project1_food_vision.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jZlc85nuM5PB"
      },
      "source": [
        "**Food Vision** : A Component of the TensorFlow Developer Certificate Course\n",
        "\n",
        "Course Link : [TensorFlow Developer Certificate](https://www.udemy.com/share/104ssS3@qr2xIEbG8LOqfGgHfmw-a2Z6r_d_6_olkS5hKSmVWT23wYDJNTbD82qAAoaJss-SKQ==/)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "mG0TWO7Xv8Hm"
      },
      "outputs": [],
      "source": [
        "# #update tensorflow\n",
        "# !pip install --upgrade tensorflow\n",
        "\n",
        "# #verify\n",
        "# import tensorflow as tf\n",
        "# print(tf.__version__)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NH2Z-ehTVz3C"
      },
      "source": [
        "## Getting helper functions"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P9twHy8-G1Qi",
        "outputId": "c1a4c67e-e11d-44e3-fbcb-77ae7083609c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "--2023-08-31 16:12:23--  https://raw.githubusercontent.com/mrdbourke/tensorflow-deep-learning/main/extras/helper_functions.py\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.109.133, 185.199.110.133, 185.199.108.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.109.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 10246 (10K) [text/plain]\n",
            "Saving to: ‘helper_functions.py’\n",
            "\n",
            "\rhelper_functions.py   0%[                    ]       0  --.-KB/s               \rhelper_functions.py 100%[===================>]  10.01K  --.-KB/s    in 0s      \n",
            "\n",
            "2023-08-31 16:12:23 (62.6 MB/s) - ‘helper_functions.py’ saved [10246/10246]\n",
            "\n"
          ]
        }
      ],
      "source": [
        "!wget https://raw.githubusercontent.com/mrdbourke/tensorflow-deep-learning/main/extras/helper_functions.py"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gu1gMQczVuRb"
      },
      "source": [
        "## Importing helper functions"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 61,
      "metadata": {
        "id": "dTI898vkVm7T"
      },
      "outputs": [],
      "source": [
        "from helper_functions import create_tensorboard_callback, plot_loss_curves, compare_historys, load_and_prep_image"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6JVfAGh5WTI8"
      },
      "source": [
        "##Using Tensorflow Datasets"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "RAZajthoVm93"
      },
      "outputs": [],
      "source": [
        "# Get TensorFlow Datasets\n",
        "import tensorflow_datasets as tfds"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LinZazH_VnAU",
        "outputId": "abcccd41-fdf5-4f1b-be24-184f2ecac799"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "True\n"
          ]
        }
      ],
      "source": [
        "# List all available datasets\n",
        "datasets_list = tfds.list_builders()# get all available datasets in TFDS\n",
        "print(\"food101\" in datasets_list)# is our target dataset in the list of TFDS datasets?"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 148,
          "referenced_widgets": [
            "16af0423a30348158f79357694286285",
            "d3481ca4b1d740438a1557b7f7318e7a",
            "636e1e5b421b4b84ad282bd7b5fec7bd",
            "363889fb320b462ea98a71ac508c9814",
            "03d2cc91c98e410db580235cf0780928",
            "83e6f7f9cf7e45129b89ce8c580d409e",
            "34bd38e5fac64f8085af23e38b570d25",
            "6a53e097d8354e0a88a95cb53c2f1b69",
            "5aa2e375c8b34969b5a852baefb27928",
            "ae0ff9e130ae4e48a796afbb833f2cfa",
            "9d1c3d650ea84257a6e0f3001899bd96",
            "0d5b1b8ba1294db3ba0fb86692d9c8f9",
            "29d22a15659945ebbcaf27a89a13b77c",
            "b3b2f72730764745ba370a3f59e81ea8",
            "1f759cb7ce3b424abdf382d4a0689f07",
            "5206303bb07547fda37d806707272594",
            "ee20a91e86654bb491ee0d19877de1bd",
            "6907f773f9e642e2a3b6597a5bc0e3c3",
            "90807f664fd341d594e22ac96d0ed1a7",
            "60f2ec19834842359e41f19f773905f4",
            "93ab551775a14d008bfdb8c67b08a664",
            "ffb1e015f3e54fecbf45e1ae50240680",
            "1861de3586db45acbfddb5a3aff39307",
            "3b6bb34cd9284777a5d5a42cbbef841a",
            "d0b1f16b3ff243ceb4a90d64c0ce3612",
            "2000cb762d4c4a1baaa4343c95820a5d",
            "7eb886c129d947c48defcc99783baad6",
            "7d098c892d254267a54765e46933fa02",
            "b08e0162001c42148bf88bec9f36fef9",
            "2d6622ddde744ce0872861296fc228ae",
            "b424eb0a47274cc0822abefe3a9311d4",
            "bf061d7e7a61404f8ec405f521235b99",
            "c6f160453bc84e1d9d8c3ab68f3f073a",
            "7ffa33ca29cf43259fa365323de6e127",
            "09618ebca4fb453f9d492bced46a4a6f",
            "7d403af9f66443cab63d62238fb37e92",
            "0c0fdfc54c1d485abe482c5b926566ba",
            "9afd82d9d6434e1e9b223c4278d02eaf",
            "1818748600f44388958dfd4ff50f68c5",
            "0ca42c19fb9d419389d6f3dbd2696128",
            "0939efe8947a44dc893da1580a4aeca4",
            "4d61904c2290432684ba7a5398633d12",
            "bbd82f1a4c284870999c855e25488f2d",
            "b498fdc1472747299067fab018efacf3",
            "f49ab68aa95a4d869c6973fe8cdc7e48",
            "bd87b229b4ea4f10842cdd9a2447bd27",
            "3c8b6cbce479466cab5a7902181c474a",
            "7603f9f135af4be891cb9065347db445",
            "792ae281d0594abd81d5218d006e98f7",
            "d37c17434377468d88b0a520834e8297",
            "5ede47b1f5c14537b641ec5ac42af993",
            "260ecced730049ec8dc8a08b6dd9c2a9",
            "9cb2d4296e42416a94506ea251a8ea96",
            "2c95db439cbe40d0ab7dcbc1e5ff8c24",
            "68b334c6e6344565af3f32dd0b138c06",
            "da6a5ac1c33d44259cd5e01d7073399f",
            "30faadb004824b72905d803a2e7d212b",
            "b2bce047d775472bad88944e10b9f9c7",
            "1d2b146a59354365a10d4745912e5cc8",
            "e9f4edfb194c45ce826f8e60535a49c5",
            "a72413f5c88b4ee59959ae8d088b062e",
            "83e95e5c41c94fe69243124a19de7a93",
            "fa6eb00a5adf4be1a41aab5fe5455dc0",
            "459818f321724e6d9ca0d668b5d30551",
            "d54ccdeed2804cb68bd7a027baee1838",
            "549c73a23f89453b9ce068398117d677",
            "c64b7a78b4484872aa9bb19e7a263caf",
            "c5402c24043b46bfa480408723b0f845",
            "bd442e88a3f8416893ee481b09c57a70",
            "56b4c9286169498f8c29fced05124ece",
            "722a0cbfb6454a41827fea08a3c2d3cd",
            "55ce6507622c4936ad7be3062dbdae88",
            "a08ae2744e664f65bb8ffbdb9306fd91",
            "4c53d86f4a4e4ec59b4fc8ae95182e3e",
            "10e55330eda8498ea164f1ecbf6580cd",
            "0d1d9ae0d830454d9df771e2fdaf2fcd",
            "719f86ba47744c0c844ebef01109f9c6",
            "675ab053feac4c288445b824ad4dbf0b",
            "29ea1116d98147d28a50720cd449e25f",
            "04a88c825af941bea2038ee29c5a9c0f",
            "2c8c131849154e62ac1a8ad4245e48f3",
            "b8d61b5fc777479c9851c339f8210a8b",
            "a8f00aff4e8c45238bb339cf2a915abb",
            "5b99433e1a1f4c13831251a6086e394b",
            "82f09c30b057455b9130cca6a171c94e",
            "1f0b8b75dd134f98ad1a7e1acd5aede0",
            "36b37aab113849b3a749026f67d66d88",
            "4c692a547b274feb98ea1a742d6e3870"
          ]
        },
        "id": "8Pn9gcEUVnCl",
        "outputId": "ec10850c-b8b3-44a3-d1fb-41179a175628"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Downloading and preparing dataset 4.65 GiB (download: 4.65 GiB, generated: Unknown size, total: 4.65 GiB) to /root/tensorflow_datasets/food101/2.0.0...\n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "16af0423a30348158f79357694286285",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Dl Completed...: 0 url [00:00, ? url/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "0d5b1b8ba1294db3ba0fb86692d9c8f9",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Dl Size...: 0 MiB [00:00, ? MiB/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "1861de3586db45acbfddb5a3aff39307",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Extraction completed...: 0 file [00:00, ? file/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "7ffa33ca29cf43259fa365323de6e127",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Generating splits...:   0%|          | 0/2 [00:00<?, ? splits/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f49ab68aa95a4d869c6973fe8cdc7e48",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Generating train examples...:   0%|          | 0/75750 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "da6a5ac1c33d44259cd5e01d7073399f",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Shuffling /root/tensorflow_datasets/food101/2.0.0.incompleteY886C4/food101-train.tfrecord*...:   0%|          …"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "c64b7a78b4484872aa9bb19e7a263caf",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Generating validation examples...:   0%|          | 0/25250 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "675ab053feac4c288445b824ad4dbf0b",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Shuffling /root/tensorflow_datasets/food101/2.0.0.incompleteY886C4/food101-validation.tfrecord*...:   0%|     …"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Dataset food101 downloaded and prepared to /root/tensorflow_datasets/food101/2.0.0. Subsequent calls will reuse this data.\n"
          ]
        }
      ],
      "source": [
        "# Load in the dataset\n",
        "\n",
        "(train_data, test_data), ds_info = tfds.load(name=\"food101\",\n",
        "                                             split=[\"train\", \"validation\"],\n",
        "                                             shuffle_files=True,\n",
        "                                             as_supervised=True, # data gets returned in tuple format (data, label)\n",
        "                                             with_info=True,#loads info about the dataset(metadata)\n",
        "                                              )"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "K_xvTyIhd7iW"
      },
      "source": [
        "## Exploring the Food101 dataset\n",
        "by finding the;\n",
        "* Class names\n",
        "* The shape of our input data (image tensors)\n",
        "* The datatype of our input data\n",
        "* What the labels look like (e.g. are they one-hot encoded or are they label encoded)\n",
        "* Do the labels match up with the class names?\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TLkmPV-JVnFC",
        "outputId": "938dd262-9fe4-4c74-c548-47dbc3bb5a75"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "FeaturesDict({\n",
              "    'image': Image(shape=(None, None, 3), dtype=uint8),\n",
              "    'label': ClassLabel(shape=(), dtype=int64, num_classes=101),\n",
              "})"
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Features of Food101 from TFDS\n",
        "ds_info.features"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Imru4421VnHV",
        "outputId": "bb5a2898-b030-4854-ae60-64b36f016304"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['apple_pie',\n",
              " 'baby_back_ribs',\n",
              " 'baklava',\n",
              " 'beef_carpaccio',\n",
              " 'beef_tartare',\n",
              " 'beet_salad']"
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Get the class names\n",
        "class_names = ds_info.features[\"label\"].names\n",
        "class_names[:6]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "mwlsdZpGVnJR"
      },
      "outputs": [],
      "source": [
        "# Take one sample of the train data\n",
        "train_one_sample = train_data.take(1)# samples are in format (image_tensor, label)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DPSoeyPfiJNO",
        "outputId": "c7a5370e-75e1-4fd3-fde5-156c81c32a20"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<_TakeDataset element_spec=(TensorSpec(shape=(None, None, 3), dtype=tf.uint8, name=None), TensorSpec(shape=(), dtype=tf.int64, name=None))>"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# What does one sample of the training data look like?\n",
        "train_one_sample"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FYf-lTiXiJPV",
        "outputId": "2992a98f-51ef-4504-8967-03d13ca8535a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "  Image Shape: (384, 512, 3)\n",
            "  IMage Datatype: <dtype: 'uint8'>\n",
            "  Target Class(tensor form): 70\n",
            "  Class Name(string form): pad_thai\n",
            "  \n"
          ]
        }
      ],
      "source": [
        "# Output info about our training sample\n",
        "for image, label, in train_one_sample:\n",
        "  print(f\"\"\"\n",
        "  Image Shape: {image.shape}\n",
        "  IMage Datatype: {image.dtype}\n",
        "  Target Class(tensor form): {label}\n",
        "  Class Name(string form): {class_names[label.numpy()]}\n",
        "  \"\"\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Rzep5QPAiJRT",
        "outputId": "4bb982d3-c8be-421c-8633-4e287aeb4e7b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<tf.Tensor: shape=(384, 512, 3), dtype=uint8, numpy=\n",
              "array([[[230, 229, 183],\n",
              "        [231, 230, 184],\n",
              "        [232, 231, 183],\n",
              "        ...,\n",
              "        [232, 233, 202],\n",
              "        [229, 234, 204],\n",
              "        [229, 236, 205]],\n",
              "\n",
              "       [[228, 227, 179],\n",
              "        [227, 226, 178],\n",
              "        [226, 226, 176],\n",
              "        ...,\n",
              "        [234, 235, 204],\n",
              "        [232, 237, 207],\n",
              "        [234, 241, 210]],\n",
              "\n",
              "       [[229, 229, 175],\n",
              "        [229, 229, 175],\n",
              "        [227, 227, 175],\n",
              "        ...,\n",
              "        [233, 234, 202],\n",
              "        [232, 237, 205],\n",
              "        [235, 242, 209]],\n",
              "\n",
              "       ...,\n",
              "\n",
              "       [[119,  97,  58],\n",
              "        [131, 109,  70],\n",
              "        [131, 109,  70],\n",
              "        ...,\n",
              "        [239, 241, 220],\n",
              "        [238, 240, 219],\n",
              "        [238, 240, 219]],\n",
              "\n",
              "       [[120,  98,  61],\n",
              "        [133, 111,  74],\n",
              "        [135, 113,  76],\n",
              "        ...,\n",
              "        [240, 242, 221],\n",
              "        [240, 242, 221],\n",
              "        [240, 242, 221]],\n",
              "\n",
              "       [[136, 114,  77],\n",
              "        [135, 113,  76],\n",
              "        [129, 107,  70],\n",
              "        ...,\n",
              "        [243, 245, 224],\n",
              "        [244, 246, 225],\n",
              "        [245, 247, 226]]], dtype=uint8)>"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# What does the image tensor from TFDS's Food101 look like?\n",
        "image"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PTYarXtpjWDm"
      },
      "source": [
        " They're not normalized and the min and max value will be 0 and 255 respectively. Since we will be using EfficientnetB0, it has an inbuilt normalizing layer so we dont have to normalize the data."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lssILnzziJT9",
        "outputId": "9296564d-733d-4daa-84b7-8ab8f409fdc1"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(<tf.Tensor: shape=(), dtype=uint8, numpy=0>,\n",
              " <tf.Tensor: shape=(), dtype=uint8, numpy=255>)"
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#min and max values of the image tensor\n",
        "import tensorflow as tf\n",
        "tf.reduce_min(image), tf.reduce_max(image)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mmxwYs6Jj_QG"
      },
      "source": [
        "### Plotting an image"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 428
        },
        "id": "92PvvAarj_oz",
        "outputId": "5079813b-ef40-4a25-831f-7082b139a540"
      },
      "outputs": [
        {
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgAAAAGbCAYAAACyMSjnAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOz9WaxtaXbXC/6+ds651trNOSfiREa2kX2SCdcU5mJuIcqmuQYMWEIqWYIXG4QMMljmwUgIIWxLFhYvBmFRpgTIdC9IPCAsjGRZ4qouVEJR2Ne4yYTMyIzIzGhOt9u11pzza+thfHPtCEzZkZSv86pyjdTOE3vt1cw15ze/McZ//Md/qFpr5WhHO9rRjna0o31dmf5aH8DRjna0ox3taEf7jbdjAHC0ox3taEc72tehHQOAox3taEc72tG+Du0YABztaEc72tGO9nVoxwDgaEc72tGOdrSvQzsGAEc72tGOdrSjfR3aMQA42tGOdrSjHe3r0I4BwNGOdrSjHe1oX4d2DACOdrSjHe1oR/s6tGMAcLSj/f+xvfTSS3zXd33Xr8t7/eAP/iBKKZ4+ffrr8n4A3/It38K3fMu3/Lq939GOdrR3bscA4GhHO9rb7K/9tb/GP//n//xrfRhHO9rR/ne2YwBwtKMd7W32GxkA/PRP/zQ//dM//RvyWUc72tHebvZrfQBHO9rRvn7Ne/+1PoSjHe3r1o4IwNGO9jWwpZ7+2c9+lu/4ju/g9PSUBw8e8H3f931M03R43k/8xE/we3/v7+Xhw4d0XccnP/lJfvzHf/xXvF+tlR/+4R/mve99L6vVit/ze34Pv/RLv/RVH5dSit1uxz/8h/8QpRRKqV/BIbi6uuK7vuu7OD8/5+zsjD/5J/8k+/3+bc95p8d95AAc7WhfOzsiAEc72tfQvuM7voOXXnqJH/mRH+Hf/bt/x9/6W3+Ly8tL/tE/+kcA/PiP/zif+tSn+PZv/3astfzkT/4k3/M930MphT/35/7c4X3+6l/9q/zwD/8w3/Zt38a3fdu38bM/+7N867d+KyGEr+p4/vE//sf86T/9p/kdv+N38N3f/d0AfPjDH/4Vx/zBD36QH/mRH+Fnf/Zn+Xt/7+/x8OFD/vpf/+uH57zT4z7a0Y72NbR6tKMd7TfcfuAHfqAC9du//dvf9vj3fM/3VKD+/M//fK211v1+/yte+wf+wB+oH/rQhw6/P378uHrv6x/+w3+4llIOj//lv/yXK1C/8zu/86s6tvV6/d98zXLMf+pP/am3Pf7H/tgfqw8ePHjbY+/kuGut9Zu/+ZvrN3/zN39Vx3e0ox3t18eOJYCjHe1raP91Nvy93/u9APzUT/0UAMMwHP52fX3N06dP+eZv/ma+8IUvcH19DcDP/MzPEELge7/3e1FKHZ7/F/7CX/jf5Zj/7J/9s2/7/Xf/7t/Ns2fPuLm5OTz2To77aEc72tfWjiWAox3ta2gf/ehH3/b7hz/8YbTWvPLKKwD823/7b/mBH/gBPv3pT/+KOvv19TVnZ2e8+uqr/833ev7557l3796v+zG///3vf9vvy2dcXl5yenr6jo/7aEc72tfWjgHA0Y72fyB7awb/8ssv8/t+3+/jE5/4BD/6oz/K+973Prz3/NRP/RR/42/8DUopX5NjNMb8Nx+vtQL/xz3uox3taG+3YwBwtKN9De1zn/scH/zgBw+/f/7zn6eUwksvvcRP/uRPMs8z/+Jf/Iu3Zd3/+l//67e9xwc+8IHDe33oQx86PP7kyRMuLy+/6mN6axDy32Pv9LiPdrSjfW3tyAE42tG+hva3//bfftvvP/ZjPwbAH/pDf+iQaS+ZNQh8/hM/8RNve83v//2/H+ccP/ZjP/a25/7Nv/k3/7uOab1ec3V19d/1WuAdH/fRjna0r60dEYCjHe1raF/84hf59m//dv7gH/yDfPrTn+af/JN/wp/4E3+Cb/iGb6Dve7z3/NE/+kf5M3/mz7Ddbvm7f/fv8vDhQ954443Dezz//PN8//d/Pz/yIz/CH/kjf4Rv+7Zv4+d+7uf4V//qX/Hcc8991cf0jd/4jfzMz/wMP/qjP8q73/1uPvjBD/JN3/RN7/j13/qt3/qOjvtoRzva19aOCMDRjvY1tH/6T/8pXdfxl/7SX+Jf/st/yZ//83+ev//3/z4AH//4x/ln/+yfoZTi+7//+/k7f+fv8N3f/d183/d93694nx/+4R/mh37oh/i5n/s5/uJf/Iu8/PLL/PRP/zTr9fqrPqYf/dEf5Ru/8Rv5K3/lr/DH//gf/28K+Pxq9tUc99GOdrSvnan6VpzuaEc72m+I/eAP/iA/9EM/xJMnT/67svSjHe1oR/v/1Y4IwNGOdrSjHe1oX4d25AAc7WhfJ/bmm2/+qn8fhuHYn3+0o30d2TEAONrRvk7sxRdf/FX//p3f+Z38g3/wD35jDuZoRzva19yOHICjHe3rxH7mZ37mV/37u9/9bj75yU/+Bh3N0Y52tK+1HQOAox3taEc72tG+Du1IAjza0Y52tKMd7evQ3jEH4PXX/hVKKZSq1FpJORLjTK0JbRTeO0qFnDXWrCjFQfFQDYWAtRVVIadMzpkYIyVnrLU4o8k5QU1YU6mlkvJMKRkUgMEYQ8iRECeUAt85tGnHQ6aWBIjGuNYKRYZimGdH153QdZ5aKzEGaq0oI7FPSpmcKjlXQKONxxiLUo5CoVJQ2qIwlFLkOFVBqYKxoHVFa0WtlVpBIa/XWlNyYBy35JIYhoG+9wCUklFKYa2llEopCoVBawtVkXNBaYXSmloVWmuUkn+pClBobam1UkpFKYXRDhD1tVITqUZqqYDFWocyilIjKe7Yjxe8+eYXuL58jNUFqzTednjb453DuCTfzxi891jTo5SiZEUuBWscWmvmOZJzRmvNOI7M84y2HVEpcgbVjrWUilYG5xzzHACFc4ZaK2Ge23sorKucn1isqzjnAcWCTynjUSiur7cMqwGlHCnJZ2ttiKlQMmilAQMVQLc1a9BaY+2y3AulFJSq8piq5Aooh9aOWmrTq7cYY1AKVK0oCjmHtuYrxhSM1TinsSqRYiDMCVBY1+OcJxVFCBHruvZFFFX+AQWFiqoGg0MrQ4wT87RHG/BWU2uk5Mg0bdneXnN7e8nFs2c8efwmu+0NpcDuKpBzxXvL6dkJq76TeyJFlFL0fU9KmZKAqrDG4azHWct60Ax9xVqFHzq0MYScMdYybE4Y9zNVWXx3wmo4oe9OsNbj7ID1FfQIKlIVxBjZ7kbGcSIXTYiZq+sdT59c8/LLX+bi2S031yOPH18QphlrKkYVlAJrLdbLdaolEULAOcfpyQklJ6y1PHf/Hn3f88ILz/Pxj7+fd73rhJP7J/iTE774+mP+6T//SX7uP/0yynY423F7dcvt1Q1pLHzqEx/m+773z/Gxj30E5xypZFIqGOuYQiHnyrPLa378//5/4z/+7H+gGzzD4FlvBv7oH/nD/IFv/Va00mjtQHVo5aGCoWJKRueIpeKtJoWAtppSNbFWqrZEVUlZYajYWFh3ljDN3NxeUkoEU4klE1UikClUUslyrxiHVQZyQM/PyPGWGCLKdwyrM2KFq9sbpjBTc2Lc7tAZ0pyYbmZMtey3I1957Sm7CkWZdj9n5nEip0jvLEYVSpwxNbHyBl0S4/6G3hoevutFTk+fp2rLLo50a8dzL95njDt2+ytO1x1xe0NXCno/83BY0cdCl+DEeq6e7nj2ZMe0HwnTxDhP2N7iTtfsdaKcOPTJis0L97j3/APOzs+5d+8e665nigGUwfcDKis609O7AVU1ZRd59sYjfunnf4lf+sVf5snFFefPv8j7P/wJPvKbfgsv/aZPoc7vUYYO23tQmVwSKNlzoBJTxhiHMp5aDDlralGyfwAaWaPLfiL7LHIDUw57CrVSa/NBRqFUptRAJYkbq/WgjmlQsjfpSs6ZUjKlVtBKPqtWqBaFRxtHqZVSZS+jKHLOWCxUKBjQGpQiUslKgda8+8Fv+zX9+jsOAGpNlFKp1IMz6rqOim0nQUGtlFpIOVGznCBFoZRIrBIAlFzaPrg4tirTwlTFWUAZjAWUpVY5SSmDNhqnHUpBkTdvDqCiDagFzFCyuVrtwBhK9Sil20kuhwtQ28XIKaOUwXsnJ1eZduEVtcgGbZQcx3I84oB1C4YkKKiLwyHK55TKMPRY69FFNrZSoJRyCAC0tpSiKBmgLY6qKAWo4nSWx40x7dhVc27/1fWholCHc6CVpaqKwrZj1mg0xliMtuz3M6+88iWm3S3WGE7XG05W91ivBzYnDt9pvO/khrARYxxa6eb8HdYawB6OzfselMJYxy5kapXjjDExT4GcMwI4qRa4yHVyzmGtxRiNsZWcI0qBVhVjNVoZKhJ8AJycnOKcR2lLzrLulJLgIacKVV6jlKZWyLm2c17IqaI0LIGF1qYFCJpKpQDGgLKWFDOqgKZitAEqpVactiilUWQKEUql5kIshVrAWgcYjPbUYqmlXYNqqYpDQLOsxUyFmkm1oqhQK865dj9XjLbkCp0f8Pcs9+/d493veje37/8A035PzpWcNCkWjFUMQ4fVimnaM017Ss6s12tyLtQo31tVLdeiVKyJeF+xncV3XtZMCKRaCAm073F+xbA6Zeg3eL/Gat+ub6JkyCUxTRO7aSTGRIiZ3W7k6dNLvvjFL/P6G8+4eHbL7c3EuE+UooGK0QprLForjFE4Y/Gdxbk1Rmv240jvHaUYcs3M80RKgRgD43jJe95zj0/85k9wz63Y70ZSSFjjKAXCNKMqDP1ArCMPHtxjc7rGdR6o5BBw2qGBlbMUb/jsZz/L5cUFAM7KfXOy2fDSBz5I3w1QwGhHypqSi+wRKGrVFIw4bRSxamzRVK2pRfYdZw19ZyT404GQArtwSywBKJRcyKqgtMFU2Z+MUhKMhkKsBVUyZIe1Z5IooZlnQ4gRkzvO/MB+d4WyA0YX5qRQXcEZT0kZ7SDvEoUi+xfiiGqBFCLoiioVawwaTc0Vg2HoB1ZdR40zxmUe9I6uc/j9iKPQZ01+tuW5YcCUzOXNDW88uSHc7mFOnKzWjPvIPFVOVhuKN+hgOX3unOff8yK508y2UNeO/nRNtYrbmxvG/Y57J6d0XUecMu5Mk1Jlt78hTJFxu+fRa4/5wuc+z5M3H7M+Pecbf+c38dHf/D/w4gc+zOr8AWpYM+pCUZGUMrKjZ9AV2nmmJa4qR9lalWr7ZIfWlRSmFgCog+9aAoJSFND2NlXQyrQ9W+71Uguoetj3JIiooC1KQc25fabmbgRHPTgyrQ3aGFlpVfxc1art8RqVZZ+ti19SgDZo+98e2PVf2zvvAlCpRSZQSr07EXoZHtKin1ypKt45em2pNaFKJReJdozSKCqlZmo1aCOvV0DOmVwzOae2Cep2Mt/i9RQSEZWCUhqjLVVnSklQC6VUchEkwFrTHEFuWV1zpopDQKPbiVZKk0u7zIrmtEv7u0L+p5vzqOIEamlRn8a09yhZLnaKGaqRi6gsVA01oXAoNDnphgDQAg7Vzq9G6QrtPMtny7lfItDFgdydlkILF+QolaYCpRpKBV01KINWnlIUF0+v+MwvfY4nj97AO8f9s3ucbR5werLmwcMThrVn6Fd0XYf3HV03MPRr+r7HWoUr7WZAzllFMnFtHYPqMFYChpwLIcQWrBnmOZCzBEkpJXKKlJLJuZBzpl8vSIaV86SdfKskTtxoQ0pVzr82gohUMEqhraaWpaol/1rTTnutEjC0gL0CJUOsuf0to61G14IxDnKmZKhaQzUS7JWKsQqjFVTZOGspVKWpxVCrRmvbkBxLrYLYOCvXgCrXZwk+SymkmmUj1pBLxmqNcxLo1iIbSymZUgxaaXEkboN3G+b1RCmFzq9JMVMo7diSBADzKIFXLjivsSuPNQ6jLapqci2EPJPqzERhN8t61qaj6zt81zEMa/p+wNoeVS0aA8qRc2acI3Haggrs9lsuLi+5ubnl4vqGR48e8+jRU1577TGXF7cMwyng8dZysjlDa0OYd6AiuiGL1EyOFaM01is6Z9FKgn9SIswTzllimLm9fUKYbhk2p8zFcn1xC0kx2J6UYZwmSsyokrFW8+L7XuT0wRnJJPIc6a3CK8UcZ6zxzCHx+c9+ht3NNeenZ/jeUUri3e96Hx9+6cOopIlzIFdBBLW2oOR6K20BTW75oh3WDR3NWOswJUMpaAq5JNwgAfhcJrIpGCXXuCqFtgZTtPiMKiu15gKpAI5kB5I1kvDkgs4VlwOuTvRAbw37cEWtM9oWcJGYZmLZoVXBq0pKBUrFNPTMO48GOm/JYSKHPSkXOut47uGLvPD8A9Yrz9Wzx7gMq+phF5j2e1bWsq5wfXHBk2lic3pGGieqscTSM5ZEoMfcO0UZQx1WbPpBrquGaT1gV56uN8w1MsaIUwaLQuXE9uoZu7lw/eSaL+wjNzc7ppi5urrl6voGpRTDsObjv/VTfOijH+P9H/4IJ8+9QO3XRK2YyyjXJUPOUGtG6Yp2tgVwGqUctcq9plRFFTnvpaQGuCpqC86XZEqp5aeSDwkcgty2xFCSHEEQa1WHfalSJdHUNNRYHXyO5NG57S2qvU+WJIh2HCwBIhS1JLPyHAkECi3T+TXtHQcAIY6SmRhDSokQEkopvLdYpw8beC4Z3RZ0qQLD6xbN5CzwP0ofNt1SMr7BwdRMCOHgyK2V9wZx1uVwko1kDdpSaibGLCiAMtSqqDXLPp+XZLkeoiuBjDXL9ShFIracc8sBJRIzqkoG1soMSsmQE62RDB1BOkqJoMBajSSKGm0UxrhWVjAYrVAskL2gC0qJY6mlNljftKxKtzizcDj6qt7yc4cK1FrlfdqCUAtSgThkMYHgay1oTYOAO4zp2e8Dz57dQKk8fbzFqjdxznBy2jGsLJvNKSebE05Pzzg7v8e983usVyf0fYf3nmEY6Loe6xrKoCop1oNz1dZgjKPvfQtUKpv1KblkUoqkFCgpS8kiJUrJdFajTUVrg9GaqhQlF2pDSuYpUNsmLJB+yyaNlay7FnKSIFBpjTXyPK01MqNGIgBBbRqCkyDlQo0z2UasMZTa7i6WyLyiaiXqijHiyEtJsgFY0xAaSCmCSmgsVcn310YTY5L1yRLEybUyB8RKPk4rift0W/M5pRbBWFKKksmhyFlDke+rbUetgZKlZGZNR7929OuNuCQtm5WuEpRRFDlVYkp4lUkqE9LMNM1oMqtVz+npabu+Hq0sKRT2t3vmeaQmmMeZcXfLbntByXuubm948803eeONN3n85AkXl1fEJOu/tnKQUrJBKaDkRN85tHGCuijVgtqMUhVNpXOCLjonQUsIATB4b0kh8ezJNb/wv/0yr37lCbchcvHsiv00Uaqi6oashJl7Jys++v73cn/o0SnTdRY9J2qcqAmc91w+esbnf/kXmW9v8euB7c0tSine8+J72azvo3Kltw5V5HYt7d5cygJVC7pVlJTuciwYZbBGAjtyplMKOsWUZ4qKYAo1Z7noSspWpaoD1GuUkdWdE1UVKWUZQ0SRUsLipPRaZuZ9YZ4nStHMUybmJMGgMkxhZJwCxlQ2vSHMiZJlHck+qvDW4rRijplcK65WfMqc1soqRtKTG7ppxJPI15n9zS1pPzIbi1eGnDL73Zah29APZwz376HXG7YxUp1BO02MM7lUSj9IGSYELrcjahypFsa4w3rN2cmGwRvCeMubTx5z+eYz4tXMuIuEXBhOzggp463jpY98iJc+8mGee/FdnNy/j+odj/fPmMcbVL9CO49RoGNBPHsFo7HFoqxHGdfQD4/RgsoqaAlKoJBwXtahapgJlEPSK2UES87xcE8rJWhrVQWjAWWaI2+l4pZE5mVPV7Zl7hIDVIyU8KjkWgX5UZqyBCJFCzJNhbr4LHVAESpvgRp/DfsqAoAdOXtAk1KmFoW1XuC2OZFLal+yorRA4rXVsHLVVGMO8Lc2RjbQmtBKYGKlK+YAYSu0MVjv7qBvpVom7qVOoqGSySETY8JWg7NSR1e1tGBKkzIYo94Cob+9BCBZvjyu0Ki2WZZSUBqsWxx3EidjDKVI+UGCnNIy/xat5YRStn1eq+2bVpvP6bAItEbKDiwwtqSqtap2DBV04gAHHerh9W3fQympg9dWbxcTiFfgSYlEjZFjKSRBKLKB6jG6l2AsakJMKCK3t1vQCWOf0HUd62HD5mTDMKzwvuPevXOpz56e8eDBfU5ONqzWK/peaq++61EqorXBWoe1whmABT1SWO3xvRPUQC9hWibPQSJodReYUQvKVqwpUAMpJblxij7A+8UossmUAjkvNX5FNpWUJVDq+wG9VIrMHeSWTEanSgyJmiNlyfKWQDaVtwQLgVIb30TJdTRG4XtPzomYC1pbjBEEQNZUKxsog2pZF0YfgtEFSzHakVIkxijcAxQhFUpKsnZyOaAAWhuc73CA7QaUdYd1ZbTGmLa5K3UITsiyTkqu4kBSJpKxqtBT2JzKBum8EX4KlavLG4wy5JAZdxNxisSY2d1subm64stf/iLX1xc8u3jG5fUV11fXjNOIUpphWOO6AasLtcqm542TUpTVKBVRNaKKxlqD9gal5J731h74LH3nUcVSolwf13m6foWtiukmMKan3OTEVMGu12SAGCjjDqMqz59suKdgevVLmFrYvPACKkTG/US3WmGGju2j19k/fYRXlRoDKhdO7z/gox/9JBRBmrzxULOsUxLlANE6ClaCbqWZwoR1PYZMyRMW8FZR4sxue82OiPYGTaakQNQFtG+BsyI3pBF0ywJBUdC1YookHTlEirIkMpnARKKQuNndIBUeTwZM5xnwhFmTxkRmy1AnSiroAuSKroohGzosttMMq1NMiYw315iLJ6SbK7a315xuTuk7y36/x6XM6cm58LJqYfPcPc43L+HWa/a5EocOPXTEWXgQrhR00TgU824mq4Q3Blcd8zwT08w879inmav8ZeJ+C2nG1Qqp0hXH/QcP6U9POX3ueapzZKs5e/4B/cmabdhx83QkW0v1HapfQdqTgV4rBouUFLWhasjKUroe71bkuYLuwVawWhI25RuadhfoHyBwzGEvXhKQO1RPtYBWSoxLll+Rfb2UAlpRlXj7XHNDBdVbkrkiQeBSakaDFt+UkeTO6IWjICVGrbS858IzeIe9fV+FEFAl5UCKEsk4O6CURJMxRZzV7YtI/XbZMGuVyF5XIw7qgHUIkU4i/4xVbTM0QoRTDQqJsQq0qrRA4bqduJxJRaIf5zqs0RiznAB5z1paZthIebXBvVK3b2jEEipoqY8r7SilkrLAMFZbaimtXtQ2MioocN5RimpOYEEflsxdNlqtayOUqAYHycastUEhdRqpKTsWYolWgjQc4BxoKMEdfl0PAYAsysXhwZKdqBZ5tuCmZeg1F8IcmKeIqg6r+8MCRRdJRmwh5cA0RvbbPdd6wpjLttgLwzAAcHJ6wv179zk5W3N+dsZ6s6bvV5yf38fZjs73DKuBk5MT1qs11jlqjWitcc4eyi7L8SkUprcHxEjKKwshT77rZiNks5SXTD6T01JHk+BM6xYANM5BSoVSkqAKprlbXQ8O2DmFVg5noNaExmCMhZbZpCjloyzIKSktjIGF8CM3cimRgsKYckd0raCUFd4CGrRFG42xC/dBoP1SWymr0L4DDQVxpCIBjzEOZy3eusaPgEylH3oyvp1HgTArmZIyIUtQVUuFIsjMEiTllCmqgJbAQduGcIXEOE6UlBmnCXJm3s/stiPT7Z6b6y0XT59ycXnJa2+8ydXVFbv9jtqyJGtXdL7D+R6lDKuVo6KxjZyHMhilyblSD3wYuceVrjhj6LqOcdyiq+RcaI2xS4alMGgpsTlDCJnr/S3jNFG1BNpp2qFTZK3hnMrjX/oMP/fFV1hpzUsfeAmc43Y/oXtHvznjs7/0y6SbG1a1ECqsuoGPf+QTfOhDHyNnQeYKmpoq6IIyRmqyzRFISVgdEBfvDTUkKJmh98zbHZ//z5/hlVc/z2/9n74RYwfZL/JSWqpo46hK6u9oe0A9TQsYU46omrC6Uq0i50RImRRnqop0K4faRU43Azol5tsbdCpslMYphcmBEidqmSVbNIpaMikmNIpV1+O1QadIDjMmT1KaCoEwj7w5Jny/ItXEyfkJm/e9h1AjuzDR3z/H9j2xFPI0kXPA7EGnjMvgtWaoGqfkus3jyNPbLbv9HjSkHCg5oHSkxJGSZk56w/nJCVY7vB/AeMx6xfrsFDX03ISR2zCyvYngFMpZsIYcJtJ+R9WSeJROU53CdU4SOiQQDrMnuhHrV5AqqVRyzIDHmB6lLGhNyQm0QqMFfVYZOWP6bU578RGlaNlra5H3UwsCfYf0VN3Qoxa4i8n6UUrJ+pLaantcSrgKqEpQY0kdtYQgSsuO1LgHNS/kxF/d3nEAEFPAaIvWjpJlE6RWSpYaiNEC60tNVP4VqFuIEKo5ttpcVKlZbn4tN30rrVBbDX6p2+ecsL4XKCSDlnC4ZX60bEuyqFqWekqry6qKNvIVBV5s5BdlUOUuABBoXx+cqQIJJnRtkCTtM5PUe1p5wFp3V1dqF/iOJdpqMkt3gJIL69ySDbbQcClrKPm3FIG/aQuscgfv33VtFpayhiAP4riWhVQaxwKV75xn+14lRVKMgoQZuZ4xCDKRkixaiyFXIWEu9aq6ZCQ1c30zklJiP0aurrcoVfHeNwTAc3pyxmq1ZjWsWa/XnJ2dce/efdbrFV3f0w8964YYaC03i9FSOvGNqa9a5mqMxZq7ZWqMaUSvuwVeSpGFj6K0Wv/CDwHaGi0t8Go3LPL7ct20NlhvqCXLOjdGnGVNqKqRcK1inadkYRKnHGWdm4rzikJjhhsjdVYSSunm6G373La4i/xIIqCFREw9oAdLFm+NpfMOrWgQZQsYNegiuajWBa1K45MkcsyknIgxipOvhZIrJRVyLqRUSCETU8Q7g/cShFknpYwYI2GeKbmQYuLm6obHjx7x6M3HXD294vLiiquLa7bjSNGeREWbHtfInFoh5D5rQElg7bsBY6RzI4ZIoLIaHNZ4nLN4YyhFnJlRGqs1qsi+kmIkJ9lyh046VWqt9F1PtRrXezYqsZ1HxjihU8TFhNeKB0PPu9DsPvd5Lo0lKM2rrz1iMpaxZG6nPdU5Xn92yRAmgayVoXjLRz7yMe7dewDVYDBo7dG2ktNEIUiykVPjQhUoGqPAuYqthTnuUSVye3XD5z77i3zh5f9C3zvON/coWjGWEVcduUCuFY3GekdSGm0tOWayihin0RbSLCQ1YZjLZ6paUSbjaqLX8HBtsXnPeP2M8uQpeTuR5oje7jmfJuo8k2KQLNIKwTTkQsqFmDMBmMJECDPagOscIc1cpcizy5G57PFrx7tOTknGMGzWFJW4dQZVE5SEs9DNCb2f2aSCrRqNoRZNypV5u+f6ZsuTpxfc7vb4vkfpSr/y3L9/wubec6x7y2blyCkKtyQmQojUFJiHDhUG9jnh1x1eeSFoFo0KLch2nSDRVHKC2StK8lTvqUqSglwFUd6cnKNMj9Y94KE6tO7R1mGsoRqNNpqqDbpqKlrKTC1r12pJ7pZggNaBxSExe2tJvr7NHxnxo1XKnOZQQjg4Hdkz5BY9bB2yG7cSadWoIilJi0MWVsGvae84ABj3M6vB4ZyXNr2oSLVidY93hZxjgx4kIFBvrYdoOQnGqsMXrzVRKQdCIY3MUEpp9XdBC5QWR7CwuZcaqlIGazS1yobWknJsy+StVgKFIfXOSj5s/ovpVrcTJyqb5+LtjZWaSmlBgwQkEriIc2oHTX0bG/1wkWsVWFM15jutLLLUQlvtRqydk3bRKg1yZnH+hyNGoGcOEI9qKMFClKwNGygloowRB0ZDLwrkPLHf3XB7fU2YZkquGOOwVmOVkNWU1ehSMFrIeRKn3HVAWGOpdQYM8xyZxpEirQwArPoVne/puh7feYZ+YL05YbVacXp6yuZ0w/nZGZsTKSl4bxvZ0LIaBnHyVh7rug5jFkZrlWCvrQ2tNMZIe+FSJiqoxi2pbe0ZdONFlNayKAFDQ0yqOMishFeCNlgtkb9wDWqD01udv92FuQjyVYsEEs41KLAFJlEnVO1AG/q+P3BCZENoKIA2GCvwXU4ZrYS0ujhRKAiK6FAqo5CAVEpJWYLtmtnPwptJKZFypsQg7baNXBljaqdPMgnpDAGtCjUlYpaAtkZDoLLbjVxfXTPNMxfPrnjy6Alf+crrXDx9xrgLxJjQxYCzFGVwXSeBLbKxSUlEuCGhoTUOuR+LAjd4tFatzin3obEWlSoxI8GLmhm8x1rLPI1M+1HWifUYpUkUlFeEHLBVsTLQh5l8fYsthVM091YnPO87HvYDPkYedh290aTbW6Y5U60l3N4wk+kUvO/effLFJTdacXJ+zsc++lH6fiBnRU2VWAoWSEuSUwsGYc7r2lAlBeSI0pCnG3bjnte/8iV+7uf/N+6fn/O7/i+/h83mHlOYmVTGEA9oDEraHTVCTM45okqScqgSlrkiQ45C7KwFXRU1JfI8o7Z71nHP/uop29e+zHR5RbrdMl7d4tCs+7UgTJOUMKpTYBy1aGKWtkhlLbXbUExHILHNmZspcrFP3ATD9W3GTYm03sLmmncZz3rdk+aJzih0LLiUyTe3jFdbTMjYqsB6quuYY+HpxSX7MWB7z4OTE1w3sFoN+MHRDxalMsVWStdRXKJMgUePH3Hv4UPcasVtTsw3N0Rd0XlG7xWroaMWCcZOT84463pySlxeXVM2nrp21JSprcU6tUC4MhPmgHEDnRuwftPujz3aOKz3YBTaSiJStQZlW3LXOogW9FhZ2RtqueN2tedKO7wA+FVBDYmqFU4bciktGdQtKBE0zArZhFSLZP9qKR/rhopLmYylEwChNRpxnO/Ir7/jAGDoT1r2rym5YRhVmM+1VFIoLYNRFFUwS0ZdObi1BX5fNglrHFAIQSJSjMFYKRXk0hxi6wJg8XmHbBjknSUCowUPsRZK2+Zyks+ptbZ+bWF7hhBAwXq9Frg/JUpupDErkVxKmVozxsnxLI5YN6ZGSo30oXlLp4EQdUxjWgtasGRmsTkkyf4lW5c+8lqUZJJ6qQNlIaG9pbZ0gD6NbJghxEZAab3TVV4PUl+a54gzAqloJbAoqlLyzP72itubK1IIrfWqI6dCKLXhJ4DSwqpXmTAnrDU47w+dFPIcQymJrl9RSmIcR6yW2vXN1Q2lXOO9aB+kXPG9ZzVI5t+vBvq+Y7UaWK0HVqsVzhnOz044Ozvj9PSU9Vq6DkBIluJIDc7ZQ7a6EPyW9aDN0nUhiE2tlaolgNAKOu8IIdI5CRxCmIUDYQV1qagWMEi2bR2trCU1uBhFX8GpSscdEawkieYXPsl6sKRVIiUhszrvmedAKQXvOpa2UKPF4VebGiJR2xVoQSUFaDAv0sYU5pEwj60lbkZpRZhnKY2kREmZJNDUYc3lUqStS1u8H+Tzo/ApaDDw7W7H9c0Nt7c73nj0mMuLa25vdmx3e3bbPSkWFA5jenHwfYdyHVMMxFzpvcd7Ib12XYd1wpbPJR86cnQL4OYQOBl6CWlzJtWAVoq+8xJ85krXOaw2pFzQMdM5h1uyH6cJZRSnGDJmt+VsnnneOM77nnvWcaINK6XxOTP0PZtVT6mJm+sr0gy7fUCTIQeG9YrNySlzqYTbHS+99BIf/sAHhFhX7aG0qGh121owpmINeJNQJUIKaF2Y91uqUrz2yhd49dWv8OajJ/TDwG//pt/J6f2HbENAK4/t1rhYQUdUSpALhCDoXdLolDC1YjKQK74mOpsJ85Y4zqQpMO1GfAEXZ24vnjDvrhlMQV9u0dsZk6D3Pc50zLmyPr1P6pKgT8ZRlCFOgd00EkrB6A6jPJOKbCeB0SddudwnrB1YDYIsXT+65V53Q/En6KlS80zJAVJkN+6Yt1vyOEGUdVicI3WeCLBxPHjxIf3mDGUdKEvX9Sgjics4bhlLJBVNTorLWEi2ozs9x65WRKWI455YC2E/0w+eyowqTfsiQRojYRaEeZsi42TpB48xkyCB1gmp3cK835HLntkN9KtZUNGU0cpgup5MpRsGbCsnO99jdOMvWUtJEpOhNUZLh5pq+6PRg9wbXUfO4nd85xnjjLbS3ppTxhknr80JsuDYtSpSSDx68oRqLA/e9QLZaGzfS0lSSdIAS8kb4RZh7hLrX8PecQCQi7DJVS3kLIzskivY0m5u16KOcldjb4lHqRmlFaWku1Y8bQ5BinP2QKqotf3NtEwtVxHfaZCICOSoOyhVtfqIkYxGtYBAVYXWpZGxSuvlvrO7LoR6cMa1NEEipKuhIvVRo438ONNQmUxMUp7gALGDwjXShgQ+B8JZqwFJXfeuPtRS/Aaztxpo+29x5suxLuTIImIRubZAAlg6FxYomYXcqCg5oigYXQEhrqWw4+bmkt32BkXFW4s1TfegWnIphCRZv1EatMJZdQiKYgj4TtoYTSunaKWoRrQWdEWcYcvSl6+ZUyaMgRgSNzcSRClVsc7hu4XRXxiGjtOTNZuTDev1hpOTDV3X0Xee1WrFZrPBOcd6s2K1Wkm2rDWd7zBWWm60sbIOjMU7f8jcdVuf4ighJ2n1ct5jjCNGidprK4+ICJDoMjRwSxycaU67LtdRQVEYbaRjoZZGFpX7wLaecmul71wbh0KRWxlAa9FPEKh7FkIt0tZaSySliRB27fHEPO6Yw0jOiRwjSlXCNDOOUyNISsBotcE4jzOWEBNpXjgJ0sc+TRPzFBjHmdubLU+fPePpswv2+4ntfqIUmEPGGo+xJ63LRTZOaxxo0ErhncEZzWoYcEbIm1pVTM2yVkyHsRrjjHxnrfAWnKa1BEPJkc551usVlip15JSI44gOgbUxuFLRIbByvbDITSWnQI0zLkfOhoGTtWejLF2u+FzYOM/JZsB6w5xmHl1c8vjxM3p6whgxptJ1Qk6rKdFTee5kwyc/8hEe3r9H8h1TSOSYhMCpFNa08hsJlSKqFMgj8+6aHCcuL57y2uuv8/TZNc8ub9FuzW/65Kd48Py7yMowF6S7qRGdrVG4UJiniRJ20urZ94KQZAkM0jST5z03+0vm3Q3jbuT62RXXz67Y9APnJ2vSODKNt0wGEg41nNKdeM76AdCM84zpO8p2R5oTSgs3QylLrz06ZlKu5KDQynPaOwkcZ8X9PjHdRs77E8xQoUbMdSA9vubmGey3V4zjDX3vMFozh4kYA9Y5VusVq3snbM42FGPAOPzqBON6UuO8zFVJt0OpVOPAaKak2e4Czy73vPDwBYzpmKZENhptB3pnqGGS+rx1WAWJiSkkYtxRC6xWG6YpUedEDlLazVVKA13XM6wHxjmitOidpDjjfY82mlw183RL0RAmCdqt9Xjf41yHtha9dK+g8V2H9+6AEgphXUpDxRRyDBQyNRtSDHjlKFlhlcHWSg1IW6d25JiZxonHbz7m33z60/jNht//bX+I1b0zpnFsyVikojDYA2qsypJx/zoHACFIRuJ0QatOiHhJ+oit1dIGp3WrZzSo822ViAJVnAbU5hzloJfN8q29kgtsuxCtlKZt9galhdyW6wJ9N/KEXlrsGtFL3TErF1syacXSUrc4ZYHqxRZ1P33oCZWasWmws0DH8tn5Le9rpd8fJVCTNW//zEbEk8ckeKm1LDoRgpa8Be4/tJ+p5ajq4fiWvwm/QpzbQqhcYKKcAk70kEgxkGLg+vIZTx69wf72Bg2t1lpbH7AoTlkHqUHotVayEbh84bw6Z0XExbb2F9WeK0VzOES8smZqVZQmvLGc90URUsdECIKK5ByoZLreNidrmpiSwPJ933Fycoq1lpOTEzYnG6zVOGvZrNesN2ucdzjr8L6j7weGQQhpC8djWA3CpjdSPkg54J1DG4tW3RLPvT0AqI1uY+yB6FOrXFsR+hFkSFaVkAHRVq6LFrGqkrO0/KFEtbIua7CQY6UkTQiBFOcWKLf+7TAyTlum8ZaUI6VE5nlPjFMrW2WI+dDWqBp6kVORtsBGhAwhMk8z0zgzjiM3t7dcX98yTrH9BMZxZByDIB7aslpthBzpBqzxpJgga7wbGPoVxlZCuKL3mqEbpG2vFHKKaCXBZe9tK5uJ8E+sCa01p6e91LhDotSEUYVOVXxO2FbIcp3jendLDbNsVClgNKxXHSsKNUX5LBS565hDhhCxteCN4/75OQ8fPEAbzZtPH/GVR495enXB9jYwlEQZC52Drjr6VcHUyr2h5/T8Pr/tk59k3XluUmToLMppSAnShMrSUpfjyNXFI9J0S4lb9reXhGnH5eUFr7/xJsP6HuvBc/bgeV764Eu4zhNzRlkLWgkkXAKdqgxO0cVCijMqFHyZCfPEuN0x7kam3UiZJsabJ2wvL6EqclHE7Z6pKsrpGe7kjO78DAysNgPjFIih0K9WlKLwJZLzns5VpqstYZpQ2aC1Y70asPuZuURqFQ7HMAzEGLG7QD9shCxadeOj9JAz1288wXqN85au25CtIlkDm1NWqwE3dGA0ZbDoTU9BkMZgKgohzVqjqTFRQkBn2YtUVULADRWqpXMr6cYoFaWER2WVp/MW7aT1O9VMbNocqu2hRFHATCmTw4zvHehKSoFpH9ntRlLKdH2P955pHLHG0A/DYd9Ic8JQ0N6RpkAcdxjrmhOurYtN9pau71s5u2CMx6gVtRpycgdfURMN5UmkEFFWgmRiQVWFtRmVCs+ePuEX/+N/4MnrX+a3fOM34lShxglvHTHsQWmccc0fyI84ksLbvd7/d3vHAcCi3CYQt2RauURKSqREY3Q3N9UgEL0QJFCSSS/klVbvv2PML7VsuWy5ESekJa45c9RbSFstyFgIdrTa5vJZLbMGWNTzlhq5EL7uTk9dNveFvNf+X7WuA6gNJWgQi11ES0SHYCH6yWcvQkBC5lMZEY4xpjmNOzh/4R/UslTt6x37kdw4AY3wtQAAbymjtLOAamITd3LBTeVOCXgsamsQp8h+e82TJ2/w9PGbhGnEaUM1tJ5lhfWWqhQxFWGgthMitWnJYo2mEeQEbi+t/VNrJeppVVjx1ohSXy4CnRojrGbdemRyQ4mkBryAOVZq0QWmKBLB+/0oj7VWvkU10DmP9w7bJH477/Gdw3lL3/UMqzXr1ZrVes1m2AgDWFs2ZxuscnSDl3JADlJXtpa+P0GEpdrnWHdAGECgPSFhiUZBw/kaaU2+fymJXFobn5LA0STdhK3kfXLOjfSHwPUJchSEJcWZmAJhnphm6bvf72/Z7W+FZ1NEDjs3md9SimyerVMAIKXENAXCHBrvoLLfj+y2e/b7PdM8M4e5te+K0qaUPjRGe0FKKuiqWK9WIh6kLGiHrlKO8brgtMKqzOAtgwdNJJcIZJw2dKbgVaKoirYiVTzFTC4zHYCzzKlSDPTG0WmFiuOhZ96jCTViKRJwl8qqROy0p0yRXidSCihjsFWRakQ7w/37D3jvu95Lbzu2V7d8+Utf4Utf+hK3+z2ZSkiIiE6rmRIzq5JZO8tz6w3dC+/iPQ+fR9WCbQJRErQFDBGlImG34/Frr/DFl/8z+90l3ogwmFaFaZ6x2uKs4ezkHu9/6QPcOzkVoR9tqCnhUBgiqcx0JaHjjJ5uCfstIYxMubLf7bm5vuXy4prtzZ5aK14ZoONmu2c/z9x77iHv/9AHuPfgPr43xDwzTTvWqx632zPtR6xSzGOg15UUIs47rLdcbffM40guihArOVasEedaY6IaICdqHlFEuvWaMEdClvLoHEdiCqzdKQ9OTlmdbMimUozB9D1+tUZbS8yJRGTKmkxmzumAZlErnXa4JtxilCTNaQ7UXPAY7p3eQytHjJCqwvpe1qhy1Aw5VZxpCGWk7TdC1ttNkRxln9TKibJpiuz2MwB97wgxklMheQlGRVVTs1mf0A0dcwz0w0C/WrcW2oLve3QdRC8gihaMrpEcRtnPdcVoh2KPqgbtDM4JciikZ6hBU2OmG9aUFChTxpuOMs28+sVX+Nn/98/yuZdf5uOf+hS/9VMfxetEnHfU6prmhyZVD9o2+XLxFzQRuHdi7zgAkF7u1m/YMm9rRdijIgtCWONFiFHKNCLTkpUI5L44f3FWkk0KYxoOqn8NQjm0WdTaYHOB6oXEVQXOZIGTZQPTaO6Eb/SBOLE47eW51DvS4XJ8d9n3Wwl9d5yD2hx2ody1EKqlVk/7bvK8JfOl6tb7LTK3JZfm1BvxsNZD5i+w+cIPWN6+BQcsmecdxH8X1HAIKg6vLYB2jaQkUPF+u+Xq4oLb6xtKzHjjMN4TEb0Baw1FiYMyrU0ORCjEGCl/5CxBXWlBR1TyHUxTAdRKiZyoNmSdERDAYEw5LFClRcgitVZM6XutiBSzKAbqAlWp1nmiGtojN1+tipQC+91EkxAgl4xSBedE2cxazzInQNCADq00m5MNWmn6oWPoBwoJ32Dys9NzbEMPrDMNSfC47k7HQDcuhFvEj1gCBk3nHSAdAtYKUlSqKGimHKXTQQlRLobIHAJhjsS5EiZFDJlpGtvPxBxGUoqM48g07STLL5kYA7mxz0sVnYAYA3GOstmGxBSCtC9WKLEQYpKOgLauWBy+MUK6RYIe7zzeOmopeGPodIU04Y1l3Q84Y6kpU+IOnTNeBXzN+FQwKAmEvMYajVaFzhSst2QKzmQ2RjHNmXl/RVWeDid8IJVxJaFrRpeEyomSCkOOdDWRU8Bow0YV1P6WeX+F0QVtFElrsrGsNyc8fPG9fOgjH8eqjldf/hKf+fzLvPbqa0z7SUhTubDdQecUvdWgMzEUhjDTzRPFOYYUKOOImic6baitRc1pIExcPnqN11/9Aq995VWePHmDEKeDDPPJ2Sn3Hjzk/kPPbj+z2ZzxwnMPUaVQc8BZh64RGxJhf0O+esq4vSRcXzLeXBDDJOJmOTOHQkiSKa4Gw2p1xmrzgIurHZePP8+jZ1fU1Tkfv/ccpw+f4/r2CcqAUol5f0UZR2wIxP3EeHVDVYoO8BXCbs/15SVlH6mIlHRIBdv1aOOZcmS31yhnKSZRHFylkdt5YgyBqjJTDuRaOckjWSWeX3X4zuN8B2hiUeioMLpD4agxg14UUUuTKpegiZIxNeOURpVMDBO1IYl9t0Fbz1QKWUk7KaU2xcdMrYn14EXDPxlyydKCbaWtPMQJXRW+dTqFkAmhNL6Xo/NWyHZz80+pMs0zcRQRoELhRl3iux6UcIzWJxvSPDWumux/JcyiJmqaAq3x5DSxtML3g8c6Q87xoDHQGU/e32CrQWfNXDRXTy752f/wH/nMZz7Le973Pn77N/wmzjeeGLZkoxmnhPEelCYnS1LL7BPVyp8LavkO/Po7etbBwajD5iXMZytDL7KQk5SC2iBolGTKpbU31SpKTNLqJs/xftlYl4x2yXi1OOtW01b6jmG+ZP3wFhY/C0HOoGrr918gd5bWKd7y33LClvos0PTjG4dyYe4fnO2i0tdQinay5WuqwzErzKH2rIwhVRAxDyFNikxsA2ka90CY3FLeEBKgSAJXqqh/tTMjDP9yKAMoLb3Qy3m4Kxeow7WiQo57wrRnt91yfXXNzdUNYQoHBMMog6qmCRoptBIhGF21ZOtVVMeW9y1Fyi9GCfkuJZlnsAxbMkAOUa6cbtoMmAaNg4ilLFr8ct5Rcl1zCVSl8V5jTJEa4iIiVOIhWNNKkIZCPgRxpQr0V1Imh4JWkVxEY90Y6SgoRVTl5jBjjcZ7T6lZ2kCpDN2AswbnvDD/jcE6K2UFZzFW/rvvpQYtC161vu+OYdW3wCzjnIjd5BwpNbcZB03fvVbmeWa/3xPmREpVlNymyDRNkpG8ZXZFjJF5nu46DKJIK6vGRykli1ZAkvFVFJqAkNyHneuIuQhPwVpMUy50ztFbjSoJVUur5yvWg8MqhdcCe9eScEROgJXpgEwqkZRmskt47emMxipNZw3eGoE7S6FXoEpmCjO96emGjgnNbc7MKWKcwSmDShlLpbMKXUXLX2cJ6kIOTNNOArmyQJ4FbTJVK5TVPPfCA178wIcY1udcb3d85Uuf5/Of+QKvvfom825GFYVaOm/cQLQV7RVKJWxNZBRTmCk7xTDPjDfX2KtL1HqD6z21Jso08+RLX+CLv/yfePNLX2Acd5QcpXXUrrh3/3nuv/CQYX3CanPGNAXOTu5zfu8BulZUTKgUYHdJ2N9y++gNbh6/znjxiO3FI6bdFUor+s0Kt1rRdUJMtMMJ3eqMzckDxjHz+Vf+X1xePcWpyrM3vsKTV1/h4dpz/cqXmPc3rHpD2N0wbW8hZbbXt0zbPZ02mCL6/uMUmLZ7Sqzkaogpi86BR/ZubShA3w+s+zPmAi+/9ow393t200S/8hSl2I6Zm+stqe/w5+esrGEFBx6WaqiHRdCjmCM1N/0JJ/uedZYcZiiJWCslREKcRU7cG6o1BK2Y0SjXUaxn2k9NR0LI6PvtjNOgq5XyF+C0xbsOvBI+SYwHfs56tWnck9r2MeFzSUu4xWlRvJ3iTDc4xmkijLMMDUMx7fdobQgp4b2j6zuUEcTad46ua5wB3VMRFURqj7GKGGd671AVXNdzfbOnVx5TLW9++XX+8y9+ltde/QqDd3z8Q+9j5eHm2RsEa1CrnuqstOk24SnJEUXF0FrROSglvSO//s45ANOM9+J8ZWOW/mFJpjPGLD3NIpmqjRK1NapkZ3qJuBQ5V2KKBzGeJXOtLRUWFbRleE5TZmvaAgcBBGXuah61HDJxVDkQIqpqf2vZvdJ3k/VUvRNxEDhgUWpr/doNTpXfZUJfya20oQ2ubfTq0LKoW2CwMP1Fz3pRqoM2YMK8VTFw0aKWRXU4FMFLxPG/hRywdCAAB2Rk4XvUZZqU/BWjLErDbr9nv7vk+uqSy4sLbq+vW0+1PhD0lh+lRM64s14mkSmRsE0ponU9wO855wbDWwkAqtzEtRRphzK5BQkieEPVQv6ioq1o/dNQH9s6PwqQsqHUiO8MqXFOjG6ZtlUtaPTSodGmN6YcAcPQ99SSSGE+TCHUtYkzFUVOck1jLUy7gNZQepqqXyWnyFW+EI3yRsJUi6Ke0Uv9q3UetGFDCBphtKGgGfoB6yxQJYixWpxkbtBiTtK3rSWomucZKhjjybEyT4EYmw5cUwIsbTJhTBIEG22IMbWOExnE45xphFSEZY9pAWcroSlh02trsM61YBO8NgwG+ua8VS04Uzh10GmFU8IxMVbRaUVnEyursLYyp5Gb6RbVdZxtTjjbnFBzIYUARZxiyRm2E3MKaKu4d29N3zv2RIb1wD5AiNKK6JTCKYWKkTKN6DjjlMIb6YQoZAZTcDVKxjU41uenrM9O6TcnrE7vkZXl5Ze/wCtffJ2LpzfcPNuxuwnUJFQpZy3W9ygK1SqSihglwZrtXJtNkuk7w8ppwu4aVRM1erZXT7l8/Aav/pdf5tErnyfubrBeHEU39HzkE5/g/Z/6FAYhWA6rDdY4UT7c3zLvJm4urthdXmDGLXl3y/7qCWl3TRlviNdPSfMt/eA5PR84OV1h1yfofo1dbcB6Sh55+sbr6PmG9z93ytB1TLuJ7Ve+xH+5vebxG68x7q558cXnefr4TbbbG042J+Qk6E+oct+nJsmr3ArrDapIkuK6HjcMaN+x1qJN0J+s6VZr9imyGjMnSsNuK/NbtIIhk2vgej/y7PqGohWu8/SuKeq1a1erQleHreBIKE3jQERyTqzWPVXPpP1eSgs1Y72nOEVQhWItu2mmhkDNmYzCOY+zDlIkTiNWK4z2olxZRM+ktvImzsrepESd1FhNSYkQZkIOktzkwpQjrrUgW+1JOZBjQaNx1lGDcGVKLCitmcOM7ztyWon4V05YJ4FHLpnVsMIYwxxnVmvZH1IKnJ2e4pXi+naHTlBdZXd7xVdeeZk3vvIKOQZefPF9nJ70jPsb4qwJpmLLGt33hFopC2LeBu9ZI236RSmZePgO7B0HAFLfFWjeWoW1MhEt5SwKVVpa4UpdVIwLVRWqFkEUbUDbuzq/Xur7DfqWaK4gaj8Nqmeph7cRvigU9i311zawIUurVy1JxIZaZl6bXGupAoXaalG1CQ63saghSYeBTEhTBwEHDpS3pT2sTZCilTCMPQxrkCCkKUWpRVBInDxI1odSLSrmQIajgFFWMj1J0JDisMBjZYHGF4fegoxaF5W72t6ztiFMuZUShPQXw8i0u2ba3VJSlAyoFqzR0CtKUiJCQqVmQeast1it0QlxRrXirMNokWi12pJUEAQjJzrvUI0jEGMkTLNkl9Yeem1Bps0JXG7buc8yWKXSZHkVnR+YZ0VtLThDv5LgISeZK9Acb6lR0JFSGySn2gSzrk0+k8UvQ4CkpTIXGaNJ1Ri7BgpViUMsJZFKwaKb9LBcL5WFDBdjIcQgxMos5DtjTetsEbJriFF4CN63AE4ctDJSjyz1jqgnI28LMaVWPpnR2oqqZoxtfoEQB5fhU8vY59z6tQUZM1jrUUomuEnJSKYh5iQtUDKxs2KNl1ZOY4W0q8GWwqom1iQ21qJrpcx77nWa85MT4n5PLonNaoVzGq81q84wbm+p8yXnpjBsNqy9YmMBrRjnzDiOwm2pUg9PcaYbOvQcWJ+esNqcsNuPpJtb8m6mZHEQiYqpTb+xFuI8kyhonYWYWmeKcvSrjrN7p3zgpfejjOV6u+f6yRWvvXHBk2dbrq9Htlcj417QlRRkKJTvBJnIJctUSzQpRIwXLgsauk7x4rvuMaw1U95z/eSC25sbHn3lFa6fvsl4+RS1v+XEatBgVx3vfun9fOxjH+L0uTNuHj8mTSPMN4RpAjT7ZzfcXF5zc3HF5eOnbPxAGPeUMGFVIc9bdC2c9xsZy5wS8eIJt48fETPYfoPr1uSk2T++5X6I2GGgAJcls3v2jNtnl1zd3OD7gavJkIfnUGpFXvVS/jJC2tZKOnhCiEBrYlKKrpFxBOhUDf2r1M6QDcRSuP/CCasHa7b7iXHOKONAa1KRANf1Fm0VxoFxBdUGv3mtySGwHcem45EwOmM1YIT8W9DSSxczDo0fOkzfMdvKlIXovExrLVGUY00Vv5FSbnoiBq1aItrGtotv0nJ/1LvyW83mgCaGlKW1WCnxFbkc0DZBb22TzzTULL5CVyH+dq6jJJh3UdoHp8KYItbJPXb79DGbkxVFw3Y3tulklZvricFa1BQZlGG2HeN2y7S9JaaJ1dnAez/8XtxJx27eUYxGdQ4VA6mk1qWmSDm30rmiWEu1jpSrECl+PQMAIS0VlNFN8au11Qn9vk3Rk9pw1ZD1krlWlJZAoBxY+7URxaQveB7n5rSX2vii5Q9aN0lhlsl/9UDMqhVSrDJGswUWhx7M1gtuLE1oAVDiDErmAN2W0jgGLdNWbT55G3OIbiUB1Wo2omOQ0EWQgCZUeihLSFDSNmgky9fLTPkFwK8KI8U6jLHCUC0LF6CR68hNeEjqs3rhCLQ2NV31wdmDOOpaJdouRUan7m6v2N5eEeOIorAaOh4+fIBznjAXpikzTpFpCsTcuhk0jcglAkLWGLxto5JpwQ8ihKMUh1HJtgna1FIbt8OhUiaXqfFFbCu9SBCptcXWTE4iZqOVapKnltAWt7MSXMR0J4AR0yIqJe02ptTDZ2tAWU+KsQkTabyHUkS5q7QCeGc6WWPqDmpXuknx1niQ6AWBzEMMjb9i27hfDuuUWjDO0C3dIUggm4pwG7QxZLs83wnxr7bafZWhwrUaLFJOs41bURHeg6LdF8upo6KdOYjnWGPQNUHN1CTdIE5bko6oCr23ONeUAxVYVfBGpsZ5NJusWaeKCxMqRfI4M6jKqbfkEslUfAqix947hlqZww5fZu7fO+GF97yLojU5ZHbbLfFmSx6DyC9XISA6rRi0xyTQSeZrhKww04weR2pMLXsqB6njUmSioVKV9brDaY+xirPnzji/d8bpZoOqissnF3zpK29ycT1ycTWSq0cXR5gq475NdATQcvfFJMlE3Aa8q6w7g3UG6zXaVk7v9Tx4fkNNW+Kc2F5e8vjN13njlS8w3VwwGFh5meOxOjnl9MF97j84J+1vef2XH3P1+BF1nlhrxXx5xYnrefb6I+bdSNxH9Jx4vAsY5zjdbDg53ZC1wpjKydkKiOQyM91OXF5fcXG5xfuB8/MHxKi4vpqp1TGbPdfjnptpYnV+n+fe824efvijYHu6kxO6YSCp0vRHCjkHQozUJmts5qkFjU0+pmauri65vb0VCesoZUdXPC7NovboMlZVlCnMcWS83VOUqOQpXaS9eC/Die6fndBbJw42ZqYpERL4alAqQ01YpVA1k+NE0oY6TTCLNolb9ZTOE73Bacs0iriOcwZvRH8mhkAMoU1Y7GSgVxVSstwvmZhndDWY6lhaeiXHUlBkIqlWhmkvJQhjFKjKfrcVdM5aFFYk6Usi59pGWEtAYRqvJM1C7CvBUJMGOoqq5LCn9IXqHSEnSoUYMtfhlpUyDKlSrGVKWx698Rqvv/kaISVeeHCGXXkeXTwhIwqk/XqFnyYwhlQrxlpKQ0VFJjjLPhATxv46CwHFOUltuEHWtXJgeKuWJVNbPdosbXWgdUFRQAUhJhwcZZtad6izN9W2hbjXYHuZAeAF0jh42dpqnwKNi3O5q9vLBi3COHbJbA40AiED5iKbk7X+cAztlaCXDgBzCATeZrIrt3G0QkyE+hYIXh6zb5k3rxYo/61vogw0PYRF2XkhES5dCKpNpDNNHnLhNmglM9SVLodsq6SZECemaZQa8+6WFKVNUyvP5nSD1pp7958jhMo0Rq5v9mx3e6Y5SK05zsSQ0Ua6NmoRSLnWZcKjODWLDMFZNO9zllpf13m5bk2UyHedOM8qveEAuinrSXugzOfWWrdI3WOjCEEtk/xK79vo4FYuQhzf0mdvjJVgoVRIhaREsEdrjes6StFMY2ilCKl1G6tJWTGnEW0UgxtE552CNUL0q21wk0IQhqUNdZEUrrUQU2zja0WLfwlkrdGN4FkpsWLcwjW5W0tKyQQ2Y2QqpDMGb30T7Sl4K21GurXOljb7QjfBKpFyVljTk2MiE/HGsLKOmh3khLdaxHVUResisLpWdEbTG8NJNfhRWupULWhvcDkRd1u8FeW9WipzDEw5YYvUSnvvWfUDJ6sNU0pc315ze3XLPIbWTWCpOaPbOUmxcPnshuvbPVWJ+FeaE/N+IrZstJZC0praebTRbE7W5JzwTTL67PyEhw8fknPk8ZMLbq9f5Xa753Y3M86Vea5MYeTqNnFzE5hmISp7bzHOUoGYYtujpAzpTjuULrzrfQ+5/9wpz73vXaxPO6b5Gu06Ts47prBid7tmNWROe4f3FoxlfXLGenNCrpmLR29y8/QpdZph3JNT4vrNR9wqy8WTJ/Smw7uee6sNBqn9nt874z3veS/KW3a7a3bTnuvtzO04E0tmLB3PSiRuK09rZJoT19c7CoZM5XK7oxr41Ec+yvt/22/l7P5DbscIVo6vKohxZop7apzpSqbGwrTfixa9F4EjQWA0ajWgYmCOQcYpl4KaJ9Hq6DtCzYwhEZNk3dfXt0ztnoxZ9p6h02y31+yee47n7j3gdH1CzZUpV5TvSUajqnCEVCnouWCmiPOKeQrS1ukdVVfmPDMHg/aKUg0xJWppo86rZlGVLTmz3+7wncUY0Z2pSTpSYhAuQdbSXSR8K4dzoKqIpilUE34TwR9njZAQKzjrCLP4mlSyzGawpk2/bXs2qs05aRoi1tH5AW0qKBEWSlW3RA9BsauCBDVXtHbsbnc8efyM3Xbihfe+wHPPv4urm1v203ggHttrz0JoU9qw3mwoiJZKaSVr1/R4hqF7R379qyABivSgMe7uwZaRKCWZh2RS9u3tcboK1IOMvrxzkk1BsCYRvaiLFv7SEaDeIvsq2XxrwmrEr0Xf3Tai2R0h7q71b5EPXjL8O+KebKqiJLegEjKakUPGLyWN0oKZeggKlJJaa20DhxYS4925qoeAZCkP1LYRLp+1tJSpdkGlbUwg6BgSyryF8Edz8O21tDqyoBKJlGdSmIlx5HZ7y3Z7K5FuzZJRdY0uqCqlKlxX0MoDlnu7iZu20EKIzGHPNG6JUQYGzXMmBrnhc1aQOVwXGQMt2QM04o/Sh2tpjKHvTXPeUkcTko061KrV8p2anHGmYqw6dIws+hJBQ1BVBFuqaiN7KyULqc1qK6OFC2Cb1K0Whr5w4aoITlHRyqJNxeaKNjKd0jsHuTLPcvzGiLhUzhWPKA/eXV9h+R5uAmTS2ML3WNT3Dte5Vqxx5Lcyc40SIptuSn21TZPX+jD1r+u7w/0Ai354ZSG8HqYJKoPzFqcdvdasnUPngMoG7zSdgfWqxxtNSRFdC53WeAVrRHQml0zVms5oKIk8RzIGYxXOd+RamecJA/huQDlPiJXPf+4LzKWy3+7Z3u4wVTP0K7QRbkjKhVgyoc7k7Z4pRaqW2Q+dcczjCLXS9Z0IDFnLatXTD9LFYYxis9k0jYTIm28+ZbfbstvuGMeJcQpULONcmCLc7gtX14kkFBacExVGqMyNdzQ0tcJ75+d89IMv4mzgAy+9l3e/7yHrB2fsVWE3XnO2eYH+7IxhZTjdGHSa6a3wSJIC53p6N1BjZbzaEbDEMLG7uIVa6XGsbMf6hfdjnSeEJIjKqqcbVujOMSk5r689ueDZzTU3855QM8PZOdEantwoXn96xfzoKbEhS4WK8ZoxJZwx/OZ3Pc/5Bz/AnMAOK1LRhCTEyzkV5iwji4121BJQnccaSTniPBFTBApuNXBiDUkrApUSI+M8k6aZPhWSqsyx4NzAan1Ct0ukSTLw/X6P85pxjjx5esMcMnOE/IKn9yuiAZSmGCPrr0pptK+GWg1dFB5W8A7dO7LXTDExzRFipWYvfCKl2W53gGK93mCMFUGs1KaclkrKc5NAL62EpihpkcRWWNt4XC3BuL68xrlGFG6cIe9XjacTUUqGckmLr6DaOYuEc4OLQbnDbqCX8jOKEDJ+3bchc5Gaoet6tCmkcY/3PTXD7c1IyZbT8wc89/yLdN2G7bwVv9D2knmemKOQobWxLfESkb1UpIZs2/PX6/Wv7tCbfZVtgA7p1W4OVAmx6jCStWRU0kjcLybiOTK9uKh6cMZv1c0viNpfzuLknfEsDH4Zo1uhZUraGJE6rNIdcBj4UrOQt4xky7ksYjOg9HI51AFi19VSyp3gzaH74LDZtm6DBVk4iAXdaRzkxjGgMdsXQqBGZhXckeyk06FW9ZYyiGqBiwQFstmZw7mkZFqTP0YVlGqEQxSQMVq6L+Z5z35/Q5xHUhJm+X4aGfqNZKWtDqsQIqW2Bm0sfbdCaY/vZWJfrqIjH8LMuL9hnkb2+8B+N7LbBcb9JJtwbjXtEiWTN4ZaHSD1tJzlvMssBNnQcyqEGKHQanHCb9BKCZkIeU1cmLhK6ohUJHNVFd9ep2olFZmzbZVB2aX8YEhVkQpYrdCdqAHGLPrfQ+/pfS83bFHEMqOVxvueUiOlJIZhhdXiyGVKnyK2oHVBloRlK4FliAHrDN4vxCMJCJf2vJSysL/NwpFIpDZLwmpD1U0XoiqculMrVG16Zd/3DaJUrdxUqaVKSQtaICU1XWc8rit0VAYFumZUTays5sHpCQ/unaIpXF88JYwBpxU6Fay2rJxn1oY5jVKOUJrUhpPsx4ivllwMqWjmBNpJ5jjtArdhSyhVdNarjP6eZlHYQ+k2X17QnIIh5yAsbaMgJmIQWLfzPd6LyuCw7ul72QNSmkklM86Rq8trpnlq9WtFioX9JPM5rm8jU4A5ihaVdTI/3XqHMpoQZlJKGC1jod/77gc8uDfwwvNnoPYyjbTCuL3hNkdmYwg5MJye4r3j7KTH4fDOECno1RrrelTSpOuR3aNL6hi5fXxBvp1ZrwYePPciSitWm1Mub265efqMZ1dXzDmhtiPq4pqT2wm/WZP8mvMPvciDVY/qPP70lF9++RW+9KUrXr1N7GeZQFi1xnSgayVUePdz97EPn2PvLWMKoB3Wd9g2rCaGTFRZOD45UHMUVUbfQa0YpyBacoyHwLdLG/pa0CEwl8o43TLv96xP71FzpCqHMYJiDBjmOAnSqQVin1Ih3ewp6prqNpyfedn/CfhssDVQS6Q3FVMyZs4oFdEUcJpJVVKtghYUSEHKx/3g6VxHMK0kZ8RHWGNYDwPjtGW/30LNDKuOzjtyycwpk0qVsrAW5KzkyhjnNhyrslqLENA4jswl4pwlhJn9bs/pyYm0b2o571Qaoqzxzt8luwiHqhQY56lxgBwxyaycMEpyR68YMBgsTnfsb2+5eHYNyrJabwjZELPC+YGYJ9lvamk+jINk/TRNxBjxbWaGbp0L4ygCUr+uAcBC3hOHVcnS40au4viXCXalKGoSxyVkJ2TYCK3uQgsKtIwEXabZ0ZyBtE7IYeUsJEPXuTYdzd4FDlWy/+V4YEEjkOy4NvRe60NmVRsLVOrZ0kVQljnMhza+hkJIpeCuvNBq5LXe8RiMecsoR7UgF1U+eynQ18XJq1Zva0GEukMrUlpEYiRcMG3I0UHbQKs7meAWWsUYmOYt29trdrtrUpiEHFerqON5K9BQisQkLZiuTbVSyqKdJcVMrhk/OLxfURWEMJKDQO4xZMYxst/NbLc7xnEkxklqZPutBAQpNV5EuyYVYVQX4QHI8Ciw7blGSYtKTaWhIk0Nr0RyCYdAaGHa06Ata4XQVlIlZanbyXltp7lkFEWYwMbiFsh9DiKJaz3LIKaUZHiLdRbrHSUbqTfXjPeWUjLLJEIVAzGlw5pVqs180AqvROzIObswOJGRFuagE3HgRxgJMHXObezu3bWXtbS0TLUulfbfuq1f04YHLZ8viJRpg5k0627AA2YeMXGENGFTYuUUH7h/zr2zE+K8l9atlGQVxkwogcknShSUJtYKxhEzAslWTdpFMFJymnPicrcX7Xcq2eg7MieigDnliLGi7259R05BAvJaGulUCLCddfS9pe88fT+0kpbc9+M8Qak8efZUAj9lqFmTk2bcS1dEyoWY1EFTPZVCrlJiUlbQJdG1iIdWVuc8Xdfx/P176DqyvbpiWGmIietnl+zzSLaaUSkevfEmw+kJL77rBYwqTHGi6xxutcKfP8DagXh9wxuvvMbnfuGz1N3E7tkVTMIcLzhuxh1ZP+PJ9TW7mOjXG/zmhG5zxoPnH/LShz/O+cOHVK0JtTDmxFwLn33li/zcF77Cf3n0jJuQSFU6O5SGofPM046Tsw3f8D/9n/ngJz7BLgYRvpsnlG6DaVqyY1VH0ZlMketZIhZp+bWdI9XCftxR2vhZ5R3DyQYfM9UYstKMc2CcE1OohBTQWlrfvPe4qInphFgiORRSKYS5EK936G4L7pSuF7EshcjVlhBIJRBSws4TvrfgYK6Z7TzJLAtjsUWmojrvZWZMaShZKWx32zalERlhnIrMSlMK3QbplFwPI7ClzVpKjzGVQwlhvdmgtRVxM2XJpTJPQhx3rmMaA7UT3ocxogNjjDvw36T9zqOUIReYJsnSV6sVVRnGSe47Z6wMxJoSyhtWbmC/HXny2mOuLrecnZ/SDyfEWNnuI24l572ShYtgDLkujk1KIjHKNFCrpeuOKnycugik/Br2jgOA7fZG1JC0zPgubeRqbg6w8zIAR4SBWnaiG+s2LydfmEiKRdJXHy6mbUMMRKRHoPBl5KL0zwvUWUpu9RoZvLNwBxbn+VaYdCFzLQS2kisoi2oTsKgyHEXJIAGaLlgLXJq8sBK29yIJvFTrS8vgpe0RBMdoyoayGzZEoZUk6iFGeBv6sSgjlpworZRgtdR4msJB+15JBC5KoZbEfr9jP14zj3tSmlsWG3HO4bsOUSRs88SdO3AiFq5BTKICp0yD7ZUQIJ039H6QT62aFEU4YxpDE6aRyXO322vmeWaeg8yJn2bmWZyItz05t3q/Ngcnjqqo0kiWCKeAhmw4r7Guw7WxucbIpLySpQ+eRhJUVpFzCzazrIVFNFpaT02bUSA98s5qvDUY64gxCweASu8sxiq0k2vjTCWEgHeeRQTRuRYsqdJq7oY5RLLKdM5jTCfEqoUA24I93YYULVLC1jXioNZ00CYACoM3GJkoaBsHYrknai2kLGx1VaX0d+AhNB6OUlqCm6pYW4dJSWR3Q4A54EvEhUq53TJGGRZUp4BJbc1mSDFyOyc0otmRqxLoNSZCKuB6QpKgxQ8eciaGWc6J02zWA0tQWktlURo6KIZqhS6NUKsNvVlhvMUZS28cBpnT7qwmlZlcMuM0EnPm8uKCECMn6xMqMksi5UpMFZSjqkqqkRILRUkg0FkNypJKJcR80BwxxohSpJFuoS987mVefO6E93z0JQZfOVvd4/Hj17nYXoHVjCWxTxG/HogXN3TOYFVhverRXcf6JuBcz9XTW179/Jf48qtvUObMtNuzvdqx3mzZ7Gfcqudyt+VyGknG8A0f+yjf+of+r7hug16fSIvfHIgpolTm9voZv/TLv8DP/Jv/J7/8uc8RKPiTAdvG0KZamWJmfXLGN33Tb+P3/d7fy7sfPs+zx09QyDomzuQScTWjnCPfiSszRdjvbkA1SW4glEysTRlRK3zX473IYg+bE1brMy4ur3nj0RUhVmqNKDXjmi6GMhV1/z6xZK5vbthPowRoc+bydo9f77inoB8Mg/H0SuET+FywrZXaDo6gZbx1aWW7misai3Edynlu97fU/Sj3U5Z93mrR8NjvIt7L3ldrvBMYQxymMrqVWw0ybquCksQgpsJuf4sqHES/Ss0Y7emcJUxTc7Sa1PZpbWXfHvcz6MgwKFKW9ZlTQVuPMort7Y6QAqvNhs16Q10BIVH2gavrC64ePeHpm49ZDR2bszO6YU3Umd0UsAqsl3KN72SM8TjNsuekjDIWTKGgZaZCLfLZ2tD3v84cgIvLp5yVM6zTONe3jEZqaUvr0dLPLWiLZK7ikCW7XjJ2cS53BMCcszhhVRrhTLIna630NWaBRkXjXKQflZIs963dCKUsynIZa70w0RWNpIjwFJVMKEOJPK9ukXJt/IDDm6mlxKGh3GWiAqUvcJcEHQJELbUg+WdhHXAoPtTGL1iEjKTH3zmHNo6cRIxFSCRtIl2B0sbOxhAJs0x/yyWy3V4zzxOaJOQXJaQ2bUpr0VRMUyCVGaWyRMmtjFIKxJzpuxXWOlKKzGEECl3n5CtUqckpJKPue08pK7k2qjKOp1KuyIXtdsfNzY7dbmTcBXKi6QckkWGgyT+TyTFIG41eznkbJuUk6y9JSIWHkcu1id2kKC00TfLZGUNVWobONN5JTuVQ5okxUGqWOQJGxmbarmMOAUXGuQ6l86Ff1nuPRtH1jmmWc2ysdBhYt5AawTjfBuosYkYOYxy6SH9+Ka1FEMXceCRGi46E0fpuqFT77k4b0KKjIANIpIuiFGnv7LteiIMlS0dGq5Pb1hZgSpVxuEqhsggCkRO6FrzW+JL50sufxxpR+lNLcFtacKk8ISdCCDKsJBcZyVuhKAUlUbTFm04CRq3oz+4zDBZTEkYlnJMgfp4CKOEvhDgxxVbvbCSmqhWt2aUNnYoYbajAPBfGaUsqonI4zhPOOTKwD5EcKiUrvO+xxRKzbO6pFpQ29P2AzYWYCnMI1FJFVrYF5LYzrIaO0spcp5uBYX3GathwdfGYF154gTDDeBO4uL1iTEGcY4585XOvcLpZ8eLD57n/4BzlHdfP9uzHyLOLG548veFqF4mxMCdYv/Au1Lpn7wzPv+dFbr7yZW6t4Xqa+B8evsj6gx9nDoBxqGFF9NK1stvf8PLjCz79n36Rz776KmOO5FpJITAMa2T8sGHcj3zwEx/lD/7P/zMvvec9xP0t99crnNLcXt2w3wdKhsF5qnOM80TIkUIkpsAUZ3rXoVRtctyV9WYje0hMBwn33ES0+mFNrgrlNmz3katnF2y3N2SrGYaBznvWq5VMhUwFlEXnzBQS+yny7OKSMt/iN46z0zW9s6xUZnCGrtMULLuauJwmtgrKsKKimcdMVYnVMEh2r9Qhl7CdxxtLSokwTTgj7dSpZHQV9UlrXfNH0nXULYFNKuz3e+Z5pqZEiW1CbKmslKIfepyVtmVUZVivmcYdMSXGOVBKpO87jNOtHdiwG0fGaWI1bDg5PSGmwu3tNc5bfKcpOfH4jddRRfHc2T28NVzstlxeXqC14kMf+TBn98/ZpxnXOYouRGZyDWjrUF5mmIxpZDfO6Dm2IE1GOFvlZPR3KDLqmjvxvF/N3nEA8PnP/xfOzs746Mc/xr3zB8QoOu/e96xWPSGENtRGHZTZrJVhK5AxLJtbq6dTZXGngjeeO3IfTdVNnqsaI15EgQT2X616pCdaIBCB4SXr1ko3voLU4GMbRSpOf2kdzAeHn3LCWYmWSrmrxaciAYpWtsn3ShCRRZ8HaiNUGYGgUg7UmtBGpHNrkR5U5zxUJQSQqppCkxI4CUUOU1Ph04cJczkn6a0tIlSx3+/ZjzvmeWaa9kLGUoW+9/RDtxwQq05G6qIdMq244DuP9yJaI9mQlMGtMUJKK1IGyK2urvVSo29IRms3q7VCEhKMc4p+fQ+FdFOc3b/PC6kQQ2aeMrvrie1OdOdjjCJCshx7mFqLnpQl1NLBUCVgsFbjjZPM3sDgO4xRhFn09b1x5JyFbW40g3dCrkoZo0WByxjNrKtIfDYiqHUeo20T/slYUw+qWVpbnF9ge+kTUlr65vf7LVopVqu1kBlzOdTaSq2HcodS0CnLMKzYTzI692Q9MI5zq1VqOi+jogVFEdTLWYsy0PXdQe5Y4H3dfhrNpFYhLSnNPI6EODJ0PWvvef/9+zz6wiuE7S0rLdfae8vgjGiMq8Z3SWCs3Be32z1zCFgvZbVxH4mh4KwSwl8Gv+rBeEKt7GPGFIU1iolEcZbz9cC8fUqtEshaZwgho61i3a8PKF9MmX7V4bqOGBNzlHG0OsE8TtzczJSaSXkmK9m45liRfMGSMpQq+0cJQnaaQiGWKryhJIGc8+4gl9x7zzRFKIn1WqZGmsaDySmxS4nPvPwFXv3yl7h//5RnNzekNDLut6RaOLl3n8vrW54+mticZPKUmbeBR29e4PqOMQRiNWynwi4V7r3wPj7wnvfz3IsvsD475xc/+0vozvHqs6d85tkFbr0mdRu+vJ25LJVqOvq+J6CZCnjf89prX+J/+Xf/nk//x59ju9tTcpGY1wA6o4smzIGPfegDfMvv/B2c9z3h+hpVA+erjrAfWfeKwfXsxsDt/pY5LoJoiRQntMqcn54wTzN35UYZ2VuVEanpHOl8J/K4OXK6OSHMmbP7PU8vbqlJgmNKIeXAOAWGYQUV7p+fc35Pc7Mfubresp0mLi4ek28im1PHu3ge5eQeffDwOezK85Wnj9gBs/YoZXGuxxRHRpKJcY4ULTLWq5M1zljG/Z4pZ4aup/MeRSWFmXEfGjJUCeMoQYO2hJIJubDGQC6M7fuv12vmMeK6QfRPtPDXYi7kRQXTtnHaJcsQMSf3apoTvmtkVVVYdT1Gy1CvnOV49rtr+qEjh0jNBasdN5dPSGPk+voSVOF9H3wfyml2847qrShMGvArR8iK/XbmZiczL4xbc++5cxmxbayggQXmmCgZtOnYnK3vEuNfrwDg+eef4/Hjx/zCL/wC73//+3npAx/hufNz9vvAOO4xxjJPE67r6DrX4OpFvcy1HmmByJcBOEovE+yQTVfphSIoA1feAt8vgYButdAFbteHlr07Gdy3/miWbGsh+clmfOgaOLQrSkvVokWgdaXm3Gq0cg4OfAVUm9rk0LqyyCA3bOOOF0AB8h1BUrVzoIT4pa18j9pQixBlklqKiZhmUgrSz7/biRRsc2ZKF7wTp7Uw8pUSxvZSh5Jxlx3Wi75+zrF1PFRyotWtnHQ6FC0BSRu2tHRK1DbHYDmX1ch7iZpcO8dZgiTvNaVTnG4s73reM44T+/2+TZgbZQjNKNr2pcTmTBMpzcxhIowTc5oxxlGUiPIoJRwTFNKK5Bw1CXPee3cHs4PULwuUlFCICp9uIk05i7KiNrAeHME1AZ8GqystSMs8TxijD4GVtZauExjCWsMcKrnIedFanKo0/0IOgvCkFIWH4EWJ0VpDJUtLGxmlDF03NIcchQtjhR/SGSdltZIxpgWJWlNzIceI1ZXeGVZujcngnaOncPvoDeL1U2wtdLbHWI3ThsFZotIEJQHSOCfKPBNjYbubBNqfo4h0aUV/NmCtY7+fCdNMSJmUAqGRDo1VeKNZdRYXLauoZASwXiRUM1pLjb3rekATc0J701q0NCEU4jwJOjVG0pQwzuJ7R6yZ/T6QM2RgnEWxcTVoOisOKbZsbRwDRYvSpFIQQwAqZycbHjx4gNaaN958k2m/ZzPISOj9fse8HyWQQFjhT1LhzWfX9B0MHVij5HuuT0BJu1ipiu2ukMlc7bdcXz+Tdsm1Z3X/If/j7/5d/J9+1+/m7IUXmaj820//O278wKMnj/ncF77A5RS5t1Jcb/d8+c0nvPLlL/P+lz7KPgZiTHTDwBsXT/lf//2/5z/8/M9zM07iuIx0HPSd6L5P88zJsOYbPvVJPvmxj2Fq4umT1zkZHJaBOE0415HSJBMWXaWzEKuoMjprUNkJ6qVkcqcUZEX4Jrc+OWsMMYostTVedAGK7EnP3T/l7KTn8uIpFxdPuboSIloImtVqzRwyqcDKd3AmHYnjdoYxkFVCn24ZrKF3AyEHbqfI3ime7md2saBVpisObzxOd1RtML6TGRcpsdvtcFaG4WitmWKQMcK1yE5vjHQOGSPC6VWGXRnbQdVcXd1Qk3B9vH9rm61YzlkQslZCRhnCvMda7lDqtkfGmNjvR5ELd5IwlJIZ9xGqQitYD57V4LkNE94o1kPH5dNLnj16So6RD3zofXTdQFYFlCGlyM32FuUMUffs5gnXeVznKSjh2KGpWmFd37rGIgrNZrWmb6UbuR9+bXvHAcBHPvoh1us14zxzfX3NZz7zGe7du8fp2QNOTk7EuQl2DKpKH7lVKOUOzlZq2ZlFp9jU1uIVY6tpqrYgdXP84qgLtIukya2VDoTxLeWHO4ncA02uIhdBe3m8Lmx8c6ivUzUZISXVRRio1oMKlNaaJfxYerp1q+uCMNQrsvi8E6GbUsNCEQUrpB1bC7X1xssFLFAj435LjJHYRvWGMDOPE3MITXVQ6tILJC6DbgyuSlaM1hQlELPS0tMaW39qzlU0640lJHG4pmW8qWZMFTXGkpOMqjUGa2Wc8CI2JJEAbyOmlUKrsbeSiJIswhiHwkG15KxYW89qc3Lo1c85U3Ji3AuCEdNECFPTxN+y227ZT3viLN89mdxaAZtss5Uss7pG0PTN6aCgythQ44TPYbTCedfElBK1GnEqKciQIHu35rrOYqwnJdlIUo4yoW+ulCQ90tqahmhpTNUyVKcRPGtFSGgaITflQrfq0MrKqGHrCCkwDB37eZSNqolUlYNoksEYKUPkLA5Oa9HVt1qmNBYr3SWbrsdpRYmROM2E3cj4xusw7un7FYNV6CpqjgpLLplcDWMMXO32jDEdpr8pBSvXYTorKoF9J/rnVLK1oA3baW7InaY3HpTwUeI8MZrIeq3RFEEnjCUaje+sSMwqjSma2Pgg8zwzTxPTNLO73VEjxClhkrS27eeJaQTjYVh1jPuZGGFPZFatuyQv0ThynxYJSE9PB1ZDLy3FeWKeE7oGmVqoEkaB1wWclDfoPP1qkBblKq2BJ5sVQ+9QqjKVSjaWB+9+gZPzE663t7IRe48+vUY5x+kL7+bjv/V/5Lf8rm/m5AMfAtczPnvCyxdXbLXny5c3vP7shvPzc1x3itlGTIUw3bK/fhPbDVg/8OzpG/ybT3+a//Xf/D947bXXKSW0KaIylEl4GBW/WvPbf/tv5xu+4TfT9bLXKFsINfDses/QdSg0Uw1kW3C9w2lFnieIFVeBGdKYSGFCScpIzZEYEn3XA+K4UuvsSHniOgZCTGit8E5jjaOcrHDmPqvecHV1wzjO7G6umaJAjP0wMGxWrB1sVWA9JN531nHae1a95/TslOg0j3bXvLHbwmpN1ZUcFSUbUZhNitzk3kOamaOggGh9GFCmtKiZppSF+GmNBOKlkHKbGqstnetZhMSKqijrSBXG/Z7atCE05lCW1loz+EGCc11RTcytlEXnU0itIQRCDAw99F0vxNMkvCDrnehrZIPKCWcdTsHu5pJpf8uDB88zrAcKilgSBYWysi5d12EGz1wzsVRqLGhn0cYwpcJ+HOl9Ei5eqnjr6L0mFpj2I7e3t+/Ir7/jAOALL7/C+fk5H/zwh5nGwFe+8jqPHj0hJtm4VquV9B5qRYhSC1xaeUoxzamUxsgXD71EUroJ5ixOXhdhM9YiwjcLm77cefLmkER3vdKmIS2Z6tIVUGsTXnlL9t9+N1o0DVIth46GxUojqoljW2bVF6nvGnXHZK9t9rsq+Ka2lmMhpLktImGU5zQfnHiMMyk2NbIYKTmSYiTHcHD2KUWsty3YKHSdaXwId/h++dCVsLQ4Nm3/+tauh0aKLE0ISYlOg6LxAEI8zFdoF0WUCUO8Qzpad4To47fJjq1nXWbag+g0WBm3WXWTt22SzXA4VqUU5/fut+l1MynPLdPYs9vtmKY92+2WoipxCsxhIsXMPI2kOfD/Ye2/emTL0jRN7FliK5OujgyZOqurZQ2np3uA4XA4VwR4Qc7wp5IAedFsohtTU126urIyszIjMiIjTsQRLszdzLZakhffMj+RDZBMAunAASKOcDexba9PvO/zapR0xDmTQglKSpmmboSsmM3jrtBWumCqT758pGsTE3Dx9YvoUQ5hzXrZMo49JyFnCJ5K5QJ7jI+sBkcSC6IWIIg11SPOeJ5nll0LRjOOsRzqFXVbY2x534pQ1loB3DRNRVNZtJY9d5DLWh4zmdqAxlJrw7KuyN5xOBw43O0Ydjs47FlaS60UFkVEyS4wOY6TZ/Azx2nm/hjwCWwNtpNQo81mJZnqZaLj+4G6a6lNhYsZ3bS4EMgxUllojKKx0NWG1mrc5LCNoq5ruq4T+FZVY0xVmoUD0+yYZi/59D7iQ2R2HpM0CckCiGMuj83QLjrqtmN2e3ycmecEOHKEqlIs2uZRrZ3JdE3Dar2k6xqmceDd23eMo6NuYNFK+l4OXh63bRl9QDUWVZXEyBLPmrJimh1KC6m07mqevHjK2cUFT1IQFKsxnE8TUWk+/vEf8Uf/9n9Ld/mMwzRx2Pf8+d/+Z/7mV58TguPrN9eoqmGxWjGMI2TF2WZNYxO3169o2jXTHPgPf/qf+H/9x//I6zfvJMAKEfAqY7BVzewSbd3xkx//iH/73/5bnj675NAfWS6sTMV0ZpomTFMxDIPoIirB8iYyUUc8jhREcJeSQ6UgPvzaUqkFbnbkmDkOQ1mDVjg38fbmlru7O2xV88nHP0Qrcezk5FlvGparK1brBUM/8fr1O6ooTUvSUGNZ14rzJ2esc8tVp2iqmmQMoa6YrWHIBm/lOfoA1mdMJZySfLJvq8QwTZJWWdfSgFCmg2i0NagUxLqacyHJ5yJsNtiqKSmiEWMqYXJEuXeLJkpU9lbLutcXr733nqTB1BUBXxqiAk6KQfQwbSvagxBwyhXbuwh852lCx5FAokbQ2/u7W8b+wHLV8eTFU5IWWFqOURq/sqN1wWOc4NGz99I4RrnvpazwPqFVKm4lKUyOw8ioZjjxUH6Pr9+7APj661fc3OwIEZ48ecYnn3yP4BPHYeDm5o6zbWK9WdF0LcZofBBhkVLl8MA82v0k4EXGsimF34luPYEbTmRBODEDRFmXC5jntB/N+T046PGXPhUBqhCSTj+zFBVZoWxFVXdUSGeSTotccqGmlTMxeZlKnCYbChQBUpAuLjticMxZsJtuHpnn8XH8RFaS7T5NpBQYx6Hs3wR7WpIcoBQdSkNdl/jg7N/TE6NoCk6e9KqqSgcsK46YisivcPs1p9AYObiqSshguvx3ioroBYJz+sAI99+ia1Nsfd8tnjRwOsjNd6KLgSyHbyp5CtroUrzI/ESXtYo5rXVyIsaF1NElKe9kKYzJE3NgOI6MY4/3kfF44OH+XlIGtfDbow8EL6EztrLUIZICeBfQVsQ5p6Q/ayUis2kWMqVBFZCUWA9BVgE5BfHUVrpQDgtNzAvFsm5rmU/p90VkjFLoKUtxsWRsdUpMFBBNXQtsqq4rYizALKVQbY1WSlC5tZUgHQVtLTRFlYWJUGuN1olGaaroOT7cM16/Y7p/IBx76hjRtiKlLIfs7AkeZp84jBP7acADXoFZWLplR9M0tLXEkyqji2pYGAPdYkFSivuHIzEFkp/xkyNrqBuodMXKNpx1DZvFGq0yi8UCU1mcc/T9SIgHhnHicBwYholxdMyzfIytNeLv9u/FvthKwqNqoZrtbo/FlaCpjJFQJgWLpqYpr6cxEkBVVwaVA8NhJAZPYzO2g9Wq40R509+5R3jn6R/uGSfR9NQ11LWSIKymYrGs2V5s+PDDl3z0/U+IGsxqwZwSb25usNs1l1fPePaDH6Cbht3xSO7WfPnNt/yH/+XP+PbdNbu7G+5vb/nehy8wxvDubkdTWZarjtVCOvtvXv+WP/uLv+U//Omf8ebtLbqSyGpjpSiViagm5cSLlx/w3/zr/4arJ8/QVtGZFcomHvp7VqsW1XZcPxwRGmcjB2Sx0/noSdkRoiPNEe9GcvZoW1HVhqauxFc+TphaGrG+P/LVN1/zxZe/ZXffc7ZdcX6+xaozmq5CNxVZCRzs6vKM9uWS1WKDmzx3t7fMY0+Ye6pa8eRiw1JZapWgaXlIcHv/wD5EbsaJZCtSlqInZ/HAowWaFMkQIm3bPuZehDIZzGSIGcPJSixNgXzmJQCLLGfANDnJfbCqWIyhqS1d1zHPozSgGVyOj3ok7z0mQLs0TI8JolKdn6aTbdMKKbN8f6Vkcim3ykhbVSgfaIyEEd0fjlhtuLy8RGnF6B3JiorfRVHxgzRwLiawsgpURsBIPs3YumX1HdBP8oF5mgT9XdV0VUvT/IFdADkZXn39LTe3D7x48YLvffoDnj17jrENfT/y9u01x37g6ukTFsvmUXSm9XudPFgeWftlAiApf4qsshw4JyDPKSzoZKOTR8Fp1p8fpwDmsUA4YXdPYyygkAdV+T0rSuQkboPHv6utVMVQRH1aDuYcHnf8qCJgzIGQIjHKB8r7mdn1ODfg3YjzAyEI2nSavCj8fShiSHBuIvogSu8gXZ9Wp+eWsYiNSURPIrQ8sbrzKaRGK5wTa5O8NDKpSFHUu2KFE1JUTsVSZ2QcppXBGlFkqxzKygUJ5Cho56bpine2FDGoIgyU/ViiCDRVsTtk8yiqTI82SAGXnGJnT6K2lCjxqUaKDpXJtLRtJuZQ1iORaSmvrS5d9fH+QT6oKTNPE252TP3ANA6yB5s9wUXqWrQhymRRI5vTCkNjrf6O0+P0iovuQVuFG2UfHoIjhIyxcn0qJWFYdQk+AorNUUnQUxG3ijXOFMEnSEJmKtAOJ4eYNkVwKfQ+pS0mRXTwKD8L4MoYsTRVlkpplk0DMZKmGX/s6a/vmG7v0N6z1IZu0VEbK8XS5GQcO3lGF5ljZohQtRrbNSyWCxarplzLmRC9QJQcxVfssAVuopJnf7vHh0xr4XxleLJZcrFsOFt2LLqay/ONrHRiZhwPPOyPDFPP7AIhiJV3doEYKAWuKQWT5ElobbGmFtsXClSF94H9cWS7PUNTy6iaiLWadtlQV5YwO0iSyxFDJLgoNDqj6GrFYrui61oO+wPGJpbdUpwBuqI1Fnt3oCKTDKy7msVaCpi2q1msW7bnK77/4Yf8+Cc/JtSah3nm6+u3rM43XD1/yZMPP2Fx8ZQxRqJteLjf8+d/8df85vMvUVlxfDjgnaPtOnyKzH6mbmvpyhUchwN/8Vd/yZ/+r/+J29v779yLFFZrmqaW9wLFk6sr/uU//Sf80Y9+yKKuIDmqphOXinekLM6pfvBst0uUrsgp4+aZmAPWKoyqiYCqZKLk6xNGWgmhNXmUzmzP1ozjzKtvv+YffvEZu3vHeqPYnm0wJKxJLErojwsSBJeS3G+vLs+wGLaLjun4wMPuLSkMtFrsuEpX7GNiN870EYaYGWcRZm7XZ1RGi/tIiTUx5EAiorNludgIZGgayVnEe5WtCNGLeFbx2OCgTxhuCSPzcwAqjK0hx1KM12itZHJidOn4w+PBLiAwCzZyGI/E6GjqhkqJ7ipK98k0T3LYJxG0p1BiteuWrm6pkyeHSdDESqbHFxcXbLdb9rNMkuZhwNgG07RSkWbNarEADftxTy7cEcnykIlVyglXYtcpOobW1izaBpVgHMff61z/vQuAm5s7SSqrEu/e3jIOgftdz9PnL1guV3gfmaaZ3W5HiEvqtnofAIMGVRXqW9EA5IQ2Mjp0TjjtOqtTE15sgifhII+qRikG5MOSCsVPDuwyIeBkb5KDy1pFDDICN1qjrIYg4/IYTwTDJExorUSVrZUAcbyE4gQ/c4LdeO+ZpwnvHNM8CNksOWZ3xLuJmD1kT0zgXaauu7LqEKV/U1kwss/XirJSKBHBKZbDJBO1vKlWCQBJDp3ECWY09BPeB3JWUhlrsa2k0vHkE3dfvy+gjBGbpkxmxA4pAUMRnUvWQEhk877IEnhTKTwwPAo584lRcJoSyHutizALfZrGfBe8EWQvXGiNqqyCyGJF0lTE7NFWU9Vabsh1g8qKy7NLEaRNM9E5UhT8aH88EHxgHkamYSLHLBhjN6GUUOLcPBNCIuSI1hUk0Tpk8uONICXParWispqxUBWbVkiKVSUjcq0ELipiylieS0XwQex8OVPXFc7NZDSL5YqcRFRmlh1CYrRoveAkGLXGUuUM40jSDUM/4MeZmpbWLrEKWm2IznPcH+l39/jDARMCnbbY2tIulmUaNwqTYYwMU2KOkGtF1VaYrsI0BlWJ7S4ETw4zldaYbBnnUUArOZO8IylFYw2XmwZtFOfrBc8vzrnatnQ6USUJHrm7uaMfxwIRCsxOplSCDBdugqLoV5BrVGFIKmHqE1zJEHxiDhGfHCkLivXRtZMCKTjqqmO1WrNaNszDwDSMaNWwXi2pK8N+v8NqxbLrqCrLsmvpqoq+H2iqGmsMq/UWQuDC1CX7QWPbGlM3ZJVk8BgjC6V4ePeW27fnXH7/Y3J/IPqJH/7ge5y/eIlu1gQQ5bixfPHZr/jVz36JDolxfySFxHqxkA7cj9hlTb2uyW3FL3/zJb/42T/wp3/657y92TFHEapaLSpz+fBFapVZLxr+2U9+wL/46Y84W3YYYJ48yQesNpxvLxnGIz4mVsszjG4Is5DzjKpojEXpTM6aXCuapsG1Ld7J6jGFiIseF2b6QcTcu7sH7na3oBOXzyyffPwJVxeXXKw3bJctWmecn1FG07UVzkf64YhKMvnrKstis6ZhxE2ZRSXi7qNLXE8TvVLkdokyLQunJA53LvdAA15Fog4oHakqQ1WZQtYz+FhibstQMpewJ/k050d6Z4xCho0xEWYtSZ1NJfbaRxZKZJyOrJeLxyhoYzVV3T42NyE5hkFW2iEFJjdSW4vWSHrn7DHKUJ0EvDFgrHAtjFK4cUJFj5vnsuYWy2o+NQ4lo0I3hWZaRG7eS+HWlihhHyBrBZWk0DrnxSVS17JeVJbGWGpjmceJ4P/AIsCzsy1Kadqu5e7ugc8//4zb2x3f70e+/4Mf8uzpc/rhyDSN3Pkdm7MVm82SWLKWm7ouASngCoXJKIvVDUEVfK7wqSTwhixvlhIf+okhf+LMnxDEAk6pSrFQPASKUgDIoZ9ULIE5Csv775O80MEsCiOMCNpKqvDkE84NjPMR5yZC8bWP40B/7PGzY3JDUQ0jEJMoCFRNLnnt74Nxcknvy4iKPwPOSZa7MsIkSPE9Hc+FQISSLy+RuOM4S7GEpqmXMv3IFq1qKtNIR3sqaFKS0akV69uj1iJl5hAwxRutiivDVt+hL5bQCspkRhf8s8Bd5NAWQmHx5VNhSkJWIhOSJyf1mJpllJbC9mTXBFRJdCRlEWVlsWZWVVuIVg7vDYpavLR1R06RUffkTjIOtt4xTSMpBqZhIsziYZ6mkWO/LyuazGG/ZxgHhmGkqiScqO+jIHjbGkVinCYUiq6paUxDjdhNQ3BMYyFZ5oL7LLkAWlvaqsEXYWhKiboSEZkyhtVqxTSJoptY4o+VEBJTSrhpRudMZQ3LRYvJNXfzyL6fsBratsUkSMc90/5If3vDdDiS/SQ32bqhshU+w+Qdfd/TT2KXShXY1lB3K1Ih452U76qsXoiRSCT7iFFgFLRN/VjstsuWp+dnpJxptKZtKlJM9ONAHgdCSuynwHGeoNyYfRROhDIl+llVEi+rhOhGokyz5CYs5EpDYyriOMvNW1t03XD9cEAVd4HVhvNFx+Zsy2bZMFcaZwVE9Oz5E9qu4X63obKG8/MNw9CzaFrOtku++frbgj+uWHetHNLpDqtE3Jn6iTg4mVRZcQgcp7e8/vwzbl99xU/+5J/ijKKtNU8qRRqP+JyJpsMuLMeHW1598Wv6/R1uGnjY3dE0NZdXZ2hryVGzPT/n4uKC1XrLz375K/7iL/+ad7sHbLtg2A9YW7HZbHF+JgePH0cWjeVyu+SHn7zg+cUSFXucT+gy9RyHGbtuySFRKc36bMvxYV+6vyQxwK1YI6c5EHPgME0E71GxaC9mh58m5uOR+XiQKZ0befnsgg+eX1I1LZutWH6Xdcuia4nBMU4jOioWzZKurohOGBzJ98zHO4yKGJNYrjtWq5bZw9hHDIa2rom6xgV571tToXRC5YzPARecNFnJ01TSTQev6Fq55yWlmFwkOy/Xc2mwpFgsguMUqauqTH2zIMGnmZR8WR1LrH1T1RyPR4jy+G0lYtZUBH5zdKi6lnS9EJn7gK41la3IIQAGXTfkMnVIUZolWVOOqNHRWMs4BHyOtMsVac5UOpJ1xWHfUzcdOseSVZFEODyOjASqttyjY2R2AeUNTdfRGM0co2jFU8aHkckLVySlTDjRzP5QBcA/+ekPuL3fEUJgt3N0rWUcD/zVX/0lNze3fPDyI569eM5iucC5nvu7HX4+sly0NE3AKtk756xYti0+RFRSRG+o9JKUIj6cFOWmTO0lUrTSUpFJprqIqCTRqZhklWgHlDIFUCQUtRSFGb5YdJAy8+xJvoj7rOyGo3flgPQoEq4fmF3Pw8OOw3FHTI4YAkM/iLglJVKUCYbVWcaRfma/uyG4mfPzcxabJQnNcT4davIhdPNIXVsqUzFPo8Q4ZpimGTd7SYSzNVVdEVLEpcjsEkpNj6l7RlfUdUNlW5qmY9EuqOtWLHBZ/NWSbKhxMWK9HFjWCNhDK1i0tuzuZ/G3ZlDFUqdtLTEEsoQWF4DSZX6ritAwk7IkDAqq1hRhWxmqqyzTHiVj3qwTpqroWrEdxig8f5UyVhmx6CDiyxNDwRqDNSf3hyraB0OzrElFf1EvNU2MOD/TbQIqQY7i845J3A2zmzgbR8ZZEtqc90zjyMaNYlXNgXmeoZYRflIC3NGq0CELftPNjqapqazF6grqIlhFdnSH4UhWiZAU7aLBKOGray0FrUYEQ+PUi1guZ/oQWLcdbQrUfuR4d4u7v0dPM3Hs2R/2WCU3zPk40N/cMo/SgSzaToKOosOFzDz2zCFiGmjqDmImKUvTNfTTTCjcc61gJD3awrrGoivRAGy6msYqVI5YU9O0S1yIDNPM7ANq0Mwm4o5Hxv0ds09QL3FZ4+dIDDJeFslIQmuPNpmmkceqUsaQSzqnwiXNHIUOaY2mrixGWQYfuNs/sPcJj8dW8PzqDLVY8Xa3Y+hh2xhqM2NI7O89/VHRLRqePnuC1oqQYRj3DPMRchA9B5r93R21qpldwNQV0Tmmw0CFTFNCTKTkyCqxWFjm6S0/u77m8qMrLl5c8e18ZN5uuPjxP2F59YL5EPj6q9f85h//lqm/JXjH7CcW6zVNu2CcZsbJY3TiBz+44uuvXvPnf/YXvHt7I+LjEAqUyjBOI1WliUQqo9iuF/yTP/oBT5+s2e9fo9UZmQbnE23T0FQV/cOeSiuWi1b2+nkixiOmsvR+xgwNPsNXr77lOPTUtcaNA9u25WK5QnuPmma2RnOx3aC1onpyQdYKrxIPfc9xHNBVzeWzJ+wfjlQ1RD/hZs/5eU32M7WteHi4JThPpyODn7GN5fmHH1IvOh6OHn/w5NHhc2JyItpTRhHmCVNbuU5CwMYa3Vum+ztmrwgu0bYdb65vAE23WND30uE2TYM2GudlnZlH6bSbpiZly+w8wScq43A+EpynrmRaF73CqEycpSC2Vq6/nIQ7EkVYRT95lsuW1mjCNDGPgWgy2ViS0twdRuquZrteE/dH+uOIsjVNVFxtnnJ7c8s4a9YXF3itcSiqdsXcD6zaLeNxwA2n+w5ogiCsVUClVEx0mepkTQyBh/2BqqqYZ0+0NUprWXeoiNaW+bu7zj9EAfCTP/oR796+5fXbax4eHtB6Yug943Tkiy++4PZmx0f393z8yUestx0qJ4b+SAwzy4UAEFRR3qt8CnIRYV4o/GaVT5hfEQrJqFUVQI+MSDARCmaYLN2/rRqsbakKfjEljw8z3juIHq1lVdDUViJ8AZUi0UcR8M0903hkmo+EMOG9AEFmN4IRMI9zXkhBWXKhtVK0jRQhQVu26xXkJavVUvbW41wmGsVVQOnmVSIlyZmPMTxS7KxRxDL18E6qwTmFMkY/sQaEPVDXDe9FkbLiEH9qfixsrG0Yx6E4C0SMpox4JnLKj4wGVTCZiShIW0WxSwKFsaB4bwM0WEI52CQ74f2fqVIkGHJZAciFKxKCWIA5pjAETtqNErZU1jeyAnzvCvmumwGdMVYj4UPynAGsatGNwmQtB1+KpSMo7533hDCjtcSjDuPIOB5lDF7cGCFMRDcyzUexIirp9p13dHnNYpmFbW/EQhp8xM9B1ktFOKethoigOnOSgBujCREqDW3XyXspVRDLpqOzFn//wHx/y+HmhhQCC2shRiyKi7MNbpyJ40SrNe1yicrg55n+5CzJAhJaYxi9R7cV27pldJIIl4prY9l1APR9L6EkKWEVLNq6EN0sJnsMhhQjh4c9cxRh4RxkPNoayFFWKi4g/Pdi1dRVJlvJmEdD0pqkhNNglOybU/RkP4vaOlf4KLbflDxhDqRKBrRRKVQrFMTBO276ibqtmCtFbBQ2G6ow4ucDbWhYbVbMPvLu7g1GG4ZxYL/bc/v2nofbiI7QNRVHfSQ6wEk3ymkNSCLNERXldfHBE52nWsGia1mEjD4ewSbmoefVHIjN5/Qh8+3dEX/7FjMd8McewkSllwQ3st/fi5ZFw29/8zm/8YHrNzfUVUO9aDkcB3xMNLVMXvzsyCmxWrf88T//p/zgxz+kW3bUjWGYjvg4IhwKqKxCqYx3nrtxzzDsyXiqytAtGw7TwNvrt7y5vuHLr18zDIOI6KaRpbZ8/4OXfHhxwXC74/abbzBEll3L1dMrVmdrnJ+xJC6WHVOIqOjYtBVuGNEhMDw8cD9HLs/PqbOmIjC4I0mJMPDZJx9x/uwJh2niGB8wTrPQAmnz3jPPjtl5higAsJBOuRtWHCrrM8iK2c0Mw8g0zKSUmeb5UVBe1/V75HYJi5PgLUqeScA7R6gSlTVgBKnsvCf5CEkEojlnctSABzLjPOOdJ9pMtDLu11lDyOQgmRY5JaJRZKPRtqLve0yMrJoWd7vnww8+wpqGwUemlKmVJtmKQOJ+kM9QjJDKvVwVKmpAbLExibbp5H6QQKGRrBSNPYnaI9FLwRCiOBa0LmFPf8gCYLna8GHTUTUdSinevHmLm2+xlaIf7jkc9qIyzY4XL5+yXDVoEwnB430mJUNdNxL6oeuixs6kKHvsqqqwtSm0P/VIxQtBgDZKGbISXrUxWsALpkZrEXdYI9YgcsKTiEW5b60Rwl1OMt5LruAjZ5wfcdOE8xPzeBQUaXDkHMWXH2dR4p9AKFojbNuEtRXkRIoeRaaqKxHKpUiMp0yCiLJIV47wBYZxeBT5HI89dVWL/SQLAZFyaIUyMhZxmawltDaPCXuVralM6cD16bA0xVNumWfxktf1aaQrwRfGniJk5aI3uoRMlMeslZZoSUxJK1Qn3aWIt1RxUahTUNEJpHRibRdx3akgOIk2y4dMFV/vyV75yBzglMEQQSFe+d/hDajHa/EUnCThT6LYt8agsgINlgpJXxThYp0aYFHWR4lVcHjvCiNAsr5j8JAdfb8v+zp5L+dZ1j/CahAvr0KKNDc7QpSCtWrkfUkpMg0SZNN2S8H7BhEpGa3pmopl3YL3VFnRWcNumrgdX2OzprYtTVURCcJqSIowevwoNi1j5HCeRuGT26rC1A26qqgxRKNRZa+YksCWchQiZFsLOrWpNItmQde2rBctTa2Zxp5p76iNoqsFdzzMgYdhJqGIWVYEvYpYAjpD1uCR61IZCNnjSrCVcCsEDmOrmqZuWDY1KgWmwx4/OaaDZ54DPkSsFn9507Y4nwgp062WOBS9jxzmyMEL73wYHH5WvNgUPHjO2LqiXTYYW3IgcsDLuA/TKPIk1sMZj0lGXtcCmcrWkJLCFTJmJpENRAW2dF1Wi4pb+Uzo97x59ZbbcWbMGl+1nKXMZDIPbubluma1qgh5pjOJzlhmN3P77jVjP9HYluwDSQVaWxULsSbGjDKWylZ8+v3v8aMf/4TzyyeyDgNmN4nOqPjAx66lNhadI8OwZ39/w9nZCqM184Pj2zdv+PK3r3j97oa7Xc8J3V1rLePnes8+GO6+fstXv/qKRsNqWTPcHHj+8QfUmw7nZnQbefb8KdqDUYYpa9RyTTV4opdCaQyRuunYVhV20XL18gVPP/qQbDUP00RSkvpobYWtKnJqhQo5O5Zdh9YW57wE6URw44RRsFwuGJ0tOHiD87Imcm4mxMjgJmJKjxZpsXdbsQUrWTHVtdBQY1YSGU7GCogDozW2qgjeM/vAHILY+nIUV4rWGCXr4jkCBdpGSmhrCCljjSYME3maWOmKShmuzs5ZVg2vd/ccgsMuWmYl5ESaislPEl1sFbYxECNzlhVmDBLcpBTgI16HItUW50wiY6u68FXKNayFi0PUaB2JJxbNH6oAmCbHarXg4uKiZHYvaZqO5fqeN69vGIaZ/f6OX/164PbuDS9ePuXsfFUOpol5SiyXK9YbhdYtTSOdrPfpMQ3vlKmulEBXTkS+k20KrUq6nygwc4H2yJsqfnzp+CY5yJNEX6bgJCksRuZxYJpGhvHI2Et8pMpiSYzRw6PHPaJyJKcgASxaADPBJ3RWVLXBz3NhA0hFHlxgjoGqkgo2+0zOkXmcUAZhbc+eOXpy6qSDTxCzBBXFAkrPRXRntS2M/HLIKy12tSxSR/GfSoEiCndFJqCCI5XYXnEKCINdDl6pkqVQEbSy1obvhqbEIrQ8URHVqQhQqkRRlkho3h/OpzwIZK0vUQqlWHjv0CgdvoKTM+Mkhjt9n+8Ork5WTlFH6/J+5xJgVAojdcrelsZaP/4cVfbMMhXRCkKUGOWmFa52TJ4TUyEmIe2tt9uiBJYSIxQ2gwgJI7YkUgqtMZafKbZXlKTixSj6AqNljZBzJvoCjFKwahpaFDWwv77h6+s7rr95Q100r8cokyajNPu7B1lreKFSngpY72PZykgBNzuPT1lurlpz7HtizCy7TmhzTUtOCUPmfL0SimBT0TUVfh6LjSiRVcUwzYxzZE6J4+jxMrBA6UxbQVNpcoDJgao8eI8t8J6L8w3nV2foRgJ5lustT5484cnVE67Oz4jTxFeffcbXX/6W4+evcYeZ6EXsteoabF1hCKAkqMguliyWS2IKTD4zjjN5HPBDplMNZ0uNNhXb8zM+/PgFi2WDczNv3rxhuVzirgLHh5H7myOHuwE3BVKJO56S4HXTCf/qAzFHNImmKULUWpGULtkCFa1tqPuJ6d0NbhhpVxu2Fx2bpmE6HuimzNWHa1StuHl4YBkiVVUxpEiKsKprxlFEuC2KZMCVgk4pxWK54MnTS/7kn/8LnlxeldC1yDBMuHkuhS5M05HD/S0xBCqjqKwIigOB4DJ9f+T67WvevfmW3c2OcQikKGK4tl3ybHvFk8U51WyoZssy1bjjyNgPvL4bmQ+O7//RD1Aqcbzf8WS1JQX5vhpDq+BssSguJQm4qrsFl+sV7WZFe7bBp8Tt7R239/eEGIpDBnIOZY2rhLrZNigM4zBzCg8Lzonro66Zp1momHZFzgtCDMxuxhdU+rHvBeEckhBWdVWmqhIv7eaA86HYRiNGGdG8oKitpe9nYUGUFNGsNdFnXPSokFmuW4L3hCAOp1h4NjWaTMbPM3maMD4Rtce2K5arhoe7HW9ubgjGsF5vOLqJPjkW9ZnQGXMkJY2qLTE5QgqopPFxJsRAYytMhjgHUpIpbi6N4jw7lBY2jin3qgRy8Ee5Z/1BCwBra7E5pMx2e8ZyuWS7PeP1m7fkrOiPA7vdnof7O4Zhz6F/4PLyjM1mQ7dY4zz0o2eYAsMQ2GzOODuzcqBa6YBV2V9/d6RsrSFl2fWLN7bYO1wkKgkR0roiGgHn5BSJwZPiTE6e2QWG4UCMwtbvj3vmWZj0w2GP81MZHYkqE2SCmbKwn63WxUYnXWdA9sYpyeM5/YMTOlIpyi5dUUXFHAJ+dlSNRZWQnpwyOUHbdmILi1mEd/G9q0EOe9kv28qcNI0y8veBZBIS+PDeXy/jcUEP13UjCtgQyiF40lacWvT3nAWxSJrika3Lb/9uBw4IkEmrx9TG3/mzYt/Mj0LM96sBclk1nCyeFEdBLqO3R2Fnxmr7O9/3vd1Ti7ZAq8IPEL2BNrKGEI4DoGUJrbKkG6oi+tRGowo+VClF1AmVJc5Zp4TJwnbo6k4+TCVDQtYAAmc6USdTLjqDR8iQIUThEijkg2qQrAqFkojhIIFGNZk6ZdIwMt7tePXZl3z5j59B7wRJHBIxyD4wGyvi0yJWBSXrihhF/Ko0sw9kMlGDVF9JdBdZIkK7pmK7XuKdTNo2qy2VNRz2e9xwJE2K5CUUJZMZo3Tfc8h4DEHJWmGaE9pANhaKsMopRVPJdXd+teXjTz/khz/5Pp/+8FNMY9kdDiQ027MzVosFy26BOxzY7Xe0d7dUywX64IhxJsTEOE/ocURpw3q54ME7VG6oa0MIMLrAPM6kMWIcbMzEqluy2pyxWm8kdyB6sk5cXJ2zXK8Y9hNtM1BXSyq75/rNjvvbWfws2aOSgiRe8hQjKSaMEhb82li00oyzZ5w8rUukOaNcoo6KpbKs2oZl25Dalvaj53z09BKzXBG15fXbmkM/Ms+eXmum0ROiZ6GEyZFdwTFrjQqBOUZWmyU//fRjPn3xnEVlORwemKaeeeoBaUhqa8kJ+uOReZ6oKsN6vWC76XjY36N05P7unsPDHdnPbLqWp+dLDDXzEOh0wwdnT9naFcPbO8LOYQdDPEoKnkuZm+GWKla0Zw3UiodvrjEkbt9ds91ssU2NrSsh+sXE5vKCqlug25pkK47TRH/Yc98fS6StKis7EaidtERkRWUbtBLHVpOsTIoriw+iK9nvd7LuRZxjupBH0RUhCK7bz55p9vgp4Fwm+iTkSeUJKmEb+b5GK2pbi4kgZ7ytmCZJtzw5lLQ2In5GY3RmGjwxenGKWYhlDRxdorUVaXaoObIwFefdkoVtuH5zzRyFuqWswWcYfcClhHEeF0NZSTqZZXqPj14KUk4heQmSJieNd5JNYIwCo6U4rgtKPwv1MJT010TGxz9wAWB0LeAOZQuDXXN+cQ5KAkBubm7xXuA/8zTzzatvubm+5vLykrPzpyyWI03dslod2WwmvM9UVVcUm3LfrmtL09bUtcV7ObhOcbwSoOJl/JLFa1lVDdZIEEQikpKgbb2fcW4ghpl57Dkc9qgcQWeG/kAME+hMjCO6xNGeulxV8MQnHHFSJ3rWKfdeLoZpkuJA1N/yhhmlH3n78zjhnIjx2lbSpaYiRGuajrbtmKZJbvoxF1KV2IqMteicS7CQKROPMtKOkoVujXDST+N86fbfj+eHcRDfamU5ZRHIIal5f76qR0eFKemOWtti13xfHDx27GVi8WizLN9LFRZBPhUUj+hg/f7vlqJAIqLz4+H//nHImkLXsts6FSryV98XFSJElA9HJj3SGlFK4pRTRqv0+NhlFCG/MhCTFHoyORMITm2FSJdikEMuZ0KQFYoxBl1FfPBiOwVUzuhK0Kq6rCpQSva3OdPY4goIDq3FWaByJowDtYJ4PPLq2zf86u/+M1/+8le440idNa4AjlLOBDJKRXJKzAWAVFU1EXPCMaGyIqRE3Vq65UKSGfuRmBNNLVTG7B2mssQc+OCDl1ycn/P61Tfs7+5IwbFaChDIWCtKaWUwVUVSgcNhwqOIusIsBJQTjcEbzWK1YNO2+BhZLFq+/6NP+dFPf8CzD56wfXZF1VY0l1tJkUMxzTNhv+P+3TXfvn3Dw/FA03W0S4k2TcEzzjNqONCt1jw5W2HnmfuxJ3i5QWgtUCRvFMOUudvB9z6wLFdbxnHm7S+/RVeJyydnnG/PsFYKAhcCTdty8aRhGhN3dzf4kPAxS8CL1jRGExRkJXkAk8/gI7VKVBnMfiJrw+wzh3FCG8tm03J+fs7q4pxUV5xpTb1csR9H6mbBD842zEPg7nbH2A/c3ex4d7vHlNVGSDComSkExhRYnG3445/+kD/69GNaN5PCyLy7Zr+/R6lMXQu2N5ZETxU8y1qyM3Y3b3n7ZsT7mcurLUYpnlyes+w6UlAsmgXZG453A8opGg8Pt9e8/tWXDO/u8YeJRkEKhUBpMt/8+jXVCj784QfUAbyb0CFSG5kkdOs164sz7vsBlxNt1zAEx+hmxijj9ABoWxGdRxHlniZjM4TkLHTVnOSatVpTWUNtF5yw5IqnhJCYSpCYT1nurUqivVVrsMsW5zNuCsxTxDvwLuG8l1TFlBmGsYhfJT3VakPXZkmPLIwTVKLSFba2Qi0kMx97lAJdV5KSmGXqHHwg68CiaLgutme8uLzi9t0NR+dIxmIXS3KIPDz0hCzR7GM/Ecs6NnohNJqsCrgsYyqDUhXJy/2+suKOC0GmSKaAsGKMxJyJWaiILiRsXWFzeqSv/sEKgBAUMSnaZoU2iXmWXGZZCVRsN+cYLTv53e6evj8w9jPX8Y7DwVM3O1kZLFcsFzt2d3tu7/bM88z97p4QJc/5/HzD2fmWxaJluVywWCylWyVhrBJPtkZiTbNcOD7MuJgKP1oAMt6PBC+wmP3+gDVQ1YZpPKJVpG4qaiv5zlrFcsgqAVEAJ8yt0SJgO3XSJ2jP7Cai1sX2pYVi951dNhSRSAxYU4blKVOZiqZuyFkRQsKYREb8s6CxtsaWgBOlxdcaSxjHKS0xhMjMSF1TAn1OsZ7lw3sKR9KgTRmrx9KFnw5glIRmFB+2KhjmmJIE8pzij1URXHI66EWRr7+LVz4d4mWAr0un/F4D8P7XY8cvbOJygMqIP0axsGlFOexPtsZcYBjyPE45COQsjzOVqQa6UCC/oxtQEp6RSoiPFCNyA9Kq4JYBhezTU5bRuuSKl4mUydS6KUVHLuzFU2FTnr3SGNNIAYJQFdEVSgnJMcVAZWqm/QNf/uJX/ONf/y3f/Oozjjd32KwfH6+yRZiWT5bMRIgKlSFo2a24nEhRmAP1ouHiyTntYsGx7+lnR4VmuVyilSGGQF1XvHz+lP/2v/vvmOeJr379a1RMXJytOd8sqatKaH0u4FBMUTGGQB8U9VLGvFlJJoGuLclIVkCqW4wGpxOqa1ldXWKXHYd5RKe5cL3k+chkToSFD3d3BO9lpEliDgmdBLhEEoZ/YyxLm9i7kTpmdGWYR1BZsbCKRsFqUVNVLfMUOA4P7I/XXD7ZoJQumg35meM4EWYFqcHWLd26ZXc3MQZZg1VWkawmGStCVKshBR5CQodMZRVeDRwmz2I54wikxmJ0zZQNC2UIPtBPEw93O7n2qyNmjlzqFusjIVsumiUX64Sva8xqAaZidI6QE0HBxdMn/OTHP2C1aNjvbhndAMMefdwDmVxZ1psVldYcx4Gh70nW4pPn5uGaftjz4sUzaiOs/K5dst2ssapi2a6IQ2JsRvZvH3h484b7VzccX9+hepmoWMNjJ95WGrqGel2zsg24QFPVXF6e07Q17bJje3XB4mzDIUe++OYbmv4AlaVZrcSFMTm0lbh1pRDwFYqgZXUWg9iVtRbGibUGonTXlZFVllKKzaqjbiqGYSRER0ieaTa4MBOCYvaZ4ANNbbBYGlujaMjJMM2OMXrmHBh7CScLIRAyuHIv6489xmiskcZW5UTysmYDiSQ21qBzBCeWQ50TVc7o5GjrlkW3ZL3c0E+ed/s9yWpcEiYEVcMwe5SVSXOMAWVkHWwwxLlg8RNEFbFZpqDeeaEjJkVdyxQ8ZckFkKwGiYtGC1zqJJZOhYPw+3z9/iTAbEtHpMk5oKiorGLR1ayWW7abK9pmRdeuubvbkVLkYb/j+vqGeXQo1RDjzMP9kRjfUNkvMFbEMd456kawjBcXG168fMnz51c8ffqUqjK0TYOtDF1TyQuhsuxD48A0J+bJ4+b3HH0fZnKUsBc/RZIPhJQh+TI9yMW3nIuQDyBJBZg0+pRDT8Jo6f4FYiMfkNoaPDKFkNejKP0zOOflYrI1xijmecTNM2QRsdR1S/SpKIMlRUrk+e87XP2ogC9RuUmwlPLzKjCn8bsUCLY84FxG7ZCKcFKVvbHketd1A0qXdUh+PNhTFmuWTDreCw7fC/DM485fpjHxO2N5Q46Fwa3lAheoRn4U9/3uukAVsWQZ4ev36wSlxKoov38qxHgsFE7CRTgVOSf9gExvTrAe2Q6UiY6SdYNS0sEqdZpoyPOiaClIAQzSESJjxlNhpZQIF6xJ759XkUWc/o543m2ZJmVUFACO0hqKEG93c8sv//bv+Nlf/SX7b98QDz1u8oSUmKEUirrE3BaKWelUm1bEoj5Gsq1pupZ2uaDtWqit+NKVjAeNsiyXS8Eal/ftkw9f8uzpFV999Vu6xvD9T1/w6ccfkqPn/n4nKmvveBgCt8dAHxLt9ownH3zIu7sdu4d79KIjxERTCYgqHY+cXWywVeZ+6ElG0S4XhML+gCxuG+dJkyOMM27/gHIzq6rmvh8JfsS5gM2wXiqaShHdiI8QvaeLmWUN2EjvFJvtms2q4cl6wZNVzboz7A89w3SP0hljatwcSWEU3Y6tQVseDnvGfs94FE3DnBSjl4KuVVqKnKyoqpqkKVbcwDTOaJeZlad2iWoKEsy0bEjjwM0UOETpRo+HvSj4m444OXw/sbQt834gzxEVEyut0LWFIOLhs0rTrVZ06zVV17Lo99R4lm6CaaDTmfOuY5wGwjyxmhu5n93ec7i5JhlFUOIDf3Z1xvlqyaKqWSwbgSYtVuisiS6Tmgh2xav7gXe3Nxxubqlzpqk0qbAEzs6WLNYty7OO1dM1q6s1x7nHTTMfffQhR9cz+kAfZ6yfaOwWs2j5zTdf4dB88v0f8HSzoTIVTDKGzkm0RaYSkV5WmeATtrIYLdj1pET8bK00AlWxSPvZQXaloIFMJVbl1DCHGR8EPrXf9ygsfobgFTEaYlCgLJWR93TsGrxbEWNi6AeiD7IarQyn0DLvPTmLRbuuamKOhOTQlcZGCfgyStEZUzJWElW95GJ7gQuJb9+95a4/EhREDLP3LJaWqISBYYoVPkVp5HRBgAeg0gajFHGWxicEKbzlYA8iaLciEhydTBclalwyc4wWPoHR5vHe+wcrALSyJd1PboJV1Za4U1HjV3aJoqGqFkzTyGq14u3b1/zN3/wN4+Q4u3hCzorb27viR5bR9Nlmy/MXz7i8PGezXrNct1xdXLI5W7FcLFgs68JfDuQsh74PjmmamacZ78SKFWMS20ZwshvPsYQnSOY6FPseMucLPqAAawQ9Kmp0VRxMGrSw4EMIoDIaRQyBREHDPuYtq7LGSBgl4TDeR9pWlKuVrQX8EkvHazSzlxukrWusqUo3K4fcSS2v1fsJQgxBOsimoW0bYpB9j/eBynliFUDbUghACO/piSdBnMBDSteuq0dU8vuDWoiDprLSLWuDUUb24bFQtqyQ28TGJzQ/UEQlVbHSopVIIT524XJYv7fz8fiz3hcG+TtX62mqIM4LsSBKTLF5nGwIfjQXTYisIaQ4teU5wQklrUuR8t2fc0IDnyYSgi0Wm6QpgkJVVh7WnvQJ4v5Q5YXLxVWRAWsyVmviaUpEEtWcvBm4aeazX/6Cn//nv+Ozn/0Dw/09epwJhx7lI5UW8Ej2QT74JxhTFqBQ1Apta3QrEcXL1YpmuRClv8rMKpKcx9iK1WZLrS1100iXYi0W2L17y3/8v//fuL+7o6sNz5894enVOe/evuawf+DYH3k4Bm6PibshMitJExyixpuaarXh8vkL3r59jXeB42EgERiS5+x8wdu7HQ+HA0/jhQCxsrxGVhvCOHG4vWPaPfDw9g3TbiehJnOiNplFC402rJYWlSJ9H5hmqDt4tlEsNwuunj5B25bLi3PImsZa4jwxDXuhHzqHrRMP+4GYMk1TyxQnaEJUTC5x93DguHf0Q2aMMCOhULFpGJ3EbXeVIcZArcVN4+tE9FKMVTmjQiTXmkpnkk7kaWBU9+QcmKeeddfi5gizRznpIBtjMbUmzwGVIsY5vB9l2qAV48EQH1rqrmV+V7PYrDC1xabI9nzLYrVkrDTDNJFDYk6ZbvZUw8SYAv00MEXPx08v+OTZc9CJ7fma9XpNXdUc9j0P9/dUQTNe7xnvbojDEZsSlVIsOsvmfM12teby6px21dBuWiZmfAzc7u5YXq44e/4E45a4h3ve3tww1YawajiME4d5ZH1xia4tx3Gg65aYytJ1C0KIQMDHGVVswUorurZDZXHUBO9RSvRlx+MRsuzGqyoL54RE14qjSZC/Fh8tLkqnXlcWa1vclHFzZugdbk50i4beOXzO1FZTmQaFWFJVVhhr6NpGEjjRuHlmGAY0WazZIeNCxCiZMhBDif2VIKEn55e8vHqGQvP6+h3X+wd2Y0+fIsv1Fl3V9N7JfDSD+HMk40Bpw+yjCHoBagsY/BTJMclU2GhCyrjJY4yA41KOTLMXaFEla+pMWQ0k0Sj8lwF3/5++fu8CIGURJFgtVfJp1Cx4WI21FVdXHW3T0fdHmrZm0UnAiDaWs/NLclaFxlbTNJI9vlgsuLw8x2jJN7eNpjKWrKPEUaaZaeyFtz8PxOhJOQqKd5pJvugElClugYhWor6PJelOiIGqpH6Zx520jHsNQrcv+1xl0MYSSoSu1Ug3iFgSZRVwCiDSRUUvB7iPZfecNd7/LqZ4nh0KTds1NHWLNlowjnVFTLkUEUHAPLwPOglBsLciXhF+ty8K/hgSKR4JIVC3DYtFh44CFqrrGlBUthLlsNKFp6AKtU8/YpA18hyryqJtRYiamMulUUbgCokbTqddvAy65RDXJYNAye+JXfDxn/PdFcCJtW1t9bgqEYuiXLCS0Z3KhIBH6pnsvMQWSdbSZXOaVqhSmBRi4eN6oqwBeP9z5Ksse8t/a62LpTCT+K7w8TsroZMgoQgQc7EiakBXEiQSszAbKq3AVoz7e379i3/kF//wn/nNZ7/mm99+iRsGbM6E/RHlAo0yTN6B1o8s8oyMzm1dUbUN1hhMU1Otlpi6IWhFVpbN2Zaz7YpFpfDDkdpYrNHgI/vbWx7ubsl1Ta01bug57ndU1nC23TAPPb/9cs9ud8du98AwRw594u6Q6TOoRcX1vudd/wVZKy6vzlldXNJ7x8PDHVNSaGslu94mzoeecZxIPlJphYqROE/4EHl4d8PbV9/A5MjjiPaOME6cby6otGZZW2Lxv1ujWC1rVHZcXbS8eHnF02fP+Ojjj3l46Nnd75nGif1hZppn0dUkYR1UKvNwmOlHJzdHWxED9AfHYfS4bHBophSYEniVJTo2eLKCum3wVjHGjCs3atNUOOXYu0xdZyptUdnQJoP3kTnMPLg7tEo0tYFaUyeEcloZQUHXLV3TYbIiupngBha2ebSyGTShP3DY79BWM+1alFHElPBnW9YbAfQYpTFtR1M1VOsNTcz0wXF33HOcB1Zozk2NbTXrdoHOku7Y395y/epbGALxZmD35g0V8vpW0XC+3PDpR5+wWqxAwxRmxuy5Oez49vod394+8LF9wt3Yc/HyCnO+4T7M0DXc9nv2/ciH3/+Eq6cv+eb1G/zNDR988DF11YioTsm9McdyjmhVJoW5hKDlIm5ToKKIM1WmrRvRBRhD29QYrZjmicPxgI8lnljgJqxWK+qqY6oCc5VkkhMk4dH2Az4nBh2ZZy+JlaZBa9FrtVaTcotWVvgax1r4pnVFmyrMrHF+EmJmStg5oWNke37BB0+eUmnN6zevebe7Y+9neu9wGqoy+ctpROcsMCwvjZCuLHXXMbv50d02pYzLERVlxWqVLbAv/4hkzzk9uge8l1WhUPAFznZqWsdp+r3O9d+7AKga6Rq1EcFZdVKVI0lwIDuUpmpYLjpSjiyXDU+fXaK0pm5a2dvHTFU3j+r32lYYqznsH0jJET3Mg8PHWchtrgcV8G7AuRFU2RmFyDzPqGxQyj6G3igKpxpompYIuCkUq5EAclAwz2PxyhtCyGXXDVnlQhwMj2PtFHzZqahHX/0p8CelhOTCa1KSblmW5bFYv0TtX9kaKBkEpSARH2fJoE6JEEMZQWVM3aDI6JyorRAOjVaEAsVQqsK7zDhOHA5H6rpitZYP8DD2LLoldd2wWCxomhatLcZksTYVf78UKCcbnQgcxUdaPT4f1OmAfX8w6lMKoJywRb9QJic5P3blcm6K4+FxsvGd7/Pdg/99HPTp6D3ZQN937yebIpwQ0ae4Zh5V8e+dBnJAl4fw+F1P//+7UweZ5wsQ5v264tHBcHp8SlhQWr3XgqQkhSpIF6tyot8/8M1Xv+XLf/xH/v5v/oZ/+Nnf492M1UI9OwwjVVa0usIlyacfR7H11HWHrSt5v6oK29b4EAgoWc9EiT/+8Pvf56d//Mc8udgy72853t2QvSCep0PP4f4eN3tqpRhiYNU2LNqWRVtjFdzeXNP3R+H/K1htN9xOA1QzIYhYsncObMZ5x5Qiq/MznBdxU7Y1Ls2EObFaiD/84W7Hb371K2z2rLoKnRP9wwPvvvmWaX9g2y1oiGy7mmAU67Ol3PxTTVo0DIcBpeD5i3M2qxXb7ZKrqwspkv3Mu9ff8PrNNSjL6CLHeSaUwC5bQa00sX9vB/Y+M0/yK+eMypagDalKaGOJc2QOjnlUtK2iOVuSjcZUih/99KdgNPf7B7569YqH+yNGSWFjUmRlpdiL2jKGgNKw0jXBJ0zO5BCwKWOBdg6048xmueJitcLfz1grELEqy248Z6FWphyphEyDGwdu+iM3r94ILrlrWG7P0U0j7oq65uXlE8KLlxznI+2mY5lgXXcon3j3+huGYRQR6TwRjhPx2KPDzGZZsagXNKZl3W1QC8U+HjkcB24fdkxh5n4YeH3Tc5gzH9QN7w578tDwwUcf86mG6/t7Zu+5fP6U5x9/xKtXr/nNl79huVjzox//hMpIZ+3K+5RUpqkrqsoSXMQFRwpJchpqW5C2DmsVZ9sNV+dnWGtw80xTW6IPOD/i3Uw/jtRtS9W0AvghPxb9dWVo6haSEoW/XWBsxewWwtDPME0TzgXcPJMK1dMoSzBQaV2mw4LP7tqKcdTUKJhmjPes64btomO43zFOI/eHA8PQM/sgDZc2DLsDldVFIK7AmHLPU6jKyPutFEFJYqHRlsY2VNqSQ0IHh7Gi+DdGC8GwsBxOd7McZJ0aUkTPCW0Fg+xc+L3O9d+7ANieLeRFfrxpykOQrPiKytZMk+wlNtsNSkVSduQcZGRL6W4UxOgLqSnhlYgi9vs9OUdsZXDTiI8elSM+TNS1IUUnO3xVqp6UKJtvCeSopGuf55mMRMSmfNrplGmFkgtMfNRBEu9Kx2VOKYBkcg5kyu63kPZiEaFZbVDaohHv9zRO5Gw4Kehzkl2/1vaRCVDXXVlLKLJK5DnhXUCFVEzz8oHPOcqhr1QBJEWUSo8WROcn5inQH3uUbggefBChmNaSmqcrwzgO7B+O1HXDcrmi6xZYIwCOpl3QdS3WyhTAluLiZK1LxeOai6jvZH3TRZRHzuXPHgmVv3Nw5/x+8iFI4vdM6lPKFrwPYvou8U80APHx339XO3CaKpyAR6fHrsr64RQSdYpgPoGXTse8PgkW/wsHwmOs6O9c1+XAz6drHMEMkzhJE04zDS3zTNw48vr1t3z1xRd89dlnfPPFl9y+eyf53/cPODezWCyYx5lpciRTMceZylhWqw2LhYw160pWQj4EvFyZNJs1q/Wa5x9+wPOXL1mfb3nx8iVPXz6nMYr9O7E17e92jP1RromUmYOn8YonZ2cEP9LUFl0+f9HPaKTYvXrylM2zj7j1X6CnSJwyvU9MSV6MkOAwTHz97RtqqzC1xieYxhkczIOn3x/58te/4e3nkUUFHz67YtFY9rd3uKHnbNHRGs00OdbrjsqsMZVldzdh8Gy3F3RtR0bx0acf8+knH7Hb3XIcR4bbO968fcvNzX2Zwil6H5hVQlkZ49fWEJLCBYXRFTlbejeyu3f0RynYqkrEZ1OUlEbVaGyGY7GbtWGkqlrWF2f8s3/zJzz78EM+++JL3v67f8dh6HFRVOyr1lIvDW1X09oKHwM+iNXvdppJIaBiotaW1hpwjjAfWPQjz9Zr6uORzmiatkKTMCOsVgvqroPoZTJYVbSLJSlGhn5kmiaO+wPT5EEbYgLbNMyHgW69FEGkz5h+Fp1ODhy/ecPDwwFtK85szeJqw/X+G7rLi/L5VOSkCTby7niDi5FsDHEp2HZjFXmY0DZQb7aMKfKLzz+HumW5WbNF2PvbiyuGUYLgnJt59vQF52dnaGNlSksiF3dBQhoFU7glwtmIaDKr5ZLtaknb1SwXDYuuIbiZlBzOTYzHgb4/Mk8z4zCTsqaqVtS2kumurYlRJq7GWFkBJw9K4p4XTYe1axKKh/2eefbkvGQandh4XcQCdWuKBU+AOnoeeLpoHou188WCCiWEwTAxjQdCmFjU0rH7EEkuMEwOWyuMLgjfLFbcum1J1rCfBnRdEVLGR9C6AqVJWZGKgFVlYYgIW6YGIjlGjAEdFErLWehKw2qsRRuZUv0+X793AYBynOhvos4uaXwJudnMrjRcCecDPg4oAiFOJIJ4FX0oHtDS0RUP7uxmObyQCUP0wuK2tox6Y0LliCKRQuAUJGKNIaPLRKISj3YsmMacpSBwIyTZ9YsOMIvdKrzvRo0WayPkYj8sNLDymGXkLAQ2T3j03acksIiUhXKlEK+/NRZQdN2KpqnQxrDfH1FKs91uqKqmRM76suePoEoQUPGqF+k46FySC70UTDGhyKJm9RCLK+DET7BNJVVumvFeioNhGDFaCoC66WlbyYuuKgm8adpaYnONRE2+Pwx/lwOQ4vuD9jSWB8o+Xj+O2G0ppr5r93v/vd538989/OX7FN++Mo+FgnxL9fh3TQEhfZfNEGN+/FlKaRmJnayC5edQLJOcXACPz7F8iOT/HtdDChELqoysAU76hSKWNFrGcfv7e26u3/LLn/8DX/z6V3z9+RfcvX5Dv3sgzhM6J7x3NF3LsD+QoAQeGVbbNYvFgrpqWK42zE7ErOM0SU44GVVpXjx9zvd/+CN+9NOf8PT5M3RdUbcNtm2I0dHPAd202Lplt9sxD4MgVY0QJ601uDGwWLQYBW4WO5Q4ShJXT5/w9JNP+JvP3zD4WwIVU8zMSeODw2ggZg6HI6uVjKDRQjjUAYZDZNz3DA9HmlbT2AblHN5NhKGnVtBYTY6etqu4eHHFoml4++YtXaXIydJ1Fc9ffsz2/BJTWb693nFzc82xP6BQfPXtDYfeYW2F8+B1xq4aVG1QRgnNz2qiNtimFRdEN9G7G47uyBwSIWcUmmBAawFKdU2Lt6N8DnUi5ZmLVUt3sWH74gr/+iuu54G3XhI618uK1eWSvK5RbYuyNYSIHyZ659mf2A9VS6UtI4DW5MpwP3mujzc0Y+TFWc3TzQajEmEa6ccJPUSSc2yXHauupa1rmrZhaWqWm00pYuUaHKcZ5wMP767p73estxuyijy8/oazyzNWmyXdnOiWW5q2FcZIyIx1RchaFPbGSDplVeMyrJuW5dkZpu2gashK89mXX/LZF19hFkt8hrv7HT/7+T/w6fe+x+bsHB0ixMw0jmw3W378wx9xefVU3DLGcHZ+xnK94tgfGeZZlP+nbZrWaCurmvPtmieXlyzahrY1TMOR/eGe4bjn8HDAKMNwGAT2ozQ5KaJXkAzaNFhdMjByJfjz4KUQUwlrwKoo74sV0I9rDIumou5ahsOA957+OBKdEWV+jAQX0Dkx20iDwvhIay2Xi4boHfvZgYXlsqbuKqqqxY2ecT9go0K3muP8ICFzTf242j17+gSahm/v7/nq5lrC0rLQNqdpJKiIUQXQFhMhCx8EF6TQQRrWeXZyv1aaGEobk4H03bbr//vX710APDzcFL31ybpVobJAClJ8b8kLfiKkiRjFpubCQEhzUU2XXW4QxW2OCTc7lssly4UhOMfsRvF/qkzwchHNgWL5CoVYF0EJfc8Um5GLM7aqabuOccz4MAu6FyEuhZiKv/13u9XT4ZSK2t4FWTOcDqTTYSNvRiyCFhAwkRHCGrLrizEJ47tqZRKRTntriUc9jd5jCGUK4co7dgL1CBdda0knFDCg4JJnNxN8kmAZLQlpUggJFENUrInsT2TACmNqclbCsdYSwuOc2KJkHWJYLFq6ZUtVWxFOtWCsfPhPIzWpSiluBzkAlVKyB38cYBQNQJZVyQnck4q967uCv9Mq4LuH/+N7ocXKR1HrnzgISr9fCaRSecgrJ0rZ8kMexY5ZyWsjRUn6nWmC0u/XAv8ldCjznQlIfj8xUCljNBgj4+j+eODduzf83d/+LX/55/+J3c1bpuMRfxyYD0fm/RGVAl1V02hDmj2LtuPJsxeszjbYqmG7PSNn2N3dE3zGxZnRR+aQ8En20y5l7g9HPvviS15dX3P55Al//M//KT/+o5/iQ+D1q2+pEjSLJW6YiCkzz4EMrJYrLi7PyfNMfzwyHB5YNDVGazSnKQwlQ90QlWKYM06DV4qkrSixk8dPGaV62mVHgxbnijKoHElOYZKmyhqbFWly3L1+C8GhkM/s1O9Zrxc8f3rJarsgx0jOjtpm2nbFB59+ysWzj7g/TPzq89/w29/+FmtN8cBr7o4elGUOFlt3aJOwqxpTaZkAGQPGko3BtEvqxYZoOhZjZEaLMK/MLy2wWLTMbpTit1XlvpmZoqNaWLZPz/ni9df8+c/+M5+/veGoMvVCkzYtcdvgVppkIiDhNr32eJ2YmppKVaRsmHwm+4COoLMVxOs4s7WGH37yPc4/eCFRsWPPsN8x7u8FO6w04zCijz0VEiu7XW/YrpcsmgqVM4vZkSJMs9xDWltze3fNsZe46H7RMrmRyydP2LxYMwVHfxhY1S2HucfHwPZiy7MPP6BaLOmDZ0qQbIXL0Cw3vPzwY1bPXpCaJe3KUtWR7eaMu9sdwUcur54yzTPPX36IC562rvn4gw9pFyu8ExWFsppm0YLVxIcj3kRSEJuasRXr5ZrzzRnPnl5RW83u9ppp9Owfbhmnnqk/MvYD28WZ/BtTY3SGPEOuIFWEAKDxHrwXrZabAykJmKutLU2lCT6SkyNHjc5B7skq0taGyihUyqi2oWsXEKWBWFpNlTz97Q3aefLsyMOBGBx+OjKmgO06tqstKmnGKbCtW7a6xSjFPZ5sEuvlQizbxnC2PUMtljRKcXfzTlbMWXRI0SUintq02FoSXhMyqWaW1E5bmo+TkF3Wt0nupVpogI+xyf8/vn5/DoAfmJ3Dl5tLZRsZtSVNiko67xjlsLOJee7Lbj0Qkkdp0Q6klIgpUhnxh0YfuN+9ZbVayQPSEVMLmtZ7J1VcPh3aMspLKEJMODdhTaKyLYmID+KvtJUhY5inqfjwDW3TYm3NOMy4MEt+8mLBcOwFxasMOQdiktG/LvtfSjeJkimCKt7u04GrjZXvO5/CQ9Ysug6fPOvFgn1/BJVYLDpSShwOEpncto0EI6mMVpmqNiiVmacRN3uaSnINTvG+fpZRGcoQk6hZvfboLOAWkAAlZRUxRFIyWFM9duanAzAVImJOnnlOeD8yuZqmrugWDV0MtF0FNpfna3l8IVAoJZfMSfx4sj++P0j1+8Pz8WDNj3/+3c7/NEXIGRRGLEJoUpIPg7WGytaPdsWTJoOCLX5PBCyCzDI5OLkBQpBMhXz6GKn3uoD3Or/3asUT9riUJAIsyZJWR3mecQ68evUV//iLn/PFbz7ni9/8hi+++JymMmQvyYLjNJJSYLsSZTUozi8vefnRh1xePSHkxPXtji+/esWx77Gmpj9KF6K0JFUqo/HeczgeOU4j7c0Nl0+est5sIMP1m3e8vblmd/2Wn3zvBcPxyFfffM2XX32N9oHgPN4J3/zl06dEP3H79g3HoUcjh53Sou3ppxnzcI/WguDOUSZ7VW3QSUiIKWd8LNOzKEVkdFGKDwuLusUCfjwy+QgmUxvFYtWBEhvjhx+85Pxiw36/Y7+7Z5hnLq6esj57hmk7fvPbr/nV57/lzc0ObSq8cxwGx1wohtpYptFzubrAVKLXCQhCW2prhVGKoDWDD4zOk5RMBLIKxWIKkIjKE/As6pbWtmSjiMCyPef7P/0puar5m1/8nL/++S/YzZF2Y1ieLWm3K+yyQnUQihh5TolDwW/rukZXLdHJtVPZmjB7xn4gRkXbdVx+8JQP/viPqKzm4eYau1xCcqxay9PzLToGjrsdru/FLeE8w90d3767ZlUb2tpSacuiW4LSdF3H9myD8xNNa9EqM+wHdg87Drsjx11P1y5ZrzacnZ9RmwO7/QNEICv6oefr63d8c3PLmBO2W/Dy0x/w/HufUq87cqMZ/MSyXvJs9Zy6brFVzTBM3N7c0XQbrq+v2fcDF5eXLFZn1E1LJHO/33NWULgpwuGwZ3KOptacn6+5PLvi4vwCUmDoj7y9eY3KnnE4iBJeWbp2JffwugFl6XtHcDJ1TWhyBG3F8z/Nos5vuwXi14+E6Sjs/nJwGq1o6gqUaHJQmtoaqA0mw7KyoqxXmaVR9DfXnGslkcDUVIuO49CjYmBjNFUrgvb5OFLlxKquWWNJbqIxkEzmrKlo2wVzhMonSU0MiZ9+/Cmv+yO34yzkzaQFcpQUpCgI9+8IqjPSyKUYHhNgT1bvqpwDOSfGef69zvXfuwAYH3ZFyRkhZ4KZiEoiCIOXVDttNFHlkpAWmIIXmI0xqKyleyeiyx5Dwmgii9aQ4ozWmraWJ+GTpzLqUdntyi5fKY1KCp3TIwzI50BVVYxjzzw4rDV4P1NXNS5KsI0LgVR2wyEHYohUucJUp/GyQqlawDsFCSqv+Am1GESgUxnqRuxy680CtGacJuI0oSpFVCP97JnjQNV2YGdmD5FAjpo5uKLIlxtE21YCG4pSKGmg1oYwjeTkSrdvqZUlhIgPCWUM0zyhdUXbdJi6wXkZH1fJsliscS7SVB3WmpKKNePCRFZJYpSzLlqDmf39Aa1huVxy2O9ZbWcW2zO6eolSHUrVKCxNs8CHyAkjXLJURNegUrH4iCAyJnVSEYCSjHWFfFAf8wUKfIniJJHo5Fa6fi2aiFMhkbMgbmPyRQtwKkhKDVyKEGst2khaoGhF3ocG+ZRFgBQlKrhpalkVleAkayvRLCTBwQY/oQuhzI0jX335Bb/42c/59S9/wa9+/SuGvmezXvPy6gm1rbi/25F9Rm8tL370jCdPnmAqy/39nrbr+OLtNX/9y8+IMXH99hpjK9qqJtOTlaLtmmJZpUxCNPM8UVvDRx8853//P/6PbM/PmYaeWzdz8+4t2/WC4/0tf/nnf8aXv/kCFQEXqFTmJ9/7Pv/VH/+U5xdb/h//11dgFdaKILSuWmLKaD8yhUDtHBdnZ2y7a3bvRiTYMEnxW9CtKcI0TDRNQw4QJxmWrVcNT84uuLpcsDCWVZv44PkFH7x4Lm6VlLBVhbWGvj+wH44c3cTZsw+p7Yab3ZFvv/g1b2/27A4D/RR4ON7L/tQYsEIGzSFgFzVJB+qqRWkjO1ol6ue9G6nrinZRM3spICHg5qGslOS9RBtC8jx/+VTWkjnx8uNP6DZnXDx7wb/+7/97fv31K/7s737Bl2/3JCsQpK5d8OzyirNNjVUzfX/Eu4gfHPgk0ycQwaeyBCUWwpwiU5SEyPViwcvvfUhuFCFHVKtJ3qEaRd02RJMYhp6qq6iqNSplKm0gwdT3zP2BaT8wjgnn7lisFF1Xcz6c45xjtVqy6BY0ZDwVbpx59dsbUnrHsyfPuTy75HA8cOx7UlS8Dl+TW4uxYDWEeSIGWG0bPCOHeYdqAof9A2fJ0JiWDz/+kKZd8qf/y1/y9as3XD37FGNXfPGbz7m9G1hurlhuarybaLuFJE3ailXb4PqAaRwX5xueXi2oLEzDNYfjEedGxvmGpjIoHZiPM36ynK83TMNA9BFrGio06+WK5XZL1VQcJ48moqxBZckyMcoQndyjarvAjQe00WKrI6OM5njsySnR1g2b9ZrRB6qsaVLAzxOttozv3vHq7/6B770448mzF1Rdx35/ZHh7B85zttnSKE0eZ6rjgImJKnl0PLBsLKtG9Dx1mPng7CWv3t4ShonDYQCVeXJ1ibMWtfCkqiYWdX/wGR8TAWHBzKMj+ijNVspF4pxEm2QEkY5ODPMBRaZZ1H/YAsBPI03TYOumHChOdt/GUDcwuxEBq5w82YqQ3u9xZQSfippKAg9VGQVbW0nQQj5R4gI5hgLEkV2+NtKbxTKaESW9LqEzkuEdoyOEmZz1I1mwbho5eCfHmMRyAaBrLeCYSoI+Hj3iyj4q1vN3OltdlKHGStoUCo5jL2r+lErgjAIVmIPD+Z5x9hir0FWDyhpX/Plt29K2DSn6Mpp3hLL6MEaslkqDj0UIojMkXWQBIm6LPqFMJJhExEmEsPOkBMZ4claM/UTdyOohxsg0jzSNxdQG8okxUDDHOjMNkkamrSHmyGR7NtsLdLNCFfGY6CHKKJ0SZVmW5ac9es4lsKko539XZHfKBxDlrdIGjRQ5CkNl28ebdcqhFAGnbv8UWCTFQ0q5YJjhxHGI3j0GG/kQS1qffOBPO/66bkhJ/N7Bz1hjWSw67u/u6bqG6BwpBbq6JkTPl7/6R/7mL/+cr3/7JWM/8HC3o8rw/OoJH334IU+fPmOaHK9fv8GFwOF4AKV4fb9j97BnGEbGccKNEzkrVoslVbdiu97QNR0uzKCyTIW0wruZ4HNxNVguLjb8n/6P/wf+1b/+r/n3//7f8xd//pes1muWywXu2PHNtOM3v/mc/e5AU9W4yXO+WBCy5ouvX/H3f//XvLu7BQ0hJ2pjwNa42eOz4jAM6P7A1cU5P/7exxzGL3j34EBFsoZuZanqWgS9bsaNEwpDjSK5zLK2qOTx457zD5Z8/PKc7aZluWmo6w6lDMd+4ub6hof9PdrUPHv+EW9fHzkc3vHt21tudnuGyfMwDMwuM7iMjsJhOK2OKisI4vVmRd20or5HkxSQxE5nimVXaRh6QbiuS0S3m2eMhp/+k5/yz/+rf0XUcDwcMFXDB598wvbqKTQd3lj+7mc/57MvXjFPmbOrmmXTYsis6opN1+GnSJwCYXQQEq0R8ZXcnzKGRE6e4DyESE2kaVsutyui63GHe+pKU+uEsoqUA24a6Z1Gx0jdLlhvthJ+laCuGtRFwk89buyZxondw57jOPCw9wwm0x8nVscj5MxmfcZmtWazvCC8u2V3u+P1ux1fffVOBNTWsHKecxQXyyuevXjCJz/+IYfoiLXhyUcf8nD/lpvrN6wXmkW7RZNkKqQ1KsO3r1/z5u0tq9WGrCoe9j3HcWb56y/RVc2zF0/pVhKkM8SE1ZrLsw1V1bJaVKg08LC7Z3aZbrHAWsPl5ZK2rpgHz9ve46Ksgt0kCZ3GSFLlCdxTZYWtLKquGCfhQVTGCj5XZVnbpoi2FoVgf21VSaFYWaJzXK6WKD8S9/dcLDecL9eMs6O/veX+i8/Y5gl1PGA2Z4Ts6G92tEnR2Y6VqmGKjP0RM41EN2EMItiLAWMiF+dbHvY9N6/fcP32FmdqDgrcqmMKM2rRsFkumBSMc8QaRWNrWZsoWdHlmIlzJJ/iiEOUqReZaRroJ2niMBY3j0z+8IctAJQRcZXY3kQwppR4UzO5hOlQdrcGYy3E4msvHHqli348q/dDZaVQRqNSJIUsEZ657IjMe7CNtiK6O43xdNnbn7C2EqSjaOpaPP+meMpBgiGcWOyquqFpmkfVvwjyAsT0KAg0piIoR0zhMYhH4hUztpLOOaRAP/QAEmVcrB8p5ZIzn9BGk8rYNMWApqHrFrRVizEy5VCUfbg1kjWdEj6KKhZUCYtIkCtSQuxNIRICJB9wPpdwiMTsXRGHzIUjIDHFTVPjvRNdhIEQzOOBKnAbyCGR0kTddozjxOQiVtViTdG1vP8yd5VRmip+VhHdyxGvCqc/ZdAlpeqxw8+8XyUUtLDSksxVVhUyfJesB0hQhJ+SgyAwEckjEnZDKnjZE98gZPlgSAKf8LHDaf1Qpr8pOqzSZRIFXV2RQuD23RvOtxcosljFYuA3v/41P//7v+fLzz/j3etvWS8XfPLxpxzPLzkejrRdR1VZOUCVZXSeN2/f8uVXX3IcRgm30YbVakXbNNR0tHVLU9UsuxXrxZKuWxLDTIwzSoObJ9zcM40DOSUpDJqK+/s7/vYv/4LPfvkLhsODxBYXhnlTy/7v/OICP3ncGBjGka++/pq7t5pNZyQfXCOAHhSH44FpDpjWcDgcuN2PnD35mOfPnvCjKRK//Ibbw0jO0FjDclGTkmGMiSkEVJK44vOV4sWTNWdLy9nS8MkHz/nogwumYc907DGrisOx5/pmR38U+2pMgdd3d3z99R33e8frt3e4EFG2ZpwTzkNViUiNAsciRynitEzkfPKEOIOhHAxiX9Voxn5izI7Dw5EUxE+ujKWrNC9ePud/99//D3z4kx+RTJF7Nh3JB0zb4RP86V/9NX/xv/4njndHllaxri3bRc3ZdsWmtqRppD/uCV5CZOrSpGTnSXNEBdGi1C5hnEN5Yb2ftw0fdAvOU6abR+pg5FDV4OpaMguMpm0WNLZmWXfEILyPSlcklfF5RLVL2m7BZtHRBsf9/oFcDri9D0QXGdOBt3cPaCRRT69WeGXw0eBmh86ZcT/AokPte3JXs641i2XD5uqC9WKBPx5ZqQwpYOuK7cWGbBTDceDbu2+Y+iM/+t5HrJYtv/jFL7i76VGVwtafs1g1nF2e0eVOBONZ4WRZj05I9O44cnwYqWwDTU1TG55dXaBS5Ga4Y3f7FhNWqOWSZtHK/R5NzOImSxkJwUnymqcUsQYUCe9GTNLSHObAYtEwzyMhOJrGoKNnqRVNt8COI9uq5ny9poqR+dUr5vsH6hA5I5OWCypjmSfJd/Gzo2uW1FVL8JH+cKC2lmdXz/DzgEas27d372g6y+WzFwzzax4OB+bJsZsGRiuutG694OLijLmpeZhn2kYhBgTFHCPTOGCzpa0aEoqsE6qqcPOELTwFpWtM3ckEsTHM8/CH5wCc1Nfh0R9fBFwpFxV8JQSiMtrWQC47V9n3ZihvnFJCYYKi1veyT0+Pam7p6k5RwAl50WOQG11dtyil6cfxEWmrlBz42gjfnyAebbHva+q6xhhD3XYltz2VIqPiFEP7PtFPBIqSaS68ciJFdCfFwIkDAN8BzKT8+N9VVXz/j0WKoWka2rYjh8w8j8TgiVpS6+Q5pxI76WlqOVgTcpHnHHAhMk2OyUVSFtSlQGQFQnMyvY3j+Lg6MadCzYCtDOMoSlNtFFUliYbGyMREKaialnkYZbqgPdOxZ6oXtJ1G0xJRoDyUsCSUHCgyzgc4oXZPhMFiliudfwEKi+NAC01Q1i/yb1KaH3MIcpaV0Qm+oxBMcExi5xIHRS7vi0wNcvKPpcYpoZASSVwZxTAc0XXDatEyzTPjfqBtG87XK+bDgd1ux+3NDfPY8+3XX/PLn/+cu3dvpfDQFeM4c3Z+xcXFU7788kt+8cu/xXvPzc0dwzgyjAMhRtZnW9Zdw8sXH9C2LUopDvcHKmMIzmOsxcWIjR6thDrm/cTY7+kPDzg3laxyw5s3X/Mf/8O/55/9s3/KctFwebElpMjr13uGoefljz5ltVqxu93zbnhDt1iAl1CWy7Mr2qUl+Em4EyoxO8c0zKANlanwc+L1uzuu7x3nTz/i6vKC7yVFfvUNLgdJsYyBSkO9bGnMxHAM+BGMzZjc05iO5xfPuNquiG6i3x+IEY6HQIgGNyqmEeZ54nDYc32zY/cwcpwSD4cAJrOoDZWtiERs3T6ui0CmTynBMI5E79FlT2sbi61FEKy1wvvIYT+So8LqmnmYCGPEFBDYDz7teNg9wNffsB97UlZ89NFHLLoVVQXTYeAf//Yf+PqXX2AH6FawjolVTKxzJu/3DL4nzANNTjRZSXLiLDGz1jZ0bUOFQXdglgntE7U2rJcrLldLtkaxyRmTo4DVjCbWNS5nEZsCyQUepgdSluZmnu6YvSepxObyDNNU1F3H1dka9eY1/Thy1XXcXt+xqERc9/b1O16/2tE1YoEja5aLM6KpCW4UXPpxoM+B6+MD3e1btk/OuJoG9rsbrDFslGLse55uXvDR8w/51Re/IRyOXP/2FR9dXvAv/+RPuPv2Gz77xT+gc6YCLInkHHEY0es1bd2iMMTsaZqa6Pcc7u7Y7+7IAdZPVrj9kZnIotXEFPDHI/54oFu2LDuDahqGeWYcPJFI3TTS4MWEm2d08Bidqa1ocXIIQthMHmsSyY28++ZrdE4833yPKiVizmyspkWh55lhd8fu+pbh9o6zdsnV+ZZmtaQfYbnZiKYNWC+WOJ8JPqLRVKbGGM3sAuPoqCuhloaoCFNijpqsKparmsFrro+3ZJ3RyfP86oKn3/+E0NbspplkGnyEYZwZ5pl9f5RGTtcSMDc5DBpnMt7NxOiwJtJ0C5qmImaHai3rzcXvda7//iuAFIXUZ+2juIoUsVqgJXIQCs0OlUvnLzdho4tWIAZUTiW/WA7gXPb5guFV5eCQ5XLM4h99XxScRr6iRCedUgFNUb6LYC14TyiVcPKZtl3Qti0AuqT1naxjJ7QxSDpVDDKlCEFG5MaUrMEgAkFtMlkLEbCxIiRJp9VFwb8aa6jrmnmeJQBpsURRo7GQNS5MMnXImXmapJPJAZXfryJyEjqU0dL5O59ws5CspimgTC086dP64qTBSAnvPW2rizhEbIV1Y7HxVJBE6tpS1RZjZIJBeR2mfsK5SNsusFXFvbpFozi/hEXb/c74X0b/0rmroq/QShVc7umX5CcYbQqaOAuJ63fgQukxP8AoVQ7+IjLIUsGfBAenYKaTIFAVpX6OgaDMe4sRRaioxMIpXn7FojJoIsf7W1SGs/WKEALffP0112+u+dU/fsbufsfTq0v6/QP73Y6m7Xjx7BlNUzOMI19/84+8ff2G129e8+btW253Dmsy621LAH7w05/yL/7Vv2SxWPAnf/K/YbFY8Pr1a3729z/n+t07vvntVxz6gaaqZQWmI9kPuHnAzwNGZxZtRWVPdEPYP+x49+4NH3z4IYtFx939jvV6ySeffMSi6/jtb3/Lfv9KACApEeYZrOL+uGd/8FQq0jU1cZ4Z51ESx7TCB0dlLV1r2B2O7IffsDx7SlN1PLnc4mIgilpMxKg50CgwLVgLP/7egk8/OOPZ+ZL10uDHnv3tA9M0YWzLOO9x3rI/eG7uHri93XHYH5mc4zA6XFaMXm6sddZU7QqSNBreRXLhd2TByBEnT64rbA4oKxZhnCkkOUsKmTAlptFT20yYEy5FTLEVf/v1Nzzs94S25u7wwGHf86Mf/IgPP/yY1WrD4XDgF3/2V1xZy8Umcnl1xpNnF2Q8eE8zwTprXNDiuokZ7xRKtayWK9bdirPNVhgfIWJiRhXOfmU1tUqE4UjGoxsrdsocmaaRfhgI3osQFoX3CVvV9MPEw/7I05cv+fTH36dddyISjYF+OHI9jpi6oluvaLLEGndPnvJsueGYPudht2PfD3gPPExsVmtSmKmtYjwcqCbYho4u9Ex+IEfHdrPkfLNBHXvsONCME/Z+IL/do93Ey3pFc/WCzns+//I3PN8s6Kzsuy/XK7ZVReUjTQTrMyl6jNISg933hMnTpooYI/27O2prGIY9vYk0naVJ8PRsw3a9oa0Vs06YCmnQTKLSQr1MCVqlixMpo7xDxUBXGRqr6acZ8PT7HTeff0bX1HTPn3G+WuLnmfSwI3nP7u01qR/o0LS1ZlOB6vf0t9dUqyWVsRglGho/Z+59z9yPnJ9fcnl+xfFw5P72lpQ0i7YjZMB0TMHzxdfvGI8jV0+eUjeBlKBrJFjr4fYNV9NTulWDbwxBKxwGazWbszVPeSJ5A6bCTxPeOSptCc4zT6ME4bkZdCSbTD/2zPNAVf9+R/v/H2FAGR9Cid19j1R1zsl430hOuvNBLvyQZB1gNEZT9q0BZVIZ3/jCKy72i8KWP6FbVenjTlY8ay3Wiur8/QEgKXqnHWFKxUtfJhI5CVMA8uM6ISPq8BjjIwxHa10CKsLjwRxjIASJ/VVa/j/mgM7vu+pHNTuU8VQ5lGQ5Q9ctpfINolEwKgtPoEwFTvS/FCMnpG0uk4CSTySOhxxxITJ7x+Q84+xoW2ENPBLyShCE+M49bdvw8DATgmex6CBnhmEgpUTTWFISH6mMTi1VZYkpctjvGfqZzUYKKjfNhNmV59NhdEH4SgVAQUGRSvTv6fGfTBSaAhIqAB8pAsDoLNoG0mPhmHIQy2Hyj+97iL5QGROngBmxT1JwwuaxaEKZx2nEY3hRThIPnCBHEfxoJAmsqSvCMPAXf/GX/Lt/9//kzetrvve9H0CO/Pzbb8gh0FayLnr16hVffvFbvv32W/px4HCM9H2i62B71mKs5uzynLPtOf/T/+V/5v/8P/9PHIeBxjZ8++23vPrmdclP33K7WnK827PtOrrFguR67g8PZXoRpYNQpogoAxcXl/ybf/tvadqWt9fvuL6+5etXr3jx4iXb7RoF3FzfcXnxhO99+gPeffuam7dvUCqy2x+pTSL6kUVlaLSkCdZKUxtFUmJBXSxa+mnk5mHmoX+FbZY4wMVA1TY0TSX5BH6itooXV0/44GrFv/npB3zybIPJAvQRYVXG2g4fFLd3B759vef2bqAfPcfjxPEwMcyJaOQOFBS0tkEZ4VO02rDbP+D9RCq2W6UyVssq0lhD1VQok0tRmEnxdC3WtJUhTBP73VHolDHS1LBZrLi9vuZ4fKBPkZQz4+j5df8PfP73/0jwkUWzgGng0805l1fnPH16SbusOPZ7+fzrDD4wpVDivhWYBmMtjarRU2BZB+ZpwE2z7PALcjyrzH4aWW9bDoeJcO/xwRfUq+iaUJq668rnXdCzD0OPXbT80X/9J3zyw+9ze5Swtfv9nl99/mvePNzzk5/+BLtccn9zJxbk/QPGGFYvnrJ8ekW/P3B7c+DQFxdHP3G+rtl2DXWtsN2CrBPv3r7FjQfUBy+oQwAfWWvL7Rdf0X9zi80aNQ6ctzUNmoc3b3naNrz8yY8YfeChH6ibJa3ScOipzzyr1QLd1kQFD4cBd5wZjr2siCfH7eHIsmuJaaJtNI1eSvhZzpA8IUzYqqZZr1g2mooeN2Z0EOx0VVlQCWsVwXv8PGIjNDTUVSaME9qNfLio0CmRb95hwznWeYbdA/M4sPv6t1yttzy7vOK4C8zjHpchl3vR1I8slmuaqia6me16zSGP3N7u2O32DP1Afxy4uDgH23G/u+PufmR9ccbNbsA5R7fN+KxpW83Z5QXLqw3L51csK0vwI/iAqQ3LtiF3lohi9kGcEHUHy1aig5UiBk+OK5TKTPPA7Gfq1qJrzTj1DOP4hy0AQvIiQEgyKm+sKK1dCDjnxHJmLLmw90OYiVnGztYUsh3COM45lcNfS1COl4PxhJSFWAoAgUboAocRfYF4zaXjl8M/lt3SCd1qtKVpGlHzn8ARpWCIKZXdKdS18J/F055xKZBCEJ+0tmgViH4WkYlSfIeRI9VsOZQqLUr7rEUkmDPMs2O1XjLPnnEYCCFjVS05Cqe9dNFVZK1QtjDpM+QYCdGVdKrAPHnmSXLhnQvMs6OqWr7LuNdElLbSEWUJk1A5Y7XBaINW+RFqk//ftP3Xs2Vpet6J/T6z7LbHpK/Krq6q9o1GNwDaoSCQM2SQo2vdKPTn8WJCDCk4GsVIJOEINNAwjUb7LtNl052Tedx2y3xWF+86WbgTLlpZUZFVlVl5zt5r7fW95nl+T5SJhrUGlSVxS2VRjQ69g5CJgyNp0U2IW6FmtV7QzhYQNCixGykj6v5b+h7IhERenpUdv5b9rDGiGZFy3ZODn7jWgRjl8JMUvKkAmIrN2/yFWxBQiv51oShWycl9gHAENHnyugv8Q6eEyjJq9YN4q2tj+OzDD/njP/xv/OQnP2EYPMdHpwzbLVdXV1xfX9N1HVdXV+x2Ww7diPOZohKKWVVrVusZbdsSUmS5nrNYLVmuluyHnt2hx5YlT5+f8d77H/Dq6pKvfuWrvPvOO/zy5z/nj/7LfyP5wMXlS4btNYTu9bpDXtkU56wVx8fHjOPIx599ymK15Gtf/zouRTa7PT//1XtCg0qZNx6+ydHREdkH+m6PVon1as79e8fcXJzz6sVTDsPwOm+gnbXY0jLGSBNhtYSYB3Z9ZBj29A4GB2UzkOpCSJgpUlUVx6uWO8crut2OGxsIYU9j4cG9E+bzI/p+5OnzMz598orNzrM9RA5d5HAYcW4q5rQhkKV7na9lpGBKtBHSnbElYexJOVJaQ1WVFIXBljIVUUhWg0JjVIHOFrKsERazgjhGwiihMjkmghsBR2EDcy0RyNUYSU4mgqBJVWJeCOthmTXm0OMOO3LoKUvDMPSkwaFGR5mgKL+AIvnDDudGhpsbuuEg8d9WMjaauqEwsHMHdCrYdQd2hy39EEDBbF5Rtw26tMTSEgpDrBUUJYujBad377F6/IAr13HVHTh0Hc/PnnHd7ymXC2anJ7SzGWc/+THGGIowYKLGVgXH6zWzkyOK9Z7lkLh4ecV+v6XIcGc952g15/7dY47WDZevXnBz8ZJPPv6Ui7pi2bQ8unMXUmD79CWVKcXqqWFoa2KhWbQNNiSOZnPuzReMLnPoPOlqz1jdcKRbFu0CZzOlOUL5nueffcqTzz8V8p6xGDKLRU15vEJFzeXlhu1+jylbCi3OsUVZoG2BHRIuJVQW669MSAdqZYg6MWZP6DpyB6umQRFoU+D09BSdIe83JDdSKEU5DBw1DTcKohu4vr7k5kbEwPPFnConlCmoyxI/jPT7Ee8y88Wa0hZcD1uGwQluWRtsUTO6TB/ANguGZOl9JHrF2cUVkKnbOYvZnNVyRd1WhG7LYYQwTUi1VWRdgLHM2wpQGCUNbgwj/eAhBVIQkTkqUJQwW1TUs5pFqF83Sb+xAqDve5qmoa5qYoy40U2HqhUYzmSx0hm89zItiImomcbGEklrJj2Ymjzb4o10ogLXehr1q8ktIOmDAOEfhMiU5W3wj3rdzetJ1HebzBdjnFj/X7zE245dgDby37wX32iOMtaPPoKV8SvWEryfCHnI4aqY1NmI1uEfsO1v64OUMs45rq6uKApR/IcA/X6k6waa0tK0FdoU9L1QtJSCqpTkwKKsZIzpRtzgGQbP6CLOTZRFH3E+ThoJyY1X1gjiNUa8Hzl0ewEhKUk1BFlLxBhwbsR7z2I5Rykjor9hpKpKUkg0ZS0pbimi0+QgGDqGYaCsWjIjWkcRUaVi2u3LA1QpsFY8s7awFLoUW980ppPOPpCilxCX5EjJc5u25/04dfzxNSfgi/AlhcQyi+jL6NsJUcJoKzZ/JZYYg9w7arIqWgzJB4oMTz79mL/5q7/mJz/+MR998CHdYUddz9hc3GBtydnZGbvDAaUUw+AJWQiVSkPXJ8pasVzPqesaY0uWiznKZGJOXN3c8J/+03/iw48+5mtf+xrBJ7bbLSlEvvtb3+Ebv/M7XF1ecn5+ztj1Et4TBggDKovGQVI2DU1RUTcVLiQur2+4/+ARX/na17hz9x4n9+7z/vsf8vHHH/P222/x4N59DjvJOz85PcG5AaUy//Sf/S7f+e1vkcPI9//7H/N3f/l9rs/PCERijlRFzayuKcqGqg7Yqqc9OLHiHUasCoweeu+xFqpKIFWH3ZYXvsPVif1NhVWe+3dPuEuNTzUvXl7xyw+ecHax5TDA6BQ+KFwEhUUpgy0qYvRCcqtngj8eAtbC4dDTti3S4itsWdDMZ5S3Mc0pkIJ4uovCSiGfxCWUIwxdj0ril64KQ2nBu4H1uib4gRR7DldMqZQ9LohuZ0gH4mioSsvL58/QKjFbtiSVSDozjoOENwSZkBUTwS3miNKKrKAfe8boqOua+UrcGovlDFsY9O7Ai1cX7PYH+l5y6etaU7cz4rxljJ6+7yjrmna5YLZcce/BA45PjjnbXvLy1SvKquL8/JwPP/qA4+Nj5qslffBYAg8fv8l+vycYmdi6oWPAc/fkDl97/E1udiOx+Ihtv+UwjOzGjkWuKBc1b3/9K3z9G1/h4w/f472f/pSr6xv211tmRcNpu6Saw7OPPsWTOPgepzKmLRlSYHl6QtKGdrmmGwKHPqBPIudjor/ece/RfYIO7A47um6PvzqQN0K83PY9TWUphzUjBdQLTJ9Z2oZV1bIqK3aHHUlbDBVNiszLCmtK8hSrO7gAXUcKPXUOBAK+O2DiwLooid0Wq2A5X+D6gM2eMIqr5emzp1gSD+/fI6TM+dUVFhhiYtv3PLp/j6P1KR9//CkXF1eURUtwmX6QuOjRBWxRslgdESk4O7/g4uICU5YEvcdUBTkmbvbXzNqCsjIM40g9jLz85BX1yZL1o/ssVgucKSRK2AhnYui7KecErDKCAC6hsCVulJWoVRZTaYzNdP0OpZTkwvwmCwCFwbtIaTNt26LqhnEcp8pZDqGYAsYWFGUtnbYXrYAxCoUVnG2MAiApRDvgfUAXJTFkDNLFpegkVa2Y9vU+iNbAMAUdCM/fTBjJqiqlKBl64m2nHyNlWaGSoqoa9JS2RorM53O8jwzDQGElYjXlhFYaUxrquiY4xzAMaCWRprYwJOT3gUS2DsOIDVGwrHaKYvQJ79yE94WURoY+EINMMqqqwkfH4eoKReT4eEFhDd7LawqDI0QYx4DzELPBhZHNdk+ciFdmEjFaWzL4jhgjtZHITOcGco74YaAsS+k8ioIQgvxaipIaZw06i5NAZ8H8BoSn0PUysirrCjVpCoZhYLfb0bRzse4Z4TXEEEWAaS22KLGlpigF1ax1Rot6UkSeIaGVUBpTdGiTiNHRDzvImbK05OSn3X/mdXaAuc3rnoKSjEyVJJxKkZTsiSWmM+HGHmwhgJeYiD4Qs+Lli3P+7I//hB/98O95/uQp+91G9trDyPZ6R4qahEwZjNbEBPPFjAwCwQpRIoOtwZqS2WyJsYau61AmYqOlaWbM5nPOz88pikLEZbbi3r0HfOtbv8V7P/oR//E//keury+oihKVNYVSRGS0PQy9WEELUcCbsmIYHY/e+BL/7v/0Hzh/+ZLNdkc5m/HN7/w2v/dP/zn9fsevf/Ueh92e5XLJxeUrNrstj7/8FrPVER5h9x/dfcDv/ct/xU/+9gf011dkJeuXo/URi9UR8+URY1B8/y/+hv2zMwoFRKjtFx4Oqw2LdsZi1qJ1IlvNfozcv3OPOw/egqLls+cXfPz5Ky63ieeXEgufVRbdQVGgswJtSaZi9JHoEmU9QwXPkyefY62lbmaEGDBFQXZS0IcQJuGVRMmGFCdX8S18Kr+O7tVKT84dAY+hoChgux2oCoiDYtlmdh34CGMAnxxHx2u5/0dHWcmEYdg7KGRaEZD00WSQfxsDo/coo6nqmhAD+35gNi9Qy4qjr36Jr33tqyidefb8KZtuzyYbblwmKssYIqqoCc0cu1oRhk6ohnXNG++8zemdU2KOHMLA4XCgbEqGoedX7/+SXbdjvppz6PasjhagM1/52ru8evWKTz/9lBQytrRsuh2mMJi25eTefcrma7QNvHz2lN1w4NUuc7JbgzWsT4/5rdWcO3fv8utf/IrzJ0/5/Owcc89yXFXcuX+Hfhx4Y/0GF7trXI7sxp7hsCObgqvNDTmXHHrP1cUNdTOntCWz0kJ01FVJO5tRjQNvlGuquWWs9uADeRMZu2v6wbCqCy63O/bdC6rRgxoZR8/hENlfd/g+cTw/pq1bNjdXuPFAiuNUTI/YnPHjwEUMqFnDnaZCK4XNjrYxXF5csrne0rQr2rKkaWZoZeiHDh8gKYuyDWUdeOPRG1y8vBbBny65ud7SHwLew9XmgLEFJsL17jmjT8IjqFo679l0A0XladqKvhvYdgNHxw3uwvFqe0m1KOnCyOJoSdU22FLTDXu8srTr42m9nIU8mEdKaykqQ3Ajykyx9zkSA2Rl0VYE1fvuN2wDvHfvHs45opeRdn4d5nIbzGKlw8x5OvQNbSlceoF0RWK8HdfLASHrBEE0xilK93V+PZNve9IB3GJ04YvgHj0lw90Gy9yK+dSt00AJPcx7P+3hE5gvgmpSkr34OI40ZUM7a3HDyGF/wBrNbNbivQAbcv7CzpgnUqCZMLbRB4SPaCaXQoUpK7abPWgJAZLRtJ687HKINFXFbfCNMea1xTGERIqKGKDvPc5lFIVMT5RGB5kyDMOA0oq6LlEqE5OMhIqyhCB6ib7vcW58/Z6UZfVFiE5KxBymqYl8X1bLuPL2dfXjQNaKjOZomvqAlhClFFAUWKspSktZSuKgxOsmFIIrTimTQhTNw+SgSMmjQiQlEe3kLOmJaVLnqpyJSZFVJCslnbyCwlhBY/pATmmaxsiEybsBrTTzpiaFxGG7pS4qdlcb/uL73+fP/uhP+fzTz3C9w4+Obj/KtVDQNBW5tKSshM9fVwxOXv/gRjCGqqzEsjrhin2QHe7hsCerQOFLjBFOf9d1nJ+f89aXZnz7W9/i93//9/now/f5v/0v/wsf/PIXlNbSVCWhH4gqU9hCYp+NpWkalIJ+cJPAVLPvep49fY5PmWa24I07dwC4ePmKP/3DP8Jq8P3IJ59+xPXFJUd3TlFa8/Lmhid/e8Znn37MzcU5b79xn+XxMVcvX6CIzBcL6rrkm1//Kl/+3u9y8+qasxfnDKPn+fkFq2VBUTVoUzD6AR8cg3fM1Iz5Ysnd4yOSHwhYnpxt+PWnZzx9+pTPn7xk0yWCAodYtmyCwmiMFXtpHzPKlgQyT87OJeLbBxpj6XaHCQgTp2dLJQyKafIWfIKoJxdRxKswOUUEF22NxlpNDBACDEBVKx49nPP2l95gXhZc32x5frHlcjNwft3Re7gIB8boIcDRvKSd1SgLyRhCToQk/xyzZKGEGAiFgKsGImMacQj5MDc1sbaotpJgnapkUJmbrmfImhAT1bylXh2xPL1LUpku7KnmC773vd/m9PSEm80Nm5trUs6vIWVPnz/DR898PscUVkbVlQhKm6ZGXTF97h3r9THHp0fM24Xg0ivNw0d3GQ5X5NgR+4ZFW+Kz4/nFGYvVjLqqmR8f8/Y3vkFZ1Xz0/of84uOPWGXFl+7f4/TeA8pZzd13H3F5c41ta770zru8ur7h48+fcnm9ozk4YrYMY2Rz2NPtPOFwIITI8mhF1TSgFMWoyCmgQ4IY8C4xPHnBfuw4uD3z9Yz94YaLyxcsZwuG3cDhymOT4nq2Yt62DP2esd8zawuqQtw+WSnKJOjcSpf03YYYAov5EoUmeEdVlyzmLW07pygb0CX7bmS1WDJfrFmtjlm0R3z++XP6wyAuitmMnLS4AKKXZ15R4rPGpciYMipOuSNVjes8hy5wGAMxQVlAOQaUscxmDdvNFj32NMs5R4CZL8laEwnstxuoqglfIsFdh36AJNPfylqyFh2K0gpdWGwxabQm3s1vrACIkzhOTzAVNSnvcxRVubEF3Fr9iMA0tii07KOZuP1GHAIpCeZW1Fl2OrjFlpZNAQZJkZp29tba115PNQW73GJyeW13+yJwJkXpBrRVk7hv2iFPKNucEgoRP4UgAjSVM5mJVmgsRakhFyJJnCx+wTuyyhRliTX2NRvhVvyWb7tjJVMOIdJrjK7I0zhdKQkyUkpxOBzwQYSU3nmx1qHxQUZM291A8IGUlKxJJkufTDQ8trAi0Ioj3gtN0eiCQpf4f/C6RURpvxDMAd4HKZKUvA6B6cgqRNYlVkJvtBKvviog20noKAmQhaloqtkUOaylK9J+WkfImDbFPNEVw4QiTgJ7yh6IqMmZ4G9jFpQUhhnxw6KnewMle79b5FDWEzVQCsVxHFHG4EMi+khbtFxfXfO//z//X/zn//t/JoVMvz9AUoydJFLOWiWksqrGhYSebKFd1xNR1HUD2hKHjoS4FMqqoqzsZE1LlFVBDInDbsNwOFC1LW27wCjN6fExf/D7/wpmLb/62c/56Y/+nmF/oGgb4iBhQVpJaVtXFVo3lGUhRavSGFMSQuLnP/8l15sd/+7f/3u+9t3vcbi64c//7M/4w//63+i3N+TocX1H1+3lWu93/PWPfsif//BvCUgWxDtfepP1vXuUOrG/uaQi0TS17NatIly94rP3PuD8xVO877l7csz65CFXmwNn56/YbgdxA4VAAvp+4OX5BSpFKmsptGHsBzabLd2QiEp4T8lA1oZkCpItQBl8SuILn9Z4u04K1WKSiPT9SK40SidmTSUYZu+xRk28hJFClVM09RTLnBO3qZ/SnES0hhBhtlR8+ztf5bd/+5t85d23iKFn3w283PX85d/9gg/+9ue86hBxlYLlQrN+sKQ+XpF1xme5h3PMuJAYXZLPl5fAphwDYz+QU+b0zpKjO6fUlcWPgatXl8TkuDx7SbfZsVodYQoRJz969ID5oqVuKy4uLzDa8uXHX2Letjz97AnPnj0hBIfVmrIqaWYLDtsdTdMwm89QCAZZTxql4B0pBu7cOWE+n2NtKc/P0lCWBSp7bq62nJ89J/iR45M1i6YkRsdHn3zCarnk0YMHUBa0qxWzo2NUVYlrYzswXD7nQRGZ6zmP772FZU5Vt7LqLQvmR2uq1RHoksHDZnfAh8iiKSB5uc5ZE9BEEsmAJtBtrtlddiQfMdliSsX83n2KuWY/9iznC47KlvOXe/KeKdTqhm53Q2kV60XDgwenGJ3Y3dxw2B6oqpq7d47AJFyEWtf4LCvXsm1Y1XMK21DYGq1L9rsBkyzLeonymu5qD9qw33aMvUTM+1Eajxhksr1erQhYXDcQUmSM0swaJYjg2XLJzW6HQxL8ooL96IkqYZuKzS5S+MTN5Q3YAtM56vWa+WrFQOYwipaorSsUQpckK+qmkDM5RciiIwsxEiZRePwHz/nfSAGw2+0wxlDZQjpwJWK+gJ+iE+WNRYEyihB6nJe9v7oF/0wHdcYQg3ScSmmMsWitBKhjLSE48hQi4lOkKArBj2YBbhirX9sRnffTn2unP0eSnMbgcW4khtt9v56Y8lpCOSZCnLVWum8vUcJWGxaLGcEHxkGQqCnd2qDCa/+/vhX+ZRGeCaxEEVOUtYhS1HUtoQxJiqGQoqRUJfGoam3wPv4Dop2alO0FY99x6Dxd5yViWIsI0mpDWU6HYwqSQqgheQ9K3AQhjOgpsbCwBUqLCuN2jBpjmPbpIugqy5IYxAWQkoRNWCuVbaENWEPVzCjKBl0UKFNS1w111VKWJZUtUIj9KCZHigMhOLz3BC+vN0VJDZMD/9YGGsTwpIGU5PcoJdQuLWTFNBUmkMVGOYkLFbf2PynmUo5UtqCwVlK80Gxvbvj+f/8+f/Ynf0Z/EEV5jmCVQmtoW8NsMSP5xP7QYYoSTKZpapqiYHSe0XsRaRoJq0oKbAqEAFVV8ZWvvMt3fvu3GIcD773/Kz755FMG59AkDtsdP/7hj6htSfSeH/3ND4neMW9q+v0eR2beNmijKY1ggY2ZrieKmDLdoWNpC3bbLRevLtjtdnz2y/f587/8C378459yeXnJ5uIlfjxATDRNRdu2DGPP0B1I1rI+PeV7v/td/qd/82945/FDPvnRX2NTYHP2nDgMJO/4+Ncf8qO//xFn5xfk5Lh/55Q79x5zvXU8fX7J+fkNm0OmqGCMmcO4x5o9lQGrBKhUmmLKbM/ousBoxRgipirBWFCGhMEHWb9pUxCCrAWtBmMLfPB0/UhhxQaXIljctAPV1E2BzRo/jIQkManaTDZBJfjnYczEEFA6U9UKbTJ37pzy7le/xsndu9xsd6Q8YJqGuijZZMfZAHsr0wo0LE4N9RvHNKdrQnSk0aFDIPsEY4YhkfpR2Bsp0feOECJHi5Z3vvIVSq0IfU9pLCpl3G4gO8+8qjl5/BaXNzv6vqcoLc6PxENkvV5zerrm+HjFkydP+fjXv8aNA6vlHFsUEDNuGETkuFjRzhr5XExZGaTM5mrDYr7izTces1odcXFxweXlDbPZDGsEV311ccnm+pp+t6HfXKOJlIXmwYO7bPYbyivL5uoKdxgY4sidB/cYly3j0Yb9fsfnNy+o+paroePoaM26KPj1p5/TjyO9S5iyQlcFnkwuFLauWJwe88bjR9TzNXufuOkHTKGxJuK6HbuXL/nol+9xfXYJGdanC772jbdZ323JfcfKaeyY+TC+x429YmZr4jiiUqRtChbLBhMd3W5PdiPzpmDRthS6wOEpZ3OM1oyDp1nOmDUzjC5JXokoc9exud5JMqATkfroPC4EbFVPU8zEft+RER1ZVVY08xmdS+RuICpFVDCmjJk0akkbsjGkpF7Tb/2YOQwRF6b8jQLGg+fi/IJ4teE4Jt48OsI0Nd04oCa3DskTJku0xF6rL5pepclKSbSwTzjv+cf8+EcXANW0K9coggukNErXTUYbRLT3OoRQTeNyoboVRYWZ7FrpdmxrbzvMitFNGfCmQBvp0iXKVUh6lS2w2hKztIjSxebJDXCbHy8V+m0E7G3oTEwZlYU2B+B9fL1LttbKoW8tYkcL0m1qyEkU8Lq4TbjLr+17KSX07eE2CSHFGqenV48Igpi8yzESUsI50S/cZg+4MFVq2hCjpFjF4MgpsO9G+jES4nRxs5LQC2MwVsu4vxRdRM5xGmM3aKPoDiPBjVTVjLKQjvaLDjySkN26yvJeG2VJCMcgqUTRNFOXb8jKYGxD3cxp50tm8yPKsqKqa+qynoAXQf7f6AnJEdNACKM82EIgT/cBWTQARumJZR2mQ1wOcyH+ya9ZLSufiQ8EWTp9nTUGWf0IcfFWYyJR1cklCHDz6oq/+PO/4A//6x9x9vyctmrZ+4OEQ1lN07SUZUVWWfIZjGFwnqPFku/+zu/w5Xfe4dcff8r3f/ADLq+vRKCqFUYJlKauSt760pv8j//mX/Ov/+3/SLe95i/+4oToPe998CHbmw3WdFycX/DZRx+TgyjSm7JgVtbkYaQuLLOyIqdAoTS+64lWi5ZhHOWa1hXZO64217x49oxnT59yfHLC9rBn9JH9boNSmZOTY1RKhOCIOWB0JfTBxYqvf/u3+D//X/6vnNy7w3j2hPlqxfd+5/f44Cc/4vLFM1KKXF68YhhH2qZmuTph10V2uy2/+MVHPD/bcOjkc64sBDkj0RqSlfosGoPXWvJBlJ40vIpsDHkqXuMUqhRGcbKYUrzsOSW0MVhtIHvI0DQtY3/AOxiGjNUjWCvvTyEdb2EVZQHaCnayLC3ayGpmv5/0AkbRVgWzxQLnE59++pyXF89pWoXTmbO948cf/po9wFoMFdpqmgdHFKcz1KoQR4zJpABpyBhd0Ggtq78xE50n+chq1vLuW1/mW1/9Ki+fPeNqt6VUGuUC4+4ALtDYghgGyiKjlKXrt7RtQ1VVPHx0n6apeHH2gpfnZ5JXUZYoFIUtqcuG/TDQtnNSTszaluVyIYwPY+kPA7vNjqOTE0iKzfWWcQysV0dUVcVus2N7ueXm4ppCG0w7Zz1vCL4jJ8/RakVKgafPPuPm8prkPKt2zt0HJ5y/GMhVw9GjI/zg2Fzd8Mv3P+Xh/WMeP1KSbBk00XkO+w269pTtjFnb4FJk23Vses/y4QkPViecao2tLMHvuHj+KZ/8+iOen50zXu84ame0xrKsSpaFprQzFq5mGPc0psKs1qzqOWnKS6lryWXxQazWZrmkKiqiz+wOI+3xkmo5w/tAU8BqeUQKmc3NDpMLdtsdVy+vGDuPGxy7m900XSwYRoffDyzWa8qyoiwDKEOI4jwKQdaEvRsISXJalIZkLdkKgMtYKyjqiepqCkMMjt5DU8o6d+w9KiWKhSZ0A74fOX7wkFlbgzWE4HBDR/CFAOSil2f2JJTOKqOUOHV0aSmm8+43VgCQZeysUXxBt5t+JMnWrkorU4EJyWisJcQ0Ud6YLF23ozpB7lpj6Qc/wXlEUPZFwtutal/ob9JdTwlJ5KkD/4dugDTpBSxGF5Rlg1aVWBOjdAUJObCtvQ0AulXwp2n02DH0PYW1VGVBiv71eDHnyaI1peBZW0wxwvLabmNqb7Pqo/PECUwjMZXxtR0x58w43gYcCcFsHB195+gHx+gT4xhIWY7KGDLWyj5dLHEi+MjZ4/2AIghAJAnIyMeAnTr+2/f+HybxFUXx+n323r9eTSil6bqBsqqYNTMWyzWL1TFHp3e4e+8Rx0enkmlvrYB7vcePgyj5UyJlhw8dPjpCcGLZm2ydaqIDJpRoKNTE9pv0H3ayf4G8Z7fQoVuaoPD/5WrlJN2etUYEpUphgOGw51e//BV/+sd/zo/+9u+5fHVBGAN719HUNRqDUoayrmjbOc6N9MqLPbNUtIsZkczZy1d8/uw5VzcbRpcoKybolVw7YzVFYTh/8Yw/+n//77x89YJnT5+QY+RoteSw62SqkRL77Q5ipNQaZRTkRF1YamuojCYrg+97YpSVTtISfvXgwQO++e1v8cv33mMcJLTn4w8/5fPPn9DOWtYnxxAThZU9cG0FA+1jwFQ1b7zzDt/+nX/CP/8//gHHd+/z4tOPKdLIYrXm+csX9H1P2zQk51A5s16v2O47bm6uud6OfP70isuLA32fb6EOU/aDTPlUoQgpggadJSQqaUUyohrMWZG03CNhct7kIJ1UjAk3DKKc0ep1119OUc1KQVWVkB2W20mhkXssGqq6ZFaW1JVFW9CFYrYQHGpMieurLVdX1wz9SMpwcbnh7//+50IHzQNvfumEfRj51ZNzLm8SqoYhQywVJ/dn3H38kPZkgS4yOiusUiQv4C0fAuOYGLqOvuuIo6cqDQ8f3efdr7xN2VRiebaG3g98+mxDv9+xXM2plnMuri+JWQ6EkCKndx+wPj5GmcTTF084O3tBiglblXjnOIwDtizJbkRNIswQI3VVspivSDlyc3PDZnND1/W8PL9gDIHZbMFsPsMYg3OB64sr9td7Fm3L8fKU7AeOlg3L5SPWR3MKq7i5vGB/2JGcI/lAqTKr9hRbwM45vv7211Ax8ezTp7j9UzbXN3y4G/ny47extmZWVlS2pl2tWRwfY5uGzjsutjtevdpA/Yp7dsXs+ARTGkIcSVgO+wOHTY/uA02rudvOWCuFu3glGHO34Or5DUPnWNQz6kIOu8I2ZDzODaBhuV5KXkDIvLp4ydn5FV9dHXPv6AHGlgz7Pd2hZ7/vuLneEcbIq/NLwuCoywalJfo8+EhlABKFncTURhpT72XimDLsuwPXuwOHPuAyBGul6yczhoDSGlsWJBQpBHKGwpQykVWBpORsiB7WRwu+9O47qKpAZzharynv3yFpRfAjwY/ynI+SOjr0PX5Cw8cESt9O2kQY/Y/58Y8uAFIUb3mWdBesMZS2JGXZ6SoEbCOpb3IYyodbBGNxKhokxe2LDs6NcRpHJ7y/PWilcr8Vx5kJOPNaFT7l0Re3ggeZQxBCJATRHxRWxt9a1cSQGMIo8b2Fpq5rYkwTqa+Q70nJjtyNwxRrLIfLNGOeEMhpAudIAVBMox2f0z+YDkx2OJOmCYKMs+GLw/8WXJSz0OpCCIyjFwTk6NjtOlKS12QmG2NUCZSBLJqGopSwCwExeQqrJrFfpihrclSv39fbg99Y88X1TAlbCD2QzOuVQVnKNGC5XHH/0SPuP3rM0dEdmnZO3S4oy1qSGVPGJ7HRBD+SYyBFh08jIfYTx8AhPP8pYlkc2cKH0FbihrNALbSymKKYRHa3RL/MLVFQa4NW4n4gycTAaOl8yBNidrPhg1++x3/7L3/IX//gx/SHnkVb0zQVTa0gZh6++QbNbMb19bUUp1ZG04e+5+jkmO1uz/f/4gdc3mzY7kdsaZnP69dwJ6MlRCp4x5PPP+fi7IyUI3VdsNttKIqKtqrJblJ/aIPOit31DWVZELwjeodVmRQcI4nKGlT21KWwEvp+JHqHSoEwDjx6cI8H9+/x05//gmHweBfZhx2ztkXlhHMdY19RL2bMZg0xJYqm5be+/R3+w//8PxNMwa7r6Yael599wvbZZ1w/+Zi4u+aoke6zOxzYvtxz/uqKi6s9Llp2ezcho6GPmZTVNKnTZK2IOVLWgthFwW3w8pTQRVaZGCJhelimBNElUkDuYyJ5ahRU+qLcEwNNxhYWoyMWSbwTjPJIVFC2M9pZwXxeSwdcapZHCxbLhYhdC4v3IwpF3zvOX13x9NklMUA7h7YtsYuacZAV1GxmGV1ita55/NZj7j28w7zV5HDA6gg2k2JCZ7Eq9juHHwehyYXE8fKI49MTTFXy8uKSm35HLhVjjuzcgflRy8mbb9B1e8xhgwY8mdVyRjmz+Dzw8sUVNzc3hBRJObHvR7x3zGczgjHkFFnM5tPzTTgG+90TvHecv3o5WWkl8KYfB9Yrx2a75fp6wzA6TAYdNcOuY2s1R4uWO+sls7ol+8jl1TXDsCdFR12W5OjYba44WtQsljNGOnwYWTdL7t+5SxUt55+ds7nY8dHu15ycnHB0eodmNqPOityP4p5JkXAY2PuRwEuq2V2Keok1msY2nMyWPL57n+HuMd3zS9R2Rzh/SV9nDv0ZKMVhU3BxfmBeFtxZHRO9vJ62bRndXtwHKrMuC5QVy4fPipg1++3I1dNr6vmSoR95+uwF4+hICS4uLri66JnVhpQk5KicNeR+YBgjGU1V1aAMgw+EBF0/4EPEltX0vJ8K4iygqpwVPkb80JNvp9LGMHppQPPoyDFQWkEXqxBJWbOYr/nK2+9ytd/yar+RCPKpSSrKkqapUCqRY6CNt42dxHSnDJhSzkJliPl2Gv8bKgCKUpSuMUVCCqgkJDYQNazS4JxDa4nOzEGoetYWTLRWeXgo9foADDESvKMoSrIGlcUul4nk152vPAyyTlO3nSfRF68fyLfo2Rg1OU6efURcFcMoOonoycljKCda3sgwHPDeUFYFdurOiqrExEgi0XuPUVmETOJMmxIKpQhyYZTOH2EDGKtJbspL8EIctLffq4oTBU/SB72/XVcINGi/94SQGAcYp8PDWAX69j2T1ERtLCnLNEFryFFjKDFak3PAGs28XdDlgFbF5KPPklZoBcLgg8cj2fPaikbDKDUJixacnN5jfXzM3Xv3OT25+9r6l6JEnUbvJZo3OkIYiNGRg4QNxejE5x+8iPyUBNogt77coDAFWxhIUzTyxHvQxkoJOTkBVJ7SxxCyn1ZfkB81ihwSm82Gzz/7nJ/+9Of84C/+il9/+AnWaE7vntLULevlmtlswf07d3nn7XfZ7nb88Z/+Ca+en9E0Nbqs0AFudgdG7yTzPmfmy4qmEUeE955MxlrNrJ1WH95TLuY8eHAfpSMXryxtO+f46BTXCRXv8tUlL8/OSMGhsxU2gc60VY1G3BFoKCtLXZfklOj6TIiZl68uuLi64evf/CZ3792X4qIu6XpHyKBipLGGrAsqlch+xNqG1WKOLisuXzzlb//sTwkZPvv8M549+YzNqzP0eODBesn99RJ0SUxwde148uwFm93IrkuMPrAdIKDwGUwtUy1l5P7XKExORD99PvKtsFPcLrci3RCSrOGYQFpJVllKKwqLaC5KDYXkIegU8AmqAvl3XVEVhqYsZEKnHNYqmpllcdSwXi+YzRqqsmA2bzlaL7HGcHV2hgoD89pSFSX9ELnZ9hx6T+oUv/ronNXdNYdeGpDaWu7MNHe/dI+3Hp8yXxhUHglplGx45DM39CPj4EVshYZbnkm7oqqW7A8jvj9w6EesiiSVZZq2WJJy5vmzM/ph4O7duxzXFVVT433g1eUVZ+cXpKwwpuRwGOm7jrK0LK24q1LO+Kjou5EcE5eXr7i8eiVkv77n6GhGVZfMlwvq0BBTZrPZcH2zI6VEUxSoMQlwKWjUohEL7NUNRIcPPZmJs1FJF+miw+fEbLVk1J6nL14wrhwmaLQVUaIf4PrlAcIlbvC08znLvsM0pUyzUqSLmVzOwe/IwzWqbzBli2Wk2F+zCgNfWjSE0xXqsGcRHXa7wQ4HMBXPPjhnGKC9e0x2gb6TMJz5TOO9Yb/1lHUJsaLbBfb7HYfdQF023FxuefH0krJpKeuaq6trfMzYsmC3E7u1sZru0FEYw7JdYEsDeLGqh8x2uydMTqnORbyfQqCUQVc1hRKhdkKh4i1sTSBmPkR0YcU19rrx01PiqzRFHsUQZD1bFJbt5prd9oby4T1ilkYlqts8HlFEGVtKsasNaGRNiZxTLvyGNQCZRIhJOnJrcM7hgiPFRNf1tHWFVoV0SPm2A4Ac5cBWypCTMPaVYoq9NagCvHdoazAqE5KMg1OMeO9xzrFohHon/594v40W+0ieRssxSqdpdEapKFhVBWPvKYqKsphMhcHTBRHslFY+vNE5Ds5hjJo0CsKcds4Rc6SwBcYUpBAnT6aQ+kJwrycCTLCGmCLD6CdxocYNI2JUMBRFg1IWNwa8C4wu4n0kxMwwKrrOkZNG6VqscjEQc0QrI0KflCAElBIhoy40TTWbVPQeYyoKq0lBo7Ey7rYToc+ALqUI0Nnig+SgK52pioqqqjm9c4c333iL07uPmC/WzNrZVFjImD79g3F/CD3eD4TQE7ODHCYXSCJ5ISpCwky+1JxFQ2G1dOy3sCahK0oOREqJkIOMmbPYLHUSZ4lMARRWfWFK9/3Is+fP+elPfsxf/dXf8OFHTzgMEV3OuXv/Hr/9W9/hq1/5CnfuPWBeN5CkWPj5hx9yVMrqZwABAABJREFUebOhqBuSVoxeVjW962UNYi11YcWLjwBf6noGWfLkm6aW+9ca6qZ5HYt9//591utT6qLmlbskhx2F1q9xpSmOtHVF1mZyzljBIBOwpSLhJQDHivgxoWnqOZ999oz33v+Yru8JLqGBWWUheGypqaxhXmqq0lJoqI1Gq8yLjz7g41/+nK7ruL66QgNHqwVHiznzdkHKJc9ebHn57BXn5xf0Q8QFQ+cyY5BdvyolvS+TKAojOR7JY7IW0I4XE0+YLHEySdOYLJqSGJKM/WOWQCqtKZuCsizBOLQKVKXGO5lizZsalTOrZc16MacqDW1bY7S4PMhieatqy2xRMptXrJZL2qoWRXTwjN2BcNhSJMdydUrWDS5VDP4l55dX9NnQbzPPD1cUy5JZq+mC4/RkzlsPltw5stjCsT9sQUXKtsb3AQ4R7zL94BlCZvABFzJNOaednWCLOX5MuFGmmS4cmDWC595ebUi9R0XNnZP73L1zn0Ti7NU5m+2W0UWMrjGqZBgTu11Cq5q6nlGULYMfIWXG/ob91vHq1Uu2mw0oyStpZwW2LLFl+Q9AbNIkzGaWcXQooJ1V3D1e0pYVy6amtJp+e8DqTNs0hDjKe9vO2LHFlAWmrVncPSHVhlcfvE++3tDqhu7Qo8oGU0VWJwZ3EDTu6EaMySxoZU3pB6y2zOctJtzgrz4i1gfc2DDuNpx/8B757AnHYcDWmaaZURuF6TuqqNje7AjbxL07c1ZNI0FTPhKNYXMzAJrDFsYusqgBNLvLA9llnItcXV6idEUxaAa/Y7s5sB+m3JZCTfwWT06K1aJl1wm75PToLjkrdrs92/2BMQhwLmlDsFr4ETGwHz1DTMQJiU6SUCeV5DR2HnQMot3yCV1A3dRAEBeZ0USteXl9yadPP+fdr75Nc1ZxfXXJ0jts01KWDSFm1G3MMeAzMEHRUo4EN1JMabV+mhD8xgoAlCZGYbUba2hti7UFwXus8yhtqWvZfflxIMUotj+lcSFO3ZOdBHdMivogh78x06hw2lEbUa7bQg5RYyzp9rBXiugjPom1SU1FBkz412LSDMSA94GYMkaoHeQknvKcJmK8UqL6IVNo8VLmCZN6GyATb9ca6nZ0P33vXhCeegq1SVmwwynfHhjNpB2QtYZ3ouhPSRGjIoTMMHrGITC4yGF/YHQOY+T90UYmLnJAeEyevudJDPd6Kz51IGDIRKJPRBzaFKQUaaoanyKHoaO2mrKU3b+2hewTl2vu33vAvbv3uXf3LkfH8iArylpgOM5Pu/xAcD1u7AluIOMlzyGOxOTI05ifxAT8meyYSQ4sNSlWU06kmG77eextToCarmWSsZt4uY2sQJKSSNGUyRZSiLhx5Gc//Rn/5b/8V37+85+x3R1QtuX4zkOOj0/5J//k9/h3//4/8KU3HjHkzNNff8Rf/eVf8rc//CEfvP8+ShuKynI4HBiDUBxCToJNNsJtKMuSYoIuKURk2TTCUViv1ywXi9eZEUppvHPsd08ZupGbqw2FqVjO57z5+DGHzRXedRij8SHJA9p7rLG0TU1ZRNEMZLBivECiTD1uGBiGQcJxcqCpS+bzlrqp0ARO10sKI2hfYy3BjbLKCoHQddiUaCZb6slyzZ3TU4wt+PTJCz7+8CmHrazHgo+MTqJ/lLXTNK9gZg3OOxSB0hpsUhDE7RINuKAIMeEjJCIhKcpCTcFO8hHLSV5TWRrKuqQsC+RmSRiTKeuS9WrG3dMT6qpgvZpxsl7RVJaYAmO/J+WILQyzpqZdVDQzKcaWyxWzeo4/HLh5dcGzZ0/Y31yxnjd8+1tfw8WCVzeepy82gMK5TDmvyYyMfcJoOD6acXy8YjUraSvNEDtScpK9njPjGF7/PQyBrhdRbwxQF4au95yfXaCzJ4c9eppW7rcSFauVorE1J0cnVE3L2dk5F9cXHPpOhGOmImRN349sNz3B5wkQluj6gZxHqsKw2264vtxzeXXD6CLzmaJtSuazhlnbSPFlNNa0GGPEbZETy6bhZH3EupmxbGevNSkmJQ59LwW3sRijsNaQs8LYSrIPTIkphEiZsmYcPe1sQcaw3+8oi4LVyZyrcMF+e8O439GXBp1GTKFAZdpmRj0ObK4vuNy8otpdkKNj2O3YvTynCZFVXZCJzKwluoHdoaddzERfcao5Ob5DTJH+0EPW9L5j2AnwbDh4lAqc5VcoJamRPnj63tN1kJD7d/By7caIsBl0iWIKGlPQe4hOeCdlJWfTdnTsfZDJrE6CfkbOw4TCA0MQsibGEBGHVYhJ7ORWmmCtFRjJ4KgKO2HjPZjEoR8Yk+fXH33Mvt+y6XZwfczs5RVf+updFos1PiJfN2tiVvgQiDlJ4xwDWZeihTJ6ms7/BgsAbQpCSsQku3FrpiAdkynrmrIoxcKlwBQlKY9EMmVhKfQUE6wkFCglSeGTw32qWoMXup8RW97tQ1dNB4FzojWATAqBEP2kJ5gO/8lX771MDlJKaG0YB4kEvt3bg57cAhGbJvV+Fn6+inoKj4FCQTYiPLNKom+TVVNkcXqdKzBVAeQofIMQ5OspI92ymXZCMSb8KB3/6CeQiZLKvD8MdIcOFyLWRqH0aSB98bWsUlgtEclKZaq64DYwKaQ0MQyEWiirg0xIHp+MeDOmKUVKkFXBar3i6PiUBw8e8PD+Q06PT6ibGVqJ9oAcRK3tBqL3kD3BDXjX03c7jJVpDIgXNaUw6TfEn2/N7R4/TbAdgQOJHkEKJ6VFEHfLhee2qNHqdXEm5L1CmrsQSc5zdXnNj/7uR/zJH/8JH374IZnMnfsPefsr3+QrX/82fT9wdHKCrko++vQz3v/VL/mrv/orPvroI168eI5GsZgv6LoD3TgSc6J3I7rQ6LKgqevXxafWBo0I1aqmpqxK7pye8O1vfovVcsUnn3zEp599ymW3k2JiDGgMx0en/NY3v81X3n2HqjB8/7//MS+efcZ+u4WchcaoDIWxzMoSbRxkud9zLFA5AJ4wbmXMrANVpTlZrDk6WmOLYvqMJObLlllTToRLz9XVDWHKcBB4TKKuaqq25fj0LmjDL371MU+ePGe3HfAedJ4mZEZEfok0XYfIrDIUSkGMLKuSpqhJo2eMgV2IeJ/JnkmuIaFaOWeK22mdknhwa6GoFUUFSntycMyaiqP1ivms5eToiNPjNXVVsGgb6sqSk2OzuUarzGo5Z7mcc+f0hDsPjjFlFgV9WaNSZn+pGLZXFCbT1CWLxYLHjx9iqzXzsy0/f+9jrBFBbegd0UT6Q6KIcPfRCW88eMidk2PapiL3nlFbXHKMg2O/G9lve4YuMg6Z4DUkmVxc9zsO20/43BrmdWY50xwtaowOpEJ2yJopbTTCp59+xma/ox87IlDNWgFRucRmt+Xi+gaNpiosVaVQeRKNBUFyO9+hdaJtFcfrGevVjPmiYTFrSdHTtA2zuqGZElD7rielRFvPKJWh3x+IEQ6HPa7vKa00Tfuup65Kmdg4yRYhJ/a7nqreYXXBydEdrl9esbm54XBzwHcjx8f3mBUVO6NoCosBxu2OYbehqixHR2sWBaibLfnygtBWbIae/X6LzpnaapqipC5Lmaqg6EKkS5HZbM68UhQq0lZzrm9u8P0IaMZhYOf2YmP2MlHs9ldkpNC0hRA9x97hJ3Ksz8KFAPk8z5YrnBPS6eg8PsvkJGeI2z0pJVkLhsgYRL+kdASt5c+ZHoS2LiEmxiDBbTlJE4dWlFUhpFQjFnWjpQCwhcaYgpAd2/0BRsXzF2fs+h3z4xXFYWDoPHXZ0tYLYhaiJ7oQIFVCztUsBYDwcvR0XvyGVwDOB26F/ylB0iIMjDFPL1TacUnFkyJAVuUy+kXJ/lAhVCOlZH+PVoIvTLKHsVNa3C3gR8MUG5ynCyOdfmVrck7i9X9dVIgbIIQgHaQtiFZJR6fEJsaUr30LpNG2kNFh8mhjKPI0vome7D3kQFRK9rVJCpkUJb44ZRFfqMQEIyowVpTRImgUNWkIsgvNWUPWxOgZR8/oBvp+pO8GnJebSiYMeeLni/DPGtEXiM9ZrHNKGXFcxDDFkspBauoCY+WmqtqSRMSHhCkKbFHRzpasj0949PAN7t9/yOnJKW3TfqHniFNXHx1+HHFuIMUvCoDgepzvsFnJ/p40rUSC1GJKTz79SfKXb90WegI/5ddTHa31NDXJ030BKfips50YCSSKUpNiou8HPvvsCX/zt3/HD/7yr3j16gJb1KzXa37nd3+Pb33ne4Sk+Nu/+Rve/+ADPvzoI/q+Z3NzzZMnT7i5uSEi3IbNfsd+t2McvTgUrKGoS6q2YbleUxYFbhhQOVNV1QTiyPSHjpurGz75+BMKYzg7e8HFxQW9G8g507YLHj9+i9/7vX/K//Av/yX3Hr+B8Y5PP/mQ3faS7c015ERTNlRWIFOF0lTWMp8vWK5W9OPIxcUlw+imwlnTzhe0s5kAqMqKjIQ4heApCsvDR49YLhZcXLxit90wdOLKsMagK8366JiirLm63vL5k+c8e/aSYYwTxx6il737vC3ISRwqOoPNUKpMoRNkWJVwumowsaZ3gSc3e1nVRTBaJj0+MxUgiqrUlKWmsBJwZIqENp4YAk2huX/3hC+9+ZjjozVVVaKS6IL6w4EcS3Ia6fY7wFMVc2Z1QVUqmlIzW9cYa4hDz3Do8MMO12857K+5d3fFW2+9w3q5wDYLXl7siX6kNPJgDiFR2ZLODwx7KNDcPT7haLEgKk9dFDhbElTCjz3dbmC/G3FDIgZLDkYmJsNIGALJOwoDcQ3Hq2NQMlmoKkmTTCGz2/fsti8ZxpFuHCjbkvlySTaWbnBcXu84v7zmsPekCFWhWC5qCltgjWIYOjSRWVPQVIa6thytlyznLYtFy9FyQU6BpmkojKG0FqMNfVlLuNXNDTsn93D0MllK0TNrG1nvFAWqmCBsWVFoi4+em6sdbvA8euM+907usTm/4bDZY1HM5jOa0rK5eEXoD7SFZV5X6NvPclmxsDW1j/h+z1HOtIWlv7zEbTbM53PWp8c0RYmKEa0LfIwELLpo2A8RFSTL4+bqhv1uR3AesGglupDDYUApQ0ia/cGTMqxWJWXb0pQFzaEnHkZilrW0raRRjaqk9+CT5rp3DEPAWsGhG6vpBscwODm3jCZZ5HDPoFLGT42s1kZ0S2pKv0VNsDuZIFtTUJYFhbGTi8VD8GSlp7F+JkUoG4UtS8qmZXV8ymKxZjVfUShL8hFlpowTRCulrCEmUUfFlChNnPgp/38oALa7HU1dS0gOgvaMURjvSskIUGA5wt+2xoAC50ZCFLKeVko8u0mEDyEHko/o6TCWEfutYjhOojtNDJPDIAq7XBe31ZRAMFJKOOcn+52d/psUEUVVCqgnivjCaIU1GmXFd6yBQCLHKIlLE9nQe493I1hhEaTJgnYb/JFSloRCBOkZUsKYEj2N0VKUX/fO0Q8jIUjiYQww9CP7fcdu3+NcnPzKkmsgND7IKb8+MLMs0SUkxgikJyW5wNYWFIWE+KTJCqK0JWZH25YMvUcZw3p9wtHRHe7ee8jDR485ObnDYr6c/qw02TXl6wQ/ElyHczLuD3Egp6kA8IMURUGRA0SSIJ3RU3a95daul/JkH0NNK5iJ0GYmpCtp+iuTlVRSdVViQe6rnNFZOpjnZy/59a8/4c///C959vyMzWGgqOdCoLQ1V9uO7//gb/jsyVOePPkcoxW/eP9XkglhZR3iYsBaK8CSvoc4/TejZWJQappZy2K1oipLjFbUZYUfRzbX1xx2W+LoGbuey5evXh+wSitmzYxmNuPk9B5f/vLbPHz0CGU0Z69eMt5cEbJ87aYqCFHSvLKf3hsXSdkzP1nz4PQEFzy1FZxpO59zfHLKcrViGD0XV1eEJEXMdrPjZjOgdTHBtxzBO+ZtS1WUeBdIOTMMnsIUPHt2zrMXF+wOHfs+Mnr5HGsDRakpCqHNqRQhBazJVDZR4tA2U1g4rhRvrFqWTc1+DAwhkVJP9I5DkAeeltrwtQBVaSVTqRwxJskEQCVmbc3p8ZKToyXLxZwUI7v9nv12wzB0lIVlMasY+54Ye4a+gnVDf7jh+ZMtx+OK+XxGDpFh19Ftt2xvLhj7Peu79zg5PsKNA7v+kqdPn7C92aKTUNqMKSmLht6NbIfM2DkshtKU7McePzr86PFjYOg9+73jsPf0h4QbDH5UuCHhRymeDDBvFUfrVooZmzFaJoQXF1eMg6cuWsE7J2mayqqlqFoGH9ge9mz2HYMPDAFSkIJJWBeJqigJQ8/xekVZlCgFhVVUpTQIVaGoSyMoluAYh4hXijAGLl5dcPHqcspREKDa7cQ0awNGsz494Wi9pCrFZ+7dIEdN8LiDI3SO+0fHzNqGma3IamBWVxRJgRsYdjfYFFjNFqznc8gJP46UZUGZMjYEKp1ZzxuKsuCTl5eEfY+yJUUQWfBh30kmSYykJAFPl5c7wsGx0DNuXl7Le2cLMlnev1yyO9wILCdb0oTGDarC5wqtC+pFRdCO3gljQimF84GhD4TDFp9gu/fC+ciJIidKDD5kXBL9UnGL/9ZfQNsioLNAf/Ltc1splAGyrAG0EV1cTomQPSYLtC0owai7OFLPSoppYlE2M07vP+Tuw0csHzxktVwydAfcOGKrBqUNypbYoiIpS0oaqwtxvCGOM6WkOPqNFgDDMFDXIsa7FfJllDxAJqvCMPRoramqkpAC3rnpwz/BaCYvPxPO9zbfPaX4mu+fUpq48TJuuNWOM+3/c+Y1gU+wwHLwOB8gJjkQEE5zCIHZfCVCiym0xlqJHDJZHgTRB7Jz+K4jTpAXM1EJzRToIyQ6+TnHLPQvEIBPzhMxzqEn7r93iZwUfuwJLuCcn1T/CucCm13P4dCT0u0mX6YTAsSL5NdxxDIiF/FolOJEG7QRgAoZVDIUZUmhC5kyJIUPoEqLLipa2woZ7Etvc/fOQ05O7rFcrgXtq/W0svAoJQVH9ANu3BF9J3nsURL7cnSkJD5UsnztdEt4nDIQXu/9c5qkFfKr0Ud5QmY51EkiEMvT778VUqos7WjwI0ZXFEXJoRt574OP+au//iHvf/ARPsHjt99luTphvz/gfaQfBs4ubwgxYKuSL7/77gRpShz2e26urgRiVViyUvRuxMXA0XrNcSX0veV6RdlWxJx4+OgNHj54QN8dePnijJvra3a7HeOhpyyEhFloKSDLQj7gRV1RNPJwPTs759D9DT/68d/jx57+sGXc3xCCY7mY0cdA7AZC8nIdygKlErura87Ik7BH8ebjx7z97jusj08wRcF2v+fkasX+0PP8xUtc31FYjTZwdXXBerFguVxwvFphjKE79Jyfv+LV+SVPn77icnsgZsPoReSXtHRCdWWZNxW1NdTWkNyALmA+q5hVBSYF5k3BrLTMreXR8Zzj+ZyrXc/Fci9an7QlbYOsvywTB0RhtcyCRAeSqaqSedvgdGbeVixnDaVVeDewvdly9uIFu82G/WFHXVpOjhYYHUl5YHNtOFrNIFu6zqNNxHcdJkMcHN12w/76GpMyOUSuLq8Iec/m4Hn6+ROG3hE9EmGtNSlO4lOf2d5s2W32rN1cPmcRgksSxT1GglekZKfGR+FdJjqEDeCgmcHD+0e8+/YDvvHVt+h217x4/pTD4UBO0untxk6S/sqS+WqJthXbbcfejXSjx8ck/m2dMQVisdSZnCJV0RCMldRVzeusA6sVOXrGLrCfbMFMyGKtNUM3cvHqguEwUpU1zjucD7SzZiLIZeZHK+4+uM981sr4vjsQncP1I6F3qDGhVGL/8prV/YKTZoayB7T3ZOdAF5wuW1STmDcNlVXsdwP7zZ7CGtSiYXG04OTkCGVgCIG61OhlK5O1DLubLbvtAT+GL54rSuNjxHUBrGM/RpSSz11MchiPQ2LnwJRWDn5ryEqzC5rd1pGyZ3SK0Wd8FLFq50d23YhLEawmJOgjtFWFS5HDECmCTJ6TEgqfdkHWo7fWZHmMoWKi1FBOKzk/jpMVXVghtqwojSX6gI9uWnsKHM3ogspaTGFpKkW0EJWhnC0IyuBj5OX5Cy5uLrBFSVk3FFWFLUtxZpmClDRl0VDUMxQWbUusmfQ1v8kCoCiKCR4jufQZNQnWJgteSlNKnAi/3ASXKU05MeKn1UHKr610Ap7J08hedq4pCbFO6H4y8IhZJga3gJ00hfLY28PeB6lWlRxot973oizx0RNTJjgnWfQxMfY93XYPMTJ2HeOhY3+zEcxvjsznLacnx5iqxNa1dKd6wjnGTEiRSCIqUdePLjC6cdrPa4IHkmK/OZCCTCf6fphU/wnnxSKiXgv4puImyYTDKlmfaKVkLVEIE/0WSawUVHUpDyfvyMpS6EqevNqCFmvjYnnE/XuPuH//IXfuPGC1PKaqGnERRAEbxeSIQVgCMXi87wjjnuR7QTJnB0k+SCp7tMqMvn+dOWAnLG/KGTeOJOJkT7nNo5Drk0KisLcTmkmIqUTpb6x97RKxSooiBVxeXvF3P/oZf/b9H/DJZ89QpuDtr36Df/X7/5qvff1bmLJidIG//sFf88tf/ZJ7D+5xdHxESjKaPT46omlqPvvsEz756GOePHmCsZa33v4yR6u1dI8pUxSa5XpNvZgxXyx4eP8+Nzc3/PUP/pKzl+cUynByespQd4RxBDKzdoY1MuEpy4p+GNn3AzFvUEpTVhU5R5zrIDgqk1hUlnVTo8eBfhwoFJRaUSiFTnC42aLJrI5WnJwccffkmEXbMHR7UoZ+dLhxYDjsRWzVd9Tzhs3NFcE1fO2dd3j8xhs8/fwJ5+fnXLy84uOPPuXQDfigRbejLEXSVFnErlYr2sJQKk1lNI3R9CFQ5szd1Zx7J2tUHDk9WrBua1Lfc9SWNCZzNe5Z1xp0RYw1zu2JvfDOhR9gKQqF0ZHKiDhtXst+Oo+jeOgnuqdzI5dXVzx99oyxH/BuxNWWHEfWq5alyLvZ7XakWGA0dNsDeXDolBj3B65eveJws+XR/Qc8ePiY3iW6buDi1YZhcBQ6ozIsmhl9sviQIIvuZ79z3FxvuNMfQaEoTEnwicN+4LAbcKMAiEBjlEGnyNj1+D5RWHhwd8VvffNrfO1rjzleNmwqzdWrl4wpsz46YXOz4+ryBqXtNJWRA9YDFBVKi10SMtaKoaaqDGVhKI1hVtf4g6Xf74VTUlqMqSi1POO6fc/Yd2itJCQmK0IfGAd5VtuqQBmLJjNvGolTzpGT0yPu3LtL3daTCHcq0n3E7w6EfqDIIlyLNzuq4yOOTEEfI4aELS0lGaNL2nVDHEf82JPjiNFJQF2lAZtRldwXOUXu3lsTIhwOI1cXN+x3PTHAft9hVIH3AtyZz2d0XWK0Aa8rmcaOop+KzrM/jAxeURUFow9kJTbisXey0w+JmAw+akLKJCXK/d4FIpJuqYzFm0woavw44mOkUErG80aDZpqeZOz0vNLTexVjJLkggLIs2TVWa3nGKY018s+B6fltFFpJC5l1JisEaT1rsZXBNi1BWz5/cY6+viEYKOqS+WJOWVfUbUNdNyyWy2kVaKjrGfVsQWFrirKmqhpSVsxPf4MFQNM04gJALIE+jNMBPvndrZk4/GGiyhmq2k4HhQWkIrVGk1MQa9EkCCOJsK8wBqs0PqXJ6mde7xLlSMhoY8FKjPAtTOc2T0DdUgOjMO6VMYzeTwWGJgdBpR42O97/xS+5fnUhQrMUSaMj50RTlexKy/XZSxbrFSf37jJfHeFjBFNgjGWMgcE7xuCxdYkyBq0LYoTgA36UgAbvEpuba8YxkBP0o+QmWFthtcWFCIRpJJ4xVlHZGpBiQFL45HC1SlwRagp9KMuKsp64B6YADGRN3Sw5unPE8YM1d+/f4dHDN1ktjyimBDaNhDPl6MXK6AfG8UAIAykF3NhBdOBHQnKoHNA6YbWAEFIKMspVBqOl2w/RQzYTgVFPCXZJLIdaE3OY1gQy6bjFQqM0VVGJZSp6Zs2c5BKFKXn67Iw//JP/zl/+4G85e3VJ1iWL1TH7Q8/T5y94+PjLPDq+w+78Fb/+5FM++PAjbnY7VkdLKRa1YX18xOO33uKNx49Zr4958Oghx8cn/PZ3v8PJ0RH7/Z6rqyu63ZbjO3c4uXcHZQ2vzs754R/+IT/5yU+pbUF7dMS8ajAoDlFAHKPzuEmh732kG3r6cSRlRVmWHB2tefTGA46PFuQ4YHOgu7lAO0dzvGLQmWF7QIdIGBM5D5SlYd60HK/WHK3WWG05e37O87MX9ONIzLA79Hgf2Ox2VGVNaQRWdXp6CmQ+/eQTPnjvAz744BN2WwfKY6yIF01lGFzGRUetJL66MppGZ0oyrdLUCkwhXVFr4M37pxQ6MqstlYJsxGZI9FQ2My8zurDEULI/yEMzaDCVpZm1zBct43igOxzIOkMDJhmW8zVDt+Py+gZrS6KP7A4SvoJWZKOo2xnHd445Pp6znBWsly1NY0FJwR+GxO4g7+HV+Rnb62seP3zMV3/rt5nNV1xe77j86HNuNj27XU+ImeWsEn2QtnT9gLUF86V02Yd9jxtEYLwfe/a7gW4/Mhwc3d4z9oYUKoiaODhCH4keVjPFV778Jt/9zre4e7rg/OwJu81mSngUxDcI4KqZ1Xg3MnrP8uiUk/sP6H3gg08+IcYshM0caOuC09WM9WrBcjFjMZsRDnvC/kBlrORvTKpCM03fxnEAYHZywm57YL/donVBUVZkPINzlEVFM29wbqRtKx49esDResG8rYijE/zyfk/uetLuwLjd09qK+XLGKiu6Fy/IMXGnadApQogk71Bk0rgX+2+K5Og4OZlzcnoCKuPcnhcXO9q2mZ6Vib7z3Gz27HYjMWjKqqWen9IfBg5DD9Gw3XpcMoxjxGUZvYckAuecNS5oxmDwNwMuRmKeRNlKAtW6IQiIKE22dK1FzK60WOpQhCFIQmVSJGXxCI8GJRqdFCNZSRCbKqYVc5TCVZgwQofMMaKBuiwnkTionGUNHkaq0lJVVuB3OlPUFpcCyWooLEf37vDgrbfwyvDk7ILdcCCoRFmXzOczKbaqknbW0LQNy/URZV0zaxeUTYvGUEwZLRnF/bf+p99cAZCSn9Ljbve3ACIMDFFsgLedt9Zq6tZlZOK9n7zfkRCFY6y1ROLqDHXViDBuGImv31hNjhE/OqyS8U6MUXzwxkzo39vVgQRuyNdPr4uCMAUFiRVNfjZokg9srq45f/qcQlvJgy4r0hQgoo1m3PUctnuImRwUuqjRlSIomW5kpUAZ4fc7NxU9kgrXHUbc4Li6uKQ77NFawozkDlQYZSWyV4u1URszvWeIjz9PgBgm6hqi9tTkaQwFxpQoo/BZMJC2Klks1rzx8C3e/PJjju6sWSwXzOdztBaEak5pEqd42e+HgRAG3HggxkFshGFAJ+EKkCQBnZRISPxvSl8IMtWtLiKp1/HI2lpcmNDISbj/dsoVqEoZYeop2TDkjBsm22U29N1ImUve/+Wv+LPv/wV/8YO/5fJmgy4kHnd36Bk+f8rVtuPz5y/5+je+RdcNPHn6jEM/8Olnn2OeKYqyYD6f47zn86dP+PY3v8Xd+/c5OT1+TUW8uLrCO0c7mzGbtdx/eJ/DMPCLv/8Zv/j5z/nRj36EGxwP3ryH1koy4p2TkW6MHOJeHBdaM3rP6ByL9YrHjx/z6NEj3n7ry3znt7/J6o374A4cnn3KL378d3z+4QfEw56GBb0CfEbnTHCJui5p6hajLMNh5GV8xaHreHl5QTf0uBAwZYnWBqMUbV3RzlpOTt9htljw+Wef8P57H/LybEN3GAEBDKFlH5mmyU+a1l/aagoSNZllXbOaN+jk6DzMVyvefuMBpYpE17EbAt5qFlWNtpCCZCqcLFt05xgqzaPTFbN5po+ZaC3tfM5iMef6JtFvDgwusskHdLas10ucGri+2eJ8IqfMbneQ8fBszunyHserJQ8f3GW9bLA2sWhKjEp435FCZL8d0SHg9nvOn16gQubkG3dYH98TLCqOq6uey6sD+4MnBIkjHkfHkCPOjxhrsFYGpkM30u1HVJ24udly2HSMB48fovAOokJFBSETR0f2gcpCqTOu27O9vqQyHpVg7EeGSftTlVBWDcYeCDFStTXGlrRtS4xJ1oEuYZKGHMWrf7LmznrBqiloqgKtMt4JAKg2BaUtCcnJmtWAMYpSyTprdI7dfk/f99SVJGgqJfHmsiuOtHXB/Tsn3D1esWxKKg1DcBjnWBYF9+7e4SZlPn11hd922EJTVZk47ikLy2wKYwthQoDHyDiKJa+dNbRtRdMImGgYBXPtxk5s46bGe8WhC3QHjw+KrCuCqlCq4mK34+Za7i+SJ6DYxgzWUpQVow9SNGSFKSwxa7rR40ISfYwxMoHD0pEYcyaQJxtyZgwCbxNhqzSNJQoVkmCqs0KlycqcMkkzdfRy/TNiPdcojNICnUNogFZrCmtlvawFB2wKTWFrmbISKdqCSGTEM+RAUTTMT9Y8/PKXWd29z0dPPufF5TWdG1FGE6/3FHaLLTS2NNSTFVkXlpQT7WzG8ckJRVGhjWG2kOf+P/+D/9/n+j8eBJT869S7FIVF7xEVvMTOutfo3pzFI+lDmg5fMyFbRZQSguQooyeefxRLYIpJkty0IoaEng6QYegxxk7j/YyxljitGYwxWGsnHvJtOp90zeKTFICIi2DRFLaCBIWyGGUoKbDJsLvaYLViWc0JvccaTXKBl09e4IfE+s49Zkc1IQViSEStUNriYqAbOkJIlDYLpnVzYLfdsd1sIWW01VijMFOIxDjepvUpfJB9XcrgswgotVECRjK3qxJQxmCKkqqUxERtpIrOQNMuePzGl3n8pS/z6NGbnN65i20qCclRihwlQSpn2feLn/+ADx0hirUvZS+YySRwJ2IWwFBKRCI5eymycsZgyFO6VU63QTwgu7GpSCGLNTKLv13lxBhEYetjFMFZUeFCnlZLiqvLG37507/n7/72R/zw735C5xzHp/fAVPRDICjFMDrSZkvX9ZzeucN2u2e2WLBYLRmGThQjWeOcY7PZ8PDhQ775zW9y9+5dPv30I957731+/OMfA/Dlt74kmes313z4wYf87Bc/54c//CHbmw0qZu7fv8+Dhw8Yu47L81fs9x0+BFHHa/HxKkRX8n/4g9/nu9/7Lu+8/bY8GJ1jNWvRuw2vzj4j7G6I44GqADOvyVbTG0UcJEhmNBmtYRxGuq6XInMH3TgwDh6yOCaqSuyVbV1RFoa6Kjg5OeLs7AWffvw5V5ci9ipLsZz1Y6TViYRmDAMupimIKaNIlEoxLy3rWcXJsiV5TWsWvPPlN/jSlx6w3V7xcrvnsN+ynLXUZYmJia7v2R8OxAzjoSMOjloXrBqD8RmXEzY50tChgqPUkrR32Hty2lMUNaiCzfbAxfUOpTX9MDKOmdPjOSfNHWbrNdV8Qdm2GC1rt9GJdz8NnrDbM2639Jtr+t2BWVVx2Ay47YiqDNebgcvrA7su4JImZEXyiZCYOO2T+1QbFInt9Y6zZy+pVyUXr67Z7vb03YjvMsobiqTxLhI7Rxo8RYZ5DW0B/e6GF08+I41HnJ6eoLLCjVMy6EJT1hZbFozOye44Zy4vr9l8/pybXUfXDwwuAJlVU7JuG+Z1SfIjY38g1nYK1hJ7dFFYdELS4ZRgvWtb0/cdl5ev6PYdWllKIxHgKSTaoiCHSKkt905PeOPeXQqlUH1PiIGw3RL30vEv2jlRKeaI+HhVWOw4YFWgsRoTPKHv0Umsxz4FbFmzXC6pmoakoB8Hdrsb+Z4jFNGQQybbTGUbgo6iOQoKXdcchsRhPHC2Hdh3CWMmKFtds0OgPnnscSHSDzL9xWdSlmvrA4QoBbXVImoek/j0/bRSTTkzJLHzGRVQU/MSCISYMQrR5Uzo55iC6ESi5Ks4F4QZkzOF0RRNTWkm+ziSjJmT0FYld0a4K0VdkhIyFa8U24Mc6PV6ztG9e7z57rvMT0+4Oux59uqSg8+YajGtFvLE4cn4LtJ1AzF4TGnohx5bWI6ON9iyIMZIM5uxXC3+Uef6P7oAiMmhtFhfnHNoJQeR0lY8k/GLWMo0JQGGyU9ZFw1qGgdbU0zdIbjeEYKIJpaLOYqJooQW2EsIr5kARaFeK9atLTBZ1JghioJaihQZSVtjRIgWI4NzRO9RSYhsKURc7yEpSlUwdiO6SCyaBd/77e+iSLz3y1/hcqCua3bbLdGdQbJo3ZDLEqU0zo2MKZFUxrnA6Bxd8gz9yO76wNiPFLqW/VGSjIKqqlDqi0heW0plb63BFHoSf8mBcquvkERFQ2EKCiusZxdAp0Q7W3Dv/hH3Hzziq+9+g/sPHlFWDYoJWBRFREgKgueNI84d8OMB7w7E0OPDgPcDOQs1LAXZ16sstEUQdKuwARKagqKS65AyJJWlw0DioVMMr++FsrBYrVBJRqykjMlSsGlVSBQnhhwN5+ev+MXPf8V//n/8b1xd3NCPnodfeouHj95gSJl+jGALinrGG28+5n/4V7/PP/tn/4If/vCHcn/GiDEWW1hWqxVtU7NaL1kulzx//pzz83OePnvCbrdluVyyXq+5e/cOfd/x05/+lF/84hf8+v0PuLm54eT4mNVyic7w8sU5/WHPfruj20v3P2saSlNAhocP7vMv/uW/4Nvf+RYxBn76k5/wwXvv4d3Aw3unlCZx/fIpvt8yrwx3jpbMCsv+ZkN2PS4polKEKGjh/X6HMpp6NiOmyKHriSmxXC05Wh9hCoMLnvlyxtHREXVT4vxAUxd85d13uHPnHu/96kOevziAFu3OMAayhtFJeqWxFiacd1kVNJVmMSuZz0q21xuGfksIPUWpWR0vuNpY9i8PpBRpmxkDht2NRKcO40jIMmEahwNjNlhbSZEeHL0fycGLp98o+jHgo2dz6JjNa3ajZ7sbsYU85/oe/OWeqJ/Rp8DeDZwsl1SlxeTI0HcM+y2pG2B/oL+6IfYjsxIikaefvyCZ97CLNS+u9+yHiM8Gl8AHhUasv4XKlKVFFZpoA1FntldbPv/158yOW653Vwze4X0iO00RC3LW+NExbHvyGFlUsGwUi5lhNa+pjCQ6Dvs9YfSkIMjvw6FHFZakoGlrhmEQbUHn2e16dgfPOOTJvw74iEkJHYOISFVgbEq0ytRNRVGLTS0nJURGJdbGqqrYba9wfSe6gapmvZhR2YqxHzFZ7NazsuLhfMlSKYbtFkViOOwJfYceRlzKbNQlft/zYDFjNZuznLeM/TVWZZoJgx37Aa0NRSWpmgrNYrZCGUXXdexvdoxupCgshIhJGpXtZBExEDSuh84JKers5sB159mPCZ9Fa1wYw6peooDd9WSRzDJMFTtnxvmIKSxZGZIxEss7dfkxCVVTXGfSpOQJyZsmPosWfpnozgpJjjUkMkIHvIWBOR/xMRGUHPQgzW8KoLNonNQ0bQVQ2qKtJiso65pDN3CxHygTtEctX/nm13n0zlu06yO8Mvz6syd8+OlTnr28oA8ZqyCELNodCnHBxYDRJbZo8F5CvFJUbG56sjpQlgWjj1xdbX6zBcDYb6CqiDERvZcKKU/VlilIU9cn8byTdz8nFEYKgW5AZVFP6qwJzsseJSsR88WM85IeV1QlKSfcIMjZsi4mG9lkBZzsNYIHFlWmtRatI6MXP3bwkumss6YoG0zWFGjGw8D1xSX95kB0UgzkIfPtr3yDf/lP/wV/89d/jR+ipPkNEZsElXnBS3wwVOs1drHA+0TvR5LKDEH8omHMdIee/jCI/53bw1y/tmYUNmOLTFPXMoLUWSxYpSHliNby62oKTTJKwEhFITkAIDfvan3CW2+/w9tvf4U7d++xWqwknEI2KK9vQpBxfgwjbtwxdhti6Mhp4viHkTi9Z9lA9JGcFFZJXLAQBqcdJuLc0FpUpil6+VlpuRxpClEyGmMURiPxv0ZNlTC43lPXJePgOH95RVYW5yJ/+Zd/xf/nv/4pru8ZRhl1L1cnnJw+wClo2iXz9Zr18TFf+do3ePjwDT788AP+6gc/4OLlOd6JhuONN9/g9373d7m4uOCTjz/m1fnf8Cd/9IeklHj04B6np6c8eviA4D2ff/YJ5+fnfPDe+5yfnTGfNbz5xiNmjQglc0h02z273W7atRq0sbTtjOViyde//nXeevwlrm4u+V//t/+Vm6tLNlc3hHFEpcCHP3c0JrOaW8Kw56037lGezslxoB92xDxS1oZcaWwJKcp+2hRTIR0h+kTImZRg3rYYo1g1S2bzioeP7lEUhs1my2I+I2fNp5+dYW3JbOYw5YzRixBOaRhHD2RKhB5WWM28tZgyE9VINhVFrbCVYnO4YQg9bVujC8tuiGx2ezIXtGVDGCPZlCSd5N5OkYwgVCtrKNtGvNNKVN+7fsD4RNFmXFIEYHMY6IYkKyMt+lVVgSNxsdtxGAdeXr7i7vqEWduSnaPrDhw2W8K2o+4Tx3ViViisLshR8erlFWdXO/RsTadKLm72bLqBzWGkDyLuKibKoyjAZY+tlSL0ns3FZtrR96AUhTKYbFAYUlQMLqKcxMqeHjUsl5ZZA+t5Q1sWGKW4fHnF9eWGfj/Qe884hZC5EFgsWplkTLheYyylyWTtMQZmjWFZV8yrkkVd4HUFKXDY73DBCVRnsQSkq7baTCjwiCaiUsLERFuWnM5nrJqKpqihqsmDwxQFd4+OOC4rbp6fcXX+nOPVnMZq4jAQ+g4zjbeblJktZyyaltEdmBUSdavJBCfit2wMGIVKBYf9gU2xF14JCRykITD2nuA8lRFSXddLxsIYLfudZx8UwzDwajeydYnDKHZrNOiQGXc9HtiOURC4gB8BothLlZDxlJZgMx+DvB/GUBQlRVVIguMEk7MK0AJ3c9GDyhPOXRrKHGVimaa02back9KU3ZL8bTCpjOeRKTY5EpIhGAmO0ShsoegPA2VToEfF5jCiy8z9h/d45xtf4Zvf+y264Dk4zycvnvKzDz7katMRtcFlicwui4asC7IWK7OPGR8SyidiFFqjnbRyCUkGTS6zP+x+swWADz1NWwouNxvKUk9dthNNQFbECExoV7gVfclhkoKsDlDyMIshoVAURY1R4pE3ZGIUy6FSitJaCmOEHUDGOz91/PJ1RPCX8MFP3bVwnZMSsdpt1K+1FhVBZ4UbRjbXG/wgU4Cj1Yo4Bs6eveSP/uuf8Iuf/QznPLNZQx9GGUMZQ/JRusAIdVSMOeFyxKtAN46MoyN7JrufhJ8kZFffTDAQ2ZlFbCWJhjF6jNUYM8GRJkV0nMa0xtbyXiqpUNu65eT0DsvVEW8+lu749PQeRSGeTx9FN2CtRXkZ8aYoWFjvdvL3uCOGgZwdKYyk6MneySGfLDkIDvc2fREQb/+UhpQnG5T4XvWt049/GOFsCzvxBJywHIwFpUleEvyeP33B3/3wp/zyvQ9JWJyPfPb5E7bXW2xZ4kJGq0RR1pR1K9CY2Zzleo02BZ9//oS/+9GP+elPfsqTz58IiGYYCFHQx8vlkvfee49f/vKX09QoMJs13NzcsNvt+PWHH3