dnsgYOhyWWwAQ9W9LmxaYntT4To8CWPbpL0S/GAY/R4zd93lMus0gAODobGHh7vLbHs074McPZ6AGnihAk0Nzeza9ebFBcVceGFFxIIBti2fTsNDV4WzJ/HqFGjqKmp6e2miYiIDCyJDKROAkhJjK+584U6W4e/BQCrpAyjAJIMUmEMtSaS9TiJVENoXFj4LJuiHOUIxbvrBmg0EUZaBTTj0Gxsyqxc5jrJQBYNIHU9e6Irn3CRvrj1Nif1vwsRDAVJHf6eZmMkC5rsMzMiQNiKDieyLBcuwGvsNsHiMIZSXB1mk5O+F68jlO8gij+H370BAsa0mZyhO/yJ7NO+Oy57PeM1FApRWFAIQEFhAeFwiLLSUhoavABUnzjB6aef1tvNEhERGXDiRbRNIPsAUk6GncUCSCqkLYPdESdIwMrugj/V3WobQ0sOO8nJnYb4newgTk474jLwWXStqHRcVzOQ6tPkOaUrFNz+HOlpNkb7baaa5S0Vx8QDEIYqE8KFxUkTSWQgQXT4Um8Uxpeuiw9hy3elqtz+dkezkLo/hUlUKFaMvi+HLfd6BtLxykomTJzA5Zcvp7CggHXrNzB79nmJ94PBEMVFmdNwK0aOxFPQ603vslFjRvd1E/JC+zVwDLZ9Gmz7A4Nzn0D71Vv8I0YQBirKy3B30rbg+lUElyxn+MnKDst2db+CbosgUPThz1H611/jqTzcxZZnp6b6RF7WK5KtXcZPiZPdpXqqzqYBmoxDRc6GsLXyxjrfAePQaNmM7cJ6irB6PBuQ9F8W3avf4nRhRFDQmE6LX7fXPoDkTZPB1B02JusAWDwscNAEKcOFYxmOmlCsAlKUhUWDsSlXZl+/4gJCJj6ELX/cEM1AzaGmHARMQxg22y3Mc/fdDbxej8KMH38Gfp+fdevWM3ToUBYvWkg40vrlZPObVXfqVP4amCOjxowelBe+2q+BY7Dt02DbHxic+wTar95UYEeLgJ46fgw6K479zBPwr2cItBvu1p39ctfUJOpYNNQ34PSzv4tIrkSADaYly2VTZCCZnte8SJY8bXWNE6bQZdGEjcd0LUKl0FHf8GD1ymx9Fla3jrquZCD5u7GFiDGJzp6L3HSoE+tOMctbOvFg7wanhYtd5RjAh90mIBbB0IJNeU7L4EtPuIBX7CaOxmbl62rGXFc4QF2P84XaOuZ0PptgZwywxfiYbfpuJtxeDyBVVFRQU1sLRAtmu93uaCHOmOKSYgKBjoXXREREpJ2u1kDqQq2kTIyvtUPtHD2Qk3WKDHSpOq820JzDYRDJQzaqCBPB0GhsQkSDydluqTeCGNI3PLEKKfmehc3XjenEk7vjFtEsplyxuzCgKXk/459rHyo4bkIMxZ3PGs3SRQ6w3wSTimjnj990nEmwp3aY3NSMdOjbItq9PnyupaWFESOGA1BSUkIkEqGpqZmKigoAxo4ZqwLaIiIi2YgHkEK9feMl6aIqkts7dCIDVaoL+mgh7nDO7tg67R43Ghs/hlNECMc64y6sTmvBhEzf1tB4q/IbJ+/xiGjdLadbneuufKZbGUhJW3BhdXkIXOZ1g8kyIGW3yTSK1kRqPwR1i+NTDaR+psnYbYI6Tg4DkO3lMvAfl8vW9uVNgF7PQDp06DDz5s5l6YUXYrkstr7xBsFAkDlzZoNlUV9fT+3Jk73dLBERkQHHKirGBAOQx4uoVJyDe3Fqqoi88HSvblekP0t1QR/BoREnZ3eL22+h0oQT240Ot/EQNk6n04/7cCjS0Jxed5Iw4ynMa/aAbQx1hLs1vKcrn+lOdkbySEuHjkGbnrLJrnObvF07NvStfUvCeS/RLF3VfrKAfGQguWPrre/THJ/ORTB4+ig9rtcDSLZts3HTpg6vv/zKq73dFBERkQHHvXApBde+l8jr63CNm9hmOFmv8bcQ+snXen+7Iv1Yqs5w2BjCGILGUJiDGRDbd5jWO82Jx8dNmGmWBy82w40bV4bt+XGowIOqIfWuJmMTxHQa4OuJMIajTqibNZC6tp2uOuQEsS3DWa5iHHKfRWFjKIwN4cu0/+0DSOmW1dnRe7KZmL79rH/5CCD5jUMhLipNz+sV5VO4DwNIyl4VEREZQAqufS8AnnnnA+BUHunL5ohITKRdJqCH1k5sd4b7pNK+w5TcAX/NaSFoHBpNpNOtBYyj/Io+EAGa85zZEMKww/i7FeDpSgZSdwYv7zfBxOx/Tiy4mksRDP4shu+1qYGUYvha4j2dI3nlIj6rmsMuJ3N9IBdw0Gk7XD8fASQbqCXMEdO/azK3//emNymAJCIiMoAYvy/x2Dmyn/BvftqHrRGRuCrTOmzIBdQl1evw5+hiP1PQJ4Jht/HTTOfFXwN0r0aO9EwYB5/J718+0s36R9C1Drndza2EYsem6eL2slFHhHps7E7Ot+Tgl51hKJ3CR/nXYhwqCdGSNDzNgg5D832W4WSHDKTcf0M2hudsb47nX8u9vqyBpACSiIjIAGJ8rUNWnOOHe73+kYikdooIe53oTIdeY1NrwomOaa4ykDo727c4PvY4fsKddM0DeZ0AW9KJGJP3jl9PBt5kOipctJ2QrLsZEKFYAC0feViVTohGE+k0gJocMApj0u63gqz55QC1JswRJ0Qg9tf2YOECNjgtNCUFlRpcHb+jbH/FulLtzWASWXL9Wa6z97pCASQREZGBxGm9pDU1VX3YEBFpr85E71vXmjB+nESwwJ+ji/3OhtTYgBen08693zh5ncFIUgvnoXB0e6EehD0yfdIA7lgIyYJuz6AWjG0lH4G0PSbIQSfYaec6OZMvU8BNZ0h+2cawyWnmoAnSbBzcRI8tC4sjJsg6pykRrAhZqQJI6SUHjTqblbJNm7Jesm8pA0lERESyYpWVJx47p2r7sCUi0l6NCeMhWufGZ1oDSD5jJ+6w94Zwmtc9WLhMdBa2gdJRGiziQZd8Zw70ZP2ZMjps05qpYxENQnZHUyxQkI9AWgRDJeFO/wbJw5Oi9cBSBxiUp5dfEQwNseG0Tdi4sIjEgqxhDM3GSQR/Qim+okxDer2m9QhrMdn/2g2UwLoCSCIiItI5lwurtAwA5+QJjApoi/QrjbHAjNfYeIkkOj87jJ/nIg2JDI7OWKSeKjnbDm26IWwGgw+HZmOrQHAvcxGt95LvwF3PAkjpRTCJ2kIuLHzdDIg2Y2Nh5fX4S5WBFy/WDLSpkRTNiNIQtr6QfAwEMRgMXhPBMYYQBj9OYplwFzOQmozNCRPGDZww6ULqqdo0MIQxiWy+3qYAkoiIyEBREg0e2Ts2E/rRVyHcv6eZFXmrid89rzZh6oydCPg4wEnsrO+Eu4BAik5wtt2FdHenHaLFvgO9MJRK2rKwCCR1iPMlXwGkECaRuWMwiWLYXRWMHXudFbruiXR/g385XlykqoGUjs6RfEr+nQphMFjUG5sI0WMxlHScpAoBZTqXfDhUm+iAzmMmlPUgtoESNIxgaOhCZlUuKYAkIiLSj7lmL8I1fQ4AVtkQAExLc6aPiEgfajEOzTj4cag3befyqctibp9CLELGpJzuPdvubLoOtGMMYyAn4gAAIABJREFUG53m2BA2dY57k4Mh1O8DSJln+QslBUS7u514UCCfXd9UbQsaQ7WJEG5XyDySIYA0ULJRBqr2mWJh49BM6+yVhuh3aQGBFBlImY5APw6HnGg57GMmlHXQI9OwuP4kYgwNfTRXnAJIIiIi/VjhTbdT+J67AXCdNSX6ok8BJJH+6qiJZgYaYJcJtHnvDdvXaeZF0Di0YKfJQMquc5OuW+EAzbG15DMDRDqKB13aB5AKulDgNxvhbtYmgswBk2jgpXUIWE8CVcnZTPmQKgMvnv0XaJc9Fc12Sb0vAyWYMFC1P95acAjSepxB9FhxA00pohaZjnS/cajHptFEaMEhnOXv3UAJGoYxnHCyH5qXSwogiYiIDACuc2dQcPUtgDKQRPqzTU5L4nH7LksVYSpN5qGnXmx8OAR6kIEUSdO1irTrOGfi66PhEYNVPOsm0u5LtGL/5YIF+HoU9Ej92QJiGUixTnhPgz8hnLwWqE41vC6e0RfCIWjaZiClO9IdxY/yqn0QshGbiGkb7AmZ6JGSKgMpXTafi9YZMTc6LRiiGUnZGCiF04+aEFVpp0vILwWQRERE+quCgsRD98KlicdGs6+J9FudzY7TWeZGlQnjmNTTpGfbcU+3jeQOV6bw0EEnwC7Hn+XWJBvx76R9pzds0s0B1nXxQt3dle6YMCba/vixnS5Ama1Au2FkuZbq+G+OtTmEQ6hd+9MFSwdKPZyBqv0xcNwJ4cPgJJ0QIQwRY9LMwpZefexoPhwL2Gc7dHSgfOfNsdnr+kKqCR5ERESkPygqTjx0x+ogBX/5Xcyxg33VIhHpoUzFhy2gxoSpI0yZ5e7wfradoFCa4RrJHet0d9odY1jvNFOOBw/RoFX8/9J98e8uEKvpEv/rO5bBk6MQkoWFvweDcBwMRVgE2x0bttW2s9+T4WsAPuy8DhVKFZyKB42CseF3yZ3gpjQBJA1hyw03qYOT7b+nXcbPae3CE/Hhjk6KUyRdAMUxhkC7d21DVql+qg3XOWUgiYiI9FNWUUmb587JEwoeiQxw8c53qr6MC2g2DntMEL9xcLVbKtvOjQ8n5UV+pN3QnVSasPFjOEmYkDGJNnVHdNp0dcig9e8dMG2/mwjRwE8u2D2YHQ2iQ7baf94CQlY0Yyh+7LYvftxVLXkuJh5JcbzGAxh1JtIhmNGcJhQxULJR+ruIMbhTHOPtf4Mcor9dTtLxFcRJO119uiB4hI6/OtkOTRsoQ9j6kgJIIiIi/VVSBhKAc+RAHzVEBrqRI0fy9rddxejRoxKvDR06lGUXLeWii5Yye/Z5fdi6t5Z4JzxV8eTkDJJ6Y3PUBNvcj8+28PUJk7o2RnI3LF0H3hfrfDtEg0kWsMPxdavTsN3x09SDIVWDSfyvHcRpEzDKtrhvVtswPQsgGQzNxm7zXUdnwIoetyEMIePQ0MP8IZ/J7/AbPx2HBcbPnUoT6pBBdcQEU64nn8Ps3kpCGAIZgnrJghjCSV9eGJM2gJTu9zBVhly2x5t+rTqnAJKISHe4XHiWX4N12ui+bokMYlZSAMk5dojIC0/3YWtkoCotLeWcs8+mrq6uzeuzZs1k2/btvPzyKxR4PIwaNSrNGiSXwrEMlFRFXZ2kLI8ThFltN7Z2skz2GUjBWCCgveQOsR2b3ag9X1K7moxNyBh2mVQVmTJzY3HYBHtUk2cwiXd2o99v2+Fgucp6CNOzfC8baEgRQPJb0eMyjOGQCbHGaepRO0+aSF7rqDSbjhl48aPwBJEOAYZ0R7dN7gqcv5XZgNd0HASbKkAXxtCYtGylE2aV3ZhyvTUmkvI3LJzit/X/Z+/NgyRJ0/LO3+dxR56Vd2XdR1f1fXdPd83FzDADmgGJAcEINCxIixYZEmCCxVaSmWB3kVa2ErZIxq6kFQsyMKQRh5CYhhHDMHffR1Vf013VXd11Z+V9xu3h37d/eHhcGZFxZETGke/PrLvi8PD4wt0j0r/Hn/d565U85deqNiIgCYIgNIE6dBz/R/8KoZ/9J4T+4b9AjcvES2gDOQHJ/ov/SuY3fw021zs8IKEXSafTvPjSS9h24aRcKcVANMr6+gYA8wsLTE5OdGqI+4oEbjnHek7g8VE4IXfKHCTpos5X3v162awhIFkobpoMFqWdwOJFU6gNHFJoVzxo0CmTNpoNHOI90xi7vXhbtbzrl93CopndZhPZGDbLZBNPQMoagzaGyzq1u0ECa2Sx22juSeBsKwtsZis7FZxMQuM4+eNq++OVuF3koLxJpmqJ4TJ2xXLKSr9V9ZewCbUQAUkQBKEJVHSgcDsSxTp2qoOjEfoWLwMpEd95OUHYAcfZfuIeCgbJ2IWT9HQ6QzgU2sth7Vtixp02eVfZE0Vtq7Nsn8B4JW0WVC3lqESlMqPiCdsVk+bLzgZx45Aymo2c4BQvEp42jJN3Z5SH0tZi07hylQhILsUCUvFU1saUZL40i6Ky86IRbAxzJl0y2VYotiw3A+ktk2ShBa3D0xjmqFw21grSbO/y1kzm0m6zngQXB8O7OrUtrLza9r2e65xWiyxuflV5vlKlwP/6u7DJPq+FdGETBEFohnAUAJNOo0IhcSAJbUGFXQeSSe/+iq+wPzh69CjHjh4teezipUssLS3t+Lp6r7KPjY/jD3T/6ePUTPeWF0c1BBJBfAEfYduPbRnSGMYcCyzD1EDp2K2kn7BjoQwMjI8z5a9vguPLWITT/pKdG/UHmMr9/UoBk8CbWcWUVgw7FgNZCx31MeVz3yPtQDTtZyoaxJ8IEK7UCqkK2hdgKhLCshXhVKDqQRYOhys/0eOUf66wL8hUJAQGgvFAPiA97AsSctS2wPRGCQBJn2EqEmx6HUaDUe74vB3mA9Ytm9D4KCN1Hnv1kALaduZUto2VgaGwj6lA6fhr/U6MZhWRZACnx2xI3fadCluGbDTIatpi0s79/TAwEPYxFRiuez2V9pcvEWBL5X4/c4S871oRA7nf0VoMBvxMhQbrHtNu6da/VYvzC1Wf6/4zAEEQhC5ERd0T8OyX/5jAX/1REZCE9uBlIImAJNTJ9evXuX79es3l0pkMwUBhohmOhEmlajsCVldWdjW+vWBqZnrHk99OE0Cx4RtnMR7nqG+QdW1zkwzHVQg/isWt0qyqZWuIQSvMYCjM3PJSxVKQSgRVgLO+0RJPyppOsrgeK1luMffvB6xBhlSI9+IrJe8wbQ2yuBljzRohbNUvTizqJIsbMTZR3OuvXB4ZDodJpfrv963S54rpDIsbbslo3DdBQLmqxLpOMahC+fvNYgPr2mZxY/elznHfBD5VEJA2oxY3Fhd6qrxn0zdOWLmCgQUsJtZZLCqNqud3IouPtH+soqOlW+nG79SWtlncXGdehTnmGwJceXI+sclilQDzcqrtr28Q4IgVJGpFUbjZa+s6yeJGaU7XhjXEmFVbWFtLxFnUibrGtFu6/W9VNaSETRAEoQmU50BaWcQkExKmLbQFL0RbHEhCqzHGEIvFGBsbA+DgzEEWFxdrvEpoBW43K80W2u1wheZVneCCjpcVN7mkMRgMWjXWFWrVONs8LTtl5GyYLPNsb3H+io7lxtGYfODkS98Mi8be95OO4hKa4v2oaU3ZTNLoXZeweZSPz1G9lw1jl5Th0VTmUha2ZSkJjeP9piwbJx967YOKQf+NsoBNJhfU78PNv9pVFzYpW6yJOJAEQRCaIZITkJJxzMoiauYwWBboXjvFEroacSAJLWB6aorTp08xODjI6OgIJ0+c5Lnnn+fNN9/kgQfuB6VYW1tjaXm500PdN8TQrJksPlR+snPL2DxaYdnLOoWN4THCDYUkJ9BkjMk7SWDnHJBbJoOttz/vuS8aCfAGSsSwKzpFXGlOWPs3Z6tYJCreD3ZZqHazxNA0UGG4I+Xj6cUzm4zRoFy5otl8KF1R0hUaxTveN8iW7IVKnSibIZET4zPGsIneVQaSJLbVRgQkQRCEJlB5ASmBWV7AOnwcdWACsyJX8IXWIQ4koRUsLC6yUMFdtBWL8fQzz3ZgRMKCzhDHwTY6L8xkMSxWaHW9SJYpE0DTmAMJ3InVUFGj650mR1totnYoJ2lUQCp+r7dMCgWcYD8LSAWccodPC2SKJWMzULGpeeO403zXM6aN6UkBqTjqW6Gaiv42IBJSC/COb6+rZEApslDScXI3bBqNBWzikDROxd/Juh1Isr9rst/dpIIgCM2RE5BIJtA3rwBgnTzTwQEJfYk4kAShL3nXpMgCWzglpWEv68odFxNoQDU8tUmZ0mnTbrpKpU1jMkL5RKxVk8VepVgkcor2QxbTkknrltFstiitp/g4MfSoA6lo1O5naHwb69xrhcYJUNn5mMhJy9qYhhyVOxHD6yCpSVC5lLPeY7gVYm6/IwKSIAhCE6hwFJPNgp1Bv/sWANbpezo8KqHf8BxIZNrX7lgQhL1nKzed2cDJ53dA9ZKOzSazQpJKs2pstnJ5SIldSAHxXJlIvZRXw6Ux+3ri4VS5rTElglKzZNG8pZO7Xg+Uj4/62zR2EXaJy6u5MkEpYWseXeay80jmfu9aJR6BmyOXNYYYDkk0doXvU7EwFK7yS6SgpwLTO8V+/h0XBKEf8bXGvl2TyAAk3S4NZn0VvTSPdeKMm4Mk7AvUkZMQbHM5RjiKSSZAQh0FoS+JGU2sDlEnjkarxn8Hruo0f+as50Osi7tQNYqX2VQv5Y6PlGlMgOo3ivdy8ZZxzO4zkBSuw2urRV6h4hKgXv3rk6HcRdX4J5E8nOZJFgnjxeJNKneMttKR6Jb3wjoOCaNJVVh3sRSYqSKGN5uVtd+QmY4gCH2DdfY+wr/8r7HuaL8TSEUimFShzadZvI0KhSDXnU3ob6yz9xH6qV8g8Jkfaev7qIEhTDxWe0FBEHqSeWOzUYe7KI1uajL7nkmTBeI4pIwhvovJUaxKd6NqlL9TCrOvO1oVT2BL3Ui7zxhyBaTWTXyzJWPtTQmp/Fht1oEkXbmaY6Noixe7ejxxJ9tgSWwtHAwXdYolYxOvsO7i/Z/MZSaV4wZxt3RYfYkISIIg9A3+Jz/u/vuR72nfmyiF/wc+jxoYyjuQoBBynC85ahbLwvf4RyAc2d16hLbiu9/tlWSdaGPulVIQHYDEVvveQxCEjnLVpFmvY2qrAXsX2suGcfJX/pslS/05SO6V/NKZmI3BYAjuUxGpeC8Xi0luF7bdzVoVkG7hxLcfHEjF+V/GNLeNDb37+TvNvLbzke6VHEjNeyEr86pOYGNYxWGxwtqLhcAtnIpitjiQ6kMEJEEQ+gaTzIWPRtrnAvI9cg7/Q08AoIZGCk94Ice7FJB89z9O4DM/QvDH/96u1iO0FzV7FAB9+0b73iQcRfl84kASBAGA3SShLRi74Q5ulUjuQkDK5nJoWjGOXkRXcPUo3Gyo3QtIqqUOJKcPHEg3TTovYDQbht2bn7zzKGCFLGu57LXiY78dGUgAb5tC/lelNRcLuHFTOd1KoSQDqQ5EQBIEoW8wOUeQigy07T18OZeTSSXJvvDNwhNp9w+X2qVzSI2NA2AdPi4upG7FsrDGJt3bmUzb3kYNDAKIgCQIAgBb1m7KzzRrZvdTo2oh35Uo7/iWxWCMqVhesh+oFCpsAWmz+xI2MC0V5oqPlF4VUTbQ+WNtN1lG+/No3R0WkDCa/+KskinL+Fo3Dj723ulT/P2L4VTsSKlbIObuB0RAEgShb1BegPUuHUhqbBI1PrX9CZ8fNTaJvnqZ9D//JZznvpZ/yrTIgVT8vtbJO3e1LqE9qJGxwp1AoH1vlBOQiEsJmyAIsOZrfmJjgFd0fNdjqFdAcrsZlY7X4AoTi6ZQ2rKfcIo2h847kFQu32p3k1Y3RLh1E9900X7u5Qn1ei5frJkAbQ/vlfuz8LI5vOMa3JI1p6x8DFrvQKqFXeaCqiQqumHrQi1EQBIEoX/IOXaUz+fmxzSBmjpI6Od/heBP/Kx7//DxvEigxiZQloVeXtj+wlYJSJMHC7dHRne1LqE9qJEDhTuBYPveJzoEgEmIA0kQBLjm293Upp5ub7VI1C0gqYpdlhwMS8auePW/3zEVHEheqd9uRRpPnGsV67nSI3Dzg3qV9dxW2c2RrzFs1RF0LxQwmPz3P2V0ibiZRJM1puUZSLWwMSjc71wcXVFwNey9sNWLiIAkCEL/UCzeFOcT1YGamCbww3+L4E/9ont/5AD+j32G0N/5n/F/5Htzy8wAYFa2C0gm1UCItlL4HnyC1Ac/VWgDP3IAhkdR45OFxRr8DMIeUSQgKX/7HEhqMFfCFhMHkiAIkO2Cs/Z6M5CgsnPF4ApZu+kG16tU6mymcx3Ydjtl1U2GRFdj3tj5SWIv76lYCxxIFoqXdEy6sTWApiDEpFWpWKNxc79amdlVD7ZxBSQfsG6yFYUix7S2FLRf8Xd6AIIgCK1ChQula2pkDKMUGAOb6zVf63vsw/jufQQAY2dQgSD+7/or7nMPPUH2q0+hJtzyMrO8uH0FuQykenKLrFN3Evjs58kAviuXcc4/R/gXfjX/vPP+JXwnz6IGh2uuS9h79sqBRDRXwiYOJEEQuoR1sljUFhUMpmKJiFKwZRzWyDK4jwrZXKdRAV1yu/K2aoRWiFDFJNCkjCGgVE8LSGt1Hq+1uGFcuWP/HLG7QxcJMbYx29yIy8bmHZ3a0zF5DiSNe3zbRoMq3aPiM6uPLriWIQiC0CLCBfePig4Q/oVfJfyL/7Sul1q5rlqpf/5LZL/+pZLn1NAIvo9+L4Hv/qsAmOX5ba/3MpDqciANDBXe9/TdqEPHSp7Wl95wb4gDqStRw8UCUhsdSLnjxEgGkiAIXcJaUWnTTrhZIhVCao0hiWa5BYHevUR5e3DvltcmfrfuoXZMfLdy+6iXJ9UrLXAgrZFtecZUv5OlIGhmMGTK3Ftf0Zt77kJ0BSSFxmBTuYROytfqoyMOpMOHDnH69CmMMVy8eImNzU0eefghlFKkUmnOX7iA1r2sdwuC0AlKHEheADHgO/cJzNYG+uJrYFf4k2FZqIOH0bdvQiqJWV3OP+Vcfhvf6bsIfPz7ALecyKyvbl9HAxlIxSKT756H8N3zUMnz+v13MLEt14X0U79I5rd/HeQ3sWvwsqlMMtFeASknIIqAJAhCt5BEkzEGX42cQU1l4cHBDWi+qtM8YrWvY2q3oQC7aG7qCUaueLQ7gaN4fa0kpjRjlGY39RpJtNvlbhcf4W3tOsx7OUx8ryneVpvGKQll7xSeAKiN+53z7hc71JwuGGcvsOcOpEAgwNmzZ3j66Wd4/oUXmZmZ4a47z3LlylWefuZZ4vE4R48e2ethCYLQDxQJM2pqNn878D2fJfjXfxL/hz5V8WVqcgYVCKLnrgNg1pbyzzkXns/fNo5D+tf+cUUxpyEHUo1lzNJtTGwDAOvIiRLHktBZ1OgYvjP3YlJJTGwT5W9fCZs1exQT2wTJQBIEoUsw1NuJrXImTxZDFljHIZHLU/Lvg/5WCkoyX0z+X4PGkN5lvk47xI2XnRgZo3t+Sh3H2ZVA975JA+JAqhc/qmRbLZpsxUD9vcYTaj1h2/s+Fv/62JJzVRd7LiBNTk6ytLRM1nFIp9O89vrrjI9PML/ghtLOLywwOTFZYy2CIAhlBIMonw+Tcq8UqZlD2xax7nqg4kvVzGEAzO0b7r9FDiQzf7OwYGzTzVSqRO59CdXOQFJecHZ2u4VfX73svkeRMKF8ElfXDRgg8ON/370d34Ks3T4H0uAwanQMffNae9YvCILQJPUEaWtTOXemuGwlmSsvcjB9n6mhUCVd0vIOJOP+bfGypdxlG6cdAtIGmgVj97zzJtEiEczp7c2wpxQfM4vYXRGar3NeOm9sNgYfcFsXKhP2V2Ft8+z5rCQajeDz+Xj88ccIBgJcvPQOfr8vX7KWTqcJh0M7rmNsfBx/oPsnVFMz050eQluQz9U79Ntn2unzZI+cIgH4YhvocATfwYKT0f/umxAIkj1+hok7zmJtlYZqp44cIwOMaBt/7j1S55/B2lhhKBzA83/4UomqYzBKsQUEh4Y4UGO7Jw+MYQORL/8BqY98GjPklkT5L3+HyNefQs1Ms3lgPL/82MwMvnD3/+YV02/HHoBzYAIrF6Q+cOEZMvc8ihMItuWz2sfPkgSiG0uE9mBbduv+Wpzf3vFQEITOUo8Dqdpce6VospbMLRUzDiPKv+syrm5GlzmyvLIwLwNpzTj5UpoAqmHHRrs6hCXRBHtc3ovjMNyCKa84kOojZrpTcnTKBKR0rrzxNhmmcC8Gyj6ujz2fkSgUwWCAF196mUgkwgfPnSt9vg7ZfXVlpU2jax1TM9N9eeIrn6t36LfPtOPnGTlA+Pt+DAB7aQHfxEy+G1rmC/+e1KU38D32YQLHz7AaHUW/e6nk5YFAGB+wduVywX30J1/IP+8VnNmryztu01A6ha18LNnGdah4rqQyAo7GB/jWlsk881UC3/tDAKRuXiN203U8Wf/ldwj+yN8GYHV9A9ND+7Inj71AAOvwCfSVd6ouMvLAEwBk/vh3Sb32IoETd+Hz+VhcXGpdRlV0kMBf/0lUwD1l33r7TTbavC17cn8JgtAxEnUISNWWuF0UXZvIFZOsG4ch1d/9rcqDsj03i7edErlsKUs1Lh5B+4KuU+ieLzFMohlsgTDQy2Hie8mCsTmguu+ip4MrtHrfw1d0AlsZEmgU7ndUBKT62HNJOZ1Os7q6hjGGRCJBNpslm81iWe5QwuEIqdTetvUTBKG3sSZmCnf8pSVFZmMVjMkHX6vBQcpRo+MYrTEbazu+j9na2Hkg6RRqepbQz/0ygc/9VPXlvBK2TKZEZPJylAD0d86T/fZfuHf87Qtq3u9Yd9yNGh0j9HO/QvAnfw515GTVZbOn7sJojb78tvuAF8geaF0OknX6Lnyn7sQ6ehIT20Jff69l6xYEQWgFG2Ud1JaNnc8z8qjmJrpttjuQ1sn2tfsICmHZhfsFB5L3r+fsipnGpYp2iRtx0/t7Zss4mBZoYN3pq+k+YnRHaHY5bmfIgnhrgNdMkmWTxcqJpCIg1ceeC0iLS0tMTE4AbqC23+9jaWmZ2dmDAMwenGFhcWmnVQiCIJSgisq99JuvlAgxZsMtVzOJmLtstJKANAab6+BUPgUz3uOZ9I7jMMkEyudeRfWdPFt9wVyItrLT+cwmANKl6zdZ90Rb+bvvSk5fMDRC8PM/Q+gf/O+oYbeM0Bp3S9QCP/g/4P++vwFBVxxSBw/jTB9GX34LvK5o2Yz7b5tykJyLr1U9JgVBEDrF+yad96Qo4KpJEy8TPeqZPiaNBgNrJlvSoawfKXY+QEHwKZZnUsZ1Jy+ZxpNY2iVurBmHQI87kJZMtiWfQcSF+shguKkznR5GRdwQ/9L9uIWT//7IPq6PPZ+VpFIp5uZu85EPfwiAN954k7X1dR5++CGOHztGIpnkxo0bez0sQRB6GDU6BrjlavrSG/i/69MQCrtCUk44yv8bLWsb7PPB8Cjm+vvV38DLFlA7a+7Od85jTbvd38wOE38VCmNsG6V1VQcS4IY0gziQ2oQaHN72WOCzn8f/sU/njynffY9g/+FvY52+CwDnxW/nlzW2J/AFt59yKIV15wPod9/E9+iHsM7ci/17/6ZmqZvKuZmMbZP92p81+ckEQRDaRwrDuskSxuIlHeNdk2bSKv07VY+gsWay+HFdSTam54WKnfDcDx42BlX2WBKNQnHdpDlNqCFXUbt8Qhtke36vbLbInyUOpPqwjeGiqRzh0GlszDZxO4sr3oaVhS37uC46cln72rVrXLtW2lnmueeer7K0IAj7gsEhcDQk4w2/1HMg6VvXch3M3BNZfa1Q/mMS7nrLHUj+7/lBlGWh16tnq+m3X8N33yPo2zuL284L3yTw8e/L3dl+BVEdPAJ2xnUgZVyxqNSBVPYH1+vSJg6ktqCKxETn9Zfw3f+Y+3hOPAJQ4QjW2ftQI+5jJSVldnUHknXfowR/6CdwLr6B7877AMhOzZZ29atEzvFk/+FvF5xOgiAIXcbrOsFNkyGVm3CVd1mqx4G0hsNNvyaGxkbTgcKIPaN8e3gCUvF0NYEmi2He2A0XALWre1QKQ6wLy5EawcF1Uu0WcafURuHmZnWrdzpbFmbvkcwJSN067m6jf3+pBUHoKcK/9M8J/cKvNvVaNTrulnvFNt37Q66zRN8ochWlkhjHKRGQ1OxR/B/4qLvswq2q67f/5PfI/N6/Rb/x8s4DSSVJ//qvoG9dRwVD+VI1ACyL4N/6eUI/+0+wJmcKbqMSB1JZiZw4kNpLxBWQsl//Evaf/v62p7OvPAuAGjmAGhl1SxiLXWI7ZCBZBw8D5MUjAGvmcO0xeeuy7Z2XEwRB6CCXTTovHgEkjQPG5N0q9ThikmieC7vSR6ZNXcS6hfJPZxvPgVR4ZtM42MYN9U2ZxkSbdiYVzZnuLEdqhKtm9/m6IiDVxgJiDR67e0nWbC9hA0hLCVtDiIAkCELnGXBFHRVsLoxYjY5j1tfypWYml1VkblwpXTARhyIByTp1JwDZZ7+G88I3q7+BbaPf/U5dYzHrK+icy6S4REpNHUQVC0o5scgUu47KStiM7Z5YKxGQ2oLnQNJLt7dtewCzsoBJp1HDB1AjY1ixshD1HTKQ1Pj09sdmj9QeU76Ebee8LUEQhG5i2WR5WSfyE4t628rrnOLU76Uj5QJPJQfSnMngKXDlmVK1aGd51fU+EJBumd1flBF3Sm0UingXb6lqDqRUbszZLha/ugkRkARB6DiquItao4TCqMEhzNpy/qHMb/1f2P/9j7a1ZDeJWEnZknXqTozWZL/95daGFXtCQ5GAZB0+UbpMBQfSNhHDcyAFpIStLUSi7r+JymWTZmsTs7mGmpxGRaKonMMt/3xRBlI51vTstkyruhxInohq9/4JuyAI+4c5bN4wiXw3tkanYf21+jZSAAAgAElEQVQvIJXifl5VIiyt4pDObb9Eg1uwe6fs/YO4U2rjYMh08XaqlIEE5N2U3Tz2bkIEJEEQOo41WSQgNZj3o3KTclNUgmbmb+E8/41ty+YFJMtyQ46PnHBfV0VAaBYTc7Nr1NBI/jHr8HH3ua2cCOGVKhWFKpuMhGjvJZ6YaJKJygvEtzAba3kHmLVV5kCqloEUjqBGx9DX30cXueDUZB1CaSDk/psRAUkQhN5jM+ecaVRAyvR4zk4tyh1Ingui+FMbYD7nlGk0d6i/t1534PR5mWUrcEx3C0jVHEhpNBZuWa1QGxGQBEHoOGqyqNwnMlB9wQp4WTP6do1wYsh3YlOjYxAMofwBzMZ6Q+9XDyYnNHhZTABq5hAmk8a5/FZhDOWUZyB5Qdw+cSDtisEhgj/7y1hn7i15WEU8AckVEJ33L5U8b2JbmM3C8WGVOZAKDrFSB5Ian3JfvzRP5nf/b9K//evo6++XZmJVoVDCJgKSIAi9h9fxqnEHUn9Tvj00YDCYMlHiZe3+PUo06CmSDmHtRxxItel2J2EWUzFw3nP+rbQgbH0/IAKSIAidRSms2WOFu15ZUZ14ZUE1u1tB3tUR+vn/FTXqdm4jVcV9sgs8l1FJm/hgGJIJzOqS+9zA4PYXlnduy0oGUivw3XEP1sQUwb/5d0uf8MoZcw40+wv/nvRv/3r+aRPbhM21/P1tJWy540mVOZDUwJD7/NYGZNKYa+9h7AzK5wOfb+fBSgmbIAg9TCwnfDQqaOxHB5IrIpXiOSDWjNPQJE0EpPbj5VYJ1elm9xG43QorfVc2cEiixYFUJyIgCYLQUXwf/V6soycLDzQoIKmZw5hMGrOyWHNZnRNvAKzDrmhlijOIWkVsu4CkgkGMbaPfeAUA+yt/kn/OfuoLZL/+pW2rMfkSNnEg7QZT3NGsyM2lIgPuNvbEmpzYkycRw6yvFl66OFe6Ys9pNlEamK0GcwJSfKvwYC7YnWBo58F6bqaMhGgLgtB7eFfyG51GbhmnryfnumyDeD6HatPVZVPJJ7HD+rt84t4PpNB9fYy2gmyXl/ll0RUFpHXjEJcA7boRAUkQhI7iZQNlv/0XQKGsqF7UgXHX1VPHHy3nxW+hr77rvm76kPtgGwQk4zlVijKQCATBzmDWlkn9bz+H8/RXCuN6+Rmy39guIEkGUmso7n4X+LGfLmQWRQYgsYMDzRic75wn+60vk/7NX8O3vlzytL5xBWPb+D/43QQ+/zOF9eYcSFQSkAI7dxpUwRDGcUqysQRBEHqFrVyWSKOOmHlj9/WkpJIDyZjKgb7gihWNZO443T1v7wvmjU26ywWSTtPtJWx2lQykJJrFFnTq2y/IZW1BEDqKCoYxWmOWF9z7jTiQ/H5UOIKOx+pbPpUk+9zXCR6/A2tqFmiTAylrY5KJ0hK2QBC81uz1igO5EjYRkHZJkYDkO30Xzqm70BdfR0UHSjKOPNK/+WugclOZTIbsV59yb8+UOo3I2pjVJdT0LL477iZ78AjK8uE7dRdQ6kDyMo1UMLTz6VUgIO4jQRB6lg3jYJV1F6uHGJq0MfhVf3o8yv/qG6hYwlb8vNunrT6khK39ZIFrJs1pVTvPcL/S7TlRWWOwKnyrHAr5Y0Jt+lnsFwShFwiFIJ3CeJ3QGnEgRXM5QvUKSJAXDNS0KyCRboOAhOtCygtIPh/K5ystpaqHrNcmXrT+3eA5kLI515eaOQSW5YqVFTrwmZtXMTfer2vdzvln87etiWmCf+vnsU7c4a6n+Lj0uqrVcCARCEn+kSAIPUsiVyKSbGIiGevjZvSVtoZD9dKzRrdet0/c+4VlcansSLcfhylM1TF2u3uqmxABSRCEzhIMu9kzuVbqXmv1evCCqEuyZmpgNtZK3sck2yQgbW244/P5CqJBg8KAkRK21pATkPTVywBY04fyZWamvLNagzgvfgv7K//NXe+dD5Q+WXxc2vVlILlZWSIgCYLQm9gYbGOIN9HNKNbHGSSVPpnG7DhlrXc6q+j+8OJ+IS1B2jvS7SJMwmjSXT7GXkAEJEEQOooKhTCZNCQ9B1L9JWwqmhMBEvU7kEjECsIMtKULGwCxnHgwMNS0gFQoYRMHUqP4HnwC//d81r2TE5DMygImtoWaOYzK5VOZ2Mbu3khr9Nuvu+959t7S55zCBMrkytJUrsuaOnISrAp/ggPBgltJEAShB9HKsNJgCDRAso8dSJWcRpqdS8/qldMskGyePSItQdoABKtsBbvLu5gl0aT6WKjeK0RAEgShswTDbgmb50BqpIRtoPESNozBbBRyb9qSgURBmFBDI/k276ZRYUAykJom8NnP4z/3CRg5gAq5rh+TTqEXbmGNTaDGp9zHdulAgoKrbUfyJWwhfA89QeinfgH/J76/wsCDUsImCEJPkzWwSuMCUv/KR5WFolaV+yi6f+LeL6SMlskzVHXxdHuBXwyHlSZ+m4RS5DsgCELnsCxUIOC6M9Ip97FQ/eGEaqBCu/Q6MOsrhTvtEpC2XGFCDQ67uTbQuDDguH/klAhITWMdOw2hiHsnncIs3nYfP57LKdravYBE1i51tVUi44VoB7HOuE4l6+x9pcv4/LmsLBGQBEHoXVI0VybSzx6ayhlIZsew8fqDyFXXT9z7hUxD0eb9y6Kx8VV4vNszkByk3LMViIAkCELn8PJg0il3Eq513q1TD4UMpAYcSICZv1W43a4Q7a2cA2l0rPkSNmNcYUJK2JrG/8FPoIZHMdksZLOY1SUArGOn3AVaISBREPmyz30NAL00X/K8Kc5AClYRFL1jX7qwCYLQw9zQzf2G9fO0rpIY5Bizo29op+3hR7GWKxM0OwQDC63FriH67Rc2TZZEhVKwrJRS7gtkViIIQufw3EbehNm2C26devC6sDWSgQToueuFO+1yIN28CoB16q6866UpZ0k2KwJSoxS1gbZmDgMFkdGsLLqPT86491tQwgZg/7ffwzp1F9mv/AnOhRcwW+ulC3jHeDCI8gSk8pLGvLAk15IFQehdXjfNZQv2cyv6SkJRlp1Folpb422d5EO+oZpZSkLrqLXP9gtZDJvGYVKVelEyUkq5LxAHkiAIHcObSBuvfM1OQ7BGm/Pi1zdbwjZ3rXBHt+ePnVlbRs/fwjp1FgaH3QebEpBsVGQA/yf/GtYdd7d2kP1K2A1iLxbsvGPMrCyVLLrrEO0czoXnsf/oP4DjYBZuQSJe+j5eCVsglO8AV36sq5xTLe9WEgRB6EGaTRjp54l5pTMNB7Oj8LNTjzaDYQsHC4VBBKS9IovBEZcNWdxS1WIsICEC0r5ABCRBEDpHmQPJZDL5SXQ9qKFhtzSpQReRWV1uaPlm0RdfR/kDhe5cTTqQ1OgY/g99Ev/HK4QuC9tQuU5+zusv41x+O/eg+4/ZWM3nFRnHgWSbuvCV4+37cNgta6QggObxvg9pEZAEQdh/7NzUvrepVPZUq+xsp6m4BpJGYzBoYyQWeA/p57D3enEw2GXHr4WqWNYm9B911UWEw2HuOH2agYEoqXSaK+9fYWOzNbZ/QRD2LyqYa6+edyBlIDxS34stCzU1my8Pa5TMf/x30OarSPr6+0AuyBkwmcZLkzyxwV2RaP51kROQSMZdN8/pu1BDuePKGLdr38gBzNpK24+BPDmRVE3MoHy56MkyAUlF3Q6EpsGSTEEQhH6gn6eezYRo1ypvS2Fw6O/t1o04GAL7PEg7awwZVX6EmqbC84Xeo6qApJTC5E6s7zx7hncvv0cikSASifDIww/x7aef2bNBCoLQp4S8LBgvAylTCJyugZo6iAoEcIrzjBpAv/NmU69r6D1uu2NTw6PuA7stTQo2kA+1j1GRnBCTTIB2rxUWd7LLvvhNfGfuw/6L/7ZnYzKegHRgojBOvx81NQuRCObae0WZXvFKqxAEQehr+tmBVMm1kqVWiPbOElIGjWN2LoMTWo8Elrth4uXdzKTD2f6h6uXsc08+wYEDBwD3Am00EiGS+08QBKElBL2SnVw+TSbtdmFTta/sWLNH3dc0KSDtCYk4Zn21cL+JEjZ944r77/JivjRLqI518k6CP/4z7p1kArO5PePIefovyfz2r2NuXtm7geX2fd4JlSP09/4xob/9D2BgqMiBJAKSIAj7D93Hc89KYlAt99BOm0Mb97W1RCih9ex3wU4BaQx2WbmaY7aXtQn9SVUH0osvvcw9d9/F0SNHePfyZWZnD3Jw9iCZdIZXzp/fyzEKgtCPhML4z30MKLgz8t2nAsGarczVwSNAWUe1LkTPXcfnlaE10V0r8zu/Af4Awb/xd2BswhXXJMCxKoEf+on8bZOMoy+/hb55leyL3+7gqMh3XFO54GyTiOcFI3C7xUkJmyAI+5l+FkIqOZCcmh6jnZ8zuI6P/V1Mtfc4xrCfN7qFm78VKrvYK+6j/UNVAcm2bV597XXGx8Z46MEHuHb9Opcvv7eXYxMEoY/xf+iT+Rbr+dBgu9DqvKaANDoOFNqydyv69g18dz8IlHYFqxs7A3YGk0pgWZYbtNxgaPh+wqQSqMFctlAyAZkMmd/8tc4OCsDJYhwnn3+kr13Gd9cD+afVzGxRCZsISIIg7Ef6dwJa2YFk2EmJMDsIFZ7YljUG3z4WMzrBfg/RVihSaOK4YpJ3LJZ3ZRP6l5qJrFuxGM89/wKRSIQPPP4Y0aiUUAiC0AK8jlMAXlesnEOnnk5samDIbY1eQ2jqNCUldrsZa040UmH5Dd6RInHNJLusFKxo/zsXnsd+6gv5EkVr+lBRdlOXjVsQBGEP6OeJeaWpdbZGiPbOXdhMfh1O/+puXcl+z0AyufyjLaOxihTOlLjj9w1VHUhnz55hbGyMdDpNOBTixs2bvPHmd7j3nntY31jnnXfe3ctxCoLQbxRZX7XnIvIm2IHtYdFGKfyf+RGc11/C3LiCGhzCxLu/G6Seu1G400QJm4fx2s1HIrC+y0H1MWpwOH+727KETCKWz7EyqST60hs4rzxL6B/9S9TMYUx8y12wy8YtCIKwF/RztkwloShrwL+De2jHDKTcvzZm3wsae81+394a97jTZQKoOJD2D1UFpImJCZ555tn8/XPnnuTGjZu8+NJLzM7O7sngBEHoXzy3Rfo3fhW2ckHHXolXcLsDKXvkFP7HP4L/8Y+Q+pW/DwODMH9rr4bbPIkYZn0VNTrWXAlbDpNyBSQVju7zU5cdUAoGhzEba9hPfQE2u0xpi8dgfMq9nQuOxxjM4m3U7FFQCpNKgpaTMKG1KKV48MEHGIgOoJTiO2+9xerqKsPDwzxw/30YYHNzk9dff6PTQxX2MQ5uxVY//o2rFBDuYPDt8GF3FpAKDqS0TNz3lH4WOutBG1e0dHDzoFTugrAch/uHqiVsiXicBx98gDvPnuWRRx5meXk5/9zc3NyeDE4QhD7Gc2IUdSnzBJaKJWy+Ir07FEb5A5jYVluH2Cqc9y+6bpjdZBflHUhSwlaVyADK70ffuoZ+961Oj2YbJeHY6aJSu9UllM+HNXVQArSFtnDk8GGcrMPTzzzDq6+9yr333A3AvffewxtvvsnTTz9DwO9namqqwyMV9jNOHwdCV8pASmFKSoC2v6Y6xQ6kLZm47yn9XGpZD1ncY1PnbnuIA2n/UNWBdOHV14hGo4RCQZJXk6TS3Z0zIghCb6HCEVcwyhaVdeU6VVFBQDJFmUlemVK+5KfLyX7pD8l+5YvgZGsvXAWvhE2FI60aVt+hhkYAMJ6jrcsw8YI4ZFKp/G29sojPuyPla0IbuHHzJjdvuY7NdDpDMBhEKcVANMr6uvt9mV9YYHJygsXF7m5MIPQv/ezsqCQ6pIzGUdXjaHfuwuY+q4AV03x5vNA4+72Erfh7mkETyJ3BpI0ISPuFqgISQCKRIJFI7NVYBEHYT0QGCq4aD7uygGTdeT/22fsLDwzkulX1iICEbe8q/wgouJfEgVQVNZQTFrtUQKKaA2llqXA7Lg4kofUYY9yOTsCpkye5efMWoWCQTNHvUjqdIRzanj9Xztj4OP7AjqePXcHUzHSnh9AW+vFzeZ9pJKsIJwPoPrEhhcO5C18GhsI+pgKlwsOgoxjUiqnAcIVXQzTpJ+xUFpgylmEqGiSS8kEoytQebLN+PvYaYSDtI2z7ai/YQfLHXhswyjA14G43fyJAWCssA76Ijyl/e8U1OQb3jsX5harPdf8ZgCAIfYmKRLdN9E3OgeT/0CfJvPd2XjQJ/uj/VHL1zhqbdJfvFQGpBRRnIAmV8RxIbHVnuHqJOFSUc2RWCwKSvioNKoTdcfToUY4dPVry2MVLl1haWuLE8eOMjI7wwgsvEirLmqt3/rm6stKikbaPqZnpHU9+e5V+/FzFn0njJ+M/QPNe3e4hHA6TyjlNFbCc2GTRlFZzxLFABbY97rFljTBkVe5KG9M2i5vrnMfP4h5ssX4/9hphXkU47Btsw4haQ/Gx12rixuGPnFV07vR70RomZIXwo3g/vkysjWVscgx2DyIgCYKw9ygF4Qgs3i593HZPoqzZIwQ+/cPYf/y7lV9+8AhAz2QgtYSc+KAOH+/sOLqZgSEATKxbBaTKx6tZKZQM6bdf26vhCH3K9evXuX79+rbHjx49wvTMNC+++BLGGNKZDMEit2c4EiaVkrgCoXO4pTH9F6OtgGyFibUbgF39s+5cwuayF+KRUMqcyeBD9XXJZTU2jFNyJMdz92ody0J/UVNAGhoa5NjRYwSCgZKrU+cvvNrGYQmC0NeEwijLQqeqlLABavhA7sb26+L+J77LvbGfHEgrizjvvoXvjrtxzt6HviTdkspRnoDUrcdFtYDsdMrNuHIczNpy5WUEYRdEo1GOHzvOM88+i86534wxxGIxxsbGWF1d5eDMQa5cudLhkQr7Ga8LW7+hALvC3DqDYWmH/CK9w4Rc0mY6xyoOGaPxVTg/7Xc2y9K8Ern72hhsEZD2DTUFpEcfeZRbc7fY2OzSTAlBEHoO5XVgK8tA8krYAMzmmnujUkc2wLnyDvrW1baMr1txnvlLfHfcjTV7ZH8LSANDWKfvQr/2YsnDKpeN1a0C0k75Rul/9SslZW2CUMzIyAgD0SjpdJqV1dXaLyjj2NGjBIMBnvjA4/nHnn3ued58800eeOB+UIq1tTWWlkXAFDqHrtirrD+oFLxscDuxVaOeLmzC3mOADZNlTAU6PZQ9Z92UOt5WTRaLnY9jof+oKSCl0yneeae1mQyWZfHxj30Xl955h6WlZR55+CGUUqRSac5fuJC/OiYIQp/i5fiUCUjKKgqL9LqNBbcLSM67b2H/3r9p1+i6FuN16NrnOUiBH/ib+M7ci+0P4LzyTOGJXHe+qk6fTpPeIZMglaz+nLCvOXv2DJZlEY8nGB4e5tSpk7z40ssNrePtixd5++LFbY9vxWI8/cyzrRqqIOwKTeV2972OQrW8c9dO7iSh/WziMMb+EpD8KG6ZTMljy8Z1IIn7aH9RvXdkjoXFRSYnJ1EttOmdPXOGTMa1bN5151muXLnK0888Szwe5+jRIy17H0EQuhMVGQDAJEtbluvbNzAZN4NDRV03iSpzIGX+w7/G/k//bg9G2X3kg7T3eSc2NeF2rLDuur/08YFBTCoJ2e7MhDDrK+iFOeyvPtXpoQhdzh13nM7fjkYivP32Ra5fv87FS5cI1dEpTRB6kf3mQKqFBkKoimV9cqm9s+xHwcTBkCz73Ek0aWOwjRyR+4maDqSzZ87g929f7ItP/WlTbzg4OMjQ0CALi27i+Pj4BK+97pZizC8scPrUKa5evdbUugVB6A3UcK5bVnmpUSpJ+p/9IqFf/GcQdUUmAu5kScU2Sf3Ob2DKg7f3E55LxXNn7VPM8iKMTWIdOl7yuBoY6tryNQC0JvNv/o9Oj0LoAVLJFOfOPcnFi5e4efMWTz75BOA6uK/fuNHh0QlCezAUyrbCqD4qi2lOGDMYMsZgKcqSZ9iXAc7dxH7c+o4xFYXQFJrqSV5CP1JTQPrSf//zlr7hPffczRtvvMGRI67TyO/35UvW0uk04bBcWROEfsY6ex/W2fsA0EuVW1eaRAw1kgvRDrgW4cC7b5Lcz+IRuGHLjoPa5yVsKhR2/40OwNAIbG24YevRQZAQaqEPuHHzJvMLC9x9911g4OWXX8G25RRd6G+cKrd7HYfmHEgm97pgBQ/SfhQwuol2b3+NwYfqqv3sUPlzp4wmI564fUVNAencuSd59tnnWvJmRw4fZm11jUSictZDvVVyY+Pj+AM1h95xpmamOz2EtiCfq3fots+kw1FiP/bT+fvjlsaqMMa4k8GJRJmcPYgzM0MCUFm76z5PK2j0M21l0qihYUa7fFu0c1/FhkfypyrjJ07iW5xDhyLEfD4CWbut26Yfj0Ho3s+1OF9ZZN4P2LbNa6+9ztjYGI89+ijXr1/n5q1bnR6WILQNjUEbg1Kq76ajzQhiBnebOBUEJMlA6iztPj4v6xQnVJhAF3V6qyaCJtEtz/gSupuaKszmxiZ3nj3L6uoquqi+cXl5peE3m56eIhodYHp6mkgkjNaabDaLZVlorQmHI6RSO4SM5lhdafy995qpmem+PPGVz9U7dONnUoeO4XkMTSbD8tXKLaMDa2v4Dp1gaSOGNRgnCGBnuu7z7JZm9lEwEUcFgl29Ldp97IUCofzp9FrGQc8voCamCQGp1WVibXrvbvxOtYLC5zJMBm0GfA4Rn8OtVJjN7PbThMlgBscoTkSTXIpFiTndf0Gn1xgZGeHkieMEQyES8QSvvf46swcP8oHHH+PN73yHeDxRcx2C0Gt4JWwW7mS1e6bOu8MY01TJmcaQBZQx+MuEBJmud5Z2b/8Vk+WwMgS66FtQ7RhO9Z3cK9Si5lnf8Ijb1WZsfKzwoIHl5cZdSS+/cj5/++zZMyQSCcYOjDE7e5CbN28xe3CGhcWlhtcrCEJvkC9LA1SF7moeJtdFS0UHIBeirbJSvgFAKuGWbe1nikLE1fCo+6/Xga2bM5C6mIDSfP7QPGcGC8JE0rH4nZsHWc4EeGx0Ex8QtDTnxtbx585pn1qY4Nm10c4Muo+5/757efmV86RSKQYHB7nv3nt5/oUXiEaj3HPP3bzUYBc2QegFvOmpBSSNJqxq9vrpCaqV/tTCUJi0+3NCgoXrfpEMpM7STgeYBWwap+v2cdZUE5BM7a5cQl9RU0BqVflaNS5eusTDDz/E8WPHSCST3JBwSEHoO6y7H8Q6dRdmtSAQ69Udsmq8dvXRwUIXNhGQADDJBFYwCD4/ON3ZbaythMIonw+TTKAiUVROTFOj4wCY9dVOjq4n8ePwk0fmOBlN8X4izNWEG9L+0fE1fmhmkcVMkHuGSjsmOgZe3xzipfXhTgy57zG43deUUkQjkXxWZCKREPFI6Gs0btv7FJpwn0xLd5PnZDBkMESwSrwo3SUt7D/a6blRwAYOWaNB+dr4To1RrfNcymiCXVRqJ7SfmgLShz54ruLh8swzz+7qjS9deid/+7nnnt/VugRB6G58j3wQ3+m78pN7561Xye7QytzrpKVGDkDOqaQkQNYllXOIRCIQ239uG5XrzmcW5lDHTxcEpPFJAPSKuFgb5cORq5wMpXhjc4Dfn5vJ520M+h0eH91kMmRzPRniy0uuSLeYDkrZWps5f/4CR48cIRgKkkgkuPDqq50ekiDsCSb3//7pwNa8W8V1GoFtDCjXAbJKlkkVkKKhjtO+4zNrTC5XqLuoNp4NsoyZwJ6ORegsNc8A3754KX/bshQTExM42X7qjSAIQrtRubbzatQthbW/+AVIxqsur29dA8A6dgrjddUSBxIAJuU2IVDhKGYfCkhEXAFJL85hHT+dL+dT41MAmJXFjg2tl1AYRvxZ7hxM8EBwiYV0gN+/PVMS1vq15QMci6RIORZ/PD/FYqZ62anQWhKJBBcvXaq9oCD0GV5odMZouij+ZVc0W4pkAG1M3vkxj40ygGp/iLOwM+2cCWcwaKo7fjpFtspRt26cbRldQn9TU0BaKQusXlpa5okPPN62AQmC0IfkBCQAk0nvKB4BmNs3MKkk1okz6NgmIBlIeZI5B1I4uvNyfUregbS5jknECxlI45OYdApyx4tQmbGAzfdPL3EqmiRguSenKe3nD+amcUzpCeBGNsC/unK0E8MUBGGfonGFk0yXTZ53Q7Nij5uB5AoJSaP5lrPJh6yh3Dr7Z/v0IqaN298Lpe4+AanyeGJoEiazx6MROklNASkaLZ2kRCIRBgcH2zYgQRD6DxWKYJIJCIUxa3V0UdQaffUyvjvvgzvudddhyx8nAJMrYVORSJedWuwBfj/+7/lB93YyjtnaKAhIY5PiPtqB8UCGk9Ekj49ucjiSZj4VZCETZDkT4FrwBHNpEd4EQeg8Gtd1018CUrMOJNeJkkFzw2RIFckW4kDqLDq3IxStL2ZL58Kquy5Ee4fxyPG4v6gpIJ178smiewY7m+ViUX6RIAhCTcIRzPxNsk9/BVPDfeThvPw01h13Yx3KOSDEgQSA2crlQ41Ndngke49190NYUwcB0IvzWMsLWNOzqMPHUcGQ5B8VEbUcJoIZDgSyPDq6yemBZP65y/EIv3XjUP7+1EwEEAGpWxkeHiYYCJSU8ywv1yHEC0IPYjBkUTtOVnuNat2raqFxxSeF4ppJAQVRQRxIncUTTMIoki3eF+kudSBJgI3gUVNAev6FF4jFYiWPHTggLXsFQagTvx8VCKBTSfTF1+t+mX73OzjPfwP/Bz8BSAmbh77qCvjWqbtwXvhmh0ezt/hO3wVA5nf/H8z199BHTuC75yF8dz8IgNloVwc2N3Ri3IpzfHSDddvP9WSYlO6e7ijFnIom+LFD80R9hWuC78UjRH0OB8MZnl0b6eDohEZ47NFHGR4ZJpksCIAYWF5ub4dcQegUXov6fhKQdlPCpoFbJsNNY5esSxwfncYT8lqPVxbrFMYAACAASURBVMLWbd+BbhuP0DmqCkh+v59gMMhDDz7AK+fP4136spTi4Yce4qtf+/pejVEQhB5FTR/C/725kqN0cueFK6Bv3yjckS5sLhtr6MXbWCfOgN8P2W7r09EmlMI6dSdmawP93tsAGC9s/ez97v2t1rlowpbDfUMxHhzZ4ngkxXImwETQxsp1rdfG7UZ2LRnmvUSEN7cGMV2Q+Hr3YIwfOzQPwKVYlNvpIK9sDLOcCRJQmqORFO8lIjXWInQL0WiEr371a50ehiDsGQaDAzhNuna6keZFBoOD4X2Tzj/iOZBMH22fXsRz47RDQMrm/+2ufdxt4xE6R1UBaWxsjFMnTzIyMsK5J88VPWNYXJQyAUEQauAPEPqZf5S/63UPawSzcCt/WxxIBfSVd/B/4KOo6UN5EaXfUWOTqMFhnNdezD+m565htMaayHVg29rY9fucjCYY9jt8anKFAwH3NG4lE2A0kGVNR3h2eYABn8OxSIojkRQz4QwfOLDJs2spnlrobFlh1Ofw/dPLaKP4rRuzXEuWCkW2sXgvsT/D13uVWCyGUkomi8K+wQ2OLjiQLHrfbdNsuZlm+2f37ks5UWdpZymht85mSx/bRbeNR+gcVQWkxcVFFhcXOX7sGFev7Y8JiiAIrcM6dWfpA80ISMsLhTsiIBXI5UipQLA914OUwv+xT6Pnb6HferUd79A4A27nGbOxVngsk8GsLKImZ9z7O3RgG/ZnORJJcSScwlLw54vj6CLH0JmBOJ+aXOVQuHCl9/zGEH+xNMZGNgDA1Mw0i2uFY9LCcDCc5odmFjl3YINLsSiX41HGg+6x+pmpZa4mw3xr5UDJe7WaD4xu8MjIJofCaSwF31gZ3SYeCb2JMfDxj3+M9bW1EhHp/IUu+V4KQovxnEcpDBawYRxGlK+nRaRmx+5lIFVaVzu7gAm1caBtf9U9cbDbMpDEgSR41MxAujU3x91330U4FOb8hQtMT0+ztrZGJiMdkQRB2IFgqORuMw4kdOG0q/PFQd2D8crW/DV/wpvC/4nvx//hT2EyadJdIiCpiOucMYnSEHazvAA5AamSAynqc/jcwXnODJYefxu2n2fWRgkozaenlnniwCaOcd1GngD0pcUJ4k71nCON4lYqzO/fnubnjt/gR2fn8SuD3yosc3YwQUZbPLtWnB1oeGA4xsloksV0kOvJMHOpEE4TR/mpaIIfmFnCMXA1GeZSbIBn1iSnsF9YWl5iaVlc38L+wgFSRuND8S29yV/zjfV0aHTz3bTMts+dbWP2jlA/Tq5ovR37wdvnqdx7dMORr4B0V4xE6AZqzj4efOABVlZWGBsbA8CyLB5+6EGef+HFGq8UBGFfY5VNvJsRkID0v/oVCIZFQSrGc2P52iMg+R7Odd90usckr6ID7o2yLn5mZTF/+6R9i7un1skYRcLxMehzuG84xoFAliuJMBdjA8yng3xudoFPTKzy2uYgP3X0FtMhm/lUkD+4Pc3tdIgT0QQKdhSPillIh3hhfYRHRjaZT4fwK8NM2L3IkjXwwQPrPL82knch3TsU52/MLpSsYy4V5DeuHm14u3xq0u3G9W+vHeZWKtzw64XuJBQKkU6nWVlpVzC8IHQnXoh2Ck0ch03j9LR4BM0LSNqALjv30TlRIdPj26TXyRaVmflU/SeoIax8l7VqeM8mjMaiO8oVLSBpRLYUXGrOPoKhIO9fucLMQfcK7+3btzl54nibhyUIQq+j/KWT76YcSIBZy7Wrnpne7ZD6h7wDKdD6dYcjqFy5GL7OdhmLWg6Pjm4yG05zMPOnvPtqmlcTS5w7uMBfLo+xagfwLc3x41/7h8yuvkt4Nr5tHbZWfHNllD9fGsdTIZ9bG+ETE2v89LFbTARtXl4f4k8WJska1zp0pYmcoC8uTPLFhQlAEbUc/urMEi+sD3P/UIwnDmzyXeNrfG3FvRDz4PAWAP/p1jQ+BR8ZW2M2nGHIn2UrW/nPssoXLBROVKOWw9FImsvxiIhHfca999zNK+cvcO7JJ/G6ABYw/KUEawt9isadnNsYNo1DGkPWGKwGJundRAjVtADg5UEVo5HJfDeQNe5+sDH4yq5w+lFVy73qKT3UuTLOrV1411qNQpEU35uQo67L10qpvH8uFAria9NVb0EQ+ojy34kmBSShAp4DqQ0CkhorBEGrYAgCgY51wPvRQ/OcHnCPG+0opt7+Qz5oASNwKJzihfURRree5WSqkNP3/12fxTaKqE9ja8W1ZDgvDHm8sjHMJybWmAjaJByLP12c3LZMc7gnkQnt4z/PuRdd5lMh7hxM8ImJVd5LRJhPBzk7EGc+FeSNLVeoGw3YHAyvcjic5u3Y9r+vYcvh50/cIGsUX10e47VNt+Pbsai7ba5IV7W+45XzFwD4y69+tcMjEYS9xRNNbAwL2k2BsTGEetCGbOGWITXroDKwrbunNkYm811AFoOFIoNh++Wb6vu7HknIWyKBZtFkmVCdn3eb3HdSEKAOAenKlSt89CMfJhQO8/jjj3FgdJQ33vzOXoxNEIRexiqbkHfYzdJPeBlIqg0ZSMUCEgDRQSgOrt4Fw/4s9w9vcWYgwVQww+VElPfiEV7fHNqW/zMRzHB6IMnVRJg/uD2N+u4f4IfjX2Nw7l3CZJgK2Xz/9DKwDMB7Mw/z9Mu36+oytmYHeGZ1hIPhNF9fHiOtWyEeVSapffz+3DR/5+gtPje7wMvrw/gteHVzML/MXMrNCzsUTvF2bGDbOs4d2GA01xHuc7MLnDuwzp8tTnAimgLgSlLcR4Ig9Acag4MrGr1uEoAnIPUeFop1Y+9CQDIVHEhGJvNdgJeBVGk/xI0mpCqfV+hyQ2mVdXvcNOmuEJA0UjYpFKh5RM7N3WZ1dY2xAwfQWvPaa6+TTqdrvUwQhP1OzoFk1ldRo2OY+ZsdHlAfkROQ/B/+FOrQMbJf/E8tW7UadwUkvXgba+ogKjpY2vmsDg7715kYjLFmB1iz/dwxkGA6lOGxkU2GA66ZP60Vj4xs8cjIFo+NbvJb1w/lRaSZUJqfOHwbgGfXRlizAwSGD/I7T/xLUv/n/wKJGDOhDJPBDBNBm9tHHubSFR9mhy5s5fzp4mTthVrE1WSEr60c4Lsn1vjk5Cq2Vry8MZJ/3is/+8TEGofCaaaCGb62MsYrG8OciCT56PgaCcfi3187xMcm1nhgOMbfPXaLrHZL9G6KgCQIQp/gUwrbuJJLKjdhzRgNqvcuQmUxxNFNd+Gs1IXNwXWoyGS+s2jcsq6MMdsEoUVjc1yFKpYuptCEqH7RqlyUWjXZrgjS1sZIFzYhz44C0uDgIENDQ6yvrzN3+3b+8dmDB0vuC4IgbCPnOLKf+gL65lUpYWsluRI2dWAc/yPnyD71Bbffdwuwcg4kfeOKKyANDDZ0ynAknOKHBy/DYOXnL2wM8t8XJzDAfcMx7h+KcSKa4rHRDZ5fd7uHfXpqmdFAlm+sjPLmlrsiFfFCtBOAYj4dYj6duya9crXhz7nXfH15jImAzT1DcZ5fHykJ6I47Pi7HI5weSHLnoHvF/QdnFnGM4pMTK1jK8Ae3ZljIhPjPczM8u5rkM9PLTAZt/uj2FHZLyu8EQRA6z9POJptl5Vm92vc5bTRJo5ueeGvMtkK1DAZtpKV6p3EdSIZM2R5SwG1jc7SKZy5Th5suW3Q7aUxXBGln6byIJXQPVQWk48eOcerUSTa3trj/vns5f+ECGxubPHD/fYTDERGQBEHYEZUTkIxti3jUarJlmUT+ANgtOsUeOQCAuX0dOOeWsNWJwvDpKbek7JsrowQtw4GAzWQww3jQPSX61uoBthz3T89za6O8vjnIL528xicnV3k7NsCg3+GOgSTvxiN8eWmisPLoACaZaJlQttdoFL9/ewZuV/av/9aNQ3zv5DIfHV8HIK0tPpfr1PbS+hCX4oXStuupCP/22hEsTNNXtoXeYGhokGNHjxEIBkr29PkLr3ZsTILQTsrFI2DbJL1XSKNdwafJqbcD22btdr6ITegkGjefqvjYtAAfilsmQ8YYAhWC3xM4DOOruv9cB1JhnRk0qgs8SN0T5y10A1UFpCNHjvD1b3wTrTXRaIQnn3gCpRTvv3+F969c2csxCoLQi3gh2l3UCr5fME629IFQqGUCkgoEMXYGs+WWg6mBnQUkv9JMhzLMhtKcGUxwPJri3cw4f750oGS5z0wtMeDTBddQjrjj50tLE3x2ZokfOzTP+7lA6OfXRkqWU5EBTGJ7l7Xeo7rgc2FziI+Or/Pi+jCvbAzxPx6ZI2gZXl4frri8iEf9z6OPPMqtuVtsbG50eiiC0DF6VkAyrkOl2dFr2PZa24AjP/0dx+SEweKzsbQxBBTEcIjjMFphmh03mqLeVNtQgF10oSzTJXKhON6EYqoKSI520Nr92UokkmQdhxdffIlkUpwEgiDUgZUr0dEiILWcbKmApIIhDFu1XzcwiO+eh3Fe+nZ1J08gCJkMJhFz113FgXQwlOazM4vMhtP4ik5mF9IBvpI6DayULP9nO2QOvbg+zPFIiodGtjgcTuMYeK+8s1g0CvOtCfPuVhbSIf7Fe8fYtP04KP7fa4eYDmW4npKMo/1KOp3inXfe7fQwBKGjdKYP6O5JoknvwjXrdqMrL+drXpASWoeXRVUs9mgM10yGLJAyetv1IgtYNQ4WqqorTaFKMpDsCmWMnUAEJKGY6hlI5ZbJjC3ikSAI9eN1XSt3ywi7p7yELVhw9ajxKXyPfojsX35x27YPfv5nsGaPQiaN8+oLZSs1jAWyHNx4i4m5BdayV3lXOzA4VLKUD8NkKMNPH71JyGe4lggzlw4xlwoylwqxkA4xPtNoxxDFf52fZCaU5mA4w9VEmLQuCkwNBFH+ALovHEg7s2YH8rfn0mHm0iIe7WcWFheZnJxkeXkZ06Plm4KwW9JdMYVunDSaBJroDqHJO6ErdFvL4gYaC53F8wVli45NDXzDcd3blULOLRTrdaQJFYs1WYz721+hHG4vycoxJxRR9Szf57OIRiN48mn5/UQisRfjEwShV5EStqYY9GWJO75cg9gqlDmQCBZEhuCP/z3UgXHM6pLrNCrCmj2Kz8kwFU6RCaWxtSJjLIJK87nZBY5E0vDKr7kLD8P7X/2H/N65XyYbiUIyQdhy+Omjt5gJu+VyfzA3xYXNyuVVjWIbi/94a4YfP3ybl8pLtqJegHb/C0iCUMzZM2fw+7efqn3xqT/twGgEoTPYPTp5tYEN4+Bvcu6fNZAte62DdMPqBtwMpFKhqDj0vJLDyGCIG71jILYpcxy5IlUdbdPbjFwK/v/Ze+8wua7zzPN37q3Y3dXVOSMHkghEZABIMVOBCrSiFSxZwUEjp7XG3t2Z9Y68M7O21pY9nmc0sqxgrbItWYnKYhITwAACIECQIFIjdI7VleumM3/cquqqTlXoRufze55+UF11wynUrdv3vPf93k9RyLTHYyAQ4OCBAxT67w4eOJh9JHnk0cfmeWgKhWJZo2fvuCkBaRJe4WDKyVeU7YE0H1/XRU/az9e7WonbU5+i5QQHklvCln1cW+/+G65lIn4jwZte/By7Io/ChsnbfTVeQc/N72BYVrD7hW+wlZN88pe/y3d33M75F17lA+19tAQMLAeeHq25ZuJRjmHTxz90rpv0fK4D28rIQFIoyueRRx/DMJZrDyqF4tqwXAUTBzlHBxKYsth9ZSNVoPESwBWQJJns7T5JcV7VVFe+NpDAxpESMY2jSDI5sNpC4lnkzEN1zCkKmVZAeviRRxdyHAqFYoUhsg6kSYHPq5xWf4aPr+vimZEajtOCT3PwIEk6Om9oHMYjYG0wwyfWd/HVK630G1M0fJ0iRDug2dy6OUDm/M9pGrvMmuEXCG3uxZYC0xF4hKTue+8EYFir5vSQwKtJKnWbrZVJfj1cy2PDdfg/9n7k5Qu80tPMBzeMsIkIB7VX2dEywObKFKdilXyzu2Vmh9Q1RmQdSFI5kBSrjNsOHsS2bQYHBxkYGGB4ZGSxh6RQLDipbMuA5TaFdXDH3iVnJwLbOEwM0rFQbpClgiNzXdJyAtL4ETqV4GJLV3BygIIifTy44pIXgYGcJD4tBfFmuYq4ivlhsR1xCoVipbKKQrR3hmLsDMU5Fg1xOl6JRBDQbDxCcltdhCafSb3PwK9Jarzupd/dDaPssI9RH05iOoKfDjTk29d3JoO8vnGEj6/r5r9fXEPE9NLiz+ATDj0ZP9aEErYmT4oPbO6nQUvC868CYAmdiKOhC0lQd9DF+B//x2pu5+grZwq2kG0t7/EiNA3HNDAcnS8NbOZPto9wXeQ81EBXys+/9jQvqHgEQDBXwqZKpxWri8d//Wv8fj8NDfV0dHSwffs2Uuk0L7xwZLGHplAsGCnpoDG1q2MpkxMUZjv1tpksHtjZ7l+KxcdGYsjxK6JSDqRcnpWFRC+4jjKkxCuEG8wtJzvMloJ4sxTGoFg6KAFJoVDMD/kQ7eV2yXd1bKuK8/72fgB2VicYMTwcjYa4q24UT4FrPWVrpB0NR0La0ajQHWq0NL0ZP+2BDO9oHQTgFwP19GQCpGyNB1uGuLNulIcH6/nEui68msSW0JUO8MN4H3WxbnZc+jXbMo/j1yzOt+xlqLqDc637udi0i/jf/gWks80PhKDmP/4VbcNnOdOdAgoFpOyFjNfn/mtm75amk7zWcZCWSCejpoevdrViytlZ8eeCqKgAVAmbYnUihHDLHQQqSFuxKnEdSMvPgzTX0cankCEkkFlm/w8rFQc3Ayl3bBaen6cSXHJh8JMdRq47SeLgQUyKjLelnNTRbaFRApKiECUgKRSK+WGFh2jrQrK7OsZd9W5r+W90tbClMsnecIz7GsbbzRuO4G/PryNu64BAz9qTQx6byoZW+voGeH9bH5srUxweDee7bj0fCXN7XYR94RjdaT9eTXIxGUAXknXBNPcd/zLrBk5SlYlg4OHb2gHO3P0pAJyeK2geP6IyhMwJSBVVpH0hLrTuRYwen/pN+SYISKbJkXX3UzNwjsee7Z02k2neyTmQlICkWGXce+89JOJxevv6uXD+ArF4fLGHpFAsOOYydd3MdczTlaol5Mq8rlpuTAw0L/xUpvrsU1mByS1N1IqWTeOQxqEe76T1lkLJohKQFIWUnA14vV62btmCP+Dn6NFjNDc3Mzo6qkIdFQrFzKxAB9KB2gg3haM4CIKaTZ3P/bN+MRngVLyKU/EqLqaC/GZbf36dV+OVRcKLnb2NFLM8BNEAwbd6Wifty0HwcqyKO+sj3FkfAeCnAw10p/380forbL/idljrqr+Ob3vvYGwshRcwvv91tOY2tLY14B/vziaqCgKvgxVF+9J27se5dA7P/tsBkAXn9xhBvr/7DzCe/M+z+B+7NoxnIKnJs2J1ceH8BRoa6lmzpoNwuJrhoWGGhofJZDKLPTSFYsEwkNgzBA8vVZx5mnNHlYC0JLCzP1OVKhaWoeXyjlJZicma4Chyw9IlvdKkTpssIJllijfz6dFbCjlMiqVDSQFp965dDA8PU1vndvTRNI29e3bz7HPPz/vgFArFMkZfWRlIYY/JmxqH0YTEdARawR//p0dq8o+PR6sIajZ9ho81gQxHJrakvwp6026AdoPPJGlrdKf9SAQ/GWjgd9f2APDQzX9K9LVLkMyKVpaBzLiuIxEIjndnKxCQRIGApG3ehu9dHy7esTk+OZXpZLH4tAioLmyK1UrnxYt0XrwIQG1tLVu3bGbv3j38+Cc/XdyBKRQLiIM7UfdA9rbL8shDkvM06R6QZumFFPNOzoGU+5QLS8+sgo/ewS1DS+UzkIpxkFySBmPTeI3KFW98iHkrb1QOJEUhJQUkn9/Hhc5OWlpbAOjt7WXjhvXzPCyFQrHcEZqOtG1Y5pkdAc1GA97ZOoBXk3y3p4mjBe3rPcLBKsoFEhyOuIJSZ7LY6XO19GTGO7C9mg3nBriQrOC/ve1rhJODDNasR/j6kN7sXSvThEzafVzoQKoOjz/OlYQBeKb4M2AWOExTCWhoBiEW77OsUCHaitVJc3MT9fX11NfVIYTG0PAQFzovLvawFIoFJ9fK3JAOKSQhoZdeaTGRTMqyuVYMLImiJoWNG3gts41IpuvCZktJApt0zoE0QYxxgBMySQMepjLZlSsgletUmg3WMr+WV1xbygq0EELkPXF+vw9dV9FJSwVR3wTBCmTXxcUeikJRjK4v8/I1yevqIryxcTjvNnolVsGxaKhoKWseQ6WHjHEr84loVdFr0comopVN7i8+P3hyApKRD84W/iBoGp63vg+tbe34yoUlbFNcrRSWsMlUEk3TXDEql6c0FaEwoiqE7O0q892VjwhWIi0LDFW2o1hdtLW2MTA4yLlz51V0gGJVYyIJAINY+KWApS4gocp+VjpO9kfL3twrFAyN7C0/iXvsJnCISXeJiQJSzsOUxpnStVau+ycpHQLi2l+TakB0WXj+FAtFSSWos7OTO+94Hf5AgJtvvonamhpOvnxqIcamKAP/H/8nANKf+sMF26dYuxGhe3A6z5ReWLF60T3LtnxNIHlL8xAHa8cwHcGllJ+ziQqeGqlZ0Bb2EkFnMsCGijTnEzO4mXx+RLaDmrTMcaEnEEC0dODZeyC/qNN9Ca19nfv52Na48FRIkQPJdf2IYMV4IPcU+P/df0BUVpH+9P9e/hssl2Cl64RSKFYZJ0+eZOOmjbS37wIJo6OjnL9wAceZL2+DQrE0yU2iR6VN4zLoASRYGuHHivnDzEpGXdKgFW+RA8nAKRKQTCkZkVb2tckOJLLLTZWbVe6VdAKHAPMhIAkiKndLUUDJM3BPTy8jI6PU1dbiOA4vvXRChTcuRXw+WKC7k/6PfRJYWNFKsQzRdVegWGZ4hcNvtvWzPZSgL+3jK11tRK3Fu1j9ypU2dCHz4dtToW/ZBlu2ub8UlrAFgohAML+cjMeQo0PQvs51IcWjCO/MApLMlY0FKoDhaccgKl2HlGhsBePahl2LqhAyMnJNt6lQLAd27dpFKp3i0sVLIKCxoZHdu3dx9OixxR6aQrGg5IKHE9KmTix9AQmUA2mlk8sbetSO8n69vkhAysjx240WbkB2PCsFTRKQsuVhBnLKssdyHEga0C9NGgu+Gx7ENckushnPb1IogNIy5evvv4+NGzcQT8Tp6+9X4tFSQiv4+AJzy1qZFVWh0ssoVi/LtITt7S0DbA8lOJcI8vnL7YsqHgGYUiPtXIVV3zKRWQFJ+ANQWfA91XVkPOa+FsrmOGWdS+YPv5FfrLiEzXX+FOUmzYDW3JZ/LOoapiyRuyqCFW4YeGR68UqhWKn4/X5eeeVV+gcG6O8f4OVTpwgGAqVXVChWGBYSHRiW1rIQZlwH0tIfp2L2ZGQuFFvmy9nyryHzpW2mlJySqbwjzZggE+V+k0x9zJQrIHXL+Zmjm1KqY1lRREkB6cmnniaTzrB71y7uuvMONm3aSMDvL7WaYiEo6qpU3uTuWqI1tCz4PhXLB6F7lp2AFNBsdobi9Gd8/P9X2shcjXCzRJAFGUj4g4gCoVeODiGjowCIarezJlkHUk5YAopL2HLbCs4gUheI2aK53X1q5378f/KX6De9bpbvJLu92ob82BWK1YbHo6Pr4+chXdfRtOV3XlIo5oqZTYcZxVo2k1lreQxTMUsyBcVlhd3YYDxgO/daIeaEQOrC36YKwj7tpLDlzAEKEre80yjYdlLO5F0vn/S8xcErlislb62n02nOX7jA+QsXCAaDbNm8ifvuu5ef/PRnCzE+xQzkJ4Bk80kWev+NzXDx7ALvVbFs0HTkIoUe+zWbsMeiyW+StDUuTNMN7bbaCE1+g6StEbM86ELi0eDYWNWMJWNLicyX/h7fez423mXNNN0cJEAExh1IzuXzmN//GqJ9vfta2D1/CI/rQMIqaAtcWMKWLR3zveejOH2vx/jy308uly0Qs3MOJM+BewDQd+zFfv7JWb+/cQFJOZAUq4+LFy9xz913ExmLIIBwOMzp068t9rAUigXHQpKRknTBxHwp4zqQ1MR7JZMuEGvsCcdloaA0URRKFuQjuesWbHOKYyaF5HEnyvVagA4xtYnDwXU9pXHItVwZkTbtQptz/HVGquNYUUxZtRmhUIi2tlZaW1sxDIMTJ1+e0063bbsh35L27LmzjI5G2Ld3D0II0ukMR48dUwGRZVDYlntGd8A1RBY6DRqaF2SfimWKri94iLZXOBysjXBnfYSg7p5DDEfw/5zZmP1zPU6VbvGW5smuFlvCS7FlVJ7p2MhUYvx8YBmQO3/6g3kByfzB110RpspdTlTXuMvkHEjmuIAkCwQk5+wp7FdfQr9hF1pLB6KmHjnQWzQEUeiGzJ4XRF1W+BkbndPby29nRDmQFKuPy1euMDA4SE1NGCRExl4mnU4v9rAUigXH7WQ1dRv0pYig/PBjxfIkQ7GAVHhUugKSBMQkASkmbTTGj4/C7KTYNGHVV6TBZulnunubVrbMrNDdNCwtOvDBHL8vmWXwfVMsLCUFpHvuvhvbtunq7uLZZ5+b84VLQ3091aEQTz39DF6vl7vuvJOhoUE6Oy/S09vLDddfz9q1a7h48dKc9rMayE8AcR1IC0JBxyahStgUMzEhRFtDEvZamI7AcDRMKa5ZRzMNyZuahthdHafKY5O0Nc4mgmypTOHTJB2BNF3pAPtromysSPHj/kY2VLilWU8M1/BKrJLrq5LsDsd4qK+RiDlFsPRSxTIhU9AdzTRBSqRluhlI2RI2mXCDrfMlbFkHUv47bRW6igo+Fykxv/vPiA//MdraTfnMpEJEaFzMFhWVSF9g/Jzkn1tei6itd4ehStgUq4g1HR1TPt/Y4AqqV7q6FnI4CsWic8RJcEBzvRXLQZiRQoVor3QG5PiNN0fKouPSBhwJmpjsQEpMcBkVvhqdodvZTMd9aXKgcAAAIABJREFUbh+5f3Wgmww7CM6wVnlklJNOMYGSAtILL7xALH7tOuoMDQ8zGokAYJomHo9OfX0DL504CUBffz+bN21SAlIZFE7aCFS4EztzfjuxyUIBKVtaolBMia6jm2lAEtQcfm9tNy2B4uMzaun8W08zZwtKzPyawz31IxwaDTNmlSfkbAsluL1uDIBHh2p5aqSGjKOzrSrOBzv6eHvrIEjy+0/a4xkip2JVXEkHuJwO8quh+jm+6YXD+Or/QLtuB7K/Jx+aDUDu7lM67XZh03TXUZRbJjaGdBz0G28C3YNMZ7usmSYyEXe7qeWey2HbOBfOuAKSp/gzES0d+N7/++6uHQehaVjrNo+/XuBOmg35EjbVhU2ximhsbATA5/MRDlczOjoKQlBbW8voyIgSkBSrDgPJE46b1bccHEgS1LR7hTNWlIHEBA+SK/hoTBaQMjjYkC9jKxQa+wtEqYk4Mxz3xgQByUbSLy1sKdHm2MxEOZAUE5lWQNq/by9HXjzKgQO3Upj1JYQ7P3n4kUdmvVM7G6y7bt1a+vsHaGpqzJesZTIZAoGZQ7rr6uvxeJd+C8+mlvkt8Uq2tOUT/X0H70He/yD+F57Af/TpedunUzB51GrqaGxtQciVcWKZ789rMVis9xQUJre8+Fl2dz5MfKsXLw4BzeKyGSYtPXiFg1fYtOgxPrSmj5cyLTyXWUNGergveI6d/gitIZ2fJK8HYK0ngiWjMM37ub3Sdad8NbqHEU8F4Sb3+Sj1WLKfFr+BlHAy00SHJ8qBWldsMqWGWbOGptL9BOaNWX9GyQgcexpamkkK8ueC3PbiloGsqIRAENLJov1Es6Wo+vY9eM+cxATqa8Pwb1/EbmihWpeT/q8zAT8ZoLapCU8mhtXcgRYdJbPvdeQud/ShPpymNqw1m/Lr6eGaSe/RrqlHi40hChxqUyGBeGsHREdpaqi72v+heWElnidg6b6vgb7+xR7ConD02DEA9u/fx8OPPJq/RvLoOrt377rq7fl8Pvbu2YOma2iaxqmXTzEaiVBdXc2uG3cigWg0yonszTyFYimzXJw9SkBaPThMdgjZSLyISYJn7spHTvgXYJDpr4umO+p1OS6qmtmjLpUtabOAyb7xq0OFaCsmMq0Kc/JlN+foqaefmbySPvcOIC0tzaxbu5ZDh5/lvnvvyT9fjkg6Mrz0w1SbWprn/cLXVzc+7ZVZN1KyvoWxedxvfV3T+C+6zmAiDdHIvO1voViIz2uhWaz3tD8c5YGmIYKdDnFPFU4qhQE8M1LLo0N1RWVrWysreXvLIPsCPWzx9POT/ga2Vg8AoFsJBvr6qfGYPLjpEjY6nz67dlJL+00VSdbVROhMBjjdEwNiRa//U6SdtcE0nckgvRk/Wyp1PrrGzfA5NFJN3+DgvP5/zMS1+ow8kUj+ZJ7bni+ZQDRUgdCQ/d1F+yksKktbNjow1NMLyThcOD/lPvTREbxAJJ5AZiz87/gIMjKCfepoft/G2VfxNLVhrXUFJGkaUBVm7P1/SOaLn4HYGKJtLf73fQL7pecxv/+1md9YKEwgWIndeXZJfD9X4nkCVu77WglUBINFmZCWbROcRcn6mo4OrnR10d3dTX19Pddffz2Hn32WHTu2c/Lll4lExti3dw9NTU0MDAxcy7egUFxzloOA5DqQlv44FdcG95ic6EDKijpT3GhPSgcbSUjoZR8n08k4A5h58SrnQEplS+FMHHzMft4umD6XSbF6mfa2eybjlnrs2nUjqVSq6GfPnj1z2mljYyNbt2zh8LPPYVkWlmWhZe+IBwJBFRBZDhVVaHWNOL3FNnahz68zS3onlK/ULJ+SH8X8c0fdKO9sHUAAP9/37/jM7r/k0+c38NfnN/DIUP2kzKMziUo+c34dvxqsI6g5vL+9H7/m/vEL6e4frLsbRvEI8Aub2+smipWSB5sHsSX8pH/qksqudIBDozX0Zlxn49lEJT/oa+TwaJhfDa6Q4zcz+ZwpEzGEz4/wepGxseLFv/R3+ceiItuvo1T5ay5k2+NFNLa669bUgc+Vo4xvfh6n2y09lsFKpG3jdLpdGkW4Fs9NrwNA27AFAH3XzSXflta6BgCn90rJZRWKlUgsFuP2229j27Yb2HbDDdx28CCJROKqt3P+wgW6u7sBCAYDpNIphBBUVlQQibjnh77+fhobVWm6YuljLwNdRiKXRVaT4tpgTfF551xBxhTSz0tOIi8wlevvKVxOz/4AGBJ+bUez+8oKSAUlbRO9GTqi7ARSHcGgnNktrlh9TKs2dLS3c911WwkGg9x/33355zVNkMnMvjW3x+Nh+/ZtHDp0GDM7IRkcHKKtrZWurm7aWlvoH1g8R8ByQVu7EQDn3CtorQVhm5VV06xxjciWsMloBFFdg6itR16e2rGgWN6sC6ZoD2Q4m6jAcATXVSUJeyxOxKroz0wuM/VrDvc2jDBm6vxT3yZSWx/Eea10OYSN4PHhOk5Gq7inYQRbCjZUpKj3mTT7MuwLRxnIeKn2OewNx3h0qI4Wv0F/xkeDz6TRb3IiWkVPpvyw5ucj4dILLSNkYYh27rmCrmUTO5jJK53YJ15wc5BC2Ywia/q6exjvzCa8XgiM/1+LbEi203sl3zENQA71F4lS2vY9iLOvoG/dUea7AtHmCkhSCUiKVcqx4y/R2NhAdagaBJw9d27WDiG/388tN9+Mx+Ph0KFD+H0+jILui5mMQcA/c4QAqBiBxWYlvq+rfU9VpiCQ9k7bkWopIJE0NDfhLOExXi3q2JueipQHQ3do8o138fUnvVTYAl9Qp8lTrHqOAP6Ul4AtqPR4aQqUdpZWZTQCZu7cK9EQOEBQ91EZ9FMJBA0NDNCrK2kKBPClPARtrUh8cgQEZHlh9BJJsLIB/xI5jtUxuHDM5Eyf9gqgq7ubru5u9uzezenXXss/L6Wck0Oovb0Nv8/HTfv35Z87euw4u3fvYv26dSRTKa5cUZOFmRBrN+J73+8B4Fw6B697PZAVdSrnt/14LkTbGehFr65B1NQhGprx3PEGzJ9/D1JXf2dUsfTwaw4fW9ODV5PYEvSCPxy310X4L2c3YMlxA6NAcnf9CD5N8vhwmFEn6JZJ2eXffxsyfXyn1+3s9xvNA9xSG+W9bf3oAh4eqmdfo8X1viHe2DjMHfURxkydAcOt7D4dX6AuhEuVqRxIo8MFjyd3MJMpNyhbhMJIy4RSWWa5iabX5zqPcuS6rGXSEIuOb7/nMhQE/WsNzfh/55Pjr5dxbGhNrtPJ6esuuaxCsRK5+6476R8YYHBwkOHhkaJytulYu3Yt69auLXru9GuvMTg4yJNPPUVTUxN79uzhWDZnKUe58wMVI7B4rMT3NZv3FBQ+Mnp4SReI+QJ++vv7l/QYrwZ17M3MmBZiVFoMyPEbeqNamCrNx8XE8KTOawBRrYag5iXqpBiIlG5YFdEqSWvu9a4tJR4h3Pw6J8PAmHv91SiCUNnAQDTCQCRJRAszJqBd+PIjiEubkNDLOjaT0qEvvjTO+eoYXDqUvIV07PhxdF3H53Mnarquc8frbufJp2YX1Hzp0mUuXbo86fnDh5+d1fZWI/oOV3yzT5/AufAaTn8PaBrEY4h1m9zHBReZ3t/8HZyui9jPzD74PE/OgTTYC5tvQKtvQuw9iL7rZpzBPuynfjX3fSjmjesqE9xZP8oLkWqOR0NZY6tk4tRhc2USryYZNT2kbY2o5eF0vIJd1XHWV6Rp8Jn0FbiQ7m8Y4c76CLaEY2MhCGSNtVchIBXSk912S8CgJ+3jVKySmhqd631D3JYtY6vQHbZUpnAknEkoAWkicmSw4PFkAYm0e5EjfP68mDQjVtZN5PUi6t0sNJmII/x+pOOAaSDj46Vy1tHD7j4cB5mI4dlza9HmhK5DRZWbuzQNoroWaVkQj067jEKxkjl0+DAN9Q20tbaxfds20ukMA4MDXLjQOe06ly9f5vLl4uus+vp6vF4vpmkyMDDA3j17yBgGPu94vGogGCCdnr3DXKFYKDJSolGeg2KxmJyIo1jJ2MhJXdgyOFhIUtMUqeVK3MrN9CrMSkojqciWohWun8FBSEhId5+aEBx3EjRqXjzZoOGotAmioZcRPJxQ+UeKKSgpIG3etImtW7egaRqWZaHrOl1d6m7woqBpeN/+IfQb9yNNE/M7/wy2jfGPfw1C4H3nh90sqWAlJLJBwhWV6Nt2o63ZcE0EpJwDSQ70IqNjaFvdNuLgZppclYBUVa0mhgtIjdfkvW19BHTJhoo0d9RFuJAKcmMoxplEJd/vbcLOCkrbq9xJ/be6W+hKj5craQLWV6Rp8hlFAtLOanf5L19uZ8zyQi5ov0SXrek4OhZiXzjK2mCGXw262UkXzVosCR4BGUfw6XPr2VMdIyM1EvbSL6eYT6Zy85R0IKULRKMS5WtA3oEkPD5EndtiHNt2HUhGxnUwGQYyk0ZoWr601fzmP6LvuRUmCEiAWwI7o4BUA7Gx0u4ohWKFkskYdPf0MDwyQkN9PW3tbWzdsmVGAWkqWltbCIeruXChk1AoRCqdQkpJPB6nrq6OkZERWlta6ey8uu0qFItBGic7dV66fxuW7sgU88FUXdjSSAw5fcbR1WcgjR9VKWyCUiCEKBKQ4tLBI2BIutdsJg790iQiLRqEFx1IYpNBp6KMcO3pxC/F6qbkrKutrZWf/+KXHDhwK4cOHaaluZlgRXAhxqaYgGhsRb9xPwBysG98ci4lSJmfiInKEDIrIIlsCYkIhRENzW4uyVzICUjpNPaJ5/Hcfj9i/WYAtMYWROuasvJKtK078H3g45g//Q7280/ObUyKstgXjhLQJY/6dhMevMDe6igtAddVsjccI27pnE8Guad+lHUVaSKmh+50cR7GYMa9W/2+9n5qByyeGKmlwWvQ4DN5OVZJZ8o9N2gdGwCQzuzuXFhS44uX24ucTgYeLiQq2FqVpDvtJ+3oHI7UzGr7K44pBaSCDKSxkcnrpMdt1tIsLSDlMpDw+RC1DfnHWIEiB1TmHz5FY0M9hZ4oZ3jcDWV8/2uIQBDvA+9G1NQjs8HbkxACqqqnf12hWAXs3rWLisoKMukMwyPDvPrqaWKxWOkVJ3DmzFn27NlNa2sruqZx4sQJAF5++WV27boRhGB0dJTBoSncigrFEsNcBv4euUQyYxQLg43MO4pyGDhkZhBgrlpAKth8Sjr5Y6xw/SQOBpKhrJz1iuNKQEkcNCCDJIlDRkoqyjhG00pAUkxBSQHJsiyklPkuaX39/Rw8cCudnRfne2yKiRR0QHMun5v0cl40qqzKn8JEaHyCra3fgj1HASnfhc00sI8exnP7/e7zqSQiWIG+6yasvi48d70Jp/MszsWzU25H33vA/fem1ykBaYHYUpHCRuOFt/7fxB//FY+/8AtqvCaDGR8fX9fFHfUR7qh3y8NOxSr55eDkrmkDxvgx+MamYZ4YqeHWWrds6bV4pftCsBLfez7qPp5lCRu4IlLfhLDuV+KVbK1K0pUqPzB7VTCVUFfYVW0qgSl1lQ6k7DKipg7hyf7p8PkRtp0/9wCQTCCM4jD/onK64cF8CLfW2oFz6ujU+6usQug6Tmxi5z2FYvXg8egIwLRMTMPEMEp0S5wGwzB47rnnJz0fi8d5+plDcxylQrGwTNXxaqmhpt2rj4me+7SUMwpIOcGpXCm0cEtpHGzcTmyF+zVwiGjjW+zJOpHSOGgILjlp4tIhI8rbq7nEhVrF4lBSQDJNk472dmLRGHt27yIWixMIqMnbYiCyWQXO6BDW4z+bvEBuEpcL0vb6EC1t+Ze1DVuwj8wuuypHroQN00AODyCjY4jqMM65V9E2Xoe+8yZkfw+eux6AuyD9qT+cekOBrIttiuwWxdzYEYpzd/0IT5lBcr16AprNmmCaK+HNZHyV6NffyMihRxkx3c/zx/2NfKC9l9OJSh4bqsu3vJ/ImFV8yjhYO8ZtdWMMZryciLqigahvzL+uZdu9XyuOjoUIeyyeXWFd1OaKzJaCygnfp8z//H+nL/8qcCBRhgMpX8JW15R/SmgaVFYVCURTUlCqKocHkJaJNE30Xbe4QvP5VyetkhO/ZXRs0msKxWrhyIuuwBoKhWhoqGfP7t1UVAR57PFfL+7AFIpFxJqUNrP0WOrjU1xbJGBNEIvi2NgzuHzGHUhXn4GUQWZ/FxMykCRnvJPl1UzWIXXUSSCBDuGbtMxUGOpIVkxBSQHp6LHj+Hw+evv62LhxA4FgIH9Bo1hgsgKS/cJTxZO/LDLhlrBp7etwXjmG7+P/B1rDeGtAbf2WuY8hV8KWdTcYX/8s3t/4INbTD6P1d+O97214f+O3Sm5G+F0BSU7xPhRXT0cgzc01UTKOYH+2VO2d/lMYVU28Eq/i3oYRNAFnwzcAIFo7isLWTycq+U9nNk1yHE1G8OxoNbfWuoLAW5uHMBzBN7tbMLJd2URNfX5pp6/rmr5PU2r8aqi+9IKrDHmlE/Ohb+FcOFP8/EDv9OsUZSCVdjXkvvOFAmH+tTKEYGkYCJ8v36nRuXgWfcs2fB/6AzL/86+QAz1Fy4vqrICkHEiKVYzH46Guro6G+nrq6uoQAnp7+xZ7WArFomIDjpRoZYQALxZq2r26MKXEmvChj0l7xgjHnHOoXLdaYYlcWjrYIudgGn9eAl3eyTvNSAdDSuLZvZVbmmZI5aVTTGZaAamiorirkd/vp7u7Z5qlFQtC3v0ztVvAudKJTCXxHLwH0dRaJB45PZfR2tai7diH8/KLsx5CoQMJ3Amq8YW/AcDu63LDvO99q/uaMXU3F23DVkSz64wSHu+UyyhySN7T2k+Dz+S7vc0MGsV3DBp9Bvc3DLOzOlH0/PORanaH43ygvY/Do2FuqxtjIOPl2a0PAm7nLVHXWJSJVVo8cvlRfxMnoiF+b50bpv/Dvkb6jXHHkqhz83GsX/8M65lHr/4tK2aF/eJVlqGkri4DKV/C5nM/67wgBG6Idgkyf/8X4+HqgH30EPqWbe42G5onC0jZ/DblQFKsZu668w4GB4cYHBrk7LlzmOV8VxWKVYANaIs9iBlwlq62pZgHMjiYE0SZJA6pGYotc84hWWajEIvxnskJnPzeymlXk5gwvkwZEqcAUkoKVUzBtALSwQMHmKq9t4vkkUcfm7dBKaYh127XnMYtEBvD+OY/4v+df4+++Yail+wTR9Da1uJ790cw/QHsF58puTvP3Q/gDA3gnDxS8GSxgDQR+8lfIq904nnb+9HqGtxStUKXUSCI78N/PP57ZdXkjaxwNCT3NIzgSMGg4aXBZ1LrtfhhXyNOwffNpzm8qXGIPWHXWfbJjZfpSvl5OVbJsWg1B2oj3FEXQRNwOeXnsaE6wl6L/oyPS6kg5/T1vC14itvq3An49/ubsWpbxvdQWQWzzMTqSvsZyHg5HXfHUoiodR1C9okjZQkLisVhtl3Y8usP9SPa1riPyylFLcxcApxXjmN855/xveej+WOmEJETwGNKQFKsXh559DF0Xcfn8+HxePD5fOzbu4cnn5pbObpCsdxxpp2jLA2Ub2N1YSInCTkGkn45/fVVbvly87ys7CxBAHFp5wUouwwBKiKt4lK3MpxFWnY/CsVEphWQHnlUOQeWGsKbKx+b/mQkuy7mHzv9PWhZp4997DDalm3om67Hc+cbsV85NmlCl8Nz1wPoew8gwrUApAsEJOktLmGbCqfzDM7ZU2i33ImoqUP2dY+/h+rirlmionLa7axU9oaj3NswOun5yyk/R8bGs33e0DjMrbVRxkydJ0dqub4qwcaKFB3BDG9scrtqDRsefjbQwCvxSiZeSPXbIT5/qZ33tffTmQxwSWsi4Bn/yovK0HjYekOz27WrzNBrU2r8t851U76WK2GbsvOXYulQKPqUc/fLmiwgkRWQyMyuFFUOuqU4EwUkUd+EftPtyOgYTo/qwqZYvWzetImtW7egaRqWZaHrOl1d3aVXVChWOBYwdVrj0kD5NlYXbqj15E/9VTn9Dbac8FNuBpIpJziQpPvEVPudiOtAGqdPmuiUFq+SSgpVTEHJDKS9e3ZP+fzRY8ev+WAUJSjlQAKQEhmLIkLV2CdeQLv/QWQyAekU5tc+i7z/QTy334//4/8nmc/+1ym35bn7geInKiohmS2RyjmQSnSCyYkHIjxBQKoqdqsQrHTbdU+cwFaF8Nz3IFpjC8a3Pg/ZfKflTEcgzf0Nw2ytSmFJ+NeeFsIei1qvyW11Y7yteYgtlSlOxKo4E69gRyhOxhH83YV1mFLj0GgNQc1mV3WM7aEEg4aPhwfrSDn6tPscNn189qI7yRftriAooxFEdQ0iG7aurd+C7yN/gnXkaawf/8uc36dW24AcGwWrHFOtYtGQEuPbX8D7xnfiXHitvFWyZWvScZDDA+MvzDIMX0bcluGFuVkA2pZtCI8X8/GflDzXKBQrmba2Vn7+i19y4MCtHDp0mJbmZoIVwcUelkKx6JQ76V4s1LR7dTEm7avuWHa1IdpWNmzCwi2Zy4k/5ew3gyRW4JEawiIjJZ4ZcsQcyit1U6w+SgpIg0ND+cea0GhoqCeZVMHHi0LW/VOq3MT41ufxHLgb+4Wn3FK1AnHGevTHiNp69O17Ec3tyO6LJd0H+o03YT/3hCtO+fxIx5lZxAJkxHXY5FxMebICkvnQt11H1A27IFCRD9YFoDKE/3f+LO9K0Hff4o7Rtt1xXA1CoG3dgRzqL57wLhiuxVpD8sH2Xqq9No6Ew6M1vBwbL9+7nApwf+MIN1bHubE6jukIvJrkhUgIU45X+accnWcjNTwbqZliXzMjqt3Pwum5gl4oIG3YCoBn/+1zF5A0DcK1yMsX5rYdxYLgnD5B5vSJ8lewTPD5IB4rKoGTmVmWKhoGMhFD1DYUP+93O33K0eHZbVehWCFYloWUEk1z/w709fdz8MCtdHZeXNyBKRSLTDmui0Vl6VbXKeaB2CwkwwwSDSg32c7Kziks6WDhCjzu+uV9F84549dqEhiTFk3CO60LyZKyKLhbochRUkC6cqW4i9Kly5e55eab521AiukRWQfSTOVjALLnMub3vjr1i46Dc/Ec+va9+H/33+N0X8L4wt+Ov56duBXifdO7wOPFfvphGq0Rqi+c50QJ0UlG3IlfLiw7/x6yApKMR5HJbNe45jaci2fzy+g79yFq67GOHkbfdTP63oP5QHA5NopzFRNe7zs/jL5zH07PZYx/+puy1ytFg9cg7WjE7clfoXe0DFDtsQjqNu2BDJdSAbpSAaq9Ns+OVvOj/kYmXlmciIU4Eaui1W+wMxTnxuoYtV6LY2PVk7Y/W0SVK1jJ/m64fud4/lR2YiKdud8vE+E6hKbhjA6VXlixbHGG+4vzrVKJ6RcugRwdRrS0g6bhuf9BnIvnxrs0ztLZpFCsFEzTpKO9nVg0xp7du4jF4gQCk/9OKxSrDVvKJS3SLHWHlGLxSUsHDVG2GJpbzshlH2UdSZkyQ7ivyOL5YwwHTVrUiqnlAEMdw4ppKCkgTSQYDFJVtfpya5YEJQKsy0WOFLjK2tch6hrxvvujWI//NC/8WC88jfXIj/D/+V8hPF70rTuwn36Y33/mPwBwWtuI4Uzf/0L2XkHGxtC37cH6+b/ly5kKBSTS7uTQ95E/wfjuV9A2XoeMDKN1bHDH8PhPEYEg+rbxMkrPgXswyhSQRH0T+s597vtsWwvVNRCde0vwnaEYv9nWT8LS+dylDsas8U5yYY/JTTVui3tbwpDhY2NFmo0V7ns9NhZi+iseQW/GT2/Gz6+G6vBrkswM/8dXTcDtrOhknVj5csKsgIQzx6A8IRBNre6mIso5shLJZZbJwb4iccfpmn1OkRzsQ+tYj+f+B/EcvBcO3ot1JBsQrELYFauco8eO4/P56O3rY+PGDQSCAY68eHSxh6VQLDpLPdpXlbApSpHGQcd1+pSDA0hkvpuaKyAJMrM82p5wouzTKqcVkCZ2lVMocpQUkN721rcU/W6aJufOnZ+3ASlmIJ+BNLc2vnKCO8Rz5xvR2tbg+8DHcXouu8uMjUA6Reav/hzf7/05onUNFYFxMaPGYzEwoaV8EY6D/dLzeG6/H23rDpxX3MwsUeWWTcl4FDk6mF/c9+6PFK8+2AfRCPZLzxcJSBMdTTOh73Kdcs6VTrQ1G9Cv24H9wtw61+wLR3lHywCOhGqvzZubhvhWT2v+9Y0VbnnnMyNhHhmqI+3o1HhN9lbHEEJyOV3unWNB5hr3gBX5sqAhpOMgcg6knDA5RweS98EPoO+51d3HiHIgrWTkULEDSQ72znpb9qmj6HtudcWjLPljVTmQFKucjRs2cPbcOQDOnj23yKNRKJYOS31qq7wbilKY2ZK0cmd1NhIJGFnBKXeMXW32Ug4342j6b5JRprClWH2UFJAe+vFPFmIcijIQZXRAKwc5wR2i3XjT+OO2tdllsh20bAvnygU8Le1c/4F3wTN/BUCN15xZQALsU8dcAWnTDXkBiVC2y1g8hn38OTcryTLx3Pc2tI71+XWdc6+4/5495YaAB4I4F15D33wDhGthbHIXs4loG7YgbRvzh9/A9wf/F963vBfPA+/B+PLfF3WrKw/JrlCcd7UOkLQ1/vlKG+9qGWBndYJ3OP08OlTHmOVha6WbC/PiWDXpbLh1xPTy2HDdVe5vHghkg1dTSTeUPJuBlBeS5igg5cQjUNk1Kx051A++AjF0DhcZzvnTyEx6XDRyHDdcH2Ydzq1QrBRC1SEqKytIJKbumqpQrFaWegbS0h6dYing5gtJrDLlUBv3uCosYXOQc3LjpeX0+06KpS7TKhaLkgJSwO+nra0Nj7d40TNnzk6zhmLeKDNEuyQTWrWLbAmT9eyv8dx6FwAy6go0XuEgz74MN72ObZefzK8T9pTusCX7upDpFNr6zW6nNdyyKZlMgG2B7QpEAMYXP4ODEj6fAAAgAElEQVSobcD/v/2lO5Ynfpkfq/n9r7mBz9Vh9M03oDW345QhIOEPQjqFHOrHfvIXeO56AKFpaB3rsa9CQNpckeSDHb34NIkt4QuX2+nP+DkeDfHGwDA31cRoD2SQCNoDGaKmTl9mZnFtMSjMlZGJ2HjAeUVWQLqGdxomipSKlYUcHkRmUjiDfViP/2xuG3McjK9/DlEdRt+yHX3PrWhNbWWF9SsUK53q6mruuftuDMPAcWS+aenDjzyy2ENTKBaVpS4gqam3ohQGkiQO5fYsljkHUvbockvamFPQdUS6ZXQTRSgNOG2rplmKqSkpIN166y2MjY2RSqk7wYtOvoRt7pMqp7cLrbUDZ6g/H1Bt/fzfEKFq9O17kYN91HpN/mj9FbzyAkP/8gQtcjw/qMZbxunOcXAuX0Dfup3AX/4P19VUFZq2vEmODmF843Pu6wWhvDmRSbtuJ5AtYzvzcsndC38gXwJjPfEL8AfxHLh7PPunBH7N5s1Nw/lMI4BLqQD9GT8AL46FuL4qwfqKNG0BA0fCiWgVjw7VZmPtlhi54NV0CpmMo2WDi/MOJO/cRC+ZSiKCbs4S8ejMCyuWJeZD30Jbt9ktcZUS47P/9ZpsV1654Bq5G1vQAVEdRqZT11TUVCiWI8899/xiD0GhWJIsdQFpaY9OsRRwgO9ZI2VnGNmAlDJfsmYhcaSc03chMc3aY9Kmu+ziOsVqo6SAZBgmx46/tBBjUZQiH6I99y+08c9/Dx4f+t4DaPc/mH/e/O5XMH/8L9RaY7y7tZ+g7tCX8VHHGI6u8aNbPsnbn/1MeQISrvijb90OgKhxy7js7ukDd52zr0z/Wu8VwA3+Lsuu6Q/AWLYUz3Gwn38Sz4G70dZtQt97APvo4WlXrdBsPrKmh45gcYjvhWQw/zhue/inyx1U6hZ7wzFOxaoYMb0TN7VkEP6g6+owMuOlQf4AoiJbyubxuC3ajVkKlD5XWDN/+h018V+h2C8ewn7x0Lxtv6j0UZWvKVYxazo6Znz9SlfXjK8rFCudpe7wWerjUywNEldxpMjsTyYr+eQcSHM51lI42FIiRPGNb3OG0jaFoqSA1NvXS0d7OyOjo8iCSWEqpWxtC43w+pCWeW0m54YBhoF95Gn0HfuwX8yGS0uJlkrwu5u6qfVanI5X8NWuVgQQ+ou/wdJ8PHj4M9R4yxOx7Beewrl8HvwB/B/9UwCcM6dmN+ZoBBkZQVu7ibyPfyb8gaJJqMy6YrS1m9DWbkJGRnAuvFa0ilc4bKlM8vrGYZr9Ji9FqzgSqcYG7qob5bnR8KTdJGwPT43Uzu49LSQBt6QPyP8r/EGoKOiqGKiYnYDkDyB0Hfu1k9jPP1l6eYViCgoFJBWgrVjNNDY2AuDz+QiHqxkdHQUhqK2tZXRkRAlIilVPOa4LweI5gSyhbqQprj02hSVsc8s/crfhltL5J1ROLPUuh4rFpaSAVF1dTUd7B2ZB2ZSqvy9GtK3Fc89bMH/0TYiNTV5A1yflDs0Kr/eauI+KSKcwPv/poqeuq0pQ67U4Ga3kX3paAOHW3HpdoSGOn3qviUCWLtWSEtnXnc9AAnDOvzqroVZ7LH7/kT8gHWrg9Jo0ZwYdrqQCOFONwedDaBpO4STUyCCNDCLrlNG2bJ8kIL2paZgDte5neGgkzE8GGvLvsTNZMatxLxVEIIjMuMJRfnIernGdR7llgpXIaGSq1Wfedi70OKWCXhWzpyg7y8hMv6BCscI5euwYAPv37+PhRx7FyTY58Og6u3fvWsyhKRRLglJX1QJ42U6yXV+ca7ekpgQkxXwgiWfdQTZzyz/K4QpIxSgBSTETJQWkutpafv6LX+QvXhST8b7jQ2iNLci7H8B66NsAOKEw3jvfCj4/2votGF/4G2R/zxx35Lv2AtIEarwmb2x0J3GPDtcViTPmz76L/+A9nIkH2R+KsCMU52QsVN6GpcT45ucnuYKuhrvrR6gzo8iRCG0VknvWQdLWOJeo4EyighHDy6WcoJQNjJ64LxmPIerc06S+bTfWr35Q5GRaF3QFlu/2NnF0LARLMctotvgDkHN4ZIUkUVNftIgIVszuT1HWxSSTiRILKhQzEBtDWibC41UOJIUCqAgGi66/LNsmGFzeNzMUimtBqYmzIyVDWIviQtKAMeVAUswDuhCMSDdGxEGSlHOXejLSIST0/IxHZretUExHSQFpNBJB0zQlIE2Hx4Ooc63m+uZtODv3IwIBEne8Ab16vKxJW7cZewYBSazdiKipxzl1dFq3kvB4kfPYlWhdMMVvtfdR5bF5eiScD4vOYT/3BFWXTvPr4Wr2VEW4v2GEV2JV2GWKLE4ZwddTsSGYosZrsr8myrAd4Evv+Tprnv8hm078mK1VSW6sjnNjdRyAs4kgX7nSls/jkZkMPs3BdgQ2oqjGV9TUoe3Yh3PyCAAe4dDsN7ic8nN0rLyg7WWDEFM6kERoQkleIDhxzfI2n53QyJQSkBRzQEpkZBTR0KQykBQKIBaLcfvttzEyMgISamtrSSTUeVahkCUmuBKISweNxXFTDOlqAq649kg5npvkIIldg6M7ik0DXgwp8QBCiGvibFKsXEoKSMFAkPvvu5d4PI5T4NR45pn5C1JdTmgbr0foOgAiXIvvXR8GskFno8OIWtfhMWPnr+oafL/1Cbdr2Fvfh+y9jEzEsR55CDk8ML6c1zeeYXON2RuO8vaWAQTww75GnotMzvrJMWz6eD4S5kDtGAfrIjw1UkurP8P2UJxHh+ryJV+t/gwPNA3x6+Fazs+y/Kvea/DhNT34slbgE6NBUobkzM63cPLh56Bf0ugz2VKZ5JaaMbZUprinfpTH/OsAuG70Zd69uZPutJ8