Hyperspectral_Analysis(Visualization)_+_SVM.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Hyperspectral_Analysis(Visualization)_+_SVM.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/DharmeshPatel33/Land-Cover-Classification-using-Hyper-Spectral-Data-with-Deep-Learning/blob/main/Hyperspectral_Analysis(Visualization)_%2B_SVM.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9QtfGZ-JNuFF"
      },
      "source": [
        "### Downloading Indian pines hyperspecral dataset:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xvE8PzTQWCOZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9d518372-7ead-4d2c-b0dc-3647fdd76214"
      },
      "source": [
        "!wget \"http://www.ehu.eus/ccwintco/uploads/6/67/Indian_pines_corrected.mat\"\n",
        "\n",
        "\n",
        "!wget \"http://www.ehu.eus/ccwintco/uploads/c/c4/Indian_pines_gt.mat\"\n",
        "!wget \"http://www.ehu.eus/ccwintco/uploads/6/67/Indian_pines_corrected.mat\""
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2020-12-20 05:51:11--  http://www.ehu.eus/ccwintco/uploads/6/67/Indian_pines_corrected.mat\n",
            "Resolving www.ehu.eus (www.ehu.eus)... 158.227.0.65, 2001:720:1410::65\n",
            "Connecting to www.ehu.eus (www.ehu.eus)|158.227.0.65|:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 5953527 (5.7M)\n",
            "Saving to: ‘Indian_pines_corrected.mat’\n",
            "\n",
            "Indian_pines_correc 100%[===================>]   5.68M   872KB/s    in 7.4s    \n",
            "\n",
            "2020-12-20 05:51:19 (783 KB/s) - ‘Indian_pines_corrected.mat’ saved [5953527/5953527]\n",
            "\n",
            "--2020-12-20 05:51:19--  http://www.ehu.eus/ccwintco/uploads/c/c4/Indian_pines_gt.mat\n",
            "Resolving www.ehu.eus (www.ehu.eus)... 158.227.0.65, 2001:720:1410::65\n",
            "Connecting to www.ehu.eus (www.ehu.eus)|158.227.0.65|:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 1125 (1.1K)\n",
            "Saving to: ‘Indian_pines_gt.mat’\n",
            "\n",
            "Indian_pines_gt.mat 100%[===================>]   1.10K  --.-KB/s    in 0s      \n",
            "\n",
            "2020-12-20 05:51:19 (222 MB/s) - ‘Indian_pines_gt.mat’ saved [1125/1125]\n",
            "\n",
            "--2020-12-20 05:51:19--  http://www.ehu.eus/ccwintco/uploads/6/67/Indian_pines_corrected.mat\n",
            "Resolving www.ehu.eus (www.ehu.eus)... 158.227.0.65, 2001:720:1410::65\n",
            "Connecting to www.ehu.eus (www.ehu.eus)|158.227.0.65|:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 5953527 (5.7M)\n",
            "Saving to: ‘Indian_pines_corrected.mat.1’\n",
            "\n",
            "Indian_pines_correc 100%[===================>]   5.68M   858KB/s    in 7.9s    \n",
            "\n",
            "2020-12-20 05:51:28 (737 KB/s) - ‘Indian_pines_corrected.mat.1’ saved [5953527/5953527]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "i-dDzD90Umt-"
      },
      "source": [
        "### Useful imports"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "G0D58G2CPEe2"
      },
      "source": [
        "import keras\n",
        "from keras.layers import Conv2D, Conv3D, Flatten, Dense, Reshape, BatchNormalization\n",
        "from keras.layers import Dropout, Input\n",
        "from keras.models import Model\n",
        "from keras.optimizers import Adam\n",
        "from keras.callbacks import ModelCheckpoint\n",
        "from keras.utils import np_utils\n",
        "\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import confusion_matrix, accuracy_score, classification_report, cohen_kappa_score\n",
        "\n",
        "from operator import truediv\n",
        "\n",
        "from plotly.offline import init_notebook_mode\n",
        "\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import scipy.io as sio\n",
        "import os"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PesWrHJfXznr",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d41caba4-c926-4556-f593-ce518d91bb67"
      },
      "source": [
        "!ls\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Dataset.csv\t\t    Indian_pines_corrected.mat.1  sample_data\n",
            "Indian_pines_corrected.mat  Indian_pines_gt.mat\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "84n3ncU5X9_3"
      },
      "source": [
        "\n",
        "## Importing Library.\n",
        "from scipy.io import loadmat"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p2hMkLXNe-Ko"
      },
      "source": [
        "\n",
        "dataset = loadmat('Indian_pines_corrected.mat')['indian_pines_corrected']\n",
        "ground_truth = loadmat('Indian_pines_gt.mat')['indian_pines_gt']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I5p40yGtYIwJ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ece7d2bf-4347-4d21-c5aa-995a5071910d"
      },
      "source": [
        "\n",
        "#The dimensions of the data.\n",
        "print(f'Dataset: {dataset.shape}\\nGround Truth: {ground_truth.shape}')\n",
        "#print(f'Dataset1: {dataset1.shape}\\nGround Truth1: {ground_truth1.shape}')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Dataset: (145, 145, 200)\n",
            "Ground Truth: (145, 145)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UigG-vlTU9Jq"
      },
      "source": [
        "Data visualization:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8RRXTyINYLL7"
      },
      "source": [
        "\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "def plot_band(dataset):\n",
        "    plt.figure(figsize=(8, 6))\n",
        "    band_no = np.random.randint(dataset.shape[2])\n",
        "    plt.imshow(dataset[:,:, band_no], cmap='viridis')\n",
        "    plt.title(f'Band-{band_no}', fontsize=14)\n",
        "    plt.axis('off')\n",
        "    plt.colorbar()\n",
        "    plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lJFjABdMYQqq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 376
        },
        "outputId": "c1f3c34e-6550-4d96-fda7-fd8f268a3fc6"
      },
      "source": [
        "plot_band(dataset)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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f7IjbRBpmvMO8nhDN002ONDsYzXrSPivT3vJLMTjS5E1J4NCUhW3xrPPawSvizZARYVWCedEs3tm1Fme/S8DsqlGYl1pdo621LhG27yXOPj/i5og7LKTLgcN9j3qpvCOaDRN4rsJ5xkARO1CS8di8E/NogHBQhseJ7Vsj80XHeNkRfcNfeX1p5q/2/FKMxJwDrp4XrIYwDR+XW208xVYWVS++vgsyU2VckXvPGEcviYoh/o1IL1Y2rZWRstax2ThyM1cLoA2THHOkpNWiKGE3MuO07n9lnsKw1VIWUr6WZk+pjjErmfXv9ffPKBxpLJvizRQhm1Ype6Sw2jlp+UDF4taTkPaeuAg3eXFrk+xGwEnCh1Rj/gBTMou3hJdkiCwXwmH2PPw5g4X1z4pw7ujvWIxieE8JoxK3Hg0OWRISYb7oSb3DLYqbE+GQ2D7I1qmAOmG+k5POxYrwoHrrvsq9FYHUvpfpTfmZ+vXw49/n92w5VkVTcn0FGACWN8qegEoN1lTvxeecj3kxmCWSyZSNsCyOOHl0cshseYbDHAi+4zr2bGMPwBAWtv3M9W7J3p2dS5N5oxaKac4fHXRKTDCdCylIjvnDdKmk8wWXlaQTJeVxmkJIFt6pnqMpZo1CctnzKdPli5cpjbKxSZcKxFhfcuuBLQsQIEaBKGjUNQx0lJPMxh23eVlJnSduAsu2PFR7q3mcW15/UbopZHCAz2N+Jkb3LG9Iy3Pvc2wRN8/+Xoxpn2PkFiNQmvChhXu15mBrCFftHqTKgFV+KdTc2ZHx9VXQA6lNFH0D0RenbJac6ERQ0TV8pmREy60kcglPQbWecCbcipWB6LrYVFdBVkJwBf2ULGQmqnXn+XKsJEuMmuubf98wmHqLI2ugMpD9sBmns3txADmpWRRqyZ2viur4vbj64QZ09KjzpN5CBdrnFZ1BBT5ENv1MyAlvBa6nHlVhSSbkdndGuDOSXhWuvsMZAu66g0UY73vCjef8ZxJ3/78983nH/iPBFMsUcDFx9Yme8a6weytx9sbE8GhmeHdqgBiOx982cLhvk1GmX+T5q70IJElrqJTsQGkoVmZR2LpaozmPJtHCeUQsr5CwpHiS/J4Xc/GGF2e6KDnEJbbdgnep5lWu556nhwEA71bPRsHyNNcBNwtuMhDA/mYgRsc72ztEFZI6LroDaWe/3U8d19ebmtDX6Eh45modZ8W4TWgvqDfU03KW0F0k7BZeu2sblc7RrUaDFHCCfZ4LYCDajaYMCGhzAWRlk/pk3mIGWdAnXGdGStdZXin4aOCP8lydw3vHstgCSYszJZqflyuggVvGQ2tQAMzngfGur2tM4vMl61HoOZDRj9mICeA4Bg60Sq0ag8qqMCqzsYay87xUMdLKk3IeobozKkBneWVpDaBsrGqXL1QUfzEGk6DxeIzVayoKqbn3oyjOSyBFid+g/SpfqGxWiKPWp/6MBfzCEzTMksM4UpL5hemPveSavD6ioij8MRO42ZKPxQVWyUxfFFaxWKQ5r6yMu7rUWfG17nW5xpLP7XN4iOa8Vemt45RFjKGX7LmJxeCXOXDIQmhafA0TlWF5b0lwJ0pygvfJ4LO9Q8Wx7CxEMl46+ld75p1jvJQ8BwE3m+J0iyleiQb7lJgMvDF4UsjH35Tx2vW9Ag5ir2tosrk/ksXZXaQCRCQaYjBuQLfmeZri0JpQ/qJWZdHoDWOJaIUrCyswoEuRoVuOIMcxmXI6omzgxL1nTPDg5oylggEWluQsFJch2yKQFs8zBmVjXKjXDP4QtDeIfNcv9H6FqZqXVcKGOT8FxvMFQaaU+OMq7FsjpoZ0Wb2aMhd5Xgq1CqfMW3k/mvmiZMrclMjEbcFZjDw95mlY14yL4BcLJaI5QkE26pwaMKMBq9TfzVbCULyh96UXeTnt/3R9ya3n1q5vXCnZyBPQyJ/6HASUYgzL84eQ2fl9QQ0n+kB6obJJQxbgHRY7vv2wIQtUzaG1lTMtnqqrhSJY3qPE7FmZv56nvBdXvE1WF+tXsjcVYXgM5581PD0J0iA8+VQgnZXj9ShG2ypNFdA+M2IUksMw+5mpCnRz97ayeS9yuOfZf7RB5wgV+GBJw4xqg5wcLuPOobIngYnhyNLy5zM+RC7ODmy7mTk5lug5zIHD3rwecYoMET4SWVR49Lrj0S/Ik6kRWRzX71lO4fxnEmdvLoSbiD8sOYTjWM4CTz7ZkXpDBW0fJMa7nunCvLLdOwupEx59W2DZGYKvJJ8h1/J8NuIPCX8wKHYcHBqE69cC1x8TC1X0hgqKLay6POjbiaDs/WpQm7RgCXDnY0X5eTGI8+AXdmFiFyZe2QhL8uyXjil53l12LIuz8w0R8Gj2brrP96hT3n7c89YmMlyMnO9GA3JkCLVziaS53mWWJrQL5LoYMppMe0Wjfe+7SBciQ1gRb0tyiCgxCdMSWBZvlrYDSGj2PEqNCK3g8o3SFZsPnOKC4kPCZeBCXZtKVbpJpcK6KzAhr60K3qle+xqFkGyYlHqSegxrpCA1xoc6IVxFNu+MVmMzeOY7npvXA6lv5ERGpBbPF4XdO5H+6cz+1Z7xwq1eSeMdH+VTCuu0yrR4GUr2xht4dOEzqHlfQl7fXjNIpaFy3gymQc0rkwznbrn1KKz/VaBvypxNDYc1SThY5YY2rq6FaYvVIMeW6qpz3v9acOR11Ouw/rCE1krYx81K9zTiYoKoxNkjbaVW43q3F191YrbEsmUv2RORhrHcovhDxM+uJjtr+Kd4WbdIFBMojXGfQ/h5LoUUTWDDap2WnEQpDKQIKlHLCWQYcPF65ikQZ8ccO1LnSL4BL/SGWEudMw9ksFyDixAOkXhwxF7obhLdk4k0eMLeZwWVQ2xZMLkJAyJkMIKh2hwaHH7yuS7C9Gp99FkIPFuJ0k5UedlzKLVLTixfUyx6l19BEp2LjDFYzmmhFlKW82lOBoga7BaEdOMs59J37IN5NMVDktarSlmAkfMshW8cZsX7XF9T8ieiuHx/Jb8Uy4JhVQYm7Rvlolio7MjqujUnbq1PKgWyQM1dFVKtq65B+klj+TcGW6NobufiSl5Gjk5GDYcVR9VqeRJ4lz3nrCyKUK/ewzFqyy2KG+MKNCq2ZDMvRzBt4HmsUzycmlNdcTHreertFo9G1+esq8d55FE+5xm19EJv7EMkBeI3o7JJJdfh10QwsFaTgyUjswW1Cl5dH1r+83lUPBnEEngto5mlZQxb/lfyOa7kiZKuyUvIcYVszS3g1Cyn1CZfaVxh51ZopYckynKWkGQ1Lm4Rrj/mGC+tNiAOx8qwhVBXCw1WppfVe6syqAiNWZAnHckp7z3teK919fPiEJ8I3VKLEwskd5qC1fTkuLOeRZZt4t1f5Hk4BtwccJNVU3dXBjO982bETUrqhf2rHX5Wdu8sxMHx5Nu2Zn0+SPAA9vccy5nQP1GGJ4nYmQdj997nG7DXUpCCAKOF6RZsLpICoQhBlyGmjSCsD9tqUfp+IWRvocCbS9goqeBc4sxP9G4hYZDnefYsY0BHj8zOHD5nXpbBvtUq8D3odeD6JsAQ6Xdz9mwUkUjaxOrl1jFGsa4SfUQcpC5BEvtbqPU93iWCJIJPNTQaXCKFaEWkeUySIdFpNARa6+XXrgGlIDYknDf4dwsqOfJmWJVtjI4UHZqLi9eIQQ55FUVMYwwgNZ+fT370XFyE7uGMW5TUO1IQ5jPHez/vjtWkbITYw3QvEXdphWkvfvWqsnLZv+KZ72xZhmYBZcOmdBtJxcut3phYHrXll7J2ExbwagzR+vtuXZMFjr8merMxIWVdmpIpBmabn63rNyMDnxeyexn0TenZlBxGRcaAPYRUPgA1gybH6JFG2RzBB2+7OEINd+GUWrHOemwtwPIrx7UWGjkfBGahlYR2sVBc5ppUYuFZ6FuexwRKQQOlgRoSNEy+sOyeIyApiobnFrHqrXs8es/WpN/ng/NbCrk2pTOYLE4I2RLvg9WczDEXjyYTLIjiN/a/cPdgOaExMM4evQ4M73i6J8LlTy6EpxM3n9gxnzn8IysgTa/0HO57XFY+/mYh+QFJju2DyPaNa8aP7Lh5rSP2a97K5pqjNilObS7cnOfOy/F8lGd1230VEAchGOy4dAloFU1SwYsyuBlSR5CM/koZUZar8QvPJA+ERO2QoOBGhyyQojB7rQrOOVMoySl68LUyv3gFziviEi6DEmreEWrozOciz+KFWUGqywZYygi1aOONgpa4cRN6rkaaM6iz8xY+a+eh8h7U0FlKBjpIutb2yO0QNKzrOU97NX7KOi3eTnORcL0YHHob0M4xXg7sP2qgnTTkavytQtcaSw2f57W/NNDnOqbsSRSYdzHYBKoBe/s8bdurlkxZyCqoy6WKovkgw3dlndVzatlAOJZLL4kUvjkBAtDMazvRLdNX5mrakEj7PbUg8Pg3enSeCp3OQl1dbj/hFe3zjzMEW7OCmu8I1x/rCQdl82DCj5HdO57lqXC451jOMpPk8fjiCbSMl7A6k6awUTQn2mep+aEjapSJVAHKyq1Sdd86f0fw6/Zc68RIMo9Ho6CTA69c730u6FPEp/p7cUq/myryCWBZHNMYWGZf23vM50rs4e1fNODmgbg1K3I6DwznHknK2ZuWh1m2jjj0+FnZPE7EQbj69B0rIH0nHY29PN/pjjBfZAhsKd5t6yASawuVXCvVLtbkLd+VolnnAIclHEF7Y3LM3rMkz5w8SYWbpWe/dKTos6JxuMmUXOr0qLi0Ir2cjUW9wmS92g4F+jw782py7kaypNFOiZ1HglTIcYyOuJhHYeiwRO/i0ZiLxzHPnmUKR+vGwrZqq68tGiyKpoTonB7xUfVqSmgrK5sYpdbZsGSPKXeAeCapXdZnEkqC/+ZVRwo7/Kj0TyIFHaoCh9cGUtiwbExZTJfCsgMNmuHOuuZsSx6qdJ0ocj/B8FjpruMKKOht7c67XKDtmpKE7EWUjiQUQa/PiI11vl0x1sgF30X5rXN4tOZKWCyAumSQdO9qaYUotXdcrelrxnCiL51enLNpP7SKobXyW+8HXRVJ8SDKcemW9Q/G1G19THOt1Ks13/M5Qa6g+1AFujqYz+D6Y47hkbJ5AG6M7N4Yc/5iIA6ln9v7yPecZDwCM6lUoegm1qRp9rCeQcSIKUCB3LbleZZVsSyPufQoDqwmHCz8VxRcnkSx4lb1Stom2ES6zcLF2aHmNWJyPJq2pmgmV5s/pouF5JSbT1j1eRw9zMJ0GZjuCtu34eJHbkCEq09uiL2wfXehu5q5+vhQC0jv/sRoLYNmE0baWU7o6lNbpssMnMjhi4po0yLwsseaFY80c5cikKvfl9zccmwseQWWEBm9t5Y0MZggR9jPHSkLVzdbbikOYp5qbqyKa8JgXi3EFMWKHgEdXbacsxczSTWOJEJahKV31htwiIhLpKzMUxCuFfo+Mg2ewS/10ZsScMTFozdF2eR/9gnJ/eTwGQlZygxKrqa06WlBAUmqEtMm92BebuPh5ZKAo5DPUf5Vq/eTnHL4iBkMZ19IbN+ccEuClIjbjqef2jJeCnGbG+oGQ+UZ7LnxZBpDUVrPEJvHzbsz3XuHKi9uPnnGzevevOUGBVllRLH9mhxP4Zsjw7VRUBqKR6s1hHaUk2tIytxXMJLdjyZBw8pTBcb/1crZwLOgyG8UenGdDawu9y33uhzwjJVRrAZZmRpPjhs37qxQPRXzMPI/ClSxWCZgiyjX9pAhzupNuKVoLvrhI73Bf71Zy8uugSq7W/dwm/eqxSL1Fp47Gfl/RWYUq7R6OWLnOFZIt1y6xjOoVdlVCSu4jGRr2oQAtboZHDoL8+h5MHlrDNq0dRHJ85cr9yTPY1l04hOKI96JjN7l2pEdAPN5QdsF+q0puVJAuuw8LlhXXLekHAIRwiGxedes3uXMJqp0KZjPYdnmnIE/fvyrl2c3WcAB3lvrGJdDhqpylLspimZJjqiG1lO3WrTH0FYbj0bLzdUEevYgnmHe7FGThU7xiGV2aFLiLERZvZTiNdfGoKJ0PlaUWynATCGZ15RrX3R2aIbGU9ZImQ6nudvEs17NGjazgZWwWq2rmaX2W3PLqsDsHHmuWg8rz0Hq7J4Ojl4AACAASURBVH06F/avb/CHRP9oQoNbC4IzjyqrgD965RB4O5frTWEh1eDqlCdvxcZH6LNbdpoU4dNAqYvHdJQ7LSG4PI4CEvkg0nLqwluCJRozarC24srotCND+SWRot+cAAHICifj0cvzO3LLS5y2MEvpV1YYkNXreSZ2GnNPqGrJ58KwPicbg9qCObjcRqLkYqxTsnlShrJatta9uYwtDtliyn9Xq1oxCDYcWSslxt0qpSJMbre8KeOvXlmrdG9ZYDUuHVegQlm8NXGbq5q1dD5WjtvvkEERUeiert0SkEAKuV1Or+idhTBExMfnDNjO57oEXSLcsdYsqsLh51sIbrwaYBbGB4Fw5bnzOeXej+1ZzgI3Hw1I8uzeBA4L6h04GN6d2bwzMd8J3Hy0y2G5GTclHv7sjcX3e7OKjwyNEm7L7VhcUEKwXmav7a5wkrhZeubkicmxZPezKJopepZoypbeEvMqJXaXlb79wPIjRagXiRXyQypeRfYItFOS16PCU3/tjEezpRsHAx0kgDNTNp2LbPxM7yIJYYqeOfrK6ml2cGWehz8Yr6WOtfg3rMaBKSp7AUcgAFVI0SDVuuSc0OwMHJG3+qghoKI8xSz+nBpfFVDOZ0QsknDTCeNdT//Yc+/Hc02MX5vj3n521aAMGSGSdIU9Fx7OU26IyFzl6iD2UrckqGuweHeNUVgjJrmzQs0RsrJ4Ld72jVf9AYqh5LYIVnQNpuDT4qwLRd7uwY1ydJ6X7uEovE8t7dc9faCyAda8BHxxmv1Fx1R3aX2po3YHaGthSGSL0KTzUVM8MUWjQc2gSnJk8ZT2GUehu6xIiryp+/MIqGj1bGBVNPocpn0mbnxLh7YKqyQaieCQ4zAjWJQs8axuKBorezrSnKyNX6N5QSQhdp6jLUJynYaIJZvbPWa8TzURD+CcY+4DSRzLzpT0dCkcXu1ZNo7xwuGi0l17Uif4MRkEFlOaohBGKyR1Y8QtiW6vLNeGxipeXRFwqbeblGQ91DRxBOktnkxpARNyEWaBGpc2NcDa7ajlnSPLu7EeisJpwif1wen6WxU1KHc25yVCuDGEX+qsbc0yChMb5l3gZrc/KrhMOXHfdrrW7LWkkJ9hW1ujYqa2CpocqqnxZnKorHhUea4qoi2aYnQ5x1CscTut1unQ2/fZ8JqCraVecit9k6puVvzB8ip0ze9V1hNVns6C2SvJC/Rqe0A5ONzzxN5VQ2s6l7pGC+qV5nG0+RHNfFPzJ23oLOfmKjL06LnzLDXDfi4pK8CoQdPV37bvX6ckIneBPwH8Hdhs/GbgR4H/CvhZwGeAX6uqD8XqTL4f+FXADfDdqvrX8nl+E/D782n/bVX9gRdd94tSNjXcVZKu0CiE55j87cd2QSNNUUkWPjn5n3zzVMXqODhIbf/fXnPt3KrEYGNLYfW87HzUhps1jFYglak5JiPASnGqLFIXj7q1pUpL1UtvhFOrxOAWk+a/tWqC0vZ/PXdSMkyVddGVRezMoi/Co4zLZeu1e2oTo08C6kJNlC47RV8ZCV3k9btP2XVTHc/Dw5arw8A8WwdkqzkxhJZ77QCiPPmU49Hf5axMf3K40THeC7bB1E/ObN4cmV7Zcrgf8JMyvDfjooIXkvecvTGxe8vyQ/t75gmlvC3BdEndPySpI3nP1HmcC+yXDu8sR6MqDH45CqUt6hjnYJ5DmXSvx4LqlreAKDr5CjeW2VE3hWsETI16OtAuWcJ99EjelGv7YCFczfibmeV84PCRnuuPDnzul93l/uU1fUbTXY8946HLWw7khzwkdKO43N269IrTkkMqxzpFCUfK60jxzLnbQd14zVnOarGcU7tWROTIWy6V/4WPj5ZrTrLPZ8KTTwb8qGzfTfjJNuY7BJvrmkdpjaqsZEoeZOnLQfZ2/a1yjJDTdCw7RGshsMyubnHhSr5U7flaqBTb56fLyNMSWi+5mlzEWXJf7XzUgtdiBWYlX5S3ZqCJmwU/SW1AW+aHsjncS6LWrn+J9P3A/6yqv0ZEemAH/D7gL6vq94rI7wF+D/AvA/8o8J359UuA/xj4JSJyH/jXgV+ch/3DIvLnVfXh+130iwMI3PpSYC3ofI6Vv36W4++FZ57UumFWPnFBpSVqgq51xyuKpFjJUAdRkM12Xo6TotnlUKh93arScs05ZB1mfX+BJVRyONw6rg0FlPHWO89zEYuVlRov6nnXKveQsMLTpveTKOuOhyUUWZpFBoP5qgpd7i/m8mR62dTwTMqILOlscfbDTB+iFZA6tR5iTzek4HNeR1i2jtQHlq1jOhM6B/0jqDsjYoANWRIpCN1QmjaaYRC3ZnoWhauTYwmBA7DfdniXLGcDdF7oGk8HrHgy3RZW7YMrfx99LgKGWqfxvkWnopknS02G5ae6RyP+4TU8fEx/cY4sl6Sw5eHomXMbIqB6NWUTNcDQhEKtnVkWR4o+dwOwZ68FbBJzA9XKM3K8PUOuWSqbppUwa90MrA19Nb97JndZY1Err1mdkq29cEj4fcLNfs2vtq92vvLvpYQphborqfPxaOfbZfKk6269tpBrYvKane05JsS8wTzM1OWGmoOiIaFRcJM79miKknk/7+YWaQEIZOVf57H1bBrWebkkxJfoOonIJfDLgO8GUNUJmETkVwP/YD7sB4AfxJTNrwb+M7WCxP9TRO6KyMfysX9JVd/L5/1LwHcB/+X7XfuFyiZujy2gYm2UEE8r/GukouwnY4ccuZ6aoYhHRVaFcuxcsrUmi9SWGUeJw+Jp6HpOdWLWa+O1tDmU9frl89o1wMJxesSotbV6Pl+t2WlJ11uooIGjRfz8OQ3XsH03EXvh5jWp7fiTVwuZtSECWZWxZs8t5XutzU0TdVuFmsTN9+kn0Pd65tDx49c9EhLdYIWT3lu/Mb9JbDbz0RhjdBymjnn2hl4rlrfCfDcxX8J4z+GWXQVrhBvH4f5AuFEuPjMRbmamy564dbhJ2b01Z2/OBMPuXSF54XDfMZ07/OgIe890seFzn96hQ0I2EQm2V8ymn+m8NeU8LKEWtmoxTkpeMJK1uKzaOIALyYS6YPeSFXTZirogjtoOzcy5wDMDEOatMF/0+OupNGXDLQYbL7kWMEXoXMKHiHO5fU/xSDKTeJ9ypwjTDFIg2Bj4QjsQzd2db/NeFcwc1ae0PNeuWdrYUYlSNHzadm2XZL3zzr6QCKOaoompojKrIJZGTRf0XK4NAmryvXS+uLMZa4+74BJXU8/VnSEfK0d1VeMUWOaQ5/C4oDWOwTyQvHFcMRDLvNQWSdlyaztrF+VaQRJFwWjmmSV7ijN1O5PaIcFZJCT2z3keHyIpHPW7+zLoVRH5v5q//7iq/vHm708D7wB/SkR+AfDDwO8AXlPVN/IxbwKv5c/fAny2+f3n8nfv9/370os9m+IKV4vG3ErzEmRtulh/kJn8VmhNW+VSLMyipApCJluAkvta3U4wlvPXL7TxSop9WizD9xP2hWndcX7naFzP2Ryp9V6OxtF8lvK5UUA8e5jVBL07E7eew/1gmP7S7aAqT6pl2CY87RHkrttic2BpHameZrsQZDH0mDpB9w71ynQWmDeRfjdxvhut+r0RkqrC0/1AXBxxH5Drxo1yBkJwIdG/PtOFyDgF5jEwXneo8/RPhfOfwTya3jGee7bvLXRPRpvbosijGSsubnGTZ/Mosn3rwPjKQNx0LDthunSkIXFQU4BdF4ndwrQ0ha1H3k2Z+9V7Kc1BnawoPY2NRi4PpgFvlO/L1udFocZe1m0dIM9/NnJE8QUQo1aAGkKsTUJTcqtHIk0dTT7NuqtkNuZiBjg4ngkFrXyqlGavR55by5d5Hm4rnHqPzX2WdeNH2DyM+DEis7ndR807E2uEAWr1vcudqcvUiFgbn+Aj58PINszsgnWAuOoGHndb6wxxy2t9Og7sp45tP3M5HCqPLsnx5tNz9mPPNAbS2Lh+cuv5FZ4t8e3yVaNo6jyp1NywzFKb77rSAb5MXw59v+yczVfo2TxQ1V/8gv8H4O8Efruq/pCIfD8WMqukqiq397D4EOiFysYdsrXV4OnL83MzZpFTPBWeeQg1GV7QK03tQ0GAiKjFrYugLg+VxhN5kTFR1lZJhGYZfNSJgCN+W60+oGwGpxlJQ0GhlC2Rizv9DCNTGbF/qoT9+rddQ+txrdcR9mtuqeR+pGFqwaz0FFlrAEoSVJ71nqp8KZ4j1Di2gIUjoIar3OwtP7ILPNgMZpF3a5S4DefgFD2LVZCJU0KXEGfJ6yW31RevyHZh+gjMl0IKA34crDYowOF+x+Z+oLuxDbNEYboMqLe6ou17ET8m1DvcrJx93goGYy+oD8Qh2P4xF8rVK6ViMN93js3bzcrKD5XX8ty04ADlGWOgzBNN/UgFkGAO083rjukiMF5csv3YHeYzx+Ge4/CqcHZ+4HwYGZdgkOysTCAhnZJSAWgo22Fm0888XrbExcHs6lpLqjln44BkdR9tfZaK5ZGKktDimVEVo7AaauRO3dIqpYaHJUH/GMKNVgMv7K0foO2TpBXEUtcCeT4pytXmM0XHDLW9UnCJ3TDhxdB6DuVm6blS82i2wTzqkAdbmquW+qo5Oq7mHgE6b8jJgkqULENU09r0tgmx11usXtyxEm7nwML2WdFk+LiboX9ku4mOl475PHs4ze7AX6f0OeBzqvpD+e//GlM2b4nIx1T1jRwmezv///PAJ5vffyJ/93nWsFv5/gdfdOEXKht/MOaMwgrPdabx/SSrgVAS7Y0w1OLqS1m8ap19ndV6uGYv79oiKgvOIliLMVaLxI4xBI2jswoFpaDKdE323k68ZCuurXK3okNZY99lJ9LG4qM5XRkDatXRu7fW5Dusx0vU1czLC15dw/jNNdp4uyzk40pfOjHheaTQbDCF+UsIrt19sNS8mOIuA4fYe+LGWX1K18y3QGqKacN2xnul6yzutFatu9rV2IkStjP95d6u8Ckb5ngzEEfP4SpweOzYPPBs3nOQlPFeYBmEs7cW+kcj6h2pc/gxcvFTi9ko42I40Bx6u/rWHY++wzoMz+fJ0Ex3rFt0DY8UcljxZM4ZKDRbNcvRPJrxZN9pl6Mzwfi1PG8Nyv7jZpAcPio8ve5Ydsp8mdCzyM8+f8p5f+CxbNnPHd4pS1J8MaoAN1g/tovNyOAXntxsbAvryeHH+lTr5oBKZtDCL1WB5GR74c3s6dCsmTY/I0KDaLx13xF2byd2b0/5NwpRc2Fn7iTgpSobuXXulqzY1BsUPChdiFwOB6tBygfvl4793HHWTVwOe4Iktn5mVsd+6SrKUFWYM7y9dGmwa7g6n5K3G9cSd2o9P255Mbf1Q/Vg8zwuFlGxziHm3W3fTQwPF5LvmUqXjO7lFngqX7Fn8+Lzq74pIp8VkZ+jqj8K/HLgb+bXbwK+N7//ufyTPw/8NhH5MxhA4HFWSH8B+IMici8f9yuA3/uia78YjdYqgWYvE2UVUFoSdhkJko7CZfk81ZtJtWjNzmsCYkWINNZ8O9851FZ3mhB9f0SImPIRyy5SR1yStIla8Fa8lQSUBoD1F3kI/mChr9hZFfVz6TnMLKo5n5KoCZ2cZxFvjD08VuK+jLneGnGwHTXbsIU+5xo2xvbesmDLitJN0D/RqsTbOZourFI6oeBzwV9dgGSUlFXApwjLvNaMPOsmAtExjl3tSqyKAQ/UaleWO8pB4dF3DJAMVm0hwsCyc/hDorteUBHSzlsj1jmuG3g5IeyVzbtK3JjVox70aYe6jri1jhNyW5GsrJX3lclFoL7wWSOYUob4lq0jXDt3huoSB8uW3IhS0V3EbxYWddwsPTdzxyEj5ZbFN3vMgDob3/XUc3CBaewsf9Ts6lqEuMbC73n7ilZoFq+9Cv92/eSPDduhlr9zjT1kPQTtuO4mIXNCO8cy+OylGIzd7xswfdHThV/zq6zp4rmBQb+X6LiZe7yzbt0A+7ljP5v3t6ijc5GL/gAYytDCatQec9K8Cl+Z7Zb3FipAjiML0N4FOTY4KwOzApKyMjfYd87/bi1vu3/VsWw7xvvCcqZWu7dN6zVeEqX3FW4fGv124E9nJNpPAt+DcfyfFZF/Gvhp4NfmY/8nDPb84xj0+XsAVPU9EfkDwF/Nx/1bBSzwfvQBXZ/zQilJxQIP9bD0WbkMqYYzany5reIuzChYAlUUzY0DtTRRLEJeWItCW08iLyhJzfetYCxM03xvX68LtISrJObCt0hdLHFTu7s8Q8MjZff2zOF+4GZwz4VB36ZiHUqy7ZlJRbNByQn1Y6S7WrLV7PJCNg13eKXj6eCIffbqyBZmEY7CmhjWjEZLUDsg5H1K+qfK5U/l9iNluvI4nn5qsMaIauiw1kOyimmFyZFmO0aW4l3aGLRXe+bevNWYxCZRsWJIlbU32RCRi4n0UXjyHSY0yu6YN+/1hCvHnc867v+/C2kQ9q8EJMHZlPBpJgWHeqF/PHP/8cxyFrh+3bpQ796J+Cnx8Dt7bj5uXYjTNpWpzu/WSFNyPMhakug6l1jyl7QWmVo/uuIxSZ5oUBTdGhIqdJGL3YhziZu543rqebofmKdQPUBK4luUEOxi+0OHJsfytLOC0dI7rvB0bpXCTF1zz+QG8x9VlpL5oewnU8Ko2cvdvGcgDVNS7bpW2zZijEyvbDjcD3UcblZ2byTcFFcFU0JJTYjSmoZGQjAwQErCNAUW522jOlGGvOvq08PANAWuVHhXoesiHzm/xrtUQ5C2BcSqbMB4P5aQYaNY1j1zVsNg3ea5mZyap2oEeQZZiLPtu1PpqLA1C3R81SY4DYt5yV1ik7uFvyx62Z4NgKr+dQyyfJt++XOOVeCff5/z/EngT36x130xQOAIeskaA88k0aqrAeIOa/PRlcWVj5HV4in7cyTNVkk5bzWXWF+357vN6Lfusjzn2HzM7ULNsnD9wVzl1Gfc/nNCZfW2XQ4jKLiRo/svY3W3Sn5VcqU22CJIrAqYrASjIjEv4ljuw0JsFnpjjZPnRFSpk6jV22XTpzyfpX1OC6N2y2q1qojF4bV4QVIVseZr1Z0a1Yotq+tXDQ77XxLQ5NZ8nHIU3gGqh+BCIgSDvobcdn8cAyk54iYRo2O+45judsTB2qZIgu5uhx+cWZ5C3U/HTc42zAPCPuIPke6qI1wJsoElAxHKLS6FT0oz0/dBF7aegwmrW6G58vyc1SOFvIFaqQGqKl20yrr2MkVIain2LEiqBs5eT1G3LW4MGjl+L95FzY2mvK9Qzj+WTtwlNGs1Nph3nYtvy06uDL4xevJ53a1Jet6c1bmzfzqXUHW1aWn7k7LJmxmaNgcxr4vS6qcD5uirYinzZp2/qaCQ0uG6GmBNvu4ZC/C28jmaS12VVsA837IfUflBMEXjupT71fHSSBEi7oMP/DqkF3s25wsFqQGsCf7R0T3xhGvh4icNIvno2wPjfWU5j+gdg0D2/XLUfj1mBJE4xWFMqdnqkNEddVc2CxPaFvH2D1bmEZptB3g+Q1VrMcdiD7ajZX+VuPq4Z7wn1gyySIraot3+HO8JyzbQXcPFzyzIc6SPG9tkUhmjVAVifaPqnR0NUsjCQYSUUU41Ph6pXac1F+elngzDVLPEyIIpKS63V9EJ3JS76Yqgg2f/akcKwuZhJOwX67acBZwfTYGlLPyScJwELV4UissFd93e+m8VQWcemo0tbtQE+3ah2yx0ne2+GZNjmgMpCctkEFa6RDxXrr5Nufm4CbsUTLE+/bTHzVZE6kc4ezNx/pOTbZZHvrf8fO98fmL7rme6cBzul7oL6+LbPVXcojz9lGP/eobSNl18UWz7gUStvdIuN+1sqdEeziXLSWwOOGzvnSJMxxAqsu+ZhplqxpdCbrNjSjwtTaPSzKtWZqAVDVeS01q6JLdFjI3CRwW3d7XrgRuFwyvGx4X1/Ajnn1XCXpkuO+LW5sy2FzfeqGHZ27I7r9nS0dv253G4vOdS6Gyn1bIjKtDUH0lVGBotlLvJKLXL/kCQxLvjjsfTlsMS2E9dVTaKhXNj6QWXYem1rub9EveS56g+xGf/Ly7hyvYZkkOH+dlJRg1aFw5eqmfzjUwvbsQZ1KzbYiqHZPUKueZCFhieJPw+4g++Jtery58ROWU72yNEdPvAVJoantVt1gKpaS26ZsFre44XWRu69l9zC3Q3Sv9kwb3qq2I54p/mcwrARuhuMkInYQrnuV6Q1LYaBdpbqSJlyuC15iPqXvW5WWTZAVHc6m20+/OU+TtStK6cR1bB5K2tivpchBkg7q0hZIVUQ/VWxDVCmPU6K8RpdSZLV+wy+aUQUIOSSo5JWC3cRtiU4rmCtMMntE/Es/V5aYJpsBBT6hz+xvrCpd4TO5d740HqHDon/CES9hHRrm7QJcm8zuFRws2J8V5vaDkvddvrEqJyxeBQqR7ZM1uhF96QHBYWxUuqTTiTSt00zaVV2RTFk2q4WOt8l91whVV4V6825/hqrVVRhCF3K84ghgK60WwpaLRrySKk2dZW7LPH3Xg65G4CGoRlkDpfKEce3ZEHVeag/CN39NbaJ9Ag4MFHC4NBnZvC/pWNmwUSnAEFtm7i6TLYjqwEYtOSvd2VdA2NSVUypSbpCA5f6LYiao9JkqHveSdWl7hNrZJRfc75P0T6KuRsvib04jBaEYJ9hm2WwrUzCycvd4S3NgGJwRJoef8ZJk+cHTejR5ziM1y2xL9TzFXruViwIkHKZmZ2dZJrOTMvRAOgrAv0Gc+nCPP8d/EQZmuA6A/gJwstSQkv5IVUlI7k30uynM3w2Krgrz7R5xYei+VibvHvcua5edXjp7UZZRnnfHfDdLFOtx8Tw4OD1TEUyh5O9zRy/jlh2Qo3rznisN6aZCUv6pCbPC/a3LozwRKHROqFORfOpQ4QOLwakCUQN1ag5qIgGbHmEDTlfUqanBYYIk6QmlgvMNAjL+wAYJY0DuKVYw49Y69c9VoRbiLW9h+o+Yyaxyt7+Wh+zp0y3YtwD8ZXHE++Y1fvUyKMdzvCTeDOFyKbt/dI7HAR3KIMj21rCuvL5W3n0R/R45CpQPLCzevCsoW4szYoaUjItq2WXSfa5a7QS3JcTQPBpbq9QLmnrotV0BZhe1gCMQnTEurePTGfv2x9oLlouuy2mTqtiMG0SSY0g1nxpe1NFZC6hpeSM89sAYOUBwj71Wsq/FbyoJWH3NrpASDl5pll4zzbXuCWEhYoncW90wwION7WexvmGio7bAM3Y89+3yOivHN9xuNxA8B5CARJ3B2s11xUq8PpsgK46WeW6Hh6tWUpW44sufVQQe/V3M76zNoN72p4NAlMDhapKR886CZaN/VhqR3VnbN9jKbxi+vw9eWS8vJzNl8revHMlQRnTgCWlukiBvVHYTpfO89WayG78kw5rKIRybs2imSU0pi9itISPebPxXrwcsu8ypZeyt8XS+tWrLsce/S7LBALrNFgwUWDcbxwmtCKqHlBm3cXDq923NwVwh42D2X9bXOtZSOM9+yY7QNZ28iIsOw8h7urldbthf6Rq0VzhUQtYbuZE/N5YP+KQ6p7n99KPH46LmCNGwvPaLAEftoo8yV1nqtQUSq8WzVvUAW53c0K+7YD14nRUquR8zSlR1s5b+n44KfsIOwtB5UGG1vsrakmXcJ3Ee+1xsCXRWFpWrdkIAIOZIj4ziry+35hngPjdY9ODnWBcC1sHrksOE1quAW6Jws4uPp4YD4Xzj9r+x1JTMgYc4JbiJvAfLYlBSFC3eLC9fHYmeTYuo3Ruk8rILK2qpEsHDtvtSWdj7V4sdSJzOLXHI4KyUkOX7mqzEuvvNRZLpTeOhRLri1yLlVotZ3HPCYrZDVPKS2OSILkSLl/2pHubBQOrIZXrZoPptlTMG/waN+ZlWnreMAKOdvwWZDELky2dbZEps76vk2ziZ+bw8DoE1ebwY5xkTO3MHnP4E0hnXUTTpTBL7U3Xpzy9tq5n+FRi552eLfXeAmPKAY7P6zepHrL8WlQGMwzL/dTOm8/L6rx4ZEQv5qb53wV6cVFnXmv9dAtuZeTZ578WiCXjwHWjalg5cTshbje+myl6JsCrLxog/0uRtuy148mGJ1XdGos6KKYUg4HFA8eqO06YAUEFKGaW9+EvbB7S/GjQWdTGEhdUTysRXCyvtoFFW4S23fAz1i349sM1y7gItSj5lAFhJvI9iH1d37MSDWg1OFYol6pN9dYnEcJbD2+1npOy724SdC9rPfxvHEWb6RpL1T0y1HYsrh6JWlekD9O1nlvPYX2UtlACA8h7CEFx7LrSR2MrySWsu2ArOfQsrVEn+h2E6FpV5KSwatTdMY/XWK+G1nOhPeC5+knL4iDNSD1B8fh3gbJ+x3Ve57jamhA7Saxe5DobhzxAcTOo8ETh87Gei/DYjcRugzh98oye26cQXvPczuW4FLt47YkZwpmMUjvGG27hDn6nL/MYaGcoAbQIaGdgFjOpSqaRsm0CepaO5ytdetUYA09y6Zskp+dBiVRPKYcggyO1K35OxUzGoYnhjId79k2FsvZs8JcGsNAcy4GrCP3hIWDShhsjKEqoMJa22HFYosoYww8mra5y4CF4e70I0tyPBk3zMlxM/Ys0XG46W13VeU4b3MrPP++lHlZu0RSR+mDpgF7xp21yikdECwHNdd6nxN96fRCZdMPZpp33YIXtS1uR0/diMtZuMD7xDz7GittLTYRa+woAoeDMwQTrLsodgZFjRpyqxqHn6FAhC0XYKGP0kYCsvVVruMwD6cKrdXid7nHWriBO1+YcXPi5qM9y13b8MtFSLEoMRokTqvAlO56obumEfRrw8kjKvyejvf/Cdcz/sYABrXQ8zkbV9i49egebntqt7+rCm4GaHo61aSyCZd2F01ZbG7qtte3vDQ7MatwqYWjWi3v1rOsG1E1VJ7X7p3E+U8fcl2WY9l4bH4q5gAAIABJREFUHn9bZ7VE5bYyGmjZKfOrC66PvH7vKRfDgSfjhv3ccX3omUdz82ovru1sKLdPRrqw4JPDJcd46Hj4zgY3Oob3IBzMmzUY7zpQ8ySU3RtWVSkxrbU9wHTZ897fPjCfCeN9IW0T2gv0iSVvx+x8ZMhFr9tupnOROdl+NmNGVlmRogFklsWUTZtbcDl/kzb2HJLPPelCQkrYzK/CtPyyAhAKYmuxCINO9l5Dz5AVSoaed+a1pN5bbi9HHlTAz8rwcLbQ8c8ZmM+tPKANOQPUZqale7VCTNbFOybHEs0DAbgZe5xLDMHAIgJcbGzOS47isAQOSyCpmMLxkfvhmifTljeeXDA1Hm3dh8gBnYUXS6NTu9lbHvJtKmE1n8s31JSyekX6iOsMQRl8pPOmdHZdYpPDgS+LFEjfjGi0UjW+yRj5OfpqvYAhckIwC4Quy8jMOCkJMRe1lR0knWjeBbFpkFcEpyuxaUgD60ZjFOGdQQS5JsGM7Qz59VphnYUPSsitbFEgC7g5IRky+zyjp/5WG2+neioKt4yamq7M1r2flP6JeU+uKJRShZ0UQasyUSekbWfhwjwWNyWrmr8Fla433MxHi1TrrjgKDRblc1QcWiDLOTRWO/iSQRBg1fN5219yHUppK1R7r/nms7Ru0LMU9uAPSjioQWyDIw6eNAhuUfzYuF3Oal3cLLg5EDeBd7e2g2hSoQ8LY/C5MBNDMwEijoSFOJbsOcRonoR2SiIxnzvSIDz9eGAZLlbod54Xtyj9kxk3Rqvp2Vp4048RF+2ZWgt/sc4LO8eyzUWR0TZTe6RCPyzErbAJeXvozPMxK4Jxti0Hljmvo0ZxVJhwMOOLLhlPF6v9GRTLF0+3jf2CbpvOHRqsk4M6UzJ+svuaLoPt29NxFHarfdzK+W59KDkb23/IVRSZz/mb4OMKGMrzUkKLBWix8Qt3uhEvikMJbu23pouFzaTs5eMzVDmjKQt4ow5LTSHWMGFWzDRbV9/uZl2QcgU5VwI2AkR1uSTg5dE3Zc7mfDMiwJ1+ZOMXBh95Eo47tfYhHkEBC0xxXjx7stLJXXh9SHRusQeYrcI0WcsTOhNw8Y5YGKEUs+UQTs1RNGGvGK1eIJV9NmQVtCXk5kfBj9YFwE2pFrQdWe26vldBnpFrbsnhrtsINJMQ9jkvvuG9me5prBa0lHh4XMMkhVIfuP54LqzElNn2nYXhMFP2VbmdV6r78mQF6kfrIn35UzPdzVKLQtUZCu1wP7CclUJLO5XPrduPEuS9ha+WbQ61bFJGOiUL3RS7IEFaBERIk0cycm3dOXQ9rygMDxO7dxb8PiJzRDeBw31P7KxosVvWZH1595OyeW9hOfN8oT/nzdcCdy9uuL+9YY6eQ4jWlj/3EouAOCFFz5jHqHlHS4aEDrBcLCzA4VvhURIDpUwGSukfOcIe7v9NZXM9M78ycLjn6a6V7dsjMifufG6y2pRsqBxe7TjcE8KNNawcLx3v/vwd15eR/5+9t4m1LcnSg761ImLvc869776X+bIys7KyqqvddCO1B4BkmQkTBiBmiJmFBAMQYoDFhBEeWViWGPAjBghhEBMky2JiyUItDIwYIfDQjbBpucuun6zKv/fe/Tnn7L0jYjFYa8WOfe7N55K7Xtuu7C3dd+4795y9Y8eOWL/f+tb8IuBqP+NqnHE9TFgoYDEr//QwrMAYoWZBEwlCtHyHTWWJ+pmGwOpdiqeUjiPcqKMeat9DZzTZM0/Aw3cZnBnhrMo0ngT7X5wxvxjw5k8lA5pgDZVWGNHGKgyJoaAOIjALxpixTwuepTPmGvGa95uc1xhz8/zOWZkWjpPmZZ7vz9jHBS/HB3y6f4VzTTgV/RGoLMHMCCdu7NPCtFLIWC8dz3c1uqy26aiVcfQUWNR5mBBAFlWSy6zisQghsnp/Dvh4V4eiF7+Fns1g8MVdyNjFBWNOiEFx71bqoInP7jutcMteAaybpvUMWI9mafjRhKrtClcAvlmq5nU8+S5RN5i3PmhCa1Jobli0iDNM+llUAhdZubCshsSvDdkOp0bSltO+Yf1zgLbM9WtWgXNYSQWEo1ZnH5cna3MAvy83ufo/kE/bY8fB58NRYFUQ5gqe1vBQHQMQNUQYThqeKoN9vb9XD1MmDa9JMqRRFwPve7Q7v1vzRNkAHa7kzDgg08viGzSognKKFM7SlF+Di5tyDYsgHoueO6+etHfqDEEAqaiBt/iRipZLbG3MLazSh5/0mTIkBJRIWLLWepzfDwDtcXoZMT1XVoUwp2ZIUBXESZVm2jPKEBAmDYmGWZDuNbm4YIc354SHccTrcW/TJsg5aIsBZ2IAGk+bObsNXquGHCAW8nIafN9PXolA4G2DNfgcWIiprRPq1kzHc+bece+xkwtjad+DPc/m2XT74CkaJQDaEO8ifKDbxODglTfdVgEl29QWBJYHFsJUo5JzVg3B93REmy3TvC6jsPHz9ozZnn8UowDqN5fLF1BDApbEACJKqCihYimCXPid19nUR5v+1+N4q7J5bzyCSfA8nbEPC+YS8LAM1l9dKTlmazlQjAHYlUePiW+5nCUiOzGkP1wPi2Ra47DNvdXftd3tSpJ3+LxifFVw/DDi+LEKs9r1vqECHH4u2H9dwbMgngrKwDh+OCjC7L5iuC1YrrRivQwKd9XvWvOqaEy/HzGmF0ObEy2uhFqHzqTszLq2ofU8As7Asx8z0u2y5mrs5nlWZJT2eFdhzbmijhHOJKCxdA0v9fPgnlfLL5GOi4rCuecXA87vKwT7/b+zoOwItz+I5rnYuKO0TqV1lJYsRbDQ2UXClfyfqOi5OtA6H7yGlPzZkgCn7xDmZwlXnzOujhqmuvppY5wEGDh9MGg4B9D7Jq37aOFFsySZBIe0IO8nlEo4p9TWmwghz0ETxnYQA3HMjT5FKqMsbEll28xjRfkko5Lg8x96weWsXvJDxPB1RJgIw2v1jG/+UDCcFwyvF4RTxfw84u77Sq3z4u9WC50SgIgaEyQA5/cYD5+qMucLCxwzK0O0tewGCbghySwHs7B2GPX26PDnLUASlK4jpVTS+ysEPgUD3BiLsefmbB2FCbj5+xnxoWB+HpH3hLwjPHwyggtw8yOlDrr9fkQ+mA4S0kZmjgZ1Q80d/EqYLUd1WtQbmXM0hKF+6EwRTJrbyVWLmMekvYq+s7/H86Q8aT+fbvBm2ePV+YDbecT5nDQK4uvDpIsY5Yzvfd/DABrDRqMeMmUOKEpPzMtFhs7ZbOH2Wf3L+hBQGMjGnNLKLP7k+Ec6/uGeDRRuOPLS0DbZayKE1ldD17gFtmn6tMrYzjpbu/YBgLfIvURauRDrQ1vxJEh3C9KzAF7IGmitp+ICDPea5PTYO10nTO/pIhqqhtRI0DieWojKkvO+kcoOnWBF22R90p0LNTSLh5S4aKio7BnxzJAiK9bfXngpkGyC1fq8OK2MhgcIG7fRLdanADHUjZ+Bmghx0nmiHEAltlMIm6JJooonSUN3EWHr1WyuYUJNjM0gErgr4HS30K3MMqpyW+4YkgKoVITTggYjDAR+kVZvzcx7Lbo0RW5rhaEKZ4gZSwlIsUCwGjmZLvlelHG5rTMyReDN/+w+x/2CECqud1NrzJYL437YYeYRfGKFDSdC2QVICs1YAEXkK0I4a01PPGXQrA3V1OslxNMOy3VATUC+XteNFs8qJZAaADZWqus+EdImYd5rpWv5TESorBny1qfHw0TVgB+5UzQZrcWxKhtBui+ID9pbqVjeJu8Y6VSRjhl1ZoQ56Po3L6ZGNCLdjYHv3r55LUJiaLQ10tH2p+exKoO5gknh0gMXjJwx1YipBm1HsAyYFmuYVo1zz57diho1g6jPA1/ujdDxM9p7Ut1Y4TX92Bu5juIzkA39MWgaAb6ddDWAunRLDQAGVTK2mFrepWjOpXqdjctTwmpNdEKWSC2wWszC9LCC82rJumCa6581HHb4hSCdKuKxoBU//lia6w8RrdepgnRbEE4Z+ZAwfTAAAoyvtLbi4eOEvAPO72u4pHoLaZi1FtE8pB4R1tBlvbIxL0Ct+5UJgSdNKL/5jYj4UdiCDTZhC2whpbL+XgbCcoWVnoS6DeUf11L2dc4FSPcZhwqUHeP2N3coAyEfdNPUQQyEoYWLYAGNtSmS9cQWI9d4zaaBF4Wq1iVXVQxd1fu6AAztZrU7ZdhjeBAcfj4bOal+Lt0X8CJtfvOBcfubA+ZnhPp8xtVhQuKqtRU54u48tsp8IsFuWLRiPRbknaK8SlbFo4SY3WSxaKGmTz0JljliAXA+e4tiE0CFlE4mVpwOKsBPHwXwfKW96bvmpgpqUPDJ/N6AMjLSQ0F8yEgPBTc/ovaMhdXbKXtFSMajYH4e8fCJetd5X7YGhiE03Utp64+g3u+gcy1g7Sw6aZF0MDohrysb3gh2r9W79qZg803EfBNb3hBQhV8S4fSBRgEOn1fQLwRlUAaK8wvG9FK9++rxUjtCqNgnRWv19D1VqIEk3MCcloilcGtVcQ4Rn8Ub3KexhZFupx2O04DznLRRWtZcG2XSPGOyJJLluy6ZA2hXEIeMYSi43k2t2BQAHmaDUM8JyxxRC6E4lNrlmD+HPqzcs3a8k+NbmrNphWiGQ682CdUEkVRGzRZT9sSnHy2mj1Zd3B6T0OrJWHzUE3Yba0nWGDPPwO61MiX7QkjHrFXRxrCs/GAVqLVZ//X5gPPzgHgWXH11hiTG9KcS5hdAGftkog9Nk9bag72fDNrU4ggpZFKiNFx+9fvJpEicrAJ+7u/NUW6uH93KJjRltM6htaHli/efOjo3hE8Zw1wxfTDi9DIo4WgyC81CaH2RIKfaaVJa8x9WP7EJp5FAQAogKGhhjVUhU7M0q/GoCUFbNLwhjK+DKixjcAjnsqGxL+OI0weE5UaQDnNDQlbREM1sSdtgPFW7lDFYrH8pAdMSMZGgFkae4mb8yoAhvrTQ6lEE26JkEiBaUWcQjKPCq/m7+t2H44jykMAPAeNXbHRCuv6W64D5WvNT4QiEU8Fh0dbRfMqQwAif7jA/Yxy+KBi/nHD67k4V5R5Yalg5zwhr59oCZWaAPT+GMWebdWLoSzZhHDwkZBGB4V6w/3zRFs9ZUAfGw8cDymjnbiFezVOWkcCL4Pqns3o/Y1CvmwfML4x77sKzCaFijHlTyOoezWJN0YoZrDNZeFMAqQGZK+6GEUsJjdj0nCPmHLS9Rd62i7cAhMqWVNu6bc8PQBozDrsZh3HGy/0RkQp2IaOC8DruMZWI+1BxCmvBpo6H21oHYAWrWrQ6xMd551/loSLiW6hsjllzFbezUkncTjvcnUcstgCkkLUIoMehnV/GAGghs29wTwXgCdh/ofDZeCzgqazfJQBMqGPA9CJ2iWZgeJMRHxalLbmtEAaO31X0V75SId53AoVzO1n+pO4Ms+9olY7CvNGrjwUctfiLQ1UBtwQIM2RSDSGdohFTkm1qOkcOJBs4csvF9BxmAEqUzfd5ASQOCFMCz2hWK4kg72lVMtz9GEU8BWn5gpb0JEH1AlOWFl5YvVNltK6oAK85uk3S1hWp0bqANR4mgfDmhxGco+Wf+vvXl+WKkK8FZS84jBmHtOAqzbhOmusJXBuqySvKmQR384gqSk/PbJx+Zo2GqHRJXhNWCmNZPOlsa5fQkTXqjdRJFeNpDi0MJ+aFowJ1qDh/ACzPCPlgBaR7BVzMzyPG5wHDQ8X+Cy1enN8bIUwIi2D3uqKMhIdPd6iJsP9cSVanF9rQzuclnhRxWAc077QtEc+T2dqiZRXG3tZ4eCOIRyA9SAOjqIcsGG8LajRvvENblpExPzOBaxB+qgJkWcPZsL3HAu8pk0LBPi6IVFq4/ZgHFGGj6mEsFvZcymPqj2nRPHBgXZPTErUmKTP4xEppNWuIugaAkuYLNx6NL0ASqzzYhvDelnx3RVPbPlRPjIMyXxCvHvW7PMo3ycN/yo+3Kpt728CnJbUCLXc56xRW78SPC0unf/8bH883/cEEdDwDz36S1QI+LtqMzBVbZNTIKCPj/ntBEVekm/DZjwl76zi4+3LG/CLh9T8TkXdAvtZchaJP0GLcCn4zRbJTWGpdeMuMwKvFu9/PGGJuRV+nOeE0DVhiQJkYRGy9ZrYKoim5TT4GtqmxKqH+s3aUnTYJQ6wI+4JcgTcfRrVqz9x6qPNiNEBdp05VNObVOKyZxdhs1xwNmcUJoJEZrOMke58ePe5eYQFojBE1BdSRka8Jy3NdM03ZeHjJTx8rqt3j9W7C9TDhxXDCTTrjWZzw/njEyBlXUZXPqQzIwshWmR/MChXRNgAAMO4WpFCwGxaMoeC4JNzLiLwYLL+i8Y21I1tYygsjBWpZi4UihwqMFenlGTEWHP600qk8TAOWJeD26z3S1wGHzwL2PxdIZJzfj6iRcPhCDaH774+4/4Qxvhbc/GiGRMbxw4iS1vDt7rWu39OHA978VliDB9StW3senpdxWDBlYPd1xf7L5WJvElAE41dTC2eu+UpBvhkxXzshnyh033oicVbgS4UqHSctpVixSxk36QymikQVU4045kFlyJw2zAn9UFyRLzkgF21PwCRYvPh1ZqT71VujqujKWm09dqH39VXf19sysAUYzaq8OBT1ZyAnBw/YMygMa/yoeaZfT1Xw7o+3KptXR4VuFtP2OfMKxewT+t+oZAw14lQnl4cLVHQwRFMyZCE0GLyXirQw1Hp+aSiv+KC1Avmg8fHlQOD3rNpcBPMVb6z8TY7EwnhOMChBzGNRIseKznurWqVNVbBEtc5y0WI1LXq10JOH3RpdSMcC3UJ23RgIa6ixzUs3tw6iiqKJ/Ki9NYQIMmhyuMKsvUXrbDhvvaW3GWTeU35lt3Wl8jQ9CkE2Csk/2/8fUtVL8voHUgFBFageGuy9O58bC9HMOWAqCn3VvCGwD4sJM+v86F8jUWuabV4EIKtaqZWQiZvlPC2xFX62w+bfvSF11qzlMPG67irWMBeb9VwZZ6uUn86p8WeJ0bw8fG+nuZqX3nwvIj5jlERI99rnPiwVUgTpgcGDIsMkAnlPmJ8nax4nqImwXOsaj/c68DoCeScdHH71ivOeMb1ICOeKePKowMpu8WhNOJrSEGf5Kmon16xhwnjWItcyEuaw7lGpSjB6v4wYgiZZs3BDEgYWiNQG2OiRhN43p2cI7xx8IAjqqIMNpqjIlP/Kdv700YrMhVCJmqfTmtv5dfrrOripGdNWOKqUBG9lwfmjHt/afja3n1/D4a7E0qRCq+J1dNQqmyxcYp81GhS5VDZPKadmVWNFnzVLzckCn15V8SHj5se6se4+jchXwOkDrZ1oYSNGK15sYaRCDaZLWV3selCvYdwvGFPGOSRkp+k5m+s/K9pmyow5VnDUeG5j3J1Duwe2e5BAcGLFRvXSo9PMCmtVfWbteT1R9XGPBemwgENFjCpUczAE004hxDWz/pwCqHAbyworR2cNUqtLaVIeq5JZ2/Ju57wPJVyGFXrEYa3KPFwEmgNi2j5GP28XivWusMezWteORLsKM56lMwI6VKQQphIbo3CujBS0BrvE0ir28xIwkSHyOoZpu0DjO4upIKXSlEgppLkfs7AhUFp/o0ipJaAswPn1Tg2L2VjMST2g00eC8wf2zJO2z+STFlM++xHw/EfmtT8sABEOc0UdGG9+c8R8o4rl+CFjeCN48QczaiQcP0qoETh8XjDcLbj7dMT9p9wofwA0AMvxY8LpOwGHXxCuf1qaMWcxpif3k9dD1Ug4fphANeLwiwXDmxnj1zPiMWB6LyLvg6LTskKu744jfkY3uBpmvNw9tJxv4oJ9WlAiWeRbsFTGnMMjgQ/YvIsWiQbLkeT3MrAQhldBiTOtYLsAWgTu6LRuTbUWD1bTAwCziTw1YFjL4wzVF1NRT8qh096y2//Plp98x65N/TYCBBqvUN2GTBTeeuHV9AoH3XsuwC7//k3eELbvC2sMGYK1J30rTCSrmqdtoh1Yk+GEbc6it9Ldm/B12sy99TPMFRwIHAnV2gSvLWYBKYxKBkE1C6/BoB3N1d1v8/o7T4ceTcg6bS4ceNZFXgdG2XEr/GsfJxWYflQBhPmJZ2I3LDZWgzL7/b8tJk0Xf7/sxNh/DtDNSZasd/qhtzN9rF4YBCiZMeeo3k0JiBSxrwGV1kTzVGMLozntyeVRfdI7EIRfbsvl0t8DWtdJcmhxBPreJ48OQ+5dgk6qW8p22bqrkKw9hrTPEKEObHOmXmmxLrKNqbzVnBkdkrFb9JB7qtCaEVrX+mXhpjCh7mw/VYsMLLV1cNUBGkwaspk2V1A8V4RJEM56HTKQUM6hNTvTj5MJdGqKxelslDtNLaueLXuzGmhtvFj32lywHM1r9NxV86Jtw/i+aQrHAE1QmeU5m36M/e/oz+m/t/vvZNk7OgTfUugz7bbxzZZMFTSo72U4qv2+ef/SLO7+1n+eDMdvCo6qYLkm3P5GRDwBN39f1AJkapBfYcLyLOL+E4VwltHkqYeqeD13Q1RZrFeCwoB9TGIULWDBPKlHkwZFtNSRgGdYGWfdAqqAZEYpOmZkWgvEyiok+jwMLoTPI2SPf0RM2MyEw2eC8U5w/0nE6aOAOgjOV1qEGQ5Z6eZjRTCgQkvad0Azz2dp+IFNEQuQFEpOImvupXkzqlwUxeWKhjaKx9l8A2+FhtdY+FGFUJk3m3cDMDBvjmwOl/sB2fqH5MoYY8brqKFdF1BTVmWjyKV1OQuAkjWsWeeg82BtoYmBEIsWenZrVAohL0D1rpOGeAvBeMpS1Y+aV9SUbhCkZ1MXgoTVnSlaE3Z9h/erdy24+y3B/Q8NFh2s5YY1O/PW5bufCZ79OKMmwunDpOCX2wIS4PidiOWHsdWBDbeC658VCAOn9wMkAvsvK4bb3LjgdK8EBQZU9WCuf1Ywfj1DqoBJFc/+83mzT7WuSNcIqiDdZTz/Q2C5UuNnBlDqgPv7hPtC+GrmxksIgrFUrAzW7omQtXJgEgxjNgWvF06hYL9fEEj74WRh/OTwAss5Qs4BNHuN0bqeVqsOVgeoSm0pQftj2eE5vmzEqB7+7hnt4fyM3f55ZKD8yfFLH29XNmZVrA9gqzSEjAizn/tv/J0eP6TNOlFuJ5Ww1Aot6wCNUQegjGFFo8GstKQAgeXakFd9PsYWRxPy/l6/eNzbIdlWQxeCCCNBLdzEgiEUTDlinhIqKqQ6SELUFHbOK6Ptf7Qm+3FcHk95fYJWuzPeVuy+ypivBixXGqcXYi3MTIpg0guuebWebqRdRlThiAk/nUde4eku8AHNpZFbf/Z98lwNtefm77ugXXuZqAcSjO5DvQJXMHaDhTWvR90k2NxJ1mewLAHzEDbLyZXNUhRSu5TwiErEL+GhECFlP2gFq1wN6OCFwaRePJlhFey+WElU/T5zDhsEFAFISfs9RcsZzVmRVJl0XBrXs++44XpQdmtvoS5CmM4JtRDylyPiA4CqYeLlJmK+UqTZcAvwUlF2wPx8ZfnmBRhuFwitnVmH24z0+ow6RMjALedTE2ytah+mIWryXYIqFJ7Kdq8AqJHN0ANIxOrdYK3CCTxp8XI4MuJxBSwAsLYemnupg/aL0fYi1t48aMiVnKrJDJkhFIwh4/3xiCyM26sdHsKAs4zb8LwbrJ2cMbwDBGher6+bp9p2bzqBEraAETv/phbtHRwC+nai0TYV/jbRYoisFh3zOLsT2xFWfqLLQP9Tbqr/n1S4aR7O+qAzGWpMX+++HxHOEfuvM9J9xvRewun9gLy34kejX5GNEvFzd7/37XXNMtKmU7IKJmsAdhZgWQJirBhTxpzDtmmThU7WhCJWT9uvx+oJ+pw1HrdGOSNtTtpecT4r8464AFwq0lEwviaACLsv1CquY4CQ9QIqAD8DlmcKmAhnVyj2bBaATSHWbNamteMug6HT4ipYL0MbOYfVGwHApkjYoK/KdEztu9HeixY6KXXNh4jY+YohhUo3Vvg6AvKinR2vd1Pr+MiQFhJZioZoimiRsbL1UpM96+AJUgJKEYO5EmTqscRQQ8dbBNu9x1iUpSAzagkqpJsHo+HM6TwApAjFRIJdyiDrKrnsQ1fHQU1RVTFm4RKwnNLWy7vJmG+Ar95nvP7dUdfQUEEz4f57CWEBDDOB8bXg8IVuRC/GTPf6//PLhIePE8bbqjQ7U8Vwy8qwbTD5GrWIMz1UpLsF+Sri+GHUgt3eePP5dEMwanHl8kwVB1WAzozxFeHqpwLOCigAtEC5RuD2h4zzd7UNeLjKujasG2aKpbHLiwDTkvBVCYhccVwU1XZeoqLZWnRANuN7FDUw72Y2L2bx/jqLQrGJtE1KT7Dp19e2KWtIi1jzpO/6+FbW2fjRYvAaY7EHKZ01Yfu1ouVy6EJR9ceGY6i9du9JMzJBDJQKSNSkf5iBOAXEY8F8xTh9qJh7bUmNDm0mq1ezuQ4an5I43NUsIAANyu08VJWiNYbSRZaXsCYOezPILf+L+255IR+LezzSPqKKtd84/Wda/keAIohTRXqgFruHfZ+qYHylyea739jh/lOrkzAo9crjZhQpllOqgZTryhVwECVMDd2UtY2r4SEBHpFDiqhC6Q/vQR+s6NKL+kQIuXCz4DKCKl6fkJZbUcVcF8YcAsrAGDg3Knov9MxGqV2tvUAx1GQ/9vZs/dRsYdBlDW0BaAl2/25DKYkCDdp52QytutZxEAFlUIDCEDN2MW8KGX25nJeIXALOU8KSo66nyQSMrd10M2PcLbjeTXhvd8JUIh7mAcc54e7mCpgY6XVAPCr79OFnJyw3A+6/q6G2q9sZnAXH74w4v9TxDa8EvAjiUY05NtbtkrS3E1UgPqhXdPyQFVBzked0RbMaa2jt4OnMyuZ9C1x9NiNMFeE4G7ScURPj9OEVTiygoWLczc0bBNCoa3IViDj4MmIlAAAgAElEQVQzfACzNB41D3npF55QNN0aaqTsVWHVGvJVUEA2FhRvjhZDbc8rG6Bgsposf7bej+ddHoo0/xYqG3arv9twElerEIItsaEfvWvbH20trER6mwTf5ed9QUdCZbSagvMLQg1KaeKWlofAXNFscjXolc5WqWmcnMETdUWU2lZZQ2uq+eoccN54NFhhxZeemns7YtcDrbBtUiHVlMlmI+uXGjOvt1NohZpAOFWMpIKCZ+Xgmp8FeItmzhW7V16hqoqoJGjjrwRggYaOWmGnj8kgqIU0KhiN36vvpWKW+FqDYJQ1Va17ZwBvr0BTCgA2yVgip8TXz0jQ66EC4nk0i+2HoSDGiirA3bIDY/U6RAiRtXI9cFW4NMdH16vFSCqNKUAmNRjCQwBnYHithszpo4DlvYw6cmuB7p5NH55py9fyOswCYvV+vcp8MVLKOUeUaooWq1fHLEhjhiRN2m/Oy9rz/u6klC2lsnpWlfTZsGAJguWFcradP7hGjcpHRwUouwE86/rZf6GAgvm9AWXQ50wiSMcKXsQ6dRLiyZgOsiCeRNlB7LbjURBmGHmrtUB/X+n92Trq8qI5mjoCx4+SeuOLFoaLFfWWAQhHzZWdwwAKgmFQwtQgxliSQ6P3V8MGOJuCKUvQfGnu9t4FszN5awFBa1Lna9S50fwZONBA7No9n1sf2XGYdqnvuqhzBTH8uh1vVzasUjFa4rkn3izZ+NHy9jstht8roP7ZdAoHgNFtdAetP173Una1wXclEM4fEOYX1BZ+jzaD10iY0niELNkMFhoSmQnxnhXamIAaCGWfQWOBdyDEFJR3CmhChzrvhmS19vqEfDcxm/405MoKUM+Cfe90isaL85ziphoB6X1WVNBSUHZRlU1Q74fPGbvPCna/ACQw6hixXEfkq7S21/axEq1Q2QDASB1FdDMrrY0VfDrgwgvebP4qE5jVW3KlUqoCOJRYUrbtJnxqDFjAXFFZa3HgzAwmLHjUPEgachP4b87KZsFmAB3SgkgVN+NZiyqXAfc82rzqtXLKEADHh51S2hflEOOZkO4I8QS8/P0F45dnfPkvXOOWI8pVRU46Pua1p8/KJEArjUmoGEdNZB/GGcHu2eG95zlponoJG/tiGBfsBrWqh5hRKuM0J7WuraBxOgXUc7dNWRD3GSEWHF7OGFNG/kEwWpeI6Zggc8D0fkQ4A+/9HcHVzxbMLyKOH4R2Czwry0Y4LpCkxoonOdT7MWPEDJ6rz2YMrzT3U3cB5/cTlmu3VAQgak0K8w54+B5vcqX++CUC8UFzPEUINVUs1xqOFSU8xzJHFGdt8O1TNXyJSb/bkveQlm/0/e45OalAXVjBoxI3isg/7w3SaqiPWiLoOl0Vzfr666kM3vXx9jCax6UrQaxJucbb7QG5lW/J6BV1pULmEUvqU15Au5QpH5Lt58xzEVGriiHNjV4pWOQbz7te4PG1SZRbamOoyGaNb/ITJmfWVsgkaJxpsn5/c8u+sLv/99cCXGmt7AEePmpEoKSoHyprq4MwVdCDniDM6slREfUO/PQpYLmJWA5WTChKf8KLoOwIeXcxR64APaRV1DPSG6ibZKrPad9B8pex+Gq3YS97HjW2AvNyxZP1F55RFbTaGq3jqEgoSFya9bkp5uuvw+IuV8vx1UQ4vxcgYa/gC/MctsJF1giyCza4VYx2/wQDSJgXI0Ktat7nj8wLYhZEY2/wcbZOo9U/CzV6LgyYWrU4NVtYcm1SCE22H5Qs9eFjRh4H5IPSNEFWhCPnAfEYlQZqLpDIamgNxoJcgHQSYw1wI1Jr3sIkGF8J6kDIe/NsrI2BejgakZifoYs4uGEoq+dfSb1OrEZM9dxdXdeGF1STMWMoa7hNSy/FzDv0ud8gHslfLWLhZRMi23XdHT07vQiepNn5VR6Cb2sYjT1WrRQ1bjG0kES2vhmlX0yyCuNL5Eb3X1cufTMkAB24AE3Sem5Fuax0wTbIMkzh/MPulLpF3oEayJJDG4Ul/Q+tiWuC5jZGQ+p4a9rFfnwx+/VsPfs8PGkQmZV5OQ/w2zcl+/BdxsNH6yIcXwtu/oFYrsb75VRI8Ng/YX6R8OY3k7I8Jw+pVIyvCx4+jsgfd/dl86FFCaQ8UMZt1sg2XUCY9QhjwQ1BWniib+bl3gcDxvoL5BI2oSQXqoArGqzzPTMKAxwKUnLFoRv+dFTvZc4B0VoEHBIwlaA9VCptBLyfn4Kxe0PhzLkwygi8+l0CakC+qqh7hZQrcGFVdhpW00LRSho+buAGqGBKhp6aEI0RnRoIQjz+v1uQkuZ19mlBEWokoqfjAMlsDBGCYdTiYvgcVlaWgqygAkdAQqAC1Pju4ssZIQjqDyrOhDYfOQeUUwQWxvGTgHiMePF3Gdc/KVj2AfPz0IhFQwb2n88IRy03qEO0dS8YXs94+UbRoKfvJCP0VINpuFcwwvQy4dXvRJQRrZtmi0IEaUZVPel5iyMCo85/K6gUUzBFQ3CcoaH1YDVLAzXkJIA2zz3ljLtZYhvLw+1ka/kpb4VJ1woRtfmrhZ/87K/y+FbW2dTO0nBCSU+oN4+jYxZoORC3BC7zMi6sgG24bWP5y/bzjhZw6wj22hsYPhZqa+rxdftXs/LXxMIqTL2hGFJVbjQAYkgpEqyQYc8JBae48BvABhbbH1sPisyT0PYJjeNKYEifbswEXNYrlhHI+6BJ3qKbhYsAYf1gKw5Meg4qj+fC50v82rBaigINhUEFhLNBXOK5L++0ihfPaU4mNKsdDVrahyScPdyT7RtS18ytSn9ZVKEJLA7v09h5BNnCVooioqbQNn2EHCXpa8bCrcULgEcV2AjSmpI9dbggQtBwcyBRxD7JBtm0mSg7VzD26a7sY50b69uCuiq6hoojsTbYFQTGSm/kFgDamJ2leEwZMVTkovPDLJhFvbe8aKHk9JyQHrSJ3fzMjUD1UMougBwdSqSs0cta1cysxaWqoGx6s4Z4eY5NJrD14qmDNIQp21pvi7s9JtuYXVF0K7OgJ4xLl0edB9Le73/vH4ZVcjd4tM0/XXx0XavrWnuXh+DdX+Mf1/FWZZNtschZOwUqLb2SUMZRscE5mddzDquLa1XMYHNZgymRCxgl0CkkP1zZbFxtfZWkC7DYwl6/03lRtP5Iv+GpO79Xs9tbZbQQRBDwQePhH7+4xyEteH3a4+E84HS7A99aXc2RFYXz/oKwK4gpI8aKeYpqbc4Msk6JvKytCVqO2TdlVSVz/bOK4a4273C6CTh+pGGepmSo+75ofcWbZI3HqiaArz/LSG/WRis1dqzPpCGZ44eM8wtGPqgSckRR824EitACQAuscFbWnjrJ5o4UJq1eikluoAlAAiBSN8nW1t/ELGwxKhn3kmkxqpepOwkB5RRwHpKuiWSWu3XhDEGRadMSMS0R9w875NeDnmfW0Fy5Lq2dAgWVHM59IMnCZR2Tdxg0T+OQXA/v5UVrekKoSENu6CSvB4lckbisiWZTFNEAAzFqyGyXMmIoKJVxP2lo1MNnHjKSST3AqejajLFiNywYYsH4TC0T6ZW4Xc/RWssUMVfCsezNoFq9UY4VcagIHy8gErz6aMDXk1kUAvVsrVXB3Q8SwpwQThquPXxecf0PjihjwPTBoGvMDbWozyuMhGp5IO+nc/VZRTpVnJ8HLFduYK4GHlhzPcJKlFt2WkMm3nMp6HPKI6+oQjcYbcyPZLS93zybDu25ETlueJnCcYh687q7MO6vgxogoh8BuIOakFlE/gwR/UUA/x6AL+xjf0FEfs8+/x8D+Hft8/+hiPxNe/9fA/BfQU3//15E/tO3XfftdTaZ18XnRJVtAxlgQIq2WJ1ZczTmGrsV54nHLQLtCWuxCz+1H/ea/OOmVAirl7P5DjoF03s40v3uf+uSiqImKShVZQiOBc/HM26GcysWPIcKz+eQ9dMopCGe/bjgMM6441GBE40luvvx23YlIzBlBKSHqsV4VluUx04r+6lcIZiyqglYnvn5lEMtv2LE42r2idVJtBCnKAU+GxWKW/ZreJHWS9bVsXQywlZsayEQ38S95QesnTFL5WbhO/S3L6SrFobSTpTcque9o2S/NmphQ0Kq4qOdh7X0g567KAuDz6yNw2a9mbLXa7i3sgnTdl4OjICVQ0EIq5IQD8GIFcsaF14KBWNUKHZ4Ioy4Db9piE17omQEEmSr/QA0rOie2CZ0a83gehj2zpB3/XUckHCENgWb64q+870rpqyd6/CwmzDEgudXSmc6LdGKUVkbz2XGFCN4JsQHRjgT0oMyrdchYDlwYyKA2F4nQNk9dO4d7DK+KRjeLBAaQd3mbZ41Q5uiJbSW4AXQ5nC2ebRDqHk83kbeT9K81u26WUNo/rr9zJZk1ryvuj7rvtDzj0vR/DGF0f5lEfny4r3/UkT+s/4NIvpdAH8OwJ8G8AmA/52Ifsf+/F8D+FcA/ATA/01Ef0NE/p9vuuBblU38MunzsmZNsAdQM2GhqFbAOaqwMEHRHjqwFfZQJfR0sSdazqJBlvtQWe8O9+e9/B16niZMPOTXJLbeg+ZX1rgtFu2XIVFwyoxzqviMBK+GPXJRfP7uasb0PVnjwARcXU8adx8W7GIG7ZRi4zQNOJUDaCGEB9biOatraUWas/fpqYinClRgeplwfqFsCNq7RJq16ON3CvlGqskGdxXg7gcBDx+H1o1xOWjRneep3JisQb9TRi3Gq6NOLi1YE7GPrEQNr4kpNykEIdaaHCZlcyYTfCYHPY+zqdMxEkyHsGLmBj0PZ6dqsU3vnVAvbZNO8FYrzOspRxBF5VClFRbPwLBbcLWfMOeIeY7Ic4C8Ui8IQddEFaurakg0rQOpQkrUaPDj8zmhDowhFrAQEglC5247C/VCq5V8tjbIIoQYKs6LjqPkgHIKTelCdM8hCMjYx9WD03N78Wq3fVoo0ZXQeFgaCak4TY6t3XKMKAC+vhvWPUQAp4KQVMGGWIBQUV9WSAVmy22evhfx+p89+JIAVSDdMcKkXT3H1wXhXEFzRZgq4lEfHs8VtBRFwE2M+Sbg/J4aBPuvKzgL6itai0WjMoec30+bfe56Iz1Yl9MbwvTSmsm51+1ItY3iARyg0Ic0V0MJG5AAeSSmUThd/O0dHfos/4nK2fzrAP6aiEwA/pCI/gDAn7W//YGI/D0AIKK/Zp/9R1M26VYffr4C6igtXyFgbZpUCZhZBZknywEV5JcPGv6nrcXe/m7JQX+OciFk+6NHujWam0vzwxEnYia9eWeAW/L+HaXZiEeCRNISmsS4jztMS0SMWpB4tZtxczhv4qlD0JDJGDMSKxrqephwlzLmKaFMQaG2kyniIu3+OQP7rzLiqSh9O7AWqSYrlCOd95ZvMXoO9p1jQrRax9GsMkBDF0a/XqMKa3YEn1uSpmQaX1XzYGxj9c/M/+ufMRQeqjTrjwCI7daW66uhhaEc1VOK5WisVoKsAyMvnbKZ7LGxDoYgcJCiD8iARJvcTwtDBUCgMHZpHozWc7x/OOG0JJxixD12yEWvjawWeTVPrxJQE4PIlA7QmINLtuLRIM2rCFQ3uZo1d9ONsSh9vHcLzdaEsJ4D+C6uzeRoVTZsAAwnpATwKKZ/mbAOXLEfrWFb0nYKedEmZLIwaAqabD/r3m15q2sGrtHg5s4KwVyxTxmjwbOnonDuu/s9yhRQP0+IR8LVz4Hh9ayca0sBzwFhsjWZFcASjwvCpASkZcegojxr4Vyah+RtQ6aXOwSDfXsn0Ro1XLb/umD8esHDJ2OjayqDeerRQr9uaPg8mRMrlxETrB53W//6bvv9so3GuzsI5d37UALgfyW9mf9WRP6Kvf/niejfBvC3APxHIvIKwPcA/J/dd39i7wHAjy/e/xffdtG3AwQGs3grwGfd/SLSXPJNItysBTGvRNx6eMoLceVi4R8PBalF14V9viE52zNOb6KohC5EglVK1u3CaodzMpFgSUbql6xVsm3uYn3S2yW6RTeRwm/vadgUGTo8kkJVK9tCZsTKD0UjUAclGOU5KkCgCqYXatE1b8bngaAKAQptbiSK3sKhy7kAJjzWbKvlYdByRRrq1HyS1DUfr+zCF3xqfr9Vb57z+txFLHRln+MnEptkc9XXp4iHz/rYezeG3Ve6jk4f0Zq47/N9FQbz5Q2lDkGt82rPvDZkHgBRZXRaEk5LxHlOyHMAT5pXkNSdn3XMxfjxgATnhHOutAAtZr097hCCtjuIrPU+u7C0LqIpqKdQKjVanVqVrXo+R9RjBE2M+OCGkF5fEjUG6IaEEoBBj8KTvu58XQIrKapIaR4moK0ehHllTSDSfR71GdVF2Q7yg3Zw41FztPkwQXZAsDCeCOEYi66fIaIW4PgdRo17eKi4jITpua0nGhHmoYV1lwO1dc7WQiRfJ9Qeuh8IuzdFw3K2rs8vtGX1iTSM54CGMAHjK0XEAYAQo+zVg19PqM0YIfq+MDA/Fyw3pYVR4R4NsLYTv6jNeZfHr8Cz+YCI/lb3/7/SKRM//iUR+SkRfQjgfyOi/xfAfwPgL9kQ/hKA/xzAv/NHGcjl8VZlU0a9dJjVUq4FKAVKYxFdClroyliBnQrmkbLoLWXzMihrTwpUgA3tVkZVOIUBxNVT2khTDyH1ntATAIGmbPof2HhhluNQwPuVn6mN0X7v2weLVw83y3oN5Ui1De9OR6zgCJRBIbbUiA7Vk1gqML/gFjbibEWlnfLwHwQNdymzgccTsCkq7edYO3HKWry4AAErUEHzRdpjXsrq8fVMBS2k6dfy1+qoKWiOKRm3GgtKok1xXX9sCDIb6qwbv72GM3D9M81fTe8l5D3W0Ig/e0OaQbTlc3+NkCriULRFdwxdXF89ieOcFExwHlBPEcNJlU2GAMk8Zae1t+fqnpon+EOoQFDAwPk0AqxhvJQyrocJQyg40ILEBaeSsI8LlhLwsAzIlfHmYa8dbx8S4m0AT0C6N2/QipRrUni1FtY6sk5RfowtWWMVtHBi6PJDBPVyRAgTCSYSCKKiiVk0sQ+B7BRAgUJavLwQ4p3lksaImgQPRnlzvZtwk9RrehiyJe0FRYDj99RAcANJ15o+t9N3gH5ReE5N2EJsVTA/C60mTBjYvanY//xs4wgoY8DDhwHzDTDfuGtr6+YEPP97C+KxIJwzqAjOH+60fsqUVTxXHD6bwHNBOSTUSLj9jQHH70abc1lfWfeR8yi2Nd2zTP+TeXwpIn/mbR8QkZ/a6+dE9NcB/FkR+T/870T03wH4n+2/PwXw/e7rn9p7eMv7Tx5v92ySWYwGCvC8jbIGdxaIwRIfhc464b45zLNpnTjd0+n+vgmbSCdgu6Rf+x75Z6QJ+825iqJr0p0Wqy1XKvC1IRmjyBYTR0BrlewSX6y2SAiKjCGleiFS7i6l7bF7487DYtGwjqC10AXsM4M0tuEaZU3I986awGDBwAYr2ynzNr/F5kG6ybMcmTsX8agFd8szwuLsARfe5+X/2zPr9DmyUdT4nwMA0qZyypZs77dxdAWhXsXvP3U9vwIwesNBVgCDh0XseUs7/2qUbBq+OW1JVySYDfUlfk3zmiRayDGsRKT98SjNKN01DWZMACJXRFJUWqTafiorrY6PudX+GOze68Ya6q+tIdlcUzwn+Wh80lgZvLjUvR8haRBoZsExszJBkO3BqMAIIaU3FWHzjk3wxtWLOs060PMSV0PMWnUIAWSw5jauLV2e3YjNW1FOtum9AVQEyxUrIi2oITNVBs9jg17XSEbs6XMPM4AE8WSFzrnCIHrgqSKeGB7W56KdR2kXwEXARTA8CMorzW3mHTVaHZCtBwfRuHf9jlmfAbzTMBoRXQFgEbmz3/9VAP8JEX1XRD6zj/0bAP62/f43APxVIvovoACB3wbwf0Fn/7eJ6DehSubPAfg333bttyubZwqFlEHrTDjDeo1A0SA+J82T6KxPoNGxPLrhQuBsXF5mnTeru9pDtTxQX3fjobaNkuotY0PBqNdi4xFNPg+vGB/8bYWMvv6tqF0Qq4UhOuvVhTgdMth44CCATAH8YJ0/x2pehnUwfYgIR27KT5KgkGj/lFiBCAiFdQ+6kLN+QWVUhA0t9uMKUqAwZLJxOqLIFZYJARFVipS14K025s/1elQUlHD1WcHu64y77w8oSelqZLRN1YXt3Jv0e3KG4MswmwSLo0elFUIAJGkFfu9VCNDGRA6tLeuz9OpzXzu+uRu5qikC50vTImMAOYAeAREIMC9HAJRJPZxSGNOUrBsjr0qegXxQmC1fZez2M3LWPieAo8nWc3soDCRgAxIMsWBMGbuwYB/Uq/FqoCwMLhVTWSv+JasQrKMK6uIgDTOeZJCGntPrrjT5lyGzyBUxKKHkLuYNIs5JQJ/vj3gxnHCfR3yxv8J5Tnjz5gBZGGGfkVJp+bSyMLLr+0MBm0c3zxGnPOLVzNv1FZVqpilg95Y7udzY1RuruhpFwoRXvxNBYjkXXiH555eEh08i2Pv7zIJnP9HupPA28f3hTQGjznw8FYSpttBz2Qfc/lBDdc9+mjG8yTj8fMbh59rn5/iBss+GuTfWoGS1FvLrGTrexaE5wHcKEPgIwF+3Vg4RwF8Vkf+FiP5HIvrnoXf+IwD/vo5Hfp+I/ido4j8D+A9ERCPnRH8ewN+EStv/QUR+/20X/iXoajQ0pslLoxShLhRl1kU7utDWZdy/F7bNWeGLJmzdpaWiFXL1IAJnQvZr6XikJbFJqCWr++uKN3/qb8+9pZa4sGtdnGMzrt6afvQBF9ZoVm/zQjaQFmnwaz/dWtiIziXQv7X5wBPz7sLH76esMPNNt9Cn5nijrLs/mJt1STrUrtEoerrQYjbvhVfvs50b/j17fq5opBsWwViEFVK7Mnjj0f2KASZqqEAN3xxPb/FIQEzhSOlYBfwa1jjPiyGZt5Ml/b3CBb2SNzJLQ4OdS8JDLohckKhqbqYEzFUp7Ys4pHa955brBJqCFlesnZJrNE0OMuFV4fTvXx6e14lcMHBuOReOmndy/jeAUVBBrbWAhhR7iLkI1r48fr0WwvZJtbXcG6Ne20a6DaQAThlUxq2xCazPpLI9a5t/7b5r4Vpxzw0AkSoZL/wkWImBFaRGW1M9JFspltdC1KzvhWmryDysV4O2SnjX+ft3SVdj6LF/7on3/623fOcvA/jLT7z/ewB+75e99tubp50t0Z2dBNOsV4JBaVdh0kgj7bObwyNMDqFmoMZq9TgEWFGiCzy36B1Bdam8Nh4NTA65IhSXLwR3Aeqh4hwFn+/1/3lfNR5rXQO1qRY2J3S6kCYThrqlNrfiOAoCuZlRr3WFSyVQqEhWdNgERF3x+u0+Pf7bNdWSVFdlZXMPAWghbVLlnhajhTdcEPNsIakFaNAbe1bVkDp33w84fhRaAd3lfT8JyjAvw9FS/UakAoRKkAxlQWBYQd8qXPoxrsqKNv+XAOS98pR9tU8tedtCudluxtdJWQ0NANjUV7HdhwvrLoxWmP0LAAmW57ZY90W9lFCb9+L6bfVwtNlaCGtfE6/JOJ0TTjLg/jQqo0CojTq/ZzkohbX76MwrHYsrdwJq0rVI+4xgJKgwcMIyK5mke1pEtcGy5xzApAwKgRUhySQ456jN24BWVOuw7JQKCmk/lxgqKgvI2zUMtvdNocVk8GsWlFgUwj5bE7m+5gX+nC0qYaEn2hVwUI8UlVA5oC4BLIrQ5AW4+nlFPAmOHzKm92hF5hEaE8ar347gHNfIhl9y3e7rGAqaLCLR/k5Xv6jgWTDcLaC5Yn4xYL4Jm/ykH66c4kkbxc3PI04f0PY6v+JDbep3rM3+MR1v92xq9+oPIWD1MoDVk2leAlp3PvtzE66t6M/zGCSacqmAgHCpQFC63zfeU2dE2YJshk41DrdKZl3pgpedYB4vAsgeg7UKZT83sDohzaBmtXw3AySLi6c19qNswLqRidBIFYllFeSXErudU7CyLqgkFZt/VyT+IwyL39v3ZGWLbsLc82xAywMs14Tst9EptUeK4dHYHn+23YJtfBZq+SryHj19cvUJb0dsrsXyWSUKyg4Ngdf6qcj6/WbUbIyO1aKVoNevw4UR4aAEn2tAPRozHNyCbxQl7Zn6WDX0RXGtvaGgrQBqCZCqoAHAACKX4T0vErSme60zrStIf+7BgA6pNNi0F8GSJx9g8Goj/SxioAHzyIfotTeap5pLwDkrqi6yKillcodR56hhxUZ14yCJtUW4fibGAmZCzkBltn3XPdN+WfvaZIVwcyggqzsq8woEAHRNa3FzxvxsbM0Qq9GxeT+mvJfmmWyTi6uh5OH7Fpq1/RCPsNqforA8Jm1pfe2hax20k9bWAOtcqq0YIJab+qW6gP3JcXm8ddqGj48QIczHpJXIE4OPq3WtlphZsKO2d61urQGr5Rm9erm2Km1yYWp5kzLzJsbfFlKF0piYgmvnJLTWsk5j0gvwRrDXk/k1RgRsFyrLinayxV962Lbfbx/uI0GlAGF+bGIRoyxh832npIeHH4GWuN5sUD+HJfsp06rYXSF4PZ/L0i48J+xz1Fn6QEv4Ss9tZ59vhW7UeSPtlAb5dc+VZKvoO4HRIwKFgLpT6DcNSi+zcqERxC37dqKLufZn4eNt68HmMKyD2Hi+7p15aMzvCwCspkfDeC7l9PM1M2oQlBSwxNqeGQSN2LE6AIGVrdmJRgnAEgoqccvTeH1RLdqHxsN4ABROvFdIMnf1M95vhVnwfH/G9TChCDdlcZwGMFdcDQvGmPHeeMRVnPGQB9wvo/LDCRsTdrHczb7hSs45alsHG/dhnFEM6eYkn+6pUbBePqm0MQHmpRnyLQ4ZECXjlN6O871XNTclonmzgtD2Hs22pxkoOxXsd59GhDkoLLpr8e4IMVgoq4W6IY3ySY3c1UJsOT+TE3UA5hfA+YMEktSQn9WKm3lRZCwv2l/LdVwAACAASURBVHailRUQML2IoBxRO57Bd3fQt5P1+fsvXyNXxufxWqGiy4AwAx6z3yZwK5DWvEnbXATQoC50TAXRqqH7ro4iSpfes/TWyo0pV85oAq/xWBGAoSLsCjgU7HaLRkxsw/hPyQG1Ghe55QnI+crc4CZqSJNWs/KU5wE0JQcQsKDFiC8PATbhEeelgmVB3AvbCNLmRsHCRNTCRb0AdtDCoyG6Evbn04/rYv1K/3m737bGe+VBNk4SU3omgC1UVROUs64bfwOG7AviWLA/THh5dUQxobkUxsNpRLHwVLsNMz5cuMM9DWuApcrJYev+HVOGphjaM+rABM2zyGhAF57JbwUgQi3SWmQ3hmt/Hi3ZbdxZg45P215rqIs5Aqi93rfhmWK1ZwkWhP2C3W7BYVhwNSiMuK+XCVzx3cMtXqQTphox1YBjHvAlXyNwxXf297gKMz7dv8J78QGfzzf4Yn6GLIxTSfYItW32KSf1eoykNAbCYLU/h7SgCuFhTsg5Ni8KQPPyYiwrqk2n2xqRafjNx9wfISiVj7Nz10KQkxoXLXxqikHnU0AJOCf1PJ1lw8O3jhbsvd0WZl4IocL2tp7QjSdfz2UAyrMKSRXpZkJKpfHMeefY45Rwuh8hU0D5OoKWdR1LULlAGQjzO9U0atN+Q+7tn/bjrcpmH3Ux3hzOOIaK+wosGIBMWh8DoMVGsy7vTZjELBdXOs7EWysj01pRDtFmbFI9DIAGj3WU1kYoP0HlEWiFfnqMvAphJmCpynqABZryZhP5ndHsCqy9uqB96rm3BDrWe33qd9BjXL4Jduq9C9e7np8p6z2zvzrljQ+4Vw523eGWEM5A2SupYbsfdHNH0rwj50XzjYzunjfMDGQgDhcEfkuVGmX/mpOhlmfSRLxeN3LV6vMlYs4B8zlpNbvnvTK38FLLYwxV10/p1kJnvW7muwOMQKBQfG/7YPfDZ22YtoZM0AAvYSIN5Z5h3ipWb9CvZfNTzhGn5jlKQ3BBCGx5FrEvlpm1O2j3nIi0ONKJO4FVYLtnUoWwCIOpYh8qqjAOaUbkiveHI/Y8gyGYasJ9GfFq3iPXgGyLokekJWOldsYLv9Y5R1NCUYlRu6Xq4bNl2fKyAWhKxvORSly5cbDb9WPKqMyaausYrSUTQFpnRl5c7EwW/fP1+ff/V4PImBLSBn1m1DqQwMbSCmQDILsCHgueXZ0xxGIs3ToXi8klRSjC+mahRSAaEzwBy0Xr83dxfCtbDLwcH1CEsAsL5kPEF+MV3uz3mM4J+S6BMiGcWIUgA6gaCustcQmy0vebIKmVlbyzUGvT26CS1QSWex4GgQZ1uHe20MxQMAxKhJjMAuv70wPAAw94EKBQQDWy0Nb6GXB09KpkPPQSa8s3tKZefnQhvgYBle532P99k3gs+SK01RA+1SzgHFpNUDgbNNxzNd4i2q7ljM7tXBm4/knF/osFD58MOH5IDZYMYK13MImQ99LYGtRalDWh7uNykkwT8mTKjypasVtPK+SoPp71te4Z1RJEY8iYcsRpSprovkvaQnhfgF2BTAw+hfbMG+N1qlrTk1n7Jy14UhGsLbR7hUibz/CiXs0mN9XNnyt1Ks7RBQ3zGB2QE5tWAZbFtFTtvCoCyr6AU1FvzNY3n0x5DVbvYWG4MWYc4tyWVRXGuURbWoRcA/ZhwT7MSKQ5ojFkfDK+xoFnHOuAu7LDl9M1Pj8+a2SnBDS6HC/wTFwwhNJyN0tlPEyDAhas6y4B2r6A0CDXeYktr0NcMQwFh3FGLozTNDSaIC14tn0lrpyAcbBePCNvPpvngErRAEX6EKrtvRphOUvAmxO60eW5mktACNrzb9PZ+jhJFKSrGfvdgu/d3GIXFtwvI5bqbbuVV8/D7ZIExcJ1QoAMGg7mXcbV9fTHQFnz63m8Vdm8mg7NFV+MD6l0IQ6JqzVyaWUDWDdzJ8A2h9AK9c1rArxPBMO+2pK0vrg61FQRAhWNI1dZe4l7eK4sinwhR810Q1nbSXdjvaTZAR4rnKfuZfOFb/gcdRagzQkZgZY4U0BFKyzzkEDbRG65ef7Kr0UKy8zXASV19/NLDLWdt6s1AtCMgGYImHYW73LZ53uA1jivFhtY1J5AKWiB4z4uGI1z62SFsLQrCFH7rcii9w4yJoo+OWT/1eZ6WBU4mqPXPJtmqFxYyZslaHNWg3mZ3K03q/uJJ0tMB63H8XxYK0o1ZQNgTfALNFfRDCm9jipmDTUn4xmLdkFXDFUEgw3Ww2BTjfpaHm/VIlpDU0GtpYFT2TRCzlAQDLXGkLY3qqx8ch6yRlAuNw0LuiFETYmhMmpd0XoOl5Yqj/oteR8eH4dAvc3GuCGEXAskkkZHZTX42sOqpOSwvh76heuKzUPgQT2Q3ruqg4boJK2h1LmElldjiHqYhrLzcIO3ZG8GKGBN6QRDzOBv2Fe/iuNb28/m//vyA3UzZ8unFCtGMygjhFBHTabCKujJYbcGzRULd5F1cwxBrH7GLCDrgeMkjI1ZAO51aLy0hX1SVSFm4SFXfhmh5XsATcxWIZRTBB0D2K4BoOUbNN8kdm5bbF1S+RHzcX/IN/zuB128Yt2ADaXUFewBulFqrJDIalkVIARu1hxbIpQKWpLU9imEgdOHhOk9S2R6aOziHpqy7gSwFBUE8AZuJjmc/LOh4MQ9CjHSQ9Hnb8WtjmCSnUrlca/K5cX+jJvhhOs04fl4wlwiXt/ssVjBIQC8edjjRKOGWJYV9dWMis67A9Cszj6c5patN+pqNRuuEE1e+XPv0VAcZLP20q3g+rOM5Trg9W/xCoIgVURSuSk0TWDXZo1LZmDSVgdtHyRBupmRhoyXV0c8GyZEKo1xYAzZbkvpWaYacSpJPZGSwCQYWOHMRRgFhEUCpqqFokUIuQScZkWc7YcFMI/mOk1tnufOml9mJekUC2EHtpB00DYIADBxQq1k7NQMooBziC1fhVCxUFg7o24KT1f6nOhcg041NCzA1XZtOhLwPKv3W84BMHRf4/tzw8ah9VG9EIrrevbnVA6Cui+gUUObpTK+Ph2QQsEhLQik3mUKBUsOOIcByEYftdBKHbQD2KIoz8Z5097hXRz12xhG2zQR8rDXRa3JGgoyNzRALfM+/t9yNlo0Jv55txJdkHQV5X5o2Mul8WOPY9P61yw2CK3dRa0hV4vnYhVSa8W8SQ2vCfijGha9ddaNmXoF1sXA/QNESoEjVbY5JAv9SUErn0FVzjpH3QD66gSDbz3cSzEvoglw95qa90QN8baG4ToDs/da+2fTwoboLGkd1GAoqUMNWGpoFfUpFkypWhvq9Tx9/mMTj+8U7eV9tTCudO9fHs2LtY/4+br7UyUrq9cEUybSzYcfvSfWeYQ9mIGDVvoPVlwJaGi5knolnkfojyw6T4EqIinabKoRwQpGFwnIVQ2tYgKfCJvaGlc0l69tbp7YV22a+jUraPKAGWsPnyYHGEJ1E2aii3sq/Von9aScYqfds4N8ohZjbp6l71f/r1CHUDTDzQyROlbQWC2PZud24zRY3ZApMGbLHTo/YW/IEFqjPkfzvatD60y/hZ7Ns8OEKsDxPCJzQJ5CCw1IDav1SRrPdMUibt3N2rgJd2pm57TmQQAovYrRlvDSeTbuMfs6Y2wt8qrKpJagwIRi3GQGk4bF7dmTxhbKqBYzl7Hj2wKshkbvQyGfaxIVQFvoDUW2CceY9POYli9SUxYU6soay8Z/5gpaaLsxuYLBgBV2SrGqcS9Oo9XyHm4FV58rnZBW2xOOH3BrM9Ag0LwdqivyMBG4bJXVI4HTBDc9VjasYR6ypK/CmTsDQoBzISyDAQJKQOLVgvfQD5uierabMKbc2JFr9VwCaWzfvI42Dx2CkHzsvI6P/Ll1hkXL5VQYGwPW5nHQ89Gov0/vE2qKSldPUGZoC9d45bskUXi357uAtuZ5IjUGWIEKZa8TGFit6WdpwkMecC5J56kcELjiEBUEMHDGFWdlYDYP8CEPOOWEP5DvIFLFXFXRvJl3WApro79FFY8n9pcc8GbYYQwFu7hgKnEtWrX6sjiUDbS5FMapDJu1ybSWB2g0QfcyswIYXKkQiT7vHFsCvhee05KwLGsvHmbBkPJG4aRQEHcVdVxQb7aL0vem9wGqC0POwaIoFrkYNceSDjOu9vMaBgR0jiq3zqqujHcp49nNCfM+4kw7Des7ldYhY9wt2mH1Qpm+i+NbGUYbY4ZAF0gpBCJHrJg1wWZbElqYzI/CuhAAT3JTI+3zVsMtqVehQtB/hwmC3vDv598FGlbQASwcx9NK7tjgv660PHzisFg/v3NQ0cpF5ctTXHJdrq+NwsEq2Pz/XuXNin4DeROm1epvX++UmyucGiweHr0z6Za+hRdgfKUcURIZdWBMzxLKjlYB6xZ6N9b2uxe70TqYS2uu9wwaFJXs43V9beAI35yORguMAmDhiGMcNJQy4JEQ855Afb+U4l0nM69juvBWWi7P/t57JZvjcu1035Xuu54jk2j1xJ2gc2XXPGCxJRhre96qlA1M0XvTPif2rCNpDsu9vlwZU4kIol4PAOyDIDqZJ1eDjGt/oNt5p+G0yqggzKacW+vtSlaQAkwh6h6x8I9/xsfihZox1MZw4NECAGsfHdsba9HrOjfBOpWmrmNptjYbLia8ffWmZYcQhKuCWCzX5MzVgZWF3b293puoQrjjUcNtiIYE7Na75QF3O+2gu5SAJQerJdIHXTxv5fdJguvdhHMoWA5RlZjV/gXLO77r8Nmv+/FWZfMwDQrBdHZX39hWoKlWUW4tdL0KGQBKKpiD0rWUnXYhdGuBFqXU90QsOtdXZCscUTWGqsSOykZbB9ZCUXf/Bc0KkQijxRG0Fsb2w0NpTgiAhhjS3vSPF9I3cU0BuFCA3YBtjnqurktYaP9en2eC0KONDJJGRCmi7LSlKsX67Q92iJNg99UCnisOXxUM94zze4T5OZkn1E7jl3g8ftl+5qmQSgvVOZKvQ/DB0IJrK3B9P1xrPcl+WHCzOzfKlmr1Npfz64IsW76tzVsUyGBsE2alNtTghefmP5twmnlDXlEuBsd3pmcJBOcnq4GAJGBaO47252+erej56jnAQzskBlk373wljtVi5+r5CgBsbNADZxxixYf7OwQS7MPSwAFFFH1WQWCkBghYaljpb6Trn0Qa6hFar1MMOFMqt0LPnRBmCjhCBfc0JUz22LnVDemzXFsk6wattkmlU0i+fj2c1vd8Us/G1o5QU15e0+M1Oapg6sbw8l5JpdsTSiyq41Y2g4qSchsrgJY3Oh5H/P/svU2sLUuWHvStiMy9zzn33feqqqt/St2WYWAxg0mLRgKJRkjGbix65hGijRgy8ARwI1lYMkZiiEcWJWRoC4FASBY9QJiSpR5acreFEAIEqLHpLlXR7qp67917zzk7MyMWg/UTKyJz73vr5z6761ZI9+6zc2dmREZGrP/1rcfHMyx/y6wLiRjLKSOTROqdUoGhMmRiXO4XbHNCPct8398veDgvmFPT4N5XkwCBD9Bn86xw4gZe6GE/2dBuGXd3q6POmuQEyKI4TUWckacJtSSsr0+eq5EvgPsFYKYMacwNbZgYoAVg9S1w0qJWEwAzpZhES9wYzcyguSrsx4acK866KC2qblsBsQWo9uH9w7PHARwSXzne+2D6aBkeJGoJ1+wOBSZjz+2HXEyDm4FqBmhi1JNUFH2aBILj/CkhXQrO31txIkI5nbF8sh/S1TYym35YvYnKfUmNAcmJ7CjUptU9PFzwpftn3E8rXp6e8VxmfPp8j60mPK+TE0RjKrEAXQuaEEGAcwImoG6k77kf4+4xoxZkfqeizv3U3IK2ziwznbP9xn0UXjjfk2oLIT3rvOhCcIBY09RJRkdF83GCJC3hyAkvpwt+9vy5VPtURvPZdo+lThLFl1cA6tyvCU/b7BpRqUmqwaIxm0rNd8lVhEU+q8kSQtzdVMOaC1QIZFhsCcia+Llt2XH9HAGdpZSE+0c3aqHPaM70lLAr9GagnzGizWiHaTEWVQfAky5NMzIfn8HupKlizs20VWrCq8c7qUz6rBh04eXRuYKniq1klKlgBtwPM5GM43mbsE1NU3w4L3iYV4/me9/tC6jU+Y+k3S4LPW+eeFkhJVyvZczHFm2OBFHFiYDtXGSRkqTpy+bnJoUC7g/wV8qQMgSAh5/yJJnrsaiY28wVZsOg31MWnLJEEhEjC5zBrPkzQfuw/vzTNyTaOUfUOyzAkYG0+jWK1xUOjdSd9TqrtdL5hxiNgCmzPn+XMV1Y6r9kwvLxjO2OxG/jDLh/rH2H11vHrIz4Vzgop5kn+4v0GcBY1wlvsuR0LFXMQG8uJ4mc0tyGKAVH7c9rt5g2nSV60arHepQax47hpjRSt4I9BxiYXwPza9PKgO2epEDg3JiIywgDk7H57IROy7EB/KXGVxohgjiLydCSOU9pw1qzErCKTBUzFZyTMJbCCU+oSJiBOuHldMGLLDk5KydsNeP1dpbcpW3G0zp7xD4DusZb0vSyZTyuJwDNsW/aN6WmTdSakBQJgUhKaYuPJKNyVsVdhDPTUlJG08oB99WMqOnGSHigD0cEfOc31ZZJNNzsWgYaY1WmNM+b7/16l1qACZpg8/R0wvNl9ug7y9VjJlw20bpFiC4454L7adXX/H6ZDeMD9dk8nFbPV1lXaFJbs0MdOcoM/M9aIsZpKgBU5b1LWJ5mlDxJTZM3GtprmeEKDeFmmipQItKh/KtnRWw+VeQ7CQe1SpumyhuigNmALeGTESJSyCgZWjE4o2F1eOFR0zlab7bL7byosRHE9MCySau6IVqSJ3ebQcomp5Y0GpI5kwY/zK8YL39vkdrsDNQp4fGnMy5fogbtEUOcY8SZfl5d0kGjI7l9+6z6oEaMo/ZnN6xyYF0zHnHGEzFe54pSEtZl6qbPAgQsB6PLkzCJPbHkqMQCfc78ZH6MsTqop2kVpoVU4O57FS++tXhuxvKlCcsnGZuuMwrPRfFdm3apa9NeWefLGvKa2Bik5nDxLKXGUxK/zDlt2FLGJWXMqtHMVPBJfkJWLjnTGZe64bGe8JAW/Mzpc8xUkFFRkPDNy5fx6faAbz+9xB/wS+l3lqCCMovG8+bpjG3NuCwTvod7nKbiEDlmEhLHv0xiXcm1xkSCn5aI8RnucXlOLkwkBZtNCupJxFhL9rwdeXcJnMUJ7wwuaO+xXEP0yxgDqjqRFPZHShUTtWtqYDKmKd/NG/K5So6RBgGsRYJUPn9zh23LWF+dQEvCatt+qqA7KYGdJwmYON1vuJs3PMwLPp6fPafp/bYP1Ix2WSf32RRVpwG449uc3kfNwP06+2tJqIZzZYT5yAyla99LGNjhEMnWNWq24pg53ZyNNSTOHSdNuQkHjcBFBnDUYglkgc2wsVJ7HjM9oEHWm0a1r2Da4Dys/DEVZTYlmGZMAtfQXBu3Y9XZtPHAF8fniIyiezAfzvHv47mmDpBpi/vLPA8jmMgAZbxmnk39XLsmyWj3tXm1yYxDeZumVgHamiS/S/70jodPDAptkBF6TXg/Fn8HJkTo+tvUuZ+HzquqZVmZT02EByx4yAse0oKMipk2VCSc04b7tOCUC+YsOF+rmpkAccxbfR4iKDQNMOXs5qneXNzGIlqn/k6yh+bTJu+xJJ1D2edMHBjHXktNYR+uhbt5iE53x4fTv6P/Mj6TJYsmYsm0MIE49Gd7nYLGBTRtrJ5Tnyhq/keGRLkR8EjAsjUSeUoS0fe+tZsf13aT2Xz26YMQQENkVoIAqq5+SiRKk0psgWw14XKZwCblMFA3vc+aNJlT+hHTGQBmxVmTvnYgfDHDWAkvq4nP6hH0ES11F9FiYZCWQ+R+KLOGWKAAy8rjoF04SrMxlaQROskixoBaoFpMCFlywZEkZLhyC5eNG3xTjSYEU6Rn/VwgddtXtCgnknt6QbhRwmYN/wZ6YqnN+btpczEE2ol7OHZ0n4QOph9K4ACohKgRUJY7YYEcQWsxxy1peFhMcrU15WPQddIjhB88mGovsSwDFZaywYmA1Bi1NeNhZEzOjg9zan4e+LnYAZ9GszBBfq8anvx6O+Pz7R4ANCpNzGiFEz4rErueqGJOGx7ogpkK7mjFy/yErA9bQPhkegQAvJ6f8Hya8Wo949XzWZznuSARcHdagdOKyzrh8jwjZUVrYPIwad8HtpZJaucUdd6fJuDl3QVTqrgokshWEy7PWsv6DCkvATiqgDGcTMLsPjpfcErFQ95N07BmDMP+BkICKBQlBEDWIIc5ydhkrtjvaecCghZQNwn1Lgoe+uJOtLr00ZMHTjATntcJz08nCeR4PYMK4YITLgDevLjHdx4WvHy44J/80nfeu9/mg6xnY8B0JmF7Fi9iItfBdSZNhBK4nvRZEUJDqTMRibROQfyHEO4EscEHKZFUC7BggpizEkEDx7DJW62rYdM5LK6dfyMB9Oi4aTn6nCMEh8+RQcToZzcvem9Ogj6c1ur1g8bhdpL329ZvZCqR0dBw36jBhWtE24Vru3FuYtKtMxqTqEknRn+/CglkJs/4Xg6I+9ii8twOesfv1Eam3Gs25F+6MehxgmgAlhu2bRlP24w320nXZsWcMlbOHhzgfhzVbuTfhgx2pmRNfD3Vw6SJWHKTVQOYsmpx/i4C8x4ekqiF/tu5pSashd1UBjQrgDOF0pt9Wh/iozENnoj1GeDXW2+jtSEyHrbvw0u2fW2JmTG0m8N9okxhgQizgpJa2ezKwDplsEeewM3YvCZs64TLtuG5zJh21SF/dO2DTep0OJU1HlRJlMQ/YhoE0F5sUZNZWRVJ9ZI85Jm2BvHeYaEBLiF2FrUUkg9Vw6kzSdQZyUKoqJ5oVhO5A96w0iJemr3ImBMUAwA8HNk0AiWMOx+O/hbLBVtyY7yn5V+0XUWAZsmz+ans98CEHZ14a3MCnYOSgeUTwud5Qn4GPvrWBtqqm9duktLASDj8bb/ZcOxdHyV8mpbpCZHU/hmjAYBSCMVyQKxcxDoQJmVSksHPXVRai05ToEdzZMfggBiwEnN+4vNYRvlE4FPrX7RCNG0laiM64cSQBFCGYNgNtkmnfzy8d1da5V1TZazfOeMyn/D/rBnfuvsY51kSBV+eLrg8TLjPK15Mosk8AEDaUDkh04qKhGeeUSrhmU9YOeOz7QGvyxkVhIdpUT9HSJYF8LRKiYHTROCzmJHOU5H8lySF38qW/JqkwTymkT49SfrDG0VX95o3lcRSwcBF32lkVG2CWrDCeZaS1Ocsftb7WQiLMZq1ZDcxrlXgd0wLM2GSAEwZapLLu1Bki1IDNJgg7POIGWfX5FRBTHhxknfxvE74jB4EKHjTRHGNsnx6POP/Wn96/4w/4vZB+my8cJVLs43RRO0hNrfHGuE1JmMEVNEC0jJI3taloQhQMOusQpCqEXU1a3j2utW56ey7HP5WNZyGCBdiZzDtAcI9TNqOjMYouRO10I9T76E5p4jXAY0ayj/T+JImBDqK8aDRAAZLQ5gUv4kik7shGDmjMce1vdf9FOy1HBwfJ/sEujVRLTfDzIMVrWCamS7HJWTrqiMgcrzzEI7X6u2ONBwTisUsO9zjqA3HI0O6DcbaxhSFKNNx8jNQV0KZZzwVwnrKWM9CcN+cT6ggnNMqTm1zFOtYTJspnPBYhdk81hMuVbbwTBU1FbyYFmc4lQlryuCaRCjUqKvJwpqVWDMDUD9MDsymVmFEXIT4FxM+Afe7uo+RD9aJTUtujGFKFXMW7c3WSlYBryZC4hbezGhOf4tcNC2n1CQmOn9B4X35fdnLHkWGFFHh7fukWHCZGE+nDVtKKJQb1BaLGbQszfT3k/b9tdtmtC1wWLNbDwvKmM5Wskhdy4xlmVCXDDwpZP7WIGN4gqKjGXQ4OqJhki4YDi/CJl1mcyhDimBdAC7Z806KluK12xV3SDc1XiLrGrBo61g/lGl5XpE66rtmxE8XYh/YoH+blGdBDXYfVc/JGHHQ7pyxGK0lSJg3wcOMCXJ92uQeEhAwUN6BQYgmIt8liREBsTlEWJkQWAODC4yuM+NlfUbTaILwsa0ZvCXc/YMT7v6w9VVPwPqRhK1vWsyq832RwNjnUANI3r2F3AfJYMek9FBQdJyJm89Gr1k+mfD0lYztgbC90AJwIXIMypjsnrZ2BaGlRcSRvkv/e+yT0TFutnWRe1ik53XCP3z6CPfTqnk1C+Yk5rPHesJjlZDlwhJUsHJGUYy0jTM+Xe7x+XqHS5nw6nIG0MKbV02evWwZ6zphI3and/SNma9SkkAbwU6ZUam6xu+aRFb0b+wbF0JdY9je25sxosoScowJ4mPT380Xe5pKh1ZguTF2TmwxGGg0HY7XmM8okUW0AvVpAplVRsFvOb/b8/yg7YNFfd6VT+6YjNIJM5koppWgtUoyVbqkVo8GZnKRG1ViMRFt5GZ764MJDeHXpMWoWToBIWADaEsoCeCZsM2CCbVBpBQrdytj1tyDLXUOSQ8GYGrMwkBH3YcU+k/GCZSamLZizIbYmbNF7bnNmRUvrirStTLVztEdNAcneppjZM8OItDWmIg/xnidflotIEGy1TwlR1rgdgPVsJzhBCLdCQWK0NCeE8qA1VR2Sfj4dxlf/t8+R72bsb2YsLzMeP3zGdsDUO5I6xxV9xWQlh8es8yrcd4fcA8St7XERFheJLz5GqGeWWrVhDlEYlj5b88nQpt3RuN3zVSGfcCArVHs34dBOxGJxL6WjFcXyZn5aL4AAD7KFxRKjuy8svh1YlvqhFWreH76fI/LNuH1kzCbed666do2wU2z10iAh/iaSdyiRWPejZjVGgxOZEyexBnM6ACwLBPQmd714y2Mx3wvZgaLaQs5idt8Vkwz04wEDbsIIoNeFwFHqzLozTQk/c3qXlm/m5bflrmoIEqgJWF66z32gAAAIABJREFUk5AuYonhCSh3/AOvw3dtH2SAQIv4aRI5IFK/OQWLviA3YQFt45k0X00il01sCM9pLHmMZvLoCSW0mBUHiBE000YSAsk1YaET1lw9qfMoadDxo7h1GENAd6aSYYy+2kzidWK815TaJSqVB1/ArplZKzUCZbAsTtyNcVObm+cvZeQ1oc7U5iQOdWBCUrJB8ysiiKQRZMj7YaWs7V7s92xwMSaha7j7JeP8+yfMr4D776xITyuQEuhOYF3KWcr0slVbVfQGQiNeDjvCYh5teF/U3oW9uytzzSCMCp/8xO5iaoJCICA36KELPyl0bdcZH7BzbG2EqbMSCLVQQ0BnyUspJeGSKz49CcLCnAoKRHsxprJxUkwvEZYMiPPVelawzkb4q+7LOJcpVw1WaKYp94UQddJ/tweCisYsQQ5Ay5Gy6LOjwIOxyudR82CAINU7I8iST28BCqdUulSGBMGQMwQA6RThfqItJfSM2q4BlAFVYFOJNivzdSZpwkqBFNl7j7yAgQ9Vs2lElXTjSwhvUrw0chA+y6lxP41FVAUThq2FVMgrI+40mhCqSwmoGV5tr5xVKr+rwMwd8GN6SrIn3ggadb1nlLlKhb25wByVALw8rdudGQ02Z2QcLM/eERAb44HzvImyaA9HUB8UB7H44PlDMms9cSDqbaMSJfFdaFh4PQGPP0sKEhm6NPoQNR29txdpG+vQWDDEmhoRjYTY/CzKZMz85ZpVIdCbCV/9XwpefPMJ+btvQG+eQCmBXsxgArZ7qTPCpyrwKLmZz0a4mmrOYdUEOwFh1LbiPGpYMxOJxjUGD5n2YVpbSAod7wWTD9qrbOjP9s4I7R1ZjlSYsuaTAxIRyibaNSUS/lkBLlIi+x/mgtezaCeXWWraPJcJVsWTlckwk5d1NigXwxqznDbmJNBONSFpqoLgjckDc20ZI5EZmODQjpMZJIRRbrrH7P2jIHWWB2rqkwkTJNn+R5GhJslHKBrzt3h5adWA7/K2Yy52zpxKByljpbUrJ9TUwqSTRvAlEo1mrRnPAFLNakYTDZuJXXhOq8yLJLXvHuFH2j7MAIFJd82WwMy6QWXzV/XnGGiio8WaryOUC2h+iWaaGZlMVwwrSNieqGi+D3sPA0GAJpmJyY5Ai1zMlQVQMUGy0AEhXK7VHDx3NIlFSTr2C2XAQdq/2kYGlgBmxfeqFEAuW0E31xyGXBxm9rLJUr9DykOnMvR1YxjxwCEEj80z64ONTIbQoWRbfRkPxjgTtocZ6XEGLSvqRydcvjzj8nFCuWOUk2pTqZnPiJoU7BNKnmIbxhwYjj3UbvxNWBECIYe3O8Ly8YTtbmD44ZNqMOtGJsNAusg8b3dACevQ5IvY/1GjSmCtvdLWbxBAGJ4r8tlyj61mgfmphqBMAwBncnRlfwxu2goAUESe1SZCVzCVBTTndk7TkID2OxEDufoaILLE0XC9r5fWb60JpVasNSGVLP6WyJVtOqjlxMVWQWLhRIguhQQaxOi7t7XUVUetQWIMfWnEHTG1V2lCW8ZuPn/S3q3dZDanlwuYge15Fjv8RgLlzyKBlMR42hKSVt9kJvBzBi1S6S5ZQbSNOgkPgJu/DACxK7sLNCc6sdeCt1Bb83k4svPEKFmO59cttBpQB3rOoi3cq4/CkkONcNrfDKEi7rynnjFGAhcXHB18t0uKqTXtPlYdtDhwpZ5sCNXU5ztEjYUJYCJUFSXrBkxMUm3zKPzfJcwwLhaHJysIqQKDONPwubEbmIRKEC3I5iw+s2kgE+PzP57x/JUzPvndhLtvZbz64w/43j+VsD0wtp/aBCD1JNIpJe78Bl2OVDLokwQ2v1b0I1pgRTxmBCHp/DI8Wu/x5wjPPzUpMjiCD6wRf1JTSdIQfTA0ghJ48e2K0+uC11+b8PTT5AxYZJYApRO0pCjPSD6U1Ukh9w+AyJWvx8czCMDrx7tuPnKueHGWhETLJbmsM7atIQbEOZTPhqJsEaIpMeZZTFOW9Hyaivs3LcnRhUhdE1W5a54q8tQjQ+fgK5E+CHVqfhcAOk7RxLapYMoFs6EAGBCmhyxXDxYA4OCj1moW89gUtJUoSc16vDBhM0atb6FyQiKrY5O91IA1QVkQ37OkaiitUgtLuee3pd/9cI0/0ACBeS660AStiYuoz1KkjGB1aYpLwRDHstnXoZvNiGUvpEszicHMPHqqACnyzgS002ysRfBOqIRaVYMwM8MCKQFtBNV8F0pPd+aZeENufhZ2UfZAwjnUlOxfkPyAZuc3rS03s1Rv1qDGcEwLzAqNz8KMU0QdDl1dHVv3nMLUu/pBw3Ut0x+ucXRmLz+Xsb2QgV4+yZiezlg+JqwvxfxJp4I0ccBEO/hntyKo3417DaAbfz/YNo72WScoWkDDjesEhLAuPfDk6NVW7iq+jt2/VeDVfhz9mxg5i+bt6AnVQn61bICiU0xzwWUwNRp0jH23AAuZu379eCpC0CaiacvKgxTAc+UcYkoz+etGwJTaXAbHjvmHnPH5ONrE2DqRbP7kUD1tG8h3K5Vdw/t23LR30Cqs6qldd0S8m1aUOl8R0DQbF/DUZM25Bdq8r8b4QAMEXt5LPfRyt4CZ8NnrO6xvTqDnjPl7yhlSagmXVpDMzSnytopuMoNcMelxtJ0zt2ipFiCg2ouWDUBirxbaREYG5goUklo3pDVqgi2eCnD6LHIzYLtn1DtGPVXwnTmUIANJYiKTQmB9MTYhFIFpIXzaschcEL5Hk1Qodx1x1gA0k4Qnjob76Uaud1X8DVkQudNCHhJNJRDVOAb0/dxc19TGZo78lItHjKXEjRBVwgZ5d8tPA8tXCJefSvjOesb2ooJfbgpyGJgHjBACSU1eQJO4p1xgUDeu1GwaGRLmwn1TeVC2oqmLpQ7QDpCU2u/WCcXvaAEqr38+g4pE09UTXFDy6Rr7Nto+WosmxnTecHe/4OXdBU/LjDdPZ3BVX4uZo0NE5JYYl9MJlCumk4DOGvw/VJjKE5A1YZJ1bpfLLMnVhk5BwDLNoNQqdDKLj2izype19U1afiAthEkZrT2mWcwvD7X5AGeB/Z/m4rhsQJMTfJuwRIjlVJFqAiyUWRGxjeFYZdeipk9jIpacHf0bo8/m5BpXahFqYcEbk9lqwsaCF7fV5KH7yFLOo866386M+lBu75kfQfsgNZs7TXQy9XbZMsqaUS8J+UKdlFfuRM30SKrMQYpUKl2FQie1i9uG7pSExC1aysxMynBorvJ7HamoEEOGEBxWycsJt93iAo8IkoskP4cTeXGl9q/dI5oA7fBN+Wr88cCn0Jzr3I4d3CfCvIzXi5YpEiarRF4JSCt75J/PX7wWIl13TMcY4dA6JqiSeEqKi0eMQgaFkoRwJQa/UIr0CVCJMQXmcjhdbEm5DUHAwl4BYWylkLwnZ+SQwA17Hgu+CMJEVyMJugzje2R4WL4LPVe0Gs7A+hFcy65DvoUn1YZ59uENkWlIwnTPU8HDLMjqz8uMgtSCGQoBW0Pe4KwIFSlhU+ZvgS6w+cvkWoppJrVIwIczLgJ4Ez/hRnCBgauetyTNAZNnSs9iDk8LeU5cCuZaTsBSkpiYXuj0J0Y+aRi7hUUjCFAQ7YmYAE3ONEgbG78xGismZ74WYy5WZqHqs0qCp2kztWk2YD+nsgibxnAKk4ZFZ0d0tnFamLflX3GCBLWc6s21/MM2xgfKbGxxmA31/rRivc94roTl44y0AfmpFTVDEm2m3lUxCd2V5nhkoEwz6oWkcBoGP44S+TpLVUZMIiXJQIQQOnyOa1BwJsZP+igTix9IAxpMK6KNUKfU8log0mmdWTbXm6nXOsgIMoTpVQicDEMkPmLdrRDT3Dh5nnfRFg6TaEzj2Q3ihvrn0r7aiThkIKYJljNrcTASP5qdm3ReM8BzCHkOkWTev/VjBJvRW6/YwmrleazML1fyMFvzgTVT2XXzR0N9MGd0xUZJlAIFtdq2hFpyX3ZBgyysiR9PQ57dlxMZbnsuinM8TidxQxmI0bKqOTGFk22tqDTDcU0rs+EESVC0dccAPWU801mz4hmlStVJIhapuhDoIr5Py1Ozom6cgXrJQcMnGCp4mRmvNuoiBOuaVcijwFhl/mrKzsTAkNy456R1puS+eZHPpLBJNof5Apw/lb3GSZJjObd1cIEwsvm0dcEHldjTJZwx6vc1Z0xJmMycC05lwyVPzZkf2lZzh5QQgwpOvDnziRFnlQnbEBBg+TdSa0iSRSctslgKoUwBx3ETn/Qf9UZEfx/AK4hoszHzLxLRVwD8NwD+CQB/H8CfZebvEREB+KsAfgXAI4A/x8x/T+/zawD+ot72rzDzb9zq9yaziS9xoor7eUW5E5PJ5eWEuhBoS7IwzUJ1YtCLDdNc8OLhAkNWrUx4A6DmCcRJHPiqZQTTudSpORekWVRxySDvCyBRruLc3tpGsxrv9a425zZBmN5UwUUTPqPTX/cerYTJAgr0unpmYSLqzCd7Rrs9E7AJ81Ay0yLTgFDl0TphkJrmRse6MEy4yUQexCQ/O89ubP+oZTOTjhVSz51W9LAsSUKpObMgNFuAxDgOfwmxT5P0ldGramHwIZHZGNNMU0vUTEG7APZMp1pgiWs3qeXb6Lm1JJHQzW7jN4MLCPI6yTWDjqHEMfizBY0m/CbaiDKcYc5rRB23qQn8zDRNu32saooK5IvcMz/J8yyJ8ag1Yc5TwWLjqwS6SNJvmygN47boRWLQkgKorTKilTQ/yzJK0RiN5bWppsU5gbewZleSBMYCpAt1VgAPE3dmw3j4gw2cgeVLM+pMyEneZ0VCpQyeYqRhnEx0GqwlU5ZKyEm+z7XgkiZsCsx4BH45+lss76ZmUjRtYVIW1Se5SdOOOVmb1JR3Om0iTFVh1syKUq/z+L4Vjy9Is/mXmPkPw/dfB/C3mfk/JqJf1+9/AcCfBvAn9N8vAfhrAH5JmdNfAvCLkFXxO0T0m8z8vWsd3mQ2P/ficwDAi2mReul5cxvq8ngCp4SyEFhRhwkQ7n/J2CBSQ3TsURKCVyfRFrgCSU1VHd7ZmkSROBoUo0liykw4sWajKzElOHqylAbILbotaFGuvVQSx18IAqACONp14kacNHLO/m4Pjn0odCDobCHMCQLsF0xYBHj4Nyw0FsrEOIxZ+3QkBhrGgebk9/VqPq+5qhbGIaIshrvynhDrGGPEWIx4sveaiFFDkIg5glOF159v2lHbSGYijOYVInb4NDvHy5JHLW83z6rBKrFmO4W4zd+RNkNw31us7hnnlc0vpCbizqwapoxCP5w4mNzk3rUr5APgkvH46gxKjKes/q/nyWGMfMw+Ge1x+mdvC0TwAgGC1plx318Q6gxqyDRcm1seQn1T6DP1Q9nuCU9fzaLV3KtFQ6P8RC2VCMmy5U4zjpNvmq/Bw1hodanNn2M05FZos5nPYm2cjVrip/lkzD/TUCla4IEhipTair/VLWn0LbXUjB9fuJpfBfDL+vdvAPgtCLP5VQB/g8WM8HeI6EtE9DU99xvM/F0AIKJvAPhTAP7rax3cZDb/9MffRIKol4mqo8z+v9OX8bTMWC4TVjqhbIT8OiOtIr3VmgVO/T4j51Z3Ik8VfCrglVDnLDU+zDRm9E2cKC2XJwmOlPyon+bANIypLOGYIHbwx/JmarArhZwYIUicbu8/CVq0mQvAQFojkSdJLj3p5pzRb+SgDZiG430YY5jqrt6LL1uOQQDCTHlTOzvFcaCFbgNNYrdACrtFcAYbs0lz6SLJgL2WAWBH+O2+RhAiKoMdB6owbM4wHDuAUCxC7mDvdM879GlEp9Yk5rUlA6uqEZHxxvllOcAQ4aEz0QL9sdjiOrDHVSZlSqfB2fgwKxyJPN7H/EkEwJJueWIvZe0ID0VTAz7P4FeWIKnzCeXxgeM6X60HfSYGkmiZVAFaVPLWMOvOasTyLHwS9ZxOUpmyPk0wnxUQtDJV2zrmpl+WGVhfJCBBIg1Nc05NgAMDlbMzHxuDPKimKxBc+NnWDEoVa548sTJC13SvjSSSrguhVqj20iWkyvoy89k1Qm5r8HmbsG0JZcuAmjIB23douXrvsX0B0WgM4H8imaD/lJm/DuBnmflb+vu3Afys/v3zAH4vXPv7euza8avtJrOJFeksokOcaamHs4BuKpBoLDOLz4V6mIpWrMyF9047MEnK/ynR4mTRWnqq+iMoWwY6fEf6flBndVcNM/Z5ZEKiZj7hUcrVS8RUJGazKFXLbXomZuHMIChT1JDhWCLXRGJCmxsbWiCqTZsJx80nUVkoukmIJoERWvJlbpLkrdYtc2oQP6Pf5vhiNScCQrzCe+laYNIRJsifVc/huBbe1qwvnQcDSSXtx30q9r0bz9B/Ww79nNs/Wx+3mjGd2gJpKJixunFQmAPixlTDfLA9Y+yCBGZm1y/LCpVLxo06MI/4oMbLfZvKfri2ZCyfic26EFMTbE3v9trQ9+6mGvDCEqXoAsvAJBKxWhGyB0R4sifRLvemlY/edzyGR3fCTw1mMyva9955wQ/VvkpEvx2+f12ZSWz/AjN/k4h+BsA3iOj/iD8yM9O7xJh/n+0ms3ldJCRyVRX08+0en613+PRy7yGV0PIB9UUBJvGPJEVfFrjyEBkT7PouBekjeaioEl1JOoSvfk7qCwhht0CThMvW6l4wAzQxmKpE2Ohesqx8qTVexXlqvhVNIOVZzika7mi+F1I7tjRZcPXETeIJZjLXxpJUryTA4UJii85xABrb38OIeESVVsP0VggUng0QiZVV0/NQ5dTmLOLDee6R+0oihd1LktYMxqQ9Q7uW7Hrjw4MW5P43I6gHjdWU2fVuRKvLcQlitjEaDb7gSTtTvK8WMBAYzugL0/swNcbKw3GLTCKFwSGGhPCHk00zIs2GJMBrN5m2LAmlKjCZeSYyHvgrbeY7z/WIz6zzEsKsHR7M/DKu4ZqAx42ARsKvzIIzydxMOoVV89BqmEduY+PUAk+aP5BbkIiuf59LDpGf1n3qhTBjNEDI29lpNlB/D2PZAswMtXMNKTo203o8+Ck11GiR26hp5yFpmFjmcsfcf9SNf2ifzR8y8y/e7IL5m/r5B0T0NwH8swD+PyL6GjN/S81kf6CnfxPAHwuX/4Ie+yaa2c2O/9atfm/KZ4Y4e6kTnuoJb7YTHrcTLgpbzpbAyZCFNRfkqWKaCibTbPwBhx0cJMidxD422yQa4ZSz9dFQa0HxE0JwpwpMkgPARqyNGHsCJe/6Ymcag0ah4zfp1COjXAKnING18SZljocJjMFmTXE+umdHx8DiWFwDjBqAEjEKfdu/1i86zTNuynYM/bjesaXQR983fE3Qrfdt7ZpsdUvm2mkivP9+cMmtAx1/M8KcjofB4bnIiLRjBUJ9gXJiNOsdTkW3P7g/6Yp25srrkQZ11ExYGZ/NtZKDwcX7jYTRGI2t7fDp6yK1NXVcS6oJQpYoWmsUJpuAVDX4yNDdSxX0g1IV1kf/mT9GPqXIY1XC3gUY+Pj3z03GeN6jJY3RxvSD/HtbI6IXRPTS/gbwJwH8rwB+E8Cv6Wm/BuC/179/E8C/QdL+OQCfqbntbwH4k0T0ZSL6st7nb93q+6Zm863nT1CZ8Lid8FwmPK4nPK0znpZZOL8TWgK2JMrB/YZpEj/NWUMIly03LESV+kzKczuxhpVWxc3iiQWbLTPyWeuOnzYhXLooJDYeSAlaA0VzOtAIpiDqmnSkfYVMZ8c/i+Njak5a3bxMAJ/Zz3GJx2BtIGOv9xCGdgqh2ixhlLXmjtDbOMfwX0/oA9w/Y4zGCInkMNXGZAiiWeaKlBlZQ2lTGMMxKi9rQiXtGE+8fpQQHQetJJdCYTVCBv+O9Z3Unu+ArQAq9SZZmxvtVfoZEyNVe7wqoKhZiLOYUSXAwyR1wSdzrD6dQveLGJHWde2aJTXtwoUfpgaxZGtLx04jQ4mMRf+udj8NIvDIOmrX+wWmuYCAYudQH9EZ5sk0JlaBiYPwZEEsUvad/RoBgFWGGO13DNHSuD9mPDBdCKhJwuonagnYrL6ozow2+CcZEqVpa0qFEYaug07YaS+7D1IBiDQJOwpNdu6BhuP30Zyc87Thxbzgsk24rBMuecLTRZNmC9BFrbzn9p4DBH4WwN9UDW0C8F8x8/9IRH8XwH9LRP8WgH8A4M/q+f8DJOz5/4aEPv+bAMDM3yWi/xDA39Xz/rIFC1xrN5nN4zajcsKr9YznbcLzOuGyzljX3Ns1ddFAs+1zEjPaKReROlLqciJc6mI0yO5AOKzGCinxNLPZlIPKS7Jb7a4phFgStZrpJgkBqiJD6m0IojCCNtCPb1ey2kwYthNUYk1RWiVCPbfnICgRt9sq0xICTvsN4H4KChJn29VChPsN6fMJdFFmI87YzvE/tCPNxu8B7KKBbGosKbA59sN1ynBqDFXT5zbeQR0MQ3tOcPP9uKce4dQrWko7hwHSgAG7tFrouQof5uviNt2w214153FL+EviM9mdY91fGZ79buezdurF22AMsL8BMdy8Q0Q7zdo0KQAtR4zQAhw0Fy6OsatCS3AznZWYiMmq4seJc6TjLBJVWu2eMzzniXVfRPOt9822buK8UHu3und25Q4AD72P9zWhCYgCi82lHI8Ra7FNVKW0NhjzVKSyryKkdykI77m972g0Zv5dAP/MwfHvAPiXD44zgH/7yr3+OoC//q5932Q2n5yesdbcgeABQkzyVFETS1y/RXythJIznvKM0ynhTgs42QueTxtWQJFrNY5f82N4ViejQdIQJNO5ZqxMWtBJE8UUyC+liskUlBsbO8bVVyaF6NBQbKODt94vkxCmWEsGsjENLs60DTuhPmdEoIPoR7Gi9oKlGTZzXGSDgdOJgmlFmUFWDFHPdROZazN7beVW6yXFntGMTMsk0Zj0OebUxPPJGIA9ngrVKVfXNDlc45KuEVPLO9J3xTZ1JjnHuQuEPHJlTuzgrjA0AuUonhflk6GM3W5hY9DOd+CfPc1uDCQcEF+S9L8zUw3rb6cZAeov0uAHexZjCHZO9OnE96D9uVk4mmWrMgXVaJhY9pM6dtr9w0bR+eAsz1VPYo3whOH4LEEwIJCHmjvDObIlMu18exS+q/7o648IqmG3t9DWMzlsThnSMcwEZ9FqiURIZia8mSo4Jc+TOprXn7R3b7ex0aZnbJzxh88vuuMpVUyzmIb4TsN0X0/IF0LJwDYJc6r3AiPh6LJqBrswJEmPIYCeBHXMc0s4tPDdAvCWwYmxAl0lxzm36nzWDDPJylRHrSYnUZk3EmgVcpMCXV9EbmohkTQDkWiFzYCY0IkK0EWh303CnAg8ia8IJLH7nndhhNz+I92wUTRjzZ+wKLPAEPJBOKZtwlYc6+DRwpBHzeaI0fjjBdt5f+2+k16jkoeJYxJtzyBTUpgH1TgYcHBXI7ykRMuo+tsiwyIfShYxFwiZMo9Yukeu4/Y74E5/ex/RfBbH4LOlTMSnQF9wnC5nRt2k6f0Nhis41CU6rGX9R+2bR6bV/T2E4ycLJNE1mghSXlxQGniWe1eQ4O5V0/TUfGhzlYA6C74gLBrtimBDkL6c4djj2jrSiXYBRhkOjeeZ5mt7xe/XT2QztbEXk4MJnKqJlyrPHH0e52lrWvvELQLNmPV7bkfm7h+HdpPZ/O7rr6Iy4dVyxvM6YSvZ7e9m6yfL+5gYtYhkFaVgI8ICB8Fgdc5jqsDWbAaemauSnxw3KVT6yJpPM6XqjCaaywAg6aLhVDVEW77bOR4CaZFxgeB4C9KkbFLspFc374BDQEGT6jzxVAklbwCKljpQImWROk6vUm1E6yTPHrWGqKWMfh8Anozm5X11cxHBGXQk8tZ6RgN/d7Yxwa1eiDHzXRTbQfNIw3fcPL1gq0yZ0ASC3e9oa+Woi8As/KQjWvG24TlT4GBKUoIXrvfH1LH7NebXMYLdra9+uBzlBiO8FoxwJDAoERzpu8spOZjnfHxhzPYOfT3H52EkY6pDn7ZVOwbHIhw2ba29IwK6fYqj9Udt/R09i39X89rex9ifN1bqHZvl6owmYkM8Yabmq+kEhvfbPkjU5//zWz8DQJIxzfZuNTGMeIk5DSinKpKRSu8pCaEibnDf81RAhbHNBfWk1SAVu4kWlVZNMtLaNQbAmSbG+W7FnAvuTytOoRa5tYiVxNCojqohxRDHpcOmlyQO0lhVFD2vA9CFZPtvMbwU1PKK5orpLEERtUhiKz9OkgS4CuZUnSABAIlRz9BKmdLFPEtQxZQFGigrTlTMoN5qQgkJapWlhj0DeLycsCJjXRLKIvY9M92ZCVJMd4xe42ibtUcVgDtqvRKr/lbU5xU385hTZQzJvh9pWE14gcAQGd1RQWXHp+wlOEGzf+GlGcPmcE0k8LGpdsSR0HU2sVbmwteCPVMKE2CXOkRN7bDVRItHc3aN/fhzh34NcigoYQ3luuXAMFhMtuNkmaAUzVum2RA8F6mrgmqmKnvOKr/7nSNjtUJ/tgY2vUdqgRWkt7Kw5i5AINxzl5NlQk3E24vzrOOMgtcYzGLaeezuUCYJ+6uyIj/r/jUUEjeHv2etg/m9Bwj8I2tvxUYDIJFmiZptnSu6muUqQdvK6jLMw4uUQknNr7AnJLrWTaSzZtLRYN4B2sJilvoUUEml1ISaKjiTS+OyHxlAdqnf7edELWxUT3ZpMjym3whojDEQPdMaLMTT8hC6ZDBjUlp+2XNyckKZtCIhE9IwQV3NdAQJDH0I5y6RtjKYkprt5N351A6M5uj6jvm8g2QXo+v6aw+CItC/w5bjcsBQnEgfdTpICW8dZGQo7ZPDPHRmNmVWJs3TMA6n0XwgiRMfE6l40TgWI/zQ/aDrzBjNjoqO96NwLN77qK/duOL5cg2rqZniuCKjj+PuNLchauxg2IDuGetgYEgdIzqYRzOhtSCkXljozg1yX9HZAAAgAElEQVS/Gs6fWTxs/8h+6ufDww2+AD7wQZrRUhJ8jG3R+g7aaKqQ0pDjQgYM+p4I7iOxSnwAUFLFZcpY0yTSX9JqZqquc1WCHZAFPL9GmZXVuvBxBi7hhZgmxhmChXSeRPL3uPuSsG0ZaWrVAFFa8hoQ+rdhaIgpSLQTkKJTJ/aQYyJ281Uye/iZBPAwwRNIaVX06VX9Oip5Lg8ytmkSB6WBEsZqhpdtwqL+qBqYDYCO+ZPWmxecMELR3UNZgC5TqjJGaia6rITBEt+KarJmdgR65hQDAkYtxqPqdDx2zdjiscZ05MUnFUiK+tYIJsmTvwt3NpP+YWtQ105H/Oz97gVoMQVXAIm02Bq0SBgEmobbDU3TEfOv0lrNabFINbHQBoapa8hhcwCPumxEO0xMRdteJhA5PpdPut/PEjU9QCDkyjj4q4eLNw0zRji6hKWWBVSoX7KlAZh2Z2PmpONJLKjoG0ldISXQVo3V102qSEhNCOKQ6O0vrY3Ngl+MfkR5gwGgJlQ1NXjBuUHb2YXtozEdyblJOOXUynAX+UfEPcJ8ZMI/ad93u8lscpaoLQ97MgKi0m4398MLiKqpaTcWDUb6O3RDUhNne9HHNsRR8uVBH11LFQagB/TSgkvxLpXR8QLq7qkbwoiZ+WgMOcA2n57URdgYUQnMzPMjoDZaBnhLqGtCgdSiFw1S6rWbU1NU/JasJs/WRtkYDkBKGJtxHRqKymDqzVw2n3EuKzFYoYncvBWI1Ghys/7H8RDQE5y3aiCyCGL4aruh/hqpjj/wKP0OXGWUuo+6Df+6R4v96e8jEjIYbrL02jnvSphsCwx0P/7u5jObx2s3H8c+9HHYeOwQ3TxEM6Px3WZe5GHuuDFaNOIvf+vv+oXMpHtrruy9qlXD1pQP1zWSSDiib/JYo2a7FzW4GreY2H8WqDOab99b+0DLQv/clwT1+XmT4IDndcKyyCU7uJgl+yawmhaVxV8zaS30qjborBAqO2ISF6wR86k6YsB53jQ4oLikP5qW4uc1dfTIKWphsZ0wzi08lmep6gmCVAWNEuKQVwImlC2DK1rhKiMgmb0UNZ/luNm66ZKAdcY2M96sCWlinM6rF6EyFFxJpEwNokefq26SEGroCCkz5vtV/VQS7VU28VWVyqhF6t4I6KHMiZdhhgRbmJZVtPzwWHkxUqjm/O0j1SJqdAxUGK9rnwZB1Chdp5FE4q7ajOfPmAARB2laWRQ4BmbVtIigPRyFxbNqVZpfZcCtrhErVl8lkssTgFnOYUIr8hfvGRiNazHj2o2ELjJE908daFF6G/eFWmZ1QDmSXJjAiCNgptkLE4NnoEz7+TKfEM0VPFcPLCENrTZ/b2M2JPWWuMEzWRDKaKJ1JILYYTTLjXM0mCT7PJ62HuO0W5DAnAsepkUEvxfApUxgAM/TjKIVTNNccTofYtH/SNsHaUb7qbs3AIClTthqwmeXO7yis5tVOofyCKMSmmkgApInprC0k4bQCDKhJXZaFFpuZWOtKJLU2SlSgY/ejdFY6xiODxRwuzf645xZmEwC0lz0HsMCVrW9VtEgLADBN/AgGTFYHcZSkTFtACkj4JRRNsZKDEoV0yTJsdUYeW0MwEsDL4L1xuciTCRXR3G4rBOqMphak843oVLdaSMAkEjzo2pSlIbGZHopcX+tMcCOntLe5+YRghiXTJNbOzDOKAEPDhIPZ/br0d/1SJs50HKEITTafSTFEsNxyJI5xYOGJYILNJKJuwgzDu//6rgo/DAypXi9rVfFDtw9m3VoKAF2reEA1jCHxmjidaFfN8/Zh5m9VbunLAJLR8xTYzS2foDkwoRoHgwUC/N5O5HtTLHGSG7s9UYHetOhT6Guw0SMSUuQfjwzlpzx2XyHWhMWNfXlXHF3Wt9BM//BG+MDDRD48ukJlQnfW+6xWSy6VbYLdn4AmE4bCrFGojXQycqEtWY3AYlTW+5P6u/wejSA19igWcKc81Rwf14w54q7acNEtWk1V+whiSRDvQt1Doyo1iSAkKHOe8vjCMi8DIm4UcmVNTLFYdNt0WWVWCthWycpuvQsUWhSsIqaqQHhOgu91v6s6mJaCMySW7QtwhjWuXo5BTL494FR0lk2iyT+AbUkPC8zUqqYp+K4cqUkrMuE+iyFoRaSc3AWbcaYgc1lIt7lslh0GpnNB2YObQgAFoQRcdnML2Qt+pz8UfSeZCZWJ7KD9kIIPgnsaZVrWsDIh4zomxnMiXVWluUIEs1fYSY8wxwzuaTjDUa0awg8idGLJpiFMfQPj/5ZDpmRXp+gUXvhNjR+HtwgmpABX3cdM7fujclYUq3+7YRefZGVkkc+GgCsRa3aOycVNu2dR19gJ/AEYfHw8SNDC5N/DY4JwC5SbWxryfju5QUqE5622U3Up2nDadr074L7eb1ZW+cn7Xq7yWy+ND9Khc1ywnOZ3ZziC4kkmx8AzucNW26LalJmw5AXCTSO7TkxxKizhLtaKVtDjJ4U0HPOBS/PC3KquJ/WjskkssCDisq5WwRROohAdZ4fAnjiKIXNZsTHCQNpEhpxiygLWejmeCUSbaao2YyW1MJcmQQrypoJ7mFzkfZJDIHw2YwayuX1lCRH51xB59oIBtoGypM4/cuWUTbBLFvXjJwJD+cVp2nDeRah4dPygFomoCqIYUqKDi2O+WrSXi5Ny0FDzUUR31JkOM54VHKksMFTUvTrgOxr62OfHGrzxOEf/B8rkxEzUmDi19qOm6HPh7Lvfn/Nmt8IlhRl6yIyHBujrJDWFzE80AXUtDMTaByZIERkmgntmGmGP+M5VefhAErFl/8thmbNBB025sWtZlLgYpIIi/a0xpgqgC0pBhsjzdVNp1L9kn39WP0qD3AJqoonYKvmHpnO2I7wBSOCQI+e0WszR20pGZ8+36Mw4fFyAgM4q+n+o9OCF9OCRGpZeZ/MhvFOEZ9/FNtNZnOpk5ioAE+etBe7rhM21VYAYNsySoDgtkipMVQZUGDOMjjCxFAt/h4kbME0uuq9rE54k7rTVZ+NtejXYVzHRgLghKNJldyieuwGQCNMFhwAtLLFoS58Y0o9sfTnVUaXVkhpX4t48/HoB8kXTsowC7VMbYKW35XImSPCzQxctoytJKwliwkuRBdec5gXDUYAjiPPxrBmR+tVzLqkErC1uAacQRLvaGU3HGNKquU4UR4vuEFJHOYm3jy+S2BfUA+syZIHjKYj/kKGYWWkDxiFB052GhZ3mg0ZEzJJiIZr/LxgLuy0l8AA0KbII81CdKdpNRSfXdUjroF5B6bc7t1yaHxchhzAkOjHYniIQJnEbFYqDWuyTVRKtm6NOZiJ7YBPBgbTJ3M2QFlLPWj9cDPt2jXYBxWZ4FO0aN8CYYom4MaApPfZPsikzlfbHQAggXGXV6mIlxjrmrFetLrfkWSpROdST+0Y9QmGALq69SYf8qbw3zmhFsa2JRCkIl9hCTiIsOUWfDAynbiYZwUERckisacrUk6QcDtfgf1cqYEZJkY6FVBiccxbCdnn7GY4AOAZLaEu2r0LIV2khny+7G3/vqb1Mxlq7xPAKWttE7l3eVG13HZtOGnKjJLaep6fTmAmbJcsDNGe12jUSL+ZsCwZ2zL1c6Dz4zVITPMAnMlwUYl0qkKDuEn+aZj4PDX/V9V1Y6V7O1t80jUSxxnfjxPx9kzgo3/hnmTCBLd6QfazVnmNUW8OzhqfwdczD/cOH4Y6bmsijNNcT6YRxXt0chO38cbW8N7aGAE0P2FujJDD4iIKe5cZTFXHSf5c3p992roeUA5INRmpqJrAVWBgeCIsalY/Sv51nhaOCbOwwBvstLYOt4/6a6UMQavwGgMDqmmaoU8AHYJAVUazbeIb3TYJf95qwrJNXwizMYb349jeWqmzgsRxVgdJQDeGSB9N0uIaNmnR3WQ01qRSI+qd3yHgVanExMSopPUoAC+MFJlN9kXTM5tRw2GIOa9U8sXUxsWgRN6njGZ44VEzseAFU4J8E/ZlCQCVzswezeH5GF7fhNQX5BI0wqd1z3AEXTC3cxUElUmIfE2pXWDzwIKrxkwCEeQaF1zzomACBXrNyM1++vxx00am4NqNmUAKoSbSomVmzoS+r3A94IwmIg/0dnw0n0GUvI/aET2Ix+zZ7H3Hd+trlNr97ZQYybATsIYDugb6AIfWvZvWxvcdpz3eMvJeexffT+uYNAFHRDNqSkfa4xHD7gaM5nONTB9RmBmYPdp7t/OiGc1Dkv0+8eHfPhGR4Rgy9Ls6+O1aqZOj5TKOksV+pO0DDX2+z6v/XUH47uVB/TXJUZgp+CvYnOib+i02Egl+oVZzg9FQYjNLPXRfmOS+Ey4K15EZTxr59pzq4SahcVEbwUK/FI3B1OephSMzRDqdo9gJ8AbP0+kIUjaNBrB8Ad4SsIiWIiWAW6+tWBbACnJIOjf5Ip9pCRLpUSN9LlcP0ApcAaBF7lMxoawCm5PnKpt2yW5T7zSBSSXSXDGdpAjdPG/OvAGgzsXNGTbPJlHaMfMPwZgM4EKGVYk0s4aZ4lpJX7QgDsAlUoHCUfw6DeLwAA5jUl3ABfpn88UQPjtCGq4biKJJ/Tyaj6ppNr0pz+i2M6JwbzaBIprRAAlBruQIE7F5HlZgaqwCDjfk0ki927PYEPy/MB4VTOwECVGmfi48GTbMkaJdiJCi4zO8sMRAInDVarBn2eQxkTNqNQCCENEKo9meNcGohghOB5TV8hnMpBVge6ia2DpBxTeJrVsVqlSjrirEdMXdhvHWSp7k+ePJBr6YdpPZHLVuXw4vBoC8XNt4Wp0wrQiFxoDK7BJCtNUK0Qi7Ru/FJrlz2jOWsRmzsEgv2zhGDG2zjMQ92qHVfr2TfE2jUemI/XlJy+Y28VOtV5LcF0wQrXJj0GwG88yhYBOIpdv6bR+ZNlUIDEEr4IlbtJ1hv6lDmc2PFELLLeDDna3cQttdWQoMw+a+FsuapUbMokarUXoWKm8ajkmqkdE04mOEYlgPcS4ikXxbC0usYwad9jZK8kFgiMd8Ocna2sk+xnCMIcS+j9qBRmSfhEBsd/tseD77tHV32FcY2zXp/to8MFqxNpfLWodiKm2MJtY02g2Dx/esfwfw2sgozOLhFpQw/ojP1z0GNf9l6/f4kf0aIDCcYWyBab3v9kEGCHz7+SUAM38kvF7O0eoF4MrEhPdiTu8UNQkAEVCwIx6WsavJj5QYaWIgSBVHeSEUNpxrAbZYXLIMEhnChot2cIJcSAeOUCXOKYvEv60K41MItIYQVw7EwaTeVbQP2iyfBlKt1DZudODG4aoGU2eGwLnr33Z6hSeFZmPKOaFOUvo0lXBfAuqpAKeK6Vxwd79I5GCq7iuplbAuE0pJ7peZ5oKHuwtyYsy5dPTzcTrh6TJjXSbw09zVheE5vE+1xRvUe/eKbpkNRgn96nnhb7u5rdHEzQTXEfPwjivJWLfkJmBayTVTsnBfA5mMjD6OIQgFdoyzdmt8OYJXRu3rbYzVz7Mbx+/aVLDxKT1iVCFghaLw4vcMwtioacWhqRbPlwReyeQaAc49Sb2pWbXj0ZkPtH28M53Wug/0ST20UlfifBhXXFM9ckg738qemDl3DDxIarkR01sNeULvv32QPpvX6xkAUBQJdSmtQucIU99NkC1eXbgeWoxGiHeMxnedMQRoQEHvS4DettuYw7sxCVrGhf1uU8bR9Tu+X9Ib7za+LXR4gINpbJ0NPjaVCo35iqZnJrdwWoSB1/4ciyrLvzorJptqSoBkY1MBsNl9KDhF5PqqwQTIjHyqOJ1X3J+ambRUQt2y4MatGbwm8eNorZy7ecOsKNRRaqzKpLYtK3FuD8BTeGdROmzT0ku43Y9BPB+F/6tSOfbvK1wTq04eNqaGX7dR88NFgq5r1ssGXLlN/NuIeQ31j6Dj4WPL8P5+FISYyDCPCNMosAzHbB07ZNNhp3Cmc9iHrnVWYYdzO49ZQ5wnoMEWYM8YzAxta6naZ+reVTSXObPpzF79BB4xmv5e7P7f2BIJunljjsFUd2WaftRtjPL8cWo3mc0p20KRTwuFZSbJbEfvwO1hLzBsUHljVaV1/xebaxV2TfspwrIcRf2086z/AYbj4NydNDna86OEnLlF3egcWAQaWBiBfKrUFv30DMmdUS3P8y1S30eTMNt3q0dSNarNqyECbqLimdwXtGO+HMYBAEtCqYQLiflsShX3pxU5iSN00+crylC4ELZVoIpKgJoxU9uyZWybAore1b7McAyXBlxStE1s9+onHB6JRFWfEY3B0I13f7Ptu2nHx2N2qmlopGOKRN4BOE00bu/LhQNlLO1YFK4Aia6LvsVWNsDnTPeCMy2g2zd2j7GSpCOSj/lIpmmqsOSf/k87tXU7wARRpZ02xxrJ59Fuk0AlxYAiEyociQJoWIn2bj103xKIQjfjvcL3UTtpgsueEUW0+EQtLcPAbtt4+jU6BiC9z/ZBBgickmbOJsk+X0rG8zah1OpZ+rYw+wVLThTcd0FAtU0XwfvspLAJAfS+Gfs8cJ7u6lzUOB47aCfFXTz8Zgwxh8UZF+pUkVTKFwQCqGlMIWPi8xiBASSEtigYpYWNWv9GdDok3R7hl7P8XhVh2mrndLA5FrljOGzdhCjBWIRIpEsCFqBkxjIV0GlzoYKZMKkpDZQFE+qSURPjss7YipgeMkk4qDCbSfKrAKSHLQgdkdkTemrpr0+mYWA4hkSwiwpDYzo/iKjpUP/XGE78PjIfHX5kMGRClb9D9vfFuf2NyGziLQOTUB4skXtxLAdCCABYOWc/rQ7n299jHZs2GUEwpCYgKuJF2zvtfH9eg7sxTVyRQNwoMYsJjYb8GUDWWCTiMSDFcNW2EPN85HcZQ5hjhOrYIkMZjwPo0EiIGDXvQTtjfuFP2g/e3qmezaLQ3WtVaPsDk4g7MaOZIRHqxKBCqImDSYiHza272AmwEJpRzR9Nd+BDgbRvtqmGDWzXd2a0uKGHDGrK7g71yDuohEUglyCly2FUJikFCdGGZvMRGUwkMDzZb6rRxM3pzDc41A+ngLUYHbXrFVqnVsJ38LCjvzkzuDJ4kiggw2ErNQGp4rIKXt7lMkkuDhrTyBrZV4uaGdN+YFFTjWGvve0+MKxuPo+f823t0G9TVUqO0vw7EJXR6uvNXpGFlzPAoOPEXmNgYUw7jLNwLnFY/4PW3l1ne2i4vv/bmDkawzF/j1kXEDSbWxsts2olOhbVelOFwj0pczZt2RhO7R92vx7a5EYm1V2j68UFX/SMpeh145VW48rKxSdinNPmzCkyF0v0jGN8n+2DDBDYOLtNvnDC4zpLrkqMQLJGmrAJIw5Sl5yqOA6p9sTVo6JsU/pGbAlnRuA9aQuAxaTstBxrR8ePCEPHcBA2oI5hUokp81BlkFAtV8VucQsyJW5ytD0emUud5G/3q4Rr7N4864WWrQ0I0OfRHBz0z7NRUj1eCOXVjEIT1s/PkqR6JyHQp/OK07zpvMsS2VZBfchpQk4Vj88nbKtoPrgkGdNdQZor7h8umHPB00XO2TMWvkpQADSokkLyjKopH2KgRVvXTQYQfh/WBoFcQ+k0XmMcw3EzjXaauDKVtKlwkI2RARyiLzuzk0rpHdyNCxzc9wsj/CQm2bh+9Tp/pAOmZsEtcd7IEKoBN8k6EoJbLHSONtlzFOdcT6NJIGocRaOKls0KBtsiGKNvjlCv+FpufT/yzxQLz4YyiYPwtPG6opGPBqVzN21IU/MFpcSClM6a8zMKAe+x/bhqULfharbJSy1b/RR36EIl0VG6BmQxWtYyidjhJW7VjtxqYPQSX1eVD21Pdy/giGiEFgH9pM+jk4bvOg6rnZNUi/C8kqpYThZyY/cOsDFHfQggtTBUVpOQSaGcBo0mcU9s/P42Rn0mT3wZ5mKcl/iM19ZvkOh5SyiJsSbFsjtw0nbmitgnMaxwXibGnCtWLU9guQoRkNNarfA15X1yy7k4fMe2KGz815pNUzQZjfNy9ZrhMMEJbQdptLtexaGqw0xKpMmI+X7uTADxR+PwWCNTORirje9tLUrMBFlHjCbFN+uEnmwaz8jg3Z4ID6FPqYI5JAwD6mjfE/qxOTTNgflqhF9yQM1w7Nb9q5GiA8YlGpiYVmOlzmtz9kU0xnU8uD/q7Xbo8ysJfZ5yQU6M53XCumbUkkS65yBdx2bV7fSTc5CWAF+gLnFF4mqLk9r5DkFjWfB6r+M8m4Gw6D17k0EYC8PHQpqwmYgxzQVEjG2T5y1LBj/ndm+ClBxQEwJFIhLWSl0FXbpW8RiTQt0A8JBYVnu3aDisDCkwG4T5MQJg82jzavZ2R7Hun9+d1FOgbN2cEfhRzaVpwkoMzIw0F+Sp4ny3YkoVD+cFBOAyFwmUOGkNk6mhdE9aDuLl3QX1vKigImOOzlxmwlaS1+jZNkHjNvMbhzBqmYIgwFxrjN4MFt63+xwQ3pG+L3eoD6Y2NgFI39euf11TXcBA0YRNfY8CliGJg2xIFar5uJnK/EBgZWwhLNuGemCObM8SBBD7jDRrTIoVat2fD26I4lBC6+UJguChQhTPErByOm84nTZcLlNU+BVQtxyGJ/s5b2VEjaFEBBE7FqMiR8bETEgER62IRNwBZRXiZk0iTJsvsk86bXhr74o+8JO2b7fNaB0jKZrhrRKAJV6Nm3fQTmK0Wi8Fy6cT6UCExhZtwTtGM0oB8bhtrpE4HDU9LyalpSRw/LbnYg6JWQvN5JdSSPKk5t+xYlleDM7GHqXISOxGxIKjZs81SOpGuI4APZmoMSdzAMR7AEM0G4FRwZm6iCE/l8S8SImkYFjS7zrmBpzKEON9L5RYKe8OoNE05pK6BL+OwQPNpBae/Z2018Bn41Jk/6QdH+6+U5u+W++GGA31GUrtTMOB1WDB7v3FPuNaeudGV/72sQ0vPH7vrg1Mlxgg9U1SfyK7VtNMT7Vyd58YBHDkZL8Vumy/H8FUxT4sSfhWJsyRtjDO7D8uAJg/ruzsJrOh8JIBFXJUq+mkfKD5EhwbiZ2mcUkhJBmN0Zj24rvLGIoc80mPUihw7DROYYN0BIL32gEdXK9MzB2b2u00ic15YUJZq2gNloy5JPAGSaJ0s1vfF5sGmBh1IgcjjYSEFX7mqnlxHKd/9lJxhMLxZE575E2eu84aaJBpFx3lYIt6HW0J/Cg+t1evZyAzXt21SKOUGDQX8CSJe0JsCN/99EUXiZbmivm0eZ2jgeRJdzr35ZJBn89Ihrzggkl/kVfGPBAk2DkIWvQZjGgO/dp3ZQ6tdg01hj0wnP4GeuuQR2X3amPWfI1gTq5TY2ydGS0IEhQGGP04tkai854KhedHuAE60xZM6BgmgaO2b4MaTZmEFiWpcyuF0HQYpiHrmDgIGJGpHPnp4ndDlSDAoY1yaqSjHDAOoNeSYnj+kY0xor+7lq2uAi/ymEVrtxSBL6TxMWP8cWhvYTZDMqWplIZ7ZguUuC3wjMZoXJJnl/asBkznw4sSnC/WIN2k9lu7Jg7UPhlekKx7kGCq44BttVvowsg4BSarJZO3LaFkY7Bq/lj12WfoToimD2MAYbN65jhhMKDvmcvoC4qcNzKc7m9y6BtPGDUaowyNlNF6xFHo0zQqzx0pQFoDploCykYoEyPfb5jngpyLQ8Sb2aE+TqA1eZh3uZONmlIFTps4pc1Bm0N2NhNQCPlJYY1mKGqCrKt+Hmw2+pyLkRkwLJQaze9y0MiFobck6PY392v9eo6aCYLwoRykAmThtbS/l2sbgenA/6RjIWQwHQu2W7ivCXV2YNCYOAos4/lxORuTiVox96amBsSqQpRp+qqhlBtzGhmNXdegjVpV19iOzHD73JrWr/t+wvyZMlZqckZmME3Mmocz1GF6r+1t6+6PaLvJbLzscK5ILMl9ZUkCOrlQoNeyi1kJwq6SZZdvAZha3jVO3YaRY0rMbeNcs1kzmtM+MMC4IQWmKpj+9FyrdBgZIKOBQVoYbq2p23ht72p0UAqSNrXz/Ibj0OPYzE8TRd2D89rNaJgn7IhjR1iN+ETBtVJL7j4aZydR23nslU1LmVHSJMCkGh5twgUmhay3+6mfiJk8AbSqebJskopfLLJtTU16Ni3s2jwe7ftIdIPG54x4L2N01zpOHaNpNgPD39E304I4XIvQTyDUJux3zKkG8537R7h7Via0ctUWrh2Yoj/XjhGND6mCTqV2fmdyxn6+ufmWyJhIgvj/slao3TQva8kaSapFEBXqJfrqRoI/ajwWKTYGAEQmEgNV8nDcHf3U0MZzou4eY5KmXVeZvAqtnZ+1ANyVCf2Rtw9Ss9lCgS1OLIThIrAkaaG2To2QVQIq9wWYgCuElrrfO7RbHk42P0ZG2BB6km2U8fqYU2LdOMNTRmOJnxm7tm3JJXZmqLPaFjF8dxNDq2rqcyjjdW0h5lfE5+dwzIjQLbHbfouO3hpPGSRRjIxCf/J5Q4OWubZ/KIxfTWy0Jne0E0tQQ50lyRRnxcGaKmhm97FZyK0xcTChbjKfVcfESwZdJCnV8o7quXryoidS1qCZXht29PPwoKmMjMAnC/4+HRy1hPft5wRG0fUZzhnmMDKaqHFEAu6MLbexAHBTIqFnNEQEh9IZ8dni12gGgwk0QRgbTcpRsLCB2/MGtARJ5JQAmcoEbEkQxhcJGkknCXu2YBEj6llvEZnFSPhzejeYfcuJMROXVwMNzMJaZCoA3HJRNCAgalSmpZvJ1zAB431+0r7/dluz2TKILCldpFeRZESqYTRGI7kD2PscgJtSvf3O+kloizuac0DisHZH+w3p1D/j5rg2Fj+31wZ2ofq2weykhF4ziMwDB99JNrq6iJ2wRevG0TWdCTAO3xhq7e/tzxoUMdE6Zc484i02J+TD/ER5wExsQKclEsPxxPiS5bxdkEP1Z7DAAMzUHpEYJTPqJKGzFjXTMlAAACAASURBVLlGc3VGZCUfxr3eacgHTKB7lrA2utsERrN7/rieIqOJ7+rKmrK5QkXQSnTPXCNadt/AE9x8tnumsIBifzf2Rlx/vulg4+H23GMfuv49WEd9tKSBNEm1GR6EPIPwtxad/OMwO60EvYQ/1kEyE1tXEsMYNDdmNTIZC1xh1WBiyLOtxa5/Yinm+AUymfcdbk1EGcBvA/gmM/8ZIvovAPyLAD7TU/4cM//PJPbnvwrgVwA86vG/p/f4NQB/Uc//K8z8G2/r9zaCwOMkhOlB802S4IMxUYPXM0ktZrcHaRrAlQzyRtCZ4fVWuMiGMO2pIe4C5S5pDRxc3VAuyY1C+421QhZmCwBzW3QNoVYd+1MFUxLNTcflW8Y+rEMj3CGnBoqiIFFf3JyytS12lzxTME3pp+T7cChOplcVNOnZiALJRuFJj0/sY+gldQKqglR2TEeJkt6new7oc6n0nxZS4SAJDbMwa6tZNAOcCihDAwUa+u6UC+bcJNJog19LQq0Jr17fozxO8iYKBak8vERbemPGO3EvvRthGQWFbkG0ufQlwGg1mfou4217nqDX2PUJ4tOjjE4b6fiDjX3MKBiZILVx0sE8HDaboxITZEeJSB8iOjUIew1dQVpTZvXdValtxATKzb8Rw4YBRVuGaCNR4zEHvYFhCsOAmK8RtR4tT6++HDa/TjDFbVps0TQcQxCwoZsWE5uNCToGpuaLqsRgrvgiGgM7rew9tD8P4H8H8HE49u8y8383nPenAfwJ/fdLAP4agF8ioq8A+EsAflGH/DtE9JvM/L1bnd7Oi2V0DncCPPFwJ9WF2imGB2afvFk2ePtntcrtb8dcipLj0XjcbBb/jZxFFqETRpWqb/pCzLzGbZP4qQdS2Ejs/PZRAh77smF2fh0O/8Kxay32OxC2/hxuGHSZe2IRTWORcHf/+OZQ7Bm6fWGPofV6YFVIDQkgnJyJndFkJTynXDDp50lzu9KVgnlHwsM7gXQS7xiCfx50c2vf33pN+xtd+Rs35aC3t3cdxMgEjx7M1y/t50PXETJLftnc8qpyrl4LCUAflQYEv0djNMBeEzEGYRVdf9REN5KWmKheInPC4TL44jQbn/8f8N9bGhH9AoB/FcB/9g6j+VUAf4Ol/R0AXyKirwH4VwB8g5m/qwzmGwD+1Ntu9m7F00hj6FNFmiDAi+pgFql2n58AoGnog4PfJXAnvmHPuIRq2kBTZ117WAdxjsNNjIhODEyax2P9FhVj1d7NhGaXV8iLuoqDM6mN1qRwAadMfZ9GrA2WPtr55XYSNGHj8lBjjdDTB+pBPPkq9Yn5GazJg2CSYA1l2MQIodTsCaM7bcC1UIKb2ez+sbicChxU4CYyf7YkTLiSaBRSNwbuY8lPMi/1LDbwUghlTiASp7FBhWSVTk36NHOKBWZ0oKrO5MI8HTF2+5vhViBbIm4uNcEg/h2ojT2PIzEzcFXAtbUcAwCutSCM+LJ/G5249bu+15Hx+ycdfLdOiY8H0c0pIz1syLNEHuYsIewvzktnnnp8PrlfqTJAlJzRfHRakKk6A9k4CfQVSxVM02SO8nAAdLk6UkGjacdjyLOtHwcLRs/YANGaG4qA4KOdpiI+HK0YG2vmxHv8Y96+SkS/Hb5/nZm/Hr7/JwD+PQAvh+v+IyL6DwD8bQC/zswXAD8P4PfCOb+vx64dv9nezmyorU1LOHZQ3qq1XEzTsPOGhe3vKClBiZvDtIbxPY5SVby32u5HBgWQEFftl3L1vJZY+ZFNujdnKyv2lmZLs1EmqH3ZUA7iw9kGHjd4SHKl7vyR2CNEnw2/j5TKxk5hMxqDtUCHkeBGDfSa1hRtP6zMwpjwwftwe39s9i5Tg8tPRrjN1KhF4ziRli8AeIoU8HqrLmVTm+84j0ft1q2Ns0Rt3Z4vir52mKBPLS/U5+Xm/eHWqCP6RIzbvpUfgKbt+mHbpGGsR31e43bd/gNSZpzPgpc3JXH8P8wrEjHWkrFpUbw2P7oWlDFkEo3VsBbBo2bTTGZHid1HIcsjkxmPR/NaZBQmyJhGw0xATSiVUd++JN97+yF9Nn/IzL949AMR/RkAf8DMv0NEvxx++vcBfBvACcDXAfwFAH/5hxrFQbudZ3NfQIkxnzbMU0EpCWVLQjx0I3EWok3AcQrvjQUu62AvTUUCYGZk2+hOHxHuEYhxZdUmKhxx2PM4FIG2LLn5aDAQfXV6AnC/UiLGNBWJGLVY/AqPUBPhUAea28AM0iNWHfV1ZA91xCTCAxocEHtpIWqhvFqhs1UUVVu0Y6y1495PHV9Gmz9PgEwBPt6GOWpcdr5pcwyv3GixJNZnKgCeEnghbOsd1sy43J1AU8X9w4KH84KcKuaDxLmcaoP4CYyWgqBw1UTVrTO4gGOgsLZ2WiJn0DgCQxO6rQss9fe+xS+N4YzahJsgAdXc0SnNNtZOUDt6xsiEbzUaztX+JUcJQ00emzRdCxpxdne/4OP7Zzc/JWJctp58TFNFORUZDks0l/+WKiYqAAGnBDyX2SPBJi9x0ZvXrB2VD4iRaCOqQIVoQolbAEBWv40lhkqUXM+s5lxUyzLGVyXqT1Gh7bz33t5fF/88gH+NiH4FwB2Aj4nov2Tmf11/vxDRfw7g39Hv3wTwx8L1v6DHvgngl4fjv/W2zm8ym2kWj+g0FV0Qcx8CDLQs70otPSBqHQgSXrfp9Df03+OG30myA53spFIjIBoe7UgE/z97bxdqW7KlCX0jIuZca+99zsm8mfd2UT/aFrT90D4qvoggLfigje2D0o0/iPgitChIo9SbqC344g8ISkM3qCiF+mI9iA0i5Yst2o0++INQWN1VXdVVdfNmnpPn7L3WmjMihg9jjIgRc829Tmbde7LszBtwztprrjljRsSMOf7HNwBX7VNe7GKozeQG5LmXERm9PhC3FydnoKba16Gq098SVlU0MkQAs3WTISsADk2BNlrNNUFvRAL9mgYrYwyzMSij7p7RbPqzuQ7PZ7OwFgyw1cb2miPYLZTX3YsJgEYwoxB4laTZWgg1VSypYE6hoe36Rtvns2V2oGsBZyOpD1065tEet4VFbzLoDaNsYLjgzXpel43w9wHQI9A2+7/JGrR5HHzdx/Xcdu6/Oa8JQPYM7RihMx3uIdRyTwaFPiAzY1NkzCnjxbTgUhLOZgpTbcYIfwwVaTKhbGQ2QPfVBGJkjiJIaF/VEQ0LEPCh0dvl8HsluPN8M8bSvjvTWrD5umsjiasAsjTDGABcQ+V8kPbhgDiZ+ZcgWgxUs/mzzPxPE9HPMvPf1OizfwzA/6GX/AqAf5GIfhkSIPBGz/tLAP5tIvqenvcPWb+32vvNaFc2VLSM454ARwOBscvo+vL+YumLXJ1UTvZiWha8MRDN8bCk0UYMjdAZXxn+da5VHcYbMwmEjGkl6mswKS7OIikltU8TSXRMzhHrIvVfOPfs+DYpM9U5n0ZbiKLz0DFRhPghzE/iCNpVEAPrgnPvtBcB23DsRkx5P/SjSbjj4d0qmH5cX6HZ+nvCOewJP9QK0EJACVjfHvB6SUhTweEoZpnDJEX7LLlPoqN4LAy3M49hjsA+IbZzSDaOZzz+GgaBTHCwpd5jYLeEJDdO0vtS1X1s8RINU8/Ov170xjj8IuocmudvM+c2RNL9Qg6eaLNfZH/ReKE9zyhFA+dUcEgZUUuDLzXi3eUwmJ1yCSib4n2VgbVEnPKEXINqOBVLiQ340sAvt4S8gWxih5HsnA8AoS22tGIMxplNIzGK9t8IO/XyAjFWhV/qeTaWw/Nh2MCmfWh+dt3+cyL6AWR6/zuAf0GP/7eQsOdfg4Q+/3MAwMyfE9G/CeB/1fP+DWb+/H03uclsWtggX3PbDotCz774V4Wghg4AjixQJCr9EkvAQZc2qUuUNEqDPdlPpUf7zeX6WKXAWtASDMEkUXJeQyBoKCcjTVmwkGJtYZi1CiJxWaIwiUzX87Uxed8C0AIPULmZ2ChWIXRDMoxcPyBgM7W5N6Zj/SmDa/fGRhPZaiVNyOxjH2rEQNbZw/ETOx/NV3nLNA/DnpsPMjBzEgd9zheSNVgJHCPWY0VeIsJUwfc6PSUSpH03TXRPixiI+w7h3DYyAaA/Lm+SbaCTnhk9RwQYo4b0nkaTCFStkucwdmP8bi46wKaZEDQ4Q/eVZ4JbIcGdv7cGch31RJbNmoUklo1jyrhPS7v0y+WI10934n+BvF+CCB9FA7BwdjVHPa0TIiUcUsYUCtYasWok2JJjozUeeLOv7zXiyJAoqseCDt4+Kzr9AkaG5YuntTXQaadQUdDDrC2KbtvH38qNmX8Vavpi5j/+zDkM4M8889tfBPAXv849bzKbqACLc8o4TrkVTisMcArNf0CMUdJvI9LPLUGw3+oIdtj6ca0RKZiEp5+WPT0KMuMY1HbRlHAeyxKMiZAyAKvBAciGZ41MYR8VtTMve/lZc4IaYdhpV2qyk2pbwt0wB4wM3Qm5X7l5gmaa4qCKYmA0XSJ/D8NxDM3oHDv/yvDIqZ9EQNeQwSBlOqUEnICe10UsNYQ85t3e/B1x9kxjO1avcVuhLfs+MBbf73bfWne8f/xqiUa62RbC9vPuuX5/MySXSgUOQYOyvUgDM2/MyZtsgWGvXk0xNP2oMyY1/05zxjxlHGLGHDKWmppWYmYlI8A5BBHsIO9nQUBJBNSAXAAOFclyaVzmvjnqm4UEY6Y/OU3d+28YPYSZiFE3US17SAKtHDQpwOfOsrTx2G/Eu76hD9J4hz58S9pNZnN3WEHE+OT+hIe0tFj6c5iwZqnTEhAkn6Lu24/ZbXLWT3s5JBdjTLDavphynviD6sZJTcDInBzRRiVhDo55DC+emlFa+PKQDd0dglVxn6rXaGxSJm2rFN/NLehF5faaJwq+v2Lrc+ta0g++9rXstT1TmxJ5P55Wd94RbFbOTrZO2JGQvdTMGm1YAWhRKoPa5+1z4s6nuJAohSWK1fFRsPWsoqW/po2f3DFgREDermsY/S9mmm3MzyCLiHvAw95SukCC7fK2MfrjXoAiaCG9bafuOmO+eg1B3xFbwwAgkJhhedSmBughgphuw+Y+z4bVOwBZZTJhljpGn7x8xMv5gu8fH/EiLfh8SXiz3GEtUc1LYl4LxFhyRF6V0bDU9FkDo6gWEkP3gWQtV1Kq1DRqFTHRiW0IHZ1g0rwr8u+mmsjWGpSxjpqMMTPPEI1hROc/CmBkDg2IM2syMU1ZankR4xB7JN4Hbx+Yn/1BtZvMZkql2WjnmFtOxFXG8p6UaYLSDQnfziX08wfp3dmkeUNkyL+kt5o3BXkCr/doMCwaIh1UImwqfdDQZ0tqM+Jhk/Nj3hnPYIraa9t5XDm5+PpcD8MDR+zJXeOI69D8/I3J3FpHW/gNod/DYts+7Gamsud1q6kpx8okG+HvUgo6lt0zl7db+LH6obl9OfzQYvrt2GZeumZhhYCuWn8RqHFznb9m51ZbpbVpVF+RwJD2PTAz9wybNsMEYlc7Z5jf5maGx9YCAgQZIESJEDRz5lpj868AYvEA0JhNjGLmIAjjsNo9vbLv+4UjXzq6XavfWx6O88FsgTSNv24rb25x2LZ/v69ttbgP276Dms0vvHwNAHgxXXAIBV8uRwC6mTV3grKYwkwCG9qGgQwM4gaBtmulMuJOXRt9t8aaIegvrdLGTlj1rXZmh9ZfADBVpENGmgqOU262WkACzEosmKaAPGepKKm+G7aoNvP/7Piw2EOTUN/05mfiq/WgpmlBTUntOgI4B7DC/rfAhq3jd9sYLfF0qOa5RTUmDNpZf3zUBtqxtXz/TrLw/ZlG4dd8+2nPMHBPgDXfliYO0+ryuRgdcZjQMLpgLN1C3itANs4dJtOYE6Gb/Zy2RLzVHIAXv1Uxv6tt/OePI55+VgmpMZ2BkW/muJk3JwbPVeGSZFDbR2jaUPPV6BJZEI2sk1v66u5VqYVU+xo//Z8KjmYiioyYJDDGBE0AWGvE55d7fLkesRZ5OPfTgk8OT0ihYNKBnNZJ0J9LgNQa6UC2JsBFp1UwVDsJjGqCBfYFE6+twOXj+CACQmc+20e+ZRSeaXomaEXg9qSaliP0ods3wc/+ANpNZnOfVgSqOISCqVXjQice7aX+im3npR+Ug43UB1yf789tDMXTCcK1JtU0mpERNO2LgBBFXfewGgDAQWLtTYVei5bFJiiB0H8Gm2MEwElne038BUa8tz/2cXVmI51KpBn3+QA9sMBP2TMvtw7UmCNGZzZ1wrZlCI2G2lrv+ZFaP51wd4LOTdoepHjtb3hmRvzRGTdVjMXgGBgQlNv01ORHWn6Zd7dPG2dL1LRxsCN0njmwMJt0ZkxvizISRj6GPkk/32FMO2MwwcFQHnQfoJgEQsN4LArTvyO0+3wxCgncjw1M1xiN7q2QRHuJqWJWYWu2cs56o8KhlRwJxJhjwcfzCYlK0yoOKbeCY4Wuw5W9dlG/pobQcmWYWnTaVRE258uxT8I1oxmuwagd2TiJerTbkMPzLfWnfBPtJrN5NZ0BSOTGWiMK9zBFcg7MoTT0IPFifGk3L3D7G+43LwVuujLJt05w0C/azC5u8CyHIpFNPlS5QbrLZ4vECoyUKibF5jI7cKmhJRs+zAUP04JTnvAZPWDNEecc0JI5t6HgRnOVSHKRcQyJli1aa0O8zXZNBI5KED3kTnYLRHL+s+/AwFz7QzBfmH8GzY/hNJTWb8Of2yESmxe5KToOucGYDnRd2hp5nLYN7h4nbrfmBNWgdfxZzatZmUtEL0Fhmk4TSDpTHk1dynACgCyUnRmyt0wLVhrGCXj6QcDl5Yzj64rDF6vFlMgSG/q5LYUrWzFU/CRoWQYGHwvii4xWcKwSyiV0oQjA1bvA0MKFKjDYHKz/vcYKN9TGwEAEpmNGSgUv7y64m1Y8TAteTWekUHAXV1QOeJsPyDXgXCasJeJhuuDFdMGLtOBn5i8RqWLliLVG3KW1mdYsBNr8LlYTJoWKSBVVAzNuFT9rJuxmDSBU5lamYIsasJVlb7EFg6nxoJyFNVih+Ywqpih0wdAPvhFm813UbO6ChDqe6oxcRYWs5njfSFGtbRnOjdaY1WaH7Er6ykg4ADzXTjjsftaPIg7HuSLEgloiKlcMYcZb0QcYAgMsWqZUQlRp/y6t+JnjW7zNBzytE8404RxmnUfPERoc1UZ8TKqv7oZ7vhKvrZhdwKRuI8KbpFp4k9ZzBGq7lu5SsnsN51DXMJ6RpAemdKtt6KCTRZtmwS3nxASAzuzaflBNJgBA1bLXuuYg6pG7kVs+CW0jQwgYcopIx8EQx3vV6DTq42kJmQSsLwn5HkhnwsH6dRPz/hcOfXyDaZKl35oAzBXzYW2mploJJcaG6g1AtFbVZLkKoCkjNLQGriKIMLm955ffhmjCBUO0PkVrvptXfP/+EZ8cHvEqXfDp/A4TFbyIZ1zqhL9+/hTv8oxcIzIFHGPGD+Z3uIsrPkpPiGA81RlnTJhDxpwKcomwkvKWTB2d1cDeMc9orjHR/PUqdKhPxmsxV7k54/R7SQP9pWIsP8DAYE4rzkwWCH28kPHm92AX/9jN04BvWbvJbP6n3/vF9ncgxrvzAVlr3NS7Aq6EelRt4QraHfsRTKZZmD1cJaABrJMAj/k1hEdXiGTvQZIYXbNRG34BBNqeHXO0072PgxiohMtlQo4S7x9Dx0iaQsVdWnGMa7u+lY/VfnsSpXIX7v4QI4Zs+RCmTXlO5xlSI0o08BE4LcTMWLKu1KPYrHlG4LUmyFhJYXugFRvbcJzwwG4MTXPY3GJgPDutaTj+mOuA2MHihA0y9V6fBE2IZDSaYGURGBI+nQlYVasxH5BpHcRuyZ+J5mv3QDNrGV5cBYAInL8XUNMB64MwDWMsXo4g2//uMVhpbtb5UhTfiJUdZu6glOYcj7EOBLXUgNPTDM4B9SyFDFGoBS4MzL0JKX1dObIA1Ea5JxEj14ClJrxeA05lwiFmfDI9yv3UfBXU5po54FRFyFpTRNUJRqqoLDkzRdMEmKAFCCXhs3IH1Nxz4JM6dY3RtD2j7w1B8nZYOXYM9Spfpp3v+g3EWEL0y9P24V549Lb5QOhtzZ0P0T50PZs/qHaT2fzOr38qT2eqIA1DJf03PayDZNvQeQEhWgEIsTgJRVVrNiRfkdSqVQM1wuTMRazmgnAJndHU/vI3zYip+R84CgETYL/e71WVQTtOMo71kqSAVxWH5WHKCKHikDIepguOMfd8ghK0bDScBCoEDFEzzz3zrUK4mftLL1qLchOTZI3B6hoCnRm349qYINA8QHdOWyMWZuyZvzWX9Cq1dSSRVu5hnWt3JqWbH8QzAdfv4Ah3S9Jt6M7xvZERmobkmE4zkfLmoqb5AJWUWWQZNy2EkNEEH45AOTA4SljvgO3m12QjSXIUX4A52psjntEY7vn7wOVT95xsa1UnNBmh576u5pviIPeJqeIwZcxRTLSCVhEGydvMTinUlufyu/NLXHLEuy/vwCepjklqWh2WzP4NzJYbKkBUQsxMOOepITHfpRXljhSNu/tpgjKmL9cjMAFrTUDICFQROHQkZwsdJpMCFdpGBbltM0Zj8ERbRtMCAahHnJUqG8IjRXutZHsXQtdyJFFTNK2t32aLPG1/BWWmthY/bV+/3QbibBs4gAsrbL++OUkgHWLLFO6RJwDabx4JlrQgEQqDKQhTaG+i3RT9u+GcTUKUhyqBG3G5+R+MIGl99P1IKD1meGVJMJ1CrJjnjEg9Gqcy4VwmLDXhXT7gcZ2x5ISclfKodtEkZSUoRqyvmjgsNtoMDdrM1VjtuyNsw+fufXD9xvnf/NfgGMaNT7rRpTf59Y4JeO7F9M/b1sRJ4GPffI1GQTBDnAouYiJpxD1AhRAGayRbj1xz1zcIc31o23wxAmrc1sAhU/hGE+QzAq8XhC0oAGF0XFfdONn5DJoEHYDAcm6iiod5QYoRyzFhJUaNESUG8aO2XDC733PrP1apTKEgsEDJHJNo8YVJ8k/cuZkjzoURaMabdIepFkSqzZ/bute90OZS5f1f9b0xwt8y+Gm7eXaGvMNw/FoxOnPyj8QngsZgzKa2xE7rb9SOxnvLsyr4Rtq3lJfdZDbhopvnIh/1WMFHAuaCMHODdbFQxm3bIqRWDS7gCa1mRPssXaIDa5JZEq3DHMUWqpnmgjT1aBlLCDOTmcX1g6XWPa9hDEuOnSHRVDEfV7x6OGOKAsuRqIc+n/OEz5d7LDnisiaUErAuScJrCeCpSpVR9JDghkrwXLPl8qYxj07A1wCPW54sB9EDDogdY6L3b1hjdIRWy8bKFSs4b6P/8mbTtVa46W5gODqeXfOqn5fJA6bdBFY4H0jggxM62vXeHKbe4jJRe8aUNVhDi/fFItpZnVmeF236a2uJ5sOy+QMQc+wwWe4wSc8kgFpfDaTVmvlrNI/FqkhechpCa828Y2H4BhdzTCt+Li2oINxPq/gPF/lXCiEvSYJILvFaYNCBcQmoVJ1fsuI+LTiEgod0Qa4RlyrjuZSEzGJmYyac8oS39YC34YhzmTBrMEGgirXGcWvoeym+S5lXKWJqs0TN9ggcQ5Al7kxo+3dlGqLZOkOTTwsqSM0P66BnqCd1+rpJuQYsGtY9oIxArp01HPIb0Wq+iz4ba+1lUYLos+O38N9DNVkzozTbPjcJIjQVtrY6FnpSd6pvx2Ghmlq8yTMb05qKIWKabXdbZE0/G7w6ScTLHAumWHBw5jJrRgRyjqP/R5nfXondW0J9O8E+eef4Zrx93L3vn+S2b4QW45q9l2ddaSEYJt76vdHRe+cyMAfeHOf+d3A5QKTMx3gw9cJu4wTcPwx8rPW7HZsFEBiRbBPdfJf9hcGn08yGO3uM/d+sBciYrlzSh5jbZ6kBOUZ9n0IPJlDswCtt00xp6icKpCWadTxLTVhrxGOehckos1lLRFYTX6kBmRjnMmmGvkAw9PowMl/72yOwC7iE4KWVq7oKunQ7GgbR9vjzWkibqjOXeSYDdK3yOf+Lrb89jwrSIIEPjyDwbbXS3QbiVPMVTFKs6GWcN82YzJ50cqvEq5neSg4SaVM2bzdT0wB4gjiHS0Bx5oFaqSE7s7vOsLdaP/ZZuZlTKAApFbw6nJFCxYskatxSo4R40+zGKp9RTYmmQZVKrlpnJ3JyA/SX3coatMWyEXfpv/uhsE8czXTEkPsQDVhkV8TlasFxda+t2YijIRF338W2j+bY73RkJPxAg5ppaNhM1y+Sjrf5tEzj0idJm+0wznPDeCBryzNLX7P7jQFaA8JZNJ+womsZhKt6PQw4X4e7DUMjwCCBGf4HbNZCGQ05CYwji6YWRjlor+29UwFiSjOiV5mw5IjlMsl7sPZE46HZ18jir5kKHg4LXswLXqQL5pDxo8sDPju9wKVEvD1JArchHyeFi7HmUwOWmhDAeFxmLIuYmGsOaNULiHv9KP2osYKnMszPhM6OINBfnv1Ez2fWTTWbWQFEDzHjTnMGKwdUEC45YamxBftYyHN1lTotOq2waD0p1L1cz59se0bQ/ja028xGiZi3p5LzywCy2YlJAneIEdwbW92muc1sqDEdnxjZzDJewm+2WXd9ve5/0I4co2mS7oZOiT1cI4OoouKZbGHng4Lifw3BbpuN0t6Xr7mBdhmBm0q7F20+/fGv0/w11A9ysOfuBrAd1BXR3+tL+8O1T6Td354vDyEF1+O06/xYaHPCIM3r5yrCQChAWKkFS8gz6n2xXeM1EZ27aStgp93sNSdkDH4TArYIxpawOFyuGvsujD51Sd2ur5W6IPgcLp8yQINlmjT4wNq5THh7mXFZJ5xPwqlDFESBOhGmWGCozKUG8RcxYQlRtQS0dRqavf9uj9XgTWwqTN4QSvdeoPdFkZlvRszjq66V+GEvSvq836rTq5FmyTkBla/BK22fPgAAIABJREFUPn/avnq7bUZTuJhKqtVEzWDPAZe3h8GMYRnuElKpUR+WCe7P0e+9dIE8XEN23TpxW3Id0EONC6EqEQyG57QVc5QY8Ub6tNwO8wnUNeB0mvGb+BhzKnh1PGMKBa/mM44qEZUasOY4mPsIAAUtOx2rlDl21GfXvGTNhuoi5BpqtNmUVKTfA75sRNBpF0Pfe+/DlsDbPS0hdCsIs/t0jJtUQ2nRaabN2W08cd4j+HAQNv5mdkxDxMV5vzOHLWNt1Mv1OTBOFt+c1o3JM4FWQphVirZgE+svcmM8FpQwMH77VE3f5n6l3X2NFtS/UJmAUBHRTWkek8vMOQAGp73VWOo4aAxMm3FYJGlkBPWVvDkd8e4y4/fevZCItGXC5SQOquaTZKBqcmUgVg1HTdgQf8ZRsRPTq4rlIeKcJzwus4BsqqawXMQHtE1DKIVQctT3WubgIZoocn/XyIRIGvrahjpzJcF1iwUHrb7ZGWI/t+XU6TrHIBqx5BIG8dEyYY4FmPSaD652EK6Jx7ej3dZsjAiozbl9rwCdNRrL42sRUBOjpioRNFPRTaOnmH+HDH/IbRS9nqwmSqMbKnGaZKQvAtcAcoEJV+Va2Wq17GyOxmyEceVLwmMNOCeZzJwyXs3CdJJKRqRj8MjRgZTZEWAI0HuC/1dqRvx1nr7UAPHO/rPwZX8zVs3TnDt6bPj0Gofxxz2iDgxrbsrtrunCC+4M1YYcw9kyHd5e5Puxm+hCOq16uN/V/PpYt/1SrFIpVQkRx4BBaWWg1UYCWmKwRemxh2TaMJ4rRYpxu47TTiOgOa/hCokZLIufvUnZ3ncw5JLpBrTKsG18Tgi0d++yiNM/r1HMbzlIDhvJGoigE8CBUWJoUDQG52TEeo4Zx7jio+mMQ8j4Mh/wernHJSd8uRyQS1T09ICKniIh4w7d9JdlQ7KOnQMjoIIJiCT7ms0vVNSiYSZsXUgTnJgJuQhwaAwBmSOC27w+0dNaDFUK9mnyusHzrDWguqfwTZQZ+Da225qNrW9kcKhdRWcMfhxPyKTsb9DNIgypRY7Qpl9rDBeySQ1VHgwEiyrS7yCgHiJKYolSs5yMMH5aPtBzUP8W/URRQp9DLD2MmwlfXO7x5XLEm8sRT5cZp/OEcjKESDSaSEHt0Vb587mN4onila1Nu/UE0zEa/4n+0/X15i9S57hnRq1Qmpu/lA5wnGxzDxEMaKD/prnwDjZZ91PxNZMBxuf/HNMiNN+WKIpGSPY47vU9WsKw/sYB4DVIUq1WaCV7XsQSmRhEE2g8kHUty/gMxK8j/TP1PF4weuKxHrDkTdI+Wx9+jb5iM+K21AQgq3QuVS8Nj4xibZA3clHPiSNIbaqkvkYikd4v51miNS9xrIJKLKkNgZHmAgqMw2HFFAum2BnNIWXJAVKz3hQKAlW8SAsmqrhMUixtKREpFiw5SqBBjo3pVdVCuFLzlcRYO1ahJrWmaNFg+2tUKmHJUkk3r7EFMpiv5TnnvpWDZohp0FsvDNXBIuAACRH/4O07yWwAETAPBSExyhIkgYxDq6jZkHG3UuUNVZA8MfWJhP762vs0aJLGbBKBFV+qzkJQ6qRmD5XIeGJwqjuOUif1K6OJsSKlHuHGTPj86Q7MhHdPB+RLAi8RdB5NL5WBVq5YUZ9vOviMmO4Q923hsuv11M8wfjdNhpiUkGLUWhzWWDPT2e29Ga2fNox1W76gSY6WL+Iv2WpP/rc90xpsrrYXnFamNXSG8gyOEfVjm5uacGLKEYlPDYVBlvyo68uRUBX6iA4FFLkRbF6CPG/3rCwb32rJMAhY0ZkNozHIts43CMeVNr53jn5Wpoa4fKlJtG6S6Mk5ZZwSS+EyQz1Q01dMIkTNqeA4r83pfckR5SwJoeESQKuGhh/UKpGkzMDxbpGE0tRxAwFgigV3aUWiIjk6EE1BoG4uOMwZK0d8mY/IHPHZ/CA+oeWAc04DAbdmdW0s0XWKHQDY7j0HiRY9xhV3ccVEFXdxwanM+I2n7+FxnfHbX3yEctE0hRyRo47RmdHEfIYWIm0BD0OuTQ2oqN1cqb61D25K+04ym0klIfPBKAHr5im6JoxbpgFcMZ7t+cOxTX9xAdIjDzDqNQnDyfeEDIVSYVLoeUhEUqg9i34zFiZ5oeyFtFDq0eEamr2ZS+iMBOjlqtcgmpWPRNu2PS3keT48aDV7Po/mExkEUbo6z2j2EChBeq4RQb/ewNUz8X12n4T929fOrsbhxtj8Ub4fdIZylZ/Eux3hZqPNp/WjqggnHoJQKOu+QRyThYMQXuaeKNlQqLU/hpiN5ZnqXnMIDVtNcTuuFhhD3LLft/Ar7M71uF4BEq4fiHGcMp7mjJIDsu6vNBUVokpPUiZGgaFrhKs9QAVAprbs3S/Du4zR8MImkppXh7DiEDLu44L7sGBl0TAuNSHRnTImDbOmHuDQSg4oQbfS0R512TQT01ImqnLfsOJFvCAQ4z4tgrqQCkoOSKngMGUcUm7XZYRhDc1nA10XBlqwRWUANeK0THiXDigpDEgiP21fr90unvZiGRmFQYlUGqE4tozGO+yeYyx2Gm1+q/2TqjCaV389Iy4VVBjEjBoDOBEef2bC4891JsME1APAEchEYISRONm4VCoPc8HhuEqBuCm300olXNYkNuYlii3ZgSOSwqLgKlLLzdVJ8ryZ457ksq28yY7oWT99Uf2F/rhEjw2MO29MQYTh+9DHhq635+M0pbEzOelqia/QlXUslqWPjaazYTrb6/z8ruwoWw2aoEmqbg+aIzlVQZbIpCY1IJzCsDb1WKXGzLHg8NEKZiCvCbUQ+MsJ4ULNv4MAlKMKKG7fbstM+EQZdppmrYS19BDiYRpO8LFP8etI2HMgxifzU/8Nkhj6eJ5BxHh5d2lmtuSiK7lERcDoWpuNOWQB9qxH4Z0UekAA0BnhFAsSVcwxYw4FL6cz7sPSmMx9uODj+ISFIw5hxVM54PV6j8xB8tjALVEyhYKX06URfm/qOpWp5fJYC2CkYJqKpCp8f3qLpzrjcT5gDhlf3N3hLTFeHi/46HDGfVrwMl1QmfBY5uYTQ6jim0EXMEvp77yZ4B8LYV1jq1z8QZnNhn5+m9ptzYZ7+B/bf5ukxlHEViFvw1R821pA9lwYV9cZj1gKqIrzkxdgOkWkU0RNGqegWF9MziRjHvu9sQDD5rEytUUdhO1aS5Azh6tqB7sEezPmZxfiViM3bt/Xc3vwue75+tYjY6SdHzZCgNeohhOuLnt+PFdMwx2/NSfeLrLvY8PhdC/6mjbtnka/IvWoNfM5lnEbkzmeS8+12J3Tdrh+KZ+7hPrabsEmW1BAk7p7K+qU30shEOIrTAUA8hQa4sAUizInho+IaBBSWkqhJvGNjmPt2swWyt+PWRKeI1aKWDniSUE6W3VPjpIQSZIflKiiBsF8S6E0BAJLO+j9BtRQkGtEpdHkVjkgVzEpPpUZT3HGpU5YOWiIMtlyO4RpkQ6MqSWqyPo9hopYgwKTxmu6xpLHV2z9P7Bm821VnG4ym/XNQf5o9qvuXG3SoHeEQlVxRT7+KrbHK58ddRrEAcj3hC//9oR0Bl7+JhCfMqiIk/L42Yr0VLG8jHj8uYBygIRstuTA3mmrv4NuWmIIMTEoGomY6dhNIEY6ZNAR4nQ8pRbBNpiudmBmGk1vkU1O2m/M2E3WWkMKvmY0W+2ntaYV0mAWGQayvcyP1Yhj1L8T4wqp2xC4M7nxbxiTHoOaGa8UFe/nuclobECjhjKY77bM3O5n4fNMMGDTcNZ9+6RdZDTwUej+rZOWBV8IlAP4HLA8bqCuVaNXL5nIIRssskEL3DBVAQQFMFWESUy3UUOKWw0XvWRV/4WZllIsqBotKYECwKX2vfrRfAJmIDxIP0m5x1IiMmvyYpUsuPt5RUkF0ySVZ09vj+K/UbgfnqqOCc3HI4yrayREjKUmLDXhKQuDMTOfmb3mmPEyiYnrLi54SBe8XY+46PitMOMn0yMmKrjU1JhTseecFGlaNZzMIgi+Xu6wlogpFvx6/BS5RrxZpJLo29MR6xpxSQWXkjAHwTuMpHV6QJiD1qeZ5CGd84THaca7peB8nrQ4omqxip14SEVKYP/UZ/P7areBOD38PzliZsdMjTEhUtX5AKCFL0HO4c31zy4oYXC01xlYI6FOQDkGhCVI0h8DlCumR0k4s9AoppE+bdveb6I+a8jjolDks7xQFjjADPBkCAc0mHzIOCS76Dd7WRxS8fVgNp/PjVsZjYz/OYaz0TZ21vdZoYwcQ2y5Tu5Ej2/GY/8DT/HEdaNVNQXz67xIniH5vzcMbpiHaUQtfE6+Ny2mCDq0QfKLj88pQsqgqABYaBAUWoE0guSCWClwtx5skGR2nZPEBO0ZEpBAPXfFa9dmqjIibwKRRGp5Z/XoezjGjBQKDupQt5ycrL4Z7++xujIpFonYukzIKkSyaTzPiNfb0sqAlI1uMDa1k+I5FtQjqfay4BAylpiHMOIpFBzDigBuiZbj/SrCoNVQw2w7rRNCZjyGWUovrBNKFZNXKQG5yHiyq48R9EFPobTyCW0+HLBGzccxa8agyalZ8wZ9+Wl7vt1kNn/4j/4OgL7BbDNZ8xvPXhqL6PAQEEUJ8Krx9gNwphEtfYBVJbqaJVGtme4K4fHnE0JOQ5EyqkCZGfllleJqU5Uos1kizFriaCFUAyfUxFF2G7NmZSSrAiGmikiEKRXcHxZMseCcqoZWJrTqioweQAA0QkjR5QBBz2kh0uiOenRG0k5+rhE0pLw2yR1MCGd3f2DwC2xb429JCAonBg6ShzLfLyJta3jrsiasa0RdIvgUO5PbMJFnif+WKVVhzEz6vI2JBmCPOTZWZhKM12C253tnlJlBSIJH6l0Vn4oyUsokmg1vBaqdQdDYvWlPlSC5LFM/blqdMZ8Wsm+MyoBGA2uSIl/5ALzpqpnVSHDMUqgO26viIUk0ljCZjFyl1sxaI96sRyw14cvLEZcSBdImp5bPY3AuMVTc3V+wTqXBPlGoOBxyS3QEul9oLRGFwpBsKuNhXDb0YQXwbj0ghYrMofmOgO6cB4DfuXyECsJnF4lYMyiZbYG1AG6aRSTJfys14JwTlhzx7umIWgLyJQI54C1LouqXxwtyDa1Mg+9z1pL3ARLpRjRL+ZAlILxLCAuBacISDjgn4PPjR3Lh33+9VX7abrebzOYf/Jn/p/1dFFOocJAHrYkFE4mjbqKC6ChAAeFSJxQOuLCA+70rB1xqGlBl86ZGhKn9pzzhaZ2axMRMqL8gfQvTCiq9iKgZATF7JUV3jRL1kvW8UgJWgsvaFwmnMZrFJZapCl2DmC9ezAumIAjXpRLOmtxmTtZaGax5LUEJieU0GFPNS0RFVAK3TVDBNbH2/iHfogQ2NBw5q+FikrUR8W1NmK1/xjSYuWJ+sWCaCn7w8l0DIg3E+OJ8h9ePd7gAYmaBSfHUCb+On83Exa4Ym2+VGsJxq4RJUJQKm4MSfm8qa/fadPisL4VUK2M0JADNpqdDRZwLag4Sxl8IpM/9is/saeCmLKn0z07jlLUh0AKgoCFP+8AKz5gtVmLrbO7EW/oO7TjUz9GjJu/i2hzzL+IZ78oR6xKxIuIpz4LQfJGSGKUEZMUrS0kgaGYt3PZwWMCzIGVk3Zu+SqbXugp3CJ0pVBSgoTczxPwXSK4vqoGslbEWya2ZY2lO/jkU/V1APn/v6SXOOeG0TFhzRIw9oXpOoxnPUBdKDWoGn7BekgiolwAqhMIJdRWrxRQr5ljwYr5cMckD+p4PpHlzOSCeCOlJCtORmlA5fM2M3d9H+076bF7EMwDgUidRczm1hDKTLm41iyw5ILeYeSsOtbI4FM3+3MIPU9B7ym+GuGyFi7w5INeA1dmtA7hFyljEzlITlhJxKQlfng8CnaHQM1biujKALBuU1HRSo2g8b+muJYsV07qKmjc8XIYGEFQAxBFrAxXUCB9NKBxMUtq2+S/wTLEqEbYSA2zBC2jMiJOWNrYERV93yJo5TaMk68WpYJ4ll+H+IMzUYNTfLQcsJeLt6YDT4wG8Sh5GK9HQ+lR+0BQOarcioJtaARickJmrWgG857QiOzkANFWQJhl6BQNOM/amSF+Ou2FyAQhJq1MmYbRcAT5oIIBbo9ZfA3G9vkd/Vp0xMqPBFlERwYUYLeEzZNkzdQnIFFEUiNKIKIDmo5Hvisflyg5szWjFhRJ4baFNg50loYq9MCvE/4mmFniwrQdDjalUFIxFz5h6LZpGtCGMJNIICVNqQAGwwuD7JTk0l4Bzmdp5phGZia9GwWK7m1dEYtxPizCLdMEh5sagnvIs+TepgFV4LEetuJuKhH5HYUqnGvC4TLCSAswaqBBrCwe/rAl8ji0k3qINmxB3w2rwE2u3/AB/C7ebzObjKKGVr3GPSxXMJIHw7/gdPlSxbJ5ChDjlDkFA8CYqmKi0zXjmCU/l0BhPZcIhZNGSlGFUDjjXabTzUhlqihvjC1RxpDyM6VInvC1HPNUZv3d5iUtJ+OH5BU7rhLfnAy5LAjiBLgEhQwAabfQTY10C1sf+Uuw2u6SOWfqyKCraGvFqTKKbAjmyIAOTMosWOkta31qrUFaB8jC7v2kvYhIDcCgN0fdwEKfEFlH3/iAv7Sd3T/jB4Z0+Q0bmgC8u9ziXhDenI07nCevTDHqM4mRfMZqqrLGYMtm0FDvsCHLz1ei5jeGQMigLnmjnK5J1lH/puGKeS/MzAJ2IWoSQmUuHihKM4TfoPSnloeYJgIFAGtE1uBK73ky8V4yJ+Ir+tFwNTQamTAgXKRfAk5iT17nXSLlToEjzfwBACVXLRHfNIqiZ2gqZVc4oDsohomILZWPmMan3IgE0tUCBMLmd1zANiRWxmRGUodgYiLgxH89oYqh4iN1fVKpU7nxap1Y3x7fMAZec5LXQ+U6hiraURJs5ThkvpgWHlPHp4RFzyHiVzpioNCb7er1rFUzvp3VIzIyqCZ7WCY+XGWuJOD3OIvhdogRDeC2aICHglwCqmjQ+QVDEtVLxc/WcfmJtI4h+m9pNZvNYD6gccKkTznVqL0KFRK5IQpSY1SoJXlPENSyEx3LaZg0bE9keN9NcBbcQHXupppARIZt+ramZ9YImeUXUthlXio3J3cXVMSZzzoq0X+eKSiTMpkmjKqmbB7mZQZ7ZDazXqDnp+re9893fXrNx5i+P0iC3GInzdvO3UtzoZhnDkZujRNRYBjag2mKhZia1nAO4+47jplGiv6GdXF3rz7M58TO/2710LYPzIZSqjLQGdV31IlvtUnYlhf26uH9ynK9Ql31fVpTLNCbPvPxaeEZHJGbYCr1mEotAy0vLhPU04Uf0gJQq7g+iZUyh700AqGHEI7sqSOjGaeWj77Di1SwlM85alM2CDGzMsl7X8zQr0fvQDUwbEvos0ZktEZWphTsfNSTbIthezWe8TBecyoSnPONcEl6f77CWgLfrUcx9a0QthDQXPB0XHGcJjb5PhhpQlKmymsojlhIbY7M5JdW0lhJbuer2HIEebNPMozwAq/JBBDo6FkzHVUAtnqt8+tP23naT2fzW5XsoCM2/Yq1ywKOjCgGMh3TBMaw4UMZRNRlAtJ2qYTjGkKwZEzOzGgAEZlQQIldEyojKKHwN8NY4wu5kzGmmjIAKcEJBUO2q4hhWfJye8BRmpPCyRwGFiumQkSOjnBP4HEAFkrwHSRKtM0SbiJ3AbonmOC7qvzszjluwAZFgSDbaEuMGCaSRQupobqHUg5Zh5Ra6PyC5QIUYKl7MF7yYLvje/IRP53dY1X8GiCnjkns9kmeh6q11PjAe3pqdbjXuJrXGRM38VmVdPHHvDnIjblU0ISX6PvNeCurpmAiaR+EYDpRYs/jmfEVHZkKqUuM+K0wM3Fra1JqJy62VRznnA8APoiWtxwm1EOgxIj5G0NuIyjNOM+PxoYAOFS8/fsLdvOJhXnBUs7PB1Axmqw0ziGAcwoqP4gk1Usvgn8OneDPf4fOnO7zViEsrZlZLHPYPAWCuCMHmQNhKCw12X59LgSSTNlRqHaMwmhU/8/AWd3HFL959ho/SEz6OT3gZTniqB/yovMBvXD7F//g3/whOlxmX33yB9EhIi2jS+YHx5tUdXt9VnP/QhJfHC6ZQMM0SEGF05jHPeLfM+NGbB5mTthAFD65WQZZmQOCboCjtRVDhW7AR+rvKEaCPFtzfL/jZj77E3/Hic133D13QBt9NzcYStJaahjDBwpLIVTdiaA4BJY4MoUnLoGb+Ml+PN58ZszGNyXCWjIkAwKTxqgXhivFIUSTRtEB2jknEFYGDbFTuqr6ZCwQTDYIkG1NzGNOPo9I+d51JUOYhbhqLic12jIYQcHvpmxbxnIalhMTME5V70n2vACkCwFojCoL8U9OHQdbvqvNeY/OPfse69rXWTXnM1zVVBzXpAGgM4rnqi3sh13ZIiGxnVlstx/rcq+BqFWdDwGDG85qTfc9Jq6ZB+WqF5PyAwLMYhpdVXskYKpA2movTegLVwUfThDqI8DeFAlQ4EMrr9aDNopukv12rymL+29OqAvoYreyBrRkAHELGXVzwMp7xMpzwMpzwKpwbDXiXjnh5uGDJEecoDM4ELFLQVC5iLl3VR7tybO/xWgXZOZcoDCWbasYg0jQJEiBS87cOZcaHRUEXFIkVUy7j5XTGJ/Njm/OHbh86QICIIoC/AuC3mPlPENEvAvhlAJ8C+KsA/hlmXojoAOA/BfB3A/gRgD/FzH9N+/glAP88xND/LzHzX3rffW8ym7erVOvzmo3F7huMhJnWEolEeJ8WvJik2qW9tJeSUEHNcX8IHWDPrjfp2vIDPppO+HiacR8WfJIem8M/Ckg5qjkuqaJwaIzxQMfmvwHUbwQGQhYzATEuJeGcEwIBh2ltFf3enI744pRAS0B8EjPSV4KLH8xeN84xO1hQW7EP4baNXnpOiPeRsDq1R61mc8/afQ2XyyT5QZshfIE7fLkc8HY94ov5rhGvXIPUm69BfBMlDCYsg9sfmB4wvrTbNQgjA7kymen1TatpVp7RLt6mZxoMxpfem8puNdNCtowAEBDIrdbjM9oBNP9Q01yAhvNlDnagm++sj5awGRg1VinDMTEoAkjC5GglUI44//AO5wC8vb9DmgqOd4tK9BUP04I5SKLkIeZmTaggfLa+HMZqgtw5TzjlCUuOTathCzbZPgqy8ctaybrKunCoLWigzUf/Zl2btUTkEpo2HUgsHi/iRdEFDlg54TXd4yEs+CS+w/3xgu/93CO+yA/47+7+GD5794B3X9yD3kXwzMChIB4KjlPGIRY85Qmf4QUe0gWXmvA2H3BaJ5zXJKkNmVqYfLxb8dHDCceU8epwxiUn/PDxAZc14emc1ERNY4QqcfM/xiQApPdpxSfpEU91xhfr/bWF5SfdPrxm8y8D+L8BvNLv/w6Af4+Zf5mI/mMIE/mP9PMLZv4jRPSn9bw/RUR/DMCfBvB3Afg5AP89Ef1R5qF62FW7yWyaeYW7U9Ick5ciDMhswlZ3oyhkhDGHytSiykzKsvoXANqDszLMWaNMElUcQlb/y3UddkvOMq2pSenUQ7MnKoBpRqwRdIriWiohkEj99iIvJeKLqWrNE+6Z8M9JQbvHtyLk5ndyF5Mz+ZukCyhSg01Uab4lXN5yUKo5zup8FIRmYzaisOaITKER0khS/CqzAo8a0fRmvr2pbf9+L7PVrPvNOYP57CsIjT+OZNkZHW2Oj4zL13xp58B8NdfnAmgSPttxdGJs31vJBgs7d9VBzToTzqKZVySscwAFcZRbZU77l9RvMVHBuU6DsAaIZp9rlNLHOq5B8WRCY4/PLGmfK19pfhbe7JtBPfnItUlhaAoIZ56wckKgCTMVzCQJnR/HJ7xO9/i1V38Ih5jxGyXgxEdBZJ8ke9/Mp0tNCEU0twtV9cdIakMLxlF1nkg0u2Na8enhEY9xxpvLsecC7exxWw8OPbfpEARkVEz+4cqi8xNvH5DZENEvAPhHAPw5AP8KERGAPw7gn9RT/hMA/zqE2fxJ/RsA/msA/6Ge/ycB/DIzXwD8OhH9GoC/F8BfvnXv22a0PLV4dguLNd/JfVqQa8AyjZs8aZKZZzJrUQiKaslgtUUuWSavD2WSkOWI1+sdMkdhOs5W+lTm9nIB3WRmduKJCu7DgkNYuxRCFVPImDgpLHvBu/MBl0vCGxzxu/QSeY3AScMeCVLjRP0HowQkH9scC2uDZM6b3x1RJs1AD6vmeZh/xk5V04yE0jrTh2WyO5Nbr/AJiVpjcSrPKcNK+QIiwUtuQtL1r82hm12exRXxf47hDnPEyEjQpeU+qRv97a2d+qE6jFDcxewaHP661h1aVbtzzOJWmXIAqBVgsnPHa1ulWYfZ5ZOVofM2phWtCqetBzEQqedCAa3mU3NYVwDngGU54odfHoBU8dsHCeX9/qtHPEwLfuHhNT6ZH5sZ+lRmvFmPQ3j00zprRBupqbJLSW0+cGuuYw4bsDSbv5kNAW4M0Mx7gIAuzIrLFohxqjMKAlaOiKgNkuZVOuO30/daUNGZE05lEuYwr1jv+vtdK+HxMuNMjHNOiKHizbTiEDPeLYc2P0xV6xTJdcsl4Yf1BX4UHvDbX75CKQHnJ4lGo1OUNAdArQ1oPlGeBLD14bjgk7snfDI/4uP4hMoBP8TLlqbx/9P2fSL6K+77n2fmP+++//sA/lUAL/X7pwBeM7O9Ln8DwM/r3z8P4DcBgJkzEb3R838ewP/s+vTXPNtuMhvLgXkRLi3L1hcPqizhjYW7vdhrQSYp2zHAwmyFcLTaEOTt4mK7yjXgicU09hAPmKg008Db9YjHMjftx/o105z5e460YkXEyklMaartSNZwxbpGrKepVSikIpnlxOIgrEYYgGbeAtCJq0MxHqPJqEvrbbHdGetDAAAgAElEQVQ2iYONUUBhVARni4reO3HzYxBDEgUrpAqmhhpT6H0RSMMzvVNc8g+GxLw6SfmEElA5obiCcYafNQQ4eI3ENzeXxmQ2LyFVHrWexqS3nQHmy7pqDMlNKQGFWMar0nUzV9HGJ2GmPl0IDtwIZOu2MR1bKwy/+Ui2bQRaCGg+GptUMeBOhWsxTSZE8b0M5sNtgAcBVsSOtSy2mNVkP1AmgcGZGJe54odMeDwueJguDeurMOExz/jR+aGVKzDLg9WJadVmdWy8EZ4IxiRHk9r4SQ2swhiNRZqVEFA1AsySTy9F/L0nzal5zAcRJOMdXqf75pNdWSwaljNzOK6SM5OlsuflMoGIsWiO0HlNmFNpOXPMQEhV3g99VnWJWBQ15FyP8g5qsm3QvDHWtW/oRlpIL0wFLw8XfHp4xPfSE16GMx7DYWfj/mSbWvJ+nPYZM/89u30T/QkAv8fMf5WI/oEf6y6/j3aT2cxKyNPGGQmgAdsFNmIlDGXSjZ8pqi/AkrmoSUD3aWkYTqYpzSEjUVBEgXKVvCZMw4IJhBmFwFg5YLIkTkdMVo4489Qi3gDxNz2VuZsWeNRWJLeDVOswIhp62QN74ewm2+A4/+5uCSo/w2yg99q++AxJZ1IaKSjWJhl3KWy4NwEMBgq1MrynZdJEObl51mTWlSOoBqyFW631y2WSF/wUgVVyQxrkirWNxuMZjZ8fU/tvnLMyT3bXW3BEQxBoC6Pnk6AyBKs66eZj0WPtFuyqKmqy3uR8Oj5abQ9F+br5vuUzhPFdYD0mvg6+ioALoQ4VIG/fjtreaM0LHGvA8m5GXiL+Gn2CN8sdplAwxyLJy5q7YgzHNNlqOF9MIAtm2ICtfp1WqrzntcRm0l7VUZ9LxDknvAuCYhDQtc6i724KFZ85HDdmwrtV0A7OCpM0hGZX3SdAK+dgNadyDi0HqiX62jrq+iHJovIkcy1mcjNm74WlKgLOqsngF04484SIih/Mb78BM9oH6//vA/CPEtE/DOAI8dn8BwA+JqKk2s0vAPgtPf+3APxtAP4GESUAH0ECBey4NX/Ns+0mszlGYTaHkNU01v0xHhIc6C+xaTgrByxVoCgaQ1EolAdFgDVmApfAaf1casK5JO0rSuEjjYDLNTYmBgAIwIFyqxgIQPKCFPL8qczt1FOZmwTfyuhy74enClSSxK4iElBw9pimahtzApwWgM2Jm7Z5oYOV4nXEpTGsqmaPhrnmiFsjxD0cmuES3ovgyhUAl4VbeV1ATBIePaFllxcCn6U8MK2hJZEOZj3CYPrxL6mZAe145zWbdWCZS1MI7V33BNavZ1A0Zi10J/VVBCmCIDZ500BMQNmaObz5y74bgbNkw+eYzp7JLoae8W/XFg2Trt7vZecT72ttaIs0rtOGWFpwBq2EmAFeJiAkfHFKeH18wHTIeLi7DOPMRUJ97Vk3817ooeKDdqcCwHa+e7lL0PU2rDXT5BbFKMslYF3l/fycHgDgKmHUmybzKmPl4gIwTLvScdRiIeayGCUHLFr23TSb/gJs1jIywiQRpyGWtpf8M12XJFYOhoREZykp/ZRnvMsHPFaxrvzhw2f7z/En2X48zeb5bpl/CcAvAYBqNn+Wmf8pIvqvAPzjkIi0fxbAf6OX/Ip+/8v6+//AzExEvwLgvyCifxcSIPB3Avhf3nf/m8zmIS0APLMR5pBCaeHIYw0KAiy7twJVK2KmEJHNAYp+vlwvTCY2ahXacTOtXWpy2gvwcjq3Ikw2BnOYWhNYmyh5Cg71dVXTX3M0GwYZ6e3NTu+ir8x23/amEkhDhW17w/qxv2+0Z1Vlfz35e1Ij9gbqaO6oAZXYzs0E5oBMSezwqp9XNZNxRavZYjA6pAXFqODa7OfHt1FYht88L+IuPOqw3B88ns/UOc/OYm3rv9gS+fDbLZFvl7vrAnHfZcQQSJhr4tojrvb72IZYE7GEMBNvFd7Bn3Qdjff8nEFa0oB1jxnWmz5/sBDokiOezvNOJ6N5sMH4uDYweZ3/+6L7WhBCFSd8UGDObEjLOQ75LiBBLLC18CH0lUlyuhgaASn7mQJfmYoBy2ciLWnuGKXbaBT7hmsanL7mXA0CaNyURU3p3g9pkbHmc7K/v4XtXwPwy0T0bwH43wD8BT3+FwD8ZxoA8DkkAg3M/H8S0X8J4P+CuEb/zPsi0YD3oT7f/QgABvOUwcNsm8+nKRywhghkIOjfjSlBzGCnMmsYdG5MJBGk9gYTIklEGgC8UUiKnz1+ifsgMfv34YK39YgvVpGcJIGzunsIozmVacBfOymqbAMcbImaVTa7wcon1npTJJhcFQ2xuZnASH5viMTAlYbS2lbAJz2ZN/4QT4ArBkJNJEmm5cCKcM0jsSpat6cQUCKYGOUSde7avcHiq9YS2nxoYKZtLGSaFA/fPd8g79dp2o52sWE+PU5A1pICm7KzmwuzbUb8WxlleMbAm3P3OzTGC3ct0BmNBZuY9rJ9lL5Xb7YDMCTR+j6LhqWP5jEeTbF+3aNqkewv4Q7jE9D8POUxodQJVo8GhIZ+Ho4FMZXGrBt8D0ZGY9FprM/BoGxou29ZtSWn0dgcT5cJ65JEQ1ldoImfm62B7SkmtIJ2igPIUZlrZHCqg4bDa9AAGL2mrYfTXoLg6DV4IYZaMYC8qlmibO5bSGoTEVAPIiTnItrNYz7gTb4HgPfiQf4k2o/ps/lKjZl/FcCv6t//LySabHvOGcA/8cz1fw4S0faV201mY5hmWzTn7XdAzGcTacazRpYdworAETlEBO6JmKaltGgWjA8wIKBSRWk2XdF8LJz5PlxwHy5YOeEQpD5GUEplm8E0GpNELIhhL0ZeVHCFZ3kuHHKvOe1ji45lWpE/tf/4zD1o87unTepUlhLYitWU6qhpKDabJYQSUTdtXTEbDMXWhvv7KdL4G7vPxjwc4xz6+SrraArOwJRcdJ3ezH6vLEmQ3lTW4Pi/wu22zWvmPozZ59LsJXPypg9//XB8cx+ZjzvJjrtn2PyHjjkPvjLDwrO+GB0k1flmzPdQqzjed82a1r3TNrbBFOO8rpM+27SUkQhAbZMqrj+vNpXOwWXyN4xAA2yNm5vyeK0xsXabQSLAyKAYjdHY+2Am4wYeyyLQrDXiVCa8K4dnhZefePuGbvNNt9s+G7JIr9qwiKxtGYQn8gJxM+FtOGLliBfx0oh+kxpRJaOfRu3LtKO9dh+WZl4DhJm9VGRqa6bRXGrCqcwtB8fmMYWCu2lFYcI7AJwJdI6SxAlHL4sSmgUOnNOkfPvS/7XXZ3i5dubhifaGkJgGMfqF5Lc6C04TT6zEpmsaQ0QTSMR9s9FvN65pS54x2Jj2cJ9sXMajnUPVtBn242hz7/cgz9Aw9tOv3fxuhBNAzRJwcsuhbyCdBjmzN/m6c/2QoGjDdAzoOfSAxoTsuAsA2IOVCS2QgRph5cggfZakWkwljH5Eu1lkQb5261+1xAUSg1Np0r1dAgbqGlEuESXoPQIjJnmHmhnWM3NjTIFgcE6WnN3Ma1H+Nt+VRZ4tOak2weCyeeC2UbzQo4nLtDXACLcXzaaq5pKgdYAUiNVKbLh3sZ5SX0M9NjDXIHWuoPMzc7NYLBg12n4VGJunpwN+V+vlvF7umrn+gza+2rbfmnaT2VgWvgHfRaqCOwZcQXoY2mxVZhNRBVYCWQE1r4mEwGp0UE2gBxg0IM4b2boRtWlf1iRKpgcp7N1TIHPs7ZKIq3jWd8EVwzKJkUonigQ434h8XJmfGD1M2k/baA1Bs7L7743RmC/GmE2SY6baGxLyzcabMQ1awzjORvDhxuaFcLo+50oz2wixjjXvStJDn7T9gbt0q39bkipTR2LeNjJ/lMt032MSwJgYalqMnx5vzt3C5m+m3e4PAFtTnP9tXAS7UPwTwcKzfdls+04AxYqoZSPapaXLNBSEGc2K9t0rz6KZjJgBcm98GzPwvMZj67OZi8eRs5waY6jUtKhtZ05Vc9qYFbBr5zA06EV8Qk0uUoGKAFT1vA3aii9MuF1uV3mTLOycWcoumDapAxYTM0kQwhLxLhyacBHDhzejfSc1G0AIegO3tGPO9LXVTEQXBY5hRYFoHTVcO9a8ZmQOOLm+NOToCAl39SjOdm1FZ2qDKS4AlXLrzxLeetIZtwTGqhuNA6McRdKsR4kcknh8q0eyoaYuQmuc++bvPYlef2vmsAAF+hQIE/HDoFP8rUZh4xikNv1s/hop+GR+mH4au9NVuvPNmJQ3Uel1rYyAoSp8lRfCGOhWwjTCpfMwwiS2+Z3aPkBDRGgRVNZ90y4iOBICSzE7k7xh5wDqX8GgIdlvUaOT7BwAQ7iyN50Z4SHqQKfdN7OPMpCLhO1bBCRlAicSPyGqK3ZHXatTomvEsW0/BUllq48EiJ+kEhbI+YE0XPxQwKkKZliWa/ISmpQfoj0fDPs3aKi5MRQfZWfza8XGWNIa2np5IcKevflH3MMTn5Q8/EHAaQJXj+LjJaC4filW+ef2R5NVdgQ8uYYxHaW8hEVjZpuP+jvbu2XmNP3ImpC+1ueF35+22+0mszECHlAxuxoS1kT7EEmqNmCrIPk3qHi48VyMgZjZyx835mGa1KwMzQAjV05YOOkY5FxDgI0sWGnn2MOmE3fGZsmmawmoZq8N6nSfKnAnzlReJDS6niOiEUMVurw7AbjWBlrb0QC82Yij/Ct3VZjMoSCqmu/fVbCUAACjl6C2F9gGAHREgoyWH9MUESPk3lRGmzfTm718Y+pBAQPDcvNx2lSTRAdVZ7zuStsyQuFs5lsG2wrdAT2hM6i0Sk7S1cRPAWHsTm5fA2eLk1Zq9700oq4htf1THmCItYWTe6w0AK0oV5ubPssWaq9+Aknk1ZBzFd8b0TeGY9TTh+myhOUOe8DuV4GKKMzmoDV7pgJMwHqawEsQgppFY+IgGoKPlDNnvOUS2W8t761er538C/DI1+2h2tL4/Wot6E3d3Nte8GZiRivX3vbdQQMCAFCoosUp43suf4gi43BYWwVfm0vJPAYM2GJYF0wuURYfvn0XNZs35d75SCQMems+W9nDxsiDMtPXNt9hey0gjAwEHLEOEWXeZLfto0qGV0d2ps6sLIjgJZ876kBNLUJtsKdHRrFsbrVn9+g0+eDEKLOq1gXXUpv/xMhM/G9mGqtRQTUJqAfvhxECWdfQXzT3orKXugZi5JpJxHtNGV0z3bUX+/qZXDmAt/ehncOOrlwzq2f+3utrWDsnqgrXVdMKd4LiGHMfv5xjYdHD7UirUIaRUexB91MQIFPDSTNIGnLEOIQ6oBcwcwfrdlqY3Fv2GkdGTcr4jRnqJ6XqHOxiGgtpJKoUKxgSpt5ahdi21LRWmYAS2sOgVMGzEvW5axicg/gtKgGpgqYK7NQKZJ2/lGPXkGdd3FyDMFTFKGPVrtszHAQLp93YP6ALG9tnb4zHHqT1W+VdocgIFh+rl9Szwn8U1SAnqUlDUSrTeuSBnArqpOuy9NLn/h2wfKxt5OGHat9Jn81n6wvVHBg1EI5hRYTXMgLWnetaiecWCWY7JV/7eogRMQYK+HIGdq+I2hiRRbtV1XImRcEyDSdANK6VJTO+Qqp9vq1HFAX5DCSmgjLXvuEDIyizKRoNUydo5BaDNmBbVmfGCmJ5RrOl+VVx1nhiYTJJNBkKTvLOAbyE379kwzqmugMvA7SXtoGM7jDL3T6ZbzKxK4eHZ4rPNWWovLl+l1lb9jhBQ6WlqqQxGi+ZWySVB45slkgy85rhwY1T34W+cf0b7Iu1EComNaP53BQjTLajzQEvTFIEGEbtIczkEAlSF/EJQIi1JeQCQK2sGoQwHuPyxAp1o99rDhJUoOa0qOWRTWupJWB9moAlIDwFxIVQjgH1vsi6HGX9GuNWs3Mpvg6O1L4xP1rJEXWRwoqNKWwEEnueMhllxnaq3z+2B0wI1MAHvkjiMTKBa5S9rBVPrSganSLCOSCegXgh5BeM9VMGpoqXhwXHtOIcJ+QqlhKuhOzNw02gk3+1drO7CRw/bV+/3WQ2K0dEri2EuHBAQN3VUL4uOJ0PSfatGhNzt4hUsSLuajrD/Z2GE6EaEAUFge0dSsKnu9g2uzdX6GYnJeAKIA0A3WzGPTfFiCQr8TANokWTJSnn3MKWt6q+mRlaFvQ4Nvl7q0JdN1YbP3tm4sY39L1tvsv3MCBbmyZRft220WQGvxIBexn3BtXT/TTXv3tHNgE3nfQ+iMBrKN7HswX79H/vMSXbV95UZ321qwNLRNdcEaaKEAumSYU4h2Pm59OQHrw2YPldFdhLqWO2zH0dn/phQmCh15HBLBpPAVp5ca6EZYkIIbRaT8XKSpupFbjKwn+27Wm2e4/Q73nSnCL9NwQz+POrCGkiSOk5iSWgBgEcGeUozCooIKpB5uQadF6ijbVtpZ/eZNvX9BtgNN9FzeZUJkRinOskmkfQEGfuDMc0B/k7DOavoI58C4uuCACPDMOYizGfi8LMWDEoX2ral4MFemBBgeTZzKbhUIXVuzGtSmrvJEGdVfymaiq+SswUGcle+hzEZJGBeKbmC2FCixRrTR2aYiKR79Wc/0eVYJMz0bUXTkMvjdmUMe5fnpA6SZ35q7UNQ+IohKUl3nrtQjOyrdlLtddP+5s356P3x0oQCFeP1PXFA0P213Vm7OYG9Ln6mzpG5DXBptWYRqLENLmoqL3mGVJSgu6RiwloxeQANEibQGjltbdRbh5NuigRM6RqOY4mAJip6u7hgo8fTojEOKTcgDMbICqAJUeUGpAzIS+KbqzjiYfSCCgb5NAaRgmdOlyRYMpVpFhV+xJthO/lveEcRGsohPW11LLCXPXdqCLL2TrHimnKbc6jvwbdwe4EqY5o7Wo2bWg3256IABIjHjsX5er6tEnmAM4yLp5kf8RXazOTVmhYfBINca0BZZ3wdBE07PNpRn1KQO4l4UFoQS21ilXF9tr70BV+2p5vN5lNrhGVuKEtT1xaJcyIcsVo9totbaQFFdh3JmEQymiK/qtUEaDJpErdRCoNrdaNXGvaV9gdj4VfX9ldG8FCg1YnI4jAlRTWCKUjnF6TkUgzIf5IxmgqKIrGQV5CbSq7+65D6mZrDQP+Kq2NSQmbIi+3nIqv+Z4YU+ranLuPrc3vo99xvDY2fva35nvYsc7449sWaN+p6xmORVU9NwXrw6Nn7/X1XNtG4xnDTLHimDISVUyxNORtO9O0riulRbW/hipdCaxvWtNwPO135sOO6yZAttVrdECP+LMpZdK9I/kzIaI/C5vfcxM3pkcMkOxhImrIB/4VJb/v3cFBo2n2ZvRNx5D3SYiAmFi1HLQPDrFnZwEixTRFg2qyT8YG/+8bVjP2lfZvRbtdqTNL1uxdlBoZSL00s2cinrCbmW2b9Olbi2rjOgQYAGb+YkArcN5qgSqievJWTigIeFuPTaOy6630cb/OvSyk5het4XGcxQtVSkCOjDolceJHABNQE1DunWO/aR3ciSN1B3YjgpVQV5VKt0l7nhg1sxKPv1ukzFb7GBYEEoHFlqMi0PSysGN/gi216cA9smHDq5biSw0IUaDxREcL+le9zhET41zCrHsfhA1yQJuXajTOTxOcr6RNS30jhak5om9lfVsUWsO+I5aoMe4h0pJHUl21pX5toF7TZfTZBATqaOdWfsB8CiGIH2VOUrE2hYpjXJFrxEnHu5bQw6VZrknqmxDTVoeeCUFMxpEIdNTnruH5ZoqbYsHd3D2sBWgmJHumMRXc3V9QFEiz1oDyOHXtAUCZKvggD9JovgUOsDEWkOw3RtdwlPFwcsxD9wKtOse1vxusuIqhhZZDGKq9JoaYYJF9QUsfJNHkplRa2Daz+Fw8nl0LZsgBtEppkbiYZqVrpzQhRkkYziW2ukMftH0Xmc1SEgJVnMrcIrsKrOLltUazxQ0yE1jZUkUGtmHU2+sKb1/v55shRxeOONdpgCAZztlrZqjVzWUO35RUDY8uH4VEYzHTGJmDP4yO6mFsNXQTiv1rzlM9f6MWWJ4JOQmzMRAdx9UcrJ/G8NxxoIU8+2ggz9+uJCojENv73HT6u2uHY47hcD/HBF9/rzbPq3vLP2/OaD9RX/uGJqznFd4PljAp1/wspIEEzNQLyLl7tbBo58choJnf7PeoiaWZRHMoZYR36aWnR61K/vX3xyNT2ziSYpzZPdcSpcgba/IjVPNiuhLUiHgwfdtawfmSQpCqoCUSUqxYc8TpyZVPZoCDmuy2/qjhmbt92gQkPRb670TQ/KAwlkdvz3sMXS8Gf2EwTPbqKgIAVQuSwKDFiVmyj7WN2b+TFm0a4EwK/jnd9v/9RNt3ktnUCCDii+UOj3nGpU4oHHAMKz6KT9dSY5NgKgoiIiRabS94oJnfHIwNgAbKGdGT8qyJDyaiCnpax2NDL952hsCEWx0bMwHmGvCuHPCYD3h7mbGsyTk8+322md+cGNUB6tbkCLjlvuR9RtZgz02a3yp7o5oAwGGbXWk+EBOEXjf6NtyJrH2gmxhk4DQSgb3xeh5IGPmKXu5NDN2pvz8vL+gaw9kGIewpMo3hVBoDKeyyjY/AF/wSwsftvKFf6uWeqzGsRjQrmHrJATvfmhdcPAhoaftWmM3TRUpYnJ5m1Eefro8WWVWj5II8XWZ8ESoOsSBPoZnRjFEGYqSUG9Gc1D+Tq1VbjcgGWSMLp/PrVJsrCTgmE3KJSLHgbspS9GwuWFdgPSfwGnAuooWlVHCcV0nUfCWo0vmcgEWTSR8TcmQ8WSBDqG39Q6rDupPVOteljEn8PUbE8xqxYgJniXKjwmJ6Vuidu8MKS9CtDJxSRc4BUSPtlsuE8k4ZoprCSo5YcsIURRPMJWBV/9l50eiyJUrE3v/H3pu9WrNteUK/MZuIWGvvrzvnttkpdk+WqBTUo0WhUvqi/4H6pliPigpiQdmg4IsPouRDafmiSIFQiCKFDVKColWUUphaVMnN22Tmvfec8zV7r7WimXMOH8YYM2bEWnufk82XSZ6TEzZ777WimRExY7S/8RtZvewApCOq140C8OSx6D209fRH+Zrf+XgejaacYg/zUF+84DLu/SQ8ZShXCfvWSi2MTfIfuGYO2OdP7Hhlsx3p8aywS7wYAw6AHRbdZtFGae/TAefS4ZIjLjkiFY8xB5xTh2mJ0kOjIr/kbTCreKMTQkHu3Zq78I35VRrraC8T2xDVlaWP6k1tPm+D8/vj8fYzck2BpnkxLQmjXhdtYvgEI/R8qnZmc+q9Q7qf736KdP1VVTho/7g9WkXb0tW0BsFqz6yFhVoX2MTnV8t1A1X2ZVPoKfkDfdrl6ezixpshVpr6rRdk4ZppDkKx/yEifvASltEwbDkoL1cQpNU8BZxch9lvYf9i8Ih1PsSEISREl3EfJ6Ti8W46YMoepfQVhrx6fOrFaMHpMgeUrH1+skPXEe66BU5DawAwnzrQ6MGZsBRC6RzuhhneSU1KLg5vcUQuATR5uAuhRHXQPcMPaeV+U1S0hQ1re2mdW9cldCHV67vM0rCvOCfhOgiTB7xcw9BJEabN9RATGMAxLjiEBT873eMzvJD6tFMAZSmATslVr9RQZ6wUNFxIINSWq4GE97gDULh266VFtk2EqiDtWX+sYa/y13E8z43WSDdmae98ydKx7uwltNa7BZawB1aF0yqSVtlYT4ha+GlggJ302oe92hADFKVWPR12FcV2zl1tHS3tBTzmEqo1OOWwWsWNENy2wtVK6ey2tQD2w6Rm7Q2JawrANYJyI6Rbj6SNJemxnVa+7xMg9drbm6T7FKyTr8eRjdmvn/N+HvvPLWSzU2w3xy0F+txo9XrzmaHRKi2JemU1Z3Xj7WvsmTXMBPWdqPFoaJv0X6nzZY+2v0sNM7bnYqn3oqAIRc3nWCdJO38NIVl+pohSzx2jgjM031SfvVrJOUvOZEyhngNYAQmeGIewYPALXsURUwn47HKHOXnMUxDyyVr46RBCajw4BseM4qki0qLPtc5IOpmSFHwGt9a0NKFBIkH3HQ4zJmKkwMiaj1pbbsi9jP0C7wtS8mLMsQj39jk5x+iCso7UEKEaCPYeZu3FtHiMc9Rnsq00HUKSe9KPWF46jHPEOR1EgZA957UtutUKLc6jZId0CaBZEGi0NEYYsHanDbKGOAmy0BT6Rx/fRGVjpHO5CBPzmCPeLwek4tG7VHvRiMGctxQ0EAWwb0kAoIa2gJXlOVv7512uJpIkUR14Lfx0CWiU1VQi3qcDphLwW+NLjDnitHSYUthAWB1xhaXWGe2sbkMupcXLi1JWwWWCgipcGSI9jbuqTcK3hIrtIL4m0lylfYU914VvXtPeXTAoqTlVJpRNqNeeJ7vr3CsJWgW9vUdsbLyt0rHzt4TKjCtkXr2eJprThtuqDWE1EX69r/Xyav/lnfe3uwXbD6gqHGAVYBulyhISYay5l+JM4PFNy5X9CnWei4SiLpcOWXMZ8ixoDZEaUSoxynGHuNiBNKR1t9/W4OgImnPoQ8LLOOIuzPiF4R3epwP+Nn+KcY4ojxH+waMcCsqQ4fpcvRqDf5tgd+rxRC+ABADog4TTLrHD0jmFN69dLE3ReVfQh4Tl6PHuMuAUBpTZgx6CQOqPcuyXxxGv+hEPc4/35wPm2aNcugqnBgNLKCidAxPD2/tEvHnWtEiOqFDAKfZi/Klh57wg8F4dRrwIE+7CjO8eP+CL6Q5/c/k2cvKqbESJDyFhUCmXisN5jphTQHrXwY8O/qIkvB4osTXYxFBjdigOyOTX9fRVjKvf6WB8Mz0bG0TCIlC7bIJwLh0yHIayVGHRei0Zq+JowxNOUWa1/qVRNLdAAwtLRbJ5Tr529lxzNQv72lJgzgFz9lJLoxxoKTfN2yy80hSotddZC/WqZb1apC2vmPWM2Yg9E85fthj3IaxWcbXCfS/o2+33vxkiUexDvvs5hLQAACAASURBVLHdrf1JQnJX39nYeSSk6KIvvcwnHLOqfOzcTY5lDTE+cUy7R7e+sgOzdZq8sc1eqLO4Nq1T2FaIb4pEAUQvMOEpZJSuWauMmrcjVTTs3BoWveUF7hQb7TatcGWli7J2HL2TsNoUE859RkkEjkVbFZhXLi3BzTOxc3i3cq9b+2zz1ur0Wu9eP2+byUUvzdjAkHtA8kxLWY9FQFVyOWVhxhjVEyyEOXllRVBFrgo9xQImvW8ZQCi17m1TxwMxgB9Sj85l3IUJxzCj7xNmgrQ5aG85rZB1rwgzREbpWIu19Xk3BLtMEEVavT25v/SxlQ3wzfRsbLENPqHzSVxrMJbi8dl0L43LmOQFcMvaPK0qmeefiikZG0K+KS+JJfXFQwpwxOhdqsWltv/EAefc4d1ywJgjHpYeUwqYbvRDByChDovb7hawIX0AaA0CqndQa2bsMODaRnZDad4CDgjr36ac2oZm68FuC1ELMzWHIc27gHHFRi3MBLQtoGuVDhpPyfa74W3UaW1yQrqtbWLFp889YtuvPWy13NQrUxRRvdZ6Ll5/634MWutIGkUswpSaW7hVnk/1sGECHAQ9ZgnnZYnIk1qxysTg7sTDuCPxFg5xweUYEXzGoEJ1ydJh1ji3xjnWfAnPeoMbJBaAtdjSF/RaIGkABYFFFww+4eAXHNyMey98f3/niy/wMPT4oS84jd2KeNSwXM5AIifrWYs5u5ArTLswYcke56lDym5tiewIRpORleV4Lh5BgQkAMMQEdz9iTh6XmGv1fV48LnMU7jGf8b0XI3JxeDx2GJeAd+/uUCahs7mkAb7LGA4zHDFe3o2S/O86pOSQF0ne93czvvPyEb1PuIsTCjv8xuNLXOaIx6nDD9In+M7dI74/vIcnxndePOK8RLw/HZAWX681uoJDWLBkj8l7FAa6lxPy0WM5B6TRwY0O8VHXtGIuSs9g9RhDl39/Qmhf4/GsstnDJx3WxVpAgFbkGyNsdFtl0459bxEDCtxqPXCL7K61sqRwkzFxwFLEqxlzxJhj9WhyESu2FLdLJqvl2oRATPHsEU4VKqULsJrz1euR7RlcQ1pPjqe8DOBJa30zVGi3SLP9/tLdgRuv64nz6ed2eVWe1zk25l2bO2l/N8cx6/YrAXX2nlurnL/Kvpv95EMj57y1/VUrZuB6+2birNB0tkJ8tdSt8DKoZ16YpHYlSO1KK5BTFiGftXiyIqkryED/1dCdKQFgBcO0cGgjwzVATCAJkw0hYQkeqbCyFXCzhrf3tYVZ2/sqzAS+Fja270EuBCKnNUNrfYonRjCUV3TImbGUIMn37DAuYb0enSMBeGgIRtleq0JXHTiNksj+NtaDwUtHXqudMS/K6mekN1ZG74VipxQhWzWYuM3f3n8BUAAlirLkpA3jGGseUQl6ScEKv2/ja6rTnlU2X5wPYigPhAM7HMOMOz9jKSLQxxLww9MnV/vZy7Gvd7HPAhX0LtXP9vt6ko54vUsIlDYknYUJj7nHwr4izR6XHj87v8CcPcYlSLyWVgoTCxN57d3BgCywKYAmB3iH4hlz7zANQWlPCrwXZtn44CSmGwQiWQ65sVLVKq+uh1rkrRBthTfwfAzqiTBW+3etQ7FTaOUzFqqKqAp/80j2eSXdrz0n7f6362Dz0FqnrVQjeB1PkHU+IdfrcUC06jXzIqsbZcpi6+G194RIBIJ1zrTEf8ke4B1P3O78rJPKWdaM9H1pkuXqydzFCcewIGqnSAOcfHE5boyj1HCbhZhRysrJJZ01UUMyPhR0ISFojgXQ/KjOdVsnRnjIA86lw8/HezwsPd5dBkxTvELdybmlxcChW9BZczNTaMoLNk8BafbAxcNNDrwQyuRQQsBDcfAhY+kXxCDeijVJiw21T1LOtJI9pkvEeOrwOCRc7sTzO8YF0We8fnkWL0qh3QbCWZaAy7kXxNxjBM0OVMTJHjPh5/EO0Wece6k/mBaBcXt9R5kJp9TX6Ef0GW+OFxQmfOtwwreHR3w+HfGbp5eYk8fp0leQCBGEQbsTBGrSXKWEQQFEhgul0iD9fo2vqwP1fJ1NCrV4LLp8tfhT8Tilrr54AGps12m8GVg9JIs/dy4jBVc9pXaYsjl4oEfa9KoZFdZs+ZlLjjiniNPS4zwLi+uyBDCj0lUAa+zdFqezxDALBbkGuMEkMMlIDQliBtxMlSm5MIDhK1rjm/Ba89t+bpXnPCEU5bPGfXC4moKxT9fkfqtc6kb6UxrHZX8pN3ap8t68inY/PZCd88lreuq6qh4jQWjsQQ3NOZ4aBFQi1bU5lobXnj23PHdrvrWhEQIAzZd0PuPgRdmcfEJwBUuW0BGwGk1tTZn3Bc4RiuNKvd+yVzvlKbPWyvv3SzqErvVoEwdccsQpdTgvEcsSkNMuikDKsKAccdHnyrvWdhE1KDQnB1JeMC6WsyrIiyjNRbuDelcQgQocQHHVw/GeAS5Y5gBMHgsBlxjRBRI6HldwjAtKWPNEc/IYc0TOhDR5YHEIDx5uWY0knjymKaJEVwEObY7JUo0LOyR2VeYco4Tn3vRnfNKd8H4ZhAsteaQlgIsoeinIVoXjCaXjzXOH1+9pjYr8voxvorL59O5c/x5TxJQD3k7HGvNliEJqux/2MaHTRWg1A6aIzDrKThYHcO31OA0VnFyHd3SQSVZrUijxxhSR2EkMNgeMKWBaQiU/FEsvIwR56fp+qXLG3HdAqDeK8g2aVX+5dJi0SI0Z4KFgfr1axjVC2DZaasetMFMroL9sPM/Qsz2unc88NqLaDgHKYmtFawbBNlZqqQrXQ9xwGizEZprGEHhGVmieTW1hDaXGee4aia+9IT0HE4R+v/HGWu+NGZqvajzI9nawQNVFKDQAAeKVDJy321dOBqaKFCOnrNzVs1mF8+t4xptwxutwxvnQ4bPpHj/xrzBnj4ex3+ROrtiai3Tl5ELS0AwixFqPQz5jOEXLLcXh/TzUvMngF8w54P04YLKiZDWiQlg7a9YcjQICJjUabVRYs5LPctAusZ6FADMyQp9EiUBRXFOHcY7Vy7HjeFfQxYQSpFA1a/O/aYxIwSmdTqkF2g/nAfMY5F5oHx2aHdxEOP6E0D0wzt8lzG8Y3BW8vBslXxaln9Z7GjAnazECXFLE59NdlSPmITpi/MbpFX7w8Al+/Tc+xd3fGEAB4G8XcM8obybJPzlG9oTsGCVHgFmg0FjXXWWlYGyYvD/KuGX8fU3Gs8rmO8cHFCa8nY4YU5D6gtzWF6w1BrWbIRP8IBQR0xI2yoa7BQxx4+fiN4gXQ85YmK0FF7T5GnsJc/3RzpvK5VRmUTbZ4Js+4aicUIuGOJJjAAWuk94dyFThvvkSkB3Dd0rk12cUz0AiUHJr/ceXWTm2YNrQ1C0P4qnDPOdL775aa0QsekcVm2Bhqpqc4eZ/O439vTtHGw0U5UJwM+AUHECMGl7cwKz382zmtbk0RqNoeFVuT3gg2Anl+hWLR8REIKINbx8BK8x6V3xrCmf925RNqTREzq0W7Ztwxi90b+v+vx6+hTEHPMwD3p8PSKmxut3Kl1Z/kl5s1Muka2ZqKWjWNc+E09zhNHdVsGcV/KbAAPHih25B8OJBtOirKUmNWYtEq++aE4uevQNHrrkKigXDIAaalQosmsvp+wQ/rALdu4JDt6AwIbiCVBymKSCNETk5zZ0wuk5yN+NjB/oQJdps7DOJ4CfgxU8yhs8XLPcDpm/Ju/fJ4Yw+JNyHCQWkrCao7/6cPd7PBzgIiANY6wO/uBzx7sMR/f834Pv/ywnLi4if/cMd5lcMfk215qgEwkzAbCHUprShBRFt2jz80fhtj2eVTaehs96vXcMcCWLGlE4l4NsNIiHDkyI4edmELp3q97foH27ReNsLaW5zyq72CymW2Fdh4bsmv5Md5jls2vvmTFguQi5YvRPHgjSzfAsAVoJGTg5YnLTyXSTQy7HcFop0Q2pbcaeGT54cOwFcN27mtGbz5YN9iKxSZWpys+2pLh5Fq3S+JN5lwn2nMNgr1Ytycll1PFNzyH2Spr0GYAtEMA+gvca9Eia7D7t+Q7q9wVEN1LHvkGlJ6QoYsMM2+5Ee33ktanQFPgiNfmKHc+rw4+kN3ucDjm7G4BY8ZoHe9iHhfpgwJ698ZXtOs4JMjDKsrAYlA+OlQ1IYcKfFmDa8Yw1hu5qD9E7yOV1IqAScWry4ZF+Nuugz7uNcw9nWqnofRbAeOtxvocLMwDyHipTzzgpaV045QF+f+l47eS91vrZ28uJRHGofnTgkZAULsNWxJckVPfyyx/jaYX4FlCCKX3pP6bwhIfjsHUaWGhjSMGdwBZ3mgc+pE8TsT19i+FGH429J8t8AAFSANAti0NZitgLu/dpjgIsAIYqCIL4aEuZ3Pr6ROZuXcawx6Ll4nH2Hi48Yk3g4zBCiweJqnw+7T54YQzfXRZiKw7wE5CxSqcanTTC0RHm7m22xVR+yuL3JbXp4kONa7DX0UoR2uvRYpgDMHrMJm0xAcgjvJDacB6B0Cm88JllYCh0qxjk1ObjJCR4/iSDPjppENrZKpgrG3c20fIqN9u9MK4KMIccOu2Oi+X11g+yNUap1hnpUDf2LhcxM6dCNI+26gXGRe8u0ht9q10kGwMrcbO+fW/+/faH7j7fKbPPdRtlIuIeakBg3+10Vb9Y/qBZy7vNGlZXbbVkGQpQeMZ3yg7lGkP/a8l04YrzqLnjTXQAAvZYE4A6Ys8e78YBpEW+iVSSIwBKzILbOncCAMyGVDogF41EoX4ZB6Fm8y7Xq3aroLUz2YpiqF5FZ+NguY5R3ozhJkg8XDH7REKDDmAPGFDeosrthRu4IjwSk4KUeZhGhu0wB2TNevjhjiEnvgdDoVGSXghlGpZzJydfiS1s/PHmAgJmESPSTVye8Hi4YU8R5iUhZri8lhw/3nRiB+hC90xyqIwSXN0WmS3EYWZBvxzCjc5JTW9jh8/EOH8Yed3+zwy/8lbMomuBQOqFvcgsBo8fkYz0XZ+VJUxh+BccUKSjNpJ1K54+vbL6RYbRLjshMslCz5GzsxTOvRKDFBIJU7JYiuRRHXENmmVtLb2fZYv2/KppqiZp1rclecigZawjBBAkBREWpMDKCz5jTCses1P7mzaiFXmtnXCN8NB5txy9Zig65QGK+FtPfCMdtiOdmMrvNntufraBtBezeqq/778ZTa552P7vD2//PDTYvYX8c2k69Khrbtt1/M6enlM4TF2Eejm0jSZsnijUhHt0uxMllu6a2zwjX949JWZQdkgpuJoa3NcGk70PEQyo1l5PY45IEdt/mDkJXEIMgslJxuCyMRB5zEGguExScsk4hZwf4glDDcWuTMkBZMJiAsnojTr0nG4UJp0WAOzaW4jfFmcSEzmdkR4gxy7ti91Kft3laq0ckeRIrJTBkWc5OCinNi3YM8pD3ZuPRrv9EnzEwYXGW1/Eoh4ySiig8DUlelghmwgd3gKOCMUu5g4U9GcBcQr0Pc/F4fxnweBpwPANuXFC6gNwHlCCcbiUy2u6fIIh82Ux2O29BExIwfXU2+t/p+EZ6Nj94EFjz49RX78RCBMYdls9BLIJdq+PqcmKNX0sOhVGIgOzWEIoejzQQJFqEqoVucdM864O294pQE7kW8vjkcMZdnPCymzDlgM9PRzy+O4j3MAsNRj5KGIz7Iu1itYtfCBkvj2O1ZpkJlzliWfwG5ZQWLdazfugArupFCj29atpNTTASo+1YWek7qhLkK2FqY1XMeuscA0EU5obfrtm15mqYauW0KY36d8ua0Mx59Wya/Wybdnrm4ZFt1/6/U86MWqRaizztmJqPsZDnrZoabo5T6zn2YRHzgiwhZVNRD4KLWLicCUsvXkgMGWEoNc8BAI9zjw/TgFnRaO1aDwqV/fTujO8eH3DnZ7yII+YS8IPHT3BJ0gJj7v0mjGxKdFm8rLdB5nXXLTjGE6YccJo7CUsbAk4bn8WQ0cckedIkSuWn71/oNjLvISb0ISH6jLs4w4GRtF7IEeMSRFm2nG+y3h1ShobxCtISKjghJYmfltzcZwJ8zDgMS71nuTiMU0TJDpc5St1MSPhkOAvfYozCCBCl8PJ8GpDPUnbwxfs7kGN83h1FhjTP3BFjTgGfX47V65lywNvfeIXuc4/jzwvcZUHpA5YXAdNLh/k1I91LJCM0IfcEoExe6aLWNUMEQaEuDnwJiG/919bz+NjjS/rZyMJN2dWwWZsAZVYB2XJkAjWPUmo1W4FreJBu52rWyMqT46nv1Aqz9rpHLbSLPuNh6gRxk1WxERresFVB1joLtYAtUeudtPCNPuPYz5hTwONF2kYvc6sdsCocav7/KmbK3qO58oqa34xrQf3MuPraPJHaD6Sx6J5Tjru/q3NGt7+/+nv/me1n17Ov0WmnYkoErKmA6wO3if7qGT/V0mE3LDRYe5xkCc9WCpZmu8KkdEjyTsxz2HjhLafYq3jBwS94E844l66GtWLI1du3xmNFwSsWhkoxI3hRBJ3X3KcCBAAtkgYqGMA30GljEuBCcF48/uQcgl/BOoAUqhYiLdTc9dIp1Hg2gPG5lmbeVZlXK2Z9aE4BCMYavSSVH4CWUqwgg94nZHKYgig6y59J22oHcsCkHtemp49byxs21Dw6p+KBcojIQ0DuCaVTMEuFNKsht1/Ddb3w9TvBuI2o/L0cX1Nl9qV1NoBYUB1JT4ngc6V/SOzwcN9jSb5Cjy2p6BxpJa/QYSxNQ6qyuLVXulq5Lqw9zhlaWezXDo0EKM33+iRS8siTh/MCRjj2M37l+Bafdo94TD2mEtE56QdymSPOfd+0BCBgIfAcQKODuxCyB352PK7hNS890H3I+MVX7/GPfvfX8D4d8X9/+B7eTkf8+vIpeHZrvsWhElOueZtGOu+HbbeR3Ni+uK038ZS31HiBlAnIqJ0MqzNkhJm1OlqOzSx5mXZb+1umpQKsbUuwv6TGqq3e0WZ+upvNE6idJG99dwW+qIrjmmJod4rtP1e5GlpzSwZrDjvqeKddWWn1zsclYCYtYGTCOEmLCjIm5Zjx5u6CPiS86i7ofMareMG9n3DwS60Te6PffXE5CsJrDsKOfA6I7zyoAEHh5OdPA6b7hHIvOZhaKa8UOVbA6Kngce5xmjpkliJJQGp84Neunkv2GB8jQsiYVNgf41xrcQBUaWA9c8zQFIDNeiPlmMqaXYz+SbxCFGnz8SF5hJjxycsThpDw4vUER4x3l4PkmOaIt+cDDt2C7909AC7jcelWI9Q8Cs35FO8AAxnEhGM/476bhYjz8AG9S/hO94CFPd70Z3x2ucePPv02Hn/5VV0DpQM4FPV60RjDWNcVoYbJqROQSIhZ7lsXsVD3pQbe72qY8v4ajufpavQBeKUd77RArPcJr7sLCgSpthSPd5cDRl3oLaSTCGvvGLMeDWIIqHfRzITUStWQh1ViG7qtrRe4QBQX0aoEX4YLvhUe0VOq/WxOQy8vbPLIyuPE2QmaZRbm1+69JNfz6MGekQ8sLaBJlO1dnPDHhh/jXT7i3XKEI8YP3Sey8JSpGYoGk9BTK0l1whvB13xeN20E+j4sxxZkfErhrD9UaC3wbM8PrKE6OzyvXTS5tAqHQJqrahXhxgm6nuLTg7e/iaiZw27b/XFUkT77/VPnrPcTjXJvFOgtBd54pqWIJU5AFbxp9iiTB8VSjavXwwXHMONb/QkHJ0WFkYQ8UwqVS01gA4aMdODZwV0c4nuqUODigXTnkSNjHnxFk9nU+pDgSShcHBWcNT8jypHUAxCPxryeMXnhaivqIYWVase2CU7mmdnVQu1TkZxJLV+AelMOmpORglWYt2wAoEI1wuxdwZv+jM5lPM4dUupXbxKAu18ZCbbKRo9HYmwZgIUA9EoV9KY/4xf69zj6Cb8Q3wEAjm7GFy/u8Dh1eMuv4CaHcCYUj5of47KClKhdQ010QYBHEp7vrc2EtZD4SOMpJ+v37PhEA4D/GUAPkbp/kZn/LBH9pwD+EQDvddN/lpn/OknHxv8AwD8J4Kyf/zU91j8D4F/X7f8tZv4Lz537S1oMyBPoQkJ0Bb2XuK/Fe836sW1uVdkWzrVyf1m0l0Qh8IyNsPVBrAhTVGv7XN5QeezBBj6K5WFz/fH4Gh+03cBUPM5pbbOZs3TxK6coUGYG4Bn5CIzWLsPQVz1XtFlODn/7i2/hP+Y/ibl4fHa+k7j1YrQmQA2fmUfT5jq+bJggLDvpDaxeiykwO37j8WBWGpSlbd+7OxQ1cpcUpWZf7doG2HW0IbIr/bZXlBtPhFbXyLa5dR/2iqY5Ts3vtPvzrX2e8BwZaFtgr8emjZLhKAKzot18AXmgLELSCAAzD2jzgwaF5+QwZ+m78nl/xCXKIroLsUFxSsO+lo8sF1LvXwsq7zLG767XwJ7hPp1xOE54dRjxqhsxFwEhMBMmjTiMSVBq1gsHQKVVEQgy0MWk8GsrJBWEV1kIJ98hli0VFLB2DLXygjZXu4FnVw4yCTlzEkJL854zAw+XAXNc0PskzMw+4+4wYVoipjFimiJ+8O6TNRzmitL86DrO0vqgGxJCyPj07oxjnPGysxYDU6WzepePKOzwkAdMJeDTuzOm7wbMU8R8ipu1w6NHvoT1PW3XlWhUlMUh6T31KouGw4yPPj6uZzMB+FPM/EhEEcBfIaL/Vr/7l5n5L+62/ycA/L368ycA/EcA/gQRfQLgzwL44zrjv0pEf4mZ3+KJ8ZX62VinwMEnDGGpbnbScnoH1m1WhE47rLveI/VKGdEgOlQwxy4pkqxUsj3XJAQzk4QK8oqEA4DYySK0UMBn4z2+oLs6j5aig4vQc7iLg5sJeWBwLOBDAV6ocDSPywQLBAb94e0R/+fbo3xnCsCq81vWZBOMO+m8h+fWvAKwWu1PCWT7rUY52bZquQvlDildOmpV/1U6qRXg2B6X2hdxL+TbeWD9bhdV2+IX2jXw1Hmf+H8FEtzYr52genE3lVCzXRseBMSrEoFIYEi4yZ6dcayVMSB88KAM+EmOk468UpowpFvqQigL4cNhwNx5BBJI8lwEuflh7vHuUZLbh34WRFdxWscjQtXFAtwlVKoZX/DmxRmv+hF3ccJ9nDBmgS0vxWNaYlVardchnTFZczbygDiKQxCVvSNljyV5FOLa76nX4kYAVdFUpF2x2hmqisVAB5IzISQnjdsoEfxF6lnYMwo8xlEAFGM/1/wMDYz3TBgh4ch3k4AA7u5H9CELWCdm8Xy8RDY+fXHCIS747uEBL+OIg5trTy1rO/I+HVFA2jQx4NvDIw7fWvBhGvDF8YBlCRgfeinQHp1Q9LThZb9dJ7xoKNExUpBanuNhurEg//AMlnjoo/4b9ec59fZPAfjPdL//lYheE9H3AfxJAH+Zmb8AACL6ywD+NID//KkDPatsBvVW7uKMwS+VTiaxE16j4nBR7P5lCUhKYcMs1cTW0rXXGDOAivKaypqMRSHpJZ5dXcidImxsZOU9y5kqHbxcJFeZ6F3BfZzQuYxzEhboi9LZjHOUO0pcCxE3aCnLSZil462HxU7gmdDfCbBWyVwpFvt+8z9vaWIqmOCGdG3m0PZYkc8KOBIQSHJQ+7CQHfeWd6GfsQJsNsqiPQcDVzGy5hxfNYTN7byqx7TzTOjWT/NlVdDApo3C9kSbefJO8dZD7Z9tu1ssyIciilzvQaV0cc2+joG49sSxcNTgR7huu/atHcFp7qQAVPcpxrrM8nyzczh1q0ceXMGskN8phWp0mRKwVgVEgkwDAFZPPXoJQXNZSTBd5WXLq4GoYCAGNkADRwx4oz1HE3GQeTETSswohTH2BVm7XDKh1oqVQniYOkxaNpELYVq2zeeYgcu5x+RL5ZEDQeq8WIzNJXuck1zY4j0OfkaGQyTJXYnSkcaMi7aBv6Qo59V7Je8CAU4KRzdrJjX/6/M1vj0Dh7QAi481bkXJfxvjW0T0fzT//yoz/+rm+EQewF8F8PcA+A+Z+X8jon8BwL9NRP8GgP8ewL/KzBOAXwTwo2b3H+tnT33+5HhW2XwynITQrrvgLkyVZXnMAY9zL4VVSoB5OffI0woL9ENGeFXgQ8KLOKHzCa86eWCfhXu8DQdMU8Dy2AGFkC4BqZnOclxAd3IwoxKfxyDFlocFfZ9XZJyG2nqf8L3hA16GET+8vMFcRNG8fThWPjRyjBLE7Ycmgm1RAbzGhTVx3OafrPkWq9VYFRSwLs5mkcpO9uLiOi6M5n9mMJxAf2i3Xbv63Hp8q+YuXokkZ82FmcVfT4y1V8x+ITtIN0q6/moz9DhVwO8V8M19blxv+67SrsmZ5YdMwfidMijriQ0AsVcsbWfTynQdd0aD7dcq4cZLI8fwXUZ5XVCSA5+CEJdqfQYi6/qQ/U14A6gcZp90Z3wrPuKcO3w4HlBAUqfGDj+ll3h0nQpcCT9hck0IlHHCgGkKyPeSk1yKr5RR59MgIJtZChHpkBEPC2IUkExr4F2WiFmF/LyEWmTqHeMYFwQqOC0d5uxreUOLTvOuwDFVgbuiUUttuWxMITk5LD6uOcwahvZ4eDzoI6TVq2fUwmwUadW8WQOhwA3i/Rkf2vv5gHPqcAwzBt/hdXfBCz+Kc0pCFpqUEf609HiYelzmqPnaNU9s/Hdk1EuZ1nbQThkHNKxq71/hdR4fdfzulM1nzPzHnz08cwbwDxLRawD/FRH9/QD+NQC/BaAD8KsA/hUAf+53NZPdeFbZJPZwbPkZX3+KMqy2fGaWUDMYKDPqgzmlDomd9uEQd36IQrmRurIK7zaUc8tcJjFKLAFp2yRymLIHUURSy0baFAiDdMtvVQcTUCR3wcAm6Wcom5onsV1g10brMZ4a1VPBVqDWAzXXuReadtr6u/FWasiIbhr15h1d5WXsPO35W+v+1qU02195IO0cnxp7pbk79+aa0oPywwAAIABJREFU1VOp7ROY7MTN8VYvY2W93k6Aa6yRAW/hEd7UgIk1jVWpNdb6mjMUC7jCYtt7RMJYAQ0leS/IsC5kBJJKd+vX1LJBL/oe3WoqSEWF3iL8biV4JAZOoUNQ6LOwcfitV82AkUXa+ayzpyPG4iTakBQpakzT1osnUEHilfY/FSMebW87w8PYnbgWVEL3yQrfBtTI0hwmKXgCQKV5qTU59VnsvFWr4AfAcCiLfDmnUM8Rna/XuRhXmnb/XdjjMXU4K3FwC113JLx3xvCNArAXr3LTVZVQvWFy2zrB9pl+tPGRD19Pw/yOiP5HAH+amf99/Xgiov8EwL+k//8EwC83u/2SfvYTSCit/fx/eu58zyqbd+NB600kmWixaONLi14w+sbuvATlhdIH/Pg4gBzj8dIjBOkz8bIf0fuET48nTH3A+yBUGJdLJ1akVvm3D9eS/94XZKiFMcVN+GmaArou41U34k0vrvabXorG5izQ7MsYkYsHZYJbAMpO0D+RkS1SYJQrJL/phqCqLaXrKl4bmtXE/K2QmApKUzCc3UZ5bLTHlXcjP1ILciNU1yZQVBhzWS19Ktu5SC6YJe/Qhgv1Jaz5DvMUbtWstPNtFYd5FDtvilhf6lsvE1tbBLGIWWugNs211OI06Opm1NwNwdgG0JXqpZArdV1Wa9rmTdoPR9mTvS9YsKIoaz6L5cIFpZQrAWYXMl4PAms+hkW62bLHQx5wyRHvloNUtk8H4VnTnAtbAo4hrSwWQvwg1Ej5TCghYLyLuNz1cLGg65Vo0kmu0fIyZoC1Cic4abKGKJRRnhizMkEPiij9lbu3OLgZP51e4sMyCNVOEuVkCDzL5bR1OG2/nVwIj+ehUtUwA3FIOBxmZaBm5EL48HBcSx4s17lvf+HEWKDFSasBR+DJgQPjcfYgX3BWoMBydCg94RikQLWA8HY54jH3+NHjG3xQFm4DOTgnyq8flg2QyeqclsVLgXoh0KKKM5T6nK3N9UcfO/vq93oQ0bcBLKpoDgD+MQD/HhF9n5l/U9Fn/zSAv6G7/CUAf4aI/gsIQOC9bvffAfh3iOiNbvePQ7yjJ8eXdOpck4SJRNEY3t8oL6LPcMXVhyEPjwX5laULYIIooWVwdX8rVOs0xjzRKmDWqmpdEKu0WsNTQOOOk8RqF0icNkt9TdSuhp3P2nkwNsWjCjVNADmqYZkNqzPVX/X84GsvzGDJtgkAPFV4uPFk7Bg15IUq/DYCuZqRzZEY1zxh+3m242obm/pO0dTvbijLzTF581kVyLTOh5i2eZrmGq9eKN2fnOoK9dw27M7Q2o4m3LnJLRU9uSpbMoWlza8KZM2WpsbI9ifgKmy6GgLtfVv/kar6FTYcNk3+LMneJNvZbWL+ZOu5vfd2H7LOJ5EkqgFkL6wbNV/pGcxFEHSWuNfjrl0+HYq9rxYi006fBzfj4Bf0Lmk92u1qxTY/CkCJqQCjqyrZ1byT3SMLsUmXTG29oN6b1KTR1rusJ7O1RNIqQ587ZgcOQNbCz5S9QrQlklFAuJQOp9TjssTKsrBlp6ea47VrzbQSmmZVftysCZMxe5n0h3h8H8Bf0LyNA/BfMvN/TUT/gyoiAvDXAfzzuv1/A4E9/y0I9PmfAwBm/oKI/k0A/7tu9+cMLPDUeFbZvOpHAMY5FJT4TygDgr5gnV+Zodu2AW0+Z5qEp+w0dZUoUBTA+vLFLsEXhxLXROl57GoXQECIOEPIlRLEahWs+I4ZeJgFw/+iG/EiThjCgtfDBX2ISNljdowxREn0LgSXSAv5SPnSdm6+sj9fvRStZ5Mhz0j10FMV/quuaJTBLWG2C9lsRvNCX+H9d/mL+kIDcr3t99V7QBMmatwqgtDEOGjdzqocSV/cq2H6yehmHLZhKKCGWMwzobzWBFFRFulKPGGAB9TKcG4VM2H18Ai1r0/Nk2kB75LFyIBbjRVypvx1Hs5g93oJhVYrvN5TOQdYarXMIg5BGql1PuNbhxMQzbvICC7jO8MD5hIqeebj0mMpHtFnXGLCyfeYU48cCaVXgadUShKK0nNmJ4l57cMyHATh1YWMLkgfqVfdqOeVG2ychgaSSY2H4ogxOIEldzlrnQ1XJWoUNQA26LeW0bo0f7N6WFCPh1mapAk/oRPqfgJgOTSLAuxCaxx4jRxr3yQBvzhhAICE6KcU8Jh6/Hx+gVPu8MPHNzgvEZ+9u0ced6JNjz9Sr897NWBBUHZ32ng2eIxYfMDiOpz3RsHHHB/Rs2Hm/wvAP3Tj8z/1xPYM4F984rs/D+DPf9VzP6tsjkEw5WOOG5pyB6rINGts1rmEA7tKCb5kyZvMSulhXEoj1mLRdgHXugPLw6S1P3qZPKCsz17jzTFkSWg6V4kAwYQ5BVxI6EIyCzeYXUcfpWOhFZKSWZBacc/mUTShn014ag9Eabex/fbhsydyT0+Op5RMe6xGoNZ99p5QozfWz7cWZL2eK+vSXkS6mitpiO0JfSpKw4Q/Q+DFKuivvSe7FtSchcaEGq+CtnNrr7P925QI6xesoTLGSloZGFAvoG5vgANTXO1FmbXOzTnU80J24CJhvVIcxiDe89z7yjlWmBBJ2YidFD/bd7O2MfYkdS9z6ABmcC8KsRuSEGSqVZ2SQ5pCraIPIeOun2snzOgyOpdxH1doblvbk7KvxJyLd4iq0R2sYaH8rrVt2gLabomQdCrUWnM2NWKs+S27jwAqfNr6TNV7aWHp9l3ZrWdjd+CMNQysSp8zobgVnj1njw+pxzl10iZ7iVI/M99AjanHDFbjqzVUVOltCqKLtlm3187W8UceHzsl9Ac1nlU2Y9Y2zHkNnwUqq0VD0j1Ttg21/bNZO9azPB0mLQxztZvmZeo25zJaDYNqHvTrOflaLBe0xYB1CzTajsKEfCcvwF3t41E2bLCBpLEUADxGBi8a/2+E3uYh74X03qp5bkG021pYZz9uhbnIJnLj++dG6x21+1nI4tb2low14Ul0fZ3NcWt6wQHUdsJsh72UVrvQKJk9oSdZPNPSVn7djjtemSWAtZ2ytojYXErm28r71j1JkLyNA6gIAs/okIwJoAup8nmlPsi5lRiM+qzFnwA0RGRUJi+HSTx2lzVn43BKfe0FtShCai6+Rgmiy9KMTD0KawIIAHcH6STpyRgABPLsifHJ3Rm9T/ikP+NlHDHlgElzqVWZ5SCJfw11ZxbqGSKWWhtXcMkdeu0BE53kcyw3k4urCqYwav7Daz7IO66hc5u7RRm8l8C3RSWKAYDq2iP1MuU+otf1ZKzs1fDAugbUY6bRgxeHMwPz7HG5CzW6ctctiL5gPgZpmTB7YKG1FxWwcgMasa3NoQEmUNIQu9at1SXlIDLjY49vorKZsixgK/4aQqroErOaTNiPKWIxRApQochQVEwqDh/GHtMUJZm4KNeRJmaNWqNTRdKHhLsw45IivghH5LJi3K2v+iEsOIYZgUp9qaccUKBQaW11ICG/jKO2lqVQwMHdTEHUQY0Q21tA7Y5PKQWz3sp+e6yhMKsVsa/2NDf70c6nCtIb8zBPoT1XO39ghQ7bC+0ADvp93bax6ombnMk6lzbFVZWNJX4dVpDARnljDe8RJE/jm9YN2lq4ehpNPRbt0Ux0+/5foewsXJNF0HFx4t12WaJj6jEPMWEICXPyGLsoYAKjbQoFTtc/kTQfO3QLOq8AAbe2RE/FS65SJ7AUqRFJ7Gs4+hhG3McJL+OIN/0ZY474+ekeuRBeH0bcxRnHMOPOzzjlDp+Pd4gu4xeP73EXJvxi/xav/AU/W17iZ/MLXHKHz6cjEnucFglZ917AALkIg3UuonRm55VlQ0RA5xI6VTiGfCu81sVZxMF7KbzulD2aNP+ai6sddI24V/I5jYdpz4FtzRlrg3iiGah0N7ZO6lpSoAaN8n1ZIpYY8KE4vNT+PvfdJMzXx4AxRExM4EUAQX4UZWJN2XKHVdEYA4iVR2TAZcBfCK7BBTDJO/KHP23zBzOeVTbmoYhV5DFbgpBWaOUxaNzYZSSWRZYUGm0JwqObq8sLCF9CSdd92omk2GvRTpwAakfQ1bUHOoVtdi5VtNyU5VLMsjOIqVMTPGk/j7JP7u9HlfeNZK6W/43tK2gAT4fH9i7TrQT+Zg5bIW+7Xc351v9tSIp37QPsOEDt5Hk1jVZIa96HDd0F3s6NscmR1H3bosfmnHUbprU5nPYRqUqpCVPU/IyFYMxTa6/bHJ3dM6X2ed1wIm0uRABZ/tEMHZ/wohfDZM9Q3jJTVD4voPaySewrOgqQpoMCtFkBNiurxfrZXIJ4KJrjeHcZxJsJHR7DUs/btkh/zAOWEnDOnZYjCF9aYm2spgiSpXgsyrzsXMGxn3GMC17HM96Esxwv93CNGV/Y3ku3SZAnciBlUD9Eqo/LoMgVQWy5HCeeffVsbb2Yx28e81Oxo/oMtf2Ivj6yHiSxP6tCtPuSuWnfbN6yF7aA2v66XRPmTe3WEBthrf1vXvlH9jy+kWE0YC1kmlPAnDy8vpR33YxDWCrxoI13yxHvl2EV9mDcxwlOETCnpcMXOAprrgk0aEKWJcTAhTB2CWMXKujIO7GggpL63cdpRfqANhxo5tmY52UKKOtvE5jVeDfhyuJpVOG6EfrrXK88jHa/VivYv+2+5hYotT9vVjeuIcr7vMomV7NdlbVWIxNoUw0NATmApfaETNE884IbwMDuhQqLenp7MTUJvxkWomjhyDYcJDah4ahWkG0Uds2ZoMbS7do290c9sfo9r8ex59oKDGLIPdCCXuuxNHQLjnGp3vLr7oLDy6UaVpkJPx/vcU4dHue+8pMBEnI6LV318tsRfcYYhWXDIgXBFThIoy8kUUiPc48xBZzPPUpyGC9dBQN0nfShedHPiG5FvP18foGleCX6lOfzIo61Di4Vh4d5wKTFoNMScOhnfPtwwpv+jL97+Bk+CY/4W+P3sLCXeRFjsZA301p5r/fawDgxZEwh1NbT0POthJq6FHxBcaqgMwQksFsThhBr02P1GTqtF/M2gdX7oOJQZukptPiCTnNzizLQV0RpYORDESPIWrqb8mvXr73LNoXAKG6dlIXWPup4zhD+Qz6eD6OlINfOtHKVmXJgEehTDppgFKtoKqHyONmLJUJf+md0TorffMgbi9gKp5glvNVGR4wrTWLFK0MsgApI2BfK2TaWrym0hv0qAqUqgvXnSgBfWf7N3+1L0wi5Ta2HfYfddjcWFfH+ZDfOaQrnVob+1nHVHBPsg1iDNV9ya9jc25MSa8gDq9JpC3GvgAc7pWwekc1Rk8Lcfm7bN+EzbiGymznubgeeu55meva7GD0+am7BkJFL9hgpVhizKZAC8VpuQV/Nmt6SxK4MD5aYN+vfEvFBc4uO1iJpR2p5q9eYk8cMgCNhUjhxYuElNO+/sJDb1vmokde+A4C8xykLoWdwPT5LL7BwwOfLHR6WAefU1bBZvb9kDM/ygKh5jIVJwBeNh1e51ZS8s7Zvr2vz2oP4Mk9/U6BsxoO9s0UKPlMpK1dcblpRmHduIVoLnbUGo2MN0+3eIzQyAriWBR9rfBOVzduTUEz0MWGIYl0Zl5I0kPL4Mb+uCsAR44vLEQ9jXz0gKy7rfKo/gCiQJVt/daCPC7xjLEleIoufE1CpN2ID6bTwg3lQLYDB0ZoDCg21+5ilS6KLBVlzBCVC4rCVLw3XAnOvgOoLox6SUV6Yp0Ko1OjXoa71ZdtU9du50Ci8zUJvXf/nFI1aoc6mLdvSorgrh2uLXyT2mkTVEJTVPYEA3yk5qiWQk0dJBG4ZP2tMhZt6JqyJ3/YiS/M3IJ6Odnv12uK4BDlIGYPqtBtve6tMaCccqnLRry20SFzzCHny4Eg4jR2W5Csay8JnLQx4G05b7z8zYVzCJrTWxwSviesxSXfKuzgj0Nomo1No9Jgl7EXEuL8bkYp4Njk5pMkjnSLmLmNZPLou4VU3IncX3IcZvZtxSj3eL0MN48mxkz7Kde45E8YS8evzG3hf8Junl4gKPliyINayzsOQcl5Zo60Svw0rTils7osJ+3kJmMcgbTyWXeGyeqdS/Lx9Qdg85Y0xYet5Z8DYNsnh9MVB8m/WGlvPRY4Bg5I3z6s5+LpWFeZORQhtXZLQbu3/tCPp/Fjjlrj5uoznizoV1294+6iNlgR5IpXGc/FwRl8DcaVTloXpi3YQ1BUiikB4m4acQORrpXJUtmdmArKr4bPWGrTftdBUoaQ2ChMKSQdDUzSWIHVKtVPhnI1gYhW8V7Fce/J7Gce7v+1FulJKuG2x7S1tOxd2iqZ+d2Net+Zwa+i2NYrHq/P15LxuHEMKEHf0Iy2CrZkz7f7fwMFb729/crf2EJGh+Q3HVQHWKfF6uKt7c+sSrrxI1HwTa2goNdB7CxdJmE2pZyyh3RzHkTBopCQegTAhKz2MKwK/b07eejDS86Yg0WqsBV82xaYGjuDkkJNH9qXSRwFApKzGlhhdFRRDtDmP1RAxQxBihfAw9rX2x3IzRZUNBVGULQN7ubHGDa1moALzFCuwIt94IPW9Yl1bqB4t79cOtu+EeX2bh5DEsuLimijFlmVjw7LQrsE6j1bDQRUN1h+PNUT7R+N3NJ6vsxkkFzNEaR8waDxbEpt+E4e2BX3XzegU8uwV/38MMzqX0Lu8iTnPWovTrp2UpRBs0f7u3hUcOqGYiOpBtaE0Yz6y0EFhQiKHezdJcRuVauXVHjz6ErQNxmqr6FZ41roPHbcEmVFsWFLc7be9YZGpJr2pWNrxXEjPFA7xJuZcCyT3no6+eObFVaSY7adWZ70mYiAwqM9wYaX5MEvWuQJ4kny9vrSrklEhYh6Bd03NC22FhUKeXczwMWsNiSo0rey2Ql9mt5IlmrfS3OJ6x3f3syomQx0Z+s2v15+S9FrKyQnZayHJL9x6PnY+RVTVzxqv6mxV/V7aZ3gvHoShpqxdRwTVUHAurpJGGg9Ya/BsQtisORVdcGbQmXKx7Tq3RhfuOqk9m9UjOcZFFKL2rHkYe5ymCLDQQQGA89KG2coOHDFiSALUUejznAIyy7tbCS9NkJu30UDGQdLcze7LoZOShAfHSItHGoOQjN4ado99c2yLENRubfIwWFtvtF57DQNanY2tg1pQzJh7PUeQ3GJFMWaCG93H9zy+pgrtWWVjFP9WVdx56WlTQAglC1VEEdfbPI/qSTQeSaCCSAW9SwhOityEmNPXpL0t+MLUWFkE7121rthr7qgIYYblcGyYwrEWtl5Db5EykjarqH3mW0iyeTgtTNcO+5TXAqDGmh1WUMEtL2T/u9be7Ez1p5TOZv+dO7TxcGiraJrNKwOyvVwmKM26Z14L3kxpakM7r/2CKtU6oBQf2zzOHkBhZJWgorkXAic0950r/5nzAiV2jmueTx6jE4LXpnaHNh6juWqoX9Zv2vvJqGwJm3ugG3ImZCKU2dfmaDWs2B6j9RIJK6quzo/1O8k9liCeilNItPWVsWs0SigrmE7JIye3u0fb9bf2m5ELWHM31Cgap6CcrJ6OIDjn4jEFee1bIs5UHM5zlLqiQsLbB4AjhG2BGETC3GEUPRZSN6+pdh9tvRlV6C5IYt57gY97X9DHhOAL7joxapfkMbuCkgnlBpCgPgM9rouSdKteVLIFAlmTyuRMieAm2rzjJRAqD6INXfdWT2XKsLbvnjwwNyG5jzToY5/gD2g8T8SpTZ+GbkHwpS7awq4u0LVxk5H/bVs3AxJqS+wwlVA9m4MX6PJRX4C303HjIcWoFplfizH3SJ/KOA1skq6BhOb94BcEypU7yfZ3oSB3RVpKFxIKjCb1IAdv/96bzvb7S7ye/efc/N7Hjp9TNJtzP78hMdYckp2LIGi05zwpexEBIbAMjO444/X9pZI3Sv5hZdJ1jpW9QbxT3oVMjMRwFUa0Ns6jlWXZGnLV3J8rcLDn3cThgY03CmCL1tuZhBXJy8Z4oPQ7oFUxFIAh1CpEkMZamQBllsD+sGReIraJat1ugyZkSB8ZFW4xZrBbw1tjlp5LUwp4XCQ571wBAjDEGcEVnMcOyyT5j+Wxw+Ijfj07dF3Cd1884lV3kUfmEuYi/VsAoLiM4Ajf7h7xIo7KISYQ6/fzUJURgMoIcuwWpBejdOfU4lmjhjJWa09ci1cPQYzGMd1jyR7zFFBGv3oaWO+NheC4EFxxyIlr/yrLd81zQMmuKrrNM2VRGoefeMQTkAcgd0DuGfko+dYy6ANXL4SSGgyMSoPEneZhOvFaXCjCMVe0XT0xXODNuoxdgg8FSyjIZqB9rNEYil+38TyDwKPAL8tRXhSvhZq5SBgNWBVAcBKust8Aak5l1kJLC3kZtNSBcfAzphLwuPSYEOpDHmLCq2GsvdYLpLjUYMxtMtZhFVRW5HnwCw5OmitZh8M615BROgdOwq/GnnGzkZZ5LjbahXBL6D/lX7fHuWWttQLLtnlq7ARf+7d5NEYwWrd3Yp3ePGz7Qlsvn046Jb6+v+BXXr6t9zkVh7fTscJ+k8b7rZFXElx1tfxCEOu110LJpbgqWMx4sdF2VfVqMQdXkOAqg03lydoL/13EhXTbqmTsvqgnyGBVxrRy4Zl8LKZoaIVZN4KTCUDgNQzT1vno/tTMlY1PLBLK0aGwCXjGJUVctBh6WkSJSyO0hE/vznjRTfhZuMc7HDCfO7gHrVMbHSYvwvpyF/GyH/G6uyBpc7XCBBdFob2OZ/xi/w4Le4wl4ly66s1clIbKsWx7303og7zf50WUlpUbRC8NysyYCy7jVRwxlYCfne7F6Jg86Oy3IdrKcweAhLE8ZzE0cloN1ZagllOzsFtFvhBe/qDg/jcmLMeAfHAYXzucv+uQB2DW5nbV2FLuw5p/8QB3BQiMMCRpJ6+54pQdljnUBWRdT50avt4x5ugxK4XQH43f/ng+jHY3g0j6mHdBPBbrEdGyBVR4aP1Z619stFQajgo+LEOlyphKWLmOUsA8BaQk8WtjFahUNhDFtiJm1r4hrfCyugOPApCrSLao1nYOBSkUFIvP7osK27DVzkqrKJqnrBAVXl/ZW9kPE67tOW8dv24jyowJNcnapprYhKTuS0WLKHdWuJ2vshFjNSZqXxatv7BGW6UpUiSIt0BV861QWOvSaLkIC8fZkMp2f+UVb7qSPnEvWkqRzb6tJ7n7XIQbV+qUq4Obp8e0fez1nLRNVtt3TqxkU+5sx/GMGBMO3YJPhxO+1Z+070qHx6XHOz4gF0ZSqz4XhylJHcuhF89+svCvzm9ZPD6MfQ3FGV2UEOeKN/+Ye7zPB/SU8MKPGNwCj4KFPU5ZCEFPqcNcPEZESfRjfaazcqpZkzQbhQmn3GljNkXuhQLunsi1tN5OtiJeDXmF5gFa2LB9Ziyfc2Bcvu3BvkcaCLkjLC+A5RUjdyyKxLMoK80NVsJXK27WYtB6Os0Br56XXruG20mfp6HwyuJ+H8JoH/f4f1DjWWXzd337cwAaI1bP4jQLDcacRDActdK6wi7LNtxlSsZqckRReYw5VuLApICDVBzGMSI/RiAT5oXWQqzAGF5O6GLCi2HCIS7V0gKwRayZx1M9nww44E4JOY+90GyMWCnLn11A+wQ4eAvTrFbZjX2rsFSpRHqy/bZ7eVcTz09orFvn0kppaQq1Oy41rLzaNG7NdbTHQI2tEwnbd6A1x7AoqeOcApbFb1ggSJUeNXk0BjAlj1n7pBjaSUJlK5JJeMFC7XgJqCBo7+GN0RZ5Vgey5qKu75ndfsoSPjMGg32inx1Lq23lgSN93qvXJPfSLPgKNiD1Ig1cYh0hY8HLYcLr4YJ/4OVP8CvdZ3if7/A+H/Bb0yv8v/wdqfFRz2TOUvXf+4zv3D8C90D5lHBZIn7+/l4T6REPpw6XQ4/TsauFnwBwUc/kp+El5hLwK4cv8HfEzwAAv9QJV9sX6R7n0uGz5R4PywBHjA9lUP60lUwUEAPvELQ1PBWhxBl76T6qtTmhy9IF19pcFxIm5eb9oKww+BZQoxD7tbutsXfretVnykPBh78P+JAJ8EXyZaHAH3IFEAECyxc+PeG2I/VywJCWDY0yNWOWmTDrNPPkgULIRTqH0uzgRlGi+xY8H2V8E5WNsSVbw7RUHJC9vJ83thdvxmFfhbfPtVQPCOLlOBbUTPbSTTAHPYGnlQbfNe2Z9RgOTaGmjrbAdK/08i3BvQ+VtV+p8btVNLvxnKJ57lytZ1KPtdn4ifPhaQXUnEf9i+vTX52n+b+x3K0AcEoByTl0LBBbgoU9VGeqJchALaQjvVkpcVVCW6UkSgfaJmILCnHIrD5xDT1+uYtYQ4jAlkLnS/apt0INitZLMTm3fq2UKe09u+EUbSe1Dlu359zhoRxwLl3NJ1ooOLhy9Xjs++gySiCEIKGclGWyUkMjoBmLOFgudS5eWgyUiLGIAvJUMHNAvjHxaqC5AmPLbqlgjIDXcqS3euCQU4QpSZG2VKeqtwBe86Okiljbktf3rR6oudH6txieJFLfs6AY9X7YWiyPUUJoLeLULlUpj+r6ba9r/7A0fxdODuFBjuU+NoMAvqGezfeGh03v9FQcTnMnbADW/wNWa7BaLHbQNozWFsSZ9zH4BS+DUKIHlytL8+Ohq7kAiZ2Weh4iFqta+4eYhzP4VJE3ALRdbFd5qZIWdY45ahtbdY0tGbkXuHqcvZKpgoyx9uGoCoS3gof1gO3q2eRvbgiudg7NPGxbMjhn+51S0NTNLEdT1k2MB42UFr+ebD9/BkqS+PUjJLxlII216p1xpk6S34sDP5EUzhSwOGjBZqnsyqBVCW3qWpLXRmdrqI1ZkUmJ1mvQeW9eSl5/rlpY13uJteiTcFsfqVdDFlZpjs9OG3oxVoh5VpqiPcDEHoZKNM6Ex7FHLg5/jX8Z/0/4LgAorYx4iJEyDoOEzIxD7ZIi3o9DJb50xHh9d8GcAj7QgDRcssp3AAAgAElEQVRLAYjBpd+r52j3d8oBYw74bLpH4e/Lvd5d+Cn1mLRIGpB322DSlYgTwJgihrCgc0DnE+7jhDEHvD0fsAC1b42LBbFf+ZLMiLCCWmlJsAJEQiiiPJN0Rs0MVVKNtq9rXZWhJvalu6oUvKZzAF08Xv+ax+HzgtP3HS7f4cqJBqgnzII6TCR5mWTox0KbJeMfPfwI3P8IePGjBfFhQfzpB1AuwL97Y+38Xo1vorJxJH5KVsoQVwWwJtBoVQAAKnxz/9LtF/c21KWFnmoyHOO8xqCL2xy/ttKFVit7Oban9TjAmq8xRWMAgaTw6ivKkdYzecYgvhlq+woW9M3t94Jy//tW6NuEqdGvsxFptnQeYsaxWorP5o1uXY8dl4GcJYfGnDFZjVN91jqdrJXXTJs6nXqpKpRZtTY78Y6MeNXuadEXnZg2CqgUC8NsL+TK+rt1P2+NTQ6o8WQqSzcLvYlNrLUTAPEY7f7X8+1N8v3cVMAxYclOuNVy0GZl25yjkcvOtAr/XAjZrTlQT0pK2xQht0J67TgKJcaV9gan3Nd3wmk5gqNylZdrqW4yrVq9BeYYo8cKfV6NIqI1DFv722Txhg3hZfuYEWnerRFLXLU9b56bMFlI8a9zprQgYc5EiGdG95Bx+dTJs9KyKYsmEIshxmWlKtpS9MDSRHCZ4BZGPCeEDyPw889R8hNJwj8az45nlc2Pz68BoOL5l+Ir6it6eXbWs8YS8EZVblDjVBzmhmrdciudEyjtZ9O9JDKXvlKvDyEhOqnpcdrWGZBkZWGHd9MB5yXWhRpcwTEsm4LR1FC2mvIyxVMHSZy45l92C3zjxTwlS56CQm4USHPOVtnY+9N6Bbr5yrS8zhUEaQOwU0SWN9gfp61Nqf1i2vqS6mDpy2OIU2swBnkZpxJwmSR5XLK8mHl2wCJvcYX7bi5zK6yrANQKe1eP78BFBU2yxLEqNAvRtagwc8pM8W5uhF5vcx8316mUROy0nYEDaMiAY8ReaiqMgbyyCzAJTX4hqbOwiv4dKq4WmzKtzqspM6/MCMRwJOt4zl4RXoxjFHRmcLkq84tS2ADm/Ti8uxykQVsSosll8dUTLXrt5AxJJc/wYeyxFIdT7PCY+pp/C1TknMT4pDvBEePdIvRU59RhnEJtbggArw4LXnQTjmHGizCJ4tSIgVePNXYJ2TG6fsHdMNdanJag1OSFheEAaHtnh8epl6Lu4JGUOsgUk62XTZtwU3QAEIFyvyAPGV/8sQ7vLwElMkps1j3TCiaZpf3BQoKazLl5qYhBAUjfnpGYsLwIOP3SAfHhgLvffF3bVX+UsffYv0bjWWXzsAyb/637JnCNCGsVTe+TVCprN0Jg69209Bfn1CGxWHupOPSqaO7jhBdxUhiz5I7E1RciwTGFDSjACkaNxqPgOkfThvUq+wlJduNJB8UUkf3dKqSrsAkaJfOMS9H2sWkE583jWRiueilNIdqtfdp5Ea9hI6sTbIsP955PU9RaT8HCqVWTrrOHUbKvPXOwOdaTbNJAVTSrN6wx86whTWYUz9X7qff/hidD9R7tPt8pnHqrDZJr3ddDgYsFzmcchxl9TLWPS9uVcpqkr81SCFhc81ioem4tTJoYGtq0+8yAW2ljDL0FAFBD6i7MlV0aEAMp0JqkPy9dbT8wq+LnIvOsyXh9hsL+4EDMmNNazGxw8t6nWp7gUXD0M45uFhYBN2AkrlxptsTEoJulpMDPSOwxKR+beTrizQBdyJWdoIIKNJdqxqG9t60MyEX67AAr7NjaigS/EqMC6rHlNdwKV9D1C7gjLN8vSIVQLgE0NUqEuS4GUsQa58a4aNYMiNEPC2LMGIcOl088xg8R6eCeRD/+no1vorKpXQazb2j6dVEb8aWhwdBwPqkkaD8LJDUTbbWzDfGUclVCzFRJM60mwLofAlL5DECLy6S2x/ihbHROuhza+WbibRsCe+G5YRQAcFW0cdOrodvmx5WZjWulw42iaffZeDHN71YpECssdBfi2SguRd+whHysSroSCt7q5bE/sYavfC1wkTDN6uXpcXeIORO4xLQijYjXlgO7W7FtwwzxGBii1BrvB0OqpI5WF0Ndc83tPWhHw5ogElOKVSkUxJhr8bDBer0rtXWGreMxB/z8dCfMwouXzqCMJtaip3frkqhRv70yh6z1V8cRvU943V3wSXfCwS/4JJyQ2eHz5Q6LQglT8XBR8pHHMFdqmXEIyIUwLREpqffHq/cIoCozQ/qReQrEuCxR2330iF4Mu4NfKo9b56Sfz6L0OQbD/jAPQAe8CKNey+q12C1xWogtpL0Zg1+uSiMqUwg7nFKH3/rwAilJUSgrga2FymKX4Byjj0pCoYbAkn31Rlai0bX3zsoSIuu5Fug25AxggEePS+nXtQ1IMzfz1nwGDjNS9Jj/f/beJsaWLUsP+tb+iTg/mffed9979arc7sZlGguBkIyMLDG1xNgTkC0kxIAhEgNmjGCAB0xgAgJZ8sAgoZZlCWEhISSEJYRkBFgIkD3BTZtyV5dfvZ97b2aec+Jn770YrLV27Ig8mfdW17vd9KveUiozz4kTESdix15/3/q+WHCOEU+ys38Ho/Vlv2/jvWi0OjkKVRE1IgY2qBlHZWFc1slV6WrUIJVCKDoxTGTKUQFY+mBMdCqxAzLwwEIUOCmBpnk1hzBV0TZDnmWtFbWRTq+pOgC4EOPeZbiyKA8KgoWqp74qlj85dOF633Zt9GG/n5pEza6uShwQFmhuC9G13zWFgwV9Y6dp+zAQQWtLLcJqqHmYlBHZkdRXaMlNcfsdFA2kJ60IH1eNqRgcgazbor+imaP1b9sHWCMcJ2SQ3jOKJwAZOXpJ3/G6kAvixzD0xlBTLHCehXYnZnQh4aaB7DOkDuKI8enuhB/0D+jdjJsw4l3aI/OP8DB1GC6ddNZXSq4G86dR5JJSbJ2E9nszvtjf44v+Dn9q9w3+dP8lAEkl3Zc9ZvZ4yD0AIFLBkQoiZVxKh4OKqE1KKvv15YjLvDzCjlAN0nmMtQcqtxFA853t/303YxcSbroRr/szdj7hVX/BkIOk7Iqk/h6mXlLk2ktj18xE1qxGE9TQdMqLCKxZ2hMv8iRvLzs8/Pwo8OJREGSlZ3BkpE6pfjZkoMI24FGygCOcK7CaGDRKhjlHRdQ23SwOTN6p46PzhAYPDAurBTzAu1zBLNaU7IhRbgjp1eLQfrTxPe0afdbYtDnjTush9txsmygTewwZ6GATeqmPtNxnc/aNxo3xYLHCoFWACYt+Tjtsf8b0HFypX8CMlRmg7flte3AejQ+9v0xPT4bn9rE1PqtdPmFgnhtL0HH1PVa4OFs6p41odHGuNZ5tOk69wXZBIqv5BLE6FJe6DgCJPDKjwluBSrJZyQ95+S0AAW2YM+lgrZvVvhaWQv1SP2nO3/6skYWlSHi5Lq0RV2Mp7M6upmG9WyshTTngkqPMx8y1y74WkVvHpL0X2/No76FeY9O7eQSz1eFRsHMzCgiRMjIcIgm3XyhFQC7sajq4D0kCwuIwZ0n/mdfdhQxgqWG2RfxAq75G7EJCHyQF7rSiHlxGB2F99k6e34EJp9Th2+mwSK8rgtQ5EXBzSm10CJMCICS7MGVf1Uhn7SGatV8LXoxLARTRqvdwJuT7iOwY8xDW0OgkwBSEgqJz0QcJ6Q16nyFRbTauNbsX+psYaAX3KDsRWvMSIc1zwKhccPTUuvHH44PHs8ZmqvrkIsrdIz16UAzdNaaAEQFTydj5RVumaMgrtDXC5lxzuIHrBO+KgAqGFKusdJvnBVBpb0wGNvpc6WkkgsqIGulEyvAoiE0nfNDoa42eQZP3eM+wRbn1Xlfvf8A+GiPxpFBbG0u3C9Z2963xaBY49tA0F4RaRTvYH6XPEq0+viCyRFWRs6CgAEEXwQNFu729IoHs4c/JI9m11HNfIYr0geZCgg5S2FHOyrJsPFYeFYJai/W1q3uTerPIhda0/y31yfIilFpfFp+UPLwvuNmNKwfkkiK+wo2kkmLEKXWi96L6PZVF2AyjLoxkXe8EWRFbypayyBhMSZ6Fmb3+BCgGC5EyXvozDm5ChqSZejdjRzPe5YNEA9orM5PHbRzR+4SHqces0YtIGzBe7gdJAQFVFdSevbY3xhHjNo7YKSlnpIJiDltm7JTZeZyDGl2qDaN2WwtLlHPoJ+xCwsvugk/7U91mKkFAByni3WWHYYqS5VApEtdn6f43p2LwoJngTx7hIq+1j0p7W3PPyDcFpSsIL0eEkCsVUjk0JKfKyze/60XbSemEhJYIcDPgB1o0lDrC2EUwL3N9e+0+1vi+2rX3ykIDS1OZ1WIA1JSXI64081U102ZDTZU03ibWcGlAoyBYg6ZEK2100sKkoYao1QmRCClrWL9MhgyHzKj0HAWPFT3fG0H8frd96vPcGJlfdn9PjScjHl4/qfo/q1FYgQba9Fa7C/td7yEt/7fIvMYQ1M9aDQfrNFrVMaHl2lzrb7LU5/rzGyP6IQ+qLj7Oad2unYvqzDhIj8qUwxKNtE6Jnaudd9Hvq0Z/5UhsvouxbZxLh2/SDSIldBrJ2PA1J7oMm+cumxMmKp+CEJVFX5o5FzG23qeaxn50GVhT45aFoAVE4zWb0ftUIdsWNbXPXi4LkKBlo7b66ViCUOEoqGfOwmptfS31EpE2zBIro4BS/nsJZ2q029xDQKfZRAAc0qQyESqHUK+bW6h25q4oDF8jI+bav1XPpYgxKlkMoszR8izw5Tsblmn4Ho5njU2bBgPQoEiauozj5QHVi5TYoyPJcwZoVzQTOoV69toQBgCD6uG0CoOdVy+rSY0BQPICMDinrtKoGOx672fERiB8Zq+ytK6y3RrPE2CL5S9wpa5NtEeRBq896m008mhhfM8JtJGL7c9eJ95spO+bx6b6HAXK02WbuWa1Nl13240xNcRSmzABW+Q3RgqLISlFFgnyvNqf15rLYwaBRZAMALJzSEotYpIDxhhBmrmqqDRdoNj6K5T+vqKzGmRWFeVSKhTanHNpFjvr3k9Foo7MC0XTlLym0ZZLzgZ6CM29YSGaXN1XjSrJL9//Ye7hiHE37/Db7nPs/YzPu3tEyji4SXtfZJ4+lIg3fERmh4OfMBePi5PIwJ6L4Ar2ccZljrgMEnUMU4T3BT+4fcBNHGuNc0gR3w4HzMXhPHaVgmiOHvsw4yaO9Xnae2knmIvHl5dbPEwCsNmmoi9DlMh25zHGoCkzuWZ3U48peZwuvai7tsi5K8aDGZJWowLuGdMrfd8kQSrJpoObAZcI3Z3KOdztxIY4IDmutR93nPH6kxP6mHCzH5EL4e27ozBUTw48OjhHSOZMG5Ht5JDcWib7D8LgfHS02x/S+KDI5qnhLOnZRBtPbVeRZs3fj4g7mdA5VENjgAODW6MADqR1nrwYPzA8NizChapOu+nuPOqz+dDxoSmt1qt/6jjUblvzab/4OUEjAsstbZ8BXZyp8OPd10gG1Rvn6lHqQu/40Ve8NqohWhmjJWIx5UqnDsfKthEjuyIqiL6AnVsMnvbbbNFVq2vP7UVfH1v+5vX/zX5I/y5MgoReRdoNqSyaRXB1HK7nWs+F9eRa7rsrF9H6SsTxiZiDx95NCmqZa3yTQZWt2dMCF5ZU1xL5e1p0nSzlmKAGlan21Rhgpo1KSpE09+Q9IucV4lRY2UUKpPd7jC7U67Oqf/KSJpyd1GHGEDCmgGGKkkZPXtKldg+bzz1ixCAoQKTAx1LvGzNQRl8jEmYCkhgGghgeJoCDsmQwoaBUlpBW1v4+ZHBw4CSOAxeAQxNpKcCAs0PxXOuMxdEjY/vH48PG87LQGgX0IVUdG0l3STOZSQaISNMyAbeaNrbAG1u0VyJOYEnHyX6MDmWJoLzWbgBg7yftfmYkvwi2OZI0mZ2vHNPVtJ9XiQJLsRl6hpUnCc95EltDs0oxNdtdm3/PRTWrRegJo2ML6ybV0+6TsJBB1uYhQgUIPEox2b7cclw2jy7IAu9CWUUeBCnkG8UIoDWaOUh/TFKKY1s0wtpYVFllWnIhDFTW6FJIqEcOCeSAEFPtNAc0cvKkjYvra8QFYCJVxYRq6AixYppFVqJMflEK5SV6KqXgEiKSd+gUQRWV3dwgwAAQfEEu0pNTrPkXEIPsbZHXxckiMLuXxbxlqtDk3ouOU+8S9n7W58f4/BxmAHMJta4zloDeJRz8gAONeBnOAICfTy9wyj1+PtxgzGG5xaxGp+rVCDrzNg4ICvQR2iaHWftwRE46VgdvyLFKdThi3GjPW9Dm7b2f8TqeMJaIv+d/iIexxzALOetAAYWXHj3nCrougePibMxTQLl4uHuPF7/t4BLj8jkh7xnpyKJNowhCu5ecCZicINcSlFQTSDeqp6S1yhIg0VFgIIrBGuaAYZZm2FIIaYjgWdcLDxSSzxFDajoMuLMDBoeyJ8wMYS1wjPKxjc331JY9j0ZrCvWSYoAYGqB6faGZ0C0SbDu49RZZkCxuuwDrMEilDTMSkUTRytIMawkDh2uNvWaoQhObFm5hz7owPOOJrgzN9vXqpW3fe+xxP7lf+3wbET1lYHTfa+99MTLtNjXgqOfZnDCxYGXrPmTxtOZDV1NouolxUunrWQvmPDtBBrGm7syYaKHfaiM2gs+1T6KNdJwrgJP9d11afRXnHEppvqddMlvY9dxJebKOuwkpOwwAUnLIOSjbgZ5jYDAXFLjaqW40LCKjbOqWBUlZM7xTQITR4avhIG/3jJXOvj1B/b8ARn9Dut+9n3EMI268pJMtWjCZgNbQzCxRhyHTXvqTfsahdwl3bfO1paOaewcI92DvkkhudMKH9jbs6/vWsD04bZYuXGtEPeUlwtH9vAgX/Eb/DQaO+HY64Ft/wJf3t9J4rQbMgBueBMZeHxUWgAYKEM6El/9whpsZ7CKmF0JDZYbJ+7JIZLOASNxEcCpuVzyQO3Ge2MAwxrSt/GlEvGguTb72bJlzJE2w8hxwAbxSMLlJgO0cHMrsATItm99fJuJDx/c1cHpeYuD2G6w5lFwl5rxPPQpL86U1Qjpi/VseyEW/husD29aBgiu4USJOACvjBUifQXAZL4OoETpIymAosTa+2b5mFi92LAGl6dt5alTeME0pVTRX3aCJaGjz2iZldC33/Hg8M4PM4370Oi2ecfuz3Yab3WtU8wvlfQ1Zpd+FQ9skqIepwZMZnQIEh8Iqw10ae6Y1Ch8yui5Lo5/2Sni3nGwuDhRZYdALfDb4gsKotCzGXrCGHC/h5Qpsoo2IpRBSUv0cTcvAosBQ4PoM5xmd9lG86i940V2w9xJxRJJFdWaPL/Z3uOSIn+xe437sMExx6eLPVLv40Z5ae7sJNaoREttc5cp3ThqUbW73bkZhh6/zDe7SDpccMZWAvZ8xs0fvEjIEGt0+B/aMhZi0HiXf/TJHfDseMBVf0aUGCrDPtHBsZqGhmbWfLhW3qtXe6RrQuVt8Mx+RisfPzi8kspmkdgNeEJ/O8fZSSHTXz5hdweQZX/65Di4B8w1XmW1/EifhnPfLrS4EpzIPxUOQlgHg2BgZqzmaDk1yyACyEpaSpucoSHrX6nz15AohO4ma3EALSvLihd7GN+y2H2NsvYTv0XjW2PzZ258AWLwsG+/SAW58gUuOOKdOONNWVBRiAKasD4JGRgYUqIVNyriNg+SgdUYZw3TnxNAc3IRPwmlV/B+bhywrjPQh95ghdZmkDNRbg2NF16tja1BWabMPvPnP1V7aSKXJWa+32fwGlDGgOQ+LatpzaiIzs5mrr/rc6dfoQA9CTR0GulhYnaM5XVfZm/XZUDZdAwpYl34f59psuJLxJkbhUqlbgl848ABJsV1GkScWTXq3jkBh12T9dXJyyLWrvunNaVKKFAtCJ+k2g+t+vnvA6+6EWz/g4CYc3IhbL53ykRKGEvF/dL+BL8cX+Mn9J/iaj6IpM4faB4T2WFccCKPkN/l0q9F4sP6WZ2hmj7u0w5eXFxhyqGzLc/HYe2E5j5TXTM3KIdh3CSk7jIMHM3Aapag/JHlWgxPJdCPQ9MTIWPf6ztnjXj93cl2VBe9cxmnucJ4ivGP84/ACmQl35x3m2SPPWpfRKF2iYOEysohYIkRpluyOGfwKmH6ojAgPe5TJw30TEe8c3ORQLtr7shfvibLMWY5S/DdNGzjAxQxyAkxxjjENAWUSPjuaJKKlFzO8L+j6hOhzwy6v6qHZYfJB+OZyhM/SEIqZkAuQOr/qL/sY42PaMiLaAfgfAfSQ9f9vMvO/S0Q/BvBbAD4F8HcB/GvMPBFRD+A/B/DnAHwD4C8x8z/Uff07AP4NSEvTv8XM/91zx/4ggMCoWhjn0uGUepxyh2/GoywISTw8Z+gcaL2kca2NPToqdbwZgKIosaKR07XhiOEVAGAGp5ASbOrqUUDoXYJjRnIejl3ttzGOtNSsvlvodfVE27Te1vg8N+qawu83OO0+r0VKjBUdxoqQs1nMKuSXteNfvXbS9KDZjna/9XvWKMgMzPpacIFCPlnSV3aOxADcGs6sXjtXY7ikt3IWD1lohSRq6YNJhotBmMsS/bYQ3XqE7fXc3h/7W+twMFTatWhD60guFvT9LMqtrq2XiNqlFOYlfeVQEAnoKOMmjJj5hK/jETHsBDqcyhISNifPnsQA63EpLECXIUW8dfuV82Psz1mzAal4dD4hsVzvzA7fjgfsFCFm9aTlPixcYgBQugRm1O+WisN57kDEgmZj6ZfJZX0/C6hGoC3ljdN7l3ihnGIo9Dl5SatOHpjl/MkB4FJ7VNrI1oyugYS6kGoPUHFCnpl7aUguUX4b6q90DPJAUXlneIbrMkwuhAsjRKkTejU+efDA5EFFlDbBQIlS7K/Xzm0avjfzzpRtefS/XzzP/1/GCOAvMPMDEUUA/xMR/bcA/m0A/xEz/xYR/WcQI/Kf6u83zPybRPSXAfwHAP4SEf0zAP4ygH8WwJ8A8N8T0Z9h5icVf95rbGb2+HqWkP6n51f4+nzEnJ10/kIQHt4xqGfsm8XCDM414j2jrpiKx7tpVxvLQq3NNAg0QFN5GUc3VoMzsEQ3I0uXda98aTs312gnFYeH3OOU+lXndaU3J16lfuTN59JdllPS/1cRxua97e9HRqzdL2rNoxqDagcsxcWA0sc4zUPX4ilB0jllIU5s+xAYyg1VpJZSpZArsMAutBqL7JC3RoagfTRX0ggkC0CNIjRamacgRms/odtJA+JnuxOc1kKsiddgshUoAgaRXzsEdpxNcFqhzJmA4sTwJlovFub5diK0tdvN+PR4VmOzqJCOJUgzMJXq0PRuxhETPGX8KL7FS3/B23mPh6nHxecKn96yEq/kESCRYFDa/a8vR3w7HPBqd8Fd1yMVry0ADoMW+l/3Z7yMElmZofjycgNPjNPcow8Jr7oz9hqlGMHmHB1KyLjZLbUgABhTwH2SVPM8W01FLo/JvrdSA9HL/ykLorP3CS/igM4l7EPEmAMepg4pO8xjkEbMwcGNDmUn5K2ly+h66fM59BOiQssZUsfxToQT671UFGLZF6SWXskz/CEBxMhRNG/kXhY4LxH0NAVM73ox9DuJWg63Ezqf8dW7G8wPB1ACePAoziGF0twz+c77bsY4B5yZFmYBiKFhKdnAvfulALwfNj5mlk6Khw/6b9QfBvAXAPyr+vpfB/DvQYzNX9S/AeBvAviPSSga/iKA32LmEcDvENE/APDnAfydp4797JU7l+4RXNg6cm3U3Owzi7QZEZMesENf+4wZJDsWIE2Z8p7of3gq9YZkdvIaGBmkCLTyqKbTfodV34jVa943ntrmF3Fzrhma5j2mVpdm/fq1UbvrK2Ny8x2bgIW4MQTbiKetV11Jz1mKyHLgxdGScrG0ntP9ezyK0qqKJxtaUR0JJ+jG0M6JpgfKtelCuyTb8yOsGkUZWCPBavoRleuq6zJ2MdVmxwVhtaDQIuUaaRcmnIqmolgi/KRGfauLdC3iM4ls74tyhgm5YyBhUb4Jkwr9YeUQHcOEo1L5V36/OQptvxeCSyvWJz8LQweF2hxtY85iYJJejra/yLRgGNoQqsANo5dqh/WztQAfo6ASkIhoyZDR+TTXpBrgzTrimud8BdrZTncWZ2ILYW9/bD609yGquGLfz5j60jwDim7TVCKIESMwZ7dq3zAjIz8s3y9ff3y/q7Gd4r+P8RkR/W/N/3+Vmf/q6hhEHpIq+00A/wmA3wbwlpktXP5dAL+mf/8agH8EAMyciOgdJNX2awD+52a37WeujmeNzf97+axGJzd+xKvuUtMfU1kKkzYRtwiyzueK1TetGWNvNs82M8GTbNPCqwFpDp3ZI8NhRzM6ypXaA8DCCqBNeIClzRYD6UkQNShLmqRsJyg1Ofa24Wy1Yl+5QO0Cvo166oVo/raFc8OW3C74VSXSdm21hqanQ9JcHjxHES6bpHBat23PwcBTjUFhW4Vbck+LXNrzbNKCnIXWmImQiRadEeKa4rA+BZMGsCjE0mWiGhnrAh9dVhCJ5NhLAyAxOiKOUJLH5bzMcJBjhJCl8bMYJUlA1sY/u5cUC0LMeHl7waeHU2VRFoSWnMfreMLOzXjpL7j1F2R2GDjiXHr8ZPwUYwn4arrBOXX46cNLvH04CDmtyjFzaRZUFvJI5yWN1AWBVH+yu+AQJvyTN1/ji3iH1+EBr/0DBo64z3tkLHQ0BzciUsK59DiXHjN73OcdPBXc+AHeWgPAOJdOJKaLr/VVi+bfjAdckuwzF0VX6TUOQRLRhYVBepwjHjYrXdAai6HznJ+rqu5lihiHCHcX4C/NA0IM6jJ8XJCpwxzQsjYHX9TIUYVgpyFKhDSREmcSKkvzxYszZhIZs0PyDISC3OlatE8gEn0aIsZNnPD5/gG3ccC7mxPuhh2+/uoWGD3czzvQTKJ50zHmvkUqgRIAACAASURBVGC8nZc1wAG8L8g9lmf27OHvP7LEQC2C/r7H18z8Lzx/CM4A/iwRvQLwXwH4p3+ZA37oeNbYjIpeOQbhj+pdwk7zyDbMk8pFUB+V7E89OktRZKaKaosAvOfacGm9OZEyZkABBguFTWERVcssyCIxGK6+DgDY5LwBVPoPTyxNbk2uue0Gv+ZJPYIgbyOCa9s+N2wBf27Taq94abSsEc7yd6VQz6KRXj3K0PbciKGoqYDmfIkbskw77pXjAFqPsbQexEjTYq5WbphxpRF73Zzr+Wb1hKccAJ8QGpLItjkYhFq8fsTyQKivmUqj90URTqL8mZOlB8lq0zU90wdhrggKPvHqJNnc692M3s04uBFDiTVVe5f2OOUObydZuAV1tag7MrAYZe2Qd07TM44r5f7OzziECV/EO/yJ+Aav/QNe+TMGjtjRjAKHSSNyr+i0nZtxKCMKHD4L9wAEsGCjwCFSqig2MzYeBWOJ0kfEDiGXJmLketsXJmWLFlqGDUYhwpZSPxqDiBpbNxP8RCgmzEcQkIhbjI2pcNozKHUbmU8pa4Rk81mRh5bmJkDlKxS27trH1qGos+TCkjexWlTvUpVpCFTwjb8BE8s5X/S5YRJyCkWsSW8uS6RuCRJN6VF9Fj7e+CUjmw8ezPyWiP42gH8RwCsiChrd/EkAP9XNfgrg1wH8LhEFAC8hQAF73Ub7mavjWWPzRX8HABXrf8od7uced8MOb+4OKMmBz2G9EFuetaEd6XaCADn0M7qQEDW/3IeEz/sHRJfxg+4evZsxF0kF3Odd1Ub/yfhaqDz8hEgZ59JhKLGG3203cyoOGQI8mIvHqA2kpqGRmvRAZfG138DzhqM1UO1oU3Hb9+rEaa0aPX5/k85aAQMai2EcUeQY3GdZ3IKmjppIi5hqGqAekrDQrGzRapbCgHh1VcHUromdQrb8kPSp1FQb5POPuMoAzLPHA3qMXmp10We87AYpgBe3cSxUPtlkvNOSHrS+FuceF55T9lKX8QJrle8iq4MPgjwDhBTyYfZVlvkYJuzCjBs/4uBH7GjCCzdg5oCHvMO36Yjfu7zAae7xbtxhSh6XMUpEY8aOTJqYq06SEUIGL5IGnc+VBXlmj1PpMbHHt/kGA0ecSi/Ok148i1wiZaF+Qlkp0QLAjgSZlt0CmCksBqt3L3HOPe5SDwEeKbCRlh4qYGlBgGsMTBHCUGbCNAcQMd4O+xVVlUVLpNF4CULfXzoGHzMOh6kizwCBsRvTt005R8CYPE73O5TZg5SAkx3AHdfGTEoEd1bDkDUtG4ESZSem5GpXJ50i4Fh0eHIQjreQMBWP2Cckx5iZkG5oUa4l1r6bJeInX2QuFzXGgTEf+Y90HwwRfQ5gVkOzB/AvQYr+fxvAvwxBpP3rAP5r/cjf0v//jr7/PzAzE9HfAvBfEtF/CAEI/FMA/pfnjv2ssXkZzuotHVGKQJmHFHAaOuS3Hdzo0N1JN28NBDS/KR3s4qxOxwj2jOE4w0fpvdh3M276EZ/3DwiUcaOQ0+JICTQdTuhFP32WnPneC7+TpeBsGOMzgPremINAQ40aRFNtqxwvY+ndeF90snq/Sa2ZDdnUOrabLh9oFuPnJu21SEPPk4sYAxck4uKgkY5prbBQ868h1Pab68O0Ot+Vx6akiHb89rtoVETNudTueWVrdnGd2OYi+iPZi7cZvBeCx2aj1tDUBmBlF2ijUGs4NfSQIZxK4SUiMjkEtcwWAQHQORxxP3byuV5SwvNeYPMdZexIwCZDibjkiHeTyJCfxg4pCfUKZ1oZG1vArYHVO63ReEG8dUa/BK4AFoucpHkzVj42ABUI89Jf0KmIoUU0hmKLlMTguKVmmdlhhsfAnUZr+RH60mnEUC+rXkODZRs7u0gyEMDSr3MKHbymx6vTpvOTnSDFeFfgdwn7bq7HzBoB5Uw12iMCCmehsTlFic6VjZmjRBXsGYgFDIVTF9SaiaDmdF7rnK9aTvpcnmOPtz6jjwkvMUhqVsXy5htxnCxqk+dncfbalG2FtjtlNvjYxubj7v9HAP661m0cgL/BzP8NEf19AL9FRP8+gP8dwF/T7f8agP9CAQDfQhBoYOa/R0R/A8DfB5AA/JvPIdGA9xibLfNs50Xudd6PmF4F5NFjRoSbCH4guBmIJyCcgNwTppfiDTA5JYWMKJ1HnjPm2eMyRUzZo/MZ/3h4gc4INZX8z6IW65exB/DCUXVGfK0dmd6OpfiGHKsUgTWXzoqsWZEwXkujbUdrPJ6q4WyN1VP7ZMtLNdu819A12yj/FjeRWBWAM5JCMx4rm3flvO27PzoP9ewUKgzwwjZgBJle0YUwgkp9OPVhbYkvjTutUFExroIHL4gq4/YCWroihi+lLlgjxGvdEoOyeuHMXPslqpT0JvVnDoY1Mu6iKLnuwyxwYk2lTexx4g6nIlG1pZLrdaxGVjxq69EAypJy1EOX4pBJom3vXBUBPJcOu9I/e8sN4HIuXW3inDms3juVHpHke0RKNfU2qfGy+k8glWqProIAJLUp18UMjcGRLUsgVENyIYPPtZcOkPR4F7L0pUSJPtpnqTDgsByjTrmaHpUGV+8LaJfBicDeCcNDS7OUNLVmU9HarXSpZKOloSYxrH844tqcOoaAuQJQlrlkAAEuJNx8AFowTVWobdeL9zyuv+z4mJETM/+fAP75K6//PxA02fb1AcC/8sS+/gqAv/Khx/6FcHx7P+Nld5HuZ59xmSLe4AZl9HDJg0bC7hvG7T+aMH4ScOc9Sqd03V6J/6L8TDFg8ozLqQM54GfxBbwvOO4mHOKMQ5zwolOopUY0Vgea5oCHucc5dXiY+rqALBeBMGYvqZXNMC+Lyxq99UHjObBAPfjm97PbXNnRxkjUmpHWH2oDJhkBJhaNlUytXtZyrrTZ77Xzb8+bLQLTBk1aNnBOMKFrCWK3fI42DMuaHmQWuvaJAe8dzupBd17mktRRJK++U0XKSx8rvc20uVZCjOgAV0BMlY5k0b6heq2sHgEsqCoXZWE2SeTeJeXYC3ibj7XoPpWwAi0YuzQygckh55beZ+lNKcVVFGHwSnaphuuSI86uEwfKpavNxoZQu+ddJeLslW3Atrd6ZVTGgx1JvWnmUM8fgDbLipjZnD1Gp60HanSs4Zaw9KCZkyDpyoLe51XTraeCXSf3aewYJWk6Sq+9yBcs/VQtI0VbO4o+I+5nkQYwDjubbplAyUkHv0YtrFl7yZ4s/GdwACmVENcGY1SY95ByRdhJJCoRk9X+mIGsDM8l0WJkwA2tFZaa6McaDFzl3foejF/I2ATSQpumBU6xw8O5l7YGL+ScxQO5d2AnkQ4VwA8AiDC+EqK9os1XIKAMWvT3otg3Hz2GXUDaOexUasDgqAaBnpV6Y0gR50m9t4Y4EoCgW1o5AX1dPE66mt36zgZjCc+vuSnvi4KuGZzVhha58LKoWpqhgZ0ytZ/5sPOuv/UcttT8zpdatLemz+rRW+oBjaFpd8+kRp4xeYlwWkYB+V3Q6QLca/po8BnJu9q30oJ1Wmg1l8UAt6CG7WeCK3DMOo8TOpcqfH5m4ewaFeJ8jcncjBkXWdiKX4zZ8lsuoIFnJP3r4OBrk7RR1bSjJaadVTp9Zv9IPgOQ5yDDYccSmc3O14L/UGI1WA4syFCyaFTSjUmL9rb4b9NtLYWQ1165ep7Ekh4MWVOz7fVZX49WyqEFfThN33VdEkcBqDD+ykqh/WFN2VKiGlp+SGlqQswAsdAbKQVSyQ7FF8zZVaizpfIKpPYn/GvmJBCK9hCumCGqM/Xolv3x+MDxrLExsTIbez9h74UK/ZNwxru8RyoOb8973H8dpUO3A8ZXHsUTwpnhEnD4KoEy492PI4ZPpaBdIoMywU1LpoYdML0OuD8WTK8DjlG8MeOqiiQ9GVMRPfQ35z1OJyEhbD1uQIkiNa9uMF0fSvWIhdMKy4L9oaONDrYRCjeLfQ2CFnLKx0ak2cf2GNtt7Th2zrYhG3oHNedd9yGu6nVvrLVf+iDZubNv0yhLTaL+3351Vg0Xt7xKbjFI9RC1tuOEYZdJvUtgF9MKvXgTprqwTcVXHaKUPNLsqtfdkiLmZJENLZ5ojWyoGiVDPprD9CpeFmp/jWzOpcd9XnjJ6vcwI9bQ4hdyIGYUv/7OWUW3AFHPBEQFtHjCKXe1xmjfM2+iGyPhTCzyGC1rgCE0T1ngzr2TvqGjH4FOIp+HLGlA1zA3Oyq45IhAPaYSFhb2xths02h9yPAK6OlUSC0VkXZ/0Q9wxPimK6Ji2sypotc7Jb8yPhY1WTTVqSQ1A3gYemkSnZSdeRakGyWqAB72kNS8FfZDgddm3eN+hHeM89gJe8XskWcHIKxYzI1Gx3uRz+5jUhE4YbzIs0dNT5vRs+f6Y0c2ev2+j+M94mmu5osTuToRd27Gzs0YOVQ0EGDrtnh6AOBnwCXVlgDkdzMhiVHlWf0or+UDoUTpPj8pvca38VjrNgUiPjVmFbTS9FJNnVhqR71OoLEF3Gz3y4xrBse+ll0L2Hd+T+ptu4/nUl2/yHm9b7SGcuW9oTIMrNMfmjpDA5ddHVs2bAvA9VDFwiS5LwuYQMgic1k3Igb14k2Jsn6txvOuDXntKdCV57SJwtrL0jKUW+S8QO/VkGA5L2syrf0+Ws9ars0a5WXXjnmB4ebikJ2rkP/iFr0c39RGPRQgYMVvh6rZJF/GwVFGKEV6nsgk1Jfjt4qZMztBt7FpRzUEuZuoxl4zg56ysKkbOtBSeFW+w5UrkY0BPGgF8CB7TqEpNK0RGVvBFIIYKMfiNNmj6gCOOj3jYmi4SdG2dSFDwOVMYE+1sbbWD/VcbFtLwWeDW3PjiH7XWY8PGB+zZvOHOZ41NoMWGG/9gJfhvEQX7DBwELTOHDGlsErfgAA/Mrr7jLxzePubAWkvuhO5XxbfkgAXhGb8+LOCeC54iwDKDhP3+L3yCs4zfid8CgCPe52YKnWLpXdqv4CisxilqjoCTXpHNVDYDJSzlBTWi2+7gNdooYlUGqjk6tT0YVxpytDmGPa7XQXbmWbH2w57CEguChs5mdPFvNDysLbHBzbfT37TrBFSg+ZhFvXD7DzYNTUJtB3fuhA38F+nqRXnhBq+MGGC1j2aRkvOUjyeZ68e7rbvRpCFU16nsqywWxSmXSOvSgzqpaOdIRREjhE7YXZuNWMKl7oYR8q4dQM+DQ+Y2GPmgLHERjZDFuAuJF2MgOy4qoQ6X3DYTQh+SQuep4hxjJhnj3kKcn6QLv0hR+z9rJEHV/Zn6/XxKECQPrGlb2aRPDcncI6hptjaz48laoNowLt5h3PqKh1Qyw5gNRNAnhmDCAOo9Z2H006QqCngXbfDbT/ik/6s50Ha6MnIvpm3hXC5dACT0AgBlTvRIuRdTHi9O6PzCccw6T1+hfMcZd5kB4oF5SDPZ+6K6geJ02Aqm0iEfB+Rg8eJGCFIT1OM8woRB4gxMQlru09RCWAHvS4pedFnKoDbZXhfmjqcsEh/dFLmX0XWZ8sN20SOJOmsARFjjhhLqOguYPFCigc8AZQZYGA+AvOtYvCDLLhyrw0FAviZ4S8ZfvKgRPAjkC5e0rZOQyUzaFF1KtziTV6VeOarfz4e9CEbXflMTWm1hnZjLMzQNak08+7kjSaNZ0ak/fw1N4ea9yTUEKOj76nvuNl2s48m9Wf3w5xrLgAR1ZTUU0VRiXoWj9+KycGLt5hJHnDvi+jOOzV+NaoCTAFxobMRD94acp9i6raIq14SjajK9ns2kQdZ+k6vaRtNydxOzf+PjZ93jFwEoVVU76XS4IRckXQAMFKo19n0WNaaTmJIAhdFecmP9c7YmDisois77wyHQovcgNU0IyWU5sJMJWDMoVLLtN/JIgvRppLrFCjDN7x0xrg9TdJv0/mM0m0usjlwzb0x9meuawOD3NI8SgA6n7DzM45+EjJdL+mskwEWfAF7B3hG6HM12AAwqfCZ8QkyxEAVx6DAiL5UpnmTvgZchcgv93SJblnPvT4TJM6NGXnKDqnQVf/vuxy/kpHN740vAQB7f1DopUcqHpcc8Wba4zT3kmdNDvlYMLLD/ALShDUT/NABTpq9AM21dgzKACeqfTjpwHjzZzwoe8y3jLxj5F1ZFkiVk6WJVPzKCRLFLb2YMyBpjb5U9UTqtLKok6do7txysRUyDCzevo33GK911MOPoyA7HzUKFd1iaSrbTqOTR8e1GXfNEHKzbU0dUk1nWM1lZZR8Y/TMUFo6K4poFNkCYbogXUaI8pAbtUk9TWIIUpTh1RewB1jSYk6grY5x6KcVMSQzYUwepThpeAwZL/sBr7ozovLaJRZYu0HZHQn6yFioF50dqudDJPTy2MkiySohPFw6zLNH9AXHOCkIISvFUqmRiwdjxmLgep8wN8bO0n05Oek2136x6DNu+xGeSoXs99GiIJVm9hmfHc4V7n1KHS45wlHBq3ipMhpmaL5Kt3jIO9z4AbduwK0f8MPwFpkdvsovhMaJpYH5lT/hhRuqM3hfdvhylmc30KH2Hxnqz8hHt4q6xhU3lSAEnFnAO+REfGwYIlLyuBt6Sb9p9JMHEaerC39Qkblm/kn6WsBBM4BLCLibdkjB4UUYESgr+jRjzDI3Ro6iilmAdAn1XEAsx+MGJt1n7PaT8qFJFOv1+xQQot6HwYU1FBuKkmWhzfLWyMnCFp3JC+mnRjjOf08twR/AeNbYvJkO0i2cI6IWF8+pwyVFvBn2SFk8nlIcuCtIt8uNoLI0adGs3oAyuFavlLRb2AGXH5ZVykew86iQR8oENwovESfUOpBNDMMyFAAcCeQXoyNMAUK9YQt+rd20KbPtoCdeb9+/9j81C2Jd3DfpM416Hu1oa2S2oz4obUSk/9u6aA8llmO0EhAr+2WpDkPoMVWWZBFAKxWR1C6epOcqgdX6IlkO3dJru5BwiAt8vTDh7bCvwlzRZxzjWIEBVhRPWicwaHthuhrBLigjbgrBHlnvq8lCT2nh84vWZElLLaTl3XNU1MtfZMkNWVWKE2cpCn9bHxP2Qbj9TN+p83kFx4+u4JPdGZ1LmErApEYpsUfvcpXRAAQs8C4d8HY+wHWMl/6CHc343J9QmHDmXntsJPp64QZ87u9FF0ch0Ld+qGk6gzfb924lntvvZyNQqTWX+shkQtbi+YgIcoDzWdCFk1tokzJQikQaIAbiOr1QjFsxCZrUUpuOGEc/IVDBu7DD4DNm32Q0zJB5WxdocfBCgQsFfZA0oMjYL/Q81gDRytNvSUEBSQET+cV5MzkCajMoH9nYPLUWfQ/Gs8bm7/7Ob8hGatkBW0hQU2c1fXI7SuipaYVSJJIoTIIIYRJND8fCKzUrF5KGw5UHrPXEA1cIJHsJ9VHM89btrIha8fkEzACnRneClE9JFQRXbL02sdpF7KlIQ49Jbpnwi+Y8mjpIs3jT5uGwfTKWek7LlGs1nJoiax/WJvV1zdC1m5qWCmPVBb0tolsqjAlKqClKhy5INBOCQmabIqvDElFIP4X8bemirBGkU1TaOAecpghHy8Nam/10Bp7mHv9YzympPMTduEMqTth41ejEmBZ0WV281r+Lzje7fuaZ5uLwdtgj+g4Pc49DEGTlTB5fzi9xn3dCvpn7iubKTLWOMXdS6E/Jo0SJKKVJ1eEbjY6GJEJgrWCcQYcDFWVqFiNxn3pMc8BYPN7lPQ5uqgZkZskg/O7wCX53+ASv4hm/138CR+WReOBX/hY/cZ+io1R53aQZ1KFzGTfdooYrUG+J6EzGY9ReIlPzHFOoEdsZQHFuheazdBYRkFE2Xf6KapwhSEgUwKNKNMcoc2qnkV8qDl9PRzgwzqnDVISlpLJBdEWepcmt530s4F60ibo+oYsJr/fneq8AVIqqrCwi1n9nyLNcFjNrc6qlRxInVuo02TcaUh9xyKP//bQ2zxqbw/+1lyLxHshR+I9MzIj7AoSCeDMhxowXhwGHOGMfZtzEsclNE06zMNAOKWDOHsMcJCIyTXCDkqpX3dZjzNvmApQgvTzUbON9kYawpFomg6/poDo5rdMYlju26EFDLEuDActkamtBOsnIrZsZixSU5KO110V+0+weoaqJIdGbx7oOouk8IyGUZjXASA1Xoz4dpJai2caMXQt/dmoYyAztlRttkVCUbWKfZFHQ+otch0WPqD2RpI2URspYCi19DkqAaX0udi0JQOxSLe4DwN3U427q1etdFgRmUnqatWS0FXptkchZ7n+ZtXAMSITmBSAQoyCe3l12NVK66Sd82p8RXMZPx1cAgEvpMOZQGckLOxzCJL0/oKrJYinZaQwAMWaNmgx+3fUJfZzhHSOqpy0Qa2lSjiSM12/HPYYc8WY+YA4eN35ARwljCbjkiK+GG3x73mMfE/7v/Q/Q+YSXcUB0uZ6fjegy9m5a1Xb2XhtBFRwQqKwUbK2VYMoB93OP0yTKnC93Q73XcxaKnpyF7mXXzShFYMKAQ4pFpmNxFabsMmnXhDA80F4M/q6bq7ZNcEWM5eUGpuybi8M4B4XGy1ws2SG1Th0Av8vo+hm7bsbL/YB9mPGj/R2CyzilHlPxOLPcyzn7uu8pybyx9ac0iNaqSmugv4aZg2cBzLTtFR9tlPdv8kdxPE9XMyyLpZt0EWVSHiSH3DHm5DD3Qltx7hJudmMtwFlfAGmoXoOE9iC60IlRsQVdu9Bdqd4ws2iDCy8YatpEti0gg1cHrpOiPUZ70Ko5fo0Xjde/5S3xkius2Rwfw983CC/LW1+Lth8jw+iRMeGt8bCUW2tkgDUibpuOawymkaG2abQt9JvNKNvbmkLJRA3KcP2ZLdcW1d4cadhdbBItypkkImvkZNHpQsaxm7BXxoDCwmk3NQt3KSZn4JBdQVbjYqCC6olyKxvRfM8ijX25hSW7teGUdFYUWH3qcE5dLeIDqHRHqc3tN+i51gHxvoAdKf2L1Els8b9kOUYBIVCuZKCANJEiAW/cEU7rJoAYkF1Mup8FgGDRpBWv23RYBRA099mQdcFlHP201KogEdfFxfrZVrvGak+SonRVLNGR3QuLjCXyZ5ObkINK2ksp/70XOehDnFUgT+HVvKTWctHrrDDk1iHhZi4Z6WkqriqOfkm3CFRwSl1lSDBqHpM28E5qLyEUFMfImasqrdRWnaajBWJNoGY+yXPwsQOPX8nIpruTRYNPAAjYvSnov00AAblzSAeHdz8OSIeAdOzw0DPuXs64e3XBLiZ8ejjVnHHbl2EeKSC1BGYIqSQtXrAjgTGGkHHoxDszjyepRwKgesz2kFtx3PkMr/u2PHse/drArE6oSVEBoOI2+ab1tk9F1Cu71abDaBPNMBbZYF3s2W+UKM2bAx41i9YuaoODEqOwVxIxjcRCQejyijDS0k2rjvvmAapRgqWkfFk15dnwCvP11kUOACGjMDA4ga+m2avAm6QiEAp8EGXFH97e41V3wa8f3uCLeIf7vMNd2uGr6Qan6YsKQy1zc0GaRb3W9tr0JPS7B71OyQGZkCYpOFtUFWKukF9brO+SNDq+GQ41wiqb71x5wXzBcT/CpBPa9506SMb03HbtfzMcBfGlKTVgqY+8nfdw1OPb+Qhgoat50Q2qvVO0xtTUgazugkXa2qNoCs5YzyVK61xCpIJjGPFp1e6RdoZv8xHn3ONNOuDr8aam1MzwGHuy1c+MDQEAEjEGu0xBnkEEFjJWu00EdP2M4Atu+xGf7x4qQa6h5ebicJkiUiPdEIJEUd5xpS0aZ0ltTlNATh6X5DEMYii/pFuZt9nXaEXkKDJilMjq0M21/gcAUxJaq8IWmTM46pwliLx3a2zyZr798fjg8XxkM6pH4QEmQrgUhPMsVDSTA3FAfBAUCmVC6YHJB1y6Hrl32Me5FiYB8b6Khs/JFxTl97rajNeMSpXiClCWzuxFg2O9nTXYWa9HHWZgnjI0aF9r/t5s96R4Ujsvt5boqdB7E5Tw9kpcM3hP/X/1nBqPvjmp9zpPLMzRyzXeRkPURHp6f0h0eOr9AVYd/VwWNmfbfqf6MRmEWYvlrr2Idn81MloappZttjDoR99fjb5ziwaOc8sC3Y7Emstn6QOquyFVgiVUL9ng2u016ILq5PhcyWFXnrkasQRXmzEB613ySGiMmn6+cyoCaLLpmgYT/Z1Ue3UAaQ6tQoKOKqmt6fbs/YyDF3n1gxvRKcrUQwyiNYFecoQoqRYlEi3VAFoU2jazWpoaBJAvFbVlWQpTKt2CEWzUJlAV6WvRhrkAgJf0qUY99kMEwGovOhc4SSrT9mPzg5kw+7X8dduAWhkodN6t5lmbJv+Yo117vmfjWWNz/NkEALXz3yXBvZvFd1PBi58kKd4HSa+dfuRx/uEO46HH737aIXQZP/jkHsc4Yd8L19mQBYkyF4eHoUcuAqsstdYiYkY5y1UfSDyXqhI6hjoxLCqwNNHiwRNKDgJTnf0CInhkBXS0HnOzkNZIhzUEYSwMPtvUVrufdmg6jKhJx13PTj1+rXrwV0Ip9bSYFtJH6HUw9uWSl5TU9lytp6AakppOkyhUHubrfS7y+eWhtY7wWTVo0iys4NCGUTlXoQ8pnce3R4Hkvu5OuPED5hJqv0nroKz5qQwxt7lIrbPSRoyKquv3M7qYcOiF5NWYpg9hqkJgez8jUsFbNXa5MQwWiVvqLmep2TgvUZoQVcp5mxpnjWia692m7QAFQiiE0rYXnrZFubZlN+jdUvz2VPDSX6qiZ6dS1tancyRJlZ1VN+dcerzNgi7d0QRPjFf+hIiM114k6e/LHvf9DpMSeRZ2uM87FZDb4ZI73Kceb8d9hbATMW5vLmAmnIcOafZiWKKok77cDytUXmKHr4abmkaz4n0uSlMzO/hY4KOm5pNHTh75IQj4wFhBYgGiRFC+KzWiAUPS23lJrTI5TC4AjjGErqbuiaBMiTT8pgAAIABJREFUI1rvtSh6m7awmqrWlq894t/d4A/wBP9ojmeNTTjN2qhJ0qXuSAyP3ZPCiKdUKTUAIO16pINAIcddwJwdphcefXCIEK33DuYphxrStt4vIMV35wiFFsEze9gFeuoWhJXjyhJQif5su+yWBQ9YFtTnBlleCzXNxY0xonZfy+pX38fmpaeP84GvbV9fGTnWug5VD75tIq1SBE/s2Igr3zdayhH7v40mWl4tSZ1hg7KzHwInAQGY5pAJ5jkoVQrWNaFH3l57zoT1m9bPBFb4tqRi+5hw0024jUPddOeF6VmaIcUwbSlfxOg2acWygBEAp5xo8h298q3V/arRMnoYuwVWA3LMtYbTNhoCKgtgnIBuURI13RoAuFVj01nDNTKOTqKWV25CBOPsLpjZ4ZtyWKXgPBgRuX7Wg+vfBQ6n0gsSz80S+SjAoTDhwfXIiux0IHRR0txz9ijZwYflmr/aXeDAmIqCPthhTKFq5ySNShZGbc0eaMo3Z4c8ObizFy0bE0o7AuwKOKwpZqTAT2uEKKg+I6wcbguEWudMllYNAOCI5XEhcTANLED5uj/5XY6Pvf8/rPE8N1pQC9IYGa5pDN1oc2F2bzNcBsaXBHYepfP4avgEX9nNtc9YSsrQK6ODa/iQyq5g3nlQlyvFxTxL7j1PTvLxjheOKmUnTlpcLrMammspr2s3c1Vs2RiUp8Z2AWxf29QWat3muZn0XCpo48lf++yiP7Nss01/tfBNMcr8+Ds2KapsdXBe0hLU/AbUUy/CKFaY0HVZ1BABlG1gRFJjykXQiZcsMF2vwmIOmoIKrhbhK8CgMbKPVEQtxWGvO1TI806L0qJdkxBMN0lJKgEgIwMFOIQJYyfw36IGhvX6W5rHUoMSfUu0PUCQeVMvxuxFGPEiXFThtsdcPN5M+5XwnwNj52etkQSkwkCQOs4ld0js0bmEAyZkciuyTk8F93mPiUNlDtg5iWpmDhUafV/2NbI5NRo6XptnLRrqKGNgYaO27QVkIMc0ccODn/C6O2EsAW8P8n2s/kIATj7j1eGCXzu+wzGM+PXdGwDA75w/w33q8WY8IDPBMa343IgY/W5Cjg5Ra2rjHCqhKXtegW9E0ZPA8JhtHia3AHZWcw6PMwnJHhBajIltMqtjYAj6JrL+vhqCP4jxvMSAuJiiBFlTQM1NacM9vcHhlBHOGS5FTC89SgDCSbt/zdttbn5NxWdIBOElTZWzQ4KshWUv+vIlC5OzFX4B1F6VasdyU5BuJxTweFFtjcr2/edyp9eijO2wL2bbt4ZmayzeN4Nb7/1aGrD1whojUL289hgOq8jHosBt5F77kfR4DL1W5hFsvob0M4h3Gr1xoy03Zk0tI/n9KYlk91hCTRM5Kkv3d8hiC8lJLauepyiFGkyVGTInGifGUqohaqOfFymB3ifs/YyjH1e1jgSHQoSdlwZNQFQ9AdHLaT1nMzbkhBkiM8AsTOfWMLj3Ez6LD5Vf8IIOqXgMOdQFdudndC4L9DiJPEDHCQkSAZQsC/JMIjXQ1hqMEy2DlDctosDh6EZ4MO6KsKG/zQcM3DUINauXFUwkhmp2ATuaq3LoxAEDR2WBEOmF6CSl/tKfgQgMHPEuHmqKbSyhIui+ONzjn7v9KW78gF+P32DmgHdpjwLCu3GPrEzThlK1qG7XzYIU05RkS68jABvtBsjipJKXIn5RzZpavGdarzPNfK+TuRquzdrAC3M6e65R6x/o+FVMo2l8C0pAS15ZR9H3V4s0A54QzgW7rxxKB0wvhQm6uwf8wI8XW9sXybZpb8eWn1oIhC6ksSibK1fYbzaqlbw0lz35nXRUj6V9fROJtOmfR8X/9xkJMzibwOTx/7bd+8/5sXEjRaCJI2Ad37bfR8VzC2SYNgZg+U71z+b7kb7nmnTlVv+ksgs0QAHRFBGWApHxFcRdKQ7sCoYccZd26F2q5JG1R6toD49qnKxG0ytFUNqS1sB7rsJYZrwMWg2gSokbKs0o/aey6CAJ3FhRj5VJmJGznJtzVrPhiswj4oXwskmRFRCCy9hBCv9OC/7BiWzGzi/1mPoVSc6xV70dSTOWmk678QOObpRUHVyVswaAztgF/IAdzyjsMLFHwRIhZQjdzVAiZvI4lR7n0mEsUYxDk9qzlJ6nIkaOF2LPpDRWc/YYU8A5dfh6vsHMHq/8WVOJVOeUVwj7w9Qv9TA16Lk4XMauSkaUSeutkZUGR55Z7rhhuiiNwJkYGmJCJcPV+W7zvx0rlnYPgBW2/4QTyu7xPr7TwXgagPRHfDxrbCibiddVg1hv6Dr1QsY8DPOUgXif8GIoSAePuxBQOuDwZcbu2/TkzeJAePfjiNw3uiy66DiydBmBfK52AJDwmUf/2MhsjUFdn5rUS5uOaSIPgymvQve8XAoACpx4n8FBNVorbZtH220MjZ1K2Uz67WZtio2skW69EWON7gEv0YV+rBqZVa2k+duMjLECLJT0a4JIKxrbwgtiMRSjl3MNDHip6+TicJo7vPEH7PyMxB6n1C+FdEMdTX6JUtUJoFhqJFcNOi/vuyCiWLFRAi3scE6dIM5YGh5vvHCajSXglHoMOdbFuPMZ7Aq8ygUH5ccSuKxD0L4RMzSeuNYh2g5/IxXd+YTiMo5hqk2ZqXh4P6+aLNshqLGpgieMoXrnZrzyJxxpkvQXx83npA5j5KJiHMTgWNRy0lSZpMwI79IBd2mHh9zjm/GoujVitIRtITfaP1z5Eg1ifUkRY/K4G3f4srvFWAJe+oscH04NvFynKYssPIAKnc8KFBjue9CDl3tpujV9XpqESTj3nBqZwkIWapFufWaqoWkuDF3/u4J2GBLNMD9eH4BW3uvjjV/FyKZ68kW8Ua7V8iaFZsSIFeykC0V0mF94pN7V1FjaOcw3Hn5k+EFhobofJqqSxuwgfSQe0pCoNRln21pR0VJmVpvZggCeihQ+YBCvDQNbpFM3eOpibd5oIqVn6zWPTsB2x/V83jtYH5IP/dp6nVgNYSVMbPZXJRnstJqoxsa2H2W1rf5m+04ajTq38J0NeVkop+Ir0KDWhjxXKOtSi8L6WluDrWflxRO2geCFVTmQFO5N/VPSNw53aScLr3adt6mqbeNncaXS5hAJIGCnxJrRi9dvqbGWNVoaJ3M1MMa7BnjAZaSyKGxuocGFBRJeQHDsUEgjmAJk5+r1MF43D4ZDqcfPStg5Q6QT6uWq8gVS3zHQgSNG75JEWj4hVvi1oORmdpiz1H6iklyelGbGrkP0GVENowEwPosPuNHU5c7P+GY4VpXdMXlt0BWWAkwO/uIETu2pRjSSwtTrExdghjlJrNmXajT4inP3vkfw0XP9AZ/5rsf309a8J41WjKqEgCL5yxoALF2A+ttpA5TUeKaXAXf/hEeJgIkdXj4njK8C9l8XHH+WVYJAF1NdzIsn+UxkcFcq87A1EQLA5dIhzx48etDoVvOjNk5+yA3bLlib9+oCT/ICe3qc7eL1IrhqAKPlZwV3bo9f978ZregaS88LXUkNkr63Svlt99mmCzW1sII723m75UNtb4JzptZZaj0GQO05sQvineXh5Zp4b8qoVKniXSzaST5jpwqJ91OPi4uV8TiQaIzEKI18IAYrG6/BVSW9Qo/YG9hnBKXbudmN6LwQT+58wq/t3+JH3Vu8Swd8Ob3AJUf8g/vPa/9IOzwtfThzlsW+zBFwBbNSO3YhrzRZWiqYvZ81shAwQlD9nKXBMgsaTa+dkWYais2MzlgiHnITYZLAhXduxq2/YMeSOrO0mYMY1x3J8b8qtziVvtZjHAo6EqP3Lh8wlOW6eyq48SMOfsKLMEjKjiSFdy5CMPrl+AJfDrf1PhUQTrPo5XhX8NnhjE92Z7yKZ9yEER4FBzfizx9+jqMb8dP0Cb5NN/hf736Mb08HzMljHKI4jbMU+OMbj+6ttFPknTRZJifPNmldpvQF3Ge4wHA+g+Akas46dzfze+usreqn17IFtGQ1/nh8N+N5NFrXvF0XU13c6k3UaMP6b4LTvhvUiMbNupYlLKhiLx4IzZo+6Bxy58AB4tE4aH5/EVyq2htMC5begAI2Qa4YjycjClugV6mj5y/YkwHGlRTX1dfe99mnPsNP/N16Xrbwb79vfbCejnpEY+TKdWrQQktUc+WzGhW1aprOifRu8UX6IvReOi9ULtR8PhUp0Leqk8IioYg0TeM6xxURBi3