A4HOj7g1Ahp2K0MJbKGA7bHTlnqqLG3arVo0yWHj18xO9+73t897vfZbvd8qd/8iecn5/R9Vvh5MdI7Ht0CpgcCHHA7SI6Js4YKNJAU1ncOIJSKCv7/Lpp8c6TooCkxq7DFhWL1Yq6aTFWT2JXTduWON+z2VxiC83uesvNzZ5u8Jy92siEzkoEqfOR2Xz1mrPh3YBOnsJq2lKK5vl6yYOHd3H9HpdHZuuWMY08ffGMN7/0BsoaQs5c32SM3rBaZGy2VEWNKQu2+wPbfiCmSeBJQhGpyxJblRQhEFVCxUxtCw4+sj0MbLeyUskWxgQEoUvaUkFpGENg1w0URUc/BvbbLfubPf0uoA6ZOxoeLlse3TuhLRWH/Zb9ruMQM+NmYJMMr3YD151jdGIo1gpUjtjkiGNmTKL7KW1JaSpx3jhFHkXEKqJlQ/IJ7xzGBeaFZj6ruXO6YLUsMcaRvaPbb5i1c64urrh8dcH1tsOlSJ0kt8NFBzoTk/D7rSmIKtCUFa2txJHRaO6u17RFAcFjENhX33fyLCsLqqakbmuqqsBaxeGwZXN1gRs6TA7MSsOd5Yy333iIiRBHz3K2IJuB7uKGhQe92dE/e0G4uiAHTzWrydHjhpHaWlaLBTqJa8JmJ0r1QkR00bkJIqSILpDcgDUlhW45e3pBzpH10YJSW3qXccOI9+CVx1ro+8jgIz6V9ENmPwauQ8ApQzYFQxwJEWazmhgyFzcHXMqEybGjlCYhltOsRXOWY5JJY57WygnqWtFWFbN2xjAOmDjQx5Ek83+01pIwGQI5yXg/RWGXiNUSEaKH6SzRagqyVRLrrbUIna1MrFOKDM6TErJKSPI99puRy2uHaTJto4hGMTtZsX5wh/urJVe7PdXdu6wfvcmui+wPI89evOTqesthf8CNDpcEblc2DSpl0VJYhcSwT+mXUXQnSuWJevsbLACG/sCsrQEzicGsjOBdhqSISQ5jraXquhXtKSLaFhglwofg02sBmcDtMt4FGQ8r8eTuuy1FUTCfzTCFJWkR993GAQsvYDp5UK+BJ9oIZc9iBWWKOBRImTQEKmPxg3stDix0QVu1YOD8xSs+fv85VZWZtQ39YSS4HmuhaipyeTuR2DPETCwLcmkJKhFcEk57gOCFc1+YknJSg5ZWfnZOVhUCLhopioKyKqibQi5aFpsME1jJhxFjSqqqYbU84tEbj/nyl9/l7v1H3L17j2ISFvoodL38uigKIjjxI27Y492eFDqS7wi+J/hODv9bfO/k2pDENkGWom7zD6bx/rRWkCLAiOpfGZQOJDVhYydaYfBuosIqscwY8SNfX2z46Nef8POf/Yr33/+Yrg9kXXB1veV6E9AWdp3DlNDYioRl3/VcbDZc7Q58/uwFF9c3XF9fc3l1xdj3lLYgp8RmsyUBP/77H/PkyRMuXl2w3+/JOdNUJYtZw9MnTymnHHHvPa7vZGfWNNRVBTERkT0rMbHvt+x3exl3xsj85IR/++/+Lf/6D/41P/3ZT/njP/kTttstd+7d5eTkXd5+602SC/zkhz/kyUcfUmMpqxodJGLaDwPRD8yOTpm1NSklmtmMWd2SQuDi1RU5C9HMjfJ9LRYrTu/cQevMod+hTUYR8OOBy6uespCKX5Ol+JlHyqph2x8oipKTO2sJ5MmZpqlkn+wOVIWmqQ2LVcO//IN/wT/53e/xy5/9mF/97MfCfAiOPo5cbm4ICorakEzAp4RPkmfgvIOkOAyRYchkK3jnlEQQFnNAewk6yQSUNWDBu0jvHS6DKRuUgRhHQo6SeG0kYnu9XAhQrCgZXOLyumN3LSK7lYXTo5qj9Ql3Tu9S6sTYdROAyzIMnovNgbN9pE9QFGCtCLi0UTg/TqAxMIWl0oaqbCTxNHiKKMmdpTIQNc4lsoNGKepZyXxRU1tFZaCwFqJnt9kQnGO33dHtemky7Bfplc459sOBuqqxZUGd/7+s/Vezbdl5ngk+w06zzHbHpTdImAQJgjJkqVRS9E1HR//Gvuj/0Sp1RUssGokSRVLwSCSQ5vht1l5mmmH74pvnsFVXqGhkBCKAzIOTZ6815xifed/nNViVUV529U5rvM10y+W/P91LToIzGKVp+hbrDa53nD/YstmuhZyYR0qRi/jRxRlnT97hweaM9x8+4fU3z7gfTmzXZ4ScUTFz/OYpx5rwKfDpxUO8kd1L5z3JObw1XHQNIQTBCJMxOjNMEto2nmaGMUC1TKOAsbpuzXq15nh3AqpAlbwmD4UcxKEcShVstPIY68jZAplxnjhNldlVqrdolTBKoYoX0XctWKvkIlzsxN4b8dtXJeJtpd4yx4wMTzEawVAXsbVmraTCzGU54zKS38dbR1kuS4NvkGAurcXtZS1VL1OGpSHLtTKFsEw6l9A1Dd5JEybTmSpR5aFy9ainNvDs9Su+nybWV+c8fO89LkvhB/0ZqVjGGU5D5PZuz/G45+Wr5zz99ltePn/N/e2e6TQJon0S0fUwBFknO8mOCXPAWui69g9bANxc3y7AF7n4+5WSzrCKtSssu1+lFAoJ38kxSlgKFWc6FCxo2UyzQFniJCuD8TjKSzKPDMeTIDRLJaaAfjNhrlXihbVUazEXmq5l27akUiQUKEsnnXMkKyHJlZgZTwPVNoJULJJO+CY7IAwTq9WK6XRL13VLoaFIAWqqTKeJaa6YLlK8x5eM367JNaOcWBcNmjHO0iUoR9u2GGM4LZdM08n/dl7GuCGI7U55ICuyEiKewGpkcuBNQ9etefzoHT78+DM+/uRTHj9+TyI4Y1l2WojKG5l65JhQTi++frnsUxwhj5Q4keaBOB+pObBgsSSx1wqTQQEpJ4qSDAPBWcv3TpUuyhq7TAcKFU2pkmpltIBLVEn/lPIXM4e7Pb/9zVf85Ce/4He/+ZYXL284DYFUNcM4iOWss9wfEkXBut9SgVevXjOEwO5wZE6Z3f09N7d3UowsF3dgEhxrTCirefXiBc+fPhUGhXfUmtl0LTevbyhpFk9uSmgl3YKm0izBGbbxlDDTWIsyhtPhSMmRzUb27f/6f/7X/PhP/pi//7v/wr//X/8dOUU+/uAdrFa8/+QRZ33L3ekaR+Zi3WFKRMVCNXBx7uk7y+XFGU+ePBLSoTF8/OmnvPfBh7x88Zrf/e4rvOtoXM9hfyAGEdumEiSaqgpIazzeo2xZVMiWaZ4JIfPy+pYvv37O9e0R127QWnM8Hpc1m2HVNHhVCDrinaZtHKvVivOLCxFt1sr7776PKoHbu9fc3+948eKF+MedpekSru3Q1jONI+M4ikBRG5KWWGtSxHtHTLJac11LNoohRmZliDoyzZFcMt2qXd5nqNWhTKUaKSDnMEPXoqoB65inieE0E0fYdnDZeT64uuD9y3Naazkd7olJYZs1xzlyGEd2x8zpBDRyoFclUaqtlRRDpaFrNG3vcb7BG0MugXme6Bq/YJo9VVV0TaQKzmlyBZ0D8xA4YNisPW0nqvjb21umMYLKeK8w3tI6TaoFTcbVSp0CMStUtXQLPVRXsLZgTV3eTdn5No1n1a9RiGvq7GzDxdmGddtgcmY47BlvbimHI13OfPzoCR89eoLLUPYHXv7y1xxuD1xlOL7a0caKq4q2seAtrQJi5vzJY1pnuX/1SqZ3U+Rwv+d+fxCHxpC5eLDCdw3TMZECOOsJ48zuLhPmE/d3A2EurNct45AJcyYlRYyarlujlBW/f0ZsetWQMTK1rTCcMoQRoy2Vyn6/J87Qrx2rdUfOWc75xX8vbi94Y0vTy4TMKGkstYIaIlPM/4TF9p5aYI6ZlETo5xtJ2ENJoWwQWqyuUFPBOoc3lqLETbBc/5SaMFr0WlYjZ3iBagrFZAKJFArKQt/Dj/7lD/nODz9l1DPf/aPPaTY9/nwLUaHdGrJh27ZcXHU8fpzJJZDKzDgOEjB2t+f1y9dcv7zm7vqW3/72t9xevyIEaebilKjFLJPZ3+9q//1RwHczqhzo1xtqrQzDnq7rcbZhGo8oZWmahpoqp+mIsY7GOYqC0zhzOE1YLcIU5yzzMHAIQUJjSuLddx6z293w7KtvePXsOU4rLs+2jMPAqm05venmfEffdnT9Gts4Rmdp12uxY6WI0orj6QTA5cMHXN/doI3DKkMYZuYxoJA441IVwzRRUyLHiGsV4zTS9w6jLcYaplNCo+n6Qh2OuNKRi7zg3cUZ+2HiNIzMpaKVY92v3tpxYi2st5tlPFSWqYOhbx2qMeQ0sl71ZCWiF+Ut7WZNqmBsw9nZFe9/8BGffue7PH7nA/rVFmVakjaoRgoFqqj1oaBVpqrANM5vd/txHojjgRxO1DhCmmi0xrmGlCNzjG8v70Ig14Rt+sXiV99axoxdLImlQI0LelnhGgdZEUuUl6kG1tZATlxf33H96p5vvn7Oz376Bc+e3zFOleEQ2O0jU1yeQA1Tlj3w1YMrzi8v2Gw27PZHbu/uOQ4TaMUUIrYq+XdrA7GQqjhHSsoiDEUtCX0JVSu+cRz391irGI4njFYYBRoZGWqryZzIrYNGkubu7vccjkdySjjnee/dR/zJj37Eh+895C//P/+eX/zsZ1hteOfhFTVOaFX44h/+G/N4YhpH0jyhygw10TaKzq95sO159PASVOLZs2dcXD3gf/5X/4qLdz4gV3DRsA6Ks80Gbyzt7p772ztyiHKYURmnxGG/YzgdqCqz2ax4edhxfzfz7MUtt/s901yJCaoWtG2KCaqAbUpVaFNp2xZVJbBkf3/kP/xv/4Ff/eQBjYK1F0W8TlWCY6aJMR6pWvHwnXPikNjt7zlbnZPQTMAUJFCpGnkepymIrdU5piEQFIylcMozAYXvV1xeduKpthZtLDEHDsOJcZxICvAtql3TrzfM+xOH40iaoddwjuHzh1d8sm3Ylpm8j0zjBLYj5Myr/cjzm8SYJIBIYslFY2CcFLiuBWdhvXZsVx3WissoKU3TbTiMR5q2xSz8iq5xhDoTcmRMhThqSlLEWAnJ0c4OZyrGVuYw4B1cXW4YhoFpuKNf99jWUEJkPow0riflRLvRKFPJNeG8BHwVY5hzRvuOqgy5WrwTwfB8Ghm9pskZbS3Pf/FLdi9estaKT955h4/Xl5y+ecWLZ8+ZDyc2w8RHD64IL15xoQ3GFOwS9qWVJk6BVd/RGs/pMHAaEtY6pnnm+vrINEUa65iPlV0aubjqULMjTYFMYncT2e+hbRSr9ZYQD2Q881xk+qoMIWbup0lw6hiUdkwhcAoj8xIhogt4GRuSUxANQu8lVC1H2pRYe8cUEmHRbGhniXnZwYOEpamlIYpCTnW9gtYQcsCpjnmKxKngfUMKcic5o/CdJ6aREqF3FoMmB4GyNbohx0LftSQLMc9QxFburaLzllXfY4zmNN4zhQndSmGx3V5w8eic73zvA/7t//Xf8PD9K5KHrC3+7IxhDNjuAVmtoHpKMZSgUVic8Vjf0nWXlLPKo0eZ739fppen44nb62tOpyO7mxuePn3Ks2fPuH71ktvbW06n4x+2ALh+feDm+kjbd2w357R9xzgU2jbRNh1KZWIYsUsARRgT8ykuFr208AEcuVbCJF2+UorWe6rWDMNAjpm+7chz5OnXv+W2X7PuO3YLva9vWvqHj+h8D6cT1y8OHKcJ3TQ0mzW+62n6TqxmMfLsy29IWqFNQKMhS8iJUgajHSEHyZaeZMJwvjGsNj05ia5he77F6gFVCt5KkpNOkUSBOTAfjkwpihIaGUs5b3BWOuRYkqwDnF24CAa3WAJVkelFCDPGW7q+Z8iJ4zCz2p7z4Qcf8+EHn/Lhh59w9fARrl2B9tQFu1xrQdU3KW4ZVTOqJGqKqBSYxyMpDuRpoqSJWgLULJOUlBjnICFNRsnqpAiDO1fk0lkmJFqJnkMvaMmaE6lEnDY4L1OBnBN+2WmqOTLe79hd3/GbL37H7758xrdPr3n1+kBImvu9ZKlLVV0ZYxJ/dtuwvVzz7nvvY1xDKZKMNk2BmDPWN8Q5yJ+JRZK4KIXf5M37xgmGOmnSQuOySsk0IkkypaoVU0X2a7Vh3bSs1yu6zqNqYTjuieNAaw22bei6nquLc1Kc+fu/+698+9XXDIcDDy7OuH8dmKcZpxTH3WuJSa4iKPIanFF0ztBaRd81jKcDx8Md2llWqxVKG1j1gMaeAtsHV6gK8zyjtOLy6pLGWabjid/8+pd8+cVvmOaBru+xTvPyxTe8urlnf4gcT5CKhJPZRpwq8zwTQqJtGmKM5BSgJHSVoJrkDEXB7m5PmWZ6azjrPTXNHA47lK2EIrajYZzZbFqarieWSAV5fo1mPhYZqRfZnYq33gnlrFYJPUkyJVptekzbMKWEXXa5JSdyfLPDFVYG3tL0HXd3d7hYuX19QxmhJsNnnzzhg4fnXPhInPYEhD1xvTvx7P7E7RjJGvHHI91/40Rh77zBGGg7Kw4cpaBGvPF0XnDawzxiSsVUWDctfdthqMzjSI2FMRbmAto7ssooUzFe8g20KWyvJInv6vKccRy5u98RU2I3DIwn8Ak2XcP6ome1WRFrYj/siXFAGcXK97RtQ06REiOlTphOC645ZJrTjJoLx2Hg8OXX1P2Jbrthc0q8+IefM+z2hOORzjhcqTRDQIVA13q8NcjkTt770zSxu5mYhpnTaSTmQtf1GOO4OH9C0zSEaYZ6TQqZPCnSbEiTEP20hq4DbRqUchjXkqplDDMpSTjONGtxOsRKt3KgM+MUZJVqHMYb2pqJc6VojVdQjAXnBQVfgSwCZV2h8R5JpK4YXdGN2HFLXELYtMIumqRpDHTegiqUHESp31pQhs47TKMoKlLziKbiG2i9lSmxcVgcCoW3hmE+EHIgSU6dhD/VSMwwRY2rivX5iu99+Anvf/SEZu35+NOPOL9a020sFw8b7qeXlKQpvsPPLVlpfEryG1aDUw5lBQuPksAhlFmSbyXJVlvH9uKci6vL5TzPy4Rs4rC75+bmht1u94ctAA4HSR4z9yPDMbParPG+xbeBtk2LtUsSqN5AfLSWcBGM7GtSODJri1psHBXZoazXa4Zx5HQ8ohG1s7eONM+kN8rOaSYVQw3CFXDe03WVOVf2p5HdaUR7h/MtZxcXrPqeUhQxJkKeoIBKMJ9G4hzRaMIoI+FubQlzJGe5mJy3WGtoXMM0zGKDUwZlQC/cemGbG1qvWGlNKILb9E2LVSI823at/HrjUUu0LFRCEra+V4ZutcG1jmosZ95z8egJT977gE8++S7vPXmP7faciiXkKjt1Jb7eHNOiSamoktElUkumTJESR8p8JMeRHCXOV9Vl1wWUKpnSpSIPnFrwymis8xRkRWKURmNQSiiDQk0sNFr+DHUSF4BVsho47A5cP3/O9dPn7G52PH/+mhcvbrm5OXE4FmKEghWNQ6lULO2qR3uHbxucbzgMJw7Hl+RcZffWWOKcUKrS9g3jOL9deeQshaVdQmyaViYvZuFRaMQvbTRAxRkBe4giVclIUMvhQZZQo5wyNWW0c3RNz8XZBZ1vONztePH0GcfdDqsUcZoZQmQ4CgDGqbR4iLWIs7TEopYcyTXx4tt7Hlxu2ax6Uik8+/Yb/st/+mt+FAKPP/6URx+9yyPvpdS633P9m9/y9JtveL0/cHd9xy9/9mtev35NzoWmmzHO8erVDVOoLPHoAlRS4K0nV+nMU67YvIyVS0Ij/mUJbjJC6ayKcZiIJRMGTU0zw3gSqrS1jONMCMJrOFtfctIDaY7L+NPgmxaFlpG5k4yJWuX7U0s66FwyxULTW/AaG0UVHycRl2rMW2tuNYrGtzAGOqX49quv0DNcrBU/eO+SP/n+Z7y7sjxsI8++nTkeRnZD4OXuyMv7RFhcZvK9g/PQdZa2NbTe4pzl4sHFgnGNGKXZrtY0TcNpGJjDhNceZzxdt2az2aBKxdkWquJMaYz14utPMyHP5BqpJVDJPDg/4+J8y7tP3iGlxOuba+7uDzSlZV8PDIcJlQOb7oL1qsUYxbpR3N3dQi30pbCu4to47fcUpbCbzKoqzoulnzO6ZNQ48CAabLNmnQzh+Q3T/kA4jThgs+lpWk/rG5K29H1LSoE5yvrPGoPFMM0zp3hif0hMU+TgRrquZbs9J83yjj15/B6vX98QE4RYGWfBDC/5OgxTpKjAnEGVwhSWlM9SOI2J41Sx3qJ9I9G6FbLSJCUi46ZrGevAXPTCQbHEWgVlXMG0kvdSEe6+QoiWtda3DVZZJqIli0XZOmkSUpQJQS4BCvKsVS0x9UmmQaew2O0bGOKIVganPKkWvFbkWsg6cfloTdt7CRebAzVVLs4u6NuO/eEOmsQ7Hz7g8z/5jGoTWU/YdUuz1Yx5z2G8x6/XON2iSHhnMQYKkg5YlxCtWgsaLcFaJYngUKoCqhIrdS1SNBvvaJqOi0tDfe89pnEJO/tDFgBGt2jXklLmfj8So2G1daScGQfJZG6bliFPhDBLQlXTYuyIspq4wFHMEqCiq6jMx3kW20YJjIcDp9sdlMp777xLGWeG05H7ux01FXQLu5sbdFGcX16xWq3Z7U8c9yeq8+iiCSlwGl7JS6sVGM04TWJvi4lwmiVsqCoJzijgtw0X5+cSiUklholhGBnqSHwzgm0MVruF5SxRl65W+qbBtj2z+v9RnsiWWlT4KUgmewWsHI6FTFVid2q1IWNxvufdDz/i+z/8Y5689wFn5w9ofU+tijkkalU4b1FVU1PGoNC1iv2qJIiRHEfCNBDGAyUN5DyQQhSRn/go36YUWt+/3amVIlgYY51gWQsY2TqLH6dk+SxLJcUqgTbTiTQHQpwYTgdu72549vQpN6+umU+R61e33N7esz8K6QttKVpREBhSRuFXK/rtdkE2Jw7DiWEc2R0O4sm1RrQZ88wc5CV2rnlLd8z5DRTFvXWBlCKxtVaJfbGWheddlp+9VmG5W9nbUSphGEkjtI3HNxLbOU8zwThUreyubzjc75jHEV0qzhlsBQc4hQRL1YLRBY/Fq4pl+fs5oWrCKYjTQOtXNMZwnAJfffEF4zjx8Kvf8f4nn7I5P6dfr6kJXj1/yn//+7/n5bNX3N7ccjqOWNtQq+XmdqBQCUlTVMW1Qj+bQyImJAwHIVU6p4hFvn+tjOw6F055qSI2zVUitscYSCHijOzKp9OEbSwZ8UJ717PZnEHR3L66JiUJ4/Le45yTcepSAKRasDljSuR0OFEtXD2+4Oqdx+yngfE+cBoGpjGhiqZrWqy1tFqEo51rCbt7bl68JOyka37vA8e/+tM/4sw3fO/TD0in19j9LYfdgRf7A4eQ0Z63wt1+EXE1rWPdNXStXYp7y+psK1ORELEKOi8OAKVYMhMCORfmObAre+Is5FG7FMaNz7iYiHmWiG4lrPeaE3fxDqaMryIELiPYqFnZNTQKPRficGS8s7gyc3l5zqrrMCdLzZl1LqxjwoeEDQkLrG1gbSb8CVQMKDIrpejwWF0xKVOGgUvbErzCW42tGhUzuQZKzkSlqRTCSRIJS6cXEbfGWsf5xnEyWhj6c+budr9oaTxaNWjlOQ4j4zAzhcIwVmGSGKihMKeJKYi9MaMWwqlAepSrVK84pcw0B0Kt5AJTDFTrSWSmUJlrxPgWbb1MYRaQUa7iGlNIgWGoWETjZXKCLM4KZRRJSW6MX5INvc30raFEmGdxWlmjqaowZSkQXQN+pfBNQ64O7zoUDePxQJlGfKP55//sn/Onf/ZjthcSMHc8HLl5fcvdzR3TMPCee0KpM/fzjq9ff833Pv+Ur599SXi94wHn9NuWgpBwp+OeTvWcNRVBqkmHKkLuIvoC5bHaUrPY35XWy/0hMDljDDXLBFZVMFpjl8J0Zf/AGgBrVgumN8vIYQY9/FPqUUWykUsuwjomMc8LgU5lseBojVKK4xIKZK2l7Tyvrl+x7TuIgd1uRxlHts4QKqRhokGjvaU1luk08uz0lFevbzC+ISrFo4fvEJXm5d0t4/3Abren8Q0pJTbbLXOYyTFRcqbMMr7OITLPcHnWobXmk48/4Z13H3Pz6iWvr18SowT4jHPESOuPsYJejCESy4mpVOxmg91usL4hFMlCV0rJzpxIKQFnO9BGOt2mIUaH957GW7Q1PHz4iI+/813e//g7XD58wvrsklINc5LuyfpOcL71jU+/4IxGV7Gv5CDxvTGMTMOBed4TykDOQdjci1qm1iqefQTFa3QlzhMhTsIrgGVaYBcVv1CtrLECviGDSsQxcNoJHW53e8PvvvoN33zzNfe7PTFCLQ27+xPHY2KYJIFLqSqjM2dptmsuN1va9YZcC3eHPfengdN0Al1pe7E/ym654hcBZQiBogp1CXVRRg5r7xzW6IVRIeM0tfhzq1EYBEpjEJW60xpnLFYhKuAKUCghop3HYQVZPczsX99wlyKnw5Gu8TggR8GEDDGyv9/hqDhd0DXjqsLXjEPjtaJ3lsZaLrcrhuM9ZRxxjWPTNJQU2V9fczjc8+WXX+C8xxtPYxtePn/Ft98+Z38vl2QtltOY0KYhFbcoshtO0yCfg5Z40ljBVcBYtENWXWF+q1IOKQvQREv3McWZcR7orEWXggcaq8lZ4ERxzJJ06D0xZqaQ0FagNjEHuu0FKkp8di2FVLI8+9ZjNdRx6Zwen/ODH/8x3WbNL778NcfnJ4YhkGYwFKJK2KoXmlrFxYSeA+xhVeHjdww/+u5HeDXz4x/+gHVr+eXrA9fjwM04coiZ0gghsViPaRrU0hm2jaNvHd4tAjEj7pacoKRCtYbTaWIaBkKchN8eo6zKQiKEzDBOIsTTRvQmqso4WRWcMzhrxOlQC1Yr7m92XL+6o29awS+XglYWHQtNLpQA5XiQMGyrJPClVBpjuHCOtkJSity0EtSEphsjehhgHPHGLrTSQMmBvutYtWu8c9RmhbOa3f5eyIUhL0l1opGa55la5fyIcyTMkZI0xnmsbdC6JS/sicurR3R9x+3NjnEM3N4diTFjnKNoLW4r06BcwzhFDkNiDBXrFb6RGHZlG5TOHGMgzZGYACVTPGUbNucXVOOJZocaA6lCiYkEi51NkOPWenlfS0GpytZbcTEhWp5qELFlVWhnqAZCqqy8xVo50IxSC8ukoD28d37BgyfnrM56tg+vsG2HbdacXb0DxfH066/5i//3/wtrHX/2b/8Ff/6//E8EFh5BTKQg9vDpdMJ7zTTec3f/mquHGz763gfUVWB3uGE/3mO6JRF3OHKYTqA39OsZowNFhQVGZKjqTQbMwnfQijgHQoo477HO8yaV0DiPdeZtUmFOS5jT73uv//4FQM88nSgZnG0oFfb3I3OA9XpNMoUUpiXwoKOkRIoBKBinqLUs8cAahSEjbOs5RUoKhHnELVkCm65nZTThbg8hcbk9W6BDihxlj386BYYQ2D58xIfnD7je73nx9Jrr2x1zyHRdyzTObNYnGacsF7NFkY3GVGicjJdziLy6fs04juxur/GN42x7QWFP3h2ogjiR6qzUZcyUKeOI8o6eLc47bNWcQqBoJesRJBmw7RvhT9dKqoVMRTtD07V88MGH/PDzP+L99z+iXW2IRRFPM8V6qhH4j9KGkgsxzihYmPqBWiKxjJLCFoTuN4UTMZ2AgCaKXxWhXL2JHs5LYeGcxZcCNUu8KBDmmcaIWFFVUBgaY3FKi3XuNPP01Te8ePqMm9evuL274fnzp9zt9pILETV3+yMsU4/Mwls1nsa1svLoe1zTkmphd9hzc3fLaZypupBSpJRCv+olflorxtNA13V47xkGQZxaJcr2rm3xzguqM0r8slHCCNcV7BI4VJTCWbmUjdJY6oLvlHQ3pWTSkaaZEgLNEvixe/2akjM5Rmxq8a0nzRPHaZDpyzyjDbQNWKPwBhwVW6QYaLRj3Qq5srGGVWupxpCBeREuqlyZDkdCrdzFTI6VHIWgGbwIAE9D5LA74loLxjKEGYdhTgatMgYRrzWAaSS2myi791QKBfXW8qmpGK1QxgJpEd4p2mXnOg7iknCuIaSATtC0jv39iRhe0C2o16JlulA1KKvJqQp6O0ZKiowxsB8HXL/m8XsfsD675O605/r2nvtjIgZQRYh2uSZiqGKdCpk6J7zKPOxge6H5sx99xsePH/CdD95js2341c9/zpffPuerV7fsY8JuWnrlwLUo36KspWq5aIwzVA0xJQlfqYo6JU6niThPWApxDszjgLWWbr2i1MowBzCVmCrHIQMKaypQ0bpCFKtx4zNGakisgU1vZQx7mGi9XwpMzbrrIQfSfWBt4MJotkbTzTMuBc5zptOWbc7YFCFm0dpUDSFiS8DGQpozjVU0TmGbhhwNa99KwNFBaHDKyQpUzDgyTSulMA8CKTPaYnBvuQhhypRpZgpRRNPOM4ZEYSAmwzRXDqfAECRrxVVRVCqXyXhy0pymRNYO01TWZ+cYa9gf9rKGrYU5I84lw2Ibh65rOLu4IpRKPyfmdGAaJ8G+ayP2cLPsvrXswlWVQtVpBYrFfQZN3zCmyGGKjCFSDDSd5vzhGaZEuT9SIqdMSTNdZ/jxn37GZ9//kG7bUZ1hrpWzB+/y4Xf/CN+e8fzrb/jq65/y/PlLAjP385ExR9G2oOiajsv3H0HJ3N+95lTgwfuP2J51vNrd0p+dcz8dmOIoRWQF6zUkWS14XbFakbQivQFO1UpBL5Q/KahTmhmGgab0bFyDb1tCiNRclhTaJao+57d2+T9oAYCyKO3QNWNdQy6VEER4ULLsB41VBGdpvEUhHGXIeG0oWcRyKIX1S0eXMjGOdK0oUJtaaZWm73o6DUdtaJ1l2EsEpsWgjcNph3GGogyH+wP/8N/+kbFUSfyKlcZ3UAyqJnIo0iFahVVaXAdJmNvbzZYUZoyq3N7e8fzZc3JOvPPOQ2KV4JyqDLkUYso4I6QzsX0oYqmokFEx4rWojuasqVaLDzMtqEltJXZXif2xW/W8884TvvPhh3z/s8/Yrs/Y73ZMx4Ht+QOafkVQhqREdZ9iXL7YijWKWmdKnsh5ZI4HxnhPjhLoE9RIURNOZbQSnFatchkLAEu8+uSCodA6jddeSrISMSpjc8IVQwVyisxT4BAir1+85sWLF7x88YqXL15wc3PDOA0M47hAoGBOBbTD+R5vDE27oul6qrIY6wk5MaXMcDwwxsAcZ0xreXyxpVt1TONIvxIx583NDeMwoTVst1uccxwOkrBWU8YaQ996nHXMUxDBF1XsQErL7lRpGmMoVYoGr4RQaGulFlENO62W50LWOzFGURlTmcdpKSAV82GkrZneGUwutN5xtbpAk3A64ow4JgBRWaeKq5pGebrFQaGWaUjbd7hcyVFwv6nW5SDTTFOCIqyFWiCkIqJNVRlDJNUM1hPRGN+KAM1pfL+CqoVmpsTzHJZ40zfln9XSOTq/FJdUiZO2Fmc9ZQqMYbnYaqFWTYoahWMKE8fTLevtSp5LKsN+T1WQWdYvSpOKYoxSAFRjOe/OCFnz81/+lmevX/Ds5S3DIL56B+hSiXMEItY5rLeYmGlcpSbND95/wuP1hvcePeCDTz7gJ3/1l3z97BUvDxOHuVJdh/MdYMnGgnMoa0VAVhJzzpIUF2dSmMmlMsyFcQqUFGVVs8SUr6wSVr91xCnR9y2r8x7TjISQMNahjKYqaXB0LcIOCBKV7ZtFsJWl0FZOvnNiRFuHioErozjvYW0dZ43HolAh4rWSkX84oFPGFeiMxdRKTYnWOHSFoAyNtuiq6F1DMQ5rDMfjkbv7e4yzbEvm/ngCrclA27VY44kpoKpaVn8iaKvFkksl5so8i7BNW8Vpmjk+P6HtK7q2kfPOdgs7X1OVpRppyMY4E1PFNCLgjShSrZxilhjrKjx+pcE6TcqVkCqEWcKuxpn9MBGSFNvVKBrrcX2Ldo7DcaCSZf1iNFol1ILx1cikstGZ6qBbr+kvzujPznj0zhM+/fBdEUjnwpdffMHXX37BNE6YJvP43TWPHndUU7g+3HHKkTNzhm0Dal25eLLhX/6bf8Hf//3fccozpzTj1iuc9zjnaRsJkZvHE267olNnTOOe+2HEtpq+6fDdBc63DNPIfNrT92umOTEddtjHWVY4WqOKpqDJxYjTkEyps2jhcpRo5SURFgXOe1IWJL6qoJZ8GqvdWzjcH6wAmKYZa51ge5USIlknXPJ5jmIXy4ppOFFrknGbhhBnnNVv8cDi2RxFyb7sNFIIpGnCWkuIgUNMVCOis9Y3nKYTXhms9mgrQqkojSsxZ3avbinWs15taLszrJVOsXEt4/GIrZlsDKhM1ZV5OJFTZLPqoFSykmxsaw3ONux2e25vd5IY5T1hCoSUsTqhl1Q+ZQVnHEvBrzrazQpcg6GC0bjGU40io7Dtmt5G2vWK9957j4cPH/Dpxx/y8OycNIz83V/9Jb/42S/YrM/54z/+MR9+/F3c9gLd9WijsbWgjcY7S86B03GHsZUSjqT5nhqPAgPJE6hA1bPsvuUmEmpfRhTWSoSIikLNyB5NZVSJbzGX8TQwR/HWj3NgGGZ2uz2//fJrfve7bwgxM4dADIVhhuMI8Q2CWFlWmwu2Z1esN1suHzzEOM+Ll6+4vrtlDIGiQHvDpl9x5s5o+46HDx5w8eCSFCLf/f73AMXf/M3fMAwDn3znM95/912ur6/5x3/8R4Zh4LC7J0f5ziiZHGYM0HsvgjQlfv9UE2lScvArWUFIrDKYKi+A02rpJireeaKCkAJGgV8ATd4qdAFiZnu2wmtFGEdsjnSNw1slz4fSlCpdvClSkDilMLXSek/nPHNJC69iAYhEGE4jh+OANo5hnAmxUKohZAk5mZb1xDBFYoXN2SXzwia31hFrRScZGcq7at9qIhZGo4R1WYszsooLUb5z7zS+6aDKVKLUilKGaYr4RgSFKAsYhjmQj0uHYTXHaSTExBSLaEe8RduGUOrbCOeQLV99e8PL61sO44mUJaioTqBtRZVKDCKfsabQouiodAU++/gRNgSeXJ3z3e9+j69+9hN2+z1jygxRUf0KCoSqCUpRqiFFmS7GnIhRLvlaIiFOQn0sEJIAr3StGA1rr+n7Fts1FGOpuoCJ2K5le3GJdgOn44ixjlASxzFScqXRy2a6KtnVO48z4giAymXfYYAaEuumwenK1aZh04j9eV0VOkMKkdYaSEk0PqXQWUdvDLoInW7lPEOYRMgKDMNACDNKQ9u2jEECeUotzFkRivyMKWewlVXrqHimOUg3qiZQhqoMFcVhiIQs+iQMWNfSbDLTFDjFyjgH1tsWo52k3An3W1YkIWO8p6K5Ox65HQa0McxBfr+iWcioBus9yhQwmULl+vYaEM6LMRrn1CLoi8QQIE10bUPOok9pvayrShCHQNMpNucNOEtvNZ/84Af8yf/0Zzx6/wMePnm8OLsScZ6o/+u/4+sXv2WeIM+V3eEFuZ4BmVr2WKtZbRQ0kVx2ZBv44Z/+kGIV7dkZxTloWnAO2/do6yAGWqtxrSUjiX9aF5RRjEGh9YqUKne3L7l99ZSz7RrQtL5hPr0L2qG8sHOqsqhiMdUua82JeZYmpOt7ur4DpZjngNKOXApUtVz+0mTEnEgl0/g/YAHgraXrOipwPJ2ICx1JqHwZay3D6UBOsyAKs0QIl5wo3hJCYJ4CvmmwzjOESMoiqKJkyjxxqoWVqLpolhFw2B/Eh64kxrdvV/i2Zz9OeAfHOBJjJpVI41p+8IPPubx8yBe/+pKvvvwSgyGFQlo42VoVjFY0vvmnmOBcCXkmackUMFYKE+cdpWrGKYgCvhYaY1ElQ644YxinmTRMxNNIsAG36mm6FipMMePbNRjPg6sHfPDBB3z66ae8+/gh665hGk/817/8C/72r/6GMI6UWPn6Jz/lu9/7nM//2Z9z+e77bLZbGelpIaQZndgUCeI43r0kpxPGJJiP5DRgrcaoQk5poSVqyQhYDhGjK+mt8MnglhFgShNhGlFFcXx94OvfveDm9p4xBPaHkXFK3N8PfPv8Jco0oiWompANU7aMU3rr+ijaESvc7Q/cHk4M88Td/T0YjXUONBhEKe+MJccZaubu5prXr17x8uULYozsdju6vmPTd1ycnRHnmT//F/+S0/HIs6dPoVSOhwPXr17TWINTeil0xGHSWAkwKiFQo3Dw29aj3iR11UrMEVc7TGMxCmxNXKw6Sm2ZpxlbJcSopITVsO09K2/RtYCuOF25WHd0raaWSXDMWUtSZkoQM3kOjCGz6luxVRY4Hg5kLKlOjKEwnTIpavKcqVWS345jYE4SYpKBpEA7jVOaKQ0o62i8FJrWGEnEzPltamdcCIa1VEHILloJb6RAKkW0+40XVfQcAjHLaNNqK2E5CpxtORxGqq6gLNe7gbb3GO+YSuYwyKSsaQ26aWn7DY1xDCFzewjcH3bynpRKKnJh5Ai2KgG8TCMxwfZMs9KGpmbO2obHZ2t0iXz3ow/5zkef8Ld//dd8+eWvKKpymOAwO4LyTDEzxERUikBmyon9MBJyIMZACJLyprUUGU2j8KsOAFOruNONQ/uGpAyxyETjyXvvgpbOuuSKt3b5PItElKtKq2ClNU2j6QysnWPVOMbDHWS4coZWa1brFePdgYu+5UxXNt5Tc8Qujp5pnGlbR2Mtx8OAwXDWN2z6njjNjHOgLmmac0js9kcBpBmLVprTFKhKEhV92zLNmZTF7bFZn5FqZQowRiE3zkHWgdbKh1LRQmqtFbQE68ypSKdeZH0Qi/Dsna0oY0WjkAqxKrK2TCFRdaFoLVvyJV+kAFiF84ambURHEQIWjXqLegdvNNMcwGqMNRzHQK7Qd6CIUDNdq0lhZNs3PHn/ipxnKkXs330D3vPJR+/z/e9/xuU7j8E6ijZUK57QP/qXP+ZuuOav/+KvcGrg9njD/nRDt7IUThz2A199/UsmlXGbK7TqadZr/vTP/xVRKVTT0qy2NH1PLYWwhJApVWncik2taCPvzjRNxJxw3hLGgYcPH+MIvHz2FRcXW2K45e72dzxsHU3bQTWU7NHFL1TCxBQGQpjwTUfjveic8ozScnUbY94W+AUR+Br1Ri75BywArFNCHKqisOytPCTOO5RqcY3F6koIBkgYLTz8WsWuoJVYhJx1aG3xWnauFIXXDt2AWV4I571Yh+ZZUK1ti1WamUBKARM9bduRreNumAgxklJhivf8+te/YdW/5ub1LcMw0hjZ2xulF7GYglpwVuHskg6YoqwmlpcpxYwxUMnM80wMYhE7DoHsEp239E0rXWbOHG5vwRoefvQB3faMkcJpmujaNdVY3nvvfb7/+Q949513efTgitYodq+e8/d/85f8l7/4C46vrzlbrRmHkW+fPuPFr7/gp3/7X3n/o8/49LPPePLkEX0vGdDGg9KZcT6QSqDoQFURpROdU3hlqNpwXKKTS44SrYyS/HpE/GNKoQwyxs1hYjjs2N1dc3+358U3O66vB07DxByl25lDZs4KTMMcK/vTiXHOgnfVmqI9RRlK1pSjAD4kt6GSqrgN1gtRr+tbqoJ+LcyG7dmaP/3xP+eXv/wlty9ecvvyFeMSUXr76hX72zuePHlX1kDa0HUdjbGcX55xtT3janNGCDP3d3vurm+ZpgmjDU3bEsOEM5rG99QYSOOJMge2645N11OSonGa3llqininKFpQ0q5ojESJkRHEqCURxyNeay7WPRfbDV3nqFl4BXkWxXXJGasFCeq9RyMXcQiJEBMxZUKRvegUFdNcmWfZoVclOODy5qU2WrQzSi5sbYzoCGompkxjGwqIQDWnZU1lJJgLWLWtJDMag16OC20UznrMsoOUqaKSaFyjUMagjKFrWnLO0v02hmIcRQXup8B8ivSt5fxRz2p7QdutMb4jFcWrm3tu90fu9wPTLNHgtS6REkWja+Vs05PnGQc8eNiwUrB2hgd9K5MVq/n8ez/kdLznP//1f+Lrl085zgOm7Xhxc2IoK8YSGeaZ4zQzpkIAkoYpJqFjimSHxolv21gpUpLSi41WLpu3F1oRxoTv1ijjMNrgOkcOiSEcyfOMx+DF5EkbM6tS2XrP1mnaWmlK5uF6TWM0F32HLZVeGwaj6FPirHE0S4HeNw7fduS+xRlNLZlmI6unMAzsZ1F4p1QkmjgvuHElYTZ5mYRq47DGEvOISgpVNSkqwpyY54GQCsY5DscJYzy2l5C24xwoIWGcJ2tPNqIXSVmmQWNcprvWUowlFpjmQFVJqiklWOi5FoYpYlr9T5e+rktxqkW81nlJqwuBXOKSvKcIaSaVIneJETKQaxVrC66DzbahFDgdl0avN3zv8w/56P33efHiKS9fvmSKAzXB+cUG6yCMB3K+QBtF1UqQvU5z8c4j/uTP/hnDdMMvf/YTTmFgf9yBaaBGUhx59vR33IeRRx9+j0ePvyPCbuvp+zV+vcI0DTJMVUvC7EwIE1YjNvClMQ7pDvKCwdYWoxyrTcfVgy392mF9YBhfMI5bVNOBrhjlUMot73NCgazF/gdVvxRvAPwPer/6Nr/l//AP/v8vAFZdxziPqCw+Y5QiLjYsbSQspm0c3vG2ACg5EsJEBUzTQKOxxqO0wWlPzAvjPyfpNqLBV0G8OgVBK3kosvg1ZZxdGaeRbALDMooupaK9pVTFq5evUOqGEhfRYCqyFzYSCuSMFmgOosx9I5aQjHf5728OqzeWn751MmVYHnRvxdGglUwSwjhyuL2j32xxbUe/6ejXW1Sz4YOPP+HHP/4xDx88xGpN5zz3z7/lv/3lX/FX/9u/5/qbr1lbSwo7CAGfAvNx4OsXr7n/7dfc/PznXFyesV73rNYt3coLY5tIs3IUncgkuo1nc7bCrTt8v6bNUJRcIvbN/j8X0jiyv7nh/vaWFCaMghwCMUyEeWR/d+TmJrA/BPb3J6aYCVUxhsxpzoyxkKtmylBdQ78+w3jPHCM5ZVZ9z7tPHoOC0zAwTCMpRZTRbM63bDYrrNGyT97tMEYzD3t+UjVffPFrwkkOPnJm3XfYCoRImWacM+x3t0wHKdT2N9eEOeCdY7Nac75e0SpNCIEYAvM8kIN836SIsYocM8oqHl+ecXV2wWl/T5xHVJpxiLgo10KuhVQCjiTrKyMdStdYDBlVC9vVlkdX5xijGIY9OWlqkcN64ZstCGWBEoUwE2J8e/EPKTOExJws46yYYiaXKoExtYoKWmuavoeFDjeXZUSrhf8ghsqlUFisniDaBmst/o1Nz2gZRRdx7ohtSPoEUe9XcpEUSqUkwdIYEQ6ilExurGUKI8e54tYNm/Oedx8/4tE772Bdy+39kfvjyO3uwPPXd9zc7hkG4WuUwpK9rvHG0XiDrYrGe1rDMmmJnK8uOO8adIIfff59/u2//Tf8x//4H/jlb7+gup6X1/fcPB8ZIkxlGXXnLCuBAGE51ZRbcjW07IeLUrLvTkAogvTNgVg1TfXSi2RpVKw1dBimcKDkhC0FnQUZXqMwJFSGtkJHZesMj0zHZWNpTOVs1aJrwlnFxntsStQpsDaax1cX9N7L+xYCjXY4bfFth7Wa/f0990OAKvkqcZ4Wx0Iil0hZRJNVKTJZfPJKCgBjLSEoYkpoq5hnSLES0kgIGdu1RGXkXc3hbZeYMuQYaLqO6hxTiEwpcpojQ6gYC30rmRsxFeYQ38JwJKd+SXRUC4jKyXRkSYnDOov1btGwTOScwAgPhRzQHsgG1yqqX9ZlK4NJlY0zfPzxh9QCX331NS+eT1itOHtyxqOPHzObwKgi98cDxcJ+PPCzX/yEKY38qEaunjxBrVdSWBuD9ppPvvspMf8Z0/yKTs9UI+uUOc3knBjnE/PtDf3VgQcKXN+D6rDtiqZbgTWkFKgloVTGKDlTrFLCerGGojTdaou2wuZXRXIbrNlg9BXKTFQV2Z9e05620K7wjcW5Dm0cdQkXQhUa5+X9Q/JYtBYxxZu4H/WG8KKWIuD3vdT/zxQAtSas0WAkEpWqqDUuo2WxV9TFYqa0xtolMakmYpWDxWiHURaFwXm1HAyVWEa80VAytoo90CrIztGte3QoDIeTkN2cYQpLtGOV6l1rTSqS823egB4c5JCIYcYZQ9USxqGM/NlqzcQws+5arDGoKkmCMgBVkCt12Qk3riHawDxNgpBdhF4yClS0ViAVd69e0qw7Pv7Ox1y++x6PPviUq0fvcHl5hTYWCxxeX/P3f/2f+dv/8B+5f/acJhVMjoynxbNfFa4qHIV1jXRpwo2GkgaGAwSr0aZSkGo7pJmkIpuLNcdtx2qzpjs/51QUtmlxxtF3Hd4KgCkdjrz68nf87re/fQvREJZ+xBjNOGZevB4YJxiGwJwLWRmmWBhTpmDRvqWxPb4RgV9IYifKVTGnzPXtHbVkjsOJYRyIC6L5/rCXFUGWEKJxGFitVlAz//Bf/kEKsIrk1efKdDgRY8Q4y3WupJyoVBGsGUvJhePhiDWGxjcYpXn04CEfvvuEcTjy6lUgKcl+mOOELhlnJH66d4bOaao3xCKdl9dgVSYhAspq64K3QUbAXrPuHE5rrIK+87StTJVS9ETnMTaJCK+wYIkLU4xYiowEY6RoQ6hy4Q/TgpbNjlj1kukgBUBRBtVobNeCkSz6MiVilokVWgSNpWRKUdJeK2RlZhTeyHfOEm6EetPpAyUhdUqBIlaqNxRDrcUxU7VCGXDaiaCQyjRnjjNcnHecXz7mvU++i2taXry65stvXnC927O7P7E7jISwhK4UUEvIireGvmnoG4fKM9t+ha4z8TjSu8qq95ytWz5992Pef+cxt/c7xnlmzopdKHz1OvHtHeCgaMmGR/J6iFZoiFLsa4xzAlhLiaoW4VsuKCWJomGaIatFxS+XrF0KpnlOIoyNEzZHfAWTwRUwSayWF61Y9rZWc07lSis2XYNKidWmpe87EdRai3Ee03ZcbLcUVQlK7GwlRYZ5IDctTdsQ5kiKGescpcC4+L0F+YVEnGmxidU36OtaqRkUlTFCLhFlRDxaCoxTZZzA6YzqPLtpZhplyumdBaSZc5sG2zSkcmSMibHAXBHHjdbMixYqvbnslfw7s1IUU+k3Ft962flX+dJTKRQl2SJo8biDWCdNMVStaDrD+dUZ3brn/njP3eGEthVvPI8eX/GjP/0erWs4u/Kon37BcIrUvuCvej5Yf8LDT9/j2fPnPHv2jOPxyOkw8LOfnRjGA599/gMefvIJ/vycWoXU6jvP+cUZn33vu/gysOotx/trhmGSP4/rMd0abzsR1XUdzm9xTSeFV5gpJWBURtdEySMljiSQdFvboI1ls97im0iYLc5U5iGTasB1MzEWQp6Zw0w7nLD9HuwZ1k9QB0qVrAOjF7iWMfKsL2K/qpAvAVhsJm8vfgHt/YHTAE/HI75pcNaJTWEZq7PsehrXEBcbELmijAgFG+eXxkQ6clXfDDAUBk1Rhbbt8VaTFegSAIFVGm+wuqEUifsNYQkXylnCapQk0FVEpGiaitEe7xpKyuR5lnNSSzLhHGaKUazWLVbL0S5dvIeSqVUuf2fcW/wkqgjFbwkIUko+/JASfumgGitq6uP+QJ0Dn334ER9+/jlnDx5j2p6aJQTp+vaW//6//yV/+7//R06vr9nahjgFmGdW1hOK4jTMeO9ZbTq2646LtWfVW2pO5CCWLOcUwzQQj7IjwonqOu73jN2O7nzPfhaandGWrmvwxkKpHPYHnn/zlGG3w/mW6uB+P7I/nii1MoXKflSE4gnJMsXImIIodq3HtR2m6ZbdYGY+nRinUfIXqiJMhuP9TsbRMZBLFiGjs0LOKlkY/c6zbnoaI0zutlnjrGUYTrS2IZZAiBGSZHCf0o5hHGm7ltI4lPcy+VmsfOSEtZ6zVcuD8y17ndldK2KcoRS8Aa0qnffolMnjiUmBLom+cWgMloh1iuIk9yBmJwyJLJoK2SEXmsaxajxtayl5ZoqFlCOlSmVelTyTQuMTDzYlEmIQWIwVe2QskKomlipgFCV0xlQFzqOswSzY00qhLh7murzsSmnZ4SoR0oEI2qxWWKPQSoBU8zySleh4Gi9jbbFDiRiRKsWuXkAqaslzz7VinYw7Sy6kAqkqQoHjnLg5zqxe33M4PuObp895dXPHnArjnBimQs7y5zTI+L21hlXj6RsjqGTfSgETE85UrIZ177m63PLZdz5if7vjV7/6JbcnIf399JtrXp8g94pTrGjRCS8fBkQNaTkAS65UnZdgGDkeNVrU0lU47yUicCtVxLKaIFEEmZwK69ZiMZgc2WjoHdgCjVNsnOFB33HZtLQ543NgXSPn1qOt5b133qG/POP08gUmZWyBcH9kuL9nzIGqEXtpkUL4OAy0bUuMiabvZaUZ5L3rrCjOS4FpjsQkvIUi7aCEMVVFnBNzhTkXasmkXKEaxqoYMphYiXUmFChOk5Ek0VoqFdhNM4TEYRgZo6B6I4hIcxzFAo1COUm8c84KlbMUSi34rgEtYU6p5rcBTEUVAQNZ8ayXCm3rafsG11iazvPuh+/y4MkVQxx48fqFIJE3Pf1mxdlFy7ZfodpPoSv8+je/ZdATsS2cP37MarPl/fkzvv3qG37185/z4tunDNORr373BXM48cG455M/+iGXTx7TbTrGw47huOfhgwe4PJLHPTlrSjaUqqna0roNm/UlfX+G8R1N12GshFwpUe9Q48gcjoyHO4bTnloq/eqMbnWG9Wva9Ra/TLyNVpLYmDK2QigKpWZKnQnZMsaCjRHXBLSaqVRQsi4Xfs4Svf7mqq/Am5NgGbbIa1CWX/EHLgCMUjhjsMYQktDWtNLiBy55obIpvGsEsqCEgpdzwTsvh0wCXQ2qasi8JbP1bYdWmeI9Ki2521p81RRNLpl+1WNtYk6JrCRWeJ4k/7iUIiK5WohJVgKmGrqupSQLNVNifJtZXxfymW6at0jFqqSjf3uaoKRzycvPVxI5S6dEFcCO7Vv6ppGQlZI5jBOn+3vSOKGBmxfPwXrub+549vW3fPXFF/zk7/6O6eaady7OaYyFpiPV5QvVFdVpfCsH4xhPvLoJ+L3Foqg1LfJpKCVQVEaZgmmlQPCdh5RJMbM7jULkihHv/GIzqUxz4HgcoCpiigwlczgFDqcsF1E2BNVxPxXGWQ79kKV618oRY2HM09v9fnnTmS8FVIxZIjeXblJpOSiarlkwvaJFcNYuws5ISnBxdcH97paVazBL/LDzDY13zNNMzZnGGrzRGBQppCWDwNK1Dd45tqsNhsqLZ99yv7tjHk9QMoZK0zXYYth0LaRIYy1WyXPjtIaacXrhgC853yEmeY5zJll5PmqJaCzOaWrNHA73spLKipBlPBpSoiax+2WVmJdxvVLShedcpXjXTgRQJRNSIqNl/VDEnyiWM0OqhVqEq+6aBlXsEoBm3l4COWdBRRv5bJ2Sy02it8uSjiY6AKP0Emuq3sxxqaosxXIVEhkVjWKKE84J0hqkw54ipNPMrO+5ux8YxpnjMDHGSEh1KYiWcwMZC3ur6Zxh1WpaB7pmGuvkm1aKpnWc9Q0fvP+ITsHLl8/Yvbrlfn9iNyWev9qxnzLFa6p3ZBNRXotfvFSqVmDlnU2piKVSy9jhjXOnLsE+GPlu7PIZ6GUqKdGhAlMpqlJ0gZzwFbbecNUZVlqxco7zruPcNayUxoUZHSqtV/QGsi6EcKIcK4fTnhbDdDwRdgeapuEYRmlcShHSnVJC38sZUSAohmEmxCwXgG3IVTGGQMiVeSEUhiLNibKGORfGkMCKiLHqyrSwR2KpTApMVQxDkJWsEXgRKFKRqcPhbr/k3CmyhmI02mu0VRQNrrGSCaKEDPmG+KiK2PNSiUvFV2mco+2sNE1akavmNEemMWKd5my9pdu0WKfZXm7wa8v6que829BcWExjePzOI4oq3F5fM6TE+cOeH7SfEWwEbzipQOuhXzc8evcxV+8+YXt5xm9+/gtefPsN+5sbnj/7hjGe8J3m/GKFMitOhzvmcaD1DYebO9JpomaDs92y/nWs1w+4uHxCvz5H2Z5MJcdJbMMWwmlkd/OM4/0rxsMdKU5obRiGI/b+Htdsefz+JzT9JcpqWttQi/w7Sh6wwwXYTDufaFZrUD2haHwqGLU0Ewtqu1QpwlhyMqoI/9+u+d9c/roKD6FS3q4C/2AFwHZ7tjC+FdYAC9ve1kLKipwjWisa5zC6kqNY0ZwWrr4ASUTgoXIlzok4CfQlTzO1BIwpqBzIYaC3ir5x2JQxFLmArKH1Hp0L4Thgs8WlDKP8vjmXJY5YfnjnG7TThGlCGUXbelHxLwpt64QLIHaojDUWKqRcxEtuBbUYc1yEXYKvVKViEd60cQ5ipm9aHljLfDzyX//mb/j66becQiTkwu3rG14+fc7hdkceR1ZaMe73Em9c6lse9zxFbNMQU+YQhORnFSJi0wZVCyXK5dI0IszsekeeC1OOWL/FKiMUrePAcByYx0m8o0qjlSGjmGfZ65/CkdOcmYsmVs2UKnPRnFLm7jgLsMhaYkkLOVD+nCklzGIzy0kIi0YpjDWLY0MeXG1k5GecpW0bSYjTZvHeG+ZhxFuHa+W/t3ahI6JQJWGdlYCiaaQgrgtdCt2Cm81Ji9+1FsI4cEiJ6XDPPI3EMNM1nlXrpchsLCoJBRCtaayh9Y6aI7pKx9R6Q9/JZyWgqoglo72hVMm5p2qaxoKqTPNImgPDMJIx5CL71xhEeKkAowpaQeuUjFu17HazAmUMxhlsTagc3hbSGIVtLL6RvW5GGnWQ/49dOgJ5HtNSLslFaq3BO4umUuYIJdO3jeQivNXAVKoqstJTsu7KKJnT12XOSF2ikyPWSp5ujmVZW0AlcogHWt8yz1HQwRHGSYppaUwVndc0RtFohTcVa7JYJhHOQus9hcDj8yv+/E++x7/4o+/xk7/9z3z79IbGtAwx8ptvbnh+M6NWloxBNyu0nai6YByoKntm74WQNg4TKSThTykl9JkinW6pogPQblmfJFkVmlLl2UBJsxLTQvEsPNh0fHC54lHv2XrNyhl6s0C0hglNpGm0BIalSRT71wV7aLi+vuGsXzPsD5Rx5tw3bLZnTGHifrfDWCcTSxJ5GV/EkBinTEVjteM0J8YpMEwBnJULPWbh7lsJyJlL4RQhxSxhMlpxzJmYlzWBUTTWMqdMjAWdEk0VnUjRmqgrMYvd2Hi73DUV4yzG2aVgMrJO4o2mIhNzpFIwBmxj6fuGrves1h1d7ylIyNgUM3m35zhJdPWUJnSqlJjILqK6gr1TrOqKyCyFZBlxrafYzBjEiXX+aMun5Tvcj4HiNNFUamMp3mBsw4ff/YTt2Zqvf73l1z/7KbevXnLaXfOzv/1PtLryw/bPUdMJ4kSYE3EOpJgpVVNUg7aa88snfPjR97h8/BHGdmAtOWUgycrmdMft66fcvX5KGHbEecAYzWZ7Qde1VCXU0pzkO6zV4doNipauvQQC7nSL8XCpM0UXQspUHDEpKTxLxlp5B3MRuI9anCd1qQD0MvR/27IuBNR/eof/gAWAwuCdF98psi/WtuCMIuVKSuXtiIhS0LWwsh5FFUHWOEuACIqcIcdCnmSvPlW5zKwRRWVOM0HDaA2+wlnTcJqCWPOMxiyjf+ssTakYHclzQvsqSl8jI5CUBgGNIF7n1brFKc04jkvM6hJGUUUYlVIUj62SF6iWIojT5YC1RqOVQFLklLPkIuAQqzTbTmAPX/73f+RX//iPTKUIMSpVUhAQhVdCgdudRvGgI5dhyVK05JQJOTJMgsF1GqqpoAqmFCzQaLEbtZ0EfOAkR/2s71h1jjkWetuSVGXKiTECxlCNZUqF0wxTLhznxBBlh5dR8tLlRFIa1cg0oQBKaxnzhZk4z1hrsNS3HaatCu+8FBryyGOtpI0pbcV7/uYQMZacIkYrcppp+5aSKuNwYtOvsIuljSLQi0ghO71EpYqzoDfgGysOkyrI31gz82nPmBJ6SZlct15wrSmiY8ACNUwYVTFVU1NAUeSyUtB2DrekI5aSSaZgvHSwpco1K5YfuRhzqQKJQi2Xf2EYI/OYlgsXMKCtlnVM6yUXIifZ2esiu3FdaBoDcQloWcKRtLXk5dka50AMScaJVp7qFAMhzDhv3o5xVVU0pkVTyaaA8jgtinWrxAZaS0apBEjBXJRoYlRlmdwoKdy1FPkVRapQjWUMmZAhBYghsdlaWXOkTMkS62qN/OzWabrWYJRw29vGCqNeCRtBUeWfKfjx59/n//J//7/R7G8ZxoFSKlOJ/PrlLV/vBkajqNbR+obsPPM0kmqkbTW+behWHV3XkWvheDTEKWC1hVwIp4kyC4PEoNHegM7UVCCDz2BSosHQtRprJOZ11RrOO88nTy744GLDmdesdMGnjC+FPEwcDnvyGFB9i9UtJWWcdTBWxtMJPVWM13S6YSQxDTPeOYhQohJxcU7EJCEvaEsomeQbcob9GElFADmpSHEScmGO8r7qDJ11ZKM4xZFUoW0cFcOQKzHLRV6XSU9WepkOyLSuWRDnWItKURwnrSRjlpxIRMwyMc1ZVqQKiGES+l7nWLxEbB+seff9J1QivrP0m5ZpHhmmETdXzv2abAr39ydCnjFzJuSZYgJ+pdG3MOWBYgpYzcvXr7GNJ4ZZeP+mYHXP+YMz3FQWJoxcdalkchSy1OrhmvfthyQ/Ef/xxPzyjrvf3fGzklh5RbNuqNOelCPKFIpRFN1wGjPd9ooPP/sx73z4OU3/WKYyVbDuNQ0cdi959fRL7l4/J6dpEY22nF084sHj99meP+b1zZ7j7kApFqowYyoW47byctRMpy9QtmCbSq4TLo7M88w0R6iFxvZYJ1qKnERP4axQTAtv1oAL6bHKuy8T7rIUA7/fvf77kwCrWbrAiF9ADjFPKK2wWi6oWpcXLC+HCIp5GIjDgM4Fvxxm2iwPfpyp8yhCO+1JMTKdBkrJYitR0BiNqQZiovWOVisBfCzCMu+dhLPMIlJUqi7TBE3NokBWBawzeAONMZANcwrkEElKLRxviCkCy+RAS254rvLvUVUEf1izFDqaWg1zLBilCDGgU8WUTBhF4ZurFAcs1qKKIpVARaq3WCszQFrCk5wjzUHCHZBgEo3GaiOUMBJeQectjdKsfcv59oxm5YlISl6aRkISJK8yK4zTTDERi2FMlfth5hiqKPuTIeS6NEiiIy9K0XU9GsX9/U6mOM4xzxMkCb3x2mCWstM5j7MSemIXG5NC9uVVWGxysWSEoJYjtSS0MjTeQk3kNLFqDSWeMKrDGBYcccUaMK2j7RqgiqXUVBonhe4UktALDcy5EmrCKI1TBVMyvXX0/UYQrNNEmsPSBUfB+zqJrtWIxiPnhFKCzFU5ompClYLVEm5lfcM0R7FIBsk7L8YRUmUMidMk06jWaaqWFUO76uj7jqaXUbqKM0wzU4ykNBNTRilD0yyTmuU5portsaoKJVFLxFmDtZpcJW/CZi2CxSUfwSyTcK2kQLZKVlwlLmsapDN2Rr6UWiQjoCSx5BrEDuu0RaYAkntQtaZt1mQ0pYq4LBQ4TiIKI+S3WQJey3vrHWgyxij6tuGs77G5YFJGVyVETlXZNI4//eHnnHcdf/dXP6Fpe+7TyE++eMqXzwYmDXVliVqEjzkOdKZi+5Zu7Wn7lqZv5BnRirMzSbj0xjGdJnav75gPk9jlstjSapZxtVWwbeB81bHxHq8ytQQ2Zx19b2g9XPSKxgRa61g5i62CzY3DiRhmtJJCN1dNDAkdC3MaiCHSeIeeCzoKSCrNgdsXN3KIJznM5wxjhlgyRWtSNWAtY4jsTkEaEutQTgutLycBqS12O43YxqYs1rSMZZgDY2SxwWlSLsRphlpxrV9goJW0BH0qrVDei/ulypqgmIo2YgsNOeGVF6hYLcw5stmsuXh4zv60Y3cY+e7jc773o+/w+vYlRSfOr7bc7iLzUdF2Fh8d2Ip2GbNYbSuVxjtyCozjgaxm8BrlHFOMuLal7xugUDXLmsEK/rtWwjRx2u+Xxi2jdaaoGbXVXH7ygPfjh7wOiThlbr9+zn/6d/+eq/cuabYt7aaTQr31kkKI5vFHn/HR939Es3lIyVLB5zgRxwP3r7/m/vobdtffcH/7GusbHr/zERcPP+T8wfusto/Qtmf/zc+53ydy1ktssCFXjVINlVYu72YDzGLhVh7nLSnBeDpRcsZ3rXAG0iz3qpHiTynx+ddl9/9GClAXHY96Iw9A/2ELAOMcWhs5dJyWcb1JKC2Z36XKo2gRfGmMMyFEwjgSppHOvUla8xhluBtHpuGEqpLspEtB5bKkz9WF4pWZlcYkSb3Lfctqu6FmjQ0Z7ztMqjSHETPNUgEtggi9HBZm6WpALIfOGuxqhVWKcRj+B5iRNubtGCWXJMKWVsRmJQnlTWsrlD2lmOPya6x0OdQk0Y2l4q3DLHu7GGW0ppVZfryF2lSLCN1ylRQ0oT/I52glmfCttUT0ZThvaLsWalzGoS3ddkuJA/fHPSlkimo4pcpYFJNuGWrgMAkje0iVuUjQ0hQrMUuXjxHrl9Ia7R11lvhnpRQlCalM9l8av/xaay1OO5QyC35XYbzGarsQ6KocVMv34Z38fW+EA2EahzOStOCVwrdeLJsl0ThHrYnGata+RykwdgHeZFEwi7hdxnK6Kpyq6MZhtUKRyHHCm4ar8w2NVdy+fsUpTdQchUZoJRxGK/N2hJ6TpCumnJjnGVTFOU+/WtG0neCrcyDEwhDiYtUxjFNmDpFcJWveOZl0VK0wrqO6BtN0WO+Is6XGTJhnppSJqYKXJLJaFVMQYp1vG4lyrRK41eoGYywpReaYxDJYM3aJNDbqjS85ifBy8SkLa18SEa2VdDy1RJyGKKS3uhSAbuEWWCVZCBIkBd5bdOtpvQfSYjiozPOAVlVWHVS8hVVjxPqE4HVba9n2Pa11pDChC9QwU1Pg6vIh/+yH38cbxU/+6q+4vbvHdit+9dOv+PrVwH0EOsgKQk6kMWK95cGTK568/xDj1dLhZqwzcuHqrQiUc2GvKhw0U9AiTk5VtB9UdIHzc8eDrue98ytWzjAdDziv8b3Bd4b1ynO57niw7llrRT6dCKOAnQ5jpGhN163AeE5jYDqdljOs0DiDco7xOCwZF1I0kwWFO8dCNRblHKUWQsmEXDmFmVgnhsV661q9TEwUGdEAqMUiTSkcxklQ0gqsVUwxcJoisUDTaJRZJng1473F97JCCzEyx0BaMMjOLslzi+9fG2FugOL29g5tRLeVayED67MVj955iL4tHOcTuQaG+UTRhVwj++M9p/HInCYoGqUcxmn69QLRiWLhbfsWaxUpzZQ5Y5SFElHF0q97Ls/PGE93xJwIQYoTihJbZNXM00mKWm9BJ6bpSC4Tzbrjkx98lyuz5fWvvubb337N8+fXnMZ7Hr/7EJ3O6c62zEqzPrvgvfMHvP/d77A6X1NNoeSRME2EYUcY77h79S2n/TU1F6xtWW8f8uSD73P5+GOU26BMJxPhIvbwfr1Ca0fBATKxFFXMokxVi5A1z5RcoWqMtqgqLWJJIuS0rpEmxRjRIbHo76o8UBUp4OThqguF8vf76/cuAEIItJ1ggOM8UV1drDYWlUV4BoKkxMhDeRoGakp4a1j1DWebLY1vmMfA7joLCWsRQZVUSSGQcxRBg6qoWsklE3PCiLmA1WazeC0PFGWZj5Pw7asiJQlOsFpsfQqDXQQ/ovOSD8Z7L/zmeV6ocYgYaBE6FapYuQCj7TISlQIIFDFGUi6kSTDH2dm3PwdI12asZdWvyLu9CIIqUCXCFqUwWi/KarHwmFSlqKpyWWolO39Y/MC1iC1Ra6pzWCcjxbtJNAFRNQy6Y0qJWC0vjgO3h5n9cWSImSkW5lIlZEgvnT8gfDy5BLUWzvTheHz7vZckWEmrwXuHVpVN38oBZIXmV7IkJFalMBi81sKIMAKKqmrRZ+RM6wwxztRcMTkTxpnGWRoDOc4446k5YxsvUZ7OsOo6ck5L7rdinARwU1QlsCTQKdlha1UXy2NF10COE2k+oYvBW0XyipoU3i57alWhxmXUJpqUQiWljLaW1WrFZrulaXtCzNzf3bLbn5hjpeCYYmIOE6kotHYoW8QxoSvWCIVsSIUwzGRjaIpimCP7MQpgKVaKNrRNLzCalMhVBH/KWOlyQlgw2kboYHNgDnHZopeFqCjai5qFH+5cL5d1ETW2blZ4q8Vr7KW7DykRQqRpEqMXt0PrG1ov30GMUWyYeolAbgzeLsI+oDUw5YRz0Ho5THonZMFlroC1TuyIuZJjpExBiocYudw0fPT4nB9+9hHffPUbXj1/ztXDh/z9T37BL353z6QgOSEg5lIXmlvl7OqMT7/3HR48OiemiWE6EcKI0dA5TbvYiNMQmcOAn8a3KyCnodGGRxcX2Fh4eHbGWdPyzvkVhsJ9W3n4+AFTHnn03iOefPgujYJmHhlv7ri+vWeYMocJjrMIa0vNDHWkzjOkLB7uLO+xK/I5llKk0cgVrUTnM0XJrtdU5qqYs2YqlcM8M5fCECEkcLmgl+mkqlK0U6AYsQJOMcokoBFveFkC2KyRyRDIGsIqhfOajFADtas0TrROxooANY5yhnZ9g/We7fYMo+W5nIYjxi9x6DPkOqNNZbPteRB7Qpr49ulXVJ0JZWYMklSJ1sS5oIolBQlCq1ljyLStY7XuqTpymvfEEHG5oe071quGzbpl1bfk6JkGuZC1lShrBfLOkSg5SDpfCczzKE1Fo7FNy8PPPsX6FfQtr795ippOzLuB/VzoTMfjd57w+OOP8U/epVn3HA+vKbqhYDnsbinjjnnYU4JMdeZUuXzyMR988jkXjz/GdpekYinaQU0Yo2m9ofFmmaA5FA6qrNPUYqFkOX9SyWIBT3mRgKq3zjmlhOZojQWll5TGAnqx/iJMiDd6AFj63T+0BgAKMYgPfrXqqDVyOt1jk8W3DdValLZ4K9nuWius9/i2YeMNK295dHnOarXi2bfPqSlidSVOI66TiM0cg3Q0zuGUp5aJHCtoQ62V4zhzs7vHWc80SbjONEm4hzCvpR4qtpATYhEzBqNFwR3mwAmx2+QsqvUpzJJlbhcmdl1EFEZG/TEV4R5oiQQupRKX8VnN5W28qvPiDUdXPAVXK8aJBaQivx4k8AVdMRWUNljrCTkQUkHrLKjYlLFGVPRVyY661kLWkjPvlYCZQorsqyHNlYTmfjbc3J+4Pe55enPi7hAYZ0lrK0rCk0wF7S1VK1E6kxYfOZQoWogQJtZ9x6prKTktwpJM6z3GiP9dIdoFtXRmuQZZV4ieGhZmQ+OdpJAliYtVGFxOhGnE1MK/+JM/5rPvfIdf/PRnfPPVV5RwIk2RXBqJPXYrVt5SCjjnSCEQi+gwKuBrIdckjaqGrApOKxpnUUVDnjntbxlVpbUWbxTeeyH+lbK8jJVSq6B/rUFpA7rQNi2b8wt80zHMM3e7PbvDwHGMhAQhSwddqiFXg9GOUiIxzGQ03mliKYynAe8dUwWlA6f5xOE4kCiyQuk6bNOLgDAXlLG4xmOcJWah/ZVSKWRSzoQpoLSibRusVvStxluLQTMOA6pkOu9oGsc0BHzbsu5bVn2HcZJVENJMnjKtaehWK7ouMs9BhILaEKbl3csJY6V4clZjdRYtBfJ59+3i79fQeRl3aq3EdGcc1jm8NegkwS0lRDSaB+dbPv/0Mf/sT76PKhMvX77gOIy8/PXv+OlvXnIfIXvIzpCtIWgwpqIstJuGqwfndK0nnyZUSuic8ErRZLl0VQqYYaCbTzzQEb82rH1D7xtWzvPe+RVt1XTOEU5H3ts4rq4ueP5SYmJbZXlw1nHVt9y9es2rp884Xd8w3B0Is+ZwyowzlClhasQrmeJ1zqANpOVc0HMkLSKuWmCeBLutlSVWR1aGkuAwzxxDJGhFQBM0RFuZayWyTEcVwidZJgk5CtxKNRKjrJ1hnqMIphuNKYiAzGjB71IZo6w+NhvP2dmaftXSrzqst9zv9zx79pphiOgw4FrDdtuzXm+pNfHyZaBtBZW+u79nCgd2+9cYW1ltGpSBVOX5jyUKo8WKItRaS4kKpQvOOEoumKTpW4vxwmiAjDYV7xR97zi/WHN+tsZZxarrCaPEuuc0EUoA7bFUUnKYrISSWCK5yJkZQmYshabxrD59n8+uzmnblle/+DVlAY6d3B0fffAJrbY4CnE+cpoioQpCPU57ynjPNBxIKZBLRbs1l48/4eLJd9HNBVmvyFXjtEYx0TYtw7SnhBnttii8lMyyF5VCTiVQiVoCKc7S/Ma02OQFF67QeC9MgbpAleryG5QiK3epIpZB3dvF/+8pAPg/UwA4qzBG2NmGTAgT0/GA9QZVOrQyuMYwnw7sbndYpdmsWqyq9FZBDITxiCqR21cvGU97WmspIUCJaGvpWk9vGrq+J+VIvSscwswcA8YYcsw8ff5iSbSzGNcyhryM1hYwRqliMVxsTNoaNDKyijFR8ygJfYtTQC+qcLR0LdKBlWVEo0llqdaoqFJk94JFO01CAo5KLpSkKDKpl25SFdRhkD2xNrK3qYpqMiw2LOsczkNVmhIiuS4VfCrkUrFa0v+0loTBqiBqxUmBUobgNVM1XN+euDsN3BxO3N4deHmfmGqRDmNZW5RqZM9sGsn8XqrGkgI1CNUqlUROQTQdJYv7oOvJJTEcD1AibdtS07wcaOJ3VzlhVcZphVeVRmu0swu9qkjiXxGNhlUV4zTHMWFU5ZP3nvDu1RnX247Lzz/jV7/8kilFdIk46+idxislfHAlAjZLfiN/walCUosP2Vqq0Rhd6VuD0yJWlJ9HfjajCo1vab0lpkgpUaY8iwdfGyv2O20wzpIynO6P3Nzu2O0PTKEQciXESgiLv9kJIjWNom94A7wKUyCljHMaEzJ1mBfWQiaWQttbutWWrpfLP1UBvQhnSuyCuUgXrZRoOUIIpFzofcvZZk3beLxK2LcxxxJta5bvMISZxhmM6XDeoKySCNGicU7SNZumJ7aZ4/FEzUXY9NNIDqJHcXjRFZAwNdFaaC1UC6teauO+MXRND1UxzWKZFcsnmFJwSuEQnkDfOD559zEPtivef/yA+3uJjP3m+Wt+92JgqDBrqNZTnCMZRYgj1IItipwHKBMWgy1x+U+mKdDEjCuFNBxxc+ChU7gHWy66FRfdmlXTsnYtYXfEpAzDTDzeU04dZttg68xxfyIZ+PIXe377y18yHQZUKBASw+7INMlKYR4TZcp4KubtqF3sdrXCHCtZRWkgjCGlwhArtWiUcUQqKVVCTOynxFAyxRmK1gQUAZgWsa0y4gZSCORIIVNBbeUsSSlK1sJyflRJ0gUN1otddBwEj9ytLFfvXPH40dUyERIkb7vSVBW4vd0LR4GZYbwXO2udsK5gbKbtPVsaSk3M6YjTmqYXdolthD5ZTYdrLBi9uKwMVEuYlsCsXLBRL0K3jG8tuB7XKFzr0E7ijje9p+864jAJ+EZJWuEcEtYXtFWEcBKRtJPMFO8d1uqFja8p3uN8x/nVFSYkxhevuf7NVwxzJkwzSWk+jZGHWmHONtScRQtUPCqNxDCQ0sxpnHDdmkfvfcaj976Hbi6J9OTkF4spOGXYbtfE4bXoTAAZgyyKfZUXi16AEkhlIoWBGAZqlgZJKYNGirY3gt+F8SXTAaUEBV31W2CX/N5v1gCF37cI+L0LgMYrVq0lT4E4jpQw0amlqh8GcimUeZZLdj7RrbcYVUnjgFEeUmB/+5qcM8fdDV5Xuran91aSjRb/ojGOdddSdSM7SCCmvOxSDVOIMrLWGV2WxKvlh39TPRkjQqnOOWytgu5clPylyEhV4AoG3zS8QVaWWsnISKYuRYVeWNc5l0UQYxHiwWLJUHVJz5JozFIljAVtOQ4DuYB1DSDrfa0MWhlQ0mkqhPWclXC1c0lgZCeYiqi6tPiZSEgnOMfM4TRKrG45cD8EXu8OHKbCHArHCDSOmSJjoqQWsaahFIXPCJ97Ib7JsyKfnwQmQS1pESuaZV9aBdtZHaSIska++wXG46wWB8YivjMadIqknFExYGpC0q41p+OJtTdcnm344qf/wKuvvuB/+df/mneePOH/8fz/yREZiW1Wnm3fiqgQKDmiiLLDVSII9DqDU6RSsU6jndgM3+Sld87hjMRRi/Mj410Vq+riffdLxKbgTBWqKkrVTGPgMIgjY7c/chqCCCyLTFQqmpiXyOQkDHWtRSdBhjkkYgRfM/GUWfKKQYudr9qWoj2xKuYoDIFaqviuo1APtdYCv0pJwoVywWrYrHseXF2w7lrG/S0lBNrO0/kth/2eEEYimhAnhgna4PDRYTGgKsYaUNKZOOvQyjIMI+M0M58GhmFYhJ5V1iQlEEcgZbYd9OcttrG0rYBxGt+itGUcZZQ5JQlR0llss9oadMk8vlzz+Xe+w3c+eofrZ7/h7/7Lf6UYx6ube377/MjLu0xpQXc9x5QJc0RZhXGKs7MV59uWdx+cszKZetzhphNdnKhxxqVKaxW9MazXK1ZnW1wu2JhoUJhUUcMJrWeGVzeomIV5UCKvnn3N7u4FSVeK1RIHDsSQ0VlhkqKMifGQGcZIrpaSloyRN84VxMUTZRQpUKcIRhnhJyx5GrlocoqMMTLlSkI6/eqWwqBmEopkxLaonaJaKMbgrJJdcE7kVEkayYSo4vBwvVk0PUuugTGs1htiTJzCblHuW84utmwvt6Q8k/LMPAe0Uzx694yzy56cKsNpYpr3DDd7pnmi31hKjaAjbW9kDZpHnGpYrTdsz9bsxz1N48GIqNrbhqoqc5xwtkdZJU2aAact2hRhUGhxjxlj0RrG4cjtDWxWK6iV3e6e4TTRtq00STGgncMutMakK8Z2GOXwXpqPWiuqcUwGxjLTW8XVB495+OF7XD99TpyOjLvM9c9/i1q3zAY2Tx6i+55cE6GI/XCcRmJW2O6Mqycf8eTD79GuH5FVh1KdnImqUMpMJtG2npgD96c9l6sn4vZRkkZLLVQipUxAIMUjKQ7kNL+99K0xNE7cU28NfVW6fxlQK5myLaFfcnz/H4uA3++v37sA6DsLNWBM5myzxpaWu9sAtdB2HVpbXr2+4bS7J6aEaRxt42nPemwS+8s8iTCwMWC7Rqqsmih5xhtBYa7Pznjw8IFcWEr8WakqTqdRbGgxiVgrZ2qeyEqEZW/+MtrgjBcPeNcQTiexXS2gIpYMAJDuPxfhvkNZiGvIREABVYRS/1/W/utJ1yy97sR+277mM5l5bPlqBw+wAQKjIUjMkDMT1IiKUIQi5mr+O13oVuZmqBgpQhLFGRAE4djobrRFd5c9Lk9mfuY12+ri2ZnF0Y0aEV0RhQ5URZ/O/My7n72etX4rpkKKGW1Fuk9JkKLCXCxYp3HIxFlrkUpHJwUippU4pJRELSgVjOzbahRoUa2Sty+lkqpkuWspD2mA3KJasUi3AcvK6e4ke+RcCQXOSyVWTbUDxWpwjhyl3c37Dt/1YvwJgTDN9N5RjIIkUCNDESOXUaia8KaT2F1YcY3QNjiH0TLlOifrhJRleLNW6p+1gqFzYsakyh6s31BKIqwLcVl4tOmI60yYj2yuNpQwcbh+wU9/+H1KWsXAlxa829J5LXtoaylRGsG0Lu11yRir6KzBFtAW2X1qJa2PtdI5L7f9NTJsdpQUGhmukjNo6+h7jzaOeFpY5khBZMRpXlljbA/vwpogFqk+vg/cpFQJbZ/bjR6sYQmBNQBKSJeCZ5V4qu88vvNgxAF+d5qwi6GzhmURdobvfANbScMitBpVLTeDUgSK5LTQ/nQprGFmHDzb3Y51Wbi9vQXuIVaZmBIhRXF8t2E7RjGtGuOhyus8zRPzfGZdA5138iAyrV8hLZQIuxHefecJm+3AZpT3fV0Tb+8OpHVGU+idFTBRrRgKthS8rvzOb32D/82//G/Ydpb/6fCaz158wd0U+ftP3/DqLpMMzFkzrzN2s6GklaHTPH3ymG9+/TlPrzZ4k3BxgmVlkzMbA7UoPIrLvufJbsejcWQ0mrqshMOR5XjifHtgPU8sGNbj2gxulbCuHI4TfmPYPdqL6rOuON8TlwxJsd4txFNAZ0XJSqRqIysuR0Fl8QUZa+Q711kU8p1NWKaYmJZK1pbTGsjQhkaoTpO1ZCeNd6SsKFqc3z0FZWVtU6mk5jmIObVnh8B+lIPNbovvvMCevJeSM2C735NSYi2Rt7dnllRYQpTPA5lCItUg9dhWYbcWZzsurzYcDmcOh5MYZo1imiIx5baeFCT1sN3z7vvPcN5iB8VxOjFPK93QtZ9TTNAxBRSyZtVKLnRGK6wtpLSyLAu+H+j7QW7chztefPE5p7sTx2NgWeJDKU5JgZI9OUq3gLYybFkyFJGnYpQ22sVmCoXFZcbBc/HuEz78rW+h58Dnn3zOeZn50d/9mB/9/Of8+u//Hr/xe7+LMXLgbvuRJWlM1/HxN36Tx+9+TCk9RXmUcpLHrxJ9LjWBKgzjQFFSt12qnHGowr2NM9eVWieoKymdSXmh5tTKp8SM6bxFWyNXHyWqQMlVPGSAVi1v2w77e8gd/PIRQPgHrQCq5ImVZvSGMk+YMAtUJEe0cwwlMKWFGhbSUbMdn/PocoPNhclUDnewaEhKMc9iZNIKSooo37Hbjlxd7ug7h/WOJ0+uKFpTjedwPHJz/YZlCZSMRLVUJpZEiF+9MLRbExXm80SJCV3lVSlF3oSUMqVKl3wq4jmoyMQusCORXuVDC+dZJG+DavKvfBA34wajIMapteLJi7/dbWXY6Grb1VSsdkL9qvdTnHgbnDOEkFhDoKbS1gcS+TBIYiBn8J0jG8MxLixT4voYWKtEf5YCRXWYrkeZTiI+qhEVveTJY07YKvuiuKzkMFM7maAJgYJI/oMzWC11t9aohzRC1RqvK95bnG6RlFrwWtzmxghWWSmhvIGYhbRSOKOkAApLMR2qZK4eXfDk0QWbviOsE9//7t+wrJGus6SsQckUPS0nUJW0yqe6IFRGrWWYM0a6AbTxNHWsSc8Kbw3WSMe8HzqBEhm5mhlj6TpRZrSWnO55WihYlNGsKTOFKOTJopv0D6V1yuYspVExSmWq8YZUCuscJWrljIBpcmBZCrtdj7GazWZL1XB3PArcyDliTERVJHUAhBjZjD3GCJ9+GCQ+aFAMvW9QkMqrl1+yH0eJOIaV+XTGW3F4L8tCTJVx7MilsKwRvzajphG65vF0Zl1WqZ+1niUEWZwZh+1aiqMWnHPkAq9eXWOAd9655KMP3mF/sYe48sWXnzMvgflwZvADQ2e4eXuLtw5vNGVN6Jz5zd/4Jv/sj/8AqwN/+Zd/yYvrG05B89mrI59fR6pTYDtSyGDk/Rv8wNBXPrja8N6+57LXWKWp5wOj0mw6T4mVzXbDx++9y2gd8XTEFSjTyvH6hnA8U0OiLpFwWgRxmwS/vKwr3WCJpjLPmZ3t6FxHqBO313fMx4AumjRV4qlgKmx7h9eleQ8U1II2sNsO5JTY7EYKwoWYU2Jdg1xiqmZaIlP+quJZG9qzw1C0EuCYEsWOZn5Mqzx/nLfMKYAqhCDG5pQqzsF77zxjv989MPiVsugkNexzmAHYbAfWLAmX19dvsZ1hs3MYI/4B3WKrWoNxFa8FYNMPmtNJhsJxc8G6zsytvjiXSIizFJUNPYf5jpwjw9iDUpzOZ2lj7Me2xhUPVMqJFAoQefRoTzf06LOoMbdvb7DOcHlxQY6JN2/ekJNFa890OoHRdH3PMHQ4Z0UprQmNMANKrZTTCW0c2glttKrIaT6RqmP7wRW//fgfc359YHj6iJ/9+KccTydSqtx8+Zq/nf6CD7/+MRdPn6BUz4ff+BZu94hxe4k2G8ASY0briNUSKbUGMlEUGt9zcXXJ7eGOp+8knEsAxLSIz01FSg1ygY1nKAFFolZhNIhvAkmxaUuIlZRWqMIh0dai9T1o7d7016KA9d4l8CseAJSqaFN5++o14QhPNz0bb8jLgm4mnMeDQ286buLMqDKXveHCK8IsRLVeSCQsWnLI1RtMBrPfPew3a62s88zbm7fElHDeM+4u5AaYEjkmzseFNVRZDYhtXrCWVWBEOWdpfmr98+Z+t58blz3nB9PEPa5W8uoi52ek0yDnTKmKYTOyLoHTHHDOsdlsJeaVxWCjlCE3Jr21llwKYVlFRLjvaFciwYt6UVrxyr2tQ6b4RCFlUTg2/SAUKAraOYrznJaJN8eVKYlcuKbKOYsp0fQeP+6kjILKEs4MZqRznSA7Y5JURcytlEVj2s1FlYhTla65Vy0tttc5+ub8T3GVjH9OYvMrMliJMUw/HPb3h5NzDtNSFbpWiRB6R9WKHFesFl+JtQqNZ54juURu7w7EVLBWcLepZAk/tQxsiIFac9vTK5nAtTSWqRZlGrqOzls66+g7x9h3eG85H09QW0TTiHK0rpF1XUkFhmHDmhHjXYOoxKTIRTj8pvPSf54yMVZKVVhv8cZRFCwhiMlTgS7lYbjc94rddovzDmMMp/OZlJIMgaVKO1rJGK0ZegeqNlZ/wfv2uQ8F7T3jMGKsYZ5mQSR3PU5rUmtBfPP2huPxSIilsdqNeExQTMvKaZ5aGZP8nFZblDLEmFnmIPXXUXb4qha8HTCuo6aEtYqLC82jy0sU8PrlK+bDgVwyzlic9ZxPZ5zr2mCSictCbxT/2R/8Hv/r//q/xJvKX/7Vv+Pzz19wXjVfXp95cTOzKli5r5rVAmSqC1vnuNpYnm8d27ywXr/BdparoWOD5qLzuHFg8B27qlhv7phub1Exk5aV+XgiLwGVK6FBmmKpnFbYP/IUb1iAtcBmP/LhN77FbnvBT3/6M443gdNhJc8ZV8FVRe8cXoMvCa2yDJlaJNu+61i15jTPZG0IBeZcOIXMkpG8f5HGwtiUWil1iXKja0uygqQDaLl+33V0XYd1hmFXwSqm00melzljvMZvevpNx+FwEBe8khzGvCytVr0QM5QiNcDH04R984Z59Ww2AhVTVkZsOVRmjBEFwXewNwOKHUop5nnmeDqiLcxzYp0nXr14wfsfvS8EUG0Ia5C1cJHdfM5SvqYw5JwJIeCcZbvpubq6QttC1yvO0x3X16/ZbDZsxw3H45mXL18y9JcCaXLiX6olE+YzOVqxBuRITJGKwXU92to2mDlsDaDFYR9LBiy2N5gnWx73H+F2G378vb/jcHfi7YtrXr94TQ6VP37nQ67e+yazv8BurlDakFNbN5fCOh2gQM3CH0hpwTowvhBLItbIutyhasJagyZiXQYl3pwlnchJzgljtJwBORFLlgI7lJjds2rnhXk4j0sr8VL/6XX/H3L1/4cOAJvdyNVuSzofOF1/ybkEmGfqOuOcQxEpoaKXib4mRgp6PbPcBkpR6Jb3VzU2idBhVSWkItnueGadF06nE6UUDqcTaIPfbHG9SKHjOBA2G3LM5BKJiebkvr/VKErKrOsqCF0tsAhAqnFVBa2oWhynaC3Of9TDJFWLZF0laiFFLTFIj4DvZFecSmKdVjrvKTExnWbcUthvBrJG8tDOoEplrUWijUq1m7Jpe937VEAk19SaE5X0DwFBFZx1KGMJGm4OR26nmagqfr/jnJKwElSmGk83bOi3OyHVpYTz8vCwWqSwpfUh5BxQJQqXH8lvW6vojCg7ndXS+WA1zljBxVaRNjVSAe60IcWMs4auc9i2p26zmOSIlSgEUgxSJILmxM0qn93MMs/yMxh5TedlIrT9qXaiVqQShdAIrfwly+dca4xrxjfvcM7htKGznnHo6TuPM4L73W1HtpsN5/H4EG2LIUkGfo3EWIXYqBxrWJjWhWkOLCFLSQwiydLKr+TwVHjr6McR3w/MYaXUJElQRfMoRKzp2WwG+s4xDAPzsrDME7pkyVoryd4rjPyetWC0kWG0tfgN4yhlRMiKRQMqZ5xSbIYBauR8VszzwrIemefCZtux3++JJeO7DmUc0xJbmYk0Wm7GgYv9BdZYzueZY50JSW7HNUs9djfuyEVMt/urR5glcDgdWVLB2Q6tLKfzzJoitvN0vooPCCAFnj3a83u/+Wv88z/5Jxid+Q9/8e/55JO/p2B5fVf45OUNd0tG+Y4cI6jK2Guokb23PH9keLbredbBNi/ktPLsYsNHz99hoy15DaQQYFq5vZu4u37Lep4xVVFCZJlmSBmtDfMkEa5qFJfv7Ll6+ph1Xbg53DCvka3v0aZDKcfgtwx2QJdblkne077XAiNzhU5nGTaH/kGWrkYRY2HKmVQqAcUxZu5mCBWUBTNohs40FU0AOyFlQs3UnAG5uIScyLnSdZah37DZbWS9UDK2k+x8WNdWF1wIKXJzd8fpfGCaThhj6LqeFAPznORZWUE7yT2HNfD2OjKdFfvLkd1+wHcK12KcThlK+65pq+itR6sOaqXve7Y7Weud5567wy0vX76QfgOt6H0n680qVM4cC5nQ9tiNGpmi+ADcFmMtY2+oWNbpxHqO7EZD7waOaWI9r5AnwICRGLfS4JVnt9vSjQO5yoUw3rOeK6SY0DrhjUR90c3DZSErI10j2w3P3n3O+x9/jR/8x+/z53/671FK8bMf/oynj9/jD558ne3Xv0FVnhAE3JXSxDyvMkinRFhnlJI1BlYil8fjDSkn3rz+jKvdBeOmF9/HeqSURNVyyTLKoAzC6ahyhsVcWKOEtEOooC3KGJSR8+D/V/YvkmP/Bx/+/6AB4He+/W1GbzB55fuvv+DFl1+yt5on25HLcUOOkdPhyMYqNvstxirW0x0q9Xg/NpdyRSE4W5xUvuSc0c6w3Y4UJdKl1lpqYrVhSYk3b17Lja9C3/WEQXbnqMwaBHOplaWaTEiFXBIpK0JWlBhFEs+yt3K2mSuSSJwxxlZfec+to0EzxHGeUnngBNRaCGtCaykayjHijGK7cZSWqbamyiGte5TWKC1vUqVQiqwdlFECUEriNq1VMvMajc7iJo4lk7MU4igrHP79MJKsIynFq5dvWAoo1zGOO/aXV3TDpvkbMkM3YJ0mxjYph4WSMjVL9KREYUv3ztIbK+Q2LWQ0C3ijZY+raJ3wWt5DK0pGVhVnDZthpNbCNIlJrWphjy+LKB8pyZqH3otLohapYs6V2+NRyjOcJoSFu/OKH3SLk1rQtRUwSTGUcw7VKUotWGdQWkBD1hm6vsMq6SKopbKukUwgx7UdnKopIYXTceI4zQJ0WUMr53GsoXKa5J8tMbZhRFO1EXKbABMectPWWjovxUBKOZQa8BapplaiYnSdQQr7EiWtxGWCFOitxliFUXJzdN4wTaIM6Fqw1tANI5ux5/LyknVdOZ/PzKezpMGyHEBd13E4zBIrTPmeZM1mv2dzccXheED7HoxhmVYoiv3+gs43eqPrWrpMybCbpNvDmo6+7xg2e1IKLOtCiIXzvLKsJ/pt4dGlxxvPMGyI01locykznc+YCr3RPNpv+fbv/g69d/zlX/wVP/vkFwzjyBLhHM/Y7Z7LvSFrhZpmUgoMg8Kj+eaHT/nw6Z6uLHR1YsTQb0be2V9w1W/QKfP2dMfdzV275Rfm00RNGVWk7neepMVOK8UaBcbjes/lsyf4XU86F1zasNeWzW7LMiem4xvW80xvHI93Iz5NqAyDV/SdlBmNztH3jq4fROqeZ0IIHNcF1Vt5HpVMTbTXAobdln63Yc6R6mR/Oy0rp2lmDoE1yWBsVCGWKrHmLMpgad/DJSd8FtCMcRrXWaHorROHdZFIWRKTdK2p+UjA6qY2aLCdoM5zzswLmNNMzlLSMwyO/XbE7XxbWYpqmmnG4CzFTbrrKEUuAM5q1rhyPp4Y9lvGYUM/bAg5E3MhJvGapBxkLWkUnbfY5i/JKYGyrHOUojIUm/ECrTxUy+XlE7RzuK7He0GOWyulV53v2I9btLOc54k1JuYQKHmVBBZSUayqJList/i+RylZHaUlUzvPu0+fUavi9nDk5tVbPvvkU/703/xPnObK7/zTgr+8IqnKFBaq0fLnOINSCWUjxkC2mZCDrGVspXOWMN1wrgth1kzzmXk+o6ycb/24pSKJolws1nu6foOxPSHfU09tK4QyAq1Thv9/f6l/gBLwSw8Aj999lxJWHr37HvvLJ7x6c42yGqcdcZUvX28dg/ekmjidT6xhZrBG0I/W43cbrNVMh4V5CWJeUeJmNMYQY2KJga7rudjt0NaRTjJtaSSq4r1j7HtSlCii0VCNOLLFxCLO3pwzy7KIlNwOd6MUzntMkca1mATOIcVJzW+pmhqQxSWOUlivWddEzmIyKzVyPkfCmtmNHZves6ZATZWhH3BGE6Lsc2vND1E+Z9RD/LACxiiKlUISpSXmZ7K06SknnQH90PP8vffpdjsOS+DTL1/x2ZcvOa+Rqhyu7+iGXiJdJFEbcqAmmXZrjNJfnQJkabezRuMUeGMYOsfo5JAyVTocSgwYr+msuNolwiPlKaiCrfe/j3AfUqpQxHOgjGA8Y1gpSW4QrpW0rOvaMuIy/a4xcJpWjJE/u9Km+5a+0Focz1ornPFtraBIWRCyuUg9dFjldmGKQZX7t1Fim4rSlAqPtZYQEjFkydUWCLEyLytLnLBuQ0y5Fe8YahUoj9ZKCJCKFgWV0hylLMZUeq/Z7jZc1IFp8q0auTAMQ9vTSmHSMq+kZaEzCt845sZIdpwKu3EgRIFheW958vgRjx8/biVEmXXRTKdJDG/eU1Lm7uaWNzdvOUyZodf0wyi/Y4VQKlVZ1iAEwDWKbFiVw3UbjFasaySsC+fzwjIFpiVSSmUYBmw/Yrx0ot8dTrx6fU1Wmt3lJf2wY14CerTYfoBl4u31W9lpK6BqPvrwHf7g298mTDN//u/+PW/evmEYLzicDxzXhBk2PN9fsOTC8XRLqgs5BC56y9fefcw/+8NfZyRyev2CskQ6I5eG+ebAp7czYY5M5zPrtJJDxFZFjZGaCuuyMM+LfDYR9ShEeeLtrcaPllQDRVWGoWPsejrnOd0dyPNKngMmZ7adxe89uiJDkzN4VXHeoL0mqUzImVOYWXImmIobhP/RKc/ltmMLYJ3I+P3Am7sbMJBrwZqC9ZVOaZQTb0CqFW3AOglqRF2YS0QpLWmgksmrqCGqFCk1alyTWsF7xdj3MrgX6RNxXtDNxslzTrfsuNYKqmZdMssSpSAnyvprHHsxBSsJsIzDhnUVD1ZMgZwD/dix3W7xqcc4C1kUU+0s1kj9785bak2cTzfMCLMlRxmuN/3I1cUlMU0cDidOxwXvRi53jxn8FqvvcLaXRszWMNp1PcMw0HUdJVUOh2NbpFaUVpiagYKuQSLh1WOURlehQ9YoLapaK4rX2I3n9e0bLt59wv/2v/vf8+//zZ+yLAvT3Zkf/OVf8clPP+Gbv/Xb7J4+hrHn8fvvcnX5lJDFGOtskRVkDqzhTC6JTsvKs1eaGk+8vTsyzzPaKjZujwbCvDIvM0X12L6jcwOu22JcL70PpcPqrj1nNF9FCVXb9dcHhVv+0s3oDr+sIvBLDwBTyqiU2V1esb245BfLyu0yMxQYjHD/ndFSfJNXQdgaR5wXYsyMuwu22z3OdZRwwzyvDZlr0MYzLyfZVSG7jnmZGQYjsY/afpkqTPa+86whMs8C0AEan1xMdFQB7uRU6LpOOOklg1YP01HO0rw2jl4UAVVQpXBvJSwFlJGO9FIkjuicTGHWWD7+6AN+45vf4qc/+RE/+9HPyKmyGTWaQskV5zTTMrdbosd3VsxLzVsgrCErbm+dSLnwkOlQlUzGbQbe+/gDPvzaN3h1e+Czn3/G56/esOaM81IjXHJlWRaB+TR6W82JsXf0fdfSEhHbkgTaKLzv6Y1mdCKRO6uwFAwCMzLG0FupGA6L+DJ6bzFa8Ds5yT/T1IcvpbWWbIVRXlpjmDZCC/ReSqHCutB3XnwZRhM1UEQKtF3HpsstBqRbll58s/fegntDZW4oYK10K9fJLEtGZ02NAkoxVhj5JcWHPG4pRaJRjbznXNf6GmT6OE0zp3mVUVArMFaUA+Mk402FRPMjgPOa7XbgYr9j3G5INXG81cS4kKN0FEClhBllZPepa2HTCx0PwDuH6zzzKoZaS6XznnEcGPseSmI6Hik5sxtGiImUCt57zuczr1+/5rxEtIbt/gI/jMSbI+cpgJkpQDid6fuelAXpfHc4U4tm7DsUUvmcmymtkbipWJTtqUozB6n5HTZ7qtX4bsBY4ZdX4ObmhtvDHaVmjDJoDc8ebfijP/h9fuOb3+B73/lbPvv0C7TVHNYzn728ptqOaj0xTxxPJ6bpDlhwGt59OvBH3/46v/etd3n7+c+pasX1GlUV5/PC8bAyzYk5VFKs5BhYDidKSBI5RLUVCnLjdYAVaqL2YAdpuIxhomRkV70k6hopJmCLxsbCcjqyHg9Ypdlux9ZHUaRbwUhZUUwrqcJMpnSWru9ZcxQXv/dsBzG/ia8kEdKR3iuhB4ZISjO1NV+CkjXbgxPPoK208UVVMUqeW3FeGss/oKj0zkg0VxeMVRKDs4acC84puk4uWCELaCokeb7d/1WyrHxQijlllvnI+bRIf0Xv2oDUMRNEXeksVI0xwruotWJNxRkpMqox0VnBVitj6FyH0hbygNXSA3PKZ3KWroTNZsMXX7zlfD6Tc22XAA0YUkRSCL2V13QxOOcYx/HB7DrPM6Vktvst43ZgHDpQSMGWMe2gNKiiCKeJmZmh3zBs91K61RnsvkdlR2d7Hj1/zNe++Q0+/dHPOLx6w/ziNfb0luff+gYf/fZvceELNRyZ17Ow+kkopCr8NE2EFHGdh+joxwFtoHeVFLOkMWaDQqNUT8qWftszbi/x/QXojlyc9O7YDqMcDa32lcmvXZwr/0v3/z1lqG0of6m/fvkUwLhD+U7iQLWypEyeJ/bWcfHoCp0SzlhiXDEoeRh5x/F84jRP4pgOGaMln+mcA12be9sxpIyyTmSjWJjnFec6XD/QV1iWVQppchbUYtfRdYFYIrFIc18pEo1BVv0oIKYWG2yvTGosZWvl9qYeWPsGoyVik7VM9hL1AtXk8ZwqKQUu9zv+1b/6V/zub/02/9f/8/+JLz/5FK00o7fCma8F14+M/SDUPyM3adtMcSAKhaKIJyDlFteqsjLQwrwwzqGs5eX1W777wx/zdz/9VG4S444SMzVEYgyC6TSKHAMlBmqBPFhi6NvBJyY8qGil8dYJlKfJ2NZqTBXcb2cNoxKAS86JUqUJzBlLKYllmVBF2PRBfXUIW23Ay6QekVijAjEIWtMgGR390KO1HKDGyc5Ra4VrPQEpBCmkETPBV+QsLesjqNQsN3hlxAOgoA1AcruoRVr2UO39zi1PX0BQGkba7VqmX5sObxSHmztCSFQF1nupwW1+g/KfDDuusQasUVCz4GjPgkxelhM1r5QcSFEO+L4TVaMqhfVNyquSHffey+/SyXdLGct+v5WEQi4cbm5JKTGMHX03UJuypRRi6mwmsK7r0c4Ls6IKyrhMkxhUYybmGaHzWaZJhvJ1GITqqIqso5Lgs7TRGCfrgeN55uWXL5jnmf1+j3Edd7dnYp3Y7XbcXL+R+JOGfhyYpplHuy1//Mf/OR9/+AE/+Lsf8PrlS7ztOC4zL1/fcJ4jc4mclhNzlPfAW7i8hI/e2/OPf/eb/O6vvYtXZ+p8TZ5vZD+6GpQe2Ix7Us4c5pm3t7dMp4UwC6FwcDB4Q99JZNVYJZAZrdFhxnrP5eNLptMNMS0oDMsUiOdAbztcV3C6YzlPxOOREsAPMHQK54XGKAVxWvb8uqKsk4HTOdwwULO0U1ZVKUoKmFJZW4MkdGYgFum8MCXhFGRdSVkuINYbslIoZ8FqlhyleU5rSkgs04w3RqKuSqFrRpXMdtvjFKQsypjI5CPOGfq+k0hqWDhPZ3KiVVwL/6Pk9jlvn50QAsucxBMwejbDgCl36FIZN33rlDCsSrGEmdrK4Er7LouyII2RKRdKEce71gbfyqaMkQTOzfUNb1695Xg4odGoanjz+obpnDgcJlKsXD7e4AbXuAISxZ7nldu3b7k73nF1dcmw6Ukp0Xc91ms6ZUi1cpyStJIWRZqlBbKvHmwkxMTxeGR/ccXbw4G3X77BG8XTd55z++VrlleveL611NuXnH6Rubvw9HuDvtgRnUZ5Q6mx+X00Q68xQTDMKU7cvT1xsdtxsRkwqnB7eyAtM8WNbHYD2+4KP17ixyswvUS55eGIUjJo3V9a/5eHfVM5G8PlK0fpP4wF8EsPADXLvlv1nifvPOfXfuu3OX7+OdPhwN3dmZ3zjMagtIdcMVk+WFZbaoK70x13Nwc6P+L7USTZKlPvzd0ZpRRd17Gez0znM3VeKBn8ENnt98z5TFhmKAXvOkxzfkuCRrUiF0VpFDWp7lWkJFQkmSjvXzhF3w8Yo5mmCVsaiELX1uzVaGxaCm5yFrRw13WMQ890PvO97/xHPvnpT/jud/4jWlW2vSfHlc5anNVoKuO+DUwxkFdNsrKLVEXUhloDRmsUQpC7/zmrVvi+oyjFJ198wc1h5ss3NwzbDbbf8fr6RghbIZJa14LRYnrLeMiSlkhqbbdxOaBrEb69rkWa2IzDaCnP0TRWeIvQ9c6gtYdNL4e7KtzcXHNzM7MZQCdNzpGSJBJplOArjRbXsqxWSotetpvu0OG9a1yGiLYe7zzKtMk1rFI6ZCXuJ6ChgrZW5H/vsNqwrEvbTcrNRXwbMuikLCS0mApUUUWMVlJA1I9Y63DWy3opZlIQOlpVmm7Ys6QjqWS0caBlcCxVsvQyOGqs7ahV/CPXb695eyN1urWIb6SRpDFKYFRD34t6kSLOSnpknUN7zQo5BfqhxxuPtYbdbitkt7RiEEra0HcSYUQawu4RoN3QY9BgjTQUrmsDwFjWORBzouvkYO59z9AP5BCZzmtbo3moRQb180KtcsP3rqPrRl68eMEXrw4cDoWr+ZaLq8csqfL67S1//8kNqcLVhdAyewfbvueP/7Nv81/+0z/m9Rcv+cXnnzOvkbvzxPXhyM0pcHeG25Nw7iuw3cnfTx55vv3bH/OH/+ibPN46ji8+Y11lXXi+i4TV8Oz5lsePnhL1zPHVgS/fnFln2HRw9ajncrdl03msBsjSyGiMxFxdoRs79o8umKaEWiGHJCbZueJ8ZFlPFBZYV8iVba/YbT19b8EKm10ctppaMxqLbc1taylkW9k/3jOvC9M0saZJuk7alds7xzJPxKrIrZHQOMl65xhZi0LpJJS/UiAa5rCyBDGBjs6SAwST0Kq1P2pp1NtfXlHTyvF4R8gR5zu8Fd9O57SkJx71HM+OECpxrSxLZA1yAalVDm2tdSupqSwhcZ4TZx/pjabGiH4rAsX+YmSzGYg14TvP8XDXCKCRaicq0lpZqVAXrFnZbAa8l1RD13UYFF98/gXX12+ZprPEZIvh1au31HKDUoaL7QXreWnFQR2bccd2u6Uk8WQdDieGYWQ6z4S4kvJAP3b0g4dSKGkBXahFUXKks8K3iMvM7TSRVOXlq5do3bHGld3FY3abAcpvosIR3rzBAG++fMmb6cTXw5lv/v63GZ8+lpKqKvHgbhgYGAhBvlvreSIuM71VeC+JtM1uD3Zkv3/GsHmK8pdUM1AZ0Xipitby3aYoOReUlAhpbR4if0LDVbKOpEUBNW0FoPhPBJ5fzQDg6oLKlVJWvvlr3+T5xZ4f/Ie/5JPvfo83Nyeyc7j01Y47lMDpdJbYRVS4LMS/u+Mt/Rh5+s67+H7LzfHI6XRC+45UhbxljBNptsDge/K6Epdzq/cVdn3f9Ty62KPViWkOYBTFQcmKlAWoY7THWPlQq1rbHjZgjbDTdYMopxhRRvDBMYn5K1cx3Vhjcc5jB4v3HbElDP78z/4diiK0QVVYphNX25Gh85haGEYPXeVcKzoVSpKaYmssw9jhvGWJC4KoQApkMhitiVWTYsX1jtOUuDnOaL8hacvh9kDVihQjFdnnUyppWRH0DigMvTZ4ZcWUVwq6VCyKDugoeKMFzbquxCC97L5zONexGwfiOpNzYmxT9ZvXr5jnmcvLTl47jUQBVWXohF5VShE/h703qriHgatWubnHJTOMI9o7lrBAFQm21io7sFGkROc91tmWmMhSXJNWllywzjKfAud5bmVNuvWqV4ReKGZPKQrJgKZWR9dtMY3Ytq5i8MxVgD45i9EpK0VB/An9MOCMGLVilFgTSqGMwfseZWCZF2qSSKRR7QGKOKGvhh2bcZBYZKehOEIQeNbYW5wz8u+spuZA5xzWKlSaUTmS4yKDvXEcTwve9+wuN+hOs4bEeLkjFXhzfce6tGa3lKQ9zBipeFWKvu8Zhw1GW3KqrHFlnSX9sKyZGBZCWCV6VjXOgTOOmDTXtzNvz5WlwHyb+OT6hSRBvGapBd3Dp9fwfAeXw8B/80/+V/y3/9W/4NOf/YLvfPd7vDpNHFPi5Wnixe2Zu1MiSuINCugKOcOzJz3/7J/8Jn/yR7/Nh8+vOLx+Qaia06pZ9Z7x6cjz3WO2+yvWrLhdD3zx+ppqYf/I8c6TCwarmM/H9udd8ujJFSknjtOJVBWPnz7m8dMn9IPjWfeIHAOf//xzTsfAu+/sYUrcfP6WrbPkKXG1kyIqrHyuUi6sJeM3G5R31CKgl1VnVGewWpFqYrwaePvZNVUXdruBdQ4sSyCtiVBm1oJwAKqge5dYSCpjh4Gd82StyfPM8bwSkmTzjQAcxYTcek+0Bt3J4WO6juO80FuDNhbvLOhCqRFTAiGuDOMGi+XZ5Y51zVzfHHDa0Tmh+mlrWVPieFpYVmHPFtmoklMiIA2KvtMcj4XD4cQ77yiqhmmqhLASUiZVRdVOWAhVBnNnIhc7Q3mk2ew0vpP+lfP5xHQ6S3VztUyHlceP91xebIkxClLaaEKc6a0jnFccnmg6jLUSlXUDOcPrN2/xXlG5QKuMJoKu2LJQ6owzPf3oyKlwffuGNYhJcUmBvh/RTrEdPdvHO8iVS/8u74Rf5/X3Yb27o6oVUuDtLz5nN+742Pfs331K7vco79HOyYWuVOoSebx5zN///O/44ovP+NB/HeV67LBljpbd04+o+oLCFq0GlOrR2qKo1JpQOQEVZcQfJDY1DVVMNrnIelFpRVGZUos0shpp8Qwp/WoHgJIFRtGNPX7sGYeBw/UNb754wfXNz0nTgsowGiMPsQBLDmSqlJsoK3jKtHC8OxHiF/hhw5IL52lm0A7jPF0nB39YAufTWX5IoyRXX8X96ryj7wdqUcQY5KGqFChHTrRqU+nArlUegkYptBE6WSlFjFIx0ruOoqTiMuWvDn+0yNdD59lud/Jhy1maEBEDSedcmygV47hB10JYJh5fXvL82WOUL7x49YLTEjG9x+AFb5wlJjd2llATW+Ux1jCtlTkgxEikBTBlWENmiomgIkuQSGHKsVUp0353cfXrxr83iCSqGudAlIZCZzROK0wt2AoWqTI2FChShXtfyoSCaTpxOBy4vZ0wBvYXjsvdvvVTZ1kHaCUxteYFUA1TabRt0rcgUlMWi3otVdDOygqcR+vGD1CMw1ZiMs3gUhGoUUgrS2xNckE1GTvRd+KMtVajjbjZAYxxdNaJdyBmYkwc7iaMMQ/1qKn5RnIVyM+8ZjnkEePePE1UXYhRyneckTaunBKxLMgTsuK8R6Xcug4cVkPvuxahlJRHjk3CK/JAM8ZgjJXBI0dylNfe2oHOe0yuhFQpFFJMLDExTWdsP9ANG7b9SEqFcJ4lYmoFYAQK3/UoawmrqBvGSJeA3OgWYkpkFCkmasjiwm5KzdB1XF5e0g0j52nm5jAzBWFNeGVJyO7dl4LvxMB6OcKTiw3/8p//Cf+7f/lf8+qLz/jb736PL67fsFjHaixhzKznhXVNpFixCi68YKk/er/jj//oH/H7v/tNnj1/iu0tS/X89Q8/o0bP5Ye/zdXlM3JWfP76NT/64Y/4+c++xJqe7aNLvIalSM5bD5ZChF6TbaXqwtW7j7i4umTcbtjsdhijON/e8PLLL1mWwH6zx2XDEle5UQO7fcfFdsR3jiWtVG0wriOvC8c1oNQ9Q6+Alt4DbTVaaT5/+QVVV548f4pCM82vOU0LxEo/jvJwz/Vh+M8VQi3kEGV9p4XLcL/KBIknC0XayDCgstz4tJgJ52Ul5cysKpR7Yl4zsLYYXAwzFIcGrDL0VlZhfpBnL8YwryvWVk7TyjS1e2RVqCKslJgLOlaMQXwzx4VUE9ZaUoEQM2sqxBrIRZGaqmlNpuTEMA4MG+m5WOZApQisaIqyliiV6bzSdxu2mwus02Aqy8sjeckoo0hBfDClZoZxixyVNN9D4nw6AYF1sczLGXSl63tUL1XpISjWNUtsvGr22wus96SGnJ9zYLu94NHlY1EpKnz2o5/A7RFnHHeHMz/9yc+wF5d82NZiFYNG8Nq9tdgRVDew319xmg7yTLKe81IIpWJdT8FjTA8MUB3S7plQTYmRl75FN8QdAqiHEiCJWfLAXhEOjuy+9VeC969mAPCdSBtFycHoNhuefvQhTz/4gLdfvuR8e+RmmkjW0DlDJRPi2m6EnVTa5iI96kvk7nRDsQeJHpWK6QZ5YEOT84WglVOm7z0VWh2swSiJxSljmtwse2nb8utrzK0YSKA1Ipd8ZcCj5haerFQvnoRUcmu1A2UV1jqs02z2W3b7Ha9fv5Z1gbVYrQXZ6BVpabdebzC1MrqBvreczgdcMnjj2W8t1vZQBKIR40qZItvdwKPtJePFHtNtuT2vfPL5a17fnNFG+uMjSeI4cZFIYhFJk3bwauT2DsIfsFpKQzqt6e6/pYhTWLX+eFXFk2CQaKZRYuhTNVNSYl5myLFFj2QfqDRsNh0XF3ucEVeqkP2V0BC1kP/6fkQZR6nSvlByiwOWRExiDFxCxBrT+q1lhWOMoaTEaV2bicmRamGZz4LULDLU5bYq0daIlOf7hsuVBrpSCiVJn4HSYiJMOTFNJ5zxDwdlrfJ5LA3YE3IhyipbTEiRhmIW5KvvZLq/36/X2joqYibFxMVuwDuD1Vqy01TWdSKslVozzgmhzyiFdpLnrUqRKOSqmudAC8rVOVKJsuIpGWMMznnhVdz/piLBYK1lGAaWkCgxPZhbjRGfS1VCFkw5sywC+iGLWzznLKVbLQBjFYzW4rxjDgtfvHrD3emEsqAKxBKl/MuICXPbdwwVnl5s+G//xT/nv//v/ztefvJz/t1f/AdeHG45G7iLM8l1knbR5YEx4DX4ufKPf+MR3/rWc668w2sPZssvXt7wF9/9nP/j//BTnj7peP99jTUH3rx5w/X1NdO0UFa43BY6b7DOsZYAFIbO47uOmYKvgWfPHvO1r3/ExdUlp+nMNE1M55W7tzfMx4lN+/wcX9yQ1oXt6LnoRh5tt4K49pacxO+SlSIqCCWjsqzqEhVVxbSqrBGeRZhx1klXx3nivASqNlRTSEqDlnhdVgKYUuKtFVhPWomlsuYiqSDVrDAizsigr40M9qYKVa9USgyEKGslqzPJFxSiLnWdx5pC34vEnFJGKU3fe7JTohh1nTzHJvl5nPN0NrRnqWGdAiWVB/Ng34sMnWohxkqtkXltcniBhMDUCjKYo+XgWpbM4TgLSrkTMNppkmdbUWK4Pp1OOCfmYW0cKQVJvdRC1/j4VFiXFaU03nl2+5HHTy7RuhDimZwXwY+HIGVIqTCfV1IKxKQxpme3u2TcSZpl2G4oVbPdX+C6kc24Y+i3XG4usVlIoPPPP2WaZm7vTnh94Nm88gyNb2VrFOllEDicw9oe122JWTOvhd2oqUhrqlYFbUpbTYSH77bc9YtMfu2gVw0QVWltc1UQ0HJWNgAbSoxjpcqFSP1yE8AvXwesLblGlIa1ajSZ8cljnn7967z48ktO9UvWdcGUCilTksiRzjp0raxrkg+TkTes5sycCmssVK1YQySzkDPC1NZaPnA5Y43DeYc2EGNgnmdSSnT9gDMGb51AVIrI/CVV0FLoU9rN8j4ik2qzPFd5SJf2puXSZJZ2kCilUWjO08ThdJJaXKMpCBTHO0ctif3FjovNiKmZsi50g6cfO4xWzPOZbT9SO82pceaNNXg/olTGWXHqP756xLMPPiYphx9+yum7P+Z0nEmxcAyRZZkl116FKV9Lxhs5eI0S4V+hMLpitaLTmt7JMEBp/87IWGiq/HPbZEWj2wBQi1Qb1CQFPlnMcPe1s/3g2WxGhqHHaSPGr6Ilr+4cPjkx9tmOkBKpFFIqpCR/Xo5ZdutFduqd87jOSbQSWkwwMJ8n+uTwKZMR12wq8cH1mrMcpt044IwAdGIr0ZEbuUiW6b7RCxksQNINSn+VAkkpPxAiUxtOdXNfW6pgUdsD1yooSWiKpgp+eHSW4jNaKy4ud3IrKkKdDOvCuiytBhp8Su0gd5jWPFjR4lFRGt+LqtZ1lpQy52mValdVMdbR+55cYA5RYow1ENZIzhVrLMYoVCoiSa8rumS09VRtmOeFaV5Y10CFhyxxoZKVIj+QGg2qMywlcZ4mXr19y1oLrneEEFkDbLtK31mUrmx6x/ubPX/8B9/mv/hn/5ST8/zbP/tT3i4Tdznxk5cvqENHv5c2Sy2XOZyCJ4PiN98f+PqTDe89uuTdp+9g3Za3p8Jf/eAF/4f/y/+Hn72FT88rf/vlD9FV0LoK8AYGp7kYB5aWCjLGk/NENJn9boMdLNlrVlU5rjPr28TxcEcMgbQETjdH9sOOwfS8/uwFx+tbbIHNsGG/2zD0A4fTkeIM1XimsAgbAkV1HqWtGPdaTZtqevkaIkVbirEc18BpmqjGMuwHwpxk6KuKSCFxb/hSYlptgKwQJfcvKpGswHISw59S8j3WVgAyWsmwJx6UBEpqcc9zwJtM73r6cctmsAy9RdXC3c0NuYoh21tPNwxoa7l69IjzNPHZl19ilMagGRKUojjXyvlcsA66TuK4qNoSANLIqjW49vNZBNEbi2rStKhZ05qoU8DaSioWbRQhZmiJppwqsSzc3NyQc6ZvJtVu4yip4o3DOo+1jjWIh8o5yziOXOwvGEZHKRLHW9YTtRZO5xO1rNJN040MY4+1G/pxR9ePVJ3Z7S+pSrF/9JQ1FCKWOEV0Bnf5mGff+g2S33B9fYN7snLx5ClPv/Yt/OVT9DBQ7tXBxuuPNWNrIhQDquN0DphuFbWwGEI4Mu4GSjpRytB2+c3wd/83mlrk8nof75OnSUapgtbCVMmNiKuqDAqSY/9VxwDXlVQro99gjSbHSGc7nn78Nd599ZpP5sj65o1Q+KrCVi3yclHktbBOImNqZ0jGkIpqBhH5ZWUfGyhV5FuJjskLMvbjQ6QtzIEwB1IqGOvpu57LiwrqxGkO0B7c1PIQEdPKoKwwxEtWD3CLWkFpJyYqXcUk0mTnlATckxZRB4ZBWvwuLvf82je/wbvvPMepys31a25evUTlTLftUSkSc6IfNuQY8NbLLlo5nBXTHkVEK2cMaY0cbu+4fLKwudoxjiOlFs7nE0tWnGIirKUd4hptagObyC3XwMMg4I16aOXzSvK/FVFUnNOyG28FMqpknFF4XYXQCG0VIIAf4zxoJWUW6T5/6+UWazQ5VtZlEbARSAIjZjJiWKpVU5tDvwJVaVCIPyNnIFGNRJVKEMVmXSa0hmkNTGtAWYH/ON8TU2JZJV4nRK92w0jtVlvbV6SIj6LWSm0GUGcs290og2FrSEwNK52zyP61QGc0Fbml30eYJC8tXgtRteQ27YzGe4PpOrw3bAYnw1PKmFqoppKVHKzWinKRaiNMxiRLmraectaQe0kelFo5HM8cTmdSrjL4akdp7YJyiBtA6mVzkhuaMRbvJP8TYmaNGdVqtrOCJQVCKTgv/38MqfkLFKlWOq/pdhvM2HEKM7fnE+dYSBqUSVQn+OhutFQyfed5/713+Be/84/YO8f3v/s36B9+h59+8Slvl4nvffaSLw4zl8/hsRZ1buwNpYdLq/nGsx2/8ewJHz9/wtXlI66unrPEjn/9r/8d//f/+S/4+2sIveJcDWWRz2XvoPNgLShfOdeIzobB9gybHqcsY6fZPN7y7MkFfWcwqrDqSlzFT+G9I54Xtv0WFzSH61vefP6asgjpz1AxGkJcZIjNmVNO3K6BqCBbI7taYwTbmiuoSgyJEgvLugCVje3YDlu6IkVUtWrBaVc4LRMhFWKUG3OslTVVllTEC6RorXC2rZU0WUkUWSsjzYpGuPHtCoiq4uBHyc+1rJEqsXy0cXjf03WGdTk3lK2wAJSSZ4k3iveePWWaZ968ekGqkc4oKfwq8u+zNwzDIG2XDWymVKFYzRKiQIkKxCqNfyVVWf0p6VCJuWK8w/UaVEWlilMaYzpqzqyp4eAL5DyRUmSzHdnuRnrlG0K9xaeVxlmPdR6XLGENvHjxEu81+32Pd8Ko8a5jHEAbg3MDzm+wTv7WzpOrxg89RTsBB51WpiWBdoDFyuKUq6//Ort3vsZ8XigotldXPHrnHcxuQ7KyYk1ZaKs6V+HIlITt9lw9fp81TJzOC1eNE7Ocbxl3O6iNzFkTKNcwefL9lqvbVwe/oggoWmVQEW0qIYlxuipwuntQ6x7cgr+qASAX6TKtyiL2CiH4Xbz7Hh/91m9xeHvHdYikm1tSKRjlsEpBqhIxyaYR+WBaI0upKKcx3hNTagYHkT0kB24axEG4ADLhi9FNKU3NhZISbthweeEpVbGGW7zVZFdFlqJ9CI2YtzBazIBarvtFiZO+NLxrvl+8aFpkUK6n4yhGwA8//IDf/d3f4Td/41v83h/8Ab0z/Nn/+//F3/yHP28sfcN0OkCtsjvKENaVrGDsNliTubu7YwkBrTPLXNm5LTkEbt684eY48cXnn3E+H0WSbz+KEKe0GNSqtARaJaKQBbxWdE5u4lZLqUevDd4aahV9UbffySjkgNdGWtqUVPjqqjBa4xuh0TkDWrOGQClZDEftgbGsM6WKcziEhNYylMQ1EHIlVY227WcxhlIhl0QuUrJUkQhVXUXaj3ElRkH+jr3DefnfrhRiIwFW5FCmVrnJQ+vPFtOg1hrd/B1aiUM2xyR77vbfKa1dUdQSTTWySpKWtXuzU8YB2kjcT+lKCAu6Zmlncw5jeoa+wxpLyVkk0xqIKaBzojdCaOu0VE1733OahKS3JjlU7rP32lg67+i7xBoTOUWO5zPLEgSapC3WeozzbFyPcR0hFanJ1YrOD8xRkMGShihycNUiZWFGk1OlWIVSBuUtMWXmKlXI1mgwGt179OCZS+RwPHE8rkQFdtAor9hsDJvNhqHrWOYjVxdbPvzGB5iN5fs/+QExZ6o3vJoOfP+Tz/nkOmE2EFsEt9Ow9ZbNheWDiz2/9dEHfPzkKY8uL6l9x3d++hn/8998nz/725/ydq0EazhHJJ6rqmBqfYaS0brSDxrjDLurHU/ff87zx5c8utjw7MkFF/uBzeBwFgwZnQOn6xvmu0PrvlD0uuPVl1/w5SefsdwUnuwUV5sNpkLNmalE8JalFK6PZyYqDD2xArmgohiGY07UVNA5oqwoh1pr5pgwsRCq4rwmQkgsU6DkyrwGQpP8U4VYFCEXllXMgcaJ0puLCMOqqVAlF4HdVFEwaymUVkeu5ccCxDdkad6CKHRLo0Epj0Gx220JoVCyYl4jKWW6LnLz9pp5nWVYKhGrHblhz+dzRFtN5+S7Y61p9EsZUpcgTJY5RuISKSmTk1yq0HKYxQxrUpglo1TAB8V+v2HcbIlrYF2TXF6p5CJDbJcchYp3PQWp1S2lcjweZXhugK85LMzzmUrkdPJ0XRvQteViO4Ay1GrROLSSv1GWimONhaLFvFhCppoOZTq6boNC4XaOznd460RmrwrjO8wwkIwoW8UYvEAl0KViUoHWlDqOW15fv2RZj7Ly1BDmE2U+UKunkKg6UumotaMqT1GNZ6FkhSgNNQVUQemEUtIwWMtESrOciS6hSo9SFvdLmgB+6QGgcyMxJ3JW8qHNCmU0brPl6Udf42s3R8oauV0T6/GMrhWLZMdzVlTlpWJRVRTSfqSw1KqopT2c0FCLGKKa2QplCCFjTSGlisJgjSemwDzNeN+x2e7pOymJcE4scCkFyLXVqlZSTHJbShlqFW690WKIahLwveStm5O9akVpRsLNuOHXvvVr/PGf/AlPnzxirfDT736Pn/zkJ+RS6XvP6XTi8vIRH7z/LvE88/qzzwnzwnmeOJ1XUq6EuOK9Z+gNiih1q1qxnE/cXt/w4svPhaVgFDTZr7P3rU9iNjJKM3qHrgnX9mKjd9IEp4ykE4wSqfZh/VEba17Idc4YVMloShs2lKxTvJbfGYkqqtag570FakM1K8bNhnEQX4gCSttnokBpQ21kw1RlFRBCJKxRmAHWknIlplVSDzETQ2o1yDLhGydMibBGqhH1wyiD85LgUIix0xmHcvKlVAoBIbU/Q1nHXGfJvK9ra2QUmcxqQ3H1IVuba5HMsgLX2g07L65clSSO451lt92w3W3Ybka0VsQYUcjvsoYC1dIPA8ZIY1hRCu8Hrt8eOJxnynEiligAmraHrwWO5kwWDZiYiuTwraHrBrwXidZah+vgeBbkqbMOYzuWtJCL8OeLNmhvsLVKjayG6hT9fkRp8T/oECidDNKmAYk67yhOMZ0nTiFQvWa3tXSbEeNkP+y9l0Fzo/BOcXN+w5+//YzlfMKPIyFUruOZ1UP/yGF7ix96OcBqZfSW7eWWr737hG98/SP6Yc8Jw1//7d/xp3/zPb54O3OIEBSkpNtgJ9n+Z1cDTy4sljMXo+P9d5/z3rsf8+zxUz547x0udiObzrHbDhhTySWQ4kyYzqR15XZaWE8zvlbSUrl5/ZYvf/4leao82lm2XtNbkU/neSYpTbRwFyJvzjPRCQ56oUCQ23cqkkgqZLSFcduz22/xzjEvCyrI0HtznjkdZ9alPKwac9v5SsyUVhtcxYBcFRYxbdbS/CNGk0sUnj88mGuVVmijURVUg/I0CYGqYJoDb97eEmIHdcOm13TOo2KgVPGvLPPCQSnWdaWSWeaz+I1qlnTJkskRrC7UuILRDIMUoqWcGDcjm2HgtMwwq68+27Jfld8RRUyVu+PKEle8q+y2PVU5lHZ0nSUOuT2J5JmjDZhO1o1Ky+pYBqHK7eFWzOB5wFh5ZtEuBcu8EENlM/YM4yDr05xQumJtJ0RWq6DKBck5Tz/usN1ANQ7b7SjV0I97Uip0/Yb7XXxzPYGyZKMbMEwi50WXBxOpNgXSKj6c7R7le27fviSmGe8qOa3cvX1F122ppgczghmpWlG1XIaryg9KvuDYpRhNkZBCoTPrcmJd2wCQB4obcG7ANtLor2wAsKajVvOwj7BW4lJZVfr9Iz76jd8kTSvlHDjMn5ITkqMuhXlNzKn12msA4TiH0vLQzlPKVzGqnBttq8gBnpPs1lKSnWdt0ZK8BqbzjO8GIbap+0Phnh4nobD7zHZtBSu6Ip3ZaJHPkDx2yWKUU1YeyhVQRqExpJB58/oabT3advybf/1/4wff/x4316+53G7YDD3P332fP/rjf8LX3nuHv/6zf89Pvvd35CDGpzUuZCU5eeMs3lt616FKJYdArorpvBDDiqbKkELBW0utYEvFOSnBUMqy7T1eVUwpeFXZ+F4OdTSqZqwSg5SxcmvOJVOSCErWaJksad5SJTE+b8XcV00GVZvEJ4e/78SEsy4rm82ItTJlSsuX+D1CjMRUUV4yzRHZzZdSRa5uMboUpfWKUtqhL4RHqwWwU2MhlSAZfsBguG++dsZiUKh7kI6xaBQ1yxYtK2n8MqYpR9bI8BESbpBY4j3aVz1wtUXBqL0MBL4RGl1DJMfRk1PEO8N27Bk3UjZUqfRG4ZwhZ0tKDq0Uw7jBWceaxFti/UBaxYTntaE6jSJD64PPMXI6J5YgEVXnTItBeowbwDiJV5UscCgjICGUYQ6BKaykKuZCrz22GdVCTsSSML2n6zzGSXPaUAp7eSHke9Re51ozulo65em6jmG7w3Q93ves68p0OlNjRanE4bRwOFzz/PGlpFPujuAc0Si2zy7oMTSgQ3vnKtYp9vsdj54/Qo+On7+95ns/+YLv/ODHvHy7sFbI8mvhEMVlM3RcbR3vPd3x7LJjP17y27/5Mb//7d/H+g1WOy72OwywTGcO5yNLXESWTwvz4UCZF/JaoHrmaeF0M3H47BUlFB7vOnZDB+siteRKM4VI9T2HZeHVeeF6TjKwxsxaSjtcM5V7EAtgoJpIP0qctuos/RHGETGcQmVZaakWeUmU2PnbIFDAlLbma/b+FgPQDZV+P8hrLStLozTWteTNvYUsJ2qrba8K1hSp5xnIdE5TsmE1UWrVy1fropTFD+O8fvg+xBAIq0wsvQNnQJWEtU4w4aqSa6KEhao1rvEGSu9JpT1zSmYNiVCkulzFzFDgYucxtpNkljI4b+gHSf8Yq9iNI6bTSJ9BJaRI7y25StxwnmcKFW0Mpoj5spKpWXw8xnuUsqxLaiVZCWt7cp0xbuKdDz5mtxtxXY8ZNnTjBtMPxKJx3ZYQFc73KKepugMMuSgqBmc8aCODTqYd1vfpM3mu1lLb7wLaOS5a0un25gVUeV4ej3fi7fAR7Wn0Nyv10M0nhE7i7m8qgCJRS0TXwOn8mmWSciGjNGkVs/lm2OPG7a92ADDKgjNSmlMrRgmuUSuF7TseP3f0f+CxUfGD00q+fiugkZpISpFUa1wrFeM9Xe8hrKhqpaEp3e+5xeUZs5jeVC5yOw+BXOSQKTmKkKsNMUb5MFQlSF8CAM4pmaZzc/63jKQ2hpokmpXua1GR4aM0xKtuf6PE0Z1CIujA7dsbfvBXf81fn0/86Z/+W3bbDZf7S6yWafIb3/p1nnzwMS9fv+RHP/l7lhDJITOHli5wFh5qH5sLuBRc51nnmfl0bjt4hYkFpwRnqVKl5oLtLNYZ9rsNV/sNtmZUjJic8MpgFOgqcb+SGydAyYOenKQeWWtAmscUBa3BO8vgPVYLorRQ0VrJwNc+l/cPI2VEZl+WhaS0vMdrJITAugRyrfiuk4M/Sz0zpaIr7c8srMtMSll+lqzx3mG9HLI1Swe9dloOemWwRoxe3lusMdLyRSOOoYWDrmT6J1dqlk4JkQtL89TIMFmKvPfWOjovsUloE3atclBqRUoBrZS8Nr2jxBUoDS8cSI1mSDNPmioVnkopdMmoYtD3Q2XOmFqJy4Kishl6FBGtMgVNyFGiiEla20LUuFQpvaKghdimwNpKSYUlRNYgtyJxjGe077HOipKRA5FMVIWkCn3vsL2jCh2HoRsZxgFltERNUyauKyVF/NYzBFm1Od+hvcd5T1SJ9bCwTmdKiuhS8V7xZr6TOlZv5DDAoJ2DYoghoasmEPFOY6zGXY6UneMHLz/h+3//kr/98QuOp4TqoUborezpeycFLu89u+T54x3vPN7x5LJn0ys+fP6Mp1d7WSXOd9xenyi5MM8L8zozx8iaZUVCjKTjjDkn1Dly+uKGu1+8RN2cuBoGRm+hSF+EVnJJ0Z1nVobDHHm7RA4JEpniFGuqKFOxXjpDrJVIXFUwL5G3N3egDblU5sMkN/4qF42sGus/g/EtuVKbabVWlBYypNSQi9pnrXmQxK2R9UIpUuqlGm2vVimBQql2aChSoZVUWWKKzGvi7jhRkpiycxtocpTvpe86QXsX6H3P2GmWJUBZWqeGYhwkhbXdDnirSCliVSXFhVgKpa1m750/tvlkQorEWtEWaN6dkKqUbaEYxlF+NysHKSox7jeN7LewhlUiltqQUuI0ndFGy3qRSk6xdZaI0pAy2ATn80pYV46nM9O0cPnoKTECJvDB13+N7XaDdp1wF2ohLitFWzIrpVjqvODHPbka8XEZec5nbItFIjHz8hV+R7Xnp5xPnkyh6op1I+P2ETkn5tM1MU6gEqWe2BiDK4FUNCVpbBXoQ4W2upEWRUhoFYGFkieW+ZoYTlgnKap1DoRg6e2KqvFXOwAobUUq/k92rPfO7FIz1Wn6y8c8/drXuXl1zcv8E07X12RrycqSV5HgaZjCGjOqKAY/SHqhvZglF2JOLKtQzEBT9IlhkCIhpQ2ltWaVWohZbkXauocJWVSCdrDrljuv9cEYobV+iFCUXFGqoFRtrnjZpzsvffOlFJSRSN3h+i3/z//x/0HOkRgWNl2H29pWZ5z54ouXnI7/lpdffMnnX7wUs1kpaGdRxhFzZkkJhRh7xHXsULlQcxF3uVLC4R8VNmTwjt54dlrjNxueP3/Gt771dbZDx/WLL8jnE3VdmA5HVK145VjWWUxGJaCNofM9TovxjXbv10Y/DDpGQ20shFLErW60btW7cmjfS9UpJeZSWdaVzkq0LabEvCxQK9b5xgSQxrzUbhelyEGpUOJbcKZFOsUEJ3lfRw4BaxTW2Id4oHUG7yWeNvQ9OUq5Thu7iSkT1kDK90hboQSKb0Gka4ngaXLN1JKhyqrEaN0ogglnDNQkUacqw0usSZrEWqnTffRSUx7Mj+saKSE+oJ7rvMjtwVpSyMyLrAmsUi2RsOKMFZ9CEQdn1pVY5AYTSyWHBDoKyL75BlCRim7Vw7J7rVpj+45YpQ5FeUNZFcsaKQbc2GNGT7GSYCkaaqfkbwWghURnKylBDQVtsnxG+0a8s+BGR7f1nE43xAgXG8VuP7DmFstUCBo3rBAKFUcpQpVMpbCWirKKk628qSupA/1ow/bZBoaFmjJDqoyDZ/QdnXXUFPnDb/8aH733jBgmdFkZvOZ0Xvnhj39MpQjwCcW6RGIsrLkQauUcF0oFW0CdA+XmTHx9w/LyhnS3coGjMxbvHKYmdJEVVlaKWA2HmHk9r9yGymIgKUTdsjD0VlaNRWTl+5IsamGaArXeyPcAKVuaF0nFKAM58lD5