vXW53XTiAfe5VtA1b8dx+P2b3RWK//ae0/uhz6FygOx2Y1ViXNNn3LXPHT15Aco9LGY0gqmsQ4VqorkFUVCH7riJjI1/CpiY2irkhI8OgBCSFAoBjx1+isbGB6lA1CDh77hwDAwOlV1QoVjilWrk4QMq9dchCe5BS0iEjtAXdp2J1YDLehc2WEBdzN3gMS4uNQA8ZWvDhRygHkmJGSgpIZ86eXYhxLFv03TcDYHzts3je8l60uob8a8Y3PgeWif9P/3O+A9kkhMD71ve64lEygUwn0dZtBkCODGI9/KPxZb1emKUDySccTCmy4o6kwWtya+0YaUcjoDncVjdG0tb4ZncLF8oQex4erOPGUIx760c4Hg3x8XVd+DRJdzrAq/FKqnSLD3b0Uuu12FCR4h8urGXILK9NfI3H5I1Nw/x6uJYHmwfz4hHglqhdOo++fQ+iph4ZGWbQDhK586OcuHiKT8R+wD0NI9Q5r7HhoQ9Tm+gDDTZWpDlYO8aRnJDS34MjJfqWbXje8l5kRRVrd26Ck4/RnZ5YCbwCyL7vnAAp01kBqcoVCp2L59Bv3I/WsQFt6w60dZvJfOY/li1YinwJm8pAUsyNXJC2KmFTKFwGB4cYHBxa7GEoFEsKu0QjFQd3sr0YE+EEzopKQFAsHdIFPdccJNFrUMLWKTPcKqs4Z2eo0734URlIipkpKSAJdQJ0CQTRrrsR5+UX3d9tCypDaNftxOnvwTl/GuMLf4uoa8D323+MHhlCDvWDpiFtG33XzUjTxPrl99A2b8f7pne5k3pNQ3i92OdexfzG50DT0W+9E+/r345oahvfvxBuF7ZZZCCFPBaf3HCJlKMzZHhp82eo9BQr1v0ZL1/vamW4TJEn5ej8crCed7QO8qbGobzI0+rPcCkV4GNre6j1WgwZXhp8Jvc0jPKd3uaS29WRfGxtDw0+k+2hOB4BXSk/HUE3UNcVkM6hb9+DtmMvzqsv4Xnd69H33Iq151a+/deH+cT6Lvbq3ZBwLyC+29PMm5sGeX3jMGcf+RbRN3wQ+9RRtPT16Fu2oW+63h370GmAFSkgiWxpWn5SnstAyjqQnL4utI3Xoa3dCD4/wutF23AdzqvHy9tBLpNDOZAUc0RGshNlFaKtUCgUimkoJQxJJAZyyhbl802/NIDyrqcViqshUSAgmUj65dyzcRM4HHJiXMbgxmweUjldDhWrl5IC0tatW/OPNU2jOhRieGSEoaHhGdZanoiWDjx3vAHzoW9Ncl547noTngP3wDs+iBwbJfMPn8L7jg8hPF6sI0+7C6USyO4Emf/+KRrr60gCOI7bma2mDs/+2/Dsv61ou9KysE+fcPcpJdgW9jOP4rnlLrTmAgEp55wpY1JV5zVpD6RZG0yzJpChPZDGo0FAt6j1WowYHs6OVdCT8bMjFGfE8PKD/iYM5+rstkfGqrm5JsqecDz/3HVVCbaFErT4jXwXsz9af4Vd1TF+NVRHxPROuS0Nybta+9kZiuPJDsMjIGrpfKWrjT/beImI6SHt6PDS83juegDPvW9F3P9g0Xa61+7ne30Gd7SmeX7fh+g9eYbz0QvYEt7f3s9vdH2PL376BDKVwvEUj6U1cQXTEQxkVuAf/Vyo+AQHElkHEqaBc/k8+rbd+VW0zTeULSDlurCpDCTFXJHDroAkVUc/hUKhUEyDWSpEO/tjU8Zk5xoigFecFAGqFnCvitXCkDMuGF2UxjXLKnpFuvMCI7s9lXysmImS59RDhw4X/e7z+dh2ww3zNqDFROtYj759D86ZU9hnXnb/CiRccUTfsS+/nAjXItZsQN98A07nWewXnireUCKOCFWO/z5FMLHxr19G1DfinHyxuHV1Fqe/B33rdtfZkUoiGlsAkMP9M76H/eEx3tk6OOVrf3d+LVHbUyQUPTVSO+Wy5SARPNTfyCfWj2flrM06hZ6PVPPjgQZA8MxoDe9qHWBvdYzHhqcu5XtD43CREPWDvkbe3DTE93qbSNo6/9/59Ti5c2Q6hfXoj/G8/u3YnWewXzmOqKzE+4Z34PvAxzn2cAvHTBPvlrdgHP0yACdjVZyMxtlZneB9tRf4dqoF2X3J7RoWCOKxMjTHu+gx/EWd51YKIidA5h1IxRlIGBmci2eLBCR90/UlMwby2887kNSkXzE3nNdOYD78Q+zjzy72UBQKhUKxRDGQaEw/0c05lCwknjKv60T2Zy6T55i0ieKwAtM0FUuAS3I8yqSUiDobMtmjXzmQFDNx1aK8YRiEQitTVXeudAKgbdiCfscbEF4fmc/+F0RNHSIUxn7tJOge9M035HOKnEtni9rAT4llAuMikvmDr+O8cmzGVWR/N2zdjtbcjnPxbN6NJGfo5FbtsXhz0xCWA48O13ExGcQj3JIwoOwMoqvhSjrAkUiI/TUxTsUqCXssziYqeHiojlwB+MuxKt7WPMjecIwnR2qwpGBbVYJLqQAJ28O2qjh31EeIWzqDhpeT0Sqej4R5PlKd30ZmgjvKPvI0ds75BRAK47n/NxCahmf/67COZkPe8zkqgh/2NRH29rCzOsFzkRTnk4LM5z8NhsGa+25Hdyx6ZAMrkmxXulxZUK4bm8h1qzMNnDOn8D7wbvf3VBJRW4+obyoOcp+OfAaSciAp5ojjYD/9yGKPQqFQKBRLmIyUM8pCORHIRF6VmDPXafN8TOoVihzDZd/anR3pXED3vO5FsdwpKSDt3bOHwtNpIBhElhJMlilyoAeZSqLvviX/nOeuB/IuDfv4c4hQ2BWQ1m5y1xkdKbld41++iL73IJ69B9ztdJ4puY7TcxkAsWYDXDybz0NyBnqnGz0PNg8S0CXf623kyNh4F7Xv9TYxaExdOnYt+FF/I6diVZxOVDBVamDG0TgeDXFzTZTf7ujlpWgV72wd5NV4BT/pb+TdrQMYjuBLl9voNwrzh67CCRQbI/PXf4b3zb+JvvsW9M3bgOIg3qSj81wkzNrgALXe7Al4bBSA9hH3M+nxtwBxVhrCnxWKJjiQ8hgGJOM4g31ojS3YR57G87rXo22+AbsMAUkEK5G2rXJrFAqFQqFQzDsGzowd1vIOJCnLvpxMSocAYk6ZSc4KnSMpVgfKgaQoh5IC0uBQQTmUBNOyGBycukRq2SOlmwNz3c78U56D9wDgdF/CefUltOtvBHDDhmHK8rNJm73SiXWlE6REVIfzosVMOBfd7nfahq3YT/0KrakN6TjIwckCUkCzeWvzENtCCS4kAxwZqy56feLv1xpLapxOVM64zI/7G6jUbbaHEmyudN0vmypS3Fk/SkB3+G5v0wTxaBYYBvarL6HvvgVtnSvw5cKic0RM95Cv8RaHznVEzwPQ1XojnDk0t3EsRXJd2HICz0QBKdvdz/jS3yEaWpCxiCsgbbwO+7knSm8/WAHKfaRQKBQKhWIBSOLMGKSdiz24moyYMWnjFZ45ZSYp54ZiOZOWroCkhFDFTMx4jqyoCHLlyni+ja7rBAIBbHvlnh6tx36KHB3GuXweEQq73dIA86ffASmR0QhQkCkTKe1Aym/7oW+VP5BkAk/XedYGk5zxehEt7ciRISjowiaQ7A9HeX3jMFUeh66Un293t7AUe4daUuNb3S28s3WAveEYALYUbK5IkrI1jo2Frsl+ZH938e8ThJKxrIAU9hRbQDsyPaT8lQzvuAueWIEC0oQSNqREZtLjx3FWQCKdQnZ15p8TVeWJjyJY+b/au7PguK78vuO/0zt2YmuAFAlqoUSNSImkNNo1Gc/i8sRJ7LLjOEtVUnESp1yVPZVUUsmDnaSyPDhVSR7sVCXjSTlOYjuTZFyTynhsjz22SIlaSYkgpREpLiAhYl+6G0Avt+/Jw+0GuoFGo4Fu9vr9VKkE9r19+/yxXJz+43/+R3YtXtMhAwAAlJLMbWHea/wlj+eTS/tZUhaXo0PyV9wzqRQqN9DKEsrKJ76PUd6u226NjIzoC6+9pkBgK8fU3d2tl196UQMDA7s9reXZmXtyvvNNuVcvKXvpotx7t5X5nf8jO33HO15QPWRdVza2dzXRQRhZ/ZWL/0w/84f/RI999TWZrm65t7eWvg0GM/rxsXn95OF5BY3Vd+aG9R+njiqRredeE/vjyuib96P6n59FNZsKqcvvaijk6OZ6l8qvZK+cXVmSTeX6/KwuS7mEX96q431+zvQndKbfS3j0Bxwd8iV1N3JUJnpEZjhak7E0k81eR4UJtcKPM2nt4DhSoILvJ2Nyzd6pQAIAAPWxbHfvB5PvgbSfCqSYzVa9q1WtdsUCGmHVZuWToZIOZe367vDkySf0xpsX5ThbN+d4PK633n5bp546pYtvvVWXATZUKqn0f/rF4scKqyxiK5Jb+40Oj3dt6MfG5nU496b+TOC+piW5Nz6SJD07ENOfOez1pZlNhfT1u0cUd5o3cVTIyuj9WL8GQxmNhb34bq7v3KXu4C9gJZ+XF3XvfLrjsGN9Sjh+9Qay+nNHZjWbCuknx73P5Sd2VJJkBocraxzdSrYvYZNk1xMy/Ydyj++WQNq9d5bv6c97yz5v/UDG55PLDmwAAKBOVuTomEq3P9hPAim/+9qSnKorL9j+HK0sKStXVikSoShj16yDkZcw2i4eT8jn37Vwqf1ZK7u8KDM4LHdqZ4LigBeVkeQ3Vl8dWdIXhryqmcl4j073relzdy/ou+f+uj4//6Z+6LGCBtCSvjM33DLJo0LTSS+hsZH16YNYbZav5dmFWZnDR+VO3y55vDewlVf/uYl7Cvutrqajesv3uPcDEaz9bnWNtlmBVJhASmz9fNuSFUgZmd0SSD29Cv3UX/ZOu+Rtt25JIAEAgDr5yE1qzIQUNTvnKvm3v5UsYQvJKCOrRZvdV9PtUlj6g1aWkZUrr0k9sJtdMw/+MktXQqH2e4O9H5lv/ZrM8KiyH75Tk+v9qbEFnemLK5H1ayyc0WI6qN+8H9XURpf+ZHRerw4t6+/85k+rb2RrydFKJqBfuXtE8+nW/Fr8INGtr08d0Z2NiDK2tgnJzG9+Xf5zLyn7zvnSx12joM/7BR/2W7232qfX7QnZfLVdGyaQNnsgFS5bK6ymy+zcPc06GZmu7pKXM5Gtx/MN5WmiDQAA6mVNru64KUX9OxNI+UROuoKETkZWaWu1IbfqTdJZwoZW58hVmibaKGPXLFE8FtfDx4/r9p07RY+fOPGYlpdr3/fn9KlTGhz0ltNcmZzUyspqzV+jVtzb16XcLmnVGghk9MqgF2tPwNXF5X59Z25E6VxS5fcWhnS6L6GBYFKXVvt0c71LPzE+p+8tDLVs8kjyaq5urJdOTlR97aV5Od/79q7Hv3H3iJ7qS2gj61fI5+q788MaHTeyuQblph0TpNubaEvFTa8zGe1QbglbaKtk3JfrGWXpgQQAAOpot4TNVgXS3pUUCevKqdH25dRtoNU5VixhQ1m7JpCuXrumF55/XseOHdXyyoqMMRoaGpKTcWre/2h4eFg9PT16/fwF9fb26tzZM3r9/IWavkYzGQxmtJ71KeX69eKhmCTp+4uHdC3eq7u5pV15SdevX75zVF1+VzMp7037ZLxHSbeDlxFW6dZGl25tlOi7lF/G1YYVSCYc8RJkBT27CpewqdRfGpzMrk2087u3FSGBBAAA6iiVawOxfRaT34UtVUElxbzNqD+3m1u1FUQsYUOrS8vl+xhl7ZpASqVSev38eY2MjKi/r0/WWn02/ZkWlyrftr5SoyMjuj8zI0lKJBIKBkMKBAJFDbxb2auDK3qyd03fmhlVt9/Vz05MayPr0//4bFyn+hJKu0bfWxiSs8tSrlUnqNWCT0XSLb1lKaqUbt8EkkJhKZ0seqgogVSK4+zeAym0s2mlXacHEgAAqJ+UdXPbjhfL/7ksntuWvFxl0LIcBXONj6pPIAGtLSMSoShvz+7LCwsLWlhYeKCDCIfDWlnd2m49nU4pHA7vmkAaGh5WINj8jaOj41G9HLmrlyLe5+8fPDa1eSzoy+pnJ6blM9KN9JCGxg43apj7Fh0fa/QQHohD/T1al9RzaFCRNokx/7WKd3VLWafoa5cJ+7Wx7bxCa35vG8/Rh47IZIunRJlodPO5eYM+V/4H/Hlrx++9doxJIq5W06xxzc3MNnoIAJpYUq5MiRqkfAVSwrryyWz+u5S0dXXFerMaKpDQ6ZI16AWG9takWZjy2x8sLS7WaRwHFx2P6lz2ml6KrGgpHdBQqPhH8VfuHtafHp/TQDCrSwsBzcVaY5IcHR9rywl9dHxMyzOzCktaT2cUa4MYC79W4UBQdnW56GtnTHBz89tSX9Pg2pr8kuYXl6VkcbrI/9BjCkqyq8syA4OSpMXJDx5EGJva8XuvHWOSiKvVtGtcANrfbk2y8xVHyQqW46Rl9Zn1qtCrfePs0nwYLS5hsyRCUVZTJJCSqaTCBT1VIpGwUslkmWc03rFIUmtZv5YypZb4WH0xckvPRlY0lwrq63cf0tdGF3Wyd02XV/t0LxnW9bUe/YfbE3q0e0NX4z11Hz9KaOMeSAddwiapdB+kkPfzajfWZAYG5d6/V4tRAgAAVMyRLflmd7MHkqyy1spnSv9x2qfihsHVvnHmjTda3aJlL0GU1xQJpLm5eT355EnduXNHAwMDSiZTcrKNX0UcMK7++sS07qfC+iDWq1vrXbKSnhuI66cOz2lqI6xfvnNsx/O+OLSsZyNLmkmG9PW7R5TIBvTN+1EFfa5SBf2L1rN+TcZ76xgRyrG5BJIJ7tL3p1UFAjJ+v9x8j6e8tb0SSLld6QLBnb9IcjvVOd//bflOPCnnD3+7NmMFAACokCNb8s1uYc+jlKy6ClY3BHLHXXlrHpJ26+xq3zrz1hut7hPb3EUcaLymSCAtLy9rdWVFX3jtVVkrfXjlSqOHJEma6ErqWFdKx7pSeuFQTJdXezUUymiiK5U7npK35nrrl9LTfXF9LbqkmBvSr+SSR5LkyhQlj9CE8hVIobDU2ycZnxRfbeyYaiFXLaTUtl8Irqv0r/2ybHxl53Mk2VwFUvCnfkaZb/+67Oz05jGTa6JtY8tyvv3rtR8zAADAHhx5y8a2VxgVpnEyctWlrY1qMtYqaHxyZeWTUbLg7EwVS9CMpPSeZwHNjRQo9tIUCSRJuvbRx40ewg7HIl6iaCYV0nAwo7MDCUnSlViPhkMZHYmkdTSS0mfJsNxcA78fjS4q5Rp9K/GU4tlEA0ePfStYwhb5h/9akpT8+b/ZwAHVhgnnkj3p1I5j7vWruz8xV4HkO/aIQj/3j5T6Z39761h4l6QUAABAHWUlbd/HuPBNcNraovaqrraWmrmyRVVD1VQQGXm7wgFAO2uaBFIzOtblvTn+xt0jivhcvTy4ondX+zWdjOirI4s6Eknrbzx8T789N6Q/XBrSaCijQ0FHH8R6tej2SCKB1FIcR9Z1i5ewGSO1ekPESJf3/+T6/p6XSyBJkvEVT802K5BKJKUAAADqxZFVcNsGPIW9iLY32k7JSlbyGyNXUqbgeFKufCpeAlcpr58SCSQA7Y0E0i5GQ2k90r2h1YxfMSegmKTfmo1uHp9PbTVa/vLIsv5waUgnerw36DfWuqSueo8YNZFJS10FTc0j3dLGWuPGUwMm0i1Jstt2UttTdudeJIEf+wvyHT4mG8steyOBBAAAGqhU42pbJoHkyJXkU7eMrC2uQFq1WflkNptw749RZu+TAKClkUDaxsjqtaEV/fDIkoI+q99dGip53lx6K4EUd/wKGFfPDXhNiW+sdytEAqk1ZdIyg8Ob/zS9fbItnkBSLoGkjf1VIOV7IOX5X/6SAs+9IqngL3MkkAAAQAOVWnZWuBXP9mSQY61c46pbPjkqXu6WkHvgZWx223I4AGhH25cMd7wfHlnSj0YXlXR9+q/3xvX7i6UTSLOpkD5KeG/MB4OOfvrwrB6KpPT+ap9WMm22i1cHsZm0THArOWh6+xs4mtowXV42c98VSE7x39GCX/vTW9ccOOTtWudSqg0AABonm2s1sGgdr9+RipNGOxJIklK587ZXLzmyB+5jVNhbCQDaFQmkIlbnBuLayPr0729N6Fqid9czXRn96rlcTo8AACAASURBVL0jenN5QD4jPd2/ptvrEf2fmdE6jhc1t32r+zZIIB20Aml7AkmSstcuS5JMTx/VRwAAoOHy9dJTNqX1XO2RW5DH2Z4Oyshu9ioqVTG0ccA+Rla2qJ8SALQjEkgFjkZSOhR09FGiR2tZf0XPmcv1QlrOBPRr0+NyLJ/SlpYpTiD5jhyT/4tfk/oPNWhA1TNdB+yBlClewpb+jf8sd3Z68982RQIJAFpJOBzSH//aj2h42Fuq3d/fry+89qpee+1VPfPM0w0eHXAwWVkZef2L8tVIhWmc7emgbEGip1TFUPKAm6e49mDNtwGgldADqcDRiLfr2tV4zx5nbrkS79FDkaReXxrUWpZPZ8vLFFfdBF75iiTJdPfK+c43GzGi6h1wFzZbUIGU/MV/KsVX5S9MpFGBBAAt5dRTT2l9fet3wenTp3RlclIrK6t67tlzikajmpuba+AIgf1zZOWTNGczcow358kWLWHbeX4qn0AqkSxKKitp/+0o1kkfAegAZDwKXIr1K5EN6Fqi8gTSWjag/zUz9gBHhXqy2yqQ8sxIa36Ngz/9V+Q/9awkyVazhC33XLtRUMWU2mdFEwCgYUZGhuU4jmIxb8MPY4x6uru1srIqSZqZndXo6AgJJLScrKzS1mq9oAF2Yd8jW6rP0eYStp3WD7gMbcVm9z4JAFocCaQCKdenyfjufY/QATI7q2psOiXfcLQBg6mODQQ3k0eSpH030S6YVuWTSQVVTDYeq2J0AIB6Mcbo5BMn9dbbb+vp06clSeFQSOmCqttUKq1IOLzntYaGhxUINv/0MTremn/42Us7xlVtTF1Jv1zXp9HuMUU2AupyfOqL+BUNeomg3pRPkUxAspLfSF3BoDZ8rrqSQUUCIUW7ir/vQ2mfIqmAZPY3DhsMKhqO1CyuZtNu8UjtGZNEXK2kWWOam5nd9VjzzwCAeipoou380XflLswqcO5lmeOPSYFgycbSzSo7Ol78wC7VVbsqEWthHyUbXznIsAAAD9DExISOT0wUPTY3N6c7U3fkOKXqLTyVvldeWlysYnT1ER0fKzv5bVXtGFctYvpYYT3sC2suFtOKr0+jvojm11c1Z715z7KvW0lfj3ySspKW19d0xd3QmcCI7m9saG41UXS9hHx6PDC8rzokI+n2WkxzNlWzuJpJu8UjtWdMEnG1klaNiQQSUMB553VZ15V74yO51y5JktyJRxV45HGZ4VHZ2c8aPMLKZUcPV/V8W+qNRlECabWq6wMAam9qakpTU1NFj7322quKKqpHHn5EPT3dGhw8pHffe1+hYGjznEhXRMkkve3Qem4ppVuu972bX8Lm2J09kHySFqyjTK6J9rp1NWN3/rFsXa7u27TGTWjHsd34JN0vcS0AaDckkIACdvqOnOk7xY8teP0gzPBYSyWQ3NEj1V2gZAVSwRK2GAkkAGgF589f2Pz43Nmzmrp7V7FYTIlEQkNDQ1paWtLh8cO6detWA0cJVC8rrxrIKeyBlEsmZazVknU2G2evKas7tnR19n2b2VcCybFWSZpoA+gAJJCAPdileUmSGRxq8Ej2x+0frPICJSZChX2UqEACgJY2OTmpM2eekYzR8vKy5hcWGj0koCqOXBkZpQsSSPnW1mlZxZXd3IHtQjZelGgqdNdN6Tlfb1Ez7vKvu/U6ANDOSCABe7CxZUmSqTYhU2c2GJJNbsiuLsv9ZHL/F/D7dz6W3lrewBI2AGg9ly5f3vw4nkjo/IU3GjgaoLYcWTmyWiuoBsongVJyNe9mNlNCy2VSPovKasNmFTa+il8XADoBCSRgD3bVaxZtBnIJpO5eyeeTEs29C5kNBqVUUulf+lcHe36u8ip76WLBgwUl4SSQAABAE3GsVcZ6PY7yNhNI1uq+MqosJeQlmMYrPDvD8jUAHYIEErCX9YRsJiPTf0gKhhT5R/9GdnlRqX/3840eWXmBoOxaYu/zdpNKKvnP/66U3WXXnjTNVgEAQPNIySq1LZmTkdcXKSlXrlRxqmfdZiUTrOjcjKUCCUBnIIEEVMDGVmT6BxV47auSJDM43OAR7c0GQ1KmdHPIipVIHmV+679JgcomVAAAAPWSkltUfSR5y8tM7th+VNr/SPKSVADQCUggARWwsWX5HnlC/nMvbz0Y6SpuKt1MjJGCISldZQKphOz7b9b8mgAAANVat+6OfkSOzfdA2l+V0H7STWmWsAHoEJUuAwY6W2xbHyRJpqevUaPZW65CyGZYZgYAADpDSnbHcrJ8BVJ6nwmk/ZxNE20AnYIEElABu7q89fH6mvdBMyeQQiHv//QpAgAAHcKRVWLb7mppWRmZzUqkSu2vAokEEoDOQAIJqED20puysRXZTEbZD96S1NwVSCYY9j54AEvYAAAAmlFaVgu2uH9jNpfc2W+V0H7O3t53CQDaFT2QgArYpQWl/v0vSF098h0/IUkyvc2bQMpXINlqm2gDAAC0CFfSdZvc8ZiRPUAPpMrOD8qQQALQMahAAirlOFJ8VVqLS2ruCiSF8hVILGEDAACdY/vSs2xuCduG3V+j60pTQuvKytnntQGgVZFAAvbJ5hJI6ult7EDKMMFcBRIJJAAA0MG8CiQpuc+d0iqtQLrrprVGBRKADkECCdgn20oVSCxhAwAAHcyVlav99ymqJN1kJN21ad2x/MEOQGcggQTs1/qarOs2dw+kYH4XNhJIAACgc2UlWdl9J5BsBecbSZmKa5UAoPWRQAL2y1opuSF19TR6JLsyIZawAQAAWOlgFUgVnG4kZcgeAeggJJCAA7DrazLdzZtAYgkbAACAJ2srqScqVukStvQ+eysBQCsjgQQcxMZaU1cgsQsbAACAxznAcypbwmYOdG0AaFUkkIADsOtrMn6/FI40eiglbe3CRgUSAADobPtdviZVVoFkZZWlAxKADkICCTiIjTVJat5lbLkeSMpQgQQAADqbc4BlZk4FiSFXlSWaAKBdkEACDsCuewmkssvYBgblf/nLW8vJ6imYX8JGBRIAAOhsmQM8Jyuvx1E5VqICCUBHCTR6AEArsgUVSCWnDd09ivz9f5E72VX24vfrNTRJkm90THJd2fVEXV8XAACg2Ryk0XVWVkYqmx7ydngjgQSgc9Q1gWSM0dmzZ9TT3SNjjK5eu6alpSX19/frzDNPy0qKxWL68MMr9RwWsH97VCCZkfGtjweH6zGiLb398k08Jv/0bSm5Ud/XBgAAaDJr9gBL2GwFS9isVfYgAwKAFlXXJWzHjh5V1snq/IULuvzBZZ0+9ZQk6fTpU7oyOanz5y8oGAgoGo3Wc1jAvuWXsO3WA8mEt5atmf7Buowpz//M5yVJgVsf1/V1AQAAmlHC7j/N46iyJWzUHwHoJHVNIN29d0+TV69KklKptEKhkIwx6unu1srKqiRpZnZWo6Mj9RwWsH/5JWy79UAq6HtkBoYqvqyZeEwaOHjCyQyOKPClPyG7sa7gjWsHvg4AAEC7SByoiba7ZwKJBtoAOk1dE0jWWrmud6t97NFHde/etMKhkNKZrdZ2qVRakXADmg4D+7DZRHvXCqTI1scDhyq6phkaVfiv/j2F/tLfOvC4fI8/JRMKy/net+XLJbkAAAA62V27/11pvSba5VNI9D8C0GkeWA+kiYkJHZ+YKHrs4x/8QPPz83rk4Yc1cGhAb731tsL57cZz9sr0S9LQ8LACwebv/x0dH2v0EB4I4pLc7ogSkiLjR9Rd4nmp4RHlpyqmt1+jDx2RyZYvn0499wWlJPlGogf+HCejY0pLGnC93dfa7WvVbvFI7RmTRFytplnjmpuZbfQQALSB5AESPa7sns+i/xGATvPAsjBTU1Oampra8fjExDGNjY/p7bffkbVWqXRaoeBWEinSFVEyWf6vBEuLizUfb61Fx8facuJLXHmzCk1PyTn+uBZ6BuV+WtxvyP9EWkFJNrYi039ICxtp2aWF0pfqG5AZGFTw0c/JJ8mmUwf+HAdc74d6+d49jZr2evPVjt977RiTRFytpl3jAoBqeGsmyqeQqEAC0GnquoStu7tbDx9/WO+88+7mUjZrrRKJhIaGvD4xh8cPa25urp7DAg7EufC7kqTQX/qb8p18uuiYyfVAcudnvH+X6YMU+ot/Q+Gf/QfyjeQqAAJByXewH818U2+7njjQ8wEAAOAlkPbqcUQCCUCnqWsC6fjEhEKhoF568QW9+srLevWVl2WM0eTkpJ763JN67bVXtba+pvmFXSo1gCbiXr0k59JFSZIZO1J8MJdAsjPT3vHh0V2v49v2XOPzST19BxtUvqk3/Y8AAAAOrJIlbDTRBtBp6tpI6KOPP9ZHH+/cWjyeSOj8hTfqORSgJrIX/0CBcy/J9PYXPZ5vou1O3/H+PTK+6zVsOi2T6wWW/eSq/E+ckukbkI2v7ns8prtXNpWSHGffzwUAAICnkv5GrqUCCUBnqWsFEtBubCImSTLbK4byFUif5RNIxQ1qzeGjUr73V65zvHvvttzb172H+gYONB7T3UP1EQAAQJW8CqS9eiABQGchgQRUY31N1nV3VCBtJpBiq7KxVflGtyqQzOGjCv/cP1bwz/41KRyRCYaU/WRS6f/0i5tVRwdNIKm7h/5HAAAAVbKS9iowYhc2AJ2GBBJQDdeV1tek3uIKJBMKy2azUtaRuzAjc2hos+LIDHvVSP7Hn9qsXLKJuPfEzQTStoRUJQJB73XXqUACAACohtVee7DRRBtA5yGBBFTJrsW9RFD/Ifmff03m6CNeBVIq6R1fnJckmcFh7/+Rrq0n5xNPa14Cya4seecMFy95q0huBzaRQAIAAKja3ruwAUBnqWsTbaAd2URMvrEjCv3Uz8h3/DHZeEzWSUvplHdCvidR2Escmf6t5Wm+0cOb15Aku7wgm4jLd+yRfY/D5HZgs/RAAgAAqNpe9UVZKpAAdBgqkIBq5ZI/vuOPSfKWn5nuPtlcAin/fxP2+iKpf3Dzqb5HnvDOyS9hk+Tevektees/tK9hmAHvuvRAAgAAqN5eS9SoQALQaUggAVWya/Edj5lweKsCKbeUTeGIAn/ipxU499Lmeb4nTnkf5JJQkuTeveUdO35iX+PwP/O89/ybP9jX8wAAALDT3kvYqEAC0FlIIAFVyvc4kiT39vWtx/M9kFK5CqT+QQVe+GNbx11XJhyRzWblLs5tXeP6VdlsVsEf/nEptyxtT5Eu+T53Ru7cfdmpm9WEAwAAAEl2zwokEkgAOgs9kIAqZd+7IBtbkcIRme4e+R5+3DuQr0BKe4mk/BK3PHv3pszxE3I/mdzcfU2S7Nx9Od//fwp+5U8p8MqX5Xzv23uOwUSPyAQCyn4yWZugAAAAOhxNtAGgGBVIQLWslfvJpNwr78rGChJBK4veB6l8AmlrSZrNZpX5rf+u7AdvK/N/f2PHJbNv/L5sIib/81/wdnTbgxkc8a67tFBNJAAAAMjZq76IBBKATkMCCaghW1BJ5E5PeY/lEkim21uO5rzxPaX/87+VXZxT5n//alH/o01ORtkr78l0dctED+/5ur7BYe+1lkkgAQAA1AJNtAGgGEvYgFpKFFQgTd/2PsgvZZPXD8n5nW9Jdu8183ZjTZJkgqE9/wJmSCABAADUlLWSzO7HHXogAegwVCABNWTjW9VE+eVk+QokSbKx5YqSR5KkTNr7/x5L2PzPvSr/2Rdls1nZ1eX9DRgAAAAl7VWB5FCDBKDDUIEE1FLWUfbKe1v9j6TiCqSCJW57SucSSMFQ2dOCP/bnJUnG75dcJjIAAAC1sNesyqn0j4IA0CZIIAE1lvnmN4ofKKhAKtnvaBc2V4FkQuUTSHnunRsVXxsAAADl7ZUeSrOEDUCHYQkb8KAV/HWqcInbniqpQAoEveuuryn9zf9ygMEBAACglHIVSD5JGyxhA9BhSCABdWQT+1jClsktfSvXAykSkSS5Nz+WYitVjAwAAACFyvVA8knasCSQAHQWlrABdbSfCiSbq0AyZSqQTLjLOzeZ3PUcAEBnO3bsqD735JNaW/N295yfX9An16+rv79fZ555WlZSLBbThx9eaexAgSZTPj1klGIJG4AOQwIJqKf9NNHOVLCELexVIBX1WQIAYJvp6c909dq1osdOnz6lK5OTWllZ1XPPnlM0GtXc3FyDRgg0n2yZBFFWVhkSSAA6DEvYgDqya/HKT84nkMo00TaRXAVSaqOaYQEAOowxRj3d3VpZ8f6wMTM7q9HRkQaPCmgu5ZawuZYEEoDOQwUSUAc2EZfp7ZPdRwWSTXs9kMotYVNuCZuSJJAAALsbHh7WSy+9KJ8xunr1mlKplNKZzObxVCqtSLhMz72coeFhBYLNP32Mjo81eggPRDvG1cwx9ST9ijj+ksccWY307j72Zo7rINotHqk9Y5KIq5U0a0xzM7O7Hmv+GQDQBlK/9C9levr3l+jZrEDafUJvWMIGACgwMTGh4xMTRY9NT0/rBz/4gWbn5jQ4OKhnnz2nN9+8WHSOqfD6S4uLNRrpgxMdHys7+W1V7RhXs8e04uvVqK+r5LGkdTWXKP3z0Oxx7Ve7xSO1Z0wScbWSVo2JBBJQD2sJ2bXE/p5TSQ+k3C5slgokAICkqakpTU1N7Xp8eXlZoVBI6UxGoYLfL5GuiJLJVD2GCLSMck20HZavAehA9EACmpXjyLruHkvYqEACAJR34sRjeuihI5Kkvr4+pdNpua6rRCKhoaEhSdLh8cM00Aa2IYEEAMWoQAKaWTpVYRNtEkgAgNLu3ZvWs8+e08PHH5bxGV26/IEkaXJyUmfOPCMZo+XlZc0vLDR4pEBzKddEO2tJIAHoPCSQgGaWSUvBMk1NaaINANhDMpnUG2+8uePxeCKh8xfeaMCIgNaQLXMsU+YYALQrlrABTcxm0jLlKpByS9ioQAIAAKitfAWSP/dfIZawAehEJJCAZpZO79FEO1eBlKICCQAAoJbyPZCMjFK5JWvh3J6FTtkOSQDQnkggAc0sUz6BZCJdsk5Gcpw6DgoAAKD95fscubLayCWM8sva0lQgAehAJJCAJmbTKZlAQPKV/lE1fQNSPFbnUQEAALQ/m0sSOdYqkUsdZeTKSEqRQALQgUggAc0sk2vRGCrRSNsYqbdfNr5S3zEBAAB0gHy1kSNp3XoVSAnryi+jlGUJG4DOQwIJaGbpXHPsUgmknj4Zv182tlrfMQEAAHSAjKyMvKqjtdwStjVlZSXF6YEEoAORQAKamE16zbFNvll2AdN/yDuHCiQAAICa20ogWW1Yrx5pQ66MrFYs/ScBdB4SSEAzS+UqkMIlEkh9A5JEBRIAAMADkLa5BJK1WrJZ+eX1Q0rJap0KJAAdKNCIFw2HQ/ryl76kt995V4uLi+rv79eZZ56WlRSLxfThh1caMSyg6WxVIEV2tGo0/fkEEhVIAAAAteYUVCCtKSsjo6yklLXswgagIzWkAunUU09pfX1989+nT5/SlclJnT9/QcFAQNFotBHDAppPyksgKdylwI/8hHynzknGyBw+KtOXX8JGBRIAAECteUvYjDLyqo6yssrIKr7ZXhsAOkvdK5BGRoblOI5isbgkyRijnu5urax4b4JnZmc1Ojqiubm5eg8NaDo26S1h842OK/DKVyRJme/+bwV/5Ce3TqIHEgAAQM1lZWXlNdFOyyprvSTSfTfd6KEBQEPUNYFkjNHJJ07qrbff1tOnT0uSwqGQ0vmtyiWlUmlFwiV2nCowNDysQLAhq+/2JTo+1ughPBDEVT+ZrrA2JEWOP6p8q8bwi1/cWnWfdTQSCcrsMvZmjKka7RaP1J4xScTVapo1rrmZ2UYPAUAHy0pyZZV/p5KRlWOtPrHJRg4LABrmgWVhJiYmdHxiouixubk53Zm6I8fZfdcCU8G1lxYXqxzdgxcdH2vLiS9x1ZcJ9SgsKTM4uvmz4R4a3jzuzn6m+c/ul3xus8Z0UO0Wj9SeMUnE1WraNS4AqJa7WYHk9TtKy8rJLWcDgE70wBJIU1NTmpqaKnrstddeVVRRPfLwI+rp6dbg4CG9+977CgVDm+dEuiJKJlMPalhAa8ktYTOHhkoedu/fredoAAAAOkZ+CVs6V/vtiObZADpbXdeBnT9/YfPjc2fPauruXcViMSUSCQ0NDWlpaUmHxw/r1q1b9RwW0LRsvon2bsdXluo0EgAAgM6SlSQrbVgvgeRKSm41EgCAjtMUjYQmJyd15swzkjFaXl7W/MJCo4cENIfkVgLJuq6U3JDp7tl8zL19vRG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            "text/plain": [
              "<Figure size 1440x432 with 2 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sortino: 0.957\n",
            "Beta: 0.308\n",
            "Alpha: 26.5 %\n",
            "MaxDrawdown: 54.723 %\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AsFvGIuoTGcf"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}