Wi0UjcIayKSwOLrA0IbZj3Uy5vNdGbDbfvBOQQHAFXJzys8nrnRfes9bQGMQ4by52K7O+1aix4Zv/JapxQO7qPiNlFK/RjqbGPmR4LEZSoo3rn/N6js7qM26JBNvzAiA1ICaRGWDCLsw4hAlHP+EmjDi4qar6Ht2II8nvs+treo5ZwDz1eS7CHG0Kvi4TimMgkdBUqbGpXf6FUWmdG+fuufHeDEP7TP0hRDa/knQ1pz8piJa2krxay1bsyFRTTUxAiYT4IOCC488z3FQkkgGQjh7nLyLChbH/+YjSOdz9Rof5hjC+Fv2b0hdQkE5k86THOUiu/xxAFxFZo2Ser5xjzanWfL6miNrRTiTtdN4KhD0Ffb42T+uyyY+3M3lZqjmlZrK3zaHb/Vb+Nt1fuXI+ZkP0/nCEhBr1oWtIA7cU6bTZDy0nLWkJ1AK71T6c8n0ZhUlpzoWZUBQxFrWx9pU29OUiNZKsDM6AeejLSRRNjRJQI4pb1cBp02qdFtStiB+cFM5Pc4cpe4xzwDjJPLnMofJjBSfNxD/vbqthCFTw2e6ExMKjVdhhyEKfAgekYo2WuaLkChNKJymdPoj4lxmI3BTUZ/Y4535Vg7HIJhWPhAUCbagv24d9vjAhpR6pOHQ+4zaMKLr4R4UqG5zZV2OUYMJsUJYAQ5qdSr9EMWB8Ek4YS8TAoX7GCv8W7RlQwOpOwWV8tnsQ8tDxIMS6STRiXt++wZ8+fo0fdW/xp7qv4MHY0VwRbQMHfJNu8OX8EqfU630n8OBXcOUSICAh8yMzEC4Ebp9kkvlXOhJePqaFY7E0aVud3xUs0GYgnnTqbC1pn1NeA4o+5vhVNDbz4WmvifSmLMisx16/m1Ue+u0Mf1mQMqXbI/UEp7o0xRPmW8J0C6Qdo0QAQTm/3PK4VjqL5EQjJ5v8sRocwiKH3Lok74sutt4Qi0F4sk6ySVW1qbXFEDebsF4nW/CfAwrYZ/X0V2CG9ti639WL9qAwUBEWq3rL+npYHXR7faxOs6J2MfnlzXmvKXAaChPiCjmu7MHF42Hq6me48VwYUiAmYkDrIiY01op9bSlmbLG/n3ucU4c3wx7TLNNaaHEKJgjC7DT3+pmEV90FTvts5Pw6MS5NSs3QWIYeA9aIsU5rEwtAwonYl/adzLTQu7SjFWSrDZ/6d3tsAJhywJADCgtkOzY3K3MDRIBCoOHqvS/s0CEDCpHeOVoh0TpKgBO5h9EiLlAFNRQmXHL3CLTQa50pFYe5uCoXsfczXocTPvUP+NSdVk2kJmU9cIdzEZBGnUsF4jQay3lD6EkawVLi1VlYgydXpgA0Diat5/T2MSbG1cCuee6urRlsQJSPORjXewO/B+NZY7P/Vov46TG8mRgogTC89kJV09ycdsFlRxg+7+DmWKMOysDxy4TcO9z9eIf5AJx/xEjHAvpkwv4geu6GUjHvuDAhEWoTF3FjXMiK2XpsrwZnO0GuLdqWfvuQlFfz2YrHbz5K16IUWHBoRkdfaBpdrxo3Xn4e5Y8JC4v0tfTBBl13TYvjOQdqad6Uhzwr/NyUM1dqh02qrdW0G1VSIjWRTVKG3V2UgnMfpAidywKlrXWMpEYjEHIpSM5p7YOU3h5AD3Qu4xAm3MYRhyCUNGMKOE9CCHrsRvQh4ZPdGa+789NfGsBNHPGquyjkWHi0Ri06tjowFTqtdYu7eVeZAQDgNozIGCrVDLCk0cYSMLOQUA5J2ZYhTNA3cUSkgt4nBMpIna/cZkflNLP9DSxsxx0lOC6SrmoYAVqQQkTGqfQoCnXOcJgUHGA/59zhLu3r+bQSBpccVSYk4pKioAhPexR1EIgY34xH/Kx7iXPpcFf28CiV0eDWXWpdCZB6Tx+TkHHuijKoA2BCPpQqPc0kyr5+kPSa0zRa7lHh6EvTbzP5amqheQ1YRzSPHL6N97iN/tv9fKRB4F/NNFq8TyBmuDGDUmNumYEClH3A+HKPirpsggnxyuW18dbV95nEiO2+HjF8tsP5C0I6AvMnCXRI+PzTe/zg+FAXnVwcLikiuyL6Jr6ZBCyGi2ujoqXy+LqXsooQmlnTekWPeM+Wv82QrKIXQ2zpPreRzXaQGQlD96mXRRaRbA2j7bMshhVo04WN0aknufneut22P22TBW3+WYzHlkSyTX0RHtcc0Lw2V1VGX3nt7H1S2vxedeiN0j/xwjBslP6OGPAa2bJ43pc5CqdZEL69YxAY895L3eBu2uMnk2jURJ+xDzNexgs+7+5xzh1OuX903uX/Y+9dYi1Ls/Sgb/2Pvfd53BuRkVlZWV3VTbfUbYQxEkg8Bh4jMUPMDBIMQIgBFkJihEdIliUGYOQBQmoeAySQhQQDC7VkwZABD2MsGbvVcoOr29X1yIyMiPs45+z9Pxmstf7973NvRBXVFY3o7F/KvDfOPWe/zt7/+tda36MSXvgZB7c075mlOLwJBwkGCj9e1ZYN1cbPCdlt1JJHm1CIGpfHU2ZVBSmlndOAUxza/keb8GKYMdqEG8fwZoAzmL5ZrxlD69tIr2uouVlDe8pC9qxSwiptW0FQaH1GlavBuQw45UHeR3LM/Lk5M3/mHAecwoA5OlxOI1DRQB+nNOBNOOCSB5zzAG8yXtgL84J8AbA0xJ03GYPNiC7Bjpm5VMkApbIygErG2IoaDOzCiwvKEB4N1mehaKaMdZFldHF2dX9+KFhsgkzdzhEfOch8E8YHg83Xf2YCKuAulZv8pXLjTjKK4liWprirSbYCVPm9ldCEPJs6wGRx+fSAeCTMn1aUqcIcIvzI3hlLck9WuQCaOqsK8m3mOZl0q9Hf0dQFGmdGS1LvS1P7v7Xshbpzunq/BLa1hNY5Yl6thNZy4xoYOCbSOutrsKH+s1IexLYnBpmAnzic6k+zinE2vTjaliLWILwNIMynqa0a0ZM3LdYST5XfW9yjilLXcljKFln4NLoC3lzqzXdrmuxJY5Q7LsH12U/syIMA8Loe4O2Er80B3mYp7diWVQHALO/9CW5brwDgTEOtqA1VwAEv/Rkv3KXBdks1TRNM+yhr/6Lgxs6Yi8fJjVhMxn2cECSbe0wDdja2zy/FrxmDZDJjR+Z0QnZcssPB8qQ8mdhInH1Zir+L1ZPGtgDkuLwmJTz93LmMDeY81wGxWjyKyOZDnppZW5Rg2fpJrSRH7TvWMqlxpakp5GpxiR6nPODgFoE6z/iuf4OJIj41ZxY6LXs8lAmORLRVVUEKW7kzsVLIyGKfUS1LH1Em5IXfW3aF0WcNfUprn/O53gpd/1yz/s1iVBeqVZ5L/f2PcnwTM5u7f0rc004OtBBM3CJFUGkVptPXoMGImipAcfwzj1yLzWNF2VVUV2D2CcZWHA8zvFgQX9Jq5ARgbcxWFkGkTDCywuEdghFsEtCenYiBhqLrG319v4V3Kg9VgZSvrkpYsi8Aa2Drb9bCQaeRwJ5L37G+vwWcPpI9CTjrPvV8nhixdX+DQSO/9e6i2ovpxTRRaWPsCaDZMxhRX+4zHIARU+rjUsGrYI5lvAUFASRxR2z7wpoFKgG0ra5BK8RYgs3ehw3T/jGOWKTpfwketQKneWhSMu0ydOdHBJyXASE5PCzSs3EJx4FLbi/9BaNJeOnPsFTwmXvEC3taz7MSvuOBAoOv0g3OWVn2DpOJ+Mw9YK5eJusBs2RloTikYJGcbWrNS3ESUAU6bXl1r/c2+8TYTT/hhT3jC3/X9VpIAgq1Y+yHAgbm6pErNTXoIn0YVkpgUMDreGxk1mbsJseix6iosVQVySYW15btnXOyyIHl/0/LgHfDDp+PD/je8DU+tw/4h/099sZiT5wxvStv8S6LQVyyiMlyRlMBOxUYmxuPThUaAKAcWAw1Bsfv1/u4oiETn4i+thvi+mf37Kj686YCIhtuQrLXk8RHHt/EYLO/WVAKYbEFJViURA1qrBM2JWqT8nXZRxXR1eirOLY7LmMBBkabWZ/h3DqxPSfJXoVZDPCkWV1hlYHMgaAatqyG+GpsVvqbIUv1irYi4kPuJ+5+ZQN2BtVz6zYDrBkT+skNtG4TaBNHffZ40B3r+tJPFevsHpSftvJqGc37tvlMr6j3sCHl2EjA6i+ElsV0onzOt+U5zTUd106SCjEuEi1y4Ya7sat+lnrMJ5daH0+BCbp9/YqbKGsVw7262gX0TX2AS1yTiV2JyuFcbNMTU3SZZjelMmJL2fhH6afEkW2kddsaaHoggJHVs07ueoxFzr2AG/OGKu7yftN7AVbkGX9ufZ39dlYTNUsKc5YHtK7vsXU9/9hJz+jxaZBp3jqUAQPE0otnYiX9VuZjDZZVBgbKCNXiJ9nDlwIgIIPwf4Xv4Q/CJ3gbGMmWO3mpWrGRJ6qW2Gpa94Hu9tPnUz7bqhLPPQt9xkLAOgnIfp9ZBLZ9XI8PPZu/iKHn8cdwfDDY/OnPf4xSCY+RVWv14VYpdWCVS+8nHoBLF6d5aLLsIpnWSjqKcppE7kNRRiFbhI682E9cAOBcQb6JyLvMKq9NoVVW8r39MYCVi4H2JVZ9j115PM9lHQCamVK7qUWO/NmVEyR76l/TfWmQ6Ofrtf72ZDvPjv5z0utZH7Knn++ts/tr0tj4+j5TpHQh36Gcs/KbrKnNddJ235PeD7kQevvuRZxUVW7GdFwpwlMui6GKwSYMNjXUWAGXk7hHk+ANG3kd/QkhO5z80IACfanNyaJlSQ5fnQ7c+xFl5iSq4bPNmEeHZbJY9g47G3BjZxwtKzbH6nCX9/hJvMVSHB7itHG7jNVI8OBANZqEb/s7eMr4U7sCg4I3+YjHPOGcB7xL+1Y6UwUBQ0AQHbhU7Ea9AODnaEoj3pgD/sC+bOWy0SR8Ptwz30YQXjpUG22gjBt7aWoCqgQ9Vw8U6R2RbTyeVCxCtu05NKhNjFSPOZFFQRZ1Z88QeFNQLUAi53MYIr41PuITd8aeFjyUHf6Py6/iXAZ8FW5wyR5fLwc8hBF3lwnn88jPcOLMpETDpfCLAwUOAtnI8zpI/b6VtfWZpvZMUePcrc/CunCj7ULt+vf++bp+3vqF4h9hgvMxBhH9MoD/EsC3wWf4m7XWv0JE/x6Afx3AV/LWv1Br/S35zL8L4F8Da7z8W7XWvy6v/3MA/gq4+Pmf1Vr//Q/t+4PB5sYtLJNBFSGvfRRHBZPcjBtlVhmlEs5paHwMXVX2cuK6Wtbm6YeGlgx00idTYCyh1IKqnXLtUZhrcUiZ46+DA3E9WE3XzOYzXbAzHEBI0nUOXObpxN9vvA8urqwlLZmMNd2vP2+6rPe90R6RntR73l63IIbnj3vdNFVVONZr8dOPs1TAYPV6f85KWsfGmkCGkjmLogrrWtJRoIgGEme419F8jio7UqqPjOqTaXBbA5/h7JxM02bTXkw/8hUuVjOR65JVATXmP4DG3GfNsLk13geT2FqACl+j7rvS/ohm7urrk4pBatDpsR3HaBL2NjzJdjSjmRCRUZsumvZscjUwKF3mU0XfjEuUrq7Ooc7ktXxWWKOsXFUd+HtcS5Z6SgUkfSGPUxnwJh1wSiO+nI+Ys8djGDF3/TQiqUZg7TG2iolu1wjd+D3qIH1ftX1GFl991t7UAAlrsNKM50OjX8g9s6j7RY+PjEZLAP6dWuvfJKIbAP87Ef0P8rf/qNb6H2yOhehPA/hzAP5RAL8E4H8koj8lf/6PAfyzAH4A4H8jor9Wa/2779vxh5063cKEM1REGxGKE9l1tJXQ3oVmWavaT6Ua7F1s9WhV2tWVp46QLR7CuCmHDC5hcmo6xUimjWlVVf4EWkazUSwmndj1Yj3NSQkS8IRHAmzLO8DTiVIn0FII2dku8HRZjt7wpoIkyFj9KQTJVeVndX5csydazc70+Bs3Z91Ffx61Evv7aH1Zj0G21TZXLZ4ABDYPIhqqZ0Wc8feWC6smVwBZvv8ozf8isOaeO6PfkwINtAe0vZYc7GK2CORkgiuS5WQUgTjrvRGqbTQX9YGBXQNWc72sBqlWkU+pKEV8kIIVeC2h2trkj+4ka/mJucW5DM235YU945V7lP0VFBj8JDKsdy7co0nF4j7t8Ji55zGahO8Md7ixF2QY7M2CvVnwbX+HDNMa8q/jEZfscckeofDEq31Kb/Nm4j6noXnGxGxBVPGD80s4k3HjF7ZNkP/2lst3E0Vx4eTfJ+HTlMKKA+p/8/lwj1gcXnoGDKRisJQVip3r+2fVPsvliA7cXSZ837zCKQ2tr/V6OSIUi4cwIRSLc/RYhAc1jhHGVOxe8cL1EjxSspgvlvuyCbALNZI4DJCHykAjX1ZCNnV0T10cdZlNK/k/W2LrXpNgd10e5/e991L84sdHDDa11h8B+JH8/kBEvw3gux/4yD8P4K/WWhcAf5+IfhfAPy1/+91a6/8NAET0V+W9P1+w8cyc4tXWlf84iwfmtjJSL3SFsAJo6CLVUNq7gKGrYT9ixAN41db7vVtTgIZKQpvkS956jZOWkt43ZHKlbqLrrQp0Ilz/1n/Jz6z6ZSItIkxaMoBa16CjKZSU80ilWfS/q35Fk1XPZiWs9lowmnFdN/X7UcRc6uo5av0jhUtXkeLvehrbD6xBU8+nWHZLLEa82rEG4T7QqJNlX4bT6/neXhG0ArjK8OswMlkYqiiaDYLvJ9tlOBsx0GQaB0izBWsKEonZWSeH0s1FSMW2iZ/LVDzxeUq4tTObklFErqZ50+g+EiyWwoqx2p9hJFsk5RH8AAAgAElEQVRay4OUsDcLopiczZXl+wO5zbG2hr9UAPgZyq3EFgujvQBgNp7RfsVi7wKSjSh2NTlTCwBLVUp2FbY+XXRNxPBzbxJicViMAxJndprRKFbuWckf+X50pGxwCgMGs8OX7oZJvHHcwtmlykFU4Wxlfbkdc5++rgfMfAPw/ZMBE+TRytTMzAoq4GglWf5syfc2+2mvdXqHulDFB0jXH72MVv+wweYzIvob3b9/s9b6m8+9kYh+FcA/AeB/AfBnAfx5IvpXAPwNcPbzFhyI/ufuYz/AGpz+wdXr/8yHDuyDwebz4QGAypNTW9Fd8orH31luqrKzoMHbZY+7MDW9K+VCsECjRzKGDarEIXHODrFY3M8TUja4BI8LPJMBRQU2R9vKT0/8WT7UsKti6yuN4rX8JD+ptn5F+0hfcuomef6bbDN3L5JmHxWtP0S1KVJnoJVw8tXqvtlc507FOvfoLbAulO6nm3irmsgVgILhy2CxotQ6B9P1GNd+iWZF66WSC1s5UAJiPuYyBpdwGHjVfI5MJGzeNcDGY74CmwxOz0UdLdt1pwprWIYlFXHFylsWvUKSs9xL2qOxpiDYFR1lqLbJrD/HvY8YrUCmJ4sUuSFtTEWIXP7SAKX2y0vxeF0cvEl4k4+YKOKVe4RFxV4Iiucy4mwGvKED7tMIVo22uJDHzh4xF98gy5FsI0/epT2W6nCfJrYzSHwtkwBgcjE4L/xcxZ3FlF1TO5ilOpCKadWFk9glAGgQagvu7RQYth7IHhmEh7wTIzWPt+nQuDuAPN+VS4IKz1YItPoLnUXZ+RwHLMkhF/lOCsG6jGp40ZMy20Z8NR+RCpNAUzE4B/7pTMFu4KrHcViaHFABYecjLxBeWiyjR14s4tlyMFBu2i6DfIEbEoYhIwSLePGo0cAEy5QMEN//hR1BKaO5byqAqHhdqK5WG5s+z/uCysfOcCr+sMHmda31n/xpbyKiI4D/FsC/XWu9J6L/BMBflCP4iwD+QwD/6h/mQK7HB4PNJ04goNJkPJURS/F4yBNMPABAQ9u8izs2Tboc8PbELGQ1rjI7lh4PYok72dQ+d/QL5uzxQOxjkqRslqJlQ7QivuH9yrubULeBZ/11tQ3Gkwm8IbQMgMI+OLVc3V2kwQjo8dG1f+9VqatX99f3FCIuYdWCcqWqrE35UmhdfTcwg+yvW3G19kkFS/YshsUKg+xrrIDrygDtPNbS4QYY0J+vBOb2flo10QbHpMhSCefo1zIYVg7OBmUmGW4ua9lzRbihAURqra1Mdi3ECTlegwoxcRVpFNMUJQAOdEbKcQrB1hLPwQdeje/5s4/ziCD6eilaRBHU1PPwlNuCShvy2h9hMckASzOmEjGWsWU6a4+y4F1k98qjZV23SLb5vtzlXYManxMz8rVfo73N8zygVob9lsrPyo2fYWhEKA4GrEWWi8Ei13kwiYODoZbJ5GoQwPbOc/V4l/d4mw6Yi8dDYs3DwbBCm/aokvjS6DkVUAMAhWKxZIcls6uo0hBqJVhbAZvbYihk9rTJlRAkMM3BI2cDt1swuYTbcca3pkfkyhYTqRjsHAcbOlaEyeKyDJjHYSVrmordPmD0CdMQsfcR7y4T7gu7+lIRvURTUbHSNEwimIUXgWUQ9Jnj5+pnDiw/a/b0/4NBRB4caP6rWut/BwC11p90f/9PAfz38s8/APDL3ce/J6/hA68/Oz4YbN4mxsO/sBd4Sah73wtFx1gqeDWcsbORWcbBt4cnU4ckMwWDENwuYgc8Z8+rUkmvY7Rs/xwNajCt/9DQV/KTZOV+faM0r/rWt6BVGXoTrK4gj9c3EqGl0g2HX7eBYBMEdBv6PhlFjr0Y6oLS1UGXDu129fn1/Ptj43OvQwEKIRuJh662FeCTjIx4v0Y//0z9evsZQkoGC7HI4r3hCaoX4KxAUwbopW10sq/tXAtDXJ/sb1V37stizelSyrDydcCbAt/sDbYlSX2Pvl5rJ2kDbu4PLrdjqpWwGyJuhxkHG5oTZSYOespJOecBb8wBU0ks6U+xybC8cifcDxOW4ltD/eAWHO2yQbdZMPz4xs7w5HGysrDqYNR6TYeBn7OdT9j7AGdyQ60BHFz3nqsCo02sGWcKUjV4zCP+YPkEnjLu/G6DWFvKStjsr1uBlsfNBrjQk01jYSHTWCpGm2GmpQXIHnqtAqxerChsK7mu/Sa1fB5MwsGGhoYrRLgkjznxXKDEYCc8G0WNHqaA0SXsfMRoE8y+YucTQrY43Q4b8rBWDlK0iLMFkoE58wLNLgTM7JWjtImVpiDPfZ/5/1FGmo8IfSZW7f3PAfx2rfUvd69/R/o5APAvAPg/5fe/BuC/JqK/DAYI/AaA/xX8uP0GEf0aOMj8OQD/0of2/cFg82W4YRDAFHAr8hxRVj7MsNYHiN0Es+g9XZLHJXrcnyeu+WuwEQOrUgmnPGAWjaWmn5UNcrQoiwWCgVnYHKp6UQawRcyx6taeGl22oRO3ZgmiNrB573NQ5+tBOkPLir/iqfKyBiRCl9J0Pwkt0D0pF7+v31Svf15nXJX7OrayVa6c6ybz7q+NBgbNtEy322eynKrvrWy8VYpBjJw1qG88yYq6GV4JyU57YNMQYU0FwM6WCQY5r2VADUobO4Iuo2l2wx2/Sq2dVdhTJ04t5133cAA0YApRbTps6iBqqeLgA14NZxwkOIwmNvZ9LMx1uYDJmKNJyAPhxsy4sRe8NGfpzbDXy5fhFqUSPvFn7E1ols06YrUwVLAU7g8BXELOQmDU63IYA6wpeDldcPRLO4/QSJYM/+bykxiaSd/plLh8xQZlSfTUQguEwBYBqERN7RcpF2i0CQfJzAwqFmIx0EAW3udGstaFQF8e7b8H/XumiugSUrbMw7EJexfx0p9F6ofJrqfgMQe/Zs2mYtoxAMk7NmV7Mc6YbGx9u+/s7vFqOLU5CAB77wjgIcPgIU74ejngq8sBP/z+ZzAXA/9IMAuQd0o2B8ogJefnFmLQSsPHDzofGY32ZwH8ywD+NhH9LXntLwD4F4noHwdPAd8H8G8AQK317xDRfwNu/CcA/2atNQMAEf15AH8dDH3+L2qtf+dDO/5gsFmKbw/IbHwzYFI4tGoweVGVVZbzxoue1AqWw7WCBlKx7WFr5Q/xp4etrInkpE7bs+eBbdnrajJ9ii6pT61cn8tonmQ2tKbO73vPh4bu47lVCsn/1A5gEzivsprnhta7nrsptdb2zEPRxHC7jI1/StBSUpwkWCR2AsbUJ7F5zVrWbSsQYnCZ+yrJIRc0MMbK3dluy7SAo0Qo7vX1WmxZ7qe+7MWMeyO6ptussZ9Ue2CGBhoNXhrgcl3JmwqH1n7FJa+Zy6NlRFmxplkxW9RWFh6lV6PHXGCaOrM6YmrZqu9PKRXASvY2mNS02GybvLcgHUcGlraBJFUuC2s/yqBiBEvjeMpC9Fy3V0BNKYGvPz+Peh1U9eA6oCvK9DpLJ6oSTAIcmQZDz5WQbcHoUkOkco+ILR1CdsLVWr9LI1mbNSvyTa0PikCj5+SxFAtPBTd+bmXBUolRehRQHPOJ5uxgDhGFHFIgWAPOaipY/ipinW/6BWR/fs8Eol/4+LhotP8Jzy+1f+sDn/lLAP7SM6//1oc+dz0+GGzexR0MFby2Ry4pFBHYk1XEZCJeWF7h5XxEBN846m8xuAxnmZPDGY3BnAxDI6PfrEy19l7GiOwM8mhQopRQpNbPZSxCjfS0pKVDMw1beRK3eP+XJ70gEqRSPz9vFJV/2tD39GU9OT6V7WlcAMLa7JS6cSsP8gf5s1kiQ6lrGbHfl2Zv12U3/Zu8dy1x8T4UHQf0D3XdoOL0WltX4EWdWS0GVE5+BTjwrqwtOEyhNX6dKbhfJkFQFZCTr6vjZfV9H0cs3QIApRaYYhDLrtX8czHcWJZJX+2K+2wIwCYbagGnmE3WY4h7iM4wQdPJva33OGcJIx7SiJBdA7xMAuf/9vSAb4/3mEzE3gQYKvjMP0ipjEttpzLioeywFI9zGVpDPkvZaCmrNA+BXT8tVW6SU8HeRdz6uUGbL9njNRhGfE5DN/lvVzMKpFBwjgaMWz+zRYH0n3JlS+xYLVK1LaBZcfF8iBNiNYImszBYG/mlcsnr69O+0RL0fiICXh3O+Hz3AK8WDiC8Xg6Ys8dgUlPPfhf3WIrFu7BDLAz8GP1qReJtafeELjreXXYoFViiR0qmUQfIcAXG2YLjuGC0Cd/d3+E7010TaD26gOULh1MY8OZ4xDJb0MnCnQ2QALcQqgXyHmJJXduC84/MtbNiKwvxx2h82BZaxlJcs4UF+GGdTJSV0uqdoVmP1nL7MkmvuxTF0Gpdha7ZkA4CBBUFDhaVnRhXUiK2X343wa4b6Sbo6z4IsAasiqbrtvK+OgXpJ9vtd9HbMndBod9XCzzgLKt2WYmex3W2dV1G2zSG+vd2D0GV4yFiC2vN7LC6cF438/uVJGcgaIROY0ornVmzNtMbJ+jqv+uja70UWl1WeyHH3h+nL6MxpFYymo58mYtpPijUbZt7UetnP0QT1tW5pTWr6aViUjHcS4H+bhr4AOCS1t4F7OyEaLn5b0CrjQDUpXPNZs55VXbOMCzXL34w/XH1v2up0KC23stzpUJLVQi129evZXB6zozZ3PBPA7ZK2DC/h49zEKJnkWxt7Y3p/QAQPc0+9TOOJFsz63yxlFVFQRecPeLSSe8HYEh4rYRsCqM3K1BUqSITjK0NuBAccwAV0t5f39EmZGfgh8TbiAYl1FXYV+DVTxaaP09140/GZnww2Hw2MqntUgY8LiNu3YwX7tJIbwCaN8breMR92uE+MIQZWCeCOfmW8agScP+glWIQFsc3TjSoiUBuJUYagScnsKPfBg12Pbn3Gcn7AlMnX0OJQIW2waYSqPVHtVbL2+af67+BLrUmjTfPl8L6ClctWkYjroRSl6VIWv8EjACsPJyrDIcqo9KoAMUaBgv4ijpyn6ua/KR8dR1omgVzN1lcB6eQGM0Vo2Udq8LS8Dlxb8dQxcNubJNKX2ZR4ABRbSv50aa22h1temI/3BrRhTDDodSplZu0WW5FNcBQhe1W9Bqk+oAG8IRz9EtDRXrKraRzKYOgrlxr4Hub4SohyvZ+cr7Bu2WHo1/wME0YTMLRLrBUMFfHkv6S0SzF4V3cI1WDuzC1nqZCnq/XS5fosZDDY2D+WS/DM9kIQxWfTY8bz5tLHnASxQ49z95d1EjpEEBDxXHG4zsZntyQcs1NtDLMulbC4BfcuKVx6h7SBJUF0qa+3ifOFDzGEbNh2wEATY5HszJV5zZ6D1gmqep7Y7Hte2ILCf6bBuofnW9xd5l4QZAsvMv44uYB3mbuAVeDH55e4PcfPmkWE7FY3M0TYrINfECvEvAKyMkiBstrwGS2waWrTlD82GW0+lHLaP9fjg8Gm6Nl/wlVhT3aBaPpU3ESxVvfHtbrB7xUhp0SwCqv2TYorI6cGepcMwFB4M4oELUOWFtRawXJimZtNmCdhDWreG5F8iRL4N/VBfD6PaSBqL8YBM4QSCX/u3uiy6qIng80myGZDFVilEt/DJKyq8BpC05q01C7c24pvvyXwMrcjnk+uQLVdef8gUFYg0vfdAeAJsLZymem/d6UFAohi198sA5ZFBP6CXDl1/Dkp6UsXbE7UqRZgat9uQ2tbBez5SqpIVhjMLnU+hAqFpkLA0sK1Q0Gw9CapQ2GeTV6fFrnj8U2YUod2hBfRA9uTq5NwhqwLEoLsD2E+pIHLMVubJS11KeBdyOVBH5eQrKyUHPwNmNyqfVxji60Hgz3ZnjS1l4NH3Nu2aJp1Qc+p7UvxX2qoRGyzar7hpV0rNmkLgwU1n3jZ3jDmUM02/5TqhYlGyRaBXZLXTlFoTCE25sinkQqN1QxZ0apcgYZsbMRL925ZSuxcilRLb8XALsh4pPpDEcF78IOJRMeoscleKZdDPzdLdG1DNtaNnDbj4H9eZYBORvm7WRay+xqaVIA+lDa/Isa38Rgo2NnuS7NUhs3mEzc2NECwNFxnT4dDEaXsCSHe5GimaPbpMYZaDDncPGoyYBmuzUHI2Ea+4IiPQZrC6ohblVQJzPOn9h+R32NtWUeMrGTvN+gs5VGK5tpBrIZhI7fg+fx+e9Ju2UeeFLqq1eIurX3wzVjDYpVj/06kPbH1r1uIkFcugDiLKcYC3KllZhUGLMvgSkbXNFiThq6ujIslTDYvCnJ9AuIGHnFOA6M+mrfuWzHkFg9Yy2hOVonfG1oA8x+/3R3xu2wYMkOsevDVMlaelSclnfaRIJViqhvagNsJa3Q3oc4bd7jTcbOBizFwVFBEBZ8LnxMtdsW9088kjU8ESs9gFagAU/aRgiOrgWRWgnOZuw9m795uwaHAsKPH29wXjyWyJn/cbfg0+nUSK5s/8yfOViWrQnF4V7KVv356FDgwymNLCUzH1qTX0tt+lkvAfYkbqfn6PFje4u9D3g1ngU0YFq2CgB7H7B3oXGDVJ1B9d4AwBXLqgjBYg4eQTx8LFXcjnNbcDjSAO/kfGvLqkYkfGt6xGAT7sOEOzNhckwU1x5XVKJqFDmgB86wrPQe92OEE8Kvzk+jT4jGysLXYv99j93rCrVPCS8Jp++y+OhHHd/EYGMFnaJSNKlYvIs7jMY3q1p1DxyJ/ebtWHDjZrwJfCMvAObI+HdvGTAAiBxNIdSzA0WCnZkNXwZGoVGkBumtIzXpF6BVwABgU+IhoEmt8OROTyb4Bmkm2YjRbIH/q26d1Hur5mdNyj40tCRGwAaj32dizw0Jaqtzp5bP8AR2uR5bl+xVznDY0ZBYEysD2fPjXixniEB5guDSk7KWFXadzTh45jXc+hlKMkyyGnamIGSGxc7J4+7CE7dvaDQOQrodb3MrBWkZVVWGAW4CZxA8+LVXI5OK5+ybC6aap53jKh0DoPVcdPSlJP23rq4Hm9ukrkoYivza2dDsAqyspOfs2yTc9xRyMVIWSohOzcoK2wRURp3pBJ6qZS+e5NYMj1hdYzBcLrJUm2jnl6cjr7Ijc85Uy02Dh2ZeFgWT5SxHe0PXfBoNPIqwe0gj5uzx1emAJXqExbFPlKIPbcEofJ8lcNn0PA8Mzd4t3Myn0jIRzU5fjhfm2xnOSJbi8Doc21yhihBBjydbQLITK4sPBWE4SSGUCH7JnO3uDXOiXg0nHNyCwWQs2WEUVZKdCXCev/N3YY+3ZoewDFhOA2Aqxl2E9wnHccHBB7ydd1jiyChAx8TUYB0KLG5+v+Dl7zy2h+vu1w94/IeAMvwx9QD4yOODwUZvXk+8olDhw9Ek3AhhLYMQi8OX8QanNOLrZY+3y77j2XQ3vSkwFa3UVouRfgmtEySYSV+GymJ7RpWSualYwTpYKhlTu3JLq6/2vY7N2L72HAqtbafvvVS0yb9S5bpSC2JdSevJ7uo2q+rf14KO7vOZDfQVuT7ASeal2lBPsjMHVAv2D9LdZ0KFQbV1bQO1n1Lq6jItzR5SNaBsEaxtKKQkXJRepqbv7VgBFkyeJyzfvU9LUifRzNJJUevzg8mCyKowMmkmKkhU4KRfZbBtQhcQqNI2gBHbFlyTP1NZZXBQ0YLOLHYG2ttQHgsAgfFyRmLLCmxpCEoQHtLIgrVilqZ6Z6GsVtGD9MTUx0WRY84UvPSXNcMj5tkAbEi2GIdBMkJHBV+M99ibgL0J8JRYJUDUDBTEozJS11ldkpLeJflWztZFnBInrWVzNEPAKN+hbdd0LT9e86Hm5PFoBgwDzw+WBi7RgYN2qkYWDlbKkO22hbkCB/SlVVWhtsQW3BkGb8IBD2nE23mPd+cdvGM042QjXviZF8io2A+Ry3aOp7ooyiSPLrd5aJAgo/e9jjwQ8sHD3S0w92ccDh63vzuhuA8JMv4hR8U3E412yvwAHYcHvHDnxqmZKODWzgjV4ofxEyzw+MH5JX58usXXDwfMdyNP4on9KWifYNzK11Cpi1IIYK1P2MABxyQuIUUrpSS7lnpKNFvCpmYPQEt1nsiNA9tJun+vNOE3875mOf3Pbnst44CUwbQs9yRi6T6vgwzwRCq9dwNsiU9d96efu87OuvOrmo2ZimLRQAwK36SFQIZQqHIvx6OVIa2VspYp7fvhYENsv+yAkJlvcR9GJNEnI2LrZvU+AdAY5ErA1OCicGSd3O+WCZfgERNPvIfdAhxZvuhoWTMrGi65xGpgisVACYNBa9r35E7mh4iyuExQk40bjo02pF3LeFYwgXo2sS0A4dYt+HR45EyqWCyGPxvK9pFRrbJLOsCgIgy2wbMBtAm2VMJhCBisxZvTHjFaxIEnaUcFXwz3DDAo3JP45cM7vBwv+OpyxDs34WZk19KdDfhHph/ilX3EZCIGZPx+eoW/v3ze9mdQcXALm8GBkXcPeWrls1Mcmsx/KUY08Er7/p1IFI024/P9A5cdpcf1mIaNErWefy4GD7KAuHULPnEnjCXinAdc8oCvlwMuQuIOmR06dTibhQS8HU6g01o+A5j795gNfnS5xdeXPR4uE86PI4ytmKPD6DK+fXzA0S8wVJrI5xIcE5BPHhnAvalYRov9EHEcF1YfF8WJJvy6JywvPfxXJ6Tv/wMMd/f44vXnbMz10UYFnhFN/eMwPkzqzKwRpVayhQwKMQV9KOzEB0Ak39lq9zQMCKNjpz3+IzP+aW08t0ADoA680s5jZUBAQ3qhm6i7n30G0Gce3e+bv/dB4Jk+DPpNUve+60DTZyjSW6JCa8Zxvd/rUfX4ux1tgk337+fOR49DodP9OUiwqyAmxbLSPmcxwuWh3pFQg5pcn94e4PrfvNDarjaB1fpZEWUA2oQRsgWJRIkGG4BLP5ohaaM+VIeSDds2hxG1Et75fWsGl8pZRxC9Mg1WaiG9JNdq/mtzXBnudqNKHARubFCRpLzmTQYKGp/DXZWp+LwLrPQQe0jx9VAUV2+jodmLrqLb5yohibXAnB0e8whvGFjAZbdVqkcBiKFYXPKA+8JSNHP1Ekh2Qhg1rRyoC8NYLZY84JRGvIs7PMYR5+iRRD7GGCbhslMuNgoLRKuvTqmmfR8N1FEMANfOL4rtyH0a8WW8bSRvI/5XBSRIvBV8oGTWBkk3BY6yyPDkLjNb/X5611N9NmoBolgXLNmxBQXQtmVtYXsQcbct2SBGhyALI0sVex+xmILL4pnrNwFxbxC/dYAPv4J6mBA+26N+1GCDb2bPRuvZho64N1ODiXqT8ZpuYOWmnkzEbxy+xK/sHH6we4kfHV/gMQy4O+02ulk5GyyLA+ShI1PhXzDiLR4coz8yl9XaipzQvFCqlVJRXyIrMjH3i4HrElf/Wv82AkQaao1jLVNaeytqC00SKKrB2lsRyHJV10yg+Wc8HfS0NAasMjjXx9oFuQbNNmik0OvgWx3zU5iQxoG87hP3sNTzhtDg46UyyqbW0lB01z2JmC0z2kUmxpuCYjMeLhNCsKj7pVk173xELAZvH/ZsyVzFodUW+CFxGekoixPHZNHLMiAng8t5wDx7vPEZj5Hvu/MyIMvk5oTgt/Ox9WxU4LEUA+8ZyKClO0vrylnRVSFbkVTSvlPm8pVjaK0y9HWc89BKawaMsIqZJf8VTaY9p56rErJt+0yF5fUVxZZFlqlWwhIcvs57BAnKrkNu3ceJgRGSRabCiurnNODvul9q0ixsB2BEDqfipecKhJa5vww3eBd3eD0f8fp8QEzcmAeAaYhwvuB2mnHwoZ2DWgKUSrgLO9wBLRN6tTvju/u7dq6X7PH6fMCSLFI2eKQBl+jxej5i7wJ+accOpl9M9yiV8Dvp23hc+LqWsi46nGTCk43Yu9hU4bXn1guEArygmFzC2ZQ2JywXjxgcHgbO6HYuMmDBRYw+wRi2zKiZkKNBDlxSC8nh1eGM33jxFS7Z43cr4d5UzJ+NAAwev7dDNTuUAYjHZxRJfpHjm1pGU4M0XtGInIfJ8DUjG8O9HBebyODeEu7TDu9cZFlxlzcrkJyBqlpQZW36UyVUzzLlNYn6sUzovbJzIyn2C/uWcaALMs+czHX2wR9uvzZBlidNeKyBRu2Un7sX+kBz9dqT97VDfiYbe99n17TkyXYaoEECXguGUibbABTkPFRlmquApm1q07cBVqRXvyoHmm2CrtwBXhWrkVoV/k0tBHgAZEHEPJI+29Edsb0CIYFNtIgqw1QL3xu6fWDtMUGPT104aVWRNqCr1bDAeIvZZClONP8KGVhbnzTXr0dBp8fWZWwbgihM60etgpVdpmTYaVale0oldsLdrOSvnEqrlDQB5sJYzbB6YugKh9aRqm3cnjkyECBnahwrK0HOdZheB+4bGXCGpYuOmLikqOfbB1nC2rfLlVFkfYZnUQAym8WMmutpsFlh8CsEXs9RkX3tXLFmQg1VmdlzSXuN/ft7MnEx7PNUK1rQ44VUZs8kyYSWsSLtCWlXkafKi7dDesJX+5Pxs40PBhuFhc7ZN0giAEwu4oW/4NbN+PXpJ7gxF5zLiFAtfg+f4X6ZEGXlZ8HllVLBq11Igz8x+kW5k1rCoUH4GJZTfGsrvE+8EqzgMl7SzmJdYYhXfZqNYut7+imbDKRDfTW4W2USl1GNewDV0KqubPEEAr3JVuj9+94cw3OBsM0h2z88kdGh2oILwNlNy4YSoZ4t7yPR6gsCgM62ofGKSnPsMowrfO2polaenJSZDQCXyMTcEBzyYhGcwzwyX4JVigv2U0BwFvN5QE0WJVo2NwsOYXEgwwRSIiBFu5YzC6FkhqsSiQdOIVQnlseOIa8FhDDyJPqlOTbnx811pdU4TPssbeIkbpL3+n6qipzqSjZEl+g0zgrqJuhtSKjgSfbSBeaNr5NIsbzcXWCptIb2c8FckWenMuA0D9xbM8wLeZiY8LmzAaOJT0irAItRAkyCnJPHKQy4nPlzZJgDNUhT/aQWZzoAACAASURBVDEOuA9j04wbbcKnkyIBV3KrKml/vRw2mdxhCM024ChW8qoasBSHBUwWDcXiMYwtW512CYNL+GS6sMKATW2e4e/KtkATrhYBqXLJcHAZbsgomTMVVGBJFqcwNGh9LJZlj7I6AgPG8YShUOiQLX5wfomQLWa9nz5fcHlpcXh5wXdf3GHnIj4VhORHHd/EMlov0Z5E10nryYNhqOHBLLg1szQ32dNDfUc26CR0K9IKhjWDV7T9ZGskyKiGl3ri8PZ0BdW3Prp0plv8Nxe/9j5sggIA1NLZycrfNXisVrLYELkqrWWsjXp0v6/aBZnnVkF9okEVT8T9+mCC7XufHZrZQLZVqgAoOFhqdtb3gkwUlQTDAbS4yv9VgkFu3ju1CzIAVlKugDSKyMmsPZPSEEyLBszMB1hLRSrECEM1mZMya+2IojmL+2jTYePNOFNwcFw+KpZLOPduamCGHsmkP5sMTquObjOGawmY3E36z2U4LcCYbRNXV9Ex2yef160PhiHhiro7ONbsUhRnP/S4tMcJoH0nITNgYTQGRmgJtqsj87lxD0czkSyBHARYw+ehYqRzGLBEB2czvF3BHRpQQlkziNJlWE0xgBg2/HI449VwXp1PiYmiqRqcE1tgN0sKUzC41AJuK0eSupSW9lnu2/nNten7fs5lJDC/CUBbICXP1Zhm9qckbgCgVTKJiGWRTnEQtQrezrQLwA74lU/e4h97+UPsTRANvI/cwP8mBhvlMnhRADgOC14MCz4ZLvi13Wu8cGd8Ye+wNxGmsGcH6zjx6vQ8DzCm4mY/w9uM425BHgNOlxFBH0SVtrEFZADnE7zPrUmZZVtqqKaTFAksmjpkV62EGk2Tl9jwbOQ9m6GBA0Djzlx5zqSRVumYilUVtv9MX9LSDb8v1b46hpbZYN3GBw2dni0R6mwsJTOxYdC/VWD10mm6UrRF9FXAnHllWEbDKMB9wrQPIGKZGr0utQLW8fdlDJe7aiWcDdfio6wgrcuoE5rkEBFaRjO4JKUyFlSMwaGeHWoxCLIqr3LdSyZEb+FswWniv+nq+XaccRyWRiY8uAW3bmbOhghOvot7XLLHZEc8RvaS0TLPJXsUQ02t+TGPjQeyCJxYSaxHv2CSEnFjxIt22iV65gnpZCoToaUVnXfwCwbLsv8KqtCsa5J/axlpj9AyDXUzPQcPa4pwe9jOw9Fuw2FRHo6WA+/j1IAX1hVYVzAN3MP4peMdDi7g7bLHKbEDZ8jM7P/B6eUma9MelUKeexTauRE/B9xPO0wu4kbkZTalV7k3YrRsYCfcu8HkDQfLCVJQFwTr9abGkdq70Mp0c3QIpiIF2xQuVHvRiKzPcVoY/Rjcel8ZuSamYPIJN34RN1IPJFaUzpnw5rLH37Pfwoth3pRMP86o38xgs6h1bjawhhm+nwwXfHu8x69PP8atmfEte4EnoNQFMJDyi2gfzQ5kK+qOm6z7iTMgNjRyKFmCAwHGcy17GBJG4SMQVZTo5OYUFejCqgLGFRib4dyqwVUKMXImGdY3yni+RKX/1ia7QKypCzYbvxwJZBuTs3479erf1xlI7d7TZUKbjKbLqt4baD40CIDj4GuHDD8kqLQ/UW3XVOv2OnI2yMkiLxb2zsIshDwxz6kMRRw16Yn5mfMZtTJcNheDkAA2AGTGe8XK1naOV7HWMFFUpWoMVZxswRIdcuIJiJ1Z5ZREsqcUQkkGlzE1R0xmrxe8HC7wJuM74x0+H5h/cmsu7ThDtfiB+RSPeYQzBzgqeBRL5iWxnAzA0kzeZJGtMaKY0fdDVn0uleZfsmMYMBksavol2ZmeH+Rcvck4+gWjZDReNM3UxkCDz0ouZZM2RwV7F/Bu2SGIptecPLJK5ktAUtSVwq4VefcQxqbC7ocEZwtupgV7H/DLu7c4SnZ1Hye8ng+Y0x45udY3G1x+kilqL+q8sBfV5TRwabyy1M6nO85wgNVTqPVdCt9vJRtEqsje4DL4JonjKHN1AyuPRz+rgqvO5CZlk4rBeZCSoRmBUqUntcpmjS7hUDkjfqxTAxi1jNlyOfEowebOTpwJFkLJFo/ziB/RLc5peOIP9CfjZx8fDDYvdnPTRPI249V4wkvPN9Hvhc8AAH/z/KssIR6PuGSP7z98irMYIPkpdQQxgVEKekYDDc1q4MQCksGWfj5mm+hsGXreGov8EGuDsZTeWtmsjfweXPRchuMrZ1S2wrrcyjha3ltdP3uLg6ttaSlPA4dkCxu+T5/5PJfFWC7LsVugbKtcvV9Hec/fiAMkuQLnM6Zh5b7oJG+IlXEzgJT4oa8a8JOi1eoqrw4JRpnFDgkcZHrxTmvLBi1WgcahYH8bwNvcSmustbWWu7Qc4nxG3iVcoT94O56D2m6I7UFPlZCKQwiuTYZLcTi6BWfHK3/lrHwVbtg2QAz7wlWpK4m1gK+5GXmZSm1f9nrxYHILOLOIduZCzZeJRULXxrc3vHq3krWE4pBgRU9w6yaq/jUWq2KAk/6Okg9Hy3JAWn5ysnrXwaVAhyYnQ1XQWAWHIeKLw337LMABYZagoHJEKftWUtKgo/2cm2FGKKzZtiTHQSZaGMP31yV53MepnUss/Nol+ZZx8L3D1hV7z1np5OJGH08BGM5k7OV1VS2wxIomfa+LqAKG4ByX1kaXWPFCVCeioABVj0rv38mz+okXqZ9BOFzGVDZ+ixb3lcu1P/Y3G+DDL3xUAOUbyLP5lZu3MFTwreERO8veHXu74G064G8/fBdvlgP+3k++hbg41MVybX7McGPGMEZ89uKRHxxJv5fENdsYHWoywGLg7qXOGgnVV4SujKX+9TkYbEpiBAEP8CRUq8BJM6EmKQ/ZCtiyZit90AD3fdwUMQy5TYYxmwalDdnJKpvWTOZ64t84flYgG16NF1VgXmHTVbgvMAJLVq8dA9CUYXxp5mMpsWMpAObNdJMdq2L3qrRdDdpztrcbA17s5oaaAtCk2i/GI8IiSdmKMvGxil87gAabBoAYpLE6W85cbWkkUCJgdBnHcWmr3lQMLsQBc3CpeZKMLiFmi4dFymBdULHi7ulcbhlqr18FcGA6+oBBEEPKWlf9vftlwo/cLW6HGZ+NJ1b4jawKfE5D43xsOC+gRhhV5v0i2l3OZDjkJiHTD+bv8DGchaSovQgnkkxeVsuDkEv59wRPRcQkTethqLQOUOBp5Zd4YtkWL9s4DLw6P3jWIVSm/GhiMylT1WqAS42OGKquPjmvxjP+zM0PG4F0KQ6nPOAu7GDA1YtzHHCqQ1tkAADtZy4B+gXf279rQfqSPX7gX+IsopchsV/Ma3PgbMEtbFkdB5yXgdXdowENDPzZDRGvxnMT3DQCKgjFoUjWZlDlb1Wks0oTOE3VrtOCYWTr6BNGz/psL/0Fc3a4RD427jUCcPxsDS7hKJpujgpgE24G7qk92InJt4tDOA0Iyypb9FHHN7GMpsxsrX9PJmKi2HSjACZH1WiASKDIcih15EmDsCUC6iDick8124WswnJLNm2CJQDGraKOAK+unRizjT4hGdNKPUkaywo02Ip1Ys1QAIxjwuQTnGW2NJGVYNOpGV/3ffrRZzlVsimVjWlBgm9u/Xc7jUp8MMJ5qZm1tDTAai+rNuE2+Vg2zWp6cxzEcE6YtW8ArDIjjgq7MoocCRkWlWS7bf68tEpQxgIIKq1dP03clMxpOYqWKirLnXqzNazSrat7K6t7g4rktxXvXNgBppe7YVjuKnujJanR8QoUUj4qV/eV3mdNj6ywN00P3+5FJ9UxtknUYG1om7o2qlOxDYaro2UrpsBVLhMXoJ2zl5KWrq5Vu8uiNCqBHrP2adozJYEwk2lOlnPmsp8hUXmu/BnuNbH45AIn7rp145fDmQAHfc3Wes04R2X9u6BhltEy6VRu057hr3wkDdCW+HyjLS2Qt4AnquPNgE+ydxV77WHsRR6c9drog4P1393Q8lrf1Edr+vN1Wgpfu5Bs436hu9+a35buU/pBBhWDS0jOIBZqj3ou7Bf1Ucc3Mdh8PR9gTcGr4QSDitFE3NgZsTq88rx6NFYa9ZlgIpBZknkTHPqar/qmuDExguQgmYNmNImQjGWXyCGBKDdOAMA/D2NoMilHv7CirqT9SkbrCXdN18mwW+gpDUjF4CArGl1l34Ud3j7subykpaV+1Kuf114zQIPpVq+zM1bSaVmRYVSBCiFVAihGyol0VUaD7kLKc5sXsQmExVjUbBBcwZwcBptxO6yNWqqEURrz7A8j5UJRe6iOeyzelVUviwDUwpNGJSbCkUEdMpxn75BTYFdFXXmPLmFwaIuN0SbcDjMMKr61e0SphMc0tsxgTq4FqFRXNJreMzfDgqNbcHABt+6Cix2aDMxoMyKxgCN71LBETZ+LKIIsZtuQkklKKo8CyR0km1C1gp6Ho2oDqs+l/i8YuDcy5xUcMIhtgsKAdzbiRjKQV45hs0vhzGaQ7fbZE/cpGPK7FOBt2OPr+YBz9Hicx8YVmVzE59Mjjm5pOmnqn6MWyHPyGCXQDSYzudFkLNU1BQ9LBbeeCaCjYYBFqQblyAHjD84vMCff7qFQHN7FHVTZoVS2ft779TkCmE+VixHZGM6Ydi4iZYNTITif23OZqmnHrUMDr/aweP/MpUI1YtvA/KFL8OyhVbdB4BQH/Kje4vX5gNNpYlCMrN2slJsB4JJ8Mwd0JuMLf99Qt++GHd6dd7jUQfrX9iNnNvWbSepMVZSYm7/F1lnQkJSyXGHRx0TSaK+N9Q+sJZNWWwV4BWILqxBfM3JbqYsb3FoCUmmL0ebGNj640HgRGmSyKkw3Eb81FS+gVjefLNsM60pys+au71m9PNezaVkNsCmrVX6DemUCbINwrRig/Z0qmdBGEUHfqj2rfj998CMIgIH3kYtBMVvFY0PrtVxsgXUZxYi3pDyARBVWdLIArPwnU5kI18NH3zN0f1rb7ktIo00N3dULcaZiQGRBuUqw6ZrS6GRyqt3Ak/USae/CC0ExG4E1P7NK1OyrFxLlVfUKjU56TxVCkQmvFGlQU+ZSLqrYnVMTG9UFVZPEF7+bSdBu/J731+Rj2aoYaLmwt4JIxSALHygWi0i2uYIqwGElTtYm/aL9kCz6aVYyB/W80azHGeYeDSZh73brcXWosCYbI6U6EJpeHfd8LLJZs0IlYBrD2Q1RbWTRuZPBASTD/CkTOts22EaabYtbvf59ltiXz6UXaR3Dtb1dM3KAg5yqM+xdQPQWJztgtvIM4HlI/J+Mnz4+GGx20rC7ZI8vww0e7IQ36YD7NOGrcMQ5DfjkeEaYHMpLNE+Iya0wTgDNVlf95FM2zKsgADspuXUoMDLcsB+kVHYYwkZbTcsqOsFkkXTvXRC5qZlaRsMw0txWYqlWzNnjMY6C4mGlXmsLSi6cYWzYmttrsxqfYdUro3qFRKP272rRAAv1egIkoJeeqVWMnK8DmDzUTwKN3vzyQJRCjDor2mAtbRW5cxEHH3DwAeFgcT+PuHvYM3t/kQPcRTjH2+FmLvOf2GOHz0nlZ/T77q2f9XtXYMmtn/Gt4RGjSfjEnxpEnuvznnsH1eGcB7yLe3z/8RWbpMl2VD8sFts4Hnr6KvA5mISXwwWv/AnfGd7hMU+wVPGYBpzOL5pywd7HTaal2QoHsNV6ORSLhzhuviZVOz6KayWAJqsyugQIdDhHzihu5XPa6/yWewAAfGlvcckDHhJDsQfDpbYCEpHLbYnt5XhB8BaTS23yvESP3377bfwOfd7M4BQ0YKjixcgq0urxoiWn0bAliEpNsX4a97UYFm44axofYKji0/GMF8PchDR7R9WDDZs+iposvln2+Op0QMwWry+HzSIH4BJsWDzOi4VxBad5gLMFL3Zz8zvSysRkIxxRUwIHeGHwGEe8W3Z4WAaE0JfHgMlzH+aT6YwX/sJ9vmzavWJNwRc3D3g5XNr2DjbgpT9jNAmf+UcYKsgwOI1jC5Ip25YRf7RRgfpNFOLU1D5Wg0seuAZqmA18TgNCcTj6gCIPsDr+GaoIkuImUdHlFYhg5gUaS8T9GKBrhHc3jTGMZJscP0B9jVgHrxJXpnEuK/yU/17hZWXlqbB7o6w8F/FIqXVd9RFhw915bihkmbrg8ARtVrH2cCpWpefnttsCSJcN9YGG6opW6wOTZllNN622TIth4MKFqIQRAGRSGmwCHFoP4+Fxh0y02uFOqmfX1bel+aoBlVGGq6YVsBIb9bpbCeLa/GU78QsGSnhpz/CUmCgMg1MZcSojvnS3uItTk8FPxch3RDhHj/PCvire5pbp6up9ZwJu7IxP7SM8Zby2x03/RhcnR7/g85En/iSZEpfO1kxKtcyAdSXrjV3LszKRj4YDgCUO6Dl6gUCvvYemIUhR+hscaFMxLPVvaW3wC2JLx3FgmLIrK6LzHAdEgR6nbJoj6uiZja/I0VGM4EaTmmuoefLsoHF2QrZih23w2XCCIf58qQYnyzwczZAYJcfBamf5vHQ/DMk+sGp4dZssFVgRpJgtijGYwYsZZ1fjNw2gCoVWfTq1bmD9ttW4T7ev/LzRJQkgF1yyx344tAKAMwXf2d3j1XBqDsPa9xpNwt4wNH1xJ0wm4s2wx3kccI4eIU4fv6XyTSyj/fDxBa+WbhJeDee2qlqKxdtl3x5CzR4UlqhpcwGBssWpDAjJ8qQWLJfbtB/ieLVOQhJsjehCjUi4OLfR0zrHETFbPLoRd8uuTTYAp/K2EnYuYpKmrNahYzcBOJPh7aqd9W7ZsZNisMjaSLxewGgM6rOXPiAIwKF/77MBi/D0PX2GAnRyNfp63UKonzku1prjMphmhZNLQigMGEzCF7sH3Li5fZd7F1gsMjmcpgGlEPZTwOhTK0/ksiK4QlCo6ypls7RJmbPbIHDYwU1wtuDtuMfdbmoTuV5/SxUv/KXZDFvhwOjQxUM/rCxAbqelZSiDSNBfyoAfhRe4S6yC/CYcNlblsRiUKvyRBqG+UhAGZHGzmstpcNm70LJkg4pYDd6EPebEkjAq0aRqyfci93Tj+KcarI3E1spvac+LI1p9eA4uPHkqQ2ZpHm26jy5hh4rjsO2TrNcj4dYtcIah3JfIyK3QQa1Hk/DCccnKC2+l1BFzYkma1+HQgooOFbY8uKV5WrVynJxXAWdPL4YZUfoqOgxVfLYjqCLAYxgRi8FpGZoUTspW7t2Makka/blddwBNe22Re7AWzr7dkOBclmc/4iGNOOUBb+c9TrJIGX2CqYS7ODVEYMiWM8vBYGcDbuwIQwVv0gEPaUIBYe+5tLZ491EpnQC+mQCBtw97WFvw3eMd9iZIE49v2lNgtvjkEpMrTWnwRB3JrBDVmC3S2YFODiYDJolEyg6M3tKVvZTRinI7qDZsvtbYL8FjDh4X6/Foh7ai6xnUk+N+zigra55QubHJ5ZOCQdiDpzjgFAYuPYmO1wfvqOssph+6cOwnMOoCxXMB7P9lWt7ENa8+p0x9J+UtZ8TWWQiFOxvxS+M7fOYeWm3/KGrHc3Z4MxwQuyZ3E4EsBrEYLiMki5yJ1RxgEU1BsK49H6UQsig9LI5XmpfJN8XjJfLDqpnnZ8cTPhnP2LuIWz+3CVWzi96C2hCvfifP2l17F/Br+6+xNwFfhhu8iQfcx6npaDVulwRNdckEgHdGV/VrqZHVqLnspNwWQIzIUPFqOGFvA85CxnwXd3i37HhSTSswxRtGT57iAIOKkx9hUZolh5d7krN1Ay+imo4KJint6MR6Ev+YmG1Do7F9csbexWaBrHDtowtwlFsAP6URD2lsAWswFp4KkrWtl+SIVQ1mySQBh/vAiwMty2mwXSkQAZ85LrVFATR44sXmZ+4Bvzq9xrkMeB1vZIHKYIJbt11c/Ci8wN/6+ns4R4/TPDCvrhJ8K+HWpk7R81sWUaFOwhUjV4VbswabN8sBj2HkZzv4ZqdQKuEhcPasKt4Hz6oOBYRz4e/tXdzhTsAQCiQavf/IZbT6zeTZ6IN5Hyb8yL1oTV6D2ohPtntoYzVQ1Ls6Am4ansnAzgR3IvhHIE+E8JKDTs3E3JOBYbeV9Lqb1pQbZbU5iMtexarf9mjGdiyGmGVtUFEsAwKUE8CY/7HVxfXGGVxiRAvJZL5pvdTnM51nLxqeBqp6le38PEPKa6iiK5aJ4eaV2JoBwicdSmsmW1MQRKJe6+2X7JtcymBSE0jklbPlDHQeW2miVjR9OiVgGgOUKj20bJEF+lUV6CAgggLOVpfZN+JtTnZzGV4DOIWB5Uq6Xp8GASu/c9m1snaXvJYKEzYHk/B6OeJd2G0XO4Wb6KeFM2tVU1DwyCAoLSPAAkO18Wzm7PAQJ161j2gl4uZaC8B38GHtp2jPoR1DNXgdDrhPI85lgEVp8jn3YXpyS1mqDYGlvSQAmMljya6JRhZDQAKSZucCKrlkD8CzMjQIpzQwZwyK7GK3ywLCO+xhqOBd3HGTHtQWJz1htB+pWDzmUYAaDBB4TGMLOH0pNRbbPHB0AXAZPB7d0q7lXdzhHFmRer4MKFGUR0wVOSRGRu7GuHrvUMXDPLIYbLJCU+hdPrcw8pRZDomo4iwcKG9zy0KHDjwBMIAC0oO6D1NTkVaViD8ZP9/4KcGGf7657HGOAz7bPeKL3QOcyXg5XdrDDKywSB2zuPJpMCCqMBcDf0/Y/7ji5gcRy0uH+18zKJ6QJ3aYzDeEOgKFCoqlhqwiWaU7yogDZzznZWAHPmNFOr7Cy82o0My944wsVbatDcXi7bxDypaFB6V5vvesvvtgJhHxpKaK3MpkwIczkT7j0flGoM9NDVp7Ld1Q7571BWzfs9mevDES3CMrNyvnMCeL4g3SYFkB11ScBWFmhOD6e/UT1Eo47BbcTkvjwLRJOTgs9yMrO5CUDH2Fv1k46DgWRw2FACXcCumWlP8jiJ/qmCZRZkJ68E8h3QQ8Png8Sj+KLBNT94cZzhQcx8DNWem5KOKLUU/S1BYI9f0y4Rw8Rp9wHLg0OCeHkCweTxNyNOwWa3n1y+WggO9Nb8WjiS/i710+w4/nG9yFHb56PHBgMgV7R/CUxYo5YzJWeiDcNPOe77tbP2O0CQ9xZG5Mdng375rGX0+0VXBFH5waak+ImoNJDDcOO5wiVxMUiuytg4lV9MUSEviapGrwGPi6jAKS0RKYPhdzdlwKx+rz403GjV8w2IQbCQjAupBMEjwuIoqpsOWvLkfMInGjBmrNhE16lTpJv5kWHIelBfu7ZYfHCweOejfAzgRKWw+pbIH7qbLa+pRZF1ERZipxRCJrVFfukJFgHZJFPjEW/wwGKAyu40lZ7mPq96DIvndhh7fzDkt0raTf84I+2vgmltF06IpBLXMBdsCDwZOaujZjGefvGqchZ8NgqsqgKhsKTKrMXGfuHP/sJnMNdrqyTcU0/TUvqxxFnqmzoA6Vkg/FYai5NZpj4bowy+YD1RKs7O/6XDaIM+Bny2w2F67nx6wB56du50N/7/o2VbMwRbkp4q0DODAbv5O8l+zjYpjBqX2dWIxIA3VCpiTHbatkOrKSNwXDAJRSkKxBdnYlwQLNmVVHgQUyw+hbQJKSYtVzyoSaWNfqjEmUIQjerXwMLY1laaQDXAJNUvdfFofFuzap50otM27XTO7Hd2GHVA0Obs8Irczndi8IsUX0xErhiTtmi++bT/GVOzapmrsw4X7hfowGpTOtHCA1P0vFIIobqaoj8LVfvxftO926uTlslsrK1qc0Ys5r70mvgyL21LkU4Mkwq8KC9EE0w3W0Zh+lrm6nWuqGE4BEMZsqBbDqwW2ENQtnl0viyTgk1jFUdQmlLgDr/Dk7zioSlWbSlpIRPUMJNFkWUFV4aaWiOv539YRKZvuMaFCUUm/fmxpsZgJyB56p0ltM1Yj+XG4W1KOQ1wGwHbbNCMkyZeH/ae9aWm3LrvI35mOttfd53EdV5VJ5QGz4A4RAGnZsSbSTXnqSiF0bgg2jCIKKpCWkJRTYSEB8QATTECUIaSqaINiIoIJiyrpl3bp1z2vv9Zpz2BhjzDXXuY8qSB0VsgZczrnr7L3X2mvNOceYY3zj++4we1Yb/zim0cysCxxYWGobnxB4SaFZFHSYG1wr+d/FzU7hs0BOvkQg4nAYLqmz8YBLJNh6vc/kWKJFlwvc8AICZ92FCedtj30ckXaqVJj8CgPfz2HRWTdgg07+wxB1UkixOEapAwy6JV+lvaS9XS8Kz+86gAX6bF2X9d+1mRO6e1nJEpjdRp7Vu5+6J8ccDcs5c2s3S/7xPsE1STuzIX0xsxNwi9Wh9PP6wWMIDchnhCbJDnLyC7dc7XczIfUBOWS0rRClPtxd4azpV1/DOsutX+P9/gTHKeLpxQmmoQVVux/jXivOJwOkdD9+jGAHPLvfAk1GezbgZDfAZIszEy6OQkVzc9mBBw8aHNxAGAjoHSQK3ifhvWsSYjsXddKbQ4t/619HjAn/tb+3kGZCUnqmjxO9BDOPn50hZ8K/9I8E3GLPxwv7uPMCBfeaoln1mGnNKGfCOMRSh1h6yGRuPWovcRoG/ET7Hhwy/vn4Sbw3nuGdozQlWtBmaWTrU5FWgkU5tI3zKpU4VU7noDsjG0q9OmVzflN2mLyHd7HIcNeiarWjkv8TpuxxGCOGKWAYIvKoc+h2U3LgEgTZemHZiekYgcEj9AQ3Sj2XZiwN0IHAUUFaJkli2YCKtd3YpN8/ivrpPox4c38p472PYA1MRVJA1gwDEj1sDvhk+wydm/AwXCOxwwf7PTo/4226tzhz3LXxj/fO5kVm2P05C3T1dhOVIJkUzau/G1FeDkBqPVIk5QmTRbgWAbttNS0KoPlnzwDSqv4y5QVddLuQFzRadm6JuD7M6hTYR6q52Clf9to6JXf7PbeP1S+rHaC9Xx2C6eu4mIRQVF+f4cC5SgnaIqnOpzSA2ueYY1P+trIzma8A/QAAEDBJREFUA2SSu2Wh3IUJD5RxOVBa5evL/5ngaIfrtsUUGrDQfxVnuUot6ncj5ZVjB9AkUWxOSkei8GsjvZxnDx49aBRH4yYqYJPMWJRISaDas/IjpeTAk/y8UCSjOYgpeaTkxHFYPVLZf3lwoMmVe8kxi//OjOQJzE5rXK7QsbC9X3dYxj5UP3LrVREmgAEeS8+S7EDWTZreyZ02N2DnIKKyo1u0owgJWDkgYIG9L7RGSx8bdCEmElXL+r2lqZMX5VOjizG1VVhNsR6+mlbL6iCN8iXlhQSWsgSdNU8fsQRNyBJAEUvjcr3Dt1jQKJ/6KRR5hs4LUCaEjJy5MCekLOnDKXnkKE2qvmIr8KSwfifvt29z57xod2xE9BkA3wTwCHIX32LmrxPRQwB/CuCzAP4dwJeY+QOS/oevA/h5SBbyK8z8ff2sLwP4Tf3o32Xmb7zq3B8KEBA0mANRwFlDpW/iXjhiyh7vDucYcihFOdcIauUwNwg+Cb/SGJGSQ38aMTggtYTjGw1yCwyvJYlyrc9GZygnwjh6eO9Ayl8WXC6FPQCFVn0mtyCPVLujC9JQeK854o3uegWb/GC/x6g9NpY6I2Jcjy2GIUJ28A6gF6S+6sFWOzPS72A6MjohmJz8Xr+/7JCWqL7Al9nJOW1nYdHdTGsmab0m9gw0DATG7mTEvh3LJU2zL/DQEXFZADQiJG0CdV4ogUJUGem9phkmjzzIjhQzgbE0xZ03RzxsbkQOXDuuJ17AIIkdTsKAm7nFG7trvHt2hpuxwbPLvchFJEmR2DVkTaXkiZA6DxCDT5M6UAUn6O7RO0b0E0aXMTQRnIFMDrlhcJcRTidhoVaZBVtQ5WfGPAfw0SNxwM3TVu5jyIBnuFbOh0Z486KfcNoJemq8J42yo0LkLVVEBMQ4r0trGmCZOZcR43pe7Roh19yHsaAor9IOnrJE2I3Q2zQV/NjR0udj3G6mqVMLuF0cu+I4mVH6olxV17y360ufVNC0liH3xDGjEJje1nCxHY6l9gqFnwVTNn51rIVuhg/CRm7p75RVumImuNHBDwQ3YH0er+lhmz8zyRxR5CpIgUWgcoXP0gkuHPB0N5Znd7obMCeH49AgJcLl9Q5gwkWzw+N4hnu7HtfnDXZ+wv14hEfGO/05rrXNYukRumvhNNx1n80M4FeZ+ftEdAbge0T0HQBfAfA3zPw1IvoqgK8C+DUAPwfgJ/Xf5wH8AYDPq3P6LQCf06v+HhF9m5k/eNmJPxIajXnpd4iUsXcjHoQbTOxxOa8RQM5PhbXWOr5TJkzkgTYhMzBFwnxKyE0Gneq2X2dqHoU9mjUaBDI4yjUspIVLL8+ywwEcLYtd9Klwp92PRyUPlYFyHnpM7EvHc2ERZqcMAk6FLm/vQKp0F/D8oKBKzE3TYcy8TilQ9dMcyS05AnLr3ZSlnyTioxLVsWewI3EcIaONCzMwAEx+gY5PQ1BE13Kd4k9N82ZZMEuKgxqMiUTCO7mFqIAYrUs48z1OfY/7XmQnRl6aIBMcoptxzx+ldyEMeH/Yi4598hhHD84OPkhOPQWpGXEkyfQR4NsEp2mp+k4bewSCOCv2DKYMeII/mfHg3k0h8WQIVD5lVxjCAYC0RhAOcj9zK7vszATaz2W8Gc9ZDbu9HDqF/qNwZbmyC1rqmrmkbeTqQ6jkGXSMGm9ZXZxOcAJG8EKXUn/vGmllrAeGoLNakYM6IpWRyJmQdcfrvRCHkssFImwQ6pvUFAYDSyUmYEX/UmcwFkdzK+iq084a1ISYEOMsNTgSEtgEKvRNlACaAZc0BrNsdp3tYIASwKDSK13IboEyz7IW84+aWWlCwlk3YHJOhRi9pPtmQp5FmI8BPGlOVaZb9Iyup7bcj6UxFXdvd8ggwMzvAHhHf78ioh8A+BSALwL4GX3ZNwB8F+Jsvgjgmyy0J39LRPeJ6E197XeY+SkAqMP6AoA/ftm5X80goAO00SJtnb/1YGTwqiPZ8PRj9hhTkIYxpVxnJlkYCEAmuJ7gBg++0clkE1LzvWnHSDuH3GRMnpF9xqjXY0iTzk2FLuTEi57JzdSAq87vMQccU8RAoci5HnMjjlDhmKJlLqgf7zNmlxcnYA/JSQrwhemxaldDIZeIFxBizVI418lnzrF+P0Ecqo0zYz4udDcKHUZhowaMwNR3sigb8sccsvUnFTqgal4yk6S1QEiTKzQ3zjHSrGwMgwcG3WXspB503g04b3s4paiX+/xiOKgdF8cujBPOZXgmtK2mbSzFZGkiB1CblvvKhCYk7NsRjQYQRrjKANpuwmRFaABdJ3T+NXzankXXTPCOMbUT+p2oMM5DWLF7kzJazLPDdb+G0xtQ5aqXHbBX1nHTiXHEOEwRLlMhAnXKOFALkZmE9mkzqKDajENuMLFHn6Okc8BoacYn4hU+Ea8KC4Fcy3oxuk4drlKHm7nFk/FE0lwKM89lvFDxASmLuJiR1mZ2GL3MWUOm1UAAh7VctjxbTUfxC1Zfq6kAMI2mJs7YtyPOmwEncSi13Sl5DJ6F6FUDMLKH6SDeLgN+kB0MQVKsOUFWL6fH6xRxNmdPOPQew15E44JPeONMdouXu7YANiy1djl0OPoorNpgXIxdUSM12YjTuARzd2EMSOr7f8GI6LMAfgrA3wF4pI4IAB5D0myAOKL/rN72Qz32suMvtVc6G9tuN35BBJk5ynCgEm0ZWmXMXmVrVRQL8pBswWMSUIAfCG4G/ABYyF3GLQHTBEyQYuPUyKQZtQM7+oSokadpYERKGHLEE3eC5FxZHObsihqjKTzOSmJohIJBKTd6a2C7LWAGyCB/WSFGEWDkF/p+7+3NhkBCgSCb7LU5BUNcWREYkFy2NDHm8loi1mKwFHyHIcCkll1FLCkL2gL9LEiaCpxgbM/IkPqNZwGMEWPug/TwzA40EnKXEXYTmnbC/e6I89gjqu7IxB4HhQDbImk7SIvWZx0TgoxiAKnUCI5jxDS5yiEzQlORgOo4PFPp53tNj2OKeO94isyEXTsWYTZb0FvjEEvrXcEuzjht1to7Rv1ydRTtkpxMr95h6F1hv/ZKJ5OzQ99HpGOA34luSvS5fG5mqQXYOZ0TcS4DthgNi6OMfZhUtVPu5YBQiuevx2uc+h5nrseZP6KhhEjzCiHmIBxn76dTPJ1P8cSLSJzIGatAYRUwrTMVJFkHt6TNrJWhBgDYz5Ie1B2NjcfnEJwEmSdVsOQ8F0fzWneDh80BzyYh+ByTx1XMpVesnmLFpxJAI6TOw7Kjp0zC4uwY7BdHQ5ZyZoAHD/aSrhv20urw6dNnaN2MD7odDnODi6ETdgFAZbdDAQMcp1AYDZowYx8nvNbd3G3dRorcP8onvE5E/1D9/y1mfuv2i4joFMC3APwKM19SBbVjZqY7wHi/0tnY4mU6IkJHo4VUbeKyvgNLnQSSRrAxeyH2U1hmykJyya3k32cGKBHm3a2TWvTVMlgbPAlLnrtepDMTbtSRAKI4aFGZ8FUpFLsw22rOG9KoaPQ1mR2OKcqWWWWSbWfDtrvgpZB9u7BtTqhmTLZdoRVF7Xdjsa4b1CzSnarna+/3t3LEwSd43cvnuBBl1pY1/zBlEapLs0M6+hUqrjA5y5YKIEaeNX8xOtDgJLWhtOwhCivBaRxwvzniRKnty73PAZfzHjN7XM/NCiprPGf1TqtXqW+Tm/ZhKchbU+04iJDd1aFDPwV0ccZFOwhV0dBoqkgCkaaZEd3C1WbpHSFuzUiEkgq7DSBhJkyTF1aEZPkbHYcKUABQFm+eXUn1OrfQ2gAVP5dKJjhazjekAMqM5JySZmqTtM6pOXtczm3ZER5SgyFE9BzR0YQzv8hd13aVdjhkaayU4HBGCBlpVs0ohtTmaBmnMm5t97+GQNfO5fa4sudnIIRld6qOoM4GQFPJWRQ8Bx8K63rrZCwNKeBplwQ04KW3KxwB3zNSR5hOy4eJI0ky7zJYRW2XoLD05miLhUHtc+9wc9Vhnj0u953o1ZDUliet21pvkPGqmc0abBh6zWTJ/x/bE2b+3KteQKLf/i0Af8TMf66H3yWiN5n5HU2T/bcefxvAZ6q3f1qPvY0l7WbHv/uq877a2egi+KA9FFVA28ofUgtPGQ/izeo9hyCd0k/Hk9KpP83SaxCbGSEmzK1HOlmXHJ+jgLA10ctuQMgG7bqUpZml16Fme56stoSKdTp7lXx1ZaCbIqA1ql1PuwIQSIMviptUy2RY70l9rQwY3QE5SdUEn7GLU4meGSiTuB7Uko6S12QmeBXy8rpgMtNzhVijkhl8KJN9qiJp6LkmJvRjFGXEwcNdBriZkFoGggjcUZfEjzpJ9bHWy8Kll0Kt+p68I+y7Afd3PT7VPcODeMDejWjdVIKOQz7HDw/3cTV1eHx5hnEMZZcQmxn7bqn8puxwOLTgpCJ3PqOJM+7tFij1mDyejgFpcuivOwyTw1WT8f5OST9nV1JfIMCdM/bNhDYIP5gVuq1oniv4PoCyqzWS2KkP4GOonulSH0t6zE0C0uCoDYatiNFFt9DUW8+XicnZs0tAaQwMXuoWkkJb5LuPHPHu4RxDCrieWnRhwlkYhOIlDHg9XK8WukFlr+1fn6NQ0PgJO5UFT0lg1zGmonpaP4dMXOZM3XBqZt/J/ma7IjH5bvNsaDSn0GSrW6ozTw7DFOEImHeysJ/FHidBFDGfne5w41qkJsAfCe2zjP3jCYdHEdOpBmr6te120UyqfAvkKi1NvARIZM9xdkhji+NJxOPdGR50R7zW3WCnLAmtcjoac4PRFPVBmsCF8iYCCHiG29Hxx293mUZTdNkfAvgBM/9+9advA/gygK/pz7+ojv8yEf0JBCBwoQ7prwH8HhE90Nf9LIBff9W5PxL02VJltWUQpIfQ6gTa3U1J9dPXr18icC1O36pb1Js21kHyoqjdJjVgMEy3Wozt+Ku/zzolaN8ns+XuX/D+qt6xOlZ+X6crbJLagiMaJ0tUWYAOeF7JtOzc9HMdMeplwt7jCEgfNi6r9IL9XFPx2DVXx22hJa6FEm9dc4ZHRoYr2caZJaiQFM6SxkmeniuWS8RLJbdfL9Y1D165t6muVxFWhKe8BCv1PSXicv9eNSZyCRiq71+nUdmaC6WQXYHunrO6kF7XM2SxfvHrV7UQHYdztUNPkPRWkkat8toEQmJX/tVW77ZW9/0FxtW8qSHWt//+SmPCc+0hOmesBcK+v4fQ99fPvIBvAIVAM160gdBHuhrLq69mtTer33AFQFC+NQtAasCRORobP/L3DEdrR/xha8vHYncrMfDTAH4BwD8R0T/qsd+AOJk/I6JfAvAfAL6kf/tLCOz5XyHQ518EAGZ+SkS/A+Dv9XW/bWCBlxk9p62y2WabbbbZ/4kR0V8BeP1H+IgnzPyFj+t6Pk7bnM1mm2222WZ3bhuF6WabbbbZZndum7PZbLPNNtvszm1zNpttttlmm925bc5ms80222yzO7fN2Wy22WabbXbntjmbzTbbbLPN7tw2Z7PZZpttttmd2/8ANslexAb5/LgAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d3Uthe1_Yzcf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "outputId": "3f345864-f03b-4939-c2da-946d0142fb50"
      },
      "source": [
        "\n",
        "plt.figure(figsize=(8, 6))\n",
        "plt.imshow(ground_truth, cmap='viridis')\n",
        "plt.axis('off')\n",
        "plt.colorbar(ticks= range(0,16))\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rpbxFqxuVKWr"
      },
      "source": [
        "### Extracting Band Information:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9_cgAsYPoC6K"
      },
      "source": [
        "from tqdm import tqdm\n",
        "import pandas as pd\n",
        "def extract_pixels(dataset, ground_truth):\n",
        "    df = pd.DataFrame()\n",
        "    for i in tqdm(range(dataset.shape[2])):\n",
        "        df = pd.concat([df, pd.DataFrame(dataset[:, :, i].ravel())], axis=1)\n",
        "    df = pd.concat([df, pd.DataFrame(ground_truth.ravel())], axis=1)\n",
        "    df.columns = [f'band-{i}' for i in range(1, 1+dataset.shape[2])]+['class']\n",
        "    return df"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "90Rz23snoJqq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 278
        },
        "outputId": "4caee13a-7201-4ecf-f241-d9278e7b200d"
      },
      "source": [
        "df = extract_pixels(dataset, ground_truth)\n",
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 200/200 [00:00<00:00, 404.19it/s]\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>band-1</th>\n",
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              "      <th>band-171</th>\n",
              "      <th>band-172</th>\n",
              "      <th>band-173</th>\n",
              "      <th>band-174</th>\n",
              "      <th>band-175</th>\n",
              "      <th>band-176</th>\n",
              "      <th>band-177</th>\n",
              "      <th>band-178</th>\n",
              "      <th>band-179</th>\n",
              "      <th>band-180</th>\n",
              "      <th>band-181</th>\n",
              "      <th>band-182</th>\n",
              "      <th>band-183</th>\n",
              "      <th>band-184</th>\n",
              "      <th>band-185</th>\n",
              "      <th>band-186</th>\n",
              "      <th>band-187</th>\n",
              "      <th>band-188</th>\n",
              "      <th>band-189</th>\n",
              "      <th>band-190</th>\n",
              "      <th>band-191</th>\n",
              "      <th>band-192</th>\n",
              "      <th>band-193</th>\n",
              "      <th>band-194</th>\n",
              "      <th>band-195</th>\n",
              "      <th>band-196</th>\n",
              "      <th>band-197</th>\n",
              "      <th>band-198</th>\n",
              "      <th>band-199</th>\n",
              "      <th>band-200</th>\n",
              "      <th>class</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3172</td>\n",
              "      <td>4142</td>\n",
              "      <td>4506</td>\n",
              "      <td>4279</td>\n",
              "      <td>4782</td>\n",
              "      <td>5048</td>\n",
              "      <td>5213</td>\n",
              "      <td>5106</td>\n",
              "      <td>5053</td>\n",
              "      <td>4750</td>\n",
              "      <td>4816</td>\n",
              "      <td>4769</td>\n",
              "      <td>4610</td>\n",
              "      <td>4805</td>\n",
              "      <td>4828</td>\n",
              "      <td>4861</td>\n",
              "      <td>4767</td>\n",
              "      <td>4624</td>\n",
              "      <td>4549</td>\n",
              "      <td>4463</td>\n",
              "      <td>4462</td>\n",
              "      <td>4446</td>\n",
              "      <td>4445</td>\n",
              "      <td>4336</td>\n",
              "      <td>4381</td>\n",
              "      <td>4319</td>\n",
              "      <td>4207</td>\n",
              "      <td>4305</td>\n",
              "      <td>4311</td>\n",
              "      <td>3991</td>\n",
              "      <td>4168</td>\n",
              "      <td>3942</td>\n",
              "      <td>4061</td>\n",
              "      <td>4362</td>\n",
              "      <td>4318</td>\n",
              "      <td>4252</td>\n",
              "      <td>4869</td>\n",
              "      <td>5284</td>\n",
              "      <td>5055</td>\n",
              "      <td>3591</td>\n",
              "      <td>...</td>\n",
              "      <td>1396</td>\n",
              "      <td>1381</td>\n",
              "      <td>1396</td>\n",
              "      <td>1381</td>\n",
              "      <td>1353</td>\n",
              "      <td>1346</td>\n",
              "      <td>1341</td>\n",
              "      <td>1332</td>\n",
              "      <td>1324</td>\n",
              "      <td>1310</td>\n",
              "      <td>1318</td>\n",
              "      <td>1330</td>\n",
              "      <td>1310</td>\n",
              "      <td>1292</td>\n",
              "      <td>1280</td>\n",
              "      <td>1275</td>\n",
              "      <td>1266</td>\n",
              "      <td>1264</td>\n",
              "      <td>1233</td>\n",
              "      <td>1241</td>\n",
              "      <td>1232</td>\n",
              "      <td>1215</td>\n",
              "      <td>1215</td>\n",
              "      <td>1187</td>\n",
              "      <td>1168</td>\n",
              "      <td>1171</td>\n",
              "      <td>1150</td>\n",
              "      <td>1134</td>\n",
              "      <td>1123</td>\n",
              "      <td>1135</td>\n",
              "      <td>1094</td>\n",
              "      <td>1090</td>\n",
              "      <td>1112</td>\n",
              "      <td>1090</td>\n",
              "      <td>1062</td>\n",
              "      <td>1069</td>\n",
              "      <td>1057</td>\n",
              "      <td>1020</td>\n",
              "      <td>1020</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2580</td>\n",
              "      <td>4266</td>\n",
              "      <td>4502</td>\n",
              "      <td>4426</td>\n",
              "      <td>4853</td>\n",
              "      <td>5249</td>\n",
              "      <td>5352</td>\n",
              "      <td>5353</td>\n",
              "      <td>5347</td>\n",
              "      <td>5065</td>\n",
              "      <td>5141</td>\n",
              "      <td>5100</td>\n",
              "      <td>4994</td>\n",
              "      <td>5172</td>\n",
              "      <td>5290</td>\n",
              "      <td>5289</td>\n",
              "      <td>5217</td>\n",
              "      <td>5053</td>\n",
              "      <td>5033</td>\n",
              "      <td>4939</td>\n",
              "      <td>4931</td>\n",
              "      <td>4941</td>\n",
              "      <td>4902</td>\n",
              "      <td>4824</td>\n",
              "      <td>4859</td>\n",
              "      <td>4805</td>\n",
              "      <td>4698</td>\n",
              "      <td>4794</td>\n",
              "      <td>4806</td>\n",
              "      <td>4452</td>\n",
              "      <td>4628</td>\n",
              "      <td>4433</td>\n",
              "      <td>4643</td>\n",
              "      <td>4967</td>\n",
              "      <td>4853</td>\n",
              "      <td>4760</td>\n",
              "      <td>5449</td>\n",
              "      <td>5768</td>\n",
              "      <td>5684</td>\n",
              "      <td>3987</td>\n",
              "      <td>...</td>\n",
              "      <td>1421</td>\n",
              "      <td>1415</td>\n",
              "      <td>1428</td>\n",
              "      <td>1415</td>\n",
              "      <td>1379</td>\n",
              "      <td>1370</td>\n",
              "      <td>1360</td>\n",
              "      <td>1353</td>\n",
              "      <td>1352</td>\n",
              "      <td>1336</td>\n",
              "      <td>1346</td>\n",
              "      <td>1351</td>\n",
              "      <td>1330</td>\n",
              "      <td>1315</td>\n",
              "      <td>1305</td>\n",
              "      <td>1292</td>\n",
              "      <td>1282</td>\n",
              "      <td>1286</td>\n",
              "      <td>1259</td>\n",
              "      <td>1259</td>\n",
              "      <td>1250</td>\n",
              "      <td>1229</td>\n",
              "      <td>1232</td>\n",
              "      <td>1195</td>\n",
              "      <td>1177</td>\n",
              "      <td>1184</td>\n",
              "      <td>1153</td>\n",
              "      <td>1137</td>\n",
              "      <td>1138</td>\n",
              "      <td>1137</td>\n",
              "      <td>1108</td>\n",
              "      <td>1104</td>\n",
              "      <td>1117</td>\n",
              "      <td>1091</td>\n",
              "      <td>1079</td>\n",
              "      <td>1085</td>\n",
              "      <td>1064</td>\n",
              "      <td>1029</td>\n",
              "      <td>1020</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3687</td>\n",
              "      <td>4266</td>\n",
              "      <td>4421</td>\n",
              "      <td>4498</td>\n",
              "      <td>5019</td>\n",
              "      <td>5293</td>\n",
              "      <td>5438</td>\n",
              "      <td>5427</td>\n",
              "      <td>5383</td>\n",
              "      <td>5132</td>\n",
              "      <td>5227</td>\n",
              "      <td>5172</td>\n",
              "      <td>5097</td>\n",
              "      <td>5313</td>\n",
              "      <td>5411</td>\n",
              "      <td>5412</td>\n",
              "      <td>5341</td>\n",
              "      <td>5191</td>\n",
              "      <td>5140</td>\n",
              "      <td>5069</td>\n",
              "      <td>5110</td>\n",
              "      <td>5119</td>\n",
              "      <td>5046</td>\n",
              "      <td>4981</td>\n",
              "      <td>5023</td>\n",
              "      <td>4987</td>\n",
              "      <td>4862</td>\n",
              "      <td>4965</td>\n",
              "      <td>4992</td>\n",
              "      <td>4595</td>\n",
              "      <td>4756</td>\n",
              "      <td>4529</td>\n",
              "      <td>4801</td>\n",
              "      <td>5077</td>\n",
              "      <td>4983</td>\n",
              "      <td>4868</td>\n",
              "      <td>5515</td>\n",
              "      <td>5972</td>\n",
              "      <td>5913</td>\n",
              "      <td>4027</td>\n",
              "      <td>...</td>\n",
              "      <td>1446</td>\n",
              "      <td>1440</td>\n",
              "      <td>1443</td>\n",
              "      <td>1425</td>\n",
              "      <td>1390</td>\n",
              "      <td>1379</td>\n",
              "      <td>1376</td>\n",
              "      <td>1363</td>\n",
              "      <td>1355</td>\n",
              "      <td>1347</td>\n",
              "      <td>1361</td>\n",
              "      <td>1356</td>\n",
              "      <td>1341</td>\n",
              "      <td>1330</td>\n",
              "      <td>1321</td>\n",
              "      <td>1304</td>\n",
              "      <td>1290</td>\n",
              "      <td>1289</td>\n",
              "      <td>1263</td>\n",
              "      <td>1269</td>\n",
              "      <td>1261</td>\n",
              "      <td>1245</td>\n",
              "      <td>1241</td>\n",
              "      <td>1214</td>\n",
              "      <td>1185</td>\n",
              "      <td>1188</td>\n",
              "      <td>1156</td>\n",
              "      <td>1147</td>\n",
              "      <td>1149</td>\n",
              "      <td>1144</td>\n",
              "      <td>1111</td>\n",
              "      <td>1114</td>\n",
              "      <td>1114</td>\n",
              "      <td>1100</td>\n",
              "      <td>1065</td>\n",
              "      <td>1092</td>\n",
              "      <td>1061</td>\n",
              "      <td>1030</td>\n",
              "      <td>1016</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2749</td>\n",
              "      <td>4258</td>\n",
              "      <td>4603</td>\n",
              "      <td>4493</td>\n",
              "      <td>4958</td>\n",
              "      <td>5234</td>\n",
              "      <td>5417</td>\n",
              "      <td>5355</td>\n",
              "      <td>5349</td>\n",
              "      <td>5096</td>\n",
              "      <td>5147</td>\n",
              "      <td>5078</td>\n",
              "      <td>5040</td>\n",
              "      <td>5237</td>\n",
              "      <td>5321</td>\n",
              "      <td>5344</td>\n",
              "      <td>5255</td>\n",
              "      <td>5121</td>\n",
              "      <td>5035</td>\n",
              "      <td>4956</td>\n",
              "      <td>4994</td>\n",
              "      <td>4980</td>\n",
              "      <td>4905</td>\n",
              "      <td>4857</td>\n",
              "      <td>4900</td>\n",
              "      <td>4831</td>\n",
              "      <td>4720</td>\n",
              "      <td>4848</td>\n",
              "      <td>4847</td>\n",
              "      <td>4484</td>\n",
              "      <td>4613</td>\n",
              "      <td>4402</td>\n",
              "      <td>4674</td>\n",
              "      <td>4966</td>\n",
              "      <td>4848</td>\n",
              "      <td>4776</td>\n",
              "      <td>5473</td>\n",
              "      <td>5894</td>\n",
              "      <td>5789</td>\n",
              "      <td>4086</td>\n",
              "      <td>...</td>\n",
              "      <td>1432</td>\n",
              "      <td>1427</td>\n",
              "      <td>1426</td>\n",
              "      <td>1416</td>\n",
              "      <td>1386</td>\n",
              "      <td>1374</td>\n",
              "      <td>1375</td>\n",
              "      <td>1359</td>\n",
              "      <td>1343</td>\n",
              "      <td>1343</td>\n",
              "      <td>1354</td>\n",
              "      <td>1351</td>\n",
              "      <td>1333</td>\n",
              "      <td>1329</td>\n",
              "      <td>1313</td>\n",
              "      <td>1296</td>\n",
              "      <td>1280</td>\n",
              "      <td>1281</td>\n",
              "      <td>1251</td>\n",
              "      <td>1255</td>\n",
              "      <td>1253</td>\n",
              "      <td>1238</td>\n",
              "      <td>1223</td>\n",
              "      <td>1207</td>\n",
              "      <td>1188</td>\n",
              "      <td>1188</td>\n",
              "      <td>1154</td>\n",
              "      <td>1143</td>\n",
              "      <td>1144</td>\n",
              "      <td>1146</td>\n",
              "      <td>1122</td>\n",
              "      <td>1108</td>\n",
              "      <td>1109</td>\n",
              "      <td>1109</td>\n",
              "      <td>1071</td>\n",
              "      <td>1088</td>\n",
              "      <td>1060</td>\n",
              "      <td>1030</td>\n",
              "      <td>1006</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2746</td>\n",
              "      <td>4018</td>\n",
              "      <td>4675</td>\n",
              "      <td>4417</td>\n",
              "      <td>4886</td>\n",
              "      <td>5117</td>\n",
              "      <td>5215</td>\n",
              "      <td>5096</td>\n",
              "      <td>5098</td>\n",
              "      <td>4834</td>\n",
              "      <td>4853</td>\n",
              "      <td>4857</td>\n",
              "      <td>4734</td>\n",
              "      <td>4879</td>\n",
              "      <td>4976</td>\n",
              "      <td>4958</td>\n",
              "      <td>4885</td>\n",
              "      <td>4754</td>\n",
              "      <td>4647</td>\n",
              "      <td>4532</td>\n",
              "      <td>4586</td>\n",
              "      <td>4591</td>\n",
              "      <td>4492</td>\n",
              "      <td>4453</td>\n",
              "      <td>4497</td>\n",
              "      <td>4398</td>\n",
              "      <td>4297</td>\n",
              "      <td>4408</td>\n",
              "      <td>4401</td>\n",
              "      <td>4102</td>\n",
              "      <td>4227</td>\n",
              "      <td>4075</td>\n",
              "      <td>4264</td>\n",
              "      <td>4529</td>\n",
              "      <td>4490</td>\n",
              "      <td>4438</td>\n",
              "      <td>5001</td>\n",
              "      <td>5378</td>\n",
              "      <td>5321</td>\n",
              "      <td>3779</td>\n",
              "      <td>...</td>\n",
              "      <td>1401</td>\n",
              "      <td>1397</td>\n",
              "      <td>1395</td>\n",
              "      <td>1390</td>\n",
              "      <td>1368</td>\n",
              "      <td>1349</td>\n",
              "      <td>1354</td>\n",
              "      <td>1340</td>\n",
              "      <td>1330</td>\n",
              "      <td>1324</td>\n",
              "      <td>1336</td>\n",
              "      <td>1332</td>\n",
              "      <td>1320</td>\n",
              "      <td>1307</td>\n",
              "      <td>1287</td>\n",
              "      <td>1283</td>\n",
              "      <td>1267</td>\n",
              "      <td>1265</td>\n",
              "      <td>1239</td>\n",
              "      <td>1240</td>\n",
              "      <td>1239</td>\n",
              "      <td>1229</td>\n",
              "      <td>1212</td>\n",
              "      <td>1202</td>\n",
              "      <td>1178</td>\n",
              "      <td>1178</td>\n",
              "      <td>1143</td>\n",
              "      <td>1135</td>\n",
              "      <td>1138</td>\n",
              "      <td>1135</td>\n",
              "      <td>1110</td>\n",
              "      <td>1107</td>\n",
              "      <td>1112</td>\n",
              "      <td>1094</td>\n",
              "      <td>1072</td>\n",
              "      <td>1087</td>\n",
              "      <td>1052</td>\n",
              "      <td>1034</td>\n",
              "      <td>1019</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 201 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "   band-1  band-2  band-3  band-4  ...  band-198  band-199  band-200  class\n",
