A2_Q3_VGG16_TransferLearning.ipynb

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      "metadata": {
        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/mehrotrasan16/Keras-Deep-Learning/blob/02-horsesvhumans-VGG16-TransferLearning/A2_Q3_VGG16_TransferLearning.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
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      "cell_type": "markdown",
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      "source": [
        "# Imports"
      ]
    },
    {
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      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import tensorflow as tf\n",
        "import tensorflow_datasets as tfds\n",
        "from tensorflow import keras"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p90uP1KLpEDZ"
      },
      "source": [
        "# Loading and Preprocessing the Data"
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      "source": [
        "(raw_data, raw_validation,raw_test), metadata = tfds.load(\n",
        "    'horses_or_humans',\n",
        "    split=['train[:80%]','train[80%:90%]','train[90%:]'],\n",
        "    with_info=True,\n",
        "    as_supervised=True\n",
        ")  "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[1mDownloading and preparing dataset horses_or_humans/3.0.0 (download: 153.59 MiB, generated: Unknown size, total: 153.59 MiB) to /root/tensorflow_datasets/horses_or_humans/3.0.0...\u001b[0m\n"
          ],
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          },
          "metadata": {
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        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/urllib3/connectionpool.py:847: InsecureRequestWarning: Unverified HTTPS request is being made. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#ssl-warnings\n",
            "  InsecureRequestWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/urllib3/connectionpool.py:847: InsecureRequestWarning: Unverified HTTPS request is being made. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#ssl-warnings\n",
            "  InsecureRequestWarning)\n"
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        },
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          "text": [
            "\n",
            "\n",
            "\n",
            "\n"
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          "name": "stdout"
        },
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        {
          "output_type": "stream",
          "text": [
            "\rShuffling and writing examples to /root/tensorflow_datasets/horses_or_humans/3.0.0.incompleteDO7YHT/horses_or_humans-train.tfrecord\n"
          ],
          "name": "stdout"
        },
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          "text": [
            "\r"
          ],
          "name": "stdout"
        },
        {
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              "model_id": "93353ec846054f318cf1f4a3b6d0ea0a",
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          "output_type": "stream",
          "text": [
            "\rShuffling and writing examples to /root/tensorflow_datasets/horses_or_humans/3.0.0.incompleteDO7YHT/horses_or_humans-test.tfrecord\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "\u001b[1mDataset horses_or_humans downloaded and prepared to /root/tensorflow_datasets/horses_or_humans/3.0.0. Subsequent calls will reuse this data.\u001b[0m\n"
          ],
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        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1kMwlxpKKTiO",
        "outputId": "871145ab-ee1f-44c9-f892-bf3231794f2b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        }
      },
      "source": [
        "print(raw_data,raw_validation,raw_test)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<DatasetV1Adapter shapes: ((300, 300, 3), ()), types: (tf.uint8, tf.int64)> <DatasetV1Adapter shapes: ((300, 300, 3), ()), types: (tf.uint8, tf.int64)> <DatasetV1Adapter shapes: ((300, 300, 3), ()), types: (tf.uint8, tf.int64)>\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "niWGT8GkLZmE"
      },
      "source": [
        "get_label_name = metadata.features['label'].int2str"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B28kxnT-MCra",
        "outputId": "6d6a1368-d522-40d4-d00b-c7af967d8b6c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545
        }
      },
      "source": [
        "for image,label in raw_data.shuffle(1024).take(2):\n",
        "    plt.figure()\n",
        "    plt.imshow(image)\n",
        "    plt.title(get_label_name(label))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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F3YA6ga0xlFIIc2Ldt5ydLShF6BqH8wbnLSIOZw3HceL2bmJ/mAnxJWDxznI8tsRTerboPCkVpiESQ02JcnR4a3DeMMcJodAILMZblrtPsccrunyDl4DJI0y3kDtyhnGKNE0iB4ilY27fp209XTOBHonzhNMBySNaPJ2zdOUT8vXMtn2Tdv1HWM1PaZoDLg30U0HjM+IseBHcfEM7PCOaFQd17G6PDJNl0T7GTQO5pOqRRRinmWmacSKUnMgxUHKNED4PwDrvMc6RinKcInOEOBfmOBFiZNEKzhk2657laslmvaYsV4xzIoZnDFMipZl5njmMyn6YKc2zL1yvPzVMQFX/AvAX/t8cK1IXhTeFY0qMY837vXeUkrGuglQhKLtdxE8Zo4XOtYQxs78dmGNiuVriW09RT8kJbyHEiTy+4vzxJdZ5rq9HQhixC0XWT3DLtyn7Fbz6Ef3+IxyRw/GmDtzlBrdY0IQfoflAKYlOlOJaSgwcR+XF9S1jdtCcUUqmMJHmG/K8Q0vCCKgz5OiYpnxadBadj4T9jklb5jmiOmLkhxAS9uwtTAqY6YZG94SwR199n5xn0jSRUsIYoesaFqtHqBcOw4EUA0Wl5vJSoyVnDV3r8K2t0fwJ6EspIwUMGVElxVSjBW8YhlPebwQxNfUyxlTkXwCVGtLGghqtz8gaCpXJMU6wXvFdxSrAkFPheIyEWMg54b1jDpEQI1OwrFYdC9syjDP765FhnKgMTmYYRlpvef4yoi/3lOOnlDefgzHkm2f4uGVKA3sRSlJK6PHWsG6qo0Zn9vsAfkVYvkFCWZRdjbZ0xpAwKDke6fwZNo/sdjeEy6+xlELjEjFCxOM7xybswe4oWcjhFSkcce1IYzz7/Usab9mcXzKmV7x4+mmNSBGmOVbGyFnGaabkym5ZYxBrMUYQUYooxlh843jy5Jzziwusa2E6QkmIeIYpnJx+IE97FssVX3vnCedLy7Ora24OI8M48mqfmOhZ9asvXH9fmn5xOUHOiuaCFiWLIc4GoxkkkbU6VI2ZnDLLxuEcdNbgrSVrBUhShn7hWW9WlFLY3h4IISG50C87vDsSDgdi3LNsYTaF7s2vsVq1nM/fo7FHZhOx/Rre+SUWa4s8v2K/mzkOBzQfMG5mnCK5WXNsI6F9g7y4JBuLsx53/SG8/C55uEI1UUomhBkJMPYrvIKwo6QjaTwQY0XerQK5JhPnfcsqPkeZmO2CMOwI4YjGkZAiirJYtKw3K/J+riAfgrUWYwxN4yqtSkao1KuxQs4QY6m0kq/nOIQcC8ZUdlKodKrmSt+lfF/oJzUtqBkHKSWSVhCxlEoN5lyIqTBOkZAcRYWuaTFiEWnxDTRponH1O7z3GDEIhnkOvHq1Z7cfKVqdTEqQohJaWwE1a2inW5gHdk8+IPueze5DDmp4ES35+fexds2m79nYa2yaOewHphBoZU8Tb5kTxGaH8xavoKzJOGACaVBZgTQs8h3LlGkkEtMeDTOqjhhmdPwBBsM0HDGup023OCIh7WisrbSlqyWSh+2BdrGkqGCdI8EJE1C894i1OGehKDFFSoGmdTjrSCmjKMYKkBHJdIsVm9hzOBy5u9syHkaWx4FF7xErDNPMy1dHrvcW8UuW5xsuHr/1hWvvS+EEVJUQ4Tg7QsgnrrwhK6Q0EGMA0+Cc4FxhvWyRbLjbHpjGisRePH5MYsI6aDuPniKJ88s1+93AbrdnCjOaFeeUaXdF/vh3GMyn9E++wdnb73AeH9NMdzReWJ6fM731TdQX3PAtNnrJLK847G4ow455ONKvDY1ZUvwSLt4nDkcoGbM4Z3H+hOIiYbjDiuAbA5KZYiSlgE4jKQaMClIUXFdz+RxoDaz7hn42xPW7NC4xHj4mj3u8rXy0sZaignMZkYRSTouqwRpH23qMFeZ5AKnRgRWDWCGGRMml5r8RjFZuPqVIHCMpFYwYDIUi8pouvNcAVEUBr/lwKwZVwUiDxTHFmTlkjoeZy4tzjOmJcyanRJgz86zcvNrTLVsQYR4Cw2AIKTMcAqjQNgvQQNtY3ni0REthPyaMdfjlOcPFW+zP3sCPLX78hLDbs/3oQ/T5d2mefJN2/U0CPVbOCMZg2jtCnnHzKx73LcvOAJZSlrjmjK59QogWtQ71GzrfIlpTkq5xLBqHxD1lOtS5OkxY2+BcQ9sI3hW8MzjTc9gf+fSTT6BUTccUI/P+QIxaqc4QCLHqRrxvatrr6jMqJeOto289beu4XDd4k4jhyGrlcG6FdcLZpqVvhadPb/n0xSus3LBYtAzTxPPrA9FsoHubN5484p03Nqwu/v8HBv9AlnNhe5g5TpaYPdJe0CzPsfEWsYkQJ2KcSdribCHkRE9L6xtutztiLuAM4pXe+TrwU8RagzGWxaKrHHfKNc1wljjNjNcfIt1jnAx06xHfHFEtOGfpG6GUkSMbFs0T2k3Don2TsNxy/PT/gDmAKvM0EOIdeqGYxQqHsjQjNjkiLcH0LJYexDDOW+LdnikM5DBjrAPxmGYJ519HjMEK9CRs2DMnRzQLunakbM44pqHy+iWjYjhMiZvbK6YTReq9wdmK/IucdnRrgUrvoTCPkRRLTRlUyaWi313rSSWTYiSWRMqZkqsugJMDAE4SnXuO4PQ3MYgY5ikyN3W3jmlkGgLOOEoRDB4jijMGihCi0pbCcBy5u5vxTUPrGwxVLNZ6jxal8YbHj9bEmNgOt1WPEAxxd4NN0Lz6Hn78XfT6gAkN7oNfxb/9LUzXUg4TZW7xvMB7ZZsXqOlo2pa+t6RimcwZ0iyw3RrpLiglkNSz6KDzASuZlGYaCXhvYCyEEIhJGeaElcj5eqL1DdY2LDpBFIbjxGE/klIipkIuM8I9fhKqzkOEooqWTCMe5+wp/QJrBaEQ5pm7mxu8b7g8WyHGEqZAOQE05+ueHCq9O06RwzEgYvFGUCc0l+/iztaknL9w/X0pnEBVNgkqUJoFdvWEZrPG7m4pRek7i0wZrCPExN2rkdXjnuWqZz+2HMNIkQmjjhgqshpTAhWMNThnWa16QBjHGauWgjBMO0woyN1L8osr4tmCYZ5orKE1gen4gmH5JsE/xrGkLFua5oZ5nshqmOIdL2/umDuPOVzRrR5xcXHJ5kyY0kdsxyucc3Rtg6KkOFM0MYWZnApN60+CMqVIQdolGmemXNgnB3NB5qcYE5A8gFbmpJSqPBuGI1cvLU1TWZJhGEETTdN+ll9qoYRCsIWcC9MYUcA5g9o6YXNRjuPIPKcT7+/IFPJp4jgj1FdVUFROyk7BkSUjxjDPkVevbhinHmMt81TTiHJ3JOVC3y+RXKAkHMK6azjsZoZxZpoj3nu6tkNzwjWGri2oCvMc2O5HxBiM8xTpmY9Hyl/5L/DGsLDX2EuHs++yeO/b8MEf5bJraZ/+FuFwSx9e0bsDIRakZOJ4x9Qs2HQtxj+ia88wKNGv6VYr7HxD106smxlrAmAoKUGOGAx91zGVBtM1JLOmpMyyn+mazDwPOCucrRdoiYSwZwqBXJR5CoDgrcGclJViKlAtQEyGrEouhRATISaGMRNT5vJcWfbKzVZZrVqKFra7kRgipghNY1isz3l1vcUbYdEtiMGTxx1692PUrtlNX9y75UvhBBCDaxqsQpOO2PETWrvAmZlkoFv2OJMoqqRYJ/PuOGCkY7loKC6hKrRNDS+tA2sghkTOiZAzo60qtaIQQkRUcBKZj1csN0tK7EmpIcSEqq2h3MvfRuYEtiEbB80C8+ScxnSQIpu8wU8vyNMN/ua34bDGHBak1QXJnIFdYOzMPCnTNBNirGGzsfjOnxarp3UeMXtCFmK7oSwfwfvf4fLdb5J+/D9x/fRDprEwjTOiJxqQqgFIOSMhkLO+lpLGHJhDQQQKlZfOaYaTdLoUZYyxiqwQnLUYW0UEWiouc68TqJGTwWEw1lXJdi4Y62tKMY6UlClkcoSUOaUfFZsAIeXM4bDncJgJ48Sia2kax+EwMc4BRUg5ME8B7ywL29A2DmcbhIpLWOdpfUPOFuYdfvcxnctcvrdh0z3iIkzEVmm98nh8io+fVOecaiSSS0DTgDWQ50QKG4zuUQJqG1pdsO4GMiO9CficKakKpWyOlFK1Co1zbBaegsN2LepW9GYgDy+wTDjrabzjfNNxdd0wvLwjhFhpbIRFU8etKHhTIyhQ5pgg1ejKGiGfxEStr8CuiBLChEiHFuGwP5JiYblcsF62dF1LGCNWHEk6mD1DsYyzcH11S1uOX7j8vhROQFWIIZDGicY5mpKYdyPZGbw4oJBzQClkTTRNpcn6xoE4jrOhaEXCfdNUPKAkFo1nmCLjHNnvRva7UENpzXjniHMkx0TrDcbUHbZrW2JKHA579vu/wfjh79AuNywu3ya8/8cI73wbuXibjYH3xh/BTeL4LJOHHWl7Rdl2DIsNRSGGmTBNDCkzTTMYQ9t1VfvgG6RZouIRnfGuYC/eoV2/A298gL18G0KHXz2iWd5WVVkpUKoYR4whxMR2u68gXS6kE60aUz6JfGpqI9YQtZw05ULWujC1KFqgeMUWgxFLTgXNBWsNi0VbUwsjGOexxjHP86kmwxBjqE5B9cR1wxSqsMiagrW26gRypPFNpROB/RSRkJlClSzfW9YKWJpJSLnw6PKCftEzx4l13/L22ZKn25ltPLJYGM56z9m6p/WCn0ce6Y71/kM4PCVc/x6mRLwcKQgpJ9Sf4R7/Iot1S99HNA0c99ekZo1LHZLvyCkwp0SWTI6Kd7Y6xKJYEYxGGqly7zC9ZIpX+KXBMuGtwTtLiDW6KbnWs5RS0yrvbVVZiQFTx9U7gyqnZ1ZwptJ/VuBy0/Pk8Ya28cyzVo1G0ap98Q19A+cXK1aLhmGaWJ+vuHzkSVlod4G9bpj7tzBlz6X/4kLBL4kTKJQCXdvgbeVQx2Emp4RIJoRETPn1TtdtNjhniSkzz5lhqDmadR7rfFViISDQuIaUhHmaGOdUhTwmk2wm56ra2u0nrD2gCdq2qbruOaCp4FNiJcq6JA7Xf41p9QRdvUH75H0upsDh8DGpuUTbFWncEkyHSZ5y9yM03BHmqTqbnGm6BsgYI4SUMKaASWjOJGa0OyJ+SxcO5LsXjLc/JL/4HuPNp4zDQM4RLVUrIaeiqWQKOWVKrrSesQbr7GuhEOYexgPT3Bc2KTZDroEpKZ2KbWxNHxCD946mb/DW1SIr6oJQHNMUmMNEyrHmyQgxplOtQX7tEHLOxAQ2GEpTpbHTFDAiJKUuTP2saEmkwg9FleMwgWwpBaZ5oBHDH/3Gt/n6G4UfPb9iTiNd52idME4DYYo4Kcjdx7jjj0jpDikDvjVEiRgrLJYburd/nn65pNFbdHjOcEyUuEPHmSFOiGzAKKVM5DyRpxE17qTMa4hpIoaRXALbISFEFr7BeUvbteSijMNICAkj1cGJWJBCVmUMkZAKxtpaX9H6+izHwDTNWOdY9p5l5zlfL9hsFkyhEGLGNz0qDV2/4N33FhiTKVoY5kCImX7Z4/wCYzzZTcRjy+Z8wxpoiF+4/r4UTsAY5fzcYYzhuBs5HkbGcaaUjDGlVpmVE/8NNZ9C2O6PTNPMeAgkVcoZZApt74lBmOdYCTAj+Kbm3VDQkpim+RSKCSFkpjHiTZWJqghN0zBnISKkBNNxxoTfYZ2V8PavYvpziusriKMTU+7IfgMlEcctxIkSQ11AWqvGcsqEecZaS4wTOkz4plavmZKJL36PcvucMhzYrHrK7sccrz8iZUFNW5eyfobMi4FTsQP3ShPVWvSYT6Iqk2seLyKYKFVaXdVXeOdxtqGUhG8dtrHkWBAsXd9gG4MBTK79QL11WF/p2JQz0jY45PVOqbaCvKUUtGRUBFOETGF/HOtnubIY+b5q81SXoCfs8b6y89X1luvrHda5Gh0Yy2468gvvvc/lqmW8egqacGS2c8YPE+F4S1lucJLQUnCmgCZyzhhjWNkDq+m7tN0HFNeieMQ6JB3J85GSC21jMCrEaWIaZzTMFC10bkMuhlAyIWemoGR19E1Bc0K8oWhmmmfGOTCNibu7Co4aU+dujJkQK4birHk9n+8ZFwH61vHkYsXlZlHVsKVuSIuuYbPpaRoPklSpv/oAACAASURBVOhaT4zK9ctX3NweaLyDXWLzaMV66TmGmWVTeNLcIBRu9b0vXH9fCifgnbBaVmVa04JvBRNAszmB0ie025jTwzVsVkuup/H15LHW1DDKGtq2TuLDTthvR8RYvDeIUbquZxzrA06p0jTBCCFE9qrEnDHWkIoyho7szzhMd4Q40TQHbPptFs0a/80/xrrbUBpPbzNpfFFLm1OAcKCkKuqpJcwWTtJbIxWorLviTIqBbrHAOEeOEzlbrHOc+4Ggd0wOGrGv9fzl5ACRz6S898Kee8y+0nmnCIu6AIwos9aQ1FqL8wZrHc45RDzmPuxvqjupgGLGGXBOXo+9Ar6ttJYWZR4iKSa89zjva1qX0qncu4BSVXHU63or3Fcdm1PEIVLD4ZxryXaMhZQKbeOACqCJFZ7dXvP2xQXvvv0ez1Pm8OITLoaJr606Priw3HLFPib2wy0mjLTrFmsSWgIxRXoJyPBjSpk5No8JhztuXj7nuHtB0xaWiwbNW0ypg6pZyCkT08Qwj6xWa3y/wDUrnAaMiSx6Ku2aM+VUt5JT5nCcmcKJnZGquQiaAGXpDJvOE4xQMJRcqsS5qyySt46+7zkMI8+uthzHyJPLM5YbsDnjJDMcRraHkd1uYLvdY4wHV/D9QGMymx7a3rE7bHl1NJTV+Reuvy+FE9AC+9sDKYNvay5aCoSQsFZYLFtSKpQMOWWaxnO+WTIOe6wmjnMDTZ3QKWSGYwSTiCFgxLy+jpEaDpdcF2Yptf675BpupawMYwRTwbS5DNiugDeAweVCPu5xL77LennG8lHPFkjtmyzagebwnGHeIxpRqQBayRkrVehirdB4j6pQMlCUgjJPMzFmMg67XOCI5GnHOBxQBWcyjhnL/W5ZTmE+VAkfiPF1V9HPcn0tQCmoBWytWS+lFv2IE5REzBk9sUfGyGf9CaRSf3OpTELXO1CYQqzAnzUVhLVadQXOYZ2t6L/15JKZxnyKOjiVKgsWIZWCsYbGN7VnQK66BNx9gXyVN+sppalqxcJu2PJbP/guF2eXXL7zdY7q+PHNFdPtwB95o+c7y1u24Y6XHLhaeI6u4TBnXBZahHCYcGZJ1Im7Fz/m6unHvPz0I8b9lsYr/aLHu4acFMGACr5x9AtHzJl+0SNxpjWwcJlQJowaSBVn0Qw2FdbWYlpPe7khn28IITDs7tAQOWsMrfcUIzydE8cEMURQpfG2Fr6VSt0WVXaHCcXXsdJEnDNjjNze7tgdAzkpOSljzizOVmy3A8ftDetlS8iZrfsGNxdv4tr2C9ffl8IJ5FwYhkh9+g4jsF61qHp8a2nbhhAy4xQYj3MFdtpaRjzFWENyUz1qQQkxVY3ASW8+joGSBdd6chR638HSVGS6JFAlnioPS1GyZkQMWRNaEtIuKd7jrSGniTl+wuJjCLzFOI1If8bCGor2GBIpTISTsjHnjErBeY87CX1SzLXCkdOum6p4ByuUFBhuX3JdbkjHodbvmyoiUS2fNZKgOjARUxufNOuKFYQDSWuTjhow1MrKIgajkFN5rSCMMVf8RD5r9GGNUE7Xt9ZVoFAd1mnFLlI67VaW1rUE0oktUFKMlFxByfvGGahWpkCEcsr5M6fmLUYqBkF1QFpOAyIgairWUQq+gcNhoqTAq7Jj3f0Wv/yLv8TFo8f4puXq5aeEF1t+5V3Lm4uWM9/zVoRtjBysMvYNxnqmBKNbcVeWXF/9APvqGW+ajD1b4Y2yHQLbac9xTqRc9RO+tazWPSEEWpR15+nPVjTW0oSJpXhWztEqGC2vC6vGleFFTBymzCCRnYep1IjzaghE35DuQUOt8uFxDphoOYyJs6jkIlxcbGjbNavViuF44HA8MsfMHKqy0FrHZrPhZntkPN5SdM08zRyHiWbyhPef0D76Os3fpJHgl8IJoOCtZY6RGBK+cXS9qw12RGmt4DuHUqWtTWeJmhFr2B0nisDFpme56JlCJJUM1Nr3cZjJqjTenYCkliebM14eZo7ThJQjw2GoHHlJdbKqkksFESXHurMnzzEZ2rah8waX90xDy3E4kKcRmgkpE85VKWhbHEVPXYtKwdmq3XeuIrzGACqIuZfiKiUFyvGawIzrGzRXbYGWwnSq9a+lrXqv3aljogbRupuKtZScUFMXllhzytpBS6FQG4AYoYpYUoZTxyUU8okaVFHEVBDSWEihlrvmorUISROda3BGaL0ll8g0BWKszAun/N41tjqqE4vA/T0CMecaobm665Zw6rZELXpqvEWMJeXCMATCbCgFfuN3v0vnHB986xdYb9bk8oSXLyL/4w9f8SvvXfD+4w2bheFdIKfEPEaMs8QCz3c7nt29QuIVhyXkvkW1CsjOWsOzXcWFxpg5zoHpWOnd/d2BcLvl3Ysli2GNbSxWhDb3nK06zlqPcwYpsJ8mfvDsiv/t4yuujoE5FWJRCtRoybc4qnCtlHs9xkkrg+EwKnN0tJ3j3dWCaQwYppMkOOK84WzTs9uPhBTw4mm9ENOBMESG1FGkZSVb3go/5pEIrSn8pS9Yfl8KJ2BMrXaLKTPngouJ41DwJ440mcQYMiEXrLMcxpGnNy9QX1hc9FhjOTtbsVx0LGKiKBzGQMpHjDttLqaGw9YYrLf4pmPTNmgspBDQooxTJp7KcQtaF4JCiAGTE1osAjg7czgoz7Xw6uaK7W7H3Nha0NN7fHPCNxqD9i0llUq4U3NtjNK0Di36WnNfsmKweA+tmbCmY87KNIzEGE758n2PgM+cQA2dMzrvKbYBzSCKdbXDkJzapXlX0yItimIoxVScQqGkTDZCrj234ISxiK16ixQTRmuDrZQqVTmXmTjOFeCypo5bbXhAKdXpWl9TOTEwHALppE40Jzyjah2ElPWU4ghd072O6u5TBS21axIqYGDWwl/74Q9xRvngWz/P2dk5WoSPfvQD/tLvveDvycrPv3mGtYama/DGMsyZIRb2YyDFgcNw5MNXB1IR8gmwSJo4Tok5Kk4cSy8ohcYpjS3kGNjvlR+MQ6X0gL71vHe+5L1Ha5aN5+pu5Hee3/B7V1u2c0Sp8671lrbvUWNRMaSTelW1nKItQYwDI0zTiDGFy/NzDsOOw2GH9h3WN7im4XzdsVn3tG3Di+s7jBQ264b9PvPq7kAyijSGznueNK9Yz4EhfnEo8KVwAjkXxnmm8xbTOIoq+2MgBkMMJ6Du1C9QUKJRbneRzWbBG2+fEaaMuU+YixJTfg0oWudOPeAs4zAxE/DWnNpsKfM9735yECWV00KpTgDDqafb/UObCCFwp8KVvWYKgTkGUjQVhRZFxJNTOYXeQts0nCoicM4BterOmrpLTlOolYRFa4/CEpmHW6ZxZp4mCicu/rV2/54CNbyGA7WyHloqG1ExkCpGcVbw3hJComJvp+iDihvcX7uYei1rDNbaU6huyFkZczjJiMvrngUUEFvBLDEW30j9/QrrTUeh4BvL2XnPrTty2NUoq5yiFnMCAbPq61QMKgBccibEQsoVPzBZyQJt37FZLzmEyF/97g9oGs83vvFzyGbF8dETPn0a+evPt5wtGs5XC7wqKRe248htyNjOcNkueHxc4oxwmAIfbQO7Kb6+LzRgTaWsjSiNVy6Xht4bbg4T13eV5oNaBv/89sBvP7tBFV7uR3ZzrAVv1p5KuR2LVc9yvWSKSgrppPy8f5InrMYURCtFHucJLYEwzdxtj7y82rE5P2OzWrJeLnHeIXak7zq6xlJK4WgzQsKL0hlofUOcB27DgWH8ksuGY87s9yOLtqVpfc1HjT8tTMGK1irBokRVcsygSo61JVPJyvlmxaLpaZuGaT4yjtOJWiy0bS2qGYcJ12SSjCy6DsVg8EyDJaeMNS1Cx36cGOa55qh64tkLhDlhbC2rFYGUaoMNCoSYyKmCZCG0cJLXirGVKjP1O3Kqog+xAiqkVIihFqosly1n5wt8axmHWNueGVNBtVQXOFRx1b3Tqg6sIvei+f6GKVlJKK0z9H1TMQ9j8Kc0wRhzwhngnl40yOseAtZYQjpFKqdGljln9CTuESNkUwgnLYexBikZ5wx929J4yzgn+kXHo0drFouWFDJIbXKhRUlRub7eMQ4BkUobjlPESDo13TSIGkpWQqmRweIeyyiFbcn89Y8+wjjLO2++z/vvvkO3XuDzyE4zLiREhZgisxVc57hY9Rz2I+ed56xZ8WI31E5HTk7DYHDG8HhlawQRYM6RYY4YcezmxO0YyapYAx7YToF5O5ww2lPTUCM0zrJZL2kXta9i23nazjJNtVx+nuNJlwFoxWqWfcu7b1zw5NEGQ2WQlFqGfPj0JeHROcveMsyFFy9uUSy5KHe3O6apzq3sO1i+wYjy0fORi8tHnK3tF66/L4UTQJUUM7NEUrkflP+TujfpsSzb8rx+uz3Nbaxx9/BoXrymMouqpJBKKiEQAiFKSEyZ1ZQBUn0FasyovgI1YwASTEowQiAkGIOEmCCqKruX70Xr7tbde0+zWwZrn+vxUEalIDNRYJMX4fHM3OzY2Wuv9V//RshVr2+O9J3l3fMLlzlcefMlVtZFNAI5Z+YpEUJlN3a4ztHF1P4bjDuPNYZaIze3o5B1QiQGudWsNfjOo4pi6HqqUoQoVNwKV7fcnAs5S6vtvcFZSy6lIfaJlDLTtBBjwjsrt1tj320+gDUUab1LJiZx76k/+B5yqTgUxgqZxDgjbrs5t926us7bRZUmEIJN1mONaeYh7c+UxvoDu13BXU4iTa3ImtDIKmwDwbRSGCMPv9Zy7RZyLtcxQSl17UZqEanv8dCL4WgQxtzd3Y5pWhi059O3d4zDgPOOZUpoo9mrgeky8+7dqbkUCTCpqlCWsxJzTmXFjEOs0hDNvbFopejGXn7Xg+d///Wv+fq7D/ydX/yML24O7P2OAxNxXVnmBaxCe8PrweOV4v1l4tAbTnPhZjcS6OjHwhwjKYO3hi9uHUYp3p8CU4TLmvjmZeUchDilFOKSVKoI2FqxNtqgFfTe0Q0DfuxBix+jrG4TqmYU4sOQS2mUrQq5cBwdn789YEzh5TxzuqygDG/e3HJ6uTAvC5dp5jItXOaA0oZ5EaOcaQ4o2+Fv39L97O+y84HnKfCVGZn7G+C/+HOP30+iCFhrePV6Lyq3KOw3VAWEgGGcZ7cTuu28BM7nmTWm68Fal0iMZ2LK7Hc9u/1wPdx932G0xjnDbj+gtWaZAmFtWwUjKHSKSdozJYi10bpNF+XqqKO3NZfVQnIpsgYE2s0q7fK6ihuwaRrxymYuI7dEzllUZG2376ymayucsG7qMoU2FusE1EtBN2eAdmG1LYEAaVJItLFYrbGqzdBA11uG3nHoFVYXzpeNW1GJa2liomZogbTiIQiush16hXQPQy+U7BBa4fKGvrfsjz0aOO579oeRm9uRD+9fOD/PjM6jioZiKCmhUcSS+eabZ54eL1L06/XHwRhpjUvNkBs20UBL5x0KxeWy4FbNbvBM88rT04UXf8Ed4Yt8gL6jGzxxXqhRdCK3fcexczw9XYixYoylqsz+MFJHj4uKO+uxJfDy8D0HlzFKPC722RAGjb8srDFRrAjQUikoMlYJt2PoPH3npTs0FmUcMVfxCbSadJaNkXRVtY1GUnBlnSwdJcDT85l3D8+cLuIsfHx1Q1gjp9PEN9984OW8kGsVzUBIpKSIqZJzpCOh0gU9OPxn/wpnc+Ti3I+fv7+SU/yX/PDO8MVnd8RU+f7dMzHKoTocRvrDQHUWmzpSCjgLxgTWODcyigBl3mh5QVMmPV8IUbYM49jzMi8cDgN3r/coreiN41IXXuZLa9Hll5BLlfk+CzFHN553bbsru/EFrGwJVIZlCbJSqzL/i+2XWExvYpvSbjhjGhOvbQRyFquvvu+w3klXUAX76HpP13tqDTJ7f6SWyWFVSuzKkQONKShVpGgqdf37UgjM50dM6XHWsBs7YizM80qIudmeyxE0WrMmoWkrI22xMWJU4p2h70WmLcIgsM7SdQajtQhrDgOH4w7vDTf7HSYbSpSRLqwRbSqX88TTy4XT80SM+XrAU5IRzxrdbOWhqtJGKo1zTgp2SSgQ4FGV5kJVONyOqJ3jt2Hi6+VC/jahHl74t372mr3fMXSeVCu5avp+4OX5xLjfcfv2F7y9/Zz35wXrOkaT+fpP/jn59B6VFmpOrDFjrGXspbv79mUiaMu+6+mdjIamcxz2e4yxfPPugfMU0LmwHwa0VqS4EpN0fwoBYY0Wq/hSctsSFJY18nxaeD6d+eb7BzGAKYXLZSKExLIEvotiNOKcaRegZCIoINeV+cOf8Gwr4c2vML3iUF4YXr790fP3kygCFSXCmgqHRayzQXj8WlmcHlir4vl0RmvZdXujWFK5BoxsERpam7Ynnen7Dq0UISa6XphpJYG1jq6r5POZmCJGNZFIFfRbQJrWpBV5wLq1eqBIIVO0kIByQ4lpzD1aOMXHQBBZ323tubzs0mpTK9poQs6UIC+70lLMhkFkxnFtXVFFbGoQlqBqs+c2BihEjVZKsySvYK38HLMSoY4CKWRKX/fxORcJY3Fafv6cP3YZFVQRV+GcCvMcAcEphtZh5VKYp4TqNdMlotRCLZl1TtRcOL1M9DvP6XxhXQOn88zzy0JKGaMV1smqbWq8glyE5SRuQ/LzdZ2n7zugMI6e42Hks7dHeq9EN5Izx5sBazWXReb1b7594PUauBk7jseRwRvSuqJrwZnCcd9hxyOvP/8F5vZz3LQKJXqZcB8+oFXFxZO07kpA6+PY0VvxO/zNVLC953A8AIWiConCsq7NbCWTqoCeIhKSZyVjmBFX7CxFmKqpphJSZl4jTy8XLnNocuFEBaYlcHvcMY4dy9NZinfVlBivQTzb7+P0+IFUNF0Z2PHPSemJ+fzDGJDf/fhJFAGFIqWK94bXr26JEdYQUUqcaKyqrCEyTTPOKmIqDM5TGmoNIhumQo6ZEFMjwqxt5y+7bt85YpC/r+8s/eDQqzjuLGskh0Ku0tLHZuuEAqNElKOUUGCFVGNkHKiV1MBH581VvSeUWNcsspK0fLWwLkGsxKykDFEhhUTWhW7wOGMwWtxnliVhrCbHj6k1mzinlIrK+XqLy0e9rvm00dfvPyQxCi2lMPSywgxB6K1VIGpqUcQGsm60Xqk7hpQrMcZGTlLsdh1eS4bByxxkpGjdwHRaOF0mTs8z1lgOw4C9TIQiZJjTaRG1p5M2tuGqcssDVDn0KFFDaq158+aWN2+OhBAZuo7jceBw8I1eW0hllZ8pZk7nhfPLytM3L/ytn90zjjt2zlJDhLa9Gb3F+gH36mcc33xOcgfGavBDz4c1cPvpz/CfvmV+/xW1ZGJ+Zj9Yem849h2v9gPj9yd+fVqYLhO7/Y6SYZ6WFuRi8N6SciHGFa3s9U2nbXq29CnvPQrdxFalBZzs2e1GrH0WT8aUMQY6L3Tvy2RZ1ojVDZhuxVuYl4paC8vlAucXdP+ecrhl6F//6Pn7SRSBXArn6cJejSjVsa4rMQWMUUyzvDjTsrIsC+v2ORS007hir645KYvNVmn7aJTifFnIDbA7nUU0NIyeLz6753DckWIiBqnIa5SiI3O2jBm6/aK8b0IWpdgf9uy6nuk8cTpfruCW1gZjKjmJEWdnPUaVBlBKcdH6I+VWOoOINuYHO3E5lCnLgdZa0N8NpJOPj/9sTCs8bRxRSv6LaWAbjaAkjEgpDtYolhaTtX1+bN3Xtv5TbStSihQaaw05SbcBmpQrRWU65xpjUxyGFYoSYV0z2SDGHKHxJIx0SSkmCXrJhdTcooUw1Q4JtO9NtCDH48D9/YGXlwlvHX2nUSLGkLyJatFKxogQEuFp5u//7Z/zb//Bl3zx+oBKkSVk1lLZd5bRa1Z/z+6Lv8Hw6lMWDLGCtpZQCjf3rzn0nmetUfMLdZroFey6DjU0FyaEX/CnL0ujUTdrvCo7f5RqLMhMiBIj5r3DIYrLNUTYnJaUSK6NsZTmI6DaRqnve0JYsFYulXH0vH2jef/wgrWW3a7nfFmIoXlJWotzFlQhPn8jI2I4Mw4/fv5+EkVAadiNA1o7SoFpXljXgLFiWbWsEjCSszDvUkpUMs4Zsb1WUhFtM8y4mm40zEBmTSMHPiaJphJ7nGtLbZ1p4F6V9t8IqKeUXNgoARp3o+f2dsfteODFGD48PjUXHrnlnTdXMFFclJsYBcE5tJHRQubqSioS26W0oOApZnLhevCtaxl+RvNRDSq7ZREGKXJjJqrKRxCzdQgiWhLchQreioDJOiOYwLbzv6LXItixLZbMULFK46ylb9z2quTn8V2jQlMJufB0mhl8h9EO7xy7weOc4TJJEQ85E9bY9AutEFZFofzOaCPySOFUGKNIKZJiZD8OjLuBzot3Qs4ZpRsFWxdOp5nL48zf+fQV/+7f+wM+v90zmExeCmCpxWGBXDV6f+Dm7hWH2zsWJSNZKoVx6LHWUKtmHHZM1jEaTWcUukrHmhtt12pQOXM+XcRwhY+dYW3jZcwZrSvZZGhW4hswW3JsL5fgQ8ZKwX98fsG5zWS0MPSevvfXPMLjYWS36zns9wy941/8yVe8nGZAGIn94Cm5cJkeWMMJdf6K8Ref/+j5+0kUAa000xQoORJS5un5JDkCtLUaYsvc953w2S8z02Vh1aIRMF7WabURUeQGk1tsu+02BNwoxThsGwNLKbGRazR955mXQIyx2W0LOKhbsdAKrLfYTnO73zEoy3cPD8SXQgiRqsTNV8YNz+3hwLSsPJ3P169T2k1vneAJVBFF6VYENj1AbniHWIi3w8kPmHaIBfiG6mvUx5Fh+zMl5hxagW9+/krJfnscXbM6F+l0La2/aM/ItLXWdjZTzGDEvDXXRoV2gpusa2FeggiyeqhJkPV+6BjHjpfzLKBY2DQNbSWIPGNVW8GmNjWkFF9jFF3vOB5Gus7RdZ6hl3VpzYVYCxGF7zwxBc4vK3qt/OrLn2HcwBIzrha8MTgM1TuJgMsQlwVVAv3gAcc47Ig58urunnUNwn3UWjYAVqGMEr+/OfJwmTmlSuccTiuepwXXdQ2orcJUtJ5cGkZAFeJTEhNRMWW1VBWJKWG1YugtKVVCKJwvU2PQRpSC3W7k5jCCgsu04pzlsN8xDh6jad6Z6mopl2IUpykKtQRUNnT+J74diDHzm9++l/bbaELM1LyltMqNYK0RbrYyLPMKjeOOUqwxYTbDkc5jrLADN7ZZKfXaDouMt7LOgXHo6DtPTKLOMkbjnZXIKXXFzkRn3jmcN7jOXltV7xzOWryzbGm0uWEGh/3I29f3PDy98P2HD8LMK+XayF/pv7R9exSlY95ujtxswbIInD468MjnawX94BhHISZJMhAsa2iutVxxjZwLYc3i5Wc1/eDxxjCOjopiniIhCH9dta5k61yA5j4sc39OhXkNlJwF1LOGaQ5iAlIgLpK1GGKk6sK0dEyLuOuWUvDOoLVkPtYiTOBt9Niey0YVoRUCYzTeGDqnBdmtMlaVXFlCxHoZB+ZLpLcefM/jHMghUXq49QqHwmoLSjwo0+WFuk446yh6wLkzKBj7HeTK4DTff3uhrBcUAp5OIfHt85nvpkS1jodpJeaKBkJOGIR92XsvrtC1YG3r+HJpGIgoFNXGKUCeyc1hIMTC49NEjBHaBspbzd1xh/divDqvgXmZxDFrXig1c7osWCcbnHUNTFOSS6+lGrvOoH6cK/TTKAI5Z3IV7bbeWnHN1afOeYexFaXkQKuzVNsrhbW2G1MrjBXWnLFaVmzI+mkLfKzA+TLjvWa/72X1pA1Jyed1nUPa9NJm7WbsGRO+M1ijSSny4fGRvMhaseu8rAUp5JQYx54vv3zDz99+SoyJYfAsS2ntXZP0po8a+9xERtsmApUpjdBeUysWpVxXg+r63KQDMVpxe7tjGHrevX9q1laFWCXgUmklQGAsraWUrkEbfW1NlaqNFi0gYeEanCOR7krhjAElvP55LuR8FqxEXM9QSjGt4boBOV9mpikwr5GU5bZSWmO9xWhLyZK/l2tzQ25EpC3SO7dU36fHCzdjT98ZipJxRYqAqDRP54kc4Plx4e71LZd55T2Z6CsUjcOxdxZjKiZFnM74FCjLmRQW1NAIZkOHUgpLxcYZXyImJ9bG63icVn7zPPGUEKJW13E4WC4xigLQynsoegixc7NWYsavVPbaKOlVnrfRipQSzy8TKYtNXG1y7MNhx82hZ+wd0xpZ13T9fZ3PMyHIfKi1wejGqI0ft1tKSTXtvMG7n7jRaCn1KkENzT7bdzJPOqdQpqCtwmpDyvlqIJJS/dhet5tZK01Mkd2uZxh68Qi4LCj1EWFPSfat59OMc3LrW2OJZLyxKA9rjKwlNfUbxJio2RHXRIqF5/M74pxIZI7HAbRiXgIhRvaHntd3N7x9dc83373HeWkNYf1oBLTd3qnhBmzy23Yb1m3zu60ef8gVqO2QZNYVxlFi1ZdVNiXXnADke5cDr64R4Y+PEzFKBLnIfutV9gsK5zT73YhCtXZW/s7LvAri3SzE8io0aTE7EcusLbrcOssaMrnEK81ZackWSKXifcEaizIKtSl4aF1BK74iLBO3o+kcOB4GMLIG28Y1lGJdIh++X3l8ONHlQFxX3tyM/PLTO+r9ntF5vBGXJGOF6tfZQnp+T7q84Pb3+K6TbtNYJhRqgc6JsWoCTiHx68cLv36aWIrm5rBjrJWwrkLpzoWsZNQJUezunXGMvYiCKpGjs6yrOBjnUgUwLkK8mpZF0qB/QAIrRfCO0yWTGh52f3PAO8M3755Ec4EURIKwYN+8vmMcHI/PZ06nRcY7Yxj6/kfP30+iCNRaOT1PMuk2Xrt14ioDUgiMhZIq6xJbWKlUuqs2qj08YzTWOW7ud3TOc3qWtY13nm5v2+0ZRE8fMjFmafWdxxrbPPKkLbZGk2prwKS+agAAIABJREFUvxtbsGSx6Y6piL7AVEbthU1XC1pXjDXEmIgxElOg6z1oidQKqzDCNufeCleFY8nb6oirK7Bs+TZUXn7IQhWhVMyScnspXKZmANoAydSwFIqMW8Pgqc2bQOntxq9XGvFWAHQzALFW7N3XmJp/4daRyLehml15SlmsxADbqL9XMZYqVzJQaQVYt61FbsXcGEXa2JhVVHvtqWCNdF6Xaeb57HkVD+LQq5GuQUnHp6Lhco5M88wDEacNH55eyDGy95b1Zid2atqiTUaRqSpjdMFay7DbE4xDlYzpDKPzvHw3EXMg18QlJL55Wfj108zzHEhC1OD90wunaZLuzRpUe4a1luYXoek7g64VRf0oKOt9W2NHlDJo256tpj2bSoiRy2Vq+I3Yih13A8eDv/pM5lQYB8e+4S5d5/j9X33B/f2B775/4Ldfv+cyLSityfGvqRNQSv0pcEJ8IlKt9V9XSt0D/xXwS+BPgX9Qa338l34drcQYo5arzDTHhBo31F6J+06IXC5L8x+UF063FrK2NVmtBdcMHLXS5HZDjbuR+/sjOWeen05Y01qvWmXN5JD1Wk2UnK7tb23tm1JKJJ9A5xyLXsml0I+W3XFAK9hpj1klD++7d0/k+U94uZwk/XcVR+WwSHiI1tJaa21BS3pNitLuuZY+s65RTErTR+oxDQaE7YUprcvgSkDaVms06nNOlRgFeEuXtfEgyu90HvKVhaO/hEh4fBaLsVKuwiINaCtgrbLmqjQsjZtwGEdKKSzLgrVGwLzesSyB02mSoBOE0nxzs8NZwzoHBm8pldY56Ov/L8TE+TLz6dsj48FRdKa2ArAxJr3zzOfI5SSW7ru7gX/zb37BdDpzPxpuvSZXmdV1DpjmN+g7BU5MZzSF424kp4ylMscJUqCmQIqRl3nl66cLHy4S+pFy5uklEFJjhTZBmWnaC6U2bUpC1UDnpaCmlOn7Xn43SQqJt5b7o2wkYik8P114OU0iLFOKaZIAk65z1JJYg3AEHh4voBRD5+XdbFueVBJZFT759J77N7dM08rpPJM3+6g/5+OvohP4+7XW9z/4938E/I+11n+slPpH7d//k3/ZF9BKkH+lJUhBgLrE+XliXQL7g4B3l/PC5SwR5fKyG6j1d9ZcuRbQ0paK0GJmq86oStc7vHcs03zdmy+rAGPrmqBROlMjxsi+VvCHVDLzKoEZl9MsyG5QzKcF5+X2FBKRzMPPj2fWtIIWk8maK85bVFPBybUNWothCm2DsAGBtbXWTeoHjQdQGxnIeTFLiG3LwNbBOPNROtz4CfMcmk0XrWiobXvK1mFsvcamb7iCdW3l6K3FKs2yBkIWbcRhJwvoy2lucVrywtcC3eA4HgbG0bM/DpxeJsIidO79bmDoOxa/4qxmXRMPj2cx2KjCFpCxprFCqRivSbU0GrU8G+89YV0bSFZIpXA8DPy93/uMu31H0ZasxErO6opRYE1FV0haoXPEVOFjKA15fiaeH7h8+Jrl+QPLEnmeI6dVMiWlGEvq8+g0oVSmtslqK386b4kxEULglBRl37dxLZGLjFepZQ/INgG6ztIpxfPzRajkTUA2TSvPLxPGaG6PA97LBitlMaZ5Ps28fxQG4TB2XNaAejpzc9jReUcd5Hfo/z+2F/sPgX+v/fN/DvxP/AVFAK7cHlBKtgHGCdARIo/vz23Nkqh5W5HRnFkENJN5NLN57j18OLNM4QoelhKhpraOawehgNqIOA2NR4mkddtUGAwpy2Gqq4ScpJgk6EFrtBL2nVKGaYoSKuFMa1mF4hySJMooYBh6os3Mi4SK6lZkaimSvpzbiifl9kw+qvZUI0VBxXnD/jhQchHrrSKhFUPvMU6+54/PVrgBpdT25/LClroVldqe28d2diNLoVRrc8F6jcOQs2FdUutcegE0K5zOF4wxAsp6R+ctXmuG3uMHIVw9fThjraUWfRVsGevolKPrI5Ug9uVV4ayh75xwLtquJkcBGAupefrD6eXCGkRL8jwtPJ8ndr//Jftes4RMNqYpJB3WgiLJc6himaYVYilXM2VdWU9PPH3/G95/9zUv04VzSNd3grpZoemmTK2UGGTN2bYWznrZcCjp7FLKov9vHcKm+UgpcwqRNUQxGa3w0g78buzkgsuViASwPD2DMcKCdd4JQGoMaY3EGPGdZV0Tr1/1eN8xr4GX5wsla7HR+5GPv2wRqMB/r4Sm9p/VWv8J8LbWuoWhfwu8/fM+USn1D4F/CEJwEM6EcK6l45VfnDeuJRZnchShz8aeC1GowsaZK3FFtcKQG+gFlW5w3N6N3N4NTHNAz6Ku28xLY8qSztOoqqlkoeu2WZg251I3Hz1wVpiK426HHwxaF2xJdKPsY+dLIBaxotbVEKe1HS4xm+g614xSGonIe3qvmZg5nRa0kSJ0DfYo9Xe+l5wLYRF02CiN1oVx7Lm/P5BK4eHDCxrVIq8N+91ALZXzNOG9FxA2RGpqqGPzBdLaMHSydlxCvBp9CBhnruq3jZexLit91+E7MYMZx47PPrvHaIMzWnL5poWXp4tkFQYJPLXW4pwAVuNuT0r1amI6jh6l4Xgcef3mjuOhZ+glpZdSqanZtWnF8ylwucwfxzbkHSoxULTBtvkdI4nLuTSjEhQqrsxP39C9/hxzeC3FxnbECs+nCw9Pz1ymhdLETQJutm5JS9FNZZM6b9qTyjSvGA3DMJBLERA2CWibc2aZF5yzshpuTsyxiMgsBLksNrXhRjqqKGIuxM3YpVbAM00LS6OiawX7sWc/DlAycVm5TIHdcIN3/kcP8V+2CPw7tdavlFKfAP+DUur//OF/rLVWtfFY/28frWD8E4Cu72rZAkPb4cpZrLCM1gyjI1fDsqzk9tLWJnHXRpxb+i3Xr8oB9l1HWA3LNLM/9ByOA6VkLqdZAjC0ltEjZOTSlO2Dcpq8tjlX14+kFtV2+7m2DsDIfJgSdZEXzBrH2A9Xz7ywRpwxKDb+gWxAjBXjDt1IHijIuYV3NFpxqZXSzE/btH61HTdaS2z4EhuQKmDT4D3LGkkp4azFGWmD50U47lSwWg5eaEYmtQp4SBWinreGzgtbzVtBtnMTJeVcsEq8DixbWIg4MPWDxxghSd3djBhtEYMOCdl8+Podjw/n6wZDyCya25sd6yqKRm0cww6OB4kh2+1H7m53DIMQbIy2xJpEiGMNMWZeniZx64XrXN4ZTQqBbJ2MMBaJbneQIxJ6CqAyy4dfs776lHE4oO1IdQ78QMAwRcFOaN2ioDGVVMC2UTFXIVXJOCfPMOeEQtN5iy6a3Lwt9CZPz5mstn624SRKg1HE5m41r+mK72hjGnXdsa5rY8BKZzFNi2APWhHWRAiRh4dnDJXTeeb8IpTiNYw/eoj/UkWg1vpV+9/vlVL/FPg3gO+UUp/VWr9RSn0GfP8XfR2tFLtx5HQ6iQ5fa3KBWgvGS8puzUL9zTqTM1devNhUSYVVVHY7z7DvKMWCV+QUyalwPs8MnWt0zUzKAkgaI74AuVVXcRSTPbmCK4KvtaIq8RKoVVGiMF3EfReM8ihryVljnZGbztvGU4jsD4PcnGsU4kwrjc40x6EsuoWNPbi9eBLOwRUM294bbTWus2itePXmFqXg+fFEWYt0Bu2N1Ebm6nmN8qyshku7tWL6ncRhUDgv+QGi7JSOYJrFzLWkShJrQqwWn4IlSlrvMHTshw6DxWWNojKnSDEiVTZWsJ7tr1rWwPPLCesUt71DmY0fUjgcBm6PI1rZxiZMVCUjTgrthmzPJAYBImMSsNgZRe8MvbNYKr0F7S1GV1JtEt5SSLUKgWY+E86PdGEGN1I0JKWJ1bAUmfkLkMrWaYgDfVvcUGvDTqpqKtNm3U7rtK5+EwatNAVZDba3CqhUVYhraEYyMrZRynUc9N7TDz1d35MeHlEodjuRKE+XudnZS8H//vsnlsuCMYqX84JzDmd71vWvIYtQKbUDdK311P75PwD+U+C/Bf4j4B+3//1v/uKvBYd9T4qRECIFScoxxjCOnnHnZMaulceH0qTGm5cAjTyi280Gh8NACEr2pEozT4HeO26OOypy+89zkBUhDehpp8s7yxqR4JAfGIqo3Nx4nMiOU5GCEaOARc5qUZItFWsH9v2e9RI4TxOwtbjSTsaYRPWomq9A2kxU5GPbyztnGYaOeY7ENTXATIpfKeJhOBxHbu8OnE8X1pBwRrc2UzgCKSZy0+17bzFWCkeM5erHAMhqD03XdwzDgLUi4LpcZuFIFMEvjPWEJVJLblHomt3ocVYKn66Oy5Lpe7Ev++7hmdp8CrXSWN26hypekMsaWZaVUsSsZA2Jr756Yr4E9ruB3b7H956UIsss+X794FGNkZeT7NJLw4qs1nRW4ZXEmvve0429zMQxoFLCbCW+iiWbqgI80g5zqppLzMwpk6rw/2P+SNZCKWytVCWbhU3dGdZAh6IfO5QSyjFa4+1WHIwwKYP8HiWxWsbHZZWtjZDgpDiYRnnfIuVyI71tbMCSk6w4x7ElSxVeni8oFGPvUaUS10AMwlv4sY+/TCfwFvinTTdvgf+y1vrfKaX+F+C/Vkr9x8CvgX/wF3+pSk7SrkobLAaVxhqsE6KNs4qb2551jaxLEm+nNoetS8SMYqYZU+H0slKrZl3EIsxZg3MSczZN4u1mtAGjmJeVLSlHed+88OsP5i6uI4H3qrng6pbRJ7Ot4BOyXoLKrAL72z1jt2tzbmqrS0PvLZM1mJb/V9sW4rqm0yJUUUqckHaHgVonSizX+XxjPuYi/oSP754lzSikpsDT1/VhimLp5ZwUgHEYUFoT0/n6vDdSUimFdZF2M5XMOPbXWbg03MAombtjyixLYHfo26qwMk+RYbBoZ7HDwHy+CJ9iWpkmSUDeth+luTKdTpOEnyhR5eVSmS9iMf7JJ5Xj7QHnHWlOnM+zMPq8xhTDGqT9pY1UWsHgNJ1WeF0Ebxg6nFXkWImlXm9kow3FGlS3Y7x7i/Y9sQg2lHLhNC0sq9jVzykTSqEo6XC2VW1VirVuuZCC+JtcSKVitICqrrM4I+NVqVXMWpxv2ghJetZG0ythosYY2/vGdfVroQHFqn2eYV2FR5BiprKIFLuBwd4a7nYDZyrvn048PlU+ffvmR0/f/+siUGv9Y+Dv/jl//gH49/+ffS2Y19rabUMJol3PsaCr5XK6gMoMvZVVzhUxb4y4UlgWQVitc1zmwHReBY3fdfSDo2rFEiLLGompopEbWIGwvXIlqEQujTJcP44CcsOICCmlgvcO37m2fpRDZIys5EKQW6ksHwhB9solCZ00lEqYI5vHtbP6yrYrueI7AW/CKsIR511D9uUA1ygxVrW0TAGlWObAY3oCVHMs4vo9bZLqyqYjaNZpiBOxNpqaajtD6pqZN00Ty7pCyaKP8A42uzQl2ITIpzXGeC6XiLEKXTOpJKxXDIjacj96fv2b91zOskIstWCUFL9N0zFNM7WZuIgyUrfiEQhLYF01Kcn7EKKYhtwZTQrpyuEoVJR2jM7gdMWQ6HTF6YytAWokKMFckvFUo9Ea+ttXDPefUfu9OPQ0FuDlciZneR8uQdKpTLOD0+pjluJgLdNG5VSQSiaEKK7SbYSrNTfqemoZA7QNB8Sa5LkihzsncSIOSZiExYJr46ourS2tNLBRQPQYIymJL2OplQ/vn+lq5TI30FBJAO6PffxEGINCFKGq1tYhz7S21n2KLOvCs9pu6Y+fu4VhxphwDdEvSRSazso4cfvq0MYF8e/vux6tDPP5QsmV3EYK6kblbKkwRYJEaJhDWJOIVYy+zqbiJagFKW6HaD8OjKbnVMTuK6bMeYqUlFnX0Ki8mZIL1rZ9PdDeDwpaZNFt90/9uEpMeXNYBqVlJZU3JqBqVurN2dgag+nEzmxZRR15uUxyG7c14ZaHAMI39863+bLgvKMfe7DyEislkVmluf+kGFnnieotuvYoY5iXlfzwwLLO9J2nFoO3HcfDvr20lcvlAohSs/OWcRxa/mNhXYWnL5qAmV//5nuUfcU4dIx9T1gSH96dKVmxH8XTb3NxgkznXctCqPhO1oE1SdG03rHOiVg1ndLYUlBuQLXkZXFAFun6vMo2Z46ZqY18tMelG6ejGk1N+aOEe3sXUwElaH2oFaq8K6U0/0yQIFQDpSRq/JhGtflXpCyOVUbrNpo2v4Va2e265lPp8J1v7444C5VSuCwrX717ZDf03NweUVbz9PTyo+fvJ1EEoHn7A9QWXKE1hcJlPhOTZAUAxCW2tZm6toG1VNA/0MMr6DpH37cDmzJGFTrvuLs7EEMlx0rtvdwsMeKNxVrHmsS3IDXkfiPpCVOsoHIRQ4jwkdsQY+Yyi2TUGcu6ZkqdSFmIMcaIj8Em3dVNqSOuMAYNpPrR2qzUKmDQaLm9G0hLJCxN+5/VtS10TtyNaK1lbisTyTYQ/v5+PzKMHQ8Pz5zPE8PocVb2yXFVFKV+CEegKBzGnnHf0Y89OWXG0ULVhDWQ14imUZer4BSdH7g53jBfJpY5YJ0o4h4+PJJS5dX9LV98/omEvk4n1nUmF+lEtpt/HDwYzTxnzi9TGwUtl0vg8cNMvRUrsZTFjPXlecZZg7YabbeMJfFLkBWetOK1CsXbdWJPFotsfZw1mATWetCuOTIpsY+fJsIqiU+ptM9R8MOnJOvBIvmQVyangLFy4It8b4hZbc6bdfv27tZrNyQ+Ey09WitZ52k+4kYNxC05c9j3/PzLtzw8PqOUpusH0bmskdoIXtYa7o57fvbZG/av7qhG8+13P47P/zSKgFI45zEKUo5SbQ2oXBkHh3eS12et5LyvMV4Bre0WdcairOz5rRN3FWdFqbYsAe8sd7d77m4dD88X3n37REyyWhH/flnL5ZTZ8vFqrSwhiO9fLSRoLkCy0xWp7TaPCoV2WSPHvvDJq3uepxeKE6u0ofPoKus2bZTMcu2lkM5AZk2lRVAk/gmSxVhqs1lvJJ4tj0Hm0IwtmoJIgQWVKPj+IwiokCJxc7PH9/7akm7iq+1F01ps17y34ERyfDlPssHIstpqBkFkpbDOMowdu/3IOAycT2dyqAxOxEfTHNrM+sAaFnrvmC4T07TIilArqldkl7mcF7Ciqd/8E1NIaGP48O7M1998IMSMdxZnHRqIS0YVjbMa5zU5tPj6tkTR3lGKbqtmMKEVWA2dU2hr8ftbdLdDVYNqh73ElTSfoSbm2IJCNjC/gchazjFFCzKv1MdDvBUMq4WktYQoW4QmN4fKlignBK6MzrLlMkY3uvaGS0neoGtcmNdvXjGMI+XhUTw49fYu0XwkNPux5+e//IJP39yzOxxYYsD+/yGLUCkRzaBNO+CNVqslmivk1mZ9XK3Kp7Yf3neOfuiuaPhKElCwc5iqCDHz/uHE4D1bQk/gY2UulLaL1uSSGxlmC9zIVxwip0zvPKWdf20sNReccRgr4M6buxt+8flb/uirlZmI9+6adLusa9PIf0zcoUp6cUFdg1RBLKSXWSjNQlVtyp+GFzhvsVdXYNEizOtKiAmdFSYV+qNlf+gY955h6Kgo3r974fR8uTL2tpFWG01RcJlmTOdxrdVe10CtmqHzHDvPEzAtK13vORyOknVAYfCOMA58+slbnk4vTUSVKJfCMgf2+wGQ4NOcxYTEWsVxNxJKZsmVsEq0+RqF73AzDigqjy9nSoXjzY79jQMjJCRrnRwQbwlZdCOG2lKmFc535ByJdYuW0yij0aaA9mTlqdpgjSfPMyVHSpaRMGRYmueiUVu7LuNoQaOtpcT1is9YY6+A7UYeEuNXGQ0wurFSYbs8jFHNW1B4ATqJ/VitzehVCQdkHDtev77h/v4WZRSffPKKdU1M0yrr15joe9+csQRQPRx30p16x/2rux89fj+JIiD66swaihggKIXRjqIg1UwImWVpGvmNJw8fEfVGplFK4Zy77ldTu9VLyQy7jvNl4fnxjFa6tVfl2uUZpdn1HTEl0iXJXrh+tCpTWvbYxrnGSMxi6R1l5rcm4rB03gtv24mTzxQiMTWgsYg+vut3ImCpE723gnC3lmZT3sUYSVGKB9uass2dIMVtN3YSbqIVa0gsawTEjacWmRFf3R/5/LN71izFqBR4ejw1Y9ba3kWZa5x3mM6xhpW4RMa9oh8HjKoi0x1Gjn3HrjOcp4UpJ1BiZFHCC+u6knPkfHnh5XxqnU6BorAKlvMkfgLG4pwYwFrnWFKm6opzmqCF17AZm35kAioZVY6eT392wzpFzk8zp6cT54vQpnV7UFprCpo1yJoQFCEFGWG0IqMoGLTucMMe3Q3C/dhMX7TGWk8pimtWJJvJSmmpWLDkdruDrBuV+AjK70FwJVU2GrYUaqVrwwXaONDeP61180eQUdQ0pqfYujt2u57b2z3DKMX89f2taGPOMwV4fjkLGzLKKvX7b95xsIZYKi8hgv3xo/6TKAIiixTlXlglbKFrRg8xRNZlFbbcDwI5ZafbTgfi+xbWyDBIUIlzPSFGlnmm7y3eaLI2LEkIO2lNeG0wTktGgTHshoF1XZmXldq6hGra36U1yhps57BoSpD0mLSupFyvLWjnrHDHa0N0lZJEZO84FTC248tf/T7vH97z8N1vMEboz5Ja3EYLLavI+bISlsAyB7Gebp2DUoqusww78VywWvP8PAlirRTD2FNyExk5YRG+e3jBWoNzmmWe2rOT66a2LkemWtUSmBLTfOHt4Zbb44GaQHgUms/v3jLNK//iq29FBXd/w3ffPvDh6QXbWea4SvzY/S3LMpPXhCmStpRVoRtHlBLyUMlwmYN8bW/onMUozWUSrsbYe+nK2MYVhzeaojX7Xc86B1KU7UpqBVtrjTGW87TQaSdsTDKpigDJ1kzIDmuVGJ7GTKrNtl5p/Ljn5tVbfvv1b4jlRURkctKpKLxppitVdvnWfBRm1ZBQbS6/vTmQc8YGYajGuLk+NxpyA2BRUuKcFYeqDfXfbqjNNzOskVIvxBgFe1oCpSoeHp9ZQ2qU5JVlXnm9G/jl519QlOJ//l//N3773YcfPX8/iSKgtb6aI65rQluL8fZKpCmltLZXXRWEWwkVP8GPEc/CyksMo8U4jbGV+7uRZYmkIIENqc15x92e3dDxZ19/J2EiWpKRNxNP2soypiR5gsZIa2jE8ShnSQu6yp9TSxaqtP017Rfb7J40dH7k7pOfkbTh6d1XV/mw1mK6saUYSWgoonBc47UjoXU5fe/4/PNbnHeEkLDe4bqZZY0NaLJ0vSdWeP984f3DJHRbVcghiqcA8p5t+oScJc1JJK+W2xvJFETB7jASppm73cDb+xueThP+e4dWitv9jss4M/QDyklB2fc9Fs1Jw1RnltMsRaox4ow2GC/ahlJrC34VnwjvHKnLV0/I0rQdMWe+++apMQM1x/3Iq1eHFsARCRvnQ14MLnNg1BecF++Jmtt6LWSCT+BgXlbsuoDx4lFhHP3+wOHVJ/jxhsx7FFkAVCUdQEG2VBVNQqjKqbk9bxwOucUNzgs+5Z3lcpkkW7B1ac5/tKrTWgkZqkgBcZ1vNGNhLJYKlykQny84b3l9f4uxjvky8/R0oZTKm9dHhr7jxZx5/fqOcTcQU+J2v+Pp+a+BMfhX+aGN4fbuSJwjKSZc7+h3Hmc1w07ksimWRhJssLxuiHCt7cYzdF5uun609KNhXaXtsjXjtaxrrNWN+lsZ+45Pbm/5/v2jkH5qJaRIRm7x2m4VlLjYdL2hHxx5yY2YocR3j9KcjQz70TM2gxFrhfC0hszD44mX04xxhT/943/G88sD50nAMgElS0OSpaB0nZCbUtos1H73mYVVshV2ux19N9B3I9Y6LueVZY4oZbHasYbMy+nMNK3knOmsak3UdtXUawdQCoRVnvPx0PHpmyMo15yEhCF50wuBaA0RrRRPz2f+OH7NdFkZ+p4lBpYpcLc/YHzPu+kdOQrK7bTFeod2roWAWFznuSwrS1iJTRjUeUXnxGH39vbA+eXSuPsScPLt1y8c9j33+wP7YeC9O10ZkqFs3oyFvCZOauLOjdSqxeyzNZCxKpT2RBRLmLGdcCjE/sxzOB7ZHfbShSS5kps8qYGySlLgTQOW66YPEet63Uxhck4t6RoOh2Ob4xf6oeP2/tjMWHuWeeWbrz6wrlH4F9bgmj6iZOkCzm2jlJotW68M1npub2+otfLpF28wWnE+XXh9dyTFQFgnvnx7xxzCj56/n0QRME5z/+bA8hg4XSZM81fb7zthUCnN6WVhuQilWA6l/kh5RV6am/2Bw82efuzRSnFeZpbzylRXuq7DYOiHDpTifFq4LAsv00Rt/GxnWiinlSCMNQRqykKWacaQ1mhCjc0O3GI6L2NI53l1s+fTNzfc3x44n85iVzX0nC7yd+VaScvEb//o/yDWj7mFsdFBaR1A31v2+15uzPY9lR8QlxSKvvd0nafrDKVaCGLbLroBg8Jz2O9JNfPydBFXG60Yxo5lWuXRNdefjQ5rWqeTG5vPKokCf1kSIS7ULLfyV99+zz/7s+94OF3AWUpWhCWgtWGJEdUk0X3Xo7WlM4n9bpD/jqZqzWAMzhj2+wPH3cjTdOHx+XRdcb55+0qcg0omVWFBemew3jHuB+7vb/js7p6aMnn9KCCKqYjOIQvr8bkEusGhtGeJkYgma8dzsnTFwjQRnz4w7FN7bo0ebhVoyHzsAGjPKZdmUoKkShckFs05RymRLcU5xkxJqaUDGW7GkbmbiGtiHHpubw5CDFpjSyiuiIejdJXeSo5DzplpninFXx2rX04XYso45/jyy8+oFLre4p1uXhma0VvuxpHDoHg8nX70/P0kioBqbXdI8iIdD0f2ux1OG1IRe2ZrDMbmq522ONRKA+aM4dO3n/DzLz+jolhiJC2BtGTWJXMyHabrOR48+/sd3RSYz4H9zZGbV/erGiAgAAAgAElEQVTszxOvb27wunI5n1FFYTrpBhQSXqmtoWZIa6akbT3Zkl+qgFwhF3Lmo5lnKVgNxlk63+EclBhRMXBaGoNr0z+0udB7ze3tyPFmJCcpDMtlaRkI8iYqrSWO6zigtKXERlnVRjL3QqZkzfGwFwGJVlC/ZZqna4rxdTGh5DlqJSy2jRvR9yJa8V2Hyw6lF7TNwolPmdM0c55XOjSdFfzkPF1IteKjwxRJ5j0cRnTQvNkNdF3Pn3x4oWrLL97ec5lX0JK6PKRA2Y9o7dntdtweD8QY2KvKy+PpKuUGOaT7oedmv+fx8XzVJQhfPzefQzm805q5TAtdp1hzZakwZ0WumlGvzO+/5k55UI6x32NURatCSCsSZSPjzWa2KvNTI/8g5riZ7Xfe+AnWNnZh5ThKOIhVFadoZDTpXtcQeHo6M01LM4ONbC1fLfWKE4VVOuSoE6YaIHE+K87nqdGQhcEa40rJGYXj5z//OZ9++pqOwIenD4z+Jx5NrioY1ZFzZRx33Nzci1RSC61WF8fgQRXN4hbm2iy1tpfCGsZxQClhrHnfCWimNV/+7HPevLnjcLNHNR97sPz88xd6LyvF8f0H/savfkGcL3zz/Xu869C958294u72FmUMwzCQcuKb794x10lotM7RHw5suHSohscp8HhaCKkwHm65ffWKcR+5Pb5mXQPfffstukR0t9ANAzkLEs72QpXI4ThyezsQY2ae1+bFv+nW5Wfe7244Hl6L4Col2d2XiPMjr9/seX5aOE8Lh6PBj2LzFZJDa8eW2yhEK0CDsY63n75FacPT4zO/+uXf5O1nn2G95yYrbncPmBy4UYVSEr/87BPWP/uWDVxIWeLfJJ1Xch2MUfziF1+il5kDmVgqx9tbtO/Y7Uam1gXtes/tbs9xHIiIbDjMK51R3O4GDuPA2PesKeG8p+SML4m9N3zIsVGGBYUPqRKbAo9SmJbIwwscd5pQFO+C4mI1N4MlUbhMF3YpoloYSlgW1vnCvAYwFu8dIYZmrybmsBkwpZArLazVNY6HxTqE1Td67u72vN7t+e79E7333OxEzluRhKlpFm8F3TAm4z6a5jrvmvNwc4GCa0BJ3DZbjd/xzVff0Q99s5Wz/P7v/T5vPnmL7w3EhHYd3fDjEUQ/jSKgNEY5Ot8zjh37cSdWTcB+7Bj9QK2ZXDLOfsX5dGm21vL5WmkqhjUVuq7j5nikM5r717/k9Sev2B0OGGMJ7bClori7mzmdz/zxH/6x5Lp5T0mRw82Bw/0N++MR1w3sdzu6zjPuRuZ15XC84cP3H3h5fmF/OHD/+rU4x7aduCqJ0yIAzy9+/29xf/+Kl6cXHoZHQojtxq58YhSfffEFa1hJMbLb7ZnOF/7wD/+oedYbai7U3A7q9qwQ56VP3v6Mn3/5t1nXlafnE8Ow8PT0xLDbiVX17YrSltdvXvHw+D2XaUX4bYqc20i1GW4ohe89v/wbv+J8FjXi7/3Nf5Uvf/5zaktlfji+w9bE/N1v6S9nXt3eMHz/wGlemRooS4Wbm1u++PKXaBJrSNy9/QQ/nejjxLvLwu/9wb/GsBt5/uYrLsv3xBA5HvYc7++Z54l1WUlZ4YeBY2+xKtF3snZ9PE8cj3usKdzuO3ZOoUvaXNpQKOaYCUno2ijNmit1ClijmbLlKXX0uwPOeREg5ZXDNBFjwPueeZ65PD0TlwVnHeO44zwtQGNlFrGZN0oRC9iu4/+i7s1hLsvSNa1nDXs6wz9FREZONd26A6hHA4m2EBIWqKX2WsIChNQO+LSH2y4SElIbCNph8MDAQ0JYGAi1QLfv7VtVt6pyqIzpH860pzVhfGvtcyIrs+pyhVCwpczI+PP8++xhrW98v/e9u7lmnGRiFQzJRjZX13z2yUt++vI52+09MUGt5d1V1kgq165ICZpGYMD7/YFUhYX0ZZpnSSWMgI7qWnQu5tmR0KKZ4D1ucgtK8vrmmrrS7E8HbDI0yjHHRHdz973774MwApWteHZ1iztO3Nzccn13Q7dqZd49waptxMq7mf3TLo9Wvi+U4WLCNh13N9c0dUUYT7Rdx9XVNRibOd1kMMU5R0iKfnDsDz3T5Ngfe5R3VG1HUBWnKaLDxOO+p21b1usepTQ31zfUVcN6u5Ueuq04Hnum2TNNExp4sz9J4fBeBCUP+z1PuwPWVqw220Xm+6MXL1h3DXNM1O2K/dOecRQW2u26oe977t/OxPRu6ZWjRH/Bucg0R5SqsKZhva2xTU1lK9ZtQ2haVm3H7d0dKXhevjzy4vlLdo879o9PZ+wBUhcwxnB1tcUYw36/zzWHCq2lOKWVktHU2XPsJw79IIIvSCRX6Lk/+ugZ/8qf/AH9YSdgq6T4zdsH1kw4ZfnB3RVN1/HwtQw0ibScylyFMnyjQqStDevNCnd4kpl6K2PVV5sOlSLrrgOlmb3n7mbDHCP7/YHROYZpkjFeK9HBcfB0teWkOuz6GVebO2JKHAYZTDNvHrm9G1hf3WKbdpGEM9pgbCVeOCWmkGgyiYt484DziWFyECEmD1qxWq14/uwFLz/6jM2m5vbW00+B4/6wzMbI70vdwGjP3dWaisQwS/3KeyGfHYZcCAe2V9d4P6PJzz7Xxop4jbIKVORxf8+vf6PYrxuq5GWWwv5/yzH4//iw1vLxR8/x00i3WrHddKw3GxQQXBFnBDMl5mlcGIeappLhEyXQ0GmaOfQ902yZjwce+5Gv3+64ur6mSI1XVtoyPiQOp4Fhkmms06nHEHFRMex7+kkm85SWllXXNWyuNlxfbbm63rLuGgiBx/1BptZaQ3IyYju7maZteP36Lb/61ZfM04TShtVqRduJIo9RisNuT2VuqLsVyQemaeL58+dUdU3TNDw8PGC/er3gAxZ0Y4zcPzzx9TdvJAxFIMxN08hASYoklXDB8fT4jhg8P/rBD1mv13z5xZf8+osvylySNFoWyEDisx98RtO1aJXw87AwHp8Oj4ReetQezTDP4p2qiqoScFKaHSoFmkpx+6MfkBL85V/+mvvdgZMGWyv2j/fUfcPQ92gFd9drbjYdN2uLmxSTUfSTww8H2ts1T4llsrOtaq67FVbDs6ut8DlqzbprqcwRrRWn0XE8TYzDiKotKQWGyXOcAnujOU6Rl80aHwJ96FEpcBoHno57tnfPBZWZCVNFpHbOsO8qo0jDwm3pvGg3TENP1zZobZjcjFcwHvf0uwcme8P1quV0fMcXX79if+pldsRHkpowaDZty7/x9/41/uXPfsaf/fxXWKVRJlF1DcZWy2h727ZMY6LrWkkLk7Qai9COtYrKKmprGMZRZiBOPbc317TXH7gRCCFgKsuLj1+gjaFqKgEGhQBKuO1MZZmP4rG1MXRVxe3tFVdXW0iJm+s1q1UttN7DQPKe/f7Im3dPrNcrVquOVdfSZW6/0zAzzp7TSboDk3PEIFDVZtXRdi3daoWtKuZ5JnifZcNFf6BtW1aNCGaCsN7G4JimiZg0KM3b+0cOTwPTMMl9GRkrVSRObma/P/DrL79he3VF0zakINj44Gf284zLyLFLvoGUpI98ve1Yd4Ies0aTvIhbphiY5hmfBGwzG0vwgd3hwDevX3P/9l6gy9bSlFFmH7BZTu3m+ort9Q1Vu2GfN1N0EziHjoF21bK62jJ99Q3DOGGM5ZOXLxjHkf2x5+3bR/7sX/6CbrWClNg97lDa0PtApSK/+fI3NE3FPI5suoa/+cc/5vb2GltXtFXFx7fXAo7ynsYKN2LT1ECGWcdE1zZUtmKaHXWl2XStUG+jGJzncJroTxNp9oTo8SFxnBK/PDxwqjw/+ckfkYzGZyMy+5nDcc/j071M/rlZpMqCOAgXAlUwAhJKYMiRp7Vsak3XNtSVjA5XJuex3mFSpFt13N1saKziz3/2BTEm7q43/Ks//gyU5tXDnrvrLR/d3PBLLSzFWokqU0KKwHWOZKfZCQFr3dB1DYTI0PfUleV63dFYWR+nw4lGaZ4/u0VtNlR1S1P//0B8xFaKZy+eCbVVErKMyXsKg9DxOPD1b15zOAhTT1XXhKSYfeRqu+bZ81uub28ElTVMjENPR2IYJo6HPcFNNPaawQnH4O44MM2O8XTKQxuyYKpKmFyqymSxR8d4knafip6pPzGPAvetzRU3t1f4DB8FjbYm6/U5rNW0tWEaE7VRdI3Fhwz8ybTUx1PP7mnHatXKgrcGH0VMBKVIwS3IsYR47vWq5YefPuf59QprDW1TZ17GSJgnBqMWEdBxHHj77oF3796xPxzwPjJPE+v1itvbG7TR7J/2QgoaHa4/0K7WqDASXcTGiDaRet2QWpEgO/QC/12vVvhMseacz8CtyLt3Dzj3ltk5vJOR6boy2Jg4vX6HRtIHaxTvng6MQUBf1kiBt9k2DLsDX7/b0/cDD/uecZ7RxvJ0HLDW8tR7wjTgo84h+5ka/s1hEEq0UdGHSB80o4GvHg6kNrE/7rF1I9GLUqgYcMcdD68E6rN7esc0jmIIvKj/9LOntZoKcU5BdPKy93fMIUg3ZL3GWMNxmLLaEjzuRx4OE/3kBEhkDElpZi/iNG1lePXNK755/ZbTcWSqZHCqzBYYa0kofBCq8ehmQHG73bBtZSq0ri3T0DMNnuNholEaf32FtppWy9r7vuMDMQKR3dMTq6sbmpTQKjGOPbvdAWMsShsOhyNv758WOqV2tSImkcbSxvLwuCcpRdc0rLqGuq2puhm923M6HpnniWnsRVUoeKxO6NoyrTrcOIgwZFPRNeCTpCGPh4OAirqWVW2oCNTaYrVCB8/x6QlT16ICFDyTDwL2MIIf74+9kHnEiELy3BBUxsxbbA51x2GgP3lWrcalrEg8TwzjyPFwyL38POVD1giMiTCN4A39nGfghwE/T8SQ0FmJeZ5mnh4eefP6HYf+xDx7pmlms9lgq1rQbM1I8p5X37yGmNhcjUTnqK3h849fUllD7wynaeDY9/TDxO3VlrquGb2kVfvDgYTm+uqKVdPhq8hWyTCWNeLRBRchNPCV0QzDyM+/fE1VPQCK1arlb/+tP+Hm2R191GgHh92JCU3TrYQWzUfmkHg4TTw97okp0s+Bh0PP5BwqJd6dRgYXUCnxeBiYTEO36fjpn/yIYfI8PD5ye/ds4ZiYFex3jxz3T7jgedofGGdJAybnMsGMQIdVDBlU5pmjxlSatqlom0bqDP0gHAAh8IsvXrHvR+q65c27R949HoQAZ3bcH0/SQq4sh2Hkn//5z/nq1Tum2ZOUpsnMVT5EaiVcESFMTLNAyH3wGGN5eXfDPE+8e/fEMM10XUelNa/fHZn8K5k7aDtW7e57998HYQSmceb/+tNf8PFnn7JZd7RtzTRN9P1IVTfMbuLh/on9oUcby/aq5fa5hKCnwwGjDW/fPXL/sON6u2Z7c42pWqZx4nQaRaIrz1w3bctwElWXummISpNMxcOux88T3nuh1o4i9qm0Ylq17LTJijcZc65EdFLA/oI7D0lw991qJXz4h57j4cjYD/S9FSpqozMgyWbBzSgMsiTcNLFetTy73XJ7vWIcTxwOp2VEIsUs44Xi6XCUyTMXiLrhOEy8efUbrFYCGjJmqWYnH0Tqenb0WdFZac3sZoxW3N5csW5qXtxc8cd/9FM++eGP+eVf/iXDYc+zm2viPDP3PfjA08MT+zysglJsVi0Rxe54RJGEc8/PECMYg0XYdyyROTiiEz1Gn2TyT2ZBpP2xOxz5F3/xS9Bf0A8zdVPJwm4ann10y4u7G3yI7I893zwceDpMKAVCzFOm9oSW+zhMGBK708gJz8uPNH/8B3/I4TTw9PiOoe+BRFSK4zTRjz2GhHOOx/2Rh92BfpwYMwlMo8GEOWMGFXOIKGtZr1Z8/vI5N9uOx/2BV2/uhVglJd7cP+D8TF03vM6bNCVpM151bX73orNwmCahE8+8EkoLJV3MhDJNKySsKkW0sbTdCh8cX71+I+S1s0MZ6XylBA+HifvDhM5aCOp79h58IEYgAcPoeP3qLce1FAVjkEGLEDQ+gLC5Vmy2V6y6Fduba6a5Y9011LVl6HuUUnQr4de/f/NWGFyNgI+8F9GHuunwwZKmkRATyTvaqmKeHcNpFFiokQVucg1AyB0kLJ5nl/UNpLjYVAZtLVNAAEVJkY49KXhsErDIVW3z7IBi3bVCg2YMJr+cEKTnDInNds3LT19Q1xVd2/D1l6/Y747Ls9JKc3W14cc//oztes107BkGT1NXDLuaZzcbPv/kI+ldZ0q1n/8qUZkEKTBO97Rdyx/+4Y+wVY3Vmmd316gYeXGz5cXNhlUNz+6uGdtaKu3jQPAzw3Dk1Zs3Ek3MM6tuxY9/9EN+8+aB/eHIOIw45ximISPmPCkGHtOZA8FHUV7+5OULpnnieDiJ9mFV8Xia+ertXohmFTJDECNtJTTon9c1uMDuOPLN/Z7ZC5OxJWSZr0hnNbfriqqyHE4ju37iMA/o+yf+IARur7YM/ZHd/glbN7SrjhAUh/2ROI0MQ8/D/sRhHNkdjwzjiNGKRkGVpDd/coHReaypGV3g6TSQlDBUbbdbqskzegFLWWMIzjMM0mZUSnE8Dnzx1TeS90cBGhVOCRkh9/gQMk5GdBxBlKXq2lKh2G4alEo8Ph4Y56LNKelxigqtA6EfRS76ssf8HccHYQSUkjDSe8/Tw47ToafJAhhaz6y6lquuwX70gmEcM8rOc3e1YvXxMybn6Y8H6soKxVU/YKLn7nYrleNOUodS2b5Zd1RK8nRLoK0kdE5KhpmMNqK+671MtRnD425PP04olVVxkOGeprJMIfF0HHBBoJ7X2xXbtsYoUfjVSZiOpMJbc3tzTV0L7ZfOeXTK1XnTNFRdlwlADX969zO+ef2QWTLUwqg0R3Ap0a47utbz7Kbjs+d/g6YyrLp2mYU49j13dzdUdU0/zuxOEy8/fsHf/bt/i9l5DocjRmvmceRpf+Qv/uLnzH/2M47DyKqx2BS53axQJNZtxd/46Q/px4mHx11GIyYqFQVIY43MMrQNxlTM08g8TyLgkUlYlM598toyz7NwKNYN2lYoHYhJOAQDCh8l9wXYn0a+fPUO7yMPu2NmctIon+jdyDhOGK2oreaqbfjs4zvm2VM3FY/HiT55hnHgxbPnfJIi754e6aeBaZ5o6hpjKsb5wOzyAJaWcWlja6pKYZWnVoo5JZ5Gh4+gkhLWIVvz0Q9+yHa75t39A7/61SvipAhNzW4emYeepEzuZCms1RwG4Z+cnUcpnSPLgK2EfdhnxSClhTFqmGaM1xit2Ww7Kisj0pvNhroKQBQ8S9NQG5mabeuKymqcE1q9X//6l9+5/z4IIxBjpJ8cfd9zPJxIQNc2eUZbs+pajBUFmpiEUyBGYeZpViswBlO3BCLH3YHT8YROia6p5RyTYOWTMmBkrLe2mq42tFVH1wg5R1VVWdlGszucSMNE3dTSLtofOU2elLyE/SAz/E7w20kpqd6GwNW6lZeZhOE2xYRBMznHcTqiTMX1lRgehYT5MQo6zJpKlIQDTF4xC3A+zw9IEXUYZ16/23EaJjZ1xVVt2G5W3NzdEL0IqgZtCM4xA9V6RRhmbNfx0z/8CZ9++glX19ecTgNPuyP9qed0PPF2HPnq9UOeZfCss6rTqhEmH6MT8zwzTTNTpiH/8tUb9oeep92ecXJ8+fWrPGWpFhbnkI2cNVpGcJVitz9hbSUalGjCHImqwthEzLMUhe05hMAr53nYnVBKJjR9lptTOY3yQXgAG2u427R8+uyK203H3/npJzyeHP/n28D9u7c8v33G9fUN3faKr7/5it1hh1HQ2IpeGeq6RVewHyZqW/GTz3/Abv+E63fsfWQOkSlGoq4oegNt1/Ls2R2fffYRz57dMIyB6TePUrtpWmqtSUpDDGw2HTc3G47HXohqhxGSQMxDRgi2XYtBUtIYzrqRIYgYSQyJ4CLX1xuuuhVEhcldkquuoa0sldHU1orO4+w45Ujku44Pwgj4EHh82jP0J8ZRrP/QD5AiVV0zZbBK19TUjXDOp5A4nnqGOUNXAe9mxmliGmdSCAyj5LyrrpWx3rohojlk9iKdp//ayqCyR5acMnHoJ5wPrLqapq6YQqAfhS7L6pOQYmYFn1UeShoGmdTrx5nTMGOMZpikwKQ5U0f9+tUjt5uVQFBjXCjOdOYC6G4k933z+h1P+6NIkGmEhEJBP0z86tdfU9cVq7amIvHixS13L54T/MzYj2yutmIArWFMipMP6Krm5vYGW9d88cU3OO948+YeUuJ0PLHbHRCNHYEnW60zW00QxibvmYYeYliYd0vrcr1asd3ojHcnIwhTps22eVzWFNyLMPxUNdHWDE64AFIugKUUKEKkC6f/LPetFlyEWWYeUjagWimerRs+vdvQVYam0mhdYWzD6jjzxf6RP//Zv+Czz37A5upatAS957DbUSnBWazqNcdTT3AztbV4PxGjJ6IYY8LJnLDcow/MzNy/u+ft69fcXrU8vH0LfubzF1fSccmAnuCuSSmy2W64vrlmv9uxe9rjZok83t4/8PU3glyMiHKzPMcyVCatUu8cIYKtK5quIc6R4EGbmuPoOZ6EJdr581CV9ykTnXz38UEYgRQT+90B72cR4kC8RiKR5hmtbaYVH6nqGltZWWA+kNQo4Y73It5gRWXIGEM/OYiiEOwz7txUNUoZtCKLZlY4K1XscZqFliomRicLy8XESinQBhfEC2sygiwzApXFOs8yQVYZxaYTJdphmhknYcmx1uQwf2J3GISZKASC82gNdS0UaTejZ55m3r19yDp7kRjV4nmmceb+Ycd6vcpCpwlvLKlpRTwlQWdrdAqYytAPI/f3jxz2PXW7ompW7PcPDKee3f5AXVULa5NSMpKrFSgrElgRiEpC1avVLc83glHIijC5pSqdBqOFm3+aZ6mz5Bl/a4wwFxlRbT6Mnqdh5uQikwssJPIxErwXht0YlnxYKbKkWaZDowjRZpLOYozamuvNClvXoAxRadCJdWOpx8A09jzcv+XYn5iGiXmYBdxVWaq6IqSEy/z/++Oe0+mIseKVdb5GozST91hlMDEwnHp++csvuH/7lsPhwPX1M569uMMqpJCnNSC6hCoTh0QUpm4wVngMqrrPNbBIcg6dCWW1UtRtw2a9Zr1u2R/2aG1AS+Q59hPeKeJpFNTqOEMGixUxXnmu37//PggjoFRmVfEuq7/GzAhbScHEuwW+6X1gGAZSTNRtQ1XVOOc47vZZrbWlrmuCDozDKQtqOJx3WUGolhzMGNqmoetaqspmHvdMKpmBKTEG0Ip63aGCVG0nl9V4kXkBhRTAQpDZhhTEmOyPo3i2Am9WCpuLdbJeJ6EGj5F5HFFKkGDt5JmSZp4mdo9PMlyUhLFWIVN/PgRpE9WRVMuO3R96bPXEzc2Wqq5RaOZpZBqFe17wATO7/ZGmW3M6jex3e47HfiG5iImsXZA9cJKeuPdBBl20oNGkqi9gJKUUTWXFI6fMHhQiwzgx5lmJtqkx1qCMYfKB/WnkODkGF3AhT2BmKvN5djmHFfmxEPx5ytIK7bYIiEDwHiLoTNiqFdysGm7XjXhhyBOFia2NGCXKVoqImyfmacraE1Jn8TESnMMHee8hhIWUVUUxVJXSWCXnqoymMrDqGlKE3WEkBpmITRoBjk0j3jmUtdjVmmk8SUQ1e5mTcJ6UEv04C19BjMTgAYtSEv4TI31/AoTCrGlqiDAOM6e+h2ho247NqqMyRp5fjIzOC10d8B6l9LeOD8MIZDCDVlLxjMGjU4Qgc/tVU/Pi+S1ozdP+QIqBcR447SUymKdJsPpKE7zDKUkN5nHMYahoENR1BYilV0RC0Chq1q3l6vlW0gZE/XV3ONKfRnxMROcIIYhugXNMw5hZX+JCcJJSJGUlZB2FONSFsHjBmMA4n+fOZZBHK8W6q4mNBUTNSBvp7ccosxJlkZRBn9Lq8fPMOI6kJKG5D4Fx6JmnieurLUYZ4jzhZiEZKWrCh92e6AN9Pyy5+jwXAyl1DJ0RinOuUrvM7uRyC21/msUIeuEQtEZTGZNn3YV/cc4DXm1t2aw76lrGwUOOsoY5cBxFP1BpveS/JS9eXFdKSzQgjMgarcszFim2FGSqblsZXm5b1k2VsfVCAUbwbOtEpxIjFh8CJhmEEFz0AHwERdY+mGdp8wWZXZFPCcWXMsItoI3QunVdy3Z7xfXNDToX9YxWDKOjP/WMxyPeBeq24co27PdHpmle1KPmecbNM9M0oXL7kMxfYCvLat1K6pOSEMDmkeUUyWpZCqOhsoqksjqRK2rWStIzQNvvbxJ+GEYgpVzxT9TGUNdGtOemWWCb08g0DmBs1pgPxHAgeMc8DTnnVlS1EEGqFElR6CS3Xcd6LaFYVdWiK+ccbS2kHLc3V3z68Qs++/g511dbtFKM08T9w0760e92HE6DTKPlxSkcAwqrxCNqlT1onjmvjcpknJ7BiehIImWl5QqtBOVlUmTT2kwRJswvMSXmeRKKNV2WXwELkRVqBa8fQ2CaBEM+TROHXeTwJGnCeruhNlpqI3OkPwlScp6O3N8/YoyhqWvxslqKokprgvckJEUb3JypCC9jSYXKvP11I3MY1lqa2lJb0XmIIWbGZsuqq1mvWuqqZnae4/FEPx8Z5llqNyBphRL6NmsiXhV5NDJkurzPRExG5OuTxVorRcUok/+VNTzfdrRNg9VZaBYprK5sYq09Mw3BJUbXk1JkmgeGecR6S9V0jMPA/cMDj09PzPOcUQERlSPEkHUhUoyiVIVmTnCaHPOxxxjNqmnRsxjacRAP78eZ6fVbpqJKFUVlaJ5n/DTKOLhW6KqSP4sWQchEq8bKn1qjtCGiZN9oGaLan3p8QKj7rWVyYviLOGr8HfnAh2EEFJAClVY0q1oAJ7XMpfsYUcYyTRPGRtp2hT0EM2kAACAASURBVEqeuGpwM8zeZG4/RwqaEEUsc56Ey02UcGUiKwXHpm3obraLiOmqqemaGmsM3jmsVlQatqsG5zw3mw6VAvePE24cSCHQNqKPmILUD8o8vVyDw1vJeyfnmGehIUtJqJ9TTLh5XnLg/f4gBZ9cDVeAj5G6rmVYSnbJMjxUvGHXtRJ2piCiIG7GO4ebRIb8zZt3snlToqolf5/HkXEcJSqxFdM4oo10XagsFBWe4HN0FXN/X/Dx11drPvnoGS/ubthuVlRW8A/lT2N0Fs0Moq/XNDRNvXAyDuPMu8cdDw9PfPPmga9eveFpf2SaZwlz64oCvQ9+XtiGSRIdhOTQRgqFta2orUERGZ28g21b8fJmvdC7GcTBKGXoas1nm8jTzjE4xe5wYJgG+qFncHkorWoYhoHHhwced3tSDKIE5T0ppKxpoJb34IPoTDw97TmdRsZ5QqPo2obNakVlFLXRKJVoRciKppH6ls80aLURRWdFhaITTgAtTNnj7BjnmRgiVa0ywrNmtVpLHSivufV6Q9t2PD0+oZQYaDdrUpQIyReRg+85fq8RUEr9l8DfB96klP5m/tkd8N8BPwZ+BfzDlNKjEuqb/wz4d4Ae+PdTSv/HX+E76GpLW9dsVy0pebSpSMpwGoVHP3iBSVqr0FGj24rQVGQFJ4Y+ZbVdzziO8oDrmnH2TPdPi+JrWze0bYPNNYa39zvePe5ZtTWQ6JqKrm3RVvrE4+jox4k+V8WLIKUPPrPMRKZZ6gkig+6y6pGE0imjCJVSpDmhtbwQ8biKYfLUjQCZ/DwTvDvn6DHnpLkCXjg0Q54J6LqOGD3Bz4uaWIxJcs38/aREVUkxVSFS6D7J9zvvsuxVhUqeyhqBKKdIZxWqkuWRgFVtuF53fHS7zfiLVS7SiZFIOWxPZAUkBdMkKUuIMv4sGAzNZr3i7saxP544ngaGYRZvHsMyJSmCqmGJEBcO/yTe0LmiShUzT3/ktqu46aQ3jjpzAoLoBny6UXx5CPzy6YnX7+7ZHw7sT4csVS/vwzmHm2d5B0q6DzEEUgr5WQi7cBVSHtISht9pcngvTNnzNOJmQTrqDAqT+QlpRWsQuXXvlvakNSzgtJQSQ5pRKmB0dS6KKtGFj1mcVCdFU9esV2uMsWxWMkvig0DvdYoYDVaVOtRf0wgA/xXwnwP/7OJn/xj4n1NK/0Qp9Y/z3/8T4N8G/ij/868D/0X+83ceCrjerNisWprKEmNAmQrTrqgnxzyOeCcvxoXAHEQXwFY1GEXbNNnrB5KS0LaucwEpa7mFbHlnN7I7CQFECTdfvXvKoXfMhA/NMrkmfe7AOE05ZNc5BZCcM5BEsMI7WaS51ejmWQqLKNGd05roI0FlzvkQpXesXK52T/hZWpsQSVqEKi7fXcqowhSlrTWeTqCE1yimlL8zLhumcOaHMGN8oGvEHcUg4ahW0rKLUWjYXUZDdm3N1boRURElPWytFW4e+ctff8kvvvgaoy15qE/g0znElYggI+DiGRJcV5amrlCIIlM/jOwOJ4ZMrJnCzOk4Lp8XrcaQI4G0bGapvSTmNGVPLc+pMprPbjdcbVq6uqauaqmOK1A+YojcrCp+fBP44t3E6Xji1J/oh4HgXCYLiVklOm8OrdAxEpQwF8kzQwRdjRR9Jc0LpEw5pjLstx8mJhekI2UU0c9Z11KUlUJmYlKwULup3CZWKnNKRkXSMp0Y0NgkiNHgc+GWJENpw0A0lq6u6BrL7CPEjqkyufCZZ8W/5/i9RiCl9L8qpX78rR//A+DfzP/9XwP/C2IE/gHwz5L0a/43pdSNUuqTlNI3v+s7YkyZ537KSr7gw4CPB1yIeC8FFO89p36kH6fczjpLQhe6MW1q2gzTTblPbatqGb+JMeG9FBHLBiBJaKWUEg76MNKPggEoPfPg/fIgVTYqAm0WcROV/Y4QnpxpwEgRoifl8eKiqlywDVpFdBSDoVJEaTDa0lRW2muZz7AQACQERhq9FxotrahykaqpK07D8D5XXZLKd/Rn0E5CZfovCT21MQJGiVLcrELA+ZwKVBVdXeWCnM56iQ6HJztqXIiMs2eYfeZ+yPMRmYk3ZF0GayS6mfPAk8vpRlNXGJWI3jFNflmuhQPi/K/SJgXI1fwgrEY3teFHz6+4vVqjrUFpi1ay+I2R+lBlNX9wB19fBX4RR/ws8wUqk9NodK7rgCXlQmVYRF80Em3qBDbB5AIxgtIBlQ0meUOnGPCzgK4kEnB5zerFANuqkVy9FDEzjkIpRV3qQXkdWaPzP4aYHQ0pMU6e2YUFiTnPEkk4l9mwq2op9H7f8detCby82NivgJf5vz8Dvrz43Ff5Z79lBJRS/wj4R3KDht+8eaRpqjOWPkZpx+XKtOiyCTba56q7UmSPLqMrIAt8mCO4mENJ8Swiu33+jKJ4VqmqKlhm9zMyd/lcZQwqW3FRjRGjEKVdS1OLFJZGKs3OSRtMsPM5r1WJLF7FqutoKgu5fahVxos7kb/KdmQhA0WdvY5cPygtMOcYzu07kcMyxFS0DKSIpPJmEs9cvEJZGFLVl0Uokc/kEvE0ZyXkSXrx+dmJOq4UKJVSVFqRlF4iLZ/hwdYYTDYSIUZCEnZepaTuETPiTyuBJ1XW0jQikxZj4lzGKriAfKT8cLJRjDGgoud21fDpsyvWbYXVCqWCyI0hoqskkVXfdIa/8/mGr183/PN+zyFGVCMOwwUxkqva0KrI42ni6OR9o8ialDLybHLUEEkYVaFz56AyhqoSnsSQJchyoETMRlKMMJk7Mism56nPsv5ALX3+Qioy+1wgzmtGpN5DfjdiWIu2paw5MWhK/Q4hQv5fKAymlJJSv6MJ+f2/90+BfwpQ13U69uMyZbV4rPyuVYbMOh8EyKIVRufWxwW7a8gpgcvqvnpBoAFIemCtps5FrLwXsEa8aNNUwleXIcDD5JhdyMIg4tW2qyYXxaQg1rQ1m/WaurbUVuOmkbdvH/jf//QXPO0FAp1SyGmFx8eI93VOVUR8VHjmq4yCk2ud52nJhbVSizMsBi9yniPQOnt7QJkmq/Gmsk8uNv6ZsRgl+i0pJqILC5uutdLzDyExJxlsijHlCILs7c6ha8qFipS9jbyzLBdHltPO30f24qVinZIIrBR4sDK1CLDGc/Aqr06dT6F07lbkqrd31Crxo2cbPr7diljpYjTKPUcwmpQjppfPr/j7f++n/O2fPOfhcCLEwOQC94cJ5xxWwZvHE4d+lN8HbjopBvezYElMiXiMxdo6T4dqlBZK8nxDcp/LWRQFkemjyLORIj5onI7oeZboy0g7damFZGeWBzffO1RpG+c04mKDidNK58993/HXNQKvS5ivlPoEKLrHXwM/uPjc5/lnv+dQC9DEBxFzLB6yqmTjzi4RjYRJJisDq5zXWyvKtCnB5LyAYzLzS9EktEbnjStGoMpFLwV5oKWisqKOE1IJ7aEyokqUUmRdV9xtGtpWpLLaVkRIk3e44Jhi5HQ68c2bexlwyedRsIRwIUZOxyOha0WxxxqZgAvZY+SN4mZHuKAVSzHnxUo8r8+yNCkmlCqeMYf0+akuEaAClUrEoxfEnVoWjmzeSPbapKybWNIhdT5nyatKuCSnOi9OCc/yPs3nJp0Vo5LQsp8v7PyuJSozsnfyJi/bv1wny2bKLTKTaLC8vGq5WVU0Vuc0RC3pnLWWqBKqthChahteWMPd1RY3T/joGJ3n8Thx/3jg/qlnf5oWGPOqNvzJR1dUVvOzNwfuB597+oqYC55KCwlIShdGDeTdcPGs8j0tMV028KG0MwFLzCpNEs1ZVYz+8rjlzzyRmYqFfs/4nReA4pxWfNfx1zUC/yPw7wH/JP/5P1z8/D9WSv23SEFw9/vqAeQL7KczMk7nqapAyu0NeXQSOioiQfjys1S384o557ZAlhpPGCXeUFvpQ8cYGEfPkApFtVhak72pynnm0o4rDy8v+mGceTqccn6slj5+XHAOkWEY2Z96pjksmAKl0lJ7gEQIjnkSyWlT+s4pZQ+YN2Dwiw95rzBGGSYJy/UXxFtKQSTTjaZ4HIkdJIT8rqnyBVZK4S88h9rL+Ut3Qz5I8ehcePmU1LLo4nd8j6Q05V6Kccjnzf+cww29pHHZzb3v0ZRazpBSYttafvjiirYWqTcZa5D0S2UVYkjSWo5x4WXAgk4aZokKDYpKS/Xe5+hHk7huLTfrmlVd8eYwcj/MEv6/513zc9bwWz8tBjMb6mVdXRpUOKdwStI3H4LIpZf75pyilp9dRkopG/Pzd/M9f3n/+Ku0CP8bpAj4XCn1FfCfIpv/v1dK/YfAr4F/mD/+PyHtwZ8jLcL/4Ped/3zxcnviESQdkBw8lToQ3icmlwchUizx6VJsE8urLjZHyYvOT0DnsFfFcxiV8iaVVIRl8xSSinTx4sp/f9fh3cw0Ddk75zecw/LiS1X2eM55GAbqplmKReUqBTMfFqORsosp21Xy4KLYy/I9Mch0pTY2G0S1PEP1Xm54Ng9lIZafaF087TmAlV8p9QT1vsc57873nsV50VK+6fw3lb61JlMmU025xnM2TBeWp5w5U6VLKmJT4JNtw6c3W+qqWT5fakbSVROjbyDXcURyzRMI2cuGmIheuk6Ti3gvwLCuttyuazZtnqisLVYprIYmKYaYr6mkO7wfnpdUoGhoiK0s70M+q1XuIBkZYxdBWo930nEqBfAlyvqOFbiYBsXCQ1BkZktR9vuOv0p34N/9nv/1b33HZxPwH/2+c3770Eqx7WpQMpxhtKKq5KForYXdJSbm2S8to1CKhcsDFm+UMvGDHOriYcvCK4w75uIl5GsXKbAS/ubvYMnJLtajOv9OfjvE6JknwScsAavKSK0kOfPlAgHx5t4HlMkeouR+weeqsT4zBDmX9Q+TtKOUfm9/lDA0m74FM3/xkW89m7zNLz2Hyr+3GIbztZbnwOXP8s+zs2aZkyitLi68Hvl56zJPkT+b31MshrecNuYC1/lil+9LKqFimXSEz286nm1XuaUpRUq08DHo6PMAT00MM9ookq5RBOnJK5YhqQC4GHGlXZgUm9ZwUwamQNZlvnBrtBik4oGVBCDlXS/eS52f33vPwwhatG1k+Eq4Gh0E0aW0RuFTLmZfrrmyCFVZZwqljbBUdyvabgVJ6kreOVSc6X7HTv8gEIMpiYfXKldyrcZajU5qqR67PCUIlDsHlafHSu6aw8bz5gSQHF/+CxnUJy2bcbGyxasptRiTlJVmyzVe2t+YPe+5r10w/vl3ly+UicNFwioLgSpj0FULVZO/PxCDI3iZAtO2pqpbYSQi4pQCJxsnpnSxXc5eWxt7sdGzVy1hNhcXtHiuc4TxW0Wl8ukEqYBlMryXdJGjl/WYuzQlrSqvSCt90bkoqYniMnIr76CEs6H05jPOYNFhLAa4fG1KbGvFD+9EvQiEwEWFhIqQCGDyvWiPMD3XOeKEqA3JavAekkwvplz/KXWh2hg2q4a2a/FOUlWjFTL+YRjzeivG7LJWchHpn/13jni01qxXLXe3VzSVYR5P7IYTfhT4uLFVjr7Ub7+fsvxVbvVWNbZdsd5s2Gy3WFNlRumK2XmSG1Bx4PuOD8IIxJQ49tMSci77hSUlzH/JCsE5rFWKpTpdZKTOAaj8Oy0huSw0Ce/PHlFdnC+lIm2Wlvbc5WZLsABYfHDLd5dDa2lDFUNUjIIqm1FJKJvyBtXaCMouzEQ/y/RYitmqd5i6QZEIbsgTe7rs2/w5CZ1LtCGpzzkpLQtFjstsMuWNnL71gJf/mzd1MYw5NciYdpU3dqmQG6NzCmIhz/krwKgkmgzZE5Y2YgJCYmmfhkiO7Eo1/FsRxHJdabnPss1erms+v1vTtZVQwaVERUL5JMXYlDAkUBZ0LdOJOJESz4VlElgMBvHs0Ue8D9RGs20rtm1FXctWqay0dlMSY6GVyaKl5DqT3Ku+MAYKqVNZEOiikmLl3c2aTWvpTwem/kR0E6lMTaYI2kBWjWI5U8prTdaUrWra9ZqmrmlNYK0ngjsQdjuiC8Qg3fL4oU8RkiQPLp5Y5cntuGzw4nkuRnNLSGl1LoSphVzivAHlsUkrrCDpzhNpxeDInFi6+P7zllg2WP5Zga6ChGDFaJwtl1oWV8qe8DIERi3OgOinHMkIUEgq2kJomvyE87MYlYxG1NoA+uxF8zUuGIJSQEwsPW0pTMon81XlsL6080q3oISvZz7AssFLAVQX75OBMUrJ4JRShmRqvG6J2i6RglER7U8EP4l3z/TdgivIffa86YsBOLvObwNczqld2WhWw4tty931CmM1mf4oNyKkraxiKqsGo7RMHCIFUKMCyUeSd9RWU1U1GE/UlgR0teGmq7huLY1VzLPPz6CcU9CavkRT6byGJBo9Rz0piQipyUXlyhhScBz2A/3ptIyiU0bGo7zfQp4ibybl9yNPRBtD01asasWmg5vrjuvra/rTkfnwiA4OEwMKjU/V926/D8MIQL55tYAglkWszsUq+bs+F69K1Ev24pwRfudC1mUIrM49dwp4JUcUCaK62KzlbEkvFXSFSFOV3z8v0nO1+nzkVCbXKy4Pmb0veTIoY1DKLtettMooQ8HJS21ANmuJji4r9kqpjGo7pznyh34/b8wbSKdvX9FyyUuIKSPPVkaEz433nHSdN2hMEh1N88isEmiLUgJAmkmkyRHnYdkIYqjOnY3SNLnIdCkGKb13T+espjz/ldX84Ystzzcraq1QMWEoxC2SwsSoBTasC0y7IgWPyRcfgicER1IyfutjwgUxSrVRrBrDtqtZWY2zCVLIhKAIp4AWT6suUq7L4nFxKCnljk6eC7Fa5+LfLPoMPi4io8I5mEgpYJRcd4GAs9SnhEmptppKRVatZd01pOhx44BR0DUVqTbowXGKl2vz/eODMQLv5d4p5VA7Lfj/GM9TdD4z+dgMZVXF42kFyhB1Ws4FKYeAeQPrAv8UD106B0VpprD+XvrZc8U8Ll7owv8uYXNJSUoUUgzaci3pbCiW/Pjyq/JRZMdUDvkujZL67Y+zVPnhvTC0/L9z6ygtkVT+pot/i9ESclTBTdiMvfA+eymEHi1k3oRiPWMO9dHTEllEVYaKpAaj1fk5lShv6W2k89XmaJ8C6152UCpPOj+wlLhpLT/56JpNW2cPe1ZUSlrhMhuQGFAr3lVFjIKIIWqQwGViHGeGecbFCRdFpbirLJvGcLWyrOqKcfIiXa4VKkaIgdoYpqSWVCmXqBanVFIBnVvSMbGEgkYrQrnvtNxZrqVI2rBqK5puxTT7LHEn61SphE6ByohkWopRuAlOPbvdnmmahKkqo3DV97OLfRhGQCmpugrcVC9hdkosvf+oxPIJXvxik+fC3GW+WHr4KYk2YMiDPQkJiZMSdJ3Mahd0YiLkRV5C/PNmuahQLAlqEq65iyLkIiG+hLI5eik/I0n1+OKsxfsukUFZzKosmrQU1QpSTv6ul8so5wbZxDK8I2HlMuhSqv5LQQ55GvmCllAVcnEvZbaluGD05dvLtSbea70qAElr5FWoXFBMGbasLha5TOItEUAx/FyYpQUVePHMy3cBViU+Xlc827SiLwmojK/3Qd59CklAQvn1yeZ1JC31C4ETa1TVwCzdGJktcWgFV13DzXZF29Q0dUNbeWprFkSiVtJNqIzB1sJvUHzIe3W8JLUQtxSa0lKbgrjA4kuhO6VEyhBuHzxVnhGxIrBASelSDExDT2NXxGjEkc0TMYSFramxKsvlfeCRgFaKVdtSWYHvokTYw/u4cLCLVrtgygv+OgbBexeLK5NYKqvlljZf2R6aGCEU6FooC7IAU84V6/c86UUYWoyBOFu9bCiZxlNLyLrUJJZzlCBXlbmhxTPrpWhY/HRJIUq4LfcmWgciillbqRuUzenzoEvIbTVpXescNZ1Ri6UqLlBrI14zxeWeUxJ25OgSqLA8hnOkm5YNKVQbF2Fwvg+9GBlFMnZx5MWMko2aAMIE0FRC3YLDiKT34MTfXr4RQdP94HbN9aaWupA2oHPNJjh5BnmMu5wbldCVrAMfPSkz9kQFQQuoTCGuvLGa61XD7XpNV6+x2mD0lAlhoficplI8f37L3d2t8EyEmId3EAKbWTQKTv3IoZ8W/onCLOScw3tJBwpno0I4JUkwzQP7oQwZ6fO95EUcgpcxcAPbdUdtNValjKAVGrVmvZIJxu85PggjkJJMorkgvGjiMvSixrLAV3MIKo+qNAWheNxIgiAb3fl49iyXrbKyjrMHPq+wMzqOfM7lf15Y9aXIlEO8UrMolODvDekUj6DIXYGSDqgFD36RSsrndKnuy586sTAgay336KNHKekWlFHeGEX0pxSmyqa+BBSplFubMRfN1HkgiHQuzhX0oM73ZjNewyLPLASJDsSoZZiuyvMcOpOPZng3yPUrVJ6bkA2ygLay0TDmnEqFmISrMBY9BpaoSAqpkXVj+PzZitWqkZQrR1wSzwVcksjFmEq8qpa2X8HrW/LAUMYExMjShm4qw7a1XK8bbjYrulr0MW0xnEsRU65LkzkekojIjrMj+IiPgXkOTF4m/UJGVRprhMTGS1SbUmJ2AhOXsWKWgaK6rjCVFUCcVvk64zKmrRVCbjNPjL0wG9VNzapr0ES8m7Oi0ffUgfhQjACZuRe1wHkvN2GpB8iHE0mdIbvve1wJFRVnDP1SaMofOHtl8hy7zPyf207nr74MX0s13GZ4ssk1BVKeegx5kSFFnTJGa/IGKtx75+GoREw6Q44zkWjepKqMNS55sAzNBOeXe0jvXeoliqxERVoq5aUVcTGPsdi+xPvepSD5UnnUKVN0vfc6fsszp3SOClSZckmJFMLyfVopDBqyYRDDKPen81yHzlTePkjqV7QHSsqjtBZUZPB8ctXw+fMtbV1R2qQqyblbbQluxgURmDVKnlBUBlKQRZ9rDtoYtDYY2+S1JN/d1pbbqxXrVU1lwfuI0gmXMSCqpJQ+cP/2nt+826NsJY86G/jybJa1h8qqU3ktBAgBYrIYC1ZryfG1ousa7m62PLu+ymIusub2x4Gv3zzwdBiIQeYXKmvYdi0qRXzWwbjarGgqzTgMPO6OuG+1sy+PD8IIgIxSoliKKylvDMF5kxfs4vfPuP1cQDyfSj5jjIz2LpXaUnhRpR0ouX9BtxmtFp1AGVsuBiZRVTLfb62RsDx7QIUAgfpxYp58JsQUz1BnLkBtdZ4IE3Ze8TaSE/rFeJyRicSLWYCcIJRZfpXveelHk43Jt17wOTXSQFgMAJdGoOTjZV4hneOqUl9JxFzIOvfUi0eRa5RNHGIgKoHeSgr/flcC3q976JzfLq3LPAVZIiSlFHVlCEYiHWu0yKopeYbeOf745TWfPL+lMhWWgCciPVlLVFIb0QDBo2YkPYpSW8JUxFRQirk2FMQo+ygGfLNesV4JE7XO9xtiYPIBn1MujSKmgHMzXpVu0zklyjGfrKWS8gAp6jwvweLwqkpEbowReXnnI4fTREoHmnqi6xrWXSvTpdFTVxCNxjvPOEVMJcpWRiuquqJpannOdYeqOkk3vuf4IIyAUiLQWY6UN2mK5xkCVAH65BFZ788POof2NqOsipFQeQqrFAkvi3WlgitFKkMRbUwx4r3kqVHJWGddiZdKEZImh3MSgiYv7DZUhsrorC8n8/3GZIOi1JL760wbJobgHK6rHNKmMgWYw83yO6VYuDyjVIA2Z6DQZWclJc5RVSrnKe0zzqF48dr6bPjEpiQU5+5EwQ4oCjxZDpvZnJXSS9oQMyiolGxjzoMFSakg5k0hvVIJg3Ux9me+/NKaRSspdiVBjtYkPt42rGuTcyBp+ckQkyIoCGhSEgUna8D6iDIIDwMQU8jXIuPccrEmtzcVXVvTtpXcGwqNIfiE94UfQi3heJM7AyG/q1Ibiksam/kUVOlIcY70UilcnhmKnHcEH9gfTpjMs/DRR88JKPp5RluLjTFzWs6MEb55+8gwBbpWogAQLce6atDbaimmf9fxQRiBkhMt3fZUeqESXpcFRM5Vl4qVOsNSRdyixpCn7XMhRZtz66Z8V8nFU4LzBJ9svpgJTWISoou2qWhqu2DSE2lp1ZS6QF1Z2WiiicLkPJOPzEEgwIWLoHxfIU0BQGt0CXlJKFs2ey6SZeaiwnB7WaBYUiGlMhNyMRznEH8plhqhTVMpt820RAoSgRUZrJAlyAJFQgzOhlbOKQ9eZaMsPIAac7GSlFaopEle+BNSLAClc9oVQljSKa01kxaOQ31hzOTxiOFy3kvRzXu2jeaHz9Z0tXjpEBXKGqxpaKySKcZoSR5CCkxegRG+PZKcTxR+leh1Bk3wLDm61YptY1lbTSvKdcRoICrGWUBtFoVPUliVSk1AAJPqPYOtlBiwOUuriQFKS2RKudeUdS7IRDELMlUo6zXCsOWyOI5Q4E9M0ywszoPj3dOJtqlZtTVNXWOtDCS9t1a+4/ggjACUcKlU0vSSn6psPWOUXKrkhpQFflG8UlHGb0PxJiXHXsA25yk6koTy3odltuB8MYm2tlxvOrq2YdVJqDZNjinP+c+5YOm9yEuPs1sq+6F4MZV7xOhMNCH3Z6xBYy7yx8tCXJmtFyMQYlo25pK7w4IhICWB7OZkvmD3Q+7DXxpJFYPwMADBRyKBWfkldViiBqlQZoOVZy0WqPa5plIYhXwI4MPFA8xGIp2v9wz8yudNaTHmKhtt57zoH5jLGX21DHKREiolPt02fHS7xRihHMeAthW2qkhpJlFRNRWT98QgeAFLRKsaLy8elKyP4BPeIV41ih5FW1dsOsu2E0ZjrQ26rvCpcEtk56EgRFAhUBmb0zpzjuRImQgkS9mnC8akku4ua0+x/BoSXZXOjXOOh/sHTgfL7DwuZPSlF11Mbaxs9iRrZX8aUf20RB6/VcT51vHBGAFIOVQt6TLHPAAAIABJREFUBKFiwUooXMBDIhxql5y+HEUAU4AscQEUSd+dPGQkYWYpzpGLPMVbWq0l1NeKrqlYdY0o1mpD8J55FiMQ03neHETNqKnPE3hVVfgGDE1lMDmdkUIXS8uzRLvWKOrMNw+yHFwITLMnZHXasmGE9VZhlMl0aKWSLIMtRSPQB5HwKsMtIlQhbdeyuRMFGmxEpCPXJQqd1RKx5IJZKabKpajlz/z6loJliRh+q1XKOb2J8fz+5PFITWIB1CQp8p65GkT4xETPZ1ct23UrzzWK5JYwcHgIWUGKHPonGcyKUeoL2uSoqaQoPuCDw809RMfVqiZpRLugqtDGLka1nz29O6tUlcgLQEURp/EqgtaQFAmJpnSuNaG1IBWL8S5RLqVDc44O9CWUHTicBo69KoWGJTVO6RwN15Wla5sFR3IGuf3u44MwAkpl8Y4sCWVULsBdzLZrm/vPSarOZWkVRJ7kXwqVDYhRcQnxfYykcC7ClHxaK6HHtkYiBeEKtBmCrghBin4xykBJTMUrSwusrivqypKSyfzuYuerqghwipJMyjnyGfcgG4yLLofznjmdU6FirJRSNJUhBCWiHLmZUdeaytqF4MQa6V+X0FsWneD6iyvQWLDnItel8m/ZkyXtKIUsSS1ktj4lFjZehZL597zAS7RPKm3I8ywIXBiEsvFZ1vOCVLTWYLKkupwok7/mdGCcZl62mh/mrkAxDspotJVpU6UTKjhIEavFcMTocb6CSiIC+QykRSRFVH2FUFW8+7pusbpBGQvRMU1Hnk4nTnNYrj6U28kpjCZK+zbZpchqMiajrWxea6X4KhRuhcSmFIuLoRQuDHKaIHDmggeJ4bxOpEuhMg1criflyNfmd2NNMQjffXwQRgDOvGrmgnARLsNJRJI5CVKqeLFKSQEOZPF55/FBPF1M386hz39XpfKeDVCdi30pz5N7IFgJrwuj7RJFlPPlvvcl8QgIF+LSm01p2fwuhHOCXRZ31uArBqr0z1k+dq6qG60XPH+Za78ciJLJPNlA54JnToFyilEu0mjFlBzepyUiKgbkPNdQrkM82+X4cAH5QOQyESgbs1T5y2fFyyVCyIs8GxK0TMIZJVGeyZ2CEhWkmGS4KkUqIi/XLS+v11Q5OlTaLClQiVQsEqIHBDyhtEiDqwJlJiHy79K7TxpUXntqdmyrmm3dsmo6jDH/N3XvEmtplqUHfWu//sc5996IjMis7KpqutstNwhb2HjgCQzMHAkxgwkDEPYAxIQRTECyPOMxQUIyAiEGYDFCCCGQGDHBIA9MqwEJt7FNdxeuyq7MiHvPOf9jPxaDb+3/3GpXdnW3y1L4SllZmXnjxolz/r32Wt/6HlhzxbplLOva72c+PaJots7ln7chOA94ytE7M3KIhi3FiBDJNVDwWepA44FLvcKpAJNV7/SXeG0nf/+M3PE5t8b04RAakKJ1iHQhHqLHt319EkVARMhxFko1fQh2eKo5C5PYUWuztde9QORased2vEkEX9z9NpFeWTu+YEaVvYq2hpxZNLY92xklmu9Ls5VNB+fsBnR3u/LWzHjSxha23AWt4ai+ubQDGOpjT6/wr8k8gMCrI50V/bAQNe8bjD66vAYz++3b/zy9tRQRoJZXpJv7OtGbkSXLoX0OXhDABxw/UQwMIT8glbvyj8X29xKt+mvngXbAsR1Re8G0JacCNEaP6MjBiN5h8LyVo+PrEWXK8eUK/GNfPuHzxwnkJhDkdD7Cq4Pz3LWrmCM1Gg1bGp8HV9sdmRdQ7BSAllds+46tEsR9GD1OQ8DbxzNuywptYsVSMSeH6MgydoAVAP49OiXmQHDoaNMBYwhaYE00slD0Hi1YklCt2HamVvXsR3urjzEzRQ9tDsVZBgKoixiGgJQShmHg6NqMRASS8GjAW771/H0SRSB4h8/fPZEg0hTbtjPVp5EZte318Bp03VpKOz9AjhaTBgzSQWiuuNwd0BJwBGDMNwBn1lK1ggEzHbbhQSePnjN7t30ixkDfgGoron5DNtsqlNpQXq1kWm/l+kagt5AGFAoUqnLYeFPGa9wFd3dacuJe3Qa9XbxvHI5Nv/QQCxgGwbazFx22qPT777ZTPR+vdI4EWB5i4MPaz3fXY+y5ErFvsCLJ18PEYN6XneDixHgdIsba42sYAw/7KQVMwWGKHufkcY4BU/QYAz+DWy746hn4fBD82i98hvOc+P5ZQUR/X8Uzh1JoJuKCR9CEuu8cB2uDbRH5vjV2jrVsQM0AGkIMcNEDugF1Rcsbcl5RFUg+4JwixpjRcsVerfh2IgsEUQBmGd2NX2qt2JRJVYLNWvVX72kjyNjHgSGGozPbSzkKrHcCFwSjMOK9fzYxOqSUEGJEre0QG3Xnqn7pfOv5+0Oc1X9gX947nOaJAohlw7YX3MwxWJVgrvP9jjLkvP/iY+7U4/Z7Dbj2DQK/VaFwHXF61abiAAj7zxRrkRmcQQNLssyIWB8HvilKq9aG2y3d7q8veBN+COC6bSAI0jV5/dmYu7GNJU7ut77rXQf4A8TJYXLRjTMb3Cv14T1jIZcK7607atVovg4psUUMzlkkdxcKEf32Nu/7o7vgn6m3sM38D2B8CShbVG/AqIh7VcTuoOAQHL44j/jiYcJ58JiHhDn6Q5UXxCH2Aii8ybayIzrF508nfOft6RjbmlNabogSHJRGsxdHrKepQ84ApDK8tjYkb4VCSRA6cAWhyWgIDhI9mjTcbs/Y94pazevPs2N9nBKmyCTj3BSXjc+qAz0OYorwIRw0ckaus2DSj8EhhXaQz2LsY1vfZHliNqUhZI9tz4YNcayYxgHTODDyXfgsbaXitmasW7HEKGffO2IcKDP+67/+6z/1/H0SRaCUih9+9Q32wtkr54qqnZvOW9h7sVCJjiC/MiM1UKTPpr3l7H0fC2H/sDuiq/DiIF5AC0o1NiCBsY4ciHOM7LYvsQAROMagrzsFTgIDtow12xWRXXWWqzv0DFSqKaDuYI05a7lbU2Stx+vvo4yzB7THgE8DY9aLZTH0FWs7/qz2E5wBiFLNx4APYimKpWXTZzQDE42KDZDrvhV0+itxRnfgFGyrjUTk2d56JwgxHOQsAMaFVwze4VfenfEnv/ce3//iCVOKgBbc1oyy7lQsZh5+ZvZxHbct3LHPKeCPffGEzx4mxEBz1p4WzLVxIDtQK4ABKh7OKSuvD+Tm7xUSCBqjvQLjXMAwJNSyITj+WaoXLHlHbTAPCeJDY3L4/GFE8nwOn7eKv/si+HBj2nDwDnGIEO+N51/pdhQCJsuqGIeE82nCOMRDnyF9FWrPx57LgUM1A4hP03D4EQbnjnzJy23DvmRsO1WObx4f8Xie8XCe8ObpAefTjPNpxl/5b/6Hn3r+Po0iUBu+fr6A/AC2886op70dTtEfKH5fg+XCG7jv+++R1h1dlWN2Pe5mocW4vGq37Xk+DomPgQXHcf0nzvPGt2ATRbEWn2s4L2IcdIOnBBgi2zXyEwTOA+LYolU03qCvvnoX0q22etfj/X380caBpTnu1ElPpfOtCzTygHIFme1gi1O0Ksfh7VoCVTIjiwm3WBlfmX30bkZ7m8+2vhem/vKd4wwvgkMnwdGI/907h+8/jvgzv/QZ/slf+Rzv35yhIli2HS8vGb7x93cNGCNbWwajKvaiuO3cxvzS54/43vtHTOMA+ABxQLTyLRA4bWitgAiEh4qgaAa0kO5bFUkor03BWIJoRrICBB5piIxXB3kX4gHUaspVFuA344AhFCQfLFYs47YXvKwZW2mQPUP9huaCjY1c/wbvkZJHihHzNOLhPGMa0k/gtc5Aho6F9VEPAELwOM0TxsSD3wNtc63wwePxPOL92zPePJzw/v1bnE8zvHUDQ0pIw/Ct5++TKAIhOHz+9gmdIbVtGXsptkcXQLkWaTBwzHE1piJ8M6oi2oqstXbcUA5CdWKjMlFMoBGDtxkVcMoWjLe3bQIajUjQGldJ1mN0Gqtz7ihKyTYZDJisx1wXPN1jYDgF9eCcs70I1DsWkVcyZkZOVcDUZD7wFvfe3VdpryjEYvtgbgw6qUohRVBbRqtcvQ2Dg/PJ1pS2PSmFkW7tvkq9A673PuqwSJN7UXaOXZl3llj0ipbdmYadIPOdc8I/849+B3/6V7+Dd08nVAWuy4rbZcG6bCa7VQzJ8QG3IrKXituWcVk2fPk04xffnXGeEnyIoKuOZ1qU614GhpVIgDb+OVyrcLrDKQ+WE0H2ag5EAOkFDl4VKbDQekfTmWCrVR+YFl2UYatvHibEZUPwDlsW7LXhIRG/yI04keaM4oWfX/RmweaQG7AvO5Z1x8t1tRud3VMI/gjF8dZdHXR34NCqOOcxDvEAdrdccDqdkGLAODDZe5wGABzjti3/xHj6U8/fz+8o/9G/vPd4epxRK9WErVbU2mdRgjni9LhZvRGGQnWoXlDyfYdf6n0OK8q2u6kaQk302NshahazRRuqO1LfBUXB84PxrwgysJmut+UpRSjuYOZrfcPdEYmFrjVBc6SnMlhCgCbHaNMDSnpKUooBMZENxnHhvm4DCPoF12PUAh8MAKUSLW6qCI43kPcepTCdiRFrO8Je4H0x2a5hI6qGg7zSHXRato0j3mjIvfOh2xC5CUOK6B563zlF/NO//BZ/9tdYAHJt+Hhd8eHlhst1QykVHsA8BQyBRayow14aXpaCbW/4bB7xi5+d8dnDjGkYEUMEb3BAokeRBq+AqxwfCfwppBW4mk3M5SDasKwLoJzVk3PwMEKaMFOxOQfvAef5PldV7LVgqxXFCYZpgI8eIRCv2EtBg2LJBQ8p4JobSlPLhCgotiZs3qMp3Yq0KVqpaJeFG6jACyXGYFz/YOOQyYj93Txm3zKutxU+WNy5EpANziGlgCXyGRCwG1QAwQfTQaRvPX+fRBHob0yxUE6uQ3hrd2vvDvjlvSDnghjjYVR5WIO9kp7y15nE9JXtVycOuVe3vzTltSBApxj7V8VCbeauamtC6YheQ4yJVGGTCR/WWwBEWBSco2WXs/13sVhq/hp7D7QXC48hRsxjwjiQvBQMWVNbyRUz7BQ7dA+nEadpxDgkiAgTnA/SUCddsUs6zyO0Nqzbjtuy4rbtuK07tlyRq1qUdbck63N99zdkce1bitZed0eCIQU8nCYMKeBpCPhTn0/4M7/6Hl+8PUNV8XK74fllwe26QVtD8pz/h+htb07e/J4L9n3H4+hxHie8e3rAlCJHEDF3Jus6xDvz+ednp5XGmmjFSF8RKAXBAc+XFewBIoZxtALGZGFtSvwmgIXXRkv1Hs4XpCAYh4BqUXiqDbF67A047xUP445v1u5iBQQhO7FvegBjhXqPux0dR85imo2XfTmwKFVFd8hynmBh6OOrPbfBdQm23LMeDFugDwcL4zgEnObpW8/fJ1EEWmt4ua2GiPMPpmoUT1VsALbSsJUNffcftswHU8W0Ah3th3W11oLbz+vt1hDpnQeoSX9hY0g1swbeaqTV3kkZveD0VpmFpkFkP9aPfYZ+/XcByCoErKuwTqJ50ljRbF3Eh2UaE07jgJPpFZzjoqnVgt3CMEvlMnBIRm2222OaBirWakVTjkDOZvXY2X1GgX5+4QhTVVCaoOkOau8Ab5ZkPSuhF9VeGEppULFbyHs8zCNO84CnhxmPDyfMQ8T3Zo8/8T7i87ePcN7j48sF37zccLnu0KYYItHuaBFxe7lLx2uuOCd2B28eJjydJ4yDg4Q+5jEyLKgyhMVxvq+12M2oRpm2TYmNYFUr9gIk51FCQ9aK/UgPVcQQD7ZnpyRzvemRjIQUQ4QPA2rLKEpp8ZQCHueEx7VirQ1oBcHxifCO2FBKwZB64g40OOU6dt0LLreVIGK9U9oBMds3Hv4jRUjvXZsdgjv4DeA1E7QzBof0DwFZSJV+bbWQtLPu2SqeR49nFuBoQ+HEPmQgHqi2HIfT2UolRY9hiMfsTnJQwZbvH0KvnNueD0Cs/97A6wLQCTFdL3+/YY/qbK+vW5UHq+KHT3wISCKIvmG0LuG1V0GIZHjBOob1xsjpHlqajXQUvMO2Z9zWDV+L2INGg43+vWQYRvjg2W01Ho5uS6ZqPHehWaUA0NBJRN2pp/McKvkGNlqF6DFaEXr7OOPNw4zH80xXm+jwq28dvv9+whAF12XBjz9ecL1SdxFs1ZYC8YV1rway8T16GCKCoyx7Sh6TN7MYz67LNUGQBucaioXTOojN5A5529BaJhlHFWJGJil41Fxxyyu0MLNRPLcuMXpyJwILiqgHKtByQ8mAakRKgFdFhIOKx46G25ZxGgsep4S3c8FaKj5slSlCkuGnka19pBq1uww36+hybdgzMwz6qCViFnmCn8BbjiAWJWAcQzjwIMAISYVdXm3NgMGAIUbET50xqMBBsql2AlOMx6EbuiDHe76RchehVBML7YU3OaBIwWEaIqZE9FWcrZt28s9ZAO7VtGvwD7mr3eF9NXNEiJkCz9lt7vvKDPe5fBr4hlNHroYv0BqKhpUJuRRs646mjSw5KwJqxKWSaVG1bNla9ny09j1CXKH2PTus9fgJZaEI50HntgMoJUGm9uUjX3fwQN/pJ65CXxOScin3W8UJIhzePp3w+RefMQvQ8b2exwExcgf/IBXffzhhnhJKLfjwcsXzy4ac6/HwpgDEINgyNwkpUBSmIkhDgtYKL4IpObgYDUWn/Fe852jmxWz5OjckGCEpm9VcQ8kN1XwRvHis+451ryi5IY0J45S42u0joJhykkJWuMbOozVFdAFAg9Zi8t6A8zhimQqu6445kex0zYq9VmgBttsN163CXVc+u6HjO0YRNyCUGFA8TkRXkvYWv2NBxGc458/TgPM8MaauNVyvK14uN9wCV8/TmPB4mg6c5tu+/iCBpP8ZgH8WwI9U9U/av/t3AfyrAL6yb/u3VfW/t//2bwH4V8Bot39DVf/Hn/V70Jyxms21B7QdN5agC3KMTSdgRWztUNptuR6S4I6olkpnlg66kVDT38x762R4OEcMszfvaPyr/zn+7kSPnbizudEbP/y40cMrr35VTMOA0zzgzeOZkuQ9Mz691sNPrtOWL0vFbd1wva3YMudj7wRToH30eaYhq/fOfk3hz9u4oirmm8cWUpFCwDSNSCmgFn5vzgW7rVdzpsFlny2LMc26HLpjDykGDClgHhO+++V7/MJ3v8T18gIp5Z5N4ASuVXyeHE5jBBxwWVY8vyxHcMdgPPboHbUgpfL9Cw7bVpGgmILDUipCZHcDbccqDU3RxKE5QXSh92IsAs5TO9IABSO4GmcuMhnh0Aq7mr04SKkYmtqWhR2piEeQZmlQVKBqawhCV2FtAhjjrzbBmBLO04xlrXgcM9bSsBTF1yu717JnNA9scNhzoTNy51o4OQ57R/CdcxgiNwApRnIDEgVJtbUDFB/trHi7DEslhXoaI8YxYkwJyXwwYnCI6e8PGPzPAfxHAP6L3/Pv/0NV/fde/wsR+ccB/AsA/gSA7wL4n0Tk15T619/3yxzboJbI26mrTYG2FwDlTm01B+Lurqt9SBdBaV3mW+w/dGec/jvdI6JeE19ETErcQZjgjwevtO7eA/N5dwR+zCiEq0IGdojz8DEyJts2Ced5wvk0mh12g3cBKTq25EYMWdaKj5cbLsuG623DujOqfRoC3pwnvH084/wwYx4HiKP5yeW64OW24OVypywLFDCC0JACUoo84ADU5sPWHKK96wBHrO5GK7LbeFSgAGKM7KqGgHkcMJq8miGxvC1zqaZ3qPgsAp+fEtIQkWvFy2W1YqyYU0AKDoMnE3MvFQJF9ByjlpYxeuv0vMPjNGL0Hq7pPbpcePtHH1i0RQGtgIcJy6rRtrnudU66VMSMT2l42vaCrLyJxzHCRwJwqoyMr3UzEJa4QPTAEIQCKCvCUh1GHfFGSAy67QV7U6y5YSkVt71CW4EPgXRkbwImNRfsys3FkCJCdAewXErFCuO3KLDnfJi2OhHsmVseAD8Rhdc7iy4aag1Y82ZM0tu3nr0/SCrx/ywiv/yzvs++/jkAf0VVNwB/S0R+E8CfBfC//KxfWBtMq0+0v5tkd7Co39v3XfR9f4rXnY7WV6o83trBmzmoeHiPI2Ir+B4L1fnttp8NXM3UUjlfrbxRYmS7P0RW89KR+lJQCm/0x/MIHwIJKbYrn4aAZBJZbbz9hhSQRfD8csPz5YrbmnFdNjMtYSptSh6Ppwnf+ewRn332BvNpArQh52wsNI8xBZQhHoClMydaai6KocxMYZ7GiGkasBeuRMXxz+jN6OO6bDYuManC24iTEtvxdc/YSsH1tsH/7jdEwq37EhEM3uG7X57w9vwE5wS3JePDy4a9NIxGUeZqi6/Pm9dDDM58DP0BBjttiCI0XzVXZUfWEkPqaoVaToQ42BhAh9/WGCLTtRkt78ef0zuuIGtr8JnY0eN5whDIC9CmaE5omEIJEiXKtSIbWB0imX6iCjeQISlNKBNvLG7XXLE3dlbQhtMU8XA+8/Kq9eg455GA6pgi9j3j48sV3zzfcFs3rCtHuW7R3kMrOq/FO35GfbU4RKPWu+6V2dfmXAN/29ffDybwr4vIvwTgrwH4N1X1GwDfA/BXX33Pb9u/+3u+ROTPA/jzAFu1xeZeAAex4aDMGknlUAO6cLCp1IoGjR+N7GE79nHgmm2MfPiHlOgXKHqnuoZgFb9QLBQip+VGO6c1V7bPOdN6ym7M623Bsua+E0DwHlttuC4bUszIBtakGOCuDuuSafkUHcqesa8b9trwfF3tsMLWQBVhGjAOAedpxDwmPMwjhpEr0VwKASXjRtCfj+18rAEQuvx0fkJrin3bbcugECFoqGAHVFvDkCJKVSxbxrpTOxBD3113oJNFtRXFsi3WjTWT6PKgvJsCPp8ecJ74Hr1cN1xvGd1vkSIoQalMlvLBIXpFdB7rVo25ydsyeu7jFQL47m0IG6EUap2aQuFthdEaL5OitGVvCmixEJRGV6IhBngf8HJbIFINizAn5KZwIaBVvr+1AhUUtbWi8InPjQFNSJ7y7aYeOka8eZhpc+4cJcqy4WUt2FqD1IKH03isgcdxQPTeNjwTnPCZ6luNaYjHs8Vu9765EjFdwED2YTDGZg9LFWPFNqVPxfW24uX6808l/o8B/EU7r38RwL8P4F/+w/wAVf3LAP4yAMSYtB98CJl+XcE2JO6RD/MPU/HV1rCsG7ZccF1WoLJVfzyPeDrPePt05rpqHDANI8YxmVBDDkoc46eJ7K0rw0Gdp4NrycZH2Hdcl9VwiIJtI8tt3TOMnIgQA1IK8LYKevt0QjRFF23PGvZ1hzbgMU4YUsKyboB4xJDsUFYMdkhC8DjP3P0PiW097MEupq+43lYsG4k/xbgJfQsxGJBWKt+jy1J+Qk/Ru6rWGrGWvmkRh9M8HFuVGDxiCogh0pZMmD4MoevvsuxYtt24ERWfTQHvzwnRAyXvuFwW7LkiBLaxHXh1hxakIRh/I5cKtAovCUUbXARVnv6ea8BKUO1zA5rwwHg4uKYQJN6WyMfPrCoYnAdQUVqDTwnnecLzZcPzdcOUoqHzQPIRKSasbYVTB6cNYkBtDN5wE4BIxN2xKjqgBeBhihCZEVwAxMP7C37nw4KvV3aUDorP373F09OZVmi1Ytt37HnHsm5Y1wwfPL54//awYe8jUFOLGSvtAJu9d3Zp0UsphAgfI98rANtecLleGeoz/JzDR1T1h/czK/8JgP/O/vF3APziq2/9vv273/creIfvfPZgRpKc9UWIGMfgjkMxjQNSJCPqsmwQ4Ziw54AxOTxMCe/envDFuzf48ov3OE8DUgyoTQ7derXwx6okKDnv4WNAacC+rsh2+K+3DXvejz17Ch57LgTJhgEqzkAzGNrdQRrFdckY1ZEAJewGJAQUbfh4vSHngmXdj63GbsSObLJPb8Clc/SfB6imK6XieltxWzbc1g3LmlEqXZe9Fcl+e7dG9mXHHLqoKETDO+xWtc+T3PRpwmkakKzwxBgwjAz36IStXghaq1jXDfu+G6NR8Y+MDe8eR0TX8PG64/m6ojVFsvFKhJiPD9Q7dPJLKUCuytsYvN1Db2lti+FUIMoMPvoIcK0GFdTmzf7bVMUKiAp/TeOqsVYadBYluv50mnG57Xi+Lni+3PD2YeTvba7DVcWoyYVKUAdEL3ASIGrkLb5YBAEQHBzisc8XDyQbpfzXN/x4rSRAnWc8PZyRS8V1t/WvrYBjCng8nxBDAuw9bTUDZhyb82bEpmbdYMGH52e0Vg2XCvAx0Xy1NixmhMLP99uP+h+pCIjIL6jq/2f/+M8D+A37//8tgP9SRP4DEBj84wD+t5/184Yh4Y//8ndRdq7v1r1QE50zcil2GCYSMJoehBEHviHzEPH26YTPns549+YBnz094HSi5LSqohoPoSwb8ivhRd53NPPrqqUQDGsK8QGn04Q36QmtFezbhtv1hmUvuK4b1sy13Hke8eZhwjQNCD4c9ON9L/jw4Rm1VnjvDzdigOYY2dr5an4JubAAAA1DStDAHb5t9UgzLrzJ9nw3WhEHBFt/xRgQIgE85zw548pWnJLSBOc8/ei9R7OEXABHB+REUEvFx+eV4FIMmCa6AHMG9YZOs+s4TQO9/hwjvz+fCuYhAfB4ua5Y1mx4i7EsQWMSD24tnGfPV82C3TuHKgrvYQQqzulSK9QpgmdhbIYViJqEGt4+443KQYuca9lcqLyYDgUHSec0jXg6jfj6csPzZWF34QTF/rvCSGgQugE5jgDS6DSsAjQoTUvg4JWx8XABQTy80CvhPDg8JIe/9eMrLtcrLtcFPkZLIqYc2XmPc0pc/baKdb2ZXwMVtS4EtvrCklhLOZ6ZnLOBvYrbugMrz0z/77VR2Rjuvfbf8/UHWRH+VwD+HID3IvLbAP4dAH8BURTgAAAgAElEQVRORP40+Iz+bQB/wR6m/0NE/msA/yeAAuBf+4NsBoYU8Uvf/xKtcPZeduqiLy8v+Ph8xbpn/Pjrb8hU42N7EH2GGHgYH094+3jCm4cZg5l2OidotXEuF4EfE/bKDDjYmxdEINqwbSv2TABRxVxd94yX6xUfPr7gw8sVH18WrDtTgN48nHGeRzyeZ4xjggLYd8VtXfByXbCtmTyAGDANiXRaIwIt60qH4q1iy2zxnaOA5jQlnOYRDzPHhpKrmXhkrkJbxTSNmE4T46dyuRuBKCybkBuSzTTsQ/LsqlJESslIRQC0mWOyBWhUC27VhmVdsW4Oy5YxDgOg1QhNxAqmcbCATIGgwmvB/OAQU8SaK55fVuTSMA93AJYeAXQPckZOarXR2KM26h+ct0gzh+Ycgtzl3Wpr4mAOUYzri6jOvkfp3AOxAuJY4GqjBKx7M/jgoBXMFbgRkN5zsTrN9bPzHnurqCKAN5EUmH9ZBAghwR+aD0bC9Z/rkoPAIToHrxnIG6QN+H8vig9ff0NrfM+Rd4geTji+ZcssXPeMddmwWIdA5qAcFBY1/KMPd8E2B52bspu9XTU7vp5F+UcuAqr6L/6Uf/2f/j7f/5cA/KWf9XN/4kV4jzfn2XzvC6bMChgdfdjyc8PLyw3XNaPYmyBQnMaINJ8wjslUfR7e28MePdZtw7ZluG03QNHRoERpAAHhXvn5csHL8wW3nT9/2wuuy4ZcMortmkUED6cJ794GDIk25ClQ8VVKwW3dcLktWLZCP7otsxPYeRvODUcb/3xZ8HJbse4FThweTyMLyuMJj+eZvvFDtPz6igwClvM8w3tgGAaUWrEsK263Dbdlxb6xw4AxIJsqIIrBthnBNgnTNGAaErrqLueCGhxyuLvxEl4inXXLGT4FWl/tBbsUtOuCD3I5VrZOgC9Gj+n9Z/Ae2Df6BBC0JLejI/MeDS6QieiU+/jajGGHhggL4wgB3UKGvhJ3hqb3HioNLgS45mnb1TK6YzEAOPHwjgVNGweIopWYkzhkKRgnsviK9i0TRxbvcayhxYoQSgUs19DFiBATcs7gqex+lwSnCxoQBIIAHRLwOLOzwIKvLh/w9Y8c3rx7C4hg2/ejePfnY98z8yFMcLTngqoVKnQh7jmG214OK/rWP8tX7Na+HgfwakX+U87fH+aw/oP6ao0ASakEUErhXF4LNfMEqBJ8achbttbRPPlNOLTlhq8/XvByXZBSRAgBt2XB9bpg27lnjcNwtMIl1+MG6EEPzpFGmjPXKmrg5ONMeuzjA4UwzfwOt3XDuq5Y1w0fLjcse0ZrcvAXQvBoueGbjxc8v9wOBt5eet4dWV9P5wmP54lEoBQhDti3/VhxiSO4WGtBKWz7lmXFumWUqtj2Dfsrc5NONz1PI+ZpQErJDDfJSLytq3HNyQfIuwGdCgxDwGiKtmFMEM/bfRwS+e15P7IGci1GpBEMU8J5CEgCrKVg2ehpRzWmO2zGotmPeQYvciVnpCky42jy4R3Zh77dk4+CHQwRrgWLNggqpBWIHXQozWKKOKhzqDlz7LFb1Clv7AZFCA7zGAEBqgpCSkBpaHVDcoLdAamLz0xyHQx0rbUYW5S7Om+jm/MkHJFpCgyaUGrFZwosVZHbih989RU+PF8xzNNBCMulYNlorkKTGfJWuqZFAVLVraA2W6lvtrWi/L0cY49zJL91bsQnXwRqbXh5uaBUu0XXDbU2rBuZcNlUc0xw5cPSoNhzxeXK217kI1sk7btU2H6Upp9icd7sFtzRir7myXdTDGYCNKQUcBoHPD2cEIPHnhsutwXbtmO5rYcEN9diVuJqTj5c/aToCVyZ71u3An86T3h6PJudWMCYuhusYl1WaijqT/6lakQSAxBvxilowOFA0x8eMhij7f8BCNAE2NcNpa40s8zF1q89TkswjAPpsN4fKTdqo1dKCacxYYViVQC2xQjBY04e7x8cpsHDQ1EzVYkiJFHREcraUmc+/BBUpd9CM8s38YEW387RW10cw1mV2gAowUkIoEI1nmiGRwM8s6dQM+AU1d1DaBig4izXkgDuXh0UBIvV7L+4NuXP98J1IqPNDVMqfE2lFMTIDkeU0eD2asgrEIGPHt4BSegA5ULA0hR7abiuC37rm6/xo28i1LnjoO5mq57NlyI4Md5/D1ZpKLUcLFluFvq0fWeocpVu44uB7L/f1ydRBFQbltuCTul1IsiVbVBfh11uG7a9HiKdlPyxthGwEsL+vndvf9rWwYtgdA7zFPFwOmGeR9ScsW7bEShSG0Gkdc9QCFKKGGPAELiNeH654nLdsOSKWoo9pHJ38FX7GKwVq7Vi6w+g+cZFz3l4GtjuM1qrYN/peFNVjdZ7F5eUcic/tca9NPUS9wCTZqoxET3EJzHSmCW3hqc6QQT8PQpxiKoNwVN9OI4TxoHWVU64W365rgZW8uePQ+da8JFhi6qorSKvGelhQIoO8A6l8cqiajOY74CJr5w3HkalAtSIYO0VgxMmlqFCtB2FTYwPQDzIwQvBVPU2CChxoL3y8/FaAU9btw6mUijk4Aq3HCF4lMwYvJwrhuAQUkQtwBDdIcZqYmhUKeSskIsOrRleWFCac9BGXQG0wUuDJockERWCx2nEem5Yc8PHteByWeFPZ8zzRPXnQuDP2eGfrAMTW4nnzIswG0GttXvM3BEYawf+zn6lO3dXw/60r0+iCACC2MU+pmjb8wVbrnShWbkLT9HjNCXM44B3b86YRvqtoXGeWvaMy3XBsjlmxDeFRId5ZD7baRoxTSNCCLjkTFCq++sZBXhIJBA9PT3AgY5FWgtQC85TxDyP9MMrjIO6rTvVdYdFF/fzxQ4QkXtBMGLLmguWPePjdYEqrA02UK/0g00npdrMF8EAqK5HsGkPvd5DcOyVh+AP/wDnmHMIAOOQ8PRwsq4kW4dE1dmy7uZXz1vyIKUYszIZuSXFYBsPgRSFs1VVg3Ieduai5CmdjsH2+/qK8OXuu+8eRqKNbMDQsRpYqo4IYCvBohakAYG0huhJF66geao2dgtNmo0bDIKlESywVzOWMdwo+AKXC1RpIbeVgnXbMKQZzgXUVikgEnYgqmpmJUbcK/xDeefhnUdW8FY3P0K0Spm4AIVER0QvOA0RT/OIz88ZH5YNt31HG9OxDaMqlrJ3AFjWnWarOzvi7pRMQpWDBMudxN0Wzrne/t+Vr5/8OCBOME8jaq14frngw+WGH39zwY8/XnC5cdd8HiLevznjy89Jtng4z/QaVMV1WWlCchNWYCcIXoyEw4OYS8V13WzvvKKVagy+iNIU0Wa94BzGkezCWivG4KwF42y5rRuuy04E1lrzbDcyqcxK6RTuQqO9cO6z08sP7aBC46AT96PN+fWVJZQZg6jgSEcKricLke7cd/uDia26QGowDoOD0FFopb3V7RVFuacI0ZNgZLJS6knMXLznnO22JIreGjP7TqcZJw9MI92EWJMUQ3QYI4FA3m7ujvwLwO+qRPGlsHnVxtlaxNpw/n84C0x1QAA1AyE4VDjO5gBKyxQJiRUQgxS7BqUYqSeAZibNe9wa+QhNBFUFu2kmuJ/v44xHa8Ek5vckJvSll/c8mHbgxTPeXGs9Pk/nABcDYkxIUTENBefB4Sk5LLcVWkYMwWE8TVB7VgGuv2/rbu1/MS2EswOPw07/LjF+lWXRuqIUB/X4274+iSIABX78zQdcbyu+/njBbePDuu0ZToCH84h3jyf8wudv8OV33uN0PgGq2PfNZltFigE5Bkwposc2KcwfvxYUL4cJhpiIo7v8WPgTANJR3U6t/rZnbOuO67pif+U1QCCm2ZtruQZKPCCFwFWRdg24zdy+J8XwIaXBZ1fsAeitvM2IXaUoXdEIjh49b/D1ZxqNJCRGZ+3uNT1CvKliy5ldlekD1i5PtqhuwDoH73CaR4xWBJe1j2LZlJvkFtC+DJgAjCpwkg7PhBQ95jFijLRa7z0L7LBA5BBPqZgFmxO04FHEUvhaQVEPcRHaFB4NXhyacgdfm5qab4D23MUGqPYeie9n5/IzXFyOv8QAxOAjCpgzWSq9B0SrxeAF1NLgfOTs33ZAHKnBAOAdmhc0YVvubFMQRNBs7Mlw8NrgpMAHhQ8VIQRMMeBxTPjR9YrltiKkCLFiRJSfgHe/bJp5VWbLIWBX1SXSztKZyTzVBoajgl6QKQacphE/+Jbj90kUgdqIoO+ZyPmeC7YtU5BzGvHZ0xlvzhPOpwkxRlJ6S0GpxWLH2j3lB4T5vHNQ81GQRKpr3jK+/vBMQo+x8wRUjTkToXhvQFGuZORl+s3HaPZOPsD7nsZjBzXQMHKeRnuNATWze1h2ch96hFn03Ah0vcKeCx9o1cMDMcRk2nxmGuTMNVAUKs68F3NG5o0QHQ/eMI7wPmKaEm21YRmLQzpyHHK5R55VO3yHoaU27NuOW/DGna821shhOhKsNa25YBVFqwUheQgoW3WOxigpBPM9MHQddEr2RvRq4kA3oIq9NITooT00xf5cEFt1iUBrI1MPeuzDAYGECKkbojCZR5pAtRIMhYWTGjhbxdvvKxBnJjOV+Q+1NizLgv08I6AhiOUpSPcgxCHkaY3FtlnT5h0DXaXa0+edaVIaWilQU/Z5X4/EZWd5m8kLXrYNW6FYqRog27cZ/ZkEiAl0X8euFOxSVz0ikgXqWJSidzjZVuvxPOP/+hu/+VPP3ydRBNSYWVyX3FvOeUx4NMuq0zwgxkBAxMQU215wvS64vOLR23KAb3AKFtrJFutFb1itu1DlHD0M8dDzd/CoNIJRD/NIIG8e6eBq+fFckXHHn2LEmBgK8XCacX44E2wyjsJl23G5rrhcrthywTAkKtbUmFzBE8WuFd5Ruut8gBfmFC49TaYpfHAYQoQTWEbDbgCRQJ3DaGBQKRm5NZsPSfhZbNPCIFQm1pASbRmMZloZo6c+vcdWKQNF+uZEvbXTdjgFFjTyKhxGwMARJwyNkUOp6ThPC7+TjMmCdd8xICACCDDHXmt5oXQHhuVQqFqQCgETYi0KuJgoLNp2KCoNXZvlN0iDOGIETViMxF5Xaw3qCO7ebiu2rAgpQbBxe+IAWHyY+ABVqvmakpPhJZBKDaVFeQjsJpqiCe3a0HDoKwQNrhcpbZBGL411b9z09OJmxdlZLepelU7CK1Vhn/XFAPMAJzS1GRIDR54ezng4nzGM47eev0+iCAgEOVdcbPe95XrM9cHilsZpgA8BeyEhYt+5NbitGy7Ljm1jSkyXVnqfDDiMJHWs29HCjubimoaEYaDZQjHiR6PJPILjDToNiSEP4lDKDlgmYTM+9jCQfBOCxzROmKeB40ZrFIZs/OtyOSEXbjc411PzHyx9Jhe60cZIFZsa/6FaUWvVsuxMuLIbkacaI5KuNEIZbWvmoFOw7o0hGoV77j5aiAhicNCqKCUjpYDHh9mUbmKEp51Zj1Y4g21K7lgGNwnF982IHNz9VgENAJpCnG1P1EGbWPJSwWET3m9+3J2beO4bUInwBxfg0ENK+Zs4Z0lR3vIh8m45AoqSM2rJjCWvzJhkIcMxloRAzkDOGSre/swbBVhwJBvVPvtHqHqgVIiH0dfNZcrRFQnOuhlHolJRxRAitn2HKO3l1W52un1x5ScK9LaVGRb3BCd7WxFDsttfUEunlXM0jJZMxNDTRKPamQrDGMiZEf9zFhD9vL/2nPGjrz/ittn+WoBpHJFiRAyO5pvzfLCixAkU9zWgAEY5pYFGGkeq6YJHA7n3e27HhuHhNGIYBwwDiwRHABpclNLXRZkrvcB1ljjFmAKGOCFZhHUwFBwGfCUPaKUNdU8iVgPuBusWGHDaQUDGZY3TyLHAyFFVK4UuKWGM4Xiot0xWG/fmpL2qknHZFLjcSFyqreG60qdx3Yt1AEa8igFDCLYJEDNLtTFIG7bMPfRtWbBtHM+iF67NWndSVngfLFRDMA9s/Vvtgh7A+nkziRFTKnZrZW8KTH/Yne1q6Q59tjbgVOHhFJYToAxYRYMPXItBuqo0HwafuQAoJBAdqzwbm4Iz/YJTeLFsytKQFdhDJmlNYFTeAnXeiFUGNboG1WpF3PwPRFCNcRgNc9JaIbXAq94LrwtQsWIBwV4UVYlH0XQkGCbkjrFBhH4L4zBgmicM0SNnUt9FGi3GzjPOY8I4Dgg+scsM9D2oRnLqMv2f9vVJFIGmOPjOUKWN9jzi6WEiN39INlfTJHTfK9a8I8SAd+cTvAAOih493hQmwKhYNsYz3TaLiYoBDWxxg3N4OE00YVQzG12zATzkHKzrDu8chnHAfJoxDgNbyFYhAmxbRq7Uwi/CDxPgDbmamENgNmQhkIloNFFtXK/h+cVEQuUwVR2HiLeP5yN1KaaAyT7HDva12nBbVlwXjhzfPL9gWTdj8/HQiR0gugd52k5Ff4xEpbGtX7Ydt2UxQRNlzQ+nEZ8NAzMLasXlcmNX0G9UmLxYACixnD3zfW7WzjcFGizorSnUC6o4NHEoBlyKt+0H+HOqcJqnJl8QhByLquQWwEZCJwPUBagWaNshYFQ5XENPRS7mQ2mcMPoUOKFQyey9uiXbHoB93/n5Bgex219bA0qBs/VbAzUNITi6PGnjSKYVwcC6BqZCoTZTPgpq57+UHS/rjjUXVNCsJo0DYuJt301n+zM5pog3j2fMpwnTkDAOA0op9HecJ9reHyOGGDnq7t605+5D+dO/PpEiQMZWCh7zPOHpPOPzd2/weJoJtAXz4Ms0/pjnhMdwomnIPKHkgmVZsK7rsQffd7Z2y8r9KlcwI1t3z8CHIXoIGmoh0JS7gGnbSJYxf7/zPCGmaCYe7fDeo/NvsduPYScN4IdX28Hj7qh959qLCGrf61a64fQMAbaC/D0fz2ec5gHeO+Sd7a0Tzv9NgWVZzbRSkct+GKM673CK8Uik8d4d3Ibua9esENVWiCEUrjC9N5LPEDkC1WKKtx5ymXBPxL1bt+eqKI3vQ+smHvb5qhmBKmBgmvVPBt7Bdv857yjRA+LRRI3t6FCdQ3agQ7B4a6vVOBANqpnYAcycVnEwC3uydX89/f0SsI1PIQK1IKtiBcdM59zx2kVYOKTQZ4ikIXIXahPTCygiWFD3PaMFTzdsCSi6owrVdLnCOCIbfvjxiueFr9uFgHmeyNg8wkmBbdshQlIaRDDPBMenxA7QO8+tghJoKYXdZDan6T0TJ6OT0SfuNtyaIg0J75/OePf2jKdHhihOQ6QhpZlfwHn4QDeY7hBbcsa2bQTrmtlqKz98EY4SoVRMQ8T5NGEYiMxvK1dlF1NtdWZetfALiGBMNPZ89+4NTucz2z+h0rAWvrnavCnx6GkoBt6Ia6bhNmTc1GncbFS0Uu7MLyOl+GCGqq2zJTfMU6LTTeHsWKHIW8a673h5ueK6rqjNNA7nCQpiKSlGnKfR8IaKddtwXaj/3/o6zJD4FOleG2wkCE4OyXGxkBRnXU6/rUvJyLsaIUuwl8RxwNRtzYA/zriB3Q84z3d7sK4XcEamKcbC9M4fycdNmQIE56EqcJUrYXEEGaVlbkLUQZoDmm1iAGyqZkOu3OwIAC1Hoe17dGnKz0MbbtcFpWT6OLQGLcw39N6j9ZKlBFf56/m5wgVaktWKqpkiKe9Qm6BJQG4Ny7bjurAA/M43V6wbwWVxgvM84PzwBs61AxCEnJGCI+B8mjDPJ8QYbHRlwS4NKLkZk7Kyy/MB656RKzMtTtP4E16Ev/frkygCwXt85/0bvHs64c0j3YB8oH9cLhbhHIjmJuVL7sSIUpppBsxazLEKj6Xi1lbDAYI5GdPnr5RqHm471o08gNYUKdE6+3yeMZu11zwOmM+nw9017zu0VARvFtlgzLdqYpqxmLOtEW02Ww8u64bbbeGm4Lbiuqycx0FWmAjTj+d5RADl1Y+nCevthmGMh9HkthfKkHfb9dvMl4LHeRzhghleVLV4Kw/ZFLflTmFOKeIcAqJz2DIt1PhF6+shRcREoJE2ax2s48iyrLv5FTBD4ORYWGthinEwelquytkb/KxQBDD9PRTH7ez5j7Yt4LyNxgyK5jK8j4Y3kKYcLKS1NYVjIwZ2JBugxTj2anThBpFAQ09PvKG1gm4br9YeqNGRny83XG8LztNIvYk6oN3j7r2IkZHomUjeADknYrkBe9nQGrGE3IC9AbvpR77+eMXf+eFHLMvO4m/MwHmIePMwwDmPcUxUfqZ0JFGnGCA+odZsaUkBog2tcQ1T9vXQexQQKO2+g9OQjNH6Lefv53qa/4hfKQZ8+e4Rpynx9g/MZ29K2SaFEO0ggIjNPuAWGt4xartaC77bQaFdt8M8jTT2gFqrWjkbnmg7Ns/jsWrpbq8fnq+4XG8I3mEcPuLhNOF8mk2koxinGdM4mR26YFs35JwJthkusawrPl6u0Ka4rjteLje02hCC4P3bJ877wuitNVdsuWIYJ0qq827FYsEwJPL6Hec8zvwkG9GOLOI0TTifT3AOyLXgdrmh5AwnjaSqko1xRoOQaqrEZaUIpVujDUPCaSb42VrDTblpqI0klZ51UC0EtsdeKXo+A1ev3ZSjNpj7EQ8OnO3+jRthW0AWLhurOn+DrLx4rAZRM7cT3sGbIOjAW2wX16w1rkWR94ZWKSsOgaYrXYMgTtDA8dIHB12BWpoxKXdLpBZICywkqmb6oRCJ8M78EgGqGkmVZLETQMVDfTiyMGMI2HLBb331Ed9cVhYN4XjkgeP9J72a2yNawtdDQ6NYoa0iWWhpUUVr7CZrLRjSBBWHh4e3kLqi7VdMg8Xk6SfOGAzB4d2bM3nvNst1VHSKTJEp7ZWhSLG5P+8MI22VO/llw7qR3tpUMUSOAKd5uqvlnFBCOk9oSuDv+eWKy23Fy2XBbdsA+4CSeRsOMeD5csPDmQES8xAPmjCQsK9k5AmAXBTrvmPbdvoLrBt6gMQYPaoTpJQwjSN8ICahpWJuwLLtbFVdwrLS+JJAG+2ljyDVRsZYHEjxnefJkoaCiYSANTdcr8RJmjZM4/19ELt6RRTDNB04xWT6ihijAZtUA665cuQyJSdXYDjScooBjFxPkm7rhXRp7xykcsSAFVo7J+jEadUGpwwFRa1ovh03vQJ0/20ZDg0QDzX7LzQKidQofCp9NKvQJpYz0OB8s0Qfse0KeQatEVvwFute94LbkvHx4wv2z99AYkLyHuooHQ7eQ0WBSsyA+Q5kN8IFcgBEUX3E1hTVfP+c4ybgt373Bb/14ys2C8nhaEWSz7rsyIUitmUriMG8AlrFMJLwM88jhhSNYyJopWLfV0rja4P3DLPthrvVTFGH+A/BihCQu4dAUyM+KU7TCGfzfYHHvm/Y1h23dcWyrAc4x7+oi3dme/X0eMI8DZhGxkDtOWPPnPnowLrjcl1wXbaDb5BzZUx0ZCAlMwIqcmQEF1TQ5gFQpZRz2/HxGTaHk36bO+HJ9OHF1GldsKMAYuDhmky11y2+ayPYNYxs4dZtO9h2MCzCO4FUMcovDT2//pqGq0xZYmvfw12bGgFIFb7fvIXGmg18b1vlVkZsVKq14ePLhdwLBQExhUmxcUStCegVMEXOwwoCpoxUd1g2WnuheR5UW9dBKXqpCgjY5rdKz0GBQEuG+MSwzryjFIEoW3jessItAQA4QTPZsCqwF8tqVLMrbwQOtXl4P5vAB2hawYhzgXcR4jL2mlFawdfffETe3yF6Wzc2gqLi2HtyE8A/iwcBuiYO0AonDkM0fMQMQHJu+N1vLvjB7z5jyQXFOh0Fx5OSC5bbFeuycMwUoCgxJ1FF8g7nabBNgLlO7xsAYmU5F6Apal7hNONlvR5kOHEBz7IiBfetp++TKAI5F/zt3/6RIehc8w0p4mXakbxg34l4LsuKZd0OeWcPEm2NAMg4JHz25oG4wjRyhiwcDV6WDbfbeqTr8Oa/cBdustgQwxEJ1u3JgqP3fgyCXDIu14rbsgLAkR2XzPr5SIWtjEi/LRnL7cbXqMamcw6KipgLbclV8Xy5HsYnDRb3ZTtjGqTSVWgYItZ1w7JseLlcSTs2HgB/PrcGDAiJhwFGU+bTLd2nwFruBkHJGd7dUXCFEZH23UxGEtIwIJpewQlFTM7UcyE4RE8CUB+3vHc4jQEvF5P9OvIF0IWWzei8rRFkMyAP8BDnzfeRRqLV5MZeAhRq9m+gESdsBen4s6oBqn39Wk2bceRJ+MgVmlbbPvQVp0dtLEp7abhcbsjbBhkmeHGA79sNAcQDUlFRzKbcjFfRTE/iEKLHFBOcErj+wQ+/wv/6G7+J3/7RNwSH7X2QTg2GRdWDCUKwjsU5jxQ93jw+IA0JNe/ESmrBuq5HIcm1HilQ2aTie6FGIQzEDmot33r+Po0iUAp+9M311btiK5zgbf/P1Zw2BRxnuqYwLToY1zSPePv4gMczW+RSGPq47QVV+f3O6GJN6ek3DCMEG1ssIUKfLGorOIfcaKjZq2j3/BfXVYMe02nGeZ4gIrjebjyU+w6AIKI4wRgGdOeiEEzo4wKWrWBZVzy/XPl6RsdDoQ5VzEE2MY6qAUbiYTpRLg15r/Ah4M04UkAE8gEGI0s54by8LAtDVIoC4hFcPKjXpyliSoGBJ8KcQFViBp1ExMIFA/6MyGMFT8A1X0fhS62QFjGkAbD3MFZF87byO7YHSq678md1pqbzhlmYmUix1yEukA6sBIVpOttNSivBMduibLkYVXrDXgqmacA4JXIPbI1Z7Pd21gEJcBSR21agjZ0JQ01Z2Ftt7IqQj9HM+YDCXSeceKSUMIwjtuaxLSt+67d/gL/61/9v/J3f+THG6DBNJ2yFQaarOQY5IS7WqfHiBENMDBwdBjw+vUH0MEDTo2SgFZqvrBvJYTFE9EATiAO8QlzA4JU+mvKJrwid95imZMwsyjWd4wPZjS29I2Gl7z372nAaB6YCpYhpHPzYHogAACAASURBVDBGhlrk2rBZ1b3cbjTq3OkhQCSac5Xr8z1gyjHHm1BJ2fXeY3OcT1trOI0BT48zSuHWYRoGAxPpCrOsjH16fGCAyG3d0AwZViickrADa2ljTHjz5G0DwiJQjDK87jtu64YenioQxBRwnge8f/tgTMkBntrcI+feed4IYu119/eDFyQfSJd1Ah8EJ9uAeFM5ek82W7EVaFMwst2s3663FVvrWYWWe6iK8nAPCKFpKDca27ZjcILcHHxTRLOJ5+6ejM+O9VCDzwIpKoAPaCWTuit69yLQRuagMnaMBYXM091GotUSm1trzIn0AqnVVIKANG5QvAKhFToiQZEbcR3nAnwI1rGQntyU46pqI4XZAFYVy8lIEfPpjJgmlGXFVz/8u/hrv/43cL1s+Cd+5Uu8ezsjDSN+/HzF//ODr/E3v3rBXmF6CNgmrLL7sM0RlF6PBWSiRs+ul7wVYh3zQAs5Mech5wQPw4jSHDwyuTD1E2cMphjwve+8tQNPhlawVrgpsG/dRtlbxhpbvGkc8fBwuuv27YPft/0w8uzodE/paY5SzVbL0UKWYuorLoG5QTAdfLHDNER2CNOYMI2DUX8BFT1Gk2EY4X2gtFVpZLEaYFlLteRi2pqfTjOGccQ0jqZazFiWG24L9/nLultb2yzVhiutx4cTI71t7FjWjftzu7FLzuiBrFB6MLZmMeWBNGwfyMCbJxqmDjEgxmgkK2ILt3UDgEPOmkvFsmy43m40t4ABuBAkdydPpeAQGo0+zmPC5bpidzx8vtERmHoB0BfQEP4+Y9MQgx1bCAFr7k7AHup5+LwjTlEgJuYhHlBzQ86KLbeDKRq9xynwNaJa/gK4niQ7mc+AE0thrg1LFZSQsBtGU02HoM4B3kMa15DaHIpwTRxSwGikMtWMb373h/jff+Nv4rbs+Kf+1B/DL33vC4QUcFk3/OjrjxCteNkKfufDag5PkYUVHikwy/E0kq0J3RECXY6yMvsx7/mVu1APqFUbdxSDA7RllMJxr5RPfEUYvMMX79/S0w1qNw8Py2oRYA6CeSRYRD214HyaqcJrDeu64esPz3h+We6UyiFBobitlf5tlaBdM8ml954tmJGAvHPI3Xe+jyAgvbgnwfYMge7A0xN+GV1lK7c947pth62Vcw7TMCAN3RWZTLu8M/dvM5uz3eTHeedBnoaIlBhHxdUkW9TLbTWzFbroOH+P1u5pztxXcQ4kTtHgpB0GrhqJdZRc4CAouTISbdtx2zbGwjWmFu+1Aiq8abcNEGoeGOsWMKWA5qOh3WQQBlE8zgO++uCxlQbnqZJUixRTdHQfLMDWGbRS4GMCYkCAoi0LSS/JwEcFrdZb/f+Ze5Nf29I0vev3davZzTn3xo0bbWZWVlFZtssNYEsgQEhIjGDimWcIIyRPYIDEAIu/wCMkj5AsMcASEiCBBAMmCAkJS4Upu9yUK11ZjTOrMjIib8RtztnNar6WwfuufQOUkRQuW7pbuhkZN25zzt5rfettnuf3ULzD6EOBaqjFEqPSmxTC2gVROQavHoyi3vwqAJNcGyuNYqW1WFPGR5H05irk5QYqBpLr01gNNpVvmKELDLuerg9A5vWbl/z6P/gBrx7O/IVf/S5/7le+zdBbplgoqbELlif7gQ+OAy/PkdB3fPD8PT56/h7jMND3ghXrQycrwCLpVxZordzyBmJSrYZ3OlPSB2cR7PxGGs654f07vh0wRlZ2NMMaV4qWoDlm5hgFgtkHtdmq973IGiR4S4mJ6zRxOk/EXGUCbBDWYM5CyS1btrujG3uGYWBUGOhtElE1tYeGNY7NwrIBKkPw9J2T4RqyE15jYppXLZ/rLe0nOCf9NXJgdNquhCBSVckWlD7Paa5cbYKgrkXzAIOkColsN9+wX9uwq+8CzkpUmNN5Qy2VYqSMnc8P4mdHFlIbXXccAr3Kf2mNyyy04sfLLFLrG75cOPvqd8IgVmcDhE6yHrug9B2sRII30eubWhg7z3HsePV4ka2CbVjczQa7fV3b3DoV1RCoIUpQ5dLa9LWJZNdamQs1+UxqRbcBAnRaNX59iUnK5+AY+h7jArUIvktCSRpVeX1VPQbbPCGkwrJmUpWVnWkGjOoFpP5Ao2/wVsRVYydmtNPjA7/xD3+PH3/5yJ/5E9/iz3zvU4JFvR0XXj5eeHlaOF9WBu+53/WkMOD6gWbk86i1CstCFaWpoHJoqWgx5mZ/BzHFOR0M1ioPt6qVqg+dKBp/zuudOARSzvzBj3+q5qB0E1J4ner2XaDrRcACMnGe14nXbx5oVM6XmSUJgcWgLD4jSiofLHf3HVse/PY039SDrcoudpOhbpPkEIIeDJU1RUqRIdt1WtQoowGaVuEcyqzf5Lci/5YPLCijbzcOeC+zjrv7J/jguJyvTNcrs7YAtVhSE7VcjJH5BhGV92ojFtfSyGTwMDjZTKQsqUJV13W1QdOdftcFjnuNGVOT0xoL52nhcp2ZlvXWQ29Tc6eDWqsDwN1uUGmxuNTeKn0qCXXFKVrNNJEyv3+/56vHK0uUiogGwTZcsFK6VjHYbEExDUNqloqDssrTWmEzBokD21KUpQ0wNESWG0tjzZk5ZaL2wNIqahaDrj8lnsGRikaPI1uBWNDcCWklahH7L6pINS3JGYTMTaza0YfO4ahcTid+47f+Cd//0Wv+/J/5ZX7pk2fkuPLqLJHzp3llXjO1iHjouBv5zjPLQ/WY5lhjY12uQLu5CV0YGMaRzgFtQ499HUAr10kI4bYhEMu0UKNvTs76zyeV+J/ZK8XEZ59/KYKgIjdkFzy7ceD+eCB0Gp3V2s0cdL4sIoZZVxHD9KIJkBtTdaibgquhzP6KyG7E7ppzovPqTWg6DfYyHPTB665fwyD0zyzbTh1UxShAjpJF3OG9RGLVZkQyu9mI9fDpOkGBg0ZtWcuaG5cpSoZBlHaiqsyzNnn6CZNQtOpbCnCtQtKdFBYiF4g8FZ0Sb0VRaLUiWfTmMcR1FXrSKk+c0mRCt+HHrT6Ft22GAen3NfHZqw/fGsPdfkfY9SxFk4KAZkWUtB877naBx0vE5ir5B97TTH6LgWvyQ9KhokyyVdZsgJgTLmehJFWZR2QlJ8nHKbqJVQ/nGKXPD06qFKuHRgOaHgLgRJzTmrZhWeg+pZKzWLdbjhQkz9CSJfKsyZ7UW4sLnmHw+ADTMvEPf+fH/KPf/ym/+i98wi9+/JQUV8kCrJVBV88cdQhYHZdYOc+R11NmIsrfZww+dBhjtTJZWJbI2EkS8cZV3LwmNHtr96oyCH3wdKGTXEIDpjl+XhDYO3EINKBtjPqhkyFWkBK3lMLlOvF4urCmSIxiuEkqjmm1yo2UskY2tZvNduPB1SxBls5aSif8dskObKxFbLOh6xh0VZiTTFhTEm+BMSoLzgLYKGpOMgbdRb/9ALpugznotN1a9vuRUirTNJGzQExevnmklMp1mnVr0W57bQFHahyWhnBYI9Noo6k0m5dAWPWio9jSiTd7rzGNzokPwVrUerwSU725Ibf98SYEMnp4bm67txAPSFmCYqxpjP1OtfNiLIqlcY2FNhpQDUBrQk/66L0j5+k185owQd43r+rBbSFsjWFVGEpnDLYFsg8Y62ilMM8TwVkiUvpmt2G/uSU1z2skZnE0NgzBB4a+Z+Pv615X3YWZ2ER+vRGXkn7NrVWBkqSM8b0W/iKFbqr3kO0VOCPX5+/+8AX/8Lc/4xc//YA/9d2PKGmlliTu1eBuCdjWQLGO0iz3+p7tFniVOrLfQeix3tOa4MROlytfvX7Nui7cHUfu744iG3abYEpKRPn29PNKmVYnvE+EzrMfBtk4fMPrnTgEvHO8//ReVkZFhCrny6zwx834clNW0PcDXS99rchoRfW2pc9uZo+Nw9930ltb79n3gTGITNRqadsFGcCFvqdoQnBcIzEKX29Dk2/ryS7I4GYjv1hlQFlnZWWptF6MVBldP0hpPy88rldSktiymBQzjbnl+71/954cFim9NcnAba1m9AZLpQgE0zqcUwOLkQBWmdkjuC3kcFjWTCOLKacpzERTnrdtS1Pirg9BUG5pyyaUKXqKlUjTnruoFLvx5vFCsIb3nnk+HQ8cRznomu7gnx4HPn1+5EcvHpmSAGC7JoNYts8Kw3WRdaJTWKrs5SH4QMyZdV4w40hADpItYiwl8YvElHXOIu9LP3T40EnLUFSsaGDNRbBtpZJ1O7BogOdmMJsvs/weJ96OZqxUNzqr8MFqLsHE3/v+D/nNH7zgl3/xY/6l731EyqKZcFbYj62q7kJkfHjXiVbFWc7Jcq4We3jCrt/J2rEVcrH0vWdnLceSia8qX3z5QGvw0fOnkq+pAq6i842YhVVhjRyMDamKz7NUNd94//1zuKf/f7+MMepO20i4UQlDIksNnZiKBK0dGMZRBiFqBU05MU2LfOPKs/PW6SBQaKtD3xE6NShZ6fW7LoB1st5KkfVykSfKLHRhSdFR5WDw3KuJZz8Ooq5rjaH37HY7UlJrMUY3BYUlLqwxYcxVsgOXKCWtWpRLydTaMw4dw7gTklKQtqGojFqixqpOiWXoKHFdYkENTt3xueLbZqXedOlN+sjaiEuUG6e2m6hEgisQAq+KX8DQ9R2bxh+g6M1VWlX7c6KeZzn4jCQRWQs/9Tuu748cR5XEl4LT//7h0wOvLguvH2cZtFWJQ5foTnPDjF/XTOjkgHNNNhddEBfcPK9UY+iGQYjByPsiwa5Fqr5SMKXS9YFu2wjkQrHiMYixEKPkOkTdIkwxc1kSUZN/UjEyE6gF07IkEJumfyc0K36XSuV3fviCv/tbn/PtTz/gz33vW3Itp6SKP8GE1VZoTcCq29DaICrFxwyrG+m8DC8xBlMyXSfV8dgPHPcHUixcrzOfv3jNsycHhidHdZAK3MYHT9f3lCIPlqZS79oaZV2ofxzFoDHm28DfBD5Ezu2/0Vr768aY94D/Dvgukkz8l1prb4xcSX8d+HeBCfjLrbXf+Hl/Ry6Sdd+QkIz92KmhpWcYegxobLiGcHhHzFvppk8cZCDYWa+Hhpf+HsGMj5rJF7yUl6lk0hypwHVaSUkIQvO63r6WECS0ZOg7duPAMA7kuNJ3mlIry+7bELG2xrpECdjE3r42iTQLPDlKeGo/jHgvGoTpOhGCJ4Se67RwengkqqBpmhfO5yvTIi3JRpyRA/CtnNVbI/HbtwFWE5OJd4LUznphNCmoxA0n7kLZKojKrMFtmLRJkjfGwpb5KAEp7aYotNZglJ70+YPhcVr54H7Ed/3tkLDGctz1/PKn7/GP1i+ZpkX6VIQ45K0VB2JrTDHj18Ted3hd43Uh4BqcllkQdBhcJ/6OUrLq8SGVRK0JZxrBGobgsaDkIPks1rRVD4W4JNYlMS2Zy6zwDVVZWmcoNREjON8JMJUKzmC8IdfM7/3oBf/Hr/8+T54c+fO/+m3GLjBNEeectFmaHNRAJfEW1ywWS6RySo3HEjBhUDlywBoPNmJsvn09w9BzPB548/DI51888P3f/QNJsN6PAuWtDRcM+74nF1FcNtRbUirNVFz44ykGM/CfttZ+wxhzBP6uMeZ/Bf4y8L+11v6aMeavAn8V+M+Afwf4nv74V4H/Uv/5ja/gLZ989AwpCmWVtfV62y5eHmoSoFG2yGb9NbkK+dV7TwhOJ6tGkdfydIvLQlqj2CpreStSUXpO1Qnq2AeGEHDe3pxbpRSGfiB0HessbYkPHSmuso8tEoAS18h2p/W95+mTI8PQa+VidTpdlHJbOMUrtUri8ro+cp5XFsWpR40jK2WTD0sEu9isZS0mX3OFEMg10mqWXt5uh5+Vm3TjCYKGcjSVlxqVMgfNuFdxkEJMo6beZtVO1LZZZS3Oy6amNSm/MYaH2Hh1jXwnZQ4GQt/RWWl1rK186gbiJ/d8/w8yl5jYNeic1dwHObhSrVzmiHWSouxURjsMHcVUTlGoyaZUghdAa2zyfmzVQNc5ht6x72Va3jagSxZJtymNHEV9Oq+r5EqoyKo0SOq0bMZRrcda0WoU07DKufjRZy/5v/7B72Os59/8F7/H8/s72WwZWfvWkmmm4dl4F9r+WEgWzrHxas6k0tFMpeLovRycBSd/hupPDEXSqFUn8zs//Bxn4U//yi/SbRmFVXwym8PUd17ba+FByqf/T3kItNa+AL7Q/382xvxj4FPgLwL/lv6y/xr43/UQ+IvA32wCt/8/jTFPjDEf65/zM1/OSWZdUmnv9Sq73mlZyVlkmVu6TM6CBkeHLDSRD2+ZgJuoZhs5BecUACK79q2o897e7LeSYiMkIO+8jloa/dBjrWHOmZKTlF3e6fpu1XZgwDrHYb+jjP2NTuu8DLC6rqMLgXVV/JluGBbdzadcOU3iZJRkZlUJloK3CGCyF5XifhxIRQaBxgoJO6opaCPwivBOblip5mWS3GvMm7QB3MpV2CYIRn9/vYW/bmEotcmvk8wj+bVGB03iiVA/hPdcEpLXWBu9lcBP74wSlwzf/uDAdU384LM3RGVKBt0+2NagoqaojDcK8LQWaxu7oac5x5wrK5CqIVZHUUBqUgSas4ax7zSnUgJIZLMk72+NhSVmrkvkcVpFJ5EzHigYmrGAGINwQVWAWUNd4PMXL/k7v/lDrinzr//ZX+LDp0csHkwRV19caUXDXI0hN6la1MVMxnKtjfOqLUwTDUsrSqN2lmaCyLH1s7WIBb1T4OtnP33Jd7/9Mfv97vbQE8/HNmSRdG236Wr+WXkHjDHfBf5l4G8DH37txv4p0i6AHBA//tpv+0x/7v9xCBhj/grwVwB248iLlw/EKPFYqWgmkKr6NuqqV/FMaR2+G4jLRNWBhzUCh9iYhBusoyQR33TBiUDGCyGo6zdJpgwQZT3o6JUbn/QDaaBGI+j0ZgRZa/ogU/e0LCzBsegcQ/zycuFJ7PSVGFemeSam8tblliV9SKSfUhZTxXUneXmOvhOp8m7o8cGTV4kPT6XdRCCmZYbeE6Mm1Ni3xh5jUMGMx3nxLYyDEGkFh1VZ11U86U388cZDcF6vJavbDxXPNKhVBoVWP6MQtnRiT3KBJWkWowFjHVaWaxjb6HrDpx/e8+aa+PyrRwCaUd6ATDrIuVJipPVBTU2WzllKA4InNJiL3PTNymdRjdy0tlVcsIRevAsFiMCyrKS1EAusSSAvp3nlNMtMwCOn5por1TbudiLEst4r+chhTCPGic9++ppX54U/+0sf8Su/8B4hCFJMxI9SxXqHJhN1etgKGj14ezu4chX5c0oJYsRa2YxZY7DWk03BhQ5XG87ptmMYCM7z5vHCZ198xQfPnzHuRowqTGsT6XMXvF57hVQa2H8GikFjzAH4H4D/pLV22iSJAK21Zoz5ZofCz3i11v4G8DcA7o6Hdpkl7GEYOo5O8MtF7aBd16mmXKbRqYDrR0paqFUimJwTDkAtlWtMt8FaTLLjF6WeowuBfuh4oo7CGFeCd/i+l/WbMTKc63sRhvgNSS43nFiHe9pOqo7leiEuM+taKA3CsIMsfADvrZT1OdN5L1rzFEEdfMsqGwBrJKK8FiBoRJaz9H3PbicOwaAD0lINa42ss2wZSpF1pbOOvpNNSO8leTc3scfWWkTd13fsB8Gm1VJxCg85n2WrYhFb6jZ/qHrT56L2aR1SWofaXIOSlzr6Lgi4tRfLStEhJUa+F2n5MyVXgjF8eN/z+uRYlkxpMHirzSC3EA45wAK+G+Tv1MPVNXDFkkPDZkNtM61qRVGrfNZ90OGYyHuXIuEjscKcMo/TysO0cFZ5tEXQYc4anu57DrsB44KuQTe/gci0x/3Ae08OfO8XPsI5T6pQbqkq8mutMTd1o0Wi53zo5fPNlphEnJSoTOtE7zv68SAnLFZJy04CTUxkSxU2RqrM5RL58uUblkVcsEMn+PctyLXTRG25rwrOffPt+Uc6BIwxATkA/pvW2v+oP/1iK/ONMR8DX+rP/wT49td++7f05775zwcNThAmvjFwnVfZzauKrDZUUptJqWDcG1FBqfZ8u4CKxpLXWiWlxkgmwVA9rYhMWBRzhlrSjSa83+8YhoG4RtKG/i5FqTNOxK01azZ9pwCQQopi+GlqQCosOouApph0FEkNYuKBiq2N0kRoZF3D2IL30nt6Iwq/fugJG302JdKyME0LF9UWNCylwl6jrSmZ/W7kuB/Y9Z5qLAnL9ToLtrzv5TBq5UYVHvugoZvyZF/UwwDm5rxc1ij+DdMIXjc26h3oNWbdaUmfmvwoNdNqpuGpXiLKTAlYigyqPBzHTgZyKWOqw2wDSmOIVfpzq3hvkcqCN2I9HpojGYctsrqzthGjwFiHLtD7jo03uG16Sqpc55XzZebLx6vMAaoo8JzZWhvLh8/uOByPiBipSnvQGpbCZUm8Oa38ye98wJNDR8VC8xjjcEayGoV/KYIp5z29tRgjs5vmrIShaMsVkdmEWVdpS6sV70eQz69p2M3Num22GUfjdLkQY5Svz1iuS7wRrdciq8yo/hT7x9EJ6LT/vwL+cWvtv/jaf/qfgX8f+Gv6z//paz//Hxtj/ltkIPj48+YBIH32k/1ASolFhzSPl4llzeTSePXmLEk4KgYCqx73puYROeW21deW09b3ovXfjb2EbPaCz+qHnk7TdKCx6wOtKkJL8eUpJ4nWiqKLLzhKvMhcoQkctHcogVeCHrrg6bzs6p3zqruXDzKmKOXw0AuqPBZK1cQcDEPfE5whaksxKO13XaMgvZOoF5c1YWjcHw8Y6/EG7X2rqix3IlSyjVQLvhpM7ci6Z6eXJ/Y4DLoJkLmDaCNWcs5cp0XszLWpAcrw3pM7duMIZksxkvCV4L1Gn+kcJxbW4oWAZC3GO4pBq4tOlX/iz3BGjDHz2iihYY3ErzXrWHNhVYmsYLtkIhFEoSNtiulwCUwr9FYI0nL/OBxS0axFDoFlERv0sqy8Ps+y/t22SsZIiEiVvMfvfPy+HMg1U5uXvAFTuM4rP/iDFzjr+IWPn8mwtWqQKw7beWwSvBoWmhHP/8ZkcL2lGYtL4qNotdCaDKlLzuS4gtG5lDE0qiovN6bD24PAGsm8mJYFYxAOZHqrqwkh4rzQolOSXM9/6kMA+DeAfw/4TWPM39ef+8/15v/vjTH/IfAHwF/S//a/IOvB30NWhP/BH+HvAASffF0kBGOJmUmdYFHjtrbLz1qZJBvTZPVTq5ZyItbZytOxD2qY6VSy26l+3ymcsZBTuqkAnQpMNmYhJMmfUwhFLfl2CAzBcX8YyU0PHx+UYSdldIkCHi2VW1sSc1N/hFB7mpJjMdB1PcUaLtNMq1W3ADLc3MItjXMMg2XsPcf7exHNlnxbGw7DQDeM1JzIOZJjJDhHTpUaV3pnGTsvijMf9Ma4krO4LLcLKJci4qkgLcRuv8PUIkk4wYuISdsGjIR3zIvg3qgyXMPKhWtqE8SoM1gbsHHFWM2MbKLZfzNFyiB8h0GVgKVa3To0biQx58AZbUcKzsgDoVVHsIHebZukKhbgIv76uEap8JKsbxsV7wzBBg5Dh3fSBk1z5tB3fPBkJ6lL1mKNGHfmZeV3f/wVVPgT33rGru9ungrb5DFRmuYcIO+LBcI2O8FhS6XWFZOjcAA1hq3pGrbVSqZIBH01NBWjeeexRAE1a76isfLAmJZGSpDWRQ+Vphb5issO54N8PT/HRPRH2Q78Lbgd/v/v17/9M359A/6j/68/9+uvWiuzlmxrLsQsgxjr5I3yTYeD2sdvBiOrybYbgKHvArvthlfsVd8FAWxaiXIa+l5MQUXsmLTGukbAMAyBXC0pCr2HBl2P9PBZdubBS5jnk+NIH7yYZrLI0YQdEImlEZyQbq6TCKDWGG/aAoFCykVeVPq8riJhPV0u3O8Hdt0OA+x2I+M4SoaBkQNvN/b0wyB+8pw1s1HEMZ01rMaS3cD9kyPWOkr5kr6/v4l/rvPK9BiZppmaZoxojG/bj/1uYBwHOh/YH/Z4HzBUhs5jUNNPq0IejlK2GyOmK0egGRFNGYAmfaqw/arqkqVvjkXgQudl5bLIYO1u6PAGnJNPOjhu1Z13RucL2wUtEWn7QXgIyTdygpgaayykKsj3mJLwFoVkxtAFnu16GRB7x5wyr84TIP9tNwScE5x6qyK1/v6PvuCzLx741/7kt3lvN2BqpRmh+TSjasxkyOuMqVloxXoQ0CqtiLZAbiWHs9Je5RwFcKPrV2OaxqYDSEvadx3rNEkOQhX/RdGV5+l0Ji4zRf8c6wwFMEWGt5J9GOi/eS74bigGm96IuTSCD9TesMRMZ8QsgRok0JP3reilicRVkVReM9y28ZL37pby671YSjGGNWeFLEiM08F72aW6jqhk3Vv8V3B4H8hZL04vxJndboRaKHHlrEamy1VYBuNuR24dp8vE6TLJLKM2uq5TUw+qP7ekVgjBs9/t6HrPRx88EQvufid0WZUyC+GnEIJVT4UM9kw/KKe/EeNCjKv08gUuVzko51kAIblUpnUlLkIO3vbvXScRWLWJj2IYeg6HvZbKouM4jDsMjZevH3g4X0WiXBsxNVKKxBTpusC+82RdbaVaqS7guoCxWYGdXlOEtISthWlNnKfImhsfP9lx3wd2vWwFgt78wcnqbOMbVmMxTZKOm3MEE6A2TLNysJJkLqEhJgbJPzj0jv4YOARBqp8XIULlVG6S2+Dkz81Zouz/8MvX/Nr3P+Pj+x270ek1ZmkFYil4n7CtkbNnjVGuPdNBe5v23FpWxJenNt1K0VjiSq4Or76PbpC1dSsi+TYGUlopVSLeSpH2cQu9vV4f6QNkF270qorRdjTjTONwGLm/e9dTiY3kueeaSTmRsuz0Rctdb8ozYzdtQNO+SIg/XdfhrDzFtqpgN/bcHfYM4yDWYuTmr2rSyc2oi08Shw0N2zKOIq47J+saO2z5wwAAIABJREFUCZvwhNDonZRX8RbAsXC9TppkNHNZEsF31DUzP1wECrqIKk/iu0TvMAYJQklVdt/P33/C8XiURGOatAulMI5in06KUXfWMPSDlt2SxFNyolrPkjLX85VVy17bNDINR0wZ7+XQEXOUxLAF78SpZxGVIdB5x37c4azHUPBGWp91EXz6m8cz13m9CZZKrVhN5hEKUuOyZpYsKkNUsFVANfSWUkQivOa38I9rKiwPF9mLv7en64TD77/mlbfOSyvgDdYEqMoqrElFEV5MNS2rdVZiQRwSLDsG+b6dd6RUuK4rpzny5iIQFWohdEH4/Ri+ePmav/87P+H7P37JV+eVX/nW+zS3zThA8hKzoto6ydPcXJQlC5OiNAGTVLDGU02l4DFWvq+a5UAWC7tRRaLFNkONE80IU2DNImaimdv6XLqDJnJ07xXSKn9WH4SC1PJMnAsv1+kb77934hBoyFOuNEtpjlLzrUdqelMba+QGV5LOJn+tVSb0tvP0vsP7oLFcAs+8Xmexrzo5HUuWkkwGU/bmGHQKHAGxm0oendhlt3ThFaP5g7J9mOdVsWdF4ZWNNS23zQI0jruBu+OeoRMbsQ8yVW9NmHjjOPLsvae3YQ86xbUYJR/LurSrgXlJtySjrKGc13kl5saSCi0X5mmmlFWiyg34rtcGSvbg1rw1I5XUqMEz+IBzhnHYY1rWXlrw1cVASyvXJUpcm84CWitQM8FZNatYLtPKw+nCZBPfOcDd2EHJmCJtkER9qcApV1KBV5dVDosms58XD2fWUtj1ksjcBdFLOO8lDMRU8R5YDTdNkVakyqBBzUJ6WnPhOqmyVAQNxNJ4My+sSTFiMXGdI9c545FN0loy1/nKZXrk7/z2j/n1333BeUm8fzzw7OlHNHckIzToWivGidNR9AFZV78ZFyodYv1NunlpzVCtIdakWy+I68LjlHDDnkNJhBagyjYoOCcx7tS3wacacS4yecu461liYrQW04yCViS1mCZzrHlNN2HYz3q9E4dAKYU3j1cV0ojibhMKbYDPplp1cY6JEKcgb0SikbLse/u+o1aBf8DXhDjBE5QHv5W4xhj8JOszGcA5+hCEy6cJR7VKmShw03a7CXIpxPR2ENOUSGtMY+g69nd3Gn8mXIShC+z3ewFFeEfNhWma5OCpWvF4IdW2LEIkFxzrmgS7nSLLuvDweOF6PlNy4aIsxZQr1lmckUFc1wltyDorIpwqHMc1KXHntoP3GOsJnWe322PCnrI84G1hCIGYJd4sWMu0JMl02AV2QI6RjRV4nuSAmKeJ03XioVW+s3d8dH+gpELNCbyl4XRl6vFW1oZxc+/Jpy5zkTmxNOhDuBnBRHGrEFoMrWSaER2+RzYwFGkBYs5c54XTNPN4nplWIQZdl8Try8wcBdlV1LsAjaWJWOur88zf/v6PePHmwj958ch1lQfCJ+/dcdgNNDfSfKE5+Vo2j8gG+fDGkmJhztDVyjB0BKfOvrKqL8QQ58I8L7x6OPHVeaXb33MXV2zfEaxurhqEvideM8Z4UQHmwqrBsmMf+OjZPfuxF/BoBawnxkjOOnTG4rxUzN/0ejcOgVqZlNIrKjg1pxiZFDcVgFi1l4KUY6VuycByg15nQZHB5qk3aqSQ3tL5oKJXdbAZlF3gbgKd/X5kWSJzlKHhxuinbbCOr6cAqbKvC9RSGDrZu+93I7v9SC2VcRw47vc6eFN5rj6RR10DDkNH33k9cMQ7YJ3DIcyD6/nC9XLhMkcu08SyCLj0uggkZNAo9yEEWUWpe25zExqj4yjr6XqLpQlafb+n73uOh71w9+PEfuwxRqblu6Hnvfs7mVo3sGvCd0EMMMuscebCWViWyHVemFfBof/ul1f+1CezimfMzWNQq3g+ShE0l7WOWL5mBLOWYb/n6fvPCV2nrYB+EwoRqU3BsCoTrxrBTq2UnEgxMk0r58vCl2+u/OTNLBShUllzEYSssVRjbr+3NZnTnE+Rry4vpOqp8jB6ehj51vsjpl5ZlwFzOFJZqUZYFjlnCcipBeMshSbD12QYUqT3RrHxjiUuxFh4fUl8/tMHPn/5wJQqT+dZdBHG3mZdtYlhrjTISVkWpeiAsBGCKAittRJP7kUxuCHHZHiog+f4jucOCNxCpqDWoJDRKqmrxeKQEAxr3S3Jp6ifvlTh+pXabvFW4rO2X3NTOUIA55riopTA4gx9cIQcsKps20IxWtXkWyNIK2O0qlTXXeflCdB1so4sRYZPQYlIwTuyraLZR26AYozmz3tKFnR0p6tM7xzzJE97b0XgVKoRBNjlwjxNRIHNqXjEMg4D4yCGp6ELOCPk2Qa3vAXr3G1Wchh2HKxYcPfjgO96idW2lpIjQ7ACVkEs28FLGR5L4/DkKX6NYvmepYd+OM2crxOX68RljlyXSMrSKr1eCuc5ibOvdbRcyalodsNCKdJLBycHowUw4iP58NMP+fjTj/BBt0CIGKxSsLZRWhFvA1seX6Pe0GbqzVgyb84rXz5MvDnPzFkqRwkhMZgmYR/OGWEKtEZT0lDNcuAYa+ic4bsf7nl6F8hlIS4nLlNg7KUlIBUxhukDKet7nnLkek002xh7mUWAGJ4eLys/fjnzhy9OpFXCaNO6yn2QEmuKmG6k6nxIPAGFZZmJSVscA3fHPb4bQKG3nZXPvvogB6jRSrY2