XUum5ILWrfDKCUOl7fukcdKIqlmReu1aJPutDU2li9J4qk37zskaoCLvR0Fu8CoW3NpirdYSY+F0WMmpMg6W0TRcsmrGaGNwFrzLUGXg7pxDKmzvB5eWgGgkUZDUwjLN8vMgwrkfFPMsqzlqaU2uSnxCzrVLX+Hy6ordfsPd4ZY1r9iim6lNUbUwLHKuD9wB7b46h1SLIWtE3VzXxLrOzNMkcfIM03mlG3Zs95fUInwNbzt027OXXFjzSqpSNa+Mp58jxm/p+g3e9+i2UkU+9e1CJQOPus8ntiEA2vc251ZIZ3F+Sx4icVHkLK9TLo36qAUCFNaZghSpWafEaFkk+aNUQLNS64yzCVUTWrcISV2pRYi4KcZf6nD/5QcAYwQhq4zs6+UTSKkFYV1ndLfh6oOP+Nocscbz+Y9/zO2XX7KcF7LRX8F0UsJkLdSyAn7o5DCmGbFybeUZVb5Yy4p1Hca6NnDIzhZkvx9Twhknt/sKqTHsFV85IkuR6dsZudXXpkaUVPCdou+9yG9aYiuqRXts5+nbz5dSZD4emhkOwjwze8/Ffs+6rnz/+9+X/KpzWN+R1iATsfUSE1kqFdkbVSXgipqkQ773Hbt+4Pa80DmN7x2PHvW4zZa1Kuy44aNvfJNvfvMbPH/3GZ7Cy88vuPnyC159/hl5OrEbR5x2vHhxJIWFmAKqIB9wVPvyyY3YeOkDaGn9B6OdUrq1z4nh6L5gqVZp28o5y5fTClTpwf1a5MAsKlJzbrt2JZ6LIsAiY1rPvdU4IyyFWjKGiFMObRR67DFGP3AYjDUSx2sHb82pHSqKEAIpxIa0lTy7UhqrBTr1UIvZjFkxxDY4CJI5Gy0P7wpUaZGMQSRE1eILKeYG26gyoNbSoj7i7pc9aiCuURr+GmsiV4Vt9bpLLGij2W1HYq6ELLXIJYvt1DnJkOcYZUCpwvOPueKrHBipQoyp3Z6ag78YsJqQM3NKGDTO9RSjKAboDH7bo73F9Ba0IpZE0ok5z2K0fICOZLAVrS2dk8+nsSJ7pppwvWN/tWedj6Q18/TRyNWjC7548Zpcmxu9NuKlKmgrD39hbBTOsRBVxcYFlwOXl3u2VfM8RC7Ok9y+YmLsB5zS4k8pjs2osU6472GdydVTzMqUI4oV37whpWjWkDnOK8U5piQqCXMkvD2QXtygb09slsoOT6cLTkn5jkJupbEU5pq5y5HXc+I2JI5FPAlFQdWyXpTvr5KiHgXWKqyVwy2lxDKtWJ/JaKY5EKKwLqxT2JY4sW1vXQsolVuWW4ZNq+8NmgWnc3smCdQnBMEHC54bYhXjnFaisFQKKikK5aHYiQq6wJrkebqkTFoLSxT0eayGeZUKa2cUpSq8rdSq0dZjixVvVlUyFKdCVYlUaM8LBKBWELDbvFCMJ2MJuYr8HzJLqVgHXstZYNrzOsaI7yyucwzWU21hWU6c1wmlhXWRkYbHlOTC13fSBmiaY9IYuahAI77mmVKEQdMrh3Udzg8M2x273Z5lWTje3eFjpNtsUDVT0aiq20pR+Cclw4AogUY5URwlqCHryhYvb/YnMZ43Fa7kwJoWeX81OOVw/Q5tNcE6QjzL4S4YNryzOO1J5X7dINX2WtXWcxNRNVJUAAKaTMkrOa4olUlpaVXoGWMm+se/wgEg3++MWz7eaCkqgEI1Bus1umR8P7DZ7nn0/DmX777Dpz/6EV/+7Bcc3rwlrUEeYjlhqxCdcsqS57ZN0lFiYqlKo4x80VLOcjsFmfju9/Zt3yJRa9mVidmtEQAb6vfBNZvbjsbc72hg3Di803Teyw1OiUcABHjkncEaEPqfSMS1FkJcyWHm5q1U7SqluH77lnHc8u6776Kd5/E7z7m9veUcMq7vuHz+nM478umOeLiRgo75RM6ZznY4LR0ChsJmO3Dx+Am7x48ZLi65fPYu73/tY54+e4bvLFvvuBgN3z/e8NlyYuws7z17SgqJmzeaM3LoprByCALMMFaQn/LEH8haSRynilznrJFyHdVIUlUMezmJf6K01/EhiVEhRDE6yU4sUWPCOrm93UfzvJUuAqNFIjRKMXRe3P45o41qJk6Ns07SAlnMVeL6VlgjVL91WTBtDTDPi7D8S5UioCyHj7ESoVK6gYG4/6IKwVGhWl5eEhXqfn9XBEBltMY6g27gIXPPRi9iZErIz+aqETUoRlCafA+bolJSpoRZutDRjLsd+8s9uh9kJ5oyh/PMGhPFapIshSUMU+TzKUbJQg2JXAohZWLND+9DChGtYIqRWAumWkrN4BRe9+AN1SrWEumNwXgLOROz+AmUMl/1i2tZBwlbwcprhoYEYVlQGoZNz9Pnj1E58eRiz3Y7soTM6TyzrOtX8WMlJjWMVG3HlFCmYrTlHCKfvH7Fm9MdAx3OVczGs5pCSZreO0pMpDViFPzii59ze7xGKymlmoLjvAa6QaPUKkmXWKjFUKrmdlo4xcRxmVmXQLg9cfj0AK8WnqnCNzYjQ9fhTf1PVmXCvMgo5pi4WzPXU2KqimAVseVtrZWDXG6Awl9wVuOdpvdy+y0ls64LISbimiTxC6QkBr9aZJfeafF1y2pMmCRaZazKWCfZdqMVFOmhUFXMv6bK5YbWbmqU/AH3CR3ILcXUGPxtTSBYXkVtt0MSGCNNqLFAmBNWy/ox5krvZRXQ9R6rxbycqihvJWYs8hy2zskhXiXhcpxXQtWkCNVoQqkc54UlVlljGcM49my3I513YtJGVrQxyUXv4mrPmDvuTndimus9F5tLTsdJTMjO4Qcvyq9MmoK+VmIEzkkQwlTF2J4B292OikG1geF8OknJWwmEErCdRzuP6zeMXvxNS6igE5YVVSfIiqo9WllJQCD+rNIuk7kKhyOklTUsxBRRqmKdweoO5xxWj5Qy0PmRmCaW5UhMgZSg60Wt9NWTipSXZVKjrlpKsVBMU7RbVLFKxFWrRC0BVSVeej5PPPolzvVfegBIGnSVJjV5AUTy0UoACGvOMoU6R/f4Ec93W7ZPHvH8ax/xyff+jh//zXf49O//nvkUBRaUKzlmnLbkkNDVNfCK5n4uz0oiMKmUVsZS0VZjiqWkJD3rpaJTwhYR1kqt5PKVm1/gI6rd8JDHmtJoJ1Lb5cVGpDwqqOaKN3JgdVYiSFol+qGn73eM48A0T0yTIcSFXBLn80Fiejlwc3ON6ywfffAh3ll8WKmD5uu/8ev87h/+IcZafvFXf85Pv/M3qBLpnBi85tOJOcuCUJeKJmNUZuwc3/z6R3z4a7/O7upK6iU1DN5x+xoOt9cs04nnl1JgcUwHxs5zclZUipgJ60ql4rteADS1ME1TMzBJ7r/vOqx1ghdVoHVt74PcfFJKInEZ6I14L9ZVBp9S5HZsjEiEILdsoxSd93TOi1RW5QnorOVit2W3GVoOWQxNuWTWkJuUD2tKcoAXRSm6DXiFZZVEQYxR3nMlWWUZ+TTUlppoBsRKRclEg2mScW6EQqEkmrZnU2IkaidZba9PqfJnV+7VpUQhy5c0J1JOODciMdlK0RVVKmsIxJyx1qNaVvhiHNDaEUulv7vj1Zu3HOaVbLwwwGolt587p0SeZtS8UBAPTabe058gaynD8pbOihqAVahGScy6klQCa4i1tbIpid+q9meUVqqUc0TlQq5WMLJtmClAaKyF0Ut1cac8pvHjd9s90xJJZZZbsbOIbqtkJ1sry7KidMF3IyUbUigEFdEUqBllJduOMSgv1E+lJZlwSgvxmBg7T+ccaw6cphPcZbQvclNbIgahsd2cJl7fncAanDXEuxPnu4X+XHEj9GhsLtL8WTIpVYyu8nOjibEyl8yqDAtQrEN7BzpTSgAlayWtNNZYvDViOqYNuc4x+I7D8cCyJjonQJ01yP+WNeCdwqjcbvvgHO0/DX3nGfqOYegwWrPOM+fpLApXyTjdKpvLvUqAkC2VDDO0g5nShjHR6JtyBNlIj4TB0GlBp5co74V3mlwKa0iUrPBuoO9GkhJ8bcmS3apFEaKsz7r7IiMlTP3TmsnKs2Qp2FpLZY4VjMZqOQyHcWC73eA74QGgK7lEcrYU5HZ/sd9zVS+Z5iMxJnbjBdZ1wllQQmqV1Yk0XDrnKLmQmhG5Yul6zzj0OGe5enRJjIXjeRZQWU6ExVJUZk0L1jtM1zHWjLNWkkYVkZDLmRILQQW07jCmx9geMAKSS6JqxxTJZHLNJBJFS3GdVKL38jMrhaoCrrIM5KpJ9UgumRgzxpUGdJPnnVWSAFFUAT0V1yT+RC4rOUJcA1bfG59BEQXn/qscALD3dDyHKqY5w5TcIDQiY6giUyIZ21nc08c87Tsudjs2vccYxSc//nuW26M41Y1gV0sSydgq2fvqmiHph11WVSKFpJIwWuKHFGH9p5xQ0eJSbjcP/fCfVYmJxiiIClISmIa193Wh8u9Tyk2KRprxGinPGdj0HcPQ8+jxFY8ePaLvO47HA29urpnXhePpxN3xhNaGYeiZl5V5kX7q69sTfT/w7vsf8p//F3/C+3/4h4S3b3n1w++KO/10klIeY1mXhZoKnbEEMmGeOB9vGfdbaknstiMXVxeYzpPniS+++ISf/viHvHn1oq01Koe7G6bjSbK57bZvdMVaMQKlnGViRw7bIhbWRruTzgCUIHBpCYz7v5RqRpcGyQkhElOTLpXG+Y6xk/KcdTnJ62kMYz8wDoNIliWjqfhmZLzYbeTIzUEa2ZbMus5iNmy3cEkPZNIqfgSUYgmryPnNYV6y5N696XBGYDolQ1VtNQEP1bm6fbGUqqjm4O+sk30qqX3GxewoDHPdVgatg/tBoYJUshhJUcQiq42KCGPOWDrnMUWwq4KZrox9x7jdkCoUDcf5zM00N4+lbiyC+7w3hBbxU0aTkFuj9bLuMk7yyK730qerIVGoRol7WWWoGjd4sipk8oO0L9+pto+tUJSoLZKGEXhWRcsaTkNJmZSlK8BogZyoLEmgUGTvrlsUtWCpWRPmyDxNpBDonKbOSYzOxeCslteugZuydhRgxRCVyMGrzixZBs2QZjpjBG9dYY0rd8vE4Rjx2nC5H8lFcXeaOYeI1wMGg+887iKx14nHxjJajc0Z6xs/ndKQ15WAdG6cQqEYL4U9xqGspEeEMpkFGJYyRSeKEa5XiJkcFL5rcVzAG0vnLVjLHBIhNl+KEhiYGDs1ndcYJYS9/W7LbjsyDrJvnmfH+ayZ51n6S2qD6hT5jGgrK4mYiqSn7rvj29pC19Ybn8Uj4pQSlkvVLBmpFc9ZCqmisFVqhhRXnAtY01NybSkUqMhwV3IhhchaFWjLHCOhKhKWkHVDAmsCYLpBADZVcvFd59luRqzNlBKljE1J10CqiTWtXHZ79lePOE4919c3zOuMtobRjQ8FRZKOEDKgMYY5CvEyhogzlmHYMm5GhqFjt9/LM0FbDscTMUem5YxKM67zmOjQcZG1XKoo46FajO9Q1ZJVpNYFpTuMHTBlRStLjpUYEzHJwY9VGCfvqdIWUz1OebRp8fQKqorRXSlFN+zlc7+cCTGhpgXvVaurNxQtkWdqbV0DUIlQHPOUmM+BMEeqL+CkTr4qiY/+SgeAgtSb3t+ya2pRNa2pRoprStOzitXEpMCC3e14vBnYDJ5hHFHG8Ivv/wjmgO0qVmnWKFKmt5bqDV4VbBZM7H1MpiKKQTVtOdsewqU5ZCsFbdpE2KSgWrPUEdMcog2x7LQSGdAZjFGUWIgpUBsUxRjT1gKWcezYjgOX2y0Xmw3H44G4LvTOUIpl0pXttsd6zzQJd9o5y6s3r9n0A++89y6/+bu/zTsff0yOgU++8zf88PvfZzod6VJkTZXOWnb7rbQGhkReFo7rzO3blaoqdx99SJqOpKnneLPy6svP+ckPvscvfvITSlh4tNsRpjOvbm7loIuJznfEkFBGWAAxJeY54EvF+w7Q5CqmwKK0wDrausVp3eKGjeWfCmsMYq5UBkPCGIczWrgGVnOx3bIbNzgD+mIgBakitsbReSeMfIwAjDQ4Dare9zIkSgqEdRb3a4VcIyFG1rAKHdJK90NYhRbZuLusayBFwUXfryRKLQ9NeFXd15HWluq4P8Rlb+idwTjdENJtPaJoLmwxnVLlS0VbH2gjIJRas+wCtQHjsUMPFWIKuK6n73vpGQiB4/FI0ZrRgHFSAjRsBx4/ecwUC7fniFHmId+tm88mxkguYoaslKZoaJS1uL5j3G1ZSmp5ZCQ+pGpbdWm08szLivIG7WRAuX9Y5dLMfsZgraNWQ8mRsCwCDyqFJWQ6J7dRFCgrw+OSIl4ZstIS3XMWNwioKCaIa/uygfhAFNSYIIihK9RKLEJ19J2haEk8BCpBFbR38kBtw9dSJZ9uayNo1soprUw1UnVPUIqiNH67oeZMKoWYMr4q9mPHU+V4Uix7LBtXGQeNsWLYimRCgilmDmvksFSWHlTXSUZ/XbG60BmB8YScqUYGJ62V8BZSQtdGevTih/HWYr1DOYHVrClJX4fRjUqp5TlkNSUFnFVsvaI3BVejgGAs+I1n12kxu2bFkjJLCsRcyFo3iJWYbcUnIgY1lKhjlHrvf8Z6oRiKN63hZ40jttfr/itZVaFfE7YTs+2aYY0J23e4biDHyBzOnM6BipSUhQpzkM9y0ZAJJAzWOzH64rEWxs3I5dUl1IVluSPliMORa2RZE4nIsu7Zlo2sulIixsR23OE7TwgSH08pU2okZXnd1zUQQsRowzCO9F1HzYXT8UQuWdoQjXi0QoyEZSWT2KiNrEJVJlAhZ0oVmb/bbBi3I9Ukao6UspLzgkkdStkHlVQ3n5LpHLrTaCvKiKsWVb7yX90rMvc0T2N7fCcRd0ninFC14lo5Xm1JnVJEkVWqb6dxICdPzpZcLTlLpfzK2noA6q92ADBtvSQ/v8iNObbnZZV2qaJEKFWlilKgHcoJ4nfz/rt8w2ju5jOH44G3n36OyeBa7W+tkbieMXZk8B1zo2wppUk1EdaV3nk6P5CLyC213QhFxkxoo3BONWNXxWvTShcUDk2vpSBlu+npuw6j5PY5OCuHmtNstwP94OmcFRAJBus8y5z48vyK0/FIzhHbGQyVzWbA5kjVip0bmZZIiAG16Batq9y8/ILjLy6ZTmf+w//4P3B88QW2JrRpvQcGXO/Zao0KgSmcIYqBz+aVw6vP+c6f/Vv8MLCsM9dvXnK4vkbFwFZpdFyIIUBKkvXPMDhP8ok1xGaWy00Wb6+3kkyrbnEIAcloMQwq1aJIlVQLa0rMQW6T1jliKqRYqClhlGK0mkEX9h3sNj0qJ1K0zURTsarizD3WUrC6qiSW+YSqhZRFYhY1oICyzbwkef1aK2tIxCQNfLneryfEsIQSGVA1b0CMCWObLAgPVZn92FFzotSMsZqucy0qBaiKQbGugZgS1jgB+rQObjH2iWHPGiM7Y3l+inztHNXIoNLVUfwHRlERk1655wN0PTI7yxd0HHseP3lEKLdixDK6dU603SJCUtRVCoFyjMSYsUNPN2zu86rSKFgq1clhusbIdJo4h5XztHL5aM/+ao+2Am9JRVGU7DBTAmd1W42Ihya0auGaK0sW4FbfeyI8rEgSFeMV48WImgWUU1KhhAKpoGttB57ctksVFSEGMU/OyyKY7U1g3O2oNWGd5fHVhmk+0jnH1eUzrKqc7u548+JA7xwfvPuMUhX5dCAdjtI3MvR4LOc5kNYCzlPXjFoimwDvqp53rWVTCuQFpwzOW9ZQWNfMOcIpVVY8c11JRoO31BRJITz4UAxKqJbGkNAkDKZqYoLOWaoyD4An7yxdp5jWI0bBvpdim0ph3DhpfdSgcqSqilGJup4oBMhya+y1xBLNOACKaV05zBNzMMRiOMfYdvoVU2r7rCDmsiqDRsqIZ0tZYmx+qCrffynpqZScWvdKcw1iOCRFniNaye+ZrSNWxTwtsjbCs+RAiJmC4bysLEmSGDFCLFICptdI3ynGTjO6Huc9rvM4qzE2gVoxBrwXdEStkel45E2LahvlKd6QjPgg0KIML2tCqYIxgtezrY53M/SM3rOcTpzPZ5JS+GXDZolt0FU46+TyUzRhmkhxZRh6YWiEwJoKzo1oEznWM67rJCpprJxrRvogUMIxMNqQqyYHS8VDlna/VBPO9A0p3tJHyjRJX9Q1Zx3DMLRn4sxUVowtjF4R15XTfJRza3yKqVuq6ul8z9AH1uEsvjU1k9ZbDscZoxy7ze5XOwA0IaL9Xy17PlPaVMJDu5zEYeBh0lGZtSSU93SPr3jnm1/nvU8/Jc9n8t0RFRPjthNcsK5YXTHOMnYdMUm6YF3WhsOVvf4aBC5RCg+ydXlouRP+ek7iZAdRJ7y1bC93eO/bQFMwVmGUIabMfr/h4nLLZjfgnCaElbis7baWWKYzOYgBxmiFrTCMPQ7FFApJKXLRnOcZqwxPHl3y6PKKv/3O37Dpez796Q+I54mb1y8hzPKFH3oSmagqzmn6vqM62Jwsy6qkVnM68+bLzzkf7/B9h6Iyn4+EecJQqdqJzKuQzDjQOYdsAxGpruVtnbV432OsmMWKAaUlf3zfRiUmLjFDiqNV2FOliudDKaFgqXpfaazZ9o5Og6sJ34Rqq0XuTKVI9TByCOci+N6a5caiEO76Mk+SIdddo321XTxiNM1FZFZJkkgEz2jzVdqgmXG0MdhO1lVVy79TrfcBZQTgUuXzErP87s4YtAVnDFU5TDKNRmjIFEFVgxDUjOyqReoXz4GycrvOqpHM2qFsmkk1l4LSVpQXJYNRKo122fgD4iIWBUKil/IdUm1dEUOkxkzRkqbIOXM8HrmdDyQFeE2/HdHGcZhOvLp+w7xmdKfYbPbSJ5Cat6bcQ0Zkt1iKpB9kFtQo4/HK4D3kEIS3oCV+mHKm73tQmmme2O92dGOHMppliizLSg4ZVcXJT434rpUpVZGRTZuehmGgUBk3wnsPJdJtOh4/vuL2AJdXF2zGUT7VFqYwsdvuuHjvHdY1cFcCj8eBzbihtz01Fiho2fUAAQAASURBVOLNAV0SyxJJd2fcTaBn4HHvuURBlVWiNRpvNMk0FTAV1lLIWlFM5HYSOThr3dQkTUr35WEQtbjpYylshoaFVlpKl3QlhcDOgDMdg7v3NGiWoDBOKs2d1tQsBlvjxG+kVCGFhTVnUlvLOS8oWmVFmeyTkWROrnQI0tblwhojIWRiquRE81iIpyqmlshZAkrrtj93zVejiEWxBrlpyuuhyFNkKkj5F2LWU0bMsvffp/MqoDe0YQ5SqJWy3BVlO1AxVr63aIg5cXu4Y/NW8+jRhqvHV1xc9oRwRikBBwmVM3C6E+WiGkW/HVhyZDkcyDGjqySFUpJ+js1uy2YciWEhrgvXxzuW4wljNElb4jRRCnjfoZWVS0GVro9SZQ1S/7+0/UmTJVmanok9Z1bVO5i5uYdn5FiZlVkosIFuEOCGXJC9o/SKFCGbf5E7UoSkCLDihmR3VzXQjWoAVYUac47RBzO7g+qZufjOtcgCNwFhwURcwjPDPWy4es/5hvd93pRpRskOb5wZ6VLpSVHrBG3GDHiT1gZtLNpYARrZGY0kR+ZsiA1yrjgTcC7g3A6URStxLtQmSZxaVYxpA3etqaVRSyRuEryk/YI2z9IYqAO974GAUgof7tkfv0OYPK2eOLUOqmDMzLy8+fstAPQL8kp4xIydqBqimKGYGL8QJdmIM+zKUFTDTzNvv/99fv8f/Iz4/j3vRuxscE5eACXIV+UtRz1TWuXpchkpboYb6KKOkZbWZoimGjlLnoBGDnRaFVV4Fa8/HnzwLLudjGJKFjFUU3Rd+dGPf8iPfu/7pO3M8/OTKCodzKGh6hWalpxnLweG0g0/KyZlWJYdftmDcuynZ06PG7p1tnRFe8N5PfGLX55o24pulcU7bvjYUjLojjJ7fAiU3pjniV3OlPOVlDLrdQUlO1NnFK0WnHP0XMTmZy2qNFLayEnEoQ2hH9Yqu3M7PLfOefk5jvx3NQp+4Sc0aim44IYKXaJyb6l5MvK2IEJznJNpyqu7hdnBFCShkJsf3tqxjhn+ef1NCSl/gJdRfWuVXBtmCmijKa2NwKYm+hBrMFlikHuVyxGlxq5aHB6lZbm4B0yq9S7/fa0pJdOqPEfiq5ZOLhZ5lq0Wi6L4n0UdrYylNdmtKi0CN7H4lHExS+XblUY5UeT2fntfyOelSVy0wNk0pWW2kRKotSbFjbRdZZHcC5qKHhzwjvxdrCbGQi0FO3uckQTEddtotjPdHdBapibn5zNfvvua98+ZsChe7Y48PNyLOLHXFyZGGxwDhXrJDzDDCaKVkSwPo9H7BWctMWZOpzNQmZSm6U7MhZgTqvVB7hRqmR4BU8aD2ntUkwux03Hes+xm2QV7j3WW3X7HfJjJNTMdZl69eoX1hsNxJ8mGRjgfYVo43r+S7PbWOd7dY30ghAmDppfGJWfSx49cHk+op4zPsJ8Njk7aVqyu3B0XlsWJcn3L9C6RwqZkSoxsW6MYSMgkQN3gXaVhZJMkrytN9sURgtVorJw1Q7t0e9ad9dLhakvRCdM7OhfqEHYputw5DCtb7+SeuPXiOlvMFsEIn6RqQ7KK1AvdeabFY2pDbRvOF66XjTi0KdZ5aFCiOE+UkgmtNgIN011s13GV4mFseVmjEAJ9yhLMNgBgN+pRa53aM9ctknIZ4k9N06K5MQbCiPV23mKMFLjaKq5x5f2TwvjG/hiEq98yKV5R2jLNDqXMiwastcbT4wcBV8VC3BLOOHbLgbCfaL0Lqtx0YklcLmfiZSVvK8EHERnmQs2VeWp4H+RcGWJwbwMV0SGVljHa0ZSipEqLZ+ziqG2llxU3xNVKj8AwbdDG4/yC1kLLrU2Rs6xUIsjza2aU9lgzgXKyrikZaHivmWcRSWpbaSpLrHSsWOXonGndkeuCaZ7eZ2qr1KYxZsEERSmBaVLcH++Y3JG746u/3wJA6Zt1TsYYdLERjSk8cHvoX/7G7YwfkJ4GxnO8f8X3f/ADvvrkb3j6/Ldy8JVC70UEJi2jemHyjjl4zuuZ/X4nY5mUMIN375yn1DwyqkXJLEEcYscppQ1mtmZZPGEOLxefcwblNKVFwuT50Xe/xz/6x/+Q3ez4xS/OlLwSnGFxAdurCMW0Y7ZBxGw0csvkHnHesNsdmY+vcH7PsnvgN+Yd796/49df/paf/P4POb59oJXM09dfcHl6wnZQpbwgQe14GUotbNsm4pAQ0NdIyiP4xSRiKViN5GMbPd7ICjUskk0JR7r1zul6IRXxDHsnFCtlxGNWxyVwszPdLH61iggs9kypSUJlWiVGyaanK/QYKxrnsZNnWRaOxyOza+g+iFylykjOfhPFfHtOlFLDmSSWPGstrTusdVL554zphj5U+pJypWnWEnWilNs+c6wLGIOem/++NpQWWxFaC7Fr7GZzzjhvhspdjUmV7NVzLkIeHB7Q3sRSqBBKGopRDBTQSrQMRghvN/ynVmpEuErewK0QMEYCTEqWtVZKaVAnFSlFgS8hUc7WCsGylT7cLwUQVLM1opbvNHoteGfw+4VwONCs5rRd+fL91zyvlcPRcffmyLJbMNaIQrkKTa4rQWnrUSCJsl2QzyGEwcgoQ21tiCkRYx42JlGR0yGEBap8X9smxax1WnIFakNhORxmCcRKljkE7u+PeO/Yto0UE1Yp0e4Yh9UK57xk0YcZrSw5n5mHnmLZ79nv92O1o7n3EznnUcCInqEqaLUyKTgGwyfKcnCGniM5b4TFstvNQoXMSQphbXHKoFoUFkOGaYaCrI9KbWSlMV3JeL1J4Iu3Q8CoRL9Q1aAnjuS+UjvXdYPesM7SbKZn0UbdVgoYN1ZQwn6orb4wBzojrhnkAksZlURf0rqRtMbWMJUX3LZTcimhC6oPVn3rL/ZMho+9lQZaPOa5VNYkM0NnRtZLGQmZvVK1dMulMciqsoaqTcSBrUsB5EPAm0xTEi0d5oD3QYBgJVJqxARN1Z3ztqEfO43K4/NHat2oNbJbFnb7ZTQtFj/N1Jo5XU7sdwvBOuwEdNFo7e922ODpSovjJjsWdWS33xPXlbxFIcmWRkpJQubGR1PgEMuwRomNLzfUQHE3RJBb4go9Qt3owWKtJKL2ZkQDVw05nwAHyqO0YzKBeXZct41SN0q5UnH0bmldopLL4NxYq9jiCC9SokspqhIvz3CNYCLWTbTisSrQy4GcpIivzdJqQHXNMgcOi8brPd5N3+pe//YuAL4B78jvh6CBW6V285ffyoD+8ltt/BjTJvy84+GTt9y/fmDZzSJeuTbZbZZC7hXVC3Z3wGmxyaRWSSXTN4mOVFrTuxlKR/HpG+OHDa1KElUSDKvXnTlMHA4H8Yi2gjGWV6/vORx3PDzc86MffhfrFL/99S94fnqH1SLMU62icmUfHLvgXkJoKmCVx3SDWgJud0CFmeYm7r77ht0nP+aH1ytffPG3/OY3f8vh+AM0Srr7w47L8zMlJo5LwBknSYZR7CvrGjHKsF8OrBH69UoulXK5UukDnpPZzROTlb+7pSIPRIfUGiXJHrt38V4bo9FN0xTkOjo1BNRyg4yoGxBGKbYs3WYb4jc1xHO3fxo9YoetcBKCszjXaLlQa35J4HvpNvugkY0VDqNrV0oUzIIjVFAVLRVaj9QqHSsIr763oeJEjTeflkdsZENoZTFWi9shyq7PDMGaHPLIyL/eBDtgtcU6YS/QZLUj36cZ9sM6wlbMS2pgVwLUeQGZKBHB1Cp2Nuc8zjpRzTd5n8h/A7btSuWGRO6kPOKDB2/iRcDXGTqXRi1CfzNjgoOS+N5pTLPMfuZpXSlac4krvSmOx8Dh9T1hv4CC0ofvX4s0vI7XxFiN9RY3jgHvhIxXWyGnKvqPc+R6vdIb7JadjP43wSTvpwVnEesqNzunkPEUMkpeJsc8G+bpgfvjHd55LpcL13Wl1IopRVCv0aKMOHVaay+rOms8y+4AaHoF5yc6WmyqTbQI+jaRaJVmFMfDnoWJV6bw5jkRcsaimHeOyWtKXolrxYWJ4/6OqjSPa8L2zCHA2wf4Kg8M6zjRCp3coKaRJaKhOAiTYd4dmJ2llyj2stxgZDdsOWLQeN/wYWCHnccaj3WOpsbkrTcKjWYszShZpCn1UgBk3citcV6v+CZOq6fnK2kt0ERUuzjHZL0kzg0tQsqRNTb52ju0LFBZgdf0wThR40zt1PYNRAgNFctWhNyaOyjTKSPfpHX57yp1s4gDxmCsws+BaZ4w3gpjA0T8qSolZ0qXyWvulY9nJSYWA1td+XhZaa1wf3/Pax/QaB7uX8u9oDTLsiNMEyHMGD8YMt7jlcJNjpwkoVGi4zdyTKPgrBJot67ybGkJnVIuYIwgyXuvWG9Z5gWMhMpt5UwrUWx33aK9QsnbFeMdugtZseRO6w4fZsLhFXM4Ap2CxDVXpclVJi6qge0Gpf3Qx3RSEhaH6pVSN+CMNleUWsl2orkd3hyhyZphWrzY6MvA46uONw7DgpDA/p4LgI74vZWSYkDYrqKEunWTL5uCscPsSgtBSkk0I16zHI8cXt0T9jMlb8x+4fKY6SmTaiRdskSqes8cAqfHJ0qpODsET01+iK3x4jVutkETP7nR31ilaY2yreTgCLPHW82ruwP/7J/+E/7J//wfoRR8/sWv+fM//Td8+cWvMaphjUL3jDeKXgTMoxAfsFIGbS16crgQWBUkF5gP9+zuP+XNd36PT97+kGkXaOt7/vn/5f/MX/zpv2PnHbvjgdPjhxew0WXdMCoRUqY2cN6jtWWaFtYkE5YQJmyYhuUxUXob1Dk3Ao1k1xRTYUuNdctsMTNPnj7G5LdCzChN14j396UrH7S2wdMGIR6WWl/+vUCEBvlvhJLc/t7NT99NH8KjAfERjx43Gp+M8yUm2Q4Nwu3fi8VQ9nE+aGqX5ylYNwbVkitAv0UCDwfImAAoZCdnnIz+a80ocwtQkV27Qo2x4o1bIDt/7wLWaXot1JxGEWDk9K/9mzQuBdoM5e5AJYsAWIQ8TSGnKn14qaPYW8d6QylFGfkWzjl5w5cku1ojdrVuGq5Dqh1GIqaQ9BjTLNFpeOuYdwsmONaYOJ0vxF7pznD/8AqzOLo1L9OL1gUkVHql5iwgGTt8xtYOopm8v3NN9Db0H00obPO8E5+79S9K5lIa1/VK14ZehTtubqu3XnBerH7aFPzk2O8mfDDkGLleL6Scxs9TE7eEsuLGUJsipUKYPZfLWQiOOUvBqBXny2U8T0qcCrWyLDPTzqNaxV6uBGuYW+IexRvn2ZeI7hXrDM5Bb/LMOsT2a4xmFyyvjwu2d3TKXD6s5Cb24QbE3skDL32TphyOO+7u73BehJXrFukto8akxY6vUwo+KLmjgRozW5e8j0qn9Eo3oiXpxtG04poLW6vk3sldxMKlNx4vBb3JPvt6yZCgF1gcTMtM6Q2jLNoaWimkmIgFeYaMFptoZ6QOdomd1QqMaGvKgHoZL895VZBSJZVCrE2+xgpd9cGAEU2NLnIuWavwztG0phtxnZReqLqjnBU0MYpqDFFZKIrUOlPXTMYRm6MOW+DcDbFqnIFJW0oUjYAxDvro2GsCCq0m3BTAakyXMzr4QFsWSpS12/m8sq0bdbh9GvqFKKutkrWqkomQQJq6WA/tTEoVWoaaqLFSekZRiFZW3TkK5wHlmKc9noo3Ha8njLFY57F+Br1QmiFXTe1O9Ff9RjFsoCqtJGI6UVOilUdSO6NKwqoV6xrWS5GhjODrfdhRcqKWRENjzIQ14Vvd6t++AFDtd0a5I2a33XCr33T73I5kpeVdoqB1ERYJjjZjpond3ZH93ZG1rCxa03vF5UzKhedrwmjZjRz3M9eYqW1FVN997H712ON2Sq5UlVEu4I1jN83omqi6onOlbhubaji15/7NA99588Db13e8uj/w5Zef89f//s/41c//Gqsb2mpKykzzRPCzvCYdcio0o7DBYryHMFGngAoLd598yqvv/4TDw/d4/fZHLK+/C7pAfcU//af/lD/+7/4bknd8+skbthSZdgu9ZNJ1I8dKrQllElp7bPC0qvn4+JGnpxPaB5QTn28pEnMat0grhdVZlrDgXEBCfQHr8NoIzneM/cRGIgS+W5GmuqTlKYRaV3NDMhGUCNSQ39sb/7t3VL9pPkZOdS2kbSVGqUS1kr22HD7976SYlRG7LKsIhUHU/dpqDB4XJpQpKO2IudJTQSkpAHKVlDA98NO8iOT0mEuJzqMhkw3r7NCNKLQzknXQxd0w0jXoCNpUfLkyTRDhoIimNAhOWCuMNS/rI23le7qN/rU12LH/TK3K3q8m4nql9441UomrLmMHLSviUbwqCSdCgbbizUdsZrmNTu3m6FF6/OIlxGe7rDzHVaAjqmONZ5omujFsTQo47Sw1SwZHq228BiNq10DrBUElDydIbrJqMDIFmeY9rhRqloNbdUT9XOS9qnqhlYg2I7gKTWsZ5xTeySukVCPGKylFSh7F0UDi1iJUxaoa1huu8Ypxlv1+oSGTgOfn55dncVs3yW4okvlBl/G36hBz4nw5cX73Nf59wpeZIxNH43BN0KnOOMJk0UFYCjFGdNccpkDY37Mrhfz8xPeOitDg1bSQ/cz7p42v359RGJxTLMHwySdvmILn+fmRtK0j7Em6uNmOS5CKRkR2UkRprFKca6e3TG6NjpZI68HnuObGJUbWIvHUuXXSsDY2BarKSsBax27ZUdarXGpulqmIykI97RrjwJQkqxGlUW6IZqtMl3JpwzItYtXamlgzjQHtiCkTY6H0zpY7vRSxtRkBF/VxlSqAUgjGCYF0fM2GJoWuEeeN3Laaqg3X3LnECL3SayYEi7USxb3bTRRz5ZoRCFQvLN4xT45ylXAjFxxhP2G8oQ4Al/NBnDjGM/lAL51tlTN32RfWy5U8tA4ayDVivMYEiwthAOIk6aOj0coweYc3UFukkynpTEpXwfJ2AZLVIs4krSd0r5QQaNOEDl4m2zmh1cy0TMxhpvRA6Z6Oow8ap2wtG7RC3J64nipPH74il4wLVoK65gXvDnQ1seUIqgozRQXkPyNAKme/3dX+7TUAoxt8EW69jI3+f/7k2H9KAaCUiJhcMNiqUbmhnCMc9kx3R3reIG/YxRP0JBGL9kmSsSZLMYbX+l68r9tGTk52j1pLgtbo5PRAZVqjqc5SrYSDTFYP2FTF0TjOntlpPvvFz/n8N3/Du3df8+79FwQrY6zr8yO7ORCc7ObsFKi5UEDCaYIXGI91hOXIj376M37vv/hnuIfv0YpBL/cQdqjLI/39V/z2t58Rwszp9IhV8Mnb77CfAuly5fz0zPX5itEGZwNai5f96flEjHlwrg0xlWGZajgvuFyt9LBsFWyYACVpcrmijSPXBHQZl3deutDeRRthnRsOij5ilgUKpF52hQp122ffxjpNGOTeO7yWkV/JmXVbMcoKjeplXfDN/hsYI/VvfskzpV7+KepaQ8fQkxAAb0LSNlL1tNYIyl9AP3Jpq7H/LKI+tzI5guEKGOCfWwFi+7jkm/y8WCFumdYjb+6PwBAU1tvkQLgSnQHhGcI/NSKnXXBMc6CjaNtG3qLoVWLkBk/SY7TiBja11E6tRaZjKDm89VBil86WK7HIyBU9hIh9rNtobFvivEVqrVxLJHuFWsZkpTXZ1Sp5bU6nE9YKQfEmqjK3lUYXj7VzDuPsyLMRi5Qat0LOifN5paaC915sVA06Gm8ts7WsF8kpn8KEc4qUV1rJwjE3FpRw4rUC5zw9wHpduZwjtVTJDtAamy2xyPd1Oe549eoVxhhOpxPeW5Zph9YFrSG1AqWzmxfmaeHxeubzd1/w1W++oH218mkyhJrQteGMYZnllw8aYxRT8Ggf0EpEnlbLTt/6wKVMnJNgaXff+z7+1Sf89S+/5PTx51zXglci7APN6XTh48dnrBX9Qc6NWiGphjGd1ouMl9WgBnovojRViVku4Eqj5kJujVg7sYjDoGqNdp6mNLl0cm3sj3corSgqs9sdOBzuuLz7QPzwgfNacPNEK1LoCRHVoZwAf2obazC0TFDawHuP7q3L4IlaKkUVVOls20bMEuSUUfSqpBgcYkE1shiwXsbkShwAqVVIMlVMRUA1tltZi5UGAwBUiwQN9V7Rz41cwFl4eFjYb5nDsvHm1T26ZF7fBYwLUDOdzNQVRUfa1pEvwROUBG6tuaBaE7aGgSns2B8d5b6IPkxrcoys64lcVskXWGbCErDW08c3qJQir9fB4ci0fOWSJXSHfmOPilNJ5owyie5NyI2mQ9mSoJSzwqgFlkkcSspi9J6KGcPDkaSos6RMqgWqQpWOC5bgBCcMotGYlp2sXEtFmc402cF80AJG+xb3+rdHAfc2xhUitlCUQS4bVd24OcYaWbpGY4XV7DQli8/UaouxnuX+gcObT3j/9ReoVrh7/ZopOM7PJx68WPMu64ozM8s0cdjPpC1JLvtOfni6d7YqfGpnFS1FurEEoyRzfYPZaO6X/WCsV+LTI1/2ja81aKfYHRaC6oRpotZIzZbjfk8IgZhWqjFopwg+MM2zqIHTxjQvzGHie9/7Ee7+E8gV3Q1cVp4+f0c5f+Qv/+j/yb/+l/+K08cnsaaskYfdjh989/sEa/n47gNffvYFT49PXK4rpSiWxbKthW3NFEY61LpJ+lvw9JLRyrJtV7xzbGRifqZ1g0jJNCklUkpy+VUJ8KiloFTCh0noi63RB8mu1Spxu8ELfCen4RBQ9NoxTmO9F8dE75Ku12S8bYykAcbUsLPHektrAnjKJUEtQ0WsX+w7uUqalxoEs5zL2OvKaFJrS62bTC3cJH82iSCuqwF20kAbWGc9HAEDxZuz2Oy0MdIRAzFv403shj3Jyr5NK3LO5Ji4hE0uooF0VUrsT2UUI9q5odbuWGXwk8c5Efg9PT+jjIzUSynowSAvVQiTbuB1FQpr5GKPdWXdrmypYrwmd8VWpNPKDXKVSYdG9rlbEsvYliJVdSH6dREs7pYF7RyX6xV/txDmiUvaCNZLVnoXAJRzDuPty1RDGyEu3kSapTbWdYUmnTVo5nmG0NnWxPkk+1PVtaBL/cx+d5DC1CtSvJJTYQqWeQ7QqnRHqo8kRRFLllIkkW24S67XldAnMJrtMiBS2lDKgtVWBG1jSvP8/CwBWmHGWkvKiZwT2/lCOa98d+f5yX7Pqw+JEDPBWKySgBfVOsYH7OQI84zXoMcqaa0V3ztvDzMqBPTrN5iHT/jVuyfWjx+xpTApJUCg0vjqq3d0BJO7bVlGhcaSKGwpYywYZ7BKBLsqCwHwFFeZQGhL63Kx1w5dGWLpXGMhTDNog/Mzd69esez2/Pj3f8J/9V/9b/mrv/pL/ui//SP+D/+7/z3pcuVf/F//7/zF518xr4USz3jVEdK5dOhVdWItbLHSukEpyQnRxuNGcVpGSFvTHesCaMdlS6zbUHc1WUW5yRLmQKqJ65oxXjMHJ9HnueDmIJqmlMkl0ahMU8CHmTVvXLZVCpBSh5hbIGrrutJqFEeU6rx7uvK0Rh7umuCBtSWWEx/PCWdkJWsdLDvP7jCzOyx8/Hjmet6Yg8d0RT1fmecFHSbKIMEp4whOhHzH456uX/P0/J4tXjltV05xBWVGwFnHdD0azEapkbSdyCmO0CzLFOwIBMvQYVsz1zUyz5ldbawfP9L1TK1wPj2iTOBgFtx8xNiFVDXgUUpJumdL9K4JoVPDQrCBFDspRnK8Zbo4vPGjuQ4oM9IMiWLHH2yCb/Px7QuAPGKAadCsPOwa1Mv+/3bxixJfKT2sg0IN1Ep8k7lVjJ24e/spb3/0Y56fP/L+s1/TJsf9J59w9/oNHz584PHxUah8YUc/Z3Zz4BoMvTdaiRL20or4i1Wn5YidLIsXPKObPK/nmZ0SiVNOQs4q50e2FlgOQopSaWVxjlYTisrr1w/sD3sZ4017TDDkuFFaoZKlc1YaauL8/h3Pv/ktvjl+/cV7PvvyPZct83xeqdcTp69/yfP7jzilabVTc2M9n9jWC/PxyMP9nYhBjOOrr95zPp/Z1kTMkg1ftYi0vDGULqTD2gTVNYVZInKdE1RnHmAJIdNwi7hVqo8d+Q3lrATXOgKNpiC7olIKOeZhcVIYZ/FeLC+9NfFOK2Fk7/d70mUlxwtPuZKzpu0D1oqdynsv484ij5cUg0ZS74Z24KYJEMiO/F5ECDLe7sjI0hixdhpTUa2Oh1u8y7UItlN2sjdvrkL3jkWeRTO64pfKOWfx32pF8I4uCS+4MKOMlZWJYnT/HcES30SL5gUj3NXtexCY0rIsYxoxLjXvXyYbxhhSKkMfo14u8y2V8VpLotxWGlssbLmSKhJq1YR3UItgRm9Cytoq25bpWtTq8XrhsJs5LgeaN8MTnlBGEeNGCIHdbsd+vxMh4RAF1tZIMY21ShUgTJNUP4mPlsvaKvGMO+dEf1M6vXaeTk9YYKcmQgjM04K1Cq1EoFdrodaGnwLeOlKsxBhfrKfGCHFNo9Fd450ftjFNWhOHw4EQApf1yun0NYD8mcmTtsQWt0Hla7w5Hnn7I8MP68TrrzZ82dC50lWmaJkWVhtEZGiUnGVduPCmISJW0UmymxbOcePDF5/z7t0TplU+ebXjujXKEG0JjreRamerlUqnRjABObtGwFlXQp/sVfC92XpS6+heMcaDF+R1qZ2qFTVYWpj5X/9v/kv+j//1/4mf/fQPePfuPTFufPj4jv/3/+ePKCnzb//dX/Iv/m//Dy4fPmCr4ssPj7w97ME5tDWUWjhfVi5bIncpCOSeasIycQonu1xyK2QZGQg9VWlya6Q2VlYdjJdwp0SR6eMQRdYqKyCA63plS6C0AM6UGr3xZPDzjDKOlDLTYeGHP/wRxjh+9ctfsZibjTaLoydvbFvkq/zE+Zw5LgKIW+aEtwrVM0pVnFNMs+P+1Z5XD3fMkyNeEpOzzM5jTIZu6LZjECy3MQ7XHCp4grcc7o5MOZCrFHG1SwpoLqI7slhSFDFhbY6uZnLubOvKGirLPDGFedAIL0MorrheV3EK9UKJG+dYaF0z7x6wU5bVr5JJkqzH5fzTWibavQkcL61XTG+UvNJrAlNQan7hvkihJ+vPrjoNsWr+vRYAvQtW9Sbuk43WeIXhpTqXSF3Jpr4BI3praGtQXVMKNGOZX3/C2x//hPP1zPPlRKEyPdxzXBaaVlzWM7VmURm3DaMr3mlKFrvU4j2WzrUkYhFxSIsb2ktAhZt3HKYFzhvpesHYirfS4ei84pvFFJlmHO8PXJPgbV+9eRACnLXsXu2ws+b56ZGnr9/zfPlIzw2rHVM4cl0b/+bjhd3xTwlhj+mwfvk1Hz77nN4rW77iamOnjezwEzx/+MD7L79gNorXr19z2C/s9wvQ+eLzr4hxQylLpwu7fwjfFGCs5KtbrbBGvk+j5XLJJQq8oo3XQytBKfeKVbLLkpdKsu21kl2RNeMR6GLkbIB3Ip67iXqccxgjE4CSpaOTnboUFB0JBzldVlprHA97vHe4IFaUWgu1p5GG1uhF4Bd6rJBqlQLSDO8vKIy2ErhiLR2F855U5fKwThK5RtITCkTJPrzukpeuMU4uf7r4j5UahMPW0UboLDcFtDGGIk+0hAMZmTLd3kc3YqIaCYrfFDENpSz7ZXkZqasOzX3z1uqI+6KPrjrlKhd9qnREq7BGoS1Kl6YlfpsRHWssNWZSKrRSxugWtgTHTwyffv+BM0lG/RrO25WtlyGEHLHb1tKqTFskWTBjrEGb2xpPhJ1WuzFirvKeL5VeKqXfVgeamseKpndKF6ugMla6Kx9wTZTJqjdc8DTXmP2EVZZeEtYY5jBR4zB20F6YFZ0KzVMyaD1zuayAWE9bE5JnbZ3tekI3NdgFll2YOFrPrHfcfdhw6YwdPztrZbfsrPx9ZW6Kd7G3tpwxTRDJWUECssk8XiOfnSO//XAias+834NrXFKiIh7vXKtoP+hkoOpvnhVhKwrMpylG0VCJvUl643iNWxRYlzYCi9otB3720z/gf/m/+i958/Bd/tv/5r/nX/zzf84vfv63nE4f+eLzL4lr5o/+X3/MeurMBnSGT+8Na67QlDQ7KXPZMtco72u0fnkPtmEh1kaU7y1lUmygG6hMaYntOlY3RgoY772wJMbXrlSnlE5Ksr9eFila1XDh9qHsb6WJ7TALSM1rJ0FEsVApeGtJrVFbHrqYSimNGDtr7azXM5dzwhvLPEkHb4Y3w1lwk+HxtPF0Shz3M4clcFxm+qzozaCDoaqCVgXnAsbIOaDpGCvaC2MMeghjuxrOIwxaObyZSHFjW8/kHGllI6crOZ5R/aZdkFXV6ZJxwYNySAhZoZQz1+szT+cLzcAn/ftYX8ktjafGDHtgATJKFZSS3/e20eqFXgqlXuhsKC0TK3FsGCCA6igyqELvItj+Nh/fHgVsnBy6Tfa0wgAYoqwhBdH6m93v734oQEsMnRyASjGZQHj1mlc//D32X3/O5d1XXFG8Puw5vn3gfD2hzUfoit3iBU+6erZrxulG8NIxRApGic2rbJGkKvPxwGxBlY1SV4wu7CaPc+IbNl722ClvGCc+eu8M3RtaV6y9cph33H3nDceHHffnV7yfZz5+8RWndx85fXzm4/aI0RMfP/uA95/z/e//gNcPD2xl5XT9yJoiU/A4LW+exUB1UNbK+68+Y3KdeTI8PLzh7dtX5DHG/OKLr9nWVfKgtR1cePUiPdbK4pwWfPEQt2mlsIPvXZrYim6vg0Bf+svevTVJzDJadrgdGf85K8ph2V1DHt25uD6Gfa/L17JeLhgl2fNOd5QZnU1trDGh9cqug/dOwE5Koi1LqeSRUmWtE0W/ktS424NSSqU04QxIyplwDdSAQbWeRTGrZCKlrHn5PlECL+q945zFBRl/k26WR0stooWQokYPIJIIE1OR6E2nFN1ozLDk9SY7TzvaHHnub8Af87LjB/k8kw90LLUKpaxkGXfGXklJLv9YCq0rCR1Rmu20seVCbp2XzIImTofrdiVfZUfNkEYED3evDD/62e8T3uz45ddfkHPimgqP2xk9BdxuFt2DtVgjdMUUBTCjWpepjrNSBNBfDkJrtCSLKU3VhRjTi7Ojd8mkz7miekUZR7NCaVzXAsoxuYD1TrDLJYloLTVKi1I8Dt5EcJJGl0uipibwm15RvTMt4m2+PJ+gNmzwAmtSihgj2/XK9968xS0TdjJSbMRCKJ309Ufs+2fmXLDWE6aZEDTWizWxN2QiU0Ug1nLBGkOunag1sXfWXDmvicfrxuNaSAZs34gFNiqRRmqVWLMAfZyGMeEqqtOGvbUjNoKu1SgAoFoZ/VclBMKaK/vdkZ/+5A94/fCaz3/zBX/6b/+cv/h3f8Fu3vH08QOPHz5wOSd6h7u9QWVFyZ3vvj0yO4suFUqmdM15jbSSxfWCA9coscpzaAO1VxodpwzaehEuxoQ2RVZetbBlmSoqC84FVC/QRKyntWKeJoyZWdNKXLN8X5WR3wJuLKB1l5+1vWyorXPdoqxXzyuP799jrMVPk+i7SqTXJp+nScF305hfrolzTTgN3poXDocPmjA5zpcTX3z5yPGw8INPPyHeN64hcdx3jq8cGCPNQa90A6k20mXletYYb7EOfLB0LWwCrcwApwW8m/BhYrfbySQgb/Sa0L2R05VWI52KumaUmQb4RxqUnDaeTycenwT1PR/uqH1DqYzM7srQ5wyWDVKENRKojLENberQvlR+h9w2unzBT6ub4wstgmP+vgsANSwLGGgCOrl1Dr2Pylp9owj8hoimBRw4CgCtLZXCtWbwO+4+/T7f/9kf8hsgKkvRlrs3rzGq8eFLz3pesX5CqWfiulG2RM/Cvdet4vUIXiiyazW9ovJKV2KhWaZA2O9Y5nkA6jqH4w5tNR+en8g0CRnZLxxe3eOPB9x+Yb474nZ77u/fMLuZtmbi88pFnclb4fK40UvE2xls47fr3/A+/AJNxdYTtkUuZ7mgTEnsHOCQoJQ1kdYn1vMe9WrPw/0DznxKa5ktXrisH6hV0zAvb6iOotZGyxGawisvDosmkAurNH343kse5D54ITjeyH+aNjoT6eB+N+XPakNzjut1Izg3xuaDMBgj3gamaaImGe+1KgIfoztuloN28oZSZA+WciUEYW7XVqm9U5p8ToPwAICRStdQVeyHpXaC9yhriMMiyejUl93uGxdA50V0eEv6Q2laFcxzCA7b5YIuXeKqtdW/U9BI0aC0xno3hJIy2SgDeHKTSOvfEQWJu0HhjORFWG2/Udj3wQ5QerwHDFp36aJzI45LvnQjnWPuEkySJXRJVdGqpJqIsaEaeKNwXhHMTf0Oe6/5wfc/5R/8+Ef8dn2klMxaE1uTYJEwB/IIITrc3aONE4xt6UzTNBIiC7WXcdgOjsfI8dBIwWOsppVGqiPYvjZqjuSYKaWwdVi9xV+FB3HYLTy8OnDc79C287x+JMeC200E7yg9sbUrVhu0N2w1QZP4U7AYNMF77o5HfAh0rbg7HvAhCNwqJXa7Ha8P97w6HOgGoiq0LaFjwm+JviZIWcRsiIXNalnVJKCkim4Wa7voKooUzluDzSg2pYkq8Jg2HlPhomBtjbKubHVgv42siqqVll9ZS7dWRrLmm4jqUos8q8a8QIVU7RhvmbyId2OXryFer3zInZ//1V+Tt40SMzU2aurcHQKvF4vqlZ4bd3cLqWTydUU7j1WgeyflRl4zpXScbRjnyFWJrqRWdJNpqVYd6ysNRXBWKKQ3p0GXW9c5EUVa5+hJJoIdcJNimUWRPmfHWZ/YUhL0dwXvYA4a5/Sw1xmZZDaE3poTtSFFXitcH98JLbNJFkFHsmc0w86thF1RJKRUtERjNWGMwk2VrmWKMs+R06nw5uHMq8OOtw+Vx+cLvUtI0LIc2C8Hgh/236Zo5yu7w4TTRiYWtdJUh5bQXX52MqiSSVUrHYOTjBlvaG1C6cobF9jtD9RecEFcTtt65fHjB66XE2ray/RhEGAbtwTbb6zactKPIqgWqLK6UoM3IhPc24p0FJjYIYgeh6LiP8UKwAy7lHh3hwkaukYrKQBuk4Db5S9jCcGa0m4KZGFmt9og7Fi84ff+8B/Ji3x9ZOudnbXsjgcuz4+slzMlXek14Y1E9FIrwYANC7omLnmjGzgsluMSsFrhjWKeZ5YQmLxHI4fwNAU+eX3PNE0cjjv+9je/4nq9sNvNPLx9yw//8A+4/96nNKO4Pj9zeo7s/Y7j8pp3+gPXc+VyrigCYEh5JOa1SowVYwshNI67hfY8vM5ZgmM6MDnYzwpvO6fndzw9Tex2E7uD55NPjjw+veJ0vXL6WqItS9eEaZKOtStKa6TUOJUom6MhmlMmwPg5v/jwB3pXQDYKO3zfzt4urIIPchmkUii54KwVbYTmRcj20mEjWhAakjRnFL1KHLSyVroJrWhI17htGylJp50Gse3mKpA1kX0B7tQisBC0lkXEsN/1UgX6og2myu7xBhlStwvZ6FvxSx8iPj2segaDcQ09gFVq2M8k0EbQv8EHKRacoTQZs7cqX4/WWlIB+d01lxUQ0mDkA5LfzU04x8uOWymFsY7r44lrysQMtUkE9bplLpdNLv/cJX62jnVWbhgFh+PEw/6Iro14uXI9b6TcuF8m/rOf/j7f/8EP+PjrK94ZYpPCw3mJR421vqj8a6lczyt1sPx3u53kk5tvDorWOq2VFwEeXaYAzolgrTdRrDvnSEmEhaU2WpSsgqtqxBhH1HTHa83T44WWEne7ew7LgZULzzwNr7ih5EatTuiPXeynNVVKqkAUzU0TmuXkwtAjGKYpkOJGc1IAhF4JrWO2goqSAmi05LXHlKEW5qZJFWJeCcw418mpSqfZDFvvbMCmNV9fNn79/pnfnDvPCtoEGVjpQvDUCuXHqkhrSeXrv5OopxWldrHZIeeRYuy5q9hcKxK0U2Picj1xfv+E1SKCtEozW43be7w27KZAyYkSI2FypFLYuYCaLM/PJ/TkccZzup7oWc6FVqAl0RTVKiyWmvN4XcHazK4WQpjxIchkJUqaIErhgxU2iXG0VihNNEKT0Xg3QncWjzOay1VWtlsqBG9YllmmcN7ivcGqiqfhrUFZTa4JE5zocXqW1YJR6DB0QzCU9p2OwppKcV3ez8qSt8r5kriuHbVmtFNop4i5cLl+5P3HC99584qUFbPJqLphtSGEmcPuyOG4Z5lnnFN0VdDtiFVaYE19xIWrTlOFbroUy7nKFBSJmpciK8h0rWfcbAXVXCNKSzMQzxd0V8zTDn84Dg3NaMhGCqtSjo40RUo1tGqSQpmFwlpLQ/dbZy8kT8l4EC7JN83+KBBubq5v8fHtC4B2Y//pF5uf0W6MQ7+Z4d52uDdgiOoNmhJeOH0IYgzdBrFRdMXxzad8ryaev/g1z1/+lms8oeOVj0+PPD1+EOVxU7y6O+C1J16LJPq5gM4RXVaCnTjsArO36CYj/f1hj+odbw0lCYpSqHsrSnWcE9JT1xBLptA4fvod5j/4GenpkcfffMmHn3/Od+5eQc7EUydeYLsqtLIcdg9c141zjSyTxzpD6omiO3uv+N733mIxnM6Wjx8TXTWWvSMsHkPlcvrI118ZQnBM857eI8dD4M2bI4/XxiWKmv9WzBlvRxcPJeWhBZBLSCHjtt5EVR38JEpxrfCjUzXwkm9fSkEbMy62fivnqLXL4dwqLRe6anhjUU5jxiVqrHsZFSujsQ6MdbJbTh1qfxGTCf//d+FBYp/pw95X6y1cRMG4XFvMskvUMubSxqKtQudEa1XKTNWFddDBKYfxMpFSRslY2+qX59KOIKky8Lc3K6LTHu+FIFmpElmshOmuzG3lorFaU2sRz36/scBvY3oR/TkrFhzVhaSWUuKyroJKRXG5XllzEwBIq1y3zPm8sW5p8ON5sWvWIm+2wzLxg+9+ynFeULlwdYYyW3rN/P5PfsB/8Q9/RlsCNUVazdAbU3AiZBzPybIs1CwFWVojKWVOjyee/BP744HD8ci0C3JZ9iIiyVJpSlw+5mbnRPbK9C5Z62GSzmTSQzQo2pDTaWW7RJ7eP2FRnB9PLJPnsDthOnL5jZ2wd57DEHflKimauUZSirx79x5lxJ2zbRvLaY9xVt6npWGVkO86QqY8LAvHnMjb1+TLii8CKKuI/sJ1TbUSvnTeIsV0QpjIqdEQclhCkbBsGH797h1fnDrvM1xkiEU1ELWiW432+sVK2xCLaO6NMsSsSrb7tK5GPKsWkVeVEXbeIudTerFRu6Ht8Voz7SZMB4dCtcpkwKnO7D2ldkrKlLUQ7ibilihFrIdffHgm2E4rw5CghiUxAwO7rTRySXThigi1s2GslTVLFopev02Zu7yHQwhoImYICHuReFw3OeYpUGomJ4hR3F4lZVqtKNUILuC1ZlFGxHn7mdIyuSWqg8PyipiiZMFoJ41A7S8xuOKUkJWZtxNGB67nTGsn1q0M3oLcUbllYpII7tqeMdrxg9cTxylglaamwnP8SLpeOXkPqnA47MjryvPTI9ZZnBP0tJ9nlDM0I8JQPS5gNSznRt0a4jpSHiO1JdGbTRarHN5P3N9/As5RradiqaVDd3QcqjsRwXY9RvhjHVA1NStK1vQe0GqWoDSsfE4tzA259m8Xv0CRvu3lD/8xHIA2vvlxSBoje0WxslRaraPjly/ohTXfBXuokLFY5YaWNejuaFUq+sP+nna88NXnv2I9nVDbiY/nZ2JJWG1YZs9hf8+6k8PFqY4jszjFfH/ksJuwGlrZZAcVLMYO5jXfkNBiSrx//wGswc2BjoAmUol8/PJLHj//DLff8fzll3zxN7/g3c8/45fnP+Py9Mzl+cLldKWmSvCOp9NJRFVkUr5idGaalYhlSuX+9ZHFBe52lv2sMbayO8zkvPF4fmK3TFijqCWTU4ReOBxmPn37ivPWSfWZyzVT80bSYFQYfHwlBDsr41IhsEm37LVhMhozB8EqA95agnUDXHfr0hLWzfRWJRlLK9DiHe9VMstlvCVdqe4SdWutwxo/FLsVxr7MaDUCeQq0LCNGKwp4rYXO1RGBj1z84yJvnUobFAyhe+VWaSmRGXxzI+P3DjIW7l20AjlLV9oEMmLteGMINk+eW2RXaKxBlRGJPJ5NZzzBe1pTbClRrxfkLhiiIDkt5WuuclDK12+GkEqe55IyMSZ51o2mt8b5cuHx+Vn+u0AqnVwVMRVilZ3mZUu0pmjaUpWRZ3TE8VJh1oo3k+W7DztmY4hH94Itfni4Z26RX/3i1zx/8Rnx4xPGa6bpgLWGa5MxsJks23kDYJ73zHPnfD6TciLGjV1boE/Q9SjK5PtlFBAo4R200kW9X3lZg8iFYildQEMVSLFwXq88twu2K3qB8MqzPm3o0tntZ0IIbG1Fmco8T3Q8KVtstpRi2ZJ8bS54jJJpQ35+Zlom3ORY9hPH+yOLNxRED3KvPPNT45w6LUHPjdbU8KkLzKo3RWyNNSvyNZG7GpHLoguIxrBZzwV4nwsxKJhl/LwpoeQVOkZJnkW5Lb2HQFp6fcNkZXVRkcuUpuibEN5KitQuo203qJP6Nr4qIsO1WtI9dRf7brOGddvExjjYH372nE/PVKU57g98/uUTDw8L23Ullk4vEshjtBTFWkuglsLSKWK5U43aEr1L+NVxv8cbx/m8DhtffwlNC5LmIwr3EVtrjWHuQS76VqUQyJu89UqFmlCmYbzGNiGFdjTVZIyByRvcFDDOkGuQ6WHXowgV+3IbU+01bpTWJVhJe+xsoHRWL5CiVDNrjEJhVNAjXD5snPwzcdaoMONdQFloveGDf8Fvx3UjxpX6Xtgf0zSz3+8J0wJGsZGYd/L3S5ECx9kheLUizFFU6IIxd0HOtaI72lj2R4+dJs6xcdqKYINLo+vGjYSulBQArctaIlcBQHWt0Cag9R6tFpQa/BZud+2ofGj08fr8R9z//xFpgHhAYZQdfHkz0LFt1CHyEL9UI6O0Fdb8GE5opFpToGrHd4PXE65nmp64/+RT7j58StouXOOVS85MYSGtF86XZybr8Kqzs1WQnV2jjfhWg/fUmohKoBV2sSzHhaev33O+FHoVxeSWO6kWYcKXFaUdwWkmr0mP7/mbP/5jLr/9jOsa+fjzX/Lh11/y+OGJFCWUpY4dbGtXeofJBxZvJVlKKXpJcCr4w4RtislbDssdy9zpRIK3lC40slQVZlrIcVg8uhwK94eZn/zwLUpbfv3Ze07nhKp1jGe7eO2NJitG9rfGOIXvGj0H2bVaJRYeRndh+hhRN0G0KodzGmMVvYuXn9qYJ0/JieANxhrZQ6NH1y+peqr3b6p7a/BGbJElV3rLOKtQVuiO21YGOQ9qq1jrx9h8dNBKLFziKhABoF/EGpNrJbdKLxqtJXqzM+J1jcIbT87phQ9gvbD5S8lD5WwGYEj+P2PsSEcUZfzleqV18G6SCQRycDWaaFb0TTjZh/J5JMPRiTnRkLXX8+mZvCVSEpsoRvP09MR2C27RhjVF/LSwXS88XyOnUyQmcN5xKZVNWXLpuC6rmkk17l1nV658f37N/eI5KWilME8TpZz4+b/5Y0618Yl3xMOOjcYlbqhqaFpz3SKlKZT2hHlHmCdQXf6pK9oqQvBywF43wUFbg3GB1sRx4b2nNHEPxFzkPadHznxulLaJqqRrWjWkqEgr+KaZgydYRT4lPqpH9JsjS5jEKuwUlZXcBXilvMJZA2USkiVadDvG4KzBBoefHIe7HXcPR+bFUUpE987RLywXOH32nstXT5it07K4Z3bTnsM0oUvhks6cqfRgWUsmb5H9ckBpy3PurAoec+a3KbLNDnvnOCwzNSXWxxO1Cgq40cmpQFd440QLYv2wTYKuipIKNSZqTLQkcda3DAGtwHkRb8k6SkkmhJJMCF07SgssqtTO+bqhxqQvlyTRGTJKoOXO09OJ4DWXc6JUKDd9mFb4IAFOukshp5UdXbVAa3LaZEwejlLMKYNpGp3HqD8YrOsoCspKd957peTC6fRESjdrb0Mrz34KYlWrRbRFWwSV0ZMmTIbFeYIp+GDxQWE9GCOcAq0MsWRUSezsRJgmKdjRbKvmMp7RkjsBzacPR3ItnK8Xwfo2Q4obJRey1Deoa6ZuiW3VlJx59eqVJDeOXb+2mhAmmVbWSq8Ng6OmTsyR1BNNFyZnSSnzfHqmlorzXtaWVYqBeZ6YJo/Slct5w1nDbjAK5mWmaYOpSbgE2pBTZJql+VOui9bBaKmbukyTqiqgq6xu2oTSi4iyx2vQehto5ZuA4JupwH8oxP//uwAQkZ8oqfVt/Nm/2fkPH5kc6PA7Y4ibKGE4ALqgC2V8IlVBbn3EQB74wU9+itaN36YNMx8wuWBNJKYT8XpmCZ5lMpimKFuma+nKrueEC5bD8cjxYc+rN0d2uwWn4ItffcmHp0ecC0xhR46RmJ7pNPb3B6lugbRGTl99Tb2ubFvm8ev3XB4fqVvBoCXUpou1SCtZhqheyVtCWcU0OTSBnjPX08r5dCZYzXQXOCwLOTVKjqSSREhiPXHNXK8nSdLygtOdvOW7bw9oG4DOz3/5jtM5AhKnKolw8qBsWZS7s3Wy3zcaRyOphldevuYqPABrNEZ7urcvYUG9S7KbGRCb4C1Fy9Sk1S6ApW6H8KTinPiGlboFwKghGNNjvAhGD7V158V9IAI9ufBkRTTSG5U8hBmpvo2RsJ2Gglqp440pcdC86Aj0qIKt1S8j/ZTF9y6jRPFg37z5Yvv5JvcgpYRCNAix5Jdp1a22FkXueIKbaAVuAKWSRZcAAh16Pp0oWxKOgDbkmIipoGwA58mlsRzvOF8TT+eVmJrgP3WjDcRvqW0k6DVsbywajk5xtB2TzlhbeOU1zRridmY7n0VvoDVtjSxKMfkJVTZOg+k+IThXvzuCtSLcRSygfbxBU8noYevUWmyOwvEQWqRQGL/JdrjFRivESVFjgd7Juck4OjcsklOhkVCkGKVonIJnt49oB846jJVmQWuYXaB0Td8ixswc7+7IW0TpPvrqjrcCLYJGrlmy5tEYFKREvUbaVrCjUyxVRKf3r14TtGL94leUlAnzAZNPtFa45gLBsBnF19vGb1Li615x33nLbgn4eSJfzjxtG/Wa6MPNUpHiXysoMVK3JBZQJVMs4UiA7Q1jxCzbBeEBQGmF3GSsbbSIuBryurVeh2tABLFdqZeCdOiu0aWhmhIEdpVsht4ruXZJvJw0wRqW4KFmWswYVUUErCvNiBbG9Y5pBarYMydvqMFD67SWBeSUynhfOylWehcxYodcJIRGUONyzhskrMloxS5Y7veBu0Wz87CbA9PkJHlyckyTwznL0+MjMSVUifJaq4IqK60qlJX43EOYacGyxcrpkoj5GeMcd/uZ1jK9a/QhCPK8NZw2HPYLzjeulyu73czd3R3eW1or5CLnYgiedd1k8hkCWltSblgt/Ir9/SvC4nHOcX9/pOTC89MzXz+/Z1uFSbNeA3fHHcviUXRS3kjbCWXuabqgbcAYmcRaLava1hLaNiDTAN2/wbEbI9obP090Gj7c4cIBZcIowsaD8Dsfqt90d6L9+lb3+rf6UzDsXCM9TksYi6S9fRNa8g0T4PaF9ZcvRSNVjh2Hj0J8saVX5mmm5UpTkePDG2rZSNcrunTqh/c8Pl9QutHbiKTVbTDJRe0tO6vOsp95ePvAd777hru3r2RcumWeP5x5/+GRnDOKjRgTpUjBYOjsQkBZxXXr1Jy4Pj2DshynhTJtTKaBdsQoNC2lrIA7ckGw2CJOEQWr7EN7KXx8/14SrMyReVKU4ZXfcqZriwmanCqPp0e00dzfHVkWz2QN2jZe3c38+IefErfIL9MjtSSqVvTqcNZKIIeYuritZyRYAuhNlPTKIALujr8l2LWKHRc0Q0kq2jWZ1oRgaSULTU+bUfx0QRYPnG1vWgh3RsRwxujxAEqXIwjiOjpuNUbqogWorY5uSvgE7TYh6p1aKtpo8fgrXhSvwpdQ1FFo3mKg9UjmU0Pw1gfmU1kLowC4CQ+VEqhPKYneZUXRe6elDMj3x/g5yM522Cir/Dwzmc5NyCipikKhk4TJ3rv42QEbZpox5ALXmOhb5/mysaUO2qMtUAoli1rLj732rBReae6s4tU88Xq/4+AdFuG01xi5PJ1IcWPZH+jG4qMI3LbaMKVjexf8rbN064TdVeWC6DIyktVLq7SCiCyVGivIJuuOcbjciieQwrcjkBSa/JyXZREkcU30JoJf5x1+OLVza6QMJooFsqRGMEIqc12JtsM5KZ7auFS1whiHt5KVoLUU18s0sQSJ5DYK3DQxG8vSZ9ypM0KYMUpRe8U7z3TYYYJMtXwITEo0Fs5M5Ja5lkZ1cNbwVY58mQrrzuG8IlvZKdeS0V2ocEYpjO6k2lAto9FjZaRITYrNYMdz1EeR20GZOuBKosPJXfLmS+kD7CINUa6IVU0qUfHtI9AlOfTG4d+6VBNNjSmC6Hd0h93ksUahKOiWoGScaewni9OiiarVkXPFO8UhOGYnzzQW6ixeoZiUFKZZQr7meR6vsRZke2njbjAY7TDGkZIQPOdgOewCu9njnYIioDVjFdZI7PDULXsj7pHjJ6+JKXI6nVm3SK1NIE+5o/3CYbcjFsXTaSVuWYomZPLgtKEOvPEcvIi+lSJYh3eWWq+kVNi/2fHjH/4IGzwpRbYUhZ+CIJJr1xjv6V2TYqTRsMYTS6Vuib1z7Jc9rVS2NUli5UhRbbUQ1yuajDHSIKELHz68w2+eeXdk3r9imgPGQWuJUlaCPdD7yENQBgEhRXpLKKXw/kAthhDuCP6A0YE21vEa/XJ+j7blxYn3u468v58CYPittbodkCPicXT2t45/1Lrw8gt6bS8HsVUScqIkxJ1OZdsizsjhrHVg3t/z5pPvoq+Jrx5PaCWjdGOQkW9MYinpAnIprYy88IV5t7Ac9kz7PTWJ6Mk5x+FwEAV5E2tc8F5QpbXhtMBEuivElCg5s8wedzzQo2QKpNIpUQRMuUbWq6jaJ+8wQwBWYoWehAEdHOt15Ul1vK70+x21NOImvGtlNalWaldcL4naMsE5Jm+gNwyN/RKY/ANx21gvkXcfr9Sc6U4WfM5anDODVS9xw63dLHcF2zVOS0yu0QPYwhCIOdFhKG7xsB2UkcNXGarpY2cuimHjHM76AZSpqC5TEKtuVkP53EoPPK/SL2K9W1eJhlyK7E67ZKhzc8AYgzGauEaMdlgltj9hS4za8mZVHN59xsXch7XQWvd3nrtWq3j4b89pH0TAoW4X0qEmlzoQmualM75V0bfnu5RKjAlrDSGIUyFnsXhNYUYpTYyRWCrKOpRzbDHydL5wjZl1q5QCtUuh1Jp0fr2LwGtHx9SOyZWj9/zBD+75wx+95eg1pmZSzGzrRXgR2ybfrzGk1rmbd/ScuQXZO6V4yoVSOtuWqFmDlzE7413XaDTVkAClJpMcI8/LLXTpNhVhBCvRjSj08y3JUVOLRBqnlKTA7gzhp0xmugLjZDVYc6Nl0SX0JjZLM3msNZKGaQ3zvNDHZCU4RxsuIx8GwhXkvVYb5I7tWp71VNCliX1MakTs5Nm/uiMcdlwfE62DVlrgP71TsETduJbOe5X5IhcuQbF8eoc6LlQtU6hl8nz3k1fCI9CGlAuP5xXVFbtlZjftUF3x+PjEtm5Y48UZlEWYqcezjG5U0/B+JneNaiutFPqIvhY72Ag5GxOEPoqA1m6nqnxzsjnrUggguixrO8EZZm/oVezSXsEyO/bzzMNhIejO5A25SbaKUpppnnHeE5Os8PrECKgxtNQoY4VBk6LdadER9FJoFazVeO+FD5Ga5GV0wcTnXDmnTCGibUPlQtky0RvSainbxhQcDw/33M07grZ87E9cr1exKHqNnQP+7hVrgeuayOkMaqDpi1j2uhJ76k2wp5QexM1Iyhdar7y6e+AH3/8hfp5ovXKNGylHYk4sxzsulyu1CXa3GoVVhu4c5y3iuwW9CR2wyapyWfZMQXRWTiucVXQypSQUBTcBYw3aFSjrmMxEUw5lLmg909xZeH7KI61kptVIzVfRfODQasbaGaMDdCvuCH0L3LspAcakXQ211N93AXAbTXDzLPZh0Xjp9of4oPdRAvzOKqDLeEINVamw1DXOyD/7INapLqEYwXg+eftd/DVx/vVvOBstyNYuPsxei5DijEZpg3WBu1evON7dQ4d3797z7sM7Hj++5/TVB7ZLHFoEUdF7I/52axAzey4Ya3BAypkaE7mCmWHxnkil5ojp4k/NudKKvLFpXVSvXWF6QXVR2FbdKKqy9pVzsIND4NBNeP65Ki5xIzXIm4z2aYxwDJiDoalGUfD6buHTT+6ppfHxaaPENGw8egQIiboZJWNvbRWqtpcYY2fUEOSply5NKft3SHxdSdqa+MMjtlt0UqScMRpCcMxjfxtjRCs1dA+MceHtVGJMCKRr6P1WFI7DrImnVmktKFoapTX6EJsxwnu00Vgs1kmMK3pYZwaYSFkZV5d068DNN9WvuREp9csKoA31f63CA/DOYfXNnXAbm/F3CFqty+Mh0dNSsN7ij78ZlRta16RUMH7CmMY1Zra8cd4ij+fIljKlyIGklZZ1AVJoqdbwveNzZWcMP/zhJ/zsR2/59OFAoLKdP3C+XiSuuI5Vxfg+c85cYyYcjuyUhqJYgsO3RswSEZxrE79xlSz62rukB+r+YgGUKGA5UKwxeOdE/FcrfXy/rXRRL8OYpIhQMg9nhkK8/NoaEWp1jaoVlBRcNUUup8h1v3KcdwQ/i9BraxQqfjcx73bY4EQhnkawyiBYGqdRXeyG1CJfj7H0XNHrSnh3Jj6d6TEP0qTHTROH1w88/OD7eGt49+GdBEYpw2XbqNazBsuHWvlt2fi6Qd9b7t68wuxmgdKkxG6eBslQHDS1Nk6XKzkXvBVC5unpLPv+mFCuSb7AzTWhbxROQf0Go/HaUXwjroWUb0Uw3xQBwzXVEGFmve31uRU4ilZvJMWOdxpnNFPQqBbRNTN7ePtq4u3DK47LzGTBtIizmpQtFy0AJ2qlxiTdtBmEQDsKgF6pRWLRU0w473DeoM1E0puI4po8GyU3jJY1ovMS2ZtTETGygnXcGTFljE2E1bBeM94ZrtfE/d0dKNjWxLpKlsk8L4TdnqK1WG+tpZYixFRtxe7bDKgmIkslzAqDompDr401njEWtsvGF599xbTMzIcZjOZw94qD0RwfXnO+XDidz1yvV3xOQ/oPQe3QWoBV6/NJDoXRNCkldvNXxwPzZFnXE09PX8vUSGtCsKQml3qKF5SZsM2i+gTdSiNgZrQJ+OCpPVPqRolnEYxWUMphdKB30Yzcotz78P2rv9NwfzN9/zYf/xEcgDr2DqMzauLwBxlzjWOd0ajxsqxC/LgG8zK+1Qqc7pjeUC3x4cvfssUzr17t2O9nUZ9Xx7vzhfXpiV6K7JjHrCuEwGHeYY3HCXib1uHDh4+saSWVjVQT2/WMb5peKlQwyuNdYApu7K6bZJnngrIGWxumNEyulHLlmgqtG6nQU0L3jlOSXz07GWmDEn9o6RgGna9K2lfpjV468RrIqaJ9oFbD9bJxLZnH08Y1CZnw9e4ICNa35EzazhLO0R2TUXzn4Y6SGvH6Nac1olWjWMUA9KEUaB+w3mMsuDQCM7RoCowVXzcaepe9s7V27NXlMVLjoBLRG3SneAmw0R2tm6SeVdmxW/WNFa43hRoIYYbavvWxs1RKrFK1ykU8qoGq6lC8Diqe+iY9sI+Lxnn7onsgl5FexsDa5tF1KpyW7r/3JiNZLZanmz6g1krwAcVwC4DE0Y7xdiuV9jvvmxv5ULrgv0tWrLWJ3EYLEbC1RkYTwh5y5vnjlafLRqqNmBW1SxCQhFZpWs9QO0ZXVG0cnOXt/Y5/8KO3/P6PvsdustTtQro8Ey/PtJLxTjQ4pYqOonCb2kg94LXmFBMxbRSlccDdsoPSeC5doDS5UFSnqApW/q61gpPWQwPiRvxzva0C2jfY4zwCvWQSKIKPKQQiimYbKogC/5bzoAGjJX2xNqHuPb8/8TAfOD7c47VizVfqVrA7gx9cgq71EHxKdyVMCnk2e6vULsMf2z21VNZTonx8Ip+u2FSGn1rj5on9wwPh7p7z+49o51Hasm4rSXlWZXlqja9r4stcibNi93BEzZ5uFc4YjPYsPnDcHySDYWhnpsVyuVw5ny48vX/m6eOF6yXhFJAlBc52xDHQhebVe0V3haoVrS1u6GfUOBO1ugGk2njOZV3aEZ155wbG6eP8HesxLWJe58Dqgqdyf+f45M7zyd2Bt6/vmawlridpzsbqTA9767ZulN4w3mCDwRkpwFV3owrubF00NtCwNuCCRevApgQwFHvEKsE059JxBZw2YyU62sFq2IqEYVmjmZshd4VNjaf1zNPa0KpzvjyTc8ZaR2yGua9sKvF83nj/4Ym4RUG6q0YrippAoKKNmgqlJAriXJFVV0Yb+Pnf/JLHZ9ENvHr7wHLY8dM//Bk/+snv4+eZaX9gubuyxhFX3eWcaV0IppfTM+fzE60k0UZ0SaINQYrX3eIxrlPqhZg6zjdyuYCqw1LbJI+gJ0o8Cf5526S7N4EcRMheW6LWjZIv3GKwjRU8fB0rdznr6ssd+3cm7nxbBcB/RAFwe1N/8yE8gNsD+/Jv1Eu/J6NbFChR9fZBo7NaghnqemE7feTP/uSPqGnjn/0v/jH28Cn5+SPv//YX/OW//ld89ctfUC/PzFbJ4YnCWc+y27NMOxSWp8czX3z5FeezjHoK4l+fg6XLZ0Zbi7eeYN3IrldYgY/Rcyb3Si6Jctmkc6ER14zyAaWskAZ7FwV8aTg3vbDrW1eyj+sKmsIZzxQkYOg2LWlV0aqhFsMWFee18uHDlbU09ncztRna2JuKTW9F0XBux2QDx8Wz7hee9mE8HJmWDGXoMayTC08ZORZkwC570GUJQsPLsts1+qbK6JIGOPCzNHnAlOpjdy+jV9Wg1kTJ4OyMs3J46DG/l3Q9PeAxlYocFKppEaWYIVpsXZjxjOAipVF2uCeqrBDmELhF194qXW1kDdC6sMmdcyigFNn/mxE+1V8ijxkxs8IKuF1gdIEfGT+htSGmNESF8uaSTvabN49Q/BB7UhXAhnd2pPBJMWutpRuLNYqtO949n/jq8cK6ZXLtcmE7g+4dSsPpJiyCCjvbef1wxx/+4FN+9skr9k5jdGF9/EC8nmWM2xLeG+YlsCXRu4R5Holrwl81RoqxtK08bxvME7v9gTwFHh9P9CakxDo87MYK8rRTpZhRWoiGzg34U5XRfk4SL61vTHvEbomVPPla8daTxhZSKyWM/JzFLYAebh0RFDo68bxx/XCmhR3oOiKIG9t5xU6W2c1YZ6i9ipgO5HMbJFgH8YfXmnn6+ISvnekp4Z8vcI3j4rGMv0AB1uuV909PXGOmolhLo+4OPNbMF+vG5yXyUUP4JLB/uMd4hzKKYA2qic99f5xQWtF7wBjNIU2cniwxnkn5Qm1JsgYA2+SituPC1qPrkbApLfqB3jE0nBK+wE24KtOVbzQ53PDqffw7yos4VpIzDc5rvFMEW1lc5dXe8Q9+7y1v7xZ6isw24XRjbRvlRp8shlgVa4LTNZFbITTLpAw+WIyVdWSbLBTQvVBypNZMTh1thw0ZC0MjIMmOghFfEUuxUW0QGDVbFlui1R3vFAuKaxNegdaNx+2Z1iqlJowwcjiXlblIbPbnX35gXQvOC4ekDehZH84mZ7XcPSOBcr1WWgU3KKwfPnzgw8cPKGuYP9+hnKHQefu9HxB0wIWJu3liaU2al1H8yoor4kJAWc16OdFzxllxwAn1sdIV+Gli3u9p10xrV1AijjQdeinUtKFwoA2tlMEliZJyWgypyDoYVWllw1jBhVsvAl6BZYnlsKPo/T9I/ZMr6Ft/fOsCgN5Gdz8mAPByUCvUy3zqxgC4VSPiG70dDpKipmrGqkZLZ371F/+WL//mz3l9v8dePpK/LPzVv/4f+Ms/+Z84ff6Ocr4I+neZcNrjppGA1+RCKTHx9PTM+XQlpQzIi6GtwniLVpIHbk1gDoFggggOSxHPtxbErlDrIi1Jtda6WEJaB5RwswtIAMmAw+ghvENbyhBBGeeYgoSPVBrWKsBQsnTQvVtqVaxr5bpWmjbUJna7basYo7CxQa8Y1ehktJaUw9evDuRcCf6Jp/MmKYgloZzBGNmlKq3QdJqSCNrg7IsV0xhZWRgjHVYuBX3zQnfZ12qj2GKmIwx5Y2SMRpUwImMVMSUWv2CUJm75Jd63a9lvK2NEPCS3qGgMxhj+ZXSmDXpE5NJF3GkUL+l9t69H1P0jpWt471u7YXaFuaCVJqcsXyd9BKuIfqDDNyl2rZGLYBlFLyB775sPu6Q4Cg4zaFsyFTBWv3x+ZYT+xrBCrimTGiQVePd84vMvPnK6xJHQKN2d0wpqY28UJmd8hzef7Pn+J6/43ts3/Pg7n3BUla8//zVbvOCshp6oLWK8Yn884KZAjw5VKtp5iVRvkao7U7DEJKCiHCtTaHit2WIkx41uPGpw6pu0k6K9qF0S65QmbpF128QfHTydPoqBxLJM9CpBR9YJGyLXJkmVTpwRYjOT17J1SQD9ZgJocRpsruhcWD888750uq7oSeH2geJguxhUEHBOM02YECWjgMXuvgFhlYaqjZYTZavEywbXiM2VVirKeIxzdKXZauHj8zOP5yuxdtbaKNZzMpbfXE58dt14VJDv4Hg4MC076caRSF1tRXRcegaliUNRbzsUInZSvP70yLJP1Gujx4ZOBVsauomGoFeZnNngaGhSHtHPNLyWAKE2+nz6TfMik7LWOk1J8aW0eonkbiLNwAfZ+XtT8Lry/U+P/PDTIz/97gOmJ9az+OJLSaxpIzbNlhVbrJzPlcenjeuWQTdmOs10sIppTIT2i8N2hVWKkhOpdtn952G/Dp7WI1uUdZMdxVfKlRgL3ukxNRTGhbWaOVhi7pxzxCkwunHYB4yW971zgTB7ulbkmwuh33glMj3QRmimqQnsSKOYvcMNDkdRDRWGvVIrWXe126pFcTldSL3yp//uz7l7eMN//k/+c2YjVlPrpTmwQRNTwk8zZhOhcwiO9bwjbyuqd2rOpG2T+Odrx9iGmwI6W6gWp2dR/SPC8a1csUljvZIcDaWwehbHUlWYXqEJGdEamcqo21pXD9cWmd6z5J5gX9g8LxVA//YsgG+vAaC+2ABvwhQ5SfSY9vcXmMH4n/KgItWuUnJZajq2V3TaePryN/zt//Q/8Pzbv+Whf4fP/v2/paaNP/+TP+HDb7/gaL0wvq1jF/bsdhO1ZlKKPD+fuJxWSu5cLld66/LwIR2FaaCbxnsRqvVaSOuKNo1epZPXwdKLeL5rGvjVof5uw+NZWkYZheqGmgptZA702seeTOw68j3fBGRjMqIE61pKI6VKJ3NZE6dL5HyJNCzKWEpVPD1fSflKjBb1akL1DjWRTcd5hTYLx2XGfS9wd3fk49OJrz9+4LxtTPNEWJbhzKhYb3FmIjjxUPcmhDI9dqkoJHmLBkoU9rX1m6BVwDpmKPe17CDtLSlr2MXaWMc0VQUQ5CTYpxYZ80soTxtEPulwtDE0BKBSS8UB1gV5M/f2klLWx1ThJnIpVQo7NT5vqUP5PIrNNkaheqwPbs4DmQqMnAGtJRhnFI8xbmhtCSHQbxZC6ksxewvn6Mje3rgBUhqJaq1JWmMqmS3Dh8vGu9PG+ZJoVVLzltAhZ/oqu9Wdgcl3vvfmE/7xH/4er3YLNSX69ZFzXsnbiVoi1jis19hpQluNP85oawVVnAulQrMKoyZ2zlJo1F7w3rKbG/M8oZ3l6bpJNkFvcni3RjFaQENI12SVJq6JlCPaGLzz9CqFuh9Fg/eemoWDYJSEPE2TxzmP044QAqtboV9IMQmvokvionUOUxqUTksFXRv1snJaE01V/MGxUwfcbGgxs57PmO7Qk6ZRuW4roNDeo5nkdXWG2S9MzeNsRa0WzCaOly6cee89flmY9wesNsQOl9bYUDy1xq/PJ34bVz7URplhPgaW3R5vDK1VjFK0FEm1cLoU2knTnaHS0LVwCIEpBL73w+9gtadsGV8NtkD6cOHjb7/g+d2TaBW0rFBVlWnGpMSaNylYnExQU+PlrBSvdxd3BoK5bqqL8G3w471TYx9vUWSsLdzvLD/78Xf4zr3nbm/oRaGqJacicKXauXTLKcPzOfP0tPF8isSR7RFpdFsw3hA8WDOAT61j6Cg9scbCFjMtV9IWsV5swfSGNmJnFRR0FQ2Hlujp3OrLdKBrMKqjqUzOEIwG4zBe46xiWSb2+4XWC3FdqX24RyZHR+x7tslVY0aR5q1hCYF5CiK67CKSzKmMs03yQBoiDq10TvHKF7/9nH/5R/+S3W7PH/5n/5ApBJmU1koumefnZ6yXCap3jmV6QN3fU1MUfUxKvPv6K67XEzFdsbZxvJ/ZHe4wZoeqG2lbWbdCKmMKWcQBoK0gx7XuOJxMcrVCKWGRdKdEq2OVCLmtFq1DzbQead2Njbw4IuQOEpfGt1MA/MdMAMbHbQ3wEkr0d0oNJVYvNTrKLhVtV0rysbVALiaraE8nfv2Xf8rXP/8L8sev+Oz5S97/4s+ZvSM9PePShu8wh8B8fGC3O6B0Ja4baYtCWiorJYmf1Ts3EuqcMLNLYnaOYCpGi3CC2qgjeMOi5OfWoWZR4toRKVtyp+U+VuYidkq1U5L8uZvlL7c8xtSSPme1TA7i0BSkKCOzDoR5IXfF8/XKZUukBqUram7E88aaO/uiMXZimqwgWGsj9chUPWHyhDCzm3fc3R3wFrZ4JtfI5A3Ba3KVC2oOAcqwq42Rbu8NtOBLe+9DYCKOgY7Y5hQSiXqD/khWu0Y5/TIOy1lcFTfYjhrdNUqJmJCb4vmmE1EvSv+GiEhbb8QkPxfjhGRYapM39hDmoWSC0LocKH1UBXUk82ltxwUv0wVtzGBLDEub0aKPqAzdgfzSamQMINqHUguKESjV5A12U8nXIXI1w5aolJEAjqFCj7mxbpktNT5+3Hg6byNCWQ5NamXSsNs77hbLcfa82gV+77vf4cdvH8jrhXdP74hpwxvE1uoUTTWUl2lXU51qFM3qkTFv6FWKEj1pbIPH8wXbLIfDDu0s024Py8JTqVgUvcozGY2le0cVHxlOeWJJkoppDLt9wFmJMe2tobVnvwsCiaITgoXaWJZ5qL5lTaCMFqW/aqQSySWBMkzBMi0zrBGVM1ZDqArfFK5WjAVbwaaGXjPFaUqL9KTRswYL13hFaYudMtpF0Bo/wF+WwOQNfTVs/kQaz2xWmmAs3/vR7/HmD/6A89fvWRVs1tKc5uN24efPkSdbSR50UOz3B/bLIp19l7F1V2JbU9ZL6E9whN3M3Rw4Tn6svBQ9d3qq7NSET506H+DpmfrhmbAsGGNYYySWRO2NLV5xTbEzFjN7rM5cUqWM/VMuTdaTRlqs2sWr0Yd2RluxZPrJoVQjrZlpgZ/86BN+/MPXzDpyXCyaHfTKx5RZS+WUOl+tmQ+XyukpcrlIBHBrwryqG2jXmSa423vCNOFRdN/Y7zoP3XBZVx6fnnk8b8RSYTQAOzsRM5wvGznJpE82jcJBqGPqpEegjXOWZZrEJmhFQe+9IXgjDc3kqVXJmLyNM8ZYal/ZtkSuBWcs0xTwXrNfAsss+q5gLdY4aIqYMtuW0M6C0ZRaMSHQNOir43w98eGrr/mrP/8L/uCnP+UpP/I3f/tXpJI4n048n050YzDW8o/+Z3/IT370Qyl2gqaVSuoKqyyX5zOtZ5ZDoHeNn3bkdEUruMSN5+cMSEFMVehSMF6RSsU4ETEag1gBkXP1tjY1o3kWy99N+SH3zi1vR9G5Dd4bI4vnP2UBcLv5Xz7RrfNv/XcUCPJEy0i1Qc+oljG6cH18z1c//2vU+RG/nXHdEq9PNKuZbWBeFhYsSnvudgfZ3V1X1uuV3utLd6qN7BdNsBhlWKaJUhLbemU3WXrdvtn1a43pllwrNWW2VvHOSJU4dp300cVW2QH3pmRlUEUhbrUW+EbrAvTpTfjRfnTLXbrrmKr8vkMshefLBa4rj89nTteNa+qsuZPHimFWmmlxlGZY14pTWljgKKoVxvzkLMYpaozMk+E7r48YC+eYuJ6f0G4iBCf72VJE+6Cd/Py1CEXqbQasZefYhAMkF4vSqNYwysm6QNux9tGgO60K9957ier93bVPqVLsCaBHoZpYheoovBqd0tvLqMqNtEGx2IlSvpVKMVYEgsiuqzThbDfETijjCyU5BIzc7gZGWbq5xR/zAvRRWngFNy9hqQVr9Qjt6KSUhG/gHZd1HY9yB4SpoJQRjYC2lNLJJQsVL2XWuHE5X7iskfPayVvBKMViNGyZsnVevVb8wY/fcj977vczk+7oFnn64reyvklXdG9oZQm7haY7TXX8HPCzJ9NIw1mjbwrsLgdqqQ2VK9My05BL3I4VkITJWExX5LjSB8SldlB2JBimRqkJpQ3BT9CVWHKdFZLjKKwoN1686AeU7sS0cr0IvTL4CestYQnM2yTTEutY5pnZBdnlb5FgNHODXTOEUtFduAVqjWRdRRyJp2lLrBUdDKXBPCAs2ugXB4nzAYdBx0YxlmI0UebDVG3R88LDT3/GfP/AX/37v+RcO3234+PliS+2xGOrrEZRdWd2lmVZmMb3anRDWzDO4nYBv19Qkwfv0N6yeIPt0gGrLtCWMDlUqpw+PvLub37D6euv8DWzMxarFfPk2VLnuiWZIipFsJbdFJicw68bcdgmix3vl7Fqocm6tcq9ihm6gN4avSd0h/t94Mc//A73e8/ea/aTY1tXmlLgAtcW+e37C799VjxdO+tWuQU8Gq1k597hEjtLhFwN2jiCMSLYHpS6KSiUSqJUv0IrMsLXDryy9LN46pUaiNuhUO6DnzBNhnlyHJaJw24ZzISMNdLlir02EzdN76Ip0MaijBFbc5VGQg1mxGE3MwWDNR1nJLhLqyGO7kMcPaA6xsnZr61DWYO2hv1uxxY3nt9/4G///C/57MvP+JM/+R+FFNiaGAF84Hq9wvVKfHzk/Pwk2Tats14vPD4+8u79V+wPM3/wD38fox01F55PG7kUYnRg77F2AuXIWTg2thpUrcRUwZQXqJVkIFSaEfBXSx0uiZTOKGPGeRWElaINut8E+JrhrP77LwBeOn81KtFxvdPlgmhDfNVv4e6K8UWJnafVitYJowr1+sRXv/pb3v/qF/icuDseeDgeOK0ntjVikM6ndYdG8+7dO7lwtDDra5UQGWsNzjqsdtK9VxGUQMX0iq4CnaBWtpgpqeDNLHu01igVVGvkWMbXJw9XaSKhu42Q88C+eutRSokVsXXplpRcgOu6UbSI5ow1ArWhj12k4vlypbTCJRYKjdw7qSEPojGU3jhdIko1WvVQLYfJsZtnjJYdbKsS9JC3M05XvvP2jmnv+c1nX/Hu6YKpDascsVem4GWEOFCqrTdqyaSSpYJUErKj+mBuD22HPPniFGhdhIJmvJ4dCeVY40YIQSYjJYs3FjUscfJwdzU6/86QJMpDKTt5EdIZYxGnVaFmKQ5u1LkmGdIv4tOuOjcG/U3Ud4s67l3yBFQXzHRtbQCFhoBqZFTUVvFTQGktjP4ie+7aO+v5zBqFma+1fG1aidhIdYNuhi0lPj6eeX4+EWMe+oRCTIVeYVZgVcPETOidV68tP/3BA7/39hV9vTD1SB8TLO0t8zzjlkm0Bc7gZxEZyQTAghfBZE6R3quEHpkBTyoiwrv9/Le4keJGLQVKxSmFVwadC+Va6K6jnHibTRPBZ0kJLCx3C94HaqukKOsWqySxsOYiz08ptF7x80xKifPzM611jncPeB/ouVFyIJc9odQhzhSgVO0JWkJ1OeR8h9AaoWssihQLp7TSW2aaX2GCYssyDXImENyEswJdaTdXQu2sKWJyxxqH3u3JwdFdYXGONz/6Actux29+9Ss+e/8O9+qO56fOr7868XUttEVTtDzT0zyxmxZU65S0oSfRp9jFC7PACNvA6jEJywVsZ5plDUJupOeVd7/5ks//7JfUr0+ErTAV6OlCUQrrHZOS9ME9SGiQJPYQJo9TnUtO5OExl/wIuZSNAl0hyyYFcRR0UooY3djP8OZ+z/0hYKnsg2c3e7FMGs/WO18/FX75eeVjgq3CYPgMF0mXkXrXmKJ4PmXe2yu2deqkmD0EZzDaMnm4PwRKCzQVuST5XlqRSVDXQ385utXaNU47vG9MXuG9hCTlWim1DtFeQylLL51eC2sspFhfrOduEot0Q6GtJcwLVhnm4FnmCWu+QanfRNm995eJJ0amXuu20XoXEFWXn6nFcLfbU9fE//hH/z3vH99xeXwURkzvbDkJntxZ/uJf/wm//LM/Q3V575Rcx5RV8fh84XA386Mf/gDbHblWrJnJVbHc7ZnDDmOmweaI5BwpPaNUIaEpqWJqwzk5K0tpaGfxfk8rgWtpXPoVlME7g58M+8P9KAZvTcvQ4w3R9N9rAfAfFgI3EZYAcW9o4PZ30K+3KqTT0KriLdja+fD1l/zi3/85T199zj5t3B0emIBiPPNxIefOu6+fKL2wW2aulwuYRpg9YTJ0RHhkjcEog9MO3eSHSI20vKFqoqSM86KALnEjJ9kBG30DkVS57JoaFx6DkS3BGSglnv0x6vYj/Stm8d13pST040aho6NNBwQ12ZHuTCrPQukNGyw752CC+LxSmiK3Ro6izr3ZpzyKvV+YwhGj1RA5RpbdRO8FTcUay/1xodbXdGV4Oke260W6I7ejtgpK/Khaa/HNdglFuok31Y1qN2o2pS2am+1K0XuhISIgNDTTWNdVXmctATZaW6wf3XyuWG1GYSNcg9bay+BKaYmCLrlQaxs+579rs7t9aK2lozXIxMIY+bm324rp1qHrIQqV76uM1sYqg3NmTDMUPScREvb6YvO5FRO1C1hE9AlNphW90XuEtdC65romHh9PnE4XObyUTAlqBZ07VKmfHo6KH7x5xQ/f3vHmMLGzjY/XR9bnKJ1fCHKgghS2xpBalehjoBtZH5A7zShM8BK3bCy966EpSazrxrZGTpeV63Wj98bkLEvwzN4zrxGVK6ZB3WTXGEygtc62brRaCccFrSy1SAFmxiVXSsV5Q0qJaQ7irimF1otgTlNkOewIs0cpTU6FUkU8ioamGr1nVB2gITMCcGgENItWHL3gry8UYops1whboXtDbUU0BItDd0OJRSKIZZFEy53H90/MJvAwHWGZabMnh0J1geec+O/+1R/z/sMjl/VKaZ1fffk5f/vxzLsCbZb3rXeK/X4hOCO7VeR9nEvh4CbsMtGNTD7mMOGtpdaNlK5oo3h6fOTdF+9Y3z+RvnqmPl/5zjTjCoRa8UPB30sh987UYNKQ+3C11CzTLG9klJwaWwFvYZ41TWkqmi0XTtfGJUKtTU5dJWP2++PMm4d7gpW0veAt3lrm3YH5ajh99jm/+urEV88SaVxBmAM3GvsYHcciuGJVCqZdoETqwdD28twd5oXgLGFacMEwzRce18h5LaxJibth9BCMTrYDVYmlUjlL01BzQhdwBXIRkmBLiMititjt5gAyRlOdwVuFMmCcoMa1Ej3RGiOGgtYjvVLbF22Q0SIE70X0RRYLWuOso7QKTfDSRhncpDlfLuyd59X3fkAtmXW9UtcN3TuHxdO2jbRt7JdFYEjOCrpcKbITcWg6b4Nro1imO8xuh50fmKcj1oaRxVBZLyeu2xO1XUEXUrqSaqVZWWNpbwjTgf3hNYqZ3gO1TdBnjN1h3Yy1Xuilw3cvpcPtjv5PsAL4XXX/3/lQv/t/65fDfPwtFBWjBY+Y1gu//tu/5tc//ytc78zWkM4XJmUoqXKNkW4Cy+EBVRSXLbI77il1G/OkRgjuRooVsl+XBC3bFTWNlCWroBeoGqcVs/d4Bc56VNfkmikpUblhaiUopvbGLXLxNv62RoI7apc9sECIKjFlGqJGcdYiK0EZK9famHYeFwLTEjAlk6+NGBO5d2G0T57tksbeXb4fQX8aUIHanMTr9szz04naNu7v9+zvFnaHRQRJ5v9L2381y5KlaXrYs6S7h9jqqBSVWWqqurrRAjMDGxjNqC+Avw0jL3hBI2GgcTAYtCiV6oitQrj70rz4VuzsHhjMasjiNsuqlGefHeGx1ife93ktr1/dgPKk/IGHx4VlEQ6CMrAZR3EEOCdjZGsxVZNyIlfRBRgjUwqpmkXHIQmDCKSn25g00n16N3QRnqw/vBslyKJ/0FoTNb9qRqY1tecOdJEL/GgrfYmSujAA2o8FZF97CQfd/DjWQxm5pEuVkZ82Ys+k/yGqVLHDaPXysymlWGNAoXHOo7S8V6AZx5EytxfwTysCFompEGIlhEIIhZQruVoaUvDU2tBVeOo3A3z9+Q1/8fMv+eLVNa4sxMMj8/HIqDPaSY69GyaJTs4ZqwYZyVuJMG5GoYzCOIsaLEU1lLNoJ66FGAtrCpznM2EOxJCoteAuZEhlxf2hBbVramXU0vWVqiAVUojkZcV7JyS9lClZ0MjOjxjX57f9EMk5vyDAz+cT83zGWBhHzwv/o4OFrBN7aEOEskojboHBM0aBHg1otkphYkIpuYS32kAzsGb06NkMG85Lxk8iqC2pUloB3UgEQo08Pj7yUBSn4YR5Dizrgi8Jk088//3/xJoyShnQmufTmftl5kCljhf6OoyDZ7KeHCOmNRg1TTVCTbgWsUqw2bVk0rJijEO7hrOG4/nEN9/8kR/+8AMmFvbV8vmbO960kVoPmBoYtEFXTciBmooUBl5RtCVUya9vFSZr0c6iWsYrhR2dqMndQFOW47ygORFyIQSwgzAyrC7sd1vevX3Nq+sr3tyN7EY5jwffcKPlFL7n6VxfOBftcm52kJwM/xSlKkpTZGBeCk9kiSceR6ZmCfGMqh7tPeNguLEb9OjRNqKWQlnEGZJqFQtslcs6FdFUFZ3x3tHwGD2yVIsqFVvFVWWN6uduIxdBliutmFTFpIiYAbUMTlrt2oiG1YVhkPNHX5xGpWE6LTBVGMaJ4Wp8waVfGrZh8CzzzOgdqjRKDdScMU2xv77lzfUVAOfzmVglR2R5OuKcZxxGUgrElNFVfBzHpyNpiYwbR7Ej2V5T1I6stozjDdMkUKFpf2YbD6zxmcrKuh5IJTEMA855tPKMwxXb7SuckSTApkZoI0oNNH3R8lyG7V1zhxLR/Z+/ALj8gpdT+PL1z2ZJ3TokIwn569rEu6hqoc4njh++5du//w88//AtX25H7oxhO4w8Hw58//GBaj3DZNG6MJkBOzhKyYzjgDGN0iIpBqzpOe05k3JlMANOiVdSKYVxRqiCwyhAj1YIRDSyQuizaU7nhWkSIVrKhVxlnKKUWMrEfqMptRLiQkEquFYKwqYRsZjzFudkh6VNY7CW4/mMchY3eLT1NFbWUImkzj/XuMGhBxn1lpwoGNxmhx4mTksk5WecgXVdyWnGOc2wcdSciSWDzrhpx6u76/57v+fxcOZ4fMYNHmedCHCyPCBGeKik2kRg09XlF3He5Z2tVf4nJxnFg3QMBQEGpZwRmp0WJfwSX4JOaI1JTz0zQoGSZ+KiDzBGY80AShFzlrAY1cNlcmcnILv92tcAtYlFsfbKXqE7xKeiregDjBL9a2v1ZSpziR9OPahlGAeUNpKUV4rYb9CsS+J0lkQ/IRUbWlOS/7AUQpRLUisZH7aSoRachsnCz9/d8lc/+4xf/OQznCqsxwdyPEOLNAp2mthME8O0FfFl6RQ5LcmEw+RlUtQqVTfcOOLHgVAzIUdQGWtdd6CItYwqosbduCHZgkOTUyWETPORWGrXYCAgmNpYnp9Zg9AmrbO0lGhJgZFgIGs10/YK4zSlJpwTG+joR6r1PDw8kNbCdrulYYSa5mU1pp3CZdMjjTOlCBBHa0FPYzQg4UG6iRBKN4VXjp1zxFw43B9FmHmz5f78TLUGM4wom8W5oiuNMzTFME788P1HPpw+0Z5W1MPCZlH8MC8yTkb2vyE2qqoEDZ8CuCu6S4GXBLd5PeGUYXIj1cL19Q1VGXk2tcEZUfJX0aeijWIzbfjiiy/48u0XXA8beF7YzJXNOZPHLeVeJgJxXrC1stNgVQf3OMuSGyVIcp42E6PRjN7SNh4zDNhxQHtPVRqnGmENPJ8Kx4pYC5XF9KnP67s73r17zc21ZjsojqczKYgYU6GxCvYbRSiONZXeASOZA5dVneoTKd2IGZ7P4GxlGBaMcqjByYWNiFRH71DGobTB2ERKZ0bbSKqS5PFEg2hYcqVZyT4puVCqe9H9jN5TyiqAI8Q5pVEC8EExjRqtVwanGP3A4DyjsQzeYZ3GGNGy1FwoWrDFkoUACmGHyOgg0Rov9uZSCusSyDkT18p2O6EZOB+faQpGL5kVSiludjvm84l1PosuKxdyLqicyWvAjQ5lNafDkbBEdrstpVlyNeSshKw6TCi3pdSGHh273Q0uPKN0IuQTuQSs7lwTbbFqQqktTW1oZkIx0PDCjClNcNF9vYm+5O7Ulzv4z1oAtP6vXvbHl6bf0A9o2kv62iU5DvpnviSsg3o68P1/+B94+Pt/zxhO3Ny847PXbxnHKz6c/p5j8wxmw+Q2gt2kiVXJKq6v911LEGgUluVMLvIApRDBZjLSnbtx6IVBkdCNUDqGWHE6n8ipvugANuPwwgePMWOcxw+u73ZXMMKYN9YL1jFVqu0WsCVhvYRZxJyZZ1F0+v6hHact5zmxhCfcNLCkxtJFLM4rtAWHJsyrkK00YlfKMFXZ051PM61EnC7sxg3OTygsKfYRtm6s80LVlv125GrvuX+8Zw2JOWap6KuMnf3gO75XdpylZKqWil8bhXKWFhK6yvsr3IYLCjeJ08ENnOazYDrHCePlgzQYidRsBaZpoiSx1uUieoLWGtT2QuErFWpXIA5dWyFFhv5xjWTEP16KYU2JnArDMJJCQimJ8cw5My8zl4hhrVS3JFbOZyFp+UGshrk1liyrm6ocyTpSyYQUSUuhrhpn9mAqy7KSaiblxnlJxDXJa1ezRFK7xjjA69uJn717zV9//gW7WuDwCUzGt8DTeiBpmN6+4fXnX/H+4Zndl1/xd7/5DX/8wz/y+3/8B7aDgSj5EilGjPc4N9AKrPOKsoqNH9DOStpcLRgFv/nVX6Ca5o+//yPLvBBaIBV5fnCeJWS+e3wiVFlreS1TH1LmZivahlQScc5QR8zgUE5U12FdGBgYR4+3IkWdjydaUwxqh/ED1/tbWb34RC4y1coksA1HQwlmQ4A+GmIPrirWonGkw4qJheurkdoMuiqi0jyezjyWTMyF+zBj9rfsbx2qivBymAxYWEPAW8c4TKzHyOM5koMkIObaqLk7PmpDOwGIhVYok7QsRsH1zZbt3URymaQCzTgm79jt9mAs2o3sr25RGmGEDJViu5BUKazV7HZbNIqNH7HTQHk4spIYX0+oGshxwRWDKYUcYWoyhUytsrWG0U3EUsktE2PD1YLzG6yzVAR4VJTmdjS0mx33h4w7Z+paqTqyu3bc7Td4C0kl9DQxlxU9WszaIM+YkNkkhd1s+bRWShWXjLKKkARYNY7CCqkk4ekjxUE1ELLheK74VsEWlDFMk8ePAxs0m2HgdlsxOdLWldBkxZHp0cS5oW2jpgix4bScheclklMGFVjj2k8csdg6A4PQ38kRnIdphHEo7IbM7X7Htsjq1DsBbCkKgxHXhHjlBfI1DiO5NNJpEdG27UyMKmFySjWx6C0zzmrR4rQO21Eiml3yQqHgBmkAjG5QE3aweK9Zun7jdDry7fffs725wu4GvFa4wWCNrJy0GVDekXOj6oYad0DGmRVTE1qVLmSUqXTDUpqR6V1vTJVpMolW8lqVbsnWKHFcyEXN8GctAC4Lo8uXai9FQFOtp40J7OZHu4KIdrbOYOvK6emeenpmo6oAa0olpcKaZz4dFp4OKzs1MU0K57S8eFbjfEdw1oy1htEPGCXgltwC2jectRhlJZVKCRku20wKGasE2uPsgN0NrOvK+XBmXQNaScZ7Q2GcewHEWGsoeErNMuYePKY0GlHEalXTmpEFR+82SwV063a4RtOK1slf4RwItcrIW0kHvZbCmjMhSrditaSnHeeAVQrXMi1HrGqY0aGGCeUGGo7znCkUTN+rNSOXqu6hP/OSUKbhfSGkAqbK4XyJJlWy/xdltbgGpMPvVWUXdxrvsFUsNE4btNPcjCO5SjCKMtDI8jyURm6SGy9FISirezKgdBmplP4c/YiSboBpIkzTVnLeU0jkGHDa4KeR7VbGdzEEcg7UlvFedUQm/SCR4jTlSq0KZ0eh21lLCJEQIkVBaZlYmwgQayNmEYiqrFGxkkpmjRJaVArUC8MgFAbVuB7gdoT/4lc/4W9+83NsWhlDpJyOPDy+Z01n/G5k3G/YX98yXL9ieHXHf/V3/4ZXf/tvICyY+x/Y3F5R1meWeJbvrwyexmBk1VSQFcN+GjidzpRaOJ8DpcJ2u+fbb95zOK7U2jitiSUWllTRgyW2zNOcOK3SzaU1sLn2vHn1WvQarXJeFo4hCLlPI5OdNUoUqbGUXiTcf/zEw8MTd7evGDYbatGEc6GalWGrZA2mG9Y7lJYWWaWG0gJOaqWANVSryQmqMuLIMZIOqqrCGk+2DXM+c14Lh/VI3FoqnvOSMapgrCeGTI4JpS3zaaGVhncj2i3MNTPHCkbhNyNWC+mtNQnHalVRlEyWNk4zTAPDxmPHxjA69jcTbrCkHHFG45WhLJGqoepKCImUW08bFHFbM2LleloO2FxxtpDSzFoiioiZLFvraWZlLSdSbLSc0MbIKtMYcZXkTChS4LEG4QEYMOOA9Q6nFcEqvOr44K6wdwaGwTBsHH7yrC0zbgZ009RTodmGHyzeQkgRgzQKsWRCiWwm2T3GJERQ7RGjzeVsR6HNhHWWXCMxFwgFbJBJq7VYMpjK25uJVhJKrXw6Qp5h7ZOFiuhKVIGsEzkbWtWEVQrwQqWJ21ZQwRqKMmIbNPLPQoF0bOQUsTpDFYdUKZVsC6pm1hppbZEL0g545ykFSh0wWr6B7QII7wXsk3IQrZBuVJIkPlpHq401BmpJgskeB3SxQrZEobZ7Si2EnBhKZs0JNKyLJBa6vQjG99eeq6trzLAFpWlVi9C8grWTTMjNhNUJhcSs93k6oDvZr7urXlY2FdVx57oqaFomKEp1q+Wf9vWftwJQ/1xacPmdyMhcuPI/qrIv8j95WBXlvPDh2+/47g/fsBxmRjcx+IkYMs/nhftPDzw8BpQ6sx02mOYE22sNrTbxA1MZR4dCVN6lZIH+oKFArolcswhEiqSPqYZ0u7EQworpu/7WmnSG2nZtg6YpSdRblvllqtGomFKwtZKzXPS5dGysUqSUiaWBgXEc0FY8o1qLgMdhKCmyxijVsJY3tJSCMQ6yCCS11bIfU7DGxHMtmBrRVLajZ2sntJ/IOI4hS/KVAh0bVSWhhRmL0o7t1TU3UXM4zxxPC6lU9ldX+GHA+6F3F5VcBJksglkBTVgDJcouUKlLMM+PO+GmFOM0QVp/zJVv0s3nJjGpFIlJFfiTaClqz7tv/bnR/e9TJaWvNvn1U4ryaFlDS5VUC6Qkl3ETDLMyVkKZiqjw5UvTqiHnjgVujVo0FYPKinVt5KKpNGJuhCxgjtIg1kxKidwiMWVKVRLwkyotgcPgaGwGxW++eMvf/vxLXo+NvU7sD/ecD/d8mme00RS9UkxF+cz17cT+7Q3+6obXX31Grgn93e/5+P57Ht5/D2mhLDNeCZGvtEouQdr40jtAxG4qeFoPpvDh0wMP/7f/B7XA4biQW+O8BnJtLKli4kJShmVNomlIMIyOr958we3dLSEFAR+FyLnTM0vL6OZpOdO8uGpUUZwPJz69f+B8XhjMyPPzkcN85u7ujv3dDjM4jDNCW1SKoiS0SJwUouNINQjECbksU2tUrdBOApwutsWNUkwoVGycVkDLpRTWjNKVnXGknCg0NtNASAslNqzyXO2uiMfCkqIkl4oGHdU1SNbSP+vClVhS5XA+Mu01N9uJYXAv3AyrtRzArXE+nVDWsLma5DwoBT05lHfUXkyjIAexwQ7W8+6LL6gfD5wOGVk8ivA0KoG6WOvFYmcHmlKUlsUq27kNzokrKOeCziJIbkbjkSma7rEeTUNRiVhXzuHMIVoGvRXRq1K0naPtPOvQOJnGcY2kEolZkUsX5TYhfO5GxeAso1WoKhMG0y42Po2xnlIjqVTKEsldaT9M/sVtc7XfUTBUeyZw5hDEbtBqRDsR9FakWUwto7BUpWRi07tJp2EcDZvBCza4qe4GKuScSBn00ghDYDBgWkM34VaMVp7DlLLE84bKsS4YrZnGEe+9iDlHaQy8kwbO2AsCO4oNVss6gKYk9r0UgQt1941FyS6ngfcD43bLlspSIqFmUgwcD0/Y7Z7pas92u2cYJlkt6vpiac31MlFHOriOKlQvTqp+7yMNAZf0PyX/oDXR2igujqtO5tWXFfyfsQDQl9/Q5fpXqn9j3UcT8gOUUroITnz1g9W0HCinE8fHZz798JHlOHN3fcVgB47PZz49nni6Xzk+wzjMhO3KoAxFNRF75UQpmcEZUqosp5mcA5qGNxIiUkul5CqKTwm8FT76vOA3hhCCUJ2067HAjc1mw/F45qIolEoVtDWoJoQr1QNvSudDX3bNDkUqQew8SCiKnzZc8uuVFXKc5CTIRSj7abkMCwqtqiSsNbryOtOAFBPZKpwBrxW2NGLThKZQqUriWRfLKSMRuyE19OAw2mPNxM3twJI+8XyYWVMAtTBt9wxFPLtaG6hiY/HWC+xGVdaQ0NahkUzzi3gOerpfqpzaQq2lf6DkoZC9ttC+9IUI2R/C0gV6hSavS3clAKiqyLVSUyY1sSn6HgB08e2nkskhk3PFe/GEt9aI69oFahqtrUxlqnoJOYqpkJYVhYgZrbVSrPSEM+kMKjWJ7WaumdSVUg1ZE+SW5Xso+PnPP+ff/s2vudWR9vADITyTw4maIhHw1xO7q5GbYcvV3Z6rN6+x2y1qcByePvLd+wfa//w/YbXBqtxhQzJhqk4xh8gaVvK6oq0o/0XIqLGlsawnctHkZjgcZowZ+XCY+ebDJ2nKnCWlQq4i6DrNRfLlMXz19g2vr25oMTOWxu12z0YBtfHxLJHFqoHyDpsbJsvr+80fvuXhYUVreH565hwyxsEwDFxfX7OmUy+kDSgB4uSq8G6garF7VW1RphCyXEJnrdlpSZpDKTlQc8Y1xa0beaMWngTtT4vyWc6lcl4CKATqUi3ebDivj5RYcdZzdbVD5RM5SnpnqeIN995JmqCWCZkxUuinvHA8Hbm5m3CDF65CaWwmGcuv55U5LGhr0LpJZ+08gxsxxpJrhlZxeIwzuFbxoZCXxHqYOT0dqaeZWgw6F7T3TG6iFt1tfqWvsITRr7XCaY3X3ZlTmrgoEsK+yJlrVzl7WAK0Rf5QMWFaY+MGRucpNVFqYXu1Yb8a1ADVIV595NLECaK7KfDesNlu8E7EdaoYsgroUjFadDelVVQRnbmulbxGLmb/YXBoKzCtaRq4aZpzgsN6IM8Qu6bHOJn4pSwaGKNl+mqdFk2CBusU0zQwDR5a61MORYwBRUU5Abu1hjD6lUxkBmcZp1HuUiUx8DkU5jmyhooxZ1lhWkkYdE6Q8tPomDYDu82Ad7IWli4+SHpmEktrzY1aEtTa/xpZlQ2+Fx6KaRhweHRtPD08EKvijb+hxYIaBDimSvf8a0leDWmVaXGThEHqP5fYdVFkv/BFSyVTAaUUl6QMpeSualxcTV3g+Sd8/eko4BeVyIU71LtCpf/ZCqAQ15X5fJLwBGdR08CoKnleKecVVRTeeBSGMGeen84sp5WSpaiiKkpuXQwuVU7NpY+8JP85pUgKAd0a2nlM1d3X2STVrSJvZIXlPL9E+FJlzK9UZUmrHCjaioK9VkKMAlPxTjqF3DDaSLdYCqXICy4UOoVzHt/koLmIuVLO5AbaZAqKNQQK9KmAenmdDLqP7DXWyaitNQR2ozVVa7ISpT2pYmfZD5fRiSo6d5FihhAbpyXSzhGtImsuLEUOf+sFF7nGwsPjkZiq7HZH4V5vxqGP6AXAEWPiartD4Sj999qH9KK0b0US+LrQUytLqzJeNdqh+/f7F8FRtf9564SrxsvPfmH2554rLzIW1T8LCm2cQEA8L7a9Uqt8wJusDECmJrUKBvOSLFhaE/CNvFKkXKh9ZVOK5NrnLGr8VC7iP9mZ12YAsYzmulAtYAtzeEDlZ8z6iW2NbHRm3MLbd2+ITpFrYNqPvPrsjs3NFQlDJPLd9x/YbG+hyfQinDOtJrabDSkl1hRZS+a8BtZSMK5gvJcDeph4/PhELI3zmmnao93EN+/vuT8uvD/CXMCYTIpAkUIzRumobq8Mb65vUSGT5hNX+4kvbm6wb9+w3Uyob/7Ih8OBlIscMqGwPp15PB4Ip4jK4k45pIwZ4NVndwyjZ51nCYFCPj80SYpU1eCtJbUs1lvjqKqRKpQAJ1O5tVr4EUrhjaj8bWrcWse7QfF+mYkF1tOCm3YsYWYNJ66ut7y6vaGVgdFqVD4xH49oknzmlUy2LpyqpivKFqwTYdQwePZXO6Zp5PHxI5lAKfVlWlULzHNEGdOz5BOnhyc+vP/Aq7evePfuDbkGMp0DsS6EeUGngg0Js0Tyx2fa4xmeF4YMRY+UDCpVNMLELz0+OxVh6BtrxYnSCuu6oowAnVTH0iqt8KXxxdZys3GCDVaVq/3E59OEPpwJHx55jkeqqYSc0OOecK60EtAacoYUYDP13TFwfT1ye3tDq4X5dKKkiKKKjkMDrZJDJBhFKRHTnVgtFlIuL/hw1yqjMQzecmUMEQgV9PPC4zmzpEZY5N/PTZgmuTYamtwhR2I/pl/wjdoyrVRalTPCDgOja1jErhpCosSC3jj224mmhVAaYiHGRum8g5ChJmCRNee4NHkeWsVqSSe82g3c3V6x3w0MFkps6A5Ms96++O11bXhrcVr3BqmwnGeKqihn8VtBEYdzd2zofyJUw+efK65vP8NYTUyBUiJqGDBc7KAy5ZBr3/S0zd7x98sfDErMw4jeSRrX7leDSwqnkkL3z1oA/Ej4k/Q5lGwqLux0JSq7PhkQdrSYpSS84XQ6cv/hA2lZcXjWOWKLZnAj3lZurzZYFxiHDVRFTbUT+iognPa4RjplFlUVcV0pIdEGsUEZNKoqSsxy4fdwipwrMWRaE6uZ9wMpVpYQGScJYsgpkmvpVZUE0uQeX9suMJomwjSBBZWXTjaWTA4LTRlCkUPU+JHzvLAm+SBNW4U2HmhCrbNaRnxaY6x7QdUa635MPeskvBQShRnVA068tyyLjL61gjVmno9BdtkVQsrkvuMfu+VsWVdyPVBbI5aJsWR2WlTSpQq/3XnHOI5dhP8v90iq78GtuqRPXcJiLhOaJHG7RvZeF2WxUhpj1EvBkFKilkuMqaOaHqnbBSaXVDGjhXj148pAStoQEu1CG2m1kw1F4JlTYl1ncpbpxGUtJZd/BiUrgJAzS7f45SrZBCEXOZgU1CJKduGxSzqb0pWn4wd+++0TP3s1cDUVnLV88fYL3tzdccqRQ1gISaNGRyARz0eSctjNFdd312w2N5xOKzlE1hiY18DkDEvKrMWQ9UByEGqUyPFV4o5LOsgUSVlCVqSaeV4+kasBN2H3hnScCVk0C1bx8jnxXvP5Z2/ZTyMlLOz2G26vdmxUQ9XCTmv2znHWmnOUqQRLYg1nwlEEbDsvwVZLalztPFe7HSEE5vnEm7e3pJCYlxXnBnQzGA2qKZbzzLIINKpcHAkaVipJK0ofCZselZpTYa8tN9ayKWBWOHx8YImVQ5hZloUvs+Lu+g22jVBhHHY81SOn01E+o7rixy5ALCIiK2SqAj94truB/V4mdZ9//jnWKjKRZS5s9xO28+xbbVg8WMv9fOD7H37g9HxGF83N9TW7SVI68xI4fP/M8dMD7TTj1sy2aIbU8AFKNUTdKFHyRuaWKE10QfrilFKirxGIlThtrNZiaSuVkrJMPhrcaMutdwyD8PJ3+5Fp0mxixp0jOa/sXu2pKVDqzMZM/Opnn5ND4uOHI+vcOB8ix6M4b243iq1JhBTJRWJ26VdPa/Iazm2FEvGqyoVV5fc5DKWPmxu+WJwzVBrOWPYbz+vbHdUYCjPxORCKBGt5byha1hAll5f8D6vBGdll1yY6opIzmdZH+I7BeLnwciLMK7EkjG2cwyAAglZJTaBJMTfW1ASjTBceZyS/JMnK5TJlP50ih8ORq+3IbmvZTJ6r7YZpGkgxY/2AtRaFOKOaKhjthMtRZUKtWkNvBoaLzorG+eEDIRRO90988eXP+clPf42frkA3cl1Aybqno8z65W5BX1bqcr4pLgWBfikCGhcz22URYFC6Av9pcu//+tf/1xwAGQ33A5p+KRswg8erLS17nIaN1diWCeczp0/3pHlhow1WQU0SsmOVZb/dY+wGmnTxKSVWBbSE1QXnFamPgaZxoDVDKQ3VZFQm94Ts7lRTGEz3rivxkSPe82VZGfyEto4aMs+HE9qaF/Sm6cASOzqUk05bY3tOfd+DoyBrcr4UPCKauQSnKG1p2ohwrhdiQssr3RYh3PwQEqX9uP8tuUKTLiTrvuMrCAVQV9yayE2j2iKWl5KhKZYYOJ+CCOy66NBOvocwSWGRSqNlWGMFE6kygGZJAXp64s5JZbvGADWJaAYBcohOwGK0xltDrRmNAHyMkj1+K+L3zzlxCeO5rKIUEnRSi4RzCNFPrDSX3ZUxYuMUrQCYnjwXltCdAeKbNj30R3Z05eVhb2RCPLGGTKoO791LAVAqkqJXKnNOLCkQs1hpaoOoBQZVqullqyanQisrTlfWAiFbfv4Xn/HXv/ycvYW7YcNGew73TzzOZ6rWqGlDNfC0ZmqcsdMVezswDhtOS6JoA34iuYlTO/Hp4ZklJKodKUpzSopTqOQqq4cwL7ScudpdEUJEmYFxuyMdIrtXrzk9nTk9BObcUFX1kCI68wKu9wNfvH3LxhlaswxeU8LMczxTauV8OjK0xt46WiqsqVJOKxmDTlUKbEBZ2Di4ubpmGgaWuHBze41XhvkkGp7r62tu9jdU4Hw48uHb95QCV7fX1JgorWAHSLmxUKlOk2ohxpWt8mwwUODaGd44mA0cc+Xx4ycOAmnkwT6zm54wbwZpNOxIwzKvgXF07G+vcFbTShKXicRH4qxju90yDQOpBvJaGIcrtLYs55nzsopbwnvWFLDestte461iGnYMduL5ceF3f/8Nn72KvHul2E0bVDKY1RGfC/E5MGbBdremyLESaiNoOY+ykUnU4zyTi0BuLt2urxlXEhoY++QHinR1WT6DFtiWQklHyvFAOHm24QZ9NXC9n/h694qlzbzZv+KQNtTBMV294rNX7/ibX/8Vx1Pi8DTzhz98y8cPH8gxU1PhfJw5x8C00R13LVdKj7MQiJMRPkjJhZBkmqCsXEy6h7zFsIop3BSsdmw3jtvWCDmJQG4V7ofSwmYoUezUGCluBi+2zKEHb9UOlytJJqvOWqyR1602Q2qCXo9FsRZQWaLMU9OEVllKYc7yeVBKiJ+Nhi7ifKqlUxYbqASnI6R1JQXQd3sGk7sDKhNcYBy8dP6loBt9VSlN1qgGUs1QmwC9lMIBLa/Epx/47tMHnt9/y3p84ouvfs64u0aZAaztTbRol1AOlKFpCapR7QJJM3LBqgv4p+fbICtWBS9N1mV1+6d8/WehgC8oV2EB6H9BHCpVlLqOyugMxlV0K6gaaWFGpRmnG7vBs7OOsWnCeebh4YklFGqR0U5ulZoSeIdqUKt0ssMgFX8pEYOmacvgJ6gyGSgqo9G0VGRq0MRvm2PEWsswjCiVWJckgSNcyH9C1moKMELlK2HBVUlYSlHgDN7Z/v1FRFRKwlgn/GuNCBGtFTpeEx72ZrtFGUtKifMSyDlhlado6TqNd6geIaxKhSYTgdo71iw3p4hPlGWOlSXMxFXYBUJHK4SQWFYpXtxo5AOG7loMhFHgJUntdF5Y48o4Otbo2bZROAjOkXPlaTng3Yg1Ft0uts4fV/qK+uISML2799Z2X3wWGl9JtA4UkkGj6hMVGR9aYyQ+GNXdEwWaHCSDmQghCJkOKdpSLF0xKwXBui7U2l7smaUnd7XWGAaDsmI3LFUYEco68JZUE7E05hSZUyZlOgJZaGXVOmoRz641ihIDJVS8g1/8fOS//T//jP/6X/+Sz+627Lwnz4lvfvsdz3MAM4IuxJKppeH8gJ926N0Vbdrz6fFMqXKp/PD9R37//UfCfCbFQiqa+4cj1TqWEJlXEaHSKnkpXA0DPimmac/xuPB0/sTjceX7hxNBD5xOCxXD5CylBQEyKdhtHe/evmYcDNRIq5H5tHI+HNhtB4ZxRJXExhrKNFJSpq6ZeV4RMb3hdrPhHFZirphBcT1NQpMMC07tcEqT51Xwqc5jd7fkXDk9nvj0w4pzBu8krVOhUdaQCsylUAdHCIElFyZvGbsQ9Mp43m4m2A58MIrz/SMqSlP08ClA+gO6aLbbLUqr/ho2rsaBm1c3jIPs0J0xqFoJPeNhO23IOfP08ISOhj8+PXM6nVlSZdpZnp9mQgoc55V/9atfMDjhF2ynG969gvfvf+CHbx95ej/z7fiB/VZWCXldOR0T8Sj2t2YVVVtokornaOQSmEMlJgSfW8HqyuBkYjMOjVEpDJUpK1wBU6tEEncbp+0X4mXNOdRCW848nR8pywHVApu7DapV5hYYbvZ4PeEavLve8/pa8035hqtff8HyxS3zaSbMgefnAx/ff+J0OrOGyBpEi4SW7AXtLOMwoUojLCulRpSCzajY7/c9yrcRwiz3hGsoK9klu63jJk8soZJy4Bxk9VabEb2KkM9wGrwzTIPFGQnHUVVhmiHn/ILprq1RrOSdxCr/bbUWM47EmokxsK6hB1VVspJpwGWP3lqlYF4uVm2EMjl5ER8OHjbThLMT53NgXU8dC1wZh4HddsfoHGjRPenc0KPFjxYdRZO0njPGa3ZGslU244bQCs/fHfiPxyeeP33LZ1/9jOtXb9nc3IFyKOXReqAqKVJy7aN89c+F95fLWNpwbXosOj09sosxqYpK+U//q//fCoDL/hbdR/9KgDANpINUjUErdCnosmJUoaWF8PSJ/PxMPj5ysxupuw3LwzOPT0fm40zJjdS98WuIrCkxjiOrlgPYW00tipwTrRZaFdb5NHisGaktEpMI3QY3MGiHspLwt66Rq52EPZwPR4xxuGEklSb0PefJSpFLfFHCO6P6KE66adc95GKbQ4IqQqQUYUo752jGopGqsjQl3XzXJ2jr0Xagasc5rIQku+uKROGKulKSEpuR3GzjLd45qSZVwxjIrfB4mqk5o1rlGKLY8NAkBcpJoYRyYCCE2Fc1oHLtQToS2Vma4IyNV6QC8big54XNNGK0wTvJufaTOCSW81niX0dPWGaUUuw2G2KM5FLxRoOz3arZGAcn65MiFfSliLhEL1ekiDLWC1+9FGE6FFBItkNTrbMCwBpPrDJmrqUwnxdSFqyz6umBWiusMzg3UPlxv4y2hNzIKTGHSMOwpEpqGpzrugKFdo7n+cjoB0paqEtk6xVffO74/M7z7/7LL/l3f/tTvng1Mjphjz88Hrl/PnNeK9f7a1nVNREzrVazFsv6uLB++I7nw0Kqiufnv+fDp0fO51NfnxSWUFmyBpNJrRJzI8aErY1XuxG73VIanM4B6zccHj5wmgs4x5xnnLFQFTnIjnY7KGxr7EfLbtTUPEsqZY2EcEKbTMNQm4B+bMiM2rAbRnKRAJPWq754lkSzjYXtZsN6PmGL5e5mT5zPtNPM8cNHbsaRFgI5BM5PRx7f36MzoArn57OsgUKlrg1bNaeWeWqZTYMtmnlZ2FnP5CfWBm+2O9rkxIL32jAcDzwcIiXD8TnwD//wT1xfX6OsYp6PbHYbdtdXoknwIu4yVlFixDpNzZJcWKsIhefTynpOzLNE8aaQOR4eWROsSbHdPhCS5vXrOwa/xbuEagM5rByXxOlw4L05YY3kJIQ5oxJsDCxjQ9cIRTroEhNZIT/LAG2AlAT3e2pQI+ya4sprBm2pWqNTwpSCKcLp97oyOs3GO6ztW1/diHEFKufTib//j//Au5+84f7xgWE/YQ9nPn54pDhL1Z2/0SPNJ2XY7CxnIqwVcztycIXDIZNGx7jZMUwbmtGsMXM+L3gz4YzBOuEfvH19h3OKUhZoBavhcDhipw2DE93HZrBcbUcOc+EUFCFHUhXbY+kTV63E87+dBq62QsoLYSWkQEodoe4NVUn+Q0Px/PiEM5pxsGSt+XQ4Mg5O4tV1IdRMLDLyl75DNGFUcXYNzmG1TDKtkYKsNEEJl6JEHF5yjz0XIXFcE4+fnpiGkeurPbvtCEoxn1dyMmjbxIKnYdAWXQqfvdrz9PyMKrC93jKHZ/7wP//3HB6/49WXP+WrX/4KM1xhttcvRUVqEr2tus5AXcKfekMEiJaq/ssrupYq530nAv5ZC4AXvO/F6vfPbAYimAtC6Uon4vxImQ+cnz7y+MO3mBixKTNYxXw68OH77yhLoqyJ47Gx3TjpghGfukVRUiAthZmG95Zx8litpKNsCkXCKdEmKOPwWuKAS6VHvjp0qcQiKnznvHTWtUlEZEzEUrDOYv3YE+4g5UjOojb21uHdhFKiWs39YPTeCxHMSHkmo/JLFr2IB0sTEI5TuuNDLV6NkJMcRjkzrwvOeYyS8fcwyNuRL6I5I7P32l0CpWn5Z03QvtVasQ0Zj8QmKaHn1ULMGeesPEjKSPdudFf7C1G9tM7itoICjkVjG8RURUVNY3SeCl0gGF+UpqXWly5VRoASKSy2vtLjVC/Ph6A5RfUt4ptSGpUAmJ4FAKAJa+ICKS+1UJsSX/4ie/MQougIGtii0bZbYVTDVqnoS2mEdSW3ivEDTWlCjORscNOEpbKmgEaQx+clsByPbK8Uo8v4Div66bsb/pv/3V/z0883vLpuvLvx1HTiFArzXPnm/SM/HM5sp9csaiTGzGEOHNaZU4yc48rzHDitUaZcTbOGwnkJxJz7bNVSqmHNilZkj9bUQFINXSIuVna+oY19SQuTxErIFLEyZrFUbbzlahoZjIwed5NjcoYcZkJYMFrAJ7U1lrgQawbtMVpT4ko4z+jWeHW9IaTK42EVDU/XYYxGMVqLcpoB8ZXPxzOEQFg1b99uCU/PzM9HfKtcD/1j0cBogx2sTAWLwmhLTImlNdYKExptDM5ZttZwbRQzSlYzfkTtFF6fOCyRtYgu5tOnB0KujJPl55+94/Wb10CW0bTVF5G6IJaRgK7NsOF23LM+Rp4+HXifP1FXWY/lAqmjoH/48MQSKuuSuNpfCXmREaOjdKGlsK6RXJKwDTJ4A9qJMFZpKXSraRSlaD3OGaOhCH45O4NuAshJgyd4T8mFJUYGpZicw9v2QnzM2hCaTFZ1bTiUJMNZw2Ado3UcPzyhnzX+amJ7e810vUWPnlwruSQ5T4pohWquxDVAXBl05nbr2I03KGvx0wY7jDQlEK7DaeT54cw4SQLfZjvinEFReH17w2fvXjOfn/njN7/nuATW05m5Kqr1qGZxRgr9GDMpyflmXRer5dZXLY7N4EFVwiJBVFDxXqaxtVWcEXiXuH8rNTTc0LCDJ1RxcSSgaEPRMlpotdG686tWyGsmxyzRw15E3daKPkwpQ5dBoCuAiNLFImpAyTr36fnA8/MT4+DZ7Uaur3Zsth5r5T5wyjJaTz6dmJRMCQoRdGP0HhUPfP/bf8/Tww98/vNf8fnPfi1R7QoamlalWdHW9ulrn71fxIEvd7HusumLfqAi9Mf/pDr4X/n60wsAA1yKgJfqoonwQVW819i8Mh8/8vjd75jvvyeeHgjHJ0ZtsFWR4pHWIjFmlnNkUHBz42WUosErURQPztBqJbRCK41Ixzd6Cwh5LrbcCUgVo+hBLrJ/MdoIC6DKRaCUjLJK72r8OFCNpYbEZruh8mPwhLEjuRhKTfLzGiGbX3LlJcXOdBtKlbjaBrEWQinE0jpqU7ryVgR3KmE2FtshIqVCKpmG7hY6gU1oLSlsSwpkhAnvvOzMlNY0LR2HvShDtcV2nr/pCveUAx6L90K8yiXRqiSvyaVaUVrUuGuuTJPECNcGOMUSM2ldZQy1FW5BrhCLCLZyFipbjFGgGRdErzJYAxgLOQGZki8rE/mjUjtDH1SWUW2uta8OFCn1D0CplM4qrQqaMqAtbjAoN5Cz/Dql/BggFGIXa6KodZDUxSAXi3dXLOuRw+NMLg3nBgyO8zlBbrzZDWxs4nYyqFL56qs7/jf/+i/5xU9uKPETgxar6XE+clwCT6fMHz48c/+Uuaob1u+PnM8rx2XhFBfOKXFKiTlGQm4Y59HW0TDMyrMqmcS0oinNEEXOgXG6xySLCHaOhaod4zhha0P1PIpcM0uohCx3irOK3TTw+nrH5BQ1WfajZzd54nKmlYh1jmH0tKVwns+oIhG8uRisMez3G3ztcTu1sRsgZsXN3Y7tzQ47OpYaZHqTI4RAPp+4HixzqthWeP74njwnNlozDsKmCD3u2Doh+uncqJ3YF1slW907MPkcqNoYNOybkQWSdThrmfzAwzhzfz5xCJGwVlKW3XH3d4r0qoLRlqvthGFLXgMtZwZj2U8biI2ndCA+Lrhq8GRyMz16t2E0nI6VmJ6Zl8jtTWAcRkKs5CLMEVU1LRdqd+O4AabRM20nNqPY0VLLxCLW1kwTjYgx+I1HlUxVooMpWUmUsQZVRSvkayMZy957tDKElAkxMiIrBa9Ek+O0ltREZdFZsYYFu2p0asSkYI7oQdJVi6ooS08GFZ1ViJGaRC1ptPzexs0GO440penGJ4IpDE50Mk7Lha5awejG3e01P//pV/z2HwPbaUPKjbWAKY0cZQp4Wc1W2c6+CNiMAu8V1/st22nCGiWYYy32v9Ztuc5Z4prQTsuKKollUGlDU4bzKq4wpXpaJAptPQaLN4q4BMJ6mTJK46OVuLGGyfX7Te6JS5Mj/6ah0vHFuVFLodnLxas6a0Ps72vwDINhnJxcx7WwmRTKNiiZGJNoGfRWgsZi5rvffyATQDXuPgsMuzeMXqOMu8iiRXPW2o9SaSVOAV428Br+Fxf+n+YD/M+bAOgfaw35H9npalUZrKKGlfVwz+P3v2P59A2+rkxaRBdGed7c7XG/+hmDMnz3++8IxwhU9vsdWosqPpcqMBpkB9I62GFdIwrZEykt1XxrMkGvVTpK0x0IooJUNGNeQBatCaHPWI0fJ7RvNB1kh5wTqWQqAuoQdb8IcXKVbtZaCVm5DD7EEYB4RXsITu2+Wuc8WitiV5iLx0WogKXKJdi0fJ9SC63z6mOMkj3PJWVR7Iw5/fhGmwtuuXP2VV8UCSLS4qwQsLSWXbuM4oWkJSOkRqoVCixxoZ1mdvvMZrvpFejQHSeOqg2htq7E14Qs4KWWC00ZcqwYo7BNPiBGFUTfI0VNrmJ3yrUJOERL6lytIszTSndHBcRYyKl1QpbuwCXRD6Al7S/XJvttxOeecxF1fM8YuCRT1gtP3xoRWNbCGiI1V9KayRHwM0VBPAtN7Wpn2RXNF6PnL//ia/76N79kvzU4myja0VCc1srHY+L3333iu48n3j8sfDokSnqiBUVJikglAQFRI2M9ZvTsbm4ZplFWRIcTcV4pTcA4MWQRRbVG61nfWjVKEH94aVXAOk1eu8uHuyJNgFGwGR1X08DoNNOgMG5k4zSmVXSTAK3NZoOxmjUEahV+ROvvEdaw3U5sjGVZA7DizMD2as/d6zum7YZM5tPxkWNYICb0urKzgpAdJodDkY0mWYNRFtUkyc6USm5KCGrWimAsFk5BVgDRGKKCpSRaqGA93nqmmknZUFUGZ7GbUeJ5nUKdzyyrCDmNKoTzTFxWjFUcTzN5Wdn5z7nabchFYUzBG0deVj5+8552llyEGjKjsRQzkGNEk8CImrqUxvEorpLBT6QgkyiVG+SeJqob2sozmFEsMeHHsQtaRaHdSiH3HAFqFvS1kW6yNiONglZUZQQ1O0hzUrRBb3YY48jzwvrcsb0gawIjzICmpSlSteBxeGUYqoVzJMxBYqC9x44WvBLlfq0iwguJkiKxZAml8gbvNM5qUvfhWy1TB0PpTWCvVtEYBWFZefj4ifl0wmnDdtpAlJ+5lEaLkv5Jk04fg+QgVEkC3G0819d7RqtpKVJLxhmD946ShB7aiij8NfIZDqvIsbMtaL1gTb8bFD0qXGONg3pxIfXUTg2DFVeS7U1f5eKfF8uhUt3SLHNSaTRy6QmKBmuFRaKVJPDlkjkdFsKyMo6W7W6g5koOGs0W5WEcLJtxg82JqmTvM6jK3ldOH7/hm1ooOfH5V5rJSsJmVp6MpdZe2KiL+0m0DOh/HvlzKQL6Qf/nngCIDenlL2hcEocEwdhyJJ6emB/fEw8fUesTTkesqoTUUMOecdhxfb1hefeKlivH+xNhXtmMA7TOC9dV3tiUaCVR0MRYBChSK2o3CelLy+Wv0f0Cr8IEsFIZ1W6c8EY48zkVKj38pV/EMRU5XBB9Q+2KU2PEL2ycZe0P8mAtQ+fnp5TQxvbph5JwDwOm9ahNCRCnxfRjwE5VoCSUJiZJ4lNa965YdAcilKt4PzANkuJXqlgBq5L9vXUSolNbxtoOhGiFVItYoKzDG0MpEqNrtUbpQaphY6XLyZlciyArY2bNMIWCd54lJK73A4M3gKGmnsltLSlViVjWBlVE79AQK0zMBU0HMcVCjOGlS6+9iNDWUJvplhwZ6ZUmHVuqhkJlzZLpVxq9gKg0Mjk3EdjVC1PBwiDuDOEyaFQzoheJkretWkFXWMPM8XiWxLsuOJqM5uZmYHonU4udN/zqyzv+6lc/48sv3rK/3jCvBw7LkcfDifVTZCmVHx6e+eP399wfAuekOM6N83lhxIjf3RiyUSylkWrBacfGepof0cOGGBNLzMwxgx8pRlOUdDxU+dmlmJPQpFoy67ywGE+pTXaaF9eLVpKglivbwbLfDAxOM2iF0Y1WM+v5JM6ZaWT0k3SjqVGKlvezXDgPjRxWGf8OlttX77i62nF3e0suidIqw/aazcby+++/Y8mR0WhUhnEcefXZO55PMy5NnMIJcsUaR6oKjGbtUxrnHJpGOEfKnJmMYpkcW60kpyEXhmYYrWIsRZLlyORWMH6L2WxQk2XcDJzOB56PZwHLhECcV2qrPNx/4s2rG/RbMFnofIPS1Bg5Pjxz+PARVxwtzmysxm22ZONZS8WUCtowbAZSTYSYOJ4D5yVQolAVTenK8X6BKKNpis6TiPK+WIO2YnNUWuOAyyGhVcNaMYrVF3cNGGMxCsraUEZRtGF1mtIKSWWSlYjrjLCBUqlkIjssW6VwrbL1I7pqdNIYZEVmikJnjY6AseQigCaVgCRnXq1ZGo5SUK1Qq2gFSoUSAjnM5BjwfsJqWfWpZmkFnu8/UdYZrZtccq7SVKC0QssQSmGwDaezrDsVWCfTW+ct1jqcdRglrgfdL3qrwTmDNgJIMtViqoIMqgjTQDdhapiNwTiZBtZc0UZsxKXzXXJJOKuwFrwRIqTVYklsVTr4ohutmR5uJA1KK/K5hIpSRuin6C5e7BNw6OvjQlsKqgpFUTPww8cDdjRc7TXTRiLZlWqksLLMR6brPWs6c/r4DR+bYmsdO2PRU0abDcrJhFpOUNsv+nYp/+UWbvrlMwx0iuCfeQLQaH2Efon56RaFVmXf0DJhOXB++kQ4fMKuB7SNtJopRXFOWQQ51TFtPJvtSFkLg3MS5kNfA/R419YytYh9RoAOwpJOKfc1WuOyVutrcdoFotMarXYbmraIa8zQtNhQKrwcfNKFy5spKwCx5ohNTQRsNRcSsk8sKQkZrgloovQJg7UGS+/iSrdpvLD/mzD3ayP3ZLqKFBnaNOjrihiTpEwlIU5hBCs8OIdyRnaZWsARtZnu9VZiH6w9KKI3iN5ZEQsZsWpWLl00KCNVZcqy80xzZAlJDqpny+PWcX01st1NOOekqPCC3Kyl4K2iBrFfDgpskyxxmhCtUlkJMfQRvcBOaulhUVqyFnKRD2bK9UeFLpLUaNyAHhzWDbTcR4iqoKyTB1YJshUlnu0UZQzXiiauiZQi2lRSXJnnwmbSfP7Zns2gSUvEqMJP3u35xddfsR0HqLL3f3N7w1dffUkhcSqR+2Xmd9+/5w/ff+DpvPJwWDmcMrFomp7IVQk6uCWOuXumnIxN1yK5DkOuqArnmMnMzPPK4XTiHLMwFYwV6EvNWIp05BmcqlgjU7BSBG3a9a8y3VLy3BYarvun/WDYTSODhrLOpBCorTJ6J2uoAnHNhLVQsxImeelrrJRw1fH6Zs/XP/2Kd2/fiEugFY7nE1orbl7d4j5qvv/+O2IpbMYRYxX/7r/6t7z9ydf83//7/4FvwvfUvsuWAtn04rbRjJFo7ZyJVcbB0SiS1mSt5fIsGRVXfBIW/9gUsUHWYjc1o6dZh5scu43DGcU8L7SU+fDte7mEQ+HVtjE/najHM6PRbJ1lPT6zPD1zNY7kc2brPN5azGbinDXmAlYxGu9EU1R1I8b842fdSPNbGhI57gzNa7kwNKAqdbRU21HaquGUxurWoWMVryreieMpZmlMYiqUokThrsT2nJXm1CIqFlrLqNGRaiM2sCVjcmIT4VwSV1ozoahKY1NjtJa93rDbTHhvxRGTRKwdUySWKB16rrTSZD3pvThtWqOlTIqyIpjPC6fDAVUNrSZSiL1Z8gzOYvGUHMk1M0xbcQzYCTtUOAfmtGC1kXXuWgiq0ax6UbGnnMg5UpTAd1prL2mX1liGwaKiXNDrGtBNc713jKPl+mYghJUUA2lN0jC0hvUWZeR8pBacAeOd2C5zI5ceYlcVtPyy3hbLswDExAIteQcxJZkiloYzPRvASiCP0dJoWl2pJTLPAUWTIDajcMlTSayp4qxiu3N4a9kMlhoXLIo0B+7/GHBVsTGeV185jB+Rp6OTAjFdC1BpXKzQ7X9p+WvtUgv8+QqA0sSO8lJpNKTU6MUAreKMwhugBPJyoJqEs1o8+WS0bnhn2e008WZPWjNzSRirX1SauuMOnTFkI/udoBWUTCmVGCXiVavG4A2ud8HGedCaVGu3RfR9uO5VYZMHO1XZ5TTAe4/u47PShWimSjees6i5L4z6WoRh3npHX6ssYJSWsfNlH6O6Ir0hopJ2ycRUrb8nchHqDrcRbj1AFdGeFtFKCIGmJMnOeInsNV1EVKu8Hxffp3GinbDWYLSS7zF4GX1pS6mVHOWQaU32SSklWhdYXgqinAqnufB8CjzPZ672G7abDeM4QD1Da1hj8MYweEcrhXHwWG0IYb0YQik1iOAIudhjaqSUxT6oRcGaa2NZEkuIL8AgAf5YLBbTpLBJOXVqmrymMSVCXMh9hLiExNr3cP0xlA7DyIjv9nbib/7qM/7Lv/s1XleWwz1xOXG33/D21R3eSFHj/IQer/jhfOLh+MjzeuY//vaf+O7TA8dQmFfNGhQ5DVizQWHJMZGSjBYzlSTKRbGCak1VjqKFSPh8OqAbxJjk+dVQsoxSrQJLpalKbkXS05zBWIOzIoTi8smTzFZQql/eoiaPYaHkEWcnrIY1razLzGAMWcEyr5TUmNfAOkdSKkgTY7Decn295SdffcEvfvVzPvv8LYM1pBRZ5zPjYLq96czh4Z6WI6MxOAWvbm756U++RHnL3X7LabtBrZk1hb4CEFFmtYpmXCcURtZYREgIrLWxmobVSjzaKaOXgPMDkzYURAcSlcIYCFZRlGE3XOENnOaFw2nm8enMssjR+PD+ibFWrkbP1SgF5XI60ELiatxw/3AvwTtoYgzMSyGs4aWgoq+QRuWASkoVCV0T8WxuDWVBW0ln00amMRLEIjoHo2QSY6wVsbHVUqiVyGZ0lFYxQc6ktciKoCmDsvLeKiVCUTsazNAdP0XAQaUmWM+EJbGWxlwqvsCxzXgUm6xZjGKxCl+sRCnXilkC52Wmqob2loqmNYvyBm0GajXEUFAGIWUm0QrUXLE9rjtFIYFqGqokdBMOf6uFWs64sWGGDUYr1nnm9HxinTOlR2o3DVX3Xb0RNkpOEuSTShZNlxFBOBqMqlirGIYNaWh89fmOV3dvGMeR3X7HN9/+ke+++4bz6UyOPSuhFkrOWG3Fwt1Uv1uQiUITDUfOqdMANd5ZSdMrRfQkhh+bLGT9mCJknXGuQnMY72QqIBKUPiXQAlBaIsdc2d0NvN6+4tXrK8Jy4HB+wNnGMHpKDdSSGZQi1cDT+z/yrfWMdmD79RY1DLTe4TddUFWDlhW3ahd3QPvxKuZPvvv/8wqApoZ+DHV/4cUc3i5MAHDei1rfQIqBSkJ7hzcKM1m8N+SY0FZz+/oGay2Hx5H56UgKgbg2SYvq4hrVJHWvFrm0c6u0lvDeyWioWLHqOYN2Riwbvd+l79pDjjTb40BzJsQCymKMx3lPzsJ6FvW6JNmp2rBOdphaG5S1LzAhpTTayMWbm9gJU5X865iKuA4u4jy0qKC1pmnhj2M0RslOvbT2cmG3VtFKoktbP2Bkfy4dja6FAY/1HoxcHs47QXyWRlEFa2UvUop8gC8K0Uol1yhxsEjn2GoU9rez1KYISaGyEMfm0KjHRmkLMYM+R8Ii6udhGPHW4ZxFt8Y4RAlsynKxtZagZbFj2e5CMCNK0YWPhZoUqcIcNWvQPVypvlxz2ggXvdZeALTa9/ldOb4EYhTARwgQUwd6IPv8pmU8+PYO/ut/+zX/x//tv+HLL+4IpyfWZWQ+H2lZdAKHnFjmlfV55f70keMa+eN333BYF85rZK3QtCVXR6oarCc1S1yzxBJrJBPdIN2L0SijsP3gsE7TdOW0nNFNUXv3oZFCTyM2SmONWEerEOKsclin0LkRUuG8JiZlpVtT4ABXJeTRZ6jnQN2cqJOTTPS0QE0UlTnPmXkJOOeIWZDPUm8r/HbHu69/yq//8tf84pdfsd+O5LSiamb0TqxQOXM4n/lwf8/D/cOFAI6isZm2/PF333A4n8i5sPeWhUpSWWJXjaMlCeyq2rEsgWUV739W8NQq25pxeBkFo9CtYZNGl4KxWkRUtXHOGZUio1E0XbHeYfTEtBuY9gPWa54ez4RTYX0ODHeWX3/+M17v94xUzsMTh6cnSi7EFdYIc0nMc+YpZM6xUQdAV0ky1BrnlFyQrQtacw+usYBRVNPPGxQFyQxZT6k7H8B72G4HvHXYQWNMwymP8gqDk514TuIW6GdWLcIPqMqivMY4J9voXGmDlaleM7RBk/1MXCPn0vBV81wrg1ZMWjHViF8KLomQ2TXFpAw5ZrQ1uCqhX2uR+NmWC+W4YFwSV5RqtCqd53a7AW04LwvWW7xV8p6WJD9vTmzHDSVDSgvllHieAw/vP3F8XolRo7u4Uynx5tfOTxm9786iQsuRRsFrw9Zp7GBw3vDu7pZXNzdst9dsNjt2mxuur6/x3vM//gfYqoVvvk08HgW9XmqmvAj95HOFEozvOAwYNCkG4ryga0M3oEr2jNYK9CUxVVY8fhgwuqBVkmkrlVoTWl1Q5gmskiLC6h5ypEhNcffuC/7u//B/4u2rG06PP/C73/4HPr3/jtwSpURxQWjD6D0hrrz/w+8Y/JafDHv8O4dxO4pyPZPhR1u16Re/PHmigqrI5Kn9iWXAf4YLYIRWugCwf8PWCwDlaMpTELJXzklgPrWickX7gtsUbH/A3bClDYZcR5RuWAPzQaqwGgoprrTaBLVYNc5AMRBSIRWFxYH2IhjLgLYvgsjB9HF6WmXYbyS8R8RksodWF7Kf0mgLxhpqFCeA0nLBaysHtDNW7GtGvkNpldKpdK1/39K655zyQsArVVQIzmi09TQnH7CslIjomuoj0kuBJV14VbLjNl6Sp0qV5EFjpCuoKVJiptHEG4tijasEgDDinJVUMS0OAIkdkQMNlUkpU2rF9ShWdJFixTpyMaRSKC1RgRAqKa2kLK+97PErzsh6wVnF4DTeGayGHCMpLSjV45mNYRhH9vsrrPUsy8rj88yyREIshFRJXSyYcyNdVNytYazCe7GzlFpwTjMM/eG3TpjkuUsrTHnJflBKBlPWwO2V4yefveKzVzs8ATuCaobSJo7nwMeHI9+9v+eHT08cl8Jhlov2AkAJSVZIpU8elLIY0zsze9nB0bUZrr+eUqk3XfvzJqzx2rPNSxK89GAliVIr08EnDYOETGmlJYyqWlqTS3uNlWkw1JowVEbVuLYarRRbo3GqsGkFmxYaGW8K2ivCKhS10hSTEkCV9k6CUPZXfPWbv+Fnf/U3fPb5O17dbnG6sB6fmJ8fePj4wPH5mYeHB1nppMI0TMSSmNeZcbPB2YH7jw+EsEpsNo3Ja/R2QBuPn3ZMWRGyYkmV5bwQQpbAQwfPCkZV2RrNTnnGJjZZE0TAaF2l+kakEsNMXhujdehBY7zCeMuIYbMf8IPBGTipmW0b+PUXP+HvfvEXTE2xPh/YTpr6HPn++Z4lGOaiOObEISZOBYoFM8ipaJ2mUbBa4SaPtw505HRKlMvHncvUUlaXtq/bMPKcat0k3GY7sL2aGLyjkhkGJ7biUiliuEB7QwmZkFax9g0eZx3aWIpSQkysCatdz12oNAN1HGjO4BAgzpwSDsWgJJ1RRKBNaIi1sevhOU5JyFjOlZAKNYhyPgPaVJzLOKvwtrHdjtzc3IpryRl2mw1Wwfn5RF5FxBzmQEuw3V1RcubpdOA4S3XugUHBxltSgxoLrYL1io2/nB0rg4Np4xl05WrjuLvd8uruhv1+4qsvXjNNI9fXd5yOM/P5yE9e3dFq4bO9hp/cYvMZS+ZxKQSlKLoxx4Dpq8rBahQCmFOtoit4bagxUbXE+RarMNOAGmQaa43FDA7rvUDljEK3gjca7zRaQa0RWqNUTSyKUIVO2oxhBW5fv+HLv/wrTCtoZ/nKWpr1fPu7/4gpDV1BtyQOiGqYlwN//N1vqcMVPxn3+BsLVr+snoyWO070Bx0g3KcPEtB3iVr/MxYAnXLSpXX9m/bLDoyMyrVBW4cxTnbfFw9JbuhSccgoRVGxdsA7w0JhuxsxQLKRoBfCEknmEoGosE7h2oU9oPoOvY/W+sjGGYV3Sgh1fczeiqinS5O9iYgHNbVo+TVqQ1mDqqKm18YCpfvYJYs65yyjFi2layvdfkbtIjZ5bXKVsYyzwuuP6ypivdJoWjyoqlv56OhcrcRaqPoORxklToZ+ceiGIGGriGlIGtM0lYIfhh5hKyJBCb+pUDKqicJbK5ks5JxoWZLLrGmdBSDFgwhePMo6Uiqc18B+x8tKZV4zawzkLDbAMkdQScaZl8RCK6NZusXQaIk7BthsCrl5jCuczwv3D0fmJRGSdAFSQPGiR9BOhku2gkNWPchdT9VNkt38ILEYpWGLrDPWJUqyola0VjCmsbu5YnN1BdZRjSA9D0vin37/Hb//43t+uD/yfIqc1kzIitIsMVdRdStNLhIv2pTq79FlFyduEudFYFprZdxONKO6VSd3/rx0HUpLet75PNNUY399xW7YkqJYo7yVMCtj5NlppXVTekKljMkNrzSjk8M/a0W1mtEpvDPsJ8duMNxcb9jvJ5SqHI7PPD4kQgNnDdMwYceRtEY21ze8+fwzvv7lL/n6N3/N/u1n3NzsuXt1jasr3/79kafDE89Pj5yfRajbGphq8M0x4AhJk8+Roz0xDL7Hc0dKyTivcW5CmZFh2rJVA6e1Eh6O5FRkpWOkA0zAQuVMYUYz9lF/qk18MFVCvFQGkxQuO0qWHU8t4gxy1uC8x15dMVVDHlduzIbX2y1P3/3AN58eWOcFrRrPpyMPxyNP55VDhbkWltITmPuZaVXvF7TobJQ2GC/7/qoVKuSuQFYvI2XvraTiGclFEZBLwxjFZjsybh2jdz1kSsJ/Soy0WnGDwzWJPq+lYo2EjanWs1YQAmAzkFVFgjxFfY5BXE1aE2sj1IxXmqI1Thls7YjuCqoVTlKFilPAeJTVpCb/ba5Vfj4lK1fbKhtjuDUj1cLV9oqd85LUlws+VCiKZZ3JIWF2nrBE1phY5gWlNFdbj/eVoVhMUHAoIvgGjGlMKuHJXG081xvP25sdd/uJu6uJd29vubnaQUtst46wLsyH99QEpmaePvyR83HhfP+eq8Hw5esbSirow8KKYS6NGIJMeTVYI9PRS1aJ1QozDoSaZIKopaCPKcuWzXppHuslFE0mpkaZl3VrLUUEzVWohqr8aNVrplKt4/Xrt6g58OH+E5/ef0crgdu7dxzuP6HTifPTPeu64j0YN2EUHJ7uKb/7B6Y3n/N62KG3HgWioelQoBfZX+vrzy4mb1X9+UWAP37L/teq7761pjUtYgptsG7AGM9axW7kjKQWpTWh1AJGRkulJlStTE5yvQer8dPQIUAV5zwlQ0iN1CK5yoUorPlIzBJ/6r3rvByF1o7WMs4oBj/SiqVW2V8pJbjZlDIhyFjLOd/tH/JzGWNlv17E+kFtlJTxfsBoI9G0OUvFbqwAJrjEMMpBoS/+zSab21Lptjm5xC4K3NYuyXi1E/94ySPHGImhNErIhllG5zEFBj3genZ5aVUOZm2xTvf8dY267PirxDK3KvnSWtPxuRY/jPhxEtBO3wc7PzJME7lV3DDRlOLx+UzOj4QYaJ1sVvtUosnnn2yk4+4xB5Jz3T8FS6i05xMozbIEzmsmZrn8c6Wn74l74sIbqPR44dgTyegrEYSgOHi5mKtqoFv/sBYU5cX+6jeW7e0d2Qz87odHUjzy/HTPH37/B373h0+c5kDBsCaIWdNUV9g23f3KMukxRtgP8uxVrJUCttWCRn4fmUytC8oYsYZKH0ifKtJKxrsBu9tDVQx+g1e2K+VhMgrbNNQsSYb0w6gDqDyVSTUmDbVnw+fW0DQmoxhc4qdfv+XLL94xeEtJmY8fHWmJpDjjxi13775grZIR8PPf/IZf/dVf8u6rL7l+8znDzQ2bzYDKK5/+8AO/+90/8nz/SQROCgZtAEtLYLKGBeaHmZArOUjsrKZ2sAv4yeHchNYjxg+gN5zTzBxWzmsgt4q2qgulYC2VY1h5NgVfwSu5/AvCnWjadrup5ITo4rAYliqvk1Uabx1b7bliQA0ZH+H88MDj8RvW89yfy8zj6cSn88q5Vs4FlgJrlQupFNGDETJ+KEzTgPOGpkSDPTmD8oYhCglUCnoRDVonllOlZHqlrayBjDNstiPTbsQZTS6ZZYk4IxGyzjusFuImTrjwrdItwE1WjtpAbbg8kFv3sgGmFrTqgsUGOWVcKzhtsEqLTCyK5z9m4XBoo6iq4VRl7NPBtSXmdLn8tYiMa8HpxpUZCUSOS+UnbhCS55pIayCuCQqSH5Eau2Y4nk6sIaGMYjN6mlaMG8NGe9RxIUT5gFcDw6R49Wris3evuN1veHt7zddfvGXrLet8YPCC5j2dZpYzvamyUDVxLczPJ1qC0RhyrmyM5dV+i3UT93Ni/nSkLlUEnIOcfW7wGKXQrWKVwmpFieLW0NLVkpoUnRpkih1FXNRqkV27saSqSLl2yJCmVSnsRIxNX5/ANO2Y/Ib/+P/6D/z7f///5nB8wjv4+su3WDVAS/JitE72azAOnpoax+d7Pnz/R27efsl2f4PRimwMRclzpy4Xf+unzQsrQPV1+J+xALjcaorG5XS7+MPlD9mr+2GDGzagHDEvhFKwKGI9EZfCsL3Geie2ttLYWMeaDrSSMcowOk3bbdhMkLPE3IZcKa1QL/trpTt8QS4TGaMbXLO0IqpyrxzKWlrKfW2huvI9k3LBWYn9LaWLURooZdFG9YpPSRfgbL/4k0wgtJH9bbe1USQWVOtLhKNU7W4YofQgGiU/S6iZkEufBkggkOQ4ixZAGS0rCmMQlIR44bXRXRAji+5SK7pWjHMYLKmjjFvTlCxOBVUhrCL0c9Z2uF5DW48fPOO0Ybu7IuXC4XiC2ri+vuLq5pYKHE8nPj48kpOEAjlrhdvf68ALo7r1Igd4wVfmIroKo0URfzyvpNzH/UVUJFVfLnrp/FsvAC5/P/PivkEBtV7WL4U1rFhn8M6JsC7XHoQkKvHRedyoeVoD/8//8e9peWZdTjw9nKh5pRRLqrq7SwylirASJaPbS62rKtSSaD1kRGsl6YAKcY0oI+r6msnLgs66x00rjOLFp1sb6JBk7K+grIGcF0gZbywbCzZLF0J/gozWmMGi9Ya9dVz5Aa9EP5B0xtSCNXC9Gbi7c3zxbsfnn11jtWY+rxweJVFuM028/eqn/OQXv2ZpsH31iq9/8ys++9nXXL19jdvssMZw+vgDH37/j/zwu3/k+PABlVdKyDgFsUkmxnJcOB7OHJ9nDo+RJULhSMiB7XbgzfUtu/3U8x0USjv8OLIEmJeZp8OB0zmQEhivsFbocKHAMRZGI0Jih0UAcYVRK5zTWCuUyhYzLooifm2KkgutRdm5d7mxsxaVM8fzkdPzM9CoRnNcZx7iwllDHDUlQY4yhgdx75YKMVbmU5D3Qnv85LGjTMSIERVFi9H6M+983/uSKTXjnUF78NYwbgaJH96OYulcKjZJ2qdxFm8Mqr++xogdLnVhbJPxYncXaIwyIkZUDec8o5vkXMuF2Lva/fUNFoVpoEqmtEyNkVSbxA5rizICHAtock6c1sw5yAREWaEXNgWj6aQ+GjFG1P09UxH2wHI8k04LpjTKWvDGEoukjtbW2O+3jBtPzKFPwjL7ceXrd5ZYwU+et+9u+fzzt9zeXDEaw9tXt3z9xeeksPLbf3piXY60ZFjnA5vNJAVyLSgklTTkRAkFUiWcF5bDmbpGfPOokAiHQF2brFk8oJ0QYqm0cmknFM4ZYhJnlraaomQyGhCXj+za5YLVWtNwXTyZCWvuDBS6JVy0QKhGU5WpGv4v/93/lXmNIr4sCdUyD9+/52br2Q2KGqs0CKavJ6jQCuv8zPP9D8T1wLWWCdAlMdJ0K6Zufe3c5LmQr85P+RO+/vQJQJP9LKp2xWEfTXWlt9IWYwfGacdmd8087GgqiLgjSaWkWmKtM+iMcSNKGUIIWCSMRZT+UQQrg8c6RWqNzXYQMZ0R+p6toLL48VOK8iG0RvbBCGXv4kt3xkAp0pEqJV2/EntSvQgqVG9Dm0IZi7W1OxxkHJyiqFNpfU2ghFpmlaG2nm7nDLo7DdAa7yfCaaWqKqTAUlhzJpaC0hqrTNcJiOirabikPygt4jGU6ACckTG0DJ8vABLF6KcuHpOOtWH6LkqhaiV1QYt4T6UqvAgUa9Ocl8C8BE7nGWMdt27g9vYVKSfOJxEX5ZRE+e9q73oaIdYftQutX9RdAG+1pCaKz//Hv1+qenFK/PMOufRJSWtcaMovnXNt9MmF5MyDkuKGJjYqK2sNVGOaBq6vr5gmTwhnlvXIb795zx++e48m4XTFGWHT5lRJUT4szjgUomDWquGcWJM0Gu0V9FWN1rJCoCS0kbGztbIGSi2js1h8vOo7fC0Fiuu7/rQmYkzENQhDrPaiYPDsvMLUzGD1i0PEaYVTFjs6ttbjUbSUsbrRvKVtHX50vHt3w9u3I4PNtLIwTntSgJgjyiiuXt3xy1//mp/+xV+xas31u3fcffkZ4901437L+eGB+x/ec//NH/j43e85P36kLicGaTFYUmQ5HXl8mrl/PPJ8mjktK/MCWcHpXLl74/j8i8/46uvPME7x+PhICAltHcpqlsOZx+dHjqczuXZ0tHZ9WpUoNbM0ONbGqGGw8nykLKu2TZNRkUq1f5YbicrjWnkqUdwyfmD0I5Md2JqRXCOLypTJSpRxyZxcI2wNayzCidcGZTVGVuovzxIVYsyouYEs+/BaYUbPMA1Y50hBnEPGKobRC67WVGrLoCvWKcbRs9kNXF1v8aMnrIsIVp0hrEEYFkZTk3TmznrxntO6qrzvyFqjNYkgTyXJpEJJA1JK4XQ8ErqY7ag0Dhn/O6XQRTDcaBHkmqbwxuKsQ6kefq4a3lbOqZJyA9u13QrMmjDe4pzn/vmML0JszUvEoxmMWCWVMcxroJRKLnA8rVQSyhTQle125O27O8bdlmm34ermiv1+R2uV+XjE1IaJmnDQrMtKXp9lnWlHvDOUlOgudPG510qJgefHA8tpJiXBNqtmGJ3jZvK82Y8otfIUxP4tbBGZ5OlS+8RSaKs1ZinsjZXmg94g5CSrOOR+EGywuNVqKYIuL0W0UEZhdQfSNUlhvf/4zMdPT+gOD4rrCi1z+PjEV1/ccvYNryvbjaVOQgI1rZFTpubKfPjE/PyRVn4u+/5aoBoRp9O6G0NOzYq8OPXHg/bPWADQ/pNf8oIFvuwaNNo4/LBh2lwxjFuiPkIqpLCQckTZSNULVVvGzZ5hnIgh4rVQ70otosyMGasqWnmUrmx3I26w2MGyrFF2LVEAGbXIPo1uLTNWCFsxV4wSrYJR0rFXmd1jrHSUIUa8G3scsNi1JIFTDr9csqiyjcV0IVhK+aWCvhQQF3pfrbVPEkQNXBElfw+8gov1z0qn36hoZTAX4aHRnezXK3+jcFrU9jkLDAlEcHZh+aumMEY+zKrrNIwDSsVvemiItXLoKtXHV5plDqzhyHleWEPCOYfxG6yfiHHldDp3zrgjxiAiuy5aNFJncLGftiJ/XgoyqrWenDO1WyIN8vM1q9C1kEovTppAeYwBmiKLgIME8j60C+xJxnEXb7BSjUah1MzgLdfXO16/vsN6x/F0YJlnyS1ovTztw5PNmMlRRFHOOgxaVi1KsR0GaFLJ5yxF6OScFJdGM3hDI0MrWKskcpYiKxEsw+TY7bfstjuUMrSssNpizIBqmjCvHJ5PHFdZLejWyErhG1w3BMfsOkBGS+I3uVFigpBBW5ySMbOZBsbBMu0mXt/t2fpCiifiMpJHzzmcSaqwe33Lzesveff1T3j9k88x05bhesd4vSWVle9/+w3Pv/098f1HTg+fqPMzY14xYelrpEI8R45P93y6P/J4XDitmTk3AuAG2F55fvGvfsnf/u1vePX6ioenj4S44KeBhufpsPL0/MTT8zOpF5OmpziKOLWhTCOXwqLgiAjGlIKkmnzmaPhyiXau1CyY8PNUeK5B3DSDx/mFwThGO5DmQK0Zv/M041gDpHGgVE04zuSisJPHGUepmmUWN0jtY15VGjUWQpPY7vo84/cDN69u8X6klYRFQmr8ILhu7cDagVRX3GCYpoFh47Fegy5UnalK9CExBQYzvYiInXcoBafTiXVZUa1zLZUAbbjohZSEK6ScKfNMzpnzPBPnhZqE1WEbuEsh0BQaufj1hWiXNMrJxEwXmJrE7FoaS8msRQBATUNeCskW0iSQstMcIcOoGq931xhtySlTFKxLFBeOEnaFtY3bV3u2O0lp3N9c0Qxc395wdbVjXVeen54ZVeR8PvC0Hlmf7sW2nBLKuN4kmU4FlZNgXRNP9088PxyYDzNpSRitcG5gv79i3N3wWjl2uyP/+P1HlvcnQtOkImJm39kMqq9MS2vkPtFWyrKkBKWiitg/Jan1wgyoKF1EaV/kWXTaULSlAK42tBIGBrVha2G33xNS5OHhiFGF6/2GeF44Pa1k35gGRUmREB3T1jO0hjOaabDE5Zmn++/5bD4yDndoysuZiLqQAKVZ/fGr/f/BBfAv/qy93PvymPaKQxm0dhjjUcpRiiLFisOwLJF5PVM7Hcz6E/vra5xzArzR8uJSixzA2lC7sOzq6lriLxfH82kmxIIymlQSqjT8MNBKZQ0RpTyDtUINNIrUY3eNMuQaiSFTlMIi0b1VSeXdiJROhKotA4pYMto0jOvcZW36CFiogdSG7kLEkEVsJ6jGwrxGQkrEIkjYav5Zl98EEuScdEHi1+fFVSmjY6EhrjH17lgyCATmUximTdcq1I65rOQcqVUuXZRGm4FSCyH0S8s5UmqEuBBiZFlFjR+T7PTn+AOnNbLfbbrYrb/HSjLKobCEiNEXIE1/GpoUASVDcxLmdNlTttZpc61inWUaB1KV96o40VJoIyLSXDORIpHQuVJT/x5NUgRp/TWqYJTi1c3ET758x+s3tzhref/pI8fHB9Zl7R27/LvOS0CHUnIomyprH9s04+BEdNVk/+uMsPmNamycFV1BS2yNYjONjKNlmjytFdYwo1Rju514/fYVr17dcXN1S6uK5RhYzitxqaSQeDpH9tsdx1R5PjxDrVjn8dYwobjd7bi+nhgGT1wXTqcDIQRRcSvNNEpK4jzP5JYYRstu65kGy3Zy+HHi6mpHypnH0wG32/DZlz/js69+yb/6L/4a40bsMBJK4HB/4PnwyP0P35Hff0A/PMN8lIufjE6RkCKn5xNzgNPzA2EJ1AbGG4ypskPeWn75q5/yq1//K77+2VeMG0vVkSXMLCGJtz4eOc0nllXwwxfhay0yNtJKgbLi8qEwK8VBjmKSgjU21pzYFdELKS1477Zkii5U06tIb4hWEUgccwZTaUNjGmAYB2rU5KhoRWN0xRbNZtjhxx0pwdP9kZwSKVSsAlUVZW20XMFCpLAEsZbd3NwwDE6QsINDotu7dxzwg2PcOKbtgBsMTWdiacQSqKoINMxZxlFit2speO9YzgsfP32EihSPvQC35pLpITRQp8R2FuJKaxIuMyhNXCPkgi4NVUQ/0rLwWwwaWzSuIsK1JGvIi9LdG8MwaNS6sJ4WMI3BerHoFc1pjtQs56HVMu4/hsCcz9Q1M1xtuBp3bEfDZuO4vpq4vhnY7hzb/cQwDaSa0dYyWEjLmaf7Tzw9PaGbEtpgRwQr7TB2pKBYVsHDH55OhDVQq2I5r9x/eCSvBa8b3mgGLx321dWG7fWOrByZyv3xGf1ekXIjpIozwne4sDSKkkYyVrBNU7PiuJReVBpJFU3SSJbWuuaqr0aaludEGXQV4FUiYxE6H6Uwqsbh+Uxthd00EcOCMx47KA6PZ9h5BjfSOqitZGHAuNExDANrDpyeHkjziek6yX0EP64qL//fb+P2wg38077+dA1AKaAy6NKv+/ZSDzQ0WjnpfBrEEMmp4N2ACd0K2AzkSMsSRbqGhZYb292OZo142pXMk402jMOIdg5UYrsdQAme0w4DD48HEYONA/F85rzMIpIxlhjTC7q2qiYUPaNQyuAGgzYyDtJopC3VLDGQY0Jp2fFUZPTTAGV7tG2/aI2x3Q1Q0J1BH0JiXYO4ALwotVOKHfIj6YF6cKw1kZG9YeksZ/G9SwpaylHEdkp8/lordrsNpTbWJDnzSus+6lHkmAmp44Z7UdFecq6tYF/LZUpRAYHqhJBZVvnzUrv4qTXqOVDUAzElNqNHa8tmswFlCCGSa8NVKURikumL0lJJX4SUtQserZYaUbjcMlo1qjIY2E8ji1GsMbDbb/CDF657aYTaQGlSzEQqOQtwhD5hcDLs4e3bLb/+1S/4/LPXrMuJb7/7hucf7imnAFmEgYMVq5H3Qu1yXW1vjexIvVGMXuGNlLHLMbMcpfu6vh7ZehFUGm3ZOM1uMAyDYeiBKhsl3d/dmzu+/Opzrm6uud7f0Aqsx8RyXnn+eOTDDx8YaiSGxNQSawrc3twwzwu6VGxu3Ew33O12aN04p4VERZkOfOq466rEK73GwGbQXF3tuL255u3rDdPG8xxmHg8nzGbi86/f8su/+lvefvlTlHOkHDk+P7HOZyiBOB+oTz9w/uEbpjlgSmQ5PtFqxjpLOJ5Jx4UQGoSAQ/Cmm2mgxkzTlX/9b/+W//a/+d+zu/bsb3eUsoJRjPsNoR45PxxYwkIuSaZGSFqmfvHOa7wbaCUTk2TQ11hJqdEmSEpxPQ3YImr9loWZoJXFKI0qlXHwqM2I3o0kA7EV2YC2JoTIViiqkAzgHRbLoBqqFJTOON/6SN+Tw8CqKiUknDHUKmLglnqIH43Tw0yNjavrDdN2ROv+uVMS0KWdiPYEYSuQMucdmsISkGhbN3J94xmGsdPoJK1vXlfZtTdFsyLuEiJqFwzXBkUChQSv1kN8jMVNA2rYsM4L5EJdMikIvvii25LWzRBiI5uCdxZnDMZ57CCOFp0LxifQSHiR85jBEdYTMRZpuFTG14YzGa/Funf39hW//PoLXl1vsToxDjCMhmGUM3eNkVrFvvb4cCTEQFhXSupiumLxbsSYkZAayyq47KfTiafDiePjAWMdp1OgxCbBRKWiMdzc7LEKCTgqgdP5ieOaOJxXlEpYCzVUliUyaIEzGKs7qriilEP7gfOaSMvMkiuxVspZCgGvf5x4OmfwZugbYjHblR4IlXSlRlk3bgaLoZEzGJUFyd4Ko3OiKWpAE8y91jLdyh0GZXpbbY0iU6l5JcczrSaMl6TBAnIX9MnsJb5bNArlX8wD/iwFgNIimABEFVsLTRtUk1G3XEKybypZQBamiaCpxIxthslt/j+s/UezZFmWpYl9+7B7r5JHjLib0+BZmdVS3dUF6UJ3Q1qACUbAb29MetKVVVkZGRFOjD2iqpccisE++jyAUZZIhIhFhLmbPbOnevWcTdb6lh7wmikBCbbTSvEG5EKwliaCM2qzCGHAWo9TcTauoruWYElFwyLcpnaa2jUKpXecImoXpBq2bl9UH7fX/U3r8ZQpqtq487xLLcRSlIntLA3ToRJXYYUCbozY/n2rkM90SQko0Wy3G4hVaMZoJKVVW0+rPSCjjzlrVcyoSCOVTKlFQTJeq38fAjEX9Yd7JRpKq5zPM2vUaFxdxcAvkc3XrANVwIoVyIWcMykrgrVUFT72wQ0YoYiwxsrD44l8mDgcDjgXGAY9uK3NOCPdgqV71HYVADQQdJ0RnFHvcasvtkDrlFRoyNjaGCRhbGGUiA6DE1Yyt3sFnVAC67hRkqqGSyrETbMNvv/2Nb/5zXfc3x6Z5898+vOf+fAvD6xzUc+x1fG0c9KLQcM0BZy1lLx18Z0wBYMzmZoWSircThO7/nzc7ALH/cAYnPL1g2HaeZyD1hLrmmm2Mg2O+/3Iq/s9u+PIbnJItYzGMjlDvcw8SoG8sl5O1KwjwNEbzKgcCWsaed0oW9QxMpr2JhYywha1C0IKsWSK9OfOwrgbMeIoVThfNraaufvyC9799re8+fZL3N5zmS8s80JcLtiSKJcT+fEj849/5PLhR2ou7LzDSSLlSNxm0rwQxFKWBVMrQWDntbJzfuA3X37L//Z/+7/w+t0rKhvFVFKrVCvYwWFHD17YaqI58DvHsFXqUvWAao1p2jOEkZg2IGnwV85cWiOgrZZ3jiaZy5JZcmUfDFYqa4RxDJhhgGmkDA47WpzTVVJOiTKvUCDTiDlTkhanpl53pSsVfY9vb0akqk1uLhGphdHrSi4WFbIoCdCwXVaeS6KVgjXCuNOkQ+ukA6k6QKdqkVNKYd5mDRISqzZfFFyWS+mBYFf+hVc2f9PPqFquVXbcGqQtUcuGMYZh8AzDpFbF/j0N+yNl2YhpBbQ5UGGZPjMxJZTa2teiBlIf40XpHABv2UqiZhib7rSrdbSgIst1zjyf4PCF5Q9/9wd+/cVbvvviLUEqX7w6YomIJMRkxFSW9cLpsrGsRQXcPQ68FKcpkDkT7Mi8Csty5vE083CaOc0Lz/PGZdGMEWsTRjRPohlH2I2M3nXaZFTQXE1cThtrUcN5qQlQbHnMhUUik3dYgjp7asU5S66WJUaWrKjl0qBKf/+7LUND54QSddpjRZCqWTh4QzYNUwvWXNcNlSxwu7fsponDNPHq7obD/sDl+Yn373+kVnh4mvniyzvG3Y5SV2U4uEBKWQmYy8w2z7QYwWeqKCBYRBu3l13s9a4Wq03X37IAuIq+ak9AaqiFrbWCoOIXRUEWhZ3kooi2mCgxY1GrTlwjNene3jQdWzkzsm4r1VnGnYZN5FRwrumb3RotKydfqDqWQqlHMavSfdsSqSqwWzpFLseIc3tNsKtKlwtBlWY5RVLKjNOk+5p+eVaK5gh0RvsVz9n6h6Q2oVbdveSsB5kYwzAMau9Tdz1jcJStMA5eI09rwXmrVT0NpzcJqXb0JE35A0ZH9c55bGcPGKv7PCtqi6wxM19mYpffy3UkRfcgiNXRejNU0Z1zqU2zzpvpEn7pSljVGkjvyWIqxC0iAsMwYbt4xfuEdYJEuqdWM+lrFykBnXh8hVPoD+80+11Fc4aUI6TESGPyBlMTbAmfM7ZWXg0Dw+jx1lLKoIdhUchQKZlXd3f86lff8vbNPTGuxKdHdlz44qZwP3XBoQjDEHBeL1gfAvv9Tp0MaaGsGzVv0KLuTJ0WXIfjXvn8VKw0tSa9ec397R7n4ApUinnldPas8cK4CxwOA7vbHW4XaE73985oEh4+U2SlmpXcZtRQZnn/+ZkheEIIUPu6Z16U/NYqlkZqVZ9FY9QRc55ZU8IHwyDw8PSMMQ2+fEM9F56WC4cv3/D7f/v3vP7+eyQEHs6fmM8rDx8/4FJmrIXl8wfS6ZHy/J5dKIhklrwoJc16crKEVIhRuywpMHrHm1dvmW5viVT2r+6oceb9w08kiRzKiDGN5zTz+fzMp4dHPjw/8bzOLHkD17CTIEVH0Kryj9TcSCWRpdBMowRdJT23QpVGI7OK4l2X1lhaxmxZCY3TnlBV0FqKUtGMNRipWCzjNGJTo/YppKSsKYXVkthIJRHFMYbAtBux5oAXsJJYTrpGkj7NUlGrYp9L0bWEsxecASd7glOfdtyiCmHXVTMenFr/Hh6eWNfIbrd/ScssuZC7gj+novHbPXRLKjqRROgCIU3wS1F5ErVxd3fDPoyocUnhbMdxRxSLy4IrUExWpXzUHf66dgGvrxiTqVRayhS7ElGYkIgyFsiaa2KNZzh46jSR00rNZ6Z95s27d3z53dcMPrDVzN//wx+wJXJ++sw8n5mXZ5b1zLIsXOZMlQFsj/BttjsuEtuyUVLm+enMw+dnHk9nTpfKZWskVCN0s/dsMXE8HghhYN0W7ODICI/PJ477AeN9D2WKL3TWLSX9jANrgsucCGZRWmrT4qMJzGtkXhtbh4s1AXGi8ewaZqEap25/lqLFpFRtOAyaX9D6imtNCVPVHt1EUdE+WA77iZvDSIkLpq+oL5/P4CpvzC1DUE0RvegzrZG2SFw3BYtZ1XI1MZSUaa3Q3de/uJeMYORfd7X/N2kAmqgvSzcM5f8nhUhEBVclJ0rWfVFNethT9RKtBdKadCc9aAWra/6GVLlKAJQjHxutOdxQyUUFXVsqVGwXfDiGUjns9zgXOJu5Ax+kU9kMtRaezhetrI1nHKxmZ/sBcQUTCsM4sm6bWm8ErBGs91CLDlK6F9e5X7rsa3RkrloZWucVT5wL87aSU6Wpsk0FikmX0YOfMK2+iH7UwqRj+9aDfKzYnnZntOqUfsOLhupsW+SyrMTctZ6GjtxVT7p3DuMCuRmwGWInB16tik7xyTlfvXeV2uRFMNcMkJvCPNZVU7X6D+c0mQvR4CbvdSJSi04IaFXhJb0IcFYzHXw/lGmJgH7/wQnjoByGLUdcD5kKZeFAZQo7vPUgV2/0ADTevnrFOGTK+WfSOrOTjd+8u+V3X78GCZwuiaencwdFafCQGMM4OQUjW09zkBO0oqI+gz4fk1UPrrVqq9kPnsPouTlol7VsF41gHfaEIDyfDdZbxuMevxsxk9OwmKL2wcxCbDOJC8+Xj6xZgU7GCMf7Pa/vX2OsZX5WjO7ldKEEwzQYDD0IS7Sid8HRlsxpXimXxHmObGmjmYY4w3ScOL56zW/+8Afefvs1YuHx+ROnx2eNVp6f2XmLSRs2Xgim4G8mSvY8PDxx2VZys3gcrVlqFeZ5pRTY7yfMMOGnQE4LzRkOO8e2PfPjXz6wmsz+MDEMjtN85vPjI5+fnjjFjeIM1Vva0GArJNGPg7WFvM46BjMN4wXxqtY0rRExJON5KoWIsgVMqayivIwijXiZcYNgHEQxRMnkIhTb9LkzCi0rWRPaXNOYYmObapSafv5S2mhW38vj7Yhzt5w85CXpiFaEMXhcs6xFpzGmNdKSuLQTQsXaA75aYlvRRk2P1lbVzrhcNlJMBDvghtBXdgoIK6Wybitxy93TrdbqKwPAKFwCPW4sUoS0JU5PZ0xpjFNgcHq2qYNFGH1g2BmKLUQ21rzSUuJ6T9CaRphnneBmQeN/B8AapdPVRl4jdfDs9rcYf+TTp0/EdKJu8F//+Ce285l/8/13/K//4X8g18qHjx/5/OFntuXCMj9xmc9UBOsOiB3ImzpL5p7hMc8ry3nh/DyzzCvLok6EVNQSbAZwQ2BLlZIhZw1dylUJqz44qAVjnToYDBjnyevKZV7JKROCMA7XbpkuEK7kVsm5sq76TBbdPtLVKbSi4uOrZbukRrC9466qMdoNwt0+MHgV8tXciFuDCse9Fi+5VFKOlOo5n59YLo8sy4LxBmcBL3x+nBFn+P67LzDWsW0ZCaqLupwvnM+qUfElUyRp1khfwzdRMTj9NpamU+C/aQFQm+6b2tWH0V8mfVyVD9BaIaeNmhKmFGrJtKypZ7U04qaxrjrSVb9pCCPnpyelZoljuUTWUnA+0PCYGNm62GrLmhSHC7TSqX9G7Vihq2ivVsjUCkvUaYPRuREFIRUdQdLf5FRa96grXdD1vXxr5RfVPspe1pEeOoKtRcN+uvfTeYUz+KQAl9wy4zCAc50YeDW1V0pJSjYzHRzTzMtfXJMMm3pnm+6aU22k2G2EMenEQLQT92F4ERMaY3q3PnBeFTZSrOlgipdPfud7N1wPF2pNrYWtq+5zg3nJII+sKTJNA845gjPU4Mk595WGeoVKa2qREcU5e++QVjUMxdK1HZlWMt4avINpsFq1WyFl19dGGckZn2C38xwGRxg1d8Ab1+ONKyKLTlmGRnaO4AM3NzcggYeHE4+DfuiGYVShVghM08Qyzzw8PPDwfKJsm45QQ0Carn3SNmNRloD3lpwjnz9/ZNsuOG/Z4kKjMO5GbLAsqbAbBg63rxj2OxgFby0tZfKayHmhsWBsJgyVkiBMlrvbV/y7f/fvSbHw4dNn0rISL5G8bOQguJuJYAN2DLhqSHPhclk5zwnjdM1y2TLlw0IYnnj9xSveff8tX3//DYfXN8TnR54vZ7ZWIGfS+YIsZ4LsNAI3dHZHNDyvmql6c3sHFS6PF9ZFi3TtrHXls26R5cN7smu8fveWsLcsLDymC6ey8iE+EAZPq41kG/72yM3uFntIlGHGPm/UcGZuz5SL7ij9oLanYTfhR4+xKoh1Ar4JI5b58YG0FTyQZp0w7oaAs4Z1jbgZhr3FsaN2t4zrORy2r+9STIoWd04LQtSd4ZvSF3NtpLJgjGEaBo5+ZAxwOZ25nBZi7PvVJpAs2UCj0FIltsTmVtbBUZtTaFlL7JhYxZFTJUujZhWNxS1jJOsq4LoHNE7Bj905I1ZtpBhHE0tpCidLq05TpVmowuU5ss2R403g9rBHhpHTutFixhTBi+mxxTrdtMYQbEfIdqeD1NadUhBEqKkofKo1yLA9XZhb5e54w3nd+PjhmfVcuA1CLo1/+ZdPtHXj3etX/PjnP5HnC2RNbBUZsc52gbZlXlae54XPj888PD3zfNmY58qyAKVpYp/VY7bR9dINUsrkrAmKa1SU+TSoLqw08MNEFZiXFZt0NV2ypRXHOFj2o+7yB6/Josaoaa529f9auoa+a5dVu3Vt9JTRoiLiovjxoiu6fYAv70fuDuoKqV14+XzSdWXXe+vayYnqDqpi23NLuKCiVG8t6yV2e23U31dW3CAQFAq3rptO11ulkDQLQgzdydhFgXoOqx/+F9n+36QA0MjB0qcADa1SfykCdPQfietMSRtGUQk40Yvhmvvu/YAY9WPmVBEKeUsMY0CqYcuJbdsoo9DMSpkzrW5YZ8ml0nRhrUKhKtDUcjEOAyEEFaG1RkwbMRac9SiizJFKZTvP1HrmGqG42+26aM4gUl8u2Cs1rzVRila+7s40lU9ER/X9SqWVrGE0QaE7g7Fk46jGMohTKJAXTLN91dDHQn1Uc/0aVwpX6QKkXFFEZ2/YvR+xvnFzG9QzbpUitm2b7vi7X7bVjMEweD30tk2DjmKM3U6ogkbvFGyUW6PmrO+nSgY4nQtbOpFzZL/f44xhGD2uM1NrjZSORqb1DAMrunLRATitaS669wGLwzT9RrwIwRtubm7w1ukoriXOH39kPxhuguNmH9gfRsYxMHjFsua0UUpW66TZdTU5jB62bSHIxquDfs/G6MRiCo7dfuBSE2Y/INuerYOKrLW05rAUioEtXih5JXmNDl0XyxZXpt1IzhtLXLHzWf3tcePdtOdwc0cYR1poBGMoubCUQskz0jJTgLf3N6xD5DAeubtT8tk//pc/8vDxg15QTci5Emsh9R26GItgcdawLCc+P0bEqcc8Jrg9Wr748h2//Ye/53d//1tcED4/fOI0n8E0Bm/J68ry+ESaFz49foa4cDMGKJF1vbDMF7wN3N/eUzPUVcjbwtapikUSy5ZZauZcMoe3e6a3t1xY+fjpE9urgcUmDTKKGWu0KK5OqFhaEMKNcDPt8YcD482ObVmpteHcgNjAuJuwo+uWLxU/kQuT8fhD6Kpq4dP7j5wfzzy3iEl9+pUzh5rZW6g9iMkHdQK5LrIqRZ0lYlX93cRwPp+pFPzgqEY5Gs5Z2jgwuIBzFev3OC+cT3owl6w2McWPK+YbIC6R54cnzKVRbSXsHK3toMA8r7ROTBXUGRVjxvu+2W+88ADo6ztrNZwHVJOUUybGTFwiaU7YDq5KScOwWotQGjGsSKnULWGKEIzFVw1gA/p5pemXcvXuatPMdTOYUqYAdtAJRCo9gzo33n35DZ8+P/Phh4WlNr593dgZeHo683/+p//Mr7/+isk5nLU8n8860a2Vz58feX5eWLbGeY08Pi88XzJr1pVdrRpuZb3t9urUaaNAhEjlfueYpqELnVWsvawb6zkx+g6QK3C5bJrUaAPO7NlNhn1cwBb2NWjAmjhqU4KhxEqShS1pDHeqKB+hVr1Hm6E2hToFZzBZhcz3k/Du9Y6vXt8SrBC3RcWERjhMF87nTamYQdhNA95b1u2Mw7GfFL0+b5EQAudlxQ+B0io/vf/Ed9+85f7mlsKmeivrFf/bn2+LoVrTaYXdnl+1tKX/qP9KFeB/QxbAdfT/14ID/XlrFSjkEtm2hZS2fjFXxRVy3WVbnOhItm2FHDMlJaxxffzflH7VDDlVymUjlQ3vqu71S6XFRM2NZUu6mzEe5z2DU3V+Tkrm81kz7z9/niHmXxLsjNWKqV/iMSeMMSo0FI2qbPqpVGFcKb07rSil1+olL7xQ4a4XeqnqIxdvaaaH+eSKtUYP4275s6WxxdjhQ3r5qwVRyX8tq0CvdkW8DYFpHLEhYKwSyYZxRzN6CM3zTEqJGBX9a61VX7/zaq+sBgnKHSj5F8eoXDUT1hG8RbzyGMQKpXZldoO1Q0umQScN3npdjQApZqj90BBDA9Ztw5mmVENnsdYROigjbyut8/vTGpneDNwc9/r3bpldXZmCcDzuuLnds9sPDEFzB7RAM2xbI+cNaZWgy3lqXMnrhkMV5ykmtlnjR1fjePYDBsvkA7/99lsEyxo35nllnme2kpludlzms7pYcoSOa82172mLQp2WNbHljTVt3H35DrEBg1IhTa3UVCAutG3D18xoIQr4wXGYRkwu/PDPf+T06SO2NEYbuOSo8bklsa5RsaM2aAhOMgogscLjWQWjv/ruhv/H//0/8j/9z/8e2TeKbXz6/IGHz58wZAbvyFHIl5kbMbRx5Pz0iLRCLomcNmLNtNKQVMhzomSw1WEIzMszT5fMWgxRwOz35HhidbDYQmSFW8+5beRBNTetFlrJpFhYLoWaDS05xXhbTzgEXu1evYhWWzXEVDR501u2kjHGEJxGLdMMh/EVt7uDTpr2Hp6edBpxXrEIxRu2UQme1hmsV0CONtcahTWnjTWqPcv5UfM6jKdlIUXFp+ae2VBdodhKdRkTGn5nCcWSiq78Wk6A02lAU5dIiQrRwYMd0bx366Hq5yMXFUc657A9AMpZr4VJzt1Oa7k2VVfMequ6Wqu5kpOKd69OKzFCGPr50Z/J0vfONYKpkG3BF4HScGIQqyJockKqcJ3itu4qEqtZBA0thq6NpHWOLSWen2eOh9d89S7x/PmReQEXgEFx8NPuQIuRy7zxw4+fuJwubFvm4fOZeVXHURXYtJ7AOIP3A8Z4FTGW2hsjg/WqL6tScdKgFbZtASD4ocd/64o258qSCsFZSmwsa9L9vbckQdc3Y0AVZIZqPRXPHDOXJbG1SiaSUiX3yxR6YdRDxhoqZr49WN4cB14fBt7cTNyMDqmJ6Uo+rRVv99zsB2JOOB/UdlgWtrjq5FfU4WacsD/uSaJ0W+8d+8GxP95ze3/DGs+c1jNgyLlSYtbANav6CWuD/i1bH/0b0eemP5d/2wJArv9Vr2aALhvL/WWl75RUANhqgyrULJpVj5ClI32LvhUlR2LUKiiXQs4r7cpDfRH+RWrR8V3JGhcZa+SybCpocx7jAjYEEBWLXSshZz3OmR5U1EM7r4Z7fckQY4k5staMs4ontc5hOjlP84wE4zR3YBgDzjnt0kvuoBhL7pjaSnnRCNSmgBOxg9ozSgYTECopxmsB/vLrYkqkmsldeWusJQyew+HAze0twzSBcX9FtOppXlHH+CmlPspvmitQMmA0+UrUL5vdFRxk+i6sdNulJ3hV4HvvyRSWZWGdF2otmq5oIDhHmAK+6BTIWiX/pZQR0UVa7d2WdR5nVcxSSqcgtqxq9gzzfIG8MbqbF7LicHMguMrhMHGcRsbRd75+htYYvGMaffdsR93hi65Z1rxSt60fmoXRBsbdAWs9peq6qZRCjBeNZsYy7SzjdKDQMM4whMq2+hdbYy6F03zh4flJuebTSKJyWSJbTgo1SllFW6J8fimZVjNCwYrqHV692lPWXiDWwno+8ebunss58pe/fGA+L7q3Fl2Vtappj02E0/Mz5/NMLoX9Af7h3/4d/6//9/+Tf/MPf8eyfOLT5T2nLXI5Pym2tFZODw940c5lcI7jzYGhJUQa8+WZ8+mJy+mMSUIQR9kSMUGqjTU3TmtmqYZzijytCdsqMnm++OZLvvj2LZ/Wz2STEa/WqG2rLDF2cZeQjaEaS3WGVCstR2quOobukzOLji0jRbHL3Y0j1tJs5c9/+YHBeTK6onquC/5uYvA3+POsY2xnMMHCYJHBaDFhddReqSwpcp5XLpeEHyvDTjhYx5u3X3GZTxqoRaZ1Z0XKqllyQBa9gPzgOOCwNnI5J/LWq+iqRUPTrSbOwG4XejiP6k9q0elcaZVhmAghEAZPGDzrWjTQp2qAVWvXDBI9v7QpUovvdb03jANlVWKq72l0OS7UrCLAnPSj4kxPLDat23wrTop+LkWQanQ1B50d0huXl5wjw5Y01rhuiefPD7zd3XC7C/g3d7gywxZ1ZF8q87Lxn/7xn3j6+EBeM09PZy7nxrJCjNDJtbiBjvs2VGzXfxX2w0QsM7VkdkPAO8hlo1S1/o5jIG4LV9/7tq4YNIxsKxlvlKKJHWlWWLZMnC80Yzi8umUYlAtQcbp7Eo9ZM6WtOGO1MLNRnWvCSy9tRDTFMUUCwqvDwHdfvOIQwNaVOJ/xTpimCWis8wURuDvuKS10jkvS1eh+hJw4LStjq4yHI1vcGINjS5njbuLdu7cgjQ+fP2G94qLtOPSGTqcrzVpdIYlOJ0y/jc21cASdjv9tCwCrgiMMSPmlAGh6qNe84gwM3mNweDsxTLA+P5Ji1Sova5rMbhg57h0Xb3m+GFIq+BB0TVA0tS+mhVQL0zQSUyFH0+1OkFMix6JgiYr6b0XHaTnmLmizlJRfLqiCCiPEWGWVl0YIjrQpax/jKTVRU+lkuo7j7IKc0XuM92ylqLLU6tpDitpnmlxxvAoxQQx+dJSYSXVFqscJLJdnjWRtEFOHBDUh10osUJqOA4fRc3d/wxdfvOV4c6eRxdIVwWJYYiLnzOeHJx6fP/P49EipBecU+7utay+E+p4fA7URnNVxZOdd11owrhImx363I3jHMI2klNiNnm03KJ1s3ZjXBaYJX9GCqmsHTL9oqLp6oMG6FFpcCcdAAc22dwqSWc6FRsN7OD0/4Grmbn8keMEPwjBYxmDxXWdgRIsyMZV1OUOpxHWhxIitut6QBr780k02sex2N3g/qvXJane9bAnKQoqKqZ56gRBjJIggEpl2llRgzYWwmyjAGjUmeI2R8+WCD46v37zhze09XgyDCDFuZDQBLngdWfq3R6bRcHp4JE+F0UxQPM+PkeV8Ia+V0XvqQVXhJSa2DVXxtgJOsNJopXD3yvBv/4f/jv/pf/mPfPv7d5zjAz99/Au39yOnpwvkRE6RuFwwTXkBj8uFX3/7LZ7KfnI8fvpI2WZsSZgUqRHmUljWjJmO1N3IuhaeWuXP7y/kAsf7W9Zt5ouvvuR3v/oN0+QZDpWnOpNSJBf0wrNdm5BVa5OLfhbMMJBtQULtzozGumyktTKOR3bDqM4aEVrVUf+f/vQnPvx85g9/+IbjrbCkjeYENzqageHG4bxTtLAVjNFusFXT9RyREgvPD2dOS2FZwKcNqY5sAw/1jPMO6y01rZSe6ZFSRbxl8IGU1NXjgyNYgzOGIMJqC3HV/XGqjZgBDy5Y/DgwjDu2njpXEXV6iHJLrDXUmlmTAspMEp4fnkgxIqb1YA3N05BmGYYRmpBjwQ4W0xpjGAh+R7COVhLz2RDnC2UreNGu3AFGpT4E3UBgSPiqZ2IzOr2trYuJnaaMTlYITTn71jS1BcZKGBuuXjje3/DVq1cM5sSf/ssniqiL6E9//oERQ4mV+QIp6jo6Gog9Y0EzMXR106SBrThx3ZlVsE6gVWK8UJJ67K98uEtdtNm6rl1b0+wQHMYpMn6LkXVLpFww3mMHJQg+PD4gwTNMI2FUEFSTyuCFw+Q5jBPLJeKtY7CeZVkoVcf3QoMSGYCvXgX+8O0X3A6G7fJAcBXjGss6M29nQgi4IJScKdsz+90OW6qKcLNCzpxzhHHCDYolf/z8CVASqLcaqNWozOumNEfrNLrdC+Ih14gYnYAoy6gzm3VD39tao5Pfv2UBUFDxSLtWR91nKNK0qjeBPFfd5daqS6WmWubUlZj73Y6QM1uKXNaFlAv7aSAFtdsJTcUSFqyDUJTBbMRiuuCsNc1PblmDPGzLhGHAGUMt7YWxr7YYo+EaKaG7bVHEpVj1WFcNd6mdVGdEsE4FMbVp+lyTrm+olTWmvnPRdYAxGlLijXYvtEYT5WKLNeSatJi/JkmJ7uSN7bznEunsI5pR+40TfcjvXt3w6tWR/eHIMAawltpU3JhL0p3SuvTLeVGFvuh+cdvgMMr1U6+iwlY6swAVZwLeGZwPDENgHAeMbd036/HBIibQKITkqC3rpSTC5XIB1LEQwkBzjZoSKSZS0vWF07qDVhW/G4wljAPWFMyu0bLGCHsBR8UL7AaHM4ExqJYiOMswDNhgaVJpJHb7Haenz6zzMzlmSA1ThXFQn61mNVhK1i5GL9SVRtUI2rYxTpbD3R25P4sijePB01ImLhvVaNRvdYYiTbn+NlDFcHeYuL2/ZRwH9vuJw36HqZWybRwOByiZn374Ex9//pn94Jh2I3E5k2vsbAtH2hqtao5F2jJbnElZx/HqQlFXByJs20ouC7f3wlfff8e/+ftfM+wdn58/cjje8P3vfsV2+sRqRNXV52e285nBW7xVrUVcF1bTdE9ZC74Hy6h+A7wLiAskhKcl8uE087hmNvRjfNo29sc9X7z7kvv7e9yNaEeUIqFWUi7k3Hrhb/UAFqtan6KahWEce6BKRWgcwhF3NxK3Ss0Nax3rvPKnP/6Ff/nnv/D4BP/u3ylcSdR3ClmILeGNxY4K+pI+DhejUdrGiLowKpwvC5+fTixbxQUdBfvQJ3iifAClmZsXy2yumRaLTjysIwTlmBiDUiMbBNvIo1HaYdoUCev7DtsaYi4a3GIUxd36933VHTUKNNUThOD0890qCQ1IU/CYqrlrVQ5AbZWWG9bo1KGgqvXW1wgxForqOfHj9e9aaUknA/4aKBYLkDt5VGhNz96YFP8rVoW8iCZwUkFaJs0zdTnj7gKH6cD9zcSnAdIC0VdGA9O4wwyWwWYua9HI75g1W6C1DurRulZMw7aGtTpJXJM6gaadnuWklZITAt2Ca3REnze8tygJv5C9V8Z+0os/RoXphEHwwVCaKGtg3dhSxq0b1gcyhm2rrFEV/abRVxDlutmG7ozKG3z3LvD1m3sGA6ZEgmgT0lDirHUWTOu5FA5TK/P5RPADfgwYu6eiTq5cC2XZOrzOstvtsE7IaWOdz1Srz+YwDNhxYLq9Zzrc9M+UR2xgN+xIRXf9eid3rgsNpHRXwN+wALhuFOSv/vvlZ11lmlJkXRfdn+aIzRut1RfErsPjvNH0triSamMKGmUZN70sxXoV5Bi1wuVc2E27TrCLrCkR+5pBUMTr4DzB6YjHilVvbYyIMxRrVS0jgrWWXPXiFmt/EcwVVfUblBENit2sTf36tUFKevl7p7a22rTw0cPaQc0KZzAN6wLVqHPAer1YUimka6IhVW0uvXBTWarGHSuVRzq0I3O6aKKi9Z5mFCoSU6KUysPjMw8PD6zrCihNsVYNMolbw9qi9iqrgh5ndR+fq3IJvHeM44APrhdCque4nC/KKUDJfjSDNf5FqLbOK85ZBje82A+rMS/QfekjRet0ReAEfP/f4Cx3u1ukFhyN42HHfhgUiTuNOCM4r4IlazX2WJPGNmJcuczPnJ8fkdaYphFct5Ea3VlqIqGnlMq2RWJM5FZ07DoFbocDu8OEHxxL3NhiwvuRw27PNj/z/oPl8/OJNa0UYyl4lnWhGcurN19we3vLNAb14pbM6AXbNJGszImnx8/813/8r8zPD3z/7VdMbqCkwjgM7Mc9k9/z9DBT6kapqhgXk3FBd8qmVWreNJ9hCIiDgONwc+Dr777m/vUdzgmpvx5DFpZlIcZIjYl4WYjrws7tOY4TzTludhNSm8YDb4q5tiYwDAeSgLETzY7MW+XHj8/8818+89OnzLrqyDaeVm7eHTm+vcfvJ8wEpXjWZskFhIB1sC4rHz4+8PnpjPUT0/4G54Pmrluh5qqfIwOHacTh9SC3lfmy8sd//iP/+I8/YwR+89sb3n7xltoK8zxTyBgnXW8EIfiXxsde43F7LHCrautMm67ohgBDCDjrdcxfitphr7kbVlkV0oN/Wi3MsbALA8ZCoWfBW4MEdRgYq8VhMlkFa50ZkHtaJc4gjpdI59ZUa2F8xmYdm5umKm7Xk+dqrQolc05P3GoQp4wOU7u9tn/PuWij1a5+dC84aRynwBQCo7HUGMEkZRsYo0I7YzU22LsXnZAYw/Ppwum8dfW9xhlffeziDFjh9PCZEArHYHl1mPjVNxPz88LOGfZuwFXBi2d0HjGRco6dDdM7VdQ5UKFnLjVIhdZWdQk5x+A83ivDo6RFV2ndep17wWpaBekJnqVRKeRcX/49oj54a9RZksrGtizEkhC7gtGdeixCwVIJlA41aX2dLaK8/WAatwfH6/s7xuDZ1gvGFIIRnLXErMUc6L0jTgjTpGu40zNu8GxbIucVsdrQTH6k5ESuibubO5Z1Zpx2LPPMP//pT/zqd7/m9f1rLnFjrYH7/WuG4xuaBMCypUyrUaduRh+V1i3p1yLzqrP5mxUA+gVt3/vXLlzpZUFTZWkt5fqLKS2Ta0ZMw3tl88/LjHVGE9DaxHnWUWypjbgljPVkoLWCGxzO6djaSf+TekScel0VRuOtwYn6pgUIPmCtjl3EWCTrh8/14Icc84tfXl8sTQNsYnQvXKqKRWrr4UFXwmDfYYnVlDOpbEmtg9lpUpz+mQZTEljRDsBoWta6bWy5vth6YkNtPmgFXpp2S7kfFktc+PRoCSHgg9dxobMvH/51TWzryuWyKKKzqYI6BA2waeWXhwFUT2CcU8AQDdtpibW/9u1q6xQh54yzRpnffaJjraXkRkyaN5BzRmoXNnXFsnMODVHStYA1MDjL5CyTE3yFyXju93sV9tTC3eHALijt0QqEYcK6Pq3po9yaE7msrOuJ54eP5LRyPB65ORwx4mhFscilFFIurOszOTZAixMnSn0cnOPN21fs9xNbWnHOcXfnlUg3DLRy1ETC4FhS5rxGPp1OXLaVu1dv+PrbL7i/u8cbw/n0zPnxQksGcqKlwPtPH/nnf/rP/PjDD9wcRpw46paoKZPWhBl1PLhczlwuJ5Y1UZtgXFXRW7m6Zuggqkpthd1x4M3Xb3n19hYxhUoihJEtz5z+8pEyn4jLTIkFqQ3b9HXfhZEqkadPn8kx6WgzF6wbEDMyTJ4qSi8vMvC0zvz0+cyPHzKPFx3VSoYisH97x3A78pBm7GY5xcJpTVzWwtW/VYoWiNJBTEPQcb9IoaamDpucGYYBEcPp6Zntknh+OvPDDz/y008Lzhl+/es3/OY3v2HbNp2A5Ihx0keeQqWSasZ5r5eV0XQqMSo6lQKDCdzcCnFrnP2F1oSSVVm+5cS0CzodEy0AjJjuo8/UXEgpsya9BK/kutTKS1hYxYDTyWdrmiFfRX3lptSu51NOSs5qK7au4Ir+mkYi8YvHX39Dv3ik54b0jZ8VFXa1WhUMVLShuhYmMlh2w5FghFc3N7QUyZeVJpVxcOxC0HyDXLCtsbVE6GmF027HME5dl/Gg9FRrdHKZtaMVa6lkvDTqOpOXM/d3N9z89lueP39mez7TUmFymkDoMJRk2VbhXJvKd0yhNE00vQqnG40takrmGDrRtepZdJwmhnGnpNSsHBjvVVullb5g+xkeo/IaehOvWRPrSqyVq1UQVOCoBUNlS1BNwwfLsiZsU3O46UAlDAQjHCbHd1+/YnCVbTnRyHhvsLa9iDkzKnBMuQvBjUKGtmTYHme2pAF2V27K4D27ccKMA7VkrGgTK/bA7dtX/M//6//G3Rdv+OHjA0s1vPvud7z9+re46RbCHkmaR9PQqZKC7PqP1jUAL9HAf6MCQMe/ST3xvfOvTV5QwCIQut96GAKrUVKgiHbRKTXituKaMEw79nYi1cS6JR19O6VmNREdJ5YG1qvSfMs0I79c3Ah4aGJU1doaJSkp0BlN7jNdRa+sAPOyG9f9v/qQU654r5e04Kg1k2rtooourMvlReUPmqltSkEQajVq62sayVuk2+qse+nuM5CaEIsh9bCQJvp9OhdIOZP6bjpmPWiuqYLGggs9IZDGNSq4ovGgtVZq6iIhpAOLAiEYBj+yritbjCrK6xV4KY0qrRc4mRgVRFR68eac67YgoYi+t9aobqASqbm8TAeulTm9+9EoU/eimDVGP5F6IXgOwXEYAjchANo5jU5FlEbrFMZx6gx2DVdK6xlaptaNWlf2PpCFPjWKDEFFfG1oxHXjdDpzPp9pxbDfHfsuN3E+PeFcZTsMeDRWtSGkkkjLivOeaRc43O4Zbw9cUuSPf/kJu5559+oLfvO7P/D111/hxJCWDamRmlbSWjk9fiZuM58+vefTz++RXLg/3nAII3G7ULdCiUrILC2xrispRZ06GccwGpKAM57dMLAfJpzzxJw5rTPHVzd8+c1r7t/cEg4DJqgOJ8VE3GZqjJQ1UmKibJE8ryxGmCuQIuuikKxaNSp7WTbVOKRKakJznrUUPp0in58z56iXvh1gzvDldyPf/v2vGF4f+Pn0nnguLGVjjoUsgRJhSyuXZcVap6sQAzHN+vms/Syg76+dp6bK88MTP//4gR9/eGZd4e3bwHfff8/h5oYta66ADUYLclELrvH6tXIqxKjFhB2u7h6hFohrZNsiFDRWfIjENVNF7WOawcEvh6agazsHplmMDeTaWOOGbeoBb6Zp89DkBYZlrT7vHceubAxnMd514p2On2s/Mxsq3NImpm9Jmyr7Q9BpyNZiv8z0rMg16RSh6UK/YDq8K6ty35huv9WzJ4qq45stuGB0sjYE9sEzGMt2vtDy2vVbCUMhODjsB+I2MS+LxqM7jzVF8eQlq07LQVkX4uWZcL/n9vUNBwefW2Q5zQxOcP3MnUbHFD3DJSpdFG1IOkNHX/M+wmnoayRNz+Rl3bDAEKxOj/xAaxXrA3GNxLhRaiWE0C3fnWjaXVmxNNZUIa00MTg30JrpqYoNWsFZsN4x7fZYSXjrWeaVGK8JsrAbLPfHieNosUo7w6I725gzqltQ8eH1fUy58fg0k1Nm2wopwbAzOt20uqKdzwvT7Q03xz0PHz7w1bsvugMm8O//w3/g3/z3/x52E29+5djMDnd8hR0PxGygCFVEtSSla/Bo/cIXXrCAf+sJwLUsatefXPdZ/Q1sIvhhYLfT8epqWsfqKjqxohdZa0pFgopIxVmVzXk/0fCkK3e7CDmqIMY5Ry5qGcz9Qg7O44cB4zzluitrOrKuaMqY7rmdVltG99feaoERYwRRsYt2wqrih9YfJH2YXNPuwBhPbeonJldVjlqHsR6c025YwA8D1qkOITXdgZfWaMaoLbBBptLEgNcDYosazpO7Y7LRqVRd66BCHdUjWHvl/esYkapjvWmY9DC0XSRTdFJSqu7+bY/aBd3FxRTJ3fcPUGt3L5RCsE7hPuhrY6+WyJS6eNK8PBLXHWejV9dVGdWuR9rqqN9yHAJv7w5Mg8U7tYBhLNZUDBnnLNaqhSvOkXVdlUuQIzXPWFMJXjvb7JzGI9cVK47iMg3DZV44n0+6FhpGjDTlUpSMqY31MnN6eKCkDRc81joenx95Os24wbG72/Pdb36NDYGHv/yF0jJff/c1v/rt7/jqq68ptXB+PLFcTpRtxdRMWgqff/6p2yY3bM4455ispSUV+i2XmcGNCJ5tiaxLUltP0Rz4ME589ebIzfGGqbMsLucLcc7cvzny5qu3HG93iFXRURgsa4zE9YJQCdaRamVbFpbTmcvDI+l0Jp3O2KoF+DxvpNJYY+W8JnI1YD3VB7IVTsvKjx/OfD6pPzuhVjIG+PrXX/PqmzdEX/l0OfH5/KyZ6cZQ0GdjS4nLGok5aafeEcZaXBcEqxGszbBdNi7nR/78pz9zft4YR8NXXx358t1XHG5viCmyLIse8DRUv1ppRnDOI+KIMbKc574qUgtWLY2cCusa+fzps660qrBsKyl1QaIRjGkUo4Cwq1aq2b96oBFscD0DRHXDzizzAAEAAElEQVQZci0cuouo5Uppmr0mVrDiqVZXgtfuvbTaM0r62dl0XVU6GlYBY32l4b0y7bOq9o1RQmBrlUqmiXb/NWe94AVll/RuPZGhPwOjCIfdwCSCS2rTDX7ibr8jOsGiwVSQqXmj5sAuOMphpJRIrTDtJgoa4pNy4TwvtK1iBmjbSlzO2JtBiZC7AHHF1gxiMKbppNdZFU/aopZtendetUO1fXpjrUa5O2O7BRlOl4V5aezGgd1uxFtNDLHuOr3s11C9FnMoPEkMBp1apoyyJba1OylUY2YQQtdsONsV+6XxbITnpwu56erjMFrubyaCqeynQFkr2/nMlqquRkRt60ZMd085TIElrixbJSW9F2M2sFaMaXgyoYfEWYSb4xGpjRwT1YrGtC8b4+EGu7slmCP4PblatqyXQq1QimqXjDRdebwUmTpl+FdiAP4bRIB9omD6Ky/SSXCi4TSt6ZjZeodxDuMtEgzNCy2DMwHjRHefRasnMaogBSGEkdoMREXWptLHzEY/KKUU9bkKmiV+VbIDVwJSE8hxU0Rv7RVhazin47PajFoOO1zHWtg6favU2kmA+qFqqMCmGb08vbVYLLSKsaoojXFjqxWbCqkqMhSrgI2YE+IDa8zMMZKKkLFdBFKpUlnKrCTC1Cl8tleTiNrKrO0UYK30TGdBg9IClS8iOKtvY86VVnRndj7P2kHnqgcWmsqn0wSNxqXlPnY03cKmQkiqQNEeRJztMZXalUyDxzmrE4PaaDWr5URUjSJGX1fTGlbgsBv48ubAV69vuduNtLZSa8Ta1gVZoKIk0e54Xvj8+YH1fMYbgxeQlgiDYQiOklZd3Xa0cSuZ0+mJnIVlmcklM40Tu3HHtmyscdXVkLNYAY9AzoofdoG8RuKyEpNhaYndq2eaEc7zwtsvv+TdN9/y+u0XOOd4fnxiW2YtKuKKlIRpQp5nUlahoTethyFV5tMz89OJVmCadrQE5+eF02nRrkUsYZy4e3PHF1+/4fbuFimV+TKT2goxc7y94+b+wLgfMK5RykbOQs2RtC2Y2pBsWOeV+bSQFuUrmJSIxhKM5XI68fh0Yk2wZuG8FowfmQ4jMTUetxMPz4n3nxbOF50WGQtZKq++mLh/94qH+YHLZWOuiVPc2LJQ6BZbdIwuYnF+wDoYhoAxmpRZYu6fU0OMK+enM8+PJ1qCN69ueXV/z7jfgbH6HraiHu6StOC2gjcKWSk9hVNjtI2y/ZtQk0YM147W3dbI5byQkhbPQ5iwV2JmcIgziDM9MKopGEdq1wNVnLe45mhSe+ZHfclBqb2wzrUizuHGgPeOIlrcl6bgrhc/Gdf/VTCOQV0GGviSlKfGNVulvXS2V1vvS8CrUaiWiK4txcgvDYN+Bbwxfe1qmZyHVijzQtks9jBwcxgh77hwURiTFGwr3ByOHHYj0rQD3+2Cvh+b7suDq2Ai486qjfV0It9PHdCl4mFD6/Y0q2dAnwJaIyri7he3Mb0RryhuXdBG0WqKKYCUChlKUyvgNHpqLXgXuLm7h9ZY11nvCLHE2JkKopPp2uPJU0a1EwbE69QyhI5bt4ZG6gFmDnaGEqFEnb7uQmM/GabQ2AVhSxpRrbAqtSe31s/i3nW3JmCGvl7KVLEsKTOvEW/hOLa+8o6cT5Wbw4Hz8zPN6ufpn/7pn9i/ecVvjSW8OZA8YPUusEFFgNX074lrzdrvSK5CeX0+/qYFwP//f/Tq7WQtdLSjM2uL9R4/DrRxoA0N2yyWQC1qdzNGx80e3S3npA9sqRbfGgGDSR3bKI1t1fAGZywueHwY2HJi3VbEOkxnvtOgJIXpiBFq07F7bvqii7mytTXnW0dSOtqv10+oMSA6xi70UCMUTmGMwWA1x30YVZIgjdpzBwq8dMFrTLTUmNeFGLNu2MXor+0K22VeVRTYVPktTg+oUlHFp+3BRSVRq3nxHJeSeo63BgaVXEjrSikzzuhaZNuicoaabvdza5hSEaM+f++CHphNP5T2Sp0zqrAV0ULI9T1bbgVrAy547Upq0WCnkrXuNA1n7S8dX9boy9d3R75++5q3xx2uJS6XjVo3/BAYuro/56Qpjlk4p8LTwxPL6ZkpBA6DcrZtE13tiKq1FZlcSFG54rmq3WrvJpw4rNO1Q6u60y0lMYaRYQg0Kutlxlr1OQfnyVZYU+Wf/vhnpsOeL776iq+++Yb98YbaGss8s84zedugKPDG1MrgPIO3DGEkpVW1Bt4TXNUgo5zYhYnd7si2FmKEVi273S27/Z67+zvuvrjj5pXu5KU0bu737A4D4/uBYbdn2DmmfcBPI7FbINO1EyyV5bJwebqwnBdMFXbjnikE9rs93qq/eV6NJr9RqbKRkiWeM+ec+TwvPDwnnk+VUhzjMFG80IbI199+jZsCP356zyaZ5h3iRkrKbLkwjnvm+UKlEEblbjSUXqeK/NovB5DmSJeN7bwhRfj1999xc3ODcyrIjKVgvcPZQKqZUipS1H7pnKGWQoqbrk7E4rvKPq6rdssVpNtdacK6Zpa1MozCPjh1oViLH1Q85b3FelFnQqv9INcfxhjGYaBIYS0ruWadQijzrE8LYRxHdjcHjHNsJVPTRq5Xd4GeKdeVmVqS9TMVghYAVxhQrY0YMylnvO3RvD3utXX6nU4AHY2r5qHfpk3/PG97wZyvAsFMF9mrSDluuHFk9JbsrULKBIJp3OxGnB9I68IjlcHpqrEa1VqJt1RjdQqxRbZ1oZXC7njg5vbAejlTFm3qrDfYYjG2YK3RYqoIrhSae+Gf6TqyaPMlfWXbWiI4ixOLtKKEvrISkzrCjgdPGHcIsG0btWrsurUaeIaoOM95g3OFbSvqCDIQnGHaDVgLrsPcaoMUZ4wJjEG43TuS1yZqF4RAxCG0VDCtMo2DirXpeg2jmoLWNH46VY03zrmxpUaqCbGazRA8GFPYYuRyFiQ7jrsd4zj2aVHh08eP/H/+9/+dh3nlH/6vBw5fvyY3bUZBJ2tGFAduWkVa00bcCDRHEaP38r9OAvDfoAF42embl70NouQhmsbmtmtSnndI8OQO0HFDIG/XRDz/Mq4brV6kl0vs6wHpKXlAyvpGOUuKUV/o1vMGcqSVyhg8GKsdfwN6t++8pbSm+3x90hDkZdTUiq4mctauwXqPNxofrOQuLQqEqoz/3pXnUrHGUo0wx6hj+u6AaNaRSmZdVoX6lEwTQ2qVXLUA0XrJKSo1V8K4IxUVnYhziFWEra1Q0ChhMYaahJqTetwFtkvC2Y7NLJV1jdSko8pcKzEu1NZ/73W6URqumR5socFHihzOXV0sOKcPjvREwuC9WrCoVHgpglrLDMPEqZ20MGkq3NztJmiZuGWGYHh7v+fLV7fcHXd4U0nrjCETRq8Ct7qBhSKZ4D0+GObnlVozAClGllpwEqhZMZ/jYLBBxX25qpp72g8grqdgQXBK5ktUXBawGgC1GwPrOiPOMo4TMWWWddOEN2P1QnMD7775Fb/6zW+0sC0qsnn+9MD7n35iu1zwQEuZw27iZrdHaOQy6+sfNdOAdtSVxrVbq475PDOfEzlZ9scD9/dvGHcD83Lm8vNHpp3nuD+wmw6EyXH35hY/ThzvbsAr195a7XbSspCXle2ysT1tPH56Ypsv3O53fPHlN9wdjnino/LCSpiEtaneIZbCmoTz84XTtjLnxryiE5x+B5Ycefv1a377+98SzYXcCjjDlgoxF2LPUd9iJhVwnbKpdlcdbZdUMRiseExzbGvm8cMzy2Xj7du3TGFHK1WdENDBJv1z55S4mYullKSgnNq9/lnPEhFL3iKXdQUMIYw441VdL2qRshamcehC3oz3Qa2dVLBe/3lJuG5nhh5djeY6EPTiXq1lWyMpJkpT8e+4m3j19hXj/sCaEmlrkPvqo39uSu96neuqe9X6UXMhlo11WXl+fOZyWVThLgZhwwenSv0OGaN3fLT6Qg8c3KCAtHKlrkKJkcEaJDe2dWashb31OCDOM3tv+xrNkmqjNi1abCs4KpO35DGAaCZBcArPuqyJmPNLrspuGFguFy7OstvtORxveVgflI1SC00cxlnN8siQpbETXfHGUoipvTD/NTbt2tw01pI7jEgp7lrlqaZh2TYeHp8IPpCbEiZtnwxdxYXWqL05hIbIyjqrtW83Ol7fH1nWE9Zrw2K8gwrbGvHjwGE0nE9PhOA4HidaXoi1UhFK0ov9Gt08Bo93onC7ei1sLDEmliWRMR3V3nVa1iLSBfNNra9x3djtRjLqEDunjeVy4eP7n0lx68FVhSvTRahQ9DOqbgWduLSqzWnFYozrv/5vWABcRWLX3Yvur3T/ImKwLpDXypKSJj1lBV3IIBhRT2quiS1qTrVGxTpqqTgXQFxX6arf3HurUbk1E4KjrhlrhCEEalMYkHWakia5aHpV01EYfbfkRFW8ctUOWKM8eW+p0ihVKU89B68fAH8FPBb9votRxal00Y1G60a1EfYCoPTAn1JbT38qJFLfS/V86T7RMNYzOI2LNU0Ro7VLgHWbIV20px2O77Ygax1QCX54edhr++tST3+/YiJ1z/TLzu0aX1xIRf+eV62IEfXaGiPQJwQGodSqgFInmqxmQFGlgjeWYXC6g6sNKkyDw4ohEhkN7AfL4EHYSClS8sJuF6iSSTVhBocfPB7Pfr/DSuDp8UyTigsOh8J1ni+JYbjl7njDbnLkFmlVGKwwHA6M+4MmOIoWDdsS2dZIcxU3OigKi8kUjNOddayV2Bo2TFTbiAh3b77k13/3e169ukfEY2jMpxOf3r/n5x9/4HJ6hpSQktkPgbvXdxx3e3LeeHp6wtpCCIaYNrb1zDjsCMFTs2NdN56eLjw9X5i3xGn+xA8/f6ZRcLvC229Gvv7mLYfjjlwjqWVssAzTwDAFqlhi1fjU9Xzh/HxmvVxYzxtP708spwVnHdaONAZyC9QsLJvhw9PGaYHzZnha4OE5McfCmhuXCKmLSAc/YETY0oqdDN98/QWvX9+zuYHHKJzypvbLna6mYso9njjgvRaGtWqUcslFi9ww6tQNx/OnR97/5RFnLGmfsUdDjnqxuMEzTBPVCLmmzvKoPQimY7NLIqfUOSMCUrgsJ9Z11S5oaoy3QW3HMWFpGK+WvdpT/8QpU2QYLI1O3qPqBe2Unimt/VUX2hkD5sqpV0FecI7DzY5hN+izKmBLxg8DcVm0Y+ysEG3U1YY7BN2R55RJeWOZFyWdGocRKLmTA3OmDeGXohy6sLno69sgrhuh6hTCtEbZNiQV4ryyGb3oTYOSVmhBBZHoVNC0pm4gI7SceH74zM3NLXeHicEZLpcLqSbGEMB5pHmiA3FCbhumNmoqGAz76UC+y7z/8RN53bDo62WtUaaLrQS5dqkazNSM3j61NxyltH6m6eFbe0EgFbLR8ywmfQ9zrRwmPb9cL5Ja65OSfm6VtGGcZgTIoMTAw85T08Iffvs933z/FX/5yw88PDzQmjC6ASOO5MDUob/eek/lGBXWllR8Ld2qXRqQi7oUqhZM1ilpsVZdyYZR78dWKnHNOiQfTI/rFbYY8d5Ch/1M1jN6i5VC3M7UtOFGBUlpcfzLOkl9sH+1EsK+OEZELP+a//zr0wCrKvobtQsMDfSu/2qjK01LNvEefMCOExI3aAaHJRDY1kjOqgCNWRGzoPuYlDKpVHzQ7GRfFVfrnGUcfRcAqrzBGBCdO+CdUS44pgtzdGdivMMW9ZsuWVnZWGHwBoxT4UkYNSSn0/1U7a56BrHyMiK/FjqVK+VMq/DWGrlmYtbDr3Z9ZO6e3tpFPg0VCPmgXs5KQ5ru76/dSmlXL2tTa2XLWu0JUHUnKKLVp1inoqK+PzTdvHpV2qqAqOmYrV1tIUpny73yvvpdXyT4Vd9nFUTq5tFaQxD1016BRtao5GQIToWNRZ+NYIXDbiQcPZI2bNu4PH8k5JF9MHhXqRLJLTMdR7779bfcv3mND9qJPXx85NPHB7CVItrhNWcVDz0MuP0eMxrISpx0o2fa7zje3XVBqCGlyPPTmeW8kjfNQo/rRk4ZNwSF3zQoxpCbaN74MHJ7OPLt3/2B737/O92Dns8s85kf/uUv/PjnfyGvC6Pr2QA5Kwzl9kCrlcvlQikRhI551ejklFK3/0ysc+ZyWbmsSivbtsSWYXcIfHlzy/e/ecu0D6oNSUoia8aSSmZeF5q4fggV8hopSyTPke28cnk8k2Khec/5kqj1zGnO1ArLHHl4mnmeV05L5LwkzrGxbo3LVpg3HSUfDiOHww2lNC5x4e7dHf/wD7/n5v7IBWG+RNo5k2pEw21UvGusjqGb6KVWi9pvaXrRegJky/l55vNPT0iCN29fcxxveH545nl+otC4fXXPwQeyNJZt1q7X9D14Ugy0qYVW+tiz65BMqwzGkWLm8vRMTdpd5U3BMjYExmHQ3IxuYZYuGHNWA3mqqPZFQWCqFTE93dIYhV1pToMWJI1CCJ4wDuRaVI/R0d/WqtK/FD0PvNf4bZoWRsMQKGkjpcS6bMR1o3XuiVz/Ln1dqcDVa6FuVO/jdPxf+1SvpUQsFY/BtUbA0XLEiIp5PYLkitiKrbCcZ7Usb5s2Fz5Ag+1yYjXCfn9g9IbsBZtBUIHtYRyoOJqFmFGSYNGVaysKKxqHkdQqUjpDpKau91HQl2asKPdgDMJWKluqpNJe0mtbP5PE9N22Eaqosv/F2ixJ1yhG+qRFJ5amN0Xbpq+vqXp+He4CrarbYb8f+MPvfs3tqwOf3v/IbvSUoqq/WkVx5DKxxUiKG1I0SpoKOev94J3tjbBOlTXLRgm21jtqaZyMNkZKo726SArZQws6tV5jYvCTFiw1ayNoBcpG3mbOjx+5n5/ZjTsUKtFb0y4ivDon1InFy0Te9Ebwb1oAvHxF+avhggitaXWdC2A90/GG/d09+dMHZCtUk4lNgzjEGl0JdLFZq6raFbF4F2jNkrZNkZi2ghRy3diSxTqtxlstOOcJ+516fo1Vm42xNGM6UjfrJW6g5QK1UIty26U5rPOEHpVpbefYt4LpVaqlJ3R5S2mG0hXyrUf6lqrrAu89gqhaoNaeVijXu1TdCeg+0niDDwPBBy0gsmJCjTi1z5mmymnoF61e3qpulZcoSKRRcu47M2Xe51w7i156gIiqpk2nfdE0ibFJ67vFXhRchZ0vcZeGWhvzvPR1j45Da9WgJy0+1NRU86ZaipKxIoTBc7OfePvqwN3OIWllfnpAoo5nnR9w3lBI3Nwd+dVvf8W3v/8Nu2nsosnMsq240UDQuGjrA+Nxx2GacPuJtR/6dXDsDoEwOdzosZNghoYdDEZGDqNhvN3RIqQ1cT6duZwuqsjdCqkamjGkZqne8ert13zx/fd89avvGY57tvOFuEU+v//Ehx9/Il5mRmuQHGklQY5oyGJmXs6s20xpFYtl2u0Zx4ABnp/O5FzxXjhfZp7OF55PC6U1xsny5nbHt796y1e/esPhladJUe94UXW5Favo3P5eg1X1eSzkJbGdFubHMzkVtjVxOW88Ps0aHDQMiHiWmNliZUmVeStc1sK6NZYrBc0IfrAcDkfevnlFzJEjA9/9/ltevdqzpJWlbGyxEHMjpsqaEjlrwSoW7dBpL8EpiGGwAesc3gTSlvj88xOXx5Vp3OPF8/z5ifcPn9jqzP52p9a/uHHZVpa4qO3XKjehZk3alFIVMtVQLO8Q8M5wns+UbSOnyjZvPUhLw2EQXZ+Jd1hv8N7iR0/w3XonQs2o4NSpzsSJoeaC7Z9lI9KFX5ZxUjiQ9RasqA4pF+r10m/a7euR2V66d1GknirfndNC2uYuptYGQBsaQ/Cht8CgiW/qXrCiP2qrmHZ1BVSdhhpdc7kGpjmG1rC54QAvDi+265P086sjdmFwenmppmdm8HrWTs6SjVBKprTKbhyJpQuPMTSLBgzVRo6ROG/K2+ijiloL1A1q1CmirVgMXoyeqQi2GIypuNqIRcfrpTc83smLdbvR18e2h5WJ6BS26jlpRV875yzBO7yBzfRZbmuUtOGdJVjBtMzPP/yJH35ItFL48s09p9NM6p8hYwQZBloprHOmpabmKdHpsvTOX11mhmF0jGFEmurOGp5cGkPQgiFnzWG5OreuzdmWFKF/3I1gBGes3i1Gz9b5+YGPP/2FN78+sb97g76T3YXXMwAa0kX5Pd7Z9P0dBf6VPoB/vQbguoW47rwx6BzHqK+divGBcX9gd3PLeZxY2zOlNSzactaaSbn0XX3AeYv3MF82RPTDOdCwXglYtTmwg178rXVvvHZhrYNvvA8Y56iiBUDMhbJpnG6rUHNSoYv3iCmIc1jnyFQVVKUVWsZbuoCtY4mbhkRfkZm2C/Ku3XEpOj68OgboxYN23frAbhncYJVs5TTxMOWiCM+rjx/Nt04588JXKLWP1vulzhVX3MNHaiWVHplZioolG/0Q5uVyV7W0oxVNM5Te0UhTGtq1ApB+wGnUpqaPiaABHrnqXi92X7+oyaTETQ9MaYzTyO1hx+tXt3z31Wve3gQClYf3A+enz0xOsK6RakSC8Prda777/fcc3t4R51mV3V4Iu4HhZmBYR2Kt+hgHC9NI8o5YEjEJfkKVvEFopjC3lSAVZxTDzCS4EDDV4tOImTx2PzIvCzs5kKth2Qq+WA53b/n+V7/n9bff4YIjxci6bTw8PPDh559Ji7IHDqOnpRUsDMeR+9s9tUYuyxNb2qhVCMOB42GPmMK6rhjrcMGQcmNLmWXbWNfGsBO++PKOr7/9gq++ecX+1UhxEec8Y5hIMWvxUIqunDo8hlZJSyKvCVLFVoNtFsGwrJHLnMh9KmRCQGzQ5LWq66Y1wpaErQirRptrN2OcJrMFQ5g8u5sjv/r1VzQiHz995HO68JAWLiWzpMLSQ2KMtdSmo2xvLUMY1BbVDNYEHI6WDPPTxvOnmbJWSku8nz+yxZVzKkx3hsPuwDiM3Tu9EUvq0CtNxDOidMlWGi3pc9u842a3582bN/z848/8+ONPlG3T1U8DGxw2OKqIqsfFKS7bKpUwBN938WqFHQeNnG4pUnPGW9PPrEKKmbhp0qZzFmR4CQ8qtelUsmdj5Fx6IFftuhrDGDQmWy/vDsnqXHvvMzV1+3K/9FvRk8Aai2k92qwb6BVTpm9ySRXbFPjkKtR5ZVszo2hhl1OhOkMYHEE8lKb6GxqtC928dVRRAbNUFUOOfoCSqUUvxME6vZBFXQdGzAvzwGNouVKT7u0VSGYIwWBvJoTC6RxJCaoRqrc0nO7vk+pFbAMpKgDMpb1oNxrScdVFxazOYlSaqDkLrak1tDvRnHjc4AnTSHCWWjK1O0JG7zGtsi0z//LH/4r1wu//8HeMw4i3A89PJ9Kqlm1BGyK112Zqbi+r79qE1GmEzuidMY0BZ/ScTAUGLzrh2FoHTeqqxfQCIJVCSqLiQhFtDANqA7UV66DWjfn5kbgsPfK8J+L231ON9Im03vlVGsbW3vBdF9l/wwJAL8D28gfodaP7EFWB94PED0yHI8Nuz5lfoAWUQmmlZwpoFWRQAYNz6uXVfAi1ICFNPc9YWkFV7bUQOm9b1wGq5BWrgpZSi0Jk2vUFs4ru9YFhHFhT1LGJtVgqkgq1ZqwNiOgkgdq6aE9H4b1876M90VyBXtGt29b3Pk7XMU2ti4ravT7IA2EYAMUJlxjVSwy6NhD956mU7lBQxGWtKvAw1r6M5UV+6S5eCjMxYH8Zj2mxoopa00mEqhS9jhEVuiNGx5KCWmR0F6odgpLo6MaKpkyAqg+LmM7mrmqZ9M6y2w0c9hO7wXOcRl7f7LA1EU+evFiMFBVOmcqbN6958+VrxBvO5yfWZX6xdcWyYUeHGQxt6FAXAwtN6WQVPj195oaBtoP9oCNOVcg2cDpJUXgJeBPwU2AMR+xhx5gyw7QjV8vD80pj4PUX3/D63bfYcc+6nFnnhaeHR3766SceHx6wpTIGw2QNtQrDbuTLr96wv9lznp9JdaNIwroD0+6WabfjfH7kMq9YNBFxvmQu88IaIy7A2y9u+P7X3/Lum1fsjxY7AmHsnvFGyplcMmKCfsjLddqjh1mcdb3RUqPlXvR1cpQzji1XzkvW4KoiFFFb7bxWTO+cTRDaFmnGYgel4m1p4W4/8er1gf3R87A8My9nznHhtC3MtZCQnh0vNCmUml4cIMF5tazFSoyRLSXyUvjw0ycuzyslwZo3RcNa9WLf3uy4ubl5Gd3WWrvQtBM/jcEbh2RND81Vk/iGKfDr777j9vaW5XTmgxiCtdjRdteK/p1s8Ers209IsDqyL5reUwrUFDV/weg5ldaiHbUPxC2ybYl13RQk1JSpgBE9a0QQo0mUrVy7O/36rVX97AkvnanmlRRSTtSmiY9GTBcW0+Fc9CmKWoGpqjloNHCCCRAGB8YR84YTy2EYkS1zmk/kkwbKVAfFQBss4tRd0qRgCC+TGmOkCwu7jgv6RSo4FSSon99bFfl6i/OWUBUUlQ3qiImQt0hNGakVK5XBCuPeIaLC4MulULM6ocRYUveqp6IYbW8c2Vli0tVVKo1G7lMUtSiXruVQj19HCVtwUjDSyNIoQ8B1UTfGgVOtg3f6e/fTSKkKhprPZy0eaiNtiZIUW6yuDBjCiLASa+o6ru6zb6IT41xY1sbOV9xgoGYMlml0HCbPMm99IKaCUmOsNsGpEU1W66F03YDVia8VDQez04A314KKF+5Drr0IsDrFrLV19HoFUxCjU5H6ty4AdO+vB9QviFntSkRUuFbFIC4wHG7Z3dzxOASMd5RlpaQNoRIGj8FDqaSuxvdhQG2iRXfVRhCjsAwnlkIjDL7/RZpODrp476riXbdEqk1tf7VgeqytSMMYr1VXyeSY+6Vn8Eaw06T79A7kyU13NsVowlQVrbxL3/mnlCi1Iyn1jnwB6KSUSbl2yx8KsAgqrLoWFLlkSlVARe5Wntr0IHDWIcao4rlcRYu69qDpjkk9+Oq2uI4opbXuPe5dfrclqq1GLUamrxJEruNkdUzoKqa8AEk0L+Aq9tQCyHReg7fSPbwFa2DaDyqGuz2ynwaombjNLHOFtLAsJ1qnZTkf2B1G3n31jv1hz+npmafzEzEnxmlkv9tjrHBzf2TeNsQHnNtRq2VeIg8PDyzxwprOvPW3tKNHGNgH9eN6KwxjoFlDLJm4JooIJmgBJqPgm8H6EdMMt9MNbjhwPL6hGMN6PpHXmfn5iU8//8jjx/eQV7yFYbAcjiPLOTKOjuPNHgwqPpNG8ANjOBLCDmMGaI6cIFVd1aRYKSUzBsf4ZuLbb7/i3bs3HA6eMDZMsGTRi+e0nnl6fGZbM4eD7/kMIJg+3auUVIhbZJkXLucL26rv9TSODPsbzmvi9OmZpzmyRChSyA2WTd/zSfpUoTSMq/o5MbDGmXF/y839ARd0d7w7Thw3y7lWTvMZOmSJ1lij5rO7TqKrVVc3NTW208Z2jqznyMP7J0rs6wEjeOd0rLz3HI83WBdYlsi8LUhQvGrMiZQSwWl0tXbPRh/JpiCeTz9/4PnzA88Pj1gRZXh03YszwugdNniK6MrAWNuz5nVcr2JajeduOZObdnGmoSFS88p8mTvLvXEVA1mvorOa9IIsWX0yxlqFlnX8eC1VXUXOaQcqRiFnta/krqs7Na+rbbT0w6N12l+fJnhn8cbTYgYjDC7gQ6DFSllWbCqMRkmAriopU02H3YqZSldtqVOoXUV3tVGzTv6sU1dFDpHBO0rQqRstqXi5wmB1nZel66qyajTSshDnrTsXegQ5hd3okLsDo6/M58q8FrZtJVZR4FFreCPkVnHS8Aa93Et/TTtLoKaiyYNy1QbYvpLMlKoJnKVU8qZ8Dp0yW03TGzWqN6ZMMJ5mhC1Ffvrzj+S3mWWOfP78rC40O/RsFT0LG0ZXl7U3WdcJeFVR9TxnRqvrP2kFF0aO40SKicslMl8aIq0Hr12JuJktNrzNXJaFmzhqtkRJGKO/XvUpfQpkdMou1kHTO6+ZX+i0jfIiD6Cp1qXUv/UKwJRfxgqd434dO9PQUZ0LVD9h9jcMN3f4cSTZR5BEZXsRTngXqLkxbxvWOootFNkwXvcgYnQd0Joht4YdbBeHqAALaVinkJFlW9Wi0ZQ22LqwzlqN4q1dN1BKRkrVvZXY7ilOuBCoueev9xs9504wFN1zllIpPTgo9dG/Eq9MT9rrxcCV1y0QhoBzAWmKEC1duSwYalG/r3FOk7FE9++tv4HGOKzvotmmufLjoBbAVjPD4IkxqZ0EfQ9M9xxLFzN5cUr365U+6NdqqAbgukuT68+v/7+vO0rOtCbYINiOX72CkkqGw35kv5s4jIHgDTld2NrC+VT4EIW8zRiB6TAxBMthP3E4TAzGc/74xPPpmc9Pnyitcry9pby6x/b0vO9+8x3n54XHp5VlbczzyofLxjlVNjzbbImzx7660cCZwTAcAnYXKC0phyMZDB7rB4wbaVU4XzZVIdvAdHvDONxQWiGtz6TzQn165sO//JHnT+/ZS4Kh4W1jf+txe4MzHrcbWWpmPS88Pl7IUVMuLZ64Jj38qsVU2+1ZQC54I7y+O2L9wDh43W0Xj7SAbZpRUdbM+UEhOdYGmAw1q/I/J6XalVTZYuJ8mdniRhWdjo3DSNgdaXagbRorHTMsCWJVNXwTYcuVPG+9eG34WnCmkdPK0gp+Gjjc3YK1hN3InQw8fvgZqQnbtTBeDKlWciyEYWDwgZYatQi2OObHMx9/emA7beStktaiB6RRJXMrCtWZ3IjzE9taWJNO4mptlKQCMyMaMV22ju9OtWtmhLxl/vzPfyI4TRttW0ayCuhqbYwhYGpFqsbMrvOZIAO7w57cfVTBC6YJNRUVe+WKL4ZgPcs805ZMmTNpjcTccMFhbe3R441SM1SrzhIRarcVD35AmtIs8zZjK0xuwA/6GXfNkQvUmNnmSN6K+uFzoZSqxVTOL5ezlEYIgndXIf0KvnAYRkzwpHlDSmYcHVtMGO0XaPaX4l2c0TUE3UHVKi1DapHS6Z0YIW0bixX2+4ExGEwRYKNltdy2JC92Nt90/55KITiDMw3XIUTeO6gKjvf7Pfth4MkV0qdnLsuJnMHZoHowC7FkjFFG/2Tg1ZuAtcJy2VhWrYkcOiEx1hHCTlcvdUVMI9cEtbGuG3inhWPVrJPghVYro/XYjsO2zVDWzIcf31NKIy5Rw9asnnOIIaO7iHEIrFvE9uluyZtOvb3aVtdYCF6YguGwDxwOnmkIDHbgv/5xZd5UA2INLFlP7BAspRa2uBDTpEJBUTEoTUgx44qKQUEnr1eHHKKrKZ3eqLibqlqJ1ozeTX9rFwBSe7+t42QAQ0G6GrFhaNZS3IiEHXZ3JEwTzRlksNSs0az6IVHIhQ2CCxaxjZQ3PaDqxlg9wYy6+2uNvqHCOIsz1wut0aQLa4zFW0UCKxda7X8pZ7aYoY/pFKOpF7c03WnVpCIXHWqIxtqmpAVHZ9RfO23EdsyvjsVrE935Va3FrNFwIuscwzDSevKexmBeg5L6uK3nODdQ32Yfe2qynWCd6X5qJQBqQdTIJeGM1cjIK4UNzVE3TcFMVtSyp5MCxYb2G5/2V+IQcxV0dqGS6YIng9DMNVtAx5gFnchYbxmCIwwD1hn2+4kvXh9xJrPOJ56fP7C2TEkb96/u2N/ec3Nz4O54QGpmfjqzLTOn0zPnRTvKFpWV7ybPq2/ecrM7UErj/acHUrU0a4nGcC7C5yXzKZ95rII73vPqqyOvb464USgmgXGMh4AzEZsM3u+wZiCnypJXpmlinHYM0x5pEJcVUiVfnnn/j/8np4/vsS1zmLw6PSRjQqX5ynCnsJSH04nzw4m0VXwbqYuh2chaBK/jMJx4XWHExPl0oqSIs06T/LaN8+nSE9lU8BWXzHJZef50ZlsSt7dHnASk6SVYc6akQorKwF+7Y6b1mOVhusGEifNaSFXAjohTrUZuhpZ4wdLWqh2G95ZxtFijVrvpsOdweyDsR5Kozfby/JnHT+85PT7TrGV3UHRpXDYMAdM8ZEveMq5Z6iY8fzzz8NOJGqvusJt06lrrLoyMHXQ9UothPi3EEhkPO3TAqTnx1hosjZZ14lG3jGlNRXoNXQeIrktq1B20NRZne2aI0ec7xsiyLogU7EG7QXGCNeC01sAWCJ0INxgNFCsktmI4L4UYG1QhONRyVvqKsCQkWLA6ValFWSfU3rWmTJJEHhJiB21+WgYMvhVs0c+9TvGMZpXUjJNO+lNcHsRCk40h6Mja5ITBvQRdWWlM3mNHA6kiV/fQiwpRX4scIy1lfQ2rOphq1YA08a43LCvR6SohuB6GVjNONGGwGj2Lx8HTrMFK4e440XImptzPrKvDQBDxlDJSSmOLjXVN1KITYdt3Hq40DhPcjHB/f+Db794iwKcPn/nwYeb956RK+r7tq72xEXEUskrkDCjVUbkJOekuVapSUIN32KZnpa0oK2RLL6LD2PHiYvqap1sSrpA4EWhXzZUAztNQ2NwWC9MYOB5H3r4+UJLhdueZl0d++Hll23KfvFZub0de3U9ITfigiGBNkXU471XguCV8qepK0x2fRrUbwUpX5F2JSq12vUy/n43929sAaWr10SFA7aNn9ZBdRYFqB3dYM+DCDj/uiS4g3UPrgqXZhq3Sx47a4RunL3ZumVI3Yk64rLn3FahV1f7WdRxvbV1ooyl/6rXvR0cfs1vrVD3bleOtCbVUYtJOxhgVTxlRwE/ORXf/RacBrXtRgnO6n2t60WK0ANhipF75yE33USKWMGiMsb4m/aGRRm1dNGjUsuecwopM/6Abq+LD1iN5bRcUStNR1NV5YcyV4KVkwCr6Z5Qqf2UJ1O/LWd15lqL+d+d1KpCyoll/ifxVsYwR00FMFWsNxgnWi+4rW78wphHblE5o7cBXX3/Bf/f3v+Fm7/n88Ud++vMf+fjDD6xx49ZUDnd7pv1ErpmybSznM/O5e7exiHXEXJB5ZXA6oqQVat7IeaNWB1LZ4szD84k5Z+JF+QC3x4Hv3t3zzRf3hCGAt1TJVCn4MSBOoLqXQJZhnDgebnAhAEJLGZMT22Xl8f17Pr//mVEag1fF8OgHxA8c9ztuX90yTiPrsvLj45l12dj5iclOLOeVLW2IW2gpMY4BbwNZKjGurJumgQkNSmVZVvKn8nIxDaNnW1een5759OlZD4L7ASsequBERas5F0rSfbNOk5TCaZxF3ECulktMrAmwgWYzqWZy1RCrjrGnNgjesN8NHHaWUiNC5s3be+7ubmg1E/NCJPH54weW04mybgw3t7w63vF4mZkfT+wOR+IctYgvwnJZOX868+GnzyznShC6SE47t0oj5c7ZsIUcM09PJ07zM1wPwKDKcFDxsFpgK5ISLWphblzA9x25tIarBmlWv8facMHgxWGsJZbMdl4pKWN2FZObOopENNMDo3a2GMENDCFgq2GQwIB2jESoK0qgdBl61ofu/guUjWqNrihAV3hbxiTVztQtM58u+KahMNuyarEfC6aAKX0Mnwo1Kko7jAE67CwEgykFmwvW6H7eNCXy5aoOsKGvGdSeogFCUiBvhY0VKVV5Hi1rwdC989dwNOcsOVsgk1Klto0xOPxoCN5jO8BNxZCNKewI3lFM5yR4h4hhWSIp9dji6wRSwNuJu+PU7Y6NDx8+6UQuVw57+M1vv+bufkcY4PXrO969+4IG/PzjT/zn//xn0v/xnsum90+VREwz3jmsUY2E1aNPJ7itkuOmkcBisa0yOIMYdZZ5Z2ip6WeWrqMStbKvuSBVI7NpRhNtrYKE1ClVX5rC1nTalHJlkwZtwPvAGAaabSCBL79ozGvm/cdMkcLdXeDVqyP73YgQkboholNv5wyIBtBFdN+hZ3RPp5WrOEyFlrW7xUwTXrryLgC/3hd/wwLAofNq/al0S4JgubaYtQLiwAbEj0gYSahv2zQh+IBxul+z1jKIpaaVUhLiYXKBQiSuC/OmIx3nAqa5F1U70Bn3qX+jQu5UvtJ0NFhqQ7yKotT2Unsino63lcoVwFrWqMK8NaYu8lGLUG2NYg0yBJrAlhIxqXWkNlXz51y0Ouxxoppfr2SuGCPVWN3jW4PHKWFQdI4iXUiYS1W16lVg0oV+IsrfNx1fXHr+txgtcqzVr23pE4Wquz3B6IN6DUsvXezjnDoR6IffXxcAoq2QFd13tZpxDnxQiFEqyizwXjuOeT4zDpZ3777g7//tH/j9b79hPxnevBk57gRnIpfLmbdfv+b123taKZweH8nrRsmRmBT04kMAMcRUcGNjHCYFWeSEkco0eL0YUsaahBN1dEjVkfXHn3/kv/xny6uD4/Db79hNI1tb1ZJndeca59zjjq2mA4aBnAopRdpa2C4z54cnPr//mcE7bgZPoyAUduPIsAtM08B+GDHGcV4iZUt4LLYaas7kNRG3jVQLcV4Yp0BDOF3OPD4983xe8W5AjHYKtVWaNJ6enjg+7RmniVbhdHrm8enCzc0tpgW94Eu/sWsf6zb1+EpnfleEOWaWGtla4nlOzElYi7AVw1YaMWvB7qyq6WkweMPNfuSwV1jM7d0tv//999y/OirAShSmQy7swsAwHphu77HDxNPjhbIkitWsCWNG4hz5+JcPPL5/Zj3nHgTFC4aV1l34PT5dCjw/n2iXM5c1s79x1JRfHEW1JWxQOI6kjKtVLXpGGIzB9eKC0rRoRJHY0HAWXIWWmyKy58xh5zmGERtrF5UZWsoUHPGyEE8zddhhJy0i0prYLgsSK74ZXC20rZLM9hLL3QTEdYZ/QqdrBloxSKpqfRaPKUI8LTwuiSX4vqbTRsYWLeQ0R8RivIp3bf/73+x23O4m0ryQ5gVy6jwAh5SGw+CtYXAKIwqiE9VWs9pJk2pAmtHJoj5DrUOWktr1oMOOOsu+64paLUgR/GCwztOKwtIMvDQ5VvplSOOwm5iGiVq0m17nTRP2suAsGFMJVvjy1YEgiZ8/fkIEfvd33/Ef/5f/nsNxoOaFYbTsDxMiwqv9Rk1PfPz4yJ9+iMQI3jedzIlVq3dVtomtmuLXuure9QnbNDr2u8BwXYMYw3zRQB2608CK4I1QrkPVolqykhN+DN37r+Jzmr4O2onrfCCEgXHc491Aymrh3e0nXr8SLmthSx8pFY7HkeCFlBacqexGS6lZ3xe8TuhoWO+Z9gdCCF0DoHdd7ZZudXy1653P9Vbuu5x/9bX+rxcBNl7U6/r0X/8QlZborr3RmkNMwA473O4G/EQWiymQW6GmomPXnTCOA3s3cVovWvUOlqFYXRFI0RAQ79g2pdupKlgrI2st3nSa0pbIqfR/r122tdLFIaYjhFVV772O6I1YjRltqHvBatlkvMd4jxOhiKE5o0CfTQEutTbFO9b2AucQ49QS43SqsW3KNzC2rzo6QEZM67t0ul/YUVtUq13nWF9VwRpTbvDOE3wgbpBJGGNVjGe7pEd0DNZaw11VxdZ2PkDGYjtCWJ9sMYZhGIAeJiFq57lqB0QqtILz6rDACO5KfOzv+TSN/ObX3/E//od/z9/94XccDwbTFoYRjvcDv/rd1xgrHI9HjvujshjIfPzxwppWxcoaoUojp8TWCkfnub29YwyBZT2T04aVQi2RtF0IvvL61cAQK7nBtBsIDn7+8Qf+0+SYnPDu2y9wk8PgKbkwzytxzdAsxjn2wb+IrdoauTyeOH38TFpWfFG4i/e6U7Y0Bu/xAvPzifn0TKmVy2kmLUk7zCLkTS9J3VNn1phI20ZujafzM4+nRVP4ts6F6FMmZRs5tjkxjiutWeZlZYuV3STEWMlrQRyqTo65K6PUDpdTJW6ZNTXWCOsaSRU2HKlZztvKZcvkanpwjB5U3sF+MLy6GdhPhuAK+/3I7//wPb/6zTeMO8+aK5iBXDO3uwNhHDncvqUYx48fH2DNTHjyacPZwPnDic8fH/j00zMtVkYn1NK6v56+iO7+daNM+wYsl0LWs1YdE81gmxa/rUHotjQd43aHS2u0LZJypm4JiuCs0U7vyk9oIN0fn+eIq41DGPBFKJcFNwZcV8PnElkfzlweztSwIftMi1m5/LHv5CuEpv0Pa6EaZeQ3oNimHWJPotPpQsPkhitqOVQaX2FbIsloZoU1vtsb9d8rMjkwhoCgE64cM3ZoSKqwZUwuOJrS9aT2FR0M1uGaQMoMPfBIjKNKglJw1uHdgPcGkV5k9bWgtUrsUy6CVYyMFKxXBXpJiRwNrRqk6nlsXOccFE3/u4pTD4d9x6jrxLYcK5fzzOl5VghOnpFmVDf0esfoN4bJ8G//4R2vb4XDUS9O2KjtjJTK/X7ju3eBz7++43x6zzKrRVCculF0C2o6kKo7JZzmtVg/qJ7CVl2BOPeSUlhyYF09QiXT77bacC9MBi24PUaLnB7CZo1Ryx0AKryuVHJSSNQ8bwiZ0Qu7w8T9/ZFmHKUmPj880WokxoqzwjCOjKNHWtR0Uu8xTtkzJoyM06QNY9PPzLVxU0eYPm/XDU+7ir+lFwHyr5sB/DeHAbV+dZj+B0h/klpVn6cYi/iB4XDLzZsvWd9+wdPDZ3J9Zs2FskVKyvioYBk/BI6HA1te+1hfqynTgTcNFX2Ueq1z1MuuKaTm5Z+bTl5y3fZnXWBLBSuONRWI+rVoShebS9SRv+hIcfJBRy8lY0rF+UAzMG8ruRbmdWXddATp6VbCKxoULYPUIdH1ANdgnJdR0RU7qr/uSjKzxtA6hlclM/3Jw+gaw9gu1DNYlBbmOxwGtKgRESoGI7V/oO0LKCh05bOuRnSi4L2ihWvWHAKdipg+PlJVr0F6l6mVrnFWRWilcDweeffuHdM08vHTe7al8upuwA9wvBs53r9TUItX8FFeE+fnz6zbhefzI9KEIYz0bQ7eD9zc3XL/5jW0jfPpxMPnzzw9nzktmpx3PAzc7V9z8+ot1VgN9SmJ89Mn1m3jzz/8QLONt+/eElzg48cHPr7/zH534Mu3XzNN/1/W/qtXlmw908WeYcOkmW6Zqtq1HckmcfpCECDo/1/rRgJOS2gRp9kktymz3DSZGRHD6+IbOVeRh0BvQnsWaptlpsmMiPGZ933eHaOfCNvG+nRClYYKibJssEVcQ8iGJUHJYoPse/ZlPbNuCzkXtHZYnDwYWgexbJnttMq0x12dypWSxa2hzSAHemrEKJHKCoQrnxVhaYAlpog2hpzg8rLgrBO3S62kFMmxUnOilkpOmW1dOa+V0AaWVEjFkLVmCYXTeeWybKQs1wRVRu+HnePb90cOs8GojLGZm5uZb759YDdbSgk4AyjDlC3fvHmgYJiPD/zw4QvPP31mezqhLollXZnGA88vZ16eLqjUcEh3X7he0/pVd4BS8roiTI9S5fBvQMuKEgpOKYbBgLLkdZODrhRMqf2g6cVW7GiU1idcWnzVpTaI4qlvtWBKw2sgJtbHjLKKW3PL4DWtWcK2ki4bdRE415oWgS11wFZrClVkZwxIHnsHfsXSBcBG3ADOObHuqSIxdFVEugqxapkm/71tG8bEfj/TyX+iudFGCiBdCrZBXleWbZPVkrV4rcVAVxpKiShMG9FiNSpey+qDpqhaaKAKEcGVQk9ULVgn6nKxP8q/0oZWlGkygejPraSgGtk7+3GUyVQtlNSw2mOVpiBFmremJ+VZqhM3xuAcOUIMEGOhtoQ3it18xLqKLmdacLTBEesFasDohjISVHS/r/z+uxs+f3xhvWxsBZquFCq5dFuctmJ7sKJlaNqw5cqyLdS48WwVu93IYRqZRkuNwkHQzTBPgzg3csa2RuzuKacdxvluLRcdmrgNhNVCEzRPSJC3CPmRVgKHnWccNPvLJq6aw8j7d/eCMe48j9GNTNOAVdCUEWeNFeFhyhV0pVQEspezvP5W9AtX8p++ToxV12z1M+U/8/GXFwCiR5ARieqLBvTrSkCrvsPWCmUsft5x8+4t9el7ysefWc5n6rJKDK8WsUsKkgq3u92TQqWoSivS0V5Dh3Jq3TtKB+FoGd81CDH2zp/O6ZbxnjHS9cZcCSGyJYF5VKTrbko6aKMby7bhdQNnyBQpUmJBh0imscRNxv2l9WLk6wtsjCg5a66/CN6R+E5lzSshsBX1Gut5hQ2JMV8QurpDiEC97hYNCqPMq93EGHlNau3pT9fBTx8J11KkMmz9gqgZ66S6b0DODaskqdFaYToIk6G9jsVavdpHvuZtl6JAycNCLjHIsfDzDz+ynD4yusxvv7/hH/7Lt9zdDfhRMYwDtRWcVThdWS5nzusjhUjTlWmYuL05gpHxvx4d+9sZNxpaskgyWqS1wm4/83C4Ybq9ZzzccPfuO1DXcVzk6fETL49fyLny/HTBu5HBeZ4fz2xb5ObGszsc2M8Hasycl5XT0yMDGpMqthTCsrJdzkyHmRQCuiZU0yynM9o0rEKEYSqjm4SHlFxIIbGeVk5PZ3IsjPOMqpJuGSuErXK5FJqKjNNBJlTZkqIkCsYmUdOqC5pyaozG0VLlcrowTQMgeo9WitAjc5adqpX3I6fIyxJYqxXAT4JLbCxL7uxyMK7ijWYeFN9/e8dvv7tH1Q2tIse7mfffv+Ht+xv8oGgIcOWyNZSemMoM2nEJmQ9//IFPf/yR0xpZl8gWK803wrLhS2PQhrAVcuqhXN5TShPbGe1VaHp11oDp11wjbJnLeUM3UU+3mInbJqryqwa3Ida5LJY03/fSztje4Ynwt2TxozclHnAqlDVQADdY0hqY/Igxmm3LlEuU+6ZCjUWcPRlKlHZHVbDdwdOqIjWZNtIFaRKmxeuOGaXwiK6ppESuQgB0RlanpRVUQQ45JCpXVYEGKYQx4JWRrWsupFrx2uCtxSJTIIUgdW3vXLVVOOswTaFrFXy27rG4fSUpWPGEtVfC5xWmZvHOSLhaKygq3unejlyvP2EbhHVFxyiZCr5PG6zBa01NEW9GrFbkHIXdUjLTaGnOEkxl8EpWijScH2kq0uqCZqTmlcv5M4rE3c1ewD1bQOXCcZr53Xd3PD3/yB9/hBT7mhdDk5qP0uRaCzFTm6wacxIXhdNwEyu5QsiOwcAwzoKSN4Z1XbG2wmhpUQ7hK3U21ErNYLRlcB7VFKkl2pWM2Gunbau8PC/ksOGdZlsz05aZdvtX0W3Oop1SWrFtUYBKupBKt7PnTCgZVSSG3Vkvj/lOd7vyMRTyfFavT+Xr/+d1wvbXLQBovTOVi+LrR8+SN1ZGlMgkgNHhb47s39wRv32P3xaefviJ+JJEeFMhhsCsDB9++EhWMM0zmGuSUcc+WsfpLDhZ6W6tjNQb1BopreGslx1VlKIi5UpTEruozYCuSvZipZIRO1XTjdKFfrGPy0MupFxJpbKugSCzSVKRacswipdTad23IH0fq9VXDnRKgBQhMQTQYjuUXX4nCqouVrxqKvu+7euMoydaaUMqhZxhmjzGiKL5l6hRSWH8JZtB3qJSCpP3aGvEcqjFHqmMfSUpio2xv2c1d0BIxjklJC9jRCFfJQTDdLeCtZ5PHz/z8w8njgfFaN8zDYlt3XFz7xmLYX+YqRTOSyLEC8OgubmduNnNvLl74P7+gdIap8uFahT72x1oyVjPXa3uRs/h4YFvf/0bbt68o5mBLVSU9sS+3jjublC5kqLAcR4/PjIOI9O44+7uDXd3D0zjDMByWajdXtOS7Hi3pxfiaSFsZ57SQiuJ4yy+3HDZ0LoxTQM30x69s6xrIMdKyZU1RcIaqKnQCuhm0MoBDeUNu1kTm6PgSBnAyN7SIEp4rRjMyOBG6RRTV8u3RgxB7KlFo7xDxo0ZVMV7wzQNrOuKcZrnp0zSiVDgtMIWRRw6GGSyYRrHw8ib24m//fV73r/Zs54+s9vt+Pa377h9f8NuJ8WG96JEPl8uohRHdD4vHz/z0z//icuXMyU14iKI4xYyPkOtkhtvq8Suai2cDu0cvOpXREgliXYFwYgj6ZmxkrZEcYYWZU2oasN30hu10LIQLWWHBiVnCekycs+4niWfu0CYWr7mprce/6s14bxQxkm6u1BIQXzzqkkBrjEijM1yTyktQkyFlgJZ+gw0Iqa0zvX3FFpOEv06DNAGVi6kEEWs2LpuKgJGfPfiuuliRgQJKzqIvr/vGGRnFDkGGkKg884xDE4cP0p0D6N3eCsugZYLWSviNfpcQUG89tcpgyCFwRrLbhoZR09OgZqjUAGRKUoskW2L7PczIawUGuM04Y2EOelaZYStDeRCriu1VmwvVOkOomkYe0HoSSmwhQshnPHe8/HnHzjeeGpe8B5UETT4cjoRV4Mqhje3Ox4Ojj/+MZGyXN9aW4rqMDUqAYltlphhObJ0L+4aFW1ltbObLHY3opDXRgBnGuMdTWVSXkV135/9IA2f9/35WYQ2m6NcW6OXBjkmWQt4J01dAXJtbKFwPi+sa8PaTMmOGFbU5IDCthViDoRSyQacE97CME4oa6lV9QmtTJ10Pyf6gXH9D64BfX91EqDWrSfelW6/k5FzLQ1q348Y6SqbSNcxu4n9wx35zQOP//w/OcUV5R1pi4SYGIzlfF7IpTHuZtZLZJxmSq3EmNgfjtAZ3RhNipGUC9YPaAvDtMM3URjnUlHGsTvOGGu5LCsvlw3jDZctEmPEjRPGWEIubCGC0oSUqbqRamGLSWx7VX6OLm9g9BrvBedbEYxuae3rTdIE7KNKIeREzhk/DrTux9RWxIjX7G/VyXe1CTPg9QrTX4ucVmQE743Y0ULYcM7jve8CnsI4jpge+XqlAGqt+yEhyYG19uhTuTqwfWSEMp2uJ6ZhrSXKdhwH7o57vv3mgWUL/PzxE1v4ah4spZC2QKuBHFasVrw8PfLTEBn8G27fvBMUbjjh7SCRvusJoytvH265O9yJLkDGNhzf7NlqIlc4Lc+EpXDZAqnBzcMb3v/6V9y9fWCcZl7OG6fnC7VpIbStm4TPKLpgrlJCoZmGmxy7ec/t8R7nHF9++sD6cqEsG/myks4rp0+f+finHwjnhRgu3Nzu+ebtG6nwtw2nNNRC3gKpSea4jIJFLJVDYl0WSm7sdzc0/XX8+fz8wuP5TNUe40a2kompiDWpaawZBFyDFIfj6LFWdtJhW3B2Yjm/YPSuTwkyqmVBrprG7d0eYzWpKr55f+LzSyWdYUAO/1RhGGE+jNzfHHi4P7KbFfsR1uePqLpyd3jHYT8wTh57jVjOiXXboFaM9ZAS4+z407/8gY8/fKBcKtsGN7PnskVSiRhtyLFgUIx+6KmTPcGtSMaG1orSASU5V2IqhAZblmtyXSolLOhaGLTcW173vI4mHVDK0s0bbfCjxlvzuibrF6esJHuIjpDuRKhljcTxNiXTpe185iUm1suGtzAPE4MbSWvmclrYtsIwiABLsLP1NSPEKUUtiYqk6qmSu2DZ4IzhZp77a5lpVgvzvj8jYhaxmnNKYqVrEWiPMZjWIGc5kOT2lFhgDV6bbons0ehKJhzayZSh1Iy1A95bLqcTox0YDzOft4UYM/M4CFitswBKSlgNd3eSAaFVpeaAalm6fRQxpVcEedwawQVQ3c7tKrYZSqqU3IhbQpmNm5sbEQoOTlwu69bXjqB7muBoDNY5/LCjFMN5eRRdjJ14e39gXS88P63c3NxwzoEvn595uH/HcpHvbfTwvMCaMn4uhC7YuxJTRYvWRZoKIRsC57XSWqDsRCPUSuX+OJJqYZwnTqcTl8sJZ0eG0bFuSWBEih4kJxh5ZxTFGUIPQbMGvEfAVrsBRZHnXshoB2wZ5ybmeYfRhdPLimkSGvbyfGHaDaTUCFnRtKyiv337HX//D/8VrTQpF7Szgp1X0kSYvubpg9o+BZYGV5l+Af01CwARkMmIS+nGlUymlEwGahWrmRKOLzkl0rqwLhee1jOrrtjDHrdTsCWImRoK68uZ2mDdMiFFliD771pldKl1JZbCNHisle4qFenAlLVYbaU7bYp1C3J45FUCcuwAxtKUrBeojRQLl7ixhSCJcKVRiKS+zxPikkYjkAvr5YWU50pfA1jbkb2V3CqlNSFicS2S6iva1xhRDJfriP6XQo5uodG9AGjdpSB/p0G7ChilA79+KCUq4KsS9zU0o7UuAKqE7SLRk8aJO8H1H6J/7Vr7prpKFru14gDY7Qf+5m9+zfffveXldEErzYfPz5zOK62o125qN80knVBtYVsjNU3oJg+XwVlay+SwieCzFkEF2xFSoeTAMAwU1VjiwpYjdpZEvp+3R3k9Nfhp5ObuluPtDbVoUohspwsffv7M4+MLueTrCAXXVe23N3sOux2H+cBxfyNZ7ueFxw+fqWugbpHl6YXLlyd++sOf+PjjR273I+8e3vD+mwfevXmgxI3PHz4Qtk2S4YymJjkQhfXeKEmQodM4Mt8dmaYjl5g67//Cusk1mFumxBU/7CkpkJF7pZREiYWUNFteGaKlkXFORJrGQowbp1Nm3S6vbhA/GFqSvf6b4Zbd8cj+/sLnpwufn06EWMnZkNE4P7Lb7bk57vFOUevK8vwJTWQeNCVvKFXxg8U6zbZFYohobbHGkWJmdAOfP37m808fyZv4y3WRnafKMBrDrqcIrjHItAvNGhMxVpoWHn9DurHcpCPKRVgaramOepMSU9WMaUVGs1phW0MVeVjr2nPVOx0u5/x6T1zvNWst4zgQYiDEIFO/CpB7trrsw09PzwzDwM1hj8EInySJMl7usR4F3g/Aa1og/YFrrlu81lC14JxhnjyH3Z7Dfg+tsa4LLZqeUgfaGEYDQYudT9UisckNDELmk9jgbl3W6hXR3e98YXF0fm+pGa0tfpbwmpgWSt7QGsbJiB7hatnWMsIvpUFR3N1OvH17x343oVUlh0RJkRwDNUvb28TWxWAddpadt1KaabDc3zwwzBPn5UKhE/yQdMCUijRLteJojINDWU2qRVa78hTqGjDLrbsBIrVULkvGKE+MjQ8/nchBc3/3ntPLwuUlolJjdDANyKGZMmsSJVxr/JuQs6s+LdWrRb2gKQxG9YlL4WzhZj9QWmUcR1q3MqIbdrCEkEkBhkG/WievKY/OaJKNaAX3tzu+/9U3vHm4ZVnOEh++XjivG/c7QeNbt1BKEpRyg+USOR72hChR4TiLHgx+mHn/3ffc3b/pqn85u9qr1a/Hxr+yZXo2D+3V0ngFCP2vPv4TICBJGFJavpHG9YLoi4da+pagyP5nubCeXricXthapc4jeRqIi4j/BmcxxuNqnyIgKNzBT7SmWJaFz1+eiSkw7DxNK6Zh6shRsX1YbUALKpSqyC1x