              "0    3172    4142    4506    4279  ...      1057      1020      1020      3\n",
              "1    2580    4266    4502    4426  ...      1064      1029      1020      3\n",
              "2    3687    4266    4421    4498  ...      1061      1030      1016      3\n",
              "3    2749    4258    4603    4493  ...      1060      1030      1006      3\n",
              "4    2746    4018    4675    4417  ...      1052      1034      1019      3\n",
              "\n",
              "[5 rows x 201 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dn49jpfmr5LL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 438
        },
        "outputId": "2f828a76-8c44-49c9-86b0-25896ae7bdec"
      },
      "source": [
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>band-1</th>\n",
              "      <th>band-2</th>\n",
              "      <th>band-3</th>\n",
              "      <th>band-4</th>\n",
              "      <th>band-5</th>\n",
              "      <th>band-6</th>\n",
              "      <th>band-7</th>\n",
              "      <th>band-8</th>\n",
              "      <th>band-9</th>\n",
              "      <th>band-10</th>\n",
              "      <th>band-11</th>\n",
              "      <th>band-12</th>\n",
              "      <th>band-13</th>\n",
              "      <th>band-14</th>\n",
              "      <th>band-15</th>\n",
              "      <th>band-16</th>\n",
              "      <th>band-17</th>\n",
              "      <th>band-18</th>\n",
              "      <th>band-19</th>\n",
              "      <th>band-20</th>\n",
              "      <th>band-21</th>\n",
              "      <th>band-22</th>\n",
              "      <th>band-23</th>\n",
              "      <th>band-24</th>\n",
              "      <th>band-25</th>\n",
              "      <th>band-26</th>\n",
              "      <th>band-27</th>\n",
              "      <th>band-28</th>\n",
              "      <th>band-29</th>\n",
              "      <th>band-30</th>\n",
              "      <th>band-31</th>\n",
              "      <th>band-32</th>\n",
              "      <th>band-33</th>\n",
              "      <th>band-34</th>\n",
              "      <th>band-35</th>\n",
              "      <th>band-36</th>\n",
              "      <th>band-37</th>\n",
              "      <th>band-38</th>\n",
              "      <th>band-39</th>\n",
              "      <th>band-40</th>\n",
              "      <th>...</th>\n",
              "      <th>band-162</th>\n",
              "      <th>band-163</th>\n",
              "      <th>band-164</th>\n",
              "      <th>band-165</th>\n",
              "      <th>band-166</th>\n",
              "      <th>band-167</th>\n",
              "      <th>band-168</th>\n",
              "      <th>band-169</th>\n",
              "      <th>band-170</th>\n",
              "      <th>band-171</th>\n",
              "      <th>band-172</th>\n",
              "      <th>band-173</th>\n",
              "      <th>band-174</th>\n",
              "      <th>band-175</th>\n",
              "      <th>band-176</th>\n",
              "      <th>band-177</th>\n",
              "      <th>band-178</th>\n",
              "      <th>band-179</th>\n",
              "      <th>band-180</th>\n",
              "      <th>band-181</th>\n",
              "      <th>band-182</th>\n",
              "      <th>band-183</th>\n",
              "      <th>band-184</th>\n",
              "      <th>band-185</th>\n",
              "      <th>band-186</th>\n",
              "      <th>band-187</th>\n",
              "      <th>band-188</th>\n",
              "      <th>band-189</th>\n",
              "      <th>band-190</th>\n",
              "      <th>band-191</th>\n",
              "      <th>band-192</th>\n",
              "      <th>band-193</th>\n",
              "      <th>band-194</th>\n",
              "      <th>band-195</th>\n",
              "      <th>band-196</th>\n",
              "      <th>band-197</th>\n",
              "      <th>band-198</th>\n",
              "      <th>band-199</th>\n",
              "      <th>band-200</th>\n",
              "      <th>class</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3172</td>\n",
              "      <td>4142</td>\n",
              "      <td>4506</td>\n",
              "      <td>4279</td>\n",
              "      <td>4782</td>\n",
              "      <td>5048</td>\n",
              "      <td>5213</td>\n",
              "      <td>5106</td>\n",
              "      <td>5053</td>\n",
              "      <td>4750</td>\n",
              "      <td>4816</td>\n",
              "      <td>4769</td>\n",
              "      <td>4610</td>\n",
              "      <td>4805</td>\n",
              "      <td>4828</td>\n",
              "      <td>4861</td>\n",
              "      <td>4767</td>\n",
              "      <td>4624</td>\n",
              "      <td>4549</td>\n",
              "      <td>4463</td>\n",
              "      <td>4462</td>\n",
              "      <td>4446</td>\n",
              "      <td>4445</td>\n",
              "      <td>4336</td>\n",
              "      <td>4381</td>\n",
              "      <td>4319</td>\n",
              "      <td>4207</td>\n",
              "      <td>4305</td>\n",
              "      <td>4311</td>\n",
              "      <td>3991</td>\n",
              "      <td>4168</td>\n",
              "      <td>3942</td>\n",
              "      <td>4061</td>\n",
              "      <td>4362</td>\n",
              "      <td>4318</td>\n",
              "      <td>4252</td>\n",
              "      <td>4869</td>\n",
              "      <td>5284</td>\n",
              "      <td>5055</td>\n",
              "      <td>3591</td>\n",
              "      <td>...</td>\n",
              "      <td>1396</td>\n",
              "      <td>1381</td>\n",
              "      <td>1396</td>\n",
              "      <td>1381</td>\n",
              "      <td>1353</td>\n",
              "      <td>1346</td>\n",
              "      <td>1341</td>\n",
              "      <td>1332</td>\n",
              "      <td>1324</td>\n",
              "      <td>1310</td>\n",
              "      <td>1318</td>\n",
              "      <td>1330</td>\n",
              "      <td>1310</td>\n",
              "      <td>1292</td>\n",
              "      <td>1280</td>\n",
              "      <td>1275</td>\n",
              "      <td>1266</td>\n",
              "      <td>1264</td>\n",
              "      <td>1233</td>\n",
              "      <td>1241</td>\n",
              "      <td>1232</td>\n",
              "      <td>1215</td>\n",
              "      <td>1215</td>\n",
              "      <td>1187</td>\n",
              "      <td>1168</td>\n",
              "      <td>1171</td>\n",
              "      <td>1150</td>\n",
              "      <td>1134</td>\n",
              "      <td>1123</td>\n",
              "      <td>1135</td>\n",
              "      <td>1094</td>\n",
              "      <td>1090</td>\n",
              "      <td>1112</td>\n",
              "      <td>1090</td>\n",
              "      <td>1062</td>\n",
              "      <td>1069</td>\n",
              "      <td>1057</td>\n",
              "      <td>1020</td>\n",
              "      <td>1020</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2580</td>\n",
              "      <td>4266</td>\n",
              "      <td>4502</td>\n",
              "      <td>4426</td>\n",
              "      <td>4853</td>\n",
              "      <td>5249</td>\n",
              "      <td>5352</td>\n",
              "      <td>5353</td>\n",
              "      <td>5347</td>\n",
              "      <td>5065</td>\n",
              "      <td>5141</td>\n",
              "      <td>5100</td>\n",
              "      <td>4994</td>\n",
              "      <td>5172</td>\n",
              "      <td>5290</td>\n",
              "      <td>5289</td>\n",
              "      <td>5217</td>\n",
              "      <td>5053</td>\n",
              "      <td>5033</td>\n",
              "      <td>4939</td>\n",
              "      <td>4931</td>\n",
              "      <td>4941</td>\n",
              "      <td>4902</td>\n",
              "      <td>4824</td>\n",
              "      <td>4859</td>\n",
              "      <td>4805</td>\n",
              "      <td>4698</td>\n",
              "      <td>4794</td>\n",
              "      <td>4806</td>\n",
              "      <td>4452</td>\n",
              "      <td>4628</td>\n",
              "      <td>4433</td>\n",
              "      <td>4643</td>\n",
              "      <td>4967</td>\n",
              "      <td>4853</td>\n",
              "      <td>4760</td>\n",
              "      <td>5449</td>\n",
              "      <td>5768</td>\n",
              "      <td>5684</td>\n",
              "      <td>3987</td>\n",
              "      <td>...</td>\n",
              "      <td>1421</td>\n",
              "      <td>1415</td>\n",
              "      <td>1428</td>\n",
              "      <td>1415</td>\n",
              "      <td>1379</td>\n",
              "      <td>1370</td>\n",
              "      <td>1360</td>\n",
              "      <td>1353</td>\n",
              "      <td>1352</td>\n",
              "      <td>1336</td>\n",
              "      <td>1346</td>\n",
              "      <td>1351</td>\n",
              "      <td>1330</td>\n",
              "      <td>1315</td>\n",
              "      <td>1305</td>\n",
              "      <td>1292</td>\n",
              "      <td>1282</td>\n",
              "      <td>1286</td>\n",
              "      <td>1259</td>\n",
              "      <td>1259</td>\n",
              "      <td>1250</td>\n",
              "      <td>1229</td>\n",
              "      <td>1232</td>\n",
              "      <td>1195</td>\n",
              "      <td>1177</td>\n",
              "      <td>1184</td>\n",
              "      <td>1153</td>\n",
              "      <td>1137</td>\n",
              "      <td>1138</td>\n",
              "      <td>1137</td>\n",
              "      <td>1108</td>\n",
              "      <td>1104</td>\n",
              "      <td>1117</td>\n",
              "      <td>1091</td>\n",
              "      <td>1079</td>\n",
              "      <td>1085</td>\n",
              "      <td>1064</td>\n",
              "      <td>1029</td>\n",
              "      <td>1020</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3687</td>\n",
              "      <td>4266</td>\n",
              "      <td>4421</td>\n",
              "      <td>4498</td>\n",
              "      <td>5019</td>\n",
              "      <td>5293</td>\n",
              "      <td>5438</td>\n",
              "      <td>5427</td>\n",
              "      <td>5383</td>\n",
              "      <td>5132</td>\n",
              "      <td>5227</td>\n",
              "      <td>5172</td>\n",
              "      <td>5097</td>\n",
              "      <td>5313</td>\n",
              "      <td>5411</td>\n",
              "      <td>5412</td>\n",
              "      <td>5341</td>\n",
              "      <td>5191</td>\n",
              "      <td>5140</td>\n",
              "      <td>5069</td>\n",
              "      <td>5110</td>\n",
              "      <td>5119</td>\n",
              "      <td>5046</td>\n",
              "      <td>4981</td>\n",
              "      <td>5023</td>\n",
              "      <td>4987</td>\n",
              "      <td>4862</td>\n",
              "      <td>4965</td>\n",
              "      <td>4992</td>\n",
              "      <td>4595</td>\n",
              "      <td>4756</td>\n",
              "      <td>4529</td>\n",
              "      <td>4801</td>\n",
              "      <td>5077</td>\n",
              "      <td>4983</td>\n",
              "      <td>4868</td>\n",
              "      <td>5515</td>\n",
              "      <td>5972</td>\n",
              "      <td>5913</td>\n",
              "      <td>4027</td>\n",
              "      <td>...</td>\n",
              "      <td>1446</td>\n",
              "      <td>1440</td>\n",
              "      <td>1443</td>\n",
              "      <td>1425</td>\n",
              "      <td>1390</td>\n",
              "      <td>1379</td>\n",
              "      <td>1376</td>\n",
              "      <td>1363</td>\n",
              "      <td>1355</td>\n",
              "      <td>1347</td>\n",
              "      <td>1361</td>\n",
              "      <td>1356</td>\n",
              "      <td>1341</td>\n",
              "      <td>1330</td>\n",
              "      <td>1321</td>\n",
              "      <td>1304</td>\n",
              "      <td>1290</td>\n",
              "      <td>1289</td>\n",
              "      <td>1263</td>\n",
              "      <td>1269</td>\n",
              "      <td>1261</td>\n",
              "      <td>1245</td>\n",
              "      <td>1241</td>\n",
              "      <td>1214</td>\n",
              "      <td>1185</td>\n",
              "      <td>1188</td>\n",
              "      <td>1156</td>\n",
              "      <td>1147</td>\n",
              "      <td>1149</td>\n",
              "      <td>1144</td>\n",
              "      <td>1111</td>\n",
              "      <td>1114</td>\n",
              "      <td>1114</td>\n",
              "      <td>1100</td>\n",
              "      <td>1065</td>\n",
              "      <td>1092</td>\n",
              "      <td>1061</td>\n",
              "      <td>1030</td>\n",
              "      <td>1016</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2749</td>\n",
              "      <td>4258</td>\n",
              "      <td>4603</td>\n",
              "      <td>4493</td>\n",
              "      <td>4958</td>\n",
              "      <td>5234</td>\n",
              "      <td>5417</td>\n",
              "      <td>5355</td>\n",
              "      <td>5349</td>\n",
              "      <td>5096</td>\n",
              "      <td>5147</td>\n",
              "      <td>5078</td>\n",
              "      <td>5040</td>\n",
              "      <td>5237</td>\n",
              "      <td>5321</td>\n",
              "      <td>5344</td>\n",
              "      <td>5255</td>\n",
              "      <td>5121</td>\n",
              "      <td>5035</td>\n",
              "      <td>4956</td>\n",
              "      <td>4994</td>\n",
              "      <td>4980</td>\n",
              "      <td>4905</td>\n",
              "      <td>4857</td>\n",
              "      <td>4900</td>\n",
              "      <td>4831</td>\n",
              "      <td>4720</td>\n",
              "      <td>4848</td>\n",
              "      <td>4847</td>\n",
              "      <td>4484</td>\n",
              "      <td>4613</td>\n",
              "      <td>4402</td>\n",
              "      <td>4674</td>\n",
              "      <td>4966</td>\n",
              "      <td>4848</td>\n",
              "      <td>4776</td>\n",
              "      <td>5473</td>\n",
              "      <td>5894</td>\n",
              "      <td>5789</td>\n",
              "      <td>4086</td>\n",
              "      <td>...</td>\n",
              "      <td>1432</td>\n",
              "      <td>1427</td>\n",
              "      <td>1426</td>\n",
              "      <td>1416</td>\n",
              "      <td>1386</td>\n",
              "      <td>1374</td>\n",
              "      <td>1375</td>\n",
              "      <td>1359</td>\n",
              "      <td>1343</td>\n",
              "      <td>1343</td>\n",
              "      <td>1354</td>\n",
              "      <td>1351</td>\n",
              "      <td>1333</td>\n",
              "      <td>1329</td>\n",
              "      <td>1313</td>\n",
              "      <td>1296</td>\n",
              "      <td>1280</td>\n",
              "      <td>1281</td>\n",
              "      <td>1251</td>\n",
              "      <td>1255</td>\n",
              "      <td>1253</td>\n",
              "      <td>1238</td>\n",
              "      <td>1223</td>\n",
              "      <td>1207</td>\n",
              "      <td>1188</td>\n",
              "      <td>1188</td>\n",
              "      <td>1154</td>\n",
              "      <td>1143</td>\n",
              "      <td>1144</td>\n",
              "      <td>1146</td>\n",
              "      <td>1122</td>\n",
              "      <td>1108</td>\n",
              "      <td>1109</td>\n",
              "      <td>1109</td>\n",
              "      <td>1071</td>\n",
              "      <td>1088</td>\n",
              "      <td>1060</td>\n",
              "      <td>1030</td>\n",
              "      <td>1006</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2746</td>\n",
              "      <td>4018</td>\n",
              "      <td>4675</td>\n",
              "      <td>4417</td>\n",
              "      <td>4886</td>\n",
              "      <td>5117</td>\n",
              "      <td>5215</td>\n",
              "      <td>5096</td>\n",
              "      <td>5098</td>\n",
              "      <td>4834</td>\n",
              "      <td>4853</td>\n",
              "      <td>4857</td>\n",
              "      <td>4734</td>\n",
              "      <td>4879</td>\n",
              "      <td>4976</td>\n",
              "      <td>4958</td>\n",
              "      <td>4885</td>\n",
              "      <td>4754</td>\n",
              "      <td>4647</td>\n",
              "      <td>4532</td>\n",
              "      <td>4586</td>\n",
              "      <td>4591</td>\n",
              "      <td>4492</td>\n",
              "      <td>4453</td>\n",
              "      <td>4497</td>\n",
              "      <td>4398</td>\n",
              "      <td>4297</td>\n",
              "      <td>4408</td>\n",
              "      <td>4401</td>\n",
              "      <td>4102</td>\n",
              "      <td>4227</td>\n",
              "      <td>4075</td>\n",
              "      <td>4264</td>\n",
              "      <td>4529</td>\n",
              "      <td>4490</td>\n",
              "      <td>4438</td>\n",
              "      <td>5001</td>\n",
              "      <td>5378</td>\n",
              "      <td>5321</td>\n",
              "      <td>3779</td>\n",
              "      <td>...</td>\n",
              "      <td>1401</td>\n",
              "      <td>1397</td>\n",
              "      <td>1395</td>\n",
              "      <td>1390</td>\n",
              "      <td>1368</td>\n",
              "      <td>1349</td>\n",
              "      <td>1354</td>\n",
              "      <td>1340</td>\n",
              "      <td>1330</td>\n",
              "      <td>1324</td>\n",
              "      <td>1336</td>\n",
              "      <td>1332</td>\n",
              "      <td>1320</td>\n",
              "      <td>1307</td>\n",
              "      <td>1287</td>\n",
              "      <td>1283</td>\n",
              "      <td>1267</td>\n",
              "      <td>1265</td>\n",
              "      <td>1239</td>\n",
              "      <td>1240</td>\n",
              "      <td>1239</td>\n",
              "      <td>1229</td>\n",
              "      <td>1212</td>\n",
              "      <td>1202</td>\n",
              "      <td>1178</td>\n",
              "      <td>1178</td>\n",
              "      <td>1143</td>\n",
              "      <td>1135</td>\n",
              "      <td>1138</td>\n",
              "      <td>1135</td>\n",
              "      <td>1110</td>\n",
              "      <td>1107</td>\n",
              "      <td>1112</td>\n",
              "      <td>1094</td>\n",
              "      <td>1072</td>\n",
              "      <td>1087</td>\n",
              "      <td>1052</td>\n",
              "      <td>1034</td>\n",
              "      <td>1019</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21020</th>\n",
              "      <td>2561</td>\n",
              "      <td>3987</td>\n",
              "      <td>4011</td>\n",
              "      <td>4023</td>\n",
              "      <td>4201</td>\n",
              "      <td>4377</td>\n",
              "      <td>4418</td>\n",
              "      <td>4248</td>\n",
              "      <td>4180</td>\n",
              "      <td>3838</td>\n",
              "      <td>3762</td>\n",
              "      <td>3696</td>\n",
              "      <td>3594</td>\n",
              "      <td>3750</td>\n",
              "      <td>3806</td>\n",
              "      <td>3764</td>\n",
              "      <td>3655</td>\n",
              "      <td>2611</td>\n",
              "      <td>3199</td>\n",
              "      <td>3036</td>\n",
              "      <td>2978</td>\n",
              "      <td>2837</td>\n",
              "      <td>2758</td>\n",
              "      <td>2650</td>\n",
              "      <td>2617</td>\n",
              "      <td>2494</td>\n",
              "      <td>2397</td>\n",
              "      <td>2366</td>\n",
              "      <td>2313</td>\n",
              "      <td>2198</td>\n",
              "      <td>2464</td>\n",
              "      <td>2261</td>\n",
              "      <td>2490</td>\n",
              "      <td>3124</td>\n",
              "      <td>3643</td>\n",
              "      <td>4349</td>\n",
              "      <td>5748</td>\n",
              "      <td>6973</td>\n",
              "      <td>7199</td>\n",
              "      <td>5067</td>\n",
              "      <td>...</td>\n",
              "      <td>1082</td>\n",
              "      <td>1079</td>\n",
              "      <td>1077</td>\n",
              "      <td>1086</td>\n",
              "      <td>1071</td>\n",
              "      <td>1084</td>\n",
              "      <td>1079</td>\n",
              "      <td>1076</td>\n",
              "      <td>1082</td>\n",
              "      <td>1077</td>\n",
              "      <td>1082</td>\n",
              "      <td>1078</td>\n",
              "      <td>1077</td>\n",
              "      <td>1068</td>\n",
              "      <td>1070</td>\n",
              "      <td>1053</td>\n",
              "      <td>1063</td>\n",
              "      <td>1055</td>\n",
              "      <td>1052</td>\n",
              "      <td>1047</td>\n",
              "      <td>1042</td>\n",
              "      <td>1043</td>\n",
              "      <td>1031</td>\n",
              "      <td>1025</td>\n",
              "      <td>1034</td>\n",
              "      <td>1029</td>\n",
              "      <td>1026</td>\n",
              "      <td>1025</td>\n",
              "      <td>1018</td>\n",
              "      <td>1021</td>\n",
              "      <td>1013</td>\n",
              "      <td>1012</td>\n",
              "      <td>1018</td>\n",
              "      <td>1015</td>\n",
              "      <td>1011</td>\n",
              "      <td>1001</td>\n",
              "      <td>1000</td>\n",
              "      <td>1009</td>\n",
              "      <td>1008</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21021</th>\n",
              "      <td>2726</td>\n",
              "      <td>4104</td>\n",
              "      <td>4024</td>\n",
              "      <td>3880</td>\n",
              "      <td>4210</td>\n",
              "      <td>4377</td>\n",
              "      <td>4413</td>\n",
              "      <td>4174</td>\n",
              "      <td>4229</td>\n",
              "      <td>3900</td>\n",
              "      <td>3786</td>\n",
              "      <td>3696</td>\n",
              "      <td>3623</td>\n",
              "      <td>3726</td>\n",
              "      <td>3758</td>\n",
              "      <td>3725</td>\n",
              "      <td>3614</td>\n",
              "      <td>2584</td>\n",
              "      <td>3174</td>\n",
              "      <td>3042</td>\n",
              "      <td>2958</td>\n",
              "      <td>2837</td>\n",
              "      <td>2769</td>\n",
              "      <td>2626</td>\n",
              "      <td>2617</td>\n",
              "      <td>2484</td>\n",
              "      <td>2387</td>\n",
              "      <td>2362</td>\n",
              "      <td>2322</td>\n",
              "      <td>2199</td>\n",
              "      <td>2463</td>\n",
              "      <td>2188</td>\n",
              "      <td>2444</td>\n",
              "      <td>3077</td>\n",
              "      <td>2808</td>\n",
              "      <td>4239</td>\n",
              "      <td>5706</td>\n",
              "      <td>6965</td>\n",
              "      <td>7227</td>\n",
              "      <td>5108</td>\n",
              "      <td>...</td>\n",
              "      <td>1086</td>\n",
              "      <td>1076</td>\n",
              "      <td>1086</td>\n",
              "      <td>1081</td>\n",
              "      <td>1069</td>\n",
              "      <td>1086</td>\n",
              "      <td>1078</td>\n",
              "      <td>1081</td>\n",
              "      <td>1078</td>\n",
              "      <td>1075</td>\n",
              "      <td>1084</td>\n",
              "      <td>1087</td>\n",
              "      <td>1082</td>\n",
              "      <td>1071</td>\n",
              "      <td>1064</td>\n",
              "      <td>1059</td>\n",
              "      <td>1063</td>\n",
              "      <td>1051</td>\n",
              "      <td>1049</td>\n",
              "      <td>1042</td>\n",
              "      <td>1042</td>\n",
              "      <td>1043</td>\n",
              "      <td>1031</td>\n",
              "      <td>1029</td>\n",
              "      <td>1029</td>\n",
              "      <td>1026</td>\n",
              "      <td>1021</td>\n",
              "      <td>1026</td>\n",
              "      <td>1021</td>\n",
              "      <td>1023</td>\n",
              "      <td>1012</td>\n",
              "      <td>1014</td>\n",
              "      <td>1012</td>\n",
              "      <td>1024</td>\n",
              "      <td>998</td>\n",
              "      <td>1010</td>\n",
              "      <td>1006</td>\n",
              "      <td>1000</td>\n",
              "      <td>1000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21022</th>\n",
              "      <td>3153</td>\n",
              "      <td>3864</td>\n",
              "      <td>4282</td>\n",
              "      <td>3889</td>\n",
              "      <td>4310</td>\n",
              "      <td>4372</td>\n",
              "      <td>4375</td>\n",
              "      <td>4208</td>\n",
              "      <td>4096</td>\n",
              "      <td>3878</td>\n",
              "      <td>3890</td>\n",
              "      <td>3683</td>\n",
              "      <td>3594</td>\n",
              "      <td>3714</td>\n",
              "      <td>3724</td>\n",
              "      <td>3700</td>\n",
              "      <td>2809</td>\n",
              "      <td>2564</td>\n",
              "      <td>3177</td>\n",
              "      <td>3031</td>\n",
              "      <td>2925</td>\n",
              "      <td>2837</td>\n",
              "      <td>2719</td>\n",
              "      <td>2605</td>\n",
              "      <td>2603</td>\n",
              "      <td>2476</td>\n",
              "      <td>2373</td>\n",
              "      <td>2335</td>\n",
              "      <td>2308</td>\n",
              "      <td>2198</td>\n",
              "      <td>2449</td>\n",
              "      <td>2164</td>\n",
              "      <td>2443</td>\n",
              "      <td>3048</td>\n",
              "      <td>3585</td>\n",
              "      <td>4264</td>\n",
              "      <td>5689</td>\n",
              "      <td>6839</td>\n",
              "      <td>7027</td>\n",
              "      <td>5013</td>\n",
              "      <td>...</td>\n",
              "      <td>1080</td>\n",
              "      <td>1075</td>\n",
              "      <td>1085</td>\n",
              "      <td>1075</td>\n",
              "      <td>1076</td>\n",
              "      <td>1078</td>\n",
              "      <td>1066</td>\n",
              "      <td>1075</td>\n",
              "      <td>1073</td>\n",
              "      <td>1073</td>\n",
              "      <td>1079</td>\n",
              "      <td>1085</td>\n",
              "      <td>1075</td>\n",
              "      <td>1075</td>\n",
              "      <td>1064</td>\n",
              "      <td>1059</td>\n",
              "      <td>1057</td>\n",
              "      <td>1049</td>\n",
              "      <td>1047</td>\n",
              "      <td>1044</td>\n",
              "      <td>1034</td>\n",
              "      <td>1027</td>\n",
              "      <td>1034</td>\n",
              "      <td>1035</td>\n",
              "      <td>1027</td>\n",
              "      <td>1022</td>\n",
              "      <td>1023</td>\n",
              "      <td>1029</td>\n",
              "      <td>1026</td>\n",
              "      <td>1020</td>\n",
              "      <td>1016</td>\n",
              "      <td>1015</td>\n",
              "      <td>1016</td>\n",
              "      <td>1021</td>\n",
              "      <td>1008</td>\n",
              "      <td>1019</td>\n",
              "      <td>1003</td>\n",
              "      <td>1008</td>\n",
              "      <td>1000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21023</th>\n",
              "      <td>3155</td>\n",
              "      <td>4104</td>\n",
              "      <td>4106</td>\n",
              "      <td>4027</td>\n",
              "      <td>4139</td>\n",
              "      <td>4318</td>\n",
              "      <td>4413</td>\n",
              "      <td>4174</td>\n",
              "      <td>4140</td>\n",
              "      <td>3933</td>\n",
              "      <td>3799</td>\n",
              "      <td>3627</td>\n",
              "      <td>2752</td>\n",
              "      <td>3667</td>\n",
              "      <td>3688</td>\n",
              "      <td>3628</td>\n",
              "      <td>2750</td>\n",
              "      <td>3245</td>\n",
              "      <td>3153</td>\n",
              "      <td>2967</td>\n",
              "      <td>2890</td>\n",
              "      <td>2830</td>\n",
              "      <td>2719</td>\n",
              "      <td>2583</td>\n",
              "      <td>2580</td>\n",
              "      <td>2480</td>\n",
              "      <td>2359</td>\n",
              "      <td>2339</td>\n",
              "      <td>2289</td>\n",
              "      <td>2184</td>\n",
              "      <td>2415</td>\n",
              "      <td>2236</td>\n",
              "      <td>2418</td>\n",
              "      <td>2935</td>\n",
              "      <td>2617</td>\n",
              "      <td>4017</td>\n",
              "      <td>5283</td>\n",
              "      <td>6354</td>\n",
              "      <td>6602</td>\n",
              "      <td>4703</td>\n",
              "      <td>...</td>\n",
              "      <td>1068</td>\n",
              "      <td>1075</td>\n",
              "      <td>1078</td>\n",
              "      <td>1074</td>\n",
              "      <td>1075</td>\n",
              "      <td>1074</td>\n",
              "      <td>1067</td>\n",
              "      <td>1069</td>\n",
              "      <td>1069</td>\n",
              "      <td>1071</td>\n",
              "      <td>1073</td>\n",
              "      <td>1075</td>\n",
              "      <td>1074</td>\n",
              "      <td>1065</td>\n",
              "      <td>1062</td>\n",
              "      <td>1064</td>\n",
              "      <td>1051</td>\n",
              "      <td>1050</td>\n",
              "      <td>1041</td>\n",
              "      <td>1052</td>\n",
              "      <td>1033</td>\n",
              "      <td>1042</td>\n",
              "      <td>1040</td>\n",
              "      <td>1039</td>\n",
              "      <td>1024</td>\n",
              "      <td>1024</td>\n",
              "      <td>1028</td>\n",
              "      <td>1020</td>\n",
              "      <td>1020</td>\n",
              "      <td>1015</td>\n",
              "      <td>1005</td>\n",
              "      <td>1011</td>\n",
              "      <td>1008</td>\n",
              "      <td>1012</td>\n",
              "      <td>1014</td>\n",
              "      <td>1007</td>\n",
              "      <td>1011</td>\n",
              "      <td>1005</td>\n",
              "      <td>1003</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21024</th>\n",
              "      <td>3323</td>\n",
              "      <td>3860</td>\n",
              "      <td>4197</td>\n",
              "      <td>3952</td>\n",
              "      <td>4148</td>\n",
              "      <td>4279</td>\n",
              "      <td>4375</td>\n",
              "      <td>4225</td>\n",
              "      <td>3988</td>\n",
              "      <td>3866</td>\n",
              "      <td>3811</td>\n",
              "      <td>3639</td>\n",
              "      <td>3623</td>\n",
              "      <td>3686</td>\n",
              "      <td>3722</td>\n",
              "      <td>3673</td>\n",
              "      <td>2775</td>\n",
              "      <td>3315</td>\n",
              "      <td>3180</td>\n",
              "      <td>2984</td>\n",
              "      <td>2910</td>\n",
              "      <td>2837</td>\n",
              "      <td>2719</td>\n",
              "      <td>2614</td>\n",
              "      <td>2594</td>\n",
              "      <td>2494</td>\n",
              "      <td>2370</td>\n",
              "      <td>2352</td>\n",
              "      <td>2296</td>\n",
              "      <td>2187</td>\n",
              "      <td>2430</td>\n",
              "      <td>2139</td>\n",
              "      <td>2354</td>\n",
              "      <td>2966</td>\n",
              "      <td>2725</td>\n",
              "      <td>4071</td>\n",
              "      <td>5261</td>\n",
              "      <td>6418</td>\n",
              "      <td>6571</td>\n",
              "      <td>4702</td>\n",
              "      <td>...</td>\n",
              "      <td>1068</td>\n",
              "      <td>1086</td>\n",
              "      <td>1084</td>\n",
              "      <td>1078</td>\n",
              "      <td>1085</td>\n",
              "      <td>1082</td>\n",
              "      <td>1077</td>\n",
              "      <td>1078</td>\n",
              "      <td>1073</td>\n",
              "      <td>1073</td>\n",
              "      <td>1085</td>\n",
              "      <td>1081</td>\n",
              "      <td>1078</td>\n",
              "      <td>1062</td>\n",
              "      <td>1066</td>\n",
              "      <td>1068</td>\n",
              "      <td>1052</td>\n",
              "      <td>1053</td>\n",
              "      <td>1049</td>\n",
              "      <td>1046</td>\n",
              "      <td>1044</td>\n",
              "      <td>1046</td>\n",
              "      <td>1040</td>\n",
              "      <td>1034</td>\n",
              "      <td>1023</td>\n",
              "      <td>1022</td>\n",
              "      <td>1026</td>\n",
              "      <td>1014</td>\n",
              "      <td>1014</td>\n",
              "      <td>1015</td>\n",
              "      <td>1018</td>\n",
              "      <td>1014</td>\n",
              "      <td>1007</td>\n",
              "      <td>1015</td>\n",
              "      <td>1002</td>\n",
              "      <td>1010</td>\n",
              "      <td>1007</td>\n",
              "      <td>1004</td>\n",
              "      <td>1000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>21025 rows × 201 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       band-1  band-2  band-3  band-4  ...  band-198  band-199  band-200  class\n",
              "0        3172    4142    4506    4279  ...      1057      1020      1020      3\n",
              "1        2580    4266    4502    4426  ...      1064      1029      1020      3\n",
              "2        3687    4266    4421    4498  ...      1061      1030      1016      3\n",
              "3        2749    4258    4603    4493  ...      1060      1030      1006      3\n",
              "4        2746    4018    4675    4417  ...      1052      1034      1019      3\n",
              "...       ...     ...     ...     ...  ...       ...       ...       ...    ...\n",
              "21020    2561    3987    4011    4023  ...      1000      1009      1008      0\n",
              "21021    2726    4104    4024    3880  ...      1006      1000      1000      0\n",
              "21022    3153    3864    4282    3889  ...      1003      1008      1000      0\n",
              "21023    3155    4104    4106    4027  ...      1011      1005      1003      0\n",
              "21024    3323    3860    4197    3952  ...      1007      1004      1000      0\n",
              "\n",
              "[21025 rows x 201 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EmW2P_hfoNoe"
      },
      "source": [
        "df.to_csv('Dataset.csv', index=False)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7Y8hYHSFp50o"
      },
      "source": [
        "def plot_signature(df):\n",
        "    plt.figure(figsize=(12, 6))\n",
        "    pixel_no = np.random.randint(df.shape[0])\n",
        "    plt.plot(range(1, 201), df.iloc[pixel_no, :-1].values.tolist(), 'b--', label= f'Class - {df.iloc[pixel_no, -1]}')\n",
        "    plt.legend()\n",
        "    plt.title(f'Pixel({pixel_no}) signature', fontsize=14)\n",
        "    plt.xlabel('Band Number', fontsize=14)\n",
        "    plt.ylabel('Pixel Intensity', fontsize=14)\n",
        "    plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tOpJc4XKrR1M",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 409
        },
        "outputId": "1f5cf42b-eb65-4c64-a379-7bc9eaf60bb3"
      },
      "source": [
        "plot_signature(df)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nADVtb9trtbK",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f525f907-704d-4875-d1e0-1ba9b722f556"
      },
      "source": [
        "ls"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Dataset.csv                 Indian_pines_corrected.mat.1  \u001b[0m\u001b[01;34msample_data\u001b[0m/\n",
            "Indian_pines_corrected.mat  Indian_pines_gt.mat\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CwUEQRrTs3g3"
      },
      "source": [
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F3KmYKN0sRtA",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 290
        },
        "outputId": "a3a42835-7873-4ce9-9b7e-9a6798e9e8f6"
      },
      "source": [
        "df.sample(6)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>band-1</th>\n",
              "      <th>band-2</th>\n",
              "      <th>band-3</th>\n",
              "      <th>band-4</th>\n",
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              "      <th>band-10</th>\n",
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              "      <th>band-12</th>\n",
              "      <th>band-13</th>\n",
              "      <th>band-14</th>\n",
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              "      <th>band-18</th>\n",
              "      <th>band-19</th>\n",
              "      <th>band-20</th>\n",
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              "      <th>band-24</th>\n",
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              "      <th>band-32</th>\n",
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              "      <th>band-34</th>\n",
              "      <th>band-35</th>\n",
              "      <th>band-36</th>\n",
              "      <th>band-37</th>\n",
              "      <th>band-38</th>\n",
              "      <th>band-39</th>\n",
              "      <th>band-40</th>\n",
              "      <th>...</th>\n",
              "      <th>band-162</th>\n",
              "      <th>band-163</th>\n",
              "      <th>band-164</th>\n",
              "      <th>band-165</th>\n",
              "      <th>band-166</th>\n",
              "      <th>band-167</th>\n",
              "      <th>band-168</th>\n",
              "      <th>band-169</th>\n",
              "      <th>band-170</th>\n",
              "      <th>band-171</th>\n",
              "      <th>band-172</th>\n",
              "      <th>band-173</th>\n",
              "      <th>band-174</th>\n",
              "      <th>band-175</th>\n",
              "      <th>band-176</th>\n",
              "      <th>band-177</th>\n",
              "      <th>band-178</th>\n",
              "      <th>band-179</th>\n",
              "      <th>band-180</th>\n",
              "      <th>band-181</th>\n",
              "      <th>band-182</th>\n",
              "      <th>band-183</th>\n",
              "      <th>band-184</th>\n",
              "      <th>band-185</th>\n",
              "      <th>band-186</th>\n",
              "      <th>band-187</th>\n",
              "      <th>band-188</th>\n",
              "      <th>band-189</th>\n",
              "      <th>band-190</th>\n",
              "      <th>band-191</th>\n",
              "      <th>band-192</th>\n",
              "      <th>band-193</th>\n",
              "      <th>band-194</th>\n",
              "      <th>band-195</th>\n",
              "      <th>band-196</th>\n",
              "      <th>band-197</th>\n",
              "      <th>band-198</th>\n",
              "      <th>band-199</th>\n",
              "      <th>band-200</th>\n",
              "      <th>class</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2596</th>\n",
              "      <td>2737</td>\n",
              "      <td>4521</td>\n",
              "      <td>4700</td>\n",
              "      <td>4511</td>\n",
              "      <td>5030</td>\n",
              "      <td>5355</td>\n",
              "      <td>5445</td>\n",
              "      <td>5323</td>\n",
              "      <td>5326</td>\n",
              "      <td>5053</td>\n",
              "      <td>5073</td>\n",
              "      <td>5020</td>\n",
              "      <td>4990</td>\n",
              "      <td>5193</td>\n",
              "      <td>5234</td>\n",
              "      <td>5256</td>\n",
              "      <td>5112</td>\n",
              "      <td>5013</td>\n",
              "      <td>4949</td>\n",
              "      <td>4851</td>\n",
              "      <td>4830</td>\n",
              "      <td>4854</td>\n",
              "      <td>4785</td>\n",
              "      <td>4732</td>\n",
              "      <td>4753</td>\n",
              "      <td>4677</td>\n",
              "      <td>4562</td>\n",
              "      <td>4669</td>\n",
              "      <td>4677</td>\n",
              "      <td>4325</td>\n",
              "      <td>4561</td>\n",
              "      <td>4290</td>\n",
              "      <td>4534</td>\n",
              "      <td>4906</td>\n",
              "      <td>4797</td>\n",
              "      <td>4724</td>\n",
              "      <td>5344</td>\n",
              "      <td>5739</td>\n",
              "      <td>5588</td>\n",
              "      <td>3910</td>\n",
              "      <td>...</td>\n",
              "      <td>1358</td>\n",
              "      <td>1357</td>\n",
              "      <td>1358</td>\n",
              "      <td>1350</td>\n",
              "      <td>1326</td>\n",
              "      <td>1321</td>\n",
              "      <td>1323</td>\n",
              "      <td>1314</td>\n",
              "      <td>1306</td>\n",
              "      <td>1291</td>\n",
              "      <td>1317</td>\n",
              "      <td>1310</td>\n",
              "      <td>1307</td>\n",
              "      <td>1278</td>\n",
              "      <td>1275</td>\n",
              "      <td>1255</td>\n",
              "      <td>1242</td>\n",
              "      <td>1235</td>\n",
              "      <td>1220</td>\n",
              "      <td>1214</td>\n",
              "      <td>1209</td>\n",
              "      <td>1193</td>\n",
              "      <td>1196</td>\n",
              "      <td>1168</td>\n",
              "      <td>1157</td>\n",
              "      <td>1159</td>\n",
              "      <td>1129</td>\n",
              "      <td>1119</td>\n",
              "      <td>1120</td>\n",
              "      <td>1114</td>\n",
              "      <td>1084</td>\n",
              "      <td>1091</td>\n",
              "      <td>1102</td>\n",
              "      <td>1075</td>\n",
              "      <td>1051</td>\n",
              "      <td>1064</td>\n",
              "      <td>1045</td>\n",
              "      <td>1029</td>\n",
              "      <td>1009</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18250</th>\n",
              "      <td>3320</td>\n",
              "      <td>3727</td>\n",
              "      <td>4011</td>\n",
              "      <td>4034</td>\n",
              "      <td>4262</td>\n",
              "      <td>4375</td>\n",
              "      <td>4285</td>\n",
              "      <td>4213</td>\n",
              "      <td>4092</td>\n",
              "      <td>3866</td>\n",
              "      <td>3775</td>\n",
              "      <td>3636</td>\n",
              "      <td>2765</td>\n",
              "      <td>3636</td>\n",
              "      <td>3713</td>\n",
              "      <td>3678</td>\n",
              "      <td>2764</td>\n",
              "      <td>3307</td>\n",
              "      <td>3180</td>\n",
              "      <td>3005</td>\n",
              "      <td>2938</td>\n",
              "      <td>2821</td>\n",
              "      <td>2722</td>\n",
              "      <td>2665</td>\n",
              "      <td>2641</td>\n",
              "      <td>2508</td>\n",
              "      <td>2428</td>\n",
              "      <td>2368</td>\n",
              "      <td>2337</td>\n",
              "      <td>2221</td>\n",
              "      <td>2485</td>\n",
              "      <td>2262</td>\n",
              "      <td>2406</td>\n",
              "      <td>2923</td>\n",
              "      <td>3267</td>\n",
              "      <td>3804</td>\n",
              "      <td>4815</td>\n",
              "      <td>5646</td>\n",
              "      <td>5839</td>\n",
              "      <td>4183</td>\n",
              "      <td>...</td>\n",
              "      <td>1088</td>\n",
              "      <td>1088</td>\n",
              "      <td>1081</td>\n",
              "      <td>1086</td>\n",
              "      <td>1085</td>\n",
              "      <td>1074</td>\n",
              "      <td>1077</td>\n",
              "      <td>1081</td>\n",
              "      <td>1073</td>\n",
              "      <td>1069</td>\n",
              "      <td>1079</td>\n",
              "      <td>1076</td>\n",
              "      <td>1070</td>\n",
              "      <td>1067</td>\n",
              "      <td>1069</td>\n",
              "      <td>1056</td>\n",
              "      <td>1053</td>\n",
              "      <td>1045</td>\n",
              "      <td>1054</td>\n",
              "      <td>1042</td>\n",
              "      <td>1043</td>\n",
              "      <td>1035</td>\n",
              "      <td>1039</td>\n",
              "      <td>1029</td>\n",
              "      <td>1021</td>\n",
              "      <td>1025</td>\n",
              "      <td>1024</td>\n",
              "      <td>1019</td>\n",
              "      <td>1015</td>\n",
              "      <td>1026</td>\n",
              "      <td>1024</td>\n",
              "      <td>1011</td>\n",
              "      <td>1016</td>\n",
              "      <td>1015</td>\n",
              "      <td>1009</td>\n",
              "      <td>1013</td>\n",
              "      <td>1012</td>\n",
              "      <td>1000</td>\n",
              "      <td>1014</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12135</th>\n",
              "      <td>3196</td>\n",
              "      <td>4119</td>\n",
              "      <td>4032</td>\n",
              "      <td>3823</td>\n",
              "      <td>4285</td>\n",
              "      <td>4435</td>\n",
              "      <td>4520</td>\n",
              "      <td>4270</td>\n",
              "      <td>4185</td>\n",
              "      <td>3995</td>\n",
              "      <td>3911</td>\n",
              "      <td>3872</td>\n",
              "      <td>3777</td>\n",
              "      <td>3966</td>\n",
              "      <td>3995</td>\n",
              "      <td>3994</td>\n",
              "      <td>3922</td>\n",
              "      <td>3675</td>\n",
              "      <td>2721</td>\n",
              "      <td>3323</td>\n",
              "      <td>3252</td>\n",
              "      <td>3148</td>\n",
              "      <td>3065</td>\n",
              "      <td>2992</td>\n",
              "      <td>2905</td>\n",
              "      <td>2807</td>\n",
              "      <td>2672</td>\n",
              "      <td>2617</td>\n",
              "      <td>2567</td>\n",
              "      <td>2463</td>\n",
              "      <td>2863</td>\n",
              "      <td>2466</td>\n",
              "      <td>2853</td>\n",
              "      <td>3588</td>\n",
              "      <td>4068</td>\n",
              "      <td>4525</td>\n",
              "      <td>5591</td>\n",
              "      <td>6374</td>\n",
              "      <td>6368</td>\n",
              "      <td>4441</td>\n",
              "      <td>...</td>\n",
              "      <td>1117</td>\n",
              "      <td>1108</td>\n",
              "      <td>1112</td>\n",
              "      <td>1122</td>\n",
              "      <td>1109</td>\n",
              "      <td>1106</td>\n",
              "      <td>1116</td>\n",
              "      <td>1102</td>\n",
              "      <td>1109</td>\n",
              "      <td>1108</td>\n",
              "      <td>1112</td>\n",
              "      <td>1107</td>\n",
              "      <td>1103</td>\n",
              "      <td>1102</td>\n",
              "      <td>1084</td>\n",
              "      <td>1086</td>\n",
              "      <td>1080</td>\n",
              "      <td>1072</td>\n",
              "      <td>1066</td>\n",
              "      <td>1073</td>\n",
              "      <td>1067</td>\n",
              "      <td>1057</td>\n",
              "      <td>1053</td>\n",
              "      <td>1047</td>\n",
              "      <td>1041</td>\n",
              "      <td>1044</td>\n",
              "      <td>1029</td>\n",
              "      <td>1028</td>\n",
              "      <td>1032</td>\n",
              "      <td>1044</td>\n",
              "      <td>1025</td>\n",
              "      <td>1030</td>\n",
              "      <td>1023</td>\n",
              "      <td>1008</td>\n",
              "      <td>1020</td>\n",
              "      <td>1014</td>\n",
              "      <td>1011</td>\n",
              "      <td>1000</td>\n",
              "      <td>1013</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20725</th>\n",
              "      <td>2730</td>\n",
              "      <td>4355</td>\n",
              "      <td>4552</td>\n",
              "      <td>4463</td>\n",
              "      <td>4772</td>\n",
              "      <td>5120</td>\n",
              "      <td>5164</td>\n",
              "      <td>5035</td>\n",
              "      <td>5044</td>\n",
              "      <td>4878</td>\n",
              "      <td>4754</td>\n",
              "      <td>4779</td>\n",
              "      <td>4648</td>\n",
              "      <td>4841</td>\n",
              "      <td>4899</td>\n",
              "      <td>4861</td>\n",
              "      <td>4817</td>\n",
              "      <td>4658</td>\n",
              "      <td>4613</td>\n",
              "      <td>4477</td>\n",
              "      <td>4478</td>\n",
              "      <td>4468</td>\n",
              "      <td>4386</td>\n",
              "      <td>4321</td>\n",
              "      <td>4350</td>\n",
              "      <td>4239</td>\n",
              "      <td>4168</td>\n",
              "      <td>4212</td>\n",
              "      <td>4221</td>\n",
              "      <td>3886</td>\n",
              "      <td>4071</td>\n",
              "      <td>4030</td>\n",
              "      <td>4304</td>\n",
              "      <td>4659</td>\n",
              "      <td>4724</td>\n",
              "      <td>4622</td>\n",
              "      <td>5386</td>\n",
              "      <td>5984</td>\n",
