EDA_Airbnb_Bookings_Analysis_Capstone_Project.ipynb

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      "source": [
        "<a href=\"https://colab.research.google.com/github/Navjotkhatri/Airbnb-Bookings-Analysis/blob/main/EDA_Airbnb_Bookings_Analysis_Capstone_Project.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y06xIdG26kRF"
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      "source": [
        "## <b> Since 2008, guests and hosts have used Airbnb to expand on traveling possibilities and present a more unique, personalized way of experiencing the world. Today, Airbnb became one of a kind service that is used and recognized by the whole world. Data analysis on millions of listings provided through Airbnb is a crucial factor for the company. These millions of listings generate a lot of data - data that can be analyzed and used for security, business decisions, understanding of customers' and providers' (hosts) behavior and performance on the platform, guiding marketing initiatives, implementation of innovative additional services and much more. </b>\n",
        "\n",
        "## <b>This dataset has around 49,000 observations in it with 16 columns and it is a mix between categorical and numeric values. </b>\n",
        "\n",
        "## <b> Explore and analyze the data to discover key understandings (not limited to these) such as : \n",
        "* What can we learn about different hosts and areas?\n",
        "* What can we learn from predictions? (ex: locations, prices, reviews, etc)\n",
        "* Which hosts are the busiest and why?\n",
        "* Is there any noticeable difference of traffic among different areas and what could be the reason for it? </b>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dByMsuzT8Tnw"
      },
      "source": [
        "#imports our playground were we play\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gNb8KkIuXBQj",
        "outputId": "7b8f720e-1855-403c-8d78-6e4d600033e6"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "working_dir_path=\"/content/drive/MyDrive/Colab Notebooks/python/ Airbnb Bookings Analysis - Capstone Project./Airbnb NYC 2019.csv\"\n",
        "bnb=pd.read_csv(working_dir_path)"
      ],
      "metadata": {
        "id": "qNAd-6Y8XIVQ"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "***Data profiling and cleaning--***"
      ],
      "metadata": {
        "id": "ggXl2xUtgAjV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#we have a 48895 rows and 16 columns in this dataset\n",
        "bnb.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zOjng6wUYLgA",
        "outputId": "73972dd6-a9c5-4f0a-f65a-492edd8b5381"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(48895, 16)"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#top ten rows of dataset for manual analysis\n",
        "bnb.head(10)"
      ],
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          "base_uri": "https://localhost:8080/",
          "height": 774
        },
        "id": "uzi4sIsrYNGy",
        "outputId": "a23db382-4f69-44e7-c691-ccd41d02cdef"
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      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     id                                              name  host_id  \\\n",
              "0  2539                Clean & quiet apt home by the park     2787   \n",
              "1  2595                             Skylit Midtown Castle     2845   \n",
              "2  3647               THE VILLAGE OF HARLEM....NEW YORK !     4632   \n",
              "3  3831                   Cozy Entire Floor of Brownstone     4869   \n",
              "4  5022  Entire Apt: Spacious Studio/Loft by central park     7192   \n",
              "5  5099         Large Cozy 1 BR Apartment In Midtown East     7322   \n",
              "6  5121                                   BlissArtsSpace!     7356   \n",
              "7  5178                  Large Furnished Room Near B'way      8967   \n",
              "8  5203                Cozy Clean Guest Room - Family Apt     7490   \n",
              "9  5238                Cute & Cozy Lower East Side 1 bdrm     7549   \n",
              "\n",
              "     host_name neighbourhood_group       neighbourhood  latitude  longitude  \\\n",
              "0         John            Brooklyn          Kensington  40.64749  -73.97237   \n",
              "1     Jennifer           Manhattan             Midtown  40.75362  -73.98377   \n",
              "2    Elisabeth           Manhattan              Harlem  40.80902  -73.94190   \n",
              "3  LisaRoxanne            Brooklyn        Clinton Hill  40.68514  -73.95976   \n",
              "4        Laura           Manhattan         East Harlem  40.79851  -73.94399   \n",
              "5        Chris           Manhattan         Murray Hill  40.74767  -73.97500   \n",
              "6        Garon            Brooklyn  Bedford-Stuyvesant  40.68688  -73.95596   \n",
              "7     Shunichi           Manhattan      Hell's Kitchen  40.76489  -73.98493   \n",
              "8    MaryEllen           Manhattan     Upper West Side  40.80178  -73.96723   \n",
              "9          Ben           Manhattan           Chinatown  40.71344  -73.99037   \n",
              "\n",
              "         room_type  price  minimum_nights  number_of_reviews last_review  \\\n",
              "0     Private room    149               1                  9  2018-10-19   \n",
              "1  Entire home/apt    225               1                 45  2019-05-21   \n",
              "2     Private room    150               3                  0         NaN   \n",
              "3  Entire home/apt     89               1                270  2019-07-05   \n",
              "4  Entire home/apt     80              10                  9  2018-11-19   \n",
              "5  Entire home/apt    200               3                 74  2019-06-22   \n",
              "6     Private room     60              45                 49  2017-10-05   \n",
              "7     Private room     79               2                430  2019-06-24   \n",
              "8     Private room     79               2                118  2017-07-21   \n",
              "9  Entire home/apt    150               1                160  2019-06-09   \n",
              "\n",
              "   reviews_per_month  calculated_host_listings_count  availability_365  \n",
              "0               0.21                               6               365  \n",
              "1               0.38                               2               355  \n",
              "2                NaN                               1               365  \n",
              "3               4.64                               1               194  \n",
              "4               0.10                               1                 0  \n",
              "5               0.59                               1               129  \n",
              "6               0.40                               1                 0  \n",
              "7               3.47                               1               220  \n",
              "8               0.99                               1                 0  \n",
              "9               1.33                               4               188  "
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              "      <th>id</th>\n",
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              "      <th>0</th>\n",
              "      <td>2539</td>\n",
              "      <td>Clean &amp; quiet apt home by the park</td>\n",
              "      <td>2787</td>\n",
              "      <td>John</td>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>Kensington</td>\n",
              "      <td>40.64749</td>\n",
              "      <td>-73.97237</td>\n",
              "      <td>Private room</td>\n",
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              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>2018-10-19</td>\n",
              "      <td>0.21</td>\n",
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              "      <td>365</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2595</td>\n",
              "      <td>Skylit Midtown Castle</td>\n",
              "      <td>2845</td>\n",
              "      <td>Jennifer</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Midtown</td>\n",
              "      <td>40.75362</td>\n",
              "      <td>-73.98377</td>\n",
              "      <td>Entire home/apt</td>\n",
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              "      <td>2019-05-21</td>\n",
              "      <td>0.38</td>\n",
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              "      <td>355</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3647</td>\n",
              "      <td>THE VILLAGE OF HARLEM....NEW YORK !</td>\n",
              "      <td>4632</td>\n",
              "      <td>Elisabeth</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Harlem</td>\n",
              "      <td>40.80902</td>\n",
              "      <td>-73.94190</td>\n",
              "      <td>Private room</td>\n",
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              "      <th>3</th>\n",
              "      <td>3831</td>\n",
              "      <td>Cozy Entire Floor of Brownstone</td>\n",
              "      <td>4869</td>\n",
              "      <td>LisaRoxanne</td>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>Clinton Hill</td>\n",
              "      <td>40.68514</td>\n",
              "      <td>-73.95976</td>\n",
              "      <td>Entire home/apt</td>\n",
              "      <td>89</td>\n",
              "      <td>1</td>\n",
              "      <td>270</td>\n",
              "      <td>2019-07-05</td>\n",
              "      <td>4.64</td>\n",
              "      <td>1</td>\n",
              "      <td>194</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5022</td>\n",
              "      <td>Entire Apt: Spacious Studio/Loft by central park</td>\n",
              "      <td>7192</td>\n",
              "      <td>Laura</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>East Harlem</td>\n",
              "      <td>40.79851</td>\n",
              "      <td>-73.94399</td>\n",
              "      <td>Entire home/apt</td>\n",
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              "      <th>5</th>\n",
              "      <td>5099</td>\n",
              "      <td>Large Cozy 1 BR Apartment In Midtown East</td>\n",
              "      <td>7322</td>\n",
              "      <td>Chris</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Murray Hill</td>\n",
              "      <td>40.74767</td>\n",
              "      <td>-73.97500</td>\n",
              "      <td>Entire home/apt</td>\n",
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              "      <td>74</td>\n",
              "      <td>2019-06-22</td>\n",
              "      <td>0.59</td>\n",
              "      <td>1</td>\n",
              "      <td>129</td>\n",
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              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>5121</td>\n",
              "      <td>BlissArtsSpace!</td>\n",
              "      <td>7356</td>\n",
              "      <td>Garon</td>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>Bedford-Stuyvesant</td>\n",
              "      <td>40.68688</td>\n",
              "      <td>-73.95596</td>\n",
              "      <td>Private room</td>\n",
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              "      <th>7</th>\n",
              "      <td>5178</td>\n",
              "      <td>Large Furnished Room Near B'way</td>\n",
              "      <td>8967</td>\n",
              "      <td>Shunichi</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Hell's Kitchen</td>\n",
              "      <td>40.76489</td>\n",
              "      <td>-73.98493</td>\n",
              "      <td>Private room</td>\n",
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              "      <td>220</td>\n",
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              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>5203</td>\n",
              "      <td>Cozy Clean Guest Room - Family Apt</td>\n",
              "      <td>7490</td>\n",
              "      <td>MaryEllen</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Upper West Side</td>\n",
              "      <td>40.80178</td>\n",
              "      <td>-73.96723</td>\n",
              "      <td>Private room</td>\n",
              "      <td>79</td>\n",
              "      <td>2</td>\n",
              "      <td>118</td>\n",
              "      <td>2017-07-21</td>\n",
              "      <td>0.99</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>5238</td>\n",
              "      <td>Cute &amp; Cozy Lower East Side 1 bdrm</td>\n",
              "      <td>7549</td>\n",
              "      <td>Ben</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Chinatown</td>\n",
              "      <td>40.71344</td>\n",
              "      <td>-73.99037</td>\n",
              "      <td>Entire home/apt</td>\n",
              "      <td>150</td>\n",
              "      <td>1</td>\n",
              "      <td>160</td>\n",
              "      <td>2019-06-09</td>\n",
              "      <td>1.33</td>\n",
              "      <td>4</td>\n",
              "      <td>188</td>\n",
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          "metadata": {},
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    },
    {
      "cell_type": "code",
      "source": [
        "#last five columns raw values of dataset lots of null values at the end of data set\n",
        "bnb.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        },
        "id": "qeqjWQKViDyL",
        "outputId": "fc2c9650-b6a1-45f5-e8fb-bc6e635b8966"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             id                                               name   host_id  \\\n",
              "48890  36484665    Charming one bedroom - newly renovated rowhouse   8232441   \n",
              "48891  36485057      Affordable room in Bushwick/East Williamsburg   6570630   \n",
              "48892  36485431            Sunny Studio at Historical Neighborhood  23492952   \n",
              "48893  36485609               43rd St. Time Square-cozy single bed  30985759   \n",
              "48894  36487245  Trendy duplex in the very heart of Hell's Kitchen  68119814   \n",
              "\n",
              "           host_name neighbourhood_group       neighbourhood  latitude  \\\n",
              "48890        Sabrina            Brooklyn  Bedford-Stuyvesant  40.67853   \n",
              "48891        Marisol            Brooklyn            Bushwick  40.70184   \n",
              "48892  Ilgar & Aysel           Manhattan              Harlem  40.81475   \n",
              "48893            Taz           Manhattan      Hell's Kitchen  40.75751   \n",
              "48894     Christophe           Manhattan      Hell's Kitchen  40.76404   \n",
              "\n",
              "       longitude        room_type  price  minimum_nights  number_of_reviews  \\\n",
              "48890  -73.94995     Private room     70               2                  0   \n",
              "48891  -73.93317     Private room     40               4                  0   \n",
              "48892  -73.94867  Entire home/apt    115              10                  0   \n",
              "48893  -73.99112      Shared room     55               1                  0   \n",
              "48894  -73.98933     Private room     90               7                  0   \n",
              "\n",
              "      last_review  reviews_per_month  calculated_host_listings_count  \\\n",
              "48890         NaN                NaN                               2   \n",
              "48891         NaN                NaN                               2   \n",
              "48892         NaN                NaN                               1   \n",
              "48893         NaN                NaN                               6   \n",
              "48894         NaN                NaN                               1   \n",
              "\n",
              "       availability_365  \n",
              "48890                 9  \n",
              "48891                36  \n",
              "48892                27  \n",
              "48893                 2  \n",
              "48894                23  "
            ],
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              "\n",
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              "      <th>48890</th>\n",
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              "    <tr>\n",
              "      <th>48892</th>\n",
              "      <td>36485431</td>\n",
              "      <td>Sunny Studio at Historical Neighborhood</td>\n",
              "      <td>23492952</td>\n",
              "      <td>Ilgar &amp; Aysel</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Harlem</td>\n",
              "      <td>40.81475</td>\n",
              "      <td>-73.94867</td>\n",
              "      <td>Entire home/apt</td>\n",
              "      <td>115</td>\n",
              "      <td>10</td>\n",
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              "    <tr>\n",
              "      <th>48893</th>\n",
              "      <td>36485609</td>\n",
              "      <td>43rd St. Time Square-cozy single bed</td>\n",
              "      <td>30985759</td>\n",
              "      <td>Taz</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Hell's Kitchen</td>\n",
              "      <td>40.75751</td>\n",
              "      <td>-73.99112</td>\n",
              "      <td>Shared room</td>\n",
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              "      <td>6</td>\n",
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              "    <tr>\n",
              "      <th>48894</th>\n",
              "      <td>36487245</td>\n",
              "      <td>Trendy duplex in the very heart of Hell's Kitchen</td>\n",
              "      <td>68119814</td>\n",
              "      <td>Christophe</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Hell's Kitchen</td>\n",
              "      <td>40.76404</td>\n",
              "      <td>-73.98933</td>\n",
              "      <td>Private room</td>\n",
              "      <td>90</td>\n",
              "      <td>7</td>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#data calculation\n",
        "bnb.describe()"
      ],
      "metadata": {
        "id": "hl3R3KZMavb0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "outputId": "9eb842e5-6e55-492b-ada0-b02a64a8e091"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                 id       host_id      latitude     longitude         price  \\\n",
              "count  4.889500e+04  4.889500e+04  48895.000000  48895.000000  48895.000000   \n",
              "mean   1.901714e+07  6.762001e+07     40.728949    -73.952170    152.720687   \n",
              "std    1.098311e+07  7.861097e+07      0.054530      0.046157    240.154170   \n",
              "min    2.539000e+03  2.438000e+03     40.499790    -74.244420      0.000000   \n",
              "25%    9.471945e+06  7.822033e+06     40.690100    -73.983070     69.000000   \n",
              "50%    1.967728e+07  3.079382e+07     40.723070    -73.955680    106.000000   \n",
              "75%    2.915218e+07  1.074344e+08     40.763115    -73.936275    175.000000   \n",
              "max    3.648724e+07  2.743213e+08     40.913060    -73.712990  10000.000000   \n",
              "\n",
              "       minimum_nights  number_of_reviews  reviews_per_month  \\\n",
              "count    48895.000000       48895.000000       38843.000000   \n",
              "mean         7.029962          23.274466           1.373221   \n",
              "std         20.510550          44.550582           1.680442   \n",
              "min          1.000000           0.000000           0.010000   \n",
              "25%          1.000000           1.000000           0.190000   \n",
              "50%          3.000000           5.000000           0.720000   \n",
              "75%          5.000000          24.000000           2.020000   \n",
              "max       1250.000000         629.000000          58.500000   \n",
              "\n",
              "       calculated_host_listings_count  availability_365  \n",
              "count                    48895.000000      48895.000000  \n",
              "mean                         7.143982        112.781327  \n",
              "std                         32.952519        131.622289  \n",
              "min                          1.000000          0.000000  \n",
              "25%                          1.000000          0.000000  \n",
              "50%                          1.000000         45.000000  \n",
              "75%                          2.000000        227.000000  \n",
              "max                        327.000000        365.000000  "
            ],
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              "\n",
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              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>host_id</th>\n",
              "      <th>latitude</th>\n",
              "      <th>longitude</th>\n",
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              "      <th>availability_365</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>4.889500e+04</td>\n",
              "      <td>4.889500e+04</td>\n",
              "      <td>48895.000000</td>\n",
              "      <td>48895.000000</td>\n",
              "      <td>48895.000000</td>\n",
              "      <td>48895.000000</td>\n",
              "      <td>48895.000000</td>\n",
              "      <td>38843.000000</td>\n",
              "      <td>48895.000000</td>\n",
              "      <td>48895.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1.901714e+07</td>\n",
              "      <td>6.762001e+07</td>\n",
              "      <td>40.728949</td>\n",
              "      <td>-73.952170</td>\n",
              "      <td>152.720687</td>\n",
              "      <td>7.029962</td>\n",
              "      <td>23.274466</td>\n",
              "      <td>1.373221</td>\n",
              "      <td>7.143982</td>\n",
              "      <td>112.781327</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1.098311e+07</td>\n",
              "      <td>7.861097e+07</td>\n",
              "      <td>0.054530</td>\n",
              "      <td>0.046157</td>\n",
              "      <td>240.154170</td>\n",
              "      <td>20.510550</td>\n",
              "      <td>44.550582</td>\n",
              "      <td>1.680442</td>\n",
              "      <td>32.952519</td>\n",
              "      <td>131.622289</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>2.539000e+03</td>\n",
              "      <td>2.438000e+03</td>\n",
              "      <td>40.499790</td>\n",
              "      <td>-74.244420</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>9.471945e+06</td>\n",
              "      <td>7.822033e+06</td>\n",
              "      <td>40.690100</td>\n",
              "      <td>-73.983070</td>\n",
              "      <td>69.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.190000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>1.967728e+07</td>\n",
              "      <td>3.079382e+07</td>\n",
              "      <td>40.723070</td>\n",
              "      <td>-73.955680</td>\n",
              "      <td>106.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>0.720000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>45.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2.915218e+07</td>\n",
              "      <td>1.074344e+08</td>\n",
              "      <td>40.763115</td>\n",
              "      <td>-73.936275</td>\n",
              "      <td>175.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>2.020000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>227.000000</td>\n",
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              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>3.648724e+07</td>\n",
              "      <td>2.743213e+08</td>\n",
              "      <td>40.913060</td>\n",
              "      <td>-73.712990</td>\n",
              "      <td>10000.000000</td>\n",
              "      <td>1250.000000</td>\n",
              "      <td>629.000000</td>\n",
              "      <td>58.500000</td>\n",
              "      <td>327.000000</td>\n",
              "      <td>365.000000</td>\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\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",
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              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-44c86edb-fa6a-4523-8472-5aa2949c826c 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-44c86edb-fa6a-4523-8472-5aa2949c826c');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "bnb.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WbziAQIrZh32",
        "outputId": "55bc08aa-de60-4de5-f638-7c09badac5de"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 48895 entries, 0 to 48894\n",
            "Data columns (total 16 columns):\n",
            " #   Column                          Non-Null Count  Dtype  \n",
            "---  ------                          --------------  -----  \n",
            " 0   id                              48895 non-null  int64  \n",
            " 1   name                            48879 non-null  object \n",
            " 2   host_id                         48895 non-null  int64  \n",
            " 3   host_name                       48874 non-null  object \n",
            " 4   neighbourhood_group             48895 non-null  object \n",
            " 5   neighbourhood                   48895 non-null  object \n",
            " 6   latitude                        48895 non-null  float64\n",
            " 7   longitude                       48895 non-null  float64\n",
            " 8   room_type                       48895 non-null  object \n",
            " 9   price                           48895 non-null  int64  \n",
            " 10  minimum_nights                  48895 non-null  int64  \n",
            " 11  number_of_reviews               48895 non-null  int64  \n",
            " 12  last_review                     38843 non-null  object \n",
            " 13  reviews_per_month               38843 non-null  float64\n",
            " 14  calculated_host_listings_count  48895 non-null  int64  \n",
            " 15  availability_365                48895 non-null  int64  \n",
            "dtypes: float64(3), int64(7), object(6)\n",
            "memory usage: 6.0+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***Lots of null values in this data***"
      ],
      "metadata": {
        "id": "QOeKHdYMgmkf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#null values in airbnb dataset\n",
        "bnb.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Dy9HfYJ8ozak",
        "outputId": "d91381f0-b1f9-4251-90a2-5d86a9dc14ec"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id                                    0\n",
              "name                                 16\n",
              "host_id                               0\n",
              "host_name                            21\n",
              "neighbourhood_group                   0\n",
              "neighbourhood                         0\n",
              "latitude                              0\n",
              "longitude                             0\n",
              "room_type                             0\n",
              "price                                 0\n",
              "minimum_nights                        0\n",
              "number_of_reviews                     0\n",
              "last_review                       10052\n",
              "reviews_per_month                 10052\n",
              "calculated_host_listings_count        0\n",
              "availability_365                      0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***We have 4 columns contain a missing value. Now, we drop unnecessary columns such as id, name,last_review.***"
      ],
      "metadata": {
        "id": "KWPb3JirmYZ4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#drop irrelevant columns\n",
        "bnb.drop([\"id\",\"name\",\"last_review\"], axis=1, inplace=True)"
      ],
      "metadata": {
        "id": "t2rBlKd4WHIr"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#what we have in data in the form of columns \n",
        "bnb.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3BYiXFJ6A8hI",
        "outputId": "7e8dbbb3-ed43-4823-9771-933a3398d82f"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['host_id', 'host_name', 'neighbourhood_group', 'neighbourhood',\n",
              "       'latitude', 'longitude', 'room_type', 'price', 'minimum_nights',\n",
              "       'number_of_reviews', 'reviews_per_month',\n",
              "       'calculated_host_listings_count', 'availability_365'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***Replacing all NaN values in “review_per_month_ with 0***"
      ],
      "metadata": {
        "id": "4GnP5SXHnAh4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#replace the null values in reviews per month with zero\n",
        "bnb.reviews_per_month.fillna(0, inplace=True)"
      ],
      "metadata": {
        "id": "VMdbjohhVpRJ"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#after cleaning \n",
        "bnb.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WIYiK1q-WG9z",
        "outputId": "d0576e29-43ce-484c-dc1b-67f4b2106063"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "host_id                            0\n",
              "host_name                         21\n",
              "neighbourhood_group                0\n",
              "neighbourhood                      0\n",
              "latitude                           0\n",
              "longitude                          0\n",
              "room_type                          0\n",
              "price                              0\n",
              "minimum_nights                     0\n",
              "number_of_reviews                  0\n",
              "reviews_per_month                  0\n",
              "calculated_host_listings_count     0\n",
              "availability_365                   0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Exploration Data and Visualizing--**\n",
        "\n",
        "***Now time to explore our data and visualize it to recognize the relationship between the dataset***."
      ],
      "metadata": {
        "id": "P5IxeLrInYhk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#last five rows \n",
        "bnb.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "id": "XWuGmGRGWGzQ",
        "outputId": "64cc9da3-187a-4948-cb4b-620d1e80dd93"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        host_id      host_name neighbourhood_group       neighbourhood  \\\n",
              "48890   8232441        Sabrina            Brooklyn  Bedford-Stuyvesant   \n",
              "48891   6570630        Marisol            Brooklyn            Bushwick   \n",
              "48892  23492952  Ilgar & Aysel           Manhattan              Harlem   \n",
              "48893  30985759            Taz           Manhattan      Hell's Kitchen   \n",
              "48894  68119814     Christophe           Manhattan      Hell's Kitchen   \n",
              "\n",
              "       latitude  longitude        room_type  price  minimum_nights  \\\n",
              "48890  40.67853  -73.94995     Private room     70               2   \n",
              "48891  40.70184  -73.93317     Private room     40               4   \n",
              "48892  40.81475  -73.94867  Entire home/apt    115              10   \n",
              "48893  40.75751  -73.99112      Shared room     55               1   \n",
              "48894  40.76404  -73.98933     Private room     90               7   \n",
              "\n",
              "       number_of_reviews  reviews_per_month  calculated_host_listings_count  \\\n",
              "48890                  0                0.0                               2   \n",
              "48891                  0                0.0                               2   \n",
              "48892                  0                0.0                               1   \n",
              "48893                  0                0.0                               6   \n",
              "48894                  0                0.0                               1   \n",
              "\n",
              "       availability_365  \n",
              "48890                 9  \n",
              "48891                36  \n",
              "48892                27  \n",
              "48893                 2  \n",
              "48894                23  "
            ],
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              "\n",
              "  <div id=\"df-6b23af90-03a0-4be9-9300-5714409d2e86\">\n",
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              "      <th>host_id</th>\n",
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              "      <th>neighbourhood</th>\n",
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              "      <th>48890</th>\n",
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              "      <td>Sabrina</td>\n",
              "      <td>Brooklyn</td>\n",
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              "      <td>-73.94995</td>\n",
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              "      <th>48891</th>\n",
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              "      <td>-73.93317</td>\n",
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              "      <th>48892</th>\n",
              "      <td>23492952</td>\n",
              "      <td>Ilgar &amp; Aysel</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Harlem</td>\n",
              "      <td>40.81475</td>\n",
              "      <td>-73.94867</td>\n",
              "      <td>Entire home/apt</td>\n",
              "      <td>115</td>\n",
              "      <td>10</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48893</th>\n",
              "      <td>30985759</td>\n",
              "      <td>Taz</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Hell's Kitchen</td>\n",
              "      <td>40.75751</td>\n",
              "      <td>-73.99112</td>\n",
              "      <td>Shared room</td>\n",
              "      <td>55</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48894</th>\n",
              "      <td>68119814</td>\n",
              "      <td>Christophe</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Hell's Kitchen</td>\n",
              "      <td>40.76404</td>\n",
              "      <td>-73.98933</td>\n",
              "      <td>Private room</td>\n",
              "      <td>90</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
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              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-6b23af90-03a0-4be9-9300-5714409d2e86 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-6b23af90-03a0-4be9-9300-5714409d2e86');\n",
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              "            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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            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#type of rooms in this data\n",
        "number_of_room_type = bnb['room_type'].unique()\n",
        "number_of_room_type"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SFzMqvIPDel_",
        "outputId": "c0d683b1-c40e-44a0-f688-6e3e426fe913"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Private room', 'Entire home/apt', 'Shared room'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#number of locations\n",
        "number_of_place=bnb[\"neighbourhood_group\"].unique()\n",
        "number_of_place"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mH7HcL2bEOvO",
        "outputId": "1e4fcaae-513f-41c7-c9d7-fb651b544e58"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Brooklyn', 'Manhattan', 'Queens', 'Staten Island', 'Bronx'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#total rooms by locations\n",
        "total_room_by_location= bnb.groupby(['neighbourhood_group', 'room_type']).size().reset_index(name=\"total_room\")\n",
        "print (total_room_by_location)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dUwHvEVnsEuG",
        "outputId": "92f2455e-1c16-495e-ba39-7c43e8d3ee49"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   neighbourhood_group        room_type  total_room\n",
            "0                Bronx  Entire home/apt         379\n",
            "1                Bronx     Private room         652\n",
            "2                Bronx      Shared room          60\n",
            "3             Brooklyn  Entire home/apt        9559\n",
            "4             Brooklyn     Private room       10132\n",
            "5             Brooklyn      Shared room         413\n",
            "6            Manhattan  Entire home/apt       13199\n",
            "7            Manhattan     Private room        7982\n",
            "8            Manhattan      Shared room         480\n",
            "9               Queens  Entire home/apt        2096\n",
            "10              Queens     Private room        3372\n",
            "11              Queens      Shared room         198\n",
            "12       Staten Island  Entire home/apt         176\n",
            "13       Staten Island     Private room         188\n",
            "14       Staten Island      Shared room           9\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#total hotels chart\n",
        "plt.figure(figsize=(10,6))\n",
        "plt.title(\"total hotels on location\",fontsize = 16)\n",
        "sns.countplot(data=bnb,x='neighbourhood_group')\n",
        "plt.xlabel(\"neighbourhood_group\",fontsize = 16)\n",
        "plt.ylabel(\"count\",fontsize = 16)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 412
        },
        "id": "oe1ShYxoc4Vo",
        "outputId": "a16825af-277a-4dbf-babf-b01f1cb37fa1"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#hotel share per location\n",
        "plt.figure(figsize=(10,6))\n",
        "plt.title(\"Neighbourhood Group\",fontsize = 16)\n",
        "plt.pie(bnb.neighbourhood_group.value_counts(), labels=bnb.neighbourhood_group.value_counts().index,autopct='%1.1f%%')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 375
        },
        "id": "orE1DqByWGoy",
        "outputId": "93300fc0-b335-49a5-86f2-82b96ec0ec94"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***The pie and bar chart above shows that Airbnb Listings in  Manhattan, and Brooklyn has the highest share of hotels.***"
      ],
      "metadata": {
        "id": "8vFmZ3EGnyKc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#types of room\n",
        "plt.figure(figsize=(10,6))\n",
        "plt.title(\"Type of Room\",fontsize = 16)\n",
        "sns.countplot(data=bnb,x='room_type')\n",
        "plt.xlabel(\"room_type\",fontsize=16)\n",
        "plt.ylabel(\"count\",fontsize=16)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 412
        },
        "id": "LosVIiBEWGcI",
        "outputId": "b2a1d738-6fcc-47f2-bc26-84504ff0d1d7"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***We can see that the Entire Home/Apartment has the highest share, followed by the Private Room, and the least preferred is Shared Room.***"
      ],
      "metadata": {
        "id": "8ihooP6xoTjs"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#location and room type total\n",
        "bronx_total=total_room_by_location[:3]\n",
        "brooklyn_total=total_room_by_location[3:6]\n",
        "manhattan_total=total_room_by_location[6:9]\n",
        "queens_total=total_room_by_location[9:12]\n",
        "staten_island=total_room_by_location[12:15]\n",
        "bronx_total"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "Mm61F563xpwX",
        "outputId": "1444f91c-1bdc-4969-c98e-819161aa316c"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  neighbourhood_group        room_type  total_room\n",
              "0               Bronx  Entire home/apt         379\n",
              "1               Bronx     Private room         652\n",
              "2               Bronx      Shared room          60"
            ],
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              "      <td>Bronx</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Bronx</td>\n",
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              "    [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-da886754-1308-4a45-8483-45892281dcb3 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-da886754-1308-4a45-8483-45892281dcb3');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#rooms type per location\n",
        "plt.figure(figsize=(10,6))\n",
        "plt.title(\"Room Type on Neighbourhood Group\",fontsize=16)\n",
        "sns.countplot(data=bnb,x='neighbourhood_group',hue=bnb.room_type)\n",
        "plt.xlabel(\"neighbourhood_group\",fontsize=16)\n",
        "plt.ylabel(\"count\",fontsize=16)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 412
        },
        "id": "QZBI8hUeVpEd",
        "outputId": "941f29df-74ac-4b52-be4f-7b7f60c579fb"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***The graph shows that the Entire Home/Apartment is listed most near Manhattan, while Private Rooms and Apartments Near Brooklyn are Nearly equal.***"
      ],
      "metadata": {
        "id": "Y2oNhMlmojiJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#location vise total availability\n",
        "average_availability= bnb.groupby(['neighbourhood_group'])['availability_365'].sum().reset_index()\n",
        "average_availability"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "MMY853zcmhCs",
        "outputId": "3f7ec1fc-73d7-40ba-956b-4b6dfcbf7ace"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  neighbourhood_group  availability_365\n",
              "0               Bronx            180843\n",
              "1            Brooklyn           2015070\n",
              "2           Manhattan           2425586\n",
              "3              Queens            818464\n",
              "4       Staten Island             74480"
            ],
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              "\n",
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              "      <td>Bronx</td>\n",
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              "    <tr>\n",
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              "      <td>Brooklyn</td>\n",
              "      <td>2015070</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Manhattan</td>\n",
              "      <td>2425586</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Queens</td>\n",
              "      <td>818464</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
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              "\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",
              "    [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-91c681b3-408c-4650-8b90-73fcccad0443 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-91c681b3-408c-4650-8b90-73fcccad0443');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#availability per year\n",
        "plt.figure(figsize=(10,6))\n",
        "plt.title(\"Neighbourhood Group vs. Availability Room\",fontsize=16)\n",
        "sns.boxplot(data=bnb, x='neighbourhood_group',y='availability_365')\n",
        "plt.xlabel('neighbourhood_group',fontsize=16)\n",
        "plt.ylabel(\"availability_365\",fontsize=16)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 412
        },
        "id": "oq_603GnVo0P",
        "outputId": "c4668f62-e5ba-4821-c843-60b273bb1ec2"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***The above box plot shows the relationship between the availability room and neighborhood group.***"
      ],
      "metadata": {
        "id": "ceHlym4So0iz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#locations\n",
        "plt.figure(figsize=(10,6))\n",
        "sns.scatterplot(x=bnb.longitude,y=bnb.latitude,hue=bnb.neighbourhood_group)\n",
        "plt.xlabel(\"longitude\",fontsize=16)\n",
        "plt.ylabel(\"latitude\",fontsize=16)\n",
        "plt.title(\"location of neighbourhood_group \",fontsize=16)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 411
        },
        "id": "VWJoIVz-qsLg",
        "outputId": "30c57e69-2eb8-4a2e-d3ad-305ad1b80c7e"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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5uUycOJHPP/88eB29LXoLFy5k7dq1gGqdHGyuJBLJ2YOjy03dwQ5qS9rotroGraMoCi21Nkq+bKCqsJUN/z3Af3+9jfqDHadZWonk3EYqbgEOHDjAd7/7Xfbt20dkZCRvvvkm3/72t/nLX/7Cjh07eOaZZ7j//vsHtLvrrrt4/vnnKSgoQKvV9jlXUFDA8uXLKSwsZPny5dTU1ADQ3d1Nfn4++/btY86cOfz85z8H4Pbbb+e3v/0te/bsITc3N1h+JHbu3MmKFStYt27dkGPW1dXx6KOPsmbNGgoKCti2bRvvvPPOkOX19fX87Gc/Y+PGjWzYsIH9+/cfUYaHHnqIhx56iMLCQlJTUwfI96c//YnS0lL+9re/IYSgsLCQZcuWcccddxw1GnSouZJIJGcHnS0OPv7XPt5+ZifvPlfAO3/YRVt994B61ftaefO3O1j3n1K2raogY1wMYVEm1r1egrPbcwYkl0jOTaTiFiArK4u8vDwAJk+eTGVlJZs2beKGG24gLy+P73znO9TX1/dp09HRgc1mY8aMGQB84xvf6HN+3rx5REREYDKZyMnJoapKzR2r0Wi46aabALjtttvYsGEDVquVjo4O5syZA8Add9zBF198cVS5L7nkEqKjo4845rZt25g7dy5xcXHodDpuvfVWvvjiiyHLv/zyy2C5wWAIyjoUmzdv5oYbbhh0DqZOnRrcX23Dhg3cdtttAIwePZqMjAxKS0uP2PdgcyWRSM4eaoraOFTSHjzuaLRTtKkORVGCZbZWJ5+9VITX4wdAUWDXp9UMmxhHa203Lqm4SSTHjFx0FMBoNAbfa7VaGhsbiYyMpKCg4JT1OdQ6tKNtZ6HT6fD71Q+8/hYqi8VyQmOeLvrLNxi9rw8GXmNv5NYfEsnZRWNF54Cyrg4XjZWddLW76G53EhZjGmhVU8DnVYjLCMMUKrOeSCTHirS4DUF4eDhZWVm88cYbgLo+Y/fu3X3qREZGEhYWxpdffgnA66+/fkx9+/1+VqxYAcB//vMfZs2aRUREBFFRUaxfvx6AV199NWh9y8zMZMeOHQDBdsfD1KlTWbduHS0tLfh8PpYtW8acOXOGLJ82bRrr1q2jtbUVj8cTnIOhmD59Om+++eZR52D27NksXboUgNLSUqqrq8nOziYzM5OCggL8fj81NTVs3br1iHMlkUjOHlJGRfY5HpYXhylEz1u/28HH/9xL6dZGfF6F6BQLUUkhCI3640sIMJi1zLx2OMYQqbhJJMeKtLgdgaVLl3Lffffx1FNP4fF4uPnmm5kwYUKfOi+++CL33HMPGo2GOXPmEBERcdR+LRYLW7du5amnniI+Pp7ly5cD8PLLL3Pvvfdit9sZNmwYL730EgAPP/wwN954I//85z+58sorj/s6kpKS+M1vfsNFF12EoihceeWVXH311QBDlj/55JPMmDGDyMjIoAt5KP74xz9y22238fTTT3PZZZcNOQf3338/9913H7m5ueh0OpYsWYLRaOSCCy4gKyuLnJwcxowZw6RJk446VxKJ5OwgJTuK0TMSKd7cAAKSR0aw4Y2DwfNtdd34vX6yxsfS0Whn1NREGsqtpI+NITEzlJjU8NMmq9ftQ2gEWt2J2Sy62p201nWj+BSiky0yIlZyRhC91yF83cjPz1d6ojF7KCoqYsyYMadsjK6urmAU5W9+8xvq6+v505/+dMr6Pxew2+2YzWaEELz++ussW7aMd99995T0HRoaSldX11Hrner7KpFIjh2P24e1yY6iQEVBM9tWVRIaZSR7ehIxKRbWLy/FYTvsKp1140jGz00NWt++alwOD9X72ti9ugZDiI5Jl6STNDISrbavAtdcY6NsRxOdLQ6GT44nJTsSU4gBRVGwtTr54G+7aa23AxASYWDeHWNw2b3EpIQSnXT0ZSESydEQQuxQFCX/SHWkxe0kWbVqFb/+9a/xer1kZGSwZMmSMy3SaWfHjh088MADKIpCZGQk//73v8+0SBKJ5DSiN2iJTQ0DwNpkJyTCwLg5qWxbVcGkBRl9lDaA7asqGTEpHkukcbDuTjnVe9v45MV9wePa/W1c8/8mkTzisJu3ta6Ld57didvpA+DA9ibm3pZNaKSJfRvr8Ll9ZM9IonRbIy01Xditbkq2NNBUZaPb6uLq708kIfP0WQ8l5y9nRHETQmiB7cAhRVEWCiGygNeBGGAH8D+Korj7tTEAzwP5gB94SFGUtadV8EG46aabjhp1+XXh6aefHrDe7YYbbuDxxx8fsP7vVHEs1jaJRHLmsHe6aK7uwmFzExFvJj4zjPzLM9n8dhk+j18NIe2Hz+fnq/T2+H1+FECr1eBxetn1WXWf84oC1Xtb+yhuzVWdQaUtKKfHz8q/7YaAqNX72ph53Qhaaw+iKGoEbXiMiY5GO7vXVDP/jhw0Wrl0XPLVcqYsbg8BRUDPz5PfAs8pivK6EOIfwDeB/+vX5h4ARVFyhRDxwIdCiCmKoviRnBYef/xxHn/88TMthkQiOUtw2NysW1ZK+a7DG2PPu2MMUUkWPC5VCRJCoDdqg8cAefPTvhJrm9fjo/6glZIv60keGUXN/jZCY0zoDNoBdfXGvmV+BTQagd+vamlRiSHUl1mDSlsPNUVtxGeG01jRSdKISEq+bACg7ZAdn1dBM3AoieSUctp/GgghUoErgRcCxwK4GOgJl3wZuGaQpjnAGgBFUZqADlTrm0QikUjOAK2HuvoobQDr/3sAk0WHwazaBXavqWHa1cMYkR9PQlY4ky/PIDEr4pRt7dNW10XFnmYaKqy0N3TT1e4ka0I865aWcHBHE3s+q2HY+FjoNZzOoCFtrLr/pdfjo7nWht/rZ+rVWcy+cSQhEQZCIgyDKnwajUBRFIZPikPxKzi7VDfwmAuSBiiDEslXwZmwuP0ReAQICxzHAB2KovRsOFYLpAzSbjewSAixDEgDJgf+bh2krkQikUi+YlyOgftEuh1etDoNl3wzh4JPqxkzMxlrswOtTsPI/Hg8Hh9Ce2qUtqrCFj59aT8uuxeNRjB1URbtDd3oDLqg5czvVyjaXM+FN4+iudqG3qAlfVw09Qc68Dh9dLY48PsUQqPNWPx+FAXm3T4ae6cHvVFLyZYGlEBfCBg3NwWtVkNzTRduh4dJCzJQUBU5ieR0cFoVNyHEQqBJUZQdQoi5x9n838AY1LVxVcAmwNe/khDi28C3AdLT009KXolEIpEMTWRCCFqdBp/38IqV5JGRWCKM+Lx+kkdGUrq1gep9bQCUbFFdkCMmJ5z02NZmO58vLcFlV5VHv19hyzvlLLhnHHUH2vvUbavrpmRLA5EJIRzc0URaTjSHSjvYsOIgF940Cq/Hx+Z/78Nl9xIRZ2b2TSPp6nCh0QouuTuH2uI2UGDYxHg6mu1sWH4g2Hd0UghXPjCB0EjTSV+TRHIsnG5X6QWoVrNK1GCEi4E/AZFCiB4lMhU41L+hoiheRVF+oChKnqIoVwORwIB8SYqi/FNRlHxFUfLj4s7NX0BarZa8vDwmTJjApEmT2LRp0ynpt38y9x6efPJJnnnmmVMyhkQiOX+ITrKw8IHxRCWGgICsCbHM+UY2Wr1gz5paUAgqbT20N9hpHySX6fHS1e6iu2NgQnuHzU1otGnAXm3DJsZxYHsjoTEmKnY3U7G7hYg4MzqDhs1vlwcVQJ/XT1OVjajEEBS/ur3J8InxjJqWiMGsYet75X36bau303ro5K9HIjlWTqvFTVGUx4DHAAIWt4cVRblVCPEGcD2qMncHMGATMCFECOq+c91CiEsAr6IoR85+fo5iNpuDqbY+/vhjHnvssWAS+R68Xi86ndzNRSKRnDmEEKSOjubahyfhcfowhxvQG7R0NNop29XMhItTB23nHsTFeryYIwxYIo0DlDejRc/2DyqZdvUwOprsuLo9JGSGc2B7E36vQt68NNYtKwFUi2G31R10haaOjiI+I5xdn1bjdfsZkR/P8MnxNFZ2YgzR4XX7yL8ik01vlmEM0ZEyKgq3w4vL7sHe6aa5uhN7p5uI+BBCo410t7sAQVRiCCaLzA4hOTWcLXHLjwL/K4Q4iLrm7UUAIcQiIcQvAnXigZ1CiKJA/f85I5L2451dh7jgN2vI+tEqLvjNGt7ZNcBYeFJ0dnYSFRUFwNq1a5k9ezaLFi0iJycHp9PJXXfdRW5uLhMnTuTzzz8HGLK8N6tWrWLGjBm0tLQEy8rKyvpkLThw4EDwODMzk5/97GdMmjSJ3NxciouLT+l1SiSScxdzqIHwWDN6gxaHzY3OqCEi1kTdQStZE2L71I1OtmC3uofo6diJTrBw4S2jMIaoP2A1WsG0RVnUl3Vg73RTsqWe0TOSmLJoGKZQPaOmJrDg2+NAKEQmhADQWtuFJcIQ7DM1O4qdH1fhcfpQ/ArWRjudLU52flTF+uUHKN7cQFSShcmXZzBuTgodTXZ8PgWDSUfJljpW/nUPa14p5u1ndnLgy0YqC1uwtTmo2teKtdl+0tcskcAZ3IA3sAfb2sD7cmDqIHXeA94LvK8Esk+bgMfAO7sO8dhbhTg86lK7Qx0OHnurEIBrJg4WX3FsOBwO8vLycDqd1NfXs2bNmuC5nTt3snfvXrKysnj22WcRQlBYWEhxcTGXXnoppaWl/O1vfxu0vIe3336bP/zhD3zwwQdBpRBg+PDhREREUFBQQF5eHi+99BJ33XVX8HxsbCw7d+7k73//O8888wwvvPDCCV+jRCI59+lotlNX2kFHk53ErHCcXV62f1BJ5oRoci9KY+1/ihkzI4lJCzJorrERnxGG4geP59Ts4pSVG8uih/LobHFgDjMQEWvE2uIiY2wMoVFGYpJDERqBTiOwtTvR6jRotIJJl2bwyYv76Gp34XH5GXthChUFzVhbHH36Hz0ziS+WHf7sbG+ws31VJbOuH8Gbv98ZLG8otzLnllF92hasrmHOLaPY+XE1zdU24jPDmXPLKOIz5Ca9kpND+tpOgt9/XBJU2npweHz8/uOSk1LcertKN2/ezO23387evXsBNWF8VlYWABs2bODBBx8EYPTo0WRkZFBaWjpkOcCaNWvYvn07n3zyCeHhAz9AvvWtb/HSSy/xhz/8geXLl/dJ+L548WIAJk+ezFtvvXXC1yeRSM5+XA4PzdU2rM1OQiONxGWEEhKm7r1m73TTVt/N+tdLaKu3IwTkXpRK0vAIZiwejs/nx+vyMePa4Wh1GrxuHykjIylYXYPeoGHhA0fOf3ysCI0gPiO8jzIUGh3Sp053h5O2hm5cdi/mMAP7Nx4iOjGUKVdm4XX7VFdqVhipoyLpsvZ1u/YOuuihsaITZ3ffTBCKX6G9wd5nv7rR0xNZv/wA9k7VuthU2cmqv+/hhkfzCY2WgQySE+dscZWek9R1OI6r/ETocWc2N6t7JVksJ5cPb/jw4dhstj4WuN5cd911fPjhh6xcuZLJkycTExMTPGc0qh/aWq0Wr/fk16hIJJKzE5/XT+HaQ7z3p934PT7sNjeVe1ppqurE7fTy5fvl1B/ooC2Qt3PWTaOoLW7n43/t45MX9lG8sR6tXsPGNw7y5bvl6AxawgPRmtf8v0lEJ5+evJ5NVZ2sfqWID/5eyOolRXyxrIT49HD2fnGIqEQzJosONNBS04XOqMXj9AXdqACmkIHr0iLizYNaDLU6TXALksiEEOIzw4NKWw92qxtr66n7fpCcn0iL20mQHGnm0CBKWnKk+ZSNUVxcjM/n66NA9TB79myWLl3KxRdfTGlpKdXV1WRnZw9ZvnPnTjIyMvj973/P4sWLeeONNxg7dmyfPk0mEwsWLOC+++7jxRdfPGXXIZFIzh2sTXa2vV/BRf8zmtIvGzCHGYhNtdDZ6qCzxUFsqoXQaBNTFmahN2rpbHHQVteN0AgyxsUQEWdGb9Sy4Dvj6Gp1cmBbE5EJIYyekUh4zKn7fDwSbXXdNJRZqdl/eGuQzhYnHY125t+Vw+evFtHd4UajEeQvzKS9oRufVyHvkjR8Hj9CCMJiTGRPT6Rki5odQW/UMvGSdMyhhj5jGUN0JGSFE51kYfTMRMwWPVqdUDf97ZV5QQgwmuXXruTkkE/QSfDDBdl91rgBmPVafrjg5Jbi9axxA1AUhQdiQ+4AACAASURBVJdffhmtduCO3Pfffz/33Xcfubm56HQ6lixZgtFoHLK8h9GjR7N06VJuuOEG3n///QH93nrrrbz99ttceumlJ3UdEonk3MTj8mEwq1GU8Rnh1B1sJyErnPXLD5A3P53GCiu2NicZ42Lw+/w0llsZMTmetJxo9q0/hN/nR6sXeF1+9nxeC0D9wQ7KdjYx55ZRmMMNWMINRCVZ6La6cXZ7sIQbMIcZjiLZsdPe1EV748CAgIbyTgwmHd0dqjXM71fY+l4Fs64fwY4PKwmNMjJhfho7P6pk6lVZRCaYmX9XDnabm5AwA26Hh5jkEBY9lEd5QTNanQZjiI41rxZxyTdzaKqwseXtcqISQxg7K5l96+uCY4+/OK2PRU8iORHEV5no90yTn5+vbN++vU9ZUVERY8aMOWVjvLPrEL//uIS6DgfJkWZ+uCD7pNa3nQ0888wzWK1WfvnLX55pUY6ZU31fJZLzGYfNzdplJcSnh2G3unHZvTRUWBmZn8Cez2v7bOeROzeF2PRQ3HYfW1dW4HH6mHpVFm6Hl33r6/rkKAWYcmUm+zbUMevGEfi9sOmtg9itbqISQ5h3Zw4Jmep6NY/LS92BDvZvqsdk0TNmRhIJWeFHTJXl9fhor++m2+rC7fThsnv7BBcAjL0whdriNqxNfb0lky/PpHhzHVFJFrpanQyfnEB0Ugif/ns/Or2GiHgzXe0uhEZw/Y8mB1NddXe4KS9oJm1MNAaTlg/+rxCdQUNqdhQRCSGERZnwefz4FYW49FAyxvaNspVIeiOE2KEoyhHTeUqL20lyzcSUc15R6821115LWVlZn0hWiURyfuByeLB3uNGbtYy/KBWPy0fV3mqSR0Zi/bIBIQbuwbZ/Qz3jL05Fq9PgcapKms+roCgMmnDdFKrHbnUjFMHnrxYFAwDaG+x8/K+9XP/oZELCjdTsb+PD5/cG2xVvrmfxw5ODil1/FL/Cwe1NrH6liOhECzFpoSRkhDH3tmxsrS50eg3NNTYSMsM4VNI+oH1kvJmsCXE0V9lIyY4ieXg4CMGUKzNBCLwuH7vX1DD/zhxWLymi/qAVUCNPp18zHHOonv0b60gdHUXyyEgOlbbTVteNJcKIRi9oq+kmaYSMKJWcPFJxk/Th7bffPtMiSCSSM0DroS7W/aeE+jIrIREGJl2aTkiUkeSREbQ3dBOfEaYu0uqHRidQ/AqaQP5RjVYQk2rB2uhg0oJMFEVh/4Y6OlucmEL1mMNVd6jT7hkQtWlrdWJrc6E36tjxUVWfc36vQk1RWx/FTVEUmqtsdLY6cNq9eN0+Zi4eTtW+NiLizLTWdVO0sV6tLGDm4hFs+6CSCRensW1lhZotQcD4i1KpL+tg/wa1bmNlJ3HpYexbfwhbmwtnl4fQKCOX3J1DY2VnUGkDKN5UT9qYKKKTLJgterLGx+L1+olKtKgBC14/0ckWSr9sZMN/D3LNDyZiHCToQSI5VqTiJpFIJOc5LruHNa8V0VRhA9Tox41vljHlykwskUYayjqYdFkmbfVdA7IVjJuTwsFtTcRnhpE6JoqEjHA2rThIV7taR2gEc7+RTUdTN8YQA9ZGO5ZIA3rjwK8fvVGL0aKWx6RaMIcbqAskgwdQfKqip/gVutqddLY6Kd/djM+jEBJuAEXB2uwgc2wMlmgj21dVHu5cgW0rK7jo9tHU7G9j1o0j0eo0mCx6PC4fH/6jMFg1Z3YSWp2G6ORQ0nNiiEsPY9NbZbQ32INbovSm/qCV0CgjOpMWjUPDljcO0LMKSW/UMvvmUbjsHlwOLx63H6Nc5iY5CaTiJpFIJOc5XR2uoNLWg+JX8HkVvlhWSs6sJHRGQUiojjm3jKSpqgtrk530sdEYQ/Ts+rgaW5uT0TMSMYXqg0pbTz/71h8iJiWU/RvrmX3TKCbMS8PW5iRnVjL7NwQW7wuYc8sowqJNNJZb6ba6sUQYmfuNbBqrOtm79hBRSRbsnS4O7GjCFKKjsrCVrPGxFG2qZ98XataauPQwYlJDcdgGZmfwuHy01nbj7PZgDtfTXNWF0+bGHGEkLMbEmJlJCI3AYNKy+uWiYDtzmJ65t47m4I5GvG4fY2YmUbSpPng+JjUUgIaDHTRW2ui9dNzj8tFW14VOr2XE5Hgs4acuAENyfiL3cZNIJJLzHKNJhyl0oPtOq1Pdn52tTpJ0RYxp+y1ZmxczJXoll0z4kuySb6O4upi5eDjZ0xMJCTcMCEYAdcPe2FQL068ezraVFWz/oAqf14/f5+fSb+Zw8e2jufGxfEZMTqClxsa6/5QwZkYStlYn65cfwNHp5vJ7c9m38RCth7owW/RU7WvF4/bRbXXTXH1Y6WyuttHZ4iAi1jwg0Xx4rAmHzU1FQQtep4/uDhc+v4LBpGXSgnS2r6rEbnWx/YPKPu0cNg8djXbScmKo3NPaJzI0JTuS8BgT5jADna2OQfOwet1+hk+OY+yFKQjN0MEVEsmxIC1uEolEcp4TGm1izjey+eRfe4PWoqy8WDqa7Gh1gssWgeGNO8DeCoCmoRByrgavk5jWVWzePAmfT7UuTbwkfUD/2dMSqS/v5OD2JgAmXpqO26G6Dle/XMzsm0YSl66uXbM2O5h0WQZlO5tJHhlJQlYEQkDh5zXkzU/H2uxAb9KRNT4Wk0VPQ3kno6YmEhplpHhLPe31dpoqbUy4KJWZ1w1nx4dV2DvdRCaEMG5OCpvfLgNUZXLYxFgayjqpKWrjwLZG/H4FvVGLb5ANdn0+P3arC0VR3Z9TrsxECEFrXRcOm5uUUVHEZUQQkxxGU1Vf62X62Ggyxsag0UpbieTkkYrbWYgQgltvvZXXXnsNAK/XS1JSEtOmTWPlypUn1GdoaChdXV3HXH/t2rUYDAZmzpwJwDvvvMOoUaPIyck5ofElEslZgNcNHjuYIwecyhofy/WPTsRa34k5VEu0oRZD+SrmPngxurbdQaUtSNH7MPt/idjwU6668lXq/BNwdPmIzwzn4ttHs+OjKlzdXkbPTCQtJxr7lnqiEkMYOSUBt8vLnjWqa1NoBBHx6qa8jdVqOimdTovP52fr+xUA6PQaLrp9NE6bB5fdS11pB0kjI9n05kG62gMuUQEXLB7B5nfLSB8bjSLAafdy4S0jsbW5aK7uYvNbZfi8fjQagc6goavVxdb3K5h8eWZwX7cD25sYNzeVnb2CI3QGDeExZra8U0ZIhIHOFgcFn9UEz2eMjWHDGwcYNyeF1kNdTL9mGKVbG9Eb1ehcU6hOKm2SU4ZU3M5CLBYLe/fuxeFwYDab+fTTT0lJOb1bjqxdu5bQ0NA+itvChQul4iaRnKvU7YL1z0FjIYy/GSbcAlGHrWNaxUW8YyPxMXpor4QOOyRmw75lEJ01sD+NDvx+8PsIb/qM2shx6PRaPnp+Lz6Pn6wJsapCJuC9PxUwZWEW4+ep24Y0V9u44cf5eN0+2uq7EQgaq6zs/LAaj9vLyPwEKgpaAIjPCCM81szeLw4RFm0mJExPZEIIDWVWRs9IxtbqpOTLBlCgZGsDuRemMHp6Ei67h5BwA01VNuLSwqjc3YLP6ycsxsT4uamYQg1qO8Bo0ZEwLJzG8k5srU4URWHGtcM5uKOJ0CgjI/LjsbU6SMmOImlEBOtfPxCchpAIA6YwPQe2NRIaZWLYxFisTXZmXJuFrd2No9tNZq7cu01y6pA/AU6WPf+F58bBk5Hq3z3/PSXdXnHFFaxatQqAZcuWccsttwTPbd26lRkzZjBx4kRmzpxJSUkJAEuWLGHx4sVcdtlljBw5kkceeaRPn48//jgTJkxg+vTpNDY2AvD+++8zbdo0Jk6cyPz582lsbKSyspJ//OMfPPfcc+Tl5bFu3Tree+89fvjDH5KXl0dZWRn/+te/mDJlChMmTOC6667Dbld3KL/zzjv53ve+x8yZMxk2bBgrVqw4JfMhkUhOgpaD8PIiKHoX2sph7a9g3W+guwUqN8K+d6BuN4QlQ+nH8PnTsPcN8Dgg93owRUHMiL59TrwNSlZBeDJNIx7E0aVwqLQdZ5cHj8tH6dZGtq2sxO9R0GgEX75bTne7G4/Lh9et8PmrxWx84yAarYbqfS00lnficXlJGBaBw+ZBZ9BwwXUjsEQaaa6xEZVgYdSUeGpL2tm2qpLSrY1s/6ASv08hIUt1s7rs3mB2gvBYM3vX1ZI4LIL2Rjspo6OYfEUm6TnRuJwezGF6zKEGNFqBx+Fl+MR4dcsToGhjPSEReqYszGTS5emYw/UkjYwia0IMRpOOcXOTiUkNZeZ1w7nwplFsebecvPnplHxZT0i4gdy5aVgiTKSOiiJ3ThoGmeZKcgqRT9PJsOe/8P731A83AGuNegww/saT6vrmm2/mF7/4BQsXLmTPnj3cfffdrF+/HlBTVq1fvx6dTsdnn33Gj3/8Y958800ACgoK2LVrF0ajkezsbB588EHS0tLo7u5m+vTpPP300zzyyCP861//4oknnmDWrFls2bIFIQQvvPACv/vd73j22We59957CQ0N5eGHHwZg0aJFLFy4kOuvvx6AyMhI7rnnHgCeeOIJXnzxRR588EEA6uvr2bBhA8XFxSxatCjYRiKRnCE662Dat8Fth4h0iB0FWr2qxLltoDWA1gjWasicBfGjobkEPv4x3LQUjBFw2W+g4gu1r+EXq597pgiaU+/gnf+rJn1sNK2HugcM3dXuCkaa2jvdOGwePn+1OHi+6ZViLvlmDhveOMis60dwcGcTI/MTyJ2byo6Pq4IZCqxNDrqtLkyWvkEUB3c0MvnyTBorOsmdm0p4rOp2NYcZuOTusWx9v4Ks8bFYIg143X5cdi9+v5/mKhuhUSbCY010dbgo3lxF1vhY0sfG4HZ6sbU5MYUYqNnXjt6oJTzWrBoY/X4Sh0UQFmVi95pavG4fo6YmYokwEJsWhk6vDW4zIpF8FUjF7WRY/YvDSlsPHodafpKK2/jx46msrGTZsmVcccUVfc5ZrVbuuOMODhw4gBACj8cTPDdv3jwiIiIAyMnJoaqqirS0NAwGAwsXLgRg8uTJfPrppwDU1tZy0003UV9fj9vtJitrEJfIIOzdu5cnnniCjo4Ourq6WLBgQfDcNddcg0ajIScnJ2jZk0gkZ4hDu1QFzHYILnwELAngbANDKGx8DsoCWVJis2HcYvji9zDpdvB7Yeb3oK0MojKhsx66W8HngYg00Blpi1lA8Q4HHpePpkob6WOj6eiXHzQi3kzpNvVzwBSqZ8/q2gEiVhS0MDI/Ho/bR21RO93tLnJmJQeVth6qClvJvyKT2uLDmQ8UBfQmLTMWD2fU1IQ+9aMSLeTOSaFmfxuNlZ2ERZso+Kwah83DRf8zmp3vljNhXjqWCANFG+spL2imvKAZgIUPTuCjfxTiDQQq9AQk1Ja0M+myDJoqbIzMT6CysIXdq2uYed1w8uanDYhkPVZ8Pj9etw+jWSp8kiMjXaUng3XgB9ARy4+TRYsW8fDDD/dxkwL85Cc/4aKLLmLv3r28//77OJ3O4LneyeS1Wi1erxqartfrgzn+epc/+OCDPPDAAxQWFvL888/36etI3Hnnnfz1r3+lsLCQn/3sZ0PK8HXOhSuRnPV0NcIbt6vr2i56HFzd4OyADx+FuoLDShtASwl0VENkOmz/N0RlqYEMPjfsWAJhiarbdMZ3YdiFkD6NpmYdfp/6P25rc6I3ackYFwOoGRXGXphMc40NFIX8KzLxun3oTQPzYJlC9UTEmdHqNUy7ehgTF2Tgdg7cVkOjE+j0fb+20sdGkzIqkkmXZmCJOPzZY+90U76riff+vJudn1Szd90htq6sCEa9VhQ0E5kQwraVFdQUtZE9LTGYGGL45DjKdjQGlTYI7AF3qBtrk4OuNheF62opWF1NQmY4o2ckUbKlEdMJZkRoqrax5uUi3vzdDrZ/UElni+PojSTnLdLidjJEpKru0cHKTwF33303kZGR5Obmsnbt2mC51WoNBissWbLkpMbo3dfLL78cLA8LC6Ozs7PPsc12OMTdZrORlJSEx+Nh6dKlpz14QiKRHAMdNaoylv8tsDVCwVIIiYLrl8Du/wysX79bdaO2lYPXCQ4rWOKh9CPVi6A1Qahq1eq2uuhudxEeY0IIUACtVkPm+FhyZifjcfowh+lpre0iLjWMyKQQOhrtJI+MpHpvK6NnJhGfEYbX6yc2NYya/W14nD62vFdObEooM68bQVx6WJ892sbPTSUmLZTRMxJpqe0iY2wMGbkxRKeEDryUsnaKtzSg+A//ePR5/AitYPq1w9HpNYRGGfl8aTFlO5vJuSCJK+8fT2OVDb/PP2BLDwBntweDWYer24Pfq+D3KxRtqmfipemEx5mpO2hF8StExB97aoSOJjvv/WkXrm5VUf3yvXI6muzMvTUbnX6QZK+S8x6puJ0M837ad40bgN6slp8CUlNT+d73vjeg/JFHHuGOO+7gqaee4sorrzypMZ588kluuOEGoqKiuPjii6moUMPvr7rqKq6//nreffdd/vKXv3DzzTdzzz338Oc//5kVK1bwy1/+kmnTphEXF8e0adP6KHUSieQswRQB4algjoAvfqeW5d0G7m5IyYfdy/rWT5kM5Z+r77UGyFkEb6lrWXE7wF4LaVMB1aLlcfkwmLUsuGccHU12DpW2o9VrWL+8FL9PzV86/ephFG+pJyzOxPg5aezfVMdV35+Ay+5DoxFodQK/109CVhhlO5sJizLRUttFU2Unkxak09nixNrsIGlEBG6nl44GOxMXpBMWbUZvGFyx8bi8VOxpHbAZ8JiZSVTvbaWmSHW1GkN0LLhnHO2Ndmr2tdJS28W2lRVotIKZi4dTs7+tT/uk4RFsW1VJSIQBfy+FsK60gxnXDcdpc1NT3Ibb6SMuPeyIt8babKelpgu30xtU2noo/bKByZdlEJVoOWIfkvMT8XV2ZeXn5yvbt2/vU1ZUVMSYMWNO3SB7/quuabPWqpa2eT896fVtkuPnlN9XieRcp+UgHPgELHFqFGlbORgscN2/oaUUnFZo2gclH6r1UyapQQdfPAPDLoLwZBgxH1bcBToT7pveQm8yItLy6Wp3Yu9009nqYPfqWhrKrVxw3Qic3V4KPq3ukzxeq9Ow4J6xdFtdaPUaYlIsWJvULTdaarso/LwWr9tPRm4MefPT+PD5Qtx2H/lXZBIWY6Ktrpua4jZmXDuc1OyoY7JC+bx+Pv7nXhKGhbPlnXK1UMDUhVnBveF6SB0dRdaEWOxWN+FxJtYtKyUuNYyM3Bh0Bg171x0CBJMuTSMkwojP68cYomf1K0V0B1J7jZ6ZRFe7g85mFxdcP4K2+m5SsiNJGjZwvzyA9oZu3v9zAbY2F1MWZrFtZV+ZtHoNt/xk6nFZ7iRfD4QQOxRFyT9SHWlxO1nG3ygVNYlEcnbR3aJayup2wrc+V92dnXVw1d/A1gCh8bD1n+oWH3N/BEIDYUng88Lif8L+96DwvxCdhRI7hta8n/HBSzB+Xjym2no2vnkQt8PL1KuyaCizAuAOJILvrbT1HHe2OPC6/RhCtPi9ULmnmbj0cHZ9XB2sV1XYSli0iZH5CRzc0YRGKxAENt+9dTQJWeHBdbpD4fX68Dh8GEN0jL84lar9rVxydw7dVjdup5fBzBTNNTby5qehKNB6qIvLvp3L/g11FG2qJ31sNPPvzsHV7eVQaTvrlpWiKGCJNDL3G6NY/XIRigKp2VF89pKau3TPmhqERnBgayPz78oZ1PJWU9SOrU1V+uydbqKSQmivPxzUkX9FZjA6ViLpj1TcJBKJ5OuE3w/NxTD2Wpj5oJotYe6PoKEQLDHgbFWDDXKuhs1/PewaFRq47kVY+QM1gOHSp7FFX8DOkNkUve7E53XhdftZvaIIFDWgwNZ6OCipq81JVFIIeqO2j4tSZ9DgsHnY8VEVCcPCsUQYiUwMxdo8cAF+xe5m5tySTVSSBXOogao9zeiMWiyRxqMqbS21NhorO3EHFDeDSUtHg52CT9R1yHEZYUxakDGgXca4GPRGLbtX15AzK5m1rxVj71SzKOz7oo72BjtjZyVT8Onh9czdHS62f1jF5d/Jpalaza3aQ325lfEXpVJQXEN5QTNavYbIeHOfzAm9gw/2rT/ExEvSGTZR4HH6SM2OIml4pMxpKhkSGVUqkUgkXxdaK2DnK1CxQXWFvvcA1O+ENb8Ee4u6Jci2F6B6M3Q3wYwHIDIDkifBwudUS92lT8GNr4Iljo1rBXu32oNWNK/bT4/ZyhJhIG1MNNnTEtEbtZRubyQ62cLsm0YGN5w1mLRMWZhF0WbVGtVY3okxRI+j00VIuGGA+NHJFkIiDLi6vRzc3kDWhHjcDh+fvrSf0m2NA7YH6aGr3aluy/FZDdtWVtDV7qS1rpvKPYfTdDVX2agrbWfKlZlodKpSlDQ8guQRkRwq7cDW6sTn8QeVth7qSjtw2AaO21jZiV9R2LjiYB9FNT49LGg9qzvYwbqlJZTtau7TNi0n+vCBArs+qcYSZmD2jaPImhCHKfT0bAlibbZTsaeZqn2tdHUc244CkjOPtLhJJBLJuU5LOXRWgykawtPA54IPH4G4bFC8alSpoxVCE6GpSG2z57/q+rcR82DM1VC4HMbdoEaSmsJRTFFEJliAwwv0tTqBRieYdf1Imqo6+eyl/VgijUxZmIVGI6jc3YqiKORfkYE51EBbfTe7P6vpowzZ2hyEx5kJjTT2iRo1mLTkzU+nsaKTyAQz1mY7rXU2Rk1LpHJPC5++uI+5t2YzdvbACPaORjumUAPtDXZGX5BEVGIIzm4v+VdkIjQCW6uD4s0NNJR3EpcWysRL0gmLMREebQIB4XFmJl+eQVTSwDVlQiMIiRioZMZnhOHq9jJmZhJFm1TF1BymZ8TkBDauUFNiJQ6LYN8Xh/j8tWLiM8KIiFP7TxoWwdzbstnydjlet48J89LImhh3Yvf+BGmusfH+nwuCSml0soXL780lUq6rO+uRiptEIpGcq/i8sO9N+OCHMPlOdf3a8ItBCLjwYUiaCI52aC9Xy1ydED1MDVQA6G6G3a/DqMshMQ/CU9TtQHwe6loiSBhuxBzWEPxy93p8zL8zh6q9rZRsUfN8WpsdbH7rIJd+ayxupze4+D8zNwaPy9dHaYuIM6PVaakva2HsrGRmXjec7g43fr9CeKyJPWtqaarsZFheHKGRJnxehbrSdkbmx6HVa9jxYRXD8uIwh/VVpLR6LT6PH71ZS/KISOydHnZ9UhVMHB+fEca0q4fhtns4uKOZsFgTih/WLi0BRc1VOvvGUbQe6iJpeAT1gXV7ABPmpREeYyL3olQK19aCAiHhBqYuzKK9yR4MeohMDMFhc7PlnXIUBdLHRZOQEYZ3eiKp2VF0tjppqe3CYXMTnRzKmJnJZI6Lxe/3ExppOq2uUb9fYe+6Q30siW113dQWt0vF7RxAKm4SiURyrtJcBG2VkHsjRGZB2nSw1asuT6FR33/6U3UjXQBTpBp88Po31MwIoOYcPfgp3ikPUNcRj6Ko1pcuewduh4ucC5LR6DQYQ3RYwg00VnVStqOpjxiKAp2tzj6BCZWFrUy8JJ3oZAsN5Z0kZIUTlRBCt9WF3erh/T/vASA+M4y8+em8+1xBcM+1PZ/XkndJGhW7W/A4fUTEmUkfG03V3lYYRL+JTgrB2eXmoluzqdjdgkarCSptoG4OHBplxG3SMPfWbLw+Px/+vTB43tXtZcdHlcSlhRGdEkpKdhT2Tjdh0SaiU0Kw2zxMviyd4RPjcHZ70GgEG1ccoL1BXasWk2IhPiMcW7uTvPlp6lSH6qkt7WBYXixVha3s31hH6ugoMsbF0lBuRaOBxCGiTr9qfB4fjRXWAeUtNTY8bt+Q26xIzg6k4naWUltby3e/+13279+Pz+fjiiuu4Nlnn+2TlUAikZzHVHwBe95QlbLcQD7gd+5TLWwA5ihY8KteSluEmtLKZYNrnoeWItCZoHIDCvDFR06Ktu4G1DRVs28aha3VyY6PqtTmFj2jZyTisHmwRBoHBBcYQ3TojX2/8Hd9Ws2oaQnMvmUUq/+9P7C1BozMT2D8PalYmxz4FYVuq6vPRrkAxZsbGDE5nr3rDrFuWSmXfjOHaVdlYQ4d6LY0huiJSbFwYHsjySMi2bP2cPaacXNS0Oo07FlTS1RiCIoiiIwfGLHZXm9nWF48Oz6sRKMVGEN0OLs85F+ZxfZVFVx+by5ZE1R3prXZTva0JCp2t5CWE03WhFje++MuXA41ZVdsaijDJ8djiTSwccVBhk+KJ/+KTA6VdPx/9s47PK76zPefM72PRr13q9qyLMvdxt3Y2KY4JA4lQDZkE5IACZsbks1lSXZh7yaXpd1dQtgkGEgPhFBsmiu4W26yrd57HY1G09u5fxx75LEMCzFgLzmf5+HBOnPajPTMfOf9ve/3i73PTVapjZ5Gx2UTbmqtimlzUxl9uTVme1yKge56O9YkPRq9EjEMpngdCnlQ4opCHk64AhFFkU2bNnH99dfT3NxMc3MzXq+X733ve5f71mRkZC43/glo2SlVzfRxkDUPBBW07JgUbSD9u+uQlDNadj1seFxKPbC3QttuyWB350OScJv/LRqOTB47PuSlt3GMuBQ9liQdINl6CAqBthPDlF+VwflDngkZJmypBqyJUq+YSiN9tKTkWYhPM9J9xh4zgdpcM0h/swOvK0BPnf2iwkBnVBPwThrTjva6yZ2R+L4vi0qrpO3EKJZEPemFkiBKzbfgnQhwckc3w10TNB0e5NibnXCRCdX4dCPC2U/ESFjEOxEkbVocIz0TiCKc2tMTrShakwzMXpfLDf+rinnX5pOcY2HJTcXRamBeZSIhf5iDL7ehNagZ6nCy/6VWOk+PcnJHNwdfbb9oP92nybTqFApnJ4MgRYnNXJWFyaYlHIzw3h+aOfpGJ/UH+jn8h37uVwAAIABJREFUWhtuh/+y3qtMLHLF7RLZ2raVJ449wYB7gFRjKvdW3cv6/EtLM9i5cyc6nY4vf/nLgJQt+thjj5GTk8O0adNoaGjgP/7jPwDYsGED3/3ud1m2bBlvv/02Dz74IH6/n4KCAp599llMJhNHjx7lvvvuw+VykZiYyJYtW0hLS2PZsmXMmzePXbt24XA4+OUvf8mSJUs4c+YMX/7ylwkEAkQiEV566SWmTZt2ya+VjIzMx0DrLnD2QNpMqWLmHgJzipQtuvFJ6Do4GWc13g3ZC6Wc0Rel9xMUSim3dLRVEnPWTA6eykIU+2IuM9I9gXPUx4IbCrH3udGb1VgSdNTv66dubx/zrssnEhExWjU4hry8+uRJFm0qpLvBTsXyLBRKAXufm0OvtFG9PnfKEqdSpaBubx8BX5iK5ZmYbFpcY5MCoXRRWowxrdGmi06rXgytQU1ipolQIExChonMYhupBVaOvtERs5/HGcA97qdiRSandvciRkQMFg1li9PR6pTMvz6fgTYntlQD4WCE2l1S9S7gDU/JXlaeZ/FROCsZW4qB8WEvthQDbz5zGoD0QiltIea17ZrgoqZynyJGixqtScX6b1Yw2uOi8dAAJ7d3o9GrmHNNLvteaiEhw0RStpmOUyMXHQqRuTzIwu0S2Nq2lR/t/xG+sPRNst/dz4/2/wjgksTbmTNnmD17dsw2i8VCbm5uNBz+QkZGRnjooYfYvn07RqORn/zkJzz66KP84Ac/4O677+aVV14hKSmJP/zhD/zwhz/kV7/6FQChUIjDhw+zbds2fvzjH7N9+3aefvpp7r33Xm655RYCgQDhcPii15SRkbkMtOyAjFmQvQBUGkiZIWWM2nKlYYP8pVCwHF69GwpXSJFXf7p98vhIGPY+Lg0z6OMRdQmk5dtQrNOgUEDTkUHGh7ykFcbR02in7cQQmcXxnN7Ti0qrYOXtpYRDEXzuICqNkpHuCWp39xAJiRx/u5OyJRkceqUtejmlSkFyjiUmIkqjV5GUY8Zcr8eaLFX05qzPwznqJeQPkzYtjpo3OiT7EaSl26zSD15WVCoVzFyVxZl3e0nNtxKXZiAxy4SgEBDDF6gkEXoaxpi9NgelWkFqvoXRXhfhkMjYoJuK5Zm8+fNTUVNhgLLF6R+Y2qBUS88zOcfCcNdEtOqo1iqpXJWFUq3E7fDTfGSQcCiCQnl5lx+VaiV5MxIZ7nJx6NXJ31fAG6Kv1UFilomRbhf5lYnU7++nZGFajFCVuXzIwu0SeOLYE1HRdg5f2McTx5645KrbR+XgwYPU1dWxaNEiAAKBAAsWLKCxsZHTp0+zevVqAMLhMGlpadHjNm3aBMDs2bPp6OgAYMGCBTz88MP09PSwadMmudomI3OlMNQAmXOk5IPxPilbtGOfNCW6+1+lfbQWWPmg1Mfmd04OIZyP3wk6CyjVdAzE8c6vGwj6wyiUArPX5uD3hLClGkjKNuNzBVEoBSpXZ3FyRzdDnU4aDw3gHPGh1iqZsTyT5beUIAJ+d5BQIMziL0yj6fAAepOGkgWpKBSw8vZSBlrHUWmUWJN0KASBytWZjPa46aobJb8yCYUSxod9uMf9zNuYz4Tdh0anIrXAivVDJAnEpxqZsz4Pe+8E06qTCUdEZq7I5Ph55rlxqQYm7D7sfW7sfW7iUgxYEvUEvGH2vtbCvOvyGexwsvTmYuz9brQGFdZkA8lZU4PszxEKhnEMegj6w1iTDdTt7aVoXip1e/sQlAJ1+/oJeENYk/UsuKGAun199Dc7MNl0JGV9cKbpJ4VrzIfL4cfe557ymHPYhyVRx0i3CwSBxCyT3Od2BSELt0tgwD3wkbZ/WMrKynjxxRdjtjmdTgYGBkhISKCpqSm63eeThKMoiqxevZrf/S42NPrUqVOUl5dz4MCBi17r3LCDUqmMVvNuvvlm5s2bx9atW7nmmmv4+c9/zooVKy7pOcnIyFwiw03w1j9K4fBNb0rToAgQlw3vPTK5n98Jx5+Hpd+HoS5pSEGphvB5JrKWDEguY1xXwo5neqIGspGwSM0bnaz8cilKtYK3/ut0tOqVVhhH+dIM7L1unCM+lCoF867L59ibnXicARRKgZkrsuhrdmDvd1O2JI2ssgR2PFvHwk2F7HiuHr1ZTTgYIeALUzw/FZ8nSE5ZAn6Pird/UYcoisxanS1ZUoiSD5ot1fCh8knPodYpCYdFjm7txO8JUrE8kyVfnMZQhxNrogGVVom9383cjXkc2drBjGUZDLaPRw2BD7/aRl5lEvFpBjpPj54VL1CxPJPZa3MwWGIHxHzuICd3dHH0jU5EEQpmJ+F3hxhodzL/+gLe/q/TnFthHR/ycua9XpZ/qYSXHzmGfcDD1V+dflmmOD0TQU6800XxPOmLvEqjwGjVEvCHqFyVhWvMhyFOw8Sol4rlWf9tcoXMp4dc97wEUo2pH2n7h2XlypV4PB6ef/55QKqS/cM//APf+ta3yMvL48SJE0QiEbq7uzl8+DAA8+fPZ9++fbS0tADgdrtpamqiuLiY4eHhqHALBoOcOXPmA6/f1tZGfn4+99xzD9dddx21tbWX9HxkZGQ+BgZPQyQIKeWQNRf+fCfsewICrovvq1BD/wk4+DNY91NJwAHE5SBufIKQNZeBAS1+T2xFToyI6E1qjm6bXKoE6G9xEHCHsCbpmbMhj7Vfm86Z96Qp0aU3F7Hs1hL0Fg2Va7IBOLm9h5GuCRZ9oZCxQamq450IRpcfexrsZJbYCPhDHHq1naA/TCgQ4cjWDiZGfWSXJ5CUZSboDzPQPs5w10RMQsH7MdTh5LUnT9LbOMZIt4udzzdgitchCAInd3az/6UWGvb303hwgDV3lqPUKCThdFaYiCI4h720Hh2WRBuACKd292Lvc9N4eIAT27voa3YQDIYZ7XOhUCqoWpvLnPW5DHdOkF2ewEi3C9eYjwva4hgb8DA+5CUp20xfkwO/++JpEJ80KpVAwBtmoG2cFbeXMHNlFrkVicy7Np/T7/bgc4ewJhqoWJF50bxVmcuHXHG7BO6tujemxw1Ap9Rxb9W9l3ReQRB4+eWX+eY3v8m//Mu/MDw8zObNm/nhD3+IKIrk5eVRVlZGaWkpVVVVACQlJbFlyxZuuukm/H6pwfehhx6iqKiIF198kXvuuYfx8XFCoRDf/va3KS8vf9/r//GPf+SFF15ArVaTmprKP/7jP17S85GRkfkYUKphpBksafDKNyTB1r4bqm6L3S97ARSvA4NNaoAvXAVnXoGl94MlE1EXR0gdx1t/DlK2WI3WqMLvnhRvCoWASqXAfl7o+TkiYZGBtjHyK5PwuoIUzU0lMdPEmfd6o/FSWqOKudfmse9PLRitWhSCArV26kdNYqaZ4c6Li7H6/f3kzkgk4AuxfUsdQx1SukLJwjTmX5uPMW6qLVLAG2K0z0Xn6dEpYml80EPDgdiVkPFhLx6nn576MSpWZOEY8qBUKwgHIxRUJXH63dhhjYrlmez+bSPjQ5M2KNd8s4KRzgkOb20HUZrOnHdtPsNd46y8vTTa53Y+erManzuARqckozgOrfHTibe6EGuKgbLF6YwPeznzbh+D7U7mX5fPYLuTxEwzdfv60OpVKBRgTtSj01+e+5SZinDhlMxnierqarGmpiZmW319PaWlpR/bNT6JqdIL2b9/PzfddBMvv/xyVKjJxPJx/15lZK44Bs5IKQlqg5Q9eo6cxZC3RAqMX3q/ZPXRUyMJuFm3wkCtZCHS9DbixscJqcy09qYw2utGZ1RhsGrY+4dmAr4wSrWCxZ8vJCnHzIm3u2m5wGh32S3FqDSSJ9pQpySmlCoFCzYVsP/FlugAQlapDaNNS/mSDDpqRzEnaOk+Y49mdhosGmatyebYW50Uzk7m1O7emOsUVieTWWLDPeafMpG55s5yplWnxGwLhyP01NuJhEVGelzR9IZzLP7CNPb+sXnKS7rurhmYbFKAvVKlQKkUCAbCGOO07PltE35PkIwiG6FgmIR0I0ff7GK0d7LCuWBTAQf+HOuFpjWqqFqTTUKGCeeIl6FOFw1ns1oVCoGltxaDCCd3dLH678pJzLw81Sy/J8iJHd1Yk/Ts2CLFoM2/oQDPuJ/anT0x+264eyY55QmX4zb/5hAE4agoitUftI9ccbtE1uev/8QHERYuXEhnZ+cneg0ZGZkrnLZdcPgZyVQ3bRb0H5e2d+6Vcki/8Gt4/V4Y65C2N70BQ3Vw1fdAoYBpawgaszlxOMyR1+ujp82dmcCqr5Qz2OYE4NhbXaQVWCldlIbXFaS3cQy1VsmsNdmodUoQIbs8gawyadLU7wnReHCAnBkJtJ8cAaTlwNnrctn5XD1jAx60BhVzNuSRUWJDrVUy2uPi0CtthIIR0gqttB4fxjMuJR1oDSqSs83UbO2gsDp5yssw2O5kWnUKE3YpQiocCGNOkKxETu7opmheKhqdMrokm1EUhy3FwLQ5yTQfmRSiqfkWtHolg23juMeDqDUKVDoFxXPS8LmD5FbE09c0HjNxWX1NLgFfKOpJF/RNrRb63SHMCXqcIz66ztgJ+MLM3ZhHOCSiUAq0nxxm3sZ8rr13Fkbr5TNU1+hViBERl31yxcgcp6Xuvb4p+/Y1OTDFa4lPNcq9blcAsnCTkZGRuZKJhGGgDsbaYe7X4Njzkofb4u9Az2Fo3AaVt0LfsUnRdg5HJ2jNkFQEnjHc4UROvBO7CpGca2HHlrqY5dKJUR+5FQnMuSaH6nU5iBHQ6BWc2t1L46FBQBoCmHdtPvtfamF82EtqvjV6fNXaHN79XSNjA9Jyq98TYt+fmtl4TyWhYAidSc286/MxWrUISpGrNhcx2ucGUUQU4ci2DmwpBky2qcImKdvM+LCHbT87FZ2InLMhFxAYG/Bw/O0uqq7OwTMRICHdSFedndf+30lKFqax8HMFjHS7MMZpiYRFdv+mkaU3FWFOiOAY9KJUKhntcyEIMGEPRMPjz3FiexcVy7M49pb0RTouRS/ZjZxndWKyaREUYIjTUDw/hbd+UUdfsyP6+MwVWTQdGmTedfkf7vf/CSEIAqUL0+ioHcWSqMM54mPC4cNo0+Ac8U7Zv2F/PxnFceSUJ8ri7TIjCzcZGRmZK5neY9L/VTppejRlOsTnwY4fSekIs74k/Tx4+uLHa82IvUdxpW8gFAhTWJ1M06HBaAqA2aZl+lUZCIKAQiEw2uei9dgwQV8Yu9uDIAgEPEEsSfqoaAOp2lS/r4+8mYmoNEr6WyVxklZoRWdST+mRE0WpDy0uxcD2X9VPeqQJcM1dM6jf1xc14BUEmHV1NmabjrgUA45B6Vz5lYmkF8XR2zB2gY2FQNAvCc+AN8TBV9qIS9WjUAi0HpOWZxv296NUK1j4uUIOv96GVqdi9rpcjr3djc8VJLcikZ7GMQ7+ZZx1X58Rk7s6fWk6tlQj4bCILdlA9ox4LPF6EARWfKmEd//QRNAXxmDVsOK2EnobHXSeHiU5z8LGu2ey9alaIiERa7Ke1EIru56vp2JFJiab7iP/OXycWJMMlC7WkpxrpvHQAM2HB5mzIY/BdieRkCRGzwnRM3v6EASBuGSjHER/mZGFm4yMjMyVynCDZP2hs0DDa5BWKeWNvvNPk/vsf1LyasuaJ1XeTvx68rHZXwaVhtBAM6/+pR6fJ8Tc9XkUViXT3+rA7QygM2qo3dUcXfbLLotn3denI0ZgtM+NWqMgHI5EY4+Sss3kzUwkHBIBkbgUA+YEHaFABJVagdvpRwyL6M1qvBOxE5N6i4aEDBPX31dF6/EhXHYfuRWJ1O7qoWhuKgqlQDgUwWjVEA6K+H0hrr9vFo5BD0qVAluqAa1BjXM01j+zp95O8YLYaX5Lgp7eJkfMtnAwQm/jGNYEPbPW5PD2L89Eq2XDXRPM3ZhHXJKe0V4XWaU2OmuHSS2wMtQ5wek9Z5cQBVh5WylNRwY4vaeX/FlJ3Pi92bidAVQaBcfe7KKjVloyHulx0XlqlOvurcQ56sPe78be5yIh0/yBKRCfJhqtkrSCOMKhCJ7xAMfe6mTONXmSSbBCwJoi9cCptUrCIenvQBZul5cr4y9HRkZGRiaWSBhO/B4OPAnXPw1F6yAcguDUZSzqXwWVHipvkQYVnH1gy5HMeB09jFsXMXNlNmqtEo1eRc0bHYz1e5izPpejb3TE9Gp11dnJmZHAe3+QmvmVKgXLv1SCWqugen0upjipnywSjtBwoJ/lXypFZ1CRMM3M2ICbU7t76G12MHtNDgdebo0OLFSuyiIxw4QoiiRlm6MWE35PEMeQl5ptHRTNS6F0YRrhYIRIWEStU2G0amN6wSIREXNCbKWqv3WcGcsyuOqLRdS80YHPFSQpx4xvIshw10TMvpZEHSl5FvpbHDFLnAqFgMGioX5fPxN2n2RGvC6HuGTDpGgDEOHQq20s2FRAd90YbceHmbkyk71/bGLB9YVR0XYOt8NPb5MDAan/TWPTsuCGfDS6K+vj12zT0dfswO8JRad4Uwus6LvVRMIiZYvSaTs5zIylcvTV5ebK+suRkZGRkYGAG7oPw+GnoforsOtfIXU6WDMunoRgSoWkYqk6JyilYYUdP4bV/0LYNg17cAZdJ6Ulw8H2caqvyaO9dpjxES+jfW5UGgW5FYkUzk4i5I+g0auwpugZH/QSDkU49GobK24robveHh1i0JvVVK2RetmWf6kEtc7L6T290aXJ2t09VF+Tiylei96kISKK9LU46KobJa0gjqzSeHRGNVqDmuzyeGypBtqOD3Nqdy+5MxIRBFCqBEKBMKrzDGqdI14aD/Uze10Op/f0EvCFKZqTTCgYIRyKsOJLJYSCEQSFQCQs0nFqNFotjM+Qlvm8E4EpkVN5lYmcfreXibPN+pGwyJHXO1hz51TrJPd4AIVCsvoQBAiHROx9HgSBKT1vIC0TK1QC5gQdBbOTsX2IilUwECYciKAzfTo2HNZkAxvvqeTQa20Md06QNzORrNJ4mg4NMHdjHiPdEyy4oQCrXG277MgGvFcgDz/8MOXl5VRUVFBZWcmhQ4cAePzxx/F4pnorXciH3e/DsHv3bjZs2PC+j3d0dDB9+vRP5VoyMn8z9J+UKm4KNRjipVD5lOlw8GkQI2DNnNxXoYTZt0vebvufgKTCyeXS1h1MuNV4xoN4nAGcIz7Kr8qkq26U0gXpxCUbWHBDAbPX5uJxBuioteMeD7DjuQZK5qeRkmcBJONcx6A3KtrObetrcWCwaPB7Q5Kp7aFJr7SJUR+HX2/HMeilu8GOc8RL7c4eVBol40NeWo9LE55uhw+FILB9Sx1NhwdpPjzIO786g9vhp2ZrB2MDHoa7nfQ1O+hrcRAORhhsddJwoJ+SBWlUrclGUEr9eYJCEkmhQISAN4Tb4afq6myW3VrMmjvLmbcxn+aaIUzxOrQGtTQle5a4FOOk4e55+NxBLuzFz5uZiO+scW75VelEzmahBvxhyhalxeybkGHCZfehN2tIyjZT914fW5+qpf5AH6O9Lpwj3pjwelEU6WseY9tTtbz4kxqOv92JyxG7NPxJkZJrYd3XZvDFB+ay9OZiCquSWbK5iPTCOObfUEh+ZZI8mHAFIFfcrjAOHDjA66+/zrFjx9BqtYyMjBAISGPyjz/+OLfeeisGwwd/4/mw+8nIyFyh+Fyg0cO8uyQlkjBN8mMDqadtwbdApQUUkFYBXYdgzUNSJFbLTkgohOFGiMvGIRSy78WW6KlHe11n7Ski1O7uJr8ymWNvSlOSfTgw2jQsvbmIsX43ZYvSSSu0otYoGO6emHKb9j432eUJIMJYvxtzgg6/J1b8mOK1DLY5qd0p3UN3vR1zgo5FNxZy6LU2mo8MYk3Ws/rL5fjcQQ6/1o7b4aevxUFaYRwNhwZQa5Sc3N5FKBjBmqRn+ZdKOPByK72NY9E80bgUA5GQyNb/nEx6Kb8qg+EuJ0MdEyTnmpm9Nof+VgfmRC1uu5/Za3NwOwIE/SHSCqzEpxmmDFVo9CpWfbmMw6+1MzHmI68ikdwZiXhdAVZ/pYzMYht+Twi1TsmuFxpY+/Xp2NKM9Lc4sCTqQYTTe3spqEpmx5a6aN9fR+0Iczbk0dtoJ7s8gbLFGehNaka6XbzyxInocMD+P7cS8IeZuyHvUxFNao0yJoLLkqiXnofMFYNccbtExl97jeYVK6kvLaN5xUrGX3vtks7X399PYmJiNEM0MTGR9PR0nnzySfr6+li+fDnLly8H4K677qK6upry8nIefPBBgIvu9/bbb7NgwQKqqqr4/Oc/j8slvbHm5uby4IMPUlVVxYwZM2hoaPjAe9uzZw+VlZVUVlYya9YsJiZi38g7OjpYsmQJVVVVVFVVsX//fkCqpC1btowbb7yRkpISbrnllug3zDfffJOSkhKqqqr485//fEmvnYzMZwJRBGMCHPhPafkzuRQExWSVLRyEvY/B7n8DewsggC1bMua99j+kAQb3CBiTILWC7uapIeIdp0YwxWtZcH0htTsmA9hTC6ws+tw03v19E0e2drDr1w201AyRXhRPcs5Uo9iM4jjyZyVg73eTPzuZeRvzqb4ml6qrczBYpUEEtVZJ05HBmOMmRn14xgPUbO1gfMhL12k7TYcHUJ4NuV92SzFxyXr0Zg1Gi4ahTieJWSYQwOXwI4qS+W35knSW3VrMohsLCfkjHH0z1u/yzLvSsivAUMcEfm+IZbeU0HXKTvb0BKnnT6ckJdeCx+lj3vUFaA2T9YyKFZm0HB3i6JudzL02n3Vfm0H5knTyKhOZtTqHojmpGCxabKlGrvt2Jdnl8YQCEYw2DTkzEhjunsDjCjD/2nyco94pwxont3dRvT6PSEjEPuDGPe7H5fBFK3jnqHuvl7EBN71NYwx3TxAK/PfRXzKfXeSK2yUw/tpr9D/wT4hng95DfX30PyBNe1k3bvyrzrlmzRr++Z//maKiIlatWsXmzZtZunQp99xzD48++ii7du0iMVF6I3r44YeJj48nHA6zcuVKamtrp+w3MjLCQw89xPbt2zEajfzkJz/h0Ucf5Z/+SbrPxMREjh07xlNPPcUjjzzCL37xi/e9t0ceeYT//M//ZNGiRbhcLnS62Abh5ORk3nnnHXQ6Hc3Nzdx0002cS644fvw4Z86cIT09nUWLFrFv3z6qq6v56le/ys6dOyksLGTz5s1/1WsmI/OZwe+GkSbp3zO/KFl8qLSw8B5pSbRhG4yfFVqGeEidASEfvP4dsOXBgm9CRpVUfdNZYaAWrWZqFqbWoKb5yAAavRpBISAIMO+6ApwjXjpqR/C5Jo9xjflpPzGM3xuiYkUmp/f0EgmLZJcnUDw/laGOcdIKLIz2eqjZ2k7AF0atVbJk8zT0FjWOgYsMUwDe866RWWpDpVayfcukMfD86/MxmNQIVg2IoDGoKFmYhlqjpPP0KM01QygUAiULUknMNpOca6Jkfio6kwZEkaYjg0yM+s5Ov0pMjPio3dXDvOvy0ZnUmBO0iKJA0BMiFIpwcmcXZYvTSUg3otQoqdvbR3edHYB3fnkGQSGw9u+no71I/FNKrpXVf1dOX7ODgTYXx9/uIiXXQlZpPDuerWPxF6ZNOUYUwecKIooi9e/10VU3SkK6iWu+PoOAL4R7PMDBv7QxZ30erzx2Ao8zAALMvjqHytXZ6C5TXJbM5UUWbpfA0GOPR0XbOUSfj6HHHv+rhZvJZOLo0aO899577Nq1i82bN/Nv//Zv3HHHHVP2/eMf/8gzzzxDKBSiv7+furo6KioqYvY5ePAgdXV1LFq0CIBAIMCCBQuij2/atAmA2bNn/7cVr0WLFnHfffdxyy23sGnTJjIzM2MeDwaDfOtb3+LEiRMolUqampqij82dOze6f2VlJR0dHZhMJvLy8pg2TXpDu/XWW3nmmWc+5CslI/MZIhKG4WbwOaQM0v1PQPu7oDHBvK9L4fJqkzRd2nMIwgFAABQwdrbKNNYuLae27oT8ZdBzDE79ntyr13JCq4xmggoCFMxKYs9vGzEn6ChdlIbHGaDl6CA6k/qiaQATdt/ZXiy4+qvlhEMRtAY1AV+Y1Pw4XA4/R7a2R4/VGlQ4R3woVQri0w1Mq06m6fBk1c0UryUcnPRJyy5LYP9LLTHXPPJ6B9d8Ywav/7+TUnO/UmDBpgJ8rmD0XOGIyJn3+pi7MU8y2z1jZ8LuQ6VRULkqm666EaTAVqnXbMLux+8J8e7vmsidmUBavpWDf2mTzq8QWPLFaShVAh2nR0nONkdF2znEiBjj73YhSpUCELEk6An6w/Q0jhEOhSmoSsZg0aA1qPB7JodLyq/KYGzITV+zI2pd0tM4xlCnkxnLs+hpsLPyjhJqd/ZKog3p6Rx9s5PM0ngyi23vey8yn11k4XYJhPr7P9L2D4tSqWTZsmUsW7aMGTNm8Nxzz00Rbu3t7TzyyCMcOXIEm83GHXfcgc83tYFVFEVWr17N7373u4te69ySrFKpJBS6yLTaeXz/+99n/fr1bNu2jUWLFvHWW2/FVN0ee+wxUlJSOHnyJJFIJOaxc9f5sNeSkfmbYqgRXP3gsYNrSBJtScWw5Lvwxvcko12A3CWS5Ye9BUIBqPklzPsGzL9LEnn6eND2SccsvR90VpLfuYHrv/wqnb1mAv4QaQVx7H+pBVEE54gP15if/FlJbP9VHRq9ivIl6Qy2O2NuLzHLTOfpUSJhkTPv9lE0P5V9L7Zg73OjN6lY+LlpUdFmsmmZvjSDmq0dhIIRVBoFV99ZTnKOmbaTI6TkmMkosTE+ONlLpr5IGHs4FME7EYgGxkfCIr2NY3idUyuIw10TGCya6ERoKBChZlsH19w1gzPv9TJrTTYKpRCzlFo0N5V3flk3ef6IyL4XW1h2SzEtNUOY4rRThJYgQFzKB/cOx6UYGejop2huCk2HB+lvdXLVF1PparCz4rZS2k4MMzEBJAYlAAAgAElEQVTqI2dGAlqDCpfdP8VvLuALIwhSvNfcjXkMdTinXOf8qCqZvy3kHrdLQJWW9pG2fxgaGxtpbp4MQz5x4gQ5OTkAmM3maF+Z0+nEaDRitVoZHBzkjTfeiB5z/n7z589n3759tLRI32bdbndMJeyj0NrayowZM7j//vuZM2fOlJ648fFx0tLSUCgUvPDCC4TDH9yHUVJSQkdHB62tUkjz+4lLGZnPNEOt4BsDzxgoVKC3wOefg4qb4dSfJNGm0sLsOyB7Pqg00LBVGlLImguWNDj9Erz7f+GtH4BrAEo2SLmmVXeAd4zk3bdQXKmTrCrCkZil0LbjwzgG3ChUAgFvCJ8rSMkCyQxXpVZIGaXayWb1+EwjTQcHoskFXlcIpUaB6qz4KlmQxpGzog0kEfX2L+uwpRkprE7GmmJg21On6GkcY81XyqlYkYk5URcz4QmSQFJf4HXmGPRKvW4XkJBuom7v1IxN97iftEIryTlmKdLrvNaxoC88xbYjFIhE+8saDg4we11u9HkplAKLvzANY9zF80WdI146T43gGPKQX5FE7sxElmwuovyqdKkCuDILvzdI+jQrpYtS8U742f3rRiJhEZV66kexQiENIvi9oZg4sXOY4i9v6oLM5UOuuF0Cyd/5dkyPG4Cg05H8nW//1ed0uVzcfffdOBwOVCoVhYWF0eXDv//7v2ft2rWkp6eza9cuZs2aRUlJCVlZWdGl0Ivtt2XLFm666Sb8fsnL6KGHHqKoqOgj39vjjz/Orl27UCgUlJeXs27dOvrPqy5+4xvf4HOf+xzPP/88a9euxWg0fuD5dDodzzzzDOvXr8dgMLBkyZIpAw8yMp9ZIhHo2CsNHvTWSD+LIQj7pUGD+AKo/b3U27byQTj8X9JyqFIDS78PiYUQ9MPRX0pVunOc+hOseAB6j04ONFizMdhMZJdqsfe7WbipkD2/a4yKFK1eRdWaHGq2dVC/v5+EDBNLNkstDCe2dyMIAstuLsbjCpCQbiLoDVO5KguVRokgQMP+PpZsLmLP7xoRRWKWQQGC/jADbU6ScyST3tnrchnqcLLjuXqW3VpEwBdm1R1lHHqlDXu/m9QCK8XzUggFwzG+aKIoMm1OCm0nhqON/uZEHTkVCTQcnLrSkZBhQm/REPSFpESGOC3ucT8GswaDRY1SrYi5V61RhYAkmHyuICfekXJPzfE6nKNeTu3uxecOMXtdDkrlpNga6Z7g1SdPRO8pNd/C6r8rnzKNaYnXMz4s9fwlZVnobXDQemyI6UszOLH9vCGRfAuOs/upNVK/4Laf1eJ2BBAEmH1NLkkXEbAyfxsI5/vHfNaorq4WzzXHn6O+vp7S0tKP7Rrjr73G0GOPE+rvR5WWRvJ3vv1X97fJ/PV83L9XGZlPnK5DYEyGgVOgUEDtH6QEBJDW5Fb9MxgSoHErOPulEPnz2fxbaUDhheulAYXzWfJd0NugZTt07oUv/YWeQDlv/fwUPncIc4KO6Velo9GrMVjUUrrB2Y+CsQEP5gQd3XX2aC9ZRlEcybkWTu7oJhIWsaUZmH5VBu/9sRlBEKhYnklCtgnVWTGz47n6GEGk0ihYenMxLTWDdJ6W+sYyS2zEpxsZbHcyZ30eJ3Z0UrowA4USQMAx5EapVHL0zQ787hB6i5qVt5WyfUs9ZYvS0eiUaAwqVGoFSo0CvVHDtqdqo5W+6mtymbU6G41ehXvcz+l3e6nZ1oFWryLgC5NWaKV4Xir7X2rB7wmhN6tZdksJNdvaGe6atDSZvS6Hur19UVGmUAhsfmAu8WnSF9NwOMKuFxpoPDjpYQew4rYSShemf+CfgNcleeuFQ2FGulx43UE0ehXjgx7aTgwz77p8MottWJMMuMZ8OEd8aPQq4lL0qNTKDzy3zP9MBEE4Kopi9QftI1fcLhHrxo2yUJORkfloeOyg0EiizDUAyeWTog2kccN9j8EXfwMFq2Drd6aew9kN9a9Jy6Xt78Y+llwK5gzQGGHhPfhT5jBeM0LponTUWiXu8QAHXm5j5sosnMNShqgt1YjHGSBnegKDHc6YYYLMkngOvdoW/Xms30Pb8WEyi230NIxxckc3G75VQSgYYd+LLVRfk0vN1g7CISm/dMnmIibsvqhoA+hpGCMhw4Rj2IOggPRCG35PgEhI8ppLzDKRkGHi89+vxjsRRGNQsuv5BnyuIMfemuxVm7sxj5M7utn8v+fwhR/OwTniRWfSEJ9mQK2VPuKMVi0JGSZUakW0Z62vyUFCuoF1d80g6AtjiteSmGHGmqSno3aE8WEvmSU2Gg4MEApEUGuVkigUIBScbAMJ+cNTegIBRnun2rBciN6kQRAEBtrH8bqCqNQKgr4QOrOGlbeXEpdiwJok9dSZbLrLHkovc2UgCzcZGRmZT5NIRDLY9Ttg5z9LQfCBi3zIe+zgcUjLnUklUuD8+YjAqd9L1h+ObmkZVVDAnK+CKQUCE2DLBV0cLTXD7P7NZG9rco6Z0oVpuMf95M5IRKVRMNDqILUgjs7To1guyAINBadOUvo8QSqWZ+EckSZOnSNebOlGNDrJRqNydTYgxVZpjUpaj41POYdKo2DxjYX43EESM00ceb2d4fPSC8oWpzN9aTpxKQaaawYZ7Zv6OoUCEYK+MCF/BFuaEVuqkXAowtiAm4lRH0arFq1RRSQUoWptDiqVgs7ToyiUAsXz00jOscQY2yZkSIIRYGLUi0qjIK8yEZVaidagYrR/gkhIRIyICAoBjV5F4exkarZ1xNxX+rS4qb/TCwiHI9Tu6uHI6+3Rbdnl8cy9Nk8Smiq5qiYzFVm4ycjIyHxaDDeCa1iy7MiYDSE/1P0F1v1fqZctct5AT/osSYgd/zWs/Sns/lfoPig9NudOaN0uVea2/xgqbwbjjZLA8zmh7hUovwHCQfyigQMvt8XcxlDnhCTYtErJyywiolApOfRqG4mZZnyeIMXzUqMRVudPfSpUAvM25jPSPcHxt7vIKIpj2pwUjHFaQoEIVVfn0FwzxOk9PSRmmZm1JptQMER8uomuM5MVt4yiOCbsPsQINB8ZZObKrBjRBtBwoJ/MYhvhoEj9vn6ySuJpOzEcs49GpySzLB7j2WZ9URRpOTbEjmelidGKlZmMdLnoa56c3Jx/fT72fjfOYS8puVMb/88xYfex57dNUSsOY5yGFV8qpafBTiQSIb3QhiBIXnIjPS46akdQKAQq12STVnDx84qiyMSoD1GUrEWOvtER83jXGTvp0+JoPz7CtDkp+D3Bs/YrKuLTTDG5rTJ/m8jCTUZGRubTYLQNfONS31k4ICUb2PKkSlnjNrjuZ/DOA+AahIxqmH4jDDVA2bVw9FdgSZemTRFAqZaqdSCd6+gW6d9X/yscegau+ak0pNB1AE3hKhatXMfOC0JdpOVRPU2HBzFYtShVAtYkPd31oyTnWMirTCJ/ViLDXS50JjVF81JoOjTI9CUZnNrdg2tMGnZyDHpIK4zDmqQjcHZSM39mIoXVyfjdQd77QxP5lUkoFAKJmSZGes4mt1QkcuAvrcxanS0JuIv0W0fCIiIiQX+Y4S4p+NzrCtLf4kClUTB7bQ7BQJjFNxaiOTv5Oj7sZfevG6I2H0mZJmp39MSct2ZbB3PW59FydIj8WUko36ey1VwzNOmfBrgdAdprR0jKNuEc9pKcY0GlVmJNMrD6K+U4RzwolQosSfqY4YVzOEe8NBwc4PjbnUTCIstvLZmSkgBSFTEUDDPU6aR+/wB+T5CCqiQCvsiH8m4L+kP0Njmo29uH1qCmbHEaqXlWBIWcM/pZQBZuMjIyMp80QR947dIyqUIJjgGwt8K8r8HJ30n/pVdJlh8KNQychHf+N6z6Efz5TqIqpO5l+Pzz0Lkfqm6HnQ9Jhr0A5ZukIYUZn4Nt3wNHBwDCcANFWSfoq3qAhmOSd5pSrUCpEvCMBxnqcDJzZRZH3+xk7GxOZ7tjBASYuTwTW5oBhUIgd0YicckGjHFaanfFCqH+FgdZpTYSMk0EfSG2PzuZgJCSa2Gk20V3g53ieankVSYBoDOqUaoUUWNgrVGN3qyOiYXKmZ6ANUmP1qBGo1Ny+PV2csoTqL4mF41OSf6sJIxx2phGfZ87SCgwubQbDExd5hUjkJBpwjnq5dUnT1JYlUxSjplQIMyE3Y9KJZBZGh+1PDkf57AXjzNAar6FUCgSvbZGqyQxY2os2DkC3hAdp0ZjlkXba0dIybcy2Da5jKwzqgmHI6TkWnnn2broRK29z828jQJxqQZM1otbkpyju26MN35+Kvpz0+EBNn23ipS8968uyvzPQRZuMjIyMp8kw41w6GnoroGrH5ZMc695RLLrOPxzKL4GCldL++75yeRxaTOhc9+kaAPp32dehvzlsONBSfgJCqkCp1BJy6qL74uKtnMou/cy8xo/bfUqrEl6iuencvAvbXicAdbcWY5SKURFG0jJBjOWZjDc7SLgDUleYgVWOmpHyDmb/Xk+ggBJ2WYEhcCEO9Zce2zATflVGXTX22MmL9d+fToGiwaDRYtCIeAe83HVF4toPznCcNcEWeVSMoBapyQu2cDGeyrZ/1ILvY1jqLQK5m7Iizbun48pTovBoolWyvRmDerzkiMA5t9QwM7n6/GMS/v0NTkoWZDK2KAHg1lDcq6Ful+cJn9WUswSK0ByroXj73SRmm+9aFXt/Rgf9dLbOBazre3EMFdtnkZCmoH22hES0k3kViTSeLgfxXk2KOeoP9BPflUyfIBwCwbCHHs7NrM1EhbpPGOXhdtnBNmA9wpEqVRSWVnJzJkzY8LaZWRk/ofhHoE3fyAtZc66FRpeA10cuIdBa5J62upfg/ceAWePlIyw4THY9AzkLOSib9GRsDSoULwe9j0uGe927If4Qlj2A6miN/8boD7PQ0wQ0FuNXP3VcqxJOva/2BIVNnX7+tGcDVbPLLYxZ0Meq24vo+aNTva92MKRrR10nh7FMeBhwaZCUnLMUxrvp81JoWZbB35PEOeoN9rcD1IKgDleR0FVUnRbwewkkrLMLL2pGPe4j8WbC3GN+3EMerH3u8mZHo+91822p05xalcvkXCE1HwrG741k5t/PJ9Vd5QRn3ZxHzOTTcfVfz8dk00SN/beCRbdWEhagRWdUU1hdTJ6kyoq2s7RdGiQzGIb7SdH6KgdITHTTHKumYoVmShUAkqVgvIl6YwPeTFYNJgTtKg/Qr+ZzxXEFH+B4BJhuNvFki8Wcf19VRjjNOz9UzPjQ74Y0+NzqLVKdKa/rt4iyKuknxnkitsViF6v58SJEwC89dZb/OAHP2DPnj0x+4RCIVQq+dcnI3PFMtoCLTukyc51PwFTKuz6F6kidvApWP8oaM3gP2s6rdBAQiG8cT8YE2HB3ZKQa9o2WXUTBMhdJEVapVZI5xIU0rmb34HRRqmPzuuAFf8b3vohAJGZt+FSZiFEoKAqhbLFGTQfGaDh4CBavRK9RcOK20toPzHC8bc70RlU9J0XwzQ+5GV82IvJpsUUr2POhjyG2p3Y+91Yk/WMDXgYbHfSeHCAwuoUFAqB7LJ4nKNeMoptmG06EjJNxKcZSS+KIznXikarxDniJRSIYO/zkJpnZaB1nJFuFyPnDSl0nhpl7oY89GYNGr0Kjf6/f99LL4zjxu9X4xkPoDOpEUWwJOoJhyIYrBrcZ/vzYjgrbIxxGkoWpjLW7+bgX1qpXp9Hap6FkR437SeHcTn8LL2piNSPWL0yx+vQmdSYbNpof6DWoKJscToqtZL4NCNzNuSTXZ6AxxkgKduM1qiSEh/OUn1NLgbzBy+TqjVKqq7O4Y2nJ5dKFSqB7LKEj3S/Mlcu8if/JdJ0aIADr7TisvsxxWtZcF0BRfNSP7bzO51ObDapGXX37t088MAD2Gw2GhoaqK2t5a677qKmpgaVSsWjjz7K8uXL2bJlC6+++ioej4fW1lZuuOEGfvrTn9LZ2cmqVas4cOAA8fHxLF26lAceeIA1a9Z8bPcrIyMDDNbBu49A1hyIywKlTjLbLVoLo62w4p9grBu+8IKUnqDSSmLr6LPS8c4+Kb7quqfghv+SIq4iwcnjQQqUH6iV/v2FFyA+R/J2s2ZJE6l9JxFX/gifOp22sWkMHrBTv68fhVLqk6pcmU3B7BR6GsfY/qs60gqsJGWZGRt0M9w9mWAiCJA7M5GEDCOWRD1qnYL+FidjQ256m8ZoPjIoGfgihax7JwLU7e1HFEWMVi15FYm8+4cmJkZ95M1MpHJVdnSQwJqkJ68ike1b6vG6AqTlT7XQSCu0fiixdiFGqxbjeUuK51ucOI1ezPFaJuyTAq54XipddaMs2VxET8MYhjgNFcuyqHuvj2nVyWSUxJGYbcIUpyU524zyIxrgxiUbyCiSplAjYRGVRkH6tLgYAWhN0mNNmqyUXntPJd31dnzuINml8aR9CIsRgKxSGxvvnknd/n50RhUl89NIznn//juZ/1nIwu0SaDo0wK7fNEQbYV12P7t+I3ktXYp483q9VFZW4vP56O/vZ+fOndHHjh07xunTp8nLy+Pf//3fEQSBU6dO0dDQwJo1a6I5pCdOnOD48eNotVqKi4u5++67ycnJ4f777+euu+5i7ty5lJWVyaJNRubjJhSAsS5Iq4A3vz+5Pa0S1vwrtO2SBg4A5n0dbPlgy4JXvjn1XMMNUoWt+ivS0mfne5BZLU2d9tZI1bb535CE3s6HJo9r3AbLfghimINn8jCnxVO/r41pc1KISzHgOBvwfuzNzmgP10i3i7gUAxnFNgxmTfRU868voO34MPtfakWjU7LwxkKcI15yyhNoPDgY7cMSBEgvisN1VgwFfWGSK8woVAJJ2WZmr80huyw+RoSZ4/X4PUFW3l6KxxnAkqQjZ3oCnadHATDatMxak41S9fF29VgS9Gy4u5KWmkEGO5ykF8Zh73eTW5HE8e1dzFqVTf2+fpoODlJYncz4iJfSBenojOpLum56YRzxqUb8XimpQaP74I/g5BwLyTmWj3wdtVZFdnkC2eVyle2ziCzcLoEDr7TGTC+BNMZ94JXWSxJu5y+VHjhwgNtuu43Tp08DMHfuXPLy8gDYu3cvd999NyAFtufk5ESF28qVK7FapW9yZWVldHZ2kpWVxZ133smf/vQnnn766eg1ZGRkPkZcA6DWwv4nYrf3n4DxTtj3qPRzepWUMWrJgOO/kSplHnvsMRojBDzw3r9LS67lm6BmC5RugMIVgAAakzT8cD5BLwQ9CIP1CMICQsEIKbkWBIHoVGNcsn5K471j0MO06mQm7H7yKxMJeMN019sZ7JCSAQK+MLt/3ci191bi9wa5+qvltJ8YQRRFkrLM1O3tY961+VgSdWj0KrJK4zFatUyrfv/3w8RMC2LEid8TZKzfQ9XabKrW5hAORrClGj6xtID4NCNz1ucx0D5O67EhsmckEPKFqVqVw/YtddFhhpqtHZQv+eDoqo+CzqRGZ7o0ASjzt40s3C4Bl/0ifRIfsP2vYcGCBYyMjDA8LJlO/nfB7efQaieXCJRKJaGQ1Cfh8Xjo6ZFG+V0uF2azXD6XkfnY8DlhvA80ZmnpU62X+tDicmCiXwqPP2eyW7AC6l+Rckqb34L1j8Hr34bI2Z6mxCKp523Xw1K/XPdhaHwTrn0S/nSHJPzmfEVKSbhY57lah5izgHJlmK5RBVll8bFmr+/XrS4INBzop3heChUrsvjLY8en7OJ2+ClZkIbfE0RrUNF2fBjHsIeFNxQy0O5Ab9GSUWSLWar8IJKyLSRlf/TK0qUiKATSCuKwJOgZaBvHHwwyPuKNmUAFqN/fz6w1OZdccZOR+TiQhdslYIrXXlSkTZkcugQaGhoIh8MkJEwteS9ZsoTf/OY3rFixgqamJrq6uiguLubYsWMXOZPE/fffzy233EJOTg5f/epXef311z+2e5WR+Zsm4IaRJqkXTR8nLYMmlcKhn0HQI1XLHF3S9kNPQ8iLVDEzQzgoWYFseFzyZVNpJXPe/f8hibZz+J2SIFx8H0wMwGv3gD4eFn8H3vrHyf00RkgoQjjzEkkt/wfPoj/j16THOIv0NzvIm5lI+8mR6Lb0aVYSs0ysvL0UvUWNQiWw8vZSfO4gx97sjHqs6S2SgNEa1GQWx5NZHA9IqQBZpbaP3P91uTHGaelusJOYZSYSCU95XKVRolDKY5kyVwaXxQ5EEASlIAjHBUF4/ezPeYIgHBIEoUUQhD8IgqC5yDFqQRCeEwThlCAI9YIg/ODTv/NYFlxXgEoT+xKqNAoWXFdwSec91+NWWVnJ5s2bee6551Aqp74RfuMb3yASiTBjxgw2b97Mli1bYiptF7Jnzx6OHDkSFW8ajYZnn332ku5VRkbmLIP1UjrCG98DexvkLobX7oahOhjrgL2PShOfyWWQNR9G22HRt6WqmsYI493w6rfg7R9KJrwBN/QemXodtUESdid/K1Xv3MPQdLYSN22NZOK75mFwD0nVOO8YGarjmCxKskrjo6fpaRzDkqRj4ecKyZ+VxPzr85l/fQGIYIhTEwmL9DaMUbe3n74mB0tvKiYhw0jeTMnH7UKPMQBBEP7HibZzqNRKDr7Sii3NEDMgADBnfS7meDngXebKQLhYzMgnflFBuA+oBiyiKG4QBOGPwJ9FUfy9IAhPAydFUfzZBcfcDFwriuIXBUEwAHXAMlEUO97vOtXV1WJNTU3Mtvr6ekpLSz+25/JJT5XKfDg+7t+rjMxHYrhJqrb5J8CcKlXYJgZhuB6OvyD1nAGkTIfqv5O83E79URJXM28Gazb0HQXPKMRlg0oH+56A6Z+D/U9OXseYBNc+BXv+D/RdUFkvv0GKBMiYLZn+WtKl5daRRkgoAmcfo+mfp/Gkj85To8RnGEnMNHPsrQ6MVi0VKzLZ89smBAE2/a/ZdJ4ZpWZrR/T0CpXAuq/NYLjTSXvtKCtuKyEx87PTajHQNs7LjxwjKdtE1docRnpcuB1+MovjySiOw2D5+FZSZGTeD0EQjoqiWP1B+3zqS6WCIGQC64GHgfsEQRCAFcDNZ3d5DvgR8LMLDhUBoyAIKkAPBADnp3HPH0TRvFRZqMnI/K1ib4exTqlKNngaitdJnmrnbD0s6bDiAelxUYSEadISaNd+SWD1HYf/z955hkdZpm34nJKp6b33ShJCIIB0EEQFARXXhg0VVkXFAnZdFRXbir2tK7ZVRFCxS+9NQiCkJ6T3ZJJJMplJpn4/Hpg4Jvqt3dU5j2MPydvnDe5c3s99X9cXy2DqHaDyhm/+JYYQNAHQ3SBE17S7xWCDXxxEjoG9qyAgfkC4eYfDqIWg8hH9cUEpYmDBYRfXkSnFwERQCgFUMH5CKOmTMzl+uI1vPq1CoZYzbFI4pQda8PRTMvnCZHCI4PdvY7c6aK3pwWax091uorPF+KcSbiGx3pyzbCRlB1uoKdQxbGIEvsFqlOrfr6+tzdRGS28LPgofIr0ikbhddN3w+/S4PQ3cBpz8Nz4A0DscjpMug/VAxBDnrQPmAU2ABrjZ4XB0DHGcGzdu3Pz6GNqhu0nEUrWIqW8icmDrioFjuhuh5DOIP1VEXA2bA++dL3raQPiypc0RgfATbgJNIEhkItMUoOxrYeIblCKqbfXfiDSG5DOgcrsYhhh/A2y6T1zz9IehKV9kluIQ1iQyudivDYI5z4HZgI9HJdkz0knKCUEqk6DUyIkbHoSHUorGW0lHk2HIOCepTAIOKZY+m9OL7c+CRCohNN6H0Pg/RizUsbZj3LrjVpp6m9DINdw37j5mxszEQ+YekPir85sKN4lEchbQ6nA4ciUSydQfefoYwAaEA37ALolEstnhcFR+5x6LgcUA0dHRP/+h3bhx4+a71O4XQqmnCWr3DWy3GAcf23BYRFhNXAofLxkQbSB606bdJXriyjfD5NvEsqrcA45vEcfYraJPbsQCIQpPvU/8c+zfITAF9j0nrhmQCOoAYdxrOpGJ6aGBuc+Bxl/0whV/IvrpUmYhCc1w6dv6dl+Xb7CGrBlRbHu7xLnNQynDJ0jF5tXFjDs3AfmfTLh9HwazgcquSkxWE1a7lR5zD9Fe0cT7xqOS/zp9bx2mDu7afRdNvU0AGK1G7tx1Jwk+CaQGpP4q93Tzv8NvXXGbAMyVSCSzABXgDTwD+EokEvmJqlsk0DDEuRcDXzkcDgvQKpFI9iD65FyEm8PheBV4FUSP21AP4XA43CXnPxG/R5+mm78wLcVQ/AVo/YUBblgWVO8S+zwGh54TMQqOrIHRV4sBhO9iM8PIy0VQfPEnYqm0tRhmPiSqanIVxE0RCQwTbxVTpxetgaqd4KESy7UAoVmiT870rSBzi1GY8cZMEJmoLcfEkuvxLSd84IZGKpOSkB3ktPpQe3oQleaPsbufaZemIpFICAgfOiv0z0ahrpDj+uPo+/W8fPRlHIj/v7l99O1ckHLBr1IBazO1Ud1d7bLNgYN6Q71buLn5badKHQ7HnQ6HI9LhcMQCFwJbHQ7HAmAbcN6Jwy4HNgxxei2iFw6JRKIFTgFKhjjuB1GpVOh0OveX/Z8Eh8OBTqdDpXJPfLn5lTH1QMNR6O+CzHNFb1vdflERS5gujqk/KPrNTv6HoU8kpM4WAqpqO0SNHXzdiNEQOwUix0P2peAfJ9IQ5BpIO1tMitot0FwAhhY49DpsfRBC0qFsMySfSD/pbhDLqN+luxH6e8WfU2aLZ+44/v9+XKXGg4TsYE67Mp2cs+JQeyvwDtIQGO1JQnbQX8LTTGfU0dDTgNVu5XjncUK0Ic59Txx6gqruql/lvr5KXwJUgy2ggjRBv8r93Pxv8UfxcbsdWCORSB4C8oB/A0gkkrlAjsPhuA94AVgtkUgKEXHAqx0OR/6PvVFkZCT19fVOQ1s3//uoVCoiIyN/78dw82fG4YD2ErG02dUAdjNEjQNHqvizNhjSzwalNyCB1FnCMHEgyGcAACAASURBVNfUCVsehGFzRcVr9FWiwtaYB2o/EQTvEwm+kaD0hNBUaCkRx9Tth2/+DXOegX0vQNQYMaEKYon2w0XwtzfFPe02KP0Ssp6Awo9cnz1lFmxfCWlzISBBpDWkzftRH1+l8UAV8+cXat+ly9yFl8KLw62HqeyuZFLEJLwUXrxe8Dp2hx2dSScad35hQrQhrJiwgpu23YTZbgbgmqxrSPRN/OVv5uZ/jt/FDuS3Yig7EDdu3Lj50bRVQEeFqF5V7RS5o+FZYghgzcVighNAKof5r0H5JtH71nGik8M7Qkyc5q4WQiooVfi0xZ8KocPBO0RYiXTWQVvRiYnQICj9HAKThHHvodcH99BNuQ12PQVnvyyEpcpPPNOhf4u+t1OuFZOlXfVQfwhixgsRmjEfAt0i4P+jtquWKzdeSYtxYMJ2TOgYlDIlh1oO8cFZH6CSqyjqKGJX3S6yQ7IZHTqaUO3QTgONhka6+rsI1gQToP7hHFG7w051VzX1hnr8Vf7E+8SjGWop3s2fij+kHYgbN27c/E/RWgrGdjE9etJTLTRdRFuVfTEg2kAsm1ZsEwMJYxbDgVegs0qItNhJYlr0yNviWtPugcjRoPEVZrxddUK8yRTimo2HQekl0hJUPkKkWYzQXg5FHwsBJpGJe+qrhYBz2MUgQuocEbMlU8HGe8RU6qRbQV8veu7cou2/ot5Q7yLaAI61H+OBcQ9wVeZV9Nn6eLPwTVpNrWQFZbGhYgO7G3Zz3yn3oVUMxBNa7VZ21O3gH/v+QVd/F5GekTw2+TGGBw3/3ntLJVLifeOJ943/1T6fm/9N3MLNjRs3bn4IY7uYyOxugKl3iqpa1Cmg9oHCdYOPt/aJZc/N98OM+0Xly9AMXy6H7MvggnfF/sAUIdoAdOVC1HmohVir2in62OY8A/7xIoT+2PtCrEWMFNOn+WuF0AM48q6w+tj6oOiDay+DuMmw/yUYcTFI5OAhpknx/fFtBV39XcgkMjwVf42BhJPIZa5fkcMChjEzZiYvHn0Rg8XArLhZ9Fp72VG/gx31O7gm6xreLX6Xmp4ahgUMc55X1VXFsh3LsJ5wvao31HP7ztt5Z9Y7+Ch9KNYVU6QrQqvQkhmQSYxPzPc+k8PhQGfSoZKrfrPfR1dfFzXdNc6l41S/VFQe7r7i3wu3cHPjxo2b78OgE9UylY/oDStYL7Z7hYtYqeQz4PhW13MSpoB9srDwcACb7hXbNf4QPwV8ooQ4055YKmstEyKw7huw9kPYcHGfGQ+IAQhLH+SvGbh+w2EIyxZDEFsfENs6KoVfW9oc4SWn8RfZp4nTwTcWwrMhZBg/Fn2/ni01W3i94HXUcjWLhy9mZMhIAtWBP/paf0SaDE1U6CuQSCQk+iYOWuJM8ElgZPBIDrcKs+PTY05n1eFVzv1vFb3FlRlX4qP0oau/i0+Pf8rUqKlYvm35AjQYGpyi7SQnq3nlneVcs/kabA6RkRqqCeVfM/9FrE/skM+7vnw968rWEaYNY+nIpYwOHY1M+utZs/SYe9jVsIsPKz7km+ZvxN+DzMVcmHrhX07I/1FwCzc3bty4+S5W84CRbV8P2EwDlh8APY3CZiN9Lpz/ljDi7dOLxAJLv0hKmPGAEHxT7xRWHzETxX7/uIHrVO2EHY8Lc97YScIypKUIJt0iJj/94qC1cPDzVW6D6PFiKEEiEZU8D40QaN7hoG8Q2/zjIHwkqH58wkF1VzW13bVsrNlIbU8tALfuuJW7xtxFgm8Co0NH/0/bKlV0VrBk6xIaDY0ARHtF89ypz7ksTQaoA3hk4iMcaD5AbXctHf2DPd+3121nbOhYNtZsxOawEaoJxdPDVdAMNSHqrfDG28Obhw887BRtAM3GZo60Hhkk3OwOO2tK1/B6wesA6Pp0XLv5Wt6Z9Q7pgek/+T38f9R217K9fjvfNIvcXJPVxDN5z5Din8KkyEm/2n3dfD+/S8i8Gzdu3PyhaSmGun0iMF7tI5Yev4tSA8e3wwdXwFe3i6lO/3goWCd60brrRS9axWZoLQGlj+iNO0lzEaxbKAShxQjlXwvBp/EXGac7nwRzj4jC+i6Ro8WAw+TlcO5rQtwZWk4sy7aBTxikniUqfD9StPVZ+1hbupaLP7+YJVuXYLVbWTJiCWq5GplERn57Piv2r6C8s/xHXfePxudVnztFG0BtTy1barcMOi7CK4Jzk87lplE3EaEdHOrjr/Knq78LgAuSL0AtV1NvqHc5JsE3gWuzrnX+LJPIuH/8/Wg8NLQaWwdds9002Nal1djKmpI1LtusDivH2o+xvW47DYah7E9/Pkarkf1N+wdtP67//y1l3Pw6uCtubty4cQMiwqqzSgwD9DSDdxTMelxU3IK/U9GQSCAkU+SMnqTpiJgC7dMPbLNbwTMYchYKA92TdNSIKdVv+65JpJBw6oAH3FnPQMEHYsggdiJU7xbbfSLFEujRNWKZdtpdokoXmATIwDMIgn+6SWteax4r9g/Edh1sPoi/yp9HJz2KTCKj1dhKin8KlV2VGC1GSjpLCNIEkR2Ujb/a/yff97fE4XBwpPXIoO3H2o597znd5m6ivaMJUAWg69MBIJfIOTfpXD6p+ITbRt9Gia6EXQ27uG30bS7najw0XJF+BRMjJqIz6YjwiiDeJx65VM4FyRfwTN4zLscrZApym3NJ9k/GSyGEt0KqwE/lh9HgOlms79fz8IGHCdWE8tKMl0j0+2UGT2x2GzKpjEB1ILHesRxtO4pcKsfLwwt9v55wz/Bf5D5ufjxu4ebGjRs3+loo/kz4nPW2gU+0qHTJ1WCzgVQGc58XS5Qln0Hi6WLZc9IyqNohMkQBjm8TQwEdlWKZNOsikYTgFwtKLZj0Yiq0eqcYcjiJ0ltkjhZ+BAdeFtsic0SEVe5qGDZPLLk67OAZIiZIU88CsxGkHjDveWEFYu75yaKtzdhGbksujb2Ng/Ztrd1KqDaUD8s/5Nqsa/lP0X94eOLDaOQa4rzj0PXp2NOwh6ygLPY27WVv417GhY9jcsRkIryGip7+fZFIJJwRdwaHWlztoqbHTP/ec3bX7+a+vfc5e9r6rf2i2tbXxVnxZ7GvaR8Hmw+yaPiiQZOoIMTbUFOk48LH0dnfyWeVn+Gj8OHspLP5uOJjWk2iwnZN1jUk+CXgr/ZnWc4ybt5+s/PcKK8oesxiQKXZ2MzX1V//LOHmcDjIb89nbelaWnpbOD/lfMaGjuXarGvZ27gXtVxNR18H8T7xpPq7Exx+L9zCzY0bN25aCkVv2Je3i6qbJgBm/RPkSjFN2t8DXiFieXLk5cK6Y+sKYYSbfLqw6tjxuBBbvrFw5uOg9ge/RAhKFIMDAG1lQrRtewiyFkDmBWLK02YW900/R4i80i/EEMKZj4sl1KIN4n9SGZzzLxh+PgQmg180hI4QvW6mTvF8/yXF7cXsathFe187c+Ln8EHZB3xU8RFLRiwZdGyMdwxNhia6zd18WfUlV2ZcyZdVX6KSqfhPyX9w4CBAFcA/xv8DXa+OXnMvG6s3srNuJ49Nfgxv5RDLvb8zUyKnUJZcxrrydUiQcFHqRYwLHzfksUaLkTcK32BM6BhS/FL4V/6/KNWXYrWLgYNZcbOYHj0dL4UXr+W/xgszXgCg19JLbbfoD4z2jkbroR10bZvDRm1PLTNiZtBj7uGlIy/RZ+sj2S8Zm8PGQwce4vnpz6P10DI5cjJvnvEmRboi+m396Pv1vF30tvNaBbqCn/VOijuKufKrK/FX+zM7bjalnaVo5BpS/VN58ciL5LcPeN732/pZmLEQqUR0XFXoK6jorEAhU5Dqn+quyP2KuIWbGzdu/trU7AepAvrbYcJNYpBArgAPJay7SixhTrtL2G+0FomJ0k+vF9YcIHrbJDJInClEnd0mlki9QsEvckC0ddaKKptfPFzwHnTVQkCyWG7tqBh4njGLRa9cR6WwATlvNRR+LPzdMufD9segKU8cm3UxRI0XolMpRIG+T0+RrgiL3UJBewFGq5EJERMYHTIaD5kHTYYmdCYdDYYGoryiiPaOps5Qx0cVInHBW+HN6NDRzmZ0hVTBgrQFPHzgYQCkSPFUeBLvG4/RYmRGzAw21WxC369nX8M+0gLSONJ+BJlExrjwcdT11JGu/PWa538qodpQbh9zOwvSFiCRSIj0jPze3FGpREqQJojhgcMp7SylsMN1YOSr6q+YGjkVf5U/z09/nvSAdJoMTTx56Ek21mwEYEb0DJaPXj5I0ASqAhkbOpbHvnnMZXuCbwJ2h53njzxPc28zCb4JKGQKRoaMZGTISDaUb+Dpw0+7nHNG3Bk/650cbTtKmGcYcxPm8tqx1zBZTfir/Ll77N0uog3gpaMvMSNmBjHeMeS35XP1xqsxWU0AxHrF8vz053/Q1sTNT8ct3Ny4cfPXxW4TmaCWXjGIcDKZIGIUjLhE/DzxZtj1JBhPTBTqqwdE20nKvoRz/w1IxFSpZ5DwW/s2+hpRSavZK0Lfo0+B9lJX0QYi1mrM32HP0xCcBjsfF9d12KB2j7D8OCncjr4roqxaCiF+Mu0SO6sOrWJ8xHjeLnzbKTDeLnqbp6c9TZW+CovdQrJfMmabGSRg6Dc4pyAD1YE0GBoI0YSwZMQSbHYbUomUPmsfFruFcG04k6Imcdfuu5yPOztuNs9Oe5Z2UzsSiYT79t7n3LevaR/PTXvuZ/yCfl0UMsV/ZXCrkqu4OuNq7tp9F2clnDVov91hx0vhxbUjBgYQdtbvdIo2gM21mxkdOpqL0y52OTfcK5wUvxQWpC3gk4pPUMgUzE+ez8HmgwwPGo6P0geNfHBiwviI8VyRfgXvFL+DBAmXDruU8WHjf8zHH4RMImN23GxePPKic9K1o6+Dqq7Bmaz9tn6sditmm9kp8k5S3VPNwZaDv6tws9qsWB1WVPI/n9+cW7i5cePmr0t3M2AV4ujbcVINuWLZUiIRFTjjt2wghqrK+ESJZVV1gBB1YSd6mfp7RfC8vlbkjbaXiu1Jp4kKXvzkwdeymUGugpyrwEMFrcWu+1U+rj+3l4kkhLKvqAiOJ0gTxNtFbxPpHckZ8Wfw0pGXMFqNrC1dy9mJZ/Pvgn/zwtEXSPNPY27CXPY27mVx5mKWj16Ol4cXqwtXD/qiPjvxbC5OvZjRoaNdRBuICUgPqQe6Ph35bYPjoz+t/BSVXIXVbiXJP4kQjQhqtzvsGCwGNHINcukf/6soxjsGuVROj7mHcG24Sy/g5IjJJPkluRy/vX77oGtsrd3qFG52h52Gnga6+rvQyDXkt+UzL3EeFruFdWXrMNvMpAekc+eYOwnzDBt0rSBNEEtHLuW85POQICHcMxy5VE5zbzNFuiL0/XrifeJJ809DKVe6nNtgaCC3JZfqrmqygrIYETwCH6UPI4JGsKlmk4s9CUCfrQ9vhTfd5m7ntimRU5Agoc/WN6Swq++pH7Ttt8DusHOk9QhvFL5Bq7GVi9MuZlLEJPxUv0Ko7O/EH//fFjdu3Lj5pTG0idzRxjzQ+A1t92ExgUwplkG/TVeDqMg15IqfJVKRkKDxB5MOQjNAcaJCUrEJPrgcptw+INo8NBCWJWKvFF4ibN7UKfap/WD6P0Rovcob3poz+Lm++zy+0WDswHp8K1v7k3iv5D0ACnWF7GvcxyXDLuHV/FeZHDmZlQdX0tEnRGhxRzG6Ph3To6dT1CHMgvNa8gjThg36Ip4cMZm3i97GS+HlrKxIkHDjyBvZ37ifa7dcy8TwiS4xTydRSBUUtBfwTN4zxHnH8fS0p5Egobq7mm5zN/4qf4LUQaQG/LGb3f1UflyYciFP5j7JtVnXUtVVRYW+gokREzkj5gxCtCEux48JHcPuht0u204JOwWADlMH75W8x+rC1dgddi5KuYhrhl/DqsOrqNBXEOUVxb2n3EuYNuwHg+XlUjkx3gNVrVZjK6tyV5ETkkO/rV/47zkgNSDVWXlqN7Zzx847ONI2MFV7/YjruTrzapL9k9H363kl/xUcDFSVP6/8nOdPfZ7XCl6jorOCMWFjCFAFsGjjIt6Z9Q7zEufxzGHXydjRoaN/5Bv+ZSjSFXHVxquc/Yd3776b+065j7+l/O13eZ5fA7dwc+PGzV+L+lwxVGBoEcuPUg9IngVH3nE9LiARpt8n4qhiJkLNiS/hw2/CWU8Lg1tDsxgICIgHuScEBw34phk7RaVt/mug9BV9aN2NMPIy0deWNhcOvyEyRBvzxLJt7ETY/ggYdZDxN5jzLHxyw8AzZV0IHSdElVwJU++Cvm7ATnP8RNYVveDyEbrN3UglUqZETiFYE+wUbSdpNbbirfBGJpHR7+hnftJ8rFgZHjgcg8XAZ5Wf4enhSZupjby2PMI8w0j2S6ass4yJERPZ3bCb3BYhYHc37mZ5znI212x2VmxkEhmpAalsr9vO9OjpbKndwhdVX9Br6eWdYvG+Iz0juXnUzdgddoYF/nfpDg6Hg4aeBpqNzWjlWnR9OvT9egLUAfSYe0j0TfzFMz4lEglquZo7x9zJoeZDxHrHMid+DlKkpASkDDr+1KhT+arqKyGKgRS/FGbEzACEuJBJZVyVcRW5Lbm8VfwWGg8Nt466lWBtMIGqwB+0Vuns60TXp8NH6UOQOsi5vbKzkhHBI1ixf4VTeGUFZXF6zOlMiZpCtHc05fpyF9EG8Gr+q5wRewYxPjEMDxrObaNv443CN7hp5E1Y7VaMViMd/R3MjJlJlGcUuxp2OU2ZyzrLmB03m3ZTO++Xvo9GruHGkTcyImjEz3vhP4LqrmqKO4qxO+y0Gducou0krxe8zmmxp+Gr9P3NnunXxC3c3Lhx89dBVynManc8Ifza0s8RE6Tx00QmadlXIo5qzGIRM3XKdaJ6lnY21E8RViGewWIgIXYCbF8pKmTeEaD0GxBtdpuYEpWroK1E5ISe+g848JKopPW2ieqawyEMeO124fW25lv9T/lrxLLs7Kegs1oskXbVQ+IM4QkXMUqcv/EumL0KicoTeYkci901bilME0aHqQOL3YIEiUslRSqRIpfKUcvV+Cn9aDQ28nTu0zT2NuKr9GVZzjJivGPYXLMZgK+rv+aOMXfQaGgkVBvKyoMrXe71Xul7PDHlCbbXbUeChES/RN4tfpfG3kauzbqWLbVbyGvNI0AVwPkp5+Ov9EcqkVLaUYqnhyftxnYCNUPHaXX1d1HeWY7JakIukSOVSpEh473S95yDFXKJnJWTVrKpZhPTHNNI9kv+mX9hXBkVOoq7d99Nv62fjr4OijuKB3m2nSTGJ4YXZ7xIZVclSqkSO3b6bf1U6is51n6Mks4SdtfvZnLkZOYnzedA8wG6zd0sSFuAv9ofh8NBm6kNpUyJj3JgeTy/LZ97dt9DVXcVIZoQVk5cidZDy7H2Y1jsFkK0Ifwt+W+sLVsLiIGDiRETef3Y69w97m7R2/gdzHYzRquRXnMvHjIPzk08lxjvGJ489CSVXZXOd3tLzi1EeUfRUDpg9iuTygjzDOPWnFu5JO0S8bN28NLuT8Fit1Cpr6TB0ECgOpBE30Q0Hq79fvlt+SzdtpR2UzsKqYLLhl026Dpqudo5/fpnwC3c3Lhx89eg/pBIROjTi2XNU66Bvc/Bkf/AqMshbgqEZoqYq6NrhA1IyixRkZN5QFAyNB0VViDxU+DAK2K/TyRoA8HvhMFua4nIHK3dL0TVyUGGrAvFkmpvO/jGC8PchkPC7Dfp9KGXa4s/FX1uuW8CDjjzSajdB/ueh3NfFROupz0EX9yG+uL3eHTioxR3FKPv1/Nh+YcEqAPwU/kRqA7k7aK3mZ80n3Xl65yXX5C6gFHBo+i19HKo5RCbajaRGpDKGXFncKz9GKtyV/HPKf8kxT+FqzKuclpXHGg6QJJvEneMuYPn8p6j19IrXnFPPX3WPnJbcnE4HGw4vmHQRxobNpY0vzRWfrOSup46ACaGT2Rs2FjaTUMLtx5zD58e/1RMfko9eKf4Hcx2M7PiZlFvqGdR5iLaTG18Xf01jx58lKUjl9JsaP5FhZvNbsNqt7IocxFquRq1XE2UVxS+qu+v4gSoAzBajTyy/xF2N+7m6syrUcqUfHL8EzwVntww8gY+rviYeQnzCNGEcKTtCHaHnRZDCxVdFVR3VaM368kKzGJs2Fg6+jq4efvNzrSFFmMLlV2VPJX7FEar6NH09PBkWc4yZkTPYHOtENxWu5XPqz7n7yP+TrxPvDNb9SRTIqfQ0tvC6oLVNBgamJMwB41c4xRtIFIaNlRsYEL4BMaGjWVv417ivOOcS7keUg8ivSJ/sfcNsLlmM3fsugO7ww7AdVnXcUXGFajlagDKOsr4uvprZ9KE2W5GJVcN6sdbMmIJ3oo/niXNT8Ut3Ny4cfPnp7VEhL2fskRMhY6+Gj65fmD/wX/BqCugcoeolJ2ku1GEtSs8Yf6/ISBJ9JT16eHMx4RAixkvqnAA7VVC2FnNsONR1+nTo2vE8qihBSbdBB9fJypyw+aK6p/XEFUK32hIPREcrw0WQi8kXVThjHqQKqj3j6Jizkq2lryFXConwjOCvLo8Hpn0CJX6Slp6W5BJZRxrP4anhyc3ZN+Aw+Eg3DOceO94SjtLkSBhbPhYMgMzWV2wmp31O5kWOY17T7mXm7bfhL5fT1ZQFgm+CXxY/iEglsh2NexiQdoCXs1/FRC9cJ4envgp/Vw8xUYEjaBCX8HpsacTpY3i65qvnaINxDLr9JjpTIyYOOSvr7qr2vmFfPeeu6k31HNBygV4K7zxkHrw2rHXiPCM4IbsG3i76G0aDA14Kjxp6W1B16cjSBPksqT4Y3E4HGyp3cIdu+7AYrcgk8i4e+zd/5UJ7ReVX1DcUczfh/8db4U3Txx6wrmvtKOUxyc/jsFioKC9gDT/NNpMbbSZ2lBIFXgqPJFJZThwUKwrps5Q5xKRFesdS6Gu0CnaAAwWA3mteeSE5rC5djMyiQyFTEGEZwQamQYvjRevzHiF1YWrKWwvZErkFEaGjOT2Xbc7r5Pfns9VGVcR4RnhEqXVYhR/lyaETWB8+HimRE4hUB3I4ZbDbKwWE7Snx55OZlCmy8BJpb6SbXXbKOkoYVrUNMaEjSFQPXRl9SR13XU8uO9Bp2gDePHoi0yKnERGYAYgBkC+u/y/unA1N2bfiMFioMPUwdToqb/psu1vgVu4uXHj5s+PvhYCU0RuaMpsIYC+S+kXkHzmgHDziRaZoEpvIazy10DGeaK3TJUlKnOGcqg7AAGpIEEMIHxwOUy8Cfq6Bt+jrwu23A+Tb4eQDEidDblviOuf9jCEDofmE5OZMg/IvhS2rYRhc2DDEuEPB5A2B8cp11HQ30FeZ5GLGFDL1SwevpiPyj/CbDNT1V3FspxljAweSbe5m/dL32dR5iIK2grotfRSoishRBtCdXc1XgovQrQh+Kv9mRQ5iQf3P4i+X0R4jQ4dzRsFbwCgkqk4LeY0gjXBpPmlsSxnGRa7heFBw7lr113cMuoWKrsqyW3JZWzYWNID0jFZTTT1NtFsaia3NXfQqzmuP86c+IFhDIfDQZGuiEKdsDSJ9ormUMshJkRMIFQbCnZYU7KG/c0iR7PeUM9TuU+xasoqttdvR92tRiFVYLFZ+KTiE7KDswEYHjR8yCnNH6Kup45799zrXIa2OWw8fOBhhgcNJ8V/cH+b89dt7aOso4xHJj2CzW4b5NU2IXwClV2VvHT0Jee2Dcc3cNeYu7Darfip/DhQdYCVB1ayYuIKtHIto0NG802L8NjzUfrQbGwedF9dnw6FVIi1i1Iv4oPSD7h51M28X/o+odpQFFIFM2NmsihjEbftvA0vpZeL+ANYU7qG+UnzeavoLee2aVHTiPCMYH7yfOe23JZcrvz6SqfAWlO6htdPf52RIcIOp9HQyJItS5z5rV9Vf8WizEVcN+K6H5wm7jZ3Y7AYUEgVXDrsUhQyBQ4czqQIgNzmXHJCc1zO67X0IpPKWDx88fde+38dt3Bz48bNnx9rPxSshwUfgFQp+sw81KLKpvQC/wQhxOQqsVyq9oX2Cij6BGY/ecLKo0zEW3VUCqsOhSdI5GBohdZSiBknvNfsVlGpC0gE3bc82mQeJ/ra7GDrFzFWm/8xsP+zG+CcV8SEqdkEDivsfQYSpsP+lwZEG0Dxp0giRhEZmsnK6q9cPqrJakJn0lHdVc2No26krrsOmURGdnA24Z7hhGnDWLptKYszFyOTyAj3Cmd1wWoMFgNaDy13jrkTk9WEWq4mTBvmrGjY7DY8ZB4keCawMHMhrxx9hTpDHafHnM6o4FFE+EZQ01VDgDoAqURKQXsBfko/Yr1iuWPXHXSbu7ku6zq+qv6KrMAsGnoaODfpXII1wThwkOSbxNG2owB4KjzpNfdyzeZrMNtFT1awJpjbcm7j6+qvaehtYOXElTxzxHWS0Wq3UqgrJC0gja7+Lu7YdQfLc5aTHpiOt8Ibg8XAU4ee4q5T7vpR9hCdfZ2DhI3NYaPd1E4K3y/c6rrquDjtYhp6G4jxjuHcpHNRypR4K7yp7a4lKziLW7ff6nJOu6mdekM9z+c9z7zEeYRpw1iSvYSnc5/m2qxrifeNJ843jhB1CB4yD+J94intKHWpPI0MGUmcdxx3jrmTmp4absm5hWdzn8VgNTAzdibJfsl4y7xpM7VRa6gd8tk9pB6MCh7FpppNdPR1cHrM6YwPH+8UZCdZX7Yeu8NOiCaEeJ94dH06NlVvch5X3lnuFG0ghlHy2/JpNDQS7R39ve8uWBtMmDaMcxLPYW3ZWudyqFqu5vXTXycjMIM5iXNYX7aea7OuZV3ZOvqsfVycdjHTo78/uuzPgFu4uXHj5s+JzSp82vq6hIhatF2IrKZvwC9OTIZu/gckzRQB7jV7xXkqHzj1Xtj5mFjqzHsLTntQXC8oRVzj/YtBGwTjb4T890VlTiIVvdybbgAAIABJREFUwwMgROKM+0VvWluJyBcdf4Ow/9AECtHXVef6vA4HbH9UxGBFjjqRyCCF8GwxyfrdjyeR0GHtpd/aP2ifxW4hMyiTNSVrMFlMzE+aT013DR9XfMychDksTF9IpFckNd01zp6o9WXrmRU/i6dyn6KjrwMJEs5PPh9PD08ONB9gU+0m5ifNZ1TIKJbvWI7VIYTk51WfY7KamBU3Czt2PCQe7GnYg75fz4SICbxV/Bb3jL2H1wpeQy6VU9lVyZlxZ7J05FK+rPqS7OBs/FR+1HTXEBgSyP377idME4ZEInGKNhATsAW6ApaPXk5zbzM+Ch98lb7OiuBJZFIZpR2lzI6bTdS4KDzlnpTpy6jtqSVcG87ZiWdztFUkBMR4x/xXBq2BmsBBfWEeUo8fbMIv0hVxtOWoc0p06dalJPsnE+cdx9qytVjtVp6d9uwgzzQApUyJ2W7mg7IPWJS5iPKOckK1oXgpvCjWFTMpchLPH3keBw40cg0PjH+AF4+8iNFq5Pzk8xkbMpYeSw895h6SfJN4aP9DxHjHkOibyMbqjRTrihkTOga1XM15Sedhs9sIUAWg69M5n+G6rOsI1gbzyMRH0HpoCVAGEKQNQiKRuDxrkCaIB8c/SIW+grzWPCaETyDZL5mjrUfJCMxAIVUwzH8YNd01XJV5FbU9tdT11LGvcR8qmYpgbfCQ7y9IHcSqqav4supLp2gD8R8m7xa/y4oJKxgfNp6W3hbWlKxhRswMxoaOJSc0x2WY48fS2tuKRCIhSPPTl9Z/bdzCzY0bN38+Go+CuVf0k/mEg65a+LV5qMQSZV8nHH3vxP5IODywHERfFxR+CHFTRag8wNH3RW7owVeg+BOxzdAKG+8RliFbHhTxVVkXwu5VosK36T4YdrYQfVU7hUlvcz7MelKIwKEEg3cYpJwJTUdEskJoFgSniMGJqh0Dx0kkFGp9WJT7CAszFlJ2ZGCwQSaREecTh8Vu4atDohrnrfRmTOgYxoSOQSKRYLQauXP3nc5zLkm7hMXDF/PckeeclRsHDt4ve58bs2/kQPMBGg2NjA4ZTZ2hzinaTrKtbhsL0hZQ1yMqTKHaUAxmAwaLgRUTVhDnE0eYNowmYxMRnhG8XfQ2C9IWMC1qGl9UfeG0lojyimJ5znL6rH28lP8S30Xfr6eoowh/lT82h41FmYtclonHho6lSl/FKeGncOuOW/FSeHF24tm8Wfgmnf2dpAekMy9xHo8dfAy7w87VmVdzefrl/+8XfYRnBE9MfoLlO5fT1d+F1kPLivErXDzUvovOqCM9KJ0+ax+fV36Ork/H6JDRPJv3LAAXJF9Aj7mHuQlz+aDsg4G/AgpvFzF5tO0oM6JnMFMzE51Rx1nxZ/HIwUec+41WI08eepJnporqY0d/B2X6MjICM5gQMYE9DXtoMDQwL3EeXf1dTI+ZTnlnOb3WXuJ94knyS6K0o5TFWYtpNjTTbmpnZuxMRoWMwkvh9YPvpaCtAJlExhdVX5AZmEm4NpzVhasZETSCBWkL6LX2srdxLwHqAK7OvJqHDzzsFIe5LblUd1ezdOTS7xXP6YHpLu/mJMe7jmOxW/BX+3NlxpXMjp8NiBizn0pHXwcfV3zMa/niPzCWZC/hzNgz/5A5u27h5saNmz8XdYfEUmR3o+hH2/owjFkE2x+GxiOi2jbrCWGgK1cN3YvWViJE10nhZjYIQ96yrwYf68ws/Rym3iGmRgs/FMui0eOFwAvNgO4mEQz/wWXCfiTrQmEj0n2i+VvmIQYRSj6D3NeFwFNKxP4xi8T96w+C2o/mqbfxYPXHGK1G8lrzuH7E9eys34mP0oez4s+ivLOcN4tElS7eJx6r3Yodu7Do8E3kmk3XuHyEd0ve5ZSwUyjrHDzZqpKreGjCQzT1NmG1W4e0VfBX+eOj8GFU8Cgu+/oyJoZPZGrUVKbHTHc2oY8IGYF/tz8PTXiIzTWbaeltQSlXOkUbiF6y/LZ8xkeM56y4s3juiGtcVpJvEkaLkTUla7gi/QqCNEE8PvlxKvQVeEg9qO6qxmQz8UHZB3SZu7hzzJ1U6Cu4KPUiDrceZn+T6IebGjWVLbVb+Nexf5EVlMWUqCmDf6/fYVz4ON4/633ajG0EqAKI8o763mPzW/OpN9ST15ZHdnA2x7uOI5PInNO38T7xTIyYyLb6bQSohKg51HyIcM9w5sbP5Y5ddzivleyXzEcVH1HcUUyyX/KQdhctxhb2NO4hMyiTx755DH+VPy29LTgcDsK0Ydwy6hbUcjU763c6l6P3Ne0jJySHRZmLkEqkZAdlk5qS6qyotRnbKNQV4nA4iPeNdyZenORY2zG+rv6ako4SZ65qiDaEYE0wR9qOcOmwS7l1+60YLAYAMgIzXCp6IPrhZsbMJDsk+3vf5bSoaawvX++y7byk85xiTyKR/CzBdpJd9btYlbvK+fND+x8iWB3MtOhpP/vavzR/HmMTN27cuDHpoXK7SCdoPCrMaSNyYMsDQrQB2C3QeBiixggxpB1iSSRuCtQdHPg56yLR4+Y7xJe1h7AmIDAZ+nogeBjMexEmLYPeFvj0BvjoGvj6DlF5808Q3nFtpTD8fJh6J0xeLv659zmQykSgvMJL9N2tuxLWXiYsRyYvR3/h21xYvZbSE1YNexv38tqx15ifPJ+zE85mY81G/lPyHyZFTmJK5BQuTbuUAl0Bjx58lJUHV1LaUeqyBAkiJqjb3E2af9qgj+en9GNv4158FD5IJVJCNCEMDxzucsyNI2+kx9xDraEWuVROub6czMBMAtWBNBmaKGwvpKKzgg0VG1i8cTFnxJzBtOhpVHdXD7rf0fajdPZ1khGYweLhi/Hy8CJEE8LdY+8mTBtGvaGeSRGTCFAH8HH5x3jKPfH08GRt6Vr2Ne3jzNgzOdZ+jBuzb+Tpw0/zcv7LvHj0RbQeWmbFzaJQV8iwAGH0q5QpsdltvHz0Za7ZdA0flH1Ac+/gZv+TRHhGMCJ4xA+KtvKOcso6yzDbzChkCko7SpmXMI9gTTBeCi+uzLiSjIAMLHYLH5Z/SKuxFU8PT85JPIfs4Gx6LD3ozWL5N0AVQKg2lOIOEXtW1lk2ZG5ppGckDb0N7KzfyV1j78JL4cUr+a9w47Yb2du4lw0VGyhoL2BksGt/2qGWQ3Sbu9H36/ms8jPn8EVNVw3XbL6GRRsXsXjTYhZ/vdjFGsRgNvDy0Zd5s+hNDjQf4N2Sd9nTuAezzczUqKlIkNDS2+IUbYDTwuPbSJG6TBcPRXZINveeci8+Sh/UcjXXZV3H1KipP3jOUOhMOup76l2mVE9itVtZX7Z+0PZvZ83+kXBX3Ny4cfPnob9bNP9b+0Gpgf4ukePZXj5wTG+7yAONmypMbBVeIkh+/0tCKEWPh8zzYf8Lwnpj+EXQfBQ8Q2HirfDpjQODAlFjxbCCZ6jwdPv8FhEMnzhDWHl8dburJci+50T81ZH/CKG26V7xPCdJPE2Y885+CtZeIvrvxv4dDr8NldtwBCTS7qFCJpFxfsr5BKoC0cq1yGVyevp7KGgvYGLERMaEjmF9+XrkUjnB2mAeOvCQ8xaNhsZB/UwauYYIbQRXpF/BE4eeoN3UjlQiZWH6QvLb8vmi6gu+qPqCxcMXi6rasMuoN9RjtpuJ8YpBK9eS15qH1WFlXNg4wj3D8VX6crDxINvrt9Pe146HxIM5CXOYFDGJMn0ZCqmC0SGj2de4z+VXmBmYyTtF73DJsEvYXb+buYlzkUlkBKgCqOqu4rPKz7A5bOxq2MXNI2/mneJ3GBc2jqUjl+Kj8MFH6cO8hHnktea5NMVvqd3C9SOuJ0QTQqA6kCenPInVbuXpw09T1S0mifc07uHsxLO5e+zdPzmcvL2vHZVcxWsFr9FgaEAmkbEwfSEXpFxAgCqAko4SVHIVBrOBieETXbzuYrxjuGfsPdwx5g5UMhURnhFcv/V6oryimBw5GYPZwO7G3dw66laey3sOs91MgCqABWkLeDbvWc5NPJd1pevYWb8TgObeZp449ARLRizhubznOD32dFL9UynpKHHe83jXcXY17CIjIIOa7hqS/JLYWrfVpfpa2V3JV1Vfcd2I6wCo7allZ8NOl89d0lHCGbFnUN1dzbiwcYP+4+Ck6G8xtji3zUuc5/I7GgpvhTfnp5zP1Kip2Bw2QjWhg/rsvg+Hw0FBewG1PbVsrtmMyWoiOzib02JOc0nWkElkxPvGk9eW53J+rHfsf3Wf3xq3cHPjxs2fB7lGGOba+oWNBwgRp/AUy50gxFlfN9iBhm9E71hAgkhJ8I0SWaTvXyL82fziRFXO1Amxk4VlyLznQV8n9mlPVM7+thq2PSKqZQmniqVWqUzEWdksIkkhd7W4jt0i7Ekaj8AZj4tBhrZiYVOSOlsIxpo9QvgVbRD3GbMY4qaw16pn+falPDD+Ad4tfpfhScOxOWyYLCaS/JIobC9EJVPxwL4HAPFlqTPpOC/5PPJa8yjrLOOjio+4adRNvFHwBvWGeoI1wdw66lYkEgmbajZxbuK5RHlF4aXw4uX8l12+5N8uepuswCxWHFjBtKhpOBwO3il6hwjPCOYliID0S9MuxVPhSU13Dbsbd1PRWcHkqMl8Xvk5/8z9J5ekXUJ3fzc+Sh8iPCOYGz+XTys/BWB69HR6zD3khOZwz557MFlNzsioz1SfcX7K+VyQcgHvlrxLoa6QLnMX5ySeQ0lnCXZEaHuYZxjToqa5iNWT6Pp0LExfSKW+kl0Nu5gZO9Mp2k6yoWIDlw27bFBo/H9DTXcN68rW0Wpsdfqf2Rw2Xit4jRuyb6DOUMeuhl1clHoR9+27jwfHP0h6YDr7m/aTGZjJmNAxVOmr6OjrYFrUNAp1hdw86mbquuv4pOITvJVCxOSE5PD45Mcp6iii19LL80eex2Q1MS58HDdsvcHlmewOuzMtYUvtFi4fdrnzd5oVlEWlvhKlTElOaA42uxiUONxyeNBnO9h8kGsd1/6gaArRhGC2mVHJVFjtVtRytTPb9tm8Z3lm6jNsr99Og6HBKRTPij/rv3q3wZqhhxh+iIL2AvJa89B6aIn1jsVsMxPuGc6xtmMuwk0ikfC35L/xZdWXzulhP6XfH3KZFNzCzY0bN38W2krg4yXCa83SLyY99dWiojb9PvjyW9FEfV2iKrb7SfGz7jjsfkr8efYqkWFavQv848X1vELEkmdQmjDC9dCC2l8IxOhxQgjW7oXxS6G/R0yXWvoG8k+VXjDtbmHm6x0ppkWPvidyTicsFRVAuQreXyAGJiRS0deWMV8IUIsRvcqTFQcex2QzUdlVyTlJ57CncQ9fVH0BiMrEyokr+bjiY56b9hwmmwmNXMPqgtWU68uZHj2dO0ffyZG2I+Q15/H34X+nzlCHvl/Piv0ruCL9CqfT/jVZ1yDplbiItpM0G5vp6u/i44qPndu6O7qZmzCXUG0oz+Q9Q6x3LOcln8fI4JEMDxrOsh3LnMfes+celuUs45GDj2C1Wzkn8RwenfQoVV1VHGw+yObazSzLWeb8wj9JR18HdofdZZCgqquKjMAMFx+0JN8kbhp5E2NDx/J51ecu10jxS+Hfx/7NnIQ5Lkt/vxTH2o6R4pfCpppNg/b12/rptfQyPHA4Be3CnPi+vfcR7RXNxIiJWG1W/JR+KGQKAIo7iumz9dFibOE/Jf8BoMfSw6rcVdx7yr0k+STRb+2npquGK9KvIEwbho/Ch2BNsEtVC8QELIhJzRS/FHJCckj1T0UpV+Kn9MNsN/Pi0Rc5Lfo0tB5apkZPZXv9dpdrzIyZ6RRt0V7RTIucxrb6bc79w/yHEeMdg1KmxGg1EqgO5OmpT/NF1Rc09TZxWsxp7GvcR5JfEkqZkmZjMxekXsDwINdl91+SHfU7yAjMYH/Tfrw8vGg1tVLfU0+KXwqNPY2Ee4U7j00PTOedWe9Q2lGKTCoj1T+VOJ+4X+3Zfg5u4ebGjZv/bcy90N8LB14VQi0gUfSdlX8tMj4jRgkz3UvWg64KVJ7QbxRVsKFQ+QjhNPVOESK/8zGInQQXvw/NhSI83toHxg4IGSYsR7R+InpKGySEW+Ro2Lpi4Jr9PaLidt5qqNgGZzwKfvHgGSieXaYAJCIvFcRy74FXxJ9PW4EjJAOz0osecw9aDy29ll4sdotTtIEwLH3hyAvcknMLN227iUvSLuHNojedAuijio9oNbYyP2k+VV1VtJpanYkHUV5RLg75OMCGbZDdxoLUBWg9tINeWZxPHIW6Qj6v/JybR93MU7lPkeKfwobjG4j3GRz2vqN+B1lBWeS25PJRxUdEeEawtW4rx/XHWZq9lCTfJKQSqUs/kkqmwu6wO4cjgjXBxHrHYrQYmR41nS11WwAo15fzXul7XJp2KYW6Qmcf3emxp7OvaR91hjrndTv7Oon2inYZkDgr/iyivL6/h+37sNgs9Jh7SPBNIC0gjSJdkct+pUzJ+rL1XJFxBUaLkVEho7DYLcglcj6t/JQZ0TN4q+gt9jTu4arMq+gx9qAz6TjUIsyi1XI1DoeDPlsfrUbxu7t/3P20GFt44cgLAGQHZ/OPcf/g+q3XOz9jVlAW9YZ6JEi4bfRtjA8fT4W+gnXl65iXMI/XC153ThKvLlxNVVcVt42+jbMTz2ZDxQYcOJgVN4tpUQPVJ0+FJ4uGLyLJP4n81nyS/ZMZFzaOdeXrnMkacd5xXJ15NWoPNRa7hdePvc7lGZfTb+3HS+HFvIR5JPuLSDKzzYzOpEPjoflZVh7fxWYX1ejSjlLnewSYFTeLOO/BoizJL+knVVp/a9zCzY0bN/+b2G3Ce23bI9DTKHrM5q8W1au8N8HQJkxxK7dD2hxYfyXMfVaIOf8EUVULShFLnSeJGCmC4hesh433QuuJ2KbWYpE9Ov4Gscxp0on77XgCJt0Mn90CLSeO9Y6AcTd892nFfeoOQOMhcR99tRCYKj/R17b3adFbd/S9gXOkcuxBKbyvL2KkfywXpV7EK/mvEKwJdsliPIlWoeWNgjecTeHfrVrtadzDeUnnMSxgGLmtuaQHpFNvqGdp9lLu3Xuv87jq7mpajC1cnn45td21NPc2MzJkJIGqQHr6e5ifNN856eet8Ob85PNZlbsKBw4quyoJ1YbSY+7BZDENKfS0HlqX6Kb8tnzuP+V+LA4Ljxx4hC+rv+TKjCt57dhr4jVIpCzMWMiu+l1Mj57OmXFnkuqXyl277yLRL5HFmYsZGTKSd0ve5eaRN9NmauOr6q9YlrMMh8OBzWGjxdjCyoMrnddTy9WsK1vHouGL6OzrpKqriskRkxkbNpZKfSV27IRrw/FX+4tfn7ENm8NGiCZkyOVCfb8eBw4aDY3MiZ9Dk6GJzv5OQIjB/LZ8dH06qvXVxPvG88/cf2J32JFL5FyffT0h6hBWF64GxJLju8XvMiVyCkuzl+KjFIMhNV019Fh78PbwZmH6Qko6SvjqWwbMea155LXmsTxnOfp+PcGaYDRyDa2mVlZMWMG4sHFoPDScm3wuPkofbA7boMioY+3H6LP2cWvOrVw27DIcDgdR3lGDhgsONR/CW+GNyWZic81mUvxSnKINoKq7ii11Wzgt+jTWlKwB4NX8Vzkv+TyiPKOI8Y7BYrNwrP2YiO2yGDnWfoz5SfPxVfgS4xPjfPc/lSmRU6g31LuINoAvq77k/JTzieOPWVH7/3ALNzdu3PzxMerEUqjVLKY3fSKgKR/ePntgUGD/iyKs/YPLB/rZKreJPrPqPWLaU18LnTWQvxbChsOoK4XgajoqxJQ2CExdoCsfEG0nac4XlThtAHgFCyEXNwmObxsQbSDsO5SDxQqROWKQYcQC6DgOhR8JWxJNABR/LJ51wlLsoxchPbYWh28MfZNuZoO5BZtnEG39bURoI1iUuYj89nxmRM8YdIuxoWNZW7YWYEjbDrVcTYFOZGLuqt/FigkrONZ+jP1N+4Vp6gmriG2121g5aSV7G/dS1VVFdnA2IZoQgtRB1PbUMiVyChPCJ9DY24jOpOOloy85m9FVMhVmmxlfpS+tplbifeJRypT024RRsFwiZ0zoGB7/5nHncyX7J1PRXUFeSx6lnaXO4x6a8BD9tn5sdhudfZ0sy1nGpppNlHeW82XVl4AwutX16eg2d7MocxH/Lvg3Wg8t85Pnc1x/nGBNMJ8e/5RJkZNYlLmIb5q/ocXYwiMTH2FNyRo2VGxgXvw8zss5j3J9OevL1xPtFY3JakIlVzEhfAL57fk8c/gZjFYjC9MXcl7yeYMMWj0VnpR3lpMRmMETh57gsmGXEekViRQpzb3NfHL8E2ZEz2BCxASW71zurIhZHVZeyX+FS9Iucb6/AFUAaf5pjAweSW5rLp8c/wSpRMqCtAXo+/RkxmZyrO3YkEvZexr3cEX6Fbxb8i7tpnamR093RlX12frQoiXCM4Lx4eM53nXc5dzZcbMJUAdww7Yb8FP6cX329YwJHYOHzGPQfaRSKflt+RxtO0q0VzQ13TWDjslvy2d23GznzzkhIp4qxT8FmVTGxxUfs2L/CuwOO0qZkvtOuY/qrmqCNEE8euhRHp34KHG+P11cpQel02ZqG7TdgQMZsp983d8bt3Bz48bNHxt9HXxyI1RuFT/7RMHFa4WQOinaZB5w6n3QcmxAtJ3kyH9E71lbiQibjx4nqlr6GmEV0tcFXqHQUgSjrxJZotmXDH4OqUz0qgX9H3vnHR51nW//17RMy6T3HkgjlYQQQmgizbZK0RVsiAUFZEXRBa9lwV4Re0F0LaveVVFQQKUKAgKBAAkkpPdeJpNJps/8/vjIwBhc3V337t77y3mePDzzrZ8pZE7e7/c5JxmsZiFkcDpFC/SnqN0HU1fD7seFOCJgGEz5kxA67HpcrH3m6yBXg28YjJov2qOF66m+ah3Fw/Mw2IwM8wkmgiCajE3ugf5Yn1jaTe2EacNYkrWEN4vfxOa0EauLZXToaLrN3XxY9iENfQ1kBWe5yRjAvJR5bK3ZSrh3ODE+MWyr2+a2PJibPJeL4i5CI9dgcVo41HaIGJ8YMoIy8Ff6o1FokElkOJwODrQc4NK4S5FJZaw5ssZNQtRyNQURBcyIm0GLsYWF6QsxWo0sylqEzWljwDZARlAG+5r2ucnc+MjxGK1GDrUc4kibyDCdETeDYb7DaDQ2EqmN5GT3SbJDs2ntb2VD5QZ3JTFaF02ENgKcYo5r1YFV7ud6pO0I9+beS7+9H6VMiZ/Sj5eKXiI9KJ2i9iI2VGzg0XGPEuMTQ42+ho1VG/mg9AP3+ZnBmcT7xBOoDuSh/Q+5t796/FX8lH7MGzHP4y1Xy9VcPvxyus3deCu8OdR6CF+lLy8cfQE/pR/pQek09DVQri8flJZgspuI9YllUdYiEv0SefHoi9yVexeFbYUeBrRvFb/FyryV7KrfxezE2WgUGrbVe87TZQZl8sbxN8gOycZP6cfxjuPIpXL+sOsPSJCwKGsRKQEpLPhmAdNip5EWmMbJrpMEqgIJVAe6s0mbjE0s2r6IN6a9wdiIsYM+4iODR7rb643GRmJ0g+OrRgaPRC0TlbphvsO4KukqwrRhxPnGUaWv4rGDj+F0OdEqtNwx8g7eOfkOlfpKkvySmJU4i83Vm1mSveRXq0hNNhMmuwl/lT8SiQSFVEF6UDqR2kia+s+OAmQFZ3mIE/63QbZq1ap/9xr+ZXjzzTdXLVz4fzdodghD+P8Cp7+GAy+efWwxiHaod6iYYwPhs1a+FQLihSLzXCh1kHODUGu2n4T4iYJA9TaIn9G3CluPYRcALih6H5TegiD21IqK2IR7xJzbGeuOxoOwfRX4xoLad/A9ky4SqtDU2cJ8N+Mq2HAbxI0TM3j5i8T1Q0bQ77BweqCFuoBYjHm38Fnjdl46/irFnSXkR+TzwtEXSAxIpLSrlNaBVmJ9Y6kz1CF1SfFR+jAyZCSzEmZxUfxFrPh+BdNjp2N32tlev53J0ZO5IuEKUgJSGB85nsK2Qk73nOaiuIvIC8vjrZK33KSrvKecG1Jv4GjbUVy4UMqUtJvaMdlN5Ibk0mfvE4asuEj0T8SFi49LP2ZO0hxidDFMiprEvJR5vHfyPer76pFJZAz3H05JewnpQenEeMcQ4xNDZW8lUomUiVETmZ04m/KecrbUbEEukTMicASjw0ZT21vLV9VfUdhWSF1vHVclX8W9e+6lrq+OnNAc6g31LBm5BLVcTZe5i9ywXDZUbvCIRgLcCQ4quYpo72jSgtIobC3E5DAxN3kuUT5RtBnbiNRF8vThpz0IVdtAG1cmXsmJzhNuH7Vz9/1u2O8GVaLCvcPBJcx6A1QBaBVaJkZNZFf9Lkq7S7E6rFyfej3b6rZ53MtX6UuwOpj1JetxupzMGDYDu8POjvodNPc3e9xDLpETqgklyT+JakM1JrvJLUYY7jec2Ymz+Wv5XynrLqOsu4yl2Ut57AeRWNBv62d3426S/ZPZ07iH0u5SpsVOY2zEWC6MuZBPyz+lz9bncb8AVQCR3pH4qfwGbVfJVOxv3s+AfYAEvwTCtGFU6IX1ToQ2gimxU2jsb+Se3Hu4bsR1JAYkuq9zqusUX1YJNfHclLl8fPpjNxHsMndR2l3KqNBRpAWl/c0w+jMoaiti1YFVvFX8Fr2WXqK8o/BR+qDz0jEmfAx2p50B+wBXDL+CpdlLCdWG/uI1/x1YvXp1y6pVq978W8cMVdyGMIQh/Gej9cTgbfUHREj7meQBv2hRWZPKBVGznPPlk78E+tvPVueK3hPxVdseEoSs+Si0lohKmjYELntBiBLkKhg5T1iMfP5jcgEI8cLsdUJpqouE0o0w+QGQIEQLPpGiknZ6s5h1azwIX98HE+8R8VohqcKyJHQEJR0lHGo9REt/C1KJlD1NewjThHHv6HvpMnXx9OGnuTH9Rl48KjItr0u5DrvTTnpgOu/DiPVCAAAgAElEQVSXvs+O+h3up3n9iOtZmr2UJw8+yaqxqxgTPgaz3YxKpuKD0g/cVaoFaQsIUgXhdDnx8fJhwD7AkqwlhGhDcLgcNBob2V22GxDGrlclX8Xp3tM8+P2D2F12IrQRLM9dzuvHX2d02Gj6bf34qfz4uvZr4n3jifKJoqi9CD8vP7QKLcmByXSaO/FX+dPQ18Dao2vda470jmRq7FT2Nu3lVPcplo1aRmFbIcc6jrmPqTYI644I7wjKe8qZEDmBP47+IxU9FUTrognXhmNxWNAoBhvTquVqKvWVKKVK1pWsY3bibG7NvBUJohpzqOUQuxp2Ea2L5q5Rd/FW8Vse/nZWp5UwzWBX/jifOLykXuf9uPqr/Gk3tROji8GFiwf2PcCcpDl4ybzw8fKhx9TDIwWP8OjBRzFYDQSqArk542ZeP/46KpmK5IBkHj7wMCtGryDSO3LQfFaYNoyCiAKMViPb67YT7RNNQUQBCqkInNcqtKyfsR6Lw0K4NpzXj73unrU7gz1Ne0gOSOZk10k+LPsQL6kXy0Ytw1/lP4goBqoDaehrIEIX4VanAnjJvMiPyGf99PWU68txupykBaUR6xOL0+VEb9HzUtFLKKQK5iTOGTSvppKp3EIbtVw9aNau29yNv8r/V/npVfRUcOu2W93t+HXF6+gx93D/mPuRy+Qk+ifyQP4DDNgH8FZ4n3eM4H8ThojbEIYwhP9sROfBgZ9six0P394PE+4VFS8QrcwDr4gUgo4yIU5IvVwkHgTEw5z1Qgmqr4OKbTDublFdqxQWGFTtgLzbBVE8eXbImmkPC+sP24+tFnOv8HNT+4OXnxAUlG2Gw+vOnjP2DuEN19cs9iddJJSjZ2xE/KKo6Kmgub+ZjVUbyQzOdNtrNBub6TH3sCxnGX3WPqx2K3annaXZS9F56XjrxFtcPOxiD9IGIj5ocdZiLoq/iPv23cdFcRcxNWYqKpmKtRespcvchUauweaw8dThp5gSO4U5iXPICM5g1f5V9Fp6uTXzVg8biEZjI8UdxeSF5WF32fHx8iFEE8LnFZ8zN3kujxx8BJPd5I5tcjgcFEQUMDl6Mr5evnxW8Rnf1n2LxWFhfur8QfYcTcYmtHIxD5gVlMWx9mO0GgcnF5R0lhDvE09bv6gsSaVSgjRByKVyPq/4nG5zN6sLVrurhSBMhfPC8sgPy6fGUEN5Tzk2h433T73PzMSZnO46zYZK8T639LdwvOM4t2Tc4lZoBqoCGbAPMCZiDJ9WfOquaqlkKm5IuwG57Pxfn/V99VjsFrosXdT21tJl7mJrzVbmp82nsLWQPmsfN6TewNpJa0EC7QPtPH7ocQxWA5OiJrnf17+U/oUH8h/gu8bv3MreQFUgwZpgWgdaae1v5cb0G9lZv5PPKz8nJSAFhUxBfW89v0/+PaNCRwEMytqM1kUzPnK8e0YQBEGN8o5iUdYilu5c6n4Nz7wGS3YuYe0Fa8/razbcfzjD/YcD8E3tN7x6/FWP/VqF9rxEyeVysShrEeuL1yOVSAepiKUSKXG+ced9jX+KKn2Vm7SdweeVn3Nzxs1E6aIAkEvl+Hj95+WO/iMYIm5DGMIQ/rMRkw95t8HhN0UKQUw+eP8oIpDJ4NMFEJYBOfOh8G1RSfOPE3FS2jAxb/bf14prTVguKmKaQJDJz5K2M9AGwqHXPbfteRZG3Qj7z2nX9ndA4xFh0ttW4knaQITRz3lbRG85nbD/ZWGke9FjYh4PaOtvw2Q3cVP6TW4lYpe5i1Gho6jtreVU9ymiddEcbDnIQ2MfQi6Vs/bIWiZETRhUnQCwOW1YHBYCVAHYnXZ2Newi0S+RYE0w//X9f+Gt8GbxyMXsbthNVW8VF0svJlQr1Itd5i4CVYGD/L9AtLRGBIzg2hHXIpfKKe0qJcYnBoVMgdluBkRr688n/8yfxv4Jg9XA1pqt7KjfQbQumjtz7uTdk+8ikUgw/nT+ENEmfGrCU4RoQijuKGZE4Ag2VW/yOGZcxDi+rP6SBekL2Fi50b1OuUTO3bl3s6ZwDZuqNrHmgjUcbj0sPjY/rnHVfmGZEe8Tz/TY6azMW8mRtiOD7mFxWNDINUTrohkRMII5iXMI0YSQ4J/A2zPeprS7FJvDRpJ/ktvG4qfoMnXRZ+3D7rLz1KGnmJ82HxCzhWuOrCFEHcJD+Q/ROtDKxqaNFHcWkxuay6KsRTxX+Bx2p93t49ZobKSsu4zfJ/8eqUSKBAlWh5U3T7zJgrQFIufVUI/daWd06Gh6rb2caD/B7KTZRHif9SebmTCTTVWbsDgsLMpaRKOxkc8rP2dcxDgmRE7AaDOSFpRGoDoQf6U/z1/wPKXdpdiddhQyBe+UvIPT5eT1E6+TF5aH1us8wpsfkeKfMiiVY2n20vOa58b4xPD80ee5ZNgl+Hr5clPaTbxV8pZ7/22Zt5ERlPGz9zoX56vKeXt5e1QI/y9hiLgNYQhD+M+Gd6ioeo2aL1qRJRtgzzNwyRrY+aM7fmsxeIfAhQ+ATCnanDIv2HDT2bZpaJogUnufFSrVS54dfC+HdfA2i0GE1Z+LyFFweqsgj+fznXLYhAJVHSTarpY+GHOLm7QByKQyvqr+yh18XhBRQG5oLi8WnSWIoZpQLom/hC3VW5gcPZkucxfl3eVkBWXh4+XjYQmS5J+EyW5Cb9GTHpTO7Zm302vpdVsxGG1GnC4nXjIvlmQuYUzoGI53Hnebweot+vO2BfMj8gn3DudYxzH2Nu0FhIv+0bajXJFwhbtS2DbQhpfUiy3VW9xxSNW91aw5sobbMm9jS80WZibM5OPTH7uvrZAqCFYHU6GvYMXeFVwcdzER2ggmR09mV4Mwd80KziItMI0o7yjaTG0e5NLusvNN7TeMjRjLvuZ97rWuL17PhMgJbKna4j6+xlDDY4ce4+GxD9Np6sRb4e3hUXdmPbMSZrG/aT86Lx0J/gmAIBkxPoOH73+KrgExmxWuDWfAPkC/rZ/0oHQ6TZ3YnXZW5q2kuKuYLdVb3IkNm2s2U9JZwpWJV7KpehMr8la4BSVbaraQ6JfoUalUSBWMChvFuyXvkheeR0pACnE+cZzoPEFxZzFV+iqG+QxzV9rSgtJ4/5L3aetv46lDT1HXJ9SfZd1ljAkbQ4xPjNsgeXbCbCK0EahkKl4rec0jtqrH3IPVaUXLzxO3WN9Y3pr+Fnua9lBvqGdy9OSfDZAP1Yby6LhH2Va3jT2Ne5iTNIc3p71Jp6mTSO9IkvyT3CT2l5AckEySf5JHTNfdo+7+j51j+2cxRNyGMIQh/OdDoRLEC6D8x+BnrT+Yzqk8Ve4QP9Meha33ipmyc2fd0ufAjofPPq7aAcMmQfV3Z7epAwRJs5/TdonMheBU0IUL4pVzo/CG840GnML6Q+UrWqhn4BsFmiCQAkHDhXmv2pPgVeur3aQNhOrunRJPhWrbQBsquYrTPae5OuVqAlQBnOo+hd1lZ8XoFXxS/gll3WWMCh3FhKgJxOpikUlk+Hj5UNtXS3VvNSc6xYygTqEjJSCFaF00FruFpoEmYnxiyI/Idw/L1xhqmBE3g29qhegj2T+ZGbEzKOsuc5O2MyjrKfNonfkr/d1zeufC7rRjd9qp6a3hrpy70Hnp2FKzhVBNKFNjp/LEoSe4Ovlq5FI5TpeTXY27CNGEsChrES5cVOmraDA2cLj1MMP9hvNTdJo6RZZn5ER+aPqBjJAMJEiYEjOFZbuXeRzb2t+KxWnh69qvmZsyl9ePn62uxvvEY7AaeO/Ue9yaeSvFncVE+0Tjp/T76S1/Fg4cOFwONAoNgapAPij9gPmp81HL1WQGZeJ0OXE4HYNitur66rg542a0XloClYGszFtJaVcpPl4+XBB9AWHaMDZWbSRaF80fsv/AqNBRBKmCqOipIEwbxp/2/8l9zSNtRyjuLOaRgkdQK4SiM8k/iR5zj5u0ncHB1oMexGpD5QaWZi9FIpG4A+fP4Kqkq/BX+WO0GjHajASoAs5LrBL8E9yE96ewOWz0WHrQKXSoFWqG+Q3jNr/bfvXr+3MI14bzwuQXRKt9oJWMoIxfXa37Kdr622g2NuNEeOzF+cThq/rtTIF/C/zdxE0ikUQCy4GJQABwucvlKpFIJMuAAy6X6+BvvMYhDGEIQziLzN+LFmfzMcicK+bUzkCmEFmgANpQoRZNmCIqabKftFNObxWzaDEFIq80cpSolE1/DA6+Dl2VInc0fQ58cx8kzRACB02giKEac5vINZUpRMpC4dtini4sE7KvB4dZEM6gwU7sNb01g4bOvWReg4K5QXhOGawGvBXe/CH7DzxT+AxPHXqKm9NvZlnOMvEl67ChlCnxlnujUWiwuCz0W/tZX7LefZ3Hxz9OYWsh4yLG8UHNB5R2ldLQ18DK0Sup7a2lQl/Bt7XfsjR7KTMTZuJ0OtEoNOxu2H3ewf9zoZQpuSnjJow246C0BRAigUcLHkUr15ITmsPI4JFo5BoOtRzC5rRxrOMYyf7J7G3ay80ZN/NS0UtuUquWq5mVMIvXj7/u9gE7F5OjJ9M+0M70uOluY+JbM2/FaDMyLXaaR/yUSqZCI9eglqs52HKQO3PupLW/lXBtOMN8h1HXW8eqsat47KBQYYZrw7E77RzvOE6ifyK5YblEekf+7OsQrYtmwDaAXCLntszbWFe8jndOvsMT458gQBWARCL52SpSa38r60vWc3P6zYyNGIsMGcc7j/NM4TO8N+M9rk+9HpVcDPRb7VaC1EHYHXY6zB3E+cZRa6h1z6Z9U/sN16VcR4g2xN02/Tll5ujQ0ehG6Xj2yLO4cNFr6eVg80HuHX0vmyo3obfquTLxSi4fdjlF7UU8e/hZd4TawsyFvzoWqlpfzfri9exu3E16UDpLs5eSHpT+q879NYjSRbnn2f5RVPRUsO7EOoI1wXxU9hE2p40RASN4fPzjP0tG/x2QuFyuX3+wRJIG7AUciHHhS4HRLpfrqEQieR4Idblc1/xLVvoPIDc311VYWPjLBw5hCEP434VTm8A6AP4xwsi25DPwi4Xxy+DAa6IK5hslPNu2PQRpMyFmnJhFqz2nchQwXChMD/xoFeIfL9qyvY2iiua0w8dzxWzdGWgCBLnbuFgIFC5+Bkq+AKVaRGt1VQhjXt8YiM4fVGmzO+089sNj+Cp9PYhVvE+8IFVlZ73ENHIN89Pms6FiA4+MewSVTIXD6UBv1eOt8EYr13Kq5xR2px0JEvyUfmQEZxCti6beUE+doY72gXYitBEcbj3M2PCxmBwm9jXvo8fSQ354PjqFDqvTilwiRyKRoJVrOdh6kEp9JTen3cwbxW8gl8qxu+wcaD6rEkkJSOHG1Bup6q1CKpHyeeXnzEuZh8Pp4OVjL7uPGx02mvmp8/FX+vN17de8X/o+Pl4+3JR+E3anHYPVQJJ/Ep9XfM6R9iOMCh3F74b9jt2Nu/Hx8iHBL4EeUw+JAYk09jWikqv4pPwTDFYDv0/6PeMixtFt7kYlU1HZW8maI2vc954WOw2rw8p3jaKqev+Y+9lavZV5I+ZxsuskRe1FXBh9IeGacGzYKOsuw+Vysa1uG+HacPLC81hfvN5t3ZETksOaC9YQqA78+Y9m1yl21u0kLyyPdlM7Pl4+GG1GukxdhGhDhM1Hww4PQnlJ/CX0mHs40HKAWzJu4YuKL7g//37u/e5erku9jrtH3e32MjvcephPTn9CraGW/PB89BY9tYZaCiIK3MKK1MBUFqQtoKa3huSAZHeA/N277/b4g+GyYZdxcdzFWB1W0ULfuYSl2UspbCskPyyfaJ9oor2jSQlMoVpfzdzNcz3SOMaEjeGFC184bzrGuTBYDSzevtjDU9BX6ctHl370D8WL/SvgcDp44uAThGhDeKnoJY99U2Om8sSEJ36VwvWfhUQiOeJyuQb/hXLuMX8ncfsa0AEzADNgBXJ/JG5XAU+5XK7/GFe7IeI2hCH8H4ShBZqOgkQiZtZMPSK+Shch1KDR+WK7yyHSFBIuhB9eE3NtCdMgahTsflJYh1z5NkiVwvzWSw2nNkLd9xA/WRA/qxH2PD14DfP+Gz66+uzjOW+LcHizXlTukIkc0oiRg07tNfcyd8tcrky4mqPtR9jTtBuAK+LmMS7wWlr7jMi8uul2FpMUMAyDtY8oXTh2h52HDjzE0uylRHlHoZKrkEqkaBQaTDYT3gpvHDio6Kmg39ZPr7WXd0reweVy8dLkl2gdaCVMG8Zdu+/ysIdYnLWYD0o/wOKw8OSEJ/nr6b9isBqYGDWRnOAcynrKeO7Ic1yTcg0KmYKyrjKyQsSM3XOFz7mrPGeyMDdWbWR67HQsDovbouLT8k/53fDfcd/39wGwLGcZb554kwH7AAAyiYzluct55vAzJPglcO2Ia/mo7CP6bf3MTJhJUXsR+5v3E6wJZn7afPosfST6J/JZ+WdcFH+RO9rp9u23u695Bo+Pf5x+Wz8R3hH0Wfow2AwUtRVx6bBLkUvk9Nn6eOzgY+gtevyUftyZfSdmhxmz3UylvpJ433j6bf14e3ljcVjIDs4mLzzvb85f6c166g31SCVSNlVvQuel480Tb3L5sMuZFjcNXLgDz4f5DeN4+3E+rfiUGF0MU2On8nbJ26QHpTMqZBQXx19MoDqQZmMzdqedZbuWeXitzUyYSXFnsTAs7mskUB1IjC6Gj09/jNPlJMo7ij8V/In88Hya+prY1bCLkk7hrddt7kaChDhfkfmqN+tBIipP39SJdrlGruHVqa/Sa+nlzl13DnquGy7f8Iv5nqe6TnH1V1cP2v7a1NcYHzn+b577PwWj1ci1W65lSswU1hV7io28pF58Nesr4dP3L8avIW5/b6t0PDDP5XIZJRLJT/Mi2oDBk61DGMIQhvBbordReKZ1VYgEhPYfzVE1AfC7F0HtB1aT+EmfA1uWnz23cpuopM16U9iCyFVQuF6QvrrvoVOYh9JZIZSqBXcKgnfGA06pg6SLRbUvf7EghkHJ4lo7Votjki6CGU9BYNx5l69T6rg9dQW7jvtgsQ5nde412OxSqpt0LNp6NjrrnunT8A/wR+qw0WU6xAtFL5AamMqU2CkEqIQnVk+/lV6TlSBvLzrMtdz87c3uNqVGrmHRSKFW1Fv1RHhHUKmvHOTptaFyAxfGXMgXlV/wQekHeEm9ONl1kpNdJ3lgzAO0D7QzK2EWH5/+GJ2Xjvmp8wnRhKBVaIn3jae6txofLx+WZi9lmM8w9BY9Lxa9iEKqYH7afP588s+EaEJoNDYCwmKipb/Fg2A5XA70Zj1vTH2DAfsAXeYuQjQhmOwmjnUcY1+zMDhuH2jnucLneKTgEVYfWI3BaiBYE8y1I64V1ilOKzek3oBGoUGCRCg8HXa6zd08dvAx9/0ujb8UqUSKt5c3y/csp9/WDwiBRrWhmv1N+z3ioBakLWBT1SZ3rNMjBY9wRcIVP+vof8Zktqi9iC8qv+CWjFsA2FS9id2Nu7li+BUM9xvOjNgZ9Nn6MPmbWJy1mD5bH++efBeAsq4ylmQt4YatNxCqDeXq5KtRypSDDHI3V2/mhtQb+KT8ExZmLsRX6cuD+87mzjYaG3mr+C2ygrKI1EXiq/RlYtREjrQfweF0sLl6M2q5mlsybmF06GhK9aVu0gYwYB/gsR8e457cewY9T7Vc/auqUGq5WlRtz/w/Omf7fwq0Ci0XxlyIUqYctC81MBWdl+7fsKrz4+8lbs6/sS8IMP2N/UMYwhCG8M/DNgDf/BekzT5L2kB4tJn0gkzV7RekbPxdIvHg3PZo6SYIz4LGo6J6V/4NTFpxlrRJpIL8tZ2E3nqYthoOvSXarVIvYfhraISIUULFamwX5O4MOsvhPAHwZyCVSDH2xvHd6XLumZaEr0TNyU4D6/aWexy3/VQbw4O9KW7SMyfnAu7KVjM6PNNN2g5Wd/FdeQcDVgdpET60SLZ5zJYN2Aco6SxhTNgY+qx99Jh7sLs8vzgBd5sMhK/amLAx7n0fln1Isn8yVyRcQUFEAZ2mTob7Duejso+4Kukq7sm9h+LOYtKD0jFajLT2t/L0hKf5vvl7ALbVbqPGUENqQCoToyYiQYJKrmLA5lkVW5azDKVMyabqTWyv286k6ElkBWeR7J/MH3b9weNYp8tJfV+9W1Eb6xOLyWriu4bv+GPuH1lfst6tJI30jmRi1ESePPykxzU212wm3jeeIHUQsp/UILwV3oMyPD8s+5AnJzxJRU8FeoueJw8/SXZoNrE+sed7iwFB3sK14QSrgynpLHGLPgxWA59WfMojBY9woOUAuWG5+Kv8efzQ4x7n54Xl8e6pd7E6rTT0NfD8ked5KP+hQfdRSBXYXXYS/RLdFbSfoqitiHpDPQ4cBKuD+aLyCwLUAbx/WsyHmh1mnil8hjUXrHFbvJyLCr0QQUyKmuRuOwMsH7WcKO9fniuL1kWzKHMRLx0724KcGjuVBL9/39yYzWHzSL6QSCTMHC6sU859njqFjj9k/4EDzQeQSCQk+Sf9KoXxvxJ/L3E7BCwAvjzPvt8D+86zfQhDGMIQfjsMdIHTIQjUuYjIFsa6dfvFY7sZdj8BUx76yVxbvKimhWXA5z8q2iSSs3miciXoG4Wnm0wpUhOmPwqH3vQkivmLRTh93T7Iu1XYkRjbIeUysA3+8juD2k4jNR0DLJuSSEyQlo4+C0mh3owZFsiBqi4CtF48dNkITFYndqeLvPhAek0O/F3ZGAdU4A1F9T3c+l4hBrMgYqnhOkZkDQ75bh9oJ1gdTLupnZLOEq5NudYj8B3EnNPXtV8DMCFyAvub97v3qeVq0VIzdWN1WDFYDdy2/TZcuLgu9TpsThv7m/bz2vHXAOGr9viEx6nUV7Kzfqf7Or3WXsI0YSweuZi3S972aK3dlnkbdYY6vq79mlBNKHdk38FfT/+VnJAcTA4TodpQWvs9TXnPVD9CNaEopArqjHWEakJp7m/2sAtpMjZxqPUQGoVmUAvV5rRxsvMkd+XcRbupHYVUwdaarecd4rc5bZR2l/LmiTeJ94nnyqQrMVh+npyfQaxPLMtylrH8u+Xkh+ezZOQSZBIZqYGpNPU1sbV2K9mh2YwKHcWirEWsK16H3Wkn3ieeyTGTefzgWTLncDkI04YRpg3zeD2uTLqSfY37uGf0Pfgp/TDajCikCg9V6MTIiRR1FNFibGF85HiyQ7L5S+lfBq23sLWQ/PD8QdvzQvMI1Yby0NiHONV1io6BDuJ940kNTP1VOaJyqZy5KXNJD06nWl9NhHcE6UHp+J7PSudncEaN22xsJkgdxDDfYZjtZregQm/RE6oJ/cV2ZkNfA1/XfM2uhl3kh+czPXY6OqWO1v5WAlQB3JB2A83GZualzMPutOOv8ueP3/3RnXUaog7hjWlv/FvFCn8vcXsE2C6RSL4FPgRcwFSJRHInMAuhNB3CEIYwhH8dpApB2gJ/8oszKhdO/HXw8TaTUH46bOLfUTdCywlhwBucImbT/OJgymowd8OWe8SxIEx9824T4oR2z7xKDr8FBUsFcfPygYJlIj4r6WJBDn8GnUYLExMD6bc6WfTBUYwWQb6uGBnBhSkhzBoZyebiZr451YZMImFWTiRRfmomJAbT0GMiIUTHvspON2kDON1m5Gr/SXxbt9XjXmPCxvB+6ftcOuxSjFYj3zd/z9rJa9lQsYEmYxOXxV9Gub6cblM3sxNno5Vr3XmRANenXk9VTxWZwZkcbj3sJmhToqeQGphKW38bd+feTXlPOT3mHoI1wVjsFq5NuZZo72iOtB8hxT+FgogCDBYD6YHpPDfpOQCem/QcO+p20D7QzueVnwNQa6hlzZE1LM1eyg8tPxCuCefO7Du5f9/9blf9nJAcZMh4ZuIznOo6xYtFL2J32nl1yqvsKtk16PUu6y4jLyyPLTVb3NuUMiUR2ghOdJ7gk4qzIe4P5j+Ir5cvvkpfei1n7V2mxkzlYIswTKgx1HCx4mLCtX+bINT2iudS21vLXaPuQiVToZarCdYEU9lTycaqjcikMqK8o6jvqyfJP4nXprxGhb4CpUzJ+uL17vnBMzjVdYp7Rt1DdW81TcYmRoeNxkvqxfjI8TQbm1lzZA0qmYr7x9zPx6c/pqy7jCB1EDMTZtJobOTTik955+Q7rJ++njBt2CBbkkjvSEx2EwszFvLuqXexOCwM9xvOH/P+iFahRavQntdM99fAR+lDQUQBBREF/9D5uxt2c8+ee7A77eSH5zMpahK7G3aTF5bHuuJ1mB1mAlQBPDfpOXLDzj8i1mfp49EfHnX/cVLcWcyO+h0sSFvAgZYD7KjfweqC1cyIm+Em8I/+8KhHQH27qZ2dDTv/9xA3l8v1nUQimQmsBd7+cfOTQC0wc8gKZAhDGMK/FD11wnYj8/fQXASjbxF2IA6rUHiGpEH9fs9z/ONg5uvQXQM4oegvooLWUy+ySn0ixdxcUCLsevwsaQM4+i5c/ZezNiADZx3hcdpFW1Xl96Ow4XMRo9VyDGLHnnf5zT0DdPRZaOwx8/HhBjdpA9h4rJlHrkijor2Pr0+KqpHd5eKTwkbunJLICzvKmZMTRUVbH3qTp8eWw+nidG0w9+T8F2+feh27086C9AVkBWUxLW4asbpYAlWB7G3cS21vLbdn3E6bqY16Qz0auYYb02+kuKOYSSmTsDiFlUhBRAE9ph6yQ7Np7GskVhfL1JipFEQWMD5iPN5e3nh7eQOQEZxBr7mX4s5ibE4bmyo3cXnC5VTqK6nqrSJcG05GUAZ37LwDrUKL3qJHLpXz0NiHePSHRz2ei9PlxGK3EOcTx6fln2K0GVkzaQ2l3aUopArq++p5qvApfjfsd5R0lbgrS6e6TjE2fOwgm5Wx4WPx9vKmtb+Vo+1HidXFclP6TfRZ+zxUsgAvFb3ErIRZ3JJxC8faj1FnqCM/PB+ny8m3dd+6j3O5XH6DkKoAACAASURBVARpgs77HoNoP79+/HW3ifCaI2uQIOHdi97lh5Yf2N24m3kp8whUB7KzYScmuwmNXENDXwN2p51gdTB3Zt/Jyu9XuslbRlAGDcYG9jXv49K4S5kQNYEB2wADtgGqe6t58tDZdvCJzhO8fOHLWBwWitqL6Lf3U9VbxTUjrkGChPdPvc+cpDkUtRdhdojqcIR3BE6XkxV7VxCti+b61OsJVAUyJWYKPkofSrtKkUqkxOhi3P5w/1No6mviwX0PYnfakUlkjA4bzVOHn2Jx1mJeOf6Km9R3m7tZsXcFH176IaGawea7FfoKj4oyCJPo5v5mwrXhqOQqHvj+AZL8k0j0T8TutHO6+/Sg61T2VP5rnuivxN/t4+ZyuTYDmyUSSQIQAnS5XK7Bz2wIQxjCEH5rmHuheqcQAETlgneYaE067CLsfewSaCs+a7wbN0EEwZu6wNgCNXuFlUd3raiKOW0w4nfQfEQQMePgyCcMzfDdk6I1WrZZVNUA0meLZISCO2DfC+KenafFjJu+ThDGn6Cl10yrwUKv2UZVx3nin9QK/ruwwf344vQwUsJ90HjJGJcQRJivisr2Pi7LCCPKT43T5SJQq6S6q5/UMB3HGnU8NvodksK8B1VGskKyyArJAqDP2ofeqqdGX0N2WDYSiYRJUZOQI+fC6AvxVnhjd9pRyYX9yOHWw6wet5rp8dPP+7YopAqCNEHkhOSwtXYrG6s3kh2ajd6iZ0HaAir0FZzuPs3S7KWsPbrWTUYClAEEq4PdwoUz0Cg0mBwm+mx9bKndQrxvPG+ceMPjmO8av+PSYZdS0yuqRk6ctPe3MzNhJl9WiWmeq5KuYmTISFwuF0tHLsWBg5reGhqNjWQEZZAamMqprlPua+oterxkXjxX+BwjAkYwNWYqMomMV46/4nHvM/5jrf2tNBub0XnpiPaORqUQg/pdpi6PAf9Ev0SS/JPoNHVyXep1pAWlsaFigzuXdGn2Ul459op7RlEulbO6YDVPT3yaZmMzUbookvxFzFaQOoiy7jKOtR2jvKecGJ8Yj3zZM9jXvI+rEq9i+XfLeXXKq5R1l1HcWQzAxKiJwpNt0rPU99Xjp/QjxjuGG7+9ERDtxLeKRfxURlAGTxx6wk1CLxt2GXfm3EmY9n9Oi9hr7XWLMpL9kzneLmxF7C67R74piPGAEx0nMFqNJPknkRYkjLvLu8s51n7sZ++xs2EnY8LG8G3dt9QZ6jDbzUR6RzIrYRbHOjzPmxY37bd8en83/uHkBJfLVQn8e2nnEIYwhP+/4BslqmrlX0PVTshfJCpuwydDYCLU/yBam1KpEAy0lwnvNm2QqJjl3gSf3gS/ewG+f14oSS96ElpLhDo0ZIRnS1QiAZVOVNp2PiLOc1ghcQYMu0Ac214q5unkKvDSQk8N6BvAJ0q0Y89Bp9GCVCLhdGsfo2L8OFLvaVRrMNlIj/ClpMnArOxIOo0Wnt8mRAsaLxmvXZuDWiFnc0krw4K0eCsVVHYY6TPZOFjTzYgwH7oNErrUKkL+hmeuzktHXngeWSFZdJm6CFAG4HA5ONBygM6BTpw4ef/U+wSoAkj2T2Z20uyfvVavpZd6Qz02hw2Hy4HOS8fCzIUEqgO5Of1mHj34qDtbNckviTUXrKHZ2EyMLoa1R9by++Tf8/yR591kLsk/Ca1C6/ZjC1GHnFe5GK4Np2OgAxCxWE3GJvY37+fqpKtZc8EafBQ+9Fh6ONhykAH7AN81fMeK0StQSBUcaTuCVCJlTsIcrk6+mocPPIzD5SA7JNtN5Eq7SzE7zMxLmcflwy9nS/UWdF46FmUtIkgVxPeN31PcWcxnFZ/RZepiYeZCEvwSSPRPxF/lT7yPUNwuHrmYip4K2vrbMNqMFLYWYnVY3QbDvkpfesw9OF1Orkm5Bm8vb3rMPWyr20ZOcA7h3uGMixyHVqGl1djK/ub9VOmr+LL6S7wV3m5rlp9CJVNR3VvNyxe+zA8tP7hJG8Cexj3cmnErerOe4o5iyvXl3JpxKyMCRngcF6AK4HDbYTdpA/iq+itGh41mduLPfyZ+C3SZuihsK2R/034SAxK5Y+QdvHLsFQxWAxnBIhXhfFmk/kp/jrQd4S+lf0EtV/PC5BcYFTqK9SXr6bH0MDFqInsaz6Z75Ibk4qv05aqkq8AFx9qPUdlTyV2772KY7zAeH/84CzMX8u7Jd5FJZNyWddt5jaD/J/GLxE0ikdzw91zQ5XK9948vZwhDGMIQ/gY0AXDR47DjEVH5Uuqg4aBIKwgJhY5SYRFyLuInwch50NcqyJVcIaw74idCjV14uMmVYnZu6sPwzUroqhLpCNMfhX3nhMvrGwRxjCsQNiOd5RCSCtMeAYkMwtKh8SB8+4AgeT/xcVMpZMQHaXnvQB0rLkrm8S2l1HYNoJRLWTAujkO1PUxNDWFXWTvDgrV8XnR2tmbA6uC5beXEBWoYEe7DBz/UYzDbmF8Qx5YTLTTrTUxNDeXKUVHMe/MH3pqfS25cwN98OZUypUcgeX54Pqe6TlFnqGNh5kK0Ci2R3pGkBqae9/zT3ad54PsHKOspI1AdyKqxq/hr2V852nGUi2MvJjEg0U3aAMr15bx/6n1uz7ydD8s+pKK3graBNp6c8CTtA+0EqALotfS626cyiYyl2Uup1leT6JdIhV4of+VSObdn3e42mG0yNvFF5RcszV7KtrptZARnsOy7Ze45tUBVINeMuIZT3ac40HKA5IBk1hevx+6yk+yfzIq8Fexp2MPo8NGsPbLWvd6L4i7ixaMvEqWL4qULX6LP2keAOoDFOxbTZe4iLyyPlXkrOdl5kvdPvc/9+fezu2E3VyZdyYq8FWyt2cpX1V/hJfViUvQkHv3hUaxOK4GqQO4YeQcvHH0BrVyLy+liYeZC3il5x53YsDBjIeX6ci6IvgCL3UKVvoq7d9/tzoSdnzafvU172VCxgetTr2d/8363UbBariY1MJU9TXtI9k/mUOuhQe9dY18jHQMdaBVaqvRVrNy7kgfGPOBB3OYmz+W7hu8Gnft94/e/SNy6TF10DHTgq/J1zwM29DVQqa9ELVMTqg392dQFm9PGe6fe4+2St93bkvySeG7Sc3xQ+gFZwVl8WfUlO+t3cmPajbx36j2cLicqmYqbMm5yVwtNdhMPH3iYddPXcbj1MP22fm7LvI2RwSM50XmCrKAsEXZ/5HkajY34ePmwLGeZ2xy5ureaN068wVMTnmJ24mwkSAjXhv8qQca/Er9owCuRSH5qAXLmBMl5tuFyuX7q7/Zvw5AB7xCG8H8MZgM0FopQeVyiQrbvJWg7IWbcZjwBH8/zPGfaw6Kilnk1nN4MoemiuuZyCOGCSS/aqwHxwmZk7FLwixbbu2ugqRDafvRXu/Q54QO35V5h/HsGujCYuAIaD4lK3J6n4YL/gowrPZbSZjBxrL6HAauTll4zUQFqmvVm/DUKXv+umkszw3n7+xquHRNLmI+SRzZ7CiKUcinPX53FJ4VN7Drdzr0zklmzrRyH8+zv8StzorgqN4IWvZWpqcF4q35dUPevhcPpoNZQi9Fq5Ej7EUx2Ew6ngy5TF8c6jlHdWw1AsDqYGXEz+KD0A4/zh/sNZ+XolSzasYhL4i+htb+VQ62H3FYhj40TfmsD9gHifOIw2UxUG6oJ0YTQ0NfAgG0AhUzBZ+WfsTx3OQargY6BDkI0IfTZ+vCWe3Oq+xSflH/icd95KfNQyVXoFDpeLHrRY9+02GlcFn8ZarmaXQ27KO0uZVzkOI61n/WQm504m0OthxgdOprM4Exh3mvt4+VjL6Pz0nHNiGvw8/Lj04pPeTD/QZIDktnfvJ9F2xexNHvpIDf+KF0UuaG5fFH5BWsvWMvKvSvd82YgyObtmbejlCmp76tnR/2OQWKCM9ddPmo5kd6RlPWUIZfI0Sg0bCjfwLWp1/JNzTdE6CL4ovILj3Nvy7yNJmMTVfoqSrvF52xu8lxyQnPY27iXvPA8CiIK+OT0J7x+4nWPc1eOXsnclLnUGerosfQQpgkjUieiwCp7Kqnrq+PZwmdp7GvEX+nPw+MeJkIbwZbqLdixc7LzJMP9hnPpsEvJDjmblWqwGKgx1GB32Lnl21sG2dcszlpMbmguO+p34K/yx+ww46f0I0wTRvtAO2HaMJ449AQdpg6P8z697FOOtB+hfUCoq2N9YonzjSPBN4FHDj5CQ9/Z8QSZRMbtWbe7UyiUMiVfzvryF8UovxV+KwPecylxFEJNuhn4GGG6GwrMAy7+8d8hDGEIQ/jXoK0ENi4S1bPoMYALgpMhYTJE5MCJj4UJb8mnQmSQNEMoQkPToKMMYscJK5G9z4qZtuSLQeUP4dmiUma3iH1n4BcL0XnivmGZwh6ks8KTtIFYT1+zqPad+G9BFtX+g5avlMuI8lNT2taPRilj26k2IvzU9JlsJIV6I5WIytq6vdXcOyN50PmTU0II9lZyqEaIJMw2hwdpA/jiWBNRAWq0XnI+KWzkguQQ4oO9/+mXHsTQ/daarajkKpqNYqC72diMFSuToiexoXKD+9hYn1jyw/OpNdSyv3m/exbpiuFX8OeTf+aS+EuI9YllU9UmQGSymuwm1hWvY1bCLF49/ipvTX+LGF0MLomLpw8/TaXeczqnqK2IzTWbuTXjVjQKDXqLntTAVA8F6Rk09TWRE5pDn7Vv0L79zfsJVgfz8emPeXDMgwzzHcazR571sE1J8ksiKyiL0z2nefjAw7hwEaoJ5a5Rd9E50IkUKVG6KELUIUiQIJVI8VeJz8C51zmDxr5GZg6fCUDrQKsHaQPoMnfhr/bn5aKXuTXzVmpKagZdw2w3E6oJJdI7kijvKMwOM08ffhq9Rc+ynGW8d/I96vrqWBy2mGG+w9ykOickBy+pF/G+8XxV/ZX7ekHqIBL9ElHKlASpg1DKlEyImsC3dd+6z80IymBC5AS+qPyCxw4+hs1pw1fpy5pJawhSB/FZxWfsqN9BS38LAD2WHh7a9xDLc5dT2Vvp9kcrbCvkUMsh1k1fR6+1lxZjCx+Wfcj+5v3cnnm7u3p4Lpw4eeXYK9yaeSu3b7/drfy0O+08MOYBnC7nINKWGpBK60Arp3tOs6FCfD4Pth4kUhvJY+Mf8yBtIGxXzrVSyQjKOG8r+t+JXyRuLpfLbQ4kkUheAD52uVwrzjnkNLBHIpE8DfwRYQsyhCEMYQi/PbqqBUlS+Ynw+O2rzu7zDhXh7v0dgpTJFMKst/hT6K4W1bmJf4QvbjmbPVq7V1TRnE7Rhv0p4ieKCK2wjB/Vo1qhJJVIPPNLpXKxHUTrtekojDwb29xvsVPZ1ofV6cTphMwIHccae5mSEoLF5iQ2SENqhA6pRMqYuAAO1nazs6ydRZOG8+f9tZhsDnJi/MiL8+eV3VUkh/lwtL4HuUw6aMnBOiWdRguvHq5i0QXDOVjb/ZsRt2NtxzDZTbx+/HWuGXENTxx8gh5LD0qZkrtH3c2IgBFU6Cu4M+dO9jft594995IemM6DYx7k7ZNvc2n8paT4p/D8kee5MunK83qm1fTW0GXuQm/R822dCL0fqx7LgrQF3L/vfvdxcomcYE0wPZYeni58GqlEyuqxq9nfsp/JMZM53HbY47ppQWmEacIGGe6CGHivM9ThdDl57shzPDr+UQ/RxKiQUdT31ROoDuTDsg8B0Y68bNhlmOwmgjRBtPa38mHphyxIX0CgSmSZxvnEcfnwy8/rxh+qCSU3NJf78u4j0jsSCRIP+w+VTEWVvopaQy1FbUWEa8PdZOgM1HI1y3OXE6mLpN5QT62hFpPdxJKRS7A4LGQEZzAzcSZ7G/cyMmQkMxNmEucTBy6Qy+TUGepYMnIJZd1lHGo5RGpgKld+eSUOl4OZCTNxuVxsrtnMrIRZzEuZR7QumhEBI2gbaGP1gdXu9fZaernv+/tYlb8KjUIzaJ1ahRaXy+Vh3gvCWqVKX8V939/H7MTZbsVnYVshk6KF3ccZBKmDMNvNdJg6GLAN8OykZ/mo7CPsTjuXxF8iKpOGelaPXU2jsRGZREaTsYnc0FxMdhMbKzd63LupvwkXLvyUfh7G1SAirgD8lH4sz13+i1ms/9P4e8UJU4CXf2bft8Dt/9xyhjCEIQzhb+AMuRrxOzjyrnicNQ8UatH2VOmEcjT5UtDXg5dOkDaJVHiulX7pSbhAbCv4AzgGIOMqKP6xxRYyQsyvbVpy9tjhFwoRxKgFwpbkDPIWiuucgcxLiCEAw4CVBv0Ah+t6eH5bOf1WB3dNTaK8zcDmYmGk6qtW8Oq1OUhwsXxGEpuON7P9VDs9wWZeuy4Hk82BFNh4vJm9FR08cGkqVR1GuowWUsJ0lLWerSLdPD4em8OJ1eHE4XLx5bFm5o7+553e2/vb6TB38JfSvzAuchzvnnzXHZ9lcVh46vBTPDPxGfY27eWz8s+oNdQCcLjtMNW91dyZcycvFb1EZlAmy3OX89fTfxUk4icYFzHOPbh/RjEKMDlmMmsUa/io9CMC1AFkBWfx3qmzI9VOl5MGYwMBygDCtGEsSFvAR2UfIZVIuT71etKD0inrLGNk6Eimxkxle/128dorfZkWO41nCp8BwGgzUtpVyn1592F2mJFJZOys38mHZR+yMHMhuaG5jAkfIwx/jc2sO7GOPlsfaYFpzE6YzZ8O/Ikp0VOYGjuVEYEjWJazjLLuMm5Jv4X1JcKbTSPXcGfOnWgUGk50nODzys+5LvU63j8lkgwkSLgl4xb6rH0szFyIFCn35d3Hir0r3CHv16RcQ4JfAjW9Neyu301qUKp79u3jso/pMp+1rlkycglfVn1JtHc093x3D3eNuosXjr7grvJNjZnKI+MeobW/lScmPEFdbx1yqZy3S95mVsIsfLx8+LT8U+YkzWFc5DiOdxwf5DHXPtCO2WHG6rCiVWjdMWIAzf3N7hiwcxHnE8f2+u34Kn2RIWPJyCU4nA767f1IJVJuSL2Bgy0HGe43nGmx01i5dyVXJ1/NM4efYe3ktcglcpQKJUXtRUyJmUKjsRGDzcDHZR9jdpgZFzGOloEWlDIl3gpveq29Hve3O+2sLljN8t3L3W3ZhRkLGR85noygDGJ9Yt0t4P8k/L3EzQLkAtvPs280InR+CEMYwhB+O3RUiDaksV2kG0xdLSpf/vGiTfr1Suht+HHG7UmIv0AIFxoOiTbn1FVQ/q0gdLLz/MqLnwT9nYL4DZ8sbEYcdmHn8clPtFlVOyFqNNQfgFlviJgtvxg48BK0/2grIZFA9nUAVHcYMJodNPSYeGJrGXNyogj3VREbqOFEk55gbyVXZEegUcjoM9vo6bcilUoI91GzfHoiUX4aNpe08OHBepwuGBntxx2TE/m6uJVXr83GaLYxIzWUll4zDT0m1F4y/DUKKtqN+KjleMmkJIT+NtW2M+kCtYZapsdN90goAEGcWvtbGRM2ZtA8VZe5i9b+VuYkzsHmtBGhjWBWwiyUMiV3jbqLN46LjNKRwSNJDUp1z4NNiJjAU4eeYkbcDNKD0pkWO42JkRMp6ypjzdE1gxIV4n3iqTXUEu8bT354PrlhuSilSmp6a6gz1JERkkFhSyHzUuYxLW4aZruZekM9Lx972d3KjfKOosPUwcmuk8T5xnG65zSbqkU7N1oXTbOx2T3/5OPlw+KRi3nuyHOc7DrJ2IixNPY18mbxm1gcFmQSGXannbTANPLC8pgRP8M9j5fgl0BhWyHHOo5htpspai/ijpF3AKIt22XpYmPVRhr6GtApdNydezcvTHqBwo5CFFIFexr38GHZhzyU/xCNxkYuHnYxH5V9REFEgQdpA/is4jNuz7ydtUfXMjV2Kp+Uf+LRmt1ev53kgGReOfYKBeEFzEycidVh5eFxD7O+eD1lPWVMjZmKxW7B5XLx/9h77/Co6rz9/3WmZEoyk8lMeu+9QgKE3hRUFFEUFXUVxV7WjthF17Wtiqtix17AuoBYkN4hgZBASEJ6QnqfXs7vjyMDY3jcx+fZ7/Vzn819XVw6OZ/zOWcmh2tu3u/3fd9h/sM90kxqE1EBUTy771kWZS/i08pPsbgsqOVqloxZglFlZFbcLB+blCxTFm3mNqbFTKNpqMnb4g7RhHB19tV0WDpIM6ZR3lWOv9KfRdmLaBpswuq2YtQYWZixkCd2P8GcxDl8dvQziiOLfWYJt7duJ0gdhFFl5IKUC3i34l3vsSj/KOL0cYRqQ/n83M9pGWrBpDaRZEhCq/wNSfYfAL+XuH0OPCoIghtYxckZt4uBR4C3/7W3N4IRjOA/Fg4zVHwNPz0s+bdlzweNUap09f0ywaE2wOS7JRWntVeaU2vYKalLQSJ0raUw6iopYD51FpR/eTI0PusCyUKk+uSXCZPvhoOfwpT7pXm4U3FCTea0SHFX4TlSZS/vUuneZAooWgwxY6k8PoDF7qKp10JTr5XbZ6Tw7cFWajok/7bJqcE8fG4GD3xdzoDVRWSgmsWTE3lm/VF0agV3n5nKsS4zH+5q9F7+YHMfC8fGkhsTyJNrK8mPMRCiU/HW1lpumJLIDxXtdA7ZuGZiAn8qjmd3bTfXT06kfcBGmP6fh4H/FoJUQWxu2ky8Ph6z04xRbfRRjAKEaEOo7atFLsiZEDWB3OBcHB4HKrmK/OB81tav5eeDPxOsDmZG3AwOdBygrr+OxbmLSTOk0WppZfn+5QSqArkw5UICVAFolVp+bvwZAYE+ex+dlk7ePvQ2j054lPKucqwuq7eisq52Hfs69vF62eskGZK4Jf8WPqv8DEEQGBcxDrfHTb+z3+vLtfbYWi5JvwS1XI3ZaSZOH8cNuTfQa+v1ChksTgsmtYluWzc2l81nJmzAMcBXNV8xI3YG39d/T5e1i/yQfCZGT+RAxwHeP/w+Z8Sdgd1lx6gxkm5MJ92YDoDdZWfQPsio0FGoFWqiA6J5t+Jd+ux9vD7zdd4rec87fzXoHGTZrmXcP+Z+3ih7w+czH3IMcUHKBfTb+zkv6Tw6zB3DfndWl5U4XRx99j4iAyL5ru67YWucHiepQamkm9JZsnUJHtGDUqbkvqL7+EftP1hfvx69nx6P6CExMJGlY5by9N6ncYtutAoti3Mle5EXpr5Au6WdP4/6MzJBhs5Px+O7HqfD0sGSoiXkh+azvWU7BaEFFEcWU9VbhUf0+ChIO62dbGnawhnxZ7CyYiWA93nb0LiBR4sf9cZ/ZQdn023tZtXRVT5Raiew+/huHi5+GJvLxg25N3Cg4wA5ITnMSZzjjcdKCUo57bl/VPxe4nYXoAOeQkpMOAERSbRw17/ovkYwghH8p6NxF3xz08nXVeulmKu+hpM/s/VBy37JVNfWB/pI3xYmSK1Stw1SzoDdK6QKXMdhSbyQPgdW/cl3fe1WmP4QDB6H6LESGTyBvMsgLFdqo3Ydlchixdcw4yFJFBEQIl1yyE5Dj4UfKo6TGx1EjFHDzmM9XtIGsKWqi7xoA3anVOlp7bfx5pZa5hVE8fGeRpp7rfRZfZsY5+VFsnJHPRWtUk7m4eMDpIfrmJ0dzvM/VvO3i/No6rWSEaajK8DBxGQTz35fxZlZYVw3Oel/9Gs4gShdFKNDRpNmTOP5/c+zKHsRrxx4BavL6m1Hmp1mzE4zfx71Zw51HeLvB6TJGgGBJyY8QbulnareKmYXzGbZrmXevcu7yykMKyRUG8p5yechF+Rkm7JpN7ejlCmp7qmmtLOUcE04btHNraNu5Zm9z1DVW+Xd//4x93Nl9pXID8vps/exMGMhYyLGkBiYyPKS5QT6BXLThpu8Lb4AZQBXZ1/NKwdf4fYCqW2plqtZVbXKqySN1cVyYcqFXJtzLe8ffn/Y4DtAVW8VU6KnABATEEOyIZnn9p0UuKypXcNL017C7DYTF3gylH5v217u2HyH97VGoeG63Ov4ufFnXB6Xt9V8Ah7Rg8Xpm7c6M3Ym5d3l3lQHpUzJC1NfwE/mh8Nz8tmZlzyPVVWrmBw1GaPKyN2Fd2N2mtnastVr/6GSq5gZO5MVZSvwiB7CtGFcnnk5h7oOkRiYyMy4mXxf9z3dtm5CtaGcEXcGNreNIecQbo+bb2q+YVH2IjyCh/X169nesp1YfSxzk+ayMGMha2vXYnVZCVIHcVfhXQT4BbB061IOdh7ksozL+DUquitIMJzURk6JnsKAY4D5M+aTH3rSZidEG4JSpiQ8IPy02adJhiQS9AnEBcYx5Bji+rzrTztb+e+E3xt5ZQWuEARhGTAWiACOA7tFUaz6f3B/IxjBCP5T0fQr7yn/YMlf7dfoqZMqaEf+IRG408EQL8VSzXwcDn4MgTGQNQ/6W33XTV0CnVVS+zU4DabcC731UL8FEqdLFbeO8l+yUlMgcrSUzvDDI3DBScuExh4zP1S0cc3EBMqb+4k3+vPyz8PvvaHbQqheRVOPNLfU2m/DGCANRpc19zExJcRnfbzJn28O+N5zZdsgZ+dEYPT3o7bLzN9/ruHiwmjOzY3kYHMfudGBqJVy2vqsDNhdqOQyYoxaZLL/nheV0+OksruSTksnBzoPsLpqNQvSFxCmCWPFzBX02HoIUAbw1qG3eK/iPRZnLyY+MJ7n9z/v3UNE5Om9T7N82nIEURimoARpIP3l6S+zp20PYyLG8MiOR+iydgEwI3YG3dZuUgwpIEgE5QRpO7H/e4ffY9n4Zbww7QU8ogc/ufQ5qmQq5iZLStZT57KGnEP02fvweDw8vutxzo4/m1Fho7ykDaBxsJHqvmqqe6tZnLMYjWJ41FNeSB7H+o5xWfplksHuryK33KKbDY0bpBm77krSTenYXDbePPSmzzqry0qvrZclhUuwuC0kG5J9VLQR/hHE6mORCTJvWzfDmMHLB062Bp0eJ68deI3npz7P6qrVHDcf56yEs6jpreGHxh94dvKzPL7zcXrtvQgIXJByASa1iTRjGhubkrv8FwAAIABJREFUNjI+crx378szL+elkpdw/VKdFhB4YOwD1PbXcqDjAGHaMFYcXIHFZSFME8aj4x/F4XbwyZFP2NIiGdyWd5VT01vDkxOfZFbcLF49+Co35N3AyoqVjAod5RWQ6Px0wz7X0WGjOdp9FJkg45yEc5geO51Y/elnNQ1qA0vHLOWnxp/ICc7xklGdUsfV2VfTb+/nkyOfEKoNJTs4+7St3n8n/I9o5y8kbYSojWAEI/h/g/4WUAVIytCIPMm/zeOSZtYOfuy7Nn4iHPhI+v+q9VL7s+KkLQWZ8yRxQn8LHPpC8lY79BmUrJRUpieEDSlnQP12SWkK0LQLVl8Fc16UxAcDx6HqOyj/4uTeuQt+mZE7LqlZdWHYnW5cbpFpaSHYnB5CAtWs2HKM/BiDT8UNIM6k5fuKk3Naeo0Cm1Nqz2ZHG4g2qLn7zFQsDjfbarqIN52cvbl6fBz5sUE4XB4Sgv3ptTiINmiYlRXG5/uaGRNvJFyvIT08kHtWHcSo9eOWT0pRK2XcfWYaFxfGoNcMd54/AVEUEQSBss4y/lHzD0aHj2ZlxUpyQ3LRKDQsP7Acu9vOpemXYnFayDBlcGn6paypW4NKMVxFOeAYoNXcysKMhcPsMQQErsu9DoWgYGbMTN449IaXtAHIBBl2t52bN9yMW3QzLmIc1+Zc6zVaBWi3tKNX6YdVU1QKFSq56rQ2ICdEABqFBqPayM7jO4etqeyp5KKUi6gfqKeiu4IrMq/wqhmjddHcVnAblT2VKGQKApQBXk+0U+HyuHC5XZR0lLCnbQ8Zxoxh1TOj2khOcA6vlr1K61ArsxNmUxBaQHlXObMTZtM00ERZZxnPT3mevW170Sg0p1U71g3UMeQcYnrMdBIDE73ZqDNiZvDawde8ghIRkS+qv+DZyc9S2VNJelA6qYZUFDIFYdowanprvKTtxPrNzZux1FnY37EfvZ+em/NvZlPzJmbFz+LNQ2/ir/T3WsA0DkotfpvbRo+th7fK32JB2gIvoTzRMgYo6yxjXvI8vjn2DR7RQ4I+gYvTLuZw92GKIoqICojink338PD4h3GLbrY0b0FEpDiimBRDCjqVjsLwQgYdg2QaM7kiQ6r+9th6eK/8PeamzGVFmfSPjOKIYp6a9BQmjWnYZ/fvgt9F3ARB+KfSJFEUG//ZmhGMYAQj+E10VELUaLjwHSkrFAFMSVC7CSbeCXtel6KnCi6XMkJP+KrVb5WI2fmvSXuYkiQLEXWgpA6deAd8f79k2QFSlW7e67D5GckHbvPTvvdxYu+mPdLxU0kbSJ5tscUSgfOXvgiOtQ8waHcR5K9iX0MvoTo1KWE6siIDqWwboLxFanOelR1OfowBu0u6F4VM4MYpSby3o54/FccRY1Bjc4l8sqeJ9gEb5+ZFEBGoZnJKMBOSg6loHeD2T6VZreggDY+em8W17+/j4sIYsiL1DNpdbDjQzuJJiVw3OZGDzX34+8kxO9w8sfYIaeE6Jv2qogcSUdnUtIkdrTuYnzIfpVyJ1k9L81AzIiLTY6bzQskL3vUvlbzEdbnXsapqFRVdFcxLkUQHCpnC54s/NSiViu4KDH4GisKLuGP0HTjcDnptvQQoA9jUtInXy17nsvTLKOss854nF+SkBqV6BQEAu47vIsI/gmhdNM2DkmXHOQnnEKrxzWc9gdKOUualzOOZvc94fyYgkGHMoG6gji0tWyjvKmdJ0RK+qPb9HY8NH0uMPoZIXSQ9th4i/SN5bvJztJpbCVAGIBNl1PbX8nPjz5yXdB7nJ5/vVcWCRDonR0+m39GPHDlh2jCO9Bxhftp8b0IESAbBD21/yFuNfO3ga1yWfhnX5FzD3Zvv9q7TKXU8PflpXi59mZlxM33uNUgVxG2jbuPlkpdpNbcSp4vjT1l/YlH2Iuxuu48w4ATq+uuICoji+/rv2Xl8J7cV3Ma6unU+XmYnYHfbvakBA44BmoaamBQ1yed9bG/dzh2j7+D5fScrrnqVHqvLSoBfgNcqZNA5SIAygCHnEJubN5NlyuK+ovuIDohGrVDz9qG3aR5q5ryk8+i39zMjbgalHaUY1UYaBhpYX7+ed8rfYemYpWiVWmJ0MQT4BfBO+TsY1UZ+bvrZe/2SjhJuzLuRrS1bqeiuoLq3+j+HuAH18CsN8HD8YZITRjCCEfybQqkBaz9Ye0DhJ8VPKVQQmQfa4JM+bbpoWHeH77lNeyH3Mjj+qVS1c9skVarLLp13aih1xrnw9U2QPFNqfSq1kvDgVFh7YN9bMM+3teWFrV+avdNF0Ge2M+jwYNAq2V3bg1al4MWfqqjvtvC3i/NYPCkRu9ONWinnyPFBNhxp54m52bQN2ogJ0uDvJ+euM1NRKeR0mx0s+eqA173kq9JWBEGgIDYIo78f3x482TJt7rXy2d4mFhRGs7qkmZumJhGk9aPX7EDtJyc8UE3HoJ0TXr3T00MZsDrZUdNFTJCGGJM/ZquTTrOVIbsLvVLP+MjxuD1uBp2DfHD4Ay7PuJwcU45Pi/IEtjVvY1rMNBICE3ho+0OEakO5fdTtrK5aTb+9n0j/SG7MvxGtXEuYfxh9tj56rb2sPLySgpACZsbN5GjvUUAijnmheWxr2QZI/l0nyNmp2N++n0mRk/ii+gvOSTyHGbEz+OzoZ1yVfdWwbNMJURP4qvor7i26ly+rv0Sn1LEgbQFvl79NdV81MkHGHaPuwOw0c07COaytWwtAfmg+odpQ9rXtIyUoBQUKWoZaeHrvSYJvUpu4f8z9bGzaiEFtYO/xvTw18SnW1a1DIVNwdsLZ1PfXk2ZMo2mwiY7eDhSCgn57Pw+Oe5Bva75Fq9RiUpuGtZBXV60e1tYbdA6yr30fdf11fF//PTfn38wHhz9gwDHAouxFPLfvOa8VR8NgA68efJUnJzyJ3W0n25RNeXe5z34phhT+uvevXpXwB4c/YG7SXHJDcvmu7juf9vK85Hk8tecp72uVoOKnBl+TCY/ooa6/jjBtGO2WdgpCCojQRqCSqxBOCVz6oOID7h9zP9/Wfkt1bzVJhiQyjBnkh+YjCFKKxsbGjcTp41hRtoJjfdKowYmWbYohhZcPSK31dnM7+aH5nB1/NtfmXMttG2/zuSeb24ZKrkJE5Pzk84c9S/9u+L3EbRHDiZsJmIOUsLBs2BkjGMEIRvB74LKDxwk/LJWEBSCZ4E65FxwW0Higco10LP1sKU/U2gdDbVC5Ds54DGRySWAgU0JPjRT8LveTPNz8/CXFKkgkzjEEh7+WVKJF18KOU+KQYsdBd42kLhU9v1TwTplVC0mD/maJAAL1PRYaeyz4+8mxuzzsb+ykvtvCrKxw/nGwlY1HTw63LxwbS1lzH0Z/P/xVCjYc6WB/Qy93nZnK0q8OcsOUpGGWc2vLjnPr9GRqO31brgClTb0sPTuDz/Y1kxWpp3vIzqTUEPrMTgJUCkbFBXG0fYBJySFYXW5e+LGaLrOdu2amkB9roKXPhkcErV8oyZpZCAFDvF/9HLPjZ/O3KX9DIVMwMWqi1yT1VIT6hzI3cS6bWzZzZvyZ7G7djdvj5uyEs3F73OSE5HCk6wh6lZ4+Rx9BqiCmxUzjzLgzeWjHQ95gd5CqI3eOvpOWwRbqBurot/eTZBgurEgJSkHnp2NhxkLC/MO4fePt3vzSDFOGz9rs4Gzcops1x9ZwTdY1pJvS6bf1c3PBzfTZ+gjXhvPmoTeZHjuddks7N+RJlqR1fXXIZXJMGhP72vaREZzhIzwAyeqkYaCBecnziNBGkBaURm1fLRekXIC/0p+XS19mcc5iPqn8hJ3HdxKoCmRh+kKMGiOfV37OI8WP8GXNl6etcGmVWuTIuSrrKhQyBdtatlHZU4nT40QhUyATZOxs3cm85HmMCh1Fq7nVxz8NoMvaRUlHCW8fepu7Cu+iw9pBh6UDuSDn4rSLEQTBx9ql09rJW+Vv8VjxY9xdeDfbWrfhdDuZFDUJh8fBmXFnsrp6NQCF4YUc6R3eGg5SBXF19tXo/HRo5Bo2NW3iwXEPcrTnqDfBYdA5yIPbH+S+ovu4v+h+9Co9btHtTdkIUAZgcVmo66/zkjaQWrYrD69kYdpCbs67maiAKOQyOT22Hqr7q8k0ZuKv8GfQ6dsaH3AMsL99P/vbpeirvNC8084s/jvg94oTVv4Xh/4mCMIHQOL/+o5GMIIR/GdjoA1qN58kbSFpEkFbf7+k5JQp4OxnwSNCQDBsfvaXrNFEOOc52PRXKfz9wrfg4GdQfLO0Zsq9sO9dmLZUCo4fage/UzzOeusk65CZj0nkUUBq0+5fKc3Z9TfCWc9Kc3INWyGmWAqR1wRJ0VjAkM3FFyXNxAZpSQkLoLRRcmTPjNTzwo++larP9jZx6/RkiuKNPPxthXf+7Xi/DadbPG0qQmSgmniTP0N217Bjo+OC8IgeLh8bQ5RBTXX7EDmRgaiVMkz+SkDk2omJbDjSwcHmPi4aHU1xkhGXKPJFSQs2p4chu4t1h6RW1oKiGK4ddw91lhJ6LD3IBBnZpmymxUzD6XZiUBsQRRGb20a4fzh72/ZSFF7ktaW4b8t9DDiktrCAwJIxSyjvKqfYr5i3q99mSvQUogOiOT/xfDR+Gm+VC2B5yXIeKn6ILksXTtGJKIoUhBZQ2lEqPRKaEPJC8vjb/r+RoE/wEjOnx4nF5Vsxreur40jPETyih4UZC0kyJHnbfYe7DnOs7xjRumgClAHsb9/PvvZ9PgIDEenaBWEF9Np6fapGJ+ASXZR2lBKnj+PRnY+yMH0hj+96nF5bLxMjJ7Kmdg0ahYaHxj5Et62byp5KisKLiNPH0e/oJzEwkXh9PJH+kbSaT1ZS7x9zPw0DDXx29DOcbiezE2aTF5zHuPBx5ATnMOgYRCbIMKqMmDQmBp2DwxIYlDKl9x6Xly7n/OTzifCPQKPQsLl5MwWhBWgUGq+xL+DNO1UpVFycejHbmrfxcunLXJ55OWH+Yajlaq7Ovprs4GwWZS/yCbFXyVUUhRfx6oFXOdR1CBGRorAi5DI5o8NGSxYgPVVU9lQyPnI8zUPNnP/t+dxecDtf1XzlnY27c/SdfFz5MdfnXj/s8+62dhOsDSZTk8mBrgO8uP9F73ueFjONB8c9yH1bTwY8FYUXEe4fznW519Fh6WBd7ToW5ywm1Zg6bO9/B/wrNbEfAu8CD/4L9xzBCEbwnwa3Q6qSgRRjNfV+qP5RyhsddQXUbgGXTWqJOoYg92Iol0kVs3/cLvmodVbChmVQfBOs+bOUiFDygRRD5bRIYfSqAFCopZSFo7+QhvqtktghZizsWgGt+yBnAeQtkLzdBAEsHVIQPW5JgVpwhdfYVy4T2FXbw26hh8+uG0dhnJH1FW24PZ5hb9PlEYkJ0nLk+ICPaOEEYescsJEVqfdaf8hlAlcUx7Ojpov5hdFcOCqaL0qkFmK8Scv80TEsfn8fr18xGo8oUpxopKHHgp9bRnOvlVC9miVfHqK5V/qCbum1Eh+sIcaoZUy8EZlMoHPQzoYj7VidHrbXdDM5NZidR+PwU4hMzrGxvXU7AgKJhkTeLX+XVnMrIZoQHhv/GO2Wdl4qeYn4wHjOSTjHp4IkIrK2di2BqkBeK3uNpWOXUtdXx9bWrcxLnofZaebS9Ev5/OjnuEU3M+NmYlAZWF21mtSgVM5KOIvCsEK6bF1YnBbqBup45cArJAYmMj91Pi/sfwGNQkOqIRV/hT/1A/UEKAPotfVy9feSqhCk6KWVs1aSZkxDEAQygzPRKrW0DbVxZdaV3jirU+HBQ5+9j25bNxsbN3JJ+iU+iQ2h2lBsLhvzU+ezdNtSAG9M1MqKlRSFFRGkCWJL8xa+q/+O4shiQrWhRPhHSO1XQYFKppLyNsc9yOHuwxw3HyfTmIlH9PDqwVe911pTu4Zb8m/B4Gfgs6OfsaVlC34yPy5MvZDCsEJ0Sh3Lxi/j06pPKe+SWqI35t3IN8ekuCery8onlZ+QHZxNkCqIdGM6fy/5O4uyF/HqgVcREdEoNDw58UneOfQO5d3lpAWlcXWWVD0zqo3MiJ3BeUnnEe4fjkyQoVfpeXfWu/zY8CMBfgGMixjHvVvu9RGX7G3fy7U51xKoCmR56XI6zB3cUnALzYNSNFVhWCFtljYvabs07VLi9HG8NPUlVHKVj5IW8NqW3JR7E+9VvOdDVDc2baQovIi7Rt+F3W0nyj8Ki9vCc/ueY8AxQKwuljtG34FMGP4Po38X/CuJWyjwv3N4HMEIRjACBGng//A3MO4m+Op6qQIGklr0opWwetHJWbXqH+CMZVIQvH1QapOCZNkREC5V7sKyoPAaOLpOsgJRByEONNMfPArH+IcIyrsMz1A3giEaQSZDuX4JaE24xt9JZ/x5CJZ2wsLzaNZlYy46m0BnF66uGiwxF6NWp3LCnUutlBGuV9M2YOO69/fxxhWFHGkbwO70YPL3o9t80lsrP8ZAY6+FSIPGJ/q0tc9KbnQgH+5u5PKxsczKCkenVuB0e3h/Zz1xJn8+3duE1k/O8kvycbpFogxqrv9QqhI1dlt4/oej3DMrjV11Paza18xlY2LJiQ6kudeKWilj2dwsQnVq5DIZn+1tIjVMz/cVbchlAs9flMeLG6q5uDCGmz8qZXxSMPOLQqhoakaljufH4yupG6jmzsI7eXbvs0Trovm65muvl1htfy372/dzWfplvF1+0pN90DlIsiEZq8tK62Arh7oOcWb8mfTZ+/j4yMd0WDu4NudajGoj2aZsumxdPDXxKWJ0Mew6vovrNl6H2WnGpDaxZMwSnpv8HN83fM8L+18gUBXIrQW38mLJizQPNZMTnMN5SefhJ/PDqDJ6iducxDlsbNrIU3ueojCskEnRk2gebMbhcRCsDub8pPPZ0LjB52ksDCsk2ZDMrT/fitVl5Yy4M7iv6D52tO4gRheDUW3kg8MfcH3eycrQiTnAW/JvIc2Uxi0/3+IVauxr38dNeTexpWULM2Nm8m7FuxSGFfLEz9KA/4XJF5ITkoNBZeDHhh+H/e34oeEHisKLvLYlDo+DTyo/oTiimJKOEra3bCc+MJ5rc67F7rJjdVppGWrx2WNm7ExePfAqmaZMGocaWVe3jpvzb8bhcZBqSOWp3U95PeuO9h7lmX3PcMfoO0jQJwyz5PCT+1EYXkhheKH0V7Srwoe0gRTPdbT3KCXtJYwNH0t8YDyP73ycbls3CkHBDXk30GmRrnfHqDtoGGigtr8WtVxNVU8VD459kA+PfEiHpYMZsTPQq/Qc6ztGk7lpmAk0SNmpr5e9zvSY6Zg0Jv6y+y/e0PrGwUY+O/oZU6OnDjvv3wWC+Oshit9aLAiTT/NjPyAbuB/YJYri3H/Rvf2vUVhYKO7bt++fLxzBCEbwx0HzPimCqmkP2Hp9DXWDEiBu/En7jxNImCLNxTXskAx2f3oU8hdKkVRV38G5L4JCA6YUnCiwChqe3G7ms5JWlHKBK4vjSQj2Z9PRDnKDnFzX/SyVeUt4uUygsm2I8UkmpqQG02tx0jFoRy4TMGgUPLbmCGPjjbxxZSF6jZLq9gGOtg1x+2cHcHtE9GoFrywswOMGuVzg7W11HGzuZ2pqCJeMieGTPY2MjguipLGPL0tOfrk+NCcDvVpJc6+VhGB/3tpW61Wj3n1mGs/9cNTn7WdG6IkP1rLuUBuPnpvJo/84jEoh45XLCrA43Lg8Ik63B49HJDhAxZPfHaG+y0JBTCBXFsdzx+cHffZ75bIC1h46TveQgxijhtX7T97bHWcF84+OB0kJSmbQMci4iHG8UfaGd/A7wj8CEZGkwCSWblvqrbzdW3gvAHva95AXnEe8Ph67x05MQAwfVn5IfX89Yf5hZJmyMKqNdFo6+fzo57w8/WVu3Xirzxe0TJDx4tQXUcikIf9gTTC3/HyLj83IiWH3hMAEXi59mcKwQvR+eq/a8KLUi6joquBwz2Hvnk9PeppuWzc7WnYgE2TMip+FzWUjLyQPQRCo7qtGq9CSbkxHJVdhdVkZcg6hVqg51HnIpz0HMD9lPmPCx1DbX0uXtYuvj32Ny+MiyZBEljGLCVETkAkyXi592VttAtAqtDxc/DCHuw/7VPcAZsfPJkGfwP6O/d4WZYohhfzQfFZVrfKu81f6c33u9Xx05COuyLyCQ12HsDgtnJN4DquOrmJ/x37mp8xnT9sen2vfUnALfy8dHkl+a8GtnBF7ho8p7q/h9rip6a3hiT1PcKBDUjxPj53OoH3Q69kGUBRWhF6l9yHJy6ct576t97F07FKe2/scjxU/Rk1/DZ3WTkI0IVK6hC6al0pe8mbYXpxyMfWD9T6tWrkg58a8G/n7gb97o7NOVROfwIdnfUheaN5/+V7+/4IgCPtFUSz8rTW/t+K2ieHihBMN/83Ajb9zvxGMYAQj8EXPMamaFpYNx0t+dVDkNCNGeEtWo68Ch1WKoCq4At6dDYHRkgFvzzEGZAae2D6Av9rJZyXSLJHTLfL2tjoePy+LuXmR3PbZASYufpWnfqhlfFIIZ2aFo5TLaOu3YfD3Y+X2evQaJbfPTOGc7AjWHDpOY4+F7KhAkkN1OF0e3rqykJZeKz0WB98cOE5zj4U5eZHYnB5mZ4VzsLmPh74q5/kFeXQM2tlW082dZ6TSY3YQrFOhVsh54KtyLhwVRXJoAEdPCZG3udzD3v7h4wNcMCoKAYE99RLBOSMzjD6rk3WH2gjTq5iWFopCBjd/fADrL15xgiDwdWnLsP1+ONxOuF5Neriev/1qNu/1Db1cc9bllPb+iFahxeVxoZQpuST9Eva27fXmlIZrw1kyZgkfHv6QC1MvZMAxwIoyyaR4U9Mm8kLyuD7netot7ZR3lZNpzGRi1ESW7VqGw+NA76fnxrwbaTW3DquqeEQPh7oO8eGRD1kxcwUDjoFh3nDH+o4xI3YGDrdU5SwMK+T1ste9x0O1oazqWeWz5/LS5VyddTW99l5ERF4qeYnHJjxGvCEepUxJclCyzzUMGDA7zPjJ/WjXtpNpzPQSwbPizsIjerh3q0RYY3Wx3FpwKy/sfwGFoCBEG8KW5i1U91ZzU/5NvFTyktcqQ6vU0mnpRCVXER0QTfOQ1BLXKXXMS57HCyUvEKY9qTadHD2Z9w6/53NvZqcU1N5uaee5fc+RGJiIWqFGQOCR8Y/QYekgWB3MRWkX8eSuJynrKiNWF0tecN6w1qSAgE6p80ZEnQ5mp5lVVat4ueRllk1YRkxADCUdJYyPGM8Tu5/wWbu3fS835t3oJW435t6IXJDz7ORnUaDgmpxr+Ln5Z7499q33nCnRU3B5XD6zeBmmDIoiixAQ2N22mwj/CBZmLOSTyk8AycRXHEZZwKAyEKo9vXXMvwN+L3GbznDiZgMaRFFsO83600IQBDmwD2gRRXGOIAgJwKdICtX9wBWiKDp+dc5C4J5TfpQLjBJF8cDvfA8jGMEI/sjQhkiRVH2NkDAZhFdOtkV766W26MFPfXNEcy+RhAT9jRAYJVmGNO6SfNuiRoMoIKadw5EuJdlRcvY19BCuVzMmwUj7gI099T0cbO7jzMwwRBHazZAepkfrJ2f1/mb21vcSpldx76x0ZmeHs2p/M8v+cZi/XJDDuvLjKH+ZSxMEgeggLW4RQnV+lLcOsLbsOP4qOTFBGq4ojqOu00xOdCAJwVrO/ft2bpiSiMXu4oWfqvD3U2B2uHh8bha50YF8sreJ/Y29XD42jnd31AOgVgx3XMqLDiQtTMe26i42VXVi9PcjN9rA3atO+qGtOXicly7J/8W/LRgRqS3bZxmuZvSTy5iYEuxNdDgVFocbBTomRU3izUNvEqGN4Orsq3F5XD7ms22WNg53H+aBsQ8gCIJ3/usEDnYeRETkzbI3aRpsommwiQOdB1iQvsBrb7G+fj3X5Vw3LBdVJsjwk/thdVn56+6/ck/RPfwaWoUWp9tJoiERo9o4zJj3VI+5EzhuPs7YiLFkmDLwiB4CVYHE6eOGrQM42n2U2oFa1tauRafUMSthFlOjp3JZxmUMOgbR++l5YPsD3vWNg42UtJeQE5zD7PjZxOvjAfjW8y0fH/mYBWkLqO6tZm3dWuL0cej8dCwvXc6CtAXo/HSIiMTr4tnRsoP5qfN9zIcD/QJRy9UMeXzVxka1Ea1Ci8Vloba/lmRDMjnBOQT4BWB2mpHL5KQb0lkxcwXdtm4CVYH4K/1ZnLPYh+RekHIB2absYTYrp+JI9xGvd9vhnsNU9VaRH5J/2pQMwEuoHi1+lJ8af+K1stdQyBTMS57H7LjZvLD/pFegSW0i2ZBMZEAkdxfeTWl7KaPDRqNVaGkcbOSKzCuYlzIPp9vJc/ueo9/RT05wDkmGJDY2buSClAv4sloy5VYICm4tuJVgTTAgZca2mluRCTKiA6KRy/74jma/V1W66V903duBI4D+l9dPAy+IovipIAgrgGuA13517Y+AjwAEQcgBvh4hbSMYwf9BRBbA4a+knFC5H5z1jBQC77T+IgRQwcUfwJE1YB+QLDt2/h06KiRrkHV3S6a68kiJwEUWgFLFgcYejrYP0GNxcHZOBEkhAXxV2kJUkIaHzsnEbHfRMWjH6K/EI8KA3cX2mm721kvmvu0Ddu79ooyHzslg1X4YtLsICVCy9Z6puDwi5S19qBUyei1OQEAug/zoQJ65MAeVUoZKKUcURQrjDAza3FidLvzkMl7bVMuVxXFkRQZS12VmQrKJ7Ag9+dGB1HZZ8FcpAJGsSD0NPRaSQ/25YUoib26tw+0RiQxUMzc/ipY+C5uqpDmhc/MieHtbrc/HOmh30dJnZeGYGNR+Chq6zShlAmfnhLPxaId3xk4uE0gL17Fo5T7unZWGSiHzmgQDxJk0pAWHoVWHcXXW1RzsOohCrhhW8QI41HWIeH083xz7hikxU9AoNKyuWs24iHE43A4G7ANclnEZq6s66WV0AAAgAElEQVRXc7DzIO2Wdp80gKreKvzkflyTfQ2vHXyNIecQSpmSRdmLWF+/XlrTV0WofyjzU+ezumq199wrs66kabCJyzMvZ0LkBDyihzZzm9fK4kT16dSKzLmJ59Jj7aFhsAGdUsegfZD6/noCVYEkBCYQqArEI3rY1rwNh8dBTV8NGcYM1tStYX39eh4Y9wAfHP6A0WGjT/tol3eV89SkpzjSdYSa/hreLHuTIadEtsq6yrgk7RIKQwuZkzgHgDtG38HXNV/TZe1iRuwM4nRxGNQGApQBXJR8Ef5+/pg0JmJ1sfQ7+n1mCmN0MYwKHcUn53zCsb5j+Mn9SDOm0W/v5+afb6auvw6VXMVdo+9ibvJc4gPjaRpo4lDnIcaHjyfTmEm7pR2dnw6FTEGPvYchxxABpyqxT8GJOTqT2kSENoL5qfOxuqyo5Kph/nG5wbl0mDuI9I+krr/O69nn8rhYVbXK25oWRRGT2sRV2Vex4uAKzE4zGoWGpWOX8mP9j3gEyTPujNgzEAQBjULDnaPvRC6Ts6lpE68eeBWlTMnCjIXE6mKxuCwoZUreK3+PiVETAXjtwGt8W/stCkHB4tzFLEhbQJA66LTv8Y+C35uc4AaKRVHcc5pjo4E9oij+Jl0VBCEaOAd4ErhTkHTZ04ETKbPvAY/yK+L2K1yKVKEbwQhG8H8N2iCY8Qi0HpCiqoISwE8nEbeGndDfJClDZzwqEbfOI5A4VVKO7n8fChdJOaOh6V6hQlP3EFuru3htUy1Wp5sog4ZrJyVwvN9GfbeFkoY+nrogG0EQeHZ+Hi63h4hANUFaP4qTjLyzrZ7OITtuj0if1YlBo+TVhaPoHLLTNmBHo1QQolPhdDtp7rWyraabQbuDSwpjGbK7UCvlrN7XRFOvlQVFMeTHGlDJBZ6Zn8tD35Tz/s4GYo1aHjsvi54hG6VNfShlAiqlHIVMoMfs4MWfqnG6PVw7KYHSxl5unpaEUibD5fbw943VLJubzdtXFmJ1uQkLUPHdoeFNEAH4vqKdDUc7iAzUcOcZqSgEePy8LPbW9yKXCYyKNVDbKXmBrdxRz2Nzs1j+UzWt/TYywnXcOiMRk0LO5pZvWdf4BZ3WTvbK9rI4Z/Gw640OG82HRz6k3dJOTV8Nk6ImcU/hPXx05CNUChUymQwlSiZHT+ZgpzRnJ+Ok2m9sxFgiAyJps7SxIG0B8fp4moea+a7uO+9c1tSYqYRpw/jzqD8zO342LUMtBKmC0Cq0XJx6MSHak+kQN+TdQF5IHhsaN6AUlDw2/jFeO/gaHZYOzkk4h1nxs7hi/RWApMb8qeEnqvuqAZgYNZGHxj2EW3Rz3Hyc5/c/j9VlRSlTsjhnMWtq19A40Mii7EW4PW48DFcS54fks6N1BysrVnJD3g1e0nYC3xz7hseKH+OJ3U9wX9F9NA00kaBPoCCkAJVcRbetm7fK32JGzAzmp81HI9dIViZ+ASjlSpINyZR2lJIQmMDEqIlE6aIASDRITl1mp5kHtj7gnRGzu+38Zc9fSDemY1QbebHkRWbHz+ZIzxHi9HE8s+8Zn8rkM5Of4ayEs0771zZEE4JMkHFv0b08vONhL5FPMaSwZMwS9rfvZ3vrdoojipkUPYmqniomRE1geenyYXsd6DhAUVgRu9t2Mzd5rpe0gaSMXbZzGY8UPwLA9/Xf02fvY2r0VPJD8onSRbG8ZDnjIseRaEgkOiCa1sFWHG4HMkFGy1ALckGOVqFldfVqvj4mtfYdooNXDrxCSlAKM2JnnPY9/lHwe1ulv5VKLOefpyoAvAjcC5xIlTUBfaIonng6moGof7LHAuC0IghBEK4DrgOIjf2nCV0jGMEI/ojwD4aUmTDUJfmtTVsqRU/JNeAYkNqgJe9B2myIKACtCcwdED1GMsnV+brNH+u08Lcfq72vW/qsfLirgXNyI/iypAWr002vxUl2pJ5us5NbPi7F9UvMgEoh484zUnnqu0pAst5YcXkBg3YXT62rpLVfagVNSDJxVk4EaWEBFMQE4vCILP5gP26PiJ9cxl8vzCHBqKW+x0Ll8UFEUSTaqOWdPxXicoso5TIUcoGuIRtqhYysyECG7C6UChl3fHYQh9uDTICkEH8yIwI51NKP2eGiudfKPbPSCdH5cah5gDVlx0kL13Hd5ESeWHuydenvJ0cmE/ipssP7Gdyz+iDLLyngi5IW+q1O3B6Rr0pbuHmaNMvVMWjnpZ+qeHhOFvXdZpJD/Om1ulj+UzV91mTmjPoL5pCNrGn8mIaBBuanzufL6i/xiB4mRk1EJVf5mLtubdlKlinLS4bu23ofz05+1vslXxhWSOOARMgyTZkszllMrD6WCP8IybTVMciQc8ireMwNzuWWgltQK9SoFWrGRoz9Lx+pIccQ3bZusoOzyQ7Olkxe5QFET4ymoquCjU0b+ar6K67PvZ61tWtpM7d57xNgW8s2NjRsICogihdLXvTOWjk9Tt4oe4Nrc6/F4XZQ2l5KijGFmt4a5iTOYU3tGgCiA6K5KO0ibtpwE8Bp/eAUggKby8bCjIWoFWpERMZGjKXN0saO1h2UH5GqVsHaYJoGmvBX+ntVnilBKaQEpTAnaY53vzZzG6UdpdT315NpyiRGF8Oedt+6S4gmBLPTTP1APbPiZ3Hv1nsJUAYwJ3HOsHbyW4feYmLkRLpt3V7S2jzUjN1lR6/S89i4x/i86nOf6mt1XzWlHaUUhRehkqn4sPJDVpSt4IbcG8gwZZBhzKBhoMHnOsGaYOL0cehVerQK7TBTYYfHgcPjQC1Xk2PKIc2YxqXplxKli0Kj0HD7qNvZ0boDP5kfWrmWH9t+ZGuLlEGcYkjhweIHUcqVrKtdN+x3sKt11/8N4iYIgoyTpE32y+tToQHOArr4DQiCMAfoEEVxvyAIU3/nvZ7YYyxgEUWx/HTHRVF8A3gDJFXp/+QaIxjBCP4gCAiW/vwahlgpscBhhuBk0EcCWafd4lBzH51Dw9t4xzrN3DY9heP9NnYe6yZQreSZ9UcJ0au8pA3A7vJQ1T5IrFFLYog/Px5u54riOL4qaaG130ZyaACTU4LpMTsZsjmp6zJjcbh5+vujhAT4cVZOBHJBYMPhNuaPjqGp10p0kJqoQC16jQIBgW/LjvP2tjrkMoHFkxJICdVx7Qf7sTvd3DMrDYdbqt6clx9J95CDWKOC7yuOU9kmVWwqWgeYlhbCO9vrASht6uOcnHCenZ/LNwdaCNerOS8/its+LfX5DDwi9FoctPZZ6RiUPqOsSD11XScrQenheuq7h/BTyKntsvDX9ZXetupbm2wsnjYVk/p7trVs476i+zCpTQT6BRIbGMstG27xuZ5CUAyrRO1r38e48HFcn3s9IiJKmZLXZ75Ol7WLDKOUgKCUK0kzpgFSFW9y9GQsLguR/pHoVXqf/ZweJ7V9tVicFlrNrWxu2kx8YDwZxgzJdb9iJaUdpShkCp6c8CQPbn/Qx3NuUtQkZsTOYHfb7mHPTGlnKUmGpGGVMpfo8oajW1wW/rL7LxhUBp6e9DQzY2fSY+vBpDFR3VuNWq7G4rLg9DgxqU1027q9+yzOXUyaKQ2D2kCsLpZgdTC99l5eKn3Ja2kSHRBNsDoYmSDji+ovCFIHMSpslHePtqE2jvUfQybIeKf8HZ/c1MU5i7k+93qvAXF1bzXnJZ1HWVcZgX6BtJnbOOE0cTqfM4VMwfaW7Tyw/QEcHgeZpkzOiDuDTys/5aqsq0gKTCJMG8b4yPHsbdvr/Vx7bD0s27WMMeFjvKR7RdkKsoOzKY4sZk/bHnpsPUQHRHNV1lX02nsZdA5SEFqA3k8/3CBYpqDd3M7rZa/zSPEjuDwuEgITvPNpBWEF+Pv5U9NbQ7+j30vaQCKSW1u2UhBaQKYp04ecA8MEKH9E/FPiJgjCI8DDv7wUge2/sfzV3zgGMAE4TxCEs5E83/TAS4BBEATFL1W3aGC4zOkkLgE++Wf3PYIRjOD/MAwx0p9/gorWfsw2FyE61bBj4Xo1e+t7EIBlc7No6DEjAoPW4UPrDreHm6YksqWmi7WH2piZEcbh4wMsmhBPgEqOSiHDX6UgwqCmrd9OfnQgT1+Yg0oho9/ios/mwOFWc6h1gACVnNpOC+XN/RQnB6NTKfhwV4N3juylDTXceUYqySH+qJRyzKekJExNDeVwaz8qpYLKtiECNUpUChlnZoax8hfxwgmsPdTGhGQTc/MjOd5nw+Zyo1IM/zI2aJVcOjYGtwd0KgWJwQHc9PF+ABKC/blgVDSbjnbQa3EQZ/IfFsP13QErSy94Er08kt4hgVRNOgNUIyCQacr0ibOalzKPzU2bfc4PUAawt20vq6pXYVQbWTJmCf5Kf7KCs1DKlcPuVxCEYV5iJzDkGGLX8V1sad6CQWXg3Yp3vcdMahNPT3qaOYlzKOssw+VxUddfNyxqalvLNkaFjiInOIfKnkqfY/H6eJoGm6T5t1MilRQyBZnGTCp7KjFpTMxPlWxAtrZs9ao9w7Rh3FZwG7fk38Iz+57hg8MfsDhnMf32fjqtnaQEpbC3bS/pxnSmxU4D4OMjH9M42MjjxY/Ta+9FKVcSqgmlx9ZDj63HGw6fH5qP2+NmT9seKroqSA5KRhRFL2kzqU3MjJtJvD6e/e37+bJGGtSfFTeLfW37+ODIBwAkBibyp6w/sbJiJcGaYNRytY+4YGH6Qh7c8SAOj6QdPNx9mBBNiDc5I1AVSMtgCwiSh92PjT9S3lVOqDYUtULNhKgJZJoyaRho4KMjH7GxaSMBygAuS79MIvyqQO7Zco/Xc82oNnJt9rXcW3Qvf93zV+xuu7c1/Y/afyAi8kbZG9xTdA9ymRy7y06fvQ+9nx69n57UoFRWHl457DnZ1rKNG/JuYGHGQjY3b6bPLiWcJBuSKY4oPu2z9UfCf6fitumX/wpIBO5tpHbmqbADh4E1v7WRKIr3I/m98UvF7W5RFBcKgrAKmI80t/Yn4JvTnf9Lpe9iYNJ/475HMIIR/Ieja9CO3eWhpmOIG6cm8domKfNQrZRx7aQEXvqpmkG7i16zk/SIAA429/HwnEy21vg2D7IiA7n/63IvaRmyu7hhShJB/kraB+y8t6OeUJ2KtDAdo2INKOUCTT1WviptISRAxTm5EWw40kSsSUtkoJrJqSFUtA5w96oydGoF98xKY3tNFznRBlweD1EGDROSg/nhcDs6jYJn5+fw0W7JdFcQBJRyuGdWGt1DdiwON6NiDXy021dEACCKAiICe+p78Ygit05L4aFvT76PsQlGAlRyVmyqxe7yIAhw2/Rknr4gF7kM2gftRAaqyI818MW+FrIihn9lmPz90IkpLF1dTuMvKtTpmXrCY3ewIG0BffY+qnqriNfFk2pM5YvqL7znahQaxoSPQSFTUBxVjL/Cn2BN8G96hf0WjvUdY339ekK1oT5CBZAyRVvMLXhED3+Z+Bfu23rfaRWEgapAumxdhPuHkxuSS1mnpMydGj2VXlsve9v2es2HLS4LKrmKG/Nu5NUDr/LExCewOC18Vf0VwZpg3jv8Hno/PddkX0PjYCObmzdzZtyZPD3pafZ37CfALwC3x83O4zv5seFH3KJb2lOhIlIbiUlj4qk9T/HRkY8IUgVxTc41PLbjMRQyBXeOvpMx4WNQKVS0DLTQaeuk39GPVqnlgW0PcHnG5YA0m5cWlMZXNV+xvn49c5PmMiN2BhsaN/B9w/csyl6Ev9Ifs9NMbX8t02OnkxaUhtVl5ZHiRzjUdYheWy+ZpkwsTsswEcqetj3MT5lPsDbYRzl8sPMg9xTew8TIiXRYOsgyZXH7xtvxiB7CtGE8P/V52s3tNA82E62LRoaMjyo/8pI2kCp1VpeVyu5KXp7+Mu3mdlqGWvi29luaByUa0mntJFYXy9Geo7x+8HV2Ht9JlimLq7OvprS9lOmx07G6rGxs3Ogl6cURxWgVWjJMGXx89sfU9NWglCtJMaQQ5u87ZvFHxD8lbqIobkbyaEMQBBF4SxTF36qI/U9wH/CpIAhPAKVI5BBBEM4DCkVRPFHxmww0iaJYe/ptRjCCEYzgJNRKGT1mOzaXh5wIPe9cVUiv2Ul9t5nXt9Qy+Es160jbAHMLIvjmQCvrDh3n6QtzeH9nAzJB4IriOD7a1eAlO/NHR/NDRRu3z0yhpLGfv6w7wuJJiXQO2rnvizLCA9XcNDWZHce6mJ0djkohY2t1JwvHxmJ3eTBqlVgdLvwUMiYkm/ihop2/flfJ43OzuGd1GSe6tKPjDFw3KZGNRzuZmRFKdJCaB74qZ0yCkalpITzyzWHv/W+t7uT6yYk8f4rnWqhORUSgmkXvSSbk22q6uGZCPK9fPpqmXgsBfgoC1HLu/LzMS/hE8WTFb8DqZHS8gYPNA/gpBK4sjkWrkkQYnf8fe+cdJVWZbv3fqZy7qnPOOdJ0ExpBiSKCiiKKcURHdFQGzBnR0RlRMeOYxlEZFJTBgAxZlKCEBroJneicY3V3dVVXrvr+KCws23vveL/51nW+23st1yr6vOect8Kydj3Ps/c+21YVCb72bZNx2E/aAL6uMHFP0iSeObiclZNWsqd5D9sbthOpiWTZ2GV0mDvQK/Qk65JpNDUyN3kuQfKg/6v32uPxMmgfZG/rXq7OuBqXd2Tl1O6y4/K48Hq93D32bkx2E2PCxlDWc86gYNnYZQzYB+iydHH32LupMlZhdpox2U1EaaJQSVV8VPkRr0x7hWHXMAICw85hnpz0JBanhe7hbiqMFZwfdz7FEcXMSpjFK8de8Weo7mjawaMTHuVY5zFmx8/mrea3mJM0B5vLRpQ6CoPCQONAI+2mdrJDs5mTOIc4XRyJukTWVazDi5dV56/ipaMvUT/o+yq8LOUy9DI9Tq8Ts8OM2WnG6rYSrgynMLyQ146/5n9+H1Z8yO8KfseBtgPY3DYqjZUkBSXRaenkirQriNfGk5idyKaaTWyp38KS/CXsbd3Li0df5PGJj494TTMMGSDAkc4jI44d6z6GxWlhXOS4gD10DXfx9om3WTpmKXHaOOoG6zDZTRitI1MQhpxDzEiYwbGuY+SE5rDy+5UB5G5+6ny6Ld2sr1lPtCaaiVET+bb1Wwq6C0gzpDFgG2BKzBTmp8xnW8M2qvqrmBw72d8ujtPFEaf7r6v3vyb8UjuQJ/9VNz5rLfLN2cf1wPifWfMl8OVPzpn4r9rDKEYxiv8/YbY5qewwIROLidAp2FnRjUwswuZykxqm5rWvawPWyyUi4oPVPH9lPnaXhz6znWevyEMENBktLCyKY9mMNPqG7eyt7qUkJRSTzYVBJeUvvymmqc/CO/t8X6J1PRY+KW3mwuwIXt51BpVcwqLiOHJjgjjTNUS0QckL22uo7hoiJ1rHcwvykElEPLutmh+N1nG0aYCril2cnxbKs1uraDL6vvj31vQQa1D6SRtA24AN47CDl68uYFdlN1F6BWNi9TT1ngtcV0hFyCRimo3DuNxeagctKGU/2Jf4kBiiYkFRLBq5hFCNDIVEjFQsoJKJqegYIjFYzaJxcXgBu9NDsFrK2u+buGLsSD1Zp1GERqah3dzO+KjxlPWU0TrUyktHXyJaHc2ijEWsrVzLS1Nf+m+RNovdhcnqxOXxUtYyQK/ZTlaSnGhNNEc6jrAoY1FAq1Qj1RCkCKLT3Inb6+Zkz0miNFHcU3QPtQO1mJ1mlBIlTrcTh8uBBw+PHXgsIC4qXBXOXWPuYkfTDlQSFWU9ZRzqOMS85Hm0mFtoHGwkRBHClJgpxGpiOSE6Qb+9f0Tw/YbqDawoWYHb4ybdkB5AauYmzaXP2seY8DHE6eKQiCS8e/JdfybpgvQFfFX3lZ+0gU+NumLiCp4+9DSLcxajkqgo7y7n2SnP+tugP8aRziPkhuZS2lVKUXgRVqeVWF0sqw6vwua2ISBwTeY1uPvcrPhuBcvHLmd3824McgOLMhaRHJSMXCKnfaidBF0Cx7uPEyQb+R4GyYKYET+Dflv/iGM5ITmsrVjLt22+1vmcxDlclnoZLx97OWCdQWFg2TfLmB43nUxDJvcU3cPGMxvpsnRxacqlKCVKEEAn07GlfguR6kgeHv8wAN3D3ayrXEe7pR0BgUWZi7g46eIRYod/N/wzM27vAX/wer0NZx//Z/B6vd5b/jVbG8UoRjGKX47K9kFOtpk4UNfLjMxwhuxOQjRyXthRjU4p4d5ZGVxaEM2X5e3+c+6YmoLb4+F48wBSsYhYg5K399aTGKomRCPD7vSw7VQn0Xoli8bH8UVZG89t98VOBatlrJiXzfnpoeyt8bVYp6SF88w/qrh2fDxyqYh/nOrgVPsgN5Yk8oevKqjv9X1xhGt9lhg9ZgdXFsXi9cJf9jdgPkvK2vqtIOAnbQBSiQiLY2R6wv4zvSglIqo7h/i+ro939jYwLSOMaRnh7KnuZtmMNP6yv4Fes28+KSpIwQOzM/zZqgaVlEXj4nlue5WfQF5RGM2i8fEs/fg4XSY7M7LCGRh2cqJ1AIlIhNXpRiISiApSjthPVLCb6MFo+qxGWszNLBu7jKNdRwlWBJNmSOOdE+8wP3X+L25N9ZntdJlsHKrrI1KvoL7XQlu/jY8ON/P4JdEszlnM57WfIxfLuTXvVg53HiZSHUluaC7bGrYxJWYKEpGE0u5SBloGmBo3lW9av2F/235/WkB2SDa/zf0tn1R/EnDv7uFujDYjD457kLrBOgQErsq4CqfbyZ8O/Yl+ez/3FN3D1LipPHbgMZQS5c8Ouzs9TjZUbyAxKNHv8v8DtjRs4e6xd7O7eTder5fN9ZsBsLltrKtcx+vTX+d4z/ER12weakYr01LeU052SLY/TSFeO3IeMEwVRpWxiuVjl9M93I1cLGdD9QZ/FcqLl4+qPmJp4VLKe8oZcgzxRMkTSMVSYjQx7GvbR4IugVR9KlqZlstSL6N7uJvtjdv9lU6JSMJFSRf55+DAp6QVBAGNVINaqvaTNoCtjVuZGDWRu8bcxac1n6KVabkq/SpEIt9c5tctXzMnaQ6vHn+VGfEzWJyzmF5rL7uad2G0Gf2vk8lh4mTvSWwuG0abkXZLu/85fVz1MfcX30+mIfO/+pj9qvHPVNym4RMQwM8nJ/wYoyrOUYxiFP9jONpk5GC9kee3V6OWicmLCUKvlPLR4WbUMjHLZ6Tz8q4aSlJCuO/CdJRSMSIRbD3VxfbTXdw3O50vytr9KQUxeiWXjYnmjbOzcQCxBiWzcyL9/zZaHHz4fSOLJyWhV8po6DUzZHOSEaHF4fbw0WGfvUVdj4WD9UZuvyCZl3b5lGxXFcfxwMYT/uqZTiHhrmmpPLutCkEAmUSM2xM4t2a0OIjVKxEJBFTobpiYwPPbqwMqcXuqe1g+M436XjO13WY/aQPoGLRR0WHi6ctzefjvJ7k4P4p39tUHXHPT8XYmpYbRZfK1RvdUdfPA7EwkIoFDDUaigxQsn5WGQSUlI0JDdZdPbXnpGAMKdQf3pTxBn8XORYlu5GI5PZYe9rfv58u6L0nSJTE7cfY//d52maw09lgwDjvoNTuID1VjUEqo6TLz8RHfa/yHze2899sUluQtoaynjA8rPiQ/LJ/agVq2N27nhuwbsLltxGvjGbAPEKoMpc/ax97WvQH3quirwOFxjDDoBcgIzuDT6k/9macA12ddz51j7uTTmk/psnRxsNMnCrC6rAQrgpGKpAEiiDmJc1hXuY5YbWxA208iknBL7i04PU5S9Clo5VpKokr4vuN7/5oqYxV5oXkBOZ/gM9wdcgyRok+h09KJVqZFJIgIU4Whk+kwOXxZt2qpmnnJ85ifMp/N9ZvptHRyacql9Nv7KYkqQSKS8NdTf8XldWFz+YQJibpERIgw2owMOYfID8tnb+teDrQfYHHOYt4++TbXZl7Ly9Ne5lj3MYadw0Rrovn8zOekB6fzdfPX/Gnyn2gaasLj9ZCsS/b7p/0YWxu2IhfLKYkuweq08uLRFymKKKI4opjSrlL6bH0YFAa2NmxlYfpCdjbtZFL0JP566q8B11FIFAQrgvmm9ZsR9xALYt8soXMYlVQ14vi/A/6ZGbekHz1O/H+6m1GMYhSj+G/iWHM/X1d24/Z4Wffb8UjFIk63m1DJxbg9Xi4bE8O7++rpH/bld/7jZCeCAPfMSqd3yM5FuZGUtwzyRdm5StycvEg++Ilas7XfilYR+L/O0+0mFFIRx1v6yYsJIilUjUjwhcr/GFanG/fZYbmEEBX7zvQGEC2TzUVdj5miBD1Xj4tnyOZEKZFycW4k/zh1zlC302Tl9WsL+dvBJvqHnVw/IQGJWAi41g/IiwlCIxOz7XTXiGMNvRbKWwa4e1YaepV0xHMFAlStHi+s2l7F1PRQ3l88DovdxaOfnSJCJ+f2qSngBb1agkLmZOsJNXl6AxEaMwWRKQDIJDJKokvwegXidQmkGBJH3O/nUNk+yMZjrdR0+YyUwdfefunqMWcd9s+tvfndJmINSl77zWT2t+33KyvzQvMoiSpBKVaybM8yJsdM5qLEixALYsaGj+VYd2Aubq+1l/mp8/ms9jP/3xamL2TYORxA2gDWV6/n5tybmZ04G4PcEBCo/lHVR9xddDdHu45itBm5LOUydjXvYsg5RJ+1j1htrH/Q/rqs6/iy7kt/ZinALbm3UDtQ67fRMCh87cpqY7U/w3Rmwkz6rH0Y5Aamx01HKVGypmwNhzoPcajjEDdm34hIEGFQGFCIFdT115EUlESqPpXM4ExWfLfCf79odTTXZV/Hh6c/RC6Wk6BNIFoTzYB9gJXfrWTIOYSAwIK0BX4T5DBVGCaHiQhVBNsat2F32f02J22WNq5Kv4rnS5/3x5ZFqCKYnzo/wKoEIC8sj01nNgVYpHzX/h235t/Kyd6ThCnDuLPgTuKD4skLyWNR5iK/gvjH53zb8i235N5CXmheQAA9+BJqmF4AACAASURBVEyHL/n8EiZFT+LBcQ/6zYn/nfBLkxPOB455vV7zzxxTA0Ver3fvyDNHMYpRjOL/HSraB7nh3UMsGBvL2Hg9fWYHj352iiG7i+Uz04gzKAnWyPxmuT/A6/X5tM3Nj+LNb+u4Y2pgW0smFvk91H563o9RlGCg12KnxWilxWglzqAiRCNDIRPhsAaeH6rxWZOEqGW09gfOPgH0mO38fnoad310nCG7C7VMzOqrCpiSFkbrwDCxehWdJisfHWrmuvEJfHWiA4/XS2njAFlRWio7ztlUTEoNQSMTU9NtYmJKCKVNgbNG56eH0dBjobrLTLfJRl6MjpNtJv9xsUhAr5T626k/PPekUA1/O9jErkqfmW9OjA69UkZFuwmbS4bD5WFeXgwGlYy0yB+1Qh2RfPadmT1V3VyYPcANJf1E6ZWEa30ZmB6Plx6zjb6ziRR9Zjup4Vqe3HyaGVkRftIGvvdt9Y5qVlySTXSQgg6Tzf++2F0evmstY1L0JBbnLkYmlhEkC8LldfHMwWeYnzafMwNneOzAYwgIXJR4EfNT5/N5ra8KlBWcRf1APVHqKJ6a9BRdli5/tFRVf6BFCPiimoJkQZgcJpqGmrg89XJWHVkF+Nqrrx1/jYfHP4wgCKgkKppMTUyJmcL37d9zXfZ17GneQ2lXKcHy4ADSBvBpzadcmnIpf6v8G+n6dCZGTSROG8cr016hfrAepUSJ3W2ndqCW+anz+f2e37M4Z7Hfh27YNcybJ94EYMXEFcRqYpGJZTxf+jyTYyazpWFLwP3aLe1opBruH3c/oYpQZiXMonu4mzfL3/RboHjxsvHMRpYWLqXX2ktxeDHBimCOdB6h3dwecL3ynnJuzL4xIGu2a7iLUGUoWYYsKvt9JtFZhixyQnJ45+Q7AeeHq8Lxer3cU3QPDpeDVUdW8fwFzyMVSxkXOQ6VWEWGIYOnDj7lP0cr06KQKLg281qah5rptPh+9MxLnudP6Piu/TteKH2B1ResRikd2er/NeOXJifsAUqAEZFXQObZ47/+hNZRjGIU/19h/5lepmeGUZISQs+QHYvDhUYhYcju4s/f1PHQnEzsTjcROrm/7fcDfsjidLq9nG4fpCQ5hO/rfb/ev67q5vLCGD4pPeeApJVLSAlTIxYJuD1ekkLV/HZKEg9uPOlf89beet64rpA7p6b6ExcA4oKVBCml3HdhOnqlDJEI9p4JtB65ODeKO9Yd88+xWRxu3tvfiEYupqF3mMvHxqCWS5mbH02jcZiCOF/CwsZjrdwxNZWihGAqO0yMiQ1iZk4ENqeHnRU9zMyKYGFRLJ+XtSESBK6fGE+wWkZNxxB7a3uZmh7KonFxvLTrDGUtA4Rp5DwyN5NXv67hmgnxdJtstPQPMzMzgsggBR9+73O7l4lF/KYkkV0VXQxYHQiCwPUT4kEQSAg9l2vZOWjlvk/LmZgcwh8vz8PuctM9ZOdgvRGd0tdq/epEB9tOdZISrmFqRhhuj5c+s4OylkEmp4XxU+hVMsw2FzdOSgCvrxraa7ZzZXEsOyo1iMVuFO5h1tY9gcvrZGH6QuYkzcHhdvB9u6/96MXL1sat3Fd8H1Oip5AQlMC0uGmYnWbeKHuD2oFaSqJKWJy7GIvDQqo+NaD1CJCuTydEGeKzrjBWURhWyP3F93O67zRaqdYfWh+tikYillAcUUyV0adulIlk3Jx7M78r+J2/gvZj2Fw2xoaPZWz4WPLD8v0zgenB6QTJg/i6+WtePvZygABi2DUc4DWnlCjJDcklMSiRr+q/4ljXMQrDCykML+TvNX8fcc9gRTDxmnhu3XUrUpGU16a/RtNQ04h1GqkGpURJ7UAtRpsRmVg2Yo1aqv7ZcPqNNRu5PPVyblHdQsNgA23mNlweFxOjJvorcSJBxIPjH8QgN2B1WXnhyAuYnWYe2vcQG+ZuQCKScKTrCIc7D/PAuAdwe9yopWq0Mi1f1H5B7WAtS/KWYHfbiVRH8mHFhxzvPjcfuK9tH9XGasZEjBmxv18zBO9Pfzr+Z4sFwQNM/A+ySicB33i93pHv3P8QiouLvaWlpf/T2xjFKEbx34Dd6eZMt5nOQStReiWpYRrkUjEOtxvjkJ0Ok53qjkESQzV0mnyZoy+fnR2TS0Tce2EGf/6mlv5hJ4IAq6/MR62Qcu8n5ZjtLsQigXtnpXOooY/0CB2flLYwaHWy5PxkbE43ZS0DjEs0MCc3isONRjaXt5McqmZ2TiQfH2pi3pgYgpRS4gxK9p7pweHy0jNkZ3N5OzaXh9ULCxgYdqBTSvm+ro9gtQyxSKCi3YROKWVw2ME14+Op7DTx4fdNCILAbecnkxGh5fcbjmOy+kLoC+J8ar3MSB3JYWqe3Vrlt+9IClVzaUE0aRFq1uypo7JjiAidnORQH/F5d18Dd89Ko7Spn03H2siM1DI9MxyvF2IMCgaGXWw52U5qmIb5Y3yCjRCNHJVcQklyMK/sOsNvJiWyu6qL81LCONzQR2XHEBfmRJIXq6Ox10JKmIaW/mFEgk992jZgw+5y88quMzxzeR5XF8chEgnsremh3+Lg06Mt7K/tY+n0VD473saYOD1FCQYcbg9DNhdrv29i0OokSCnl0bmZ9Fsc7KroZmpmOM+fFYSAz0D5uonxrN5xzgKlOEHPbyYl8fv1x/3VN7lExIoFWrzyRt468RYPjnuQdVXrONUbGL4zM34m0+OnE62ORiwSc9vO2wLIUHZINpemXEqoIpQeaw/bGrdRbaymOLKYy1Mvp9vSTWZIJm+Wv0mYKowJURM43HGYaHU0F8RdwGc1nyESi/iu/Ttahlr8150QOQGNTMPXzV+zctJKnj38bEBKwOWpl1PRV8Hi3MWEK8MRBIFYbSyRat+cZVVfFaVdpf4KH8DV6VcTp4tjdelq5iXPI1mfjBgxm2o30Whq9K/LCs7istTLePbws/6/KSVKHhr/EF2WLsQiMTKRjHhdPGvK1lDTf+61Blh9wWreLH+Tm3JuospYRYelA4vL4ifFAEsLl5Ibksttu24LOPe2/Ntwup18UfdFQJtzZclKBEFg0D5IqiGVpsEm3j7xNg6Pg2syrqHD0sGWhi18cNEHHOk8wutlr/vPlYgkLB2zlJeOvcQ1mddwuPMwdQO++dQXzn+B+/beF7CHSHUk0+Omc2X6laQZ0vg1QBCEo16vt/g/W/PPqEoTgR83gYsFQdD8ZJkSuBlo/oV7HMUoRjGKEXC6PWw81spjn58iK1LH1IwwZmaFU9rYz5aTHeRE65iRFUFssIrlG8p48rJcP2kDX6vsrW/rmF8Yw18PNOL1QrReSdeQjXduLKKsZQC7y8Pxln6uGR9Pi3GYpy7LYdXWKt7eW09utI77Z2ewekc1f9nfSHGCgfsuzMDh8rCnupv5hbFEBCnYU9XF6XYp7+6rRyOXcOe0VJbPSsfh8lX3RAK8vqcWk9WFyeZk+GwV7Z5Z6by4s4bJaaFMSAohLVxLeesA7+5vICVUzXML8jna2M+ktBAcTi9SsYBIgL8dagow2W3otWBQSTlUb2RSSijXjI+nsddCqEbO9tNd9Jjt/OGrSt68fixdJjsHantp7LNw/cQEes0OKjtM/tZqn8VBaoSG1TvOIAggl6RzuLGfCSkhFMUHc9/Gcj8ZOtE2yB8vzyUqSMmN7x32CxryYnRMSgllyObC44UnN58mQidHwKe+rewwsb+2D51SgkQkcNmYaI41DfDkZl+6glom5r7ZGTy9pZJBqxO708uuym6yonWEaqQ8e0Ueaw82cbrdl1rxU1sXENh4tBWpSMRVxbFE65VYnW7MJhG5KQJ/mvwn1BI1eaF5I4hbgi6B9069R+tQK49PfHyEhUdFXwU35dxEeU8566rWMTlmMgszFnK69zRrytawsmQluWG5XBB7Ac+VPkfLUAvzkuYhFUm5fuv1eLwebi+4PYC0ARzqPMTtBbezu3k3Lx59kT9O/iNb6rfQZGqiJLoEs9PMb7J/w8nek2w6swkBgSvTr2R+ynzSgtMwKAxMiJzAO7PeodvaTYwmhu7hbpoGm3h12qscaD/AK8de4fb82wNIG0ClsZJF4kXckHUD+9r2Ea+NZ17yPGQiGXWOOj6s/BAAqUjKy9Ne5qnvn6JruMv3nLKuZ2PNRkqiS/io6iMWZy9mbeVaLk66mKWFS7G77SQHJWN32ZGJZDw0/iE+PP0hNreNhekLaR5qJk2fFkDaAFZ+v5JlY5dxXvR5nOw9GUBI3z31LvcU3cPRrqO0DrUGmDmDr2XdNdyFVqrl05pPWZyzmLqBOkqiSsgOyWZq7FS/YEEsiLku6zreLH+TgrCCXw1x+2fwz7RKfwM8gU8x6gVeIzBs3nv23y7gzn/1BkcxilH870N9j4UnvjjN9RMSGHa4yYjQsO5QM38/5vPUKm8dZGdlN09cks2Cwlh6h0ZmkfZZHKSGaYgMkvPkvBw+OtzCVyfaEQkC8wtjcLo9HKwzkhGpIz1cQ7hOzsuLxnCk0UhCiJo7Pzrut+Wo7THTZbIhEYuw2N2cbBtgV5WDglg9L+zwVYHumJbK6h01WJ0+cqaVS3j7xiLqeiy4PYGdDYfbQ4ROTrPRitPj5blt1SikIu6ZlcHhhj7WHWzipvOS+ORIKzsqugjTyLlzWirXjI9nV2VPwLXqeix8Wd7BoNXJ72eksuFIS4BdiNXpprSpn2uK47hmXBwyiQi5RMSG0ha2n+5ibLyeOXlRDNldvLjTR369XhAJApmRWgpigthf2zdiru9vB5vJiwkKUKGebDNxY0min4jZnB6ONQ/w+te13FSSiEQsoJSKuWdmOnU9FpJCVf62NPjawl+WtXNBehhfV3VjtNg50thPbbeZzMgMznQPkR2l47dTkhAQMDsCxRgyiQi7w8Uri8bw3LYqGvqGkYoF7piaitOSTL+7lh5pIzPiZ7C/bb+fRGUYMnB73dQO+Ihgv32k75hCrMDldhGuCsfj9QQoUafETEEhViAVSbk05VIUEgWdw53EaGPYdGaT32bk54Llf7g2wKB9kDfL32RlyUreOfUOm+s2E6wMJkmXxLrKdf71H1Z8SJw2DqPNyEP7HyJMGcbsxNlMjp7Muqp1fkHFrXm3+hMkfrD6+ClMThPJQclMjZvKRxUfUdZTRl5oXoD/m9Pj5HTfaabFTfN77u1o3EGDqYG8sDxO950mSBHEssJlrK1c65vdy7oOj9fDwc6DtFna0El1vHDBC/RYenjl+CvEaGMoDC8kUh3pn0EDX3vU7XHTbGr2z6P9GNsat7Fi4go2128mVBk6YiZQLVVjd/uMlg1yA8vHLmdS9CRO9p5kRvwMckJzcHlcyMQyNlRtwOK0/GyL99eMf4a4vY/PKFcAvsZHzip+ssYO1Hi93pG2x6MYxShG8QthtNiJ1ivRKiS4PV7UcgmfHW9DEOC68fEUJxgwqGW4vV5mZEdwoK53hD1GWoQGg1rGVUVx7K7uJjtKR4txmOMtA2w82so9s9IpijewemcNg1afVcOCsTFcPS6OY80DRAYpuDA7AqlYREqYmkc+O8WVRbEUxAWxq7IbsSBgc/kIUlq4hvKWAT9pAxiyuzjW1M/5aaHsqQ4kW0FKKXfPTGfV1iquGudzbf9NSSJv762j1+zg9WsK+aKsna1nlaSdJhsrvjzFW9cXcXlhNJ8dPzcAnh8bRKhGhsvjpTDOgMcbqGRNDdfQO2QnJVxDm9FKx4CVcUnBRGgV3DU9lcoOE4cb+tAppAHkLD1cw+ycCO7/+wkuLRhpsKtTSGgfHCmuaBuw+gmvQSXFepZEfnCwkecW5HPLlCRe/brW15aeMlLRd6bbzJVFseTHBtHa72sZ3jolmf1nekmN0KCRS3hvfyMLi2OZkRHOrqpu/7kn2wb5y2+KeWF7NQ19vr053V5e2X2Gx+dlIRZisaureer7p7gy/Ur0Cj2Rqki6hrt4//T7/tD30q5SZiXMYmfTTsBXcVoxcQVSkZTc0NwAsqEQK5gRP4Nht+9+QYogxkeO54OKD3ij7A0WZS5iV/MuAFqGWsgNzQ2o9s2Mn4lepgdgUcYiEnWJHO8+zrTYaRitRjKDM9nbNlLzt7d1L6cUp7gs5TJah1p5vex1ZGJZgAo2RZ/CykkrcXqcxGnjmBIzJSBwfU7SHBwuB13OLrQyLSaXid1Vu3nh/BdYkL6ACZETsLqsKCQKui3dvFXz1gj7EpEgIjkomc9rP8fitPDs5GeRiWUc7jjM68df58r0K3mz/E0cHgdysZynz3uaty98G7lEDl54atJTPLzvYfpsfSjEChbnLuYfDf9g6ZilhCvDRzzvSFUk9YP17GzayT3F91DZV+n3jvuhfezwOBgbPtZPop86+BSR6kj2NO+hOLI4wDtvVvwsYjWxI+7za8Y/YwfSBDQBCIIwDTj6c6rSUYxiFKP4VyE6SMnymWm8uvsMS6enUt9rQSwSuPm8JHKidUjFIt74to6y5gHGJwYzNz+Ku2el8+Y3dVgcvjblE/OyufOj435SBr58z5quISwON1UdJsQiAo7//VgbMzIjiAqSs2RKMi3GYcx2F/tqe3h8bhZPb6ngkblZlDUPsGxmGp6zTEevktL3I4+0H3C8ZYA5eZEMWp0cax5AI5dwz6x0bE4XVpGAVCKQF+urYMilIr/Pmk4pYWdFoH2H1wst/VaKE4LZeqoTlUzC8plp7DvTw5flvqpDuFbGCwvzeWFHDQ29FooTDNw8OQmRADqFFLEgEKKRoVdKyYrS0jpgJT8miC6TjXFJwTT2DTNkc7KwyDeX9sY3dTjdXsK1cjRyiZ+QiQS4oSSBHT+xGBEEUErFZ/ci5/YLUnh5d41//+FaORaHG6PF9zw1ipFfQT6RiQFBgL8eaCRSpyAnOoiWfguv7q5FJMAVY2Np7R/morwIQrVytp7qJDFExeLzkrDYXRxpGlkxc3u87KnpRh53CJfXxfrq9f5jq6asYlHGImQiGUn6JKqN1UyOnsykqEk4PU7CVGG8deIt2s3tzE2ay+MTH+d072k8eJAIEhoHG/mi9gsenvAwWSFZJAQl8PCEhzFajQgIrChZwZrja9jbupcHxj1AR2wH1cZqkvXJdA93Y/fYeWLiE2yq3RSwr0cnPMq4iHF8XP3xiEip5KBkmk3N2Fw2tjdtB0ApPqeOvCzlMrbUb/ETNbEg5rnzn6MgvICe4R4yDZkEK4OxuWx8fuZzWkwtTIqexPGu44QqQ5EJMh7Y+wBevESoInii5Aluy7+NN8rf8N/jxuwb2deyj4XpC3np6Es4PA7mp87nTP8ZDnUdYl7KPN468ZY/lN7utvP4gcf55JJPiFBH0G/rJ8OQwfPnP8+hzkO4vW6+qP0CvVxPYlAiCPjJNPjm76bFT6POWIfL62Jd5TruGHMHdredaE00dpedd06+wxWpV3BTzk0EKYJoMjXxVf1XLMlbQqOpkTBVGEsLlzLsHEYr01IcUUx6cPqIz8uvGb808urb/3rVKEYxilH83yEhVM3pDhOxBhUKqZhNx9pYMNZXhTnROsjnZW1+dei+2l4ajRbm5UVxQ0kCErEIh8tNTddQACkD2HSslRlZEXxZ3k5OdBDv7h8Ze2y02DGoZTy9vYIesx2DSsrvpqbSbLTw8MVZxOh9X44HanuZXxjDgrExfHWigzumpgS0/QAK4w28+U0dKy/N4VjzAF4vdAxaeWdfAyXJwTy7IJ+dFV08MieTaL2C389Ipa3fitvjJVqvpK4n8DeyQSWltNHIshlpdJrs2JweP2kD6B5y8NrXtdwwMR7jsJPMcC0ysUD3kJ36Hgt7z/RQGGfgqc0V/nk7kQCzsiJQSsVckh9FXLCKtQebGLQ5cbp9xPStvXXcfkEK/cMOZBKB3OggXthRw8V5UczOiWRXZRcRWjn3zc7AoJTyt1vGc7jByEs7awLMhXvM9gBfuH1nelhyfjIfft+IzelhfFIw0zMjcLhgYnIwPUM2sqOCeGlXDXqVlBXzsnl7bz0bj7by0JxMvB6BogQ9UrGI9kErj35+khcXjiErUkdFxznVJ/jINeAn2z9Gh7kDvVxPTX8NBzoOMD1uOh3DHTQNNZGgTeD+b+/H5fUpHlP1qRitRuJ18TSaGolSR7GlewuNpkb2tuwlKyQL8FXpflCALkxfyNTYqZgcJu7/9n7azG1EqCPY37afW/Nv5UTPCVL0KZzsPRmwr1ePvcr6eeu5JPkStjZs9StZDXID0+Kmsa9tHx9UfOBfL5fIiVZH025pJy80j6cPPe0/5va6WV26miX5S6jrr+OZw8/g8rgIUYRwb/G9vH/6ffpsfeSF5tFr6+Wj6o/853YNd/mEHcUPkqpPxeK0oJaqz35+RPy5/M9+ciYWxJzuO83cxLlo5VpyQnICPPJsbhtdli5O9p5kzfE1uL1ulo1dxpSYKTSaGnlw/INkh2QTqY7E5rJxe8Ht9Nv68eBBIVZgd9tJ0icRrgqnzdzGmrI1PDLhEeYlz8PtdTMzYSZ6uR6p2Pd+SwQJSomSL+q+4K4xd/GXU3/hu/bvCFeF88fJf6QgvGDE5+HXjl9qB4IgCBcCvwMygJ9qfL1erzflX7GxUYxiFP+70T5gZXpmOKfbBxEJIOClttuMTCIaYenRYrQik4h5ZfcZNHIJK+Zl0dg3so1nc3qQS0Qkh6qYkGxgf61uBNlKDtNwx0fHGDib4dk/7OTFndXcPTOd72r7uDgvkhcW5vPizhqe3Hyahy/K5KLcSESCwIp52byzrx6xSOCmSYnoFBJm50Rx7yflPD4vm9puMzql7wulKDGYE62D9JkdeDzw7LYqooKU3Dw5EbPNxfIZqSz/pNw/H1cQG4ROISFYI+flXWdwuD3cOW1knFKLcZi2ARvvHWjgxavG8IfPT/lfr0vyo+g96xP38u4a7C4Pz1yex6Zjrdz+t2MEq2U8cnEmyaFqJiQaWKuUMmh1YrK6eGFHNVFBCp66LIcPv2ukodfCmj215McGcdv5ycQYlMTqfbmR31Z3U5hgIDVcw/GWAZJD1dw9K51PS1soiNMTdPa6B+uNtA/YeG5BPh2DVsK0Ct7dX8+pNhPRQQoemJPJs/+o8nvIHajt5e6Z6Ty3vZrWfisbjjRzUU4U648043R7WTYjlSClhEXj43hhRzUmq48kXl4YQ123hWsnRPNKTaA4QCfTEamJ5Pkjz/srO6d6TzE/ZT4mh4kQZQhikZinSp6ivKecbU3bKAwvJFGXSKQqkm9av2Fs+FhiNDGoZCo6LZ3+lt2PEaYKI0wVxpL8JTyw9wEaBhuYHj+dvS17Ke8t5/b820ecY3aa2dOyh+ahZv488880mXzq45zgHCLUEXRYOohQRfjzVP9y6i8sH7uczfWbA5IafkCHpQOdTMfWxq3+v/XZ+tjdvJsQRQgaqYarM64eMXM2L3keMZoYht3D2N12Pq35lCvSrkAn1/H+qfe5MOFCZGIZpV2lNJoamZ00m/dOvedX3d5ddDfrK9dTEF7AoH0QAYFH9z/qv8cj+x9hzfQ1JOoS6bP1MeQYIkwZRq+tF41Ug81lw+K0YLKbqOirICski7dnvk2PtYcQZQiJukQ/UVNKAj3ZYrQx3D32bo50HaG8p5z5qfMJVYZyQewF/5bmu/DLDXgvBjYDu/D5tm0DVMB5+Nqp+/7js0cxilGM4p9HVpSOZeuPc2NJAg/NyeKpr04zM0vmb8X9GCIBihMN/Pm6sXQP2XhuezU3n5eEVCz4q0bgi4UKUUu5fmI8ZruLZTNTad9opck4jFwi4rdTfK22geHALz2b04NEJNDQZ6HH7GDrqU4evCgThUxMv8VBc98wGrkE8PLKojF0mWys2lbN5LRQInUKpmdFYHd5eHd/A7dfkEKkzveb1+3xkh/rq16FamTcMDGBVVurcbg9xAUrWX1VAS3GYaRiERmRWnZXdCIRi/3KUpVUjCAEGgJflBvJ3poeJqWE8PejLQEkd/OJDu69MJ0tJzt4Zn4uqeEa9lR1kx+rZ8jmoqpziPs3nuCNa8dS2tTP72ek8s7eBjpNNsK1cu6dlY5MLAqYJTzROsiJ1kHmj4khPljFTX89wlOX5nDnumM8Pi+bey9M58uydt7eW0dcsIr39jfw4tUF7KroorXfxkW5kXxX14fN6eHTo23UdvuqjO2DNh749AR3TEvxK4adbi/9w06UUjFRQXLaB2zIpSJcHi+3nZ9MfLCKE62DJIaqeWROFsZhB1FBCkQISMUCCWEubpTcyBe1X1BprCQlKJW7Cu+iduDMCHXj5vrN3FFwB1anlZtybmJ16Wr/miOdR1iQtoC80DyCFcEBlhT72/bz7JRnMSgMP/u5nhE/gw3zNtA81IxEkLD8m+VnP8Mi5GI5dve592t6/HS+afmG0q5SdjbuZN3F64jTxfmPT4ufhlQs5eF9DyMgUDdQR91AHXOT5qKQKEZEdk2MmugneT/G6b7T3J5/OxGqCBoHGzEoz+39tvzbqDJWoRAr2NW0C71Cz+8KfsdbJ97id2N+x5OTnuRw12EiVBEsHbMUpVTJYwce81cH97ftJzcklznJc9jVtIsEXQJGmxGD3OAXgUyKmkSbuY0TvSfwer28Vf4WdxTegdfrpcHUwNsn3iY/JJ87Cu8g3ZbO2oq17G7azSMTHglQg/Zb+zncdZg9zXvICM5gauxU1FK17z+Jmih9FGPCxhCniSNGN3Ju898Fv7Ti9jiwBrgbcAKPeb3eY4IgpAPbga3/2cmjGMUoRvHPoihez5+uyOONPXX0mu1cURhLYqiaD75r5LIx0QHRVIvPS2T1jmpqusy8eV0Ri89LIjtKy1s3FPHxoWa6THbm5EUiEQkkh2soaxnk48NNrJiXzaMXZyKViGgbsNFsHMbl8aKQirA5z9luiEUC0Xolp9tNxBqUNPSYqe+18Pbeen87Vi4R8fyVBTy1qJjCtQAAIABJREFUuYKl01Np7bey/nALEpGAQSUjTq9kwdhYwMtd01NJDFHxxp5aChN8X5LzC2N445taf1JDi9HK3RvKWD4znWe3VvHqojFcmBvFk1+cG2z/+7E2Vi3IZ82eWrpNdi4piGJObiRJoWoigxR0DNrQKqR+kQNATJCS4kQDG4+2cmlBNJtPdNA+YGNWdgRTM8J489t67C43p9tNHKw3Mr8wBr1Kisnq5LPjbSyZksS1E+I5UHeO6AgCFMbrOdpo5IlLstl8oh27y8tjn5/mzqkp1HSb+e2UJIKVMhYWxVLbbeFwYz+3nZ/CidZ+2gZsjInT83lZIKlwuD0jFLkSkUB+rI4uk50wjZysKB2/KUlgUkowJ1pNrN7pm6nLjNSyYGwsSqmIUI0ClUxMZriWflcCv818mNouOzUdHpo73XjlI9unIkFEmiENiUhCy1DLSGJXt5nckFzKussC/v5d+3fUDdRRHPnzVlxSsZSskCyyQrIo6y5DJpLh8DjYUL2Bu4vuZkv9FpqHmpkcPZlLUi7hd7t+B/iUrrUDtQHETS1Vk25I55EJj/h8z/SpZBgyiNREYrKb+OPkP/qjpoojipkUPcnf4vwxiiOK+aDiA9qG2nj2/GfpsHRwbea17G3bS89wD0URRawuXe0ngQa5gZemvcS2hm0BM3nZwdksKVgSYE6cpk+jzdzmD4FvHmqmtKuUJXlLeOX4K4gEEVdnXs2a42uYFDOJtKA0ErMT6R3uRSfTEa+J58bsG7G6rNy1+y7EIjHXZl5LRnAGy79Zzto5a4nWROPxetjZtJN+ez9x2jg2VG/gaOdRskOz+XP5n/37SQpK4unzniaG/z3ELRNYAXjw2YBIALxeb40gCCvxEbtP/pUbHMUoRvG/EwqZhOmZEUQFKThQ20tcsJqXd9Zw7YR4OgZtPDo3C68X9CoJ2052UdYyCECP2caXZe1MTc/nkc9OIRYJjI3XU9dtJilUjdvtISJIzuNzsznTbcbu9PDp0VbOnK30xBqUPDo3m5Vfnsbt8Z7NM01j/5keXwKDw82NkxIZsjkDZujsLg+by9uI0itQySQsKIrh70fbcHm89JjtpEdq+KysjboeC1lRWlLCNNwyJZlmo6+lq5CKMdkC7S28Xp+nneisk4PF5uKJS3M5WN+Hw+XBoJaxubydogQDwWoZe2t6mJ0TyfvfNfqFDiUpIVw9Lo4NR1rIjNRytLmfdYeauX92Bo99cdpPjL4sb2defhQ50To8XhifFMyuym7+dvCcY/4NExO4/+8nefKSbF6/tpD1h5uRiEVcnBtFapialn4rSWFqnG4vSpmEqelh5EbrmJUVTo/ZQd+wk5quIbyA1eGmssPE+iOtrJiXjdFiDxBA/ACJWOR/rJVLmJgcTGKIitYBK5eNiWb76Q6uLIrD44E3v63zr63qHOKZf1Ty8tVj2F/byxt76vh4yQTSDcXMX3vAH392qFbG01ePDcgMBbg261rcXjdh8jCGHOdixH6AIAjo5Dp/huiP4cFDh6UDiSAhTDUy8eEHhChCuDX/VtaUraHP1sfzR57nxuwbuST5Ek71nmLANhBQMfuhHfgDGgcbWbJjCZ3DPmIuEkS8MeMNIjWR6OQ6knRJPFD8AH22PpQSJY2mRuoH6rk+63rWV63H5XVRGF5IrCaWr+q/AmBP8x4KwgsoDC/kvJjzONB2gC31W/z7WJi+kHBVODXGGiLUESQFJdEw6FMyVxgrRrxW58eeHzCHB2B1WVFL1YSrwskwZLC2Yi1XZ15NpCqSMwNnsLqsxGpj+XPZn1lSsIQwZRirj64GwOV28dfTf+Xh8Q+ztGAp7eZ2ojXRVBurOdZ9jO1N24lURXLHmDvQSrXUDtSilqqxOC0ANAw2UNNfQ35Y/n/4vvza8UuJmwdweb1eryAIPUA85+Kv2oHR+bZRjGIU/zKIRQK5MXpSwzW0GIe5+bwkhp0uJiYHE6SUcuuHR+mznFNzhmvl9JodrL6qgJyYIP4wP4ejjQOc6R5iXFIwaeEaWo1WwoMUVHaYaOy1UBhvICtS6yduJckh9A3ZuHdWOhKRQG6sjn6Lk29rejnaPMAlBdEkh6pHqD4BeswOFp+XwHd1vUxKDqEwzoDN6SZar6C220LPkJ1H52ZxrKmfFuMwlR0mihMMXJwXicnqJFwrp/tHnnQSkYBUJHBDSQJflrdzpLGfFxbm85f9DdwzKz0gTgtgfKKBjw83+0kbwPd1fUxMCkYiFrj9ghTu3+jzxrK73COqWdtPd7JiXjZahZiooCAuzI5gx9nnWZxgQC0X0z1kp9fiIFgt4+riOCRigSCFFIVMzLyCaMQigfxYPbdMTvJf92RLP9tOd/p9+B66KJOcKB1NfRYWjI0hNVyNy60iVCNn5eZzblMLi2LJidJyaUE0QUopk1JD2Hi0jZ2VncglYu6bnY5WIeVgfR/5MUFYHG4EAWL0SgaGnZjtLix2F1qFBIfbw3v7G7huQnxAZm3HoIOvjrm4veB2moeaaRlqoTCiEJVExfun38doM3LXmLsIU4YFkLT5qfNJCUohVZ8aEGS+KGMRB9sPclflXSjECpaNXcbsxNloZIG+9Sd7TnKg/QClnaWsmrKKZlMzYaowRIIIu9vOFWlX+NuoANdn+Ux8v6j9ghBFCB6vhx5rj5+0AXi8Hl47/hpjwsaglqnRK/TILXJ2Ne3ieI8v6mlKzBSiNdHcU3wPUpGU79u/92eZAgw5hth0ZhPVxmruL76fBF2C37NuYbrPcPhT46eAz5duedFy3j7xtp8YWZwWZifM9itdbW4bKokqoAoHMOgYZGXJSjRSDZ/XfY5EkPDw/of960SCiFVTVrGvdR/1ppEiokOdhygOL0YhVuB0O1lbsdafu9pqbuXxA4+zsmQl+1v3c3Puzbx2/LWA1+nfGb+UuFUDiWcflwLLBUE4gM98916g8V+2s1GMYhSjOAuLw01TnxWZVIRKIcdkdRGjV/L8lfnct/EERouDGL2SVQvyyYvREaTyGWrmxxpIC9fSOWDD7HDRNmAlVCvnqc0VftXhB983cee0FFZemk1Vhwm1XMrLu8858j80J5NV26r8c2RVndXcd2E6OdE6Nh0PbO1dkh9FsErGeamhmGxOkkJVqGQS3F4vOyq6WHxeEq/uOuNXWpa3DnLrlCTUMglROgWPz8vmqc0+NatGLuHhOZm43F5OtA2y+2yg++7KbmL0StoGrCSGqGjsG+aq4jjigpUkhqj4w1eVI14/q9PNW9cV0WmyoZJJGLQ6EYtEI9aFaeSkhWto6rPQM+QgXCdn1VnhQFXnEG9+W8+lBVE09ll4/IvT/vPSIzSsX1KCWPTzJq9DdreftAF8dbKdR+ZkUtk5xPvfNRIXrOIv+xqI1iu5f3YGVqcbuUREhFbBjopues12zDYnKmk4MomAzenhhomJeDxe3txbx8Cwk2vGx7FgbAzJYRpqu82EaeUopCLcXg/hWjl6lZQuk53KziG/OOIHxIW6WXlwJX+Y9AeOdB3h+SPP4/K4uDztclQWFR3mDm7IvoE+ax/1g/VMjZvK2IixpOhTeHzi46yvXs+upl1Mip5ErDaWF0pf8L3uLisrv19JhDqCyTGT/fcbdg7z6rFXyQvL42j3UQ51HuLy1MuJ18WjFCuJ1kYTrgrniZInONh+kIlRE9lcv5k7d/s87iUiCc+c9wzdw+c87H5Ar7UXu9uOGjUx2hjqB+u5KuMqJkZP9H3mespZU76G3JBc5qfO5+uWrwPOHxM+hteOv4bb6+ZI1xEuTrqYOUlzeOfkO0SoIvykDXw5r+ur1jM7cTabzmwiVBlKjDqG3OxcxkaMpcfaQ7AimNvyb+P50uf958VqYzE5TBhtRj6r/YzzY8+nzdwWQO48Xg/rq9azJH8J2xu3j0i6iNXE0jncidlppnu4m380/CPguMfroc3cRlFkEVaX1a+21cl0pBv+vew/fopfStzWAVlnHz+BT6TwQ23ZDVz7L9rXKEYxilEAvsrQ29/W89bec7+6Z2aFc0FGAemROjYvPY9+i69aFa4bGWY9ZHOx6Xgbb++rRyER8di87BFWEe/ua+CRizNJDdfy8aFzyX3Bahlt/dYRqQFflLXz2Nws7r0wnQ1HWrC7PFxRGENtj5nCuCCsTi/npYbyTXUPT39VybDDxT0XpmOyupBKREyJD6Wpb5hm4zBrDzZx06REVm2vRiuXcGVRLEUJBgwqKVtOdvLR4cAkwbpuMysuyebpryq4dEw0sXolfz/exielLWREaJmQFMzmE4Fu8tlROh77/BQur5frJyawZk8tvUN2MiO1VHX6WluCAEvOT+aBjSdYUBRLRqSWvx1s5sJsO/mxeqKDFDy7IA+xIHD/xhMB16/pMtMzZCdYPdKBvmPQisP1kwqHF+p7h/0k0+XxMmR3Ud01FJBHunR6KlWdJm6YGI9GLsXucjM3P4qvTnSQGKJk2+kuv5DkQG0fVxfHBpwfH6zksblZ/GlrFTMyw4kPUbOxtJVn5ufyeVkb39b04HR7SQ4J5ZagW6jqq8LkMPkVmZvObGJp4VI6hzvZ07IHgAlRE/4Pe+cdGGV9//HX7ZWbuVz23gmEGfaSjSLiRKutoxUnwwpaq63WuuqurVUclWpr3bgHIEOG7BHInmQnl9zO7fH74+Agxm5ba395/QXPfZ/nvvdw3H3uM95vxprGkquNFpiytFmsHb+W68quQyQQcfVnVw+5B7s6dg0K3AYCA9RYa+jz9nF+3vm8WfcmGxo2sKFhA6MTRvPEWU+gl+uZmzmXuZlz2dm+c1CAFQwH+c2R37BqzKohAwiXFl2KQWGI/X1i8kQOdh/E4XfwXMVz9Hv7KYkvYVH2Ija1bOJnk37GG7VvIEDAJYWX8EHTBzGR3c9bP+eE4wR3TbwLjVSDN3Q6U3mKXncvmZpMFucs5tycc2m2NxMhgifoIVGZyN6uvUxInsCdE++kyd6EVqolEI5myK4ZeQ2bTmyi1FCKJ+AZcm27z05FXwULshawtW1rbJghRZVCWUIZ9++5n3Nzz0UhVpCgTBg0DQvRAFcj1dBoa2TlmJVsat3E5cWXM9r03TKV/yr/qI7b02f8+aBAIBgJLCLqVbo5Eol81VFhmGGGGeZfoqVvgOd3DC6VbK7upb7XRXmWgVSdklTd159rd/vZVmfmN1ujGTSDSjpIR+wUF49PRywU0tDrYNmEdI602fj4WDeBYBiZZGhmSiUT88c9JxibZWBSTjzlWXqe/6IJo1pGXpIajVzK3qZ+Vr12unH98Mky6/mjU2izepiRbyRRK+elXc3MLDDh8AQIR2BafjyBYITKTgejM7S8um/wc5dnG1j558PccXYxyRoZdk+AvU1R05raHidnlyUzKs3N0XY7IqGAS8an4faH6DopqXHwhIXbFhTSZnGzak4+Tm+QAX8QjVxCr9PLlVOzkJyROdtY1cPGqh6StHKKk9QxaY4zSdLI0StP91/1OLxUddpjE6C+QIg0vSLmhDA6Xc/uhtPN/o29LkamajnWYY8dk4mFiIQCFpYmkaRRUN/rRCoWUZKs5vkfjAME1PWc7qeaV5LIs9sHv09aLR6qupxEIjA110ib1cPMwgQe3ViLXinlkYtGIRKATm3hSGcf+7r3MdI4krOzz+bpI08TjoTxhXwUxxfzeu3rRIhgVBi5+rOr+e3s35Knz6Pd2Y5IICJdnY7D7+Cigovo9/QjEUp4p/4dOgc6SVUPboTXyXXMy5zHm3VvkqHOYMWYFVFXhfgRTE2dilFhHLTe4htqStTh7KB3oJdHZz7Kuop1WLwWLi++nCW5Swatk4qkTE6dTHF8MamqVGqsNdRaa3n84OOcn3c+h3sO8+NxP+a9hvfI0eQMyWyFIiHern+bGakzUElVCAXCQaXGuZlzGRE/gkmJk2h1tuIL+1i5dWXs8V9O/iUGhYHj/ccp1BdikBvoGehhednyWJZMIpJQYCgYFITOTpvNhYUX0uZsY0P9Bn4x5ReYPWYC4QAmhYnXa19nWeEysjRZyMVybht/G7duvzV2fomhBJ1MR1V/FVNTp5KoSGT12NUkq5KH3MvvGv+wjtuZRCKRduD5b2gvwwwzzDBD8AXDhIcO/eE9w17qL9Fp97CjLtqXlG+K4/KJmWQZleiUklimZsmoFOq6nYOa8C8Zl8bPFxdjcQcoTdbwuqwtVt4UCOCcsmQe/rSG4hQNbx1sJy8hjjarh7sWl6CRR7NOZwYhEO276rS6KU3V4g9FyDAoKEpS88slpXxc0Ulhkpo0nYIuu5dffliNLxhmYWkit8zN57kvmghFIlw0Lp0OmweHN8h9H1bx6MVlBL5yc57cXMeiEUn8aHoOoXCY53c0k6CWIRYKCIYj7GmysKfJQoJaxoyCBMKREBKhAK1CjEahpsfuwaSR4vGHUMvEOH1B9EoJ107Pps3qISdBxTVTs/j9rhYgGmD96qIyTBo5Vref2i4HD39Wy6FWGxDt07vznCJunVfAJ8e7OXjCikwsIFV/Oju6saqHtQsKUcvF7G7sJyteyQ8mZ1HdaWdibjxXvnTayL4gMY7zx6SSbVQxu9DEn/e3xfZxyoLsTCIRuGFWLi/ubGR6gSkW3LX0uzn6xhFevKaURw7fSbMj2mDf5mwjT5fHktwlvNvwLpnqTHwhH1KRlCW5SzC7zdh8Nhrtjbxw7AW2tW9DKBDy0wk/ZWfnTra1bYu+boGYW8bdwpu1bzIlecqgPUmEEn5Q8gM6XB1sadvCnq49rBm/hkXZi4b0wgFkqjOHHJuUPIntHdtZNWYVLy14CX/Ij1FpHLLuFDq5jjJTGWKRGI1Mw6y0WSglSo72HuWXe3/J3Iy57OvZxyMzHuHBfQ/S4+6hUF/IeXnn8ULFC1yQfwFN9ibWjl/LqzWv0j3QzZyMOVyUfxHrjq7jgvwLCEQCPHv0dL9ckiIJgVDAowcfZXHOYroGurD5bBQaCgk7wqTGpRIniWNr21YuKbiEteVrOeE4QbGhmO3t22Ol4SkpU9jTtYc9XXt4cNqDNNmbuH7U9RQaCpGLo++jWemzeGbuMzTYGhAgQCfXsa9rH+81vse7De9ye/nt/Gr/r5iXOY+VY1eSqRl6T78r/M3ATSAQnJog/XuIRCKRfykYHGaYYYY5k0yDknGZeg6eYWNkUsvITRj6BXcmzX0uDrVYSTcomZitZ8moVO567zhnFSbwwPkjeftQO429LqbmxXP724MV69861M6qOfn8dksDeqWERy8exeE2K3ZPgMx4FW/sbyMQiqCUiHhi2SgEwPqry5mUEx+7RoJaFvuzQSVlen48R9rs/OLD08bZ6QYFD19QRo/TyysnS7QmtYxb5xfywMfVfFrZQ6fNw7rvj2NHfR8bq3po7jvZBO4PYXUH0Ckkg+RLIpGojVeyRk6j2cWt8wvZXtvDjbPyeGpLfey55xSZeGlXM1PyjHgCIZJ1Cg63WDjYZuPskclo5GIum5hBZrwSmUhIu81DMByhw+ahw+bh5WvG0+/y02X30WP3MOAN8tz2JoxqaSxog2gZ9NW9bRQnazh7RBJzi020Wz1MzDHw+v42HN4goXCEJzfXsf6qCfxoeja+YJj6HielqVqe3tIwKHCv63HhD0V45LM67l9aSkv/AF82WfiizszF49IHlZbjZGKKktT0Oj2sXVDEz98fXBQKR+DwCQd9nr5BxxtsDczLmMd1ZddRqC/keP9xvlf0Pba0beGE4wSJykQarA1sa9928jphbD5bLGgDCEaC/Lnmzzwy8xH2dO3hUO8higxFFBoKkQglZGmzeHzW43S6OpGKpKSr0xEKhmZ3AYoMRdw/7X4e3v8wdp+dsaaxTEieQJuzjUJDYdT38+9AL9czNXUqU5mKxWPB7DGTqclklGkUQoEQIUKkQimPznyUY33HONp7lA8aPuD+afejEqvI1+Vj89m4afRNhMIh5CI5Ozp2sLxsOc6AE5/Phyd4uuR577R7eWT/I5yXex6/PvTrWDZsaspULim4BIvXgkFuYHLKZGw+GwqxglpLLU22JmakR/ve6qx17O7cTYG+gD5PH66Ai8W5i+l0dVJhrsAf8iMSiIiTxuEP+RmbMJZjfcfodHaSoEwgU5PJCccJjvcfJ1WdysYTGxEKhNw39b6/+779t/H3BFn38vcHbsMMM8ww3yhapZSHLyzjD7tb2FTdw/hMPTfMyiNFp/iL54TCEV7e3UKSVoFYJOCH06O9W5EIbKkxc7zDwY+mZ3PNlCyqu4dKPYQjpw3rre4AN716iGevGMsdG45jPjn1maqVk5+oJlkjwx+MUJCkRiA4XWIck6GnMDGO2h4Xc4pNSESiIaW8NouHfSeszCwwsbEq2mje6/RxoMUSs/eq6HDg8YdYv7sFgQC+NyEDQ5wUyUltuQc/qeEXS0p5dW8r9b0uZheZuKw8ncpOB+YBHzZPgDlFifS6fKyZX4g3GG3839PUz74WK1dNzeKVPa28uLOZhaVJlKZo+fl7ldy+sBCVVMT+ZgvvntTM0yjE/OqCMoQCARsOd9FojparB/xBDrdZyTPFfW0ptc3qZlahiQhw28kgOe2Qgt99byy1PU58J6VN+lxeOmxe3jrYzvR8I2l6Bd1fcckACIbCNJpd7GrsZ1S6jlVz81HLxegUUvQqCZuqesgwKJldZOKOdyrIiFcxs8CIXiGh9SvXUsoEMbumMxmXOI6RxpEopUp6Pb3c8+U9sceK44vZ27130Pqvu0aHq4OtrVt57thzAJiUJm4dfysTkyYSr4hHJVENEpD9S8jEMpbkLqFAV0CLo4VqSzVamZbFOYv/6eDDoDDEeuG+ugdP0EOCIoGJSRNRS9Ukx50uL9p9dhqsDdh8NpQSJeWJ5bS52vjFl79gad7SWKAEECeJY0LSBF6pemVQH96uzl0szllMZX90wOVg90F+Nvln3LHzjtia/T37uXX8rTx2ICoDUt1fTbYmG5FQRJerixeOvUAkEuHt+rdjfqo3jLqBT5o/oSyhjKePPo1MJGNZ4bLY/QqEoln2jSc2smrsKtLU3y1z+VP8PSbz9/wH9jHMMMMM8xfJNcXx83NLWDU3nzi5GJl4qHtCn9NLh9WNSBRV0hcI4HiHnaa+AVK0ikFuCL1OHw98XMOqOfm4fEESNbJBDgPjM/XUdJ8eYAiGI9i9Qe5YVMSeJgt6pYSpefHUdjt562A7hUlqDrfbmFWYQLYxmgnMMCj5/VXlHO90IBEK8ARCX1veDYXDqGRibpiZg0Iqig1CzC1J5Neb6zHGSdla08tPFhYhEgp4bkcT7VYPSqmIG2bmcsWEDNqtHvIT4xifZcDtD/L24Q7eOWOKc+WcPOYUmvjZu5V4zthDnimOTpuXOJmYtfMLef9oJ3qllBWz89AqpJg0Ml7+8nQJ2eEJsu6LJvISVGw4OVFb0W5nyagUDrc2MCE7HqloaNZoTpGJ3Y19jMnQoZCIUEhFXDohgz0tFpQSEaPStLx5sIMPKjqRioScOyqZRI2cddubWVCaNEiYV3jSyF4mFhKJgFAg4KVdLaz7flTw1hgnI9sYR4/Dy083RPu15pji+Kyyhxtn5XLLG0dj99igkqLTWpiYPDEmeQFwdvbZjDCOQClVAtEg7slZT/L8seeJEGFZ4TK2t22nzloXO0cmkg0ZFJiSMoVgOMjysuX0efr4tPlTGqwNSIVS5mbOHXKf/hZF8UUUxRexMHvhP3zuP4JCrBjSl3cKrUzLuKRxAPQO9FJnrWND/QYAPm76mNXjVvNew3vUWmup6a+h1FjKn2r+NOQ6Z06QFsUX8V7je0PWHDcfj+nE5emj9m4mhYkqSxXJqmSeOvxUbG2Pu4cPGj+g1FjKwZ6DlMaXUtlfyctVL7NqzCqKDEUIBUIUYgWCiOBrLcG+KwyXNYcZZpjvBGKRkPg4GQP+IFa7F71KEgvgms1OKjocuP0h1m1vpKXfzaQcA1dOzuLJzXXYPQFGpGo43nH6y0IiElCYpOZAi4U7FhWzrbaXw202ZhQYSYiT8/imukFrlRIRlV0Ottf14vQGGZuh461DHRQmqvnkWDcj07TolZJY4AaQqleSqlfS0OPA5g1w0bg0Xtt/2iszapMV7dcTi4S8caA91sAvFgp4YtkowmGwuP3km+K4+/3K2ONuf4jHN9fx1KWjiQjgN1uiAxi3zCvgiTP2DrBuexPT8ow8evEoHt1YS3PfAOMydJxdlsxDn9QQCEXYVNXDPeeWIhTCb7c00Ov0oVNKuGFmLi/taoll0io77UzKMQy6/gcVnaxdUEhjr4uqLgdr5heyfnczlgE/ZxWZWFCaRFPfACqpiOtm5qCSiXl8Y10siFTLxKyYk8e7RyJ4wiF6HT5qup3U9jiZUZDARWPT+PBYJ4kaOZdPzOT1/a1cMzWLUWlaNhzpoDzr9H5Gp+l4fX9bbFo2SSMnJyGOtw91IADeWD6Zfc0WpNIgGm0Pu83vYJAbuGHUDXS6Oik0FDI7YzYq6WmHAaVEyZzMOUxOmRz7e6IykR0dO2IWUo3WRh6c/iAP738Yi9fCtNRpXFZ4Gesq1lHRV0GKKoWbRt+Ey+/iSO+Rfypw+2/DqDRS2V8Zmzb1h/08fuBx5mTM4ful30chUpAal8rklMl82fll7DyRQBTTfTt1nlamHXJ9uTiq0VZsKGZS8iQkQgmN9kY8AQ9y0dAJ8iPmI1xRcgWvVr/KlaVXxjJ6YqGYRmsjicpEXjr+EhCVJElRpXwny6XDgdswwwzzneFYu41ffVrLkTYbMwsSuGVePh5/iB6Hj+a+AZ7Z1hjz8dzTZMHtCzKr0IRYKOC8UalIRUIOtdpI1sq5Zlo2939UjTcQIhyO8L2JGUzLMyKXCBEIBLHGfLlEyE8XFfPJsU4StUp6HD7Ks/TsbbawZl4Bv/yomun5Rkamahnwff2Zm4C7AAAgAElEQVTAhFAgIEklZdHIJExqGZ9WdpNuUDI5Jx6b24/F5UcqEsaCMohm+X6/swWtUsK2WjO3zMun0Tww6LqRSDQL1n+G4G4wNFRc1BcM4/YF+em7FdyxMKroJBYKONJmGyTC6w+FeG5rU0zA1+YO8PimOq6bmcNTJ7XtpuYaqWgfPHghEgjwBkKkG5S8faiDLnsT55alUJamZUtNLytPTtem6RX86vyRvH24Y1Dmz+kL0mX3sqw8nUMnrEzI1tNoHqCi3c7zO5ooTFRz1znFpGgVHO+0c/6YNLbV9hIIR/AFwswrSYxda3SGjocvHElzv5sm8wAuX5Bfb65Hq5BQlKylMElNebYBT9DDwe4+RgtGIxaKMbvNzEybyQjjiEGlweh98XOk9wgfNH6AVCRlce5iyoxlrF+4niZ7E2KhmFxtLvGKeMYnjscddKORaLhx841UWaN9dZ0DnTx56EkenhHtU/tfQCgQopKoWJK7JKZdF4wE2dy6mREJI/CKvMTL4lkxegVSoZQv2r8gSZXELWNvGZQta3e2c2XJlWxv3x6bWJUIJczPnM/MtJlANKN52xe3YfNF+ycfmPbAkP2MMI7A7rOTFJc0qG/RF/Lx2yO/RSqUsnLsSh498CiPHHiEbG32oAGH7wrDgdswwwzznaDd6ubKl/YjFgpYPiOb0hQtzX0D9Dh8WAb8KKWnzddPUdHhYOXcAqSiqGjropFJXD4xkwyDglf3tSKXCDlvdAqj0rXc/1E1P5yajVAAmyq7+M33xtDr9CJAwEcVHVwxKZs9zX3cdU4xnTYPv9/VwrhMPT9fXMy2OjNbanpZNDKJqk4bJSlRfZKaLgd7GvvRx0koTtJQ0WZjcq6BqXnxWAcChCIRAsEwSVo59T1O1swv5JltDWgUEpaOTkUlE2FQSTnYYsXs8A0p6UK076xvwI9CIsITiLohfNU6Kt2goH8gwIpZ+TyxuY4ehw+pSMjCEUnceXYxv/woqqcmFAgGuS5ANOg7VVrMM8Vx8+xc7tgwWDJiWXk6n1f3UpKsYXaRiS01vbyy5wQjUjVcNyOXjVU9hMIR2q0edjb20WUfqtnV6/By9ZQs5hWZTva8ydhU1YPDG9V3e3prI8vK02OG89HXpeSJZaPQKE7rxwkEAsrSo8LLh9U2vqgzs3ZBIdMLjBQmqWPrFGIF09KmMS1tGn+Lgz0HWb5pOQA6mY5EVSL11nrkYjkl8SXk6fJiaxNV0SCysq8yFrSdIhAO0OvuZXra9L/5nN8VSuJL8If83DP5Ht6pfweVRMXczLmoJCoy1ZmMSBgBwKMzH8XsMaMUK1GIFWjlWra2biVBkcD4pPGkKFNYv3A921q3IRFJYkG0QCAgGA5y1867YkEbQKerkwvyL2BD/QYiREhQJLAgawEWr4XvFX6P3xyJOiXMSJ1BsiqZG0bdwKs1r+IP+bl13K24g25sPhufNH3CvKx5XzvN+9+KIPJVZcn/IcaPHx85cODAt72NYYYZ5htgR72Zpz6vZ15JIr/d2oBQIODqKVkka+VoFVI8gSCrXz866By1LDoZOSnHgM8fJlknj/YgRQQIBRGUcjFSkZD9LVY2VvZQ1+vkjkVFaOUSvqjvQyERkZOgQq+Scu3LBzhvVCpJWhmBUASRUEBeQhx3vXccmzvAmHQdOqWU6flG5habSNTI2XCoA4lYSL/LS1ZCHH/cc4Iv6gZPMM4pNlGaHJUVcQdCrJydh8sX4tntjbj9IRLiZKyel89Tm+u5aXYe939UHQtQr5uRQ7vVzZdNFm46KzeWZbx8UgaPfFZHc98AI1I1XDAmja013aTqVby2v40Z+UbKsw3saeonUSNnRIqWp7c28OjFo7jp1UO4/aezYUIBPHnpaNotHsrStNz7QSVzS5IQCKDJPEB5lgG9UsLuxn4+OtbFgpJEFoxIRiYWkKCWcazdRt9AAH8wjFgkJEElRSAUcMc7gyd5n//BOOaVJHGkzcrSp3ejlom5eloWAgSIhAJyE1Ssfv0IgdDp76zHLh7FheP+vQ3mwXCQVVtW8UVHtAduzfg1PH3k6dj0pEaq4cUFL1JkKBp0XkVvBddvvh5nYPDwy+/m/I7JKZMRC/938iaBUICq/irEAjFhwpxwnEAj0TA5dfIQf9V/hkpzJT/Z+RNaHC2xYxKhhMdmPkaDrQFfyIfT70QpUTImYQwOvwNvyIvT7+RY3zE2ndiEUqzk/mn380btG3zZFS3bTkqexDnZ55CmTmN80vh/eZ/fBAKB4GAkEvmrmxHdc889/6Ht/Od57rnn7lm+fPm3vY1hhhnmG8DhCZCmV/D+0S6unpzJxePSkElEVHc7EAgEZBtV+AJh6npcsXPuPKcYAaCSiei0e0nVKSAiYEymniStgniVDJ1SSq4pjvGZBr4/MZORaTrSDEpyjCoMcVJuf6uCKXnxTMmNJxiOMOALs6/FwifHuzinLIWd9WZumVdAj9NHn8tHsk5O/EmhX28oTJ/LT0a8ihv/dIgrJmayq7GfucWJzC9JRCYRMjnHiDcQ4ssmCy5fkIvHp3PPB1UxtwH3STP2yydmMOANMjXPyMQcA2cVmUjXy3H5QiflMPpQSkUYlFIS4uQIBDCnOJFgOML63S1MzUugstOBJxBi4YgkntxcT5vFQ3WXk73N/Ty5bDQvf9nCktGp7Gu2EIlENevWzC8gEAzTYfOQplfyYUU32+vM1PW4uHRCBg98XM28kkR8gRArZuczPstAcZKGklQtJo0cAQIe31TLiFQtoXAETyDE6HQto9N1VHU50Ckl/PzcEmYVmJBJRKhkYtotbo51OtjbbGFvswW9SoJYJCRNr6Sm24lULOS6mTkUJanJiFd9/RvmGyIcCfNh04e0OdvI1+XjD/mptZ52Z/CFfOjleiYmTxx0XpujjQRVAvu798eOzcucR3V/NYd7D5Otzf7avq7vIiKhiCRVEr6QD5vfRoYmg5EJI7+RoK3J1sSaL9ZQnlROVf/pDGY4EqbYUIzVZ6U0vpRQJMT29u2sr1pPOBImS5PFg/uimm8QzbAmq5J5t/Hd2DXaXe3kaHNQSVSx4Ydvm1/84hdd99xzz3N/bc3/Tsg/zDD/Q4T9fiKhEBG/n4jXi9hoRCAaOkn5/4Wabgd7m/pI1CoRCQVsq+9jQpZhkMl6ukHBA0tHMi3fiC8Qza4JAJdPTH3PAK/ubcUyPpXrZ+YOub5MLCLdoBx0LFmnwKCScv/5I0/2vAnYVHWCRrOLqXlGVszO56nNdfx4XgE/e68ylgU73uFALhExJSee321toMk8wC3zCgiGI+xs6GPdFeP4zZZ6ttX2MiknnkStDLvHH+v5srkDQ8zfu+xe8kxquuxewpEIz2xuxOkL8tglo1BJxVw2IZ13DnXQ5/SzsDSZYDjCtlozloFo2VMggPIsAya1jJZ+d2wi9BTeQJj6HhdfNllo6Xezck4+/mCYDL0CpVRIvXkAQ5yMn7xdwY1n5XHvh1XYPQGc3gD5iXEopWLWLizmq/S7fFjcPn56djE3v3o4do/qe51cPzOPl64uRyQQkKSVo5ZHv+TVcgk/WVTEmAw9tT1OUrRymvoGeGxjHb9YUsqqOfkEQmE+qujk3LKUf+Rt9E8hFoq5ovgKdnfuRivT0u/tH7Km3dk+5FhSXBK7Du9ixZgVqMQqXAEXVf1VMeuqQDjAnRPv/EaCm/8W0jXppGvSv9Fr1lvraXG0MDN9JjPSZrCjfQdioZgL8i/giPkIZo+ZTlcnm1o3xc7Z2raVScmTBrk8ZGmyOGo+OuT6R81HWZj1753S/aYZDtyGGea/iEgwiPvAQfpfeJ6Q1YbuogsRJSTgra4hbtIkwh43kuxsZOnf7IfjfytmpxezMzp4oFXKqO5ycKTNxmUTMvjdtsZBa9ssHg61Wsk6mYF551A7nxzvASBRLeOpy0Yz4Avy8u4WDCopMwoSSDf89WyNTCIiSSvnRL+bW944EhO53VLTi80dICNeidsfGtJb9/udzcjFQuYWJxIpBt3JHqzCJDW3vnk0ZnC+o76PLpuXUenRzItUJCT+a/w+9UoJ4UiEez+sQiMXc+XULF7f34bHHyRJK0elEPPLpaVUtNt562Bb1Mz+0tHsbbZgcwdI1Sn43bYGpuYZGZGi4VCrdchzCIXw00XFPL65jic21TGrMIGxGTquffkAEYj1uX16vJvpeUbGZupx+oIY42T0u/zU9ThpMrtw+0PkJ6rJMihoNg/gC4ZxeAJoFWKWjkkj26jCGwjx/I4mttb2cvWUbDqtbn4wJYuRadHewFS9kql5Rt4/2sFbB9sJhSMsHJGExx/isU11ZMYruW/pCAoS1UNex7+D8qRynpn7DG/Xvc1o02gO9hwc9PjXffGnqdNYW76WX+37FZNTJrOuYt2gx99reI/lZctJifv3B5/fZUTC6A/WP1T+gfGJ41letpwCfQHV/dV82P0hVxRfwdv1bw85r9fdS5wkLiY70uZsY1nhMvZ07Rm0bmziWNLV363P0+HAbZhhvkUC3d0EOjsR6XRIMzPxHD9O6zXXQDgaCPQ0NhJ/440ox40DlQqCAQa2f4ErFEKamYHIaERRUoJA+PWK698FQuEIZpcXhURMnExMS/8A1gEfA74QQoGAX31aw/HO6IevXinhx/MKyIpX8coZ+mKnCEeg3uzijf1tXDQuDeghTa/g6qlZ3PzqYUKRCFkGJVdOzeL5Hc3ceU7x12rCQdRvc8PhDlJ1clotnljQdopDrVYePH8EDu9Q71O5RER8nIz7P65h6egUJmQZGJGiJkkjjwVtp2gwu7ikPI3ZRQmcPyaN2m47K+fk85st9UQiUSunu84pQSSA1XPzkYqFjEjRMDZdh8sXJF0v53CbnaJEDckaBROyDLT2D1DbE+bFnc3IxEKsJzXslFIRmXoFP5qezc/erYztQSkVIRQIkEmErJidRygcQasQ0233DrEb67B5WHVyf62WaJ/Xtlozl4xPo7LTQYZBidsf5MWdTZjUcqQiIbYBH08sG8Pq145gdkWHK8Zn6rnr7GK67F7GZhpotbhJ1yvQqaLyDIVJatZdMZ6mvgFkYiF5pjgkIiGLRiYRJxMTH/efk3GQi+VMS53G1JSp2Hw2pEIpzx17DpFAxE1jbvqL/VFlCWU8O/fZWE/VmcQr4pGJvntSFP9pklRJjEscx8GegxzoOcCBngP8cMQPOS/3PM7JOYcB/wBtzraY7+kpcrQ5XFV6FS8dfwlPyMOi7EXMzpjNnq49HDFHp5zLjGUszlk8SPrlu8Bw4DbMMN8SA/v20XnrGoJmMwKJBNNPbo8GYOEwIr0ew1VXEna6iLgHCDudBG1WfNXVBFrb8Bw6hCQrC8M11+A5dgzlqFHf9sv5p2izuFm/u5k9Tf0sKk1mVqGRox0O+pw+0gxKbO4Al03M4EibjTcPtGN1BzjUauVEv4slo1N462C0RDUxO2r2nmeKo8PmodfpQyaOBrM/mp7Nn/ac4NrpOXTaPeQYVaRoFYRSI2yu6iFBLaO+x0U4EkGrkDA1z0h8nIxPj3XRbnGToVeglg/9qFRJReSa4tjV0IdBJcUy4CdVp2BZeToGlZQOq4elo1OIj5Ox4VA7dywqjmmLnYlEJKAkWUNlh50Vfz4MQGmKhocvLEMiEqBXSem0evAFw6TrFdz57nEkQiEr5uTFXAVMGjmv7jvB/JIkGswuDjRbOG9MKvNLTovXGlRSrpuRy61vHmV0uo4nl43m4+NdJKnlnFVkotns4ufvVeI/Q07khlm5pBsUtFlOT4FeMCYVhVQUC9pO8c6hDl66upxdDX3cdUZQmGNUcf6YVP6450QsaAMYl6nnuR1NNPQOxO7n764Yx9gMXaxsmqiVk6gdLNWQ+W/uaftrCAQC9HI9lxVfxryseQgRxtwH/hJqmZoyY1lMEPYUP5nwE+IV8X/lzGEgWuKckz6HycmT8QQ9qCQqAqEAJpUJlST6XpBL5NRaa2m0RbPw5+edT7+nn4M9B3lk5iMkqZLI1GQiFop5avZTNNujvrRZ2iwM8r/+7/ffyPBU6TDDfAv4mppou+FGAicGZ41Sn3ySjtWrMd22Fteu3ShHjSISCuHatYuEm27EW1OLvKgQz+EjeI4eRTF2LKqpU5BmZSEx/mWD6f9GAsEwd79fiSFOSoZBid3tQy2X8sTmOi4tz+DXn5+WfSjP0pOmV7LhcAe5CSoKk9TolVKkYiGpOgW7G/vZWtsbncCcm8/vd7Vwzshkfv15PfcvHYEnEOKZ7Y1cPzOXmi4HHTYPk3Piqeiw09oftWN6bV8rt8wrwO0PMjknns9rennvSCcJaik/nlfA73e1sK3WHNvTbQsLqe6wo5JLSNEpcHoD5JnU3LnhGMGTaarxmXomZOuRi4X0uwM0mQdQycR8erw7dp0bZ+UyLlPPD/8w+LNKLBTwh2smsOLPh2O9avEqKbcvKuK2tyo4b3QKxzvsXDYhgzSdnL6BAFKRAJNahtnlR6+UYB0I0OXwEgyHSdUpONhi5Y2D7ayYncfGym7EIiEOb4BAMMLdS0q44Y+HBu1BIxfz5KWjufWNo7h8QZaOSWVClgGpSMiq148MWisSCnjm8rHc/OrhQcEfwC+WlPLCzqZYACgTC/nR9Bye3towaN30fCNj0nVcPjGDRO1ftjT7LtLl6qKyvxK7z06uLpeS+BKkoqFl8WGG0uvu5VDPIWosNRTHFzPGNAaT0jRojcVjodXZilwsRylW0uHqQCfTkaPN+U6J7P49U6XDGbdhhvkbRCIRIsEgQsk/10QciUTwVtfgq61BKJcjLy3F39o6JGgDCHvcyIqLEShVCKUS+p55BkQidEuX4m9tJeL30fvoY/gbo78s3Xv34mtsJP7aH33nArcepxez00uiRsb6XS3cfW4xP91wnMVlKby0q3nQ2v0tVqblJwAwrySRTVU9NJoHmFOUQIfVw5aa0z6fd757nLXzC8lOUKGSikjVy/n15gaumpI1SK1/T5OFG2flcrjVhkYuxh8K8+reVtYsKKCl3022UcWK2Xk8/FktV68/wMvXTGBhaRKWAT/JOgUDvgALRiTRbvXw0Ke1/HxxMc9ua4gFbQAHTli5tDwdnVLKg59U02geYNGIJG6dX4A3ECbDoCBdr2TAN7TcmqyTs7GyOxa0AfQP+KnqdJCqU9Bl92KMk3Go1co7h91UdTq4dX4Bz+1opqE3Oll7zshkLp+YQb3ZyUu7WkjTK7htQSH+UJhzylKo63HyYUUXADvr+8g2qmIm9gAqmRi9UsLd55aQrFEw4A9icfsxaWQkaeQxNwW9UsKK2XkYVBIUEuGQwM3lCzI9LyFmAK+RS+h3DfUgbbW40Sul7GjoY35JEl12D1Z3gAyDghSdcsj67xLJcclDhH2H+fswKU0szF74V62+zvReBcjQZPwntvatMBy4DfMfIdDXR8hmQxwfj1iv/7a383fjqarC+trr+Kqr0V5wPuo5c5CYTH/7xDNwHzxI29XXEAlE+4zEKSmkPPoI4uRkgl1dg9aKTSaSH3oI+7vv4tq6LXowGMT21lsk3v1zlGPGIEAAYjH+pkYcH32Ma+NG9N+77Jt4uf9Wmvtc+ANhJGIhOQlxyMRCJmQbSNHJ6XfpCIYiOL1BlFLR1/aNBUNh5pckMjZDT4Jaxn0fVVOYpOHZ7YOHFCIRUEhFWFx+Lp+UiVwiYsAfwhsID1Lrh2h5b15JIg5vgDXzC9DIJdzxzrFYT9j4TD2/PG8EP3vvOLXdTnodXvY2WzjcFhUCLUnWcPe5xUzI0mPSyGm1DhWWtXsDvHuknfGZUTeAT45388nJjNvKOXk8+lkdt84voDxTx/4TpwVGzx6RzPGOoQr7zX0DXDYhnRSdgiZztP/ry8Z+8kxxNPS6YkEbwEfHuihN0VCcrCYzXolGLuHhz05LWSwckcS0PCM7G/o41mFnZKpmUOC2ak4+D3xUxfKZedz61tGYs8OjF43kikmZtFrcqOUiEuLkvLizBZFQwG0Li0jRy6ntcuELhtjV0EcwFOLcUcnkmuJwegPsrDczJTd+kP0XRIPyjyu6iJOL6XX6eGxjHaFwhMx4JQ9fWMbYTD2Sr/FCHWaY/08MB27D/NsZ2LOHrjvvJNDRiTQ/n+T770NZVvZtb+triYRCIIxaHvmam2m9+hrC9uiXp/fYMYKdXSSsXjVEmiNos+GtqibY3YUkNRV5SQkitZqwx0PfM8/GgjYASWIi1j+9SvxVV2F+6inCAwMgEBB/3XIk+fkIgkHcu3YNur5AKkWoVNJ+8woi/mgGRjmhHO3S87C/+x5C+X+vZUu33ctr+1p5/UAbxjgZF41LY3dDH2VpGoxqGa/saSVOJkEgEPD9yZnsb7YwOTeeLxtPyy7IxEImZcczM9/IzsZ+QuEIj11URppByQdHO2n7SsDk8AYJhsI890UTJ/oHuGhsKo6vyWqJhALC4Qj5JjX3fljF3eeWxII2iGbMZhQkcPH4NFQyEaEIsaANoKrLwRf1/dwyr4AXdjQxqzCBz6t7Bz1HtlGFYVw63kCYAyesMduqGflGeh0+zC4fd2w4xh+unsAnx7o42m6nPNtAhAhjM/XsahwsP7GoNIluh5fmvgHkEiGpOjlJWjm5CXEcPWNvp2g0u9jT1M/1M3O4/MV9gx779Hg3t8zNZ2dDH7MKTUzK1lOUpMHuCZCklZNuUHDrvCLqzU4uGZ9Ot93LB0c7kYpFPL6pliyjimXj0wfJstz57nFuX1jIIycDxDvPLmZMho61b1XQaB4g26hizfwCfIEQj18yivs/qsbmCbCwNImyNC3rd7VQmqLh7vcqY7IoJ/rdPPl5PT+emx81kU/47qjcDzPMN81w4DbMvxVfywnab7qJ8IAbAH99PR0rVpL1xutIEhP/xtn/6nO34KmoIOx0Ii8tRVFaiuAvlDtDdjuu3bux/vk1JElJ6L93GcGenljQdgrLH/6A7pKLkZ4hxxFye+hftw7LS+tjx4wrVhC//FrCfj+B9sEaT8ry8fS/8CLu3bvRX/49EIoQSCRIMzORmUxEQiHkZSPx1Z02ClfPnUv/Cy/GgjYA9779JKxciXrBAhD/d/1XjkQiNPS66LZ72dvcz2+3NhIni2ZR7v2winvOLaG2Z4C1b1UgPKkx9uLOJn40PQepSIhYJEQrl7C1tpcco4pLytOp63Gwo6EPuyfI3OJEEjUK7v2wih9MyeKhT2piX/LjMvV02z2My4xmdj+r7OHS8nR8wXDMf/QUF49PIxKJEAiFcfmCbK8zU5ioprbn9BBBr9NHXoKKFJ2CT451D3qdKqkImViARCRAq5CQZYwjEAzzRX0f8SopaxcW0u/0cee7lYQiES4el8b1M3PpsHk41mGPZZwikagLwZJRyfQP+Pn4WBdmp4/FZcn8YHImbx6IvoeWz8hBrRDz6y1tdNmjZcrzRqfww2k5PLu9kVHpOlr63YP2mKZX8v7RTn4wOZOva2kORSIsLE0iVSfn3g+rGZ+pRyQUYFBJOdJqwxAnY1+zlRSdApNaxso5+YiFcP3MXA61Wvm8pnfINY+02cg3Re/jA5/UcN/SUhrNA4xJ1zEh28Atrx/FHwqTpldw79JSarqcbK8z82VjP5eMT0evkAwqOQPsb7ZwtN1OokY+HLgN8/+a/65P+2H+5wh0tMeCtlMEe3oIdHYhSUzEU1GBY/NmJCYT8uJixJlZhLo6CbtcSDIykKam/lPP62tpofXqawh2dSErLkbe0ABCIWGbHaFSgTQvD7FOF1vv/Pxzun56JwAewPnppyTff9/QC4vFUcGrM/C3tGBZ/4dBx/p+9zvU8+YiLyhAv+wSeh9+5PQ96epGmpmJv7mZ/ueejx03/fQOAnY7Eq0W3SWX4Nq2nVBf1B5JVlyMY9MmvopAqUA9Zw6BtjYGwhFUZSP/4Xv172BPUz+/3dLApRPSqel28shFZSCINtwLEJColnLfxzVkGJRcOSWTz6t7Mbv81HQ7Kc/UwclMWGa8kjarm621vQiIBkdxMgl/2nuCljwjxzscODxBVs89KRhrUJJpUBIBuh1uHr6ojFStnD/uPcGxdgf3LCmhustJm8XNWUUmIuEIAqGAxzZFg+ROmxejWkptz+nXkqyVk2FQ8tDH1SwuS2FbnTl2/IfTslm/u4XHN9UzKcfAwhHJxMdJWT4jh10NfdgG/Lj8oVjP12v725CIhHxa2Y3ZObjHSySAY50O8hPj2FgV3cCHFV1cNyObnywqIk2vwKiS8tCntbGgDeC9I51MzzfSZnFzaXk6NV0Oak+6R8wpNtFp8xAnE9M/4CfHqKLpjFJookbG9Dwj2fEqwpEIwXCENIMCk1rOizubKUpS88jG6L2ZV5LIhGwD6XoFjWYXTX0ubp6VyxsHB4v5AuiVUiq80R89oXAk5q86u9jEYxtP/yBpt3p4eksjWUYlFe12rpycxc4G89eWyktTNOxp6mdyrhGb249OOdzYP8z/T4YDt2H+rYjOCI5OIZBKEWk1eCor6fjJHegvvgjL+j8gKyhApNNhf+ed2Llpz637p8qqnsNHCPb0kLB2Db6aWgY+/5xQdzfK8nLMT/4a1bSpJN19N5LERII2G33PDhbHjPj9IBQO6UOLX34tIaeToN0O4TCeimN4Kysx3nwz/hMncLz/fnRhKETYFf3y1JxzDsF+C7bXX0eo1aKeN4+4mTPpvOMOOFlCVU6ehDQjA8uz65CmpyNOTyflwQfwHDkSlb0Ph4ibOhXXtm2D9inNzCTY00vY50NsTCDk8SBSfDvTeL5AiMNtNrbU9KI4ad7e1OvionFp/HlfK6UpWvQqKXKxEK1CTIJayrllKTzw8elsWUW7nTvPKSYUChMB1u9uwRcMc/PsPJ7Z1sjKOfk8samOGflGarqi2m6tFjePbayjMDGOO84u5kibjbyMZGEAACAASURBVM8quyhM0kZFW4MhbO4g7TYPt75ZQWmKhvuWjqDP6WN7nZn3jnTGsnDnjU5m68kMklQkZFl5OlnxSvQKCZeUp5OsVTC7MIEttWYuLU/nV5/WxLwz9zRZ8PhDJOsUhHLjeWZ7E6vn5iMSCAbdp/ePdkZ7xz6ujmWVLp+YQapOwa7GfgoS43jm8rH0uXyoZGJ21fex7ovosMZr107iyNeUQ23uAOuvKmfD4Q4uHJuGQiqif8DPoRNW3j7Uzpr5hTy+sY6rp2Wzt6mfg61WRqRo+f6kTNosHu589zj+UJjVc/NRSkVsONzBzIKE2NTn5RMzaOkf4P6TZvT5pjiWjk7hUJudsjQtn1V2x0SI1TIxWfEqXrNHs4kysZCEuGiQ9VWhYoiWm88qMnHxuDTqehyIRUIkIiGXTUjnz/ui1zCopCwdk8oDH1ezoDQJsVAw5DrDDPP/heHAbZh/C0GrlUgwiCwnB+PNN9H326djjyX+9A6kmZn0r1+Pbsm59D76GIRC6C66EPOTv46tC9ls9N7/AOkvPI9I/Y8ppAvVcSQ/9BCWl17CVx39snH1bsNbVY1u2TKsr7yCZ+n5SObPA6EQaU4OgbY2zqwl+Ts6SH7gftwHDhA40Ypy0kS89fV0rFyFUKnEeP11dN7+EyK+aDYhbuZM4mbNwrVtG5LUVCQny6mSxER0ly5DqFAgTkmm9/HHiXi9JKxcgVCpQpKZScQ9gPfYMdyHDmF56SVkBQUkrLmVvmeejYnxJqxeRXhgAPf+/QjVahJWr6Jv3XN4j0RlGdQL5pOwejWi7Ox/4l/sX+eL+j6uffm0pIVOKeH3V47n5lcPc92MHDwnFfQ/buijLFXLxePScXqDnFuWEtMaA3hjfxt5pjgOnLDy5LLRPPRpDbYBP0VJcXSc7GWr7nayaEQSR9ujWZ2bzsolTa9k7VsV2Nx+zi1LQS4R8tr+Vi4tT2dOsYkvm6K9YpWdDs7/3W5e/dEE0g1KRCIBcTIxV03JRCQUMCHbwAVj0xAIBHj9ITQyCT0uH0kaGXEyET+clsPMwgTkEtEgw3OAo+12rp+Zi8MbDcg7bV7yE+OIV0npPzkdavcESFBLeeWHEzjWYSccjuD2hxCJBUAEBPDYpjoael1IRUKunJJFeZae/S1W6nqcTMg2sL3OPOh5dUoJVd0OknUKHvy0hlkFJsZk6JhdZOKsQhPtVjeFSWoe+ayW0ek67j1vBK/va6Pb4eXLpv7Y0MYTm+q4+9xSQuFI9PdCBOQSIXqVlD/tbY09X32vi067l8ZeFw1mF7cvLMQfjBCKhClK1nDv+1FPSY1CzI2z8kAQzVCe0tY7k5wEFaPTtazb3s+bB6OODnua+vn5OSWUJGvodfrwBsI8trGOpaNTyYpXEif/37GJGmaYf5ThwG2Yb5SQ28PAtm30Pv44YbcbwzVXo73gQlRTphDs6UWSmoqsID/qFqBSEfEHIBT90gh7h8oDeCoqCDkcf3fgFgkGcW7eTNddP8N029pY0HaKYE9P7FqBjg48lZX4m5pQzz4L7eLFWF5+GW9FBUKVEkVpKV133kXE4yHhltWEHE7w+lCUlSEvLsK24V20F1yA7c9/BsC1fTvGFTcT9nhIvP12JAkJseeVpaejmjqFQHs7gZYWkEgQymSEvR56H3oIf0MDCARoz1uCxGTCuWkTIbs9OnzwzgYAzL9+CvWSJaQ9+wwCqRTzU7+JBW0Azs82ol16PrJvIXBzegI8sal20DGbO0C33cvckkQOttr4oKITAXDh2DSkIiE3vXqYkalazh6ZxH1LR3DP+5UEwxEUUhG+YBiz00dtj5M18wsRC2F8lp7mvmjZ3ez0IZeImJhtIE2vIFEt5453jsWe+53DHVxWnk5Vp4NG8wCj0rT8bHExbx1sRyIUcO2MaHD11sFWrp6SRUmKhhe+aGJvi5V1V4wlPk5Gt8PLvhYLbx1qJxKBH8/LpzxTjzsQ5KnPG7jj7KHenBqFmAMnrJSlaolXSXnzYBs3zszl7nNLqOlxYncHmJ5nRC0Xs/r1I7ESIkRLgWsXFPDcF6flPPyhMM/vaGLN/EL2t1gJRSL8YHImjWYX7VYPAgEsG5/Op8e72VzdS0myhuXTc1j3RRMV7TZ+c9kYNlX3sLm6B5Nazp1nF/P2oTYgwo+mZ6GQiNjXYuHa6dnEycSEIhEMKimXlKfx1oEOZuQbabW4aTmjvHqKo202Lp2QTq/Th0kt5+1D7exs6EMhFXHh2DRGp+s41mHnhR1NJMRJueucYjRyMVdPyeKl3S1ANDt31znF3PDHQ/iCYbKNKuaXJBIhmkl1B0JkxSup7XHx88Ul5JlUlKT8bxizDzPMP8tw4DbMv0zY68XX1ETIYkUgk9J9332ELBYAzI8+hkilQn/ZabkKX3MzrddeS7C9A+OKFbHjQsXQyUjlxIlfW279S/gam+hYsxaCQYRKVbTM+NWO7JNyArL8PKyv/BH7++9DOIxizBiMN1yPc/t2NPPnY39nA8HOzugpOj09D/2KiDsaODg+/BDT2jWIEkyxwA1AXlqK4aqrEKm+Rt1dICDQHe1dUs+ejfvwESJ+fzRoA4hEsL/7HgmrVuHctIlAcwuieCOm227DtXUr0oJ81HPm4m1sIGy1DQraThGyD5WP+E8QCEcGNf2fQioWEicT8/JJe6oI8ObBdm46K4818ws43ungt1sayElQ8bPFxfxmSwPnjEyO9UFFIvDizmZM6mjfmE4pZVZhAttqzTz3RROXjE9jZkECh1qHlg83V/eyZHQyDk+A5v4B6nuc3L90BB8f6+JIm5VEjZyrpuTQ6/Rx21sVrJ5bgDcYzRiFwxG+/+K+QfIhT2yuZ/WcfE70D3D7oiLCkTBzi01sPmOK9EfTcnhlzwk+OdbFgxeMZGNVDwdOWJGJhUzJNiAVCznWaSc+KB8UtEE0EygRidj9f+ydd3xUZdr+v+dMr5lkZtImvZOEEprSi4KI2NBVV1x1dcWuYMXyrt0Vde29ru6uiro2RJGiCAIi0kJLSEjvdWYyvf7+mDAhBH11xd33tzvff/zk5JkzZ85E5pr7ue/rOjg0xNwTCJKfpMXm8nPV59v5zZg0JuaaCIRDONx+tjVYSYlTsq/VzpXTc3n2/DIaepx8sbeNN/rvfWOPm/ImK69cNI6GbicvrKuhoq2PkWlxTMkz8cCK/Th9QaSiwNO/LWNGoRmpVKTT7kEulQCDrWsWTs3h0VWV0QSF2cVJnDI8Uj19fWMdc4cnMyHHyN2nlbC+spNXNtRw2igLI9PiePGC0bj9QdRyKTpFxEPvtJGp6JVS/rIpYity6aRsTipNptQSE2oxYhxOTLjF+EUEnU563niDrqefgXAYQa3GfN11dD39VHQoofett9GfeioSbWQSzPnttwSaIltj/uZmVKNG4d65E+fmb4lfcD697yyDYBCZxYLp2muOLoJ+AH9LCwQiAsJ78CBxv/kNtnffjf5eM2UKnn37MV51Jf7mFmwffRT5hUSCNNFMsNeKfs7JBHt7cX0XsU4QdTq8B6ujou0Q9s9XYl68KPqzNNGMoqDwB69XVKsJu1yIOh3y9HSCjj76Vq8Zsi7Q24Nu3jzkRYXY3lmGs7eXpDvvQNTpcG3fTucDD6KdNg3V6NG4t0ec7tXjxqE+/nhEpQJvXR2KrKyffM+OBQkaOQun5PA/Hw9E+khEgXiNjK11PUPWB0MhNh/sjVpd7G62c6C9gifPG8WTa6vwBUNo5BJEAbqdXrKMGrbU9GAxKLnw+EzOHZuOKIBRK6eitQ+NYmjeqCVeSUlqHB12D15/iDNGpfGHN7dxztg0Vu1tjzbp6xRSrj8xn0SdglcuGodZp2BHQ+8Qz7dwGAKhMB/ubOGcMen4QyFyzVpGphvQyKW4/UE+2dkSHTq448M9PHXeKOweP25fEKsnwOp97aTEKQkEh1wuohARtsUpOva1Do7GyjVr+MPkbG77YDdhIC1BzSvf1LC9wYpeJeW6mflkJqhw+UMc7HTg9YfwBIJ8sH3w4IA/GKbP4+fxNVVRY99dTTba7B4emD+cui4nbl8kAH7B8RkMS9bT5fBxsNPByaXJUf+5M8tSWbm3bVDs1ap97SyeVYDYv8XqD4b5tqablDgVOYlaClN02D0BDrT3sXxXK4tn5SMIAr1dPv44r5hup49nvhxIUnj6q2oKk3Ux4RYjxhHEhFuMX4T3wAG6nno6+nPY5aLnzTfRn3IK1nffA0BqSR1kw+FvHDDdtH3wAYazz0Z/xukEu3uQmIwk3ngDoT4HgZ5uvNXVaMaM+cnXIzUPpAf0vPYaKQ/9CfWoUXj27kGWkYnUbEJQqkAA54Zv+h8kJfGmG7EvX07r7bcjMZlIvPUWNCeeiO2ttxAkEkJuz5DnCvu8hANBJAkJqMaMwXzVlchTf9gZXZqUhGPzJkxXX0Wg14qgUKIsLsa5YUN0jaBSoTn+eLpff53WG29CNXYs5uuvx9/ahvOdZWgmT0I5cgSODRtIvOlGQm53xNTYZKTr6cj7IKjVpD//PJrjxv/k+3YsmDs8BalE5C8b60jQylkwPgOpKFKaGsfWut5BawuSdLzwdc2gY95AiG6HD5lE5KSSZMZlxfP0l5HEg492NFOYrKXb4aOh102cSsa3NT18vqeNZ35bRl2Pi1yzJuqRJpMIXD0jj3abG4kgMNyip6ojIkoEhEGTlX3eAJsOdrPk5ELMukg0TnKcErNOMWjyUyEVmVmUyOQ8E3cv38v+1j4umZSF1x8iUSfhsdUHcBxWdezz+rF5/Kyr7GRWcWK/8FTx3LqDnDAskWkF5kG9avNHp7G9rodrZuZx6/u7oxXMucOTsRhU3LN8H6FwJBbq68rOaJXR7g5w/4r9PHt+GWv3dzA+O4HqTgcObwC9SjakEuryBgalMQC0270c7HDw9JfVpMWr+M3YdHbUW9lY1c3dp5VQlKxjXHY8w1L0GNQylDIJj34xeGscIlvYOqUMu8fPcdkJ2N1+1HIpS1dWRAvfI9LiePjsESz5oBy7O3JtYzINnDBsqD3Qp7tbmTcydcjxGDH+m4kJtxi/iEB7+9BjLS1I4iPRI4JMhumyyxAVA1lx6nHj6Hnt9ejP1vffJ3nkCGyffDIkBirxtiU/63oUeXmYb76JzkceJez10nbPvaQ8+CDqKVPA78d3sIaev/wFQS7HdOUVQMQjzfbRx3grIiaiwa4uWpfcRvqrr+D5fiveA1WRfjWJJNqPB2A45xyCfX2kv/oqipzsQa/xaEjj4ki65RYaF15OwqWXIi/IR5GXi/fAgeh9TLzlFtruuptAZ+QD3bV5M/6GBjTTpmJfvhz755+TfMcddDa30PHnx9DNmoXupNm0LL4h+jxhl4vWu+4i662/I0341wUoG7UKfjs+g1NHpBAIhvEEQxiUMkakO0mLV0Vd93PNGvRKGVqFdJDQAQgR5g+Ts/lsdysvb6jh7DFp5Jk1TM43kp+oI0yY975vYnhaXLT684/tjcwpSUEuEVFIReRSCSPS4rC6fLh8ISbkGNlc200wFIlm6ugbKsLru50k6we26lPiVDy/YDTXv7OTZqsbk1bOA2cMRyDMwU4H+/srYq9trEOnlPLQ/OHcf0Ypf/xkD3Z3AJ1CytUz83hgxT4WTskhFAqjU8n4aEekArZ2fwdnj0lj8awC1DKRDKOa5l4PB9r7WL2/ndcvHkddtxNRFBAE+HxPK6cMT2Z2cRJ5iVqufmvHoOufXmjGFwwxoygRjUyCTinlzo/2cOnkyHbmISxxSkw6xZAOAokoIPZPv9o9foqSdPiDIdSKELubbcQppTy5tooR6QZeXl/DeePTKcuI54u9g33tcs0aJuUaKcuMZ9nWRi6elMVTa6sGPVd5k41Wmycq2gC21VuZU5qCVBQG+bcVJv28oaQYMf4biAm3GL8I2VF81uQ5OajGjSU5LZIgoCgowFtTQ8jlQpaWhiw9HeMVV2B95x1CLhf6U0/FW1VN3Ny5kWzO6MllqEeP/lnXIyqVJCxYgDw9A8++fQgSkY4H7keMMxB32ql0PvFEdK2vuQX1ccchz8qib+XKwScKBvHV1GB55hkCHR0glWJ56ils771HwNqLrn961PnNRiTx8aS/+gryrCwk6h/PU1SPHk32P97HW1+PIJfjqT5I4i23EPb5EDVqQh5PVLQdwt/cjLK4BNO11+JvbqL9kUewPP4YQZsdaUJ85PqOwF9XR9Bm+5cKt0McOfGnlkmYVZyEXilDEKDb4cPfbz1x/4qB4ZGJuUZS9Squemt7f0Uqka8qOkiPV1GYpMft86NTyVmzv52C5IEP9K8qu6jucPLHecWEgS01PVzw6pZI9JVMgvxkkQc/q2B8dgLH5xjJNg01bz2zzIJOKaOuy4nLF8ASr2JsVgIfXjWRVpubdruXOz7cjUQUmVowOBP2nLHpPPJFJXZPgHPHZqCQiYxKM1Df4+TssRnkJeno7vMyIi0uajUC8P62Ji6ZlEWbL8gjXxwgXiNj8YkFTMk34fQFeH9bE3+Ymo1SKmFCjhGpKPDKN3U4vAEyjWrq+412f3d8JnXdThYv2wXAhJzI67xmZh4HOx3cc1pxf+VQYEymgdc31nHu2PRBcVOXT82hxRY531XT8rjh3Z04fZEvKW9squP2ucNYvb+D/W19nFlmISNBTWqciuqOvmiV89yx6QSCIaYVJHLrB+VApAJ3pF8dgMPjH3Ks2+HFEq+Kvi6zVsEpw2PZnjFiHElMuMX4RSjy80m+527aH3iQsM8Xydp88EHUo0YCEOzro+f113Hv2oWyqAhRp0M9cSLu3btJ+p878e6voO/LL/HV1KCdPh3Ttdfg2LABWWISCRddiLKk5GdfUyTIvTiS9/nllwAYpkzBuWnToHU9r7yC6dprUI0YidVgIGgd3OAuarR4dpXjWL8e5fBStFOnkvL4Y1jffpuuJ5+K2oAEe3uxffAhvqZGEs4/P9JrJh9sDhq02xGUSkS5HHlmJmJcHLYPP0SaEI8glyExmwi0tCIxHKWfRxQJtLbQ9exzqI8/Hu2Uyfhb2xAUClAqEeRDjUiVw4cjNRp/9r07FvgCQSpa7dR1uxAEKErSISDw2qZavP4QJwxLotnqQq+U8eCZpdjdfuLVclIMSnqdfm6YVcC+Vjtyqchvxqbx2OoDXDQxC5vbT2GyBINajlI6uKetsdfNzkYrX1Z2RKthAGUZBpbvijTVf1fbg25YIol6OYtOyOelDTV4AyHOGZvOKSNSeWNzPUs/r8DtDzIyPY5Hzh5JQZKOZqubhX/dBkRmXdITBotzvVIaTSt4eUMNggAzCsyMyYpnxa4WhlviSNQr2Nlo5cIJWexs3EkoDFlGNS5fMCqg2u1elnywm5tPKmTlnjaumJZDQ4+bQCCEKIAnEPG2s7sD3HpSIYuW7UIuFdEoJGyo6opez+aaHgqS9TT1uilJ1ePyBTmxOIlXNhxEq5SyvqqLyXkmbpxdgDcQwqCSIQpEDXxru51R0QaRLeyN1V2UpOrZ22Ln6f4+tBcWlHHf6SW4fEEaety4fQFsngCE4dY5hby4vob1B7qYXZLEyj0DlXmJKJBqGOo1WJisY0q+mR6nF5lEpChFT5bxp/e3xojx30JMuMX4RYhKJYazz0Y9bhxBmw1ZauqgKCv3nj0ErTZCDiddzz4HgoB+7smYb1iMe8t3dL/6anTPxrFuHZ6KCjLfeRuZyYTwC2Kc5BYLqUsfwr1nD4HOLoKOvshW5xEEe62gUWO+YTFtd98T9UzTnXwygZ4eOpcuBcC+fDnW9/9Bxosv4FizNiraDhFoayPQ0kLj5VeQ8eabaMaNBcDX0oJ9+XJsH36EPD8f02WXoRoxHNe2bXQsfXjQORLvuB3d7FnEn38+vW+9FT1uOOssHF9/DYDr228xL16EPM1CoM9B4wW/Q1lagvHyhfT85Q3CXi+y9PSIn5te/0/fv1/C1toeXtpQw7gsI+kJKl7eUMNJJclcNzMPq9tPMBSp4nxfH+l7E4VIf9xvx6dT3+PisdUHyEhQ4/IF6HL40KukuHxBBEXEv+2m2QV8Wt7KxROz+PuWevzBMHlmLQlaBfNGpLK/dWBr0On1k2PWsq3/udbu72Dt/g5uOamAW+YUouzfVq3rcnD3JwODFbsabSz9vIJnzh8d9Y6DyJ/q9norl0zK4q3vGvAFQihlA39X+YlazhmXzsaqLr6v6+WamXm4vQHkUhn/2N6CVISHzhpBbaeTgiQt960YbFcDERuVA+191HQ5MarlqFQyarucPNUvmDbTzfaGbl783Riael2sr+occo7dTTaGpWi5e/k+cs1aipJ1ZCRo8fYPXHxT3cU31RGxl56g4ubZhXQ7fZw1Jm3IQAOA1e1H319JVckkXDEth/peN9YmG0XJevISNdz50V4aelyoZBJuPbmQ+04vQSqKWN0+wmGBtfvbSYtXseTkIixxqmi4vUIqcsW0XKbkmTDp/u9m7saI8X+FmHCL8YsRJBIUOTlH/V2go5Owz4try5bIgXAY+4rPUE+YiH7eKQhyGe0PLYVAAEGtJuXee5AnJx+T65LodGgnTCAcChFyufDVN2Bf/ikhe8RxX9TpiJt/JqriYnzJySTfdy/+xiZEhQJ5YQHN11436Hy+AwfwHqzBcPbZ0WnOQyhLSuj76isIh3F+swHNuLGE/X66X3oJ6zvLIo+vq8O1aSNZH36IY/36Iddr//AjtJMnI0lMxHzTTQhyOWGXE9f2HXj2DIgKaUoqIZ+PjvsjkVyePXsJ2vtIuPgilEXDcG7cSLDPfkzu4U/F7vZR0eagudeFWiFlaoGZryo62NkowaxT0OXw0eeN9H5plbKoaIPIBOKn5a2cXBppwr//9BLu7J9OFQS4bEoOm6q7SDGoCIWgvCkinJzeIFMLTHT2ednZaGVdRQcGtYwnzx2FLxjEHwxjUMtJ0ilYubcNty8iyuNUMkDg7k/2oVdJWTKniG6Hb8hr+qqyg26nl5TDqkOiAP5gCKNWzpu/H097n4depx+ZRMAfDHPOuHQe/Gx/tKfrq8pOnlswGl8gRIlFzwfbm7nl/XL0SimT801YDMohgwIahQR/MITbFyQ5RYlGIeWuw0QlQFWHi5pOBxlGNSUpcazeN3i7vNSiZ9XeSJXrYKeD697eye8mZJJj1g7pIzt1RCr+YIgzRlm49f1yLpqYxSe7Bt+Lk0uTeag/SP6q6bm8vqkuet2CAPecVkKrLSJw3f4gd3+yj5tPKsSokdHj9DMx18hZoy1km9TkJ+kJBEPcfVox7XYvOqWU4mQ90qOY88aIEWMoMeEW41dFlp5G71/fHHLc+e1m4s8+i/hzz0V93HEEu7qRpqQgz8w45tcgiGLEiiQcIuHii6JVNVGlRuzvSZOnpiKdOxdfYyMIIoSC0XWHEw4F0U6bivmmG+l+4UUEqRTDOb/BtX17dHBB7K90+Vtbsb7/j0GPDzldeKuqjip0FYWFODdtoqu/Dy/5vvuwfvopnvLy6BoxLg5JfDwEAwTtA+LM39BA94svkXT7bVjffx/tzBm/5Jb9LOweP4+truIv/aaqaQYlS04exqWTc1i+q4W0eDUGjRybx88jqypZcFzmUc9zoN3Bk2urGJ+dwOu/H0dlax8SiUCX3cukPDOPra7kljlFPPR5BWXp8VwzMx9/MMS3Nd0Ri4x4NaFQiDi1jKv+vhtX/3ZfcaqeZ387mh2NVmQSkZJUPW9srkOvknL9Cfl09nmjjfmHU5CkRaeQEp8s5+aTCnl9Yy1Xz8jj8z1tvLm5ntLUOJaurCQUCnP73GHsaOhle33vENvAf2xr4uqZuYzOiGd7fS913S7sngA2t59rZ+Zz9VvbowkMuWYNfZ4AoTAk65UEQyHUcgkcJeFJJhVpt3uYkm9iQ3VXtKpYkqrHqJHTZh8YwujzBpCIAvtb7fzx1GJW7mnD5vYzsyiR6g4HCpmE576qZsnJRXxW3spNswv5cEczgVCI00el0mJ1c90J+eSZNdR2uQaJzXAY3vu+iakFZtYe5mln1Mh5aX0NNV1O5BKRZ84vIz8p8v+GVCKSl6gjLzE2fBAjxs8lJtxi/KoosrJQlg7Hs2cvMksqqpGj8DU3I7ekEejtRRofjzI/H/Lzf9XrCPn9dL/8Mn1frBp0XFCrop5nokqFsqAgst7jQT9vHvbly6NrpcnJKHNzkRqNmP7wB+LmzcPf1kbTddcT7B8QELVatJMmRc4tlaLIySFosw2avhUEAe2UqfT89a8EmprRn3oq8uwslMOG4d61C0VREfp58xBUKsyLF2F9+22cW75DkZ+P8eKL6Xr+ebTTpqKfM2fQ9QkyGRKDAWlqKoqiol/jNh6Vyra+qGgrStZx6eQsOh1e1h3opCgl8sH87veNDLfEcfvcYYgC5Jm1VHc6oucYlxVPRVtEiH5X28PUfBNfVrSz6IQCrE4fn+1u5ZY5RXxaHjFEzjVrcPkC+ANBnN4gn5W3sqPByrnj0nj1m9qoaAPY1xLpt/vLploc3iBXz8hjXFYCw5J12Nx+SlL1lDfamFGYyFeVkfdRJZNw80lFxPUHmf9hcjbjsuK56LWtUX+3j3Y0o1NK2d/ax4OfRew4Du/lOoRcJqKTS+lxern+xAL6PH40CikCsGZfG4+fMwqr248vEKKx10V5Yy9PnTcKi0HJyr1tzC5O5vqZ+YO2VSfkJGBQydl0MDKYcd64dE4clojHH6Lb4R0SxQURsfTaNwe56aRCtAoJarmEd79v5MIJWbz7fSPeQIjlu1rRK6U8v66amUWJnDc+g+0NvchUIkl6BVvqeo72fQa7x0+OeXA/mlwictZoCyPSDaTGKck6ylBIjBgxfj4x4RbjV0WakIBu9iykSYkEWlsjAiQ3B2VpCYj/uq2RsNeL92DNkOP++oajrI7097CxagAAIABJREFU7pkXL0JZUoJ9xQpUY0ZjmD9/0BStLDkZqdFI2pNP4NryHYJajea48SgLCwn5fPhbWlCNLoNgCHluDr6WFgSpDMWwYchTUsh84w18DQ10PfEk9uXL0UyZgv6M00maNg1BoSBktxPs6SHh0ksxXHABUqMRUatFkZtD9wsvkvbUk4gaDX1r1iCzWDD+4VKcO3aSdMvNyFMj3ldhvz9iSiyRIEtNRfgV7nnPYduMv5uQSbPVw2vf1DI6M54Ou4f1/Y3za/d3MCItjhyzJhKVZPfwbW0Po9INqGQSXlw/8P6EwnDJ5BzKMuMxaRW02tw8vvoA3kCIBePTEUWRC17ZwqWTs1m6spKGnshwgFQiRuOiDqfD7uH4bBOr97fj8gbQyBSMyojnzg/3cP5xGcRr5CTpFSyeVUAwGCLbrEV7mKmvQiahvts1yJT3sz1t3Di7gP2tFcwqTuL5dTWcMiKFj3Y2c2gnUhBgSp6JT3a1MCnfzJp97TRbXeSadUzMNTKnNIWtdb2UWuLodXqYmm/C4Qnw4voaJueZmJhrQqeUMW9EMslxSj7Y0UyOKRL7dN07A5YgWoWUK6bl8uTaKgD+dGbpoNd//vgMmnpcOH1B/rzqAL+flEWWUUOuWcubm+uiKQ7NVhe5BWacviCNvW7e3FzHF3vbEQR4YcEY/rq5nhtnFQ6xE7nguAxe3Vgb/fk3Y9L4x44mNlZ3o5FLeO+KCUhiwfAxYhwTYsItxq+ONDERz569ONauBcBfX49r23ay33sX4v41rugSrRbjwoU4v16Ha/sOAq2RSUPNxIk/+Bh5airGiy8i/vzfDpkSPYQgk6EuK0NdVjbouGvbNhovuTT66SbI5STefBM9b7yJqrAAycyZyC0W+tasxbNvHyn330/fV1/Rcd/9qEaNJO6cc3CsW4ft3feQJiVhvmExipISZBoNybffTsKCBYQB5dgxqEaMwNfaQu87y/DX16MdPw4Af1s71uXLweeFUBh5Xi6a449HGh9/DO7oAJlGNVJRIBQO4/BEvLnsngCj0g08saZq0Nrypkhl6/4V+5mUZ+RPZw7n9U110UgsiIidklR91JC12BLHohMLOHWkBZVMgjcY4qLXIqkW53qD+IMhrj8hn1A4zJRcI05fgL9uHizIC5J10ZD5klQ9GQlqXv2mluEWPaMz4tndZGN4mp4OuxcEePHrg9x5yuAs0iMD0r2BEF/saeP1i8dicwdYtGwn3U4ft80dxu4mG6FwmFOGp7D5YBer9nXQ0OtmZJoBjVxCgkbO5ppucs1aEjQybvuwnMsm5/DYmvLoNuTeFjudfV4UUpEmq4tLJmdz1bRIRNfThyUMADi8Afo8ftRyCS5fkFSDihcuGM3elsh07ra6Xkw6BfecVoJGLqG6w0FHn2eQWAY4Y1Qq1R1OipK1nDYylQc+i1T5wmHY22ojGArz3rZGbp87jOW7WrC5/Sw4LoMzyyzMLEqivttJk9XNp+WtfFcbScxw+oKsq+yMZYzGiHGMiAm3GP8SDtlyHCJks+Gtrkaecex72iASdu+tOkCgpRVpmgUCQfq++AJvVRW66dMR1Grk6WmoykYNepyvvh5PZSQnU1lYELHu+AHR9kOE/X56XnttUEki7PPhraoi7PPRcusS0p5/Dt2MGbi2bCHu7LPoeuEF/E1NADjWfY23+iDmxYuwf/wJgfZ22u+9jzSLBdnYsZEt3f6tUIlaQ/sjj+BYvRpBLsd4xeWoRkVek+v77wk0NeH46ivU48biratFotWinTLln76vRyM/SccLF4zhtg92o1FIo9uUR/Z6HcnG6m7qe1ycVJKE1eVnbUU7Zq2Ca2fmMSxlcO9ThlFDRr81xO2Hhck7vX4umZzNIysr8QVD1HY5KUzSMas4iTX729HIpVxwfAaddi9jMuK5bEoOvkCIbqePLJMaqzPA7/+yFYBsk4aFU7L525YGFFIRlUxCRZudHJMGuVRCaWocRUk6KtoH7EZmFCWSGqciSR9GIgo09Lh4YMV+ckwaBEFgRFoc7X1e2uweZBKRQChEpklDj9PHG5vq8AZCXDk9l5KUOAKh8JBBhY92NrP0rBGkG9X0uQNUdzgRiIjGI/EHQ0gEgfllFkZlxCMQRhDgyTVVNPa4mVOaTLvdw9+21HPltFyCoTC3zy3iha9r8PiD3Ht6CdUdDkQRLpqQzcbqLoKHDTFsrO7mjFEWPtjRzMMrK5iSb2a4JY55w1Mw6ZSYdJBiUHLOi5vZ0zx4OKbPMzTHNkaMGP8cMeEW41dHkEoRZDLCvsEfSoL8x5MG/lnCfj/W996l408PAWC66ip63vjLQHZqQwNxZ59F3KLrEQ+L4vJUVtJwyaUEuyOVGYnRSMZrr6IsLPx5zx8OHz0iy+uLRn/ZPv4YaWIimkkTCbncUdF2CH9TE4HOTlQjR+D6bishp5NAW9uQc8oz0kl9eCn+5usQpDLk6WmRiC6vl0B3FwSD6ObMwfH118iSEvG3d+BubESVnv6zXtOPIREFTixOoiRVT4vVjTcQRKeQUtFm57jsBLbUDmSVFiXraLFGpg+NGjk2l49Xvqllcp6JO08ZRm2nk/e2NXHaqB+OOYpTD7xnbn+Iv2yswxeMCJmKtj6kEoEep4+rZ+Th9Uf6tq6ZkYs5Lo6dTVbCYTBp5RQk6bnh3YHxydouJ19WdDI138SYzHg2VHdRmKSj1+EjGA7TbHWzeFY+Dl+Q8iYbSToFXx/o5P1tTby7cAILjsvgzc31jM9OYEKOkXi1DKVMxOENcMHxmexusvL+tsj7rFNIWTyrgPtW7OOJNVXcNLswMoRwBDKJiEElY0eDlT+vOkAwFGZMpoHzj8vkvk/3RddJRYHjc4wRMZUW1z85C7lmLaPSDYzPNlKUrGNJv+hdurISs07BohPyuOe0YggL3LtiX9Qsd/W+Dn4/KYuMBHV0G7qi1c59p5dSlKLj0/JW0uJV/HZ8BqnxA752armUP0zOYdGyndFjggAzisw/+jcUI0aMn05MuMX41ZGnp2O86kq6nngyekw5fDiKgl9nIMFbW0vHw48MOnZItB3C9uFHGC+7DEXmwISje88e4s89l3AwSN/q1fhqauhbvx5RpyNotRIOBJCnpSNN+PGtRlEuJ+GiC2n+/vuBg4KAoiAf28cfR9aoNTRfdx36U05BWVp69POo1QOmwKKIqBxqWgogUakIymR4Kirw7NuLoqAAaWoqglIJokDvm5GpXn99Pe6du0h79lm6v1qHfvYsZMfIegUgxaCiscdJcYqeP58zknWVnRyfY2RirpENVV2UZRhQyCQ8+1U1ElHgsqk5KOUSarucUfd9gFtOKiRO9cNVzpNLknl9Yy1JeiXZJg2djgFPveoOB6ePSmV/iz0aWH5yaTJZJg0Xv741WqlKUMu4YELWkHNva+jFrFNw+d+288S5o3D7Irmed3y0J7pmdnESGoWEN/oHMmQSgf1tds4YZeH47AS+2NfOU19GYp6m5JkYkRaHQiphV5Mteo4+b4DV+9s5PsfI5oPdGDUy/MEwWUZ11MwXIqkI3U4vb303sPW7rd7KxFwTS+YUsnJvOyatnIVTcxibmYB4RB9ZXqKOK6bnsb/VjkwUeH7BaJ5bd5A+j59TRqTy9YEuilP1CDAk4eCd7xpZODWHJ9dWYdYqeOyckRSn6ilO1XPOmHQael3Y3X7a7G6S9QN/m9MLzTx2zkheWl+DXiXl6ul5jEo3/OD7GeM/C6ffSauzFaWopMnRxLqmdUgFKcOMw8iNy6XI+K8bnPpPJSbcYvzqCBIJ8eedh7KoCNe2bShyclGPG4ssMfFXeb6g1TooUxTJ0IZ8UalEPMzg11tTg/Xd9/Ds2oUgk2E47zw0EyYgqtQ4vvySzsefIOR0Is/OJuWB+//XKC7NhAlYnnmanjfeQFQq0UyejHXZu5Hn1miQZ2dj++ADRK2WvrVfop87F/tnn0Ufrz9lLoJCgfdApEfMeNWVSH5AMHqrq2m45NJo9JWo1ZL27LPIMzKGmPyGfT58DQ10PPgg/ro6km5bEq0CHgv0KjmnPbORURkGxmclsK/Vzr4WG3efVooYhgMdDq6ekYdSKuLxB9AoNNx9agmPrqrE5Quy4LgMTh81NEbtcLRKKY+fOwpfIMTa/e3kmDSDQuOfWHOAx88dxcEOJ6IAdd0uarucg7YXe91+4tVDX/cISxyV7X0EQ2E2HewiQSPn71sG98ut2tfOE+eOwuEJ0OcNMHd4Cg/3D0hcPTOPT8tbMWkVWF2+SNUuWYfHPzjiSSOXEK+SkWvWRoSbVs4Vf9vOFdNy8QfDNFtdFCXrmZibwNa6Xo7kzc31zC9LZX5ZKhkJasZn/3BKRkaCmozD0h6m5Jsob7Jy5d93YHP7KW+ysejEoV+iQuEwGQlqrpmZx6RcIxNyI1FfXQ4vj62q5K3vIokPafEqXr5wLMNSIlYfBrWc+aPTOKkkCVEQUR2lkhjjP5NaWy0PffcQW9u2cuOYG3lo60PR32lkGi4bfhkSUUJ+/K/rIvCfTky4xfiXIDUY0E2fjm769GN2zpDXS6CrG1GrQXrYkIPMYkFyWIRVsLcXeXY2vtqBqTfzouujE6IRq5BX8OyKbJuF/X56//pXUh95mLDPR+ud/xNt2PLV1tJ2z72kvfgi8uSBhIgjkWi1iFotgjrSlxX2eIibPx9BKiHsctP98ssoS0tw7yrHsXYtupNOwnzddQRtNhTDhiFNTSXkcJB8372IGg0SsxnVqFGRadXWVgSZHEJB3OXlBDo7iV9wPr1vvU2gvZ2Qw4H1H/9Af+o8JFoNAdfgamPYH9my7l22jPgLfxe1QzkWHOrj+q62J9qcDrC32YYlTolKEREsLn+QOKWMYcl6Zhcnc8KwJAKhEKkGFbKjCO1DNPS4uODVLfiDYWYNS+TT8laWnFzEq9/U0tTr7p+uzOHJNdUcPMxupMQyOEUiHAary8fZY9Ki25dp8Som5pl48LP9KKQiZekGBEHg9xOz2Nloi1qFALTa3JwwLAlBgLs+2YvHHyIvUUswFBmUaLa6SdYrabd72FzTzWVTsqOPPWV4CjlmDZsOdiOKAg+fPZxgKEwoDM+tO4heKcWkVbBqbzv5iWWMsBiYNyKZT8sHtspLUvXIJBI6+nzkJuqo63KSZfpp8VBapYzhFgMPnFnKi18fRCGVkGvWEK+W0esaEJhnj0nj2a+qqelykm5QMSE3cnxXozUq2gCaet08tbaKJ84dheKwFAmN4th9IYjxfx9/0M/L5S+zqWUTUyxTWFG7YtDvnX4n3Z5uqqxVKCQKGvsaaXG0IBNlKKQKMnQZlJh+fsThfyMx4Rbj/0u8NTV0Pv0MfatWIc/NIfmOO1CPH48gCMgtFtKefYaW227H39CAe+8+Uh9eSqCjA3f5btRjx0REkMeDoFAQ7Omh74jhCSQS/G1tke3JI7rsvZWV+Bsbf1S4+Tu7aL3t9uj0qvPrr0EmI/XRR2i5fhEAyuJi+tZGnrfviy8IdLSjmTIVQSrBs3cPEn0cqrFjkaelIcpk+Jqa6Hr2OWwff4yo1ZJw4e9wbtocSXGQyUi66Sbaly6FUAhfbS2CQoHp6mtou+uu6HVJU1MJe33EX7CAgNWGIB7bakhagopzx6Xz9mEf7CatnASNnDe+reeq6XkYVFJ0Shk5Jg3xmkifoyX+6NvAR7K/1U6L1UO8WoZcKsEbCPHQ5xWcUWbBrFMwwhLH37fUMac0mXA4TEWrna31vahkkQSHw7cDUw0qsk1qphWYkUkEvIEQ5U02DGoZ18zI4/E1VbTaIr2KMwoTmT/awgfbm5FJBPIStVhdfpQykftOK+GDHS1IRKjvdvHu9wP9ipPyjJxVlobFoOLyqTms2tdGkl4xaCr0q4oOnr9gdFQ42T0B7J4A2SYNjb0ukvRKTh9lYUttL519XkxaOZdOzuZAex9SUeTat3fg9Qd5bsFophX+tCq2TiVj3ohUZhYlIggCKpmENy8Zz/vbm9nfamdcVgJNva5oJdOsG+hHrekaarfybU03NrefRFmsuvbfSrenmzUNawBQSpW4ne4ha3xBH0JYoLyznDs33kkwHNkZGZc8jlRNKvPz5zM66cd3M2LEhFuM/w8JOp203f8Arv7QeN+BKhovW0jW++9FDXTVY8aQ9c7b+NvacG3aTMsttyDLzMR0+eVIU1Kwvv8P7J8uRzWqjLizzkJVVoZz3bqBJwmFkCUnEz6K26g0MRFR9eOZikGbNSraovj9SFRqEi67jJ5XX8VbfRBlSQnO9euJm38mIbeHrqefhnAYzdSpyDMz8dXWoj3hBDzlu/DVN2D78MPI5dntdD3zLObFiyLCze+nb80a1OPH4/r2WzTHH0fI5SYsQMpDf8JbWYmo1SFNNONva8f28SfIUlLwNzUhs6QiHCXH9Z9BIZVw7cx88pN0fLSjmdJUPZPyTNR1OfmfeSUUJv88p/xQKIzd40erkCKViARDYcw6BZdOziZZr0QpE/H4QyzrD2p/5XdjSDNoiFNJSDWoEUWB6UWJ5Jm1nDXaQmqcis92tzCrJJmVe1q5cEI23kCQbfW9/PXberQKKQ+eOZxPdrZERRtE4q8Wn5hPRoKKW+cU8cCKfdR1Rz6Y5pQmc+KwiAC6b8W+Qde/sbqbc8em09DjYkJuAqMzDNz8fvmgNU5fkNouJw+cOZyX19dQ3mxjbGY8s4qTeHhlJWqFhCfPHcVz55fhCYTINmkIBIL8dXMdhcl6ziyz8PnuVha/u4vl10z+ySIYIsMEhxieZsBiUPH1gU5W7m1j1b7IlO/Fk7IGpTDkmoca6U7KMw0aGonx34dUkHJd2XWEwiEsGgutrlaWbl0a/b0oiKTr0jGqjINEG8DWtq1cPepqPqj6gMa+RqanTydOEbOP+SFiwi3GMSdgtRHo7EBiMCAzH/tpskBbW1S0HSLs8+Grq4sKNwCJwUDPX96g+6WXAPDV1uHa/C3Jd99FR394vGfvPvpWrcLyzNO4t2+P5pgar7gcX0trf57pfGwffABEfNtMV1/1v9qYSI1G5AX5+A4M9jGTxBswX3M1cfPmEXK7EEQJvtpapIlJdL/wQnSdc/16FBddhH3Fp2imTCZot+NYs3rovejqRtRqCTkcBDo7UY4cQfzvf4+8aBiB5mba77sv8rxGI5pJk3CXl6MsyCfU14e3r4+GhQvJWvYOqpJjt0WRalBxyaRsFozPQC4VEY4SJ/VTqGiz89aWhuhgw2/GpFGSqmPRCfnc++k+NAopi04soKHbhSDAqHQDu1vsDE+Lw+ENcM1bAwa1w1J0XDMjj8XLdvHKRWNps7lZcFwW9326j5ouJ5lGNbfOKeLxNQfYcKCT7Q1D+8r8oTD3nlbC0pWVUdEGsHJPG8UpetITVEe1QKnudLB6bxsnD09ldIYB6VG2glUyKe9ubeC2uUV8VdHJnhYbD/RnnvpcIVptHmaXJOPyBKhqd+APhhiWouf1TXXIRJHfHpdBdYeDLof3Zwm3I1ErpHxa3ord4+fqGXnYXH5e3lDDg2cOj64ZmW7g9xOzeL1/OCPbFOmDU0hj1bb/VmxeGy/tfom3K94GQC7KuXfSvdxx3B18WPUhOrmO0/NOxx1w4/K7aHMOnZAPhAL0enoJh8Msq1xGKBSi1FRKn78PvVxPsbGYeOWx9aD8/5WYcItxTHHt2EHbPffirahAmpRE8l1/RDt9+jF17BeVSkSdjlBf36DjEt3gak6gvZ2eNwfnpIa93iHWG4HOToK9vWS//x7e2lpEtRqpyUTtmfPRzZqFft481BMnEOjoRJ6ehqKkBIl+cM/UkUjj40l94AGarl9EoKUFQakk6Y47UOTnIyoUKAsHBGbmW3+n/f4HhpzDtXMnqnHjCdlsyPPykGVmEejoHPKaQ55INUQ392REhRJRp8VbWYH1729F1wW7u7F/8gmJt96CZ+9hVaFAAO/Bg8dUuB1C8Qu2zXqdPm5+r5zdzZFJzNouJ9vqe3lofikV7X14AyG8AR8PfV5Bok7B3OFJNPY68frCGNQyHvxs/6Dz7W/tw+UL4guG+HBHM5kJah5aWRn1TavvdvHEmirOG5fBxuouJuWa+HBn86BzZCao6XX7KUrRs79t4G9PIgr4giF0Shkj0uIoP2x61GJQYXMH2N/m4NoTtKwob+HKablRY1uABI2c5DgFBUl6uhxeXv2mNmpvcgiNQkp9l4Pv63vZUNXFpDwTz38dMc/1EOKl9TXcfFLhoC3NfwalTMKiE/O58LXvokMRM4rMlGUMTIUaNQpumVPI2WPTcPuCZBrVmHU/XoGO8Z9NZU9lVLQB+EI+ntr+FFPTpvLHCX8kPz6fLxu+5PZvb+eGMTcwJW0K65vWR9cLCMglck7MPJGlW5fi8Ee24yWChBvH3sit62/lnMJzWDR6EVp5LDotJtxiHDP87e20LLkNf33EBT/Q3k7zosVkvPV31D9gefHPILNYSLr9Nlpvuz16TDNjBoqCI/zWpFJEjYag5whPtaP0dQkSKfKMjGglLeR2o5kwAfvy5diXL0fU6ZClpZG05FYUqT/sMXY4quHDyVr2Dv6WFiRxccgzMo4qYGVmM/Lc3CHHFQUFqMeMpvnGmyAYJGnJEjy7dxPufz2KoiIURYXI8/LQTp4MogR/SzOO9RswnHEGIadzyDlFrZa+1YMrdxL1T2tq/1dS3eGIirZD1He7qO9x4zssdgqgo89LdYeLSyZn0eP0IZNEvNOOxOMPYdYpcPuDKGTiELNbm9uPXCqyt8XOXacWU9FmZ39bH4IAZ5ZZ+LKig8/3tHFcdjyXTMqioq2PyXkmHN4AKXolfW4/d8wdxie7Wlhf1Ulpahwj0wxsqOrkrlOLiVPJsLoCHGjv44EzS9lU3U2CRs7UAhPdDh+T8028uK6aP0zJ5rl1B6PXNdyiJxAIUtftYmtdLzlmLVqFdMgwQWWbnVRD3i++98PTDHx89SQOdjpRyyXkJ+lI0Ay2Z1HJpZTEkhBi9NPl6RpyrMXZgl6hZ1/3PkpMJRiUEfH/5PYneWLGE4TCIb5p/gaj0sjvS3+PTqaj19sbFW0AwXCQ9U3rKUssY1nlMk7PPZ3h5uFDnuu/jX+LcBMEQQJ8DzSHw+F5giBkA+8ARmAb8LtwOOw7yuNGAC8CeiAEjAuHw0OdTmP8W/DV1UVF2yHCPh/+mho4hsINQH/yycgzs/DV1SJJMKIsKUZqTBi0RmY2k3jTTbTedlv0mDTNgixz8DanvCB/iKecqFJhXnQ93oMH8Tc0EHI60U6dGk0s+KnIzOb/dbvY19aGenQZjoL8qP2HzGJBP+ckmq65FvqtJLpeeIHku+8m0NlB2Ocj2NVN8w03Ynn0UdxVB/Ds3EncGWdgXfYuvqYmFPn5eKsGtmoFuRyZJY2wd6BBX1FcjKK4+Ge9pn8FcunRK7RSUWBinoll3w+umk7OM5GkU6JTSNla18Oc0mQ+2z2wHaOUiaQnqHB5A4zOiMfpDSAVBQKHJQOIAqTGKTl/fAYf7Wjm/jNKcXgDVLT1sXJPGzsaraQnqJhZlESXw8sISxyiKPDe9010OrwMt+hZOCWbLbU9TMg1UpoSR6JeQU2Xih6njyv/tg17f4LAJ7taWHpWKUk6FdsaellX2UkwFGZ6oYkRaQaePG8U5U020uNV9Lp8NNu8PLqqMnqtKpmEa2bm8cgXA8cKk3+8CvxzODypIsb/v9g8Nux+O/GKeBRSBT3uHtQyNTp5ZHei092JP+jHrDYjE//5HsV07VBD7+KEYjqcHRQnFPNZzWckKBNYMm4Jj3z/CNd+eS0XFF3AwjkLUUgUdLo76XR10uJoGXIel98V7Xc7XNT9N/PvqrhdD+wnIsAAlgKPh8PhdwRBeAG4FHj+8AcIgiAF/kZE1O0SBMEIDDZHivFvRdBoEDXqIWa34q+QRyoqlahHl6EeXfaj63QnzUZqNOLYtDG6BSozGrE89xyONWtQFg9DM3kKsqShE6LKwkIy3/o7/sZGRLUaeVYWouLYpz0E2tvpfuNNTNdei6/6IMhkyHNz8Le2EnYP9FIFe3oItLTQ+dRTgx7f8ec/Y7z6KpxffoVzyxbkOTnYV64k8cYbsH+6AkIh9KecgjQlGanZTOa7y/Du248k3oCytBR5asoxf02/lPwkLfPLIvFKh5iUZ0QiCITDYR4+ewRvb2kgEAozpzSZLys7MGnlPP1lFVdMy+W34zOIV8tZtbedDKOahVNysLl8LD6xgA93NuMPhrh0cvagrM6LJmaxq8FKXpKWBz6roLbbxYLxGTz8RWU0+umiCVn86fOK6M8Kqcgdc4extqKD3c02arrdNPa4SI1T0m7zcNaYNN79vonrTsiLijaAxbMKeG5dDVUdDq6clsvkPBP72+xoFDL6PAF2N1r5dHcrVpefE4clUdk+uC3A7Q/S5/ajkklw+4OYdQrGZ8f6f2JEaHO20WBvoNPViSfoIU4Rx4bmDayqW0WmPpPbxt9Gi7OFh7c+jNVr5ez8s7m49GIs2h/3UPwhCuILuH/S/Ty45UFcARfZcdnMz5+PRJRw2ze34Q64EQWRy0dczt9O/htd7i7ilfEEw0EuW30Zdl+kt/imsTcNOfeszFnIRBkjzCMwKAyEw+FBfbP+kB+nz4lOrkNyjKfk/6/yLxdugiCkAacADwA3CJF3YCZwfv+SN4C7OUK4AbOB8nA4vAsgHA53/0suOMZPRllQgOm666JRUwBx8+ejyPvl2zf/LBK1Gl9TI30rPiPocESEkERC1ttvkfrg0L6yI5GZTMhMpl/1GkWNhpDVStu995G69CECHZ0EmluQpVmQl5Tg27s3ujbkH1KIxt/SQqivj6Q7bkeWlESg5yyar7uejkceJeHiixHVajoefRTCYQSlkrSnnyL+vHN/1df0S1HLpdwwu4CEXoYqAAAgAElEQVTjchLY0WAlN1FLsl7JgfY+ThuZwssbatGrZIiCwFNrqzBpFWxr6KW+x80r39RywXGZnFSSxNzSZCQSAaNGgccfoMvpo7HXhdMb5OoZOh4/ZyQHu5wopCJfV3aSbdagU8q4eXYhTVYXVpeP2cVJfL6njRFpcWys7h6U3+kNhKho60MuETizzEJxso6bZhfy+Z5WpKKIzx+i1KJHctgHzbiseL492M2Bdgfnjktn7f6OqDD7Ym87Z5alcvZoC+9ub8IbCCERBUKhoVMPKrmEq2fkEgiFKUrWsejtXbx35QRSDZHhhB31vXywo5lWm5tTR6YyKdeIKdaL9h+N1WNlW/s23AE36bp0VtatxO6zo5Pr+LrpawD2du/l+/bveWL7E9HHvVP5DhqZhutGX4co/HA/si/oIxAKoJapBx1XSBWclnsaZYlltDha8AV9SEUpt39zO+5A5MtnKBzi+V3PU2wsxhVw0dLVQrOzOSraAD45+Al3TbiLj6o+whVwMTdnLoUJhezq2MXK+pW8tuc1/uf4/2FO1hwQIr11Vb1VfFL9CXnxeZxfdD7Zhmz+0/l3VNyeAG4BDnWSGwFrOBw+9HW0CTia7C8AwoIgfAGYgXfC4fDDRy4SBGEhsBAg41cKMI9xdES5HN1JJyFLT8dXW4csKRHFsGHILQNvZzgcJtjbi6BUIlGrf+Rsx4ZATw89r75GoPOwpv5gMNL4P2LEr/78PwV5ZibGy/5A0OGg/cE/4avu9/gSRVIffYSOpQ8TaG9H1GpRlpREwh8PG1/UTpsWzYGVp6cj6nSkv/IyYZ+fkKOPhosujq4Nezy0LLmN9FdeiVQSVUoUBQVHrTj+u0mLV3PuuAxmFCbS0O1CJhM5oSgRtULKzKIkrvjbtuharUKK3R35J+Rgp5N7+nM8J+eZeOOS8UhEAY8vgMMb4OGzRqCSSVhR3kqX08eXFRFj3aum5/JVZQfv9W/D5iVqGZMRz2mjUrF7/PiDYdz+ob1zVreP2m4Xq/d3YHX5qO1ysr0hYv78XV0PS04uIi1eRV6iBqVMwoUTsljyj4glSEqckmVHVNM+2tnCjMJELpyQhUQQSNQrKMswcM/ygaEShVREo5Dy1pYGzhmbxjNfVdNsc9NidZNqULGnycaCV7fg8kX6Adfs7+Ce00q44PhMJOI/N+Ub4/82Dp+DF8tfpKq3ilJTKS2OFtY1rWPhiIW8XP5ydJ1SoqTHM2CObVQauXLklYTCIdY2rGWkaSSJmsF+gP6Qn+3t23ml/BVMahOzMmcRDAVJ16Vj0Vk4aD2I3WNHKVOys2MnQYJk67Pp9gytr+zu2o1GpkEn0w2ZLj3Qe4DPaj/jlnG3sKtrF432Rp7d8SyCIHB67unkG/K5c+OdZOuzWVGzgncOvINMlPGbgt+Qocvg44Mfc3HJxdF+uv9Ujt2o309AEIR5QEc4HN72vy4eihSYDCzo/++ZgiCc8P/Yu+/oKKv0gePfO71kZtImvSf0EoHQQQULWLCtuooNe8cKtl3Xn72ufW1rWRXE3rCgIk2RJr0nhJBKepuaKe/vj4GBkICIJBC4n3M8J/PWO9eQeea99z7PngcpivK6oih5iqLk2TsgFYW0b7qEBKxjxxJ75RXYTj8dw26T7t35+VQ/+yxbz/kbJVdfg2P+fJT28iccREKrRRXRdhWSynjgKRMONpVWi3nYMIQQrYI2Y//+NP3wI7E33kDMddcR+fe/AwL7bbehibODEEQcdxwRo0fhWbMGXVoazsVL2HbJpWydcAbVzz2H4vfDHjnaArW1OH76kbLJkym5+hpKb55Myx4rbQ8ncVYDeZnR5KZEYtKHvmsOy4rm3lN7YdKp0agEvZIsjOrW9snohUNSw4GKQadhaGYsJp0ajy/Ahu3NZNlD87iizbrQtopdQVRBlYPVZY207CiVNTwrmr8NTGlzj5HZsdTuqJf6+YoyRuW0bsea0kZ+2VzDjcfnMCQjmk9+Lw2Xh2rv13/ntpd+LuD52flsqGhmydY67ji5eyih78Bk/ntZHolWPecOSsHZ4mdQejQ6tYrIHbnUlhXXhYO2nd78ZSuF1XKO0JGqsLGQaRumMTRxKG+ufRNfMDSTyOlzYtWHft/iTfH8Y9g/yLBmoFFpmNhjIncPuZsGbwOLKhYxdf5U7lpwF4UNha2uva5mHVPnTyXGGEOMIYZb5tzC7fNu5/yZ5/P91u/Z7tiOWq3mvl/v4+VVL/PqqldZWb2SRHPraRgCgV4dmmtn1VkZlTyqzfsYFDeIUkcp9Z56Ptj0AX7Fjy/o45P8T8iwZhCjj2FJ5RLe3/g+/qAft9/Nu+vfpdHbyJySOfxe+Tv+YNsvWEeSzn7iNhI4QwhxKmAgNMfteSBSCKHZ8dQtBShr59xSYL6iKDUAQohvgYHA7E5pufSX+J1OGqZNp2HGjNDr7dspvfEmUl57FUPv3mgiO+YbktpiwX7LZEpvuHHXtshITAP2PTeus6mtVoKO0IeqoU9vrKeeinPhQhSXC6HX0zxrFkowiCYpCW/RViLGjEUdGYknfzPodMRcdRXB5mZKrr02vOrUuWABgfp6LCeeSPOsWeF7aZKSWj2B9KxejXvlSnQpbYOSw1WkScfVozM5sVccCwtqmLGshLJ6N3ee3IPPV5QRCAa5cUwOo3Jaf3lTqQRDMqMpqnEyvk8C9e4WclNCczALqtoGNZu3N3Pfqb3oHh9BUIF4i4FHz+7LjKUl5NgjOL6HnV8LajjjmGTiLHr+u6AQi2HXJG+VgCy7mV8KakiJNvLWr0WoBPzz9N4U1jipd7WQFm2iuG7XvNCxPeNYXxEaPtJrVPRPsTF/czUDUm1MGp7O1honT/+wmfn5u1byDc2M5oULcsnYsaCgnbzRKCh49liRKx056j31xJniKG4uJkIbQU5UDjcecyMCwaMjH6WkuQStSku9p55AMMDUvKm8u/5dpm+ajlqomZI3hbyEPIJKkOLmYpIikjBoQkPrVa4qTss6jdLmUnRqHWflnMUXBV+goPDUsqe4tPel+AK+Vk/Qvij4gnuH3Mtzy5+j1lOLQW3gmv7XEGuMRVEU3lj9Brfm3co1/a/h8/zP8Qf9nJFzBr6gD7vRzoxNM9q8x3W16zgh/QRmFc1qs29j/UYUFO6YdwfTT51O79jDb9HVwdKpgZuiKPcA9wAIIY4H7lQU5SIhxMfAuYRWll4GfNnO6bOAqUIIE9ACHAc82xntlv46X3ExjZ9+2mqb4vPh3bQJ98qVRF96Kep2nowdDOYRI0h79384f/kVdXQ05hHDD+m8u/YEnE408Qmg0WA97TSqnnwqvM+5YAFJzzyNv6oKlUGPechQdGmpBL1erKeegrBawePBW7AlHLTt5Fm7lujLJ+GYNw/F40FjtxNz1VVUPfVUq+N8JSV0NUIIsuwRqFSCikYP36ypoLzBxcsTBxBvMxBl0rV7nkGroWeiDa8/yNerKuiXYiM7NgJ/MNgqGAIY3d3OlmoH8VYDMRGhhSlZsWYSbQZG5sQyecbK8LEX5CXz4oUDqGzy8takPDZVNhEMCrZUORiUFsnOaWpBBZ6etYlbTuxGnEVP3yQb68obWVPWyMicWIZlxfDp76WcNyiFnLgIYs1aTuwVh0GrZl1FE1qVipQoI2qVCM+3W7y1jqtGZ1LnaiHOYiA3xRZeuLDTeYNSSbDKOW5dkcfvIagEqXPXUeWuIqAEyLBmYDft+mKSaknF4/cQbYjmrsF38cDCB3D4HBjUBib1mUS8KZ5qdzX13nqyI7NZWbWSUkfoSfvFvS+mwlmBRqVhfe16SppL0AgNo1JGUe2q5pVVr1DQEBoNmFMyh/EZ48m157KqehVuvxu9Wk+Zo/XzFrffzcebP+amATdR4axAURQ+zf8Uf9DPlLwpbGrYxFcFX3F61ukoQYVmXzO1rloGJw7G0eIgy5rFiqoVra6ZYknhmNhj8AV9rK9tXaUkwZzAku1LCCgBtjRukYFbJ7gLmCGEeBhYAbwJIIQ4A8hTFOV+RVHqhRD/BpYCCvCtoijf7PWK0uFFrUZlsxGo2SPfj0pF8w8/EjFyJIa+fWkpLibo9qBLSf7DJLf7S2UwYB4yBPOQIQflen9FoKkJX1kZKpMJbWpqOK9boLGR6ldfIeW1V6l/663WJykKgZpammfNwr0iFCiozCZSX3sN3/bteOfPp/n777Gd87c291OZTfjr6oi78w6CLS3oUlNxLvyt1WpVAMNhMt/vQGTEmLlzXA+uOTYLk06Ddi+pRPbUJ8lGRYOHBQWhSglxVgPj+8Tz/bpKAI7tFkt1s5dJby/lipGZ9Ey0cGw3O2UNHs7ITeKV3XKtndQzju4JNi55awmKEpqG+M/TerOhsjG8MnbquF15Bj3+IIoCt364CggVuM+IMZEZa+biNxfzwITe+AIKiTYD36yuoFeijf8t3MaKkgbiLHruHNeDsT3juOvTNdTuyEfX5PYxe0MlFw5JZ1BGNK9fOohPl5dR6/BybPdQQGiXgVuXUuOqYU31GuwmO06fk8aWRiqdlbj8Lr7d8i1ndTuL3LhcAMwaM1MGT8Ef9LO8ajnegJcT0k7gpPSTeGrpU+H5Zpm2TEYkjmBV9arwfdIi0lhWtYzvtn4HwG8Vv/Fr+a88a3yWem99OGjb6YdtP3BNv2tYVb2KeFM8Va4qsmxZbdp/fOrxvLD8Beq9rSuRFDaGhmK/K/qOuaVzuWPQHQyyDKLcUc6soln0i+3H2d3OZm7p3HC7k8xJnJp5Kr2ie5EZmcmP234ML2xINCdi1php9IZyP+5Md3KkOmSBm6Ioc4G5O34uBNp8qiqK8hXw1W6v3yeUEkTqYnTJycTecAOVDz4Y3qZNT0eXno530yYCXi9177xD9XPPo/h8GHL7k/jIIxgOsydjf4W3oIDy++7Ds2o1wmAg7s47sZ1zNmqTKVQeLNaOe916xJ4pR3akwNgZtAEEnS6q/v0sKrMZ58KFRJ5zDmq7nYiTTsKxW4Ld6EsvA0XBs349no2bMA8fhtpsJmLMGBxz56IyGbHfcuths1DjQAkhsO3lCdveaNQqTuqTQEq0iZUlDZQ3uOkeH8Hw7FjqnC2sLGngnR1lnepdLUz+YAVvXz6YolonRTXOVk+zJg5L55r3loXnpykKPPbdBt68LI9VZY3kxEVQ2eRhQv9Evl5dweCMqPCiCIDSejel9W4SbUYyY0xUNnl5Y0Eh/3dGH7LjLMxcXcHK0tCCh6pmL/d8toZnz8/l6mMzefy7TfRNsqISgg+XlvK3gSnoNGpGd7PTN8mGq8VPhF7zp/tHOrRKmkrIb8hHrVJT4azgh20/4Av6OD71eDx+DzaDjfml81FQ+LXsV5ZWLiUvPo9jk49lUcUibht0G79v/515JfNaLRLY2riVUkcpI5JG8OGmDwGw6q1thh9Lm0vZ1rwNi7ZtEKQoCghIjkjm4l4X8+KKF+kX249bBtzC2+vexhvwMrHnRIYnDufFFS+2OlclVCSYE8Kv3X437214j+GJw8PDo2dlhwLS9059j4L6AoQQdIvqFk5X0iumF9NPm05+fT5un5uN9Rv575r/ApBrz6Vn9J/Lt9nVHC5P3KQjnNpsxjR8GEnP/hvP6tWorVb0PXvS+N33RF9xOUKowkEbgGfVamr/8wqJjz3aIbnTOlvQ46HquefxrAqtJlQ8Hioffhh9j+6YBw9GbTIRfemlbH/wQaImXohjztzwLHVhMoXnv+2upbAQy/jxEAjgXrMGQ//+qG1W7JMng0aDJj6e+vfew3zcseiyc9BlZlH37rsEamqwnDGBjM8/Qx0RgTY5+YDriXZ1apWgb7KNbnERlNS78PmD3Dh9BYU1ratONHl86DVq5m+uYWBaJP/7rYhLh2fw0s8F4f2+QOuVBr6AQqPbxxUjM3jr1yLMOg1/H5xKTlwEfZKtvPlLUZv2aFSCO8f1IL/SwdTxPfH6A8RZ9OGgbadAUKElECQjxsx/LhpIjFnLI99soEeiFc1u1TmizDqizDJg62rW16znqWVPsaxyGXfk3cFzvz8XLso+u3g2T4x+AqfPyQ/bfsCkNfF5wedUuioZnjicyXMmc9eQu7hnwT2MSBpBmbPtlPHV1as5NetU1tWsY23t2r2mABEIsiKzSLWkUtK8azrF+MzxjEoahU1n44UVL+D2u3H73QyMH8jxqcdj0pqIN8XjC/q4vM/lvLVu1yjCOTnnUNJUwrX9r2Vj3Ub62/ujFmpeWBHKT3l2ztkMSQg9x0m1pJJqaZvcFyDdmk66NR1fwEeaLY1ukd2w6q30iu7VKjA8EsnATeo0hszM0H+9e+NYvISAK1QcvGHGDJwLfiHuzjupfftt/NtDE1yb587FXleHLvHwSxD7ZwXq6nDMndtmu6+4GAYPxr1+PWW33UawuZmGjz8hbsqduNesRW2zYcobhL+qqs255hEjcC9fDoD11FPY/s9/ttpvPfVUlEAA04ABeAsKqH/vg/BQtXXsWIx/sgrEkazR7WNpUR0fLSvhzGOSePan/Fb706JNVDu8qFSCQEDhgQl9WFRYy72n9uSrleXEmHVY9Bqadyu1ZdFriLca+HhpMWN6xPHa/EK2VDtItBlJjjJyWt8Eftuy60mIWiUYnBnNDdN2zet56Mw+lDW4iTbr2pTo8gUU6pwtPPzNBjJizFwxKoPMGDMrSurRqgWF1S5iI3TYLTqK69xUN3vpk2TDoFXxa0Et7pYAw3Ni6J9sa7fwvdT5WgItrKpaxfKq5SyrXEaKJYVNdZvCQdtOX275kuv6Xce2qG1sa9qGVWelzlOHJ+ChzlNHlSs0D25d7TpOyTyFjXUbW52facvk9rm3c/fgu7mo10VYtVYmZE3gyy27ppenRKTQLaobCeYEXhz7IjMLZ7J0+1LGZ4xnbNpYkiKSMKqNPDbqMXxBHxG6CAwaAzlRu0ZJ1Co1V/S7guFJw9nu3E6cOQ6N0DC7eDaZ1kzuHnI3KZYUql3V5NpzMWqMZNgyMGv3v2qHVq0l155Lrj33AHu965GBm9TphBAEGxpwzZuHY3ZoUbB382Yqn34a+/XXhysDGPr0aVM4/nCk+Hy0lJSgBIMItRpfeQVqiwVddhZqc+gPkCoiAn3PnnjXrm11rjo2loDLhWvJUoLNoVQULVu2UPXkU+iys0l64gmEQU/A7Sbmumupe/c9FJcL08iR6DIyaPr2WxCCoMvdpl3Nc+eS9MTjuNeuRZeWTuR55xH0ejENGfKHFSeOJoU1DqYvKua3wlr6JdvITbVx5agMPltehsWg5e+DU/l+7XZO7BXHxoomcuxmzshNIi3ahNcXINlmwOn18dBZfXj4mw3UOFqIjdBx32m9eOfXrUSadAzOiOK1+bC8uIG7T0nA4wuwtdbJSxMH8PmKMkxaNRNyk3hwZusJ1098v4krR2Vy05hsHvpmQ3go9uTe8czeUMmybfXcckIOq0ob0apULC2qY8bSEkZkxxJl0qISVp79KX9HIuEEFhXWMjAtioe+WY+igOpHmHbVUIZnd2ySaWn/rK5eTbWrmgZv6AmrClW7KZMURaHaU02/2H6UOEr4csuXaIQGRVFQUNCpQ09Z6zx1BIIBTko/idnFs1ELNWflnEVBQwG+oI9HlzzKlf2u5J5f7uH87udz1+C7+Ln4Z/rZ+zEufRyZtlAy2+zIbG4ZeAuBYKBVdYLuMd3JjsrGF/SFV6Duyaa3MSxpWKttQxJbz4yym+ytFlpI+yYDN6lTBX0+al55FU1cHI45c1rv9PlCeccAlcVC3J13dthK04PFX1tL3f/+R+277xF/+21Uv/wfgo2hCbJRF19E7E03oYmMRG21knDvPRRfdTWKK5T6IfbmmxAqFa7Fiwk6HW0S67YUFyMMegw5OWiTkvBVVRFx0kmoNBpAUHzllaEDFQV1dNtyR7qUFAy5uWjj4wm63ZgGDTwsE+0eSnXOFm7/cBUrS0IflOvKm1hd2siUcT2It+hJjDRRUufi0uEZLCqsYV5+DVPH90CjVpGXEc3M1eXc+uEq/n1+LvmVzTzxt/54/UEMWhUfLNnGj+tDaVfirAbsFj01Di+xZh0RBg3ZsRE8/M16RnW34/D4WV3WSGl96wDc4fWTFGnAYtDw30vzWFnSgFatYk1ZIz9tqEIloHu8la9XV3DLhyuJMmm5anQWny0v4+axOdz64YrwatZX5m3h2mOzWFpUx4DUKJYX1xNU4NV5WxiUHoVOc3SUCzqczSudx8jEkeGJ/sXNxZzX4zy+K/qOoLIrx8spmafg8rmIMkRR0FBAUAnSorRg1prRq/WohZoUSwqlzaXM2DSDXHsuzxz3DAAvr3w5vNggqAQRhKZJ/FT8E++c/A4X9754r+1rr6SUWqU+akpNHS5k4CZ1Kv/27TR+9RVRF/wddVQUgdrWmbV1OdmkvPwSmvgEtFmHf+kS1+/LqX39DSzjTqbh8y/CQRtA/fvTiBgzloiRIwAwDRxI5qef0FJUhDo6Gsfs2ZRcfQ0x11yNc/ESoi68kPrp08Pnx90yGX1GBhAq3aXe8fNOmR99iLeoCJXBiDo6iqbvvsezYscwm0ZD3N13o4uLg7jWWdClXbbWOMJB207rK5rYUt1Mv5RIjFo1qVFGvlxZRvd4K1cfm01m7K4vE/YIPf6gwuQZK5k0Ip1gUGFRYS3v/rat1TVnrq7guO6xmHQaFm+tI9tuJtsewbqKZsb1TeS1eYXcemI39BoVXv+uD+icuAiizTpMOjV1Th9vLCjE49u1/8Re8bz0cz5ry0Kr6+pdPp7+YRNTTu7Bxspm9qyU9c2aCs48Jhnnbsl565wtBDo2D7a0n+xGO0GCLK9czpnZZ/J14dd8vOlj7h92PwvLF+L1exmbNpb5pfOZ2Gsitc5akiOSmdhzIkVNRSiKwtPHPc3PRT9zz5B7WFuzFpffRZQ+ivy6fEocJa1WiJ6UfhJLti8h1ZLK/cPuJzPq8P+bK8nATepkwmBAEx1N0zffEnvTTVQ+/HB4n6F/fzT2OJq+/56g04HaasV6+umYDtMVj4rPR9DtJvaGG1DHx9P8wwNtjvFXVrZ6rc/MRJ+ZiWfDRmrfCK2Cav7hR8zHHotn3Trst95C0ONFE2fHMnYsQrP3f6LapCS0SUnh1ynPPYtnw0aCjmb02dnoe/TY67lSyO4T+XcamBaJSqi4ftpymtw+zhmYwuSxOaTFtJ130yPBEl4p+s7CbXy8rJQbjs9uc1y23czEIWnkVzYzL7+GBJsBq1HDbSd2w2YMJeydvriYe07pybqKJhpcPhrdPiaNSKem2UswCFERWi4YnBZe6QqQm2rjqVmbW91LUUJF6PXtzFuzGDRkxZp5+9et4W1XjMrCqJVPTPYmqARp8DRg0pr2Ohx4sAxNHEqdp46ZW2fSJ6YPj49+nG2N20gwJfC37n+jwdOA0+dkfMZ45hXP47ye5/Hw0odRCzWJ5kTeXPsmTx33FJMHTabSWcnAuIE0tzRj1BgRimBA/AAidBGsrVnLCWknMDBuIAoKaZY0Yk1yuLyrkIGb1Km0djvx995L5eOPE2huxn7brQRdboROR6CmhpYtBbgWL4JAENuECTgXL0YdG4t+twDlcOAtK6Nh2jScS5cRefZZaKIiSXzySSqmTGl1nDa1/WoEgR2rRO1Tp6BLTsZfXY1x4ADQaFAcDowDB6JN+HMro7Tx8UfNUKjH56egyoHTG1p1Wdbg5qOlJZj0Gs4dlMKAtKj9qsmZGWvm5N7x/LB+V4B9zsBk/vHFuvDrT34vxWbUct+pvVDtds2aZi8z11QQG6HjhQuOYVOlg0iTloxoE2nRRorrQsOeZp2aUTl2flhXSZ9kK2cPSKaszolOoyagKMRa9GjVgpQoI3qtms3bm/EHFS4fkYHL6+e9RcXccmI37BE6ju9ux27Rs7q0kdQoI0MzYoi36qls8rZ6Xzq1ih4JljaLGq4enUWyzUCPeAsOr5/rjstiTA85t2hvSptL+Xjzx3xT+A3dorpxfe719Ld33BfJHtE92FS7iSEJQ1iyfQnvrH2HDFsG7298n791+xsalQaj2ohGpSHSGEm6NZ23x73N4orFNHgbmDJ4Cv1i+6FT64g1xeL0OWkJtBBlCE2lqHRWcnXk1dj0tvA8OKnrER1dK/JQysvLU5YtW3aomyHtIej14i3YQsXdd+PNzweVKlyjx3r6abhXrsK3o3Zm3JQpGHJzMecN2uc1lUAA79at+LdvR2O3o8/MROg65g+Tv7mZppkz8W0rJuhy0vDZ5wiNhuhLLkablc32e+4BrRb75JuJuvDCdufp+bZvp+G778DtpuaFXXmOrGecgTomBl9REXFTp6DPlEMXe2py+1iQX81vhXXUOryc1Due2z/alUxUrRJ8dO1wBqW3nffXnvIGN7/k17CkqI7T+iWwvqKZp2ZtanVMjFnHKxcNpF+qDaM29H333d+KuP/LUIB3Xl4yJ/ZMoNHj47FvN3DOwBSy7GaqmrwkRxqIMGjYWu0kLcbElionWo0KtQqmLS4mGFCYMr4ngaDCHR+vanXfZ8/PJSPGRO8kG3qtmupmD5WNHoIKmHRqlhbV4/b5efTbjfh3jItO6J/IxCFpbK11YNZr2Vbrwh8MMiwrhkFpUei1apxeP8GggsWoRWqf1+/l/oX38+3WbwFIjUjl1kG3UuWuospZxcD4gQyKH9QhyV5XVq1k2oZpzCudx6Tek9Br9PxU/BPdo7pzfMrxfFHwBXfm3Umqtf1UGVLXJYT4XVGUvH0eIwM36VBQ/H4qHvg/Gj/5pNX2mKuvom7a9PAE/ogxY7DffjuGbntPxKsoCs2zfqB8ypRQHji1moQH/kXkmWe2Cd5ayspxzJtH8+zZmIcNxXLSSeF5ZPvLuex3mmbORBMfR83zL7TaF3//P1ECQfRZmZiHDEFo24OEKNYAACAASURBVH4wBpxOfOXl+BsbafziS5o+/bTVooTk55+n7JZbsJ5+OomPPoKqgwLQrmrhlhpumr6COmcLw7KiAVhUWIfNqGVcnwS0akGc1cAtJ3QjGFRaPSXbl9J6F7d/uJLzBqWyqaqZmuYWvl9XgccXZGBaJOfnpZJg1XN8z3gaXS1c8uZiclOjsJm0LNlaR6JNz/ZGD4u3hrLEP3Z2P/77y1YmDk3lie82cfMJObyxoJAmd2gBjloleOa8XJ78fiPpMSaizDq+XbO9VZtG58RyZm4CmXEWBqVHt9o3Z1MVt3+4kn+e3osok478KgeRRh0ajaCq0YNBpyY50sSAVBuxFlkxYX+VOcpwtDjQqrRcPetqLut7Gb6Ajx7RPXh62dNsadxVMeOuwXftczL/X1FQV0B9Sz2KorC+Zj0mnYlsWzYmrYlUSyoRusN74ZZ0YPYncJNDpdIhITQaoi+6CMecOeEFCvru3VECwXDQBqCJj0fzB8N/vuJiyu+9N5y8l0CA7Q/8H8b+uRh6dA8fF3C5qHrmaZq/DZV1cf36K03ffkfq66+hte//cJGvvAxD3z40fPBBm32uxUswHJOLNiGh3aDNtWEDLZs24Zgzh6DLjXn0aIz/up/KB/4vfEzQGUr+2vT999hvvw3dYTZMfKgVVjupc7YgBBzX3Y5WrWJC/yTcvgBv/rIVXyDIxcPS+XplGe8u2saonFiO62HnmNS9P4FztfhZXFjHgLQofi+u58uV5STYDNxxcg8+WlrMhNwknv1xMzeNzcHTEkAAZxyTzKvztlDrbOG47nbG9oznvs9D6V7G900gyqzl7AFJPPLNBiwGLXXOlnDQBqEkuh8uLeH647MpqHbgaWlbAD7CoMFuNVDd7G2zb2FBDfUuH7d/tBqzTk2PBGt4yHXi0LQ2gZ60by2BFmYXz+bhRQ/T1NJEz6ie3D/yfr7d8i2jU0ZT465pFbQBvLTypXBOs4MtJ3rXl9U902dIRzcZuEmHjKFXTzI+nIG3oACh1aKyWCi+9LLwfmE0YjtjAhrrvoci/HV1rYI9AAIB/NXVsFvg1rJtWzho28m7YQMthVv/VOCmTU7GvXwFupxueNatb7PPlDcYfXbbCereoiJ8RUVU/OOfsCPtiXPBAhL+dT+6bt1oyc9HGAyooiIB0GVkoDLvfyLKo0GDa9d8rWtGZ/Hp8jIKqx3ccXKPVsObz/2Uz+QTclhX3sTSonp+K6zln6f1ok9yZKvrtfiDLC6s5Z2FRRyTaqO8wc3XqysA2Frj5LFvN/D8BQN4cOZ6qpu9bKt1EUShoMbJw99sCF9n7qZqTDo1lw5P5z9zt9An0Up+ZTOxFkN4WNOxW3Le8PtxtzA/v4ZjUiPpmWDhi5Xl4VWlWrXglL4JrKto5oQebVcGp++2WMLZEmB5cT0n9Y5nUHqkXGywn7Y0bKHcUU5QCWLRWbhr/l0ohJ5+b6zfyH9W/CcclG13bm9zvtvvxhfwdWqbJUkGbtIhpUtJQZeyawJ/+vRpoWoAQmAcOBBjr15/eA2NPQ6VzdYqFYfQ6dAm7u/kfgUlGERpaUFl+OMhJWPv3njWrsV66ik4580j0BBKJ6FNTsY8bBimfn3bPa+lrAz3ypXhoG2nhs+/wDp+PI0tLcTdeQd1b70NWi0J992Hxmbbz/dwdBBAglWPPUKHEFBQ5SAnLoK1ZY1tjv0lv4aBaVH8UlCDQJBf5eSzFeWkRBk5vrsdvVZNTbOXK99dii+gcG5eCi/83LqYdlCBzZXN4Sde9a4WTDoNW6raliD7aX0VX9w4kkWFtRh1ajZUNKFWqVAJqGj0kG1vO7R1Qq943vm1iBizju52E8/+PZelRfUEAgoD06NYX95E93gL3RPafnkZkR1DerSRbbstghieFc3y4kbOzE0+kO49qiyvXM5PxT9R4aige1R3InQR4aBtp/V16xmVMipcicCkMeHy7/qSeHrm6R3ytE2S9kUGbtJhxdi7N8bevf/UObqUZJL//Qzld9xJoKEBldlM4mOPottjYr8uPR3LKeNp/u778DZ9r16obTYqH3oY9+pVWE+fgGXcyeHhSU9+Pt78fFR6PfpevdAlJaEyGom+6CK8hYUkv/giLUVbQVHQZWdj6LX3tgedToS6nX9yKkHECWOJOPkkAo1NRE+8EN0/7kPfrduf6oejgc2kwx8I8vR5uczc8WSs0e0jpp16nHaLntJ6NzFmHXkZUdz64UqEgNtO7M6j321g/uYacuIiuOeUXrw8p4BtNS7irYY2SXB3Lwc1rk/oy0Ckqe0weFqMkcRIAw+d2Zd15Y30TbYxfXExN47J4dV5W/h6VTn3ntqTL1aU4fAGOL1/IvmVDhxeP8lRRubl1zJzTQXnDUrBZtSiAKtKG5k0MrPdWrJZ9gjeu3IoS4vqqWh0oxAqVn/FyAzMBrnoYF/Km8v5fuv3xBhjMEaGVmnadG2/JMWZ4qj31KMxapi+cTo3DbiJ+aXzKWkuYUTSCM7tdi5atexrqXPJwE06IkSMHEnGp5/gr6pGExODLq3taiu1yUTclCmY8gaHFyeYR4yg+KqrwzU8PevW483PJ+Ff9+NZv57iy69A8XgA0GZlkfbqK+jS0hAaDYbuoWFY8+B9ziMNU2m1GHr3Bq0WfLuGV6IvvgT38hVET7zwr3bDUWFUtziWFtVxTKqNj38vpbrZS2KkEZtRS6M71K8GrYrBGdHMWreBS4enM21xMQDHd4/j14IaFm+tA0KVErZUb+S647J5aU4BU8f14F9frwuvFemdaKXJ5SParOOOk7uHF0P0S45kWFY0iwpD19GoBP+a0Icok45IoxZ/UGF7o4fje9j5bk0F1x+fTaRRR99kC0Mzopm2pJjpS4ppcPlIiTKSZDPwzA+hfGxvLNjK2J52clNsvHDhAOwW/V77Ii3GTFqMmXpHC80tPpIjTfuVBuVoVeGoYFnlMhq8DVS6KvlgU2ieqkDw0MiHOCvnLL4o+AIAjUrDJb0v4fVVrzMmbQzp1nSeXPokg+IHcYz9GJIjkukWJb9cSZ1PriqVjmrNc+ZQev0NrTeqVGR9M5PKx5/AOW9eq12Jjz5C5DnnHNC9HAsX4tm4EV1KKo65cwk6mrGMG0fA48Gcl4c+Pf1A38ZRqc7p5f1F23h5zhZ0asH9E/qgKKHKYRmxZtaUNjJvczXnDkpm6idrcPsC3Dw2hxf3GA4Fwttz4iL4x2m9KG9wY9Sqybab0WvVWA1aEiONrc6pbHKzoaKZJreP7LgIeiVYW61gbXC3sKG8ie2NocA/qCj8sG47U8b3oMHlZ0u1A4NGTXqMCb1WzYLN1fxWWEteRjSD0qPom2wjQi+/Wx8sTd4m7vvlPuaWzuXGY27k5ZUvt9pv09t4Zewr+BQf9d56Yg2xrKhawdeFXzMkfginZJ5CUXMR+fX5DIgbwAD7AKKM+5dyRpL2l1xVKkl/oN3KBGo1SjBIS2Fhm10tO/LL7Y03P5+mWbPwbNiI+bhjMfTqhSEnB5XRiKFXbxxz51H33zcx5uaCAH9NDVVPP0PWl18crLd01Ig267lxTDfOyE3GH1RI3ZHAdqfBGdGcOyiFQCDI1aMzeeHnArz+IBF6TZuFApmxZm4/qTsjsmPonxKJTtO26sCe4q1G4q3Gve6PNOrCxdurGj04Wvyc0i8Rky70O5eX0XrVZ69EK9cc13ZRi7T/Gr2NlDWXEVACxBvjiYvYtaijsLGQuaVzAfAF2y4oaPQ2olVr6RfTL7wtNy6X83ucH6o8IAT94w7PKi7S0UUGbtJRTd+tW3hF504xV1yBPj0d2zlnt8nTZhq09y9CLcXFFF91Nf7aWmIun4S/rJzmbdvw9e2HJj4OtdlMxNgxqK0WCATx19dT/cy/wedDCbRNBSH9MbVKkBG795W31h0JZi8alkZMhJ4f11dy/fFZrcpEjelh57judmIi9j4k+VfF2QzIirEdq6ihiE0Nm/ii4AsKGgoYmTSSc3LOCQdbuwdrWpUWjdDgV3YF8IPiBpFiaVvpxKQ1dXzjJelPkIGb1KUoitLuRO0DpU1IIOXll3DOX4BnwwYiRo/GNHgwQqPBdsaZBGrrqP/wQ1QmE3F33oExd+/fuL2bN+OvrCT68kk0ffd9uPoDQNx991H7yiskPvYoDR99hL+qOrzPcsopaFPaL40lHRzxViOXjcgIP4HLy4imsNqJPUJPvxRrhwZtUucoai7ikUWPUO8NJUD+NP9TSh2lPHPsM9gMNjJsGWRaM9natJXP8j/jtkG3MW3DNMqd5YxMGsmdeXfKpLZSlyADN6lLCLhcuBYvpv6DD1BbrERdeAHGAQMQ6gPLV6UoCp61a3H+8itKIIB51CiiLryg1fV0yUnE3zWV6EmXITSaP6wdquwo26WKiGgVtAHUvf46URddRNmtt5H23//S+PVXuJevwHraqVhPOw21ce9DbtLBY94xZ2xoZgxDM2MOcWukg2lb07Zw0LbT4orFlDhKsBls2I12nh3zLB9v/pjfyn+j0dvIyye8HKrraYyVT9akLkMGbtJ+8VVV4SsrQ2WxoE9Pb7cqQEdy/rqQsptvDr9u+v570qdNw3RM7gFdz716DcWXXILSEkroWvPqq6S/8w6mvEEEXC48GzfiLytDk5CAvlcvNO3UG91d0ONBm5CIOioKAsE2+wNNTWjsdiLPOZug203CP/9J0OtFbZIfFpJ0MFi0bXPdaVQaTJpd/8ayI7OZOngqLp8Ls9Z8UJ/eS1Jn+eMZuNJRz712LUV/v4BtF05k69nnUPf++wT2rFTQgYIeD7Vvvtl6YyCAc/689k/YD03ffBMO2gDw+6n/4AOCbjcNH32Ma+FCvFsKcS1ZiuPHn/DtSBfSHl9VFZWPP862SZOIvvxytKmpbQJb62mnUffOO6BSo01NQajVMmiTpIOoV3Qvcu2tv8hN6jOJNGtaq20qoSJCFyGDNqnLkk/cjkItJSX4yspQR0aiy8raZxHzQFMT2x98CH9FKNkpPh9VTzyJMTcX08CBndRiEJp2hkQPcJgUINDYNtN+oLERz9atKG43Na++FqpwoFIRc+21aAsL0cbGtnst15IlNMz4EIDqf/8b/THHkPzC89S+9Tb+8jIixoxB8QdCq1RVKuyTb273OpIkHbhesb34x9B/sLpmNaXNpfSL7cfgxMFoVPJjTjqyyN/oo4xr6TJKbryRYFNTKIi47TaiLpq416c//vp6PKtXt9neUlr2lwO3gMNBS1FRqOpARgZqS/s1SVUGAzFXX03pst/D24RWS8ToYw/43rYzz6Dpyy9bbYuaeCHBxkZqXnttV1mqYJDaN97A0L9fO1cJcS5a3Oq1d+VKal5/g+hJl+GY/TPNP/6Ev7ISCNVnVcn5bJLUIXrG9KRnTM9D3QxJ6lByqPQo4q+tpfzee0NBG0AwSPUzz+DdvHmv56htNnTd22YH1ybE/6W2tJSVUT71LorOPY+i886n7PY7aCkp2evx5iFDSHvrTWxnnknUxReT9t67GPZSE3R/mAYMIOWVVzAMHIihXz+SX3ge09Ch4POHKyWE+f3g8e71WsZ22mHs3w9Djx541q0LB20qq5XoSZPazx0nSZIkSftBfoIcRfx1dfjaCY7827fv9RxNZCSJDzxAyXXXhwO+6GuuxtDzr32rdcybh+Pnn8OvnQsW0PzTbGIun9Tu8SqjEfOIEZhHjPhL9939epYxx2MaNgxQwqs6tRkZqKzWXcEtIAwGtOlpe7kSmEeOxDhoIO7fl4eukZpK5Lnnoc/IIPWNN/Bu3oTi86HPyUG/R/1USZIkSfozZOB2FNHExKDNzMC3taj19sTEfZ5nGjiQzE8/oaWkBLXNhj4r6y8P9znmtl1Y4Jjz814Dt935a2sJeL3g9aIEAmiTkg54or/aaGj1Wp+WSvKz/95VsN5qJfHRR/YZqOpSUkh58UW8BQUo/gD67Cy08aEnkrqkRHRJ++5fSZIkSdpfMnA7imiio0l65FFKb7qJQF0daLXET50SLpa+L7rUVHSpbQu3HyjzyBE4589vvW3UqH2eo/j9OH5dSOOXX6JNiKf+gxkobjcRY8cSd9fUcK3PQHMznjVr8W7ZgjYpEUO/fmjj9j9vfcTIkWR89in+6h0F6/cjOa4mOhrNkCH7fQ9JkiRJOhAycDvKmAYOIOOTj/GVl6O2RaLP+Os52ZRgEKH6c9MlLWPG0PzDD+HhRUP//lhOPnmf53g2baL0hhuwT76Z6mefA0Dftw+R55+Hv6YGodejMptpmDEjVEpqh4gTxpL48MNoova/ILQuKQldUtKfek+SJEmS1NFk4NaFBb1eWgq34q+rRZucjC49fb9yEx2soMRfW4tjwQIaP/sMfY8eRJ5zDoZevfbrXF1aGikvvRQu5K7LzEITve/AqmXrVlQGPf6aWgAiL7wQ89Ah1Lz0Ep516zEOGoR98s3UvPhSq/Mcs3/Ge1kBmiGDD+BdSpIkSdLhQwZuXVTQ7ab+gw+oevoZCAYRRiMpLzxPxOjRnXJ/RVGo//hjap57HgDXkqU0fvkVGTNmoM/avwn4mqgoNIMG7fc91VYbilChtlkRej3mUSPZft8/CDQ0AOBetgz3qlWtE+vuEOzEhMGSJEmS1FFkOpAuyltQQNWTT8GO+piK2035Pffi28cK0YPJX1FB7etvtNoWbGrCs3Fjh9zPV1VF0O0i+oIL0GVlYTn9NHylpeGgbSfP6jUY9sgvp7JY0GdmdEi7JEmSJKkzySduXZS/sqrNtkBNDYH6+j8shn5QCIEQAqXj70SguZmqJ5+iaebM8LbEp59qtyZo85w5JD//HE0xMTgXLUKfk0PURRPRyvlqkiRJ0hFAPnHrojRJibDHfDZNUhLqvZRlOti0iYnE3nhjq23q6Gj8VZU0zZpFwOFo9zwlEMC9Zg31H35E48yZeIuK/vBe3i1bWgVtABVT70KXlUnkZZdiO+dszKNHg1pNzFVXUfP8C/gqKrCdMQGV2UzlE0/i3+PJnCRJkiR1RfKJWxel79aNxEceYfuDD6J4PKhjYkh68gm0dnuntcF2ztlok5JonDkTTUw02sREqp97HsXrJeXll7CMHdvmHOfSpZRceRUEAkAoh1zaW2/uMzFt0O0O/aDREDVxImqrBRQFgkHUBgON389Cm5JCyksvomi11L76KgCetWsBsIwfj9pqPcjvXpIkSZI6nwzcuiiVVovtrDMxDjiGQEMDmoQEdH+QSBdCudBQq/dr9ekf0URGYh0/Ds+GDTR99x32m28i7u67CTodKD4/Aa8XtV4fPj7gclH9/AvhoA1Cc+Vcv//eKnALer20FBWh+Hzo0tPRZ2SgsduJvODvNH72Gb6ycvTdu9FSVkbTF6F6o/7KSspWrybt/fexTphA09dfh9qYkEDsddei2q0dkiRJktRVycCtCxMq1X6XUPLX1OCYP5+GTz5Fl51N1N/Px9j3wGt97i7odGK/ZTK1r73equ5p4uOP4d28GcuYMRhzc1G83nDdzt0F6ut3tbO6mppXXqX+gw9AUTANHUrC/z1A6ptv0vjpJ/jKygGIOO446t75X6vrKD4fvm3bSLj/n0RffBFBtxtdRkbnzPmTJEmSpE4g57gdBRRFoeGzz6i49z7cy5fT+PHHFF82CW9BwUG5vvXsswg0NrUpVl/97HMIvYFtl16Ga/lyNFFRRE2c2OZ804AB4Z9dv/9O/fTpoaFQwLV4MQ2ffoq+Ww6eLYXh44IOJ6p2hj+F0YDaYsGYm4t52DAZtEmSJElHFBm4HQX8lZXUvvZ6q21Bp/Ogpe4w9u6N0k6eNH9tLZrYGFAU6v73Lorfj23C6cROnow6KgpdZiYpL7+EoV+/8DmuFSvaXMfx02yCDgfW8ePC25q++65NEKjLzsbQu/dBeU+SJEmSdDiSQ6VHAyHaLWslVOqDdHmBrns3UKtbzV+znnoqjd9+C4TmrQFo4+OJvf46Is/9G0KnQxMZ2epa7VVeMA0ZgspkImL0aKIuvpj6Dz4g0NyM0GhIffO/eNZvQBNnxzRgALrk5IPyniRJkiTpcCQDt6OANj6e2JtvpvKhh8Lb1NHR6HvvX3mq/WHMzSXpqSep+c8r+CsqsJwyHmP//jR99RUA0ZdcjNCEft2EEHst+m4aPCRUgP7XhaG2p6QQddFEhFqNNj6euLumEjXxwtC+1FRUWi0RI0cetPchSZIkSYczoSidkUL10MjLy1OWLVt2qJtxyPjr6wm6XGji4lBcLpxLl9H8ww/oMzOIOOEEDN27H/R7tpSWong8BDweal/+D0Gvl+hLLsY0dChqk2n/2t3QQMuWLQRbWtBnZaGNjz/o7ZQkSZKkw40Q4ndFUfL2eYwM3I48it+Pc+FvbH/kEXzl5dgmTCDm2mvQp6d3ejuA8JM2SZIkSZL2bn8CN/mJegTybNpEyfXXh+ebNX72GYrfT+LDD6HS6TqtHTJgkyRJkqSDS64q7eL8DY24li/HuWgxvh050lq2bGm1SACgaebMdnOoSZIkSZLUdchHIl2Yr6KCigcewDlvPhCarJ/yn5fbzW+msdsRRmNnN1GSJEmSpINIPnHrwlxLl4aDNgBfSQn106Zh6NED46BBuw4UgoR//ANtJxWglyRJkiSpY8jFCV2Qv6EB7+Z8vJs3E2iop+HDj/BXVwOgy8wg46OPQgl2168n0NiILisLQ+/eqNrJ5XYglEAglBtOJeN+SZIkSTpY5OKEI5Cvtpaqx58IF1EXej1xt99O1b//jeL1EjFmLCqzGbXFctDLPQWcTlyLF1P3/jTUERFEXXIJpgHHyEUIkiRJktRJ5CduF+PdsCEctAEoXi/1Mz7AMm4cvtJSIs87t8OehDkXLqTs5snh182zZ5P+/nutao1KkiRJktRxZODWxfhra9tsa9laROITT6BLT0djs3XIfYMeD7VvvtV6YyCAY+5cGbhJkiRJUieRgVsXo0tLa7PNfOyx6Lt1Q92Rq0aFQLSTA669GqiSJEmSJHUMObu8izH07EniIw+jMptDr3P7Ez/lzo4N2gCVXk/sVVe22iZ0OiKOPa5D7ytJkiRJ0i5yVWkX1VJaStDpRJuYiLqdvG0dIej14l6xgsaZ36C2WEKF5Pv1QwjRKfeXJEmSpCOZXFV6BNOlpHT6PVV6PeZhwzAPG9bp95YkSZIkSQ6Vdoig14u3aBu+7dsPdVMkSZIkSTqCyMDtIPNu20b5PfdSeMopbD3rbBq/+oqgx3OomyVJkiRJ0hFADpUeIH99Pa6ly3DMmYO+Wzcijj8OTUICzt9+Q5+eju7aa2n+4QfKp95FelIyprxBf3xRSZIkSZKkfZCB2wFQgkEaPvqI6mefC2+rmz6NpMceo+6tt/EVFyO0WqIuvgh3VBTeLQUycJMkSZIk6S+TgdsB8JWXU/PKq622+UvL8Kxeg6+4GADF56Pu7Xew33oL6uiY0DZFwbNhA95NmxA6PYY+vdFnZHR28yVJkiRJ6qJk4HYggsFQofU9N7ucbbYpgLFvHwDcK1ZQfNkkFJ8PAE1cHGlvv4U+O7tDmytJkiRJ0pFBLk44ANrERKIumthqmzoyEpXJ1OZYQ+/eaBMTCXq91Lz+ejhoA/BXVeFctLjD2ytJkiRJ0pFBPnE7AEKrJWbSJDSxdppnzUKXmoqhbx+E0YjKYiHY3AxA1MSJGPv3B0BpacFXUtrmWr5KmTJEkiRJkqT9c0gCNyGEGlgGlCmKcroQIhOYAcQAvwOXKIrSssc5GcAGYNOOTYsURbmu0xq9B21CAtZTxtNSXIxnxQqavv0WVUwMyS++QKCuHo09FkPv3qh3lKZSWyxEXXABlY880uo65uHDD0XzJUmSJEnqgg7VE7dbCAVhO2s1PQE8qyjKDCHEq8CVwCvtnLdFUZRjOqmNf0iXnEzstdfgWb+eQH09Qq2m4bPPsI0b3ypo28kybhyB5mbq3nkHldlM3O23Y8zNPUStlyRJkiSpq+n0WqVCiBTgf8AjwO3ABKAaSFAUxS+EGA48oCjKuD3OywBmKorSd3/v1Vm1Sl2rVrHtoovB7w9vS37heawnn9zmWEVR8FdVITQaNDExHd42SZIkSZK6hv2pVXooFic8B0wFgjtexwANiqLsjHpKgeS9nJsphFghhJgnhBjdwe3cb85ffmkVtAHUvvFfAi5Xm2OFEGjj42XQJkmSJEnSn9apgZsQ4nSgSlGU3w/g9AogTVGUAYSe1E0XQlj3PEgIcY0QYpkQYll1dfVfbPH+ESp1240aDQi5aFeSJEmSpIOnsyOLkcAZQogiQosRxgLPA5FCiJ3z7VKAsj1PVBTFqyhK7Y6ffwe2AN3bOe51RVHyFEXJs9vtHfMu9mAePQqh07XaFnvN1aiNhk65vyRJkiRJR4dOXZygKMo9wD0AQojjgTsVRblICPExcC6hYO4y4Ms9zxVC2IE6RVECQogsoBtQ2Flt3xdDnz6kvfcuTTO/IdDYiO3MMzANHHiomyVJkiRJ0hHmcMnjdhcwQwjxMLACeBNACHEGkKcoyv3AscCDQggfoflx1ymKUneoGrw7IQSm3FxMcoWoJEmSJEkdqNNXlXamzlpVKkmSJEmS9FcdrqtKJUmSJEmSpAMgAzdJkiRJkqQuQgZukiRJkiRJXYQM3CRJkiRJkroIGbhJkiRJkiR1ETJwkyRJkiRJ6iJk4CZJkiRJktRFyMBNkiRJkiSpi5CBmyRJkiRJUhchAzdJkiRJkqQu4ogueSWEqAa2Hep2HEZigZpD3YijmOz/Q0f2/aEj+/7Qkv1/6BxI36crimLf1wFHdOAmtSaEWPZHNdCkjiP7/9CRfX/oyL4/tGT/Hzod1fdyqFSSJEmSJKmLkIGbJEmSJElSFyEDt6PL64e6AUc52f+Hjuz7Q0f2/aEl+//Q6ZC+l3PcJEmSJEmSugj5xE2SJEmSgXCpUwAACKFJREFUJKmLkIHbEUYI8aEQYuWO/4qEECv32J8mhHAIIe7cy/nThBCbhBBrhRBvCSG0ndPyru8g9P1NQogCIYQihIjtnFYfOQ5C/2cKIRbv+H/woRBC1zkt7/r21vdCiCG7bV8lhDh7L+ePFUIs3/F3539CCE3nvoOu7SD0/wk7+n+lEOIXIURO576Drusg9P2C3Y4rF0J88Yf3lEOlRy4hxDNAo6IoD+627RNAARYrivJ0O+ecCny34+V0YL6iKK90RnuPJAfY9wOAemAukKcoisy9dIAOsP8/Aj5TFGWGEOJVYJX83f/zdu97IYQJaFEUxS+ESARWAUmKovh3O15FKN/mCYqibBZCPAhsUxTlzUPyBrq4P9v/O87ZDJypKMoGIcQNwBBFUSZ1euO7uAPp+z3O/xT4UlGUd/d1H/nE7QglhBDA+cAHu207C9gKrNvbeYqifKvsACwBUjq6rUeav9D3KxRFKerwBh7hDqT/d5wzFvhkx6b/AWd1bEuPPHv2vaIort0+qAyEAuc9xRD6gNu84/WPwN86uq1HogPsf3Zst+742QaUd2Q7j0R/oe93nm8l9DfoD5+4ycDtyDUaqFQUJR9ACBEB3AX83/6cvGOI9BLg+w5r4ZHrL/W99JcdSP/HAA27/aEtBZI7tJVHplZ9DyCEGCqEWAesAa5r54lDDaARQuxMVHoukNoprT3yHEj/A1wFfCuEKCX0d//xTmntkeVA+36ns4DZiqI0/dGN5DyCLkgI8ROQ0M6u+xRF+XLHzxey2xMH4AHgWUVRHKEvBn/oP4SGSRf8lbYeaTqp76W9kP1/6Bxg36MoymKgjxCiF/x/e3ceY+cUh3H8+7QUkViGqi2WSBBLbJGQWBqhaEPUWkQQ9QdiKaqWYCTWNCqoRIRUpfYtSi2NWGoPEa21VIit1tZOK52fP8659Xrdmd65Y2773nk+yc2d97znfc95T26aX8/yHqZKeiIi/iycD0ljgOskrQLMBJb0y0NUWH+1fzYOGBkRr0kaD0wiBXNGv7d9zdHArQ3Vx3Pc2k+e2PslsEtEfJHTXuCf/8WuBXQBl0TE5DrXXwrsBBwaEV2tqXV76Gvb5/yf4jluTWm2/fMwx3fA+nlOyu5AZ0Ts39IHqLB6bV8nzzPAeRHxRg/3GQGMjYgj+6em7anZ9pc0FHg1IrbIx5sAT0bENi2odlvo629faTHaXGCjHgK7pdzj1p72BT4o/oAiYs/a35I6gV+7CdrGAvuTJgo7aOu9ptve/hdNtX/u9XmWNEx3D3A88AjWG/9pe0mbA5/nYHhTYGvg0/KFktaLiG9zj9sE4IoW1bmdNNv+C4E1JW2Z5xnuB7zfojq3i6Z/+9nhwGONBG3gOW7tagylLtueSHpc0ob58GZgGPBKXp58SX9UsI013faSzshzTDYG5khqqNvc/qUvv/0JwNmS5pHmvHlVY+/Ua/s9gNlKr0h4GDi11pNcavvxkt4H5gCPRsQzrap0G2mq/fO8q5OBByXNJs1xG9/CereDvvz2u7u+Wx4qNTMzM6sI97iZmZmZVYQDNzMzM7OKcOBmZmZmVhEO3MzMzMwqwoGbmZmZWUU4cDOzFZ6kTknLfQm8pOckPVc43jHXraMfyor83jkzs6X8Al4zs8adWjreEbgUmAYsaH11zGygceBmZtagiHhvedfBzAY2D5WaWeVIWkPSZElfSVokaa6kcSrsIi9peB5uPDjn/T5/pklaq3S/oZLulvSzpIWSpuTrQtLwQr6lQ6WSTgCm5FMf5bwhabP8iZynWM7wOvccLOlySfMl/Z7L2Lab595B0vRcxz8kvSRpz3p5zaw9OXAzs0qRNAiYAZwIXAscBDwJTKL+HpfXAwEcA1wGHJbTih4CDgQuIG0/8xdw4zKqMgO4PP99BLB7/szv1QNBJ3AhcCdwCDATmF7OJGln4GWgg7RF0WHAD8DTknbpZZlmVlEeKjWzqhlJ2gfwxIi4PafNlLQ6cI6kSbU9AbNZEXF6Id9WwFhJJ+TN5Ufk+x0VEfflfE9Jmg5s0l0lIuI7SR/nw7ciYl7tXKHjr0eS1gbGAbdExLmFOi4Bri5lnwh8BuwTEYvz9U8B7wAXk4I+M2tz7nEzs6rZC+gC7iqlTwOGkHq9imaUjt8GVgGG5ePdgCWkjaCLHuhzTZdte2B14L5S+j3FA0mrAXsD9wNdklaStBIg4GlSm5jZAOAeNzOrmg5gQa3XqeDrwvmi8mrPRfl71fy9AbAwIv4q5fumT7VszAbdlFU+7gAGk3rWLq53I0mDIqLr/62ema1oHLiZWdUsADokDSkFb+sXzvfGfGBtSSuXgrdh3V3QgD/z95BS+jp1yq6V9W4PZf9I6mW8CbijXoEO2swGBg+VmlnVPE/6t+uIUvqxwGLglV7e71VSb9boUnr5/vXUeu9WK6V/k89tV0ofVTqeA/wGHFlKH1M8iIjfgBeAHYA3I+KN8qeBuppZG3CPm5lVzRPAi8DNkoaSeqpGAmOBq0oLE5YpImZKegm4RdK6wDzgcFKQBKmnqzu197qdJmkqaTXqnIhYLOle4CRJHwJzSUHb8FLZP0q6DrhI0i+kFaW7AifVKetsYBZp4cRtpN66dYGdgcERcX5vntvMqsk9bmZWKXlIcBQwFZhAWnwwihTYXNTkbUeTXilyDWmhwKr8M5fspx7qMpv0Oo+DSMHk68CG+fSZpNeMdAL35nue/p+bpPNXAseRXgMyIt+vXNabpKDuB+AGUpB3PWmBw6yGntLMKk8Ry337PzOzFY6kyaR3xXVExKJl5TczawUPlZrZgJd3OFiTNOw6BDgAOAWY6KDNzFYkDtzMzNICgbOALUjvePuEtJvBxOVZKTOzMg+VmpmZmVWEFyeYmZmZVYQDNzMzM7OKcOBmZmZmVhEO3MzMzMwqwoGbmZmZWUU4cDMzMzOriL8BDVsUjP0pdVgAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***above scatterplot shows that the hotels listed by location*** "
      ],
      "metadata": {
        "id": "35Jbaj4GsveZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#price hike\n",
        "bnb[bnb.price<100].plot(kind='scatter', x='longitude',y='latitude',label='Map of Price Distribution',c='price',cmap=plt.get_cmap('jet'),colorbar=True,alpha=0.4)\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 254
        },
        "id": "gNX8MwtlvlQ9",
        "outputId": "73ac1046-73f7-4a55-86f4-26dc886e93df"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***The information we got from the graph above is red color dots are the rooms with a higher price. Also, we can see that the Manhattan region has a more expensive room price.***"
      ],
      "metadata": {
        "id": "QMzt6WRJpnGk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#prices per location\n",
        "plt.figure(figsize=(10,6))\n",
        "plt.title(\"Neighbourhood Group Price Distribution<500\",fontsize=16)\n",
        "sns.boxplot(y=\"price\",x ='neighbourhood_group',data = bnb[bnb.price<500])\n",
        "plt.xlabel(\"neighbourhood_group\",fontsize=16)\n",
        "plt.ylabel(\"price\",fontsize=16)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 412
        },
        "id": "S7V7C6SAzPmL",
        "outputId": "9d6d9177-9e77-434d-db1c-89cf7cf9c06e"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***1-We can say that the Manhattan has the highest price range for the listings,***followed by Brooklyn\n",
        "\n",
        "2-***Queens and Staten Island seem to have a very similar distribution***,\n",
        "\n",
        "3-***The Bronx is the cheapest***."
      ],
      "metadata": {
        "id": "PCqhOUyNp_Oq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#locations with total reviews\n",
        "location_reviews = bnb.groupby(['neighbourhood_group'])['number_of_reviews'].sum().reset_index()\n",
        "location_reviews"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "Y5YaayAKCZp3",
        "outputId": "a4463bbe-28f8-4347-cd53-87ddae3c876d"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  neighbourhood_group  number_of_reviews\n",
              "0               Bronx              28371\n",
              "1            Brooklyn             486574\n",
              "2           Manhattan             454569\n",
              "3              Queens             156950\n",
              "4       Staten Island              11541"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d34bb6e8-8ca1-4c96-87ca-51bb86ee28aa\">\n",
              "    <div 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>neighbourhood_group</th>\n",
              "      <th>number_of_reviews</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Bronx</td>\n",
              "      <td>28371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>486574</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Manhattan</td>\n",
              "      <td>454569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Queens</td>\n",
              "      <td>156950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Staten Island</td>\n",
              "      <td>11541</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d34bb6e8-8ca1-4c96-87ca-51bb86ee28aa')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-d34bb6e8-8ca1-4c96-87ca-51bb86ee28aa 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-d34bb6e8-8ca1-4c96-87ca-51bb86ee28aa');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#number of reviews per area\n",
        "area = location_reviews['neighbourhood_group']\n",
        "review = location_reviews['number_of_reviews']\n",
        "\n",
        "fig = plt.figure(figsize = (10, 6))\n",
        "plt.bar(area,review, width = 0.4)\n",
        "plt.title(\"Area vs Number of reviews\",fontsize=16)\n",
        "plt.xlabel(\"Area\",fontsize=16)\n",
        "plt.ylabel(\"Reviews\",fontsize=16)\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 411
        },
        "id": "SoHVLktRnlz8",
        "outputId": "ccc6f21e-3875-482d-edda-c2d3f9d1225c"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***above bar plot shows that the brooklyn has a most number of reviews followed by manhattan , least reviews on staten island***"
      ],
      "metadata": {
        "id": "z9uooJyutXoy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#price preditions with the help of reviews\n",
        "price_area = bnb.groupby(['price'])['number_of_reviews'].max().reset_index()\n",
        "price_reviews=price_area.head(5)\n",
        "price_reviews"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "Ve1A9ikr26sd",
        "outputId": "6b666690-22dd-40f2-bc2a-24ec6b07fe01"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   price  number_of_reviews\n",
              "0      0                 95\n",
              "1     10                 93\n",
              "2     11                113\n",
              "3     12                  8\n",
              "4     13                  9"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-97d7b969-5b8d-4c64-9629-eb72416f0426\">\n",
              "    <div 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>price</th>\n",
              "      <th>number_of_reviews</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10</td>\n",
              "      <td>93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>11</td>\n",
              "      <td>113</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>12</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>13</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-97d7b969-5b8d-4c64-9629-eb72416f0426')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-97d7b969-5b8d-4c64-9629-eb72416f0426 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-97d7b969-5b8d-4c64-9629-eb72416f0426');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#prices and review relation\n",
        "price_reviews.plot()\n",
        "plt.title('price vs number of review',fontsize = 16)\n",
        "plt.xlabel(\"Price\",fontsize = 16)\n",
        "plt.ylabel(\"Number_of_review\",fontsize = 16)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 302
        },
        "id": "sv7tm8lt7HHr",
        "outputId": "475df3ec-e8af-4829-8d76-03ccf6d72a7f"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***From the above Analysis we can say that most people prefer to stay in place where price is less.***"
      ],
      "metadata": {
        "id": "6X3N3P22uAjQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#top five busiest hosts\n",
        "busiest_hosts = bnb.groupby(['host_name','host_id','room_type'])['number_of_reviews'].max().reset_index()\n",
        "busiest_hosts = busiest_hosts.sort_values(by='number_of_reviews', ascending=False).head()\n",
        "busiest_hosts"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "VRejquVv7OXl",
        "outputId": "365b2f8f-6fe7-46da-ad01-1d3b1508cb47"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      host_name   host_id     room_type  number_of_reviews\n",
              "10279      Dona  47621202  Private room                629\n",
              "17708        Jj   4734398  Private room                607\n",
              "25566      Maya  37312959  Private room                543\n",
              "6235      Carol   2369681  Private room                540\n",
              "8947   Danielle  26432133  Private room                510"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-6e10c16b-10d6-4f27-8aab-8d98f51c1572\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>host_name</th>\n",
              "      <th>host_id</th>\n",
              "      <th>room_type</th>\n",
              "      <th>number_of_reviews</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>10279</th>\n",
              "      <td>Dona</td>\n",
              "      <td>47621202</td>\n",
              "      <td>Private room</td>\n",
              "      <td>629</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17708</th>\n",
              "      <td>Jj</td>\n",
              "      <td>4734398</td>\n",
              "      <td>Private room</td>\n",
              "      <td>607</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25566</th>\n",
              "      <td>Maya</td>\n",
              "      <td>37312959</td>\n",
              "      <td>Private room</td>\n",
              "      <td>543</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6235</th>\n",
              "      <td>Carol</td>\n",
              "      <td>2369681</td>\n",
              "      <td>Private room</td>\n",
              "      <td>540</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8947</th>\n",
              "      <td>Danielle</td>\n",
              "      <td>26432133</td>\n",
              "      <td>Private room</td>\n",
              "      <td>510</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6e10c16b-10d6-4f27-8aab-8d98f51c1572')\"\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 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      padding: 0 0 0 0;\n",
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              "    }\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",
              "    [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-6e10c16b-10d6-4f27-8aab-8d98f51c1572 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-6e10c16b-10d6-4f27-8aab-8d98f51c1572');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#top most hosts were maximum booking  \n",
        "name = busiest_hosts['host_name']\n",
        "reviews = busiest_hosts['number_of_reviews']\n",
        "\n",
        "fig = plt.figure(figsize = (10,6))\n",
        "plt.bar(name, reviews ,width = 0.4)\n",
        "plt.xlabel(\"Name of the Host\",fontsize = 16)\n",
        "plt.ylabel(\"Number of Reviews\",fontsize = 16)\n",
        "plt.title(\"Top_5_Busiest_Hosts\",fontsize = 16)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 411
        },
        "id": "nbwHki7d5whk",
        "outputId": "82e2afdc-204a-4b3e-9d85-b94c31e0f4ff"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***from the above bar chart we have a top five busiest hosts..***\n",
        "\n",
        "1-***Dona***\n",
        "\n",
        "2-***Jj***\n",
        "\n",
        "3-***Maya***\n",
        "\n",
        "4-***Carol***\n",
        "\n",
        "\n",
        "5-***Danielle*** "
      ],
      "metadata": {
        "id": "ot1CfcRyup9L"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#maximum bookings in hotelst type with locations\n",
        "traffic_areas = bnb.groupby(['neighbourhood_group','room_type'])['minimum_nights'].count().reset_index()\n",
        "traffic_areas = traffic_areas.sort_values(by='minimum_nights', ascending=False)\n",
        "traffic_areas"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 520
        },
        "id": "tyV1mBE36yiw",
        "outputId": "54df2c25-a83a-4fe7-b3f5-aaa896b29696"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   neighbourhood_group        room_type  minimum_nights\n",
              "6            Manhattan  Entire home/apt           13199\n",
              "4             Brooklyn     Private room           10132\n",
              "3             Brooklyn  Entire home/apt            9559\n",
              "7            Manhattan     Private room            7982\n",
              "10              Queens     Private room            3372\n",
              "9               Queens  Entire home/apt            2096\n",
              "1                Bronx     Private room             652\n",
              "8            Manhattan      Shared room             480\n",
              "5             Brooklyn      Shared room             413\n",
              "0                Bronx  Entire home/apt             379\n",
              "11              Queens      Shared room             198\n",
              "13       Staten Island     Private room             188\n",
              "12       Staten Island  Entire home/apt             176\n",
              "2                Bronx      Shared room              60\n",
              "14       Staten Island      Shared room               9"
            ],
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              "      <th>6</th>\n",
              "      <td>Manhattan</td>\n",
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              "      <th>3</th>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>Entire home/apt</td>\n",
              "      <td>9559</td>\n",
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              "      <th>8</th>\n",
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              "      <td>Brooklyn</td>\n",
              "      <td>Shared room</td>\n",
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Bronx</td>\n",
              "      <td>Entire home/apt</td>\n",
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              "    <tr>\n",
              "      <th>11</th>\n",
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              "      <th>13</th>\n",
              "      <td>Staten Island</td>\n",
              "      <td>Private room</td>\n",
              "      <td>188</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Staten Island</td>\n",
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              "      <td>176</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Bronx</td>\n",
              "      <td>Shared room</td>\n",
              "      <td>60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Staten Island</td>\n",
              "      <td>Shared room</td>\n",
              "      <td>9</td>\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#traffic areas in hotel type\n",
        "room_type = traffic_areas['room_type']\n",
        "stayed = traffic_areas['minimum_nights']\n",
        "\n",
        "fig = plt.figure(figsize = (8,5))\n",
        "plt.bar(room_type, stayed,width = 0.4)\n",
        "plt.xlabel(\"Room Type\",fontsize = 16)\n",
        "plt.ylabel(\"Minimum number of nights stayed\",fontsize = 16)\n",
        "plt.title(\"Traffic Areas\",fontsize = 16)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "id": "e5mgLplO-MR3",
        "outputId": "90cf584c-c8d4-446e-ca8d-2f62f949104f"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***From the Above Analysis We can Say that People are preferring Entire home/apt or Private room which are present in Manhattan, Brooklyn, Queens and people are preferring listings which are less in price.***"
      ],
      "metadata": {
        "id": "2SLgMlIOwMXI"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# ***Conclusion:***\n",
        "***1--The people who prefer to stay in an Entire home or Apartment are going to stay a bit longer in that particular Neighborhood only.***\n",
        "\n",
        "***2--The people who prefer to stay in a Private room won't stay longer as compared to a Home or Apartment.***\n",
        "\n",
        "***3-- Most people prefer to pay less price.***\n",
        "\n",
        "***4--If there are more number of reviews for a particular neighborhood group that means that a place is a tourist place***.\n",
        "\n",
        "5***--If people are not staying more than one night means they are travelers.***\n",
        "\n",
        "***6--For the given data set I found that there are a total of 221 different areas out of which “Williamsburg” has a maximum number of listings.***\n",
        "\n",
        "7***--There are a total of 37457 hosts and the host with host id- 219517861 “Sonder” is the top host with 327 listings.***\n",
        "\n",
        "***8--No strong correlation was observed between price, reviews, and location***.\n",
        "\n",
        "***9--Out of  5 different locations in the dataset, Manhattan is the most crowded location with 44.3% of listings.***\n",
        "\n",
        "***10--Top five busiest host are Dona,Jj,Maya,Carol,Danielle***. "
      ],
      "metadata": {
        "id": "uAB8mKuqwsHa"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "***Thank_you***\n",
        "   \n",
        "             ---Navjot"
      ],
      "metadata": {
        "id": "cASOFv-hzbVD"
      }
    }
  ]
}