fk438G4cAsBtGm+Q3X8RBaY+faXnyho3VnSfLd52+SHZFcIVbChcQx1vG6G41noz0QRnGEcx5fRdkAvCihquqlTWOcdut8OHIHLfKiAIEYcIpHLDb3lvKektaKNWMS85tchaC30vRFrBZveY1tTP4MgxaY8tZXDnHecZLpdJTv2uo7JCc5jdIAeQsxx2wjQ8TysPp4m+szo38QzDIDOIsPkAdL+PwbaKKRHvHaauDA6ck8n0YTcyDj05S3jLkgsFK6vONXG9XHl4uPBwnrjOE9MSiam+rZQQqIYEkjYktqveXJSCxq54K4PITYFegd048NEHzxXrvlKwajDa5hoNSlFvhBWpLu0mKVfRLqlUzrOsHnNteCPxdq0WmtVfv/k8NM/AWavtpyr0EL/I3RiotTGtCW8nzAOsY88wdDjtu3PJzFOm6tDTO2lRXp9WllLogqUPnmWNvHh95fPTyuMig1dnJCCmpoTDYJsRP0RrVGvJVVSFW7RdrZWhC3z4/BkHFcFJCO8iorXdka7bs7MLFpGDl/bHlA3/83/JDbquq/ZCTVNjRRnmblRZIfxsSUCbqm2TDW/x5W/LX6NVgL0x/oKzAgIZR2EFDL067MQZY6pc+NOagMZukIjo2jvJKlDjzi0QxDrN75MLs+s6Ee14J/HWVp6mDak0HEYMNbp/q3pYWWs4jhLxfV0iD6/f8Oq0sMaFfhxEe744UngLFjnud+z7jnmR8ncY5CneD6KH6IaBw35P5wzT9YLxXpiMpWB1feqdk8MpyEG0rVyFhCTx7edlJVU4nSSfcF2ESLymSM5FnXsyxHXOkXXItuG4apEbWBKVRRRGkz5/7By9txo9bhjGgWfv3Ytbc1v2toapFdtEZ2ArN83I9qTLrUirsbEZa2NaRWLugGyMbpCs7vD1ukPqkOANSUntxoljMpdCzIU3l8jgJh5PM6+6mcNu4slh4Hgc2XWemjPTMvNwSTijc6XaiLlwusz89HFmLlLiY+A8rZyWTFbgSzOGcp04Pzxyt9vLMLdK5sHNEVq5JQsb4P6454P3n8qw2Xe39GNrLb03BKdBLhVyUUbmN7zeiUNA2Gv6ODBSTm25fhpSrbFjcmFJvHa9peJu8WJWqULOinqw7z3BOcYhcH/c0fc93hn248DhsGcY+hssUyb6ogh0GO4H8XY37fm2GcT5LGX5lh23G+UGlvxAy64P7Meep3d7DvuR87QKR98g9lIdLMZcmNeKsY19L+upU0qCHlsTj9eFiiH0PcF3sorTVkSWCGKffpxmpuuMc4aPjneUBv24k8Tivhc9A43cxJ582O1orcpa1fmb6KI2wagtaeLxzUl8985L/FnKt9WjDFAtezcw1sDFyVM3J0dMwi0o3nEYRU4ssxQJRk1VQlaWtbBkiTnftPEidHEcDnv2u4Fu6KlphpRoxitGHd0WyVzl1ha2dtP9S0cs/yuQ2aYrSkPR68Jac8s7ADH65CbxdDUnmrEMu5HBWtYYeXOJmsVoaSScmxmD47gfeXYcoBbeXGfeXBNDF7gfPbY1pjlyXVZeX1ce10pzQtKOpbA2mVctSQ42kyYeT2c+/KjQeY8DbAVbGssaoRmccdKmGvj0g2d89+PnPDkeSFiG0dyYCd4u7LzMWLw1iMXmm/R+78ghYK1o5SXU4a0GQBRTQqStNAFhYsFI2EZVz7ZAP43630Xs0XWe/W6UG37Xc3cYGfoB34lRaeh7nPekGMUrUGTdZW1Quq+sWS7Twukq4Y8lZ67XidZkBTn0ojrbDUH62+AYewGWblSjrzv6koZm5C05FwkPTSWyzJHLdboFkNRa6PqOmgvXeNHqRrBlNLmss8uaTSASu+ADozOEztF1otAzDYxaklNc1V/hREzSmgZVNOK6sMwTRQ+iEMQXIPhyKZc3vv0ySyWQi2OvbVHpVKxSRZL7wf0omLQmKUhNbd0pVVJurDEzp8qS8+0J5pzj/v5OqETWyQ8kWATrKM1RTYJWwEjOwQY6kWrXikU3J6iVoFZwFRFgnceFINXJTfkIbIk+Oi/CeT7+5EPef/8Zr9+cmKcrj9ay2x8Yj/e0krjUhtkfOLy3F8dqv+CPldIqPzmfmF69ZJomTtPK45rJVQZ8S21isGpbiOrmTq1cpgtxjfR9lKoBaaMsDdNk9pCShIyM+x2uH2XjtdGi4TYAdAb2KqEvwJre8QQiZy33h90tSUem8uVmBybLaT72g9wM6ppqraoHYOMPyOpvHHoOu5Gj7uf7rmMYOimNu6DDQ8eyakpxFhJMLNIXp1x4/eYkkeXzypql16cWWs6EvmMcB+6Pe95/sufDZ3cssbDmRj8OuC5QrGdKkozELGu82gRcQmuUkqTSKZEUBXmNAR+cJNm0xvky83C6SDy1l+FPNZ5WG71r7I73VBOgrcSceFMb+92eJztZS63rygx0/SASWCcR7bVKr24R5sK0LOQkEFLvLYfDTuYKGjlea2F/t8d4D7WxBI+7ittvWTzzugKGIWW8d4zB863ndxyOUiVtROY1VnKKLFHSpecls8SqOHVppd7/4DnGeS6xMtdGrA2PuU3EnSnQCgmBf4g8ydxWxkU1GoIQl9VjMzIncs5pZJwcqK1UdYxW0IoEYzjuRr717W/x8aef8OG84JxkS/TjnuPTD7g8vmK5XiWF6dBDq/gkxquH05UX65mfPETO50VQ9LoNSlVCawzSlmTdUohV3EmCdoz0MYvZSvtayZqs5BJlRd4qn33+gvee3NP9yi/gnGeeF9ChdkyGZZ65dIFh2FOMpam9/We93olDIATPRx+8J7Zd61nWhWmaoIpDT7Lo0Cev4Ka2b1icY0VBDDKQ6fvA3fHI4XgQNx4yY+g6T68Qzev1yvU6sa6RZV3VBCPhnxvVqDToxpGDUxYejVwyu+NRMgl7aTPu9ntKuap7UAZCKYk0OUUFjRTh8HlrhG8XI80YFXVwK9EbsnOe5pnXDyfmeRGrb1EGoJUBXyqNdVkYR6N7aumZYymstWGK5RozdUncWamalnmRwFIrPbgzwhqYlkjQPAF5r8TPjhGmQT90uhOHut3oo7QTfecZo6zycsrsD3s677gfAyEsMstJIiPOpRFjJS6CCLsskcsisfDOCEvv7v4ozEbTiCmQayZXsfGahqLkpZsXlFe7xYqnDKVYWrHEBLMyHjZa0LJGLJI7SFMoKQ2jmyWQ7sg6hw2OmFb6scc7x7Js69AXzNOFZbqScuEnP5EK7nSZOF9mTpcr52lmmReZkVhdLSn2SwjEQQNbPfeHHR89f49nT+6wTbQxGLRaaTd02xYjtoWI/PTlG/rf/xGH/chhv+N8uWgk3hZXH7VVAt91N0Xoz3q9E4eA9577u4PIeJ1jn3tZwVVpDZY1kkthHAZ2+x3WWmKMlJzZ9YIDGzVZN6eoU/2R3TASOk+OOgV3jqSl7+V6FbVf0fDQlDVGq7Hb9dw/OeBswPiAKUkdXBXfBbq+E+y0k9nrNSNCn2BEdhqC5P2Ziu176fmQNeTQdTzmrGUpoNLfnDNJrcKXaWG5XoXTj7kpGuVJJeIniyGllU7XnGsULatzEi2eayOVxjxNVCCtUSfMAnVNOWu53Ki5aF6foxnDfr/HW4PVUn3oO1nJtUzWmLZx6GXzYgzD0BO8Z1kWDvtRw1Ijqa6szlB90FVuIaYqOow1cVmE6tOU9ziMMsdwPtBq5Zog2Uy1CPOvNVXnqWCsFloT4VZGIshiFnx4LIm1FHJrRAzOW4IBmnD7ShWp9HZrbGIlYwzd0BM60UuUIhbl6xR5uMxcTg9crlceTmemaWbV97XpbGWLeJeIPIkAa0j469AJyr3vRX/x5P6ejz98xgfPnnAYd5S48tmLM807rK0aIWeoudBKU8irHAIxZ378xZdc51WyCNeVdZXPRlaKVXUZVTmL7/hgEIQgM3TSj9fgETwXYAy7KtBM0dL3miaUbzdPq4UQOl01jfQh4HzHmjLWGZwKjVJM5DRBzfQqk60VzqczXXBYFzBG+n2vZayk7wbNf+cWVuqsrP5Syiyx0HmxpG5Jyl0/8sHzA904cnrzmiUlGTuXldD1xNy4LIuSgCPnszxNLpMYgLwRWEgXnEZMCWwiN+lte81QXNYV43aEfkdqjTkb8vlKUGZjrvDmzYnL5cqySr+/xlWerroG2w2B3Bp96LDOEFLCeMduNzAERy/OKWqF17MEoXadZ0tm7kK4RbflnNVgg0iuk8SN5VqZ18y8iKd/WlamNev7qxg3TWg+nU4y9M2NxVb2ndywxlSalbi4qs48qVCklxfgpijqolJ4K4bee947DthWeXVZWIqEsxbEiIOuo6FirCN0Ayk3Pv/iBV+9esPlugj5+TqL1Vu9LNbJE96APq0dvVWWozV0Xm743X7PECzvPzlyd3eg73ucWrDHQfIrztPENC3MKbIbD8I3wJBjEqblumrVKENQg8SlffHiK/GEqP+gtSblol6j4kZ/e9j9rNc7cQiISlBhiwgEojQkhCJI2bk/HOjHUZn+kcFAikL4XVbRn49d4HA8YK0jl0ZvZWOwZbbd7IfG3vb9xsK4G7hTYYxz4o5zVoJOUxViDTVztxs4XRdxx7EFoxau5zOt7zFDIK6VV68fGA8HmQHMK9Ppkd3dU2y349WLz3h4eOT16xO5Vpx3TPPC4+nK5TKRcmYYBg7HPXejxkipiKZXQrAzlmAFC56LlSCNXLkuK7mcsYjwymnc9bquzNPMMscbR6FZw9gJa+F4PLAbekInF+1hNzAOPbuhu1GSKo51lr6yYW5x8KUJQMSqzNtZSV5CXXElF8SDsQWFZtHsL4klidZeBz2Eob/BY1uzuP1BbMB6BTvdILVaaCmzsZNNraIdaEXXuDIL0LExYx/405884dndjl/77Z/w2WvRDmwaAxDfRmvyrw+nC7/+9/4R04Zwq28VrN47uq6Xp2zJVAS35qzkXMrKWdbRT4577o9Hnr7/AbvBMQTHsgrcZCMFiZEpaa7ARCpVwaEdVEN2mWwKa44saZXZh1bIcu80VRZKvFxrYKqsZK11glzPRZOwf/brnTkEHh5PPD5KOR6VktqFQDMRayo5LnTDwH63w4IM7JaJXERm663V5JxAw9B7cW2lFAWYUcV8lGshWKOTb+EN7MZRTln4mqgl6gnv1StQeXO6COzSuJufoSHGlWWdOF3UTNQaZl158eIrbJBe7rK+5nT+jHl6ZJ6FLryJmiQaLGGd5TjsORzveXroGILhfLoy7gaOdwdKFbR5jplYxX4tibqZeV6Yl6jfp6ELMsAspWmYSqRqPkDfBcax58lh4Mlhx/F4pO87gga7jEOg95Y+BGLKXFQKXGtlNw5icjKCJ8s5U5G17kEhpjkXbLLY2lHrKs7QJAEhS5TKaY7y70mtsf3Q8fz5M/q+v1GgQxdY60TOs9yARiVCRWZAGUPUO9c0OQg2hdltw2Qah97zned3fPf5Hb4V/tYPKn/w6iztQNtCViyYKgPnWrhcLgKbNeZmRmtNXJ+lChjVOIGROmfYDT33xwMfffAeT457AbiMA7vdSDeMXJeV0+lCzIXj8cDdYceyRqYl32ZEy7KQsp5GBVqqYkemEbMg3kByNDZJMToLA1l/bu2IKF2N+kS+toL/Ga934hAopfLiq9fqjOP2NHHOgxVc+N1h4f5uD0WeZssiO+tcpMej64QD4J3AQdV2nHXHba2l6/Vpb52IeFqTqXhT1DfiJ2ilkGOSG2bf0XcDOXdM88KyzjiT6L0TS21pDL2jes95jTLBtoZ5XsmhspwnxVutvDld8M4I8inK5iPXiusGutAx7p0COy27zpKTuvZ8IBc4X66s88qSC0vtISVMjZRauSyRNUn7Ii2JmHE2HHnnHT44Druew37H8bjnyd1eV5gdwxBw3uE1A/LpYcQCL9coTxFjcK3HOalKpiXe9BO2NZmUd567w17i46KBxant2WisuhCMpliYYiGK8ANjYBgGPnj+jN3hSGswDjLQXf1AKjPdJgDFkAW9Q6GJ465Ba+XmP2gNYhUwmbOWJ7ueJ7tA8IZf/vgZ3jp+7Xc/5598+SjuS2TQuF176PVXkLSoIUigaR/kgeC848ndUbQmWjl5Zzgcjjx/eodthdPpggue/fGJaPYyhG5l3I3sVMBlrOd0PfPqp1/y2ecvePV45pOPPubZ849wOXNjlFdUFq0Yc73GoOla297Wnl6xe+LPqDcNy897vROHQMqFVw9XHfzIydv5irWF4BN9J87AZV5ZFokbq1kkvJtSL6VKTvLG+ZC1R5RTMKu7a+vnUxWZsSTxCKbKOsfQS+99WhayegdcbdgmYaLXtXA6T3SmwWHPVYEUfrYM+0EIsbWyrgnjKuW6cr5cZeugHofgPa0U4iLrSazF16SpQRbTKq1mYu2EedD3TPPCw1niy0uWcnpeTzhTMJrSW41RF5kkGxltV5w1jLuew9BxN3bcP7nj7nhkGCSqHGBaRJeg1Da5iUoVWIvzdA5cVYiLE1nyzjjRTNQiJbCaobz3UAt5KRQgF/l9qYieYIlZY8CrrM4Ujz6Mg2DUUlb3qBTqtduxTo+MXyt3rXWy55cHJkIOkGGYeEh0By+jfsbdiDWOoivgT57d86/UhjOG3//yxEV7bWOEYLQ/7Dne3xG6Xib5rnJ32EuKlfd0w8j906cMw0CKKx75bK1zwjzA4fqedU24ecH3I2PfM7g7hmGgGs9XL1/y+tUDv/PDz/jsiy94eDxjneXD5x/K/MM1hZKi1YmE3rYq63OaUJa29ag1RnIaasMZyZesqtYEDY35htc7cQjUVlm1BeitV766TKv7znM47Kil8vrNg4IVdJijwZRd8Lja6IdA1pmBVYffdkqWkjSPzehQx+vFVukMohNYKsU5lhiZU8I7z6LSWGME7NhKZWmN+fWj4KpwXJfMZb2I8k2rlK9bj3Pe2ISNPgQxNumBh5VEmxjT7SIqrZIuC601lmVlXZYbr2CT0TaaZg8g2wcjsNPgHa3VW8Bp7z1j53iiiba7/Y79OLIbe3bDoPOURqtGcxSk3896wzXr8NZy6Aau84wxTTcGsq5d1pXgrPx8rTyezoydx1urQp56w6qV0si1shTd4euAy6tI6KBW62agFqEcF2fZN899S8iGvQhyYasANomyrjTlB6guGOMs/Thqvy9PT2vh/fsdf+GXntN5+O2fnrguCazl+YfP+e4vfodPvv0t7u7uCBQVahnGcYc1MMfEeDhKItX1QsuJ4IMY33QwF0InsmlrMdYzBovfdcyx8Xs//EN+8/u/zU+++JLT5UItIhoa3SgzjiZsgGYquIrxqCei6ebBqv1dKqzgrbpaxSGbq6iorLIe7Dan+YbXO3EIgBBih6HjsBNNv1PFYMmZ08Mj0yIDwLGXDIIYhVozDLJSGnrFMrV6CyvJOWt/JAIj5xzeyU0iNkuRrUaMIqkyrRnJtitFqgRrcUZ2x11wGDrmtfDy5Utag9CPikaTVsar6EP6t7cOSb0jmNIsugHQG1emwN57coFFFYHNVIxxlDVp2W2kUgmdDqpEXSkDLXkC9p1iz5r8/DjIqnXsJbxkVMjq9XoVfLdOj4N34sv3HhXlklOmITty6zrJZ7CqIaiVITi8Vda9FZ973/XkKGvOvhugG6jLCZCLs1Uh/FpdxTkjfbixjid3BwHCdv5m3/YWlpw5F8v7RVyfpklE2Havb2YikY7LylIefjr0ayJCasaykX23B8mh7/jeh08pufGDFyeicRzv7/j2d77FJx9/DDTJa9TNUsoJHyTp+O7pM3a946u4Mq+zZFdYD04Q6d1hz7ysmG5PsTuWdOH6+oHf+r3P+K3f/gE//fJLeS/kziWo01OEU+KQbLViaqMoA6KqnkEG2pJ2bExV5Bh60EoiM0ZzKr3c/ObntATvxCHgrOXpceRw2As3AFG7lVJYY2RZIrGUW58jfZk86cZhpB/kYKilYJtl6Ie3OQVNpsCSwiN5Aa2iNmVlETQJ4ey8u8U+bRy/lCI1F4FxALE0ltg4TRL6YEthHDriKq65rgsUJ/LlXKpKgNuN5LvJRK2T3ERjZYZhrCXFKAx+5+k7S+8q3XHAMBCC5YNnT8FYHs5Xhr4X737K0s87zzgODH1PSjLUDApc3e3USNR3vHz16qYazCVLiIh3UrFUNJhVDrOmlm7R4WckIlIPnlrxRtyIJcsmQGf31CYW3eodhbeOQmEq2NsPa8QtGjpPGHfy2baCN4Y6QOKvAAAgAElEQVTUZGhrc2ZtHVNZ6arB69ysGUczW0WoUBZjwMh7WpoGr4DGeklGQy0bpl4kw8Fa7vrAvnMYP3C8O2rUnATY5CqHlFNfSm2FeS2cThOXMpMWUeqlLOtJawp9cHShpxnHcj1T24nT44nf/Mc/4Ae//4dc5wWDfO3b9ZBLxdqm9CCZ7FMtrSbWaSWq1Vjs8dzagI0bIRWvGquMtDZy2Mk9ltM7zhNw1nJ32NEP3S0WPClmPGkPbLVfwwqZZxykXzPqmTYYiRhzjhiTnJg6EfVemH4SSFJUwCG71OC9WlAFDV4QL/08L0yLRKS3UlhTumXalQrvP71nv9+zV4nvy1dvWEvDWU9zBlulpM1VboAKGB/EFmvMTZu/9cRC1tVtxeGO/eDZ7XplKP7f1L3Jr6Vpnt/1ecZ3OMO9N6aca+rq2XhCwMJ/BGIHC1hgYRYghMQKr5As78CIFZIRGyQQQoIFQpYQLJGY7G7b3e7qoSqzsjIyMiNjuMM55x2ekcXvOSfLqCppaGSlj1SqyIi498YZ3uf9Dd/v5yvDus7L2zVsRpnch0QIq3y/rmOz21JSgmwp2mPtgEqT4NiVGISsMlztNuQYKU4IxilLJJYx0HsrybylUJK0NbUqlPakEkhJMhjPxqvcrLcKmE9HueNXmJcFqz1Vm+b0oxGhxEHZWYnkKlEqN+9lmCvxZQq0xehOTE1Fcx8rVyaBh6wM5VzhZQW12YLP/2uRZbnKYRXXgKkdFGlRcm4zg5bWPMdEKLC7uuK7H7zD4C2n04mKpP3kUvG25VamhFWJOt9xXAUl55xE2+VlRiGzhjlESndNmN/w/NOP+YM/+SmffPZFi5eXbqW0QaZq74/s9Ut7jQxa5cvcIxVILYBWDu3Q3KcyF6ht1VpyaU5aGXhaY/7p0AloLeWwsO1aDHa7cIx17Lq+IacNWklf5G2DhpRMKVqm68OA0prT4cg5DrxWkQEfj7XRg89PuTn/rLCfShbrqHU9umpiOEh4p/HklHFD39JdRW5KLVjnUChO8yw8+1RYkuTZxVIgC/9eMgW75o0wrT1RF7KRKnLHvd5vub7ec3V1xX6/ox9EVGKNFqVYbZ56VCsHJcduXQPOy79FKxkmxlhJYcapikK3KqnQOYPRVu78VcmnSxmUyqQoSUreC6FmWducIiV0swqnVFGNl78kCdo4i3xysxJLsnHG91uqG8jzfYN4NFKukdLeaGmFxs3Idre9UH5SLFhnsF3P8XjEaE0wPbFM2KIaIEPWvaKEU62vPm/9VRP/iB39LNulluY3UORm451j4hCEffjRk0d03UDKFeM04zhKSa5t07BIWziYAWc0pTiWmOn6QazbRgvDUksWZooLL796xT/40Y95/uVrQmvrlOaihr0wEBoMRkCiipzjhZykmvHpLO7KbWqqZbjUDhJB5EllJO2EUerSSqaUf+n19604BOSFEZKLbXt+oF30IkJRVu64NUekPBW2QEsh4BDbUAYIqyC25zagE4SYbX136yFbAnGtublJNd731GZLvn50w9D3TfMudytU5XSamKeJmBR9P4pmfFqoTZpakohWpGPPIr9FoCPGmnYIyYWglWHXO8gBjOE7H33A9dVO3I+bjdxdWpZiLYXQzFLO2XaxZdawcla6KER8FNaAUmC1rPOsa5wFpM2x1mF81+7qBWs0sSRRv2lFiDIMs9ZcSEo5J7ngOy+lcmlWGK0lGDQHeit39Ko0h+NEaBkSXcioZgE2bX/trby3pVb6YWC7HYWKrGXIaHQlrAe0Bqsd0QxMYcYVhS2QalNzYsgUMuUs+5OLQEn7UZDwkkSlKFBNe5+qYknwsETeToHqPB9+8IzdfisXei96hZArKQQMCGchVaz1lKLRKmN1pcRAVqU5WQ2pStz9Zz/7MX/3d36PT55/eamCqDKszA1Yq7QSFFjOZG0us010ew717JmQzyntNbtUEG3oeqYMK9rcXMsAubSq45vWhN+iQ0Cm0puhJ3kBRZwNHppCTavgnGubuGeJ9075a/LqGS6aW3tgrUxFe+/QpmJ+bg3kvCDFqaLt1tZe8GHD4LHWUFNC5YJuO24JAG2xUVnCRkoudA0eOoVAVAVjaJFQQuHViM/AKaH5mG4LWog/296irWe33/P+e+8wdudgSVnvKSdeALTGay2rKG2wjSpbShKLr9asq8S4xZi5udljFAxdT1WWw8M9htgCOjXKFkrJovo7w1mMpWpDrbkNUqGWJHz/C9otXSAq3rumsJRDI5VKjVEUh53heFrEONOYnLGc/Q2SnUA7FNTP/Ru0UXgjG5MY2xxCKVZtOFZHn1Mj8AphvxT5ualCqOI6XGJqceYKbx3dMJKUIbUeupbG3YuRhyVxDIXdkz3vv/us7d2hd5ZUKmEVaq8yoiFxSqFyICXh+FklP8dQCWdHIoYvXr7id37vD/nk+Rfyuv3chVuTrO+aOFJguFpfIDml3XgumVtVFLVwpmOpNl+hTUe5VBVnFPl5lVrbQFbrfwq2A7XWC0a7HeiXYY8M72S3/POIsXO+PYi2/HCapBy2Vu64bSaQS0ZnTTYGlbMMT4Ksn844sNpUh2ftgRBx8mUdV5uwKMUo9GKtODzc0XUdVRvmVfQLuWUlqHM1YzVjJ+amc1WyHQZx4llxwj16/ITHj68kKQkpI1NeGTabFoIhIhGjjUhiayaGSiwV1QQuisrxeJTUX+fofU/NDeYRZ6bphFFCHSolQ5wb2Ui+VhKOBPle4kSJQXpiJXddTSGFKOpAbXBW8hpqPmf6VdluhFV6aKcZR88yjaSTrHZzlUKVJmiJJQsHwXcyfGtwzZjFsVma2MU7S0yFN7GyVRISe/5cCD+gEItYiQVaqihF5hWqCgehAiHJIRAKnELiuARu58ha4aMnT/DDVtSnVjOvQdazMbMZNxQca1KoKis5Uwtai3NR169diM5o7h7u+fu/9yN+8umLi6knt2GzQib1Gn0ha5/f4zOP0liLosXZKUVCKobalJq06vcMvK1tGHtePcvFI9+nXUjfeO19Kw6BUirTaYLWI9um4fe9h9pWfbXJOmmTaypd4wuKY+rrJ3o+ULRqhqSqRP8PaOXJWgJFNGLtTLlRaqjUkjCmgSq0DORqlYw5Zw20yPLed+QiOvO7+wfpdnWrPhoJiKnS9z1X+ysOhxPWGa73G7SCsVds+pHtdsvNo2uUstzfHei9wRJZ5pW4TpSiKHaLUVn+XWhqFgKx7Tzj2JNS5HA4kWKSuYc1xCjcOtQZpuHprbRFKQb5PSVxWzkJwy43BJa0MyLmqRW6Ttar3kigRWq4MEGIZ0JYpAQ1FuvEHBXTilaKoC0Vg6vxax9CroRU2pRfc/P4Rla/AMYxhUKdF3GSOkttvoOK55ATQ5H3SYaucpDmBgvN7RBQrTS+XHhKWoAYM8samZbE7Zy4XyLjbseH7z9DtYxC7zqc8xjTMbbP1LJGur4ThLs2+HEgxwgqN+m6VK/zMvP3/sEf8vt/9GMOp0UO0jPRSAnsJsXUthbSNAo9mXbgeayy2EZSMq1FoA0c5UNsWh10ni0plKotxERmA7KNCpJ3wD9+ffzfH3+aVOKPgP8CeAepSf52rfU/UUr9B8C/Abxqf/Wv11r/Tvuafx/4q8hg89+ptf6P3/Qz2v0BrXQr3fUF4FlKoXeC+sq5MNCJd72l564qorKQXksul9NQa9NSesXQoVVlGAb6hg0TTbhuFlXVDggZJX1w4zjNK29X2TbEmJnmFWMQz0FpEVtZ5Kr73UAplXkNqJRxXc80LbL+04ZahYp0fbVjs9lQ04r3lmGzo+tkwxFC4eHhADvP4BTrNIljTRn2N5UpRmzX4cct0zxRcsbWFqga4yUazRnNdrsV7UCKVKXY73a4Fuvd3h+5M6eIPt9xciWuK1ZlUbWVQsiibagpSihMPpOaTZs2S9Tbsqo2pC1U3XL0qiKkwhwlT8GmAEibUWqb6Fc5oMbtDmWclP9OCMQxy8dXG90uJE12jlMSRLlqEea1ocSrxBvJnv28GlPq8ne8MeSqmRbFFDIPIXK/RE6x8NF3nvHeO08wyKFtrJMh7rihlsLh/i0hLJQSUH1HZ8AZS2cdDymwRlkjrinyox9/yu/+wY+Zl9jyJqt4YGq97Pq1VhcHJnyt5rvkF6qK1hWdCqZkaoqkIPZv8UO0DkGJe/Ai624Vfy3/+NbLWsM3nAF/qkogAf9erfV3lFI74O8ppf6n9mf/ca31P/z5v6yU+i3gXwZ+G3gf+J+VUr9Wa/2l40kFTQhjxatvztWABFRoLcqo2NKDldaUSUQ3Wmtsha6Xvth7R9d5um5oWXZaEmSNGGKUblHjReF0BG0a+VZ+hjWetVqyBm+10GCdoVTf9tgVdLPJpoI2nr5XF0lsrVk8BssKtUrUdlygCvixlIouic46FJmUYJ4qKVWuHl1RUJzChPI9vhpiyty+fc1mu2E/7nC95u0xCJvAmSbWEcmtqqVpxxU5J5wTGMbx7pbeGaoRw1JVuvWNst7yrooOAElWDrlitKNW4TCsWcw55310Xpef+1DVJsGWecXGS8VRlUMXka2G6QFXNRXd7trCPMylop2+vPfO98zzSYaV7pwpKK3D3OYdNUeurWJ08smJJV/WlKlUUE1bVxs5qc0BjFbU0izNqXIMiYc1suTCZrvFOs9ZnJZLpRCJxxMpxsbpS4jx2cucqkiqT28NtXjWEPjs+Qv+4R/8CbcPR7lTNw3AEoLc0X+uXFfnHSHqAgEVWnZLHVJVhta5opF2SAxrldx+LQgyWZGLqUjeEd0sxXIWC4DmG4jjf6pU4i+AL9qvD0qpHwEffMOX/IvAf11rXYFPlFI/Bv554H/9ZV+glFBmh6EXZoCzTenUJL9tINiW+aILqCJWwVqsV9zsRrp+A0qCP23XQ04sy0RMkcF0gHiwtfWUCjFXBm/IWbYSqs0e7pdKzZqaC2sSF+IaBdRZ2pR+WQPTLCkvIa4cTquUrK0sEyWeDB5zld42xhljq1CB291GGcMSEkPXSaaeMriuI2uEqhwKzndseo+tkXJaebwfZLpcJE59XQMo6K0lJUFTg8J3wuorDR2etcI40zTvgrROubAfFVTLEq3MHOzIarak5SXWO6wzDWmmJex0XtsMIKO0YbMZCCFICa20DPO0XHD90GHGAdJM1YocEkXpZgI+Z0SoNnNZGh+i0NtBUou0Ia5Ceeq8Zz5N3K+Z3llykew/UJfVn9FWvneVC6CWQs0Jb3tMllzF2Hv2mw1Xc+TlSTYp3uiLyMhRSSmyTLN8PtsQOacs0E9tiKliTQdxoTNycP/hH/+YV2/vzqOoFodnLmu9c9LV2dmnzludpkg1zQlbUMSSyLpQ2iwgNd+LQsmx2NodqUzls3AeCJrmMjxrLspZRPRLHv+vZgJKqe8Bfwn434G/AvzbSql/Dfi7SLVwixwQ/9vPfdlzfsGhoZT6a8BfAyQIw4nOP+dMqIUY1QWEWZv0M6VIDEnu8MZQ+p5N4+oPnafrdszTg0y0c2jxVoqqHUVbATwCKayklHBWkVOUoUuRiO0QBbWVgpTSWilKC6IoSVDjOWXWJXD3cBRwR5Nq6iZJtk4UeL137DY9m3GQHAOrJTbdOdHpG2kX+n7Au555PmBdbZqFAlrT9zIsmtfIukY6Z3nUDxilCSkLKSkmHIqkFGuIpBCgeQm8s2hnyDFcpsopyppVJv6RZVFY67HtokppRZVK7xVW2xY6mi8pP85ZaTXgAmwxSrHb7VAlMYcF67VYwNOKpeKGEdtnivNUL4i3lAvHczRZW+sNQ0+KgVpl3hMadJVSiLWwYrlbZh4NYotWxkILftFnNaI2Um2UIvmFJaOqBJJe9/JvrUozp8yr48q6zNBWjs53DE6jg8jFJahUiFBnWo9qQ75SBZSiKHz6/CWfvviKGCNn6O15xX0e2nXOtguzXQSVprSU9a5SX6de1yp81VATIUfqeRzQJOe6qRirtqgqFcz5+6YWSy7bNFo78v8DaFQptQX+W+DfrbU+KKX+U+BvyFPhbwD/EfCv/2m/X631bwN/G+Dx9VVdF5HnOqPbtFM86mPfYzTMpwPGWMZNL5JPVRm3jmEYqE1kVIqw92OSqGxrHc4NaD+04MqMNxo/9qxruIhejLUY34nm29uWCmMEdWUUYRFeXCiLiDhyRlexcXo3tHRj0yqWhNWWomDsPLvdyNV+LwQgKr2TrAPbd3K3qoXOWUzN4p70XlRlRZOCDKpaRSt+By1bkVq5gE36rkNr1VaSIokuRaCe3hq0NZjOE1NFq3LRCxTkQzhHBQ02IivqSAkB33k2w4aH0xFKIbQV3tYPLKti4zqMsbIqxWCHR0zHO4yXMnxdAmlZ6HKiH2VNZ8eMG0Y6Lyixz98+EMJKrYlpWtjuthjXXKPrwjIvbIehbWks1m1YQmINmaHzWCM3CvlM0JbicgHl1r5EZXgIsO002np0Tjhb2XSe3dhzPMy8uT/yyDi6TuY7x1nYlUobAa5YyxoSp0XYDH7oUWXBWcPbu4k/+vg50yLBINY6VJMvr8vSBpQGtAMlytB6lo9rD1UqzPM8QNq0DlMNq1ouK03alsp5L2vRUmTt2+TvZ1BOaW0DtFlNbYEKf5ZDQCnl2gHwX9Za/7t2Eb/8uT//z4D/of3n58BHP/flH7bf+4Yf0HzcpUjYorUYZ+m6nmEYUSVAsSgjCb21afStBnJkjUVSa60VEw9SJhnnxGpcI9ZUBu9AGYyz0gPW0gQ8XvQGWpNDIQU52UqzyeaomaYJVRK9sxQrsd7G2WZm0W3QI2o2CZkQp9c4iNvu0e4R63Sgd/prs4hSnE4zOawiAbXiIAxrgJYTUCuX3s94cVemXNBKt3VqaWvRTtaXWpOS9JcKWZ1O0wJKqhClRK137peXdvfXSmAjqtKcj5GZyhrfADI7UFpELUPXi3pOa5b5RFgi2nUt5Xem8+BU5f7hSFhXdtqB3VO0JedE8D1p00OwpIfA7d2Bd5eVXAuHoyDdrQJvKsYbYgzMITEMG6pSJONIF/v11wIh3Z6z0QqjQFXoe8/45AlHXUE5tFdUAjZVOu/ZDh0PaBKah8OJGIKkPRWpCpyVbMdcFVkbtJF1Zqow+J7eOG6PX/Hi1W0r8/WlRaHpT3JcsdpdovLqWb2nlBzKiiYu0zgjs53cJNu6KFTLdT8bhUpO8v63rZhoAqTcN1qw6xLEqzinen+TcPhPsx1QwH8O/KjW+rd+7vffa/MCgH8J+P326/8e+K+UUn8LGQz+KvB/fOPPQMlJbmVSba3DKkjLzLFknNXCom93TqNNG8SJtDIVxdB39N5KNBUWaxwhCI6ps5a+93ijOU4LOSY636GMZxhHNpsNb968Ji6T7NYbwzBmIevGKJuHVGrbOAzUHBnHRKkSRSZAEsmYr0qUZUZD31mUMlhVyKbFQWUJL1VK4TtHjDJDGIzgoDovYqacM3FZm1hIIrr6XlKKzhsOKCKdTkpSetodxTmDMyIXzavozr0Tl+W8yJ2n86LOtFa2J95qQiyEoglZtgPe076uMh3PRGXDdJwJ64Kxls6K0aUsb9BElNmwVEdSDyQyi1JYZVqYiSZbTTKVZDuytsSQ0DmRYmJaF8luGC3b0fHq9Sqe+BSIQXQOptswr7cMuSVVVaANkCUgRGR38vp27J88Ic4rb3PFaQPWEn0Bn+mcI02B+4cjsfOUPKBDZOgHLEiyTw5gPAWF7zydN1xvBpTS3B+PvPjySw7HY9OzVGqpWGegJAxiyqi1UOIqlZqVtiXFRDVNClwbLn53jbeOqorMT0oRdakxLc06yXuvlcBm4nrBxyst8JN2vjTzkOgpbCNc/X86BJDe/18Ffk8p9ffb7/114F9RSv3F9qN+CvybALXWf6SU+m+AP0A2C//WN20GgDaky/jBU2ul080ObnQr2dv0tPXuqQiCTAHWdnglq5h5niXF1hjcZscahPTjjGQHih3Xs4Ym2UyRaCqvjw8cjkfOQaQpBozSxArHh4N4FbzDeU3Xjxjr6fs9RppkUmqW46baiwXGvuXsnQ82U3CbnuMs/XpFt2hzURNa55F0WYXKgquyCh6oYu6xRjwEbfDnjMEayVSQSO5KoNB3Xmi9OZGxhDBjvW44LC3biiLTdmUM47jFGksIk7QbcQXElxBChNrJDGSNxCLZPrm1DiFGTMxsrrcSoErFeg/K0vmOdz/4kGU6Md/fU3QLYFOG0hgARStKS/uJRVG1RxkhS4+ba3bbji++OrJE2QqNzmBdxzIfuZtXOqew1YnmQyX55Dd/hm7CmpQL94dAzQWtLV3RaOVJpie5QrKeJc7c3R+4+uBdunGglBYCO890/QZnNf3YcYaa1mqZlkqME1+8/IKPP/lZQ8hrtK6XLAtnnVgzaKh4Zb6+exeRudci8BWjDd/74Pv86g9+jc577k+3MuBV0oLJIWfIVRBjAtvN8HNlvz5PBqHlKkpFkkv9s7kIa63/C7+4ofg73/A1fxP4m/9P3/v8OBN+c5SIrkpzgAGmnvkQwmufT0dCLhjTMGFKMNlrFnag1bJyySmwGTwgXnpBNavG9o8oKvMUWNdAPsMplWaJmeNxofeWvusBheu9EHW0ubjtrDONLS/TWOddc7VVeqPxRmNsR8xJ0o4aGBRjCfPMNAtj0GhF10moR86JjJhQrJmJtPe0vbFrSM0GnBk7qWyaqVwcZ1k4CM6d24iOcbwSz0GcKCnRbTbstj1V34oj8lx6VjC1yVFrvbgJbSf9eUwzftxDCmgKw9iTkuN0kqRcYxVrythuw+AqSi0EPaBcBX2icH6voFRJD4opy87fGEnaRZR4T5894Tvf+4gSE657zXR3ZBwHERiFgEaxVs0aMno4J0aJtVhpfZkLyHxEkG1gmU4r3nqK0kTliSoRcIQsRrTOSVEun0mI68rptPDk0Z6b4YqCZ45yVw0xMGXLP/rkK754dQvI4WhagE6MiVrFzVpy/hrM2piKpiHUQeYWvR/487/9z/Drv/qbKK14/uIzUs7M06kpVKVdlij0eDHUlcZeOM+MahVjVkxfDwK11t+oGvxWKAZF0aXa7lPAFuf+tiJvbChBdtWl0vcDpvnvS0ns9zsZiih502NMchJ3Hu/9RY2llGJdAmENlCxrvlortvMiJ10DIWbGcURr1b6vYY2yl3feUUKms5USVubTRMzSDhh7JaXi6JrfAWrbC8tbLTNg7xwlyjBHK+nNtTL4sUdRCOuK0pppiRdktGoaBqEPyayk5khImSWLdLhmgXmGdUXrE9Z3+FLpug2KhKqJWuVOr40TnoGG3gjh+RQzS8qkVERKrK2kgNWC07DpPcV4NAVvM0orxr5HZSU8gSr5BYEZnRsc0wAIMZq275c0INmhH6cZ7zQ3+1FSnsOMM5rOe3zXc1zvGceB3XYjmpFaMBRc1xFny5oKvghbr6IpJYltOcs2IWXZpQ/DgLMQ1kDKFd+JNiJYMTs579htNzjv6bueFBfIoo8Ye83YGabpSNWejKJk4Qoc5sTHz19ympfLXj7n3KA2qh1CckdOLdHa6JaXWOsF6lJL5cP3P+I3fu23eO/dD0CL1D3nyDxP6NsD1ohuJsQoN6PcQm2VzEDOs4Ez+VnmTm08qNSFW/CLHt+OQ0CLXZa2tzaqYL2/qAZpcWMlF3wvllxZc8mpZ4ySrL0kJ+7YOXIV7/jSLvhaCjELI9BZK/mAJWOMl4GSk0CT3aan6wdJ+YkrpLaP9Z7OKKpKWCXmmONxQinIVjLiaGsb70