              "      <td>5936</td>\n",
              "      <td>4166</td>\n",
              "      <td>...</td>\n",
              "      <td>1399</td>\n",
              "      <td>1382</td>\n",
              "      <td>1380</td>\n",
              "      <td>1370</td>\n",
              "      <td>1343</td>\n",
              "      <td>1336</td>\n",
              "      <td>1330</td>\n",
              "      <td>1319</td>\n",
              "      <td>1307</td>\n",
              "      <td>1298</td>\n",
              "      <td>1314</td>\n",
              "      <td>1316</td>\n",
              "      <td>1302</td>\n",
              "      <td>1286</td>\n",
              "      <td>1274</td>\n",
              "      <td>1268</td>\n",
              "      <td>1250</td>\n",
              "      <td>1244</td>\n",
              "      <td>1233</td>\n",
              "      <td>1229</td>\n",
              "      <td>1225</td>\n",
              "      <td>1207</td>\n",
              "      <td>1208</td>\n",
              "      <td>1189</td>\n",
              "      <td>1153</td>\n",
              "      <td>1169</td>\n",
              "      <td>1142</td>\n",
              "      <td>1121</td>\n",
              "      <td>1127</td>\n",
              "      <td>1130</td>\n",
              "      <td>1101</td>\n",
              "      <td>1101</td>\n",
              "      <td>1102</td>\n",
              "      <td>1082</td>\n",
              "      <td>1069</td>\n",
              "      <td>1075</td>\n",
              "      <td>1055</td>\n",
              "      <td>1024</td>\n",
              "      <td>1009</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18661</th>\n",
              "      <td>3152</td>\n",
              "      <td>3850</td>\n",
              "      <td>4016</td>\n",
              "      <td>3872</td>\n",
              "      <td>4141</td>\n",
              "      <td>4263</td>\n",
              "      <td>4322</td>\n",
              "      <td>4119</td>\n",
              "      <td>4079</td>\n",
              "      <td>3787</td>\n",
              "      <td>3620</td>\n",
              "      <td>3590</td>\n",
              "      <td>2721</td>\n",
              "      <td>3611</td>\n",
              "      <td>3620</td>\n",
              "      <td>3621</td>\n",
              "      <td>2734</td>\n",
              "      <td>3261</td>\n",
              "      <td>3091</td>\n",
              "      <td>2923</td>\n",
              "      <td>2852</td>\n",
              "      <td>2762</td>\n",
              "      <td>2674</td>\n",
              "      <td>2580</td>\n",
              "      <td>2532</td>\n",
              "      <td>2436</td>\n",
              "      <td>2344</td>\n",
              "      <td>2293</td>\n",
              "      <td>2248</td>\n",
              "      <td>2166</td>\n",
              "      <td>2377</td>\n",
              "      <td>2164</td>\n",
              "      <td>2421</td>\n",
              "      <td>2959</td>\n",
              "      <td>2791</td>\n",
              "      <td>4129</td>\n",
              "      <td>5590</td>\n",
              "      <td>6780</td>\n",
              "      <td>7034</td>\n",
              "      <td>4906</td>\n",
              "      <td>...</td>\n",
              "      <td>1085</td>\n",
              "      <td>1087</td>\n",
              "      <td>1084</td>\n",
              "      <td>1081</td>\n",
              "      <td>1079</td>\n",
              "      <td>1079</td>\n",
              "      <td>1069</td>\n",
              "      <td>1079</td>\n",
              "      <td>1078</td>\n",
              "      <td>1078</td>\n",
              "      <td>1077</td>\n",
              "      <td>1085</td>\n",
              "      <td>1074</td>\n",
              "      <td>1068</td>\n",
              "      <td>1066</td>\n",
              "      <td>1059</td>\n",
              "      <td>1053</td>\n",
              "      <td>1049</td>\n",
              "      <td>1050</td>\n",
              "      <td>1049</td>\n",
              "      <td>1039</td>\n",
              "      <td>1035</td>\n",
              "      <td>1038</td>\n",
              "      <td>1033</td>\n",
              "      <td>1024</td>\n",
              "      <td>1020</td>\n",
              "      <td>1023</td>\n",
              "      <td>1023</td>\n",
              "      <td>1020</td>\n",
              "      <td>1020</td>\n",
              "      <td>1015</td>\n",
              "      <td>1013</td>\n",
              "      <td>1012</td>\n",
              "      <td>1006</td>\n",
              "      <td>1010</td>\n",
              "      <td>1007</td>\n",
              "      <td>1012</td>\n",
              "      <td>1000</td>\n",
              "      <td>1009</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10967</th>\n",
              "      <td>2763</td>\n",
              "      <td>4386</td>\n",
              "      <td>4324</td>\n",
              "      <td>4422</td>\n",
              "      <td>4838</td>\n",
              "      <td>5193</td>\n",
              "      <td>5338</td>\n",
              "      <td>5139</td>\n",
              "      <td>5120</td>\n",
              "      <td>4938</td>\n",
              "      <td>4880</td>\n",
              "      <td>4949</td>\n",
              "      <td>4869</td>\n",
              "      <td>5088</td>\n",
              "      <td>5263</td>\n",
              "      <td>5280</td>\n",
              "      <td>5201</td>\n",
              "      <td>5094</td>\n",
              "      <td>4999</td>\n",
              "      <td>4952</td>\n",
              "      <td>4862</td>\n",
              "      <td>4925</td>\n",
              "      <td>4854</td>\n",
              "      <td>4794</td>\n",
              "      <td>4791</td>\n",
              "      <td>4727</td>\n",
              "      <td>4604</td>\n",
              "      <td>4712</td>\n",
              "      <td>4694</td>\n",
              "      <td>4403</td>\n",
              "      <td>4612</td>\n",
              "      <td>4309</td>\n",
              "      <td>4595</td>\n",
              "      <td>5084</td>\n",
              "      <td>5100</td>\n",
              "      <td>5176</td>\n",
              "      <td>5956</td>\n",
              "      <td>6589</td>\n",
              "      <td>6432</td>\n",
              "      <td>4538</td>\n",
              "      <td>...</td>\n",
              "      <td>1412</td>\n",
              "      <td>1415</td>\n",
              "      <td>1420</td>\n",
              "      <td>1409</td>\n",
              "      <td>1380</td>\n",
              "      <td>1364</td>\n",
              "      <td>1366</td>\n",
              "      <td>1360</td>\n",
              "      <td>1346</td>\n",
              "      <td>1326</td>\n",
              "      <td>1353</td>\n",
              "      <td>1362</td>\n",
              "      <td>1347</td>\n",
              "      <td>1316</td>\n",
              "      <td>1291</td>\n",
              "      <td>1281</td>\n",
              "      <td>1274</td>\n",
              "      <td>1267</td>\n",
              "      <td>1248</td>\n",
              "      <td>1244</td>\n",
              "      <td>1245</td>\n",
              "      <td>1223</td>\n",
              "      <td>1223</td>\n",
              "      <td>1195</td>\n",
              "      <td>1177</td>\n",
              "      <td>1175</td>\n",
              "      <td>1148</td>\n",
              "      <td>1128</td>\n",
              "      <td>1128</td>\n",
              "      <td>1141</td>\n",
              "      <td>1105</td>\n",
              "      <td>1096</td>\n",
              "      <td>1103</td>\n",
              "      <td>1086</td>\n",
              "      <td>1072</td>\n",
              "      <td>1076</td>\n",
              "      <td>1046</td>\n",
              "      <td>1024</td>\n",
              "      <td>1014</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>6 rows × 201 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       band-1  band-2  band-3  band-4  ...  band-198  band-199  band-200  class\n",
              "2596     2737    4521    4700    4511  ...      1045      1029      1009      0\n",
              "18250    3320    3727    4011    4034  ...      1012      1000      1014     14\n",
              "12135    3196    4119    4032    3823  ...      1011      1000      1013      0\n",
              "20725    2730    4355    4552    4463  ...      1055      1024      1009      0\n",
              "18661    3152    3850    4016    3872  ...      1012      1000      1009     14\n",
              "10967    2763    4386    4324    4422  ...      1046      1024      1014      2\n",
              "\n",
              "[6 rows x 201 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pL_D5AwlspI6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0a9e6db3-12bd-44de-815f-8ce1046cd8d6"
      },
      "source": [
        "print(f'Shape of the data: {df.shape}')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Shape of the data: (21025, 201)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xKzelZgYVl2b"
      },
      "source": [
        "### Band Information visualization:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p4kaR6lWsp0u",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "40eb5079-0ecb-42b6-ac38-4887534f2f6b"
      },
      "source": [
        "print(f\"Unique Class Labels: {df.loc[:, 'class'].unique()}\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Unique Class Labels: [ 3  0 15 11 12  5 10 14 16  2  4  8  6  9  1  7 13]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BA3gi1oustvO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "063afe67-df78-40c7-eb8f-09a8ddc5463b"
      },
      "source": [
        "df.loc[:, 'class'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0     10776\n",
              "11     2455\n",
              "2      1428\n",
              "14     1265\n",
              "10      972\n",
              "3       830\n",
              "6       730\n",
              "12      593\n",
              "5       483\n",
              "8       478\n",
              "15      386\n",
              "4       237\n",
              "13      205\n",
              "16       93\n",
              "1        46\n",
              "7        28\n",
              "9        20\n",
              "Name: class, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E3P8FoOEsyKB",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "outputId": "a6f1f9c2-9617-4f82-bf30-e28d538f8790"
      },
      "source": [
        "\n",
        "plt.figure(figsize=(14, 8))\n",
        "\n",
        "ax = sns.countplot(x='class', data=df[['class']])\n",
        "\n",
        "for p in ax.patches:\n",
        "        ax.annotate('{:.1f}%'.format(100*p.get_height()/df.shape[0]), (p.get_x()+0.1, p.get_height()+5))\n",
        "#ax.yaxis.set_major_locator(ticker.LinearLocator(11))\n",
        "\n",
        "plt.ylabel('Class count with percentage', fontsize=14)\n",
        "\n",
        "plt.xlabel('class', fontsize=14)\n",
        "\n",
        "plt.title('Bar Plot', fontsize=16)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tlsWz-3LtUxE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 58
        },
        "outputId": "9d7cfaea-21f5-4a4c-f775-026a5826fd9c"
      },
      "source": [
        "# Visualizing the pixel\n",
        "plt.matshow(df.iloc[1, :-1].values.reshape(1,200), cmap='jet');"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 1152x144 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i6EIegz2xe3K"
      },
      "source": [
        "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
        "def plot_pixel(pixel, n):\n",
        "    ax = plt.gca()\n",
        "    im = ax.imshow(pixel.reshape(10, 20), cmap = 'jet')\n",
        "    plt.title(f'pixel - {n}')\n",
        "    plt.axis('off')\n",
        "    divider = make_axes_locatable(ax)\n",
        "    cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n",
        "    plt.colorbar(im, cax=cax)\n",
        "    plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M6pWNE6Pxi-N",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 263
        },
        "outputId": "0df3b8b7-cac1-40b8-d938-2bbd416be049"
      },
      "source": [
        "plt.figure(figsize=(8, 4))\n",
        "\n",
        "rand_n = np.random.randint(df.shape[0])\n",
        "\n",
        "plot_pixel(df.iloc[rand_n, :-1].values, rand_n)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 576x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ExqZDhe1xpTR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 427
        },
        "outputId": "d221c1da-37df-4162-9f0b-e0ae067a3e05"
      },
      "source": [
        "plt.figure(figsize=(16, 6))\n",
        "n = int(input('Enter the band Number(1-200) :'))\n",
        "sns.boxplot( x=df[\"class\"], y=df[\"band-1\"], width=0.3);\n",
        "plt.title('Box Plot', fontsize= 16)\n",
        "plt.xlabel('Class', fontsize= 14)\n",
        "plt.ylabel(f'Band-{n}', fontsize= 14)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Enter the band Number(1-200) :25\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vc-86JEGxxwp",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7457b95b-314d-4289-9f74-12754494397d"
      },
      "source": [
        "print(f\"Details of Band - {n}: \\n\\n{df['band-'+str(n)].describe()}\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Details of Band - 25: \n",
            "\n",
            "count    21025.000000\n",
            "mean      3651.536837\n",
            "std        948.550739\n",
            "min       2398.000000\n",
            "25%       2741.000000\n",
            "50%       3605.000000\n",
            "75%       4457.000000\n",
            "max       7081.000000\n",
            "Name: band-25, dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ex4JRvOrx1DR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 498
        },
        "outputId": "888f2ca6-4b5f-4a94-dd1c-5838e0d6aa7c"
      },
      "source": [
        "\n",
        "plt.figure(figsize=(16, 6))\n",
        "sns.distplot(df['band-'+str(n)], color='mediumSpringGreen', bins=100, hist_kws={'alpha': 0.4});\n",
        "plt.xlabel('Band - '+str(n), fontsize=14)\n",
        "plt.title('Disrtibution Plot of Band - '+str(n), fontsize=16)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/seaborn/distributions.py:2551: FutureWarning:\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PtFEhgjkDYO0"
      },
      "source": [
        "### Implemetation of Dimensionality reduction using truncated SVD"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "r4Nd6fQkx3jf"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "# !pip install seaborn\n",
        "import seaborn as sns\n",
        "from sklearn.svm import SVC\n",
        "from sklearn.decomposition import KernelPCA\n",
        "from sklearn.model_selection import train_test_split"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nYAHil6FEeVY",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 438
        },
        "outputId": "92fc962a-51f4-416c-b949-5f3e9a39d66e"
      },
      "source": [
        "df = pd.read_csv('Dataset.csv')\n",
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>band-1</th>\n",
              "      <th>band-2</th>\n",
              "      <th>band-3</th>\n",
              "      <th>band-4</th>\n",
              "      <th>band-5</th>\n",
              "      <th>band-6</th>\n",
              "      <th>band-7</th>\n",
              "      <th>band-8</th>\n",
              "      <th>band-9</th>\n",
              "      <th>band-10</th>\n",
              "      <th>band-11</th>\n",
              "      <th>band-12</th>\n",
              "      <th>band-13</th>\n",
              "      <th>band-14</th>\n",
              "      <th>band-15</th>\n",
              "      <th>band-16</th>\n",
              "      <th>band-17</th>\n",
              "      <th>band-18</th>\n",
              "      <th>band-19</th>\n",
              "      <th>band-20</th>\n",
              "      <th>band-21</th>\n",
              "      <th>band-22</th>\n",
              "      <th>band-23</th>\n",
              "      <th>band-24</th>\n",
              "      <th>band-25</th>\n",
              "      <th>band-26</th>\n",
              "      <th>band-27</th>\n",
              "      <th>band-28</th>\n",
              "      <th>band-29</th>\n",
              "      <th>band-30</th>\n",
              "      <th>band-31</th>\n",
              "      <th>band-32</th>\n",
              "      <th>band-33</th>\n",
              "      <th>band-34</th>\n",
              "      <th>band-35</th>\n",
              "      <th>band-36</th>\n",
              "      <th>band-37</th>\n",
              "      <th>band-38</th>\n",
              "      <th>band-39</th>\n",
              "      <th>band-40</th>\n",
              "      <th>...</th>\n",
              "      <th>band-162</th>\n",
              "      <th>band-163</th>\n",
              "      <th>band-164</th>\n",
              "      <th>band-165</th>\n",
              "      <th>band-166</th>\n",
              "      <th>band-167</th>\n",
              "      <th>band-168</th>\n",
              "      <th>band-169</th>\n",
              "      <th>band-170</th>\n",
              "      <th>band-171</th>\n",
              "      <th>band-172</th>\n",
              "      <th>band-173</th>\n",
              "      <th>band-174</th>\n",
              "      <th>band-175</th>\n",
              "      <th>band-176</th>\n",
              "      <th>band-177</th>\n",
              "      <th>band-178</th>\n",
              "      <th>band-179</th>\n",
              "      <th>band-180</th>\n",
              "      <th>band-181</th>\n",
              "      <th>band-182</th>\n",
              "      <th>band-183</th>\n",
              "      <th>band-184</th>\n",
              "      <th>band-185</th>\n",
              "      <th>band-186</th>\n",
              "      <th>band-187</th>\n",
              "      <th>band-188</th>\n",
              "      <th>band-189</th>\n",
              "      <th>band-190</th>\n",
              "      <th>band-191</th>\n",
              "      <th>band-192</th>\n",
              "      <th>band-193</th>\n",
              "      <th>band-194</th>\n",
              "      <th>band-195</th>\n",
              "      <th>band-196</th>\n",
              "      <th>band-197</th>\n",
              "      <th>band-198</th>\n",
              "      <th>band-199</th>\n",
              "      <th>band-200</th>\n",
              "      <th>class</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3172</td>\n",
              "      <td>4142</td>\n",
              "      <td>4506</td>\n",
              "      <td>4279</td>\n",
              "      <td>4782</td>\n",
              "      <td>5048</td>\n",
              "      <td>5213</td>\n",
              "      <td>5106</td>\n",
              "      <td>5053</td>\n",
              "      <td>4750</td>\n",
              "      <td>4816</td>\n",
              "      <td>4769</td>\n",
              "      <td>4610</td>\n",
              "      <td>4805</td>\n",
              "      <td>4828</td>\n",
              "      <td>4861</td>\n",
              "      <td>4767</td>\n",
              "      <td>4624</td>\n",
              "      <td>4549</td>\n",
              "      <td>4463</td>\n",
              "      <td>4462</td>\n",
              "      <td>4446</td>\n",
              "      <td>4445</td>\n",
              "      <td>4336</td>\n",
              "      <td>4381</td>\n",
              "      <td>4319</td>\n",
              "      <td>4207</td>\n",
              "      <td>4305</td>\n",
              "      <td>4311</td>\n",
              "      <td>3991</td>\n",
              "      <td>4168</td>\n",
              "      <td>3942</td>\n",
              "      <td>4061</td>\n",
              "      <td>4362</td>\n",
              "      <td>4318</td>\n",
              "      <td>4252</td>\n",
              "      <td>4869</td>\n",
              "      <td>5284</td>\n",
              "      <td>5055</td>\n",
              "      <td>3591</td>\n",
              "      <td>...</td>\n",
              "      <td>1396</td>\n",
              "      <td>1381</td>\n",
              "      <td>1396</td>\n",
              "      <td>1381</td>\n",
              "      <td>1353</td>\n",
              "      <td>1346</td>\n",
              "      <td>1341</td>\n",
              "      <td>1332</td>\n",
              "      <td>1324</td>\n",
              "      <td>1310</td>\n",
              "      <td>1318</td>\n",
              "      <td>1330</td>\n",
              "      <td>1310</td>\n",
              "      <td>1292</td>\n",
              "      <td>1280</td>\n",
              "      <td>1275</td>\n",
              "      <td>1266</td>\n",
              "      <td>1264</td>\n",
              "      <td>1233</td>\n",
              "      <td>1241</td>\n",
              "      <td>1232</td>\n",
              "      <td>1215</td>\n",
              "      <td>1215</td>\n",
              "      <td>1187</td>\n",
              "      <td>1168</td>\n",
              "      <td>1171</td>\n",
              "      <td>1150</td>\n",
              "      <td>1134</td>\n",
              "      <td>1123</td>\n",
              "      <td>1135</td>\n",
              "      <td>1094</td>\n",
              "      <td>1090</td>\n",
              "      <td>1112</td>\n",
              "      <td>1090</td>\n",
              "      <td>1062</td>\n",
              "      <td>1069</td>\n",
              "      <td>1057</td>\n",
              "      <td>1020</td>\n",
              "      <td>1020</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2580</td>\n",
              "      <td>4266</td>\n",
              "      <td>4502</td>\n",
              "      <td>4426</td>\n",
              "      <td>4853</td>\n",
              "      <td>5249</td>\n",
              "      <td>5352</td>\n",
              "      <td>5353</td>\n",
              "      <td>5347</td>\n",
              "      <td>5065</td>\n",
              "      <td>5141</td>\n",
              "      <td>5100</td>\n",
              "      <td>4994</td>\n",
              "      <td>5172</td>\n",
              "      <td>5290</td>\n",
              "      <td>5289</td>\n",
              "      <td>5217</td>\n",
              "      <td>5053</td>\n",
              "      <td>5033</td>\n",
              "      <td>4939</td>\n",
              "      <td>4931</td>\n",
              "      <td>4941</td>\n",
              "      <td>4902</td>\n",
              "      <td>4824</td>\n",
              "      <td>4859</td>\n",
              "      <td>4805</td>\n",
              "      <td>4698</td>\n",
              "      <td>4794</td>\n",
              "      <td>4806</td>\n",
              "      <td>4452</td>\n",
              "      <td>4628</td>\n",
              "      <td>4433</td>\n",
              "      <td>4643</td>\n",
              "      <td>4967</td>\n",
              "      <td>4853</td>\n",
              "      <td>4760</td>\n",
              "      <td>5449</td>\n",
              "      <td>5768</td>\n",
              "      <td>5684</td>\n",
              "      <td>3987</td>\n",
              "      <td>...</td>\n",
              "      <td>1421</td>\n",
              "      <td>1415</td>\n",
              "      <td>1428</td>\n",
              "      <td>1415</td>\n",
              "      <td>1379</td>\n",
              "      <td>1370</td>\n",
              "      <td>1360</td>\n",
              "      <td>1353</td>\n",
              "      <td>1352</td>\n",
              "      <td>1336</td>\n",
              "      <td>1346</td>\n",
              "      <td>1351</td>\n",
              "      <td>1330</td>\n",
              "      <td>1315</td>\n",
              "      <td>1305</td>\n",
              "      <td>1292</td>\n",
              "      <td>1282</td>\n",
              "      <td>1286</td>\n",
              "      <td>1259</td>\n",
              "      <td>1259</td>\n",
              "      <td>1250</td>\n",
              "      <td>1229</td>\n",
              "      <td>1232</td>\n",
              "      <td>1195</td>\n",
              "      <td>1177</td>\n",
              "      <td>1184</td>\n",
              "      <td>1153</td>\n",
              "      <td>1137</td>\n",
              "      <td>1138</td>\n",
              "      <td>1137</td>\n",
              "      <td>1108</td>\n",
              "      <td>1104</td>\n",
              "      <td>1117</td>\n",
              "      <td>1091</td>\n",
              "      <td>1079</td>\n",
              "      <td>1085</td>\n",
              "      <td>1064</td>\n",
              "      <td>1029</td>\n",
              "      <td>1020</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3687</td>\n",
              "      <td>4266</td>\n",
              "      <td>4421</td>\n",
              "      <td>4498</td>\n",
              "      <td>5019</td>\n",
              "      <td>5293</td>\n",
              "      <td>5438</td>\n",
              "      <td>5427</td>\n",
              "      <td>5383</td>\n",
              "      <td>5132</td>\n",
              "      <td>5227</td>\n",
              "      <td>5172</td>\n",
              "      <td>5097</td>\n",
              "      <td>5313</td>\n",
              "      <td>5411</td>\n",
              "      <td>5412</td>\n",
              "      <td>5341</td>\n",
              "      <td>5191</td>\n",
              "      <td>5140</td>\n",
              "      <td>5069</td>\n",
              "      <td>5110</td>\n",
              "      <td>5119</td>\n",
              "      <td>5046</td>\n",
              "      <td>4981</td>\n",
              "      <td>5023</td>\n",
              "      <td>4987</td>\n",
              "      <td>4862</td>\n",
              "      <td>4965</td>\n",
              "      <td>4992</td>\n",
              "      <td>4595</td>\n",
              "      <td>4756</td>\n",
              "      <td>4529</td>\n",
              "      <td>4801</td>\n",
              "      <td>5077</td>\n",
              "      <td>4983</td>\n",
              "      <td>4868</td>\n",
              "      <td>5515</td>\n",
              "      <td>5972</td>\n",
              "      <td>5913</td>\n",
              "      <td>4027</td>\n",
              "      <td>...</td>\n",
              "      <td>1446</td>\n",
              "      <td>1440</td>\n",
              "      <td>1443</td>\n",
              "      <td>1425</td>\n",
              "      <td>1390</td>\n",
              "      <td>1379</td>\n",
              "      <td>1376</td>\n",
              "      <td>1363</td>\n",
              "      <td>1355</td>\n",
              "      <td>1347</td>\n",
              "      <td>1361</td>\n",
              "      <td>1356</td>\n",
              "      <td>1341</td>\n",
              "      <td>1330</td>\n",
              "      <td>1321</td>\n",
              "      <td>1304</td>\n",
              "      <td>1290</td>\n",
              "      <td>1289</td>\n",
              "      <td>1263</td>\n",
              "      <td>1269</td>\n",
              "      <td>1261</td>\n",
              "      <td>1245</td>\n",
              "      <td>1241</td>\n",
              "      <td>1214</td>\n",
              "      <td>1185</td>\n",
              "      <td>1188</td>\n",
              "      <td>1156</td>\n",
              "      <td>1147</td>\n",
              "      <td>1149</td>\n",
              "      <td>1144</td>\n",
              "      <td>1111</td>\n",
              "      <td>1114</td>\n",
              "      <td>1114</td>\n",
              "      <td>1100</td>\n",
              "      <td>1065</td>\n",
              "      <td>1092</td>\n",
              "      <td>1061</td>\n",
              "      <td>1030</td>\n",
              "      <td>1016</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2749</td>\n",
              "      <td>4258</td>\n",
              "      <td>4603</td>\n",
              "      <td>4493</td>\n",
              "      <td>4958</td>\n",
              "      <td>5234</td>\n",
              "      <td>5417</td>\n",
              "      <td>5355</td>\n",
              "      <td>5349</td>\n",
              "      <td>5096</td>\n",
              "      <td>5147</td>\n",
              "      <td>5078</td>\n",
              "      <td>5040</td>\n",
              "      <td>5237</td>\n",
              "      <td>5321</td>\n",
              "      <td>5344</td>\n",
              "      <td>5255</td>\n",
              "      <td>5121</td>\n",
              "      <td>5035</td>\n",
              "      <td>4956</td>\n",
              "      <td>4994</td>\n",
              "      <td>4980</td>\n",
              "      <td>4905</td>\n",
              "      <td>4857</td>\n",
              "      <td>4900</td>\n",
              "      <td>4831</td>\n",
              "      <td>4720</td>\n",
              "      <td>4848</td>\n",
              "      <td>4847</td>\n",
              "      <td>4484</td>\n",
              "      <td>4613</td>\n",
              "      <td>4402</td>\n",
              "      <td>4674</td>\n",
              "      <td>4966</td>\n",
              "      <td>4848</td>\n",
              "      <td>4776</td>\n",
              "      <td>5473</td>\n",
              "      <td>5894</td>\n",
              "      <td>5789</td>\n",
              "      <td>4086</td>\n",
              "      <td>...</td>\n",
              "      <td>1432</td>\n",
              "      <td>1427</td>\n",
              "      <td>1426</td>\n",
              "      <td>1416</td>\n",
              "      <td>1386</td>\n",
              "      <td>1374</td>\n",
              "      <td>1375</td>\n",
              "      <td>1359</td>\n",
              "      <td>1343</td>\n",
              "      <td>1343</td>\n",
              "      <td>1354</td>\n",
              "      <td>1351</td>\n",
              "      <td>1333</td>\n",
              "      <td>1329</td>\n",
              "      <td>1313</td>\n",
              "      <td>1296</td>\n",
              "      <td>1280</td>\n",
              "      <td>1281</td>\n",
              "      <td>1251</td>\n",
              "      <td>1255</td>\n",
              "      <td>1253</td>\n",
              "      <td>1238</td>\n",
              "      <td>1223</td>\n",
              "      <td>1207</td>\n",
              "      <td>1188</td>\n",
              "      <td>1188</td>\n",
              "      <td>1154</td>\n",
              "      <td>1143</td>\n",
              "      <td>1144</td>\n",
              "      <td>1146</td>\n",
              "      <td>1122</td>\n",
              "      <td>1108</td>\n",
              "      <td>1109</td>\n",
              "      <td>1109</td>\n",
              "      <td>1071</td>\n",
              "      <td>1088</td>\n",
              "      <td>1060</td>\n",
              "      <td>1030</td>\n",
              "      <td>1006</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2746</td>\n",
              "      <td>4018</td>\n",
              "      <td>4675</td>\n",
              "      <td>4417</td>\n",
              "      <td>4886</td>\n",
              "      <td>5117</td>\n",
              "      <td>5215</td>\n",
              "      <td>5096</td>\n",
              "      <td>5098</td>\n",
              "      <td>4834</td>\n",
              "      <td>4853</td>\n",
              "      <td>4857</td>\n",
              "      <td>4734</td>\n",
              "      <td>4879</td>\n",
              "      <td>4976</td>\n",
              "      <td>4958</td>\n",
              "      <td>4885</td>\n",
              "      <td>4754</td>\n",
              "      <td>4647</td>\n",
              "      <td>4532</td>\n",
              "      <td>4586</td>\n",
              "      <td>4591</td>\n",
              "      <td>4492</td>\n",
              "      <td>4453</td>\n",
              "      <td>4497</td>\n",
              "      <td>4398</td>\n",
              "      <td>4297</td>\n",
              "      <td>4408</td>\n",
              "      <td>4401</td>\n",
              "      <td>4102</td>\n",
              "      <td>4227</td>\n",
              "      <td>4075</td>\n",
              "      <td>4264</td>\n",
              "      <td>4529</td>\n",
              "      <td>4490</td>\n",
              "      <td>4438</td>\n",
              "      <td>5001</td>\n",
              "      <td>5378</td>\n",
              "      <td>5321</td>\n",
              "      <td>3779</td>\n",
              "      <td>...</td>\n",
              "      <td>1401</td>\n",
              "      <td>1397</td>\n",
              "      <td>1395</td>\n",
              "      <td>1390</td>\n",
              "      <td>1368</td>\n",
              "      <td>1349</td>\n",
              "      <td>1354</td>\n",
              "      <td>1340</td>\n",
              "      <td>1330</td>\n",
              "      <td>1324</td>\n",
              "      <td>1336</td>\n",
              "      <td>1332</td>\n",
              "      <td>1320</td>\n",
              "      <td>1307</td>\n",
              "      <td>1287</td>\n",
              "      <td>1283</td>\n",
              "      <td>1267</td>\n",
              "      <td>1265</td>\n",
              "      <td>1239</td>\n",
              "      <td>1240</td>\n",
              "      <td>1239</td>\n",
              "      <td>1229</td>\n",
              "      <td>1212</td>\n",
              "      <td>1202</td>\n",
              "      <td>1178</td>\n",
              "      <td>1178</td>\n",
              "      <td>1143</td>\n",
              "      <td>1135</td>\n",
              "      <td>1138</td>\n",
              "      <td>1135</td>\n",
              "      <td>1110</td>\n",
              "      <td>1107</td>\n",
              "      <td>1112</td>\n",
              "      <td>1094</td>\n",
              "      <td>1072</td>\n",
              "      <td>1087</td>\n",
              "      <td>1052</td>\n",
              "      <td>1034</td>\n",
              "      <td>1019</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21020</th>\n",
              "      <td>2561</td>\n",
              "      <td>3987</td>\n",
              "      <td>4011</td>\n",
              "      <td>4023</td>\n",
              "      <td>4201</td>\n",
              "      <td>4377</td>\n",
              "      <td>4418</td>\n",
              "      <td>4248</td>\n",
              "      <td>4180</td>\n",
              "      <td>3838</td>\n",
              "      <td>3762</td>\n",
              "      <td>3696</td>\n",
              "      <td>3594</td>\n",
              "      <td>3750</td>\n",
              "      <td>3806</td>\n",
              "      <td>3764</td>\n",
              "      <td>3655</td>\n",
              "      <td>2611</td>\n",
              "      <td>3199</td>\n",
              "      <td>3036</td>\n",
              "      <td>2978</td>\n",
              "      <td>2837</td>\n",
              "      <td>2758</td>\n",
              "      <td>2650</td>\n",
              "      <td>2617</td>\n",
              "      <td>2494</td>\n",
              "      <td>2397</td>\n",
              "      <td>2366</td>\n",
              "      <td>2313</td>\n",
              "      <td>2198</td>\n",
              "      <td>2464</td>\n",
              "      <td>2261</td>\n",
              "      <td>2490</td>\n",
              "      <td>3124</td>\n",
              "      <td>3643</td>\n",
              "      <td>4349</td>\n",
              "      <td>5748</td>\n",
              "      <td>6973</td>\n",
              "      <td>7199</td>\n",
              "      <td>5067</td>\n",
              "      <td>...</td>\n",
              "      <td>1082</td>\n",
              "      <td>1079</td>\n",
              "      <td>1077</td>\n",
              "      <td>1086</td>\n",
              "      <td>1071</td>\n",
              "      <td>1084</td>\n",
              "      <td>1079</td>\n",
              "      <td>1076</td>\n",
              "      <td>1082</td>\n",
              "      <td>1077</td>\n",
              "      <td>1082</td>\n",
              "      <td>1078</td>\n",
              "      <td>1077</td>\n",
              "      <td>1068</td>\n",
              "      <td>1070</td>\n",
              "      <td>1053</td>\n",
              "      <td>1063</td>\n",
              "      <td>1055</td>\n",
              "      <td>1052</td>\n",
              "      <td>1047</td>\n",
              "      <td>1042</td>\n",
              "      <td>1043</td>\n",
              "      <td>1031</td>\n",
              "      <td>1025</td>\n",
              "      <td>1034</td>\n",
              "      <td>1029</td>\n",
              "      <td>1026</td>\n",
              "      <td>1025</td>\n",
              "      <td>1018</td>\n",
              "      <td>1021</td>\n",
              "      <td>1013</td>\n",
              "      <td>1012</td>\n",
              "      <td>1018</td>\n",
              "      <td>1015</td>\n",
              "      <td>1011</td>\n",
              "      <td>1001</td>\n",
              "      <td>1000</td>\n",
              "      <td>1009</td>\n",
              "      <td>1008</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21021</th>\n",
              "      <td>2726</td>\n",
              "      <td>4104</td>\n",
              "      <td>4024</td>\n",
              "      <td>3880</td>\n",
              "      <td>4210</td>\n",
              "      <td>4377</td>\n",
              "      <td>4413</td>\n",
              "      <td>4174</td>\n",
              "      <td>4229</td>\n",
              "      <td>3900</td>\n",
              "      <td>3786</td>\n",
              "      <td>3696</td>\n",
              "      <td>3623</td>\n",
              "      <td>3726</td>\n",
              "      <td>3758</td>\n",
              "      <td>3725</td>\n",
              "      <td>3614</td>\n",
              "      <td>2584</td>\n",
              "      <td>3174</td>\n",
              "      <td>3042</td>\n",
              "      <td>2958</td>\n",
              "      <td>2837</td>\n",
              "      <td>2769</td>\n",
              "      <td>2626</td>\n",
              "      <td>2617</td>\n",
              "      <td>2484</td>\n",
              "      <td>2387</td>\n",
              "      <td>2362</td>\n",
              "      <td>2322</td>\n",
              "      <td>2199</td>\n",
              "      <td>2463</td>\n",
              "      <td>2188</td>\n",
              "      <td>2444</td>\n",
              "      <td>3077</td>\n",
              "      <td>2808</td>\n",
              "      <td>4239</td>\n",
              "      <td>5706</td>\n",
              "      <td>6965</td>\n",
              "      <td>7227</td>\n",
              "      <td>5108</td>\n",
              "      <td>...</td>\n",
              "      <td>1086</td>\n",
              "      <td>1076</td>\n",
              "      <td>1086</td>\n",
              "      <td>1081</td>\n",
              "      <td>1069</td>\n",
              "      <td>1086</td>\n",
              "      <td>1078</td>\n",
              "      <td>1081</td>\n",
              "      <td>1078</td>\n",
              "      <td>1075</td>\n",
              "      <td>1084</td>\n",
              "      <td>1087</td>\n",
              "      <td>1082</td>\n",
              "      <td>1071</td>\n",
              "      <td>1064</td>\n",
              "      <td>1059</td>\n",
              "      <td>1063</td>\n",
              "      <td>1051</td>\n",
              "      <td>1049</td>\n",
              "      <td>1042</td>\n",
              "      <td>1042</td>\n",
              "      <td>1043</td>\n",
              "      <td>1031</td>\n",
              "      <td>1029</td>\n",
              "      <td>1029</td>\n",
              "      <td>1026</td>\n",
              "      <td>1021</td>\n",
              "      <td>1026</td>\n",
              "      <td>1021</td>\n",
              "      <td>1023</td>\n",
              "      <td>1012</td>\n",
              "      <td>1014</td>\n",
              "      <td>1012</td>\n",
              "      <td>1024</td>\n",
              "      <td>998</td>\n",
              "      <td>1010</td>\n",
              "      <td>1006</td>\n",
              "      <td>1000</td>\n",
              "      <td>1000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21022</th>\n",
              "      <td>3153</td>\n",
              "      <td>3864</td>\n",
              "      <td>4282</td>\n",
              "      <td>3889</td>\n",
              "      <td>4310</td>\n",
              "      <td>4372</td>\n",
              "      <td>4375</td>\n",
              "      <td>4208</td>\n",
              "      <td>4096</td>\n",
              "      <td>3878</td>\n",
              "      <td>3890</td>\n",
              "      <td>3683</td>\n",
              "      <td>3594</td>\n",
              "      <td>3714</td>\n",
              "      <td>3724</td>\n",
              "      <td>3700</td>\n",
              "      <td>2809</td>\n",
              "      <td>2564</td>\n",
              "      <td>3177</td>\n",
              "      <td>3031</td>\n",
              "      <td>2925</td>\n",
              "      <td>2837</td>\n",
              "      <td>2719</td>\n",
              "      <td>2605</td>\n",
              "      <td>2603</td>\n",
              "      <td>2476</td>\n",
              "      <td>2373</td>\n",
              "      <td>2335</td>\n",
              "      <td>2308</td>\n",
              "      <td>2198</td>\n",
              "      <td>2449</td>\n",
              "      <td>2164</td>\n",
              "      <td>2443</td>\n",
              "      <td>3048</td>\n",
              "      <td>3585</td>\n",
              "      <td>4264</td>\n",
              "      <td>5689</td>\n",
              "      <td>6839</td>\n",
              "      <td>7027</td>\n",
              "      <td>5013</td>\n",
              "      <td>...</td>\n",
              "      <td>1080</td>\n",
              "      <td>1075</td>\n",
              "      <td>1085</td>\n",
              "      <td>1075</td>\n",
              "      <td>1076</td>\n",
              "      <td>1078</td>\n",
              "      <td>1066</td>\n",
              "      <td>1075</td>\n",
              "      <td>1073</td>\n",
              "      <td>1073</td>\n",
              "      <td>1079</td>\n",
              "      <td>1085</td>\n",
              "      <td>1075</td>\n",
              "      <td>1075</td>\n",
              "      <td>1064</td>\n",
              "      <td>1059</td>\n",
              "      <td>1057</td>\n",
              "      <td>1049</td>\n",
              "      <td>1047</td>\n",
              "      <td>1044</td>\n",
              "      <td>1034</td>\n",
              "      <td>1027</td>\n",
              "      <td>1034</td>\n",
              "      <td>1035</td>\n",
              "      <td>1027</td>\n",
              "      <td>1022</td>\n",
              "      <td>1023</td>\n",
              "      <td>1029</td>\n",
              "      <td>1026</td>\n",
              "      <td>1020</td>\n",
              "      <td>1016</td>\n",
              "      <td>1015</td>\n",
              "      <td>1016</td>\n",
              "      <td>1021</td>\n",
              "      <td>1008</td>\n",
              "      <td>1019</td>\n",
              "      <td>1003</td>\n",
              "      <td>1008</td>\n",
              "      <td>1000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21023</th>\n",
              "      <td>3155</td>\n",
              "      <td>4104</td>\n",
              "      <td>4106</td>\n",
              "      <td>4027</td>\n",
              "      <td>4139</td>\n",
              "      <td>4318</td>\n",
              "      <td>4413</td>\n",
              "      <td>4174</td>\n",
              "      <td>4140</td>\n",
              "      <td>3933</td>\n",
              "      <td>3799</td>\n",
              "      <td>3627</td>\n",
              "      <td>2752</td>\n",
              "      <td>3667</td>\n",
              "      <td>3688</td>\n",
              "      <td>3628</td>\n",
              "      <td>2750</td>\n",
              "      <td>3245</td>\n",
              "      <td>3153</td>\n",
              "      <td>2967</td>\n",
              "      <td>2890</td>\n",
              "      <td>2830</td>\n",
              "      <td>2719</td>\n",
              "      <td>2583</td>\n",
              "      <td>2580</td>\n",
              "      <td>2480</td>\n",
              "      <td>2359</td>\n",
              "      <td>2339</td>\n",
              "      <td>2289</td>\n",
              "      <td>2184</td>\n",
              "      <td>2415</td>\n",
              "      <td>2236</td>\n",
              "      <td>2418</td>\n",
              "      <td>2935</td>\n",
              "      <td>2617</td>\n",
              "      <td>4017</td>\n",
              "      <td>5283</td>\n",
              "      <td>6354</td>\n",
              "      <td>6602</td>\n",
              "      <td>4703</td>\n",
              "      <td>...</td>\n",
              "      <td>1068</td>\n",
              "      <td>1075</td>\n",
              "      <td>1078</td>\n",
              "      <td>1074</td>\n",
              "      <td>1075</td>\n",
              "      <td>1074</td>\n",
              "      <td>1067</td>\n",
              "      <td>1069</td>\n",
              "      <td>1069</td>\n",
              "      <td>1071</td>\n",
              "      <td>1073</td>\n",
              "      <td>1075</td>\n",
              "      <td>1074</td>\n",
              "      <td>1065</td>\n",
              "      <td>1062</td>\n",
              "      <td>1064</td>\n",
              "      <td>1051</td>\n",
              "      <td>1050</td>\n",
              "      <td>1041</td>\n",
              "      <td>1052</td>\n",
              "      <td>1033</td>\n",
              "      <td>1042</td>\n",
              "      <td>1040</td>\n",
              "      <td>1039</td>\n",
              "      <td>1024</td>\n",
              "      <td>1024</td>\n",
              "      <td>1028</td>\n",
              "      <td>1020</td>\n",
              "      <td>1020</td>\n",
              "      <td>1015</td>\n",
              "      <td>1005</td>\n",
              "      <td>1011</td>\n",
              "      <td>1008</td>\n",
              "      <td>1012</td>\n",
              "      <td>1014</td>\n",
              "      <td>1007</td>\n",
              "      <td>1011</td>\n",
              "      <td>1005</td>\n",
              "      <td>1003</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21024</th>\n",
              "      <td>3323</td>\n",
              "      <td>3860</td>\n",
              "      <td>4197</td>\n",
              "      <td>3952</td>\n",
              "      <td>4148</td>\n",
              "      <td>4279</td>\n",
              "      <td>4375</td>\n",
              "      <td>4225</td>\n",
              "      <td>3988</td>\n",
              "      <td>3866</td>\n",
              "      <td>3811</td>\n",
              "      <td>3639</td>\n",
              "      <td>3623</td>\n",
              "      <td>3686</td>\n",
              "      <td>3722</td>\n",
              "      <td>3673</td>\n",
              "      <td>2775</td>\n",
              "      <td>3315</td>\n",
              "      <td>3180</td>\n",
              "      <td>2984</td>\n",
              "      <td>2910</td>\n",
              "      <td>2837</td>\n",
              "      <td>2719</td>\n",
              "      <td>2614</td>\n",
              "      <td>2594</td>\n",
              "      <td>2494</td>\n",
              "      <td>2370</td>\n",
              "      <td>2352</td>\n",
              "      <td>2296</td>\n",
              "      <td>2187</td>\n",
              "      <td>2430</td>\n",
              "      <td>2139</td>\n",
              "      <td>2354</td>\n",
              "      <td>2966</td>\n",
              "      <td>2725</td>\n",
              "      <td>4071</td>\n",
              "      <td>5261</td>\n",
              "      <td>6418</td>\n",
              "      <td>6571</td>\n",
              "      <td>4702</td>\n",
              "      <td>...</td>\n",
              "      <td>1068</td>\n",
              "      <td>1086</td>\n",
              "      <td>1084</td>\n",
              "      <td>1078</td>\n",
              "      <td>1085</td>\n",
              "      <td>1082</td>\n",
              "      <td>1077</td>\n",
              "      <td>1078</td>\n",
              "      <td>1073</td>\n",
              "      <td>1073</td>\n",
              "      <td>1085</td>\n",
              "      <td>1081</td>\n",
              "      <td>1078</td>\n",
              "      <td>1062</td>\n",
              "      <td>1066</td>\n",
              "      <td>1068</td>\n",
              "      <td>1052</td>\n",
              "      <td>1053</td>\n",
              "      <td>1049</td>\n",
              "      <td>1046</td>\n",
              "      <td>1044</td>\n",
              "      <td>1046</td>\n",
              "      <td>1040</td>\n",
              "      <td>1034</td>\n",
              "      <td>1023</td>\n",
              "      <td>1022</td>\n",
              "      <td>1026</td>\n",
              "      <td>1014</td>\n",
              "      <td>1014</td>\n",
              "      <td>1015</td>\n",
              "      <td>1018</td>\n",
              "      <td>1014</td>\n",
              "      <td>1007</td>\n",
              "      <td>1015</td>\n",
              "      <td>1002</td>\n",
              "      <td>1010</td>\n",
              "      <td>1007</td>\n",
              "      <td>1004</td>\n",
              "      <td>1000</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>21025 rows × 201 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       band-1  band-2  band-3  band-4  ...  band-198  band-199  band-200  class\n",
              "0        3172    4142    4506    4279  ...      1057      1020      1020      3\n",
              "1        2580    4266    4502    4426  ...      1064      1029      1020      3\n",
              "2        3687    4266    4421    4498  ...      1061      1030      1016      3\n",
              "3        2749    4258    4603    4493  ...      1060      1030      1006      3\n",
              "4        2746    4018    4675    4417  ...      1052      1034      1019      3\n",
              "...       ...     ...     ...     ...  ...       ...       ...       ...    ...\n",
              "21020    2561    3987    4011    4023  ...      1000      1009      1008      0\n",
              "21021    2726    4104    4024    3880  ...      1006      1000      1000      0\n",
              "21022    3153    3864    4282    3889  ...      1003      1008      1000      0\n",
              "21023    3155    4104    4106    4027  ...      1011      1005      1003      0\n",
              "21024    3323    3860    4197    3952  ...      1007      1004      1000      0\n",
              "\n",
              "[21025 rows x 201 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ObpjGF0CEt5-"
      },
      "source": [
        "#df_sample=df.sample(8000)\n",
        "X = df.iloc[:, :-1].values\n",
        "\n",
        "y = df.iloc[:, -1].values\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VFPYXEmoEycK",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "041d99df-8f69-4176-d911-eb9233bd3236"
      },
      "source": [
        "X.shape, y.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((21025, 200), (21025,))"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4RLQXcTALp34",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "36ff665b-4077-4cec-ed11-addec64bc0a1"
      },
      "source": [
        "#kpca = KernelPCA(n_components = 50, kernel='poly', eigen_solver='arpack')\n",
        "kpca = PCA(n_components=50, whiten=True) \n",
        "#pca = PCA(n_components=numComponents, svd_solver='arpack')\n",
        "principalComponents = kpca.fit_transform(X)\n",
        "\n",
        "principalComponents.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(21025, 50)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v_v89o8VMX87"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GJ3_ZlJ5PH5O"
