meteo_forecasting_data.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0cWgxWhT17mP"
      },
      "source": [
        "Observation météorologique historiques France (SYNOP)\n",
        "https://public.opendatasoft.com/explore/dataset/donnees-synop-essentielles-omm/information/?sort=date\n",
        "\n",
        "Ici nous utilisons les données de l'aéroport Lille-Lesquin (LYS)\n",
        "La description json peut être récupérée sur la page dans la section \"Modèle de données\".\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "wKGW6wIAJeWo"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "import json\n",
        "import random\n",
        "\n",
        "import tensorflow as tf\n",
        "from tensorflow import keras"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DP32uVKRI8m8",
        "outputId": "88876100-fcee-42b8-8615-b473de44e598"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "# I runned in google colab.\n",
        "# from google.colab import drive\n",
        "# drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a8B4ZIho43yK"
      },
      "source": [
        "#### get dataset files"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "vTyHO6-JlJ08"
      },
      "outputs": [],
      "source": [
        "dataset_filename = \"data/donnees-synop-essentielles-omm (LYS).csv\"\n",
        "description_filename = \"data/description-donnees-synop-essentielles-omm(LYS).json\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "N8LMaXqa4Xsq"
      },
      "source": [
        "#### Read dataset **description**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "A0Cw3a5ykF8W"
      },
      "outputs": [],
      "source": [
        "# load the column names abreviations from the json data description\n",
        "with open(description_filename, 'r') as json_file:\n",
        "    schema = json.load(json_file)\n",
        "\n",
        "synop_codes=list( schema['definitions']['donnees-synop-essentielles-omm_records']['properties']['fields']['properties'].keys() )"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9lLq53It4eJX"
      },
      "source": [
        "#### Change dataset columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Vv3o5dcAzWJ-",
        "outputId": "01fe664a-63c1-4167-d82d-17db8b5343dd"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "<ipython-input-6-88326cf9a84e>:1: DtypeWarning: Columns (62) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(dataset_filename, sep=\";\")\n"
          ]
        }
      ],
      "source": [
        "df = pd.read_csv(dataset_filename, sep=\";\")\n",
        "\n",
        "synop_desc = list(df.columns)\n",
        "code2desc = dict(zip(synop_codes, synop_desc))\n",
        "columns_na = df.isna().sum().tolist()\n",
        "df.columns  = synop_codes\n",
        "\n",
        "df_desc=pd.DataFrame({'Code':synop_codes, 'Description':synop_desc, 'Na':columns_na})"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "nR6z-kF8znxu",
        "outputId": "488a2859-5986-4cc9-9162-6870102d6e2e"
      },
      "outputs": [
        {
          "data": {
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              "  text-align: left;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_e5b4f\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_e5b4f_level0_col0\" class=\"col_heading level0 col0\" >Code</th>\n",
              "      <th id=\"T_e5b4f_level0_col1\" class=\"col_heading level0 col1\" >Description</th>\n",
              "      <th id=\"T_e5b4f_level0_col2\" class=\"col_heading level0 col2\" >Na</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "      <td id=\"T_e5b4f_row0_col0\" class=\"data row0 col0\" >numer_sta</td>\n",
              "      <td id=\"T_e5b4f_row0_col1\" class=\"data row0 col1\" >ID OMM station</td>\n",
              "      <td id=\"T_e5b4f_row0_col2\" class=\"data row0 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "      <td id=\"T_e5b4f_row1_col0\" class=\"data row1 col0\" >date</td>\n",
              "      <td id=\"T_e5b4f_row1_col1\" class=\"data row1 col1\" >Date</td>\n",
              "      <td id=\"T_e5b4f_row1_col2\" class=\"data row1 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "      <td id=\"T_e5b4f_row2_col0\" class=\"data row2 col0\" >pmer</td>\n",
              "      <td id=\"T_e5b4f_row2_col1\" class=\"data row2 col1\" >Pression au niveau mer</td>\n",
              "      <td id=\"T_e5b4f_row2_col2\" class=\"data row2 col2\" >5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "      <td id=\"T_e5b4f_row3_col0\" class=\"data row3 col0\" >tend</td>\n",
              "      <td id=\"T_e5b4f_row3_col1\" class=\"data row3 col1\" >Variation de pression en 3 heures</td>\n",
              "      <td id=\"T_e5b4f_row3_col2\" class=\"data row3 col2\" >24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "      <td id=\"T_e5b4f_row4_col0\" class=\"data row4 col0\" >cod_tend</td>\n",
              "      <td id=\"T_e5b4f_row4_col1\" class=\"data row4 col1\" >Type de tendance barométrique</td>\n",
              "      <td id=\"T_e5b4f_row4_col2\" class=\"data row4 col2\" >17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "      <td id=\"T_e5b4f_row5_col0\" class=\"data row5 col0\" >dd</td>\n",
              "      <td id=\"T_e5b4f_row5_col1\" class=\"data row5 col1\" >Direction du vent moyen 10 mn</td>\n",
              "      <td id=\"T_e5b4f_row5_col2\" class=\"data row5 col2\" >8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "      <td id=\"T_e5b4f_row6_col0\" class=\"data row6 col0\" >ff</td>\n",
              "      <td id=\"T_e5b4f_row6_col1\" class=\"data row6 col1\" >Vitesse du vent moyen 10 mn</td>\n",
              "      <td id=\"T_e5b4f_row6_col2\" class=\"data row6 col2\" >6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "      <td id=\"T_e5b4f_row7_col0\" class=\"data row7 col0\" >t</td>\n",
              "      <td id=\"T_e5b4f_row7_col1\" class=\"data row7 col1\" >Température</td>\n",
              "      <td id=\"T_e5b4f_row7_col2\" class=\"data row7 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "      <td id=\"T_e5b4f_row8_col0\" class=\"data row8 col0\" >td</td>\n",
              "      <td id=\"T_e5b4f_row8_col1\" class=\"data row8 col1\" >Point de rosée</td>\n",
              "      <td id=\"T_e5b4f_row8_col2\" class=\"data row8 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "      <td id=\"T_e5b4f_row9_col0\" class=\"data row9 col0\" >u</td>\n",
              "      <td id=\"T_e5b4f_row9_col1\" class=\"data row9 col1\" >Humidité</td>\n",
              "      <td id=\"T_e5b4f_row9_col2\" class=\"data row9 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
              "      <td id=\"T_e5b4f_row10_col0\" class=\"data row10 col0\" >vv</td>\n",
              "      <td id=\"T_e5b4f_row10_col1\" class=\"data row10 col1\" >Visibilité horizontale</td>\n",
              "      <td id=\"T_e5b4f_row10_col2\" class=\"data row10 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
              "      <td id=\"T_e5b4f_row11_col0\" class=\"data row11 col0\" >ww</td>\n",
              "      <td id=\"T_e5b4f_row11_col1\" class=\"data row11 col1\" >Temps présent</td>\n",
              "      <td id=\"T_e5b4f_row11_col2\" class=\"data row11 col2\" >26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
              "      <td id=\"T_e5b4f_row12_col0\" class=\"data row12 col0\" >w1</td>\n",
              "      <td id=\"T_e5b4f_row12_col1\" class=\"data row12 col1\" >Temps passé 1</td>\n",
              "      <td id=\"T_e5b4f_row12_col2\" class=\"data row12 col2\" >27007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
              "      <td id=\"T_e5b4f_row13_col0\" class=\"data row13 col0\" >w2</td>\n",
              "      <td id=\"T_e5b4f_row13_col1\" class=\"data row13 col1\" >Temps passé 2</td>\n",
              "      <td id=\"T_e5b4f_row13_col2\" class=\"data row13 col2\" >27015</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
              "      <td id=\"T_e5b4f_row14_col0\" class=\"data row14 col0\" >n</td>\n",
              "      <td id=\"T_e5b4f_row14_col1\" class=\"data row14 col1\" >Nebulosité totale</td>\n",
              "      <td id=\"T_e5b4f_row14_col2\" class=\"data row14 col2\" >10938</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
              "      <td id=\"T_e5b4f_row15_col0\" class=\"data row15 col0\" >nbas</td>\n",
              "      <td id=\"T_e5b4f_row15_col1\" class=\"data row15 col1\" >Nébulosité  des nuages de l' étage inférieur</td>\n",
              "      <td id=\"T_e5b4f_row15_col2\" class=\"data row15 col2\" >1328</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
              "      <td id=\"T_e5b4f_row16_col0\" class=\"data row16 col0\" >hbas</td>\n",
              "      <td id=\"T_e5b4f_row16_col1\" class=\"data row16 col1\" >Hauteur de la base des nuages de l'étage inférieur</td>\n",
              "      <td id=\"T_e5b4f_row16_col2\" class=\"data row16 col2\" >7873</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
              "      <td id=\"T_e5b4f_row17_col0\" class=\"data row17 col0\" >cl</td>\n",
              "      <td id=\"T_e5b4f_row17_col1\" class=\"data row17 col1\" >Type des nuages de l'étage inférieur</td>\n",
              "      <td id=\"T_e5b4f_row17_col2\" class=\"data row17 col2\" >25883</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
              "      <td id=\"T_e5b4f_row18_col0\" class=\"data row18 col0\" >cm</td>\n",
              "      <td id=\"T_e5b4f_row18_col1\" class=\"data row18 col1\" >Type des nuages de l'étage moyen</td>\n",
              "      <td id=\"T_e5b4f_row18_col2\" class=\"data row18 col2\" >26379</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
              "      <td id=\"T_e5b4f_row19_col0\" class=\"data row19 col0\" >ch</td>\n",
              "      <td id=\"T_e5b4f_row19_col1\" class=\"data row19 col1\" >Type des nuages de l'étage supérieur</td>\n",
              "      <td id=\"T_e5b4f_row19_col2\" class=\"data row19 col2\" >26444</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
              "      <td id=\"T_e5b4f_row20_col0\" class=\"data row20 col0\" >pres</td>\n",
              "      <td id=\"T_e5b4f_row20_col1\" class=\"data row20 col1\" >Pression station</td>\n",
              "      <td id=\"T_e5b4f_row20_col2\" class=\"data row20 col2\" >5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
              "      <td id=\"T_e5b4f_row21_col0\" class=\"data row21 col0\" >niv_bar</td>\n",
              "      <td id=\"T_e5b4f_row21_col1\" class=\"data row21 col1\" >Niveau barométrique</td>\n",
              "      <td id=\"T_e5b4f_row21_col2\" class=\"data row21 col2\" >34477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
              "      <td id=\"T_e5b4f_row22_col0\" class=\"data row22 col0\" >geop</td>\n",
              "      <td id=\"T_e5b4f_row22_col1\" class=\"data row22 col1\" >Géopotentiel</td>\n",
              "      <td id=\"T_e5b4f_row22_col2\" class=\"data row22 col2\" >34477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
              "      <td id=\"T_e5b4f_row23_col0\" class=\"data row23 col0\" >tend24</td>\n",
              "      <td id=\"T_e5b4f_row23_col1\" class=\"data row23 col1\" >Variation de pression en 24 heures</td>\n",
              "      <td id=\"T_e5b4f_row23_col2\" class=\"data row23 col2\" >8625</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
              "      <td id=\"T_e5b4f_row24_col0\" class=\"data row24 col0\" >tn12</td>\n",
              "      <td id=\"T_e5b4f_row24_col1\" class=\"data row24 col1\" >Température minimale sur 12 heures</td>\n",
              "      <td id=\"T_e5b4f_row24_col2\" class=\"data row24 col2\" >25863</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
              "      <td id=\"T_e5b4f_row25_col0\" class=\"data row25 col0\" >tn24</td>\n",
              "      <td id=\"T_e5b4f_row25_col1\" class=\"data row25 col1\" >Température minimale sur 24 heures</td>\n",
              "      <td id=\"T_e5b4f_row25_col2\" class=\"data row25 col2\" >34477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
              "      <td id=\"T_e5b4f_row26_col0\" class=\"data row26 col0\" >tx12</td>\n",
              "      <td id=\"T_e5b4f_row26_col1\" class=\"data row26 col1\" >Température maximale sur 12 heures</td>\n",
              "      <td id=\"T_e5b4f_row26_col2\" class=\"data row26 col2\" >25863</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
              "      <td id=\"T_e5b4f_row27_col0\" class=\"data row27 col0\" >tx24</td>\n",
              "      <td id=\"T_e5b4f_row27_col1\" class=\"data row27 col1\" >Température maximale sur 24 heures</td>\n",
              "      <td id=\"T_e5b4f_row27_col2\" class=\"data row27 col2\" >34477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
              "      <td id=\"T_e5b4f_row28_col0\" class=\"data row28 col0\" >tminsol</td>\n",
              "      <td id=\"T_e5b4f_row28_col1\" class=\"data row28 col1\" >Température minimale du sol sur 12 heures</td>\n",
              "      <td id=\"T_e5b4f_row28_col2\" class=\"data row28 col2\" >7557</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
              "      <td id=\"T_e5b4f_row29_col0\" class=\"data row29 col0\" >sw</td>\n",
              "      <td id=\"T_e5b4f_row29_col1\" class=\"data row29 col1\" >Méthode de mesure Température du thermomètre mouillé</td>\n",
              "      <td id=\"T_e5b4f_row29_col2\" class=\"data row29 col2\" >34477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
              "      <td id=\"T_e5b4f_row30_col0\" class=\"data row30 col0\" >tw</td>\n",
              "      <td id=\"T_e5b4f_row30_col1\" class=\"data row30 col1\" >Température du thermomètre mouillé</td>\n",
              "      <td id=\"T_e5b4f_row30_col2\" class=\"data row30 col2\" >34477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
              "      <td id=\"T_e5b4f_row31_col0\" class=\"data row31 col0\" >raf10</td>\n",
              "      <td id=\"T_e5b4f_row31_col1\" class=\"data row31 col1\" >Rafale sur les 10 dernières minutes</td>\n",
              "      <td id=\"T_e5b4f_row31_col2\" class=\"data row31 col2\" >8410</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
              "      <td id=\"T_e5b4f_row32_col0\" class=\"data row32 col0\" >rafper</td>\n",
              "      <td id=\"T_e5b4f_row32_col1\" class=\"data row32 col1\" >Rafales sur une période</td>\n",
              "      <td id=\"T_e5b4f_row32_col2\" class=\"data row32 col2\" >17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
              "      <td id=\"T_e5b4f_row33_col0\" class=\"data row33 col0\" >per</td>\n",
              "      <td id=\"T_e5b4f_row33_col1\" class=\"data row33 col1\" >Periode de mesure de la rafale</td>\n",
              "      <td id=\"T_e5b4f_row33_col2\" class=\"data row33 col2\" >6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
              "      <td id=\"T_e5b4f_row34_col0\" class=\"data row34 col0\" >etat_sol</td>\n",
              "      <td id=\"T_e5b4f_row34_col1\" class=\"data row34 col1\" >Etat du sol</td>\n",
              "      <td id=\"T_e5b4f_row34_col2\" class=\"data row34 col2\" >9460</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
              "      <td id=\"T_e5b4f_row35_col0\" class=\"data row35 col0\" >ht_neige</td>\n",
              "      <td id=\"T_e5b4f_row35_col1\" class=\"data row35 col1\" >Hauteur totale de la couche de neige, glace, autre au sol</td>\n",
              "      <td id=\"T_e5b4f_row35_col2\" class=\"data row35 col2\" >10197</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
              "      <td id=\"T_e5b4f_row36_col0\" class=\"data row36 col0\" >ssfrai</td>\n",
              "      <td id=\"T_e5b4f_row36_col1\" class=\"data row36 col1\" >Hauteur de la neige fraîche</td>\n",
              "      <td id=\"T_e5b4f_row36_col2\" class=\"data row36 col2\" >25804</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
              "      <td id=\"T_e5b4f_row37_col0\" class=\"data row37 col0\" >perssfrai</td>\n",
              "      <td id=\"T_e5b4f_row37_col1\" class=\"data row37 col1\" >Periode de mesure de la neige fraiche</td>\n",
              "      <td id=\"T_e5b4f_row37_col2\" class=\"data row37 col2\" >26272</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
              "      <td id=\"T_e5b4f_row38_col0\" class=\"data row38 col0\" >rr1</td>\n",
              "      <td id=\"T_e5b4f_row38_col1\" class=\"data row38 col1\" >Précipitations dans la dernière heure</td>\n",
              "      <td id=\"T_e5b4f_row38_col2\" class=\"data row38 col2\" >137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
              "      <td id=\"T_e5b4f_row39_col0\" class=\"data row39 col0\" >rr3</td>\n",
              "      <td id=\"T_e5b4f_row39_col1\" class=\"data row39 col1\" >Précipitations dans les 3 dernières heures</td>\n",
              "      <td id=\"T_e5b4f_row39_col2\" class=\"data row39 col2\" >170</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
              "      <td id=\"T_e5b4f_row40_col0\" class=\"data row40 col0\" >rr6</td>\n",
              "      <td id=\"T_e5b4f_row40_col1\" class=\"data row40 col1\" >Précipitations dans les 6 dernières heures</td>\n",
              "      <td id=\"T_e5b4f_row40_col2\" class=\"data row40 col2\" >6651</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
              "      <td id=\"T_e5b4f_row41_col0\" class=\"data row41 col0\" >rr12</td>\n",
              "      <td id=\"T_e5b4f_row41_col1\" class=\"data row41 col1\" >Précipitations dans les 12 dernières heures</td>\n",
              "      <td id=\"T_e5b4f_row41_col2\" class=\"data row41 col2\" >6825</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
              "      <td id=\"T_e5b4f_row42_col0\" class=\"data row42 col0\" >rr24</td>\n",
              "      <td id=\"T_e5b4f_row42_col1\" class=\"data row42 col1\" >Précipitations dans les 24 dernières heures</td>\n",
              "      <td id=\"T_e5b4f_row42_col2\" class=\"data row42 col2\" >8151</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
              "      <td id=\"T_e5b4f_row43_col0\" class=\"data row43 col0\" >phenspe1</td>\n",
              "      <td id=\"T_e5b4f_row43_col1\" class=\"data row43 col1\" >Phénomène spécial 1</td>\n",
              "      <td id=\"T_e5b4f_row43_col2\" class=\"data row43 col2\" >25961</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
              "      <td id=\"T_e5b4f_row44_col0\" class=\"data row44 col0\" >phenspe2</td>\n",
              "      <td id=\"T_e5b4f_row44_col1\" class=\"data row44 col1\" >Phénomène spécial 2</td>\n",
              "      <td id=\"T_e5b4f_row44_col2\" class=\"data row44 col2\" >25967</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
              "      <td id=\"T_e5b4f_row45_col0\" class=\"data row45 col0\" >phenspe3</td>\n",
              "      <td id=\"T_e5b4f_row45_col1\" class=\"data row45 col1\" >Phénomène spécial 3</td>\n",
              "      <td id=\"T_e5b4f_row45_col2\" class=\"data row45 col2\" >26268</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
              "      <td id=\"T_e5b4f_row46_col0\" class=\"data row46 col0\" >phenspe4</td>\n",
              "      <td id=\"T_e5b4f_row46_col1\" class=\"data row46 col1\" >Phénomène spécial 4</td>\n",
              "      <td id=\"T_e5b4f_row46_col2\" class=\"data row46 col2\" >34300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
              "      <td id=\"T_e5b4f_row47_col0\" class=\"data row47 col0\" >nnuage1</td>\n",
              "      <td id=\"T_e5b4f_row47_col1\" class=\"data row47 col1\" >Nébulosité couche nuageuse 1</td>\n",
              "      <td id=\"T_e5b4f_row47_col2\" class=\"data row47 col2\" >7564</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row48\" class=\"row_heading level0 row48\" >48</th>\n",
              "      <td id=\"T_e5b4f_row48_col0\" class=\"data row48 col0\" >ctype1</td>\n",
              "      <td id=\"T_e5b4f_row48_col1\" class=\"data row48 col1\" >Type nuage 1</td>\n",
              "      <td id=\"T_e5b4f_row48_col2\" class=\"data row48 col2\" >25669</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row49\" class=\"row_heading level0 row49\" >49</th>\n",
              "      <td id=\"T_e5b4f_row49_col0\" class=\"data row49 col0\" >hnuage1</td>\n",
              "      <td id=\"T_e5b4f_row49_col1\" class=\"data row49 col1\" >Hauteur de base 1</td>\n",
              "      <td id=\"T_e5b4f_row49_col2\" class=\"data row49 col2\" >8625</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row50\" class=\"row_heading level0 row50\" >50</th>\n",
              "      <td id=\"T_e5b4f_row50_col0\" class=\"data row50 col0\" >nnuage2</td>\n",
              "      <td id=\"T_e5b4f_row50_col1\" class=\"data row50 col1\" >Nébulosité couche nuageuse 2</td>\n",
              "      <td id=\"T_e5b4f_row50_col2\" class=\"data row50 col2\" >20753</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row51\" class=\"row_heading level0 row51\" >51</th>\n",
              "      <td id=\"T_e5b4f_row51_col0\" class=\"data row51 col0\" >ctype2</td>\n",
              "      <td id=\"T_e5b4f_row51_col1\" class=\"data row51 col1\" >Type nuage 2</td>\n",
              "      <td id=\"T_e5b4f_row51_col2\" class=\"data row51 col2\" >30794</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row52\" class=\"row_heading level0 row52\" >52</th>\n",
              "      <td id=\"T_e5b4f_row52_col0\" class=\"data row52 col0\" >hnuage2</td>\n",
              "      <td id=\"T_e5b4f_row52_col1\" class=\"data row52 col1\" >Hauteur de base 2</td>\n",
              "      <td id=\"T_e5b4f_row52_col2\" class=\"data row52 col2\" >21024</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row53\" class=\"row_heading level0 row53\" >53</th>\n",
              "      <td id=\"T_e5b4f_row53_col0\" class=\"data row53 col0\" >nnuage3</td>\n",
              "      <td id=\"T_e5b4f_row53_col1\" class=\"data row53 col1\" >Nébulosité couche nuageuse 3</td>\n",
              "      <td id=\"T_e5b4f_row53_col2\" class=\"data row53 col2\" >28989</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row54\" class=\"row_heading level0 row54\" >54</th>\n",
              "      <td id=\"T_e5b4f_row54_col0\" class=\"data row54 col0\" >ctype3</td>\n",
              "      <td id=\"T_e5b4f_row54_col1\" class=\"data row54 col1\" >Type nuage 3</td>\n",
              "      <td id=\"T_e5b4f_row54_col2\" class=\"data row54 col2\" >33701</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row55\" class=\"row_heading level0 row55\" >55</th>\n",
              "      <td id=\"T_e5b4f_row55_col0\" class=\"data row55 col0\" >hnuage3</td>\n",
              "      <td id=\"T_e5b4f_row55_col1\" class=\"data row55 col1\" >Hauteur de base 3</td>\n",
              "      <td id=\"T_e5b4f_row55_col2\" class=\"data row55 col2\" >28989</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row56\" class=\"row_heading level0 row56\" >56</th>\n",
              "      <td id=\"T_e5b4f_row56_col0\" class=\"data row56 col0\" >nnuage4</td>\n",
              "      <td id=\"T_e5b4f_row56_col1\" class=\"data row56 col1\" >Nébulosité couche nuageuse 4</td>\n",
              "      <td id=\"T_e5b4f_row56_col2\" class=\"data row56 col2\" >34471</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row57\" class=\"row_heading level0 row57\" >57</th>\n",
              "      <td id=\"T_e5b4f_row57_col0\" class=\"data row57 col0\" >ctype4</td>\n",
              "      <td id=\"T_e5b4f_row57_col1\" class=\"data row57 col1\" >Type nuage 4</td>\n",
              "      <td id=\"T_e5b4f_row57_col2\" class=\"data row57 col2\" >33259</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row58\" class=\"row_heading level0 row58\" >58</th>\n",
              "      <td id=\"T_e5b4f_row58_col0\" class=\"data row58 col0\" >hnuage4</td>\n",
              "      <td id=\"T_e5b4f_row58_col1\" class=\"data row58 col1\" >Hauteur de base 4</td>\n",
              "      <td id=\"T_e5b4f_row58_col2\" class=\"data row58 col2\" >34471</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row59\" class=\"row_heading level0 row59\" >59</th>\n",
              "      <td id=\"T_e5b4f_row59_col0\" class=\"data row59 col0\" >coordonnees</td>\n",
              "      <td id=\"T_e5b4f_row59_col1\" class=\"data row59 col1\" >Coordonnees</td>\n",
              "      <td id=\"T_e5b4f_row59_col2\" class=\"data row59 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row60\" class=\"row_heading level0 row60\" >60</th>\n",
              "      <td id=\"T_e5b4f_row60_col0\" class=\"data row60 col0\" >nom</td>\n",
              "      <td id=\"T_e5b4f_row60_col1\" class=\"data row60 col1\" >Nom</td>\n",
              "      <td id=\"T_e5b4f_row60_col2\" class=\"data row60 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row61\" class=\"row_heading level0 row61\" >61</th>\n",
              "      <td id=\"T_e5b4f_row61_col0\" class=\"data row61 col0\" >type_de_tendance_barometrique</td>\n",
              "      <td id=\"T_e5b4f_row61_col1\" class=\"data row61 col1\" >Type de tendance barométrique.1</td>\n",
              "      <td id=\"T_e5b4f_row61_col2\" class=\"data row61 col2\" >17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row62\" class=\"row_heading level0 row62\" >62</th>\n",
              "      <td id=\"T_e5b4f_row62_col0\" class=\"data row62 col0\" >temps_passe_1</td>\n",
              "      <td id=\"T_e5b4f_row62_col1\" class=\"data row62 col1\" >Temps passé 1.1</td>\n",
              "      <td id=\"T_e5b4f_row62_col2\" class=\"data row62 col2\" >27007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row63\" class=\"row_heading level0 row63\" >63</th>\n",
              "      <td id=\"T_e5b4f_row63_col0\" class=\"data row63 col0\" >temps_present</td>\n",
              "      <td id=\"T_e5b4f_row63_col1\" class=\"data row63 col1\" >Temps présent.1</td>\n",
              "      <td id=\"T_e5b4f_row63_col2\" class=\"data row63 col2\" >26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row64\" class=\"row_heading level0 row64\" >64</th>\n",
              "      <td id=\"T_e5b4f_row64_col0\" class=\"data row64 col0\" >tc</td>\n",
              "      <td id=\"T_e5b4f_row64_col1\" class=\"data row64 col1\" >Température (°C)</td>\n",
              "      <td id=\"T_e5b4f_row64_col2\" class=\"data row64 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row65\" class=\"row_heading level0 row65\" >65</th>\n",
              "      <td id=\"T_e5b4f_row65_col0\" class=\"data row65 col0\" >tn12c</td>\n",
              "      <td id=\"T_e5b4f_row65_col1\" class=\"data row65 col1\" >Température minimale sur 12 heures (°C)</td>\n",
              "      <td id=\"T_e5b4f_row65_col2\" class=\"data row65 col2\" >25863</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row66\" class=\"row_heading level0 row66\" >66</th>\n",
              "      <td id=\"T_e5b4f_row66_col0\" class=\"data row66 col0\" >tn24c</td>\n",
              "      <td id=\"T_e5b4f_row66_col1\" class=\"data row66 col1\" >Température minimale sur 24 heures (°C)</td>\n",
              "      <td id=\"T_e5b4f_row66_col2\" class=\"data row66 col2\" >34477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row67\" class=\"row_heading level0 row67\" >67</th>\n",
              "      <td id=\"T_e5b4f_row67_col0\" class=\"data row67 col0\" >tx12c</td>\n",
              "      <td id=\"T_e5b4f_row67_col1\" class=\"data row67 col1\" >Température maximale sur 12 heures (°C)</td>\n",
              "      <td id=\"T_e5b4f_row67_col2\" class=\"data row67 col2\" >25863</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row68\" class=\"row_heading level0 row68\" >68</th>\n",
              "      <td id=\"T_e5b4f_row68_col0\" class=\"data row68 col0\" >tx24c</td>\n",
              "      <td id=\"T_e5b4f_row68_col1\" class=\"data row68 col1\" >Température maximale sur 24 heures (°C)</td>\n",
              "      <td id=\"T_e5b4f_row68_col2\" class=\"data row68 col2\" >34477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row69\" class=\"row_heading level0 row69\" >69</th>\n",
              "      <td id=\"T_e5b4f_row69_col0\" class=\"data row69 col0\" >tminsolc</td>\n",
              "      <td id=\"T_e5b4f_row69_col1\" class=\"data row69 col1\" >Température minimale du sol sur 12 heures (en °C)</td>\n",
              "      <td id=\"T_e5b4f_row69_col2\" class=\"data row69 col2\" >7557</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row70\" class=\"row_heading level0 row70\" >70</th>\n",
              "      <td id=\"T_e5b4f_row70_col0\" class=\"data row70 col0\" >latitude</td>\n",
              "      <td id=\"T_e5b4f_row70_col1\" class=\"data row70 col1\" >Latitude</td>\n",
              "      <td id=\"T_e5b4f_row70_col2\" class=\"data row70 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row71\" class=\"row_heading level0 row71\" >71</th>\n",
              "      <td id=\"T_e5b4f_row71_col0\" class=\"data row71 col0\" >longitude</td>\n",
              "      <td id=\"T_e5b4f_row71_col1\" class=\"data row71 col1\" >Longitude</td>\n",
              "      <td id=\"T_e5b4f_row71_col2\" class=\"data row71 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row72\" class=\"row_heading level0 row72\" >72</th>\n",
              "      <td id=\"T_e5b4f_row72_col0\" class=\"data row72 col0\" >altitude</td>\n",
              "      <td id=\"T_e5b4f_row72_col1\" class=\"data row72 col1\" >Altitude</td>\n",
              "      <td id=\"T_e5b4f_row72_col2\" class=\"data row72 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row73\" class=\"row_heading level0 row73\" >73</th>\n",
              "      <td id=\"T_e5b4f_row73_col0\" class=\"data row73 col0\" >libgeo</td>\n",
              "      <td id=\"T_e5b4f_row73_col1\" class=\"data row73 col1\" >communes (name)</td>\n",
              "      <td id=\"T_e5b4f_row73_col2\" class=\"data row73 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row74\" class=\"row_heading level0 row74\" >74</th>\n",
              "      <td id=\"T_e5b4f_row74_col0\" class=\"data row74 col0\" >codegeo</td>\n",
              "      <td id=\"T_e5b4f_row74_col1\" class=\"data row74 col1\" >communes (code)</td>\n",
              "      <td id=\"T_e5b4f_row74_col2\" class=\"data row74 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row75\" class=\"row_heading level0 row75\" >75</th>\n",
              "      <td id=\"T_e5b4f_row75_col0\" class=\"data row75 col0\" >nom_epci</td>\n",
              "      <td id=\"T_e5b4f_row75_col1\" class=\"data row75 col1\" >EPCI (name)</td>\n",
              "      <td id=\"T_e5b4f_row75_col2\" class=\"data row75 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row76\" class=\"row_heading level0 row76\" >76</th>\n",
              "      <td id=\"T_e5b4f_row76_col0\" class=\"data row76 col0\" >code_epci</td>\n",
              "      <td id=\"T_e5b4f_row76_col1\" class=\"data row76 col1\" >EPCI (code)</td>\n",
              "      <td id=\"T_e5b4f_row76_col2\" class=\"data row76 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row77\" class=\"row_heading level0 row77\" >77</th>\n",
              "      <td id=\"T_e5b4f_row77_col0\" class=\"data row77 col0\" >nom_dept</td>\n",
              "      <td id=\"T_e5b4f_row77_col1\" class=\"data row77 col1\" >department (name)</td>\n",
              "      <td id=\"T_e5b4f_row77_col2\" class=\"data row77 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row78\" class=\"row_heading level0 row78\" >78</th>\n",
              "      <td id=\"T_e5b4f_row78_col0\" class=\"data row78 col0\" >code_dep</td>\n",
              "      <td id=\"T_e5b4f_row78_col1\" class=\"data row78 col1\" >department (code)</td>\n",
              "      <td id=\"T_e5b4f_row78_col2\" class=\"data row78 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row79\" class=\"row_heading level0 row79\" >79</th>\n",
              "      <td id=\"T_e5b4f_row79_col0\" class=\"data row79 col0\" >nom_reg</td>\n",
              "      <td id=\"T_e5b4f_row79_col1\" class=\"data row79 col1\" >region (name)</td>\n",
              "      <td id=\"T_e5b4f_row79_col2\" class=\"data row79 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row80\" class=\"row_heading level0 row80\" >80</th>\n",
              "      <td id=\"T_e5b4f_row80_col0\" class=\"data row80 col0\" >code_reg</td>\n",
              "      <td id=\"T_e5b4f_row80_col1\" class=\"data row80 col1\" >region (code)</td>\n",
              "      <td id=\"T_e5b4f_row80_col2\" class=\"data row80 col2\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e5b4f_level0_row81\" class=\"row_heading level0 row81\" >81</th>\n",
              "      <td id=\"T_e5b4f_row81_col0\" class=\"data row81 col0\" >mois_de_l_annee</td>\n",
              "      <td id=\"T_e5b4f_row81_col1\" class=\"data row81 col1\" >mois_de_l_annee</td>\n",
              "      <td id=\"T_e5b4f_row81_col2\" class=\"data row81 col2\" >0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7eca9f9a6890>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "display(df_desc.style.set_properties(**{'text-align': 'left'}))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p37BWcKm4Iqj"
      },
      "source": [
        "### Prepare dateset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "af7kJVBK36_6"
      },
      "outputs": [],
      "source": [
        "columns_used=['date','pmer','tend','cod_tend','dd','ff','td','u','ww','pres','rafper','per','rr1','rr3','tc']\n",
        "\n",
        "to_drop = df.columns.difference(columns_used)\n",
        "df.drop(to_drop, axis=1, inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "-c-aYoY75aMC",
        "outputId": "5375ad3c-8a5a-4a67-bd82-d576220574d1"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-c98dede8-62f4-4111-8d81-a7823f62a3d4\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>date</th>\n",
              "      <th>pmer</th>\n",
              "      <th>tend</th>\n",
              "      <th>cod_tend</th>\n",
              "      <th>dd</th>\n",
              "      <th>ff</th>\n",
              "      <th>td</th>\n",
              "      <th>u</th>\n",
              "      <th>ww</th>\n",
              "      <th>pres</th>\n",
              "      <th>rafper</th>\n",
              "      <th>per</th>\n",
              "      <th>rr1</th>\n",
              "      <th>rr3</th>\n",
              "      <th>tc</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2013-03-30T18:00:00+03:00</td>\n",
              "      <td>100950.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>50.0</td>\n",
              "      <td>5.1</td>\n",
              "      <td>267.05</td>\n",
              "      <td>50</td>\n",
              "      <td>2.0</td>\n",
              "      <td>100370.0</td>\n",
              "      <td>10.8</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2013-03-31T12:00:00+03:00</td>\n",
              "      <td>101460.0</td>\n",
              "      <td>70.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>50.0</td>\n",
              "      <td>4.6</td>\n",
              "      <td>267.65</td>\n",
              "      <td>60</td>\n",
              "      <td>2.0</td>\n",
              "      <td>100870.0</td>\n",
              "      <td>7.2</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2013-03-04T21:00:00+03:00</td>\n",
              "      <td>101130.0</td>\n",
              "      <td>-70.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>170.0</td>\n",
              "      <td>3.1</td>\n",
              "      <td>275.65</td>\n",
              "      <td>66</td>\n",
              "      <td>2.0</td>\n",
              "      <td>100560.0</td>\n",
              "      <td>4.1</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>8.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2012-01-10T03:00:00+03:00</td>\n",
              "      <td>103280.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>270.0</td>\n",
              "      <td>2.6</td>\n",
              "      <td>280.55</td>\n",
              "      <td>92</td>\n",
              "      <td>2.0</td>\n",
              "      <td>102700.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>8.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2012-01-13T12:00:00+03:00</td>\n",
              "      <td>103110.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>280.0</td>\n",
              "      <td>3.1</td>\n",
              "      <td>275.15</td>\n",
              "      <td>96</td>\n",
              "      <td>2.0</td>\n",
              "      <td>102510.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2012-01-16T06:00:00+03:00</td>\n",
              "      <td>102430.0</td>\n",
              "      <td>-30.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>70.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>269.75</td>\n",
              "      <td>78</td>\n",
              "      <td>0.0</td>\n",
              "      <td>101830.0</td>\n",
              "      <td>5.1</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>-0.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2012-01-17T21:00:00+03:00</td>\n",
              "      <td>103010.0</td>\n",
              "      <td>40.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>2.6</td>\n",
              "      <td>270.15</td>\n",
              "      <td>79</td>\n",
              "      <td>2.0</td>\n",
              "      <td>102410.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>-0.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2012-01-18T18:00:00+03:00</td>\n",
              "      <td>102670.0</td>\n",
              "      <td>-130.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>210.0</td>\n",
              "      <td>5.7</td>\n",
              "      <td>275.55</td>\n",
              "      <td>93</td>\n",
              "      <td>50.0</td>\n",
              "      <td>102080.0</td>\n",
              "      <td>12.3</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.2</td>\n",
              "      <td>3.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2012-01-28T00:00:00+03:00</td>\n",
              "      <td>102300.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>3.1</td>\n",
              "      <td>275.15</td>\n",
              "      <td>89</td>\n",
              "      <td>1.0</td>\n",
              "      <td>101710.0</td>\n",
              "      <td>6.2</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2012-02-19T06:00:00+03:00</td>\n",
              "      <td>101510.0</td>\n",
              "      <td>200.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>300.0</td>\n",
              "      <td>4.6</td>\n",
              "      <td>272.75</td>\n",
              "      <td>87</td>\n",
              "      <td>0.0</td>\n",
              "      <td>100920.0</td>\n",
              "      <td>7.2</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2012-02-20T09:00:00+03:00</td>\n",
              "      <td>103450.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>230.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>268.25</td>\n",
              "      <td>91</td>\n",
              "      <td>2.0</td>\n",
              "      <td>102840.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>-3.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2012-02-06T03:00:00+03:00</td>\n",
              "      <td>103310.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>200.0</td>\n",
              "      <td>2.1</td>\n",
              "      <td>262.65</td>\n",
              "      <td>56</td>\n",
              "      <td>0.0</td>\n",
              "      <td>102700.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>-3.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2012-02-03T03:00:00+03:00</td>\n",
              "      <td>103600.0</td>\n",
              "      <td>80.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>40.0</td>\n",
              "      <td>4.6</td>\n",
              "      <td>258.05</td>\n",
              "      <td>51</td>\n",
              "      <td>2.0</td>\n",
              "      <td>102980.0</td>\n",
              "      <td>7.2</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>-7.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>2012-02-03T09:00:00+03:00</td>\n",
              "      <td>103720.0</td>\n",
              "      <td>110.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>40.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>258.05</td>\n",
              "      <td>57</td>\n",
              "      <td>2.0</td>\n",
              "      <td>103090.0</td>\n",
              "      <td>6.7</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>-8.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2012-02-04T15:00:00+03:00</td>\n",
              "      <td>104040.0</td>\n",
              "      <td>-50.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>263.95</td>\n",
              "      <td>62</td>\n",
              "      <td>2.0</td>\n",
              "      <td>103420.0</td>\n",
              "      <td>2.1</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>-3.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2012-02-25T06:00:00+03:00</td>\n",
              "      <td>102750.0</td>\n",
              "      <td>-110.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>290.0</td>\n",
              "      <td>2.1</td>\n",
              "      <td>280.95</td>\n",
              "      <td>98</td>\n",
              "      <td>10.0</td>\n",
              "      <td>102170.0</td>\n",
              "      <td>3.1</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>8.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>2012-03-05T18:00:00+03:00</td>\n",
              "      <td>101420.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>270.0</td>\n",
              "      <td>9.3</td>\n",
              "      <td>273.75</td>\n",
              "      <td>100</td>\n",
              "      <td>68.0</td>\n",
              "      <td>100830.0</td>\n",
              "      <td>12.3</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2012-03-11T09:00:00+03:00</td>\n",
              "      <td>103600.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>3.1</td>\n",
              "      <td>280.75</td>\n",
              "      <td>94</td>\n",
              "      <td>0.0</td>\n",
              "      <td>103010.0</td>\n",
              "      <td>5.1</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>8.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2012-03-11T18:00:00+03:00</td>\n",
              "      <td>103550.0</td>\n",
              "      <td>-130.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>330.0</td>\n",
              "      <td>3.1</td>\n",
              "      <td>279.35</td>\n",
              "      <td>57</td>\n",
              "      <td>2.0</td>\n",
              "      <td>102980.0</td>\n",
              "      <td>5.7</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>14.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2012-02-29T03:00:00+03:00</td>\n",
              "      <td>102650.0</td>\n",
              "      <td>40.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>250.0</td>\n",
              "      <td>2.6</td>\n",
              "      <td>281.25</td>\n",
              "      <td>97</td>\n",
              "      <td>2.0</td>\n",
              "      <td>102070.0</td>\n",
              "      <td>4.1</td>\n",
              "      <td>-10.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>8.5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c98dede8-62f4-4111-8d81-a7823f62a3d4')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-c98dede8-62f4-4111-8d81-a7823f62a3d4 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-c98dede8-62f4-4111-8d81-a7823f62a3d4');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-e78e3dad-fbf8-444e-8062-db303215af2c\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e78e3dad-fbf8-444e-8062-db303215af2c')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-e78e3dad-fbf8-444e-8062-db303215af2c button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "                         date      pmer   tend  cod_tend     dd   ff      td  \\\n",
              "0   2013-03-30T18:00:00+03:00  100950.0   60.0       1.0   50.0  5.1  267.05   \n",
              "1   2013-03-31T12:00:00+03:00  101460.0   70.0       2.0   50.0  4.6  267.65   \n",
              "2   2013-03-04T21:00:00+03:00  101130.0  -70.0       5.0  170.0  3.1  275.65   \n",
              "3   2012-01-10T03:00:00+03:00  103280.0   60.0       2.0  270.0  2.6  280.55   \n",
              "4   2012-01-13T12:00:00+03:00  103110.0  100.0       3.0  280.0  3.1  275.15   \n",
              "5   2012-01-16T06:00:00+03:00  102430.0  -30.0       6.0   70.0  3.6  269.75   \n",
              "6   2012-01-17T21:00:00+03:00  103010.0   40.0       3.0  180.0  2.6  270.15   \n",
              "7   2012-01-18T18:00:00+03:00  102670.0 -130.0       5.0  210.0  5.7  275.55   \n",
              "8   2012-01-28T00:00:00+03:00  102300.0   20.0       1.0  180.0  3.1  275.15   \n",
              "9   2012-02-19T06:00:00+03:00  101510.0  200.0       2.0  300.0  4.6  272.75   \n",
              "10  2012-02-20T09:00:00+03:00  103450.0   60.0       3.0  230.0  0.5  268.25   \n",
              "11  2012-02-06T03:00:00+03:00  103310.0   10.0       4.0  200.0  2.1  262.65   \n",
              "12  2012-02-03T03:00:00+03:00  103600.0   80.0       2.0   40.0  4.6  258.05   \n",
              "13  2012-02-03T09:00:00+03:00  103720.0  110.0       3.0   40.0  3.6  258.05   \n",
              "14  2012-02-04T15:00:00+03:00  104040.0  -50.0       6.0    0.0  0.0  263.95   \n",
              "15  2012-02-25T06:00:00+03:00  102750.0 -110.0       8.0  290.0  2.1  280.95   \n",
              "16  2012-03-05T18:00:00+03:00  101420.0    0.0       5.0  270.0  9.3  273.75   \n",
              "17  2012-03-11T09:00:00+03:00  103600.0   30.0       3.0  360.0  3.1  280.75   \n",
              "18  2012-03-11T18:00:00+03:00  103550.0 -130.0       6.0  330.0  3.1  279.35   \n",
              "19  2012-02-29T03:00:00+03:00  102650.0   40.0       3.0  250.0  2.6  281.25   \n",
              "\n",
              "      u    ww      pres  rafper   per  rr1  rr3    tc  \n",
              "0    50   2.0  100370.0    10.8 -10.0  0.0  0.0   3.4  \n",
              "1    60   2.0  100870.0     7.2 -10.0  0.0  0.0   1.4  \n",
              "2    66   2.0  100560.0     4.1 -10.0  0.0  0.0   8.5  \n",
              "3    92   2.0  102700.0     3.6 -10.0  0.0  0.0   8.6  \n",
              "4    96   2.0  102510.0     3.6 -10.0  0.0  0.0   2.6  \n",
              "5    78   0.0  101830.0     5.1 -10.0  0.0  0.0  -0.5  \n",
              "6    79   2.0  102410.0     3.6 -10.0  0.0  0.0  -0.1  \n",
              "7    93  50.0  102080.0    12.3 -10.0  0.0  0.2   3.4  \n",
              "8    89   1.0  101710.0     6.2 -10.0  0.0  0.0   3.6  \n",
              "9    87   0.0  100920.0     7.2 -10.0  0.0  0.0   1.5  \n",
              "10   91   2.0  102840.0     1.0 -10.0  0.0  0.0  -3.8  \n",
              "11   56   0.0  102700.0     3.6 -10.0  0.0  0.0  -3.9  \n",
              "12   51   2.0  102980.0     7.2 -10.0  0.0  0.0  -7.6  \n",
              "13   57   2.0  103090.0     6.7 -10.0  0.0  0.0  -8.9  \n",
              "14   62   2.0  103420.0     2.1 -10.0  0.0  0.0  -3.6  \n",
              "15   98  10.0  102170.0     3.1 -10.0  0.0  0.0   8.1  \n",
              "16  100  68.0  100830.0    12.3 -10.0  2.0  6.0   0.6  \n",
              "17   94   0.0  103010.0     5.1 -10.0  0.0  0.0   8.5  \n",
              "18   57   2.0  102980.0     5.7 -10.0  0.0  0.0  14.6  \n",
              "19   97   2.0  102070.0     4.1 -10.0  0.0  0.0   8.5  "
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df.head(20)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "otfm8eGi6Y-F",
        "outputId": "1c9b6b85-18fc-4ec2-a7f3-3792f0378090"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<style type=\"text/css\">\n",
              "</style>\n",
              "<table id=\"T_b6951\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_b6951_level0_col0\" class=\"col_heading level0 col0\" >pmer</th>\n",
              "      <th id=\"T_b6951_level0_col1\" class=\"col_heading level0 col1\" >tend</th>\n",
              "      <th id=\"T_b6951_level0_col2\" class=\"col_heading level0 col2\" >cod_tend</th>\n",
              "      <th id=\"T_b6951_level0_col3\" class=\"col_heading level0 col3\" >dd</th>\n",
              "      <th id=\"T_b6951_level0_col4\" class=\"col_heading level0 col4\" >ff</th>\n",
              "      <th id=\"T_b6951_level0_col5\" class=\"col_heading level0 col5\" >td</th>\n",
              "      <th id=\"T_b6951_level0_col6\" class=\"col_heading level0 col6\" >u</th>\n",
              "      <th id=\"T_b6951_level0_col7\" class=\"col_heading level0 col7\" >ww</th>\n",
              "      <th id=\"T_b6951_level0_col8\" class=\"col_heading level0 col8\" >pres</th>\n",
              "      <th id=\"T_b6951_level0_col9\" class=\"col_heading level0 col9\" >rafper</th>\n",
              "      <th id=\"T_b6951_level0_col10\" class=\"col_heading level0 col10\" >per</th>\n",
              "      <th id=\"T_b6951_level0_col11\" class=\"col_heading level0 col11\" >rr1</th>\n",
              "      <th id=\"T_b6951_level0_col12\" class=\"col_heading level0 col12\" >rr3</th>\n",
              "      <th id=\"T_b6951_level0_col13\" class=\"col_heading level0 col13\" >tc</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_b6951_level0_row0\" class=\"row_heading level0 row0\" >count</th>\n",
              "      <td id=\"T_b6951_row0_col0\" class=\"data row0 col0\" >34472.000</td>\n",
              "      <td id=\"T_b6951_row0_col1\" class=\"data row0 col1\" >34453.000</td>\n",
              "      <td id=\"T_b6951_row0_col2\" class=\"data row0 col2\" >34460.000</td>\n",
              "      <td id=\"T_b6951_row0_col3\" class=\"data row0 col3\" >34469.000</td>\n",
              "      <td id=\"T_b6951_row0_col4\" class=\"data row0 col4\" >34471.000</td>\n",
              "      <td id=\"T_b6951_row0_col5\" class=\"data row0 col5\" >34477.000</td>\n",
              "      <td id=\"T_b6951_row0_col6\" class=\"data row0 col6\" >34477.000</td>\n",
              "      <td id=\"T_b6951_row0_col7\" class=\"data row0 col7\" >34451.000</td>\n",
              "      <td id=\"T_b6951_row0_col8\" class=\"data row0 col8\" >34472.000</td>\n",
              "      <td id=\"T_b6951_row0_col9\" class=\"data row0 col9\" >34460.000</td>\n",
              "      <td id=\"T_b6951_row0_col10\" class=\"data row0 col10\" >34471.000</td>\n",
              "      <td id=\"T_b6951_row0_col11\" class=\"data row0 col11\" >34340.000</td>\n",
              "      <td id=\"T_b6951_row0_col12\" class=\"data row0 col12\" >34307.000</td>\n",
              "      <td id=\"T_b6951_row0_col13\" class=\"data row0 col13\" >34477.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_b6951_level0_row1\" class=\"row_heading level0 row1\" >mean</th>\n",
              "      <td id=\"T_b6951_row1_col0\" class=\"data row1 col0\" >101626.234</td>\n",
              "      <td id=\"T_b6951_row1_col1\" class=\"data row1 col1\" >-0.022</td>\n",
              "      <td id=\"T_b6951_row1_col2\" class=\"data row1 col2\" >4.319</td>\n",
              "      <td id=\"T_b6951_row1_col3\" class=\"data row1 col3\" >184.050</td>\n",
              "      <td id=\"T_b6951_row1_col4\" class=\"data row1 col4\" >4.159</td>\n",
              "      <td id=\"T_b6951_row1_col5\" class=\"data row1 col5\" >280.467</td>\n",
              "      <td id=\"T_b6951_row1_col6\" class=\"data row1 col6\" >77.241</td>\n",
              "      <td id=\"T_b6951_row1_col7\" class=\"data row1 col7\" >7.500</td>\n",
              "      <td id=\"T_b6951_row1_col8\" class=\"data row1 col8\" >101057.532</td>\n",
              "      <td id=\"T_b6951_row1_col9\" class=\"data row1 col9\" >7.242</td>\n",
              "      <td id=\"T_b6951_row1_col10\" class=\"data row1 col10\" >-10.000</td>\n",
              "      <td id=\"T_b6951_row1_col11\" class=\"data row1 col11\" >0.078</td>\n",
              "      <td id=\"T_b6951_row1_col12\" class=\"data row1 col12\" >0.244</td>\n",
              "      <td id=\"T_b6951_row1_col13\" class=\"data row1 col13\" >11.657</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_b6951_level0_row2\" class=\"row_heading level0 row2\" >std</th>\n",
              "      <td id=\"T_b6951_row2_col0\" class=\"data row2 col0\" >981.915</td>\n",
              "      <td id=\"T_b6951_row2_col1\" class=\"data row2 col1\" >129.980</td>\n",
              "      <td id=\"T_b6951_row2_col2\" class=\"data row2 col2\" >2.697</td>\n",
              "      <td id=\"T_b6951_row2_col3\" class=\"data row2 col3\" >96.599</td>\n",
              "      <td id=\"T_b6951_row2_col4\" class=\"data row2 col4\" >2.446</td>\n",
              "      <td id=\"T_b6951_row2_col5\" class=\"data row2 col5\" >5.399</td>\n",
              "      <td id=\"T_b6951_row2_col6\" class=\"data row2 col6\" >16.880</td>\n",
              "      <td id=\"T_b6951_row2_col7\" class=\"data row2 col7\" >17.601</td>\n",
              "      <td id=\"T_b6951_row2_col8\" class=\"data row2 col8\" >975.606</td>\n",
              "      <td id=\"T_b6951_row2_col9\" class=\"data row2 col9\" >4.017</td>\n",
              "      <td id=\"T_b6951_row2_col10\" class=\"data row2 col10\" >0.000</td>\n",
              "      <td id=\"T_b6951_row2_col11\" class=\"data row2 col11\" >0.472</td>\n",
              "      <td id=\"T_b6951_row2_col12\" class=\"data row2 col12\" >1.118</td>\n",
              "      <td id=\"T_b6951_row2_col13\" class=\"data row2 col13\" >6.880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_b6951_level0_row3\" class=\"row_heading level0 row3\" >min</th>\n",
              "      <td id=\"T_b6951_row3_col0\" class=\"data row3 col0\" >97180.000</td>\n",
              "      <td id=\"T_b6951_row3_col1\" class=\"data row3 col1\" >-1200.000</td>\n",
              "      <td id=\"T_b6951_row3_col2\" class=\"data row3 col2\" >0.000</td>\n",
              "      <td id=\"T_b6951_row3_col3\" class=\"data row3 col3\" >0.000</td>\n",
              "      <td id=\"T_b6951_row3_col4\" class=\"data row3 col4\" >0.000</td>\n",
              "      <td id=\"T_b6951_row3_col5\" class=\"data row3 col5\" >255.550</td>\n",
              "      <td id=\"T_b6951_row3_col6\" class=\"data row3 col6\" >14.000</td>\n",
              "      <td id=\"T_b6951_row3_col7\" class=\"data row3 col7\" >0.000</td>\n",
              "      <td id=\"T_b6951_row3_col8\" class=\"data row3 col8\" >96630.000</td>\n",
              "      <td id=\"T_b6951_row3_col9\" class=\"data row3 col9\" >0.000</td>\n",
              "      <td id=\"T_b6951_row3_col10\" class=\"data row3 col10\" >-10.000</td>\n",
              "      <td id=\"T_b6951_row3_col11\" class=\"data row3 col11\" >-0.100</td>\n",
              "      <td id=\"T_b6951_row3_col12\" class=\"data row3 col12\" >-0.100</td>\n",
              "      <td id=\"T_b6951_row3_col13\" class=\"data row3 col13\" >-12.300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_b6951_level0_row4\" class=\"row_heading level0 row4\" >25%</th>\n",
              "      <td id=\"T_b6951_row4_col0\" class=\"data row4 col0\" >101070.000</td>\n",
              "      <td id=\"T_b6951_row4_col1\" class=\"data row4 col1\" >-70.000</td>\n",
              "      <td id=\"T_b6951_row4_col2\" class=\"data row4 col2\" >2.000</td>\n",
              "      <td id=\"T_b6951_row4_col3\" class=\"data row4 col3\" >110.000</td>\n",
              "      <td id=\"T_b6951_row4_col4\" class=\"data row4 col4\" >2.400</td>\n",
              "      <td id=\"T_b6951_row4_col5\" class=\"data row4 col5\" >276.750</td>\n",
              "      <td id=\"T_b6951_row4_col6\" class=\"data row4 col6\" >66.000</td>\n",
              "      <td id=\"T_b6951_row4_col7\" class=\"data row4 col7\" >0.000</td>\n",
              "      <td id=\"T_b6951_row4_col8\" class=\"data row4 col8\" >100500.000</td>\n",
              "      <td id=\"T_b6951_row4_col9\" class=\"data row4 col9\" >4.200</td>\n",
              "      <td id=\"T_b6951_row4_col10\" class=\"data row4 col10\" >-10.000</td>\n",
              "      <td id=\"T_b6951_row4_col11\" class=\"data row4 col11\" >0.000</td>\n",
              "      <td id=\"T_b6951_row4_col12\" class=\"data row4 col12\" >0.000</td>\n",
              "      <td id=\"T_b6951_row4_col13\" class=\"data row4 col13\" >6.700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_b6951_level0_row5\" class=\"row_heading level0 row5\" >50%</th>\n",
              "      <td id=\"T_b6951_row5_col0\" class=\"data row5 col0\" >101690.000</td>\n",
              "      <td id=\"T_b6951_row5_col1\" class=\"data row5 col1\" >0.000</td>\n",
              "      <td id=\"T_b6951_row5_col2\" class=\"data row5 col2\" >3.000</td>\n",
              "      <td id=\"T_b6951_row5_col3\" class=\"data row5 col3\" >200.000</td>\n",
              "      <td id=\"T_b6951_row5_col4\" class=\"data row5 col4\" >3.800</td>\n",
              "      <td id=\"T_b6951_row5_col5\" class=\"data row5 col5\" >280.750</td>\n",
              "      <td id=\"T_b6951_row5_col6\" class=\"data row5 col6\" >82.000</td>\n",
              "      <td id=\"T_b6951_row5_col7\" class=\"data row5 col7\" >0.000</td>\n",
              "      <td id=\"T_b6951_row5_col8\" class=\"data row5 col8\" >101130.000</td>\n",
              "      <td id=\"T_b6951_row5_col9\" class=\"data row5 col9\" >6.700</td>\n",
              "      <td id=\"T_b6951_row5_col10\" class=\"data row5 col10\" >-10.000</td>\n",
              "      <td id=\"T_b6951_row5_col11\" class=\"data row5 col11\" >0.000</td>\n",
              "      <td id=\"T_b6951_row5_col12\" class=\"data row5 col12\" >0.000</td>\n",
              "      <td id=\"T_b6951_row5_col13\" class=\"data row5 col13\" >11.300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_b6951_level0_row6\" class=\"row_heading level0 row6\" >75%</th>\n",
              "      <td id=\"T_b6951_row6_col0\" class=\"data row6 col0\" >102280.000</td>\n",
              "      <td id=\"T_b6951_row6_col1\" class=\"data row6 col1\" >70.000</td>\n",
              "      <td id=\"T_b6951_row6_col2\" class=\"data row6 col2\" >7.000</td>\n",
              "      <td id=\"T_b6951_row6_col3\" class=\"data row6 col3\" >250.000</td>\n",
              "      <td id=\"T_b6951_row6_col4\" class=\"data row6 col4\" >5.600</td>\n",
              "      <td id=\"T_b6951_row6_col5\" class=\"data row6 col5\" >284.550</td>\n",
              "      <td id=\"T_b6951_row6_col6\" class=\"data row6 col6\" >91.000</td>\n",
              "      <td id=\"T_b6951_row6_col7\" class=\"data row6 col7\" >2.000</td>\n",
              "      <td id=\"T_b6951_row6_col8\" class=\"data row6 col8\" >101710.000</td>\n",
              "      <td id=\"T_b6951_row6_col9\" class=\"data row6 col9\" >9.600</td>\n",
              "      <td id=\"T_b6951_row6_col10\" class=\"data row6 col10\" >-10.000</td>\n",
              "      <td id=\"T_b6951_row6_col11\" class=\"data row6 col11\" >0.000</td>\n",
              "      <td id=\"T_b6951_row6_col12\" class=\"data row6 col12\" >0.000</td>\n",
              "      <td id=\"T_b6951_row6_col13\" class=\"data row6 col13\" >16.400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_b6951_level0_row7\" class=\"row_heading level0 row7\" >max</th>\n",
              "      <td id=\"T_b6951_row7_col0\" class=\"data row7 col0\" >104890.000</td>\n",
              "      <td id=\"T_b6951_row7_col1\" class=\"data row7 col1\" >1330.000</td>\n",
              "      <td id=\"T_b6951_row7_col2\" class=\"data row7 col2\" >8.000</td>\n",
              "      <td id=\"T_b6951_row7_col3\" class=\"data row7 col3\" >360.000</td>\n",
              "      <td id=\"T_b6951_row7_col4\" class=\"data row7 col4\" >22.600</td>\n",
              "      <td id=\"T_b6951_row7_col5\" class=\"data row7 col5\" >294.950</td>\n",
              "      <td id=\"T_b6951_row7_col6\" class=\"data row7 col6\" >100.000</td>\n",
              "      <td id=\"T_b6951_row7_col7\" class=\"data row7 col7\" >97.000</td>\n",
              "      <td id=\"T_b6951_row7_col8\" class=\"data row7 col8\" >104280.000</td>\n",
              "      <td id=\"T_b6951_row7_col9\" class=\"data row7 col9\" >36.200</td>\n",
              "      <td id=\"T_b6951_row7_col10\" class=\"data row7 col10\" >-10.000</td>\n",
              "      <td id=\"T_b6951_row7_col11\" class=\"data row7 col11\" >26.300</td>\n",
              "      <td id=\"T_b6951_row7_col12\" class=\"data row7 col12\" >46.300</td>\n",
              "      <td id=\"T_b6951_row7_col13\" class=\"data row7 col13\" >41.400</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7eca9f9a6c80>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "display(df.describe().style.format('{:.3f}'))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "_eC1XHUs8Iu5"
      },
      "outputs": [],
      "source": [
        "# per (Periode de mesure de la rafale) doesn' variate, we can drop it\n",
        "df.drop(['per'], axis=1, inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "0OS5S8F58vLk",
        "outputId": "4f4ed7c9-b5f4-4a52-e535-cac241742c8e"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-21bb27e8-de16-4464-b8b9-8740ce81f29e\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Columns</th>\n",
              "      <th>Description</th>\n",
              "      <th>NA</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>date</td>\n",
              "      <td>Date</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>pmer</td>\n",
              "      <td>Pression au niveau mer</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>tend</td>\n",
              "      <td>Variation de pression en 3 heures</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>cod_tend</td>\n",
              "      <td>Type de tendance barométrique</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>dd</td>\n",
              "      <td>Direction du vent moyen 10 mn</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>ff</td>\n",
              "      <td>Vitesse du vent moyen 10 mn</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>td</td>\n",
              "      <td>Point de rosée</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>u</td>\n",
              "      <td>Humidité</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>ww</td>\n",
              "      <td>Temps présent</td>\n",
              "      <td>26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>pres</td>\n",
              "      <td>Pression station</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>rafper</td>\n",
              "      <td>Rafales sur une période</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>rr1</td>\n",
              "      <td>Précipitations dans la dernière heure</td>\n",
              "      <td>137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>rr3</td>\n",
              "      <td>Précipitations dans les 3 dernières heures</td>\n",
              "      <td>170</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>tc</td>\n",
              "      <td>Température (°C)</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-21bb27e8-de16-4464-b8b9-8740ce81f29e')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-21bb27e8-de16-4464-b8b9-8740ce81f29e button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-21bb27e8-de16-4464-b8b9-8740ce81f29e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-709da0ef-1b04-4c33-bcc0-6e838a250dbb\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-709da0ef-1b04-4c33-bcc0-6e838a250dbb')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-709da0ef-1b04-4c33-bcc0-6e838a250dbb button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "     Columns                                 Description   NA\n",
              "0       date                                        Date    0\n",
              "1       pmer                      Pression au niveau mer    5\n",
              "2       tend           Variation de pression en 3 heures   24\n",
              "3   cod_tend               Type de tendance barométrique   17\n",
              "4         dd               Direction du vent moyen 10 mn    8\n",
              "5         ff                 Vitesse du vent moyen 10 mn    6\n",
              "6         td                              Point de rosée    0\n",
              "7          u                                    Humidité    0\n",
              "8         ww                               Temps présent   26\n",
              "9       pres                            Pression station    5\n",
              "10    rafper                     Rafales sur une période   17\n",
              "11       rr1       Précipitations dans la dernière heure  137\n",
              "12       rr3  Précipitations dans les 3 dernières heures  170\n",
              "13        tc                            Température (°C)    0"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "dataset_na = df.isna().sum()\n",
        "dataset_na_counts = dataset_na.tolist()\n",
        "dataset_cols = df.columns.tolist()\n",
        "dataset_descr = [code2desc[c] for c in dataset_cols]\n",
        "\n",
        "# reduce the description to the used columns\n",
        "df_descr = pd.DataFrame({'Columns': dataset_cols, 'Description': dataset_descr, 'NA': dataset_na_counts})\n",
        "\n",
        "display(df_descr)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "yX0xTCLOI3GE",
        "outputId": "07e8411e-9222-41fc-a305-57ebfffdf47d"
      },
      "outputs": [
        {
          "data": {
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              "    .colab-df-convert:hover {\n",
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              "\n",
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              "      fill: #D2E3FC;\n",
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              "      background-color: #434B5C;\n",
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              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-5eff4496-7b26-41be-af0f-c0600358e0d2 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-5eff4496-7b26-41be-af0f-c0600358e0d2');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "\n",