TkdB6oSXqMlGRGKTbbLbkqpsMDToMyBqMK3mpiVJiqmGcpL7v2GiyLiGW2uy25irFFDhmxVWvv6VzDpRth4IewEkKk32ylnDRypz8e71lTxnmHVbVtHxQoR9WyVozr0i4tGdIVo1nWB4lWN3JQ3x1mEXp5Q0yg/IhxHSGu4vZMD2w2W/qrDff3MxRFraLFmJaFw+HIkyeP2F3fMM8LayzYonj16q0Ewqwr02mic/KamlaNKRTZOmJdUW0Wo3QlE1E5Y2rFK81gzQV1bq3DOMuyZGznUW2QrJRhMw48eXwju3yrMdrRe0/qIjFXllgJJWJ1xltDVZkYEj/5ox/z1cvPLxr+sz4gZVFGKvU17tu2UBhZZOTLCvAsFf7h937Ih+++x/XuSgRBT9+hxMB0OnD79pZhGITclAMhRCSOTA7UWrmkX4lNUV3mBlIllMs24hc9vhWHgG6gEKUNusmeSi7EmoCCNUbWLu0UXeZZvAVd18QlFdtIuSWL591YUZA9HI5MxyMoGtNdNQzXSFUSe740k0fXb9G0N81bprBSc2W72TTkWaEaQZHNLUVntxmwWhGWldR6/LPV1zrLZrMRUU4Sea+3hnVZOT48kFNAOUevJKV4WUPbMSOzi8ZdrMi+WisLRRFK4hSlJx87h3YdvTMYK8EsZ3OVMaYBKqUflBQmC0nulutaiEGx2dywysgOnMM6RVoXSVhKSeAj7bA1Wig1pzURYmWz26NNIYYZv9uIccVYqpZhrveeeZkpNWFwUETOPM8LpVa2201zg9K2P5Km89lnL9BasdsMdHpgGLzYlM8x55MjhRW0CG1KTGjAULFGCY/AakpOQqE2AoOJMZCTF2WlsqDMBZDqjIYkw96r7Qa92/GwGJbTLbtxFE9IXElh5sWLl/z4Jx9fXqdazqzDs5OvBYG0/48xXu7KIuApqKoYO89H777Pb//6b/Lo+oqh8y085DEhRB4eHnj9+jW74Q3juGENKwERqWknSLXYtg2lWcFLc9Zm5L+10pR/GqzE2vqGdRLayzLLZN93nr4b5CJOmXUVY8owDGzGUWypl+AQkVeGdWU+TkzTidv7AyElhr5ns9kwbrY4Z9BacXO9Zz5NzDmijEXpxrsfhws8UmtN33npF3Nm8LKZGBY/ipsAACAASURBVL0h9pZaMhiP0+IpyLkIVaaKs+twmATSUWTDcJcia8NLee/Z7ndCSOJ8mlusc+QUQYurru8Nj+wW2nxk03VYq1hPE847tPWEWDFpFpGQ9+R1beQaWSk5I/i1hzW2MJWM85L1GIs44vI6oYDj1FDiRlR4IRVxCC4rx9NEQeN8J7MM23N7uIe0YONrUso8eXQld6FkyV6xRkgRjBOxzRJWjtOJzdjzg+9+hLGG+/sj8yKDR+86iImqDNns8BZyjYRVaFM3+x1z50lRk5VG17NzU3pnaw2dk/dujZHTdIISG1Uok2LCNg2I85YyJ2oKjLtRWqR+5IOnV8yrrKztRmLsbxfFTz55xcvP/piPf/Y5X725J8Yk3v3S8gDUGRZSLuvKenb4Xdb1is55ntxc8Rd+81f4y3/uz/Hnf+s32W63WCvJ2LXb8OjqKXeP73n25DVvbu94e38vB2pJHKdTU6bWZhiTjQ/NFZqykKHFGm2bsegXP74Vh0CtQhAqRZiCJUm2m3VWdAJadsWlWXHHvufpk8d87/s/wDrH4Xjk/u4tx8OBbrxiu9lzerjn4TSBUkLr2e/phw2hDhzvXzJ0ls3NjpIsuyzeAqUS49UNbtzw9uWXhHXFak3qPCmrFioJhsKT/cC297x9mFja4SSwSUVqQ5oYYzOLiOrcOY/SBeOcDDHtWRgl3oV+3OB9T8kR0FzfPOZ4emBdT1Ku19zmJYkSIt53KG0Bg7YDy3IUJl75OqVZW/HFW6tZQxKfepG1YqedcBfjkV7BXL92ZGoKznV024G+79Fux+tXL1mnI7fTSlGGNayYELl/eGDT9P8xRl69eQPaoO2JfRRxTwuXBzQxy3q396KZ6PoerRRXoZPko82GZV2odsNsb1jefiq6DOMw1ZCVZbfbMcVVsOxNbUdTC1ptcVozGMNDTLy9vWf/4TuMzjKdRJqcnRdIirdU4ZDJsHeN7LcDY78RV0R5RdWGz7564Pd/9Af86I8/5v7uLSEmMV6Vgq4t6aoN6FKVPX6DSctcR8kcwRvH45srfuU77/PrP/wVfvj973K12XNz/Yhh2IAyTYMh8NGr7Y7Hj57x3ntHDtPMcZpIYcXZVdaHzY+CEnetQloA56W9jiljWqjKL3t8Kw6BUgrH03TJFjwnqJx10THKEEUb6a03vcPUyP3dW3b7Kxm+IG3CaVrRrmO/37O/vqHvOjbbUQJBpiMPxzfkHNhtHvPo8TPu1C1lDSgjO+Xeyh2xxpUQVrRzPDwceJ0KY2fYdBZyYusUj3YDaMXdYSXXjNeKwVu0tlQzsGbIqmUjaEPfd5RaRWdvDDFICxFjkuzBnaf3juk4kVLgeLq9rARFg6Db91fkaGUVWCulZkqaRY3mLKpkTiHjfc8wbkhpEQehNlC1tDVFykSNQDhU4zB4IzShus6ibVey+fBOvBCHlMgxCL2puTydtVhneXP7AFrWdtZqwnLg8PCAVprNuMMNGmXFKZdyYlrg5es39H2LPfMS3dUPPaOtLHElzS+xnbAhnBJ7dwGMH8G4ZiXWzW+fqdoI8ttbtkPH4WHi+PCAdx/KnZkqWpCmMPTOyfNA4bo983rH/WHixasHIp6Xr17x4599ycefv+aLzz4htHXl+S5fivT+l728hprEyCQXaGlIOcWwHfnu++/zl/78X+CH3/++KD2NRpsR73uUsdLn19o2HVIt7nfXPLl5xttH93zx1Svevn0r2poK5xWhPQ8Lm+1Y3IZig19jwv5ypsi34xCIKfHm7R00fbVvCjlqRhWZtOrSgkWsRVGYDkceTgu77Vtym/RvRs8aEjEtkDzPHu2JaeB4OLYIKNhsOnbjnnEzyrQ8J3SDSaZcuL+7ay2FaAy0kSlxKoVqBqaicEXgp0kbqnNsrzvIkRJFNtpZhTISsnrKIl7pvL3EUee+ay7EQElF+uyUOR0P6LRcRD3H40HmA33fmIJJlGNFYZ1g2dewkhUYJeCPWmRI+nCcOawHstIMXkrkvlf0KKEaZzGixCjYsFwq6zLRtZVgyQWnO25uHrHGwBcvn3N/f2opzjJsctYjgcyeYei5fzhweJh459lT+r4jhHNSLlTl2O1vZGV2CUaBsCykGDncP7AZRqYlolRhN/RsdzuuBkUulpg1aT3idcY6z/Ek9F28pSjpe6prmYEp45zjajdwDInjwwPrunK12+C9ZYkVXwQZ1/UDyjjuToXv2h1jv6KJfPHyJT998SW/83t/xE9fvCTGJB9J6mX6nnNuq2PZ8tQ22Naqpf4ohTcWYw1X25Ff/d53+Wf/4j/Hb//WX2YYNszziTVEOje0LUGhNLKTZEaKH2AYNmzHHX03oJHqyRojg+2m4pTtV7ugGk/jnFfYe/dn4wn8k3jkXFiWhaHFN/s2WLvZb0Qd2DTtpRbGccR7WRdZa4khUNXXbjSjIClwRmFrYpkXTscJZSzvPHkkw68UefvmDff3BwmS7Ly0FNMsg8dlbfhwjxs3dFqjVWUcNxynmTmsRO2wUbHdDZgiCbnHUpljJKvKOk2ydbDSalhtLyU6bVAIAkxJzeqqkbtaUhZjKrZKb5mzMAtzTFRdwTrhLAwdaEVNSVZCGJaYWGJufMDKOh0p0aKGrmHZ46Vi0MiEWVL9xP2YUsEay+7REzDShr169Zr7u3vWkLDOUqHtvYXboCicpgmtNUPfC0UpJbwx2EFhjbQsKYsNloIM+Iym7wYKiofDA/vNtYSm5pV1WcF5Weu1+YBRlZw1tlSOpxO6gtIW4c3kVrnIMMy0cNDdGHl9nPj85VsJY/GO4zKT63kOJTbfly+/5P7dn7JMJ55/9ZqfPv+Cn33+kvvjiXNWgbWGXKTVW0KrBoyoE2WlVy5/zxqN955HVzu+++G7fPfdpzx9/B6/+oPf4L1n75GrCKvcLJLxGAMxBHBOBGs5X3IljRFWgBiMzGUb8LU56QxW5dIa6FaenG34F+LQL3h8Kw4BYzSPbvbsxp6x60HJsHC/26BAlGnGURHzhDEa0359PM1ydyqSe9/3HUPvmQ4H7teA7TtunjyVdU1ceTgcJX+wFJRa6TpHdY7cIA1agbYGby3b7ZZxM8qQrhSW+dTizaAqcQDaWtA1SdJN56WUrhVnBc2llMwGsq6UFNDWcThN3N0d6DsvNFslk/veO662G6ZVgkwqskYqRe4IOWfmlNHtQzKvimUJqJoJQQZCuVRikX5yf7WXyK8o8mptHEWZZkqqYHtRt4WINYZh6FEKxs3Io8fX3L695TidSEHWsaVktHIXsMW57Cwpk2ui7xz73dg4/YL+Vig2Q0eplkt6FLp53ytYz2leOS0rbw93aC3pvnle+fz5C8mWNIY1RJTSDN618JlA37T4Rc4VWR+qgtG2JQMbNr3ldg5S2fge43tOSZOrwlQRdA3DyOs3X/K7//Af8rMXX/Hi1R3zKmh1Ywxdc4VqpcAInUj+TO60JRcKtWHhHc8e73l6c82zZ894/92nPL65koSs4REffPA9Ht08YV4XUIa4JpZ1Yl4XlnUVB2GRlfPZa5CS6F5ySnjr0Kq5aIv8m9YoCtJSc1uXSmUnuoXmxP2zeAf+STycczx7fI3VinHYypQ9LsyHI8oYNvs9xlpZgbQsPGUNsRYK0k6UtiaZQyYcFtJ6YrvdMQ4b3LAnrAtfvfoCKpIW2zmMhpgKEcXm6oouReIa6cdRbM0pMR0OWCM5fzlGdEvMneaVWi3LcsCR6fqu4bWk9FrmjO0su03P7f2J5TRRKbh+ZDpOLfWnMm4GnLdNogtv7o4c5iAkICsXU80ZpSuboSOWgt/sGZXizVdfMS8r3hkoghQ/LAllPcYYjqdVAKUXr7z0idICVGqUklobg3GGwXlKzSzryhfPf4bzjkc3V9QUmyxaXaLNx3HAe8+yrIQUL+1OSoWQZV6QUqQ0+KayPVde9tVn/3tMlfl0IIXIZuw5zZNguIxm9I6+k4zDZZlZQ8R7jzJyGHlncTkLxQghCmsURlmMLjgtGgtrBVN/d3/HEiO+H2Q9V4pUaJ2jHzruDzM//ulnzE1AZtqWwVjTtCpywOqW/5CizGn6rqPvOh7d7Hm833Cz3/O977zL45s9xknWYwqyEXr85Iarq5s27NasLejFO9cqiURpcXmlFDSqAW0D0xqYl4XT6UgtCecNqZqLUSi1kzDWjNO2zV1EuOS8bTFk97/w+vtWHAJGKXH4IYQb7yxdv+FwOLKkzN53+M5LsEhMMoHPheNxYg0BXUWJp7VhsT0P84H7+5ndkrFdT1dkaHjz6BHGWlKMdJ3FaoNKhhgmJNTBinvNdxJ+GpJoGJSBUrGuw7gOoyPTaWVZVlJahRicC53JEuflHMuqmNdI762sfTCgfSP5WInkVs0Yoi3UhEKxLiv39wc2vWWzGfCmAy1UJLTGcFY0aqbNBr/ZE+cJy9lMJWwBaw3LEnFd12hKQM4tS0GCT2MUiMk5kxEQDTxIm5E10+mAsQrT9ehlaio0OUz6cYuznvD2jbQFrieGiWlZROFnmgS8FEzz4ldVqWSUqvjmsNO1sB233DVjVIyRVSseP30KSjHdP2CMxTlHUZo1rNICedfccxImk1HkpsxU2khrVeSgT1EgsD97/oIvX77h/fe+I32294Q58vH4GemrVxcZuDGmOUkrSwhNqyIqvL7z7G6uePzomg/ee4fHLSui03Kg2n7Ae3nNlzUxP0xYZdlsrhj6QTiPWeNamY+1lJTIcSVGI3LunFiXhbjKXOV4OnE4HmUG1NoEawyJzDD0knCdMyXkFmVGow1JBXCGmv6ix7fiENBaMXSSa++dYuxlYus6TwoB7wzOGHlh5hMBEf6EEFEVhqGj6zu863hYAwcEh2Wa8EaTGYeOYbOlVghhpXOaGkUFFlLAOTnRDw8zlYym0llZ/dQshJaMGHB6b7nadCzL2lBQmnVdMaaTaX2SfbfSmjUVuq5DDyNrkuDVS2qPNiyh4LxqlYTBo9nvJNykVElVirFS0BJnPp9Y10A/9FyNHQrNfZpxVsCnN26gKi1Mw50TowPntWAl10xnDFo70BZle0GR1ZUYU1NbQiqKVCpGZfa7EbesxKNiqbJ/HrqO9z74LjElTtOE63qwDtd5VOMv1CJeDaVorIMWFdbMVpuxp/OejKRE9da0HlYu2MPhIHgvVTFWkVq8mjGGXGRzUZBDWoJIiuQLWAumWcuR0vju4cD/+bv/iE+ef4HSlh98/7f44Q9+g8c3j3h08x5ffvWG5y9esDYoiHD+ZRa03W7Y7zbc7LZ88M5jbq523Oz37HZ7NtsRSyWmRM2J3W5Hf/WI4/0dcV2YppVStFSf/SAegJqxDV/nnWVOoYXIrJJdUTVLWDmdjkzTiePxntu3r7m/e0uKM+8+u2YYHKd54eXrW1KuuK4jpcKpHBoxWzDpJSbmZb1YjX/R41txCCilWj+d2m5VYqTWkFhjJsVASpFpWihVwhqcNSSr8daw3W5a9BKMFp7tOnbmCUPfCXMA6PsOTeVwOFBrZjPciOsrJ0onpeyTJ495OM58+vnnvPPsCX3fsQQRqJzhpoqK7ewldcdYK4eGbaETYSWmwna3k9IW8J0kIyUC+2GLd46Yi5CEi4RbdFa+f8iZbrNrbIOFUCoRTSqVGDIlVkZbUS0ejMYvKAhO6+b6ijkE4nxHVRJXbdsKVakieQbtLqKsZVoDMUR8Z1CmEnJpeKuKN5YQAlqHJuiSAJcShaazLidSlufquw3Hh7d0Z9Cogq7p9mMIlFTl4FFysBUEIrrpBuacWWPGW8Wj/Za3hxNaFXRJ9AaWRlBSpqUgW8t2u4OcJEWpBY3qqlEIoy9rA1rMQ2PvefHqLR+/eMWyrtxc3XC12fPBsw+4vnmEUY7f+JXf4O//3j9oidYaazS77cjTxzd8+MH7vP/Bu2w7y34YJPTTGFzXy1wnrkzTTDWWgELHiPY9cS083L/iaru7BMgI0xK8Hxj6jHcTS4uGP04n8VwkoRdP88Tt7VtevXnJ8xfPefXmS54+3vKX/8KvM3jP8TTx+3/8CT/6+GeEJJDUHEOjSPF1bsc3HADwLToEMAanNSUVjqdF+jFj0Dnz8HDEOovbXGGHR+TpLbpEnBX9u3DstQxWamZwFr/f0Y/bdpIemaem3Mti51nXgNNQ0iqzgSYvBbC+R3vx7ru+cjw8iDRTaZwf6MaBHBfWdaXzmjUmCaewHaTCZuvx/UCOiZQj87JQS2UJkd1WYawC41nm+fLznC4skwSs9GN36UOr7cl5EpgKK8YLWw9VmOYTRZmG1VbUklnniZxTG0pKOb7mjLWOrinIlFL0TkI6q8jdBItmHVEVdDUs8/Gi4Lx9OxFjZBxH9kpznCb2m46HNy9Z1ojvPJSA3JcrnRW3oLWWd54+5e5w4OF+vrzfhsYC1JpMhpJFO2GhiOpH7NtO4ryWVYnic7fl9e39BeMmGglaBuHZat5MV8Zhu55hSAzDgrqfKHm9TNEl609jtGUcN3zw3oc8e/IU32turve8++Saq92Om92G3X7Hdr8XhkQneZlFiw8i5yjzGK2p1tENA8siQ76ffvo5g+rYXT26DDiFZOUQ/Y7H2g5rJqKCZZ1F0ZiSbEzu7vnyixf87LNPefHl52hd+M6H77LfX7PdXbPZndBOwLp/+JPPeHN/kJlNOedenFOKf7lkGL4lh0CtsIbMOHh8b5nmBYViu3fsrZygznf02x3VOOZF3ryu+fxLyqQ4y520Vjrr2t1WyLE1S5pNTZHNZqRWRY6BVARkMXQdIWU+/fQ5pVaePn0iYRw5tMmzYhg3OD/irUfVTE1BaEbGYoo8iaHzDE7oNimfWwLLaRLlYsmV4zxTqmxEOifY82WdmY0o+5y1THe3GKvZbbYsy4m6LqxhRSPT6rgsLE5YdJYiPgtZI5BKEodlkZ22N5WSJMqsqMqUJBOwZEO2PVfP3kPfvuX21Zd4D733LIvIaHfdhmJ7jgohIZXMsqxsxpGh7znePvDkyVPGccAYzXQaeP78BWsM9P1ArZW3t2/FJNNZkRpbyzoureIzKKMZuh4dLIdp4vVhoVbNskbcNAtuDQkg0VoApYfjTHCRvfdkZ0RlV1Lb2sjBZqyTqPBGeHLma7XMEgK3d3dNnRrwznFzfc2vfv8HXF3/UCLSnRi3vHXiSQlBeA4xtmAbOfznsAoi3PXUYccSCzlG7u4eePHFK/6Fv/hXePed99E1iHowRxS9BNnkgHWiHen78RIrt6yB0+nEy5df8MlPP+Ynn37M8XjHD37wHh998B6briMnmd147/nNX/s+23HD7/7BH/Pi5StaABNWy3OPSQapv+zxrTgEUAIbhcq8yAe+Vhlu1SjJxHvryGFG1QmDCFxazYNVGaUKyjmqEaCFVpU8z3Rd16yskMMihF+0AEJjxHcOtEHZs2rMs71+Jkac41ecJsFNaW0JMUAOks2XIjkGCtLKxCAqOq0qJSVSFi++s5agZSWmrSLEhFIGapSYryrbBNd36CKqQN+cgIrCYCtGWY6TEHe977BdT4iFmgJOV9GlWi+oMa3R1kIqLMtKbYYapWiJt+IlKDmDKeRXX/Bwf09KSTIQAK0rnbecpgXnLLv9NUofuH04tGTezE+ff4nShqtiWOZA58F7h+97yv0DkrIs9BxrFL31PL15wvX+GqMd23ErzMjtloq6lKynJZBSwhvLzc01ylmW17fEnIhBnk9opKfRils0l4Kh+eZbRmLJtcFqCmuSVOnadui1Vr746isOhweePH6MtSJDfvfZuxhzoJIFge4cSot0PaeA04oUBeRhNFBE6amUZq0KcuG4zuiUuL+7x7qRZ+9/h92jK9LhNcsyczo94L1BY9G6ZWC6gaEzrHHlNM9M0y2fv/iMTz/7lD/5yR9ze/8W5+C77z/lyaM9T54+43B/z7RIqa8qfOfDd/F9x4/+5Cc8f/EVD8dJ8HNNI/Ct1wkoJeKOsCyyCjJahCUxM88nrPPk6rm/u0crSRnebHekmIgkyjka7Bxn1XQERmuU7bh+/JQKfPX580ugRlgDRlViEB++0oZ+GChVEZXjsETm2xO1JB5vRnKW3rkYw6B71lRZUmFo4sbYPuzaGAnXUJVhGEkxUGplXhMxRYw2DIMgwuaQKEgEVZkmYkyScZAyxjhiik1zDijNZttCSpVCGUPMSXh0JWGAznlJR6blGDZFoNbiNKwlSx+dClkrvK4c7m6Ja8Q4Q0oFY4Q8FGMkhoixjs1GchVqLuxvtsxLpMwLusLd7VseX28YdyO3R4mVd87hu44PP/yIdQ3c3d6itOeDdz/ian9NCJmx31KqwBxr23df7baMfebN7T3zPJOan1+VTEYCX3MM1JokFBRFKnIhKa3k9UASh0WZqIipsgRJK1Ja4bQh58irN19xe3/P92qhs56r3Z5nT97h089vGUZRkJpGANJV5hXCt5SBdMWgrWXoByqK9XSCdSbFlf3VI/x25ipvePLuu3Rec3r7knWVOLjNZsQ74QxYbbjeXZNSFIn4MnF//5Yvv3zBT3/2CV+9+YpaEtZ4nBXwrnUdQ4OsjP1A7TsUlaePrvj+e4/4/T/6mD/85Dlfvb5lmpcWl/Yt3w5QIQbBXfVDj7eyCpzngDIW1w/8X+2dS4ysSXbXfxFfxPfMzHreR3dPT0/P0PLIwmIYW5YXlpeAvRnYeYUXSGxAggULI2+8BQkWSAgJhCWDEN5ghDdIBoQEGwwG+THGsmfGHnu6+77qVlU+vkfEFw8W57vXrVHfBo+mb5XoOlKq8mY98tzIzPNFnPN/jHNk2A90tbD1CiJlU5GSxS+ACtDokHDDIBrxk2Nz3mEKw9j3pBDJWi3aeono3QK5FC8+XRTEOeC2j9EhiO2UaQGN0gmVpGEjCLIkePemZn8YcM5T2QJVVlS2JgbPHGbmENG2plKRYpZRZlVZfN8LIgwBJ/k5UGgFMQhyTL2wbC+p6oo5iwmKTpGQPGXVUpYN/aHHh0itNLlQ5CQWaWmhXYfZY7UmziJSQo6ix5A1g4+EmNGlpSwrQI5OKSXqupbJTKmYpoFh9FTV4gSVAl1T4+aZqoSukXFm7zw+zFxdH1ivj2SkpmsOHzjOTk45Ojql61YcH51yfnpG3z8hBimSLwRkiwJhSM6eZxeXbIaGeZoxrSVkjbGG+00tsuFZkwtN1mJCkpJCpeVxJYIhMWfcMq0pFoWdmBL7w5br7RVkhSksbV3z5sM3+fDp+ygtEnBzTHKlX/wHQ5xFaj1ldIGoQKEX+3OB75a2om5b2qYmZUuz2hDHHf3oGIc9h0PParVhmvzCbl0tsnEiLOpcZOgHLq+ec3X9nBAEtxAybH3Fxc7j0jVpYbl2VUnKgt2wOvPW2/c4erjhrTfv8/z5Nd959IQnF1fsDiNPnl9/7MfvVhSBtJhzdF2H915YdarApkwInuAndJxpLTRtLX4AyxwaLS+0nyOnbz1EF4bx8olAWJuK1hZcP/6Aqe8FqLIwzawpiG4RbFRLYy0njBH5JkHYFctMN5ARGawQAv2hxxSKtqnxc8B5j9KC3qNcUdg1eb6iUlr8/coGpT2V1czeQRKii1q47KXR0pn3TtB3MVEsijlpDpiqfCkwKmYWmuura2k+przMxOHQH0T0Yvl/WmNJIQg9WjzWiAud1hjNPCeMBlOIfoBSCBiq0DS2Yl6ky8WC8IVe34jWmXvnR1xcbplDXP5moms76qqUOfc88+jRE7KpwNbUVSPYAa1p24aHDx5wceXAFvjBU1vDMAwUxtBt1iiTKZc5t6ksKQaGYcRWcpEotWYcxSsgsnB0lYBnxEdykfguClhUpV4oNa2bijfvH7FZt6JTURhsVXNydkbXHnG9/4C2XqGMZdVWUsyMIcRpmQalpbAoJueY5z+hKbd1hR8HohuxpmTyjjBNTG5it9/y4eMPaLpWXpsUxFC2KPCzX+zfWXZ5ok2Rlx1MW1ccryykmcP+mtqWy2QkYVVJYSIQobLcu39C4eCte+d86Quf58PHT/mD7zzmd//g/Y/9/N2KIqAAq2VbOAcRYNS6EJEUeOlKU5aW4D1ZW2JwpOCZ58A0OlZdTa2TmGPGWba+SrHdXpKzJsVZkG/lalHqzVhbLKKPSSYDiz5hyiL+WSix10Knl42+0Xm0MdRNzTDNhDzTdY1ANIOIoFgVyAasTgSj8EGaem3bso9JPPqS+BSUMS3qujXXVxE3OsqmIS9MStOu8cFDEg2AYVbsdgdiiJiyYtXWODe9hD1HVTB6+f+3VYXWjcy9c4QkOPNERi/yVeUCVFELnDemKJyEDFW9ZuhHWbflapgQwRVblXRtw9Pn16QkmAxTCjb/wb1TFJnGWKLVTDpzdnLGuumoyhK/XvHw3n368ZkcXcoKXdUMu56zB28QYsD4GRUDGEW7auWY5hxuDvjFsCWkhIoRq0VdSBtDWJB9GU0qKrIRqW8xL4XTTcsP/9B7/NgP/wjvvvP2gmNQckyrWzarIx4/+iZpbQl+xmrwSrAeShUYDdpqYSwuWgbRjxS2pqwrlFa4cY/3I1M0XDx7Rh573OQYxokPPnyfwhjOzs5YtxW5UIQsTWw3j8zzSIwepRcOxEJPv392xNlxS1WKzqY2mtkFwbBYS1lXlHVFv5tw/R6tDHUjRrSFKTg9PeGXf/W/fuzn71YUAXJie3FBWrT1jo6PWG02bDZrYd5lQRJCFjtylSmsxdQVfhzRQNO2uOHA4TAQvcNaTVPJudrqjCoSMRmqskBr+Vu5ULgQUFoERcrK4tzEPE2ossQ2zVLl0yIXpqnLkrqt0EvHetOtKDS42QmpxmhsHpnjzJyjKN0o0NowOY8pK+bZo5gpCyX+hDmxqmtc2zCNE2UpV1OFoL76KUAUjoBzM5ObaUvDNPSsqoLaaEIEXRr8MgkJzlNXFdZarDGL5JXCjwM5JtarauiWqAAAFdNJREFUFdYYaYourDVTyJY2hURbWdzs8E7s1VatoOAO/YgpNGM/cdR1pJA5DAMXlzuyVhz6SYBPKbE77KAQJ5Dj45MF6VhQlw1ds6Y/BKY5cHJ6T+S3gqe/upAG4CwzdRYZNFImBCnW0kwrXhp+KiWjt6Q1GCNmNEGsylFi9YaCddfw537gi/zQl9/j6OicrjtGL7DgF7eqajgMM4f9gLGGnoApS+aYWdUVTdeijcVfbcWCrW5QqqAfR7nie9m+9/3I9uB49vhDSJE4OYL3HMI13/r2N5iC4+033xIKcYx45xkHz6E/LByCiqqqcdNI25Y8vH++ODfLlGacBhmjl5asIt5HnO7YHhKNFlOUlGQy1FZWFIteEbeiCOSs8AHm6OnHgbIqadpGIL+1aAHMk8zK7dKNLdsVtirZP38q4Ag0znlyljeP8zMxBPwcKQ2YsmHVtqQwYMvEnEV+rGxaqrphjuCnUbbPWo4bVd2Rc08Os0wVFsrmPAl4yVhLVWRckMUuCvlAeSfYb1u1It6hwNqSvh9RhaGsWwoT0QRWlbwEw36LGwZ8CJRRuBDOOY4KTXQjh8ModlxIDwEttOrSWipreH69l3lwFofmrrbElDgMA20jVOT7D85JzzOHwwDLDsj7mboUay7ZbSQGL43WcZxIIeCdIzUVurAUhROxT2MX16dAXYoqVD86pnGUERoiHCtErDOO18eyBc5CRS7KErLlsNvx+bdbpnHgbN3g/YGpH0laDGhWbcvx6akgBxdtyZcQWC0ju6BFyk0VBSpndBHQKaIWhl+KAlH+8pfe4c9++T2O1sdkFh3+LFLkSC9XHHwp2I+eB61YkvWTw+vEUdOBshz6CVKg7s4EgdmIs5Gfeulr2IqyrLi6esSjD/6Y9arFJk8MjuvDlvlC3n9V1ZKyxRaWaRg4HA70g8O5wDyLDZsxBe+8/QYP7p8SvKMsxElJhGIM2pZoY5mGETdN6EKDNhydnTD2I/3WoXKiqtqP+eRJ3IoioLRoqhck2rZmDrNAgrWo1eScUMa81OaHTLfuKNoNF5fX9KMo3ZhyzXRwxOjxIVKVJRnFdnCcnjYUC/bdmAqIoPOiaJQZhgHvBE5cGQuIc1FdVYSyJMyeqqmp6go3jszzjCk0kxvo3UxpLW3XyNnVRwIFTWEWLYJMoWR6sDvssGXDyfk5u6srehfp2gY/DmgFTWXx3jP0IyknqkmOEqU1xFgs2IfEerOiKQ0BjfeROYOfE/0wkcJMfXbCNHqGfmBTGwpVcH21Y+hHrLUcnAfAVpV4MkY5EhRFQSoK5ijKQsZaOaOGyHYvfZUQM7mQfo2xcl63lX3pFG2NnP2NUlSm4K2Hb3L/7D6mtCItrsAUhqZqCMGQph0XTx7TtS2b4yPxJsiCpJymke12S1osyEOMpBjp+1Gco2aZLBSmQCU50mhtxdlnaQKGlLh3fsqX3/siq/Va0JC2RCtxgiJHiFGOkElQoTlGurZGAc57pllw/O9+/nPU1tCVG3RtuXh2jeuvqboVpigoSxk5a6148uwRddXx9htvUuqE8yMX15dc7/c8en7Jo8eP+OLn3+N4fYYi0g97nl085cmTJ1xfXUD2fOkLb/LlP/MOD+6doxT4KOxUrSPaVExzwuSA0eDmHhUDYwwc9hZi4HjVkGKkbG95EYAs7r/es1q1ooJrFiPMGBdFYcM0jaKGUyj808dQPEfPk/gXhoiqXsg5w3q9Aq04DBPOyxveGMMcIiGDNSWVlmbOMEwcDj2lLaSzvPDHQ0zUZck4TPhpemm8aUtLqzQhBHaHARcyMSs2qqBra1JW+CTjQhAqtJ9Fx35c3rzTsOPZ8wucjzx8cI+XfnHakGZPoRUP7t2jHyaudgeapkUXoL0cTaZhYlV1Uri6DXWd6RftwroypCxjxrJdM86ZWmfirFCFxVrptVTWUlYiZzYvY0mtFI0O+CB49P1uDyhiYnE/LvB+Yo1w29ddg5smwuwZBrkSbtZC/vIZ2rpitTqmLGsy0u8RbQVpsh6GEa015ycb9v3E9fUev1jQO+fQVBg746aJQ3/A+biIg0YSs7AW50AV48suvV4cikEwAVrBu59/g83RCq2gLMRqXHT5NIG0sPji0n8SQJXQwmG1aumyOAHvp5Fhf+D0eMOR1tw77uhtZr/bkkyJMpYUPOPQs9vv+da3v4XKInA7TXv2hx27YSDs9jx+9oxvfPObnGzOadsWReTq6jl9v2cOM198+5yv/NB7QozzszSQswZdUhSCgTC2pCgNKmhMFsHcECKz86y6lmZ9gg+Kw+7ilZ++W1EEUhKn3xAjEU1ViKtMSuAmt5gsCL46Rrla6SwvlPcRKETQIQzUlUV3LdoUpBhoyshxd8a6EWmvrArpAShFaWEMgRBmuqoQB2ClqWyJthY3B3a7a9xytdnv9osWYE1MmdIW6MpgFpcZFyK26qjXFa3KAiYKTgwl0QzOU7cNp/dOiVl+6eToSABFs0dpTdda5rlgF4Q4o3Nks17Tdiu2uy0hzKILGAJX2x5UwdlZgxsGbJEpakuIi7moynTtEX6OjEOiqgsplhmC97S1IM8mL8rJq64lJfDTTNvWJEQ41RhLygWXT55xtFlhtGa73VPVNWkWDbswz6gkDM+cMuPk6Y42cmyzDTHODH2Pn+V4EWbHHCK7Xc/F8yvOjjt2h4Hdfk+BFHLvHQcyc8qMvTgHq6LAlJbPvf0QN008fXrF6GbKMqEqUEpAQjGL/VVMAny6f7qhqSyb9UoUmdxAP+zZbI5FZDW9MHERqnphjWAFjKVpztjudpysDFVV8eGjpwJVL0qO1mvOH7zB2ckpu+01U9GgjGUcvk6Kgcvr5/x+Etu7EDyTmwhpsbj3M0+fXaDVH1KV5XKcTLS15Z3PvcF7X/o8Z8cbdv1ECAmdM1pnkgabFeM4YmzEqg6VYdUJfuX4eC3qVFHhVcNl0kT/6s/frSgCSim0rQnjiJ9GQWbZWqy3Z8dmtYIUKW2JQ87KXWUIIcmZTsk4b56dcNDrFjdHjIFVJ+fytCixVFWFKQwGIbrY1tDZilVl2E6TWIjbipAi0zjgfKAsRUt/GAeKQhhqBYn18Qlt2zAMA7vtgfGwE08Da/FuIubM5fZAZY3sHlqx9BqHiQS0dUNdlfhpIiEy4MoYmUMrw+EwEUNgs9rQlgW2a3g6jbhhYC4KzFSgC8O33/8OikTbWHJRcvnsQJPkSq9jwJYN/XaLG59SFvIm05UoGStdsKpLUpgZBlESHkeHKUuxOY+CtptjpjKaTVMyusDF1cTDbkVMiboVk9TRBZpuhXMy5pyHntitRQsiZ7wXf8fDcGAaB2Y/AYn9NEM/E7CgI0pBozNKlSRlFuKYEJCE6y+03llrvJsYnKNpOupWXJNSzqSlFxBDwhYi2KK1oShrYesxsz8858TfoymF/akLjbUlhTYoldj3A5ujY85Oj3Fu5LDbEpqW9aqlquV3/OyZdKKxlnVbUxYN1dGZ+FGkTD/0DOMoaEor0PAUxWFYNAMySWXm4DGm5v69E9596yE/8KV3qLtjrgcRnW1O3mTykTRcQJoIWjQOhd8xL8VPYRaJPqUUoxuJ7jEmJsrq1fyBW1EEQEwajTFirJgiREecZ/b7HoC2svjgePTkgpwTb94/pbaG0hh2UZh7qEy0iRgdpRUXnRACs3OiJmsMtohoVYjuPCLT5HNi6wIUJSqLy08OYZH4Vi9deNqmQZtSEIHAs+fXlNsd0zAwuZnjkxOqqsLFxJPnVyil2PUjZ5sORabvB2KEOV4KJDoGvB/ZH3ogLnbparFUr7naHfCzk/FW26KA2opr7XYUc8vVqsN7ERYJITE6h9LCe9/3AzEDqifPM6XVjOOE0uJAPIwT1lZMwYsXZFXjvRwLfBTVYbL8TVOIwGlVVWhjKa4Uzk1UpeV6N+Cdx1Y1m6M1OWvsYFA5492Ec/IhLgvZ3UGBC4HRTdRlQWkUwzCidUGKCUciaygKS920XPut2Hctmnneex6//xhF5upqy9PrkfPzeyidF1deeW2V0jJq1YW8P7KYqoYYKU1kt78kBIduWlR4YX4jsGCtxUvSENg++WPi2BNDYFKTYELmyOy31KWgUp9fb2H2pLilf/4B++tr6RstILQUI8MsfBOy4o2H9+T9qzPWllRdx/1757x575TjzYqyrGjWD3n29DvEMNGdg7bibWlQVMbQtBUUmkM/kUJk7x2VFWxIzHIMNVo8Ky23vAhkRETBVDUzGZ8VtTYcnW44OT9nGkfcYu4h4iFK4KnGiOJscvg5igMwEINw+434hJNrUcrtGjmvTwGutk9pm4aoCoL3aGvQWQtBxtbU6yOudntphM2OQsFms2FwM4f9gU1X42dRFApJSYHQmqurS3b9QKkLirJi3bWUdcnkg9h7LVDlAnEncgus2A3TS5+AjKYo5Ko5z3GR7B6JMeGcp21qjmyF84uDby0Nsu1uYHROCERkxnHA6owtq4V8AwolLklGUxQWsubxduGgZ+mm102FLgxtJVoApqqIs2e3ndn1B7SxC3BJ5N/32z3znFitV9SmgLKhGxqqQlxxYpIjkS40RTIvde/87Gi7hlVt+eDRM443axoDU4TCWg6HnsJ7VE4CzqorslKi+DSMjOPIN/7oA6YA2/7A6ckxcdHWs9rglcJoMalZbzrKqhQ4dIy4EBnmKw6HPau6ZXJOQGiLf8UwjWySyLTXlYwkVV0yjRMxJExVEEn0oyMWFqUMISeG4QDBcb3riUHQmaLlILuulOBo0/GjX/lBHp4dY3US/EEt7tgqOpyPGDImezZti9cnuGFgXUEsDSFEtC2ompphWvLWCp1lF1cajWlq8AJLNioRX21AdEuKwAIbXnUtbp4Znee0qVkfHXH//hlXz6948uGHuDRxdrRCLwzBfvIYC8pYamNEjbdQmMXsw01BGkW8EGDUuJDJRQUKpmlAmwrnJnyfRHyzsEzTSFOXHK1apmliHEdcDLS2olutBNUYg5iHrI/48PEFtSlk1Ohndts9bWWpU2TVlDy7uGSeE23byAhrMZf03r/Usrt/7xTnZxkFIj4BXVujc4KUqJuWtlvz5PFjnJsxtmDVdYKeK0smP6CLgqqs8G5EVyXrrkNHj6LhaHPEMAxUdc04eg6HnratXoKwytIyh8joJsqqpiKzajrqriN6R9Lw4OyE6/2eKcjxyrsZ1WbqrsEl2TUVZFy/R5FYbY4pbM1h2L+EBuskFlr9cGByA+uzY6aYKatqmf1bQj+Jm9ALDT+kOpZViS1L+kPPOAx8448e8fjZJbas6BeXKSEIKUDO9uXiwuT8zDj5hbYux4owOw77Pen8PsYoTCho25au6fBxJKTM6BNtaylLxfV2T11ZqkqmJVoXsvMylqaqSBpUWbMdJq6GiTllVJadhXqh+58zlbU8OD/n5GRNjlFs3nJenIMKcp5RGmLoxUWpPsYNWzjsqQpFyoqsDS5G5iieDn4W4Nw8R2IQhq0tROb+hS/hq+JWFAFrDN1qTUxRUIEhMu4PzM4TwyydebJ0cIHalOQQKbS45BRKy2gmJapKJJ6nQ09lLYdRPAWqquL6+pqY5cqojMWNI0WcpPBMjiqUnN07Yr1Z0dYlYaro+54pZIZpBuO5t97QNjXzsOfy8opdP6CBt996k5wTzy6vcN4TFhmo0paMix25m6XzXCjFrITgkpXo9pVliS4Mzy63Am+Ni9hkEHx/OXlsFbGFYXsY8EPg/umxjMt2e8ZxoqlrUUVuZBeklMEWJevNhqPTU65sgZ9G9he9AIqy8M3F8LNAK5HDKm2BjkEUcN0sjEufCIuS7qqUBuocA7t+IC0kHnHDFcvsummJKVOXNaPzzCFQaIhaXJZYZMvlyiz6C1e9FHm16OW3tThMbQ8DWQtj1CrxoLi83vH+k2f4ENFGfB5jCGgtPomqKMjakrWAZvrBUW53rLqWaRhpuxa1eDOCoqkbYoysu5bTkxNMEZmziJ24EMgU+Kg47To2dSn6/ilz3U8QAi4JfDppi4swTP6lO7FSCmuVyJYDL2zImqZmHCa0zng/MztHvcDC57wIuKZME68xaqKfRibkmGJpZDfjPGmeubzaMjtPtz6iqRrZwVkZkQ+TTBZeFeqTKIavK5RSz4AeePUc4/XHOXf5fFLctnzg9uV02/J5J+d877sfvBVFAEAp9es55x+56TxexF0+nxy3LR+4fTndtnxeFZ8sPnYXd3EX/9/HXRG4i7v4jMdtKgL/9KYT+K64y+eT47blA7cvp9uWz8fGrekJ3MVd3MXNxG3aCdzFXdzFDcRdEbiLu/iMx40XAaXUX1JK/Z5S6ptKqZ+9oRy+rZT6baXUbyilfn157FQp9R+UUt9Yvp58yjn8glLqqVLq6x957GNzUBL/aFmz31JKffU15fPzSqkPlnX6DaXUT33ke393yef3lFJ/8VPI522l1H9WSv1vpdTvKKX+1vL4jazRJ+RzY2v0PccLTfKbuAEF8C3gi0AJ/CbwgzeQx7eB8+967O8DP7vc/1ng733KOfwE8FXg6/+3HICfAv49ApT9MeDXXlM+Pw/8nY/52R9cXrsKeHd5TYvvcz5vAF9d7q+B31+e90bW6BPyubE1+l5vN70T+FHgmznnP8g5e+CXgK/dcE4v4mvALy73fxH4y5/mk+Wc/wtw+f+Yw9eAf5El/htwrJR64zXk86r4GvBLOWeXc/5D4JvIa/v9zOdRzvl/Lff3wO8Cb3FDa/QJ+bwqPvU1+l7jpovAW8B3PvLv9/nkhfy0IgO/qpT6n0qpv7489iDn/Gi5/xh4cAN5vSqHm1y3v7lsr3/hI0ek15qPUuoLwJ8Hfo1bsEbflQ/cgjX608RNF4HbEj+ec/4q8JPA31BK/cRHv5llP3ejs9TbkAPwT4AvAV8BHgH/4HUnoJRaAf8G+Ns5591Hv3cTa/Qx+dz4Gv1p46aLwAfA2x/59+eWx15r5Jw/WL4+Bf4tsk178mL7uHx9+rrz+oQcbmTdcs5Pcs4xiyDiP+NPtrOvJR+llEU+cP8q5/zLy8M3tkYfl89Nr9H3EjddBP4H8J5S6l2lVAn8NPArrzMBpVSnlFq/uA/8BeDrSx4/s/zYzwD/7nXmtcSrcvgV4K8uHfAfA7Yf2RJ/avFdZ+q/gqzTi3x+WilVKaXeBd4D/vv3+bkV8M+B3805/8OPfOtG1uhV+dzkGn3PcdOdSaSL+/tIt/TnbuD5v4h0bX8T+J0XOQBnwH8CvgH8R+D0U87jXyPbxxk5L/61V+WAdLz/8bJmvw38yGvK518uz/dbyJv6jY/8/M8t+fwe8JOfQj4/jmz1fwv4jeX2Uze1Rp+Qz42t0fd6u4MN38VdfMbjpo8Dd3EXd3HDcVcE7uIuPuNxVwTu4i4+43FXBO7iLj7jcVcE7uIuPuNxVwTu4i4+43FXBO7iLj7j8X8ATtjG9/zNq7cAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yvIAVVTCMkrs"