      },
      "source": [
        "from sklearn.metrics import classification_report, confusion_matrix, accuracy_score"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8DAM7WxtHJKv"
      },
      "source": [
        "\n",
        "\n",
        "X_train, X_test, y_train, y_test, indices_train, indices_test  = train_test_split(principalComponents, y,  range(X.shape[0]), \n",
        "                                                                                  test_size = 0.15, random_state = 11)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mgcpBuTWHLUC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "af4225f0-261e-408e-a0da-10e2cd43bf6b"
      },
      "source": [
        "X_train.shape, X_test.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((17871, 50), (3154, 50))"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "plmEvOrOHOJL",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "48a71629-6ecf-4d35-ea11-dfaa71543cea"
      },
      "source": [
        "for i in range(20):\n",
        "  c=100+(i*10)\n",
        "  svm = SVC(kernel='rbf', degree = 11, gamma='scale', cache_size=1024*7,probability=True,C=c,verbose=True)\n",
        "  svm.fit(X_train, y_train)\n",
        "  y_pred = svm.predict(X_test)\n",
        "  print(f'Accuracy: {accuracy_score(y_test, y_pred)*100}%',\" @ C=\",c)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[LibSVM]Accuracy: 72.91666666666666%  @ C= 100\n",
            "[LibSVM]Accuracy: 73.08333333333333%  @ C= 110\n",
            "[LibSVM]Accuracy: 73.08333333333333%  @ C= 120\n",
            "[LibSVM]Accuracy: 73.0%  @ C= 130\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 140\n",
            "[LibSVM]Accuracy: 72.66666666666667%  @ C= 150\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 160\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 170\n",
            "[LibSVM]Accuracy: 72.83333333333334%  @ C= 180\n",
            "[LibSVM]Accuracy: 72.83333333333334%  @ C= 190\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 200\n",
            "[LibSVM]Accuracy: 72.83333333333334%  @ C= 210\n",
            "[LibSVM]Accuracy: 72.91666666666666%  @ C= 220\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 230\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 240\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 250\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 260\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 270\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 280\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 290\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6pF6q7W0YmU3",
        "outputId": "294c8a27-bd31-465a-f8ad-ae9ad5c749f2"
      },
      "source": [
        "for i in range(20):\n",
        "  c=20+(i*10)\n",
        "  svm = SVC(kernel='rbf', degree = 11, gamma='scale', cache_size=1024*7,probability=True,C=c,verbose=True)\n",
        "  svm.fit(X_train, y_train)\n",
        "  y_pred = svm.predict(X_test)\n",
        "  print(f'Accuracy: {accuracy_score(y_test, y_pred)*100}%',\" @ C=\",c)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[LibSVM]Accuracy: 74.33333333333333%  @ C= 20\n",
            "[LibSVM]Accuracy: 74.25%  @ C= 30\n",
            "[LibSVM]Accuracy: 74.16666666666667%  @ C= 40\n",
            "[LibSVM]Accuracy: 73.33333333333333%  @ C= 50\n",
            "[LibSVM]Accuracy: 73.41666666666666%  @ C= 60\n",
            "[LibSVM]Accuracy: 73.33333333333333%  @ C= 70\n",
            "[LibSVM]Accuracy: 73.16666666666667%  @ C= 80\n",
            "[LibSVM]Accuracy: 72.91666666666666%  @ C= 90\n",
            "[LibSVM]Accuracy: 72.91666666666666%  @ C= 100\n",
            "[LibSVM]Accuracy: 73.08333333333333%  @ C= 110\n",
            "[LibSVM]Accuracy: 73.08333333333333%  @ C= 120\n",
            "[LibSVM]Accuracy: 73.0%  @ C= 130\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 140\n",
            "[LibSVM]Accuracy: 72.66666666666667%  @ C= 150\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 160\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 170\n",
            "[LibSVM]Accuracy: 72.83333333333334%  @ C= 180\n",
            "[LibSVM]Accuracy: 72.83333333333334%  @ C= 190\n",
            "[LibSVM]Accuracy: 72.75%  @ C= 200\n",
            "[LibSVM]Accuracy: 72.83333333333334%  @ C= 210\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_5sR1SvZaNcy",
        "outputId": "715f37da-ae43-4e98-c0cd-7924513f66c4"
      },
      "source": [
        "for i in range(20):\n",
        "  c=2+(i*2)\n",
        "  svm = SVC(kernel='rbf', degree = 11, gamma='scale', cache_size=1024*7,probability=True,C=c,verbose=True)\n",
        "  svm.fit(X_train, y_train)\n",
        "  y_pred = svm.predict(X_test)\n",
        "  print(f'Accuracy: {accuracy_score(y_test, y_pred)*100}%',\" @ C=\",c)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[LibSVM]Accuracy: 71.33333333333334%  @ C= 2\n",
            "[LibSVM]Accuracy: 73.25%  @ C= 4\n",
            "[LibSVM]Accuracy: 73.66666666666667%  @ C= 6\n",
            "[LibSVM]Accuracy: 74.16666666666667%  @ C= 8\n",
            "[LibSVM]Accuracy: 74.41666666666666%  @ C= 10\n",
            "[LibSVM]Accuracy: 74.0%  @ C= 12\n",
            "[LibSVM]Accuracy: 74.08333333333333%  @ C= 14\n",
            "[LibSVM]Accuracy: 74.16666666666667%  @ C= 16\n",
            "[LibSVM]Accuracy: 73.83333333333333%  @ C= 18\n",
            "[LibSVM]Accuracy: 74.33333333333333%  @ C= 20\n",
            "[LibSVM]Accuracy: 73.91666666666666%  @ C= 22\n",
            "[LibSVM]Accuracy: 74.16666666666667%  @ C= 24\n",
            "[LibSVM]Accuracy: 74.33333333333333%  @ C= 26\n",
            "[LibSVM]Accuracy: 74.41666666666666%  @ C= 28\n",
            "[LibSVM]Accuracy: 74.25%  @ C= 30\n",
            "[LibSVM]Accuracy: 74.16666666666667%  @ C= 32\n",
            "[LibSVM]Accuracy: 74.25%  @ C= 34\n",
            "[LibSVM]Accuracy: 74.16666666666667%  @ C= 36\n",
            "[LibSVM]Accuracy: 74.33333333333333%  @ C= 38\n",
            "[LibSVM]Accuracy: 74.16666666666667%  @ C= 40\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p47zEnTWP0Bo",
        "outputId": "730d2050-d7be-43a6-fea0-ad47c01da41a"
      },
      "source": [
        "svm = SVC(kernel='rbf', degree = 11, gamma='scale', cache_size=1024*7,probability=True,C=30,verbose=True)\n",
        "svm.fit(X_train, y_train)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[LibSVM]"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SVC(C=30, break_ties=False, cache_size=7168, class_weight=None, coef0=0.0,\n",
              "    decision_function_shape='ovr', degree=11, gamma='scale', kernel='rbf',\n",
              "    max_iter=-1, probability=True, random_state=None, shrinking=True, tol=0.001,\n",
              "    verbose=True)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lENauL9DQbLC",
        "outputId": "def0f921-37af-407d-d441-68caa3c1f8e2"
      },
      "source": [
        "y_pred = svm.predict(X_test)\n",
        "print(f'Accuracy: {accuracy_score(y_test, y_pred)*100}%')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Accuracy: 77.4571972098922%\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HJohhL8IMe2i",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 689
        },
        "outputId": "0e9d90d6-8866-42e8-af3a-dab46ca90913"
      },
      "source": [
        "\n",
        "! pip install -q scikit-plot\n",
        "\n",
        "import scikitplot as skplt\n",
        "\n",
        "skplt.metrics.plot_confusion_matrix(\n",
        "    y_test, \n",
        "    y_pred,\n",
        "    figsize=(12,12));"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x864 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pRqt24PbMtg6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fdad29cc-a79a-4d13-9338-378cedcad9ce"
      },
      "source": [
        "# print(confusion_matrix(y_test,y_pred))\n",
        "print('Classification report:\\n',classification_report(y_test,y_pred))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Classification report:\n",
            "               precision    recall  f1-score   support\n",
            "\n",
            "           0       0.81      0.85      0.83      1613\n",
            "           1       1.00      0.12      0.22         8\n",
            "           2       0.75      0.77      0.76       228\n",
            "           3       0.73      0.66      0.69       116\n",
            "           4       0.79      0.51      0.62        45\n",
            "           5       0.92      0.82      0.87        74\n",
            "           6       0.83      0.89      0.86       115\n",
            "           7       0.80      1.00      0.89         4\n",
            "           8       0.86      0.91      0.89        70\n",
            "           9       0.00      0.00      0.00         2\n",
            "          10       0.73      0.69      0.71       139\n",
            "          11       0.73      0.76      0.75       336\n",
            "          12       0.71      0.61      0.66       101\n",
            "          13       0.94      0.94      0.94        36\n",
            "          14       0.57      0.51      0.54       189\n",
            "          15       0.32      0.16      0.21        57\n",
            "          16       0.78      0.67      0.72        21\n",
            "\n",
            "    accuracy                           0.77      3154\n",
            "   macro avg       0.72      0.64      0.66      3154\n",
            "weighted avg       0.77      0.77      0.77      3154\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/sklearn/metrics/_classification.py:1272: UndefinedMetricWarning:\n",
            "\n",
            "Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
            "\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LVzUMxAwM0er",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 379
        },
        "outputId": "064add91-4732-49e3-9031-fadbf634f92f"
      },
      "source": [
        "\n",
        "plt.figure(figsize=(8, 6))\n",
        "plt.imshow(df.iloc[:, -1].values.reshape((145, 145)))\n",
        "plt.colorbar()\n",
        "plt.axis('off')\n",
        "plt.title('Ground Truth')\n",
        "plt.savefig('ground_truth.png')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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BA/CzWchmCfVWt/rebuCrEJsEffhpJBzBScZLKyCuo5kMfjZLNc/+Go8i16RK64ZsoTeS5bUHzm/63n3z1yO9PTj5jTkWms+jbbTcb/HSZZxNFtAKhSP43/8aLhTLP7D0uWm6pdCSQNCoqUZM+7A+DtMwuTffzIWfKBKPrx0C7ftC4i96GPjEA01dEGrvNVM8/wt7cXL7Nry35xGf5OcfaXkz1na0WODon+f45dMf3HofVwi/Y4I/uPEPtj1fIzrHGzXViGkP1sdRL1cnbmn/2ltTzR0N85d3/WdOhpNrthfU4/qz/5gBcUCbd6M+1T/OqddtHJLtqfDo/E10uS7a5oEDVZxvPM7wN7beRUIhTp+4Hf9GYbvZr9uxacq0O8ErN31Cm2jbwKELC0QuhdB4lGJfvOOnUq8XB+HmO87wt7/22uV5wWKTwsHPnad44eKG/d2Tx5n43hHSe4TB3rGGlCl9bY6xn7kdWT9VvgfDD87gP/V8Q67bCOore78LPyD/bOv5zUS5/TUv8e8OftGCh+lIbRs4vNk5mJ3DHRqEnoN0ygir1RrRlOGKw2eOf4nCsZWn+9+cuoVvP/RaZJPAkTo5SPyHRrm2a5aQs/MawfqfyRXlruvOUDy58SlqNhdnNnWInqd2fNnm8T26Pvcw1/6PrRMRJRzi0V+7GQ425m9s/RydqzQ7rtU4dq5R7fTqE5rJkBhb+RVEZ3JQaN4EepXeUFLFCE9cOEhhNkoyCfM/eiczN3t0b3F8WFzCsnJjuyl+kc++8R56rrmztEGh9/kF9PFnQCDsekTd+mRab/YzhR2P8CZd9cWww/ljDvG33b68LTKTg6debKvO9A18r2yzm3oePS85/OSzP77hxjy7mGDf6M4+Y9bP0dmsj6OdqaIvvEz85ZVfgXoefi7XdvF+Kptk6Atx+r91gef/xSE++jP3sj+0wIhbWT7H9ycmOf4zv828ltaL99XhZ//4ZznyZPnpOxotEcpz+M3nWPzelXXszz07wqmL/RSvjLawZDvke+z7o2eQ/7lxZOCAn8Ofmm7pmguWu9G+VK2Poz48DydbRL1Nhp2GHNR1au4410IeLWycmFGLHpFZITWR3OSorQ3OK9qAGpKvQmTBwxsdQ0MHuTtWxJXKy5ZwItyycm/G0yL5vQXca4+SHnIZkMbdxso11bii7EvMw6r4d3moj8LRPYSjEfzR8dLw7AC62tTaKDu5sVey4p8FDVNO2wcOfzGFvHQeZ7MpJBqUJOjPznH4T6+gyeomcHamFyjmy8wQ3CZccfiR1zzEZ/7tbSSSc/THGrfY09WgUWlb/8mDY5z5+WG8if1c9/EkPPlcw8oWZNZc1bn8XddU1YCZbNXz0MXNs59DvT2I54O/9roqVDVBooQjSCyKrC7/+FTVfz4/n29q7kQtZrw0KfU5GR/lDSdequu5t6tdVGJfYp59x+Z5qnsfXlciAF+hnRMPcvkQi6Holvu4jk8sVLQbfYcr5XHslqYqEdyBfiTW5CVWfJ/wK5sMIXUc/OE+ir1bfxFXy7z9Fs7/XR8J7azJpvehGHv+66Nt27F7pbjI3ff/AvHH4yzekOfu61+s64gfG3pam8Rzo4z80T780NZ9VrPHXby7J+mKtudny9RLY/s4ROTjwLuAcVW9ad17/wL4LWBYVSfLnaduNQ5JJNCe6voEdkQVmZ6jOLpJ4BDBTcahu7LAMX1diE++6aMMu5UvNLWZt/ML7P3DSN0CR70nxZv1HXq/GWPo3u8y+ouvwz/l4DZ4anGzveK5C8TPXSi7T/jtdzD1OpdkZPPPhNVEOkMThuN+Avgo8IerN4rIIeBtwOZzCq3T9n0cZcVjpTyPqzwff2EB9TyYWyDsb6xBSNHDzwbjqe3s/CBXHt9LeFHQ20C/5w5ec8tp3E3mp6pEt+MzfUcB8e9k/vrdu9BREMXPz+H+zRDT0f4121Vg8ViRa06MW/Aw21LVb4rIkU3e+m3gw8AXKjlPcAOHCBqPQnxVraJQRHI5NJ0urUg4vsnTWZv3Qaw2Ot3DiT+awVnIsPAxh7+88dNEJQzUNox2wInwc3d+nYdPHeGk+DgNHE1l6st77jR7Xnx54xviMPFTt1E85hB2rfbYCXbY0jAkIo+sen2vqt5b7gAReQ9wSVWflAr7qYMbOGBjZ7wIkoivGYGl+cKmQ26DQFWQggeFIq4TosuprQ/pfHGR/zhxD5czvUQcj2QomL+PXa3M6oddlz0uPTNC2abx4RyHRmasVtLm6jCt+qSq3r79biUikgD+d0rNVBULduBYL+TCYD+yqlYhcwt1Xw89aP5y8Toe/vXb6Dm9wPM/28U9t9oQ106S+NozXPdw19Y7iHDpvccovnPOaiUB4Dc3AfA4cBS4Wts4CDwmIq9V1S2zcDsrcIiUgsdVqkg4jIQjq7b5pT6QADVZ1epKcZGHcyN8bfoUoayWfmZt3VrYpjEqWfUwMXGEK5O9OM7av7uI0t2VoSe2tt9vJwmG4UXlq9PXV1Wzjbt5bkpeYiQ0X9M1O0Wzh+Oq6tPAyNXXInIWuL1po6ralSZiuAdXrRFR9PDGJyoa+RT0G+y/uvguzvx/p1AXxr9PkYEYR/aMBfpnMrXpv/88PWcGN2z3YiFeec8APa9eu+rjTpq09nzlIuNnjlY1o3VmKMwL/3AP/+jwfTVf12xPRD4N3EOpL+Qi8BFV/W/VnqezA4cIhENoeNWPWSgirrvdUgpA6/IScl6IrBfC9wQ/FsHxlWgNQ4XPL/TT//AYfn8Xk+9wufngJWJ1mszQBEvx0mXYbNXDZJLo3a8mlY9sctSKiOtV3MxVPHcBd5vhxev1HznMK/+gj9F9vXS7WZJOMEY+1psiDV2bXlV/ZJv3j1Ryns4OHAH14CtH6P96jJ648MLPhegaUv7PQ1+q+jw/f/Rr/OpvvIvUZIy+b4c5nzvB7Jsz3H3sTANKbYJIczkOfD1F6qWNtZGrvDBcusvnyLWNWa8FwJ+aYfCP9vGxA+/B+b4p/vWpv8LdpaP+bFp1UxPnUoyRP3mG3O3X8rM/9yU+1HeppvO8r2uO9935KX5z+jhf/sO7CT9zjpkbroNjdS6wCSwtFpHvPknXd7fex0kkmD96C3qicU/C/sICic8/SDIa5fSxW+FUwy7V1lSx2XGNMcGnhSJDTxeZyu3f8F73ghIav4Q1gO4uFjh2IOid58ZUQgt54l98lIS7SeKp+hQ9G+JbP7ILZ8ftcJsti9qI4OHtyTPzzhuYP+KwPzxT13MbU5NtVj2s33WUrnMOv/bcOzaM7JqbS3B8urOTVxVrquo4mwWIRtQ4fvSWh3jd955m0Elxc8QDyo94aUdWGzO10EKeA598AfnCxoTGfX4af2yipasnNsPumVbd7Jinwli6h+lMgkx/mJviFyloiNFVo3AdfG6MjHM8XCZLOEA8FS6l+pjPbpxKZWa6i+F8oaJh06azeJNTMDnV6mK0hCL4DRyOWy8WONpE0Xc5963DHPqbDBORbn43cWLD3EPqCLM/vsDT3/NHrSlkFSqpbaSLEcb+5iD7vrVxBcLBXAHn9Hms9dyY9tOZgePqdCKbTSuyw6lG6t0E46mQ9cJkvTDJy4pz/+M4bP6HkVCIy2+4nfHbU8uV2bA4dEm05qnWW6nou3Rd8HG+9cSG90pTLxiz+1hTVQvJfArNbJJt7XnoDtYFr3e7/XQuyZmvH6XnFWXkqbmy7bfqeVzzV0XeNP6vlrdl9nt8/B2/zz3xTm/5NabzKU2f5LAmnRk4VNFUGm+m/UckLeaj7H2wQORLD2/f6adK+MuPcPDLK5v8N97KE28+zD3xsw0spTGmOQTPhuPubppKM/SgywOjr9pyHzcDhy9M1dwsE74yz0f/8vv52DWL/Ootf877uuZqPJMxptWsxtGhqunj8ObnGfzkowy5W38QVBVvB01n3umXufbfXsLZv5ff/b17eN+NFa38aIwxNatb4NBsDgnVtqRp3anib7Fa2jIRnJtPkTnYReqoR1gqe+avto9DC3m0UNUh1VHFz2ZxMlk8P15+12KRrvMO9/VdV7fL9w8tcNPwFcvZMKZOdk9TlSre1DTSRn0Kus00CE40yun39/Gz3/9lrolM0i2NvLu3B39xkQOfOs3BPysfYKpx/n0HKb5nHHfddO2WAGhM9VRllzVV+R4atIE9ooTF43Khn8uF/p2fbzYCfmt+Cer7jE738D/TG5PpHpw5ipMvrXroTUzARP2uGx87wAvTw4Td6n/udD5MT9aCizGr2ZQjbczP5bj2k/N8/v6q1mgv6+TFBfxMtm7nq4Y/PcuRj+7nP+z9iQ3vRRY8YqfPNCQvYvgbl8ifHUSl+up1t6dEXr5gM6saEzC7NnCgiv/Es8Q35p7Vfsr6nar6axfyyLefILnF+41KpiuePY9z9nztx1ezswgSCpfdRT0PtpuMb/15NluHvsy1KrpGucuHI0iZARNBp8Uiul0fo9mUgs2Oa0w9yWtuYOx7eimXWNv/Yp7I154oe+Nybj7F2Ov7ULf0BXUzyp6vX6H48tmVfV51HWOv70dD677ECiOPLsIDT9X0Mzjd3Yy9/ybmTnZuE93Iw9D72UcseNRErKnKmHpaPNpF6g2LhEJb96dMhXrY9w0Xyty0Uke6Wbg7QzhS2iczH2PguV7k5ZV90od7mH9Dhkhk7Xl8X5ibTdL7QG0/gyTiLNyd4Tdu/3xtJwiAD/Oj9H0+ZIGjBqU8DqtxrBDB7etDEvUb0VMLLRbxp2fRwkruhESjOIlEC0sVPP5ias3vsJnWr9Ow0/M4EY+JW5N0j7x2+b2ZEyEcJ7vJtXb4pc5kSX43wb+c+2Guu+4SP3Pw/o5aWzsIT8vtzuaqWk0cGBkkP9zaKcHdnIeTy+HNrtz0nEQCRgbBaf9I3xZ8xVF/ze8wyKKxAqm7PVKrnvTEyRKqYaTYdrz5efbe+yj7o1Fe+uUb8d4rtEn2kzEVa25TlSPgtvbmrJtd3xFwHahhZNDu1DlPyFCqeYTDzZuLV3M5vEIRx1pyzDq2Hocxxpiq+R3bVOW4OJHywyKvUtWVacyLHpJf9bQqoK5TdpSMMYEhgtvbA9HoyrZMFm9+vnVlMoGiWpp1od3VFDjcwQGKJ/Zv3uyzft9sEeeFc/gLC+jlMUKTK9OSSG83hQMDqPUtmA7gdHUx8YM3MH9sZVvfCzDwJ4/jZ1uTGGqCp2ObqiQaIT8QwYtsX1UIL7jEImEQwU+nIZ1eTrRyHQG/fyU77Wofg9VATABJKMTiISF0/crU9oupXgbjccgXdpQ0uCs4FQwTsN9hW2h4H4cfdfCOH8A5uGd5mzM5R/HSZTSVJnx+ApylSOEI3lAPXlek0cUypinSh4pc/t+uJz7h0/+V03iTU60uUltyEglyr7+e7NDWTeBuTul56ALFS5ebWLLmKnWOt/+Tc+MDR1jI7F+bu5H0FC5dxs9m8Vd/CBwXNxGzwGE6RnwkTX4EFi520f9wD1jg2JQk4kzdGGXxmq1H7IUXHbpe7oUODhywm6ZVL2P95HeiitcbI3zsyMrcQIUi3sQkms8jswuE/ZWkK42GKPbEWj6M1xgotabOH3GIvvu1G94rxh1yAz7xNft37tQi9eD29VK8/gjpvgiFLsrmV/phmDvVS6L/NRveCy3kkGfOBL4vyTLHy8gORcgNjKwUIu0RTaXxcjmKo2MwOrb8njs0hCQr64g3ptFEFO/mRS7fuLE5QUSJlpkOxWxizzAX35yk0KvoNgmXXlQZv10QP7rhvcSVGAcv9eKPBjtwBEXTA4eKlIbhrvre+WEH6evBXTVjqKYzpc70XA53IYeGVzrO/FgIraBj3ph6E1FCIQ9C1km7E25fLwwPkjvYixdT/HAFNTMBDemms1AX40LxyB7cnq1nppBcHu/yWMumyqmM9XFUzIsKqVMjiD+8vC1+dhZeeAlvYQHnpbMrNVjXJXTkIIUhm1vKmKAq3niUS29M4MUUL77z5rzcgHL+7V3gbx044uPK3v+Rwxsb3/H1GqmR06qLyMeBdwHjqnrT0rbfBN4N5IEzwE+q6my587RF4FBH8GKr5glSxU8sTTy4tKLe6kRCN1+wREJjAshJJJBolK1XOnUAACAASURBVHRfmFy/oqH69AFpSMn3lj+XU3Cgrwc3v3GZaM3lSi0cLdaEBMBPAB8F/nDVtq8Av6KqRRH5v4FfAX6p3EnaInBsJjcSJ5Q8ufx6QyLh9EpAlK7kUiKhRQ5j2pbjknv99UxfH6XQDTjN7Q8q9CoX3zmCUxjZ8F7fywVif/MUmss1tUybaWRTlap+U0SOrNv25VUvHwDeu9152jJwqAjFhEsxsdKvEUqHiEcjsCj4qRSkUsvvub4i+/o3rnluccSY9iCCEwmT3htm4ai/49npa+FFldShzWsloXSIuOu2dBXPOhkSkUdWvb5XVe+t4vifAj6z3U5tGTg2oyHBO7YfZ+8wcmUcb2p6+T0/nSZ0YXJtIuFAD16P5YMY02pOMkn+zlOkR8IsHHKgg9Yfqbc6zI47qaq313KgiPxrSqs5f2q7fQMTOK4mEooXpyuVgVWBQ3O5tdmkIrix4+0ZOFTbf/r2IJTRVMRTZ9uFoirZZyckkWDy5iiLh3w6bUr+RmjFmuMi8gFKneZvUdVtK16BCRxXEwmlwsqkzC8SXjV5oobdUiJhKwXlhhyEMm4hs0dJv/3VOMWtPyezJ0I47u4Y719JQHDFb0jwcPv78a47RLo/SiFJS5qngqYVCYAi8nbgw8AbVbWiEQKBCRxVUS0lEo5NLG9yB/pwEgdaWCgCfUMOCjmW4vI15Tu3HCfXkNX9gqwhNY59w1x4axeFbkUtMbItiMingXso9YVcBD5CaRRVFPiKlO5RD6jqh8qdpzMDB5Se7nUlSUtzeZzF0nBe9exD3KlCIa+UoNfu1Cc+JvzO2Td13LQkiStO6TvmOPhh8COd9fM1WoNHVf3IJpv/W7Xn6dzAsY6/uIjz0tnS/7fBkDuzy6my/0/P4H+jv9UlqbvDM2cpFvLWMlUL7eSlY1VxCsrG8a+lNb3V3Ti5YcupBn4CNNNZ1s/LtikRkHVPoFfXpNjsvfWW9nViMSSZ2Nhcqoq/mEJzudI+3d1V/ASl8/tz82hxZQF1q8/XTmlN53i1agoc/tQ08ac8cDcuvOLtHyR9IL7JUcaYarm9PUhvz8qGfAFvchotFnAHB0rBYCu+4k9N46fT5O+6kct3RTfkNkkBDn1lAR56muwbb+Lim8JV5T+F54QjnxvHe+Gl6n4ws6WOrXH42eyWs1C6PUnQ+PLop7areWyl3Ai0oPwMpvOEI2gyvvIZzOWRGQctgsTjaFe5wOEjC2FIQ2pfGL1pAXfdoIBcLkzuiRhRSvuM3DJGxK28j+jiRD/eV+xBcbepfx/HxDRdvuL3xMnsjaMB6EXRVBqZ2LzaL10JNB614LGaCNLbgxvdOL113Xge/txCm89kakx97dr1OLzJKZicInTwADKynyAM3vazWdii/yMU2gvxBt4gA0qTcUg28EmzUETSGQscZtfZlYGj02gmg6zuywm5pRpILRMqBiUBcDud8DO0kJNIIJGt19ZeTWLRTpg/yVSoDlOONIUFjm14s3MwN7/82kkkkAN7awscdsM1josz0I92V7aeTGD6CE3ddOyoqlbTRAy3v8bx7+qXhh+uGj7oJBI4q0auqO/jT8+uNJOs7jj3PCSXh+LGDkQNuRByLUCY8kRqe/Awpk0ELnCoC+nDPTj7tl7pqxw35xN+9tya2XU5dpiJ2/qXl7MNZ5T+b12gePHShuP9XA69PAbOxuDg9PTAUJ8FDmNMbdT6OBpCpbRaoBer7YlNQz5hZ23+icZC5HtLiYsAfrjU+eskVpoTtFAs1UBUt+6wLeTB88FfVUNxHQskxpiK7NpRVZ3Aiwoztw3h3jS4vK3rXAoee24la3cT/mIKWTUPlrgOMtBf6kw3xpgKWOAIKA1Bes/aGk0oHSfmuujVaVY2SRjUYhFdWFjZ4LiEenvKJxc2g9V4jDF1ZIGjQpnhEO7dr0KWmqGcvEfohQtr+0rWUx+dm4d0a+bIkmikNHrHAocxgWDDcTtMdkDIDqw0OYXSyt7RnjUrEW6gWhrO2yJuT08pSc8G8BgTGGqBo4Os+1v6ISF3eIDIqv4LmVssLWHb6qapJZrP4yym1wz91HgUwvZnN6ZdWR5HB/MjMHVTDHRlOdq+l7qJjo6tyRFpJT+bxb98Zfm1uC7uvr2oBQ5j2pLacNwOJ6Vhu6sVulwS+/bCUuBQ38efnUNbuXDUqtqPeh4UCkhmpTzqOqUaiPWDGGMqZIGjjlJ7XHJvPcTVlUDdnDLwnUsUz11obcGuUi1NQrlq7i2nKwkjgxY4jGkT1sexy/hRyEdX/uihNMvNQk4shsRXZpPVYhF/cbHp/SFaLC7XiAA0EkGKHjiWtGhM69moKnOV47L4jlczdsdKJ3V8VDj42ZcpXhltYcFKs/8yOoFcDRSOIP19aCJW/kBjTENYjcMAII4wf43L/tsuI0vtWGfP7Cmt3rb6yb4Fo7E2JC2KEOrq2rwsVgsxpqFsyhFTVnQgw/kf3Et4YS8A4ivDjy3CQ0+3tmCq6PwC5Fbm47JEQmPMahY4WmRv3wL+mxeXX3sqTOf2MPBQCwt1tSzz82teO93diCUSGtN42jZpYGU1LHBoJkNsLIOG2utuIzkPWjk89mo5RHFl1SfEd1i8Rki+447lTeH5AqEnz+CvbkpqhUIBWZdIWA2NhiESthqLMRXY1QmA3vQMMr/Yfr8C9fG8rWe4bRVHlO47Jpi5ZeVPsnCul1OjQ9DiwOFns/hXxmo+3h0cgOEaF94yZhdROrhz3O3rhf172q42UQkpeOj5y/ipVKuLsoaIkozkSUZW+hYWehNkjw0Su7o+tSpMzuJNTDS/gGWmk99WIY9k85ZsaEyHqClw5F5zgld+HMLxQr3L03D5mRjX/X4EHn2m1UXZ1tDwPGff340Wlpa1Vdj/5UG6PtuCwLED3vwiksmWkg2HBkrL6xpjNtHBeRyFbpfjh65wMDlb7/I0lKfCc8m9ePFEIPp5k5E8yX1Ty68932FheB+9/f2wtC6Ien5LEgmr4ntozkNDIaSdy2lMGwjCV2RXjapa0xkdQI4os7fnSO87tbwtNiEc/NzZ0qy8xpjA69g+DtMaIsqRg5NwcGXb2fPD6JeTcLm1iYRVaffyGdMiqhY4TBPEe7NcePcwkbuHlrcNPZWCB55qYak2p/kCMj27ZpLFLXkems9vv58xpukscLSIqixPP7KT/UZ6FvHfsjJCzFNhUvYw9KC03ZO9FvKl2XmNMVtqZOe4iHwceBcwrqo3LW0bAD4DHAHOAu9T1Zly5wlCH3FHqiRoVLKfiOI6/so/UVIHIP93bl/+p3fdUlpG1hjT9lRr/1eBTwBvX7ftl4Gvquq1wFeXXpdlNY4O44jSc9skUzeHlttKU5e6OTU5AuumEjGmnEprxaa+GtnHoarfFJEj6za/B7hn6f//ALgP+KVy52l64PBUAj+6aafq9YXc7DybJRKme6NkjvQR1+MrO07PWrORKcuCRvMpstPAMSQij6x6fa+q3rvNMXtU9eoa06PAnu0u0vTAUUnQ6PTgUq8vZKXnGRxY5NyPdaP5pWk/VNj31WG6PzPddv0gxpgdmVTV22s9WFVVKrixtLyparMg0clBoxU2SyScH9lHX28P6pUSCfF9/HTaAokxLdaCb+CYiOxT1Ssisg8Y3+6AlgcOCxLN54gyd2uOzPANy+ujR6eFg//jQvusj27MbtSaPI4/B34C+PWl/35huwMaHjg6vdmpVs3seFx/rc0SCc9dGsL/WrIp5THBYR3kLdDAX7eIfJpSR/iQiFwEPkIpYHxWRH4aOAe8b7vzNDxwWNDYXDO/jJVcK96d5eLbB4i+9nXL2waeSSMPPGXNV7uYBY3Ooqo/ssVbb6nmPC1vqjJbu1plbcaXd7g7hf+W9HLykQITsb2MPOiAtt/6JcZ0qo6dciQ2nuPlxw5yJr6/3uVpuPCcw/DMNEG4FTa7VuKKcnUyEFUhvU8pvPVW8EvlCGU8Qk+/vGFpWWNM/QShgl9T4HAee56TL/WA0/6RcQPPw5+da3UpgPZvP+559RTj14eXX6fGklz/0X3wjAUOYxqho1cA1EIRXVioeQ3qZvCzuZ2tWtcE7Rw0RJSuaI6u6Mr67NlsmPThHhL5Yys7zsxZImGH83yHyYUk2XRkw3syHcHJzeG3oFwdSYFODRxubw96eG/bLh0rnuJemmjNEqsdbKhvkfM/1IvmBpe37fnmCL2fnm37IG1ql/dcol/v4Zpvb1y4TfKL6LlLLSiVaaXaOsdDIbxkBA23Z+DAUyKR8Pb7marEwwWuOTC5/FpVmH5xPwM9XWiheHUjfiYTjIZaUxHPd0iOefhPPFvVceL7OHlwcu3/BO0UAb896k1B+OrYqCqzI4uvyvHyP7txOZEwMgcH/+wSxVfOtbZgpvUuj3H4y1G8aPuvMR+eWMTLF1pdjBILHKaTiWipBnJgZdv5sQG8b3bBK60rl2kP3uwcPPx0INZuaJ+G1h1PctgUHR843JPHWbhpaLm/KZTxSTx6Dm9s2+lYTA0SyRwX39pH/NUriYT9L2SQ7zwZjDq4Ma0WgK9JxweO1MlBLr5NwS39NdzZENdeHAALHA0xmExTfFN2+bUCY3+9l30Pumix2LqCGWPqpuMDBwI4K4EDJwDhPMBElLC7UvFXFTJ7lPw9r0aW+h7dbJHQs2dLTRmmKRKjBeae6cZb124UyUN0ahGA5GiRi0/uQdft4xThmrEspglaM8lh1To/cJiW671pirFrw8tfiMxkglMfOwBPWOBolui3nuHoE5tMYqmKv5hCgdg3n+HaR5MbE3t9RRcWLFejWQLwbGuBownUV0Ip5fJUb0PO7/sOiNLbnaYnltv+gHVWZ7DXO5t9s0TCS0WHzIEkyfkjK2WYX9g2kTCU8ilOxCmE1pVPwOkqEIvnNz+w3RSLUOMIHikU8WvoK/KzWciWrzX46TSk0zWVy9ST1TgMgPqMPDBDcryn7qd28kp0OocfdTnz9/vpuX606nOsn3K90QZ60pz/B2E0O7K8bfi7+xj41MNl+0ESD7/MdReGWT9MR8Mu59/ei95aaOtsfAB8D29yGpnZmExX0eGqaD4gAdJ0LAsczaCKMz5DV9EHqe/ThGRyeJeuEE4kCL39VF3P3SibJRJOnt3PUFcSvfok7vv4udyakVje5BRsUiuRcITYa29jPr/ycXZECYW9tgwkWsijO00ZqPPnyLSR9vvIbmCBw7SF9PVZXvnFlUTC8AIc+IsreC9tnxCixQJ7vjNL94Xu5W2pfS7T35sj3lV9012zSDSKRCJQKJSakowBCxzGVEJEuWb/FKyapf/iRD/ed7oqO4Eq/pPPEXtyZVP81huZuj2BJtc+mbdTDURCISQWK9Ue1tWuKqJquTGdppMnOTSm3bmTc4x8u4dCslQLUUeYv9YnenCxrYIHAOEQTjyOel6p/6LCYKCLi0iZPiFVRbPtW+MymwvCs4AFDtORihcu0vfJK8jS0FKJRNCfvoX8wW0ObAXHRZJJpFjEKxQrW3FRdSkPxoY0m+azwGECI3TwAPmjIxtGVeFD5JVxihfXTe/te+hS8oH6Svclj/HnVvpBvLjiHMgQjrQ4o/1q3oQjOJEw6rlosRCMR09TfwH4s1vgMIEx9z0HGX9vFje0NhXNKzqMfO4gyfWBYzXfo+uv/5bu+xPLmwo3HOSlH4sQHmyTqVAcF+lKIqr484towYbd7krWx2HM1qpNNizGhIHeFPHw2rGs2WKI9HCC3iOHNx7k+fgTk/jZLH4qBanU8lvhiX7C04Ok/aWMalGcZJForEX5II4ALviKuA7quaB+02seEgoh8ThSZsivFou27kqDtFsX3GYscJiWqdfNOez4TLwhw8zNeze8F5p3OfHpbnjyuQ3v6blLnPhD0Ejpa6CucOFtvehtrV+XQZIJ3LiimUzTh+q6Q4OkX30IP7L1hOjR6Tzuo8/bMOJ6U6ypyphmcB2fQ8MzMLzxvSszPRS7o5uuCeGnUvDsi8uvJRQidtsdaxIJxfEJhfzm1kAcAScEvoLbgkWQohGyAyGKsa1rHOKFibeibKYtWOAwZol6XmlqmLGVqWHSwy5Td+VJ9LTmyVoiERzHsSTBXUOsj8OYQFHFf+p54k+tbErefIqp23rQ7hYkEjoCkTASCUOmxiRBEzwB+BNb4DCmDGdqnpHv9pPvXqqFCMwf84kebnIiYY1JgiaAAvCntcBhTBnFS5fp/6NxkFIvibgO8oFbyW4ygKuhakkSNKZBLHAYs43VU71rUega9Ui9sCqRMKbIviyRaANHY61KEhRHlhMbm0k0EM3vwWc1DmMa4+pqgk3Pt1Al+dXnOPHASiJh/sQ+Xnp/hMhw64fxNpIFjSbo6EkOfQ8n76HF9lxMUnTlKdHNeIRmIujSmuPheQcpNL+ar54PhQZkKHteadim5xGeFy5O9Nf9EpFogcGuNK7TPn/vVk5U6C8s4C8sLL8O93QRnh4hLUvBRMBJtDCR0ARaED4yNQUOf24e58XixrWJ24ifygAQe+IsJ8ZXBvhLwUPPX25+eWbnkFVZy/Wivo8WC/hpn2s+P4739cT2B1Vp6qYeFt7t0ZfI1P3cnUAvXuHEp0L4saWvk+Nw8c3d+Hd0dg3ENEiDA4eI/DPgg0tXehr4SVWtaqx3TYFDi0W8+flaDm26rVaNW0MV8aj7H0xWVWxKq741bu4hLRbxXnipIefu6bqNca/1yV6OB5lCdR/ZYtFF/MZ+E/10Gp55YWWDCPFX3clcYeV3JgVpeDnKEkG2SdhTX8G3TvdOJiIHgF8EblDVjIh8Fvhh4BPVnMf6OADn4gR7HqD+y7oWPJicrus5d7O+J6cQfxDdeiaMDfbllPC5CzR1GkNVhh6ZITbbu7wpMpdHlz4LTiwG4TASat7Xz73+WhZO9ZdtPu8+s4C/ydQspuOEgLiIFIAEUHUTjAUOwBsbh7Hxup83AE2VgeI9d5qu505XfVwr5r71n3qexFNrt3lQevKPRCAaXbXzqk9Kg5p/c/u6mbzJ3Tgl/VUKbr6L2FNVRGXTEI3s41DVSyLyW8B5IAN8WVW/XO15tg8cjkvo0H787mT1pWwjTiqDd+HSmqGV2x/kwmtvZO54/fsN6iU655P89mm8mZlWF6XhJBrF6Wrjz6Gv+Iup8k2Sqlsm8ImUMsVbMj+VaR87G1U1JCKPrHp9r6ree/WFiPQD7wGOArPAn4jI+1X1k9VcZNvAIeEQ2RMjLB6IVHPethOf6CY+PllV4BDX5fJdXSTeUv/aSL2cPz/A9S8OQJMCR7VTodeT05WEkcG6NynWTdFDisVt+7L8bBY2mXdKQiGccM8mR5hdY+ez406q6u1l3n8r8IqqTgCIyOeB1wP1DRxQCoB+0B+CaqmBq098XBl/aRDpz3NgZLathqQCEPKbeiNt+fBSkfYNHK6DxGI4/iafEc/D32auKfUVzRcQb1UHteuWar5tPILRBMp54E4RSVBqqnoL8Ej5QzayPo4ytFhk8IvPMvT1Lsbefpj8D7rE2y1wmPYhAgO9SP/GWoPk8ujlsfK1Ed/DX1xcs8lJJJBE+zaVmgZobB/HgyLyOeAxSt1/jwP3lj9qIwsc2/Bm52B2jsjCIYoByOisJ6e7G6e3h1RfCMcC5vZEILRF1bzoVVZrWF8j8bzSKoDeymtt5bBe03CNrtSr6keAj+zkHBY4zJZSb76eS29y8HuK7I/lWl2cXcnPF5C5lSx11Ldci04XgOeCpgSOZk6O1kkTsbWyIxpKixjtOzVG2F25UbW6TLuO76EWKEybaUrgaOaNvFOCBrRBR/Qm2rFMxnSUAHzFrKnKGGPahGgHT3JojDGmQQLQbGKBwxhj2onVOEzTOC7uiSN4fXUa8+8ImWEhEYR6szGmqSxwdAi3K8m5v7+H/KvSdTmfiBKPz+BY4DCmqYLwlbPA0Slcl0KPcnC48yc7NNVz8j7hFFtPSa/g5nxaspi5WcsChzGmHYSfPcfB8YHyO83O45WZS6uTcqTalo2qMsa0C29qGqYqWFSszCSSFjTMVRY4jDEAhA4eoHB4iHR3GD9kUaJlrMbRfFadNqY2/lAvs9cmwL4/rWWBo/ksaBhTG2dqnt6XoxvWrlFHyA6GyXXbsrLNYH0cpiybMNC0k+LFS7hXRjdsl1AIXncDue7oJkeZ3SiwgaNck1RQmqssaLQJVcgXEK+BQ1HzBWj3dTRUN11aWX0lNJ8jMblyu4jMFUprhZhdKbCBo1xgCELQaCe7vubj+TA1i7eYatw11K9qvfu24nvIM2dInlmpcWihWFoK19RfAL6KgQ0czRbK+UzMJcnEw/TGs2vWqAi6XR00oPSknc+XX9Z1l/OzWchmW12Mzmd5HLVrx6am7ocvEp3aw9zxXqbf5bCnd2H7g4wxploBCBxNGSZRbQQt13dRy7XFZ8d/jOKlyzj3P07/s4sU8m0Zb40xnUB38K9JAnUHrLYWIgrxKY/4xRTOQtraZI0xpg46bunY9aLTefTJ5/Fs3WZjTJsTrI+jZcSH2KxHZL5IaGIBz2b8NMYEhQWO1hCF5Jl59PmX8HwtjdM3xph2Z6OqmsctKOGUIksJVuKBk8pQDOq4eWOMaWMdETiicz5dj5xHM5nlbV4qU+aIzqB16jxanQC465MBjWm1AHz9Ahs4RJdqFkUllPbw5+bx0/VZNjUo6nWDX30eCxrGtFgAvoKBDRwAybEC8dMTaDqDl7WhtsaY4AvCs1vFgUPacGBSaKFA8ex56/w2xnSOANzOtg0cWigSPzNJZKqrGeWpijsxS9GChjHGNNX2NQ7fo/jKuSYUpXo2ZsoY01GaPHVIrQLdx2GMMZ0mCH0cthakMca0kwZPcigifSLyORF5XkSeE5HXVVtEq3E0geVGGGMq1YRbxX8GvqSq7xWRCJCo9gQWOIwxZpcQkV7gDcAHAFQ1D1S9gpk1VTWB1TaMMRXbWVPVkIg8surfP1x39qPABPDfReRxEfmvIpKstogWOIwxpl3sJGiUAsekqt6+6t+9664QAl4D/K6q3gqkgF+utpgWOIwxpk3IDv9V4CJwUVUfXHr9OUqBpCoWOIwxZpdQ1VHggohct7TpLcCz1Z7HOseNMaadNL5L9BeATy2NqHoZ+MlqT2CBwwSGZnM486n6n9jz8G3tFtMmGj2WRlWfAG7fyTkscBigfrkmjcxZ8VOpxk2db3OemXYRgI/i7g0cIoQO7Mfv667qsIXDCdxQ56370Yi1PRrCbvCm0wXgI75rA4eEwoy+8zAzr6su98WN5Bjp2VlzyWZP5bU8qddrBcCdlsMYs7vs2sCBI2QHhMP7p9bcKK/ejHd68yx3A95sey3Xa8QNvpE/dzX7bMpxcSJhcOo8GND38XM5q82Y1tNgTHK4ewPHFgLTZNOmKvm5a/3duMevYfHGIdSpb03LzfokHztPcXSsruc1piYBuHVY4GiRSp+6m910pCr4DWgCq7ocm2zz+5LMHw6hbn2vFUo7JF6sep43YxoiCM+cFjhapNJg0OyaS7YYYvqJYbpbvHbXYBpCl8/bYl1m97HAYYImVwix90GP+J8/3NqCqFrQMKZNWeAwG4iPdRQb0yLWVGWMMaZytua4CTonmUS6kog0v7Nci0X8uQW0UPUaM8YEmwUOE2R68gjTr+qhFYOswhml7/6zFK+MNv/ixpiyLHCYLfmJMNl+acnk+/4CEAk3/boSCiGh+n8tVBXN563vyJQlWB+HMcEigtx4LYvHeup+6shckegjp/Hm5+t+btNhLHCYdmFzUFUmN5xg/hq34uXUKhWbcog+Ha3vSU1HkgDUSi1w7BIWNIwJgICMqrKlY40xxlTFahxm13JykJj0CWV8/P4u3BtOkuq1r4RprSA0Dti3xOxa0XmfvvvPooUC8288QWpPd90nUDSmahY4zGbaeSGnXUVL65hrLkco7RNOr7TcehEoJqTuneTGbMdqHAbYGBTaeSGn3cjPZEg8dIZkJLK8LX9iHxO3xFH7hphmC8DX2r4WTRCEG/yuHq6rijc1vWZTaLgPNx/D91eqHH4IG05iDBY4zJJdGzS2IBfG2FP0YWmeLj8WYubGHrKD1nZlGsiWjjUmuLyZGZiZWX7tJJOEj95EdmCp99zih2kUCxzGdAbNF+g+PU9sKs7i/giZYceCh6m7oMxVZS22xlRAC3n8J5/D/caTJEcLrS6OMS1lNQ5jqqE+kck03RdCFJJOy2YPNh3M5qoypsOoos+eoft0CL3hGGN39uBb4DB1FISmKgscVWjkkNVWDIfdrUNwnTyEMkpk0QfPq/p4LeTRQh4nX2xA6cyuFpBJDi1wLCl3E736Xq032Upu0K24ge/GoAGQHPXofeQymkrjLaZaXRxj1hC/1SXYngWOJeVuoju9we7WG3QriLf0xSvzKw8veniXrqBFqzEYUwsLHKajJMZ9ep+fB3/rxzZnZpFiDU1UxjRFAJ4zLXCYjhKZ89C/fbFsbSIALQFmF2t0A4WIuMAjwCVVfVct57DAYYwx7UJpxnDcfwI8B/TUegIbSNjmmjV1uk3Rbkx7EK3937bnFjkIvBP4rzspo9U42lyzOtYD3YGvEJ0tDa+NTWZRP8A/izE7MyQij6x6fa+q3rvq9X8CPgx07+QiFjgaaLfmSTSb+NB3OoP7xOlS34ZvHd8mwHZ2y5hU1ds3e0NE3gWMq+qjInLPTi5igaOBGh006tW8FNgA55cS+dw8uAtZ/JTlZJhga/Akh3cBPyAi7wBiQI+IfFJV31/tiSxwNEGjbsw7PedOExtbzc0pw48t4F6Zxp+da3VxjNk51YZ1jqvqrwC/ArBU4/iXtQQNsMDRFO16Y27XclXK8cCdWqB46XKri2LMrmKBwxhj2kgznudU9T7gvlqPt8BhgifYFSVjygvA59sChwmcUFrpvlAkvFBA5xdaXRxjQip9QQAACdZJREFU6ioILcgWOFqkkg7zwI52arDIgpJ44CW82Vm8ACx6Y0zFFAhAHpIFjhapJCBY0FjLmc/QdTlBdLqI5vMtXynNWcjQddnDD20/LDoyV4RCvgmlMqbxLHDUoNKagNUq6ss/c5bui1fA8/BzuVYXB+/CJbrGJ8GpYOYez8PLZBpfKBN8AbgdWOCoQaU3+qDUKoISvLRYbKs1NNqtPKYzBOCraIHDtEfwMsYsCUC/3a4OHE4BUvlIq4uxM0Vn+YPmFGAxF93R6bL5ML3e0gfXV5wiaAvmUBaPQHQSGlNvQXiO27WBQwtFDnxjgcWz/a0uyo4cnfdgfBI/leHQlzNkntrZzxMvKslnRykC4VdG2ZsZrE9BqyQFD396piXXNsaUt2sDB76HPvw0yYdbXZCduzoXrPOtJ0jW4XxXW+2Lo2MwOlaHMxpjKqJY57hpIscldPgAfu8OQ4enyKUxvBl72jem2Uqz47Z/5LDA0SEkHCJzYpjFAzvrs3ELSn8uDxY4jGkNv9UF2N6uCxxOLIZ/y0nyfTvrRG4X4YUC7lNnSglxjuy4I7sVHeHtKHTNIVI37EVdW1J3p9ysR+yJs3iTU60uiqmT3Rc49gzz/E9FufXU2VYXpS6eunCQk//XPvTMuVYXpaNM3X2Ak//4WYYji60uSuA9OnWY/L+/Bvc+CxyVsKaqduS6RPuy3N53vtUlqYsL8/1o2G11MTpOMS7c0XOOQxG72dXDtw7vY/DkcZiYtv6zcgLSOW4NE8aYhrohcZk9P/0KV34zzOzbrmt1cdqcrqwCWMu/Jtk9gUMEJxZDYxEcJwAh3ZgOMRha5Kf2f4ufP3kfiwccnGQSCQc88baBRGv/1yy7pqnKveEkr/z9QXJ7PG7f+1Kri2PMrpN0ciS/b4wXjt3E0CMOA596FLUZgwNp1wSO7L4urn/r6Y7p2zAmaGJOgV868ddwAv65/hiDnw1Z4NiMdY63ntx6IxN39LBwBI5H060ujjEGGDk+xaV/dAtdl3z6vvQc3uxcq4vUHhTE8jhab+K1Pbzug4/RE8qQcO3pxph28E+Pf5XssTC//fxb6HtkACxwrLAaR4s4Lu6p4+T2dbNwDfSF0yQcCxpXiYJaXptpoZhTIEaBa/pnGHv9UboP9RN5+pwlCQZERwYOJxbllX8wxHVvPsMbY4vEnEKri9RWLGiYdvGekSd4/p+O8cjUYXL/4Qihr1ngCEIeR0cFDgmFcIeH0P4esnuKvLb/bKuLZIwpYzC0yF3dp3FEue/gfoaOHUGnZ3Z1n4dljjeZu3cPp3/+MO7xRe7Yd6bVxTHGVOhkbJRnfuosF36wj+Qf76X7jx9odZFaxwJHk4ggkQh+XzeRk/P86IlHWl0iY0wVBkOLfPDA/czuTfDbe99Ld6sL1CqKzY7bLM6N13Hu7w2Q3eNx+4gl9xljTCN1RODIHOrmhre9yC29F3GC0LNkjDGbENT6OBpNbr2Rydt6mD8G10VTFjSMMcFngaOxxl7Xy+t+8jG6Q1m63Wyri2OMMTtngaOx4lM+f/PSdThuAHqTGqRwMclwaszqWvUggnvqBNlDvcwfhajl/5hms87xxuv76+fof6gPZBdntOWn8cYmwNnFv4M6Edfl7HuHuecHHuPN0Vn63FSri2RMWwpk4JBQCFwXP5OFzGiri9NavqKFPBLtjDXUW0oc8j3KW3qfxQ3CTHOmIzWyc/x/tXcHr3GUYRzHf8/OpmmaFNM2GMoaNGIFFYSi6MFbQShevAgK4n8gKHjxL/AkggcvgXqoCGpVpOChVAmIINqmKGhLNRRtE1PbNE2zabKbzMzjoaEEDd1MNpt3Zuf7gYHsMLzzHHbz2/d9d97XzEYkHZc0rDv9mzF3fz9rO8ULDjNFtYNKBwdCV5ILtrwivzwtL8C4KIBN6OxnOZb0lrufM7O9kibM7LS7n8/SSAGDoyLf3at4cHfoSnIhqlZkUSTFsZS6Kkl77fFFGwips1vAuvuMpJm1v+tmdkFSTVKXBwc25Kux+iavq/fanrbascSl6yw0BxTUkJmtXzpjzN3HNrrQzB6SdFjSj1lvQnB0izRR/Ce7GwKF5mq3xzHr7k+3usjMBiR9IelNd1/IehOCAwDypMPDxWbWozuh8bG7f7mVNggOAMiRDv+qyiQdk3TB3d/bajuV7SsJANA2960frT0n6TVJR8zs57Xjhawl0uMAgJJw9+8ltf20MMEBAHnhktL8P5NFcABAbnT2OY7tQnAAQJ4QHACATAoQHPyqCuigxPmIofvQ40DpVfr7tXTkCdVrkfoeubWtbbPK7r39tPiwPv31KaVLa/+KEtODf5R4HxQmx4FiqOzfp5lXG3rjyXHtrSyHLqdUxq8e0qPvNqRLU3fPeaNZ4o3JXPL8f9kgOICKqbc3Vq3nZuhKutqKR/p2/nFdnB++e+6fySHtn5tWXK8HrCxnCjDHQXAA2BH1pE/ffX1Yoydm7557bPmqkpmSb8ZWQAQHgB2RqKLeOSk5/3voUvKLOQ4AQGYMVXVQ/uePdk4B3mgANqkAn+fiBUeaSLNz2rXUCF1JPqyuKllZCV0FgG3BkiMdk9yYk27MhS4DAEqpkMEBAF3JJaX5H4cnOAAgTxiqKiarVhWN1JT294UupSVrNJVe+VvebIYuBcB2IDiKqbJvny6/VNPiaBy6lJb6ZqoaPR4r/utK6FIAtM15jqOorBqpud+1Z/h26FJaaqzsle/qCV0GgBIhOAAgL1xyFjkECiB1panpdtobupKutuqRLP+jMOExVAXkn99a0MBXI3rn7MuhS+lqlUQ6OJH/4d/gmBwH8i9ZWNDgRz9oMHQhQEEQHACQF+48AAgAyIihKgBAFk6PAwCweayOWwruptWVqpLVSpD7V5dNFidB7g2gnAiONqWpqW9ij+4/F2Z/kOriotJrs60vBJB/bB1bDu6mgalU0fi5MPdfOwB0CZ4cBwBslkvyAvQ4wgzMAwD+z/1Oj2OrxyaY2VEzu2hmk2b29lbKpMexAW80NXhRul2/r+W1PanUP720A1UBQHvMLJL0gaTnJU1JOmNmJ939fJZ2CI4NJPPzOvDZLzoQRZu63htN5hkAbIsOD1U9I2nS3S9Jkpl9IulFSQRH29yVLtGLABBAZyfHa5LW7/o2JenZrI3cMzhOpycsa4MAgK2p6+apb/zzoTaa2G1mZ9e9HnP3sXbr+i96HACQE+5+tMO3mJY0su71A2vnMuFXVQBQHmckHTKzUTPbJekVSSezNkKPAwBKwt1jM3td0ilJkaQP3f23rO2YF2BBLQBAfjBUBQDIhOAAAGRCcAAAMiE4AACZEBwAgEwIDgBAJgQHACATggMAkMm/MZSBxt7ym5MAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C6eUwA9IM2J8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "131f2a5d-1881-4778-8b49-413ce953e5ff"
      },
      "source": [
        "# !pip install tqdm\n",
        "from tqdm import tqdm\n",
        "pre = y_pred\n",
        "\n",
        "clmap = [0]*X.shape[0]\n",
        "\n",
        "for i in tqdm(range(len(indices_train))):\n",
        "    clmap[indices_train[i]] = y[indices_train[i]]\n",
        "\n",
        "for i in tqdm(range(len(indices_test))):\n",
        "    clmap[indices_test[i]] = pre[i]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 17871/17871 [00:00<00:00, 1121665.32it/s]\n",
            "100%|██████████| 3154/3154 [00:00<00:00, 1035606.30it/s]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vGUDeobLNR57",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 379
        },
        "outputId": "25892bef-13f0-4301-e9ec-ec71d07726c6"
      },
      "source": [
        "plt.figure(figsize=(8, 6))\n",
        "plt.imshow(np.array(clmap).reshape((145, 145)))\n",
        "plt.colorbar()\n",
        "plt.axis('off')\n",
        "plt.title('Classification Map (PCA + SVM)')\n",
        "plt.savefig('Classification_map.png')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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vsPgvn6f3N7YytCFw1oLDPniEqkNH0fx+ZFE9dlWII1UBtxrLJOIxH02/sPD2JjlSGXTTY06iOhTDuc61l5TPT/XdGWGdOEnFXe3u/yeNQ04yCcmze27zifj9dG/1YF8URZww5S9CcmklPW9I4/Vn5u26CnDmfP2e075St02z633FtFNQGug1NYiuYXvOvSnEO6DoOlyDv0dHrPQEo7geT6MlLSQanzjTnUt1moCpTR0Mg2VJeq9txLexbsq+QHsMtevAjPS1FyJaOEzmkpXEK03MKHS/VE99m8WM9Ay57QQC2JtXkgmbBA6cwjpxctpjk0rnH7tv5PnOJWxb1Mon636KT9zn22mF+bu2N9ExXMavLt/Fu8temtV91RojnLpMIxW5mKpl/Zg4U1Yluih0FD5srNVxBt+/lcFNNgEtNaNrvJqu445jr6ejp5xlHRNXAcaiRhJrG7D9OqkyjUxAcCIZlBLa+8pRPT6ciEVj4wAeb4aB1X48jQZOJP8AJjIH6rO54gJV66p0mrJjDiNOiFCH+x17+xIE95Zjmz63IMI84RSdz/TcU3jFsdLNAae0c6/XqzicpqxVQxwbPZUzECuFfmoIu/vUeVnibqjrYuj2IWw1VUq1PdXMkv1enPjceMcsNKS+hqPv06hpGCB4dxVNdx5EJRI4RQ4OWk0Vh9/pR2+KU/edBvwFBMeo4+G5H29k6Z1H+flvbOIjH/w/fLr7vb+SbGbwPxbT9ItO7vzzq3jndTtnNWCuNHv553feSczxUm8ULkFh4vAfl99Fz6VhqvQoNdrMvuvHh9ZjfKmS1S+34YyMTJhTxjc0cvIDFoFAHD1rt2j0uELBsz9A0+Mx+i8KkHiLSXU4Ruz6NI6S8WNKzD1OLEb5D/dQ4TFxEkkUoPYeovlYADSBvzzfPTy/FBQcyix+Cp8Om6TDGkZK4R3IILOZcTigJyzMYRtlaDimDkqhpW0k46BSaZSVo7rKWOjxNMoysL066PMn6Px6Bn8g/wt7tHoRat1ytOREtZooBT0D2L3TOilcEIhlow8b9PtCNA/Zs7fz2A7mqEZy2IvSBL2qEpVI4sTj6OVlOMuaGFkeYqWvGx1FOqKwFtciNvxHz7W0BHp5Y/gVvFqGZKVGurkKM6s+eCXVwNOjq6g1R7kxvBcdxePR9XSly7gidJRN3o4pwsUUh+XmVFtBPnRRNBqjNBr5CghOj19PE68zMZfV41a5BaNzAKu9Az3lYA97iKZ1xHAQTSFhhelNY/sU6XIPVkAwRKFrDhHfzFY5k1FK8hrTS+THicfdMmRZlGVhj4zM6zUVCvsCWKXNuQ6q7yID/fJBYsfLaH5Ux4zPzofcGIyj2rvRyyJkFlcjjsJo68EZjeKkJr44djSGdqQNze+DJfXYIc9c3ErRtGzooPUPynGciddXjkbNj1oIf+/CFhx2ZzervmagfCZycvaujvapXpbfZeKEfKRrgoxes5LQ8VF4eT+pLSvIfG6Ay6v38+bylwlraT51y0Psub6Jw89v4MQfruLFTRup+/gwm30nePtHn+JUOsJHIgfRRfGFvbdQ91UfA+u8VP5WlICW4tt3vp6aXUke+vg6fnTFv8/pM5kpt5TvQvuMYiDt1ppylPDidzdS/4+deHYfZe2pWhyfh3SNn3RYp+P1HsLLe/CsG+bkYi+mN0nZWa4wZiI0SsLl/DOfNo65Ys4Fh+2DJWXD7A+GJtZnK0ROkJ/t1XF8ggk4o6OucT7jgOPgxOI4sZy6MyKu6y1ubIGWbeusUQpJ6nTFpwYQFkIXh6XVAxiaQ7knMW4jSdgmB+rWUF5RMW4PULaDE41eUDpglUphHzo64+O1QADxmKhkyjWGjrWTSWMda0UMA/3yDWQaTByf+1PMRHR+rflFXh88XUrjjaFXuTG4n8fDa/Ae7SFY30Tc8VKupbmtfMeEayZiHnxHewhUNRJ3vGii8Pc4eI+cIhM9UwXYqcQdg247go1Qr48Q1mY3eNfrMT5S+QwZpdGdDTJ8NrwRACcaQ+s4heb34XWq0DJ+JG0ioqgOxSA0Xa2luackNM4vCrB/GQVHxQGHjqGlVA8r9OTMXAHFcjC7BkEpem9uZniNTf0vqggfPOa+VMfdCqBOIjHhPL2qEmoqx32rlabh+M/+lpyBQZZ/v45Y5ewCcUabdEZu7qKlzHWFNsQhfmWUQ0tWjx/j79JY/J1WrI7pqpte2IjXS/+vbmLgIkXtDgh/f8cUpwFl2xhHOqnsCcHQaMElui6K27c8x71f2UxjeQcX+fLbRW7f+Dz33HEx9WVdbPKfwBSbsg+3c/xXKnjviqmRxpA/rmPs8/0jW7j3u9diJGHrrS/z2fpHi30UE+iwInz8oQ9TtVtj8SujKKVg02pabyrD9itsDyhT4Wucu2DKEhcWF/6KY7rZewHTR6gzRajIsVCzHNTAEMq2SdY007S6h+FjDYRxZ6fTpbEQv590VfDsbBqTA3xwdZv6UzsJzLLJwBUb6bnB61YZx/XOumrp8dMVx4Gnj65APRB4zQYaimEwtBquuPIAuwbWEckX5KUU9qkeODUxp5qjNDJKm+AO6yDcWraDWy/ZUdAAflv5Dm679PQqxFbCV1ruwUGmDdbL50E1xv7RehY/NIg2MMrLNzaOmSdmzZAToPYFoezuZ8fvLlkfwLx0kLqzTDmiJgVKllYPJeaLwgGA7TkGQxGcSAArPPvAuulwTA2tvgZRilCbokevp/b49G6eenUVEgriRM4w8OZBaeIGCVZWMLKpjtEmnUCPQ+RYDG04jnP8JOIxSVyzjkRNcauXyPEk+rOvzGi+UF0xSuu7avGM5HHEz+Lvd6h49PDc5X86h6h0hoZnbV4eWEftK+kZe8CFDg/zr/fczB0Nb+R3tj/KdYGDfHz/e+nbV0P9Raf46urvEJCZ281OWBV8aset2F1+Lr/8IH+66MGF46o6x3T2l6EfDOKYCs+6YVfNtUDRwmG0ynJIpbF6+ubFhV0LBpFAAJVM4owW58xwvlBw4RvHreMnJh68bAnMg+BQukamzrUnlB9LUnZc8LQP5n+Amg5VFaRnGeg3FiTomBod18MVl+zn2QMtpH8RItTtw9/VgxYM0LndQF9ZnLog8WyYRTuMGQmOVRU9ODf34RRIp/FC61IqdlXChSg4Mml8P9lB44NaUYns7H0HWbxfR1+7gifWruGy5mPEf1pLy5efp+Ozl5NcZRCYNuHEVI6ma6n7vo/Q/77Cs/+wHhbN9o4WPlafj6WPxshEPJxo8i1swREJk2mqQo+mkMEhVGoeBEc4hKosQxuJXVD2xIUfxVGkjUPFE5gDcRyPgR00587tNTe4L5oT3DfhGB09EgKvF+UzZx/spxRG1LW9+LvLeam9GX3AdHeNrV5EQEDTpv8KM2kDdTKAERWSjRb+6vjMnQHIBpRJ4ZclHErQu62aQEuF2y2lCBwZxD54BKNpEfENjehJG8/OI/PuJjgrlJpdRLlju84QSjDFZnRNhsB7LiO2Oo2Z55kllc6/917HMx3L2NrQNiFIsMYY4dSlGqnIRqqbZi+AVSLB8K5mfs36CG9d+gq3lhVWmc0FSglt3ZXonV6scpvGpX14sjEsGVuns7sChk20miRN1UOokMXA+gCWXzBzXHaVEjr7y7B6faiQTWPjAMmMwWBrBXpCQxbHWFR1brNFq2QSYzCOJFLY8xSPpZJJZNREjdlGNd31vNQ0nFh8QQbqKtRrzzhu9/Qi/QPoNdU4y+pQcxwvIY5C7x7EPtWDciY+PM1johY3YIe8ZxWQqFkO0n4KFY1RV72eocEgYoMUKeYzCZPl/5vGu6eNjveuJHP1rLuUF1sJq6t7GHxvFCsbbJixdU79oJ7qg0eIbl7E6G8MM9gbZm1XLSxEwTEHhCXD167/bwauCVFjjORVU8Udkyd/soXlXz/GMx/exAc/8jS+bFbb9Z5uvvzu/2LU9tNoDs56sLf7B2j58kEkFOSuP7qKW9800Y4yH0LEUUJ4p49F3zrM6PbljNzuHU+9nrIMyp/3UL07TvvrgjjXDNPYMEj8LR40UdRMct3VDgVZ8WicgTV+ord4icV8tNybxnOslyO/0QznWHDYA4PI8Ij7ns/TAG4Pj8BIdHzFq3lNtLoalK6hdZ6a6KG5UFBgL3y5UaRXlVJuUrJ0Gi1hoSwNxzMHAXd2NrjPdlCp1MTgvvFLKzTLQcs4OB797GSyZeGkM+gpByMBRSRfPY0oMiEdb2UZk8I20BIZhroivKSEpRWDVHmL/4Hqotxgw+DpFzrj6OysbUBfv5roIp3GyAhpyyDeUkGAFdDVszBXHtMhgrF0MXbVVLVjvM5P/6DJnZGruCp8mC2+9mmb0cTBCirsRdWIA3f1XcVyfx83hvYR1jKsNPvBnF0Xq70xOlZFCJvr3RIwhob4J/4+dVEThMdYtl0bGc95NeD4eDK6jp1DzXiiM5+l2D6gupxMQMaz5p7eJ2TKPOO/P49u4wkkpjYCOB5FOmJi+09n1U2HPRiVYZycZ1MojkMpYSTpJRr3Ypo2FcH815oR2bFkXhHNzao9hmmC4yBKUSqZfXbMynfVGR5BDqXQQkFkcd1ZJ0DULMcN7ovFp7jcjqHSaVRrO5rHRJoasKr8Z3XNyRQ7YfQEMpx8k452fTWqPIUvd+eRNtb+cxOp+hB7P+Dn2lWH56SPmjhUXN3NkfVhwqF+ImaSFVV9HP5INfGhclr+J4L+1M45uda5QPP7OfLrjVx5w94p+44OV+P7Xj0vtW3hkU+s5Qdb/mPC/rFU67oogmLxiZsf5uVrmjn00jqO/NE6nl/vpezjcV4XPHRWfXxn5Q48f2gxnHF/bxqK28qntjl5xTHqeBhyAgS0FDVanB8Pb+HJr2yj/FCc0OGjMwqe1ERhXzLK/pZy9GCSeu9p93a/mWF02ygnNpsEwvEpQmUy3jXDtC3yYXpT1HjTeE2Lk++OoNJBwtWn06ycyRNr6HgFtTsg1qARu3rhqXpy0SvKkLKcWKyMhdM/6I4l6fOXNbgQbpLDhc+sRnxlWSjLQlMKrBrEUhOr8+VjrGJfnt+lZGxXaEzn+aC56dSdZArJWGjzoBMtdtVhGDZGbf6VhJNIorW2403XoZJVE/bZSnDUWN2Fqcn0CqGLYlV5L6vKT0ege3WLrYva6CwvI1qziLJIBCeVcusSLHR0nXSVzbuqd0zZ9b/GRextq8T7i/1E37GBw5kqyrX4eOW93OdmisObQ/t4c2gfPwuvxHeoh1DFIuJOYUeOuGPQY4dw0KjXRwhoU2fAzcYIv1X9s7znjzomvXYYUyxq9Ni4XQXARkgqE59yVUajlo9IWwrjQBtOdGYrUBFFffkIlE9dReqaQ0PFCFTMrJ3qUGyCsdzUbZY0FG/z0ZOCb8AiHRKsaV4a8Xrdyn9zjXJworGZr1QMA+XNLqdEEEAlU6jMwhQaLu5KdaFzVksFJ5lCb+tC93iw66uwIwVSfSiF2TOKjEz1VFKWNe1KQwsGkUX1oGelkshZ1do4FxhLmzn59kaStYqaRRProYyk/fQmgpiaQ31wBL8+N4nqyrwJDr3ZoufS9TT+3D5dnnMBoxIJlt9j82c7PzRlnxlTVB04iZVM0fJ9iz/b/SGGrklyz1VfIyzTP7P3b3qe7/3DFurLT7HJf2La4wDuHb6U+7+3Hc2Ca9/9Ep+qfaKo/v9l2y20/qCFRK3i997x4wmrm7CWxpRBPNn54w1lr7Lj04vpO9XCirtstJ/tKupaCwVtaYw2vx8VyFDvTZOIT30XE2/YRNstCoy5VQdpIwYr747Ci1NXqPlQwyNIKoX4/aiK4rJAnC8U4FwAWrSz0zE5Nnb/gOvxVBHBnqzsz0EUMDyKNSnY60yIz4tVFUJ5zlMJwllgVwSJX+IW2anxTxSUSdtgOO7HY1jUBuZuZhE00ly39hCZ1TqvdK2jXtMXpNdILsqyMJ54ieppxuuxeaX+5E6qn4R02ZUkrzQIqOlnnLeW7eDWrTsm2BtyyV2pvDpSz5If9yPxJHtubMxb26IQ+zoaWPmtA6QvWsrxm2uwA4fHr6FjT1iBXOTt4lsX/Re7VzVyx5O3jcWGTmByAF8u8xHMN9mekS+AMPbmi4AAACAASURBVPcYEUVj5TBUFjakD7UY/Mn2+6gypndnn5xdWp+Bd8ozoyt54aeXTVQLF2Cs5ocOUH72dXpKnGZuUo4oB/qH8BRKMaIUTnzmxjQ9EkEqylA+r5vG+AJCPzVExeOL6a1dxMC2QbbUnzbsBow01aEYpm5jFOvKNQM0cRhZl0H7zcuJnLAIPL5nPE+UmB6sqzYQXeSh/MAo6qV9c379+aRmV4oP3vsJnAIz2fp1PfxLTpDgSauMT+28lXRXkKu3vsofNTwyLjyurjzKv3y0BbHg1rpniu7PdS2H+dlnNiIWtP70Cu4JbuX2K5/hveXFrfbEhlTaIG6a+AyLjKNx6lANvl6NxJIMS5bMT3LMyULjxLFaIvsNkjWKyOZ+Qt7UvEWff6Pjag6/sASrJsMntz7Bcm9xE8rXMq95VdU4Y6kj5hApi5Burroga/xa7R1UfrMbo7GeV5ctmpCmImSmCJnza3+4asNhnPXCC8+tZtUz/vFKa5rfR9c2H9bmKI4ZoWLn1HQrCxnzpztpeapw+eDO39lKbJU5HiR4OF1PzXcDhB7bx9NfWssfNTwyfuxNob3c+PZX3bZnYZL83brH+cStT/B3nW9i4HcWofcO89C/rC9ecDiKTMog6THw6DapjEHVy0L1iwO03VyJs7g4d9/ZZrgNHzJo+PeXyFy1ga41HkLe+fudHtjXzOq/2kvyqjUcu6imJDiyuEkOF/6Yd+5L+50BLRxGvB5UwOcKjQWqoRIBj2Fh6A6pjIFlT+qoY0MeI/5c+fsnbJO45UFDETJT45l4cwMLlcaE1ZqyLMJtDsOeEMHuaarHGQZctJpUXQD/8WywYX0dyfVNaJaD+fIx7KFz6/M/zgxcOCMnbD7+8vvwme5xA0NBWrqTqGSKyAGD25s+yGV1bXy85il8YqPPOjm8a5Q3xWFlqIf7r1mLGQ2zsuIgthIyuPm2dBResQt+70pANxyMbMCpoTtEGwV9YzmpSnVGj6nJzHaVkKxVpK+9iKHlJqYx98XIko7Jd7u3cuBULUZUY+Sm9Qy1aFxlzm/hM5Wx0KIJyGSKrlZ5PiiUTWKhsLAEh6Yj9TVY1eEFr57SNIf68CgRT5KTo+UMxebWPfhMjKR9dAyX4TFslpX3z8hDy4nHqfjhK1T6vKhYPG/lPi0Q4NivRKi/oovOBxqpO3ycxIYmen4rSTzqZfU/NML5EhwzIPzwXsqeLRtfqdbaI9gDg6hMmkX/vQ+5N8TPbt/Crb/+HPX63ASAvTWyi/Ufb8dRGktN1xli1PHQb4eIaEnq9MKpa5Qu+PxpQt40migMzcG+vI/4pTqV5vzEOuRblZRf1EfPKg+mHqVslsWiChFzvBx5uIWWbx6j/d1hLvvcDho8wyzx9J355LPAicVwEtm0/gvd7kdpxVE8ykFsB81ycEyNonJ4nGOUEmxHw3K0M84Q5iqy2FbCyWgF/bEAibgXa8QDmiKa8GLmGWC8/dqUVY8Ti0GeiFkxPeiL6rGrwqSqbRaHB+iuaUBfvZzBRR4aynroNwLEF5cRTLRMPT+exOrsPu8vphOLTRsRbA8Nw9Awwc7FfLf/CsoLzKpbfD1c4T+OmWOHmu57DGsZNns7Jxy3M7GM54eXsSbUzVsju9Gxpxjqc8k1TIuoWVf5y8V2NHpHQqSTp19z02tRHXFtbGPXlWxAYNCTJuiZaqccO0YpYTDuJxr1YZg2NWXF5XLTxcH2gVNVTrocNgfbKNfnfrUhhgGiuYk1x36PC1xgXGgsMMGhcDq70foG0OqqydTn8z1ZGDiO0D0aplcLkrEL693nSj3lKI2uXyxi6U9GwcogmSRooEwdZGoftKEu7Dzuz3n72NzIoY81IIvjrKjtAqB66ykOrYgQDAxR5YsRNpMc/KBBR2qqh4pnXx1L/z3hetktcGoeO8Hho2sLpsz5/pu8fOPd/zZhVTLT7zGDxh1Pv5EV38rw4o3r2Pa+wzQbI9OeL7YikfBgaA5Bb3p8UD9bEhmTwGMhlr5weoU4sLGMkXdYVGVTl8xErZV7TGpPOSt/PMrQ6hBD7yyunwEtxfU37+Tg1bVcX9ZKQJsHG4qmo9dUg8+LGhw6f2rVWaIQ7IWqn89hYQkOTrvQGWULz+96zE4/puGxbG2qbWMecZTg6wO14xXE9CBBv5tWYdJxKpHASSaL0t4rvxdZEnPrhuDOmhtDw5T7Eng0C49m4dczbF3Ulvf8p0bWImURtPRU24lKpxdUQKLV0Yl2hgJakdXbOJauJWlMX1c9qKXGAxInYw7pmHsP49+4lqQyC642RIFypOAxYxRj+HYU+AccOHw6nsXfuI6Yo83agG7EBO1oB4Hy5QwX+dv3iM0byvfyhvKiL1schoHymKC7kykxDMTrBdt2y04vcIeQko3jNUTAm6HSHydlG/THAjjO+f1yU6/byMkPWPj9E1ULjiMEfhKh8r+fO+sX5MWXV1D/tDDUorH89cep8U2/eqlf0s+BT9ajpaaWZ6170SF434sXlLqg9plBvmq/E6fAGzJ4aYa7X/d1avRJlSlRbL/uFX62eAUtdW3YSqPXCVClTZNHShe8vgzBrI2jEPkGe69uETJTpB2D0fTpgDyfadF5PXjXbxrflqp0qPXN3s02vi7J8d9ZS7rMoSowwuBwcFbtzBvKwRkYREaN03aNi9fS9vow3kFF/X1H59wDdC4p2TjmijEV8zxO7GfyDnkMixp/lGjGy2DcjzOPX26hoLUxhpeZPHTVP7LKnPjiZpTN2tZPUCna7FKa5xBs1Qnf8zyeN20hdp2HmgKRV2sqelizbeoLaSvhpZENhHQddQEJDmfvAarOEKAsH9vG6HV+KrXkhO0ais/UP8rnGv6XIcdDp1XBqOOjfNJxOSdgGjY+Y3aGcI9uEzDSaLYiJp7xGatHt1myqhtWzarZKYgoljT2Q+PpbYMsNMGhpti4Yk0BfNv6GOgso/6xIJw6T32bETIlOHIhsmAFhxodxdNhoPxerHL/WaVSnw4tY6OnFEoHxyjcfiJt0hErI2Pr876UfKmzGbWrjExIsfjSDhaHpleXTEZD2HjZUfb+1dZxgejrE5rubcM6OTXDrBYIoFVWkKoNYhgTVy/R1Wl6Pn45sWbFGs/sVU3xlSlOffRSZHKqfBtqnh/E2XNg1m2fTypfTfLJ+z6MakrwxUvvp94Y5rf33Ea0LcKlW47wF00PcHf/lTz49CU4ZRZ/ddX9mEVUL5wpaVtnJO3HUmd21HjNI4IeDoPHREVjOMkkoWMjRB+ppm7YgaELKHv0AmbBCo4xDxi9ugoiTcyHh5VkbIykwvZIQZUEQCpj0JMJzen1p/PSSR+NsPLfDmC3LKJjVbgowaGLxvdaHiGz/PTs/kv9m3nmha1IHsEhwSCZ5mridR5MY6Iq5ap1R7DWurW/DW1mq4XJ96SL4qrVR7FWTZ1FDaX8DMWaieyZ6d0tLLSf76blOZPM9ovYvXYJ6wMdBO4tY9F9e3jprzZCEzx6bA1r/vY4qTWL2L15MZeFjp31dSfbJ1K2Qcou/lWerZ1jQSOam3Ei4HNHjGQSZ88B6vbpKEdhL/BVr5sdt7TiOGtUKo0xnEB5DOygB3WGlcHMG3bQRhL4e0wcj4bt1fEMpdwgoXPEdF42VmWG6NUriFfrhHy9xCwPu082kRnyEgzCyHuuYHCjTXia803RMXO8rDb427nn2uuILLnC3aCg7MAoatc+qIgwsC5Aok4oz3EBHQskNPOY2FO2wUvtzaQHfYTqolxc3z5+L3kNxVr+dixTo225hv8Nl45v8wymYM+hBWVMnxalUJk0nr4Y39m1FW8oxaLODE4yReSIxodevR3ZF8aJteLpjXHvrkv4SWQDDdMEX86UyalC2nsroNuLHbFpbO4frxJYTDv5iKU99LZVoCU0jEVxN0/VPJNWOvf2XMre7gbW1J7i3XUv4tOKe14qmXIz4Y45apyL2h9zSMnGMQc40ShyuBXN70Nb2YwdKpCBtxiUwjnehn7SQAdMzfX7dlKp8y7vL151gr7fClGm29T5RzmVCFP9Iz8VPz/JgU8389WPfp1GY5RafWapq28K9NHy0S8zolzDqaM0Pvbdj7H0ZZ14SyX2WwdpDo9S6Z2ZT33U8hJ5JEjtI8c5+Z7lWO/oQteLfzEDRprFrztB9OrTBt0Tr9aypr0Cq6u76PbOF2r/Mdb9aTWI4PT14zg2Dd/ehzwYoTJ2EDsaRQ4dZ92fVbtlS/sH5rTmgn+Xn8XfOsbItiUM3+4dd7Wdtr8zWGkoJQyNBFh+r43vaDdHP7wIts2/4Ig7XvY+vJpld7Vx+LaVjHxoX3GCw7Gxe7Pp4i+AKPHJKFWyccwN2Vmdowla0kLppx+qMjT3c4HnbPkNMiENzVJ4hicObmN1RaZc0rLxDAmx3uIMf1UjEyuLKcfBGNLZ119PdSBGtS86o1iAMk+SMs9pQ6qjBM+ojd19CmU0sd1nocvM+xbQPGzOyX5tK4t0fQZ95TJi9Qa1oSgNgZnrfh0leGIKq6sbI76soKNAoeBHXZR73Rz511ldTmZZHabXg9PdM56gcSGjMmmsSe69Y6rW8WNsGxWLuYFpmbOf/eYO/soAFfRje2RGc9XJK5Z8QkREgShsr4YK+FCFQ5Um4BlRPNy3gSWBAbaEThAsIl5Dw8HxgAoHsLNzxB4rwu7oYl7ub8QXn8FqaoGro14LLHzBkWWsAqCu5/yCZxAkOLDGJHXlKOnuAM2PGuiJM7+0ztAwi3/QhQrONIGzizYwipVTWUwNj7D04STxnVXsv66C7RcvDCOwLhq3bXmB7/3pJQSCw1T45i9XUG5685kIzVVNpzj62zXYvY2svjMIL++ft76dS/TKcqJXtWB7Ncpf6MRqzR8PM1NyB3tryyj7l9YggTQNRUacF1p5VEbinPhVE1LlBGpmPrGofewkw0ebeXzzKvwfynBp8PiMz/VpGa69aRf7r6hnW9keyvUYd3dto/drSwm3JjAOHj+L7GIXBvPpsTlXzJngEK8X0XVUxkJZGUTXEY87ZXCSqTlZNjrx7ACXndUbkTBiOzAppkIJ4wkSrQCsqO1jf7oeZZyh8LSmowUDiAj09Bf99Tnp9ITYCWVZmJ3DhBJBjNG5NawXg60cBp0EmWzfbGCVv5trVhyZfZumW2RLiTCU8mOZGgEjXXB1MUbG0YlbJo7S8BmZCcWsGgIjNCwfYU+4ATsUuABeoZkhhkEqomP5cYPTcvdl06pHjekLlOmag8+wpgz0IipbCbA4byHb0UjbOraj4TWsvNHqfjPD0qbi80hZJ9vRTrZTEbiMESv/5CvmeBmyA5hiU67H8GQTc3rE5qaKV7ip4pXxY4eSfsoOjiIHWrETC38Feja4cRy/JKoqzedj+O2bGWrRqNpvE3mhndTKOjq2+9BT0PTTEfSuOUpF4Tg4wyM48TjO4BBmvjKymoZTU45V5qXsmMOJh5YRiYIRL1wyUtu4moMfikD57EpLlr3go+4/Xxo37GrhMJ031TOywia8eOgMZ88fjyX8fOLHv0Www/1BKoHoujTb1x6aVTqUkJli3w0WA+s34uuDoW8007ZMY+kNrdT5pyn/m0N7tJz+xxrx9yh6r3MLUL3WcUZGqXqxz00P0zNxMA7s76b22w04xvQ2q6EWHXt735ylOu8bDeJ9MoJvwKFju8PSlec2uOGOQzfgPFJNrElx+81PssE/1eNvjKtrj/K9370ErWsjLd8ZcZ06XrPMr41DRO4E3gL0KKU2TNr3aeDvgRqlVMEZw5wIDvF46N8gNGztpNdpJHQozNByL4uvbaMnGiJ+MEIoMUfeSo6DJFMQj0+f0E4EPeiHsJdgR4pgx8yaTiwK8ts3PMpbwq+c+eA8vIlPUn+XZ1xwiM/L8DqL6zafVrfMJLhvumNnyyvJJpbfl0T7+W53gwjdn9qGs0YbT8FeDH49w3XrDmKvFXb+aAPl33sR/40XE93uzSs4Jt/HcMJHw89j6C8fZnjVJlg7q9u6oHDicdh/OO8+68RJ/CdOFjzffNNl9G/TCXqmqfNd5AQglTBZ/Ith5FArQys3wcqiTi9YrfB0p6bfNdhawer/2k3q6nV03lheUHBsDR1j6xXH3AqAT1+G78KsujsjzoE77n8DXwXuyt0oIs3AG4AZ6VDnRHCodJqK/YpTViPlJxxEKYKnbE4804yWEqqG5nB5KYIEA+h6nodrOzijo25WzOFRTGeqekws21Wd5fZ/2yY6rwkSW2bNe0EZy9FJ2gaaKHy6VXDgbh2pomtXPWZUUJeAuvwytmw+jC6Ff1i/23UpP3p5M6uXdvGdld/nMv9x/vV9NxDYfiXNjwyjdr86Z/cTW5Gm9yOXEW2Cld6p37OthOdal2G8GiRZY7Nh0wkqg3Hab6jEt3kT1uLXtuphrvC3DaM/Xs2At2LCdiUQXW6xZEVPUcLDH0zT+boyvBdvJLmo+Eld50AEc0+ISJ/C6OlgguVw60V0XxlmdJnDTd7zt9I+IyKobRsZWBcg0pbB8+QeVGZ22oYLBaXU/4nI0jy7vgz8AfCjmbQzJ4LDSWeoeqaTir1BsN0fb6B1hGUn3QpzYs9tkJGKBCGSx6soYyGpFCoed/PR9OSZ8uTJ39S9Lcjff/Qb1OsjeGcxAy+GtKMznPZjiIPHV7geRPdAhBXfHkQbTTD67xoPrf8OXjGB6V1cMsrmgacvZc3n93DqA5vo/Jxwnd9h31u+yt6M8Ft9n6Jq99zdz1XrjpBeo2OIM22QoLEvyJI7dpO8Zj0DqwIsL+uj5iY379V8lM99LWLvP0zdoTzBg6LR++FLsJZrRWXVrQ7FsF6fQAHNs1BX2t0BVn7rJHZHF9Ykz8RTV4T59Y8+SKURxSfnLi6qaESj68oga99+kF0/X8XK53zYC0BwnKWmoVpEXsz5/HWl1NcLnSAibwM6lFIvywwrrhYUHPFfuRwtowi93Jk3XcU4ygHbQazTg4AoBdYcCAzLRrKBPMrnAa3AbFsECfjRcm5epTNnnEUEuxz+/NAtrKro4WN1TwHwtVPX0REr55aGPbwx+Oq0KqWM0vjW4OX8onc5vkO+vFX/ctFEYWo2huacMaGdUoJkbMhY6JpBSDuzl5eG4F88yvAtGxla6xDWbNqsKHf0Xse+oQbSYcF63RYSdYqkbeAowdAKV6ibjvEgwTwCI2Ub7O5aRGLATygFqSvXMrTCpNrMoIuaYBAvfEM6cvEaYotDBFuj7mppgWc3nRcKBLGFOm069tVSUDVek6K5dnB8VSKizip9uxO0iW5swNtYidne76b3iMdRqRRKc1OoF3LD9dTFib7pIoZadK40Y/RbIe7pvJSeaIjti45ybeQg+nxPKpRDsMthx77llJ+UBREkOAdp1fuUUpee+TAXEQkAn8dVU82YgoLjvf/fTzicqOPZv9tK+HsFBMc8Iqk0dtcpRNfR6mtR/uk9TzB0qKpwhdbY+cOjZ8yGWfHgq8iz5Ry4dj27P3ccHYcDX1tP9fN9/PPnr+eN26dX7cSUwb2PXMXKr3eyNHoYO17YtdWnZ/D43BdWm4cXQxeNBy75Gic2RajRYyzSA/zHcDM7/uYSIodGSLxXkXzDIPWiGEwF8BsZyj2JWdk6ChG3PAT+N8yyh07QdcsSor83QqU3NSPjeS6az8uh94X57Bsf4O8ffCsr93sviNiOc0ngiX2s3lHAa0+Ejnctx7p5eM5qfdQ3DdD7AT+JYR8NjzYRPh7DaOvB6p6Zkf2TG56i9U+qCekpVvu6eCm2lOE7m2h4oYcHPn0x177u4Jz0syBKUfnAq1Q9FULFE9iJ/NmLzzXOuQ0AbAGWAWOrjSZgp4hsVUpNG4VbUHAMWCFGLP+U5HTnFBHXPXYmSygRV3iMoRRimoiZE22uHNcGkjtr1XWU34tjgI67EnBMUF4T0fPfe9wxeCm5hOOpGoy4uPUs0hm3DwVmxLk1wecCWzlEVQpHKUKaF1N0lpkhlpkOXZbNg/EQTwyswUi6fbJCNi1lfUQzXkYzU1cwGUenPVrOaMpDZSBBQ2C4qNVIwjbHS+kG04DXQyYkrCrvn/kqYxJiCQNWiHnWIl6wFKp6OEagdyldfWVo2lR33nAoMaXi4Jmiy32Gha9slG4lKN1wa4pkf/dmVPHTgbUEjTOrfTRR2GjZd05QXreq5bnCHhmBkYWT+PBcu+MqpV4Basc+i0grcOlZeVU99tntaBlF+f4TnK9FnPKYaI317v+9Z4jDyHd+wIfelFMjwrKxe3on5ELqf8saIh9s58qyF9nsc50KrvzYi7S/v5w/qNmXd+Dcl27kjrveQc3LGVI3Onj+bZgDT7Ww7G+HTsebnAP6nQT3ja5i1PHxtvCeCWnWP9v+Fo7+8xqUDj2vV0ilj6V17owwYGTw6DYaasLKZyTjY/DhRupeiNP2xirqbhwtStC1DleivlNDw8kUnVcLfV+opKKyD482u1+Qk0iw8puDPPb4dla2D2BfCDmsFiAVT7cROVo1ZbvtMzj+tkoim7ombJ+pod22NIJdabSDJ8brX9Q91k7P0WUzymi9Y70X/UM/Z62/k8MfPkLPrWHeVfviGc8rMTtE5DvAdbi2kHbgC0qpbxTbTkHB4X1iDygH6wx6+3nF0FFGEfkOchEB00CZObeZsdxAxZzD4nXCHct+NF6QJ6M03lP5HOlKnYjkH6hGbR9lxx0CLxzDeWsLf73kfm5e+tvjVcemI2UbE7yq8tkHbCU4SkNE4QQ8aI7Cq+dfRqeVoj1dyYjlIx507zPupImqDPv7a6l/vhu7Kkzfm3U2NnVkPbmmT2BoORrBLgd992H8F29iKO3Hp2cKBvflkkib1LYmMQ+0k7lpBdeunuqCaishaZtu6hLNxlsoz5VSOHsP4NnLvEYMaz7f6e8u145m2ziJxIRVpJgexGO6KWsuEEFmdXRCnqqHRjCId/smYunCOeA8up1XzaWUoMcy7sx97FonTqKfwb14jCouoTVexWJvP2+odlXCYT05wb6RVjpDdpCBdPDstB8iaN5svrZ0ZkGmJlHMrBLkrNtX6rYz7F86k3YKCo7o2y5GyyjCu7uwZvhDeC1wIF3HZx+5jWCbTuNNbXyl5Z4pg+ZKbzfO7X0cuGkJt6yfuWP5c0eXUfWUl2SVUHFjFy1lU1eE0YyXnniY8kic1s/5ME0Pf9n8SN72KjUPby3bSUbpNBkWtjK55cC7OPVYE+lyxdD/S+LEDcqfMWlLrWDodQm2Lz86bf9CZor9N1r0r9+IbwB6v7GUkeVCy/WFKwCO0RAZ4dC7IxjRFfhX53fF7IqX0fZcE55BIXVJjKuWnX2q8bNBr6qk/QNrGF1hgaHcvyzekx5a/jOnlommM/yuLZy6WlGxR6P2m7suaJuLSqVY9GSM2JGpq5ExbBM6rpqfIEHfoVMc+foaDgTWAG5dHO31/fzxmofHhcfDAxt54ccXEexU1LzaOWvth7F0MSffsQjbC4t/MrBg68Bc8GnV+9fr6CkIngjDiUJHvrY4mamk+VFF4PGdHFh5EbRMdZFr1Ef5r3V3oYsqaoZgdHqp/v5e1JqldFzpx4645+YKprjlYSjuZ1HZMHdv+O8pVf5yCWgeto77CwTJKJsTLzfS8nfP0v/rV/DN2/6Vh6IbePSu7Zj7TjC4bjUsn75/QSPNdRsOYq8Xdt23gfJvvYD/TVuIXV24AuAYDYERGi4rHCcynPRRvdshfCzK4aawa5o7j0goiNo+xJc3/JgafWRCRb8vtN/C6H21kJ03iSb0bxK+9Ppv8xnfu6n7nhcuZMFhWcizLxN6dvpjtECAkWWbUSvmfiZsnWyn4punHW/E6+Xw8othzeljDgzWsuT+Xuz9h89KZW5XhVFXD1ETjJPYVYN3AdaBUYoLPztu9R4bPe2g9Q3PaRrohc5STx9tb4HAxi2sX+0maPu3vmt5YNdmsN2XRwIWn7rkCV4XPMDnW3+FfQeaqXpJR6ULGwTtpiSn3utG+jsvCM+Hyohs6mdD9Wkd87GeKnwvhDjaEOHk0girzJkvqTWEVVvaOP6n21AbRqnRZ//NRVdk6P/wVkaXwOqzqAA4mQpfgmOXaAy3lGE0nHkVMydoOqk3baHvIpPKAxaBB3eOu1+qkSj6k818uvV9KFOhclYc/pMGy/pPjP/+laOoecnhD7zvoWqvoJIXhqrqbFAZi+pXLPpTjVP2hUenBgA6V2+m85oAgS5FzQ8PYA/OvBBZLqZYBCXN5bUneOTWrQQ7qql7ohv7yMySJmqBAOL3oZIpnFgMvXcY/clm+r3lNLf1v+aTJc4nBQVH4EeukcpagLrA+WS12cO9b/wqNoJP3BiHB17ZyNo/OoaKut4rsqyZH/3TJq5ccZhjjy9jzd/vnDZNey7blh8nvVTnxWNLWPO3MWQkxqt/3Ag5gsM5GaTproMktyzj8M313OCfYc4UXHfc+1f9iORKCxOdgDb7mtDbNhzBWu96vMzWuJ2PusAIFdtdd8tzFQAopkHbTRrfvvmfue2Jj7Hmce/4d2UPDlL/by9SnzXm5gZBKdvByo0DcmzC979E+Me6a/9YAL7/843KpPE/8BKBfPa7PDbQzmsC/ORjf8fvtb6T9DOVMEvBEZQ0dXqU91Q+yxW3HuX/Rlazr3MjvhkKDgmHoKocbTiKE49jtbVT/2+uus22FmpgorwGsuMWITBUMoXommuINo2p7rNKQfr/Z+/N4yS7rjrP771viz0iI/el9l1VWkqSJUvCiww2whtehMcwbtyGZmkG6O7PDDIM3dMLDODunmEGPIZxN7YBAw023hrbIG/YErYktFhbqUq1qJZcK9fIWN92b//xsnLPyMisXEv5/Xz0UVbEe/e9ePHinXvPOb9zfEQQzmwTqsbFfetIql/x0MsPcjR3lZ9q+w6tRpX0PMVrS2uRwv0HSQx6Ua3GiwAAIABJREFUmE+/jHD9KDCIprrbp/zDt5DoLcMzp+teN0tGgrlEymXi5ibMahaZmnss1eox/uZDTO6VdFkr/9E5wppSmM9FBwGJfsl3zh1EBxIdCGJZl1u7+hakyhpCYxgBdVQzq6YRAWDS9hk7FqfJPIl9/ipBb+PGc1GUJnnZ4NcvvJv4RXuBUHO2SHR2NMtozlM7uQ9tShLPXiEYGIwMzgoNhpHL4t5+kNCRJJ/rW9C/Y8ujQnSDz4PEgOZfXXwvz57ZzU3VgeV3mHMcTeqS5DdfeiuOFZC0PUIlKbo2ExNJDoyvQNnt+YhKbboToEyl0Id3ow2Jcb6PcHSNCq+uIZobwFXVMFoTjo4hxgVGSzM6v0iPDK1hvEBYmEQ256E5N0fcJ7rawVmj7n4rpOlvTiEey/P862/m+w9d4s3JhUGz3zn215z+91384ZnXseuhdgijmXJCBPy/9/8Zl+5r5Xe/8QBHTseWzakHuKltkMEPVQi14NbEXFHcT9z2BPf8wFmaZZlb7BBYm+uiq1V2fXUU78kk1ngFOVZk9A09jH8oQTy5tt3dGu2/sRQ9qQn636cZqcZIfLqH1Geuz3Bo32PXJ8/A5zPsLZ4jbDAu4R/bTeJf99MZn+TMbx0n/sXVdSYMD+9G/vpVjmWu8v2P3Ebys9vMcKyA1s+fwnu0mZuq/YQNCgKvoX2P7k+fQXwxFdWSkgZCaZLapUNVUUPDDbvNw4kJRLGIVjrSdO3u4syHUuh4yMFP7kY+uvUMB9wAZdWFGb29QDC3GCpEq2hpvxxCiOlZXcPivvXEiFJ+tYwEgIsRaomrLGwzwN3dBBoyTh+G0By1hzlqD/O72R+cs2rSQbhkB8Ck6c3JqAq1YKiSYayaoNpkcSLei69NBmdl4UoUx+2rHLBW39tDGwItBVpKMGRDufbrRagFfeUck7Wlo+6hFlyH/Zk71sgojIyuaB+hwQ8NXGVwPV41oaNUZ1/LuUuaG5D53Q9XvP8qvqdFWaxMiwLU2t1Ta41GoNYxHXetqGs4jF3dUf+L4dHrF7UJAU1ZjEx6WpehHRvZ2R7NLKy1WfyshrG3HSH+wQFek3tmWgA4n1899R6Sn8yh2yVjvzzOoeZhfqL98brjqokCBz89jt+S5uV3NNNy79LZRoEyuPTobnZ9vcqwneYPEgcX1B7SUjDxk0Wev/vPV/wZAUQ8Tu8DeWq3VVChjQpaSWQm2bcOHQAbWW1UApuhr/fQ+ejSxxcarAubJ0A1T13C+4199BntpF5c/XnIs5cxf3M/Z60Wstcxzg6rR1/s5cgnDLQpkef7doLj10Hdp7WO2VEcwmzwoS4ELDWDFQIce+5k63rEffW4tjpabJW0yGvlDsn/deDz0wLAxZgYS9Hx6AXEvft42/6neHdm+RKz2vfgzAWsSw7OPTdT8h1sI8SWwaIP1sSgRj7yDJLFvxhhmvS//k6u3lmeXsxaQpISzqKl1n0dUlIu434SoaP9Kx2K19fRcWwkgTJIXVEzfUKW2m6DzmcxwvFxjL8fv+7zCCcKyG9H3+1WNRrCNBG2HfVHX0rYKARcu9e2WdKMKpdhqqXAVj7zbe+q4uooKD1dSmBJhMDI5RAxB+KxLbESF5Nl9GJFy8Jw2ZTZxXj3zc/wuf94klx+klvjjfWLNjIZhh88Tmm3wB6H3j86yMQxuOW+s6Stladx6jBkz1cD7r/6K9OvVbtCPvHW/8Ib4wv9KL85cgt/+cXXk+yFjouXtsT3ssPWpfyOO+h9QJG8YLH7v55eNHhs7t1N5XAr9riLfO7sthY/bkU0G17kcFXUNRwryToQqSQ6PdX6crNjFlqjy5VV548vxs+1PMI/u/9RoDE3DIBIJhi5K+Tum89x9k+O0PTH38N8/2upvdZaleFAa6yHn6Tn4ZmX1BtO8v037eaN8YsLNn+4/ygHPnaBYHCIADCamhZss8MO1xg9bvDZt/w+v3zm/Yj/loRFfv9Be5bxIzaJIZPcaXtbix+3JoJw26fjrpQ6BkMbguKhLLW8JDkQknxlVvBMKUSpCkqhEzGwV17McL352Mgb+OKzt5HJl/nIic9hiYCHTr2XsaEMP3LrC/xS6zcX7KPLFVoeN3i2/yjdL0c/sPSFMhe+to/z8z+igq6XV25MrIFJPvqVH+EP95T4D7d9ifelCnx46DY+++JJ1KRF4WfaiQ3vp/O/X0JXohVYqAWeMvFCA1MqYoZ/XRlQAC+MdFJ4vhllQtctg4uWUqmHcfgAxeMtxMY8zH88s6GFItcKYdmI4wfxmuPEXhkluHBxs09pRbS8EPDg3/0iqQsm2dLi5TjMoQL50zbWhIvaJnW6thM3xIpjLdGWwegJg/BYCe+JFImLYqZvRhCiRsdQNRezqwO9BQ3Hl56/lWMfvkTp3n08+5u7yRoVnE/nOfbwGb7627fwSw8sNBzh5CTNn36KZinQ/pRn+8lT7H7WZH6nLa31zDYrIDx7gUP/pg/Z1cEf/P9v5N03fY7PfOe1HPnXLzL0P5/g/3noY/xt4RaefP52zFMzdWNqgUXBixE3fWwZXnep95HeHDf9YS8qneTsr+VWbDgmb2lh8N0e5vkY+0+nYBsaDhmPMXR3lsn90P3tVpxtZjgSf/M0Rx+OYhxLVSEOLl7GuhSVCGlU17HDjUddw+G+7TWIQJN4oX9ZwZKuuYg6gW4ZWCQGNcVYksRVhazUZgLVfoDyg6hXhushKnWWv0Lg7WrCbbJwRjzsvkXcUVovr+gVAnnLUao9Kcr7QqxlHpxNzUUmX7+fiYMGTWaZpHSZOCQx3UMkWpfWbSzoPqhCtBuuXbxBa1SthqzWCFUcicDpKlP6oZtw84L/fOUBzl5tZW/JRQcBqcuSR3KHwZMIX0TlNWxFvdVxLB2JBGuBxYt9nQS1mdumqaXIidYBZNKndHMnQVzgNFAMcT7OeIBxMUZiAPC2qqq3PjoIiI8qgriBXdh+n6GRygdoDXrHYKwn295V9baPfJNzlTZe+E+3kPpMHcMxLQCsE1MQkvaRMTpisajbVqkctZy9NsS18g/LjCPicUbe2sXE7R4tj8ZpefL0oje7Xq6Fq+Nw9gM5fu5HHmaPPbJAKT6f3z72eV7497vIGhXuiEUz94c+8FnGghQ3xa5T1byGGELyxbv+kNO3tfJrz72b2q+1s3+wQNg3gPY8uv/sLD1fiEcPgGslqo36S+PR+7oY/akkI6Uk3X9qkXxpRtR1+X09BD96lVv39NL/C1kMqTiWnFyxANB+7DQHT6XRvk9Y2DqNdVaCqlbJPPwSGcdBl8uvqvpuO6wNeqqlwlanruGwRIglVGPB7ikBYD0aCrYvM47wfUSoIRSIsMFZ0pKDaSwR0u830e8vHziWQlFUMf6+cmTOa6fdTk67nTBhg9qcx4VWisGxDF+uxIAYhlC4NRvzbC/B8PD0duHwMAwvPc5iJPe3cnmkCa9k09FXJLg4k1UWH+rmzFgr1lQxxVBJeou5hsateBaZqc6EjXSx2/JoPacvxQ6NI0wTo7Mjag09PLamiS3bjW1fcuRz//tbkJ4m9/yVLZN7rlyXzr8boPWpNObQBMEqjYZyXQ59epLPPbKiHu11OdxbXD51eZ1QYxPs/WgXv93xwenX9g/UUNeh4L2G8/xl9vxeNyL0EBfnrjxbv92Hd7