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              "            title=\"Suggest charts\"\n",
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              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
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              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
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              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
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              "  }\n",
              "\n",
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              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "    (() => {\n",
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              "        document.querySelector('#df-35253adc-5a64-4fb9-a2f3-2a492cf0c620 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "  </div>\n"
            ],
            "text/plain": [
              "                        date      pmer   tend  cod_tend     dd   ff      td  \\\n",
              "0  2013-03-30T18:00:00+03:00  100950.0   60.0       1.0   50.0  5.1  267.05   \n",
              "1  2013-03-31T12:00:00+03:00  101460.0   70.0       2.0   50.0  4.6  267.65   \n",
              "2  2013-03-04T21:00:00+03:00  101130.0  -70.0       5.0  170.0  3.1  275.65   \n",
              "3  2012-01-10T03:00:00+03:00  103280.0   60.0       2.0  270.0  2.6  280.55   \n",
              "4  2012-01-13T12:00:00+03:00  103110.0  100.0       3.0  280.0  3.1  275.15   \n",
              "\n",
              "    u   ww      pres  rafper  rr1  rr3   tc  \n",
              "0  50  2.0  100370.0    10.8  0.0  0.0  3.4  \n",
              "1  60  2.0  100870.0     7.2  0.0  0.0  1.4  \n",
              "2  66  2.0  100560.0     4.1  0.0  0.0  8.5  \n",
              "3  92  2.0  102700.0     3.6  0.0  0.0  8.6  \n",
              "4  96  2.0  102510.0     3.6  0.0  0.0  2.6  "
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GaSG5slD_jEF"
      },
      "source": [
        "#### Sorting the dataset by date"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Jt-oF_SBE5KX"
      },
      "outputs": [],
      "source": [
        "df.sort_values(['date'], inplace=True)\n",
        "df.reset_index(drop=True, inplace=True)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YZ7GQ6wP_p7d"
      },
      "source": [
        "#### Interpolate NA values:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "ZpIiiaF_9hxx",
        "outputId": "b1013f4e-853a-42a9-caa5-319f6c7ca635"
      },
      "outputs": [
        {
          "data": {
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              "\n",
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              "\n",
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-4a4fc72c-1504-478d-a8f4-2a0671c2fcc7 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "                          date      pmer   tend  cod_tend     dd   ff      td  \\\n",
              "97   2012-01-13T03:00:00+03:00  102940.0   50.0       1.0  270.0  3.1  275.75   \n",
              "182  2012-01-23T18:00:00+03:00  101830.0  -20.0       5.0  290.0  4.1  276.95   \n",
              "413  2012-02-21T18:00:00+03:00  103120.0    NaN       6.0  230.0  4.1  275.85   \n",
              "414  2012-02-21T21:00:00+03:00  103190.0    NaN       3.0  190.0  4.6  275.05   \n",
              "415  2012-02-22T00:00:00+03:00  103220.0    NaN       1.0  200.0  3.6  274.45   \n",
              "416  2012-02-22T06:00:00+03:00  103150.0    NaN       8.0  200.0  3.1  271.85   \n",
              "417  2012-02-22T09:00:00+03:00  103100.0    NaN       8.0  190.0  2.6  271.85   \n",
              "418  2012-02-22T12:00:00+03:00  103080.0    NaN       5.0  210.0  4.1  273.75   \n",
              "419  2012-02-22T15:00:00+03:00  102930.0    NaN       8.0  220.0  7.7  272.85   \n",
              "644  2012-03-21T18:00:00+03:00  103280.0 -230.0       6.0   90.0  6.2  275.05   \n",
              "\n",
              "      u   ww      pres  rafper  rr1  rr3    tc  \n",
              "97   94  2.0  102350.0     3.1  0.0  NaN   3.5  \n",
              "182  78  0.0  101250.0     8.7  0.0  NaN   7.4  \n",
              "413  70  2.0  102530.0     6.2  0.0  0.0   7.8  \n",
              "414  81  2.0  102600.0     6.7  0.0  0.0   4.9  \n",
              "415  83  2.0  102630.0     4.6  0.0  0.0   3.9  \n",
              "416  88  0.0  102550.0     4.1  0.0  0.0   0.5  \n",
              "417  91  3.0  102500.0     3.6  0.0  0.0  -0.2  \n",
              "418  77  2.0  102490.0     6.2  0.0  0.0   4.3  \n",
              "419  56  2.0  102350.0    11.8  0.0  0.0   8.0  \n",
              "644  38  2.0  102710.0     8.7  NaN  NaN  16.2  "
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "na_rows=df.isna().any(axis=1)\n",
        "display( df[na_rows].head(10) )"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "u-k17Xo0_fal",
        "outputId": "fc501649-e0d5-4022-a695-f1084a493c8c"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-7a3a979e-737e-4144-8af0-fd12513e81c7\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>date</th>\n",
              "      <th>pmer</th>\n",
              "      <th>tend</th>\n",
              "      <th>cod_tend</th>\n",
              "      <th>dd</th>\n",
              "      <th>ff</th>\n",
              "      <th>td</th>\n",
              "      <th>u</th>\n",
              "      <th>ww</th>\n",
              "      <th>pres</th>\n",
              "      <th>rafper</th>\n",
              "      <th>rr1</th>\n",
              "      <th>rr3</th>\n",
              "      <th>tc</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>2012-01-13T03:00:00+03:00</td>\n",
              "      <td>102940.0</td>\n",
              "      <td>50.00</td>\n",
              "      <td>1.0</td>\n",
              "      <td>270.0</td>\n",
              "      <td>3.1</td>\n",
              "      <td>275.75</td>\n",
              "      <td>94</td>\n",
              "      <td>2.0</td>\n",
              "      <td>102350.0</td>\n",
              "      <td>3.1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>182</th>\n",
              "      <td>2012-01-23T18:00:00+03:00</td>\n",
              "      <td>101830.0</td>\n",
              "      <td>-20.00</td>\n",
              "      <td>5.0</td>\n",
              "      <td>290.0</td>\n",
              "      <td>4.1</td>\n",
              "      <td>276.95</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>101250.0</td>\n",
              "      <td>8.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>413</th>\n",
              "      <td>2012-02-21T18:00:00+03:00</td>\n",
              "      <td>103120.0</td>\n",
              "      <td>-13.75</td>\n",
              "      <td>6.0</td>\n",
              "      <td>230.0</td>\n",
              "      <td>4.1</td>\n",
              "      <td>275.85</td>\n",
              "      <td>70</td>\n",
              "      <td>2.0</td>\n",
              "      <td>102530.0</td>\n",
              "      <td>6.2</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>414</th>\n",
              "      <td>2012-02-21T21:00:00+03:00</td>\n",
              "      <td>103190.0</td>\n",
              "      <td>-47.50</td>\n",
              "      <td>3.0</td>\n",
              "      <td>190.0</td>\n",
              "      <td>4.6</td>\n",
              "      <td>275.05</td>\n",
              "      <td>81</td>\n",
              "      <td>2.0</td>\n",
              "      <td>102600.0</td>\n",
              "      <td>6.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>415</th>\n",
              "      <td>2012-02-22T00:00:00+03:00</td>\n",
              "      <td>103220.0</td>\n",
              "      <td>-81.25</td>\n",
              "      <td>1.0</td>\n",
              "      <td>200.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>274.45</td>\n",
              "      <td>83</td>\n",
              "      <td>2.0</td>\n",
              "      <td>102630.0</td>\n",
              "      <td>4.6</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>416</th>\n",
              "      <td>2012-02-22T06:00:00+03:00</td>\n",
              "      <td>103150.0</td>\n",
              "      <td>-115.00</td>\n",
              "      <td>8.0</td>\n",
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              "      <td>3.1</td>\n",
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              "      <td>88</td>\n",
              "      <td>0.0</td>\n",
              "      <td>102550.0</td>\n",
              "      <td>4.1</td>\n",
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              "      <td>0.5</td>\n",
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              "    <tr>\n",
              "      <th>417</th>\n",
              "      <td>2012-02-22T09:00:00+03:00</td>\n",
              "      <td>103100.0</td>\n",
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              "      <td>8.0</td>\n",
              "      <td>190.0</td>\n",
              "      <td>2.6</td>\n",
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              "      <td>102500.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>-0.2</td>\n",
              "    </tr>\n",
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              "      <th>418</th>\n",
              "      <td>2012-02-22T12:00:00+03:00</td>\n",
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              "      <td>5.0</td>\n",
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              "      <td>273.75</td>\n",
              "      <td>77</td>\n",
              "      <td>2.0</td>\n",
              "      <td>102490.0</td>\n",
              "      <td>6.2</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.3</td>\n",
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              "      <td>102930.0</td>\n",
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              "      <td>8.0</td>\n",
              "      <td>220.0</td>\n",
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              "      <td>272.85</td>\n",
              "      <td>56</td>\n",
              "      <td>2.0</td>\n",
              "      <td>102350.0</td>\n",
              "      <td>11.8</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>644</th>\n",
              "      <td>2012-03-21T18:00:00+03:00</td>\n",
              "      <td>103280.0</td>\n",
              "      <td>-230.00</td>\n",
              "      <td>6.0</td>\n",
              "      <td>90.0</td>\n",
              "      <td>6.2</td>\n",
              "      <td>275.05</td>\n",
              "      <td>38</td>\n",
              "      <td>2.0</td>\n",
              "      <td>102710.0</td>\n",
              "      <td>8.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>16.2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7a3a979e-737e-4144-8af0-fd12513e81c7')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-7a3a979e-737e-4144-8af0-fd12513e81c7 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-7a3a979e-737e-4144-8af0-fd12513e81c7');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
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              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-856d052a-3891-4be3-8acd-0a9e5d8495c9\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-856d052a-3891-4be3-8acd-0a9e5d8495c9')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
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              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-856d052a-3891-4be3-8acd-0a9e5d8495c9 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "                          date      pmer    tend  cod_tend     dd   ff  \\\n",
              "97   2012-01-13T03:00:00+03:00  102940.0   50.00       1.0  270.0  3.1   \n",
              "182  2012-01-23T18:00:00+03:00  101830.0  -20.00       5.0  290.0  4.1   \n",
              "413  2012-02-21T18:00:00+03:00  103120.0  -13.75       6.0  230.0  4.1   \n",
              "414  2012-02-21T21:00:00+03:00  103190.0  -47.50       3.0  190.0  4.6   \n",
              "415  2012-02-22T00:00:00+03:00  103220.0  -81.25       1.0  200.0  3.6   \n",
              "416  2012-02-22T06:00:00+03:00  103150.0 -115.00       8.0  200.0  3.1   \n",
              "417  2012-02-22T09:00:00+03:00  103100.0 -148.75       8.0  190.0  2.6   \n",
              "418  2012-02-22T12:00:00+03:00  103080.0 -182.50       5.0  210.0  4.1   \n",
              "419  2012-02-22T15:00:00+03:00  102930.0 -216.25       8.0  220.0  7.7   \n",
              "644  2012-03-21T18:00:00+03:00  103280.0 -230.00       6.0   90.0  6.2   \n",
              "\n",
              "         td   u   ww      pres  rafper  rr1  rr3    tc  \n",
              "97   275.75  94  2.0  102350.0     3.1  0.0  0.0   3.5  \n",
              "182  276.95  78  0.0  101250.0     8.7  0.0  0.0   7.4  \n",
              "413  275.85  70  2.0  102530.0     6.2  0.0  0.0   7.8  \n",
              "414  275.05  81  2.0  102600.0     6.7  0.0  0.0   4.9  \n",
              "415  274.45  83  2.0  102630.0     4.6  0.0  0.0   3.9  \n",
              "416  271.85  88  0.0  102550.0     4.1  0.0  0.0   0.5  \n",
              "417  271.85  91  3.0  102500.0     3.6  0.0  0.0  -0.2  \n",
              "418  273.75  77  2.0  102490.0     6.2  0.0  0.0   4.3  \n",
              "419  272.85  56  2.0  102350.0    11.8  0.0  0.0   8.0  \n",
              "644  275.05  38  2.0  102710.0     8.7  0.0  0.0  16.2  "
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "df.interpolate(method='linear',inplace=True)\n",
        "# practice : do it with sklearn.impute\n",
        "display( df[na_rows].head(10) )"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xLatGj2-C6Bp"
      },
      "source": [
        "#### Summary"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "tIIX2051CWLI",
        "outputId": "1410258e-5f8b-4221-8859-c915b4d657b5"
      },
      "outputs": [
        {
          "data": {
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              "\n",
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              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
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              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "  }\n",
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "     Columns                                 Description  NA\n",
              "0       date                                        Date   0\n",
              "1       pmer                      Pression au niveau mer   0\n",
              "2       tend           Variation de pression en 3 heures   0\n",
              "3   cod_tend               Type de tendance barométrique   0\n",
              "4         dd               Direction du vent moyen 10 mn   0\n",
              "5         ff                 Vitesse du vent moyen 10 mn   0\n",
              "6         td                              Point de rosée   0\n",
              "7          u                                    Humidité   0\n",
              "8         ww                               Temps présent   0\n",
              "9       pres                            Pression station   0\n",
              "10    rafper                     Rafales sur une période   0\n",
              "11       rr1       Précipitations dans la dernière heure   0\n",
              "12       rr3  Précipitations dans les 3 dernières heures   0\n",
              "13        tc                            Température (°C)   0"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "dataset_na = df.isna().sum()\n",
        "dataset_na_counts = dataset_na.tolist()\n",
        "dataset_cols = df.columns.tolist()\n",
        "dataset_descr = [code2desc[c] for c in dataset_cols]\n",
        "\n",
        "df_descr = pd.DataFrame({'Columns': dataset_cols, 'Description': dataset_descr, 'NA': dataset_na_counts})\n",
        "\n",
        "display(df_descr)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "3r4oSbq_DOOz",
        "outputId": "8c5bdd7e-0c4c-48d4-d5f2-eb1c617d5926"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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FLl260LFjR3bv3m28/f333+e5557jwIED9O/fH1AzPLt3786zzz7L22+/DUBeXh7+/v4MGjSI9evXGx8/a9Ys1q1bR1RUFG5ubjXaZ1UyMzNxcXEhIyMDZ2fnmvxKxTXuhk93cTImkzdv7sZdgwNNvRwhhBDCbOj1CoU6PXbWlqZeihBCCCGaocLCQuLi4sjNzTX1UpoVBwcHfHx8KgxoVje+VuOAZmlXC2h6eXkxcuRIVq5cWeb2Tp064e/vz+bNm6+676lTp7J9+3ZSUlKMtw0YMACAAwcOlNl2/PjxREREcP78eQA2bNjA5MmT+fvvv5k0aZJxu5CQEIYMGcIPP/zArFmzarTPqkhAU9TWN7su8L+/z9CvjRu/zxli6uUIIYQQZiG3UMvd3x7gTFwmi6b3ZkJ3b1MvSQghhBDNkKIoaLVadDqdqZfSLFhaWmJlZVVptmt142sNMlY5JiaGxMRE+vXrV+6+AQMGsGHDhir3ER8fT8uWLY1f6/V6jh8/zv3331/hPjdt2kRWVhZOTk4cOXIEoNz379u3LxYWFhw5coRZs2bVaJ9CNJQbevry1oYzhF5KIyo1F393B1MvSQghhGjSdHqFx385QuilNADm/nSIN2/pzp0D25h4ZRXT6xWOx2TQxccJWyvJJhVCCCHMiUajwdraGmtra1MvRZTSIFPO4+LiAPDx8Sl3n4+PD6mpqRQUFFT6+F27dhESEsKMGTOMtxkeU9k+AWJjY43f39LSEk9PzzLb2djY4OHhYdyuJvu8UkFBAZmZmWX+CVEb3i52DG6n9mr981jFf2+iacjML+JoVDp/HYvli+3nWbDmBI//coSoVCk/EEKIxvTm+tNsPpOIrZUF47t5oVfgxbUnWfxfGHUoPgLULIzzidn8EHKRZ1Yd48d9l9Dpa7/PtJxC7l9xkFs+38MdX+0jv0iyO4QQQggh6qpBMjTz8vIAsLUtP+DEzs7OuE1F9ycmJjJz5kzatm3Ls88+W+N9Gj5W1ljUzs6uzHbV3eeV3nnnHV5//fUK7xOipm7u7cveiBT+OBrD3FFB0mi4Cfr3ZBxP/naU/KLy09iSsgr4+aGB8v8mhBCN4LvdkSzfexGAxTN6M7G7N4s3h/PJlnA+3hJOYlYBb97cDSvL6l+3zy/SsfFUPNvOJrI3IoXErJIL778fimb14Wjem9qTjl41q9o5Hp3OnB8PE5OuHk8evpzO/JVH+eyOPlhYlH/P2H8hhcjkHPoFuhPUqoW8rwghhBBCVKJBApr29vYAFWZh5ufnl9mmtJycHG644QaysrLYvXt3mUFBNdmnvb09hYWFFa4tPz+/zHa1WSfAggULmD9/vvHrzMxM/P39K9xWiKpM6O7Dy+tOEZaQzdn4LLr4SB/WpmTz6QQe/fkIWr1CKydb2rg74O/ugK+rHd/siiTkQgp/HY/jpl6+1drfnvPJ/O/vM/Rs7cL0/v70CXCVk1YhhKiGjafiefPv0wAsmNiZST3Uipr54zri6WTLK3+c5JcDl7mUksMLk7rQvbVLpftSFIUTMRn8djCKP4/FkpWvNd5na2VB3zZudPJ2YlVoNEcupzP5k13MGdWeeaODqiwbVxSFnw9c5vU/T1Oo09PGw4GHhrfj9b9OseFEPO+5n2XBxC7G7Qu1et755wzL9lw03ubpZMvgIA+GBHkwobsPLvZS5iaEEEIIYdAgAU1Dubah9Ly0uLg43N3dy2VFFhYWMmXKFI4fP87GjRvp3r17mfsNj6lsnwC+vr7G76/T6UhMTCxTdl5YWEhKSopxu5rs80q2trYVZnYKURsu9taM7tyKjacSWHc0psqApk6vYFlBZoeof9vPJTL3p8No9Qo39/blw+m9y/zuba0s+fC/MN76+zRjOnviaHv1l9V9F1J4YMVB8ov0nInL5LfQKNp7OjK9nx9T+vjR0lFeV4QQoiK7wpN44tcjKArMHBjA7BHtytw/a1AbWjra8sSvR9gbkcINn+5mfDcvnhrXkc7e6vtqoVbP0ah09kYk8+/JeM7GZxkf7+dmzy29WzO0fUuCA1yNk9Nnj2jHy+tOsvlMIp9sCWfDiTg+mtG70mBpXqGOF9eeYM2RGADGdfXig2m9cLG3poWtJU/9doylOy4Q4O7AnQPbEJeRx7yfDnP4cjoAvfxdOROXSWJWAX8cjeWPo7F8uvU8Kx8ejK9rxRfahRBCCCGuNQ0S0GzdujWtWrUiNDS03H0HDhygd+/eZW7T6/XcfffdbNmyhZUrVzJy5Mhyj7OwsKBHjx4V7nP//v20a9fOOLzHsP/Q0NAyU85DQ0PR6/XG+2uyTyEa2i29W7PxVAJrD8fwyIgg3FqUb5ugKArv/nOWXw9G8dGM3ozu7FnBnkR92XM+mdk/HKJQp2dSD28WTetVLpA8e0Q7Vh+O5lJKLp9uCWfBpC6V7A1CL6Zy/3I1mDm8Q0s8nezYcCKO84nZvL3hLAs3nuP2/gHMG90ebxe7hv7xhBDCLGTkFvHWhtOsDI0GYGTHVrxxU7cKM9sndPdm45Mj+HhLOOuOxrDxVAKbTidwfVcvcgt1HLyYWqZ1iI2VBRO6eTOjvz+D23lUWAbu42LP13f34+8Tcbz25ynOJ2YzZcle3ripGzP6+5dZx4WkbOb8eJhzCVlYaODZCZ15eEQ74za3BvtxOSWPxZvDeOWPU6TlFLJsz0VScgpxsrPiw+m9GdfVi/wiHYcvp7EvIoXVh2OITstj5tf7+O3hwXg5y/uDEEIIIUSDDAUCmDp1KuvXrycqKsp425YtWwgLC2PatGlltn3sscf47bff+OKLL5gyZUql+7zttts4ePBgmQDkuXPn2Lp1a5l9jhkzBnd3d5YsWVLm8UuWLMHBwYHJkyfXeJ9CNLTRnT3xc7MnMauAh384RIG2/NCAb3ZFsnTnBTLyinh29XEycotMsNJrw/7iTMpCrZ6xXbz4+PbgCvux2Vlb8uqNXQH4dnck5xOzym0DcDQqnXuXHSS3UMfwDi35+u5+LJreiwMvXsc7U3rQ29+VIp3CD/suMWLhNt5cf5rk7MqHpwkhRHOnKAobTsRx3Yc7jMHMuwa1YcmsPlftjxnYsgWLZ/Rm05MjmNzDB0WBjacS2BWeTH6RHo8WNtzQ04d3pvTg4Atj+eSOYIa2b1lhMNNAo9FwQ09f/ntqJGO7eFKo1fP8mhM8+/tx45Cff0/GcdNneziXkEVLR1t+fmgQj4ws3xf78evaM7WPHzq9wgebwkjJKaSLjzPrHxvGuK5egPreMiSoJfOv78TKRwbj52bPxZRcZn69j6QseW8QQgghhNAotRgF+dlnn5Genk5sbCxLlixhypQpBAcHA2pw0sXFhaioKIKDg3F1deWJJ54gOzubhQsX4ufnx8GDB43l2h999BFPPfUUgwcPZu7cueW+16233kqLFi0AyMrKIjg4mKysLJ555hmsra358MMP0el0HD16lFatWhkf98UXXzBv3jxuu+02xo8fz65du/j+++956623eOGFF4zb1WSfV5OZmYmLiwsZGRk4O0v/Q1E7YQlZTP1iL1kFWm7u7ctHM3obT4T+ORHHnJ8OA+BkZ0VWvpbp/fx4/7Zeplxys5SaU8jIhdvIytcysmMrvrq7b5X90h5cEcrmMwkMCfLgpwfLDgg6GZPBzK/3kZmvZVA7d5bdOwB7m/L7C4lI4cP/znHwYhoA9taW3DkwgDsGBhDUyrHc9kII0RwpisKByFS+3hXJ5jMJAAS1asG7U3vSP9C9xvs7FZvBH0dj8XWxY3BQSzp6Odapb7Fer7BkRwSLNp1Dr0AXH2f6B7rxfcglAAYEuvPZzGA8r5JJWajVc//yg+w+n8z0fn68cXN3Y4l7RaJSc5mxNITYjHw6eTnxy+xBuFdQySGEEEIIYe6qG1+rVUAzMDCQS5cuVXhfZGQkgYGBAJw6dYr58+eze/dubGxsmDx5MosWLcLLy8u4/b333suKFSsq/V6l9wcQHR3NU089xaZNm9Dr9YwaNYrFixfTvn37co/9+uuvWbRoEZGRkfj7+/Poo4/yxBNPlDuIrck+KyMBTVFfdocnc++yA2j1Co+Nac/T13fi8OU07vhqHwVaPXcPbsNNvXyZtjQERYEfHxjIsA4tTb3sZuXtDWf4aucFOns7sW7e0KueZBpEpeYy9sMdFGj1fHx7bwI9WrA3IoWQCynsv5BCgVZPvzZurLh/AC2u0mdTURR2hifz4aZzHIvOMN7er40b0/v7M7mHz1UfL4QQ5ioxM5/fD0ezKjSayOQcAKwsNMwdFcTc0e2r9VrcmPZGJPP4L0dIzi4ZRDl7RDv+b3wnrKsxYV2nV4hNz8Pf3aFa3+9icg7Tl4aQmFVAVx9nfnloEC4OMihICCHM2cmYDA5eTC1zmwYY0r4lHb2k/Z24NjVoQFOUJwFNUZ9WHozi2dXHAXVy64q9an+tMZ09+equvlhZWvDqHydZEXIJPzd7Nj01AgcbCXLVh4TMfEa8v40CrZ5l9/avUZ/SjzaH8dHm8ArvGxDozrf39sPJrnonn4qisPVsIj/tv8z2c4noi1+pW9hYMr2/P3NGBeHpJH3UhBDm70xcJh9vDue/Mwnoil/sWthYckNPXx4Y3rZJn9DFZ+Tz1G9HOZeQxdu39mBCd+8G/X7nE7O5/asQkrMLuWdwG16/uXvVDxJCCNHk6PUKX+6M4ION54zH+aVZW2p45YauzBrUpk5VBUKYIwloNjIJaIr69sHGc3y27bzx626+zqx8eLAxOy+7QMv4xTuJSc/j/qFteaW4j6Oom5fXneSHfZfo28aN3x8ZXKMDiPwiHZM+3sWF5Byc7KwY1M6DIUEeDA7yoKOn01X7s11NQmY+vx+KZlVoFBdTcgGws7bgniGBlQ6QEkKIpu58YjYfbQ5j/fE4423mmo2u1yu1fo2vqR1hSdzz3QEcba3Y/8J1ZvV7EkIIoQ67e3rVUTafSQRgSJAHHo62xvsTMvI5UJy1eXNvX96Z0kOSV8Q1RQKajUwCmqK+KYrCE78e5c9jat+vtfOGlptsuv1cIvcuO4hGA6vnDKFPgJuJVts8RKXmMmbRdop0Cr88NIjBQR413kdGbhFxmXl08HQqNxG9rhRFYVd4Mh/+F8bRqHQAHG2tuH9YW+aNDqqyz6e5Op+YzYHIK0pxNNCjtQvdW7tU+BhFUTgencGByFSi0nKJSs0lKi2PmLQ8fFzsmNrXj9v6+sm0YCFMIDotlw//C2PdkRhjVsrknj48cV2HJp2N2VTo9QpjFm3nYkoub9/ag5kDA0y9JCGEENV0MiaDOT8dIio1DxsrC16/qRu39/cvk0ShKArf7o7knX/OotMrdPB0ZMmsvrT3lJ764togAc1GJgFN0RAKtXr+PRXPgEB3vF0qDrzMX3mUNYdj6ODpyN+PD8fGquq+XaJi/7fqGKsORTOsfUt+fHCgqZdTKUM5+qJNYZyOywTgjgH+vDOlp4lXptLrFT7bdp6jUenc0NOHid19KhyCVB0HIlOZ9c1+CnX6Cu/v6uPM9H5+3BLcGlcHG1JzCllT3IPvXELFE+cNLDQwqpMn0/v5M66rV70HoM2doijEZ+bj42Jv6qWIZkKnV1ix9yIfbDpHbqE6GXxcVy+eGtuRrr5y7FQTX++8wFsbztDNV52OLuWIQgjRtOUUaFm+9yIfbwmnUKvHz82eJXf2pYdfxRfnQT0OfvTnwyRmFdDCxpL3buvJDT19G3HVQpiGBDQbmQQ0hamk5RQybvEOkrMLeeWGrtw/rK2pl2SWIpKyGffhDvQKrJ07hGAzyHbV6xXWHY1h/spjAPz80ECGBJl2QFShVs+zvx9j3dFY421Otlbc2NuXGf386ennUu0T7wtJ2UxZspf03CK6+jjj51YSWMvX6tkXkWIMdNpYWdDbz5UjUWkU6dS3NVsrC0Z2bEWQpyP+bg74u9vj62rP4UtprAyNMk6TB7h3SCCv3dStPn4FzYJOr/Doz4f552Q8g9q58/T1nWo1XVoIg3PxWTy3+rgxu7x/oBsvTe5KL39Xk67LXKXlFDLwnS0UavVm854lhBDXovwiHT/uu8SS7RGk5KhD5EZ3asXiGb1xdai6bVRiVj6P/3KEfRfUaqX7hgayYGIXSWIRzZoENBuZBDSFKf28/zIvrD2Bq4M1O54ZLVNPa+HRnw+z/ngcY7t48s09/U29nBp5ce0Jftp/mTYeDvz7xIhaZ0PWVXaBljk/HmJXeDKWFhpm9PdnV3gSUal5xm08Wtjg5+6Av5s9/u4OtHF34LouXrRysi2zr5TsAqYs2cullFx6+bvy60ODyv1c6bmFrDsSw2+h0ZwpzlQFtRR9en9/burli4t95c+FiKRsftl/mW92R2JloWHbM6OqPW24uXvjr9N8tyeyzG0jOrbi6XEdJQAlakSr0/PJ1vMs2X6eIp2Ck60Vz0/qzB39Axqt52RzZajQmNrHj0XTe5l6OUIIIUrJKdCy+nA0n287T0JmAQAB7g48cV0Hbg1uXaP3QK1OzwebwvhyRwQAfQJc+fzOPsYqmtj0PFYfiuaPY7E42FgyZ2QQ47t5y/usMFsS0GxkEtAUpqTV6Zn48S7CE7OZPaIdL0zqYuolmZUzcZlM/HgXABseH252pY9Z+UVcv3gncRn5Jvv/T84u4L5lBzkRk4G9tSVfzOrD6E6e6PUK+y6k8FtoFP+cjKdQW7503N7aknuGBPLwiHa4tbAhv0jHnd/s59ClNPzc7Fk7d2i5gOeVTsZkEHoxlQFtPWr8/zfrm/3sPp/MnQMDeOvWHjV6bHO0Yu9FXv3zFACv39SNs/GZrAqNRlvc7PDW4NYsvK0nVpaSGSCq9s4/Z1i64wKglpe/eXP3SluoiJo5fDmNKV/sxdbKgv0vXFetTB8hhBANR1EUDl9OZ+XBKNYfjyWnuL2Kr4sdj1/Xgal9/bCuw/HTf6cTmL/yKFn5Wjxa2DB3dHt2hiWxMzyJK6M63XydmT+uI2M6e0pbkmZo06l4hndoZbJEloYmAc1GJgFNYWrbziVy37KD2FhasOXpkZJpVg3hCVmsDI1izeEYUnIKuaGnD5/N7GPqZdXK1rMJ3L88FAsNrJ07tFGz6C6l5HD3dwe4lJKLewsbvru3P70r+P45BVoik3OITsslKjWP6LRcDl9O50RMBlAy4CgiMZu/T8ThbGfFmrlDaO/ZsENC9l9IYcZX+7CxtGDns6Ov6WDLljMJPPR9KHoFnp3Qibmj2gNwOSWXj7eEs/ZINHoFvpzVlwndvU28WtHUHY9O55bP96BX4P2pPZnWz09OquqRoihM/mQ3p+MyeWlyFx4c3s7USxJCiGvC8eh01h+PQ68vCaXoiod3nk/MNt7WtmUL7hsayIz+/vU2vPNSSg5zfjxs7KNvMLCtO9P6+XM5JYdvd0cag6m9/V15+9YeZpewISpWoNXxv/Vn+GHfJab0ac2iab2a5bGVBDQbmQQ0hakpisJd3x5g9/lksw7MNTSdXmH1oWh+OXiZI5fTjbe3drXn19mDzDoQ/MSvR/jjaCydvZ3489FhjdJb52RMBvcuO0BydiH+7vZ8f/9A2rZsUe3HK4rCtnOJfLAxrMyBmbWlhu/vH1irSfO1MX1pCAciU7lvaCCv3nht9tI8EZ3B9KUh5BXpuL2/P+9M6VHuAOndf87y5Y4IhndoyQ8PNN3BWcL0inR6bvx0N2fjs7iply+f3BFs6iU1S4aWM21btmDL/JFSXiiEEA1Mq9Mz4v1txGbkV3i/vbUlk3r4ML2fHwPaujdIsCm/SMf//j7NnvMpTOrhzbS+/gSWOv5OzSlk6c4IVuy9SH6Rntau9myeP9Kss/m0Oj3f7o7kh32XmNrHj8ev63DNDfSMSc9j7k+HOVbcj/yxMe15amzHZvneLwHNRiYBTdEUnI7NZPKnu1AUWDN3CH1kSEA5L6w9wc/7LwNgaaFhTGdPZvTzZ1SnVmZfQpuaU8jYD3eQmlPI/HEdefy6Dg36/XaFJ/HID4fIKdTR1ceZ5ff3x9OpdtmNer3CxlPxfPhfGJHJOSyc1pNbg/3qecWV2xWexF3fHsDWyoLdz42pssS9ubmUksNtX4aQlFXA8A4t+e7e/hWWREWl5jJi4TYUBbY/M6rMwbMQpX22NZwPNoXh5mDN5vkj8XC8tp5TjSWnQMvAt7eQXaDlpwcHMrS9aQfDCSFEc7fhRBxzfzqMm4M1M/oHlLmvbUsHJvXwwcmuacwzSMzK59bP9xKTnsdjY9rz9PWdTL2kWjkVm8Fzq49zMqYk+WF4h5Z8NKN3nY4volJziUzOIaq4eiwqNRdXB2ueGteRlk3suGVHWBJP/nqEtNwiXOyt+WhGb0Z39jT1shqMBDQbmQQ0RVPxf6uOsepQNH3buPH7I4ObZQp6ba0MjeLZ34+j0cDT4zoyvb9/rQNwTdWfx2J5/JcjWFtq+HX2YPq2aZig9h9HY3hm1TGKdApD23vw5ay+9XLwptcr5BRqG/1AUFEUbv1iL0ej0nl4ZDsWTLx6H9IinZ6VoVF08HRiQFvznv59IjqD+5arWbadvZ1Y9cjgq/7+7112gO3nkqRfr6jU+cQsJn28m0Kdno9v783NvVubeknN2svrTvLDvktM7O7Nkll9Tb0cIYRo1qZ9uZeDF9PMJkD478k4HvnxMDaWFmx6aoRZXYzOL9Lx8ZZwvtp5AZ1ewdnOihn9/flh3yXyi/T4uNjx2cw+NT7f0esVXv7jJD8VJ7lcydvZjs/vDKZvG9Me4+v0CqdjM1l/PJavdl1AUdThp1/c2cesqwqro7rxNfNORxJClPP09Z2ws7bg0KU0/j0Zb+rlNBknYzJ4ed1JAJ4a25FHx3RodsFMgBt7+jCxuzdFOoWHvg/lUkpOve07v0jH+cQsPt92nid+PUqRTuHGXr58d2//egtAWlhoTHJVW6PR8NgYtV/kDyGXSMsprHTbnAItD64I5cW1J5m+NIT/W3WMjNyixlpqvdoVnsTtX4WQnF1IN19nvn9gQJW//1kD2wCwKjSK/CJdrb5voVbP7O9DeWbVMeS6qvmKz8jn0KXUMn8HOr3Cs78fp1CnZ0xnT27q5WvCFV4bZg1Sn5ObTicQmVx/r/lCCCHKOhmTwcGLaVhZaIyvvU3d+G7eDO/QkkKdntf/OmU2x12nYzOZ9PEulmyPQKdXmNzDh81Pj+TFyV35Y94w2rVsQVxGPjOWhrBsT2S1fy5FUXjlTzWYqdFARy9Hruvsyb1DAnlxUheCWrUgPjOfGUv38d3u6u+3vsRn5LNsTyQPfR9K8BubuPGz3SzdqQYzZw4MYNUjg5t9MLMmJEOznkiGpmhKPtx0jk+2nsfZzoqPbu/NmM5epl6SSaXnFnLjZ7uJSs1jTGdPvrm7X7PsNWKQW6hlxtJ9nIjJoF2rFqyZM6Ra028VRSE6LY/LqblEpeYayy+i03KJSssjKaugzPb3D23LS5O7NJvfZekBG4+Pac/8Cq66p2QXcP/ygxyLzsDGysI4tb2loy1v3NyNid29zSYret0RNctWq69Zlq1OrzDi/W3EpOfx4fReTOlT89YAP+67xEvFFxj+e2oEHbwadvCTqF/xGfl8ti2c3w5GUaRTsLGyoE+AK0OCWpJbqOPLHRE42lqx6akR+Lram3q514Q7v9nHnvMpNXrNF6KpKtDq6m2AihD16emVx1h9OJqbe/vy8e3m0xv6QlI24z/aSZFO4eu7+zGua+OeGxbp9FhZaKp9jLwqNIqX1p2kQKvHy9mWN2/uzvXdyg6jzMov4rnVx9lwQk3gGda+JW/f2oMAj8qDfYqi8Ob6M3y3JxKNBhZNK38cm12g5fnVx1l/PA6AyT19eG9qTxxtrWryI9eYTq+wYu9FPth0jtzCkgvFTrZWDGznztQ+fkzs4dOga2hKpOS8kUlAUzQlOQVa7vp2P4eLh97MGx3E/HGdrrnGyaCWFDyw4iDbziUR4O7AX48Ow8WhafS1aUiJmfnc+oXaM2dAW3d+eGDAVU8Ocgu1PP7LUTafSbjqfh1trfB3d2DmAH9mDWpjNsG76vrnRBxzfjqMk50V396jTms3DFe6nJLLPcsOEJmcg5uDNd/e2x+9XuG51ceJSFKzosZ19eLdKT2abL9ARVGISMrhj6MxfLr1PAA39fLlg2m9ajREytAfsU+AK2vmDq3RGvKLdIxcuI2ETDVA/tyEzswZFVSjfQjTSMoqYMn2CH7cf8kYzHd1sCa9ggzl/93S3WyyV5qDxMx8bvl8D7EZ+dV6zReiKYrLyOOVP06x9Wwiz47vxMMj5b1BNB1JWQUMfXcrhTo9a+cOIdjMZhW89+9ZlmyPwM9NHRBkZ9047xHHotKZ8VUInk52TOvrx239/PBxqfhiZ36Rjtf/OsUvB6IAGNWpFYun98atRcUX6RRFYdmei7z371kKtHrsrC14elwn7hsaWG42gqIovPfvOb7cEQHAe1N7lOuBWnrbFXsv8r+/z6DVK7Rr1YIvZ/WlYwNdgD8Xn8Vzq49ztHjYTy8/FyZ092FIkAfdfJ3Nfs5DbUhAs5FJQFM0NYVaPW/9fZoVIZcAGNreg49vD25yDY4b2sebw1m8OQxbKwvWzB1CN18XUy+p0ZyLz+K2JXvJKtByS29fFs/oXWEAMjWnkPuWH+RYVDpWFhoCPBzwd3PA392++GPJ1y721s0uiFmaXq8w4eOdhCVkA+qkyv5t3enXxo3vQy6RnF1Aa1d7vn9gAEGtHAE1k+TzbREs2X6eIp1CTz8Xfp09CAebhr2SWxVFUcjM0xKVlsvp2Ez2RiSzNyKFxFKZtg8Ma8uLk2qeZZuYlc+Qd7ai1StseHw4XX2r/773za4L/O/vM8av+we6seqRITX6/qLxbT+XyJwfD5NXXF4+INCd+dd3ZGBbdyKTc9gbkUJIRAoHLqbSr40bn8/s02yyt83F2fhMpi0JIatAy829ffnoitd8rU7P8ZgMOns7mfz1STQviqJwLDoDPzf7Wh1n6vUKPx+4zLv/nCW7QGu8/aXJXXhweLv6XKoQtWY4p+jt78q6eTW7mNsU5BZqGbtoB7EZ+Tx+XQfmj+vYKN/3rm/3sys82fi1hQZGdGzFLb1blwlUanV6Fm8O42RMJhoNzB/bkXmj21frWCIyOYcFa46z70IqAD39XJg3un2ZoO2e88l8tfMCAG/e0p27qnHR9dClNOb9dJj4zHzsrS15d2qPcn3BY9Lz+GzreY5Hp/PYmA5M6O5dyd7KS8spZNnei8ZzCCdbK56f1Jk7+gdc88dQEtBsZBLQFE3VH0djWLDmBLmFOryd7Vh2X3+6+Fwbf6MRSdmM/XAHigILb+vJtH7+pl5So9sVnsR9yw6i1SvcMcCfOSPblynFiErN5Z7vDnAhOQdXB2u+vad/gw0SMheRyTl8sPEcIRdSSL2il2YXH2eW39cfL+fy/VfPxGVy5zf7Sc0pZFxXL76c1bfaWdF6vYJGQ52DxZdTcvlg0znCE7OJTs0lq9SJoYGNlQX92rhxa3DrOj0n5v10mL9PxDFzYABv39qjWo/JKdAy4v1tpOQU8vh1HfhkSzgWGjj00rhKr76LpmHSx7s4HZdJTz8X/m98J4a1b9msL26Yq9Kv+YbWGReSslkZGs3qw9EkZRXg62LHW7f2aNbTUUXjMrQ6Aujs7cSgdh4MCfJgYDsPXOyvXhUTkZTNgtUnOHBRDUT09nelt78ry/deBODNm7tx1+DAhly+EFUq1OoZ+t5WkrIKzHrYnWFCu42VBf89NYI2Hg07IOhoVDq3fL4HSwsNL03uwj8n4zkQmXrVx7i3sOHj23szvEOrGn0vRVH47WAUb204Q1Z++eNfg1du6Mr9w9pWe78p2QU88etRdp9Xg7J3D27Di5O7kJFbxOfbzvPLgSgKdXrj9hO6efPGzd3wrOBcISu/iAORqeyNSGFvRApn4kqmto/t4sX/bumOt0vzm/FQGxLQbGQS0BRNWXhCFo/8eIiIpBx6+rmwbu7Qa+Kqz4f/hfHJlnBGdGzF9/cPMPVyTOa3g5d5bvUJ49dDgjyY3s+fAA8HHv7hEElZatbhivsH0N7T0YQrbVr0eoVzCVmEFB90ONpa8sYt3XG+Sp/JQ5dSuePr/RRq9dw3NJBXb+x21e9hmN64bE8k7g42DA5qyeAg9USwpr0H84t03PTZbmN2qUFLR1vatWzBwHbuDA7yoE+AW72UGe2NSGbm1/txsLFk/wvXVav/pqFUPdDDgf/mj+TGT3dzNj6r1r04ReM4GZPBDZ/uxsbKggMvXCf9GZu40q/53XydORVbcsKk0YDhyP/m3r68ckPXJtsiQ5iHgxdTmbE0BH0FZ5TWlhruGBDAvNHty10ITMzM54vtEfy8/zKFOj0ONpb83/hO3D04EAsNLNx4ji+2q6Wh707pwe0DKi4NFaIxrDsSw5O/HcXL2Zbdz43B2kxLgBVF4e7vDrArPJl+bdz4dfagBi1nfnDFQTafSWRqHz8WTe8FqIkDq0Kj2HM+Ge0VLxxtPBx4aXLXOvXfTszM5/2N58oECwGsLDTcPiCAO2rxWqLTK3y0OczYrimoVQui0/IoKG6/M7idB118nPk+5CLa4mnsL07uwo29fDl0Kc1YxXIiJgPdFT9zJy8nHruuPZN7+MiF4lIkoNnIJKApmrrk7AJGLdxOdoGWj2b05pZg87yyWF2KojD2wx1EJOVIsATYciaB5Xsvsvt8Mle+6nf2dmLF/QMqzDoUNbf+eCyP/nwEgNdu7Mq9Qyu+ChwSkcKCNce5mJJb4f0dPB35YFovevm7Vuv7vvbnKZbvvUhLRxvendKTNh4O+Lk5YG/TMD2SSj/HrvZzGmTkFjHs/a1k5WuN2Q0fbDzHZ9vOM7mnD5/P7NMg6xR199K6E/y47zI39vLl0zvMZwjCtWzhxrN8vk0NBlloYGTHVszo78/goJZ8uiWc7/ZEolfAzcGaV27syi29W8uJ1DUmITOfZ1Ydo13LFsytIOBYHZn5RUz8aBcx6XlM7ePHC5M6sz8yVW1xcj6FC8lqf2lbKwvuGtSGR0YFoQGW7rzA9yEXyS9SgwEjO7bif7d0LzO5V1EU3vr7DN/sVod3fHBbL6b2vbaP5YRpKIrCLZ/v4Vh0Bk+P68hj13Uw9ZLqJCo1l4kf7yK7QNugP8+p2Awmf7IbjQa2zB9Ju1bmnzSx9WwCT/12jIw8tXd43zZuPD2uI0PatwTUyezPrznO8egMQH3/vfJiT6CHA4ODWjIkyINB7Txo5SQXFSsiAc1GJgFNYQ4+33aehRvP0drVni1PN14zaFM4E5fJxI93YWNlwaGXxlYre+xaEJ2Wy++HolkVGk1Meh4D27rz1d39qiwJEzWzZHsE7/17FgsNLJnVl5EdS8pmcgq0fLDpnLHhuZezLa/d2A1HOytjNujx6HT0CjjbWfHzQ4Po3vrqvV93hCVxz3cHAFh2X39Gd2qcUtLvdkfyxvrTALRt2cKYXTqonUe5PmqG4GUnLyf+eWI4FhYajlxO49Yv9uJka8Whl8fVaDCRaBx5hToGvLWZrAItPz04kKHFB+2iadPrFb7bE0mRTuGWYN9yAxiORqXz/OrjnI3PAmgWJ+miZp5ffZxfD6rvQ7ZWFswa1IY5o4Jq1APzqd+OsvZIDP7u9mx4fHi5Y629Ecl8uCmM0EtpADjYWKIBcoon+PYJcOXp6zsxJMijwoC6oii89ucpVoRcwkIDX93Vj7E1mM58IDKVDSfiGNvFiyFBHtdEdZKof4cupTF1yV5srCwIeX5Ms8hqX3M4mvkrj2FpoWH1nCH0rubF85qY+9MhNpyIb3YXQ6NSc/k+5CJD2rdkVMdW5V67tDo9y4unlecX6fF1sTMGMAfXogLrWiUBzUYmAU1hDvKLdIz+YDtxGfnNfrKwIXhyfVcvvrq7n6mX0+To9QoRSdm0a+VY7T6PovoUReGFtSeMQcvKzBwYwPMTO5crY8/ILeKBFQcJvZSGq4M1v84eRGfvit9bUrILmPDxLpKyCrhncBtev7l7vf0cVckp0PLEr0fYejax3BXoTl5OxgBne09Hbvh0N7mFOpbe1Zfx3dSG6Xq9woC3N5OcXcjPDw40XuEWTYfhpMff3Z4dz4yWgEAzUqTT8+mWcGPvw2uhekOoYtLzGLVwG0U6ha4+zpwuLs20t7bk3qGBPDq6PS1srz446s9jsTz+yxEsNLDqkcH0beNe4XaKorAzPJlFm84Zs5a6t3bm6XGdGNWpfDDgSnq9wvNrjrMyNBp7a0tWPTK4yot8oPbmvPmzPcYhQ35u9kzr68+0fn4SUBDVllOg5ZbP9xCemM20vn4snNbL1EuqF4qi8NgvR1h/PI5ADwf+fnx4lc/5mghPyOL6j3aiKLDxyRF08m6Y6eBNWUZeEZl5Rfi52UsFRC1IQLORSUBTmAvDyamTrRXb/29Us7jKeCVFURj9wXYupuSadeNuYd6KdHqe+u0o64/Hlbuvvacjb93SnYHtPCp9fFZ+EbO+PcCxqHQ8Wtjw28ODaO9Z9oBQURRm/3CI/04n0MHTkb8eG2aSzOvM/CIOXFCbnIdcSCnXt8igl58L6+YNLXNg93+rjrHqUDT3D23LKzd2bawli2qavjSEA5GpksHXjL294Qxf7byAjaUF3z8wgEFXeV0SzcOrf5xkRcglBrVz55eHBrEzPJkPN53jWHHAsb2nI1/O6lPuPccgJj2PCR/tJCtfW+1pyYbApl6vVCuQWVqRTs/9yw+yKzwZTydb1s4bSuurBCVzC9UgVFhCNoEeDqTkFBqHhGg06vCNV27oWqbEvTStTs/Z+Kwygz4APJ1s8XOr+DGi+VEUhcd/Pcpfx2LxdLJl/ePD8HRqPu2ZMnKLmPjxTmIz8rm9vz/vTu1Zb/t+8tcjrDsay/huXiy9SxJLRM1JQLORSUBTmAu9XuGmz3dzMiaTuwe34Y1GzOZqLIYBFnbWFhx6aVy9XnEUoqZyC7Xl+pY62FhW62QuI7eImd/s41RsJq2cbPl19iDalppI+VtoFAvWnMDaUsO6eUPp5lt11kpjSMkuKOmjFpHChaQcNBr48YHyJcv/nozjkR8P08bDge3PjJKr2E3IhaRsxizagYUG9jw/plzZsmge9HqFeT8f5p+T8bjYW7Nm7hCCmkGvM1GxxMx8hr2/jUKtvkxmvKIo/Hc6gZf/OElCZgEONpa8N7UnN/byLfP48IQsnl9zgkOX0ggOcGXVw4MbdKiIQWZ+EdOWhHAuIYtOXk6smjO4wiF9iqLwxK9H+fNYLK2cbPn7sWE42Vnz76k4fjsYxb4L6oRlBxtLnrm+E/cMCTRWquj1CutPxPHR5jAuJOWU27dGA/cMDuT/xneSY8trwLI9kbz+12msLDT8OnsQ/QIrzkI2Z/supHDH1/tQFPhyVl8mdPeu8z4jk3O4btF29Aqsf2xYtTKqhbiSBDQbmQQ0hTkxTCe2tNCw6akRze7E5d1/zvLljggm9fDmizv7mno5QtRJWk4hd3y9z9jrriIvTOrM7BFNt4VEfEY+uYXaChvC5xRoCX7jPwp1ejbPH0l7z+b1emTODK+lozu1Ytl9A0y9HNGA8ot03PH1Po5cTifA3YE1c4fUqJeiMB9v/X2ar3dF0ifAldVzhpS7iJSUVcDjvxwh5EIKAPcNDeTxMR3491Q8vx2M4mhUOgAtbCzZ8MRw2pS6yNbQYtLzuPXzPSRmFTC8Q0u+u7d/uWnTy/dE8tpfp7G00PDLQ4MY0LZsECo8IYsX157kwEU1sNnb35V3p/bgYnIui/8L41yC+l7raGuFewsb4+P0ikJ0Wh4ArV3t+d+t3RutX7VofKEXU7n9q31o9Qqv3NCV+4ddffChOTO81zvaWjGjvz8z+vvT0av2JeKGyhs5dhB1IQHNRiYBTWFuHlxxkM1nEhnX1Yuvm1GPSUVRGP7+NqLT8vh8Zh8m9/Qx9ZKEqLPk7ALuW3aQEzEZ5e4b3akV397T36x7G9793QF2hiWxYGJnHh5ZEpjV6RXiMvJo7Sr9h2pKq9Oz7mgsfx6Lxc/NvtJhTZUp0ukZ/M5WkrML6i1rQzRtydkFTPliL5dTc+ng6ciUPn4MCfKgm69zo2Tg1Yf8Ih1puYXXfDaxVqcnNacQzysml6dkFzDsvW3kFemuOkBOq9Pz4X9hfLE9AlAzEw1njFYWGsZ09mTu6PYNMkikKidjMpi+NITcQh2D23kwqYc3g4NaEtSqBYcvpzFjqRqEemlyFx4c3q7Cfej1Cr8cvMy7G86SVdxj08DJzoqHhrfjvqGB5YYc7QxL4oW1J4yBzVt6+/LyDV2bZfuma1liVj43fLKbxKwCbuzlyye3927WxyCFWj13frOPgxfTjLf18ndlRj9/burti2M1s5FTsgt4Y/1p/jgaC8DqOUPo28atQdYsmj8JaDYyCWgKc3M+MZvxH+1Ep1f4dfagZtMz62hUOrd8vgd7a0sOvzwOe5vmO8ldXFsURSEtt6jMbRrA1cHa7A+0V+y9yKt/nmJAW3dWPjwYgFOxGTy3+jgnYzIZ0Nadp8d1vGrPUaEylkz+F8aF5PIlk528nBjZqRXzRrXHxaF8uabBplPxzP7hEC0dbQhZcF25LCjRPEUkZTN1yV7SS73WONlaMbCde7kgoa2VBdPrmMlTXwq0On7Zf5nPt0eQlFXAhG7ePDWu4zU5iCIpq4D7l6sXwG7v78+CSV1wsVef6ws3nuXzbRH0aO3Cn48OrfK947/TCcxfeZSsfC1BrVowo78/twb70crJtAG8LWcSeOj70DLD6DydbCnS6UnLLWJyTx8+uyO4yp8vPiOfl/84yX+nE3CwseT+oW15aHi7q7425hZqWbQpjGV7ItEr0MbDgfXFZe3V9d/pBLLyi7g1uLXZv383N3mFOu5ddoD9kal08HRk3byh10R7Aa1Oz46wJFaGRrHlTCLa4ieXr4sdn9/Zh+CAygOTiqKw7mgMb/x1mrTcIiw08OiY6vXWFaIyEtBsZBLQFObo5XUn+WHfJXq0duGPeUPNOsPLwFBKdUNPHz6b2cfUyxFCVENUai7D39+GpYWGPc+NYUXIRb7aeQHdFaPTh3doyfxxHa96YH0t23Imgff/PWcsmXRzsOaeIYFk5mnZG5Fcpm2Bv7s9S+7sW2lvqweWH2TL2UQeHtGOBZO6NMr6RdMQn5HPPyfj2BuRwr4LKcZhKhWxttQwZ1R75o0Owtaq8S8gFun0/H4omk+3hBObkV/mPo0Gbuzpy5NjO1TY7qI5upicw93fHeByaq7xNk8nW964uTuD23kw9L2tZBdoWXpXX8Z3q17WdWJWPomZBXTzdW5Swbdz8VlsOhVPyIUUQi+lUahVB/i093TkjxoEoRRF4WRMJq3d7MuUmFflaFQ6c388RGxGPlP6tObD6b2r9bhd4Unc9e0BAB4e0Y7nJ3ZuUr/Xa9nF5Bzm/HSYM3GZONpa8cejQ5tdW67qSMoqYN2RGFaEXCQ6LQ9rSw2v3NCVWYPalPtbPZ+Yzf/+Ps32c0kAdPZ24t2pPU2SvS2aFwloNjIJaApzlJxdwKiF28ku0PLRjN7cEmze08D1eoVh720lNiNfSiSFMDPjF+/kXEIWTrZWxhLAST28mTOyPb8evMxvB6OMGQMTu3uzeEZvk0x0NwWtTk9KTiFezpVPV/39UDTPrDoGqCWTs4e3494rSiZTsgsIuZDCe/+eJSo1DxsrC968uRsz+gcYt8kr1PH3iTie/f0YegXpa3qN0+kVTsdmsj+yfGDzREwGW88mAmoQ6b2pPejbpuZDMw5EprJ8byQ39WrN+G5e1Q7u7D2fzPNrThiDd97Odjw6pj3BAa58vu08G07EA2ChgbsHB/LyDV2Nw1+q4+udFzgRk8ENPX0Y3dmzyWcpH49O575lB0nJKcTf3Z5nru/Ex5vDjZnabTwcuJSSSycvJ/55YnizuIhtkF+k4/DlNE7HZjK5p0+jtRw4eDGVGUtD0Cvw2cxgbujpe9Xt03IKmfDxThIyC4y3PTamPU9f36mhlyqqsPFUPM+sPEZWgZaWjjZ8PrPPNV8VkpVfxP+tOs6/p9TX0lt6+/L2lB4oCvx9Io6VB6MIvaSWqdtYWvD4de15eGRQk3+tFOZBApqNTAKawlx9vu08Czeew9fFjq3PjDLrAMGhS6lMXRJCCxtLDr08zqx/FiGuNe//e9bYr83TyZY3b+leJoMoKjWXT7aEs/pwNHoFZvTz573beppquQ1Kr1c4G5/F3ohkQiJSOBCZSlaBlvuHtuWlyV3KBSL2RiRzz3cHKNIp3DEggOcndL5qyWRGbhFPrzrK5jNqMGpaXz9m9Pdn9eEY/joWS3ZxQHlY+5b8+ODAhvtBhVlTFIUNJ+J59c+TJGcXGidAvzS5S7V7biqKwtgPdxBRPFG6e2tn5o/ryOhOnpUGNvV6hSU7Ili06Rx6BVo62jJ3VBAzBwaUed8/FZvB4v/CjH/nU/v4sfC2ntUK5O2/kMKMr/YZv27paMvUvq2Z3s+/SWZs7QxL4pEfD5FbqKObrzPL7uuPp5Md+UU6Pt0aztIdF4wXhD69I7jc5HJRe4s2nePTredxtrPi3ydH4OtacTBVURQe+fEQG08lENSqBdP7+fPOP2cBeHpcRx67rkNjLlsU0+r0LNx4jqU7LwDQr40bn83sg7dL5RcQryWKovDNrkje/fcsOr2Cn5s9aTmF5BTqAPWC0ZjOnjw/sYtc/BT1SgKajUwCmsJc5RfpGPPBdmIz8nl2Qifmjmpv6iXV2ut/nWLZnovc0tuXj24PNvVyhBA1EJOex7yfDtOjtQvPjO9k7Pl2pZ1hSdyz7ACKAu9N7VEmu7A5OHI5jbk/HSbuivJZgxt7+fLBtJ7G8t7whCymLNlLVr6WG3r68MntwdUK2FwZFCotwN2B6f38uGtwYKX/D0IYpOcW8tbfZ1h1KBqAFyZ1ZvaIoCoepQqJSOGOr/dha2WBlYXGeJIcHODKvFHtGdLeAwebktLhjNwinlp51JgZOr2fH6/d1K3MNlfacCKOx345gk6vcHt/f96+tcdVnyNanZ4bPt3N2fgsevm5EJOeR3J2ofH+2/v7886UHk2iTFir0/PN7kg+2HgOrV5hWPuWfHlX33JDPE7HZvLOP2dwtrPmkzuCa5SpKq6uSKfnti9DOBaVzuB2Hvz04MAK/75+O3iZ51afwNpSw9q5Q+ne2oWvdkbw9gY1qHnlUDzR8PR6hQdWHGRbcbn0A8Pa8vzEzpJhWIEDkak8+vNhErPU7OJADwem9fPntr5+V60eEaK2JKDZyCSgKczZ2iPRPPXbMRxtrdjxf6PMclpjWk4h1324g9ScQr65ux9ju3qZeklCiAZiyCy3sbJg9SND6OFXcR/IxpJfpOP1v06TmVeEn7s9/m4O+Ls70NajBQEeDtXez4noDGZ+s4+sfC0ONpYMaOvOkCAPhgS1JCwhi2d/P45WrzC0vQdfzupLXpGOWz/fS0x6Hv3auPHjgwNrnJm+93wyj/96hKx8LZN6+DCtnx+D2no0q3JU0Th+2HeJl9edpIWNJVufGVWtk9x5Px/m7+NxzBwYwDPXd2LpjghWhFwkv0jth2htqSHY343BQR508HLk3X/OEp1WcbuEq/nzWCxP/noEvQJ3DWrDGzd3qzQg+d3uSN5YfxpXB2u2PT0KRzsrtp5NZOXBKLadS0SvwLtTenD7ANNeTDkZow5OOxWbCcDNvX1ZeFsvbKwkGNPYIpNzmPzJLnILdRUGJkvf//zEzjxS6v7PtobzwaYwAOaOCmLu6PbVniot6uaHkIu8/Mcp7Kwt+HB6byb18DH1kpq0xKx8Vh+KoU+AKwPaujeJizqi+ZKAZiOTgKYwZ3q9wk2f7+ZkTCZ3D27DGzd3N/WSamz+yqOsORxDB09H/n58uBzQC9GM6fUKs38IZfOZRFq72rP+sWG41WCYQ3177c9TLN97scL7pgS35t2pPat8TTodm8nMb/aRnlvEgEB3lt3Xv9xQi51hScz58RA5hTq6+jhjZanheHQGgR4OrJk7tEYDLUrLL9KhV5SrZrkJURW9XmHKkr0cjUrnpl6+fHLH1SslErPyGfLOVrR6hQ2PD6err7Px9i+3X+Dfk3HlBv2AmkH8xZ19Kh1oVZnVh6J55vdjKIqaifXS5C7lTsgTs/K57oMdZBVoefvWHswcWDZouXRHBO/8cxZ7a0s2PDGcti1b1GgN9SGvUMdHW8L4ZlckOr2Ci701L9/Qlal9ZGK2Kf164DLPr1EzMJ+b0JmgVo74udnj7WLHrG8PcCwqnUHt3PnpwUHlMmQ/3HSOT7aeB9Rhbo+MDOLuwYHY20jrpIYSk57H9R/uIKdQx+s3deOeIYGmXpIQohQJaDYyCWgKc2co+7K00LDxyRFm1Qdl+7lE7l12EI0GVs8ZQh+ZgCxEs5eRV8RNn+3mUkouIzu24rt7+5ukjHJHWBL3fKdOrH1kZBD5RTqiUnOJSsslIikHnV5heIeWLJlVvgzUIDwhixlf7SM1p5DgAFd+eGBgpdueiM7gvuUHjCWwbg7WrJk71CSBFSGudCI6g5s+342iwC8PDWJwUOVDNQyZacEBrqydO7Tc/YqicDk1l70RKYREpHA0Kp3gAFfeuKn7VXvEXo0h6ARqH96XbuhSZnDW/N+OsuZIDL38XFgzd2i51xS9XuHOb/YTciGFXn4u/D5nSKOWp2bmFzHli72cT8wG4IaePrx6YzdaOZlfZU1zU7pHZkWu1mNTURT+PhHHh5vCjEOcWjra8vCIdrSpRpa/r6s9XXyc6/U9MCO3iKi0XDLyihjY1r3afXHNgaIo3Lf8INvPJdGvjRsrHx4sVQlCNDES0GxkEtAUzcGDK0LZfCaBsV08+eae/qZeTrVkF2gZv3gnMel53D+0La/c2NXUSxJCNJLTsZlMWbKH/CI9s0e0Y8HEzo2aoZSSXcCEj3eRlFXAPYPb8PoV2e3bzyUy96fD5Bbq6N7amWX3DigXeIhIymbG0n0kZxfQo7ULPz44sMq+lZdScrh32UESM/NZfv8A+gfWfLK0EA3lpXUn+HHfZTp6qRUTFQX8dHqFEe9vIyY9j0XTejG1r1+jrc9QZgrqZPT/3dKdsV29OHgxlWlfhqDRwLq5Q+nl71rh42PT85jw0U4y87WNPqHa0HOxpaMt70zpwThpr9OkZOUX8fWuSM7EZRKdlkd0ai5ZBVo0Gvjsjj5M7nn1kmatTs/aIzF8vCWc6LS8Gn1vF3trBrVzZ0hQS4YEedDBy6lGj88p0PLuP2c5dCmNqLRcsvK1xvvMtXqrMoZWWzaWFmx4YrhZJXEIca2QgGYjk4CmaA7OJ2Yz/qOd6PQKf8yr/GC+KXn1j5OsCLmEn5s9m54aISWTQlxj1hyOZv7KYwCM6+rFB9N6NcogG0VRmP3DIf47nUAHT0f+emxYhf0rj0Wlc//yg6TkFBLg7sB39/YjLbeIvedT2BuRzJHL6RTq9HT2duLX2YNwdahe2bhWpyevSFcmu0yIpiA9t5DRH2wnLbeIlyZ34cHh7cpts/l0Ag9+H4qrgzX7FlxX496vdbU3IpkFa05wKSUXgMk9fYhIzOZsfBZ3DPDnnSk9r/r49cdjefTnI1ho4LeHBxsvKqRkF7DvQipZ+UVM6umDcz0+P7U6PSMXbicmPa9ZDkRrjhRFISOviAKtvkaDUwq1elYdiuLPo7EU6fRX3VavqMfv2QXaMrffOySQ127qVu3v+X+rjhkHexm0dLQxVgOsfHgwA9qa/8Wz5OwCxn64g/TcIv5vfCfmjTbfYahCNGcS0GxkEtAUzYWhF+XYLl58c08/Uy/nqg5eTGX60hAUBX58YCDDOrQ09ZKEECbw8/7LvPbnKQp1etp4qP31uvk27KCgXw5cZkFxv7R184Ze9ftFJudw93f7iUqtOOOml58L393b3ywHsglREUNpt6OtFVufHonnFcGc+5YdYNu5JB4a3pYXJ5umsiK/SMfizSW9KAFcHazZ+vSoavWjfXrlMVYfjqa1qz3Xd/MiJCKFs/FZxvtd7K15eGQ77hkcWK4fbm38ezKeR348hJuDNSEmCAKLpkur03MiJoO9ESnsu5DC7vPJKAq8f1tPpvfzr/Lx/5yIY85Ph9Fo4L2pPent74qfmz0ONlYsWHOcXw5E0bZlC/55YrjZ/9099ssR/joWSxcfZ/58dKhMNBeiiZKAZiOTgKZoLs4nZjNu8Q4UhTJN+htDak4h+y6oB2N5hTr83R3wc7M3fnSwLjkhKNLrmb40hAtJOUzr68fCab0abZ1CiKbneHQ6c348TEx6HrZWFrx5S/dqncjVxoWkbCZ/spu8Ih0vTOrM7BFBVT4mMSuf+5cf5GRMJh4tbBgU5GGcYB7o4SDDPESzotcr3LpkL8ei0hnbxZMPpvUyZh9HpeYyYuE2FAW2PTPK5P1fS08LX3hbT6ZV83UjK7+ISZ/sKnehorO3E4U6PReS1F6IHi1smDMqiFmD2tQpGDRjaQj7I1OZOyqIZyd0rvV+RPP36ZZwFv0Xhq2VBavnDLnqAK34jHzGf7STjLyiCv+2MvKKuH7xDhIyC5gzKojnzPhvb+OpeB7+4RCWFhr+mDe0xoPFhBCNRwKajUwCmqI5efTnw6w/HsfkHj58fmefBv1e4QlZ/HIgir0RyWUyG6qrlZMtm58aWesBAUKI5iM9t5CnfjvKtnNJADw7oRNzR9VvOVl+kY5pX4ZwIiaDIUEe/PjAwGoPEyjU6olNz6ONBDDFNeB4dDq3fL4HvQJOtlY8OLwd9w8L5IvtESzZHsHwDi354YGBpl4moPb0TMkpwNOp+mXBoAZD3/r7DG1btWBIkAeD23ng4WiLTq/w17FYFm8OM5a1t7CxpH9bd+OFjJoMcTkVm8HkT3ZjaaFh93Oj8XEpP1hGCAO9XuGh70PZcjYRf3d71j86vMLjZL1e4a7v9rPnfAo9Wruwes4QbKzKZyz+dzqBh74PrTAQqNXp+e90Au4tbBjYrvIhYKZ2Nj6T25aEkF2g5ZGRQTw/0XwDs0JcCySg2cgkoCmak7PxmUz4aBcaDfz31Ajae9assXh1rQqN4qV1JynQlvQH6uTlxOAgDzxa2BCVlktUah5RabnEZeQbS8IMbK0s+OLOPlzXRZriCyFUer3CJ1vD+WhzOJYWGn5/ZDDBAW71tv8Fa07wy4HLuDpY888TwyWwIMRV7AhL4p0NZ4wXLF0drNHpFbLytXw5qy8TunubeIUNq0inZ83haD7Zcp6Y9LKZnC721tw/tC2PjmlfZWDz2d+PsTI0mht6+vDZzIa90Cyah4zcIm78bDeXU3MZ3akV397Tv9zFt292XeB/f5/B3tqS9Y8PI6hV5cNxDMkOXX2c+ePRoVhqNPx1PJaPN4cbJ7PPHRXE/HEdm9xE9ITMfG79fA+xGfkMbOvO9w8MwNbKvEvnhWjuJKDZyCSgKZqb2d+Hsul0ArcGt2bxjN5Vbm94KalO1lF+kY7X/jzFrwejABjeoSUz+vszqJ0HLSvpIafXK+iveLmy0GiqnRklhLh2KIrC478e5a9jsQR6OPD348PL9bDT6RV+3HeJ84nZ+LnZ4+fmgL+7PQHuDpUO5lkZGsWzvx9Ho4EV9w1gRMdWjfHjCGHW9HqFv0/EsXhzmLEM29vZjt3PjW5ygY+GotcrnI3PYm9EMvsupLD/QipZxUNchndoyUczelfaQzclu4DB726lUKtn9ZzB9G1j/oNZROM4FZvBlC/2UqDV8+TYDjwysqQ9SnhCNlOX7KVQp+ftW3swc+DVh0yVHqYzJbg1p2IzOZegXqhwtLUyDiUa3M6DT+4IppVT0+gJnVOgZcZXIZyMyaRdqxasnTNUqrqEMAMS0GxkEtAUzc2J6Axu/Gw3Fhq1x1Ubj8p7XOUV6nhgxUEuJOWwYFJnburlW2lg83JKLnN+OsSp2Ew0Gpg/tiPzRreXwKQQol5l5BUx8aOdxGbkM6OfP+/dVjK1OL9Ix9Mrj/H3ibgKHzuqUyvevLk7/u4OxttOxmQwdYl6Yjh/XEcev65Dg/8MQjQnWp2eP47GsvZIDLMGtWn22ZlXo9Xp+fNYLC+uPUlekQ4fFzs+v7MPfSrIJv9sazgfbAqjp58Lf8wbKu0qRI38fiiaZ1Ydq/T+cV29+OquvtX6u1p7JJqnfivZl5OdFbOHt+O+YW3ZdjaR51YfJ7dQh5ezLZ/P7EO/QNMG33V6hdnFpfceLWxYO3coAR4OVT9QCGFyEtBsZBLQFM3RvcsOsP1cUrlgQGk6vcKcHw+x6XSC8bYxnT353y3d8XUtKcWMTsvl90PRfLc7ksx8Le4tbPj49t4M7yAZTkKIhrHvQgp3fL0PRcFY3pqZX8Ts70PZdyEVa0sNdw5sQ1puIVGpuUSl5ZGUVQCAg40lz1zfiXuGBJKVr5buRaXmMaazJ9/c3U8uwggh6iwsIYtHfjzEhaQcrC01vDCpC3cObGPsY1ik0zPsva0kZBaweEYvbg32M/GKhTl679+zLN0RwRWdmwhwd2Dt3CGVZgdfSVEUnvztKNvOJnLPkEAeHNauTLbj+cQsHvnxMOcTs7Gy0PD8xM48MKytSYLwiqLw2p+nWBFyCVsrC36ZPajCCwZCiKZJApqNTAKaojk6dCmVqUtCsLLQsOPZ0bR2Ld8r7s31p/l2dyQ2lhbcPsCfXw9EUajT08LGkucmdsbNwYaVoVHsPp+M4dWmt78rX9zZp0zAUwghGsJ7/55lyfYIXB2s+f7+ATz7+3HOxmfhaGvFV3f1ZUj7lmW2v5CUzfNrTnAgMhVQX68cbCzZG5FCgLsDfz06TMrVhBD1JrtAy3O/HzdmjNtblwwP0ukVFm48R0tHW/Y8P1r6/olayy/SletFb29tWeOLc1W1mMop0LJgzQn+PBYLwKQe3rw3tSdOdo37vvnjvku8tO4kGg18MbMPE3v4NOr3F0LUjQQ0G5kENEVzNfPrfeyNSKFvGzdeuaErvfxdjfet2HuRV/88BcAndwRzUy9fwhOyeH7NCQ5dSiu3ryFBHszo78+kHj5YXyN9s4QQplWo1TNlyR5OxmQab2vlZMvy+/rTzdelwsfo9Qq/HozinQ1njH3ubK0sWDN3SKWPEUKI2lIUheV7L/LZ1vOk5BSWu//JsR14cmxHE6xMiJpTFIXvQy7xv79PU6RTaNeyBUtm9aWTd8MMGb3SkctpTF8aQpFO4bkJnZkzKqjqBwkhmhQJaDYyCWiK5urw5TRu/2ofhcWTyMd28WL+uI7EZeTx0Peh6BX4v/GdmDe6vfExer3CT/sv8f6/53C0s2JaXz9u6+svfWuEECZxPjGbGz7dRX6RnrYtW/D9/QPK9MesTHxGPq/+eZLt55J4b2pPbglu3QirFUJcq/R6hbDELPaeT2FvRAr7I1Owt7ZkwxPDKx2aKERTdfhyGvN+OkxcRj721pa8M6VHg7+PpmQXcMOnu4nLyGdid2++uLOP9J0VwgxJQLORSUBTNGeXU3L5eEs4a49EG/vv2FhaUKjTc3t/f96Z0qPCg4VCrR4rC5lELoQwvd3hyWw7l8jcUUHV7hdmoNXpr5lpzEKIpkOnV9CAHEcJs5WSXcATvx5l9/lkAD6+vTc3926YoKZOr3D3d/vZcz6Fdq1a8Me8oY1e6i6EqB8S0GxkEtAU14Lzidl8vCWcv4r74gzv0JLv7u0v5eNCCCGEEEKIcnR6hTfXn2b53ou0dLRl6zMjca5FoDG7QMvfx2NZGRpNfEY+13fzYno/f7r4qOfe7/97li+2R+BgY8kf84bSwatxStyFEPVPApqNTAKa4lpyNj6TgxfTmBLcmha2VqZejhBCCCGEEKKJKtDqmPjRLi4k53D/0La8cmPXaj1OURQOXUrjt4NR/H0ijtxCXbltevq5MKidB1/tvADAp3cEc2Mv33pdvxCicUlAs5FJQFMIIYQQQgghhChvZ1gSd393AEsLDX8/PozO3pWfMydm5bPmcAwrQ6O4kJRjvL1dyxZM7+9Pu5YtWHskhs1nEijSlYQz7hsayKs3dmvQn0MI0fCqG1+rcZ1odnY2r776KhMmTMDd3R2NRsPy5csr3PbMmTNMmDABR0dH3N3dueuuu0hKSiq33VtvvcVNN92El5cXGo2G1157rdLvHxMTw/Tp03F1dcXZ2Zmbb76ZCxcuVLjtt99+S5cuXbCzs6NDhw58+umndd6nEEIIIYQQQgghqm9Ex1ZM6OaNTq/wyrpTXJlXpSgK284m8uCKUAa/s5V3/znLhaQc7K0tmdbXj1WPDGbL0yN5ZGQQ13fzZsmsvuxbcB0vTe5Cj9YuTOrhzQuTupjopxNCmEKNa0WTk5N54403CAgIoFevXmzfvr3C7aKjoxkxYgQuLi68/fbbZGdn88EHH3DixAkOHDiAjY2NcduXXnoJb29vgoOD2bhxY6XfOzs7m9GjR5ORkcELL7yAtbU1ixcvZuTIkRw9ehQPDw/jtkuXLuWRRx5h6tSpzJ8/n127dvH444+Tm5vLc889V6t9CiGEEEIIIYQQouZevrEr28MSOXAxlT+Oxhqnnken5fLSupNsP1eS/NQnwJUZ/f2Z3NMXx0paXHk42vLg8HY8OLxdo6xfCNG01Dig6ePjQ1xcHN7e3oSGhtK/f/8Kt3v77bfJycnh0KFDBAQEADBgwADGjRvH8uXLmT17tnHbyMhIAgMDSU5OplWrVpV+7y+++ILw8HAOHDhg/L4TJ06ke/fuLFq0iLfffhuAvLw8XnzxRSZPnszvv/8OwEMPPYRer+fNN99k9uzZuLm51WifQgghhBBCCCGEqJ3WrvY8NqYDCzee460NZxjd2ZO1h6N5f+M5cgt12FhacNfgNtze31+G+gghqlTjknNbW1u8vb2r3G716tXccMMNxmAmwNixY+nYsSMrV64ss21gYGC1vvfvv/9O//79ywRRO3fuzHXXXVdmn9u2bSMlJYW5c+eWefy8efPIycnh77//rvE+hRBCCCGEEEIIUXsPDm9L25YtSMoqYNTCbbz212lyC3X0a+PGhieG8fINXSWYKYSolhoHNKsjJiaGxMRE+vXrV+6+AQMGcOTIkRrvU6/Xc/z48Ur3GRERQVZWFoBx/1du27dvXywsLIz312SfVyooKCAzM7PMPyGEEEIIIYQQQlTM1sqSV4unnKflFuFoa8Wbt3Rn5cODae8pgUwhRPU1SEAzLi4OUMvTr+Tj40NqaioFBQU12qfhMZXtEyA2Ntb4/S0tLfH09CyznY2NDR4eHsbtarLPK73zzju4uLgY//n7+9fo5xFCCCGEEEIIIa41ozp58n/jO3F7f382PTWCuwa1wcJCY+plCSHMTI17aFZHXl4eoJanX8nOzs64TUX313Wfho+lhw5duW3p7aq7zystWLCA+fPnG7/OzMyUoKYQQgghhBBCCFGFeaPbm3oJQggz1yABTXt7e4AKszDz8/PLbNMQ+7S3t6ewsLDC/eTn55fZrrbrtLW1rVFAVgghhBBCCCGEEEIIUXcNEtA0lGsbSs9Li4uLw93dvcbBQMNjKtsngK+vr/H763Q6EhMTy5SdFxYWkpKSYtyuJvusiqIoANJLUwghhBBCCCGEEEKIWjDE1Qxxtso0SECzdevWtGrVitDQ0HL3HThwgN69e9d4nxYWFvTo0aPCfe7fv5927drh5KQ2ETbsPzQ0lEmTJhm3Cw0NRa/XG++vyT6rYhgeJGXnQgghhBBCCCGEEELUXlZWFi4uLpXe3yABTYCpU6eyYsUKoqKijEG+LVu2EBYWxlNPPVWrfd522208//zzhIaGGieTnzt3jq1bt/LMM88YtxszZgzu7u4sWbKkTEBzyZIlODg4MHny5Brvsyq+vr5ERUXh5OSERnPtNjQ29BKNiorC2dnZ1MsRQlyFPF+FMA/yXBXCfMjzVQjzIc9XIZomRVHIysqqsmJao1SVw1mBzz77jPT0dGJjY1myZAlTpkwhODgYgMceewwXFxeioqIIDg7G1dWVJ554guzsbBYuXIifnx8HDx4sU3L+ww8/cOnSJXJzc3nnnXcYPXo0Y8aMAeCuu+6iTZs2gBqdDQ4OJisri2eeeQZra2s+/PBDdDodR48epVWrVsZ9fvHFF8ybN4/bbruN8ePHs2vXLr7//nveeustXnjhBeN2NdmnqFpmZiYuLi5kZGTIm4IQTZw8X4UwD/JcFcJ8yPNVCPMhz1chzFutApqBgYFcunSpwvsiIyMJDAwE4NSpU8yfP5/du3djY2PD5MmTWbRoEV5eXmUeM2rUKHbs2FHh/rZt28aoUaOMX0dHR/PUU0+xadMm9Ho9o0aNYvHixbRvX35K2tdff82iRYuIjIzE39+fRx99lCeeeKJcBmVN9imuTt4UhDAf8nwVwjzIc1UI8yHPVyHMhzxfhTBvtQpoClEZeVMQwnzI81UI8yDPVSHMhzxfhTAf8nwVwrxZmHoBonmxtbXl1VdfrfEUeyFE45PnqxDmQZ6rQpgPeb4KYT7k+SqEeZMMTSGEEEIIIYQQQgghhNmQDE0hhBBCCCGEEEIIIYTZkICmEEIIIYQQQgghhBDCbEhAUwghhBBCCCGEEEIIYTYkoCmEEEIIIYQQQgghhDAbEtAUQgghhBBCCCGEEEKYDQloCiGEEEIIIYQQQgghzIYENIUQQgghhBBCCCGEEGZDAppCCCGEEEIIIYQQQgizIQFNIYQQQgghhBBCCCGE2ZCAphBCCCGEEEIIIYQQwmxIQFMIIYQQQgghhBBCCGE2JKAphBBCCCGEEEIIIYQwG1amXkBzodfriY2NxcnJCY1GY+rlCCGEEEIIIYQQQghhVhRFISsrC19fXywsKs/DlIBmPYmNjcXf39/UyxBCCCGEEEIIIYQQwqxFRUXh5+dX6f0S0KwnTk5OgPoLd3Z2NvFqhBBCCCGEEEIIIYQwL5mZmfj7+xvjbJWRgGY9MZSZOzs7S0BTCCGEEEIIIYQQQohaqqqdo1kNBTp48CCPPvoo3bp1o0WLFgQEBDB9+nTCwsLKbXvmzBkmTJiAo6Mj7u7u3HXXXSQlJZXbTq/X8/7779O2bVvs7Ozo2bMnv/zyS2P8OEKIxpCTAoU5pl6FEEIIIYQQQggh6olZZWi+99577Nmzh2nTptGzZ0/i4+P57LPP6NOnD/v27aN79+4AREdHM2LECFxcXHj77bfJzs7mgw8+4MSJExw4cAAbGxvjPl988UXeffddHnroIfr3788ff/zBzJkz0Wg03H777ab6UYUQ9SEzFj4fCL694Z6/TL0aIYQQQgghhBBC1AONoiiKqRdRXXv37qVfv35lApLh4eH06NGD2267jR9//BGAuXPnsnz5cs6ePUtAQAAAmzdvZty4cSxdupTZs2cDEBMTQ9u2bZk9ezafffYZoE5TGjlyJJGRkVy8eBFLS8tqrS0zMxMXFxcyMjKk5FyIpuLoz7BuDqCBBdFg62jqFQkhhBBCCCGEEKIS1Y2vmVWG5pAhQ8rd1qFDB7p168aZM2eMt61evZobbrjBGMwEGDt2LB07dmTlypXGgOYff/xBUVERc+fONW6n0WiYM2cOM2fOJCQkhGHDhjXgTySEaFBRB4o/USDxNPgPMOlyhBBCCCGEEEI0DzqdjqKiIlMvw+xYW1tXO3nwaswqoFkRRVFISEigW7dugJp1mZiYSL9+/cptO2DAADZs2GD8+siRI7Ro0YIuXbqU285wvwQ0hTBj0QdLPo8/LgFNIYQQQgghhBB1oigK8fHxpKenm3opZsvV1RVvb+8qB/9cjdkHNH/66SdiYmJ44403AIiLiwPAx8en3LY+Pj6kpqZSUFCAra0tcXFxeHl5lfsFGh4bGxtb6fctKCigoKDA+HVmZmadfxYhRD0qyFKzMg3iT5huLUIIIYQQQgghmgVDMNPT0xMHB4c6BeWuNYqikJubS2JiIlBx7K66zDqgefbsWebNm8fgwYO55557AMjLywPA1ta23PZ2dnbGbWxtbY0fr7ZdZd555x1ef/31Ov8MQogGEnMYFH3J1xLQFEKI2svPgAvbocN4sLYz9WqEEEIIIUxCp9MZg5keHh6mXo5Zsre3ByAxMRFPT89al59b1OeiGlN8fDyTJ0/GxcWF33//3fgLMPxiSmdPGuTn55fZxt7evlrbVWTBggVkZGQY/0VFRdXtBxJC1K/o4v6Z3j3VjwmnQKc13XqEEMKc7VwIK++G0G9NvRIhhBBCCJMx9Mx0cHAw8UrMm+H3V5cepGYZ0MzIyGDixImkp6fz77//4uvra7zPkK5qKD0vLS4uDnd3d2NWpo+PD/Hx8Vw56N3w2NL7vZKtrS3Ozs5l/gkhmpDoUPVjzxlg3QK0+ZAaYdo1CSGEuTJkucceMe06RPOTGQeHf4CifFOvRAghhKg2KTOvm/r4/ZldQDM/P58bb7yRsLAw1q9fT9euXcvc37p1a1q1akVoaGi5xx44cIDevXsbv+7duze5ubllJqQD7N+/33i/EMIMKUrJQKCAQeDdXf1cys6FEKJ2Ui6oH5POmnYdovnZ8gb8+SicWGXqlQghhBDCjJhVQFOn0zFjxgxCQkJYtWoVgwcPrnC7qVOnsn79+jJl4Fu2bCEsLIxp06YZb7v55puxtrbmiy++MN6mKApffvklrVu3ZsiQIQ33wwghGk7qBchNAUtbteTcu4d6e/xx065LCCHMUVE+ZBQfUyWHg15n2vWI5sVQPZFy3rTrMBeHlsOlkLrvR1cEIV9AwumqtxVClJVwGg6tUJMohBAmY1ZDgZ5++mn+/PNPbrzxRlJTU/nxxx/L3D9r1iwAXnjhBVatWsXo0aN54oknyM7OZuHChfTo0YP77rvPuL2fnx9PPvkkCxcupKioiP79+7Nu3Tp27drFTz/9VOvGpEIIE4sq7p/p0wusbEoFNCVDUwghaiztIlB80qbNh/TL4N7WlCsSzUlmbNmPonLxJ+GvJ8DJF54+U/X2VxO2ETYugLYj4Z4/62d9QlwLFAVW3QPJYeAaAEGjTb0iIZokjUbD2rVrueWWWxrse5hVQPPo0aMA/PXXX/z111/l7jcENP39/dmxYwfz58/n+eefx8bGhsmTJ7No0aJyU83fffdd3NzcWLp0KcuXL6dDhw78+OOPzJw5s8F/HiFEAzGUm/sPUD8aAppxx9WDEOl3IoQQ1Zd6oezXyWES0BT1Q6+HrOK+9xLQrFpymPoxKxayEsDJq/b7MjyvU6S/uBA1khxe8lxMPCMBTWFWRo0aRe/evfnoo49MvZR6YVYBze3bt1d7227durFx48Yqt7OwsGDBggUsWLCgDisTQjQphgnnfv3Vj55dQWMBucmQnQBO3qZbmxBCmJsrB6olnYWO402zFtG85CaDXqt+nhlt2rWYg/RLJZ/Hn6hbQNMQQM6KVcvPLa3rtjYhrhXnNpR8LgNHhTAps+qhKYQQVSrIhoRT6ueGDE1re2jZUf28umXnod/Bga/rf31CCGFuDBlcVnbqx6RzpluLaF5KZ2Vmxko/uqqklQ5o1rEveGaM+lHRl3wuhKjauX9KPpcM56ppC+C/V0tagjVXigKFOab5V833znvvvZcdO3bw8ccfo9Fo0Gg0XLx4kZMnTzJx4kQcHR3x8vLirrvuIjk52fi4UaNG8fjjj/Pss8/i7u6Ot7c3r732Wpl9h4eHM2LECOzs7OjatSv//fdfff52K2VWGZpCCFGl2MPqwblza3D2Lbndu4eaVRR/HDqMu/o+shNh/VPq5wGDSkrWhRDiWmTIQGk3CsL+lYCmqD+GcnMAXSHkJINjK9Otp6m7MkOzLkoHMdOjwC2wbvsT4lqQkwxR+0u+vrIliyjv2C+w5yO4vA8eqLqC1mwV5cLbvlVv1xBeiAWbFlVu9vHHHxMWFkb37t154403ALC2tmbAgAE8+OCDLF68mLy8PJ577jmmT5/O1q1bjY9dsWIF8+fPZ//+/YSEhHDvvfcydOhQxo0bh16vZ8qUKXh5ebF//34yMjJ48sknG+qnLUMyNIUQzYuhf6ah3NygJoOBYo+UfB66rH7WJYQQ5io1Uv3YaaL6MemcZNKJ+nFl30zJFLy6tPoMaJb63WdE1W1fQlwrwjYCCjj7qV9nRIG20KRLavIu7lE/SvDX5FxcXLCxscHBwQFvb2+8vb1ZsmQJwcHBvP3223Tu3Jng4GC+++47tm3bRlhYmPGxPXv25NVXX6VDhw7cfffd9OvXjy1btgCwefNmzp49y/fff0+vXr0YMWIEb7/9dqP8TJKhKYRoXqKuGAhkUJOAZszhks+P/wbjXgdbp/pZnxBCmJOifMgo7m3Y4XrQWEJhlppZ52yiTATRfJTO0AQ1yObb2yRLafL0+rKBx5TzaqlhNbJyytEVQVZ8ydfpEtAUoloM/TOD74SQz6EwG9IuQquOJl1Wk6UocKk4oJmTCIW5YONg2jU1FGsHNVPSVN+7lo4dO8a2bdtwdHQsd19ERAQdO6p/2z179ixzn4+PD4mJiQCcOXMGf39/fH1LjgsHDx5c6zXVhAQ0hRDNh6KUGgh0RUDTqzigmRKh9tm0Lf+ibVQ6Q7MwG078Dv3uq9+1CnEtUxTY8H/qhYKxr5p6NeJq0iIBBWxdwMkH3NtBSrjawkMCmqKuJEOz+rLj1bJ8jSXYu6kDlRJOg3//qh97pax4oFSWdfrlelumEM1WUT5EFJfgdpqkBjfjT6htWSSgWbH0S2Vf1zOioFUn062nIWk0tbvAZGLZ2dnceOONvPfee+Xu8/HxMX5ubV12cJxGo0Gv1zf4+qoiJedCiOYj9QLkpoClDfiUvYqEYyv1ZBwFEk9Xvg9FKQlodr1F/Rj6nZRXClGf0iLh4New+0O1WbxougwDD9zbqgfrhhMR6aMp6oMhoGnnUvy1BDQrZSg3d/EryWKt7WCgKwPJGRLQFKJKkTvVPolOvuDTC9yD1NullLpyl/aW/bp02wxhEjY2Nuh0OuPXffr04dSpUwQGBtK+ffsy/1q0qF6AtkuXLkRFRREXV1J1sW/fvnpfe0UkoCmEaD6iQ9WPPr3Ayrb8/cay86ucAGTGqiURGksY/zZY2qrbly5DF0LUTelgWH6G6dYhqmY4UfMoPnFr1Vn9WN2AZkoEfDMOwjbV/9qE+TOUnLfuq37MaEIBzc2vw8+3q+XZTYFhIJBbm5q10alIZnEbCUub4n1Lybm4BhVkwdpH4OcZ1bu4aig37zRRvcBneF+USeeVM/TPNEiXgKapBQYGsn//fi5evEhycjLz5s0jNTWVO+64g4MHDxIREcHGjRu57777ygQ+r2bs2LF07NiRe+65h2PHjrFr1y5efPHFBv5JVBLQFEI0H5WVmxtU5wTAkJ3p2QVcWkP3KerXod/VzxqFEBLQNCeGCeeGTJSaZmge+VF9bf73ebUHoBClZRoCmv2KvzZR/7Er6bSw91MI+wfijpl6NSpDZpNrQD0ENIt/z77BxV/HyPNTXFtSL6gX2479AmH/wuk/r769Xq9uB2q5OagtWKDkfVKUZ+if2bK4JD/tosmWIlTPPPMMlpaWdO3alVatWlFYWMiePXvQ6XRcf/319OjRgyeffBJXV1csLKoXLrSwsGDt2rXk5eUZJ6a/9dZbDfyTqKSHphCi+YgqDmhW1k+qJgFNQzlXv/vVg52Tq2H8/9S+VUKIuikdDMtLN9ky6kV2Ihz+Hk6thfZj1SFizYmx5Lz4xM0Q0EyuZkAz8Yz6MTUCLu6EdqPqdXnCjBXmQEHxBQ2/4vftplJynhEF+uLMzORw8Otn2vVASWaTayB4F7fVSTgFeh1YWNZsX4aAZut+anWLrhCyE8DZ5+qPE81XXhr8NF3NPhw+39SraVgXdsCqe9SfWWMBil5NXOg5rfLHxB1VM8ptHKHtcPU2KTm/usxYtcWQxgJ6TIdt/5MMzSagY8eOhISElLt9zZo1lT5m+/bt5W5bt25duf3u2rWrzG1KI7RskwxNIUTzUJijHthDyYnRlUqfAOi0FW9jDGgGl+zLqzto8+DYr/W3XiGuZclmnqGpKHBxN6y6Dz7sClvfhISTsO+L5tcTNDVS/WgorfPoAGjUfsU5yVU/PvFUyeeS6S5KM2Rn2jiWBMozY5tGz+rSGVcp4aZbR2lppUrO3dupU221ebUrd80oLjl3DQDn1urnMhjo2nbuXzWbfs/HTeM5WB8URc2sLP3vwNfww61qMNO3Dzy4WW0zdXlvyQW4ipz7R/0YNKakrZXhfTEjuvm999cHQ/9M757g3V39XHpoinomAU0hRPMQewQUndqo28Wv4m3c2oJ1C9DmV1weUnogkCGgqdGUTDiX4UCiqYvYBgs7QNhGU6+kcopyRcl5usmWUmur7oXlk+HUGjWLy6+/OtREV2i68tTCHPhyOKydU3/7LMor6bVnyESxcVCDIKBOOr+agqyyQZKzfxdPVxYCyCrOEnTyKR7apwFdgRosN7WUUhlXyU0koGl4Lrm2UTMyvbqpX9dmMJAhQ9OlNbj6q59n1KGPZtQB+KATnPi99vu4VigK/HonrLix8ovrpmA4/s1Ph5TzJl1KvUg4Be8FwhtuZf9teEY9X+g5A+7boPbv7TRRfUzossr3ZwhoGsrNAVq0AhsnNcNTSqnLu7hb/Rg4TH3dAsnQFPVOAppCiOahqnJzAAuLkiuEFZWdp1+GvFSwsFazMg16TFcDoclhJb1ghGiKQr9Th1rtX1o/+2uIk63MGCjMLvna3AKa2kI485f6efBd8PAuNcOjzVD1NsNrUWOLOaQGNo79DPEn62efhuxMOxdwcC+5vbqDgRKLA56O3uA/CPRaOPJD/azNQFHkQpO5MgTVnH3AygYcPdWvDdmDplS6hLQpBHd0RSUXF9yKAwN16aNp/N37gktxQLMuGZr7lkB2fP0/v5uj9Etwdr06Mbsp9V40BDTBdO9j9enshoqPLyxtYOzrcOtSsLZXb+t3v/rx2C/qxcErpV+GhBNq6XSH60tu12jAva36uQwGKs+QodlmSMmF0PwM8281JJoUCWgKIZqH6IPqx8oGAhkYTgBKH7gZGG7z6lp2Srqdc0lfnatdvRXClBSl5ODx0l4oyq/9vgpzYfVD8LZvyT7ry5VBMHMrOU+NULM7bJzgpk/Bp7iVhaHVRbSJTgQNwUeAQ/X0OpVaqn+mRlNye6vi5v5VBjSLy829upacMB5aofb8qy+/3w+LOkNOE8jqEzVjDKoVlzw7+5a93ZTKlJxH1O/fbG1kRKtZYFZ24Oil3lbbgKZOqwYfQf3d1zVDU1sI5zern8ceaVoXGLa/B+8EVH+IWWOIOljyeVPJ6tNpy2b6mup9rD4lnlY/jloAz0aW/HvuEgx7sux7WrvR4BYIBZlqz/wrHf1Z/eg/CFp4lL3PQ/poVig7qaS9UMBgsHUEh5bq19LeQtQjCWgKYY7yM029gvL0OjWDwBQUpSSg6V9FQNOQRXVydfnssyvLzUvrPUv9GLaxfvrkFOY2rYP+pkynVU+YxNUlh0FucU9DbR5E7avdfjKiYdkEOLFSLf88+3f9rRHKn1ia25V6w/pbdSx7QmR47Sl9stqYSp8YH/sNCrIr3bTaDCdohnJzA0OGZlWDgQz9yDy7Qteb1aFqGVElwY+6urRXLfvPjlf7nwnzklXcQ9OpeBCNIbDZFAYDlc620hXUrRy7PhjKNF38S153DH3BaxrQzI5Xg6MWVtDCs1SGZi1/xkt71EAQqBeomlJg58gP6uCpM1VMsG5MpYOFpS9EmVLSWbUdk0F0qOnWUl8MAc3WfdUKA8M/G4fy21pYQN9S7aVKi9gGO95TPw+eVf6xxsFAkqFZhuE92bNbSYWHW/MrO9fr9aZeglmrj9+fBDSFMDc7F8K7AXBhu6lXUtaPU2Fxd9MEJ9IuQk6SWipuOMCvTOfJ6hXCrDgI+7fsfVcLaLbuq2ZFFGaV9ISprXP/qplv+76o236uBYoC34yBz/rVT4CmObuyHULEtprv4/J++Gq02gdSU3yIUFE2c10YgmCWNupHc8vQNAY0O5e93TdYHSyQFQsZJgjIpJU6MS7MgpP10MvOENTxqCSgWVXWk2FQm2dXsLaD3neqXx/8tu5rA9jxfsnnTaXPoai+0mXP0HQCmjptyQm3vZv6MdnEZeelBwIZeHZVX6dzEiErofr7Mrw+OfmqgRxDKWhts6YMvQUN6vs9o7Yy40oC0bFHTbqUMqJLZ2g2kYCm4f+sZfFwrsTTag9kc6UtKGkV4dmleo8JnqWeR8QegZjD6m2pF9Se2Ypeff/qPbP849zbqR+l5Lysi8XHpG2GlNxmeK1pBoOBbGxssLCwIDY2loyMDPLy8sjPz5d/1fyXl5dHRkYGsbGxWFhYYGNjU+v/C6t6/H8VovnJTgR7d7BsQk+ViG1AcWlpu1GmXo0qLx0uFAdPog9Ch3HVf6y2AHJT1R5atWU4OPTppZ40X42VrXrQsucj9SpslxvU2xWl5IDXt0/5x1lYQMcJcHiFevDe/rrar3f/EkBRs0QHz6v9fpoKvb781X1Qs27q8v8K6sG+YchKxFboelPd9lefclPBpkXZ9gSmZDh49OigTuWN2ArjXq/+4w//AH/PVwfbeHWH616Bn6erv3+9Th1CUR8MQTCf3mqmiil7aBZkqc99O+fqP8YQkG3ZseztNi3UIR3xx9Wfy+XW2q8rMw4cPNS+gtVlyPQJGKJmRhz8FvrcUzaLtKaMGZrtyt7esoP6MStODUjbuVT8eGOGZvEJZd/7IOQzCN+kBk8MJze1ER1a8r4DTaPPYX0ozFGrHexdTb2ShlcuQ7OJlJxnXFb7vVrZqVUdZ9err6kdxppuTYYAq2upgKaNA3i0V7Pz40+Ak1fJfTqteqG3ovdgQ8DYpTiAbHgeZkSpr4c1ec1QlJKApmsbdZ2xR6DHbdXfR0MpHThsKkHWoryyGbVNpeTc8PvpNEFdY8ZltS9zUznPqKnkcPU5bOtScqGkKi1aqpUEJ39X27a07AC/zFSPUVr3g8kfVvzckJLzihnaFQUOLbmtqQ0G0uvV9yGXav6NlGJhYUHbtm2Ji4sjNrYJtEkxUw4ODgQEBGBhUfs8yyYUpRGiibm0F5ZNhMGPwvi3TL2aEoYrgE2p/4ghCwfUk/maBDRX3admSt65qvZBQuNAoCrKzQ363qsGNCO2qEEA97bqgUhBBljaVn41t9OkkoDmpIW1CxRkJaiN4AHijqt9DqsKwjZ1uxbBtv+Vv93CGh49UD4YUhOlT0LO/dN0AprJ5+HLYdBxPExfYerVlO2fOep5WP2A+lzMSVYP0qty9m/481H18y43wS1L1Gb51g7qAJ+U89CqU/2s0zAZ239AcUDTRBma2kL4Yoh6wWru/uoHDyvL0AT1Z4o/rpadd6tlQPPCDvjhVvViy/Tvq/84w4nx6BfUjPn44xB7WM0ury3D+82VJed2Lmp2V1YsJIVVPIwtO7G4BYKm5HfVsj20HaG+Bh5aAde9XPu1GbIzHb3VEtrmkKGpKPDt9Wogat6B5h/UzCwOaDpfWXJu4pPDlFKBfMOFC1P/fVWUoQlqH83ksOJjr+KAq7ZAfQ25tBdmbwff3mUfU1lmbFGueqHuyh6BV5NwSg1+WdnDkMfUCdJNJRuydGl3Zox6/FU66GsKsUfUQJtBUyk5L12hlBGt/p9GHTTfgKbhYppX15odq/e7Xw1onvgdsuIh6Yz6HjPjx8qP1Q3vjxnRzeOYvj7kpUFC8XDCgFIZmobXr6aSobl7EWz9n3rMW1H2bRVsbGwICAhAq9Wi05m4z7IZsrS0xMrKCk1dLrwjJedCVC78P/Xj8ZVNp9dhQXZJI/fa9jpqCKWvNtekl1PUQTj3tzpg4+/56lXh2jAOBLrKhPPS3NtCUHHw9NBy9aPhYM67B1haV/y4diPVg/bM6NpNFQU4vU4tXQHQF5VkHzYFhbk1P2nTFsKB4onajt5qLy4Xf3UqvL6ofClaTZUOaIb9a/rBDAbnNqh9KsM31c+aks7VbYhPWqQaXLKwVgPvXsXDIqrTmkKvh21vq5/3ux+mrVCbt1tYqlnPUH/ZLTnJ6oEumpLnq6kCmmkX1ZO21AtwqZptJPS6kudIRQFew1Cy2g5UUBT14FrRwek/SsreqpKXVpLp2roPdLtF/fzKXmA1UZir/k1B+ZJzKDUY6GzFjzdc6HJvV7ZnmWE40OHva993OfYohG9Uy20nFvc2S2kGAc3sRPUkMDuh5BikudLr1J8T1OA4lGTJVHfKuaJA/MnaHztUpvQwLEM2sqn/vgwXsV0rCGhCyTGJosDfTxe3IFEq7ldryNA0BDStSw0ayqjhxXLDe3zQ6JIe5XFH1fcVU7uyn3HcUZMsowzDBXjDe3TaRdP/rrSFJcEn3+BSA+5M1A+6PhgG0lW33NygzRC17L4oVz2+s7SB23+6erVRi5Zg6wwotc+4zYxrWud1dXV5H6CoFUOlLyLUJkMz+bxacVT638U9dZ/boNfDweJjpD0f1/pcX6PRYG1tjZ2dnfyr4T9ra+s6BzNBAppCVM7QTDonsWwGoimVLmeo6UFnQ6ptQHNnqf5naRdh90c1/96FuSUHYtUNaAL0f0D9eORHNZvhav0zDaztIWiM+nltA3UnVqkfLYqDpk1pkuTfT6u9Kk/XoHn+2fVqNpGjNzx1suTf6AXq/bXp41ha6UyPvNSSkwFTM/SrLMqte5nRqXXw+QD49/k6rKc4O7N1HzV4FDRK/bo6v/+wf9TnkI0jjHlZba9gYHg+1FdA0xD8cmsDTt7q56YaClT6gLq6z+e0i+qAECu7isul/fqpH+OO1W54WOSOsq8JOz+o3uMMWT6OXmrpe7/i17cTq2v/+zX0drNzLWnoX1pVg4GuLDc36DRZHUSSkwjrn6zdwK9dxb+X7reVVATkpZn/pPPSQbNzG0y3jsaQnagG7jWW4Oip3la65Lw6J5cHvoYvh8KHXWDji/XXw650qwWP4oCmqXtopl8lQxNKjr0OfqMOwjGo6LXbGND0K7mttoOBDH+nnSaq2ayls/pNSVtY8rMbjg2bQtm5IUjY/Vb1b19XUJKoYCqJp9VWM/ZuasDJeGHuYNNJ6KiphOJzOM+uNXucRlNy0Q3gxo9L3tev9hj3turnNRkMpNdB2Cb4eQYs7qoeBzaVFgR1ZThGLt0/E9RJ8qBeoKnO31ZyOHwxSM04L/1v+aSSC/G1dXlvyUXbpLNwOaRu+xMmIwFNUT3ZSbD1LdNfRayKTqsOtchJrvu+DG+GoF4NagpKB04yY8tP6TaV+OMln6dEVG94S+wR9eqnxgKue1W9bffimp+QGMp3nHzAxa/q7Q06jFezQnKT4cxfpfpnXiWgCepBO9TuZDPtonqAqLGA/g+qtzWVAJ2uSP09gHqQUN3nuiEDrM/dZTNbDYHfi7trPxVery/5fzFkMzSFk3y9Di6VOvAp/fdfGyGfqx9Prqn9NHdj8/XiDJl2o9WPF7Zd/aBRUUpKdwc8VD5wVd8BzeRS5dp2rurnV8vQLMxVeyU2xElV6ROHc/9U73sYys1bdqi4p6h7O7X3pa5QbSlRU4YAZvtxgEbNYI8/WfXjDD+L4WTBf4A6WVSbB8d/q/k6oFS5eSUtIwwZqpUNBjJkyHh1K3u7lU1xb1eNekHp+5vUY4zqSjhd/FqlgRHPqAFcQ2DG1Fl0pcWfVJ/Tpf+dWX/1QRulM+TPb67964E5MJQ9O3mXPJcMmZq6AsitRnD6+K/qx7w0tTfrp33g+1sgvIKsxJooPQyrZXv186xY0w2mK8oryWYtl6FZPAgx5TyEbYR/nlO/7lzcH7yi8u8rS86hdoOBMuPUthZo1B7jllYl66nLe0ZuqvoeW5dzjoQT6t+RvZt64aOua6oPilIS0AwYAq7FQWRTl53HFlcC+AarwTnvHupFu7xU8x10Y7ygVsOAJqh99rveDOPeqH4ZsnHSeTUucOdnquc7n/SGn6ep1UeKXr1AbqgaM3eGY9LAYWVvd/EDNOrPWp1z9YPfqtVeLVqp5wFePcCtOHhcUfZ5TZwoHpyosSz5XnWRn1H9qpr6oCuCLW8WVz1d2ySgKaqmK1J7Se58H7bX8WpIQ8mKV0/KP+4J312vXu2qi/zMshmQpQcPmFLpK396bUlDfVPSFpZkXVnZAUr1Mlp3lsqwGfaUWgKuK4AN/1ez4IUhm8mvf8365FhaQd971M8PflNSilRVQLPjeECjbl/TScYnV6sfA4eXDCOKDq3ZPhpKdKg6GRnUnkFn11f9mKQwuLhLDdD2ubvsfZ5d1WwxbR5E7a/dmlIj1DVZ2cGwJ9Xb6lrCXh8STqn9Vg1q237A8FjD33BBhnrFuDYuXRHQbDNE7QebGaP2V6vM+S3q37K1g9ov+EqG50Pc8fq5gGIMCHYsGSSTn1H5c37He/DNdbUPyl1N6QzNjKiSTO+rMQ4EqqSfqEZT+7LzSyHq88nCGm78qKRs3JCNeDWGbErDgb5GA/3uUz8P/a52AeHUUkGdihh+B5WVnFeWoQnqSeLMlWqZ3uUQ+Hp09QPAht9H15tLgqqGoJOp+xwaZCWoP9Pv95X999udsOmlyh9XOqutILPked0cGTJjnEqVclrZqNm7UPWk86x4dWgJwK1L1YuUaNTjtZ9uq9vFwtIl5/Zu6sk0mC7r0BBktHEqmbpu4OipVkigwG+z1KzXHtPVnnBo1BY52YllH2M4dik9LMUQXMuoQYZm2L/qR79+JVm2tb0IpihqifjaR2BRZ1hWPISxtgzl5n791coFw5pMmXGYflkNTFtYqX1NDa/Xpp50fmWFkpWNOrQPmlYVUXWVPoerack5qC13pn8PQ5+o/mMM75NVBYCTw9X3hs2vqX8Pdi4waC6MLz6/PvyDeV/IUhTY/1XJ31TA4LL3W9mWXEipquy8MBeO/ax+fuuXMGe3+u/e4vOThFPqEL3a0BWpbX2gpJf36T9qdnH1Suvnq/+3db2gVl0bX1SPh76/ueknnDUwCWiKqllaw/Cn1c93LoRTa+t3/zqt+uQvnRFZXfEnYeXdsLgbbHur5AA4JhQSKznJqg7DCZpl8ZCIS3vr1t+uvqRcceWvJgeeDSU5TM1GsnVRA3VQdcZa/MnigFlxho1Gow7ZsbRVB/UY3mSqwxAQrO5AoNL63K1embscopZIWTuUn1x8JUfPkvIlw8F8dZ0oDmj2uK34SrilelJX3X5hDckQtDf8ze9cWPWBv+FKcofxJSdDBhpNSTP52padG/ua9oQO16uBnpRw0wctDOXdFAfQ6xLQDF1W9uvaBGwzotUDQ40FBAxUb7O2hzbFB5KV/f4VpaTtQ7/7Kx4e5B6knkRr8yovLa4Jw2trq84lAU1Fpz7/KmIIMtbkNaG6jJlIxf+P1fndX20gkIFhQE5NAyqG/4vgO9UshuHPqF+fWld5FqSBIcPHUPYG0HOG2su2tqVUxrLbSgKaht9BelT5kwq9vuQ92POKDE2DjtfDg1vU/WdEwXfj4divV+9Ja8h6BBjxfyW3G8qCm0qG5uW96vuinav6vhg4vCRz7Wp/F4bXNhtH9WNTuIDTUK4cCGRQ3Unnhvff1n2h1+1w50p44pg6dAqlpOKgpnRFJQMrDH/7xrJzE/19lR4IVNGFW0PZua5QDUTd9AnYOZf0/yydpanTlpQ4l57sW5uSc8Pfp6FyBWoX0Dz2GywdAd+OhWO/qBe3oW7JBMaL3QPAq7t6vJWdUP1EgIJsdVheXfv0lVlTcZDVu4f6Hm14vTZ1mXFFLZcM72PV7aMZe7T+2jJcCqlbf3nDcYaTT8XtUhqCMUPzKgHN8P/g6+vUCyPOfnDzF/D0OZjwDgx4WF1vbjKcreVrl6lpC+GvJ+Cf/wMU9bjyynMDKMkyr+rv/tRa9YK3axtoN6bkdhc/NZtf0dU+6zpim5qB3MITBj8Gvn3UTNCjP9Vuf3o9nC/ue32mBm27KpMSoVaHVnYedvj7kvkFI54t2yrqGnRt//Si+nrfUZK9s25u3U7gDTJjYds78FF3+GkqfD2mZiV62gK1VO30H2q2ov8gmPJ1cake6pS62jL0z2wzVH2D0eY3jd4aV5YyNIUG0oa/Be8e4NOz7G2V2bVI/Vg6w8YjqCQL798FVy/LM1CUkpPDmvTPNHD2LXsg7t1TzdysirHsvAYnmwmn1RJMC2vocqNaJmkoxWwKZeeGoNfoF9UgSPxxtSVAZYrySt74S/cbKs1Qdl7blg2lD7LtnKFtccDc1Cf5hqwpw99BbV8PC7JKMg8HzVU/nttQ8wwSQ4DVpxfYOpXcXrrsvCKRO9XsWUtbdTptRSwsSibk1ke5XlJxtmirzuoJnSGAXlmfR0NJUuSu+j2xhJIgQadJ6sfqtDMwBjSvMvG9NgMVog+pzxONJQx9Ur3Nu7vabxKl5DWzMsaS81IBTTtn9eIJwL4vqr8WA8MFtMoyNFt4gENLdX1X/m2kX4SiHPVvq7KSdVAHCz20RX2tKMqFtQ/Dx73VDH5DVpler2YS/3qnGvRAUf/PvLuX7McQuDF1n0MDQ3ZYj9vUbJJ718PtxZkmyWGVZ+AYArJ9iqsHqtsKwRwZMzR9y95uaB1T1YW+ioJpbm0guLhaoLbBsPTL6omylX1J9qghA9hUAXNDJtOV5eYGhmOvFp7q35m1vfp1RcHF7Hi1vNXCqiTzFEpKzqvbn70wp2TonOE1tPT3jK9mVn/YJlg7W93e0hZ63QHXv1V+3TVlzNDsp/aVNmTqVXef29+BX2eqVUP1xTjAsvgCvKFFiClLzovySrLpSwc0De9jVw5WqkhOsnpBatmEur9Px59Q97N0BHw1Wm1LUphbs30YqsRqU25eW4b3uSsTT0B9Dd/7Kfw8Xa3ECRgMs7erFy8Nz1VLq5LX/SsvdJuDnGQ1U/DwCkAD496EyR9WvK2xvUUVGZqGllb97isfsKvthWMDQ4yg263q795wHnNoWe2yHVPCS9onRVTR6qnKta2GJUPVXqF/zCvftuvyfjUbFGDUCyUVf9cwCWiK6hv7unqCXJQLv8ysffP9+BPqicni7rDjXfVqqcZSzQD6dWb1+19G7lJ7LDl6wSN74IGN0HO6eqUe1OErtX1BMWSLenWrOijQmAxX/gwZL01hMJAhG9O7R/nm9BVJCivJ8h3xTNn7hj2lHuBlxcL2d6v+3umX1MESFtYl5TE1ZSjLhKrLzQ0MB++RO6rfU8vw5tlhXEnJmCGr1NRl53npalYzQPepJQOTdrxf+XPo1Dp1qrJLALS/ruJtDBmaccdq93ph6EVj+H8xBp6qGdBMClMzP+pz6IyilAQQBzwEaIqzPhJqvq//Z++8w+SorrT/VsfJOWgkjXKWEAKERQYDJmcQ4AjGGK/DYoy9Ztld72evA15jsHHcBSfAS07GJIPJUTJBQkI5jDTSJE1Onbu+P+6cqtvVFW5V9yTp/p5nnpG6Z2qqu6tuOOc979nwCFMmVs8DTv0PVlrfu1dPqIhiLDcnKKC8+3XzAMprt7LvR12lN+gxI18BzUiPrgyqmc+URnzZuRnkoxcfyP99QovpVdcBUNjrs1OFqapYQHPqkUwt279f3JaC1JnLr8hUWZ48spne8LB9KZvRQ5M45svs++a/6ptWUfiyWysWnsW+v39P5uP0t2oXOCeJCiuBTz0MnHIz+3ffXuCl7wO3L2FrhV8eCfz5EqbqV1NM7Xj2TzKPUZ2HgFMqAWx5ho1tuXbNNgYuABaoC5exBKxZ6XIyrgfZP3YtC6j17Z04TQnzTS4KTatgGqDPO20bskutReAbAtEmetwVmk3su7EhEHH0F1kjsM88mqm6NAto9nOBZN4HWAsyCCbKd77MlJSVszIV69XzmMI4MWxvd0LQenDJhcA3t7DS0iM/O3Iue72tHQbaRtbHClPwAu7nMVpnvPen/M09FHyhtd9EKDlv/4iNScW1mRYENHZ1fOQsMGjfyIQfQwdy74xONhIA8/b8y1eB2xexwPLrt2d+rX/AfI1Ka6j6MQxoUuKvf1/m/JGMA098mVmNqGlWGfa5J4GS2uxjHPk5tnZoel1P/k4GOjaz4PPet9gc96mHgOOvt7YBo3Gsxyag2bqe7Ut8QWDFZ7Kf5xtXuSU+zPysAT3pu+wSVmnY0+Rtv8+fR99eb81C02nmifnINSwmAjDhyJ/O0/cYffuZtUg6ASy+ILNS5RBGBjQl4vgDwGV/YBNw317g4au8ZeIeu07fmMw4Drj092wRQ2VnD31O7Likpll0bqZSY+HZrHS4p8m7OS9NhnVLOJXZOAc0YwO6Kfyck9n3iabQpJK6jk3WmfnXb4OusDks87lgIXDOiD/aO79xNnymzHHDciBY4On0MedUPQhAC18nahey+yAVF1Mfqqrun7nsUv1xr157+abpdbbQqp7PykOO+2e2md7/rvXETpnTo64yb44CsCBZ3RIAKrD7FXfnlErqwXLyv1owEjxpfsd5k5NKsiDI49cxP66/fDU/Zt2d21hJUKAQmHmCHkhpd6nSVFUu+3wNU+xS8sRt4yNjQyCifhlT0CWGshd9vF+jk09UvhoD0QK9bBpTDwLOjYH4BFc+k0rRft1IfdpRYjYSffvYe+kL2Af5wiW6+lpksd26nv1dxafbuxBTj2BVB2qaNREwIxnT1Wx8MBRgqqTFF7B/O6k8eeJDemmm3WslVcNHT2Tek1qHWYtycyP+AHDKvwI3bgYu+h/2eaQTbK3Qs5ttkj72JeAra5ja0VjGRgrN7t3uvV779gEv/YBZ1zzwSba2yaVrdjKmezLz3XEVRVeJmSUtenazdVGohM0vc2k8OEjLzq0UmhRUsfPQ3PUKC6BUzMxWYZXU6muLXa+6Py+tGRZ3L9H1NW4KzZHktZVCs6wBOO92XalJmAY0yT/TqIwduaeivWx8dEJTyJ6TGbjw+fQEs9OckU7pY+7RXFO6gnJ9bm31MO/QuFu3RJ9r3MxjPXu40mEVeOobuXtIJyL6mobmm4lQcs5XwvCfY1kDuybUtPPaiQ/059pElY61/Erg9O+yaz7aB6y9E3jxe5lfj3/JvJIol4ZAXimqZgExQP88VRV4+kZmo6D4gbNvBc7/BfMoNaN8GrBgRHH+3iRSaf716ywuUDWX2cgsOMP+52kcs1Nokkp1yQXmwV9NQbzWvXhp23NsLVcxQz9OqFgXRNHa3A1Gpajb+yA2wDy2ySP8uOuBTz/KxsJ9a5k359532M8MdbC11UW/PeRLzQn5LgCIxWK46aabMHXqVBQWFmLVqlV44YUXxvu0JiZFVcAnH2AL7qbX2YLfDfEhfaL54kvANc+y7EhJHfDJ+5lX25439S6NVqhq5mKKJ1SsP+al7FxVdUVE/RIu2/9hbmbBuULZnqJqFqgA3HWjHA1UNVOhWTmblSsno+YKlO5dTGkEWGeV5n+CZSnVNMtS2W0ozVQwbvH5gNV3M4Xc0ovFfkdR3KkF97/HFjjB4szyOCqZaF3vvRN4PqBgPW2gS+qAo65m/3711uyfp0Y2vgBwxGftj+01IdC5jSk8QiX6xqaikV1natq+HB5gz5PHbDLCypbu+jhw5ynMx8grTW+w741Hs0WpiCrZjP3vZ5bYAd6sDAY7RjbZiu6ZSfh8nI8pt7iK9DDPYYA1Z6ESTyu0EsKNuZnVd5qoGzWFZm/2z8eH9Sw1kN+kEi2kC6tYmb7Ie0/nXz2PeUvb4UY9QA3Sll6il7bynPxt9n39/eZjfm8zAJWNL8UmC39Swm98VDxARyWQhZX2HmRTj2RWB6mYbt4PcElBlw0ZgoXM4ubavwNfeo35iJ7/C5b0POcnQJ2Fd2nZdJZkSCecy9iI7l3A/Z8Efn4YUysPtrOKj/JGQ9fsC93d360fsmRXUXV2MJg22GYBTdrIV88bmWPomnSZ4LAjlQDW3jUxkqGWCk0KaNooNOk9MQbTiFwqa8yaYWkerTvFyhE7tgDv3W3vB+sGreR8hrvfm3IYS5QMtunvd59FQDNcolePOPmz84FIfk1DiKohm9cyH7uCCmDGMYZj5JBI05SQnBURfzynAAhdN3VL2RzV9iHwbo4dkFvWjSgh6/TPkZLpw11iQeTRwMw/kxC1T+HX+7nO03Ss6StZ1db164BPPwIc9Xmm1KOvqSOJbmPDQH4PN5YBTUUBqqnsfGQMWXsX8MG97B688j5WDeLUvJSShOv+z3ulwLbncw8sizLcrd9vn3uCVWU44aTQjA3oe0UrS6uGw1lCfrjTfUKAF5jwnwdV7G191tnD2QjdIySMoQoCI+kU8PavgRf+M/Prd6ezec0fZk3uzvg+MP904Isvs94O/fuZrUPLB2yc/uR9bMyWAJABTQDA1Vdfjdtvvx2f/vSncccdd8Dv9+Occ87BG2+8Md6nNjGpW8S8KgFmSOum03P7JgAq68hoVMPVLgQuvQuAwhYOdhmS1nUsux8s1hvR8JCEfONj7heUgx1sgQWFdXEtqQXqR4IWuz1k+/MF36DBSzfK0aCvmWVOfUFWcuTz6WpZsw3gP37PFChzT9NVd2ac81OgcRU79v2ftF7oaabvK82fF2XqChZgFfHPJGgRv+0552tsw0hgfdE5LOBOVM5mm95UPDcD9FyhhQ8FHwFWLuIPsRISUgASlDlddB5QWm9/bG1j+Yq7LCotshsOz1SAivod0vhx3D8Dn38OOGw1ez0tH7Bryms5D5WbkxrSa0CTzm/ZJXrAiBSo+99jJXNC5zPy2dQvze5+C+if6a6X2XGf+Cpw2+KR7vR+tmFwonI229SlYsABl2XLPFqHcy6gWVjBvpspNIdJnTmy4Nz/bv7sA/gmG4B+Xe2ysZHgO7Q7wasH7Bjs0JuXGC04iMaPsUYn6SSw7r7s57UO57PMN0sNh7NrS02LqzTperZqCEQoir7heJfzntJK/gQVmmY0HM66jx51Vea4aYbPpwegRMuCH712xLM2zdYRq/8EfOMj1ljmkw+yRmRQ2Nh1/6fE1xJ8MxLj50EbbLMmiKT+IzXggrPY3295Xw9G5coHfwae+Rbw1+vzczyvqGpm6TOPVnJusbZMp4CtNsE0INO/2a16x6wZVuVMlsBLDOvKUjue/Bp7j70ofcwwjleihIr1cnCaU+l950vTCdHGQPveZeNzQXl2F2NAPBhJ8/j8M7KTRNox1tkfw/T8KNnNBTTrl40EQLqc1860JlpyIXDa/2P/fukH4vOy3Tk1cuNCuHTEhxjjV3ZuF9DUbJEcApr8mNvyvl794IVOwzjo8zGhw/k/By76tf517kgicOuzmU3paA+n+OytYUYDSmB172Qe5c/9K/v/6d/T7VmcmHsqC3hH+7w14e3ezbw6/2+1Nyskt+x+DYDKxhnRhAspNPv2mc+rHz7E7JhqFmRXHhHBArZGANyVnUd6dUHEsssyn6tbzCpH1RTrNi9KtE8Xa508Isja/Zq5qnv9/cDf/g14847MrwNbWGzk88/qSlGArWuu/fvIegRs3b767mx7oUOcQz6guXbtWjzwwAO45ZZbcOutt+K6667DSy+9hJkzZ+Lb3/72eJ/exGXROXqQr8VFGSev5jNj4dlMKQcwv5Q9Fo14SEUz71TzUuO5p7GM72CbvuEXhTZiVXOYkTigK9dEMo+pJPMe/OvXM7+eu9ld8NcIZfyq5+qLzr5949swgDa9tYv0EgotwGNo8JRO6Vkx8mi0IhAGLr+XbXQ6tzKbAqMqIhHR/76XDue5MuNYdo1Fuu2DFukU8NFIV17j5KkoufnA5IOeJraQ9gWAWSfoj5dNBY4Y8a156huZ1zJlxK0ypzwzj2OBxL5mc9WuFVaLbNrA7ngRSETNf7enSbcrOOrzTLl46e+Ab2xiisV0Anjmm+7vHd4/c+Zx7DvZLLgJaEZ69HuBfw9L64FpI8F5u9JnHuP5GKGxa/97rPHauj8z1WPdUuCKe7NLlM1QlPyUnZv5T5JC0yxQSeXmpQ1MIaWmWSA2HxibbGg2EjFrVZdIh3OCxqTWdfbq612vAFDZdWSnZiT1eJNJotWsw7mRk0jl+YCYmoGuP1L42rHsMlZd0b0TaHqNvV7alI6lQsaNj2bLB+ye8IeAL7/FytiXXsyCKj4/23x++mHg6+t0X88dL4qdhxa4MGlUR55uHSa+mNTQiNSAJXV6sk50PHCC1kO7X8s9OdC3H3jxv9wrWQAg1s9K/oBshSYF2vpbzMfo/e+xYFq43Hrcm3Es8yQeaNXvW1H4tRbhD+p+h04B80RUD8K98fPcVO0A2yyTgt2q5NwO49itlZybBDS1xkAOAT+7QCT/N9s22FtImTV2sjpvUVIJ/Xf46p1AWL//7Eqo0yndqmDux1m1ytQj2TX7/H+4OxceLdFhGBdyLTvv3csqaaz8JO2ID+kdwc186HmFpt2xacz1Bdg8vfs1d+dBJOP6++CUOJx6JLsnE8OZlRU0tlbN0RvujBWUBNn1KvDQVSwwdtjl1k0XzfD52LoV8JYQ2fgoAJUlQDc94f733ULBfxIviFA2lSUX0gnd2oZQVV00sfIae0UrrbPcNAba8hQTkdQuMk+40pr8/bvFbSb2vw9AZePnvNPZmiHWn+kHS9BnOu8TrNkyfZ38r6xR1HQT67OCclYde8GvgM8+rtvOSTQO+YDmI488Ar/fj+uuu057rKCgAF/4whfw9ttvo7l5ApTlTFS8NIrg/RatOPGbwJKL2GD8zLfMy3v4ciMzAiHmuwHo6jhRzErltICmQLb/nd+wcs73/pT59c5vWJc7r/CqgbJpABTdhHu8MPs8rRRre95iE1dBORvwnSitB678P7Yp2fasXiJLUPlOyRQ9wDuW+AMsawzYl7W1rmeljAXlmQpIItdOfblCQfrpR2d2yAaYes8XZEFl/lqOD7JN9+yTnI8fKtJLydyUIlkFNBtWsABXYsg8uAOwUj+obIHFb0pLaoHzfs6uqd2v6UFFUXp2M3WOL6gv9Ol679yeqRKwY/2DLKhYvyx7c+O27NzKP5Mom6onn/wh1nTmmueBL7/J/IdFGe2ApqlCc8STsbjaXVJJBCrdJsUTbyOxxUL9K9IQiKiaw6mvP7T+OaPdgxX0+e77R3aA1KohEM/0o9j4o6asvTiJZEwP3lnNsTzhEuDwK9i/3/0DuxfUFAs4GctaRxOt07lAQJM2FUsusleRVs4CVnw683ec0LormwQ0KcDbuze70Yam0ORsB7zYUNie28g8k046e1TbERtgHsWv38bUJm4hxWlBebb6ljqLJ6OsnNGIFkz7hLX1Q7BAD3a6Kb1MJfSxwWgXoPloOiTmOj5iG3WANQhZf7/43zeD1JlF1d5KDC0Dmib3pmj3YbtAJMDeu/CIqt+qGVnndnbN+4LmjQWnLAegsPN1ozRr28CunYIKPclBiMxjretYADlczoJmPj/zJ4XCymC9+LKqqj4uGBPwXjqdp1OsrPi+K4CfLwde/gHzk/zr190F0Ns2sABkaUN2YgFgn4E/zOZiqyYniYiu6F1yIfvudZ7uadJ9hEtNzodHUfRqPH6fNx7+mQStN3e+yMQODSuAC37hXGZu5IjPsPti3z/s1w9m8Otat/tft6iqvv9xWsPw+Py61ZGx7Hzfu8yTPlCQqVQ0gxJ+bvoQ0Huy7DLzz2XJBcyKqH8/S9CKwNuf+fzmVk8A27fuf499thf/D3DmD/Wvj99sfg8SPj9rliaDmaYc8gHNDz74AAsWLEBZWVnG4x/7GJtw1q1bZ/p7sVgM/f39GV+HHF42uCIBTUUBzvsZU3y0b2TBLJ7eZnYcxQfMP9P6OKSG2/QXdxO8WancjGPZpD7QYt+1sW+f3p37yM8BH/8P9rXkIvZYp0ulAA9vVB8I6ZP9ePpoOgU0+eAv+ZkuPp9lykWYdiTzTwOYUfL9n2RZz4euAv52M3u88Wj3i4V8QWo6O3UePTf1SHMj8PFWaJqVmxMVM1jXVLqO6evU7zA/INH3fQ6XEBAhleDeN0NAk/eW2/JU9u8m48yzCDBXkFbNZr58ANuIWzWjMYPUkNOO0jP/pfXMEwuqWBfpjGZAn89+D7XS51ecA6TD3boawUqpBLBS2ot+C9y4BbjkTmDGKvf3TK4BzdjgSNdZZCoctaZAvdm/QwrNoprMEtJ8QItoXvFkZyOhqrqSRSSgqSjO/mP8ZsBJ3VCzgL0PyWj2Z8CXnNtBKs0P/k9vImRG0xusq3xJvXkZohmkKNnytP6a6peM7dhcLRhwivbpmxoRlTn5CW//m3Mpbn8LC2IpPt3jjaeoiiXhAOazyKN5aM7XH3MzHjgx2JEZqPIaJE2ngce+pN8Pm59y303cqiEQwNYHxXXs3/0m16lTMI3w4qPZu5cFVIJF2QEVCo45Bczp/vSNBFvfuD23hjJGNblb6Dok70hS1JaZeCeLlJx37WRrWV/AOjmtKM6iB/ocZ52gJ7Z4wiX6WEtNtkTQggsrsxtmiMxjNMfMPlG3IZp6BHD0tezfT3/Tveq2r5lVjPkC2UpIt53ONz0J/GIFcN/qEeW2ytaiio+pyu65QNzv367cHGBrVvocreax7l3sHMLlTI0IeJ+nKalTPVds7qB93o6/68kPrSHdOAQ0eZuK4jq2TvaiEi2pY3slwJ1Ks/0jtof1BQEoLNA3mg2nunexMdMXtE6qW0HJZGPyhLxql11qbqPEQ/unto3Mc92JwQ7dOm7ZJeY/Ewjryf6tgpURmmfvyPlYzT1aIvVCoLhG7NgSIQ75gGZraysaGrIj4vRYS4t5Kc0tt9yC8vJy7auxcRwUYuONG4NtgG0QyaiZyjStKKoCPjayeHj1J5nHp9KrxmOYcseKWSewjUO0l2XLRDGbDIOFXLbfZnH83M1MOTbjWOC8O4CT/4V9fWxEAeylYypB2VHKAGqZ9PEMaJpYCNQtYR4fw52631AyzrrgAtll104cfoVerrH1GVZCsekJfSFm5qE6Voj4JzoF8acdyRai/ftzsyTwQjqlT+5WAZU5J+vXMX2d9C0x42+CglFNb9iXnxEdm5myI1yuL/Z5aLHxwZ+zbSm2PMVUyyVTrDe8x1/PFp6D7cBLPzT/GTMooDnLsHCjzrJGmwUz2jeyzWCgUF/889QtZhvXZNRZ5UCfXc0CtgC2omYea/5jN146QeN9+0fWpf520EaluDazyYyIQrOomo3nvgDb9LlRslhBi2jek87ORmLoAJtLFF+26seKxlXsu9X8c2ALU60HCsx96HgURZ+DjDYqIiXnALNemHUiU4+9+Qvrn6NAw4KzxDtoTlnGXm86yRrsAO4bAuVKjWDA6cOHWJli7eLsRiSmxx1Ro6tpFjCwg66b+qXWajqt7Jzz0RzqGvHuRqaqvHYRC1SnYrmrkykgERjZYG9/QWw8NvLqj4GtT7Mkb+Vsdj198Gd3x7BqCERoPpqGNXjXTnbf2AXTCFIMNb0h3nRPSxzPyQ6oiHY6p7XJqi+xJERPk97gwgte/TOJ+qXs/aLmGVTiaarQFPBndwpEEk7BQzqOXaWAl0SaXbNI3pfTat+y8xX23ag4O/U/2PzVtR1422W1lTYuLNOtrAg3Jefdu5j3b+9eNlcd81Xga+8BX3wR+NRDQLgM2Ps2a4AoouxzCmgCzok5zfNy3sg8HWTzq5Wi0w6zpI4ddYtYBUo6AWx+kj1GSd76cQho1sxn87kvyCx9zHxqRaFk24aHs9X8VlCibv4ZLCAPuK9EcgMFrhtXuVeP0x6WV2i2b2LzMyCWbCyfzhJPakpsjHj3D2wen3ZU5jxrhG/66hTfSKezPXtp7Nj3rr62dZtIlbjikA9oRiIRhMPZarGCggLteTNuvvlm9PX1aV+HZGl6/VJWwhjpEesq2rWTlVkGi8V82479GsuSt67LLI3Sys0dsvM+v56BEZXdp9O66sCY3ePLzs3Y/gKbUBU/cO5tmRtBGjj7mr35KUX7gaERBQSVQY13Y6BIrx5MpUZAAAv+kvcNBfN2vsSCAcV1YmXKRk7/L+Yfcs5PM78uvlNXz4wH9Lr7ms1L4wAuoGkRxA8V62rgsVZptnzAJtmCcnEllhemLGdBqfgAm+ABFhRb/yDw8NXZJVzaIvtw84DK3NNGbCkSwEOfzVSbUQb0yM9ZlyMGwuweBYB/3CXedIBK3I1qSDeNgXj1R0FZ9vOKwmWHHRRUWuDJRqmeL8ob2eY8ndQTU24wawgE6E2BzPz8qClQcQ2zQ6DFopfOxTyqyik0Z+mP+wP6e7n16czfoXmhYqa44mLxiO3Jzpd1tSkPBahmHmfuBW2EPG75Jl2qypWcC8yrJ/0L+/7+3eZlnKrKKeAEys15aJFOC/ixVsjQJniow1p5naGQdvDn4tF8te6xDwLaBVMIs07nFCQrm55Zgs1bIeTa7ZyCKoddyu7lWJ+epBFl01+AV/+b/fv8O4CTR1S/7/1RrPs3YafQBLhO54YkHyW0Zx6vjx1W1C1la47EsLilSzcX0DRC1xd5nVpB88nM44Djvsb+/fpPs1Xf3buAJ//ZuYSZ1lleFZrBAv2a2/Y3tqH3BcyTYCIKTdHxwS4YOdQFNL/D/k3N8NwewwqzDudE7WIWiI/1mQfcYoNA8xr2b2PVSmEFcMZIAvTVW607NJtB6x4zv3fRknNVZb0FUjFg9snAjZuBs36kJ3LmfwK49kWWrO1rZh2Rna4tkYAmNfC0Wid1cUHIcIn+Gr0kYIyN0UQ47FL2fcMjbAzqsNjDjQWFFcDVTwNffEksWWbHrBPYexof1IN8dqiqHrw87FJdPLJhFAOa1Ml77inuf5fGM4ofqCrw9I0sOLn4fLFmrxmVMA5jfLSfWb8BLL5gx5xTWGC6b6/zerdrB9vfBgpYwgJgwdrqeey17B7xff/wISZ4qlloX1El8cQhH9AsLCxELJaduY1Go9rzZoTDYZSVlWV8HXIEwnogRmSxQeql+qWZXYutKK7RNxGk0oz264ODyGaLBvStz4iVa/U2scWvP5y9oCUFW9Mb2UHJRIT5fQLAMV/O9uQqqWeeMGpaLPhrhBZeRTV6Rly0G+Vo0b5x5DxmZJcFGBsDUbn5skvEPnsjPh8LYH/si5lfh18hXr4+GhSU65MyvR886bT+uJ3NwniVndOCc/ZJ7jq8u8XnYwtwAFh/HzPWv30x8Ph1rIvjA5/KLNd2WmQrCnDRb1hmfugA+/34MOtc3vQ6U9Ed+Tn7c5r7cVbSoqbZIsppM963j927il9X3hGuApoCJcZ2pc9EKsk2p4D7wJMXMhoDuWgER1j5T9opNPmSc4ArO88xoDncpTckocQQseg89v09Q8DPTUMgomYe68KppszN+UXLzQlaBDev0UtYB9tZolDxiXkJzz6JjTfJKPCWiUqzbQMr8w0UuvdqWnJh5lww1hvKgjI21wLWQafmNSyQGCzSfT9FWHguC44NttsHFs26KxvROp1zGyVe5ZT1t8nb9encGsxozYqO0YNIbsrO2zYCj/8T+/cxXwVWfJI1UiooZ0E3N2WmTgpNUjYZqxbcBNt9Pt3LTDQJ0mUT0KQgS18zW/OZER/W5zIqUy6sZJtefgzY9Spr0vb+PcCjX7Avl9RKzgU7CJtBYzfZtJQ2mK/F6G8MdZi/xuFupgAE7AOR/N9s/yhbIbv9eTb3Tjkseww2O4ZoJZhmq6AwFZaRQEhPRJvtW/a8yRKlFTPNr4HllwMzT2BjLnWwFoGCt2aJDkpE9e2zT5Zs/isTd/hDwLm3Zys9AVY588UX2ZySGNYtsMwY6tQttOwCmk4NnmispbHLrcWQ2bFEqyAAto4D2N6s+R322QQKzD+/sWD6Sr1qJxcURd8Dv/tH5+t/37vs2g8WAwvOZl6QviBTrIrYIbklldSbP5lZVjlBgXxKDKy7j40twWLgLJvr1ojWGMhh//SPu9g6s2aB7vVqRahIv46d5kiaV6cekWkrxpedu2l0JPHEIR/QbGhoQGtra9bj9NjUqWNoaD8ZcZM9FfHPNHLcP7Pg4r61rLxy54tssVE933zhb2SaRRc8K6jcvHZhdoCnfhkrN0kMAW/+nAVXiTd+zlQypVOBU0wWOYqiq1K9lJ2TaoCXyNMicLxKzu0+Tz7AEx/Wm2y4LTefDNgFs3p2s+xqoMB+gealU18+cBtQyQVa8Lx/D2uOFelmaqT6Zew9uv+TuspVRDUQKmZNo4qqWeOlv17PVEIA89a12yQRZ/yQefXuf0/33bSClEwNh2c3TyL1bftH1gFIgG0QaTNotwCccSwLEgx3Wge5m99hWeHCKns1WD7hy/Xs6NgM/Ok84H9P1r/os3ET0OSbAgH6dbr7Vfv32QlaQJc2ZCdEFp1r3tHWTUMgHiuVRDKmK35FNwN1S9n7FR8E2tazx0jVUz7d3KPXiKLoqrp3/5CtHKV5cu6p7r2/goV6Ax1gfEr+NB9Ni7JgUmcuu9S+XNZIIMQM+fljGEnG9XvDTIlFUCk+v8nkVU5GZh7HArXRXu/edKmk3tm58WNcs6FnxAJF0X7ggU+ytdScU4BP/Bd7nP/MyftMBColt2r8YVZy3tOkj8MLHYJphNtmYkZrH56i6hHPX9V6Hde+kSUwSurZawuXAsd8hT332k9Z4mztXcC9F7PqJoAl5eysDDQFtkeFJqCP3fT+WTXrKqxkyXfA3Gd3+wvs9dUvcz6fihlsfkon9HmPcGrsSdQvY0nEwfbsbshm0BqqdpH1/W23b3Fq0qYoIxVYAfYarBrI8UT72RoFYLYfRkqnsASSmrKuuIoN6gHU42+w3/8UVrI+BADbO1mVK5O6rn6ZvZ9f5Wz2Xlo1eDKOXTSf7X7dvXesF4VmxYyRJLOqWwjVLvQmnphoHH4l2z+0b9BVvlaQcGTROSwgV1ip23J4bQ6UjAGPfxl4+9fZz+1/j62TCiqyfWFF0BSae9na/4XvsP+fcpPeMEgE3hLBai6LD+mv4cRviV0b/BxpBylDjUlMfu5pXssCy4FCd4lUiTCHfEBzxYoV2LZtW1ZTnzVr1mjPS2xwFdA08Vt0onQKcNRV7N+v3ipuBk8oCsuoAkxq7rRwt+uO5/MBS0dK2F/+IXDbItZRcMvTetfYs27JDnYQlC3s9hLQ5DqcE+UjmfTxKjkXDWhue5YFgStmipUQTDYomGUW0KTH6pbYKyBpImxdJ+71lSuxAevSqtFg/idGNkoKW2RdeT9ww4fA555kC9Ke3cAj17AAOCmXnMrgK2cCl9/DNhcbHgbW/A97XNSfpqwBOOmb7N9OHmfkW2hWKlI1hym+EsP2vlF732bKuNIG+8CYP6irX9Y/YP4zfLn5aKpreUTH+/fvYUrZ1nX6F23ejepW0aZA9PcLylnwM5du671N7LtZCWdGR9uHdAWCm4ZAPGR7svetzABB81p2vRTX2XfZzjg3HzCDfDRHAhNuys2Jeaez9zIxnL1REbV0sWLlNWzRPuUwZ0P/0cDOR3OoS/dy9uJhdeRVABQWCDALaLV9yDb9RdX26qDaRew4w516Mx1N5WSykff59bXHRo8b0/aNTLlUUM4CD3M/zpLFvXvE1DsbH2Ubz/IZwGV/zBxzqCHUtufsm03xUMk5lZYboYY1VHK+523grtNY0GfaUc4NsAhKgrR8YG0Lw6OVnJsENBXF2UeTT8aRCudj1zFvw45NwN3nsWoeNQUsv0JXIr15h7k38e7XRsYehZVLe4XGbnUkEWT1visKV/1jkiwnKw6R8UFRdJX3A5/W56xEFNjxothxQkV6AkBkzN/+PPtuV+5rl5iza5JI1C3SS1afvcm5GUnzWqZGrZhpHqhRFOey81d/zO6FipnAiTfa/z2ACSgqZzOLGEqcGdES2qfYHyujOsPwGahq9tg1dQWb12Mu5+nhbj2J6UahCeiJwz0jr3U8ys1Hg6Iqfey3aw6UTrFqJwA4bLX+OHWB3/iIWOLKyLbnWFXV3/4tW3ChXT8newseU0Kkfz/w/HfYZ1+7SE8AidKwgilRhzqsKyDf/SM7fuVsXdHrBK3BW97XKwrMIGWoMYk560SWjOneCbz4PfaYSKMjiScO+YDmZZddhlQqhTvvvFN7LBaL4Y9//CNWrVp1aDb7cYM2ya23L9lUVd2g2qkhkJHjv84Gqz1v6AO2mxLLo7/INlj733NWNziZSZ/xfeDsW5kHRmIIeO9PrNw1FRvx9bORsdMC2YtRdhepBrhNktYUqNnbRJUrdgFqeqx7FyvdBNjEejDK7O0UmqKq5Ko5bBOcirOGGkNd2T8z3A289Svgf08C7jg88+u3x4v7QBJNb7LFbuUsMU/bXCmdAnzlbeAbG1nn9EXnsEVQcTULbgaL2ALpwc8wRUdhpZhn2KwT9E2hmmYb7nmniZ8XbVzaN9rfR1pDoBOyn/P59aCUXWMgvtzc6V44YkQNZmYIr6oskQJ4Dzx5gcb7A5vtN3EU7DnmK8CnH9G//ukNvWMqIdoUCGBBFPLgzaXsnDbqVgojs462VJrnNqBZPl0PQm58TH9c2zgLXAs81JCKfDRFO5zzKIrupbn2Lj3Q07d/pJuw4t2XtXou8NU1LFExHtgpNNffx+bqhhW6L5wbKmeyxAygK455mjmlht1nGirSx1zy0dRUThYbedqYbnlGrJurEVJ6Txvp/Bwq1gMZIt6c5M129Bcym3oBrMx11okjTZPuETsf4aZA+9kx7z6fBYCnHAastlEzZh2nYSQQqOpN1KxIxvWxwaphhJOPpll1QWGF3hhyz5sAFKZwvfh/WWC9bBpTH64zNFZKxtn4A7D3PZcGI3VLWKkyYaXQBPTqBuNaNRkTD0QS59zGrg2qwnj9NhakTQyxxJ6IssupW7p2fnHm8QowKwTL4418Nq3rMruB9+1nDfsUn7PX+8nfZoHfvr3MH9UOCrKZrR0IrfzWJKDZvgl4e8T775yfiivn7dTJqsqpUQUS2lYBzaEDLHAJRU/i+PzcPO1CUd41ck+VTcv0ERZh6UXscyMOloAmoCffPnrMOinT9DpTMRdWZlZcLTybra17mnSFvhv4ysanbsxU3Lq5fswormXnBlUf+8693dr73opggV7ib1Z2nojo9jonflNcAFBaz+ZLQPduNhLt1+dwo0KzoEx/jAQRshnQqHHIBzRXrVqF1atX4+abb8a3v/1t3HnnnTj11FPR1NSEn/zkJ+N9ehOf2kVMDh/rM5+IicF2thhVfO47n5ZPB44YKWlKxVkJi105l5GSWr1xzGu32gctzDqc8wTCwKrr2Ibt6qdZ5swXZGWr59xqv4mhBXIuJee86oMyvfEBc3XTaJKM68bbZsG64poRs39uE3EwlpsD+us/sCVbXSka0FQUFhAH2DV6+2LgseuAvWtYmcnjX2aPPf/vrHSppynzq30jC0y44cMH2fd5n3D3e7lQMcNcoTBlGXDxiLqSOkLzChcnjr5WXygc+xV32eLaRUzhGenJbkBBRHr0gJZRYUiI+GjucrEAtDOE79zGxlt/aGzUtURZA1uEqlzzNDNovFpwFgsA0ZfZfUDZ6vhgtj8X3xSI4H2JvKI1BLIJmFNH285twEvfZ3MYoDc8cwM1LeDVdV7tHkghvPctlkQU7XBuZOE5I3YPA8Ca/2WP0aJ9+tHmDUNEqZyZHfQaK2osAk7pdKaHlVfodz/4v2xFneafKVCJoPlobmKbRPocrUotSZWYGGJVD27RGqVwayetpM7heP0tusrLSt2yckSl+d7dzp3TUwkWCAFsmgKNPE6Nc9IJ1gjumr+J2YnwODV0JHr3sLEtWKx7sRohBbCIQpPn2K8CJVOYUvNTD7FEvaKwNeXxX2c/88bPMz1S3/4VG3+Ka9l4lAuBkN6wArBWaPLn/sqPM1WaTa+zcbpkCtDgUD1BFFcDn318JEGkAi/+F/D4l9hzC88Wm+NFKwOo+WTJFPvgYc1CpgCOD2Z2A6cS7KlHOKuoQsXA2SPNsd78BfPvtoKSoXaNQKw6nfONUhadByw4w/68eOzmys7tbL3jD4s1KLH6DEgJX9GYGWid62Ge7nRI6thRUpepND2YAprTVzK/+GTUumKHKoyWXJhpPRMq1gVATlVIRnifdl+Qlb3/Y2SfEe3T5zuvllWKkukLfPgn9YStW7Q+BCa2Xe/fy9Zv5Y1MFe8Gpzly/3sAVCakKJ2S/TxvXTFlubdEqkSIQz6gCQD33HMPbrjhBtx77724/vrrkUgk8NRTT+Gkkzx0Yz7U8Af1TardYoM2+dXzzY2snTj+BibdBtgm2a28/fjr2eZ/79vW5RfJmJ4hdJoMFYUtmFb/EfjWNuD6D6wz+kQuJeeaUT33N0JFeinmWDcG6tzKNhjhcmujej54UbdkfPzUxoLy6ay8Jp3MDvI4dTjnueCX7KthBVMRffgg8IczgN+dxpRFyShb1Jz3M+ALL+hf54yoA8h4WoTBDmYwD+i+cOPNkgt11Rjgruu6orDM7j+/D6z6J3d/NxDWG71YBSNJ/Vo52zpQ4xTQHOzQn3Mq8QLsDeFJUTX7JGuLi9FCU8BZKJRSSX1TJmLKH+Ya6vG+xKmErtos4gKaFMBtXmPdydoJKkuy84DjO9pSdr9surf3e8nFLGjeup4F2oa79WtK5FrgmXI4s26I9rGKAi8l58CISnOkkd2a37L33q2ly0SENsPdOzOrRrb/jT0WLhMvOTNj/hnsOoh06x1TCZEO5wQpujs2sesxnWCVJGUmCR+AfV503l780MyCrVRSt/9d8473xMbHAKismZBVMHHR+ew+HWyzVrMQA23seL6grr42YlQQfvw/gNV/cq/cAvQxY8dL9t67mrXPHOtAm6bQNAlgxQZ1r12j8rCoCvjqO8A3t2QHpY78HLOe6GsGPhwJWPTuZc0wAeCMH+SnTJGfU+3UnsffwNYsw516wz2AGx/OYipfUfxB5jt53s9GkocjKjPRSivRxkCUMFp6sf0ewR9gQVa+G/imv4iVm/MsPIfdQ+kE8Oy3zX8mPqwr4+wChzR+G0vO198/0iilyF2jFICtDxQfu1aNVhD0WmccI6b4tGrwZOX9q83TazPndTu8+Gfy8KKJg2m/oSh6wujdP2TfA8kYsGlkPW8mHCF1/0ePufMe37eW3auFlcDZI9feSz9k6vqmN1iQvWpObt6+lFQuKNd9mb3QyPlo8iRjrOcFAJxwg5jPOA+NUbteMW8sTL6m9PeN8GOJbAY0qsiAJoCCggLceuutaG1tRTQaxdq1a3HmmR7LrQ5FRLKnXvwzeapmj5TsKLpa0w1lU/USztcslLed29gAXVBuX45jpKiKqUCdoGBk3z53PonRPl2pZAwQjFdjIF55aDVA8591LhvIiY6imAezhjpHfMIUscVVsIBtbL70KvDFl4AVn2HqZ38YWH4lC17+0+tsUmz8mP614tPsZ/r3m2+yzPjgz2wRPm0la3IzUTjl30ZsGxTnDqpGFIUlFbwsGJyCkSJNiuy8VAHW1RZgQWmR8QKwNoQfz8CTnUchwDaI6SQ7bzsVEOEPMIU7kKk0p3JzxZe5ma+azQLQ6aSuuHOLiEIT0DvaEm7LzYnial3FsPGRESWQyhI9ViW3VvgDukp4z1veSs6JxRcwxWm0jy36SU3vxtJlolExkwXKklHdX7pnD/DEiC/XEZ8FwiXej+/zA8d8mf37xe8BT3+LBd/7W9nfU3zm3ZWNaI2BNmUqk+wCRbRZ3f6C7kkrwuAB/TqZxgU0yxpYAyzAPghJgaLDTDbLhEjTJIKau5Q2WL/eQJgphUMlwBV/Bk7+F++bwZnHsXVd/z77c6PEcbVNIobmy5Z12euutg8BqGzcKzVReBZWmgdkg4Us6Q6wkuxUEnj2X5nn6czj3auKrODnL7uxOVQEXHkfC1C3bQD+8lWWHHDTYd6MldcwK4qiGha4n3Wi2O/VL2P39HCXtWd8fEi3YbG7TgnqBj73VOYl/NDn9CSvqOJMUViQUfGxhLKZndS+f7C1VulU+6STVnLepD823M28BQHg5JvcK5MLK/SxyFh27qZaBGDqtqJq9lrI4xzQxy5jELJyFnu9aspaRGKk0yI4Ksri89h5Nhxu3WxssrL8cjYWdm3Pfj93/J1VSZY2mAfN557GRBeD7eKfBaDfT/PPBI66ho3H8QHmp5lruTkx5xQACnDmLblVhVBpd9sGVmJOrLuP7Y1KG9ieyi11i9maIhUzt27QGgJZJDGnHsnWWBUzxMYliWdkQFOSO0IBTQ8dzo2cdQtwU5N9KYkdJ9zAssO7X2OlvEb4hkCjkUUpqWMTkprWN9Qi0CKpuJZ5cvCQOnKsGwOJfJ78cwf7QG4WzKJ/V81xr+qadhRw0a+Bb+8GbtoNXPK/LHhpdl2GinQDfBFfwXRa93+baH4uPh/zR7upyZ2tRK5oAU0L/0uRgGbdEraxGWw3VztpGwgX5TlmhvCDB/Ty0QXjENB06iJNCvTK2eIqHs1Hs1d/jBoCFVZlH4dKNN/+lXs/wXRaHy+dlAV8R1tAV/J6gcbADQ97LzcnaNOy7W966a4XH1yfn3X8BIDXb2eWLpWzvQduJwL+gF4t0bmdBToe+BRTmjSsAE77Tu5/49ivAqeOHOcfIx2rKSBYt1QsYFpHCs0trOIBsO9cDLDEWN1SFlSg4IsIpFqpXcSCHDwUnLIqqevaycY/xc9Kvu2gpkk7X7L3CidrD6dg/tXPAN/cCiw+3/7nnAgV65/Xi9/XGzEZofHfrCEQUTkTmH0yAFX3BydIieemuoBYeQ0LGPU0AU98mTXf8QXY+JOv9WhGQNMhaV/RqDfc++gxVibev58pBZ38Je2YdTxwwwbga/9gSVwRAmE9KWy1z9j6LAtMVs4SSygALMD8qYf1Bj+pGLMbMHrh2VE1e+R6gO4zy8OXm9t9jnzJOSnwXvo+EzN4aZRCmJWdJ+N6YEt0PWLVGIgqNczKxOnYr/wI2PSkc8dzOpbTOGhFQTm7rq596eBTwoVL9WY/tBZMRIH1DwJ//y77/7JLzZXJgRCw5AL2b9Gmcqqa2SDQ52NVUIqPjQdkWeV1DUMc+xXgX/d6EyrxlDcyq4l0EvjhFOC7FezrqRvY88d/XXy84VEU6zlSVbnKB4sxwx9g3vFfXTv21VSHGDKgKckdzWB7vbWcPR8BTUXJXoy7oWIG8+gAmE+hEco6jpb3iqLoixY3Zedm5eaE1o1yjAOa1B3b2OCDZ9aJzIdqyUXe1EOTCTOFXz6u+VCRWIkdZUlF/Ip2vsSUJQXl9sb540Wu97kXHBWa69h3u41qqEhf1LcbjqOqmU1g3GA0hN/+NwAqUyHk0iTCK1YehYTWwMzBgoPHrDEQKTR5/0zisNUsaz50gDVms8KsUd1AKwvc+QLW/n08dYuAj/87UwgtdKka5ll0LlOtdu0ANoxsfN1eCwQl9eh+L6zS30O3LLt0RDk0soleeM7k3wzSfdi5jQWH2jeykt4r7xNvqGEHletfeR9LUja9rm+cRPwzAZbo8oeZJyY1WhFRJpEfq5uyc01FYrLpIpX3rpfNkwMUpJlzirOyvGq2fk3bnR8l3pwSBIFQbmpanpXXsIB2rA943sSPctNfWHkv4Jw0pzH5/Xsy/UK1xNcK9+cXKmaBcgDYMOKZfOzX3HvO21G7aMT+Zxnb/Dsx63jg7J9kntPcU3O/h0JF7q2naO61amxC1+myS92NX/4AcOYPgQt/w4K1h1/hvixVS1aZBTRHmoE4eQNWzACgMF/PoU5g33t6BcK5t7k/J0JbG76iz4f7/sH+TlENqxgRxSygaaXQBIAjPsPGuLYNwEOfBX6+DHj5FubJaySd0pMgXhWaALs2RZu+TDao7HzzX4Hnbma++o9fx+a5cJneK8IMqpLb8oxY2XnndvZ5+EN6k82G5cDHRvxvY/0syTVbUGVth1Go4wVFMQhnVGhrmqo5I8k2j9Acue25zPeuawerlAgU2O/zAuH8rDsktsiApiR3ahawhUB80NxXLTaoB+XcdjjPNyfeyDJMO17IXhhpCs08LiCNUFDSTWOgbpsAgabQFCg53/Y88IP67AYjbokN6gEeO0+g4mqmrlj9p9z+3mSAD4hRdj0fAU1RaBO5+/XMpgJmUHZ3xae9+dkejFCzhJ6mbF/GoU79/nIqz6fPevdrmY8f2MoCaf4wMONYd+dmNITPtewvV3gPTbOAodbAzIVikALYkV79MbLZMPPY8wfZWA4Ab96R3ZwFYMGGH07JVlFRmWjZNPGNz4k3Av/elpsyKVyqdw5PDLGNgkgzBjOmHsEW0erI+59LwsgfYJ0/icnsn0nQ5vqN21mgyhcErrg3/wmARecyKxDeukBUWe4PsLJXQFdLiXjH0ca06fURL0oByK7CLKBZv5Q1NEhGgY8ez3xOVfXApGiVBamINjxi7nfId6JedonYMfOBzw+cdzsAhamLdr+uP9e2kTXeA4Bjvqpv4K1YdC5L1g516GWZgJiS346jv8hKQwFWkn2yhS+jV0gtdN2r4ur5o78AHPV5/f/jNT7YVYJFepgNA+C9+eQRnwZu2sN8Pt2y6Dw2nh/YnFmOnYzpCq6ZDgHNQFi3AejaATz9DQAqsxvyWpUGsPVDqJQlCEmBrFUInOzOC1X7DNax78m4XiJvFoScdhRTTJ5wIwueDrQCr/4Y+MURepUJ0buHJRoDBbpQQ5JJw+HMMiSdYP7NkW42Tnz8P9j7bDd/zDye9TwY7hxpZOMAqTNnnZipLPz4v+nJkOkrvSdSR4Mzfwj8yy7gW9szv776j9z2OjOP09+7fe+yoOa254GnvsGeb1jhPeEgyRsyoCnJHZ+f8xUyWWx0bAKgMg8LUe+40aJqjr7gfvW/Wek3fdFChMz6RwMKStqVYxnhjeqNaApNgYDm2v9lm5Y3fi7+t83Yt5b54pTPsG4IRCjK5Ff7iFCzgC1oY/16wxE3DYFypf4wtmBMDGWbYvP07dc75PKblEOdoir9XuI3JIC+eK+e75xJpiDjW7/UVVeAvoGYeZz7TC1vCP+P3+lKz/HaWFbOZOrGZMS8K7w2XuWo0BwaUWhaNQ05/FNsAzjYBnxwb+ZzTW+yxWYqBrz+08ysukhDIDPyofrgN9uNq7w1OAF0f0HCS7k5z+FXAjOOY8F2sq+YzNDmmsrxz/3p6L2u+iXAF18G5n2CKX7nfUL8d6nsXB25PkW6+1bOYp+9ms4OQJqRSuobWLNgq8L5kj/zL5njX/tGVg7vD7OgjQiLzmM/37mV/b4RrRN1vbiHYr6YdpSurnz6mywgM9QFPPBJNnfOOUWsMYU/qHuyU4Iw0qsnc0Q7gBspKGOWCAXlwAV3eB8f7PD53Y9lZ/+EeVpXzWHB3PGAD6YZA+Wb/8qCPLk2n/QalCisYM3CgMxO0vvfZ2vuohq2RnSCxvEXv8cq3sLlwBnf93ZOhD+oq+hoHeLV/5A+g45NzKewp4mNXcFiawuDypnA6f8PuHETcOnv2Xo4GQXeMASOqeKjaq67IOuhxsdvZuPDvNOBK+8Hvr6e+Qubddjm8QeB+SNzEwUr7bDyaS8oA86/g9k1rPyC+/MfbYqrmb0b/5Xr2o1/7174T+AXK4D7VrOkIgAsX53b8SV5QY4akvxglz3NtSFQvjnxWwAUJh+/Y7n+1T/SBXAsFJqeSs5NAppaUyCHkvPYgK4a6/hIV6N6oWmkhMaruuhgJBDK7JSdiOgNesbiuvf59G7JdmXn79/DNsKzTtTVQRKGVdm5G9XNsktZmZWaBh75vH7vei03J8gQvnsn8wkrmzZ+and/UG9uYOajqTXWcBPQrGDfM5oCjSg0zUrOAXbPHX8D+/cbP9eVyb17WYOHdFL/Px9cFm0INBrMP0Pv6u71WiB4xY/bDudG/EHgmmeBa55j/57s8EqVo79oX4qXD4qrgc88wjbtbpK2xrWGSEAT0APjImXnHR+xMSNcDtRYeKOe+C3mA5gYAu7/JLO2APTgzIIzxMsCC8r0Lt58cIfQOlFfYt+JerQ47TsswNS5lam7H76KjRGVs4DL/ii++T1qxC9096ssGNO6nj1eMYNdD145+lrmKTfvdO/HyDeBEPDJB4DrP8hPt3Uv1C5mgfJYX3aVkVsV8WhAyumNj+oB1z3cWlkksU9K+71vs++nfSe3RikE+RzufImpWVvez3xclNIGlohQU0zVrHU4F2jGGAizz+fS37P/b3sus/O61uHco3/mocK809n48JlHgUXnuAvWUXDSyi+ZGOrUbcXMEucLz2I+94fnqVnZZIDeh+Z3Riy7Kpia/2vvsTFbMu7IgKYkP9gGNMew9FaE2gXAcV9jWcVgUebXYatHd8FGQckuNwpNmwABqcoi3az5gRU7X2LlHIQb/y0jZHLu5Al0qME3BurYzBZ9RTXOmdN8MZdbtJqRSgLvj5TfkuJPomPVGMhNQFNRmHH69KOZ2vD+TzIFECUBvBqo84bwAFtcjafy2cpHM5XUFZBmCRgrTBWaVHJuEdAEWFflknqWjFp/P/MAfOBTLBg6ZbmuQuY7G3tVaOaDYAErI61bykoJc4Eff3NVaB5sNBzO1KZLL2bNBMcKt/ckXw1SMkU8aLj0Ymads/9doHu3/c9Saef0o6yVT/4As4apnMXuj4evYgmCjY+x592W8dLPb3ws05bCbSfq0aCwEjjjB+zfL/+AqWxCJSxgV1QlfpyKGbqFxHt/zL3cfKIz3pU2gRBL7AHMN/DF77Nra6BNV0pRUHE8WHAWu4569+pVMlpDIMG1Mj+ON6zIX9NGWhvufYc1klPTTDHq1oLD2BiIkvYiVhlE7QKWUFfTLMFO5NrhXOLMvNNZdc2BLfa2Z9tGfNqnLAfKp4/Z6U1oFp7N7uPGVcxv95tbgLN+JAPwEwgZ0JTkB60x0IfZnewmWkATYAvaf28B/r018+vS343u36WgZF8z89dxItKrN8cwCxAUVjDlBWCv0qSMHCl5Nlr4WzmRiLBNFCC+SDtU4BV+/DU/VhsBCpa1fMCy8Ea2Pcc8jIpqgEU5do09GMmHQhNgSoQr/szKTzu3An88mymfimt1r04v8EHo8fLPJEhJZlRo9u1lyshAgVjDHYICmhkemjZNgYhgIXDc9ezfb9wO/OUr7PMrqmENW6jJxva/6eOjptCcJX5++eS4fwa+8lbufo7TVjJvSODgb7rmlkCYqU1X/2liK055haaboEBpve7n6lR2buefyVNUxUoYg8WsmuP/LmPrlBDn/SrKgjPZ7/U16w2JAG+dqEeDw6/MXL9c/L/eKnMo4LTu/1iwCDh4A5oTgfPvYOMnwKxEHvw08P69LDg2/ejxHQdDRXo5/oZH2D6IVG6iyX/t/BXm5ZkvBXP1PCZ+SMWZ1RbgvtycyAhoUodzl0FIum/eu1tvqqV1OJcBzVGjsEIf97Y9Z/1zWnfzcV5nTiRCxcDnnwG+8DyzaJFNfiYcMqApyQ9Vc9kCNhlhm3gildQ9mca7IdBEoLiWvU9QdTNtO8iPrrgu05iZh8rO+ywCmqnkSMYNzAspWMT+tlW3SDv2v8cWRSVT3CmwDgWsAppjRfk0VlKoprOb0gC6Su3Iz0oDazPos+rYrC+yB9qAgRamhnLzWZZOAa78s+4lBzBLgFy8oRoOB1b9E7Dkwtya0+QDTaFpCGiS8rxqjrvXSk2BzLqcW3loEis/z36mp4kFd3wB1gCmopGdp1ENMp4KzXwSKgJOvol5Fk4XbEQjmViUTdMTkqLl5sTCkeCJ2VjPo3U4F7hG6pcAl/zvyHFfZd8Xn+d+8xYsZL8HZFaDeO1EnW8UBTj/F0wFd9Z/6+fqlnmns0BRpEf3ppYBzdHD52dihIv/l82tW59hKlvAezOgfELn8NHjrKw7PsiSdXWCvp7zTmcBp0/8FzDtyPydl6LolkS0p/BaLcIHNLUycZdByEXnsb3QYJseWJMKzbGBgpRWZeeJ6Pj7tEskHpABTUl+8PmAqSvYv/my8+6dzAA6WJy7z9fBgKLoZSUinc5F/Oi0xkB7zJ/ft5aVpBdUsKwsTWhm/lZONLn0BDqUmDKivutr1jeZYx3Etyo73/06sPNFAApw5FVje06ThYqZzN8wFddLqaghUM1CIFzi7njTjgIu+IX+f68bCJ6z/xu4/J7xV53xnc55tA7nLpMdtiXnDgHNULGuxASAc27N9PclNcj797CSdGpkNB4emvnm5H8Brvw/maCYrCiKrgx0GxQg1VfzWj0BY2TwgB7AmC6oiFx8PnDKzfr/vQaK+OBOKpmfTtT5pGYe8KVXgWP+yfsxfP4RL00OapApGT0Ov5KppajbsuJjNgzjzdyPA4VVwFCHroSccZy40rKgnL2u468fnXMjfAHvllENK9j3zq26F7/bZEwgpDfV+sfvgWg/C24CsoR3tFl4Fvu+5y3dK5ln92tMRV86VY5lkkmFDGhK8gcFNDf/Fdj0F/b1wZ/ZY1OWyc51hJtO520jRvN2ndedGgNR+cCCM5lXFnlXffRYZvdfEcjkXPpnZlNQrgdJSJU31jYLmvk71xioZw9rkgIAKz4l/fasUJTssnMyz/equjn8SuDMH7EkwpILcj/HiQIFX/qaWZCQ6OYUmm7w0hSI52NfYoGYj/97tu8Yrwb5x++YWjNQkJ9mCxJJrhx/PRu3l1zk7vdqFzM/yMQQs/oxg1SW9cvceYOf9G3g2K8BKz6tK7vcMudklowY7gR2v8J1ol6aWyfqicYRn2UBIoCNe+PVNOdQY/pK4LqX2fh+ys3MhmG88QdZBQUA7Pg7+z5RmmfOPgXAiAihcZV1xZcTpfVMWa6mgVg/e8xtQBPQm2rtehnY/jx7rLhOT25KRofKWWwMVlP6NcqjlZuPs0+7ROISGWGS5A/a9G97jgVQHvoc8NaIQmki+WeON246nZNCzC6gUjGDfbcqOafSAiofmHsaCyAMtgNNbzifA5GM6w0GpH+mOfx1HijwttDLhVknMF+93j0suBQfYk1SIt0ss37ubWN7PpONrIBmHho9HPtV4JP3e99ATESKqvUgJD+OeelwDmQrNNNpXT1g1xSICJcw39KTv539HK8GeX3k+q+YIRfrkonBonOBzz3h3lPV52PqLwDYYzGPU2Jrrkt1uM8HnPlD4KLfuOuiy+MP6kHaDY/qFSGHjWPjltGgdIrunSjLzceWsqlMoW427o8XxmZXEyX5X1ytK+5yrRbhr/PSqe6rVwAWWJt3Ovv3i99j36V/5tigdTt/JvPxnj1M6AKwDuoSySRCBjQl+WPB2ayUaMaxmV/zTgeO/uJ4n93EQet07hDQTKfFAprlNgrNzu2sLNQXZIFMgG3wKYu80UW389Z1zCO1qBqoXST+e4cSfIl53RLvm0GvhEuAxhGvtB0vAk98GWjfyDLfV94njayd4Dudq+rB37nWK4pi7qOplZy7DGiShyY1BYr2MgUB4FxyLgKpQUgBejCUm0skpP6ibso8qqpbj+TD7sILFNzZ9Bc9eTqenahHi9O/Byy9BDjhxvE+E8l4M+M4vSFesBiYMoHKds/4AbD8CuDoL+R2HKrGA3IrEadqit697PtYCwAOVch2bPvfmVAF0MUP0T4mfph98ridnkTihTHebUsOakJFwGW/H++zmPiIlpx37wTiA0CgkHn4WaGVnO/Nfo4ycLNPBArK9McPuwx4/25g05PAOT9lXWGdoHLzGcdKdZMVvEJzvFTJcz/OPquXvs8WJ74ga5KSa1flQwFeodm3Dxg6ACh+3R9VolM9H9j3D91HM5XQO4jn4qGpqnpDoHB5fvwhSQ2yY8TDb7I3BJJIAF39tedtZh/De/V1bmMNzfzh8St7bTyGlaeSb+14d6IeLapmA6v/ON5nIZkI+HzAskuAt38FzFg19kltO2afyL5yhU/w5tLEZ/4ZmeODVGiODVOPAErqWZXenjdYwuuJr4yIH2qZ6nm8fdolEpdIhaZEMtaQeqlvH+soZwWpwxqW2y+KykdKzgfbgGQs8zmt3NxQPjDzeGaoHu1lSj4RtIZAE6SEZiIyEQKac05l36l899yfAjOOGZ9zmWzULmJ+aJEeYMtT7LG6JVLZagYpM0ih2buXqSoDhUBpg7tjUUAznWCG9FpDoKr8nCuQ6a0pFZqSg4H6w4BQKRDrA9o/ynyOys1nHjt+45fPl6nIPGz1+JyHRDKWnPhN4OhrWbfyg5EGLqCZSxDSH8hsUik7nI8NPh+wYKQ50NZnmRXPpieY+OHye4Hy6eN6ehKJF2RAUyIZa4prWDdlqEBPk/XPiZa7ascD8NSNelBzqBNoXsP+TZMX4fOzLDIgVnaeTgF732H/niieQBOR8um65994lSlPXaE3Jjj6WuCoq8fnPCYjgbBup/D+Pew7X14l0dE6nY8ENPmGQG4bwIVKmBIWYIF4Nw2BRCE1CCBL2yQHB/6AnqyiCgpivMvNCSo7V3zuGx9JJJORoirmV36w9g4orgYqR5pL1i3O7VhHflaf+2ttKtEk+YVELusfAF76Afv3uT9lCTCJZBIiA5oSyVijKHqnabvGQKIBTUUBzvg+2zCs+zNw9/nAYAfrHKim2aKKytJ5lo1sNLY+a90hnWjbwMrfw+WsY6rEHEUBLr0LOPtWYNpR43MOPj9wye+AU78DnPXj8TmHyQxtQjo2se/SP9MczUNzBysTJ09gGtvcoCiZZeeaQjOPAU1/ALj8HuDj/wEsODN/x5VIxhPNR5MLaCbjumfl3FPH/px4Gg4Hzr8DuPT3E6MTtUQiyZ2Lfgt84vu5ey2WTQVW/wk4/xfe1g4Sb8w5mVXTxPoBqFL8IJn0TCBzD4nkEKJqLtC63tpHM51izwNiAZWjrmbqwIevYarMO09h3TeB7HJzYtqR7Dy6dwJ3LGdNnY6+hpUsGxVWmn/mMZk+XZJs5p46/pvI+aezL4l7phwGrL9f/78MaJpTNYclUeIDzIuJxjK3Hc6Jwgog0s0aA5GHZnEeGgLxTF/JviSSg4VZJ7Dve95iiQVFYd62iSGWEJgICUi5UZZIDi5mHps/Nd+SC/JzHIk4wUJg3mnMWmnm8VL8IJn0SIWmRDIe0KbfqtN55zbmJRcqES+PnHc68MWXWClo/35g/3vs8YVnm/+8orDM6MwTmJJz69PAny8Ffnkk8OYdwFCX/rPURXW8mgtIJGMFXybmCwL1S8fvXCYygTBQMeLf27nde4dzgldoUkAznwpNieRgpGEFU9oMdwEHtrLHtHLzU9zbP0gkEonk4OfMHwGnf1c2AZIcFMiVjkQyHlAXYKuSc60h0OHuFJE184Br/86CmwBQ3sg2PFY0LAc+/zTwlTXAx77EvDh7dgMv/Cdw+2LgseuYdyYFNEkNIpEcrPCKpvqlLHAnMYf30dRKzl12OCcKKtj3aC9Xcp5nhaZEcrARCAGNH2P/pkqKXSMNgca7UkAikUgkE5PKmcAJ39A99yWSSYwMaEok4wGpmLosSs5F/TPNKKwAPvUQ87i58v+YEtOJukXAOT8BvrmFedk0HA6kYsCHDwJ/OJOVggaL2eMSycFMURVLBACy3NwJ8tHs2My6nAPeS84zFJqj0BRIIjlYmTnSqG/Pm8BwN7D/ffb/uePcEEgikUgkEolklJEBTYlkPKBNf/8+IBHJfj6XgCbAVJ0rPuU+ABkqBo66CrjuVeDal4AVnwYCBey5OSfLsgTJoQF1DpaKZHvIDmPHi4CaAoJFQGmDt2NRQDPSOzpNgSSSgxWtMdBbwO7XAKhAzULWcEMikUgkEonkIEY2BZJIxoOialbeHesHepqAusX6c6kE6yoOjJ9CTFGA6UexrzN+wDZJ0j9Tcqhw1n8Dyy4FFpw13mcysSGFZjdXbi6iCDejsIJ9j/YxlRmQ/6ZAEsnByPSVgD8EDLQC7/6ePSbLzSUSiUQikRwCSIWmRDIeKIoexNzyVOZzB7YAySgQLgcqZ4/9uRkpqgKWXgSU1I33mUgkY0NxNWum5TU4d6hAHppEVQ7jlVZy3quXnEuFpkTiTLAQmHYU+/fu19h3WW4ukUgkEonkEEAGNCWS8eLoa9n3t38DxAb1x7Vy88Nlh1KJRDJxKZ0ChEr0/3vtcA7oTYH697OEDiCbAkkkopCPJgD4gpn/l0gkEolEIjlIkdESiWS8WHoJK9GMdAPv/kF/PFf/TIlEIhkLFEX30QS8NwQCdIUmNUoLFDBPX4lE4gxvCdO4CgiXWP+sRCKRSCQSyUHCpApovvjii7jmmmuwYMECFBUVYc6cObj22mvR2tpq+vNvvfUWTjjhBBQVFWHKlCm4/vrrMTg4mPVzsVgMN910E6ZOnYrCwkKsWrUKL7zwwmi/HMmhjj8AnPhN9u+3fqk3B5IBTYlEMlmo4crOq+Z4Pw4pNPua2feiGlnyL5GI0rgKUPzs33NPGddTkUgkEolEIhkrJlVA86abbsIrr7yCiy++GL/4xS9w5ZVX4qGHHsIRRxyBtra2jJ9dt24dTjvtNAwPD+P222/HtddeizvvvBOrV6/OOu7VV1+N22+/HZ/+9Kdxxx13wO/345xzzsEbb7wxVi9Ncqiy/AqgfAYw1AG8dzeQjAFtG9lzMqApkUgmOryPZi4l59QUCCr7JhsCSSTihEuA+WcA/jCw+ILxPhuJRCKRSCSSMWFSdTm//fbbccIJJ8DH+QqeddZZOPnkk/GrX/0KP/jBD7TH/+3f/g2VlZV45ZVXUFZWBgCYNWsWvvjFL+L555/HGWecAQBYu3YtHnjgAdx666341re+BQD43Oc+h2XLluHb3/423nrrrTF8hZJDDn8QOOEG4OkbgTfvYEHMdAIorAQqZo732UkkEok9NSMl58Ei5qnpFSo5J2RDIInEHZf9AYj153YfSiQSiUQikUwiJpVC86STTsoIZtJjVVVV2Lx5s/ZYf38/XnjhBXzmM5/RgpkAC1SWlJTgoYce0h575JFH4Pf7cd1112mPFRQU4Atf+ALefvttNDc3j+IrkkgAHPEZoHQqMNACPHcTe2zqEbLcUiKRTHwaVzG/y1kn5jZmUck5USwDmhKJK0I5JhUkEolEIpFIJhmTKqBpxuDgIAYHB1FTo29+NmzYgGQyiZUrV2b8bCgUwooVK/DBBx9oj33wwQdYsGBBRuATAD72sY8BYKXrZsRiMfT392d8SSSeCISB47/O/i39MyUSyWSifDrwzS3AlffldpwshaYsOZdIJBKJRCKRSCTWTPqA5s9//nPE43FcccUV2mPUJKihoSHr5xsaGtDS0pLxs1Y/ByDjZ3luueUWlJeXa1+NjY05vQ7JIc5RVwHFdfr/ZUBTIpFMFgorWZOzXAiEWNk6IQOaEolEIpFIJBKJxIZxC2im02lEo1GhL1VVTY/x2muv4Xvf+x4uv/xynHrqqdrjkQjrFh0Oh7N+p6CgQHueftbq5/hjGbn55pvR19enfcnSdElOBAuB4/5Z/78MaEokkkMNXqUpS84lEolEIpFIJBKJDePWFOi1117Dxz/+caGf3bx5MxYtWpTx2JYtW3DxxRdj2bJl+N3vfpfxXGFhIQBWFm4kGo1qz9PPWv0cfywj4XDYNBAqkXhm5TXAhoeYUrNs2nifjUQikYwtBeXAAKuwkE2BJBKJRCKRSCQSiR3jFtBctGgR/vjHPwr9rLEkvLm5GWeccQbKy8vxzDPPoLS01PTnqfScp7W1FVOnTs342f3795v+HICMn5VIRpVwCfBPb4z3WUgkEsn4wDcGkgpNiUQikUgkEolEYsO4BTSnTJmCq6++2vXvdXV14YwzzkAsFsOLL75o6n+5bNkyBAIBvPvuu7j88su1x+PxONatW5fx2IoVK/Dyyy+jv78/ozHQmjVrtOclEolEIpGMMnzJufTQlEgkEolEIpFIJDZMqqZAQ0NDOOecc7B//34888wzmD9/vunPlZeX4/TTT8ef//xnDAwMaI/fe++9GBwcxOrVq7XHLrvsMqRSKdx5553aY7FYDH/84x+xatUq2exHIpFIJJKxoLBC/7cMaEokEolEIpFIJBIbxk2h6YVPf/rTWLt2La655hps3rwZmzdv1p4rKSnBRRddpP3/hz/8IY477jicfPLJuO6667Bv3z7cdtttOOOMM3DWWWdpP7dq1SqsXr0aN998Mzo6OjBv3jzcfffdaGpqwu9///uxfHkSiUQikRy6kEJT8WeWn0skEolEIpFIJBKJAUW1aiE+AZk1axb27Nlj+tzMmTPR1NSU8dgbb7yBm266Ce+//z5KS0tx+eWX45Zbbsny3IxGo/jOd76DP//5z+jp6cHy5cvx/e9/H2eeeabwufX396O8vBx9fX0ZpesSiUQikUgEeOmHwGs/YY3R/mX7eJ+NRCKRSCQSiUQiGQdE42uTKqA5kZEBTYlEIpFIcuCtXwHP/ztQtwT4ytvjfTYSiUQikUgkEolkHBCNr00qD02JRCKRSCQHKYWV7LvscC6RSCQSiUQikUgcmFQemhKJRCKRSA5SFp4NLLkIOOIz430mEolEIpFIJBKJZIIjA5oSiUQikUjGn6Iq4PK7x/ssJBKJRCKRSCQSySRAlpxLJBKJRCKRSCQSiUQikUgkkkmDVGjmCeqt1N/fP85nIpFIJBKJRCKRSCQSiUQikUw+KK7m1MNcBjTzxMDAAACgsbFxnM9EIpFIJBKJRCKRSCQSiUQimbwMDAygvLzc8nlFdQp5SoRIp9NoaWlBaWkpFEUZ79MZN/r7+9HY2Ijm5maUlZWN9+lIJBIb5P0qkUwO5L0qkUwe5P0qkUwe5P0qkUxMVFXFwMAApk6dCp/P2ilTKjTzhM/nw/Tp08f7NCYMZWVlclKQSCYJ8n6VSCYH8l6VSCYP8n6VSCYP8n6VSCYedspMQjYFkkgkEolEIpFIJBKJRCKRSCSTBhnQlEgkEolEIpFIJBKJRCKRSCSTBhnQlOSVcDiM//f//h/C4fB4n4pEInFA3q8SyeRA3qsSyeRB3q8SyeRB3q8SyeRGNgWSSCQSiUQikUgkEolEIpFIJJMGqdCUSCQSiUQikUgkEolEIpFIJJMGGdCUSCQSiUQikUgkEolEIpFIJJMGGdCUSCQSiUQikUgkEolEIpFIJJMGGdCUSCQSiUQikUgkEolEIpFIJJMGGdCUSCQSiUQikUgkEolEIpFIJJMGGdCUSCQSiUQikUgkEolEIpFIJJMGGdCUSCQSiUQikUgkEolEIpFIJJMGGdCUSCQSiUQikUgkEolEIpFIJJMGGdCUSCQSiUQikUgkEolEIpFIJJMGGdCUSCQSiUQikUgkEolEIpFIJJMGGdCUSCQSiUQikUgkEolEIpFIJJMGGdCUSCQSiUQikUgkEolEIpFIJJOGwHifwMFCOp1GS0sLSktLoSjKeJ+ORCKRSCQSiUQikUgkEolEMqlQVRUDAwOYOnUqfD5rHaYMaOaJlpYWNDY2jvdpSCQSiUQikUgkEolEIpFIJJOa5uZmTJ8+3fJ5GdDME6WlpQDYG15WVjbOZyORSCQSiUQikUgkEolEIpFMLvr7+9HY2KjF2ayQAc08QWXmZWVlMqApkUgkEolEIpFIJBKJRCKReMTJzlEGNCV5pX2oHZUFlQj5Q3k/diqdQsdwBxpKGnI+VjQZxWBiEDWFNXk4M28kUgls6d6CNNIZj88tn4uSUMk4nRXQG+3FnoE9GY8FlAAWVC1A0Bd0dazOSCdKQ6UI+8P5PMWDkmQ6iQPDBxyv730D+9AV7cp4rDhQjLkVcye8f293tBsF/gIUBYvyfmxVVdE61IqG4oZxex9UVcX+wf2YVjJtwn8W+aQr0oXiYDEKAgU5H6ttqA21hbXw+/yWPxNJRhBNRlFZUGn5M6qqYnvvdkSSkYzHawtrMbVkas7n6ZVkOonOSCemFE8Zt3M4FOiKdKEwUDgqY8140DHcgfJw+ajMpal0Cm3DbZhWMi3nY1mta+aUz0FpyF5hYWQ4MYztvdszHlOgYFHVItdrzMH4IFSors/BjAPDB1AaKnU93vXF+tDU35TxmNe11WiSVtPojHSirqgu52OJrmtEiKViGEoMoaqgKudj9cf7oaoqysPlOR/LiKqq2NW3C4OJwYzHqwqq0Fhqb03WPtSOqoIqBP25Xw8tgy2oK6pDwJf/rX48FUdvrNf1NZJIJ9AT7cnLtWVGb7QXQX8QxcHiUTm+JL/rXFVV0TLUgqnFU0dlzdwf74cCJS/jvmRiIwOakryxu283LvrLRTh5+sn4xam/yPvxb3vvNty76V787ozfYVXDqpyOdcPLN2Bt21o8dsFjmFU+Kz8n6JKbXr8JL+x5Ievx6SXT8cwlz4xLQCSSjOCCJy5AT6wn67lL51+K7x73XeFjHRg+gDMfPRNH1h2J3535uzye5cHJD975AR7d/ijuPfterKhbYfozm7o24YqnrjD//eN/gAvnXTiKZ5gbA/EBnP3o2ZhZNhMPnf9Q3o9//5b7ccvaW/C9476HS+Zfkvfji/DQ1ofwgzU/wL+t+jd8ctEnx+UcxpqdvTvxyac/iZX1K/Gb03+T07HWdazDZ5/9LK5YeAX+45j/sPy5656/Drv6duGR8x+x3CjTZ2HGoxc8igWVC3I6V698963v4i87/4KHznsIi6sXj8s5HOz0x/tx9mNno7G0EY9e8Oh4n07O7OnfgwueuAAnTjsRvzrtV3k//s/e+xnu3nQ3fnv6b3HCtBNyOta3X/s2/r7371mPTy+ZjqcveRo+xdrU38hVz12FLd1bsh4/furx+J9P/I/wcWKpGC584kKE/CE8fuHjOSVe2ofacdZjZ+GIuiPwhzP/IPx7iVQCFz5xYVYyEgAumncRvn/89z2fU76556N7cNt7t+FHJ/wI5889P6dj/dfb/4XHdzyOP5/zZxxee3hOx7r+peux/sB6PHDuAzmt29NqGqufXI1oKoq/Xfq3vCTieJ7d/Sxuev0m0+f+dNafcFT9UabP7erbhYueuAinzzwdt59ye07n8Mb+N/Dlv38ZVy25Ct86+ls5HcuMb776Tby+73X89eK/OgZpeX71wa/wh41/yMs+zkg0GcV5T5yHynAl/nrxX/N6bInOU7uewr+98W/4+pFfx7WHXZvTse788E78at2vcOvJt+KsWWfl6QwZw4lhXPbkZQCApy9+Oi9JAsnERXxlIZE4sKt3F9JqGm+3vI1kOpn342/t3goA2Ny1OafjbOrahDdb3kQincBbLW/l49Q8sb2HKQ/qCuswvWQ6ppcws9t9g/vQGekcl3Pa1LUJPbEeBHwB7Zzqi+oBsAWSG3b17UIincCm7k2jcaoHHdt6tgEA3mx50/Jn6HotCZZon09lmKnU3txv/XsTgf2D+zGcHMb2nu1QVTXvx6f3b1PX+F1vm7vZ2OT2XpnM/HnznxFJRvBu+7s5f64iY3xaTWND5wb0x/vx0DbzwHhaTePuTXcDyBxfSd22s3dnTueZC3SdmgVqJPlh38A+RJIRbOvZho7hjvE+nZzZ1rMNaTWNd1rfQSKdyPvx8zlu0fhbV6Tfdz7Fh32D+7C3f6/wcZLppHaPTCuZlrEW2dqz1dU5dQx3oCPSgX2D+/C3pr+5+l0ju/p2IZlO4r329zCcGBb+ve5otxbMpPeFVNoTbe7+qOsjAMDvNvwu5zGdrq18vMaPuj7CUGII92+5P6fj9MX60DLUgu5ot3Z++UJVVfzpoz8BAGoKa7TPujBQCMB+3N/avRUqVLzf/n7O50H7i9Fai2zv2Y6UmtLmM1Fe2vsSAOCV5lfyfk4dwx2aCtrNvSlxx+v7XwcA15+9GXT/fdD+Qc7HMvLUrqfQOtSK1qFW7Bvcl/fjSyYWMqApyRsDiQEAQDQVHZUNY1+sDwDQHevO6TgPbdU3wbRwGw+GEkMAgF+f/ms8e+mzePbSZ7WSr+aB5nE5p42dGwEAJ007STunJy96Ej7Fh/bhdleBVvq8BuIDSKTyvwk72BiIs/uHPgMz6Ll/OvyftM/nxyf9mD3XZf17EwF6fUk1iXg6nvfj0wK2J5qtLh4ruqNsbNrYuXFUgrYTjYH4AJ7e9TQApu7ONRHTFx8Z46PWY/xAfAApNQUAeGz7Y4insq+lt1veRvNAM0qDpfjrxX/V7pVjpx4LQB97x4PhJLtO7V6jJDdo7gHsx9PJAo1psVQMO3p25P34/LiVK1Td8aez/qTdd4fVHMaO72KO6o31AmAl5k9f/DSevfRZ3Hv2vQDY5+tmfO2P9Wv/fnDrg8K/ZwaNUWk17SoYNpRkY05pqDRjbeVX/DgQOYD2ofacziuf0Fp+V98uvNv+bk7Hyte1paoqBuOshPvJnU/mFLDi1wj5Hh82dG7A5u7NCPlCeOyCx7TP+oK5FwCwH/fpua5oV84BOZrjdvXtGpX5jo7pZr3VH+/XLBdGY1zmX6dZlZkkP3zUyfbN/LjqFbp+8r3nVVU1Y6wfrz21ZOyQAU1J3qDFBjA6gcL+OBs8uyPeN4L98X5tAw6M72aHJt/igO71Mr2UqTT3DogrGfIJTVTLapZpjxUFizCnfA4Ad+8XfV6AXFyIQH5LH3V+ZLlZo/d/afVS7TH6d/NAc8ZGfqLBjw+jssAe2TCOZ6CI/nZ3tBttQ23jdh5jxZM7n8zwqMx13KIFst1nyJdsdke7TW07Htj6AADgwnkXZngokq/WeAY06W/LgObowc89B0NAk7/mRyNxRdfilu4tOSlAhxPD2njA+xzSeoLWF27OqSJcofnploVZw81EOoFoKip8LApCAizg5OY8jPCbeDfXFgWoeG+/wkAh5lbMZceaQAlJfq5+YMsDno+jqqr2OX7UZb2uESGSjGiJrMHEIJ7e/bTDb1iTcT/leXygIMpZs8/K8Him+0EkoAnkHoCheUaFOipVK17mMf48ch1r7M4JyG2fKLGmL9anrfP4edYrdP3kO+C47sC6DAWpDGge/MiApiRvkAILGJ1NBAVrcgmO/WXHXxBNRTUl5O6+3RmLt7EiraY1pQ6/4Z5ROgPA+A2+Gzo3AACW1izNeJyCZvS8CHxwbTxVc5MFun96Yj1oGWrJev7A8AG0D7fDp/iwpHqJ9nh5uFy7biby5p1UH8AoBTQ9KAbyTYbyYwJtUEcDPgPuV1jAIddxiwIPw8lhxFIx058xfr7GDXfLYAte2/caAODyhZdnPEfJo/EsR5sI1+nBDj/3jGcVRr7gr5VcgnFmpNW09n7FUrGcqmtobRbyhVAU0Nc1XtYP9Jr5oFBRoAgBhVn/u0neGZVElPDwgtdguVkCG9CDvRNp7ubX8i/tfcmzbcNgYlCzn+qOdqN1qDUv5wSwcd9rgHS0FJo90R48t/s5AMCVC6/MeI6uY7txn38u17mU9hdA/seMeCquBSPdzGP8ez0alXz8a5YiitGBn0/zIaCggOa+wX1IpVM5H4+gdWG+1qaSiY8MaEryBh+wyPfiLJFOaJOV141gWk1rG/Brll2DhuKGUcteOsFvqPmMPZlrN/eP/eDbG+3VfEZ4BSDgTWHBqyKkGsmeRCqREcAxu3/osTnlc7I691IAeiJtiozwG5JRDWiO40KWH5vcbN4nI2vb1mJ3324UBYpw5qwzAcCVR54ZIkkQeryxtBEBJYB1B9Zl+JI9vO1hpNU0jmk4BrPLZ2f8Lo21xu6zY0UqndIUbLlap0isMQadJrv9w2iOK/2xfk35luvx+SAk39SQ1g9uVFlmAU1FUTSVppvNNP0seXA+u/tZz5txr3YGNOYYuy/TWmsizd2U5K8MVyKpJvHoNm+NtYxjeC7XFr1/hYFCFPgLsK1nG9YdWJfzee0d2Ju3ypbHdzyOeDqOJdVLMqqcAPcBzVyrHXihRr7HjAwlpIu1vfEaz/c1z79muecYHfjPjN/jeSGRTmhzdTKdRNtwfqqaOiOdeH7P8wCgNQjNdW0qmfjIgKYkb/CTyfae7ZYKGy/wGXavE9Wa1jXY078HxcFinDvnXD0zPg5KKloQBJSA1qgC4AKa45BNoszbzLKZKA+XZzzHv1eim0P+M5NqJHv4ZABgEdAcuU6NC2UAnjzKxppRLzkfOWZvrDevmV5REqlExueYb1XERIOSQ+fPPR+Lq1i37n0DuRmv8xtLq3GeHp9XMQ+nzTwt41ziqTge2/4YgGyFDDD+JecZChI5Jo4a/HXUH++f9OoM/lrZ2bszw+YhV4yB9VzGLbo3+XJzgK0pSoOlrhSgVseitYmbckf62eOmHoeFlQsRS8XwxI4nhH/f7FgAUxX1RnuFfs+s5BzgksU5lmTnE5rHPrPkMwCAR7Y94qk82DiG53JtUUK0qqAKZ88+G4D3cvisaz4PKu5UOqX581+58MqMgD4AVBdUs789ViXnSX2Oy7dKPcOr0oNCk7rd5zugyb9mOb+ODvxn1h/rR1pNez6WMZGQr3n68e2PI5lOYnnNci3ZPtnXABJnZEBTkjd41UtSTea1i2s+1H60+Llg7gUoDhaPa6kPTbxFwaKMhY8W0Bwc+8HXzJ+RWFC5AEFfEH2xPuFucfzCX2ZL7THaHphdk5q/aXV2QNOLgnas4ceH0QxoptV0zpljLxiv8U1dm3Ja7E1k2ofatW6lVyy8Im+JGJExgw90XLHwCgDA07uexkB8AC/seQHd0W7UFdXh5MaTs36XggnjVXLuVdkicYcx2DWR1G9e4D3/Umoqr2sro9dcLu+VVRDSp/iwpGaJq+NbHassxBSabhpS0Ma5PFyOKxaxMeOhrQ95Gp+Nm3DRYJFWcm4IaM6vnI+QL4SB+MC4eafzJNNJLWB+8byLUVVQhY5Ih6eu1MYxLpeEK60fSkOl2mf4/J7n0RXpsvs18/OK5C/QSrzZ8ib2D+5HWagMZ80+K+v5yvCIQtOmgiSfAU1+jts/uD+v842Xeawz0on24XYoULB6wWoA+Q+08q9Zzq+jA3+vqFBzqnYx3rv5CDqm0ik8tI0lFq5YpK9N9w/uHxehg2TskAFNSd6gDKoCFqDL5yaCX7xGkhFEk+KG8ADQNtSGV/a9AgDaJpgCQ+MRBBqKmy9uafDti/WNeYMXOwVgyB/CwsqFAMTfLxG1lYRBigi6dzZ1bcqYfFVVtf18FlUtmpDdUnn4kvPRCCh5VQ3kC9qoVIQrUOAvwGBiUOvoebDx6PZHkVJTOKr+KMyvnI/GMjZu5aspEOBccl5ZUImV9Ssxr2IeIskIntz5pJa0Wr1gNQK+QNbvjnfJufEanSiKrIMNmnsK/AUAJrZyXQS65huKGwDk2fcvlnnsHb07PCtAzcrECVpviZ671bFIoekmaUU/Wx4ux7mzz0VJsAR7B/bi7Za3hY+hHct4bQm+HhpzjHYxQV8Qi6oXuTrWaMKPURUFFbh0/qUAgAe3uO8Ob7xuc0nyUdK3JFiCpdVLsbxmOZLpJB7f8bj784rl/36iKoGL5l2EwkBh1vN0HffF+izVrnywM1fbKWPSOJ/7HC9rLXqP51bMxaqGVQBYJZ/bvZwd/Lwu9xz5p2O4Ax2RDvgUH4K+IIDcfDSNwf18WK29tu81tA21oSJcgTNnnYn6onoEfUEk0gm0D0/MvZEkP8iApiRvUMCCGpbkcwI1DppuAxbkq3b0lKO1rpJLqpdAgYKWoZYxn/xIoWkMaBYFi1BTWAMg9/JNN6iqqi04zAJmgHufxgw/PGnQbQvdO7PKZ6EwUIjh5HBGMGzf4D70xfoQ9AWxoHJB1u9P1G6pPHxAM98BpWQ6mWFxMR6LWfqbNYU1WFTFNqgTWTHrlUQ6gUe2PQJAL+ueXjIdAFPG5bLAFVHi09hfVVAFRVG0BNWdH96JdQfWIaAEcNmCy0x/d7xLzvm/G0vF8lo6LNGha3DllJUAJvd9mFbT6I31AgBOnHYigPw3MgFYUqy6oBopNYWt3VtzOpZpQJMrrRY61siagZRtRHloJKDpwUOzLFSGomARLpx3IQBvzYFojKJrS3S+pSReSbAk6zm3wd7RhNTNhYFCBH1BrF6wGj7FhzVta7Crd5erY9FnuLJ+JQr8BRhKDKGpr8nTeVHStyTE3j9eaetWeUXXqXY/5bhm2jewD6/vex1AdiM6oiJcoSWsza7dZDqZ8XjbcBviqbjnc6K5RmsYmcd1YYZCM9YtlJjjK8Dqi+q1sSafavPxTmof7PA+/qScd6OUN2L8jPKh0KTEwsXzL0bYH4bf59eaAMuy84MbGdCU5A0KUhzTcAyA/E6gxhIyNw0VEqmEZmpOm1+ALYxmlc8CMPYLSavyI0BXaY5l+VH7cDs6I53wK34tGGPEreco/5nJxYU9pD4oD5VrfoT8NUn/Xli5EEF/0PQYE7FbKs9olpwbjzcuCs2Rv1ldUD3hP4tceGnvSzgQOYDqgmqcNoN5WPKJGK+LxmgymhGUtvoMaeynoMl5c85DUaBIC4CePvN07VyMaCXnyfEvOQekimS0oLnn+KnHAwA2d2/Wui1PNgbiA1rTnhOnswBMPks1+dJuzYvZ47hlVSYO6POTqCpLO1ahoeR8pCmQFw9N+l0KOr227zW0DLYIHwfQN/B0bYk2nbJb802k+YJXQgJAQ0kDTp7O7DsoWCCKluQrqsHi6pF1jcd9ASVES4OlAIAzZ52J8nA5Woda8dq+1zyd13HTjoNP8THlmcdO7gDw0LaHoELF8VOPx8yymaY/4/f5URGuyPj7PJS0UKCgMFCItJrG/sH9ns+JrjdSQ+ZVocl5VSbTSaEENV9hpCiK6wSHCHzlj9xz5B9e9OJFKW+E7oOiAFOt57rn3dO/B2+2vAkFCi5foCcWxmNPLRl7ZEBTkjdowXHMVBbQbOpryvIG9Ioxo2n0wLHjxb0voivahdrCWpw649SM59xmxl/f9zq++PwX8+ZvYxfQHMtsEi125lbMNS2XAfT3ylgObcWhWnL+uw2/wz+/+M+uTPTp3ikJlZhubrTsdk22vykxEbul8vBjQb5Lzo3Hy/V6e6X5FVz3/HWuNjn0NysLKvPScOz1fa/juuevG1OltgjU+OCyBZdlBNdJCeJ13MpKWjl5aIZZoKMkVILz556vPc8nrYx4VWi+tf8tXPXsVdjV506hZCTf16nEHJp7Dq89HMXBYkSSkZw/u/GC/DNLg6VYUbsCANu4uQno2cEHIWl+MeuKPBAfwNdf+rp2/zsdy4hbVZbxPidyUWjS784pn4NVU1YhraY1tbko9L6valgFv+LXvAGdoDHHWHIO6PP6lu4tox54/6+3/ws/eOcHls/zXpXElYuYEv/JnU+6mrv5zzDXoC2tH+i8wv4wLpnHOhh7DbROK5mmV7Z4PK94Ko7Ht7Oyd7u5B7DvdE7nVBGuyMsegK63jzV8DIB44F0Et/OYqqq6B/zIdWA31nhFelS74439b7B1jaDymoLPh9Ucpjdny0GhSZ/RYbUskdY80JzTNfrw1ocBsMTf9NLp2uMzynJbm0omBzKgKckbtOCYUToDU4unQoWKTV2b8nJsYxbITQnz+gPrAbCMLvl+EG7LqB/Y+gDeaX0H/7P+f4T/vhm0aJwoAU07f0ZidvlsFAYKhTaHiVTikO3oe++me/HKvlewuWuz8O9om4hgqWnm2skOgH9uInVL5eE7gOe75Nx4vFyvtzs/vBNvt77tqhMuX25Jn8XW7q2eusMCbJP2duvbOY81+URVVazrWAcAOHfOuRnP0QLS67glaitiVtb6qcWfQoG/AMtrl+Oo+qMs/wYFE9wGNB/c+iDe73gff2v6m6vfM5Lv61RiDgWdKgoqRsUCZyzhr/eKggrN3iFfr8ds3DJTTT287WG81PwSfr/h987HCmeXnPOqLJH1llX5Oqks3QQ0adNNm3BAD9I9uv1R4dLeeCqu2UTUFdVhXsU8AGKfhZ1Cc1bZLJQESxBNRYW7wHuhK9KFh7c9jAe3PphhAcPDJ1eJYxqOQW1hLQYTg9jWs03472VcWzl61pud1yXzWUBzTeuaDHW/HWk1rV07leHKnMv9t/dsR2+sF5XhSpw0/STbn6Vr2SzYxr9Xue4B4qm4tu44qu4oBJQAuqJdefMQNApVnOax/YP70RvrRcAX0CyTRqOHAT+/Spsre1RVxX+v/W+83/E+fr3u10I/T/PC0pqlWnO2nDw0R66bw2oOgwIFkWQkowGeW9YdWAcAOHd25tpUu5/y4NEpmbjIgKYkL8RSMcTTbFFYGirVA4V5Kjs3ZoHcbARpwK0rqst6jkqsRINApAx9bvdz6I32Cp+DEaGS8/6xk8eLBMz8Pr+2OXRa/BkD0IdKtlRVVW0z7Wai59UHtNDb0r0FiVQCqXQKm7tZcJSuVzMmWrdUI/wieLRLznO53hKphKYgcrPJ4RWaM0pnoDRUilgqhh09OzydB10/zzXlNtbkk2gqqo3zxvGUFJpex60sFb6JrYiqqtp7wavA5pTPwTOXPIO7PnEXFEWx/BtURun2+mseZAvhXMoSzf7uoTIujiV80Kk8XD6h/Am9YAzs5btUkz8+qfyNCtBUOqUpMzsiHZaNXTTfSxMPTf7cndaFqXRKDzpZNAXyVHI+sgkHgFMaT0FdYR26o914Yc8Lro6jQGFztQslPt37Zh6aPsUnvLbKBX78slqf8MlV/vzIh87NGGgWLKd1jVvMzmtm2UxUhiuRVJPCvq/9CkGaUAABAABJREFUsX7NwsEpiC8CBR1nl8+G3+e3/Vmas5wCmrlWO/DzTGVBJeZVssB7vq4tvuQccJ7H6P5YWLkQIX8IgD4WNPU35U1tzitHI8mI9Ki24Z3WdzSf/pf2vuR4X+8b4Hz8KxbkpeScrvm6ojqtQVcuQh4a02qLajMeHw+RkGTskQFNSV7gO5wXB4vz7glEg6ZPYZesm40g3+HSyMKqhQgoAXRHu9E61Op4LFqwx9NxT90VCbuSc1rMjFWpKZ95o82fFXwA2A5aoNDn1R/v96xUm0zEUjGtZMzNRE/vV0moBNNLp6M8XI5EOoFtvduwq28XIskIigJFmFU2y/IYE61bqhE+ez6RS8639W7TrlU36gHeQ1NRFC044LWkiq6fWCrmSik6mtCCMaAENN8jItdFo3HMMEta9cf7kVTZ/WUMdNQW1ZqWc/LQeBtLxYTHI1VVtbH4wPABod+xwujdKVUk+Ye/jkqCJXlPro41xjJuWlttOJCfUk1KHFQVVKGyoFILXPFj35stb2p+fsl0UvP7szrX6oJq0+e14JHDuNob64UKFQoUzXeQcKsMiiajiKaYZye/Bgz4ArhsIWseJlqyrDUXCpfBp/hcVfhQEMhqjBqL6/RARB+/rNYnZkpIQE9g8cdwgr8eGksbURYqQzwdx7ZecZUnoXl7cuflVvUL6Nd7abAUIX9Ie9+9VrZQ8pgvcbWC7mG7kvOqgqqcqx0ooFngL0DAF8h5LWLEuN5yEphsPJAtmODHmnxV8k0EL/XJAj/mJdWk1mfCCrp2FlUtQtAf1Ow78lFyng9VMqDP/ca9Pn/siVi9JskPMqApyQu02CgOFsOn+PKuiqCFJE2ArgKaBv8knrA/jPmV8wGInSv/dx/c+qClUsEJCu4YgwKAPvh2RDrGJMO4d2AvBuIDCPvDWibXCtEFPE1yDcUNWoBioqjMRhM+aOdKocn5VvHBsI0HNmrv9ZLqJY4KgImqRkqkExnXsjHDnytZpbw5BIr4zXZHRLxZAL84A3JXUvHXTy5jTT7hN/RGJWSuPkUiYzw9VhIs0ZQebuCDCaJB9c5Ip3bt5qrQNJbqufGClohB11FpqJStRUbuw23d24TLUicSxoCmNjfkKfBF16AxYMqPWw9syewGbnYf8IooK4UmnbuTKotec3m4HAFfIOM5twpN+jm/4s9SR142/zIElAA+6PhASOHHd0sHuLJZgWCYXRI741ijaI3AlxxbrU+0gGbQPKApWrasqmrGnMiva7y8Rj7py+N2nqXrna7RBRULEPQF0Rfr8yQioPmOhAh2iHhoVhVU5VylZfRrFU0kiGJcb4kqNOnzJ/ItfHF7XocqbUNteLn5ZQDAl5Z/CQDwyLZHbJO8xs9Qs/7IQ1Og6oJqNJblds2rqmq5159WMg0KFAwnh3MqaZdMbGRAU5IXaCKhxcaS6iVQoKB1qBVdkdwHEFrMzC6fDcBd5s3Y4dKIaNkQv2AvDBRi/+B+vLn/TeHz4LErOS8Pl2vG52Oh0qTM28KqhVkeo0Zo0b21Z6ut7xRNLBXhCtvOjgcbvC+VmzIaY2dRftMqYgdAjEbnyHxgDOTkq1kYQfdTyMeCXLlk5o2La9HFtlZuOeIfl0twmbcuCPgC2De4D2+1vOX6OPnGrHSToE3YgcgBTwpc4xg/lBjKGmOsfPVECfqC2jUiWnbO2zfkq+Rcu06lQjPvGDc1U4unui5LnUgYr/kl1Uu0zsy5KobTalpTW1qNW80DzXhj/xsA9KCn2X1A5xn0BS2DdqKqLLv73K0yiH6OkoU8tUW1OG3maQCYP7rjsUgBNHIO8yrnIewPC9m8aGtkk5JzwH0XeC/w14vV+oTmZuMYryk0Ba+5ocSQFiAxJvm8zIn0/pUFM8/L7TGNtghBfxCLqkYqWzwkCSgAQ/OfHXSPOZacjyQH9w/uF2rAacS4v+DXhflIjBrnMbu1fSqd0u514xo230F8WneInNehzCPbHkFaTePoKUfjS8u/hKqCKnREOvBK8yuWv2Ns6pQXD01uzZyrQnM4OaxZSRj3+iF/SCtpn2hNNiX5QwY0JXnBmNUtCZVoG9N8BFdoUUolt148NM024YD4gohfsF86/1IA7rsrEjTxmi1uFUUZU88PbaJyKDcHWKarIlyBZNp+c8hL/7Uym0Ng854R0HRRikENcyghwF+TWmbUpsM5QT+zuWvzqHdLdYMxgGksvc0VOt60UvcKbiP0ftcU1rD/i5ayGZVUI5/Fzt6drpXWkWRE+/wunHshAODBLd7Gmnxi1lyDyEjEDLpfNPIKTVJlGT9HGoPNuiiLQveYaECTH4O7o905WWfk8zqVmGMsO/NSljqRMDbaKQoWYU75HAC5v56B+ECGnyCQXYXx8NaHoULF8VOP195Hu4AmqfGsEPksqCzYrLkQbVYHEgNCc5yd5RCgd6Z+etfTlo1ytGPFMo8V9AWxsGohAOdyXrsu5wCrZqkqqEJSTQp1gfcC/7lZrU+M4gSCfOlEkzp0PRQGClEYKASQW1m9Wck5oCd/d/ftFhrTzYLluZRkU4CEgpB2VBXaeGhywZ0pRVMQ8AWQSCc8NfIx+rXOrZiLsD+MwcQg9vTvcX08I7R/oXnMbm2/u283IskICgOF2rhF5LvTOb1u7bxkyXkWiVQCj2x7BAAb+4J+bj9rscZMppOajz+N3168jI3H5H2Sac/rNeBIxwr5QijwF2Q9r6meJ2B/AUl+kAFNSV7gS2aJfG4iaLCaVT4LgPhGUFVV2004oC9mNnVtss1e8ptpWgS/tu81zVvKDU6L27EMaLpRACqKIrQo5YPIWmfHQ6C8kg/ceWoKNGJ4T16lu/p2aV1FRQLOY9Ut1S18h3Ng9JoC0X3TG+v1pEQYTgxr7xst8kQSMolUQtsMU7CtvqgetYW1SKkp1xtUunaCviCuXno1AODVfa96GmvyiVNwIJdmBnwgigIZxg2JFujwqNAEdJsPLwFNFSo6hzs9/23jdSo3XPmHt0UgJqpyXQTN47JQD+K7aUZje+xopp8gwNZDPsWH9uF27BvYh8d2PAaAdQW3U+k5+Wdq5y6gXNf8iAuzj8Unpp0CkIC95RAArKxfibnlcxFJRvDkzieFjpVxbQmozFRV1UvOA+bqVT7wPlrXqUhTIKuS8/qi+qxj2MF7sxL0Xu3s3elaxW9M+hLVhdVoKG6AClXIi9HsOvVakh1JRtARYe+HiEKzKmyd3OcTon6fH9NLvPtoGv1ag74gFlctBpCf/ZibeYzGKDPLJKrkax9uR2fE+7wKsDUYNSyU86s1L+59EV3RLtQW1uLUGacCAC5feDl8ig9r2tZgV++urN8x8/HXmgJ5VGhSZQD5JGtNJT0GHPlkk1lCjUraZWOggxcZ0JTkBb5LM6GVzeY4gfLllzSYigY0I8mI1kTCahM+t2IuCvwFGEoMoamvyfJY/IJjVvksHNtwLFSoWvdPN9iVnAO5BQbckEzragCRgCYgtiHhAx9acOJQUGgmPJacGxICtUW1qCuqQ1pNI5lOojKsl+rZ4VN8ebvv8gmNDwrYQiPfAU16/+g9SqtpTwutzd2bkVbTqCusw8cbPw6AvY9O/mh0bfsVv7bZzQj+u/ws6P4pC5VljDUPb33Y1XHyjZYcsggO5JJl5wMPWhLEMM4b/f68QGOucECzP3MMpg2sF+g6pc2qVGjmH7OKjMms0NTWHeHswFCupZpG318gUwF6+3u3oy/Wh4biBpw47UTUFVr7KJodywyRMVE7lolCM+ALaME2kTHeLAjJoygKrljEEtQPbn3Qdqznx2VC5NqKpqKaEtYYkOMZbQ/sDIWmVcm5iTgB0EvOhQOakezPsL64HnWFbF3jJsmnqqo2XvNdzgmtUZaA0s/sOqXf39ztrrKF5rmyUJnl/oJH1EMT0JsMeQnwDMWz9xf5DJbTZyEyj2mCCZOEfHGwOG9qc34+l/OrNWStcdmCyzSLsSnFU3DK9FMAmFcd0jyztGapFpSmMdBrUyD6bCrCFSyAP3K998Z6Pak+rRoCEbn60komPjKgKckLmmE3l9XlJ9BcOosNJYa0xSAFNIeTw0IG/7zSyUyGDrAF8uLqkeyljeLB6L1Di+DHtz/uutmAsSTEyFgNvjt7dyKaiqIkWIKZZTOFfkckm22q0DwEFhdeFZpmnUX5BeDSmqW2ZXw8E7GrL70+KuPOd0CT1B582bOX7DwtqpfWLMWCStYsoD/e75hYoL9VHi7XmmAB3jeoRlU5jTWPbX/M1rt2tNE29BbBgVzGLT7DbjVmGH1KveA6oGn47HPx0aTrVCpIRg8tmcYF3d2WpU4kzEpkeYVmLmsrK69Ker9e2PMCAKbg8fv8tkEtUX9bXgFqpcpyOpabckc731/i/DnnoyhQhN19u7G2ba31sUyqfeiz2NK9xTIYxl9zVH5thtcEmCgZXc5dKjRrC1nJ+XByWMgD27heJry8xuHksFZxYRYQdpPENVo4AGxfURwsRiQZwa6+bIWaFTQ3iKgzAf296I31Zl0rxms+F1GDmWAin9eWUaFpt7Y3ei8aydd5kSo17A9r9giHwp7DDdt6tuG99vfgV/xaBRJBa8wndz6ZpZ42C0prCk2PTYGM13txsFhTTXu55p2s5eh+kh6aBy8yoCnJC2ZZ3YVVCxFQAuiOdqN1qNXzsWnADPvDqCms0fzVRDaDvFIwZ18nQ3fEk6efjCnFU9AT68HzTc8LvBIdmnytFJpjVXKuBXBGNhki0Hu1q2+X5eaQz5bRJHUobN4zupy7mOhpE8GrD/gFoKh6lv/Z0eyW6hZSrlLZWiwVy6vHp7aADxRrCgcvi1l+8Z3RLMBhsW1UVxBeVRHG0m5+rPlb099cHSufOJVv5jJu8YEHzXfXWHJu8T67wW1AkxQylEzLJaCpKVtG1AjRVNRTAyWJNWZBJ7dlqRMFVVXRG+0FkBkYomRLX6zPk18tYaWq5OebgC+Ai+ddDED3UeQDY9qxbHwveUQ8QJ3Unm4aUhh9L80oCZXg/LnnA7D3RTcLls8sm+lo80L3eFGgyHadRe97U3+TUDm9G+KpeMac6BjQNAQOi4JF2vpERKXudG25SbjSOQWUgKkwwc2axyxY7vf5saR6ifAxCLcBzYpwhValQiW3AGucw/sJ8sf0EoAx219QMGpL95acfKCB7HmsJ9pjmlhJpBLY2sO89q084MleKdcEPB/EPZSqwtxA1YSnzjgV9cX1Gc8d03AMZpbNxGBiEE/teirjOTMffxoDY6mYpyZmZvdhLutH0WS7LDk/eAmM9wlIDg6MXZoBFoCcXzkfm7s3Y2PnRkwtmerp2PwmWlEUVIYrcSByAN3RbkwpniL8u3aIlHAZF+wBXwCrF6zGLz/4JR7c+qC2IBZB1EOzdagViXTCsfv4hwc+xJst7juuU5d2kYYzRE1hDaYUT0HbUBs2dW3C0VOOzvoZPlsW9ocBHBrZUn4TIqrQjKVi2gKT30Twn4mIf6bxZ6lbakHAXJk8ltD4UF9cry2OhhJDQmVaIvD3U1VBFfb07/F0vdG50Xu4tHopNnRuwMaujThnzjmWv2fVrIaUI3v696Av1if8eo3jVi5jTT5xKt+0M15v7m/Gxq6NOGvWWabJJT7wYNVILNcu54C7gGZfrE8LtB5ZfySa+ptyCmhSwqO2qBYhXwjxdBw9sR7LecCJTV2b0DzQjDNnnen5nIh1HeuQUlM4qv6onI/19z1/R31RPQ6rPSznY7nFrCwYYEGP1qFWbOzcaDpnufobsT48seOJrOZm00um47w55wmr6QGgdbAVb7W8hQvmXoCgP3Oe74/3a5Y5/NgS9AexsHIhNnZtxK/X/dqxuuKYhmNwRN0RWY9rXpUG30s+oHnGzDM0L0s7H0U730sjS6uXYkfvDmzs3IhTGk8RPi+Cxh+RpKFTKSJxxcIr8ODWB/HS3pfQPtSeteEH9GA5P/6RzcuatjXY2LlRaxLE42QxRFQVVGFq8VS0DLVgU9cmrGpYZf/iXGAMQlu9d1o3cROlU21RLQb6BtAx3JHV4MWI5bXlwS5BS/iadKoHdC/GlqEWdEe7bRNetI43O69/tP0DGzs34uL5Fwudl9uAZsAXQHm4HL2xXvREe7SKld5YL1SwgGBFuCLjmF6qHcz8WmeUzUBpsBQDiQHs6NmhVaV5gcY9OsdEOoGhxFBWEHxbzzYk0glUhCu0MnAjfDBaVVVXY2fGOXFJA6uE6MHAYHwQj+94PEM8AQB1hXW4eP7FlgmTwfgg/rrzrwCAKxdemfW8T/Hh8gWX49Z3b8XdH92NrmgXe0KF7uPPzQvFwWL4FT9Sagr98X7X+wyz5PSMshlYd2Bdls2PCE57fS34HuvBQHwgy1JDhOebnsfOvsykVdgfxgVzL9DuZTPWtq5FMp3EcdOOc/03JeLIgKYkL1hldZfWLMXm7s3Y0r0FZ8w6w9OxNeXOyCKyskAPaLr9XSsoeLSle4vlpGq2YL9k/iX47brfYv2B9WgZbBEK2vJ+QFYL3NqiWhT4CxBNRdE62OrYQfGGl28wVU2Isrx2uaufX1q9FG1DbdjSvcV0c8irZChYdzAuLoxkdDmP9wst0Oh3FCiZJULVSxFQAkgj7SrgPKV4CqoLqtEV7cK77e/ihGknuHwV+YcUmhXhCi2QMxoBzZJgiWVDGSf6Yn3aBoXe72U1y4CtzpsvKzVKRUEFGksb0TzQjDWta4THQLNx65L5l+C369lYs7lrc04bEq84lW/SONU21JaRiEmraXzlxa+gqb8JtYW1WDllZdbv8hl2+gyzPDTHWKFJ10NtYa1WsmTWEEUU2nSVBEtQWVCJ9uF2dEe6hfxxzfj2a9/Gnv49mFcxD3Mr5no+r6HEEK574TqoqoqXL3/Z1ufPib39e/GNV76BusI6vHj5i56P4xWrJoBLqpfghT0v5KWD9N0f3Y27Ntxl+tysslmuArk/e+9neLbpWYT8oaxEBV3vJcESrWkPsbx2OTZ2bcTTu552/Bv3broXb1z5RtZm12rcWlC5QFt/XLlI3/zypZyJVCIjAGvne2lkWc0y/GXnXyzVsk4KTdq0ivi3aUFIm5JzAJhfOR9H1h2J9zvex4t7X8SnFn8q+1gUHA1lX1tr2tZYXlsUfHAKaALsvWkZasHbLW/nN6BpGLcsPTQtuokDzEdzV98uoTHQ6jOkuXXvwF7hwIJV53WiNFSKWeWzsLtvNzZ2bsRJ00+yPq+I+XktqWEKTTfjg9uAJv1dCmhq58T5CVIFGt/ExG2gz+x68yk+LK1Zinda38E7re94Xj8k00lEkhEALChcGChEJBlBd7Q76/PZ1M3u7yXVSyzPf0HlAgSUAHpjvWgfbncUqVjBXyMHs83VI9sewW3v3Wb6XENxg2XQ7PX9r2M4OYxZZbMsE3oXzrsQv/zgl9g7sBe/WfebjOeqC6oxtVjf3yqKgrJQGXpiPeiL9Wl2JKKYreUo6JhThY/FXp9K2ruiXWgeaNYU2aLs6d+Db776TdPn9g/sx3eO/Y7pc4l0Al976WtIpBN49YpXHechiXdkQFOSF7SSc4Nh95QiNjlp2R4PGL0x3GTfRBWaNFCTYsZsw2y2YK8prEFjWSN29+1GU3+TUEAzmorqfkAWHpo+xYfppdOxo3cHmgeabQOa8VRcC2ZePO9ibUEkSm1RLU6efrKr36ENePtQdnMAIFMVQa/1YFxcGOGzprTwc1Jf0QaiOFicseEsD5fjtlNuQ0pN2Wb/jCiKgjNnnYn7ttyHh7Y+NCECmvQay0JlKA4WIx6L59XLLqPciBazMXfXGwUtZ5TO0IIhxmYBVveW3Wb+rFln4a4Nd+GhbQ8JBzTN/IBqCmvwiRmfwLNNz+LBrQ/iu8d9V+yF5RGn8s3aQvNEzNstb6OpvwkAK6c0BjRT6ZR2jdg1BcqrQjMpHtBsLG103RTDiKqqmrKlOMisEdqH2z2XxamqqnW939G7I6eA5qauTdomdc/AHk1Z7IUdvTsAsLJUN6rkfGGlyKONclfE+1qEaBtqAwAcXns4FlQuAMCqHVqGWrCjd4ergCb/GRqxu96/cNgXEPAFtM/Nise3P46BOFPVGYMFZn6CABDyh3D7KbejO9qdoeysDFci6AsikU7gQORAxnrHzb05u3w2AOuNq9Ox3Cg0jfYddiytWYr3O963tEiyGv9obODLiHk0xZxAQPOs2Wfh+T3P4/Edj+MrK76SFcj2CjVyogCUWQVJIpVANMXKR83WpvQ6zZpCGbH6DEmB3x3tFg4sWPl68iyrXobdfbvxUedHlgHNtJrWPiPjeZGCsG24zfF8CFJPOgkOeKoKqrC7b3fG+sTsvZpeMh0KFAwnh9EV7XK1BrQSTJw16yy80/oOHt72MK5aepWwzRQPr0qn8m4KaBrfB3p/7NS8IX8IFQUV6Ix0ojfW6zmgqVXpcArNg3HPQWPTkuol2jz9j7Z/oKm/Cdt7t1sGNKnh7RF1R1gGl2nP8UrzKxmPK1Bw+szTs36vPFyOnliPpyY++S45d2pYScfvinZh78Be1wFNmp9rCmu0hqF7+vdgbdta2zGjL9anr6369oxL1cqhggxoSvICXxLCk49MmXER6eaYTiWSRNAf1BZZB4YPmAY0rRZoM0pnYHffbmGvG5p4FSi2BvEU0Nw7sBfH43jLn6P3IaAE8L3jvue5ZMMN2ubewkuJD8jQoulQ8LMx+l71xfocA5pW9w7AvG68cMXCK3Dflvvw6r5X0TrYioaSBk/HyRd89rw4WIyeWM+oBDSp5Bxwr9A08wmaVTYLRYEiDCeHsatvlxa8MELXttm4sXrBavx+4++xpnUNdvXtcizVA6w3zlcsugLPNj2LZ3Y/gxtX3jjm2V6n8k1FUTLGLdrgUGdNwFzhOJgY1EruysJlpr67qqpalva7gTZ5It6VfECTym1FNvNmRJIRLbmTj03XQGJA86HN1ReK9zJsHmjOKaDJn8u+gX1jHtC0ag5AXcLdJjrMoPvg4nkX49IFrLnC99/+Ph7a9pDrz4I+f7Pfswvs1RXV4V+O/hfH469pXYO9A3vRPNCcFSzQbHRMjn/i9BOzHlMUBXVFddg/uB8dwx0ZAU036mnNH3BwH1LplNY5F2DJDQo6WR3LjUJTNKkNQOvibpW0sLIzoPWl1cZetOQcAE5pPAV1hXXoiHTg73v+bmt14gYad+eWz8XGro2m7x1VUgD2AU03Ck2zz7CxtNFVQJOSXXZqzqU1S/HXXX+19WIciA9oDUaN50WvrSvSlXVNmpFIJ7TgkhuFpjbuR/RxyMx/NuQPYUrxFLQOtWLfwD5XAU2rAPrZs8/Gbe/ehuaBZrzV8panZDcdO+gLavumlqEW0/UWjWmkvLOiLFSGzkin547Z/HnxSe1IMjJhbJfyBY0xZ886G1cvuxoA8PP3fo7fb/y97dxDzzkF30+afpKtwpnHjZexEbMGj1QFY2ZZ5ISIVzKVtHvxpaXfWVm/Ev957H8CYNY6a9vW2l63/JzQPNAsA5qjiGwKJMkLViXn+WgIY9xEuwlYiPonAc7ZZ6sFmtusEh98sQs+inY55Dc9YxHMBGCrVkqr6QxVBC0u+mJ9OZuRT3SMvjYimUvaRORS5mlkTsUcrJqyCmk1jYe3PZy343qFV1i4CSiJwm8YvQaKzDo5ijYLsAu0NZQ0aApoMmV3wmrcOrLuSMyvnI9IMoIndzwpdKx8IlK+aRwPWwZb8Nq+17TnzcZXWowWBYoQ9AVNk1ZWfoJuoevPeK+aQQqTxtJG24YoItA16lN8KAwUaq/R69zI/16unTv5gGaux+Lnq/Ew4LdS5FUV5s9XzWzzRBtFt6+ZNnZm7zsFOnK53vnS1ay/7eBVaQZ1uzbO/W6SDfVF9Qj4Akimk1njQV+8L8tP0IjWYTdPTYEIp3UNzWPGY1Gw1Op83JScB31BXLbgMgCZiaBcodc0r3IeAFYpFEvFMs9zJHBYFCgyDehZffZm2CX53K6ZtYSonUKTa+xp1qAGsLdwqCqogk/xIaWmhNYOrYOtSKkpFPgLtPdFBLOGNRTctNpbuA3wWAXQi4JFuHDehQCAB7dYN7+yg68oAvRkiJlgQbQkP9eO2UDmNVISLNHsbg42qyu7ucdu7hYNLrtBU8p7CGia7afpOukY7nDdaEhkr0+v3Ysvrdm1LHLd8sFO2ZBodJEBTUleMOtyDuRHoWmUklv5q5lhpdYwwyn7bLVgdztIimbrtUWfg0Gyk9/UaGC38B9KDGlKpLJQGWvmNNLZ0cvEN5mgxR4h8no19UHQ2UvKDVcsugIA8Oj2RxFPxfN6bLfwKlQ3ASVRMjw0PQaK+A7nPPxGyQqne5BM2P+y4y9CgVyrwKGiKNqxHtz6oOXGbTRIppNa8N02C05Z9pHx8JFtjyCtpuFX2AbZbMywUuHznyH9uzhYnFMZphcPTb7kfCgx5EldrI37gWLW3C7HuZH/PS+KBp6PuvRgvZfFPg+/aM/1vNySVtOWHpq8ty7NT14xC5pq6wAXrzmWimnXxd6BvVn3s1Wgww2NJdbNRbysHczm/mgyqpWiihzL7/NrJb7G94tec3m43NLig953kYShk+8vDyUtzMaowcSgvq4xVPw4BVjdlJwDwKULLkVACeCDjg+wtXur0O84QdU0s8tna1UzRmURje9WSki7plA8qqpaelUC4sl6gj5DO4XmoqpFCCgBdEe7NUsII3bXe8AXQE0BU0GKBGz5AJEbIYHp3GYR/PVagmu3x7h84eUAgFf3varZXbg6tqGDutU8pqqqrgostVcFOiUEhM7LIBQ5WH00zbp5iwS+6Tk3amIn3IzDRswCmhXhCm0f5DaxKrLXz6WknU9uEyIKVf65sV4PHWrIgKYkL5h1OQfMJ2+3GAdwN0oLNwpNu+yz3YJdW5wNulNoOi1uRRd94xLQLNSDv8ZNGL3nYX8YBYEC+H1+TWlxsC0ujFDgLqCwjZhIxtnJ8N4rVLrWHe3G3/f8Pa/Hdgs/PlAJfr5KztNqWrs3i4JFnhay7UPt6Ih0wKf4sKhqUcZzFNDc0LnB8vedPN+OmXoMZpTOwGBiEM/sfsbxfOx8386dcy6Kg8Vo6m/CmrY1jsfKF7ydgsiicd/APsRTcTy6/VEA0JQhZgpHY9CBFrmDiUEtGG9WouQFLyXnM8pmoDhYrP2uFx9N2gjS9Z9ryTn/e7lk/ruj3Rkb21xVBOOp0MywLjBco3RvptRUljWIW8w2T9p83d8snGjg1zBDiaEslVM+rnmrTZyqquiN9rLjewlocnYz9DoCvoCtik7kvERes2ipYyqtf9ZOtkOAHrA7EMle19DfKgwUIuwPm5+PxXxvDAI5UVdUp9nNPLjVm5LOCI1Z9UX1lu+fU2m3k9UQMZwcRjzNxm2zz9Ft8w+RkvOwP4z5lfMBWM/VTvO0XUDbiNcAkdm4b3VeoxHQnF0+G8c0HAMVKh7Z9oir45odm9TdxnmsK9qFSDICn+JzbHqXi9KPMCYNDlYfTTOvSLpOWgdbTavghhJD2vuQ14BmDoFos2ueLIsA99e8iFey20QKj51Csz/Wbznn83NCrtUvEntkQFOSM6qqWmZ2zTambjF6ILnxwnLjn2TnkWa3YOc38CIbGW3iDYgpNPcN7rNVlGjK0bB3FYdbaOEXTUWzsnNm7/nBurgwQvdBfTG7lkQ8gUQM773Al67la1PkFV7BTa+TN5fPBb4phteSc/LdmlsxN8vzlAKa23u2Z5XoEU7+cT7FpykjHtjygOM4YTduFQeLcf6c87VjjRV0TiXBEtvGY/wm7IU9L6A72o26wjrt9YsoNEtDpVpSgMY37T0uzG2cE1UIR5IRLfhKrymXxkBD8cyNoFevV4L/vfahdstr0wlSJpOCNhcVQSKdQMtgi/b/sQ5o8kEno4o35A9pY08u85CqqqaJUtqIDSQGhDd4xvMwqijzkay0KoX3auFgdg9opfHhKmG1mnZehgoUES9O0RJVPsAtsgakdU0kGcnwkwT0udwsqEYBmcH4IFLpVNbzvHpMFOou/9Sup3IOwAP651VXVGf5/lkJEwh6fzqHO23XpPQZFvgLTF8zffaianDRpK9WTWHho6ldWxZrZTfju6j60IjZ+sTqPhet0jLiJJqgKo/Htj/mel9mDBxaiVbos20obkDQH7Q9JgXYvSj9CONrNivtPxgw6+ZdV1SHkC+EpJpE22C2Opmu1YpwRV591528g61IpVPaHJklEPJo3SLaFAhge3w3Je28Xy7vQUrvZVJNWjbnkyXnY8chH9B85ZVXoCiK6dc777wz3qc3KYimolpzAuNiz2xj6hbj5sGN6tOLh6aZgshuwT6tZBp8ig+RZASdkU7HvyPqpzSlZAr8ih+xVMx2gaWVq+S40XdDQaBAe0+NJfpmjZjyodSd6Kiqqm0IqJzOjULTTn3gFSpde7/j/byVrnnBtOQ8np+SczqOX/GjwF+gbRj6Yn3CpaVauXn1sqznphZPRWW4Ekk1afoeJtIJbZyx24RfNO8iFPgLsLVnK9YfWG97PmaLVh7a7L7c/LJleV2+ES3d5D377t9yPwDgsoWXoaGYNabqjnYjkcpUERiz6z7Fh4qCCu3n+e+5Jm6KAmyD7aTQpGx6aahUOy+npiF28LYIQGYJtBcyGiZBxf4B9+WDgG6lcMzUYwB4868i2gbbtKYbgPuNeK44ebzmGkQGWLCL1jv83ykMFGpVHqIbF+N5ZKkV89AEi08w8IkUOraZn6AdmpcsN+9r5+liDWKp0BR4zVoAxCFhSM8XBgodgyr0czQPZ61rbBRAtIlWoZomSoz3vggr61dibvlcRJIR/HXnX4V/zwxVVTMCmlbvn5Ofd01hDRQoSKpJ26SA02fIe+WJJGJEk74U0LTyu3a6TkUVqIC4P6QRs7WwVRDfa3DHKYB+cuPJqC+qR3e0G8/ved7VsY37F6u1vRvPRjeeuKLnlU/P5ImCqqqmyW6f4rNVNnoNvjvhVaHZG+u19En24hubSCU0gYSdEp8vaXdjt2Dll1sYKNS8Wq3eA34PeCByIK+9AySZHPIBTeL666/Hvffem/E1b9688T6tSQEFFHyKT9ssEmYbU7cYy7vcKLDceGjalZvYLYSC/qC2WRdZeIiWnAd9Qa2LqN1xtexujqWYbrEq0TcLIh+sfjY8kWRE28zT4kJkorfrcp4ro1G65gW+aZhWcp7MT8k5X8qrKIp2H6TUlHDXTK0hUE12QFNRFK3zuZmPJpVt+hSfbeKkPFyOs2efDcC+2UMindDGCKts89yKuTh6ytFIq2lPZWNeEG2u0VDcgIASQDwdx/oD6xFQArhs/mWoDFdqiz9j0sgsEGXcKDmVC4pCm3UnywNaUPObgJwUmoaS83x6aALelZWkZjpx2olawMCLtxqgz1PUkbcj0mGpXBgNnK7RfMxD9DeCviAKA4UZz7ktETWeh7EkzU3ncCuml06HAgWDiUGtezh/bLf3k5mPonZvuliDWG1cRc6LVxjaqd1FyhCNWFXq2CmAgv6gtvY1m/PddDknFEXRfLBz9UseTAxq92FdUZ1e4mtIuGprEQs/74AvgOpCVmJsNwY6fYaV4UqUBEuEEzGiSd+l1Wye3tS1yTSZ6bRWdqXQ7M9fQNMqAEzH7on1CKt0k+kkoimWkLIKAAd8AaxesBqA++ZAxmvZaj/mpiQ/Fy9GIks5OvIZd0W7PB9zojGUGNL2GMYxza6cejQaAvHn4DagSddKRbgiq9qHr3gUhcYxBYrtGMGXtLvxCrfyy1UUxbFawPje7BuUZeejhQxojnDiiSfiM5/5TMZXTU3NeJ/WpICyusXBYtNyo1zVeVYNI4YSQ47lEm46XNoZnjsthNxkldwYxItskMbDQxPg3i9DNtssiJwPZcxEhxbdfsWvvTduApr5Ljkn8l265pZ4Kq75aVEHSiB/Xc6N91PQH9Q2ZCK2FKqqak1RKHBpRFN+dGUrP/jFGTVbsII2qM83PY+uiPlCmw/C2i3OrlioN30yKh5HAzMzejMCvoCWiAGA02aehtqiWiiKYrlhNDu20VokXwFNsvpwCmjSgprfkOWz5Jy8x7yWxBk3kF7KmVRVzQjma/OYx8ZANP8tq16mXbtj6RvlpCLOS5NC7m8Y1ztu1SVOQel8XPNhf1i7bvnjez22WSLTyxrESjkqciyt1C9tXeoHuLMcIuj1WVaeWFxbduWXmmIuIF5yDgDnzzkfRYEi7OrbhX+0/cPV7/LQaykNlaIwUGiprNJKzm1Ku52aZwLO15aiKK7uFadSeGJuxVwU+AswmBhEU3+T6/MSeW0A8+2mwARVJIhCa+HeWK9mT2B1XryFjuj4zlv52O0xqHpn3YF12NK9Rfj8Rb0q3agCRRXXdhh9ag/GPQeNLSFfCAWBgozn7JrS0XzOl0vnA69WAXb3oReFJm8H4rQG9+JLaxecd7p2je/NWFetHErIgCbHwMAAksnkqB1fVVUkEglEo9GD6mtgaAANoQbMKZpj+vycojloCDWgb7jP0/ELUYiGUAOKlCJEo1GE0iFMD09HQ6gB7X3t1uc1PIByXzkaQg0oRKHj3yn3s58Np8MYGBrIeK4/0g8FiuVCyM0gSYEvET8lkePmoyzNC1aKVjOF5mh5aE4k+T4tuouDxa4yziKG97nAl649sOUB7BvYp315Ccy4hQ+ilgRLHLtMq6rq6nPVSo04T1otcBFxvt6aB5rRH+9H0BfEgooFpj9DpehmCk03jTuWVi/F8prlSKQTeHzH46Y/Q8G90lAp/D6/5bFOnXEqagtr0RnpxIt7X3T827niVM7Lwy/8KPAKWKu67Xx3szw0cxznaNwdTg7bWhKYdbXUym1NbEmcsOoOG0lGPKkY6X1xW+bM0zbUhu5oNwJKAIuqFuXUBZT/veml03M+lhecEpj52OTa/Q23JaJ2n6Gqqpbdj91i9lnwNjpuoKDPcHJYm7u83JvTSqZBgYJIMpKhohJZz/ClfnZzrJN1hxlWSQsn+yK78kut5Nxl47+SUAnOnzvil2yj6neC1KZkmWG1PnHqcs4fw8xrnhC5HtyMDyJdzgGWTFtcvRiAedm5ds1bnJfIawP0UvmAEtCqs0ShElsVqhbUJOW02XnR+/ThgQ8z1m5WayR6POAL2FpJ1BTW4PSZpwNw58Wt7V8CmZUGPdGejMSEWULQClFPXNvziouVwk9mvM49bj4LN3hWaMasBUJODY7McGMt58XGwc5eQlShSYFW6aM5elg7+x9ifP7zn8fg4CD8fj9OPPFE3HrrrVi5cqXlz8diMcRiuvdLf7994CIej6O1tRXDwxMnAJMv1KSKm+bdhKAviN27d2c9f0n1JTi7/GyURcpMn7c9tqrihlk3AACG24exW2G/f9O8m5BSU+hp6cGg39yLL6WmcNO8mwAAB/YdQKfi7G/5r/P+FSpU7GnakxFMmJuci89P+zyUAnPDezfm3W7Kj0QUM+MV0LRUW5kEJ0ZjcXHvpnvx03d/il+f9mucMO2EvB3XK/yim+9+54RmeD9KCk0qXfvRmh/hFx/8Ar/44BcZz39r5bdw1dKrRuVvA5neRn6fXwsoWTVl+eUHv8QfNv4B95x9D5bXLnc8vnY/hfT7qaqgCnsH9gqp30h1ubhqsaXPGik3d/ftxlBiKOPedesfd8WiK/DhGx/ikW2P4NrDrs16XjRwSE2ffrv+t3hk2yM4a/ZZQn/fK27KN0ktMLd8LlbW6/OoZbAglr0gNarp8hXQ5D+74cSwZZDBbBFr1zjOCeO4XxwsRtAXRCKdQE+0B4UlhXa/ngVd2yvqVuCFPS94KjmncvP5lfMR9oc9qSN4tDL9shnojHRiU9emsQ1oOlyjWkAzh0YRdn/DbRDX+BnyvzeQGNC8OnNVJc8om4F329/NWJ948b0EWEKgNFiKgcQAOoY7UBIq8bQGCflDaChuQMtQC5oHmjWbApEgLpX6dUY60Rfrw5TiKaY/50WhSWOU8R53Cpbbbe61e9+hEaQZly+8HA9ufRAv7X0JXZEureTbDZSAodfmtcs5fwxbX3eB68GNGtyNz/jS6qX4oOMDbOzcqAWDRc/Lzkefh+7TqSVTbRvkmRHwBVAeLkdfrE87Hys/QYC9T+sPrMcP1/ww4/GiQBGeuvgpLclGGAN7dly56Eo81/Qcntn9DL599LeFRBbG4DwFpeLpOIaTw9rfdVVynkO3bIKUqQezQtPr3OPms3CDlXWFE/SZmI1ldUV1CPvDiKViaBtsE1JAu7GW85JopXnTTG3sdO3S2nZO+Rzs6N0hA5qjyCEf0AyFQrj00ktxzjnnoKamBps2bcJPf/pTnHjiiXjrrbdwxBFHmP7eLbfcgu9973tCfyOdTmP37t3w+/2YOnUqQqGQcCfIycBAfAD+IT8KA4WmHh3FQ8Xoi/ehMlyJmiJ3ZfyJdAKpPlaWMadijva++fp9iKfimFo8NSOQwRNPxqEOqPDBhzmVc8T+YC/rWDatZBoKg2yDqaoqWvtbcaz/WCSTSaTTafh8meJmO/8SIzTxigSwqHSzbdi68cd4lZxbNcgwU0WMhofme+3vIa2m8V77exMioMkHJrUNg8BEz/tLjhYXzL0AT+x4Arv79IRCMp1EIp3Au+3vjm5A01AuRps6K4XBe+3vIaWm8ErzK0IBTa0EykShKbKYpez17PLZlj9TU1iDKcVT0DbUhk1dm3D0lKO159x62H688eMAmE/hcGI4axPhJtt8zuxz8Nv1v8W6A+uQSCc01dJoINJFkjhvznl4p/Ud3Ljyxoy5zqrpglmp8Gh5aIb9YQSUAJJqEkOJIcv7zmwTYNYQRRRjqZ6iMMV/x3AHuqPdGWX6IpD6+PDaw/HCnhc8lXaT4pgC9qRe8FomzitB6D0aywW80zVK96iIctsKu82Tm3UAfx7La5bjhT0voDvajcH4IEpCJdpzxcFihP1hz+cLWCg0c/Deri2qxUDfADoiHZhTMcfzvdlY2qgFNI+oY2ttet1OxyoLlWkBTSvcWA4RVmXHTsFyu/JLL13OiQWVCzCrbBaa+puwvXe7p4AmrdFo/LJKuIokV0VU6iJrUu2aHBSoahIsOQfsO507nRe9tr5YH6LJaFZZL5Gr4q0yXMkCmlxipTxcbhocPWf2OXir5a0MFX80GcVwchibuzdnBTSpEkDkvTqy7kjUF9WjfbgdH3V9lLGuscK43ioKFqHAX4BoKoruSDeKg8Xoi/Vp957Ie6QFxnIIaFp5ex5MHpoic8++gX1QVVVbd8VTca1xZN4VmiPz7GB8EKl0yraiiMdu7vEpPkwvmY6dfTvRPNAsFtB0kWz3FNC0UWg6dXqnx5fVLMOO3h2ek8USZw75gOZxxx2H4447Tvv/BRdcgMsuuwzLly/HzTffjOeee870926++WbceOON2v/7+/vR2Gh+48XjcaTTaTQ2NqKoyP2CZqIzjGH44j6EQiEUFGQvAArSBRhQB+AL+UyftyUJ+II++H1+FBbqCpZwLIxkIgl/yG95zHQiDV/Uh6A/KPx3w4VhpBNpdtyw/juBRADF1cWIdcYQj8ezjmfnX2LEzeLWydMnnopri9CJrNCksrZclDFGaBM1FmXTIvDqBjcKTQpoimQXvVIcLMaD52Wav7+450Xc8MoNo57BNpaxOTVlocWOmV+lGWaKZzcWB1o53sj1bMVhNYehbagNGzo3mAc0BTfzJcESFAYKEUlGcCByADODMzOed6Mqmlk2E6WhUgzEB7CjZ4dWbjcaaItpgfLNFXUr8NTFT2U97jhm2NhU5CugqSgKioJF6I/3W16DiXRC2wTwvlOk0DwwfABpNe3o18Rj7MIKMB9NCmi6QVVVrWyLgv77B/YjmU66Ugxp/pkjlgq5lImn1bS20Z9ROmNcAppOPq9aYk3AW9cKu4QDrQM6I52myQojdB6NpY2oDFeiJ9aD5oFmLK5e7MrKwgkz5W0uidC6ojrs6tul3cdej9VY1og1bWsyVHqir1ukTFXU95fH0krHQTlvp9B045tuxoyyGWjqb0LzQDOOaTjG9e/Ta6Hxy+q9o2vbLrkqolK3KykltNJPh6qmtJp2VbJ/WM1hAIAtXVuQSCW0qgtVVbUGflZr5bJQmRacOzB8wDKYkqviraqgCk39TRnjvtV7deL0E/HqFa9mPPalF76Et1reMl27udlfKIqCw2oOQ/vednzUKRbQNDt+VUEVWoZa0B3rRiMatXmgprBG6DxorTOcHPacmDWuAw/GknM7C42Gkgb4FT+7diMHtLXW/sH9UKGiMFCo+XbnCzoPFSoGE4PCiSOntVxjWaMW0BTBTbKd7tmWwRah9VJaTesBTZPxwErtTtDjy6qX4YkdT0iF5igiPTRNmDdvHi688EK8/PLLSKVSpj8TDodRVlaW8eWEUdV3sEA+ZFabOxowqHzKy7H9SmbmRzuman1M6gZn/F07aCI1enck00lAsT4WDZL98X7HLKPZxtYK4wbaCE0MfsU/ah6MVlgqGQSCE/mAjjVRApoUuCsJlbjyBBrtknMrxqrzvLHpEXkvOQU0N3ZuFOrsanY/uXltdP3SvWYFdVA1+mi6LbdUFMW2AZkb3zdFUfTzMlGk5BMtkOOifNOIlcLRLMPOl4zxATy3nn9mOPm4tg62IqWmUOAv0PwNAVYipUBBUk26vm/MAu9eN12DiUFtPl1YuRAhXwhJNakFYUVIq2ls6toEQFc1GRf7bjgwfADRVBR+xY+GkoacGwx5wan0LJ8emmZ/ozxcrj0usnHhN3a0WaLfy5fFAmAeqM7FqsaYmPB6rsbzSqtpWz9BHhqH7JKGbnx/Cctmhw7BUbvyy1zneDeWRmYYFZpWjSy0pKxFl3PAXVMgkZJzp7FmKDGklWSLrHEbSxtRFipDPB3H9t7t2uP98X5tv2DXrEgLaEes15V2ii0R+PWwl3vHbn1jVrFiB6nzRdcPWnCZu5aN85jb94f/XL00BkqlU5qC1RjQHE4OI5aKWf7uZMIu2R30BTXrDX7O5Zsz5bsyNOgLaut5N+papwSYW+sbN4krKmlPqkm0DrU6/nzHcAfi6bilX65dIiutprVzW1bL1litQ61j0sTzUOTgjLDlgcbGRsTjcQwN2XdClTgHDgOKc/DR7bHp/9Ql0PR30+4DmlbBVzp3q6BtUbBI84ByKtejBYfI4pbfQJttwjQ1Q0GlK7VQPqCFbWe0M+P9sis574v1eQpsmzHRApr8ZoAWHEOJIVtja1VVhTqLjgZjlcE2vj67YFIindCun/54v5iFg4n6xU3gwrjZs0LrdG5oNuAlMGDnQ+bW900rsTNpWJRPvJRvGjEL5Kqqapph5zdt+fQTBLhrMGk+v9NCenrp9IxNQNAX1D5nt2XnZtep13uQfr4oUISiYBGmlU7LOG8RmvqbMJgYRIG/AHMr5gJg1yUFR0UW+zx0rzYUNyDoC+rm/kPi5v65Mt5NgYDM0j8n+LHDGNzLpzc2Hbs72q2Nu/kMaHptXkTnRe9VX6xPS9xWFFTY/q6If5ubUkSCXltXpCtjfek0Llt5qSVSCe3691JyDuSmnAb0z4lem1XCVcSr0krByiNybfFjjV0ihtYPIV9IyHohI8nHzYl0Tk4WDiIeoWYN49zAj/ueApph63lDS/BaWHEZcbt+EEnMuQ1o+n26IMNLYyCzzu6lwVJtP3ewqDTNvMZ5zCxPcg2+O+GlMZDmoWmhGHU73rnx0KSSdkAsQaSta0oaTNWcdg1ghxJD2nw2p3wOCgOFSKtptAy1OP5diXtkQNOCXbt2oaCgACUlYxtkmIyk0/YKTfLVsAs+WqEFJX05KDQFfT0Aa4UmnYdd0JAmE6dNpZuSEH4DbbbAEvWbGg2qCqrgV/xIq+mMTLHZwr8iXAEFLDBACoxc4ANfEyWgyXthimaco6modg2PtcKWrqvBxCDiqfio/R16X0j1QYF8s4CmcVEkssjOVflGSgwnheaS6iUAwEqruOvdS7mlnRej28ChXQf2fOIlOGDEbLMYTUURT7PrzywJ0hPtyQjgWfmaucFJoWm3CRDZ8JqhbTR5r9ewHrR1g/GacxNEIygwv7h6sTaf+hSfVjbtVg1mfM9qi2pR4C9ASk2hbVBcOZoLZl6sPFYdefP5N0TVJbxdTGVBZdZmNJ/e2KWhUu1ay8fxSbV8YPgAYqmYdh+5PZZxzUTnVBYqcyw7dSr1A9yVIhJVBVXwKT6k1FTGfampPR0UmsaNLT/GeC05z1tAk7qcWwRfRfy8aZ7sjfWarhtUVRWyB+HHGrt7RaQM3oiWfORsa0Q9Y53Gd1VVdWsNzo7EDbxC04uVil3Fk9sGVLSu2T+4X2geoiSgseQc0P0qvZTkW6mGRaDXHFACCPlYZ3dFUbRqjoPFR1N07uHHiVyD707YeQdb4XTNu/WidrtmdjOe8gpXM+yuW3pPwv4wCgOFmFYyTfjvStxzyAc0DxzI3lCuX78eTz75JM4444yDtkw8n2hl4RaBQ02hmU7i6quvxkUXXSR8bEuFpkCQ1G3JuaIo+NtTf9POlUiraceyekD3z3IarNx0OQfsOy/mswzTLX6fXzOo5xd/ZgpNv8+vTTb5yJbyC/HBxKBlg5mxhC+t9vv8WgDPbqIn9YFP8WmlG2NFaahUuzdHM4NtVH3QQng4OZxlo9AVyVx4ipRB0fEzFtgj94OTV14qndL+ppNCszRUillls9h5ccFDLwoLq066gPvAIZWM7ezdmdE4IN94Kd80QoGQ4eSwdu3TvRxQAhn3AH2G1E0ZyF/iximgabcJsGps5IRZIovGT68BTbrmvAQ8tIZAI2omwu1mgjAGNEUDFvnEScFC71dSTbragLn5G8bScSvoMwwoAZSFyiwVmvm65vnjq6rqWVUJZCqt6TwDvoBtqbIZdH30xnrRH+93NZbaKWMIN/YdRMAXQE0Bq7YxW9c4KTSNG1sKABX4C1x3xCb4ILnbQHwqnUJnpBMA1+V85P0YiA9kzMEiJedloTItaGQW9IskI4imogCcP0eRRIybDueEVkZtotB0OierZpdEX6xPsxeiAIVbzBSaXgKaZp70bv1ay0Jl2rrGWH1ixlDc2rPcq0ITELufLc+J9lSh4oyKioPNR9OxOqAse+6283/MB14UmqIl59TgyAk3jTQB8Tma/xmzhsf83zRTFhvFPVoCbwxteA4lDvlo3RVXXIFzzz0XP/zhD3HXXXfhG9/4Bo477jgUFRXhxz/+8Xif3qSAAodOCs20mta8cEQ45ZRTcPO3bjY9tkgZu5eSc/pZXqFJx1Gg2AY0RT3D3GZQ7YIf+d70uMVYQhpPxbWginFyyadnozHwNRFUmsaFt0jnRgqCFgeL8+5v44RP8WllfaPpo2lUffALYWMg2rhAF1lgm1k4aNeaQzfjrmgXUmoKPsUnZJhuVnbupXmH3abJbeCwvqgeNYU1SKkpbOneInwOblBVNS8KzaJgkbZZpoAg32yIvwfKwmXaeLyrdxeA/DU+cwpo8s1tjHhVaJpep1Q66LJZmnHc1wKHLhbKlCyga5oQTcwZ0ZQMnGopV2WZW5yu0ZA/pH32Xje5Tn9D9DXT368oqICiKFnKznx6aAL6Jm5v/96cLRz4NQmvfHM7hxUHi7Vxt3mg2dV6RmQj7da+gzCWVUeTUS1IZ/W5W50PBQm9lpsDLHDmU3yIJCOu1WY9sR59jhtJoNDcokLV5udYKqYp5e3UkIqi2I6BdD2QKskOkXHLTYdzgqoW+CSf1qjI4dpy8gil+7O+qN5ztQAfkPRi/WC3vnHj0U+48dE066KeVXLeb69qM8NKNSyC1Z7qoAtoOsw9ZnP3mJWcC1oFpNIpR59kY4MjJ9yumd14dNLYZHUt2123xkaaY70eOtQ45AOaF110ETo7O3H77bfjK1/5Ch588EFccsklePfdd7F48eh1jD2YcFJC8o+7zS5TANSo/nSl0HRRck7nyis0KWjqFBgVVba46dgI2HsW5dNnywukuKJzo0yZT/FlLUDz4V9GGAMAIpPeaMN3OQfESjEo0z+aHc7tGIsFn1ZyPvK+hP1h7V4yBpToPMiPdnP3ZkfPVbsu572xXtNmWgRtWmoKaoTGCc1vamThn0wntUVLVaF7habZdeu2M6+iKKNedh5JRrTPIddr1TieWWXXfYoPFeEKAMCO3h0Axi6gabcJEPGQM4M2gnnx0DSo67S5Z1BsoZxIJbCliwW/jQFNCki6VVXyvqOEW3P/XIgmo1rzB7sAlp26SQQnvy7RdYBx7qb3qn2oHfFUPO9zO7+ZEvUTtILugc5Ip5Zc9HqeZuclciynElVVVT37/hoDdjRG+RW/ZWDNar4nfz+v5eYAC8RPKWINP9xuhikRXl1QrSlEQ/6QFmyk94/maQWK47naqdT5z9ApwC2yweebLYpSX1yP2sLajCSfsELTRkDAn2suASI+IOklcWE3hrmtAAP0ALBTAllVVS0xxwfoNeuUWDeiyah2XbgqORcQAFhhZeM1Gs1IxxPRuYfm21Q6hX2D1snZfODWKqAv3qft62l9ZyToC2oNeESStG6T7W6qUJzudyurEf4xeo/MFLSS/HHIBzSvv/56rFmzBl1dXUgkEmhpacG9996LefPmjdrfpElhPL7cBhTT6TR+8pOfYN68eQiHw5gxYwZ++MMfAgA2bNiAU089FYunLMbxC47HDV+5AYODg9rvplIp3HjjjaisrMTxC47Hbd+7TfPbdOLqq6/Gq6++it/95ndYVrsMU4qnoKmpCQCwceNGXHL+JTh65tE4duGx+OxnP4vOzk7td0855RRcf/31+MF//ADHzT8OS2cvxXe/+92M42/fvh0nnXQSCgoKsGTJErzwwgsA9KBlWk1rwVLayDsFPIwG92bEU3HXBvF2GeN8+mx5wbjwpwm3NFSapWbN5+LCGACwWnyOJcaFt4iCxIv6IJ+IlmbngrHDq6Iolk1Z6NpYUbsCxcFiRJIR7OzdaXt8M08nuh9SakrbqJlB1w1dx07wBvqqqmqZZgWKKxWQncLFi+/baDcG0srCfQFH1Y0TWcECm+w6fY67+nZl/D9X7AKaaTVtu4i161BvhaqqWqmemfeY2zGRgkj0frgt0dreux3xdBylodKsjY4XFYGqqqaqnLFUJPBBJ7vNvKh62+nvOCk0nbqZktKOzqeqoApFgSKoULFvcF/e53b+GhH1E7SiprAGChSk1JQ2Pns9T9PzcqPQtFAG8d68XgOaND/QGFUaKrUM0vHzPX8PegkwmeH1XqJ1o3GOM75/tBYpDhY7NpjUxvAhk4Am16jSCW2Db5OIESmDN8NYdi56bTkp8L34QxoxU2i6uX+Eupy7CWga1jVWRJIRLRjFH1+zTol0a/uf0mCpq/tOs2zwUHJu1Wj1YAtoOs09lEwciA+gL9aH9uF2JNNJBHwBR494r4g0Z+Oh6708XG5rweEm+Od2zSy6XlJV1TGgadcA1phQ81r9IhHDm6GLJCciyQhW3bdqXP72mk+tcVX6cvPNN+Ouu+7Cz372M5xwwglobW3Fli1bMDQ0hDPPPBPHHnssHvn7I+jo6MD3v/l9fO1rX8Of/vQnAMBtt92GP/3pT/jDH/6AomlFuOuXd+GFJ1/Aqaee6vh377jjDmzbtg2zFszCl/7lS6gvrkdjYyN6e3tx6qmn4povXIOv/b+vIRaJ4X9//L+4/PLL8dJLL2m/f/fdd+PzX/k87n/ufjRvbMaXv/hlHH/88fjEJz6BdDqNSy65BPX19VizZg36+vpwww03AAB8Ph98ig9pNY1kOgm/z59Rup6CtSKUBuCOSAciyYjpxp/fQIt6JtJEZBa0y3dZmlusAppmE4vXBhhmGI/htuPwaGBceIt4AnlRH+QTbcHncXMvglkX9+JgMfrj/Vkl5/S5VhdWY2n1UqxtW4uPuj7CwqqFlsc383QK+UMoCZZgMDGIrmiX5QLQarNnxaKqRQgoAXRHu9E21KZ9fhXhCldKcP6+UVU1Y5PsxffNrAlCPuH943K1RsgaM2yy63R95ho0MUJjr1lAs2O4A/F0HAElgIaShqznjap0EeLpuKb0N1MSux0TNYXmSEKCL0ntjHQ6+sHy/pnGz9O42Bf5vHlfOV6h6aVZkVd49YrdOeeSxEmkE9o1Y7V5qimsQWGgEJFkBPsH92NW+SzTn9MUYyPnoygKZpTNwJbuLWjud1d+LQKv3sl13RDwBVBdWI3OSCe29GzJ6Tz5UnhSi4oEWq08Kwl63K/4XftTGxX0Igogei6ejiOaimrrPy8lwGY0ljViTdsa15thGqeMY0JZqAxtQ23a++TGq1JramdSYWBMttghMtYYKzxEOazmMLzS/EpWQNPpmudfm9k55doQiD8HvoLETXKBfj+SjGTtNbwE0Gld0xXtQvtwO6YUTzH9ObpGfIoPBX693J63TtECvmWNrtYKXrwYjedlfM0HXcm5g4VGYaAQdYV16Ih0YG//Xi3ZP71kuqv1qRvcWgWIJtNEEzhpNe1aoWksabda//fGerVry8pD09gAloL7QHYAml8PpdW0Y+JI4g75bkosGRgYwB133IGf/OQnuOqqqzB37lyccMIJuPbaa3HfffchGo3innvuwbzF87DqxFX42R0/w7333ov2dhZ4+/nPf46bb74Zl1xyCRYtWoT//Ol/orRMbFFSXl6OUCiEcGEYNfU1mNowFX6/H7/61a9wxBFH4JYf3YI58+dg8fLFuPOuO/Hyyy9j27Zt2u8vX74cX/32VzFz7kx85nOfwcqVK/Hiiy8CAP7+979jy5YtuOeee3D44YfjpJNOwo9+9CPtd42dzrWSc4cJoTxcrg1uVhs4WmwUBgqFDeL5jqJGxttD06o0y2xiyefiwhgAmAgemkavSJGJ3qv6IF9on4nH8ksRzMrqaeFJiwWCLwszM/Y3w8zTCRC73ihJ4BQAIsL+MOZXzgcAbOjc4Pn+o3s6kU5oKk/AUCbpQqFJjV329O/xtCFwwmvpphlWCk3TJMjI+0pqtnw1P6N71CygSQvohpIG0zHayWPNDKtEFr2+SDKCaDIqfDzjdRf06yVaIgEPCnwfVnNY1nNTi6e68q/i/2ZdYV3G5prflNhZP+QD0Ws0l3mID55ZBVgURRFSYpgp2fgS/Xw3/KNzahtqQ/tQe9bfdgvdB1u7twLIU8m5i0ZFTgpNfpPrNgnjJlFLFAWKtAof/jrxopgzQ9Sj3QjNcUaFlvH9E+lwTtgl2Y3JFjtorKFEjBlek75GGxbRuZo++1gqZpqMdmoSIgK992k17egnaEZJsESbm4zjmJeAZkGgAPMqWVWi3XqLP7ZV8x2vJfm0PhRV+pmdl1GsczAFNBOphOYHa5fs5uee0fbPBDjhhmDJuWhiQTSgOZQY0tYWoiIA0ZJ2bV1TVGfpl+v3+bW1gHG8MFYfTSmegoASQDwdnxB71oMNqdAcBwoDhVjzqTXj9rdF2bx5M2KxGE477TTT5w4//HAUFRUhFWGqxROOPwHpdBpbt25FQUEBWltbsWoVU6L6fX4EAgGsOHKFq/MlOTgFE9evX4+XX34ZpaWlUKFCVVUty7Fz504sWLAAAAto8t6eDQ0N6Ojo0M69sbERU6dO1f7Oscceq/074Asglopppeak0BTJpswonYGPuj7C3oG9WuCDR5t4XSgG7EpgculUmg+ylAw2Hi+5epfx0AKlLFSG/nj/hCo5p+CknbcKYaZeHEvGYsFnVlZvVfLLbzqoWYRjQNPGP4n3ZTODrls35ThLa5Zic/dmbOzaiCVVS7S/5Yb/z955h7lRXW38nVHXanvzVvduU0yHUExvppuWECC0QOiQQggBQugfNSSBUJJQQu8Qqo0JzQYMGFxxW2/x2tu1q97m+0O6VyNpZjQjjcp67+959gGrzFxJM7ec+573mAwmVFmrMOAbQI+nh/4O7qCb9ltagocV1go0O5rR6erEqv5V2LdxX03tSQf19dTB6zU5IKjkGZr8vWrxKVWCFA9IVggDQJerC4B8BVvS/kH/IALhAMwGc9rzERWxzWhL2BgjC9NQJIRB36CkIlQKKT+4ltIWdLm60D7Sjnn182TfGwwH8XHHxwCAnWt3TnneZDBhXMm46LGG21Wpl6X8M4FYUJiLjqe9nl7Ul+Qm7Q1I9auSIxsvZ3KOUlOp4gZni6MF6wfXK3qHyv2GALCmf01WRXukqLZWw260wxPy0D41m3lDna0Oq7Eam52bszqWWDlK5lhaPDRJqh/ZiCak85tTIrloG/3dLfIbjxzHodxSjgHfAJwBJ73WtRaBlEONpZEUpJ8lm2iE5A1XqtBUsbmqZpNdzW+Y0NeMtEtuLGabct4+0g6n36m6XRaDBRWWCgz5h9Dj6UkYhwVBoNkCpDJ4Jph4E527EkiBRjVwHIcqSxV6vD0Y9A2i0RFfy2RqcTC7ejbWDqzFD30/4NDxh0q+Ri44T75Tf9hPNzi0ejZqDYwltEvGp5ZmQOTQUilfkHkSB05RrdxS2oJver5Bx0gH3ezPZUBTTa0AMWrvQ7X+2+S8VoNVkx90S2kLOl2d6BjpwO7jdpd8DTl3umu5zFxG0/zFJCtHjbwRjY5GtI+0o2OkQ1YJzcgMptAsABzHwW6yF+RPy061zZY++ClWXSgF/EhVcs0enogen+x8u1wuLFiwAN999x3e+N8bePmjl/HZl59RT0x6PqMxIVWc4zjV/p1yCk3yGZRIN+nMZLKRvIAWQ1KFC63QJAHF5KpuYnLhoTmjagaAwqecC4JAf1sy2VCj0CSDccE8NPPgMUQ9NM2pAU25lPNKayVNo14/uJ4W+0hG/L3LVbhU+mxy6XhKiA30k33wtCC1UUEmQBaDRXMFVakK7HpBVZR6KDRtGmwqkr7XTD3/kiHB72SFsLhdckHuCksFzHw0iKlWwShVEAiILUwzuAepYlUiGJZO0bCofRH6ff2osdVg3ybpwLcW03zx65LTMI18PG0/14WBlMYeMcmq31ycg3wPSsEnqb6D/IYrelcAiG58ZlpJORlxJXVyfD0UmmQDJlsPzR5PD7a6tqo+lnhRL+WTnIl1ByEThSYgUpmJxnw6PpmzC2gmF/xQC/kMyRsTyRuuWhSaaqqcq70e0vU1mW76llvK6bW1qn+VpnbJFX7rGOnAcGAYZt6MyRWTNbUnGXHfXWYuSwnIp0NufiM31qRDzfyBpnYnzbVsRhtNQSd9i2aFpkYvxoR2yXjR58NSKV+IfXyV1trion7U1zoLe4R0aLUKUKuUVjufUTsmJ6PGo1OtwlXOXkxq3BBbrDD0hQU0GbJMnToVNpuNpmqLmTlzJlasWIERV3wi+cXnX4DneUyfPh3l5eVoaGjAsmVRJaqBNyAUCmHFdytUn99sNiMcSqygPm/ePKxatQoTJkzA5MmT0TqpFeMnj8eUKVNQUiI9gCcrKWbOnImOjg50d3fTx5YuXUr/n6RypCg0+fS3S7q0oEwCmhWWCjrZES+gg+EgVQXqlZamFTKxHQmMwBvyxnekFIITenpoEm/FQsv3PSEPDe5rKgqkwbcqF+Q6oCkIQoKqiSCn0KQemtZqNJQ0oMpahZAQorv+yfjCvpTvnaDms8kt9pQgE//V/auzqvAr5cWoVCBHbbtyURhIq0eREskVchU3QZL6Nb2rnEspNNNdExzHaa50Tq5zqY0LrfegIAiSiwK6ABhWXgA8t+45AMAp006RXURrLUCiNPHPVFmmlXQFEwh6KDTTnUPN96ek0CRBK703KpOPn839lLwJlOkcpMJSQe8LUpFXTbvEqX5SY2wmxdUI5LMNB4bhC/lU2xlIqcz0UmgS9fOQf0hT4RTSz6aknCdtuNKAporNVXFhtGSRglZ/1nT3Ck05z2DTV5x2riUVXi5gS8bWGdUzNAcgkxF/P5nch3IZT3IZK+kQ+3DL2YPIBec5jqN9lZxaPx3pPHGVkE05F3l7jnbUzsHE420+U87VBqLVigCSCxzJkakSX80YTeZSaQOaMuIVqbltiyN/hRLHGiygyZDFarXit7/9LX7zm9/gySefxMaNG7F06VI8/vjj+OlPfwqr1Ypzzz0X69esx9effY3LL78cZ511Furro5OdK664AnfccQdee+01bPpxE/78mz9j2Kl+sBo/fjy+/+Z7dLV3YXBgEJFIBL/61a8wMDCAM844Ayu/XYn2ze344L0PcO655yIcjhfsIcpOjuNSdrMOPfRQTJs2DWeffTZWrFiBTz75BNdffz19ngY0Y8rMTBSacp1VJrunHMdJTrDIIG3gDBmpEPTAYXJQG4NeT6+ikisXHppEodnjTZ1Y5xOyGDByRrpTrcYTiKZTFSigmeuUc7F1gzjgSCwXUjw0ia+cpRIcx1FvyB/6fpA8vjggmmynQSezCp+NBq9s6gOakysmw2qwwhV0ZaV0Sg7sAdkFDsl3tbI/BwHNLNI3kyHBgj5PHyJCRJXvrty/M4UsjuWKAgHKNgTJyvR0KC0ytS66xNU0xd+HGlXlj4M/Yvn25TBwBpwy9RTZ12mpMCp+nVJAM9cTeLUqumz6PLX3AVmMqUk5l/oNCXpbyRB1CCGb+yn5/sj0WGLlqNZjSSkiCdn4/paZy+g43uvpVR3Ilkq/1KvKeYmphNqwaLmXZIsCWRK/u0yKAvnCPhpwJGj1lU63EUPmSJmMPSTtfFn3Mk0WDslZBAQyDyGB0mwQtyOTe4cKBJLUh0qbZ0pMrpgMi8ECV9CFLcNbJF+jFJxP/gxaU86Tr0ctyKWci618krPbRhtqxx6xkpsWaMplQFMUiFazBlObck4KHAHKasZM58xqfK7pvKZM+fuTsxcTF9MkaJ1bMdTDApoMRW644QZcc801+OMf/4iZM2fitNNOQ09PD+x2O9577z0MDAzg9MNPx5XnXolDDjkEDz30EH3vNddcg7POOgtnn302jpx/JEocJTjsmMNUn/uKq6+AwWDA8T85HvV19Whvb0djYyM+++wzhMNh/OzEn+GkA0/C9b++HhUVFQkKSuq9yaX6XPE8j1dffRVerxd77rknzj//fNx66630+ZSU89hESI2HZrrFW6YG8ZIBzdjAUGGpKFi1NHGwdbtnu6LXHhnAnH4nVb1mCln8T62I+pSGIqGC7sKK06KIrQMd5BR2nAtd5TzXAU2ySOLAJVzz5POKFXKhSIhO2ki70qVBkffbjfaUeyCdEssX8tEJR12J+oCmkTfSQPo3279JOJcWJFPOswgczqqeBZ7j0ePp0d2CIdO0HilqbDXgwCEkhKJ+cyp8dwl6BTTlilIBIs85BRsCrYWBlIIaWu9B8jqb0ZYQxFcTRHth3QsAgINbD1b0s1Qz2RdDU84lFrFqvbCyRW2KcT4UmuJqpnJjndTCrs5el6D80j2gmbSwzcpDM0nBnM2xUgKaKq0l5FL9xI9l0pcmz2vUKuelsjIyVcxJoXVzwB/207akpJwnBV+1bK5ajVb6/h53YtBPi4cmEA8WyCo0NaTCJ0PmD2ScVmvhkOwNTyDF1Mhxs0E8lmWj0BT7QwqCkPEaw8Sb6LxGLstD6djiz2MxWDTZ+ACiwFhAXWBMjFwQt8xcRoUoubRVygdqxx4ydvd5++ANecGBk/UD1wMy3gYiAfjC6Qsbaqn7kK5vADJX4qux8FAbEE6n0BT/Zvna4B2LsKJADEV4nsf111+foGAkzJ07F2+99xbah9thNVpTPGWMRiPuv/9+3H///XAH3WhztsFsMEsWy5Fi8tTJeOadZ2DkjTS1GIimwr/yyit04V5prUwwxV6yZAlcgeguI0k3f+211xKOPW3aNHzyyScJj5FBlAzaoXBiyrkahSbZfel2d0sa1ZNJo9bJrVR6ajb+fXpSa6vFluEtaRWaFZYKAIAAAUP+IVTbqjM6nzjwVWevo8VVej29BSuOJJUWpbTYIhS6yjlJvxoJjiAYDsJkyC6NKhlxGps44EgUmmKFHKn2yYGj1wpNo5ZRHVJPJ4UJtpwhPAlG2Yw2zd//nJo5+K73O6rezkahKQ6KqZ20SmE32TGpfBI2DG3Ayr6VmN86X/Mx5JDaac4UI29Eta0afd4+9Hh6FD+z+H5ODuBlA+l/lVLOlRSaUv2xEkrKFvIZ1Xo6SvlnAvGJ8nBgGE6/M+X7dAVceHPjmwCA06afpngOLUFIT9BDKxRLpRlq9ePMFLUKTXEgQBAETb7ias9BqpkGI0H0eHpSij0FwoG4XYzodzTwBjSXNtNCO3qP7ckB52yOnxywyOZYYo+3UnOp6nFIyac6G4UmEP187SPt6PX2qlYBSaVfZqqYk6KltAXf9X6n2r6B9E8WgyUlGJscfNWScg5Ex6/hwDB6vD20QjYgyrLQqNCU62uy2fSdWTUTPMdrHqelFPihSAhr+tcAiCs/s0F832ej0BRvzHhDXgiIrmO0FB4lzKmZgxW9K7CqfxUWTF6Q8jyZb0mtX4h6GIj+plpFFuR6DAthuINuTb+3XLtIKnyvtxcDvoFRXYRF7dhTbilHuaWcvr6hpEFV4cJMsRvtMHJGhITouizdHE2LgrultAXLty9XnIdkOmdOTmlPfr876KZBcLUemsnjkNQmq3g+pHX+wVCGKTQZWUG8VtINXiQYSNSOaqBFfWSqiSZ7XSa8V1ThXCskCBmKhBARIvHPqMJDs9ZWC6vBirAQRrerO+V5knKudXIrFfzQuhOeK8RKM6VFhJE30sez2S1NDnxpTf/MBWQxIFY3iBdbcjvO2agP9KDMUkbvkVzsYMsZ+ksp5Mj5KywV9J4nadRtzjZ6LDFKyrd03oTkeqm11WqeVCQrNDLxj9NboSlul95p53oWBQJk+ow0RYH07OdoynnInXBvhiNh9PmiwTklhYnYQ04NSoVBtCoG6YIgScVmN9lRY6sBIO1X+damt+AJeTCxfCL2HLen4jmaHer8q4B4oJIspJIRp5Tm0hZEbQCLXFOhSCglXVbtOdKpQI28EU2lUVWMVCCX/IYGzpCiiBMvnnLloUnIxntbHPA3csas7CjE7dJynyttGmbr+6u2jxJDVY9SHppZppwD2gtKkPlinb0uZYxL/u6k5jBKSI1fnqAH3pAXgPrfkfQ1ZCMmmWw2fe0me4LQQm2bpD7bxqGN8IV9cJgcWVU4l2pLJsXupMYNMp/iOT6jzb90PtxKwXnxZ9DqnwlEVb+k2J7WwkBUOaqQCp+rLKR8oSVLhvg0ArlNNweiQWMtdgG0OJeKa16NmjHTOXO6lHYyh6qwVKQ9tpTVSCAcoH2h+P1NpU3gwMEVdO0Q3q7FBAtoMrJCbeCQBChIgLC9vR0Oh0P2r729Pe2xaZBU0DegSdoqQKDVlTlwqo7FcZxi6l+m6SBk8SAO2mn1KsoVYi/AdGleanwN0yFOtTfwBs1qqVwgla5FBvmwEKYePynvIxXAC1TlnOd4qobMxeAqp64gn1eskJO6nqtt1WgsaYQAAav7V6ccX00KlNy1RtLJtBQEIiQHNPWqcp5t4FBcgV1PlKwkMoFMJLvd3fQekJqol1vK6WaZXhXOgfj1EhEiCWlS/b5+RIQIeI5PUJwkk2lRID0WXEoKKDm1kyAIeH7d8wCi6sx0AXy7yU771XTKSjLxFy+ixFAlRDB9cDQb1KYYWwwWql7SOg5pUSorpe2T31DKLiYhuKdzsb96e31C1kg2c4cycxkNQFRYK7JSmiQEcTXc52o8NDPts8Q+imrtDJQUmoVIOaf+mbbUzZlkdavWuQg5ZsIme+y6NvNm1QpBcV+TvBETjsTnTplu+or9LtVe76R/F382km5OrF2yRXydZ7JZJ1VkUzzOZHI/ku9q7cBaarklRs6rUtweIPMgmlRRLTWosXTZUVLO1fRn4u8/k+CyVqQCelJEhAgVpKi55sXWLXJkk9WkNEaTOZQaL1gphSZpFwcuYV1oMVjo3J+lnesLC2gysoKoF9MGNEXPhyNhNDY24rvvvpP9a2xsTBuUJIFHKY+qdOpOJXiOp+pPX8hHj6N2gqA06VRK2VCCTrBEnj5aq0nmigQlQxpVhJTvj1boDl9soqLVzy4XSC0GrAbRjrPMQp6oIvQKFGVCLid8VPWRpK4g17845VwuQE/Su6RUh0op5+RaG/INSSrD5IolqKG1tDVhkpJNlfMB3wBdPGSrKhIrNPVUw+VKoblxaCN9TOoeEAfcq2z69XM2ow0cov25+Bok10SNtUZx7JCrgiuHGiWx2uCaUr8vN/Ys374cG4Y2wGa04bjJx6k6Dw2OplGDUZ8pGeN8q9Galwm8lhTjTH00tZxDyaOL/oYS13RCQFPHax6IzmOIn5paP0E5xD6T2c5BcqHQzGahC2Sn0BSP9zQgp8OmpRrfNzFkA1zKPiO5kIXWbBGpzBiaNWSr0hRQk9uIEWdwZGrLI958VHttke+r39dPM8CIalGPdHMg8d7OykNTNG+jnuIZBs9by1pRaiqFP+xPGJsJSpZZ4s+gtSAQQWvFbNouMg/UIQOiWNEy9ojHYrGdR65QG4h2+p00ZlBhrUh7XDXWN9lYiyit1cljagLCVKEqum7FitrkDRBWGCg3sIAmIytI4DDdjiXHcfEApBCG0WjElClTZP+MRmP6lHOFNPZsFJoAJAOaalHqJJWUOkpILaCTA3uFgk5s3dvTBj70mFwkB76k1Kv5RmoxwHGcrLcKEFVN0RSeAqWcA7md8KVLOScWDIC8N6BSGpSS+oUcJySEJBe8arwS5RBXYBd7fmqh0loJI2+EAAH93uhnV1t8Qo5pldNg4k1w+p2qfdbUkG2gNRnSZ6wfXA8gutgnfW4y5HfUU6HJcZxkUJ1WvU+j2hUXjVATOFZznar10FQT0EwOQj637jkAwDGTjlGdUqpWDaZU4TylXTksDERVxCpS8rR+55mcQ+n7o7+hhAIzU7WiWsjx9Zg3kPsg22PV2evo5p+WYymNr1krNEUBO7rxqFKhKR5vyBioS8p57Lfr8fTQuakSSgXOSHDWH/bDF/LFlfIqvy/FOanG61buXiFtshqsGft7iwOQaq+tKmsVDJwBESFCx2Yy/9CjwjmQ+B1l5KEpke2Urb0Bz/GYVTMLQLyiuxglhaZ4PMpUoamkuFZCKeU8nfXQaEHLHEz8/ec65RxQH4gm12qZuSylvoQU4gJHUn7nQHb9PAksSs1LyBxKzfcnrvROUFLUim14GPrBigLlkVz6R+Uad9ANb8gbTTMSGQxr8Zc08tEgpVofTbUKTZLGLg6qZhvQNPEm+OCj6YhGzqj696OmvxKdFemUtQawxJNHYiRMd8N1TkvTCmnbJucmakgum3Iem7h9vvXzhABGjbUGB7UcpGpXP3lBL6Ve1UqPpwefdH6CCCIJj8+uno1Z1bPSvl/Of6rMXIZeb69kQM0b8tLrtFAp50BmE74vu7/EpIpJ1LNPDrIgSf5eaEAzkKrQTAloVssHNOn9JPH9mQ1mlJhKqLl38kRQKR1PDXNq5mBp91KUW8ozVoLX2eqw1b0V2z3bMa5kXNaBQ5PBhOmV07GyfyVW9q+UVc1JIQgCvuj+ArOrZyecPxgJ0oWSHkWBgHifsWFoQ/S4Cp+X9Bl6K9HJtSEV0Eyn2iXt94a8GAmOpJ1MK12nmVY5l1oEk7Hn+77v8eKPLwKIbvgt2rIIAHD69NNVnQNQH4RUUwm0tbQVy7cvx4dbPkyw36iyVmF+y3xNKZyeoAdfb/8a+zbuS8eQcCRM+2A116jSd77JuQnBcDChECFBy4aDUkBTzW8I5Cb7orWsFejS59hUoZnlHITneLSUtmCjc6OmdikFQLJVlYtV5GRek41CU4+U8wpLBRwmB1xBFzpHOhOK8UihtEFTYiqBgTMgLITh9Dvjm48aigIB0U0p0tf80BsNgmm9tuQ2YvTwGJ9WEd3kC0aCqq9TnuNRY6vBds929Hh6UGGtoJtvc2vmZtwWMeLvKCOFZkzh6Ql54Av5YDVadbEwmlM9B8u6l2FV3yosnLYw4TlFD01RX5apQjNZNSzGG/Lii61fYO+GvRPuJUEQlFPhSeA3A0ulz7s+R5e7K+Exi8GCQ1sP1XQ/R4QIPmr/KCUzzWFy4LDxh8lu5orRMvaIv/9MfwstyBVnW9m3EmsG1tB/k7FQ7fUuLnDUMdIhPSartAORgvQ7Upv/5DE1Clep61ZJ1Z9NpfOvtn2FtuE2yWPu3bC35uPtSLCAZh4wmaI7ER6PBzabPlVa802PpweeoAdGzpgQ0NQSODRyRvjhp+9JR9qAJmcABw4CBIQiocR2RbILaCYrNI28ER5PdNAkv6ccahSamVY594a8cAVdKDWXaq4mmSvIxJZ05jajTbaqHvkcSzqWYEnHkoTnHjnsEezbuG/a85HPTQZFremfUly15Cp83/t9yuM2ow1LTl2S9veSm0gqKUjIZN3AGXSr3pwJWgMq3/V8h/PePw+zqmfhuWOeUwxCy1VOFRdlIcgt8klAudvdjUHfYMLz5P1yioQqaxXcQTf6vH2YWD4x4Tm62CvR7qEJxBc26YK6StTaa7HVvZW2RW1qoxKza2ZjZf9KrO5fjaMmHqX6fR93fozLFl+GoyYehbsOuIs+Lt51VqvuS0dyn6E0SSffbzbfsxQ0qJ6BQtNmtKHMXIbhwDC6Xd0oq1KeTKuxRvCEPHAH3WnVNUrBsPHl4wEAm52b8acv/pTw3K51u0ouCOQgE/ktw1sUX0eeV1o4jS+LtuvD9g/xYfuHCc89dPBDOLDlQNXtemLlE3jk+0dwwdwLcPm8ywEkpqaqWdjI9XnBcBDnvnsufCEfPlj4Qcp1qSWNmaYHD7enbLgq/YZNjiZaNbbaJu/jminkt9DjfmooiVZvr7Fnf6zxZeOx0blRU7vkAiDhSJj6N2er0BTPa9KpBJNTL8ORMC0MocemJcdxaCltwZqBNegY6Ugb0Ox2RwtTSmUhcByHMnMZBv2DcAacmquJk9++09WZ0tdovbbk+hqtldelMBlMmFk9E9/3fq/pOq2310cDmt4eRAYiCAkhVFmrdKuUXWGtyOo+LzWVwsgbEYqEMOgbRIOjQRe/VpIRI+VZrnR8Mrc38kaMc2T2HckFxgDgmTXP4IFvHsAlu1yCi3e+mD7uDXmpsEZyfI0FfrWuD1b3r8ZFH14k+dz307/HH/b+g+pjLelYgiuXXCn53DW7XYNz5pyT9hiaxp7Y/cSBy4+HpkQ/3OvpxdnvnI1AJJDyei39Q2tpK37w/4DOkU7J+Us2KedyFh7BSBDrh9YnvEaJ5AKwHMcptoscc83AGk2VztcNrMN5751HN9jEHDXxKBbQLHQDxgIGgwEVFRXo6Yl2qHa7PSsD9UJgDBsRCUYw7B6GFXHfpYA/gEgwglAgBB+nnAIjhAREghF4vB5YBEvac/p9fkSCEYSDYfh80sc2RAwIhAMYdg8nTMSC/iAiodh707RLsq3BaFsjiAAC4Pf7MTI8goqKChgMykFSoorqGOlIWchkmnJuN9lRairFSHAEPZ6eaECzSKqcJyvclBYQJ049EZ2uzoSK1euH1qNjpAPLty9XFdAc8Ep7aGYa0FzZtxLf934PI2/EAU0H0MeXbVsGd9CN1f2rsfu43RWPIavQlPBWSX6Pw+woaH+g1UOTTHRX96/Gd73fYde6XWVfK6fQlPTQJAH6pHQ1h9lBFxftI+0JQQAlTycAmFwxGR0jHVjTvwZ7jNsj4TkavLJlFtDcv3l/nDXrrKwmEcnXbra+bwAwqXwSAPWVcAlEAbuse1nCJIu0qdRUmpESVYpkBaRSEOoXc36BMnMZjpl0jC7nJpA+WCqgqcaGYErFFHzT8w3WDKxJGyhUWgiWmktRZ69Dj6cHawfWYrf63RSPpZRyPqtqFs6fez42DW1KeNxkMOG8OecpHjeZ6ZXRz7RuYB1CkZCkimTAN4Bt7m0AgKmVU2WPdfyU49E23JYQHF83uA5dri6sHVirKaBJ+p+XfnwJF+18ESwGC1082I12Valscqr0H4d+pI+1OduwU+1O9DlBEDRtOLSWtcJqsMIT8qBtuI3el+LzSv2GJoMJN+xzAwZ8A7oFT8QcPfFobBzaiOMnH5/1sU6dfio8IY8m5a8cF+58IWrttZo2YeQCIGRsBTJT7gCpfZSaPpm8ZiQ4klDQBtAn5RxAQkBTiXAkjHWD6wDI35vllnIM+gfR4+mhmVNqN61mVM3ABXMvSPFatBgtOHv22aqOQaB9zWBiXyNVbDETrt7tarzX9h7mt8xX/R5x4TfSx82pmaPbXM3Em3D93tdjJDCS0eYCx3GotFSi19uLAf8AGhwNGRcdFUPnDyPtKcEWpZT2BkcDLtv1MtTaalX1wVIoeTGuHVgLIDoeiSFtkqvsPqViCn2/luDR8u3LAQDjSsZhVlV0U90f9uOzrZ/hjY1v4Ip5V6i+Lkmbmx3NmFY5DQAw5B/CNz3f4Ll1z+GsWWelnVtpGXtqbDW4dvdrYTFYdOt3lJDqh19a/xICkUDC9wdEMyvPnHGm6mM3lzbjh74fZPs7LYX6pI4NxFPayfzso/aPMOAbQLW1mlpLKUGu27AQhjvohsPsUEyF36thL1gMFmwY2oAVvSuwS90uqtr7/LrnIUDA+LLxmFw+OeE5Ne3c0WEBzTwxblx0YkqCmqMNb8iLQd8ghgxDcNviC8A+bx8C4QCC1iAGjcoKL6ffCXfQDY/ZgyHzUNpzqjn2kH8InqAHHrMnoePo9fQiGAkibA3DYkwfPE3GE/TQamwCBJSYSjChfgL9HZVoKGmAkTMiEAmgx9OTsCjJxuOmzl6HEWc0oDm5YrKs52C+MRvMqLRU0oCU0sR/XMk43PqTWxMee27tc7h12a2qKzMnB75IUGjAN4BgOKjZa4lU/z1iwhG4Y/876ONXLL4CizsWY1X/qrQBTbnAnVJKHH1Phmb3ekHSsNQGNMUTi2fXPqsY0JRTWIjVcWSSSbyqpK7n1rLWaEBzuB071+5MH09XcGFuzVws6ViSkq4uCIJqNZ4cJt6E3+zxm4zeS0gOaGbr+wYo+wIpQV5PglQNjobENmUYGJAiOWCoNBmdUTVDkxpCLVIKTWJboaZQ1Nyaufim5xus7FuJE6acoPjadNfpnOo5WOxZjJV9K7MKaHIchyvmXZG27WqYUD6BpuVvHNooGbQl99WEsgmKi7saWw1u2e+WhMceWfEIHvruIc3XKel/Bv2DeL/tfSyYvECzSkMuoCkeg9pH2hMCmu6gm2aNqLkXjLwRM6pm4Lve77Cqb5XqgCYAnDT1JFWfIxPKLeW63U/Npc26HWt29WzNizK5okBkA7HEVJJxcMVisKDCUkHngWoWzOJ7YCQwErcs4o2yWStaUdu/b3Jugjfkjc5dyyZIvoZcx10j0bRanuNVVyfnOI4qpLNF3Ndscm6iQR89UqgBYLf63dL2q8mIi03SgKZO/pmEU6adktX7K63RgCYRNyhlAqilqbQJHDhq1SNWjyqlnAPAhTtdmPF5AdF8WUIAQDZok697ullolBYKzaiaAQNnQJ+3j1r7qIGMbSdPPRm/3PmXAKLzxhNfPxEbnRvxxsY38NOZP1V1LNLmk6edjPPnng8guqY+9MVD0eXqwmdbP8MBzQfIvj8iRDSnVmvdVMgGKtyIjcPBSBAvrXsJAHDVvKtw9KSjMz62kvVNIBygCvhM5qdyKe1kTXjytJNVrSetxmgB2EAkgOFAVFyl9HuVW8px9MSj8eqGV/H8uudVBTRHAiN4a9NbAIAb97kxRaDBYAHNvMFxHBoaGlBXV4dgMFjo5mim29WN333wOxh5I54/9nl6k9+3+D60Odtw8743Y1a9stfgs2uexbMbnsXhEw7HpdMvTXvOexffiy3OLbh5v5sxq0762O9sfgd/X/N37FK7C/70k3jay5/e/RP6vf2456B7MLFyouR7lVi+fTnu/PxOAEAEEVy060XYp2EfVe818kY0OhrRPtKOjpEOXQOaG50b0ePpQTASpMGiQqecA9EAAAk0ag3GkNRdUpk53Q5qcoXYCksFTb3p9fai0dGo+txDviG8s/kdAKn+cnNr52Jxx2JJ78Zk5PynlKqwyqk68w35HtWmnIsDmh9s+QB93j5ZhYHcZyTfU0SIwBf2wWa0pVgJiGkpbcFX275K8bpJdz9R/82kCunDgWGaCpNpQFMPxIumbCdnBLEvkBZFgvi7Xdm/kgY01aSFa6XMXEYngIC+wVK1ZJNyDsRT89RsxKQrDDKnZo6qvkYQBMV0ZT3hOR6zq2fjy21fYlX/KsmAJvns4krCaiGBGS3Fq8KRMDpd8dc/t+45LJi8QPM1KpdyLv7+kxUh5Bxm3gyrQV118Dk1c/Bd73dY2bcSCyYvoI/n6zfc0SG/97B/OFFVnmVxNUKtvZYGNNX0USbeRANzzoCTqh71VEkp+b6JIdfyrOpZsuov8v0Qn0CHqTDZIjzHY1b1LHy17Sus6ltFA5qFnCOJi0KR+YNeFc71IrmgY7ZFgYBoIL++pB7b3NvQMdIhGdDUww9WCjmFpiAI9HpPntcQ2yG5NtmMNkypmIJ1g+uwqm+V6oDmqv7o2Cb2TOU4DqfNOA23LbsNz697HmfOOFPV/SJVOM9mtOGEKSfgydVP4rm1zykGNN1BN02r13Mephe0H46NkUs6lqDH24MqaxUOHX9oVsemNSkkFJrkfDzHZ7zp0eJooUU0p1dNx6ahTfhy25fgOT7FQ1aJcks5er29cPqdaHQ0pt1kPW3GaXh1w6t4r+09/HqPX6cVJr2x8Q14Q15MqZiC3euVBTZjFVblPM8YDAZYrdZR9zehegI8nAcdvg60+9rp41s8W9Ad6EaJvSTtMWw2G7oD3ejwdqg65yb3JnQHulFWUib7mul109Ed6MZnvZ/BYrHQxze6N6I70I0KR0VGn7e2rBbdgW50B7qxPbAdlTZ9qjZmM+EQF78Z8g0BiHbkelUezgZxAEBrexIqM7vSL26TiyGR4iqA9rTz1ze+Dn/YjxlVMxKUf0Bcwq8moCnnPyVV/Y5A1QcFrHAOaDdNJzulNqMNoUgIr65/Vfa1cspVm9EGDrEJaeyeUFrky+3SkuPLqUrIAqRjpCNBJbvdsx1ANBiul3ImE4hdQ4+nh07OOHBZLeAaSxph4AzwhX2aCmWJ+yrxNZ+NR5EcHMcl9hk6FRvSgmJAU4UNAbm21g2uQyCc6hMlJl1hEHKsdH2NJ+ShQeBcVMDW2i6y0M8koJmJMf42z7ZoSipnhJE34vve77G6f7Xma1SuzxNvfCQX9ROfQ23Qh3wvyRsqcvYaDG2Q3zskhBLSu7MtrkbIpI8Sp1+mU7RlgtpiXSQgo6QqJN8PUWgWcnOV3iuivkZu/pAPyG+/2bkZm52bAWTWz+WSZLsgpeI4WpAKIgmCkLFlllrkqmUP+YfoHNsb8tLsNCBeWFLpHpPrh+UYDgxTP9dk1fiCSQtgN9qx2bkZX237StXxpAKaAHDa9NMAAJ92fao4DpKxx2qwwmpUt5mWT5JrBTy/NqZwnHpy1vNrpXmCOKNJS2FBpeM/t+45AMBBzQdpsnxJvnbpGCQzbsyuno25NXMRjATxyvpXFI8tCAJVjZ42/bRRZ1mYL1hAk6EKjuNoxy5WpGgxEqe7iSoDJ7RKpcJEcmrlVJh5M4YDw7RDSlA6ZbiblZwSqVVJQbw5xJ1wKBKiKUiZTDhIm7a7t9MJTIWlIuOOXE/E35fWRQSpzAyoUzuRzy7+TTLx0YwIEcVBgizmO12dNIAsB1USJKWPqykKVMgK54C2KucRIUIXP+fOORcA8MKPL9AiXMnIKVc5jqPBHU/Qg1AkRL8jpYBm8qQmnWdUuaWcvld8bfV6ooG+Qqozgfh90+Ptof1dqbk0q3vaZDDRiZjaYNFwYJgqkYDE70oPX08pstkE0YNkH1dfyEc/q5pCUc2OZlRYKhCMBPHj4I+Kr023kUXG1nR9DblHbUZbzlQyYqjCWSKgKQgCfTybgGavt5fex+kg13NzaTMOG38YAOCFdS9oDmARVbq4z/MEPQl+gMn3DjmHljkF+V7W9q9FMBLPzEnOMmBkhtVohcUQtRQSj7F6FFcDEjc21F5b4gIZdMNNx3uV3Dfdru6EayqZH/qiFceVVIXk++lyxRWahYL0NaTdQGHnSGR8Iu1pLGksuL1TMslzNz0UmoD0fMsfjhd0zZUvo5xFU3JfLPYHV/OZ1W4YEsj8p9nRjAprRcJzDrODqu1J8EsJkroPpAY0W8tasV/jfhAg4MUfX5Q9RiZjTz4RZ6JtGtqEZduWaVY4ykEyObrd3QiGE/s7PSyaSM2L9pF2eIIevLHxDQBRBaUWxNkCgLrq6ySg/eK6F2XXUEC0svlm52bYjXYcO+lYTe0aSxQ+EsIYNSQr1iJCJG7arcIHUEs1ZX/YT4N/ShNJE2/CjKoZCe3SQ+lEUiKT264WcYVTQrYG8WKFZjoPrnwj9pzLZBGhdsIRjoQlA1/i70YtX2z9Ah0jHXCYHDh6YqrHS5m5jFaETbezSwN3SYH95FQMMcWSck6+x5HASMqEIZkeTw8CkQCMnBFnzzoblZZKbHNvw8edH0u+Xukzkl1+V9CFIf8QrdxXYalIeW06xbPi7rxE2jkJfKvxSswl4sIDeqmKAJGKR2VhIPK9EtXsqv5VNMVJj0mjFIUOaJJrhlxD5JqwGqyqxjPxJp9SvxWMBOEP+xPOmUy5pZyOGURZJQXdzMmTso8E5NYPrqefgbDNvQ0DvgEYOSMdg7VQbimn15QaZT6QqHQhFiFvb3qbpiOqvUbFvsGCEO131g6sRUSI0HsgJeXcrz2w31railJzKQKRANYPRqumBsNxuxjSDkbmSBWk0Mv3V9xHqT2WuD10w01HRVudvQ5m3oyQEMI21zbJ1wTCAbrJorTZQD00SUCzgNkiUn2NuHBivklW6RdbujkgUprrmHIOxAUZYhWwOJMh5ynnSfPl5L5Y/O90KedAfA4ontcoQdXNMvfOqdNPBQAsbl+M7e7tisciba20VErOg0lQ69X1r6aMsYRc+JjribjPe+HHFwAABzYfSG2LsqHaWg2b0RYVU8T6KYIem+3itcVbm96CO+jG+LLxmot9JheAVSPIOmLCESi3lGOreys+7fpU9nUkcL5g8oKCZ/QVMyygyVAN6dzJjqUn6KFBCC0KTTVKMNIZ8ByfdnCmwbBYwELc+WeqdEpOiay2Viu8OhWpAAyZ3Jp4U0YyfLEKsdg8uDKZ+ItJvrbkIIEvDlxC4IuqVz3Kkwsxz62NDhLHTzlePhVURcAiIkToZC95wqKk0NTL8D5byi3l9D5Jp54mAbKm0ibYTXacOPVEAHET7WSUPmOJOZ7yS65n4oeaDLmfBnwDCRNrNZ5OUsFyLdWscwk5vzvoRrerG4A+6ddKvkNSkPTaOTVzYDVY4Qq6aMpVLlLOgaQ+owDKg+SUc7F/ptqUHjUbMWL1odbrNJl89/sNJQ2oslYhJIRolVkC6aunVk6lKjmt0HFyWNt12lrWil3rdsW0ymnwhX3U9kLt2EO+v1AkRPso8nlIAbh+X39CX0NVMhrGN6mgN+ljDZyhaBeoowmxIpKgl+9vJn2UuEAGDTCZ9Qto8hyf1q5h3UC0WnilpRKNJfKe4mSsIer8QhYoFPc1pCp0MaScE8ReisVCsv+5XgFNqfkDGcfsRnvOssKkNieAVHsF8b9Ju5Tm0VMqp8BisGAkMKJqkzdd5sG0ymmYVzcPYSGMl9e/rHgscr5kdSbhgOYD0FDSgCH/EN5re0/yNbnKktEL0ue5gi68vuF1AKk1CTKF4zjZ/k6PQK/4WifrmFOnnar5Gk++dtXMm61GK06cEl1Dyal9t7u3Y3H74mi7YoF0hjQsoMlQDencNzk3wRP00MmGkTeqMskni4jhwLBiqgygzRsj2XuHdv7ZphvFJjQGzqB5QkVk8h0jHVQBkq4wRNr2iHwii82DS7ybnckiguygrhlYoyi9JxO3ckt5QuCLKjQ96hSaXa4uqiokO6SS7VJR+MMddNPAvmxAU6JqY7EoNHmOp8HhdOppcconACycthAcOHy+9XMaACMIgqCosCCqFU/QkzZQU2oupdd6wu68igm81G9IFZq2wio07SY7nYhvGNoAQF+FptqCK+Q7nVg+UVbxrrfPZaEVmskp55lUvRcrP+QgxzfzZsWKy+LiaHLkO6CppELVo1CG5sC7SKHJcRztu4n1jdpr1Gq0wma0AYh/p6R/2KdhH9ofiu+fTNOYaf8Tu0bEY1gx2MWMdqTSVPXahMmkjxKrzHLlOZguoCm+N5U2Z5I/UyHVP1J9jZxlTT4oMZXQPgIoPv9MQKQ09yelnGd5vUnNH/SooJ4OEpjyhrwJvtSkHaRfFl/3atpl4k20qJ0aH01q11AtP7adPiMasHvpx5cU17N0zCqTDmgaeANNzSbek8moUfsVEvGazxV0obW0FXs3alM4KpEuoJnN90KO3eXqwo+DP8JqsOL4KcdrPk5yQSu1NgGnTjsVHDh81vWZ5Mbuy+tfRlgIY17dPFosjSENm00xVFNnr0OdrQ4RIYI1A2sSfAPVKFrKzfEJfDpPQi3plzQY1r8mwYtPr935THwqmxxNAOLptEA8NSLjgGasPX3ePvR5+wAUT8p5tsGJieUTYTPa4A15scm5SfZ1Uv6Z4vOr9dB86ceXIEDAXg17YWL5RNnXJVdgl4JMuk28KUWpJOcJBBRWfZCMWvU02RkngYjm0mbs37w/gKiXnRhvyEs9l6TuRbFCjkzIlQL01OtGo3/SzKqZ4DkePd4emh6USfAqV5BgPElJ1UOtKPYFUoM4UJ0cgNnhFZqxfpnYVWixIUje5JNCrWpGvDEn19cUwmpEblOHVjhXKDqSDimvaSXI9UwWIcdOOjbhe9VyjSb3eeIgkFThFVo5W6MaJNmHtNjsYkY7UpuGeimaMikKJB7z9VLMJSOVEixGrbdt8vdT6LlI8thDNioK0S6O42gGBQcOs6pn5b0N6aBFgbyJAc1sU8LFGTFkfpura1lMqbmUWn6IFddkzrdPwz4AEgOt9DPLFIYk0M3HND79vZ5e9Hh6wHO84m9+aOuhqLZWo9fbSxV0UsgVBBJz0tSTokXu+r6X3Bwt9pRzI29M2HQ4bfppum7WyQY0dfAWrbHVJGxcHD3p6IzGDbG9WESI0PhIumO1lLVgv6aojypJ1ycEI0G89ONLAIAzZpyhuU1jDRbQZGhCnBantUqzgTfQHbbkwElEiMAX8tG/fm+0ip2ajmpC+QSUmErgC/uwcWijbgtwsrDNRA1jNVrpZIh0wtlOCKpt1eA5HmEhTNVcxbIoEgcBMhlcDLyBTh6UUi7lAl9aqpwHwgFaVS5dWsT0qukwcAb0eftk09nJxEtq0k2uQW/Im+JPWUj1QTLJ1TLlkJqcke/w1Q2v0mJcQDxga+AMCRMGArkPXEEXnZArXc/Jk5pAOEB3xpXuKbvJjknlkwDEgxY93uJIOQfii+b1Q7GApg6TVq0VpMWB6uTU51wZ0ovVsYX00CSBSHJ/a7kmau21qLNHN/lW96+WfI3afn9G1Yy0fU0hA5piZYv482ajXCKZDGoC74IgpPQ/dpMdx00+jr5GyzUqDmg6/U567NnVsyXvn0yVyuR+2ji0Ed6QlwU0dYb85gPeATp/JCpYXVPO1XpoSik0dQ4CiTOApFC72ZD8/RR6LpJsPUQ9+gsUaCXz2onlE3MayMsUWpfAn5hynu3v6DA7aP9ErjG9KqgrwXM8/a3JBpK4Dfs27QtAOuVcy4ahEuT5SeWTFAPDJoMJJ087GYC85ZK47UQEIEW1rRqHjz8cQKowAMhdloyekL4kU4WjEnLz2Ux8rZPhOI5uEAHKGXtKiO3FXEEX9WpVM26I11BOv5OOYx+0fYBeby+qrdU4pPWQjNo1lmABTYYmiGJtVd+qjCoQUhNrkVefO+jGca8dhz2e2YP+XfPxNQDUdQbinbRV/atUVRdTA1nYavXPJCSrPLKd3Bp5I20L8RgqFg/NKmsVjFw0BTzTwUVN+iZZqFTbEn8TLQrND7Z8gAHfAOrsdTio5SDF19qMNkypmBJtl8zOrpJPpMPkoDvOyWnnhTS8T4ZMXtWmnIsDmvs17YcmRxNGAiN4d/O79HGxxYKUgpvcB56gh/YHWgKaYn87tZNZ8hsWS1EgIB6MJ4bnegT3mh3RCdpwYFhSHZyM+Hcl9+HagWhl5kyVaekQBw4LodAkixVy/xK7Cq02BOn6LbX9vs1ow+SKydFjyfQ1hfBOJvfOZudm2me1DbfBFXTBarDSNmeClsB7v68f3pAXPMfTDAggcQGi5d4RFykk33draSvKLeWSRbUy3Sitt9ejxlaDsBDG2oG1Red/Pdohv8dD3z1E54+fdH2S8FymVFmrYOAM0WOpDCaIvdRyFdAk12fbcFvKc+6gm2a5pLODSO7TC63QJCm+bc42uAKuglY5B+LzymJMNwfi8yV30I1AOKDr9ZasAs7WMkstyYprd9CNfl9U4LJvYzSg6fQ7aX+sVlhD7oW1A2sRioRkX0eV+grp5oSF0xaC53h8te0r2cwyNQpNIJ7C/t9N/6XXPSFXWTJ6Qtp21MSjdG+nXH+nVyHNFkf0+DvV7JSxElt83ZLfy2a0qfIX/0nTT9BY0gin34mfPPcTOo799pPfAgBOnnYyTAZ5uyJGFBbQZGhCXIAnEw/A5BQJAHhj4xsp/ntANFC5f9P+qo4r3n3Tw1cDAPZq2AulplKaUqsVuQBMNukgZILV7Y4WECmWRRHP8ZjfOh/NjmbFFG4l5tSm30Gli8FkhWbse/GEPHTiJQcpBrRw2kLJAjQp7UpTsEhJRWDgDZI7zoAonaqARvwE8n0qKTTFCinxbjPP8TSo8OzaZ2m6bLp0MephGHKrWuQn++2R+8lisKT9Hal1QN9KhCIhqgAvhpTz5DboEdyzm+w0MJcuWOQL+WiAt7W0Fa1lrSg1lcIf9mPj0MacGdI3OBowo2oGdq/fXVLBm2vEAXVAZENQou2amFsbv7ak0LLIlFJDilFjzaA3VdYqWliEqDJJAHBG1QxVfagcZIzsdnenKNiTIdfxOPu4hKJ6kysm4/jJx6PJ0YSZ1TNVn1u8uZrsB0oUcAkemhkqlTmOS0g7z3el+h2dvRv2hplPLbJYYanIupALz/E4uPVgtJS2YEL5BFXvERcpylVAc2bVTBg5IzY7N9PNbcLq/tUQIKChpAE1thrF4yTPkQu9uVptq0ZDSQMECFjdv1pzFpje7N+0P+xGO46YcERBzp+OMnMZFRIM+AbihXt0qEKeMt9SUU1cD5JtmsT+mXX2OnpNk8fVppxPKJsAh8lBM/nkIGObmr5jXMk47DluTwDAV91fpTwfCAewzb0NABJUgFLsUrsLmh3N8IV9+L73+4Tn9LJRyyXzW+ejzlaHc+aco/uxyTxjy/AWrOlfQx/XQ6EJAIdPOByl5lJcssslGR+Dppz7hxWz9qQw8AZcuNOFkmn61dbqjFWjY43MZ6KMMQnZteoY6cBW11YA2nZPqRIspsgSBIEaIV+7+7XUHBmITiatxvTFhoBEn6qda3cGkL2iaEbVDHx6xqcZe4HQtKDhxABMNrvNtfZaoD/+72JKW7v3oHsRESIZf1/kN1w3uA6BcECyErychyYpruIKutDj7ZGdAK8dWIvver+DkTPi5Kknq2rX7JrZeHn9y7JBBhK4kztnmbkMw4HhBE8gQJRyXkwKTYUq54P+QbiDbnDg0FTalPDcCVNOwEPfPoQ1A2uwsm8l5tbOTauuoCnnAZfs7ypGboNAzWKRBCpW9a9Cn7cPAgQYOWNR3D/JKlG9AoctpS3o9faifbhdUWFCFgalplKUW8rBcRxm1czCsu5l+L73+5xNpo28ES8cG02vUltVXE/IdUmuI5LmLS5wpga5ojkETddp9Wy8sv4V2WPJKdRzzeya2djq3oqVfSuxV8Neqj360lFrq4XVYIUv7MNW91aMLxsv+1olpcst+92i+RoiFYIHfAP0HiBjkGTKeRaLpzk1c7CkcwlW9q2kAQFyfkZ27N+8P74484sU1ZXZYM4q2E7QOq8RKzRJ0FrvgGa1rRoHtx6M97e8j+fXPY8/7vNH+pyWezNFoVkEm6tzauag292NFb0rqIVNodp1zKRjcNTEo4q2eBfHcaiwVqDP24dt7m0ICdF7QA9Fa3IfqKaauB6ILRvE5ycB1pbSFvR5+9Ax0oHZNbNVp5zzHI/Z1bOxbNsy/ND3Ay0SJEYQBDrPVzu2za2Zi6XdS7GyfyVOQ2LgqdPVCQEC7EZ72kw/juMwt3YuOl2dWNm3Evs17Uef00uJmEsu3vli/HKnX+ZkLldprcRh4w/DO5vfwfPrnsdN+94EIH6NZDs3PWbSMThm0jFZHUNKoanl9zp52sk4dvKxKUVx9RrHxgLF2UszipZySzkdWJZ1LwOQoUIzFsD4evvX2OjcCJvRhpOmngS7yU7/1AYzgfjgs35wPS3uoIffSDYTmeSCB2oHXiWS/d2KISAjJpvvq8nRhApLBUKREH4c/FHyNUqBLzVp58Tr5pDxh6hONyaL3NV9q6kvihiq0JSZdIu9VSTfVwRFgaSU08mQ9Mv6kvqUNIpKayWOnHgkAOC5dVEFbLqALfUwDHlU+cqRCfY29zYEwgFNnk7TKqbBxJswHBjG8u3LAQA19pqiWKgk39N6+SSpTecVFwQik1FyzX+17Sta2CkXk2mO4woSzAQSPVwFQaAp51pVuyRY3unqlCx2l4lCc1X/KsnCQIVS9yUX69C66JND7F+V7jol/Y9UtdhMriFaIdg3EPccrEkMaHa7u2m13WwWleLvj/oFW4pr7B7NmA3mhLmj3WTXdRGoZZwQj/fZFoJUgqSovrXprYQUVRLQVJMya+JNCcq2YpiLkHuFrC+Awm76FsMcQQkydxP3n3qoKLPZQM4G8YYAEE95J+OEXLvUBFqT/cGT6XR1wul3wsSbVFeUVvLmJGKWltIWVWMUFeYkiSf0slHLNbmcyxGfybc3vU2/j2JKxRdft5lWpbcYLDkdx3Z0irunZhQlZFD4pucbANomQclefSTAdOykY7OaTDWUNKDKWoWQEMLX278GUPhOjgR+qQdNLH0mXWqEEsn+bsWScq4HHMelnXBQhZLEbicJUJLARDIjgRG8veltAOmLAYmZUjkFFoMFI8GRBE81Qrq0KKkqrBEhUpRVzpUUmum8gMh3+u7mdzHoG1Sfch6Mp5wrBTSrrFWwG+0QIKDT1anJ08lkMGFG1QwAwEcdHwHQrsTLFblUaAIqAkWkIFBZ3EaApFt90f0FAMDMm2E1qN9gGg2Q6y8UCaHP24dAJBq40uqrWmYuo8pCKRW3loXg1MqpMPNmjARGUgrlCIJQMP9FcQZEMBKkaa56eMvRcVKibxWj1otMLeQ7XDewDj3eaFVb0kdUW6thM9ogQKDettlY2ZDg0pbhLdReZ0cauxlxEooCBXIXBNq9fndMLp8Mb8iLNze+SR8nmw5q703xeFMM2SKkryHrC5vRxhb1CpA5U6crqjK3GW26BGGT5w90/ZLrlHNLYsp5cr+fXJtAS7uSN+aSIRtb0yunq/YsJHOlTc5NVLRCoOpS0dxKVfuSPLSLKXBXKHat2xVTK6fCF/bh9Q2vAxBtMhZBsSRy3XpDXur5WswWATsiLKDJ0AyZcJAKw1omQWKFZq+nF4u2LAKQeWUxAsdxdNFQLH4jZOAd8A3AHXTrssMpVg9x4IqiI9cTcm3J+VUqLeiJ0k2uQvAbG9+AN+TFlIop2K1+N9VtMvHxYJhUwILsFsrtEIu9VQieoAcCBMX35RNxgQw50gUU5tTMwazqWQhEAnhtw2tplavkPhAHNJUW+RzH0XN3jnTGPZ1UbhCQ/uGTzmjBiGLwzwRSFZp69VtaFZri35VsLNC+1FJWMCVlrhBfN5udmwFEfbrUmLgno5R2rsV7zMSbMKN6huSxvCEv/GE/gPwr82dVzwIHDt3ubnzZ/SX8YT9KzaWKlVvVovU61eOcQLyv2TC0AUDUi5P8RuK+pmOkA8FwkKa/ZqKSqbBW0EJdG50bE87P2LEg/XcwEkSfrw9AbgKaHMfhtBnRefPz656HIAgY8A3QALza4hbi8aYYUs5JX0PWF8XQpmKGKL2JbYZe1xrp/7a7t8Mf9sczzIy5VWgme2gSlSMJCiZ7e2rJfCPri/WD6+EL+VKep+rmNMW0xNTaa1Fnr0NEiGDNwJqE55LVpemYUTUDPMej19uL7e74OoYWZhzDATKO46ho4vl1zyMcCVNlejEoV0vNpbQALLk2x3IAuhCwgCZDM8k7vxl5aPoG8dL6lxASQti1bldJP5Ns21XozqTUXEpTAztHOnXxoBEHYSqtlTDwhuwaWWTI7VASlFLOiXpVKuVcEARaDOi06adpDs4otYsE7uQmG1IKTTIQG3ljRgEUvSH3JdlZlCJdQDN5wkEDvWlSzocDwxjyDyW0Qw4yqW0fbo/fTyo3VMhvSFLVi6HCORD1QyMTIUC/fot6+GYQKCKVmWmbdrCNEyB675FiRCSgmWmQW6l/ICottf2+WA0phvR9VoM170WUHGYHLfZG+tHZ1bN1CXJrvU71Umgmq/zJ907bJVo4k76bA5fx+J08P0nnqcYYnYgVhWQukitV24JJC2Az2rDJuQlfbfuK9j8TyiaozvwoNoWmw+xIKMBUDG0qZpJTzvXaIK+yVqHEVBJVqY90xVO7c/x7yHloJis0aW0CDbYO40rGocpahbAQxtqBtSnPEyGF1swDuTFb6yac3WTHlIop0WPFxBP+sB++cDT4Wug1baE5ZtIxKDGVYMvwFnzY/iG1ACuGQC/P8bTPJdkmY/33yjcsoMnQDNlFImSSct7r7cVL614CoC39V4liC2gCiekRelY5B3bMKqnkN9zk3ES/L0I4ElYMfJHvRirl/MttX6JtuA12ox3HTjpWc7uIAktKOZrOKzJ5xxlIrHBeDMo3MikeCYxQZUQyZLdZKaBw5MQjUWYuQ5erCx9s+QCA/ASb3Afdrm6qVk13z4r99qjiWaViILl/KBaFpok3JVzPeu02k9+p19ubkgolRuyhSRBXZgaKoy/NBUSluXk4GtDMNMgtrk6e7H2p1UdPzpNLvJlTiD6DtOt/Xf9L+He2qPHQFG966J1yTkj+PHTsHm6nCplSc2nGm4jJx2cKzR0TjotnzpAFd66yMBxmBxZMWgAg6l2dibdtQkCzCLJFgMTNBRbQVIb0I0ShqVfwXKxST1i/ZGGZpQaxACAQDqDb3Q0gNaDZ4+2BL+TTlPnGcZxs2nk4EqYKy+TNrXTIbWiS30TLmJV8LDL28BxfNPdnoSgxleC4yccBAB79/lEA0Q0kqQKyhYBcu0yhWRhYQJOhGbvJjskVk+m/tXSyJAjXMdKBHm8PqqxVOHT8obq0K9kEvRg6E8kAjE4p5zvigqjGVoN6ez0ECFjdvzrhOWfASQNfFZaKlPeS1F0phSbxal0weUFGE2QyyVg7sDYl4EernMvcB1JFgYqpwjkQVeCRTQqpwiZAfHKmtNtsM9pwwpQTAIB6xclteJD7gBbxspTDxCv7FolVU1o9nSaUTUiYjCenehcScl/bjDbdFLvllnIaTCf+WskEI0F0u6ILhuTfVZx2VQwpPbmAXINtzjYAmV8TM6pmwMAZ0OftS7G80LqRRb73tQNrEyo3F8o/k7YrNr6SII3WRZ8cYhsJqaJrQHyBUG2t1m3Bnvw9JqcZkuJDYoVmNkoQ8fyE5/iimJ8wckNyf5nLQiok7Xxx+2Is6VgCQFtAk1zTBs6Qd+W3HOJ7kaWcKyMWiQD6Xmti2418FQUSWzR1ubogQIDNaKOK9nJLOZ1TbnRupGOk6g1DGVurTc5N8Ia8sBltNBtBLdT7X2RJFY6E6bxLS0Az2b6GrBtKzaVFX6AqHxB7unWDUR/vYhpHybVLbD+KQTk6lmB3ByMjxIuZTKqcE06eerJuuyvVtmo0lDTQfxdDZyJOkdVjQlBmLqMBjx0xoAnI73aSBX25pVzSJJ6oq3q8iQHN7e7tWNy+GEDmXq3jy8bDYXLAH/Zj49DGhOfSVSunE7RA3EOzmAoCAYCBN9AgMVGCiXEFXPTxdJOzU6efmvBv2YBmkrJSjeJYPMHWauFg4A0JvmLFknIOxAOael8PyelZyWxzbUNICMFisKR8H+JFcTH0pbmA9MWbnJsApBZdU4vNaKObfMn9lpYqrEA08O4wOeAL+xL6GiW7jXyQHCTR4jOmRENJA4ycEYFIQHIzCtBeXEENNqONBnBMvAnTKhKr2or7Glq1NIvF06zqWXRBWmGpYIvTHZhki45cqtqmVU7DvLp5CAthugmspsI5gQRfS83FkS0CJPY1xTJHKlaSs5X09LgUq9S1jmOZIk45F6dsk2tTrBwlxekADV7qsXEreZwmAcRZ1bM0q/DJ/dYx0kEFAds82xCKhGDiTZo2SpOzPYqp8E0xMLliMvYYtwf9dzHNTcm1S0QvO6oQoFhhMypGRmQ64aiwVFC/OJ7jsXDawpy0q1hk6FJFTLIJaHIcR4Mf+S4MkS/EA7oYuqCXCXyR76XP05eg9Hlp/UsIC2HsVr8bplZOzahNPMfLFv4gfpjpqpyLiwKR9xST+oB8r1IBTTKxrLJWpVWVji8bj30b96X/lvXQTHpczfVMVISdrk76HWq5n8T9VrGknAPxtui925xsoJ8MTTd3NKcEWMSL4mLaBdcTcu2QtLZsrgm5fkvrRhbP8TTwLu5rBv3RDZ1CeS9Or5oOIxfdSCJKej0w8kY0OhoBKFynw/r6ZxJInzOzamZKVVs6drs6aZ+YzX1gN9kxqXxSwnkZOybi64Tn+JwrH0+fEbdtMnJGWsRQDSRQUkzprDOqZtC+pliyWIqV5A2uErN+AU06f3B16GKZpQZyPTr9TlnfZNKuNf3RFHGb0aY6CEnG6bbhtgSRAUlBzyTzoNxSTttEjkN8FJscTZoCpFMrp8LMmzESGEH7SLsum2k7GmJhSjF9L8lBZxaEzi+pMicGQwXiwICWiRBRgg36B3Fg84FocDSkf5PGdn2w5YOi2bURBxS0pkbIUWurRcdIxw67KErnISf3uUlxlZAQwhUfXUHTl5d1LwOQvVfrnJo5WLZtGVb2rcQp006hj4v9MKUgA+5G50ZcveRqAPH07WKarFdaKwGndKVzKZ9FJU6bfho+3/o5APnvJXlirEZ5Vmevg4k3IRgJUvWalgl2QkDTVjwBTaKO1HsClM6fkPqilqUGiiqtlWh2NKPT1bnDTsyS++JsA5qvrH8lpd8iSmItKq05NXPw5bYv8a9V/8JnWz8DEK3MChTOO9lisGBa1TSs7l+NOTVzdFVztZS1oH2kHe3D7QnqC4LeBYEIlZZKdLm6JNWm4+zjYOSNCEVC+HHwRwDZq0Hm1MzBhqENO2x2BSOK+DopMZbkXPl4aOuhqLZWo9/Xj6mVU2E1WlW/l8xPikkJaTFYMLVyKtYMrCmqTd9iJCWgmQOFZudIZ/5Szi3xjCZiW5Q8PyHtIoV9tLSpylqFJkcTulxduPqjq+n5lm9fDgCYU5uZlcqcmjloH2nHyr6V2K9pv4yzCky8CTOqZuD7vu+xsm9lXO1XJGvaYuDg1oNRa6tFr7e3qOamyYpMptDML0yhyciIqZVTUWYug4k3odqmTTFC/EnOnHmm7u3arX43ANFdsWKABBS63d00dSDbCcGkiqjKQ+/FXbEwu3o2DJwBXa4uuogH4oE2uYCmiTdhfNl4AMCSjiX4YMsH+GDLBxgODKPOVodDWg/Jql071e4EAPik65MEb7t0KeeNJY3gwMEddNM2EfNxokwqBsj3SpRgYtQUBBJzYPOBaHY0gwMney8mB3jUBOgNvIEej3joaLmfdq7dGUbOiFpbbVEFk4lyS+9+S2zqL0W6QBHpT4vpOtWT5GB4NgHNnWqi/cO3Pd8m+OVmshAk33vbcBvtM9qG2wDom3atlb3G7QUA2HPcnroet8URT++WQmv/o/q8sYUy+b7FGHgDmh3R8ZuobrJVg5DzqK16yxidiK+TXCvaAMBkMFHV0u7jdtf0XjJHLbY+ntwreosedjSSFfu58NDsGumiNkn58tCMCBEasEzu92nKeQZzQCB+bS3btoyOrwO+ARg4A3ap3SWjdidnaGSzCUc9OftW0rkEC47FMfEmqkov5HwomeSgczEFW8cCTKHJyAgTb8I/j/wnPEGP5p3dO/a/A12uLs0TLzXsXLsz/n7o32mAoNBUW6thN9rhCXngD/sBZD8huHLeldi/aX/s37y/Hk0sOkrNpZjfMh8ftn+I59c9jz/s/QcA6opi/OXgv1BFppg9G/ZMSSnUyn5N+6HSUokeTw8+7vwYh7QegnAkDE8o5uUoEyBrcDTgscMfw2bn5oTHzQazbgWx9IB8r1Ip52oKAokx8AY8ccQT2OreignlEyRfY+SNsBlt8Ia8CedPR2tZK9qG2+j7tCjEx5WMw+NHPF5UahQAOKT1EDww/wHsWrerrsclk710Kedyv+u1u1+Lg1sP3mH7muRrJ5uA5rTKaZheOR3rBtfhtQ2v4ezZZwOI++VquU73b9of9x10H/q9/QmPl5pLC9pn/HLnX2Je/Tz8pOknuh5X7XWqd0Dzt3v8FkdMOALzW+ZLPt9S2oK24Taa2pitSubYScei1FQqGUBl7DiIgw+5DgARLtzpQsyomoE9G7RtNuw1bi88dPBDCf7SxcCvdvkVdh+3u+59zY5GqbkUBs6AsBAGoO/1Vl9SDzNvRiASQKweZ86vZ6vRCqvBCl/YR/tduYAmmQNq9aj99e6/xm71uyEYTizwObliMsaVjMuo3cne/9mMWeJK7GRDhAXHEjl/7vmYUTUD8+rmFboplOQNz2JKhx8LsIAmI2OmVU5L/yIJGhwNOd11LaYJEDGwJjuJQPYTgnJLOQ5uPTjbphU1p804DR+2f4g3N76Jq3a7CiWmElVFMSaUT5ANoGWLxWDBiVNPxBMrn8Bza5/DIa2H0GAFoOyHuWfDnpoXGvmGKCSlApqZKKTU3Od2o51OStVaKCS3QasCZl598UyACEbemJN7mnxX3e5uBMPBlKB+ukl3hbVih+5rxH2xkTNmZePBcRxOm3Ea/vTFn/DCuhdw1qyzAIgWXRquU47jimqzg2A32XFQy0G6H1dcgCcZX8hHiwXprWystlUrKvdJu3xhH4DsFyhG3ohDxmeXKcAofsTBh3x5Uxp4A+a3SgfmleA4Dge2HJiDFmWHw+zIOqtmLMBzPCosFej3RTe/9Aw48hyPptKmhM34fAToyyxl8Hl8tN9N7veT5ytas20qrBU4aepJ2TUyiRlVM2DgDOj19mK7e3t2Ac2Yj+ea/jW02CALjiXCczwOaD6g0M1IQPwbGThDUfkSjwVYyjmDkWPEAxrP8bAa1PsbjVX2GrcXJpRNgCfkwVsb3wKQ3kMzH5w6/VRw4LC0eyk2OzfTgKbFYMlaAVpoSKBYyUNTb4WUeHKs1hswuQ35UsCMRmpttbAarIgIEWx1b014LiJENCtvdzTEQcYae03WlaePmXgMHCYH2kfasXTrUuqfCbDrVAlxQFMQhITnyDVaairN+6IuOZ2N+Zgx1CBWaOYj5ZwxthFv8us9zojnBhaDBUY+9zoocT9r5I0pBehq7bUJ6yg9fUMzxWa00eDjyr6VWc2ZJ5RPQImpBL6wD9/1fAeAjT2jAfFvVGouzbl3MiMRFtBkMHKM2NA6HwbxOwIcx1GPlOfWPQdBEKi3YyEDmk2OJror+MK6F+IVzneAnTjqoZkU0PSH/dju3g4gtwHNKltmCk0WKJKH4zjZwkC9nl74wj4YOAPGOTJLsxrtiBdCehSJspvsOH7K8QCi/RbZ8DBwBlgMlqyPv6PSXBr123UFXSkevnRhWNaS97Ezua9hKhmGGsQKTTY+MXKN2EdT7wC6uA/M17Us7mebHc0pVcJ5jk8oUFksmwYkVXxJ5xJ4Q96owjUDX3Se4zG7OuqjuWFoAwA29owGxL8R+73yDwtoMhg5JmFCYGaTW7UsmLwANqMNG4Y2YPn25ao8NPMBMd9/fcPr6PX0AiiuCqGZIpdy3jXSBQEC7Ea77sFkptDMPbQw0HBiYSASKGooaYCJH93q4kwRp6pl458p5tTppwIAPu78GBuHNgKIXqNsI0sei8FCv//kwHuuCgKpQbxoBtgihaEO8XXCxidGrhHPifXeXBf3gXkLaIo2BOT6fXG7ikVQQIKQi7YsAgCMs4+D2WDO7FixwkAENvYUP+Lrlnme5h8W0ATg9/vx29/+Fo2NjbDZbNhrr73wwQcfFLpZjB0EccpGMaRGjBbKzGU4euLRAIDn1z0f99BUGfjKFfs17YdmRzNGgiN44ccXAOwYAU3yvSYHNGnhmLJW3YMyCQpNlcHSJkdTQmowWzAqQ/qf5ECR+Hcdq4iVHbX2Wl2OOal8EvYatxciQgT/WvUvAOwaVYNcYaB0hatySbMjqhwlsLQ/hhrE1wm79xm5Jl8p5/m6lsWWDXLzk0K0Kx1za+YCAEaC0cwtcXaeVoiPJoGNPcWP+LottYz+NeFogwU0AZxzzjm499578dOf/hQPPPAADAYDjj76aHz66aeFbhpjB6AQKRs7CiTt/MMtH2LIPwSgsCnnQDQdhKg0l3QsAVA8O8TZQCbFw4FhBCPx6o+5VEiJA0oV1gpV7zEbzBhnj6dIs3tKGbmCK7nyRR1NJKSc66TQBKJFzQBgaffS6HnYNZoWep0OF891ajaYE6reMpUMQw1MocnIJ+KAZi5TzrVWE88UNQrNhHYVScr5lMopCdYy2YxZJH2dwMae4kccdGYKzfwz5gOaX375JZ577jncfvvtuPvuu3HhhRdi8eLFGD9+PH7zm98UunmMHYB6ez1N6WSTW23MqJqBXWp3QUgIISJEAKgPfOWSE6acADMfTyXRWmWxGKmwVFA1ktPvpI/nMqBAAsFl5jJNac9k59vIGxN+B0Yq5LtiAc1UcpFyDgDzW+YneHKyfj89xRp4FyuBmEqGoQZxxga79xm5RuyhqffmujgjJl/zXHHwTq7fL0aFpok3YXrVdPrvbLIKGkoaEsQbLKBZ/FiNVlqsiv1e+WfMBzRfeuklGAwGXHjhhfQxq9WK8847D1988QU6OjoU3s1gpMfAG6gxdLEMvKMJonYCtAe+ckWFtQJHTjyS/ntHSDk38AZUWCoAAP3efvp4LhWa5H7QqrolbWHehOkh31XnSCfdFAAK601YLIgVJ3oGNI28EadMP4X+m/X76aFeryNxr9dgJIitrq0Jz+cb4tVmNVhhNVrTvJrBiN7/pabonIDd+4xck8uUc5PBhIaShuix82SZpSagKX68mDKkxKni2YxZHMdRT06AbaaNFkjaOQto5p8xH9D89ttvMW3aNJSVJXYWe+65JwDgu+++K0CrGDsaZGArltSI0cTh4w+n/o6FTjcXc8aMM+j/F9OEKhvIxPjjzo+xuH0xFrcvpoVNcuFhR+4HrYWeSFuYJ216GkoaYOSMCEQCeGPjG/R3JUWCCuFNWCyIF396BjQB4OSpJ8PIGVPOw5CGjJFtw230Gn1jwxsIC2FYDBbdPE61Qjzc2IKSoQWysGX3PiPXiH3lc7HGyPf6hfS1HDjZKuENjgY6vhbTukqcKp7tJhw5ls1oy7i4ECO/kGuXzRfyj7HQDSg03d3daGhoSHmcPLZ161bJ9/n9fvj9fvrv4eHh3DSQsUMwvmw8Pun6ZIdQ8uUbs8GMk6aehMdXPl5UAc05NXMwu3o2VvWv2mF246pt1djk3IS/fPuXlOdyUTyGDPrilCk1kCDcjpDqn2uMvBFNpU3YMrwFN3x2Q8JzHDg0lUovGMYC4v5YnCKuB3X2OhzcejDe3/I+6/dVQO5pp9+JKz66IuG5ltKWhEJg+YS0q9y6Y/TxjPxQYalAl6trh9nsZBQv1bbo/MlqsOYkg6m1tBVLu5fmbRwjtlINJQ2ygTwjb0SjoxHtI+1UDV0M5CKguaOsL8YCRJxBst0Y+WPMBzS9Xi8sFkvK41arlT4vxe23346bb745p21j7DicMu0UdLu7ceKUEwvdlFHJuXPORY+nB0dPOrrQTUnghn1uwBM/PIEFkxYUuim6cO7scxERIghFQgmP71q3a0JxDL04pPUQLN++HGfOOFPT+/Zt2hdHTTwK81vm696mHZFLdr4Ez617LiHlHAAObD4QNqOtQK0qPOWWcpw35zxYDJacBMev2u2qhCJiDHkcZgcu2eUSfNb1WcLjBs6AM2dq6x/0ZL+m/XDUhKNwcOvBBWsDY/Rx/tzz8X7b+9i7Ye9CN4WxgzOhbAJOn356zmw5Tp1+Kvp9/Thu8nE5OX4y8+rm4dhJx2Lfxn0VX/erXX6Fjzs/xrz6eXlplxomlE3AL3f+JRwmR9bK0X0a9sFxk4/DbvW76dQ6Rq45Z/Y5qLJW4YDmAwrdlDEHJwiCUOhGFJI5c+agvr4eixYtSnh89erVmD17Nh5++GFcdNFFKe+TUmi2tLTA6XSmpK8zGAwGg8FgMBgMBoPBYDAYDGWGh4dRXl6eNr425hWaDQ0N6OrqSnm8u7sbANDY2Cj5PovFIqnsZDAYDAaDwWAwGAwGg8FgMBi5Y8wHNHfZZRd89NFHGB4eToj8Llu2jD6vBiJ0ZV6aDAaDwWAwGAwGg8FgMBgMhnZIXC1dQvmYTzlftmwZ9t57b9x999249tprAUTTyefMmYPq6mosXbpU1XE6OzvR0pIb/xIGg8FgMBgMBoPBYDAYDAZjrNDR0YHm5mbZ58e8QnOvvfbCwoULcd1116GnpwdTpkzBv//9b7S1teHxxx9XfZzGxkZ0dHSgtLQUHMflsMXFDfES7ejoYF6iDEaRw+5XBmN0wO5VBmP0wO5XBmP0wO5XBqM4EQQBIyMjshaQhDEf0ASAJ598EjfccAOeeuopDA4OYqeddsJbb72FAw5QX6WK53nFyPFYo6ysjA0KDMYogd2vDMbogN2rDMbogd2vDMbogd2vDEbxUV5envY1LKAJwGq14u6778bdd99d6KYwGAwGg8FgMBgMBoPBYDAYDAX4QjeAwWAwGAwGg8FgMBgMBoPBYDDUwgKaDF2xWCy48cYbYbFYCt0UBoORBna/MhijA3avMhijB3a/MhijB3a/MhijmzFf5ZzBYDAYDAaDwWAwGAwGg8FgjB6YQpPBYDAYDAaDwWAwGAwGg8FgjBpYQJPBYDAYDAaDwWAwGAwGg8FgjBpYQJPBYDAYDAaDwWAwGAwGg8FgjBpYQJPBYDAYDAaDwWAwGAwGg8FgjBpYQJPBYDAYDAaDwWAwGAwGg8FgjBpYQJPBYDAYDAaDwWAwGAwGg8FgjBpYQJPBYDAYDAaDwWAwGAwGg8FgjBpYQJPBYDAYDAaDwWAwGAwGg8FgjBpYQJPBYDAYDAaDwWAwGAwGg8FgjBpYQJPBYDAYDAaDwWAwGAwGg8FgjBpYQJPBYDAYDAaDwWAwGAwGg8FgjBpYQJPBYDAYDAaDwWAwGAwGg8FgjBqMhW7AjkIkEsHWrVtRWloKjuMK3RwGg8FgMBgMBoPBYDAYDAZjVCEIAkZGRtDY2Aiel9dhsoCmTmzduhUtLS2FbgaDwWAwGAwGg8FgMBgMBoMxquno6EBzc7Ps8yygqROlpaUAol94WVlZgVvDYDAYDAaDwWAwGAwGg8FgjC6Gh4fR0tJC42xysICmTpA087KyMhbQZDAYDAaDwWAwGAwGg8FgMDIknZ0jC2gy8k7E7YZ/wwZAEBIet0yfDt5mk32fEIkgtH07TA0NuW6ichu2bYOpsbFgbWDIE3G7EfF6YaypKXRTGEVAJBBAeGgIprq6QjeFwWAwGBoIj4xA8PuLbjwPbtsGQ3m54nyVwcgVEa8X4eERmOqzn9eEh4chBIMwVlfr0LIdi+D27TA4HOBLSmRfo+dvwWAwModVOWfkjYjfj/4n/okNBx+CttNOR9vpZyT8bTziSAS2bJF9b/t552HD/IPhXroszy2P03vvvdhw8CFwffpZwdrAkEYQBGw56+fYcNjh8K1bV+jmMApMqL8fm088CRvmH4xgV1ehm8NgMBgMFYRdLvQ++CDWH3gQNhx+BMIjI4VuEgAg0N6OrquvwYaD5qPjlxcXujmMMYgQDEbnuQceiM6rrkKgrS2r47UtPBXrDzwI3TfdhGBPjz6N3AEIdnVhwyGHYv3Bh6D/8ScQ8fkSno8EAhh48ilsOORQbDjkELg//7xALWUwGAALaDLygBAOY+jlV7DxyKPQc9ddCDudMFRXw9TSQv/48nKEenrQfu4vENy+PfH9wSC6rroani+WAgD8P/5YiI8BAPCt+7HgbWBI4/32W/hWr4bg9WLbH2+EEIkUukmMAhEeGUH7BRcgsHEjEA7Dv2lToZvEYDAYDAUigQAG/v1vbDzscPT97e8QPB4IHg+CW7sL2q5Qby+2/elP2Hj0MRj+738BIJplxGDkmYEnn4Rv5UoAwMg772LjMcdmHIyMBAJREUkohKHnnsfGI45Ez333F80GQiHxb24DQiFEnE703H03Nh55FIZefhlCMAjnm29i01FHY/tttyE8MACEQui+6eaUoCeDwcgfLOWcoRtCIIDtd96FYHfi5DOweTMCmzcDAIwNDai99FKUn3A8OIOBvibU14e2n/4UwS3taP/FeRj/9FMwVlZCiESw9frr4Vq8mL424nHn5wNJEHG5Ev7LKB6cr75K/9+7YgWGXngBlaefXsAWRYn4/eh76CFYZ85E2dFHF7o5RY/nm2/gfPNN1F11FQwZ+BFHvF50/PJi+FevoY+Fh4f1bCKDkXd8637E4NNPo+bSX8FUX1/o5jAYqul75B/wrliR9nW+tWsQigUvzRMmIDQ4iIjTiYi7cHO+gf/8Bz3/dw8EjwcAYNtlF3i/+27MzwGFYBC9D/4F5kmTUHHiCYVujiZCg4MY+Oe/IIRCqD73HBhra/U9fl8feh94EPY990DZMceA4/XRDgU6u9D7l4cAADWXXAzvqlVwf/w/DD33PJyvv4G6q65E1c9/rvp44mvYtvPO8K5Ygf5HHsHQc89h3M03oezII3Vp92gk4ooGdY319QDPI9Tdje7r/4Dtt96GSKwvMNbWovqii9D/6KMItrej7+GHUXfllRmdL+xyYfCppxDxeFBz2WXgzWa9PgqDMSZgAU2Gbni+/hqDzzwj+ZyhvBzVF12Eyp+eCd5iSXneWFOD8U88gbYzf4rAxo3ouOBCtP7rn+i9734Mv/EmYDTCOn06fKtWFXQiSQOa7rE9mS02Il4vhv/7DgCg9KgjMfLOu+i5516UHnKI7pNVLQihELquvgauRYtgrK1lAU0V9D74F3iWLoVtp501L5SEQACdV1wB7/Ll4EtLYRo3Dv716xEZYfcrY3Qz+PRTGHrxJRjKy1B37bWFbg6DoYpQXx9677tP9euNdXWoufRXqDjpJGw+9VT4nc6Czrd6H3gQgscD69y5qLvmGlhnTMePe+8Dwe+HEAiAG6OBh/5//Qv9jz4K8Dws06bCNnt2oZuUlojHg4F//zuaQhybyw8++yyqzjkb1b/4BQxpquiqZfiddzH04osYevFF9D/2OOquvgolBxyQtqiFEoIgYNstf4Lg88G+++6ouewycBwHz1dfoef/7oF3xQr03v9ARgFN3m7H+OeehWvRIvTcdz8CGzei729/H+MBzeh3Y505E00P3I/B/zyL/ocfRtjpBF9aiurzz0fVz88Cb7PBWFeLrsuvQP/jT6B8wQJYJk9Wf55AAIP/+Q/6H34E4aEhAECgoxNN9/xfguiHwWAowwKaDN0gnbF50iRUnXsOfZy3WOA46KC0aitTUxNan3gcW352FnwrV2LTsQsQ2rYN4Dg03n47Am1t8K1ahXABA5rh2MS6kG0YC0Q8nlTfQ4MB5tZWcMbUbmvkw0WIuN0wNTej6e670dbeAd+qVdh+x51ouuf/dGtXaGAAhvJyVRMNIRJB9/XXw7VoEYD4/cFQxr8xmsoXdg5pep8QDmPr734H9/8+AWe1ouWRhzH0wovRgKaLpVAxRjfhIScAwLP8m4K1QRAEhAcGWAEJhmrCzuh1y9vtqLvud4qvNZSUwDF/Pi22Y7BHi3EUahNbiEQQian7W/7+NxhraiAEg/T5sNsNYx4CmkIohIjPB4PDkfNzqSHQ2Ym+v/4t+o9IBNv+eCMmvPC85LxIEAQENrcB4ZDm8/B2O0xNTVm2NqomHXzxRfT97e8I9/UBACwzZ4IzmeD7/nv0//1hDD37HKp/eREqzzhDUnShBfFcz79uHTou+iXsu++OumuvgW2XXTI65sh778P98f8Akwnj/nQzDY7a99gDLY88jB/33gcRjwdCMAjOZFLXzlhqOe9wgOM4lB56KIz149C2cOGYTzsPxzbBeYcDvMWC6nPPQcUpJ8P92eew77UnjJWV9LWlhx0Gx0EHwbVkCbpvvBHjn3wyRZUb3LYNkaTv1PvDSvQ+9Je4Kn38eAS3bsXIu++i21GChltuySoIzmCMJVhAk6EbZAAwT5iAyoULMzqGZfJktDz6KNrPPjsazAQw7o83oHzBsej/578AABG3R5f2ZkLE5U74L0N/IoEANh59DP39xZQefjiaHrg/ZZAn6eblJ5wAzmjEuJtvRtupp2L47bdRfuKJcPxkv6zaFGhrQ88DD2DknXdRsXAhGm75k+LrBUHA9ttuh/P1NwCeByIRCMEgIoEASyVRIDw8jHBvdMGh5R5zL12Gnnvvhe/77wGTCc1/eRD2efMw/M67seOO7ck5Y/RDVGq+lSsR8fuzXnRrxfXZZ+i99z74Vq1C0333ouyoo/J6fsbohCziDZWVmueFfCyAV6iU84jHCwhCQls4kwmc1QrB54u2SxTYyBXt518A35o1mPDss7BMmpjz8ykRVQreAsHng23nneHftAm+Vasw+Mx/UPXzsxJeG/H50HnJJXB//kXG52u443ZUnHBCZm2NRDD8zjvofeBBBNvbAQCmlhbUXnEFyo4+CuA4jHzwAXrvux+BzZvRc8edGHjySdRedjnKj1uQsUKOBOArFp4CvrQMg08/Dc/XX6Pt9DPgOPQQ1F11lSYVX9jlwvbbbgMA1FxwPiyTJiU8L67CHXG7YaioUNnO6H3Fi5SpvCO2iTDGA5pUvVoa30QwlJai7MgjUl7LcRzG3fAHbFy2DN6vl8P56quoOPlkAIB/40b03HcfXB8ukj2Xsb4+qko/8USMLF6MriuvgvOll2EoLUPdb37NgpoMhgpYUSCGbpABwFCa3S6ybc5stDzyMKyzZ6P+979H5RlnABANtIXarRcE5qGZB/xr1kSDmTwPQ1UV/QPPY+T99zHy4YcJrw92d8P9RXTCXH7C8QCi11Dlz34KANh2c+Zm3cGeHnTfdBM2HrsAI7HgmG/16rTv6/vLQxh8+umYuvg2+ji7bpQhXruAuu/Kt2YN2s+/AO3nnAPf99+Ds9nQdPfdcOy/P4B4X8QUmozRTjgW1BGCQVoUIh94f1iJLeeei47zzodv1aroYyu+z9v5GaObMAmaZKAuJO8pVEYMTXU3GsGJNhB4Oq7kp13e775DxOnEtptvhhALsBaKkffeo0rBhttvQ901VwMAeh94AEHRJrQQDKLryquiwUyTKWEup+aPBNkGn5a2sUqH67PP0HbKQmy95loE29thqK5G/Q1/wOS330L5sVFfS47jUHb44Zj05hsYd8ufYKyvR2hrN7qvuw6bTzgRI4s/yuj7JplcpqYm1P/m15j83rsoP/kkgOfh+nARNi04Dluvvz6l3oAcvfc/gFBPD0zjW1F90UUpz5MgOxC/39RA5kVkbQWApt1H3O4xXViTfDdqVdGmpibUXnopAKDnrrvhW70aW6+/HpsWHBcNZiatZwxVVTA1N6Pu2msw+b13UblwITijEWWHH46GW24BAAz885/of+SR3HxABmMHgyk0GboRJoNjSfZpMfbdd8fEl19KeMxQUuCAptcLxAZ4FpjKHd4foov1kp/sh9Z//IM+3nP//eh/+BFs//OtKNlnXxhikzDnG28CggD7HnvA3NxMX197+RUYee99BDs60Pf3h1F31ZWq2yAIAvofeQR9j/wj+rsDsEyfDv+6dfQ6l2PgP/9B39+i6Vj1N/wB5ccfj203/wkRjyd63VRVqW7HWMMvDmgq+KZF/H5s++ONcL7+evQBoxGVpy5EzcUXJ3im8qVRmwum0GTIMfTSSwDHUUVFsSJWLHuWfwP7brvl9nxeL7qv/wOt6syZTDBPngz/2rUIxdI2GYx0UKVTJgFNOucrkEKTbNKXlCSopAwlDoR7+/IyD4wEAhBiG7KeZcvgfP11ScVisKsLA08/g8rTToV5woSctCU8MoLttxKl4AWwTJoE84QJcL76GrwrVmD7rbeh+S8PRot5Xvd7uJYsAWexoPXxx2DffXdN5woNDGD9AQfCt3Il/OvXwzJ1qqr3eX9YiZ5774Hni6UAotdQ1Xm/QPXZZycoGcVwRiMqFy5E+YIFGHz6afT941H4169H5yWXwLrTTjC3tia83tzaiprLLpVVzlHlY2wtZGpoQOOtt6L63HPRc//9cH24CM6XX8Hwm2/BcdBByj6skTDNNGm48UZZZT7vcCDs82nym6XXt0Os0Izdp4KAiMdTNDYH+SZM+y31vqpVPz8LzjfegH/dOmw+KT6f0KrKrTj5JIRHhtFzx53ovf8B8KWlqPrpT7V9AAZjjMECmgzdkEpf0JNCpx+JVQJhVhQoZ/h++AEAYJszN+Hxml/+EsP/fQfB9nb0PvgAxv3+9xAEIZ5ufuKJCa83OEpQ/4fr0XXZ5eh/4gmULzgWlilTVLWh97770R8Lptp23hl1114Dvqwcm48/Pm2Bmf5HH4u297JLUXXmmQCi1y4NaDJkCWyKBzSVVDmer7+mwcyyo49G7RWXwzx+fMrrqEJzjKdPMaQJDQyg+4Y/AoIAY/24rK0pcom47/AuXw7ggpyez/Xpp9FgJseh/LgFqLnscni//QZbf/0bFtBkqIYEWMQqMLXQrJxCpZzLBGPzqRyNxDxICT133gXHgQcmePgFe3qw5ZxzEezoQNjpRONtt+akLb33P4BQby/M48ej+qILAQAcz2Pcn27G5pNOxsgHH2Bk8UdwffI/DL/1FmA0ovnBBzQHMwHAWFUFx4EHwrVoEYZeew31v/614uv9mzej94EHMfJuNPjHmUyoPPMMVF90EYwqN5F5qxXV55+PioUL0f/YYxh48in4vv8+amWThGP+QbDNnZt6EMhfN5YpU9Dy0EPwfPsteu+5F56vv8bI+++ralvZsceiZN99ZZ83lJQg3KctyC72iSRwFgtgMgHBICIu15gNaEZGtPdbnMmEhptvQtsZZ0ZFFrvvjtprroZ91101n7/6nHMQGR5G39/+ju23/BmGsjKUL1ig+TgMxliBBTQZuhEZSU1f0BM6iSxQMFGsEmAemrnDG0untM6dk/A4b7Vi3B//iI7zz8fg08+g/LjjIQQDCLS1gbPZUHr44SnHKj30UDjmz4fro4/QfeNNGP9Uqll3Mv2PP06DmfXXX4/Kn/0UHMchuHUrgPTBsfDAAACg/Pjj4213OICeHlZMKg2BzZvo/yvdY8R0377HHmi69x7Z11GFJgtojhoiXi8tCpJrAps3U4+8bTffjElvvgE+lrpXbIiDOp5vv4UQiaTty7IhFEuHLD38cDTeeScAINgR9aEL9fXm7LyMHYu4ylF7YIQEUwq1ERhOE9DMxzwwHCtKxDscMDU0wL9+PXr+7//QeGs0aBkeGkLHeecj2NEBAAhs2iR7LAC0qJHawjEE7w8/YPA//wEAjLvxjwlKQev06ag652wMPP4Euq66CoLfD3Acmu66E44DD9R0HjEVJ54A16JFGH7jTdRddZVkQchgTw/6/vq3qNI+HE7YgDE3Z1ZQyFBejrprrkHlz36GkQ8/TCgENfDvJxHq7kZ4cFD2/fGApvRayL7rrmh96kl4li6Fb926tO3hrda0wSw+g3tFyieS47hocHRoKDrXHTdO9fF2JOIWatoEOrZddsH4p5+CEArDvuceWflf1lx2GcLDIxh8+mls/d114EscKD14fsbHYzB2ZFhAk6EbZCde6wCgloKnH4kCqUxplxvCLjedkEvtfjt+sh/KjjkGw2+/jW033gjrrJkAgLLDD6cp6GISzLqXL4fzlVdQccopsucffOEF9NwdrYpee83VqDrrZ/Q5ojwWgkHZohyRQCA6mUfifZDPBdBoxr9JnYcm3T0vK1M8HlNoji58q1dj82mno/qcc6g3Wy4JtG2h/x/s6EDfww+j7sorc35erQiRSDygyXGIDA8jsHGj6jTMTAj19AAATOPq6WOGWHVzUriLwUiHXFBQDXTOV+BN7NSAZv7sj8LOaEDTUFmJcTffjC1nngnny6+g4oQTYJ01C+0XXQT/+vXg7HYIHg8CW7bIHksIhbBpwXGAwYBJb7yuqejN9jvuBAQBZcctkFQK1v7qVxh551268TvuxhtRdvTRGj9tIo4DDoChogKh3l64P/8cjgMOSHg+0NmJzSefQlWsjoMOQu1VV8I6fXpW5yWY6utTUn1diz+KBjQV5hR0LaRwzXMch5J99kHJPvvo0tZMVMPUJzJps4EvLUV4aGhMb8Bn02/pZQfDcRzqf38dIiPDcL7+BrquvBItjz6Kkr321OX4DMaOBCsKxNANmr6gg4emFOS4BUs/Ek1gxrphdq7wrVoVTf9sbICxpkbyNfW/+y34sjL4Vq3C0ItRn9XyE0+QPaapsTFu1n33/yEUU1AmM/zOO9h2400AgOoLzkfNBYkpnXxJCRDbbZULkIkfF0+EDI7CLsxGA0IwiECsEimQJqCp0rCdKjTH8MR8NOH+4gsgGITnm2/ycj5yvRG7gv7Hn4B/w4a8nFsL4mrLtp12AhD10cwlwe3RgKaxro4+Rvxpw04nhEAgp+dn7BjIBQXVQOZ84YKnnCdulhroXDQPAc3haLDOUFYG+7xdUXHqqQCA7ptuRsell8K34nsYyssx/p9PRF8/OEhVnckE2jsQaGtDYOPGaOFFlQiCQK2Aan55seRreLsdDXfcDvOkSdFinqefpvr4cnBmM8piysShmLWQuE3b/vQnRJxOWKZOxfinn0LLw3/XLZgpB9nYVrIeyqYQVqZksmlOg3ZJIpRM1J47Gtl4/+oJx/NouPVWOA45BEIggM6LL6Z1BhgMRhwW0GTohlT6gp6QoJDg8yWkgOSLhKBIzDCboS++ldL+mWKMtbWouzqu3jI2NsC+p/KOZdXPz4JlxgyEnU703HlXwnOCIMD51tvo+s1vAUFAxWmnofbqVHUYx/NUMSK3O09tF0pKEtQPNBg/hieI6Qh0dgKi+1rJWoJunqRRg1OFpswCj1FcBLZEA4z5+r2Imqni9NPhmD8fCAbRfdNNRbdZRTfxDAaU7BdVR3m+WZ7Tc4a2bwcAGOtECs3yciCW9im3MZQNw++9D+dbb+t+XEbhiKduZl7lvNBZOSkKNqKGy4Pyn/SFhvLo5lzdNVfDUF2NwMaN8HyxFLzdjpbHHoVt551hiG0Ck340GbGlS6CjU3UbwkNDdAPDpJDGXbLnnpj837dR9fOzVB87HRWxzWrXosUIi/xER957D+7/fQLOZELTA5n5dGZC3AZBQaHpyq24QwpDBqphOZ/IQls9FANkLl8MHqKc0Yime++Bfe+9EfF40HHBBQkFNBkMBgtoMnQk1wOAuEJhIVSayZPqsTzY5wqy85jsn5lMxakLYdtll+j/n3BiWi85zmhEw59uBjgOztdfh3tptAKm+8svseX0M7D12muBYBBlRx+FcX+8Qdb3hu7Oy/z2coG2fBYRGK0ENrcBADi7HYDyIpYGjtMskunv5XZDCId1aCUjl5AAY748T8n5zOPHY9wfrgdns8H79XJaaKxYoIVVSkpgi6WzeXOs0CQp52KFJsfzMMbSzkM6p537N21C15VXYuu11yYotRmjm/i1m02V8zHsoRlLOefLygFENxXqf/c7AFEFY/Pf/kbteYjSXC7tPCAKggQ7O1S3gag5DdXV4JUqcucAy8yZsEybBiEQwPA77wCIjg/bYh6i1RdcAMukiXlrD5lThGUUmoIgZBXEz7hdGaiG41XOCxewL1aIKrzQCk0Cb7Gg+aGHYJ07F+GhIQw+9XShm8RgFBUsoMnQDToA5MhDkzOZohX4UKiApkvx34zsIdUk5apHEjieR/Pf/opxN91Iq22mw7bTTqg84wwAQPeNN6L9oovQ/vOz4V2xApzNhuqLf4nGO+5Q9JWiO9eyCs2YmkI2hYd5aMpB1CO22bMBRO8vIZZmm0yYppwr9zXivojdr8UPWYjnQ6EpCEI8oDlhPExNTai97DIAQM9dd+dEgZgp4tRX2867ADyPYFcXgjEVpd4IgoAg8dCsr0t4jliB6F0YqP/xx2la/ciixboem1E4svGiMxS8ynkReGiKUs4JZcceg+a//Q0TXnwBJXvvRR+PBzTbJI8l9qjWotAMxgKapvr6NK/UH47jUH7iiQDiaee9992PcG9fQrX1fMGn8eUWPB7ajxUi5VzLpnn83kyar5aO7fmqEApFf0fkbj2bCQZHCSpOXQgACHZ1Fbg1DEZxwQKaDN2Ip9vmbhCPD9oFCGi6WUAzl4QGBqihvDUW1FLCWFWFytNPlyzOI0ftVVfCWFuL4JZ2uD/+H2A0ouKM0zH5vXdRd8UV4NKoD9LtzssrNAurNBkN+GPFoKw7xYLZkQgEr1fytTRVKp1C02ymmyByvxmjOIh4vVQJFPF4IIRCOT1fuK8vumjheZibmwEkWlP0PfRQTs+vBRLQMZQ4YHCUwDIj6hPnzZHXaMTtpgs6sUITEAc09VNoBrdtg/ONN+m/RxZ9qNuxGYUlHhSUrvisRKG9/GQ9NB3a1XCZQtKsSco5EA3ylR48P8UvMq1CU1QBPdihXgVN7ScKVPG6fMGxgMEA34rv4Xz9dQw++ywAYNzNN2ma/+kB2UQNy6Sc07WJwQDOas1XszLaNJfziVSTVr8jI95AMZRo77dyiSl2D+ZqM5PBGK2wgCZDF4SE6s45DGgWsOpl8s5nIYKqOzLEdN48cWKKwlEvDKWlaPjzLTBUVKDs6KMw+e230HDjjTAlLdrliO9cKys0kwNtzJMoPYGYesQ2ezYtviSnNtBib8GXERN/5qNZzATaE1Mgc32vkEW/qbGRbmRwRiNqfvlLACgq432qpImNf/Z50bTzXBUGIgEMvrQUfMwCgmCojQY0wzoGNAf+/SQQDMIydQoAwPvNt0WlkGVkjlxaqxqoZ3WBiwLJpuTmYTyP0JTzsjSvBMzjWwEAQQkPTUEQEnz3NCk0u2MKzXH5V2gC0U0Ux/77AwC2/u46QBBQfvxxKNl777y3Ja7QlJmbuONBQjnropy0KyMPzdg8Kmm+SotxjdH5Ktn85iyWtCKHfGOMqaRD3d0FbgmDUVywgCZDF8QTTj6HO1p8AVOQmIdmblHrn5ktjgMPxLSlX6Dp3nupokEtdHdeJt2ITIQMpYmLj3i1VnbNSCEIAlVomidNSqs2kKvOKUW634xRHATaE1VFuf69aLp5a2vC46amRgD6KhCzJTn11b7bPAC5KwxE/TPrUzd6qEJTJw/NsNOJoeefBwDUXXstrLNmAZEIXB8t0eX4jMKSTbVg+p5gEJFYUZp8Epbx/4wX+cuDhyYpChTz0FRCSaEZHhhARFRUJ9ih3UPTOK5B9Xv0hqSdQxDAl5ej7je/KUg70toOkSB4npV9mWyay/lEqqnkviMjDkoXG6aG6D0YdjoRkclgYjDGIiygydAFMohydju4WBXUXGAoYLXoFA9NFpzSFaLQVKpwXmjSBdrkFJrMQ1OZ8OBgdLHFcTCPHx//vmTuMWpvoUWhyTYgippg0iI8nGMfzUBb3D9TjDilWs7DNd9EkhaetnnRgKZ/7bqcqGhIOpuUct1YUwtAv4Dv4LPPIuLxwDJtGkoOOACOQw4GAIwsWqTL8RmFJZviGmJ1cGHmfMXgoZlY5VwJsjkTHhpKqAgOxNPNDVVV8deo3DSi/UGBFJoA4Jh/EAwVFQCAumuvocXJ8g21HZLLHskigJ8NWlXD4uJFKR6aY9wiqZgqnCfDOxy0XwyxtHMGg8ICmgxdoANAjnclaQpSMQQ0x+hgrwW1AQFBEOBdmR+FZjYY0hjCyyo0x/gEMR2k+qqpsRG8zZZWbUDufzXWBFShmYdCM6OJYgnWEZJVRXL3mN7nS1ZpG8hCORhMUDQVErrwLIkuZEz19TA1NQGRCLzfrdD9fKHtpMJ5agBDTw/NiM+HgSefAgBUX3B+1Bvw0EMBAO7PPkMk5uPJGJ0kBE0y8FbnDAZwscV7QQKaMim5+bSQiUgUBZKDLymBsTa64ZDcn5J0c+vs2bSPC3aqSzunCs36wnhoAlE/7Oa//w0Nt96KilNOKVw70ig0symClQ1a/WYFrxcIhwHEi28RDKXKPqE7OoX6DdXAcRz1sg1uYwFNBoPAApoMXdCSApoNceVW/pVuJP3IUB5N/Rmr/jJq8a37ERuPOBKdl12GSMxfVY5QdzfC/f2A0QjrzJl5aqF2+DSG8FQ5mLwAKmUqQSXE6eaAstogYZGsor8Z6+lTUgjBINoWnor2iy4qdFMoRDFJyLlCsz3qM2dKCmjyZjPt44sl7ZwolcWKEVss7TwXhYFoyrmUQrNWe0DT+8NKrN//AHRedjm91wFg6JVXEB4YgKmpCWVHHQUAsEybBlNzMwS/H67PPsvmYzAKjODzyQZN1GIoKaTNkHRgg45PeWhTmHpopk85B8Rp54k+msSj2jJpIi2CFlCRdi4IQlEoNAHAvuuuqDj5pLx6UyZjSKvQzLwIVjZoDbLTIok8TzcNCPm0VChGIjLFPYsFch+Gtm8rcEsYjOKBBTQZupCvNIu40q1wHppkd2ysDvZqCGzZgvbzz0OwvR0jH3yIrquuhhAMyr6e+Gdapk0Fn8fKkFpJZwgfpoqOZIXm2DZZT4d4sQWIVRASAU2PR7RITt/f0AUIKwpECXR0wLdyJdwf/68ggQIpiKLIUFkJILcKTUEQaEDT3Jrqo2vIQSXvbKAp5yKVGy0MlJOAZqyqsZKHpobvZuiVlxHq7cXIBx9g07EL0H3DDQh2dWHgiX8CAKrOPZda1XAch9JDDgEAuBYtzupzMAoLDa5wXErQRC2FrHQu6zEY+7fg8UCIjUU5awNJOa9QF9A0xQoDpSo0Y5uGEyfB1NICQJ2PZmR4OKrmQ7wgyViGF21OS2U5kIKR+U5X1nqfKBUvSpeJtKMT/26Kq8I5gSilmUKTwYjDApoMXcimkqUWaJXzAqacG2O7Y0xtJ01w+3a0/+I8hHv7YJ4wAZzZDNfixdh6/fUQIhHJ9/h++B5AcftnAmKlpTaFJl9A79fRAPH3Mk8kAU35+5wGhUXpiEowhWYqwa3xCpnBmBqvkEQ8HqoKJJYT4eHcLaZCPb3RwDjPw9zclPK83oVvsiW5yjkA2ObtCgDwrlihuFmUCUElhWbsuxE8HtXBcG+sGrtl6lQgEsHQiy9hw2GHI9jZCUNlJSpOPinh9cRH0/XRRxBCoYTnQv39GPjPfxAu8g1FIRiE88234Fmem8JNowGiAsum4nOhbIaU0uXFAc5cbghFAoGoyhXqUs4BwDx+AoDUgCbZNDRPmghTi3qFJgmaGCoqinqzOV/QNU44HB1DkghnYbGQDTSgqTLIruQTGVcgj805ExUmOIpToWlkCs2MESIRDD73PHr/+teEv4GnnmaCk1FO7qq3MMYUYQ1FOrLBUMCUczK5NcV2x1hRoFRCg4NoP+88BLu6YBrfivFPPQnvDyvRedllGH7jTRhKy1D/h+tTFjf5qnCeLTTlPK1CM3EiRNLtBJ8PQjAIzmTKYStHH8TfyzwxmnIev89Tv2exGlzNItlQphyEHosEu7fS/w/19MISCyQXCrKw5svLYW5ugRvxAls5Od+WNgCAqakJnNmc8ryePpF6IFWcxDJlCvjSUkRGRuDftAnW6dN1Ox/x0DRJKLL4khJwdjsEjweh/n6Y0/hmh4eH4V+/HgDQ+sTjCHR0oOeee+GNBfoqz/oZeJst4T32efNgqKhAeGgInuXfoGSvPaPtGhjAlrN+jsCmTfCvX4+GG2/M+rPqjRCJYPidd9D7wIMItrfDUFWFaZ+PzdR5PaoFx22G8uunqpQuz5vN4MxmCIEAIi6X6mCjVqiHL8ep/g6lKp1H/H7ql2mZOBHBjuj/k/8qQYImJDNprMPZ7YDBAITDCLvcCZtMgHwhqVyTEGT3eNL6iyv5RI71TeBC/YZqMTGFZsaMvP8Btt10k+Rzw2+9hdYnHk+5pxmjA6bQZOgCHQBKc63QVK5+nCsEQaDpR2R3jO3mJBJ2udBxwYUIbNgIY309Wh9/AsbaWpQePB+Nd9wOcBwGn3kGfX/5S8L7hEgEvlWrAAC2ucWu0FROxYkrNJOqRooGyGJJ8S0WEhZbJOW8RD5FX2sFShqEzqHib7QR6o4rNEl6cSGhFcfHj6dV6XP5ewVJuvn41HRzQBzQ7M1ZG7QQr3Ie70c4nqcp4eH+ft3OJUQiCPVGP7dciimpMKwm4Ov97jtAEGAa3wpjbS3s8+Zh/NNPoeWRh1F7zdWoPv/8lPdwRiMc8+cDAEYWfQhANL7E1NzOl18pmoAzEJ0juD79DG2nLMTWa66l11h4YABCIFDg1hWGeOZO5gvEQhXUS5cunw8bGZJuzpeVgePVLdfME6J9WlAU0Ay0bQEEAXxpKQw1NXGFZqcKhWZ3NKAptbkxFuFEwWWpTdL4hmt+gyK82Uw3ytXcK0o+kWS+SjbgxxpymVbFAlmDBrd1p3klIxnXp58AAKxz56LitNOif6eeCr68HN4VK9B52eWIjNHxerTDApoMXciXb0zB0o8CASA2sJvGNQBgHprJdF93HXwrV8JQUYHWJx5PSOUsX7AA9Tf8AQDQ97e/Y+v111Oj+UBbGyIuFzirFZYpUwrSdrXwaQzh5RSanMkELpauVeypkvkmsGULEInQxRYg9oNK/a7CGg3bqUJzjPpBSSFOOQ8VQcq5uOI48Z/NrUIzdr7WVsnnSeGbcJEEzCISKedANA0UAMJDQ7qdK9zfH1Wm8TwNXCajJSXfE0s3J56fQDQo4DjwQNRccAF4CYUsAJQeGvfRjPh86Lz4EvhWrYKhqgqWqVMhBAK0QnoxsO2Pf0TH+efDt3o1+JIS1Fx2KRBTkOe6wFWxokf6bbwoUH7nfOE0mQBKY5RubYgVBNKiADXH/DHDTiftFwKb4+nmHMfR1wS7tqZNT6YKzQam0CTQDBKJOUW+7Lek0OKjqeQTKW77WBRuSBXhKyZMMbV0iCk0NSEIAtyffw4AqL3sUjTcfFP07083o/Ufj4Cz2+H+/HNsvebaFKsbPfH+sBIbjzwKa3feJeHvx732huvTsZnNoQcsoMnQhfjkL19VzvObfkQnLhxHfcWYH2IcIRzGyJKPAQDNf30IlsmTU15TdeaZqL3qKgBRdc3Gw49Azz33wP1ZdICxzpxJC0MUK+T6lprIJlbfTl2A8App1GOZwOY2APHFFqCsytG6eRK3CWABTUJQpNAkGwuFhKSAm8ePp6qIXCo0qSJ0grRC01BkHppyi2QS0AzpGNCk/pnV1bL9sRYFK0ktJ56fainZd19wViuCXV3YctbP4fnqK/AOB1ofexS1V1wOABh89tmiWHCPLP4IQy++BBgMqDr755j8wfuo/dWvwMcCUWGSOjzG0CN1M56Vk9+NwHRtp2NUDsfz8HD0utES0OTtdjpHJRs3gVhBIEvM0sVYXx9V84VCCG1T9uEjaa0mlnJOoRvbEinZYR1sFjJFi2pYySdSvAE/FjOK4t6/xemhSe7F8MAAIn5/gVszeghu2YLQ1m7AZIJ9990TnrPtvDNa/voQOJMJIx98gO4/3ihb8yEb/Bs2oOP88xFoa4Pg9yf8hZ1O9Nx7j2SxMUZ6WECToQuRkfwM4oVOP+JLSkSefIVfSBULob7+qIKV52HbeWfZ19VcdCHGP/M0bPPmQfD70f/oY9h+660Ait8/E4innAt+f0oaYUL1bYlUFUMBC1oVM8mLLUCkgJAqCiST1i/HWK/YKYU4oEn8EgtJcEs8BZws3nNZlV6sCJXCWFMLoHg8NMMe6eCKMVYRXk+FJrkepAoC0fPWqvMYFQIBeH/4AQBg3203xdcmw9tsKNlvPwCA74cfwFksaHn477DOmgXHwQfDPGkSIiMjGHr+eU3H1ZuIx4Ntf74FAFB97jmov+46GKuqAACG8mhl6rEb0CQbfNl7aOY7cB1XaUmnDhvyUOiPeGgayrV5dCb7aPppQaDoGMvxPEzNpDCQso8mCXiSysoM8fxESqEZ66vzXBQI0KYaThuwH8PzpkLZBqiFLy+nAediyLAZLbi/+AIAYN9lF/ASNiIl++yDxnvvAXgezldeQc+dd+kaXAx0dkYL5jqdsM6di8nvvYspixdhyuJFmPTWm+BsNvhXr6EqUjVEvF5s/f31CXP6sQoLaDJ0gSpIcuw5UqigUFg0+Bdqgl3MhGJFRoz19WlVlvbddsP4Z55G89/+BsvUeIq5UiC0WOAVUnGoAtBoBJdU5EL8XhbQTMSfVOEcUK6yGfd+UqnQpAGysTcxl0KIRBJUOcUwIY4HGFvjBQlypNAUBAGBdB6aJGCnozdlNsQXyblPOSeeqnL+mUBcwZouJd+3ejUEvx+GioqE+1stpYdE085hNKL5wQeoqoLjeVSfdx4AYOBf/y6o51XvQ39FaGs3TI2NqLnkkoTnaHB+aIwGNHVI3eRpynm+FZrK6fJ58dB0Eg/Nck3vI8pzokQnvrPEoxqAqNJ5u+KxiILfNI55aBLiCk0FD80C+C9qsWegXuQy7cxHwL5YCbukraOKBY7jqKdtOoU1I47782hAs2TffWRfU3bYYWiIiWwG/v1vjLz/gS7nDvb0oP0X5yHU0wPL1Clo+ccjMI8fD1NjI0yNjbBMmYKKhacAAPoffUzVMYVAAJ1XXgnnK6+g46Jf5kRROppgAU2GLpABIPcKzUKlH8V37HjRQM+k4VHI7pCpoUHV6zmOQ+nB8zHxtdfQeNedqL3icpQdcUQum6gLnMFAd/aSd67FxWqUPLdYIDyRwKa4vxchfo9JeGi65FOlpFDyuxqLJBcpCRU45TzidtMiNAkKzRxVpQ/19EQrGBsMMDU1Sb6GpFSHBwZy6qWkBiEUguD1AkgdX3MT0CQKzVrZ16j10CT+mbbddpPsE9NRfuwxqL7gArQ88jAcBx6Y+NyCY2Gsr0eotxfO11/XfGw98K1di4F//xsAMO7GP6aoPqhCc3iMBjR18NCMZ+Xkd86nVAVa/HguK0ET71WtVdRNMW/gQHs7BEGAf3OiQhMAzM0xH02m0NRMXL0oZYkzOjw006XGK6XV7+gUe5VzADCOY5XOtSCEw3AvWwYgamejRMWJJ6D6oosAANtvvTXrNVt4aAgd51+AYHs7TM3NaHnscZpdI6b6nHMAoxGepUtpZoscQjiMrb+7Du6P/wfOasW4G/+ounDcjsrY/vQM3chXmkVcueXOazCRKg1KHPEUpEiELjTHOrQSpsqAJoEzGFB+3HGoufjiovfPJMhN9NKlQuejiIAckUAAW845F9vvuDPv51ZCEASReiS+2FL00NRYFIgoNIVAgPkNQZRuHquIGuztLejGDFFLGioqYCgvp6qIXCk0iWrJ1NREq8ImY6ioAAwGQBAQGhjISTvUEvHE/aLzodCkiiwFhabalHzPN6Qg0LyM2sKZzai75mo4Yqnnyc9VnXsOAGDgscdpcRNBEDDy4YfYfMpCtF9woezCINjdja3XX4+NRx2NgSef1KzyFMJhdN94IxAOo/SII1ICrkA8oBkZoynn6YKCalCyH8klqj00c1rlPPuU89D27VE7HIMB5liaOQCYSGEghUrnYZeLigdM9fIWFGMNspkqtekW0eGazxQtm+aRND6R+fCILVZolfMiDmgSxTQp2sVQxrdqFSLDw+BLS2GdPTvt62su/iVMra0I9fSg94EHMz6vEAqh45Jfwf/jjzDU1qD1icdl+1JTYyPKjzkGgLJKUxAEbLvlFgz/97/x7BWNlj47IiygydCFdOkLekEXdMFgiodhLhFPUji7PV69lKntAIgUmo3aApqjEbo775JRaMoE2gwF8n8FAN/KlfAsXYrBAvvNJRPq6YkGbAwGWnkVUF7Eau1r+JISer8ylWa8wrl1+vTYA0GEBwcL1p5kP0sSgI64XGkr8GZ2vraE80nBGQzUB7HQlc7JPcCZTCkVweMBTf0CZqGeqFrWWKcQ0FThoSkIAryxgKbWgkBqqVy4EHx5OQJbtmDkw0XwfPUVtpxxJjovvQy+lSvh/uQTtC08FZ1XXkVVaqHBQWy/8y5sPOJIOF9+BYHNm7H9ttux6aij4Xz9ddXX3NALL8C34nvwJSWo//3vJV/Dl7OiQEB2XnQFTzmX89DMQ5G/CE051xrQnAAg2reSDUNzSws4Uf9hpinn8gpNos7ky8pSNlPGMtQWJWlTWxAEhN2FU/fRIKQKVWX663vsFlMspMpWLUQxzRSa6iDp5va99lQlnuFjqkcAGHz6aXh/WJnReQefeQbeb74BX1qK1scfhzmmnpej+vyolc7IBx9Q7+Nkeu+7H0PPPQ9wHJruuhOOAw7IqG07GqNDEsUoevK1KylO6Yq43eAtlpyejyBWGnAcB97hQGRkJDphZxvXCBIPTY0KzdGI3EQvnEY5GK/Wmv+AJlnUCF4vIl4veAmPz0IQIKlwSYutZCW2OF01fi+qU2hyPA++pAQRlwvhkRGaLjtWIfequbUFwe5uhPv7EerpoQG8fBOIFQQyjY9O9MSLiIjLRVVu+p1PuSAQwVBTg1Bvb8ELAymp3GhAU8eANLEgUCwKRFLO+/shRCKSqU6BzW0IDw6Cs1hUKSIygS8pQdVPz0Tf3/6O7uuuo2pWzmpF1VlnIdTTA+cbb2Dk3Xcx8sEHKD34YLiXLqUbG/bdd4dj/kEY+Ne/Eezqwtbf/g79T/wTdVdfhZIDDpBNkw9u24aee+4FANRedZWs4iJeFCh3Ba6KGT0CA3weAodSiLNypCDjeU49NGnKuUYPzdbo5mBkeBieb76NPibKgABECs0OeYUmq3AujVyhQcHvB2IWJYUoCqRFzZzOJ7KQGUWFJBIIQAgGAajPAioExphCM7itOIrBBLf3wP3pJ2l9HDnegJL9fwKTwvwiF5CCQOnSzcU49tsPZccei+G33sK2G2/EhBee15RJGOzuRk9M3Vn362thnTYt7XssU6fCMX8+XB99hIF/PoGGW26hzwmCgP5HH0P/P/4BABh3800oO/po1e3Z0WEBTUbWCIIQX3TleAAgHoYRjyc6aOdpEZ6sNKABzTGYjiFFaKs2D83RDN2dT5roRUbI4kN5glgIVa94py88MABexjsw39CAZlLBEBq8iSmxOdHGBU0H0qAG58tKEXG5mEITQCimpjY2NMBYVxcNaG7fDsyYUZD2JAcYObMZnM0GwetFeGRE94BmME1BIIKxpgZ+pPeJzDURBcVPTj00FVJMDdXV0f8JBhF2OiX9oLzfLAcA2ObOTVGW6knlz36G/if+SZXeFQtPQc0ll9AFU9UvzkXvvffB9fHHGPkgavBvmT49IWhZeeaZGHjqafQ/+ij869ah46Jfwr777qi79hrYdtmFnivi8WDgyafQ/9hjiLhcsM6Zg8ozTpdtm6G8AsBYVmhmv9EdDxzm2UMzTdppPgI+NKCpMeWct9lgHDcOoW3b4FqyBEBiQSAANP08PDQU7Wcl5u6hWLDEyAoCJcDTlPPEuRwNJHIceHv+N42Viikmk84mbKxWORd/XqlK2MUC2WQIFYFCUxAEdF5yCXyrVql6vW3nnTH+uWcz8tXOhIjXS7NFSvaRLwgkRf3vfgvX//4H3+rVGHzmGVSdfbbq92679VYIHg9s8+ah4pRTVL+v+oIL4ProIzhfex01l14GU30d3EuXoefee+H7/nsA0QBp5amnavosOzosoMnIGsHnA2JpWvnYleRLSuIBzTyRrDQwOEoQgrqd0LGA1qJAo5l4Wo+MQlPWk6hwO94kcAgAoYFB2WIo+SbQGU13I4oSQoIS2+VKUGLHiwKp72sMjlKE0D0m06eSCdLNh0aY6urgX7OG+iYWgnhAcwJ9zFBaipDXi8iw/so24qFpHq+c+kNViAVPOZeucA4AhlggMTIyAiEUytqHOOL30+CokoKCN5thKC9H2OlEuK9PMqApLgiUS4xVVWi88054ln+NqjPPhHnChITnrdOno+WRh+H5+msMvfQySvbdB2XHHpugKuVtNtRceAEqT12IvkcfxeBTT8Pz9ddoO/0MOA49BLWXXQbvt9+h769/pQWsLNOno/Huu8AZDLJtiys0x2ZAk6bfZlMUqGAp54X30IwQD02NKecAYG5tRWjbNvhWRlMlzRMTFZp8SQkM1dUI9/cj2NEBw6xZKcegCk1WECgBuWBfvAhWSUEKdCgVU0wm3cZwPiwVipGE31Chby80JKAZLAIPTfdnn8O3ahU4qzWtAtL92WfwrlgBz7IvUbL3Xnlpn+fr5RCCQRgbGlLmB+kw1tSg7pprsO3GG9H7wIMoPfxwVevckcWL4fpwEWA0YtxNN2rqD+zzdoVtt93gXb4cPXfdhbDTCfennwIAOLsdtZddhuqYfzgjDgtoMrKGBgk4DnxJ7ne0eIcD6O3N6wSXDOpkwpCPdKPRQsTrpSmPYyGgKWcIn16hWTgPTZJyDgDhwcIWORET7IqmPycHWFOU2EQRBu1FgYCoQjP63h0roBncuhXdf7gBjoMORNXPf67uPSK/W5JWTHwTC4FUCjhfVgr09CAsUxio59774P3he9RccIGmFCIhEqFFiNQoNIEiCGjSarQSAU1RoCPsdMIouk8ygagzOYsFfBplrKG2BmGnE6H+flimTk153hNTaNp3y6wgkBbKjjgcZUccrvga++67w7777oqvMVRUoP7Xv0bVWWeh96GH4HzlVbg+XBRdmMQwNTej9orLUXbMMWkXKYYx76Gp7NOnBvG4mWw/kktUe2jmMuWceGhmoFI3jx8Pz5dfxv+dpNAEoipNb38/Ah2dsEoENEnBEabQTMRAs22SNrULXB1bS5XzdHYQVIU6xqqcx4UJxeufCcSrnIf7+qNZTGmyIMJDQ+i6+mpUnHKK7mnK/Y9FC9hUnnYq6q+7TvG12/50Cwb/8x/0P/ZY3gKa8XTzfTIaPyoWngLna6/B++232H77HWh+8AHF10fcbmy75c8AgOpzz1WVap5M9QXno3P5cgy//Xb0AaMRlaeeippLLh7ztllyjKqiQF999RUuvfRSzJ49GyUlJWhtbcWpp56KH3/8MeW1a9aswZFHHgmHw4GqqiqcddZZ6O1NXbRFIhHcddddmDhxIqxWK3baaSc8++yz+fg4Owzinex8TDYLkbqb7GM2Vv1lpCAVznm7XbN5/WhEzhA+nqImUxSIpqrn2QssEKBKSEBfv71sCXZ1AUgNaAKiavLJaV0ZVKDcEQ3uQ/39aP/FeXB//jkG/vVv1e8Lxgo9mBoaYKwnlTILo9AMu1y06I5YMWkojQWCRlIVmoIgYODf/4bni6Vo/8V5aP/FL+BdqS7VKbR9e9TnzGhMq1KOF74pXLAXiCvTpLz8OKOR9rl6pJ3TdPO6urRjOa10LpGSH+rrQ3BLO8BxCSnbowXTuHFo/POfMenNN1B62KEAAENVFeqvvx6T//s2yhcsUKW4GOtVzvXw0KTvjUQgeL16NEsVtO1pPAbVpPdmSjzlPIOA5oTEDRvLxNSAZrpK58xDUxq5OaAeAfxsoN6eaeaYQjhM/YZlPd8LuAFfSOhvmOMCt9liqKwEZzIBgkCzBpQYWbQY7s+/QM8DysE4rXh/+AGepUsBoxFV55yT9vVVvzgXMBjg/vRT+Fav1rUtcrg//xwAULKP+s1vMRzPY9xNNwEARj78EKEBZVFI718eQqi7G6bmZtRccnFG53QceCCdO5Udcwwm//dtjPvjDSyYqcCoCmjeeeedePnll3HIIYfggQcewIUXXoj//e9/mDdvHlaujFeg6uzsxAEHHIANGzbgtttuw7XXXou3334bhx12GAJJlbGvv/56/Pa3v8Vhhx2Gv/zlL2htbcWZZ56J5557Lt8fb9RCqj3nawCgKUh5DCZKeWhGHx9bg70U1GepsSFv6olCYpCrcj6sfB8UStUbbG+nlhBANOW8WKABzcbGlOekNg3Efr1yC00p4grNHeN+DQ8Po/38CxBoawMQDSAJgpD2fRG/nwYQTQ0NMNbFglKxQFa+IX6WhsrKBLUh/b0kFJoRlysalAQAkwnuz79A2ymnoPOqqxIC91KQAkTmpqa06dlk4hgutIemKAVOCj19NGlBIAX/TAJRg0opWD0xvyrL1KkZpcsWC5bJk9H8l79g8gfvY8qHH6DqrJ+lVcKIGesp53p4aHI2GxALHuczKydduryW9N5MiAQCUTsnZJhyLlKgG6qqaD8hxkQrnUsHNEmVcyNLOU+Azk2SU87TFJLKNWoLaInvI7l7k27A70CbwGog8/pC/YZq4TiOqjTVWAaFBvqjr93SjkBnl27t6H80qs4sP/ZYVRl65uZmlB11VPS9MWVnLgn198O/di0AoGSfvTM+jnX6NFhmzQQiEbg+WiL7Ot+aNRh46ikAwLg/3pBxAVaO49D6xOOY+uknaLrn/9JWR2eMsoDm1VdfjS1btuDBBx/E+eefjz/84Q/45JNPEAqFcMcdd9DX3XbbbXC73Vi8eDEuv/xy/P73v8cLL7yAFStW4F//+hd9XVdXF+655x786le/wj/+8Q9ccMEFePPNN7H//vvj17/+NcKiIABDHrqTnacBgO4c5jPlPElpEG/DjhEgyYa4f2ZqUGpHRC4VJ141UnrxUagdb78o3RyIFgUqBiIeD22LpEKTfl/xCbXg88WriGoIaMYVmqO/2nDE60XHxZfAv2YNDLGiaEIgoOq6IgtUzm4HX14OU0yhGSxQQFOu4riSQpME0PiSEkx+578oO24BwHEYeeddtJ16WkIBLLnzmdL4ZwLRKufi8xUKpSrngL4BTXIdqKlAGk/JT1WHeKl/Zu7TzfOBuaUlowIRfKw6dXh4OG311x2NhGrB2QQ0OY4G8/O5GZhObZfr8Zyqejkuo+/PJFoAS6WbA4C5mVQ6l94IIoESE0s5T8Agyh4RbySmKySVa9QW0CLXLGc2yxZsiyuQx1YWWr4K3OoBmb+ReZ0S4f74vN/9xee6nN+/aTMttFd9/nmq30deO/zue9QCKFe4ly4FAFhmzMjakqf0kEMARP0x5ej5v3uAcBilRx4JxwEHZHU+3m5nikwNjKqA5r777gtzUuc7depUzJ49G2vWrKGPvfzyyzj22GPRKhrQDz30UEybNg0vvPACfez1119HMBjEJZdcQh/jOA4XX3wxOjs78UXMd4GhTL4HABI4zWcwMVlpQAIkTKEpLjKy4/tnAgqG8NTbMY3Jep6vmUBSgCdUJB6awa1R/0y+tFRSgULvc9H3leDXqyHAIJciNtoQAgF0Xn4FvMuXgy8tResTj9M+SU01brr5MG5cdIefTIiLLaCpoNAkClNjTQ3Mzc1ouusuTHztVVhmzkR4YADt551Hry35801I2zaaUl1wD81YaqBsQDMWNNNFoUlSztMHMEhKflhBoWmfl9uCQMUOrU4dieS9qE2h0bNacCEsftKly8eLprhzEqwmql6+rCyjAjNiRY8lqSAQgSo0JVLOI243LcpmZCnnCdC1TihEVbRA+kJSuUZtkF2NT+RYzUKLjBIPTSB+XwZVVDonCk0A8OgU2xj45xOAIMBx8MGwTJmi+n3WGTNQcsD+QCSC/iee0KUtcsTTzbVVN5eCBDTdn32GiIT9SbC7m56v7pqrsz4fQxujKqAphSAI2L59O2piUeyuri709PRgdwnz9z333BPffvst/fe3336LkpISzJw5M+V15Hk5/H4/hoeHE/7GKvEBID++MYXYrZfz0GRFgRKLjIwF4rvzyVXOSVEgOYVmgQKam6MKTWPs9wkPDuXlvAPPPIOua38NIcnmg6DknwlI32MJfr0aFnk0QDaKFZqB9nZ0XHop3J98As5qRcsjD8M6Y4aiUi6Z5M0HUhQo3N8v+zvlElpxPMnvjacKzdSAJgkwGmrjO9fW6dPR+sTjME+ahFB3N9p/cR5C/f2J7xschGf519HzpSkIBMQDdhGXCxHRojXfxFPOpYNCVKGpgzcu9dCsTx/QpArWpEB6xOOh3lj5KAhUzPBWKzirFYB82rnr08/QcemlCG4vzKZCrqDXrd2edbVgcu0XIitHvsp57HFBQMSjv7cn9c/M0LKBt1phjPXz5knSAU0S9Ax2bYUQy3wgkOuRdziy8kDdEeHtdiBmrxRJmJ8U2ENTNMdUsqChheYUbMIMMmn1OzrUNqDIPTSBuHI6GLP9UiJRoblU9SZMaHAQnZdfge6bb05IbQ9u74HztdcBANXnn6+l2Qnvcb7yatpN44jHg65rf43um26i681kwk4neu65F5tOOgmbTjiR/g3/9x0A0YJA2WKZPh2mpiYIPh/cn32W8rzz9TcAQYB9jz1gjvkTM/LHqA9oPvPMM+jq6sJpp50GAOiOXewNEmqxhoYGDAwMwB/z3+ru7kZ9fX2K7x9571YZlQcA3H777SgvL6d/LWP44qUDgEwxFL3hRTvj+SK+qExKOWdFgRDsjlWqHisKTYeMITwN7CsXEYh4PBDyaGfh39wGALDvFt3kyUfKebCrC9tvvwPDb70F97IvpV+zVbrCOUFKlZOpX+9ortgZ6uvDtlv+jI1HHwP3/z4BTCY0/+UvsM+LBouo16MKJSG9V2PBbUNlJWAy0fPkm/QKTYmU816i0KxNeNxYWYnWJx6HqbERgbY2tJ9/AcLDw4h4POh7+GFsPOxw+FZ8DwCwzk6t6JsM73CAs1ii5+zrT/Pq3JFWKZYLD8262jSvlFewupctA8JhGBsbJL1xxxoGWrRJOqA58M9/wvXhIvQ/nns/sXyiZ+ZOvrNy1KTLc1YrEPPhzUW7SAA8Gw9a2y47AwDs83aVfN5YVxctLBIKpai8qDc6SzdPgeP5+IaraE4RXwsV1kMTggAhVvRHChKkVLIJo0UZ3W5V/tw7CtQ2oMg9NIG4t21IjUJTlJkVHhykvpJKhF0udFxwIUbefx9Dzz6HjYcfgZ7/+z+EnU4MPPlvCMEgbLvvJtu/KGHfYw/Ydt4ZQiCAgSefUnxt71//iuG33sLQc89j4xFHYvtdd9P5TsTrRd+jj2LDYYej/9FH4V+9Bv61a+mf4PXCUF4O+27ZZ4twHIfSQ2Np5x8uSnhOEAQ4X30VAFB+4olZn4uhnVEd0Fy7di1+9atfYZ999sHZZ58NAPDGZMCW2EJEjDW2U05e4/V6Vb1Oiuuuuw5Op5P+dciYao8F8u0bU9j0o5LYf8dmOoYUoa1k4js2ApoGmZRzch+QYEwy4vsjojDZ1BNBEBCIeWgStVQ+Apr9//o39bokCtFk4gpN6aCHVPoU/Y41bp4oBciKlYjXi94H/4INhx+BwWeeAUIhlPzkJ5j4wvNw7P8T+joDrcatPuWcKHc4joOpNhqYUmMsrzfEP8nUmqTQVKhKHxKlnCdjGjcOrU88DkNNDfxr1mDL2edgwxFHoPf+BxBxuWCZMQMtjz4K+67pJ+Acx4mCxfpVOg+PjMD1ySdwffxxwl9QxgeLbNzJja/GykoAQEhPD00VCk2jzHU3sig60S+df3DW7dkRoJXOh6UDmqRC7fCbbxVEJZ0r9Ey/zXd2g/g8cunyHMfBUJI7H80IrXCeeUCz8bbbMOntt2DbeWfJ5zmeh6k5mnaeXOmcVjhnBYEk4SWKQ8YzuQrjv8hZrUBMDa3ko6lms4Het8FgvAjfGID2W6NBodlAigKp99AkWTnuNGnnEZ8PnZf8Cr6VK2GoqIBt3jwIfj/6H3scGw47HIPPRgsnZ6LOBKL9Z/UF0fcOPvusbLajb+1aDPzr3wAAy8yZ0QDoE09gw2GHY9ufb8XGI45E7z33IjI8DMvUqWi8+260PP5Ywt/E11/L2vaE4Dg4GtB0LVmSoGr3fvsdAlu2gLPbUXbE4bqci6EN5TKfRcy2bdtwzDHHoLy8HC+99BIMsU7cFqso5ZfogH2xtDHyGpvNpup1UlgsFslg6Fgk3wMATT/K1+Q2EKALDTIBGKv+MskIgjDmUs55kSE8QQiF6I643CSRN5vBmUwQgkFEXC5NVbozJdTbG71GeZ4uakI6pKYqnnNwEEMvvUT/nVyUiBCIBTTNMgrNuEeZSAExkpnqhwbIRtH9uv2uuzAUmzRa585F3TXXoGTvvVJeR5VyKjw0QzTlPB5ENtbXI7h1K/VPzBdhlwvhWFq4OalIj6JCUyGgCQDmCRPQ+tij2PLzs+GPeWubmptRe8UVKDvmaE1WBcaaGgS7unRTrwrhMDouuBDe775Lec5QWYmp//s4qpgSESbpgTmuci4IQjzlXENRoPDgIIRgMNq3hcNwLf4IAKiSYayTrtI5ubbCg4NwffIJ9eka7dC0Vh3Sb6nNUJ6yctSmy/MOB8JOZ07mgWFntO8jhaUygbfZYJk8WfE1ppZmBDZvRqCjAyV7x6sAh2JBEqbQlMbgKEUI3QmbboX20ORiBaQiTmfs/pPux9X4RNK0ekFAxOUCHxP67OhQ9eoosFlQq9AUBAGhmJCh7OijMfCvf8H9+ReoPk+6kI8QDKLrqqvh+fJL8CUlaHn0UVjnzIZryRL03nsf/OvXAwAsU6fCceCBGbffcfDBME+ahMCmTdh+2+1ouPXPCRmzQiSC7htvjBbZOeIINN1/H9z/+x967r0P/nXrMPj009HvobEBtZdfjvIFC7K2N0mHfbd5MJSXIzw0BM8336AkZlHofO01AEDZYYfJztUYuWVUKjSdTieOOuooDA0N4d1330WjKK2JpIt3S/gsdHd3o6qqigYiGxoasG3bthQ5PXlvI0uXUgXZoczXAGDIc8q5+Dyko4pXExw9AZJcEB4YiAZ7RQVGdnTIJFDwemlamnhSq3Qf5DsQTgoCmVqaqYF4ZHiYtjsXDD79DASvlyoFArGU92SCXWlSziXusUz7mriH5ujwgxIiEYy89z4AYNyNf8SEF56XDGYC4mrTKhSaMRWg2B6CBK/yXRiIVObky8pSgvvUQ1PiPiFeocZa6YAmEDWdb330Hyg5YH/UX389Jv/3bZQvOFZzcQ29K50PPv88vN99B85qhXXOHPoHnkd4cJCq9cTQRbJMCpxeAc3I8DAtcKEmoGmoqIje44KA0EB0k8S7YgXCAwPgy8pgl/AxH4vwFfIBTSEYTPA+JYuiHQGa1aJD6ma+s3LS+WcScumlnq2HplrkKp0zhaYyUoUGC+2hCUCValhNajzH8/GNhFEyb9IDuoFYIJWtFoiHZqi3N8UDV0zE5QJic/6yY48FAHi+/hoRCUGXEIlg6/XXw/XRR+AsFjT//W+wzZ0TTbeePx8TX3sVDXfcDseBB6Lhlj+lWPZpgeN51P/2NwDPw/nKK+i5866EeMzQ88/Dt+J78CUlqP/978FxHBwHHoiJr76CxrvuRMm++6D+ut9h8rvvouKEE3IezAQAzmiEY/58AIArlo0S8fkw/N//AmDp5oVk1AU0fT4fFixYgB9//BFvvfUWZs1K9MJqampCbW0tvv7665T3fvnll9hll13ov3fZZRd4PJ6ECukAsGzZMvo8Iz35TrPgc5jmIwU5DyfarVdbTXBHJ9gd28WvqQFvNhe4NflBPAkk1z69Rmy2FIWVmHwXkyLp3paJk6ILo1hARy74MbJkCTovuwyuTz/LyDcp4vHQXdOqmA1IQEahqbYokHgRG85UoVkqn8JcjPjXr0d4YACczYaKk09WnDSqDWjKqamN9SSgmd+U86CCX2M2Ck2Cbeed0fqPf6DqrJ+By7BvMsoUvpEiPDKC7htuwMCTT0reO8GeHvTeex8AoO7X12LiSy/SP6NoYZJMPOU8twpNEtDmy8tVqXE4gwHGqqroe2NBZuIr5TjwQMV+cCxhKCNV6FMDmqGBQUB0rYx8tIQqaUY7yYUUsyHf8y21badjVA68mcMxi4JsUs7VYIr5/wc62hMeJxtOTKEpTdx2SqzQLKyHJiCaYyrMddTahNGg7RiqFTCaqpwbqqujPr6RiOL8j2TC8CUlsM6eBWNtLQS/H16Jwsc9d96F4TfeBIxGNN1/H1UgEjiDARUnnICWRx6GTYcYSTQwegsAYOBf/0L/ww8DiM6FemLzpdorr4SpPr7JyvE8yo87Dq1PPIGqs8/O+9rTcUjUTmdk0WIIgoCRRYsQcblgamyEfc898toWRpxRFdAMh8M47bTT8MUXX+DFF1/EPvtIV606+eST8dZbbyX4Wi5atAg//vgjFi5cSB87/vjjYTKZ8Le//Y0+JggCHn74YTQ1NWHffffN3YfZgcj3AEAH7HwZxFOlQXxByTw0o5AiI8Yxkm4OAJzJBC5mR0F+f7VpKvlWmvhjCk3zpEngDAaa/kgUVckMPPY4Rj74EB3nn4/2c38B7w8/aDrf0EsvIex0wtTaipqLLoyeq7c3ZXId8XrpJEuucIjUIpZ8z9qLAomqf6qs7lhI3J99DgCw77F72mCcnJdhMuGhoahyFqBqXSDulxjMt0KzJxoEM9WlLpiVAtDhWHDRkCagqQdqg8URnw+dF1+CoRdfwvbbbkf/I4+kvKbnjjsQcblgnTsXlaefnnge4mMq8RvEC9KlC2hKpzSrhVQ1NqlQZ9Jz18YLUkUn9h8CwA6TNq0HNOVcMjhP1Ma1sM6eDYRCGH7r7by2L1fo6qFJNrHzlnKuru10jMrBXDRCU85zG9C0TJsKAHAt+ZhuMgLxDSfTOKbQlCI+Rok8vt2FD4apmWOqtQkz0DnY6NgI1gO63hsFHpocz9PxOiTjwQ2AbpIZqqrAcRyt+O3+PNFH0/3llxj4d9SvsvH221EaUyLmmoqTT0L9db8DAPQ+8CAGnn4G22+/A5GREVjnzEHlmWfkpR1qcey3HziLBcHOTvw/e+cdJklVd/9T1bl7uieHnbizOcMGlt0lBwHJKEFBUViC4RUR1J9gFnxReUExgQIqQSXnDEtaNrJ52Zwm55nOuavq90fVrQ7TOffM/TzPPLAz0901M91dt84933O8Bw/C+uJLAIDySy9JeQqIkj1K6jd/++2345VXXsHnP/95jI2N4cknnwz7INx5553Q6/U444wz8Kc//Qn33HMPrrjiCixcuBDXXXed/H3Nzc249dZb8Ze//AU333wzHnnkEVx00UVYu3Ytfve738m5nJT45PsEwMqNl/kpVok2fhQUVSdXA2Akgf7xmXyTAVnQlgQXziYJbQkuPuRxoDyJ8cQdqZnWLj6+5KjizNFdQKHFJK6NG9FxxZXo+e6tcK5fD9eWLcGPrVvHhc4Lfj9G//kvAED19ddDUV4uCzW+Y8fCH0dqOGfLymL+zqJtGnDyyHmqpUDSY/B83gqZMoEEthtWJt5UC4pu8YtryGtVURvuppZHzvOcoRls1B4voJG/V6QALXCcvDhP5NDMBsmIxYLfj97v3grXli1yK/rwHx7A2L//LX+PY+1a2N54E2BZTPnlL8aNRpHXSfSR8+RbzjM5F8n5mSlEhwSfe6PwHTkCf2cXGJUKhpNPTnDLyUMwQ9My7muc9LxS1Nag/NJLAUycsfNsjt/mewM5GG0S/9jl9vWcjpynn6GZDIZVq6BftgyC242BX90lv4fIDk06ch4VNko5ZKJ4kHyQjJs5+Q340ssezxSyxiwFhyYQ3Jz2x8nRDEjmATJRoV9JBM318vfwPh8GfvFLAEDFl65C+UUX5uR4Y1H1ta+h5lvfAgAM3n23OMLNsmiIsl4qNKxeD8NJJwEAzP/5r/x7JOdwSmEoqVKgHVKQ/quvvopXX3113Ne/8pWvAABaWlrw0Ucf4bbbbsOPfvQjqNVqXHDBBbjvvvvGFfn85je/QWVlJf72t7/hX//6F2bOnIknn3wSV199dc5/nolCvk8A+R45jzZ+FNYA6PPJF7KTDb9cMjJ5HJqAtDs/PCzvzieb7ZjvDE2vNHKunjYNgNiI7EP0pnOB52WRqe3JJ2B59jlYX3kF9rffhv3tt8d9v6KiAtU334zKq78MVqOB9fXXEejvh6KmBuWXXSo/bmB4GN6jR6FbtEi+bei4eaxx6mhO7HRLgRiNBlCpAL8fvN1e1IHvvM8HlxSZYkhiSoA4FbnRMQgcF3PxJ4+bN4S/VpWSQzLvGZpxBDT57ysVEhCBk7NYAI4TbyctznNJIrFY4Dj0/egOOD76CIxGg9ZHH4Fz/XqM/PVBDN51NxQmE4xnn42BX/4KAFB17bXQRsTkALEFTd7nk/NuY51fiaCJQCCjsjESOZBMfiZBLqQaGZHHzfWrViYUgiYTZGQ4WoZmaHyC6cILMPi738Gzdy88Bw5AO3t2Xo8z22Rz/FbOU87TRqC85ksgTOUlQzPHI+cMw6Dhl7/A0Usvg+Ojj2B/512UnXaqHGFBmpQp4ShksW/8yHlBMzSjlClGkmxOZC4jFYqVoDu7+DM0ATFH041giVc0OGkiS1FdDSC4Ue7ZswecxQJFRQVGH3kEvqNHoaipQd1tt+X8uKNR853/AWezBWOrvvoV6ObPL8ixJMJ41plwvP8+LE8/DQDQLVsKdWtrgltRcklJCZoffvhh0t87f/58vB3lIjwSlmVxxx134I477sjgyCY3+T4BBMd8RHdkJqHEyRD8+YKLFFavD/m6A+xkFTT7J6ugGb5oTNahmc8MTd7tllut1e3hDs1oTeekrRgMA91xx0G/bBmqrr8eI3/5i9xqKH+vww5ueARDv/0txp54HLX/8x2M/fMfAETRhrwe1NPa4dq0SS4nIiTKzwSij07JwnGKbnCGYaAwGsGNjYGz24v6+eresQOC2w1FdbU8DhgPZVWV2EbK8+AsFiilRWsksTYfSIYlEbPzhZ8IaPXjBTRWrQaj1ULweMDZ7LKgSQQgRWVlXjIa5SbvKBmagiBg4K67YHv9dUCpRPMfH4B+2TLoli4FZ7PD/OST6PvRHTCsfAX+nh4op0xB7Xf+J+rjyGNjkYJmaJrlMAQAAQAASURBVCFdyDknFFanA6PRQPB6xYuTNAVNOdM0yt8jFqEj+e6dOwHQcfNIiEOTjBCHQrJZlTW1UFZWwnj66bC/+y6sL74E7Y/+X16PM9vILefZKAUq2pHz3EXI8HKGZm4dmgCgmT4d1TesxuiDD2Hw17+Wz8uMXp/y5uFkIV4pUEEzNJMoLE02JoyssyZLtJYgbaAChRWlU4E4qEmfQTS4McmhWS2u/1X1dVDPmA7f4SNwbtoM7exZGH1IjMmpv+NHOS8iiwXDMKi/8w6wxjL4O7tQ851bCnIcyVB2xhliJ4E0QVRBy4AKTkkJmpTiJDi+kJ8TgLxY4HkIbjeYGBd62SJaIyCjUIDV68G7XOIJMIaIMNEhgqZyku3ik9158txPVmgLjgPl/sLM19EBQHRwKSsrxf+vEv/LRcnQDC14ImKRdvYsNP/xgXHfKwQCsL70Eob/9GcE+vrRf+edAMQFcuWXg/mAmnbRGUrKieTH6ovfcA6EREuEjpzbk3MWRL0/Yxm4sbGibzon4yuGlSuT2qxhlEooqqrAjY4iMDISW9CMsflAxDTe5QLncObtfTyYoRldQFMYjQh4PODtNgDi8yTZQqBsoQhxIEZuno385a+wPPU0wDBo+t1vUXbaaQCCi3Lebof15Zfh/OQTAEDDT34cMwczpkMztGxMGXu5pqisRGBgQHRVSSUfqZLo7xENZY34XPPs2QPPrl2A1IRKCcKWx245l0cBpedz+WWXioLma6+h7vbbSrpYictmhmYez5vi4yRbCpS7aSEuTxmahJqbb4bt9Tfg7+rCwM9+BkDMV861YaBUCYp90hrQ54Pg8wEohQzN5GLCguJoca+ZsoXgcskCVbobg/mGOKj9cRyagVEpQ7MyONViWLlKFDTXr4fl6acg+HwwnHQSTOefn9sDTgDDsqj77ncLegzJoKyqgm7JYri3bAWj1cJ47rmFPqRJT0llaFKKD4Hngy2seToBMDpdsK05H063GONH+W6sLkZIKdBky9AMNklGODQTCG35zALzHg0fNwdE4QOInqFJRlaUSZQAMEolKi6/HNPffgt1P/i+fNFeec01YQtB8tjeyAxN2aEZ+3lDhDXB65UvFNItBQIAhVEa/Sx2QZPkZ6ZQSpdMG7f8Wo0o8GINBvn5nM+mczlDM0ZmI7mQJ68tIJg5SLItcw0R7ASfL0wI5xxOjP797wCAhp//bNxFAMOymPLru1EmuRWNnzs7rnMxpqCZoOGckI2m80R/j2iQ55172zYAYrM8+VkoIoryCgCxRs6lUiDp91h2yini5sTICBySEF6qZNPplO+YoWSPPZnx3nQhz5d8ODQBgNVq0fBzUcj07N0LgDacx0POlySxQ6Fu+hgbV/kgGZE92ZiwydZyLl/LKRRgtNrCHkySEIdmIE6GZqRDExA3zAHA+sILcK7fAEajQcPPf0Y3MFKg/IILAACmCy8o6hiryQJ1aFIyIuwknqcXNMMwYA0G8Ha7eKJN3lCSFtEyNAHpZD80NGlO9pHwPp88ihkpkkx02MjdeeJSNiXKJJIWiHnIAvPJDeft8ueU0g5ttJZzUgikSuEihtVqUb16NSquuALuXbthWLki7OukjMjX2QUhEJBdZr4URs4BsXxLqVYHS4HS2DyJFuJfbHA2Gzy7PwOAcb/LeCirq+FF/GKgAHHgRhm3V9bXw+dwIDA4CE2IAJ4rBI4Lui3jODQBSA5NEXnkPE8OTVarBWs0grfbERgZlUexnJ98AsHng6qtFRVXXRX1toxSieYH/gDXtm3QL14c93FkQXMoukNToc+DoEkyTWtTaDmP+DsYz6bj5pHEy9Dk5JFzUThnVCqUX3QRxh57DNYXXyppt2s2x2+DwmGeHJryVE6C83kS471pPb7XC8HrFY8hj+OfZSedBNOFF8L22msAABUtBIpJ5HpCdtPr9QUtMZHPm/FGzpOMCZPF0SJeM2WT0PesUhH2yHo9rkOTZGhWBad39MuXAwqFnNFd881v0gzIFKm46iqoWluhX7Kk0IdCAXVoUjJEPomrVHnNkWTzuMCNlqEZ+u98NVYXG8TRw2g0svNvsiAHwpOWc0dyDs1IZ2cuIWPeZOwbCGk5j1IKRHZ402k1VZhMKDv5pPHtzQ0N4k633w9/T4/8eX+v6BZUxxE0GaVSdGMj+DpPNvsp6jFG/M2KEeemTQDPQ93enlLOJ3EscnHauIMj5+NdsSopNzFfxUCB0VGx3IdlY47Is9LmQKhDMzRzMF9EKwayvy8W4BjPPCvuhQ+jVMKwfHnC0WEiaHKjoxACAfnzsTbTIpEFTbMl7vfFgvd4ggJzShma4X+HsjOpoBkJcdgJHg94SaQiRBPoSaGa44MPooqgpUKyY9vJkO8yvWTH5XOVoSn/3Rkm7+PL9T/6f7I7njo0Y6OQJ7TCBU1FAd2ZQHIFWsnGhCnyuAFfDMgTQCXktiMTVYGhYQhSYWIk3Oh4h6aizADdcccBANQzpqP6+utyfKQTD4ZlUXbSSWCl6xRKYaGCJiUjuAKdAFiDmJuZjxNtLKeBIkrG32QitGSkVHYzs0Vwd14aN5JLgZLc8c7LyHkUhybJ0IxSCkR2eFNxaCaCYVm5kIgcD+/xyMKbqjF+VEGkQyC4EE/9/Yb8bXhb8QqaLjJuLo0DJYsiwci54PfLYmU0NzVx5fkH8yRoSo+jrK6OmQ1JIgKiOTTzlaEZ+ljkOSv4/XB8+BGA7DkSFVVVYoyKIMh5V0DoyHkiQVPKaUzToel4/32A56GcMiWlkfHQ0X/1tGmyI5sShC0rC0bkRAiUwedz8HeunTMHmpkzxOfZxx/n70CzDJfkczcZ5JFzlwuClHGXS5IdOc/V+Zy3BfMzGTa/l2nKmho03vO/0C5cWPA8vWImshSoUNdCkSQS2cOyPhNMuuRzA74YkDcySiQ/E5DWJwoFEAjImcyRBCQDAzE0EKpvWA3tggVo/M1vwajVOT9WCiWXUEGTkhF8gU4A+RQTY+XNTPYMzViZfJOB4FhPuEMz0Sh0vjI0BZ6XS4E07UGRIV7LuezQbMju35M8PnGMkkIg1mCQszdjEfo6571eeTwmnfcb2W1QxAH3zvWSoHlS8vmZQFAQCcRwaPoHhwBBAKNWj1vUAsHcxLw5NIeHwh43GlEdmnnO0Ax9LPLYri1bwNtsUFRVQXf88Vl5DEahCMlBDTpB5fNrAtdPpiPnlhdfAgCUX3pJSptTbFkZGGkyg7abR4dh2eD5IkTQ5N1u+TwQ+Xwm2av299bk6SizT6zs8XQIXXvxLlfG95eIZMflc3U+5yRBs1Btw8azzkL7s89AO2tWQR6/FJD/9vLIefYE/ExIJLKHfj7ReYWdZC3nvHytVxoN54C0diCRNYPjczQFnpcNDJFrP+OZZ6L9uWehWzA/9wdKoeQYKmhSMqJQJ4CCjJzHKAWarBmaAbnhfPIJmuMC4YlDM8kd71w7iwP9/RA8HkClgqq5Wf58sBTIPM7pkguHJhBSDCSVFPlD8jMTiSehmwapLMSj3pcp/G9WbPj7+kQRmmXFfKMUCI5FRxc0A9Lmg3JKQ9TfOcmxjLYgzgVyAU2cRu1giVOoQzO8RCUfKKrD3a/2Ne8DAMrOOD2rWWnBYqCgqJx0OYksaI7fqEiEf3AIznXrAAAVl16a0m0ZhoFm+nSx3Zy2fMaEJQ5aW8hzWXLTMBrNOBGEiMPOtWvHjamXAoLfL55/kLhJORkYtRqQYhvyIa4k33JOxntzM3JeKEGTkhiy1hP8fvA+n7ymK7QYlkhkl5/bSWR9Bu+reDeBs0lwI6N0HJoAoJLGzkmUUyic1So3tysnWTQYZXJBBU1KRhTqBEAEjby2nMfK0Jwku5eRBEfOJ1fDOTA+ED5Zh2awRCC3Irg8bt7WGjbSK2edcpw81gYAgiCEODSzWwQgFwNJx+RPohCIELppIOcbGQxpCUnRSmaKCdJurlu4MOXSo0gXYSTx8jOBYG5ivhyaflJAEyevUX6Nhbacyxma+R85D4yMQBAE2NdI+ZlnnZ3dx4nSdE427BI6xTJwaNpefQXgeeiWLIG6rS3l2zc98Ae0PfkEdXnEIVrTOfk7K2tqxm0yaOfPh7K+HrzLBdfGjXk7zmzBZbj5FAnDMFDopZihfEzlJDkuH5rtKQhC1h6fnJtJoRSl+Ah9XosFpcUhhiXKm01lNF7euJ8kpg0ug4z2QkJMC/7ennFfI/mZivLyhFneFEopQwVNSkYU6gSQT3dkzAzNPAfVFxtBkWTyNWESwUkOhCcOzWRbI3P8nIlWCAQArFotv3ZCx845i0VuVY3nmksH4tD0RXFoJiK0eEt+r0kz3iLSVVtspDtuDiR2aIbm3UZDJf3N/fkaOZcyNFVxRs5lhyZ5jfl8QedSgQRNz969CPT3g9HpYFiVWs5pwseJKmiSsd34ohBxXgRSFDQFQQiOm0tlNKmibmmBfunStG47WSDFQJwlRNCMkwfLsCyMZ50JoDTHzokQz+h0MTNyUyW/UznJjcvLa0KOkx2p2YCzkgzN+JEslMLBKBTBbFe7PekCt1wTOtUSTWRPJSZssracs1lwlecTdWsLAMDX3T3uaySTO1rUEIUykaCCJiUjZLEvzyeAoNCR+8Ut54y+UCGL3cnSABhJUNCcvCPnvF1cNJLFrCJBKZAiR46OSMh4NxETw46BNJ2HCJqBAXHcXFFdDTbL4eDqtjaAYcBZrQiYzfJYTDKCZliGpuyCTe+9RiGXAhWfQ1PgedmhmWohEBAURXirFbwU+B9KoteqnKE5PJyX0g3iBCVlRNFQRJQ4EacBlEpZIMoHoe5XBxk3P/lksFptlh9HEjSHgoIml6ywkqZD07N7N3xHjoDRamE677yUbktJHjI6HOrQJCVTihh5sKQx3v7BB3l5TWaTZKMSUiFfmeVh4/IJjp/R6wHJXZvNTcpCZ2hSkoOIgpzdUTwZmob4InsqMWHyVIvTWXLvQekgrzFLzqEpCpr+7igOzTHJoVlNBU3KxIYKmpSMkAtzshD8ngryzmheRs6j72gGF9iTYxwjFEEQJnWGpiJk5FzweoEky2rkxa4gQMhhuQEZ747WOkzcXNxYsE3ZLwma8Rxz6cLqdLKQ5jt6NMShmTiqIPQiNjgqlaFDswgd1d6DB8GNjYHR66E77riUb8+Wl8sZc1yUpkv/gCRoxijwUtbUiBfmgUDY8yJXyBma8UqB5AxN8e8uO9qqq/Pa/Bt0aA7L4+Zlknsuq49TF82hKb5HJG45rwAQ7gBMButLLwEAjGefnXLMASV5ZIemLdShKb5OY8UnGJafALasDNzICNw7d+b+ILOIvNGdxXVhcM2X2/VW6CZ5Imc0wzA5EVrJ84SOnBc38jrQYc+JiJ8OrF4XV2RPZTQ+dL2ajzKuQhN02ZbWuVDdIo6cR3VoSus5ZVV1Xo+JQsk3VNCkZETBWs7zVK4iBAIQ3G4A4xe3k20cIxTeZpMXOJPSoUl2rl2uoCuKZcFKOV+xYLRaQMp/zKUQ7j0Wx6FJxlNDhCtZYMpyfiYhtBjI15duhmZm40DF7NAkQpn+hGViAUaKMAwTd+zc3yUudFWN0UVkRqmEokZc8PrzUAwkOzQlES8akX+veCO6uYSMt3PDI/AeOAAoFCg77bSsP45czBTWcp7cyDkRNAWXK6pDNxq8zwfr628ASH/cnJIcCqkUKLTlPPh8jv4aYNRq+XnmWFNaY+e5GL/N11QOOS8zWm1SmXO5iD/i5ZFzKmgWM8EYG3vMaKp8w7Bs3I6BVGLCGI0mr2VchUZeY5ZQyzkAqFokh2ZfH4RAIOxrnDxyTguBKBMbKmhSMkIu6sh3y3meylVCF8+KiIvKyZyhSUZYFVVVWR+9LAVCF63kd8GWlSV0joU6OnIlxnN2u1yeom4f79CUR87HgiPnskMzyw3nBLXkFPXu2ycfWyxxLZTQzNHgOFCaDk1jcTo0BUGA9aWXAQDlF1yQ9v3IguZwuKDJu1xiezoAzaxZMW+vqpPGznOco8l7PPLobTxHcEyHZp4FTWVVlex4AQD9smU5aQuNmqGZpOuHNRoB6b2HM1uSejzH+x+At1qhbGiAYcWKNI6YkixEmIqeoRnbOSPnaEpRB6VCLsZv87XeCo7kJnfsCvkclb2N7eDIOc3QLGaC5ZCOYDRVnqfVohFPZE8lJ5JhGPm6ZzIYN4IRaqXl0FTW1YmbL4EA/APhG9IBaeScOjQpE53spHVTJi1ElMn3CUAeP8rxbj05wTEazTjnlDxqNAkzNBOVjEx0GLUajEYDweuVR++TfQ0oDAYx6zBHF2a+Y+K4ubK2NqpbQCnt1IZnaJIR4Nw4NDWSQ9Oxbh0AgNXrZVdZPEKd2JmWApG/j+B2Q/D7i6bx0b11K/zd3WD1ehjPTr85O3Q0OhTvoUOAIEBRWxNXDFTW1QF79siFPbmCCHaMRhPXgSQ7NO12CDyfMHMwVzBKJRRVVfIovzEH4+ZAiKA5MgKB58GwbNIt5wzLQlFeDs5sBmexQBWnPZ5gffFFAED5xReDkVzjlNwgt5yHuMPJ6zTea9Jw6qmASgXfsWPwHj0qv48WOznJ0JTXfLkWNMm4fHLHHtxcz+LIOSk/y2NWMCV1yOaqOHJeHBma4jHEfq3IG8NJCq9sWRk4i6XoNoJzQbEUO6UKw7JQNTfDd+wY/D3dUDcHp59khybN0CxaOI6DX4otm4yoVCoosrAGpYImJSNkkSHfGZp5aovm4ixS8tm0Xmz4+6VilxiZfJMB1mgE5/UGHZpJCm1sjp0m8QqBAEBRKS5sAuYoGZo5aqxXS23r/s4u8XGamsCEuN5iEZpPRhwC6ZYChb6GOYcjJy67dLBIwpLx8+cljCyIR6yRc8++/QAA7Zy58W8viWC5dmiG5mfGew7IrydBAO90ys7TfDs0yWMSQZOUtWT9MaqrgzmmFguUVVUhrp8kChwqKkRBM2SjIhaB4WE4PvkEAFB+6aUZHTclMXKGZmgpUBLPZ0VZGQwrVsC5di3s762B5qYSETTJRndWMzTz03KeqqiRi3UgzdAsDcJLgYpnXDm0TDES+fmd7HqVxCtNAkGTL1FBEwBUrS3wHTsGX3d32MQFWecrq6lDs9gQBAEDAwOwpFjmOBGpqKhAQ0NDUteFsaCCJiUjUhlfyCZ5Gz9yxl6kTOaR88lcCERQSIUNxK2abHZSrttaSSGQOkohEBDM0AwdOSct57lzaIYfSzL5mUDIRazDGSwgS3PknFEqwej1Ys6g3Q4UgaDJu1ywv/U2AKDisssyui+SgclFCpr79wEAtHPmxL09yXD0D+U2Q5NkdKrq4rsIWY1GdkHzNlvCzMFcoqypgffAAWjmzg1zP2QTRqWCorIS3NgYAkNDUFZVpeT6SbbpXBAEmJ96GuA46I4/PmpxGCW7kAxNImgKgiA/nxUJns/Gs86Ec+1aONasQc1NN+b2QLNEbjI089NynqrTLhcblDRDszQILYcslgxNIP5rJdWcSEUeC1gLjbxpXgR/w1RRN7fAifFN57JDs5I6NIsNImbW1dVBr9dnJOaVKoIgwOVyYUgyUkzJQFOggiYlIwp1Asj3yHk0pwFZNAheLwSfL60yj1LFe+gwAECdpDA1ESE717JDM8mLj6C7ODfPXZ9UCKRpj+HQJCPnUimQIAhBkSlHGZqKmhqwRqP8fpG0oBmaoZlhKRAgjp0HXC5wtuLIg7K/9x54pxOqlhboli7N6L5iZWh6JYemZs7suLdXt7SKx/TOu/B89avQzo7//ekSGJJGbRMImgDAmozghr3g7PaCZWgCovsB6wDTOZ/L6eMoa2tFQXN4GMLs2fL5LZkJCHmjIo6g6d61C0P/dx9cmzcDAMozFNEpyaGQzg2kFIi32yFI5U3xMjQBoOyMM4Ff/BLunTvhHxpKuBFQDORi/DZvLecpOzSzPwovZ2jSkfOiRi4FctiDbvoiEMOSydBMNiIp6EItjjVTLuHI+bbEMjQBQCU3nXeFfV5uOacj50UFx3GymFk9yd2zOp0OADA0NIS6urq0x89pKRAlIwp1AgjmVxZucRs6Bpjr4ygmeKcTzg0bAAD6lSsLfDSFg+zO+/v6wv6d8HY5HzknDs3ogqZSKgUKWESHJm+zQXC7xa/FKWnJBIZhwgqKkhU0Q39XcvZTBu81coh/EgUOgiCk/TjJQsbNyy+9JOPdWeJcDB05FzgOnkOHAADaufFHzo3nfA66JUvA22zoWn0DfJ2dGR1PLEJHzhOhIMVAoQ7NPGdoAkDtt76Fhl/+EtWrV+f0ceSm86FhCB4PwHEAkh85B6ILmt6jx9Bzy3fRceVVcG3eDEalQtX116Pi8i9m7dgpsZFHzm02CDwvP5dZozFhqZ6qvg7a4xYBAOzvvgve45E/hCLN3cpJhmaeWs7lcfmkHWzZPZ/zXi8Er1e8b+rQLGpCS4GKMkMz3sh5Chma4n1N7GscIRCA4HIBKI6/YaqoSdN5iENT8PvlTTTFJBfNig2SmanPIGZqIkF+D5lkiVJBk5IRcst53jM0JXekywVBuujLBfFGpxilEoy0s5DrRXYx4Vi3DoLPB1VrKzQzZxb6cAoGec4HMzSTdGjKWWDZFzQFvx++LnGHVtM+Ner3RLack1ZERUVFThvrNWkImqEbF3Jeb5oj50CIQBbHbeDeswddq2/AweUnwvbuu2k/ViL8fX1wbdwEACi/5NKM748IfaGCpq+rC4LLBUarhbqtLe7tWY0GLQ89CM2cOeBGRtB13fWyczebkIzOZByaRLzmC+zQVNbWovKqK3Puwg9tOpcvRhkGrF6X8LaxBE3Xli04evHFsL/zDsAwKL/0Ukx/603U//AHtAwoT7DEaScI4nM5xTxYo5TbOnjX3Thw/OLgx7ITMPb44zk55kzIxfhtviJ+0hV8sjUKL+esMkxJCiuTCXJ+4iwWeVM4mc2nXBNaphhJqjFhihQ2gbOFv7cXh848EwN33Z23xwy9hku2EKyYUDUTQbNb/lyA5GlLpYGU4mMyjplHIxu/BypoUtJG8PmCO8l5DsIOXTTw0q5aLgjuukb/+fJVTlRMONasAQAYzzxzUr8Zy2Hp0gVIsgvE0CD5bOPr6QH8fjBabcx8U1KGI3g84F0uBAal/MyG3ORnEkIdo0kLmqSZ3OUKNr9mMHIuOyqijJz7OjvRe9tt6Pji5XCuWwfebkffbbfDuX592o8XD+srrwCCAP3y5VnJZYxWCuTdL42bz56VlHilMJnQ+sjDULe1wd/Xh67rVwcXxVmCZHQm08RNYhz8AwOye0JRnX9BM1+ECZryuLkBDJt4qRZL0LQ8+ywQCEC3dCnaX34Jjb+5J+nXHyU7sGq1vPnJWa1JNZyHUn7RhfLfNxTB68Xg/94D87PPZu1YswGfg/Fbsubjct5yntrUUbYdbLwtmJ+ZzOueUjjI5qpfWkMBxSGGBUfho2VophYTRoT9fLacjzz8MAJ9/bA8/3zeXOhkPc5oNCUZH0bWkJzVKkdWkFgpRWUlfS+hTHjoM5ySNqFj1vneSWbUakClApBbMVEec43x82V73KjYEQIB2D/8CABgPDs3bb+lQqSwpkjWoZlDEdx3rAMAoG5vj7mAYfR6ecEWGDMHG85zNG5OCC0pUjU1JnWb0I0LMqqcSbwF+RuFug14jwcDv7oLRy64ELY33gQYBqaLLkLZ2WdB8PvR/T/fgXvHjrQfMxqCIMD64ksAstcyTVosBbdbFsOSbTgPu5+aGrT+41Eo6+vhO3IE3TfeBC6L42apZGgSBwwpumJ0OrCGiTuiEypokt95so4fuXgmRNAUBAHO9WI8SO3/fBvaWbOyeLSUVAg2ndvAjY4CSD4+QdXYiJmfrMXsrVvCPqpvECMQBn72c9jeeis3B54Gwedu9kuB8pWbnuy4fLbP53J+Jh03L3rIGjAgTbkUixgWT2RPNSZM3rjPwQZ8NAIjI7C+IEbxCB4PPPv25eVx5U2YEszPBMR1Ahkr9/eIY+cBcp6povmZlIkPFTQpaUMWcIxOB0aZ334phmHy0r6XaPwoX82bxYJry1bwVisUlZXQLV5c6MMpKJGjz0mP8ORwdC5YCBS7uZhhmODYuXks2HCeY4emVoonYMvLo7qNosGq1fIFAnGDZ7J5Qv5GoaVAQ7+7F+b//AcIBGA49RS0v/gCmu79HZruvx+Gk06C4HKh66ab4TlwMO3HjcS9fQd8nZ1g9HqYzj0nK/fJGgxgpRwa4tIMNpynVvCjampC6z8ehaKyEp7PPsPQ/92blWMUBCGlDE3WJAma0vNaWVMzoV3hsqA5NJRyOUk0h6bvyBEEhofBaDTQLVmS1WOlpEZQ0LTKI+eKFOITGKVSfI2HfNTefjsqrrwSEAT0/uCHcKxdm5NjT5Vg8Ug2HZr5yfJLdVw+2+dzeRKBCppFT2gxKFA8YlgskV0QhOB5JelIhfxOoY09/oRcmAYArq3b8vK4wQLYwjts04XkaPqkHE3ZoUnzMyk55vTTT8ett94a8+tTp07FH/7wh5weAxU0KWlTqIZzQj6azhMFfU+WwGyCXRo3LzvjjEmfvxYpYCbdGklGeHIwOuc9Kgo/sQqBCHLTudksZ2iqpuR45HzqVEy5+y40/d//pSRKRb72Mnm/kTMZJYeme9cumP/7XwBA0wMPoPXvf4d2zhzxcdVqNP/pj9AtXiwW5dywOmtFOVapDMh0zjlZzdxSRORoBhvO56R8X5rp09H0+98DACxPP5MVlypvs8kXf6k4NL2S87gQ+Zn5JGzk3BU/7iQSWdAMiQggcQn6pUvBajRZPFJKqhCBirNagnmwGcYnMAyDhp//DKbzPw/4/ej5zi1wbcuPABCPVMX4ZGDzsIENpD4un+2CSl5uOKeCZrETKWAWixgmi+wRWeGC2y0XzSVdekUikvKQock5HPJ6TLd0KQDAvW1rzh8XCOaql3JurUouBhJz9ImgSR2alMkAFTQpaROvMCcfBN2RuRQ0448fTaYMTUEQYF/zHgA6bg6MFzALlbkVChnN1UyL7dAEAGWl1HQ+FuLQrM+toAkAFZdfjrJTTk7pNpHvL5k5NElrth1CIID+n/8CEASUX3JxVKckq9eLRTmzZ4MbHsGRc8/DvvkLgh8LFqLzuuvg3rUrqccXOA7Wl1+G7fXXAWRv3JwgN50PjyAwOorA8DDAMGmPGhtWnIjyyy4DBAH9P/9FxnlWpGRIUV6elMBG/l4BqXhrwguapOU8pBQo2YvkaA5NMm5uWLUyewdJSQsSCcDbbFktuGIUCjT+5jcwnHoKBI8H3Td/A/6+vozvNxNyIWgSAUbwenOaq5fquDyb5dghzkoyNGmJR7ETublaLGJYLJFdzm1nWTBJtivnyxkNAJannwZvt0M9fTrqbvseAMC1bTsEQcj5Y6eanVuMqFuaAQQdmoFRyaFJBU3KJIAKmpS0CbblFeYEwOZwdJeQaPxIkcPG6mLDu38/An39YHQ6GFatKvThFJzIkfOkHZo5EsEFQUjBoRlsOicik6ohtxma6RK6mcDo9RnFW4Q2do498SS8+/aBLS9H3Q9/GPs25eVoffQRaGZLY9scF/wIBODasBEdV16Fnlu+K//+IxEEAfYPP8Sxy76Avv/3I/AuF7QLFkC//IS0f5ZohBYDeaRCIHVbW0Yu0Lof/gCKigp4DxzIuFE5MCg1nCeZ16owhb+mks0cLFXIzyf4fPD3iSJussIKKfvibDYIHAfB74dr82YAoO/XRQAbOnJOBM0sPZ8ZtRrNDzwA7cKF4O12jP7jn1m533QQOE4uasyFQxPI9VQOzdCkJEc2N1uzSSyRPdR9nOyUjLxmsufWocn7fBj712MAgOrVq6FduBCMWg1udBT+LE3GxH18B3FoFofLNh0im84DY1KGZjUVNEsBQRDAu1wF+Uhl08DpdOLaa69FWVkZpkyZgvvuuy/s60NDQ7joooug0+nQ3t6Of//739n+VUUlv8GHlAlFUOwrzAmAlEPkcnHLJRg/KvUMTf/AANy7d4uN5QlGyO3viePmhpNWgdVq83F4RU1kPliywn6uMjQ5s1luXFe3tcU/hsoK6Tb5dWimgyJE0Mk03oI4/rxHjsKxThzHrf/B9+VCnVgoa2rQ/uILYQ3igLjIH33kUVhffhn2d96Bfc0alF9ySZhDVhAEOD76CO4t4ugUazKh+sYbUPWVr2S9eTIoaA5D8HoAAJq5qY+bh91nZSXqfvhD9N95J4b//BcYzz0v7Vb2wJAkaCYxbg5EGemb4A5NVqMBW14O3mqF75jotk46Q1MSzCAI4Gw2+I4eBe9yQVFRkVbkACW7yBmaltRbzpOB1elQ971b0XX9alieew413/6WLHLnk9D1WDbjNBiVCoxGA8HrBedwJp3DnCoFz9CUHNZ05Lz4YZRKMHo9hBwI+JkQS2RPJyYs6PbM7TWO9eWXERgehrKhAeUXXgBGrYZ24UK4t26Fa+s2qKdOzenjB1/3E8ChKZUCcbJDk2ZolgKC240DS5YW5LFnb9uatGv7Bz/4AT766CO8/PLLqKurw5133olt27bh+OOPBwB8/etfR19fHz744AOoVCrccsstGJLW/rmECpqUtAlmjhTmBCAvJHN4og1maEb/GUs5Q5N3OtHx5asR6O9HxZVXouGXv4i7a0vyM41nnZ2vQyxqxoktKY+cZ/d565PcgarGRrA6XdzvJZk6vu4e+QJUVZ+cyJRvQi8SMnWDExGa/K50S5ei/AtfSOq2DMtCFSnE1dWh8Z7/RfX112Ho93+A4/33YX3hhei312hQ+ZVrUHPjjTm7GFeGZGj6e3oBANrZmYtZ5ZddCuuLL8L16acYvOsuND/0YFrlPIEhUgiU3HMt0qU00UfOAfFv6LNa4e2QBM0kRSFGrQZrMIB3OsFZLPK4uX7liqwL55TUUUgjxJx5LHihmeXns37lSmjnz4dnzx6Yn3gStbd8J6v3nwxyWaRaDTbLjc9sWRk4rze3m9gpjsuTc5Lg94P3+dL+mQPDwxh58EGYn3kWAKCopK6qUkBRVoaAJGgWytwRSSyRPZ2YsHy0nAsch7FHHgUAVH39a3IRpH7JElHQ3LYVFV9Mbp2WLmQcv1hE6XSQMzT7+iAEAsFSoKr8b2xRJiYOhwOPPvoonnzySZx1lhg999hjj6G5WRTTDx48iDfffBObN2/GCSeIE2iPPvoo5s6dm/Njo4ImJW0SFebkGrlcJQ8j5wkzNHM8jpELhv/0ZzmbzvLMM1CYjKj7/vejfq+vpxfe/fsBlkXZ6afl8zCLlnHjRikKmpzTCUEQstba7JUcXYnGzYHgxZJn317xmEymrLppskno7zlzh2bI30ipxJRf/DwrYo9m5ky0/PUvcG3bBuvLr4S1dALiyE/lV74CVY6b5Ingxw2PwNcr7tJrM3RoAlL5yC9/gaOXXArHRx/B/s67abWz+1N0aEZuEpCM0ImMsrYWvsNH4JOKkFIZgVNUVAQFzQ0kP5OOmxcDxKHp6+gEeB5gmKyXNTAMg+obb0Dvrd+D+d//RvXq6/P+vp7LbHW2zABudDRnm9gCx6XstmNDXC28wwE2xb8p53Bg9NFHMfavx8TSFgCGU05B+SUXp3Q/lMLAGo2AdF5LNh4k18jt6xEiOxElU9kYJu8fgscDwe8Ho1Jl+WjF6S9fZyfY8nJUXnGF/Hnd0iXAw4B72/asP2YkwQi14vgbpoOyrg6MWi1G1gwMIkBKgWjLeUnA6HSYnacSrGiPnQxHjhyBz+fDiSeeKH+uqqoKs6VIrn379kGpVGLp0qDTdM6cOajIkYkjFCpoUtKGZI5Ejt7mi/y0nCfI0CS7lykusL2HD2P4gT/CuWkTEJFdoZk9C7XfuQWGE5enccTJ4dm7F2NPPAEAKL/8i7A+9zxGH3kUrKkcNTfdOO77He+L7kz90qUFGWMrRkLFFkatTrpFWF70BgIQvF4wWRrfJ4VA6gSFQEBwx9bfKbYhqpLMNCwEoYJO5g7N4O2rV6+GZubMjO4vEv2SJdAvWZLV+0wFhbRw9fX2BAui5mRnZ1QzbRpqbrwBI399EL23347+n4QsgBgGpgvOR8NPfhI3uoJkaCb7fGMjHZoTPEMTCDady23HKQhDiooK+Ht74e/tg3vnTgCAYSUVNIsBUgrkPXJE/HdVVUZ5wLEwfu5zULW1wt/ZBctzz6Hqa1/L+mPEI5cb3bluOg8bl0/y+BmFAqxeL2aR2e1AkoIm7/PB8t//YuTBh+Qxc+2iRai7/facrv0o2SX0/blY3H1hebMhInswQzOFTbKQn4lzOLK+/uc9How8+CAAoOqaq8OOXS+NsPqOHUNgbCynbd3y9WyR/A3TgWFZqJqb4Tt6FP7uLnCjUoYmLQUqCRiGSXrsmzIeOodESRt5J75Au5K5HvcWeF5e4MbM0EzRJerv70ffnT/G0Ysvgf3dd8HbbODt9rAP95at6Pra19B1401ysUc2EThObHfmOBg/fx4a774bdT/4AQBg+P77YX7qqXG3IfmZtN08SKi4ltKOt14HSK7MbF6YkTFqTRIOzcgFjjLHzsFMCLtgyHDzRNXcDGVtLTRz5qDmm9/I9NCKDuJg9B0+AvA8FFVVUNZlz9VYffPN0MycAQQC4e9bNhss/30K/T//edxw8VQzNMc5NCeB0yAy1iAVhx2JMrC/8w7AcVC1tqadd0rJLiQ+gbzn5yo+gVEoUH39agDA6L8eG+cWzzXpiCbJEixhzM2aTx6XV6lSGh1PJUtd4DhYXnoJR8/7PAbv+Q04iwXq9nY0/fEBTH36KSpmlhhh68AiEcMYhUIWRkLXmJycoZn8epVRqeRN92y/7gS/H73fvRXe/fvBGo2o/MpXwr6uqKgQ1xsA3Nu2ZfWxI+ESxIuVCiopR9N76LBczqaYBOsmSn6YPn06VCoVNm3aJH/ObDbj4MGDAEQ3ZiAQwNatQafpgQMHYJE27XIJdWhS0iad8YVsEiv42rl+PZT19dBMn57R/ZOTgfhYsUqByDEET/SCIMC5bj383V1h3+s9dgyWp56WLzDKzj4LNTfeGOZCEnx+WJ5+CuZnnoVz7Voc++QTmC68EHXfvz0lF50QCMDx0UdQNTdDS9qZJcxPPQXP7t1gy8pQf8cdAIDq1deDs9kw+re/YeCXv0JgaEh2CgkcD5f05lR2FhU0CaxGA0alguD3J52fCYi7qKzBAN7hEJ+7MS5sBUGAe8sWeA8fjrwDlJ12KlRTpoR9Wh45b09m5Dx8l71YG86B8A2TTAPbWZ0OM9a8BwHIer5bMRDpYNTOmZO1SANAfM5Pfe45+Pv6wj7v3rkT/Xf+GNbnnofCVI66H3w/6uMGBqUMzbr0HJoTvRQICDo0CalcJBNB0/HRRwAAw6qVWTsuSmaQlnNCLvNgyy+9BMN//hMC/f2wvv4GKi67NGePFYk81ZKDje5clzCmOy7PlpUBQ0MJN9edGzZg8H/vgffQIQCAsr4eNf/zbVRcdllO3LqU3BO6yVpMDdkKgwEBlyvs+ihd9zRrLAPn8aQcrcW7XHB8+CF0xx8PVWNj2NcEjkPfj+6A46OPwGg0aHnwr1GdhLolS+E9dBiurdtgPDt3+f28vfRbzgFA3dwCJwD3rl3iJ1SqohHaKaVPWVkZVq9ejR/84Aeorq5GXV0dfvzjH4OVortmz56N8847DzfffDMefPBBKJVK3HrrrdAlOdKeCfQMSkmbRPmSuSbayLn1lVfQ98P/BzAMyi++CDXfuSVth4q8EFCp5JDqSKKFb4/86c8Y+etfY96vftky1N5+G/SLF0f9esPPfoaqr30Nww/8EbY33oDt1Vfh3r4dbf/+d8LiFkEQ4FizBkO//wN80mib6fzzUXvrd6FubYV/cAjDv/8DAKD2tu+FuYFqb/0ueLsN5v/8FyN/fXDcfWtmz4ZaCv6liLBGI7ixsZRFfbasDLzDIe8KR+LetQtD990PV8guWCiaOXPQ/uILsmjEe73wS82G6vapCR8/UtAsZodmNkuBADEeIHsSX3EReUGQi3ZrVqOBpj081kDT3g5wHPp//BOM/eMfUJhMqPnGzWHfIwQCCEgjUMkWULEajZwJxZaXT0gROpJxgmYKwhARNAWvFwAdNy8mFOUVYf/OpaDJajSouvZaDN93P0YffQTll1yct2KonGZo5jhmKG3BJ4mCSs++fei64UaA48CaTKi56UZUfuUrYLMUOUMpDKGbrMU0rsyWlQHDw2Hiv9xynuKki8JQBm54JOmJIsHvh+X55zH8l7+AGx4Bo1Kh8uovo/ob34CyshKCIGDgrrtge/11QKlE8x8fgH7Zsqj3pV+6BJann865Q1PeiCmQQSdbEIcmiZxRVlVldVObQrn33nvhcDhw0UUXwWg04vbbb4fVapW//s9//hM33HADTjvtNNTX1+Puu+/GT3/605wfFxU0KUnBu92AIIQFoHNyhmaBW86lExFnsWDwN78VvygIsL78CqxvvInKL38JNd/4Rso5IkGngSHmCSGysXrsscdkMdNw2qlgNcHFKqNWo/yiC2E49dSEJxh1Wxua7r8PVauvR+/3boO/qwtdq69H2xNPxMywcX36KYbuux/uHTvEY5Mab21vvAHbO++g8sor4B8YBO9wQLtoESqvuirs9gzDoP4nP4GqqQnunbvCv6ZUoPLqq+Me82SENZaBGxtL+TUQy13sPXoMw3/4gzgyCnHcx3DyyWFB7I5PPoF3/344165F2amnAgB8nWLRBFtWNk4QiYaivBxQKACOA4Ccl9VkQuiGSaHyeksFRq2GoqIimMmWhUKgZKn44hfB2ewY+u1vMfyHP0BRbkLll78sfz0wOiqWoSgUUKTwXsyaTOBGRiZFwzkQTdBMYeQ89NzAMHR8tYggGZryv2tyOwZY+aUvYfRvf4fv8BE4PvwQxjPPzOnjEXKaoRllIiabBMflUxR8YpzPCaExP4bTTkXT734nl0RRSptiHDkHokdycWk+v8nPyCVoOhd4Hva338bwHx4Q16TSbXm7HWOPPQ7Lc8+javX14J1OWJ56GmAYNP3utyg7LXbRqE7KJHfv3Qve7QabI6dXLjdi8omaNJ13dwMAFNU0P5OSXcrKyvDEE0/gCamHAwB+IMXWAUBDQwNee+21sNt89atfzflxUUGTkhSjj/4D5qefQu23v42KL34RjEoVXLgWOEOTk3brh+67D9zYGDQzZ6DhV7/C8B//CNeGjTA//gQszzwru1cIyqoqVK2+HqbPfz6qe4FP4gQXegyW51/A4D2/ASC6HWu+kXlGn27+fLT+4x/ovOYa+A4fQfdNN6P1n/+UF9AA4DlwAEP33w/nRx8DENvKqr52LapXr4a/pwdD9/8ezrVrYf7Pf8UbKBSY8stfRC3vYFgW1atXZ3zckwVFmRF+pO4cDGaBhTh7H3oIw3/6sygyMgzKL7kEtd/5H6iawh3Gg7/9Hcb++U+M/v3hoKB5NNhwnsxuLMOyovBFQsPri1fQDA/dL+3d83ygrK0JCpo5cGjGo/q6r4OzWTH64EMY+NVdYMuMKL/oQgAh4+a1tXGLgyJRGI2TW9BMseWcoF2wYNw5j1I4WIMhbBOJ5N3mCoXRiMovfwmjDz+Cofvvh6qhAdp583L6mEBuJ3eiTcRE4u/txfCf/wLnxo3jCxdnzUTtd74D3cKFUW8buomdComy1M1PPw3Prl1gy8ow5Vd3UTFzAhG6yVosLedAiPgfssbkRkalr6W5AS/dl6+rC8N//jNcn24Je40JPh84qVlbUV2Nmm9+E5VXXgHn5k8xdP998O7dh5E//kn+/oZf/AKm88+P+9iqpiYo6+oQGBqCe/duGJbH3qRzbtyIkb8+CFanQ813vgPdgvnjvidgNmP0ob/B/t57EKT3YiCY713qgqaquSXs38oqmp9JmRxQQZOSEIHnYX/3XXDDIxj4xS8x9s9/iePJpIW1CFrOXVu2wPLscwCAhl/+EvrFi9H2z3/CuX49hu67H549exAYGAi7fWBgAH23fx9jj/4DtbffhrKTTgr7OpeE04B8TXC50C9Zqquuuw7VN98c8zapom5uQus/HkXnNV+BZ/du9Hz722j5+98QGB7B8B8fgO3V18RFhUKBiiuvQM03vymPkivmzkXrw3+Hc9NmDN13Hzy7dqH6xhugnZud5uPJDhEyFabUR86B4AXU6D/+ieE/PAAAKDvjDNR+71ZoZ82Ketuqr38NY08+CdeWLXBt3w794sXwdUiN1u2JG84JisqgoFnUGZpZLAWaDChqaoBDh8Go1VCn8HzIFrW33ALeZof53/9G349+BLbMAOMZZ6RcCERgpdfWZBU0U205JxhW0vzMYoJhGChMJnBmM4D8PJ+rrr0W5qefge/wERz7whdhuuAC1H73FqhbW3P2mLIomOeRc1GoeAjm//wXgt8f9faBgQE4P14L47nnovbW7447X2aUoYnozlH/0BCG7/89AKD2e7cmHbdBKQ1CxcFiyl+MFP/N//0vHB9+CADQzJyZ4n2JP6PvWAcGfnUXzM88AwQCUb+X1etRtfp6VH3t67Lxouzkk2BYtRK2N9/E8AN/hL+rC3Xfvx2VV12Z8LEZhoFu6RLY33wL7m3bogqanr17MXTf/XCuWyd/zvHRRzB+/jzUffe7UE+dCt7pxOhjj2Hs0X/EjKxgjUaoGku7RE/dEh4LpqjKbis9hVKsUEGTkhCGZdH+7DMwP/0MRh58EL7OTvR+7zb564Xa0ZJ3xa1W9P/iFwCAiiuugF4aUQAAw6pVmLpiBXxHjoD3hrR9CgIcaz/G2KP/gGfvXnSvvgH6lStQfvElYBSiW9O9+zPxceIsUsLGAXke5Zd/EXU//EHWM0s006ej5eGH0fX1r8O1aRM6rrhSLIGRFu6hJ+5oGE5cjqlPP4XAwEBR5yWWGuS5kfKOd8gIj+W55zD0u98BAGpvuw01N90Y97aq+nqUX3wRrM+/gNFHHoX+L3+GV2o4VyfRcE5QVlbBBzFntZifE6G/21LPN8oHxPmlmTWrIEUTDMOg/sd3gnfYYX35FfTe+j20PPx3+CWHZqoX9AqjWAw0WQRN1mCQ40LIv5MlTNCkhUBFh6K8PCho1ub++aysrUX788+JedyvvQbb66/D9vbbqLzyCuiOPz4rj8Go1TCcfLIsoMhjrbkoBYoy2RBNqNCvWIHqG28Iyy0V/D5Ynn4G1pdfhv3tt2F/7z1UfPGLqPn2t+X3JHnqKI1MbPH24x2ag/fcI8b8LFyIyi99KaX7pRQ/oZusxZWhKa0xHQ5YX3sdA7+6CwBQ/Y2bU44iIc/v0G4Aw8kno3r19WCN4cV96rbWqOs0hmVRfsEFMJ1zDgJjYymVnOqXLIX9zbfgisjR9HV1ie9tr78ufkKpROWVV4BzOGB79TXY33wL9nffg+mcc+DcvBncyAgAQDNvLmq//e1xk0nq5qaw6bdShNXroaipkX9W6tCkTBaooAnA6/XiZz/7GZ544gmYzWYsWrQId999Nz73uc8V+tCKBkatRtVXv4Lyyy7D2L/+hbF//ENuAY9sos0Xcm6R1Qqf1QpFVRXqbr9t3PcxLBt1R1K3cIGUM/U3mP/zX7g2bIRrw8bxj2OKPR7EqtVgdDoIbjeM55yDKb/8Zc4CmHULF6D5r39F9403wnvwIADxorX2ttujjlZEwjDMuGZsSmYQASHVETIihNreeEPOPK2+YXVCMZNQvXo1rC+8CMeaNfAeORIycp6CQ1PKMWQNhqJaiEcSusCkI+eJUdaJgmY+8zMjYVgWU+6+G5zdAcf776Pnm9+CbtlS8fhqUxQ0pddYqs7OUkZZWwufM/UsQqWUl8VotdDFKJ2jFA62PLhWypdAr25pQdP/3Yvq1deHxc/IETRZQFFRgepv3IzKq68OEQVz23Iu+HwwP/ssRh58KEyoqLvtdhhOWhV1HaZfvBhV112H4d//Ho4PP4TlmWdgfeUVVH31q6i+8Ya0x+WJgGN++mkxO/iaa8BqtXB8/DHsb74FsGzMmB9KaRMq3mWjtDBbkNeKY837cH/2GSAIqLz6atR+97sp31fo+la7aBHqbrsNhhUnpnVcjEqVkpgJALol4rnMvX0HBI4DZzZj5K8PhjlFI93n1ddfL0ZxfbwWtjfeAACoWltR+91bYsaMTRTUzc1wS++JNEOTMlmggiaAr3/963juuedw6623YubMmfjXv/6F888/Hx988AFOPvnkQh9eUaEoM6D2f76Nyi9/CWP//CegUoU1ZeeTSOdK/Y/+X8qZYcqqKtTfcQcqv3otRh95GP7unrCvMyoVqldfH/c+6n/0I/g6O1F763dzvmA1nLgcLX97CJbnX0DFFy6DYRVtsS0kVddcA3A8yi++KKXbkQxN0txYceWVqL399qRvr5k2Dcazz4b93Xcx+vAj8EkOzZRGzqVRlGJ2ZwLhgg4tBUpM5RVXgBsZQdXXvlbQ42BUKjT9/n5033QzXJs2yRm/yhQvZqq+di0YlQomKYtzMqCsrYWvowNQKsFoNEnfTjN7Nqq+di00s+eATeF2lPwQKgzk23GsDYmfMf/nP0k3FifC190Nf1cXhn7zW4w9/jgYRhQKcjly7j14CEcuuFAuvkhFqNDOnoWWhx6Ea+tWDP3ffXBv347Rhx+G+Zln5HK8VI+9/OKLYHvnbfgOH8HQvf+HsSeeRM03v4nRhx8GII7+5yO/lJJ/wkfOi2d9QkR5smFuuugi1P/kx2kZLiquuByBkREYP/c5GM/5XN5bs7WzZ4PV68Hb7ej/+c9he+NNCJKhxnDyyai77XvjXl/aOXPQ+ve/w7l5MyxPPQ3dsqWovPxyMGp1Xo+9EKhaWuS/e6pluJT8wvN8oQ+hKMjG72HSC5qbN2/GU089hXvvvRff//73AQDXXnstFixYgB/+8IdYv359gY+wOFFWV6NO+n0VilBBU79yBUwXpSYqhaJubsIUaWw9VZLJgckmhpUraT5akaCdOxeN9/xvyrcLXfiazv88Gn7+s5QXidU33gD7u+/C+vLLcoaqKoVsNGWluNBJdbc834RnaBaPA6JYUU+disbf/rbQhwEAYDUaNP/lL+i67jp4du8GAChTHDnXLVwI3T3RSzwmKiRHkzUYUnpfYFgW9XfckavDomSIPAKtUoEtUDGM4cTlKY+cxkMIBGB54QWM/PkvCPT1y5/PZcs5yUNX1NSg5lvfTEuo0C9dirb//BuODz7A8O9/D++hw/BareLjpDgur546FdNefhnWl1/B8J/+hEB/PwZ+/nMAgHLKFNR+539Suj9K6UA2WRmVCmwRiWWhonzZGWeg8X9/nbYrUTN9Opr+795sHVrKMEoldMcfD+f69bA+9zyA5J2ihuXL4xYJTURCczQVVNAsStRqNViWRV9fH2pra6FWq/O+UVAMCIIAn8+H4eFhsCwLdQbvoZNe0HzuueegUChw0003yZ/TarVYvXo17rzzTnR3d6OlpSXOPVAKBaNSQT19OgIDA5jy859PyjcDSmmimTkDAGA47VQ0/uY3aTl7dYsWQX/iiXBt2gRAHDNJZUGtmT0bgNiGXMwwGg1UTU3g7PZxhSmU4kdRZkDL3/+GrmuvhffQYWjnUqdSIsjzPNW2ZUpxQxyaypqaCbNeYZRKVF55JcovughjTz6J0YcfAW+3Q93WlvXHUrdNBVgWrE6H6htWo+raa1PKmI2EYRgYzzwTZaedFiZGphLdIt+XQoGKL1wG0wXnw/yf/2L0oYfA2e1o+OlPMzpGSnGjamoCo9XGzK8vFJoZ4hpTv3w5mn5/PxiVqsBHlBnGc86Bc/16qNvbUXvrrQVxipYKoU3nymqaoVmMsCyL9vZ29Pf3o6+vr9CHU3D0ej1aW1vBZhAFMekFze3bt2PWrFkwReRALpd2dHbs2EEFzSJm6tNPQXC7qdBBKSmM556L6W+9CVVra0ZZPtU33BAUNFMoBAIA4zmfw7Q33oC6tbjf3xiGQfvzz0Hw+8FqtYU+HEoaKCsrMfX55xEYGoK6uTnxDSY5JAe1mEYYKZmjME3cgitWp0PNjTei8stfBmc2Q52DdbO6uQnT33kHCpNR/l1mg1Ax0t/bC02K59JQWI0G1dd9HZVXXoGA2Uzf7yY4ivJyTH/7raITrQ2nnorpb78FVXPzhMhurbjqShhWrhAF5AKUHZYSoWt6BS0FKlrUajVaW1sRCATAcVyhD6dgKBQKKJXKjDcoJv27Qn9/P6ZEKUohn4ulnHu9Xni9XvnfNpstNwdIiYuirAygF32UEoNhmKzs6BtOPgmauXPh3bcvZVcJwzDQpOFEKQSpZuNSig9WraYX90mirBNjIGjEwsRCUSnlFk/gDVhFWVlOS+bUzU05u29Wo8lIzAy7L4MB6iITuSi5oRhjexiGyYlLulBMtJ8nl6hagtFTSikrn1KcMAwDlUoFVYk7qIuBSS9out1uaKKE52slJ5Db7Y56u3vuuQe//OUvc3psFAqFEg+GYTDl7rsw+re/o/LLXy704VAolCxQdvppMH7+PJRnkAtNKT6M55wD15Yt9L2aQqFQKDlBVV+H6htvAKPRgtXrC304FEpeYARBEAp9EIVkwYIFqK+vx5o1a8I+v3fvXsyfPx8PPfQQbr755nG3i+bQbGlpgdVqHTe+TqFQKBQKhUKhUCgUCoVCoVDiY7PZUF5enlBfm/QOzSlTpqC3t3fc5/v7xbbGxsbGqLfTaDRRnZ0UCoVCoVAoFAqFQqFQKBQKJXdMekHz+OOPxwcffACbzRam/G6SijaOP/74pO6HGF1pliaFQqFQKBQKhUKhUCgUCoWSOkRXSzRQPulHzjdt2oQVK1bg3nvvxfe//30A4jj5ggULUF1djY0bNyZ1Pz09PbQNnUKhUCgUCoVCoVAoFAqFQsmQ7u5uNMcpFp30Ds0TTzwRV1xxBe644w4MDQ1hxowZeOyxx9DR0YFHH3006ftpbGxEd3c3jEZjxtXzpQzJEu3u7qZZohRKkUNfrxRKaUBfqxRK6UBfrxRK6UBfrxRKcSIIAux2e8wISMKkFzQB4PHHH8dPf/pTPPHEEzCbzVi0aBFee+01nHrqqUnfB8uycZXjyYbJZKInBQqlRKCvVwqlNKCvVQqldKCvVwqldKCvVwql+CgvL0/4PVTQBKDVanHvvffi3nvvLfShUCgUCoVCoVAoFAqFQqFQKJQ4sIU+AAqFQqFQKBQKhUKhUCgUCoVCSRYqaFKyikajwc9//nNoNJpCHwqFQkkAfb1SKKUBfa1SKKUDfb1SKKUDfb1SKKXNpG85p1AoFAqFQqFQKBQKhUKhUCilA3VoUigUCoVCoVAoFAqFQqFQKJSSgQqaFAqFQqFQKBQKhUKhUCgUCqVkoIImhUKhUCgUCoVCoVAoFAqFQikZqKBJoVAoFAqFQqFQKBQKhUKhUEoGKmhSKBQKhUKhUCgUCoVCoVAolJKBCpoUCoVCoVAoFAqFQqFQKBQKpWSggiaFQqFQKBQKhUKhUCgUCoVCKRmooEmhUCgUCoVCoVAoFAqFQqFQSgYqaFIoFAqFQqFQKBQKhUKhUCiUkoEKmhQKhUKhUCgUCoVCoVAoFAqlZKCCJoVCoVAoFAqFQqFQKBQKhUIpGaigSaFQKBQKhUKhUCgUCoVCoVBKBmWhD2CiwPM8+vr6YDQawTBMoQ+HQqFQKBQKhUKhUCgUCoVCKSkEQYDdbkdjYyNYNrYPkwqaWaKvrw8tLS2FPgwKhUKhUCgUCoVCoVAoFAqlpOnu7kZzc3PMr1NBM0sYjUYA4i/cZDIV+GgoFAqFQqFQKBQKhUKhUCiU0sJms6GlpUXW2WJBBc0sQcbMTSYTFTQpFAqFQqFQKBQKhUKhUCiUNEkU50hLgSgUCoVCoVAoFAqFQqFMetwOH/w+rtCHQaFQkoAKmhQKhUKhUCgUCoVCoVAmDAIvpHwb+5gHj9+5Hu88/FkOjohCoWQbKmhSKBQKhUKhUCgUCoVCmRCM9Djw6PfXYts7nSndrv+wBQEfj849YwhQlyaFUvTQDE0KhUKhUCgUCoVCoVAoE4KuvaPwugI4sm0YS85pS/p25kEXANHdOdLjQMO08lwdYsnRs38Mm189hhMubEfL3KpCH86Eh+M4+P3+Qh9GzlCpVFAoFBnfDxU0KRQKhUKhUCgUCoVCoUwIbCMeAIB1yAVBEBIWixAskqAJAIPHbFTQlOjeN4bX/7oLnJ/Hzve7qaCZQwRBwMDAACwWS6EPJedUVFSgoaEh6ddnNKigSaFQKBQKhUKhUCgUCmVCYBtxAwC8rgA8Dj90RnVStzMPhAiaHbacHFupESpmAsDAESsEXgDDpi9CUWJDxMy6ujro9fqMxL5iRRAEuFwuDA0NAQCmTJmS9n1RQZNCoVAoFAqFQqFQKBTKhMA27Jb/3zLoSkrQFHgB1hCH5hAVNMPEzKkLq9Fz0AKvK4Cxfieqm8oKfXgTDo7jZDGzurq60IeTU3Q6HQBgaGgIdXV1aY+f01IgCoVCoVAoFAqFQqFQKCUPzwuwj3rkf1uGXHG+O4jD4kXAz8vOQ+uwGx7nxM0wTESYmLmoBufdtBAN7SYAQP8Ra4GPbmJCMjP1en2BjyQ/kJ8zk6xQKmhSKBQKhUKhUCgUCoVCKXkcYx7wvCD/2zLkjvPdQcwDTgBARZ0O5bWSe2ySujTddh/eeDBEzLxxARQqFlOmi5mifYcshT3ACc5EHDOPRjZ+TipoUigUCoVCoVAoFAqFQil5SH4mIXSMPB6kEKiiXo+6qaITcahzcgqaw112BHw8TDVaWcwEgCkzKgAA/UcshTs4CiUEKmhSKBQKhUKhUCgUCoVCKXlIwzkR4ZIdOSeFQJUNetRLguZghz0HR1j8OMxeAEBlg0H+PQJAfbsJDMvAMeaFfcwT6+YUSt6ggiaFQilJrMMubH716KTOtqFQKBQKhUKhUChBrJJDs2lWBQBx5FwIGUGPRdChaUB9OxE0bRCExLedaNjNolhZVqkJ+7xaq0Rti1gGRF2aqcFzPLa/2zVhXb+CIOCmm25CVVUVGIbB9u3bw/69Y8eOnDwuFTQpFEpJsuXNTnz6egf2resv9KFQKBQKhUKhUCiUIsAmC5qVYBUMOD8Ph8Wb8HZE0Kxs0KOmuQwsy8Bt88luxckE+ZnLKrXjvjZlegUAoP8wLQZKhb3r+rH++cNY89i+Qh9KTnjrrbfwr3/9C6+99hr6+/vR09MT9u8FCxbk5HGpoEmhUEoSu7RYSXaMhEKhUCgUCoVCoUxsbMPiNUJFvV4u97EkyNH0eQKyiFdRr4dSrUB1s+hEHDw2MR118XBI4+RlVZpxX5syQywGooJm8giCgD1rewEAY33OCSmSHzlyBFOmTMGqVavQ0NCAzs7OsH8rlcqcPG5u7pVCoVByDDkRRAZ/UygUCoVCoVAolMkJydA01ehQXqeHecAFy6ALLXOrYt7GKjWh64wqaA0qAEDdVBOGu+wY6rBhxtK63B94EUGus4xRHJoNUtP5aJ8DXpcfGr0qr8dWigx32THS7ZD/3XNgDHNWTEnqtoIgIODjc3VoMVGq2aRbyL/+9a/jscceAyA2l7e1taGzszPs3x0dHbk5zpzcK4VCoeQQQRDglEZHbKM0kJpCoVAoFAqFQpnseN0BOV/fVKNFRZ3o0CSCZSzMg04AojuTUNdmxB5MvqZzQRDiOjQN5RqU1+pgHXaj/4gVUxfW5PsQS449a/sAACzLgOcF9OwzJy1oBnw8/v7dj3J5eFG56YHToNIokvreBx54ANOnT8ff//53fPrpp/B6vXj88cflfysUyd1POtCRcwqFUnJ4XQEE/OJOlWPMAz6JoG8KhUKhUCgUCoUycSGTWzqjCmqtUhYoE0VUkYbzUEGTNJ0Pddon1bWG1xm8ziqrGO/QBELGzo/QsfNE+DwBHPx0EACw5PNtAIDu/WMTqmyqvLwcRqMRCoUCDQ0NaGtrC/t3bW1tzh6bOjQpFErJ4QwJ9uY50a1prIp+wqVQKBQKhUKhUCgTHyJommpEZ2ZFnSRoJsjQlAuB6g3y5yqnGKDUKOD3cjAPOFHdWJaLQy46SMO5zqiCQhXd/zZlRgX2bxhA/2FLHo+sNDm4eRABL4eKej2WntuG7e90wWX1wdzvQlWjIeHtlWoWNz1wWh6OdPzjlgJU0KRQKCVHZJCybcRNBU0KhUKhUCgUCmWCM9bvxGivAzOX1Y/7mm04mJ8JBB2XtlEPuAAPhTK6SEMEzYqGoEOTZRnUtRrRd8iCoQ7bpBE05XHzKPmZhMYZFQCAoQ47OD8fU/ikAHs/EcfN55/SCKVagcYZ5ejeZ0b3/rGkBE2GYZIe/Z6M0GcehUIpORzm8NxMEv5NoVAoFAqFQqFQJi5rHtuHdx7Zg+69Y+O+ZpUcmqTdXF+uhlKjgMALMYtEBV6AZYA4NPVhXyNj54Md9qwdf7EjFwLFMYuU1+mgM6rABfhJlzGaCkOdNgx32cEqGTkzs3mOWE7Vs2/885eSOlTQpFAoJUfoyDkA2EZp0zmFQqFQKBQKhTKR4XkBoz1iW3R3FEEoOHIuinEMw8jFQJYYxUAOixcBPw+WZWCsCRfx6kiOZsfkEe2IcaSscnwhEIFhGEyZXgGA5mjGY4/kzpy+uA7aMrENvmWuKGj2HrSA4/LfXj7RoIImhUIpORySoKnSivZ7O3VoUigUCoVCoVAoExrHmDg6DgC9B83jvm4bDs/QBIJj57FyNIk7s7xOB4UiXB6pbxcFzdEeBwJ+LsOjLw3sY+J1VryRcyCkGIjmaEbF5wng0GaxDGj+KY3y52uay6A1qOD3chg6NnmE8lxBBU0KhVJyOKVRiCnTxBMpdWhSKBQKhUKhUCgTG9JGDgDDXXb43AH53zwvwD4anqEJBIuBrDGazs2DTvH7IsbNAdGlqDOqwPMCRrodmf8AJYDs0KyK7dAExGIgQHRoCpOoBT5ZDn06CL9UBtQ4s0L+PMMyaJ5TCQDo3j9elC9Vbr31VnR0dMT8d66ggiaFQik5iEOT7AzSDE0KhUKhUCgUCmViE+qyFASgL8Qd6DB7wPMCWCUDQ0VQjAuOnMd3aEYTNBmGCeZoThI3nWMscYYmANS0lEGpZuF1BTDaNznE3lTYszZYBsQwTNjXiKDZs5/maGYKFTQpFErJ4ZQFzQrx31YvOD/NIKFQKBQKhUKhUCYq5oix8b6DFvn/icHBVK0DywYFpHJ55Dz6RBe5z8qG8YImADRMFw0Ux3YOp3fQJQTPC/J1VrwMTQBQKFg0zRKFuQ//fYBei4Xgdvgw3CUWSc1e0TDu6yRHc/CoDT5PYNzXKclDBU0KhVJS+L0cvC7xjb+mxQilmgUEwD5GXZoUCkUk4ONwaMsgvG66SCxVBEHA0R3DsA7TSBEKhUIpJQRewJHtQ/A4/Vm/b8uAOB7eMo8UqwRHdiMLgQhk5Nxp8UYVj4jrs6LeEPUxZy1vAMOIJS6xcjgnCm6bDzwvgGEZ6MvjC5oAcMpVM6HRKzF4zIaPnz6YhyMsDcZ6xeepqUYLXZl63NdNNTqYarTgeSFMlKekDhU0KRRKSeEMKQTS6JRyRg5ZxFAoFMquD3vwziN7sPXNjkIfCiVN+g9b8OZDu/HUXZuwf2N/oQ+HQqFQKEmyf+MA3vrbZ3jn0T1Zv2/ipiQlK6E5mtEKgQBAa1DJDdORm2Q+TwAOKZu/MsrIOSCOXrctqAYQbK2eqNil/ExDuTrM5RqL8lo9Prd6PsAAez/pw2cf9+b6EEuC0T5R0KxqLIv5Pc2SS7Objp1nBBU0KRRKSSEHVUvZOKZqcRfWNkodmhQKRWTgiBVA7EZTSvEz1i/+7QI+Hmv+tQ9rHtsLv3dyNMxOdGh5BIUysencPQIA6N47hpGe7GUr+twBuKw+AEDLnCqYanVhOZpBh6Zu3G2JSzNyXWAdEm+jLQuKntGYd0oTAGD/hv4JPVrtSLLhPJS2+dVYcck0AMDapw+iX1qDFRt8Hs89JFO0uim66xcQn8MA0BOlGIjnJ+5zLJRs/JzKLBxHSfPhhx/ijDPOiPq1DRs2YMWKFXk+IgqFEg9SCETCvo3UoUnJgKFOG168fzuWX9iOxZ9rLfThULIEaSIljm5K6eEYI021WthHPdi/YQCDHXacd+MCVDXGvkBIlq1vdWDb2134wveXoLoptoOCkjkepx/9hy3oPWhB70EzRnscWHJuG1ZcOr3Qh0ahULIMzwvoORAUaHau6cJZX5uXlfsm7ky9SQ21TommWRWwDbvRd9CCqQtrYJUyNMtrowia9ToMHLWOazonDeex3JmEtvlVMFRo4LR4cXTHMGaeUJ+NH6noIMYRY4KG80iWnNuG4S47jmwbxlt/240r7zwhrJip0FiGXHj2fz/FgtOasPKyGTl/PDJyXh3PoTm7EmCAsT4nnFYvDOUaqNVqsCyLvr4+1NbWQq1WjysUmggIggCfz4fh4WGwLAu1evxYfrJMekGTcMstt+CEE04I+9yMGbl/sk90uveO4aOnxocEm2p0uODbi6DW0qcgJTUig6plhyZtOqekwZFtQwh4OWx/pxOLzmyGQkEHF0odj9MvZ+o6JScHpfQgY2/zT2lC/VQT3nl0D8z9Tjz7m0/xhe8vRW2rMaP73/NxH3zuAPZvHMBJX6TrvVzAczzeeHA3OveMAhHGmO3vdmH+qU0JW3QnAjzH471/7oXPw2HxOa1yiQaFMhEZ6bbD6wqAVTDgOQEHPx3Eikunw5BEHmMiLBHlPU2zKrFvXb+coxnXoRmjGChew3korILF3JOmYMvrHdjzSe/EFTTTcGgCYhv8mdfOhXnAhbE+J95+5DNcdvuSohHjeg+Y4fNwOLZrNOeCpiAIGJMcmlVxHJraMhVqW4wY7rKjZ98YZq+YApZl0d7ejv7+fvT1Tex4AwDQ6/VobW0Fy6Z//UXVJIlTTjkFl19+eaEPY0LB8wI+fvqgbOUPxWH2ovegBe2LagpwZKWD38th40tHMHN5PRraywt9OEUBybkhu35k0WIfpQ5NSuoQJ5/b7kf3njFMpe9JJU/oeJtLCrdPJgeKUlwEL6o0aJpdiat+shxvPrQLA0dtOLBxICNB0zbilkXv7n00uypX9B22ovOzUQCiANE4qxJNsyrw2Ue96Dtkwba3OnHa1bNzegyCIGD7u13wuQJYeEZzVFGF43gc3DSA/iNWLL+wPeUL+UTsWduHQ1uGAACdn42iaVYFll/UjsaZVNjMJk6rF5++dgwLTmtCTXNmGx6U9CHvqW0LquG2+zBw1IbPPurFiRdPy/i+g+U9ovjYOLMCgJij6TB74HGIJUSRpUBAyMj5OIdmcoImAMw7qRFb3+hA7wGxHCiZ25QacrRXig5NAFBrlfj8NxbiP7/YhP7DVjgt3qy/n6YLEbud5twbYBxmL3weDqyCSfgcaZpVgeEuOwaP2TB7xRQAgFqtRmtrKwKBADhu4kbtKBQKKJXKjEVvKmiGYLfbodPpoFTSX0s2OLxlEJZBFzQGJS789nFgFeKTdeNLR9C9z0xHhJNg77o+7PqgByM9Dlx2+5Ks3/9YnxMDx6yYu2pK0eygJYIImuQESRYt1KFJSRVBEDDcbZf/fWDzABU0JwAjIX9TgRfgtvuy4gyh5Bf5okp6r9eb1Ji1vAEDR22wZbiB1RvSKDra44DL5oPelP64EyU6HTvFHL05Kxpw1teDI6d6kxov3b8de9f1Ycl5bTl1aQ512rHhhSMAgB1rurHglCYsPrcVhnKNLGRueaNDXkNYh9y49HuLwWRpE8Tj9GPTq0cBiBeu/Uet6D1owYv3bUfT7AqccuUsGnmQJdY9dxiHPh2E2+7H57+xsNCHM2np3ie6JVvmVkFnVGPg6Gf47ONeLD2vDUq1IqP7NksN50QkMlZpYarRwjbiwf6NAwAAnVEVdQJQdmiGCJo8L2BMKm8hrs94GKu0aF1Qjc7do9j7SR9WZcndP3DUCpfNh2nH12bl/jKBbPalK0RW1OlRUaeDecCF0T5n0Qia1mHx5/J5OPjcAah1udN7RnvFjfXKBn3Cya+aFnHzZaQ3PGuWYRioVCqoVLFzXSkidLZO4rrrroPJZIJWq8UZZ5yBLVu2FPqQShqeF/Dp6x0AgOPPbkXDtHLUtZlQ12aSd02poJmYwWM2AGKwsCBkN8hY4AW88eAufPDEfhyWnAOlgDMiQ9NULTo0PU4/fJ5AwY6LUnq4rD647X7538d2jsDrps+hUidUpAZojmYpIvCCnJcc6hIxyZnJmW1g9R0MD+DvPTA+kH8iYB5wyhen+UYQBBzbNQwAaD8u/CK9aVYlmmZXgOcEbHurM6fHcWCTKHIoNQpwfh473+/GEz/ZgPef2If//Hwj3n98P2wjHuiMKijVLPoOWeK29A522FJav255vQNeZwBVjQZc/N3j8ZVfrcSCU5vAKhj0HrBg3XOHMv4ZKcBYvxOHtgwCEN16lMLg93HoP2IBADTPqcS042tgrNLC4/DLr8VMiHRoApAjHPav7wcQfdwcAExSrqbXGYDL5sPBzQP47y83BQXNKcllM88/WWxX35elcqCAj8Orf9yBNx/aLQu2hYQYRzLZaCKbNKO92SuEypTQ923yM+aKsSQazgk1zdLvqif71/qThUkvaKrVanzxi1/EAw88gJdffhl33303du/ejVNOOQXbt2+PeTuv1wubzRb2QQlyeGvQnbno9Oawr5ETCnXUJWaoU3xeeZ3BVr9s0XPADOuw+Oa+f2N/Vu87l8gXuZKgqdYpoTGIu2z0OUVJBSJ8VTboUdmgB+fncWRb6Yj7lOiQGAECzdEsPdwOP/iAADAIKxUwkszkUXdGC3/i0KyWLiS690+8sXOn1Ytn/vdTPP+7reC43LSl+uJsAI31OWEb8UChZNEyr2rc10+4oB2AOImSK9GV43gclkSu825cgItuOQ717SZwfh771vXLQuaqL8zAV+9eJeeqrX/hsLw+CmXHe1147jdb8ORPN+C9f+0d15YciXnAid0f9gAATr58JlgFC2OVFqddPRsXfec46Xvi3wclOba80SHntNrHPPA4/XG/n5IbBg5bwQcElFVqUFGvB6tgsehM8Tpw55rujN63eV6ARYoxq2wIio9NsyoAQH7NxhI0VWqFnL//9N2b8e4/xNewRq/ESZfPkEfSE9G2oBqGCg08Dj+O7hxO98eR6dozBp9HHCseOFrYdnAuwMNlF9dM5HeVDqS4jwh7xUCYoGnJ7fUiEXKTKTAUXycMfB4O9lF6HZsOk17QXLVqFZ577jlcf/31uPjii/GjH/0IGzduBMMwuOOOO2Le7p577kF5ebn80dLSksejLm54XsAW4s48q3WcpTs4IkwdmvHwOP1h+aOjfdnd5dqzNhg03L13DE5r8buYuAAPt238iZa4NOlzipIKRPiqaTFi9ooGAMDBLDgIKIUj4ONkgYBkLFKHZulBBC6DSR02rkVK4PweDl5nem5qkp/JsgxOOH8qADHzbaI5Izo/G0XAx8Np8WIwyxfJXncAbz/8GR7+3sf47KOeqN9zTBo3b55bCZVm/Jhpk5SnyXMCtr2dG5dm954xuO1+6ExqtMytROu8anzxh0tx0S3HYc7KBqz6oihkLj6nFSqNAgtPa0LjzAoEfDw+eGIfBD74nNjxXhfWPXcYACAIwIGNA/jPLzbGFTbXP38YPC9g6sLqcaIuEdMdZi/8vombkZYPQt2Zaq34XAvNUqbkD7I51DynUo6ymndSI1RaBcwDLnTtTX/zyDHmAefnoVCy8uYWADRGlGxFy88kEGeny+aDRq/EiRdPw7W/XoXjz25N+jhIORAQfi2VLoe3Dsr/P9hRWHex0+IFBEChYqEtS3/Uudgcmh6nH15XcM2Qa4fmqCTkJhMnolCysju4WH5fpcakFzSjMWPGDFxyySX44IMPYgax3nHHHbBarfJHd3d3no+yeDm8dRDmAXHHa9EZzeO+Lo+MDWfmsJjoEHcmYbQ3e7tcLpsPx3aIu4pllRoIAnDo08EEtyo8RHRllUzYiZYsXujOFiUVSNZibYsRs5aLgmbvQUvBRjQpmTPa54TAC9CWqVDXJgmaJbBZQwknWEoQfmGqVCvkrMt0czSJO7NuqhGt86vBKhk4xrxRCwxLma49o/L/d36WPQfqcJcdz/zvpzi8VXSzf/p6R9Sxy2OScyle+WMqLk23w4f//GIj3nl0T9JjnmTEddayerCSMM4wDFrnVeOsr83D4s+1homtDCu29CrVLHoPBkfPQ8XMZRdMxeU/Woa2hdVBYfOXm7DmX3vDsvm69o6iY/coWJaJmrOnNaig0UvTJVHcoJTkIe7MacfXonmuKByPdNOx80LQs1+M72ieExTw1Tol5p0kjmnvfK8r7fsm5T3ldbqwoj+So0mI5dAEgLmrpqCiXi8LmcvOn5pWluK8kxoBRowrSeTUjkfAx+HY7uB79VBHYSc+5XNvhSajbgXiTDT3u8Dzhb/Wj7w+zKWgyXG8HB1QnYRDEwBqJOEz1Y0YuhkmQgXNGLS0tMDn88HpjC4iaTQamEymsA9KhDvz7PHuTEA88TAMEPDzcNnoKGAsIk9qY1l0aO7f0A+eF1DfbsKSc9sAICvZNrnGaQ6Om4eeaKlDc+JwbOcwXv3jDhzaMhjmjskFZOS8prUMxiqtPLZ0cHPxvxYo0QmK1GXyqDJ1aJYeoQ3nkWRaBEfyMxtnic7BKdPKAQA9E2jsnON4uZgDADpDxM10EQQBuz/swXO/2wLbsBtlVRroTWq4bD7ZHUdwWrwY6hRfi/GK1ppmSy7NQGKX5uEtQzAPuHDo00G89ffdCUVNrzsgu0SJAz8Zymt1wdHzF49g/QuHw8TM5Re2o36qCRd++7igsMkL2L9xAP/5hShsmgec8m0Wnt4cNh5LYBgG5VIE00QT0/NJqDtz2QVT5Ty6yCxlSvbYt74f7zzy2bixfrfDJ//em+eEuyYXndEMhhELg9J9r7VI0xeVUVqjm0JcmuVxBM1ZyxtwzS9XpC1kEoxVWrTNrwYA7P0kfZdm154xBLycvLkx2uNAwF84kcpOzr1pNJyHUl6jg1LFggvwsA4VPlYjMkLEkcOmc+uQG3xAgEqjSDqHlDj2U3FoDnfb8diP1mH7u12T3iBGBc0YHD16FFqtFmVltHkwFoe3DmHDS0fQsXtEzlFK5M4ERGs1aTybCLvSx3YO47OPe7P+ZkLGDhpnVgDInkNT4AXskU6+809pxIxldWBZBiPdjqyPtWcbR0QhEEG+wC0Ch2bnZ6MZ5wRNZnau6UbX3jG888ge/PeuzTkTNr3ugCyI1EpFZbNOFC96D2wcoH+/EiU0RiAoaNKNs1ThAjw2vXK0YHlesRyaAGDMcAOr95AFQDB3jTiJuvdPnGKgwaPWYIsrI14kZyLscwEe7z66Bx8/dRB8QMDURTW46sfLcdxZYtzSjohz3rFdopBY326CoTz+hXGyLk1ynwDQsXs0oah5ZNsQuACPygY9alpSW8vLo+deDtvfER1ly84XxczQzdR4wuZYnxNagwrLLpga83HKpcw+y3DhL/hLlVB3Zm2LEbWkMbi7uNezpYogCNjw4mEc2jKET54JL7Tq2W8GBKC6yTDudW+q0WHGsnoAwCt/3Ilt73SmvLYzRykEIpD3cyDY1ZBr5p+SeTnQYSm3fc6qKdAZVeB5oaDPXXLuNWbYTM6wTFHlaJL1AnH2OnPo0AzNz2TY5FyuqTo0BUHAumcPwesKYKjDlpGbdiIw6QXN4eHxYb47d+7EK6+8gnPOOQcsO+l/RVHxuQN499E92PZWJ17/yy48ctvHePaeT7HhhSMAYrszCabaiZGjyXM83nl0Dz76zwF07cmeu0MQBAxKDs25q8ScFnO/Myu2/Z6DZtiG3VBrFZixtB66MjVaF4i7jMWeH+iMKAQiGGuKw6FpG3HjzYd245NnD8l/P0pqkAtaVsHA3O+Uhc3Qi9lsMNojbhiUVWrk+IIZS+qgULEwD7hoS2qJIrtuW8rkCyo6cp46x3aOYMsbHVj7TGEamIlLJNpFVSYbWLYRN+yjYn5mg+TMbJ4rOnt6D5iLYjQuG5AR87YF1aiTsmQzcWnu+qAHh7YMgWUZnHT5DJz/zYXQGlSYd3IjlGoWoz2OsKZ44oxsPy62O5PQNLsSjTNFl+aetdHbxb3ugHz/p35pFhQqVhQ1H/4sppBwYKO4npm9oiHli73Q0XNAEjMvao95P7Kw+f+WoU1aTwHA8ovaoTXEzqErr0vs0Bzrd4b9bilBzAPh7kxA3MwSv+ZCgI5jZh37mAduu+jMPLBpIGxtFm3cPJTTr5mNmcvqIPACNrxwBG88uAseR/LlTZZBURiraIgiaM6uAqtgoDWoxpkeckXbgmoYytVplwMFfBw6pN/fjKV1qJ8qTnsW8vpBno7IoOGcUFVEOZpW6fqwbqr4/uDI4eQOEXCTHTcHgg5N67Abfm/i961jO0fQe9AChZLFysump3egE4hJr9ZdddVVuOCCC/DrX/8aDz/8ML73ve9h1apV0Ov1+M1vflPowyta+g5bwPMCNHolTLU6CAIw1GmHw+yN684kkHEAaxG1Uosn6dScPLYRDwI+cTG9+bVjWXN1OcxeuG0+MCyDaYtroVCxCPj5rAh2e6UA61knNsjZUbMlZ9rBzbkf880EknliiLjINVUHL3AL6axb/8IRcAHx+VDoHJxSROAFeZFxxR3LsPyidmj0Spj7nXgzxYVvIoa7gk4+glqnlC/ASyGCgRIOzwvywrk2xKHpooJmyhBh2NzvLMh7quzQjDpyLq4f7GmcD/skd2ZtmxFqrbjpWtdqhFqnhNcVwHDnxNjIIOJl24JqecOyK01B0233YcvrxwAAp10zG8ef3SoLe1qDCnNXipuuO9aIWfI+TwA9B0RBtX1RbVKPseC0JgDAwU3R1yBde0bBcwIq6vVYeHozLvjWIlHU3DUSVdS0jbrlvzXJR06V8lodLv9/y3Dhd46LK2aGUt9uwoX/cxyuuGMZzr1xgfxzxaKCjJzHcGgKgoDX/rwTL/1+O/oOFZeoaRtxw+sqbJP4p693hLkzAcBQoYa2TAWBF+RiDgoQ8HPoOySOe4d+pJoZPhRRWvPhk/vl0fOekEKgaKi1Snxu9Xycfs1sKJTipsTTv96c9CSAWR45Hy8UlVVqcMn3FuPi7x4flq+ZS8RyINGlmU45UNeeMfi9HMqqNKifakKdJGgW8voh3rk3VaqLyaEpTYSSqUdHDrPygw7N5CcD9CY1dCY1ICQuAeb8PNY9L0aaHH92S9zM2MnCpBc0L730UoyMjOD+++/Ht771LTz99NP4whe+gC1btmDu3LmFPryipU8K1Z+2uBZfvWslrv3fVTj7unlYeEYzzr1hQcJcEjIOUGhHHSAuGHe814Unf7IBz/5mS0qC3lh/8E16qMOWNZcmOZlVNxmg1ipRJbWfjWU4du6y+XBUKgMioxIAMHVRNdQ6JRxmL3oPFteiOZSYDk1J0Ax4uayKXqnQd8iCI9LoCAA5P4ySPG6HH3xAABigcooBJ1zQjq/evRKGCrG4KvT1likjIU6+UIi4f+jTQfBceiNE2aLQj19qWIdcCPh4KNUsyuv0MFSI5TFuu1/eaKAkx6g09uT3cgUZ2SebV2XRHJrV6Ts0yfktNG+NVbDyuGL3BMjRdFq84t+PAVrnVck5b917x8Cl8Z6y6dVj8Hk41LSUyeJlKIvObAEYoHP3KMwDTnTvHQMfEGCq1aFyyngnVTTaF9VArVXAPuZB/xHLuK/Ljk8pj7NlblWYqPnS77eFCTMHN4uuvaZZFUlnmEWjuqkMbfOrU3Z41rWZMGNpXcLbkZHzWA5Nl80nl1lsfu1YSseQS5xWL/79i414+Q87CnYMlkHXOHcmIGaT1krndVoMFOTDfx/Ai/dtx8t/2BH28d9fbRqXhRkPcn0yZ2UDKur1cNl8+OTZQ7AOu2EbEd3vRDSKBsMwmH9KE774/5aivE4Hh9mLV/+4I6E47nMH4LKK56JoDk0AaJxRgdpWY9Sv5Yq5J01JuxyIjJtPXyK+VxSDQ1PO0Mxw5BwAqiVBrxg2FojeMGVGBQDA5+HkuLxsIzs0m5J3aAKQ839HE4yd7/qgB7ZhN/QmNZac15beQU4wJr2gecstt2DTpk0YHR2F3+9HX18fnnjiCcyYMb6RkBIk8qLAWKXF7BMbcOpVs9AyL/qoQSimIhkR9jj9eOPB3Vj33GHwvAD7qGdccHA8yMmLrFmz5dIkJzNyciM5JJlmXO7f0A+eE8uAapqDJ32lSoEZS+sAFLczTXZoRgiaSpUChnKp+bYArl+BF/DJs+JoJsn2oSPLqUMuSA0mNRRSI61Gr5IXBaQ1MBsM9wSdfKG0zKuCzqiC2+4PK9XIJzwv4IMn9uFv3/0I/UcKk2FYihBXYXVTGVhWHD1jFVJeEnVppkToiBgZ88sXPMfLrtpoxQTy+mHUnfJEAWk4D81bA0SBDJgYxUDEnVnXaoTOqEbdVBO0BhV8Hg6DKWaijvY6sFcaAz/lyplR88Aq6vWYulAUGne+3xM2bp6sEKhUKzB9ibQG2Ri+BuE4XnaXho6wt8ytwgXfXgS1TomBozY8/evN6Ng9AkEQ5PgckotcrJCRc4fZG3U8OvTCtveApWhcmsNddvABAcNd9pTEsGyy8/1uQADaFlaPO4/X0BzNMLwuPw5vEcWzyikGVDWKH0qNAn4PJ4+KJwO5PmmcWYGzvjYXDCO+Ztc9J66B66eZZPd7PGpbjLjyjhNgKFfD5+ESZgdapGIZnUkNTQZlPtnGVK0LlgOtS96lGTZuLr33EYemdchdsNdVML86c4dmlbR2FzebCxf/wHO8LNTWNJfJBUy5aDr3ezl5vD0VhyYgrl2B+IKmy+bDljfEza0Vl05L6rU2GZj0giYldXzugCzWxNuFi4d8QVLAUqCBY1Y88+tP0bFrBKySgc4o5hylsjNmlhxjC05tglLFZs2lSXZAyclN3uXKwKEp8ILcxDfv5MZxXyfOtCPbhuEv0twhhyXxGKJtNPXn1Gcf9+Kpu8R20n3r+1MW2vdv7Mdwlx1qrQLn3jgfgPjcSCYHhRIkVhEIEYlT3f2OBefnYZZ2UCMdmgoFKy8uiZs5n/C8gPcf24e96/rBBwTs39Cf92PIBTvXdOO5327BnrW9OXNLkotXcnHLMIyco0mcHZTEeJz+sIV+tl53yeK0+iAIYo6u3qge9/WySg0YlgEfEOBM4e9K8jMZlkHD9PKwrxFBs/+ItWjPf8nSFTJuDoglCGSjmWRrJoMgiBt1ggBMX1KLxpnRx0gBcewNAA5s6EfHbvEifVoS+ZmhkDXI4W3DYS2//Ycs8LoC0BlVqJ8W8XebU4Ur7zwBdW1GeJ0BvP6XXXj30T0wD7igUAXfy4sVrUElX1xH20wficie2/xaRz4OKyGhG8eF2Lz1OP3yufH4s1vHfZ2cA2jTuciRbcPgAjyqGg348s+W48s/OxFf/tmJmHeS6LhOdiOH5wUMSX/vuqkmNEwrx3HS759sZJD30mRQ65RhmafxMMdpOC805Jpq/4b+pNc3XXulcfNKDerbxWs9rUElTzAOdebfpen3cvC6RNdipqVAgDhGrTEoIQiJ/765xGH2QuAFsEpxTUhMMeSaMpuYB5yAAOiMKuhN49cv8SAOzcj3/VA2v3pUnpiYs2L8xMRkhQqalJTpO2yBIIhj4+mO8pAMTafVl/ddG0EQsHNNN178P3FEyVSrw+U/XIZZJ4iL6VSyS8akN+jGWZVyVtKnr2fm0uR5QR5Xlh2aTSSHJP3d5p6DZlilMqCZUtNgKFOml8NYrYXfy+FYGuHWuUbgBbik0cdogd9GUhSRohjJ8wI2v3oUo71O7N84gPcf34cnfrIBj/94PdY8thf7N8QXOH2eADa+dBQAsOz8dtQ0G6EvV0MQkm+ro4jIYeQRgnVllgXNMalgS6NXRn0Paz9OzH3r2DWS10xZImaGuqS79oyWfOO61+XHxpeOYPCYDR/++wD+/bONORE2o8UIkLHzTBqes8mR7UP44Il9Rb3ZEekOyPeFCHFqE+EyElbByu8RqWxgkUzFupD8TEJ5nQ5llRrwAQH9hy3pHXgRwHO87CxvDSmnIeJmKsVAHbtH0bPfDIWSxaovxJ9aapxZgZqWMgT8PLyuADQGpVy6lCyNMytQVqWBzx1Ax67gcRKhpG1hTdRsvPJaHb7w/aVydvshyYnWflxNwvijQsMwDMrlHM3xz2XyWpx3SiNYBYPeA+aicGmGrokKIWjuWduLgI9HdXPZOLc1EDwHjPY6JkzRVyaQNcXsE8MLsoj42J2kQ9Pc70TAy0GlUaCyQbwuOfGi9rDW8VQETSA4Pm5OEClE1n+xxs0LydSF1dCXq+G2+8dthJsHnHjvn3ux64PusOvdw1ulcfOIaIp6OUcz/68rYipQaxVZee9kGCZk7Lxw10PEMWmq1oFhGXmcPhcOzXTyMwmyQ7M3enb5SI9DNiadcuWspBvUJwNU0KSkTF+Mka1U0BiUUGvFQpp0crDSxeP0yy3UPCdg+pI6XHnnCahtNaKuXdwlTNahKQiCPAJbOUWPxee0QaliMXjMhq696bs0LQMu+L0clBoFKqXsTHJCsAy5YzZ6JuKgNMY1c3mwDCgUhmVkh8SBjYNpPUYucdl94HkBDAPoy8fvepmqiUMz1YBzG9x2P9Q6JZae14aGaSawLAP7qAf7NwxgzWPxBc5tb3XCZfPBVKuTL6hIq+xwFy0GSoVgGHmEQ7OBjJxnR1gJbcKONhLZOKsCaq0CLpsPg3naJed5Ae8/LoqZDMvg7OvmQaFi4TB7iyJQPRMObh5EwM/DUK6G3qSGfcwjC5sHNvZnRbAVBAHD3eOLnsjmRzGMnO9b34e3/v4Z9q7rL4j7N1nIRgx5aeTboRnrfSAU0nRuT+H9Plp+JoFhGDSTi/sCRU1kg4GjNvjcAWgNKtS1meTPt86rAhhRIEtG3OcCvDxCelwSpQMMw4Q55aYurAGrSO0Sg2EZucCHCDCCIMgtyiQ/MxoKFYtTrpqF824OZrjPO2n8JEoxQnI0yUhtKOTiuH1hDeauEt04xeDSDF0D5TsvnAvw2P1BDwDRGRztHF5ep4dSzSLg42GN8nudTNhGpIIsBpi1PNzM0DizAizLwDbsTsoMQK6P6tqM8uaCUq2QR891JjXq2lLLsKxqSC5SqJgdmqyCld9viOAEAAc/HcCz92zBgU0DWPv0ITzx0w3Y9UE3vC7/uHFzQiFzNLPZcE6Qi4Ey7IDIBDINSjaPyIZoTgTNNBrOCZUNerAKBj53YFxZlyAIWPccmZioS3tCdqJS3FuXlKIk3kVBsjAMA1OtDiPdDthG3HLpTapYhlwYPDb+Tb+iTo/a1rKwBfXgMRvefvgz2Mc8YJUMTr58Jhac1iQvhsjif6TbAS7AQ6GMvxh3WnzwezgwLIOKOj0UShYLTmvCjve68elrx9A6ryrlIHkgZMHQGlwwGCrU0OjFFlbzoDMs/zIZuACPo5LLYdYJ492ZhNknNmDLGx3o2juK/iNWTJmemsMil5CLMF1IvmIo8gVuig5N4kZtW1CNFZdOByC6LgeOWtF70IK+g2YMddhlgXP/BvFCy1itRePMCjmX6KQvzoBCJR5XbasRHbtHJ0xjbr4gGTeRrkmygLWNesD5efn3nC4jUYSvUBRKFq0LqnF4yxCO7RxBQ3tuXweymLlRFDPPvWE+pi+pw8HNg+jaM4rOPaPyzm2pIQgC9kgZfIvPbcP8kxuxZ20ftr3dCfuYB+/9ax8694zh9GtmZ5QF5LT44HH4wbBMWBA7GTkvtENz3/p+vP/EfkDSbrOZB5ttiIjSOKsCvQcsMOdb0Izh1A7FVK1DLywpOfJj5WcSWuZUYv/6fnTvK90cTeLAbJlXFeZm1BnVqGs1YqjTjs49o2Fin8fpR/e+MfBccGNh8KgV1iE3dCY1liZZOjBjaR02vHAYTqsP045Prt08ktknNmDbW53o+mwUbrsPTqtYiqNQsUk5v6YvrkPDtHI4zF5ZGCh2Yjk0OT8Pc7/42qtuLkNVkwH71vfLLs14EQC5JtyhmV/h5fDWITitPujL1VGnjQAxZqGmuQwDR20Y7rbLbsLJSLAgq3LcJpFaq0T9NBP6D1vRs9+MeSfH37gg4nVdxGurYVo5rvzxCVBpFClvZFQSh2aCDWuS5VxRhIImIJYDbXmzAz37zRjtdWD3hz1y83l9uwlOixcOsxdrnz6EjS8fHTduTqgLETQFQUjrOjJd7FlsOCdUNRXeoUkiMsjGHPn5nObsG6rGpPVTOmt2hZJFZYMBo70OjPY4ZKMOIE6YBCcmpmfteCcKVNCkpEQ28jMJppqgoJkOPMfjhXu3wm2PHpys0irQOKMCjbMqIPACNr96DDwnwFSjxXk3LRzXhFdeq5NFw9FeR5i7IRrkgrS8VieLn4vPacNnH/XKLk0SFJ0KkfmZgCgAVzUa0H/YitHe8YJmwMeB54SYIwLd+8bgcwegL1fHFSkr6vWYs6JBHr2+6scnQKke7+YsBHLrbZRxcyDEoZliKVBogQFBrVWidV41WueJfz9Z4DxgQe9BM4Y6RYHzwKgobjbNrgy7fa303BmixUAp4YixmNKXq6HSKMSw7WG3XJKVLmQ0ObJIIJT242pkQXPlpbldPBzZOiSLmeesni+XY7QtqELXnlF07RnFknNKs8lwsMOG0V4nFCoWs09sgFKtwHFntWD+KY3Y8V43Nr92DIc+HcRwlx3n3rhAzhBKFfI3rWzQQ6kKvmfJDs0CNHUTRDFzHyCIGyH2UQ8sBcyTSgRxaM5YWo/eAxbYxzwI+Li8nQvk9/o4LhGygZWsIz9efiaheY4omI32OPDifduw/MJ2NM0eLxrxHA+33R81+qTQROZnhtK6oBpDnXZ0hQiafYcteOeRPTEF/xWXJF86oFCyuOB/jsNQhy3sfJgKVVMMqG01YrjLjkNbhuBzi+u7lrlVUSdLomEo18gbGaVAhVQMFOkkNA8Go1HKKjVgGAZzV03BnrV92PxaBy79XmEETUEQYA1ZZ9lGPPA4/dAaVHl57J1rugEAC09rjms8qGk2YuCoDSNdDsw6IeeHFheBF+Bx+qGLkgmc08cVhLBx82g0z6lC/2EruveNRc3XD0W+PolyfZSq0YJAJtEcZi98nkDU9xuBF2AZEq8VK4tw5BwQr0Fa51Wja88onvvNFgT8PMAAyz4/FSdcMBUCD+zb0I+tb3bI5zjSbh5KbUsZGJaB2+aDw+xNO9otHRwk7iUXDs0CThoRnYGsG/Lh0Ez3OqWmuUwUNHsdcvwVAPl9b86qKQknJiYjVNCkpEQ28jMJwWKg9HZIhrsccNv9UKrYsAsUgRcw0uOA1xVA52ej6PwsmMU0fUktzvjq3KgNeQzDoH6qCV17xzDUYUta0Aw9uepNasw/rQk73+vGtrc60xI0IxvOCdWNZeg/bB2Xo8nzAp6/dyscY1586afLo15kHSFZLYvrEmZunHTFTHTvG4Nl0IVNrxzFSZfPTPlnyAXkgivWGCLJ0LSPecDzQtSsrUgsgy6YB1xgFQxa4/ytogqcR0QHp23EjRWXTg9blJCRc1IMlOyF2GRHFjIi/sYMw6CyQY+hTjssg66MBE3y/gAgrnjWNr8aLMvA3O+EZciFirrcLaJ7Doiu90VnNGPG0uD4kficPIT+w9aYC/1ihzgUZiypC7vgVaoVWHb+VDTNqsDbj+yBZdCF5367BadeNQtzT5qSsithOIZIbZDiKQo1ch4qZi44rQltC6rx+l925d31mCw8x2NMyjJrnlMpb/JZhtxpi82pQkatjHFcIkZpAysZR37fITM2vizmHEfLzyToTWqsvGw6Nr16FH2HLHjp99vROLMCJ1zYDpVagd6DZvQetKD/sAV+L4fTrp6NBac2pfrj5Qyn1Su6zxlpxDyCtvnV2PJ6B7r3mcEFeOxc042NLx+FwAswVmnlxm1CdWMZ5qxMrXSgtsUYd6MoGWaf2IDhLrsoxEhxFOkKpKUAGTm3DoU/l8l5qropGI2y5Ly2EJempSBjh267HwEvBzDiBrPD7MVwlz3l7MR06D9swXCXHUoVi/mnxhffSI7mSE9hN5YFQcC7/9iDQ1uHcOmti6NukuQKsmZSqlhMXxLdNd0ypxKfvnYMPfvNEHgh5jVCwMfJma6RrsJM0BpU0BlVcNv9sAy6ol572cfE6RxWycjv/cXI/FMa0bVnFAE/D51Rhc9dN18uZINCLJCdu3IK9m3ox1CHDUvOHb9RrVQrUN1kwEi3A0MdtvwKmtIaPN65N1WIQ9Nh9uZt4yOSoKApOTQrpAzNLE/ueBx+uYAy3esU4uwM7WCwDLrk6JXjzmzO8CgnJqV3dUQpKNnIzySUSwKUNU2HJhl9b5lXhfO/uSjsazwvYLTHIV+A2Mc8mH9yY9iIeTTqJEFzsMOGBafFf3wyChS5W7jgVFHQHDhmTXk8NuAPLhgic2jIGGVk0/mxHcPyCO2uD3vGucm4AC+/Ec5YmngMTGtQ4fSvzMHrf9mFHWu6MW1xXVGMnpMTbSxXTFmlFizLgOcEOC3J7WoSd2bTrIqoIncs1FolWudXxxRBDRUa6E1quGw+jPQ4iuL3V+zwHA+XlTizxv+NK+pFQdM86ASQ3jgjII71+b0cFCo27k6/Rq9C46wK9Ow3o2PXSNQm1WwxcNQKAGicURH2+Yo6PcprdbAOu9Gz35z2GGeh8LoDOPypOO42/5ToF59TZlTgqp+cgPf+uQ9de0bxwZP74Xb4sPS8qSk9lixSR7TWBx2a+Rc0u/ePhYmZp35plrywtg65k954ySckp1mpUaC8RoeKej0Gj9lgGXTlTdBMLkMzsSO/75AZm1/rQK+0YcAqGCw+J/7reMm5bZi1vB7b3urEnnV96Dtkwcu/3x71e7e+2YG5J02JGoFSCIg7s67VGNUJVjfVBK1BBY/Tj+d+u0VeN8xaXo/Trs4s8iGbzDyhHuuePxwsaGTETM6JChGSHWZvmBOarAWrQ153pmod5qyagr1r+7DlzQ5cPPP4vB8veQ8rq9Cgvr0cDvNQ3gTNHe+JLqXZKxqgK4vvdiRTWMPdjryP7oZyaMugXFS1+6OevAqaxJ3ZfnxtzNd3XbsJKo0CHqcfIz2OcdNrhJEesWBJZ1JndSQZACobDHDbLTD3O6MKmmQDsLxWX3TnzFCmLqzGjGV1EHgBp1w5K+r1ikLFihthcTbD6qaaMNLtwGCHTZ7YyQfJnHtTRaMTHeYOsxdj/c5x69x8QHQGOUOzKjcOTTJWb6zWpn0+Jeus0Gv9Xe93AwLQtrB6UsdnxKM4VmGUkiEb+ZkEUy25IElX0LTEPBaWZVDbasTxZ7figm8twpd+shwLT29OuKAJhjEn3tE1DxKHZvibS3mtDlqDCnxAwEhvapkh8oLBqIKxOvyEUhWjKY7Y0AGx+TGyPbd73xi8LnHcvGF6RVLHMXVhDWavaAAE4P3H9+W9iT4aQYdm9IUUyzLywj/UlRuPY7vE/MxQW3+2qG0rvWKgY7tG8OZDu+Gy5X8812n1QRBE0UEf5WKc5CZlOqpLnHzVjYaEWU/EFUSE71zgdQdkR1z9tPELedJUnOxzupg4uGkAAT+PyimGmGO+AKArU+PCby/CEimr78Cm1EvJgg3nEQ5NuRQo/8/pg5sGAEEUaE790iwwjOguYZUMuACfUqFNviD5mdWNBjAsI+fX5jPzMzhyHidDs4a0lHrAceFFeTzH482/7caL921H7wEzWAWD+ac24St3rcT0xYkvDssqtTj1y7Px1btWYuFpTWCVDDR6JdqPq8HJV8zEFXcsg86ogsPsxdFtxVHuxHE8DkmbB61Rxs0B8RxJ3EIj3Q4oVCzO+OocnH3dvKIRMwHRKRsqjjW0m6A35XdUN59oDSo5Lih0g1/epInIYjvuzBYAosGA59IricyEULcT2XjPRzGQZSjEpXRWS8Lvr5LewzwOf8EylJ1WLz5+6qD8745do/C6osdkZRuO43F4i/ieEGvcHAAUClY2qXTvj50fTPoK6qeasi4Ok7HzsRjrO7LuK9ZxcwKrYHHuDQtw3k0LM4okkZvO81RKSbAnkV+dDsR1OJbiNXE28Lr88DoDACBfV5O/jc8dgM8TyNpjEREynUIgArmOtQyJBcEepx/7NvQDAI5P4n1vskIFTUrSZDM/EwgdOXen3HLLczz6D1vEY8mCW5RAcivNA86Eb3JBh2b4GxfDMKibKi3yUmypC83PjFwwEPu6Y8wLn1s8tsFjNvQfsYJVMCir1MDrDODAxv6w2x3ZFhw3T2Vn8+QrZkJfrhZHz189ltLPkQscFvHiP94iYaZUeHRAanSPh9vuw8AR0Rk3NU57arrITeclVAy09c0OHN0xjO3vdOb9scmYaVmlJurIE3mdZTqqm6gQKBTyvOg/bIHHkZuLkKEOm5ytGC33jcRWdO0ZzUobeL4Qy4DEcfP5JzcmvABiWAaLzhBHaZJ5/w3F6/LLTr1IFyH5nfrcgXGbPbmGbLrNWdkg//ysVCIH5L89PBki4xgqGvJ7rAEfJ7/W4rlE9CY1FCoWghAsESL0HrTg6PZhsGxQyDz96tkpj+4RYfPmB07D6v87Bed/cxGOO6sFdW0mLDxdfK7ueK+r4K9L+5gHL923TWxnZ4Dpi2Nv0JFG3Yp6PS7/f8sw76TEr81CMHtFsOwlFxuOxQTDMCE5mkFBU95ciHhPq6wXG7y5AD+uSCgfyIJmrS7ogszDxu2u93tEl9KC5FxKSpVCFsCGu/MvpAiCgI/+cwBeZwA1LWWonGIAF+BxWIqAyjXde8bgtvuhM6nRMje+CaVZ2kDo2W+O+T1EXKufmlmkRDTkYqD+6BtnZMMy3QLZUiMoaNrB8/k5vwT83LjR7GxBrl9HC5CjSdaGOqNK3rhTa5XyJlI2XZokEq4qgxJPvUkNnUkNCGLu6N5P+hDw8ahuKsuru7vUoIImJWmymZ8JiE3GDAME/HzKjrDhbgf8Xg4avTKr7b96k1p0hQjxhSivyy8fc7Qdw9CWulhYh13Yv6Efo30O+YIoVn4mIO7iEzGPnBR2rukCIAp5x39OHKXb+X4PBOkEyAV42V2WzLh55OOdcc0cAOJFGxmLLRSJSoEAcXSOYcQRXutw/Avwjt2jEARxRDUXGTWlVgwkCILsFNy/YQCcP7/Oj0SjLrJDc9CVkYAQLARK/L5hqtahurkMggB0fJYblyZ5XTVMi+5gbJpVAYWKFcd1ChiqnipiGZDoApu9IrY7JBSxzENcyIXmByWCXPiXVWnG5TOptAoopQzbfLp0SAkNyzLj/rahz+ViYzSiobOyXrwQydexkvd5pUYBjT62a5BhGJiqSTFQuKhD3MyzVjSkJWRGwirYcZss809pgkLJYqjTLm+MFYKOXSN4+tebMXDUBrVOifNuWhC3nKP9+Bpc9ZPluOrHJ+QtQiAd2o+rhUavBMNM7PxMQmSOptPqhdvuB8OMz2JjWEYWdiIjiPIBEVHLa7SyoEmKgXIFF+Dl8WniUE0GkudKzvv5hJQKsiyDs742D3Ok8yD5OXINeZxZy+oTTqO0SIVo/YcsCPijb/wNRikszRZVZMM6hkOzT3qPjTfpMZGonGKAUqOA38PlrUBwuMsBnos+IZgpZD0xWgCHJnm/ihRpg8VA2ZmUEQQBfYcsAMa76lOlRoqYG+q0YdcHPQCA489uKcrNx2KBCpqUpCEv1GzkZwJiIyYRL1Jtpiaj71NmVGQ9T6U+CTGSnHQNFZqozeLy7lqc+3j74T1Y89g+PPWrzfjnDz/BW3/fjZ594s8Va8FAcjTH+hywj3lwWBp3O+6sFsxdNQVqnRKWQZd8QSePm5uSHzcPZeqi4Oj5uucOp3z7bCEIgixGGOKMQhjKNfJOc6Kx1WM7czduDkQUAxXByH4inBYf/B7xOD1OP47uyO8opSPBqEtFnQ5gAK8rALc9/Qun4Z7kHZoA0L4o+bFzj9OPwWM2eUMhGQaOiu8RDVHGzQExIJ6853buKc6xc8uQC9YIp/3eGGVAiSAbAak4m8lFfbRFJMMw8iZIPouByPmybur4EppCjHEny2ikQ1M+1sw2EpLFbg4WAiVavAeLgcLXD3LTdxqlfMmiN6kx+0TRRbgjJPYlX3Acj/XPH8brf90FrzOAujYjrrzzhIQj9QzDoKa5LG+N9emiUitw6W1LcMmtiydFZhjJdrNIG7Hkwr+8Tg9VlL8VcQBFlkTmA7JeN9WI8Uok/mE4h5u3fQct8LkD0BlVaJqTvEtJLgbKs0PTZfPJo+bLLpiKmuYyzFpeDzBA/2Fr2lFbsbAMudC9d0z+6PxsVB7PT2ZDsXKKHvpyNQJ+PuoGjcfpl8X2RIWp6VA5RRL0h93gAuGb6U6rF7ZhN8DE3vidaLAsI19DxLsWzSZkc72+vTzrwllVSNN5vicaYrlOs910Ptxlh3nABYWKjRn7kizV0qbktrc74bR4oTepMXNZfYJbTW6ooElJmniZleliqiWCZmon92yWE0VSl4QYSZxssfJcyAnfPOiC1z1+dNJp9cqLP6WKhdvux5Ftw7LrM7IQiCDnaPY6sfsD0YnZNLsCtS3iRfO8k8XijR2SczM4bl6btvC78rLpYFkGA0etedtdEwQhLBfN6wog4BP/Hc+hCQSzgg5sGoh54gz4OHTvE7OC2nMwbg4Ei4EEISgSFDOR4sqeT3rz+vixGs4JSrVCdlql6xazjbjhtvkABkk7u4k7qGvv2Djngtflx7Gdw/jk2UN4+teb8ej31+K5327BB//en9SiTeAFDB6L79AEIJdPdRWhoDna68B/f7EJT/50Ax6/cz3e++de7Fnbi0NSdte8GGVAsQiOMKYgaErO1VhjPoVoOiebbo1Rzpf5HuNOFo/TL78OyeujvFYHhgH8Xk5u78wliTY2QiFCSuj6wTbihnnABYZlEo5ZZsoiKc/q6I7hvI/+7nq/B9vfFc/zi85sxhe+v1QWxSYKNc2TZ8QucuQ8tOE8GtUFHeEMFwhqW6VNqBwKmkScm7qoJqW1LNm4HM6jQ5OMmnucftS0lMnZ0GWVWvn66eDm7Lk0zQNOPPWrzXjljzvkj9f+vBOclF8dWZQXDYZhZJdmd5SxczJuTjoCso2hQgOVVgGBF8JiFwBRAAbE10Iq5Z2lTjLXotkkuBbNgWDdoAfDMvC6AnBa8ptnbosoBCKUZbkwUi7gWlST8fOUODTJemzh6U0pFQxPRuhvh5IU2c7PJASbSpO/GOA5Hn1SfmY2xVVCKg7Nyhh5LnqTWrTsC8BwlFBnklNT22rEDb8/FV/4/hKcePE0tM6vwrILpsZsbyQOzYGjVuz5RHRAHX9WsLV10RnNYFgGvQcsGOywBcfNl6Xfkmco12CqJOrslR4zl3ABHk/dtRkP3/oxXvr9Nnz6+jHZLagxKBM6S6YdXwulRgHbsFsOMY+kZ78ZAR+PsipNUou9dKmVA/OLvxiIPKdrW41gGKD3gCWvggsZ+zDGKQKpzHBUd78UrN00swIqTXIOpdpWIwwVGgS8nPy6dZjFoP9//nAd3nhwN3au6RYdIJKGuW9dPz77KLEgbBlywesKQKFi4wqsxGnWf9ia1QDzbLB3XZ+c8eQwe3Fg0wA+/PcBBHw8Khv0mJLiiBhxJaQS1TAWUmQTDb2Uo+k0528h3Rtn0012PRaZoEk2Xkw1WnnyQKFi5fN0Po43lZZVk+TQtIWUKxHRv2GaCRp99i+8Q6luLEPrvCpAAHZ9kF+XJtmQO/HiaTjlyln0YqfECY6chzs0Y8UCVDcSh2Z+Bc2An4NDEgDI+0Kui4EEQQhO1KS4AU1+f/ZRT97KeA5vGcLRHcPSqPlcKELGvYMb7oNZc6qte+4wuAAPvUmN6uYy+aOuzYhVl01P2m3XLG0A9ewbXww0lMNxc0AUVGNNLsh9CZNk3JxAXlf9eYo0CU4LZf/3rFQp5E2bfLvKgxsw4WuKMskg4RjLfOScDynli1fAlSzVIbExChWL+ac2ZXyfE53Js9VByYj+I1YIvJC1/ExCaDFQsgx3O+D3SPmZOciAIoKOw+yF0+qNWtRBTrhVcRr36qeaYB/1YLDDhuY5VWFf65GaBJvnVEKhZDFlRgWmzKhIeGxkEUvE5Yp6PdpCrO3GKi1mLKnFoS1DePfRPRmNm4cy/+RGHN0+jAObBrDysuk5HVcb7rLLi/TeAxb0HrDIXyurSPzcU2kUmHZ8DQ5uGsSBjQNRT87BxXFtTjNJaluN6Nw9WhLFQOQ53TK3EvpyNTp3j2LPJ3046Ysz8vL4wVKg2H/jigY9uvaOpTWqy3M89q4TBc35pyS/OGAYBu2LavDZx73Yv6EfXXvHsHdtnzwWVVGvR9OsCjTNqkTjrAoc2DSADS8cwSfPHEJ1U1ncDSAy4lPXZoRCGVuQqKjXw1Srg23YjZ79Zkw7vjhKMkIXcefcMB9agwq9B83oO2iBecCF5RdNS/n1RTYBLANO+L1cQuFZEATZpRRLFDbkeeQ8Xn4mEBTmXVYffO5A1NiSQjDSG90VVtGgh3XYDcuAE805dswFndrpOTQ794jn1tYcjpuHctzZLejaO4Z96/qx/KJpeXEQCYIgCwxtGY62UYqDculi32H2IuDj5M2FWGvcKmlz2zrkQsDH5S1CwD7qAQRxnaUzihsGuS4GGul2wGH2Qqli5UihZNEaxDxA+6gHO97rxtLz2nL6uwodNV96/tRxebbTF9fio/8egGXQhaEOO+rbMxMIO/eMovOzUbAKBpfdvkTeLEuH5tni73aoyw6P0x/mxBzsENew0fL9s0XlFAOGOu3jBU1J0EvmGmki0TSrEqyCwWivA4PHbBk/V+JhH/PAafGCYZmcRAoA4oShecCF0V5n3s7PAGANicgIhawLHVlwaHbtlQq4jCq0zE/tPSoalQ16sAoGPCdg9oqGmCYnShC6pUtJCjI+l+0R73LpDcaagkMzl/mZgNh+RpyXsaz+ZnnkPHa2U3BcIFzMEgRBdnq1zEntja+yQY9QfeC4M5vHlRUcJzk2yQhcJuPmhJa5VTBWaeF1BXB4W24bGsl4SdOsCpx29WzMWFYnNr4heXcw2SE7tHVwXB6PwAs4tlt08eRq3JxQV0LFQGQRWdlgkAW//Rv681YOJAsZOXJodu4Zg9PihdagSlkQJGPnR7YNY/cHPeACPKbMKMcltx6Pq39xIk6/Zg5mnlAPQ7kGiz/XihnL6sDzAt76++64geMDkoO4oT3xjjhxaRZTjmboIm7a4lq0zK3Cikum4ws/WIrV952CGUtTd4aTYiBBSK7IwWH2wucOiO3hMS7m8p2hSfIza9vG52cCgEavkt/TismlGUtEyaejlLglypLYOJU3RCWHJufn0XNAPLfmMj8zlJa5VahqNMDv5fIywQCIY8leVwAKJSsLW5TSRmtQyRsb5gEXzP3iay2WQ1NvUkNrUEEQYhep5ILQ/EyyWZXrYiAybt4yrypqnmgiyPl+yxsdeOInG7BzTTcCOcg1FwQBH/03OGq+9PNt475HrVNimrSeyLQciOd4rHv2EABg4RnNGYmZgLiJVNmgB4TgdRYg/lxyYWkORTUS4TXWH3w++zwBeR0wZcbkcmjqTWrMPEHMTSQFsLmCbK7XNJclPb2UKmTCcDSPDk2e4+GQ1geRI+dGyTyRjQzNg9Jrecay+jBHdroolCxa51VBrVVg8dmtiW9AoYImJTlykZ8JhI6cJ2/5zmV+JiFeS3nAz8kXULFGzgGgfmr0QGfLoAsOs1dyZqZ2glaqFfJoksagxOwVU8Y/brspbMxzehqiQiQMy8j5nKTsI1f0H7EAANoW1GDBqU0494YFuO63J+Hrvz0Jp1w5M6n7aJ5TBX25Gl5nQC5IIgwctcJt80GtVaAxh88hoLSKgcgFVGWDAW3zq2Co0MDj8OPoztyXAwV8HDwO8UIorkMzA2Fl71pxBHzOyoaUxzObZlVCLwlQRMi87PYlaJ5TNc6ByDAMzvzqXFQ3lcFt9+PNv30WuzU0QcN5KK3Srm/XZ6N5D1WPRbYXcQRSDJTMCCNxc1c06GO6XPUkQzNPLefBDcDY58tM4xOiIQgCDn46gO6940cGk0Eec41waGZ6rH4fh23vdMou7HjYpYsLYxIj56SJ1W3zwe/j0HfYgoCXg96kzmmUSCgMw+A4KUtz1/vd4LncbwCRNUVta1lWX3eUwsEwjDyS2bF7BDwvQKNXxnQqMwwjF23kszk42vhmWDFQEptQh7YMYu+6vpjnxUiCBY7pbUCv/MJ0nPGVOTBWaeGy+fDJs4fwxE82YO3TB7HuuUPBj+cPo2P3SNrn18Nbh3B0uzhqfua1c2O+NmeRDfctg2FZ8amyZ20fzAMuaA0qnHD+1LTvJxTigN2/YQCWQbEIzmH2wm3zgWWZmAJ7NiAGkdDzzOBRGwRBfK9PJoZkokHOLYe3DSd1/kyXQTJunkPBmhg8jmwbylvmtMPsBc8LYJXMuGlLQ5ZKgXzuAI5K8W7ZGDcnnPeNhbj2npMy3qiYLNCVECUpzvzqHJxy1Uw0p9AumAykFMhp8Sa1uMl1fiZBbimPckFtGXQDAqDRK+WRm2jUtIij606LN+xCultqMm+YXp7W6AvZDV9wSlPMnbTjzhZPgoZyddbGNOaeNAUMy6D/iDVnO2yCIMgOzVCxl2HEk1GkGzUWLMtglrSzGboL3r13DG/+bTcAoG1hTdwx32xQKsVAXpdfLqQSRx1YzD1JFMv3rM19ORBZUCjVLDT62CObZMFrG/GMc94G/Bw6Pxsd93lAHKchwjYR5lNBoWLxxR8uxZV3nhBTyAxFpVHg899YCI1eiaEOGz7+78FxF0k+d0Aela5PIoS9abYYT+Ewe/NeQBKNXC3igNSKgcjFfFWM/EwgZOQ8b4KmBUD8TbdcFAN17x3Du4/uxSt/3IGP/3sgacEAEM+t8uh+xEUrcc6k6wTb8W4XNrxwBG8+tBsCH18skDM04zi1CaGuNvuIR3Yvt86P//rMNrOW10NnVMFh9qJXcufmklzn2VEKA3EQHdkmCnjVTWVxn8ckGiKfxUBkmsoU4XaSi4ESbEJtfasD7zyyBx88sR9P/GQDdn3QHfd9yj7mEfOpGXGTOx0UChbzTm7ENb9aESZs7vqgBzve6w5+vNuF1/+yC8/9ZkvKwqbL5sPH/5VGzT/fhtqW6MWeANA6rwo6owoehx9de9LbfPI4/dj06lEAwIkXt2ctL7h1nihoduwawb9/vhH/+tE6vPvoHgDieSGX4/rB84xTPk/0SQaHyebOJNS2GNE0uwICL2D3Bz05e5wBqRCoPoct8q3zqtA0qwIBH48PntiXcC2QDeQNmGrduOtHslnkcwcyyqY/sn0InJ9HRb0+ZqFvOigU7KQqwcoUKmhSkqK6qQyLzmiJmieZCVqDCmqteIK0jybefcp1fiahPqRdLnJRExzN1cddbKq1SvkiO9SlSfIz021gXXnZdJz6pVk44YL2mN8z7fhanPX1uTj/W4uyNpZvKNfII9rJjtZ53YGULqotgy54nH4oVKwsaqTL7BWiyNKxewRuhw+bXjmKV/60A267H9XNZVh52fSM7j9ZapMMzOc5HvYxT15O8pEQocJQoZEFgnknNeatHChYCKSN+5rSl6uh0khNmBGi3oYXjuC1P+/EO4/uGfea3beuD4IgCkzxYiLiYarRSfm6yb2eymt1OOeG+WAYYN/6fhzbMRL29cEOGyA5D5J5X1WpFUFHThGI47laxAGpFQMRhybJF44G+f06rb6cu1tto2J+JsMyaIhTYhCrACETdqwJFtPs/qgXL9y7Ddbh5F671mE3OD8PpZqVo2AIFfXi884+5klrVJOUug132eOOWXrdAfg94v0n68aRczRH3ej6jAia+c2VVKoUck72QB4KHEjJXK6yziiFgUzfjMbIso2EnA/G8unQlM67ke8RyRQDbX2rAxtfEkU4bZkKLqsPa58+FFfY7JDGzadMK5enJNJFoQwKm2d9bS4Wn9Ma9jHvlEYo1SyGOu0pCZuCIOBjadS8urkMSz8/Ne73swpWHiU+mGDsXBAE2Mc845ycn75+DF5nAFWNhrQ2aWPRNr8aK78wHU2zKqBQsnBZfXKGZa43UMprdWAVDAI+HnZpTSgbHDLsAShlSPHrnk/6clIKyfl52Vmdi4ZzAsMyOOOrc6FUs+g9aMFnH+feLGGLkZ8JiNfo5HonE5cmWdPMPrEhrxuplHCooEkpKAzDyDu9ybiOcp2fSahqMkChZOF1BWAdCj+uZPIzCXUhwiggila9UsZXS4rh5gRjlRYLT2+OOzbLMAzmrJiS9QueeaeIC6cDGwcSXtg6zF48dsc6vP6XXUnfP1m81E81ZeyerGk2orrJAD4g4Om7P8WWNzoAAZh/SiMu/+HSrJZbxSPZwPyP/nMAj9+5Hv/44Sd462+7seuDHoz2OvIicI71B0V6grFKi1apcCLX2XD2seSKQBgmmJNoCXGLeZx+7F0nHuPR7cPY+lan/DWe47FvvVgGRJ6/+aJ1XjUWnyvmaK17/lBYHinJLEplxIeMe40UgaB5YFOw0THbi7jIYqB4ELd4XIemNHLO+Xl4XbltiSf5mXUx8jMJFVkeOR/tdaB77xgYBjj9mtnQGlQY7rLjmV9/isNbE+cek+dUdVPZOCeDzqgSndNCcufpUGSHlcSGl47EvCgj+ZkavTLpHC/SdN4rFVExTPrn1kwgF4KkKTZXcByP4S7x95nLgg5K/iHFQIRE472FcGjGEggSrXNCxcwTL27H1+85CaddPRtllRpZ2Hz1jzvHTViQcfOpaY6bR0OhZDFn5RSs+sKMsI8zrpmDa3+9CovPaU1J2Dy8dQhHtoe0miexdiVTDcd2jsDrjn1O2rmmG4/fuR6P3rYWr/5pB7a93Ykj24fw2YeiGHTy5TPBZjF2gmEZLDmnDZfetgQ3/P4UXHrbYpxwYTtmn9iAxZ9rydrjRINVsLKobx5wgeN4DB4bP7E12WhbUI2Kej187oC8ls0mw9128AEBOqMqqvCXTcprdVh5mVg0uv7FIzmfNiKO8vKa6Nd75JrDmaagaR/zyBM5s5bXp3UflOxABU1KwQnmaCZ+Y8tHfiYgWr1rW8XFYmQGJnGzJSNo1kdkcQ512uGTHKY1cUZSipXQcqAjCcqBeg6Mwe/h0LPfnHTGE4kTyNbihWQVOS1eqDQKfG71PJx+zZy8NYICIW6zOM4FLsDj0Bbx9+lx+HFk+zDWPn0QT921Gc/+ZkvOc9nk53REJux8aed/34b+jLKeEiGPmSbhypLHkgaDF3F71vYi4OPlcfVNrxyVR8y79ozBYU6vDCgbLD2vDXqTGrYRD3Z+EHTQEeEjlREf+QI2T46cnWu68ej3144TxBxmj7y5lItFXLLFQDzHy9mv8dxMSrUCGoP43Mh1MVCyedPkeWwZcoPPwqbFzvfF59a0xbWYf0oTrvrJCZgyoxw+D4e3H/4sYXREvFbl0I2EVMfOicOqbqoJphotXFYftr8TveDAnkIhEMEoXajsWy9uaDRMKw9r580X9VKx1+Axa05dwGO9TnAB8b0uUgCjlDYVdeFZack6NJ0Wb07KeCIRBCFqhiYQvxgoUsxcdn47FCoWC05twld+tRKnXT0baq0CfYcscskNIDq2yftprgscCTqjGqu+MANfvXsVFn8uurDJ8wKGu+3YuaYbbzy4C+8/vg9A4lHzUGpbjahs0IML8DHX0oIgYPeH4pix38uha88YNrx4BG/97TPwvICpi2rQMi93mzdKlQJNsyqx/MJ2nH3dPJTX5j7Lr4qs7/qdGOlyiOs6gxJVaU7WTAQYlsFxZzYDkHKas2xyIJvr9e3leXEYLjytCY0zKxDwcjkfPbfFiMggEEHTHqe8Mx4HNw8AglhYm2sxmBIfKmhSCo4saA7Hf0PJV34mgbgb+/4/e3cd3tS9BnD8G6t7qQulpVCjQHF3l+FsbMzdx9zv3Hend8yNbWzAGD7c3QqUUtrSlrq7N8m5f6QJLXVv4fd5Hp5nS05Ofmmb5Jz3vFJl2h9UKTl3afjL3bFKL05JKxnKzd1727ZphmlbkVcZDnS+gay99NgrgeCLRxo3zTHFENC0adb6ruY31AVLexMcvaxY+PxAeg1q3V5/jeHUwxpkutLYusoaUqJzqSjTYGqpYt5TIQy5wRsPf1vkChkZ8QWGkp+2ov+btnOu/jfdPcgeY3MlpYUVZMa3XRDNMOG8gQxNqJnZplFrDb2FRi7y1WVhSrD9h/PkphcbAjm9hzmjVLVfIFvPyETJ0Dm69gYnNsdRnK8re9ZnHjRmIJCefTtmaJYW6np0lRZWsO3780SdSDPcF3ksrc0P4gyDgeopO8/LKEGj1qI0VmBlX38QTF92Xpxb3nqLrEWyYSCQTb3bWdqbIlfK0FRoDZmJzVWcX05kZcZs38ryNAtbE+Y80Z8+Y3UnQmd21d9/K7OOgUB6VwYDNS0bTJ9h5RPiwIj5uqFup7fHk59V8wJmoWEgUONb2+gzNMuKdFlO7V1urtfN3QKFSlfV0ZYtOtKq9M8U5W3XlmpTeGU0OMHe2FRp6DWb3Q5ZmiUFFbqMedmVgVx61QYDxReQnVJE2N5ENn91tkYwsyp9YHPinYGArlWG/uJE/PkstBoJGyezZreKaS4zKyOGz689sPnNY3v5663jHFgVReyZTNTlWlx6WjdYal6VTCYztEWq6/g49VIe+ZmlqIwVzH92ACMX+tKjbzeMzZQYmysZMb9na7zUTkV/UT0ntdgwINTFx6bR/fOvVb2HumBsriQ/s5S4M5kNP6AJDNVCbVhuXpVMLmP8rX7tUnqub5FR13GqRQv6q0uSVK1SSehYIqApdDh9KnheZgmSJJGbpgtC7P4tglNbL5MWm49Wo223/pl6+ml/4QdTDFdJtVpJNxSIxmVo2rmao1TJKS9Rk5tebBgI5N4BJXGtxX945XCg6Lx6D6KrZrZGHktt8KpiUW4Z+ZmlyGS6fkmtwczKiKVvDGPhcwPb/YC46hr0mbpx52o/ELlc2RjeM9Ael542DJzmxezH+hsGG8W28gHM1epqoyBXyA29i/QHl23hyiCQhjOzrs4Uiz6ZTlFeOWbWRvgOdGL0ol44e1tRVqxm05dnDZmaga3YZ6qp/IY64+BpSUWphqMbYshNK6asWI1CJW/S1FB9sKkgq7TeMrXWELoznopSDXKlDEkrsf2HcKJOpFUexF3pGdRWGjMYKCupMhDvYt7gCY9+MFBhGw4Gys8q0X2GNdA/E3QXh/QZLzktDICF7U1Eo9bi1MOq2kmJXCFnyOweyJUyclKK6h3mVl+GJlwZYtSUtVbNsPLu60CPft1w62WDpkLLkbWXamzflExtvaszxboHdUxAU6GUG/oItmXZuf57VZSbX3tMLK4MubJxNEPViEoSfe/g9sja12c7WdgY13pxUD8YaOOXZ/jjtaPs/SPScOxSWzCzqh7B3Rg8S3f/3t8jSYvLNzy2udPNW0PVwGa/SZ4oVXI0FVpUJgq6B+n6TS54biBzloU0uU1Sr8G678/kqNxaL/Dov2d9+jvg3MOavhM8mP5AMHd9OIo7Pxh1TU4/rjoY6Er/zOu33FxPZawgaJQboDs2a03676umXFxvKWsHM8Mcg0NrLzWqQrOpJEm6MsSsjoCmeeWxRnN6aF4OyyInpQiFUo5PSPtXfwnViYCm0OH0HzRJkTn8/NxBfnv1CHt+u0j4/mQOr73E6vdO8N2y/ez4MRxo+/6Zel597Ok3SZftsm9lJOf2JJKfqcsIUqjkNa5Q10ahkBtKy5Micw1Xwpo7EKgzMLcxNpw0Rp9Mq3UbTYXWkPGjUMkpyis39A6tiz4L0d7dwnBQ3xo6w5Vd/QG5PlvpavGV03m7X5Vd1KOvg+FxTSljzEoq5NLp9EY9Rl2uIb9yINfVJedwpfxff3DZFvQ9NC0bVXKuW2NuWjGSJHGmchBKnzHuKJRyFCo5U+/rg5m1UeU2ukzCjgpog+5vcOQiXXbahQPJnN+vy0Bx7G7ZpJMgEwuVITDXloMgSgsrOFuZ9TrpjkD8hjobgprHNsSSndz2B3GNadWQXRmgs6+nf6aevo9mW5acN7Z/pp6h7LyZ08MB1BUaQ4ZD3wkeNbL2jM1UeFZeQLtURy/NnFRd9rhMVneZa229axuiz7CydTbDxkk3RG/EQl+QQdSJdENGvp4hU7sRE8719BmaAKZWRk26QNDanCvLzvUTY9uCYcJ5Kw/iEjqeTCYzZGnaN5Cdqaffrj0yNPMbCA64+ur+/rVqCYVKjltvWwbP6sGC5wbWG8zUGzjNix59u6FRa9my/JzhYmR7lZvXx8zKiBHze3LbuyO48eXB3P3RKGY+3JeQyd1x8rJq1jmJpZ2JIZM/8lj1Y2lNhdbQ6qXX0OoXDmVyWZes8GoM/XFaTkqVDM1Wqtjq6vqMdUeu0CWTXN0KrbkKc0opyi1DJpe1+5C5PmPccelpjbpMQ9je1s/SPL8vibIiNXKlrMaFTz19VVhhE0rOU2PyWP9ZqGE+hHd/B4zN2r/NjVCdCGgKHU5/olRRqqEorxy5Uoarrw39J3kayisqyjSGMi733u0TDJTJZAyf51MtqHm4MqvExsms0QcU+kyKMzsT0GokLO1NunyvDX1AU38Cf7XMpEK0agkTcxV++rKaBqY5GsrNr8FphvrAZOLFnBoDMQqyS8lOLtINs7iqH5K7vy0KpZz8zFLD4J7G+PebMP79OoyDq6IbDGrmpheDpBvEYWpZ80vZtfJgMuVSbpv1hruSodmIknNHU5BR2cc1g4z4ApQqOYGjr2RgmlsbM/XePsgVuvdoa04BbS7Xnjb0HOCIJGEIwuoDIE3RnMFAZSXqJk3T1mdn2rtb4NPfgXG3+huCmic2xwHgFdytTQ/iGjMYSD8Mo76BQHr6QHDxVRmaBdmltWbHNEdSE3s8G7KNW5ChGXksjZKCCizsjPHpX3uA2WeAIwDRp2q/oKJvH9K9TzeM67iYZFs56Tyn8kJCY+gzrLyqBCQcPCwJGO4CwIFVUdV+t/rS+6ZkaFpWOVHpHmDXoRew9BkuaTFtE9AsL1UbvgfaeuKw0DH0rYwa22PdTp+hWU/2dWupq3+mXuAoNybdFcDcJ0O45+PRzHmiP4Nm9Gh0NrFMLmPi7QHYOJlRlFtGeYkaU0tVk/pMtzUTcxX2bhatNohH3+c98mhqtc/VuLBMyorVmNsYt0uLrc7CxtkMZLpBjyUFFbrMd09x8QZ0xzC+A3VVW/pjyJbSZ2fau5k3ehBfa5HJZQSN0WWdXq5M6mgtydG57P9T1493yCzvOi8wXwloVj8uLCtRc/l8FpfDrvy7dDqd9Z+Fsub9kySEZ+tasI1wYfSNvVp17ULztF4alCA0k1U3U8be3Jui3DJce9ni3MOq2tAWrVYiK6mQ5MhcigvK23VSsT6oCRC6PZ6Y07oTwqt7DdbHsUfliXnlSauHn22X732lP2FPjclHXaGpUX6UXqXPV+8hzpzfn8yl0xmMuUlT55emPkPzWpxmaOtshrWjKXnpJcSfz6ZnZYABrmRnOvWwqjHMwshEibu/LZfPZRF7JtNQXlafspIrPdz0g0JGLOxZ59+cfqiKrbNZrds4eFiiUMkpKaggN6241TMdy0rUVJTqghqNCWQojRRY2ppQkF3KwdW6A5bew1wwtTCqtp2LjzUzHgwm/XIBvoM6x/TBYXN9iD2TaZjk6tSMnkX2bhZcDstqUonhluVnSYrMZdbDfRvsMVhadCU7c/CMHsjkMmTAuFv9AYio7PfVe2jb9gwytzbGzNqI4rxyMhMKas3S0GclNTQ8Q78/gKK8Kz00MxIK+PuDk6grtPgOdGLQDK8W/X3r+2e6NvIE1JCh2cS+lHpVM5SDx3nUeZLdI7gbcsWVsvOqnyPqCg0XD+t+p4H1fLdaO5gik+kuPBbnlxt+nnXRaLRXMqz6Vg+0DrnBh6iT6aRfLuC7J/bh6GWFWy8bQ2DXsgkZmiojBWZWRhTnl+PZQeXmevr3c1ZyEeWl6kZl6TZFRnwBSLqTsIZ+/kLXNHCaFxa2Joby0oZUzdCUJKlNjy3z6phwrqdQylvcp9zIVMn0B/qw6t0TVJRq8OrT7ZrNRgToGeLIvpWR5KQWkxFfYMiS0/fV7DXY6Zp+/VdTGSmwtDOhoLJqyNFLd/wp6PSd4MHFo6lcOplOwVwfLJswQK82V/pndsx5l6e/PbLKGQMF2aVNej0V5Zpa23IU5pTx7ze6wVk9BzjSf7JnnfuwqKXkPCe1iH8+Pk1xfu391mVyGX7DnBk4zavLJyddS8SnhNApBI5yY/Asb9x729aYQC2Xy3DwsKTvBA+GzfFpVF+h1nR1piaATRNOeq++Ot2V+2fq2TiZYWZlhEatJS22ZunDlT5fljj7WGPVzQR1mYaY0NozhMpL1YZpxtdivxyZTGYom4o9W/1noD/pryvQZHhcI/to6oM8+lLmM7sS6s3UzE6tvX+mnkIlN/wNt8VwIn1WlrGZstFXiPWBIP1BiH4C5NU8A+0ZON2r05wQWHUzpd9ED8P/N+cgsqkZmjmpRSRdzAVJlxHX0LT6MzsTDNmZVXuXyeUyxt3qT8gUT/yHu9A9sO0/xxzrGQykLteQl64LgDUlQ1PfQ7OksJwtX51DXa4FCaKOp/H7a0fZ9v35JmWz6mUlFxr6Zzb2M6w5ZdxVJVzIJju5CJWxot4sZGMzFZ4BtZedx4RmUFpUgYWtcb3BboVKjmXlwXtjJp0nR+VeybDqUf070MzKiIm3BWBhZ4xWK5Eak8fJfy9TXBlsbkqGJsDQOT74j3DBu2/H9rEytzbWnZBJtFpJYFWif+a1z9bZnGFzfDCxaFz2u62Trn9wWbG6WYMtmqKhARutxdbZnOn398Ez0K7eYMS1wMhUafie1QcxSwsrDMeF1+OwkarHoq6i3LwaB09L3HrZoNVKhtkOLdHRAU0TC5Wh2iC+kVmaGrWWA39F8c1je/n7g5MkXMg2nN9oKrT8+805SvLLsXczZ/yt/vVe5NFnaJaXqCkvVVcLZppZGeHgaVntX8AoV25+bSjjl/qLYGYnIwKagtAI+qDmwOleWNga492v8SdOVt1MMTa/kqnRXiXzbUkmkxmyNPVlllWlXzWJtWpZTW1SY/KQJN3kzKaezHYV+iyly+ey0FYGlTRqLYkRuqyuuoZZ6Ms10+PyG9X/T5+559bbhrE39wbqD2rqgyn1ZabpAzRX97xrDVf65jX+9161GX73PvYd2h+zqUKmdsfZ2xrfgY7NyrLSZyNmJRchNTBoC6r35spJLeZ8PRMlS4sqDFm9+uzMquRyGcPm9mT8rf6tVnJXn/oGA+Wk6vqjmlioMLMyqnH/1QxTzvPK0Gq0bPvuPAXZpVg5mDJnWX/dSWWVwGZTTha0Wok9Ky4CuvdxYzPz9JPDi/LKKW/ikKfUmDwOrYkGwH+ES52l4np1lZ2f35dcuQ/XBgP/V3p+NhzwrVpuXtt+vfs7cOtbw1n65jDG3+pH76HOWNqb4Blo1+SsE//hLoxf6t8pMnn0Q5naouy86veqIIDuQoONo+7EOquN+2jqS86rTWNvI+5+dsx6pF+X+m5vLn3QMupEGhqNluiTaWg1Et08LBpVfXCt0bddANE/szZ9J+qC/Of3J9doYdUUmgotGZWJJO014bw2+nOf+MrhqPXJzyzh7w9O6o5TJV2SxfpPQ1n70SkSIrLZt/IiabH5GJspmXZ/cINJEkYmSoxMdNskRuQYgpn2bhbc+MpgFr0wqNq/cTf7tcvnn9B0HX/0JwhdhEwmY8hsb257Z0STBg/IZDJDRkU3DwtMLRs++e4K9GWV+jJLPV2/Pl2QTP+6e1dOc0y4kF1rUE4/cOZavhrr7GONibmKsmK14fWmXMqjokyDqaUKhzp6ZplbGxsynOLONpylaSjDdbUgcJRbtaDmkX9qThbWZ6NVPYi8mv6gsi0GAxVUZmha2jY+uGdbpeVD3wke9WzZ+RiZKJn/zAAm3x3UrMfbOJmiUMpRl2kMExzrImmvTCTXDyI7tiGW0qKKWrevKzuzozjWE9DUB+7tXc0bVWapz9Asyivn0N+XSIzIQWmsYPr9fXDrZcv0B4JZ9MIgvPrYgwTHN8UaLjw05OyuBFJj8lCZKJrUT8nYTIVpZTA2N71xWZr6hvRr3j9JVlIRRiYK+o5v+D1Qtexc/xmRk1pEclQuMhkEjHBpcB/6zyj9RZi6SJJkGIBW30APmUyGVTdT/Ie7MvH2AG59azizHunXKQa5NZe+319bTDpPEwFNoRZ2rTjpXKPWErYvia3fhVXLVNdUaA3Z7SIzqXV5BNhhaqmipKCChPBsw3f29ZidCWCnD2LLOjbQ1ll5Bdlj7WhKeYmaiMP1zyaoT0ZCAVq1hKmlqkPf0/rKkISIbEM7ptrEhGbw19vHSb9cgLGZkom3+xM8TjcMNCU6j/WfhBJ+MAWZDCbfHdjowKM+mWLrt2GGYOYNT/Sr0cZK6NxEQFMQ2oFHZZl5UzI7O7ur+2jqZVzWnXRZdTMxBG9tnMxw6mGFVJkBdbUr0wyvvXJzPblcpguWcCV7KV5fbh5gX+9J/JUp6Q0HNPUnNXaVvbWqBjVPbYuvdpKi1UrkpumCYvVlQjh7W4EM8jJKWn1KtGEgUBMyc50qh+k4dre8JjKem0KukBtKrBs6gU25lEdBVikqEwVT7+uDnas5ZcVqjm+MrbFtcX55vdmZHUE/GCgnpeZgIMNAoEZmsJhZqUCmC/Lq+05OuNW/WgaMg6clU+/vg7G5kpKCijqHnlWVm1bMkXUxAIyY37PJ2YX6LM2GyriL8srYUEtD+sUvDW7UyYixmcowdCz6lK7sPLzKMKDGvP/031+Xw7LqHNQEunYIhdllKFXya6LFSlPoS/dSY/NadYhacX45hdllIEMMyRCqaY1J5/pA5oqXD7P394tEn0hn45dnDRe/CrJLQQKlsaLW4YFC8ykUcsOwlxOb40iNyUcmo9P0/m5vTt5WyGS6yiAxPbommVxmuIh5ZlcC2kZU6tRGn6Dg1MO6Q+c6OHpaYmqpoqJUQ2otba0kSeLgmmi2LD9HWbEapx5WLHpxEL2HujBqcS+WvjnMENgEXQsaz4DG99O2qLzYrdVIIpjZhYmApiC0g+DxHsx9MoQBU7t39FJaTV19NA1ZJN2rX1nVX22+etq5RqMlrTKb5VqccF6Vvuw89mwGkiQZJvt5BtV/0q8vO0+MqDklvSpJkqplaOoFjnIzlNQe3xRnuD0/swSNWqvrj2dfd0DD2Exl2F9rZ2leKTlvfIamg6clC58fyKxH+3X5AVvNYd/IPpr695pPiCNGJkpGLvAF4NzeJMO0ZNBl/a1697guO9Otc2RnwpXBQJKEoceuXnaVDM3GkCvkmFXJjg+Z2r3acC49hUJuCNzVNRVcT6uV2PXLBTQVWjz8bevtY1kXQx/NBiadH1l7ifgqgcybXx/KuCb2ceoZonu9l06lo67QGLI7Ahu57m4eFlg5mKKu0BJ3ru6LK/pMco8Au3bved3RurlboFDJKStSk5defwZ1U+jLzW2dzTFqoL2AcH2xb0GGplYrcX5/Eite0QUyC3PKMLM2wtzGmPyMErb/EI5WKxmqAay7mVyX37ltTT9kT38s7eFvd90O/rJ3tWDRi4OZdl+fjl5Kp+U3zAVjMyX5GSWNqtyqSpIkwg8kc3SD7kJsR1fGyeQyQwCytmnnsaGZhG6PB6DvRN25tJX9leMecxtjXWDzrWHMe3pAk/vuWjvqjsHs3cxFMLMLEwFNQWgHcrkMV1+bduk7117q6qOZHqcLPFxdFuc70Am5QkZmQmG1A+/M+ELUFVqMzZXVSomvRR4BdiiUcvIzS4kP1w30kMl0k/7qY+dijpWDKRq1loQLdfeZKc4vp7SoApmMGj/LQTN6ALo+TfosTX1WmI2TWYP981wrs2f12bRVSZJEQXZpszKSmpOhCbqA+dVT4a8X3fR9NOsJaKorNERXDoDRX0zwCLDDK7gbklbi0BpdT9XT2+NZ++EpCrPLsHYwZfJdgZ0iO1NPf2Ek/FBKtduzmjDhXE/fAN4z0I4hs73r3E4f+Is5nV5v9sPZXQmkXNKVmo9bWn/z+bro36cNZWgmV/avnXpfUJMDmXo9+urKzrOTizi55XKVYUCNy6KUyWRXgqJXDReqqmr/zOuNQik3ZFCmtmIfzaqD9gShKn01Rk5KcZOytYrzy9n4eSh7frtIYbYukDlykS9L3xjGjAeDUarkxJ/P4tj6mHYbCHS9cvC0rHbM1us6LTfX6+Z+7bTnagsqYwWBo9wADBUnjVFeqmbHj+HsXhGBpkJL9yB7gsa4tdUyG02f1HH1YCBJK3Fsk66iKGRKd0Yu8DVkYl7N3NoYF5+mZ5sOmNadUYt9mbMsRAQzu7BrJ7oiCEK7q62PZl2TWE0sVIbmz6veOcE/H5/i2MZYLhzSlT26+Nh0qkBKW1AZK3Cv7GV44K8oQBf4bWiiqUwma1TZeXaSLshj7WiG8qrMKAdPyxpZmjmVWXp2jQgk19dH89jGWH554RB/vX2c2DMZTQpsFmbrMjQtm5Cheb3TZ2jWl5ETdzaL8hI1FrbGuPnaGG4fMb8ncoWMy2FZrHn/JIfWRKPVSvQc6MiiFwY1amJ4ewoe7w4yiDiUQljlQKPSogrDRF87l8avd+gNPvQZ586kOwPrDeC7+dk2WHbe0lJzvcZkaBbnl5OfWQqyK5+5zVG17PzEljhAN1CnKRfa9FmtdZWd56YX63qeysCrz/UX0ISqfTRbL6CZXkflgyBYdTNFqZKjUWvJa2Qv3qSLOfz51jESLuSgNJIzYkFPlr4xjL7jPVAaKXDwtGTcUj8ATv57mfOV7SlEQLNtVB2eqTRWXFPtqYS20WesO3K5jOSoXNIvN9yzOSupkFXvnCDyWBoyuYxhc32Y8WDDg3Pag6e/PTIZZCUVGZIcQHe+k5VYiMpE0eTMy8YytzYmeJzHdZsgca0QAU1BEJrt6j6ahTllFOWWIZNdmVBcVciU7pjbGKNRa0mKzOX4xljO768MaF7D/TOr0g/J0Acw6ppuXtfj4s5l1jmsJCu5/jLcq7M0rwwEajgopP/9ZCYUVCt7z00v5tS/lyvvK2TzV+caHdiUJOlKyfk1Ot2+LegzNPMzS+ucjq0vN+812LnahQIbJzP6jHMHdOVtCqWcMUt6M/muwE5ZyurhZ8fQG3TZlPv/jCTlUp6hrYKlnUmT1uwRYMfoxb0aPHBVKOR4V7aHiK4lE1GSJHb9qis1d/drXqm5niGgmV53dpU+MGbnYt7gNPOG6DMskUAm0003b4puHhZYdTOps+xc/1ngGWDfqOnz1yL9IIvWGgwkSdKVC4U9REBTqE4ulxkuRDXUR1PSSpzYHMu6T05TnFeOrYs5C58bRL+JnjUugvYa7GwYuqevBhABzbYTOMoVdz9bht7g3SmCTELnZmFrTM+Buu/zhrI0s1OKWP3uCXLTijG3MWbOsv6ETOneaZJITCxUhqq+y5WzBapmZ/YdLwKOQv1EQFMQhGa7uo+m/iqhnatFrQdkzt7W3PbOcJb8ZwhjlvTGd6AjplZGGJkq8el/fVyRvroMs7EBTRcfa4zNlZQVqevM/DEMSqkjoFk1S/PE5jhDmWt9A4H0LGxNsLQzQZIw9DwFOPz3JbQaCbfetoRM7Y7KWGEIbK55/yQlheV17rOkoEI31VB2ZQq10DATC5Xh51VblmZJYblh4FRtk1IHTffC1sUcO1dz5j8zgKDRbp26L1rIlO74hDig1Uj8+/U5Q9sFfallW9BnItZWdh59Mp2U6DyURnLGLfVr0c/OqpspRiYKNBXaGn1C9dJide9351YIZunLzkH32dPUzFKZTEbPAbphFZdOVQ/25mWUEHFEF0gfNMOrxWvtqvSDgbKTC+vtedwYklYi8mgqZcVq5EpZk1osCNcP/Xd+YkROnRcSi/PL2fB5KEfXxyJJ4DfUmYXPDaw3K3/4PB/cqgzes+omLjy2FVMLI254vL9h4IsgNER/wSH6RLohOaA2UcfTUFdocfSyYvGLgzq8b2Zt9OdC8ed1x3exZ69kZ+pfpyDURQQ0BUFotqv7aKY3os+XTCbD1tmcoNFuTL47iDveG8HdH43C2uHa7p+pZ25tbMiyMbVU4eDRuJ5ocoXcUMIZU0fZuWFQSj0nvYYszeNphqEyje1dqs/STK7so5l4MYeY0AxkchmjFvsybI4PS98aZghspsXms/Xb83VmlOpLS8wsjersiyPUTv87ri2gGX1CF4Tr5mFR68mqsZmKm14ezE2vDKk1k7qzkclkjL/VHztXc4rzyzmxOQ6oPviqtdVVdq4u13Do72hAF2it2py+OeRymSFgUFd/XH2mn76UuSWMzVT4hDiCDIKbeZJgKDs/V73s/OSWOCSthGeAnSGodz0ytzY2XPzRfyc2laSVuHQqnT/fOsaOny4AuqxX8Tkp1Ma98jMkbF8S238IrxFIT4qsUmKukjP+Vn8m3B7QYCagXCFnyj2BWHUzQaGUd4nvC0G4Xjh2t8LFxxqtViImtO6+1vpji6DRbp22N6lnoC6gmRCRjaZCy/HK7Mzgce4iO1NokDgyEgShRar20TRMOPdqfCaRTCbrNGUP7UUfEOjR16FJr11fdh57JrNGFoaklQyTq+vLuNBnaUoSaCq0yGRg49jYgKYNoOujqdVKHFil6wMaNMrVEFwytTBi2Bwf5j87AJWxgqSLORxae6nW/V2ZcC6yPpqqWz2TzvXl5rVlZ+p1tfeckYmSaff3wdjsSsl1W/b7rFp2XnUATuiOBAqzy7CwNabfpNbp6eTup+trmRiRU+M+jUZrCIq1VpBw/K1+LH1jGB5+jRsGdLWqZef68rBq2Zkze7TKOruylpSdJ1zI5s+3jvPvN2FkJRWhMlEwcLoXE+8IaO1lCteIXoOdGTbPB5lcRtTxNFa9c4LMxMLKEvM41v23ssTc2YwFzw/Ef7hLo/dtamHE4pcGc8sbQ6/byduC0Fl5VfbX138XX62suMJwDOHu1/we3G3N0dMSU0sVFaUaDq2NJjNBl53Zb0Lb9M4Uri0ioCkIQotU7aOZ3oyA5vUoeLwHU+8LYsT8nk16nEeAHXKljPyMEnJSqjf/z88qQV2uRaGUY91AgFKfpQm6kleFqnFfBS4+uoBKWmwe4fuTyEosxNhMyaBZNQMY9q4WTLjdH4AzOxKIPJZa7f6MhAJDppu1KGNrMnt3XTDv6gzN3LRi0mLzkcnAd5BTRyytzdg4mjHprkCojMV282jb8lufygsPlyrLzotyyzi5Vdcjctg8H1RGrdPnzKNyUFhKdB7q8uqDdrISC1FXaDE2U2Lr1DpZ7EqVokW98HRl57qfTfTJNEBkZ17NqUflYKDYpg0GykoqZOMXZ8hKKjQEMm99azhDZnu3uH+qcO2SyWWETO7O3GX9sbA1JjetmNXvnWDNByc5uj4GSYLeQ51Z+PygZmW2G5koRZ9rQeiEuldmNiZF5tY4ftDfLkm6FmHNHV7YHmRymWFo4dldiUBldmYDQ1MFAURAUxCEFrJxMsO0so9meakGpUre6SYldzZyuQyf/o5NHsJiZKLEvbfuCz/2bEa1+7KS9AN+zOqd4AxVemnSuIFAenYu5hibKVGXazmwSheMHDSjB6YWtZew+PR3ZMDU7gDs/jWCjIQCJEkibF8Sa947SV56CRa2xgycLjK6mqqbm670LyupCKmyx6NGreXgal3WrEeA3TWZTdM90J5p9/Vh9I292rTkHHTZDMZmV8rOj6y7hLpMg7O3Fb4DWy9YbONkZhiWlnKpegDMUG7uZdWpsmp9Qq6UnWclFYrszKvog7qpl/LQ1NFy42oajZadP19Aq5HwDLQzBDJFuZ3QWC49bVj04iC6B9mjqdD1NteVmPsxsREl5oIgdC12ruZY2BqjqdANW71aYmW5uUcnzs7U0wdnAZGdKTSJCGgKgtAiVftogi5YplCIj5a2og9Exl7VRzM7ueH+mVWNXOiLT38HQiY3/oBBJpcZsjQ1ai02TmYEjXWr9zGDZ3vjGWiPukLLlq/Ose378+z9/SIatZbufexZ/OJgEQBvBhsnUxRKORVlGvKzStCotfz7TRhx57JQqOTXdJDYu58Dfca6t/nzKBRyvPvpys6PbYgh4rAuaDdyYa9WHaIkk8kMWZqJEdX7aOoHArVG/8zW5OBpaSg73/zVWZGdeRUHTwtMLVWUFatJCK+9N+rVTm+NJyO+AGMzJeNv9ReBTKFZTC2MmPFgMCMX+tKjbzcWPDcQ/+GuHb0sQRDagEwmM/SfvHy+Ztl5QmUrG3f/5rWYaU8eAXaGChyRnSk0hYg6CILQYm69rlz5E+XmbUvfRzMtNp+ivCtTDfUZmo0NDlp1M2XqfX0MfTEbq+r2Ixb0bDB4LZfLmHRnAFYOphRklxJ9Ih2ZXMaweT7MeCBYHLA0k1xxJRM6/XKBLph5NhOFSs70B/oYAs9Cy+jLzlOidYHF3kOcDUO9WpO+j2bChep9NFNjKiece3euz9WqZef5mbrhXiI78wq5Qm5o+aDvaVufrKRCwxCEUYt7XZPZ1UL7kcll9J3gwfQHght9kVMQhK5Jn9kYf1UfzYLsUnLTipHJMAwf7MxMLYzoM9oNRy8r+k0U2ZlC44mApiAILVY1Q9NJBDTblLmNMY7ddeXGcWevZGlmJesCmm198tKjbzfkShk+/R3oHmTf8AMAE3MV0+/vg7G5EgtbY+Y+GULI5O6dqoS2K7J30wU096yIqBbM9Axo3O9FaJi+7BxAaSRn6BzvNnse0PWWLSksB6A4v1wXLJRd6cnYmejLzkGXWSGyM6vTD+WKPZNJWYm6zu2qlpp7BXej1+Brq/etIAiC0Hbc/WyRy2XkZZSQm36lv76+4sPRy6rL9GAefVNvFj43UFQoCE0iApqCILSYjZMZNk5mKFVyXHqKk9q21qNy+nJsZUBTU6ElN013EGPfxuXbts7m3PXhKCbfE9Skslt7NwtufWs4S98cJrIHW0k3d11gu7xUI4KZbUShkNOrMtNuwFSvNhuMYW5trMu4lSDpYi5wJTvTzsW8U56MOHhaYudqjkwuY7DIzqzBwdMSW2czNBVaLp1Kr3O709uulJqPvbl3q7YzEARBEK5tRqZKw7lXfJWyc33Fh0cXKDcXhJYQAU1BEFpMJpMxZ1l/Fr80WEzCbAf6PpqJF3KoKNOQk1aMpJUwMlVibtP2pYpGJsoGBw/V+TjRX7XV6DN1RTCzbQ2f35N5Tw9gwLTubfo8Hvqy88qsCn3/TOc2KHFvDTKZjBse78/iFweJ7MxayGQyeg/VZWlePFJ72XlWUiHHN4pSc0EQBKH5DH00w3THD5IkGTI03bvAQCBBaAlxZikIQqswtzbGxsmso5dxXbBzNceqmwkatZaE8GyykvQDgcxFds91xNnHmvG3+jP/6QEimNmGlEYKXHys2/y95a4fDFQ5ldQw4bwTBwvNrIxEj7569BqsC2gmR+WSn1VS7T6tKDUXBEEQWoG+BVRSZA7qcg3ZyUWUFFSgNJLj3Alb1ghCaxIBTUEQhC5GJpPRI7iy7PxMBtnJ+oFAIrBwPZHJZPgPd8HB07KjlyK0AldfG+RyGfmZukb+6XG6gKY4Gem6LO1MDD2mI4+lVbvvlCg1FwRBEFqBnas5FrbGaCq0JEXlklB5YdTV1waFSoR7hGub+AsHysrKePbZZ3F1dcXU1JQhQ4awffv2jl6WIAhCnfRl53HnsshMLADavn+mIAhtx8hEiVPlNPPQnQmoK7QYmymxdRaZ711Zr8rhQJFHU5EkCbiq1HyRryg1FwRBEJpNJpMZys7jw7JE/0zhuiICmsDtt9/Oxx9/zM0338ynn36KQqFg+vTpHDhwoKOXJgiCUCuXntYYmykpLaowHLjop14LgtA16U8+LhxKBsDJywpZM/rVCp1HzxBHFCo5OanFZMQXoNVo2fVLlVLzyoCnIAiCIDRX98qAZty5TJKjdOcF7n4ioClc+677gOaxY8dYuXIl77zzDh988AH33nsvu3btonv37jzzzDMdvTxBEIRayRVyuvfRHbxIWl3Wjyg5F4SuTX/yoVXr3tOduX+m0DhGpkpDRv3FI6mc3h5P+uXKUvMlotRcEARBaDl3P1tD2xp1uRZTS5Wo3BKuC9d9QHP16tUoFAruvfdew20mJibcddddHD58mISEhA5cnSAIQt30fTQBzK2NMDFXdeBqBEFoKUcvS1QmCsP/d9YJ50LT9K7Mwrx4NJVjlaXmIxf5Ym4jSs0FQRCEljMyVeLS88pFUHc/O1HhIVwXrvuA5unTp+nVqxdWVtVPGgYPHgxAaGhoB6xKEAShYZ6BdsiVuoMVMWlYELo+hUKOWy9bw/87iYDmNcEjwA5TSxVlxWq0agmvPvaGIKcgCIIgtAZ9H03QZWwKwvXgug9opqSk4OLiUuN2/W3Jycm1Pq6srIz8/Pxq/wRBENqTkYkS9966AxY7UVYiCNcE/UmIrYs5xmYi6/paoFDI8R3oBFA51dxPlJoLgiAIrap70JWAphgIJFwvlB29gI5WUlKCsXHNkh8TExPD/bV55513eO2119p0bYIgCA0ZNtcHlbGCPuPcO3opgiC0Av/hLmRcLqDnQMeOXorQikKmdKcwp4zA0a6i1FwQBEFodXau5gyc4YVSJcfSzqSjlyMI7UImSZLU0YvoSEFBQTg5ObFz585qt4eHhxMYGMjy5cu57777ajyurKyMsrIyw//n5+fj4eFBXl5ejfJ1QRAEQRAEQRAEQRAEQRDql5+fj7W1dYPxtes+Q9PFxYWkpKQat6ekpADg6upa6+OMjY1rzewUBEEQBEEQBEEQBEEQBKHtXPcBzX79+rF7927y8/OrRX6PHj1quL8x9ImuopemIAiCIAiCIAiCIAiCIDSdPq7WUEH5dV9yfvToUYYOHcoHH3zAU089BejKyYOCgrC3t+fIkSON2k9iYiIeHh5tuVRBEARBEARBEARBEARBuOYlJCTg7l73rIjrPkNzyJAhLFy4kOeff5709HR69uzJzz//TFxcHN9//32j9+Pq6kpCQgKWlpbX9eRKfS/RhIQE0UtUEDo58X4VhK5BvFcFoesQ71dB6DrE+1UQOidJkigoKKizBaTedR/QBPjll194+eWX+fXXX8nJySE4OJiNGzcyevToRu9DLpfXGzm+3lhZWYkvBUHoIsT7VRC6BvFeFYSuQ7xfBaHrEO9XQeh8rK2tG9xGBDQBExMTPvjgAz744IOOXoogCIIgCIIgCIIgCIIgCPWQd/QCBEEQBEEQBEEQBEEQBEEQGksENIVWZWxszKuvvoqxsXFHL0UQhAaI96sgdA3ivSoIXYd4vwpC1yHer4LQtV33U84FQRAEQRAEQRAEQRAEQeg6RIamIAiCIAiCIAiCIAiCIAhdhghoCoIgCIIgCIIgCIIgCILQZYiApiAIgiAIgiAIgiAIgiAIXYYIaAqCIAiCIAiCIAiCIAiC0GWIgKYgCIIgCIIgCIIgCIIgCF2GCGgKgiAIgiAIgiAIgiAIgtBliICmIAiCIAiCIAiCIAiCIAhdhghoCoIgCIIgCIIgCIIgCILQZYiApiAIgiAIgiAIgiAIgiAIXYYIaAqCIAiCIAiCIAiCIAiC0GWIgKYgCIIgCIIgCIIgCIIgCF2GCGgKgiAIgiAIgiAIgiAIgtBlKDt6AdcKrVZLcnIylpaWyGSyjl6OIAiCIAiCIAiCIAiCIHQpkiRRUFCAq6srcnndeZgioNlKkpOT8fDw6OhlCIIgCIIgCIIgCIIgCEKXlpCQgLu7e533i4BmK7G0tAR0P3ArK6sOXo0gCIIgCIIgCIIgCIIgdC35+fl4eHgY4mx1EQHNVqIvM7eyshIBTUEQBEEQBEEQBEEQBEFopobaOYqhQIIgCIIgXPO0Gg2FOdkdvQxBEARBEARBEFqBCGgKgiAIgnBNK8jK5NdnH+Xbh+4g+viRjl6OIAiCIAiCIAgtJAKagiAIgtCBJEki7uxpCrIyO3op16SsxAT+ePlpMhMuo9Vo2Pr1ZyJTUxAEQRAEQRC6ONFDUxAEQRA60Pk9O9i6/FMUSiXBk6YxZM4izG1sO3pZ14TkyAusfe91SgsLsHV1R6FUkhkfx9blnzLvuf802JdHEARBEARBENqSVqulvLy8o5fRrlQqFQqFosX7EQFNQRAEQehAZ3dtBUCjVnN6ywbO7dpG/6mzGDR7PqYW9U/2E+oWc+o4G/77LuryMpx79mLus69Skp/HiuceJy70JKHbNtF/ysyOXqYgCIIgCIJwnSovLyc2NhatVtvRS2l3NjY2ODs7tyjBQAQ0BUEQBKGDZCcnkRIZgUwmZ/ojT3Jy8zpSoyM5vm41Z7dvYeHLb+Hk3bOjl9nlRB8/wvqP30bSavHqN4DZTzyPysQEMytrRt18B7t/+pp9v/6AZ2Bf7N09Onq5giAIgiAIwnVGkiRSUlJQKBR4eHggl18fHSElSaK4uJj09HQAXFxcmr0vEdAUBEEQhA5yYf8uALz69sdvxBh6Dx9NzKlj7P/9Z7IS49nz63cseuWdOq9cVpSVolCpkMtbXrJxrchOTmLLlx8habX4jxzLlAceR6G8crjTf8oMYk8fJ+7MKTZ//iFL3voQhVLVgSsWBEHovM7u+JespARG33y7+KwUBEFoRWq1muLiYlxdXTEzM+vo5bQrU1NTANLT03F0dGx2+fn1EQIWBEEQhE5G0moJ378bgIAxEwCQyWT4DBjCvOdfQ6FUkhgeRnzYmVofnx4Xw1f3LmX1my+jUavbbd2dWUVpKRs+fpvykhLc/AJqBDMBZHI5U+5/DBNLK9LjLnHor986aLWt7+LhA4Tt2UF+RnpHL0UQhGtA0sULbP/uS05tXse5Xds7ejmCIAjXFI1GA4CRkVEHr6Rj6IO4FRUVzd5HlwpoHj9+nIcffpjAwEDMzc3x9PRk0aJFREZG1tj2iy++wN/fH2NjY9zc3Fi2bBlFRUU1ttNqtbz//vv06NEDExMTgoOD+eOPP9rj5QiCIAjXscSI8+RnpGNkaobPwCHV7rPq5kDwpGkAHPzzVyRJqna/VqNh6/JPqSgtIeH8Wfb99mO7rbuj5Wemk5OaXON2SZLY8d2XZCZcxszahpmPPVsjmKlnYWfP5HseBuDY+jXEhp5s0zW3h8SI82z85F22fvUJ3z58J98/eg/bvvmciIN7KcrN6ejlCYLQxagrKtj29WdQ+f1z9O+VVJSXdfCqBEEQrj3X65DK1njdXark/L333uPgwYMsXLiQ4OBgUlNT+eKLLwgJCeHIkSMEBQUB8Oyzz/L++++zYMECHnvsMcLDw/n88885f/48W7durbbPF198kXfffZd77rmHQYMGsW7dOpYsWYJMJuPGG2/siJcpCIIgdDKSVoskSchbYRqf3vm9OwHoPWwkKiPjGvcPmbOIczu3kRJ1kdjTJ/AOGWS478TGtaTHXkJlbEJFWSmnNq/DtZcfvYeNarX1dSbq8nKijh0ibPc24sPOAuAdMojhi27BqYcPoCuLDN+/G5lczszHn8XCzr7effoOGU7fSdM4s30Lmz//kKXvfoqVg2Obv5bmyEqM5/TWTQybfyPmNra1bnNup+74xtTKmtLCAnLTUshNSzHcbu/uiWdQXzyCgvEI6IOJuUW7rV8QhK7n6No/yU5KwMzaBoVSRUFWBme3b2HAjDkdvTRBEARBAEAmXZ320YkdOnSIgQMHVkvJjYqKok+fPixYsIAVK1aQkpKCp6cnN910E7/88othuy+++IJHHnmE9evXM2vWLACSkpLo0aMH9957L1988QWgy/AYM2YMsbGxxMXFNbqWPz8/H2tra/Ly8rCysmrFVy0IgiB0pKLcHFa/9TK5Kcm49vbHM6gvnkF9cfLu2ewAZ0VZKV/du5SK0hIW/+dd3P2Dat1u328/cnz9Ghy9fLjlnf8ik8vJSU3ml6ceRl1RzpQHHic7OZHj61ajMjHl5rc+vqaG3KTHxXBu1zYiDuyhtKhQd6NMhkwmQ6qcBtlryAh8hwzn3//9F41azeib72DQ7PmN2r+6ooKVrzxDWkwUTt6+3Pj6+yhVna9H3Ko3XyL+XCj+o8Yx/eEna9xfVlzE8vtuRV1exk1vfIi9uydJEeeJDztD/PmzZMTFVNteZWLKvOderfPvThCE61tGfBwrnnsMrUbDzMefpbykhG1ff4aplTV3f/4dRiamHb1EQRCELq+0tJTY2FhDtfD1pr7X39j4WpcqOR8+fHiN/gK+vr4EBgZy4cIFAA4fPoxara6RXan//5UrVxpuW7duHRUVFTz44IOG22QyGQ888ACJiYkcPny4rV6KIAiC0AWUFOSz+q2XyYyPQ11RTnzYGQ6s/IXfX3qSL++6iSN//9ms/UYfP0JFaQnWjk64+QXWud3AWfNQmZiSHneJqOOHkSSJ7d98gbqiHM8+/QgcM4GRi5fiEdCHitIS1n/8NuWlJc19uZ1CaVEhods28+tzj/Hrs48SunUjpUWFWHZzYNiCJdzz+ffc8fFX+I0YAzIZkUcPsumzD9Co1fQcNJSBs+Y1+rmUKhWzlz2PiYUlaTFR7Pn5mxrbqMvLyUpKQKvVtObLbLSCrExDH9WLh/aRn5lRY5uIg/tQl5dh5+aBi29vjM3M8A4ZxNhb7+bW9z7jgW9/Y9ay5+k7aTrWTs5UlJaw+YuPrgSJOyFJkshLTxUlrl1YYsR5/vngDXb/9E2NthkC5KalUlKQ39HLqEGr1bD968/RajT4DBxKr6EjCRg9HhtnF0ry8zi9ZUNHL1EQBEHo5Pbs2YNMJiM3N7dNn6dLlZzXRpIk0tLSCAzUnRCWlekOfPVTk/T0DUdPnrzSJ+v06dOYm5vj7+9fbdvBgwcb7h85cmStz1tWVmZ4LtBFkAVBEIRrR2lRoSGYaW5jy7SHniQ7OYH4sLMkhJ+lrKiIg3/+irGZGf2nzmrSvsP36aabB4weX2//GDMrawbMuIEja1Zy6K/fKC0oIOH8WZTGxky652FkMhkyhYIZjz3Dr889RnZSAtu+/pwZjz7d6fvxSJJEUW4Oeelp5KenkpeeRkbCZWJOHEVdUQ6AXKGk5+Bh9Bk3Cc8+fatNc5/x6NMMmbOQg3/9RvTxw9i6ujP1wSea/LqtHByZ/shT/P3ufzizfQsuvn4EjplQIzvU0t6BwLETCRo7EWtHp1b9WdQnfP9uQw87rUbD6X83MOaWO6ttE7Z7GwB9xk2q9fWbWVnTa8gIeg0ZQXlpCb8+8yi5aSns+mE50x95qu1fRBMU5+cRvm8XYbu3k5UYT6+hI5n1xHMdvSyhCVIvRXHwrxXEVelN6xHUl55X9Qq+nsWHnWXVGy+ATIZjd288goLpHtQXJx9fivNyyUtP0302ZqRibmPHwFnz2u0z/fSWjaREX8TI1IwJd92PTCZDoVQyfMESNn/xEcc3rKHv5OmibYUgCMJ1auzYsfTr149PPvmko5fS9QOav/32G0lJSbz++usA9O7dG4CDBw8ybtw4w3b79+8HdGXmeikpKTg5OdU4QHBxcQEgObnm0AG9d955h9dee611XoQgCILQqZSXFPP3O6+SHnsJUytrFr78FvbunnQP7kf/qbPQajUcW7uKg3+tYPdP32Lt6Fytx2V9CrOzuHw2FICAUeMb3H7AjDmc/ncDWYnx7Pj+fwCMWHQLNk7Ohm3MbWyZ9fhz/PX681w8tI+c5CQ8++hK4939AlE1UMai1WqICz2Fk3fPOns0tpQkSWQnJ5IQdpb4sDMkhJ+jtLCg1m3t3T3pM34K/qPGYmZlXec+u3l6ccNTL5KfkY6JhQVGpmbNWluPfgMYNv8mDq/+nR3f/Y/T/24gLSbacL9MLqcgK4Mja/7gyN8r8QzqS9+JU/EdPByZvPZil9KiQuLDzuDVN6TZ5ZmSJBmC375DhhN19BBnd2xh6LzFGJuZA7rS0NRLUcgVCgJGN/z3ZGRiyrSHn2Tlq89w4cAeeoQMwn/EmGatrzUlXbzAqU3/EH3iKFqN2nD7pZNHqSgvq7XPrNC55KQms2/Fj0Qf11U4yRUK7D26kxEXw77ffqRHvwF1Duq63pzd+a/uPySJ9LhLpMdd4uTGtXVu7+jlQ/fgfm2+rsz4OA78qWvZNeaWO7G062a4r/eI0Rz9ZxVZifGc3LSOEYtubvP1CE2n1Wq4dOIo7gF9MLWw7OjlCIIgtKkufVQRERHBQw89xLBhw7jtttsACAkJYciQIbz33nu4ubkxbtw4Lly4wAMPPIBKpaKk5EopXklJCcbGNQ+Q9fX7Vbe92vPPP8+yZcsM/5+fn4+Hx7XTt0wQBOFaVFZchFyuqDfAV1FWytr3Xicl6iIm5hYsePEN7N09q20jlysYMm8xeRnphO3exsZP3uPG19/H0cu7wTVcOLAHSdLi2jsAG2eXBrc3Mbdg0Kz5HFj5C5JWi7OPLyHTZ9fYzs0vgHG338euH5YbTpBPbPgbuUKJZ1AwU+5/rNZBOZIksfP7rzi7419MLK2Y8chTePUNaXBdTXHh4F72/fo9hTnZ1W6XyeRY2Ntj7eiEtYMz1k5OeAWH4NyzV5OykVpjmM+w+TeSEhVB3JlTpMVE67JDBw2lz/jJuPkFcOnEUc7t3k78uVDDv24e3Rm++BZ6DhxqWG95aQmnt2zgxIa/KS0qxDMomAUvvlln4LM+aTHRZCcloFQZMeX+x8hOSiQrMZ6zO7cyqLK0PmyXLjvTZ8AQzKxtGrVf115+DJ23mMOr/2Dnd//Drbc/Vt06biBS1PHDbPj4HUNfVCdvX/qMn8SRNSspzMkmJTICz6C+HbY+oWFFuTn89Z/ndO9xmYyAkWMZtmAJplZWfP/oPeQkJ3Ju1zb6TZ7e0UvtcOWlJVw6cRSAuc+9SllxMQmV/W7z0lIxNjPHytEJawcnCrIySYuJIuLQ3jYLaKrLy4k6fpiwXdsM7S3cA4LoM35yte3kcgXDFy5hw3/f5dTmf+g/dWa9F5zaWklhAUojI3Gx4yoHV/7KsXWrcfcPYtGr73T6ag1BEK6QJAl1Wce02lEaGzfq8+L2229n79697N27l08//RSA2NhYwsPDefzxx0lISGDo0KGG+Fxb67IBzdTUVGbMmIG1tTWrV6+uNrxnzZo1LF68mDvv1JVkKRQKli1bxt69e7l48aJhO1NT02pl43qlpaWG++tibGxcazBUEARB6JyK8/P4adkDmFnbsPS9T1Eoax/+svOH5SReCMPI1Iz5L75RZ5BSJpMx8e4Hyc9IIz7sDGvfe40lb31ULaPlalUz7gLHNJxNp9d/2ixCt26kpLCAyfc9Wq30uqp+k6fTc+AQEs6fJf68LhMyPyOduDOnWPXGiyz+z7s1gl4nNq7l7A5dtlBpQT5r3nmVEQtvZsjcRdWCcKWFhUQc2oemopy+k6ajvKqndV2K8/PY9vVnqMvKUKhUuPX2xyNQP1jJp87fQ3uTyeVMf/RpDv31GzZOLjWyQ/1GjMFvxBjy0lM5t2s7oVs3kplwmfUfvoWTty/DFy4hJyWZY+tWUZyXa3hcfNhZTm5ex8CZc5u8Jv3fSs/BwzA2M2fAzDlsW/4ZpzavI2TaLCSpsiQdCBo/qUn7HjJ3MXGhp0iJvsi/X/6XhS+/1ayga0vFnj7Bxv++h6TV0nPQUIYtWGJ4zyVdvMCF/buJDzsrApqdmFajYdNnH1CYk42dqzuzn3yh2kWgYQtuYtePX3N49e8EjBrb7Ezqa8Wl40dQl5dh6+JKj34Dkclkhizpq7ORE8LP8ddrzxN19BAT7nyg0Z+7jaEuL+fAn79yfvf2akPXvIL7M+neR2r9PPAdPBwHL28y4mI4vn5NjfYX7SUjPo6VrzyNrYs7N7/9sQjaVUqLieb4hr8BSLwQRsTBvfiPHNuxixIEodHUZWV8dtuCDnnuR39e3WBFF8Cnn35KZGQkQUFBhirpsrIy5s2bx0MPPcS9997LiRMnePLJmkMs20KXDGjm5eUxbdo0cnNz2b9/P66urtXud3Nz48CBA0RFRZGamoqvry/Ozs64urrSq1cvw3YuLi7s3r0bSZKqfRGmpKQA1NivIAhCV5UcGUFeWkq12+RKJT36DehUJ5eh2zZzavM/TH1wGa69/Fp13xEH9lBSkE9JQT7h+3fTZ9zkGtvkpqYQvlcXRJrz9Es4+/jWu0+FUsmsZc/zx8tPk52UwNr3XufG/7xb689UkiT2/vodmQmXUaqM6DW09h7NtTEyMeWWdz9FXV6GtaNzvdta2NnjP2oc/qN0bVcy4+P4+93XyE5OZNWbL7HolbcxtdRNC4w8epB9K34AYNSS28lNTebcrm0c/GsFKdEXmfrQMjIqe0lGHTuEpqICgDM7/mXyfY/gXs9AI71Tm9ejLivDybsnN772fquekLc2UwtLJtx5f73bWDs6M/LGpQycOZcTG9dyavM60mKiWPvelTY0Nk4uDFu4hPLiYnb+8BUH/viZ7n364dC9R6PXolFXEHFwL4ChlNx/5DgOrvyVwuwsLh7aj0JlRGlhARZ29k3OqlUolUx7eBm/PvsYCeHnOLHpH0PWZ3uJDzvD+o/eRqtR02voSGY8+jTyKheoPQODdQHN82eApe26NqHxDv75Kwnnz6IyMWX2Uy9i71a9Yil44jRO/7uBnJRkjq9fw4jF1/fv8kLl+9pvxJgagbirsw3d/QKxsLOnMDuL2NAT+A4e3mrrOLDyF05u+gcAS3sHgsZNJGjspHoz3mVyOSMW3cI/779O6L8bCZk2G0v7ui/itQV1eTmbP/+Q8pIS0mKiSImKwLWXf8MPvMZpNRq2ff05klaLmbUNxXm57F3xA94hgzE26zzHeYIgdG3W1tYYGRlhZmaGs7PunOSFF17Ax8eHjz76CNC1gTx37hzvvfdem6+nywU0S0tLmTVrFpGRkezYsYOAgIA6t/X19cXXV3cyGh4eTkpKCrfffrvh/n79+vHdd99x4cKFavs5evSo4X5BEISuLu7sada89XKt9/UaMoJZy55v5xXVTX/Su+Hjt1n63meNLqFtjPOV2W4Ax/5ZReDoCdWCJwDH1q1CkrT06DcAj8DgRu3XxNyCec+9yu8vPUVGXAx/vPIMs598AVvn6hfFDv75Kyc3rQNg/F33N3mgQnN7W3bz9GLhy2/y52vPkxkfx5q3X2HBS2+Sk5zEls91Bx79psxk0Oz5yGQyXHr5sfP7r4g5dZzl9y6t1s/QwdOL4vw8cpIT+fPVZ+k3ZQajbrqtzqB4aVEhp//VTcQdMndRpw5mNpWJhQUjb1xKyPTZHFu3mjNbN2FiZcWw+TcSOGYiCqUSSZKIDT1BzKnjbP78Q25++7+N/hnEhp6ipCAfcxtbuvfpB+imsvefOosDK3/h+Ia/DX8TgWMm1pm1Wx9bFzfG3nYP27/5nIMrf6HnwCHYurg1eT/NkRhxnrXvv466ohyfgUOY/shTNd6P+qzM1OhIykuKO9XFF0En+vgRjq1bDcCU+x+tEcwEXfB81JLbWf/R25zY+A/Bk6bVm8l+LSvOzyPuzClAF9BsiEwux2/EGE5s+JuIA3tbLaCZGh3Jqc3rAZjywOMEjB7X6M8Q75BBuPkFkBQRzsE/VzD1wcdbZU2NdWDlL2TGxxn+P3zfrk4d0JS0WtQV5aiMG858aokTG9eSHncJE3MLbn7rY1a9+SK5qSkc+Xtlh2XSCoLQNEpjYx79eXWHPXdzXbhwgSFDqg/+GzZsWEuX1CjtX1vUAhqNhsWLF3P48GFWrVrV6B+SVqvlmWeewczMjPvvv5J5ccMNN6BSqfjf//5nuE2SJJYvX46bmxvDh7feVVBBEISOUFKQz9b//RfQBaO6B/ene3B/PPv0A5mMyKMHqw0/6UjF+XlkJyUAUJiTzcZP30er0bTKvjPj40iPvYRcocTEwpLc1BQuHt5fbZv8zAzOV2ZnDpl3Y5P2b+3ozNxnX8XM2obM+DhWPPc40cePGO4/smYlR9f+BcD4O++vNTu0Ldm6uLHwpbcwtbImLSaaNW+9zD8fvIG6ohzvkEGMu+0eQ6ZQn3GTuemND7F2dEKrUWNkakbfSdO4+e3/svT9z7n9o68IGqcrbw7duomfnnzI0HftaqH/bqS8pBh7d096Dhzabq+3PZlZWTN26V08+N3v3PP59wRPmGoYfCKTyZhy/2O6v4uEyxxY+XOj9xu+dycA/qPGVQv09Z00HZWxCZnxcVw+exrA8Ptojj7jJ+PVNwSNWs3un75Bqpyo3pZSoi6y9t3/oC4rw6tvCDMff67WYTFWDo5YOzkjabUkRpxv83UJTZOTmsy/ld8vIdNvoPewUXVu23PQMFx7B6AuL+Pgnyvaa4mdTuSRg0haLU7ePbFzdW/UY/SBz0unjlFWXNziNWjUFWz9+jMkSYvfiDEEjW3aBRGZTMaYW+4C4Py+naTHxbR4TY11+VyoIat0wIw5AEQc2oe6vLzd1tBYklZL5NGD/Pz0w3x5541t+hmWk5LE4VW/AzBm6V1YOTgy7vZ7ATi1eR1ZiQlt9tyCILQemUyGysSkQ/511dYdXSqg+eSTT7J+/XqmTZtGdnY2K1asqPZP77HHHuO+++7jq6++4rPPPmP48OFs3ryZ5cuX4+l5paePu7s7jz/+OF9++SX33Xcf3333HbNmzWL//v28//771fpyCoIgNFdmwmUy4uMMAy/aiyRJbP/2CwpzsrF1deemNz9kwYtvsODFN1j40puGnl0H/+ocJ5fJkREAWNjaoTI2IeH82VZbmz470ztkoOEk6Ojav6r9Tk5s+ButRo1HQB/cejc928PZx5el736Ka+8AykuKWffhm+z//SeOrVtteB1jbrmT/lNmtvwFNYO9uwcLXnwDE3MLUi9FUZyXi4OXNzMee6ZGZpxTDx+Wvvc5859/jfu//oWJdz+Es48vMpkMEwsLptz/GAtefBNrRycKsjJY++5rpERdrLaP8tISTm7RZQANmbe4Q/oztieViUmNnyOAmbUNk+97FICTm9YZJtzXp6SwgEsnjwHUmFxuYmFRbViHR2BwtYn3TSWTyRh3+33IFUpiQ08anretxJ09zao3XqS8pASPwGBmP/kCSlXdfVQ9KzOl48POtum6rjXlpSWsefsVtn/zRYv3VZyfx28vLuPHZQ/w97v/YecPX3Fi41o2fPQ2ZcVFuPYOYPTNd9S7D5lMxtillUGwvTvJuBzb4nV1RREH9wCNy87Uc/Tyxs7VHU1FhWGCfEscX7eGzPg4TCytDEGvpnLx7a0LYEsS+377scVraoySwgJDAL3vpOmMvuUOLOy7UVZURMyptv3cagpJkog5fZwVzz/Bho/fISsxHo1azYnK3pZt8Xzbv/kCdUU5nn36ETh2IgDe/QfhM3AIWo2GXT993S4XqwRBuD4YGRmhqZJ04u/vz7Fj1T+Hjxw5cvXD2kSXOrsIDQ0FYMOGDSxdurTGP73+/ftz9OhRnn76aV566SUsLCzYuXNntW303n33Xd5++222bt3KQw89RFxcHCtWrGDJkiXt9bIEQbiGxYWe5JenH+GXpx/mq/uWsuGT9zizfQuZCZdJibpIxMG9HF37F9u+/oytyz+jtLCw1Z47fN8uoo4eQq5QMOORp2qUOw1bcBMyuZzY0ydIjrzQas/bXEmV2QveIYOZfN8jgK40PLpyGmxzabUaLhzYA+iCQ/2mzMDI1IysxHiiT+i+bItyczi3cyugC741l4WdPYteeZuQ6Tfo1r9uNft//wmAEYtuYWA79yi8mqOXN/NffAMTC0usHJyY+8wrGJnUPgDP2MwMr34D6iyT6x7cj9s++JIe/Qeirijnnw/eIC89zXD/2e1bKC3Ix9bFld7DGt8v9FrkM2AwfSdNA+Df/31M6qWoere/eGg/Wo0aBy9vHDy9atwfMv0GQ4C4JdmZenaubgycOQeAPT9/Q0V520zYvHBwL2vffY2KslI8+/RjzjMvN1iG6VFZdp4gAppNsvunb4k7c4qzO/8lLz21RfsK3bqR1OhIspMSiD19gtCtm9j76/dkxMdhZm3DzMefqTXD9mouvr3pVRkEO1SZTXY9yc9IJykiHGQyeg+vO5v1ajKZDL+RugCo/rusubISEzjy90oAxt92T4umlI+86TbkCiWXz54mLvRki9bVEEmS2PHtlxRmZ2Hr6s6YpXcilysIqBx4U7WlTFuvoz7xYWdZ+cozrH33NdLjLqEyMaVf5UXMmJPHyc/MaPU1ndu1lYTwcyiNjZl0z8PVsqzG3noPCpWK+HOhRB071OrPLQjC9cnLy4ujR48SFxdHZmYm999/P1FRUTz99NNcvHiR33//nZ9++qld1tKlApp79uxBkqQ6/+ndfvvthIaGUlhYSH5+Pjt27GDcuHG17lMul/P8888TFxdHWVkZYWFh3Hzzze31kgRBuIblZ6Sz6fMPkSQtMrmckvw8Ig/vZ8d3X/LzUw/x+0tPsumzDziw8hfO7dpG2O5t7Prp61Z57ty0VHb+sByA4Qtvxsm7Z41tbF3cCByju5LfGUoAky6GA+DmF4DfiDH0nzYLgH+//JjctOafkMefO0NRTjYmFpb06D8IE3ML+k/V7fvI338iSRInNq5FXVGOi2/vFk9TViiVjLvtHmY89owhWDNk7mKGzm9aGXtbcfbx5d7//cgd/13e4mEOKhMTZj7+LA5e3hTn5bL2vdcoLSqkoryMExvXAjDohgXN6u94rRlzy13YurhRmJPNby88wboP36rWB66q8H26cvPAq7Iz9awdnRh32z0ET5japOFS9RkybzEW9t3IS0/jxPqamUT5mRmc3rqRCwf2kBwZQVFuTpMyfk5uWsfmzz5Aq1HTe/ho5j33ap3B9Kr0GZrpl2MoKchv/Au6jkUdP0zY7m2G/7908niz96WuqODM9i2A7rtk0j0PM/iGBfQeNgrPoL7MfvLFJvXDHL7gpso1HaUoN6fZ6+qKIg7tA8AjoE+Te4jqMzrjz51p9s9N0mrZ9s3naNRqevQbgF8Lp1/bODnTf6ouWLf3tx/RalunRUxtLuzfTeSRA8gVCqY//KThuzVg9ARAd/G4OC+3TZ5b0mq5cGAPPzx+H58tnc+mzz4gPuxMtQqP5MgIVr3xIqveeIHkyAsoVUYMnDWPuz//jgl33o9HYDCSpOXcrm31PFMT1yVJhO3ZwZ5fvgd0F02vzta3cXJm0GzdxOQ9P39HRWlpqz2/IAjXr6eeegqFQkFAQAAODg5otVrWrFnDP//8Q9++fVm+fDlvv/12u6ylyw0FEgRB6ArUFRVs+O87lBYW4OTty6JX3iL9ciwJYWeJP3+G1OgoTCwssHZ0wtrRGTNrG05u/IcL+3fjP3IsPfoNaPZzazUatnz5MRWlJbj2DmDQDfPr3HbY/BsJ37eL+LAzxIedxTOocYNwWltFeRlpl3S9PN38dEPaxtxyJ6mXokiJjGD9x29z0xsf1JgA2xjhlZkbfiNGG0pbQ6bP5uTmf0iPvUTEgT2GE/ah825stR4yfsNH4+rrR25aSqMHDLWX1hxOYGRiytxnX+H3F58kKzGeDR+/g3fIYIpyc7Ds5kDAqNovKF5vVCYmLHz5LQ788TPhB/YQffww0SeO4Dd8ND4Dh1CQmUFeeip56WmkRF00DAOpiz4o31qMTEwZu/QuNn7yHsf+WUXA6PFYOzohabWEbt/M/t9/pqK0pNpjlMbGdPPojv/IcfiPGouphWWN/VaUlXJ49R8cX78GgJBpsxl7692NbkFgbmOLvbsnWYnxJIaH4TtE9DevT2FONtu+/hwAKwcn8jPSiDl1jJBpzft7iTxygOK8XCzs7Bk8Z2GjMjHrY+/uiUsvP1IiIzi/dyeDb1jQov11JRGV2ZVNKTfXs3V2xblnL1KjI7l4+ECzfp9ntm8h+WI4KhNTJt7zUKt81w2Zt5iwPdvJjI/j/N6dbdIfujg/z3Cxd/jCm3H28TXcZ+/ugbOPL6mXoog4tI+QabNb7XklSSL6+GEO/fUbmQmXDbdHHNxLxMG9WDs6ETB6AmkxUcSc0l00kCuUBE+cwpC5i7GwtTM8pu+kaSScP8u5XVsZOm9xi99HeempbP/2S0MfZY/AYEKm1/7aB98wn/B9O8nPSGfNO68y55mXmzyUUBAEoapevXpx+HD1FiheXl7MnFm9rdYdd9TfjqY1iICmIAhCG9jz87ekXorCxMKSWU88h5GpGe5+gbj7BTKsMkPlapJWw8lN69j+7Rfc/uGXjZ7oW15STF56GrnpqeSnp5EUEU7yxXCMTE2Z/vCyerPjrBwcCZ44hdCtmzj41wo8At/rkKbQadFRaDVqLGztsHJwAkChVDHr8ef49bnHyIiLYdcPy5ly/2NN2m95STFRx3RfuFV7EZpZWdN34jRObvqHf7/61FDe26P/wNZ7Ueh+vlYOjq26z87I0q4bc599lZWvPKMLjp/XlQcPnr0AhbLu/ojXG0v7bkx7+EkGz1nIob9+I/LoQcPJ8dV8Bw1r9mT75uo1dCQegVtIOH+WPb98y8ibbmP7N5/rymQBRy8fjExNyUtPoyA7E3VZGanRkaRGR7Lvtx/wHTycoHGTUKqMiD9/hoSwsyRHXkCjVgMwasntDJo9v8mfMR6BwWQlxhN//owIaNZDkiS2Lv+U0oJ8HLy8mfrA4/z67KMkhp9r1pR4SZIMk7D7TZ7R4iCMXtDYSaRERhC2e3uz/h66osz4ODLi45ArlPQaMqJZ+/AfMYbU6EgiDu5pckAzLz2VfZXtT0bddCtW3Vrne8nUwpKh825k76/fc+jPFfgNG43KpHWnee///WfKiopw8PKu9QJtwOjxpF6K4vzena0W0My4HMvW5Z8ahiYam5szaNZ83AP6cGH/bi4c2ENeehqHV+taJ8jkcgLHTGDY/Jtq/c7vOWgoZtY2FOVkE3PyWLM/x7RaDaH/bmT/yl9Ql5WhVBkxbOESBs6cW+exnsrYhOmPPM3ad/9DUsR5/nz1Wea98FqTs4QFQRA6IxHQFARBaGXh+3ZxZvtmkMmY/shTWDs6NepxIxYtJerYEfIz0jiw8lfG33FfrduVFhWSGB5mCBhUzRyoavwd92Pt2PCwkCFzFhG2azvJF8OJO3OqRdmhemmxlyjKyaZH/4GNOlnVl5u7+gVW297SvhszHn2aNW+9Qtju7bj28q82EKUhkUcOoi4vw9bVHWefXtXuGzhzLqHbNqGpqABg6NxF18WJdVtx9PJm5uPP8s/7byBJWsxtbFulv+O1yN7dk1nLnictJppj/6yiICcLawddtrY+a9u1GYOpWkomkzH+jvv45ZlHiD5+hJhTJ9Bq1KhMTBm95Hb6TppmyKzUqCvIz0gnNvQUYbu2khEfV2dw1sK+G6NuvLXGgKPG8gwKJnTrRjEYqAGh2zYRF3oSpcqIGY88hZ2bBzZOLuSmpXD5XCi+g5sWREmJukhaTBQKlYo+E6a02jr9ho9iz8/fkpOSRNLFcNz9Altt352Vvty8R/+BmFg0Lzuu17BR7Pnle1KiLpKbltroYWBajYbNX+iqNtz8Auk3eUaznr8u/abMJHTrRvLS09jyv4+ZePdDLerNWVVK9EVD+4QJdz5Qa9Cu9/DR7Pnle9JjL5EZH0e3WvoON0VmfBx/vfEipQX5qIxNGDDjBgbMnGvIanTr7c+YpXcSdfQQFw/vx9TKmsE3LMTO1a3OfSqUKoLGTeLYP6s4s2NLswKaFeVlrPvgTUNWpntAEJPvfQRbl7qfV8+ttz+L//Mua955lcyEy/zx8tPMf+F17N08mryOxtBqNFw6eRQ3v8BW+1sQBEGojQhoCoIgtKKM+Di2f/sloCvnbkpwUGViwqR7HmLN269weutG/EaMxrWXLqghSRKXThzl2PrVpEZFIknVJ6abWFpVBkScsHZyxt0/kB79GpdtaGFnT98pMzi5cS0H//wVr74hzQ7sZVyO5eBfK7hUOchnyNxFjLzx1gYfpx8I5NY7oMZ93fv0Y8TiWziw8hd2/vAVjl7eNXqCSlothTnZWNjaVStl1ZebB44eX+M1WdjZEzRuMme2bcLOzaPJJ/tCTd4hg5hw1wPs+flbRt54K0ojo45eUqfm5N2TWcue7+hlVNPNozsh02ZxctM6tBpdr72J9zxUI6NLoVRh6+KGrYsb/afOJC0mmrDd24g4uA+5QoFHYDCeQX3xDArGxtm1RRcL3AP6gExGdlKC4X1+vZIkifB9uwjbvR0jMzPdZ76DMyYWFuz79QcARt18B/bunoDuPXlqy3piTh1v8mfc6X83ALoS6dYMShiZmtFr2EjO79lB2K7t13xAU5IkLhzQBfr9Rza93FzPwtYOj6Bg4s+FEnFwL0MbOcDu2LrVlVUbZkx7aFmj2z00llKlYuxt97L+w7eIOnqIxAvnGX/7vfQePrpF73tJq2Xn97pe4IFjJuBWx0UeMytrvEMGEn38COH7dzP65uaXOGYnJ7HqzZcoLcjH2ceXuc++ipm1TY3tVMYmBIwe36SLNMETpnBs3Wounz1NTmoyts6ujX6suqKCDR+/w+Wzp1EZmzBm6V0ET5jSpN+lQ/ce3PT6B6x5+xVyUpJY+eqzzHnqJUObn9a066dvOLNtE72HjWLm48+2+v4FQRD0REBTEAShhSStloTwMMJ2byPq6CHUFeV0D+7frCEwXn1DCBwzgfN7d7J1+Wcsfe8zEs+f5cCfK0iLuTIZ2dbVHc/AYDyDgnEP6NPik83BNyzg7PYtpMVEc2b7FvpNnl7rdhVlpZzZtpmykuIrAVRHZyrKyji85g8uHt4PkoRMJkeStBxd+xdKlVG9PwutVkNyZARAnQfWg29YQHLkBWJOHWf9x+9wy7ufYGphqetxdeIIh/5cQWbCZSy7ORA0diJBY3WZgQnh50Amw3/U2Fr3O3LxUl1T69HjW/0k73rVd9I0gidOFdmuXdiIRUtRqIxw6N6D3sNGNfi7lMlkOPv44uzjy4S7HjTc1lpMLSxx9PImPfYSCefP4t/CYSbNlZ+ZTnzYWTLiYjCztjF8/lk7OmFqZd3mf/N56Wls//YLQ4ZWbbz6htB/ypUMPO+QwYaApqTVNvpzrjA7i8gjB4DW79cK0GfcZM7v2cHFI/sZd/u9GJs1rRy+K0mPvUR+RhpKY2O8Qwa1aF/+I8YQfy6U0G2b8B0yvMEMu9ToSENZ9IQ77290xUhT9Rw4hJve/IBtyz8jM+Eymz77gAsH9jDx7oeaPXzu3O7tpMVEYWRqxqglt9e7bcDo8UQfP8KF/bsZedOtzRpEl5uWyqo3XqA4LxeH7j2Y98LrtfYFbi5rR2d69A0hNvQkZ3f8y5hb7mzU4zRqNZs+fY/Y0ydQGhkz77n/4B4Q1Mw1OHHj6++z9r3XSI2OZOWrz2Dt6IRHYF88+/TFMzC4xa1Owvfv5sy2TQBcrhyeJI6vBEFoKyKgKQiC0ExlxcWEbt1I2O7t5KalGG536dmb6Y881ezJzmNuvZvY0JNkJyXww+P3UpCZAegyAkKmz6bvpOktnk59NTMra4YtuIl9v/3Irh+XY+PkjFffkGrbqMvLWffhW/WeTIOuLG74wiXEnjrO3hU/cPCvFSiNdBM/a5OVEE9ZcRFGpqY41FEqJpPLmfbQk6x4/jHy0tP498uP6TdlJgevCvQWZGZwePUfHF6zEuvKPlaegX3q7BdmYmHBuNvvrff1CE0ngpldm8rEhFE33dasx7bV794zqC/psZeID2u/gKYkScSGniD6+BESws5W+5y/mp2rO/NfeL1Neubq++YdWPkrFWWlKFVGDJ6zEDNra/LS0yr/paJQGTHlgcerBQ/cAwJRmZhSnJdLWkw0zj2rt944tWUDxzesYcC02YTMuMHwvXVmx79oNRrc/AJw6uHT6q/Jtbc/tq7u5CQncvHwPoInTG315+gsok8cAaBH3wEtHsjWa9hIjq1fQ05yIitffZZ5z72KS8/etW5bUVrK5i8+QqvR0GvYKPzbeECbS8/e3PLuJxz7ZzVH/v6TmFPH+enJBxgwYy4DZsxpUtC6pLCA/X/8DOgGATUUZOvRfxAmFpYU5mQTH3YWr+D+TVp7fmY6q954gcLsLOzdPVnw0putGszUC540ndjQk4Tt2cGIRbc0WMWg1eqGPEYfP4JCpWLO0y83O5ipZ2ZlzcKX32Lb8s+IOnao8vNjm6G03ztkEBPufKBZn2UZ8XFs/+YLw/+XFuSTlZRAN4/uLVqz0LVkJSaAjDZraXAtkiSpo5fQIbRabcMbNUAENAVBEJqhtKiQ1W++ZGgYb2Rqit+IMfQZNxknH98WndSbWlgy/o772PjJexRkZqBQqeg3eTqDb1hYa+lTaxk4ax6ZCZcJ37eLDf99h5te/8DQi0qj1k1t15c7+Y0YTX7lVOb8jAy0GjXeAwYzYtEtOHp5A7oDGXV5OQf/WsHeFT+gMDKi/5SZNZ5XP3DExdcPuaLuILCJhQWzlr3AHy8/Rcyp44apovpAb78pM0k4f5aw3duIDztLXnoaAAGjJ7Tmj0kQhA7gGRjMiQ1/kxDefn00Q7duZNePXxv+XyaX4+zji0vP3pQWFpCXoQsmFuZkk52cyLZvPmf+C6+3alA3KzGercs/JSXqIgDu/kFMuveRevv1VaVQqvDq25+oo4e4dOp4tYBmTkoS+1Z8j0atZu+KH7h4eD+T738MWxc3zu7YAkD/qa03NboqmUxGn3GT2Pfbj4Tt2t6ogGZpYSHGZmZNzvYqKy6mKDe72m0KpRIrB6d2ufgSfVwX0PQZOKTF+zIyMeXG197j73f+Q1pMFH+9/gKzl71Qa3ubvSu+JyclCQs7eybe/WC7vFaFUsWwBTfhO2Q4277+jJSoixxe/Tun/93AoNnz6T91ZqOCugf/XEFpQT727p70m9Jwz0+lSoXfiNGEbt3EiQ1/071Pv0a/3pKCfFa98SL5GenYuriy8OW32qzvo3fIQCztHSjIyiDq6MF6g8ySVsu25Z9x8dA+5Aols5e9QPfgfq2yDiMTU2Y+/izlJcUkRYQTf/4s8WFnSI+LIebUcRLOn2PUktvoN3lGjfdbRXkZ6vLyGgHfsuJiNnz8NuryMroH90erVpMQfo7EC+dFQPM6UpyXy28vPIFcqeDe//2EkYlpRy+pU1OpVMhkMjIyMnBwcLhuEgIkSaK8vJyMjAzkcjlGLWhRJQKagiAITVRFkUSjAAEAAElEQVReUszf7/6HtJhoTC2tGH3LnfQeOrJVJ3v2GjqSUUvSKCnIJ2Ta7FbPyKyNTCZj8n2PkJ+ZTmJ4GH+/9xpL3vwIMytrNn32ATGnjqNUGTH32VfwCAw2PE6r1aAuK6t1gu7Q+Teirqjg6No/2fXDcpQqoxpDffQDgRrTx8mphw8T7nqAbcs/qwz0zmDwDQsMgV7/kWPxHzmW3LRUzu/ZTkVZGX4jRrfgpyIIQmfg5heAXKEgLy2VvPS0Niud1UuOvMCeX74HdP37fIeMwN0/qNYss6ykBH599lEunz3Nhf27mz38qCqNusKQ6abVqDEyNWX0zXc2uW8e6MrOo44eIubkMUYsuhnQnUzs/ukbNGo13Ty9KMjMIPVSFCuee4zuwf0pzsvFwr4bPQcNbfFrqUvA6PEcWPkLKdEXyUy4XCPoUZyfR8L5c8SHhZJw/iw5KclYOzox6d5H6N6nX4P7Lyks4Pj6NZz+dwPqsrIa9/sOHs7Mx5+t90JaS+Wlp5IZH4dMLm9xubmemZU1i159m/Ufvc3ls6f55/3XmfLA43j3H0Reeip5GWmkx8ZwZrsuKD31wSfaJNuwPt08unPT6x9w8cgBDq36nZzkRPb//hMnN/1D8IQp2Lq4YeWoa1tjYWNHRXmZIds4OymBs5Vrn3Dn/SiUjTtdDZk2m3O7tnH57GnC9+0icEzjLmYeXv0HuakpWDk4seClt1pccl0fuVxBnwmTOfTXb5zetoneI0bXWs1TVlzM1uWfEHX0EDK5nJmPP9Nqfz9VGZma0aP/QHr01/Vcz05OZNvXn5EUEc6uH78m4tB+Jt79IOXFxcSfP0N82BlSIiPQaDR4BvWlz/jJ9Bw0DIVSydavPiEnJRlLewemP/IUZ7ZtrgxohtXZxki49oTv20VFWSmUQXJEOF6tMGj0WqZQKHB3dycxMZG4uLiOXk67MzMzw9PTE3kL2lLIpOs1v7WV5efnY21tTV5eHlZWVh29HEEQ2khFWSl/v/MfEi+EYWJuwcJX3jZkJF4rSgoL+OOlp8hJScLJuye2Lm5EHNyLQqlkztMvN/ngRJIk9v76PSc3/YNcoWDJmx9VG+rzzYN3UJCVwcKX38YzKLiePV2RFhONhZ19m554CILQufzx8tMkR14gZPoNjLnlzjYLRBXn5/Hrs49SmJ1Fr6Ejmfn4sw1mTRxd+xcHVv6CiYUld3z8VYuy6VOiLxp6EYKuBLQlvQiL83L56r6lIEnc+9VPWNp149LJo/zz/hvIFUpu+/BLjExM2PnDV4ZsQoCRN97KkLmLmv06GmPdh28SffwIA2bcwNhb76G8pJiIQ/sI273dkJVam6Bxkxhzy121TgwvKy7m5KZ/OLnpH8pLigFd4KbqCVNZSTGSVku/KTMYf8f9bZYVc3LTOvb88i3uAUEsfvXdVt23Rl3Bv//7hIiDe+vcZsCMOYy99e5Wfd6m0mo0hO/fzeHVf5CfkVbjfrlCiVajrnF77+GjmfnYM016rqP/rOLAHz83+n2Yk5LET08+iFajYeHLb+EZ1LdJz9cchdlZfPvwnWg1Gpx9fJl8/2PV2u1kJlxm/cfvkJOciFyhZNpDT+A3ovnDpJpK0mo5s30L+37/iYrSkga3N7GwxKVnL2JDTyJXKLnx9fdw6dmbhPNn+ev1F7CwtePer35ulfeYfgBkXnoqSLrWFW15QUJoGkmS+OnJB8lOSgBg0Oz5LRrSdT3RaDRUVFR09DLalUKhQKlU1vnZ0Nj4msjQFARBaCR9D8nEC2EYmZox/4XXr7lgJuhK3uc99x9+f+lJ0mKiSYuJRq5QMPOJ55t1pVUmkzFm6V3kZ6QTdewQmz//kFve/QSVsQn5mekUZGUgVyhwuaq3W32unnIuCMK1z2/EaJIjL3Bq8zoSL4Qx5f7HWv0zWKvVsOnT9ynMzsLW1Z0p9z/aqBPxgbPmcfHIATLiYtj10zdNDsToHf1nFQdX/ookaTG1tGL8Hfe1eFq0mbUNLj17kRJ1kdhTJwgYPZ7dP32jW/fMOYby9dlPvkjU0YPs/GE5coWCPhOmNPs5Gyto3CSijx/h/L7dlBYVEXn4gC67p1I3Ty88A4PxCOqLk7cPx9et4XRl7+rY0ycYe9s9WNjaVeslGnPqOKWFBYBusvOIxUvxDhlU7WcYefQgG/77LqFbN2Hr7ErI9Bva5PVdquyf2XPgsFbft0KpYvrDT2JuY8vJzetAkqoNq3L28W1UuXZbkysUBI2diP/IMYTv201y5AXD76sgK8MQzDQxtzBkbXbz8GLgzDlNfq6BM+dy8fB+3fvwx68bnLC9//ef0Wo09Og/sF2CmQAWdvZMe2gZO777nyErevCchQyZu5ioY4fY9vVnqMvKsLDvxuwnnsfFt/YeqW1FJpfTb8oMvAcMYsd3/yP29AlMLa3wqBxE6RnUF7lCQdieHYTt2UFhViaxoScBGHf7vYaers6+vZErlJUByDRsnJybtZ6c1GT2rfiBrMR48jPS0aivBL8tbO0IrBwEaePs0vIXL7RISlSEIZgJEB/Wfi1iujqFQoFCBOebRWRothKRoSkI1zatRsO6D98k5tRxVMYmzH/xDdx6+3f0stpUUkQ4q958Ea1aw4zHnqH3sJEt2l9JQT4/P/0wRTnZ9Jsygwl3PsCFA3vY/PmHOPfsxc1vfdxKKxcE4VokSRLh+3ax5+dvKS0qRCaXM2j2fIbNv6nB4RqNdWDlrxxd+ycqYxNufvtj7N09G/3YtJhofnthGZKkZc4zr+AzYHCTnruksID/3b0EJAn/kWMZe9s9rdbL78jff3Lwz1/xHjAYZx9fDv31GxZ29tzx3+U1epxptRo0FRUtHmDTGFqNhm8euoOinCs9Lm1d3ekzbhL+o8ZhYWtX4zFJFy+wbfmnZCcn1rlfO1d3hi+6hV5DhtdZon98w9/sW/EDyGTc8OSLrV5eX1JYwFf33Iyk1XL3599h7di8gE5jn0upUrXL76w1aTUaCnOyMDYzx9jMvFX2mRYTzW8vLkPSapnzzMv4DKi9d2lSRDgrX30GmUzOrR983u59Hguzs6plRZvb2hneB559+jHj0afbrJdnU9TXu1ar1XD5bCgXDuzB1tmVofNvrHbhQJ9VP+WBxwkaO7HJz63VavjthWWkx14y3CZXKLDs5kBZcTGlBfmG2z0CgxkyZ1Gr9RkVmm7r8s8I272N7sH9uXz2NDKZnAe/+73WTHpBaIjI0BQEQWhFFw/tq9ZD8loPZoKuZ91tH3yBpqLCMByoJUwtrZj6wOOsefsVQrduokf/gYaBQG69G+6fKQjC9U0mkxE4ZgJefUPY9cNyIo8e5Ng/qzi/dyfdPLobMtOsHZ1w6N4DWxe3JmU2Xjp5jKNr/wRg0n2PNCmYCbrM8QEz53Biw9/s+P5/dfbcrEti+DmQJOzcPJj+yFNNeu6GeIcM4uCfvxJ/NpT4s6EAjFl6V60DG+RyBXLj9skUkSsUDF+4hMOrfqd7cAhB4yfh1jug3t+bW29/lr73GUfX/smZ7VswMjPD2sHJ8Pu39+iOd/+BDZaiDpw5l9zUZM7u+JdNn3/Ajf95r1Wz/2NPHUfSaunm6dWmwUyg3Xtktha5QoFVt6ZP066Pk3dPBs6cy/H1a9jxnf59WD1YKkkSe1foeuQGjZvYIUNrLOzsq2VF64OZQ+YuZviiJbX21uwI9QWj5HIFPfoNqHUoFYC7fyDJkRdIvBDWrIDmuZ3bSI+9hJGpGbOWPY+dixsWdvbIFQo06gounTjKuV3biDt7moTzZ0mKOM8t735arYRfaB/lpSVcPLwfgKFzF1OQmUF2ciKJF8LatBezIIiApiAIQiNEHj0IwMDZ86oNxLnW2bo0bpJuY3n1DSFk2mxObVnP1q8+NQxSasxAIEEQBABzG1tmLXueqGOH2Pn9VxTlZFfL8NOzsLXDI6gvnkF98QwKrjdwkhodyebPPwSg/9RZ+DezZ93whUuIPnaY3LQU9v/+IxPvfqjRj9WX5zW2l3BTOHTvgYV9NwqzMgFdNlPvYaNa/XmaI3jC1EZNOa9KaWTEiMVLGbF4abOfVyaTMeHOB8jPSCfuzCnWvvcat7zzCRZ29s3eZ1XRhnLzlk83F5pm2MIlRB07RG5qCvt//6nG+zDyyEFSoi6iNDZm+KJbOmiVur/BXkNH4hHUl9CtG3H19b+mMgzd/YM4tm41SRfON/mxJQX5HFj5CwAjFt+CV3D/avcrlCp6DR1Jr6Ejyc9MZ9vXn3P57Gm2ff0ZN73xQacJCF8vLh7eT0VpCbYurrj5B+IR1Jfs5ETiz58RAU2hTTV/nJAgCEI70Wo0RB07RH5mRoc8f3lpCXGhpwDoNWREh6zhWjJyyW3Yu3tSnJdLXloqIDI0BUFoOt/Bw7nr029Z9MrbTLn/MYbOvxH/UeNw6eWHQqWiMCebC/t3s/WrT/j2oTvZ8sVHVJSW1thPelwMa95+hfKSYtwDghiz9M5mr0llbMKkex8B4Mz2LcRV9pZrjITzlQHNwNbv5SeTyfCpnJIsk8sZf8d9bTYIpyuRKxTMfPw5unl0pyg3h9P/bmiV/arLyw3HDT4Dxcl8e1MZGTO5yvtww8fvEBt6Eq1Wg7qigv1//ATAoFnzam1r0N5MLSwZNv+mayqYCbqhPTKZnNy0FAqyM5v02IN//kppYQHdPLrTb3L9vWCtujky5YHHMDI1IzU6ktNbWud9LDRe2K7tAASOnYRMJjNcmEsQfTSFNiYCmoIgdGqSJLHrx+Ws/+htfn32UZIjI9p9DXGhJ1FXlGPj5NIqpdfXO5WRMdMfeQqFUlckYOvi1qKJwIIgXL9UJiZ4BAYTNG4SIxbdwvSHn2TJGx/y0A8rWfjyWwyZuwgX397IZHLC9+/m95eeJDs5yfD4rMR4Vr/5EqVFhbj08mPuM6+gUKpatCbPoGD6TZkJwL9ffUJxfl6DjynKzSErMR5kMtwDglr0/HXpM34KxubmjFh0S4eU2HZWxmZmDJm3GICoY4dojfEC8WFnqCgrxcLOXgyx6yAegcEMnDUP0FXZ/P3Oq3z38N1s+Pht8tJSMbexNdwvtA1jM3McvHoANClLMy0mmjM7/gVg/J33N2qSuaVdN8bcorsYdeDPX3WT0KuQJInQrZtY9eZLpMVEN3otQsOyEhNIjryATC4ncMwEADwC+gCQmXCZotycjlyecI0TAU1BEDq1k5v+4cz2LQCUFhaw6o0XiTl9vF3XEHn0EAA9Bw8TGS2txNHLm1FLbgfAu4mDMwRBEBqiMjLGM6gvI2+8lSVvfsSiV9/G3MaWzITL/PbC40QdPUROShKr3niRkoJ8nLx7Mv/51zAybXzPy/qMvvl27Nw8KMrNYce3XzYYJIuvzM507O6NqWXbDJd08u7Jwz/8yZC5i9pk/12Zd/+BKFQqclKSyUq43OL96cvNfQYOFccNHWjMLXey9L3P6D91FibmFhRkZRBzSncMOXzRzbX2kBVal7u/7gJNYmXP9IZIWi07f1wOkoTfiDGGwFhj9Bk/GfeAINRlZWz75gvD5255aQmbPn2fnT98Rfy5UFa/9TIZl2Ob/mKEWoXt0WVn9ug/0JDxbGpphYOXNwAJ4eda7bmK8/PY//tP5KQkNbyxcF0QAU1BEDqtqGOH2LviBwBG3ngrXv0GoC4v45/33+D83p3tsgZ1ebnh4FeUm7euATPmcMd/v2bUTbd29FIEQbjGufsHccu7n+LmF0h5SQnrP36b315cRlFuDt08vZj/wuutNmUZdKXn0x9+ErlCSdSxQ5zfs6Pe7RPCzgDg0Qb9M4WGGZma0b2yR1/UscMt2pek1RJz8hgg+md2Bo5e3oy/4z7uW/4LMx59mh79BuA/ahxBYyd19NKuC+7+gQAkXQhr1Pbh+3eTEhmBysTUkHHZWDK5nMn3PoJCpSL+XCjn9+4kKymB3198kouH9yNXKLB1cdMlSLz5ElmJCTX2oZ/c3lFtrroajVpN+L5dAPQZN7nafZ6BumB0a5ad7/phOcfWrWbjp+8jabWttl+h6xIBTUEQOiXdgIaPQJLoO3kGg+csZM7TLxMwahySVsu///svx9atbpXSsPpcPhdKRWkJFnb2OPv4tulzXY/sXN1aXN4pCILQGBa2dix8+S0GzJwLQFlREXau7ix86c02yYp08u7JiMW6gSO7fvqG3NSUOrfVZ2i2xUAgoXF8Bw8HIKpyCGBzpURHUpSbg5GpGR6Bjc8uE9qW0sgIvxFjmPf8a5UXG8TQmPbg5qcLaGYmXKakIL/ebcuKi9n3248ADJt/Y7MGdNm6uDFswRIA9vz8Lb+9sIysxHgsbO1Y9Mo7LHnrIxx7+FCSn8eqN18kJzUZ0F2IiDxygJ+fepjVb73EX68/j0atbvLzX29iTh2jOC8XM2sbevQfWO0+j8p+0PHnz7TKc6VEXTRMUk+PvUTEwb2tsl+haxMBTUEQOp38jHTWvv866vIyevQbwPjb70Umk6FQKpn64BOGnkf7f/+JY+tWt+laoo7pys19Bw9HJhcfmYIgCF2ZQqlk7NK7uOHpl+k7aToLX36rTXv4Dpw1F3f/ICpKS9j85UdoNZoa2+Slp5GXlopMLse98uRfaH8+A4cgk8vJiI8zBDmaI/LIAQB69BsgLtgJ1z0zK2vs3DwASGqg7Dzi4B6K83KxdXElZPrsZj/nwJlzcfDypqy4iIrSEtwD9Bn6AZiYW7DgxTd0g8Bysln1+ouc37uTX59/nA3/fZfsJF3WZl5aKhf27272Gq4HiRHn2bdCF4AOHDPB0Btfz90/CJlcTm5qCvmZ6S16LkmS2LviewDDd/b+lb+gLi9v0X6Frk+cnQuC0KlUlJWy9r3XKM7LxcHTi5mPP1vtKrpMLmfMLXca+i8e+ONnw9W61qZRq7l04igAvoOHtclzCIIgCO2v58AhTLz7wWZlADWFXK5g2kPLMDI1IyUyguPr19TYRj/d3NnHt9V6eApNZ2phiUegLkM2qrJ3dlOUFBbw7//+y8lN/wC6vtuCIFwpO09soOz8fGXpcvDEaS26GKBQKpn+0DKcfXwZMncxC196C3MbW8P9ppZWLHjpTWxd3SnIyuDf//2XjLgYjExNGbbgJobOvwmAY+tWodXWvAh1vSsvKWbnD1/x56vPkpuWgrmtnWEQXlXGZmY4e+uq2xLOt6yPZvSJIyRFhKM0MubG197Dws6egswMTm1Z36L9Cl2fCGgKgtCp7PvtRzITLmNuY8vc5/5T58nd4BsWEDL9BgC2fPkxyZEXWn0tiRfCKC0swNTKGjd/kTUjCIIgNJ2VgyPj77gPgKNr/6ox8fVKuXnfdl+bUF2vIbqy8+gm9NGUJImLhw/w07IHdP29ZTJCpt9A76Ej22qZgtClGAYD1TPpPCcliZTICGQyOf4jx7b4Obt5enHz2/9l5I1La20vYG5jy8KXdUFNpZExg25YwN2ff8/whTczaPY8TCwsyUlJJvLwgRav5VoSc/o4Pz35EKFbNwEQNG4St3/4P6y6OdS6vb4vdHxY88vONWo1+3/7CdD137d1cWPkjbr++8f+WUVxfl6z9y10fSKgKQhCpxFz+rjhC3Lqg09gad+t3u3HLL0Tn4FD0FRU8M/7b5Cbltqq69FnaPQcOAS5XPRaEgRBEJonYPR4XHr2pqKslEN//Wa4XZIkQ4amPjtQ6Dg+A4eCTEZK9EUKsjIb3L44P4/1H73Fxk/epTgvFzs3D256/X3G3XaPaFMjCJX0fTTTYy9RXlJc6zb6wTJefftXy6ZsS5Z23bjtg8958PvfGb3kdkMvZSMTU0PJ+9G1f4nhM5XObN/C2ndfoyArA2tHJxa8+CZT7n8MEwuLOh/jaeijebbZcw/O7dxKTkoSplbWDJo9HwD/UWNx6N6DsuIijvy9ssF9SFotYXt2kJ0spqNfa8Q3rSAInUJxfh5bv/oUgJBps/HqG9LgY+RyBTMeeVrX3Lsgn7/f/Q+lhYWtsh5JqyX6uC5Dw1dMNxcEQRBaQCaTMXqpbmLvuV3byEqMByAnJZnC7CwUSiWuvf07cokCusFRrr10v4eGpp3npaex8pWniT5+BLlCwdD5N7L0vc8MjxcEQceqmwPWjk5IkpbEiJpZmpJWS3hlv8qA0ePbdW0KpQqVkXGN2/tPnYWRqRmZCZe5dPJYu66pM8pKTGDPz98C0HfSdG774Eu6B/dr8HGuvf1QKJUUZmWS24zexGXFxRxa/TsAwxcswdhMV7knlysYfYvuO/XMts0N9j0+u3MrW7/6hI2fvtfkNQidmwhoCoLQLK3ZU0aSJLZ9/TnFebnYu3sycsltjX6sysSEuc+8goV9N3KSE/n7nVcJ37+bguyGMyvqkxwZYZhSKqbOCoIgCC3l7hdIz0HDkCStYZJvQuX0V9de/rWeVAvtT192HnWs7mnnGZdj+eOVp8lJScbKwZGb3/4vIxbdglIlhgAJQm28+g4A4MialTUyHhMjzpOfkY6RqRk+g4Z2xPJqMDG3oN+UGQAc+fvPZmcXXgs06go2f/4h6opyvPqGMOHO+1GZmDTqsSpjE1x6+QEQH3a2yc99fP1qSvLzsHV1p8+EKdXu8wruj1e/AWg1Gg78/nOd+9BqNZzctBaAjLgYMuPjmryOxhD9VjuGCGgKgtBkh1b9xpd33sS5XdtaZX/ndm3j0okjuibejzzV5JM6Czt75j37KioTU1KiL7Lli4/45oHb+eGJ+9nx3f9Iib7Y5DXpp5v7DBgsppQKgiAIrWLUktuRKxTEnDpOfNhZwwmeh7hw1mn0HKQb5pN0IZzivNwa9yeEn2Plq89SlJNNN08vbnr9Axy9vNt5lYLQtQydt1h3nB51Uddrtgp9uXnvYSM71YWdATPmoDQyJi0mistnTnX0cjrMob9+Iz3uEiaWVky5/7Emt9PQl51HHTvUpMBwUW4OJzf+A8DoJbfXmKIOMPrmO5DJ5EQePUhSRHit+7l04ig5KVcyOCMO7WvC6hum1WjY8uXHfHXvUhLCWzb8qC6xoSdJi4luk313dSKgKQjXKXV5OVlJCSReCKvxr76y7cgjBzi8+g/KS4rZ9s3nNQ5KmionJYndP38DwIgbb232SYFD9x7c/NbHDLphAU7evshkcnKSEzmzfTN/vPw0x9evafBLVKOuIPFCGIdW/W6YtOhbmakhCIIgCC1l5+pG8MSpAOxd8b2hf6b+hE/oeNaOTjh590SStESfOGK4XdJqiTi0jzVvv0J5STFufoEs/s+7WNjZd+BqBaFrsLCzZ9gC3fTwfb//RGmR7lyjoqyUyCO6wTvtXW7eEDMra/pO0n1eH1n7VwevpmMkhodxbP0aACbf83CzPu96DR2BXKHg8tnTnG7CVPKLh/ahrijHydsXn4FDat3GwdOLoHETAdj54/JasyRPbFhr2BYg4uDeVsu41Wp1wczwfbsoLchn8xcftVr7M734sDP8/c6r/Pmf51pcgXgtqhnmFgSh0ygvLeHI33/iFRzS4rLnrKQETmz4m+zkJPLTUynMya5zWyNTM+Y88zIeAX2q3Z6dnMi/lX0u7dw8yE5KYOtXn6JQqfAbPrrJa5Ikie3ffIG6rAyPwGAGzpjT5H1UZe/uwegltwNQWlhI4oUwLuzfTeTRg+z77UeSIyOY+uDjGJuZGx5TVlxExMG9RB8/QmLEedRlZYb7TCytGtXLUxAEQRAaa9iCJYTv20V67CVAV5Ln3NO3g1clVOU7eDhpMdGE79uFVq0h/vwZEs6fo7SwAICeg4Yy/dGnO1U2mSB0diHTZhO2ezvZSQkcWvUb42+/j+jjRygvKcHa0Qm33gEdvcQaBs6cR+jWTSRFnCcxPAz3gKCOXlK7KSsuYvOXH4EkETh2YrOTPOzdPRmz9G52//Q1e1f8gJO3L25+Df+uLxzcC0DgmPHIZLI6txt5021EHj1IRlwMZ3dspd/k6Yb7ki5eIDnyAgqlkhuefomfn36EvPQ0UqIu4lpZCt9cklbL9m++IOLgXuQKBWbWNhRmZbLjuy+Z8dgz9a65Kc+x99cfAF3wf9+KH5nx6NMt3u+1RGRoCkIndmH/Ho6vW82qN1/k8Jo/mj1l7+LhA/z2wjLCdm8n+WK4IZipMjHF1sUVW1d3wz9zWzvKS4pZ8/YrhinfABWlpaz/6G0qSktwDwji1vc/p8/4yUiSls2ff0jU8fqb59cm/twZEsLPoVAqmfrA4606EdTEwoKeg4Yy84nnmHj3gyiUSqKPH+a3F54gIz6OxAthbPnyY5bfdys7vvsfcWdOoS4rw9TKmt7DRjHpnoe57f3PURk3rkeMIAiCIDSGmZU1g29YaPh/N/9A0dqkk9GfuCdFhLPzh6+IOnqI0sICVCamDJgxh1nLnhfBTEFoIoVSyfjb7wMg9N9NZFyONZSbB4we36rnAa3Fws6eoHGTADiy9s9m76eirJTwfbv48z/P8eVdN9VZHt1ZVJSXsf3bLynIzMDayZnxt9/bov31nzqT3sNHo9Vo2PjJu7W286gqJzWZ1OhIZDI5vYaOrHdbMytrRiy6BYCDK3+hOD/PcN+JDX8D4D9qPNaOzvhW9miNqAyWNpckSez8YTlhu7cjk8mZ/sjT3PDki8jkci4e3k/EgT0t2r/ehYN7SY+7pDsflcmIOLi3zcrauyqRoSkInVhaTJTuPySJQ3/9Rmp0JNMeehITC4tGPV6jVrP/9x85uWkdAB4BfQieNA0bR2esHJ0wtbSqcfVIXV7Ops8+IPr4Ydb/9x0m3vUAwROnse2bz8lKjMfc1o6Zjz2LQqlk4j0Poa6o4ML+3Wz873vMfvIFfAYMbtTaJEni4J+/ArppeVYOjo38qTSNTCaj76TpOPbwYcPH75KTkswvTz9cbRs7Nw+Cxk6kR78B2Ht0b5UraoIgCIJQl5AZNxC6fTOFWZl4Bor+mZ2Nnas7PfoNIP78Wdx6++MR2BfPoGCcvH1r7eMmCELjdA/uR68hI4g8epB/v/qEjLhYAAJGda5y86oGzV7A2Z1buXz2NCnRF3Hp2bvRj02Pi+Hsjn+5cGAP5SXFhtsPrf6dhS+92RbLbZG02EuE7d7GhQN7KCsqQiaTM+2hJzEyNWvRfmUyGZPve4SMy7FkJyWw8dP3WfDiG8gVilq31wccPfv0xdzGtsH99500nXM7t5IRH8eBlb8w+d5HyElJMrQNGThzLgB+I8cSvn83Fw/vZ+ytd9f5/PWRJIm9v37Hme2bQSZj6kNP0HuYLug6fMESDv61gh3ff4WbX2CLzm8ryss4sPIXAIbMW0xBZgZntm9m1w/LWfreZ81a+7VIfCMLQieWVlmO5jdiDNHHDhNz6jgrnn+MmY8/h6mlFXnpaeRlpJKfnoZGrcbKwQlrR90/hVLFli8/MlwBHHTDAkYuXtrgh5/SyIhZy55j53dfcXbnv+z47n9EHTvM5bOnkcnlzHz8WcMXi1yuYOoDj6OpqCDyyAH+ef91rB2ddAf+ffriGRhc55dQzKnjpERfRGlszOA5C2vdpjW59OzNLe9+wubPP+Ty2dOojE3oPXw0fcZPwsXXTwQxBUEQhHajMjJm9rLnubB/D30nTevo5Qi1mPf8a0habafMGhOErmzMrXcRE3rC0HbDtXcANs4uHbyqulk7OhEwahzn9+7k6Nq/mPP0y416XMzp4/zz3htIkq7CzsrBCb/hozi+/m/iz4WSlRiPvbtnWy690eLOnGL/Hz8bficAVg6OjFh0C269/VvlOYxMTJm97AV+e+EJEs6f5eBfKxh10201tpMkiYgDuoCm/8ixjdq3XKFg/F0P8Oerz3Ju1zaCx08hbM92kCS8QwZh7+4BgGdQX0ytrCnOyyU+7EyzWoud3fGvIVlo8r2PEDBqnOG+wXMWEhN6gpTICLZ8+TELX3kLubx5gcfTWzZQkJmBpb0DIdNnoy4v5+KRA2QmXCZ02yZCps1u1n6vNSKgKQidlEZdQVbCZQBGLF7KwFnz2PDx2+Slp/HbC080ej9GpmZMfegJfCundjaGXK5g4j0PYWZjy5E1f3D57GkAxtxyJ+5+gdW3VSh0k8mNjQnfv1sXZE3fRthu3QT03sNGMe3hZdXK6SStloN/rQCg/9RZjbry1hrMrKyZ9/x/SI2OopuHZ4uvNgqCIAhCc7n07N2kTB+h/YlgpiC0Pqtujgydu9iQfRbYyYYB1WbwnIWc37eLSyeOkh4X0+AQU61Ww74VPyJJWroH92fQ7Pl4BgYjk8vJTk4i+vhhTv+7gYl3P9ROr6BupYWFrPvoLdRlZSiUSnwGDaPP+Ml0D+rb6p+B9u4eTL7/UTZ9+j7H/lmFm18A3v0HVdsm43Is2cmJKFQqejbh/NXdLxD/UeO4sH832775nJzkJAAGzppn2EahVNJ72EhCt24i4uDeJgc0i/Pz2P/HTwCMWnI7fcZPrna/XKFg+kNP8suzj5J4IYwTG9Yy+IYFTXoO/fMcrRxENWLxLaiMjFEZGTPqxlvZ/u0XHPxzBb2HjWq3c+jOTHxLC0InlZWYgEatxtjMXDdxs4cPt7zzqWHKm0KpxNbFle7B/QmeOJX+U2fhPWAw3Ty6G/o+OnTvwc1v/7dJwUw9mUzGiEU3M+HOB1CoVASOmUDI9Btq3VahVDL1wSd4+IeVzHvuPwycNQ/HHj4gk3Hx8H42ffoBWs2VqXNRxw6REReDkakpg6p8ybQHuVyBay8/EcwUBEEQBEEQhA4wYOZcHHv4YGHfjV7D6u+R2BnYubrTu7KX49F/VjW4/cXDB8hKjMfYzJyZjz1L9z79DMHBkGmzADi/b1erT8RujnO7t6EuK6ObR3fu/epnZj3+LF7B/dvsgo7f8NH0n6r7GWz/9kvKiour3X+hsv+kT8hgjM2adr42+uY7MDI1JeNyLOqKcpx9fHH3rz7IyW/EWEB3PlpRXlbLXup2YOUvlBUV4dC9h6GM/Wo2zi6GnqMH/1xBXnpqk54D4MjfKykvKcbBy7taBmjQ+Ek4eftSXlLM/t9/bvJ+r0UiQ1MQOil9yr+jl7ehHNrEwoI5T79MWXERRiamdX7RSJJEWXERxmbmLS6l7jdlBkHjJqE0MmpwWyNTM3r0H0iP/gMBiDt7mn/ef52oY4fY8uXHTHt4GQAH//oNgAEz5mBqadWi9QmCIAiCIAiC0HUoVSqWvPkRMpmsy/QCHDJ3ERcP7yfyyAGyk2/GztW91u20Gg2HV+nOdQbOnFtj9oF7QB+6eXqRGR9H2O5t1TII25tWqyF060ZA19vZzMq6XZ531JLbiD19gty0FPb/8TMT73oA0FXxRRzaB4DfyDFN3q+FrR3DFixh76/fA7rszKvPhV17+WHl4ER+Rhqxp443OHRILzU6knO7dBWI4++8v96/28CxE7lwYA/xYWc4vGYlUx94vNGvIScliTPbNgO66siq5/tyuYIJd97P7y89yfm9OwieOAXXXq3TEqCrEhmagtAOYk+f4NdnH+NCEyaq6ftnOvaoWdJgbGZe71UzmUyGiblFq/WFbEwwszZewf2Z9cTzyBUKIg7uZdvyz7mwfw/ZSQmYmFswYMacVlmfIAiCIAiCIAhdh0Kp7DLBTNBVvvkMHAKSxLF6sjTD9+8mJyUZE0srQqbX7HMok8kMGYqh2zah1WpqbNNeLp08Rn5GOiaWVviNaHoAsblUxiZMulc3pPXMtk0kRpwHICkinMKsTIzNzOnRb2Cz9t1/6iy8QwbhHTII38HDa9wvk8nwGz4KgAsHGnduLmm17PxxOUgSAaPG1WjBVttzjLzxVgDC9+4iu7L8vSFajYbdP32DVqOhR/+BdO/Tr8Y2Lr69CRo3CYBdP36DJEmN2ve1SgQ0BaGNZScnsfHT90iPu8SWzz8yXHVqSHpcDACOPXq25fLanM+Awcx47Blkcjnn9+5g29efA7orZsZm5h28OkEQBEEQBEEQhIYNmbsIoHJuQM1SYo26gsOr/wBg8A0L6mxx5T9yDCYWluSlpxFz6kTbLbgBp7dsACB4whRURsbt+tyeQX0JGqfrQbnt689Rl5dz4eAeAHyHDG92Qo1CqWTus68y99lX6wyY+1UOG4o9fZzSoobL/sP27CA1OhIjU1NG3XxHo9bh4tsb75BBSJKWw6t/b3B7Satl61efEBt6ErlCyeh6nmfUTbfRPbg/E+964LofbCsCmoLQhipKS9nw8duUl5RgYm6BJGnZ/PmHRB07VO/jtFoNGfqAZgNNp7uCXkNGMO2hZSCTodWoMbWypn9l/xhBEARBEARBEITOzqVnb7oH90fSajm+fk2N+8N2byc/Iw1zG1v6TZ5e535Uxib0mTAFgNNb1rfqGiVJojg/j9ToSC4e3s/prRvJz0ivsV1GfBwJ588ik8vpO6nutbalMbfcibmNLTnJiRxa9RuRRw4CtHm2qIOnF908uqNRqzmzfUu925YWFrL/958AGLZgCRa2do1+nuH/Z++9wyM767P/+5TpTV2rlXZX623e6nVZN9w7ccOmg6nBEEhCiElIHN6X/AJOgJeSvIGXGAKBgE0xYGywiSvGXrd13169q131rukzpz2/P545Z0arNuWcGWn1/VyXLl+WRpqz0sw5z7mf+3vf77oNAHDg+WcwcqJrxscxxvD49/8f9m1/CoIo4oa//js0LVsx4+P9kTq84/NfwpLVa4s+llMVEjQJwiHME9NI93EE6urxwa9/GxsuvhzMMPDQv/0fHH395Rm/d2KgH2o2A9ntmTGfZaGx/qLLcN0nPwNfOIJLb/so3F5frQ+JIAiCIAiCIAiiaM6/5d0AuHj58m9/jeTEOABAVbJ48dc/B8CdnGZJ60xsveZPIAgiTuzZiZHu4xUfl2Ho+N03v4xvffhd+I/b3497P38HHvq3r+IP/3U37rnzMxjtOTHp8a8/wt2Za869EOGm5oqfvxy8wSCu+OifAQBe/u2vkUnEEairx7KNmx1/bnPs/7mf/wRvvvrSjI977r57kI7H0Nix3PqeYmlduQprz3sLwBie/+X0Lk3GGJ760few+8lHIQgi/uQv/6asQt/FCgmaBOEQOx//H+w3d1n+6u8QamjCtZ/8DNZecDEMXcNvv/EvOL77jWm/18zPbF7euaCyZeZi46VX4lP/eS82XnplrQ+FIAiCIAiCIAiiJDo2bELnGWdB1zQ8c+8P8b1PfRgPfv0u/PFH/4nE+BhCjc3YfOV1c/6ccFMLVp97PoC8uFgJb768A4d2PAc1kwYABOobsHTtetS3LUU6HsMvv/R5jPfzLMd0PIb92/8IADWfmlt73luwukDAW3fhJRBF5+9/N195LTZfcQ0YM/Dw//0/1v23CTMM7Hjgl3jjsYcBAFd85BOQ5NI7tS981/sBQcDhl57H4NEjk5+DMTxz7w+tv/+1n/wrnH7hJWX+ixYnJGgShAP0HzmIp370PQDAJe/7MDo2bAIAiJKEP/mLz2LVOedDV1U88LUvYWKgf8r3Ww3nK1dV76AJgiAIgiAIgiCIWbnpbz6Pqz/+l2hbsw6GruPIyy9i15OPAADOf/t7ILtcRf2cs67jpUH7nnnKcnqWy8sP3Q8AOPv6t+HTP/k1/uzuH+O9X/oa3nvXN9C8vBPJiXHc96XPIzo0gN1/eAyakkVL5yq0r9tQ0fPawZV/+kmrW2HDxZdX5TkFQcCVf/opLN+8FWo2gwe++k+Ij44AADLJBB78xj/j2Z/9N8AYznzrjVi+6YyynqexYznW5zI7n7vvHgDczbt/+1P45Rf/Aa/8jv/drr79L8j0UwYkaBKEzcRGhvG7f/0KDF3DmnMvxNk33DLp65Is44bP/B2Wrl0PLZvF7qcem/IzhmZpOCcIgiAIgiAIgiBqg8vtwZYrr8X77voGPvT1/4ezr78ZvnAEbWtPL0mUal+/EUtWr4WmZPGHH3637OPpPbAP/YcOQJJlbLvp7ZMKfnzBEN7xv+5CQ/syJEZH8MsvfR6vP/oQAO7OnA+lMsH6Brz3S1/DOz5/F1pPq14hriTLuOmOO9HYsRyJ8TH85qv/hN4D+3DvnX+NN1/ZAUmWcfXH/wKXf+jjFT3PBe94LwRRxLHXX8HD//41fPfPPojff/sb6N63G4Ig4vIPfwJbrprb1UtMhQRNgrCRke7j+Nn//hvER4ZR37YU137yM9NeJGSXC2dffzMA3pLHDMP6GmPMajhvXeAN5wRBEARBEARBEKcqTctW4LIP3o5P/ee9eN+Xvl7SWLIgCLj69r+AIIo49OKzOPLyi2Udwys5d+aGS65AoK5+ytf9kTq883/dhbrWNkSHBpEYHYEvFJ5X482NHcuxYsvWqj+vxx/ALX/3j/BH6jB8/Bh+/o+fw8RgP8LNLXjPF7+GLVdeV7HoW79kKTZddhUA4MBzTyObTCLc3IIL3/l+fOzb38dZVJZbNiRoEoRN9B7Yh5//4+eQGBtFQ/syvON//TM8fv+Mjz/trHPhCQSQGB3Bib27rM/HR4aRScQhShIaZ2k3IwiCIAiCIAiCIBYuLZ2nYduNtwIAnvzBd5BNJUv6/rG+Xhx5ZQcA4Ozrb5nxccGGRrzzC/+McHMLAGDLVW+F7HaXedSnFpGWVrztc/8bsov/Pjq3no3bvvxvWLJqjW3PceE734+ODZuw9oKL8fbPfwkf+/fv44J3vBfhphbbnmMxUnqqKUEQU3jz1R146F+/Ck1V0Lb2dNzyd/8IXzA06/fIbjfWXXAxdj3xCPY98wes2LwVADDYxcfNGzuWF52/QhAEQRAEQRAEQSw8zn/He3H4pecx3t+HZ+75Ia7++F8U/b2vPvwbgDGcdva5aOxYNutjw00teM8X/w+OvvoSNl56VaWHfUrRtnod3vOlr2GsrwenX3AxBNFe71+woRHv/sev2PozCXJoEkTF7H7qMTz49X+Gpio47axteOf/umtOMdPEzFg5vON5KLlGuqFjfNycCoEIgiAIgiAIgiBObVxuD675+KcBALuefATd+3YX9X2p6AT2Pf0HAMC2G24t6ntCDU044+o/IXfmNLSuXIX1b7nUdjGTcA76SxFEmTDGsOM39+Gxu/8dzDCw8bKrcPPf/C+4PN6if0bbmtNRt6QNajaDIy+9AAAYOnYEANDSSYImQRAEQRAEQRDEqU7Hhk1WMcxj3/13qEp2zu95/dGHoakKlqxag/b1G50+RIKYd9DIOUGUATMMPPXf/4nXH/kdAODct70TF73ngyUHBguCgA2XXIHn77sXe5/5AzZcckVBIRAJmgRBEARBEARBEIuBS97/ERx99SVMDPTj51/4HPyROutroiiiZeVqrNh0BpasWQdm6HjjsYcBAOfc+PZ50VZOENWGBE2CAHdbHn3tZaTjMSzbsBmRltYZH6upKh75f9/EwRe2AwAu//DHcdZbbyr7uTdcfDmev+9enNizE4NHjyAxNgoIApo7V5b9MwmCIAiCIAiCIIiFg8cfwJUf+3M8+LUvYejYm1O+fvS1l/Hir38G2e1BXesSZOIxRFpasebcC2pwtARRexaUoPnyyy/jv//7v/HUU0+hq6sLjY2NOP/883HXXXdh7dq1kx5733334Zvf/CYOHDgASZKwadMmfO5zn8P1118/6XGGYeDrX/86/uM//gP9/f1Yu3Yt7rzzTrz3ve+t5j+NqCFKOoVHv/stHMoJlABvOlu28Qws37gZvnAk/2DG8PLv7seJPTshSjLe+ud/jdPfcmlFzx9pWYKO9ZvQs38Pnv7JDwAA9W3tcHt9Ff1cgiAIgiAIgiAIYuGw+pzz8K4v/AtiI8OTPq9mMug9uA8n9uxEKjqBke7jAICz/uRtECWpFodKEDVHYIyxWh9EsbzjHe/Ac889h3e+853YsmULBgYG8O1vfxuJRAIvvvgiNm3aBAD41re+hU9/+tO4/vrrccMNNyCTyeBHP/oRdu7ciV//+te49dZ8YO6dd96Jr3zlK7j99tuxbds2PPjgg3j44Yfxs5/9DO95z3uKPrZYLIZIJIJoNIpwOGz7v51whtGebvz2G/+Msb4eiJKElpWrMHTsTRi6Puv3ubw+3PzZz2PFlq22HMfupx7DY3f/u/X/6y68BDf81eds+dkEQRAEQRAEQRDEwocxhrHebhzfvRNqNoNzbrgFkrygfGoEMSfF6msLStB8/vnncc4558Bd0Mh1+PBhbN68Ge94xztwzz33AADWrl2Luro67Nixw8qSiMViaG9vxxVXXIEHH3wQANDb24uVK1fi4x//OL797W8D4CeISy+9FMeOHUNXVxekInc7SNBceBx8YTsevfvfoWbSCDY04sa//nssXbseSjqF3gP7cHzPTvQd2g9NUSZ9ny8YwiXv/whaT1tt27FkUync/fHboKn8uS55/0ew7aa32/bzCYIgCIIgCIIgCIIg5jvF6msLSsq/8MILp3xuzZo12LhxI/bv3299LhaLYe3atZOCccPhMILBIHy+/Bjvgw8+CFVV8alPfcr6nCAI+OQnP4n3ve99eOGFF3DRRRc59K8hqg1jDKM9J3Bizy4c3/Uajr72MgBg2cYtuOGv8qHLbp8fK888ByvPPKdqx+bx+7H63Atw4LmnAVDDOUEQBEEQBEEQBEEQxEwsKEFzOhhjGBwcxMaNG63PXXbZZfjVr36Fb33rW7jxxhuRyWTwrW99C9FoFH/1V39lPe71119HIBDA+vXrJ/3Mc8891/r6TIJmNptFNpu1/j8Wi9n5zyJsJDkxjmfu+S907XodqejEpK9tu/kduOjdH5gXuSMbLrkiL2iuPK3GR0MQBEEQBEEQBEEQBDE/WfCC5r333ove3l588YtftD737//+7xgZGcGnP/1pfPrTnwYANDU14cknn8QFF+QbwPr7+9Ha2jrJyQkAbW1tAIC+vr4Zn/fLX/4y/umf/snOfwrhEI/+x7/h2BuvAgBktwftp2/Aso1bcNqZ56B5xfxpEl+xZSs2XnYV/OEIfCGKLSAIgiAIgiAIgiAIgpiOBS1oHjhwAH/+53+OCy64AB/60Iesz/v9fqxbtw4dHR244YYbEI/H8a//+q+49dZbsX37dqxezbMP0+k0PB7PlJ/r9Xqtr8/EnXfeiTvuuMP6/1gshmXLltn1TyNsovfgfhx741UIoohbPvcFLNt0BmSXq9aHNS2iKOG6T36m1odBEARBEARBEARBEAQxr1mwgubAwACuv/56RCIR/OpXv5pU3vPOd74Tsizjd7/7nfW5m2++GWvWrMHnP/95/OIXvwAA+Hy+SWPjJplMxvr6THg8nmnFUGJ+8fx9PwEAbLrsqqpmYhIEQRAEQRAEQRAEQRDOINb6AMohGo3irW99KyYmJvDII49g6dKl1teOHj2KRx55BDfddNOk72loaMBFF12E5557zvpcW1sbBgYGcHLRe39/PwBM+rnEwuPEnp04sWcXJFnG+W9/T60PhyAIgiAIgiAIgiAIgrCBBSdoZjIZ3HjjjTh06BAeeughbNiwYdLXBwcHAQC6rk/5XlVVoWma9f9bt25FKpWa1JAOADt27LC+TixMGGN47hf3AAA2X3kdwk0tNT4igiAIgiAIgiAIgiAIwg4WlKCp6zre/e5344UXXsAvf/nLSQU/JqtXr4YoivjFL34xyXnZ09OD7du348wzz7Q+d/PNN8PlcuE73/mO9TnGGO6++260t7fjwgsvdPYfRDhG1xuvou/QfsguN8675V21PhyCIAiCIAiCIAiCIAjCJhZUhuZnP/tZ/Pa3v8WNN96IsbEx3HPPPZO+ftttt6G5uRkf/ehH8f3vfx9XXnklbr31VsTjcXznO99BOp3GnXfeaT2+o6MDn/nMZ/C1r30Nqqpi27ZteOCBB7B9+3bce++9k3I5iYUDYwzP/oJnZ2697gYE6xtqfEQEQRAEQRAEQRAEQRCEXQjs5ADJecxll12Gp59+esavm/8UTdNw99134wc/+AGOHDkCANi2bRv+9//+37j88ssnfY9hGPjqV7+K7373u+jv78eaNWtw55134v3vf39JxxaLxRCJRBCNRhEOh0v8lxF2cvil5/Hbb/wLXF4fPvat78MfjtT6kAiCIAiCIAiCIAiCIIg5KFZfW1CC5nyGBM3pGe3pRt+h/Wg/fSMalrY7/nzMMPDjz/0lRrqP4/xb3423vPsDjj8nQRAEQRAEQRAEQRAEUTnF6msLauScqB0jJ7qQSSSmfN7l8yHS3ApvMGh9TsmkcfCF7djzh8fRdyhfuNR++kZsvuIarD3/LXB5vLYfI2MMT/7X3RjpPg5PIICzb7jF9ucgCIIgCIIgCIIgCIIgagsJmkRRPPPTH+HY66/M+HWPP4BwSyuCdfXoObAPaiYNABBEES2dp2Ho2FH0HtiL3gN78YcffhfrL74c5970doSb7WkfZ4zh6Z98Hzsf/z0gCLjqTz8FbyA49zcSBEEQBEEQBEEQBEEQCwoSNImiCDU0oX5px5TPZ5MJpKITyKaSGO46iuHc5+uWtGHT5ddg46VXIljfgPjoCPY+/ST2/PFxRAcHsPOxh7H7yUex5arrcN4t76qouIcxhmd//mO8+vCDAIBrPvGXOP0tl5b98wiCIAiCIAiCIAiCIIj5C2Vo2sRiztBUMxlEhwcRHRpEfHQETR3L0b5+IwRBmPJYZhg4sXcXXnrgPpzYswsAILs92Hrt9dh209vLKvB54dc/w/P33QsAuOKjf4Yzr72hsn8QQRAEQRAEQRAEQRAEUXWoFKjKLGZBs1xO7NmJZ3/+Y/QfPggA8AaCuOxDt2PDJVdMK4ZOx0sP/grbf/ojAMClH/hTnEO5mQRBEARBEARBEARBEAsSEjSrDAma5cEYw7E3XsGzP/1vDJ/oAgCs2HImrr79LxBpaZ31+5792X/jpQd/BQB4y7s/gPNvfXc1DpkgCIIgCIIgCIIgCIJwABI0qwwJmpWhaxpeeeg3eOFXP4WuqnB5vLjovR/E1muvhyhKUx77+Pe+jb1PPwEAuOg9H8R5t7yrFodNEARBEARBEARBEARB2AQJmlWGBE17GOvrwWPf/RZ6D+wFAISbW7Dx0quw6fKrEG5qgZrN4KF/+yqOvvYyBEHE1Z/4C2y+/JoaHzVBEARBEARBEARBEARRKSRoVhkSNO2DGQZ2PfkInv3Zj5FJJvgnBQGdW85EJpnAwJFDkF1uXP+Zv8Pqc86r7cESBEEQBEEQBEEQBEEQtkCCZpUhQdN+VCWLIzuex+6nHkf33l3W572BIN72uS+g/fQNNTw6giAIgiAIgiAIgiAIwk5I0KwyJGg6y8RAP/b88XGMdB/HRe/5IJqWraj1IREEQRAEQRAEQRAEQRA2Uqy+JlfxmAiibOqWtOGi93yw1odBEARBEARBEARBEARB1Bix1gdAEARBEARBEARBEARBEARRLOTQtAlzcj8Wi9X4SAiCIAiCIAiCIAiCIAhi4WHqanMlZJKgaRPxeBwAsGzZshofCUEQBEEQBEEQBEEQBEEsXOLxOCKRyIxfp1IgmzAMA319fQiFQhAEodaHUzNisRiWLVuG7u5uKkciiHkOvV8JYmFA71WCWDjQ+5UgFg70fiWI+QljDPF4HEuXLoUozpyUSQ5NmxBFER0dHbU+jHlDOBymiwJBLBDo/UoQCwN6rxLEwoHerwSxcKD3K0HMP2ZzZppQKRBBEARBEARBEARBEARBEAsGEjQJgiAIgiAIgiAIgiAIglgwkKBJ2IrH48E//uM/wuPx1PpQCIKYA3q/EsTCgN6rBLFwoPcrQSwc6P1KEAsbKgUiCIIgCIIgCIIgCIIgCGLBQA5NgiAIgiAIgiAIgiAIgiAWDCRoEgRBEARBEARBEARBEASxYCBBkyAIgiAIgiAIgiAIgiCIBQMJmgRBEARBEARBEARBEARBLBhI0CQIgiAIgiAIgiAIgiAIYsFAgiZBEARBEARBEARBEARBEAsGEjQJgiAIgiAIgiAIgiAIglgwkKBJEARBEARBEARBEARBEMSCgQRNgiAIgiAIgiAIgiAIgiAWDCRoEgRBEARBEARBEARBEASxYCBBkyAIgiAIgiAIgiAIgiCIBQMJmgRBEARBEARBEARBEARBLBjkWh/AqYJhGOjr60MoFIIgCLU+HIIgCIIgCIIgCIIgCIJYUDDGEI/HsXTpUojiLD5MtsCIx+PsC1/4Arv22mtZfX09A8B++MMfTvvYffv2sWuvvZYFAgFWX1/PbrvtNjY0NDTlcbqus69+9auss7OTeTwetnnzZvbTn/60pOPq7u5mAOiDPuiDPuiDPuiDPuiDPuiDPuiDPuiDPuiDPuijgo/u7u5ZdbgF59AcGRnBF7/4RSxfvhxnnHEG/vjHP077uJ6eHlxyySWIRCL4l3/5FyQSCXz961/H7t278dJLL8HtdluP/fznP4+vfOUruP3227Ft2zY8+OCDeN/73gdBEPCe97ynqOMKhUIAgO7uboTD4Yr/nQRBEARBEARBEARBEASxmIjFYli2bJmls83EghM029ra0N/fjyVLluCVV17Btm3bpn3cv/zLvyCZTOLVV1/F8uXLAQDnnnsurr76avzoRz/Cxz/+cQBAb28vvvGNb+DP//zP8e1vfxsA8LGPfQyXXnop/vZv/xbvfOc7IUnSnMdljpmHw2ESNAmCIAiCIAiCIAiCIAiiTOaKc1xwpUAejwdLliyZ83G//vWvccMNN1hiJgBcddVVWLt2Le677z7rcw8++CBUVcWnPvUp63OCIOCTn/wkenp68MILL9j7DyAIgiAIgiCIBYQeV8BUvdaHQZxiMMagjabBVKPWhzIJphn8uBir9aEQBEEQs7DgHJrF0Nvbi6GhIZxzzjlTvnbuuefi97//vfX/r7/+OgKBANavXz/lcebXL7rooik/J5vNIpvNWv8fi8XsOnyCIAiCIAiCmBeoA0kMfvsNeFfXoenDG2t9OMQCh+kM2a4oMntHkd47Cj2ahW9zExrfv37ub3YQI6shc2Ac6b0jyBwcB8vqqLt1NYLnttX0uAiCIIiZOSUFzf7+fgB8PP1k2traMDY2hmw2C4/Hg/7+frS2tk6xsprf29fXN+1zfPnLX8Y//dM/2XzkxKmANppG7KlueNfUwX9GS60PhyAIgigDxhi0wRTSe0agDqbgXhGGb0Mj5AZvrQ9tWphqIPrIMbiWBhE4u7XWh0OcQiRe6AM0A5nD42CqAcG14Aa8iHkAYwyxJ04g+UIfjJQ26WvpPSPQxjI1Ob8aGQ3j9x9Geu8ooE92ZCZf7CdBkyAIYh5zSgqa6XQaAB9PPxmv12s9xuPxWP+d7XHTceedd+KOO+6w/t8MLSUWL0w3EN/ei9gTJwDNQPbNCRI0iVMOZjCogymwzOSbEcEtwdUWgCDOnnNCEPMdpSeO1M5hpPeNQh/NWJ9P7x5B9KGjcC0NwLexCb4zmuFq8tXwSPMwxjD+wBGkXh2E4JXgP6tlzswhp9DGMtCj2UmfE2QRrqVBCBKdHxYaRlZH6o1h/j86g9KfgGc5ZcUTpZPeNYL4kycAAKJfhnd9I3wbG5F4thfZo1EkXxlA5JrOqh9X7KlupHeNAADkJh+8GxvhXVWHkR/thdqXhDqUgqvFX/XjIgiC0HUdqqrW+jAcweVyFdVVMxenpKDp8/EbjMKRcJNMJjPpMT6fr6jHnYzH45lWCCUWJ9kTMUzcfwTqQNL6nB7NgumMbuCIBQ/TDWSPRpHeO4rMvlHoMWXax9W9bRWC5y+t8tERhH2k941i9Cf7ANOkIwvwrqmHuyOEzJEJKF1RfoPbl0TsDyfQ9rltkCK1Xwskdwwg9eogAIBldBhJFVLQXdVjMLI6Yo91IfF8X/73V0Dw0g7UvXVlVY+JqJz0rmGwbD47U+2Ok6BJlIyRUjHxuzcBAKHLOhC+utNaHzPNyAmagwhfuaKq62Y9lkXiOT6N1/De0+Hb0mRtBnnX1iNzYAypN4ZqIrQSBLF4YYxhYGAAExMTtT4UR6mrq8OSJUsq2oQ/JQVNc1zcHD0vpL+/Hw0NDZYY2dbWhqeeegqMsUm/SPN7ly6lm3NiZhhjiD12HPE/dgOM7zhH/uQ0jD9wGNAY9Gh23o4nEsRcmONhief7wNJ5R6bgliBF8mIJy+rQYwpSO0dI0CTKRhtNI/pIF6R6D3wbm+BeFqqq45fpDNH/OQYwwLOmDoFzl8C7tgGih+8eh69cDj2hIHNgDLHHj0OPKsh2RWvuxM8ej1lCgYk2lqmqoJneP4qJB960nJlyoxfI/e2YakCfyCKzfxQgQXPBkXxpAAAghlww4iqUnkRVnjf+XC/0iSwib11Jzv9TgOj/dMFIqJBbfAhfNVm09G1ohBiQYcQUZA6OwbehsWrHFXuST1W5V4QniZkA4N/azAXNncMIX72iZq53giAWH6aY2dLSAr/ff8qdfxhjSKVSGBoaAjB9VGSxnJKCZnt7O5qbm/HKK69M+dpLL72ErVu3Wv+/detWfP/738f+/fuxYcMG6/M7duywvk4QM5HcMYD4U90AAP9ZLYhcfxqkgAvxP3ZDG0lDG69NHhCx8GA6v+mXG+fHCCvAR2yt8bCAC74NjXwUa3UdBDmfoaaNpjHwtVegHI/CyGgQvafkpYVwEHUoheHv74aRc/8mnumFGOKvOd/mJnhW1Tm+mEu9PghtOA3RL6Px/eunfR1LQTcC5yyB0ptA8oV+KN2JmgqaelzB6L37AZ3Bt7kJelyB0hXjo/JVcNHpcQUTv30T6d18XFNq8KL+bavhXVuff0xSRf+XXoQ2lIaeUKruHJ3PMNWANpaG3OSDIM2/XEp1IAmlOw6IAiLXrsT4rw7x/3f6eYdTiD50FGCAe1kI/i3Njj/nYkAby0Bwi1V/D2aPTiD5MhfG629dM2n9APBICv9ZrUhs70Xy5YGqCZraaBrJl7mzPXJt55RrjHd9IwSXCH00A7UnAfeyUFWOiyCIxY2u65aY2dhYvQ2eamNOQg8NDaGlpaXs8fP5t3qyibe//e146KGH0N3dbX3uySefxKFDh/DOd77T+tzNN98Ml8uF73znO9bnGGO4++670d7ejgsvvLCqx00sHApdMeHrOtHwrnWQAi4AgFTPHcD6WGbG7ycIE6YZGP7ebgx87RVEH+0CY9PMa1YZI6Vi4re58bBLO9D2+fNQ//Y18J3eMOVmRG70QW72AQaQOTxRg6MlFjJKbwLD390JI6ZAbvHDt7UZgkeCEVeR3DGAke/vQXrnsKPHwDSD5x8DCF22bE5R3t3Bb2yrIe7MBNMNjN673/q91b9jjbUhoo1On/9t9/MP/+cuLmaKfKS89TNnTRIzAUAKuOBawvPnssdijh/XQiF9YAwD33gFg//6Gvru2oGx+w4ivXcEhqLP/c1VwnRn+jY0wLu+AQCgjaRhpJzN80o822vFFsSf6ZkX18SFCGMMSncc0Ue6MPCNVzDwf17G0L+/DqYZ1TsG1cD4b44AAALnLYGnMzLt4wLnLgEAZA6MQYtOjQJzgujjxwGDwbO2Hp7Tph6X6JHgzYmrqTeGqnJMBEEQZmam33/qZ/ea/8ZKckIXpI3m29/+NiYmJqwG8t/97nfo6ekBAPzlX/4lIpEI/uEf/gG//OUvcfnll+Ov/uqvkEgk8LWvfQ2bN2/GRz7yEetndXR04DOf+Qy+9rWvQVVVbNu2DQ888AC2b9+Oe++915agUuLUQ48pGL0n74oJXdox6etyvRdZANo4CZrE3Ez89k0ox/mNfvypbrCsjsgNp9V0zC76SG48rNnHR63mOBbvugYkhnuROTgG/+amKh1lHqU7zsVgdfKNmtzgRf3bpzpCiPlB9ngMIz/cA5bR4eoIoukjmyAFXFamWuypbijHosgei8K/1TknZOLFfugTWUhhN4IXzD32Yjp11L4EmG5U3V3HGOPnja4YBI+Exg+sh+iRITfxiQBt1PlrT/LVQWhDaYgBGU0f3Qx3e3DGx7pXRqAOpKAci9bk/DCf0OMKJh46mhfpBYClNaReG0LqtSEILhH+M1tQd8vqmo6YMVVH8jUu4gTObYMUcEFq8EIfy0DpTcC7pn6On1AeekJB8tWceCQAak8CSlcMnpXTC2HE9KR2DSP68FHo0cmZ13pMgTqUgnvpzO9XO4n9sZs730MuRK6bOXLC1eyHe2UYyrEYUq8MInzlckePS+lPWu/ByLWdMz7Ov7UZ6Z3DSO0aRuT62q7LCOJUJ769B+k9o1M+7z+zeVFGWp1qY+bTYce/cUEKml//+tdx/Phx6//vv/9+3H///QCA2267DZFIBMuWLcPTTz+NO+64A3//938Pt9uN66+/Ht/4xjemlPl85StfQX19Pb773e/iRz/6EdasWYN77rkH73vf+6r67yIWBkzLuWLipitm7ZQ3o5QbM9fHq7PLTCxcki8NcBeMAAS2LUHypQEknu+Doeh8NKsGi+fssajlzKm/pTgx0LuuHolne5E5OD4lk9hpmMEwfv9hqP3JKV9TjsfgP7NlimuMqD2Zw+MY/fE+MNWAuzOMpg9vtJyRgizCu7YeRlrF2LHotH9buzCymhUdErpyOQTX3BuZcpMPgkcCy+pQB6snDgD89T7xwBHrPdrw7nVwNfMdbrkh59B0eDqAqTripqP18uWzipkA4FkZQfKFfmSPRR09rvkMYwyplwcx8ftjYBkNEIDgW9oRvmo51P4k0ntHkd47An08i+RLAwhd2lHTCJLU7hGwjAap3gPP6joAXMhPj2WgdMcdEzQTL/QDmgFXRxDupUEkXxpAfHvvvBU0mc54C3arf96IXdpoGmP3HQI0A4JbhHddA28Tf74Pyok41L5kVc5Z6mCSZ8wDqLtpFUTf7LedgXPboByLIfnyAEKXL3P09xl7tAtggG9L06znL++aeoh+GUZcRfboBLyraS1BEE6QPRpF9OFj035N7UsgcG7bvDnHEvOLBSlodnV1FfW4jRs34tFHH53zcaIo4s4778Sdd95Z4ZERi4GJh49COV7oipl68yvnRs7JoUnMhtIdx/iDfBQrfPUKhK9YDveKMMZ/dQipVwbBFB0N71pXVXch0wyM338YAB8Bm24Mazo8KyMQ3CKMuAK1vzo3Sybp3cNQ+5MQPBLq37HGElPjz/RAORGHNpYGQDch8wlD0TF6734w1YBnTR0aP7ABonvqudTVxl9H6kASzGCOLGYTz/bBSKqQG70InNNa1PcIogD3shCyRyagdMer9npnuoGxXx5C+o1hQOB5dIV5c3Kj6dB0duQ88UI/9JgCKeJB8Ly5Ha2mGKUOJGGkVIh+l6PHNx9J7x6xzq2u9iDqb1ltRRd4VkbgWRlB5PqVGPzGqzyDu8aZyqZgHjhnifW+c3eEkN457FjUAlN1JF/k01ehSzrgWhJA8qUBZPaPQh1OWcL9fEHpTfDNtN4Egm9ZirobV9X6kMAY4yPemgHPqgiaPrwJgouvIZTuOBc0+xMAijvXVXIcEw++CegM3vUN8G2a25nt39SIiQdl6BNZZA+Pw7uuwZFjy3ZFkTkwBoh87TUbgizCt7kJyR0DSL0xTIImQTgA0wyM/4ZfH31bmiblJo/ddxBMMaANp+BqDdTqEIl5zIIUNAmiVqR2DiH5Qj+Aya6Yk5HqTYcmCZqnCtpoGtHfH4Nva4stI5N6QsHoPfv4Yn9DI0KXLQMABM5uheCWMPbzA0jvGsGoaqDxtg2TGkGdJG6OhwVdiFzXWfT3CbIIz6o6ZPaPIXNwrKoCT+wx7tgPXdIB/+b8Iih7LJoTNMkpPd/QxzNgGR2CR0LThzbOKNrLTT4ILpEvZkfTtgsaelJF/BkeWRO+ZkVJo+OFgiaKEPUqhakGRn92AJl9o4AooOE966aUpZgldEZChZHVp91wqxQjo1muq/BVyy2xZDakkBtykw/aSBrZ4zH41p+6IfczkbLGt5eg7ubV057TBUGAVOeBNpK2GuNrgTqUgtIVA0RMEvndy/h5XemOO+LET742BCOpQarzwLexCYIkwLu+AZn9Y0g824v6W9bY+nzlYig6Yo8fn5T1mXihH8ELl9a82C/1+hCyRyYAWeQTFgXvT2uDyEHHu0n28ASyR6OAJKDuplVFvVYEl4TAWS1IPN+H5EsDjgiajDFEH+kCwMX6Yq4p/jNakNwxgPSeEbCbVxd1zisVI6Nh7L5D0OOTIwIESYBnZQS+jY1wtQcXxQgq4TzZEzEknulB3Y2rIEU8c3+Dw8SeykdT1N+yZpKb27W9F8rxGJTeBAmaxLRQqBhBlEB8ey8AXhoxWwujbAqaMaWq4euEM6iDSQzdvQvpvaOIPXF87m+YA17mcQB6VIHc7EPDu9ZOcp75Nzeh6YMbAFlEZv8Yoo92VfycxaAOpRB7qmA8rEQXlXnzkTkwbvuxzUTylUFooxmIQReCF7VP+poV/TDmfEEKURp6rs1cqvPM6kAWRAHyEr6AdeImPP50D1hWh6stAN/m0pqUTXed2uN8MZCh6Bj5771czJQFNH5ww7TNz6LfBdHPbwScGjuPb++FkdIgN/vgP6t4l5fp0lyMxUBGVkPmCD8vBi9cOusGlXlzWUtB03Rnetc1TLrZdS0NAiIXzE/OZqwUZjAkcmus4EXt1u8odDHPKE++OgQ9Ye9zlkPm0DgGv/kqP1YG+M5o5pMMBkPs8crXB5WgJ1XeDg++2SA3TRZXXUv5uVTpSzpatMQYs9YtwfPbrDVxMZjlQOn9Y1PEPTtIvT7ExXpZRKjInE53ZxhSxA2W0ZE5OGb7MQFAckc/MvtGoXbHJ30oXTHEn+rG0LffwMBXXubZyVW45hCnNrEnTiC9ZxSJF/pqfShQh1L5aIobp0ZTmJEQam+i6sdGLAxI0CSIItETinUyDV44uxtHDLr4Di4D9Alyhy1keAPzLhi5hbU2lKq4hTbxYj+UY1EIbomP2k7TqOxd14CGd63lj3+mB6ldzrY8A7wICDqD9/QG+MpwoXrX8VEs5UTM8RZcgI8nxp40c/yWTXGjmW41p/MEidIxxRAp7J7zse42+wVNI6tj4qGjSGzPuTOv7Sx5nN0qBhpMwcg620wdf/IEskcmILhFNH1kE3ynz+xcsoR8B8bO9YRiiU7c0Vr878y9MgwAizJHM3NwHNAY5EYv5NbZHWFShL8narV24KU8gwDy4pKJ6JYsh4zdY+eZ/WPQRtIQvDIC2wpcoSvDcHUEAc1A8sV+W5+zVJS+BEZ+uIcXiNV50PjhjWh87+mI/Akvu0ntHIY64Lz7cSaiDx+FkdLgWuJH6OL2KV93tfgBUQDLaI4K5uk9I1B7ExDcEkKXLyvpe11LAnAvDwEGQ2qnveueKYJvkc40QRTgO4OX0tl9TAAXgJMv8/dc6NIONH5og/VR/8618G1qhOASoUezSDzfh6H/2EmiJlE2zGBQTvCNRaWntiKhmYE/272HKydoKiRoEjNAgiZBFEnm0DjA+A63FJ59ESQIAiTK0ZyCOpDE8A92W06V+U62K4rh7+3iNwgdQYgBF8AqE1YYY0ju4Ddlkes6+Q3GDPi3NCN4CXenjP/qkKM3SkZWs5wHkes6yxprkutzN+sMyByesPkIp5J4oR9GTIFUN32OHwma8xc9xm+m5zqXAoDLFDT77FnMpg+MYfBfX7XGRQPnLrHE+FKQwm4uPjHnnQOmCFh34yp4V9XN+lhz5NWJpvP4U91gig5Xe7CoTLxCzDxetTfuuAA830jv5a2t3o1Nc55b8w7N2rgRow8fA0tzUWy6kV9TyLdbUInnNheC5y+B6Mlv8gmCYLk0Ey/0gam1e+0kd/QDDPCsqUPrX59tbSy4O0L8RpyhahMVJ5M5PM5jDQSg7tY108ZnCLJorTnUPmfWE0xnVgxM8OJ2SMG5N61Oxpv7vdr9GptL8J0N/1buiE/vH4WR0Ww9ruzRKBfz3RJCVyyHb32j9RE4uxWNt23A0i+cj8YPbuBir86QqLG4TyxctOEUWIafR5XuOJjhnFt7LpIvD0DpikFwi6h72/TRFJZDsy9Z02OtNYwxGIpek49SHP2dnZ34t3/7t0mf27p1K/6//+//s/cXUgBlaBJEkWQOchGu2Ewfud4LbShNgmYBE78/huzhCSgn4mj5i63zJuBfT6p8BKnghG3u5Bc2MI/97AAyB8eh9iXgWREu67mU4zFoQ2kILhH+s1rmfHzk2k6ofQlkj0xg9Cf70PIXZ87ZFFoOmYPjgF6cg2g2vOvqkRhMIXNwDP4zShvhLYXJOX4rph1bNrNsWUZftEUk8xVr5Dwy982ua6k9uW96QsHEb99EetcIf+56D+rftrqinDZ3Rwjp6CiUnnjRBVqlwgxmbWa4l4fmfHxeyLfXoalNZKyb6HI2PeQ6L6Q6D/SJLJQTMcdasucbTDN4AQkA38a5s0OlupygWQOHZubwOFKvF4hi07iW3ctCSL40ANVGh2b2RIxfgyUBwQuXTvm6b1OT9dpJvjZUVBGV3RhZHak3uDsvdNnUiYDw1SuQ3jOCzP4xZI/Hyl4jlHVsis6LgAAEL1gKz/KZn9u1NAB1IAm1LzFrdFK5pF4b5Fl4frlk0dDErnN+IcUIvrMeU1sAUqMX+mgGyvGYrfmeyZd5xIN/a/OMuceCS4JvQyNEn4zh7+5CeucwjBtOm3bChyBmI3s8H/vCsjq0kfSs5gqn0GMKov/DW83D13RCrps+mkJu9uey1HVHstQXCkw10PeF52vy3Eu/eCGEaYo75wvk0CSIImAG4w5NoGgnT74YiEbOAe7OzOZ+hyyrY/Qn+2Fk7d3lLhXGGJKvDGDg669g9Cf7MHrPfutj4jdHeAPz2no0fXQTRK+cH3uoYETDzCbzndFc1EJUkAQ0vPd0XhQxmsHYLw46skNZioNoNqwczUPjju6kxp/p4Tl+Lb4ZhWHRLUEMcRGTXJrzC3PcsSiH5hK+eNVjSkUZeuO/OszFTAEIXtKO1r8+u+KbUpfpVnOo9Rngr12mGIAsQm6aeyHvlEMz8UI/oDN4TovAs7qurJ9h5WgeXTxj59k3J8CyOsSQ23I3zoY5Bmu6mKtFsaJY3qGZsO0cn9xhCjot054TBEmwMpIT23tr4tJJ7xoGy+qQG73Tbl64Wvzwn81H5aOPdDmaUXkyyR0D0McykCJuhK+dvbXb5UCEhwlTDcSeyMXAXLasbLHNjBnRhlO2OHJLEXxnQhCEfPzJUKriYzLRkyrSu/km28kRD9Ph7gxDbvaBqYYj4+/EqY9yfPJ6xcn1y2zEnjoBltHh6ghOu5FlIkhC/rxFY+fENNC2DkEUgdIdB0trEHwy3MuKWwiZIegkpHDMQiXP6jqoQyloQymM/+owGt53ek1aG9XhFCZ+c8S6sZYavJBCk91i7uUhRK7ttNx/7vZcZl6ZF1QjrZW0cDWRAi403rYeQ3fvRObAGOLP9CB8WWm5VLNRqoNoNjwrwhA8EoyECrUvYRWn2IkeV/i4MIDINbNnH8oNPihxFdpYxpFjIcrDcmgWkaEpemTIjV5ooxmo/UlIa0ofYWSqYUVdNN++GZ7T6kr+GdPhroKgaY7au5b4i8qslBtz1x6bMzS1QX4T7zujuexztue0CG9hXkQ5muZmkW9DQ1E5raZD00hpMBQdYpVcEfEnTxQlisktfgjunFtmOGVL66z5epjN1R/Y1orYE8ehjaSROTDmiLtwNszNSP+2JTO+/sNXLeelM8eiyB6egHdtdVzImf38NRa8pGPSuP50mE3nigOCZmJHP/RoFlLYjeAF5btoxbAbol+GkdKgDqYqvnbH/5B7bYfdCF8zu+A7G3JrANgzCnXQPkEz9foQoDO4lgasTfPZEAQBgXOXIPrwMSRfGqiJW5lY2Jj5mXKzD9pwGkpPHIGziy/4swPGGDL7+H1H+KoVc14bXe1BKCfiUHoT8G+de7rNadThFCZ+dxShSzvmjAGyC8ElYukXL6zKc0333PMZEjQJoghMsce7pq7oEgSpIeeyoJFz6DEFqTeGAPAiCTBg+Hu7kN49gsQzPQhdap84NxfMYIg/1Y3YUycAjUFwiQhfvQLBt7TP+bc1F5vqUBJMNUo+wafeGAJTDcit/qKcOoW4O0Kou3EVJn5zBInn+xC6tMM2IThTooNoNgRZhGd1HTJ7R5E5OO6IiDjx0FEwxYCrIwjvHAKs3ODlY/60sTCvsDI0iyxlcC0NWoJmOaPKSncc0BjEkAvulfaNhrvbg4DAx4P1uDJlU8QOTCeVu23um10gL2jqE1kwzZi1Rb4U9An+HpLrivubTYf5u1e640WdQ5WeOOQGb0lxEUw3oByPQU+cVEwmCHAvC1V0/KXCDIb0vpygubG4zFHRK0PwSGBZHXo0C7EK43VKX8LKsKy7efWsopggCvzm8lgMSne8YkFTjyvQxzKAMHukguiRETyvDfGnexB/pqeqgqY6kOTnEFGY9cZfrvMieH4bEs/1IfpoFzxr6hzfsDUyGrJdXKCYrSzMxHQ66WMZGBnNtpFlI6sh/lTOnXnVcgiu8oV4QRDgWhpE9sgE1P5kResIpT+J+DMFr+0K/r3mWK5mk0OTMWYJ5YFzZxbKT8Z/Viuij3RB7U1A6U1YGYPVgDEGbTgNphpwLQ3UxJCwkGCMQTkeg2tJYF7EA+hJFdow3+wMXrgUEw++WROHpjaY4pM6sgjvqrnXZO72IJKYPw7NiQeOIPtmFIIoVE/QFIR5PfZtIorilAkFVXW2KLb27yyCWADkx82LH0+0HJo0co7E832AzuBeEbZGfepuXIWJB44g+kgXXEuDVctTS706iNjjPLDes7Ye9W9bbWXOzYUUcUMMuGAkVagDyZLEP14GVPrCtZDAWa2IPnQURkzhi/yl9ixiMyU6iObCt64hJ2iOIXzl8op/XiHpg2NI7xwGBKD+bavnLtjIlXPpJGjOG5huwMiJTcU4NAHefJvePVL2mKTpAPOsjNh6AyZ6ZcjNfmhDKSg9cfjW2y+ymP9m19LihCMx5OZ5U6oBbSILV5PPluMwr2VmnEo5yI1eiCEXjLgKpTs2q1M22xXF8N274F4eQvMnz5j172YoOrKHxpHeO4r0gTGw9MxxJq6OIHwbG+Hb2OR4bphyIgYjoULwSiVlrEoRD7ShFPSJrON5YVbLrAH4NjUWJRS6l4UsQTNwTvHTBtOh5PLcXK1z3/AHL1yK+LO9ULr4c1e6AVcsVlTMhoY5Ny1Cly9D8uVBqL0JZN+MwltmPEOxZI9MAAaD3OSz4iZmQwq4IEXc0KMK1IEkPJ32bPAkXxyAkdQgN/kQOLuy1wTAhdfskQkofQlUIpnHHu3ir+2NjRVPoLhy+eLqYAqMsYqvJTxTPcUz1UtwnUkBF3ybmpDeOYzkS/1w37KmouOYC2YwKD1xZPaOIr13FNoIF8S86+pR97bV1v0OMZX4H7oRe/w4PKvr0PSnm2ouABe6M/k97ZtQ+5O2bn4Wg9VLsSpS1OaHmaur9PKoEzvuVcolc3gc2Tf5mtLJstaFSnNzM/r786VlsVgMx44dc/Q557d/lCAKSO8ZwfD3dkGLVlcg1GOKtSNUShOuedNnxJWatnLWGiOrI5Fr9Q5dkg+ID5y3BP5zWgEGjP3sQEXZeKVgChuBC9rQ9JGNRYuZQM41YOZo9pa2o6n2JPiFTxYROLO8cQnBJVrZdeZioFLKcRDNhfk+Ubrj0JP27coZio4JMwfrLe1FuTbkhlyeIDml5w16XAUYAEmAGCjOeWeKeUqZTefZrrygaTdOj51bI+dtxd3WC4IAKXde020aOzfSGliumVyqwOEoCEI+R/NYbNbHmucl5UQcyiwj6rE/dqP/Sy9i9J79SL0+BJbWIAZccK8Mw70yYn24cm5atSeB2KPHMfjNV9H/5Zcw8I1XJn2M/uwAmG5P/qE1bn56Q0k3i1YxUBXWO8kd/VB7EhA8EupuWlXU95jn3krypE2yuRts94q5z+dSxGONpZuOUqdhqo7ka3zCJHDu3OO9UtAN73pnWrqnI21OEJWwPjXHzu1qOudOQ3Od11H0JNNs2JH1aWQ0ZA7ztVL42s6Kj0lu8gEiz4E3Y1MqwRLKtxSXqV5IYBsXjVNvDMNQnLvHyB6PYeCrL2H4OzsRf7qHi5mSAEgCMgfHMfjNVxHf3mPbOfNUIn1gDLEnuIEie2QC2cMTtT0g5PMz3SvCkOo9EAMyoDNHMnVnI3PQPG8VZxRytfoBWeDvvRoaFBhjiD7aZf2/PpGFkaltH8R844orrsBPfvITbN++Hbt378aHPvQhSJKzzlJyaBILAiOtYezXh8HSGpI7+hG5prNqz505xE+6ro4gpGDx44SiX4bglnjOVBVcFvOV1CsDYGkNcqMX3gL3kiAIqL95Nd+hHk4je2SiKrkoZpi757TyRsHc7UFkD41D7S3t4m/lb21uqqht27uuHpn9Y9z9eHnlo/rlOohmQ4p4rGwetS8BySb3bezx49AnspDqPAhfXVwOVr7xmQTNQtShFARZLEnQtwtr3DzkLnqX3dydN0fdSol7MEeQAacEzSBSrw7aIu6cjJ5UrRtn15LifUpyow/aYMq2YiBzQ0AMuCrOdPSsjCC9a2TOHM3Cm7/4M73TujnVgSR3YDEuAprOS3dneNrXlh5XkN7HXUbZNyemFQy14TRSq+sswaBcGGOTytZKQY54kEV1ms5Tu3ixSPjK5UWVdAF5EV/tT4KpekXjxdYNdpFFLcGLO5B6bQjp3SPQxjKOn8NSu0fAMhqkOk/RZViutgDSO4cdFwkYY2VNELmWBpA5MFb2BtHJZI9GoY1mIHgk+GbJQS0Fd0HTebmOrMyBMUBnkJt9trixBVnk59bhNLTBlFXgVQ7lZqqbeE6LWK3r6Z3DFZ+vpoMZDOO/PgQ9qkDwSPCuq4dvYxO86+qhxxSM/+YwlGMxRB8+htQbw6h/+xrbJocWOtpIGmM/PwgwPjVhxJWqxVDMhtlw7lkR5kVXHSFkDo5X1fFeGJNR7EaMIIlwtQWhdvMcTdmmyZNSyewd5RuAbhGCLFo5v54VpReNnarceeedOHbsGG644QZEIhF86UtfctyhSYImsSCIP9NjjZCZNu9qYdniS2zDFQQBUr2H54SMZRaloMkMhvhzfQCA4MXtUxakgkuEuyPEF4dVuHFjBrOyj8zRoVJxl+HQNLIaUjtzDo8KF53etXxERDkRg5FSKxJHASC9pzwH0VzIDV5ow2noNkUuKD1xqwio7m2rIXqKu4GWzDzB8SyYzmxxjix0ki8PYPz+wxDcElr/+izIddUVNfVo8YVAJlJhScRQqqTMMKU3AaYYEP0yZAdGjC23WnfcljHEQtR+LjhIjd6SHDyWkG+TQ1O3xs0rz580RWXleAxMNyBIU887elLNi0ECFybUodQUUSKaEzN9GxvRcNv6uSMoQm4Ez2tD8Lw2GBmNu+YLjEWZA2OIP92D2BPH4d/aUlEQvjrAr/2QxZLccwCPNwHy7xWnYIxBHcht8pWQAybVeSAGXTASKpS+ZNk3c0wzLBdjsT/D3RaAZ00dsocnkHi2t2hXablYGYfblhQtqllt2DYJhjOh9idhxBQ+vVHCZo3lfrRpXNLasN3aXPS1eS7kZh8g5RxZ45mixulPxnJIb7Jn+gTga0dtOA11MFlR6dOkTPVZsmNnQhAFBLYtQeyRLiRfHnBE0Ey9NgRtKA3RL2PJ35wzab0pemU0374FqVcHMfHwMai9CYz81x60/d25875AxGkMRcfoPfvAMhrcK8JofN/pGPjGq1B7E0jvGYF/sz2if6kw3YDak3doAnxzyhQ0q0WpMRkm7qUBLmj2JWYtkHMKZjBEH+sCAAQvaofSk+AGl4Hyr4GnIuFwGD//+c8nfe5DH/qQo8+5uM84xIKgsNEYAJTuWNXs3Uw3rHGVUm9IgIKbykWao5neOwJ9LAPRL8N/1vRB+mYpSDVG6/SJLJhiAJJgFWeUilUMNJgC04yivif1xjCYYkBu9sG9srKLntzg5aKMAWSOTFT0sxjLj5uX6iCaC3Nk0o5Rb6bnMt4Yb1gupvjAOo6Qm49HGawqr7H5TvzZXoz/mv8uWVbHxANvTgnvdppSC4GAXNxDmSKBkhttdndGHMldci0J8FGotAbdJkekSb4QqLQUOavp3CZnsmZDIZCJ3OKH6JfBVAPKDAH/2Tcn+GNb/Zazv3AdAHCnSWb/GCDwcdJShWTRK8PTGYFnZf4jfNVySGGeL5h4sX/uHzILmb3cfeVdU1eyq9U6fzp8zjJiCt8sFgBXS/E3lqazB6gsakHpTQA6gxhwWZtPxRC6pAMAkHxlAEbKubIBdSgFpSsGCEDgnOJbgC1H+Uja0XFgc8Pds7quJBHJLBhTB5IVjwrrSRXpPTmnoY2imiCJ+czKMpyuTNWtsdZKszMLkXMlWJU2nU8SysvcBAuc3QqIApQTcduz/JhmWOPSoUuXTbt5boqqSz57NqSwG0ZCtX7nixXGGMZ/fRjqQApiyIXG958OKeJB8GIeuRV77HjNxvO5o96A4JMth6PLjMypQjyGSTkxGQDgbs9NBtSoGKhQ4A9d0mFNzVCOZu0hQZOY98Sf6uZtestCfMFr8PGWaqAcj4NldIh+uayWRTMoezE2nTPGEH+G34AGzm+b8YZOqss5Uarg0DTHzeUm37SuoGKQ6jwQ/bnMmSIvYsmXK1+4FmIuAjIHKls4qv3Jsh1Ec2FmyNrxd0081wu1LwnBK6PuhtNK+l5BFAoKuhbf+9CEMYbYkycQfegoAMB/ZgvPwDowZt2MVgtzhLoUhyZQkPtW4s1tYSGQEwiyaI3Z2X1TYGbcuYpsODcxXQ92jZxbDk0b3LyCKFhuwExuQ+VksrnNGu/qOit7OfnaIPQ4f+0wxvioOXjjr13lPoJLQugqXmQW/+MJGNnyN08td1gZm0XWRp/D10XzGiY3+UoeGzcdPtnD5ec5m1EQ7tz4Y7F4VtfBtSQAphhI5IQhJzCv3d7TG0ragJFCbohBF8B4m69T5HPoSnQAN3h5W67GoI1Udnyp14YAncHVHqyojXw6zPOeUoagmTk8AaYYkCIeayPalmOyoelcHU7x65gkIHBW+VFLUsgNXy6vNWnz+yCxox/6RBZi2I3ghbNnx0ohN3y5yKjUzmFbj6MUlP4k1MHaikuJZ3t5caUooPH9660Yj9DF7RD9Mo80eW2wJsdmjZsvD1mbu+Z7VhtOw5ilTM8uyo3JAFDQYZCo+kb8JIH/smUQvTJcS3IbLiRo1hwSNIl5jTaWsQplIteusNoiTfeG05j5md619WU5e8zxvMUopKgDKajdcUAWELxg6YyPq6ZD07yxKHfcHDi5GGjuXUJ1OAW1JwFIAvwVLFwLMRcBmUPjYEb5F3Ur360MB9FcyDa99plmIPbkCQBA3fUr52yYnQ6rIGWR5mgyxhB9pAuxx/liLHzVctS/ay1Cl3KX08Rv36zKQtbEyL3Xi83rMzEdmkp/8bvzzGAFhUDOjQTZ4VabDnPkvNhCIJNCh2Yl5wgTPefQtGPkHAB8W7jIl3pjeNrjM93nntV1cK8I85FMjSHxAo8wyR6e4BubkoDw1cttOSaTwNlLIDf5YCQ1JLb3zv0N06CNZbhgIcIqiCmFapUCmePmpeSzmvg25K5DRybKnpqxsm2LKAQqRBAEy/GUeK6v6GmJUmC6YQkP5TgPrfOVQ2PnRkq1Got5FE3xCKJgS+kOYwzJl/ka3YmRZ7MMrpzR/fyGQqOtMSAnN52Xg3lsnlV1FccGmfmbqTeGbBN5jKyO+B+6AfBs3WI2O/xb+Qhwev9oTUpSlJ44hr71Ggb/7TWMP3CkJsegDqcQ/Z8uAEDdjafB05nfRBW9MkKX8dz72BMnwFT7z1lzYW0gFeQVSwGXtUauhkuz3JgMIPfek3LTMFWefEy8yAV+KexG8AIu8OcdmuWfCwh7IEGTmNfEnjgO6Aye1XXwrq7PNzxXOGpbLJkDuV2kEkZcC8k7wxbfqGthCcdsIlQ1BU1z57ZSN4+Z31fM2IMpcLg7QiWVSs2GpzMMwS3BSKgVZXRlKnAQzYXp5KrUYaT0JsCyOsSAC/6zix/5K2SxFwNFH+lC4mneCBy5fiXCV62AIAgIX76cCzdxFdFHnA3sLsRyaEZKdGgWlkQUuXhUB5JgGR2CRyrZ5VgKTjSdM82AOsQzMF0lFi1IdR6+wtMMy9VYCWbGsXlNqxTf6Q0QPBL0iawlyljPNZbhmw8iL77g4lVuxPjFfhiKbrWMBs9vsz0DVpAEhK/hpWPx7b3Qk6WPNKdz4+aezgikQOmChXldZFnd0Rtz01lSjqApt/j52KLOrNHnUmCMFTScl77Z4D+jGWKYl22k3rDfFZY5MgEjqUEMukp2EgHlO8qLJXNkAjByf4cyipHygmv5x6ccj0EbSkNwiZagZSfuMkVXpjNk9ptxOvaNmwP2NJ2bUxF2jMJ7VtUBogAjpdm2jk482wsjqUJu9BYdteBqC0Bu8QFavgytWjCdj3nDAMD4dWLgm69Wffok9vhxwGDwrqtH4PyprtbgBW25SJOsZdapJsqJyfmZJu4qjp2XG5MB8GkY81pVSo9BpRiKjvhTXOAPFQj8rhY/PxekNRhlngsIeyBBk5i3qINJpF7nRSqRazsB8GZqCNxpZ8dN2mxo0Sxf7AuAp8yWZmvsdhEKKZaQN0drnnnjZiQ1MNW5rCmgYOS8tfSbt0JMcaEY54UpepZSYjIXgizmxf0ybiQBXhaiDpTvIJoL06Gpx7IV5QXlx4Wnby0u6lgWsaCZ7YpaYmbdrasRyglDAC/lqr91NQAguWPAcjI6Tdkj52ZJREYvenfejCdxrwg7WghlZesOFC+2zoU6mAIMBsEnlyz+CpKY31SwoRjIjE2RbMjQBPhot3kzf7IYZY6bu5eFIXp4EZJvYyOkBi+MlIaxe/dD7eUto6HLl9lyPCfj29QE19IAWDZ/I1MKhe6wchDdEo82gbNj53lBs/RNPkEQrH+fKeCWgj6ehRFXAVEo6/ooyCJCb+HTH/HtPbY7ZNK516V/S3NZ5w730sodkLNhFVaeXt761HI/luB4PxlzzNm3pbmk0rJiMUVhfSJbUlZqtisKI6VB9MuTXHJ2YDadA+XFCWjRLJ/aEQDfhsoFTUEWeYES8o7rStCTKuLP8DVD+OoVRcczCYIA/xm5sfM3hio+jlJIPNcLtT8JwSej4X2nQ270wogpGL1nP0Z+vA96wnmxSelNIL1rhGc6X7dyWlfwpEiTpyqLNCkVLZrl1xJh6n1ZfsLE+WzKcmMyTPKGkuqNeWffnICRVCFFPJMEfkEWrSxSp8bODaP6Tt5qY8e/kQRNomgYY7aMrhVL9LHjVnupefKVAi5LTMo67NJM7+YLdHdHqCyHBZAXUoyk6mgw/HzE3OmbK1NJ9MvWLp2Tja52NJybWBfU/uSco27mWLqdGU5A/iamnAB2Q9Ex/sARAOU7iOZCDJplPPkSmHKwBKkK8g/lRTpyzjQD4/fzv7P/nFYEz53qGPCcVmeNCo7ff9iR0c1Jx8Ty5UyljpwLsmi5q4u9CVdMQfw0Z/IzTeQGL9+pVwzbdurNf6O7LVDWyKQ1dl5hjqah6DCS/MbLLocmAPhzmWvp3cNgev51l8lFypibNgAfkQ1dxEeMTSEneFG7ba73kxFEwdpITbzYZzlUi0GPK9aEQiVla+Zmn1PFQExnUIfLHzkH8u63zMHxks8dpjPX1R4sOb/TJHBuGwS3BG0whezhibJ+xnQYim6JtL4ynYf5ke6E7WtnZrC8MFDiuLmJVQzUV94mjJHWrHVy4Dz7x80BQPTJVsxFKTma5vSJd32jIxtZhWPnpWIem3t5uKwInWmPx8ZykvjTPWBZHa62AHxbSnvtmy7d7JEJx00nJtpYxorTqfuTlfBvaUbrZ87im12igMy+UUz87qjjx2FODfjOaJ61xC9wdisXXJMaz5+tEuY1ydUWgOiZfL51L8uZNLpjjo5OVxKTYZKP/KpyKzu4CHuywF84dm4nbrcboiiir68P0WgU6XQamUzmlPpIp9OIRqPo6+uDKIpwu8s/H9q/nUackoz+/AAy+8fQ8L7T4Stj9KZUlJ44v+jn2ksL8ayqg9qbQObIBC+2cACmMySe51ld/rPLfw7RJ0PwSjlHUQZihc7AhYKR1SzxcC6HpiAIkCIeaCNpaNGstdtlN3Y0nJtIDV4IXhkso0EdSlmFICfDDGaVetjp0ATyOZpKdxx6Ui1alDQyGkZ+tBdKVwyCS7RGK+1GEAVIdR7ooxno45myhBCms0nRBeUiLVKHZvzpHmhDKYgBF+r+ZOWMj4u8tRPp/aPQhtKIb+9F2CHXGwCwjG5lR5XqOgS4O1rtT0LpS84ZlcBYYX6ms4KmIIuQ673QRjNQR9IlFYjMhOnsKnXc3ERu9CF7eKLi173pEBQ8EkSffctGz6o6iEEXb8Y9MgHfugaeeWrePOSKg0z857Qi+vhxsLRmtYw6iWdtPdwrw1COxRB/8gTq376mqO9L7x8FGODqCFbUCi9FPLy4zSGHpjaaBjQGwS1a0ySl4u4I8bHvmML/hiXE8xQWVJSL6JMR2NaKxHN9iD/TA+9ae8rtMvvHeKFMg3fONcxMyE1+QBbAFAPaWAYuG9c2al8CRkKF4Jbg6SwvG1hu9QNCbsM9rpbsmE+9MQSmGpBb/WX/jorB1RaEPp6F2p+cck6YDsYY0vsqc0jPhdwaAPaMllVAYwnlNh6ba4kf6Z2AVqGgqccV694nfG1nyVMxcqMPrmUhqN1xpHcNI/iW9oqOZy4YYxh/4AiYasBzWgT+nHtOcEmIXNsJT2cYIz/ci+yRcTDGbM1SLSR7NIrsoXFAFBC5evY1tSCJ8J/ZgtgTJ/gI+AWOHNIUCgvYTsa1NAiIgBFXoccUyDasX6aj0pgMYHLkl5N/00IKM71PxtUaQBojtjs0RVHEypUr0d/fj76+Plt/9nzD7/dj+fLlEMXyfZYkaBLFoTOwrM7HK6ogaFpi4taWKXmH3tV1SDzTg+yRCcdOZum9I9DHMhD9MvxnlZfbZyLXe6H2J6GNZ+FaJIKm0pMAGB9PLGYHWqrjgqajo3U2NJybCIIAd3sA2TejUHsTMwqa2kgaTNEhuETIzfa08JrIEQ9cS/xQB1LIHh633E6zoSdVjPzXHj6u6ZXQ9JFN8JSRXVb0MeYETW08i3KWR2o/z88UvHLZDiLgJKd0VrPGWE9l1OEUYn/IlSndeNqsxQOi34XwNSswcf8RpPeNOipomm5dwSeX5coqpchCG0pxZ6Es2r6hMB1ysx/aaAbacBoo4sZ7LhSr4by8174VtVDhyLk5bi7bVAhkIkgC/FuakXi+D+k3huFb1wB1MAUjqUJwibwIqADRLSF0aQdij3QhfM0KR0ZcJx2fICBy3UoM/8dOJF8dQPCSdriKOI9nKhw3NzEFf6fypa2G89ZA2XEegijAt6ERyRf7kdk7WpKgOdsNdikE39KOxAt9yB6ZgNI38/W4FMyRWf8ZzWWvMQVJgGtJAGpPAmp/wlZB08qhW1MHQS5vPSO6JcjNPmhDaSj9CfjCxf/tGGNI7uDj5oFzlzgqKrjaAsjsGy16dF/tTUCfyEJwi/CuqXPmmMpsOteTqhWjY6ug2WqPSyxzZALQDLjaAmWPBPvPaEa0O47UTucFzfTOYS4kygLqblk95XXoWVUHyAKMpAZt1N5NBRPGmOXODGxrteIIZsPlQOb2XGRz+ZnTrflFtwRXawBqfxJqd9wWQVPpTUBPKPCeFrHWepkDlY2bA7nXekFmrN0Z2iejxxUrWsIzzbrOTnf0ybjdbixfvhyapkHXdd4poOpwd4TKPu/PNyRJgizLFV9DTv27OsIWXK1+pHeXN15RKkZKRWpXbozlgqkjku7OMCAJ0KNZRy5QjDHEc82mgQuWVtz+LOUETX0RNZ2rPcXlZ5pUoxjIjobzQlztIWTfjELpTSCwbfrHmIU9rraAI2NP3nUNUAdSyBwYm1PQ1GMKhn+wG9pgCmJARtNHNzsu8nDXT7RsoTp7LOfg6Sw/PxPg7ZKiX4aR0qCNZeFuO7UvfYwxPmquM3jW1sN3xtxjY2bOmDaYBDNYRb/v2TBjJUp1A5kUjnHOhfX6WV6dxZ/pLtdGKs+sZIzlHZrlCpo2jZyb49aSAzcOvq05QXPvCAxlNbJHuFDjXhmZ9m8WurQDgbNay379lIpnRRje0xuQOTCG2OPH0fi+9bM+3sholpuj0rK1fNO5M6ObVn5mhddE30YuaKb3jXJRoYhzh5HVrdd3pYKm3OCFb3Mz0juHkdjei4Z3r6vo5xkpFZlD/HVYadGNuy3IBc2+JLDZvtKcSnPoTFxtQWhDaaj9yZKmr7ShFH/9yAICDk1KmbhLbDo382u9a+vLjjKYi5Obzou9Gc8cGAMM7qgsRvgq+nhMUWU4BaYbZW/am2t3z8pI2QKDf0szog8fhXIiDm00beu/sxAjpVqj5OHLl0+72STIItztISjHY1COxxwRNDMHxqAcz008Xbm8qO8xo7i0kTSMlFpx0/1cMFXP5/kvn/58614W4tMv3XH4NlV27TLSGoa/uxNMMfjGwtp6eDc2WefVckrWTASXCFern4uvPQnHBc1sLgLHtTQw7SScmT/N33vM9ns9QRDgcrkgJHSM/OAAz1X3SvCd3gDvxiZ419VXrFOcCpwa8i7hOLKZW1bibmQ5pN4Y5juES6YfYxHdkrXDZN782IlyPAa1Ow7IAoLTCKqlYrpaFtO4a2GzdzE47UQB7Gs4Nymm6VzpcSY/08RcFGQOj8+a0cVUA8P/uYuLmWE3mj9xRnUca7kbcq1MMT9fCFT5uLBk5WhWLjbNd1KvDEI5FuWlP2+b6lqYDrnRZ41HOrn5Yjo0yx3JNrOp9PG5SyKyVcrPNDGLGbRhG4oZJrJgGQ2QhLLPWVZxRYWCplnAJNns0AT4TZTU4AVTDGT2j+XHzacZ7QJyESVVEjNNwtd2AgKQ3jViZSLPRObgGKAzyM2+iq81Tm/0mW6uStzvQK6J3ifDSKqW63IulO64NcVhhxsodDF3gqV2DlecOZraPQLoDK62QMVTNaU4yotFT6rWGqsSYQAoOL4ixUIT833g7gg5LsZYbfFDqaJyWvOFXJWJMrNRbtO5JbbafGxSvQeCRwJ0VtGGmll0WcmaVQq7LSdbaufw7A+ugOgjXbyJvcWP0KUzx4+YGybFnptKgRkMsUd5fmfgwqVF54JLAZe1Jp3rmmIHSk8CMBjEkHvG67jbRtdo9niMR3yB54qn94xi/BcHK47JMMnnaFahxGiWcXOAGzcEtwhorOJpmNlQTsSA3H0ey+hIvTGMsXv3o++LL2L8N4cde96FAgmaRFGYu5FabjfSKRhjVmtiYNvMYyzmxdKJYqD4Mzl35lmtthQOWELKInJomk15ZtD0XFhOlGqMnNs09m9dUPuTM7Z4Kw40nBfiXhGC4JFgJDWrhGna4+iJQxtOQ/DJaPnEFttE3bkwc9nK+bsyg0Hpsk+QyjedO/camw/ocQUTvz8GgDeUFptTJBQIZ061NQKVOzRFv4tnvyEfTTIdjDFL0KykUKoUrLZLGxyaZvauq8VftrvUvPawjFZSQ/DJaNbIuf1OCN6My51ryVcH8yL0DDcPtcDdFrBczuZo4UxU2m5eiCVoOnRdzDecV3ZNFCTRGjU3//1zYde4uYm7I8Tf5wZD4rnK8sZSZrt5he5MwJ4m8ZNRjkUBxjMwKxWDzbWJuflaLFY2uA3j/XNRKNapw7OfW9XhFB8DFwV4S4g/KJVyms4NRbccanZnewqCkHeNlnn9tjPz3XzvpN4YcuSekak6Uq/zWIi6m1fNeo00M3qzDgiaqZ3DUAeSELwSwrOIqtNhp4A4F5Yo1xme8b7aOp7eykvMzDJP/zmtaPmLrQhdvswyRvnPbK54Ysa8ZtkxDTMbjM2c6W0iiEJB5INza2fzfjJw3hI0/9kWBC9u52s8zQAcmqhaSJyyguaHP/xhCIIw40dvLxetLrvssmm/ft1119X4XzC/4LuRApiiO+ui60nkxljEWQt/PLlcnMybUVvbI9XhFDL7+YI8eJE92S/mTaA2fmoLKSZ6TOGvEYGPZReD7LATxc6GcxO5wcsX2ZoxrXOZLw7N3W5nAvMFKZ8RNVvDqxkV4Vkecmz8ZzoqEaq1oRSMlAbBLVo3hZWQFzRPbYdm4vk+sLQG19JAyflV1tiajW6ik7EcmhW47Myxrvj2XujJ6YU6fSzD28YlwdHCikJcOYemPpapuC3eFEDKHTcH+DSDmMswrsSlqVsj584UBVjNuIfGwRQDYqCyzFwniFy9AhAFZA+NWzdrJ8NUA5kDpmBRuQNLrstfF+0WBYysDj03NWKOzFWCKdCk944Udaxm0+3JOamVELqEn++SO/phZLSyfoY2kbU20oqJ6pgL83WsR5UZz1WlYqfz3L0sBAj8nFVKK7Ud56diEQQhLwzP4SRN5+KqPKsithaYTUepTefZQ+OAZkCq9zjye6u0bVkbTfPMchsy332bmgBZsOIM7CZzeAJMNSDVeeZ8H5ibJtpQCka6vPPCyTBVR/SRLoz/8hAAIHRJR8lOZXOCrSqCZhERFXKLH4JL5H0ZFQqFSsF0lbsjhMi1nVhyx9lo+9/no+7m1RX9bGDytdFJ9NEMX/9Iwqwb407maJqoBa54T2cEddefhiV/ew5aP3MWQg5n1S4ETtkgsU984hO46qqrJn2OMYY/+7M/Q2dnJ9rb83/8jo4OfPnLX5702KVLl1blOBcKgiRCbvJBG0pBG0w5llmR2NEPAPBvbpr14uBu5840ltag9iWKHm2e8/mf7QUY4F3fYJuLTZ4nDs3k60OIP3kCkRtOKym4v1RMp6Dc4ofoKS7Xw7xR1iacyQqzs+HcRBAFuNuDyB6NQu2JW6OwJtpYBiyrA7IAV4tzIqJ7eRjpPaOzXkjNcXvZJjG3WCwxfyJTci6j5a5bEa64xAkoHDk/tZ3SZqt38IKlJWf5WIsyB7OSzfG8SlrAfZua4FoagNqXRPyP3ai7/rQpjzGdMO6OUNXyhcSQG4JbAlN03mpcwTVEqbDh3ERu9EKJK9BG02ULu7qDDk2Ah/y72gLWja9nVZ1jGa7lIjf6ENjWiuSOAUQf7ULzn22Z4nTJvDkBpuiQwm5bYkbM9whTDRgpbdr8rnIxrwli0GXLJIpnbT0El2i1Uc/m3GMGm7Wgoly86xp4yc1wGsmXB60x9FJI7xoGGM9qt2OdK3plSA1e6GMZqP0JSKsrb2E3BXU7olhEr8zz6AZSUI7HisrOsyPft1TcbUEox2KzimPMYEi+zCe8ZjNE2AV3nBXfdF44Cu9EiVKlooopmNiR+S56ZfjWNSC9dxSpncO2O3mt3+WGxjl/l1LIbb0Hle44vGsrew9mjoxj/DdHoOc2CX0bG8s615gTbEp33NG2bj2uQM05sL1rZ773E0ReYqZ0x6H2J8tevxhZ3XITniw223UNs6YXSoh7KAfT2epePvs6UjZzNCss5ZoJxhiU3tw5t2BtIQjCvNv8rRWnrKB5wQUX4IILLpj0uWeffRapVArvf//7J30+Eongtttuq+bhLUhcrX4eBD6Yqji3ZzqMrMYXk+CtibMhSAI8p0WQ2T+GzJEJWwRNPaEg+SofYSjn4jQTplhnpDQYGc3xZtbpSLzQh4kH3wQApF4fclbQ7C6tEAgouHHLaDCyetFCaLHY2XBeiHtFGNmjUWQOjCGwbfJrVu3lvwdXW9DW5zyZYhaxlju1SqPmJlLEDQgANAYjoZbkyrNcKJ32jAtb4mqNBU0jpSJzeAJyk8/2KAKmG/m4hzKEgmrsMluCZgUOTUEUELm2EyM/3IvEC30IXtQ+afRSHUoh+kgXAL45VS0EQYDc7IPam4A2nK7o/WaXYCA3+qB0xcp2aDLNsJxbTjk0Ae7SjJqC5jwaNy8kfOVypF4bgnI8hsyBMfjWTx4bTe/h7jDvxkZbBFlBFiEGXTASKvRo1lZBU7MpP9NEdEvwrKlHZt8o0ntHZxUwtJE0WFrj5Q42CmKCKCB0cQfG7z+MxLO98G1uspw8xWK1m89RslcK7rYA0mMZqP1JeCsUNI20Zp2f7RA0AX6tUAdSyJ4oTtDUYwqMlAaIqDhjtFiKKYPLHpng7eZeGf7NzuVnWseU+7cX03TOdAPp/dwlZ/e4uXU8SyobOTdFqEo30Uy8GxqR3jsK5YS9DkSmM2uSzlvk79KzIozUWAbZ47GyBU1D0THxwBGkXuPnCCnsRt3Nq8p247uWBgERufO7UvK5qljMzV3X0sCc6y5L0BxIAmU61M2sR6nO49gmqPnv0GOKoyWWZiHQXOdtp9fO+lgmn6leZWPKQuGUHTmfjp/+9KcQBAHve9/7pnxN0zQkEs6Hyy5kSh2vKJXUG8NgigG52cebzOfALA0wTziVknyxn5cRdQRtzVwzG5aB2oydx5/utsRMwPnMEaXEhnOA/46EnIjpxAiB3Q3nJr4t/IKfPjg2ZZTF3E1z2zAuPRvmIlYbTYOp04+5qta/v7o7eYIkWiHp2kTxgkph/qFdhS7WyPl41taYimLQolkknu/D8H/uQt9dL2LsZwcw/L1dMBTd1udR+5KAZkD0y1aeYylYr6WRNJhq77GZmO/vYsPzZ8Kzth7ulWFAY4g/ccL6vJHRMPqTfWBZHe6VEVs3p4oh33Re/nXSyGiWk/hk53fpx8Nf9+b7qVT0aBZgAHLimlP4zmjmmx+YOauq1khhDwIX8umd2KPHJ51HmMGQcUCwcCpH0678zELMf3dm78isj0s8yyOfXB0h2zf7/Ge2QAy6oEezGPjKSxj89uuIPXWiqEJLdSjFz6GiAJ+NgpgpEJn5hJWQPR7j+ZlNPkghe8qxzNZj5XhxwpM59i038xHVamD9DvuTM0YaJF/KTXid2exYu/mkYzqp6Xw2skejYBkNYsBlW27slOMx4w3GszCypY9WqzZnvstWBIu99xzZriiMlAbRLxe94e1ekRvvPlF+jmbsyRNczBSAwAVtaL3j7IqiRUS3ZK3JnRw7L6VZXK5QFAfsLfOcCTHk5gqWwc0STsAMZukLc22yWu+9sQyMrP1rZ2WSe3pRSXdFc8o6NE9GVVXcd999uPDCC9HZ2Tnpa4cOHUIgEICiKGhtbcXtt9+OL3zhC3C5Zl68Z7NZZLP5BWYsZn/Y8HzDDPQtZjeyHKwyoHNnLgMqxDzBZI/FwFS9ogUMU3UkXuBB8qGLO2y3/kv1XhipBB/dq9KIDmMMsceOI/5UNwDAt7UZ6TeGoQ2nHRtvYAbLO8RKdM1KdR5ogynoE1nbnYR2N5ybuJb4Ibf6oQ2mkN47gsA5eZem6dB0O5SfaSKG3BD9MoyUBnUoNWUxqidV64IvOzj6PhNSvQd6NMubkpcX9z3aSBpGXAVkwbY4CanOwxdAmgEjoVQsqBXLxO/enFpSkWtHzR4et7WJ1Qy9dy8Pl7VjPfm1lHbEQWrkcuSkSGU344IgIHLdSgz/x04kXx1A8JJ2yI0+jP3yELThNKSwG43vO73qiz9Xsw9pYM7yitkw3ZlSnafiBmH/5mbEHj+B7JEJZI9GS94g0HJCmlzncWwkjv98LxrevQ5MY1XN+S2V8KUdSO7ohzqQxMiP9sK/pQne9Y3QBlMwkioEn2zrjZwU8UDtTdi+0ZcXNO27JvrWN2BcFLjb73hs2nHy5EsDfK0nAOHLl9n23CaCS0TjbesR/Z8uKCdiPJe9J8GbiGURs72ETYHau7beVjdsMe7CYrFz3NzE/DspPXEwzZizsMM8P1W62VIKrhY/d7Ol+GbPyecIPa4gvY9vKATPa6vKMZ3cdD5bQZNZYOOzyb09HaLfBTHshhFToA6kSopzYIzZ0nBeiBW3FVUqvkcrJGM2xa9vLHo03hLtT8TLcvQxg1l/w/p3rUPApkgD97IQ1P4klJ64I65iprO8oFnEZJ4dsUPVEDQFUYAUcvNs4mi2oomfmVD7kzzH3yPB3TH7e0IKuCCGXDDiKtTBJDzL7d20sHuz4VRk0ci8jz76KEZHR6eMm69atQqf//zn8bOf/Qw//vGPcd555+Guu+6acwT9y1/+MiKRiPWxbJn9C7P5hrUbOWR/07nSm+BvWEmA/6zWor5HbvFzkUIzim7WnInka0MwkhqkOk9RIzelItfnXGpVytFkuoHo745aYmb4uk40vGMtIABM0WGUEP5eCtpomtviZbHkGyXJwWIguxvOTQRBKGhzHLY+P1PeiRMIgmD9u6bbVTU3IKQ6D0RP9fewrPDuEhyayrGcMLcsZJsDRJBESHXVHTtPHxizxEz3ijAif7ISS/72HAQv4C6vSs9bJ2MVbawoTwSe67VUKXpc4W4/SahYqAP4jbj39AbAAGKPH0f86R5+syMJaLhtvW0OplLIOzQrEDRtdM/JTTz7EeAN3aVeu838TKne+Q0A/9YWBM4p7vpfK0S/C5FrOwHwko/xXx1G/z+/iNGfHQDART07RXQnyg8YY/lNPhsdmqLfZbk0R/5rz5TyJKU7jvEHjwAAwlevqDjLbiY8nRG0fPIMtP3Deai7ZTUvwpAEQDPA1Jk/oDPuvjrfXkHMKrQZSldcFmaWbbhX2nfDLDV6IQZcgM4sJ9BsqDbl+5aC4BItZ2P00a4pX0+9NggYDO5loaplyhXbdJ7aOWyNKdsZZTAd5Y6+6qMZsEwu892mSSYx4LImr+xaczHGkM45wEtxwruWBHi+dVYvS6zLHovCiCm2xxmYk2yqQw5NpTvG4z18clFTc5OdhqW7fJlq5GPHbDxHTYeT94wArHZzz8pIUdd0q3ndgRxNy6FJguaMLBqH5k9/+lO4XC68613vmvT5H/zgB5P+/wMf+AA+/vGP4z//8z/x13/91zj//POn/Xl33nkn7rjjDuv/Y7HYKS9qyo25pvMsbzq3sxjIDPL2bWwsemdcEAQEzmlF7IkTSOwYKHuhwAyGxHY+AhW8qL3iMOzpqGYhidIdx/j9h61FZ93NqywBRWrwQh/NQB1OO+JQU3ryu0il3tTJdR5kYf/FyYmG80L8Z7Qg9uhxZN+cgB5TIIXdVc87cS3xQzkWnTacXnVo3L5YpPr8qHexOLXDK+eC4bXRjG3ZnDNhZHneEsDPK3U35ItrfBubkHiuD+n9Y2C6YZsAohQ4NMvFei05IWhGc1mMIbdtLpXwtZ3IHBxDetcI0rv5jU7dzats3yEvFrMdVqvEoWkKmjY5oMJXLEfy1Vz248HxkjKUzfetU1lYC5HgBUvhWRlBes8I0ntHuZMjt0lodz6eEyPnRkKFkdQAIT95Yxf171gDI6kiezSKkR/uQeNt6+Fd1wA9oWD0nn2AzuDd0IjQZc6vl6WQG8Hz2hA8rw1GVoeRmns0UXBLtrozAf43FHwyL7EcnDpFUSy8bCNXpmRTFAvA19LuFWFk9o1CmcFZW0i1C4FM6m5YhaH/9zo/1585amXYMsYmTXhVE1erH9pwmncLTCPQqwNJjP8q14R9aYetf7dpj2eJH9lD4yVfvy135hL7RloFQYDc4IXan4Q2mrEl8kjtSUCPKhDcIrxrit8QEUQB7uUhZI9MQDkeK9ldnN7JDQv+zU1zOphLwRQZlZ6EI1mQmYM5d+ba+qJ+9mSnYarkdZTSHQc0BjHoKiv2qBT4tTHumKCZOcJ/d8VmertaA8genrB97cwYs2I+7C7XOpVYFA7NRCKBBx98ENdeey0aG+debH72s58FADzxxBMzPsbj8SAcDk/6ONURZDHvPrExR5OpumXlD5xb2s64f9sSQOC71upweceUOTAGbSQNwStZTha7kcsQdUrFyGqY+O2bGPrOG1D7kxD9Mhred7olZgKAywb30GyYu4xz2fOnw7xx02zOCnOi4bwQucEL9/IQwIBUrtTK2k1bErB18TMT+V35qe8BzXKn1kjQrCv9htwxQTP3PtSr4JSOPX4c+kQWUp0H4atXTPqauzMMMeACS2tlZxuejDaR5YKhWFp+7ck4GW6ux3L5mRU0nJ+Muy3A8xcBgPEb2mCJ1xE7MTMrjaRalIAyHapV2GLPe1aKeBC0sh+7SsqQNd+3ThYCLURcSwIIX7UCrX91Fpb87TmIXL8SkbeuhHe9zYJmHXcZazbetJnvbbnRN2tzazmIHhlNH9kI7+kNYKqBkR/vQ2rnMEbvPcCLL5p9aHjX2qq32IseCXK9d84Pu8VMICcY2jB2zss2+HvRTkMBwFt8gfym2EwYWQ3aKF8/VlvQdLcHEbyIZyJPPPCmlVWXPRqFNpqB4JGsXPNqYW4ITLeZbKQ1jPxkH5hqwLO6DuFrOh0/HlfrzGvB2VAcGmm17hltMnOYUy3edQ0lT+8U+xo/GaYZSOU2S31b7X19yS1+CG4RTNGhlXkPOxuZgzyGwbuuePG3kjVgYfa9kxE1QL4YSHOg6ZxpBpQu/jrxFitoOrR21sezvIRNokbz2VgUguYDDzwwbbv5TJhOy7GxMScPa0HiRDGQ0psAy+oQQ66Sdy/liMcKOk6+PFjW88ef6QHAc3ecGsm1smRsDsc2yRwax+A3X0Xi+T6A8WD81jvOhv+kxZ21uKjAPTQb2TIazk2cGh9wquG8ENMdnMrt4lq7aVUaD5jtQupUfmix5MX84ha02niGiyiiYHt4vumUdnrkXOmJI/Ecd33XvW01RM9k0UAQBat9266xc3Pc3NUWrEikmE0crxTLoWlz3lHk6hV8pGplGHU3rbL1Z5eK6JEh5v59ahkbR4wxRwpbQpd2QPBIUPuTSO8anvsbcuRHzsmhORNyow+hizv479hmoS5/XbTvps0SzB3a5BJcEhpvWw/fliZAZxj72QEox6IQ3BIaP7ABonfRDIdZ5HM052fZhunKzJ6IzRpLoQ6kAAaIYTekYPUjPcJXreCTRtEsYo91Acjn7/u3Nk+51jqNJSD2JiYVQzKDYeznB6CPZiDVedDw3tMdmf6acjzm2OvgzOVJ06E6NNJqlTGO2nPPUc64uUnha7wUMofGwdIaxLDb9veeIArW79zuYiA9plhFZKXEe5iv6XJGp6uRn2ni5Mh59ngMTDW407TI66S5Aa2W+N6bi2obZBYqi+I3c++99yIYDOKmm24q6vFHjx4FADQ3V3enbyGQ3420V9AEeIlMOTcD5ohJ6tXBkvOJlO4434WRBMvB4gSFQord+aPZEzGM/Pde6FEFUoMXTX+6CQ3vXjftYtMah3TAock0Iy/klSVo8uO1++LkVMN5Ib7NTYDIHaraSLrqeSfmhdSIKVNcYbVqODcxs/f08WxRr31zQeTuqEyYmw65CoIm0xnG7z8MMN7cPNN4r5nVm9k7akvren7cvLISJeu1FFegJ+1tj9RjzgiacqMPSz9/Hppv3zIvFnyVOOH1iSxYVueOchtHtqSAC6FLOgAA0cePg+nFXSsLS4GI6iMVZGjacZ4AChyaDro9BFlEw3tOh78gE7XhXWtrtrFWa8y8SaWCpnMnCoFM3B1BQBRgxFVe4DcDpsO0moVAhYhuCfVvWw0ASDzfx+NG9nCRK7CtuuPmwGShuu+uFzH8g91IvNiP6CNdfNxXFtH4gQ2OOH+nPZ6C8qRis/J55ru5CW9viaXUaAqala+51KEUN2NIQlEFNydjRvHooxnoieI3iFJv5PJPtzQ74ix3L8sVFtksaGYOcVOWqyNY0uZDuU5DphvWOnTBC5oF7ebFOk1drX5AAIykZmvzOo2bF0ftV/4OMzw8jCeeeAK33HIL/P7JC6lYLDapqRzgJ/a77roLAHDttddW7TgXCqYoZGfTeaXtXd51DbzZL6kiva80t1N8O3dn+s9otnUM8mTkem+ukCff8msHelzB2D37rVyq1s+cNWuuTN6hab/7Su1PAjqD6JctAbcU8qPJiq2ibzUcilLIDc9q/ntPvTFU9UY60SNbwmHhIqTWDedAXghhig6Wnjtk3CoEcmBBVA1BM/FcL9S+JASvPCk382S8q+oguCW+i15EEcNcmA3npTSbTsdMryU7cGLk3ESQxaqPsc6E3Fy+E95yZzb7bXeUBy9qhxh0QR/NIPnK3BMNzGDWzUI1SoGIqUghNyAA0JltawcnCoGmQxAF1N+6BvW3ruGOTQcKFxcKhU3n5QjTk8o2HMhhFFxS3ik2i4PNdHy52mp3c+1dW8/LGBkw8mOey+pqD8LdYa8YVwxysw+Rt67k6yudIXt4AhMPHEEiN/lVf8vqqjYTC658UVGxUxb6eJavzRzIfJcb+LHY0R9gTrN4VtWV5fIWfbLltlOOFyceGlkNmf1cGPTbPG5u4l6We9/1VL4OLMTKz1xXmvhrOQ0HSnMaKr0J7mr0y7ZnM09H3gRj/8i51Qxf5Lg5wM+h+feefWtnKgQqjlNe0PzFL34BTdOmHTd/7bXX0NnZiTvuuAPf+c538I1vfAMXX3wxfvGLX+DjH/84zjrrrBoc8fzGiaZz681a5u6DIAkInM1dAGa5UDFoYxmrRCJ4cUdZz10sgizm8z7savvTDYz+dD/0WC6X6t1r53S0ucwb7fFMxW2bJ6P08AWCqyNUVnaKKXIwRedtizbhVMP5yfhzOX6JF/p53olY3byT6UaFa91wDvCLvBjk7oRiMmTNcHpPBTmQM2EK7UZM4a22NqONZRB7/DgAoO76lbO2bAsuEd7TuQhuOkzKxVB060bTjjH9fFujzYKmQyPn8w25qXwnvN35mYWIHgmhy3mkTuzJE2Dq7OdZPa7w5mcRkEIkaNYCQRIh5s4jdhQDMYPlpxYceI2djCAKCJy7ZFGLmQDfUBV8MlhGt9pzS0HpjvMN45DLkSxwAPDk3P3ZWTIGFavhvLZZbpEbToPol/n5CbVxZwI8HzV0aQeW3HEOWj97NsLXdcKVW7sEL2637k2qSakOOydHWs1MaW08U7HDvJJxc5NSx87T+8bAVANyk88xQclqOu9PznlNLhamG8gcNgXN4sfNgQKnYUqDES9+E00xp6s6I1XZXC50aNppgskcGYfak+BO4LUlisE2x/IxxqpukFmonPKC5r333ouWlhZcddVVU762YsUKXHzxxfjNb36Dz372s/jCF76ATCaDu+++G3fffXcNjnb+M7npvPJdEUPRLdGlnCIZE3Mxkz08UbRgmHi2F2CAZ01dVcZn7G46j/7+GJRjMQgeCY0f3FCUYCWG3RDcImDY71JTKsjPBPgokejn/wa7RgicbjgvxLexEZBFy0XjavVXdfx1ukWsWqV/+1zk3bezv+YYY5Z72IkdXtEv89c/AG2OYymH6P8c4wUAp0UmjVrOhLkwT+8drWhBpvYkAIPxXDMbRoOt15KN0SIAYJgOzfCpLY7Z4dB0ahw4eF4bpDoPjJiC1OuzZ2la+ZkRT1Xy34jpkW0crdPGMmCqMcnJRTiPIIsInMmztpM7+kv+/sJsOqfKNszNsJlKU5jBrE2uahcCnYwUdCPyJ3wCQnCJjrnnSsHV7Ef4smVo/fOtaL/rLai7fuYJDUePo0RB00nBRAp7AEkAdFbRhowWzfJ1jgD4NpQvaJpj58UWA6XNcfOtzY6976SIh2/6G6yiSIpClONxsIwOMSCX7Fwu12mYPWaOm1enJNmJ6QXGGKKPdAHIrZVK3Hw371vsmoLUowr/t1XZILMQOeUFzRdeeAGDg4OQpKnOtZUrV+K+++7DsWPHkE6nkUwm8corr+ATn/iE4+1cC5XJTeeVn3jVgSQPGA+5KrrJlRu88KypA1CcS9NIqUi+wh9n5oo5jTl6YYeQmHx9CInn+gDkcqmaixN/BCGfy2Z3jmalgiZgf9O50w3nhYheGb71+d28ao8HFI6JmJhOnFo1nJvki4Fm/7vqUYX/vURn/l6CIFjlJrPlhJWD0pvgjm8BqLtpVVHXEO+6BkASoI2kK4rxMN0GnhVhW65d072WKoUxls/QjJzaDk0rQ3M0XbIrxYlCoEIEWUTgfN4Cb2aDzUS+4ZwKgWqJuUlhR9O5WUojt/jnTUTDYsHMe0/vH+Pu5xKoRtmGKWiq/UmrQbwQbSQ9r8Rw/9ktqLt1Nd/Qn2dFU7XMci71+m1OxTixZhVEoSDqp/x7jkwuTsy9PDzr5MtcuFfkms574nNOqekJxXI5+s5wTjAXBMG6b7IrR9NqN1/bUNZ5vtTXEDMYsl3VKwQC+HvMnP6ya+w8s3cUak8Cglu0pllKweoZGbLn/lrtzU0+tvohuE55ya4i6LdDlIydlmprZ9CGsFtzsZh8ZRBMn/km0khriD1xAkwx4FoSgKeEjIxKsCu/T+lLYOL+wwCA0OXL4NtY2iiXVQxkY9O5kdGsn1eJ09bukGfz5s3V7FzDeSGFLoFKfg/lUDhyboootW44N8k7NGf/u1ruzEavY3+vUlvXiyX6aBcAHj1QrBglemUro6eStvN8IZA9O+PTvZYqhaU1a8z/VB85l+q9gCSAqYaVG1oMTDOs86iTu/H+Lfw8lT0WnfVca25AyJSfWVPsvC5m9pvCQPXzBhc7riUB/ns3GJKvzp1ha1Ktsg054uHXaja9sGIWArnaAvNCDBcEAcFz22bNjV+MWNfvodSs90KAOdKaMyM4VDqSbzovf81lFmKZMT1lH0uTj0+CacwScmcivXsEMHipTrGmkXIxXZRmdFel5PMzy/t9lezy7U+CZXQIHqmq+bp2XhuZwRB9rAsAEHxLe1nCuRXrZpNDs9JIvsUECZpEyeR3ICp/w5ohyHbsDPrWN0IMuGDEFaT3jcBQdOtDi2aReLEPwz/Yjb4vvYjE89zdGLy4vWpuXLtGzuNPdfOx1rX1CF+9ouTvd8KhaV6EpXpPSW16J1Os8FX0cZm7WzY3N86Ed10DBB93CpjNhdVCbvJxEUXRrd9ffuS8tqMKsuWKnP21b+WdOlngZLWu2ydoZo9OIHtoHBCFkt+T3oKx83JgjFklDqb7oFKmey1ViunOFP0yBJe97fXzDUEqcKWUsHGkjaQBg0HwSo66WOUGL3djMSC1a+axczMiwo4YA6J8rJu2Ct+LTNWt84zfQccRMTPWxvvLA0VvFlWzbGO2sXNrg7jG4+bE7Ej1Xh6tozFoo7Nff/RoFkbS2cx3081brqDJGCsoPaxM0BcEwXqNp3fNnl2eeoNfG/1ntFT0nMVg5Wja4NDUk6olRHrKFPtLjR0yHeTuFeGqxtOYk52lbBzPROq1IWhDaQg+uezJTdMwZCRUGKnKx+At01eVDTILkfnl0ScWBFbTuR0OzT4zu6XyG3FBFuE/uxWJZ3owdu+BWR8rt/gROLsV/jOdv1BZz2mXQzN3wQtd2lHeKEFuB0m1selc6c79HSsscrHdoVnlMGVBFtH04Y3QRtNVD3AWJBGuZj/UgSTUgSREr2QFeteq4dzEGpmc06GZc6c5uBtud9N5YeZO4NwlJY/i+dY3YkI4ArU3AW0iA7nE8V5tNMNvSGTBNofFya8l83dWCVZb9inuzjSRm3zQhtP8NV3kTUXhuLnTG23+rc1QjseQemMYoRlK8fIOTRo5ryVSnT2lQOkDY2BZHVKdxzY3N1Eavi3NmPjdUeijGWSPRotq0a1m2YZ7eQjpncPTNp0r86DhnJgbQRQgtwagdsehDiRnndAx18hOjrRKufggfQ5xdSb0iSyMmMJFVxuEneD5bcjsH0PixT4EL263MooLUYdTXNQXAP8ZzheamYKVNpqBkVIh+l1l/yzTrCJF3JAC5f0cuUDQZAab9bzDNMMq2PWcVp1xcxO7ms6ZZiD2BC/0DF/WAdFXnjwmevhmtB5VoA6n4VlR/t+RMUYN5yVADk2iZOxqOmeqYe3+2PVmDZ7fZhXLnIx7WQjh6zrR+tmzseSOs8sWBMvFFAX0aLbshnE9qVo3NeUKZo44NM38zBLDp0/Gdoemg9lAM+FZEUbgrOo3WwKTc2/UedBwbiIV6dDULIemcwKsbHOGZmb/GJQTcQguEeErlpf8/VLInXcMlOHStMbN20O25nbZnaNpOTRP8UIgEyvao4TzrNP5mYX4NjcBIr+hnWlzyyoFIodmTTEFJKUnAb2C8gPLcbS1eV6MDC9GRLdkRdMUk/cOFJZtOC8WWC3Qx+NTHKTqPGk4J+bGuk+b4/pdDcHEcmiWuYlsrnFcSwMQ3ZVPd3jW1sPdGQY0hviTJ6Z8nTGGiQeOAOBTV9UoMRT9LuvezJxcLBdzzVFJzq3c4OUCt2bM6vI1FB0j/72X/41koaIG+nKwywST2NEPfSILMeRG4IKlFf0sqxiowilWI67ASKiAUJ014UKHHJpEyZzcdC6XebOjDiR5M2/AZdt4ndzgRdvnz58iGAqiUPNAXTHoguASea7aRNa6eJWC6WiVG71lh6Cbz2skVBgZzZYwdXPkvFKHpmzttlUuNumxLHcoCotnRIrvqg5zh2ZuZ7bWDedAPoPPSGkwFH3GRakprDjp0JRszNBkBkPMzNy5cGnZ7kPfxkYoXTFk9o0i9Jb2kr7XEjRX2Ou4Knwt2cFic2iW44RXB3Kv/yXOv2eloBveNfXIHBxH6o1hRE6KSmAs30orkUOzpriafHC1B6HmiseCuVKnUjDSGjIHeFGEf2v1JlOIqQTObUNyxwDSe0agJ9VZXVRM1a38wGq0B7vaAnydmtGgjaQtd58eV2DEFbq5XiC42wJIAcgemQCumflx1ZhiymdopsEYK3n6QDnB7y88Nq1xBEFA5LpODN+9C8lXBhC8uH3SmjP12hCyb0YhuETU3Vi9pnp3RxDaSBpKdxzeteVnhZoCZDn3mCbc5euH2pPgLt9p1uRGRsPID7mYKbhFNH5wo+NZoydjCZqx8h2aRlZH/A/dAIDwlcsrFs1dzX5kD09UPAVpCttyi98WIf9UhxyaRMnY1XReuDNo53idIAkQPdKkj1qLmUCuYbnCcVc7dlNFrwwxF3ZsRzGQHs2NgwiV7/JaLedRpSL3L7A4LwaFZS5Ww3mNC4EA/poTvPxvMJNL00hrVRmRt8TVhApDmdrkWgrpncNQB1IQvBJCl5aXuQMA3tMbAADZrhiMrFbS9+azpezNiS18LdlBvuF8cbj9ynHCWw6oKgkGvpywld45POV8ayRVq8Sp3E1Lwj7MzMu5mulnIr1nBNAZ5FY/CVI1xt0e5GslnSH12uzlQOn9Y2AKjwmoRjGEIIlw5SZt4n84ASPDr0fmuUlu9C2a9dRCxrelGZAEKCfi1hrhZJjObO0xmAm5wQsIAFMM7jgrkawDm7aezghfdxlA7PHj1uf1hILow0cBAOGrllfkciwVl01N52ZWaSWCJjD7GlBPqhj+z91czPRKaPrTzUXFZ9iNuUFeiQkm+WIfjKQKqdGLwLbKp+vM+xetwqZzpcqRaQud2qs8xILEjqbzaucbzgcqbVi263dmXuhUG8bOzYuvq7XycRBL7NAMGKnShJ2TyeezLp7Xl7kA0UZS+XH7eeDQBGBlQ86Uo2nuZkpht6Mj8oJPhuDJiasVRBswzUA0txAOXdpRUeaR3OTjOVM6446KIjHSmjXWYncmXuFrqdyIjEIsQXORODTlnENTn8iCqXML50Zasxbl1Srx8m1ogOASoY2krWuLifneEENuW6MMiPLwndEMCIDSFYM2Ufr6wRRCyZ05P7DKgV4amHXzthYxAYFzWq3nHvzmq0jvHaFx8wWGFHJbHQGJZ3qmfUzq1UEYSRViQIbbwVxUQRbzZoUSzRyGokPtz63lbV7jhK/hUwnpXSOWeBR9+BiMlAZXWwDBi0qblqkUc8JN6YlXZOiwY+QcmLnpXI8rGP7uLqi9CYgBF5o/vsU292ypyAUj5+X+ztL7+eRC6OJ2CFLlax0zbqhSh6Zag8i0hQytUomysKPp3GygXkyCU6WFJHbl3ZjjkJoNxUB2jZsDfOEjBrkwVGmOpvW7qoKrYb4gRdzcCWkU5A7VuOHcJN8uPv3fVatCwznAndJ2FANlDo5DH8tADLoQLHFMfLpjMkeMMgfHi/4+pTsOMB66L4XsFQoLX0uVnOdNzE2cxeLQFAMu/vtjxbW7qrlpByniKTuQvlREjwzveu4ONoUTgI+STTzEXSqVujwIe5AjHitDsfBvVQx6LGuNLVO7+fzAf0Yz30wYTkPpmt5BZ6RUZA5WPyYgcHYrmv50E6RGL/SYgtGf7EfsDzxrcLHE95wKhC7m65L0vtEpkwJMNRB7Mrche/lyx6fYCsfOS0HpjgMGX4/YPSngXhrkG0UAYo91IXNoHKnXhwABqL91jS3iVknH0xYERAFGQi37/ocxlhc0myqLijGjb7QCQZNpBkbv2Q9tKAUp7EbzJ7bYVkZZDmZcHVMMsEzpE1dMNSxTjmd1+WP+hVgxHWMZa8ql5ONiLN9NsYg0kkogQZMoi0qbzplmfyHQQsAcOdfLEFKMlGp9X6UXENM9ZEcxkOXQXGbP39EqBqowR9Oy69vQirhQEAQhP06Y26ysdcO5iTxHMZCaiz8wX5tOUmxJ0WxYN5pbmm0ZwTPHzjMHx4reabbGzR1oLC58Lal9leVoMt2wzjWzNa6eSgiCULBTP/d5Nl8IVN3fjymUpHYOgxksP0rWxUfJIm/trOrxEDPjy5XJpEsUNFM7RwDGRzZNYYGoLaJXtsSUxIv90z4mvXe0ZjEB3jX1WPKZsxC6bJmVmQ9Qw/lCwtUagHddPcCA+LO9k76WeLEPelSBFPEgeF7pmbylYhUDFbG5V4hywpmMcJPI1SsAUUDm4DjGfnEAAM9Dt8OgUSqCS7Q2DModOzeSKn+vCoDcYI9DUxvLWPFMEw8dzY+Z37655us5wSVZRcDl3DMq3TFAZxBDLsiN9lwbxWDhZnZ599jaYApGQoXgEisu210skKBJlEWlTefqQJKfRPzyompQrcQZpuREBanBW9F4K1CQ71ZhhiYz8hk8dp107Wit0+NKPtdzkS3AC2985kPDuYn5Pp9p5Nx0aFZjgWTmaJYb/cAYswRN7zp7dnW9p0UAWYQeVYreKHJ6se85jTvCim3jnQltOA3oDIJHspy6iwGXlaM5998zXwhUZeFibT0EnwwjriC9cxjD3zNHyWQ0377FEbGcKA//piZAEqAOJEsq60rtNMfNyZ05nwjm2nTTu4Yth3YhtY4JEFwSItd1ovXTZ8LdGYbc6IWnk84HC4ngJTzbO/XqIPQkz680MhriT+VKUK5y3p0J8CkSANBLdWgez7nUHLoOyU0+KzfRSGqQIh5rFL0WFI6dl4O5cSxFPBX/XaWgm0/MMS6wJV8ZQDK3+dLwntOrXgA0E5XcM2aP5UwBKyO2dXkIgmDdx5Q73ZTJRU+5V0Yo8qdI6LdElIXc6AMkvmtb6o4b4Fwh0HwnP3ZR+u/MzsxR0zmkjaTBjMqyWlhW5zuLNo02W5koFYycm68vuckH0bO4AuwLHV7zJT8TKBw5n/61b42cV2GRlHdolvca0wZT0KMKIIuW6FcpgkuCdxX/WaZYOhvMYFb7p1OCZvD8pbxY4HhsxmKBYrDch63+xXW+z73/Mvvndt3mHZrVFTQFWYR/cxMAYOwXB6ENpiCG3Wj+xBk06jTPEP0ueNflIgJ2FufSVIdTUHsSgAj4cn9nYn7gbg/Ct7ERYED00eOTvjafYgJcSwJo+bMz0Po350D0zo8NUqI4PKdF4GoPgqmGJUbFt/fCSGmQm33wn1V5CUoxmO63UswcjDFr09bJjMbwlXlRt+5tq2pqAjCNIeU6NO0qBDIx1yPJVwcx/sARAFwE9+UmiuYDeUGz9Kbz7DF+jjXjXOzCuscuU9A0s/RrUbS0UCFBkygLQRatHbPsmxMlf79V2LKI8g2B/Mg5y2gwUqW1/ZmZo3ZkQsr1Hj5GpBpWWUc5WOPm7UEIkj1CheXkq8ChuRgLp0wKBZH50HBuYpUCjWemiDtMM6yFbnUcmpWVc1nuzFURCC77BHNTrEgfmDtHUx1M8c0Ej+SYcC2F3ZY7KLF9+mKBYqiV+7DWBM5sAWQRyok4MgdmFqkZY5agKdfgd+QrEEykBi9aPrGl5qNkxPSYLsvUG0NFTcekc8KnZ3U9pODiKORaSISv7QQEILNvFNkT+U2j+RgTsJg2o04VBEGwsjQTL/RBm8gisZ2Pn4evWWHbun0uzPHnUswc2kgaRkrjhgkHy6iksAdNH9uMxg+sh299o2PPUwzuXHSX2pMA00s3m+QLgew5Z5hry+SL/YDG4F3fgNAVy2352XZh5miWes/IdMPqGrBb0HTlor6KiRua7rjMzSzPqjo7D+uUhgRNomzMnYNSWnlN7Cq3WWiIbskqvdFKdIeZOXZ2iHSCJOZ3TIsYh5wJK7TYxowP8+Jkh0Nzsb2+gMklQPPJoSm3+AFZgBFXp+xaaiNpgAGCR4IYqixOoRgqybIF8oKj1+ZdanN8XTkeg5HRZn2suRBzLws52n4buiRXLLB3tOw8oFq5D2uNFPEgeCEfK409enxGN7weVXigvShYhW3VxLMyAs/qOriWhdDyiS0Vt6MSzuE9vQGCW4I+nrUc2jPBGJvUkk3MP1wtfsslF3u0y/o8xQQQduHb3AQp4oGRUDHy/d1gig5XexC+TdVzbJv3G0ZShZGdfW1jYhVbdgQdL+jxrAjDt7H2Dna52Q/BI4GpRlmlreYazW6HpvkzG969ztH1ZjlI4fJGzpXeBJhqQPTLtps/KnFoKt1xMEWH6JephK0ESNAkysZjCppvTpQ0tsw0A2q/feLcQiOfo1m8OGBktHyphk2/MztyNO1sODexI0NzMTs0RZ9sFevMpzBp0SPBm2sRTO8ZnfQ1dTifn1kNF4iZoWmktKIX1yZGRoNynO+ems3kth1Xo4+/Lw2GzOGJWR9rCZoOjmIBsxcLFEutCm/mA6FLOyB4JKgDSaR3TT8mbLkzm301yUsSRAHNH9uM1j/fumha6BcqolviY8rIZyzORObQOLSRNASXaH0PMf8IX7UckARk34wic3gc6kiaYgII2xAkEcGL+MaaeR8Rubazqo5b0StDDPBR7mJdmmZ+ppPj5vMNQRSs+5Zyxs7zDk17BE3z3k5wi2j8wPp5GTlh3TOWOG2o5MbN3Z0R20VaUyAtJ9bNNIl5VtXNO/F4PkOCJlE27o4QBI8EI6VZAmUxqEMpXhDhlS2n1GKiHHeYOaIv1XkgBexxsFXadM7UAmHaTkGzLn9xMpv1SkFPKJYYasd4/kKk8QMb0PSRjfPOEWfeVKf3TRY0taHqNZwDucW12YxYolM6c3gCMPixOuFkM12ac+VoZquQLWUSzI2spV7JFwsUi5HRLLf1fHs9VgMp4EIoV8wQffw4mG5MecxidbAS5WG69tK7RmYcS2QGQ+yRLgBA4Py2eVMOR0xFrvdaTdPRR7uQzgnVFBNA2EVg2xIIuTx5z2kReNbUVf0Y8k3nxd1zmLndThUCzVesYqASBU3GGLQR+zM0G29bj+Y/O8O2ngS7sab6SjTBWGPdNo+bA7lYKykX61bitKFZCOSh/MySIEGTKBtBEqxCjFLGzvPuucCizOQpp+nciRFqV1Ouha1Mh6bSn+BN9QHZ1uZiKezhoq/OkHi+r+TvN0fz5SbfvNxNrAauFr+Vxzif8K5vAAR+DijMrzQdmtXM/DSLgUp5HwIF+ZkO/X7Nn5s5OD5jRp4eV6CPZgDB3s2EmfCsqoOrLcCLBXb0l/S9aq6xXQy7IfqdjxOYjwQvaocYdEEfzSD58uCUr2uL2MFKlI5ndR3EgAtGUkX2yPR5u+ndI1D7kxA8EkKXLavyERKlErpiGQS3CLUngfjTPK+Yxs0JuxC9MiLXdkJq9CJyw2k1ufcqpRTVSOWjidzL58+kUTUoV9A0EiqYogMCbM3d9W1qmtd9F+VM9TGDIdtl5mfaL5gLkmCJymoJ0QFGVrf+7lQIVBokaBIVYQbWZmZYVE9HXpxbXBcpk0oETTsvKtbIeZkOTbUgP9POxZEgCghfyUOn40/3wEiXNhJslSctwnHz+Y4UdMPdyRcP6b15l6a5cHVVoeHcRK6bvXV9OhhjyBzM5Weus3fc3MSzMgLBJcKIKzM6383mT7nFD9HnvGgvCILlMkw83wemTnUZzgS5D3ncQuhyLirFnjwxxXlulSbNUwcEMb8QJBG+LXwUeeKho1PydpluIPY4b80OXdxu21QH4RxS0I3gRdwJz1SDYgII2wleuBRtf7utZuKUlHNoFjOdls3dX8hNvkXnUnblBE11MFnSlJrpfJXqPDWJrqkVpkOTZXQY2eJ+X2p/Ml+q6dD7wcxDNyfQiiHbFQV0BqneQ1nmJbJ4XvGEI3hzYwtKVwxMK+4m18pdbF+cN29yOSPnpgjcYaOgmTvZ6uOZov92hSg9OZHVAYeY/8wWyK1+sLSG+DOltSsv5vzMhYAZvG4KmsxgVo6r3FK9C7gZ/VBKOZfan4QRVyC4REfGVADwn53bmTXF05PJnqh+tpRvSxOkiBtGQp0zu6+QxZyfWUjwvDZIdR4YcQXJF/qgxxUkdvRj+L/2QB0k0ZcojfAVyyGF3dCG0xj75aFJOV3JVwehjaQhBlxWXAQx/wld0mFFoXjXN1BMAHFKkXdozi3wWBnhi8ydCQBS2A0x5AaMfNxYMVj5mTaNmy8URI8MwcvjFPRYcev5bC4/09MZdiyn0srRLMGhaU67mn0DRPGQoElUhNzihxhygamGlXcyG9p4hoedC4Cn0xlBYL5jCSkT2aLCgo1svhDIzp1VMejiFwFWfKZNIaYt3uWAoCmIAiLXrAAAJJ7thR4vPuzZcgDP4xGJxYxvA3edKF1RK++UqQYgCZAbqrcQk82R8xIcmua4uWd1naM74HPlaFarEKgQQRIRfAsXR+Lbe4oOOif3IUeQRYSv4ue06GPH0f8vOzDxmyPIHhoHGOBZU2drdAdxaiOF3Gi4bT0gCcjsHbXGlJmqI/7ECQBA6PJlJIotIESvjLqbVkFu9FqOeII4VTCbzosZOVdym7bVXOPMFwRBKBg7L0XQzOVnLkJnX6lN56ag6XbImADkJ87UEprOrUKg1YtTH6kEEjSJihAEAd7c2HkxOZqpnbzl1bMysmjbVKWwB5AEQGdF7SapfUmA8V07KWTf6IUgCJYjKPbkiRnz+qbDSKl5kdWhJm3vhka4l4XAVAOxP5wo+rjMkhdyaM5P5AYvXEsDAAMy+8fy7sxGHwSperlO5ZRzZQ6Y4+bO5pN61/Kfr5yIwUhNLuFhmpF3uVfZvRA4lxcLaENppPeMzPl4xhg0ch9a+M9q4bv2OgMYd9yHr+1E6x1no/lPNy/KTGmifDzLw6i7eRUAIPZYFzKHxpF4oR96TIFU50Hw/LYaHyFRKv6tLVjyt9scW1cRRK0whTY9mp11KozpzBI0F1PDeSHuZbmm857iczRNY8qiFDStYqC5zS+MMavh3KlJK6B0h6aeyMdMmXF+RPGQoElUjDkemX1zYs7Hpt/ggqZ/a4uDRzS/EUQh7w4rZqfSgUIgk8h1nYAoIL1rBIntvUV/n3lMUoPXsXwuQRAQvq4TAJB8aaCozNHC46pGtiBRHoVj56qVn1ndRZicc8MVO3JupFQru9Kp/EwTucHLF0MGkN4zuRFe6UsAGoPol6s+WiR6ZSvnLfb48Rkblk2MuAIjpQEiL6pa7AiigKaPbkL9u9dhyZ3novUvzkT48mX0uyHKJnhuGwLblgAMGP3ZAcT/2A0ACF+1fFHlqBEEMb8Rgy4IbpFPhc0yGaP2J8AUnm9YzaLI+YS5oVFKMVB+5Ny+QqCFQinFQNpQCkZKg+ASHTW+mLFuRlKDnlTneDSQfZOLrK4lgUWXG2sHtNohKsYUNJXu+JRw+kLUgSTPU5ME+DYt7rDzUtxhTmZCejojqLvxNABA9H+OIVNkW715kXW6Ydm7qg6eNXWAzhB74vjcx0X5mQsCs+wgc2Tc2oGu9sJVquPvQZbRiiqeyhyeABggt/qtDQkn8Z/FN32ij3ZNWgwpx/OjWLVw9IUubofol6ENp5F6bWpjdyHmuLnc6IPgouUGwMuoAme2QF6kEwqE/dTdvAquZSGwtAYjpUFu9sF/ZmutD4sgCMJCEPKxQrOZOVKv8Yxu79p6x/IN5zumoKmPZYoSwxhjeYfmIsvQBEoTNK1x8+UhRzf9RLcEKVc+WoxL0zSFeajdvCzoDoOoGLnOy0+gDMgejc74OHPc3LuuAaJ/cbdultJ07qRDEwAC57dx8YQBYz/bD21i7mPKHJ4A4LygCQCRazsBAKnXh6zyjJkwA7Sp4Xx+I7f6eZ6SxpDezUeXqy1oih4JYs5dXEyOppln6bQ70yR0UTvkVj+MpIro749ZnzddorXKlhK9cr6x+4njszaeU8M5QTiPIItofP9663wWubazqvEdBEEQxWAWP2YPT194yFQdyZygGdi2pGrHNd8QfbLl8Ctm7NyIq2CKAQioyob7fKOUkfPsMb6GdnLc3EQuoek8Y+Vn1jl4RKcup6yg+cc//hGCIEz78eKLL0567PPPP4+LLroIfr8fS5Yswac//WkkEsUH8RIFY+czOPwYY1Yzrn9rc5WOav5SbCGJoejWzo673RnxUBAE1N+yGq72IIykhtGf7J9VpNAmslC6uHBdDaetuyPEn4cB0d8fmzHrk2kGlK6c2EOC5rxGEAR4c2PnyI0tV3vkHIBVwqLP8T5kql4gaDqbn2kiyCLqb10DCEDq1UFkjkyAMWaVr3mW1y5bKnj+UkgRN/SogsSL/TM+jgRNgqgOcp0HLZ86A40f3gjfpqZaHw5BEMQUAmdz53jy5cFpJ2NSu0fAMhqkes+iF3ZMl6ZaxNi5OW4u1XsXZdRIsQ5NxphlvHKyEMjEjBOaqxhIG03ziU1RqIrQeipyyr/qP/3pT+MnP/nJpI/Vq1dbX3/jjTdw5ZVXIpVK4Zvf/CY+9rGP4Xvf+x7e+c531vCoFx5mgO1MI8vKiTj08SwEtwTv6dURBOYzxY6cq/28EEgMuSCFncvUEFwSGm9bD9EvQ+1NYPzBIzM+Nr1rGGCAuzMMua46O4Hhazt5m+vBccvRdzKxp7qhxxSIQdeibEZcaJhj5yZyc/WzkvJO6dkXQYkX+mEkNUgRDzyd1XtteVaEETiPF3tM/OYwtJE0jJgCiAJcHbUT7QWXiPCVvLE7/scTMLLTj+znBc3FmYNFENVEbvTBR+srgiDmKZ619ZBb/WCKjuRLUzdDky8NAAAC5yxZtOPmJuYEnLmJPRuLedwcgBXhM1fRrj6agRFXAEmApwqlmsUWA5naiXt5CKJHcvqwTklO+daMiy++GO94xztm/Po//MM/oL6+Hn/84x8RDvMb1c7OTtx+++147LHHcM0111TrUBc03lURQOBhu3osy5u8CzDdmb6NjRDd9GYtduTcbPpzyp056ZjqvWh47+kY+a89SL0yiOBb2uFum+qsyjttq1fs5Gr2I3TZMsSfPIGJ374J7+q6SbEF6lDKKkOou2kVvcYWAO5lIYghN4y4AiniqclFXMo5pWdzaBoZbXLRhlTdfcDIdZ1I7xuFNprB2E8PAABcSwM1f437z25F/JkeaCNpJLb3InzViklfZzrLFz6RQ5MgCIIgFjWCICB0cQfGf3UI8ef6EHxLu+UoVIdSfMpKAALnUAaw6SDMHp5A7InjCF25fMbcdKsQqHHxjZsDsAw/RlIDU40ZM9vT+3jJpntZCILL+TW0OXmmDs88cq7HFcSePAEA8K6pTqTVqcgp79AEgHg8Dk2b6iCJxWJ4/PHHcdttt1liJgB88IMfRDAYxH333VfNw1zQiH4XXEu5Yyjz5uQcTaYzpHdxVx2Nm3PMi46RUGFk9RkfZ4YXe1ZWxxXmXVMP32Y+rpbY3jPl6+pQCmpfEhAF63HVInz5MsjNPhgJFdFHuqzPM4Nh/P7DgM7gPb2h6sdFlIcgCvBt4G4iM1ep2uSbzmcWNOPbe/NFG2dVf5EtemXU37QKQM6xDe7crDWCJCB8Tc6lub13SnC9NpoGNAbBLVrCMUEQBEEQixf/1ma+mR1TkNo1bH3edGd6T2+wRogXM+62gLXGij1xAtH/mTlyy3JoNi5Oh6bgky0RcyaXJmPMeo2ZpZtOYzo09fEMsl1TO0aYbmD03v0wYgrkFh+CFy2tynGdipzyguZHPvIRhMNheL1eXH755XjllVesr+3evRuapuGcc86Z9D1utxtbt27F66+/PuPPzWaziMVikz4WO95c3kl69wiYkT/pZt+cgJFUIQZciz4TxUT0yhB83CA9kzuMGczKqqxG1odJ6OIOALzE6eQ8EtOd6V1bDylQ3WInQRZRf8saAHzhY4q9yZcHoHTFILhF1L1tVU2an4nyCF7cAfeKMIIX1OYiLs/h0NQTChLbewEA4WtW1Kxow7epCd4N+RF9dw3zMwvxbWqCa2kALKsj/ocTk75mjpvLrYFFPzpGEARBEARfywffwtd8iWd6wRgD0wykXhsEAATOXbxlQCcTvmI5IjecBoD/riYeODLp/tpEG+Fr2MU6ci4Iwpw5msqxKLSRNAS3CP8Z1TFXiQEXLxJlwMgP9iBzUhlW9OFj/P7VI6HxAxsgek75wWnHOGUFTbfbjbe//e34v//3/+LBBx/EXXfdhd27d+Piiy+2hMr+fp7f0dbWNuX729ra0NfXN+PP//KXv4xIJGJ9LFu2zJl/yALCu567rTL7RjH0nTeg5BqnrXHzLU1VH9ecz7hyFx6zxfxktKEUjJQGwSVWteTGvSwEd2cY0BkSz+ffA4wxq6m+Vk5bz2kRa7Ezfv9haGMZRP+HN0CHr+msWqYnYQ+uJh9aPnkGfBucL5eaDskq58pOu/Mdf6obTNHhag/WvGij/uZVEDwSz/6pkmN7LgRRQOS6lQCAxPN9VnESUJCf2Ur5mQRBEARBcILnLoHgFqEOJJE9MoH03hEYKQ1S2A3vWsoBLiR0UTvq384LIpM7BjB+30EwPb9eZYwt+gxNID/5mN43Nu3XLXfm1paqCYeCIKDh/evhWVsPphoY+dFepPfyidXk60PWPXbDu9fBVYMegVOJU1ZduvDCC/GrX/0KH/3oR3HTTTfh7//+7/Hiiy9CEATceeedAIB0mp8APJ6p1nav12t9fTruvPNORKNR66O7u9uZf8gCwtMZQf3b10DwSlB7Ehj69uuY+P1RpPfwzIpqZi4uBEy3aubQ+LRfNx2I7hXhqgvBoUu4SzOxY8Aq/FB7EtBHMxBcIrzrayNAAUDkrSshhlzQhtMY+n9vgGV0uDqCCF5IVn2iNMyRc5bVYaQmx5JoExmrwTtybWfNnb9SxIPWvzwTLZ/aOiWjuJZ419YjcN4SgAGjPz9oLazVAcrPJAiCIAhiMqLfhcA53JwQf6YnLzad01qzSZj5TGDbEjS853RAFJB6Yxij9+4H0wwAgBFTwFQDEPNr2sVI8C3tAIDEi33QJia7NI2UitQeLiQGtlXXASy6JTR9cAN8mxoBnWH03v2IPXEcE/cfBgCErlhWM1PHqcQpK2hOx+rVq3HzzTfjqaeegq7r8Pn4TkY2O9WenMlkrK9Ph8fjQTgcnvRB8BPFkjvO4TmGRm6cQNEh1XvgrkKj2ELCu46H/2YOjU/abTPJ52dWb9zcxHt6A+QmH1hGQ/JlPgZijZtvaKxpC5vok1F3I88UNJIqIAL1t66hsVaiZASXBDHEoxNOHjuPPXEC0Bk8p0XgWVNXg6Obitzkq6pbu1jqblwF9/IQWFrD6E/2w1B0qINmwzkJmgRBEARB5Ale1A4IvPQm+2aUlwFVWWxaSPjPaEbjbesBWUBm3yhG/nsvX2uZhUD13kU9BelZU8fj2TSG2BPHJ30t+frQ/8/efce3Ud//A3+dtuS994yTOImdxCGLUJrQstOyKbMtFAotUGiAsjpofwUCZZWWMkoplBRaKLRA+bJHaHbiTMd2huO94m1Ltrbu94dzQrYlW7I17dfz8cgjsXR3+kjRne/e935/3oBNhDIjCsrs4J9DCwoZEq+YNzx3p2P4+kK0OqCZmzCmoSZNzoz75ufk5MBisWBwcNBZai6Vnrtqa2tDZiYzviZDHqtC0lXzkPS9+c45LaJOSgt5hlO4UeXEQtAqIBptsDTrRzwnimLQGwK5EmQCok89cbdrc8vw/DYhLjd3pS1Ndk5xEHNqNlSZ4RfkocigcCk7l1g7hjC0eziQH3t26LMzw52gkCHpqnmQRSthbR9E7+uHYe8ZDhAr01lGQ0RERF9RJGpGNPFUz05wno+Re9r5SUi+ZgEElQzmo33o+utBWE9MWyafoQ2BJIIgIO7sfADA0O7jsHYOVwm5NgOKWp4esvN5QS4g4ZI5iDp5OPYkT9Ig8bK5TMbxkxkX0KytrYVGo0F0dDRKSkqgUChGNAoCAIvFgn379mHx4sWhGeQ0oZ2fhLTbT0LyD0sR843cUA8n7AhyAZo5J7I0D42c88PWbYJDbwXkAlQ5oclsjVqSClmUAvY+M/rePQaHwQqZTgHN7ISQjMeVIAhIvKIYydcuQOxZ+aEeDkUwaR5Na4seg7va0fVyJY7/YQ8gDs8LrA6TBjzhTh6nRtKV8wCZAGNlNyACsmgl5NGqUA+NiIiIwozUhBQYnleTJqYpSkDydaUQNApY6gecfQSUM3j+TIk6L3Y42UUEBj4eztK0NOphOz4EQSmDriy0U98JMgHx581Cyo8WIu3mxZDpgttcdzqbtgHNzs7OMY/t378f7777Ls4880zIZDLExcXh9NNPx9///nfo9V9lyG3YsAEGgwGXXnppMIc8LcnUcmhmxfMOhAfOgObhkQFNizR/Zk4MBGVoyrsFpdzZfVq6u6UtTYagCI/Dhkwlh2ZuIr9bNCVSRoB+YzN63zo6fHPBJkKRpkP8ie6S5B11YRzi1hY4f2a5OREREbmjyolB9NezoStLdVZd0cTUebFIuaEUsiglcGLGMqkpzkwXd1Y+IADGii5YWgwjrl9lmtB3ERcEAer8OAYz/Sz0/7MBctlll0Gr1WLVqlVITU1FVVUV/vznP0On0+Hhhx92Lvfggw9i1apVWL16NW644QY0Nzfj8ccfx5lnnomzzz47hO+AZgJpHk1r6yDsAxbIY4ezmcy1oZs/01XUygwMbGwGTkw+rVvExk40vahyvpquQJkVDe38JGgXJEGRpmOp+SREr8qEtdmAob0dUOczu5WIiIjciz+3YOKFaAxVZjRSblyIrr9UwD5ggTJE1XzhRpkeBd2iFAzt60Tfe8dgbR4uyY9akRHikVEgTduA5gUXXIBXX30VTzzxBAYGBpCSkoKLLroI999/P4qKipzLLVmyBJ9++inuvvturFu3DjExMbjuuuuwfv36EI6eZgp5tArK7GhYmw0wHelxdv0LZUMgV/JoFaJOSsXgjnbI41RQMUBB04xmfhJSfrQQ8jg152/yA0EQkHDpHEQtSw/ZdBlERERE05kyVYe0ny6BtdPI6ZFcxJ6Rh6EDXbDUDQAAFKk6Niae5gRRFMe2VyafDQwMIC4uDv39/ex4Tj7p/6QB+s8aoS1NRtJV82DrNaH9kV2ADMi8f1VIO4oDgL3fjN5/H4XupDToFoa+IRARERERERHRaL1v12Bw+3DT57hvFSLma1khHhFNhrfxtfCYDI9oBpPKzk1HeyHaHc7sTGVWTMiDmcBws4/ka0sYzCQiIiIiIqKwFfuNXAhqOQS1POTNgCjwpm3JOVGkUGXHQKZTwDFkg6VB70yRVxcw05eIiIiIiIjIG/JYFdJuWwKIIuRRbMAz3TFDkyjEBJnwVbfzIz1hM38mERERERERUSRRJGqgSNKGehgUBAxoEoUBTXEiAGBobydsXUZAANR5zNAkIiIiIiIiIhqNAU2iMKCenQAIww14AECZHgWZjinyRERERERERESjMaBJFAbkUUqocmKcP7PcnIiIiIiIiIjIPQY0icKENI8mAKgY0CQiIiIiIiIicosBTaIwIc2jCbDDORERERERERGRJ4pQD4CIhimzohFzWg5kGgXk0apQD4eIiIiIiIiIKCwxoEkUJgRBQNxZ+aEeBhERERERERFRWGPJOREREREREREREUUMZmj6iSiKAICBgYEQj4SIiIiIiIiIiCjySHE1Kc7mCQOafqLX6wEAOTk5IR4JERERERERERFR5NLr9YiLi/P4vCBOFPIkrzgcDrS2tiImJgaCIIR6OCEzMDCAnJwcNDU1ITaWnbqJwhn3V6LIwH2VKHJwfyWKHNxficKTKIrQ6/XIzMyETOZ5pkxmaPqJTCZDdnZ2qIcRNmJjY/lLgShCcH8ligzcV4kiB/dXosjB/ZUo/IyXmSlhUyAiIiIiIiIiIiKKGAxoEhERERERERERUcRgQJP8Sq1W4/7774darQ71UIhoAtxfiSID91WiyMH9lShycH8limxsCkREREREREREREQRgxmaREREREREREREFDEY0CQiIiIiIiIiIqKIwYAmERERERERERERRQwGNImIiIiIiIiIiChiMKBJREREREREREREEYMBTSIiIiIiIiIiIooYDGgSERERERERERFRxGBAk4iIiIiIiIiIiCIGA5pEREREREREREQUMRjQJCIiIiIiIiIioojBgCYRERERERERERFFDAY0iYiIiIiIiIiIKGIoQj2A6cLhcKC1tRUxMTEQBCHUwyEiIiIiIiIiIooooihCr9cjMzMTMpnnPEwGNP2ktbUVOTk5oR4GERERERERERFRRGtqakJ2drbH5xnQ9JOYmBgAwx94bGxsiEdDREREREREREQUWQYGBpCTk+OMs3nCgKafSGXmsbGxDGgSERERERERERFN0kTTObIpEBEREQWd0WiEyWQK9TCIiIiIiCgCMUOTiIiIgspms+Hpp58GAFx33XVITEwM8YiIiIiIiCiSMEOTiIiIgspgMGBwcBCDg4N47bXXYDQaQz0kIiIiIiKKIMzQJCIiAIBer0dzczPmzp0LmYz3uyhwLBaL899dXV3417/+hauuugpyuTyEoyIiIiIi8i+73Q6r1RrqYYQVpVLpl/N+BjSJiAgA8OGHH6KyshJXXnkl5syZE+rh0DRmNpsBAGq1Gg6HA7W1tfjggw+wdu3aCSf/JiIiIiIKd6Ioor29HX19faEeSliKj49Henr6lM79GdAkIiIAQH9/PwBgYGAgxCOh6U7K0IyPj8eaNWvw+uuvo7y8HCkpKVixYkWIR0dERERENDVSMDM1NRU6nY437U8QRRFDQ0Po6OgAAGRkZEx6WwxoEhERgK+y5qS/iQLFNUNz3rx5OOOMM/DJJ5/gww8/RHJyMmbNmhXiERIRERERTY7dbncGM5OSkkI9nLCj1WoBAB0dHUhNTZ10+TknSSMi8lJ/fz/sdrvP6+n1+hFzBroj/dILJQY0KVik75hKpQIArFq1CosWLYIoiti2bVsoh0ZERERENCXSnJk6nS7EIwlf0mczlflFGdAkIvJCa2srnnzySbz77rs+rTc4OIinnnoKr7zyyrjLvffee/j973+P5ubmqQxzShjQpGCRAvxqtRoAIAgC5s2bBwDseE5ERERE0wLLzD3zx2fDgCYRkReOHz8OAM65PrzV29sLm83mXH+i7Xd2dk5ugFMkiqIzyMSAJgXa6AxN4KvgJr9/REREREQ0EQY0iYi8YDKZAPgebJHWs1qtsNlsHpeTstKk5YPNarVCFEUADChR4LnOoSlhQJOIiIiIiLzFgCYRkRekgKOvwRbX5ccLVk42YOovrq/LgBIF2uiSc9d/8/tHREREREQTYUCTiMgLk82gdA3OeJob0OFwTDpg6i+urztRAyOiqXJXcq7RaAAMf/8cDkdIxkVERERERJGBAU0iIi9IgUy73T5u6fho3gQ0wyE7MhzGQDPHeCXnAIPqREREREQ0PgY0iYi84BqM9CXg503JuevjDGjSTOCu5FyhUEAulwMI3VyyRERERESBIDVhDcUfqVfCRN577z3Ex8fDbrcDAPbt2wdBEHDPPfc4l7n++utx1VVXISUlBW+++abz8cWLFyMjI8P58+bNm6FWqzE0NOSnT3AsRcC2TEQ0jYwOaEZFRXm1nmtgxlOGpuvjoQrkuGbEMaBJgeau5ByA86SH30EiIiIimk6sViseeuihkLz2fffdN+a8251TTz0Ver0ee/fuxdKlS/Hll18iOTkZGzdudC7z5Zdf4u6774bJZMLGjRtxySWXoLe3F9XV1dBqtTh06BCKi4vx5ZdfYtmyZdDpdAF7X8zQJCLywmSzKL0pOZ9s9qc/jc7Q9PYuHtFkuCs5d/2ZAU0iIiIiouCKi4vD4sWLnQHMjRs3Yt26ddi7dy8MBgNaWlpQU1OD1atXY82aNc7l/ve//6GsrGzEYxs3bsTq1asDOl5maBIReWEmlZwDwxmbo4NNRP7iruTc9WcGNImIiIhoOlEqlbjvvvtC9treWr16NTZu3Ig77rgDmzZtwvr16/HGG29g8+bN6OnpQWZmJmbPng2j0YjbbrsNnZ2d+PLLL7FmzRqkp6dj48aNuO6667B161bcddddAXxX0zhDc+PGjRAEwe2f7du3j1h269at+NrXvgadTof09HTceuutMBgMIRo5EYUbURRHBB19KQuPxAzNUI6DZobxSs5dnyciIiIimg4EQYBKpQrJH0EQvB7nmjVrsHnzZuzfvx9KpRLFxcXOzMsvv/zSmXVZWlqKxMREfPnll86A5po1a/Dll19i165dsFqtWLVqVaA+TgAzIEPz1ltvxbJly0Y8VlRU5Pz3vn378M1vfhPz5s3DE088gebmZjz22GM4evQoPvjgg2APl4jCkMVigcPhcP7s7wzNcAxosss0BYrD4WCGJhERERFRGJLm0XzyySedwcs1a9bg4YcfRm9vL+644w4AwwHaU089Fe+88w4qKyudSYJmsxnPP/88li5d6nXficma9gHNU089FZdcconH5++77z4kJCRg48aNiI2NBQDk5+fjhz/8IT7++GOceeaZwRoqEYWp0ZmVvgRbvGkKNLrk3OFwQCYLbgI9MzQpWKxWq/PfzNAkIpq5rFYrtmzZglmzZiEnJyfUwyEiIgAJCQlYuHAhXn31VTz99NMAgK9//ev4zne+A6vVOmJezDVr1uCOO+7A0qVLER0d7Vz21Vdfxc9+9rOAj3Xalpy70uv1sNlsYx4fGBjAJ598gquvvtoZzASA733ve4iOjsYbb7wRzGESUZganVkZyKZAQGiyIxnQpGCRvluCIIyZz4cBTSKimePLL7/Exo0b8cknn4R6KERE5GL16tWw2+1Ys2YNACAxMRHz589Heno65s6d63E5YDjIOfqxQJn2Ac1rr70WsbGx0Gg0OO2001BeXu58rqKiAjabDUuXLh2xjkqlwuLFi7F3716P2zWbzRgYGBjxh4imp6lkaPpacu7r9v1ldBCVASUKFNdy89Hz+TCgSUQ0M/T19WHbtm0AhpNPiIgofPz+97+HKIooLi52PrZv3z60tbWNWG7x4sUQRREPP/yw87Gf/vSnEEURZ511VsDHOW0DmiqVChdffDGeeuopvPPOO3jggQdQUVGBU0891RmolP4zMjIyxqyfkZGB1tZWj9tfv3494uLinH9YJkE0fY0OOHrbFMh1rkB32/G0vVAEc5ihScHiqSEQwIAmEdFM8dlnn8FutwMABgcHQzwaIiKKRNN2Ds1Vq1aN6Kh03nnn4ZJLLsHChQtx77334sMPP3QGF0Y3JQAAjUbjMfgAAPfeey9uv/12588DAwMMahJNU5MNOI7OevS25DyUAU2lUgmr1cqAEgWM9N3y9LvXdRkiIpp+mpubUVFR4fzZYrHAZrNBoZi2l6ZERBQA0zZD052ioiKcf/75+OKLL2C326HVagG4v3AymUzO591Rq9WIjY0d8YeIpqfJBhxHB0LtdvuIhiielvM2A9SfpPcUExMDgF3OKXA8dTh3fYwBTSKi6UkURXz00UcAhksVpSaIzNIkIiJfzaiAJgDk5OTAYrFgcHDQWWo+eh4A6bHMzMxgD4+IwpAU0JQ6t3kbbJGW0+l0zrkC3WVpTnb7/iS9pnRzhgElChSWnBMRzVxVVVVoamqCUqnEN77xDeh0OgDA0NBQiEdGRESRZsYFNGtra6HRaBAdHY2SkhIoFIoRjYKA4eyRffv2YfHixaEZJBGFFSljMj4+HoDvAU21Wu0spR0d0HQ4HM7lfN2+PzGgScEyXsk5A5pERNOX1Wp1djQ/5ZRTEBsb6wxoMkOTiKYjh8MR6iGELX98NtN2opLOzk6kpKSMeGz//v149913cc4550AmkyEuLg6nn346/v73v+OXv/yls9Ryw4YNMBgMuPTSS0MxdCIKM1IQMj4+Hs3NzV6XhEtBGY1GA0EQYDQaxy0vj4uLQ3Nzc9CDOQ6Hw1kKP5mApsPhQE9PD5KSksZ0rSYazZuS81BMuyDp7Owcc2Gt0WiQlpbG7zfNWH19fdDpdG4zq4m8tXPnTvT19SEmJsbZ6yAqKgpAaDM0u7u7x3RaV6vVSE9P53GfiCZFpVJBJpOhtbUVKSkpUKlUPJ6cIIoiLBYLOjs7IZPJpnRuMW0Dmpdddhm0Wi1WrVqF1NRUVFVV4c9//jN0Ot2IlvIPPvggVq1ahdWrV+OGG25Ac3MzHn/8cZx55pk4++yzQ/gOiChcSMGVuLg4AJPL0JTmiBqdoSn9rFKpnFkKwQ5ous6XKd3Y8WUM27ZtwyeffILzzjsPS5Ys8fv4aHoJ55LzxsZG/PWvf3X73CWXXIKSkpIgj4go9Lq7u/H0009j1qxZuPrqq0M9HIpQdrsdmzZtAgB885vfdP4OCHWGZnt7O5577jm3z/G8hogmSyaToaCgAG1tbWhtbQ31cMKSTqdDbm6u8zp5MqZtQPOCCy7Aq6++iieeeAIDAwNISUnBRRddhPvvvx9FRUXO5ZYsWYJPP/0Ud999N9atW4eYmBhcd911WL9+fQhHT0ThxDVDExgOtoiiOOFdNikQqlarIZfLRzw2etsajSZkwRzp9eRy+aSCqtI8xO7mIyYazZuSc4vFAofDMaUTnMmQvsNqtdoZ3B8cHITRaERbWxsDmjQjHT9+HKIo8hhPUzI4OAiTyQRBELBw4ULn46HO0JS+1yqVylmlMjQ0hKGhIX7niWhKVCoVcnNzYbPZYLfbQz2csCKXy6FQKKactTptA5q33norbr31Vq+W/drXvoYtW7YEeEREFKlGBzQdDgdsNhuUSuW467kGbqRlR2doSgFOrVYbsnJb13FOJqhqMBhG/E00HikjeLwMTWk5ae7ZYJG+wwsXLsTatWsBAJs2bcJnn33G7zfNWNJ3f3BwEHa73XmDjsgX0vcoOjp6xM2qUGdoSuOaN28eLrzwQgDAjh078MEHH/C4T0RTJggClErlhNeNNDkzrikQEZGvRpecA94F/FwDhVqtFoDnknPXgGaoMjRVKtWIDDlvSfNOjZ5/isid8TI0FQqF80I3FGXnrhfcEunfvLClmcr12M7GLTRZ0vfI9fgKfJWhGeqAJo/7RESRhwFNIqJxOBwOt0FHb7IoXZsCSZlm45WcS8uEKqDJDE0KhvECmoIghHQeTemCWyo3d/03A/Y0U7ke23mcp8mSvjuux1cg9CXnPO4TEUUuBjSJiMbhGlTxNYvSmwxNdyXnkRTQtFgszmUNBgNEUQzMIGnaGK/kHAhtYyBm6lAwtba24qOPPgr6NCO+YkCT/MHd8RUIn5JzT8d9ntcQEYUvBjSJiMYhXWgqFAooFAqfgi2uTYGk7EtPJefh0BRIrVY7g0xWq9WryatdL25tNlvYX5hT6I2Xoen6eLgFNIeGhjihO/nVl19+iW3btqGqqirUQxmXa5YaM9ZosiYqOQ9VhuZ4x32bzRaS30VEROQdBjSJiMbhWm4O+BZscZehOTrgFw5NgaSMOdcMTdfHxzM6W4fZOzQR1++bO6EKaDocDmeGkGvpoU6nc87rye83+VOkzD/MDE3yB08l51KGpslkCslNI3cl565ziof7/klENJMxoElENA5/BzTDuSmQWq2GQqFwdrD1ZhwMaJKvXJtQuROquWQHBwchiiIEQXBmDAGATCZz/szvN/mTFEAPVWaaN1wD/QD3AZo8TyXnWq0WgiAACP6+YDabYbVa3Y6L040QEYU/BjSJiMYhZUtKQRZPzX3ccQ0UetMUSApoelvu7S+jS4B9CayOzlxgJgONRxTFsC05ly5aXTMyJbywpUCQgjfh3DlcCvRLeIynyfJUci6TyZw3fYO9L0jHdKVSOeZ3Eo/7REThjwFNIqJx+CNDU6PRjMjQdL04dFdyDnhX7u0vozPmpHGw5Jz8zWazOb//4RbQdFd2KGHHW/I3i8XizAwL5wxNHuPJH0RR9FhyDoRuHk0e94mIIhsDmkRE45hKQNO1KZC0vsPhGBEodN2+1HjI2+37y1QyNHmxS75w/U4plUq3y4Q6Q3N09pDrY/x+k7+4Bm7COUNz9HeewR2aDNf5MV2n9JCEqtM5j/tERJGNAU0ionGMLjn3Nthit9ths9mc6yiVSmcZq2vZuWvJuev2g9kYyB8l58nJySN+JnLHNRt4dFm3JFTNsXhhS8HkGrgJ5wzN0cd4g8EwosqAyBvS90ij0bi9mRWqDE0e94mIIhsDmkRE45hshqbr82q1GoIgjGkMZLfbnSWHk8kA9ZfRAU2p9NyXDM2MjIwRPxO5M1GHc9fnWHJO09noDM1wDRJKx/T09HQAw7+3gn2zgSLfeOXmQOgyNHncJyKKbAxoEhGNw1NTIG8Dmq5dw6V1pYCma8dzXzNA/Wl0kGkyJefSxS4DmjSeiTqcAyw5p5nBNXDjcDiC/n33lvSdj4+Pd/6eYoCHfDXe8RVghiYREU0OA5pEROPwlKE5UYaKa0MgibQNaV1p22q12ll+623A1J8mW3LucDicF+VShiYvdGk8E3U4d32OAU2azkZnooXrPJquGWzcD2iyPHU4l3AOTSIimgwGNImIxjHZknPXhkCS0SXnrh3OJaEsOR/d5XyiMUhlkoIgIC0tDcDwe5LK6IlGk7KBwzFD05vSQ84fSP4yOhMtXAOargEf1/2AyBcTlZyHc5dzo9HonBOdiIjCCwOaRETjmGxTIHeZaNI2RmdoumZxhlNTINdu7O5IFyhRUVHQ6XTO0vpwvTCn0AvXDE1RFMfN1JEutu12+4ipIogma/RxMlwbA7nuF9K+wUx88lUkZmhqtVpn9QyD+ERE4YkBTSKicUy1KVC4Z2jabDbY7fYRr+3tGFwvUARB4MUuTShcA5pms9mZgePuwlapVDpvPPDClvwhEjI0RVFkyTn5hbdzaAZzP7Db7c790N24XM9r+J0nIgpPDGgSEXng2qhBCjq6znE5XumpNwHN0cFS1+WDFcwZ3Y3dlzGMLiHjiT9NxNeSc4fDEZRxSd9ZtVrtcWwstyV/kgI30u+UcMzQHB3o5z5Ak+Vtl3Oj0Ri04760DwqC4Hz90fidJyIKbwxoEhF54Fr2PbrkXBTFcUuy3TUF8qbkPNhNgaT3oFQqnaVVUkDH24CmFMhkQJMm4kuGJoCgzcc6UTmk63PMQCZ/kAKYKSkpAMIzQ1M6lqtUKqhUKu4DNGnelpwDwQvuu45JOv8Zjd95IqLwxoAmEZEHUsBRpVI554dUKpUQBAHA+AG/SGkK5C7ANJmSc+CrTAae+JMnUgB9vICma3A9WPvBROWQrs8xYE/+IAUwpYBmOGZojm6Ywn2AJsNqtTqP5Z6OsXK5POjZyjzuExFFPgY0iYg8cFcSLgiCVwG/qZacB6sp0FQCmiw5J19J36nxSs693cf8aaJySNfn+P2mqbLZbM7gfiRkaI6+acV9gHwhfV8UCsWIipTRgj2PJo/7RESRb1oGNHft2oVbbrkFCxYsQFRUFHJzc/Gd73wHR44cGbHcNddcA0EQxvwpLi4O0ciJKJyM7nAumWxA05cu58HO0HQNMPna5Zwl5+Qtb0rOXZ8P1n7AknMKJilgI5PJkJiYCCA8MzQ9HeNNJlPQpoOgyDe6gaAnUkAzFCXnnvC4T0QU3hShHkAgPPLII9iyZQsuvfRSLFy4EO3t7Xj66aexZMkSbN++HSUlJc5l1Wo1/vKXv4xYPy4uLthDJqIw5C6DEhgOQPb39085Q5Ml5zTTeFNy7vo8S85pOpICNjqdLiTdnb01uuRco9FALpfDbrfDYDAgISEhlMOjCOHN8RX4ah7NYGdo8rhPRBS5pmVA8/bbb8drr702IuPosssuQ2lpKR5++GH8/e9/dz6uUChw9dVXh2KYRBTmJsrQHK8sfKKmQA6HIyyaAo0X0LTb7bDZbFAoxv6qEEWRJefkM29KzoHQBTRZekjBIAVsXAOaQ0NDEEVx3Ay2YBsd8BEEATExMejr62NAk7zmzfEVCH6GJo/7RESRb1qWnK9atWrMxdLs2bOxYMECVFdXj1nebrdjYGAgWMMjogjhKUPTm2DLeE2BpA7p482hGcqApuvx09M4zGYzbDYbgLHliIODg3A4HAEZL0U2X0vOgzWXLEsPKZikgE1UVJQzK811Xs1w4S6DjfsB+cqb4ysQ/AxNX477BoOB5zVERGFoWgY03RFFEcePH0dycvKIx4eGhhAbG4u4uDgkJibi5ptv5l04IgIwtYCmu8CNUql0ZjsajcZxS85tNpszYBhI7kqAZTIZlEolAM/vUboQUKvVzmWlE3+HwxGW88FR6Enft3DN0PTmwtZsNnP+QJoS1wxNlUrl/L0QbsfN0SXnADPxyXfelpyHKkNzvHFJY3KtqiEiovAxYwKar776KlpaWnDZZZc5H8vIyMBdd92Fl156Cf/4xz9w3nnn4ZlnnsHZZ589YSDBbDZjYGBgxB8iml783RTIdVt6vd55nHHXFGii7fuLp3FO9B7dlWrJ5XJnhgUvdsmdcGwKZLPZnBeq45UeajQaZ+CJ32+aCtcMTUEQgp6Z5i13AR+W4JKvvC05D+Z+4G7aHHcUCgXPa4iIwti0nENztEOHDuHmm2/GySefjO9///vOx9evXz9iucsvvxxz5szBz3/+c7z55pu4/PLLPW5z/fr1+M1vfhOwMRNR6I3XFAiYXEBTq9XCYDCgt7fX+Zi77Eir1Qqz2ezMDgiU8QKaBoNhwoDm6MyG6OhoDA0N8cSfxrDZbLDb7QDCK6ApfVdlMtmYfd2VIAiIjo5GX18f9Ho95w+kSXPN0ASGA5sDAwNhlaHpGuhnyTlNhbcl58HM0DQajc7fRxOdZ0nnNXq9HmlpaQEfGxEReW/aZ2i2t7dj7dq1iIuLw5tvvgm5XD7u8uvWrYNMJsOnn3467nL33nsv+vv7nX+ampr8OWwiCgMTlZx7mt/PNXAzOrtT2pYU0NRqtZDJRh6Kg9kYyFOTFuk9eprTzdMFCjudkyeu36VwKjl3Dc5P1JCF5bbkD64ZmkDw5w70hmugXxofwH2AfBeOXc6lMWk0Gue0OZ7wO09EFL6mdYZmf38/zjnnHPT19WHTpk3IzMyccB2tVoukpCT09PSMu5xarZ4ww4SIIttkS85dA52jAzfStqSA5uhtS9vX6/URV3IO8MSfPJO+SwqFYsKbi6EIaE5UDum6DL/fNBXuMjSB8JpD01Ogn/sA+cLhcDi/7750OXc4HGNu9voTj/tERNPDtM3QNJlM+Pa3v40jR47gvffew/z5871aT6/Xo6urCykpKQEeIRGFu8k2BXLNehx9Qu4uQ3O0YAZzphrQdFdy7vo8kcTb+TNdlwnGPuBtOaTrMsxApqmIpAxNT8d47gPkjcHBQYiiCAAjMn3dkZ4XRdFjBYy/8LhPRDQ9TMuApt1ux2WXXYZt27bhX//6F04++eQxy5hMJre/mH77299CFEWcffbZwRgqEYUxKaDpa4bmeIEbaVtSFrinDE3Ac0m7P3kaq5RZOlGXc5ack7e87XAOBHfaBW/LIV2XYcCepiISMjTddTgHvtoHBgcH4XA4gj4uiizSsTIqKmrCzHyFQuE8Fwl0cJ/HfSKi6WFalpzfcccdePfdd/Htb38bPT09+Pvf/z7i+auvvhrt7e0oKyvDFVdcgeLiYgDARx99hPfffx9nn302zj///FAMnYjChN1uh9VqBeB7U6DxAprStqQT41BnaEpBJpacU6CFa4YmSw8pmOx2u/NmVSRmaEpjFkURQ0NDXgWEaOby5fgKDO8LZrM54MF9HveJiKaHaRnQ3LdvHwDgv//9L/773/+Oef7qq69GfHw8vvWtb+GTTz7B3/72N9jtdhQVFeGhhx7CnXfeGdB5W4go/EnZmYDnDE1PGZTeBDQ9/ey6HkvOaToJ14AmSw8pmKRAjSAIzuO/FCSMhICmXC5HVFQUBgcHodfrGdCkcflyfAWG94Xe3t6A7ws87hMRTQ/TMqC5cePGCZeJj4/Hhg0bAj8YIopIUrBSrVaPucHhbVMgd+Xkox8bb5lAB3NEUZywy7m7MdhsNmfAlyXn5C1fSs5D1eV8IgzY01RJgRqtVuv83SJlaEZCyTkwvB8MDg5yP6AJ+XJ8BYK3L/C4T0Q0PTANkYjIDU8NgYCvgi0Wi8XtHGKRkqFptVqdk/V7ytCUglCupJN6uVw+ZvzSib/Vag1KMIoix2QzNKXvaKBMpvSQ8wfSZI1uCOT670jI0ARYgkve87XkPFj7wmSO+xaLhec1RERhhgFNIiI3vAloAu4Dfv4KaAa6KZDribkvGZquF7qCIIxZT6lUjliOCJhchqYois65bAPB4XD4lKnj2oU3nIJPFDlGNwRy/bfVag3o990X4+0XLMElb/lach6sDE1fxqVSqXheQ0QUphjQJCJyY7yycaVS6ezW6S7g502Xc08/u64X6EwA13G6C0x6GsNEFwIsOyd3fMnQVCqVzu9kIPcDo9HozLR0zZjzRJo/EOCFLU2OuwxNjUbjLD8Ph0C5a6DfU8k5wH2AJuZryXkwMjRdK0i8GZcgCPzOExGFKQY0iYjcGC9DExg/4BcpJefjjVPKohsvQ9NTqRZP/MkdXwKagiAEJVNZ+o7qdDooFN5NK85yW5oKdxmagiCE1TyaEwX6uQ+QtyZbch7I/UAak0KhcHtT2R1+54mIwhMDmkREbngb0HQXbPGlKZC77QerKZBUAuwuwORtybk7DGiSO76UnAPBCez7Wg7puiwzkGky3GVouv4cDhma0rFbq9W6DfRzHyBviKI46ZLzQO4HrmMaXZ3iCb/zREThiQFNIiI3xgtKApPP0FQoFM65mDxtPxwyNFlyTv7mS4am63KB3A98LYd0XZYBe5oMdxmarj+HQ4bmeB3OAe4D5B2z2QybzQbA95LzYGRo8rhPRBT5GNAkInIjUCXno7cZDk2B3GXMuXY5H91lmiXnNBnhHND0thzSdVl+v2kyIilDc6KbVgaDYczvByKJ9D1Sq9VeZ+a7ZmgG6rvF4z4R0fTBgCYRkRtSQNNThuZ4ZeETBW6kdQVBGDeYaDabA3qx6E2Gprsu0yw5p8lgyTmR5wzNYGSmecvbY7xrcxWi0SZzfJX2A4fDEbDvFo/7RETTBwOaRERuSNmRgczQ1Gq1budvktZzOBzOcq1AGG+c43WZZsk5TUY4Z2iy9JCCxVOGZjDmDvTWRCXnKpXKeWOC+wF5Mpnjq1KpdE7LE6h9gcd9IqLpgwFNIiI3AtUUyHWbnrbtmsEWyGDOeAEm1+xR1zE4HA7nRQZLzskXvgY0g9Eci6WHFEwOh8MZ0IzkDE2A+wFNbDLHVyDw0y/wuE9ENH0woElE5MZEJeeessdEUfS65NzTtmUyWVCy08brcu76uOsYjEYjHA4HgLEZRhLpInhoaAh2u91v46XINh1Lzjl/IPlC+r0CeG4KFA4Zmt4ENFmCSxOZzPEVCHyDrKkc9wcHB3leQ0QURhShHgBRJLFYLGhsbJzwZEYQBGRnZ4+5YJlpjh8/jr6+vgmXi46ORlZWVuAH5IPJlpxbrVZnkMObknNP1Go1zGZzQBsDTRR4dfcepQtdnU4HuVzudj2dTgeZTObM5oyNjfVpTI2Njc6gaSBkZGT4NKZwYTAYYLVakZCQ4NN6RqMRBoMBKSkpARrZxBwOh3Mu1kCUnHd3d0Or1fp8zJ1K6aHNZoPZbPZ4Y8KfbDYbGhoavJqCIisry+cAQiCJooj29nakpKRAoZjZp51SsFKj0Yw5foZjhuZ4GWzSd6y+vn7CmxTp6emIi4vz+Lwv51ZZWVkeb6aFC5PJhIGBAaSmpgbl9RwOBxoaGpw3jcaTmprq8++QyZrM8RX4al+oq6sbMS1PfHw80tLSQjIunU4HQRAgiqLP5zXeam1tnfQNgkg9rwkkURTR1NQ04kYSMHz8zc3NdTvlk6Srqws6nW7GX8cRRYKZfWZJ5KMPPvgAe/fu9WrZrKws/PCHPwzwiMJXR0cHnnvuOa8zmL7//e+joKAgwKPyjslkcgYOPAUdPZXDuv7s6SLP24Cmu+3702QCmlKAerwLXZlMhqioKOj1evT19fl0kv3f//4XBw8e9Hr5yYiNjcVtt93mMSAbjux2O/7yl79gaGgIt9xyi0+f6RtvvIH6+npcd911yM7ODuAoPfNmvxjN231AOtakpaXhhhtuGPcixdXQ0JAzAOBL6aFKpXLecOjr60N6errX607WZ599hm3btnm1bFJSEm655RavP4dA27dvH9555x2sWLEC55xzTqiHE1Ke5s8EwidD0263Y2BgAIB3Jee7d+/G7t27x91mVFQU1q1b5zGg/eGHH2LPnj1ejS8jIwM33nijV8uGyltvvYWjR4/i2muvRV5eXsBfb9euXfjggw+8Wlaj0WDdunVe31iaCm/OF9yR9o8dO3Zgx44dzscFQcBNN900pZtzFotlwmlz3JHJZIiOjp7UeY03Ghsb8de//nXS60fieU2gVVdX44033nD73IUXXohFixa5fa69vR1//vOfkZmZieuvvz6QQyQiP2BAk8hLFovFGWhJT0+HTOZ5xoa2tja0tLSgs7MzpFlRoVRRUQFRFBEVFTVuZobBYMDAwAD2798fNgHNI0eOABgODPhacu4aJPQUUCgpKUFLSwuWLVvmcQzBDGh6CjBJY3DN+jh8+DAATBgYy8nJQVVVFQ4fPozc3FyvxmMymVBdXQ1g+KI1EAGZjo4ODAwMoL6+HrNmzfL79gOlrq7OeXFYVVWFlStXerVeb28v6urqAAD79+8PWUBT+g7JZDKvs/S83QcOHDgAh8OBtrY2HD9+3OsAo/RdTklJ8fniPicnBzU1NTh8+HDAA5p2ux379+8HMJxdNd7nd/z4cXR3d6OlpSVk/9ejSTcB9+/fjzPOOGNGZ2lKgRR3AU3pMbPZDJvNFrLPqa6uDlarFTqdbtxMvrKyMhw/fnzC/bOzsxODg4M4duwY5s6dO+Z5q9Xq9blVe3s72tra0NHREbTsR18NDAzg6NGjAIaD+cEIaErHh6SkpHGPZd3d3TCZTDhy5AhKS0sDOqbBwUE0NTUBmPh8YbSlS5eit7fXmdUPAP39/RgcHERFRQW+8Y1vTHpcR48ehSiKiI+P9zlzdDLnNd6S/g9jYmJ8DgBL5zUNDQ0oLCz067gi2b59+wAMZ/ZKN4yMRiN6e3uxf/9+jwFN6Zyiubk5rI81RDRs5p5VEvmopqYGVqsVcXFxuPHGG8cNtrz66qs4evQoKisrsWbNmuANMkyIoui8QDnnnHNQUlLicdn6+nq8/PLLOHToUEgv4lxJY1+wYIHHZTw1BZqoIRAAJCYm4oorrhh3DMFoiOJrhqbdbncGHMf7bKTnq6qqUFlZidNPP92r4OThw4dht9uRnJzsU6adL/773/9i9+7dqKysjKiAZmVlpfPfBw8e9Dqg6bpeVVUVzj777JBkcHgT6B/Nm4CmKIpjPhtvA4zSeuMdnzxZsGABampqUFlZidWrV/u8vi8aGhowNDQErVaLG2+8cdz/v7feegsVFRU4ePBgWAQ0BwYG0NjYCGD42FhbW4s5c+aEeFSh46khEDB8zJdKWoeGhkJWPirtF/Pnzx/3u5aWlobvf//7E27vgw8+wI4dO1BZWek2oFlTUwOLxYLY2FjccMMN4wY0X3vtNRw5cgSVlZVhG2Soqqpy/ru6uhpr164N6HlNT08PWltbIQgCfvCDH4xbjv/ZZ59h06ZNOHjwYMADmtXV1RBFERkZGUhKSvJp3ezsbFx77bUjHquoqMBbb72FgwcP4rTTTpv0+YH0/V6wYIHP25jMeY03XM+tLrjgAp/PTaTzmoMHDzKgeYLRaERNTQ0A4Morr3QeL3p6evCHP/wBdXV1GBwcHLO/jD6nCOdjDRENY1MgIi/5chIkBXtcfynOJG1tbejt7YVCocDs2bPHXTY3NxfR0dHOi91QMxqNOHbsGADvAprjZWhORTiWnNfW1sJoNCIqKmrCrJPZs2dDqVSir68Pra2tXo1nKhca3pL+T6urqyNmYn+bzea82AGA5uZmr+amBUYegwYHB9HQ0ODv4XnF14ZAgHf7gHSskVRWVno1zcXQ0JDzeDNRcN6d4uJiyGQydHR0oLOz0+f1fSH9H86bN2/CYLT0XqqqqgI6D623XIM7wMz9nSgZL0NTJpMFvBnKRFyPNZPZL9yRtnPo0KERGXcS1+P+eMFM1215u5+Hgut3PBjnNdLrFRQUTDi3qPT51dTUBHR+btdx+et7NGfOHCgUCvT09KC9vX1S27BYLM4KnMmMazLnNd6or6/H0NAQdDod8vPzfV4/Es9rAu3w4cNwOBxISUkZEZBMTExERkYGRFEccV4laW5uRn9/v/PncD7WENEwBjSJvODrSdDcuXMhl8vR2dmJjo6OQA8v7EgnsnPmzJkwsCeTyTB//vwR64WSlCWYkpIy7uTzMyGgKQWfpOW8zdyR1pWycbyZE9P1brq/LoDcycvLQ1RUFIxGY1gE0L1RV1cHk8mEqKgo5OTkABgbKHKnp6cHbW1tEATB+X8Rqn1sMvuFpyxoV9L7KSoqgkKhQG9vL9ra2ibc9qFDh+BwOJCWlobk5GSvxyTRarXOLJpAfqZ2u935f+3NfjFr1iyo1WoMDAygubk5YOPylmswFoAzE3+mGi9D0/XxUM2jWVtbC5PJhOjoaL+VSmdnZyM2NhYWi8V5jJdYLBbn1A++nFt1dXWF5blVf3+/s8y6uLgYQOCPub4EDtPS0pCUlAS73e783APBYDCgvr7e63F5Q61WO2+QT/YzPXLkCGw2GxISEpCRkeHz+iqVyplh7s//V19uWrmTl5cHnU4Ho9HonGJmphtvv5Aec3du6nr9Es7HGiL6CgOaRF44cuSIs7twZmbmhMsH62I3HLmWa3h7IiuVfHrK4Agmb8c+UVMgfwU0A5lFIWXNeZOhabPZcOjQIQDe/7/6kk3j6W66v8nl8rAKoHtDOumeP3++s0zQm7G7Zu4sX74cQOgyOKYS0PQU1Hc91pSVlfl0oemP7KFgZOLX1dXBaDR6nbmjVCpDHryWuAZ3zj77bMTExMBsNjsz4Gei8TI0XR8PVUDT9abVRNmS3pLJZB73FdepfLKysibclkajcQa1At08bjKkmw+5ubk4+eSTAQQ2iN/d3Y329nYIguC8aTAeQRCc51uBPD5I5eaZmZl+7ag+1Qxdf1SB+DtL2LXcfDLTnwCReV4TSENDQ+NWWkmPNTQ0jOgq73A4nJ/fkiVLUFRUBICfKVG4Y0CTyAuTOQmKhNKoQGhtbUVfXx+USuWE5eaS7OzssLjY9bbcHPgq2GK1WkcEiCIlQ9PhcPgU0HTN3PF2MvyioiKoVCqvssX8XZ42HtcSyHDPFnMNJJeUlGDevHkQBAEtLS0jSq3dcf1M8/PzodPpMDQ05MycCaaplpy7O4a2tLSMONZ4e8wdHBycUrm5xDUT//jx45Peznh8yYqWuH4OoSw7l8ael5eHuLg4XnDjq0DlRBmaoSg5n8xNK29J2zt8+PCIm5au81VPh3Mr13l5c3JyAn5eI71eYWGhx+/UaK5l50ajMaDj8vf3SCo79zYT35XZbHY2a5ps4BD4quy8v7/fL1nwvkzlMx7XsvNwP68JNKkCIzU11W1j1oSEBGRlZY0pO29uboZer4darUZRUVFYH2uI6CsMaBJNwPUkyJeTs3AvjQoU13INb4MX42VwBNNEJ0GuXIOArkFHKaMy3AOarp3LJ+pybjabJ5W542222ER30/0t3OZtHc+xY8dgNpsRHR3tvECWLnrGKzvv6upCe3s7ZDKZs4xNyuAJxT42lQxNURTHnXtv7ty5UKlUXs9vJmUPpaen+9yswlWgM/EnO5+hVHZuMBicGZKhMDqoMdFcijOBFKgMxwxN6VgTExPjnNrCX7KyshAXFwer1eo8n3KdyseXAJM/5lIMhL6+PmeAa968eUGZTmcygUPp/MbhcASk7Fyv1/u93FwylZLvw4cPw2azISkpadzphCbi7yx4f2VF5+XlOc9rZnrZuTcN/9xdc0g3WIqLi6FQKJzXcd3d3QG7aUlEU8eAJtEEpDl3EhMTve6eC4R/aVQguJaA+noH3FMGRzB5091cIpfLnZ1LXYOO0r/H63LujUB3OZe2K5PJPHZglQJKQ0NDk87c8SZbzHU+w4kCyf4QbvO2jsddw4zx5n8avZ5r5k4oGwdMJqCpUqmcWVuj9wPX0jDpfble7Hrz2UwlS0fiWr7p7wwO17lTfcncUSgUzuB1qH739Pb2oqWlZUQp7HhzKc4U4ZyhGYhyc4kgCGMCCJOdz9AfcykGgjSW/Px8xMTEAAhsEF/KDJduWvnCm98hkyXdaMvOzkZ8fLzftz/ZY64/mw5KY5hq8zV/ZkW7ntfMlGsOd1wrMKTPwx3puYaGBgwMDMDhcIyZr9r1WDOTP1OicMeAJoYvlO6++25kZmZCq9VixYoV+OSTT0I9LAoTkymJksy0cgWpO6BKpXLOPeOt7OxsxMXFhexidzJdj91lUUZKybnrOD19r6UxNDc3Tzpzp6ioCGq1Gnq93mO2WDDLzSWRkC1mtVrdXuzMnz8fgiCgra0NPT09btd195nm5+eHrCHSZErOBUHwuB+0tLRgYGBgzLFmootd12YV413seEtqHBCIDA7XuVN9DTCFutu5dGGYl5fnDO6ESyZ+qDgcjrDN0PR0rPEnabtHjhyBxWKZUoApHM+t3B1zAxnEl15v1qxZ0Gq1Pq0rjbG2ttbvwfNA/z4vKipyZuK3tLR4tY7JZPJr08FZs2Z5PZ3OeCYzlc94Imk6nUA5dOiQswJjvIZ/8fHxyM7OBjB8k7exsREGgwFqtRqFhYXO5QJ505KI/IMBTQDXXHMNnnjiCVx11VV46qmnIJfLce6552Lz5s2hHhqF2FRPgsK1NCpQXEtAlUqlT+sKghDSrDnXMlRvux67y6KMlKZA3ozTteQXGJkl6C2FQjFut1d/OTM84QABAABJREFUzWfoq2DMbzZVx44dg8ViQWxsrPPEGxgOehQUFABw/5l2dnaio6MDMpnM+dkDoc1Mnex+4Smg6elYM9G8ra7NKhITE30aizuumfj+/EynmrlTUFAAjUaDwcFBNDQ0+G1c3vIU1AiHTPxQMZlMzmNpuGVo1tTUuD3W+JPUIMZqteLgwYOTmspHMmfOHCiVyknNpRgIPT09aG1tHdOcJ5BB/KkEDlNSUpCWlgaHw+E8zvjDwMAAGhsbAfjnhpE7KpXK55Lvw4cPw263Izk52S9NB5VKpV+62Ps7KzoSzmsCzZf9wjVT2bXTvGvV0uzZsyc9bysRBceMD2ju3LkT//znP7F+/Xo8+uijuOGGG/D5558jLy8Pd911V6iHRyHmehI0mTl3wrU0KhDclYD6SroTevjw4RFzPAbDZMY+XTI0PRmdTTfZ/9fxssVc76ZPZT5DX0VCtth4GXrjjX28zJ1QZXD4M6A53rFmovnNApE9FIhsMde5UyeTueNadh7s77en4A7gfi7FmUIKUqrVao/TfIQqQ9Pd1Bb+5lp2/sknn0xqKh+Jt9NLBIuUkZyfn4/o6OgRz7kG8f11XtPR0YHOzk7I5XLn8c5Xgfj9J30OOTk5iIuL89t2R/O18Zk/y80nO4bRXLOi/TH9CRBZ0+kEgsFgcM4f6ktAs6mpCRUVFW7XU6vVk563lYiCY8YHNN98803I5XLccMMNzsc0Gg2uu+46bNu2LaQT6lPo+eMkKBxLowLBtTug1CjDV5mZmYiPjw/6xe7g4KBPJ0ESd1mUkdYUyJsMTQCIi4ubdOZOYWEhNBoNDAaDM3tD4su8pf4WztliVqvV2bDB3cWO1O28vb0dXV1dI54bL2gXqoZIkyk5B9zvB01NTSM6kY7m6UIzUM0qXDPx/ZXB4Y8Ak+uNhGDOmSqNvaCgYExwx91cijPFRPNnuj4XzAxNi8XiPNYE+jgsbV/qrl1SUjItzq2k32PujtWuQXx/lZ1Ppdxc4lp27q8AerCmj3HNxJ+o7NxoNPq13Fzi2nxt9HmNN1ybcPkzKzoSptMJFF8rMGJjY503DE0mEzQazYhyc0k4HWuIaCz3t4hnkL1792LOnDmIjY0d8fjy5csBAPv27fN7t8dI1NTUFJKum6HkcDj8chIkXez29vZi165dY75r08WBAwcATK7cXCJd7G7ZsgXl5eWQy+X+HKJHDQ0NEEURGRkZPpWhSsGWxsZGZ6BGr9cD8G9TIH+WhEmkMlRvA5rSvI2TIZWd79u3D9u3b3cGfW02W8C6oXojKysLsbGxGBgYwJYtWyaVKRQo7e3tsFqtiIuLQ1ZW1pjndTodCgsLcezYMWzZssWZpTM4OOjM3HEtN5dIGRw7d+7Ezp07gza/Ym9vL4DJZ2jW19c7v3/SsUbqRDqadKGp1+uxc+dOZ2MK6aZFVlaWX5tVSJn41dXV2LZt25S/y6Io+mU+w4KCAmi1WgwNDWH79u1By4CW/n88jX3BggXYunUrjhw5gurqar9lTIU7KfDiaf5M1+eMRmPQPpu2trZxjzX+lJ6ejsTEROfcv1P5fktzKfb392Pnzp0BzQgcj8lkQnt7OwRBcHvMlc5rtm7divLycr9kwHrKJvNFUlIS0tPT0d7ejs2bN/vUeMwdi8XiTAIJVLm5RMrEr6iowPbt28e9PmlqaoLD4UBqaqpfys0l0nnN/v37sWPHDp+nB9q1axcA/2dFS/O2DgwMYOvWrVPq6B5p9u7dC8C3/WLBggXOgPS8efPcXnfMnj3bOW/rdL6Oo8gUExMT8N/d4W7GBzTb2trcdleUHmttbXW7ntlsHpExMjAwEJgBhon//e9/M648TJKSkjKlkyCpNKqqqgrvv/++H0cWnqZ6MS8FNOvq6pwBiGDxdexS0LG8vBzl5eVun5ss1/kr//nPf05pW968zkTP+eP/dd++fTh06NCYAK2vgWR/kcrOt23bho0bNwb99b0xXnb4ggULcOzYMezdu9d5Ii8pKiry+B1csGABdu7ciZqamqA34PI1oCm9hx07dmDHjh0jnvP0nZQudg8cOIAPP/xwzPOBCJ4vWLAA1dXVqKiocAYbpmqqmTtyuRzz5s3Dnj17gt7o0FNwB/hqLsXe3l68/vrrQR1XOBgvoKnVaiEIAkRRDPpn489yXE+k4N6mTZumPJ+hNJfiwYMH8cEHH/hxlJNTWFjo8f9WCmjW1tb6LTN+KuXmruNqb2/Htm3bsG3bNr+MKzc3NygBnwULFqCiogKVlZVeZXsH6ri/f/9+VFdXo7q6etLb8CfppuX27dvxxRdf+HXbkcKXgPq8efOcxw9Ppf/SdVxlZeWMuI6jyFJSUoJLLrkk1MMIqRkf0DQajW4vsKSLKKksZrT169fjN7/5TUDHFk6Sk5M9fhbTmVwux9e+9rUpb+frX/86TCZT0OeFDLaUlBSfu5uPlpGRgZNPPjno0z1ERUVhyZIlPq2zdOlS9Pf3jynrSU5OnnK2n0qlwpo1awIacFIoFM5sdE/Pn3nmmTCZTFO++zdr1iwsWbIEHR0dIx6Xy+VYvXr1lLY9FStXrkRnZ2fAmi9NhUajwYoVKzw+X1JSgtraWvT19Y14XKlUjvuZ5uTkYPny5R5v2AVKXFycs5mRt5YvXw6DwTBmvs+UlJRxp7Y49dRTYTAYxhxzo6OjUVZW5tMYvFFcXIxFixahu7vbL9uTyWRYsWLFlDN3TjnlFPT39wds6gpP5s+f7zG4IwgCzjrrLGzdujUkHdhDSS6XY+XKleM+/81vfjMgWfnjmehY408rV65Eb28vysrKphxAPfXUUzE0NBTycyuFQoHTTjvN4/OZmZl+Pa8RBAGlpaVTvnF60kknobm52W8VWBN9Dv40e/ZslJWVobOzc8JldTodli5d6vcxeDqv8VZWVlZAmnCdfPLJ6OrqCsvzmkArKipCQkKC18vHxsbirLPOQn9//7jnJ1//+tdhNBpDfqwhGi2Y/QfClSDO8MkgSkpKkJaWhs8++2zE41VVVViwYAGee+453HjjjWPWc5ehmZOTg/7+fqaiExERERERERER+WhgYABxcXETxtdmfIZmRkaG2wmlpYn9MzMz3a6nVqun3PSDiIiIiIiIiIiIfDPjA5qLFy/GF198gYGBgRGRX2mursWLF3u1HSnRdbrPpUlERERERERERBQIUlxtooLyGV9yvmPHDqxcuRKPPvoo7rzzTgDD5eQlJSVISkrC9u3bvdpOc3Mzu6ETERERERERERFNUVNT07jzDc/4DM0VK1bg0ksvxb333ouOjg4UFRXhb3/7G+rr6/Hiiy96vZ3MzEw0NTUhJiYm4F0iw5k0l2hTUxPnEiUKc9xfiSID91WiyMH9lShycH8lCk+iKEKv13ucAlIy4wOaAPDKK6/gl7/8JTZs2IDe3l4sXLgQ7733Hr7+9a97vQ2ZTBaQTnWRKjY2lr8UiCIE91eiyMB9lShycH8lihzcX4nCT1xc3ITLMKAJQKPR4NFHH8Wjjz4a6qEQERERERERERHROGShHgARERERERERERGRtxjQJL9Sq9W4//77oVarQz0UIpoA91eiyMB9lShycH8lihzcX4ki24zvck5ERERERERERESRgxmaREREREREREREFDEY0CQiIiIiIiIiIqKIwYAmERERERERERERRQwGNImIiIiIiIiIiChiMKBJREREREREREREEYMBTSIiIiIiIiIiIooYDGgSERERERERERFRxGBAk4iIiIiIiIiIiCIGA5pEREREREREREQUMXwOaBoMBtx///04++yzkZiYCEEQ8PLLL7tdtrq6GmeffTaio6ORmJiI7373u+js7ByxzKFDh3DXXXdh8eLFiImJQUZGBtauXYvy8nK322xpacF3vvMdxMfHIzY2Fueffz5qa2vdLvviiy9i3rx50Gg0mD17Nv74xz9OeZtEREREREREREQUOoIoiqIvK9TX16OgoAC5ubkoLCzExo0b8dJLL+Gaa64ZsVxzczPKysoQFxeHW2+9FQaDAY899hhyc3Oxc+dOqFQqAMCdd96JF198ERdffDGWL1+O/v5+PP/886ivr8eHH36I008/3blNg8GAJUuWoL+/H3fccQeUSiWefPJJiKKIffv2ISkpybns888/jx/96Ee4+OKLcdZZZ2HTpk3YsGEDHn74Ydx9992T2iYRERERERERERGFls8BTbPZjN7eXqSnp6O8vBzLli1zG9C86aab8PLLL+PQoUPIzc0FAHz66ac444wz8Pzzz+OGG24AAOzevRtz585FdHS0c93u7m7MmzcPc+bMwebNm52P/+53v8Pdd9+NnTt3YtmyZQCGMzxLSkpw11134aGHHgIAGI1G5OTkYOXKlXjvvfec61999dV4++230dTUhISEBJ+2SURERERERERERKHnc0DT1XgBzbS0NKxevRpvvPHGiMfnzp2LnJwcfPrpp+Nu++KLL8bGjRvR3d3tfGz58uUAgJ07d45Y9qyzzsKxY8dQU1MDAHj//fexdu1a/N///R/OPfdc53Lbtm3DqlWrsGHDBlx99dU+bXMiDocDra2tiImJgSAIXq1DREREREREREREw0RRhF6vR2ZmJmQyzzNlKgLx4i0tLejo6MDSpUvHPLd8+XK8//77E26jvb0dycnJzp8dDgcOHDiAH/zgB263+fHHH0Ov1yMmJgZ79+4FgDGvf9JJJ0Emk2Hv3r24+uqrfdrmaGazGWazecR7nj9//oTvi4iIiIiIiIiIiDxrampCdna2x+cDEtBsa2sDAGRkZIx5LiMjAz09PTCbzVCr1W7X37RpE7Zt24Zf/OIXzsekdTxtEwBaW1sxd+5ctLW1QS6XIzU1dcRyKpUKSUlJaG1t9Xmbo61fvx6/+c1vxjze1NSE2NhYt++LiIiIiIiIiIiI3BsYGEBOTo7b5EJXAQloGo1GAHAbsNRoNM5l3D3f0dGBK6+8EgUFBbjrrrt83qb0t9R0yN2yrst5u83R7r33Xtx+++3On6UPPDY2lgFNIiIiIiIiIiKiSZpoOseABDS1Wi0AjCjJlphMphHLuBocHMS3vvUt6PV6bN68eUSjIF+2qdVqYbFY3I7NZDKNWG4y4wSGg6CeMkxnCpO5HTJBAZUqeeKFiYiIiIiIiIiI/CAgAU2pXFsqPXfV1taGxMTEMcFAi8WCiy66CAcOHMBHH32EkpKSEc9L63jaJgBkZmY6X99ut6Ojo2NE2bnFYkF3d7dzOV+2SYDV2ofe3u3o6d2Cnp6tMBrrIZdHY+nSNxEdNTvUwyMiIiIiIiIiohkgIAHNrKwspKSkoLy8fMxzO3fuxOLFi0c85nA48L3vfQ+fffYZ3njjDaxevXrMejKZDKWlpW63uWPHDhQWFjrr66Xtl5eXj+hyXl5eDofD4Xzel23OdPsP3ICurs8BiCMet9sNqKi4BcuW/hsKRVRoBkdERERERERERDNGQAKaAHDxxRfjb3/7G5qampCTkwMA+Oyzz3DkyBGsW7duxLI/+clP8Prrr+P555/HRRdd5HGbl1xyCe655x6Ul5c7O5gfPnwYn3/+Oe68807nct/4xjeQmJiIZ599dkRA89lnn4VOp8PatWt93uZMp1DEAhARFTUbCQknIzFhFaKiirB7z5UYGqrB4cO/xPz5j084xwERERERERER0XRht9thtVpDPYyIoVQqIZfLp7wdQRRFceLFRnr66afR19eH1tZWPPvss7joootQVlYGYDg4GRcXh6amJpSVlSE+Ph633XYbDAYDHn30UWRnZ2PXrl3OkvPf//73WLduHU4++WTcdNNNY17rwgsvRFTUcOafXq9HWVkZ9Ho97rzzTiiVSjzxxBOw2+3Yt28fUlJSnOs988wzuPnmm3HJJZfgrLPOwqZNm/DKK6/gwQcfxH333edczpdtjmdgYABxcXHo7++flk2BjMYmyGRqqNUjO8f39u3C3r1XQRTtmDv3t8jOujJEIyQiIiIiIiIiCg5RFNHe3o6+vr5QDyXixMfHIz093W1SnLfxtUkFNPPz89HQ0OD2ubq6OuTn5wMAKisrcfvtt2Pz5s1QqVRYu3YtHn/8caSlpTmXv+aaa/C3v/3N42u5bg8AmpubsW7dOnz88cdwOBxYs2YNnnzySRQVFY1Z94UXXsDjjz+Ouro65OTk4JZbbsFtt9025gPzZZueTPeA5ngaGv6MmmOPQBBUWHrSG4iNLQ3ZWHp6tqKu7g8QBDkSE09BQsIqxMSUQCYLWDIyEREREREREc0wbW1t6OvrQ2pqKnQ6HStWvSCKIoaGhtDR0YH4+HhnDx5XAQ1o0lgzOaApiiIOVPwIXV2fQqPJwfJl70CpjAvqGGw2PY7WPIzW1n+OeU4uj0ZiwskoLLwd0dFzgjouIiIiIiIiIppe7HY7jhw5gtTUVCQlJYV6OBGnu7sbHR0dmDNnzpjyc2/ja7JAD5KmP0EQMH/e76DRZMNkakJV9V0IZpy8q+sLbN9xtjOYmZV1FebM+TVSUs6EQhELu92Azq5PsHvPZejrG9sAioiIiIiIiIjIW9KcmTqdLsQjiUzS5zaVuUdZh0t+oVTGobTkaZTv/g66uj5FY9NfkJf7Q6/Xt1i6oDccgsnYBKOxCUZTEyyWLiQmfg052de47aA+NNSA2toncLzjPQCAVpuLecUPIyFhBQAgJ/u7EEU79PpKHDn6APr7d2Pvvu+htORPSE4+zT9vnIiIiIiIiIhmJJaZT44/PjeWnPvJTC45d9Xc8hoOH/4lBEGOJWWvIT5+6bjLm82dqG94Bi0t/4Aouo/MK5WJyM+/CdlZV0ImU8NsPo66+qfR2voGRNEGQEBuzg9QWLgOcrnW7TbsdiMqDv4E3d1fQBDkmFf8CDIyLpzq2yUiIiIiIiKiGcZkMqGurg4FBQXQaDShHk7EGe/z8za+xgxN8quszCvQ17cLx4+/i4MHb8Xy5e9CpUoes5zV2o+GxhfQ1PQyHA4jAECnK4BWmw+tNhtaTS5kMhUam16E0diIo0cfQFPjX5GYdCra29+Gw2EGACQlfh2Fs+5AbEzJuOOSy7VYWPosqg/dg/b2t1FVfSes1l7k5v7A4zqi6EBf306o1enQavN454WIiIiIiIiIKAwwoEl+JQgCiuc+AL2+CkNDNThYuQ5li1+GIAxP8mo0NqO19XU0t2yAzaYHAMTGLsaswjuQmLhqzPYyMy9DW9ubqKt/GiZzK1pbXwcAxMWdhFmFdyIhYbnXY5PJlJg/71EolQloanoJR2sehNXag8LCO8YEKx0OK6qr70H78bcBABpNFhISViExYRUSEldB7SZIS0REREREREREgceScz9hyflIhsGj2LXrQjgcRuTn/RjRMfPR2vI6enq3ABj+ykVFzcGswjuQnPzNCbMf7XYTWlpeRW/fTmRlXo6kpDWTzpgURRENDc/iWO3jAIDMzMtRPPf/OYOuw+Xpt6C7e+OJx2SjyuEFJCZ+DZmZlyEl+ZuQyVQeX8dq7R6eE9TYBKutH+lp50Op5PeDiIiIiIiIKFKx5Hxq/FFyzoCmnzCgOVZ7+zuorLp9zOOJCacgM+sKpKac6QwihkJLyz9w6PCvADiQknI2ShY8AbvdiP0Hfoj+/j2QyTQoLXkaCQkr0Ne3Cz29W9Hbsw16Q6VzG0plIjIyLkJ83FKYTC0nGho1w2hshMnUDLt9aMRrpqdfgAXzHw/yOyUiIiIiIiIif5lJAU2LxQKVyn0i12RxDk0Ka+np56Ovfw9aWv4OlSoVmRmXIDPzO9Bqc0I9NABAVtYVUCoTcLByHTo7P8S+fX2wWHswOHgECkUsFi18wdnUKClpNZKSVgMAjMZGtLa+gda2t2CxdKCx8S9oxF88vIoAtToNGk0m+vv34Pjx/6Kw4Kdh8xkQERERERER0dSJoujsERJMMpnWpwrWNWvWoKRkuA/Jhg0boFQq8eMf/xj/7//9PwiCgPz8fFx33XU4evQo3n77bVx00UV4+eWXsXnzZtx7770oLy9HcnIyLrzwQqxfvx5RUVEAgGeeeQZPPvkkmpqaEBcXh1NPPRVvvvlmQN4zwAxNv2GGpnuiKGJwqAY6bQFksvCMn/f0bMWBih/Bbh8EAKhUqShb/DKio+eOu57DYUN39xdobXsTZnMbNJpsaLU50GpyhxsbaXOh0WRCJlMDAPbuuwY9PZuQlXUliuf+NuDvi4iIiIiIiIj8z12God0+hI1flgZ9LGtWV0Au13m//Jo12L17N6677jr8+Mc/Rnl5OW644Qb8/ve/xw9/+EPk5+ejt7cXv/rVr3DBBRc411u0aBEeeOABrF27Fp2dnbjllluwaNEivPTSSygvL8fKlSuxYcMGrFq1Cj09Pdi0aRNuvfVWt2NgyXkYYUAzsg0MVOBAxY+gUMRg0cIXApJB2du7E3v2XgFBUOGUVV9CrU71+2sQERERERERUWBFekCzo6MDlZWVzszOe+65B++++y6qqqqQn5+PsrIy/Oc//3Guc/3110Mul+P55593PrZ582asXr0ag4ODeP/993HttdeiubkZMTExE46BJedEfhIbW4pVJ38JQZBBEGQBeY34+GWIizsJ/f270dj0ImYX3RuQ1yEiIiIiIiKi4JLJtFizuiIkr+urlStXjihTP/nkk/H444/DbrcDAJYuXTpi+f379+PAgQN49dVXnY8Nl9g7UFdXhzPOOAN5eXkoLCzE2WefjbPPPhsXXnghdDrvA62+YkCT6IRAl8QLgoD8vB9j/4Hr0dLyGvLzfgylMj6gr0lEREREREREgScIgk+ZkuFMmhdTYjAYcOONN7otIc/NzYVKpcKePXuwceNGfPzxx/jVr36FX//619i1axfi4+MDMsbApKIRkVtJSWsQHT0PdvsQmppfCfVwiIiIiIiIiGiG2bFjx4ift2/fjtmzZ0Mul7tdfsmSJaiqqkJRUdGYP1IHdIVCgdNPPx2/+93vcODAAdTX1+Pzzz8P2HtgQJMoiKQsTQBoanoZNpshxCMiIiIiIiIiopmksbERt99+Ow4fPox//OMf+OMf/4jbbrvN4/J33303tm7diltuuQX79u3D0aNH8c477+CWW24BALz33nv4wx/+gH379qGhoQGvvPIKHA4H5s4dv9nyVLDknCjIUlPPhrY2H0ZjPVpa/4m83OtDPSQiIiIiIiIimiG+973vwWg0Yvny5ZDL5bjttttwww03eFx+4cKF+PLLL/Hzn/8cp556KkRRxKxZs3DZZZcBAOLj4/Hvf/8bv/71r2EymTB79mz84x//wIIFCwL2Htjl3E/Y5Zx80dr6L1QfugcqVSpWnbwRcrk61EMiIiIiIiIiIi+M16U73K1ZswaLFy/G73//+5CNwR9dzllyThQC6ennQ61Oh8XSgc7OD0M9HCIiIiIiIiKiiMGAJlEIyGQqZGZcCgBoa/9PiEdDRERERERERBQ5OIcmUYikp5+Puvo/oqdnC8zmDqjVqaEeEhERERERERFNYxs3bgz1EPyCGZpEIaLTFSA2tgyAA8eP/zfUwyEiIiIiIiIiiggMaBKFUEb6BQCAtva3QzoOIiIiIiIiIvKNw+EI9RAikj8+N5acE4VQWtpaHDn6AAyGKhgMhxEdPTfUQyIiIiIiIiKicahUKshkMrS2tiIlJQUqlQqCIIR6WGFPFEVYLBZ0dnZCJpNBpVJNelsMaBKFkFKZgKSk1ejq+hTt7W+jqOjuUA+JiIgoYoiiHXa7CQpFVKiHQkRERDOITCZDQUEB2tra0NraGurhRBydTofc3FzIZJMvHGdAkyjEMtIvHA5oHn8Xs2bdCUGQh3pIREREYc9mG8Tefd+FwXAY8+c/hrTUc0I9JCIiIppBVCoVcnNzYbPZYLfbQz2ciCGXy6FQKKac0cqAJlGIJSefBoUiFmZzO3p7tyMx8ZRQD4mIiCisiaIdlZU/xcDAfgDAwYM/gW3ub5GVdUWIR0ZEREQziSAIUCqVUCqVoR7KjMOAJlGIyWRqpKaei9bWf6K9/W0GNMOY3W6E0dgIo7EJRlMTjMYm2G0GFBb+FBpNZqiHR0Q0Y9TUPIKu7s8hk6mRlLQGnZ0f4dDhX8Bi7UF+3k1TvuNvNDajt3cr+gf2ISZ6PjIzL4VMpp709gyGw2hu+Tsy0i9EXNySKY2NiIiIiBjQJAoLGekXorX1n+jo/Ahz7f8Pcrk21EOiUXp6tqDi4M2w2fRjnjOamrGk7O8QhMnP/0FERN5pafkHGpteBADMn/coUlPPRW3tE6hveAa1tU/Aau3F7KL7fDomOxw2dPd8ia6uz9HbuxVGY+OI5xsankdBwW1IT78AMpn3p88OhxUNDc+hrv5PEEUr2tvfxdKT/oXo6Dlul9frK6HXV0KjyYJWmwO1OgMyGTM+iIiIiEYTRFEUQz2I6WBgYABxcXHo7+9HbGxsqIdDEUYURWzddhpMpiYsmP8k0tPPC/WQyMXg4DGU774YNpseCkUstNpcaLW50Ggy0dz8KhwOI4qLH0JW5mVeba+/fx9qjv0OsbGlyMy4DFFRhQF+B0RE00NPzxbs238tRNGOwoJ1KCi4xflcY9NLOHr0AQBAcvLpmF10H3S6vHG3ZzQ2oqX1DbS1vQWLpcP5uCDIERu7CLExC9HR8QHMluMAAJ2uEIWF65Cacs6EWaAD+oOorr4HBkM1gOFGgFZrLzSabCxb+hZUquQRy7e2voHqQz8H4BgxDrU6E9lZVyA39wZ2TyUiIqJpz9v4GgOafsKAJk3VsdonUV//NJISv47Fi18K9XDoBIulB+XlF8NoakRc3ElYUrZhRNlhY+OLOFrzEBSKWKxc8THU6pRxtzegP4i9e68ekekZH7cMmZmXITX1HMjlmoC9FyKiSNbXV479B66HzaZHevoFmD/vsTEBvrb2t1FdfTdE0QZBUCAz41LkF9wCjTodwPANRKOxHj2929DR8QF6e7c611UqE5GW9i0kJZ6K+PhlUChiAAB2uwnNLX9HQ8NzsFp7AQApyWdg/vxHncu4stvNqKv/Ixob/wxRtEOpTMCcOfcjKfFr2FV+MYzGBsTFlqGs7FXI5WqIooiGxj/j2LHfAQBiYkphtxthMjXB4TA7t1tY8FMUFPzEvx8qERERUZhhQDPIGNCkqRoaqsO27acDAObPfxwZ6Re4Xa6+4Xm0tb2JefMeRnzcSUEc4czjcJixZ+/30N9fDo0m50RGTdKoZWwo330x9PqDSE09F6Ulf/S4PYPhCPbsvRJWay9iY8ugUiagq3sjpGwchSIOebnXIyfnGsjlugC+MyKiyGEwHMax2ifQ1fUpACAubimWlL3icU5Lvb4Kx2ofQ3f3lwCG56rOzLwMdtsgenq3wmxuc1laQGLi15CZeRlSkr8JmUzlcRw2mx6NjX9FfcNzEEULdLoClJY+i+io2c5l+vv3oKr6HgwNHQMApKauxdw5v3JmYw4O1p7I+B9AWtq3sWD+E6ipedhZQp+X9yPMKrwTgiBAFB2wWDrR1vYfHKt9FAAwu+g+5OZeN7kPkoiIiCgCMKAZZAxokj/UHHsUDQ3PQRBUWFK2AfHxS0c8X9/wvDODQ6vNxYrlHzCjL0BEUURV9Z1ob38bcnk0li59c8RFqyu9vhK7yi+EKNqxaOELSE7+xphlhobqsXvPFbBYOhATU4olZRugUMTAZGpDW9tbaG17AyZTCwBApUpGft5NyMq6fEpNKIiIItnQUD1q657C8eP/BSACkCEj42LMLroHSmX8hOv39u3CsWOPob+/fMTjgqBCXFwZEhNPQXra+dBqs30aV//AflRU3ASzuR1yuQ7z5j2C5KTTcKz2CTQ1vQRAhEqVgrlzf4PUlLPGrN/Tuw379l0DUbQhKmoOBgePABg/WFlX9zRq654EABTPfYDd3ImIiGjaYkAzyBjQJH8QRQcqDt6Czs6PoFQmYtnSt6DV5gIAmpo34MiRXwMA5HId7PYh5OX9CEWzfhbCEU9f9fXP4Fjt4xAEORYt+iuSEr827vJHax5GY+MLUKszsHLFh1Aoop3PmUyt2L37MpjMrYiKmoOTlrwGpTJhxPqiaMfx4/+H2ronnc0oNOpM5OffhLS086BQRPn/TRIRhRmHw4ru7o1oaX39RIblcAZ7auq5KCxY5/Ocw6Iooqfnf2hr+zc0mkwkJKxCfPzSKTffs1i6cPDgbejt2w5g+EaUxdIFAMhIvwizZ/983KDr8HyZ9wIYnidzXvHDyMi4aNz3cezYo2hofB6AgPnzH/NYyUFEREQUyRjQDDIGNMlf7HYjdu+5HHr9Qeh0s7D0pDfR2fUxqqvvBgDk59+C2JgFOFDxYwiCHMuWvYuY6OIQj3p6GRyswfYd5wBwYO7c3yI768oJ17Hbjdix41wYTY1IS/s2YmJKYDI2w2hqxMBABazWHuh0BViy5J9Qj2oE4crhsKK17V+or3va2YRCLo9GWtq3kJV5GWJiStkUgoimHaOxGS2t/0Rb25uwWDqdjyclrcGswtsRE7MghKNzz+Gw4VjtY2hsfAEAoFano7j4QSQnrfFq/fr6Z9Da9i/Mnv0LpCR/c8LlRVHEkSO/QXPLBq9vthERUXizWvug11eNfFAQEBtT4naeZqKZgAHNIGNAk/zJbD6OXeUXwWxuR3TUXBgGjwJwICfnB5hddB8EQcCBipvQ2fkRYmMWYunSNyEI8lAPe9qoOHgrOjr+D8nJp2PRwue9Xq+7ZzP27fu+2+c0mhyctOQ1aDSZXm3LbjehpeU1NLe8CqOx3vl4dPQ8ZGZehvS086FU8lhDRJHNZG5Hff2f0Nr6BkTRBmC4OU9GxsXIyrwMOl1BiEc4sa6uL2AwVCM7+7sBv/gURQeqqn6G9uNvIy5uCZae9K+Avh4REQVOV9cXqKy6HTbbwJjnlMoklJY8jYSE5SEYGVFoMaAZZAxokr/p9VXYvecy2O1DAIDMzMtRPPcBZ3ae2Xwc27afCbvdgNmzf4HcnGtDOdxpw2A4jB071wIQsXzZe4iJmefT+nV1f0RX95fQaDKh1eZAq8mBVpuDuLiySTX6EUURfX070Nr6Bjo6P4DDYQEw3OQiNfUcZGZejvi4pcza9ILF0oP+/nLIZGrExS1lGT9RCFksPWhofB7NzRucnbwTElYhK+vKCZvzzHRmcye2bD0VomjFsmXvIDamJNRDIiIiH4iiA3X1f0Jd3VMARKjV6VAovoohWK29sFg6IQhyFBXdi5zsa3iuTzMKA5pBxoAmBUJX1+eorLoTqalno3jub8dkYTa3vIbDh38JuVyHFcs/hFabFaKRTh8HKm5GZ+eHSE05B6WlT4d6OCNYrX1ob38bLa2vO5tIAIBOV4TSkj8gOnpuCEcXOA6HGUMn5hWVCBCg1eaM2zTJbjeht287enu2oqd3GwyGr8p5BEGB2NhFSExYhYTEUxgUJgoSURTR3LIBx449DrvdAACIizsJswrvZBaKDw5W/hTHj/8XGRmXYP68R0I9HCIi8pLVOoCqqjvQ1f05ACAr62rMmf3zETfy7HYjDh36OdqPvwMASEv9FubNWz+p5AiiSMSAZpAxoEmBIop2j+XkoujA7j1XoL+/HElJa7Bo4V8YlJkCvb4KO3d9G4CAFcvfR3T0nFAPyS1RFDEwsB+tra/jeMd7sNuHEB01F8uWvQOZTBnq4QEAenq2YmBgH+LilyEudtGks62GhhqwZ+9VMJvbxjynUMQjI/0CZGZ+Z0QwV6+vRmvr62g//jZsNv2IdaKiZsNuN8FkahrxeG7OdZg9+75JjXG6GhqqQ0fHB0hKWoOYmPmhHg5NA3b7EKoP/RzHj78LAIiOno9Zs+5AUuJq/u7yUX//HpTvvhQymQpfO2XrmEZzREQUfvT6SlQcvAVGYyNkMhXmzv0tMjMucbusKIpobn4FR2segijaEBU1B6Ulf0RUVFGQR00UfAxoBhkDmhQqg4M12LHz2xBFCxYt/AuSk08L9ZAi1v4DN6Kr61OkpX0bJQt+H+rheMVi6cL2HefAau3BrMI7kZ//41APCa2t/0L1ofsgdSeWybRIiF+GhMRViI1ZBK02G2p12oTzvppMrdi953KYTC2QybQjuhI7HBZndhcAxMaWITlpNTq7PoNeX+F8XK1OR1Li15GQcDISElc5GzIZjY3o6dmKnt4t6Oh4H4Igx8oVn0Cny/PjJxG5TOZ2lJdfDLO5HQAQE1OKrMzLkJb2LU5QT5MyNFSPioqbYBg8PFxCN+se5ORcA0GQhXpoEUkURewqPx96fSVmzboL+Xk3hnpIRETkgcNhRl39n9DQ8DxE0QaNJgulpc94NWVIX185Kg7eAoulEzKZCgX5tyI394eQyRRBGDlRaDCgGWQMaFIoHa15GI2NLyAqag5WLH+PDYImYWCgArvKLwAgw8oVHyIqalaoh+S1tva3UVV1B2QyFVYsfz+kTTQaGp5HzbHfAQBiYxfBaGyC1dozZjlBUEGjyYROm4u0tG8jPf38Ed9bs7kTu/dcDqOx3m13eFG0o7tnE1pb30BX12fOZiLD21YiJeUMZGZehsSEVRMGTPbt/wG6u79ERvpFmD//0al+BBHPbh/C7j2XQ6+vhFKZBJttAKJoBTAcnM7J/i5mzfoZA1HkteGmB+tgs+mhUiWjZMEfWV7uB61tb6K6+m5o1JlYtWojf/cTEYWh/v59qD50DwYHjwIAUlPOwdy5/w8qVaLX2zCbj6P60L3o7v4SABATswDzih9xzvVvsXShp3cb+vp2Qa1OQ27OD0YkAhBFGgY0g4wBTQolq7UfW7edBputH/OKH0FmpvvSBfJs3/7r0d39BdLTL8CC+Y+Hejg+EUUR+/Zdg57ezUiIX4mysr8HvXxTFEXUHHsYjY1/AQDk5d6AWbPuAiDCMHgEvT1b0du7DYNDNTCZWkcEIIHhUvDCwnVIST4TNlsfdu+5EoODR6DRZOGkJf8ctzu82dyJ9vZ/o69/N+LjlyMj/UKoVElej31g4AB2lV8IQIaTV34cEV2VA0UUHaiouAmdXZ9AqUzEsqVvQS6PQlv7f9Da+gaGho4BABYv+iuSklaHeLQUCTo6PkTFwZsBAHGxZSgpfRoadXqIRzU92O0mbNn6NVitvVhY+hxSUs4I9ZCIiOgEs7kTjY0voLHpJQAOKJVJKJ77/5CaevaktieKItrb/4MjRx+AzdYPQVAgNfUcDBqOwDB4eMSyWm0u5hWvR0LCSj+8E6LgY0AzyBjQpFBraHwBNTUPQ61Ox8krP+VdOR/09+9D+e6LT5QdfwydLj/UQ/KZ0diI7TvOgcNhCnpQ2+Gw4dCh+9DW/hYAoKjoHuTl/nDc5c3mdhhNTejv243Gpr/CZusHAMTGLIQo2qE3VEKlSsVJS/4ZlDLw/QduQFfXZ0hPOx8LFjwR8NcLVzU1j6Ch8c8QBBWWlG1AfPxS53OiKOLwkV+hpeU1pCSfgYULnwvhSCkSWK192Lb9TFit3cjIuATFc3/L7uV+VnPsUTQ0PIeEhFVYUrYh1MMhIprRvqogeh1dXZ87b+Cnp1+AObN/4Zf5js3mThw+8it0dn484vHo6HmIj1+Kzs5PnFMGZWVdiaJZd3G6oGlGFEUc73gPiQmn+JTpG0kY0AwyBjQp1Ox2M7ZvPx0mcytmFf4M+fk/CvWQwpooitDrK9DS+jqOH38PdrsBGRmXYv68h0M9tEmTgtoKRRxWrvx4RIl2oNjtJhysvA1dXZ9CEOQoLn7I4+TmnlitA2hsfAFNzS/Dbh8CACiViViy5DVER80OxLDH0OsrsXPXeQCEE1MOzLwJ11tb30D1oXsBAAvmP4H09PPHLGMYPIodO86GIMhxyqpNUKvTgj1MiiBV1fegre1f0OmKsGL5u5DJ1KEe0rRjNLZg67Y1ABxYueKjGXnsIiIKtt6+XTh+/F2IouOrB0UHuns2jWhkGRdbhvz8m/3e40AURXR1fYK+/t2IjVmIhISVzuokm02PmppH0NL6DwCAWp2BkpKnEB93kl/HEAomUytaWl5DcsoZiItdFOrhhITJ3I7Dh3817RMxGNAMMgY0KRy0tf0HVdV3Qi6PxqqTv5i2d2ymwuGworX1DbS0/hMGQ5Xz8aioOVi8+KWILoV0OGwoL78IekMl0lK/hZKSpwL6ejabHvsP3IC+vp2QyVQoWfBHpKScPuntmS1daKh/FgP6Csydcz9iYhb4cbQTO1BxEzo7P0Jq6rkoLfnjuMuKooi+/nJotTkR/Z2RdHZ+ioqDN0MUbcjPvwWzCtd5XLZ892Xo7y9HYcE6FBTcEsRRUiTp6d2GvXuvBgCctOT1Edm+5F8HDvwInV2fICvrahTP/U2oh0NENK05HGZs2boaFkun2+cVinhkZFyIzIxLER09N8ij+0pPz1ZUH7oPJlMT1Op0rFzxMRSKqJCNZ6p6erbgYOVtsFp7AciQm/sDFBb81C9ViXa7GSZTM4zGRqhUSYiNXTj1AfuZKIpoa3sTR2sehM2mhyAoUZB/C/Lzbw76VGPBwIBmkDGgSeFAFB3Yues8GAzVyMm5FnNm/yLUQworoiiismodjh//LwBAJlMhNeUcZGZ+B/HxK6bFL4Ph5kYXAXBgXvHDyMy8NCCvYzZ3Yt/+a2EwVEMuj8aihS9EfJMPg+Ewduw8FwCwYvn7Hk9CRdGBo0cfRFPzy5DLo7FgwRNISf5mMIfqV61tb+LQofsginakpX0bC+Y/Oe6+IDWhYiMS8sRuN2HHznNhNDYgK+sqFM/9f6Ee0rTW07MVe/d9F3K5Dqes2gSlMj7UQyIimrakhmwqVSqys64a8ZxOV4Dk5NMhl4dHRYLNNogdO9fCZGpCft6PMWvWnaEeks9EUURDw/M4Vvs4AAfUqjSYLccBAFptHuYVPzypa5Ceni2oq/8TjEP1zu1J8vNvQWHBT8Pm2tBobMahQz9HT+9mAMNTdM2b9wiio+eEeGSBw4BmkDGgSeGiu3sT9u2/BoKgxMkrP4FWmxPqIYWN2tqnUFf/BwiCAkWz7kJGxsXT8sKvtu4PqKt7CoKgQNniv/l9QnCjsRF7933/xF3MZCxe9BJiYub79TVCpeLgT9DR8T5SUs7CwtJnxjzvcFhRXX0P2o+/PeLx/PybUVhwW8QF96RpCgAgI/1iFBc/BJlMMe46drsJm7esgs3Wj0UL/zLpMqqu7o2QyzScsH4aOnbsMdQ3PAu1Kg0rV37EubsCTBRF7Nh5LgYHjyAhYRUWL/orZDJlqIdFRDTtiKKInTvXwjB4GEWz7kJe3o2hHtKEOjs/wYGKH0EQVFi54sOgzE3vLzabHlXVd6Oz8yMAQEbGpZg75zfo7d2KQ4d/4ZwrNDvru5g162deZ6C2H/8vqqp+BlG0Oh+Ty6OhVqdjaKgGAJCVdRXmzrk/JOf2drsRfX270Nu7DT29W6HXVwIQIZOpUVi4DjnZ1054vh7pGNAMMgY0KZzs3ft99PRuRmLiqVhY+iwbBAFob38XlVXDZbTzitcjM/M7IR5R4IiiiIOVt6Gj4/+gUMRh2dK3fO7cLYoirNYeGE+UX5iMw38bTc3Q6w/CZhuARpODssV/i6gTo4kMzxF5DgAReXk/RlbmZc6bAna7ERUHb0F393BWYvHch6A3VKK5+RUAQFLi17FgwZMRESQXRRHHjv0ODY1/BgDk5l6Poln3eH0n+sjRB9DU9BKSk0/HooXP+/z6fX3l2L3nMshkKnztlO1QKuN83gaFlmHwKOrq/gjjUD3i4pYgIfFkJMSvhMnchl27zoco2lBa+gxSU84K9VBnBL2+Crv3XAa7fQiZmZejeO4DYZNZQkQ0XUiJI8MZ8VugVIb/db8oiti3/1r09GxCcvI3sWjhn0M9JK8MDtbgQMVNGBo6BkFQYe6cXyEz83Ln7zabTY+jNevR2vo6AECjycK84vVITDxl3O02NW/AkSO/ASAiNXUt8nKvh0aTDaUyAYIgoLn5VRw+cv+J58/FgvmPBW0O8MHBGtTWPYXOzk9GBFsBICHhZBTP/a3P13SRigHNIGNAk8KJXl+FXeUXQhRtiI6eh4Wlz0CrzQ31sEKmr3839uy5GqJoQW7uDzG76J5QDyng7HYT9uy9GgMDe6HV5mPZ0rcmDLR1dW9Ea8s/TwQum5wNetyJji7G4kUvQa1O9fPIQ6/60H3OkyMASEw4BRkZl6C5ZQP6+/dAJtOgtORpZ2ZiW/vbOHTo53A4TNBosrF40Yth25jDah1AX98OtLW/jc7ODwEARbPuRl7eDT5tZ3CwBtt3nAVBkGPVqv/5NI+oKNqxa9eF0BsqAQAL5j+J9PTzfHp9Ch2jsQm1dU+hvf1tAKNPIWVQKKJgs+mRknwGFi58LgQjnLk6uz7DgQM3AhAxu+g+5OZeF+ohEfmst3cnOjo/RE7296DT5Yd6OEQj7N13DXp6NiE7+/uYO+dXoR6O1wYHa7Bj51qIog2LFr2I5KQ1QXttu30IdfXPIEo3C+np53mV8djR8SGqqu+C3T4ItTodpSV/QlzcYrfL9vRsOTFXaDMAIDPjOygqundMsFkURdTV/QF19X8AAGRnfxdzZv8KgiAbs83jx/8PlVV3QBStSEw4BaWlzwZ0/lGjsRl1dU+hrf1tAMONpjTqTCQkrkJiwiokJJw8La+5xsOAZpAxoEnhprd3OyoO3gqrtRsKRSwWzH/C7x32IoHR2IRd5RfBau1BSvIZKC19xu0vrunIbOlCeflFMJlaEB+/AmWLX4ZMphqznCjaUVv3FOrr/zTmObU6HRpNNrTaHGg1OcNNcLQ5iItdPG1LGh0OGzq7PkZr6xvo6dkM16CNQhGLRQtfGNPgRK+vxoGKH8NkaoJGk41lS9+CKghd5j0RRRE2Wz+MxiYYTU3Q66vQ27sVAwMVkE6UANmJbGXfutJLdu++HH39u1BQ8FMUFvzE6/VaWv6BQ4e/mt83GA2saOpsNj1qjj2G1tbXnVkDKSlnIzXlLPT370FP7xYMDdUCGC7bWrnyo2nRMCvSNDb+FUdrHgQgYGHpc85GbaIoYmioFobBI4iPXwZ1CI9PRO7YbAbUHHsULS1/BwAolYlYvPglxMaUhHhkRMO+mmtdhlUnfx5x03odPfoQGptehE5XgBXL33d7TRAIx449jvqG4WmcdLoizCpch5SUs9xWETgcNtTWPu6sIIqPX4HSkj9MeE5tsw3iWO1jzqoptSoNObk/gFymcS7TP7AP7e3/AQAUFPwUBfm3jFvJ0N2zGRUVP4bdPoSYmAUoLXkWWm2W22WNxmYMDOw7MX+qxu0yo4miHXp9Jdra/42Wln+6nFudiYL8WxEdXTyjKy0CFtA0GAx49NFHsWPHDuzcuRO9vb146aWXcM0114xZtrq6GuvWrcPmzZuhUqmwdu1aPPHEE0hJSRmx3IMPPogdO3Zgx44d6OjowP33349f//rXbl+/paUF69atw8cffwyHw4HTTjsNTz75JAoLC8cs++KLL+Kxxx5DXV0dcnJycOutt+InPxl70eXLNj1hQJPCkcnUhoqDP8HAwF4AAgoKbj1x8J4ZAT273Yxd5edjcPAoYmIW4KQl/4Rcrgv1sILKYDiM8t3fgd1uQFLi15GX92PExy9z/oK0WvtQWbkO3T3/AwBkZV6B5JTTodXkQqPJCptJzUPFaGxCa9u/0Nb2FgRBjkULX/DYLMhi6UH57ktgNDYgLrYMZWWvevX59Q/sR0PD81AoYofvwiaumnSwYWDgAI4c+X8YHKqBzaZ3u4xOV4CEhFVITz8f8XEnTep1AKC9/R1UVt0OtToDp6z60qs77lZrP7Zt/yas1l6kpX0bx4//FwpFDE792s6gnVjT5FRV34O2tn8BABITT8WswtvHdAE1mdrQ11+O6Kg5Ie3sOpOJoojDh3+JltZ/QC7XobDwduj1lejt3eaca0ypTERJyR+QmHByiEdL04XecAg1R9dDq81BQuIqJMSvhEqV6PX63d3/w6FDP4fJ3AoAzqYfcnk0Fi58jt9VCgtVVXehrf0tpKacg9LSp0M9HJ/ZbHps2346LJYuFBXdg7zcHwb8NS2WHmzdtgZ2+yDkcp2z+ismpgQF+T+BRpvtXFZ0WFFz7BH09m4DAOTmXIdZs+7yaa7I3r5dqK6+B0ZjvYclBMyd8xtkZ1/l4fmR+gf2Y//+62G19kCpTEDJgqdGlLSLoh1Nza/g2LHH4HCYoFalIb/gFmRmXDom8WP4xmIdenu3oqd3C3p7d8Bm63c+n5hwCgpn3YG42EVev9/pLGABzfr6ehQUFCA3NxeFhYXYuHGj24Bmc3MzysrKEBcXh1tvvRUGgwGPPfYYcnNzsXPnTqhUX124CIKA9PR0LFq0CB999JHHgKbBYMCSJUvQ39+PO+64A0qlEk8++eTwvBD79iEpKcm57PPPP48f/ehHuPjii3HWWWdh06ZN2LBhAx5++GHcfffdk9rmeBjQpHDlcJhx5OgDaGl5DQCQn3cTZs26I8SjCo724/9FZeVPoVIlY9myd2ZstlB395fYf+CHEEU7AECnK0Rm5ncQE1OC6up7YTI1QSbToLj4QWSkXxDawYap4V+V4oQ3AwYHa1G++2LYbANedQxvafknDh/5DUTRMuLxqKg5SEr6OvLzbvZ6fiazuRM7d30bFkun8zGVKgVaTTZ0ukIkJKxAQsIqaDQZXm1vIna7GVu2ngKrtdfr5kCHj/wGzc2vICpqNpYvewebt5wKq7UbZYtfmXDOIwodq7Ufm7ecDIfDjNKSPyE19exQD4nG4XBYsX//9c5uqBJBUEGlTDjRzVWGoqK7kJtz/YzOAKGps1r7sXPX+TCZmlweFRAdPQ9JiaciJ+f7UKvT3K5rNnfg2LHH0Nb+FgBAo8nBvOIHERu7EPsP3Ii+vh0QBBVKSn7P+XgppMzmDmzZ+nWIohVLT3oTcXFloR7SpEgd2uXyKJy88tOAlzHX1DyChsY/IyZmAcoW/x1NTX9FY9NfYbcPelxHLtdhXvHDSEtbO6nXtNtNaGx6EQZ99cgnBBky0i/0uWLRaGxBxcGboNcfBCDDrMI7kJd3I4aGalFdfTf6B/Y6xy0FbLXaXBQWrEN8/DL09m4/EcD86sbiV+81GgkJK5GT/X0kJq6a1PudrgIW0DSbzejt7UV6ejrKy8uxbNkytwHNm266CS+//DIOHTqE3Nzhufs+/fRTnHHGGXj++edxww1fzddVX1+P/Px8dHV1ISUlxWNA83e/+x3uvvtu7Ny5E8uWLQMAHDp0CCUlJbjrrrvw0EMPAQCMRiNycnKwcuVKvPfee871r776arz99ttoampCQkKCT9ucCAOaFO6GJzj+1YkOd+/PiAmF9x+4EV1dn86oIK4nen0Vmps34HjHe2PmxtRqclFa+gxiYuaFaHTTS0/vNuzbdw1E0YaC/FtRWHjbmGXsdjOOHPk1WtveAAAkJ58OnS4fvT3boDdUQSpzj40tQ9nil6FQRI/7mqJox96930Nv33ZERc1GyYKnoNXmBDwjWSpf0miykJp6LhITTkF8/FK3jcgMhsPYuevbEEW7M4ApZf1F2lxUM01T08s4cvS3iI4uxvJl7zEAFgGs1gEcPPgT2Ox6JCScjMSEVYg7kZF9+PAv0db+bwBAauq5mFe8fsJjDE0/RmMTDlT8CGp1OjIzv4PkpG/4PJWMKIo4UPEjdHV9Co0mB8nJ30Bv71YMDh51LiOTqZGd/T3k590IpXL4+stq7UND4wtoanoZDocJgICc7O9j1qw7nL+37HYzKqt+is7OjwHIUFz8ALIyL/PX2yfyiVQ2HRe3BEtP+leohzNpouhA+e5LMDCwH4kJX8PixX8NWBdvs6ULW7eugcNhHHHj22LpRn3Dc+joeB+iaBuxjlabi+K5DyI6ek5AxjRZdrsZh4/c76xUiYs7CXp9BRwOC+TyaMwuugfp6RehtfWfqKv/E6zWbrfbkclUiIs76cS8mKsQE1My7buVT1ZQ5tAcL6CZlpaG1atX44033hjx+Ny5c5GTk4NPP/10zPYmCmguX74cALBz584Rj5911lk4duwYampqAADvv/8+1q5di//7v//Dueee61xu27ZtWLVqFTZs2ICrr77ap21OhAFNCneiKGL//h+gu+d/SEo6DYsX/SXUQwooq7UfmzavgChasWL5B2H3izFUbDYDjh9/D62tr2NAfwBJSWuwYP4T7DLtZ62tb6D60L0AgHnzHhkx+brV2ofKqjuh11dg+E7v7cjLu9GZ/Wmx9KCnZzMOH/k1bLZ+xMevwOJFfx13Th7pRFsu12HZ0v8ErSnR0FADyndfDKu11/mYIKgQF1eGxISTkZC4CrExCyEICuzdezV6+7YjJeVsLCwdnq+1s/MTHKj4ETSabKw6eSMDZWFIFEXs2HkOBgePnijTujrUQ6IpEkURLS2v4cjR30IUrdDpilC2+CVoNJmhHhoFkes0EgCgUiUjI/1iZGZe6vVN74aGP6Pm2CMQBBWWnvQGYmNLAQxXDPT2bkNzy9/R378bwHAmUl7u9YAgQ2PjC85pUWJjyzB79r1up0BxOGw4fPiXzpt/Cxb8Hulp3/b6PYqiCFG0BK1DMU1PdvsQNm85FTZbH0pLnkFqamRnCxsMR7Cr/CI4HEYUFNyGwoJbA/I60k3v2NhFWHrSWxF/jieKIlpbpcqq4fkuk5JWo3juAyN+f9psg2hu/hsaGv8Mm82A2JhSZ3OfuLiTvJ5jc6bzNr4WkHBwS0sLOjo6sHTp0jHPLV++HO+//77P23Q4HDhw4AB+8IMfuN3mxx9/DL1ej5iYGOzdO5z2O/r1TzrpJMhkMuzduxdXX321T9sczWw2w2w2O38eGBjw+T0RBZMgCJg9+5fo2XkOuru/QFfXF9O6SVBn58cQRSuiouYwmOlCoYhGVtblyMq6HBZLN5TKxIg/wQhHmZnfweBQLRobX0B19d1ul1Eo4lFS8hSSEr824nGVKhHp6edBp8vHnr3fRV/fDlQcvBkLS591O89kV9cXzsnWi4sfCmqHdZ0uDytXfIjuns3o7dmKnt6tMJvb0Ne3A319O4C630Muj0Z0dDH6+8shk6kxu+he5/qJiV+DTKaGydSMwcEjnHcxDPX378bg4FHIZFqkp58f6uGQHwiCgOzsqxATMw8VFbdgaKgG+w/8ECcteZ2ZmjOE2dKF9vZ3AAAZGZegu3sjLJYuNDQ+j4bGPyMv70bMKrx93Myt3r5dOFb7GABgzpxfOoOZAKBWpyA9/TykpX0b3d0bcaz2cRgM1ait+71zmeiouSicdQeSk77h8TxEJlOguPghyOU6NDW/jOrqu6DVZCEubsmE71EUHaiq+hnaj7+L5KQ1yMz8DpKSTmM2FPmssfFF2Gx90GpznY3WIll09BwUz/0tqqrvRF3dHxAXW4akpFP9+hpmcweaTzT4Kiz46bS41hAEAVlZVyA6eh4aGv+MlOQzkJ5+wZj3plBEIT//JuTmXg+Hw8LfqwEWkM4gbW1tAICMjLHzdGVkZKCnp2dEMNAb0jqetgkAra2tzteXy+VITR05J4RKpUJSUpJzOV+2Odr69esRFxfn/JOTE1ldzmhmiooqRE7ONQCAI0cfgMPh234YSY4f/y8A+HQnf6ZRqZKmxQlGuCqadRcyMy+Du1+1cXFLsXzZO2OCma5iYxdi0cIXIJNp0N29EZWVt8PhGFmaYzK1orLqTgBAVtbVIfm+D2f1XID583+HU1ZtwskrP8Xcub9Faso5UCjiYbcb0N9fDgDIy70RWpcJ4OVyLRJPfAadnZ8Efew0sZbWfwAA0tK+BYVi7A1eilxxcUuwdOmbUKlSYDAcwsHKnzrnWqbprbl5A0TRgrjYMsyf9whOWbUZpaXPIClpNQARDQ3PYd++a2Gx9Lhd32zpwsGDt0IU7UhLOw9ZmVe4XU4QBCQnn4bly95FyYKnoNMVQacrxIL5T2L58veQkvzNCc9Dhm/I34fk5NPhcFiw/8CNMBqbJ3yPtbVPoP342wAc6Or+HAcqfoQtW0/FsWOPebU+ETCcIFFb9xQAID//5oCVZwdbRsaFJ85RRVRW3Q6Tqc2v269veA4OhxlxcUuQmOjfYGmoxcUtxsLSZ5CRceG4xy+ZTMVgZhAE5BaV0WgEAKjVY9P7NRqNcxl3z091m9Lfrk2HRi/rupy32xzt3nvvxe233+78eWBggEFNiggF+begvf0dGI31aGp6GXl5N4Z6SH5nNnei50SHvLS0b4V4NDRTCYIM84ofwrxi7+ZidichYTkWlj6L/QduREfnB7Ds64FWm+t8vr9/L2y2PsTElGLO7Pv8MewpEQQBOl0BdLoCZGddCVF0wGCoRk/PFtgdJuS7Od4kJ38TXV2foavrMxQU3BKCUZMnVmsfOjqGq2qystwHLCiyaTSZWLjweezZcwW6u7/A0Zr1mDP7F6EeFgWQ3W5ES8urAICc3OsAADKZEqkpZyE15SwcP/4eqg/di57eLdi163yUlv4JsbELAQxPW9PXtwv1Dc/CYumATleE4rkPeBGUlCEt7VuTPicTBDkWzH8Cu/dcDoOhCvsPXI+lJ/3L402Wtra3UN/wLACgaNbdsFi70db2b1gsHahveBaNTS+iIP825OZe7zZjs7d3B453vAeHwzricbUqBdnZ3w14IxUKDwP6gzhYeTsAEVlZVyMj/eJQD8mv5sy+HwMDFTAYqnCw8lYsKXvN53l03TGZ2tB64mbodMnOpPAVkICmVjvcDMBdFqbJZBqxTCC2qdVqYbFYxiwnLeu63GTHqVarfQrIEoULhSIGRbPuQlX1z1BX/yekp1/gsftkpBq+AHcgNnbxiOAPUSRKSvo6SkueQsXBW74q5XahUMSitOSPYTlHmCDIEBOzADExCzwuk5z0DQDAgP4AzObj0+54FMna2v8Dh8OC6Oh5iI1ZGOrhUIDExS7C/PmP4eDBn6Cp6SXodIXIzroy1MOiAGlr/w+s1l5oNDlITTlzzPNpad9CVNRsHKi4CUZjPXbvuQwZGd+BwVCFgYEDziYeMpkWpaVPQ6GICsq4FYooLFr4Z5SXX4zBwaOoOPgTLFr4lzEByd7enag+9HMAQF7ej5GXN9yIdlbhHejs+gzNzRvQ17cDx2ofRUfn+5hX/IizKeLAQAWO1T6Onp5NHsfR2PRX5ORcg7zcH0KpjA/Mm6WQM5nbcWD/DXA4jEhMPBVzZv9y2gXm5HI1Skuexs5d56G/fw+OHH0Aswpvn/K8+vUNz8LhsCA+fjkSEti5mwIrIAFNqVxbKj131dbWhsTERJ+DgdI6nrYJAJmZmc7Xt9vt6OjoGFF2brFY0N3d7VzOl20STSfp6RegueU1DAzsRU3N77BgweOhHpJfHe94DwCzM2n6SEk5E0tPehM9PVtGPiHIkJpyFrTayK0QUKtTEBu7GAMD+9DV9fmITEBRFGGz9Tk745L3RNGBjs6P0N72b8gVUdBqsqHV5kKjzUFU1GyoVckTrC+ipeWfAICszCum3YUcjZSWei6GCutQW/sEjhz5NbSaHL/PqRYMomiHzWZgozsPRNGBpqa/AgByc67xWD4bHT0Xy5e9jcqqO9HV9SlaTsyFBwBaTS4SEk9GVubliI6aHZRxSzSaDCxc+Dx277kCPT2bcODAD5GW9i0kJKyCRpOBoaF6HKj4MUTRitSUczCr8KtqOplMhbTUc5Cacjba2/+DI0cfgF5fiV3lFyA393oMDdWjs/NDAIAgKJCRftGom+IiOrs+x8DAXjQ0PIeWlleRm/tD5GRfE7SgLgWHzTaIA/tvgNlyHFFRs0/cNJ6ec6/qdHmYP/93qKi4CS0tf0dLy2uIiVkw3IU7cRUS4pd5fcPcZtPj6NGHnE28mJ1JwRCQPTMrKwspKSkoLy8f89zOnTuxePFin7cpk8lQWlrqdps7duxAYWGhs3mPtP3y8vIRXc7Ly8vhcDicz/uyTaLpRBBkmDvnV9hVfhHaj7+N7OyrvJpgPRIYjS3o798DQEBa6rkTLk8UKWJjFzrL/qablORvYmBgHzq7PnMGNIeG6lF96D709e1AcvI3UVh4O2Kii0M80vAniiJ6ejbhWO1j0OsrPSwlw6zCdcjL+xEEwf106n395RgaqoFcrkN6+nmBGzCFjfy8mzA0VIf29v9g3/5rERM939mZNT5+KQRBCZOpFSZTM4zGRthsA0hNPTdsbqj09+9D9aF7MDh4DBkZF6Eg/1ZotVmhHlZI6A2H0Ne7AxkZF4+Yw62r+wsMDdVBoYhFRsal425DoYjBwtJn0dLyGvT6SsTFlSEhYdWIeZBDITa2FAsWPI6KipvR3fM/dPf8DwCg0xXCYTfBZutDbMxCzJ//qNvjmyAIyMi4CImJp+LwkV+hs/NjNDQ8Jz2L9PTzUVhwm9sKn7y8H6Or+3PUHnschsHDqK19AsePv4dlS/8Nudy36kMKTw6HFZVVt0NvqIRSmYhFC1+Y9vNHp6achblzf4umppcxNHQMen0F9PoKNDQ+D52uAKUlz0zYYLWr63McOvxLmM3tAIC83BuQkLAiGMOnGS5gtxouvvhi/O1vf0NTU5NzbsnPPvsMR44cwbp16ya1zUsuuQT33HMPysvLnR3MDx8+jM8//xx33nmnc7lvfOMbSExMxLPPPjsioPnss89Cp9Nh7dq1Pm+TaLqJjV2IjIyL0db2Jo7WPIKTlvxzWtxFk7IzE+JXsHSVKEIkJ5+OY7WPo7d3C2w2PVpb38Cx2ifgcAxP/zI8x+bnSEv7FgoLboNOVxDiEYen/v49qDn2KPr6dgIA5PIo5GR/DwplHIzGJpiMTRgyNsBobMCx2sfRP7AfC+Y/5vZirbXlRDOgVDYDmikEQcC84gdhs+nR1fUp9IZK6A2VaGx8AYKggCg6ADhGrFNb90cUzfoZsrO/6zE4Hmh2uxG1tU+isekl5/ja2t5Ee/u7yMq6Avn5N02YkTyddHVvREXFzXA4TGhs/AuKix9yZts2Nr4IYDjr2pusQkGQITv76oCOdzJSU87CsqX/Rkfnx+jt3YqBgQoMDdUCANTq4SzOiQKManUKSkueQUfnBzh27HFER89FYcFPxw3cCIKAlORvIjnpNBw//h6OHH0Ag4NHUHPsEcyd82uvxu5wWHHo0H2w2fSYN+8RZhOHEbO5EwcP/gR9/bsgk6mwcOFzYXPDJtCys65EdtaVMJnb0duzDT29W9Dd/SWGhupQvvtizCt+GGlpa8esZ7Z0oebo+hMNuACtNg/zih9GQsLyIL8DmqkEURRFX1d6+umn0dfXh9bWVjz77LO46KKLUFZWBgD4yU9+gri4ODQ1NaGsrAzx8fG47bbbYDAY8OijjyI7Oxu7du0aUXK+YcMGNDQ0YGhoCOvXr8dpp52Gb3xjeE6t7373u8jLywMA6PV6lJWVQa/X484774RSqcQTTzwBu92Offv2ISUlxbnNZ555BjfffDMuueQSnHXWWdi0aRNeeeUVPPjgg7jvvq8aJ/iyzfEMDAwgLi4O/f39iI2N9fUjJQoJk6kN27afDofDhIWlzyEl5YxQD2nKduz8FgyGahTPfRBZWZeHejhE5AVRFLFt2zdgNDVCrc6A2Tw87UtCwirk59+ElpZ/oKPj/wAMN4fIyroSs4t+MW1LwNwRRce4AaOeni3Yu+8aAA7IZCpkZ30XeXk3QqVKGrNsS+vrOHz41xBFy5jsC5OpFT09W3H4yC/hcFiwbOl/pm1mMHlmNneit3cbenq3ordnC0zmVgCATKaGRpMDrTYHVmsvBgb2AQDi4pZi/ryHg36zYXi+xHtgNDYAGJ5SJyP9ItQ3PIveE80BZTItCvJvPpGR7P2NW1EUI+5Gb3v7O6iqvguiaINMpobDMdwnICPjUqSnfRt7930PgqDAqlVfQqNOD/Fo/cdqHUBf3w4M6A8iI/2CoH0Pu7v/h337rwUALF70slfTNBytWY/Gxr8AAGJjy1C2+GV2Qg4Dff27UVFxCyyWDsjl0ShZ8HskJ58W6mGFlMXSjYOVP0Vv71YAQG7OdZg16y4Iggw9PVvQ2vo6Ors+hShaAciQm/sDFBb8lNnK5BfextcmFdDMz89HQ0OD2+fq6uqQn58PAKisrMTtt9+OzZs3Q6VSYe3atXj88ceRljYya2rNmjX48ssv3W7viy++wJo1a5w/Nzc3Y926dfj444/hcDiwZs0aPPnkkygqKhqz7gsvvIDHH38cdXV1yMnJwS233ILbbrttzMmJL9v0hAFNilQ1xx5DQ8Oz0OlmYcXy9yM6QDA4WIPtO86CIChw6te2c949oghy5OgDaGp6CQAgl0dj9uz7kJnxHefvbL2+Csdqn0B39xcAgKysqzB3zm8iLuDgLau1H729251BJaOxEXPn/NrtjRqTuR07d34bVmsPkpNPx9w590OjGX8O8IGBAzhQcRPM5jbI5TqkpJyF/v7dMBobncvExi7C0pPemrafMXlHFEWYzW0QBAVUqhTn90EUHWhpeQ01xx6B3T4EmUyNwsLbkZtznU/fmcaml1Bb+yTS085DfsEtXgXaRNGOY7VPouFEJ2u1Oh3Fcx8YEYDo6dmCY7WPY2BgP4DhkvpZs+7wakwOhw37918Hw+Ah5OZej+ys70Iu13j9nkKhqellHDn6WwBAWtp5mDvn16itewrNza8A+OpyLz3tgmk3d3ooHT78azS3bIBalYYVK94ft1FQZ+fHOFDxYwDDGfR2+yDi41dg8aK/hv33a7oSRRHNLX/H0aMPQhStiIqajYWlz7IS5ASHw4ba2sfR0PhnAEBszEJYrD0wmZqdy8TGLsac2b9EXNziEI2SpqOABjRpLAY0KVLZbHps3XYarNZeFM99YERDjkhTW/t71NX/EUlJp2Hxor+EejhE5IPBwRrs3fs9xMSWYu6cX0OjyXC73PGOD3Dw4E8AiJg9+xfIzbk2uAMNsMHBWlQfuufEXMCjT9EEzJ//GDLSL3A+4nBYsWfvVejv343o6HlYetKbXl8YD2df3ObMZAOGM2BjYxYiIXEVcrK/7zbDk8iV0diMQ4d+jp7ezQCA4uKHkJV5mVfr2u1GbN5yCmy2fgDDGaDZWVcjL+9HUKkS3a5jsfx/9s47PJay/uJnZvtueu89ub1XLkVQAem9iNJtgKCAIiAoSBUpilLEH0hVQECqKL1ze7+5Nzc3vfdke53398fOTDbJ7mZ3syXl+3mePHBTJ5vdmXfOe77nDGLfvmvln1eQfy6qq2/2G43AGEN7+zOy0FdZ8QuUlV0x6XG1tj6J+kN3y//WqHNRVv5TFOSfA55XhfS7xQvGGBqbHkJz8yMAgKKii1FTfYvs6B4e3or9B26E1doEAFi75i0kJy9M2PHONjweGzZvOQVWaxNyc07G4sV/8vt5NlsrNm85FW63CcXFlyEv9xRs33EhPB4zMjO/gaVLHgfPq+N89MSBut+go+MFAEBOzolYMP9eKnnyQ0/vu9i//1fweCwAAKUyBXl5p6Eg/zwkJy9I8NERsxESNOMMCZrETKa17e+or78TanU2Nhz2ERQKfaIPKWw8His2bjwedkcnFi18EHl5pyX6kAiCiBEtrX/DoUP3AuCxbOkTCR8L8zYH/x02e9uY9/O8FoUF54Xs9DAad2Pnrsvhcg0C8JZcZKQfjvSMwzA4+BU6Op4HxymweNGfkZNzPIDR8UWFIglr17wetqtEENzo6PwH7LZ2pKWvQ3raWsrMJMKGMYampofR1PwwlMoUrF/3HjSayWObOjpfwoEDN0OjyYdOW4ThkS0AvC7tosILkJl5DFJTl8tCj9G4B3v2XgW7vQM8r8PCBfciN/fkSX/O6DkDqKm+FcXFlwT8XJutDRs3nQBBsKEg/1wMDn4hj9zrtCWomfdbZGUePenPjAdDQ5vQ0Hi/uAECVJRfi7KyqyY4ZD0eO9o7nodKmYKCgnMTcaizGqNxN7ZuOxuMebBo4UMTitQ8Hge2bTsHJvM+pKaswMqV/wTPqzA8vBU7dl4MQbAjO/s7WLzoTzN6Umqm0dv3P+zZcyUAHlVVvwrbXT7XsFgOoa39GaSmrEROzgnkKiZiCgmacYYETWImIwhObNx4PGz2VlSU/xzl5Vcn+pDCRtph1WjycNj692ekKEsQRGgwxnDgwM3o7HoZCoUBq1a9nNAG9PFuLl+UyjQsX/bkpKNYg4NfYveeK+DxWJCcvARLFv9lTJswYwL2H7gJXV2vgONUWLr0cTDBhd17fgIAWLL4EeTkfCdqvxNBhIsguLF121kwmfYiJ+dELFn856CfzxjD5i0nw2w+gKqqm1BSfDkGBz9DQ8MDMJn3yZ/H8zqkpa1GkqEG7R3PQRCc0OlKsXTJY0hKmhfy8TU2/glNzQ8DABbMv8evsMcYw85dl2Jw8HOkpa3DyhUvgDEnOjpeRFPzI3C5BsBxaqxe/S+kJC8O+WdHG6NxDxoaH8Dg4OcAvJsnNdW3zOgpm5lOY9PDaGr6E5TKFCxZ/AgMhio5ouHAgVvQ0flPqFTpWLvmzTGRIAODX2DXrh+CMScy0g9HVdWN5KCNA263CRs3Hg+HswelpVegqpLKgAliOkGCZpwhQZOY6XT3vIV9+34OhcKADYd9BPUMagTtH/gEu3ZdDgBYsfxZZGQcnuAjIggi1giCCzt3XYqhoa+h0eRjzerXoNHkxP04zOY6bNl6OgTBify8M6HxGZUfGPgMJtMe8LwOS5c8iszMo/x+j57ed7Fv33VgzIn09A1YuuQxvyURjHmwd9+16O19BzyvAcep4PGYUVx8KWqqb4nZ70gQoWIy7cOWrWeAMQ+WLn0C2VnfCvi5Q8NbsH37+eB5LY44/Cu57ZkxAX1976O39z8YHPoaLtfAmK/LyvoWFi64HypVeOttxhgOHboHrW1PAuAwr+Z2FBZeMMaR1d39BvbVXgeeV2Pd2v+McTx7PFbs2XsNBgY+hlZbjLVr3gz7GKaKILiwf/+NcqMwxylRUHA+ysuuhEaTG/yLiZgiCC5s23YujKbd8vt4XgONJh82WzMADsuXPeX3OtDX9wH27P2pWK4C5OacjIqKn4fkuHe7TeA4FbnlwkQyQuh0pVi39j/0+BHENIMEzThDgiYx02FMwJatZ8Bk2ouiwgsxb95tiT6kkHC5hrBx0wlwOvtQVHQx5tX8JtGHRBBEnHC5RrB129mwWhvFIP/HodeXxe3nC4ITW7aeCbN5PzIzj8aypf83Rhxxuy3Ys/cqDA5+Do5TYeHCPyAv9xT54zZbG3p63kJD44MAGHKyT8CiRQ+A5zVBfqYLe/Zehf7+DwF4W3JXrfwHZa8R04b6Q/eitfVv0GjysH7dfwNGGOzZezV6e/+DgoLzsGC+f4czYwwWy0EMDn6JEeNOpKWuRFHRRXI+ZLgwxlB38Dfo6PgHACAj/QjMn38XdLoiuFxD+HrjcXC5BlFRcR3Ky66a8PUu1wg2bzkVdns7srOOxZIlj8V1RLWz8xXsP/ArABzy8k5HRfk10OlK4vbzieDYbO04WH8HzOYDsNs7AQjyx8rLrkZFxc8Dfq3V2oTGxj+ip/dtAN4847zc06Abd03zuM2w2dths7XBZmuD2z0MAFCrs6HTFUOnLYZOX4bCgvPD2uRjTEBX16twOHvHvJ/nNSjIP0fecJgNDA9vxbbt3pzfFSueR0b6YQk+IoIgxkOCZpwhQZOYDQwOfY0dO74PjlPisPUfQKcrTvQhBYUxhr17r0Zv37vQ6yuxds2btMNKEHMMq7UZ27afD6ezD0plMhYtfChumZqHGu5HS8tjUKnSsW7tu34zAwXBidraX4o3qRxKS34El2sIg0Nfw+6TuVlY8F3Mm3c7OE4x6c/1eBzYv/8GWKyNWLb0r5M2mhNEPPF4bNi06UTY7K0oKroI82p+O+Fz7I5ufPXVUWDMg7Vr34lrZARjAlrbnkRj40MQBAcUCj0qK2+A0bgL3d3/hsFQg7Vr3gi4SeDNSzwPjDlRVXUTSkt+EKfjZti0+URYLAdRWXkDykp/HJefS0SGILjgcHTBZmuDIDiRmXl0SOK3yVSLhsYHMTDw8ZR+vl5fgTWr/+3X7e+Pltb/w6FD9/j9WFbWt7F0yeOzIl9SEBzYvOU0WCz1yM8/BwsX3JvoQyIIwg8kaMYZEjSJ2cKOHRdjcOiLGXGR7+p+HbW114PjlFi96hWkpCxJ9CERBJEA7I5u7NnzUxiNOwAA5eU/Q3nZTyN2cYWC1+HxXQAClix+VC7p8QdjAg4e/B3aO54b836OUyAlZRnyck9DYeH3ZsXNIkEA3lzAnTsvBsBh9ap/ITV1xZiPNzQ+iObmR5CWtharVv4zIcdotTZh//6b5CIiL/6Pdzzt7S+g7uBvwHEKrFzxD6SlrQZjHphM+zA09DWcrkHkZB+PlJQVUXtdDwx8hp27LoVCYcDhG76I+7g7EV+Gh7eip/dtCIJzzPt5Xis6MYug05VAqy0CYy6vY9PudW22tz0Dh7MHuTknY9GiP076HDSb67B5y+lgzIns7OOhUqV5P8AYurr/DcZcsyanuanpz2hs+iNUqkwctv690d+VIIhpBQmacYYETWK2MDKyA1u3nQ2OU2D9uvfiOr4JeDPihoY2wm7vCPp5AnPj0KHfw+Mxo6L8WpSX/zROR0gQxHREEJw4WH8XOjqeBwBkZh6DxYseikljt9ttxubNp8Bmb0V+3plYuPAPk34NYwytrU+gt+89pKauREb6BqSlrQnZPUMQM419tdeju/t16LQlWLT4j0hNWQbA65D64ssj4XINYPHivyA354SEHSNjAto7XkBDw33weKwhR+4wxrCv9lr09LwFjToXKanLMDS0CW73yJjPMxhqUFBwLvLzzpiycCJtOBcXXYKamlun9L2I2c3w8FZs3/E9MOZGTc1tKC66MODnCoIDW7aeBbN5P7Iyv4mlS58YI4BKmw9qdTbWr3tvRgvpFksDNm0+GYw5sWjRH8dEwBAEMb0gQTPOkKBJzCZ27rocAwOfIC/vDCxaeH9cfqbd3onOrlfR1fky7I7OkL/Omx/3InheGcOjIwhiptDV9SoO1N0KQXAgO+tYLF36eNR/xv79N6Gz62VotYVYt/admIimBDHTcToHsXnLKXA4ugHwKCm5HBXlP0dv339RW3s9NJo8bDjsE/C8KtGHCputAyMj25CT852Q82jdbgu2bD0TVush+X0KRRLS09dBoTCgr+9/EAQHAIDn1UhLWwedrkR013n/m5Q0PyQnudlch02bTwTAY8NhH037SCAi8bS2Pon6Q3eD41RYveplpKQs9ft5hw7dh5bWv0KlysC6de9CM64U1ONxYPOWk2G1NqKw4LuYP//OeBx+1BEEB7ZuOw8m0x6/mdcEQUwvSNCMMyRoErMJo3E3tmw9AwCP9ev+C4OhMmY/a8S4C01ND2Ng4DNI4elKZQpSU1dNushX8DpUVt4Ana4wZsdHEMTMY2RkJ7ZtPw+MuScdBw8XqQUZ4LByxQtIT18Xte9NELMNp3MQB+vvQE/PmwAAna4MHKeE1XpoVkxXWK3NaGr+C/T6cmSkb0By8hJ5g9XlMqK75w10dr4Es3m/369PSVmBJYv/DK02P+jPqa29AV3dryIn50QsWfznqP8exOyDMYY9e69EX9970GoLsXbNmxNcwt7olPMBMCxZ8ihysv1fK4eGNmP7ju8CAFaufBHpaWvkj3k8dnR3/xsqVTqys4+ftiJhXd1taO94DkplGtatfYuypwlimkOCZpwhQZOYbeza/WP093+A3NxTsHjRH2PyM/r6PsDefdfIDoa0tHUoLDgP2dnHU7kPQRBToqHhATS3PAq1Ogfr1/3P75icw9EDq60VOm0RNJrcSTdRzJZ6bNlyBgTBhvKya1BR8bNYHT5BzCr6+j9E3YFb4XD2AAA4To0jDv8c6nFusNkIYwxmcy2Mpr2wi83UNnsbzOaDEAQbVKpMLFn8MNLT1/v9eoejF19+dRQYc2H1qleRmro8vr8AMWNxuYzYsuU02OytyMw8GtVVN0OrLYJCoYHbbcamzSfDbm9Dft5ZWLjwvqDfa/+Bm9HZ+RL0+kqsW/sWAB5dXa+gqfkvogsbyMw8GvPn3THtxMLunrewb9/PAQDLlj2JrMyjE3o8BEFMDgmacYYETWK2YTLVYvOWUwBwWLf2P0hKqgn6+d5TCQu5hKOz6xUcOHAzGPMgM/MY1FT/Gnp9+dQPnCAIAtKY3EmwWptQWHgB5s+7Y8zHe3rfxb5914Exb+ECx6mh0xVCpytBXu7pyM09ZYzTxHe8NCP9cCxf/veQGskJgvDichlx6NA96Ox6mXIgAVitLdiz9yqYzfvBcQpUVf4KxcWXTXC4NTTcj+aWx5CaugqrV72coKMlZiom0z5s3Xb2mHIhjToXvEIDm6015OgUl2sEGzcdB6ezHznZJ8Bk3gebrdX7/TR5cDoHwZgTCkUSqqtuREHB+dPCrWmxNGDL1tPh8VhRVnolKiuvT/QhEQQRAiRoxhkSNInZyO49V6Gv77+Tjji5XEbs2n05rNYWVFffjLzc04IuYlpansChht8DAPLzzsL8+XdTBiZBEFFnaGgTtu+4AACwauVLSEtbDQDo6PgnDtTdCoBBpcqE2z0CxtxjvjYz8xjRaZIPxhhqa69Hd88b0KhzsXbtm3PCWUYQscDtNkGhMIS8ATqb8XhsOHDgFnT3vA4AyMk5EaWlP0Zy0kJwHA+Px4ovvjwCbvdI1OMziLlDX9/7aGx6GDZbCzwei89HOKxc8Q+kp68N6fv09P4He/deLf9bpcpAedlVKCz8Lmy2NtTuvxFG4w4AQHr6YVgw/17odEXR/FXCwuOxYsvWM2Gx1CM9/TCsWP4MbUQSxAyBBM04Q4ImMRvxhtCfBIBh7dp3kJw0f8LnuN0W7Nh5sbyAAcYKAb4IgguNjQ+ipfUJAEBJyQ9QVXnjtNjBJQhidiIV+Ehjci2t/4fGxgcBAAUF52P+vN+BMQaHoxs2WyuGhjehpeWJUadJ9c1gght1B38DjlNg5Yp/yMIoQRDEVGGMob3jOdTX3yVvrCiVaUhPXw+FQuttiteV4LD1H5AYQ0wJxhhcriHY7G1ed6YmP6zrGWMM+w/ciP7+j1FcfDGKiy6BUmnw+bgHbe3PoqHhfgiCHUplKhYv+iMyM4+Kxa8z6bHW7v8Furtfh1qdg7Vr35pQeEQQxPSFBM04Q4ImMVvZs/ca9Pa+A52uDAsX/H7MwsfjsWPXrssxNLwRSmUqCgrOQVvbsz4jJzchJXU5hga/wuDQlxge3iLvDFdV/gqlpT9K1K9FEMQcwXdMLilpPszmAwCAstIrUVFxnd8NFbOlHvv33wijceeY91dV3YjSkh/G47AJgphjjIxsR3PzYxga3jTORQfU1PwWxUUXJejICCI8rNZm7Ku9DkbjLgAcKiquRVnpFXF1ZXd0vIgDdb8GxymwYvnzIbtQCYKYHpCgGWdI0CRmKzZbK7ZtO18M8udQXHQxKiuvB8cpsXvPFRgY+AQKhQErVjyH1JRlAYUACZUqA9VVNyI//6y4/h4EQcxdenrewd5918j/rq6+BSXFlwb9GsY8aGt7Gg2ND0AQHMjOOhZLljxGjnKCIGKKILhgNO0WN4O/hkKhx5LFD0Oh0Cf60AgiZATBgbqDv0Nn54sAgKysb2PRwvsnzeqMBr65oZWVN6Cs9Mcx/5kEQUQXEjTjDAmaxGzG5RpB/aG70dX1CgBAqy2GXl+GwcHPwfNaLF/29zE7n6NCwEMAgPS0NUjPOBwZ6RuQlDSfcrMIgogr3gzMX6C373+YP/9O5OedHvLXWq0tGBr6Cnl5p5GgQBAEQRBh0Nn5MuoO/haC4IReX44Vy5+NaQu6b7N7VuY3sXTpX+m+gyBmICRoxhkSNIm5wMDAZzhw4NewOzoBABynwrKlTwTMxhEENwABPK+O41ESBEFMhDEGxpzgeU2iD4UgCIIg5gxG427s3nMlHI4uZGYchWXLnop42oExDwYHv4DTOYDs7OOgVCb5fIxhz54r0Nf/PrTaIqxd8wZUqrQo/RYEQcQTEjTjDAmaxFzB7TajoeF+9A98hJrqW5GdfWyiD4kgCIIgCIIgiGmKxdKIzVtOgiA4sWjhQ8jLOzWsr7fZOtDV9S90dv0LDkc3AG+MVVnZlSgsuAAKhQatrU+i/tDd4Dg1Vq96CSkpS2PxqxAEEQdI0IwzJGgSBEEQBEEQBEEQxESamv6CxqaHoFJl4LD170GlSg/6+YLgQn//h+jsfAkDg58D8MoWSmUalMpk2O1tAACNJh8F+eegueVRMObGvJrbUVT0/Vj/OgRBxJBQ9TVlHI+JIAiCIAiCIAiCIIg5Rmnpj9DT+zYslnrU19+DhQvv8/t5VmsTOjtfRmfXq3C5BuT3p6cfhoKC85CddRw4jkdX92toanoYDkcXmpofBgDk5pyMwsLvxeX3IQgi8ZBDM0qQQ5MgCIIgCIIgCIIg/DMysh1bt50LgGHF8meRkXG4/LGhoc1oan4YQ0Nfy+9Tq7ORn382CvLPhl5fNuH7eTwOdHS8gOaWx6HVFmDliufH5GoSBDEzoZHzOEOCJkEQBEEQBEEQBEEEpq7uNrR3PAedrgTr1r4Li6UeDY0PYHDwc/EzeGRmfgOFBeciM/MY8Lxq0u/plTQYNZoTxCyBRs4JgiAIgiAIgiAIgpg2VFZej77+92GztWLzllNhtTYAADhOiYKC81BW+hNotQVhfU9va3pkzekEQcxcSNAkCIIgCIIgCIIgCCLmKJXJmFdzG3bv+YkoZnLIyz0N5eXXQK8vTfThEQQxgyBBkyAIgiAIgiAIgiCIuJCdfSwqyq+FzdaCkpIfIClpXqIPiSCIGQgJmgRBEARBEARBEARBxI3y8p8m+hAIgpjhUGouQRAEQRAEQRAEQRAEQRAzBnJoRgmpLN5oNCb4SAiCIAiCIAiCIAiCIAhi5iHpapLOFggSNKOEyWQCABQXFyf4SAiCIAiCIAiCIAiCIAhi5mIymZCamhrw4xybTPIkQkIQBHR2diI5ORkcxyX6cBKG0WhEcXEx2trakJKSkujDIQgiCPR6JYiZAb1WCWLmQK9Xgpg50OuVIKYnjDGYTCYUFBSA5wMnZZJDM0rwPI+ioqJEH8a0ISUlhS4KBDFDoNcrQcwM6LVKEDMHer0SxMyBXq8EMf0I5syUoFIggiAIgiAIgiAIgiAIgiBmDCRoEgRBEARBEARBEARBEAQxYyBBk4gqGo0Gv/3tb6HRaBJ9KARBTAK9XgliZkCvVYKYOdDrlSBmDvR6JYiZDZUCEQRBEARBEARBEARBEAQxYyCHJkEQBEEQBEEQBEEQBEEQMwYSNAmCIAiCIAiCIAiCIAiCmDGQoEkQBEEQBEEQBEEQBEEQxIyBBE2CIAiCIAiCIAiCIAiCIGYMJGgSBEEQBEEQBEEQBEEQBDFjIEGTIAiCIAiCIAiCIAiCIIgZAwmaBEEQBEEQBEEQBEEQBEHMGEjQJAiCIAiCIAiCIAiCIAhixkCCJkEQBEEQBEEQBEEQBEEQMwYSNAmCIAiCIAiCIAiCIAiCmDGQoEkQBEEQBEEQBEEQBEEQxIyBBE2CIAiCIAiCIAiCIAiCIGYMykQfwGxBEAR0dnYiOTkZHMcl+nAIgiAIgiAIgiAIgiAIYkbBGIPJZEJBQQF4PrAPkwTNKNHZ2Yni4uJEHwZBEARBEARBEARBEARBzGja2tpQVFQU8OMkaEaJ5ORkAN4HPCUlJcFHQxAEQRAEQRAEQRAEQRAzC6PRiOLiYllnCwQJmlFCGjNPSUkhQZMgCIIgCIIgCIIgCIIgImSyOEcqBSIIgiAIgiAIgiAIgiAC0m53wsNYog+DIGRI0CQIgiAIgiAIgiAIgiD88re2Pqz+uhaPtvYm+lBmLJ8MGnHAYkv0YcwqSNAkCIIgCIIgCIIgCIIgJtBpd+Kepi4AwLv9Iwk+mpnJF0MmnL+rEUdvrsPle5uw30zCZjSgDE2CIAiCIAgiYjweD1wuV6IPY9aiUqmgUCgSfRgEQRDEHOX2hk5YPQIAYI/JBptHgE5B3rhw+GLILP//O30jeKdvBKdkp+G6slwsSNIl8MhmNiRoEgRBEARBEGHDGEN3dzeGh4cTfSiznrS0NOTl5U0ajk8QBEFMjXa7EwYFj3QVSSWA11n4Ru8weAB6BQ+zR8BOkxWHpSUl+tBmFDuMVgDAj4uz0Wl34a2+YbzVN4y3+4bxzJJyHJeVmuAjnJnQq5SIKRaPB2/1DuOUnDQYyF1AEARBELMGSczMycmBXq8nsS0GMMZgtVrR2+vNLMvPz0/wEREEQcxemm0OfGPzAfAALinMwpUlOchWqxJ9WAnDJTDcfLADAHBxYRb6nC683TeCLSMWEjTDQGAMO0wWAMDZuelYkqzHfrMNv6hrwzajFV8Nm0nQjBASNImYcvuhTjzbOYAWmxO/qqBFOEEQBEHMBjwejyxmZmZmJvpwZjU6nXcUrbe3Fzk5OTR+ThAEESO+HDLDIXhbvB9r68PTHQO4VBQ2s9RzTzp5sr0PB612ZKgU+FV5Hl7uHpQFTSJ0Gm0OGN0CtDyH+QbvNX1Bkg4nZKVim9GKfqc7wUc4c6HgAyJmWD0CXusZAgB8PWye5LMJgiAIgpgpSJmZer0+wUcyN5AeZ8oqJQiCCA2BMTDGwvqa3SbvWPAxGclYnqyHTRDwaFsv1m6sxeY5dj/b43Dh/uZuAMAtFQVIUymxOtUAANg6YoEQ5mM7l9kujpsvTdZDxY9Os0gi+YCLBM1IIUGTiBn/7R+BWQwP3mWywiXQSY8gCIIgZhM0Zh4f6HEmCIIInV0mK0o/3S0LcqGyV2yePjcvA++uqsZzS8qx0KCF1SPgyY7+WBzqtOV3DZ0wewSsTNHj/PwMAMCSJD10PIchtweHrI4EH+HMQcrPXJEydhM4S4wzGCCHZsSQoEnEjJe7BuX/twkMtRZbAo+GIAiCIAiCIAiCmO283jMEF2N4qr0/ZFONhzHUioLm4iQdOI7DsVmp+G1VIYBR9+ZcoNnmwKs9Q+AA3F1dBF7cVFPxHJaLohyNnYfOdqP3sVqRPFbQzBSLp/rJoRkxJGgSMaHT7sSnQyYAQI1eC8BrTScIgiAIgiAIYnL+0TmAW+vbabSTIMJk64hXfBxye/DlsCmkrzlkdcAmMOgVPCr0Gvn9S5K9mYdNNieMbk/0D3Ya0iC6LxcmaWUBU2JtqrcMaDPd24eE3SOg1mwHAKyc4NAUBU2nO+x4BMILCZpETHi1ZwgMwPpUA07LSQMAbDPOnV2tmYqHMVy+twnX7G+hkypBEARBiLz++uuoqqqCQqHAz3/+80QfDjEF2u1OfGvLAfyjcyDRhxIUxhh+e6gDf2vvl8dgCYKYHLtHwC4fN+VbvcMhfd1e8WsWGXRQ+MR8ZKiUKNaqAcwdl2a3w5vXnK9RT/jYalGUI7NSaOwz2+BiDJk+zyMJyaHpZAwmMaqPCA8SNImowxjDS93ecfNz8zOwKtV70ttGJ71pzx6TDe/0jeDl7iF0OaZ38YDVI+DLIRMJrwRBEETM+fGPf4yzzz4bbW1tuOOOOxJ9OMQUeLV7CPvMdjza1pvoQwnKoMsj3+C22Z0JPhqCmDnsNlnhZAySJPlu/0hIY+d7pHFz0ZHpy1LxfbtNc2NzQboPzBMzHn2RioEabA5q5w4BqRBoZYp+Qh62XsHDoPBKcvRYRgYJmkTU2WG04pDVAR3P4ZTsNKxMMYAD0GJ3os85vUWyuc6mkdH2vul+wf59UxfO2tmAf/hktRIEQRBEODidkwtFZrMZvb29OP7441FQUIDk5OSYHQ+1mMeerWKW2SGrY1qvS1t9RMwOEjQJImSkUehjM1OQoVJg0OXBVyE0lO8V732WJE0UNJeJ2YdzzaGZp5koaKarlBQpFwY7TP4LgSSyVNR0PhVI0CSizouiO/Ok7DQkKxVIUSpQLZ70ttPY+bRm0/DoRWnXNL9gfzrozcP5YMCY4CMhCIIgGGOweDwJeQvHqX/00Ufjpz/9KX7+858jKysLxx9/PB588EEsWbIEBoMBxcXFuPLKK2E2e29+P/nkE1nA/OY3vwmO4/DJJ5/g6aefRlpaGl5//XVUV1dDq9Xi+OOPR1tb25if98Ybb2DlypXQarWoqKjA7bffDrd79KaF4zg89thjOPXUU2EwGHDXXXdF4a9BBIIxhm3G0bXOdM6Aa7WPNgi326ev8EoQ0w1p02J9WhJOyk4DMPnYOWNMdmguIYem7NDM9yNoAsBa0aU5nc+h0wWpEGh8fqZEppyjSef5SFAm+gBihdlsxh/+8Ads2rQJmzdvxtDQEP7+97/jkksumfC5+/fvx7XXXosvvvgCarUaJ510Eh588EFkZ2fH/8BnOHaPgDfEC8a5eRny+1en6nHQasfWEQuOz0pN0NERwWCMYZPPRWnPNM5rMrs9qLN4w5U3jZjBGJtg4ScIgiDih1UQUPnZnoT87IajlsCgUIT8+c888wyuuOIKfPnllwCAd999Fw8//DDKy8vR2NiIK6+8EjfccAMeffRRbNiwAXV1dZg3bx5effVVbNiwARkZGWhubobVasVdd92FZ599Fmq1GldeeSXOP/98+ft+/vnnuOiii/Dwww/jyCOPRENDA370ox8BAH7729/Kx3Pbbbfh3nvvxR//+EcolbN2aT4taLY5MegaLfXYOGyWBY/pRqvNx6HpIIcmQYQCYwxbxEKgtakGLE7S4bnOAfynfxj3CkVQ8v7vF9rsToy4PVBxHOYZtBM+vlR0aDbaHDC6PUhRhn7NmYl0i9ML/hyagPfe/vmuAVk8Jvwz6HKjWTyXL08O7tCkpvPImLWrpv7+fvzud79DSUkJli1bhk8++cTv57W3t+Ooo45Camoq7r77bpjNZtx///3Ys2cPNm/eDLV6YhAuEZj3BowYcXtQqFHh8PQk+f2rUgz4R9cgFQNNYw5ZHWOs7tN5pGKXyQrJjzPo8qDe6kCNn8UHQRAEQYynuroa9913n/zvefPmyf9fVlaGO++8Ez/5yU/w6KOPQq1WIycnBwCQkZGBvLw8+XNdLhf+8pe/YN26dQC8QumCBQuwefNmrF27FrfffjtuvPFGXHzxxQCAiooK3HHHHbjhhhvGCJoXXHABLr300pj+zoQX6eabByBg7GTKdMN35JwyNAkiNBpt3vsZDc9hSbIOCnDy2PnXw2YcmeE/MkQq3ppn0ELNTxxizVApUaRVod3uwh6TFYenxy56ZDrQ7fDeEwYSNKWm810mKxyCAI2fx4zwRvEBQKVOgzSVf+nNt+mcCJ9ZK2jm5+ejq6sLeXl52Lp1K9asWeP38+6++25YLBZs27YNJSUlAIC1a9fi2GOPxdNPPy3vpBOh8ZKYZ3h2XsaYdjipGGiH0Qq3wALujhGJY6OYn7kiWY9dJit6nW50O1wBL2SJZHx0waYRMwmaBEEQCUTP82g4aknCfnY4rFq1asy/P/jgA9xzzz04cOAAjEYj3G437HY7rFYr9Hr/jgoAUCqVY9aX8+fPR1paGvbv34+1a9di165d+PLLL8eMkXs8ngnfe/Xq1WEdPxE50sb6KTlpeKN3GHvNNpjcHiRPQ7fVGIcmjZwTUebdvmEY3QLOy8+Y/JNnEFvEabNlyXpZZDsxKw3Pdw3grb7hgILmHlPgcXOJZcl6tNtHsNtkm9WCpkMQZJOLv1IgACjXqZGpUmLA5cZukw1rxBF0YiySoBkoPxPwcWiSoBkRs1ZK12g0Y3bRA/Hqq6/i5JNPlsVMAPj2t7+NmpoavPzyy7E8xFlHr8OFT4a8eYbn5qWP+ViNXotkBQ+bIOCAZfqOMs9lJJfC0RnJsjg4XV2aO8XjylB5b0Cms8OCIAhiLsBxHAwKRULewo0cMRhGb7yam5tx8sknY+nSpXj11Vexbds2PPLIIwBCKwwKhtlsxu23346dO3fKb3v27EF9fT202tFNON/jIWLLNlHsOCk7DSVaNQRM31IL3wzNAZcbVrHxnCCmypDLjR/ua8bPDrTOusIpSdD0FdhOzvHGnb3TNwJ3gLZzueHcTyGQhFQWNF3vj6JFj5ifqeE5+V5rPBzHUY5mCEj5mUEFTTWNnE+FWStohkJHRwd6e3v97oyvXbsWO3bsCPi1DocDRqNxzNtc5+NBEzzMmw9RqR/rluM5DitTvCe9rTR2Pi2RHJrr0gxy8PV0LQaSHJoXF2QBGD12giAIggiHbdu2QRAEPPDAA1i/fj1qamrQ2dkZ0te63W5s3bpV/nddXR2Gh4exYMECAMDKlStRV1eHqqqqCW/8LBzP++2hDqz8ah9abI7JPzkBWDwe1Iqb6qtT9FiX5l2XbpqGN+MexuQiIEmun23CE5E4Ph40wS3qevVWe1x+pktgaLLG/twgiWtrfQTNw9OSka5UYMDlDnjPEKzhXGKp3HQ+u805UsN5rloVdMNwtfgYT9dNoUTDGJNNOJIO4o8s0QU7QA7NiJh9q6kw6OrqAuAdTx9Pfn4+BgcH4XD4P/Hec889SE1Nld+Ki4tjeqwzgU3iBeIIn+xMX6Sx820UHjzt6LA70W53gQewOsUwrS/YXQ4nuhzeY72sKAsKztv+2U4LfSICPIzhtZ4hDNKuKEHMSaqqquByufDnP/8ZjY2NeO655/D444+H9LUqlQpXX301Nm3ahG3btuGSSy7B+vXrsXbtWgDAb37zGzz77LO4/fbbsW/fPuzfvx8vvvgibrnlllj+SgnBwxhe6BxAp8OFP7f0Jvpw/LLLaIOHeVt7C7RqrBcz4DYOT79N0S6HCy7GoOI4VOk1AKgYiIge7/ePyP/fEAeREQBuOtiOwzbtx4cDsTMBDbncqBd/n9U+ApKK53BCttel+aaftvM+pwvdThc4AItCEDQbbA6Y3J6AnzfT6XIGbziX8HVoMubf+TqXabF7S+jUHIdFSYGj0TKpFGhKzGlB02bzijUajWbCx6RRIOlzxnPTTTdhZGREfmtra4vdgc4QpLHfdQEyNFaJF5ZtI9PT9TeXkdwJi5N1SFIqsHQaj1RIWSTzDVpkq1VYkuRdXGyahjckxPTn3z1DuLK2BZfvbUr0oRAEkQCWLVuGBx98EL///e+xePFivPDCC7jnnntC+lq9Xo9f/epXuOCCC3D44YcjKSkJL730kvzx448/Hm+//Tbee+89rFmzBuvXr8dDDz2E0tLSWP06CeOAxQ6zOBL9r55B9DqmX+ajtKG+Shz9kxyaO8RSi+mElJ9ZpFWhROu9T2mnHE0iCrgFho8GTfK/G+MgaHY7XHixewAA8E7fcMx+juQUrNJrkKkeWxVySnYaAOA/fSPwjBPfpPzMSr0GhiB5ullqJQpFkW/PNDR9RAtp5Dx3EkFzabIOGp7DgMuN+5q68d++ETRZHRMe37mKdM+6OFnnt2hKgkqBpsasLQUKBZ3OK9r4c2Ha7fYxnzMejUbjVwidq/Q6XGiwOcBhrMXfl5XiArLR5sCA0z3hQkMkDsmdILkVFiXrwAPocbrR43BNekGLJ9vHhSuvSzNgp8mKTSMWnJU3u4LNidgjtVp+PWzBl0OmWR3yThAE8Mknn0x437XXXotrr712zPsuvPBC+f/T0tICuk/OPPNMnHnmmQF/3vHHH4/jjz8+4Mdni6vFN0PNITA82dGPmyomTkAlklFB07tOrdRpkKVSot/lxk6jFevS/E8YJQIpP7NEq0GR1rsGo5FzIhpsHrFgxMdd2BiHiIhnO/vlEfevY2hAkPIzV/sZ7z0iPRlpSgX6XW58OWTGUT7lQHtDyM+UWJqsR4djBHvMVmwIMJU40+kSBc38AIVAEhqex5oUA74YNuOhlh75/Vqew0nZafjLgpKwM65nE1J+5sog+ZnAaCnQoMsND2NjipWJyZnTDk1p1FwaPfelq6sLGRkZJFqGiOTwW2DQIlXlX6hMVynlsZntNHY+rZD+fpJbwaBQoErMQZ1uOZrSbpeURbJeFNA3UjEQEQHNPgv5+5u7E3gkBEEQM5fRZmGvIPB0Rz8s02gkkzGGreKEkJT7xnFcQnM095ttAR+jVlG8LNGpUaRVAwDaSNAkosD7A95x8zKd93kV65FzpyDguc4B+d9NNic6p/hcHnG5/ZbM+svPlFDxHE7NSQMA/OZQB5w+rmxpIi00QVOaYpu9Dk0pQzMvBEPLnxaU4NcV+Tg7Nx1LknTQ8hzsAsOrPUPyeWyuIjecJwcXNDNE7UQAMOSaPtfNmcKcFjQLCwuRnZ09JtBdYvPmzVi+fHn8D2qGskkulAm+UyWPnVMx0LRh0OVGncXrSPZdAEzHC7ZnTLiy9+KwVnSVHrTaKQeRCJtm2+hi6+thC74aougCgmBitux0LXchph+SoHlTRT4qdBqMuD14oWtgkq+KH612J/pdbqg4bkzpxzp5UzS+5/5XuwdxzJY6/Opgu9+PSyPnJdpRQZMyNIlo8IGYYfnDomwAXqHc7old5MJbvcPoc7qRp1bJOYJTdWn+pLYFR2+uw6Oto3m9TkGQ7xHWBJgWvKE8H5kqJQ5Y7HioedRRKDk0l0wiPAG+xUCz915WdmiGIGgWatW4ujQXf1lYivfXzEPDUUuxXHyM5nJZkN0jYI/4vApWCAR4xfZ0Meqg30XRIuEypwVNADjrrLPw9ttvj8nA/PDDD3Hw4EGcc845CTyymcVk+ZkSUm4RFQNNH6SbkGq9Btk+owXLpuEFu95qh8UjQK/gUWPwLooy1UpUi87fzeTSJMKAMSYLNt8QR80fIJcmQeCzITOurG3BVbUtiT6UmGF2e9Bmc8IVYXbiJZdcguHh4ege1Ayl2+FCm90pFwteUeIVSv7a1geXMD1G6qWN9MVJOmgVo7c/68WN+C0jlrjlvo243PjtoU4AwCeDJr+xA5KzqVirljP7KEOTmCpNVgfqrQ4oOeDs3HSkKHkwAM322G1ePdnRDwC4qDATR4lrra+nsF4XGJMd1b9r6MTjoqi512yDXWDIUCnkicDxZKmVuLemCADw59Ye7DFZYXR75M3tcByah6wOmKeRCz2adDtDd2iOR8FxskFmLhuYNo6Y4RAY8jUq2Q0dDClHk5rOw2dWC5p/+ctfcOedd+Kpp54CALz11lu48847ceedd2JkxGu3v/nmm6HX63HMMcfgz3/+M+655x6cc845WLJkCS699NJEHv6MweT2YJ+4A7F+EoemNOaz3WilwOBpguRKWJc69m83HR2aUn7msmTdmHwR6Xm3cYTcdUTo9DjdsAkMCg64b14RVByHL4fN07LxliDiyUHRtb/NaMXwLHW+dzicGHS50WJ3zpocy0QhjXkuSvIWC56Tm4EslRIdDhfe7B1K8NF5kZxCq1PHOrAWJemQpOBh8gjYb47PeucPzd1ym22/y40OPwVKkkOzVKeRHZpdDietnYNQZ7Hj2C11eM+nwZsYizRuvj41CakqJSp0XnNArIqBdhit2G60Qs1xuLAgE4eJ6/WvprDO6nC4YPVxlN7W0Im/tvWOyc8Mltt4Sk4aTslOg5sBPz/Qip3ivUWhRhVSv0O2WoUCjQoMo87O2QRjLKyRc39IU3Rb57CB6aMBb/HWMRnJIeWIUtN55MxqQfP+++/HrbfeisceewwA8Nprr+HWW2/FrbfeiqEh7wKruLgYn376KSorK3HjjTfivvvuw4knnoj333+f8jNDZMuIBQKAUq160hPfPIMWBgUPi0eQb5jmKv1ON7aNWILeSAmMYfOwGaYY7gCOz8+UWJykAwfvLt10aSvdKWeRjD1WyRm8iRyaRBg0ie7MIo0apToNvpvvLZUilyYx12kXR1sZJh8NFKZZO3QoOAQBdo/32mtxC+hxTo9rXDAieZzrLXa0xyHDbIu4mShtWmsVPH5QlAUAeLStd1LBuNPuxKeDppiKdeMLgSQUHCePp26Mw3hkrdmGp9q9jrVUccRw5zgXk90jyA6pEq0auRoVlBzgZqPtw8REnmzvwx6zDX8XHYHERN7r946bH5uVAsDb6g3ELkfzyfY+AMCpOWnIVquwLtUAHt4iou4In8tSTNY8gxbXluYCAH57qFMePw80bu7L3TWFyFApsM9sxw0HvVOai5Mnd2dKjJo+Zp8DccTtgV101udOUgoUCOlaUGu2jRGf5xIfD3pfa9/MSAnp8zOp6TxiZnXNdHNzc0ift2jRIvzvf/+L7cHMYgIJYv5QiNlFG0cs2GO2YUEI1v7Zyo/2NeOrYTOuK8vFDeUTm0AFxnBDXTue7xrAuXnpeHhBadSPweLxyBfj8XEBBqV3ZKPe6sAukxXHalKj/vPDZbtxbH6mhJTduttshcXtgUG8SSCIYEiFQGU674L+6tJc/LNrEJ8PmbFp2DytGm8JIp74til/PmTGCdlpEz5HrVaD53l0dnYiOzsbarV6xrSZDjhdYE43FBwHD2Podjqgcrmm5bWDMQan04m+vj7wPA+1evLRNQDodbhw3NaDSFby2HLYQmj42HkYtohlO7453BcXZuHh1l7sM9vx6ZAJR4+7qeu0O/F23zDe6h3BFlFs/FZGCh5fVIrkKP8dbB5BniRa5UfsWJdqwMeDJmwatuAHYq6gW2B4u28YNkHA+XkZUXluM8Zw88F2CABOzk5FmlKJ57sGsNNkxcliWQkwuqFgUPDIUCnAcRzyNWq02Z3ocLhQoA3tOTDX+HTQ64jab57bholAGN0eeZLpuEzvmr5CFztBs8/pwpu9wwCAy8QNjlSVEouTddhtsuHrYTPOyE0P+/se9BE0byjPAwPwx5Ye9IhCUCiCZrZahburi/CT2hZ53HxJ0uT5mRJLkvT4b79xWk2xRQspPzNdqYBOEdl1o1CjQq5aiR6nG7tN1kknOGcbrTZvtIOCA47KSA7pa6SmcxI0w2dWC5pEfNgkujdCPVktFAXN2llo0w8Vi9sjFyk92NwDDsAvfURNgTH86qBXzASAvTG6YG4fscLNgAKNCsV+FsjLkvWotzqw22TDsVmJFTStHgH7xUbDFeMETSljqsPhwjajNeSLx1xBYAw313dgnkGLSwuzEn040wZpEStl2xRr1Tg/PwPPdQ7ggeZuvLy8KpGHRxAJo8Mnq++LAEVZPM+jvLwcXV1d6OzsjMtxOQUBJo+AVIUCSj5yganX6YJDYEhTKuBmDGaPgAHO60ZRTFNRVq/Xo6SkBHyIwuQHg0bYBAE2p4CPBox+ReloYPUI2GueWMSRrlLie/kZ+Ft7P362v1XeOAIAi0cYM6rJAVByHD4cNOLk7fV4dkk5SnXRm5LaZfKudXLUShT5mSRa5xNb4xYY/t07hIeae9AobnpZPQIuF4XOqfBazxA2jlig43ncVlWITwZNeL5rALvGubxafAqBJCG1SKtCm92JdrszJMFmrtFic6BF3Ijpdrow5HIjXUW3ub58MmiCmwFVeg3KRWem5NBsjEEB3POdA3AyhhXJ+jGlKIelJWG3yYavpiho1ui14DgOvyrPg8AYHm7thY7n5A6AyTgtJw1v9Q3jnT7vGP6SCBya41+7s4GpjpsDAMdxWJ1qwDt9I9g6YplzguZH4ubKmhQDUkLcoJMzNGnkPGzoTE9MCbtHkF1z61NDO1ktEl2Zc3kHdavRCg8DNDwHh8DwQHMPOHD4hXhRvvFgO57rHG0HbRMzvqLtfpF2atel+s+bWZqswys9Q9htTvwFe4/J+5jlqpUo8HORXZ+WhFd7hrBxxJxQQfO39R3YbrTixWUV08bts89sw9Md/UhS8EEFTYExDLo88kV1tjPeoQkAV5fk4J9dA/hsyIztIxaspBtHYg7i26Z80GpHj8OFXD/nXbVajZKSErjdbng8sS1HsLg9uGhPI3qcbpyfl4KfiqOG4TLodOGiHYfAALyyvBypSiV+vK8ZjTYHVqUo8OD8kmknaioUCiiVyrDWAB+JTcYA8FrPcMwEzR1Gi7wxWjRuY/RHxTl4tnMAPU637J7yZV2qAafkpOGk7FT0ONy4eE8j6ix2nLDtIP6+uBzr0pLgYQxfD5vxZu8wPh404YSsVPyuujCsY5SKKQJl661I1kPNcehzurF+U61cvqNX8LB6BNx+qBNrUg1yu3EkmNwe3N7gFf5/XpqLIq0ay31EEYEx8OKxSYVAJT5FEoUaNQBLXCIEZiKSO1Niv9mODelzS0SZDClb9NuZo27pWI2cuwSGZzq89zGXF41ddx6eloS/tvXhqwCbZZPhO3IOeMWzmyrysSBJhwyVMmRXIcdxuLemCBuHLbB6PBOmv4IhiaaHrI5ZNxnWNYVCIF9WpngFze1zsBhIuv5+MzO0cXMAyBLH+8mhGT5z466ViBk7TVY4GUO2WonyEBq8AGBBkvcCVGuZuw5NqXTklOw0LEjS4Y6GTtwv5vb1OV14tnMAHIDf1xThhoPtMHkEjLg9SIvybvNGqZ0+wM7ZUrnpPPF/q9Fxc/83JOtSDXi1ZyihOZpWj4AnO/rgZsCnQyacGKMbyHCRbo7MHiHowuvW+g481dGPd1ZWzwkhT8rQLPcRNEt0GpycnYbXe4fxwaBxTjwO0wXGGL4YMmNhki6kYH4iNjgEAb3igrpIq0K73YUvh804M4CThuM4qFQqqFRTu/mZjN/UtWGb3QOAw26HB1qtNqLv8/GgBW0Ch6XJOpSlem827lxUgeO3HsQbwzbM6xnBdWV5UTzy+OMWGD4bGhV43h8YgcntifooN4DRIg4/58pirRr/W12DQ5axYgnPAcuT9WNGp/M1avx3dQ0u3t2E3WYbztnZgFNy0vDZkAl9Pjd4f2vvw+VFWWE5OLeJx+hv3BzwZn4uT9Fj84gF7XYXMlQKXFGcg0sLs/DT/S34b78RP9rXjPdXz4v4MXyguRu9TjcqdBr8RGyBn2fQQctzMLoFNNkcqNR7n9Ot4rWpVDv6O0pTNCRo+ufToXGCpsVGgqYPHsbwkZjpJ42bA6Mj5wMuN4Zd7qjdZ/y3fwTdTheyVEqc4hOnAIgmCgANNkfAzbJAMMZw0Co6NA2j1wCO4yJye2arVfhwzTyYPR5kh5EXmaNRIU+tQrfThV2m2fVci4ZDEwBW+xQDxcKUM11xCAK+EO/zvxmGwUYqBSKHZvjM6lIgIvZI4lEgh58/5hm04AD0Od3omwFB/LHAN3f0qpIc3FLhHTe/v7kbz4hi5h/nl+Ciwiw5U6MtyovYYZdbHns/Kt3/CXeJWAzU5XAl/G+1QxzrGD9uLiGJstuNFjgTVFKx0+gdawNGb/KmA743QH1BLpRbjRYwQM4zm80wxmSHZum4zRjpubRjDu4qJ5L/a+/HObsa8Ov69kQfypxGys/S8hxOETdlPh8nFsSbzwZNeNZnaqFpCuOR74oupRN8YlRqDFrcW1MEwCs8dc5w0Wib0QKjW0C6UoFKnQZ2gcm/d7Txl5/py3yDDifnpI15OzE7zW8OZL5GjX+vrMJJ2alwMoZXe4bQ53QjTanABfkZWJmiBwPwVBilL4wxuWl3VRAH1k9LcrA0WYebK/Kxef1CXF2aiySlAg/NL0GhRoVmmxO/qGubtODIH512J/5PLEe5s7pQzjNV8Zw8tbTLZ+PYr0NTfLz8NaLPddwCk6MxjhSFpQNzvHh0PNuNVgy6PEhVKsZEFhiUCuSJQl6oY+ebhs14vLU3aInXi12DAIAL8jMm5PemqpRYLD7vJyudG0+HwwWLR4CSGxVjp0qeRoUqffgbZJKI+b+B8M6tDVY77mvqkjcuphuyoBlhIZDE0mQ9lBzQ63SjfQ6dtzYPW2D1CMhRK+XzeyhQhmbkkKBJTAlpZDmcbAyDQiFfhGrn4Ni5UxCw3SgJwd7H7aelufi1KGpyAB6aX4zzxMblohjtyn8wYISbeQXmCr3/RYFUDAQk3qUpPWaBRkJq9BqkKRWwCUweR4k3viLmdBU0gzXWS66sueAAGXJ7YHR7he/xTh/pObbDaI3o5pXwT7DHssfhwu+bugDMzkyqmYT0+i/UqHGkuNkVKEczHpjdHlxX1woAOE4c32q2OSNqxDa7PbI4e0L22Fzo8/IzsDbVAA8D3hCLLGYqUn7X0RnJsrP23z1DUf85go9YGK1cR4NCgb8tKsNvKgtwUUEm/rm0AnsOX4wH55fIztl/dg3A4g4t4uDDQRN6nW6oOS7oyPhxWal4b/U8XCMKmRLpKiWeWFQGJed9XvjGAYXKM50DcDNgfaphwgjicvGYfJvO23wyNCWKtF5xYS5cn8Nll8nqnWJSKnBennftfGAO3l8EQxo3/2ZGMlTj8ocrwhg7dwkMP9jXjNsaOvFqgHNKj8MlNzxL9zLj2SDeN34VpqAp5WdW6LQTfo94c7J4DXm7dzjktaLF48H3djfiweYeHLOlDs929E+7daYkaOZP0aGpU/CyoLdtGt0TxZoPxef+MRkpYblSpbivfnJohg0JmkTEeBjD1pFRh2Y4yGPnc7AYaLfJBrvAkKFSoNpHSLy6NBcvLK3AayuqcH5+pvx+acwo2g5Nfy4Vf4yOnSdOZOhzutBud4EDAoZ9cxwnL8paE7Tg3+xzwd5tssHuSYxTdDztPgUfvQF2/gTGZBeubyHIbKVZXLjnqVXQj8tbWmDQQsNzGHZ70GSjm8docHdDJ1Z9XStvTIznjoZOmMXXS5vdCZcwvRb4cwnp9V+oVWFdqgFKzvs3aUmQm+SOhk60210o1qrxyMJSqDkOLsYiEnY+GjTBITCU69SY58eRI4t/vdEX/+KJb36XNIbpHd2O7rn9oNWOEbcHOp7HIkPoTpTJ4DkOV5bk4L55xTgmM0UWLr6ZkYxynRpGt4BXQhBo7R4Bt4iO78uLsiac60NlVaoBN1cUAABuPdSBPWGsh+weAc91eh2lP/BTLLRM3EDb6fM9pXIb37JGb4amV9CcbgJIopHGzQ9PT5IFlAMWGz1OIg5BwEvdXsfk8X7W/HIxUAiC5seDRjkC4sn2Pr+P8as9QxDgHTmuDOB8PEwUNMN1aI7Pz0wkx2SkwKDg0eFwhTzRc29jF5ptTvDwlqPdcLAd5+9qnFYbFdEaOQeAVWIZ1NY5MPkl8dGA93z0zczw+hwkQXPE7UnYpOFMhQRNImJqzTaYPAKSFTwWhmGpBiB//r5ZIGgesNjCcuNJ+ZnrUpMm7Nx8KzNFvshLxELQtHkEfDzo36UyHqnJL5Hjt1J+ZrVeGzS/SnIztCRAhPJ1qig4wMnYtHGahTJyPujyyOPy02lhFSua7WMbzn1R8zyWJEnP+7mzCIsVjDG80DWITocLF+9pmnAu2zRsxis9Q2LTMeBmY0tpiPgiPfaFWjUMSoV8Q5IIl+YXQyY8IzriHppfjGSlQo6ICOXmezz/FTfyvpOV6tc5cUp2GpScd0PqkHVmOrx6HS7sEddWR2cko0KvwfJkPTwMeCvKzlNp7bMyRT+l1vlQ4TlOLrZ7KgRn0+NtvWi2OZGrVuL6Keai/qQ4G9/OTIFDYPjOtoM4b2cDXugcwOAkbpo3eocx6PKgUKPCd/yISZJDc4/JBrfAMOJyY0R0n/o6NKWRc7NHgDFEd+pc4VMfR3KVXgsVx8HkEebUmGswXu0eQq/TjQKNCif6WfNXilMqDSFsWknCKOCNSRhf+MIYkz8nkDsT8EZucQDqrY6gk0PjGc3PjM64+VTQKXgcKzqu3+wbnvTzNw2b8X/t3s2NZ5dW4HdVBdDyHD4dMuHozQfwh6YuPNHWK7/9ra1PdqTGE6kUaKoOTWA0W3nbSOLvhxhjeL9/BPtjqD202504aLWDR+A4t0CkKRVQiJdRytEMDxI0iYjZ5BMEH24jqNx0PsOLgRhjOH9nI07fUY+GEG9+NoXpai3WRV/Q/HzIBKtHQIFGhaWTiNFrU0fHQhLlmpKaEANldElIi/9EODR9nSpSg+R0GTtvC2HkvNfHudM+B8SkJuvEhnNfpKzW6dLOyBjD850DeKy1N9GHEjZdDpe8OOtzunHh7kaYxBtyt8Bw00Gvg+p7+ZlyjlUkYpUvgy437mjojLqzfS7QKTk0RUfY4WJO2BdxztG0eDy47kAbAOCigkwcId4cyG6iMB2jTkHAB2LWWaDCtky1Et9I956/YzGiHQ+kzcqlyTq55OLM3DQAwL97hqP6s6Rr3GTX5mhyfn4m9AoedRY7vgzi7mqzO/Gnlh4AwG+rCseMkUcCz3F4eEEJ1ouxBJ8OmXB9XRuWfrkX393V4Fd4YIzhyQ5vdubFhVl+Rd8qvQYGBQ+bIKDeapfXL1kq5ZgCP72CR4bK+28S6kYxuz3YJm48HpXuHaeWopJiKVzMFATG8Fibd93ww6JsqPmJt/4VITo0B11uvN/vdX9LebRPjsuz3W22oc5ih4bncGqQYsx0lRILxWm9cMbOpddZzTRwaAKQC4/e7gs+dm71CLj2QBsYgO/mZ+DbmSn4UXEOPlwzD6tT9DB7BDzQ3IPfHOqU32491IHv7mqAO473Xi6ByRmO0XFoep8ne82Jn1r7b/8ILtzThGO21OHyvU0xOT9IUQurUgxID7Ngi+c4uRiIcjTDgwRNImIkp+H61PCb3RaIF6KDFse0GC10CAJ+tK8ZNx5sD2tEpd/lRrfTBQ8DXgvh5kdgTL4BCDV3NBYOzXcncan4sixZh0yVEmaPkDCBTso8O2KSFsESUZxKRND21pHR0qLDxNfEdCjXMbs9GPZxc/QFuEj6CpqDLg8sntntAGm2T2w492Wl6ErbMQ1ctnaPgJ/ub8Uv6tpwe0PnjHOOSfm7xVo1ctVKHLDY8aN9zXALDE939qPWYke6UoGbKvLlv8dUSl8A4E/NPXiktRcPNHVP+fjnGqMOTe/NjJyjOWyO6wjnxwMmtNqdyNeo8JvKAvn9kT5Hvho2w+gWkK1WBi2HOcNH/JuJI6tSk/G3MkazGk/LSQcH7zUpmtEB0pogWvmZoZCiVOAccYz+yfbA5UC3HeqATWA4LM2AM8a1LEdKhkqJ11dW4+t1C3BzRT4WJ+ngZl4R+cLdjROck9uMVuw22aDhOXzPJ0rIF57jRidhTFa/hUASUqZ6B23UyHw1bIabAeU6tZyHvUAeO59Z18pY8P6AEfVWB1KUPL5f4P85WOmToRnsnPd6zxCcjGFxkg53iyVqb/UOj9kof0ksAzohKxWpkwg6G8IcO2eMyYLmdBg5B4BvZqRAr+DRbncFXS/+vqkLjTYH8jUq3OZzPavUa/HGymrcU1OEM3LSxrylKhXocLjkc3o86HW6wACofMS1qVCiVSNLpYSLMXlyIFH4ZmO/0zeCY7bU4Yd7m6MqbEY6bi4RTtO5hzEqLxUhQZOICMbYmKbucCnWqpGk4OFibFrcnD/R1oc3e4fxdEc/XuganPwLRJp9RptDufmps9gx7PbAoODlhr/JKJZLgaKzI+8WGP7XL7lUgo+bA97F9jEZ3hNzPC+qEv1ON2rFBczhkwiapTHKGw2FzSOjLlLJrbJlxJLwG+Lxj0VvgAy1HsfYi2fnNMrR7Ha4oi5SN1u9j8v4hnMJyaG512SDI4FZNn1OF87eeWhM+P7eBBd0hYsUvbAhLQnPLKmAjufw8aAJ19a14j6xCOjGinxkqpVyBEDzFP/e0ibIHjMt9sJFipwoEh2aK1P00PEc+pxu1MXxei2JEd9ITx7jrgunwMKXd/tGN/L4IBt538lKhY7n0GhzjGmengm4BSaP3/qWz+RqVDhcFA9CKTxqtTnkHLVA9DldaLI5wSF4e3gsuEzMovxf/4jfa8Mng0a80zcCBQfcXV0UVjFDKJTrNbimNBcfrJmHL9bNR7FWjRa7E9cdaB1zzX9SbDY/PScdmerA4oBvMVCLn0IgiVhlqs9kPhGf777jnZJpghyawKPiVMdFBVkBI5tKtBooOMAmCOgK8rp/udu7DjkvLwPLkvVYnaKHizE8K8aCOARBdrafmxd43Fwi3GKgLocLpig3nE8V37HzQJEeW0YseKLNey74w7ziCUKvQozSeGxR2Zi3C8SR/UiKyCJFOu/nqJVBr5OhwnEcVqd6z29bEzi15hAEfCBmSz84vxiniO7ht/qG8c0tdXJp1lRwCoK89jwmI2WSz/aPXAwUgkPzv/0jOGHbQVyypzGinzWbIEGTiIgDFjv6nG7oeE5eiIUDx3Fyjmaii4E67E482Nwj//u2Qx0hZwj6Oh1CufmRdiFXpxhCzpuSmi1H3B6MRCFTY4vRgkGXtw1yXYjuWlnQHIi/oCktdBYYtPL4XCBKfMbzhTgLib5OlcXJOmh5DoMuT0iZRLFk/HM5UCnQeKFzOuRoehjDY629WLexFt/cUhfV3DDZoan3vygu1aqRoVLAyVjCsn5rzTZ8Z+tBbDVakapUYI3oGt07w27SJIfm0mQdlqfo8cjCUnAA/tU9BKNbwNIknewcGR19i/z51+d0yZsgBy0OClcPA8YYOhxSKZD3fKrheTl6JJ45mqNZaWOdOJE4NAXGxuRnBiNJqcBx4ufMtLHznSYrht0epCoVWDFubSYVHgWaJmm2OfDnlh4cu6UOazfux8qv9uGOhs6AY4LStXmeQTupEyvazDNocVR6EgQAT3eMvdl3CgJuqe8AAFxWmCW79WJFlV6Lvy4qhYrj8HbfCJ4WxYcehwtvibl6lxdlBf0ey0VBeJevQ9OPoCnFQMyF4r5Q+UwUEL6RMSpoSu69/XPcobl1xIJNIxaoOc5vIZWEiudQqg0e5VFnsWOnyQolB7loTPqez3b2i5EeRgy5PchTq8b8PQIhTarVWx0YCEHAkQqBynUav6PziUISx97uG5lgYrB5BFx7oBUMwLl56XIkVShI66IPB4zojNOavCtKDee+SDnc2xI4tfbVkBlmj4ActRLn52Xgb4vL8PGaeViXagCD9zGeKltGLDB7BGSplLLrPlyyQhw5Z4zhEXGzYkEUC/lmKtPnbEDMKKQFxPq0JGgjbI2UBc0ELzhub+iETRCwNtUg55j8sq4tJGdd87jymclufiJxtRoUiqjmJkkulWOzRptDJ+PojBRw8P6tJnNtRJsvQhw3B4ACjRo8ALvAAgp3sUByqgBep4qa52Whf3OCczSl50yuuOsXqOV2vKDZkeCMrgarHadvP4TbGzrhEBjMHiFgQ3a4mN0eefS+zM9NI+DddFmRLI6dJ2Ck44shE07ZXo8OhwsVOg3eWVWNc/O9NxEzqUyNMYbdoktymfiaODE7Dbf4jFzdXVMk5zBLYtVUHJq+bg+Xz4gaMTnDbg+sooDle0NzRAJyNOsCZKVJ45FtdmfIkTU7jVb0ON1IUvAhXUsk8e+N3mF4ZtDYuXRT9o2M5Ambpidmp0LNcThgsWPTsBmbh814rrMft9S347gtdVi/cT/uauzCHrMNPAABwCOtvTh2a92Yc2Cb3Ylf1rXhqtoWAKHH50Sby0Ux5R9dA2i3O/HlkAlPtffhx/tacMjqQLZaiV+W58flWFamGHBLpfdn/bbe24L+bGc/3AxYk2LA0kk2/qX1Qq3ZLuexl/hxoEkb3HMh5zoU2u1OHLI6oOAgO5CB0ZHzQ1b7nN7QktyZZ+WlT5qHOJnz/WWx6OfbmSmyi+yk7DTkqpXodbrxdt+I/Dln5aWH1K2QrlLKwv3BENz/gTa5Es03M1Og43m02Z1jjC2MMVxf14ZDVgdy1Ur8rqowrO9bqddiQ5p34+afYUwPToVu8V4gNyaCZuImZnyj1iTn6YIkHS4UReO6KKwTP/IpJ4vU3So7NCcxMG0asWC70QoNz+GySTbM5gIkaBIR4W/EI1wWihekRDo0Px804c3eYfAA7qkpwkPzS6ARxyH/2T35xUO66ZbGrYLd/DDGsGk4vEIgCXnMaIrt3Ywx+aR+wiQuFV8y1Up5wR3vsXPJEXRkCM81Fc+hQFzwxzNHU3JnzjNokSburkmZYokcsQBGnZZSJmSf0+1XrO8RBT6pYS9RDk2BMTzR1otvbanDFqMFSQoe1eJCO1rCYov4u2WoFEGdRdLYebwFTbfA8Iu6Nlg8Ao5IS8I7q6pRpddikbgLO5Mcmt1OF/qcbvAY3cQCgCuLs3FfTREeXVgqt2ACo4Jmq90ZcRD+eBfhdHm8GGO4v6kbx2+tC6vVNZ5I2XyZKiV0PpuVUiHPV8PmuAh8LoHJBRXjs9Ly1CroeB4eBrTaQzvPSw2038pMgSYEZ88xGclIUyrQ7XSFnO82HZCuz9/0445KUynxLdEddNqOQzh1xyH8sq4d/9fej91mGxQccFR6Eu6fV4w9hy/GM0vKka1Wot7qwEnbDuKOhk7cUNeGDRv347nOAbiZ9/OvL8uN6+8o8e3MFBRr1Rh2e7D661qctbMBN9d3yGuc31QWIGWKRUDh8KOibByXmQInY/jRvmZ5THQydybgdWNmqBRwMSY/30r9OTQpQ3MMn4n3IiuS9WOu5UUaFZIVPNws/GiK2UKD1S6/Fq4ozpn086Wmc3/FQG6B4RXxnsh3lFzFc7iowPv8frilR95QCWXcXP65YUSI1E2z/EwJvWK0DPQtn7bzB5p78FrPEJQc8MjCUvn+IBwkwe0fXQNxufbGwqG5LEUHBef93vFymvriO6Ex/t53vvhcqrPYpxwRtkk8d4fiTg5Elsr7uE/m0JTcmeflZUw6vTgXIEGTCBuHIMiFQEdP4UUr3dzuNyfGPeMUBNxc723XvaQwC4uSdKg2aHGDuKN/26GOSU+80mjQpYVZk978tNqd6Ha6oOI4WVwKlWjlJtVa7GizO6HjORwdZr6HFHAcz7HzDrsTjTYHeITuAinRjgoi8cJf0+sanxzNRCIJk5I452QMI35GtyWBZaEomiVK0PxDUzd+c6gTdoHhG+nJ+GTtfHlBF63GcanhXBqxCsTKBAmar/YModnmRIZKgWeWlstNifOTdODhFaWnqyA2HmncvMaghd5HIOM4DhcVZslOOIl8jQoanoOLMbmcJlwkF2G5GEFRm6BrjC+MMdzW0In7m7uxy2TDf6KQ1xQLRsfNxy6QlybrkKLkYXQL8t80ljTbHHAxBr2CR+G4GyuO4+S/7WStvID3ZkbKjTw9xHIYNc/jZHGMcKaMnfc5XbI7KFB+18WFo6UgBRoVjslIxo+Ls/Gn+SXYtWExXl5ehe8XZCJTrcTxWan4dO18nJmbLrs1n+0cgIsxHJmehDdWVOHl5VUJu5lScByuLhkVakq0ahybmYKrS3Lw4rIKnBOGqBINOI7DnxaUoFCjQpPNiV6nG7lqJU4K0vTs+7WSg90t3lMHKwWaDpEw04FP/IybA97Hc764lpmrY+ePt/WBATguMyUkR6MsLPoxA3w2ZEKP040MlWLCyPSFBZlQic5vN/O6jcMRHKVG+lD6FOSGc/30EjSB0bbzt3q9fQqvdg/i/mZvKeHva4rlTcFwOSErFRkqbznQx4Oxn5CQpvDyonheNygU8r3F1gS4NHcYreh1upGs4Cd0MVTpteABDLk9U5rsY4zJud9LIhw3B0YdmsFKgeosdrw/YAQH4CchbFbMBUjQJMJmy4gFNoEhR62UdzYiQQrt7na6QspOCQW3wPBUex9e6xmCeZK8vSfb+1FvdSBTpcSvyvPk9/+kOBsrkvUwugX8si5467nk0Kw2aCe9+dkoujOXJevGOF9CIVqC5n/EncNvZCSPERdC4ZviDdJnQ6aInVPhIjmtlqfoQ3ZaSCUviRA0fZteJddZvdWBwShkn0aK9Jyp0GmQKj6G/i7a0vsk4TNRN0zvDXiFnl+W5eHFZRUo0qpHG8eN1qiULEmv20D5mRJSrlmDzYHhOP0N3QLDQy3eRfCVxTkwKEaf93oFL990zJSxc6kQKNQ8IZ4bzfKKpOm83e5Ek80JHsBlhd6R1EQ7NBlj+F1DJ/4qlgIAwJ4gbaiJZHwhkISC48IucJgKdT43rv5Gt6TXbqC8N182DlvQ5XAhRcmPKcqZjNPFtvO3+0YSWgwWKlIZ0OIkXcBxwaMzUrBzwyIcPHIJtm9YhH8uq8TtVYU4Lz9DvpHyJUOlxKMLS/Hk4jKUaNU4Kj0Jr6+owr+WV2FdgkbNfbmwIBNbDluIhqOWYPNhC/Hc0gr8urIg7A3baJGuUuLxRWXypMNFBVkhR/ss8xlL5+GN0BmPlKHZ43TPiOdkLBEYkzevvuFHLFqQNHeLgfqcLnn8+8qS0ASP0ZHzicLiS+L3OiMnfUJ2ZY5GhVN9NorOyw9vI6FSFCcnc2gyxuSR8+nm0ASAb2UmQ8dzaLU78X/t/bj2QBsA4KqSHHwvQLt8KGgVPM7J9T6mz3f2R+VYg9EdA4cmMGoQ2JYAk4e0gfytzJQJz1+tgpcngw5MYfOjw+GCOQqFVZkhZGg+JrozT8xOlV+3cx0SNImw+dRn3HwqzZEGpUJutN1vmfqCwy0wXFHbgpvrO3BlbQsWf7kXl+1pwus9Q7CMEze7HS555+yWyvwxoyoKjsMfF5RAzXH4cNA4pl3YF4tndDenVKvGGZPc/GwSW7AjuQkojtKufKilCP5YnqJHhkoBo1uIW7DzF8NifmYYj5mUx9Ma4Xi+QxDwXv8Ifr6/FXc1dE5aLmT3jDqWfB2aGSqlPCqdyLFz6TlTrFMjR7xh9dd03iO+T8q6SUSGpsCYvKg9MzddPr8sStJByXkzZaLR7ipl35YFaDiXyFApZSfYzjgJUK/1jrozLy2cOKooOdsTLdKFymghUOjlcRV672PeFMFrWLrBXZ6ix2FiVvE+sy0qQngkMMZwR0MXHhPFzOOzvELLnmn695PKRsY7NIHRc0M8xNjRrDT/i/Vg45Hj+Xev9xp+cnZaSOPmEoelJSFPrcKI24OPB+KXHRoJwy63LGD4Gzf3JU+jCnsU+6TsNGw+bCFeXl6VsMxMf3Ach2KteszGT6JZk2rAnxeU4szcdPywOHARy3h8CzYLtCq/QmimSgGd+P5gbdSxZsjlxm/qO/BSnHL9xsMYw831HRh0eZCi5LHCz9STZLiYikgxU7mroQsOgWFlij7kiCtps7TV7hyTOzricsv3DucGECulWAUNz4XsgpeoCnHkvNvpgtEtQMFhWoo4BoVCjvS49VAHnIzhpOxU/Lpi6jm+kiD6/oARXTHOz5UdmlEWNFeJz8N4raUlGGNyd8QJ2f7vfecnSWPnka/LpPNMpV47pcKqyTI0ux0uWZe4ktyZMiRoEmHzaYARj0iQLOhTzdF0CwxX7W/BW33DUHEcKnQa2AWG//SP4Ce1LZj3xR5UfrZbflu3sRYWj4CVKXqc52csaZ5Bi5+VenOhAgUxS4JZmlKBNJUS69OSkK8JfPMTaX4mMDpmNBUxp8XmwD6zHTwgN7iGg4Lj5F3wj+Iw9sAYCys/U0ISNFtCzFYDvG3a7/eP4Jr9LVjy5V5ctKcJL3YP4s+tvbizoSvo1+4yWeFkDFkq5YTMq0SPnds9giy6F2nU8mhg37idP4vbA4tYBCLtonY5nHEvw2i3O2EXGNTiTaqETsHLQt6OKCyGJIdmWQi7qNKNUrTG3YPhFhj+2NwDwJt5ZfAjOiwWH4eZ4tDcbRpbCBQK0t+lKYLsM+mccURaEmoMWqg4DiNuT0IEesYY7mrswqNt3t30e2uK5FKAA2Z7yIU28UQa8y/04w5bFMfn3mhWmn9nr+TQnMzF6xQEvCWOm4+PN5gMBcfhNHGj8umO/mlZDjTicuO+pi6s+boWnw2ZwcFbukUkljNz0/HowtKwhGNpIgAYjc4ZD8dxco5moqYoGqx2nLStHk+09+H6uta4F0VKYubTHf3gANxVXeRX/JWKgaJhmJhJfDhgxIvdg+AA3FZZELLxZGw2sfe5xRjDo219cAgM8w1aLE3yfz5emWLAXxeV4rklFXJETqhUiQ7NFrsjaIHTQYs4WaPThLUxFU9O8RFzlyXr8OcFpRGXw/hSY9BifaoBHga8GMNNBMYYupyxETSlDYb6EKIFokm91YFGmwNqjpMnDcczLwqbH9KaZSqTq4CPoBnAofm39j64GMP6VIMsEhMkaBJhMuB0Y4/ouJlKIZDEQvkGKfKTiFtg+On+FrzR6xUzn1xchi/XzceHa+bhZ6W5KNep4WaAxSPIbw6BQctzuLemKODF5ljRSVMbwN3TIgqa0oizguNwmngxe613rKuzz+lCg80BDmNdfKESjZHzt8UdqvVpSciIIJgaAI4Rdx/jkaPZaHOgy+GCmuPGlIZMhtQMGo5D8/oDbbhwTxNe7h6C0S0gT62Sd5kfbevF82K4vz988zPHLxwTLWh2ijcaOp5HhkoR0KEpiZ46nkeFXgMl583xiveNSr11dBR8fEPvyigKi5IIUh6CoCkJvPEQNP/dO4RGmwMZKgUu8+POBOIrKk2VbocLvXIhUOiLPOnvEu7I+fhNEDU/WiiViMfrjd5h/EUcDbq7uhCXFGahRKtGipKH02d8bjohlY0U+ikkkZ57DVaH3IQeK0az0vy/RqWRrslGzj8ZNGHY7UGuWonDInAWnp+XAQXnzer72f7WaSNqOgUBf2jqwpqNtXiwuQcmj4AFBi2eWVI+RhgjZg55GhVyxWt0aZDpASkOIhGC5ueDJpy4rV5+3bkZ8GwcxmAlGGP4dX0H/i6KmQ/NLw6YlSrFWrXbXTBNEkE1WzC6PfhlnXfU+YdF2VgbxjmP4zjZpdlo9YqLv6xrx59avJuslxVmBRVHT8tJx1ERGF1y1UoYFF4htTnIul1yz03HcXOJb2emoFCjQqlWjWeXVIQd7RWM74suzRdiWA5k8gjytT3agqb03Bp0eaIWMxcKkjvziPQkJAfYYIqGoHkgSs/PLPH+3CYIsHjGnrdMbg+e7fCeb0ONkpgrkKBJhMXnQyYweBcKgTKawmHhFDNu3ALD1ftb8LqPmHlcVio4jsOiJB1uqsjHV+sWYPthC7Fp/YIxb7s2LAo6Blmj10LBeYOCu/2M6Eour1IfUURygLzXPyJneDoEQR7Lme/Tgh0OkqA57PbAGMHCTGAMz4mLTmk0PhKOERcre8y2mJeSfC4KE6tTDWFljkoOzS6HKyQHVIvNIecDXVqYhTdWVGH7hoV4fFEZflHmzVa98WCb3KY5ni3GifmZEmt8RiyC7TzHCjkPT6sCx3HIER2a4zM0pXHzXI0SCo6Ts7vi3aQqhcJX+xExVoiv1Z1TFBYdgiALvZONnPv+3GjldwbCwyZ3ZwKjDs14iEpTRXJnVum1YY2EVkQoaDbYHOh2uqDhRzdBFonZnXvjUGQznv+JY3o/LsrGZUXe0VPp2gRMzxzNQKVAAJCjViJLpYSA0cV7LHALo9ETgcospJHDDrsL9iCvg9fE0azTc9KhiMApsyBJh8cXejMRX+kZwrUHpoeo+WhrLx5o7oHRLWC+QYv/W1SGD9fMi2j6gpg+SBnW/hrOJYrkpvP4bjg+09GP83c3YMTtweoUPe6s9rrNn+sciMv6hjGGWw914ClRzHxgfjHOzw+cTZimUso5gIkeO6+z2PHnlp6Y557efqgDnQ4XynRq3BjBqHOFT0zS+bsa8XzXADgAt1cVyOWM0cZXSPWX3ykhOTSnYyGQhEGhwFfrF+CzdfOjco/sy0nZaUhTKtBud8nRb9FGirFIUfJRj/EwKBRywV8oBVDR4l1xHRZsckEqEJtK03mdOToOTYOCh1Y0dIx3aT7XOQCTR0C1XjOhnGuuQ4ImERbSuHkku3D+kByadVZ7REUzNx5sx79FMfNvi8r8LuY5jkOBVo1SnWbMW+okwqJWwaNS5z0x+WvJbRbFnjKfheeSJB0qxXH3PzR1yyPMdzZ6x5Y3RJg9laRUIEPlvbhEsiv/4YARzTYnUpWKsMfufMlWq+Ryj1i37UlZeEemh/eY5aiV0PIcBCCkluSnO/rB4A2Vv6emCOvSkmTX7vVluTgzNx1uBvxgX5PsGpJgjPltOJeo1GmQoVLALjDZ2RyIDwaMuLK2JSLBOhCjgqb3OZo9iUMzVxQ8JTGjPc4OzUOiiFHtZ8EqOSV3m6xTGtVttTnB4F00ZIWwubAoSQcVx2HA5Y5p0dTrPUNosDmQrvSfnSmRo1HFRVSKBqP5meE1PpaJNzcttvBiDyR35uqU0U2QRI7obxbPDeMXnkuTvM/l6ZaD6hKY7MoeXwoEeK+l8Xg8m+0OOBmDjufHRE/4kqVSIlnBg4mf7w+L2yOLymdM4bp3Sk4aHhNFzZe7h3DdgbZJs5VjjRT78ouyPHy0Zh5OzkmLymgjkViuLcvDeXkZQYtVRq/P8dtwvK+pC7862A4PA87KTccry6twcUEW8tQq9DndcqxDbI+hG//X7t2Yf2B+MS4IImZKSOJCIouBBMbww73NuKuxC4+39k3+BRHyyaARL4jmiYfml0TkDpSyiR9u7cVXw2YYFDyeXVKOHxfnTKkzYTKksfNDQWJmRnOVp6+gCQAano/JSLxOweMs8Tr2Roxebz1yw/nkm/2RUB3C3zmadNqd2GmyggNwXBABsEKngYrjYPEIEd33eBiTR+nnB4jJCRWO4+RiIN+mc6cg4G/t3vPHFSU5dL0fBwmaRMgwxmSX2tFRGDcHvG46g4KHQ2AhtZX6Muxy4/ku7yjwE4tK8Z0AYb9TQXKQ+sv4bPGTw8dxnHzj9Nf2PnmEOVetxA+KsnBtWd6E7xMqRVPITXpKtKifn58x5V23b4kZJB8Nxm7sXGBMbtI9IsznGueTvzjZ2LnVI8gZqVKo+fjv9eC8YqxNNcDoFvD93Y1osTnkHbwGmwODLg80PIfFfkQbjuNCHju/r7ELr/UM4cWuwOPt4SJFFBSPEzTH7/pJAqf08VEHSHwdmvWiYFzlx6FZqdcgRcnDJrApBXeP5meqQ1qgaxW8fB7YEaOxcw9jeEgc67qiJAdJk+SuBROVPhk0YvmX+/BhHGIhJHodLr9u0UjyMwGgQKOCmuPgYiys5+Dn4ibIET6bIIka0e+0O9HhcEHBjYrxEosT6BoNRpfDK/arOc5v4zUw6nidSkzMZEgbR9UGTcBFO8dxozmaAW6O/jdghE1gKNepsSxMUX08p+ak4dGFpVBw3sbfRIqaDkHALvG1dWZuOt3YzCKWJevxpwUlyPezoSAR7+vzkMuNP7d4ozNuLM/DXxaUQKvgoeI5XFzoFRWf7Ijt2LndI+BxMYv4vpqikMRMAFhgkHI0E+fQ/GDAKItxz3T2R2TemAyT24PrxVbtywuzIorXAEbHggHvZM/bK6txbBxc35KQGqgYiDHmk6s8vQXNWCLFfsWqaLQrRg3nElViyV+8cjSlMqvVKQbkBPmdVPyoS7gugnNFq80JmxhlFywuJFQy/dyrvd03gi6HCzlqpSxsE6OQoEmEzCGrAx1ipmEkTd3+4DlOzrkJtxhoqyguVOo0OCFGIfjSzbB/QXNshqbE+fkZSFcqkKtW4vLCLLy+ogo7NizCndVFAW8SQ0EW6cJcxB6y2vHxoAkcEDCXLxyksfNPB00xWZgB3sd70OWBQcGPaf4MFSlQf7JioNd6hjDs9qBEq5bbCcejVfD4++JylGrVaLU7sW7jfiz8Yi9O316PG+vaAXjbSQPtyK4Rsx+3BGmG9/jk6Umj9tFgvKA5OnI+dgdS2pWVHJqSOysajeLhIO3aVvlZsPIcJz8XppJnOdpwHnpLppTfGStB873+ERyyet2ZobxGg41RP9DUg26nC690x6d9do/JijUba3HmjkMTzgeROjQV3OiiMNSmc4ExfOWnREyaAmixO6Pqfp4M6fW+yKCbEB8gCdJ7zLaEO/18kcbNC7SqgCKZLBDHUIwN9cZ1NEfT/3NEGjc/Izc9Ku6i03LS8ciCUvAAXuwexHm7GuJ+jgS8ryuHwJCpUqI8CjdPxMxCKuxq9NlcjSXv9I3AxRgWJWnx87K8Ma+l7xdkQs1x2G60YnuQNc5U2Wq0wCYw5KqVYY0+L5hirFU0eFTMUQa8uebSCGw0uaOhEx0OF0q1atxcGXmr9mFpSUhW8DgszYB3V9XIxUqxRhK6Ao0i9zrdGHF7wGP0vD8XWS1ujjbYHAFLY6aCNKGRq4n8XjUYsXRodtqdeKajH0+198lvkmElULu5L5Kb+0AE5wppWqpar40o2mY80vSYb9P5k6I78+KCrGlbipVI6BEhQkYaN1+baohq0PHCIKJhMCTHWziFMeEiXcxrx+3YeBiTb2RKx11ci7Rq1B6xGDs2LMJdNUVY7zPCPBUibTr/uzii8+3MlAnHGgkrUwxIVSow7PZEpXHaH9Lo6PrUJL/tlZNRopvcockYky8QlxZmBb0IZaqVeGFZBZYm68DBm6u6ccSCL0QXabCiJ8mhGWxHtdXmbfcGgK+HzVETisePnI+WAo13aIoj5+IOZiIyuoZcbvniXRXgeSo1jk/leRdOw/noz9VP+ecGY+Ow97lxem76pO5MwHejZex5qdHqkIW0eGSGMcbwu4ZOOASGnSYrnvYph+h1uNDtdIHDqIAXDuEWA+0z2zDk9m6C+DpCM1RKObcp3GvMVJCuT/6ydav1Wmh573hTsBKEeCMXAgVxh8mCpiV2YuxoIdAkgqZcYDHxuT7gdOMTcYrgjJzouRlOF9urdTyHz4fMOGbzATzfORAXYUli9Lmlj+kYKDE9WZKsg5bn0G53YVccXN7yxoCf11G2WoVTxQLFp9ojc2k2WO34fWNX0A3DTwZH467Cec4v8Cn7iOdrVGL7iAUbRyxQcRzOF8uLpHVntNhlsuJZsbjywfnFU5rCKtSqse+Ixfj3impkq2Pj0vOHNHIeyKEpbXKV6zTQRvH+c6aRplLK18VYuDSlhvNgDvGpIE1fxSJD88f7WvCrg+24ub5Dftsjrvm+E4LLeP4UioGi7R6WzE9SedJOoxXbjFaoOC5mWbYznbl7ViDCRho3/0aU8jMlAomGkxEsuzBaLDRIu0n2McUDHXYnXIxBzXF+rfkcx0V9DKw4yMj57xu7cPneJgy5xgpVZrdHLrzxN1IdCUqew9HicyBWLjDJpXhEmPmZEiUhuFm/HrZgv8UOHc/ju0HyqiSq9Fq8t3oeGo9aivdX1+CRBSW4piQHFxVk4kfF2QG/brEogvY43ejzUy4FjM1CNHtGxwmnipSxVTTOoTngdI/JJgw0ch7PjC5px7ZQowpYiBNO47jF7cFv6jtw9o5D+G/fiHwzE07D+fifuztG5U47xb/3ihDbiQOJSi/7vB4brI4pZY2GwieDpjGO4vuauuTn+C65EEgT8O8ZjHAFzWCbIIkYO98cRNBU8pw8CrnHPH2KgaQNDH+FQBKVOg20PAdrDMXY8B2aE58jb/cNw82ApUk6VEd5RPH03HR8uGY+1qYaYPYI+EVdG767qzFuI8CjgmZ0JmWImUWyUoETxBv0l2PsxO+0O/G1uHF7eoAxx8vFwrM3eocDrnH80WC146e1LThy0wE81NKDK2ubA4qO8v1HmBFE1QZvuedwgHLPWPOIOCZ/Zm46bijPg4IDNo5Yorq59mBzt/wzDo9CHJg6Ae4v6Xo/5PbfgD1T8jPjgXTPuzkGgma3uOaPdsO5hOTQbLU5g5b5hcs+sw1bjBYoOeDk7NQxb3dUFcqbn8GQ1hvjuxJC4UC0BU2V9/GXXLhPdng3QU7NSQs6Oj+XIUGTCAmXwPCluKiJtqC5SDwB7DPbQt5BdQkMO4K0S0eLfI0K6UoFPGxs5ocklJXo1FGxl4eCJNK1jbuJbLc78VBLD97pG8F5uxow7CNqvtQ9CLNHQJVeg6OilHsKQN4heql7MOpjD26BYeOINDoaoaAZgkNTukCcnZceVvO8TsFjSbIeZ+Vl4ObKAtw3rzjoTrZBoZCzWQIJKuN3BL+Iwti5W2ByHk6RKFBkqpXgAQjAmEWjJGhOKAWyO+PmapBeX1VBXFlS4/hBix3mIOPDXw6ZcMyWOjzR3ocvhs24ZG8Tjtt6EP/rH/EZOQ99B7pCp0GuWgm7wPCPrujeQHoYk0ezQ41X8CcqCYzhXz43t07Gwm4JDweBMdzZ2AkA+EFRFpYm6WB0C7izwVuAJv1O4eZnSkyWjzieL4YCnzPiLWhaPB75ZwW6Pi2ZhjmaUolaMIemkufk0PtYPJ5ugaFBfN6GKmg2WSee5//tM24eCyr0Gvx7RRVuqyyAlufwyZAJx26tC0vQiQTGmHwjG8vNXGJ6I5UG/btnKKbN2W/0DoMBWJ9qkDc6x7MiRY+VKXq4GMNznZNngLfYHLh6v1fIfKVnCAK8N6NNNqdfY0O/043d4rkm3HWshufl88SWkfhuHjVaHfhPn3e8/IqSbBRo1ThJjMeKlktzt8mK//UbwQG4tjQ3Kt8zEegVvDxJ4a/pXHIjSnnmcxl56isGEQ9yhmaM3LnZaiVSlDwEhL5ZHQrPi+ed72Sl4v8Wl495+2EQw4kv0rrmoNUeVhklMHoPN9WGcwnJodnv8hph3ugZBuDNxyX8M+cFzU8++QQcx/l927hxY6IPb9qwzWiBxSMgQ6WIaHwwGIvE8Zkuhytkl+Zesw02gSFdqfBbIBItOI4bdZD6jHdKIkJJgAVeLCgO4Jp7XbxxA7wiwnm7GjDickNgTB4BurQwK6qO0cPTkrAsWQe7wPBUR3THZw5a7bB4BCQreDmOIFxKJ3Fodtidclh0NHJFJ0P6PQKJF5IjSXo+fTE89Qb5bqcLHgaoOE4WKhUcJ4dN++Zo9jjGjpxLgobFI2AkTrmDhyxifmaQ13OORoVCjQoMo65GXyweD359sB1n7WxAq92JQo0KlxdmQa/gscdsw8V7mmQ3Vzgj5zzH4WfizcIDzd2wRPExOWixwyYIMCj4MYH8wVDynCz2SE3ZXw6Z0eFwIUXJY1FS5KMzofJazxD2me1IVvC4riwPd9cUAfBucmwdsWC36DwMNz9TIhyHplMQ5E0Qf65uSdCMV6v4DqMVHuZ1GxcGuEbIOZrTSNAcH1ERCOn5FQtBs9XuhENg0PFcwIZzCUn07na6xrwmD1hs2DhiAQfgNHEcNhYoOA4/KcnBB2vmoVSrxqDLgw9iXMbVZHNiwOWGmuMifm0RM58j05ORr1FhyB3b51yoGwPSjfazHQNBJwOGXG6csO0g/tXtFTKPzUzB/1bX4HjRceqvLf0LMe5qoUEbkTvpm2I++q317VHfcBh0ufHvniFs9+OWe7ytFwzeuCdJLJEep9d6hjDomroZQHJnnpGbHnUneryRm87HXfMFxvCZ+Bw4MorGjJmKtJG1y2SN+mZGl5yhGRtBk+M4+e9cH6UcTatHwKs93s38Cwsiv58r0amh4znYBSZ3ZISCS2ByVML8KOkjcsu5040XOgfgZAzLk/VYSZuYAZnzgqbENddcg+eee27MW1VVVaIPa9rwqZRfk54c9VFqg0KBY8TmbH+LGX9sEW9eV6UaYt7w6a/pPJIcvqki3WQOujxj3Gmvi4/ZD4uykKFSYJfJhnN3NeDN3mE02BxIUvA4L2/ykepw4DgOV5V4BZ6nO/ph8URP4JFGVZck6yP+25aIf5cBl9uv+PRMRz88DNiQlhSX0PNgrdTAqPB0qbjY3TJimfI4hiROFI4r+Bifo+kWGAbEhbX0MZ2Cly+oUlFIrJEydfwVAvki51mOGzuvNdvwrS11ctvqhQWZ+GTtfNxVU4Qt6xfi6pIcOftXx/uPigjGhQVZKNep0ed047G26In4kjC7NFkXltt78bjsYSla4vScdCwVXZFTaYMPht0j4N4mrxPz6tJcZKiUWJ1qkDPCbjrYjl1GqRAoQoem6KBtsTmD7pYfstpxxo5D8oabv00QqVW8zmKPWZGZL6HkO0vHtCeMyYRI6HI48au6tpBGHKXXerCRcyC2AnGdT7j+ZOf/dJUSGSpvnIEkfDPG8OuDHQCAE7JSURCHTccqvRaniMLplhi1z0pI339ZkCI6Yvaj4DicLYqML0V5akCi3mLHbrNNHONMC/q5p+SkIUetRLfThXf6hgN+3hNtfRh0eVCh0+DdVTV4bmkFliXr5dfPW73DE86HvvmZkXBDeR5q9Fr0ON24urZ1ytm/Qy43/tE5gO/uasCSL/fiitoWnLi9Hr840AaTuN7sc7rka/KVxTny165NNWBxkg42geEfIbhZg7HXZMV/RXfmz2ewO1NC2tAdn6O5z6ckdFUKCTplOjUyVUo4hNHpnmjQ73TL9wWxNAqNFgNFZ8P9rd5hGN0CSrTqiKf6AO85VTq2cNbOjTYHXIzBoOBRFCUhWHJodjldeEY8T0QrNm62QqshkSOPPBLf//73x7xlZdGTR0IqBIp0QTEZwRYz/pBGR+IxcrXQIGV8jp7gWiIYW50qyUoF0sQsOqkYqM5ix16zDSqOw7VleXh1eZUsal5R2wIAOC8vI6SikXA5KTtVdqW8GMUFdaTNyL6k+DxW412ado+A57vie4EIJgD47u6dlJ0qjzZPdZxEdluNGx/NVo1tOu93ucEAKLjRXUFgdEzdX2ZrLJAyNKsnWUj5axzvtDtxwa5GNNu8rswXl1XgD/OKkSw+BzLVSvy6sgCb1y/EjeV5eGh+SdhRESqew40V3vbQR9t6o+b02BXhaLbvc8rs9uAdcbTtvLyMKYWbj8efmPh0Rz/a7S7ka1T4QdHoOM+vK/ORovS6YadSCAR4ywlUHAcnY+j0I6p7GMPjrb349pY6bDNakazg8eC8Er8iWIlWjSQFD4fAcMgW+7KkYPmZEgsMOig476ZLrLLdBMZwxb4WPNM5gGv2t056bQ2lFAiYfINmKhwUndqhZqWVj2s6f6N3GF8Om6HlOdxWVRD14wuEtBaJl6AZy6gdYmZwrriB9OGgMSZRB//u9bozv5GeIk92BELN87hIdEf9oanbb9b0sMuN/xNHrW+uyB+TGX1cZgo0PIcGmwP7fa5bzMedd3SE9x8GhQJPLPYWeX0yZMKfW3on/6IA/L6xC0u+3Ivr6trw8aAJHuaNgAGA57sGcPTmA/hs0ISn2vvhEBhWJOtxWNroa5XjOFwmrjuf7uwPe7TVlwebewB4XeizIVsyUGGMJGgfnhZZSehsg+O4mORo7hY31yt1GnntHAtG/87RcWhK4+bfL8icssFpXgTTTVIHwjyDNmolfZKgWWexo8vhQpZKKZevEf4hQdMHk8kEtzu6eYCzhTurCvHLsjwcEyNB03cxM9mJhDEW10X9Qp+bN+mGsEV0g0SjNTwcisc1nUvj5sdkJCNDpcSCJB1eEUVNaZl0WYxEO2ncDgD+2tYXNeeTdFGNNHtPIlAx0Bu9wxh0eVCoUeH4zMmb76KBJAA0WB2wjXNe+u7uFWvVOEIcqZlqjmZbgPHRbI33Qtkn7sT2SIVAqrFOzqIgJVTRxiEIsuu5epJm4/GN4xa3BxftaUK304UavRYfrpmHo0XH93iy1Er8vCwvYLnBZJyanYblyXpYPQIeEG8mpspOUZgNNT9TwldUeqtvGDZBQKVOg5Upenm8rW6Kguajrb0o+mQXTtp2EH9t60WH3YkRlxt/avH+7r8sy5Ndr4C38faG8nz535V6TcSbKQqOQ6m4YdQ8buHbZHXgjB2HcFtDJ+wCw9Hpyfhk7Xx8J9v/65nnuNHzeIxHvAXGsM04ecahTsHLz/VYjZ0/3dGPjeK1cq/Zhv/1Bx5NNbo9MIvnpoJJHJrSY9nlcPktcJgKddbwwvXlaAKrAxa3B7c3eHNdry7JlZ368UByDtVbHVEZJQ0E5WcSEtUGLVYk6+Fho03k0YIxJo+bn5mbFtLX/Kg4G9lqJRpsDvzVzxTDE+19MHkELDBoceK4c3WSUiHfX/hOah2yOtDpcEHDc1g3hRKs+QadHIvy+6YubBwOf3311ZAZD7X0wM28sRs3lefjq3UL8OX6BXh1eSVKtGp0OFw4d1cDHhXLgK4syZkgcpyRk44MlQLtdhfeE6OPwqXWbMN/+ke82ZlleRF9j+lGoKbzz2JsqJmJyDmaMRA0Yx1lIjs0o7Dhvt+nDOj8KEwiSmvncATNuijnZwJA1rhehwsLMmkiYxLo0RG59NJLkZKSAq1Wi2OOOQZbt25N9CFNK1amGnB9eR7yJ3FuRIrvYubNScbO2+xOdDtdUHJTF71CocagBQ/vqHev0w3GGJrtkqAZP4cmMFbQZIzJi1jffKOFSTr8a3kVynVqXFSQicpJBKKpcF5eBjJUCrTanXinf3jK388tMHk0cskUL6rFAYqBnuv0jiRfXJgFZZx2e3PUSmSqlBAw8UI5fndPygCUcqMiJVAentR0LguaovstZ5wDQ3J2xkPQbLI5IABIVvATjmM8S5N14OEVU9rtTlxR24K9ZhuyVEo8v7Q8rIKncOE4DrdWegW75zv70TjFHWanIMjP91AbziV8RaUnxJvH8/IzwHGj+ZpNNseUogv+2TUABmCb0YrfHurEqq9r8c0tdRhye1Cj18oOIV8uKcjCQvHnRzpuLuEvR3PQ5cZpO+qxecSCJAWPB+YV45/LKgJmVUrEK0ezzmKH0S1Ar+Bld38gYpmj2WJz4M5GbyyAtNB+oLk7oEtTcmdmqBQwKIKL0ElKhTydEM22XmC0YTRUx5HUXtpoc+DBlh50OVwo1apxVUnOJF8ZXTLVStl5Es2bTF+GXG657TdYnAExd5DKgUJpO2eM4c3e4ZAyN3eZbGiyOaHjOXwnK7SN3xSlArdWel3RD7X0oNNn7TDi4868rizPr5PqFHGs/a2+0UktaTpsXaoBOsXUblnPz8vA2bnpEABcUdsS1maMW2C4ub4dAHBRQSY+XDMfPyvLlc8/h6cn4+M18+TYIIfAUKZTTxBuAe9m1gX53mLNJ8Wc+3B5QMzOPDUnLWrNyolGGjlvtjnkHFarR8CmYe/5NFKH7mzE16EZrcia0em42N5XVxm8f+d6q2PK8Q8viNN2x2elRqX9W3othWMGqItywzkwdlpOyXnvV4ngzHlBU61W46yzzsKf/vQnvPHGG7jzzjuxZ88eHHnkkdixY0fAr3M4HDAajWPeiKkhZfS83Rd87FxyZy5J0o9xB8UKvYKXFy21ZhuG3B4Y3V6RoFSbGIdmu92JHUYrWuxO6Hgex2WNdaQtStLh6/ULcd+84pgej17B47JC78jpI629U76w1lvtsAkMSYrRZspIkf42rfZRMWS/2YatRmvUdvNCheO4gGOa43f3JIfmDpM1aJP3ZLTbxzacS+SMKwWShM3xi4HRpvPYZ2iOFgJNPrJhUCjkx+qyPU14b8AILc/hmSXlcXFkHZ6ejG9lpMDNgLvFlu9I2W+xw8m85WbhFoz5ikr7LXZwgJyplqtWIk2pgIdBbowOl26HC/VWBzgAv60swPpUAziM5izeUpnvd0NAyXN4ZGEpTsxKxRUhtksGYnScePR3uLW+A71ON6r1Gny8dj6+V5AZ0phPLMekfZGuTyuT9ZNumMhN51E+JoExXHugDVaPgMPSDHhleZVcjPV+ADGjPcRxc4lYCMQexuRxw1BvDqTrxJfDJlnYv6O6ENo4rA3GsybGY+fbRDd3hU4jj6QRc5vTctKg5jjsM9ux109RnkSH3YnzdzXiR/uaccmeRvRPIuZJ7szjs1JhCMNlf05uOtamGmD1CLitYfT6+ER7H4xuAfMNWpwUwEl/XFYqNDyHQ9bRSS3f/P6pwnEcfl9ThCq9Bl0OF07dXo/v7mqQ3763qxFv9Pp3uv69ox8HLHZkqBS4qSLf7+cYlArcU1OEV5ZX4qTsVPwxSLTNJYVZ4AF8MWzGC2FmadaabXinT3JnzvzsTIl8jQo6noebja7bNw2b4WQMhRqVPNpPeNcOGp7DgMuNpjAKbIKxK04OzVKtBiqOg00Q/MYJhYrNI+Bf3d7X6/fFDYKpIt1bNFgdQcvNfDlglu7hove4aRU8ksU1zEnZaciLUUnTbGLOC5obNmzAK6+8gssuuwynnnoqbrzxRmzcuBEcx+Gmm24K+HX33HMPUlNT5bfi4tgKR3OB47JSoeY41FuDj50nYuRKckPVWuxyfmaeWjXlHeNwkVyHbXYnXhMXXidkp07qqIkllxZmQcdz2G2y4csIxnh8kS6oi5N0U85CKfEpFZGQslaitZsXDoEEgPGCZrFWjVKtGh4GfD2Fx1MSKMY3BUsOzd5xI+e54x2a4td1OGLv0BwtBAptwSrlaO4WH8s/LSjBqjieD26pzAcH4O2+Eb/tpqEijZsvS9ZHlL2zyCef8qj0ZLkAxdeleSBCwUlyCC9J1uGKkhy8vrIa2zcsxF3VhXhwXjGOzfQ/1g8AC5J0eGpJOZZMcadfEmylOIL/9o3g1Z4h8PD+zSdrwfZlkSxo2mNawhNKfqbEkiTv47PHHFiIiIRnOwfw1bAZOp7HQ/NLkKVW4jJxh//+AC5NSaiebNxcIhyBuNZsw5Gb9uNfk7jIWm1O2AUGbQgN5xLSZmO73QUXYzg2MwXHhegoizaxFjQpP5MYT7pKKTeEv+Tn9cUYwz/EbEfJ7ehmwEeDgU0YHsbweq80bh5ePAvHcbinpgg8vNNWXwyZMOJy42+TuDMBb0685MJ7q28YTkGQ15TRcucZlAo8sagMWjHi6uNBk/z24aARP97XIk/xSPQ6XLhPLMG7qSIf6ZNMgRyRnownF5djfVrgEfkirRrXiaPivzrYhs8HQ5vIsXoE/PaQt/Ts5Oy0qIooiYbnuAnFQJ/4jJtHK59wNqDheXlCMRrXmwGnW14DTHXdNhkqnpPXdlMpBnq7bxgjbg+KtCp8I0rnh0KNCkkKHi7GxmykB8LuEeQJomiOnHu/n3ca7UdFUzMGzBXmvKDpj6qqKpx22mn4+OOP4QnQ3nzTTTdhZGREfmtra4vzUc4+UsYtZgIhlaXEc1EvjVDWmm0++ZnxHTcHRsWpFpsTb4ij+WckOCg4U63E+eLu2COtkYetA6MjD9GIEhifoWnzCHilJ7q7eeGwKGn0OeSLtLs3z2dheqSUoxmhoMkYk4XICRmaailD07t4GR05H+/QjN/IuRQOXhNiPILvePZN5fk4LSeyTMxIWZCkwzl53p/5y4NtGIkwM09qOF8e5ri5hK+geW7e2McgktEZX6QM1yN9nDH5GjUuL8rGBSG6IqeKJFY12ZwYcrlxw0HvdfbKkhxZ1A6VeWJ0SCxLeIDR61MoG25S03m73RW13MVWmwO/E51Rv67MR5noavlJcQ50PI/dJpvfkdNQC4EkFoUhaD7fOYB6qwM31LUFjWmQxqmr9NqQS7t8nfwansMd1YUhfV0skP7mO01Wv6UoU2XziHnMzyEIYPTc/2rPkPy8G3K5sXHYjO/tbsR1B9pg8ghYlaKXr1vBshu/Hjajx+lGms+aPBwWJelwibiBcvPBDjze5nVnzjNocXIAd6aENKn1Vu8wthmtsHoEZKqUsqkgGixM0uGztfPx5wUlY96kdeEv69rlzW8AuKOxEyaPgGXJOnlUPBpcX5aLM3LS4GbA5fua5LiNQHQ7XDhjRz0+HzJDzXG4vnz2uDMlxhfGfCYKvd+IgkN3thHNDTRpU7VCp0FKDAuBJEabziOPbZJeo9/Ln3oZkMQYM0AITeeHrHYIANKUiknjssLl/xaX4X+ra+Jq1pjJkKAZgOLiYjidTlgs/k8UGo0GKSkpY96IqePbdu4Pk9uD/aIAFFdBU3Jomm2yWygRgqYkTu0x29DndCNDpQhYgBJPflKcDR7Ax4Mm/L6xK+JclGiGUksOzVYxbzQWu3nhsCh5VACQHp9Au3tTzdHsd7lhFxh4AAWa4A7NQCPnUoZmr9MNRwxuzn2pl4WM0Byax2elYqFBix8XZ+Oa0vhm5UncWJ6PDJUC+8x2nLerMSJRc5fs0Izs+S655JIUPE4QbwQlptJ0zhjD5+Jz74ggLpNYI42ct9gcY0bNfxFBCYJOwaNafEzO2dmA13qGptQw648+pwvNNic4IKRFaIpSgVLxnB6NsiLGGK6v846ar081yK5MwFuIdWkQl6bkzpgsi1RCEjTrrfZJc1q/EjdmbALDtQdaA14fIsmiSlIqZHf5lcU5soCbCCp1GmSoFLALDHujnIvqEpjs6CaHJuHLMRkpyFYrMejy4JTt9Vj65V4s+GIvTt9xCB8NmqDhOdxaWYA3V1bLEUGfDJoCiu6viGOcJ2enQR1hEcUN5XnIVClx0GrHQ2KJ3LWluZMKD8f7TGr9TYyQOCo9KWqChUSJToNz8jLGvP1hXhF+KJZo/qKuDf/oHMDmYTP+1T0EDsA9NUUhb7SEAsdxeGh+CdakGGB0C7hwd+AogF0mK76z9SB2mWzIUCnw8vLKWeXOlKj0aTrvcbjkOJ0jSdCcQDSbziUzyVS7C0JFWuvXR7jhXmexY9OIBQoOOD8/uvFh8trZPPmx+U7YRXuTP1ejirlbdjZBgmYAGhsbodVqkZSUuJu5ucjxY8bOJ94QbDNaIMDrvsuN48jwQp+bt3pxRykRN05F437nk7PToIpTsU0wSnUa/KLcKzI81NKDH+9rgTXMMhK3wGS3TzRCqSVBzuoRMODyyLt534/ibl44VOm00PAcLB5BHoOXdvfSx+3uHS4KmvvM9ohahNukWASNasLzQ/o5I24P7B5BHjkfv7uYoVJAJ97MdMYwR5MxJu/SVoXo0MxSK/HR2vm4vaowYWNIBVo1XllehQyVAjtNVpy/qxHGMDJPrR5BbnSO1KH5zYwU/KAoCw/OL5mQJzxvCoJmi92JDocLKo7D2rTEiSeFGjWUHGAXGF4RR83/OL8k4nzE31QWIE2pwCGrA1fWtuDozQfw7ygKm9KNxXyDNmSXg+TS3BOFLMpNIxZ8PmSGjvfeKI8/z11Rkg0dz2OXyYYPx404jjo0Q7uuFmhUSFcq4Gajzkp/DDjd8nNQr+CxacSCpzr8F2HIhUBhFtndXlWIHxRl4ZrSxDqWOI7D6pTo3WT6stdsg01gSFMqQt74IeYGSp7DObnem/pdJpu8WVmoUeGk7FS8v3oerirJgYLjsCxZhxy1EmafshVfLB6PPCF1Vl7kkw9pKiV+XTmaNVmj18qGhWCkKBXyhvN/RBdpvDagOY7D78RzCQBcX9eGH+1rAQBckJ8R9lRAKGgVPP6+pBylWjVa7E5ctrdpwgbR273DOH17PbqdLtTotXh3VU3QcfaZjG/T+Wc+sTeZlBk8gVXi8/Gg1Y6hKU54jOZnxkdAqzJMzaH5SKt3k+TbmSlRLyuW1s7B1jUSB2JQCERExpwXNPv6+ia8b9euXXjzzTdx3HHHgY9wd5KIDN/FjD+XZiLyMwHvwjBF6Q2r/ljMHioNs8QjGqSqlEj1uVE+I8x8o1hyXVke/ji/GCqOw1t9wzhjRz26wwh8PmTzFgIZFLy8SzsVtAoe+eLN+QcDIz67efEfNwe8Nx3Szp+Uo+nrSPIV5rLVKvlzv4pg7LwtwLg5AKQqFVCLP6vf5fbJ0BwrZHAcJxcKxTJHs8vhgsUjQMklZpNgKixM0uFfoqi5w2TF+bsaJoiafU4Xev28DvaarPAwb3ZppAsyJc/hzuoinOrnRlGKMGi1O2EJEJ0SCGncfFWKPqH5vEqeG1O89uPi7CmN33wrMwVbDluIG8vzkKZUoN7qwBW1LTh3Z8OU2zaB8PIzJZZKOZpBCj1C5U3xmnlKThrK/ZxDs9UqXFLoPf/d39SNvSar/CZtsvg7Z/iD47iQxs43imPS8wxa/FZsQL6roRNNfm5kIm0LPT03HXdWF8U909of8higMbqC5hbxcVydakjIhhwxvbmuLBe3VhbgwfnF+M/Kahw6cgm2bViEJxeXo8bn9cRzHL4t5h+/NzBx7PzdvhFYPAJKtWqsn+I6+/y8DHmt/svyvJDdjeOFz3hO1HAchzuqCnF5YRYYgG6nC6lKBW6qKIjZz8xSK/H80gqkKHlsHrGg8vPdKP5kl/z2g33NsAkMx2Qk4+1V1SidYeukcKj0GTn/lMbNg5KlVspFSVJhXKSMxn3Fx6EpjZzXR5ChWWu2yWVAPyuJ/iam5HwOxaFJgub0IfGrvwRz3nnn4aSTTsJdd92Fv/3tb7j22muxYcMG6PV63HvvvYk+vDmJtJh5u2/iYmtrgkLxOY7DQvEkN+jyigOJEl+kHM0CjQrrptno2fn5mfjX8kpkqBTYZbLhO1sPhnyjLo88RKEQSELK0by/uRsAcFxmakLb4hb5RBcAwS+G0tj55xGMnY82nE8UJziOk3M0ex2u0ZFzPzvg0te3xTBH85CP43k6uI3DZVGSDi8vq0S6UoHtRivO3dmAGw+244wd9Vj4xR4s+XIfVn9di23jHFu7opgX648stVL+Ox+0TBSPdpusAfM1peec5BROJNJ5tlKnwQ3l/ttlwyFZqcDPy/Kw+bCF+FV5HnQ8hy+HzRFtHIxnawQbbouj1HQuMIZ3RGfVKePiB3y5siQHOp7DTpMV3956UH6TckULwjg/hiJofiWK4xvSknBhQSYOT0uaMHre53ThtkMdqBWnMmpm8M3BWp9cs2iWTyVqM5eYGSQpFbiqJAcX5GdiZaoBSUEc4lKh23v9xgnPUalY6Ny8jClPP/AchxeWVuC/q2pCcmdKHJ+ZApX4s2v02qg7sCaD4zjcWV2IHxdlQ8t7/z8rxg7BaoMWTy0uR6pSAQ8DXIzJbxyAHxZl4bklFXHJN0wkkkA34HLjfTHrORERUTOFaORoDrrc8hp/SRSzaoMhTRn0Ot1hxzXd2dAJBuDk7FSsjMH1UDKTNNkck8bpjI6cz774h5nGnBc0Tz/9dPT39+PBBx/ElVdeiZdeeglnnnkmtm7digULFiT68OYk0mKmzmIfE5LtFpi8C5WIDKkF4070idollbI7T8tJm5ZOjfVpSXh3VQ1q9Fp0O124dG9TSCOdu2Mw8lAsF9t4b9a/X5AYd6bE+KZzSdCc72cRIWUGfTpogimMUWYgcMO5RLboxqy3OuAQvH+b8aVAwGhBSEcMR86lHdrqMMdMpxOLk/V4eXkl0pTe8fOnO/rx9bBF3vxwMoabDraPeR1MtRAoFObppWKgsYJTi82Bk7bV48RtB+VyKAnGmN9CoERxcWEmViTr8eii0qg68FKUClxbloez87yjmv4agoPxv/4RXH+gdcybtCkTzvVJuoE4ZHVM+Fv40mpz4N7GroCjZZtHLOhxupGi5IPeAGarVfh1ZQEKNCrkqpVj3s7ISZNd7aEg5QIHy4v8WhSKD0vz5uA9OL8YegWPjSMW/KmlB7cf6sDar/fj8bY+eJg3L68sAfnU0WJZsh4qjkOv0y0X0k0Vxhg1nBNR46j0ZKg5Di12pxyhBHjXDdK5/5wpjJv7kqxUhH2NS1Up5XPYNzISs6nGcRxury7EwSOX4Jy86Gb0BeKI9GTs2LAIOzYsHPO2/4jFuKO6CMoZuOEbLgalQr4Gjbg90PEcnfOCMJqjGfmG7B7x+l2mUyNVFZ/R/mSlAnniPUdDGGPnXwyZ8NGgCUoOuDlGrulstRIZKgUEBC+6tbg98jWeHJqJZ86HUlxzzTW45pprEn0YhA/SYuaDASNuO9SBq0pysD4tCfstNlg8ApIVfEJOHr6NwgYFj0xVYnZKry/LQ75GhZ8lOC8sGKU6Dd5eVY31G2vRbnfhowEjjs0K3m4piQHRKASSKPG5MS7UqCJq7Iwmi8c5muQRSz9i3vpUA7S896Zjzde1+HFxNn5QlI3kEHboJUFTGhkfj+TGlI4jVanwm0sofX20ms4ZYxNcH6P5mTN7jGpJsh6vrajCI629yNeoUGPQYp5BiwyVEt/eUofdZhue6xyQ21+lgo/lMcwsmp+kxRfD5gk5mk919HvdHx6Gx1r78Juq0YXhAYsdAy43dDyHlTEUW0PluKxUHDfJuWMqnJuXgec6B/BO3wjurfbAEMLrq8/pwo/3NcMuTNyoKdSoZGd4KORoVFiRrMcOkxUvdw/hqhL/JVe/qGvDZ0Nm9DpdeHB+yYSPvy26M4/PSp20yOMHRd5zyVSRzme1Fpvf1/agy41a8bl3mJjFWqrT4JaKfNxc34HfN3XLn7s8WY9flufhmxnJCcvFjQZaBY+lyTpsM1qxecQSlY3PNrsTPU43lFzsHN3E3MGgVODw9CR8PGjC+wNG2RH9SvcgGLxu6pIEjzXfXuXddEl0Lm6kpUiRolfw0Ctm7oZONKjSa9AlxvSsT0uChqLfArJaFDR3Gq1wCSyiKadYmElCoUqvQbfThXqrIySnJWMMdzZ0AQC+X5CFihjdM3Ach+vK8nBLfQf+0NwNJcfhZ2UTz0NSBn62WkkZr9MAOksQ05Lvia1lHw2acNbOBiz/ah9uPtgBwHsCj2bTYKgs9BFRy3TqhN10LUzS4c7qIqTFaSctUlKUCnln+/mugaCf62FM3iWM5kXVV1i4ID8zIc8bX6RyqU6HC212Z9DdvVSVEk8vKUe1XoNhtwe/b+rGmq9r8cfmbliCODY9jOGQeKEtCjCqJbkx95it4r/9P5ekxuNoZGh2O1w4avMBnL69Hl0+309qOQy1EGg6szBJh0cWluKWygKcm5eBZcl6FGvVuEEszLq3sQsDTjeMbg8axHb7WAoU0hiM72i5xePBi12jbsS/d/SPaVaVHDrrUpPifjOXCFan6FGh08DqEeQyjMl4qr0fdoGhWq/BTeX58tvNFfl4Zkl52NeGC0Xn+POd/X7HlOssdnwm/l1e6R5Cz7hMVoExvN3rjWgJNm4ebar0Gqg5Dka3gBY/mx4bRXdmjV4ru8IB4JLCLBwhllosS9bhuSXleHdVNb6VmTKjxUyJaIwB+vKJmCW3PFk/ofyLICJBGjt/XyzeYYzhZTGX7twouTOnQqVei/vmFY85bxBzg0qftWCiTQjTnSq9BulKBWwCk4t9wkUuBIrTuLlEtVwMFFqO5pt9w9hpssKg4HG9H4ExmvygKBu/rvBGHN3T1IWHW3rGfLzV5pDdm/PJnTktoJURMS05ITsNryyvxHfzM5CmVKDP6ZZD9lfHoGkwFOYlaSHdas208pJE8X2xgOeDAeMYEWs8h6wO2AQB+igVAklI7hgewHfz4zM2FIxkpUIuk3q9x3vzkBNkd+/ojBR8snY+HltYiipR2Ly3qRtn7DwUsOjloeYeNNmc0Ct4LAkglmWPc2j6GzcHRjM0p+rQdAsMV9Q2o97qwMYRC76z9aDsUJQcmtUz3KEZjIsLsrAoSYthtwd3N3bKO+LFWnVMd3YlodxX0Hy1ewgjbg/KdGosTdbBJgh4vG10rEbKzzxiGuRnxgOO4+QbeOmGPhgWjwdPiy3dvyzPx8/KcuW3a0pzsTgCgfq0nDQkKXg02Zz40k+W51Pto+WFTsbwpM+/AW92Z7fThWRF8HHzaKPmeaxK9f6+L/sZ2R8dNx97zeY5Ds8vrcDHa+bhv6tqcGxW6qwQMiXWRlnQfFcUnY6PoVOZmFtIEzNbjBYMudzYarSi0eaAXsHHdVOEIMbjO61z1DSIvZnO8BwnX/Of7eyP6HvsiXGeeyCqfAqgJsMpCLin0evOvKI4Jy4bHVeX5uJmUdS8u7ELf27pQZvdiV/WtWHDpv14R+z5OC6TrsvTARI0iWnLEenJeGh+CXYfvggvLK3AeXkZODwtCRcUJEaYMigUKBcFMt/mXSIw1QYt1qca4GEY4wobjyTwLEnSRdVFuTrFgNNz0nBTRT4KEtBK7w+pBORVUdCcLD5BwXE4Izcdn66dj0cXliJDpcBukw1X1bZMyCb9YsiEB8QCpN/XFAUMss8RM4qMbm/gdW6A3LxC8f2dDteUWqAfaO7G18MWGBQ8qvUa9DjdOH1HPf7ROSCXkVTN4l1OJc/hnuoiAMA/ugbxd1EQi+W4OTD63Op0uDDicoMxhifFn31pYRZ+UeZ1jj7V0Y8Bpxtugcki1BFz6Ebi7LwMcAC+GjajxRZ8cf3PrkEMuT0o1apxUnZ0FrIGpQJn5npF1ec7x7rZjW4P/iWeKy4X4wqe7uyH2cel/ZbPuHm8x/MuLvAe03OdA3AKYwP0paKlDX7Eca2Cx4Ik3awSMiUkh+YBiz3swoPxmNwe2TX9HRI0iShRrFVjgUELDwM+HjTJGxInZaeGFLtBELFCimDKU6vI/RYCPyr2xse81jOEzjDNB8MutzxdsSRODecS4TSdP9c5gGabE1kqJX5SPPW4nFC5pjQXN4lllHc1duGwjbV4rnMAbjHv+80VVfhhHI+HCAwJmsS0R83z+FZmCv60oASvrqiKe+OhL1Km3IIkusiGijRO+ULXQMByIFnQjPIFVcVzeHxRGa6eRnmjUharXAgU4oJNwXE4MzcdzyypgIbn8N9+I+5s6JQ/3ud04craFjAA5+dlBA2yzx4XVxBo5Dxfo4aW5+AQmDz2GC6fDZrwR3Fc4/55xfjPqhp8KyMFdoHhuro2AECuWjnr2zvXpiXh7Nx0MEDe2V0W4wVkilIhi9J1Fju+HDajzmKHjudxfl4Gjs1MwdIkHaweAX9t68VukxUmj4BUpSLui9tEUqRVy47UV4K4NN0Cw1/bvO7In5TkRHXzRSos+0/fCAZ8IgBe7BqA1SNgnkGL31UXolKngdEt4AUxxkNgDG+Lz6dwmoSjxUnZachTq9DndOOt3mH5/UMuN2rN3nPchrS54faVyFarUK5TgwFykWGkfDhghIsxVOk18ogeQUQDaez8rd5heWLkvDgV4BBEII5IT8KvK/Lx6MLSWbnhFW1WphhwWJoBbgb8bdz0xmRI7sxSrTruMWaSQ7PZ5oDLTx65hNntwYPN3nuI68vzkBTne4WfleXiV2JslJsBR6Ql4fUVVXh5eRXWzrG1zXSGBE2CCIPbqgrxxKIynJ6T+IyhmcJJ2WlIUyrQbnfh0wCi2O4Y5GdOVxaNy6mRcg5DZU2qAX8US0Eea+vDc539EBjDT2tb0et0o0avxV01hUG/x3gBM9DIuYrnZAfWXY2dYbs0ex0uXLXfK7J+Pz8TZ+SmI1mpwLNLy/Ejn1KS2ZCfGQq/qSxAsk8GXiwbziWkwoc6qx1PtXvdmefmpSNVpQTHcbheXKg92dGPN0Wn34a0pITnzcYb6Ub+5e5BvzmWgLd4p83uRIZKEfUb/6XJeixN1sHJGP4luqUExmQ37+WFWVBwHK4QS4OeaOuDS2DYbrSiy+FCkoLHNxLgqlXxHC4q9IqxkvsXADYNW8DgjZKYizl4q6M0di6Nm59A7kwiykhj5+/2j8DkEVCkVc25zQdi+sFxHK4uzfXr7Cf8c1WJ17TxXOcAjEEy9sezK0GFQACQr1HBoODhZl5RMxCPtvViwOVGhU4jx5jFm2vL8vDPpRV4e2U1XllRhfV0npx2kKBJEGGQpVbi1Jy0iJrk5ipaBY9z8vyPUwJiIZA5+g3n05XxguZkI+f+OCM3Hb8Ux4VvPNiOn9S24NMhE3Q8hycWl8KgCL6DmTNuxDw3SI7jz8pykaLksc9sl8fkQ8HDGK6sbUGf040FBi3uqB4VWRUch99VF+L+ecXIVClxem5ayN93JpOjUeGXooAIxGcRKTmAPxgw4r+iOHKZj5h8XGYKliTpYPEIsvvw8Dl4I3FCdioMCh4tdic2+RGhGGN4VAyBv6wwOyblLHI5UNcAGGP4aNCEJpsTqUoFzhLPoWfnpiNbrUSHw4U3eodkV+TxWanQJqgw5sKCTKg5DtuNVuwQHYlfyfmZc++5BEQnR9MhCPhwwAiABE0i+qxM0SNDNbpWOCc3A/wc28giiNnAtzKSMc+ghdkj4NmO0LM0dyfw3ovjOJ8cTf9j570OFx4X16U3VeQn9N77mMwUeaOSmH6QoEkQRMz5nnij/r+B/2fvvuOrqu8/jr/vyCYbAgmEvTciICCKA/esotZRtVqttVpX62itWq27+qN11rqtW+vALUMBGbL3JhAySEL2vuv3x8m5SchO7s3NeD0fjzzuzb3n3vvNuPee+zmfUVBnQu+e0gqVutwKs1q9PVW6sr4hQYqpUTLRmoCmJN02sLcu7B0rl0f6rCqo8fDwfs3K+Dyy5LyhHpqSFBdk101VR38f3Zuhcpe7wW1NRU6X/rwrTUvzixVmterfYwYqrJ5gy+VJ8do8c4yuqMoC7Q5+3beXfpUUr7sHJbZLmb35//BNTqHckmbF9qj1P2exWHR7VXDczEuc1Y36Z5oibDadU1WyXd+Am6V5xdpYXKYwq0VX9/XP/+v5CbEKt1m1u2p4ljn855LEOO9BilCbVdf2NQLSzx7I0vyqrNpADvLoFRzk/d2ZazZ7sXbXjC+zj+aawlJVuJt+zazP0rxiFbvc6h1sb5dsbnQvNotFJ1WVnUvSRZSbA52SxWLR75KN6o2XDmY3+z3HbPfV3gOBTOa+6LsNVMY8mZKpUpdbR0WF6ywf9SxH10RAE4DfjYwI09QGhgOZb6hjfTwQqKOyWCwaXZWl2TckSJGtDGpZLBb9Y2SyplV9cL6wd6wuaeYHkgi7TRE1AoxNlYRe26+XEkOClFbh8JbA1qfI6dL/pWRqyvKt3knQj43o12jvt+7WI8lutejxEcn6w8D26et6ZMD8mr51G5if2jNKY6v+J3sF2zW8C0+cb4z5gf6zrHyVHhG4f65qEvwlifF+m0zfw27TL6ramTyyN0OLcotkkfTrIwKoV/aNV7jNqm0l5UqrKjef3Y7TzetzTVXW72dZ+dpdWq7NVZkf3TWgOSI8VL2D7Spzu7Uyv3VZmmZG9Wk9o8mcg1+cU3Ug5NiYHhrUTV/3ga7g/N4xSgwJ0qFKpz5uRjVVgcOplLLADAQy/aZfLwVbLPomp1D/OVj7s8Xu0nJvr/B7hyR1u88KaBkCmgDaxWWJ1cOBzF6MNSe4dodyc5MZPGptdqYpxGrVuxOG6IMJQ/R/I/u36A2/Zh/NxkrOJSnMZvWWSs/bf0j5R0zuLXa6NC/lkKYu36pH92Uq3+nSsPAQ/XvMQLI+AmxYRIjM/4rk0GDN6RlVZxuLxaI/D06UzSL9IiG22+44TouO0IDQYBW73Ho6JVOfZ+Xr86x8vZGWo0W5RbJKfp+waWazr6oqVT45PkoDwmoHGmKC7LV6SZ0SwHJz06SocB0VFa5Kj0d/2HZAHhlN/49sb9FdWCwWnRBnPNcW5ha2+PYuj8cb0DydzBT4yZye0fpw4hC9OGZgoJcCoA2CrVb9purA4nMHsprseW+2+uofGqzYdh4IZBoXGa77hiZJkv62J93bskYyDuq6PMbwsu7augbNR0ATQLs4OyFGUXarDpRX6rx1uzX5py0atmST3q0q7+wOA4FMlyTGaWh4iLdnXluE2ayaFRcpewt7y5iDgEKsFkU3I0v04j5xGhERqnynS89U9RIsdrr0r/2HNHXFVj2yL0N5TpeGhofoudEDtHjqSG8ZKgInwmbTgLBgSdJVVYNl6nNCfJQ2zxyrv1btXHZHVotFc6sC8P86kKXfbEnRb7ak6E87D0qSzkqIqRNc9LWJkWHeAx6SdE2/+svbr0vuJVvVn7KjlGJdU5VJak727q7ZmaYTq8p5Fx6ufxheY9YWliq70qkou7Xb/x7hX8fGRvot6xxA+7kiKV6RNqt2lVbo+8ONH0jbUNQxZhf8um9PndkrWg6PR9dvSVGBw6k1BSX6IrtAVkn3DE4M6PrQOfAOBqBdhNusmts7Ti+n5XizjySpT3CQJkeH64wO8qG8PYzuEaal00YFdA09qz7A9Aq2Nysjz1aVxferTfv0n4PZCrZa9FpajnIdxkTFwWEhum1gb53fO7ZbtA7oTP46JEmLc4t0Vd/GA+iBOkrfkfy6X09tKynT4craWcgRNlu77FhbLBZdkRSvO3ce1LDwEB3XQD/TfqHBenR4P20vLtec+I7x2nl2Qozu35Ou7KrfXXfPqjg+todsFmlnabkOlleqX2hws2/7ZVVv1JPjoxVsJfcAANC4SLtNv+rbU88eyNJTKYd0TEyPenu1L84t1Lz9mZKkSVGBHXRjsVj01IhkbSoq04HySt22I9W7/3VRnziN6tF9qvfQenx6AdBu7hycqF7BdsUF2TUyIlTDI0IVQxAlIMwMzd5N9M+saU58lI6JjtCKghI9lXJIkjQoLFi3Deyj8xNiW5wlivZxRq8YnRHAoTGdSVyQXS+PHRTQNVyeFC+Xx6NjYyMb7Z3Y0YZpBVutuiIp3vva0N0DmtFBdk2OitCqghItPFyoXzVzmJTH49FXNfpnAgDQHL/p10uvHMzW+qJSzV61XU+NTNbsuOpWQy8fzNZfd6fJ5THa7PzKB5VibRUdZNeLYwbqnLW79EW28d4XarXoT1WtroCmcNgXQLuJstt0y8A++lXfnpoa04NgZgCZPTQTWhDQtFgsemBYX4XbrBoYFqx5I/trydRRmtsnjmAm4CM2i0W/7tdLw9vYYzcQrkrqqd7Bds2K7aE+3bR/Zk0nVg1rWpTb/LLzHaXlSimrVIjV4r09AABN6RMSpPcmDNHAsGClVzh0yYa9umN7qvIcTt2186D+vMsIZl7UJ1bvTxzS6sGkvjYpKlz3Dqmugrm2Xy8ltaCqAd0b0QQA6IZO6xmtz7PyNbdPbItuNyEyXFtmjlWI1cLkXQC1JIQEadX00QritUGS0Ufz0X2Z+jGvSJVud7PKx7+qylCZFRupHh3kwyYAoHOYGtNDC6aM0MN7MvRyWo7eyjisDw7lqsLtkUXSnwcn6sb+CR1uAORv+vXS7tIK7Swp1039EwK9HHQiBDQBoBsa1SNMC6eObNVtwwI8URlAxxVCz0evsT3C1DPIrhyHU6sKSnRsAz1RazIDmqdTbg4AaIUIm01/H95PZ/SK1q3bU3WgvFLhNqueGzVAp3XQmQUWi0WPj0gO9DLQCbHXCQAAAPiY1WLRCfHNLztflV+sjcVlslukU3pGNbk9AAANmRkbqUVTRuix4f30zeThHTaYCbQFAU0AAADAD06qGsiw8HBhk9v+o2qg0iV94tWrBf2NAQCoT4Tdpiv79tSwTtiXG2gOApoAAACAHxwXFymrpG0l5Uovr2xwu58LSvRDXpHsFunmAfQPAwAAaAoBTQAAAMAP4oLsmhQVLqnxsvN/7MuUJF3UJ079w0LaZW0AAACdGQFNAAAAwE9ONMvOc+svO19TUKLFeUWyWaQ/DOjdnksDAADotAhoAgAAAH5yYrwR0Pwxt0gOt6fO9U+mVGdnDiA7EwAAoFkIaAIAAAB+MiEyTHFBNhW53FpdWFLrurUFJVqUa2Rn3kJ2JgAAQLMR0AQAAAD8xGqx6ISqsvNH9mboi+x8lbnckqqzMy/sTXYmAABAS9gDvQAAAACgKzsnIUYfHcrTqoISrSooUbjNqlmxPbSQ7EwAAIBWIUMTAAAA8KNTe0br26OH63fJCeoXGqRSl1vf5BhDgi7oHatB4WRnAgAAtAQZmgAAAICfjY8M1/jIcN07JFHrikr1WVa+Ussrdc/gpEAvDQAAoNMhoAkAAAC0E4vFoqOiInRUVESglwIAANBpUXIOAAAAAAAAoNMgQ9NHPB6PJKmwsDDAKwEAAAAAAAA6HzOuZsbZGkJA00eKiookScnJyQFeCQAAAAAAANB5FRUVKTo6usHrLZ6mQp5oFrfbrfT0dEVGRspisQR6OQFTWFio5ORkpaamKioqKtDLAdAInq9A58BzFeg8eL4CnQfPV6Bj8ng8KioqUlJSkqzWhjtlkqHpI1arVf369Qv0MjqMqKgo3hSAToLnK9A58FwFOg+er0DnwfMV6Hgay8w0MRQIAAAAAAAAQKdBQBMAAAAAAABAp0FAEz4VEhKi++67TyEhIYFeCoAm8HwFOgeeq0DnwfMV6Dx4vgKdG0OBAAAAAAAAAHQaZGgCAAAAAAAA6DQIaAIAAAAAAADoNAhoAgAAAAAAAOg0CGgCAAAAAAAA6DQIaAIAAAAAAADoNAhoAgAAAAAAAOg0CGgCAAAAAAAA6DQIaAIAAAAAAADoNAhoAgAAAAAAAOg0CGgCAAAAAAAA6DQIaAIAAAAAAADoNAhoAgAAAAAAAOg07IFeQFfhdruVnp6uyMhIWSyWQC8HAAAAAAAA6FQ8Ho+KioqUlJQkq7XhPEwCmj6Snp6u5OTkQC8DAAAAAAAA6NRSU1PVr1+/Bq8noOkjkZGRkoxfeFRUVIBXAwAAAAAAAHQuhYWFSk5O9sbZGkJA00fMMvOoqCgCmgAAAAAAAEArNdXOkaFAAABJksvtUXp+WaCXAQAAAABAowhoAgAkSfd9tlkzHl2oNfvzAr0UAAAAAAAaREATACBJ2p5RJEnaeagowCsBAAAAAKBh9NAEAEiSiiuckqSSqlMAAAAAgG+4XC45HI5ALyPggoKCZLPZ2nw/BDQBAJKkkkojkFlUTkATAAAAAHzB4/EoMzNT+fn5gV5KhxETE6M+ffo0OfinMQQ0AQCSpOJyMjQBAAAAwJfMYGZCQoLCw8PbFMTr7Dwej0pLS5WVlSVJSkxMbPV9EdAEAEiSSipcxmklAU0AAAAAaCuXy+UNZsbHxwd6OR1CWFiYJCkrK0sJCQmtLj9nKBAAQBVOlypdbkmUnAMAAACAL5g9M8PDwwO8ko7F/H20pacoAU0AgDc70zhPQBMAAAAAfKU7l5nXxxe/DwKaAABv/0ypeto5AAAAAAAdEQFNAECtIGZxjWxNAAAAAAA6GgKaAIAjApqt72MCAAAAAIC/EdAEANTqm1lChiYAAAAAoBkyMjJ06aWXavjw4bJarbrlllva5XEJaAIAVFQzQ5Mp5wAAAACAGiorK2t97/F45HQ6VVFRoV69eukvf/mLJkyY0G7rsbfbIwEAOqyaGZqVLrcqnW4F2znmBQAAAAC+4vF4VOYITEVcWJCtRdPFZ8+erbFjx8put+utt97S4cOHJUlffvml/vKXv2jTpk369ttvNXv2bM2bN0+S9Morr/hl7fUhoAkAqBXQNL8PtgcHaDUAAAAA0PWUOVwa/ddvAvLYW/92qsKDWxYGfP3113XDDTdo2bJlWrx4sX7729/qrrvu0pNPPqnBgwcrNjbWT6ttGgFNAICKjigzL65wKjaCgCYAAAAAdFfDhg3T448/LsnolSlJf/vb3zRnzpxALksSAU0AgOpmaBZX0EcTAAAAAHwpLMimrX87NWCP3VKTJ0+uc9nRRx/ti+W0GQFNAECdACYBTQAAAADwLYvF0uKy70CKiIho1mWBwMQHAAABTQAAAABAp9F5wsIAAL+pE9AsJ6AJAAAAAGja+vXrJUnFxcXKzs7W+vXrFRwcrNGjR/vtMQloAgDqnXIOAAAAAEBTJk2a5D2/Zs0avf322xowYIBSUlL89pgENAEA3inn8RHBOlxSSck5AAAAAHRjixcvrvX97Nmz5fF46t22ocv9iR6aAACVVBoBzN5RoZLooQkAAAAA6LgIaAIAVFLhkiT1ia4KaNJDEwAAAADQQRHQBAB4A5i9o0IkVWdsAgAAAADQ0RDQBIBursLpUqXLLalmybkrkEsCAAAAAKBBBDQBoJsrqRG89AY0yx2BWg4AAAAAdClutzvQS+hQfB6iRM8AAMe2SURBVPH7YMo5AHRzJVUDgMKCbIoOC6q6jAxNAAAAAGiL4OBgWa1Wpaenq1evXgoODpbFYgn0sgLG4/GosrJS2dnZslqtCg4ObvV9EdAEgG6uqKp/ZkSIXREhxttCEVPOAQAAAKBNrFarBg0apIyMDKWnpwd6OR1GeHi4+vfvL6u19YXjBDQBoJszBwBFhtrVoyqgWUJAEwAAAADaLDg4WP3795fT6ZTLRSWczWaT3W5vc6YqAU0A6OaKvRmaNm9As5iAJgAAAAD4hMViUVBQkIKCggK9lC6j2w8FWrx4sSwWS71fK1asCPTyAMDvzOBljxC7eoQS0AQAAAAAdGxkaFa5+eabNWXKlFqXDR06NECrAYD2UyugGWy8LVQ63ap0uhVs7/bHvQAAAAAAHQwBzSqzZs3ShRdeGOhlAEC7M/tlGkOBbLUuD7a3fuocAAAAAAD+QOpNDUVFRXI6KbME0L3UzNC026wKDbLWuhwAAAAAgI6EgGaVq6++WlFRUQoNDdUJJ5yg1atXN7p9RUWFCgsLa30BQGdkDgUyBwIxGAgAAAAA0JF1+4BmcHCwLrjgAs2bN0+ffvqpHnroIW3atEmzZs3SunXrGrzdI488oujoaO9XcnJyO64aAHynpLL+gGYJAU0AAAAAQAfU7XtozpgxQzNmzPB+f8455+jCCy/U+PHjdffdd+vrr7+u93Z33323brvtNu/3hYWFBDUBdEpF5dU9NGueFhHQBAAAAAB0QN0+oFmfoUOH6txzz9XHH38sl8slm81WZ5uQkBCFhIQEYHUA4FtmJmaPUDI0AQAAAAAdX7cvOW9IcnKyKisrVVJSEuilAIBf1RwKVPPU7K0JAAAAAEBHQkCzAXv37lVoaKh69OgR6KUAgF8VV7gk1QhohjIUCAAAAADQcXX7gGZ2dnadyzZs2KDPPvtMp5xyiqzWbv8rAtDFFVc4JNXtoUlAEwAAAADQEXX7HpoXX3yxwsLCNGPGDCUkJGjr1q3697//rfDwcD366KOBXh4A+F3JkRma9NAEAAAAAHRg3T6ged555+m///2vnnrqKRUWFqpXr176xS9+ofvuu09Dhw4N9PIAwO+KGxgKRIYmAAAAAKAj6vYBzZtvvlk333xzoJcBAAFR6XSr0umWJPUIPrLk3BWwdQEAAAAA0BAaRAJAN1azrDwixCZJivROOXcEZE0AAAAAADSGgCYAdGNmWXlokFV2m/GWEOHtoUmGJgAAAACg4yGgCQDdmLd/ZkiQ9zKzlyY9NAEAAAAAHREBTQDoxqoDmjbvZeZ5ApoAAAAAgI6IgCYAdGNHTjiXqrM1SwhoAqiycPshnfzUD1p3IC/QSwEAAAAIaAJAd1ZcbgQtI4KrA5rmcKAiApoAqnyyLl27s4r19ebMQC8FAAAAIKAJAN1ZibfkvGaGpnG+0ulWpdMdkHUB6FjS88skSWlVpwAAAEAgEdAEgG6svpLziBrBTcrOAUhSRkF5rVMAAAAgkAhoAkA3ZgY0awYxg2xWhditta4H0H05XW5lFhqBzHQyNAEAANABENAEgG7MzMCMrBHQlKTIqoxNApoAsooq5HJ7JEmHCsvlcNGKAgAAAIFFQBMAurH6MjRrfk/JOdqLx+PRir2HVVDqCPRScISaWZlujxHUBAAAAAKJgCYAdGPFFS5JtYcC1fyeSedoL49+vV2X/HuF7v10c6CXgiMcOQgoPZ+AJgAAAAKLgCYAdGPF5UY23JEBTTI00Z7eXnlAL/6wV5K0Oa0gwKvBkY4cBJRRQB9NAAAABBYBTQDoxkrMDM3QI3poEtBEO/lhZ3atrMzUvFJvv0Z0DEcOAjoyYxMAAABobwQ0AaAbK2qih2ZROQFN+M+2jELd+N+1crk9On9SXwXbrHK4PEzS7mDMv0fPHsG1vgcAAAAChYAmAHRjZgZmjxBbrcurS85d7b4mdA+HCsv169d+VnGFU8cMjtNjF4xXclyYJGn/4dIArw41pVX1zJw8IFYSPTQBAAAQeAQ0AaAbK/YGNINqXR5ZVYJeXMHEafie2+3RdW+uUUZBuQb3itCLlx+tYLtVA+IjJEn7c0sCvELUZPbMPHpAnCQyNAEAABB4BDQBoBsr9pacH5GhGWwGNMnQhO+lHC7RhtR8hditeu2qqYoONwLqA+LDJZGh2ZGUVDiVX2oc2Dh6oJmhSUATAAAAgUVAEwC6qUqnW5VOtyQp8ogMzR7eDE16aML3dh4qliQN7x2p/lVBTEkaEGcGNMnQ7CjM7MzIULuG946UJBWWO1VUTvY2AAAAAoeAJgB0UzUnmB+ZoWn21GTKOfxhd1aRJGlYQo9alw/oWVVyToZmh2H2z+wbE6aIELtiqrJpMwroowkAAIDAIaAJAN2UmX0ZGmSV3Vb77cDsqVnMlHP4gZmhOawq489UnaFZKo/H0+7rQl1meXlSjDGwKTHaOE2j7BwAAAABREATALqp6oFA9jrXmRmblJzDH3ZlVQU0j8jQ7BcbLqtFKnO4lF1UEYil4QgZVYHLxOhQSVLfmNCqy8nQBAAAQOAQ0ASAbqrEOxCobkDTDHIS0ISvudwe7ck2MzRrBzSD7Vb1jTUyAPfnUnbeEZgl52aGpnnKYCAAAAAEEgFNAOimihrJ0DSHAtFDE752ILdUlU63QoOs6hcbXuf6AXFGH82UHAYDdQRm4LIvAU0AAAB0IAQ0AaCbaixDMyKYDE34x65DxkCgIb16yGa11Ll+QNXU8wNkaHYI6QVH9tA0Ss7poQkAAIBAIqAJAN2UOfAnsp6AZmRVhmaF0y2Hy92u60LX1lD/TJMZ0Exh0nnAud0eb6/MpBizh2ZVhmYBAU0AAAAEDgFNAOimihvL0KxxGWXn8CUzQ/PICeemAfFGyfn+w5ScB9rhkkpVutyyWKTeUUZA08zUzCwol9vNJHoAAAAEBgFNAOimSipckqr7ZdYUZLMqxG68RRSVE9CE7zQ3Q3M/GZoBZ/bJ7B0ZqiCb8XqQEBkim9Uih8ujnGIm0QMAACAwCGgCQDdVXOGQVP9QoJqXl1QS0IRvuNwe7a4KaA5vIEOzf5wR0Cwocyi/tLLd1oa6zICmWW4uSXabVX2i6KMJAACAwCKgCQAdwJJd2brro40qKne022MWmxmaDQU0qzI3i8nQhI8czCtVhdOtYLtVyXF1J5xLUniwXQmRIZLI0gy0tPzaA4FM5mCg9Kr+mgAAAEB7I6AJAAHm8Xh07yeb9e7PqXpn1YF2e9zGemhKTDqH7+06ZGRnNjTh3DSwqo9mCn00A8oMWPY9IqBpBjjTydAEAABAgBDQBAA/+2Rdmlan5DZ4/Z7sYu9E5++3ZrXXsrzDfnqE2Oq93szcJKAJX9mZZQwEGt67/v6ZJrOP5gEyNAMqo2qSuZmRaUpi0jkAAAACjIAmAPjRqn25uuW99br6tZ9V7nDVu823Ww95z6/en6vckvbpG2iWkvcICar3erPknCnn8JXdhxofCGQyA5opBDQDKr2BkvO+MaG1rgcAAADaGwFNAPCj/607KMmYFL5gW/3Zl9/VCGi6PdKCbYfq3c7XqkvO68/QNEvRmXIOXzEzNIc1MBDINKCq5PxALiXnLbE5rcCnQca0qpLzuj00zZJzemgCAAAgMAhoAoCflDtcmr8xw/v9/9al1dkmq6hc61PzJUmXTEmWJH3fzgHNyNAmppxX1J9ZCrSEu8aEczI0fW9LeoHOfXaZ5r6wXJVOd5vvr9zhUk5xhSR6aAIAAKDjIaAJAH6yeEeWisqd3oDh4h1ZdcrJF27Lkscjje8XrcuPGSBJ+nFnToPl6b5U0sRQILO3ZkklGZpou7T8MpU73Aq2WdW/gQnnpgFxRoZmdlGFSvn/a5ZXlqbI5fYoLb9MX23OaPoGTcgsMLIvw4Jsigmv3ZbCDHAeLqlsl9cqAAAA4EgENAHAT8yMzEun9deYpCg53R59sal2oMEsN58zqrfGJEUpKTpUZQ6Xlu3O8fv6irxDgRoKaBpBDErO4Qs7Dxnl5oN7Rchua3z3Izo8yBtE20+WZpNyiiv0+YZ07/ev/ZTS5vs0B/4kxoTKYqk9kT4qzK6IYOOAR0YBZecAAABofwQ0AcAP8ksrtWh7tiTp/El9df6kvpKMieem0kqnllYFLueM6S2LxaKTR/eW5P+yc4fL7S1LbSigafbWZCgQfGGXWW7eRP9Mk9lHc/9h+mg25Z2VB1Tpcmt47x4Ktlm17kC+t5VFa5n9MY8sN5cki8VC2TkAAAACioAmADTD1vRCHfvYQj329fZmbf/lpkxVutwa2SdSI/tE6ewJSbJapDX783SgKuPsx505qnC6lRwXphFVQZ6TR5kBzSy53R7//DCqHaRsqOTcLJUvJqDZIR04XKoT/7FYd3+8UR6P//5XfGVX1YTz4U30zzQNqCpLJ0OzcZVOt95csV+SdOMJQ3XWhERJ0mvL9rXpfr0TzqPrBjQlKbEqoJlGQBMAAAABQEATAJpQWunUTe+s1cG8Mj2/eI++2ZLZ5G3MTEwzM7N3VKhmDu1pXLfeuM7Mwpwzqo+3pPOYwfGKDLEru6hC6w/m+/pH8TLLyEPsVgU1UP5rBjoJaHY8DpdbN7+7TnuzS/TOqlS993NqoJfUpF3eCefNC2gOZDBQs3y1OUNZRRXqFRmi08cm6uoZgyRJX2zKUFZh68vBvQHNejI0JalvTGit7QAAAID2REBTUkVFhe68804lJSUpLCxM06ZN03fffRfoZQHoIB6cv017sktksxpBxzs/2ugdmFGfg3mlWpWSK4tFOmdikvfycydWl507XW4t3J4lSTp5dIJ3m2C7VceP6CWpur9mWxWUOnT7+xv01Hc75arK+jQH/TRUbi7VCGjSQ7PDmff9Lq1Pzff+Tz7w+VbvBPGOqOaE86EJLSs5P5BLyXljzH6Zl08boGC7VeP6RWvygFg5XB79d+WBVt9vmjegGVrv9WbmJgFNAAAABAIBTUlXXXWVnnrqKV122WWaN2+ebDabzjjjDC1dujTQSwMQYF9vztQ7qw7IYpFevvJojesbrfxSh259b703OHikT9cbwzmOGRSvxBrlmqeO6a3QIKv25pTotZ9SlFtSqeiwIE0dGFfr9nPMPpo+CGhmFZbr4n8v10drD+qfC3bpD++uU6XT7Q1S9ghtOKAZWRXQZMp5x7Ji72E9u3i3JOn/Lp6oY4f2VJnDpT+8u04Vzo45cTotv0yllS4F2SzezMumDDAzNHPI0GzI+tR8rTuQryCbRZdO6++9/OqZAyVJ/115oNX/E+awn4YyNM3LGQoEAACAQOj2Ac1Vq1bp3Xff1SOPPKInnnhC1113nRYuXKgBAwboT3/6U6CXByCAMgrKdNfHGyVJ1x03WLNHJGjeJRMVFmTT8r2H9e8f99a5jcfj8U43N8vNTZGhQZozuo8k6YlvdkiSThyZUGfi8+wRCbJbLdqVVayUnNZnpx04XKoLX1iu7ZlFio8IVpDNovkbM/SbN1Yrp7hCkhQRTIZmZ5JfWqlb31svj0eaO7mfzp6QpH9cNEGx4UHakl6oJ6v+rzoaMztzcM8eTU44N5kZmhkFZR02UBtoZp/Ms8cnqVdkiPfyU8f0UZ+oUOUUV+iLjRney11uj77YmKF/LdjVaEavx+NpsuQ8sSpz0189NFNySvTMwl36dH2aHC63Xx4D6ArWHcjTo19t1+a0gkAvBQCAdtXtA5offvihbDabrrvuOu9loaGhuuaaa7R8+XKlpnb8vmQAfM/l9ui29zYov9ShcX2jdfucEZKkwb166P5zRkuS/vHtDm04YpLwlvRC7c4qVrDdqtPG9alzv+dPMkrQK6omjJvZmDVFhwVp2mAja7O1Zec7Mot04Qs/6UBuqfrHhet/v5up/1w5RWFBNv2wM1t3frRJUuMZmj3oodmheDwe3f3xJmUUlGtQzwjdf84YSUZ/1scvnCBJemnJPv24MzuQy6yX2T9zaDP7Z0pSzx7BCg+2ye2RDuZR1nykrMJyfbHJCFZeVZWRaQqyWXXF9AGSpFeXpajc4dJbK/brxH8s1o1vr9U/vtupOU//oOveWK21B/Lq3HdBmUOllUYQOTG6/pLzvjWmnPtyKNWmgwW68b9rdeI/FuvJb3fqD++u1+wnFuvVZftUSrY4IMl4P1i0I0sXv7hc5z/3k174YY/Oe3aZnl20u8HqEQAAupqGP8l2E+vWrdPw4cMVFRVV6/KpU6dKktavX6/k5ORALK1DWbQ9i0mm6DJsVotG9InU2KRoBdvrHtfJLqrQy0v3afnewwoPtmneJRNrbXfR0cn6YWe2vtyUqT+8u07XzhrsvW7xDiOYNGdUb0WFBtW571nDeikuIli5JZUKtll13PBe9a5xzqjeWrb7sD5ae1BhwbYW/XwVTrf+uWCXCsocGtE7Um9eM1UJUaHqHx+ut66dqqtf/VkFZQ5JjffQNK+rcLr15vIU7+CijmJgfIQm9Y+pd0p7UblD6w7k60Bu1ylXTskp0VebM2W3WjTvkom1fu45o3vr8mP6660VB3T7Bxt080nD1JH+Wt9vM/rFDm9m/0xJslgsGhAfoW0ZhXprxX4N6dX8YKhkPM9H9onUmAae51lF5Vq7P085xZUtut+OYuW+XDlcHk0eEKvx/WLqXH/JlGTNW7BLm9IKdMwjC5RfajznY8KDNDYpWkt35+jbrYf07dZDmjooTmeOS/T2ZM0qMjK4e/YIVmhQ/a8/faoCneUOt15euq/B7ZrL7fHomy2ZWrb7sPeyGUPitSOzSGn5ZXrg863654JdunRa/1qtPIDuptzh0odrDmp7pnGgyG61aFRilDalFeiJb3Zo4fYsPX3RRPWv0d4ju6hCa/bneasz2ktYkE0TkmM0pFdEs/YhKp1ubU4v0I7MIgKzANCEgfEROnZYz0AvI6C6fUAzIyNDiYmJdS43L0tPT6/3dhUVFaqoqN4pKCws9M8CO4g3lqdo0Y6Ol/UDtEWI3aoJyTGaMjBWidFhWp+ar9UpubWmKt9/9hgNPiKQYrFY9Mj547XuQL5SDpfqL59srnPf59YYBlRTkM2qs8cn6vXl+zV9SHyDAcWTR/fW/Z9v1fbMonrvvzmO6h+jV6+aqujw6sDq5AFxeu/66frVK6uUXVShmLC6QVdTj1C7bFaLXG6P7v10S6vW4G82q0WjEiN19IA4De8dqR2Zhfo5JU/bMwvVVT8L3X7KiHoDWH8+Y7RW7M3V7qxi3dvK/xl/G9GnZUHJwT2NgOary1Ja/ZihQVZN6BejKQPj1Ds6VOsP5Gv1/lzt7yLT06+aMbDey+N7hOi8iUl6f/VB5Zc61DcmTNfOGqSLpyQrPNiu3VlFevGHvfpkfZpW7cvVqn25de6jb2zD/U5D7Db1iQpVZmG5Hvpim69+HNmsFp0zIUnXHz9YI/tEqdzh0gdrDuqlH/fqQG6pnl20x2ePBXRmEcE2/XJqf/362EFKjA7VR2vTdP9nW7Rmf55On/ejrpk1WGl5ZVqzv/Z+TSDEhgdp8oA4TRkYq4E9I2odcHO6PdqSXqDVKXlan5rvrWABADTunAlJ3T6gafH4sk6oExoyZIhGjBihL7/8stble/fu1ZAhQ/T000/rlltuqXO7+++/Xw888ECdywsKCupke3YF/1qwS5vT6c2DrqHc4dbGg/nKq8pYOpLFYmSS/eKovrruuMENZhVsOligF3/cU6e/28CeEfrTqSO92U5HOlxcoX8u2KXLjxmgYb0bzlh7ddk+rdh7uMHrGzMwPkJ/OHmYwhvokXngcKn+s3SvLpnSX6OTGn7NenvlAf2wM6tVa/Anl9ujbRlFjWaOJ8eFaUTvKDWzZWOnMCwhUrfNGS5rA/9be7KLNe/7XR2y52SfqFDdc+Yohdibn8m3Jb1AL/ywV5Wt+HnKqp7n+Y08z0f0jlT/uHB1sOTjZhvYM0J/PGVEg31Js4sq9K+FuzSpf4zOGp+koHq2yygo0xvL92tvdu2emjarRZcfM0AzhjS8o/z15kx9si5NHvlmV3JAfIR+NX2A+tUTSHW63Ppqc6a+2ZJJT010e+P7xejyaQNqHbCUpNTcUt3+/gatSql9gCJQr3e5JZXaeLCgRUHK2PAgjesXo7CgLvTmDQB+MGVgXK1Kwa6ksLBQ0dHRTcbXun1Ac+zYserdu7cWLFhQ6/KtW7dqzJgxeuGFF3T99dfXuV19GZrJycldNqAJdDUej0d7sku0Zn+uVqfk6VBRhcb1jdLRA+N0VP9YRTeSuYiOI6OgTKtT8rQ6JVd7sks0rHcPHT0gTkcPjFXvqPp7/6H7cLs92ptTbPyP7M9TVlGFJvSL1uQBsZrE8xxAF+Rye/T6Tyn6aU+ORvaJ0uSBsQHdrzHLyNek5Gn1/lxlF9Uue7dYLBrUM0JHD4jV0QPjml2eDgDoughoNtOcOXOUlpamrVu31rp8wYIFOvnkk/XZZ5/p7LPPbvJ+mvsLBwAAAAAAAFBXc+Nr3T6Xf+LEidq5c2edHpgrV670Xg8AAAAAAACgY+j2GZorV67UMcccoyeeeEJ33HGHJKOcfOzYsYqPj9eKFSuadT8FBQWKiYlRamoqGZoAAAAAAABAC5ktHfPz8xUdHd3gdt1+yvm0adM0d+5c3X333crKytLQoUP1+uuvKyUlRS+//HKz76eoqEiSlJyc7K+lAgAAAAAAAF1eUVFRowHNbp+hKUnl5eW699579dZbbykvL0/jx4/Xgw8+qFNPPbXZ9+F2u5Wenq7IyMhu3cjajKSTqQp0fDxfgc6B5yrQefB8BToPnq9Ax+TxeFRUVKSkpCRZrQ13yiSgCZ9iOBLQefB8BToHnqtA58HzFeg8eL4CnVu3HwoEAAAAAAAAoPMgoAkAAAAAAACg0yCgCZ8KCQnRfffdp5CQkEAvBUATeL4CnQPPVaDz4PkKdB48X4HOjR6aAAAAAAAAADoNMjQBAAAAAAAAdBoENAEAAAAAAAB0GgQ0AQAAAAAAAHQaBDQBAAAAAAAAdBoENAEAAAAAAAB0GgQ0AQAAAAAAAHQaBDQBAAAAAAAAdBoENAEAAAAAAAB0GgQ0AQAAAAAAAHQaBDQBAAAAAAAAdBoENAEAAAAAAAB0GgQ0AQAAAAAAAHQa9kAvoKtwu91KT09XZGSkLBZLoJcDAAAAAAAAdCoej0dFRUVKSkqS1dpwHiYBTR9JT09XcnJyoJcBAAAAAAAAdGqpqanq169fg9cT0PSRyMhIScYvPCoqKsCrAQAAAAAAADqXwsJCJScne+NsDSGg6SNmmXlUVBQBTQAAAAAAAKCVmmrnyFAgAADQMRQclNyuQK8CAAAAQAdHQBMAAATegZXS02Okr/4U6JUAAAAA6OAIaAIAgMA7tLnqdEtg1wEAAACgw6OHJgAACLyKoqrT4sCuAwAAAPADl8slh8MR6GUEXFBQkGw2W5vvh4AmAAAIvIpC47SyKLDrAAAAAHzI4/EoMzNT+fn5gV5KhxETE6M+ffo0OfinMQQ0AQBA4JGhCQAAgC7IDGYmJCQoPDy8TUG8zs7j8ai0tFRZWVmSpMTExFbfFwFNAAAQeOVVGZoVZGgCAACga3C5XN5gZnx8fKCX0yGEhYVJkrKyspSQkNDq8nOGAgEAgMAzA5muCslFbyEAAAB0fmbPzPDw8ACvpGMxfx9t6SlKQBMAAASe2UNTIksTAAAAXUp3LjOvjy9+HwQ0AQBA4JUXVJ+vpI8mAAAAgIYR0AQAAIFXMyuTDE0AAAAAjSCgCQAAAq9WyTkZmgAAAAAaRkATAAAEXs2szEoyNAEAAIDOYOnSpZo5c6bi4+MVFhamkSNH6umnn/b749r9/ggAAACNcZRLrsrq7yk5BwAAADqUyspKBQcHe7/3eDxyuVyKiIjQ73//e40fP14RERFaunSprr/+ekVEROi6667z23oIaAIAgMCqWW4uUXIOAACArsvjkRyl7f+4QeFSC6aLz549W2PHjpXdbtdbb72lw4cPS5K+/PJL/eUvf9GmTZv07bffavbs2Zo0aZL3dgMHDtTHH3+sJUuWENAEAABd2JEZmUw5BwAAQFflKJUeTmr/x70nXQqOaNFNXn/9dd1www1atmyZFi9erN/+9re666679OSTT2rw4MGKjY2tc5t169bpp59+0kMPPeSrldeLgCYAAAis8oLa35OhCQAAAATcsGHD9Pjjj0uSMjIyJEl/+9vfNGfOnDrb9uvXT9nZ2XI6nbr//vt17bXX+nVtBDQBAEBgHZmheWQJOgAAANBVBIUb2ZKBeNwWmjx5cp3Ljj766Hq3XbJkiYqLi7VixQrdddddGjp0qH75y1+2+DGbi4AmAAAIrCMDmJScAwAAoKuyWFpc+h0oERF111nfZZI0aNAgSdK4ceN06NAh3X///X4NaFr9ds8AAADNUc5QIAAAAKCrcLvdqqio8OtjkKEJAAACq07JeVH92wEAAADoUJ599ln1799fI0eOlCT9+OOPevLJJ3XzzTf79XEJaAIAgMAyS86DI6XKIkrOAQAAgE7C7Xbr7rvv1r59+2S32zVkyBA99thjuv766/36uAQ0AQBAYJkBzagkKWcHGZoAAABAgC1evLjW97Nnz5bH46mz3U033aSbbrqpnVZVjR6aAAAgsMprBDQlMjQBAAAANIqAJgAACCwzIzOqb+3vAQAAAKAeBDQBAEBgVRyRocmUcwAAAACNIKAJAAACy1tynmicOkoktztw6wEAAADQoRHQBAAAgXVkyblEH00AAAB0GW4O1tfii98HU84BAEBgmSXnEb0kq11yO40gZ2hUYNcFAAAAtEFwcLCsVqvS09PVq1cvBQcHy2KxBHpZAePxeFRZWans7GxZrVYFBwe3+r4IaAIAgMAyMzRDo6XgHlJ5PhmaAAAA6PSsVqsGDRqkjIwMpaenB3o5HUZ4eLj69+8vq7X1heMENAEAQOC43dUBzZBIKSTKCGgyGAgAAABdQHBwsPr37y+n0ymXyxXo5QSczWaT3W5vc6Zqlwxo/vzzz3r99de1aNEipaSkKD4+Xsccc4weeughDR8+vNa227Zt06233qqlS5cqODhYZ555pp566in16tUrQKsHAKAbqSyS5DHOh0RJIT2M82YZOgAAANDJWSwWBQUFKSgoKNBL6TK6ZEDzscce07JlyzR37lyNHz9emZmZeuaZZ3TUUUdpxYoVGjt2rCTp4MGDOu644xQdHa2HH35YxcXFevLJJ7Vp0yatWrWqTbX8AACgGczsTGuQZA8xSs4lSs4BAAAANKhLBjRvu+02vf3227UCkhdffLHGjRunRx99VG+99ZYk6eGHH1ZJSYnWrFmj/v37S5KmTp2qOXPm6LXXXtN1110XkPUDANBtlFdlYoZGSRZLjQxNApoAAAAA6tf67psd2IwZM+pkVw4bNkxjxozRtm3bvJd99NFHOuuss7zBTEk6+eSTNXz4cL3//vvttl4AALotb//MqonmIZHGKRmaAAAAABrQJQOa9fF4PDp06JB69uwpSUpLS1NWVpaOPvroOttOnTpV69ata/T+KioqVFhYWOsLAAC0kNkr0wxkBkfWvhwAAAAAjtBtApr//e9/lZaWposvvliSlJGRIUlKTEyss21iYqJyc3NVUVHR4P098sgjio6O9n4lJyf7Z+EAAHRl5QXGaWi0cUrJOQAAAIAmdIuA5vbt23XjjTdq+vTpuvLKKyVJZWVlkqSQkJA624eGhtbapj533323CgoKvF+pqal+WDkAAF2ct+Q8svYpJecAAAAAGtAlhwLVlJmZqTPPPFPR0dH68MMPZbPZJElhYWGSVG8WZnl5ea1t6hMSElJvMBQAALSAt+S8qoemOeXcDHQCAAAAwBG6dECzoKBAp59+uvLz87VkyRIlJSV5rzNLzc3S85oyMjIUFxdHwBIAAH8zA5eh5lAgApoAAAAAGtdlA5rl5eU6++yztXPnTn3//fcaPXp0rev79u2rXr16afXq1XVuu2rVKk2cOLGdVgoAQDdW3sBQIErOAQAAADSgS/bQdLlcuvjii7V8+XJ98MEHmj59er3bXXDBBZo/f36t/pcLFizQzp07NXfu3PZaLgAA3Ze3h6aZoWlOOSegCQAAAKB+XTJD8/bbb9dnn32ms88+W7m5uXrrrbdqXX/55ZdLku655x598MEHOuGEE/SHP/xBxcXFeuKJJzRu3DhdffXVgVg6AADdS8URGZqUnAMAAABoQpcMaK5fv16S9Pnnn+vzzz+vc70Z0ExOTtYPP/yg2267TXfddZeCg4N15pln6h//+Af9MwEAaA/lBcZpaLRxag4FouQcAAAAQAO6ZEBz8eLFzd52zJgx+uabb/y3GAAA0LA6JedVp5ScAwAAAGhAl+yhCQAAOomGSs4riySPJzBrAgAAANChEdAEAACBY2ZohlZlZpol5x635CgNzJoAAAAAdGgENAEAQOCUH5GhGRwhyWKcp+wcAAAAQD0IaAIAgMBwVkiuCuO82TvTYqkObjIYCAAAAEA9CGgCAIDAMMvNpeogplRddm721wQAAACAGghoAgCAwCgvME6De0hWW/Xl5mAgSs4BAAAA1IOAJgAACAwzQ9MsNzdRcg4AAACgEQQ0AQBAYFQcMRDIFEyGJgAAAICGEdAEAACBYWZohjaQoUkPTQAAAAD1IKAJAAACo9zM0DwioGlmaFJyDgAAAKAeBDQBAEBgNFRy7s3QJKAJAAAAoC4CmgAAIDDMgGadknMyNAEAAAA0jIAmAAAIjKZKzumhCQAAAKAeBDQBAEBgmEOBjgxomt9Tcg4AAACgHgQ0AQBAYFByDgAAAKAVCGgCAIDAKG9gKJC35LyofdcDAAAAoFMgoAkAAAKjwZJzM6BJhmazuZzSx9dJy58N9EoAAAAAvyOgCQAAAqOigQxNM8BZSYZms6Wtlja+Jy18SHK7A70aAAAAwK8IaAIAgMAwMzSP7KEZTIZmi+XsNE4dpVJRemDXAgAAAPgZAU0AABAY3h6a0bUvD6GHZouZAc0jzwMAAABdEAFNAADQ/tzuRkrOq753OyRnRfuuq7PK2VX/eQAAAKALIqAJAADan6NEksc431DJuUTZeXORoQkAAIBuhIAmAABof2a5udUu2UNrX2e1SUHhxnkzixMNc1ZIeSnV3xPQBAAAQBdHQBMAOoKlT0tPjZZy9wVuDXsXS5/cKJXlBW4N6D7M/pghUZLFUvd6M0uzkgzNJuXulTw1JptTcg4AAIAujoAmAHQEP78sFaZJ2z4L3Bq++bO0/i1pxQuBWwO6DzPz8shyc5PZR5OS86aZGZnxw4zToozqDFgAAACgCyKgCQCBVpghFaQa59PXB2YNxdnSoc3G+Q3vGANbAH9qaCCQKYQMzWYzA5r9pkg9ehvnD5OlCQAAgK6LgCYABNrBVdXnM9YHZg0pP1afz98vHVgemHWg+zAzCEOi678+2MzQJNOwSWaJec9hUs/htS8DAAAAuiACmgAQaKk1Apq5e6XygvZfw76qgKbFZpxueLv914DupckMTUrOm83M0Ow53Ahq1ryss8pLkR4fLH19T6BXAgAAgA6IgCYABNrBn2t/n7Gh/dew9wfjdMZNxumWT6XKkvZfB7oPcyhQgz00KTlvFo+nRobm8BoZmp08oLn1U6n0sLTuTcntCvRqAAAA0MEQ0ASAQHJWVvfN7D3WOG3vPpr5B6S8fUZ25qzbpNiBUmWRtG1++64D3Yu35LyBgKY55ZwMzcYVZRhBX6tdihtUI0Ozk5ec7//JOK0orO7vCwAAAFQhoAkAgZS5UXJVSOHx0pjzjMvau4+mmZ3Zd7IUGi1N+KXxPWXn8CczQ7OpoUD00GycmYkZO0iyBVVnaB7eI7mcvnscj0dyVvju/hrjdkn7a/TxNYObAAAAQBUCmgAQSGb/zH5TpKRJxvn2ztDcVxXQHHy8cTrhEuN07w9SwcH2XQu6DzNQ2WDJedXllJw3rma5uSRF9ZPsYZLbYQz48pXVr0gPJUjbv/TdfTYka6tUUaOX8P5l/n9MAAAAdCoENAEgkA7WCGgmVgU0c/e032Agj6d6INCgqoBm7EBpwExJHmnje+2zDnQ/5v94QxmalJw3j3cgUFWpudUq9Rxa+zpf+Pll43T1K767z4aYGZnhPau/93j8/7gAAADoNAhoAkAgpVYNBEqeKkXES9HJxvcZG9vn8bN3SMWHJHuoEVQ1mWXn698hkAD/8JacR9d/vbfkvKh91tNZ1ZxwbvL1YKC8/VLWFuP8vh/8H2Q2MzKnXGO8NpUe7vxDjgAAAOBTBDQBIFAK06XCg5LFKiUdZVyWOME4ba8+mma5ef9jpKDQ6stHn2uUrR7eJaWtaZ+1oHtpsuS8KnOTkvPGeUvOh1VfFm8OBvJREHDn19XnXZXS3kW+ud/6eDzV/TMHn1B9oIU+mgAAAKiBgCYABIrZP7P3mOpstKSJxml79dE0BwKZ5eam0Chp1NnG+fUMB4IfNDUUKDiy9naoq6JYKkwzzscPrb7c15POd1T1zQyNqfr+K9/cb30O75FKsiRbiNT3KGnADONyApoAAACogYAmAATKwapy835Tqy8z+2hmbPD/47ucUspS4/zg4+teP/FS43TzR5KjzP/rQfdSXpWhGdJQhmZVkJ8MzYYd3m2cRvSSwuOqLzdLzrN3tL1lRHlB9evEnAeM051fG5PI/cEsN+83RbKH1AhoLqP9BQAAALwIaAKAP7nd0rJ50tbP6l5nZmgm1whomhmah3f7PzMtY4MxSTgkWkqcWPf6QcdJMf2l8nxpw7v+XQu6H7PkvMmhQGRoNujICecmM1uzPN/oP9kWu7+X3E6jjH3iZVJotHGf5gEZXzMzMc1AZr8pktVuZKLmH/DPYwIAAKDTIaAJAP60+SPpu79KH1wlHVxdfbmzorpPZs1hPBE9pah+kjz+Hwxk9s8ceKxktdW93mqTjvmdcX75s0ZwFvAFZ6XkLDfON9VDkynnDTtywrkpOFyK7l97m9Yyy8tHnC7ZgqRhp1Rd/mXb7rchRwY0gyOkpEm1rwMAAEC3R0ATAPzF5ZAW/d0473FJH18nVZYY32dsNIZrhMdLcYNr3669BgOZAc36ys1Nky43MjgP75J2fePf9aD7SKsK7lvt1b0yj2QGNJ1lRnsE1FXfhHNTTx8MBnI5pF3fGudHnFF1erpxuuPr+m/TFvkHpIIDxv9Fzcz1mmXnAAAAgAhoAoD/rHtLyttn9LeL6ivl7pG+vde47mBVuXm/qZLFUvt27TEYyFEuHVhhnD9yIFBNIZHS0Vcb5396xn/rQffhdklf/ck4P+GXks1e/3ZmyblEH82GNFRyXvOytgwGOrDC6KEZFlcdYBx6shFwzNlhDPDxJXO6eeJEIzPTNGBm1fVkaAIAAMBAQBMA/MFRLv3wuHF+1u3Sec8Z51e/LO36rkb/zCl1b2v2s/Rnhub+ZUbJb4/eUq8RjW877XojgLF/qZS2xn9rQvew+hUpc5PRi/Hk+xvezh5sTLqW6KNZH7ereijQkSXnNS9rS4amWW4+/LTqthSh0dUBRl9POzczMM2MTFPyNEkW46BQUaZvHxMAAACdEgFNSRUVFbrzzjuVlJSksLAwTZs2Td99912glwWgM1v9slSUbvTDnHy1NHh2dT/KT2+szjSqOeHcZGZo5uzyTyBn34/Sh782zg89uW6G6JGikqRxc43zZGmiLUpypIUPGudPvNfoGdsYJp03LP+A5KqQ7KFSdHLd670Zmq0MaHo81X0yzTJzk1l+7vOAptk/c2bty8NipD5ja28DAACAbo2ApqSrrrpKTz31lC677DLNmzdPNptNZ5xxhpYuXRropQHojCqKpCX/MM7PvlMKCjXOn/RXqddIqfiQVJIlWWxS36Pq3r5HghSZJMljZLL50upXpTfPN6Yf9z1aOvmB5t1u+o3G6dZPpbz9vl0Tuo/v7zdKmPuMk47+ddPbeyedtzGgWZprBPGfGiNt/rht99VRmKXk8UPrH+plBjTz9hsZ4y2+/51GywxbsDTkxNrXjTjNOD2w3Pjd+kJxltGrVxap/7S611N2DgAAgBq6fUBz1apVevfdd/XII4/oiSee0HXXXaeFCxdqwIAB+tOf/hTo5QFoC49Hytws5ae2/b5cTqOnZXM+vK94Xio9LMUNkSZcWn15UJj0i39L1iDj+95javeJq8nXfTTdLumru6T5t0hup5FxedUXUo9ezbt9n3HS4BOM4UYrX/DNmtA2breUsUEqTA/0Sprn4Gpp3ZvG+TP+UX8Q7kjeSeeFrX/cfUuk52dKmz+SCg9KH15tZEl39unpDU04N/VIMAZ6yWOUareUmZ056LjqTFlT7EApYbTxerD7+5bfd33MQGXvsVJYbN3rvYOBCGgCAABAaqATf/fx4Ycfymaz6brrrvNeFhoaqmuuuUb33HOPUlNTlZxcTylXd+d2GxlmbpcU2ad5H0yB9pKzS9r4vrTpfSkvxbis/wxp/EXS6HOl8Ljm3Y/HY/Sx3Pi+EQwpPmT09Bv7C2nqb6S+k+vepjRX+ulfxvkT7qk78CRxgpGp+d29dcs4a2030QgotKWPptstZW0xBm1s+Z90oCoQcOJfpFl3NF1qfqQZv5f2LpLWviEdf6dRBor2l7VN2vietPEDI0AnizRoljT+YmnU2UaPw47G7ZK+uN04P+HS+jPw6mMGNFtTcu5ySIsfkZY8JcljHGAYdooRkF/3lvG8uPBlKWlSy++7I2hswrlkPL97DjMmyufsNA6geDxSWZ4RII5MlOwhDd+/WU7e0OvUiNOlrK3G69T4i1r/c5i85ebT67++f1VAM2uL8Trb3NfxzoR9K7RGZYnRW9btanrbkB5Sjz6StdvntAAAuoBuH9Bct26dhg8frqioqFqXT51q9LVbv359vQHNiooKVVRUeL8vLGxD9khn8PN/pLS1Rs+ugoNSYZrkqjSus9qNHnvRycZXcHhg14pGWIyMwNAoKTRGCokyBm+UFxofcM1T82/b0QSFG8GakCjjZwgKM3bkywuq135guZS+rvo29jBj+M2Bn4yvL/8oDZsjxQ+puq9o477sIUapuHlf5fnS3sW1+8/ZwyRnmbThHeMr6Shp0uVGD7vyAuPxU1cap73HSmN+Uf/PMfNmafQ5Rn/NhpgZmvuXSz+/XOPvU2RkRTWlIE1KrZpQXHP9578gjTmv6dvXZ8hJRlZW1lbpg6ukuEGtux9fCQqv/l8IiTL+tytLqn5XVX9HZ1lg1+hLHo8RnKrZhiAoXHKUGn1R9/1oBA2Hnmxk53UkxVlGcD4kSprTzDYHUnXJ+a5vjfce83nubEYJddra6gMCk66QTnvU+DA/6izp4+uMrMX/zJHGXWi8lnQ2uxcYpw0FNM3r0lZLCx6UFj9q/A5rBod79K567+5nZEWaBzk8nurBZcMbCmieYbTW2PWdNP/Wtv88ZgD1yIFA3rX2Mn6enJ3Sp7+XInu3/TE7AmeFVJBqVBLU3Ley2KSovlIM+1Y4gscjlWQb/zcFB42KkJawBhn77TH9jee+P1//LDbjwFRoVPX+mz206QOqblf1Ppm5/9OV3s+BzsIeVr2fHVq1r+0oq/HZscDYD0VgJB0lHXVFoFcRUN0+oJmRkaHExMQ6l5uXpafXX8r3yCOP6IEHWvChrLPb+Y3xgbImi83YIXE7jUBn/oHArA04ksUmDT3JyFgbcbrxZrvpQyPT8tCm6lLK5rCHGh/cx19s9JHL3Citekna8rGUvtb4qs+Jf2k8AyJ2YOOPa046LzggfXFb89d7pOAeUvJUI0gw+nyp59DW35fFIs24SfrkBiNTc++i1t8XWs8aZGQajr/ImD5dkiV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",
            "text/plain": [
              "<Figure size 1600x2000 with 13 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "window_size = 240\n",
        "i=random.randint(0,len(df)-window_size)\n",
        "df.iloc[i:i+window_size].plot(subplots=True, fontsize=12, figsize=(16,20))\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "IXkd8_iUKAuk"
      },
      "outputs": [],
      "source": [
        "# nice_df = pd.read_csv('data/donnees-synop-essentielles-omm-NICE.csv', sep=\";\", parse_dates=True, index_col='Date')\n",
        "# nice_df.sort_index(inplace=True)\n",
        "\n",
        "# display(nice_df.head(10))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kKFAJ_d4di1_"
      },
      "source": [
        "Export new dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "tuOvunygPvVT"
      },
      "outputs": [],
      "source": [
        "import os"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CZzZ0F0bMVxi",
        "outputId": "cd77aa8d-08f6-4566-8de8-2d320b42014e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Dataset saved. (3.5 Mo)\n",
            "Synop description saved.\n"
          ]
        }
      ],
      "source": [
        "output_dir = \"data\"\n",
        "new_dataset_filename = f'{output_dir}/cleaned-donnees-synop-essentielles-omm(LYS).csv'\n",
        "new_descr_filename = f'{output_dir}/new-description-synop-essentielles-omm(LYS).json'\n",
        "\n",
        "df.to_csv(new_dataset_filename, sep=';', index=False)\n",
        "size = os.path.getsize(new_dataset_filename)/(1024*1024)\n",
        "\n",
        "print(f'Dataset saved. ({size:0.1f} Mo)')\n",
        "\n",
        "with open(new_descr_filename, 'w', encoding='utf-8') as f:\n",
        "    json.dump(code2desc, f, indent=4)\n",
        "print('Synop description saved.')\n"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}