      },
      "source": [
        "IMG_SIZE=160\n",
        "\n",
        "def format_example(image,label):\n",
        "    image=tf.cast(image,tf.float32)\n",
        "    #normalizing the values\n",
        "    image=(image/127.5) - 1\n",
        "    #scaling the image\n",
        "    image=tf.image.resize(image,(IMG_SIZE,IMG_SIZE))\n",
        "    return image,label"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RV2NCkyVZE8R"
      },
      "source": [
        "train = raw_data.map(format_example)\n",
        "validation=raw_validation.map(format_example)\n",
        "test=raw_test.map(format_example)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RXLYQi3FiYO4",
        "outputId": "04615e01-8657-41e0-f1e5-10de0007c7fc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "validation,test"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(<DatasetV1Adapter shapes: ((160, 160, 3), ()), types: (tf.float32, tf.int64)>,\n",
              " <DatasetV1Adapter shapes: ((160, 160, 3), ()), types: (tf.float32, tf.int64)>)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9UJOhqNKGDte"
      },
      "source": [
        "# Batching the Data\""
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dzd-zNQGZMij",
        "outputId": "10715d87-4827-4ec8-bb1c-3acb45a35881",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "BATCH_SIZE=32\n",
        "SHUFFLE_BUFFER_SIZE=1000\n",
        "\n",
        "train_batches = train.shuffle(SHUFFLE_BUFFER_SIZE).batch(BATCH_SIZE)\n",
        "validation_batches=validation.batch(BATCH_SIZE)\n",
        "test_batches=test.batch(BATCH_SIZE)\n",
        "\n",
        "for image_batch,label_batch in train_batches.take(1):\n",
        "    pass\n",
        "image_batch.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "TensorShape([32, 160, 160, 3])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xwdA2iM9GINP"
      },
      "source": [
        "# Loading the MobileNet Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kz2gjU_KbGnr",
        "outputId": "68d416c1-806c-4116-b400-083117b323c3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        }
      },
      "source": [
        "IMG_SHAPE=(IMG_SIZE,IMG_SIZE,3)\n",
        "\n",
        "base_model=tf.keras.applications.VGG16(input_shape=IMG_SHAPE,include_top=False,weights='imagenet')\n",
        "feature_batch=base_model(image_batch)\n",
        "print(feature_batch.shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/vgg16/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
            "58892288/58889256 [==============================] - 3s 0us/step\n",
            "(32, 5, 5, 512)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Nt4ossnLGPiG"
      },
      "source": [
        "base_model.trainable=False"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P8uGCdFZb0S6",
        "outputId": "69139b73-e660-41eb-b312-81d0db9e22a2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "global_average_layer=tf.keras.layers.GlobalAveragePooling2D()\n",
        "feature_batch_average=global_average_layer(feature_batch)\n",
        "print(feature_batch_average.shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(32, 512)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LlFxgPtocZ7S",
        "outputId": "b8b12cb7-49e6-414a-f4b1-64529499cdef",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "prediction_layer = keras.layers.Dense(1)\n",
        "prediction_batch=prediction_layer(feature_batch_average)\n",
        "print(prediction_batch.shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(32, 1)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NFcFtoEacqKP"
      },
      "source": [
        "model=keras.Sequential([\n",
        "                        base_model,\n",
        "                        global_average_layer,\n",
        "                        prediction_layer\n",
        "])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pdEDO6Hqc8Sd"
      },
      "source": [
        "base_learning_rate=0.0001\n",
        "model.compile(\n",
        "    optimizer=keras.optimizers.RMSprop(lr=base_learning_rate),\n",
        "    loss=keras.losses.BinaryCrossentropy(from_logits=True),\n",
        "    metrics='accuracy'\n",
        ")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NJjNzXBzdYi2",
        "outputId": "8e07c84a-72eb-4b5c-ca48-359d38942943",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 255
        }
      },
      "source": [
        "model.summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "vgg16 (Functional)           (None, 5, 5, 512)         14714688  \n",
            "_________________________________________________________________\n",
            "global_average_pooling2d (Gl (None, 512)               0         \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 1)                 513       \n",
            "=================================================================\n",
            "Total params: 14,715,201\n",
            "Trainable params: 513\n",
            "Non-trainable params: 14,714,688\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ebYVFlTfGUPi"
      },
      "source": [
        "## Initial Shallow Training"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QQX3DIJKekof"
      },
      "source": [
        "checkpoint_filepath='weights.{epoch:02d}-{val_loss:.2f}.hdf5'\n",
        "model_checkpoint_callback = tf.keras.callbacks.ModelCheckpoint(\n",
        "    filepath=checkpoint_filepath,\n",
        "    save_weights_only=True,\n",
        "    monitor='val_acc',\n",
        "    mode='max',\n",
        "    save_best_only=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jvTLtqnSdauo",
        "outputId": "4fd397ae-1a4e-4265-ed6b-11892588adee",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 697
        }
      },
      "source": [
        "initial_epochs=10\n",
        "history = model.fit(\n",
        "    train_batches,\n",
        "    epochs=initial_epochs,\n",
        "    validation_data=validation_batches,\n",
        "    callbacks=[model_checkpoint_callback]\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/10\n",
            "     26/Unknown - 1s 51ms/step - loss: 0.6991 - accuracy: 0.4672WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r26/26 [==============================] - 2s 94ms/step - loss: 0.6991 - accuracy: 0.4672 - val_loss: 0.6636 - val_accuracy: 0.6078\n",
            "Epoch 2/10\n",
            "25/26 [===========================>..] - ETA: 0s - loss: 0.6780 - accuracy: 0.4700WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r26/26 [==============================] - 2s 61ms/step - loss: 0.6779 - accuracy: 0.4672 - val_loss: 0.6551 - val_accuracy: 0.6078\n",
            "Epoch 3/10\n",
            "25/26 [===========================>..] - ETA: 0s - loss: 0.6621 - accuracy: 0.4650WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r26/26 [==============================] - 2s 63ms/step - loss: 0.6610 - accuracy: 0.4672 - val_loss: 0.6442 - val_accuracy: 0.6176\n",
            "Epoch 4/10\n",
            "25/26 [===========================>..] - ETA: 0s - loss: 0.6478 - accuracy: 0.4675WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r26/26 [==============================] - 2s 61ms/step - loss: 0.6465 - accuracy: 0.4672 - val_loss: 0.6338 - val_accuracy: 0.6176\n",
            "Epoch 5/10\n",
            "25/26 [===========================>..] - ETA: 0s - loss: 0.6322 - accuracy: 0.4625WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r26/26 [==============================] - 2s 62ms/step - loss: 0.6324 - accuracy: 0.4672 - val_loss: 0.6219 - val_accuracy: 0.6176\n",
            "Epoch 6/10\n",
            "25/26 [===========================>..] - ETA: 0s - loss: 0.6184 - accuracy: 0.4750WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r26/26 [==============================] - 2s 61ms/step - loss: 0.6189 - accuracy: 0.4720 - val_loss: 0.6118 - val_accuracy: 0.6176\n",
            "Epoch 7/10\n",
            "25/26 [===========================>..] - ETA: 0s - loss: 0.6059 - accuracy: 0.4800WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r26/26 [==============================] - 2s 62ms/step - loss: 0.6053 - accuracy: 0.4818 - val_loss: 0.6003 - val_accuracy: 0.6569\n",
            "Epoch 8/10\n",
            "25/26 [===========================>..] - ETA: 0s - loss: 0.5920 - accuracy: 0.5200WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r26/26 [==============================] - 2s 62ms/step - loss: 0.5918 - accuracy: 0.5268 - val_loss: 0.5867 - val_accuracy: 0.6765\n",
            "Epoch 9/10\n",
            "25/26 [===========================>..] - ETA: 0s - loss: 0.5790 - accuracy: 0.5462WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r26/26 [==============================] - 2s 62ms/step - loss: 0.5791 - accuracy: 0.5426 - val_loss: 0.5758 - val_accuracy: 0.6863\n",
            "Epoch 10/10\n",
            "25/26 [===========================>..] - ETA: 0s - loss: 0.5674 - accuracy: 0.5713WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r26/26 [==============================] - 2s 62ms/step - loss: 0.5667 - accuracy: 0.5706 - val_loss: 0.5639 - val_accuracy: 0.6961\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TK2s9ZBNdn-D",
        "outputId": "95ec924f-e2c8-41b9-c794-4ad1185a3231",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "model.evaluate(test_batches)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "4/4 [==============================] - 1s 140ms/step - loss: 0.5737 - accuracy: 0.6214\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.5736774802207947, 0.6213592290878296]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m5jUvJEPcNqa",
        "outputId": "50b20a61-1bde-4cab-b00f-04d37fe77725",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        }
      },
      "source": [
        "#Evaluate the Model\n",
        "plt.plot(history.history['accuracy'], label='accuracy')\n",
        "plt.plot(history.history['val_accuracy'], label = 'val_accuracy')\n",
        "plt.xlabel('Epoch')\n",
        "plt.ylabel('Accuracy')\n",
        "plt.ylim([0.5, 1])\n",
        "plt.legend(loc='lower right')\n",
        "test_loss, test_acc = model.evaluate(validation_batches, verbose=2)\n",
        "print('\\nTest accuracy:', test_acc)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "4/4 - 0s - loss: 0.5639 - accuracy: 0.6961\n",
            "\n",
            "Test accuracy: 0.6960784196853638\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GpnP2KrPo_l2"
      },
      "source": [
        "# Fine Tuning"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lgC9BDQdpBZY",
        "outputId": "45cc0b3c-0d8b-4cd3-f9e6-ba312a0bab16",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "base_model.trainable=True\n",
        "\n",
        "print('Number of layers in the base model: ',len(base_model.layers))\n",
        "\n",
        "finetune_at=155"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Number of layers in the base model:  19\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VGfQ8ps5p3wi"
      },
      "source": [
        "for layer in base_model.layers[:finetune_at]:\n",
        "    layer.trainable=False"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LWgnA2iNtuHV"
      },
      "source": [
        "model.compile(loss=keras.losses.BinaryCrossentropy(from_logits=True),\n",
        "              optimizer=keras.optimizers.RMSprop(lr=base_learning_rate/10),\n",
        "              metrics=['accuracy']\n",
        "              )"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tYgwowpKuGPZ",
        "outputId": "cc4634cc-30fa-4dec-e9dd-f74935a79371",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "model.summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "vgg16 (Functional)           (None, 5, 5, 512)         14714688  \n",
            "_________________________________________________________________\n",
            "global_average_pooling2d (Gl (None, 512)               0         \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 1)                 513       \n",
            "=================================================================\n",
            "Total params: 14,715,201\n",
            "Trainable params: 513\n",
            "Non-trainable params: 14,714,688\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tOAYxHcVuIUQ",
        "outputId": "84ce4c03-0154-4ab9-897b-bd1a3e206b50",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        }
      },
      "source": [
        "fine_tuning_epochs=10\n",
        "total_epochs=initial_epochs+fine_tuning_epochs\n",
        "\n",
        "history_fine=model.fit(\n",
        "train_batches,\n",
        "epochs=total_epochs,\n",
        "initial_epoch=history.epoch[-1],\n",
        "validation_data=validation_batches\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 10/20\n",
            "26/26 [==============================] - 2s 68ms/step - loss: 0.5591 - accuracy: 0.5852 - val_loss: 0.5624 - val_accuracy: 0.6961\n",
            "Epoch 11/20\n",
            "26/26 [==============================] - 2s 62ms/step - loss: 0.5578 - accuracy: 0.5900 - val_loss: 0.5612 - val_accuracy: 0.7059\n",
            "Epoch 12/20\n",
            "26/26 [==============================] - 2s 61ms/step - loss: 0.5566 - accuracy: 0.5900 - val_loss: 0.5602 - val_accuracy: 0.7059\n",
            "Epoch 13/20\n",
            "26/26 [==============================] - 2s 60ms/step - loss: 0.5554 - accuracy: 0.5973 - val_loss: 0.5590 - val_accuracy: 0.7059\n",
            "Epoch 14/20\n",
            "26/26 [==============================] - 2s 61ms/step - loss: 0.5541 - accuracy: 0.6022 - val_loss: 0.5578 - val_accuracy: 0.7059\n",
            "Epoch 15/20\n",
            "26/26 [==============================] - 2s 60ms/step - loss: 0.5529 - accuracy: 0.6010 - val_loss: 0.5566 - val_accuracy: 0.7059\n",
            "Epoch 16/20\n",
            "26/26 [==============================] - 2s 61ms/step - loss: 0.5517 - accuracy: 0.6058 - val_loss: 0.5554 - val_accuracy: 0.7059\n",
            "Epoch 17/20\n",
            "26/26 [==============================] - 2s 61ms/step - loss: 0.5506 - accuracy: 0.6034 - val_loss: 0.5544 - val_accuracy: 0.7157\n",
            "Epoch 18/20\n",
            "26/26 [==============================] - 2s 61ms/step - loss: 0.5494 - accuracy: 0.6107 - val_loss: 0.5532 - val_accuracy: 0.7157\n",
            "Epoch 19/20\n",
            "26/26 [==============================] - 2s 61ms/step - loss: 0.5482 - accuracy: 0.6131 - val_loss: 0.5521 - val_accuracy: 0.7157\n",
            "Epoch 20/20\n",
            "26/26 [==============================] - 2s 61ms/step - loss: 0.5470 - accuracy: 0.6180 - val_loss: 0.5509 - val_accuracy: 0.7157\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mWhNwAPxvctH",
        "outputId": "a5080852-1cdf-40f5-f713-5459db69f636",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "model.evaluate(test_batches)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "4/4 [==============================] - 0s 73ms/step - loss: 0.5608 - accuracy: 0.6796\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.5607730746269226, 0.6796116232872009]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Otsr3RCr300K",
        "outputId": "02728143-5210-475e-e7f6-7c1414fbf6e8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        }
      },
      "source": [
        "#Evaluate the Model\n",
        "plt.plot(history_fine.history['accuracy'], label='accuracy')\n",
        "plt.plot(history_fine.history['val_accuracy'], label = 'val_accuracy')\n",
        "plt.xlabel('Epoch')\n",
        "plt.ylabel('Accuracy')\n",
        "plt.ylim([0.5, 1.2])\n",
        "plt.legend(loc='lower right')\n",
        "test_loss, test_acc = model.evaluate(validation_batches, verbose=2)\n",
        "print('\\n Fine Tuned Test accuracy:', test_acc)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "4/4 - 0s - loss: 0.5509 - accuracy: 0.7157\n",
            "\n",
            " Fine Tuned Test accuracy: 0.7156862616539001\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
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    {
      "cell_type": "code",
      "metadata": {
        "id": "-6jkELMQFmgx"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
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}