EZvYpMunSosS9snXtrh83D6Gjn1L/p5NYjl+n71FHyn6xT532HTaeu4Yh/8QlgEwRL9fp2ax1lq1y4zvPSGvX9U8SX1/E1PuTaDbXyY/se4h++z/xauGtxTuHwMGJq1TLfARhcvIy82JiuZTFW9B0KgTCtKBY2NWEQpjkjSGPKRblc0PbaONM7LdKHfv42s2joGPUOb9mIZdyDW5XpFb4QCNtekOQxZ5uVjBt3uPXIZX5371/z1l0P0ZJIoP1gYYxwKWadz1bt7tcIGm6A6rgbjRCY7W3odDIqiLhEvRojl0XE45FWY8c18KpB3H4TQ3dnSQyHZP/uJQAKP3yMSvtMUkbTyx72N79f98ElbznK0L05tDHVRKuqaf/WwJz0WXnzEYbubUKb86s8Q9tTJXhsdV2AZDrN0AdOUDi8PeWYbU9A9jNPIm46yCsPNuGnF36Otn+E7F89uTLjMTxK36du4q27HsJtVpz52DFyj9u0feLphtrzGjcd5uUPNaEczaE/q676+9l8xPZ3VW04QqKbMvgtKSytFy90JgQimURnU1E6747heNVQ2pei/PoS5VeS5B6NxKbDt0vMQzP3wKiZofPbRt2y5+W9aYqvq2LZ0TbVyRj5l7KIWR1sK7szTL6+im3PHUcpQWEiSfax1X0GkYhTfF2V/3jn51Y3wCbz4fAnyH7OoLI7w9ve9jj3ps8t2OYhfoLc58wVGY5wokD+k9+jJRbjzB8e58Jb/ojDzgdp/7TdkOGo7srwf7z9s+y1R/jw936ezCq/n80m0nHsrDhmuFaWJBGvu00Yi0qI64SD2b2w4xiAzqZQcQuZTWMu1lymDjoIUGMTc5bAwnGQicSKxtlyaIUqV9G+h4zFEPE613kNUKVy426ENcbPhoy+ae/031ad7C1h2ci9PahUHNk/TDh0dea9qf2kHTJ8Mkm69S5SL40SvnweZ9TFOp3EyyhEVw3buZZ1d50/6mqN5PcS/G+F93PkSB8/0/PIdG/ta4wGKX7vzP1M9qc5fKSfn931nQXbbAahliQPFhj6mTso7lW81S4uOK/rnS3rICD3uM1h54MkvpdsuDxQrL/Iv/vae9G24tDFpWvObQe2f62qtURIaGvGa12mJPiUzzTIxiFTp8m1EIRxC5Ybbx6GGyJdl3Bi5oaUiQS0NS9doHE7ECrEwNUo1pFOQ0tjmU2rQmmkVnOu4UYSa60y9vboxxUz6z9QRcyhcFsrlTaD9ickzDIc13BiPuXXhRRDg/YvtJB6+TzW5WG6v2NQ6rEZypuzDMf1EU5O0vHxp+hyHM796nHCBwXzpz4jQRrnCzmO/vULvPIrJwjfv3CbzcAQioeOPUz5iIMtAtJy7RNBdBDQ9omno5WG5zW02gBQL5zlyIcdEGLTElReTWysq0oKMFbycF5u2zolTqRAi0idLtTMjFQvdnwpIi3DZtfYuk5ELIYMQ4RtRVlOa/15lAI/QARhJNjcYJyxAF5J4qYUZmsVq5Fe7GGIUwjRhkCW3UWrogqhsayQQEDoCGQigc6lqXTY1Jok4jr6ti+Gdl1CP2CpbryO9CntEqTuPozbuvogb01Z/M3orbwymefW5n5+MHtqyZVLqCXfLR7kseG9dCYneWfr98kYCx/ASemSlC5nap386dBrkULzI+0vst9ZaJBXi3bdhg3GNCrclmVq5nND9OPYzoSOgbIE0lOYte2ZYbEihIB8FpFLR02a1oMgRA+NoKrVZQWW64H9+GkOvZyjcqKLiz9mY+WWd0moahXne2eImeayDxYhNH5SIHo6Gb+licH7Q0TMw45trAq8yxrnPe99hOF3pPjh+AjGKnPjhoMMz/31TfT8zVW+/qGTvP7dZ+q6vD73xJ0c+2iBi/cc4vwvDXAycWnJbb/QewvJj2QJbcmXHxL80p6FJXd2WB3qhnVVSQPZYD0prfWMnzIIEd6sG1eANiTrdZ20ZNuvIhpGCDANWE+nhhBRGqlpTrXj3GDjEYZo10P6ioZjDVqjisXlt5siSAiC1jRuTmClvekAekMIgZHNgDOrU3u1tuLMP1uE3Jl8hQW51bPwtMG5WgfjQYJuZ5xd1tiiRkEEIFwPES7vOxehANdDBsvHKkIlkV6I0JpgG8yQtwtaR0VItzqrMhxGc57gYNfibp/529YC5JlLqGIR3T+EOTKjCBXZNH53fl3alxpuiPTFHDfVDteHjlmEx/aCAPP8wJxA80bgv/Ymeu+P4acVVmLtA6BSaiaP+ZS7Y4SpcNn4yYL9UymG33MTk/tnXsudgfxnnlnzvhXDQYY//tKb6Hg85PLbNR+5/68WTBnyZokD7z3LuftbuLv9RWLLlNV54O5n+Yf/vI/OzGUOxur3Cn/nruf50q/fjCEV7+pYurPlDivnhnVVCcfGy9uE9vJLBatoELOtKGhVqURVT6eEVoYUoJpmVGXXVgdrsAIRSu8YjbVGSvysjTIFVp+z/PZrjJu3CA5WsawAKdf+uxVCk2iuQPMq9zdNSrsE5rEZtX6pnKU5Ho8KN66hKM1VFpnzEH/4WWIn74jqG80r1JmULj/Z+T3oXH48QyjeknuBt+ReaOj4J+K9nDjcS6glNW0xGcaISX/VbjUAZAOr5W0q7LvRWPcYh3Ik4YFuZE/79GtypEDQ148uV7AuD8M1n7wUhC0ZwpS93qe1w2pQCqsQuR11beN7MaRfHEUZzZQ74hTvqhJLbE5W10qo7Aro/yfHiA8rmr52dklR60rJmyXKbysyfuIkHccHkZuUrvtSrYtPfuONxAcl+TcN8C/2fWNV48hEAvfeY9RalnaBG64m88SVZSt1b2ei4PiNGuNYAcoSVLvmagqSoYa+flSthpp9E0gDIxHbMRxbFBFqzMlalF21CU18wjPnSJ05R/o1N1O4JQbbwHDE2yp4bVDsTdH0j5nFRa2rIC1r/MYtX4Jbon9vls7jSq2JPV/2cb53mtN7jsO+1Y0jEnFGjzuU9iz9OaySJHUhCzew4YAboKz6WjC/+J3QmjAbw9q/d04/jnB4BO15iIki1uz0WcckyMRWmMa7w42IuX8v5WOtFHtMhLM53eeEgMm9Eucddy14L4hL3LwiPmf79XGXFlWM3z/7Rsb6ZvQ6mY4iv3zkWzSbjfdDmQxjfPT8/QxfaWLvgSH++Z6/x15BU68up8C33mSTPHorrXtWWHaZqHxQcGwvlZyNn6JuzoOyoHA0S6Lp9gXvmUUX8eL5bd8DfUc5Xodai42bb5s5iUqIU64Qui7B4BAMzgTmjJYWRLKxQPwONzaTt7bT/x4Pw3JXHLheK4TQhLeU6D++0J0ghMbZoPMaC1KILzRz9K9mYhLjP3qcgYdyKzIchTCJ/+VWjv7p81z+xZvx/6m5IsNxLN7Hh9/9eXxtkF5E97Es7a30vimJn9XoZfQyoaO5eqdAqIXxtcRAjJ6+LGpwexuO7cLm6Tg0U+m4oCyJyGUwZlUM1ZVqFEx3XYyii7ZmAmcqZqIbCMzPQYEIFSJQ4DjIWGxbV9FsiCBE+EGUtWaZM7GkbYo2wLDCxoR/9RBgmCFSapRa2YRECI1phmBuzn0z6Gf5yvDNXBxvIj8YoIpFzL27cfe2UOqROHJlmhNLBFQ7NP6dh6i1rdzoFcM4Xx05wUg1xQ+0na+r/ZiNkctCazNuT5YwplFWAyszAdrUi4bfg7gg2NuOkVm6koRwPcL+oU0rldMYOzGOJZGexqyFKEsSxCWhIygfbUOo1ult4hcn4Mw5wmIRee7izArWMDD39uC3rKy2lAgVRtmDUEMug0gnMUbGCNegX8VWRdRc1NAwWBaivQWcndgRgDIFybiLZShKNWfJCv5bke8WDjD2+3voeX4UBs4QAn3v6OHEj5/ijvgEu6wGmqXNIm+WePCdjzLwlixvTIwsm7I7n2fLu7jy8UM0vTDJn//L13DynsYMR3B8H31vSBDGNGH8+r8AN6+5/EAK1NKGI35V0/F5d8PTyFfKepZVF0J8Ang7cFVrfWLqtf8EvAPwgPPAh7TWE/XGqWs4hDVVcDDwl+6PsVoiZ170pxSEsZmLJbRGO+Z0eq6eOvY1IaHh+fWFhNfe0nqBAFBoHZUY2QirrjWEUycjp0qAbLAgUWuNWKOuhNoQqISNFgJzbOPTcRtB2WC0tqBLpagF7SL3rRZgSI0hVeR6Cg18z0SFAtMKMa1w3WITKyHUkn6/iV6vibxZZp9zlUAZmFWFqNQgm8FsylLp1Ly9+VliK1xtQGNiw3ooLTFdjSzX0MHyhTVlIoFwHCo5C7dJRz3v1wBtarxs/bGkLyGXwVikp7123S1RsmQDBICfAj4K/Mms174G/JrWOhBCfAT4NeDD9QapbziO7Y/atPYNrunMXJuCIGlM1VOqv62RbyI80I1Qeq6QcGzGIIpUckpIOGMMpBsgvRBlGyjHjIxT0kZ6IUbvMKpYWnk9nJUSKhgroGs1ZC6LTm9sBV4dczA620EItHX9i8ugKc6VH4zhpzX7v9CN3IIzt9Ihn3M/v5tkL3R89uWG0l891yT9RJzkoGL4pIBDjSvN15MQwf/9+Jvp+e8GwyclP//er3JP7gL/7ZeauFTJTm/32s4XsVYQl1hLTiR7efFnOugtJ/jRXct0RZMG7r3HGDvm4KcBubFxKj+r6X1bG9JvW/Be7oJP7OvPrf8zoQHW01Wltf6OEGLvvNcenvXPx4AHlxun7tMkyMYRgcK8unYuDi0E2oRlLYYQICQiFsNtiSFCTdyxoSSi3tSz+lMbSiM6m2Z6lWsdxTP8EHEtqG4ItCHQSqNrtQ3rb61rNVSphExen9HQQkQrKjW1amoE00Cba1dePbQkbo9PJl/GzaVZ38LtqyOWq6GzUDJSCKexVZEOBcmBkMzZIhMHchveydHTBn70oyAm/DmptXafRfIrT+MnTlIJHW6K9/ErBx5eaqgN49o5p40av7jnW9PnvGSpEiGQtkWlw6K4T113dfrVEDqa8q7Fv12zYhI3rku+uFVoEUI8OevfH9daf3wF+/8U8JfLbVTXcNgXh6NaPxv0kJ2Nn49j3XwYP2FHGVUCwv1dyI5WxMBVwtEZX66qVDCvjMwREqp0EpWwUeYmBpqkQOaykdGo14dkGVTMZPjODJV2QdMZRe6F8eV3Wgeskk/zd5ME8SaSr4yxOXlN9fEvpmh5VhMf9lGTi68cZAjlmo1thiglMO2Q4ZMOhQM5qj0hdYr5rwt/0n8vF76xDz+tec+bv8c9qag5koGm/a5Bzv/G7YjdZVqsrbESAvjSyEme/PoxtITXv/k53pZ/dsltZTKJ99qjVNosirskbIHeIluVNaiOO6K1vnM1Owohfp2om/OfLbdt/RXHld7VHP+60ULgZU28bHrmNSMSEoowTqpchVmGQ7vuXDWpEBiH9hM0bfKcWIi57qlrvdRXGOdQtsn4cUXX4WEKtQ4arAqxepY4R6Po0vY9NxIADmw9NxVAsk+Q+0zUbnSpx5MINZ47o1A2rRAOF1FAjPXTXizFqcudHP2DM4T7uzhzd/uM4RAqUmKvUlQH0QpgOXFgI9vM57mrnRz4ZD/atnj+9s66hkMkEozc4lDapWBLTje2FpvRc1wI8U+JguY/qPXyLo26hsPcuztacQyPbnjg6JpwUPoaY6osehhvvPKrKJaxZqf3WkYkJFzsWDUXWSiBZaLjztqlrc5/+NYzGlojah54Pv6uFsZuSmDWNLmXy0g/JH3eYKjSTnN/4z88rzXJxAEHw4PcmVKUVbaa895GVNs1lQduRQZL3/sTB03kLM3BpgTCtSJ/SvPhb70Pc9xk8MHD1FoFP5Q8zUSY4P8790ZGBrIcO9jHT3c/umpleCP7GUKt2Hgcbh7m5fccxqhB8SXFvxp4P/cdO8e7W55eeqcNuK2kL0j2CqySptIhqLVsjltstWyGAFAI8QDwEPAGrXVDD/q6hqN0ogMZaBLB5jVJkb7CGamihaDWkUCbDVxUrSMh4dCMktXI55CJ7kU3V+UyqlJBplKIzrb10zss80DWxTLhyAjuyW6qb52kMpYgMWQTGyjR9e0JtCEiHUqDFHc7VH6kSHUyRnwkRqJRw7GNEfvL9O+p//1J6WKucXOmFaM1mc8/Q+4rDiPvOc7rfulxDsWHyJslXnHb4HPNHPv8ac7/r0cJ3/cP694BcKWG6cG2pxj96TN8e+wwV39rP8lnevmHf3eId99fx3BsANKD9seKyBcvMPHOm6m1bOrpbDmEEH8BvJEoFtIL/FuiLCoH+JqInlGPaa1/vt449bOqQh09qFaRzml4CqMaWfsgYaAaeeAvehICZRsIDVYpiALE89LpjJZmgiO7QGvMUxejDDA9t1+Edj1kaapAXzjv80z1FxFTVXw3C2EaSMdB+prKcBKzYCDDKMtD+CErTLHHrGmqIwmMklw0BfFGxDTDSKC3DdCuS+i6JIYDvtl7mKcTuwAYKydoGgwIJyZI9sLHLt6/JdKDF6N3uIn9IzXU+ASJS/v56KX7SQxIdKiQiQSyvZWwOU24QRIiLcHLx4h3dxDEBWzDcPc6Z1X9+CIv/9FKx6lrOOIDZVAKXV157wOr4GO9dBlh21SPd6PSq0sHDR2B2xrDqCliZwZRhUnCeedTvXM/yV/tpezb6P+wH/nIMwvGUaUS8tzF6O95KXdGJgUt+WilYWxeMF1nUohUgthgmf2fiSPCAGt89X0n0hdK7B91rnucHdaXxD+8TOKVdrSMYnLdKoT+lwm1puPz59GP5jf5DJfmkF9C9w6gXJe9f3IJ9aU0u8cvEvgect8uet/WjpeBILkxD3DlaAbuNZGvaSdIbD+jgb4BWseKqhcZjvkzdK2RvmYm/3XWW4ZAGyD0VOltIbieyZKWgtAWSF+jq9VFu7kpU7A7Oc6EF+equUQzBa2XLoBmGLDJq43ZHfyEH+IMNl5vaClk1cepLrPSmC1S3CZ918NQ4nvRrWvZAUYdt5NSEq9mokOJYYdYdrDlZu/hRAGW0EmFV4dheJ4W5VqZnKmU9bpMbStjMUQysWjcTZXKaNeNtkmnFxmk/vjadSP3cG8f9M7S39oWbg78zMa5BbUEP61Z6UpDmyAzaTAMVKm09oLnRs+DzQmOr5S6hkP3D0WGY94MXY2OEX8ujB648wi7mql0xwmSJsahPShDEDrrO4tPPdPL878VBUSTpy6yPRwVWwNRddHjE9F3mc9FBnSL447FaXk8uvdG7g5JtC6dLu5WLVq/7pC+4tL3+gTcvLI2rpuNkc0gspnD2wRHAAAgAElEQVSZFzyfcGQMHfgYzfnIGCyF0qjRMVSlgnffcfrvcxY0SRM+7PpaEZ54ntobTtB7v7WiRmpWQbD3s1cJz5xb2QfbYpS7oe/HDhAfWdu+Kath2684lurVrGq1JatQGpkk6DjKFPi5WFQORIpFRWvzS67XQwuWnA0Hff0kPh+l467aaDQ6w9jokiFTx1v0+hmiYUHgNQGhCOdtG4SEkyWEZWJkM9vCIyyrktyF6P4bu6W+yE/7kuy5CsbTZ4gdv53N1wWvEMtGJ+Mz953rIcYlOgARj6NT9QyHQpQcqFYpd1roE8UFqzPXtXC/H8MByp0WbbcNYRuN/4p6h5sIv7YGae+aac9E9Fu//iFXgp/SBElNGJfkYxut5Nl+rH2Rw+ExUkqjUg5ecxw15boCMEshhqsI4wZBYmWrEG0K1L4ujPYW6L9KOL52IjhdriCG6y/7RczZ8JIhfj7B1TvjhDa0ft8j3jtjyCt7MozcYmFUof0fy5iFpctJB7k4Q3cmCOPQ8qxP4vLMrFvHbMz2VpCy8bIkQiCyGYwGldmrIgxRheKilUxVNqD/vvjU3/UzxYx4QN8bksRuPsnkfsXWrLC1PmjDIDy2mzC2n1K33NJeSMMTNJ2C2HjI2BGTStfGptHGr0rypwOccRdV2LxV6au2H0c4Mgojo5g93aiOBMqauggazHIQdZDLJ1ZsOJQlqHRPCQArNVhDw6FqNVimAYzR1ASp+IauOLycRfk1FRIJl0p/jvgsPWa5w8S5b4Tx8RT5M3Zdw+FlLEp3VslmK5SH8iQuz3rTMtFNmSX3XQqdjENyHQWWfoCoVBc1HPFMDX179HmXOwPbDtB3TFIlyjfcavGNdcUQFPfGqbRJaq0Kewt/dulB/ulx9OlzpNJ3Uuna2OPHhjXJh19AVSqbLlF8VRqO+cx2taiYQUBsdTEPDUZNYXhqQTruRqA9DzlZvj6R4ApV41YpwDqdwHXiNI3PdR/Ex0IGX2gmVhKY5foZU1YlwDkdp5SM0TFvnFUZwk2euq7k4b8VDYVMJKLU7wYQMWf17sNQkxj0scoGftJE7xFb8noAKBOKR7LEm26m2jxVlO1VyBqUHNkQNq4fhwAvY0LGXNUSVAYaZ8xFVjx0ZeNTS6dFgokEortjdYZjhQ9ca7jCni9PZaZ5wZz3khcm2d9rRopzt75P2hytsvtvvUXH2WGDkQYy39Sw23MlccD5iDDEee4iVrFEOns7hVtXPdS6E8Y0Q3dJ0DG0ub3U3mvNts+qWrDxnl34XXnMsTLq/EV0sPxDSAYaoxoiNIQxSbjSzn1TaCGigoW2iZFJYTBTQ1+YJjKVXD41EUCrKP1w1rnLRAI5K3NFK4Uam1joJtEawhDhehAsfFhr04hSatdoRi60RtQWv8Yi1IjlUm0bGOfViBAgpUJrseIOgGt4AhtzrCBAuy6xsZDRK0ncpMLJV+umMM8nVJLBsQx+ycbOuHQ2Ta79ykWAsrfmamiHhTRuOISg9127OPTgy3z/iYMc/s3RhgLU0lPETw+iq1WCI7uotq8uY0Gb4OVt0DaiLY4I24hdKcDL55G5LP7x3YTW8j9Gw1VYpy7Nqa7L/t0M39E03dvJqmqaHr0S5aXPQ7lulKYsFz5wZCYDLblNd+XsUB/LCEk4HqGS264D4GpJPnqGI6eamLytnb53WcSTjeeXeaFB5psJ2r59lf4H2vHfWlpR5tUOK0DfKDEOIaJc8ngcrwmOZwZ4KrWvYYW10KB9PxIDXo8QUERCQKE1aIFQoOM20nEQ8Th+wkQ5M4F4xOLLfG0qLDlXf6JjJl52JvtLWVHwVyZm3AnaD6IViNZL9yz2vUhMp2Z90ClRnYqZKMdEeiGywZXCqwltGaiYOb2SWu+fjiE0aov6+1eE1tF/Si/sMikEIpXCmNJb6fECdqEZXTKpCY3l1F+FhkpS9iwqNYemoobRccxq1ATJCw2KNYegbCFCf1ukcW8HbpisKiOb4dI/P45/SxnjDHz9/3wdB/trqEJjvQFCW+If7UYEGj+9NuIyezLAKPuomIm+/Qi+bUTFD6cC6CLUKEcS2qv7AkJHMH5HC8aJGRV66lIZnn5pRrW7CKpURsxS2QtDIvJNqFSMwXuzFG71SL2cpPtrBeROrGEO4ycyDN8JsSFJz7dKGO76FWT0Q4NCNYZm0wTCa4ooVdGFSYjHIJ+dablsmwy8cw+l3RoZgPQEzjjs+4KHl7bp+yELo04683gljng0R3pEU9gnGP6VIwTtHruE5kpvM91fNWgf8pAX+ndEt2vIDWE4sGxqN1X5tye/zG+/9D5Sn3k8mnU3eABlCWr5NaxwpkG6IUbZw2+K47bYMyXYg6gUigwVqgG31fxxr30obUKlfe7+ZiVOzDDQ18qsLCbICwL0bNGkNDCnYieVTs09x87zWPkIGGJjnljbyGVWy0vajgwx6DSjLGNdq8FqDUG4iQ2+1hjteYSTk9E1U5lp5bc2JaW9ms5bBym5NlXXxn0hTeyZS8TTSQbv7YDs0uN6nknbKyHJy2XGj6XpuaM/igtpgSyYZB+7QtDXT3gjWN8dVsSyhkOXy7R9xeEjL72PzifczZ+iCQhSFtqSBLF5LicZBeCVkpGqukGMgTHanjLwcjaFfRZqETtXbTUxXnczYsoNJb0Q88yVubGS+WiFLkwiai5dj6Q5NXCMnisBxsAYeh1TikUyjk5sL/Vr5lLA+DfaaZ7QGNXNKeG/XRGJOEZ7G8K20bNib8ILaH9cUTnbgRFCJgAtNFffeRA/JQhzXl0DnYy7DN6dxDqeQXVX0Vpw6UoLybM2SR/63r0Hu7ib1m9c2bSmbzcaN0w6rqpUyPzFY2TEBs2SGyBIyMUFhALUKtxTQV8/oq+f5L49lLq7Fh2jlhfU8jO6Y7Oi6RjMzOlEuACtowJ2gPPVq7RPXcP1dlIZsg22meFInSuQ2t7ljjYHISJdUXyh3kP4IZlvnCY5q4Ciet1Jzv2UJJ52iROtKpYiE3PJnByY85rTa7PrbycoHM0w8WCJkmfSdKoJdgzHmqFvBMMxzQqNhq5WiQ1WUDELL2etOg13wbh13C+rzXk3mvPQ3oLXmkQtdUXmDa1Mgbs7jx2fMSaiUIpa2C51rTbK8FZriMnyoq4qHXeg0dIim4mUiGQSwzRR1dqchIRqMYbzSnTd3X0u8XR91f8NzxL3vTYM/JMH8JNR0oEMNYV9FtKqNZROO38brQVeS8jwnVmChMA/l8aqCIzi8E6MYw254XQcKyEcG0cUJjGzGcLb9q2Z4VgP1O5Ort6diephNXhFlA2jJ2KgZ2b2uXNpnMGhhvQt60k4OQmLFKgUhoHR2dF4TarNxJBRarPSyKujhOMzhsMYtNn354MAnP3pdni1G44l0DGTy292SB4fp+ZZeK6JlAGOvfr7s/PAMLXdJpOXmtj7hQBnuILuHVzDs351o2+YdNxVIgwDmUpGFTxXeB2E1khPY7gKbYjI6AjQRmOrCqE1Rk0jfUVoS5Qj6u9nCJQ9k47b2ElGabuz8VMGic4OmDIcWinURGFBWfoNYbHgfRiC7yOqM+ejDRmtQLZiID0IEaGKznsWytYEbZnpv3dYGmVBNl7DNBQVeX1lPITQ2EaIbYSMJUJqLRZCJXD6bGgsyXKHG4R1MxyyOY93rAdly1XVpopdrSLPXUFkM3i7W1C2JEgY6AbOWIQQv1yA3kH07i7KBzIbUsKg3G7g/tCu6fLQhqvJf7eP4NKV9T94I2gdFaGc1UdFppLQ1rz1DEcQwvAoYbWG9ufOkGVHjbMfiDIYzOzOamMzaG0vMPKjCYKRGEfG2mET+1fcaNxYMY4VIiyLIGlMu6iE1ogQhNJoKZZdPYhAoao1jFgsymTS0b5CMW0EpscTAm3OGy8IUdUa0t84t5FywHOiHhkymOorMPWQlrEYIj5Ty1UHwaZ0GtNBML0iAtC2jQhCkAtFi5uK1mjPX3S1Zjs+dtvWEFFuoZyRRTFcGKvEUWptXcVJ2yPZ4tGrm1D2eiZPv9q4QbKq1goRQuJyETk6SdiZp9JdvyC225bAjB8lNCV+KiqMKH2NdBXKkShL4Iy6WFdG0Zkklb2ZacGfNsDtyWE0p/ATqyuqeD3YRU3zc0VkoYIaGgZpUHrrrQy9ZubHGx8U9PzVBYKBzfUP62oVBocR1wyFFIim3LZL590MDEORsH1CJal61pYzIKIWsPvvagSPprh60kLdXkRep7tqh/XnVb3iWIAGWSgT9PZhpBPM7qQwv4OdFgI/aeAnZ7lUAo2oqTniPqPsEfT2YXa0w+7MnP29rAlZc3rsRrrkrRWGq5Gv9E9rPIRpMrnHoOuO/ulMlYvn26PubYvN7DfwXBeIFoXATKUWP4fNXoVsMQyhiZkBvpLUfHNTf/BaLOyyKZTCev4CcqJAuuW1TJxc4Zh6ZvYr52VYbdXy7OvGBi0tb5iSI2uFNsDvbMJMxvHzc0tKS18TG6wg3BCvPRmVX5+/v4TQkSgto/IigN8Uxzp+hCBhLSr4E1ojgsjoaMFMLat1xk8Kqnfux5rchfnylUU7ijn5Kpff04FV7FjwXu6Cj/ONZ5euibWeaI2eLMKskh/CsaMy4DuGYw6BkhRdG63FphqN0qEshX0msRFN0wuTaMdg9OYkoSPo+I6EWTqOlTBWiRM+0YRdgIkTAfmeCWwzxHmVFTiUJ45SOpQlMVBFPHV6c36XW4wN7cdRa3egfWHzTulr5MUBVGESK35sUcPBvAe/FgIvZ+Ll6nevE6HGrAYoU26YLzZICMaO2ZhVi/bhLCxiODpyRdSbSovuP/jdTvb+g7NpN2g4Ofd8ZTqNSManS1nsEKGUoOatTf2162Fyt4l7T5Hq+RS5M5IgaTF2q0LkPHLn0tjPrW7cSjnGwa8VES+eJ/iF26i1RZ/1VWU4hKB0OMvAfYLc6SStz5nr+7vUWztmdo11Mxy6WiU2VEWbyz9tZC1A11y00hgTZRIrKBeyHMIPo/ENgVm0EL6C9U6PbeD0hdAYQlP1La6+0oxZkAQ9Lrs7xnBbQ0o/dBOxYRfz2fOoRTQZG4rvI0qVVfeQ0I4FtrUpKxbfNwgHEhhVgd8aEG+qLupmMQyFITSBkpvTo+M6iI8oqi+nSA4KRKgwaiHJSw7BcBx7rPF7J9Xr0feP7fh5Rdu+UWzHZ+S2NImuE1TbNWkzxJDb4Km2DmzkgnJHADhZaugSaK2mRXPh+UuIi2u4MtBqugmlEBK0Igy3zoypVHPY/RVF4vFzXPnQEeiA9gMjTPbY9F3KcnSwZVEx30aiajXUwNCq9zea89DatIZn1DiBa9L+BKQvVuj9wSQ0LeweKQQkbB/bCCm5Nm6jKtAtQu7UJNmzBiiFrAUIN6T7m1HWmbw02LCq237kBQ48GaNy72GGf9qhJV2m9A6fgpK0TF2f+bGOHdaWqGLzDWo4jFwWutobWk00ykZdKuGH6Mv9qHJ5bQbUYFY1Rg1CJ3JTLfphNPhKMlmNUS7EkZaiNT+JlAo3axDvaCWcSmSKmQExM6CYTVDb30xskf7UYrJcv7zJWlOnnPyy+B6i5m2K2FArgV1SmGNlpJ+c08nacy2CiamKlh2QTUSrESn1VNxiw07zuhB+iPBnvp/pjo9KzUm9BnBrNmrCRguNmZvrcpHpFLTm8TIGUmoMqcjGa4RKMjSRxivbxNIu7dlXl9rPmgyIDTs4BRVd0x1WZzjc2w/yyk+CFd8aufQrwRuPceS/2PDUi2szoIbcWY/YqV68Q10M3xZfIFLUSiM9mKzG8J/PcviLk1R6kgy+P0VbU5Ght9cY/KEUydzcIGZL6yQXP5BG+wvjOJnnWuj6rxNrZwDXkXCyhKjWIrFhSz5qr7tRKIE97qH7hzCrbcx+VIbDMQ5+poYMFOd/LI08oHDMkGy8hhuYVNzNj1+sNeJKjMN/XSJMmJx/0EE2z7hti687SO9bFUayRnt8RljphQbJbyU58MgYfW9uxn+g/OrpAKg1sSfPsfdcFl2uEq57FYgbWMfhpw0O7BqgJzmx5DbV0GLCjSOFJmdXMWXIhJfADUySlkvKcjE2eNkbasFLyQ7CeGLN4rxCg+GGqIkCRq2tznYapQRGVWD0j+LELZSSWEZIT+viLXiTtkeyc3FFbn9/F8LYJsIrFaLdEG2aG5oWDUSlakwZZYbN+9KlD9ZoGeH6SDdJGEowI3fMWqebaqnRCQcjm0GnE4RJG+nNXSlsBNIHY7iASCUQoTNncexmJV27hhcYBaUFdlFD3yDORJ5izSFmBSSs7TdxXA2qXEX4QeRO34iU3G2w0l03Z+6Tl3bT8uUYflIw+PYxdmcnOPf1/TS/GHL+Hslr73sJQ2zsj2Y9DJWWUDgQx2m9BTdtLHg4AQgpUJYgHXcZPl7l7C/vI4xrcpk6Jdl3WBOsuM/lBxKY9x2h2hMwW3aqWj0uvL8VocDvdLGAmm8ShJJwjWd9osnjlQebkG6eIK1Rlib/nKDlyY29B7wunws/2YOyNGZnGdsOUFb9Rmu2EdL3+pDxYzdhFwSxL+Uodwj8u18d96+68xhjJxKkrwQ433pu3WvP3bAxjkZQow75r1+AlibO3R/DSxs0nQ5JfP4J0p33oO7d+henIQTUmgW15vqXUhtR7GJ3+xi0r9Gxr/WYXnCwLT5l2cDzs+wADkXpxYl578VTLpxw57ynlMBTa7+Sc+I+3OQjhCYfdzGlojC0UMPTMGJ1a+ZErgq5KqbUZOK1SLgo595D013+piZalhGyd/9V9D7B4Pe66PlagcLRDIU7tsmK93oQgmpnjImjGjCjLqDreLiohfzWfzaum+FIdJe48sGDhA60Ng2SMD3O3CtIdd3D5E3+TnbGdeL1eAx84DjSW3gdW54rw2OrTN5fR7TnI8Ym5hRZXJIwRHs3jtCqOhkj86yNVdZUsoLQhqYLK19xq1yS4u23EdqQvuRija2uW6LWgqpn4fomyXDuPdQ73ETi6TjaAO+OEl35mdib2+Nx5YEcbpMm5/h4N2AcaA5ak3q5QCdZ4gPVBQU3X62sm+G4vfMK6l19AEgRZSLcc/dpuHvm369mtBYN+dGX2m5P9yiqa+HMJNSCEdFOy+Nbr/qe9r2oOu+rEDlp0v2VQdQrlzF6ulCpxKriPV7OYeANGpnz4KsO+VUbDnB9E9e1kMG8kj9DDrv+/ALEY5za3wZThkMIzZ5dI6iemTIkEwvWcTce6oXTJF6Mfk8b8Ytaz+C4EOITwNuBq1rrE1Ov5YG/BPYCF4H3aa0XD7xOsW6GwxB6QQxjo2MaW5l6RmOokKY2mERbipbuAilnoU/1moBwAUpS7obMD9+5wHBIXxN7qW/TCyveKAgBxlTRwCBswHWkNVppCNWqkwTMakj6rEMQjxMbW31w2nUt5OU4TkEQu1qc80BUmYDCvXsQChKXDXoLXYjdFbpbJpa+77YRIhDEhwRWWVNrEbhNCj8jCE8expyoos9fQtXmlevfyPpx63uoTwEfBf5k1mu/CnxDa/07Qohfnfr3h+sNsr2UTq8S3Msp9n/Jo9pmM/zu+KKGYymk0GTuGGH0loVF96pVm92f6sHaMRxrgmWEpGMuvpKUas6GKM7N4SLdf9YHKkRkM1Er4FUQTtrs/2IF86WLqPJcUWRXzxjFf+IwOZLk4Kdc7Feucv5n90LL0lmU2wnpQ+d3y5inLjL+I8e4+hood2kuvj1OfChBz0QR1de/aee3njEOrfV3hBB75738o8Abp/7+Y+Dv2WqGI9Ri289YGkVLUNkERmsL4azf93JuKm1pvKyJnxCIJUo8TNYcJosJpKFoyZamUyiF0FEar70wPlAwQkqdeVoOH5h+TZSrBAND1yfwe5WitCBssMChtjTeriZsw4iEkKs+qEIXiyjXxUwkYJWGA6EJ0hZWvinqsjir/pJthOSTFao1C68phjmZueE6LYZxEyubwfA0sZGZmJtZ0bCJlSU0110ws0UI8eSsf39ca/3xZfZp11oPTP09SAPpOxtuOBoxGjeKcQltwchtGeTNGSpds5S9y3y23J4J+h5MIA2PlsziAr+x3hzdXxe4WcnIDzMngLkUCdtn6IerDL9upvxH5sV2uv+otKCw4Q7LE05VAgCWXW1YLVXO/6SFKDfT9S3InN7c2buVdXnlXTHMUid7v9yE/PYzC7ZpzpbpfZ+B8lKkGri/tgvK1vTf52DcuYvmUwF7/6Jv5k3PJxyt697f6oxore9c7c5aay0aCL6uqeEItaAS2FSCmbxwKTQZq4ZjLJ6NsJiRuF6jce08PGViy4CE6W2OIRJTJUgAvYIZWzZeIxuv3xJVupL4iIvQNhON+NdhUbFh72gXoimLnOVY1dXqdO2wHZZmJamTlhWSyHtUEjZBbPMDypYVYrWXcXMWfspi9rrFDw2qfvRo6GwtYN1gKnFtgNekEAr0GVBDw2g/WL7qrTSQtrXqYp8Nn9+6jr4oQ0KITq31gBCiE7i63A5rvuJ4+pkDdD7CdN/tSotk4G2j3NI6sOj26/FA95TJM08dJHtaMHFc8drbX8ZYwnCtJ9KH/Esu9lgVN5+D/Ws3tt1d5sK7kihHkU+vLrMGQO4tc/bne5B+T/RvV7D77ybhyRfW6lR3AMqjCdoeMcmOBjjDW7tMTF9fno6vmyhLMPCWWqQ9ugHRAkaPmVRabiVz0cP+9vN1jYdxcC8j97Sh1jMDeXN0HF8CPgj8ztT/v7jcDtdlOK6pa689/JWWpC4ZpP768Wmfeeb4Ec69IQ6ty4+zGPUMy/z9rm3rhQapi5KOR0bx080EJyWr9ARfFzLQOJfHUBevYN9/15z35sc5FrtZ6q0YO3KTkGvMvVQvptKVL0ynWwJMVOJUn8uw0zh2bZFlg+bvDhJeuIzZ3YnOJDf7lJbEmDDJf+sViMe4em/79QtWr916W03XJqDWpqi1Adqm1arfayNoTjFxFEJnndcE6zi8EOIviALhLUKIXuDfEhmMvxJC/DRwCXjfcuOsynCkzhXo/+IuLrf10HnXAPsyUW6+FIriMQ/5v9w9veJws5EAsB4DlSyXnujBGZu5s0pHPO676dySKbyhFnjKpBZYmDIkYc4N7k0eCVBWM6WDPuYW1I0s9iB3Q4MgNDCNte2ytpK6S44VMHiXQbr9nunXUv0B8W8+vzBFcYcbEtXiMfjO/ShTYGauYzU7Mk7HE2lqOYPCIYmX3Xq/w5Vg9Y/R8ZiDsgT8y80+m9Whtf7xJd76wZWMsyrDEb54hvaXDOTNh3nlcHracADcd9M51LG5UwtT1n8IDhVT7Pt8CZ48BUS1nYZ+9i6CYxKrTjeBWmBR8GI4RkDMCKaNjC0Djh3tpbTfYZftLnv8rYIXGNQ8C9uUOPFwehWykf2dY2ZA+12DqNfMfId932/n0BNJ2DEcrwraWieZfEsMITQtidV/58HgEM5XrpJsb6PadgAvu4YnuQkEl64Qv9y77se5sUuOqBBZKCOf7+HbV29acjMdDzmyb4CcU+Xpy7sIxmIkOkvc3nmFi5PNXHmlFbNgMHlQE2s6SeLUIMGVXjJXAp546tCCdqXa0DR1FziYH+HM1Tb8iykQmpcdPWcpLDyB9AXK0pyeFZi2CpLW8bGGm9tsJJahCAyFaUQzs400GNe4JvCaXRQkyIWUfuAAseFdmM9fICyVkScO4bYliV2eIHz5/Iaf50YxW+QXKrnVxPjrwkQpjj6bQhtQPAyx9OItjpfDyGTQe7tw8wmCG8X3uVMdF7jOGEdwuY+9HyuBufQwwcEuLv6LPAfbRsj9bYKWvz1P7wcOErynnysXWzj2exOopMOZn3PIt08SfKKbxJVeEt94gaOPJaNCfrMQ8Rjn/lk3o6+tIp9Oc+RTF9BBuGA7lAatomJws98LoxLoW4H5sYeYGWzJLmsde0YZ/6BDaTDFsY92Ii/2cuWtefRrCsQebqPl3MUbVgcipSIVcxFAseY0phDf5ngDSY7+8VV03Ob0L6RoXaXhoLudK2/N42U0yt7ebqqN4obuADg7LU1X6y9ljWINdyzDK0aefFGhS2XsgubMWCvmuIkoVqJFhR/H9S3iEmQiSlfUizUpCgLsCcGVkRzJAuhyZdHUUVVzt/zDbLbRuPb3VtSvxMyAWCqgmrWp7M4QN3bhNmm602XGY9vb/yCnBJZL6TBmV4q9nm9Gmxq/M4etNNra+IINWggMQ+F7Jn4hShWxsktUJDA1YS6BckwwNKGSjBST1CoLy6+LMRvpFljMLGjDIIhDGN969/SWRbOxDc5Xyepax2Yz6N0dDbWOVY5J1zcloZ3GLvjoo3tJ9wZUPtNMR0kRdDahTUnXt6JtnAkffWzfkuNpIcifDnAHEsTGfdShXQu2EaHG6BsmHB5ezcfbYQlaciUu/09ZtJ8m1bI1Vm3Xg5SapOMhhKbs2lEjp3koJSjVHITQi77fKEbe5fz7HMxSJ53fDUle2NjrpyxIx12u/g/23jw6juu+8/3cW1vv2BcSC/dFEmUtlmzZimXLjm3ZTpzFzmInMy9xJm/yMieZJC+TzLw5SU7OG3uWl5lMzjuTxePE8xzHnjiKY8fjNd5kKdZGiqIkkqK4giD2HY1eq+re90eBAEiCQKPRDXQ36nMOziEbXVW30VX3e+9vHUpw6K8L+BGDyz8WQbbeKh5NvXO89s8TIKC1Y56ib+B8J8Wef7w1aVEUF9ADQ7e8HtLYlLf0MU38uI22SnuQYmPLN6efsDFzHqmBYJegouaq71kLO+1ip9d4r6+xV+nTHbI5opbLnp7Jpf9rLdAmGKnEquWmdaFQ04mEQmjMRf/FWmu8YDeyuVWgafnQVsCNmnjRTe44pCy9+6PjIONxlAW2VBh5ifnaEFYihizsWvWQ5liO5v7l+lULBYf4mI968cytbxYCGYthpFKoXP6GcFahFLIY5AaVgzYCnxDvrHAAACAASURBVKbQQWFCCHZuWoDwBWXXTBW3nkd61Ew/8Yb3cYSELNxd4NKv38XNFjbhQt+3FmqyL8h1lJJkCsHCw1fV9V3kZyJ0PWEQnfRwpjeRAGiZyI42UHrdAofaNpl+9wEyuwTZXp9k3kEWCXx/FcLs7uLyP9tPrsdj7xc09teeX/7l8Bj933DwnfIaPs0diDJ9TGDPCTpPuEhfM/Z6m0K7ovlVaDmXW/8kq+BHDMYfcMh3KJpfg5azOayJBfxijbTCDYUjpBxudo6tlSi4HZFXK6+9p2cSem793ULBIfNqC7Wb5has7Ire1nSxk1mD1mfH8C9dxejbjU6UWXZECHQ8euNrNy9RxfXVuWTuIMg754kArmcgvcraz3UyTupN4/zq3qf5+Kn335Dn68/OwfMv3xwYWTIp635m7nQwcxA/eRXtulhHjlJoFSSHPORTL5Z1XiuVwjp8jHx7kKMkn3qxhqIsN13kcEtoeOEwDh8gfax9yd9k5hSxEwP4Y+uWY9k2rk20YJ2P4kU1iaMzNMeClZXWgoGBDqJXLfKdPrsOTSxVxa01TMNn4n5JoelNtJzLIb5/qj724BXCMBSW4eP5Bp4vUSmPofftIjLTTepyvuzOffgKsZANquTGo2BbiFwBcnmwLHQiuiQcwvVpP6XIDSVJ7wPjwAKFDp+J9x/Gt8FPeWxaNmfmKXzlEH/Y9X76X6lsno99bZau5zpwZj1UJgu+T/vLeRIjFtGB2bIne1Uo0H46R3zcJnZlvoZEY5E6eEwaXjgyh9u49i4NxmLU0qzJoWutUMPCwXCE/q+kye2OMtIXWRIOpQXxCxZ9X5th4oFm8nvNmhUOx/DpemAU//WCsa93s+tZo6b9HZXGMX3idpG8Z5LOOSRaskTfPRuYxj7fRFvZwuGjpqZRRTcoXWJb6GwOf2wcI5WCWGQp90m4PqnvnicxN4/5oQeZ2w+RrgzpxwJhiUpNsbi5KcCfmKDzj6cRUqArXI7cP3+J+MUB0Aq1uOgwnjhJXEj8TURM6kIB+b0XN32enUzDCwcCkMvCwW36W9QSfspj5s4EhSaBZd84wRTaNDPHmsjuFiRq+LNcTySUWpDr0hTfdg/XK78YeQ/zzJXAlLEJ3KKJGopiZgWFbo9YW/nlMSqN50sKvoG7GImVz9lkrqawFgSts36w+3I9RNEFw0BH7KWdQkms8FMI20YmkxCN3JrP5PtozyM+UmT+dJJCsyLSn8bzDIqXE1hpQb5ZYbz99SgLxl/quiUaVHqwZ+zG3YS5q5v0G/oRPsSfv1K9HfzNE7vWoCsw2VfqPJVme4ocbpjGF446pLt/mkyXjSE0rc5ylIoUmpa7JskcsoiaHjGrRpx569B0bIqxQ9bSA5GbjHH0T3vgxU0KR8Zi/1dcImeHGPzwfrw3ldbHfSsoegaubyxZ5/wph8N/uYBxbSLwb9gWIp3Bn5wKJv3u9o0Jxwp0IoqILaZm3+YczlOn2fdinIWHDzD1T8FzDfb/rzz2pQmu/Gw/8z9WwHrK4fAfXkLfHF2kdNA8asVLmfv6uOPfvkzajTD2O/sxa3kHX2/Uxi28JqFwbAFaacyMZnhq48lymezqkTMFLNILgZNUKQlC05TMkoqU3mZ2aXwrMtjX6064UYTQJJzCDe1vB4smftRCOg5Gaws6GYeZ+XXzbsyMwpuI4prB+Kw5A3tyBn9yGlmsYM36NdBakM/Y6KwJEZ9IooiUq0cprXTpCF8gZzN445OYogMtBNp10Z6H9jxkwS2pM6BwvSWzTfCCCH7WOVTl85DPE5noJTsRR2Yl1sQ0amoaM9vPQs4iltZ4YxMlJc76juSO+AhzXowR++C67w/ZCOGOIwRAKzqfmSE+nqr4qWVR40wXUI7BxQ+0kLpj4/3EV8tgryZSKoqtDrH9/Vz94Q6yr8vR/L1OOv5iZk0/SOz5SxwZ7LjBhq+vbm1vaKUEqeMRdn1vhqn7mpl5l4/tbCC8Vfn4k9OImdmlz6oyWXBL2z0qrdHFdRoOrYF55gpH/3gXwtfogSFULkfvF6/hP5XEGBvHK9HmLz3NeDHFgu8gVB0skUMqSigcW4HWiLFpEq6/HCopJdoKYlqE6yPKjDgSuQL+0AhWLIb52NGKDbmaSKlx4wZeS4xMr88PHLjI8+ePIZNJdGFxZ6IUqlC4YdnuT07B5NQt5xOWjfRudPRKoTEtvypCaM9rOD9AZG+yLKuCdovolTqhfFR+g/b2Us1ajoOMxdDFItrzAr/STb4l78pVuAIbCV0QnuZavpmsZyPd2kicaxjqQIdD4dgi9Nw8ougiYlF0UwK3I8bwmyMoG7qfdYkN7Jye38lYgZFHYhjZGM6uBaYLcYqHclz+1TuWHOhWGnr+1wj+hcvrnk97Ll3fnyU5mFx6LbPLYPoHCkQTGzfdrYUQMHWPJtdxL/l2jWHU7qSpbZOZd+4n0y3pPFnA/PYLFQuJjp8Z5bX/didCQev5wQ2JTsg6NLxw3PzMNHLh0Ju/zLUWfKt88ddtzIZWkIpTTJl4xzJEokUK55qIDVRysLVNwimQOLJsUsu4dtCedEWnuWsTLfjfT5R2Qq1Rp84SObX8UvS+u5h6IIaOVzZhUkpFZE8atQfWLoyzBQRNz2//a1Mye1gg75xnbi5J23dkxSKJvIFBmgYGg39X5IwhQGMXObyO8BXmTBY8H9Ucx4817gbGmdEkRly8mCTdY6LWmDXMnCZ5zcNa8GA22EnIWAwRiyIiEbQQOLMuzok4vhUnMlW+zTpkdYzJOTr/MYUbD3YhWgrmDymc3oVtibxSCY+xt3djP9iFFwlqfLWeyWGcfA3temu2LL0demEBsdIn5NjoWASURmRyGGlB5wtxFkaStLyar2ipkZDqUQ95spua6WXRR18bRedyyCMHGlo4YhMe9hMvE93dTbZ9N8q+/arAymhiz17Cn5rGX7wLZCqJbm1a2oxYk1l6vxEk9gm/Du6UOsMbvEbzp0cQi3kNwrbRv3Avxd7tGU+0OU/mBwvkpKanZY4mO8e5Lx6m70ICkcvje+7GZgytF/Nglv0VRioFESdIEpycQuXzRIdGiF1PzquHGSmkLtjUTK+lwEgl0ZHIkqO36igwci6i6KEdCz9irmkic6YKJC7EcROaQlf5m2ovJpF7evFa4+h1PqpvCXRvF2YijhqfRGWz6EIRkc2jTQMWK/eGgnErs9kos2NJrCkTI3Njp0azt4fivs5bv28F9uVxvGs3lfdW/tIiWytNcshn/OyyH8SPamRPDsuuvrGlWLAQQxG0CxeTcbSt6Rxb/P4NA2HbS8l65aI9D5nNB4EF/uIHX/E3CKkT6mBa2JRwKMfE3dMRZDsaW2SX0xpjbBZ/dByjpxu/r23NtxsvnKPvXAz3zj1c+sDa1UTXYmGXQa6tEy3BX2O3AeAmBWMPNWHmmuj4nkBdHsCfnUWk08imFHS2lZ3s1ejMjifZ80WIjC/A4MgNv5t7Yy/jH8xjmDfOhL4n6Xy8l/jNwrES5ZP4+iskn1wuLuje2cuFn7Gx2qovHGra5vDn0siBMYQhg+9fLzaHMk1kMgGehz+/UHYDMpXNBg3MoOabmIWsQcP6OJSPLHhoy0CZEsoVDcXy9rmEJKYlpFh++NZjcTWnLBnU3y9vpGgTPLO0o7UBflQgtF5O6hJy8acyN4WKmHgpByNjI8fqs2HVqsmGUuPbBsqSyJt6TngRQWtThuhNGfN5zyTbEaNpb/+tF/EVamISlc+jMhlY0VXSmmjBmm4jqxZr+AqNjHs4EbfifpDrCYArkxxlPI6IxRbLhBhB2LZhoLUq36xUAcEQpomIRhEr7tXrvTaEZSOjEbTnoXK50PxVBWqk+MGalCUcam4eed5DxKJ4/Z1LzZg2ivAVRtZFC4GKWeib6+ysepDA62pGtKbwSmgk5d1/mKG3RvHiGh31IL1FJrWbMFqaEKlkYKqqgHjMH0wy8jaFPeVwcKIdPVt/4byrTc6tnfMM/UgSORnl0Ke6YGZm3fNYUjHxSI6Z13Xf8jtz3uDgZ5Nw6uwtv9MDQxz8VBC2CsGuefBdTejXb1MpF2kgU4nAR5HJleUwrwRGexvZe/pQdvB8CaWJnx7Du3IVubeXzJF2nJkixolXg2jBkMqhqX9TlTAXH6ibHGva8/DTaaTWJWWNKkOCCGz6NyS6acBTCEmwpC9lPyAXuwZG138rQLHZItfvgrm934awrKDxzgZEQwsBpkQLcUuSoBcVJLoXWBCJbelhXS1SkQKpngJDTjNeKoIZiaCK7poraUMq+jpmuKEZxCIjMym8pLPqZlZlMnDmtaX/C9Mk8voHmV+RSCikwjTV1kRiSQHSXNx9b6O5wrHJt5p4kWAM0oNYPIowTXQ8Qq7NQCiLaKldCEMajjVnnPy77kN6mujpYbyh5dIOMplEdHeAbeHba988xaTF+P0mXkzT9oomObickKUNgVps/VrSbmOH4bbHGHlTBOVA1/MusSvLu4rk1SLqK00k0xqmb+0FXe8kEzmuvL8N5wfuZ/cTGcTTp9Y/aJNo3w9Kw4wtl4bJdhhMPVwkltrClbWQgTnIXhHz7brbtrrXEjL7mrDb76bQbNVDKaU6RtS/j2PmsIUsQuRaAlb4HUUkgteRLKnnuBeTFA/naG3OkB9uJzm44peGQNXSquX6orJGvjc3aVK4O0s8ViB3sZnYleXfOWMLdI4tlhxJLyBjZXaUq1GSTpHkvSPkPZOFy+0kn96Ci2qNeulVoiu63cZfd5Sp16fQyS3svCgFWDbCuuGCcFMJlq1Cy0BAsx1GXdjf6546+BuvKRxtZ4pIVyGmyy9/bc/7pL4fpehESQ7VZqSHMTFH22mHYspkocdAWesfsyGEoHhoN1N3RYhNKJLn50oKxbXnXaInY7h2jJbJ+iihXinm8w6Zl1uxZwR2k8b/J29i5g7ovE0l2mohp+bpfLqFYnJxFyJgfr/C6V9OJBQCLCOoi+X6BkptcuWhNLhFtL/isyqFjEbRvh8UOdwGAREanDlFZKKAOZtH10qP7kaj3oXD+uZJgJIrZq6GM5Vn1/MX0Zks4sAe3PbaWxl7V69hDg4T2dtHtmMXyqrwlkNIpu+MkHk0Q+50gsQlA+GvHwIaJAkumid2WM7HQibC3q/kMF++xMC/OEbqkTE6hcbcYuHwhoZp+cx4EBEHCEMifu4+8isCuKRUxJ0iUmjmchHUZresWgVRTIVls65wHGQygfAVvuttWxOi6HgB+ewrqDChcEeztlf1doLhFjHn8ijbDKKh1ghT1YZARCIgBNrceDEr4d4UeVViSOwt58kZOGMGzizIhfwNZbaMZBLR1oLXmUJXqd5WbFyxcCFObFRvqBKu8BTalOT6kxSTy2Y9Z84nMpyuFataxdE6CAhQi5NnxNy+ikgrk/K0J0iM+mTOLScS5mMa9s0Rs93KLBaFDAJTVgSeCMMIxEvqoE3rNiX1eXGTaM8udDaPPzW9dtBCRweF1wUK65y6ElQ3DlmfOtDjssJx/Ll5RCaHTMThYC++efvTKMvA7Q/CXcpJEjQyRbh0DWlIONCLnyivtJwzZrDvr8dhchp/7sbQVb2vh/EHmlH2+sl9ZaF8Et88Q+rpWFBPKB7dUHSViloMP2JiHVoet3c2xb4vNE401Ua53k1wy+tOaU38W2c5+Mzyzrl4cBcX/kkC1ZGt2CJcRCOIaKQyJ6sgmS6LfGsP0QkX++kMKnv7dr2Fu/tR/3oSrQXFj+3B+G4oHOvS0EUOtQ56ChRMRMFFGgJtSLQUCKURvrphtXQd4QNSoGXwfrRGequ/d+mYvIvK5dCGgcx7pXVJ08urRCPnY87YOLMEojE1fevHsQy8uFi3lMhmUOk0Kp0O6glZ5oaEQ7gmwg3KVlzHLAYrcnw/+Pv5Pta84NpES8XHbjsubYksxhabiZaunw6q5UZjBVpjOYTQ6wqG1gKlBUqJTTl0hWVjtLWAEPjTM+hCYem7vI6VSmBNdZJhUUwEyNgmEgmvJwSuxjaXDxFal5xrIHTg89GAFZq1SqYeAhA2V3IkX0BeHsKwLXRvVxB3P52B0cm1K3F2tuN2pTAyLnJwFNaoz6NdL8gj8YNub0YJwgGgMkEBwciLVzg43oFcyN+y09gO/IUMcoP1iOSYyYHPduOnllegxtwE+tooynXRnovKKvZ8fhz/O5X3IU0dS5H+YZ/mWK7i514PXSyy+yvDeMdTjDzcgvvOAraxvn3fU5JMwcbLW6DKN3PJPT0MfHAXvg17vziDXi2R8NoIB//KREUWHycpufb2JOrBxnMex0Zdoq+OovN5/PzavU7slwcQ/74fFFhnBqjN0JgapMrCIYT4deCfLV7pZeDntdYbivXeZD8OP1h5SQOjsy0omZAr4K2T7WsmkwilkUUPNTtXcmG3lau8UrneNW7NhZrWwW6owl+YWO1JUf6a2/vbcuZG0bv51Nrz8M9duM1ABMK0gt1eGRE5qcTrGfe3KWxaa7xLV+ASJPY+RLZg41vr3y9FzyCbt9F5A+kVy/5qdcQhu9tHRxR+wlnVp6SyWTh9bvkFIYje/RBz7vLfTLhie1usChH4SdZAK71uyRIz6wU5XSXcQ/7kFPKJwDx181mFaQYVi33/hiCAkOoihOgBfhW4U2udE0J8Dvhp4H9s5DyVMZJrBaOT2PMZdHph3ber2TkspdD5fLCb2GbktQm6nqHihQeF68Pkraaxrcbs7mL0h/fhJgQ935pBrbJqrgeaT00hVFtJAQwRDTFPY+YUxuB42c2GxOgEe76cQJsC60qJ59Ga9uMzRGabll6y54roxXtBRiJgWUuVGbYC445DpI+2rGk+T15Mb9m9UXz7vQy8xyQ2LOn71AX8sfEtuW4IEMz7USGEC8SA4XXev+oJNo/W+DMzJdUVAm6xEW83/tg4VOHGrRVTpW5JMf1Gl1Rbhty5BE71k7Crgn/2PImz5zd83GbisfzJKeyvT234POqlV4m9dONrPgQrf9sGZ0Wl5pU7kesVFFZ7bRMUdiWZPGbcvpCoBqOYIPLS1rTxnDls89uPfYFPXHoYvpCoyvNXr1TTx6G1HhJC/AFwFcgB39Baf2Oj51lfOKSB2bcblYxvfJQ1hMzk8AeHNtbvQBrwhruYO1B5v4G9oEicnUK4Hpk7Osm3rG8KEhqaT8+hTp3F3L+X2Qe6MbOK+D+eD4T7dsfNzNP2dBtuooXo4PR2+1fLRjhOEMlXqyiNWsisXZxQ69uaC4UQQa8WIZcSAIVpgmlub+2qFRRbbKJ3H0Gmy3ieVtDyaoH/9OX3ExuRMLv2YsDs62X8nX1oA7q+NRKYLhuZzUVVtQshjq/4/8e11h+//h8hRAvwI8A+YBb4GyHEz2qtP72Ri6wrHMIyyR/sZKFn2zssb4roRJLo+OSGbnRhGAw/nCD2jsqvhgZHm+k12jFyiqvvk3Tum1z3GE9JJv6ujbZTkDnawexPpclOxLnjtdY1d3veyCjt/19gJlHe5hy2q5ZC3yJkIl7bvUw8H+Gt3wb2ev/5mxGmibRSwHICoIzHt9SktRZaQLbdJNfWQmw8SWSDz9NKrG+/yKGnLLSv8Nf5exUOdnLgF87RZOU4N3wMp5GFY/PVcSe11g+s8fsfBC5rrScAhBCfB94MVFY4ILhhVBV9o9IDJ+0jPCgm5VJVzspepIxjtCI6rhm/0IZoKdLTOVuxkFQrVmS+L4FRlJAs3NJjYjV8JZnsFrQ+fC9zey1ijkvWVLdMpEZLC6I5hc7m8McnlsKnN4rZ14vb18b8PhvLCPpYbJdoLCFE7QqHIRGRCFKpwBFtGEE04GJUoFqn1pRWGl10g14z131/NRDGKnSwQzZzy/e+NVdcHmM5KB+VL+14c77As+f2I22f/XONF6m2xVwFHhJCxAhMVe8Ajq99yK3UxFLGLGiSp8bQs/MYDx4g3VPpYlHloT2Pti+dof07CcYe66f44wbRCglHR/MC6UddXC3oipQWVSKFxnnDNFfutnGcWZK3ERv/SB9Td8dJDno435krO2pl+i29TP5QHicyT2uJY9zRCAGtTYiWFDpqo6IWouAjswVEvoAeHltbwJWPWlgMLqkBwbiOUJC8kIaLKyqUbmG1XnH6Inf+fgcIEbRi3pKrbiPV9XE8K4R4HHiBwG13Evj42kfdSk0IRy3jz87B7Bx2ug9vhe3RV5J03sH1DWJOkZi1sWQv2/Bpi28sLFcITXMst2X5FG5M0NU6j1VC3sR2ow2x1I5123q5CwFmsDW/3h1TKh28Zhil+SluFgylgqjF61+B7wdhs3WOkUoh2luX2ikIz0eNjq8qRiqfRw0M3vJ6o1LtTb3W+veA39vMOWpCODxHkL6nC+F1UUxuTVTHZknnHYrPthId00zer+g/NLbdQ1rCODdI19iiqaq4PV3ktho/GcFNmJgZD2tm6xMVb0YUPUxPBRP/JlBFFzG3IgJRqy3vJ64lpA8mMXuOLr1mTxcxTp4re9cx9+47mPvQAs7irnlmpoWDf9KyJX1Xap46WBesLRzSCGy1m4zoEHrtQAFtQL4pqPW/2SKD612rUnhKEpnUpAZd5g5Vx7RWriN6I6HRG2U7neNroSyJH5UYxcWOidts6hG+3pwP4DrKR2+xUNyMFlBISgpJiVDBMyZ8MDbRSyfXLvnfDj9D66Lv7PtzB7nUdAf1HYKzc1hTONSb70YZgkLz5jYm603kRlGTvJzDyBbJ7EuSKyE0tdxrVYq4U2TsPp/5gxa6tzor3FqcoGtxTADmQtA7Rhb9bReNRkVoiE16RAfTQTjuJjK+O5+b5zPGu5eCbqyMpuvc8KZybhqGOrh911SEuYNBY+9qT8ZGUWNeGkFNTWO3vm5TwrFVRC2XPQeCMN1anUx3EjLnInNhxE21sWeKqJfPoTYpzvrEaTpP3PhaKBqLu7k6mE7WFI6tWr37lsDf143saqWYqgm3S0nUgmBYiSLjb+kgcbCF+KlhvGtD6x9U57gtUWaOBoualldzNeHTaGSEguiUjz3nBru6Ow8jMjn8a8Nl53GErEHDllWvML4jmD0cB+JVa6TUqLQ1ZZh9t2Zq3uFApgtjBwhHrtth/h1BRFpkNhIKR5URCuKX5/DPXkDcfZjp+1qITqaITEyFwlENtn89ui5rCkdsYoVTToAbk3hRUXFB1IKq9sJoZPJFi8JIDGfGwFyYRxMk7nm7NtmXQwpyHYJYDeyqbsbMKfzR6OK/az9UuO4R4CcdzF1duAkHZYhwgbfDWVM44t979Yb/e3fvZ/ZQtKoDCtkYczNxDnyugH1xFDUzixaCyUf7mHost6m2skJootEZZA0KR3Qow/7PB0UCzXSYmFhttIT5/TFkfz++BQ3br7hGqMFH7hbWFA5/PugBIRwnqOgZRqvUHNoTWBMLeKNjGM3NmG2t5DoEu9vmtq1jX7URro81XUZPk/XQOvjxF8u4GLJ2y5tsEFlUWJk1wt01GAW1agM2LYJcK5xVjgupPHUwzZZQ5NCGuw+R64rixkN7Uq0iEwlGf/ooc0c0sjNLaz0sW2oQMZtGzaeRyQS6JdUwwmGdGaB3vHXtN83O46+xONyqHKkdTSNEVQEgBcVmh0xnTfjRQ26DME0W+qHvzlE8JSn4BobQmFLVRPRXvaBdF5XJBDvsBsKfmoapEpqKrVFEMhSNkOuEatCAjL7SSdspwdxeQeKhCeL2zig7UglEMoFpWeDY6AbZbZSK2duD299ONmmhzJ312WuKOljnNVxsxE5fXCstaDovaP70M3SecCm44dqgZIRARx10SwodizSMmapUVHsTs4diZHZZYZTjdqI38bNFNNysstO301Jo5vdB5CfeyOwBScwMw1U3RKXFougicgV0YZP9K7YAOTVP0yXnluWkloJ8m0WhTgqQ1jv1sPhtOOGoJ6pVMLDz3jGKx0xSho9TByXRGxmRL+KPjgXNnGo8KtG7NoQxMnrL68I04U13UkiGYVUhAXUrHGtFeNRy9MdEOkFmPA62oqNrbsn/oLVAaYGvBQJKdmrLiM/C0VbsXSm8RHCMbfjYDSQYwrIRlomwrOrsxrUOdgZ+5cOXdbFYF6IBBJ0iV8kE10pjzheITS5PF/acW/M7qJDqUbfCsWaZ9hoVDYDiuRR3/OUUuf4mrv3TOPGOZcd1zrXIuya26ZF0SnNod7bNM/qhOFpJ2lLllVKv1VLp15GtzZBKoGWVTCW+gqlZ/IVMxU9dN6KxFspHnL5I/OLyjkO7XtAKN6Ty1MHtUrfCsdWYBcXEXJxc1KIpml+zK17RN5jLRtEaUrH8krlIaYHwQOQKGAV/1ftDa4HegPJFTI+etrmNfpwbqGXRABBCBBFOm+wLsyZSIAyJKrpb3iipHlD5PGxRq9gdTcPkcWwDtWhqSj5/DWeqi7kDTUz/kKSrKX3b946MNbP77y2MoubqD8fYs3eCrGtRcE28fXle/dVdqKiiPTV7w3GO6WEaPkY93DlbiD8zi0gvIFPJICmvwmjLRB3qRRsSa2BiR1QYDqlh6uDx3xLh2KgQVNJ3ISoUquYNDSOHhmkp3M3Mu9b+s+mcSeqlCUQ2j3y0HwBfCTxf0pTKkuqcuWWVL4TGMnw22ktQa4GnJBowhG7IMiO6UEAXCohIlZyzhsBN2fiOxBy/6RpCIMzgW9GeW/9mp5Dapw5usZrccdyOckQjOuUTvZZBprNbZpONtOW48pPdCAWye7H8t+UhBZgVdlqPziZxvp/EzGmmHyqyt3eyouffCQjXJzIwG4jC5I1+IuPQfi5/uAvf0ex/fB594vQ2jTIkpHbYEuHYTrOTM11En3oVfwvt1l1NaXjrsilLCI0lFVYVMrgLaYf9Xx2H8SnSe49Cb8Uv0fh4PnpoFJW51Tle6GvmAz/6JPucCf7i5I+SOLHK8SEhFULQAD4O48hBtGXiJeorjVQo9g5CqAAAIABJREFUiMz62PMe5kQaf5WKn1W9/irffNUc0HVwk1Uc10Pkgt2jjjpgVW/944wu8NnvPIyKKA4Nhg2jQraAOnim13zipt7QAaxRirlGERriF+fRr17AVzq0SzcYwvXwxycAMHZ3o6soHP7ZCxz+3RgAOperh2c6pJ5phKgqZ94HAcW4xLdrLMxpBYarsTIaoYK/uPBBZnJ4O6CtpYz4ZA63Yncn8eKN5xhfFSGWq9dWu56U8lHp20fQbTUyHkffsQ/lmJgXhvHHxrd7SCE7kDWFI/HEOXAcsvfvIdNdu350Z06ROH4VnVs2JfiZxjcraC3obJtn5MMJlBa0JDefAFjryYAA2rEQ3Yu7YbO+zKibRezt5eJvSvZ1TJL+b/uIfT4Ujoajth8/YL0OgLNzCMdBurW3khV6cWfhacysj5qbR2XL6wonk0lkcxO6WMSfmKqbBDAhNFJonIiL1gLLKO97WikUtSwawrZxm6IIXyGzLmIHmiC1IYhHi3TF5rlohpEQDUkd3Na1u40ogfiYS/T8BDqbw8+XH2o79967yH14lvmLzRz9zybe0HAFR1ldxqZTdHwpgp1WXH1fnL0Hx7Z7SFUje08fA+8xiExIer+VwZzfeZnM4uoILf/vQQaiR2l+aYjGN8buPGp47bZEycIham/TgZl28a5c3bTze6FH8ofH/oaPxd8X9GEogeuJdxCUMt+uxDs/a9LywiSMT2E9fHRbxrBV5FsN2g5MM+k0o+0tiNi47j+poZ2NPzuH9c0TWBCKRqNSO7fbbVlXOLTrEb04iT2V2IrxbAhjYhavAg9113NZfiX6z4mNaTqnz5V0zFwuQuG5VmJjmun7FP2HxmrazNMIpC5kGP1mO+3zGiNTnlmyVMye3RQOdWNmXMTpi2WbQUNCGpH1dxzKx7s8sAVD2TiVWnHJp16k76ng36V6N3IFi77v5TCeOU2x6QE4VKHBhNwW4+IQPQvtW9KZT3U0M3UsgjNj03o5CqFwhGwFW9zJr1zq2sexnTi2x8R9SRKd95HdrWjd7gGFVBQ5u0DTpThWxkPndp4vJWT7qAfDRSgcZdISy5F9t0dOCbqs0NrcaHgDg0SGRkEr1A7IBwqpIaosHEKIZuATwLHFq31Ea/30Rs4RCkeZCKGXuvetRz3kRoTchNZot/K1xULKR1g28vA+vKYI1tXJhi1/vwVTxR8BX9Naf1AIYQOxjZ6gzoqJhISE7FSMznbO/koTif8wzNh7+rd7OHWJEKIJeAT4cwCtdVFrPbv2UbcSCscWEO42tgGtwfODnxoKpw3ZBFIi4y4HEpP4Tu2WQNo0ehM/0C6EOL7i53+/6ez7gAngk0KIk0KITwgh4hsdYmiqCmlMii5MLS6k2prBsbd3PCGbRk1Msu/PO3m67Q3sOjNRcgRkXbH5qKpJrfUDa/zeBO4HfkVr/awQ4o+Afw38zkYuEgpHI6HB9Q3kYimSnbzTEb7CX8iAVhhNSXSVmgeGbB0qn8f47gvEKT1svt4Qiz9V5BpwTWv97OL/HycQjg0RmqoaBJXN0vM9j/zfdnHt1a7tHk5ISEgNorUeBQaFEEcWX3oHcGaj5wl3HA2CLhSwv/Y8bdLA/6U3oo4KjB284wgJqVuq/9j+CvBXixFVl4Cf3+gJ1hUO4Ti4P3CMhR6bljNp9PFXyhhn42DMZIi80M219ijWwXTQJnYdtBZcm2hBTdnQ5LK7axarwr3Hly9Wg0XFKoTOF5Dzt7Z3XfW9hSLaD/7GOpNDeGv8vX2/arkaxqH9zDzYiZVVJJ44jz9TXun7kJ1Dtdd7WusXgbX8IOuyrnDIZIJLHxL80hu/yac+8056T4gdHaXiXxyg988mEN0dvPorHVCCcHhKYr8apeu5IpOvi+B1yOoJR5lUKtekmjkrKpPZWM2oxfvUn5ws+b2VZubBTh78jRM8N74HfakLQuEIWY86mF7XN1X5CnPS4tvjR7Dnt2BEW4UQmD27Uc3J279FaxibxJ+cwmhrhe4O9GKdJLctirZL+4al0HgxTb7VxIvdGJ7r+gYTcwncgkkilaM1litv4pUGZn8PqilOsWnjh1dqsq+6Q76cCX4bFzpWVvHc+B7Gx5toLcxt2zhC6ohGEA5/bp7DHx/B/+smdo9eqkg12lpAmBaj7+tn5k23zw7WnqD/i01EvjRF9o0HGPgxEFZgChKGorW5tLwZKTTRO2aZ2mvjRFysFSXYMwWb2JMJmi65DD/SDPeX3rlQ6+X4CyMR5+oHe8kcKxBLzSHLnMDDLPfKknjyAvpyF63FefTAte0eTkhIRSitOu6lK0CD1f+XgnyroH/31A0T5fXJWAhN3jPJdnQSb2sl22HS1TOBIRUL+SC2M7JGjaqVE7AQmtZ4FuK3mlmUFthZjT1bRBY3FqtwwwRvGBTaNHt6SjDLlHrOMihFeMoWJ2kgbQtkhYMBlUIVClXZmaiFDHJ4MuhdXnQrfv6QBkOHRQ7rkpUTmiUVow+7zB06gtvh0iMVw2PNdH/VRvia4cd89vZPrHuetYg5RUYfdpm6J4rZWf+lu0v53OWKk3FgDwt3taNlZSPdjbwi/sJVvNHKd08svuUYlz8kMKcsDv/pyNIiLCTktjS0cNRgd7RKY0gVCMPKsjgLFi3PjoDrMfrmvrLPfX3VHTG924rPyvdtFVoLlN66cg7XExVvvu5qn1g1x5nvN9FGZcdgZiWx1zZc560kMrttfukN3+Tb40dQqVTpBwoBQgZRcg38jIXcSsPuOOS9d3L1Pc1YGej5/EBNV6k0u7vwezuQmQLqwsCmK56abTmufrAHoUB0lb9DKFUMttrfkPdMpl/sILkFvbuUKZi912XPngkGLnXScspYalHclgVz+Grdm0dbTs/zqc+8E3sOdo9dopRgaRmLMfPjr2PuoKTrWRfnq89XfZwhNUSjCsfsHSk+9KFv89zMXopPd0ANC4dqb2HmziTRySjRq8ObFo7drfPwziC8rBGbNxVck+5nfaJ/X/3JSsZiFH7tHtgDiYsmnX9xAl1c/H60rnvRANAnTtP7QrCTKjWwRMTjjL+ryP/9xi/y7/gp+r+2s0PgQ2qPsoQjMVzgz59+C+acyaHZMZRl4z18jMxum6ZzafSJ05UeZ9nIdIbEUBxrroCuQJLXTog4Eootmah00aX5omIktouOSz7a9RpzgtzoZyoUiL8c4Xf4ETovNG5CZ8jq1MMUU5ZwGN8/zR2vJEBp/Ll5jKYUF3/a5Bff/B0+/dfvoO+kAao2Ety8wWGs0XHw/YoIR0jl0G6Rpi+8SPPXHHS+gKqRe2a78efn6f3TlxGOjc7mUI0opiGr08g9x7VbxJ+aXvGCwpw1eGZmH9YCtVX2QvnoQjghbQbhOMhUCmFUryamiESQLGcuas9DzaUbrwufNDAO7EE1xTBGpvGGhld9m0qnYf2iBCGNSKMKx8348wsc+sQoxcfb6R0daJgkwZAAY1cX02/ajW9vXbSVldM0P3kFb2R0y665FRgtTbz2S50cff0AQ5/bR+efjDSmeS6koalMHofy8S9cBhosSXCns5hwpxIxCs0CP7J1wqHSgG1t2fWuI0wTYVY+vUlrHTj+pYHf7PFQ62X+Z3Jfxa8TUt8IGtjHEbIzMI7sZ+FIC25MoqwGbtV5HSEQdx1iYf8G8i1KxJ7zcI6fR83Pc+DTii9/6230nZkN/Rcht1IHt0QoHDuElYmE18uqKC2WalqtFi3mtcaZ22OW1+5rtZu/DrSn0BFjfo9R8bFGpiTOyw56fh7jOy+QgpJyOkJ2HqIOFhOhcOwQbhaGq6910XTGILtb03TfJHG7sk5ooSAx5BOdLJLtcljYHTabDAlZlzqJqgqf5h2I0oKmMwZdH3+OXf/okXcrv34QCpIX08gnThIfzNXFwxASElIa4Y5jByKFJrtbk3/nfcwctm7bVMqcyZK66uDGBPk2uaEaUVpCvitG9I5DZFvtCo28ssgCxCYVZk6hWhIYdx4m0xQ+EiHbS+gcD6lZmu6bZPqYiWX4JJ3VzVTqtUskLplwcC9jb2nBN0o3/GsJs4dsZg90BIJTg/4NZ17R/OQVtOsy/9aDZLqSFS+gGBKyYULhqAJCYO7pw29JYkzM1nSBxduxWsXbcqrg6jKr2AqhidvFdf0awrYRyQQqai11Piz9IqC2Ppp2Y+igj7kuFDCzCiu7bLn1bfBioiYFr6I0wPPUaIQ7jiogo1Eu/nwv+x+5wtWv7qXnv4zVfCmRm0VhNYEopwZWtetm6SP7mL47hW/XgQhsApXLEXvuInF72aRWPLiLiXuj6Lp7QjaGjMW4+JEe9r9lgKtf3kvPf63956nhqQPhqD/nuGFQbFY82nGOYpMOehbUOPVQGHG13YuKWeRbBG5S1OOdUjpa409N442MLv2YczmMokYWWfqpdPysjEQw2lqR8XhlT7zWtZLJ5V46gDAMii0rnqeQkBKou/WUzuU48HiBx4+/i73nM2gvbMdZCepB3LYSMThGl6eWJlkVMZm5K0W+rUK2KyGY+eC9jP+gS+Ilh57//nJQn6pKzL//XoYf84i/ZtP/Z2fxZ2YAUNksBx4v8vhzi8+TH9Z121bC1rHVQXse8smTND+53SMJaWT8mRlYnFwBZDyOte8Y+bYKec+FZPaw4GNv+jz/l/gxhGNXtajh7AHJ77/5C3w0/l5ELLr02bTnIZ84SXP1Lh2yUULhCAkJWRWt6H7W4/fET9PxGuhsrqqX6zpR5GPRnyB1BXT6SlWvFVI+Ya2qkJCQ26M1zleOs/erQV/xatessv7hBHu+GVzLr4OSFiG1zc4VDt+n6bJiqGkXXqdLX88UhgyrB4XcBt8nOlYEvRx55cYl+ZbSAgd8G9TebozmJHp0IvBnaA268j4Fo7mJ3BsP4cUNUidH8S4PVO1aIVWgDoR9xwqH9jyavvQyzd+MMPH+w7g/IUPhCLktKp/HeO4MSWPZx6Hv3M/YQylUCcLhxgVjDyYx8wk6ngSq6Ainp5vZX17gge5BXvmju0ldHqjetUIqTmiqqnFEIg5NSbyIKOkPUU6SXqlU89y1dM31kC4YOY29oMGrzgpZFsHMaewFBRuIItKFwg1+S1ksPd9BaDCKGqOgEX75CxQZiSD29KItEzE0hj8zg9ndhepqRc5n8QaugVKkFxJcWWjFKKz+/QrHQe7pRUcsxND4jR09Q7aPOilyuGOFQ1g24z98gKk3eFipBZJr7DauT7DlTrKlTNDbMYHXmmgAOLOK1mfHYX4Bf3q2KteIj/o0HR9GZ7L4C5mqXONmrAVNxzNTiOk51Oxc2ecR+/o4+1sp2jvSxP7sEJEvPcfoj+wn9cFhrp3czaH/mEYPDHHo/9mLirSQunyZ1aRR9u3m7G+20tU7g/nnh4j/7bPlf7iQiiLqwPCxY4UDKch1CPbsnaj6pF4rE7TWgqxr4fnLthXTUMQst2bGKD1gZi7oN15Gjo7wFx+8NT6OteDjD41saYa09ICJGbyJiU2dR9smu3fN8GDHVZ5NPEAEKDQLHus+w591toNporJZePEMwKqiAYBt0bprjrd0X+SJRAfVT0EMaSR2rnDsQDJFm/z32ml5bXnCnDlo4r91klSksI0jW6bQJEg/chBr3iPy4hX8yakNHR8bVzS9Og/q9ss2ObOAV6eJbuLaGPLjh3g63kXb8TF8oPebc/zt2A+yZ8RFz82XdqKRCeJ/fojvJR+i/fjk7QUmZOupjTXcmoTCUUeUW9TwOkXPoO20i/Pl55deMx57kMmHTaA2hMOLCeb3GFhpSfR8DDYoHPacj37ltTV3E3VgCbgt/tQ0sc8/S4zl3YQ+cZqWE8G/S/1s/swM0S88R5Q1diUh20K1N/9CCAM4DgxprX+onHOEwlFnDAy1YQ/ZFNt9du+d3NCxjuUx+gaLZNebll5b6BMkrLCoXUhITaDZinDcfwmcBVLlniAUjhpnpWNdaUHkskPPk3km745Q7N3Y1xezXCIPjaDeuLxziQqNFLomI6xCQnYi1XwMhRC9wPuAjwK/Ue55QuGocW6ezIutiplDDrlOTWSDeSdCaAyhabheRRqc2SC8NjKZR6udJYDGnYdJH2lZ6h1iLfhEnr+4VMgwZEfRLoQ4vuL/H9daf3zF//8r8FtAcjMXCYWjilR6FS+FpuPwJLm9FinTJ2KGJiYIoqiaz+cwXjwf+DbUzrLaX3tPO+/+madxZHA/fGvkMPbv9sLzoXDUJZubMia11g+s9gshxA8B41rrE0KIt23mIjtXOJTGmdUMjrcQiRbpSGYqbqqpxvmilkvUcpnPO1ybaMGcshCut6l7bdvNVDpIyjMKGm2AFy0xCEAFiXxGEYx0HpXZmpyMWkMWYTDXgr0oHPPZCE3e5kMAhGVj9O1GR2wYmQh3MFtAlYscPgy8XwjxXiACpIQQn9Za/+xGT7RjhUN7Lru+co3OZ1KMPNJE4bF81Vbw1ZiYZy+0cuDxPOb0JGp4FBGNlj2uWvBtJIc9kidH8DubGX99oqRjjIKm44U0xsj0ppLq6p2evx9k6mT/Uu+QvpyLuDCw6ahOo3cXZ36rk46+GexPHib+eJgkWHW0rppzXGv9b4B/A7C44/jNckQDdrBwoDXewCAMQOzoQ5sOdV2LakzMRk5gXRxBzc6hCgWMiIN0YaHgYJsellS1l62ulrNitcEN/byNvEaNTSAdG6FLEw7pgzGVxhsarvxY6whvYBA5MLj0/0pVrdC2RcvuOd7Te4YvNz1SW0mC0kAYRtB4ahOmSeE4SMdBF4uofL6CA2xsdq5w1Dl6b46Lv7yf6Khg999dwp+cpv9rWbKnWhh7UNJz/8h2D/EWnDlNy5kFtCmZviOGm1pWjoVdJuqdr8OLSnxbYOa2fxe04xmbIP7Jo3yl+RE6n5uunXwPIZB3HiK7N0V0KIM+9Wp54iEEsx+8j7G3+jSfsuj+5ItB1v02sxXrOa31d4Hvlnt8KBxww8q3XujtmIGOGa4MdLDrWwn0yCji+6eIC0Gi602o+wRGDZigVmJlNfLsFYRtYe47vCwcAorNgmJzibdjbX2sZW4eVx3eVyvxZ+eI/d2NyYY1gZAUuuPMHjQROkbkFQNdhnAIw2D6LsF/fNvn+G3zJ9j1GQdqQDhq9v5ewc4VDmmg3nw3cwejzB6BzjovqS4ch+JbjpHus5k/pGiqMdEAKCYE3v0H0VLgxcqfVc2sJjnoYaVd9HwVy5NvEOFDcsjHmvfIdlvk2mXdi0dNohWRwTnadRPO6AJ+meVjtO/TdVzxb40P03EWdK66XRhLpQYf3VvYscIhLJORh2M0PTpK92IS3FZSisN8I051GYsx9KhN++vH6KnRO6+YEozfu+jE38SEaqc1sWcu4M/O1lQ3O+lpkmen8c9dIv62e8m1O9s9pMZEa/xzFzBfE8FOqNx7QGtiXzjOgS8FvhJVC2HcGqiDPKRtFQ6jrRX/QA/CV4jXrgZd0bYQLSnJibwaec9kbKwZnTOItOfoakpv6DylvHej49ISbKMGbv7bIdiUYMj5HInhGM60hy4Wt71TmkznSAz7KDP4UEZRIdJZUD72dI7EkLkU6WTPeeAWt3O4jUclvn/ll2Xm2ulsq3B4h/u48OEIRlZy6C+64FztmB3WQmvBQt6h7Qmb5kt5Bt6dgAduHXuldxU7HXXxCslrI+D7qML2F2X0B4dIjE+CXCxTrxReLojM0acvkLq4Ysfh+/g1YgoJqXHqYDrYVuEQvkIWRdCroIZMDuuxVDvKAt8x0LdpHVqNXcV1MkWbhZyDTJsb6mK3GvUiXtrztrSHxnqsNR7tFtHl7jCkgbm7G52MweQs/iZ7eITUF3XwKG6zqerVAQ7/xS5QCn2t9sJH1yIVzTP2NpvpvEm8ucQeCBVkYriZtmdM2id9mNpcp7x6EI2dhJFKcOGX+ml/YIzcFw/S8aeTdbWwCtkkdfBdb6tw+PPzcHrrJ93rSDdYuZdLSyq7VJi43PMIobENH1MqXCUpeqV9Jca8QWqgiD2VRxcKQSLTYgLgZsgXLZr8xRtXaaTHbXdU66ElgU9Db7wdpvCpWSehsGxEJEga09UwmZkmxV0uP913gj9pe99NFxfIaBSECHqg19AOLKQy1MM6bsdGVWnXo+eJNAtXWrZ1HG5MMvQ2l76eKSZPdNFxsrQZdu9UEefCODqXQxWLaNej7xs5ci9t7vNEPU38zCgeYF0epTvXVtZ5tCmZO5wg2ylJjCiSF9MIfwPBA66Pmq7B2kjSYPYn72fsLYqWUwZdnzxZ8YxjlV5gz+OC//Hse+l9OXPDCtTc08eln+ul2KzY/7cF5JMnK3rtkJBS2LHCgfLRz79M/Pn131pNjI4Opu4+iNotSF1kQ/WAbl5ryqderEhZiOvn9UbHYHSsrHMIy8bpuodsp8SZdtEvnEHXwRZ8PYQUTN8t+IO3/09+0/pJuj/rQIWFQxcKOF99ntX2jn5Lkn1vvcKjHed4/MS7aH6yopcO2W4qVS+myuxc4agRdDZL1/Oa+ZFuus9tImtVGpj9PaimTUqHrxFDY5uuhKp9n+hAGlmIExmcq63M402glabzuOK3zQ/Tflqg81sb3WVMzjHwtb3896Y97L2w9v0iHIfse+5hdr9Jx6kC5rdfKMt+LkyT3GP3M3PEpO2VIvY/nNxxpeu3iqA6bu0rRygc24zKZEg8/jxJw0B7btnnEZZJ7mAHCz3l+2wADFfTUijCZktoKx91+hzWGYmvVV04/EpC+cQ/f5yDXwqi2dQW+xi8wWv0/pdxgHXvFxmNMPg+ze+95XH+/eMfYN8TRlk+EeE4DL5H8LvveJyPfvEDHPiuiS6EwlE16qCIxeaEQxoYiTgYBmohU3744RZgtLdRPLYHP9JY/e+stIvx0sUgIU6Ksh3Z19ns8TeeTIOuzwnG3NNH5s5utFGdmiFCa2IXZoIM6N4essd2LyUSVgovJmnunCUp87h9BbLvuz8IOtggfkQQ27VAUubRfTky770X6Za+EDDyPpEXr+BPTm384gTPbuGevWhDEDl1FX9svKzzhFSOTQmHjDjofT1o20ReHi77xtgK3Lv6mfr1LPtaaneM5fDSYC+HP7oLfXFgu4fSUEy9pYfD/+IMHfZCVc7vaoPvfuZBdr12kbmHetn9axfoi1Y2GEAKzYFIMMn+6gPfZvBYa9nn2RuZBOBf3vMdrhzZWMDEial+ih/bg/Hd8p4992gfhX81Q9wqkvtP/dhfb2zh2Bmmqio2Hqkovsb1DZSWHEqO02LWQBXMCjA434K2GmsXVQt4UcGDqQH67M0tNAaLbZzN7iIqi9wTv0rKCBzpRW3wlV0PYBw9SLrH4KHmy+x3qjch7rUn2WtP3vb3vpZcKnZwIdtJm5XhdbFBIvJWU1ifPbXq36SoDc7meriWb2FPdIo7IsNM+QleyfSgtCDbZdN8+ABMTG/YfyY0FDwTUyrkBiLz6pKd4BxXuRzy8hBSiJqoY78W1ukBdv9BPxM9exn+uRQ/2vfSdg8pZAfwifNvpumTSTLdBgu/4PCelpcBMNC8620nOXmshztSr9JlbX8Hwz858Vb2fNZg8nUWsZ/9Nsei10o+Nu1H+auvvpXebxb5znssfvd9j/O3w/cz/4leDFcz8m6f3Ictop85QvKvn9nQuMwzAzT/hz0g4lhnrzRMoMXq1MdCfHM7Dq23vDBhqQjLRlgm2vXQbhF/dhbjhRxNs/1cyYVVS0O2hvmZGD3fO0/kaD8zxRi+lqRVhKI2eTh1nnc0ncHYaHZklZCTNtFnzpJKHiXr2xS1QdqP4iOJywJxefsIMh9JbFjgPP0q8bvvYcxrYng+Rd+pabQp6fqIxy/ue4o/6vlxmuJxdNEt2Sfqz8wgn5pZvE7jEyYAbhPCspn9qfuZvEfQeUKTevw48sgBLn+gjUKXzwPdF7Z7iCE7lFGvif/8rffSdM4g/9Y0/+6eL273kJa484ErvPyxI0Q7M/Q7U5zO9fLZrzxCdEyQeGyUf3XgG7c9Ni4L2O+e4NzhY1gzms/86bshBud+UaGaPD7YfSIQn3eOcW7/MdqPS1r/6kRNB9SE3J4GFQ6TyXvh5971HT7lPUrq7wzyuxLc8YPneaD56paORa2oIy7rwXgZUlVmvDjdTwmSf/MsA51vwL9HUAseKkMoPrL7Kdi9/Nrz8/vo/3oB68R5Xj16BxxY/VhfSyLC5bcPfR0OwW99+cN0f/QkubffzaM/+SJvbzq79N7fPvh1OAi/oX+Gts+ZoXCsRsObqmoU7Xp0nIBPeY9ipQXjH7mfhT444GytH2bcTfLFl+7BHLdpvmuKH+l/KRSPEhGOg9zfj4o7yMHxug3BPNg/zuAv3kGhRfNj8SlazAwjb1Vkdr0R4645jBq+H/qj03zvvQ6RB+6mb9/qRUgvFTr545ceQU073H/PRT7U9Ryth6YZ+uX7yfQq3uOsXoCz88AUQ//HvSSGFM1fO4s/u/0+npqgjLpu20GDCkeRpr85TtPnDcZ+4fW8+SMvkDJzxIytXd2M5lP0fcEg/u1XuPTbx6B/Sy9f18hohNl72si1Sbp8DXUqHL/Q+xT5j1hIFHEZ3H+///bP4z5qrukzqAWORa/xO+//GxTBjmI1zmW76P1Li9hz5znx0YP8bPcz/J+H/oH8wRs/88382oFvkd9v8YevvoPm460QCscy4Y5jm5AG8vB+CruSZHo1zVaW2G1u4GoSN4rM7Tcx8kcotteOW09o0DXeC1u7HpFpD6FMZCZft07RiHSJcOOkez0k9zrHM/v4/9s78+g4rjrff25V9b5o3zdLliVLlrc4cfZJyGq2JCTOQlgHGDjk5Ux4wHlAzgzvZVgnjwcDMwQIzADJkJlACCEhdhKyO7ETb/Fuy7KtxZKsXa2l966674+2Lctqa2+t9TnH57i7qu69pa6qb93f/S2M1C0AAAAgAElEQVQvt1biska4LW/vlF2ApwtVGCPGej6pliC9yy0Y1nJs6fFCVWfOuTaUx3MtK1GE5IP5B6i0D81azuxTktZL+xWleIrSsO5vnNOxYCZDLEjhUOw26u/MpPK641xjH0zojz4TFDp6id51gP6Igw86p1YzYzqZ66IBYAQC2N4+jF1VMYLTm0RwrvHU0TUs+WeDYH46b399kHuy58/Dc5XzJJZPbWFQt7HUPrzg1LMtK3F+JwWpCp7/Rg2VZSPNXbdm7+HIl9rZ2V1M+HtL0F6dP+eeNOb+hGNhCYfQNNSsTGSal1BOjPVpDbM6HpuIsdzVzrSkrF1sSInh98/2KGYOMTJdjC4VGiOZnAhmkWUdoMrRgnUyOUOSiEsJc7GrHl0q1IbyeNm3gnybb2h2oYDQJW29Hl7tq2KZo2PYjCpDG+RKTx2KkLxemE9m2RJkT++iXvOYD5Hj05mZaNZRc3Ooe6CU+odsXLLq+GwPx8RkXNxduZuBbwew/f0prk6rO/u9juBft17PgW+u4smnrqU1Oru1Y0bDpzv59ebrOPgPK/n3l9+H37ByS8F+wg/6aLzPwPuyi73/Zy3/uu9a9AQJ0SrsbWR9poHmHzrwbaiahTOYQ5zJxjGZfzPEwphxCIGwWjFSPVgr+rm3fOdsj8hkERGRKgHDhi4VPGpwwrOCtc5G1i5NnGvM2qHheHMfnsxVBPS5G7iqo+BqFtjfOIBz5UUYKJTaOvhMydu86l1OU2slznePE9uwLOHxGdognyvYgi/XyY9yN+KZ4fHPGSSLIDvuHEFZUUnjR9IJ5ehcnG0G95nMLG/2LeflTevQglD+/uN8Ov/taWlXRVJ8eTO136vBUdA/J9KSXAiXEka9qYvaZavJLu/ALqI827WW3c9XowUh+DcS/YPLWLPyxJyJlDeZPAtCOIJFHqpvOsqalGYzTsJkxqntz6b0jz0onT4Or80ZFkQ3FVRh8D+KX0MvUs5+nqu4lDAPVr4AlfHPqjA41JVD6X+1IlWFzh9pfL3ihTl9DnMBgZwXaxzzWjjE2hV0rfPSXwaVNv+iEo3XOis4sa8AZ4uC0t04b91VFwKV3g5euX0d1t50ZL3ky50fo6K6mb8r3DItD8rJttGv2/l/R25k4KSX4sp27lvyWtIW1/2GjX+pu57u+jRyyrt4oOxVlmd0sPeeKrQgBA5Kvtp0D+tWnuDjuRNLcrjoMIUjubRfnsLlf7sbjxbCM4a/+ULj2LFcqh9uQO/pJRaJIKxTq/xnMnn+JuUIa+9uZH+gkO0PX0zq5sPUPbgCCmd3XD26G8vzqVQ+sY/GL68mWqIlVTiiL2VS+as9NN+3hlCphduydnP9Jw7zhq+Cpm9X4nz3BLsfKuejOdvNmcdomMKRXBzdBi8fq0RRF99F6Kq3xKsuhud29PG8QgjU5eWEilLoLwXbOON/rEInQxukwNZLX5mC7YpKYlnTGzu0N1DMX08tx2GJckvuvrMurbpUeK2vip2dRRR6fNySteds0J5F6AwWgffKKkK5Ouo5q65t0RSebV9NX9jONTnHWO8+MaHx1Iby2HxqBUJIPpy3nxQ1gD9fEr6qmmCegYJx9u9SaPext8IClKGmmdfrqJiL48kn9cXDpG1PBTEPItqmGelvRx9MTnW6xYpQVRo2ZnHtLbu5zuYjVZ1YHEmRpYeN97xB9+1uPuzoHPuACfCH42sp+L5CKNvBlq8HuDdnKBZi89trqfxZFyfet4zm+05S7WgBIEvr56O3vkH7+73cbO/Gcs5sY9fAEvoeKcJbN8CTX13H+ksnJhx/Orkazz97MDSF579Rw33Fr/OpD7xG6/Wp3GDrHZZqZIWzBT75Fv0xB7c5283ZxgJgVOHQSkvAMDA6u0cv1CQEanYWwulA+voTV/gSAjUzE+F2IvsH0Lt7UJxOlKwMUE77dUsZ72uMwC+hafE658EQBNvGPMlko7hdCLsdGQphDM5c0JqwWsGQ055hVDqsqF4vRji86GY0UoBViU1qvcyuRFnrbARnEsYlQegGwpAY54f+G4Cuj6jjYBU6q51NCcdjSBFPpmcYk45UFjGJUCS6FKjCoMbRnLD4k0sJT3hGMyaKirBooOvIWGx6255lkrk4LoQoAh4Dcoj/8o9KKX880XZGFY5TP7Yz6LdT+OscLC9dODZC9Xio/0I59nU9KM/nk/nLd0bY6RS3m4bPL8O2vgfxQj5Zv9hOdP1yGj5v4HXHc9wEw1ayf5uL/S/bLzwoIVAL8jBS3RM4zeQhFYW2y7z4lku8xxVyt/YjojO3VC2CEWRTC3KaLjZDE/SuTEWpSsV7dADeOzgt7c4HpK5T+sdu9uxYS+s1Gl+99c9ka/2zPSwANpbv4cVvVWHX/FyTXjds281X7+Gd8hIKU+opHGeeq0u89TTdl0ZX0MHGgvcmPJ5bCvfz/D+uQAC35h2Y8PFTRcvLwchMQekZINbcMi/WBcZNcs8lBnxFSrlbCOEBdgkh/iqlPDSRRkYVjr+veI3DwXy2pF+GZbQdLRqhJRG+WvE6P9h9OwgF5PCHp9A0giVRvlLxOg/v+whZQDjNwocqd7HGFa+R0RxJ589Z78M+Wl9CQdptxFJH3WtUpCKQQiCMqbu+SUUwWAR5lR20R3KIpNpQozM3FVc1BaGqEIuBIVGmqFlSgXCKgmEFZ4cNVYiFdVOOhpQYtcexH1NxL7mIqJzZShkRqRIyLBjnJHSwiygWoceDBJeNDBJUhcFNqQe4KXViD+8sbYBPFGwbNfPtaFQ7Wqhe2jLh46YFIcBmJeaxYQlGEj5v5i/JjQCXUp4CTp3+/4AQ4jBQAEyfcPzo5xtRw5Lcfd2junsag36KnlX4yb7bKXwvCHLkg9MIBCh+TvCTQ7dTtDcE0sBzsIs3f3kJr9nXA6BEIXd3b1LXhmIOjc41FiIpkrTD4G2cojeWhNRa6OvLJa1Touiz85CV0RiOY53YOqZmJ5Gqiq/aQzBrQWWjGR+KSv/Gi2m/FNylPjxKcEa7f3dgKc+9eCmOjtOmKAGRKwZ4aPWz017s6b1ACU++eBX2bkHmjS08sOSVae4hiUiJ7OnFGoki/QEwFopoTAuZQohzzUOPSikfTbSjEGIJsBZ4d6KdjCocuf+yFRi7zq8Mh3E8sx3HGPvYn9tO7jnf6UePk3V0eE6pZL+r63aBvyJCbl4vgz05eBNnehg3QkpSGkKkNEzL8CaPoRNrmHp1Q2GzYS1evSiFQ6gqHesED3/wd8DMB9zVDWZT9vQAcufp2YMQNHkuh9XT31dDIIMlfwlh2Xucw+WVsGT6+0gmuq9vYdbwkEx1xtElpbx4rJ2EEG7gj8CXpJQTtseO6VWl2O0Er19Jf7FG5t4AYuveifYxqwRybAwUKlgGJSknhhaRVSHxFxq0Gw4cnRJPU3hUs1Ug28pgoYoWkKTUR1HDI+VUDcRQ+oNIi4aeYkdqI729REwiojpSVZCaMvfSTOo6ziY/SsSJtW0AfbGYqc5jNjx/ytxdvPihMhyXXA6AFAK9Ou45t7l3JS/trUFxxPjbVdsSLkJPhGJHDzs2VGFfV0NBcXIcTN4eWMZTey8CYOPq3VzpqRvjiNlDKy2hf20uxul7VolKvDtbiJ2c2t95UiT50hNCWIiLxu+klE9Ppo0xhUN4PDRuNPjy+k387IkPUrRtftm8+0sU7Nd00dWSgvvU0IRfUwzyKzvQKwTde7NxNwvEKGamgSIV7dpuetq9uNqVhMKhDIYwjjegeDwIZyFSG/nnFbqBEoiCKtDdNqQyt1yJZSwGe49g3y/QddMEMJNc4amj+u7WYV5TTiWMiuS1E8uo/k470fw0tn9vyZSFY42rkaW3dxCVatKCZ19vXUbVDwaRqmDL95fOaeEYXJFD971+3I64F2HfoAPLQA6WWRCOJHtVCeDfgcNSyh9Otp2x4zhiMazNVn6XcwmOzvkjGGfQ/NDV7sXSqyH0GMIArdNCk5Jxdh9Hnxjzx9ICkt4OD1qPhoglfqBKVT0tGg64gCBIIUBTkKqYVEGlcJqFsFfFEjCwdyWpQJWhJ1qmMkkyVqFf0IsrxR2if20eoTSFKusorvEJ0KXCloEKdnQWU+Du40OZe/GqITK08cUBhQwLm3pWUufLoia9jRvTDowrAj3dEcC3shApIN3RRESqvNizkkO9OVSntXNz+v45U1/E2hcl3OQmaI+vEap+FcsMutYPI7kv5lcCnwD2CyH2nP7uQSnlpok0MqZw6H39lP+iCelyQPfReWe6SD0ewX1KRYnqaAEdBORvERjWoVNXQ1GEMfp5pZ6I4mpXUWI6Fn9iv3E9xR6faZwxQyVAagq6yxoXjQkGLkoh6K7SMC4aQD/upvDVuWbnMkkWny7bxsEHC7AqsbNeiBPh2a3rWP5zH8eurqD+i6fi8R3jpN9wsOvZGkqe6eTNe1dx9Z21WNWxH/h35O9m31figZCr3CcZ0B1s3bSK0ic72HbXKq6499i4xSvZaLuPsrwpfeie1A2M7p75EMQ9IaSUbwFTNnOMPeMw9Lif9DxFC+loIR1DVYi54qYqLaCjDIxySRgMqb4QoIAa1hOap85FaiKheWoYClMyT0kFNE0nNguacabCIpqG0dO7uCr0zTIFll4KUhME1o4ToQtEMMz5WVQiUqU+nE1X1E2etY8Sa9eI9R1DCpQYiEAIJRa/drtjbo6HslGEpNzeTqo6chaUrfVzQ+pQHFB3zB1vJxRGnPfuFTIsHAvn0BpORQsk5+VUWKyo2ZkgBEZXN0ZoyERn+P1z43qWwBgvsXOBeZ1yZCIEciy0XwZCQs42FVfbKBHRUqKGYoiYge6wzJlFbCEl6Ud0Qu0peAYlygzGiwCoxYUc+ftc1Jwg+Y/nYdu0Y0b7N5k8N1yxl21LlpDvbaLE1nX2e5/u4lebbiD/LZ2TGwTfveH3I4QjVQ1QectRaq/IZm32YexKlCeaL6Xnt8UYGhR/6hifzNs25hg8apAVH6jl8CU5rMiqxaMOuTvXhvL4w39dS8aBGDlH2pKS7VlUlnHofi/CGWPpv2ejvDHxwMfkM7OV/CbLghUOKUR8QibjD9yYXWAvGEBKQcw+dtS5iBnxCHCHJe4dJedGLWBHVwRH19j7JQPDbaegqp0NeYd4Jvs65m49uqlzJhhPFRK7iE67l5UuFaJSJSLVpPVxBlUYvD9tP+9P2z9iW9iw4D0Bjpf24lyxDh3l7LlDPI2KXYnGU6Gf40t/qt9LwbYOpNXCqY3ecY3DKnTuzXkXcob+vlGhYRdRemNOMg7GcLy4J2lOGXqKnXUrTlDi7GF7xiXJyAwzPcyB58xYLEjhkIqgu9qOv1DiboL0w2EcPTrhbfEL3NEzRm4bITDsGtJhoXuVk4El4GoWZBwKjbkWspARp7oJ/Vc5T6bkkf9ecgM1Z5ufNV5Lx6sFhDMNPnbDlngOqmlER/CtAx9AeSeFwYooX7tyE7mzUOEvRfUTvrmfY+UXkV7diUXEeKbzIt57qQrDIrn+5vcSRqVfXXCCTQ+sQaqS27MnXqr5Jyeux/d6LsFcg89e9xpL7Z08d3cU5cp1FL0cwfLyruk4vWFYGjtpeGwZx22CvIMdc7eGjSkcs4NUBAOlBoWr2mgReaTVCmy+KDk7x++FZFhUDItCfxkUrD1Fs5ZH+hGxqIVD7+wk7Tfxxc6FLBoADSeyqfrpAaJrl1J/RcakhUOXSsKZhCEV5J4U8n+wjb6PXUrfZc5ZEQ6XEuGhmuegJv5ZFQb72vMp+48mpMfJgUvyEgrH+1IO874bD0+639a6LCp/sofwVdU0X5nG9SmHeHj9Hxm42M6P2jaS+/Kkm74gseYWMn4ZX6+ds6IxT1iQwoEEV4vCSSUXT+vYrrYjOL2eIaTE2So4acnF3TI10RgotBHMVrD1SLxNYUTUQInFHyiGpoA6t+I5FhOKy0XguhUMFKg4yuMP79ziHk59soZAjuQSu2/SbV/I/KQIg0hVgK6/u4zeGgP3LBUi8xtWHjlxLe0n0yhb2s4Xit+gPKOLE3cuxbDCpSn7Eh43VbNa2pJe2j69Bt0BL7yzms3WlfENuqCkLklu5vMBc3F89lB0g8y9YTL2gzCY9ANfGJLM/WEyDk6tHakIepcL0tZ10HUwC3eLQAtLlEA8kl26bEhTOGYNJT2NUx8L8cCq187mp7q/7HV89zmxCH3CdTnGg4rkmxf9hYE1DuwimtAraSbo012E/5JN1X8eoPH+GqKf0rgndzu+z8VnGcka15crXsG31MmjR6+i8psS6oc8N2UovIiKQJ+PTJjrb66xIIUD4uIxHfPRaWlHgsUv6OjyYhsQw+smzP1rZOGjCGy2GAWWIXdXlwjjUpJbi2S3fwl7ugsp9vRwc/pBXGJ2ap+oEYne348SA10KXGqUXGX6zGY+3cmmrpV0BDwjtg2c9KL0thAbGJi2/uY95hqHCcRNXpl7o8TqLGih6FkTlcniRUfwl9cuZtlvfOy9sYY1n22mzNYx28NKCvv9hTT8qoLM7SNrhVQF29BPzX4xNpOJMT3CIQRqehrC4YhX9+ufG8Vv5hKWQAzL+bN+IUCZ+28XJpOnI+alKZyBXYlSauscNotRogKlbxAlnI4+zmBev2GjPpxFyLBQbOuedKGpM+00BjMwLKAVFhBzxpN/+nQn9eEsFCSlto6zNcwni46CFpSIvkEMX9/cCLSbqyymNQ7F7abx88uR6/pxbSom/dcjKwCaDEeq8dQjSMz1jQXML49fhfZEOoEshas/vutsJLWK5LJrD7KrooiS9AZytPGZhrb1l7PlP9fh7DTQP9bNgxWbJzWuHYOlvPrEejxNOv3rIfzjVFbnHsEiYjzWfDm9jxeh22DZJ2u5J3uUipzjoNrZyp7PtlF3WxbZTxXh+uOEyz8sLubBs3NahENYLQQqwjxU8wLfO3AX6TNRkWu+WXuUeFCikPLs2KV6Tjj6RM/ndHtn67UnEyHiVQYTIHV9Xlzoo2JIdF3Bb9iwiNi0Jt7r6vRQtbkWz/JiOu4cCjxVhcHtmbu5PXP3hNprC3nI2RlAO9bKkQ2Fkx9X2E327hDW/Y203lTGd1b9+ey21n4vxW+0YngctN0xvuC+0cjW+vlS6ct0FHl5ZOttuKbc4gxz+vqXhpyZolHz4H6aFuGQ/gAFz2v838N3kb8rnFyvAEOHrh6sgdlxX5wUqoJvfT69FQqeRknGtjZE+DyXQ0UgXQ4MpxURiqEM+EedsoaW5dC+3oa1z0Zesyep039ldRUNt6YSc4wcT+52A+czO+d1FTbZ14/3T4V8d9fduK7q5GvLXpyVehzjYaW3ld98qhRlsIz1S49Oup1q9yne/ng5qm8ZayuHF1O7oqCev/7PVUhNsjGzdqpDnt8IQfCWS2i7XCWlFjKf3IsRSKYH3CJKOWKEQrieenfG3iT07h7o7pmh3qaO0DSCGwpgTT+BsJf01nb0BBeflpuDQgqi30+spXXUC0hW5RKsCRLsspHrGq324tQZKPdw1+1vsMpxctj3OoJ/kPdS9qyYDx6EF0Tv7yfld++QarFyLH0dLJvtEV2YGkczP7j2ySm3U2k/xQ+u/n3CbTelHuSmDQcTblt0CIWOdSrfvv0Jvv7OHWQ9a4ekCsf8YFLCoZaX0n15LpaggfeNE+idndM9rgWF1HVS6qNEt3tJq4sho4lTnshAEKFp8TrKY2BrG8S9Mx3LgEQMJvdCdjUHefz1q5HOkbOK7EPEp/AmdMfc/LTuGno7PKxedpJP5G2jKL+HU/dWEU6HlY7E2W1f8tXwwqFqLPYYn6neRqX91AX7mK6Z0GjtTKUPXSr8ofNi3q0tw5Pu5wsVbwHw89qrGWx3U3J8ngX3SYO0w5KvvXEX3gMWZCjJLtMSMOb+W9ikhKPvohwufWAn+3oKMOqzwRSO0ZES26v7KHzLgozFkNFIwt30/n44488+xnTVOFBH/jEbGAaxcHIvZrHzEMsPORMWp5KhMMY8NlNNJ82RdKy/T6Nq81EO/q9K+Mg2vrDkTXruc6MIg6wLeEC9VLecqod6CJeks+OfSqjMvbBwzAe2v7eM6m830HflEuoezMGQgtTHPBS9chgjGJpfwX1SkvL0e6RttiMj0SSbqYb6nOtMSjgsAzpbWpbS1+tieWhwweV9EZqGWlSA4XLEU4GI0+VyRyktC8RTlSjKqPuqvoHhZihFRSsuwHBPLlenCIURJ1uRSRQPGYvNnou1EKjlpURzvFja+tCPN0z7jSUsVkRlGdFMJ3rG5N+I7UoUf56Cp6aEWGp8VulSwriso/82LmcYf2UWgWyNIsvsBAFOlu6Ym7/2VNMbcnJZZn3cnOmNEqouJOxVeKWpAikFTq+Co6YUS2Nn/PqfR8hwGD3JL2fDO1ygwuHcdhRnUy55UR+yaf4WeboQSloaTRsLGCyNgdVAWA1kVIHwGB5MmkTYdaQuIKwm9JTKeC+NrMeHisioXjfNtxXSXzFGxt4L4DilUfpYjFjjybF3nocoNhsnPp7LRTccZs8LVRQ/PP0iqWamc+h+L5evrOM6z+QfaiXWLq6/Zzsdt3m4xjP+WcPfLtvG7m8W41CjrPfUT7r/2WB/oJATv6wk7dAgj9+fzQ8vb+QLa7ewv7yAhuOlLPk3B1JA46dD5H6mnbb/KCXtt/NLOGYWuXDjOHRfH/hmPpPnTCE0lXC6xJnjx2mL4rBECUYtBMKWUY+zajoee5iooTAYsmEYI007wcwUlMwMRPB0EZu0FEJZ8b7GHJcY+TISiniQ1tHHNd/R7ZJl7g52OpYjhJh+U4fVgjtnkDuydtEaTWNfsOjsJqcSocTahf380nkJsCtRrvUegQl6sHqUEEudXViEjl2JEpEqzZEM+vQhp4cUNUihtXvO1Og+Q8xQsQ4aqD2DyEgGEF94r7Sf4pgvE83vRApBXuYAH8rexyPeslkescl0YKYcGYNQVCMSUzHk2EF6UV2lL2g/vb6VeP9AWZTjf1fCmfVHQ5NE8iNj/hB2axSrphOKWIjEEsdULESMSJSlTw3yyo6rKGsYwEiiySAkLfxwy83kvzKUT6yvTGXDPdu40lOXtH5/1XAl+n9nE04XXHnvbqqcp/j5czeTvWtoytq5VuGLt21miXWWqnhdgBpXM+99roD6ATcfXDK8UNT7Cw7xx6+vRgB35h+anQHONyTIeeCiOPvCcaY4/By16xmGwBhnOggpIaaPbs5ypgcgfeizwtg/ghBgUQ1sqk5EUYFZEA7ldJ8zsRB+bl+GjtyxH9cOkreoakgMQ+A3bHjqNNx/2Hp2k+PqtZy8NQ2/a/z1DlUMFGGgItERGFJBH6X2cHt7KsufP4pRmk/DLelkWQfI2C9xPTUUYW2ol9H7IRdZ2tjJAFUMLKdnJjqCqEzebe5RQ9xX+sbZz35j6O9Ubm/na1Uvnf3s053DE3yaJGahmqqmCzUri2hlAUKXaAfrzRxXF0BKCEc1orpCVJ950VDWVNP44VTUEBQ/1UKsfnqr4Z2LWl1B422ZCAOKn25HP3p87IOmiOzrx/1MET/ZcRt57w73mrE2dVH7u+XsT1k+/gYF2C/v4sHKF3is9QqOv1aKktiRDoC84wZy0I/a2k3bf5fwJ9cSCg70DFsiSzno40+/vQZ9HPoVTpfcet27VDtb+c72D+A4Yh//2JOIokPeLjNP1ZjM0Zfoc5ndGUeal+4aB2oEspvcYArHBYmbp2bHRDVQ7uHOjW9QO5hDz9ZiRBKFI7AkhRvv2E5Qt1C3sxrL5IOjx43e30/q49tITbAt1niS7Ecm5nggNI36hy6BSjjUkM/yfzsSD1odBQMwWlrJ/EXr2c/Dth84Qt7IQnwJUdZUc+CifIrsPWS8biP911vHPsjEZALMqnCIAT8pDTGUqIEMBGdzKCaj4GwJ8fibV6EGFJZ1dSbV/dreHuC5LRcjdFjW4Zt3KckgHvCZdljy1S134d1nTX7Q2HkovkFObCvixxn5lDUmnuqoaWn0X19B2KuQ9U43+qEZUOjREAI1NRWsFuTA4MzES8xFpFy4AYDTRaytHVtX/E1Mj82ziNJFhLLjIMsPu+LJAAeTbGrYW0vl8XjyGr1/MLl9JQspSXtqD+nPO5CRyIynEY81tbD0YR8oAsMfTLg2JItycHyxlY/n7eZXP7qFjFleuxaaBVmQg+61YWnsXLzCAaapakykvGAUtcncQcZicRfsCaKmpsRrtPgD6P39CJsNNS0VKSVGjy/hbz/ZvuYaRigEodETcSoeD4rbhQyF0X2+6XtgGPqY64UiHKO+LZNN2kqsA7P/oBJWC+F8N6F0jVSfG8YZHqZmpCPzshHhCEZD84J4nkhzxmGyWBGaRmTNUvpKbaTVBhDb9qHmZtNzRQGKDqlbGogt8spvRtUSuqvduJsjWLccSGr0/4i+G05S8Z0SIrYMUk/WzXr2B+F20XqVhdjSEEo0Ddc4Z0DBS5bScDvY2jSWPhom1jzfA5IXUXbcxYyUgmhEQ48mcLcUYLHFUFXjwvtMES0oELHZvu0TIBR0m4JuB8Oqxpf1FQXdJuIevReo7zFVFKcT4XFDLIbe2wfSmHbbueLxoLicyFBoSrMjaVGJ2cGwzkBNlfP7DofPrmvMhatHCIFhBYs1hlSHu44JTUNxu0AoGAMDyNhQlgXdJrB4Q8QGVNAWT3zTbGMKxxQxDIFjl5Ps3SPNElGXRvMNVpQCP/bdTnJ2TX8NEW1wEKNjbgWFAchYFOe+ZhxNHujpQ5cSo6OLzLdVkBKja2T96ekgcH0NJ++MYTlpo/yRRmQsRv0Xy4ksDZL3jHXq1ecUlc67aui7Pohjl5OCn+2ZtBhpR1vI7UpBDAaIRea/iWUqGL4+Sp8eJOq14jjWyrkJeJSyEhrvyEGqUPJMD/LAkbPbPLtbsQzmoAaCc/I+mDCLqXTsYkZKgZ6XOIoAAAVZSURBVLvZQH1tZCU3a1YWlkuWoecK0i6wz5T7J4mBcVNByrgp6hxzlOH3Q92JibclBAglXiBsjGl8f5HGVy7ezG/SL0c67YhoDMuaXh6oeJOf7bp1yjVjhCLoXwrfWvdnvuHfiLBa4FzdmMBY9c7OoczSigqcc8xo7ZzZtoCyEhuhEGzfjwU4P2ubkeIktCKIZtGJveEYFkoZO9mMdrI5vt9MDTbZmJHjixvp95O3LUrgmIuUw/PTtXS2EZrGwEfW0b1SIXOvgfvPu4aZKs4n6z0/jzz+YRydEnpqkbqO7c8F/GvereTvmrrLt9R18t+K8U+Bj5J/1MAIDs0iFY+H7jtq6C8V5L8dwfLSzvGd47oVNG1IwToABU83YvT00nPHavrKBbnvRrFt2nF2X60gn5Y7lhDxQPGL/cid4wzumIcoHg9KRhq6YZD5UjyI0XqyZYSwLCQk86O+jSkcScQIBLC+sAMrC+htaIYRViunroHv3/QE3/B+lIrntVGFQ2zbS+E78WyQZ97H03+9jfREGSIng5TYNu2gaHO8vXNbVNwufBv8/O+1z/Pd0N0UvnTBVobhq/Lw8btfYWtPGbGtGSjhCJ03hvnupX/iIflRijcPjV3PTiP/Iw1ck1nH0003kDo+bZqXKG4X0YJ0VH+E9KfiJVsXsmgA8d85yTMOIcQG4MfEI4p/JaX8/kTbMIUjATIUJrUW/AMpY+5rMcDVsoh9zk+jeDyI/JyhBUrDgLYu9N6RVe/U1BQGr6kknKKSsXN48JlWkE/f5UUgIeXtBvTuXlIPKnzdewdphwVST3BTKSry0hr6lzrw1ocQ2/aDPM+Mc45oqJXl9F6Uia1Px/lW7eRS3SQQIRkKY93j5h9Dt5F7Yvg41cwMBq9aim5VSN3eSqyh6ew2d0uEX269Bs2nsszXBuEwrn12HpQfIfvYee30+al7t4TDaQUsbZ5ftTsmigyF0Xr8iFAE/dyqmUKgVlcQWOLF0eLH2Fe7oMx2yUQIoQI/BW4EmoEdQohnpZQTiuQxhSMBus9Hxu/3kjFOzx8ZCs/NdYYZRORk0nllFjFHPCGkEpVkv6NCAuEgPwfji118tuQdfv7jW8k655IN1OST/6VjhHQLge4C1NfbyXlsH7m/t8WrDSbw01esFo7d6uTzH3qJX7xwI8ves426YN1xVRbX37+NTQ3VOI9lTVuqG93no+in+xFWC9IfGDbLNErzUe7roDKlk8MP1+A6Rzi0tw5QtccF0ogHPRo6hb843U4whHGOSMUaTlL+/V5QVYz+wQV93ek+H/Sd/m3OEQahqpx6XwbGDb10b02j8Ojov/d8I8mmqvXAMSnlCQAhxH8DtwKmcEwZKRfUhTgjKAq6FQzr6c9CxKshJkAqCtnOASqsbRjW4ZmHpSYocvQyqNuo0wpQOb2oPkb0tWGXlFk7Mexj33SGBUptnaQ4QvFF5ulCSoyBxNlrDS1+ziWObg5q551zNILeO1wQL9QOhr4gAiTHhZQjZ46n0a2Q7gzSYU2b4UHNAMk1VRUA5yZfawYunWgjQs6DYBMTExOTxYAQ4gUgcwpN2IFz/f4flVI+ek77G4ENUsrPnf78CeBSKeX9E+nEnHGYmJiYzBGklBuS3EULUHTO50LGneBliJkPWTUxMTExmS12AMuEEKVCCCtwD/DsRBsxZxwmJiYmiwQpZUwIcT/wInF33P+QUh6caDvmGoeJiYmJyYQwTVUmJiYmJhPCFA4TExMTkwlhCoeJiYmJyYQwhcPExMTEZEKYwmFiYmJiMiFM4TAxMTExmRCmcJiYmJiYTAhTOExMTExMJsT/B/Yy162QCIJCAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}