3jIhpm5nMWxb4rJt4n0vmdY0S9zYkiR3+WmgVIT6pBXGO4y1mCrTDqXV6w6z1UpF0Tk7NOTALab1rOavT6dSJOVQafsa2NOQPR3Iw0Vfmbu/0G3UThoUjr9czdrw9cFnTX/jemHSigwQmoj6ShcxShZ3FxXRx6jd9XAtFK60Q6WvQu2Gd47jYceb21uOu704P5uh5Y/kBNZ6UkrykLIyIpmnkfv7B26Pd1glqxilGrpqLBavHbZJkp0B4nJhvZxIrRJIZK3QbaU0Ed9Nu5l7q3h498Dx9hatDaeXM4+fPvHy5cSHP/7In/7wE6eTIDuPNwPvvnngOHh2fuT+5p772zuc9aRl5fz4zHo64wvky8rTh098+PMPPH/8zDwa/u7v/o7f//ZXovTNicfnJ2rOWG3QNOIWKangxiZ8+1ypWb1Oeu4eblFuIl1WtpZIQSJpZeTsSV18VUsC5PBuSvCzTckIMreVabQcDiPjOIAS8EfuQSRVKayVN6tW8W77YWIcHb//zXvubha+eXtLE504JUs8trOOeZ54Pj2ybZmwnak6oac94zRy/+aBw/1Dp15KtofRDo0lxUJO8Kd//Uc+/vSRGrqq30CK4I3mu199z+54YFkDHz58JqaMHkSEtcYk65z2VfSXS5PXr0pS2jUhpTQ5UE2r6FowtXu3qZ2H3tBWiJlGu16Ai9NGdcn2VSNkrGU00vG2bZOCCYT7rsW6ppRinifmeQ9VHsZLWCTLo/vkU9cXOadfw8Bokg4na0D5mhoYFMzGcBgctkl88aALWRWZntZGy+Ik8KYPF5V0axoJiqFK9K5TTuyETdGM/J7WGqsVXg8M1vRrINFalGC1weGMYH+d1gyjpuXCfueIJop2Z2sYC340PNwfeffmASgslxdiEovuKweFRklF9Eba4IwnVdl7Gys6rLhsnL48UxVYb5mmiXBZSCUyjAPXoIHWPIoiYC3kPXTOYZDmzU8D1I0QVl6eV26PRwbnucSV2hS1CLCnxILVmnmsjBHOubGmQq5CJ2wgZ1MTWXa7Nqm1B7kpSRxMOVNcX8PmSM6SdTCOI77By+mCMpZxHMnlgjaKwXsBsNWuM5MtNX43MAyew2HHPM+4YaCtF0HIK0VTlnXLnM6f+fDxixh5SkHtDDeHPctyIYSVkBLzcU9Kkcla9vsD2lrRkImBS1bF13+6JVheYfUfDPz/yiuA1sT+cm1EG4WqZCwF1zhDRenUrhwlp7o6R5tnyjxzcY+EmiBFJjR7O+D2M0ZbtjWQzmdivGCUBWugVqweKK3xcpax3DhNaKXYYiZdNrQ2NGVJubKsgXVLxJzJRSImL1tiS8Lxt96ijCE3REhmNXYYJf3LGpoCY11PnULGvyW/Jv5VVIcvAE2Ig8YalFG0LElSWgtMR9YCCt3L0WvUsHNO1gG1dAufiHVar/SEKlgwRpgE6hUGoTHu67izVV6zyU2fBhSdXpeTgx9xRhjSKSVoBWNlinIlChoj1kVtFLUK11v83wGj4fZm//o95hLF/91FPfRUs9vjDd9/9z2/+dWvuDuO2JrJW3hV0dqiSUG4+aEURjdwPr2wbis4xXAzM97uUQ4amZubG9wwEWvkeHcLSoRHNSZM1bQ10dbI8nnj5TMcbxR330y8PRx5d3/PN+/f83B3jzOG5XxmOV8Ilw2vDel8YXl64cuHj5wenzjuZ373u9/xd3//t+x3E58/fODzh59Znl8YrWXwhhg2VIVcIssq9r6YsjD6q2IElhQI68aaMqFEQt24bCcBwzhFw7CtQSxSYuKntQS24CbP/mbk5uC4ud0zjaME6YSAUopxnGQEG6Ok7jkvdlMruFUJJynsd5Zp3GGtp1XNsmycL4GSAsvTC58//kRKG6kGoBJ3Etq1O9xQWw+2UuIGiVuSMa42PD098sd//SPLub4enNYbKIKyrkX29XHZiGFhi1mQ4LWL/bqTpCK+/dxFbbUhjActXbRpMDgYjBJCHgmPRevar0FZl4jwuD9rKlJAACXXnhwnkwRrbbcHQjOyi/bdltta43BzBKDGQOkRiuoXZExZn8nb1Zroh65PPm2QJDjV9U+A1Q1TMulyxo4ercCmhLvqpkT2hG29X2rdKgE43dPijKFpqDVJVd4PGYntNYzOyTrAGVoxxCSPfms0b+5vebg/cn5+IS4LqmW81dzfHYhrYDmtnAuMO803747c3RzJaSNsF0oKtCp7f6s1ufTJRBFtUq2xZxxE0IqUKl8+PbNtG+clMIwa7SXG2jgj4mbv0ShijqznCtYSqkSmW+MxxyPGKGJMoLIID/3AVgopXpkPI3qwPD+fGd2IM5VxnPF+AzK5Is9RI6tZORj7VKn1a6xI0apNL/zkJcX1a8JqRUlRmCcdMFcrshpVBe9HriFw27ZJgmMXUdceSGe1ouTEly9fOF9eCEEcQ86PLDFhfSGkSrueOdqSSmbZAhoY50lQ3RpiyrzZ77h/eHjNiZHzV67B9ovz4tUv2647f5kY04ST8Jd8/MUFQEfZC3xEye5LflEiSbVxVEQpac2AchNmd8NAYamJlALVOXgXUMtGPV0wseCU5vz8QjYFt/cYP3CYdwzDKDvzVDm/XDhfLmwpk9uCUpqUEyEkQq6k3GlMMROTjPxyFUZ1lLCp7iIQb71yMkpVWosNqYsBv1r2amcJSHlTq4z1rx/XF/9rFSbqU9tH8uivUb5KXYE9qg8HdH9IKa4peMp8FfLJ5KGPKul7faNRyr5+7dq/x9Jyf4AIolc7+f6Nkr2/tbJKiUVuPFHz225JlC5HG40z8kTL/UbRquGt4rgbGEYB45zOj4R15fn5xH5/gJqZDxO/+u6B795/w37e9aKpoothuazEDiOJS4JUGHqUc15Fqe295LkPg6VZyRzQpmFdpeYm18y5obVndiMPhxsu5pmpKo5GcfPO8P2vH/juN98y7AZu5x37caCmyCUGti2wXVbyltC58OXnDzz98DPPHz5xGCd+89tf8/b9e0JOPP34yPOHj2wvLyIaslYEpVsQ72+DnFdSa2whUkrFagmteTo/Y6aBYkXJW3URtmwp0CK1dNV+hzgJ+Cozz4637255eDhwczOy3++oufD89CITIi3Wy1oVrZoOs6pdDi+HXW1y2Gn6AVYLJVTKttLCJmPtUrA1sKYN4zRYx3x7x937b1F2EHZBqXjr+jhRitx13finf/oXfvrpA6LxQTCqRlC5CsXHn39GOaFqKtULXKVeISVy8FdSk/z2UrtWWNH1KP3w13C7g+NoGFXFqIbXkiwnYUNOMj9yJZW+squ1O0JUV+NXVFOSyVGyiCZ7h25VwzSxqgGUGPqIv6/aqhwamtZdNH3ED/3vyL1mtMIhICKtRazrrMY5jTcaXTI2y0+uY8TkKEI7C9oZsm00ZYhRhGw1i6/d68boJKhmSYFS0vXJ2y3AQgf1XQBdmvD3vVUMBvaj4/3DHSpFXtYzJW9YN+IHg8lQXcPfaL55e+T+7gZrYDmfCOGCtQrdZF0lI25J01TdbSWTIFlFWKfRShOWwLYGrFbspyO5JOIScZPt7APVBZ+QYqSkJOFqTdFMIywXaSxyRDWHIjMddwKPS4ntklDKcHO4Yxz2vFwuguA1jloDMUPOvYYy/b5rfSoNUsR1wahQTsFbmb54LQLCwUjxZWkcppHaFCEo5nHkdA5c4so0zZRc2ZaE8wVjeugUMgmpJRPihiJTSmCuA8MwMM0Ta4isKaFSkpW10T0JU7OFjRQ33t7fMoyGkDculxPKe7799j1vv3lLu2a4/PvD+Kry74d9vUr+rqtkZOL2l3z8JyYAXw87XqUHcAUClVzBqG6VGKh6R9OieHG6YgfLzZs3uJwx543Lx8/E52cRLZmC2zumaWIeR+ZpBqV4eXwhhATmBmUsIQRyEtKf9RPajuTzyhoCpWpS1Swxk0rDWIedJjmQWu0HserjVxmlK6OJIdAJAT1vWV5CjYB+UEo6mV4EvI4ZdYcuaCGBvfrvjfjDrTXSWSi6CEq6hWuB8XVRxVfxHnLAG0Sh2+BVMyCJT/pV4OI68KO1q+hD9oOSNCYHBH10aCS4+hUvbGxHFquu4dAVZ4Vk6I0hp40YLqQkZMPbm5nvv3tDzRFjG9tlwTvD2ze3/Oq7b9nvZmpKFC1im7gVwjkjEiyNKgJ5UUWxnjYePz2iHIz7kXGc2E87znlhXS9EnaG5Lr40DNOEwVE3hcmF+HxhqIq/+eYtN8cjtw83jNOA8YbRCGc/pkRTCmuF4LUsL6xfXjh//sKXj58IS+bd/cThcKDWynlb+zjZMo4zugoAhiIOE0l6lAdy7WjlUqCpTE0beamM/sglbizrRkzb69qm1ECKlVZlGlOa2Dyn2fLNrx74zW+/4+5ujyKjWmXL8ZX0VjKcl1VGvGbAW0PTjZgirclkSm5D0XKUVPpDTzGZxrBzVDTrlpjnt9inZyKV6ebAb//277l79w1FSRE4u1HGxK3gB7GlffnzB/71X/8oGfOjrBVSFDT1MAxURE0eszDKrZUusCGK+9SaAIpKIfXxfyqVcm1eylWkBbsRDjvD7BTeVCarOUwO3Q9AjPxooYnVr+bSrb8FEFaG3BuVmjXGKZzStA7m8c5gTSfuqUZcV4zRjNajlCOEwhYjrci6gSZdIlxT9ehOGi0HrxFynjWayVvmSUA7WjVqyRhtaGbkZnS90BfS4WULrClinTiTVNM9VE3TSgQMk7WEHL/mh+hC1ZpmEtY7VM29SZHuv5XE+fTEp581ab1guo3XtAI1o1ridjey280c9jtqipzTpRcZ8v3WnEkx9VAiKdIk1U/Tahc/WpkQKS0j82wbw+CY/cTzWUipWjeqESy0Hww0cX+ghLbnnUVpcUiVmmWXbjUpVS6Xc1+NCKuklMbpdCKthU8fvvC8ZHKUJEcQUWEtDa3Fj6m7XMIoJboOo2RSVRrToDhMGqcL+wn2k+UwW+bJiv9fKSqG/TTj7My2PRLXhDMDzUi+gbHinlrXgCQ0KsbBM46SKJlzoDXPMHhqzSzPL5TW+NNPjzgL3337LeuSePr8iZLh3f2OJWwUpUg1UVXhuD9w9/YW6zQ5blTv+3S40bRMD1U/kGv52pRe7eWSuaH/Yh7AX04C7Df7K66mXWE2RnbE0tSKiA6HNSPK5f6ONPTkaccLLBtqPkuozm7E1YzbWc7Pz7QmCX2ndEJrTWABJ8KeYRxBG5RJfcdtWUOSvaWRhKSWkReJhnIDfpwxNGwXD5XWB0VKuM8oI+rK3DsF3fn69Cqqyj7wOobRquchqKt6u8+UrireTtxrtK5V6FhiRLksYSg9Zc8K6rUfkVwLqtc3TvWI344Zkteajr/UaGe/0qiqfMe6ZyuUlpmMhAI1pQXBPFqsHahNPo8fhPmfU+zTAockEYqlLoYLMXiss8yj5/37OxqVYTD8yz//s4RevH3g7vaI0ZBSFFVCbqQ1Q3FSK1aFaR5VC+u68PnTB3766Yk33xzZzwduDrfsDnvyWiEnjLJ4N2JGzzwfKE1xfjrz8uHMn//nj3z+6Wds1Rx3O3bjgCsZmw07L7vRnBOxRzdP40xYVj79+COff/yZ7csLOWzi2b2svDw9s1eVaZB92zAMhBDFPoaSKE4aW8dAp1ooVMbdxDBM/TrQDPuJNmpyLLjZoNqBsIp1qgSIuaGUyKBjTpQaubk78OvfvufNN3cMXhO3LEwLJcVdDJUYA+V6C2mN7hGRg7ZMu5HDcY82mk8fPtCMCGGt8xJ52qBEGT2mEIkpY40iY7l7eMe7b79HuZFYk3QmTfzupchuPqyBP/zxzzw/PWOMlTm6RhjniP6miCQfiuiCcsqsIVK0pmnXHTWVmBuhT+Vq/dpCaAVOwezh7mB4czOxd5XJFB4OE/Pkaf2wq01RmsJq6dKtEZ5HzsJjFw1O5/NXhVGuT0ZE33IV1mkt96pWHQ3eV2oFEfY5I5AzSad73ajhjMY5Ge07XRmNlswIZ+UQ7KmYqlWcG9B0a25rsu/WlrgFnFboc0E5K1G12lJzIcREahIpjLVQ0xX8KBOp/rk04L2ThLuS0EgeQVwuvBhxTgzeYLHoIq/bYRw5zjuOxxsZ24eNXIJMX1SjIlHm15Ab3Sc9QpsDYxRDT33MOYrlVRuskh1+SuKG0RZosnK8XC6U6jBORt6qe9dVbb1IKmil8EbTstxzYQ146zHeM46WVjUff/rM05cLT08rl6hIVdgSzsPeaGpoFGPQtb1amg09KyHL9bab4OF24G4/YHVi5xqHnWE/OWZv0Iwd8qXxdiRsshYySiKunXci2qQSYxR3hnXQKtYahsFRcyJVRcyJl8uZ8/nM6RRZG1wW+Ob9xN/87d/y8eMj63oR+qizxLCRErjBoJzkxFwuJ56ePrP3O7AiKG2tipW2T/3pjSjX1/XaRGrJpKh/bQ2AHPStozqvPADZqDQjh1J5/bIGpTzG7QSzOx6YNZgUyedn2vrC7vaZdPoM4cLpDwu1aayysMqn1s3AIja6rPrnNUi32yS04ePjE6fzgjJeoD+lUbWiKUVBVMnWOZrSVGoPT2qvMxXdu0Rp9opAjOTqp5T8+gBDK6x2MpKld+dKOhJqfVXqyhj/epbLnKaV2lWZPdCntm6Lca8iwFdnwHWUI8iiX7z2V2qglf2ZMfKzdfW/6t2/9w7XKin2tYDW5B7s40cvXVtpxJjJMWG6AEsy0vs+mYIZJuw4d0Fkw/vKYYJtD+FceH83cXvc8eY4sR8MGlEQrzmTgVlZHJoQAiFsDNZiFGxbIOXE/uj5ze9/zfe//TVthC1uxBiwzjJYgZKUXHn+8JnHjy98+NNnnn5+5vOfP6OiwpuRkguXvKHYcbwZmAax5zSErBZj4rxGHj8+8tMffuD5w2fW55XZSkfz+emMnn/mm9nB5lgvJ3yMxOXCaA3OOcIlSAw0DTcMaCrz6Ll9+8Ddw4Pky1vD8eGWMmiSysxeAk9OTyeevzwSNpnclCbI6C0G1rgy7kbu394yDF1nEEUV7UcnxLbTImP5YQKMgKi2LOs3rRgnLU6EGPF+wBkveGHtsMoQ1o2ny5nzZSHVyvPlTDaGYTfx5pt33L25wziLN4qmM2FLeOMxzpDXwvKycXq8ENeMQXjp1/SxUrZXv/G2RSkyvcdYJQmFKFH759x9/pIJUOmfQqzrDBoOHm73ive3wikYVWB2mncPRwYHKQW5XnMTZ4PTOG8IsXFZMrmW14PRdLm9toqmak8/lHVGaUYaFwNGNQbrCTGwhkWeYfQIWeV6PKzgmhu9UDH6VZRoWsX1zn8cHN5IVoBKBdUKs98R0sp6OhO2Desc8zyLfoLG/bEjc0sX8arG4A07P4G1MiHQkvOhFVgjXAWtHDlndtPM5CdiWil5w2jYTZ7DPFNTZPYO1QolJLTRDH7ksNszjQOX5YQyqhd7iUZ9hZspQGuPbhqMWCprq6KY16CqQLNqrYzjIGsWpclJYERWWRHKlQw9h8D0KQIUYtxeC1xlpDGBwul0wTqLtRo/DqSeFjgME1lB0YqkFKEgNjetGEcNaqCaTGzCAShKHp2yCpLxvy5w2Cnu95r7g8GahtOV/WTZzzLVuDnc8OHTZ5HnaHg6nzgvAbShLSsuK4y+Nr2N4+GG43FPDBvrdiGGgDXCRyml8vJy4uW8sQbIBm5uFIfjDU/PF3766Se0Muz3e7YtyL0SJDAjpsLT5YndP/4Tb9//mt8e3jBMCdUSqhqarrS+xmrQcfDS0IlGph9srdth/4KPv7gAMFciUWvoLAdpa00EdS13cVrrdgxNaY6GATNBM5SqKDpjDrfYwxnunlHnmXj6icm8x548bBsvH55oa8G0AZQnhELIkepklxhqZsuJy5q45MRaJZ9ZcJAaNzu86R1QlQSsdrX40fPEJZmC1iRL3ciCTnZIyqAtEjBRSo9W1GgrBYCk6/UXz1rpLlCknDqxT2w/OQWsMcKM77v+1keG15hJrYx4bWlfAUOtCdbXCN/aOhnDhxCkKrcCB/Ley43Ufc1KSWGh++twjWA1DZqpaFNoNXUaoOBmFTBNO6qqrNuGcorxMKPmW5LdUa1l2FkGE1F149sHzVhH9uy5O95xcxywJVJqpJRISishF5QaqSmxnM9iVZlHjIGcItpq3r99z3gcOaeFphpJ5Y4FjijlGbzl5z985h//2//B008Xli8r6ZyZtGceJibv0F5TyOSyEsuG8/c4Z1hLJKwbeUtcni789K8/cPn0TDxHNApjB2JdJToaOK8X1Cgef6sb2ilKSsRSujq/ChPCGObdgXffv+fwcKA5hfGa+bjH3B1ILTG4Ce085MrOOey066sDmcRgHcoI2yJXmfDQJMZ11BNhSYStUHJjGCdO58iXl2dKAq2dCACdwXvH5WklLQllFX4UL39cVp5eVlqG9XzhdFnJwCVF9DhinWW6O/L2V2853u9JRaxxsVb8aFFFUUJDNcvPf/7Iz3/6mbqKIHBwHhxcVgnOQin8MFCV6CAkclWmTrWJQE8Id1UsbtfxrGzVMA1GBd8cFL/9/p6Hm5HRZA7zzLv7HQ/3Ox7ub3l8/MyHD594OS1dlS4FnmrytVTL8rmNQHxiFfeE6poe5cU1YKqixEzuq/WcN0JOpAjTOLwmJVoNy2mlFphmg7OWmqXTVi2LJsFUvKvsZsNuGqhh4/z8TI2ZwWm4nMgp0WpjNwz4YRA9UxHmhmoiTqy6SUqfkyS/3BoxR7Ef95FubQrMSNOeSxBdw81hzzTP6LVSTcXZimoJamT2BmqSomI00ki1ynk5cVkXYqmyQqkFoxHMdOhseSzLkmlFCc9CacZBQoZKupCwOCso3LCJFkujyCEwDoNYM0MG1WPS80YtQs5rrlFVAQ0hJ0xR1Lqhuy6m1oxzey7nFW0HDsdbhnHHGz2ylk/oZWRZXrhsmcP9Db45Pjxd2EyWREUEyW6M7Pp1g2YVb74b+O3bPXeTRauMsQ5vG97Bm7c3xBhoJvPmmwfWrfJ8TpyXM6kJ8bRZmSaVVrBKMY8T4zyRc+FyupBzollD845xHEgld41QoyoIQQ7ZTx+fOT9vpC0KN2CauCxdxE6l2K5xKYkf/vCJ/+f/4//FWjV/93+17O/7eaAGUsqonqRbOlxLYpFl8qVyxTT7H/oC/v8qAK7Jt9dRtCyv6Qd+e+1dpSKRykSECgqUxK9W5LArZKq6ELRiU2D3Myh5pdSjYnmOXJaN58cX4lowGKnKY2bNkTVmtpSoSqGdp+S+jugUrZQk5ck6gVFIZK55xfXmktHY16pLUJet+1RT784t3iuKzLuoqicxNXkzrJVDuTaNtsLtv9JylBJrj0ELj7v/c7XgyWukJLLTaIxSX6cByM5Rsk4Vpv+at5bWNM4Z1OBIqYiNSCuGQehUxsoywagBp7UculkmGUpVKpHWNIMb8E7G3U2BG4XiVXWlaNhyoimDn2asT9S8Qd2YPQwPe94dDn1kvVCLo6lCSRvbtqBTpuWAzpV1WQTUUzJulKCdw7DHTZ4CFEQNVvqeUPbvWrz+P/zMj3/4ifxcmZk5+pnRDj3psJHDRiIzDBPeXTuPDlrqJLT1cma5XMgpElNj8oYlrOzvLXf3NxxuZ95+d8fN3R3h+Yn1cpIHuG7U0sitkjplbn9z5O7dA/PNAT1Yss7EFihbQT9eyE6BMzilqdtGPF0I2yagGKPZH29oplC0HJCpNXJtkCsmN1TKfWJSSPmKNE08v1x4fpYDafCD6GTmkd1uYhwH6bCWgNaKeFkpsTDZkVgUIVXWkmjOEFohlcS3b+453B5oqmK92EKt1sLiT7JT/fDzR/7wL3/k6fMTkg1ViHnFGMdgNUyO0r9H058FYV1l9FjlHlFNHkY1VEYjUKJreIvSosx+s1f8+t3Mtw8Th53lZhp59+bAN29vOO4GUtpQLZHWlXU5U7KmYkmpUXLF6hGnG0sMcp8D1gvu1w9ygGml8dpBaSRkImeMJsbaUcLy/ogFSLCyqXa3U/f+K2OwSKaA+PTBWkWriRQqLUWcaVhvGJ1lcJasGzSF80aidlsmo8mtW3m1ouRGKIEtrKgccW7EWQGl5VSkm1W68+4bVltyDqSwkZMcuLppagpYWxmcOB9arqh63Q93DHNfX7aeiqr7M6qhurNLOPMCqfLCV6kyKURnSha091XYp5WspIwxslotRULGFLRfrC9bbYSQUArGeezNVe1MlK5gb+21G9bKc7g9ME57jBuwvuDGkdP2hPIju0mC5tpWcEamSLrJzzA60W2M3rAbLYdp5Ptv3vL+MFHDCVpBm4z3mpubXSdqWozzPJ9WYg7knBlmz5gjscpZt8VNXCTjjDGW08uJuG0Cq3KWUioqZ4w7YIaBLSWazgxDIzXJYNjWCLWSt0iisXMD07ij0UhZVlm5FKqCdQn86V//RBs9490NfzvvGHeTTDW0rJhjTmBkZV0aEtbUmhTdFFT7q4OAvn7IGXYdN1x/rZf4Xbn++qGAJmPBLpunNOHnC1JV8oy19jQiyjhJkmqlWx40IQrLP6ZESFkocD2ZzzmH0o0tZNnbGvuKF81Xa5614olvrSd8FTl0OpHKWCse0SSwnlyLHLw9zER1yMj1sLr+vNdMAeeu1ro+MusPuc5vkHZHy0GCMTgtmC/J4e5JfVrwn32o84oXvlbIthcvtSQGO+BGgSLpvhsWAIQcqMobSgxSo5naVcqqOxcaTRcp6JyQxOxg0U6DbVirON4cmHcTfnDkvBLOZ+LlBdckJMQ0R06RksE4ydOK20ZNURLdOo3wChyKMVGoTLtRdBN0UaLxsngtmZwLIWb2bkBrw34+8Ob+DaFF2qbJp8x5O2ONYd4JATFTJRlvyyznVeJLB8vhcIBpR0uZliPl3R3nlxNfPj2RlsY//Nff8Q//9e/wo+PuzR1KKT7+CZ7SgilwejkT1oAdPdN+ZBxG3rx7y92be1JNbPlCKIGmK645dMvEEGm6YWqjxkS6rJQo6Y3aGjbrUM6ivAdtJawpC9kvh0ZdEpfTwroWcjakJEEnMVWWrRFCo7Hi7MY0D+x2M9M0Ya3CuobWQJA5e3BiZdpKFgcIlbVl9sc7fv3733L39g3KWpqukDNGu5433sgp8PMPP/HxwyfJfXcDrbXX6/71XOnXKV0FX6tYUAdtUFniTfdesRs0w2jwo0zLaheeOlPZT5o3d577W8ubuz3fvL3l/Zsjg4GwnckhkNbAtq2kVQKWtAF1zWPoVEWNiBaVFhDKFVJ2FelZIyuBYovAYLRht58x1gn6OzUuWyaXTM2K0F14TRm0sTKepuGNCBada4zOSJfeRA8xjhNeCdDHGIM19MmhuD9ak/7AVMgx08MDcN0ynK7FK9Jo5Fxl7aOh5YJB0OCm7+StUVjvUUWRQsIZoZLGEKCWLnwWMRyAUhWtFM5oIYAq0Su0JkVg7Y3JNVlRqw5aagVltQj6qqxXjZZjw2jXHRhyKI3jSKlSaIrVOZNypYSGa47jYc8wOLS62uzkyMg5d4F3pdXArkgAToiZy/nCsqxcYiAreda3miit4pwRRHqspFCYrGYeDaM13Owm3twe+e7hnuNoWV4CSlWMdRhd8VazLhfQmqEpcpAJYcmRwVk0kdEIylcrxTgMTNOIVo3QI6Wdc2irsdYw72Yp9Gplv9+jneXp5YxzmpbFXlhkXN6DqqQAPV9ONGRqklKhGVA58fjlC+0Plu9+/IHf/M3fM+9E6Ku1pyqByMnr16mH/ey9niGYv/IE4OtHe7Ug/Bv+fP+96y7836oQr5nTtXO0r6I3i8ITUoNYCask9OkO85h2I0ZVXqLsQ2MWTK/sEgUe4p3DeENuoXcAHjcMbCFwWRasd/1mQ2JRncFUxZW1qZrYMrRSOOVprXa4iOgIpDi5huFosIqUszD5bVf+X3f0yqCqojXh+otQTyTPYilUr+INZUSXcMUCX8sn+gVne+ZBLeL1d26Qm6VbWpTqzIAqRMTWMqXP9Z0VFbTSckAqA9brPq1Rr19jf3vDbn9g3E340THMI/vdwJv9jndvbhhd4vwYWdeFvAo9UdfGzu9QTWFQrMuZy3Ji3c5oq9nt9hzHHdtlw9qtW1kUYYukmmmmsTMz+x5pq6zB2hGlMiU3TtsFHTUUuNndsKwby7bJWLfJCTK4Ee01OVTSmjg/nalK42923L5/w8P9HeM4cXPc8/7be5SC88sznz9+5MuXz/zqb99ycz+hVEMNQE3c3u85zr9jfT6zlIBqkfmw53B7y253YH88oK0mXzah/aUVZeRusBiKSqCE5dBCoqyZkrII5XQhbM/YccLP8l4UNDk0Qii0rVIuidM5cblEYoJtqVzWxBrFPtRMZdsaa25sNbIUxZgEluM9jE7hsFAqKa2ie+nXGX099N1vfs2b9+/BWooGlNgbyWK7bAVOLxc+fvxEjpnRD5QujrJaOr0r0ro1EYjVUsU94ujWPwHeeAuH48DxZs8wiO1W66s7pfbkyowbCqPZuN0f+eZhx3FnOL888/Llo0StpojTBm8KuYpdTzWE118k2rmk8sp+Vwq0lZhdpfgKClKiGhfrnsLZAYW4CFKVqeB5iYAjo9AVStUo7fDeMOiGV5Jnb00VH7nRGBrOWLxSmFrIIQjd08gX1Z35oFpDNUEG11wJfTVknJUJpBaRI031bJMkOQWlSMaEkaYjlYR3hnn0KDK5BMESt8bldEZ1iqI1osvQ6qvFuLQi7WL9CnHTvbFpVcb5pXU2UxGomFKy6vSDJ6xRmialv+bSK5mK+J4xUl4dToIXv1LrUGLPdHYQ5srVZ9knstO0Y7mshJBl+pCLNGRJLMtryCQtaZHTMHAcdthhwL2snE4LaYP9ZDjOE141dlYxqEYLK0U7rJH35HA8YFTDOUUpUd730wutaKZhoGXRTuQAyhRihmEUcUHOsT+/JfBMVXF0bZtoUfbqgDGGEAU9b61B54yzEoBEa2IVtUCrxLSyroFpUox+pPZcAqMlcGo5n/j880+cvnxmnm5QztCaoVSw1z9P69Z8yQeQppmvDfr/4uM/YQNs/RCHq4Xt1aL2fyoE/s3fRKm+q6DfoRhQHmMGjB1ReiSVC+dLIIbUFfuFppvQp5SIqAQYaLHO4IqGJA9HbR3TzpBK9+9bJ7GkcUN7A0rGuVw99c6+ZmLXUimUHvEpKVlXe5Vu7TX4UDzH9M8hD8MrHewatiOefkmlojW0s2I5vB7yrQpVUCFjZiXeXnV1LnQlpzygxLKUikRqjoMFFDmJHcVoIxwApbDdIiVjta4dsBZUEZa6VUzzgPUO5wfGac88Hzkc77g53rI/7JnmkXk3MY0eVyJ7DyU+c/oiytdWCjUlvDLELUCBGArLshBCwHvN8XjkZndAJy20K6VEEa0Uac28nBaqrrjdQKtaEgqrwk8T1TTCslK2yPPnZ54+nLi8bKQ1U2LBWSFuGSUPSFTDaScTklS4PJ+JtbC/Ocj7MA8c7ZFxVhK8M2bGo+LwxjPM8LJ+wmmDOiURSe4nsjfouOD2A4fJcf/whuPtLdaJ/mWLG7EmqpIiuORCXTZsFAUvrVFTIW2ZsvaKX+IZsZOjVEPOMmnJrZBjJSUFWaPr2BVfQbz7LVHwND1QUKQaSdf7DkMrUEIl1cYMohvQTcQ/TbDFZvACkrGK42HiN3/3N7jdxJoC3vjXdVSrjVoghczHnz/y+dPnDkQRtb0xBtPH1lMzhJLY1szW1y1ayw62Ftl7z1Zxdzvy7bcP3N3s0CqjVRHlPYXWMrUVqlE0XdmPlcNQsfXC5emJ88sTJaxsW0SVwmGe0NVx2RpbrPIw7YlyKQYZlyO1RakVPBgk+EfYHgJ1sba/ekq86TkpZIgwkprmssmCMjZNiRVjK2OFWRucbjjV8FZLl6zbV7GZPCx61kfCXf3bHRPe5MuKErJUVDMisKuyDhWdkWg7tPWE0nDO01oibBXt5M/oWpkGw/u3b/n1r96xXF749OFCSgk3WErJWOSaM9rijMEoI9kMQrchhUTLGSivkCFjrAjeah/blyzPw+tUqBRUzqgeeGa0RvW4ZJTYQrXuOiXkWT9YufZqK6SSxXnVBCGvlRGiKgJEK0lE5VJs9jVDL1JMj0MvBUJuoBPHwXJ7f0dMDaM+keNKHWG0MJrGoGDUDd8KZbuwVoVWmXhZOe4HhskzDBZr4eX5hVhTn7BCzYlWEoOVmOEtVRibTDyNaGGUVjK9a1IklVKpVC5naYJaL8BKvzesdtQYoDTG2XVLKsR1Y/KKsYd7+dHSNGQKeVlZTit//ud/4Y+/+R/sdrcc7kdQViBDRomgphpQAhG6ruI7r/YvOtf/c2mA/fFz7Xh/WQDUK93jP/qbrdC6uU4eAK0LhQy1yhSgNUeIlVKlG06tUlQjk2UUZx1GNDQYpxi0R+dGyhLMY5yj6NLFJ4mmGm5wDKNwnmu+YnxlFH6F+zg/iIiwv4l00QyVfrjKSqEUiYfU2nT6nxZyV8cEG3sFB1XxoAKpdgdAR34qDK7JnxMwkYAlVNdRKCNeaq003lmolWY7BU1dGQTSURir0c2IjkAJt8D2iYR1hqYz3o8M88DxZubu/pbdcc/ucGR/uGUcDwzDzDhOTOPIOPiu2M24GjHlzDkU1vXMtlzQReyX2ltyjJQ1kWLFKZgOe6ZpYLcbsdqwrAvbFtDa4LwUAK5W8uXCJS4cH+4wbmKejuhBOtTL5cLL4zPblxPL00J8KdQkXSlViXshJaxWrEo43ZMf0KOIGC/nhVgi6/lIOD1hTUE7aCaR8gZOzM3T7SDwjpyIVZFSYB4mylh5/vRJUvB2jtv9gd3+wDAOpNc1RiG1Qi6yLspJchRyT+vKuZLXJOuQ2Ln1Riry/BiIKpPamdDBVbnKnlgrxaClo82lkaJEi4akqThSzT3ulM6qUKKsb0W6AWMpuUgAl+77bC322FgjTRl+9f33vP3uG9w0SXa7teTU6X/aUGvi6fGZH3/8ieWyUpLsb99/8w6lOvzLCtp4zZHHLyfC87OI+qh4BUWLf/y4N/z+u3u+++6BwXavu0oCqFKaWqpoFFoFp7nZWWZbCedHzi9PrOuCapocRcE/GIvaOZxTnJdEq/H19deqMY8e6628T30i0HKlaUUsEYm3bmgtD2SFJBfmrATTbCprqDwvhVwlfVMkOJlpKOShUSiiXerTSaNET1CbPH/StRjQMt6+ArvaFTFuRAnfahUcsJX7rWktqXVKobWl9JG4zA+Eu1BCoZSNOih+9XDkm7f33N4caHlFtUYrkoypGzgnAjAZZ4svK+dMLdLQdICxFCal9cAy1b+vQslZ+Ayo1whb5QyZKjZI25G7RkG9WisVKAF3aauwVgrzjLAF1pCoSWEGjfMOqpPpjJavW4rkBwCM48TgB1oTP79SihhCFxhCXRLbeqbEg0wUDEyDpg6aljM5LsIvcCOqJUqmF86Zy/LCy2mklgGj9yL23TZUgxw3lm3B0NhNA/PkiBmc28AKkK7YghlEVC4iz/J6JrampFFKIugW4Ftm9E6Saruz4+a4Z/IORSMaRcwbrRWsbszThPaWNci0NcTChx8+8q//9E98++3v2O/v0db39zxRm6bpKjb4qmlKUSly7f71swCuh/nXbv91KqDga4Hw7ycCjYaw4WVc0aMaC9RqyL0rytWQiwEMaEOhUbUw0JWzeDylRVKIXU1vUA5q9zjXKnt96c6kM/Z9/N9aQ1nZ5ws6WL1ampQR3yhKnAGq7+Jzl/oro3DaYGrr6F2xYV3Rx2KcRYqCXljQZMxYjbw4Wqs+OekwESd7I2t1/zuiS1D9QSFb8kappf9591pkmSv8RTV5gHCN9hUPuPVOPvdoubk78u79G95984aHN3dMu5lxt8f5iYZBGy+6Ca6q4ybEvsEQngPn5y+8PD1RcmYeR2jCf3fzwBLFYTFNE8ZaSs4sLxdU06wXyQIf/EgpkKqQxJYlc14TyzlQksKYCaMay3rh9HTh+fOJ+Hhh0iP7m4m1Bb48PssDPULKkcGY7tOvODdiquQq5C3Kz64qKVzYTpnxONBUJBMwo2IeZ2rxxMtGWhNPT8+UkLk73FLLF06nR6pqvHv/Dftb4XI/XxK5NMk2z+JVTlukhEwOSYJTmiFmQ0yQ1kRYInFNPThIk1E8r5GtwJoLlyBpjgXVxVT0sBk5nK4EtpwkNU8rgXtUKqrRcyVEFyJkR4U1nmHao7VmXVeuUWjNWY5v7/kv/9vfM+wmEZN5J+lpHTqlerLhD3/8Mz/96SdyFA7Cft4zjiMAqSQpfPJGzLkz44uo/1tlnvyrIvx2Z3g4eg6+0cqG0xXnJNJWKUVOmpgVrsk9YksinJ6JrZDjhkUOMt0qQXKW0YNj8B6tJaNgWQNaV3a7QaJpx5Fa4bKusjLq32MuUXCxVuEHi3OGqhrODSil2LbMeQ08nwPnTZaVYRNinDWVkHtR1sQF4FAUjWQ41Mx1eVeLgJysFpiSkBql7dG2awqarCmuD9PSUbuqp8zlWolZpigGEbM5U9guMk0YLUze9rCqnzm9PKJaZR5HDvMOWsZbQ8mJWoS2KY1/Q3diokyGu/gOLWyVnpFQaBKKlIUiOoye/WHHMA9UYFkXShf2tVpoUk3JNCcXsWIq0QApjQTYVBHB5drY1sAwruhaMUbhnJXzoWQpgqeJeXfAeS95EX1dGUKQZ3V3n+ewcX55IlfRPAxOo/cjl5dFvAAGMI2m6tf3n4o1hhwjT2HBWc1yPpNi+oqRXyv7aYc1FWtntliYdyNr3Hg5LYQtYjWM3uO9IycEbZ0aNaUeFy/TTxD4VMVgjYbRsd9NvHu4k2umFZg8z6fKZb1AzRg1yDOgX0eT17S48fjzBx4//Mjx5p6dMhi/Q9UsZ2W3/ynV+n+L3uUv/fhPrQB+udevtXek/Zf0lWf/qg24FgGVa5BQFw9I52wdKItkMskL5YZJxBIp04ymKmjGYIeBhEKXhm0Qu0CmNrDeUbUW6wX11T6vlcaNlq2PJZU2fR+oe8cuVbywqCV2UzvTxXwZ+/qj9vxsfRX5ywpAacGS0pXBqvuctO1EP2DsN7XrnITaQQ5GSZ704EXIVwvkvrMxHVRyrVGsMRgnRYFTIkiSqYIUIAo6v0AzjiP7/Z5xN7O/O/Lw9p5v3r/l/uGWaRpQ1qCso2lDadLJUJqM9xAMsWiTKufnz3z88BOUzH6e2Q+WpgyuVbyy1CGTVUY1RVy2fuhUtHKENVGropRGCBvLZeWyrDw9BkKGl5eNy8vC+WXBjZolB7ZzwJuRt+/v2NuZsjV+ePlACol1XbHF4JXFecfoJYsgbRs5C29cq8ZhmpisIq8XlrYy7O8xrlFj7AfAQMseqzzZJM7PG8sWOdVAI5NKZdoP7Pc7rDO8nE8sl02EYlui9T25bhpdNbpaCc1JlZKsBPAkxenpxOllpeTGeU2EUrhEiCjWApetdZKgXCcdOojSdAuYRGFYLePZsWOrZcKjX4FVRgu4JYTMeDzgp504YIwlNwkg2j8c+Nu//3veffcd1UDTUpDFGIQ4WSotK16eXvjhTz/w/PhESTLFcsby9PhIQx7yawhC9WsQgyjDDZXZe3aDZvQOe/TsZoNpkXh5otWAchqnrORsaFGJt5JlJdgqea2sMaCpDN6x2+3x48DlHDC6YBLSIFRwVuFsw5iCHw3WWZyXkbz3Dj8eGVbPsq5sMYrot1VUFcVZq52e1wBjQSsuy5nTktkSki1fBYYTC6yxEHJl9IrWYV6SQlhRrdBr/B46I86OpmViZbRCW4G7KG2xWtaFRnlCLrLuVOBGjdPXSakU9l7BPFj2cyZs8uw8zhOH3cR6ORO0jPSP+x23h5H9NFJzIm4rS0rk1Lr48KtWS1ItZcXamghxtfEoZcghE2KlVnXtjfCDww4e5Rw5BWKPDh+cl8anNHEPCTdYijajcNaCadTcMd+qcQ5iN0zbBiVjrCannnqqwDrHMHghANZCzOKGWbcNax2zt9TWmHcT837q6zZhNexvjhit+ag+yDTEaopqbCVJkU1BU/FOk0ullczT0zPbumK0ppQqTUaRtY6hUXPEGsNxnFFrI+XIukhiobMWN1rCFjifF7HGG5kSW6s57HdoI5kKyyqizGlw7OdRuBtFrh/jFLfHvQhGjXldpTlrGQdP64jux48f+T/++/+Xpjy//jvD/o3FjqPod6qm1X7mKPn7ir72+gs+/tMiwH+795eL6xpL+/XjFwJB1f7thEDJYaWU7OFrU6SiiLli/ECNUUKG/EAtYAdDjY68Cd7VDANGZWKJArlxriv8izCve1FitISWDK2n+RWxLX3duYkwUBstxDdj+s6qib+4yvGq+02vrWBDaxe0WGsIqoM0dIcxGIN1ouOvtQq0KDWxqV3jMZ3rnccqD0GtO+vcAPXVVSAMAzmkrbM462QP20NCti1IvOg4sdvvmOYDh8OB+/t79rc3zMc9u8Oe434WRCuVpjVNSxhSU7p7fcXKNQAqBmK48Pz8xIcf/sj58QuHaWJ2CpUDyjpMKYQ1ysiwVpblzPl0kdxvpRiGGe8mIbVV2NbE8/OJp+cLyyYY2KfPZ3764SNVNabjSNWFvCZu9ge+u/+G7Xnh58cPnJ5PKDTOenRtIkZylmGw4mUuGas0qhbmybMbLDWsXMoFHQzzwaNHUfsq1xXdesB5S9pgHI/UvUMVjdGVpjN3d3dYZ1iWRQh6mzDPa2p4O+CN/IuB1CJWOy5I9ncMiZxqX2UZrBsp65mUFSEXmnOiOyGKLFYpaoVQWteKiHW2VtENjH5gv5tRrZKTxKqOoxfvdhKMq1gcM8Y4QBPCJpMhVbHKcffmgW9/9a1MwIwUutu2UrPgalWFFBM///gTnz58JIVI3goNxzkIDQ8FlcoWo9xDSmZUg1V4rbk/jnhvGL3h9jjhLVADYV1RJHQzDG5C4b9OM4pMbtANaxxOS1HntMe7EWc8zlbAYZ1iS428ZBQZ7xXDaIlROvGUAilFhmFknGb284jqz6CcCyU1coScMsE1nFXoVnBekwqsIRNSzy1ommYgt8YSGy+XwN4rJu0ZB0tVsibQ1zF7fw5KDgjkeg2KgmG0jNMoziAjKXi2JMIGDSnsrw1E6Rol07+20ObgZichNUoZvv/2gYebA0pV9vPEfhopORLDAk3EmjFeJ08N222QMiUUYqKzjpjE6qqN62l14kDJW2IePL4f5LlWPj8/48vEtJt48/6tCARrY10WWiykEAlb4rAfxVbY172qP4etM5haYKuU1AhbIMWA847iRDg4zTPj3IOsmiamLBbWTWia+/2Rw67gbOP24Q7tHGuIVKtwVrHfzVJEDI7tkiVQqFZSK8yjZ7aOnCQTBCRz4XxaaK2SahZ7eJ8kXs5naUprwLiJcbA4DZM3UITfQKsCeGsVI4Nj0SsocVEoBTkLP8MgyYHeWlqKLOfnVzBaoXDY7RicERy9dH/S1LZK2BItVp4/PfLf//f/RkgF7Qd+P+9x0062/U2a2lJEj3FF3f9yIv9XKQBk54+M8tt17P9vJwLXw//f/54o3SXNqJZKiZEYAzFlUi6kXIhZ0vtyrT2gx6CMJPOVLD78Qkf4GgNO2PIYGaN6PLqU1517rY1UhLDk+gtaQ6L2PVmtEGIUTGfvqq8jdt/DOmqtDNNAq199+ldxFKrhB9ftLDLO0tbI/q9Xcc57jImvIkCtuwhRK3EnNCkIpKv/+jobY7pwpjGMI0OHiTgnKXDXAKFpmri9e+D+7p7d/sg4jkzzzDBN6MGjjXmFfVwRxnTxY69YUKpRUuD55Zn1y0fWx49sl09sly/svGXnHbpmIbnFQk6R9bwQFrmhcqqcTwuX84I2luNhkAewMqzr9hokcgUPtQovz4kf/vgT6MZ9vkVZGddNxuO049Pzhc+fvrAum3TAo9gKrdYMztJ6EqFSDa0qk7c4pyEFtnMCD5aRy+Mj1cGaN8zgmMcDfjegjCN7zd3dyMOdJS+Z55fPDKpyPNxQUhE9wrIS1kiNhdHP7MY9NEsJleW0cTmt1Fx5Pq2cQ+LxeaVm4Urc3B3R2nPJmUig5tzFnyIzEcW6HPTayQ7YOvHyGhTTNHI47BmdpZWE08hYdnDUnIEsNLemcOOeZU3E7Vk+p2rElni3e8v9mwfm/SxFsekR0EWEXqUUVIHHj5/4w7/8gefHJ1lp9OtbId2cHGqFK82ndnHTMFgmKztYa8CQ0SXivATC1Po1UlZ0LKaLVTUKjzcGdMMbLxQ+JI7amAGNQSlLRUadWkvXL6K1Th4sjS1XUcHXSiq5czFG5mmgNlnb5VzEikVDVRGbDYOjpMp5zSwhdzHg9bmlSFVEcOe18MVsjKbhjO8iryIPTi1kwNppoFqJqFI1mcwUbSjItE0VaRBElxC6xVCBoVNF5blRupBLGcNushz3Ew+38sB9ezsJyc5IBPc8T2xr5eU5ENcLSsHlvGCsNC4xJRQyJaE1Uqp4P9IAbSzaDTIBe17Zlsxo+orSS9ceaia2xvGw5//yf/+/Me0mLh8/8PHnD5SapcuvlXRaWJbGPAqboKQoqnQr6wBrDbu5gVFY3dHC3ouN1cmO3LuJhiLmxhYzl02AUzk3SjU461EIVrjkJqP7Usm5EFNiS4mX8yKIYS12R4XksrSUaOGqQUmkWGQqS2VbJXWzVLGIV3R/veS6khWLl31/lmd/q4WK6oe+JApqA95brFaEVdIA/eCwWougm0rcArZ6dl6im1POqFZQSsiSxlmaETG71QZnDFmJ/mA7n/nzH/7A7vaO+/ff4XZ78LvurLmKg0HV0i2Af9ka4D/pApB98y9+9Re/188URS8QrpMCqQpLaVBlfHaNOw0xkHLB9INNKUtV14GN/FtUo2kraErb3Y6tgTEoLaE/4gQwmJL7SElu/NrjQb3VnRege0qfAIBqLaDd6/6+VFlPWCtFRMoZa8VVUHuinnVCBky9wqutUemjPiMiwwZd9FO7o0BzjS0VHQToK0WwFwDXSYBzHuf7z+QMwzgwjlIADOPIMI1475n3e8ZpYrc7Mu92rzcIRqOMBGHIeFm6B3EHWIrqEalILoEqmcvTI3/6x/83T3/+V2yJTL4xec1hnjFNonxLyJQQ+8EfCYs4NkpqrGtkWyvjZNBKqnilNClWAdvESor9vStQIoQ1UUKB1KitYJ3CKUtcAufnM2GLGGWlU24V5yy7cWSaPa1FtDKUGsk5YpSMUFVJlE1S+myDtG7kBMPoGIYdgxmgCoFxfzjCZCA3VrVRasCPI845tiwH+3paWS4ro5+Y3ISumpfHEx9+fuLL5xfCmmjNsGwba6mcLgWn4eFhx/44UbGMi2MtCROUiACr+IBrv31UL5iv/99Zw34euT8e2Y2ekgJKG/H+UjsbXw5CbXsKH/7183hvyDVhWuXm7pZ3797h/SD3gZbCUpUMRTrVnBpfPn7my8fPlJh7MI1oQgYv5MEaC6bB5L2s3mIUfQKZ29lLdLVpEkKDwRsngJRcyRSslu9T4EGFFBsg4TzSLVpRxitozVGS7Me3LbOEKNMrY2QnrAS6pTWEtHHuyZKtSoqks5ZxHF79/9bItE4bQ1OG0pSM6ZUjlsYlitUy9mS53CqlCoCraQgFTlvhZU3Mk4RLce1yZUYoQkAaVim0crRWUMAaxcVUETW7c9DoU4QsqwltBOCFbpT+3lpnmEfhTwzDQOtFi1cZowzTOOGsYV0XlsuFUqSJSjFQa0OwRaIfoZXXiWctsIVCqRq0J0b48rTx/BSxSixqqQrLoqmKnT3DbsTuZszoaapxWiTr3g+ekDbmeYJSOL+8EDXsdqOIdmuV6alWDEooeRjdQ7c0gx8YhxnnvHS/SuBSIWbWTUSZW2iS9UDD2lGE1amyRTnst5wptZKbFA2tyYQDGbzSciOXiC2JnVHMx72IiM8XoioM1hC7A0FpKU5fYeytQknUkiglo2vBGyXwuQaqypRDA95K4JpzFq3FqqlKhaLFrpozRisGb/FWU3OUQkMLdTSnhPEy1jfOo1QWJ18FfQX8oLm8vPDjn//E5fTE2/o9V9pfp+z0QkBcQH/1AgAEGvHLSf81Pheu/3bt6i/WBCJyu7oG5GAQwZN69fu3pL5WDyiakpsVrcCIhUQ7K/5ToKmMV9fJgozhlBE7mIwVxfpkvMEbi+pjc+878KQ0htEzTgM5Z6kWO7b3OuVQg4yKmxYbmYxooVGorUoyVN+3iN5FOhXnxB2gFOQi1a/+pWOCnlXuXN+zDfjBS9ey33E4HKQy9g43OKZ5Yp6nLu6zcqEYizIWax3GeRnl6p4L0G+6VAVCY5SSFgNDbaK1kG5DCqNaEuvpifX5I/n8GavECWH0iM6OmgstFhwGrQZCka6+5ErOEhW6rZl1a2jTRJ1e+mh7y2xr7EVA51drGAZ5rcuWWU4XrFfs7vdMdoTSOJ8Wzi8XvJpwzmObxSvDNHoONzs0mcFrwnbh5fQkqW6DQRkZpXttGbQhRcGa+mnHbGdqyGxxwTlRG4OsUgqJcT8yz4awvlCbiOpqaXjtmexEXhMvpwufPj3x409PnE+BWjWlKtYkjoNpht3oOB5mhsGSi2aeB5aU8MGKk6AH9nWnqGhI+7h3N3tuDjv288RkHUY1uRdKI12hUoj9RyvXO9zKsrxg7fCqvlZUbvY3fPf9r7h/uAcqJVdqVrScaFkKBA2ELXB6fibFgFFK2Iz9e9KK7vmXAszPI6kIjjsn2QenkmjNMu927EfHYR6YB0srgdhk/K+AGiOxNOF4VLGptR62JbZfWSUOukK4WnMNKSlyD8lpzfQNmHye06VwWiVyWivwtQpau3TrcI0CKKJIIJabJEY4ZOk0s4j8UvtFTgGqC9v6Lp/GluBlK+y2jLWmW9qQjv/VD69QyCSxKXk25FRRHQ9urSIjHXYorVsAK6b26GHdui1PJsHzaBgHRS0bLSVm57k97Lm92XPY72g18/z8TAxb70olr6GhiP05mEtfxYYkiPKmKU0aq5gap8vG56eVdWnMHqJpeFuZJrH7uWnEzBNrSvz44WdmZ3g6P3F5vtBSYvAOiyKuhsNhT45RBMyvdmbJIqEKgEcpS1EGqy1GDbRmKcW8ItfXkDktiS1WtqxYgoCwas2sQeyfOhdibWwps8QIWjQLpYHWloYhRgk3MqZiFeyN4mbeMe9uSHFjDS8YDd4N+HGi1R7CpHp4m5JUWEUll0RYN1l1X8+9Jg4fmmgg/CRraHFoVbRzKHttsmQiMfiReXSCxa65F/tCqtVK4Z1DK0VOiZyTwKXcyHYRmmrbMo0NVRujl0I0t9bda5na9Ouhrztr469aAPz7eMFfxte2Vv9DFoAk46lXRbJGxts4LzGVdcSoyJotxtlO7HMkLTDnpjJNVbkYi0KbnvxVQdciVgeFjDSpEgCiO+rSakYtquFc5NfEWwspZtASabosC8bafgFcfxb6jW5eR3Jyw8qTQnWhXoVXylfOsdu+RKiVa2GYvPhr+5P+Cg0a54nD4cgwCc1tnGemncTTHg4HvB/kgWJEiSto4l5waHEeKHX9no08VJtYrFTrRZlRr8FJLStq6ZwCbXDWoU3DtABaMdiG15m1rIL9ZSK2wpqr5BBmyUgvVVGz2Lqs8TRXyQlqM8RcqOeIsWe0FnfBpYM9FIZxFDug8Yqb2x3zzqOqJpxX2qSx9UjLlfOy8fz8TFgj8/HA6CaarehcqDXLg95pplEeKFuUNcfgDMrKFW21paVCjplqDWWNLOos+hHr0MSeISGEyUpFK+kink+XHpTS2I07jg9HyJoPP33m+fHMy/PCumS2KDbPZZMD/dvbkbvbgdEPeDtSSyVsck3UIvCclKB2CJwX/RnOiVBqN40Mg2c/T4zeSchUSWL1bQ2sQtkB6wZyrWxBEthO54WWFd7P0mUXKVDn3cybN2+Y5xk3WmIWMRK1oErFomkl8/z4hQ8/f2C9XCRmtRkG5/HG46wl5Yi3BjdatLPEvJGzhHMZC+tWGMzGzXFi3s3Ms8PpRlrFqkSRh13OhawiKCPxxlZ4AjFnVC14Bd55atPkCiFXNA7xildSgVSkI9xC5XzJXNbGskrb4S04J8+dUgvGNYxp3T4rdj2lerSwEiRvaqofkoh4uNGL5S5yRtR9uUk3fwqZcfISOtR98q2H5RjTVbu1iYdd9YOdxqC0KMXXAFqTcsF5z+hknVCyrIic1XgnTQQ1UbPoc+bRcHPYcXe3x3pHCBuX8wuXywWNZIFsy4rRhpS313WstYJgF2FzZTAW5yYuW+L5vPF0uki+gNQILEoKAKU1bvCvOpW3337Dr//hH/At8+XLzzyfnhm05XCzw2tDCZHqLFHJhDe3jPVODrWW2VolJbkOrHG4YWT0M8Y4ShP3SwxwOkceX1Yum4B/zltgDZGUG00b3DC+PndjlYJAUMnyUFbK0JSIBWMUUaVqYCd5lucqhY+ycmCX13j1JiwC1fHpXaxtnUG1ghXEh0yO6leug2rXaGwv7pYiMcFayVQnhEAtjf28Yz/NKDLk3AW8phcQktxXcyESiLmSauXKS2iloaqipMx83PH73/2W9+/fy9nazz2UpjWJDZVitPYpwF+xAPj3B/u/7/JVJ079n/4sX9cC16xAbQzee5QasTriOKDLiskRUwolFlJRFFVpSJpVLYGWBQUqoR/CHVd0dWupMkpvV2tKxTQRd+gGWgtowxhHtOIjrjljjKBMUR0ighz+KCQsRUswS4yZbduwg2Xwg2gK4HXk7xEhn+vj/EJD9WhLrTXTPHG8vZNOf7fn9u6WcZq7hWkQFew44rz/+hprUS4Ln6B1gq6GrlxtWlwARV+zoD2CFM7klvp4uF+sWsuUwAi+stZIioGBwmhBl0BanlA1UlRjDYHmolD3Wg9i2jZSTFjjwElOgjJVphCuELbC50/PbMuG9x6axlrHNO478lijTeNwnHEOjG9YX9FautEUAi+PJ1LMzNPMfr+nZU2K5ZVutYaLvHdF8LNW93jRmjDNyPgzN4k7dVaIXQmWpxNuzpjBs64rMUvMrO2nRs0yvl7XIALQVNjtDtwebzk9Cho4bII/bk0AMqEosIY3d7e8e7fnZidTh5oVIQSWRTIIwpaIa+0Z6+CHbr0yit04spv7YdAyKi80rMBVEHuV0QYzeowdUMaSQiLWyJYbIVUG42mlElti3g1YI2PieZwknCeL/zyHgtYClmq5cr5c+PDTTzw/PdKaIGxb4RVEdTweO8glUlWhdB3COBqUylQFqcDzObObT9weJgZbqapKxGsRsZxRqq8uwBiP1ZWWErVlchUniW1OfMxNUWJl2SK1SpRyzI0tBNYg1sXzEnl5iayrYt2UKJ9H2FuLHwaMk/WgdQrnFTpDrpGaNK1ZEVoiResWE0ni5X8xUJUVXkX0SEZLCl3I8twpsjmixj4NVGDRlFpeATrOmm7By5SqSSUT1iJUTnulNMqovrQqKxwt66p59FAT1mhudjP7cWJ0jhIWTudEKlkyLnJmsI5lWViXi9wv0nBLB26ccCM6kjtXOC+B0znwfF65bIla5aBzVjHNjsNxkORLq0hUdvPE7/7L33L3+9+x/ss/EWNknAasMnz+8oXb3Z7D4SCKehrn81mE0UrLGB3RXOUojYI1I0YPaDWQY+XlIlyMSyo8XxZezoFLLFyWyPMls6yN2GB3VNwME7rBGgIvW5RntRLRoEQ/a6wbUXhyEKZ+CqBC4ThvuL7KHcY9lsYaNkoMHXtcZHVkLSkv0kQaJ+N5pXptKL77brh7nexqJc/pq/Yuh0SzAm3TWuLsrbXibhPpPrVTQv3oCetGSBk3DpKeq/QrGhoU3nmaU7x985bf//73HHY7YpWVn1bCIKiyTxTxu/46DfhfffynCoD/iAEg//s6EfilBfC6DhDFv6K87iaU1mjnUXqiKNmblhRpWRgBLlYJFmkanSW/vahKVQXrLKMfwENOkkpWaqGlilUC6JFuS4RB4zBQanvl/1sN4zSRTGIL0gEbJ1VjyQnrLdM8y25pXfpkAfzoBc0LmK5GjymRS8E4yzzPjOMoqtfOD3e7A9YPWOe5ub3lzZs34lqwjt1+J+JBP6CtpSH6A61NH+W1bsnTaCWiHKAztisg3X7t48imVacRyutOlR2mQmOURTfXRVUIo14lJqdRWyKtJ0q4oMpGDhuXWClZkYYJdQBvrIzJtGYeZ7Z1peRCDJHUb0RnLLEVLktlXVb2+8zxcGCeZ/bznsEP4h1vRZLPyoqqMBiHsTC5gdF6SuqQna1weT4Rl0SJif04YgZLTbDVQEpFigireiCNiNoknlLEorvdxOHmjtQqeTlRU2aLkViiPKRHhzNIFa6F7Oeto8aMUgajLKfnhcfPL4Q1SyqfclhbaE3EjcYp3jzc8u7NEacSj+uz2EPb13tEN/GVa6dRxoF1XUwqaNnBQI0XnBUqX0wbyovvXSBYXnQdaNYUOV8uLGugNdnF7se9ZO6qxm43o0wjhcjTpy98/GGm2oq2DWMVx+MBp4RkuZ0XPvzwM4+fn6AqpqHfj8pwPO74/d/8RrLJXx55WU54a5h2N+yOM4/PJ5bTSTqjAhWFcQ5tLbQou1St8MbhtKGkIgFWSPBWjAJGiqWgjMFkUEaRm/y55/NKiAllBmrTnC+By5p6pLJMXtZNsa70bg201QyTYxg0cVuoOeI0OCUTnZQyuUGomo3Mad14uWTWAFVL4V8wkGUAXJKsJwwyYk5VfqtiqcqRW+0oZA3Ndo1T6QeDCI9jioSUCDETg0wpaquYc8U6GEeYZ8VuHpgGwziIX1xVx+Qd3jpSjIR1pRQROvpxwChNTJVQEjkKjS7nIr5+5FBIuXR3iKxPtlj58ukzITVCqeTObvPecHuz4zga/Chwsdoa027im2++4e7mlpd//QP//P/5b9QU8M6ynVe8sRyPR7wSIJpVEMLWv4fG6eWF0ppQ7uyEUiPaCschpoXPzyf+9U+PvFwK2l/hb5qqDVuCLcr6pWg4b42jEdjTy2XhsjYOB8c4jjLut0aKnyJdeqmVLnVhiXBZEoMX59U8TkL5yxX32hCtWOeFx3A5i2g2JkJIjFfhtZb1BcrQmuqpsD38rlVc56rEEF8LgqED3XStTONEMhDXhZSS6FjIMv3xE6N1VC3XX0I0O4PRwqAwlnEYMNpyOZ8ZbwfRrNRM0z1Yrp+76vX8/SsWAJXSrXNS7bReYbT+a6XJPvxqU7uO0r5WRp0FqKwIZ1A0PaG9RpmRvfb48YjyM1UNmHEhTBeqeSadNuxsKaGQiTgnaM7UokAnEPiGsx5jHGEDZcGPg/DytRbxYciEHBj8hJs9yhtCzv2hJZ2RCEgElrJzB0rLGGu/4jqnEe/H/jPLqM8OnmkamQ87dvuZYRgx3uHGI8O0Z5xmrBPxkuwDZf5biwQSVSW+5NoUrRkRguj2C9X11SLUE55ePZ6SP2DMNbhIXm/deteF3MgS1qEkRpWGbQVTIyaeOX/8kZ//5X+wPH5m8pI3YJlEgbtmVs7UYWA/TyhlOK8rKUbiupHXjFWKvRcqYwtZuj6l2U0jx8OO+9tbjocjtMrz0yMprsSl4bxi1E6Em6Hx/OEz8Rx4/vzC+fGCzhCzJLkZ47C5spsdVzuBBD9pvNegMikFqS8LjH5kPhywg6OEjVybHOpasZsnfNWEEHEVVJAd3OQnlrRh0Vg3oIyiBcX5eeH8HCnRYNpASxvhkolniRT95s2Rt7cTTlViWGg1UVsBZTEWaooMg+JOjSwp4waHcY5tEyXx4Cs1LdQcmPwk4+kuxnPadX6FoaFJuaJSRJWAU4ndbmJ+cwtZcbksjF6saqVGWkn84Z/+B59+/iPzYebb777h4c0dsV7IJfPp00f+8b//I3/+w0+UqPpOXsKg5tGz2ztiPFHVxrw32GnPMI5gNJd1gRaJy4nnZ7i9Ucz7A2hHLkgS5TDQqAJQao1hmME0YhAC35Yrm1JsWexmqWR2SvQzp8vGl6eNVBUpb6QiLqGQKilv5NJYk+GyRLFBWQhVngHWV26OA3pv+fThC+XSGLXlHArnKNaxpRaWUnlZE0uSmrG1vq1QEvJ1jVp9fUpq8XlfLhtD9UzaI9Cy2ml7fWxsBoxzMjGokcsW2GIW7kMDFaUgGaxMM8fBc3dz4Lhz3BwnjocRQ2O9nKk5s4lnF5oiJfGopyJ7f4pE1taqsWYiRgnRMUaCZcZxxzTtWdfA09OZ59PGy1L7vhwGr3n7sOf+uMfrhiZS2kYsAruZvKdtkf/5v/93np8/sr58wLaIWjOTsTwcH9AYnp9e2LZFnCreklKk5ohG1jHCi0hsYSM3Q8bysmR+/rTwdE6kpqBoslIyofTiPNlyIiKmr2m/o2JYYyDmwjQJz2XbFsZhIKcePLYFmTRqQy6ZlBr7g4gTx2lH2DYumzQAWhncOBJLRnvNVkHHjB/mjnhG8hS05LIYZ1FaEWNi3QKtyYo1LklyYJRYygc/E8OCNYaaEiWtlGB4Pm2oVhkHTy1JoHab2GqnYeDt/S3Oz7ycNx6fT2QdOc6eNSciAht6fnzkmxhxNZOQLBNj+0RY7B00tGDi/5oFwHXkf5UCXNWSX5k//eCnH0TXzhTEBvQqFOyq+F4sNAXaeZy2GCMWLed3xPXE5eUZ4zxpONNS5HR+IYZVOlulsFhyn9/NxwmFgWaYnBfPb5BxdkP299UqvHWYcaChKC0w+hnV8ZYO8ZpP88w8SdzqOA9oIygvpTXDOIm/m4YfJ1HzG4XzDjcKetg6GbXHpHDDTjLFm1jxTE8gBMTLrWV3pfrERF4TxS/TnSpSCyjEY0r9uoZ5fV+ux39HEyutOhde0LHXECCLRLGSEp9//oGf/uc/8vzpo+w0S6HGDC1RYhFCHYoO/5R1i5YQIGss3jYZx7eCVTB6+XXrR/b7meN+x93dDYf9nsv5hRjOXE7PsuNsnrVZYhDR5XoGeEKbmeN0wFRpuZw2TE4eKltYGGePHzzGNiqRNSxo03BebFUV4YunnCD1a9KY/p5YCepIG9CdGBWJD26BQQk+NW2RuGXSubKcEyVUqJqwBdbLSg6J3QD748DN3kNayVtjOT+zXjbQ8n5vWyCHxOA8zil8shg/oIzGIgJT7wy5VKpxwoJXmmosVssqiaZIIeOcZxx8z//uojmj5JDNdBxrZduEhua9ZTtdOD89gm28fPrCbj8LM5zGsiz88ONPXC4bVCtiv1okOU8Xqops6cT9wz3OG9YQUVqcMSmDVgmA441inGR0mWsjduGZVRqMR3sZhRclS3rVGnFLbLmQreyZU83iDHneiGXhfF55uUTWLZFkiQD9868hEULhsmmWJaOsuEqGEW5uR96/u+Xbd7fkZWV9fOZ0Rd6WJnki1RBK42XJrN373/qOt5RCU+U1v0NZusBXdtRrybi2Ykth08KfUFoYAFqJxa1YWFMgbBsxyiFyBT0NAxz2O94edhKRPMB+5znuB0YH82gZ3f+PtT/rkiTLrjSx744iooMNbu4eERmRQwGoAgrdTXI1+U6+kWv1L+YDX/gH2OyuLnRVF4BEThE+2KSDiNyZD+eqmUcg0cisRV3Lwz1sVBUVkXvuOXt/25PDSs2ZFFLX9xhUV5OXMKOpWGNBS0S4YnixfzY05zVgjCMrx4fPB56fTixrZY6NamVseXU98dXdDd999YbRKebDI1TzomswRpNC4P7DR9EtxJn9JLY6YxzaeEyD+XjifDrTKGijWNeVEFacU4zTiK/y/lsNZvIcl8zpeObxEMkYpt0OlWSUVFsRKNqaOC2is6kKrLPEXIkxv+Q+gCLHTKoKmZqqvgGt/b0Udf84wWYjkczGWvw4EkIkJ8E6x6Y4Hs6S60DDKqGdeqvxWlJk0ZpmNKU1coyEFMitUKuiFYlRbvoyCpD7NE3OiWnQlLByiAGqWCWtasRaUK3gnRZ9XI0sx2eyExTzoC0b75kmz17B07wwn458+P4PvP/FzzG7DWoYKDFTchT3l9LkgOgl3J+2tP9XigAv8/8vLIBf/PciPJGvabwuUYYLz1Ep07/cClyiFdyw6epMR0l7ttsd4zBSrhZqikzHZ87zkZojMQV8zpKGp6QLsCyBFBvWDjgUrCsxJ4bthmnYCIwDJ8py50FpdrtdV5I2KhLPu9lMvQAQ253Spuv9ZfFWxgqswwrMSAJfNMpqQRRrQBncaNDaSSJereJfN305be2FLSBjEsUFY3gJdVDqMka5HFfd34sv34fLH14KLlTPeG+X496LgS+cCLUUzuczjw8P4k9tIlDzdqAVCzX9KArTGUMOkZoi5/MJpcTSE0MkRYkxnUZpWbtpy+BHXF/QSs6kFEVsU7JYBJOSGb7VOC8piiFGBu/w3lJzlbamrkQl6JxmYL8bwRSqyl20JboCbRRmEHsYWlFUofX5MgqqaWgLMUWwhnGQbkdKidwaMXSBToUUCuspcXpcOR8DYSnkKOLRVjOTBzdN7K/2DM4R1kVIakGANLlmSlWS9NfUS+EkaGqxjhoN2smFqlSjGjkHrJHFjtbDnfq1NE0T26u97L5PvaCtAgvRyjB6j2qVuKwYq7Cjp9bG+TSTcuTwdOgJmg3rBT2bUsFq/xJPqpTCOov3XsiYVoS3+92E95qQE+PoQRVKWkkhMc/Scp2XhaO3JCeOhtGqXgRIJG7CorBElTmXwlolbe+0ZA7nc2fhe9acWc6ZUBvrCkUVlK4oK+3deS0sa2XNlWGQS8I4+Nk3A7/47g3v7vbc7CfcfkM4rTw+ztRTFJKi84SqOC+J81myIGjgtFAra7+GpIkpVEyjQPfOUs0SuhRTJSs5F6yme8oRT3eDnCUR0WgYJ0RAqTT7qz1vbq4ZHXhTRaVuIJfInKJgo8NCWoWsWbpDQtxX5qWVrOTpCMGuQSoyA66AmzYsqeK1J66Vj/cHwir48hXZjP3imzf8N3/zb3n/5gqnCsvzAzMy1qKJ0NZaTauZ4/OCUgbnFNU2as3UHsd8mhdOhxMpRPzgOMWF0K2IY2dWlFK6+yWjte1OlUzqXn7jnVzzypLPM6d5IbZGkCkMTUHOFZ2rdICqoqKhCGKY2tA6oZEcFN25J0ZVGa1sR64nIVBCxVrD6VyY574JUAqqQSPERmMVxkl6pffyvi2rXNco5H7X7eG1IdjmnhbbLiOgzpAwWjqNJTf8trHdTgzeQkugMtvJMoxCVQyp8PT0QGtHtB2pWLE4G6EjatWYz0cO959Zj8/oKKmTxvuXWOLaBeCqh279KY//KhLgZWG5yGaU6ovMT5wCvCw3fTfbfYqqjxEua1c3xIDKNG1RdsAbJ2phN8CNyKev1jNhXck5sC4zMa3SFm+wLquovpssfLITHVjCwmazZ399gzWOUhoKxzhucOPAZrPposFMqkKKslaLAhRFa1q4oH2xUcbK2OPCbr28Zi1Mdy6LOn1X3nfp1kofUehk0rUQOmATUpjSXPIbhCJoXo8TF9zwpQsjI40LXEj1zovWrwVYJfXf33nRSsui0nfItVu7NtMG5TwEg7Eej6IGyE5+v9adkHVeSWvoLUYtvAIjs27nHNY4GooQRcU6jB4/DsQSWJ5PxFV27+P0Hk3rbAjxeNeLCb6rXed5JobEOI5EVTmHM+PkufvmDkaHUhHdJMPAKIuqmVYyuRW0EUeJHT1VS0pWERklaMXu+orrN7c453j8fM/8nGUnXTMlRUyRGXUtmZxW1nnmfEq0ojHas99u2O3Uy+9pVZjzMa9Ya5iGLcfTTIqVwTpK0xKGgkJpS9ONmKNQIbVoOERxXqVIKqIArqWhlcV7ed+NMXjnWdaFuAZiTnLcrYzUsJoSk+RVNHoyXkP89p4Yo4CxekGolcPbAVUTMQdaB7ZMm5H91YbdfosbLNNu5PruhuV8gtMRtMIFhVb1RdB4nlfmdcFoWBQYIzsdbzTWaqZpgKbJuXBaVk7LgjIyVjunxuNRhK7WBZlrB8iIl7tWcVHoKjbk0jTaVAYjY77a4LvvRv6P/+3P+KtfveWbuy1fvbmCVHn88NDzMgQZbvGUOXFeEiHKJWyUQFysVejWZPxvoNNtMUqEm30KQKsQUnrhoTgLjYzpBTQFthNcXXu22y3WgNNGNhPDiDWgSRjXbYRkcqrSxmhKcMKxi/O6ir/W7vCptVPrZCSSSiNXJXNzJcLjkDRLMhzWKC6cBOPo0W7gxhm+/eYtv/rF1/zyu5+xnp75/PEjZT3hrRE8cVyZhhFvOxytFJTSeGt6W9z1iGHZcIVU+o5XcT6vTJNnc2UYBtk9l5J66A+ENaL0wNX+itQ8H5/OrCmK/qYWcg6k3C4ynu4KV+SiGM0gBU+mF6yt3+dVxxHXl/ulUjBtPFtl2G5GPCI4ra1gtGNdFx4eVzRgLYyjw+nL5s2gjaYoCKnIeLEUYg4i7OwFmdZGop61uMustgInWoOo81tDTwbjGm6Cu7sbJu/RtVJSwhvHZjP2TAVFLpEcCzFFVMoUDPO84tkw+R3eyfNeDs+cHz5T5q/ZDxZvB0Kc+fz9PadlZrffs7+6FqfKn/D4s+OAv9xxvi5InRLYW/wXZ8DL31VU7O2L71dKLAvtMkxQ4mOvuica6Ybxls2VeCdbK4w5it2hVdawEMMKqpFyoqTC6MU3frkJjuMk/t4ioAdrBpwdaBjxY7eLbU/CeiwJyKCkGq5Vc7n02+V5a8slU0tp2/GtuhcA5sXqh6q0nLtf+LI4vzolLqK/2l6VoQLQUb0YUC/H8MeL/+vfF873j8cBndRY+6KvrNzRlIJ6yRfQLwvKbrtjRZNTwynHMs+QWlcRG1JKxLAyzyd0g3EaZM6dJQuh5ARFtAYpF9Zc0X6LHTzaWZZ14Xx4hlrYbAac8aQUyCkCQnF8tS2J2DDHxJoCbjOQVaH4xrvv3vH+L3/B6XxgMA2rMnU9k+YTtYvxUhXr32AVRnkR6smdFIzGjY793Q2br76CUhiW0J1xhZJPbIctaV5Yl5X1NJPWiGoNbw25Cid88CLIKw1KSdJeplBSwTkvMaxOrGfaOHJRhB6gIrzwIou8VlCF8nUZ94jlVCy1KVWs8WJdrXA6nUhV4pfXdSVX6VZN40C1ShDEXYbcSmM+zRK4op0I6YqiVNGgaOXISYkos7TOEhdFmLMWPw4Mm0FIf9uBceuozbImgZI4I3+s1bhmcFaU9WuInGKAWpmGgcFJjvwUJbcilcJ5XVhCxHrN4B3aTQyb1NvzijUvhCxt+TXRw3Ma2l4ssBo7eJyuTLriB8Pf/vuv+Ou//IabPewmxWgbj0/PhPUsx2AwqGxIEZZUiBWsdRJ802OrhbLdoUwaekyHjMwUWAWmFyMJeX5ayeeUlS6Cm8BrxdVm4nq/Y78dXzoDxhhaS+QUGDYW55QsIFW2uTLe06LoruKGoEiXR2JyRf/Tcu50Qyi47jkXUVuphe+//8gSIqdFrH03tzB4j7/e829/9Qt2Q2OaPLkE1nAm55VWIymcKX2RG5xBt4Lq41Tdiw6jvGhRSmOeI+fDSs4FqxXrGrHGsdvt2U4OpTI5BxTiiFBtRFVFapZp3PD15prtTeLxMPN4PPF0nF8cFanJvbkqQGmMG6hNCcQoV1q5dDdFd6G0xncHVs2FBvhJ+CitRda04HVDqR3WipYrrNLt8V5GD840CiKmpkA1SiKfkX/nWPHaMW7Euy9rAXIO1SLahQsZslxWusx3373H2srkPSlENJX99Uirsu7QFCEmvFbYwXQbolBzUZIdYZOE6dWc+PT73/Kf/kdPXs68/eY91nsejs/8+ne/Y40r3/7i5/z1X/8tb9/f/Unr+n9FGNCPF6DXXX/7o5+7HIr2xedfiwktHl0U0OE2SlGy2LoakhmujaaVRENgC9poxmFiqOLhrn1nY63MToUVIDsGbYwkSxWF0YPkD5QL6MEQEfGfsZeORId4lCIze22kC9Dn8/T5jtjtZDRwaXJIxGbp+ocmz6WlrvhWLzt8iQPW/Udq6O1XWej1S2CKLIw/DmG6HLtLofHTz70ozy83FKSNJhkGrUMsJLRiu9lwdJ7z4czp/okrZ1BJyG0lZk6nI0oLnrXkRI4ra5iZhlEKJqvZ7aau8RA7jimghw2lZT7df+Dp4YE4z+y2I86/gZaJcRWOv+3EwCQKfmMqFHlddnAUJzPV/bs3fP03v+L667ds054SZtJ8JJLQxUlRWAXL1FSjtEJIq4i7tMxImzOvx+h8pjXFMAyYa8vp8ZnjEtC1EU4L6+lMWKSSly6DvOU5JmJrr10VKwWXpDk25tOC0U7EqB7WkEkpSStcdWGmEpGcdDFrJ6ZpjDXkWrqVTMJkqpLPK23E653iS56EafJ6Sin4nmyXk9iAWmuEsGCMEUqkG8hZUVoUgVtByHFJujlKWXkPqGSUaHKmETuIAvkcFiGqeYH6TNPAzc0VqWrOPxxeujixNOJaoMhCFS2oucDT2llUfY5aC7oFTqlRqmbcXtMaHE8rKQdKrRjtUeQepGNQRkaGrUoHS7XKdgN/+ZdX/Hd/+x3ffXVFSwfKeuAPjx+5/3wgrJHtdssUHfdPmcP5xGGuvSPgqVSZxVax1F4eusIwiCPDKBisYzSWAYNTIIntEaOli+O0JB3uRs9u4/FaUdpMWAPjNGC0opS5v9dQm6U1K+93LsJ8yIWkFMkUSoqUlOSe0neTznmMkeTHVA2xNrn/RE0MiTkk5rDyj7+NMjf3MO3g9u0bNrstv/jFz/l//A//d372i3cc/+kfuP/4A/PhE7WJaNB7S1EO2+/ScQ2AZpwmnBXRalgltjesicPhzOm4YpTGO0ergZvbPTnBua20FqTTJ1dlv+dMWDuSlWh1bq+37K937A4jw+cHuD9yXuU+PA4w+Q1r0YRUmZcoYwQU1vWRJlC1MFqmaej8ldrvj0DNrOuMbRk1WnoUolw/RjHPEsplOjvGJMhOOjbWeYZRo4FlWTDWgREdga3tRYuQsyRYqlG0UYOzYJJkMZhKyXOPF7bMHerkrOtjA9htt5znFa3OvfBVqCI6OT94sjYcTgdqrUzO4pxlvv/EP/zPM3//v0ixWo1oEDCazzUytkg6fstf/c2/vq7/GRqAvgh+sdh8+XiZW/Plx1Xv9CvETPO68EOnbSGRkJcFVKkBrMzQajUy66rSZqravSxiFY22wubW3eYXcmbNGd0T02iKVBqtKYwbUdqSMoRcsEbGALpdAk96z09VFJLcdcnprrXRK4bXI6B4KYhkRvfjhL5/7sOUExVkQTaovvP/oiAwl12AfL0CWqso9ZomeCmsLu3+f8Zk6P0JraS6zA3xZUstK7uOVjBKiZVxiZxOM/NxwQ2ejRfxWdaFlCIpR9Rmi1KvGOdWZNGyXaHvem/UWY1yjuI8KWceHx/59PFZ7H7e0Wpls9uz3UxSUGRBQseYWNeVlDLbcUdrlWHy+KsdbTK8++XPeP+X32Inx2ivyM/PnO8LJQXIkVoKLdE58cgCjcGYBtagvSFrRcyB4/HIEiLTtGW3u6bazMOHe86HM2ldUT3m1zaEwmcaVXcOgVHkUsgloYzGINjRmjMGS0mNqiUcSvcisBQpDmoDuhVVabkJrSHIjd45WmoSD9sa+oK7NY5c2msyZeNlHKCqVHUlRbAOo0Ey7+XkLLXrcPolZ/uNK6YsynmEKImRHPPjOaBNY7regfe43RbnNdN+QHmDwTN48TKr1eKGCe+CiL+UehGfWOO7HbV32VIllwz9JtWsxg0DWMP5GGidFVEaiCbWvBQx4zj249Xpek0Ep7Ufw6trx1/9xVt++fNbvrrdkOfM06cTp9MzLSWMFhhWKpnTsvA8N+YIzdDhIHK81BfH1nWAluziROfjnGM7bdhPI1fTgGqZUha8FzdSywFKYuMtu03nHNSEpeCGzGDFNpZTBwdpEQS3KjN1gXf1bketlKQoRQvFQ/WUOG1RypARi1hCsQZYwsxpCRzPkSXAuoIb4N07zdXtnvfv77h7+4a//uu/4ue//Jb16Qd+89t/ZD480WrCGdV5GAbTLCVFUhLtidaGWryw5atijZnjaSHGyjI35kUY9taJSv48x36PyWiVGQcZUdVWe6elYJCiJ+SM04Vxv+Wt37Hde6bdgB4+c1wbze7IeoC1EnMghcIcksQkTwZrWiezCt49F9H8QOn0VTlXvJPAKm81cV1IWjY4+52h5IxS9K6LWFlzraRcCTlRg2zacs4oIyyHXPILPEj1sWvOhRBWifB1XRSrMru9I8QzpTac3zCN0uH2TgpLYxSjF5T3uoaunwBrN9SmMVZRjSGtC4rG7fU1b26vsEYTUyDlgNKN7WZis91SNZwOH/nH//iZH379n/ir/+GPLuU/evzJBYBWhkvz+mVJ+2LHeXl8uSO95Jo3RVexv5YHrzoCuRmm1H+WqnIDtyOqyY291SIBF9LQp1bJaDe9LZ9r6nYg33dbqiM1ZUGOq/hkxc5hcS1TspzQTTUamdoSrUW0KViHtBv7gqxo3Yf/+kchc+OLFQRtJGxCiyDokshkehSw1prWCikLs/qymMsx0z0h8fX4XOb6oF9GAPIzXsWVXx7vl0KgyVqlUS+/oyq54WjVULqiawEy6/nMw6fP5JAZB0FixrWQTWYzDexvbjkfnlnCSs0JpRS7njlvenaBtwO6IXhXJdGUaw5YPzBtBjZbSytZ2rBWkVrCa0EhCybTsu271HVdaT3EaXQbbu6uaTvP1dd3TO/uoK6oWrFXG3b1hrauHJ6fqaXirZc5eomSqGg8wzTgNwMMntQKT/NMJqCaYty9gf0tuhyoaybHgouVlossrg1huzuNNyM5NdY1kVKltdi5EtIUagjDfxxGLjPbijATatU8r8cXoiStod2lFa+6q0Izr6GfoxrvRqyTlqKIqKKIpYah/3+m1tx3MoZ1nTvLIlFqFNukFQJlaYU4z9CplqnKe6V76liqjWOYeTjKwrQPmaoN2g3oAfxmA1paraOx5BAl0AfLJha22xmvEyVL5wJANwtN0LTaiJDQOCH/VdUYx4lps4FyZJ4DyzyLcK5pnLHUkokx4Y0RS2UVyxwKRl9pA2x2lv/+v/8Zf/u3P+fd3YbrrSM0x0MSLcIwDBzOkcPpxKf7heNJ5vqi04FSV5puKNPkltOT86wRaEsIq1yTF/GsbvjBsr/acLUd2E+Oq/3EOBhKXInLUYRnoyWnGduVgzmJKNM5I9fbw6OIbGnULBwBjekQJGilsoYItclMuncB1pbItZGAhGxk1rUyz5nzUonCXWIcYbeHb79+jx8Nk1d8/e6Kt7cTpBPZNh4+f8/T509YBTHOtBjxWjQ1coqK5kCjabkS60oIhefjyqf7Z0pA4D3PoFQm5YVptGiTMcYwDvYFRGSN6Rs4Q8mV0+mJohXKGWClZOFw3OxG/PSO/d0VHx/OfP954f60oLDsr7asD2dKlnPP2AJV4weDtQ6lG+uyoDWS3teFtdDYDBt0lYMzz2dqCwz+itubW5xdBEG8xJcuiOs5MMJuiNAKugkYK0QJP3NWzhNFFwo2YZXEJhHw4+QYnWe3N+xvtxhTqHWhkRgnzX7nKEm0Q6fTUazgLRNToFTLMDqqMYTzM4ejREZbYDmdOVLZjQ6jKrfXe5SppFoIhwdJx9UK5WxH0//rjz9DBKhfF7+fzKO/XIwu1Ckh2fWK92VBlBtrfakZRDsgITxOBFW1gbJc6gpjR0n7aj3pD402Gm8sXJL3LgxQ6G+8zNhrhVY6Ua8qQQLrhrMTIqqVA6a1ICRBi+JYi8in0Vv6rWG7h7+U2hOnTJ8/GTSGVJpgVrXGKE1BCezB9OMiXFCssz9a/Pv0H1UFu3sR2HzZ/n85nr0I+OnjUohdCg2DtDG1tsSc5bVoRakZowpWNUzJzM9PPN/fM5/OTH3WZq2mlkCpDesGhs2WfD73Ck6zROGKb8eJcdhgjCXHRK5J7pPaMhiD9Z7Nu/dMg2c+HRi9p9REKYaiNVaLoyIXobspLaRa1URPkFXh+Xzi7dffcfP+DYWE2Uy0EGjrmXmeOR5P1KJBObFLAa0YalaoHkHrlCWGQmmZPEdqblxv9rSQuP+f/gOHpwPnpxOEIjz1KFoI6w2hZMEKF0MOQa6CHtesujhK7Kji0Y9hYRgnAcDkjNK2B18lAUn13W1u4tcexxFWOJ2XHnqkZSasxJXSSiMkaYnbLk/33uGcI4T60jGY1zNllYLYeCPgmBBQylCUwtpBCkHAeSdz3FQ4nM4cl8jzvDBHOT8PS5asO+cwg2GJmc3G8eb9Hd55TsejgFoqjCHzq195cqgcn448fn5kXnoLH4NWAsVqWlqbxhm0s7x58walFMf7Jwat0d5TdCWkRs2ZzWAF3tMSunUYT9fhxgx3d4a/+uv3/Pt/93Pe3I5oHXi8vyceDzhtqLmyrpnzvHA4RmIGO8D1ADrBYYU1iIK+SKid7CibpiaoSmHMSCnrS1GT0srjITL5wn68wmvF3dXIm9trjCrU/AZnG5tJomRVy5QaSGmVm3tceXzMrHng/BR5ej6SE4yDkE6pQo6jgnaOHDK5yMYrlSp2Z6WpzkuI0RpZl0KM/e6s5Zq/3sP/9f/2f2acFMfDZ+5uJtr5ieOHf+L01RVpORGXmZySdFZqYxg8o7WkdUUbJ6YmRNMUc+V8PvJ8OHOcIcSGUY6UEsezbOS0zcRUsabS2srt9cS432CcxxqwVEJMEozUnUAoGRe2XFFe7qW7aWK7u6M2xfcfH3EK9Oj5/HwSXZOR2ORSRbhnjLTgGzKmGQbDbhrZ7ybGwVFKZp3PpJiZBo9qRQS9OoorrCqa1synWQ5gldAq0xNba7NCxrTSRWo9A8ZYyziMjG5CN02YF0oMKDLUTC6BN1+/5/rGM20bfqjiWnAyLtlNEyVnzodn3DiwrAXvPdNWkc5F7iVZcV4yS8h4Z1FWEZaVlcrO7lGqQAxo16hhpbXMMHiB04UFu5n+pFX9z3MBvHQU248W/x9rAX68MMHr7rSheifg0gHo4rbO31c9nrZq4fKrKsEmWimxn3S1dOvzbYxFtfxFF6K9FA7yiy+7dddbfZI4qJXGcFlMheMtDQkHKstzVfKGK6v72teV/UpRtSzb9GQ9BXjTOwa9qNG1Ccyn78RVUzT148wE28VTl9fzMmZpr5HKr4FLXz5elf9ftnlblRa0aiJOkdckLWNtFJSKrRldM/PTEx9/93vW4wmLoeTCWjMaz9XVDa0llrPMpdAW5Q0lZWIIOKsYvALthJFgqtxJtcF5z2a7xTiJe91uPHHdSaZ9jAJdAmJOtNbwfkTbSmNls9tyPp7IrXK92fDum/fcvL/DjJ41RWxNDEpLSz014pI5H06UOeCUZrPbsJ0m2QEUmJ8XlFUUCkuOeGdJa+bhh88oHphPgZIqpii2fkLNK4oiKFVEZ5Ji4RxWWdCVEcFfJ02+vD9ocpU2r6dJ1n2uoDNGiR1qHEbmKPQ+txFFeC6lY+N1BzoJ+Me54SWy2TQNVc76GMVCaa2jeWHAH05njBdBke67N+00Xo9STGgtjoFxYjADS0gcjjOH45klJFL3xed++YaYmNeVlAuT8qAbqYpveRwG3m62bK7foKaPZDTeLCzPZ05anCrjJOFNqskOUvgAhdxqB6gsfEpipTJKMRhFKw1rDaN35KEQUuaUEzEUtntNU5U1imDru68H/uav/5Jf/uV73rxx7HYepxVRVYlmNR6jB5b1xGEOhFKxA+xGy+AGdsrzVinun554fq4sTYaTG6uw1qOa6b59sezSEjGWTpuEp0Nh5xK3QyOdB/KosaNl9OAHzTgoNptrGpFSB2rdEPLC6QzKXbPfb/nht58Zh8D5vJBTI6QVqgiNdcdl28FSk3AXagNtHFUpUpE0vFyqaKOUuCamSfGzrye++uqGb95f41zFc4L1xNPzDOsTf28bnz9/4vj8zDrPYC03V1dshgGVC8UN5BDJUSy2rcL5fObp+czp3DDeY5pCVS1ZIzbSKqSqMcWgtGJdK0cTMVaAZ9VK4l2MgdpEv6WKMDLWeGbKAlBT1uC1R7nG1TRwd7On6JVzqFjduk6o9s1Rt0Aawd5ekvZGbylFOmP//m/+hnH0/N1//A/cf5RIdmsVzkm4UCFI2qWfiPuFnMXS6b3FGl4WfK01KUbZ7ClewuS0skzTRhj+y4rRAh+aRstXX93w1VdvGafGEj8SQ2Kwlt1+xChLiIsUJiWxHCJryJzXhrJ7pr3nvDQen8+czoGqDM2a7oSBkjLrPDNYONXAMDiMN4xaE2Mgh0A1CqL519dz/kwR4MXGJwtP//gXs+6ftqUv+9tLK1uIdD9ewLj8f1cQKKWk9aSMMINa38GXnsrXLptRg1ZQkThO1c/YC4r4oqaHCyXvImCUFdt1ZG7JWT7aZBYkXQARd8lCLDPZVhq1pa7Y7e1ELfoCKTS6h1/JjqXSXrj+L8en/30h+7WuIbhYKF8tllL5//SbL4df5lZf/sQvj2NnBRjRDFirBJOpxLLnW8PWxtPxwNOHD8K8HyfSsoqTYRiw44YYVjKLtIyRNlvTYiM8zQGjPX6MbLT4sbSRaGbrrbwHtaCsYb/f4t9cYYDlfOLp6ZE1LIQgQTmjnwgxs86r5CFMG04p0LSEJk3TxDiMbIYRqMTnI5/+6Xs+/cM/8fHXv2V+PNJSYfSe29s3XN/cMA4SzFFywHqN8YaiCuPeYmpF1YzRjo3qu9NSSc0Sc8PqoYfdyLkgcz858HLI+znSXSvaGPm6NQsYpEpkdspZLFutvrDAiQGlLd6PXYm8kKKMQZoSRLQUa5YiFbG817WI/W6YGKZBumatYqzMEiUzQ0SFsiNSIlpCbHPWWUIuhPnEaV77DT3LQE1X4iWhsMI8R47HmeW8st04XD+PagVtDW6343qvqc6itOP7+R+JpRCi6AGm0TG5CYMhhcw8L9Ca3KDHiVQ9TcuiW3t3arTqhbSZFZQcGWxjGi372w2tJda8cvfVhr/+93/JL37xDVe3A9srzeANhEBLAmtKWXE6J+alELNc++PGYN2G4kaa8+jBcfd2w+dPDxyfVtZjJZ4L5DNOe1IQtKx3hqY1tETuBqFDmTlamAfNky1oIvv9yGbjMcqSlEVvbef6jziviXlgGC1XN3ucHvnuq1+ynAOPTwfu7+95fj5yPiwcj4EcYRoy0zChjaEsMiZIKXNeK9WKQFZrxzwHvIPbbyfevrnhaj8yeMXz5w+UfCKuR5xu0BJJF+6//wPrsrIfN2IRqBXdNMsciOuC75bSpg1UzRpWDseFZW0iq9EipCsdLmYctAypNloswrigCHtXVWpODM686FOM1WinMc6jCzRVGb1ltJYcF4qxWC1I5Dc3e45z5unpRDhnQhBY0KUPfdHVaG17WJrM4pwTfHJOiWI0N/sr6royn87EVbDy1oKzWrxcZeZqPzHPM0pXCenSXStTK8ZK2JD64k6releXJgTNaRwpBloNDINlt5swFtZwwg8OazTOaBmVpkQp0kU1xpFSIeNwgJ2uUNnz4fGBh+PKGhVu9Gg7ALJO1daIOeOMkUwWpGsaY+bpdERpxdv377i6veFPefxXFAD9QKiLsv+fP17taPL52hpiMxKrG+3VsqZeV7Mffb8shlo0AU2h6mUGjnQH5DcApn/tpdCo3W9wWcz7RFzJLooqojhZ/0Wd3RQvoQovWLDmuFhNMKoLdnhl7SO7saZrT2C6/FbxcXf+zI/GJY3XVv0XSgpeF/Aff+Snu/8vLYIX69zlcdEJXP6YC79Py7EpOfbdf4FlZv78idPDI6rIzinRiYzjllggVihYqvaUIlY/AG01eYnMMePmiFaSrIWyPYIV4rKgFKxGs5kG/PVekJpqS6uVeZ4JQcSHZwLneaG1xtdff803332HvZ8Yrq5k9rmutFxkFxwiy8OBD7/5Ax9+/QcOnw6URVTn8ymQ84nWBq6vLNMwMQwea0E5TVGZ9TCjut3GOc1gLDEn5jmyHGfqWjBePOshJmotLEsQfYmx5FD6LP+y85cbEQh7XIJYvhjvdOtra42Y+0XvxNu9LIF5XimlYtxA68qNKv1y+Xl9FBA67VIpjZK7aQ9EaiirxLvehX+5XyfOT2hlUbWwhsz905HDcRaiWhaffevjt1iki9QKxJgI60xaF3L0clM2wnpfQyA1UM6hh4H93S3nhydyiDwfnsUelRq5hm5lqwxeris/OtwwEEpmDdIJWXsXaBw20inITVgOFJkp20YrC8oVvvvmiv/2//Q3/Nu//hXTxlJZsUMlp5VwmonnlbY2jsfIx89HjnMjN4syI4OzDH4iOyu5A4Pmq3d3vLvZEE6ZH377A7/9hxmnG9tNw6pKyBnT5N5U++2rAspCiiuPTw+oFil5ZZ4HIfrtN+z2I85Jq9h5yNGAbkxuYL/bMw0T9s1Ia4p1DTw9PfH4+MjnT/d8/8MHHj4fiGuj6kQrikwi1ULqKGFnFdZrStEUr7jajLx7d9cjgiM5HHh+PGBUwijhYox+ZLCeuKwSj16qiJDRrHMgrqvcgbzc+2puhBA4HM4cF5lBj9OWlCXoKaOkIJ0MLRaq0nJPdRZjFMYpSm0sa0QxsN9OWAdrnClLFAeRt1LwNk2aV3GnqCjvd7XsxglvnlnmzOko40G5zyHgNlVp1YoYV2tKLuTWGLxnnmf+1//0n/DOsttsMNp1wbXCd66/bllK+lIZnaOOIgTUSoLJvNYU1ZP9lICiGgJ3UihyzhJ8VCqtZEm+rIHtRkYGmEopidEodvsNVhmWw4mUAlZpvPekUhndhJ0cbS5Uu2VZMp8ezhzngrIDxg5YO2JaxGhoKhNTEa3DOImFMxYBDkXF7mri/d3X3L1790fX5p8+/qvSAF8eL7tmqYpeOwCXf7/OuV9bBu3lL/UyU2gvfy7Ng3bpErReaGjVd8XiJmjdMiXq3a6er1WQu73rYC/VbF+N5eeIva8g8aDY1ouEBlXideWLK7ootCrdk19B1ReHgSri+S99Zi1aoV7YKI1Roq7+UsAnccPtxapiv5jn/wjrq0FqXfVyDOVrfiwI/Gdvh/T8OwOqUlqBqjpiM+JVQ5fM44cf+N1/+XvODw+0sAoCuIHzA1hHppKLkrZ2V7oXugI2N7QfCQmO5xWlHaN3GAW5NbRsXDtSN8lCEhbxfCuxfTYl76+wAyKxZK6ubvjqZ9+yrgvDZmLYTGJnUprBelosnD8/8/k3P3D84ZG2VAYGiimkUljWzKElaEdSaNze7NhunXSFcqSZ9lK8lTWwRgmPyqFQY0JXCXoRi5zYg0qRXYfsqkWcWCvk0khZQplk110x2lJbIefUxy4KlEGJkZ2YEnR9RwyJmIqMo0yjKWmV165otlWuq1JlQVRGdCNziFRg7KlhtUiMqblQLrWMHbTSgCPWwrpmPnx84Div5ALGaYzXKFVkwX29YCWmWCtGrfFK4VvFlIKu0EoihYU1F7T3YC3VKK7e3ZFS4nqZqaWQznNfYHrKZu+e+MHIKASP1eJA0U1S/rQSxLV1GuU8sQSZ9xJBF65vNvzFX/2cX/2br9juNMomRi9iqeNDZF0CYcnUoDidC8dT5flcOGeJfLXWY0cvmcEGtGlsTOXqaofewpRXxhLYbffcXN9yngMfPt3z+Bw5nOQStF6AQGMHZIWUWMKKOleW9cjxqFnmHeu6g5oZR4e14hX33rDf75nUiK2GEBe09Qwbw9fbt3z1szuW5VseHh759PEzH374xPmw8vxwJkTxpysL20FjvCXlhCqVq+3AMHhaWZlPEWtlDr/bb3lz/R7VpF2smuQvnA4L22kihPWFMrkmMcSLjko0Tud55flwYp5XWlNo6whV4ta164YYDYMewEhX1hnRzLQmOGlrJbyq0vNIlEEryxrjy/3Z0O+1VTFOExRLSJFUKyTJAXEA0gDjQpHX+rKxFC5AzhXXdSZhjeQQ0KrinWE5HCkx0bJ0VYzSrEsg5oB3A+PgiXHBKdnoOcBZy+iNJCi2wmANpcgIIiXhMNSykE0R3RaNmiMlyUK8rjMhKVCiIytFgFjGGWKAkBO6Crlv3Dq08pQlsqyZp+PK58PCcdFMk0YnRY4NZXTvFDYwCu0HitKUKoU/2jNMmu32FmsmUvjjm/OfPv6MAkC9LM4vH/nRBy6L+Gsr+0UboFR3AvTFvPUdeoP2EjL00mT94ufJ97WqwChMrxfaZdGlInr3fg+7eHn7jkhCdnpLvL8Z8rtkIW61E5suOzVEiaxVH1coWc0uow/dg4daU6AlY7o2sXY1JJXu0gy4PJXLMRA/d6chfLFTl+emf/z/8o0/aoz8VHApYJHXL7jsPF/RzMI6ML2JYrXCUFmOB37361/z/e9+S14DDgk/2Wy3bPZX4o/Oido0qSoJb3IGWiSXRAwZDaQYSLmgtLSarRGBm6WijdibcgqkUJnPRxSSzGiMwE601mx2W5YlssRIiImHpyc+ffqB7c0WU7folMQOhyE8HXj68Jn16Qih4JqRIiWCweGcJmX49PnA589PTKPjej9wdeW5up6Ydh47iPK+1CaJiK2QQ6bFjFMW7QRyUmoDbYXv7mCNi9gfO5JVGdkVqAq6VvQLf1x4BsoY0KqDItUL66G0RloCVYEyjmGYZD5eGqp3UFqt5FY7mraRqhSd9CK11Ma6RmqVOa3EO3tyExBMzAJSCunMGgJryJzO4sPXVtO07bsZGQ1JgS1JgkbLAjc5y2A0tjY8DdMqhiK7u8HSvKVqTUmNYb/l+u4NMQR0K5zuoawRj4JUWU5LF1JqWhUnQy1OCgClSSl1zKpmGEb8OLKsM9XIzf3mzZ6/+ne/4N/9+3/DzZstIR/RrbC5uma62rKeZpQyVAwhFpa1katjDlnCXfyAGkbRhVh6yFYhHJ7BDozW8PZ64M30jQRXXV2xxsTD4Zp/+PX3/OOvn5nnhrXgrWbQnnFwTFvQg6HQyCEwL4V1OXM4PPF4P3C933B9vWe7GTG7DcUVQl2ZVUMZRYmiWvejJNpdjSPT/h3vvr7hV3/xHfefnvjwh3s+fv/Iw6dnjs+RuAit0luFGZykDpK7pcxI91EpcpbcDNUg5YpWltpkfqzKTC1ZonE7v8G7gVLE5ruGyP3DkcNxRavGtN1gnRQdWoEbZERaYkWjIdUeauZe0ha1bmy3jmk34a2h9g6Z7mOeUhodX493js1mg1aGpS+uoTRSEKfmdtCMXuBLgiaHS+yMALMSWYMbnXQvqowbUI0QEmFe0bUxWEdTlVgFJKeptBJoBVoSx4dzlmEQGqZ1TjJFUpTOsZLAp/N5Zj6vAkHrhUypmZKKPCfdSCUQo2HawjSN1Co2Z9Xv0eu6YpRlnPY4N1CKIaRVYq7nwBwacyjkurAukRQ8241lGpTg5oeBabPtKbKQWxBYlHKUDA/3Bw6Hhf/uX13T/8wsgB/Pnf/5o7XX6uyP/IS+ePd5O/WlG+DMK2PgFRgktL1K69Cdyy9BhpVNQ5PWZHtRyNfXhRz18keq3YYA+/rMvpZXEEt7heaoF1XDq4ZA+PViD8ndHUBvBZV2qTe6V/mlPaxwznGx/F0O0IuPW6mX13wZ7DdkXFKrjD30FwXWP7f/XaZhP36PLse0fjGCMKqiqKT5zO9//Q/8+n/7T8zPT3gq3lq8Hxiv9rjtjpAyS0yEUqR7InJsmq5oNzJoR44Blau8L0pTMdT6WviVLEPlVunRryulSL65cxO1Stqi8UNHM8PpdOaffvMbdvsNwzRRSuHwfOD6eGJ+fOL09ESaA1s3MRvx2YayoqvGDCNNNVLfWcdQOBwKy3lFqZ3AipQlhsigvIyBUiG1SlgDaUkSm9oE5ykBLI2cW39+l9GTLMRGK3STTo+cjo2YEi0qWWQV1B4JXHs4E+0SUdoo9JGWkZ2R4F0vo4RGTUVmkPQ2fcw0pBBISkJ7Ss4YY/Gj4vh4YokSHhNyoMTcoUF0HYEw/tG2v7aKNlY4B7Vhu0PF9BYoJVHWmbhWDBa0h1J7SdlFs9bB1BhGhzMW5w3T6PhkDE8fPpHnGVUrzmuc1tQSCUHstClGKgpnDEbr3nnJVFtxSlIe7aC5frvh21++55d/8S1v39+y2Wt0CmhT8N5QYpJQlyoQpMPzzMfPBx4PK8c507xjGLbowYuVsVV0y9RSKWsmqojt3v1pP+FsxLRnbvYDV/sd3tyhW+D77xdilF3uZpjYTiPTDqypGN3QzkBN1Bw5HU483z/xMDreXO+4vbliv9syb2d2uy128ritIdYoM/DqqS3iBovzjv1m4s3dNe/eveWbb37G4/2Rh4/P/PD7T/zhdz+wns5yX9C62+uEb+9dv1+pzHk+EeKK1cK4dwacGcQ/HhYJOOquHmojhEJMiWVZOZ0XjudIyiJqTN0S6McJ2or3jmQgN+FvlJZJBTwCFFKq4QaFnzzTZmRyDqcFtxzi2rtgwlkoUbI+ki7UklhTBuOxGOE4NM3kR6yeueiugV6YW2y/x5VSiAH0oLFahNityobVWo9FMQ0jtEI4nwXupRutRGppWCtwKWssu2lk2ghBNkUZixpnBPZlG1YbBuuli7Bm1pCoWUbKV3vF7c2e7XZ6uR6M0dSSO6ukUHtHsAG5VmIWrcoaK8/HxMPzzJokerolifstuUBz5ASrbRhTGWbDmC3eKdmIIo6blCun04L3/3/OAnjdbL7O7tuXq3K77FB/0iZAbpad6IlCffkpuUn2hfFLoZ4sC+ZVFChmOflMUzQt7YAXeYaSjoIsi70MaH2w2Z/ja4dBeAKK2iEbTexnLxK61nUGl+fSFfpa9XZ5Fapbk6w8o6QjYHo6l7y0y4IoHuraWo+glKf6mjXaf0fHIgvFsPU27pfH6RLti8yLsywIklfQZFHiFSWba0WphiqNspxJ5wPL/Ud++5//Vz797jfoGEX05yxumrB+JJXKHAKHOdAysrtXlVIjRYPZjHhrWJcV2//t/SAzuSrOh5ortkOLaNJGq52j792I0ZacIqVE5J1V7Ddb1NbihpHddstgNzw8HzmmM/u3t7x7f4c1mu1uZD6eUGRUjVhVUE5abWuJ5CQ59EZwbbjBYq3kyYc54JxB106P0BqqQqlCMzLHDGtmDiL0zLmwruHlfdJKvSSl1X5+lpcZv4jYrPdgnYw/8mX2Ly3+1sTmSWc5pByoWWH8iLGelGXIm1sTWFXM0vrVBoyTVmrugCd6ezWDOmfun55YUyJFmVcr6OFDCudEGW20FieIRhaPIrRLKTSNYHBrJcXK8ThzOp4Fh1slzCqFjA8yQisqoLzEqRYMw9UV2pquIxBu/+lzo64B6xVOiTVPiuKGacKuP8eMMk1GdblRUyYvC0Y3bu/2/Df/l79h/3bg6m6g+JW1VayVdnUNiXWZmR8PhHnhfFr54dMzv/3DIx8fAms1WGUga1hFvKpNYXAGq6zETKuGt5rt6LEkzscHVt24vr7BuYnbyfDdux35vPL01HAOdpPGe9meGK3wTgtq10zUuBLXhfUcmedICo8cnk9Mg2O32/H27R13797Q5oKyFTd0kaWvYv/rxVpumc1exmDXd7f87LvMNz//hve/vePD7/7A/cdPnA6LcAKUFUdK6zQ8O6ApeO+wxpJCZA0LzTfcOOHtDkol9fvYumYOp1lseilLdHEFY0UnsoQE1jFOGxQeYy2lJUwE1IICyTswwsXwDrxT0CIxCihpGCeG0aO9JuYCi8YoK8TR1FjqLAusavhBotD1XBisZuO7QK6BF+kBTim8FnGh0w2NkvwE4zo+uEkbf3CS1FiFKlhrJplEK0kW4tawF8xny6hWJVtAycZF9w60G6ykFebKaCf8MGHtmcf03HNchL9w92bDu7c37DcGSpCY4KawqqGriAlNbQzGUWrlfD6xJE2oI6el8ek58OFh5hTo7GlLS5WQC2rtTgEay5o5ngO7jeP2estm9AyDZfCur0ug+P8zB6CUL73oXy7+l12petmVSjv69etbEwXkyxjhC5dAQ9Cgr3Nt/fKzX0l7IrhTl4pBibUP21nZJfe8AVBomccW0QhopDrT9JlRrJSWBYqjZJetKkC3z9WM2HFkh1dA1PpKIjm1MqLK7g0M3fPDqZ0JrUAjudGlRFmEe4SuMNe5QK6lTcxFuS+7d9Uuy2IvqNTlYFz+0xd9mcT1w1G7BSwJFrkrcK1RrM/P/PDrv+fz735DfLzn4Xe/oYYZq5oktQ0Dahg4xshpDcRSqdrSusLc2IZyGooRfYUxNCqj27EdRnSutBCxBkwplLBQKbJQ1sqyiODr+mrH4KaX1jW1CDugNLwWcM84bPB6Q1413//+Ew/riav3b/j2u4XNaISl3yJ2gKYjzosfGG0xg6aYxnEOGGC/m7i73bPdDNQMsUgFr6pm2m4ZBkvJlTTAEgvzEsjJEIM875wyIcaX8UzJWdwByqCsp2lLTJmQOlrWKPwwkGpjCVIA5Cw2P2MkfEd3JwUlC++bSm5ZOihaE7NQ+gqGalwfR/RC2DqaEt7+PC+sKZGz6B9irC8xwao/F2cNWWuxD2mFsg1jmjAiSqPljlXFUlW33ZrKGuDDxweudwPTOLDbXqGaYz0X/JAZvSEukeW4gLXs3rzHbnc0pTDbM7dfvWeyjifvmR8eKeuCaU2ss03RakSTyBnmeaGUQA6KvIryNIeZ3d2Gv/1v/oK//T/8ijzMZL2Q9ZHzcWE0hndXd9jcSEukLIHlsPJ4f+SHD898vA8cVyjWkE+JT6dHOa41451hvxvYjAPTYBkHhZk8znhKWqg54b1i1A2rCtVk7jae486zngJGF1Q7khaDV152l8oI0W502GlDngxlV5hPZxSamgunJVHqzBoSj8cD2/3I/mpi3Agf39sBZyGuhZSDqP+bEhGnVwzO8Xa8YXPj+OabG37/69/yu99+4HRcWWZRh3vneitfUuuM0hgNWVVhHHQ2PzgUhvOapJ29Js5LJHVQWmkCVrNNM2qL8Q7tLAWFM3tJ8StQa6CWwuBgHDW7jaXGyH5n2EwjRoM1pWtcKoVMc6C9pgXZ8GhlMaphNSjXMN5gt5Y5F4axsdWG7eLZbxTr3MR63Bq0iqmi29HWYL0RYXSuPfrbUXPhHMTZMLqBY1woKaKQ8J6qFDkFYox4q3HOiKOmiNVZa8vgHOeU0BamcSTG3LMbZJ7fqKSYiXNm8HB7PXK9G9kMjRRWyjKDdZzXGZUNTltqFACQ0OWF03FcM3MxPM6N+2NibVJUgWiqWlHkVYoV1RopN85r5s2VghZQt47r7Yh3GqtlDUtp/pPW9f8qEeBlFPA6c77MnS//6etc7WENXyxc/Sf86Oe9zrdfiwboM+5uu7rspH/60J0HUMiiyOxuANURmq0kFLLnf2EWfPm7AVql1svrUZ1iJYu1FD6Xlr1IPi5cgovu4aJjMFo+r5Cd0GWYcSEg/mjmjyjIRWB4IQXKz7u0gy8qcvmexisrQDQKORacNThrSGGlVlmIVSvE84E/fPgDv/0v/5k//OP/xvpwjysJ17JkvjfAOVLfrVdt8ftrJj/0XXOVi9gCJFIKhCCQFx936NJw2mJLA2OxOaNVIhdDXAO1SRRua5cgJdmtDJ1wF9ZGi4LU9dZjlHiMT08njinx8PHAc2p8+P1HPn/7Nd9+847BDVjvMd6inMVuFNO0QxlHOc8MLaO62Oz25pr9dqTGSIir7BzQTHrCewHjxBKl1a7EZ51yojSIKQvcKNeOnpX3pKHRziAux9qTKyspJnItkl7XhDBZET95K5WmDaM3tCbUrlorTUukb85RCgU8panXkYBCvPOlEkukkIgpc5xXznPsHQY5r4epl4atS2Sb4hIwY4wSJ4TuQjtjhLaXK3FOvQ/WgMJm0GwGEWc+Ph8ZBo8bRrZsiS2SOHKtDMNuYrCKrDQxREo7M2jFzd0dZZpYnMVYzbSfOD88iEr/eKLmIuFPSvDeIUVSylAtCvWSD3F7u+eXv/iG7c5QJs9hPbIsMzmuZOUJaqFmRTxFWmiEc+Tp4cjpJCjV1hTzObKUTGqQaqWKS43z44yzCu8Um42hfrNjsLeMvrGdRt7e7vnmq6+pFU7HlRoPXG0cp22gtCbqeqpAZHKjWYNqFo3GO8/oNuRY2G33OO2ZT2dCDIx+IMWVw/OR+XzkePAyfrjaEGPi6s0N02YQYJSHEGa0NpI0ZwfcYNibHW9vr7i52XL3/o6PH5743W8+8Pj4jB402/3E4Wl9ucW2BlZbsIJ9LgXWsKK05XCeeXo6Cnypn3eb3RWtZZ6fnzs0zeH8CA3mNTD1CHVxccHgDXajuN6PXG0H1uXM1c4zDSNaNay1PSiqUhFxrHi4a0cbyxMtpbCdHNqJg2DrPaEa4iFhdWO/NRxjpvlOWW1NYD2ItskqSS1ENXLKqNbzB2ojlExNDacN1CLc/6LEXm4Mzond3HnH5MV2jJIxZpVZHiEsOOXRxmK9gyZ6p7rfcD6cMWQ2Gy1QJwfUCDWy302UtBKXAFlTca/R6A6KGRgmS9Oa8xKZ1ySBcq2KTqlktEgW8MpgjZURXRNr8nnNaBVoDXKMxOTZTFZG6l92kP93Hn86ClhfxHQ/XcR/pFTrguIfz65flP0vW/t/XgDI4iuL90+Rt7X1lv2XtrjWLs47Lva4Jtv8l3mF6jv3ixrzJdFP+gH92dcflSOy0L4WNa+v/dLONyJkKz1NjV7kvLzky8JdX47JRaj45XO9vIbXl/OFgO8n4kpp6yPPuY9KjJG5o0JTspwlo7ecT8/87jf/wH/5u//A73/9X/j4h9/jVWFrNKlm9tPI7uYKqw273TXDdo8dN4ybK3Y3b9hcXaGtI9VMq0lmZTWyLmeOpwPrvBDPq8wic8XkKjqMkiit0DQoZ6HISAYj5MRUG7k2DLpHaRpqjVyUiqVUwjLz+LRyjhGyZlCV0/2Rj7/7yM20xW5HFA7jJvxuR00FM21oRtT0V9uB/W7HzdUeazXrfOZ8XIHehRkMdutQThHXwHmdWcNKjOLzFqmGJpdGQWOGidopbM2IqLRWCDEKKdEPGGvRznXxniKWSmhyjjctMbTb7QZjGs6Jive8LLQ1ULJAZmIqYn/TXgqIZeG8ZEKWLs2aCrHv9tcIMclprrSc3rXraqq6DLckE9xKxN1LYf2lccQazTQ4mvLkKql4m8mx31qMSpzOgQ+fHlhj4vpmz/XbO+6sZ1eVBGtZyzhNNGOJKWKnkf3NFXUz4AeL2wxMN1vsfsPnP3wQseMSabmCMjTvMEOFsFBS7eS1RiHhB/H3OyMRrWVNrMczJktHZFlPLAnCOZCWQlorORRUFb6Hqk2Ifh0c00tm6UIWudZya0RVeX58ZvKF93cj795c8dW7d9zd3LDMgRIb0+C42U8d/Sz8h1YLqIKqgZYNJWRCS5ASg5NOlmodSrQ37AHbUcCNzDwfCGvidD5zPB05HI9s9ltubm+4vr1ms9+x2W7w3pGjXFvOebHSUtm+2fDt9C3X79+wf3PFpw+fSbFgUCyLvMZSMyUoVNFY46jJMC8rp+VMSoXTHAlRIEPWerbbDeM0SrFsrfyQPq+nCfAsplU0VDWhVGYYDfvtxPXVyHZy3Fx7WWBFAY518odeZMacKVW6lLnJiEE6tJWQKqqKEFUNG2nda9CqMHrNNIIaOw6S9iLIttrgvac1S1hXYowoHJtpQgExCGM/a9nh6yaFu1FKihDjBQ+NkoyYKCjxWiuGRs4Ji5YZfhUstdCpK95pbm48wS1sRo33Bm0qNQVqDdDkdTck3ruWSM0S7uW9o9hRoFO1MZ9X5vMCTQlJthbBUOs+9jZaIuK1QVXJc0kZDqfIsibmxZDrFdp5tPVgXum4/3uPP6MA+Mmi9KM2fS/u4OXfrb228Pu3cJnO80cXukux8JOPcfnYj0VvohnoQ4QGLyl6IAtSEyGdtQ7JD6gCqeg2f3EC9BtEDw3hi+dW+/dfVvcLDEVs2B0VmQVhK9ZA1dveUjy8LvT1i9f6ahOUY9plh18s/r1K6K+vyXNurwXSyzFuGprE8UpbVdpR//AP/xv/7//X/5P//D/9f9jYxugsm5s9d7fX7KaJNzdXXF1dMfiJ7dUN4/YK47f4ccOwucJMI8pbUs3U3PGWLRPXhc3hifPxxOfvP7LmQlkCRmlZ8L1Up0o3YskveoUC5CJil5SLzOG1BN20tgrdjkpJsC6JVjwlVbbe42wmLYX7H5643z/B7R5rBsywwW0zy7IwUzDesb++42q35e76isE7np8fOKcn1EbhRmFvD1cjehAhXahSsNCLypRyR9HCmhJog3cjhcIaW5/7d6qdciirhYKotCjiWyXVypLltbZW0EacDm++eov3mu12QinN0+nA4+HE4TwTn4+kGDrdrRFiY14zIVTpTFjVhZZy3nkHSl9cMHJZGCvcANGHSBei1N510gZrjdiQNNDklThr8NajjCNEyUIwGhHgaemG3D+e+PRwZLcfeX+OGL9hf3NDI2Krw7qGosrsm8ZqpLAYb65QoyV7zaBgpzV1GDk9HIiLQHtSyDTraUaobNbJImMHxWY34LzG9t2ZLgWTGr5ZdGws65m8FlrRzIdAOEdaUgzKMVrDxjdC7sFLHRijlKQ6Dk52rtudBRItV86HA7NL5MmQlpX5dCQskbSu1BQZveHd7RWqky9bzZQSaC1hurC4tUJNgYxCtchgR7RRWGPZbjfsdlvO2zO1BLbbEa0V5/OJx+MTh+cza4gsa+T5cGK723Jze8tuL/yMcRjRG4PVmkikeZjcgBk02sD+ZuTw+MzD53twl4TUAsWiqqY1Q1obj4fAEhPH80qQDCmM1TSl0M6JtXEJr9klFWLMmHFgGEdKSahWULYxeMdu2nK9H9iMBqNlZJiTHBPvbU9BDFJE9AXdGBEEkgu1SndWOQhxQZk+3GyA3jI6w+A1o9dcX3lwnlwyOYuFuxYZBwiQx+CMRJSnGInGMHhJUFxTEuskosFq2uCNCCRjBlOV3O+aZA1YJ2wBPzhKTcS1YZuMTgwyVmtdWD6NGrIRl4iDUlZaDVgHKQtR0xiLHQw5ZDSNcRywk2cpMIdETJYQMmHN5PSqlzNaCm06f6a2JoLs3mcuTcLJltDINaPtgvYjTQ8M7scQun/p8WeIAH+Msf3JZ3lR71+Uz+3Lxfr1q378My9iwn/+8Zfvhb5gfiEDpe/j1YWZf1H3dxZAqSglRYDpITytFVTroT4KqVLV5fmpHosqxYPE94rTQJmuAC2X2kDJwq1AadlVGSss65JF7Kf1hS1wcTfI35fxxuVVXLoqP3r5l5GJ6jf5l0Krv2qFLEVGYpMNYJylpMDD54/85//0d/zH//D/pRweubrd8fNvfsbf/u3f8PPvfsY0jUy7HX6zRSmDcxPaDjTlaMqBdTRrKVZRmoGiATlp/TCwdQ49bjmHTMiVyIkWA81qWs+2rtJPl8W/VHL31+cCayw43/BOfO8oQ6m9l92FdMbaLtCBYRipqhHOie9//4nD/RM3+63sGsaJwTuKheFqy+3dG+5udmyMJqwzaq3YraZYI7ux6hh2G5QRGxzOMkwbIBBWCfloyA5eolZlRLMUOMTGmjK5iA/fORHclKqpMZFykSKnVNacBOLTGsYrrp1i82bP+7tbxslLQM5R0vbM84HHNbLElWUtrKGwBtnhAygruwPnRHdTqlhWlekJlVoJCGXwxCijBNV1MHItSrfIWotWkhLpnMdb18/xi+21kZVBUyg5YZwAndYlkXJjjoklQe1ahK+/ec/UFLQTZnCkHMlBoqI3+y27qy1KDag44Wrjbrfn7c9+zvOnRz78/gOnxwPxHDDZMjWPsQtWNWpeMB42VyPDxmKc7LxMbYzaMVRLyZlwTqzHQGmKw/2J+XmG1HBYvCqMRrGxilYyUfXQpiYYgP124Go/sd15YjrhbONqZ9Al8un7e1pcyF+/xypJyixhFbfM6HvIkpVY3qKo1fQRnuS2lyrXtNWi/J7PCaUMb+9uubm+Fvtfsvzql9+xhoWnp2e2+x1zWFnCQo6FVQdiyCznwPXNwvX1NXnMlFhRV1siZ7Rr3caX8Bt4v73m5nZg2mr2V57zIbIcIudDYj411jkxnwtPx8iaEiFLpoJTislZmrYsMZFTIoYVa2Aw9iJLovauiWqZWla0bkybkZubLbutxyAfN1aum9FZpmmQxM8l02g4O2KVpSZHWcVa15k+QturjaallZ9iwE6TOEicCEe3xlKMJkUEcaYkU0M6dJIWS5U7bc6VZVlEPY8i5CpW7drHv6rQnIS8pSTR0s7qF4tySplqtIiIjSauwkow2tD3d7J+UDGqMg6G/d6z2w20GmmtME6OdskEsU4Es0H0akMX8cp9o0cLN3qY2oURw0voECh0/33ieqPfO/uGUMMa4dPDSkgPrLFyfX3900X6jz7+LBLgT2f3P1q1vtAEXHbBcCHUwWV78lOynfzs+pP///GOuBaB8Py48/DqqdfqlVFQlfivjdK96S+CE3k+um/oddcW9Pa9bi8CxiYru4wBLiLGWr8QIcpXaS03VtSry0Br8zIuUMIx/tExu4wgXl9jf80XVPELKvk1DOjLY3VxSoh+oGsQ+s8pOfL0/Mjh6UHsV1pxd3vLr371K37+i1/w7v1b3DBQtKIai9KGY0qUWGhY0A7jBswwooynWS+twBp7UWOxSjNaz3A4M3ZeeDlDSwHVBlQWAI5TGmKiLIGmOvrTWGIshCCLVKtgjMMPiLCmKrSFZa5gtWTZ7/b4zYAdDOspcn4+8vzwjLENbRtusly/f8P1u1vefPWGwUBez2QCZtRM1yM6gDWO7bTF64GaCnnN2KooEWJaWNYkKuhixAKZMmvJpHNmyY3jKhjWmGQ3aU1iGiPTYEVolQsxN2IR5r2yRkalpTLnyNoybj8ybgZKqWx1QY8jbfR8Pp5x92fWlHFedUeMnCbeG4yzNCVdlEzDas2oRZNirEV7T7qcUyW+XEuttd52LKQkLhdtwVnHZjMK/jglSio4pWhGLILUQkliWezwNFJS3N+fiPE3KO2had6+f8OUB3zNKKPIJRNylDGclnjW0hTjfsfoJq6u7pgPJ9z+H3n89EiNjcePT4TTQpjP6BZZ5yesS9x9dc2099S0sCxHyhqwVUlq45xosZGXwvPhxOm4kOaELqIUN7VCKphaceo1RbD1AuBmM/L29orNxqKUY7uxbCbF+XTP4fHIfEiE3YZmR0gCQrJUrGooVXBaMXjxs9c+i9ZWdCE5N2rV1KJZg1wfWiuOxwPn+Yh1hr/8i1/y7c++5h/+8e9Bwe3NNZu8YQkr777+iq+/+47T0yO//8MfePz8wHpauLm5oV4VWksUFbAjbKZRWuAdmbzd7Rg82H/zM57uz3z+8MzvfvPAw+ETn+5njsfGPGdQBW01hUarSsSMvQuUUuyWZ7mHSXhV1zTVDGRKWTHasJ08V/uJwWkZkRXZEV/tNux2G7w3LPNMzDJiqzV1XVVB6YZ1GqeER4iWrlWtjVyTdHFNYA2NEM5oJXZLpRW6dzWt9T2ePAuBM0tehWqyy6cJ1TKXRmoC+SkNcTch7XOqFCFON8bBMgxWilx18ZHJfXczTlhrhXMQErp31ZSSDI2r3Ya3b68YxwGqkD291+KyxJIi5FTJWSyXSicGLZCqmCrH00oIUeyN/T5vrGwkjZZNrFEKpSy6ifpc1dq7eQqthH+whEYuK5Vn4p9mAvhzRYDqny1K8rcsbl+G8gC9laQ6AOhffryK/y474teAoQu4Rz7+R57Oy6/7spUuDHCtZCjalLTqFaLa78NpULXP+2vf+deXH2ysFV1BbdKK1VZSA3sxcVnoa1f/a6063/myO5Dfc9ECtEuD5DJiqAJ70aa/uRedwSVNUf/4+L4cq+7zyiVLmFDKrOsCtTBOIze3N3z99decPjTOS+Q3v/+BCEy/+S0YTciZWAvaOIwf2V+9YX91yzTtGMYNw3aH11sMHmtEJ65akXrJDmgM13fvaU2hmmYFUo5SRCUlBofcaKkIblZLK26YRrHfdNqeVoZhGNHKEUImpkhImTmLWh8tFhxtXC/YCgrP6TxTWiSWmel64OqbW7bXG7SDZTmSlxMxrMQSsINls3/DMG7wxqOrJpwDOa2UVljWxOFwZp6j8M1bX2gbLKnwPAtMZi1wDshNQwGpEltDe4n9zDWx1Ego0LR0B5oW/sHjuvJwOvJVCmzcxLQRbriNBbMZ+DZEllD4/e8eWJeMIjN4xWbyMsfUllQ78OTSy1amz/ll/DKXStAQapaZS9cClFTJ2qAbcrM1mlaLcBxak5sJkhBpvKI1iTxNIfWfL9dUzmJNLGXm1//wG9Y18MtffcvPfvEVV3rPOHkRSpZCWgLPQUSRQi2cuL25YtrtadXwi3/7N/zy3wvZ8fEPn1meDhyf78nxzPn4iVZP3Hx1DapQi5DsasiQGsvzQjxETHaUUIjnQFkzNSTSXChRZrxOV7yu4BEoE1KkGQ2DqWwc3Gwc+/2GcTDEeCABVxvDdvDUkIhJFsiWEro0jJHFxSklwV9a1BZaN6zr+Q0FYhSok/eWFGUctK4nQlwYp4Fcvua//P1/5vD8TKsJjMVZzTBe8/Offct3v/wl4e1b3r19xz/94z/y+9//jo/rQg4rIWyYto6SoMXM4CRzoKSA85phMgyDxZg9026L9huezpE/fD7wHDNLAOcUVtl+LzSkYihrpr0snkI4ddZgjTAvnBUEsTAxClYrxsEyDnJvoGW0ht1mw/X1jmG0rOtCyhmtxYpKq3JdhpVaMt4OeOuoF1EsWnzxpaCMo+XM8TQzLyvGOjxKdu1e0jjHYSKnLDjtLHwNGzNBKWIUyqUQCJVYVK0FXUklsUYZsVEbFtiMjpQC85xorbDZWJzXLOtKCgtXm60U1FFw9spBU4qUIykErjZXeDeQYma7GSS3pEaM0YS4ElpGa8d269F6pZTCEjPFOE6nhY+fzjw9VVIU4aIxYjNtuVJbwFiNdQ7vHFZbas7EkHFOQoLEaSQOC6NVh6o9/++suK+PP2sEIIvRZbd9WeAuC/PrXF9r8/L/0hGQFs2XO/zXn/Pa1r/E3kpnvO/IXxbO14rssuN/CSfSMnpQqv0ziyJdK6BUnz9p+mw9U6vQzUqfWV92/7q3WC4YS9WV8rJwaei2MBFhGWi9XV+LcAmale8t0h2QYuSSFCjHQGslM+i+83+d87cXbPBFS9DfgS+Op8StXo6jMRao7LY7/u1f/Tuup5FPv/0dD58+8TwH4g+PbPcrTStiyTSt2e723GyuGLY7pt1OKuqaiYcDIwqXZM7nnXj4tRItr7KF67sRpSzOepbBcbaKdHwiz42SEtpZBiWRsyXKe3ieF7GetYbRA9bIYlua7DYFrRpZaqFaYYUvOXK4/8w4jmw2E9YYxs2eJRyxJnP39o7vfv4tV1dbluWZFE7ktDIvJ6yxgl+dOhMfTQmVGDOHw4njw5Hz48KyRHLuHANr0b7SSteLWOE8OAz7jaMpSylCj5wGz2Y30WohrJm1KopxYAxJdXZ+gcfTyu8+fGR/u+Pqdo8bFcZqvDEo7/j6q3eS424nPvzwiaM5obVh8BZnwDqp/GPSlAYpZYx1xCSL9JpmvHZ4XQk0smx2XnQuTlu2o8ebitWKliNLiqgGg3MMVgvR0EjnLlOxg8EPEzEVng+zBBMViKFx/+mZ43HmfDoRcuDr/DX76w1TDylawpmXAllrcjKk7crjek9psH9zx3j7hlbg+uufUZaV9fMHDo8/cP/Rsa6fMZMhNbFzWmPxxrGcZsJpZX5eKUsjLoWaiqCWc4Gc0FXhlGIwjWobo3O4cejEw0otSchypnK7G9ltLDHOxPOMN4ppt2UaHKObZPwTAinIvcFow2hHvJF5rzbdRmw0xjbQEvrknEEbBzhirBxOMyklBm+oJfB3f/c/441oOqy1VLwIepvh6eEeWmGaJvbbDd99+w20zP3nz8R1ppVAWjzjdoDJU23EeYuuhVZktp5SRVnLtPe8//kdf4NBTRP8x9/yh386sh4VKFHn51JJx0BrGa0rVsHoFXro49CWe6fTYK10h7abkbd3t4yjFxhVt3eOw4SznhAS5/lEKUmi0+tFM2VIUXpVErerMYPFMXBeZnHUKIUxAxlFWCKxFLQzVMB7h3JWrs2aaNUwjR6rJ5ZlJbaEGqRjYUxiWTMpdeiwMgJsq/Jcc260IrwSbQzrKiLqaWykmMkWxo4Nzk0YFTFL7rJEfUeKLWJhjZn5vHLeeMzW0qqhNQ21MMfI8bRQisZrj3EOX6U7FmrkNC+c18TpmCkFnDf4ycu9Xme8t13jVXAKvBYOSCHjdBEWhb1sKAHdJK7YmdfN8b/y+K/PAvhiN/vHtAGXoqD1du/Fd//j9v7rTv/Ln9ELt5987Re/+ost8ctnFWLtUK9ditbnoZe5ubq09nvr/DKWkM+al5Y/6gtqodbQhO4mEve+U+9UNClkOpGQHijU5/6vDgHNS1/3i3dG8J2vnY8faSc6ne31d6gXwaIom02/yWuc82A1G3XNN99+x831NX/1F3/DfD6RSsJPA8PoxFaWM9poxs2GadowjR3OkwthDcRU0VVDagJbUloEbyLJBV3RyrC7Bu89YRrx3nLyhjOFsgZ0brQqpDplEilkdIPNOKK1ltYcFWO0oDBzLwJKxmydzN+BmCLrmoipEnPFGMV+P6Gs5+56xy9/+Qvev31Dy5Hj0z3n04HW0x3HcWQYhg4eqrRcmJ9nHh+euP/0wPlpJi6VVvRLdwhtUa5CSFStURassmgz0MxFWSvFmjaKpBRrCBxDZC2IqgrIWW4UIUNaKp+eDrz9/MTD00Fups7hFZjSeHN3jdaGnZ94c7Xh/vM9YQkv06OU48v1o60jNMklqHWVsYxTPCxnbEu4L04bo2A3Gt7eXLHdOFIQAVrOUsBYbVDOYJXs8JQSot3dm/fsdlfUqng+zqimWENhVpGUCzVVnubAGn5giQvP84m7d7d89e6O690WZ4TQplUjt0SYjzwkjdttma6vxK40nwVKsxnAKWzZUNhQ2BPXzLhzErLVGlZpTFOkOTIfF05PZ/JcX9T8uglJdHCGWoWkmHKjWDCDZtg4iUy1mlYS3mg2g8HqimmVHBZSWJhGx26/RaFE71ONaBuyxBlo0/AdBU2tVNW6iLfPgs1F5GbwfqRWzbwkSrWUIgtNTCun8xGKotRKso6Rhu6Uuvl8ouSENQZrHeM48Mtvv+Pd7Q2Hp0cOhwOnx2dK2NI2CesUdfKo4iiuj8XGAeM11imu/MQvpwl3tcHtJ65uPvP3//Nnnh5EwDhNGqMaNRecE82JiGIrOQcJxbEyQykloSkMzrLdTHhjRJ/Ru5atalKqhJDIJbxcUxd7taKPpKpsqJTWCE7dUtDEqihay79z5fk8c5gzlYYZncQzV0NtmZwS1CKiY6WExmga3hiMatA0Shmiq6SqyEpRUqXmKl1aBLZkuoOAIkJn3QopZFZVpJOinYxAmmIzjWhjOJ1n5mWhNaEnQsG7lfPJYdQgfJMo11RtCqW90FbNhhKbBB5pjTEDFst5OeMHuPUTTY0Mwx7rNRDxTo57jrFrEBS0Sk6KksUp59yAtkb0BLX08XUXDP4Jjz+jAHhtj/+x8uJfEgh++eHW7Xyy8P+xEuV17n9Z/NtPxHqXFLbLzPxVF6BeEvheRxV94VV00VntO+uKan3Wc+ksdFToy5y/n7StdwHoyYIvow51SfejL4xSKPDFyMMY+1IA/FTfcPk8vIoBde80vCQhtvpF//8CUdLiQcZ0pHJPRDCWcbPFOs202dMK3F6iaL1AK3IVF4RzTtwRrfWLV9Cyzg+UDDB2pb7GKrlgtDbCpFdQq8JPimEY2YwjzmqZy6nGXBu1Hpjn0Gl0norharvjm6/es/GG5+cHnp7uybWhm/jBldFs9lv01cCSC+fTInhdDGuqzOsZVOU0r2x2htu7K3bbK2quHB4/c3p85PH5CaMVb+/espm2eCvY3xIS63nl0/efeLo/cLg/EZaMLrLzEisHYIwkGjaBU6WiaDqjrMd5i5s2aO2IKXNeZpbzwnw+c5oTynqMErZ+7R7iVKFmOM6Z3//hA5vNgKqVr9/fobRGt8bVZsQrjUkJR2LjK+u8sMwr63kmtoyyYj9sNaFUAjTaSmUdWmMkomzDTrA0KEncKre7ia/vbhi85vk5cj6eyaUI7dJCLYmiBOZitcIPjq/f3rLd7bi/f0KXyMYZCQNK0hauQCES1synD48sJfHm0w2Hrw589eYNd9dXXG+3jMOAR5NrYa1H0Xxow8fzStY/sN1uudpsMDVzeP7A6fiZVhf8RuNHDTVBgbxG1uMifIjHI/PzTIu9MOvFwWAszQmlM+fMqhveaNxgGAaFHzXeGlpptCIKflohxkLq5/1uf812v2NdA6d5JaXGHDVrkddMNZhscNWiEUaGMhVtJWDJet1HntBUppRGyRFaFFTyYHF2wOjG+fQs13btN/gkbBH8SM2VeYl4n6BkWnJ4a9iMA2ExhLlRlshaGkoXckjU6LG+YUZDyIlxJ4uhtprNfuRrc00zle10hUkj/+F//A2fPy9opdhMnRVhFNYqrFaoJi4C4zWbzcjV1chgFKpZBmcZve74drl/5JShJDQDOUe07ir1WvqOuMq8PiRyzihlQalubc0cl0hBU6phzYXDaebplAipMUyqn0cN04SQ6qxDK8g5Y5SgjtVg0dqSkoQWGasZkDCv45JpzgiSOlUGP7C7u0WVxjrPxJQlBhjR7RhtUa1SOixLUyXytxZSCuQUqa120FdjniPnYUFRKVkDIzdXG7bjgHFB7Ja5gTYM45amIJaVliQFVRvFxnmm3RsZi+qGdxObSaip4jsUbZBWmlIzKUahPVpHbXAKC+u6EpMc05jTH12Pf/r40wuA13VIGv9fLOw/Dar58pte1euv/76wAS47/1f4T+VPfby0/1+Eebws3tI9uIQEmW5h7JY81UFBl/9VCtNeITy6PyfZjZcOgumjCdV3GZ2u9lJ0tI76UVJ5itfwAiTii9fHy+LfLk2I/rGXlL9LTkATswd050J/hTKJUQhYp9sVa5VEOaMxg0K5EWs9oeett35jcsgF1BDGNE3mlcYpnO+FTVUSs6nM5UhL10HL7FkaHK3bzyxGwfVtZTt4NoPjqB1PSyI8HWX+Zx3GDLy5fcO7u7e0HDifjzg3opQkeWlr2Ox2mM1A8gqVEvMsGF43bAihcF6kIPjDh5n9tWF/uyHmyjoHnh6eeLx/pKnK1fUb7t7csdtsURXSGlifjzw/HHj+dM9yDNQQMO01IrpWcSso3dP9aiEXeZO0UXhvmLYTw3ZHiIXzunA8nTmcTiwhE2PDqoYtggnOtfRz2ULLxAi/+/6EUb9hNJrRaqZxwHmHGRxGZbSKDL5wtXUMpkCaySp2q50om3OpoEU34o0h5UZLiduN0AnzDpY5MZ8SpcCVN1xNHucUebWkWch0IOdNLQJnccPAbjsyTQOjgRZnWpxReWY/eEyFNlhSa+QGqWharKyhEj8dWY4rx88HPux+4P3NDV+/u+PN7TXTNGCdRQ+SpBZCoBhFaJWDtSz7Dc5UjqcHYjww+MQ0OgZv0DlTowg/Hz/cc/j4QDgs1Jgw1YpHvG8krNJy/HWTQsYifPzJM0we1UcAKQXCurLOld12IqaVRuHmzRu2t7fk0jilxJIta6icVsMaRdhb7YhuHlscusKIxVjErugbUsvXHjCWpMs2WUCy2lNYcd5xfXVNKYF1DaQYpfs1iCbJ2UzNMuK82d9irebp8b63vDNeW663W4yVeNsQEuc8k0JgmCxTFZ1LdZlmI00p6QRceZreM5iRqW0wqvF3/8s/cjxI5PU0aAan8U7LbN/D4ApXO8+7tze8vbtm9Jrz89NL7gA0VBXip+0W6JQSMSbpuBhDrVl0U00TigT90DSmL1rrshJi5bxm/OaK0gyH85EPD4klNaatwYwTqYntGmVk86KV+PlbftEtiFPGoJXQNL03knuxRsbB4Jq4OjKZ66trvnn/jvU885vnB3Zby3ZytCqI8sELvCjHLMFL1qFVIaRAqzJ7b+huTpPuT66NEBNaWZwteFdkzAwsSyAuFesGtuOWYTMQiicow927TDOBmA3OCvdAURgHxzhoitHSrUNGJ87KplKOtWycaoNq2YDrvQABAABJREFUBBmus0JHaOlPW0v/jA7ABejz40X+y0yAP2bpexWyveYHfNnCv7TsL8XBP3uoL7/u8oH+by1dgB/nC/TEwf6lfZL+xc83Ly1+bXoB0uEh8u2yeItZT/dMcIVSru/oe6mhoLb0UsC8/sIv/91kE69fn7PCcOmCXFr+9ZL41o+upAl+YR3snQhpdPR44y5vVhcUsWrSlkTRdCEqRb1YEbUAJFrtIwCtcXZ80UZoo17eu5qLhCNxKQB6k1P13IUm3ANxRQjL3W1ADR4PqMORs7W9dSavxShNipFPHz9yOjzx+HRPzpFhsGhrGLcbpnGLGhyHeCaVitWDtPTsRAqRlFeW2Ai5sj5Wfv/DEx8/P7PZaFQzjH7i+nbPV1+/Z7vb0WJiOZ44P584fH7k6f6RtiRsbeAcVStp1ReJh0ZrUinkPuM3Bkar8ZuBcbfBDlasW4cTnx6eeD7NrEEKh9QgrRFyk+5B6cl5ujFaTTVQqBwPKx+//8TWW97c7Ll7c40eHC2vbCbDZrrifDhx//HM6EFtPet8AYQg7XVjSDmJ5kVrmQd7hXWjdCdC5XBaOZ9mJldRZcUPI6PTjN4I4bBc3hdBBhtVGa1iPznIMzXB1kPbOM5zpqhCNgpdhdYn6XMyeg8nucmGQ+LRHPg8fOL7m++5vd7z5s01X33zjmkzoQeZx7tpQBtD03CKR4ZBU+oZqxJeN2H90xkdsbI8nXj84Z754QABBiULskGuydrE5ithMU0S9rxDDSOb3ZZhtyG3SgorrYnFN9fK9x8/klvl6voKPWwpeuIcA+fsmDMc18jDUax81lp2VZGdg8FDhKYS2okvXFNRqsg5ryveOVrTmAQlN+nmLBHvRjZ7zc3VLQ/5M8fDiVICYwKKFtyrtYzjxMP9I9MwEOZAziu0ynY7Mnhp+bYiPvplXZlX4e7XWhmLI+hVFtqp4JTGjxazt2yV58pumHxlHBb+17/7LacDGNPwA6hSSCFiqjRgTIscxoYzhThaNBGlDKlLzHUT+/Q4eCkoc+riwgvOvAe6dUcKTUTSWltCKqyxUrEMm4liRk7nwMMx8Dw3mgGnPEWPKKfl/tgqtYmY1SD3Vk3r2ONL+FsF61FKS7ZBqrgKuhX8ZDAbi1ErD59/y2gdf/lv3vHLn3+Ls5rD4YGHx3taTlRV5Pr1FmtED2GtjCDXmDmfZ1orGCtd35yLaImcjABPp8B5WdBG0v9atTRlCTEybEdu3rzh+t173HTPm/eNH34483xYMaZ2dwWUNL+QXi/3attTkYqpQM9zMRanNYOWzI2sEXHmn/D4M9IA//Wv+Rdn9l80DH76NbKAXhZV9c+/5l8qANTlY7Io/RggdJkFvO6Y5dN98X1B+9ZXu516/V6FRfGFva+r4S9EP60Ukul20RTQRxqaxk8RjD8ukC4z/Yt/+CUpkF6sXHQVUmO+PjelZO6veqRmRtL6XhwElYaIEJtS0l63EgiilEJVKZOc9d2u2Bd8RJXf1KU7cbGcdHqBunRPekGjNBgh+dE0qkjISiuSy344noghyHHqT10Dy2nm9PREq4llWYhxYY0a7z27a0OlspxOQtwLGV0VGkfNmhQVISrWiDD4S+bpmHl8nvlFfcfNzVthq08Wow3hfCacZpanA8vhTDgdUTExWcvQKpFGUojDw8BgLc14aRUqOZJywlYokRJmQog8nhY+Py08njKx8IqYqxAK1JpIRY6ntQ1nJGGveYdzBaM0x+cTH/7wAyotDEZyzEtJDKPED1MG1u1ADQuqGoySzgpNk2IlFcWFSNWqcNCtBz8ZnPHUrWPnPQ9aLIukgKoGrxXOCGynNLBaM02e/XZk01PtVI9w1q3hlcHVTJ5P1AxejzJrDNJWF3hLJi+ZkiG3RiuN1UZCfGIJC0tciCUyTkJDvLq+ZrOZcM7hRk8thVgqpa1YV9CDwVSNqgVVG2mN5HMknwN1rdhqZRzVqlimjCP1oDFFt0Sh8dainEQPj+NIruXlWjLGdRV2wI0DetyyFC2efxxZb3mKB3738cjnh2dOxxVrNft94mYp3MXKV7cT1oyMzZIbqBplguR0T5lrrGEhLpWS1Uu8eAgRrQ3Xb7bc3LzB2JGnpxPn08L5uDIMW6ZxQ1gry3nFW+FwWKMk7jpmsJXBe7S2+ElspeeYyOcgeSSlEEJgWFaG3UhNGR9XMBajHG9uR/jVhpi/BnXmn/7+gbg2xkHhjcMA3oiTYhpAIaOMnDKjEwZGy5nWpNitTeGGUWAfIDtUVL+viXMgJuFslK7bKDWxxkquGjMMWLvl/v7Ih4cDD4ck8LAK988LAcWbuzfdgZVJtdJiYjAGbyyDl25Y3z8xNidgI2OJMWGM4eH5TE4V62wf8xYmb/nZV3d8+83XjH7AGNjvNNYkDodnShWL5+As1jVai1hn8VUzz4lSE8PohbbZKsZZ/Dgybif84CUavkViDqAU47BhHDdYY1/vtQpu39ySmVH6iLYVZyW3obUCreD9iDWmj1WaZM80caL4YQtGk1qlRXEBbOyWqgRs9Kc8/mwR4B/z8f9Lj3/t8/+SiPCnSNwXZcAX3YbX3wEvu+teEEh7/aKOlL/1RQtw6RcoUVdDF95dRIFdN/BCXkIq+4tSX2kpVEqRQuIiBGrdn8kXz+dLemL/qpc5ziUWuJRMUxdbIS/PpfOKeMUXg3AMZMSQW8M29fp9/be2S8CQLqA7ijL1kKGu3G8IYIaecFiRLoXSknNfWkBdRhj016NkBqiQ9rHpUTIiitKkkHm4f+Lj9x8JhwM5RXLJqKqpvEKZtLIM1mLtBj84GsICP89nno4nps2G9bjQggj05mVlnhMpKZYAS8i4EUIqPB1njucVf+Mw2pNSZFnO5LDSYqQtkbKu2NbYTyO6OYopBF1YTUPrKtY9NM14lgRaJzmaTeb3oQbWkEhNc14KYW3Ubt4QuT0027++n0bSHdKEJDjR2jRWabyd0Er0FjEEjs/PkqQ2eEmSVIppM/D23S1eK5bTgGqK/eaKkuHjh3sOJ7mZaWspRWFMYzc5vNdYo6hN0bxhtoo1RGqYiRZayTijcU7OFe81g/PsN1uuNwZnCk6DUg5qIseE05W76y1zgoznXBRrXntErHSLBu3EPVDy/4+2P3mSHE2yPMHft2KRRRdb3CM8IiOzMquLui79/5/mMnMYmhmippk59BB1ZWZlZIQvtugiIgC+fQ4MURVVM/dwr84GkZmqikAgAEQAZn78+L11VBS0t+Acj2Hh/t/+hdFbrvc73t2+YTcOeOvoR4/baFpXQCdu32zY9ddse49DkWJmfjxSQ6bHgUni3V6KWCk7UFWL98FqKqNaXi/jJmQv68QYDDnH3jlyl4QHsSwU1TiEwuGHT4TaULbntDR++Omef/v3TzweMiGAsgX/+Mh4N3H78Z6Hdzvy76+pbLlaPzftDV5ptBV/+JzECKrvB4Zux+gjtWqZsHCG6+tr3r8z/PD9R/7lX/+du7tHlrkx2YA1jtvbG9TY4ayV+0FVnE4n7Aimh85paW8oQQLDMov8dtGEY5T+dRPhqDRPGGexzuPdwHZX+NOfdqj2BwZv+PDjgRoVVjlUA6sKvVdsB0vfrTLmVJxzjL2jZgnwOYh2QFaKEERB0FqZlClVYKZSEiklGZcujZIzBUWqglDmWDgdHvj+x3seJ7EWbtpQWiVX0bu3hwXfi62wNax8gEJnLc46Ou/EKGcVYNPWorQm5Yz3juubW46HiU8fPpFT4HffvOMf//4f2Iw9yzxx/3CHd4aWi5gmpYlcM9Z0KEQqOZeARmD9hiTsu91G5Jm1Yhw6xsHjDNRaiCUDFaW18LL6nmEYSaXKGOLjA6k1TLfhw8cf+fz5M77bYsyqfdALV6si7V1rrWgPsLYBbccSgpAklWHwdnWPfMvu+grn/4OlgJ+C01eWZ5b6pUHQRe+7Pdvbfi0paE2Y+lpbyXwutisrPD2yri+/q1fbPPfxL/UAzu2AupoRqYttn4NwLaz2ws8kRLX22Bs8yWLWytrTqpz1/tXKAj6b8cp+yToiLyyR4bkzcJEUtHbB1jwTBVeE4Hzc7XwE52RJfjXrCIv02iqqaZQW6LmqiiWvlazGWIXVDo2mFASOU2YlRkqLodRzuwKs7RABhfLssngmLigLzdBWLkVTgozUUgiLsJxzWGhhIZwmVIbcxIBmc3W1cjMUqkKrmZgznTXcvLnm5t17/u1f/51lSiThQDFNqyzuirD0G/FP/+HDwv/6//lnGpH/+j/9kd+/v0JVWKYjeUmYCqaeyXNSmXjjSNpQVQKr0F5BEhGfTEVZhbHiU++cjHk2zRMWZJ3Gd4UOhKDWnpErrRtr14gVmCTFimmQE5jeshsGbreaN7uOXd+jSqHGhO48WsHV1RWaxmw1Y+douRJnkZVtRUyKUqnc3R3RVWHdwH43MgxNoMi28gJapuVCjolkDW2e5XM1iqFzWJNlvFBXYp6orZfv9WojS4GaMrvthpBECCFkTaoVS8EjnNfSzpgTFAvagh8cnbOi954zWlWy0jzeH0jTIgpzuVJbYvumw+8UVzcb3l3/IzebHc5Denzk84+fSIcjpCKQetcRUiTHvLprQipnESuxM25KSzLSKp2xeCuVMqxiKsagnKOmjNGenz5+4uHHR5ZcOZwCc4I5wOeHRqqi+6CQkf/jCT4eMh8fj3y+P/H4eOCfwjf8oV5xe23RxtBZTdOiQKjQOGcZhgGlLA3p1XajCEJ576EqdjdX3D5OzHPk/vMjOUHfdRwOJ7abkZvrPVo1dpue/e0O14E2BqxYCTsDBiHxKQVpWQhxxgRwWloUTVeMc7DJK9xvubntaeUGDYze8dNfP0FJGGVQpTB2ns3o8avcM1WCudaduIhqGY9LKVFKIaX0dE+tayFknaVUYcOjNU03alVUZVDGopTneIz8+fsHPh8KtvN0vWOJEas0u02PUorj4QE7azbbkbHv0CuKlZumIiOVaClizlLDDfEVGIaO6/3I9W7L1aZjmWdUq/z4w58Zh56+77jeb0V/xcg0QUwJraHvPYN3KMRJ0ese7wzjxlOqtLVTCnS9kIStO8tEJ7RSeD8wL49PpOuUEvf3D8Sa2F/vGa92fHx8FCXQPIE39E4Io3a0lFKZ8oJVluahWx0C0QrrLa73WO/w44ZuGBn3O65ubnHjZrUN/9vLb2gBvJzth2cm/2uVQPUqyJ0zyOf84Ry4nyum5xpWMFWp3OXWq1f3unbu07OO41X11M8/99Kfuv5rJX6uwl+MB7J+KRvP4208swvOfXjZ5kqYWne0rHoIevUYOHMAznPUkhick5OzotRZHVH251y11yZqeE/H9JSgSHWuzhnIeZ+UgJzqokOvEOKTUlKNC0LRqNWskpmy3VLPEsQKZS/HEuV/qzXnT7EVBUp8tE1TmHYGWSWwFbVOFTSFImDXC0/pjDZgu57l4QHSCZ0KulqMHSmL9MVA2Mbz4ZFcG9Z7Pt7dc/dwhKQIS+b+GIhFk6slVpHYzRSWJaMdLAv887/NYL5H+xHsyL53OG7Y9IU4TYR0wPdXuBHiPHMMEd/34vg1J2LIgsboQp5Fy13R8J34isfaSE1Tm0Y3i9ENWyIdTYJkEPEOlLDuKdD1ntwsp1OCVY2ypIq3lj9++57rruF1wuQs/ION9LpDXjjygKIQwyJnWyuUqxQic4xUlVEGsR2OCu8GtBnod8M6slYouoF1mM5jS6G0RmfWpDXXJ5ii5gTFoNDkElmiEihzHASmNBZlDb0VXf5TSGy3nu3Y89PHe+YlYr3Gjp5lWfCdZ3u1xXhLVZlcM7lUuUdk6YXHqkhUDo8Hak3084F/+i/v+Mc//ok/vv0GmxrT3QOff/qe08MDXVPQCtYbamdXgx1HyYVYG7nJSGvMheOysKSC0p6u61DNEkOmmUzVhmogAY/LxI8f7/n8mDhMlYdD5OGUOU5winJ6sFA1LOvtxCCXUUMmLMpj4zgd+f7TiT/9eMV//adv+cc/3OCboc4ZqzSqWkH4WmaKJx7jjB8H+qsNyWgihcF73n73DmMMOQaW48xhCUyniPOKGGamWbTjj5NiKZ4+aLZ7S981VAv0zrLddQyDIqWEbh0p9UzTxOHziTgntldbnDKkqYKNWAfWea6vekg7Ogqjy/z4lzvyMuEdtBJYTifMZmDcbeg7AwQeTxMGQ46FloVEHGN9Rr5qJZWMsZZYodkOVQ0xLvI5aEvTjpg0j1Plp7vAT4+VVEGnjC4F0dh3bO0q404mpsbjQ2A+Wjrv6X2HxjIMFuN7jBeYPuRIpx1UWKaAdwND57neX/HuzRWPDw8c7h9WeN3iNNx9+kTXdcR54f7TZyjQdw63Fk2tVFZqN/Oy4Jxj249oLa1Law1916FUI8SAVkqq91oIsVJbZUkyCl1Spus83vakUDkeJ0KO3Pxuz+bmGoxjqZluPzJ4R5xmxu2Gvu+xzjNsRvZX1wzbPdZ1GOexvqMbRowfQRtqZSUi/+3lN0oBXy6XPfmvIwMXr34KgM/9+HNgPvf8z/D+S5j/nEs8v4skCaqpF+u+9hlg7Qw+IwX1Aim4PK7LvXw+ksb6jVYyq6/1M7LwzOp/iUCI/0C7SIgK54xNN9mP59c+/3v59/nAz1yCM8dhbV88vdfzus+KiXI+6hnBQAL5E+5xMVJ5fp0kaCs2oqSqk6+FwLyaJqTA9XRm1QThwKBNw6gO1RLKCTlLIP2EtZpcEjVG9tsbtlfXZOUxtZHjTIozMWZCWsRG180cQ8ZhyWuPMefCkmXqonGe+RWSjbLSlfnhw5H/5//63/jhpwf+8O6Kb/Yj+00vksXdG7SphHBiLgvKOukvoqjWoqukNTXl5wRyTVjP57fWJi58pRLXhLO2SiuSeOneiHJgyTQgZpEfRa9+7kpuNH/3+9/xZr/HlSM1nGSUCJhPM8Z6xt0AVXrb3okyWYgLYYkY7VlyRjtDPw40Hnk8HMlZkxp8nh9BN6z1aAzTFDjMgWVJa4IsFsloS22RlMQV3nvPdrdj7M2qNBeYlCAgDdDWkFNj3PT0/UDMjZYLV6PjahhIuYLWxCwVre89mUpMlSWL6FIpjWEYVlMuI5MbUdC0f/ru9/znf/wT37z5hhIVd6cHwnKgLBWLJ0UxknG2Q4+O6mAxiTAFSgGaJgOpNQpQECOqsjRG5zG5EKaFwzLxMJ0ILZNqYkmimz4HzRIbpWpB64xMf+TVSAlzRjlWwps1lKaYSlmnMhqt3WNqooWJ9t0t7296lFklyHWjNpFKdoPGbwxqoxk3O8KSxaLYGK7e7Pn29+85PE6E8JnjMVOrIHj3h0BOma7veH+45ebdnn1oYrvbG5wxawvP4pwiLcvq7mfgdFo1JY5YFJ3vha8SlnXyxHF9NdBpEU9SeebTT4kc5broOhlBpMq12A/+aS6+NpmYsUpao1pLQVTWYumszV8bNBzoSmxRyH+p8DgXHpfGcSkkRG3TqiqIhpbRO0MVe/POcD+vxYWCmosYesXEPC8YVRi3BmdF09874SdRNcZ44bWouhIWDeZqsw4ySeu2TIkQoORM3/dCytZ6lRlu+FWGuLWyes6oJ/RWJhvUGr+EWFxyIIUoapgVUlyYjz/SOcfN1TW3b96RVeOn+8+cpoXbd7fsvnnP/t0bdOdBa3zXM3gv4kzd6jqq7WqH3qOsp6Fo2qGNp9oOjEMhPh7nYvlvLb86ATjPpwvcedGv/hXLMwrwcnk9PvilgdBzC+GXtn3WCnhOLNZe/vNaPCMML/aAs8Lh83J+3fqeehX3WffjF4EVrdf+/Rkzl+09v0ZfBG65cM4IxtPja0JUnx5TTwgF6ukgL1oJ65ePi/PXWKFPvkgYLj0WzroD5+fFqOhZe0C4CoJkcJG0tVZp6rnNct6HUsUNLE4nVJgxXuP9BtMPBGvIxmK6Kzhp4RmUDlUy82mi6ETFEEgy5GCFu3D+bK1SpLU3f85jSoa7z3B/f+THn0787xvFzaZjOzg2veObt3ve3+wYLDjdcXu9gyaiQEoXmi6UtqAI6/dbZqKdc9KnbAWKoFGqaTrbYYzse8rhKSlrtawck0ZMYiGqTEdrhVIKzmqGsZMqfTlRwhGNWHwuU8C6hWEcxG++W5n+MbOETIgiT5piQ+seZcR0aI6ZpiJTeYBOU7VC64LBEJbIlBToDmMMIWtCLtKvXa9jtCFmxeEwUWZFK5GSo8z8G03OiZwy3g4rH6WRwkKcJloUg5cYI+NmhxsEVVHOMIWwgkvP6NVZ9CWVxrREllikhYChNce0VA6HO5bpEdUyroFl5YdQSU2mLWqtFAzKdnIPquJWN8fIFGfmmIhZKv25FOy8UJ1hSonDdGLOIk/MyqKniZCNt06mZExFhQylEkrDOLlGU5IW3hlWLUXGIXMTE5aPn070LOhwYH675c3Nlq5X9KPsZ+8sne/o9yPDfovxnUzxRJGIHfeeN998w+Mxkoohlo88PERShpQE7Wpt4tPnid0Pnt31wPXNhpvrDd++27Pf9Wx6w9j16MHRSqK1Be8tFZmgOU2NrCO6WKzv0E6Rc6WmiusM7755Q06JXBJ3HxeUAufFglgpLZh7k5E+6eUj0rX2TC7V4kpZxO63tCgTMgWUcuSqqXhCCjyeAp8PicPSWPKa0PN8mxdBJbkWvTNo15PakaYNrShyytQsEtZeF1SzaO0wg2MYPc6uZFBtKKWR0kwmob1j6Czb3mOUbCcugewd02lmniZojc1ms45la7QqoCq6QW4VY520nJSmKSMtsKaZg0xBPN4dCUGIo+eR0M12oPcD1vdstntM13P/eM/n45GoFN/87nd8949/T7/foX0n5NQ10fLGPUnMK2PEnA5FKk1atcrSlKYpR1VGkgKjqOo/OAG4XM6DaeeA8qqw/NXLyxG658ee3ucyWHKOS2dGOlz2+8+KfOopMF1uSwLVy4TlNXKhLtbl4vf2IohebuOJwa9eJSrnwK0UWklj+MVxtvU4nmL518/e5fl5MgP6Yl31vJ2LT+FrSMHLv19u72n7zQgP4+lxg9YrwZGVDLlqyhfpbNJqo1UNysjcf+8w1YEZaUWxIEIgmIFYG4GGch5nRJK51XkdGlJMKZIxtFXdy1glssKlomql9x0OSC2Rkuj2qwYPh8bnh8af9Yxhxir4u28f+fs/vuH3b/f84ZtbbH9LLZHCAmRUDgKXJXEVM8bhaqNYja1KtNBrxlTAWJTrMIg8aMpQlkRN4gJXzteAUCbwRpJLq2EzeFpOhLnQU9FavO6V0eRYOT4uoA+Mmx5r3ZNuhdFC7puXRMyRVhOP08wpLBQFsRYOd0eiWaHrdSyhrqiJUaKbLnBkJca49vkNVMNpzqiUiDbjjRI7VxJVCZu86YIZDPPxJMGiKTbDiPcdDcO0BE5LwGqPao0aIzkuMt+eipimeOl/x1Q4nRamKTAvFevgn//lL2iTeXg40ncapxrWiEKfpWFppNgISdOKaHVULTK/rTZKzJxC4HGamOdCFL0UKpBi4BQDGchNZnrOytsUufHpisDYJPl6r4SRJ0OmMx9nJeScPUtY22y+V/SjwdjKNBe+/+mOMB9o5S23t1vRjnA9ZjDo3kjP1iqWkjHOiWR6hdoa3X7g3e+/oVTNYQo8HD5Rm/AqtJUk4HgHnw4R9zEyDg+8eeP4+PGadzcb3t7uePvmiv2mp7WCMp6ug0ZiXgJhjhQiJnf0G+HHlFKpueFdx7Dx3LzdM03XlPSJFBJNV+k3K5l5Px2TTB8XiCFRcsGYRvEWYyq2VqoSXpC2lhoyyxTINVOVIzfNMVbm2FgN8DDGYLsqbnfrrcw5qdS73tBbTWkKZbaElIlBxnZLqSzzhLMVax2LyXhTodfSwtQNs1o3ayVWrm1tfxlthVSnDUY7en/Lj+UDnz5/ZJ4yw9Ax7rYiJEaitShIYEq4zj3xsGqBUqQVfR8nptOJ+8+iRtp7izbgu8ZYDTFmlnAg5oq9uycbhR03vBk73vzuGzY31zQvVb7vO/GUqYKeVLNaqFsHVq8OyJWiHVVp4cGcR5KUaBRU/R+cAJwhZcUFVF8v+vo/Szo4O+mdg/DLZ38NivAcCC+q+rVSPheoWj+LDSl1QSZUcjG3pxbE01ZfBccv919gnfpivZ8XPXq5nKt36dubF889MRn065HB5zUEmfhl5OPyOP7WxMXX9+91gnDWN2hSKatVgUCdtaU1uhm0MWQF1CLkQwzGd4z7G968fYtVCxwtn3/6wN39iawg1sTD4RMf7x+hFm4Hzd41DIred7RmmHMh5kxARsu0tmwGS6mOXCMpZ7rNyBQzKUBtAruX1sjrKJoYQDVIDf05kdUjp7kSsqHpEacTuhRaDpSYWILA1Ctp+cuECb36IIiyWakyqz0MPak2chYYdCkVhRWWfSoYxJK6t7DpNdutCHvsO4utHa02lhQ5nQKH08K8BN5985Z+GCXoKM8wGrSzDDHz4adPfPj4uELZlbnAwzzzcIRipBrVuj5puoNGK02oFaaZrhPyZq1N7IYVdM7iBs/YNUzLlBIJQUYTe9+xGQYZeS2FmkVBTRnHEhPKWPzKUF8vMEqRiirGQGpNKiUcSyyEVDhOgbBUUpEq/dN9xfz3D0xT5s2bPdfbAa8rNUYsYt5DLqhqcdqBUoSSmZeFmJJ4289BKvvV70UpDdpSgGWVLm6rmVHO0lmzXmGrjGia9RrqrQSurBQtF2KrpAaohnWrpXUtOG3EXEYrqlE042gG8iqVHELj/u6Et4bd1Z5W9aoPoGglkeKCHQaUs5jaaFGCkht6rm41ITTG7z/RjUdyS+SMtL8MGC+aEzlAiAgEfvrIx4/3vL3Z8O27R97cXrPbOq63I8oIuTfGKH713kNsxLagi7DM+6HHexkndIPl6s2elBKPnw6UnIgpYp1GFcXhcZE2HEYSwtrQJhNTRhuJiNaLjLE1PUYnakuEkFhK5ZQVh9PCEiupaWzvscZjVpGoHCMNcAaG3jL2Dq8VhYLvHceTwP2dg3leRKKaBasyuka8rcwOao546/DWoVvFG1CmQROicmgNby2DH2XMb3DEuOPxccv94z3Hz4F9KVzvr+l6RauKVIoUIStinLOohcalCCclRObjkeko6JZWBlsr+/0WoxxKK7yzGN+RgKoU/dWe8d0NbrujOidfYOtoxtKMQWmHNj0oTdWGpvWK9iq0k8RIxr4NCosykgg0lPDjfsXyG0iAZ6j3/MivyzBY1ez+9rafl+cpgt+yb09/8dwCkCTgRV//4jXti9eeX3/+rb1IWF4jAK+rcq31xb5fJg1n8Z9n8uPlOi+Tiktkor1MJP7GCXlBvvzFNX95uSRMyvSE9DQrAgA8ORY2GXFryqB9z/bqhnB7y3L4nqVEim7oznE6Rf7tr3/h336cuT9Wxh7++Mag9h1X3tD1vVQVq/NiXis5ZzX9MKDoROlQKVKrpGWmloZxnlILMSeatTQr3tm1BkoutHuYl4nHw8zjQW4YGw+9BtMK3ol1sTYyB5ziOqtc1+SvnnkBoNSqfFYbRmt674kxk02itIozloZDtyaoQIg4hWiClwVdMzlWdNdRWyMuiTkEjqdJ3P5yY9gsjNuIUh6lLV3X0w8DxlhCrnz4fASr6bcDnx5OPMyNqmX6S/gHokGgAGdkpthqGTWtEVQtGKvofc8w9DJidk7kEc0BpRLOGIZuECGaENZvgSRIKS2cDifRIDcWb7R4yZdCplFSpuSGWu1Xp2lmiYWqNAWD6S0GYe0bEznOhfbTI8uSmW/2DE6jSsJr+fzTslBSETXUpFjWajaVQlVK5GCNpR9FdbCtF9iSEsY79s6Ti+LxOPF4jNQivJakwCsh+zUDWUvro2rpy7ccKXktcAxPWiaSEDcyjawMVa9VmVbkKi6Cn+8mWmtoZ1FWs7cjnXOoKu6i46YnYxAqOTjvKE7m4sfrLW/fv+HHH+74dBfISdrZktUpSpGbvm6FKTTqY+O0JKb5ntMxcDhF9qPjcd8zjhpDwShLK5nltOAcWA9ZJZlOAirSz2+6MOx7rvKeWirzw0xKgUOScd6ckSQSaE3TmhYL3lJQqtH1llRgCgt6ycRYRAUvwik3HmPj/lhIBTCSqFqrsWvroOQ1CdfSa7em0TmDtp6QMq33DF5yTt0qKc6k1FimhFGFflYsptE6S3NJyLBGrzoucu9OKYqK3jo5svF7pjAz7kd+//ffkVrl+58OLLmQVWPse2rM1JQEgleepjw5K6YpcjwuhCVTcqXmIgmMdTJCqAofPz4wj4r91TWd8dwdThzjgh47dqPn9+/+Z/xugxkG/Ci2wwolglWlQhEnVmWeR7K1MTI2vLanZdhYo5sGZdck+D8YAWgr5H4ZJM4V9y9Xw2vf9um1PwdJv97O2lpYK/92QaJ7LSZ0GRxbO2/nghsAq5zu5dbXfb8Itl+iAIqzJO5zsL44rlfHdIYNz8tzhb+2Lb4gDb5+v3M7Y61keG4f/Bzy8Gsr/69pKDy965OJkgR+6WcLoa81gdnPx9VolFZWhKWtfVot2Wo3ovuRuRbmmrB9z2gGPjze8fHjzMePVQR0EkxdoWyg856x70QSOBWMk/5sadCtKlgNGL2hDJZPDycR2dGaqNfBSys4qTYduUJIiZwKJYiimVUNZxaM+sCuNwxGiD3Xu5Gbqw1NGfJ58mGdNXYNbK6YLLdIpZQEzCqBDQVj78kpkmrEYShVzqNF4MH9Bt7sFRtrOB7uyS2i80heFsIUhLHbtCjXKc3pNHF47HHO4jrz9FkbZ7m+veXd7wPN3aN8R2oV0y1oo5mzlvEsYAmB6VSJSyWWRqmZzq2OlxkGoxl6x2bscVrRWiIsmc6yuj86OicjcymtynBGU7Oi6ILWmnEc19noSguRMJ1IKJQ1qwNcoxmH0pZSAik3UV5s4lypjaeqtX1TGswQ00zKmv1GdOe9aagWmY8Tp8NECpWyJjhniwz5pxgG2abSMp2CamzGnq4f2G53GO2YlsjxNLMskjzcHw8c5sDj1JhSE8JqzbQs14PRUpDldfzXKNZWwDqhpBqxVGKFWDSuaqIRUxudK58fZqr+BE7kuW2vsF6EdlrJ4itmDM5adLXUmlAO+m3H+9+/4y9/+YkffnwkxEbTlpwbsTSWpFBGJLhLzquozLlvXtAfJw62cv9ZcbX33F71DL0T0aVTJHvwvZw3UUXMVFVFXc8pPE5cLlPFYjjeHTk+zpQA2myk1QdP00wVTStiUGWctO5CqrQYibEQQmaeG49R8RDhOEsRoWnUta0nULmlVQVZxvdUS9RqsM4yjh35PrAdZPxuCZHOafZbs8qyn+/dmpQaRldUS+QQ6HuP62QcVFmNwZJbWZHDQlWJKc1sNjtu3l3TjEH3f+XhMFGdpmlDVoZYQRtPRtOaYQqJz/cTh8NMjgWrNd7JrL4gRDJ+2nkvI7fG8nA48uHhHj12/OlPf+AP//RPbN+9xWw8dhixfYd3kuG0JYppFEbuz009KbA2Y8WYrKknl0OJRlpEg5Smmf8TEIDLcb9zcD4Hq1rLFwHmHJtkMO5lgP1a4HrJ0n/do//6/lxqEMhrL1+zjuJ9QfTjad2X+/G1JODFu75Y7zVS8SXH4MKWsWl4dcxfTTkuAvXZRfCl1PF6ftTFo+fzxs+ftTO68BrFeE7sLuyIz7JaTb5UT0lSW1XytBAENax64Fr0ANyA6kYYBjZv3pCPC+HzCa01u43ldp+Y5oZV4JrGGUvf97jeU5ZAs3JDKRQhFZYqdpitUFsSeNs1rsaBU6qkJQq05p0Y79RCDoUSC2plIKcM8wKPh4hTmtApet3wVqYZ+nGDbpolFryx0krSmqrAFostFdek4nvqQq0N/03v0YyU3MihQi4YregU2B6+uen57t2Ob657apxJOXFshek4kWJkHHd045Zx3BByYJkD8zSTrrYif5rFKCm3Sj92fPvtu3VsUmR1d9cP5GLohzfs92Lik1Li08fPfPj4kcP9kXmemY4LxilabmhdyGmmVUvXD4y6xxSNUedZeSFfKRQpJ6wVu9qcAzFGnOtwzpFz4fHxgLJOCHElo7ShKrVKRktS6HoNWUhL8xKpqqCMyC0719j5nqI1NUUOU8XaRrWaRGWejkI8DFKJGy293VYkSOckSbYtmpAF1YGCdYbb21uudzucEwlvWiOXSlgSUwws5Q0fH458+PzIx4cFpkIJlWpFXTOHjDerlO2KqhgjCUhddT2WJfNgTuhsyQ7caNnbEdspSjpyOGbuHyZ2x5l+18k4o0mU4yOm39B1g7TcKISSKRSs1+yuNnz7+3d8+PBA+vGRaTlXzZ1IluuVI18LqohsdcqGkA2f7yO7UUswLQFdoOwczspoYkuGOS/kUhiuRobdhnEcya2sqF6h6z3qSqOrZj7OxAjL1DA6CjcEMHY1otGiCNhqYYpHxk2H9yNd19GlTHs48vA4cffQeIjSwnAddNpgrMU6g9WgjUYrRwlRznONlNRQTbhCRjWcFX3/uFS81Vi3Wa/xgLUa7zZoLaPbOVdKiVL4WYM1GqctvvcoI1MMWC36H16RKThvuX5/SwDiDz8Qlsj9dEKlzLI0nNeUKqPgh8PC5/uJsFS0AuVWiMhIwdBa5jwVlrK0YZYUiQVudjve/e733Lx9R6pFWkfzCZOi3A+tpa1aLdZ24kaptGh1KAkCouWi11u/3Ji0ksTd+O4X2ssvl98sBfy6BfASGXgdetSXAe3icXgphXtezsY451E+pc4V9Mtq/3K5FCGSdeTk5JoEvn1itL9c/xm2f37uOamAc+7QuAzw675o8/SciArpp2M6m/5wRjEuKviz+I8xa4C/OLm1VkmYtHrKDr6wdlQXCdRZYUhd/PwiwD8/ddm2kMpB8xpNabU+ZyZP+34GoCRR0Eqt5D+BxJXrGHe36D/8PYQfufu3/x3dDLvW8S54ljCg2wOfPs1c7Rx/fLfh7ZWn73vQsNRCBmKqeNejrVSLqLP6okCD11cblgpJVzZanApjK+SQ0dUwGrFCVU6JcEZZyTpVVARbqkxUegfjkLgpirHrGbaNFsV7W0xdKpQsN0QnPeiMiK5oJToSvvN0zjCdZkKumM6QYsRq2I1ws3Hse4OpGVUKvfecjgce7gObTUdTVnrEzrNMB1xnqK0xTSea7hjdSIqBmAIqWVCNN2+v2OxGxsOEto27z0d6X+ldZb+xKCyjf8ufvntHbZX7z3f88OMP1JRYjhPTcYaaqfFAMZnie8x6Q0lIEmS0ETU7aUDTW0M3DKQopj4xJ4F2a6EG0XHIqZBLw/qR3bYjozkF8Tw/TJFTEAa+ceY5Ca2WJVtJMpwj5MLjKZOdpIE1K1y3YbBpTUzP0xGBEiWpMKtdsTKZrjN4b9ltN3TeEuNEq5b9diM9+FV+udtasKMIUS0LMTSOywlNxWpD08I+D6ViAbWi9TXL9WxWTYBaYQmF+1g4VVj6QIqFd1cjVhsGBZ/vF7oPD2yvNgyjJx4WOtuxu7oh58oUTwz9GrhaplFxHr77wzs+ffjMx48naq1Y54lVPBBKkSkhYw2VzJJBIUlyb8UevJVMCYXe9zgDgbwiYVH6xzWhbKAbpe+OFUJePwz0bmDSEyYrlquZ491CWMoTotqqJhZoWqG1F238OZBL4yo3vvvuiv31rUySFFB3YeXP8HRP1Now9J6+c+QccEajveU4Pdtf5xyY5gOHhzu+ef+eZUlYbfjm/RumOfI4zSxhJdeOW65uvgUy8/SAUoXSElMsFB1RIbLdwtXVXsyIasV78QRROELNmFYYd1u+7b5FDY6//uUHPv34ibY0NsOOWGQcNOfG54eFJVThlLiVFK8bm+2ApuB8wyJCbSkHlphpSu4Z43aPH0aaXgWRtEhKtyrSynVFuYSbFFY5YFGcPMeV2io5FYz1OOdoVaG1xbkOoz31P1wH4Bzc1auo8vTgGnsuHpG4cRFFz9tqL4vhL1sIvwTLv6y6n7d3kSCsDHz1JLF7DvDqKT5+EQzr88k9w/CyvV/OpC6Rh/Oo5PNzq1reK17Aa8Ti5ySRz8vXSIgXz37x3M+RGy8nAL76Vm3FTNSZ+6AuPk/9lGu0WlFmdRbUZpUQNtAV+uu3XH/39zzcfeL+0xFdFNvdFb//dqBzW97fLlxte97uPE4Hal44TRPHJRErDJstS2zopnBOhGpiTJRasFbG3XwF3yCqtRqrlWIlaHfdgNtsoDWMUhglxk7eioVraWJYYp3Mz6bS5MI2FkyWI1WaTnuaVhSjWKKoB3jjKE3MjWTiQWHR3Gw6YpqZQ4JScQ12Fm4Gw+3Ys/GK0W1IYYGS2e7EwOM0LzwcFqYU0F7TrcqMISbKsaCMSAPPy4QyhmHcstsOOG/FE6oWWqksxwM1e1ryGOsYO8RExPe8vRn5w++vCcvC6eHAfDoRl5k4L8ynE/MpkLByjpxGtUJKCk1BNTm3MYmoTykNYzwYIStZ7UhIUHKu0EojVcV0WnicA4c5suRCKOsXSxlqM1CFuNSagVhxXjP2HbUGQqkoJVKvm2Gg750oLlfxumBZiK3KMEoVNCDWim0VhyRQIQYeHwvj4PF2IMVptaxuVF0oFOZlwdQFT8WoiNeVbWcIynLKlcFZ0BmlZJY7l3USriL9WL1erw3i+rxegPsF32/ojCbVQm4zsQZJ9tt7xquOGjPpNKFXC+mcIzkHFAXvNN3GMz80+k7T9wYzlSf0VWvEobRmSquotu5XgZQy0YLXFrPtsYOn4TlNgVYyna2rTbJGV4OeC9Mx0JSiGzsqkFPGaYezjjbC7mrH7uqBmBbmo4jaxFworVCaRTfDtFTuHhpzhG6raEYSwIrCdJ5u9Gy3CTIsUUaIc4zMc8XZDX3noCWUaQw9DD2MY8/gNM4acoj85d//Qt973r7/HVe3V8zff+Du7p5UFQ0RFvr+p0f0er0Pg6FWTyuRVNNKkk/YLuG9FUXGrqNSefx8xzBsUE4xp4C2njfv33KYJv761x8osVHyRG0aVGaeM8fjQkrgvRRyVldcJ66qWik6LwWhM4a+eYqGkiLee4yV9p4w/c9tEIvRIm6SVzNRoy3WSHuwrXbAKL2KlxmU1TjXraRXQQxaE/TtP1wJ8FKi97k6PD9XXxDs1lgigRb1Io4/SfS+GnF72rSC52pcKs9aXgbQ55h2Kfurn4P/ix1cofj19+fAd17nkqHfnpKbJ9TiIv6/hlVeB+5LBOL5Pc69/OflJYrxpYHSmUvwmhT41X6/4mWL4PKJV+/5c88/JyTre1VAXSg9rq2eM5qh1tdoJS0COXZQdsRubth+83e8PRyY7gN3D3+hzDPW9fzdH39HzUXMU/KJFBbm+cApBI4h8zhnCp5lyVDBdx5VIazsYO0tS0ykJsx/gQVlNNFo0WHf9R3DsCHHTKtFLrZayHFGKRl7ShViLuJHngudE0tTrCHXJDCnIK1Yc04iFIo1NZdOLrqAR3E1ekJImJpYolSIN73i7dhxMzhGZ/DOc4gRug21Wh6PE6dpEQIgld3Vlr319MOGfhDhlLZaT9cqktPWKPw6w9x7x8b3OKW4Vw9YXQnHe5r3+KGn1UgMDe8946AZXMeu0+QwyHk/nTg+esKUCHMmhEBMkVoymiKaj0pubkppjBMnP+N6SlPEJTKlBNYQcmGOlSlE5lg4xcRxTsy5UZWiIPKvucm9QgHKaLRxxNYIFTotTpvagO81FI3rHJITNTrnGcaeJQbqx48cHyZwTch3pQjRkITNilQNS1DU0qPIpKDYb0c6Z1Atio9FTTgynW10ptEZgadjyZArzjpK06LwaRQy7bWihs5gnEDwMiEhxktzhTKDewjsOs31zmOK4fEQ+P77e8a+5y07XOc51k/4cY+ynrAmsUNnsWhCmqEGxl6z3Vg+P0TymZDYQCS6hRx2bvXGAiki0zl5JoWKUSL97M1ZehsSER1Ae81GaWxfMFamR4zTIuxjBUG11rDdj9y8v6bywN39RIkilpQKTBHQljlE5gRLhuNcWWJlpzXNGIy33L7d0+0Mh0Vz93BiDhO5JIxqdF5zczVCS5SsmYioKhoNoMk5E0OiZaBLlBKYpkfm+SQ+J8oyz5X7wwH7aabzBu9hs3F0nViWt5BAVUqZyU1ze71nsx/Y7XZU3Yi14rxHKUVIEasV42bD+29uefj0nu//5SemeRaek4awRFFxdRIflJL2QNeJMZehoXR+4UuQk5jzdJ2jlsx0PFFiZNxtaNrSlJOJCG0FATEabzxg15baqjC7+qkobaWNsfrDKKWo1VCrphoxQ/o1y29SAryMIZdM8V/qs9e6Jv/r+udM9udn319W979mv2TfzgHsDLWf/1urWLUew5kV+LTnrDD6F7AEvGhf8OL3M5pwDprPx39Oala97MZTIIXnQPx8Pp6PQz3BJuc9e9lyeJ1gqBVy+VIF8cuA/xzgn476xTZE2+H8mSqp/s77p/TT+7YmkP+5+dGaknlVpWjN0FQPww3v/u4/kw6BPCU+he+ZDhOpVTpjKPlEmR9JyyPTPBNLo2LQ2hNjRa3jlykkCYJr37MViFHY5m21AK2tUVd3uM12ZD8O1FKY04mUMp136DWB8b4D02gpPB37MPRsNwOqRpqptKaJJVKyqL1pxBJUCHsKnaQSbbXQcsZoy8Zr3l719KYyqQUHvNt6rnvLoBWmVmoUdrxWMtJ4mgKpiiQrWnqbuTSpKjohI8ZYyOUkFR+VkzlQc6GUJiYz13tUadRT4HicuP90pBs63r17h7KGnBMlW3JMeOewWmNMpVnYbnt240CrhpIUMUZCmDkdHjk+HMg1o61h3O8opYG2KOcJBeYQmKaFx9NC0Y5QGiFl5phFBbBUUXBUGmWsKKatI5OVirbS780pk0tejV8yg1HYrRediaZItdBZz9g7xk3PbrehtEzXG443EyUpcd6bZ1IMpJiZlsS0BHoPIQYeDgfeXA3s9v2KDkz0/cCmd4QQ2XRCPDzFxnxMqFIQvxUj8L/W4oCpn6OtMgrjheMgo39JZJirYmmNv3w+MhjFYbLsukZnMjlGtn2PMeB0RXvN9XtPv3WrWU6hOSvjynXGmcybm5Fv3m25fww8TFCUooayjt+u1+/KWWmtrvwcxTQ30rKgasKbxvs3I32/pdWFnAopBFpoYC3dJotTpanoJjbNpVVKyuQSMV6zv9lQSmP7Y2I6FfJSaVUxR5GoTqWKKruBD3eF7U93dGOP0Zk5zHSjp9/v4HNimcWquCnLMHreXG+5fbOHlomLxdTI8XAiLIuQgI1lGDw1Z7bbgVoi3//wPR8+HSnNkovm88PEcRKnQmmtJfrTwtW+p+skyFkUKQROp0iJVfgvfsR0mr7ryUUEf8xq/RvjQt85vvvud8Rj4uNP99A0zntqk3MUQ8Ea8QbYjp6xNwydRaOoOaJUJeaA7waM0zjtKEpxeHjg/tNn/lj+Ad3EsTalQiELk381nTsbuz0Hf7XGKlE6bA0qBqc9KCOv1R6UlQ/jVyy/QQjorPf8teh8Gay+9tzr6vvLyvnL1zxv9+yAd7bePVfIT2s/JRVrMHwBX+uXEwCv9r/UV8HwdRLQnn89Jy6Xv59bCaIZ8FypX04NXB7e5fz+i+M/H1N7+fqvwfUvUYb2xfPnx782ZVDrc/LxEqk4T0VInwt1oYC4IhlKicqhvjgoGY/SPNkh655m9/hd45s//RODsXx+85Y//8t/58P3P3J/nEjTAZ0XVI7MUxZYtdvRecs0nzBaZlxTFDUxMVeSKsn7EdUqTq9aBDlT83l+WNNUZQ4T8zILbKYbRhusVuSaRRe/ahEI0Y2h8/TeiqiIM7QqGt6NusJq4LWjoUWVj4pWZjV6Au8s2omt7qk3zL2I2NxuBnbO4IrAtxXxBEALKQjt6HqHNppKI1fF8Rgw5oHGns22B9UoIQKFmCPLtND3J4xxqD1sNobBWd7e3qIKnB6P5BA4HQ5PLOC+97Qm440aK2melkTYOQc4zCi2uVrBdDzwcH9HDDNaa5Ylcnw4EFIg1yOHYxKDIETFLbRCbJLopwqxKSKaYqApI5V/LeQq57MBtRQx7clFJGVLppZI7S2db3Sx4XUFbdnuN7y9vWIchZ1ujOLdtzcS7BA1u+k4s0wL02nm44fP3H18oKTE52PGNNjtRrpxgJJFL6C3mGrwWlz1rjYDp6h4mB+xqtE7TWzr6KNe4VaRApTLVIl9sh96MgptE6c5EFMTAaTamJfC8ZgYFOwHGD3kbFDVcvj0gO8N++0tZtyhm5yTUhI1J2oMOFO42nbcXm8Y+gfuDpEcpYnu9MW1qrTsoxXyrNIGhUjYHk6Fj3ePbEdN73tRHzRWjKJKZjoGtDnSiqJzA9pZWlrp2ustyVjNsO2JsfDdH6/58fsTS5ooBYpqTLERksScBqTQ+OHjgW60bAZFq0GSvqQIUyAuR2qOdINmO1j2245tL9eXIVG3AzkGNOB9z9D12O0G3Rb63jHHQs6RVESbo2KIRTNHkeouWpFypY9QVMKdCqNRjFajVKGR0FXT+Z6WCt3oUKpSqKu1dodSoFtBq0rfGb759g1xWQix0fce33m0NTzcnbDGyGPeoVWlViH/1VUaXFstXPAqSjqlVuK0sBxP1JiwTdGQ/r5qorGgjMZo0d0ppdGQz1jgBrGcb2i0ddJGsj1GeUpT8pxyq3na315+AwJwloz9Wk/8smf+XK1+bb2/1QJ43t458Fz+g2dToeek43IS4BkOly+yqKq1FQE47+Pze5YiN7OnKcvz/l/sy8vz8PVq++eIiV9fJBC/OIYXr6sX2/z6B3kZvJX6pfd6esWL/Xr5+nOC9pxgyQQCqwHQs1GRFpckqbrP5231O29aodRAUwlsZvvmPZvOcnOzZ7ja0F8NfP/n/870/R0tLfRW0Q0OjagGnpbCWTJKvgOrj8GaADaEdGRaQxmDVopaghg0aUgrV6CurHlrhQFecqHVLFC60RhrsE2mEcx6M3dGQSsYq/G9A6NQKhCTtL5STuQwQ9N4b54cvoZuxDpHyJneVpIruAabzjEYhSqZVJpUDEukqkYpDd93YC0hRlHOq0JW1Nqwv7qi70ZQmRABRIgnzoEaq8wKFygxozBcb/e0JOTSOSxSzZeItVYSFq2opYDzeGsFFs1V/NxrpmqNa46u73i7ecvN7RWn44HD8cD3P/0znx8OoBwYw2kpzDGjrSI3Q7WOkkWuNxbph6dVObEpTUhZWOJKxgRFMKiSSiHU8yx/gSbSruo+oYrld++uePP2hpvbK66uNwyDY3e9YRy7dcyqnv0uSVGso0tqfPrwmR//8gMPnyQRqCGyvd5juoEaZ9ww0A8D8TijWsYoMWryRuO0xijhjmjOjZ4XuOJ6KymYprCqYYwjdYopV3IuZKWxGgqzCA8puDEwjgP9sMfgIS3Uljh+viOVSjEa5w3Ga7RuZFXoraL0hu3GsxkcEMhZkm+jDUYpqbzXhN4Yi9EOirS9vBbRmuMpc/fwgHMZZxrOWqxvtKQISyHEB1IojP2G3veiyKfBGkdrBaUrnbYM246rG8XxWNAPC3kReeamoKAoqaEt2A4yjcfTEe9HdjshW54OB1Is6CYiWVSxb1YtAwlrFFY3hr6j7DeYqtlsNhil6b1hN244nO4JccF6Rz9UDosmpEKqkgDUUJhTROYqNJiCVYnQGvQW76VNHKfC/acDqhS2+55x06EsYBQtJ7SS8WSjLNlrdvuecesoRzFS8p0kCSVJoiVtstU0rlacVatPnZD+GoVpnsmlYLueoe+oOfLDv/+VYX9Ff23pXE/V5ontr5BJjtqUkM2VfCMbRiB/7VHGoXRH0w6lHKppGQtsBv7PSAAkyL4mul1W6y8fe4KsL2RvX6/7evki6J3xey4q6RWePiceWpvn16x8AHnVCrPTJEC1ywr+deJxnjR4Lfbz+jifl0t/hC/Px3Og/RKOl77RGVE5s9zPB3yWV37++/X54dV7nlGI9pX1nvkUl2Oc8sL1XL/ev/W/dpl4qaczKe9V5S+1JiCVs/GHplVHwWG7EfKM3ozsv7nlGwJFByonyoNiUIa2ANVT20hpM5vNSEwRlRXeG3KGkBulKYyypJhJNHRVoDUlVXIsYBSFhtWicKaMwjovSUAq1BxxWgxHdK2IS3yj5ITVA34zMk2P6/HrtaQRbkspDa0q3oIxlqH3eOuxxuGtCE5VVWim4b1Ax15rVC2ULD7oxylyOi00Iy0MEQMSBcAGlJooVfzMr44T11dbrAerLZ3v8UpzzIWSMrUq5jKhimZ/dU2r4ip5dXVNnwKf7+6YY2DJkTkEkQO2ntobWpNSrSQZzVUNrBUTnTYLp6Jzhn4z0AzcvLnG9T3DZo9xHX/560d+/OnTk7pfbZlUlbAGNGINWypnv4ja2iqdq56+100pmhLTqkKj5IYxjT4l0qnRacXVP/2RN29vePNmz37rsQ663jJsexlTs42lRmzXUbKiFg3Fsrm65ubtW+bDibuPH5gf7xmdYS6ZWhO2c+BEKMVag7UKVs8JsSwv5FxEd34thZ+uggbq3KorhTCLh0Uo60x+A20tcYmAwtlG38HuyrC/eoN3IykUrvY9rS5MDweO84LpPZvdgNt0eNNwBppTWF0YesvVrmPTz8RYSEkIsmgt564WaYdZYZy3nKhJJHs7qzA0Uk4sYaE5hdEDrUkwKbUQl0TJR4bhM845htHSqsV0MgaqTBETHqfYbDxv3l8xpUooj8xRJJ07LVLdlUbXg3PSmrOdZ399RQoz8/FRELfeComwVnJKULNwTZTEGGsNm3HEactmM1JSwXUKpRPWKXZXO0bVM5dHPjw88uk+cn8QPYaUGqmKKmGZ5Hs4dlIvZ6vonEUh0t/HhyPUiGIruh+dw3XrBEzOhHlCG0PfWdj27K82pJzRZIwRie5hlPuRJEoGow3eGfrOEGqiqUaIEdd5jNGEuEBWuGGkpMT3f/0zV+/f8W7o2AwjRa8t3bJOfqmK0kICVMqsYmhGCIPO01a4vzaztqrsz97Tf275jUJAayy4CKLnn7W+hpSf11WcBXwu++ZftgBemgw9/1M8B9InqP2cGKzbf9rPp/flsqO97pV6gth5Sk54CmJy9tvTc8Dq1/Pl/PzPBf0vphFenI92sY5U0evZuTzTF+davXj10w5d/Hz6HM6Jhnqq1dfHDU8rqme04DKdefnXy7HNMzegtmccYLUqkk9m3Z0nGmirazasiEVRm2aujQDYoePm7TUtfMvsHG1OZJXJC5QQUKpgvUL8WDKoKvAXiK+5quuNBnJtVG1IShGQZMytroVqVVHOWQIwrWERbf+2+tQrLUY9MSeqgqH3tNYzz0dUqdCS3MgqZN1ANawRo57OaQxNGMbTIpB2azgtkKlR4mxQamNOkdOcuD9MLLWhasN2HU5bjvMkPIWhI8VKrpHSCpv7nmFj2YxuhUg7lpZYmhCQGgnX9WSXmScR2smlMmw2+DYwhcQUE9Np4niaMM7h/cD+qkOHzLJIsJJmZuVqo7miQ7WA04Wh03ROsRkdf/jjO3Iq9MMWpTqsMYTlxA8/HUW9MQWSlIxo49BaU1ompSi98/V7qbX8XpvM1q96qbQGpSRigqBhaxVvbq/55ptbbm82bEbLOFqMa6ALpWUwPTgxS3HDFq8cMTZq0Wz6LW6zIcfAze9uCMcH4vGB6XhHnhpaVyKJQCYrML5jPiw8HGZiFifAlBu6N1AypYrxkUYqM70KZMWUKDHTdKQqjU4Nm6X2bLXgLWysYjPAOFq6zqy+IEUCNZBDJIcFlQaqqqSaUJ3COUshE1sGo+j6jsFqpnUiQWkhUhoF2hrRhXBGikQtyIBu4L1m4zTeKSwWpw0lJmoVqLo1kdCOKfHh4z2+99zUPU01bIWYA1onul7jrKYO8P6bDbUVUo2gAveHQl8hFkUuSpQv8zOCe3aELLXivCSp83Li4fFhvUfLPVkrg8JgjMYPdg2qhXFncK6i6sLtNxv68T0PJ8Oh7Pjn7zOfjw88zICFYppMxyhoWVBWqwzFV6JqeCVIX6qFfMrQEoO3bPoebxxWOUzT5DwTwiJEVe3orOXN1V68J04zJU+CHCsxT6JmmQZQStwjW0X71S0wJFFT1ZpuHGhaUVUmtUBLCm0y2hS0Eel1ZTRKW87aKudrqK31qdJK0E9jaZj1/r4Wt7pi9doq1y+ixs8uv4ED8CUcfwnnv37u3B+HlwHsa7D2Jbv+PMPf2qq4xZng91y9t3a51S975C9a+UpJj+3S9Y41HoKQbhRc2gWfEw+Z2Zf52OcK5jkZ+VoS8LJCXzO6px28SDTW54D1OM+PP1f0X2u3XIAgT4lEO///3Id5zgQvgvnrrZxf95SoKKCdxSWeRSZWaReeMRU4KwWetycdgxUjqKJ1PRcoWTFXzbJK917fvMHXxuequI8fyVRyy6TVRSzEsFqKinKdVmJJWqpk986JE9fu5pbDEvjx7o7qRCBjSZGcM1oncc9CkAqrNaN3aPd8sTQg10osWUR+rMV3nlIcqLZOAyRyXUBB5xWd6/Gmk9GtJTNNC8tppkQZUdxtt2zGLQ3NFCJTiBznwGFamEpiCYrNrjFsBuYQaK2itYxelSKfd0iR03xkXkY24wZnO1I4EecjrNXdHBImFlqznJaMtQ5lDbZ5jHFsdztKU+SmmZbMx0+PKBv58T4wh8a0iGhPq42t7/jdreLz/YRukauN9G69TlzvBswqkGJVorXKbjS8u90S5ojWkXqCUis1VrKpopGeq4wyKZmT1mf72KYoK6mzKPGAz2d2epYb+O27kT/+4Xfstz3bwQMyQ26NoynILRFyoDZNNQZSpesdbujQxmONJcXAdHqgi5rNtWU5atxDZXqs5GUm5YLqO6ZyYoqK+9PM3WFhqZ5UNLnJDHelyHexZunJKkUzGpoWn4Mq14VvZb2ORF3OaRi9ZuMNvSuoVpinR04nTW80p6liiKtYjShgZiSoquZQpqMaMIOj3xjGcaCzBpWTKLyqhlbgV0Mp3xmMUZSayGXBWXCA043BG7yxUMUkRzWwWnrlpUqxsSzw8eNCUx+orWLcLb5CLglrCroXGL6EgNaw2cG3325orVApAk+rjlREEGpeFnLIHB5P5BzQNEIs7DdXvHv3jnkeqIi2QymNsKR15M2uhPFKiDMpZ8bdFmsr3il2Vz395opDyphOs9SOQ4SoZVql6kpeG5bi86DJyRBdI1DpdBOXPiolN8KSmY8Lk1/wtiNOCWXFe6BRKDlSa8AwsOl6bq92qFaZFyF9CtNfFFFrSSjvQEPIC0aLRPVoBu7uj5TW2N9uMb1jSjPaZDZXA1dvNvheU1uitoaxHdrIuKxwqxpnK3RRX1QrqXktqJGxZVEjaiizilX8uvj/29wAL5ngl4/BlyNycFElX1TUr9GB88+zeI4c6DlgFblArP353vsrNOGr789zO+LnRvleEvfkZ101719v+8txv9fthF+3vNyX5wD+P7Kt837JT2nOXZL9vlQ9/JlFcdE/em4ZfPFKdfnoq/ODoipLwRKbJhRFUhpvPd1WbDp1U+RQCeEjKjV8J2YsXRM4WKtGXDJKtVUBTpK13dWO//Rf/mf+6//yv/Bvf/me/8v/9f/GX3/6iZiLkJtgHeOL4uFuFH7s8VYqINHK7qQyKJVpWohRYL2qFMZZnKooMzAtBVfEyGU7juw3e3o/kEPh8dMDy0FmeFWrqLy62ClNLJWwCCktpNVD/Pyd0SD2vgGjZRyrYda2BTQCKS7kHDB6pOTAwzwR55mSCjUXptNEOS2krPBDz3a7wRthOVtr2AwiHKK0wRhPLPDp/sSPf/3E40l0Dxqw3Vj0G8UPP/1EOE2MvvLt25GrrWV0DfKCtwIv9l0B5WklcbPfoppiuDvQdwKBL7kyrT3RvEqRN1gldVf9/CY3nAwstWHK6l1QBK/qNLy7vebbd28Yew81UfJCTgaTxL++ZkUMjaIVuh9Ix0TJla7f4fTKE7HQbxzVebKNKDVg3Q39YJkfH0nHRb4L7pHTITHFyJLgGDNLFjGWmAq5NjKrBHCVpNRW8ZV3VqZCJIgVrALl1Fq9KTqj6J3BW0WrYnl9Ojmuhp7jYaZ3Qk5VpVFqIBqwtqJdRTkFxmOdwXXCD3BOPckRKyPf6yaaumgl3BylGqlkvJEuh6pC2vXG4q2RiZbO0Q+OXDPzIoHI2EwIlfm0MJ9m4hLRaBkzU6wjhGcNgsowOt4oRwiVWi3Wb0jFElIl5cLhsaFUJYYIq2x4Sc/3qK7v2G63LMss9uEx0eoq6asFpVvZP2L721mM76nK8/H+xD//+Y7/379M/NtfHzkFaNpQlF5baVWMjpDvVEyFJVTiIKhhquopmIroVkTxAEqjjcEPDuvFRTM3kdBOKeJdx3YzkksGNcv6WuN0IsUsWijG4pwStcaVLFybuC421bDWUWiEFNntNrx9/55hGMRieL3tnkXwahPUpK3ouV5bxVo/cwTUSgrU2sjEmVZAEanj/3AhoDW4vBa7OS+vE4MXz/18y//F9p8D2PPfr5ONr1XgXwvSP7ePf2t5HdT/R4Lxc+Lzy+sZY56PUT3V1k+v/9vEvovlDMI8ve+Xfgn/UcvLbb1642ZoOJQqaNuj/YjuN+i0FSnSEul9h7cdLWtKgcOnB7IKoBtX2rCkLDe0VYddm4azDu083/7+Pf/lP/8D17uBu8Hyx/fXnO4/iMGvdoQoFX1b+7UWhdNGEgBr0Dhh+6qMIbLMCykkMd/pB5qqVNUYBk9RIk6iqGz3I9f7Lc50nB4mgShVkzFD64XBVxvzfCKmSg5JBEGsxRhFiAW3FU2C+7vPlFJFdc9ajHMo44k50JrFWSXthbAwE8lhZplmYkhMUyCERFUWFxNKGx7zIzc3V6IWlhvWeLw1XG9F5tV5Ty5/5ocPCylKtW08bDYeZxuPd4+kOdLfOJQ68zo0KRbitJBz5uoKho2lxECrmav9SN953r1tpFqZQuYwB46hsGQRi2mA90503hUyClggxMJhyTyEyuMUCFOjLmAK7MeO2/0GqxslLTQ1k63FpgqqUHWj1USiYVumNNGiLyliwwnrPUqB0U1MZQx0vcfb9bNQlkWdiHnGbwbMSYMRJbbTUkkKMFb6yU3MqYS30NBKPnNNRWmFVdD0M4LmlHgSlNxwWmGNJACKQkqiF2C0Q9UF02S6BCeXjzPiOkltlLOs8tmNVFecUzgPSSFTXuu4nqB9FaMFFi5utVVWq46DUnhr6bsOb0V+ebMZqK3gO81eCTM9hIyzls0wUHMR4yqtaKqwnMSpz1iPM5bN4DFa8eamsd1eU1vHX77/JM6BVjOOnlpFRTLFTAiJEhtOPeC9Z7sdGIaRUkRZMqVMWmaGsUM7i9Ya343kEgghMm56tBtJtee//fef+L//v/7Mf/u3zMeHTEY96UuY1bRJKUmSUJqYC3ppTDNYHclWse0NY+cxupErYt6EwjrH3uyk4MzrnW1NAkzXyXfZOYxecNZitEe1RFQRjaKkQkEzdB3Gim3w6RQx1qGtIqRMShllHPvrW27evBVHv6bW3r4TIyotBXFd5X0lwIsokDZW1lVmZfqfuWtntGB97X90AvDzc/u/XFk+Q+6XgWJ97WrRK7utUXqF3Ve4vrW1Sj5j9qxxcm0vPAHga4vgHHDlLxFJOMfAc2b1Omn4OUTgxf7/H6zMvwyYz+/1lACs0N5vQRWe0At42fNR6rX44m9cfkPi8bwHnD8RhUXrDusKSlVKjeS00KIm1YZVlW6zZffmLZu7Rx4+H5hjpCZhUlOqyO9eWUoR201jHa7rOBw+8f/9f/8/MM5z//DI/PjIVaewpXHKQkRSCjAi2+usxluN10KIslpIbtZYSpQLcpkDS4g4q3H9gPaWphLlVGg603nL/mpgtx9QSbFQoGYZRzRGpJCbgdpI80LKFYtCOUtFBHA0hsd5xliLKg3tHN/93d8xDAM//PQT87LIfLdR9F5jz4EuNmqMlJRISyRH0QFIJVPahD4FemfonMMojbWOZoS/3jnD2HVAJZdCKo2U75gWePPOsdtq4nyilMj1leGbd1v2uw3bwbH1llYCpQjqkEMkmYU4T+QYGcYtfrTsaTRliLWx5IHYlDj/NTF5GYYegJgyS8zkdUpgzo3D0vh4d+TzxzsePxdGC71J6BoIxxndV5SNtOJpuVFagpYx1lNqZZ4m+nEnN8PaVnEZkZaOLaGUwO9KV3FOMwbTDfQbQ10a4/U15nBH1ZpmQXlknKoaahOHxNV44OnbrfVKPKZiVvOoZgzVKRFhQRTgzrMzFGmJzBrCkihJPuOSMoUs0yROksRaCjFWnJMRuN474gDj6PG9WkVnQKSVWFk4ev1bo1FCPiXjrWYzOnovToApNCxanAtbRq0kSNHg12w3+skzIcwLqhk6r0g5U3Kh7x3WSi/bKoO10PcGP3hyMVgTsSaTi0KrRMrp6f6UovgpHE4Tzt3TkERKVDzlu2XOIxetiVKfNyyPJ8IS2Ox2dGrLFDX/+uc7/vtfFj4/iJNjqYolVFynn5z/tKqiiY98jhURLpqXSrViMkbvKSsSl2OFhwnXH7F9R6mZUgOYjHNePnvdpJDw62dVMylJwqa1Xu9dGbKhM6t0eC0432GrYgozh/CIHSy3v3vH2/ffstlekZuiU6IM2owVL40m0y1ay71Fm9VSeq34z21vrQ0oaRXUeukArFdi/N9efnUC8HPmAj8XsF5Uz+qZDvdzRe2ZDX8ZFGW8Yj0QdbHeRYX8ImBftMDXd/uCvPjzbPmvIxiv3+91W+Fr23v9+JdTAF85Cerl8786+D+R/y7XV785hH/lHV7u1M8uX1vHggJte6leui34gZwDKEvLgRgzc6lkpchKYGGUEKC0zqCkr91oFEQwxznP3eMDP374d7zzxCWgU+btrmPfO366O/I4rZCyBmcV3ls23tI5jbcKowWadQYSjlZEBe/weGTYdvhBYztPyRXXOYzNDKNnGB19b2Re2Ml2OyfcBKqYJkvloXEN8lk3FoVVms5atoNHG8e+63n7/h3/9J//J2pt1Jz48cMPjMNIaRHvFL0XRnHLAWMM3jmSlr7k6RiZQsX1ovRnNwMPdwdKLOyv9vjOY40YGhlVudoOGPeWrrc427g/nLh9e4NSsBwqu9+NfPv2hpv9FtMqgzUM1hIXDd7hV4Ga0+GBHGbxNSexzBOdF2KcNwY3WJEJNueZ5QotUGulpzJaVrMnQ2qGRMft1vG5zzwMDzgLtxuNKjONSe7wOdKyTC2QKiU7jEmSSBTF1u/on3QiEiorcovkKkx4o6XvXXIhlSzjWZ2n3+954zbcTQ37/QPViJ1yNYVcV9OfhszY054gdqWaJJIKMamxMqJVV3OikDIGCaQlZSIR1RpJSzWcQoaurfuTsEqjnYMmExQtg21O2kZa4zwMg3z3rAP9VJkWMdHRCq2KJEiq0TkRzHK60RlJJGsJ1OSoThNixoaKcRJxS5I2h7NefO1jwhiFUx0JRc0J7xV68KhmKLnK9agVqExYFoztefNmxB4WpikChpITMVZSEoXC2iDnTC0PLMuMtZa6HoMCSXbCan/cPFp5csqrI2Ul5Y4fPxz41z/fs0TQVkC3mCq5KjptEK7YalNey8oHENnoUgT5spo1KTfklImhoAucjoWH7sQwDJTqQCV8Jy0BqcBXYjLCa2lVnDJTUKRQyVEswa131GpoReGtI+QkhkW1UTSoKu0lGV+EXT9ifI8yjoKco6YN2sgYYqvq6R7bWqOVihg4V2nznROApoAKSouk8K8M7f+HEYCvPf/6dyn+v6I/f04MlFqTv3O5Lr39M/GsvRbrWde9hP6/Ph73Moj9UmD9Obj8a4nBL0Hzl8G/nV//tM2zsh4XjyEKT/Lq5+282PNfvzyfjzM09B8J/9dXicbrRa0qfg2tDE1ZqrEo6zB+RCE2qHWqHJcjj8cTc864fmC8En1Rbx2tVSGKIfPy43aL7ztKLfg7xzzN1Ji43nqGrmc5TdzfH1lGR2uKZKUCEIGOjqHzdJ2w99U6zmdNAwxNF3JJHKYju9s9xmm8V0RV2Oy2pAjWNXKN5BrkAm1JIGYl5B+Kout66Vm2RtVAytTShNyjDEY73t/esqQMWrHpO44P90zThNWNNzd7jFGc5keULjgFLWWoooyYY2GZI/MxsJwKtcFwtef65oZWI4/HIzlX/DDS5ypKjaqQY8I4R28b729H3H/5jsNpwnadWB+rW95db3l7e4NusJwmnFI4NMfHSg2BrrPkGFjCgjUe7QylBHSd8NoLFN0MWnWiG1FZe9SNlETUpXO9jOw1JTdDGrEkehQ7NbLsoPeWb9+MjL5gjKW1SCuJOBdaiTJpZAw0Sy5gzMipTbSosZ3FDg6jKqVFqpIKtJ05LSvIVleHNu0N15s9vwuKz6fCj/eJH+8fVqXJKjP8WmONXgNtfqI4a8AZxeitBDIk4VNVAINcsnSEaiLWIr37HlTT8p3IMq76ROYqIhDVjFy3ogyXyLURA2hd2G4c19caZSohr8CEkue0bugm6oC9dzSjsVRaSeKdYRXeaaxRlCbkNa2kvZCrEBHJQs7MKWOMQbeKCwpjikjSFk0MMm5bV8Eh52BeAlZbbm9G5nliUUlQh+ppNbPMiXkWDSI0sMhkRd+5VXxKbKdlvMGglSRyhopB0bRlnjN6btw/Ru7vM1qBsyJ/7LRU5xpxADVa9ElaPmuVPLuCWgVJQ4gVYzIqS9m8LG31QJlQ5jNvy4791YC3HcZYvLeklFhiIKeAN5qhc6Qlixvi+T4usxnUIiiYtpbj6YHUCl3fU61iSYmHx5njHGna4bsR7XowhlbkuqA2tFGr69QZsRZehWrr9NiZnnUmm6/vLWOrgqb/muU3cwBe//5063/Vlz+v93JCgDNK/PSa81JKoVbxGzdGP5lt1FpQTb8I3uftvobxX1frl293iSz83Ajf6316eQxfnotf4j2sK7z4jJ6C/8pxKK3wTGQ88x/OM8ki8fnzm/76fp7Pt2SBv76d8OuXX0AnGk+61VoLua01aQd0/QbdG1rnSAqWxwNTiIRccYM40sX5JNr8Yy+ELq24efuG999+izKK4/HAm2/fkObAfDgSTkfyEpkfZ4yKbHpNxVJyxXvP0PdYazFaxm16Jx7dSolxjVIFtCLnyOF44P7+gZs3V+z3WwoBj0cZz2awbMaBvhdCXdc7hsETugi5oZuh7zohNE0TOWbqCme2IixyO2haiew3A6nChx++5/Onj2w2I71zONMRc8QA1mgomWXKDJ30XTVaNOfrqkqrHTTRSfC+Jx5PGKsoTRFCQsWK9QqKeKMPTrZ5vdHc7vcYK73WUgLeJ7SeyEG01o12xFxZwpHOWhGCGS03aktrhePpwDQF9tc93mpiChRVsb5RVKG0hnPmSVkxp4RxDeukEtJFpi5cKnS6MhhL2Y5s+p7NxuBVoes0SxACVsyNEldfdDQ5K6Yp83j4SFOWzX7D9dsrbt5fc/VmK8HWZWota8AzWG1xxlAThJpQSqOsYnO14T/905+Yk+Xx9L/x1x+PPE4C81uNaMs7IwJVTSxuOgOj02wHJyN7pZFzIxlFsorDKVKKtLNKBLt2EmoupJCJZIxr+LW4iSlAFTTBILLM1Vrxq69CANxuPdd7i1KFaanMS6Nk6X5aJex2q4AW6Z2mNw6nKnqdGMhpobUqn5l3KAUhZGrJAl+XJDByEW385SSEweubDVp7chLFxmGzgdUTYzv0Yh2tDDGJedE0NTAGhYXqSXGRgO5kjNd7+2QDvhk3GN0IyxGlxMXQnu10axVXw5Y4PJ6YymfmU6IVOZ+mgF+jV8iga8Fo6J3Ga02NhZpFzOncRS4VYoLjFMkp4VQTAyxTMEDKjcfHie1m4PaNx9mOnDK1LoS4Cvk4w8YO1Aqno6Bhg+9ZpsQ8BU6nidb3NGvIy0IomayFoxBCJrZCP1xzdXPL9c07imj/ARLzjBLL4doqWpyn5D6u4Dy0rpFJqNrEjfW5BXyOIxV+Xfz/LVMA+qmPfhkUa62UUlYr3PPo2rnyXOPCUzDW5zjxtJy3J+xGzVPtu5I5jDEXc6Vc8ANkK+cRvcvl104EgIjGXOoRfC3ReZ1YnPe1rDKvPzcSeO7DvCY4Xu7Pz/18JuCri6Tp2Ur4siVzphDI+T/v58XY4xP68LVkZ4WOLh57lvptLyr+1hq11Of3bpfjm/JTryMoqgrz22BWS9IbWpnAO04hUpVBuY5u3FC1IZcKyWI6B51HO8e423L9/i3+aoP1hvF2z+nxgLoqOK/5aTmwxGklRWVaiUJ42o6M40jvPQox9HHeieiPsZxOC73vMNZwd/eZiMV4zTwH9uUcZKVaG/qR3a6n8zJq6HrPdq+ZDxHfLVAgzJFcI003TGfwRmNXfksujVwbm82IGwec74m5SlBQis4Zus6xLInSKmPvqS3RSmUcxjVoVVRVWCUkNmdE+Ob4cOI0JW7f3+K6HZnCTx/uCWHg+mqQy6gGRr8hLQdaXHAloVGrmAw0MmlOfJo/0yrUVDnkhq4Gqw25FSFOGiPCPjlhXWPcGtqqW279SF1tdKtWKCNGUVqD1Q5rB7RxlGaIuWGqjNFZJ5ryDD2tNZyxOK9QROKcKHEhxRmjLdopaJpcKksoHO8j3//lgeO0YHvDZt/zzR/e8od/+Jb9m5GrNwO6ayxxFp6Q79eEKWOUEZGbMKON4fbNln/8p++YQ8b/b//Ov/zrR0KEfpDWEWRRCDTSTvDqeczPWEWoRToeTRFzhJwwTaZXsmqMPex2YkG7LAujrvRGi4NmE9Jfo9JyRVeNd156x91IjpqWZvb7gbdvt/R9YwlwnALLIomDVkYSzVLovGH0ltE5rGkYCkYXbANj5VqPyyxkvM1AipFDPAmiUBU5VVKUHr0zlhgqKVbGTUdRWVocVlj01ip67ZkXUZ/UpmKsoBfebTA7z9Bfk7IilkhtUdjtueL8hs3mipqD3E9VJMYEDpwzpJQwxuBcRyvyXfvxrz/RsrT4Nk4kkaNTbJSm6zxvbq/QFJmYiYFWxN5aCq4i5M1WSUmmI4yXcbscC7qTZGGZC/f3B/b7kc55jG+g5J7XUiSEiFKW7TiQdpkPHx6Zl0hJwv2oufH4eKDzjmE/gFZUVYi1kBvsb2/5u//0j7z95juUE0vw2kRvQJ2LJ/PsI2O0wjqLUppc1oJYVZyTqQWlzoZBKx+uyQj2c9P9l5dfnQDkvEJDF9U28OQn/3pK4KsMeqW+mpm8XO8c7eSnUloIIhfLz43gfa1a/3L7L19/Tih+brk8ljPi8EtV/9cY/F/yAX5FO+XyLZ5+f9Y2vNzu64TqtxAAnmL9iwcv/7hEXr62T69f1M4dq1XWV77c0AGNnBNoj/MbunFPi5myBlurNZWC6Tts39Ff7+hurnDbEWtEz992jjIvhGlCW7s6gjWss+yvHFU7FBpnC33XGIdBgnkSODSliCYxbnb0vSeEiSUsHB4e0aajGzr2u56uGyj9SK0z8xyoWTFYR2c6fOfZ7kbmw0JOE646lBbrT200p2nCWM31/hbnO2JMwujW8l0WiWIhxilEc9ya1eudRtd5tpueceygFJaQKUXIaN56OluY58CcjjRr8eNArokYTiiVOB1HFG95+2aH95ZlfkSrgl+FdHKMVKrY2pomKoYgCZ1S6w0IUDLiFnKhVL32mxvaKTrfoxDDIuM6tLUUvSpB6EZrAn07u37flUE3J1bGGKrSdEpU2miNkjM1F2qK5BKpJRHTjFEiIVxmcYsrzRDnQjgVvO7J88wyJXIsOKvROnM49BwPPdfvtvSDo7RCrkVaB6mglRPte9OwOmOs45t3O8J//g6tLb13/NuffyLniMFiNUDGqkbnFaMzbDpLZyThzTUxL5FlgbA0SpDrQ2tBcb1DiKd6ZXUruZ/OS2BjPV3f0Wyj6Spqmk2JC2QQR8cYF7SqbDdr0E6KaZZgFObIMkdyTAL91oJWBa0E8ncaeV8UKFGt6/sttzc3bMaRaZqpuXE6Lmt7oor9bQWto7jSeU+/rZi+g1aoRRQ0jZdEz1qFtTB0hqPVkjS0hDED/TDim8HEQG4eUMSQqc0yzYmcIs42GfVT4rDnnFkTLkerEELk7vMPPN7dyYifgpyB0th0iv1+x5u3b3j79obT8ZFPP0WaFYnxnDJKO8BTaxKt/pYxK8SutCW3KCJQBeEG5UKMhbBETEl4pTHO0HW9iBIpmSZy3pJS5nCItCaqnRqD7RxdP6Ct8Ayyytiu4/rmhve//yO//+MfuXn7js1uzykmVNXoKjdjpYTwxyomZi7I60pLp+S5EENaRzSedFnaueX+6+7/v6kF8BpCv0wC/lYg/fpyZjSeyXrnbbSLn/Urx/Iakv/6/p5vPC/Si9cV7c+MNX5t3S+3//WAf3789bbPlfj50/k5tOEZMfnKfl20UF6851N7oX39dV85tt/aFlBqVXRDv3jsctdku/X85NrisJKptkZTA87vGHdvCXOkFghNQVldBp1AsxhD9T122DJsd3SdxRvDcjpyTKLe14wS0xujML1nVFaENFZuSd937MaOViunfGK/3TBNlc7vePvmGmMUKe44HDSH48zh8YD3nuvdyM27HUZ7clqY50iODT1ofK9w3rPZbTlsZ+Yl4fuezncopZhOJ1SaJQDYJlVkL0SdeQ5UMs7KvHpKlRzE3z6fzWBKRFmPVlBTpOaCd5ax68hdgyZwrT4G8Tig8Ze//lna3KWto1AL+71jvzN471FUnEFkTo0ha7MmZkiwNkJkKwVoFms8NEMt63ewSo/UaiXz5Pr52slUtHUoZyWBU43ayvodkB4zSmFMh7YDSnlybsQQmecj1sDQeazxOC1eDQKXN2qCznm88cxzJIWMQtOSoqaGUQ6KuB22XqOrJk+JMmri1FCpp9t0LCFI/1QJBlxqpKmMdaLpUFVA43lz7ah/usWoQkszP/10Ty1JTKZqY3CGq33P1aanW6WeFaJAuMyi1O41KI/wINbcZ+jWMb9VxCWXQmc11q/jYko4ALbzmM4LirqiKysuj9GNzhtyKhhn6UxH9IqTlvovqbNttAgU1RLkGnHyvtbo1UpW5gZqzqQQSCFAaVhl0U6jqqXkhRQq81SpbUJpjek9feuxnUwAoCVAWavJrYhWRN/jXKTkiWk+ANAPGpoX+W7naU2RS+V4nLjLB1oN3N5s1kkIuW2Ump9R1tpIKXG8P7LrLdt/GKlo7u4nPtwFUI3BZXqTmR8+EeaJdzd7fvfNO2rK/Mu//nemWYiJSp/RTblnlVIIRbxlZNwYvIdx2Mp1oxQlN1IUsa3O+fUeaCgVfGdwXq9kU0ErtNIMw8B+t6foglVHXNdz+803/Okf/5Fv/vj3bK5v6TZ7sA5dNc3Y9Z4qhFqj9ZPzX2siq80ZmTWrGuU5dgEXhID1d/P1oPiV5VcnAOfq/3XA+9ps/m8NLJfbWh95/te+vu7l8vOBuq0nUH2x3t9aLlsdr5OeX5pEuDwXP/cZ/BJ34BeD/6vXX27n2dH4PFb55Tb/1vZeHMNX1nleQX2RYT63LiQbZZULBisXzUqGsK7RDY3NvooSWpZASNXChrUi52mModvuGa6u6LcbDBL4Hg8TD/cHHg8TqSCGGK7HmYLVjr4f8V5Y2KoUIKG1Yhg6ak4YZHa/xMDj6cQ8B5RSWG1Z5sT0cOLx/kA/OrrO4kzPsgTSHCAralZ0RsQ/5hwIeWHsR7Y3G0IIqCjuaSUVlnhCW8VmGFfCViWXTM5NIH0jATKXirWOreuE2OTEGIUqwV9VCOL+Q1wCcYoiP2qhmMp2O9JvesbNwNgbthshZcmsvsIaK5UPhcE5nLsCEOMkLf341hCSF3Z1XDTE+CwZrFE4b/HGUkpimWdiSty8fbNKEa/bUjwH21bIKbGEyHJYSDkyB/j8OHH38CDWvJ3l+mrH7dWW223PdrC4VXqZzguqoqV52FIWWVUMne+gKDaDJ+VEiQL9hrmSZ9i837LvBmyp1LDgvcdZI2hAziJtvZLOaknUutAZzbsbiypXxNMbdAkcDzO0ijJwvXN88/6Gfd9TUyQti7i+OQNbz9DBEhvonpQaNSVyXHBmlWddZ/xLKUJxU4L4tNXe1xghjjVlZATMevAF5wKqFWpaSEulcxtxciyivmg3jmQbyxzoOk9OgRqKEBGVjL5ZO4hiohOFzOl4YjqdpMddKs45alW0quk6qARqK8QMpyXijzPKO5TVKyRdaG3lbq0mVn1v2Ww3HA+VT/dHTqcHjA1o3ZPWcbycG8fHmdMxUQv0HThvGUaDNiJpnXMkAGMDqqakzGboef/tDZvdFbk2fvrwifH7DxxOCyVPfP5housGrDVUVbj78CM5JUqcRLIZjbZqTYRFajjnSsrQebll+c6y3w1iQmTc6sRXULFQOktreZ1Ma2htGceeq6uRECKlaIxV1NpIZGITL4Df/+n3bN/s+eYPf+B33/0dm5v3KOtJypEa9OOWZvSLuHJG2UsVNVzdQJu6Sm0L6vKs1dYu7sWXMeoXb/lPy2+aAvi54H9JxDs//iJIcVH3nhHqdb8VsJYUq+QWqLX3/CRB+zNTAP8jy9cQjJ9b7/Xym5Mb9XIc7yLE0l5nNpcv4wJQf9VKuAAAXm73K7DP1/b11+z/+RN7fm/z4tmf397qDfAi+WmrU9B67vWA7xTsJeNtzdKsw00nFJFSItY0nHPc3Nyw299QS+bjx08cH+4JxxMPnz5zOpwoTUv/uRlayew3W7bjBqNFvCMHUdWzWrHdjDze3QvdRike7w8cDgeUEUhaN01OkRwz83Fmfpzobjf03YacI3PK5KqISSqyUitVK3AK3VnwogXgR4/xihwTJSYaCYx4sKMKrSRCCijt8Z3DVShtrdyNSM16r6UX3oTwVJaEIqNIhGWm5Mp+2/FmGMF5/vgP37HdbdhsBjqvUSSMbTjfsLqRS6A1Idd2g8P3UsnklEBpjPXkUgk6UzF03YjWDhdEJ0GqWS1FgNLkMouUaoT22DguC0uUihMtM9K1RUCg/U93D3z8dM/DMbJExWlpHCYpcq2D/XDk7XXPH99f8+2bLbseXI0YralZpi9qrk+B2/k9m40lpYlxa5miIicZrfNGsx0G9sOIa4o8T6iYBJErDZ0CDktMiapmSk40JBmwiNjUbsj8/XfX6Bz48OM903FCKcXbq5Fvrnf01jAfC1NSIlrVCpve0nsr/XbXsyyFhYrKYJSISYlbnIw7TyHC4Y6RgXHf4zq3jkGDtV6CcSq0XOX6aZIQ3lztsNpRKxjl8EaTUiF3lt2mxxhDTl40/0tAk7FO0Q+Wvu/IIUvL5SwUsk5I5BTJRVOrfM5d15FbJZVEyoXTHOhSRmWNyhqUBEal5DrQSlQndztHCpb7Q+bubiGeZpQNxMyqFAhhgpLldi/B1663eIO1mlqyGPLEhMFSa2XoxTbY6kwMgc7B77+54jQNPB4X5jmx3XbQFMfDgU8/fsBajXdWZIxrW9tvwttoTZFUIrdG11mZLHAWpTUxRh4fC51VWF/ZOS96DimTVcOu4lbb7Ybf/V5Tm+aHH+6Yw4w2DopiKZGud/zh77/jzXfvuH33LaYbpDWiheOEshjvxO2Pc/v8fNuU1lhrjdqy2K63ZzRb6GFrory2DpRC1ADV2QX3by+/OgE4E94ub/xfE9H5Ivg3sQL9Ynn1UOOMWqyZwUVm8/rVvyX4X2rg/48w4V+o9V28/8/twxd8g8vnXq33c0nAE6nva22Hr2R3iouMEEEPfo6L8Pqxy23/3Pl53Wr4+qGfPyxFVSsG0fSazBgkiRC5X7SMbW2uLdr3uO2OFBecLtQyUdNCDIGmFPePR5bDge//8heOD/cM1jJPgVqFW6C9ArQYsPQj1nmMgr7raN4zTbAcJ45hWVEs2Z9SIs51dN3AvLq3bboeDRwfDrSWqPWGt++v2Y5XGG1krKquevCrg9i42+D7Djd4+u3AuN1wPDwwPRwoBZY0s3ycV/lOkR9OMaNsESKYEwvXnBbiEsA0fNdjnRUN/bRAzXROTGW2G4XvOvY379hevaEZzdXtBmsVRiUZPyRBbVjlqE6xhEXczrynKsMc6pPMtcasPWkIUSaMU8ooJYz942GhFflCttpoqTDPM9PpxDJHfvz0zywhkWrB9SJfW2um1IRaha2Op8DdfeY0Q6KRmmJODeU1IVROE0zTQst3uNYw147BipNbrcJ9EAhcoXTHMA4U5TjOJzbVEovjdBIhp+vdhm/e3LIbRsxKkNO+J8XINB9Ejc/2UDRzTEzLCesNvutoWMgL5Mhu4/jumytMzXxSCVUbnVHomoWIaQ3OaJJC+AWsrqc1U3IkZxFvkpsxiPtnpaGYY8JbqE8a7iIj23cjbhxp1rKEJFyNVCm5iC1u59lt+v8/bX/W5UiWJGmC311lAaCqtrh7eGREZORSXT09b/0w//8vzJnq7DNZVVmdERkZvpjpgkWWu84DiwBQNTVz8+wp8WOuZlCIQCAQXGYmJiZiHCbCOOOaDtc5jjFgvWG3u5MJguigisZyjiOlZKyTKjPnjF4SeqVWgbQLoVnMG6SFUWol5ELIFexM/PkDm7Hlzdsd210njPU6L34qlnlOaO3ot1tubmZ+/jBxmqBksQ7O0qJGW0RJUSsKhWGcaQdRHmxah29bahZET1dD28LxNLPf3y+W17OQhLsOpcRMqnGiPRJjxllD9+YG5+yiObDkTyVRVZYevtYoZbE6ARLfQqhMU0WRCbPiZmPZmIbVgC6lDEqsx62ztK3n3bs75lj4+Hji9DQK58IatFNs3mzwnaO7aWl3DRlDKpf4lmqlpiStj9XFqFRQZfFEAG30Etyl9KslkxfHM2UvJltVqwtnXH19rPv6KYAqfalz9YxkfXX9b9Gfl8rxEgzOpLcvnE/Oi2yhujD8VwhdgXhUvzyd6x78VVq0Ig4shIjzc17Z9/q11u1z5MKrvT957DVkYJVy/NJxP/eeXi3zzzs/P6/1/b4oxF8578+81mv/vtpfco7nXg7X7Ym63HVKXTdu1ptRFL3NgubIypIoSoHVWGvonUc1LaVEvCmQjoyHez789BMfHx6pMTEfDhyfBjGcKQWjPNoqComcRBfdOS39xRTRi7a20qKMp5RingLWGHIsUo2lijUtMRQOTyeUUiJPXBLTMAkRjYQylTdvd3jbMMQoY2khiqtgyfiuwTpDf9NjnSONkVID8zgwHybm00COlbvdDqXscj0hp8g4nbDl4m+vaqXtGnbbnq4zqKpJcyFWMaPRtx3WWlL1+G6HaUQzocwHUVvTMtKEEhGtSCRlxTCMMM2U/UCuhVhEs73kiikGlQ0xiVxtKpVchHGcKjw+HKi1YpSFLOS1OAeB3HPieJiYk8zb+3bEOENelN6axtI1DZoO5wI6RFKozFH82xu/JRMpcUQXOBwTxyFy22m8Ejlau4jtqFLwvmKdo2lFXfH2TUu70XQ7w/H4iG+0aLFTMEvAtVqjtWUaj6TTJPeIShi/QVNwi4NaTSNziFAb7EKoenPbkuYdqiTCFMhx5LC/R2/vhG+BqMoVoxinQMwJVRVxnohzEN6Eg65tcEZBCYQ5oQoyDtc02MYvVq5gFlXAkOtSAKqFAlCoWe7b49MD0zhKBW0UxojMsVKrOqGQCRULKqsseY6ENIme/1Ip5lyppYhXwwLfpyRiSDnLfT7nRMoyvqmMJaXCaZxpR89m06MbR5xFb8E4uwC5hqZ13Ly54/bNxDDvGUYh2GWgVhlfo4h3fYpwf79nu7lhDpUQKn6xNtbGCKrmPeVw4nScCCmCVvTeoFlafKouXIyMQXgOMUZSioQQcItGcMkR4eYoIdppQ1ag0aKsmTM5K1JCxhC1wbqKHcG5/vzdlWkOETWzVrHd9nz73RtyzYSYCGmmkLm5u8F2llQSU5oxzmCcTMukkghpUZtUFmM0lUzJ0j6rAFqjjSBGiktcU7BYyC+xb0WGf319+/UJgF3mhp+PxrEwE+u5bK1LFPikV/6FY5+P+4xQJm/OLCn05e3XM0jwyXZ+cAn+z177KnDXy3HWx859+/UwC3pRygX5WLPlNXP+hPh47nE8TxJeJwK+TDCWIHrV03/NQ0F98q/L+3g9sXilN/CZ7ZKArOOY8rOeE6s1xF+fwXr815CPdRJAgjFKhIJWaEsZIeYYFGTR3c8pUlRLVg0pa8IUCWHxPHeOkjPaSPsg5UBagrRqFhhNK4qpDNNInEVzvel6nPUMx5FaEto4sQamMs0j8zhwc3PDOJ5QCvq+w2kR+nj48ASlcHOzYdNsGYejyJcW0M6x2fRCGGoc0xzIRUiB7aaB+0LVle22xXshQLEwpuc5ModB2ly6IcaAcZp+0+C9oVZpf2mt2Wx3WG2hGN5lRSiaEEXVLaZAmqRtor3HO3EkSykyzhOZSkJxHI7sh5E5FhJijBJCpoYCQRKCkCpzKgxzZg4inxqCEKM2bYu3Ds06VmURGEQBgVwLY4A8yzy5iNvJFEjOijHAcSyMEVKtKOMIUcxZyApLZRgKh0Pk4LXA322l76R1Ib3zinGFGGfmVOhbR9MYum/ekMobUJm372/55ts3WFsI04FiKtRCDAGFBN7TMFGKwjUNjTEoBcfjgY+PT/hmi7U7DJq298Sbjpoyw/HE/f0901honIMs/XxjpApLUeSZrfVynlqhjaKxMuZpTFmsd6FvRBNgnANt8bhmg/WekBPzMJCqCAkbLdMlpVRh/A8jaZ5oXcNm0y/f90K7aSmxcDweMMYwzzMlx8XEKC0JayGoQp4K3reUsuquWPmcqqFiiakyhcQ4RYqqGKvpu4672zs2Nz1jOJIinE4TMRhSCThn6J2haxth01fP2wRP7245nUQ8J1VpvYFGlYJ2Cm9lddj0mrb1KBIpJIJVmCrKhhpNmhO9dzzN4jJovUKXAjXhjWGz3XA6RT7eH1HKYpSR9wZs2oaUIjGKhKIxGqsNzkprQVVw1lKLGDoZI+YM8xTIIRJSAg1tK5oHxlhqFkOfkqHp4Ob2jv/U9bR9y48//8xpnGhazftvbnn/7XuKUwzjgE0yQaMxohjqnKyRSv6UutiqLyiBrAFmmeBQgqQv95U1ZuHQr22ApcA6r+VfteT/GingC2wkS3smF7ieIb8EB0VdDYzX7Wy7u94ILEQhJBtb9jmz95fDrUcsrP3vSx98jbeX59bld+sYkzrTB9YLIiHsUmlfJyjy1zUZWM/3jMeLAOMi76qUeDRL8rDstwRMtYgymNWSl0vbQPrglwTpOfHx4lnA83zokhic38y1NbLMrV8nNFXnq/dXr34KlCvJ2nPy5voaaZ1eWP9cfbLPPuVnv68vPtvlPGuiInAyVbxfqy6AWUb4PNppMIVaIsVsQSd8m+i3Gqf3eO0ZgOk0o8jkOqN1xvSKbKWXHZ2i7Tp2bYcuhf39SMxBmO1ZUSJstm+ILjFNk/SpU8TUxO3GEqYDORZcs2jXh0iZM3EKlDlT58Lt7RaLpxBpNg2xBKKp+I0jaEVyVuyKU4JHQfW81UtFLopnZfmsUgrMpwGVA87f0LSa/nYj1q7OYJQVYaGMEMWcVC2inx5F1SQliLMsIGjCdGI4Jrq2pWlbUigcD0e0balJMz0mWaDRTLGglIUcpTTDkSuMKTNmzZQzc5AFssTFPU0ZsUJOwgtQVjGUQrWGUjTzHIhRIO+sNWlUHOcI2or0r9JkLaTHqhMxL+3BCsMET7rydMrc9mJxqsmElGl9pWkaNhvLMEdiqrimI+dE4yyKyM2uwfiK1jM/f/h3Son0fcNm05FSJqXKFETQxSjDza5Hn+WmwWFReA7HyDiO5JzpOlHwqTVQSdzc9igFqYyEEFBVowpMs/AdWufY7O74h3/4z/zp3/7CDz/8SMmBWhI1y3tyVjMeErWr9Fsw1qOcpxpHWcxgdNXUIoHCe0/pIkcemYYJXTW68WjtJDEICe1kfbat47A/UpPoGFutUdWygEIoDLapzCEQY8b7Bm1bQiyEKIl11RpjKze3HadxYJxmgin07Q3jOBEjTMORMM78ze++pXUtIQ7ENIvYVC3UIqOt799sOTyO7B9nOgspVrrOcvfdDq0rbWO4vdtQU8Bocf8skxYJ4lLpesOu36C6ymG/pzE7mQxQMMxBRjpNC6oyhYh2llo1Oa1tI9A1oTNs2l4CroF5GnncH2g6S9N44TxYI+hfEI3/kqTwmWPCqIGa4e5uR/EWbUSafBWXynHEN5Z//MffcnfX8NcffqLrDWE6MJx22NsNrff0mw7jG0LKFCJt04ESoyxKRi2OhMKpA4whs7ROSkGhUUbW2LookbLIH4OQEytQy9dLwf8qHYBz5aovYO/6RwIXSBayigItAeOqIlZLgfz8Z/0kEF4hzp8EoZc/L9Xp5Y2XFwe55iV8/VaXIHqViVxlHOek4hXeg/zicg1eY9p/rhdfq1TO18nD9c/1eC+3a5joNR2C88+rlszrxMZPK/pPXuuV13/OFXieMpxvTnWNSCio6wiMpHjWbTE7i3Mdu37LeHzg9OAWpnag94p5PJLTJIYmvUGbHZu25bbvaY0lnEZSmKWKGBNlruAVJQOLLG/WSSRjS8YaUU503jKMgWEY6Dc9WhtiTMzjzLgfqCHiGo1tNKY1Atm2lmbToWyDGmZySuiaUEbTtg1VGZzxpGWUCO2IMS4jRxqjFbVGmm4rUwdO4M9aMjFlpikQ5ijz/85TcyVOgZwElm+sJqtMSoEYo2hVWEdNlRQzJYo0ahgi+/uBKVZ8v0WbZpm+kDlxpZ2YjtgKKUl7pQYRdEIxZ1BJzHBiEj/1EjJZK4E1VSUrgTVBPtKq1dI3lUCvzCIFlgXWdp2nogSaTRCXyvLQCVJkkQmAsgjDGuOwzkjiUMEtI596UY5bzZ1KTRhnSRHG4yyjlVXjbYOqItFcQ0F7jS6KQqVxDdtOc9x/5OnhCWM37J9GQlR03YZvvnlHzonD4cDxcCKXLJbSUVzommZBpVLkf/yP/8HT02Gxpa6kWEhKo4qgIZ3XWCXXMEQxu9I48S2wBq8dORTR9y9JyGcxkWPFOukVhyCfdUiFGmZSKoQQmMdIDBmKjB62xsmIH1LUKF3R2mGdo6CZQhbfCmOJRaSbJdBHMpW7u1ustfz5z/8GuqKtCGtRNeMw07SGrtmw63vGEKgs2gcWdpuWb7+5Y78/8rQP3O023NzcoE2hbTTv399hNHz48YlpmsgxYbqWZtPSNqIkmeLMPE84Y2i9p+07Mdk5zSRlOYXM8LTncDoxx4pSBlM1emHQh1ShymhprBGlFTkWtBKnyqZpiNMognMUIcZqQ9v2UCopjTw9hkX4yNO2BeMUrXI0rSXnhLailYBBkkT7LcZYrNUM48zN7S2+aclLz18pi6qZEAaa1kobQML7wpfTC3FEn70A9OoPYBpR8Vy4bbXmBbFdl1zF16zf6/YrlABfzykuJLu1klz1i+WNXFfIl32e/1ytC59D5Re4/mvezLORuGfB53kQvv75ScDmeUBcE5pPA/XKhfgly8UV2n997O+1FsH6eH3ZEniVt/BaQvN6YH6eAF3O6/l5XNwTv2pa4Oo5L8/z+TW9fu7Lz0DuGa1F817rImqAXUPqWqauwWlFTtLr86bInHkA7w1tJ5n1brOh85YyTqRRkgNjDdUkiipoNPM8EWMmzAKd55KpWqQ3pd0j2bW1Vr7QGsKcGIaBmgLOS4+53Ta89Xd0NwssXhVWG7LR1AQaRWOdyAMXCWalZJzTKKMpWdM0DV3TCGHIa5TV5+/Jql9eUiKGGbUEySklVNUYbZZJg8xwmlFGrqfFkKridBo5nUYKFq0tw2liDpkQRUY2MNJ2BmstYY5MMaJtXUhaCmvFeMaVIkS0KrC73D9SYaUiJCblFKpkSinEJP7xWgseVlakaRFq6l2Ly4lKIJVKrUIas12D9TOtEpRIkrIGay12qdBTKThlsV6T58wcKiUGnDc4r/CtwTnhhkDiNBzZjwcaZ/GNxekGXRXjac8wDIxHRJ0QkYPutzshkWoRjxmnE2/efsObZrcs/B1zCJyGgVpBK4v3LVUXUpNIujLPhcPhQIoHclXi/541pyGQo8apglWGiAZVKDis9TjXoq2RlmIWrYOcMzlkaizM00yKMpIZ5kAtYJ1MDSgjKo1GSYUfpyxE06kSKEQ7401e1Pbk29e0onEfs5j/pFzxrYjW7PdHUqlsdz0pRbn3lSCCzhvyHLFGCHzzmGh9gzVODH/yakkr33PvLe/f33LYD6j6hFaWFCa8N3RNT46Z4/FAzgWtLSGLJHfOiW3n2GxavLdordjttsxhIudIRbHdbmi2t/z8eOKvPz9hrMFWBRjIZblnqnA1tCgiUpDvInUZy5Vku1wpzUm4EaRXLYipNoqCJsQk6qZFob1hYyzaGox3FCrzHDHec9e1Yt0dZ+b7B/ybO26KMBZKTVjvMMaSqxI0Ta0Ceyuqq6R4xEq1rzRoKwmw9Sgtnid1JcmtCMCyukoK/nW6PL9CB0CzkvRWYp9aMPhLNSta3WqRMbwmiH0aTy5VKGco+tPX/dpexpe21yr/Xxrpu7w3uFTUa/C69MU/3ef6dWXfL5EQ13P59Hf1F9/75xILtd4K6nnScDmnBS14hpB8/bX+tdMU1+f5Ut/g0n5A5DmVlxmhAtoVmi6xuXnDPI9AIYUj2nc4a+k3DbubDdvthr5rsTUxxsicA8dl/EukxTPzQkCLi8MYCpq2A1pCGIghkKcsvT7nKFV6iN5byIkYAjXDeApM0eE7KyN/yopFbx2JIaCrLLZ+MTuZYiHOiaaRgIbWVGewpsMYJXP+TpGtOP5Za2m8l4o2SpsiLxVdRap17z1URUkTOSdKKmijsVqU1uZ5IswJ7dqz9PA0RVKq5AzhFJjiEWMtOQUq0pssupKrQWlN14gRzoiM34m2/URVilw1VcmQbms90zTJZIMC54XTkUuhpmWx05rGS8CakybGhM2Z45TIOokKopbER2tF23ru3tzSN2B0JsaZkAvaVbS1zDExnGaMcuQq/gdmFhU9bYUEmCa5jVQEVzW6c3INo6UEww8/fkA7S9d33L17w83mFqyVYKotXdvz+9//jr6/JUaZkw8xcDzuGYaReUjYG0frPH3TM5XAlAdSyBjnoYjFa4mJaazMY6a10hKKVoOp5CJ9d7Rco7KQ91YSY1nakEZpWt/CtspIpjYYZzHaoLQRLo0y9ErRNR3DMHA6TIzDLBoNJV0GeYsCbTBGXOmmWZIxjMFYi2ssnXP8/ve/ZxgGfvrwIzlXttueVCI5qIWTEHl6PAoCY7YiGmVFqk5phUZMa7rG8e03d+QM9/cH9o9HNn2Hs4rHjzPzPNJ3DY1vMCYwDYkcT+SkxRTLb2m6hsf9I9YYtm1DrpXTNMHkcVaz3Wx4OgWZdKjiMljVikpfAmFFWqxGLXbPi8iQcw2n00H8AZy0cU+nSUysWkAbQiochxkbFdZpqgbXeFy2zDmhpomiK9vdlgocpoEpV2rfkLJa3PqEqJxrwSiZFsi5UFnsfxdtCEmitcz9I2RJ8QRYHJWqTGic4+ozlHpZ97+SEfj1CMBZbWh5kfMlVUvluAbIa3h3rTbXufcXEeYZzL++kevqHDhnlF9xiq/B8J953vkUXkUNnp/kS0RhbV28rGpfHrt8RcvhGpV4VuU/O+qzPbgebbw8as5nUtdk6kUL5hma8ux365O/rkXyOeTi5e+fnd/5c119BKRavE5CWE0uVKWogtIe67c0m0w/jaQcScFg2warC9tdx2bb4Z0R0lWeUd5TlWIOM0wTvhqmeeL0NJIDVGVQxi1mSVApKCOVpXOKNEemecRkQ9c3eOukak8zOc/kxVt9OJ7odh272x3OOqZlQsBWsS9WCCrgjBVhIy3kIpTCOYeqAlvL9MxS/ddMToUUNSVnEXSJUSxalcZbL8E1JmoVbfpN3zFPkZgTMUZhky/QeYoSPHNWHE8T81yxfunjF5imIPCzM6iyCI8AKKm6Gm8xdKQcmMaZcRZItai8TC6IlKrSFmUWF7aqicjiahSYhTNTF5SAnLFKxJ52nVoEcwpVQ7dRvLntuHtzw3azoaYTeYG5lTFU7chY9qfAxw97jHI0jRABp5hpW31uq6hqqUkxTJE0FgYbqDmQQqYkh1UdYUqMRLa7wjgEQh6Zx0jXtnz73ff85je/oWl6Hh6PDNPA/vjIaTgyjpHhEGntTLPzMqGhRQu+7xUozzClZXFfZs7ziuw0YBxVzeRimUNlDhG9tH+0rvK5C2WemuvCDNc0vpXraizOeYxd7mGtaJqOtm2ZQ2SeZ07bicfHR4bDwDwLgVKmORQhVWoKhJhIWVpvorFQFn5S5TQcmOaZtm9EiW84ikJdBWs8OVYePu6Jc0Iry9v3d6Qpoq3GWkvfasYpU2rl7ZstJVXmYWIaFDnOPN2nZUa/ZR5m5mFGq0LrNb7R9BuPXoymtJbWRcyBOUwY22CMYZpGnk6B4/HIMEwULAqRM1ZZJka8MeK1UCHXfDbNWbX2SynEvDgicilstQajFEYb0PJ90UUvQL1iipnH04ledfTO4ozGdw3VWp72e56GAd/f8M2337PdvMW5Ddop0VZIhUKgdS2lCrHcGCcaAkiLxxiDsoISLBkAIO0CIQbq83qyFnxKL8v69eL/C9uvkAJevJCVMJTlsRVwWF5wUYir9fkJCJT/csG/bMZcTHOutxVp+KUE4PlkwqfB/5cq8NePd90GWBOZX96+BPWzHuWVxOCT3SpnYt1ztOLixfA8eHLFhXiOPjybxPjKbOqXrtFLTsWn1309dzm/V4/3SU6olgAk/Wi0RluDq4V2O5OpGP0GSsAY6FqL8wbI1BQgFrSzKGcpGqYwM4yR6XFg2A8oHE23pe9atPHkksglY3wj0q6p8nAaCGFm6zfnQF1ykn5uznInpMxxf6DpG969f0d/48gK6TXHSEqJeRwXNra0iWIIksVrsSq2WqGsGIVAlYWmyuhaSoEUllHCacIai9WGkhIpR4EHtYwJylUDoyxFFXISQleMlbgE9DkJo981FuU8pykyBLGbRRsshroIElUqxlQZwaLS9Q05L86BdSTOcodFYZFyHCdqrVjboHWlLASstnU470SBUBVSmqmloI30wEGTimImkWtl4+HdXcfbN7dYrdgfHrFGJHAxhnazo93ccBwTT6eZn+4PUBRd14kzY8q0nWPTebpmSZRCJicx5KHMzNOJFCeUUjRtxzQ8kU+BWh84DRNzTeSi6Puet+/eymhWlbGs0+nATz//yPG4R1EWgp0+m/AoqrgGGs1pSsQUgUouCmMderFnTdlyOAY2G40yLcZ1KFYzLJkqkCrfglYLB0AUM5VySzA02GVksOQi3wuraDppJbRdS9dtaNqGh044C+MwkYIQMrPWEvARMpvWSvrKRtOIpeAyypZoGodzBu+NiFstOhYyAaU4HEba9kTfb0EXetuJHr61FAchZvrW8eZuw36/YRxOhHleOAod3nrG/UCIka7T+FaIj77x1JqZY8QYzZs3bzgcDuz3B6wPaOsZ5sTj45FhGChZAnwtkGJBV/lO1CXRVkr4FKUKIRelUIvT3jSNWOdxRlFrxmpoW7NwY9QiTQ7aOrQ1ZBLDFJhSYIyBqST62tNQyPPEaZxodzu+//3fcvft72i2dxjrMVYQiTTPInFnNDlJe0WjoRrxLVAyuoqyKCUS01SF1hatLMpIAlAX2FbCrhCrxQ5YfW38/zVKgEu/4ZNF/roKvkDml8e+fjuz5J8Fxy8f4/Ojdl+3/fJzP00qPt3nc3D95499jVRc9+afkyGv99cvEoHlGGsmyNVurMnDVQKBeQUVeI4mfC6B+tL5P3u3Z37Bc92AlyiLvMb6us+TI4ErrTCJsgQlbEu7fYNtvEjk1oDSS3BQhVwSyswyS9+2uM2GdntDOI6c9ifmMKGdxmiLsavhDWjnsUpGcVQtpDjjvKNqgaJLirCwbZ0T90KpqKNI8k6BlBJhmql6RbqQ8aFpIs4zKtWznbXWahEcmXFepES10WTysgjLDLNzFnLGaIUzGqMEUk21iGmOZEnSBihglaVSibkwT4E5FBnzS4q5iNFJReO9oxiLsYrONBQFxykwzEJaBIUyVuakzUJQLHlRSBM516BnchJSX60wLyp7ymqpTI0IrPRdg3PS8y0lklNC1cqmlfZNRbE/nIRQ6aGxhcZqnKloJAkKYaZpHG3X0XQbMA1jCDweA49DxRtNMYVAZC4JdxRfgb5tZLY/JhHwsRarKmlWVBzeW46nyDgkqoIwZayNRJXR3uOcB+B0OgGLPsDSTotReuzGSFJUcqHWjPcC3w5zgpoxRgqhkgq5gNNOPCnGwCkNKNtREfU8lKGUIMJMWmOsw5mWrCBPM6VqSjWCNBik72wdxjmqTouBUlrErQzGNXQbhe9abN9ivCNyz5SjJBpGoX1DYy1t0wAsvfWKRUYula5YJazzSqHrW2gbcszLCGCiFMXxEEHt2WxvuHuzxVoZaSUXahblS3TBO8Wbuw2nY8fTgxgXGSDPaSHhGhpvQWVCmDCzoBHGSv/76XCSa24d4zxTppmn08Q0ZSHPTpmaBGnJVbRoQsyESVwKrRVvFm0sLIh1LpUUMlUt7pXGClG3SMJfEOOuXEW6O6RCJi8aIUH4KCIGgW48xWpwlpt373j/7Te8ef8bXLtD25YkAqIoI9V+AkLK5GrQS9+/KIvGgjJU5dDKYTSL/PCKTizj1IifyGuy7/WTOP357esTAL0sOkv/+3mPQbNa/a4nsfxFwpiS/11b1H5pex5cLoHwP1rZfwmS/uUE4Mtw9+e2VVPgk8c/g2jIOV79Rl3J6S6X4BqHqPV8Zs/xCQVUTa3pWaNm/f8Kfb12vv/zt9emIp6/bqlLkrPMQlMFsnf9DltaKAFqBBK1RmrNVBVh0XU37Uh385a7bwbqHInDRJ4jrlrCnBmmEyEX2q7HOY/zllIr0zhhaqVrPYRKiBOVyKZraZfEQ1EYyTJypDXOWeoCpVdbyCkKgz4LWqYVUkFUTdM4alFi+EM5k4usE6OZnBMqgXfuqv8vxwphwi4EIGM0Mcpcs0IqBWs9IQXGITBMM7VoqnJMITLMkTlWolL4tqfrN7z5ZsvNmzuqMfzX//Fn/vXP/06KEWM1VukFtpdKKeTFCteKPGyvDTplhoj0/bVaZErXEVdxPFTLouq9peRKQnzpW29pnMy3q5oXP3tQJdC1hm+/ecvb25bT8YEPH3+g4uTz7zaEAg9PAx8eRWFutoW5RmyMuBmMKjRupveT+LtPMzVVdl3HbtPhrcMZjzIW0kgtmpAKwzCLqZStbLqOrusYx5GqJUAPpxMfPnzg/v6ew3FkHMEUYYwXIxils5Jgz7HQekVVhhArtSRykZ5vLZXTGDC1CkqTMjFFSQS0WZXQmedAsQayJyTFMGUOY6TmIONznUMZQ+sc2jlaZ0Xnv/XEGLFOYX2D8hYaS3WKsUZOYWY+ZVQVT4imF9+MlCIlKpwx9H1HWaYqMHKPj9OErgVVDWYhj56GwDwmTmNkCiNv3x3Z7npyFvOcgtwbJUcoGa09223D2zc7xuNImBIpJXF20BrnHc4rYhbnxhADxhq0saJGOMySUKa0IE4Oax21JlLKWCsE2BLEYrqwtjoKpgifwqgVYRSsPKYiKoKNE4ErUzDVMs+FHCfxDAFM46lKC/E1LoR1Y2m7nnfv3/L+N++4eXeL9ppqLbu7Gza7G7JyKCN2vRWEd5ArRWkUlpjAGI9SFrQQdrX2aOXQxgrKp9RZQ2Xt/bNq7rGulWfc9/zv/wktgBX2Xx9YR/2e944vsX+dexeJR3VFSLuuNF/CyOu+z35eV4lX+7w8zuvb5y/E5ycHPn3e557/fGLgGrLXKzD/4jj1ijNxfT3kuReynF6Y1EvSxEI8OL/XZdxSnV9cssGlDVBLXar79ca5qCyeWzbLrq9xIl6+5+v3/TkC5XUS8+k1e02e+FPipzZuSTALaLtcR4OqRTTDiwEcEKF6qAlVEqpKlaaaHZs330KqqFgoIaIKpCEQ55mQIsr5BRKM+LpIuiLjTXHpvackUsHG6oVcJCy8pm0oquBaS9f3wg9g1T6sYg6TM85YqrXkmKm54JzhMA0U4Ob2RioqlUDJjLvSWgKFMdL/T9JKmKaJNEe0jjReKk+Rp0bsW0tmmCamKUl7rmjmmImlchojGSM6AgibuAK+9dy9vUNZy/vDgYenBz4+HMmlokoWYpRZzJzVmvQXjDNsG0+LQo+R42EQZ0KlUGSZv9Z60QxZSHlUvBPrXOeMjJCRaZ2jOEMthdYJme43373jf/1f/gFnM//Hf/kJYwyb3Q3vfvM93373e/76456fPj7x4X6i6kXMKGYaIFWkys9xGZHUpEn0Z9vWYNsbfGMI88hpP+CNBixaxwWedUQVSHkhiDaNMOCZ2R+OHPbCVnfWYEyGLJVq14jl7jwPMnaZM9ZYdFqllmXBTjWI4lwoFA2io5KoVe4N6xSlCrpQMgwhYLVlTnAcEx8fBx4fR6ytvPtmSzaWjVJsNh1dK2b2UxJOh1++ItoYdv2O/s0Ws2nRref+xz1hnJlrRKWBUDQ1J7SqdO2Gt+/v8I1jv98TU6JScE6JKFERGLo3PaZpCV1mSonDofLzx3uM1xSVaRpJhrwVj45cCr4x5Axd62i8YTrNTOO4uCSKtG7XeWyR0cgQM6qAcZr9ccI3Hac5iESwE08K33Q0TWVKkbbzVF1Fw6GKfkVMabFyhpqgGshB2jzWiQ5JLhViRlFwBU7DxHia2G4tbd9zGkeMsXhrpYVQCs7Lumu9p9/uuLm74+27dyhvwBmaTY9tGpxuQDlyVjS2QTsY5xHlDE27JRcFqkXpDmtE28GYBm0cShmxhi4C/1/a5xIHViVAKShXL4BlouqqGP+l7VeMAV6Fs6v+yfrzRfF6XtxrvQQ3XgTy14L3a5D+10DSXzzzr4C1X31OXc+bcwZ2ITb+0vZ1WdjzxOnLx30efF9en+evZYx5FdI/JwVcX+Pnic21kcTL4P9ypPDXfjafftbXCdR6rdf/LdzlKpapCoGaIaOqo5KpVSBXmb/TeEBjsVh0Uagqzl3j054xRXrvMcqAzjTeUUukVri72dBYw2FfGYajKM8VMT3RRhwNVdUYDNV4XOtxi4xrqZU8z+QyY0peKn+x9axkyf5TQimF946ubXHOEmIAJQu1sRaW6mb9/FYfilKh5swcxDtda5lf1loW1fGUCHEmJZHvrcaRciHESqbgelGzq1ozx8DT/hHtNU3XoUjc3faEFBnnuIzkypjRHBONtZJ0KIS0qA2N99impXWOp4+Poj+QMtppvBMXRSjLVERFO/Gmp8i0Qusdzmrc4h54s234zfu3vHu7Y/94zzwf0EYEtba3O/7wt3+H8RvUh5H9cSLmJT90UtE5pcFqmeOuhVCghEicC95oQlGMqRJrYpoicQqYkjAKtLcY63FtizMOlOJ0OuGaDutbkbBNGaMcre/IbSE2I7GAtUp4KEZRjhMhR3SFmMOiryAqiufvXi1yq1YwtmI9KF1JKaJiwTiNcw1RK8KQmcbMx6eRH+6P/PtPA/u9tBameiRgeI9Fe6imYCs01tHd9NjWy4tTUc7SWMtb+x7VeHa3R57uH3m8f2COAW0dbSv+GTd3W7799h3eWxSJp/2emArOKuEbFEmAfNfQZMXT44m339yxvQ3c3+/56cM9rtHc3m7wTmSInfci8EDBe4Nzmr73hCkyjcIpaNuWm5sNb95uCXnmw/1HHp9Gaspou8hWjyeMNYJG5USLxfmGtodQE4325BrQehZUcImbVcl9UatMUFAqIQVsWuSGgZiChNGl1YZmsWlebLJLJqYkehMU8SFRoo0jcsOJKUQab2mbFusbqhYROpnUsALxZxZUcyHzaQuqQRuPti3atGjtUZgzsF/rgvEqtYjb1fMymdMiHqQXq2ctxdK639dsvwIBWEt7fYaxBW649P6vR/mej8opZITwUgGuwec1i+HzF2Y9WIWXFef/Hcj6c/u+HtCW86/X4fnreuS/hD48f64c93os7vVzXXtBl2v2ssKW/TSfvs3LBMNq5PRpr/71tsprKMBLHsAlefvs235lU89+anUGsxAcZE24ypJ4WiCjEMMTVTO1ZnlMWzACo3njccbKdIA1HD9+IFHIYyBNCas03ipqynTe8/bNHTklhtOT9PmTuIe1nSyQa5JRKmAbfN9ivaMq0fXOOUmTb5kfrlXY2yUlcpLrZLQESKWVEJY0C8ypSUWYyKtgpjGWru0IzYxRYtmqlbC/tbaiRGYdMVZOpxPDNDNPlaxAWU/VBts4vGuxbS/kRFXIVdje1snUQ9cYbne9BPHHA8dTIqWZUirOOqyVUT/nDKYkIQ22LV1Feuu1MA4j0zCBriJJrFYkRNoKaoF5l+UPpw0lJqxSWKt4e7Pl+998gybz4eNfSXGg7S09PRU4ngamx5EffvqZh8cj4wQY2HQWa0BZvfioVEpGyG5ZPo4YCzyemGLBOY3RoqnPNNF6g/eaokVm2jWekCNzmAkxoownJWHgbzc7tDIcn0ZyFuGfu7c9b97eYKk0rnJyA/vjLLPizmBdi9JGbK9zIcXEaQiUBDc3DX1vMbaScqDGQmMcVVmRvbYNpyFxv5/58X7g/piJGUqE8pipbkbZGWzDplTe3G3Y3b0llUAEFDI5oZwCb2hsxxvv6He3bO62bO56ptORNE2wJKeYQiwTKhpynoG0uEtqqlbCLei3PD4c0Nbx7ts7/HHgdBp4OBx4Oo70+3u0K9xst5iccMax2WzAWKYx4Z1mu+spCXI8UEtmu+vY7Vra3pPHIAi9FX2O05h4PMyMobLZWjadpXEW02isdliv8SkwJSVTVwuXpmYJ/IUCRaZO1vWvFhmN1FoQGmPFrjymilkCbK6CBlZEqbbWIsEXdY5zOWUOhyP2oUF3njetB20EaVs+Q+FuWeqqiaOd/MGhtEfpDm1alG4E/teiZrgW2mZB7ZTiLP27GnmJOJ9eWndLyqBWH4mvW31/HQJQLxcR1uzkumK//P2qtnu2oF9IapwhjAXfuHSzlWQ9K5txdRU7n8lX9++vzv4rE4hnScD5/D69FnJu//eQiefbp+jDa4TINYBfP/ZaovEpqfC1wP58389xKn5dlf/LSIsc8yo5vHpcLZMlq0SsOs+2ZGpdtShEclS+1bKgV/L5y4eTvnRTCzclUsk0jQOtuf/hB7SaaLXDZCH33W06emd4GA7EMJGSzLR7b+n7js2mRSHTACknEoVm0+P7FuMNuUrgXr95pWRKjNJymGdylEXGdyJHWpd73LdeeARKvAFKrYJYVHDG0HUdNRf2TwfmLD1Q7xtSLouBlmYOAvePMTHOMuZtUiApS9WWZrPh9s07um3Px6cHjuOR737znv/9//W/U2rl//qv/5UYRo5esyi5Mi0jbNutFdJbgc46nHaiRe4suVZ0sdibDZ0zHC0yelmjtD2qICHWSOUi8/WKru3o2lZIkjlireftm1vubnd8+Omv7PePWAs6Foy1pJI5HPaE7Pjxpw8cjokQoXVAKdjGYZSiFtET0E4Rk1jequX9jCGSSsI6g3cab8ApRV4CjWsbNtsdrgU1j8SFLT4MA8MYCXOhVkUIhWmSoNBtLLublr53OGDT3LLtGqzdM8wR7Ro2u1vatltEkgKn04n9/gkwvHnX0/UGYzOraFKtioqhVEOqhqfjyM8PA4e5ElBERKwpHmEuE1WPNP0O3zoSnqwcwiHTGGdQzqC9pXqLrtD6hqatuNaxuWkZDweePnxg3O9xWlFKYH+4x1tLTDPWQNN6FBBSwreWzW3HYThhnePu9j3uaY/bW8Z44sOHJw7jgN4rms5jkvBbmqYBrWWCRVfatiFvK/M0U0vm9m5D01qMBeMN/XbDmDXzPjDMkadj4TDCVJbvyM6TiibmCsrgfEMomZwzKcvoIRqcdWilResgZYwqgswpg1JVVo5asNotdtx6QcAUIWW01RQFqoi8sbIarUVfwFqJWdMwsn/c4/oO13fYzZbWFVHus1a0KJYKvRqFXfr94FGqxdmeqjxKeSr6woFCyh+UWZuL55W61sU6WGuUMmdUt54Ra/1q1Hpt+3oS4NJvPjv9XVXFn8bShZ+olrNdA6ZMCq9PYTXsqeWaC6DOB11bHtfQ95f7/a+f+Wd/8xXIw/kdvejZX/7+6f6vMeS/7jyvMYaX1fglWD4//ktdgFV46fmY4LWR0/PzfS0BeP36ft17ev4+Pn+MzyQtiwnOmgFfDImsoEoUZBx1RQVYqvNMVYZqNDVXlEmYJtLe3FGyLGYpRR4fP2JDorWWcppkVl9VxsMjx/0TKc20XpM1dK2n6zy7nWjAh3liihOqFlzjMN6A1eiicd6iYkGRFindxdSjViiV0/EopDLvqA68M0JiohJSFqJPAciUUkUdTS2iP4jh1jr/HdNETAlTFNMcGGZh+ovSmDi9pZopSqRFN7stTdfC/gGlYHe74fd//D1FVeb9Paf9A6fjiUNj2fQiTTvHgpmD2MdqjbeGrvdLW6JArXgNWVe61kLx1DITQ6IiQX+dIqhK2gfGOBl3zBWKjM8ZLYIoc5h42j8wzxNKC8ns5u4WvwgoVe1l1lu4abStkYkJrQUwrQpvLd4Y5jzJLHhVVHvpnZZaCEmuLRY23rG7veGbb9/z3W+/wTSwPx4Yp4mUCzGIY6JSmnlKhDlJUOkz2mSm+cQwwq6R0cOuu6HvW35+eEJZy3bX0W97AHKJnE7QtolaFd3G4F0RTwull0R35bdYQircPw18eDxxnDJzUcxJFtyY4BQyxg102xFtPdZH2m3AN0pMbXIVk6xc0HkZ67QSuDZO4xqFtRVNpPEQTsMiu6swtFirxUpZiYOgtYpCppD47rff0PY7ajHYznL7ZsuUTuQqZlhTmCSweg9FplN0Be00bddAtSjEU4KS6HqHb2X6xFXL9mZHVh1zPDHOMzEnqoY5wxArPlV8yKAi1jVY16DmWSrjKiun1pwlc03OxFgkYagFp9UCl0tMicv1yYtRGVWSSBOluq41k3MUoZ6luNAoSspLa0G+3/ahwXY9pvFi1hMTVJlAkBVRY52jIgJQWjco3VCRxyiaokWqQCvRj8jnYnSNs2pp0S4CUFfS+wt2iMLwLCR8YfsVY4D6UrVVeTOo53D0utVal0ptCfdnwqA+twYuQeJCdJPXubQRvtQXf0kG/PK5f50w0CfPUfB82qF+8uv/6HbNdXj1+i3Z3BrcP3f6173zlwH8usr/2hG/T5GDTxGX13ga1/t+abtuFV2fyhlpUUjZ9my8cb0nVplpzUWYqi7/Ngv8pak2o2pAqYhmQ5N21DLTn7ZsbracpkDJEUWGlBmPe8IspKSUIsZUfGPZbjv6TUfbNgtBS8lYnwJlFFVBJpMX1UCxX2WB//PZjrQEiCEzHI8UDVu3w3eWXDK5RFKtONdRckXEkKR9kCjUCs56sis430hPdZyXkbFCzJnTOLKIBUqw1UbadMtC9sNPP4LRjPOJSubx6YF/+v/8v0EV9h9/pHWaXd9w2DSErBjDzDwUpjlQsugBOAPGbmmUoyxSR85ogipYp6C1xGRZeNZC/JWmKyDCRllppnFkOhVKCqJV3zbM48D9hyCTCMvsvTGGrhMXRZRifzhwOg0ooGnAKENrxFlOqYI1Cq813hh04yWOVkWKApdW0YGlUkm5EhVsdlt+89vv+e6373j3zZ0YUmmRHb7/8WdKMTi3oWQ4HE6iPri0Vqgj03RkMJlGb+m8lfYODq0KtYgMoXeVphVW92ZTaJrC8ThhvcKYLPcgmpwXd0admaPm6Wnk5/sDD/uRw5iYgwzpVRRFVXLNPOxn1J9+Yr8/MM3vsK2n3xjajafRDtSSvCmFtoI0FSrWaJRusGZL31rG3vHw44+EsSzci4LXIshVl5aWVpUxjjBq/vD7v+f9d78lhQzaEqaZYT6yvenQGj5++EiuknCJAJYQmruuw2qPUTMaac/lHDFOicOfgRKESNp2G25uHKfhSEwnlIVqDKmKf4G3SRxql7HevGj/X7hPlz69tganFClKYp6rIud6Fm+aZ+EAUC1WV6y24m1RxZPFWUup6fx8u1iZ52WKBSrzOPHw8IBqPNo7NlrjTFlaClWUAEsVBEA5Kg6jPZXFVRPRJmBBz4taY5x6FhNhnbRZOHjL95wqPy/h4Oui01cnAKVcAjbrS78go11v14xwCdTXkO+lT3EdQ5RSZ07Aun+ty2LyaqBcz+fLlevL7avg//OxX1bi65Pr+eHXAqvM6P/ydkli5PXWpEdeVa7BhRPwnEexvvbl2i77Vvm8JLHSz1CK57P4r51P+WwP/zoBeK0Nc0k4XrYdniMZr77uAiepT55/2U9eY32tywTKeg9In24ZpbEtSkWoHfgOfEuz2/Hm/Xvmxz3j/ZG+isfAMJwARU6B8TgxzJWtW0VmxMQjl4xuHLo4LOBaj/UiylEoMjGQRZI1RwhmpiK+9blUNtsdU4ykmMV9zHuqSaAVdlEAi0qqQWs0KldIwhPouh6qxlmR+k25EFIiV71USALT57LeIQWUJuXMOM3MKQliYRXDPHE67Pnh3/6M0fDzX/+KLqCKxiqFKlnsWpFlSdVCDBPDqOhaJ62QmrFG47uOvvXCb1CQU8RqkTrNKVOSWK065zALWSmnRAgBo2Tksms7QohoXfjm2/e0B8X+cM9m27NOtWhj+fjxB07DRExiolRSoWjFHCPeQdN7rBbtAt/LvHpJVSqxpZWYS2aeZ+YMrld88+0bvv/dd+xuW5QplJKY54Hj4YkwB0JE3PtOgfuP95QMXdfgrcG7lsYqYbpTqArGKfLzh4/8+NMRZcQRsd+0bHYNXW9o2obKREgjxso8f9WOkB1zKtSQsSlxmhL/7U8/8N//9DMf95GYpfotVRJEs2iCDCGSHkaOw0zKiVgVv//Db7jTDbppsIDSDmcbrNVkkshal4Sxis1Nh+odrYPGKeI4kqaZGpO8hhU0TVoYGd9YSs6EOOGdof3mPRxH/vThJ5w3/D/+t//M9vaGf/4v/wd/+fNf+Pgxsut2+K2hqILByP2tCo2D1vfUZa4eiogb5YbjMTCMM2PIxJwZA5QCvdcULHPKhFop1lKMFt6MdxSjqIuAmFIaZbyYV4UgKau12LWgysKRsFYzpyCJM6IF0LROWleLPodaRvSMszSNY7vpaFtHKoFUE3GaMKoSDoVqrSAAXUu/W/wdyOSSKdVgK0h5bkQRclnbFOIWqZTwWdZ17mJBXxHSsxTjK6K+ro3X5G6Z2Lv4G3xp+xV2wGslusDwS3Wynv7FLniF6dcAgYwsIH2LS2LwekX6aRW+VIssSUhdg6M+JwbPEopz4JXsotSySON+SpwTxvtFWW/5GM6vK08WJENeZUEq1tbE+eNb9+dZ7PoMkM5a715EHFZU5RI4xSq5LgS3tYpfAq6SCvO64l4/lwt6sk5ofAkBuVyH67esxEh8fQYs8pfnkcQrGF+u+fmsZR/12s23vv71OOL6Xq8v3DJWVytFyX5qfc75i3G5J64eRFEXC2ZDrlaya91Q/QbTzejmhG5aXNtRmgGmQI6BMs1UIE6REgteK276ju1mR9N2FFWIsaKs5+72ZjERkgVcaY0tSx9OacQrFJSPVD+hG41xmndv3zMnYevnnCglY9yiCtg0TJNwDGoV8ZFaMiVlGmOp1qF6jbMt4xQYhokpJKrOHE4zMRdREM0sE0PyfRA1vEDNItAzz4EcZ2wBjxAgyTAMgZSriM7MEZOhBUiSCFgL5MThuCdES9M2eN+hVKVpxK/cKMc0a6zpmcNMQhOLLNzrdyXlJPCm1aQYcL6lVJhjYLPbsdl1hNxgZo3zerkPYRpm5imSo7DocwXvLDku9702iPYFizyyR6EkCckLMTAVQqjgG7zTfPd9y+27hjk80MUeSksKE6YkpsNBNCTGzJwj85xQOeO0BC9bC50ybNtOKrEKp6nwtB/4//63A/cPCd/CmA/MuXKcD/zh9+9489Zh255qIh8fZvYn0HHDcYYxKdpdQx3gw8MT//yvH/jhcSQkTUiKca5ApnEWjMI7h9aKOQWGY2GuB04JhuT44x97tG9wKdPWgmoLSiVyOtJ2jSAIYaZaC7age8PG3UDoydPMdByYh5Eas9zSqUIsOO2pyvL08ZHD3QPx8YnHDx+Fv5Aj725vGIaB1hh+/5tvGfZHyjygGnFxNEXaW94m1HKzVsR86+l0IlXDnCBng2086Xjg8fREAnRZdCc6R7fdYnrLUDOJgHEN45SJRpOtcChATLPwArunaSLMAWcNzjpqXpR5tMY1DpbE1jjH7mZL1zniPDGMI8MQJE6kSoN8zb1V7NoN4zxwGE/kmjGqW9Q7R8I8kdIMFHIF63uKcYSaqGUxtVpankZJS1OW9hUF1AtHYYmvCzpwjY6vBfSF+Z9Zx/W/Fp7+FQjACtM/V3Bbg1CpEpDq6qy2wNhKSQWPWvd5Hmyut9eC1HVN+Yy4tgbctVK/tEougUypq1d8/fifbldIwxL8zwe+2v3ZsRTnT+McBOtFnOH8tBfcgjPsXbkEs/X81QpzL4nCGgDJ52RhJVZepQFXx7h8tJ9LtF5OH1zOsbwAVS6pjrp67+L8+OJeewUUusD9r/E31qx2TdsskmpdIS/Xx3yGdlxOUVWZGDBoKpaiLbVKZYeL6DbS30ba7QOu78nHA8SIcgqdFWTR1jdGiGt937Hd7ei3W6LKhEEG+qqzouilQDsr/VtgHAd0Aa8N2reoNqPbGRUMNcEQ8kIHENdBYSsbUBmlpFJtvKdEUSFTRYSExBVsUU1LhXmOhDkzh0QolcMxMQYwXuFbT0qZeRLtd7eo2k2TtCFyCtScGJ72/PzvWiq7WVTZak4YFJ0FWogOUoGmE4TDmII18tmHMGGdpmktWhXCHEAp7m52KG057I8cDifmHEBLoSBKg2X5ula0gWmeKaUHpdjvHyl1oNQZrRSn05EuK6wNKDPhlKX1Dc7IhIZ2kihpbXBOElHRzBfypjGKLNQQSoIQxHfBaINW0HUO10AtgZQV0xiYxomSAgaYTyPDITLPgkpue2lHxBhI04SxPY32FKVIwNMY+fNPj/x4nxgncBnU40zSCUzDu29a3vpbtm1L0Zafnn7kxw8DQbfMdUvSHhU1h/GJv/70Mz/+NPC0l8QlikowKAgh0HdSjSotRMZipTf+15+PPDz9Cz/8eOA//eMf+Ie//x6N4SE90m9hsxNFxGbTMKpESlJaay/qg1lVNA6vO7Q35HEijJMoH3qz8EEs8zTx3//5n9nubvn2229BKY6PD/zLf/tv1BDRBXrjmFMmjiei1di+o6RCiJGS63JHK0JCzKrGyHE8MRUFtmMu8HQ88nhKktwCtVSmGHEhUD14I8S5HDMfjyf2IRIWTX/RSM1STuRKFUYqUwjkXNh0LRpLDBM5LoqfaHIyhDCjVCbME6dhomqLW8YBUwqU4tDa4q3cV5aK1QpnDW3bcLfd0jlLTTPaLB4YRYHW5GIpKomiJyPW9iiy2PtWKSLEFEikoCnl+QJYL2v3ZcLuCv2lXhXGv7z9iimA59uXmPj1HPyvKvQFnHxJoHteJ68V6VrpSuJQztX2BfKtZTniy/79VfAHqWbPl+dZtfu5i1SuzqhesJhX3/+nwf15gLsKYp/87rXjrc/jLPTwmkbC+T1cdl524pNE5Wu29VpcgvDnD/C8hbBObrw4/9f3fPU4l9O/IjZ+4eZ9jY8gf9fLBIFAYVpligFdqyQAOWL7RH/7ht3bt5g4g9NkC0ln4hxpug2tF+JN9ZqoIlOZSTVTDVhrBVafZ4yzuKrEKrQsKl9ArhqKoE7aWqy3SwtBkjjrPF27oes22BZyncll6VVqCCkShhGzSPzORbzsS4YQI8M4EZIYikxzYhxBOXDe4V0DKBpfRJEtJsI8kFMm1BmoGA3TMPAxR7TROCvWpKpEnCpsWkPrRWQnlUrbtzIOpTTWCxEs5ECYMrMt3N7s2D8OpAKbfsc8TZRSsNbQdQ2UKtoATnTZUwzUUsQ+eTE5stpwOjwRpgObrcdpR0qZxjVQCrlmnDX0bUPfSjBsG+EKWKOWvjWLjbOoDFbEt8FogYWLLhjqwgfIC6wqpMpaDdMQxUK5VLxtgRPTMBOiYnfT0HcbQDGcRtKUKVuL8d35OzCPA8cxCelQQywQMsv4nAe9LM7OU7Tjfl/4p38+sp8mqt9RbMdcEx/3j5yGSAiZeVpG6CV2UCtkVXEOcW2scuzeKEpKDMfMh9PI/Ye/cHp6Yh6P/N3ff8vdG0dRikKhzxnvHN44Uq1gpEWYUySbgmqk/25utsynmfLwSDIzXmuOh4FhOLDZ7Bingbu7N+y2W/70pz9xejrweP8AMbPb7DBUwjhRYuHwdCCGIG2RUkFpjBUJ5JwLIWRCjBynmVAdqtHsx8THx0emsKBaottELJn9cRALX2uYT8JVmWdNrV4mP6QHKmO4S3VlrWiDxDAxjhFNwShNmCc2jcNbjVs8acYhMk2BvChu+kZhlHgEiBVyRiFSyJCxVmF1pXOWb97e8d3bW3znMLrgW02iEPMkwmbGo8iomqg5ofRaTUgoXs2G1pYA+vlaWF/EnJcxTHgK5oxs/9L2q1sAFwTgeUBd/Yyvg/za088lLYYM5gyXr/vL83jx7+dBs5RyftI5KNZPn/9apbsmEl967iXwPH/P0q14fQTx/HvqJx/CJ+jAf2RbcoevIe59afvFa/PK8ySDvn7u8+d96Xz+42d6dYyvTpRenGOFWjQCXDtpo5BRukO5TM2J/vYdd999T6ML4ckQHEwmSx/PtHhvQBXcTUttFKYVolqTM+McCYuaoKlFxs20kKusd6gs1QZUlFFY55jUxBwC2i0IhTPkUpmnsMwLFwoKawy1aoJW1FJEs51KyQpVFCnDPGdx8MtFBGqqaBWgoe+2bDYbxnFkmg4iMVsF0XBO+tQXtTCk8tOicFjiJEI+JHqvUEb0DWIu2MZiXScOizEQc8BajVKZ6fSEUxVrNe9u33D39h0//PVncspi51odKUVyDMw5UmslzjO1Fhpn6LtOULZcsMagKJQkCYNzXpTz5gxKvB/6VtE1apkCkBZBCBPDGGmyZtNv0FaknVVBFNGW/qnc1gVqWlA0TQpQGimhldIYnaBC12nevbXM4wdqtdzcviGkyOPjA9McUEVxCoVNrMScOM2Bx+OJKRWUEcqJ1uBbRb/r2d3tcK0XGZmqKXiGyfDjfeHHh0DWDwS1ZyyZ4yiJpDNS/OXMWRYWqojBaCcmQwWc93StpYREnk4EVckh85d/2zOO/8T+8MB//l9/z3fqRiR6o6HEJ6zT+EZ8IVIKop5nNTKl5sTQxxg6DWZOqALdzY77nz9irJgJfbz/mePxwA9/+QGnHQ7LaZp4GD5ilRZOhtKEMTKPE7512EZGX1WBomTSpW08nCKpFOaYGccjD8eRORV8ByGBdYgipzVgLaUqhrFwGk487QfGQeyuxbYelMpYKyuZs80C5hbaxlF0IsaZgogn5ZzJStQjw2IZrjV4Y3FOo8qIQdN4T9d6tIY5zmizOg4qUk44q3h3u2HbaJRK9G2L9jAmEXDINQIRrRu0VjI5xEULZ9XXqfWSxFyve9drdCnledH2H4wRv0oI6LXF99kL14spzrMKTR64fBFfbNfQeF0r2TNPgAUJuGgGPCd/fR6FOAf4JXl5OQr3pXG9C1fhcxf2Ze/609Jb6efJ0ue218/hcwZDn3v+r9u++L7Va89Tl17/Cj293I+1I/PLFfzzxy6/+2Jy8QW+iOjRK4HalAElfWAhaxa0BXvr8bqiS0ITUVoWbLfzdCExR6jDSIwzurfoTov2eWPJc6HMQgpyzqGXaiEv0rFKieCQ0aC0xSlLmRL3P33kw4cPeC1kuL4X4lMm0kdH0xthFitDKLMMCBlz1olXVdT+coI5FULKxFyJuVIxNJ3l5u0bus1Grsk0orWi61oaZ5eZZZk4iCEQYxQGNAqVs2i1U1Cl4JQkLbaxoDUxF5x3NF1L1TAFEI2dTIxJRhCPT2xv3vL2zR277ZYHd89sNdnopSUj8955EUkS9zMwVhbfEiNRCztaayirf311jMMMSgiMm67lzd2G+6cnDscZ2yR2ux33DxOHQaRj225iu2tofIexTlaLClVVbM7i9b6sq/Mc+fjhwDiObLctu01PrR6qovGem13P/M4AIrp0+viBYZiXz7lhSorDkBjTzIf7B05zoOhK1dBuZF7cOnX2jBCkKFEwKN+D25A0ZAUBw2EuzLUQFecgYLQRCV4lSpQrQz+kjJoSuncY7bDKoqzB7DQ17Dkd4TBUcgnE9Gce90/8b//Pv+c//eP3tFYxU0m2MM8z1oEyBeuFUV9rWSrWjPKGzbdv6YoijCMuF7Y3vUxE/PVHfvzpQeyV50LnO3RV3PQbptO4yB4nqlE0vmOaB+KcWBtaymmMa6X1YDx+mKlDZJhHnobIfhZ/j37b0FDRppJrQiuFbRypwOP9E/cfj5wGSYyUAmsF+Vmmh6kVwjRRk9yLTSNjpCWytIsUBpHXNtZScyGlQk2V4hWN1uJMirQInbdi6TtFjDNs2g0ax3E4keeJOJyYDo6md9BUxqkSlQa7w5mGQiCXGZSH2qKUyBCrupzzGdK/EMJfBvk1bn0Ozb5w7X55++oEIC1qUUp9Ci+8rCQ/PbnL/P/nqunLdpUkLH8xerU+hGcoQ/30GJI7XN58qVVsSK/Ifp8jAZ7P4Csv3qeIxWvB7bli3uf1BF6Bel4896vOscKK0nxyba7O5TXU4rqN8mowVlx4C+sD9bXz+eUE5fnrX1+fdXLh86jKZ7kiSqGMnJPWMlaTV49zrVC+QenCHVlG/TpPHDak4USKMzFA+fhAOd6jOotqFIGZ4XgkRWH6C8zcSBa+9MNLKfhlzCoWGS20RYERmeApZH66z/TNzNt3YmAUi0PrHc6LoVBJE9M4kOZAzokUI/MU0dWgllGhXAq5SH8z5kJI4Lyh8R0pFmKS/vnbt3dYpykxEOKE8HMzRcsonDXr+FAlJxE5MQaMVVhTMVr8O6wC7xS1BjSKpreEWDkNkUpk4w0JQwgjP/zl3/hL/QuPj0+CPGiLtw6MMMdTkJlpvcDZMqctSFPOkUxBZ4FTE5k0Trx991Y86m2g6oyyhbYTboJtQLvE9s5imkQtlbYX4RvbthjFYuFcxCXSKpSt1JjJNfD0dOB4PKB0oe9b3r+9pWkajBLp4zAXUqikPBP3A+NxxGhLKZWUYJwy+fFESDNPh0gBfNux2abFWEmkgq1DWOXWklKmhpk5tEt3GhJCYqxGL/B4QWuZ6AAZtaxUEgmLIpdKTpEKbJXHGAeAc45N21FCJsUTK0ns4bFwmp/I9V+IIfOPf/uWv/n+Dd57pvFIKYW2t8KhsUaUC3MiJrEC3tzuUBjGgyGeDvTbLbZ1+NZzv/nI/Q/3ZJc5PRzIY6BresI80TX9Uj5pXOPJNZLTJHbAKbLd3dJ0hmosOVfatkWZgdM4Ms4ZhUFZg28bdrc3VALDcCItfhPDMPLxw8D9R0grQmCgugVRXzTDaoFNB5utkvG+JPyYVqhGxHlGN7JeZsT+tzovtsLGY21Bq0CoiTEVXMjYhZ/T64akBILT2nI8HPnLn/4v5vGOt+92DPsPBF2h7dneVjbdFgwMKVLKSFIOZzTZOPSi5Ke0omot8D+cK/3rte+XYtdzfteXt1/NAXgtqKwvrPUqTPAyoJzBDc4sxXMgv17QBSWQbdFvVqAXOcTlLcJyNP1KANXLjPjZeRC5Ces658GaAHxdJf35QHQdkJ4XvV9GFT7f6ni237Xg0qfgwhrxuARh9exEXiYXL1/ztXN4uX2aBHwF8vCr0YnXblRRXnv9UHKPvN7qAWpFVyWSAVip6lQFrUjxgKVD9W/p3iVs5yjzHdNpz3Q8EEKmtB2bacO2t7y529AYGE4yC+2tgWooWrLzkCI1L85pVu7vnCM5JKhKRq22Hbe3HeNhpCiYp8hRD0xRKn+0wlqwZrWWrZhlztfofDb8qUtFUJVGGzFBSjGhTeVf//XfaPtusReGaR4oY8IZlkRgRgONM2CMeKeXKoJJWZjeTWOxC7KhF2/4opAWRQVdRS7V6kJjpe9dqmHMEOLMKczEVMQ2NWZSiZQyoJSM/lFkgbMGEezxHtc46lptKlAkcgWlBVof53lhDmVEES1wc9uyve1ptz1ttxXelBJzGK0tjWvoGuEehBAoMYgGQZwxx0ohkkZIJTOMiRjg0USOTwPeW7Qy9N2WGATliLEQ4jK1YS2lCnkxlhn2x0UdHjCKEjNt03CakyA5CkwteKPw2kCKhBpIObDZtWxvNOqpkElo5/DKEEoRnwMNumbQAVXV0jdGesVaVsBcBMq2VdO2Ak/7796x7TqejifGeWROEEPlz39+5LA/cbj/luP+d3z/22+wPrOzHophnmdBgBaFO+sM1hogSTFiKpt3G7G4rvB+94a29+w2HWnMPGweefzhnhQShSJ+CAqUtaSaUEamUmIWUZ1SErWKsFDKhaa17G562sc9T2NGW2i9p9k03N5tqWWmbTQ5Z2pVOF2IM3grS47RirZt2XYtbWPYbh2brbD7HZZtt6VWeHp4FBMiJ86JHz8+8vE+EfNMZUY50NqhnadVGqUNw6RwTpMmTXTQd9J2CaqDqHEGMA0lDTx+fCCFEzW/QTvIjcFutnjfsi3vMKrgqCSlFlm8gmElm9cz0r3Ona2tqzWCKlXXHoFkOOrSrj23bdXn1s5Pt69OAK4FFq6DyPpHYIcLZ+GSABSUVpwD+heqWnX2C1iOSxZpRLOM+ZXn+55D8VVVW1dN5CW5UBIJBPo7w/osXYXPtxAuz3u96n45xvaysn7Zani5/8t/vw5/n9/JK+fHJXaqJfifWYBXR7h6j59rf7x8zqeX4/kDl6z0OQlwPU55uftXbJ+2Yy4tnufvZ81zXqBMIFAaZ3HqRfhEAWL6kYoj10iJmpgdprnBdz1mc4PZHmjGwPbtHZQZpyZMCcTxIOz5VKCKME7JMptrUbSuwVjFOA+LRasHY2mqJdtMuNky3Ixs/5cb5jHIaF7OlJJJSckoWy5iJ5wLpbDwCEBpZJ69VNBGZpm1wjmPMYlaEyVD32+JObHf7/GNoWstXe/xVvrlppUq0WoHRXM6ThwPAzkl6ad7R993kgBoLYx9o0HDOE241qOMZgwzuiS2fUvOjsMQcbWSWBGrhLMtp9N0blvkDG1jaBtP4y1N49n2PX3fUYkcDo+UkmgXydkxTFijadqGMQaapqHbdPSbDe/MO1LJWN/Q3+64ffee0zCSUkZhUUqU37z1KDRpnonzRI6BMA08PbZoVzFP4G3HdJyYp4mUMjHINEPNlRw1pcA4Tqz1Sq7IpJPRWOOpqjCHTFWF7c2GXArTNLHdbCitwZlKSZnxcGA47Mi3FttqGu0oKXF7s+HN3Q7+/MQ0J4qr6MXlLleZuNAg0yAazIIIalOXZCcT5pkTM6q19E5TSby9u6VrPE3veTpaHp4OHAc5f1Ui/+d/+XcePzzxd3//N/z2d+9w/ptFBheyypSYUVp66apEptORkgshJ4rWhDTS9S3aGm70jm/evGE+BXzj+f7bb/j40z2ng8jjhrAw+DLSS1cKjxjsVDKxTJBFv98Zyzfvbvl4PPHjY6CS2fYO31mMzuIZ0Fm87TDO8O6u5dv3O2pVWOvxrqV1DW3T4Jxm0zs2vaeWxPHpiCmamgudDoTgaBpPiIm2gbu7wONx4OM+cZyEbJvniJ4mnLM4Xeh1Q8yOGB2639D4jrH6SyFpKq231HRkOg3EocP1llQmsoLxdCTMJxp/i1FeDIeMEclgfWl1S9yTAqhSFxdUzqP0F2G4+upPIYyqRSjol7dfoQR4tcAvZgQgffVLS+CV4KP0pRp/BXqWbUUHBAJWui5veOn7L4/LxV5er9ZzW+Llm63XgX4NjGuwOJ+HPr90faZP8OwNkM+Kcy9YlWr53xrwWeDrBYLXy3jY5yB/rn73ueB8bZT0WmKx/nyN8fk5COhz6MP1z5LLuQ2wXAa5fHUZ7+RyDRVAuSSC67zHs0u1JgvqMk76slV09ewvvofr/a7bOVDPinzrJECtMj9blaMAxmwBkZDtfAPlRE0nMh7TN/Q9mDpR0544fKTMAW80yjtCiqRxomSLVg7j/ALTKWKMqFJJJcr9iGKeR05PUoX53qOiYbe5YR5G9vs9ORWeHvfMYWSzbdl0buljiqrZhVOxSPuUjDEe6yqH44kUA95Lb3+cJuaUFq1zMeRBCelQO4PznqZpyLFQcuX9+7d88/490zAxTQN967i73ZGrzOp776lacxyP3N7eMMaReRqgSnKdQqSUQuMtTjl2O89pmHh6SoRpYBlVJysZU7NCKeD9+3d88803UDKpJBIKkw3zMFPSyKr3oAyEmvnm7g1t33Bzd8s3331HUpXbN3fkmphjwjQW2+7wzpMShFjYbW652d1ijeGHf/93Pvz0E841uFbjt4btm477nz4Qj5Ftu+V0OvH0+EichPil0BwOp/N91rReSIWpLBMGhlqjSMUq+Z7kOWKtpfeeYb+XYK3kPt94TziNpGmLzpl5VsRTos6FxmgsMuNOLYxzpijwbgGtqpjT6OWORoucNUbsj8cMukKjArEdKaUhlxnfGH6zeUe/aeh6z8P+wE8/BX7aw9hWcjoxhz/x8PjEOA787d99y82dwyBqfMZWrKqYnKEUDNCYQowBXCUSUUWhtCJOkaoK3/7+O3SAm3d3PHx8Ynv/wDxHcs7M0wRphlqIIZFLYsqRrkSKNkypYrot1bTsNoa3b+Awg3MZawKHxx/YNJJ0vX/7He2mw7dyXz8+PjIOE23j6LuWMEfCOJMmzZA1uhYaFKfDCWMUtk58+90bvvv+N/zrn/+E9zuGkPlD/weehsT/+d//xL/8aWBaZLlJBedaPs6Z29pyqy1P04n24xGnMzed5XffveN3v3lL7wt5tjjVUGIhz5HH+ZGdd0KcLVUmcvJMxNLqDfrKLVICnCy4sm5xrqZeKyLXe/R6TbwU4/WZE+Xntl/VAlgX2tfIc2tP/tm/1/2uMOxf7u2+DMKfPrQe5zrwXxMJL8dbz+saRr8EjF9GAOqCXsif5/FIPfuprne7SpS+tF0nRJ9DDj5HvvzyY58Pop/jADw7hxePr4d4+TrqnBl83fY1fSm1Jla/crvgBZmzYdCSCMhHb+Q2KI6qeqoxKONAO8CjTUNOk0wnqxnbdpQ8Mpc943AiDwldLGUSVa/sMmrRR4dMWXzPU0qQMnkKzKeJlIQl3/iGeZAFsWkaSHA8HjkOlZJ39M1bUqqLGYnYkVIVMRaMb1DKkbIWMR0jekMmQ5IZAiG4Lkp3VLNIj2oxIylLYrr05pvGYY3Dao33mq519JsNc5iZjzPDeEJZ8XSv5HPCr43BOUdRixVqrpimI5RKYw03u54QCqdhZg75/Hk2jWe73dJteozRaGfofMvTlKiTJutCLIlN0/Lu3Xvevn1L2zZs+hZtFb7t6TYtUwyUkkglEovYybZdj7Yao+F2t+Ptu+9oug2HhwemHMi6olSRHnRNaK/pbntUGmg3DZtti9aa/eOeEguqimnNOGa8B++LVIHOYYwm54KqBaPlWlYlgbrGCLViWPwNFhkPTaExYk09DZGiKqfjyP6hMO9PpAnyLBMdSryWyBGcFk0JZxYLXCX3tbjMaVRNqCqmSMZAjJFxPEFNbNqOvm+4dRuaztP3DVr9xLBPjAd4eqyUMp4RIKsrNd1xd9uw3VlsqUyHI0oVbnY7mqZhSCNFi89D1YqMoIDaa3HhzIqiwemGndrhei9IYamEaSLPI3kciCESUiLEtIxHGrqqqKYhactNafnm3YZ2SrjWyChvztga2XiHUzN32w3/8I9/AA3/9E/3TMcnyDOqZjpvIUXGcWQ4BEFNMmybjpubLY3fYp0hjPfcbj39xnIMlVANAbi529A9DUwHSCwIoumopfJwyjweHyDN4gCp4d2NwRrN27st267DNB1Oawm+aqbrNrRNB2hCKnRVY31LLX6R/laIVP66gOVL9c/nCuZlzXsFkf7a3v+6/coEYKnQr7KOX97W572GElyg5JfnfWajL0H708NeoPfrN13OrkmXPr/iopNcyZxbDPWaSHGJZWtr/fKP5+/n+nrIU9aZ+MW6ka+7Pp+rcK9/97lj/HJr4vPHfO0Yz0/scqz183kN3an1Nbnjtdp/+ZuvvTF/+Z767E2u6pkMeGmPVM7+ASjQ7VkvoFa7KPc5lHJoM1GLgRpR6kQulWEYpULcz7jqKdliTYuvBV0tWSUSGXO+zyCmSE4Biii3ed8ynYJU80YkfVVSzCEwzwLHd13LdtPifUuMMyEGUooyU54jKQYZBQzyHXTeYIvFZJiSplGGYjRCK5P3n7N4ClglYj8KIfWthinKKHzj0c4QcyLkuBi+FJw2OGXQSznfts0y5WApikX7oJIqMM4EMl5rqpFWTF20AJTSxDSTSgNaYG6jNbEkjtPAftgzxYm3b2/5uz/8gW+/fY930rttnSeWKKI+RfrG43RalD1FDTOGQE6FmCp6nEkpYbTjdBpAF27ebBhOR7Qx/Pb730HN/Plf/gcb68lTItxPGKu4e3OLKnD/4ZGPHzN9LyQ+Y4Uf4awnxEiICUXG6QpaNO5LEYhaIbwkq4VkprX0sb11DIeBjx9/ZowF5W6ZHys1FBrAVMhZoY1ZbI0X1Z/F+0JspC3WChFTG0hpIs1BGO1F7pE5TNQS0bpyqzfs2pbNpuVm19I1jtNx5OMPS2UeYBoy+4cDP/7FQJiY3vXc3Dbstg1951GmMB0mOc+NYybJtIESXQookn1UIaUqpVFOo/uGxoqcda0V4zUkj7ndUXIhxsjpJN8vpTVoh207qnbc3BZu724Y5sBcFOMUGRvD1jW0jaOSmA/3PN03lBoxTPzu+zuM86RYl6um5Z6oBactJYr5008//zu1ilNkVYXf/e0f8N5jk2ZMBrzh3WnG/fUDuVSKFlvgYUo0bU8hUotwMmqSBeZ4zDw9nRjHkbiz5HkiqBlVFVM+4e5afLuh3d7StFuM6zB+g6YF01NfIssgBlpUlDaLlPXr2+cKzK+Pzf8hBOB5z/d55vGFinA9n3r9b1EHE9b3KhG7Bp7L06X3/0KsRp54Ppfzy1xF8jVB4PJULtyBlxnTpYdSlxP5NMi+Dlk/r5BXy97PQBdX2zXD89Of+kXuIf/Qen3/6/t52UK4ei+vXZur7UvJwmvPXxOya9h9fdFnhM+vvPleO48LCfS1TX3yeT0HIa5aRvD8fl3aNYqFKrwcIa9tCwXaOXJMVI6UYpiTjJfFmBiHgeNwRFWPb7b0VLwS0xmzXH9TAW0wzhNDBp0xaJw1RKN48+aWvIN5cS5r24b94YlpGnh8PIhYiW0RCWeBWFdVr1zqWZgkhkyIUEtgjFBo0VaqemMd3il8I7NOpURKNeeR4lwyIYkokNIKbTS5Zk4hUGuh6VusF75PyplMpek8KC0tgpTJpaCVmN/01mKtpeTCME5QDZu+xZpMUZqQMmGKjPPE02EvVrXWMExHPg4fmWtk92bHH//+j/zx7/6WxlnSNAIGYzUlLMF+neQpYJzDOosKgRyTSONaIRQOp4OMli28Auc6nIW2cfz2D39DnUcO9x95Cj/R7RzO3FBK4fA0MIVArRnnoOsV253He4u1GmMVMVWUqvjGnNeJXESroVaDUSJFrHWkaSxay4hXSoX9fuawH4lZ0e5kBPJ2u2W3eeQQoWhLqrJ2NE0vqE1Z4VyFcY7Ganrv0KYyFk1GGPB6QRxyrWQKIc6CBqiMt57eW+zbW3j7lt99+z3Hw54UR7recLPz6Fr5+acnHj58oO00795u+Zu/+YY3b3dUnYlhwsRE6SreWLSzpFJQ1aBdg9JQSFD0AllXFAWSjJdqJ9mQQdEojUuJjDq3cNFiX6ytod/03N7umEJimAOnKZLDDa225BwZxj3TfOQv//rfsI3j+99+z+//8Ef2+yOHw4D3HcZ6np6eeHp8JMVEComaCo/7if3TQC2V2xtN24mV8LwfaLwD3+EMxKEynQQczCpzGg6oXSKpiCGyaaDroLMSQOMUmMYT4+SgJBHT2m7wuuVUZ5rulrs332L6O7J2pKKpyqKwUu2vBcqSmMBK7LsqXH5hu26L/k9LAF4ivp8EkKsF98WeqE8ynYs+gOyqEUNTuHbgqyyMfm0Ws4SFDb0oPSklWtKXV7r+3/oFEiLg8yBrlkC29qTl1a6Dp3wIeel/Xwf065ZAPSMM6zVZnRO/lABcJ04ve9qXJOe1qvvlkdYPfJ3/XLPCz7Rp+BQ1+dzzXnmlJcdbWxPPE7HX9v8c6vC517ic/+vb662LdWepyNb7Ryp9tdwP9ZwYXCw0rWgB1IZaFakqlGpRuqXahqosFWHkW2fBFMiiJZGzuACaZfGKY6DMSVQAc6KWRM0ibmKV5c3bOzbtjpwVw2lgmiQJsM5hi8dYR8qVOWactfS7LbVkxmGQvl6NpKQkmIlBHllalJxCXHQQBI7VygrE7xpqjTgrQRcyaCWSpjXROI8xqye6xViN8w5tDbkkVIrourgeZgn+CbFcTSURS8bFgNWGxhmmEbRRdF2DsUKSKxW6vqMAH+4/8rh/wjeerDK4zN/89nt+9/vf8s3bO5xTlBppWkvf9xwenxAtX8hTQFlDigWVDRpLgyUhMqsGETAqC0rprabkmTlVnDU03jE+PHI87lFU2s7QaI3VnmFwpOhQSlFCJJcj262j3zQiZmMEz/de4720HGIOxJSIMVOyLNJm4QvJxHkWd7slgGvtef/t91jbMMwZZVre33p2/YR5ms4j4BWxj1VFQQJdZQ5dG4XVipqkgrWA00pkUjVUpahKvBjnOLE/HQjzQOstfdthjKNrenTbsu01YWpRNWFrIY4z0zQwjSe0zXz88MjH+yf+5nff8f67tzhvmA57bK9pNxnfNYBBWYXRwgVafTtWrtaqYW8QS+uaKzlXqhFdiqYUmpzPa8cwTeSYUDZRqhEPi5Dolcb2HqM0KRW83zDMsD8dsNbhTcc0JqapgmrY7O64ub3Bd56iEtM0kbNMvvymsfT3PzOPB969ucNaQ8oTcRrQ3jKOkf2HB/IITV2QmQrtBpyeyXNGa9ht4N2t5m7jeXe74Tff3PL9b97Rt5ppmkhETjGQVaJ7c0ezuUPZnlgMsSAYm8rUHPBO9Er0uYoEFt6Hon6yfn5ue7mmf+32K8cAX1ce+qVs49XfV8VF/eB60b8E2nMb4Hq3q2p7DZb5bIwDlyC+thXWrOXzQelzW631gj78Kmj6glh8aftcH/5loP81QfR1Yt2nlf2XrsF1oP/SMb5m+6XX+v/vJpAp6+cOwErM5Nz+kfzQAAWNQxkhlqYMSkV03ZCDJ1aYUyalivcdN+9anGqxTYduHEUXIrO442lDLIkYIpRMTQssnKGoSM2J03AgRQghcToNPDzdcxqOeO+5vb1lt9vivCbngCKjjaLtWnJKy/2uxJXMZLoEqSiaCdJDZkqVUKSiKt5RiwRz32zQqoJK5CyjVymls0WuseIb3zWduBtqJeJI2mKVJcTMnBIpRZnJN4BWxDEwTxOmwKbt5L0qhXcGqywyuS5z7CVkwjQxh0SpYJyi6Qzf//Eb/u7v/8h3376j5oii0jgjDo3HR8bhgKoy3jfOgcb3zFMk2UKJFW0N3rsFms80vSAaMUSqUjLGpiDHwGEeOJTCNA2EMNE0hpoCMUeshe22w7uKqQWI4lHvNd6ZRYVP4xuP9y1VF4b5yDyBCYvnQKnUnJfRvIJK0G883XZD0/VYo+n7XvrmxwNVKzYbQ9cJ1yIX8ZsvqhDitIwRCgTsPGhbKGRSLOhq8Mpg2164H2QqWTQiYiYS8W6gRkWJhhoDzljUoh9glIWSmOeRIUfU0jYtVTMPIss7hSf2p4mbnx54/81b3r2/oQ4JW0WkSTuH1o6SFWgZW1sbgmVxu6tF7jNdFRVBkMgL2qsM2mpJfGrBGUtKiek0cxomjscTU8w46/GNp1LZ7XZsugZtYA6BUgwP9yMfH/+Ktp4KzOme4ziQSsBvPL/5w/c4v+Pj/ZHT4QnXWcJpw/vbG0rNnE4DKSViOPDXvzzy8d8/sNHQv9Nk1ZJKEbEgXVAUeq94e+t4c9Nzt23Ybjy3Nx6rRGDLNwbtDMoZ2rbj9v13mGbDEIqobXYO73syHbk0C9q3jqkLX0VG2ZGW5hfWzucx+NOi8mu2X40ASHVbP5Ei/OV99YsACZc+/nVVvs5ESvWmWFRDzoGkwmIFa639JPMpy624JgCXc1Rcx/BLj/36HC/POR/zWcvi6nnPEoLzlOb59790WT5NpC77P0cRrrdPIZ6Xqk+vTQR82qp5reXwIrg/uw5qfZvnRGi9BnKNr/dTi53lrw36cqy1xfEf2pS4wi1nvpyDRj+bo13OW55ySRiUAe1RqkPXjqQcuWhQhmazoes0vdngTIf1LUXBmEch/WUZm0ogCi5VhHS0VuSYiXHmcb6HapmnxDRF5jkwDrK/NkLaa9qeprVM45EQB1GT8wbnpAo1JmGMjCPOVaD4SsV5wxhltLBWEasJIUkCoC05B3KW2XxjQCtDqSKSY5VoEMQSZPTJKJquwbtGxGlSwDjodIuOUvHmJMI62moaJZoBtsJ206KtiNxom1BzZJhm5ihMces1MQlz/vbujr/74x95/817jJUg1rYeVSOPH+8Zjie0UrRWdByG00h0if1hpFZ9nj7yjSPVgvaWze0NdgkWymhM66WNUGQ6RGtD6xrcJnN4fMAaRbdpUdVBDeQycXO7ZXezIcYRlHA4jBXLWWsbmqalkDFNoe0cMRZyElJknAMxKdAzYa5Yb2m7Dtt4jNa0mw3zMKC1JGPWWW5uG7r+xP4ISmdBQVQmVzCqoF3BeYt3CqsKTotmvVYaYxyua4DKPI+SdOWArsukloKcZV4eHQlLlZ60xmiNswpdFSlXUBZjPHOUQDWFyunDwJ9+GLj76ZG/++NvuesNfWvptpFud4PrFdqBsrI+l9VGOquzf0UKWSZkMpymIF/NnAjjcCZLWqUoKRND5DSO7PcnTqeBOSWoRkZKdCbld/imp91s2G3u2A+RYSxY32J1K62sxxNTCmy2hs1Nx/vf/5btzbfov36kve/pdx3h+ECrNWWeAY2zcHgKjIcjcYK7DnBbUvYYCzk94VziZuu53TVsO83N1rHtLbe7ls22JZdEzpF202FbC7rS7rZsb9/iuy3LhUKbBoxHKY9TDev4qtS9ogGBlvVfCpoMa0Lwcrlbl+nz7y4aO1/yc7ne/sNSwGvG8Xmy1/PH60I8WvD0c4/8EwR5IXBdtXXPQWc9hqKevZMVV8FGrTS8C5Sfy3WwrufgVClr5iEBbAleKwAhp/epJv55fPDZVp5/EkqQi5K/AGcrzmpPz1CLM9pQeJa4nGdCLupPZfFaveY3XCdpL7evJQEqtdgor8kCPM+ULkeU93rO1z5Fh9bj1XML5RqJuW79XItAXa7R8/v4Szf19ZMv1/N8TCUkTfn3grBULSp8VS9sbiUEnwqlGrRtaHe3+L6hKQoCkDVziYQYiTksRLqGOI2UFCh5XrL4KtV2nAlFY2hx1pBTYjidKKXinHARUigc90e6rkOpXoKwdqilap+ngRCiVJqILoZ1iorFZZGHRUWoBVQReWIK06jQqsqEQp5A5QWed2hdMVbhGoO2kEoh5yiJhjfYYsRR0BnarsM1HSFlxjEwhUhY+u/zMBJikSCvNdpUsRlete5qpnEaZRt5jSHSbRr+5u9+w9/87bf0vRVrYKuxqnJ4PHB4eESlQk6ZqmZihMfHA0p5Hh6OTCGJRr7WKC31b7PZ0PQbipLA++b9O5pOdNs3m47dtqdU0VrwrmWze0eKE2kG2zluXcdmt2EeZlKYCUEqcbckAKIEqTFWvrebpl9aQWK8FGIkTjMpeUK0PD2NKFVJJRNCoGk8xhics9ScSGHE2Y63t567G83DVMgKjDViaJMTVmm8VjRG0zuDX9oAWpllrFXRWCMVNYZaCgEtOvtVk4siLoVUQaNzpeRAThlnHV3bUpRmnBMxRqnklSMVxXyS+ZYEnP594sef/oU3O0/rLdvdjpu37+hvtljvME5jrEUj0yBea2zJEANlnlFF7slxmik5UXIkzhNWK7zVeGuJMRJjZppmxnFmjlkMsEoi5kq/tTw8HEj5ie++/y399g3TeOTpeM9mW2l6hfMehcVqudZhTjz+/DPTBGFOoiVxt2PYbxj2T1TXoGzLTbE07cibv97z5mMl18I4D9QysrEt1lecU7zdeW42DmcLO6+53TT0rUWrRCgzymnu3r1h++YG5TW3774hmRbb3uHaLUl1FBRxnila4azwaJSuF8S1ColRLxXKi5L52T8UQjo9a59oe1nX/mcgALKwX8Z75DVW1TbJUi7VIBJAl/iweuxdjGXrMqN/QQCUVpIFXfW+FyTk/PfzY9QlO7oKKWssuqrQ11BwCS71HKAvv5cKcbVefTYO90K5cO3tP+/VvwxMikug1s/gGRDnMtkvX97csp969mbrVeBXl6tXhTV8CfhX13wJPAIrXY79smXzmi/Cuhn1/2Puv5ZkybI0TexbmykxM3c/JCIzK7NquhotkJmBQIALPAFeB2+LC2CkSXV3ZVZkZsRh7m5mqropLpYacXJOnKwumYGKuLi7KdtKbC/2r/8X7e0/cT3YtS+1XZCn122KrApWRtqr5zrdh+ux1DOp0+leKd92rUpEst6N8xfjedfGy2Vljbh6ttdvQFvft0tZyCLGKDWtQnkgZWwTUmzEpZCao4WRuBRKS6sBECXgQnBiqbVxfDxQ5olGwjhFp+e6is5II+eEdYFpOhJjwYrWdFMppFSIqeF95uHLI33nGLdKj5qKRqW5LWBX0qVm8J1yy5dWMDbhO6EvlloFkcI8H5QKuSbSMnF3dwsEnFPykZgSIo1gPM5oKvbkcJac2T/sWeZ5TXkH1TdPkX675Xf/8FuM9Xz49Jm//vVnSl2IppAaWjAlk5XNCEvFay8cIkKcM5sbw9//44/88LsbQg+pHKA2rPUs+yPLwxEzV+Jx4nbccP/5kT//9AtLrFSUiniJcDhEdepMI1ew3YTr9iwpkVtj3P3CsOnpBs8wOHa7njd3O25vN9QukOuAH26wPjMfJmgJXMMOgusD+XHWXvc1usU0jDPaQpYTNOXqp4ExDWM93iuGpJae3U1Py1oSWOJMbYV/+Zc/YaXRu0CwkSCNbSe823keDgv3GUpqWK8toNvO05mGiRnvLNsukEqiSSZ4h7WVEh+pFDW8veJWlmWhpMIsDSOriJBUQlrojEA1xIK2VeZMzg3EY8Sp8YsQc6aJObNe5tr4dK8sk60dGcYvDJtBHUYjeKfU0bdjj5VMJ4XeCb4VnLRV3ChSclSRoT4gwdO6gIjFG0usM2nVm0hZVTQxFu802DseF8Q0DlOk3zbevX/HflKRKWrDGUfvO1pKpENh2Fgefnng0y8HYm740CFkjEDfbUhtYbzbMh8jd7/Z8n/7f3h+9/efeLg/8ueffuYvf34kxT1OGu82He9vBza9x0ilc5bOGrw1TMtErIkffvwNv/nD7xjf3FKtwY83JDNQ7UCyPb4bqc1RS8OZhrGFVCaCHVHGzIo1Dm9U+0HBtlbxHciqisu5ZGNWDQHF6Vhk3bYa/5U58uXyNxEB/Rp47Hq5bHdJvV63lV0Mw1Nmuev9z9tcpaGfnvNltuEloO2EorxEgrrHKQNxHaW/ZsCeGpzvS22f3Y4n+1zKCt8G6Om+qyNyjrBP5z0pI37r3vPkup6Xaq7T/t9TL7oYYHlhhHVfcz7H8/vz/H25LkFc1pnz8zcriffJ+F8/4lOb3VdGudZCzWnzq+XitJy25cmxVLZGxCEYSoWUm6ZDK3jrFAjWBEqj5YY4o1/O0pSS2grVrAbDOkoClqg5G2NYUqYVS2263jTBi4fB4H3DiGeeE/f3e8T0DKPHepjmjBitj1sx2nvePDUbWl3ITeiasOSKMZ6u65iPC8fDgrTKZjOQc70wjp2eldF3rGTNIFgrOOdXSdRViTBlplLIrSpnuxHG3Q3DuOH27obcKsMysn/ck6ZMXgrzYaE2xSyIaYQgtNRIOTKOwm///nf8+//zP3L7Zqsta6L0uSY1Hr88MN3vcU0I3UiZEpILtlRa1N7xUo2K/WwtORemOZFjoZTMNE8c50QRYV7APc44Lzhf6TvDbtdzczPQ9R23b94ybkbtYlvvj3VKEC+t0Pc91ho6r7oPJWW885Sqmgbea+q9taaYCXHUqu+eNYEYPTkuKsZk9bg5Z1LJ3Ly9ZXe7JdrGsCyMgwI7I1Bco9SED4ahM2yCwdWGaQtxScrXD7Scadi1PTAAlZInuq7DeEcxq3ZEaZRatVwqllQKTrQUs6y4C03fo4hSMRjXY6WRiqpSFhVs5PP9QeV5ge6w0D9oF6A1Qu+06+SPywcs8HYrvLkJbHrP4IXOCUaqxo+2kU1DvMWagBG3YjYaXdco4qlzoqSCGIvvlNly+rJAa9ze3PDb3/2G+8cjh+NHxXGUQi0FnNHyQ9Z3ESnYrldthVoRaVqea/qW997TDeBcwPo37G5GSqn8T//wnj/96c98+fyFD3+9x3eVxgRGtR36U+asJZpp9F3HuNvghx7rO7CCDT3ib0ito+Eo+aRpIyvfR8ZaS20a4BmnAN7azApdOgWE7bxfa6f5v1wCYbnwn1bhXAT/nuVvKgFc/742Iq+j09EA9qpI/LpxBlaykQvq8fpc33Y4ThH5af2L9PM5LXGVPzhHyr921U8Zlp6v+9Z+VyO8upaX/z83xqd1p1T1iyOf7kG7ThBdL9dlha/se9riKzfgtY9PaObX8QZfi8qfH7c9ue6X4zlhALT3VdZalvoGGsX/2kM7UUE/3ezqHbr69HJ+q18Z52l02DDguhHbDbTsKWUmtzVHUdUhrSJgDQ2NkmLOK2Lck5aointGFdaUzlcQsTjvQVARnlI4yRaXAhjhcExUKjetZ7vt1IA2T86ZcpqgpaM5Q8PSbGHKkd3On0uAXRCGfsQg5JQ4HidCcIBiZqwVnLfUIsQlkooS2zgrOKtKdormLvgQtJ/feVouPHz5whwTiMGJ0FnP+PY9N5s7ciz85ae/cP/pkXlKHKeJWBKxqHTqu/dv+fvf/x3v39xivABJUe5NSMvM/uGBZZoYnYVceXz4ghHLzXakC5XHY+YwJUyrK7WDOYUF1AYxFqalkkVYWiQUR9cZXGnkHMl5YTrucc7y5f5RgZfbDcPQMXQeMYayvmJd1+O9x1u3tiA6nHWklKFot02uCqgMxhGCpzVLrQVn1+zayg0AlRwzaVmIcWYYDK7ruXED75rnt1Pi8/ED6aFRRFPv3lWsbVhnCKJCSd7r8Y1oiyQUpFbseUqrpPmA955h6GgC8xyZpkSeD1Rj6Z2laXuCciZYi3VWOztSoa0oqlxgzkUzKrmRWiNmSCtESxKUFlf1SqE4S+cNMcIYVJJ7WiqGipGAtYZgLLk1puPCtGhJS4wyGQXfYa2j6zrEec1gLQuC0AVPrRkXNOM2x6NmOUpmmg58eZjxfqIft2w2I33vcL7ifFXAqVExpmC1pfPUXttMRaSy3Q3ISq/svAorvXm3Zfdm5OOnT7z98a+rXLaCVJ015KbP0zWHCR4XHKlV9vsjSxNs32G6ivMdpvUKPy4GsZZgPU08rO2+NSufgnUOMV4dgHVqqm3NWK/l74tGwPVcXNd1hYpdn+H3Lf8qB+C1nsPn8/J1BuD58nziPxmSRlmPtzK4CbC28H1jZN+2CVe2qZ1v5qmEcaoJn0f2bGzrWFr9irH9teU1I/68sH1K4z/PFnDe7smYzkmEU1ng+vrgeR39tZa8rzs1T7e/jOnpyS/vwOvH/97l5b4nR+36HlxnjIRvtQmejnA9jOd3/+UTOQE2rQqt4PH9hu3tWwwPHOuBOR3IOWLFnkVtyjrmXCpzVOS3WR2ClKuC3bCItWqorKMVq5S1UVP/rYE1HuNEP4uVOU4cJmjG0PVbnPcaJZRIblFJfNbviHWe0Hk2G0/dLyzTcjZWXQhQhRTVASglUEvBJoP3hraSCImrUAqJijXgnVW1QKM4GWOKZjikUInkukemBRFDrhVrDHdv3/O7H39Dipm8JPpuYJkz948PmPt7lrJgg+Xtmxs2Q4CcsFaj15Ib6TBz+PLItJ8gqRJdOsxQK74L2HGg7wWRWd/bajBFqYaHvqOZypQbSy7ECrEqD3/fDLbr6IMn+Io1mZJ04l6WSpozx8eJzdhxsx1wRo2qt8rd4J1bs055pch1NITSGrVBrW3VddDPtban2g2nEtfT/iEtzz0e9gzGkJvOP5vBsds69nMirxUx65qm0p2l91p26p0lx0zXGfq+J+dETgmpC916ncfjASsGZzKtgmsJ17KCQFNizu48JhHFfpAL+quSi5ZUUtEOmFgU5FjaWuFZE5JKeKn/eKfZjThDcMK4HTDBMMUZEbS7JEJ2DUNHbhBjQo4R62dKg814iYS9tbTgKS0rW56ohPT7H95SSibmyMPjI6EbsN6zf/yZ4/SFfhjZ7nZsNj3DYNnuem5ut0gRgnf0onK/tSSNlFvlsBzxb+5AKs1kxBVMsHSjQ/wt3U748fc7csq0orwOLSsBVc5Jy4g+wKoG+nh4xNXMKDcMtUEVjLj1O2S0Nbmtr4qo6a6tQNX6fV0T/CIWQ6PWpOVYcerwrzXfJkJtBdMuvAEn562Rrzvpv7l8twNwXTM+v86tXaXvv8JH366yuK9G8M+9GYDX9QV+rfzwPKp+bd3FApyM28mgmGfjuI60X7+bv36+10oTr+3zdLtT5uO5gT2N8/o4Lz9/fr6vj/t1sF47OySvOXHnBMST67sc53ucgF/vHHn+Plyf/+vZhlP3xyvDOu28bvfs/Gu2pWJpzWCNJwwbTH1Dm7+QD/fUmDg5KCdf/CzaIUI/bJBcaC3juoHWLPNhIddG6LdMx0xOspILQcnrhGADTYRYZlKqpBwxtuG7rOCm3pGzIyednEWgoV0DGh3A0GsvdFyd8ZISU87YtZYoKx6kruDAVkWdAWdWWd0TmZFOSLmuGSjTmMuCLBnxBd93eKMsfbloR0AfOtJx4eHTZ+YlkXNms9vQbxumM3RjoBscrRVudiO9N1gqQSymVPKSON7v+fLhE/P+iM0FGpS4cLPdIGKY50hJFdMKvbc425OqWbnzG0uJTPuZwzEzF5gLTLHRxYRY1Xp3YnBOu4xaEYz1xLmQ457lcGTZT3SdIwTD2AeyKEuiiqAZvFvpgB2IddTWMKUoP4mziNFrrEBOeVWt41y6MqLU5V3XEXOlTYkpVaZDxdbK212HwbG0po6V1WfQOa0zS7N0zmM6Rxc8XQikDDmx8jcoeDDYgQbUoiUDUsKjvm0uEIsCKEXAOUupKKBTeYfWbdQBKEqxoClrhCYNY1hr0Y2mK5XFcP1mdZ2l4DjM6gym1MjFEBxsR8/Yd9guQFpIpXCYK42o2TJzUr/TbFTvHcko9bPve0LXYd1IylqG6fue7Vad5JC13Xf/uGf/+IB3sLsZmQ4zb+9uefPGrQFmwxoQZxALx0XbIcUoYVHwBmML4oXOCsUpNkJLORa7loNyTCuAWBFkpQm5sTYhFaRlKBFywvu2dqxBa0qnLGtwWTEUjKpurvwcVRxiLLY1LVsY1Q080ZqsE7QCtU+AQVkzwmuJ4Htjsb8JA3BanoPHTqCy5+ufT8BfA86duMZPMjJmFRA6TdRW7Plcz8f0633mz4zTOQNwVRL41rjP5B7mPPG/OEO7GMYn4zO68sk1y+vjvvx5AuhdH1/bQk5+S3t1/E85Gr7lnDy51lfXrUfUC3h2nqd/f62t8GvHf63t8On/L8sn159/03d45ZyXOEy/JU/2Pz9vUXpbMUrq0ixeHM50eNcTbEdipsbMCthFimBxGC/UfkPohDzN5BzxTqA5jodEqeBdWKMrUQfDaavanCLHx+UMBhQj1OooOfLLxwNiApttTy6RmhPGQOg8wWmKsBmDM5acK3d3WzbjwP39I1Ob6YJy3E/TROhWoaFVXKrWzLIkbBZSFmwQuuBwzpJKBVF5Xrvmlr1XhLUlUKOyvrWqk1hZMo+fH5gepxUrYOjWpJ2xjc1uoN944rIwDB19sHhplHkh5sxynPn4l1/49NcPmAzd6uD11q9o9kyOkVraKkpj8N5isjA1ZXlblsw0FaYZkhFihTk3ytIIx4T3lmCDchuYVWSracuoaaIg0CYscyQeM0swWAEfPN57+mFg3HhAnT3jFDzpm7YWavBvaEWds5yTlmuqzjelVlpJmuoVRy2FZQFBjfrtaOnCjt+8a0wps+S4diysMsQihBBUaTInDFrH7n2AQXkskEqrjd51NKAkwyKNbCCXQs6VJZ3iHzUgxhjNKLXV4K/EUnmNRBFRql5Rw0fREoEamKLy79IUSCqqY5Cr8OVhxrSCQRksc4kMnUOsaGbLaVa15IaZG0bAu8zQO7xf5xxr2IaRSmHJCbvZkGrDm0AIQqlKrrTb3jEOW5Z5T82FZUksy4IxjTgn0jFz/Hzg+HnPdrvl9s2Wcc32hOChVXrniXXBGFXeW9JMbEpY5HolkvLeEkKHE6s6GDHTVnKs2qCJYUnavokp1DIx7T9Ra4/vKpQARh0lawNGAq1FRALWDjRjiLWp+LI5ZTKbOgGr3WhcCJbWlw7T5NL895VA/FvLdzsAOefzSV5O4t+ONp9nAL6GTj8H41ZQoqDLeV7DIFwDCa+X585K4xqx/ryE8Rzkt17O2k/+9HxPr+tb130eywoiPkXWz8f3+jlkrcFeG9fTD8C1gX/F8Xr299eM7vNtXjPKr21zwgJ87RzPgYVfy9y8duynLYwvMyhfd1yeZ3iufjd58mFbpanl6li1Cc1qnVxwmOap1SDZYKrBVau0phUo2iuNCMYJzjjinNYoRiV0lznBiqr+8nCkFMccM3HKlCqULBznyDzNpFqwVuueRiy5WB73mVLvcR/vKTUhZEJwbDcDm82ADxoJeh/0pW2Qvb5jXd9hjCHGTJ3q2nWieUdjhZwaKS3ULJSlIZNQhk5xAqJJSB8cxijIMVYFWNZasN4oOryu3yUPpeqEiDVIcMzzhHUOH9b+5pUUhqblhirKaBenyOF+z8//8lc+/7Ln/c0G0/dIhdB3lLzuQ8Ma0dmqsbYXAq0Rl0hOWQGOpq3tb5oMTQ2W1JijZl1qZxFtSSDFimCQYJUFUZwK1SwzcWkMXWCeJmprjNudCh85T6lgrLZGOqs93LUVShF1AKpgrbK7SSm0qgJQJSnrnViHM57WAsb24AymCmPf04xljnHVZNCIL8VIrY2u63HWskx7KFGzGmuHQmkaPdIURGuspebMsjjSrLoSMSrgL1c0GkWNvD9xrMyZQ9FzOmexOHLVNuq6dvmc5k5ZAxBrLG6VMDaAs0KrmeOkLX6dd0yLOh+5FKblyHbM7LYDvXNYFGhrbcGYhAuWYCy1ZowIm01P6AJLKbQw8DDNyqQ4LewPj9zufmS7vaMLWz59+AnQ51pypessyTUOZaEcMulh4lP4yI+/fc/bH97SDZ53P9xyM+xw3lCXpGoZVjkJSo6IDZoZcKKyi2LBCVYUc5KlKmOmGNwqn10bYBqVmRw/k4tgp0esdZrZMEo/bIynNMuweYvvbxHbKE0zVCcuFAX+6tRVWctK67l1TrTnae1kIk7OgfnqPPl0+R/gAfi6MfnWMZ6D4dajoSAMPaZ6lieSoPZE9OBkKM64ga9Euqftcn36Gc8M0PNo+3QLORui61Ac9Yp1sxcR/GUsvMiKvHYPXhv7tSE8W7PTsZ9c4t/2LF4DG/5aSeZlxuZkoOuz/VeH7XyLXjpsr2FIro/xPKv02ri+ds8uG63p+efbXPymqzbG85M+f3FUPthhsZRYMRmIjfnLERsTHUJdVPXNGxVsj3NkmSPLtCAonLAUSGstdZ4TD/dHlgmWGdKsHQYl670qpZJrwzVtt7QGWnOkXNgfEtY2So3aepS1rUuMoWuVWpuqBYqlVQUmhsFhvV1JgmCzHQA4HvbMccJXgVqoNWnGYY1ak9HaKFIpOWGdYbvdKECsFJZ5wnWVcbO2m+VCjDP91lFrphiwzWFONp+6sitmjscjaVmwfUdaFvK8UFJm3k98+fiFw5cjNTYVcmxG+9ljxpqKMStgskHXD0irlJzpuw1jDXz4rNzu1hmsF6RYSi6KXE+wxEqMlVwgZyVrsutkGqPiG4p3ZFOQtmoK1ExOmXmZQSDmyrwkRAypVJwPjOPIOG7OhERiKq0o7XhwAdv1LIcjKWW8H7Bm5TvwHmt7lkUZJm0DL1BrotVMkIJ1gDF0Q0dtAyll6pqqt1K19gt0QYF+S4znLIT3qs2At5im4EEjun1rhdyEJXNmNq8CYoTQeYrofRITSFWoudGuKNjFCBR9rqIvqnKd2IazjuAtJTVwAWmVuGR9v11TTEytLDGTK7zdjYydCvrk2vQ7UQxxyTgvdF2HdVbJnqwliqcLjsfDnj/+8098/JyIs+W3v/s9NTfiXIhRsxA1Q0uVzlSkVCqJOgulJObDxMdfPhF6y+//8Ftu3u3Y3o5UW1XoyAqdC1RZr1PUEOecaaVSvKbwcynKjOlOxrdgXdPWPEGZIdtErV/I8UgGbauuaMsejoajvvs7bk3G2UZnOlwttFYpyeJdUH2FNSA1VJo4QImpLIZm1iZsucLCyVfmx1eWv6kE8FqUqJPpt9PNL5fXnIXrKPWq377qjzHmiRE7nfe7I/FrY3UFlHsKuuMq83CJxp+kwRsgL6WEX0O4v4aZ+Nq4XgXr8Tw7cW2QT/u/fq2vReHPwX/fgxO4vpbnwz/vf404ucr4/NqxX1uuBZK+d78Xhv6V9+G1t+TkrOgxDAaDswFbA7VAXQrLw4HPf/5AebhnGzzeWDoflC+/FZYSaTSsOHJWXgpjPdZ1zBSWJbPfT3z+FEnRULJQsp7cd/1qJLXn1wcUb9I0ohJjsFbTsF1n2G5Hht5hHbQmpKzkPTke6LpOEcei4DRnDVs/srkZqaUwbAKH/Z5lOlBbQvkJGg2V+G1NpYNrbcyLUrim2HDOKqNgGEDgSCJFoRadBPf1SGuJZg2+D3RWsGtv/knaQ2ql7wKdD5SVFjgtKpdcU+Fms2HjC94GYiy0FdzWBYt3Qi6VWgre95xKasEHZFq01a1qat05hzMGEy9OXk6VlIo6Ar7ixWCc1tAbCe88Iuo0eGsIXU+tiXmZKaVirQLvjnWmodwNxizsHydCtyf4QN8PqqooaxtrKXSdJxdhWRp2tArkrIJ3HTTBtAwlY41gnHILVKDzBkzTLEDOWuMVZV2kCd54ktHrSycJ6pIAlYNGNIAK1p1T3CZqOaJUYWM89TBr3RpRqvNWVgS+xRShNkOK9TwHn8hmSq04q2Wnus7NImBapaZIqoZaVJei0ihJMzV5dcpF4DhlqAd1fN5s6fqO7XbAkpRamILzgS50xLRoGjz0HA4TsVj++N//yn/+Tx952DekVpwd6H3Hbhz5OB8RgbAK6LXcqEsltYxbweTHx5n5OJNb4vHLPbdvd2zuNvS7jt27DdvbkbDpCJ1HxCjIj4oRjbhrZb3ndZ0/NFArTTNnrHV4LTmWtcVUgbxYfWZxzpRmQBzmc0FaZEwTXf+GnB2HKXM8JG7v3rPZvAWa4i8QxQqsGbhmzFXgpWUZ4AwU/J7lb9QC+NctzyPv15bX0tfnKLR9e7vXjvPSiLyOHj+XgSvAJcX9cv/2bJ8LlOzaObo2vGrMnm7Ds33OSQZNd1xO81UbeUpnP+9tN+dDnFJ1L6/1+9JCp/FdO0etwUmV7XLA7zvO9e+vSVg+PejXDD2Xe0a7eqVO3tD609aK/wuPZR3HNdGUnFcgCDkmBfAYx5cPn/in/+0/8fM//TMcHrntR242G1LoSEVrta53bG93ay92ouWsLYDicLajtkf2h8Rxgjiv7X6sDF6+YkXIVSlAKxmzgoiCt1hQsh8DoQtsNqMi+Fs6Zy1qU0nV2k4CRcomibAij6HkzO52xzj2HB49cZ7IOTIfI7VqnTbliBgUZR0rtUDKC10Qur5RisVFwS5CchUjHqRxTAvGV2zncLVQcwZRKVWx4JynDx3eOaxY8pKoGajaAz52DnfTkedESZW4LORYCE7IJdN5B8ZRMxyO86pCOFAbzEvU52wttll642hVaZFjzqwgdW0PPC4EAxblXxezGjYxyuZXo0ayRvvsOx9U1EnMOv8YSpO1fa5Sysw8JeUPsHs1usEzDD2tVu5uthgs4ClFmSZLtcxLwqCOm4hd58YV9W8NJhjECa425hjJpa7ZSM1uOe+xbgM04lqLruh3dYkLNludvzplfAwrwVarUKWSjxVv0WMaQ6o6L6Q1srdN1uhVcSmlgjUOY63yGnhHqVmF2Ax459eMTaStugTOKIZCLMrVpmQYWKP97/NceJQjnTMEOyro1nnErBgLFT8g5xnbwFmHtXB4mPjrnz/x5UsjJ/j4YebDz5949/YNv/vdj+T0Z+bDQrDru58ViBl6j6VhrFPDXCstw/2He2opPD4+4nrL5tPI3bsdu7c3DDc943Yk9Mr3YbzDGEduUFbwXVnndzGiZSkRoJyQkwiVWiPeqkbGaaoqpawpeiHFez5/iBzu7xk3b5inxsePjxyOkfKHf0/3h/+AH27xfgMYatUA1orWw1oTxf43OIdeje+GAvybOACXSPm5kZHzC/619PXLY12D2U6ftheG/3qbV7PBr9SRn5/2ZEh0MefPTtej53iZsj8dSpsuXhv3xYrr8Z62TV5f6/XAnty5U3D9on7+ev/802yFvHpPTsd7fayvOymXDIs8uV9nWN13eprfwgg83e57jnW5lqsr40Rgs251caqutjg5APLktVidAqPIWmnaEvXTP/+J//y//Ufk8Z6dgdoix1g5tEcFapnGzd0Nsr1BnHIJnPAmRjwhCM6Gc/aksRKnWMuJrCOXQi5ZGcJWrfnWMjE2SnGMo2fcDIybfq35KiDUWgNlnXhLJsZEY6EZwbuA9R1tFRNRFDFrVLNjdsJxXxETaa2RU6LkgvNag3ROwDdS1JrmNC1MU8KIo+t6hmFcFQYb4gSwWKym73Ol0LRmujoXINhqcOskak1HlYQzUCmaGjWO0FlaNcSYmJaMQYmY+r7DOAXpee+V0CZpq5MPAdcyrgqdcdAsQ9R+9FRXqbGSmWdN/Utr1BaU299WgnfrtTiCX3koaqUPHmk9BVk7Lgw1FVWDLHXlg9DX63CcmaYZMcLQD7RWWN5nxr5TuuRUCU609bPMDAFKSTS0BZQVHIeBuhoS03mMFEIzGKtdIJiq726zSgglhVQ0tVxroWCJc2aJqjbZ+YC3BkRJpXwrUJXZzrg1Xm0NZ9RcmVV3paaGtEotmZShULR/vhbSXKkGQnBYAzXPq6ZE05KDBUs9Zy2KqDNpUKPsnFsdoML+8UDLC6Zlfv/bd+SsZEG1CE0M1ncYa4ipUbLw8eMX7r8kpMJmBGca02Eibze8vd1wvBv4EBflSqsNK5VhGBi6QKsLQiMuC9Yahr4n5wVTLYPpqbly/HRg3h+5/3zPzbsbtrc7usGyvRux3qrapLFKpe2CqvqtGZJCQSjQ1t8rJkM0IUCMmZILMauTbozBWu0sqamQ5weOaeH+y5EvHz6TIxx6w0fbuHv/B4Y3v1Wp6apm3lhzBf5jneeuQPTfmYz/3yUD8O3lZTR2Ab1pNKhc10+Xp7Xi16PdkwH/1RLBr0ay1/tfZyfU6xLz0ri/Hm0/LVloNCyvnv+lgXxaAvkaCc/pml8z8M/r8N+63lOkfRFnuhzjzNL3/OquMBDX4/kaYPD16728yK8t17f1qQMHZ30HTvgRfY/Od6g9a49pcn7LQCPlfhiRuDDf3/PxwwfSHBnFYGqlpcI86xe50PBDwFn9yVU52sXp/atUWjV03cAwdMzTgrMgtkewOiGcU7gNxNFKwVit8baoJYFxu+Pd+zvGTad11bhQy9prnjPLHMlR++qN85RWOU5HGpMS2XSB7Tgi1lBqIhdNiaeiXQd2zSIYbxnH/gpbUzkcJ+ZpVVBslZoz8xyZ58jNRhg3gSKVltQS5lKwEWVJdIKxFmMN3mnJxIinoSnr6RiRlJUut1S87xj6Dc7NHOeZ/WGiC44SC8Y3aIZcjdY9V64F4xwueExUsKCRihODt9B3BlsatTRqhWV1KJxzOF8YTABTaDTVXvAdY2ewUlnmTKsVa6xO4MZqbbxpdGfQKDsvGesMBos0y3xceLjXbo0YK84qD0PfW253W5y3SImkOdOqtjCGwWpbnDhV8yvgggcac4HSGp01SNAa+HJMzFOktUwFpqz6BsY6bBiZ46O2Vh5nhpAYh15xDVIx0thtRvyidfdjXChR2y770NOsV0mJVlYeAjVetTYqheBRyl0HXTDKFhjLmukxlFTVmajqaAUnqCoEOofXhvNKqGRaJi6JPCeokd2m50Z6QmdIZQUHhoDxjnlOTFPhrz/9meMjBA+7Qbi72WCl8eXLB/rOMXQw9tp9543DW8/Ye5yHlKHWwhITIVjuuh2LNGrMSIauCxSE5TgxlYprhrRfSBIJNx3GW1zoGW/uePP+B8Z+i3hDXjs9Wi2r+mGmloWWI61UrPW0rPS/pVitMDu7do8YKg5jG6aBIdKZhV4mHpcjh0+W1iKtRpoUutvf4t0NIobalCtAVtI0ncjKeWoz35kC+N/FAXg+UV+WlxH2ZeJ+PTL9lvF6bmi+Fx/A09O9OObXruFiJC9p6+8FSl6uQ84m6tuG8en/Tz9/vt83Luhq39cwCtdZicuzeL7PiQToss9rBv5rgL6vX2Pl28b/28c6PYdL4P+0THP67HzeJ5mXtnJuF8iRkhJj33N7c0P9vJCXhSQVLx5vA1YaxniohlIaJ0SuAZpplFY01WeMkrT0mrbEeEoWao2kpHXfVgWx7VxztCKIg93tyG9++57ttsPIGnXmRl5r9FKVbTCEgIjWdFOOHOeFwzRRq9aw3717x9u3dwydA2NxvmOzEaKbWZYItp7T19YKpRaWeUak4rySvsQZYlSBq3meaEWobWTYeqRkllhVYCioQl8IHmylGoMflZToVI/P6ZRCbcgqcawGUFvQxHi6YUOjEFPkcFw0dQYAg0wAAGVZSURBVJrVMKUKua05ZmFVQWxY8VQqvTcY0xFLZZojKTZSAV+algVkBbEZTZ+mHDEYgnVUKjlGUiso4FWZ8traFG+NZm9qzcrueGoFW5vAc9IWyof7CWikDL1XLIIPnhZnutCQ2sCBTw6/qeAaiUKx0DVP6B24DU40O5By0/7z3Ijqk2G8U0ZHSYrhMJVmvd7r0phzpWsrCVXTlkpnhMFbimg3DCJIqeA0c21NQ6RgpLKWrSlNgXUmQDdYTWfXjDQYO69ZlZoJnZL4pEU7xsaVuU/LGJZcm4q1lUotijGQCsux8OHnj9BuuL3bMsdEKlklmb1HjAJNU4qEAN6DtQp4zHlhng60TYeVynYU6IRgA60YSpo0Zb/yKoROuNkO3Gw3xOhY4kyaF5wRZVpsFlMMLI2UF45l4mHaY3vPePOGbmuxYUsY7sB5ylpurLXScqamhRxnikSaKdq+ano676grnkd1QFQQSZqoQFKcCWIYfCP3wvRlT10cUgYePv+RZuGNdwx3HcZ6ltyg6fdmhVjo3CVAq0j7P8gBeJom/zXje4rWnvfEv/z7a4bwW0ahfa0+cD6GjlK35TwWlWHknM692uPZ2C9/tnPd5bmD8nJ8v24UL/3315u+Flk/P9733JevjeVbZZWTE1ZrfXFJz1PxF6GfXy8RvL7+K07AOdX17LP1uRiRF6t1RKf9njpnstZOBWgidL2nLHu8EXa3t/z7f/9/Qh5+5uNygFoxWYV8ENU2L7mqFn1M9CEo5qBd3vuyFvxDCBgTMaaBEcQbXFAQoVRNvrIS1WjrgbAdB96/v+P2boc1lZRmWqsE57G9UWaytWvheJzJKROzgpFqsaQEx2MkZVjSX8k58+7NHZ33DKMhR0fJGTGRzhmcF2pdKK2RsrKt2QDD2Kk4kiukWEgRSmnM85FSZvrNj6RVClUEumpxRtB0h0OAHBMTE8YVWtX0rrGeKglEacDneOTxsJBzArHsbu/YHx4ppbAklZktRQGKrUUyhmPMzEskJgXLWdF09tBbOgKxKBjr2OLa496YY8JNjWGojD24YBFTSSmySKL3FjFCjpr21vS6ZhIERd7XClIN0llKgXmamKaIsQ7vVmLW9Xm6oOoUscB8WEhTZtOt5ExWkLnSDjNZEsecmEui2sb2duDu7uaclamlkhZFtbemdLXWB3ACNRCXzLTfExM0LA3LnDJdTPT9oDiK2mgxIU0VE4fglBsiZZYVP5JTWx1X6Hv98pyIg7oO+qAOaqHhRAheoEKOMHSeEByL0TliuxnPmaHWDFPMK+hQ2/ysNEyFLliWZebLFyhkYumASn/0pFJYYuavPz8AcHenzmXX9VoakkzfbzAtIlLoegMZXCuUquA55w22d+SYCb5nHBXoGbzFSKCmRI4JUzmD95b9UQmePEgz9P3I+/e/4Te//QM3dz/g+x3VBiXGWgWXFCGYqTnRcqKVyvFxwXc9wXsyjSqN0jKtHqkY+s1Ang7EJSGtYqXSOxhDowsFy5E4Nw4PgW67w3YbzGAQ6dfksTrRq7WCJuq1me+b///NHACRpzz++qEmYNvpn1eXSyve88n7EtH9beQGz4//0gi/EqWfyw5XkeGLe3hJU1+ntk8GUJGi187Mr0fhX70rTzIPl4j+Jbr/dWP/ml39/i6Nl9tfsjDfOsZaA69fbxn9NgbAcDH+1+Wbr/w+l4xeH3Nrz8srl2zGCZsi5/euMh0nOifgO4x17N685d1vfsfjT/9MWRZ8E2qMqgFPww29TmTG4kIg50ihYrArx7rBOUPfdzQ+a93Z9LgV8OStIcXIEsEYcF7IudAo9P3AduywomCinBbipP3f3gZabcxzZEkLJRuQgOs0DXvcP/LlceFw1FsVS+LT5595//ae/+n3P/Lmdod1jdD3qj1ulep6nhdyzdRWMc6wGQd637Pb7ri7fYvg+fzhC3/58wcOjwfAUGom5UTKygsvWJxF9eY7wYkjLxnI9Fbv67Ik9o97SFEdhFRJSdOoOauQkGleRZNcTyt5ddgKc8qkPNGMY3+cORwm5gkkgGtKFuSdBWORLOQQqLWqkFDRen2KQksHfvhh5HazBQxLmmilYgg4UTyA94EYT+dWFHZw65S5cumXVYTGGYP3gVoidm3NCqvAUKt5zeoI0hlyzogJZCwxVY4PR/Yp87gs7GPmsECTL4ybvxI6oe8dN7stvQ8EJ+jlqTBOA0LoyLnw+dM9hqp15ZiJ80xLQnAjXfBgAv0gzPNMXBZlbkSd+lZWfEFtBBouWAbv2XZaw0eEzltSXGgNNp3T3vdSqVJwHXSu0nkgNyyGbSfQhJIrqag8sHiDd+ooOKcdE+OgIL+cF758+ULKI2Iq8th4eHzk8XHPYcp4b7i73TH2I955YpyoJXGzHTgeVBvANsi5EEvBu467mw0//P63uN7z5eMnykrmdZz2jKGnc46H6UhNC9YbuqGn5sJxmsGC3QRasIT+hrfvf8vbH36LH3Zk8WB6sAoqNaJASbeiw6gahe/eOJwPCHCcJqY4Y1rGuAUXjizxQCMjbqCWiThPPOw/sywHXB+I0yPNVWp8YH78GWMdfY2E4Y3ug4eTgNDqvrzE3H19+W4HwFp7NbFqnfYJKOzUKyono6SCGQoFFWjmYmOb0qjKKeKu+iVT6crLMTUClyfxYLsM4vx/q+WpkeHSD271LGeOgafx/CViPAWSAnAm4dH6zqtLU/rUF8p4p8xBLQoG5SRwcxrfyuh3ikhlTYFeH7ppVHhxN9Z7tnpJDbQnd73S00XIFeit8dwYPnUgrn+eL04ugEh7GsVK/PKsMfHFvsIKgj2vu7QPPgUUPsteNE1JXl6za4PPs9/r5y9KPBdnoDVOb8H5R0w7vxtnxOzqpIoYemMo6aAAmmFDciMy3DC+/ZF5iZi8R1ApT5zjECcOD5bx7gZXNf3amkbrS5zoOk//wxseHh4pTd+H4FU85W57x+PDA4uALTPiG943ioVhHPnh/S1dsJS0qCCM81RXmaaJx3TQlG6BXIQMBN+Tq+Pzwz1/+TTz+NhY1oygK0CrFBb64Z5+GNiNI9YZejqMUx0DMSuy2aKEPyR673j39o73b94j1TJuhdom/lpnDoeZZdayw+GQGHrD0Cn5jAG2/YDBkGpFcqUsiTlNTJOuz7WuZD8KgIsxIhh8F2is7ZS9J1in2ZXaCN4yHRf+8stHHveJZVF+BXKltplqIs15bbEUQxf8ytxWtFRj9F2e9vC5HXDN87vfvGUc7nCm0g8dcTko8G6trTvnGIZeNR3EUlLB1IoFcjwyuIDpA/O0sO06ak5AxdaMpAJGCBJoRkhkcD1LVjGhqTQep8whVR4j3E+N+wPE3JAvyoPgXMLYma4Thl7wTgN/VnbEE3leSop3CE6/V63CcbdHbM/ddotbQX7NWUrOpFKJqa495VBzo2swWBBbNIPhx5WhsrFMB9qqNCtSzjgGYwRrHS1lpTXeOpXLddrmaEXZKvdGOxecqzjfFL/hNDNxiEc2mw2IckAgjVYyadEMzBiMKiSGQu8mnMx4n6kmkQ8zoTa6fkPxlcUu5Kz6Df0gGKvYGWOEIhDjAigZVlxm5mlme3vD/eMDTSybu1umKog12H6D3275u7//n3nz9g/kbGmp4fqAsR25OjAduJGqzYx479esTVNHrzqkGboboTeNkiNLPJKWBx4efqYUD8EoiVU8srTM47Ln+DHyznRsb7e823n2jz/x0y9/Yti9p9u+odu84+6H3xOGO6ZiQHqq6chFnY/Ni9n55fI3ZADWNMOzmrhOpBpBPAVyXRsHwwmspkep67S9ChmcaH/Pc/lpklexjPYdaeQXJYLTGcrJOTDnNee6Ndf16yuqXS7iP79exng6jvPli70CL8q5THAi0WmtnZ2qp10N7XKMq7uBrBxPzwiQnl7zadenPfuvR/Iv152fLSe2al6kEq4y7q8upyP8rdkGffynFszTh5dnpuO7OAF6Hc/vRX3lup/ep9dYCtpKlKLUGmbV1g5U39H6DfRbqg2ImJWZ6+QAl7UWXCmtIU5BajRHiaKRey4s8cBmdOSk4KlWMzXP2JIYvMFvB7CWJS6IZMZh5GY7suk7QOvxpWi0WUphWaLSqBqLmIDzPUuBx4cDH+737A+J3NRwiSnkkugCGNc4zjO/fPhIu7vhZtvT9RuwGnlP80Julds3N/zmd+/YbBzLsqfz0MyEiGPoYbu17EdLSUKtCW8Ntzeeu92Gm9st0/FIyZl5msEaJbFZMpiFCqRSSSvn/zQtxJQx1tH1A103UFJlfzhQa6XzHqzBG1VhC9YiAm/yLX6AmOH+cOThMKkSYKvYTt+/ipBzJVgINyMNFaFJS1QHZIGHzw/cbTZs3t3SeUOtkeNxpgsqitT5QOi0j7uUQs6RlFSXXkzFOaU7nmctg5Qc6b1dMQltBWxxDobEKcpeZz6VaDbWq6qfVXU6pGC9YL0q12G09zxVS54yThpewDYIQHOwsgHjBdIChwNQoRPId4U6iuoimEJcMkuMGGncjB5rrLZ/pqzUx5tx7bY4BRsOY4Qvn5aVcVC/LaWcygUObw1WlGq5c5ZgDd621QEQDB23W8c0R51TnKdZS26VOSY2u5HtdkPJmZwipjUKmkFqFpxvKzBRJaStMVgKOSfFuogjzzM5K4vldqcOrljHdNgz56qOW1OUfIwzuVa60CvpkPXstrfYrkfwIJ3S7pqeP/zDf+D27Y/4bqA5i3UBY1ZMg/GIdNRswFjAkuNK6uUCpanWhxWHN1bvUahgBpzvwDrmoydNQouV5h+w/Uh/c0M6JtI8sX1vKPvPpP2B5Thz/5f/juk33L77A6YcufvxH7FuR6JRjYDpvrsE/P0OQDOcXtvTVMrV/61eDHi7Rlt/T9r47FTUJ6lmOWdwXxqs17ABrxodY56d/ZlB+LUb9Q1Dlp8xFJ4NuVxa5FqDdiqbX0XCz1PqzwFz9dm4vlUyON/qq/+f359vASe/hcH4t16+Ni6tgz+/khd7v8hgnBbtqHh93N/ljFxN0oilisX1I+PtW3Zv3xM/fCAejkjXiMc9Kc7gLbYPZGXwXotdKjbSeYcTQxHYjQPxmGi9U7GWDKYZ3NAR1gjoYVoQHF3fs9uMGFHkvbWWDMzzzP7xsEZHKlCTSiHHiW23JS2ZaZq0HXDNjOSSqEnR28GvbVPHmU85ISXhzFtsEo7LkcfHPZ8+H8mt8He/f8M49tzd/sgQHMfpC/v9I8EGrBWGoWcYAmlRTXrnHcF77m53SoATE9NxQmRms7uhCiypkMtME0tpQkzKhlTE4oJ2MDQspTZs8GzMlrjMBOtUyrdmuuCoxWIsvH9/xxvpWDK8mSZ++fSJnz89cJyVdnY+HLWz0wlujchA8MbRfCPNCQNM+8qnX/5M7yv2ZmQz9Lx9c0fOM8EpSZJzZv1+FkqJpBzZTzPTksAGljgTNiP/1//w7/jll1+Y94+kvKy98CuRkUTEBEJnyWvTWGuCq2DISKuY1nCt4QFvBR/sGVeUc8NScALeQW8FDwSBwXu8N9p9MM/YjXC3aSwReteo6UhLHSKQ8p4hCLvxhuA9wXcYo2WAnIvK9naBUhvzMqtQEJnW4Dc/vl3LBxlp7ZKxXb+TBpBWVN5GMiKs7W6GEHo6Onzn1MF2lmpUe8LMi86loiBgYw3BmJU4yVEKuCBI0+6MkhvOaURVa9GSo1vnAEFFgnZbEC09zDFhqmb5FGfjOD4eKDGz3XT0G08tjRB6Ymk8Hha87whDx/b2DV3Xndv2THA0KtN0JGaD2EIziSae0G3wvkcQrEBwgQXNcJ1CmVPPvriGs4Gb7o6ua6SukSYwZabczBixTPKZfNwzf/kF4yw1JcxxoU6RwyeBaSYYy6bfMrztAE+smmH6NbaV0/I3ZAAubWiXzOwlkq/10oLwPQbkGi9wJvx5bszbel7zMkr9nkn9ZIzlK9tfI95PUeX158/zGF+/jtc/v5zyFL2/nnZ/ng5/bayvbfNiuysP4Nci/VezDqe/X7mk63vzP+IgvIbnuDgBp6T99y0vQZAvI/6n6792IGhNcShmbTNrNuCHW25//B0yHymHAx+mI/tPH5hzptREKhOHx0rbdtz43+CDJ81JhXusqHqb97x/e8PD50esMdomJYoet86ooTdCHyx917O73dGPHSKVWjMWTX/XUkgpkVLVdrKVsEZJWBLTNDNNk9aXT4+6qtBK5y3OVMw6+dRSiPPE48M9zjmOS+T+y8yXT4VYQOQzt7uRm23H7V3PMk/Ew5HaDTg6DBlrIHhVTjQryYtBoGrUa4zTVrMlqcJcrqSi7WSlquJdaxXvDMOwQUTYH45MKbHdbhnGQbEARpUSc16Q1dUKTqVeqzWY3BjGHZtt4M27HfvjxOf7Rx72y6pm16gtIiVirGXsA851tBE6Kzw8Rpa5Mu2/4CTizY6hd7SiUqzzvDzB+pRSwLRVc96RqtCk8I//+Pf8X/6X/5V/+qf/wn/5z/8RMyUVHnKWGCNLqRiTscZT5oapldyapvFrITQoRkhhDRiM4IP2c1cqxRi8EyyF4GAMKqrTiyLvO680trlrdJ06arlEpBbGzjK4wqa33GzfMnTq2Mha/y85k1KiOTXoOc/UnLGoVHET/Q6Nm4EHSbSivfZ9ULXEkzbGZjvQclJ+/FZU1dJrFwUNUsxgtGUQt9oTa+ml4/7xUeV1Ae+VVrhmc3YuRFad+1YppembULWsQ1NHYxzDKpHdoURGytIZbMCGgbKOU6zQ9yPRRLphQ62V/XwgDCMxR1LL3N3cMm439MOGeYlM80SYOyRbppg4xqwYADPRCPhuu84fKEtoNcTcVN4ZgxFHaRZZ68JWVvpomqoQbnY4VzA10aqyYnbV8+X4J758+MDtzQ6pGRMn3vQdfYYWH9n/8ieOb36kv/2R4EdKXXk1vjMD+zdQAa9IR9qTVP05VS7X56w8122XVyfn6+zAdY/8Ke7/HwH/nQ77VIzoBJr7NhjtevevG4/XjOw1OFCa+YZJO13762uvqY9/bRyvjev699f2fwkofG5QL8f7nnv1fWODVyP803P6ximu7/dzfYiLXPXzDA9Xn32dIOk0OD2qpeEwYaTfvcf8LkFMlBj50zQhLeNN4fjwmeO051bKufUtTdrnbkoiNUVKG4Hbm5FWNf0LQqsF5xslLog43t5uiSWz23RsNoMKzLRCXCYOhz2tFLquo9bEsijiOXQD427L4/7I4+PE4+OeeVa4hrGWYew1rc1McIbgobONzgvWKSubSEdwI94nui4jqbEc4NOHBx6+7NlsdPI+SaG2FElxVrDbqWWyQbWGxRla6bXeGUbmmPjLXz6w5EYTC9auGglNoymr7/8hNbxXNLUxliVW5rinpMjgvRrucaR3hpIWoFLqrLVcMQzjyHY78O79hiVXPn95YH88sp8m7u8fOc4FK+C8wUihloQPShlbeugD3G57NhuP1IX5eGQzDpzY8GKKlDUbY5yQ5wVqxRnP/ZcDPvQYSfx//z//bz59+ICpmc6qg2ScYBq0lRdZqiA1aiq6aSbIkxm9pwteU+cspNYQ0V5/MVqP7oLFmkpnG5vgGLwjGI02nRU1rCas56rsBsdue8NuM9JZR3Bwd9ezzAdS3KuxdR7vQWpW4Kq16qwldVStd9oGCcSy0PXgbK/7ikdKg2IgwNBZWmDNUCm49FR0y6VBkZVVUHEhMWobbKlNlSL7QYGYxmDN2kXTVKhLOTuc2pFWVn0I/b575xiGAR/C6ihATJElLjjvgIq3TRkvl7iyNypwb1oiS8w8Hhduhi2mH+nE0m93GN8Ta2PbBeZlIX38QKapemc1+H6LcQVjBozxTPs9aVnwXcA6Q6ZSTANr9V6JwzSHNR7nHNYKMR6gpRVA6yFsFeBXLbY08v4RFqXMbiUSWmYMPb2zzCVx+PIzH37679y++z3u/W4tO0aqCd+Y6C7L3ygHLOcI8QSvak2jOiOnFO71BPws3fvKca/74a/30XNoWeFrxut07Nei0gvS++tgt8t+jTNG4cqAq0H6usX4miDR0/OdgJHt6oc1Peae7He9nAzc82O+ZgBfW15kM76SZXitBPB8+Vq24F+zPHmPnpwDLu/Lt/d/Xi65vi8vh3dOV33dgRGNuExT9bu6im40EzDdlrB7z+3vFOk9brc8fvyJFPe8yUcqids3dxrN5UTMiZwTThqVpLTAZDaDJy6Fw3FSprKmoiOxQKmqHz54R2ctlkYuiZgWSiukGElZUew5p1VgRjMWMUb2+z3zMdKapvpbM7QKXirBKcd/7wxjZwm2aU3cO7pO+QOoKyB3jeCXGb58fuTTLx/48ccNY+gwXqPiw+PEfDzQSlL51xypVYWA0hLJsbKkzJwK05I4HBNTajRbaVKYYyFmzWI4p/V8nxrjqKRJxloylpQ1Ws6At6oV3+wqwdwqtaook/UdSKTkglgFn7259dzsbolp5OGm53F/JMZIzio7Tqk4Y9mMPbuNwwfLOFg6K4ROSwW3dwOtaenleGzElKhNlQ+900gul8pusLjgifs99/cPpDhjW8XR6GiYqhK6YtS5rDWxGzyzrZQquFS1FNCgmga1cayNkhrNKNWs89olElpiE4TOQR8KY7D0Vh1MKxXjGtYJLgQ2m4Gb2y2boVf+/gZIpuYjzuVzb5Z3Fe8dm8145q3YuaBU14u2hVrbsN5RjzN3Q8fQDTixpGkhHqM6MdaxLIuqnxqjKXkx5JZJKVOaVWKfJjSEUiIxJ5ooMDH4gPOOXNOKqRFq1Yyc9x2tgjFVlQdFtGwiDmMUdDcMw8o5oCI9tWVkLSnmnGh1puTKtMz6HEvjGDOPMROGAUKgGIsNPb7v6NcMQHZF+ST2j4gIrg/4rscZQ80ZIUHoyHkhpQTG0ucOF7xygdgG1pCNV2ro6lZ76RQyQENaQtqC1ITkRrUdrt9ic+H2h8J8/5H7z7+w7Qxv372nlcxymBAcZcnsP//M/ae/8vbmB7zzFFOQf+s2QCPunNauJ3a4ddJuq3d8mnAr5VnkdZpoX494n6Ti144Brj+7Wn6175+nE72sGIB/TepazmP+9vl+LTp+GmVffl/vd05zrRvUms+YiMv61x2Zr43tOnL/W1L4Ipce+X/r5SQje30u/Q2cgaB/2zO+/vx6+XbZ5+Uiov3NglHCnqZ85264JbytdGPP7t1bvvzlv3H/+SdoMznPlJqILWuE0RKZSuct3hs8wri7TK7TcY+UlXLXN1LKKtSSDM6NlDQzt5m0OgBiDc4KYjwtao3UOUvXBWqrPDwezq2DzijnAM1RSlnb8RrdEBj6xmbwDJ2jc4K3ghVDk0o/OO7MoMZLKlWgc1DLwrx/YDM4jDMsy8zj/Remw4HWhD4Eje4B7wJODFNOTFPksESWDNb3OKksubKkwhSrEtmkgnUqfdq1QG4FWSb6vmc3dkobLCrkYigUAUom+KAMdTnhe4sPQqkLOVat9VuHN0pD0HeO3XjD8mZgvz+wzIqPsFYFncZxQFoj58S8aIfH2O8ArWNjZBVjAmV7q7SacRhqypQ5sQs9MSUePnxQRwWUGhdN60vRdzNYBaTFVCjWYI2ivp1XIx/rSsTToGxgUX0fjAMXtAwagqHvGk4Kna2ModB5wRnBWvDBMO427G63vP/hju12pOREnA4YlCIaMXivxEbzNBGXCBSccyyLtmBa12GDwYewygMrZbHrM8YKwWrLZbWe7NRxFiydN2sLXlxxD5pFwDnEeEo2qz6DoWDBqQS2WMcSo6r2ZZXXraJg0WCdki+pUCXNaIuqc05VCpuKFeesjkYuuv40i9RWKbUxRdWGKKI/VQS/GxHnGbY7fNfTbMCEQOh7/HbL5t1bFhaO5RFEtRqc84zjhoqm+MU4rJGzk4c0cslIXrtptE535hhQHIkh1wUQusFDK7RW1BFfOTKaLUi/w90IaUrM8oAphU0VKIWYtGU32BHKwv7+AzeHe/zbHUEqxeSvznPXy/c7AOYEhFmN1vog4VKjOZUIZI1wT9F1a3rxXzOm59T8agCkXcdtv270n0e3WjtcX4KVjOUSOT81Ptba1Si/jgH41nIierm+R88j1NeMsIIknxvBpwba2kvnxN+6XA79lNnvcr5fj+TbZUPWJobz319fvsdZa69udyr3PC8dPR2z7v8cQPn1c70s03x9+xUIVVFpWat0rLVC84LdGsR7Wk6Ed78hSOLjz3/k8+cvGNP48f2PeO9o3lOTwXpD6DslFWqNN2/esBwXxnGk5ko8LIoKto1lLsohskwclyPd2BGGQGuWJWsteTOMIA4xlv3jjIhRJsCmNVOZo34na1a0vLOMQ8922yEknM2MvWe36xh7RZ3P0wQi7G46huJI+UDoMtY1djcdfefYP3xGas8QPIfHA4fHR+Z5wdLhe09zTdvcug5xnqUouY/g18lXqM1qFLVU4gqIzRVyFkqpPBwPGDNjvePmFjAdXfAIOkGFccT1Ft8qXTCQE0t+ZAweY1VPwVrDOHQYZ2hrUFJrXdviHDebO2iykvpoJkYjr8pmdGw3N2y3PTe3N+z3e2KcNRXtoOudEgZZi2mGMs3gPeOo19ZVw+Nx0kjcO0ot2vcvKFgOfUZmDZL2k3ZDWBPoHLTe0GNpxrIZHbe3PUtOSnXcebq+07nKgfMF6oJtlSF4hhBwThSw2Bu2tzusF/oBrI8YUzAr2UUIls1mS0wL02EBl+hWo+acY2xe70+tlFZxWDBaxCwlcvumYz4emY9HLIZeerreUSPUnOlCIOWJ4zFxTKpLYTolLDK2Q5rem9oq9dxt42hNSFGpihsOh2a3ShaiDh0nRuv3Vd83K0qhS9GMwf5wQMTqPRaj3+V1fp5L5RATDUPoRqzzCra9/YHN7oYpZW7u3muRxgfAUJ1lcYa5QL+7w/h1ThdDroLzgT44rO0BT+V0ncrzkHPGisEU0XjWnLpCLNUITZpyhggo/tlot4VUGoWcEs12JFvIYcfw7rc8fvgTD//8L9wMTrUl8kzoBoxJxP0vzI8/47Y7rMtQ/Kvz4fPlux0A1ztKLuSsEjitmQvyWiAVnURltf4No5zm54m2aP1LZG1luxjrcjaI62S9GtJaV8sjr6evn6elX0vBnwzqJWX+tZR6e1FX5rzu6edfKzn8GpjvpDKoh76krPXwq/P07Nq+tlyf/3kp4nSdJ8fmVHK4XvccjHe9/glq4Tp78c0RXaJ4a+yTksdl/dcNsRr+U8nn+XHV2J+5HJ4d93JNr4/wWyUk/RvUeq4iO6icrRhHE6Gu+udGGu4248jYeKQ93JP9I8vxgV1GU5hNmGJi13tccEgt3NztSKlgTMdt2iDNkMfE/mHP7e2OyUfilMm54IMn5oWHL3uG7ch27BHrcSEwzSowsxl3xNT4+PEzpRRS1IxDZ6zeJ7Haux4c3lSGTnXj+85CiRweJ4J3YCpiKsYtWKm8eTvy9t1ATgvD6AiuMXSB3jv6zsNmw2N3oOYJaqE6ELGKJ2hQYmWJhcOU2B8TcxWqOMqKFo+5sOSKC8qhHpe6ft6Y5gySeVwax2jYDB23NyObfsNShbRPeCkMxdI7j9/c0m8cQsH3A7UWYklIqdp6Zo0K4VjVeGjo83HOQdOoa1kiQuXh/oHdbuT3v/93vHv3jmU58l/+639lWRYFy9mOZcmkkrHeMnY3DK6n7zd8+PLI42HmdjuSkxL+sGJAaJV4PBCCyuc+zAe8D7z94ZYlFZYlUeYFbxvGGbo+4PsBcY6lZIxzDNuR3//9H/jNb3+kGwLWN/7bf/2PfPn4gd040DnHPB+gZO7e3+KC4fF4j3ih3wRyTDQpOGMxpvBw+KSlF1cIg8FbNVqa9fPElKAqU2Eqamy9c9gKP/x4y6cPUdUyE0zzAVsClsASC8aI6tW7HrIBa3Fh1PIByqtwWCLTNJNX3ftaF2pbsysoeHROEVnLAtY4QtfhqzDFe5XPTpkoSglMBeu8kjF5h/HKIVERmlNZ5UUadjNgg6L6f/jN3/Hm/Q+EYYfrR4ztKBgq2rVTEdoK2B5sw/eGXBZay6tEt0OsoeFoxWCcU3IuUeXAYQjUtUUxeH8uk0uzK5hXqRWtd5SSOE6PGDJ9sNQ4Mz3eU1PEYkE8/e1bWuewZA4fM7lM3G5GtjtDv9ky58L9xz/yE4W7x0+E3XuM7wlv/p+vzofXy9/QBVCx1qy61qw9sXJl7E5G/cTnLqu0qbyoV78Eaz01nKcoUf99Kql7/ftryxMDLLJSxD4VD3oaGb5SOrjKAoisnAHI6tygtkrWjMXzsHgNV79m8F5exys18W9e4WW9yNW2J+N5NabnNf5/GyDf9x3j+XanTM9peeIcXPX8Pz/8a/iD14/9XLjoev1Lx+Lp/5rqbVfgzFMWpIgo3aar0Gdcyww1cVsLLQTi8YF+HLRW2veENOKHAbGOeT5yjAekCiF0eG9xxiOhI1jHtD8Qp4XgHSkuxCXjO8cwjrg1BVtaIS0LcYmUpAI20xRJUaVGb394Q2uGFFdwVGVlDBQtAfiGdY4uGHLJ5JKwzig3PTOlzfjOY72llsqhaE97qwOtRJzrkQZxmmkFttuRdLTsHyeGrqetOumPx5nPjxMPh4XjUkkYYi0cYlkb1VUhronBulMqszHHxnFRzvnYFo7LR5y1bMeB3Xbg7bZjMzi2Q0CcJ1ZFSy95oe8MIbh1/jHn55az1ur7vkM6R87KoRCXiVIUdOa8wVpR+ljT+Otf/8wvv/xEpTIvkfvHR0Lf048bhtARamAcNvz2x99yu3vDshTSn38hff5CE8s4DGzHgS8ffmZ6fCAuBxpOU8fWYjaefrPlNz/+jj/+6U9MP++V6c8GGoL1mRASxgumNWyAbqhYvyBuoRvVadvcBuboOU4PxCwq8OMDYhM2BAbj8Z3B9arNgDM4Ebz3hKLvtsRGKWcN1PO3xhlPMIZmBJeLyk1bA1UUjErFulXHwVpSVinhahxLqizZ0KSj22zBe1KtPDxOPBweOB4X5bAo5USbep6ruq4Do22gpYE3BnFOsThiOR6PtALitN9eDBhvMKJtmjFmUgNKpYho22kF8T3GGcJuy93bH3j/m9/yw2//wO7uLSYMuH6DdT3NWtY+GSWoKkWvqyXteHGC2EZMkZgSIoYuDIh4QFsL6zqHGKfXVUth6AdqUSEkYxymmdX5aTQLuRX6Vqg1gqlUsWA8zVSOU+K4Pyro03ds7t5i20J8+Jn7/YFh7doI/Q13feDh45/4j3/6Z0y3ZXv7lv/7//L/4teW73YAai2KnDQGUy+Gq6zSmGdIAGuEthpxwayR28XInxyArxqSdkqTnw+oZ/uKIXg9Ar463JNo9Jot7mVm4Po8pw3blWF9YpqfsQvK5cDrvq+n8C8lAS2bfBVD8B12tl2GeTVGntTwXzP+/5b1/afP46Whvd5OJ+pX8AVnp2XNIL2S1flWnV/W+/31d+DFnrx0s9oZ97F2NYNUGqrK1iSA32Bo9LVy0wy225DmR0yekLTHuI6u3zDuNgze0mLkMN2zHLXm55zDG49UqN6yr5klLrRs9DvmhK7z+D6gfJl6P6Q1NkPPdhtYYmWZP2Jao+8CN5uRXCvHNjNnjcTGoWfTd1jbGEaHsZm1Y4vaqYCQ7yy5VkLfGMaAt4FaCq0tpDjRWlYyITQLZoxhs9kQ3I7Fw+PDUdPiJhBT4ThH9oeFKVZSFZYGx1ho4rm9u6MbRx6PRx73j5QV5GcsYCLilLluzjDtE5D45cvMZnjg43bg7c3A+zc70o2lCwbXHNgM1lIQNMNY6YKj78JKoVzWMp1+x723qlpXm0rzGm3BGuxApbCfHlnmiW7sSSnTjypHm3Lk3Q8/sN3dst8f2KeFlic+PjzwqRxo247N9gbrHB8evmC2HutGNnTcUOl8ABFSTtzs7vj3//DvGG567t7uiFmJdWJMxKyc0MaDrQ1sJnPgl89/4uP+z4Q+4ILjOO0xDVxnaK0QmTA4Qt9TbcZ5C7ay1AVrGolErcpA2feBlDKmFoxVrE8pWoJTmWqzKtUJpSn51Knl9JcPv2g5oRpatRin5Fa5WKwfwWhnh1gh5aLSto+PHKaZwzIzzdoxYsyKQTGKbTBmzX82ZX6V0lbCqEYtMwejYElbM0UqKR5wvjHmgHMqM52K4kxO3SYF8F3H5u6Wd+/fcvPjD7z58UfevP2R2zfvcd1INg7XjaSibKwiFoxRHEar+KIBrZG1o8OsDsAyIxi60AFOS+FiKbUqFsDK2uEieOPVASgVa53ibhDt8jGNUiu+72k1UfKCMx5vAi1FZj8jOKREap0Q8dgwgu+ZpwNxnpmXyM1tI/RbTFoIpbLzjrsQX5+Eny3f7QCUOtPw2ObPRldWQpJzS0bTlo2TDCtrQV/n6OvWwJfp24tDoBP5tVHT7PDrLWvXy6uTf9Mi0nV24fUo9GkXwNkIXdXLn6Phn0fzz2v931pOp31xTZckxf+hy9eu4fX0+9/wPL52vovn8uL837qfT1P5f5tT8/S4jQsRUePCe7E6ccZSCSgSqSJdIWwFsQM1PlKnzywPhdIsrVlNDQaP90ElQetMyxXrPa0UlmPk8PDI4WFPXBZKAmcNXd/RhUBrlZgi1jn6vsfYwDDu6Mctn78c+Pjxk/INiJDmvU7cLeEoOOvpHQRbESmUmGg2U0+p5i7ggkrzYgSxylzWDR3eWGpJ7B/WtjeBlCK1rpzxFUV1FyXYyblSEeaY2c+ROWsU04ylZiVmGbYjN3dv6IZeI8L9w4rW1lKh9Y7OVFpuxKzUtCAaXU6FY9zz5XDk8+ORd2+O3O5GtkEo1VAROgzSDK1oLOs9eCeUlJS1T2DoOrrBY8We1e/CSmFby4JzAzlbXHBsdhs+fPzAuNtgrQNj+M0ffsft+x/483//I3/95ROLgd2P79n99jc87I+EbmT35g0pTjx+/sDx8wdIkXHoeXd3izGGx8OR3gd++fJXQm95/7t3isNoKp3cGlSpVCMsOYG3+KHD9p5UM8Y7Yi74jeVm3DB4h7RKCJZWoiry9R4XrHIfiEodY1Sfvh8DZtVvME4DENOUQlDE4n2grej7UrQMVirULNAM4/AWa4TjYWHOGdM8RSzVe3x3S5kKD8eJz/cH7h+PysdwOJJyU301c5WxbMpuKA0cQl4mBQLWQi0V6yzGqMEcfMfGd3R9zzAaTBRqW8gGlpIQKsYFZOgxIeC7gX675e7tW+7ev+f2xx8Z39wxbHa4bsR0I0k82ViaGalOHZ92UtAzRvEfK/NnW0F6pRWs7xj9lpVgfi3fqgNg0GwdUjFWS7O1aVlO1gCnrVlpaapOaH3DmoFGoaaF6jfYQUWFdilydzMxTw8s+8/UWbsesA7xA8SJmiJTtpQlY1CJ5M3YUZaH75oDv9sBWJYZa5M+FBOwVgk1tO5alLyiVaSK9m1yamNrICew3Ov95BeAoToAck7DXuq/+pJ+3Shd/75eXu7x1LB8HyL+Ms7n56v1KVL/+vfX8/gv2wevqyJtTafI6xfw/zfL6/f9kmF5/Xm9xFBc37faXrY/fk/nx+k5/Jrz9fX1jSZ1ve9KSfSktiLaA6766CABggRc2CHpBuk6HpYJimU5Jh54xKYOiRlypbMeVrR+Xgr7+0cePz2wHGecsSutrIKxTtelQkMr4nlFjkurpOlIPBxoqSA2kuaGDR1DH9h2AStKMVvyTC6L9o87i1kjE+MU/Gq90pRWWUipklymGzrGcUuaJ4wpgEZHhkZKiWmemadGTZZcDUtq5DZzv5/ZT4klQZHGUhuxojXZJhz2B+JKOKNigZbSKhjV67DGITWz6O1CnLK7ZSPU0kjHyjQfuD8e2W16bnvPD7cDb256bnYj3qr/VnKh1AkhQ4t4a+h7D8aRKxiUWrwCRoRcC3FZ8Gv2pRkh1cL2dofQsEEdsJoT9z//lfuHezCNzXbk3W9/0NTvLx8ZN1ve/eM/YIOn7O+ZfvojDx9+ppXMsAnEuDAdH9jnTFoifejwITBsVdgJEYyxuM7jx54lR0znuHn/hu3bW6U4do7jnGgFld2djjgat7c3HB4/89Nf/oTxgvUCzdKaZn36wSN1VaBMlWZ0smm1kqtKNEOh5EYpjdZWNswqgKNWoSTwMmIlEEJaWfc68rGwf5j4dDzw5cuBv/7ymQ+fHoixrGDPRqnKS+E7zXhq9n/NAhsUg2CVorfmSm0rQZaFYei52d1Q5qgGvxUWinbn9EGJhrwHG9jevmXY3dHvdty+fcfb9z8w7nZ02xtcP4LxVBzV9zSziuj4HsSBGDVZ7cJYc4rHRAyVjJB1XOvE3Jqs+AUwYlXqV6pi32R1hDFY71VTpTZaqeoEGANGKEUZKdUT6rCm4ESJogiZvk9sdm9Itz9Q04EWj8Tpnnn/iXh4YP/5I1M8apeMqcRYmJd7lmXhH745E+ry3Q7A8bgnBI/3/Sr2YpTUYSVVaCKaLhI1b3V1814Dy52j66to9zrakisAG2jqhRegtaeT/XPH4mxArmrgzzEAz5dXP7sCn10DAK/79F8by2n0ry3XWYTXDdwpl/8/mqZfjXG7OBWn7MY3zeT/gNNxKrP82jZfw0esSZcXd+CcMTmP8bLVc2fiexyG6+2fflChGYRVU1u0MNCAWg2tOSpBJ6CuQ1zB+oBI5Gg7BNVDf4gZlxK9qPZ5zYUpLhSTWY4L8+OskXlR56Bas4JrtS3NWFURNNbQcuY4z0zHhdoMH375QoqR7egJQ6/RhdXWNydW2f5axkkldA7nhZvdBhMMmYYYg/OecbvF+kpMe1pt5Azzojr3papTFZdM13mkNpZlYZ4nags0DCklqnjmJXNYEktqpKbtW7FoM511WmY4TBNBowRCCDgPrjRMqqQCUoW5qGBSQsVpdGJVYyc0Mo1DVIcjxUirlXlJ7A8L3dofP3aGUg3eKstg1yk7XGlCSZXgLV3fk9d+cB8cvvVYp6p7rguIQC5KUCMiTHFh+vNPxKTyw853PH75TKmNWCoP+4nd3R3OCFIi0+M9eT5gW6alyD5OLPNMng6ELuA2Hc57tlvt088587h/1Po4DSMG24MfLd3W40dLWiKxZcRbKipj7N0IuTDnSC6FcTOCVO2lV4odrfM7o62LtTDPCzUrQK2s4kEpFmoVnNVMgLMO7wLG6ntQaqMmwzJVDqlwnCL7aWGe9zweIh8+P3K/j0xzZIqZGNU4WgfGO3VcnUG8AVaQpgEjdS0HGHKJWAuh03feWm07d9YiTsAbsmkMY89N1zNsPJvNoDgAHxDXcff+N+zu3tPvbtjcasQv1iG2w7qBijo2zXU042l4kKDvn2jGwVhRroJa9acppsBYrwj9mkklAYqXMEZbh5ucgMICLdFa1u+zcVTnsc1SqMgJ7KwkAIhxa7skGKvMl9oxlxFTsEGfo99kaomUPOHigbAcKMsB+/FnDg8fcTXR4sJyeKDUwjj+G3cBHB7vke0WaxwYSFFTIM56LQVYAaxGcbVAW0FZbU2hoJ7TJaJ/Xbv9MsVfsSefckbfXK6N+/qXCNR6VV96igE4bwM8R8Wfjvack5+rY50yApd9TxHx6b/Xo9znx9Esgzw5xr/a+F/tdsqknACM147Jt47+rSD6NefludF9TmL0fICvgjlPjkO7GP9TvvBJyWb9+HRtIm010O3pcz8f9uslgsv4T8/qqkR1foirc1fXAAFALGI0+yVSoRZEAioFZKEIyzJzyAvihBoX4jyTpkiShfmwYKowdj0tZo16BDAWI0LJChLqB50Ml5iYp5llORBz4XF/xDtD328Qa8FUSsnUmpR8pFRyTEpwEwJ9HxjHHttZctPJqsmpt7zHeUtOmekwcYgLsjLgdV714qdpoaVEyQUjhlQSacmkZJBuIDbtvy5AbpCr0IxB0JYs67w6Mq2SckJEuLvZMeVEO8y0pUAVlYj1mYyWJAqqP5LWd0GMYgm1B1u430eVFt5P9EEYe8NmsMyL5XbXAYbjlCgVuuAvGZCsnUc5R1xwuOCpJaugk+g5S2nrnAYpJp0HRBHxtWQePnxg3h/JCIc5sv/ymc8//QtpmXGt0AfLtvea1o0qmRxjxsmO1im4LZfEHBVQrboFhiKVlhasXbtB9l+Y28wUJ8R6DofMMhVuxg3BWvJxIqWFVhYVELKNuMwgSoZDTgpCFMipYJvDGbvO4w1nLM5oV5d3ymiHeGo1TIeJ/eHANC/Mx0Q6NKWMftjzZX/gMGXVecjCw74RBocL2mZaakVWMKq1hmahGo38nTOqaKhdhooPTRXvLMEHur5j6AdUX8PS9QPTFHHO8u6HO978cMvt7YjrHKlkXOjZ3b1j2N7Sbe9wwwYTOrBrOa46mh3WNjsDVmv3qvfbqYCXrCyFCHYVYBIaTRpLzmunRFXDjDrZxq64gbKWrUSUtbGJsn4CxniU90DLVZpBV9xAaQVxKjIlTbTtU4zWXcgoeYC2ZCKN2pTFki7itplAZng/EQ9fKNMeyQvx+EiOC334N3YA0v6eWBOuFbzvtaYojUIAvCokWYOxTqOkUhUgSNGXgbpGnmuqf62BXFLfigTRdFhdJ/lVSes0J6P9vadWutccAzVuahzMs0j3lGp/YniNPad04FSHv8jIcn2KK2PT2tr3j4795Fxcj6mdAFzXg1uPo5asnQ0eq/LWxQC2S6bk2TWcx8m1EZPLUJs8seKvGuoXtvkScz+9rxcmQz3v11P7p8Gv/RLrc3h6ilM25fT/03vcnmx8GtH1+dcXA6Q9yRRc35vT/fm18s51RujpbzRNd34g6hiYUzbAaM0ZtGar4Cf15GsqECtyjNS5EE1FWiKnBYMQSyZTGPyAbRZTrSLUhTV169Yoo7AcE9Y7WgWpBmqhxELNFWs0sko5YjujUVJVLM4yL0zHhaEZ+tEwDDcMY8CGta2RFSUdI3G9BbUK0iw5J3KZEGvotwObmxvm416ljDsHpVDjxGGZgJ6UYUqNJTeqMeRWWWpTJLQ1tLX2m2phmSMxaW16rImSIo7E4CBWw6Yals4idb0fVtsFaW2ljNWUsrSGMVBiZBZhDpbtoJF/XCLHQ2NZkjIfOmGz7bm5CXSd5xhhyYkff3xLTDMUBU3mIkgxlJyUaMn2VKkE6xEMce03b1RsM7QqtCXjnefGafvccvhMXma6zUAtkcPxQCmJYJ220gWDRZjnRGuiTlSMNFAa2/V+9aGjlkY8zEzLjNs7HUs/YLInNEObK3PN1FTUCOFIKRH6HicNMYVSVmIrq5bW1EZnB6QKtm/QqYGs1VGqpRbHwyHx8Lhwf3/gzz9/5NPnR5ZlJsfM8T6yzOvXwllSVYdFjBA2Hf24yjgbi1RlWwxOMWPNQqZirRCCJQTBOUGk4qxw63c453DO0g8DNzd39P1ACD39ZqusgNay242M24HNdkM/djSzqvO5DuN7TOjBBqoYqogyKa2qmcY4zQCstLxOPM521HMwuvIPAAZ1OEUE70+MrQ2sw9pwsjCoiNmpLrgGJVjEeBWDWltzz/sbixgHGGzTuaPVTGuCQR2UZhqNtVzIiRHSrOWSirSCUCl5IfRC2PwddZlwpkIppHmm1n9jIqCHv/7EMQTu3rzj5u4O2w20GrFlAOPxjIh4jO0URYrRem4TRBxNKue5v7YVWLEaraK61zTWLxnYtaZ3NoirxdfIW1YFqwI816hHDSDnvAoKWpR1oqtPjENtlzR/a01rOleGw8hTg3Uyb0qbKhdT/yTy1tSxwqPa2WhpOyG06zq3rPvDKQDWE70oW1wd/xulj9NnetxLZuJpdNyubd16YZfMwykVf9r+5DSdj419MQ5QOylr3frV5Qob8evX1s734Xox5rTukmE5OWQnnoWvdT9cl3DOY74ah1yXhuSi4nByOrWZpZ2fW61NXzVrqN4Qa2I6HknHCT9lap0oUul6QzBC2Iw8HiekKDPatF+IS0WMowudqqxWwYknFzjcH5WP3SkqOxjP0jIlVSqZEJqqm1kljqqpYI3FF0fJlc22YxwH2irWJUUoTVk6ayqk3ChTplWd7HywFIF5ngi9ssrZrkOiyrNSUcESU6HO5NZ4mGeOc2IpWvOMpbIk8G79fpdGWsqqnLlmW2rh48ePeGuUlChYpthwYpAakLowZZhKBgHnrJKq1ELNyu6WrUatKi2cz7Tac8v0HmI8MPSWsfNMEXIL3Nx4fOfogsP7DaYZfvn0M1YMUOiCJ8asfdxV5Z1D3xM8mGXWYKZV4lRU0yAXfFUufhsjNiVtoZsX5hwpOSIiRGtxzuNDoLSE8YG6aAAkeLz3eN9pvTwncmzYpu2irRQkVrpg8UmIS6ElSzWVEDpsP1JbprSE2EIpCe+Hld8hK/GNVY0FOzhc9hweDsp70gwxNVISprny6fMD//LTJ3768yc+ftrz5X5ijhWnSV9MgS4E5cpwikfJueKs4ebuRrkYlkWBlaKpfR8cwWlpZSkJ6xWT0XWGvndYD/3QE7pA6DpC3zNudtzevWUYNljfEfqBitCPAyF0ag+MwXc9Yp1izoynWU9Zo+vKCnJcSwkFoxwFopG/wWrdvqLlkVMJemV91LlaAxl7bnFvNFbCu3PwcspMNU4cc2KcqhaIMgSumyn2omlQa4zBrY6AGOXRkCog2jVXsbRWVJz0PFlxJUcONmxprSiFdFfJp9ior8ivUMWflu92AP7bP/0nxu0Oqso1+phwfaIbGtb3mg4xmg5XVLHWnbTkYanNXs3/5WxY9H+z3jw1nNIatItxvSxqqE8T+cloP4keT0jOU/r7K1HgSR70bPZO9ef1YSuo7Pr838iLc3JQnqW229oO2dqToFz5BNZjrmN/epXX5ZFnEXO7jo1PBlKutrs2fk8N+9UJnl3N022uswyvi+584x48H/Oz5WsaBt8H+nvazfF8nY756TGvf07O3/P15yNcZQQuGJR2lcmQq/f25KQpkj2lzJILGVS+N2fyMtNcwwWNvr1T/v2SIyVlUszUCs4YrHNUmmqnG8BYMpmcEiknXAjQtL+9lkpFlen6LpDqQm0VZxzbcWTTGdpNZjuO5xLFcX9As4t1nWQ0J5sriGjtM6XEcZqYphlxHU00ZTkMWx6WPYJSve4fj9QK07QwF21jM8bSkgK+2urIl5o0O7IafjHmxHqFc5abbU/nLTEpfWqtEAx4IySpuLXMppryjVM3sRdRpwChWQEKsWTaDCudPmKFgFEWuC977g8Lt7cHxu2GofcKgJsnDodHgvPUqiRLrTWmWBQ75CBXhx8cDTUmRhreaxYixsQ8RUpO1Bz1ws0qRLMsiuUwK+DSZroeusEhS6IbRlaXE2s8REMrlVpgf5zoNx1d76ktk0lIH8BnSvFrZF8pKSNWnXljLU5W41cLtWVi0XJQa5lSFlqEeqwcHg4cp4mcKyGMdN0N8wL/9F//wn//4898/Dhz2GsHh+9UmIemAEHvPeIsS14wznB7t8EGjdwbCjDtfIDa8MYSfEfnPaEP9BKUSGkMjJuem7sN46Zne7PFeU/oR8IwMmx2bHZvsKtTZIyltkrXdxjrVFgIEBfWFkWD2LAa/rV9F6GJpaH7iqxIfVFynXNw1Jp+H2B1Aq4M+/pdl0su8mqWvcpIrouRpwGZlnZPbLlmnU9Pc4y52AsucsFrAno99reZYPU8Wsppcslat6b/f8/y3Q7AH//4z/TDSEqZVCs3b96xRbBOSSwagnWVVhu2FZxdpSKtINWtHmddJ2F00jhFZKfouCkSdLXEK6WwAkf0iq8TvrDG7pwTwedJ+zod/rRd75L+t2dn4hrNr62Na235ibF5zag9cw7k8opoxHiF9m/X251yCJdywpNFFIRyOs4lvX8x7mcsxemFeeZQXMb3yovQ2iufPjWM37u8huj/14LwLl+cV0f9ZP/n0f3FMXnJIfBat8Lr4zQvMipnY3/24K7et/V3W0sD2IAZRtxuR2ta70+mUDvH4XjA9x1j10MUjseZZZ71rM5qfa+pCAoIxkLXOaxX+lqsYZpm5nlGTMMZ5fvPMREGh/UGZ7zWEI3l/ft3/ObHHzlMj/z1Lz8Rj/MqSKOTkfOBUlQv3VilFK45s8wzrTW88/RhYBi2ZBN5lFnR+KkSUyGXRkyZdgIDi9BqRlCGNmvMOWXeGlhjsUYoVb9XbjXswTu8t4goyKnmRM0FA/ROVPLXaTuWaVrDVwdgTZdq75/WkalaHnBKv1o1SceUMvs5cYgT/ss9zhn++MefaangXGW3HaE1xiGrIWsJZ1XJb79AN3qsszi/1orR6NxaSy1omlaAmkmpMB8Tccm0po5OTlDKwnFqDDOYZrjZOHLTqLGOAjavXBNwmGfiPjJuB5pUmmRqJ8SysBTLlGCaIsuciGXNTrmG83JVN87EFElZ0f3LUshLJR8TNSlexHnDm7t37LaNZYGPH74wH2ZMbfRO8EFZHhsF7z1TjVQWpBpCELo+4AYlkHJetTN66ei8psidaOYjOI/zjmAr3eC5udlyc3fDu/dv2d1t2d3egHX4MIBTQF8YdyCOllcOB1Mwzur8rG8xsuLPVIhOkfxW7DqBiHL/FwXdnYyxiFmdgVX2m7Xmv9ownRsuYHT9mj+lfH86V8mrnz/9X9bzwgVndLFPIpwdhFPgpvbjRaT2XeP4nvLnafluB+Dz58/Ily/EpPXJH6aZtylzUyvdsCF0GecL1SVqCTSfcDYo0YMoNqA2rWpgNH16YQ+8imzXC1kJh6+cg3p6PLr+5Em1S1r54p9domKVPH2eFl6N7zqpP422T8e4cjzWET1d/zRiXE2AjnfdxohZvc+nRu572tVO9+Sy7ckpgRPl7aVW/3RcV0f4lf9f//y1Fr2n616eS04OCLy6/rLddQvk0+3b5fG/Op7L9T5d9zR7cDHu3wIAvl5+0LE8XfUsAwNP3rm1BqCdAX6D3dzi7iZwjeoKOR+ZTaPbjCBCzYWaVPTECJjOYb1VdjBpnHT5nFEj3RmYF9W212+IplyNd1jn6fuOrtNsWPAKnrISuN3dYI3l+Lhn2u9Z0qRG0zslJDEBKhoJt0iKiVQWcol0Q8fN9obNuCP4nvkQoXmWZSJl6LotcdrjveG4aDmilgytMvQW3/e4EHg4TkzLonigWrVPv2q5LzirxEabbu06aBwP2v/sUTzEgraCiWWVSxW8s3ij+ACxjlpQ8R3T8Aa8bQy9W6V4DVjBDx5TKpXClBKmWPYxk2LBW/j0GGlZCOFA34mmtf3JyHm6ldbZe+148mIJ1hO8CsEotbBQimre5+K0/ClKF5tzYpoWSs0cHyveOMpsWJJG6P2YlHrWCL7vmJdIronH+5mK3l8xcL8/so+V/Vx53CemY17V+rTULQYKFeua8uSLzkFiTq18jTJra6T3ho7A/WPiy5efOTxGDodI5zvCTo1lCB05R3JeGMaOm01HbhkRYbjZMW5HYtGWvGGzYUkZHzq87/BWwW7eOoJTatzSIsOmY7Pdstnu2O5uGHc3DJsduIANA0UsuVmKUe4LsQZjQFoEWWl6WzlH+4KjNbNiuVZuGmPVmcrK6GetU1pvDLVdmsxl5bJpq2N/gmbpXHv67r+c774/QGqrnbvMaydDf5pvTvPVZQ68nnsNr4Vq56Of50OzHusa6P59Y/xuB6A1TTkej0c+fvxAzIXjPPNjStzcvWGzK3Stoaj9DCSkqTyi4BWBaSzGBazRY2l66mQgr260sHJD699i5CzqcxrL0yjvGux3iozVW3+NH16NqkGQc93mtYn/RUb7q89ijQRPTsD60atx9lVGwlzVyp9HrZeX7zQW4fqFPKPXXxnTNx/+q6uuz/V0LK93Lbxyvqsvz7cdgKso/8ngrz+H5zf7UtJ4ebyn2Z2X13BaXrvfT8bQLlSy56u5eh6annv6uXJ8O0J/y937P2AxtD/8AZk/M336E8cPf6I8fMQ0BcO2VNaugYbrHM52WjNNStoisrYIW7Mij3VEOeez6I1zgX6zxYeBEJSzP8ZZ067WkVPmzz/9RGuFL58/UWtiSSr8Y50jBBVmsS4gCClnpuXIkmZcEIZ+p/VX8eTYOD4ulNg4HiLzlEEscyzUas6KbKyENH0YtFTowtpjrjK8JSvvrLX/v/bObEdyLEnP31m5uEfkUku3ekaABAwELRfSvP8z9DuMRmhherqqMjMi3J3kWUwXduhOjyUrawBdSOUGVEWGB53LIWnrb7/BEDvuxp53dzu66ElLYQyBPPYcp4V5WZirVluNK1gBa/X30NrGvAPfeUoW8pJwRojB0kfLOHbc7QaCN6S8aGm3FJZUqaJtdv04Yn3BGZjnmZorx2Wmm2BuJGp9Dz5M+GDxQWu1wTu80cn0fdfRd4HgHEilJAU2Ru8bAQyUjE7BKxGphozFhchpFg6nxDTN2MeFVCpioBs6qhRSTogTpbgt6hweTplshSSGtAil6P20PigHQirKzIjFW9va6RRfYK1uY2qhlIVa1ZGsFZYlY53n/fsRiwcMwQctV5WFlGdCdIgzlKbnunFg2O1IonTBoesYjXamqCM64kMk+kBwgSVNTMtR2xdDoBrDlAU7F8QnXKcDbowPFDwGTyVQrWdLJlexiNNzlJbWXw2/tKBOR3pLi+491inob02vGyOtDV+zV2UTgHDWABedeEnjv8xWvhUsXQcfW32zBnMrRuB1o7LixbbD657LGci+Cb6+NfJf5ZsdgDWqWpaFxy9fOJ5OOod8PvHh8Qc+/vAD7969Z7e/07JADYhEjPEYOpwblKTC6cQmNcClAamap4SixKsoWYdeoGBMOS+TbQtzSRas6ZtmGmXTUifXN0U/M1e+xiUSvV7Aaw/wuVzSNJda8WV/Z4fm9WD5G6PRtx6mb7zB35g6eu0Lzzn1v/V4v8Iu8MZx/+3yco2+fd/Puyd0J+g+XtZkNPqoq3cNF7ZKQfnAB8b7f8e4v8eZCdJnjj994Kd/Cjz+bzj9/DdqLvRWI6uSBUw5E/yIde2R0fq+Neh7IdIoWhOC9kn33cj+/h3OB6bpxPF4wqD8BcuyMB1nHp80Qg9d0ImGrjLPM3NKrbfb0PUDqVYOy0wuGRcs9/s7vvv4PXf7d5jqeDocWeaiQL6kJYD5lFiSsOTEUrX3vxbBBjXOiLBME2WZiU556IsTnVLYeYa+Z4gRqdoCabHsOm2jnKaFh8eFedZSgrGCsxUxgjcQvKPzRgczSSZ6i9iAM5XOG2Iw9MHRe0eMDmcEKZksYHwkWFFWxyx4FwjeU0ol9J7T6UgumVTAe0WD16Qz5kNV8KElE5zDIhyeFoK3OKMBSi0K+u2Dv3S7VGWV8yFqb7uBxynBnMm5kosgKTXeedG5CUYoUkk1Mc1ZCYzU5pELiHF03mOiJYRI6DqMNWRJjLse3zlC9BpkuEiMfeOtN0ynJ2pedFqdA6nCaZox4hj6HeEM4hYwFed3WAu5JKqzGK8U1cY7hv0OHyMFMNbRj3vG3R7vOna7O20xdQFnHdN0ZE6ns3NTSuGUheVpwiXY3XnuOkOM8dyKqPV7NMJvzjlGCZNMI94xbWIhYlW1V7UlauhXJ9rr39u7LCIX0s+Wnr/uktrW3rcMtZcfG7N/0X2mdT+d97V2BnDOcF9lLDGs3V/XalHLivqlt3WaKJuVZlVFr/1r278mv2kccCmF+aRjMn3O5xrf4emJ0+mJ5Q9/oJTv6PuREDt8jBjrieEdxgRy1sh+5Vz2rUVknmcuNMGNfOWqdr+5qFY/1zawtu2Vl/R2BKr7vBj69YbbtQb0LLNwyUy8Lm+D3q5z2W8Z86/JdUr9Ap5bv2/fQtpfff/Fp29tffWbgiuvj/uy1r491jYD8PVr3CLxt6WZa+/6FVzEM3l+/XofG5+5yFW3x685WJfzX9NzF2finKJ7NVux/nQ4v8O4SJGBVL5onf7jH7hbTjgHB2Opv/zCcpzwjcXMhMYvlgviLXlJ5LSoO+s6og0g2m8cuo4731FEiXZSSlQxLLNSwI5jzzwtPB0OgHLex7EHKeQCthoySgtcpHBaJipGR5NS6MeO/X7H999/4N3dPZIrv3z+hU8/f6Jk4enLkZSE03Hi8y9PlCwcT4WE1tkt0Eet9RpEjUxKGBHtwTeWEDxdDDo/PS8sU8LGiHdBe9ON4I0wdloCOCXBBuVMEfS57KMleIspQjod2Y0d3RiJzmApGMn4WrC1MPiOXRfpnGNJiYoC9+ZUdVStU477WjMh9KRkSOhEWO/Be6sc+sHT9wMiFSmV4BqIMCU0M10pSwYRond8Oib8av8LOG8YBsFaIdUFnKOizI/WR0rWnv3cCKOsd6RSOU6ZpAkXLHo+tlq864lxwFmHj4FhGIi9crGMe3UArDeacRJLCB1dHPHeInc9pSTmedJsk7MsqWCN9rSH0DEMO6b5xNPTA8MQubvfMaWZapXiWTD4LrK/vyd0Eesioe/ox3vGcY8xjmF3T4y98mKI4bScqDWTy8LheOTwdKCUylwy5ZjI5oTtE4SC89uuMeVjMCZqORVlazRYxcuIBn2gQEilqK9Nbxkw7qzztyld4RKZK0eFGk8F0K38LtvU7+vZ3NdKultHwjYbsgWr6/eaQ7I6COsRtoq76aW3RKTqtZ89iN8eXH2zAzB0PcMwkHNWbvCSdGKYVNIyM50OTKcjyzK1TMCe3X6Hc5Ep6wAPEzuKKLK460esVyBTCB0eHYxQ2phIVeRtprcoaE8VezMiCpVuivkC9ADOdLLW6vhF59bxwlVfJqsP5XkqFZp2rXWr59uNY4M9aA8ksk1TG7b4gNci3NfGCW8/f6vO/hy4uG5rrX2xz+f7VoeqXj2k+vnl+lYj+vw81rrV9nyuDfXF+L6Gb1jBdM8NsDG65rZxbT+XbSnotTr+dru3nIy3AIDrv9/6XP+xdegu5aPzNW6rBRsHVUzr7ZWuzTkXqjc4V9n9KOy6jvw08fnLAWcTtYLrtFc6Lwu+7ygz2mZndSSxsYaUNZGJaXwVdeUk1Ge5LgspLXhv+PzwyDzPeB8Zh47YB6x3OvXPWB4evmCig1rxIfLx4w/c33/ABceSF+bphDE6jyDNM9PxxOHxiV9+/oIUKAnSolMIl5QpGZxXvVONgvL6oSf0A6kKx6nQBe1usM7jjGHoO+7vdzhnmaYT1laG2GGwPHw5cHg8QcncD5FsHXFOhN1Aksw0TTr3vjkAAYsJjj4ErBGiNQTntOXMGgWxWaglEwwsecE5j62VaGlrqjPjh2iRMikNa+fo3kVK1tGvobXvIYrur8bgnDIwUoWUFtIy4aIHEUothBjpY+RwODDnTDSW45TxDrJUiklY7znNR4wxOoSp6r323pGlzVAYe9w6W95buq4jBk3TOxeInTIKOm/phkA3Bj58uKeaDE6f21yFWiBGGPqArQ6pkSqDdm15JWsC7cbAOozzDKOn/7DHBwWk7syA7+8w3iuwr+/pdzu6YSDEER8D1nf40LXBOq3sazRaH2TfOlcy/m6he3dinicluFoWUik8Ph0Q4xlHQ+gVrBeCx3pLKmhWuNH1cgbzgbbSWVYba3BttsKaCWgl39YSLk2HYgxFGu3u5v02a5bPOHQabQO0igJabRtXfwlUNlG+vKVzX+ro1/TaVrcIes3nz6uwjk03xijPBjq4aBuA/ZYk62/KAKSUWNKis8aHAWMsJWUmObLMM2lZmOcT3//4Az/8+CPOQYgF7zxLdeQ042OHd5HpJHivD7DyczvMSrlbNQUmwrlW9XKBzMUQn+sqjZRhXWwrZ+/wWta+8W2k90pavhERrH8yLTOxHk+uAv2XDHffEn1uP7vedvvwXp/jr+9TnaLXgHDrNVvrXv3bWlPaPsTPj/eaw2I2L8HXHsA1Ot9e87Vz8/p32pE5e9OvnM9rOIF1zsSvytUm5uoazlmXNzNCltKGflQq1TeAqwdXlOve7/+FEv7GVCdM1VJAQXhMC96AzYFamvKxmt6UWqilUGshl4K0F997HTFbi/7+13/9RQlB4gDGcEozrncMXaQfAyFaiHBvFbVureduf8847AldwFA5Hg6cjkckF46PTxwfDxwPJ6IL5KqEXs45hmHAGs88F0oVcs1kqe3dLYrir4KzMPSxley0pBGdYQhtEqERjqeDdh0U2kCkBXImGMs4dLz/+J6wG6kOUknknFiWmZwWvIXeO4IVnBG6YDFSCEYI1uBMhTyTU6bkBFUJf7qgDG3HwwTWUEsB1CmzVgjRM+46plnvYRcD/TBiseSisxGc6xG0s8nWQldGamno+qJTCbGWbr/DdpmnpwOSC+PoSEmn9V1lOI1oL39VohxTKzkt2OAYOo/dd/gYtFUu7nRiXNczjjtCpy2csXf0u4jvdRaLcfqcCEYjfOvxzmqLNR5jUKZDaykYSm0zIkJHiD06ldApuNCAj5Fh/x7no86s6KJmeUOH8QGsJWUgxDPgTvCtdmERa1uJthK7iu13dMtCP86kNPP582dqNSxLIoSkdsFVfMOUCb4Z/va+r0HgWReblgluoLv2mWI+rt9x00YRq4ld+WjsxgG42AVYO7VexxeteqLW62Bnm1led/yq3nwRmL0tckYMXGeBr/T815MGL+SbHYBlyZRSccYz9ju62DHNMznPOPGkRZimI6f5yPH4xDQdWdLEON7x7l6IHdjigYLYAla5vM26SFaNUnCWWg1OtDd4vXTTPL01u756SLBmCF4u1xrlNjgFq1GsVeulq3d3oRuGC62vAps4K/2L8VzlYqyeG9/1s9WYPjuzV4zky23Wh3n1Nq9ZDC/y7Om+2tmG2raR96y/iyjfFbweTb+Wqn8t3bU938uLsR2QtO5br6c53i8+f2sd1nO5rMlL2Z6jyPbYr2VW3tjnVbrtFSfj/L/XpYjB4Km2TQx0uk/TC6bC/sf/wMPPD8xTQeYDyVbm+cTDkqlLYjA7dv2OvosghWWekKrteHmupFywRmlVndAQzpVlWZT3P+zpup4swjB2fPjhO3Z3A8YUdQJ27uK0F2noeVV+fd8R/R2UzJdPnzg+HclzAgwx9Ep41UhMrDe43uG93rdpUVxBFt3fUk5kGlCvBQ0pZ3KtzFJ5skIXAkWU0XBqVMhGDDEEUqo4F7i7v+e//ON/R7zlmBPTcmJeZg7HJ2opRCuUxwOyLEjNdN6SU4aacT4wz08cjuk8XKnrPKVqi+FxXrRU4SwUQbLqD+egHwPDvoMgYBxd7BnGkRA0U2FtQEzgtFRyyjhr8MaS0kxZJpCKtHbKOAzsQqCGX0CE7777jtPpwOnpAYOmnmMb9CRZszveKPGOs2pkfR9wa5p/UD576yL9uGN/1xwACy5autHjIuQ8UyjYYDHikNDS4M4yxIGSs9b0rcH6QBc6rO9IxeC7kd3+HusDOAEHPjj6YSTEPdbFNlhKMztidHpgXd9tH5SUB4NUR22pbmlOAKjeDL7Hx0zoMzUnvO9YlgmphZwSJc2It43d0mOtp26o11eGvfW1Vc65Zks2aXV9aW0DDG7e4RbgmbMOKM0mbAz2anAFlBtw1XOsSmyTHTxHo2edUGtV0iS2ZdPVkXgZxLxWDl0jfv38eYCzBdC/vt9fk292AHLOjarRn/EAeqN0JGnXwCCSM18+fyLlxDxN3L97z/x95uOHym53p2Aik+j6PdYUlvmEwSnRCVZnKVsF1jivbTfLsgDmTAOgBtRu2AAN5srwKohN2ixnztH+uqgKLrTOvlDqF8P0Mpq/bGM2f+dqe90WoPHvP4smt9t8DYh3fS61pbfWuharf9M2XH9pP9uDfWk5eb7fX8sRve61bh2Ar0XV2wf54uyseItt+eDFNy8vym9IYz0/7lt/eyvzsj3+Ww7Rr4lZHzTjWrRSqHSIGRGX+PB3/4kyC96P5KdfkHQiffkZOWj57HQ88uVxZhwi9/s947CDnJino/ZyV5A2dTPnSs6FeU48Hg7E2IGgg14M9GOHsRqx5nJiuI/0safve0qpmFSYcuJ0mrQeXzokZw6PXzg+PWk9uwoOR55mqAYrkEtmmhZSEqwPxBjJVR12UwFnSSKYUrHWErqO/TCwLAs5J5BKmSempAx5LrQ+bqtlwWjVaOA9u3Hk3d0d7374iB17UtVBObkmptOJdDxw+NtfOT1+4fD4oEQ8M0pzG8F2AZMU7DUv2vompjCOPYP0zFmHtZAEyWC805JJdJhoGYd7jHHE0BPioINfXMT7SDVeQYRF9YsRgRRwKWCk0vnA08MjOSf6seeHXaQivLt7xzjv+PKzQ9KCsZY+RgC6ScF1zltSyfTeqOPRd9joGHY7hv2eggMb6PuBbuj0fbIVFx1x8PT7yJJmUp4Ro3XyIEoVHJxOmzSlYKWCU6bDftgTh50OUYoj/X6PGNuQ9BUbYOhHcnWAEgGtUXgVpcMuoBkDp3MOpKL4EmnsqtCAfKaFI0Y7E9qgoPcfIvN05OnpgZwT8zzjgsX5Qdl8DazEOHZN/1+/ti1DZ8/vtJEWAtnN9ldBjLRMQG0ZzMql/XsbMF168rfYoteCoS33i5aUt0h9XujDVdG9qp++oofOQfBXssLfIt/sADjU05VcmNJR03jW6bSjLHT7qMM0nKXUyvHpiZ+A4/HE0+OR6XDij3/8E+O4x7pKyZ5lglItLnaK4BTRiRG2EX1giD6cL7S2PmJjRFM/slL8KjfyirxUtHZL7ZwXdTVKsHqO1hqdxCTbv3Fe0PaMv7wP5kwZcfXx5SasN/bXjeVbYmzLWhglUNI0lZwdHy37NEDl5sGV9iArScrFs7zQD2/LKa9Hylsv8nn0/zUDub5U9ey1vkJixAbMeJW0WL1ue74P27V7nt5/3Zg/B++8fo6vlRC2Hroxa6pxs5Gw8fCfZ2CkwSKcZj8EEN+ueaRawdy/48PfG3y8Iz38zOnLTyxmYDc7kC8ke0LSwlKEUypYXzEFpiQ4PMbR+umFtOhgmbRkxbFkwRWH945aK58/f2bOE+8+7tjf9QiFGDxI0syCAFRKWZAqHA4zx6cnHj8/4sQyDgM1FZYptcEmGiXXnM8lCamVUnWqm3NO+7V9IGBYUiVVnXw29B1d8NRSyGlRQ00943CsVwZRZf40dFHIGNKy8M///D/5rz984McfvmeuC9Uaui6wLDOHh184ves5Pn7i57/9K4fHzywng6kZbVZzkEXPPQkhOny1jLsBH3seHg4UAzZ7Qu2JfYeJ2kMeYs9+/w7juzbsTFv4MG0aqtM59RoIaetfVwuuTXvrQuAufeDp6YnYBbxxPB0PCBDHPR/HSJpmpBYd6JMX7BCUbjdYukY5PNztuftwz7Af6fpBwYPGQyMhMs6rprGC7Tx0gWSEGgdM6MFYHA5rIs53eB8bwZIndpHQR0KMWB/BqIMTuhHrggISKY2IqGJiwBbfdOr6Fps2QXfNUrYaO8DK3IjVAZuszK0arjljtDzbIAhGBOsCPijVr7ROCLFgvceu3V2rAW9v34r/9t43Y75G8SrurBfc+Z02dmMH1ohyW14QDb6UqlmdHFnrCMZeeP+NAhIv2Whz5oFZycHqmsld9VKbH7NaiCss1wtlpe+pbH6/BibqTz3+/2UHYFkWpYE0hmmaKKUQYyQGJfuZjydSrbg1tWYNp4PW+J4eHpmOR3Ja+Ls//Xt2e8vxUHF2JsQRYxzVOIqx5/pZMdoyqHW4gVor2RRFzJayMRi6XaPiAgRjr1Hk5xruBu1vzgr+efngkjiCLXXj9f5kNRRvrvvZ1XuRRbicz5b9ifO2amdXA33JAlx+2o0TslIW14uRlAsQ8ny+G+dkBbGsHuh1yunlBX2tdrXZqNXdrrffrtPXEg+/Buy7voevn9fWqXlLnt+D7Tpc7evFMeTte20EDSMLK4BIB4UEjBsRb0lpwgzf4+8rxvYs2RPGxO4dGOkI+0p0hpJmDo9f+PTlCW+FXddjq7Ccjpfoo5W2tGXKKvmLcXjrMGKY0sTx6Yl+tLx73yvvgKhjXsqCwTVHulBaN8+K1jcFTC2YKvQh4H3keFhYygkLjH1snQuZnBfMWpYwSrrjjUL285wVFDxNxBB0PSVDA9VKLaS8EIIOVEmpqJGtQiqZ6fER/3kgpYT3liKBRMYESx96rL+n64T9h56wDzw9jEyHR6QoLW9eFlKaMQaCD8TYKeuh9bgQ2X/3EeODqldnGfY7XAyN1ykQuhHne6ztoOqgISMBFyLFGsQ5QvCUksjzhDMQnc6Dz/NEFwMlZyUL8o5Pn34mZwU9TscT8+mkpFB5YT5NOhe+9bvHGBAr9HcD3TjiopYDnA8gF9BebXTpa+bCh8BxesJ4T9f1WN/jXYd1Hc72OK9zB3zQc3deHTftc9d+eec7ZWskNd55pSIqFWwIyDoqt014VWO/iaoNOjfCtPKr0+ehNNIpWqxtaRz73iPikJKIsccYSyqzkh85QxKQXLBe2rPjOKvHti9jVlBf+4+tjljHbJuzztc4YaPDVuf+vM3lWrbW4LzPtfYObS02+psLZgCagyJy1ltmXS9e6tqX+u9loPLyd8PzjqffEnD+Bh4Ap4xKxuJcJs06V3ps9bGHx0eq0dKZWGXAs0vBRUcNmYfPCgvJKfHhwx8Yhnu64Z6+GnKphFrxtbaHZj0t5YE2NmDtysR14UOXWliN/tk7qpdIdTXwzQVtN259gPUc6ya63QLU7Np7dL0KV78pWZE+ztt78zxtDhej+a0354IBeNuBWNfoxXmhNX5NR12j6t4y9l9zAp7Xpl6NsOXig57XfY36N7u7rMFln5fMwnNWxsvxr4GAr5/DS0fqeu23+3p57bK+nS+v7XwRr80xUGyJsqxopVBEoxuLBRPBGBYRrDHM9FoWiHtc/4FuFC0N1BnyQloWirG4OBCsIBbmeWKeFWQGnEmxYlCFrr3rmSnNKGtOcy5z5vh0ZBwDtUza6VIKJS88fn7icDghteKtpQ8dY9chqTIfZ6QKfVDMgGtOojXgom/V0EpJet3OKa5gnmegUazWSk06C0CsZq2ssWfQ7zTrPATIGNEZA2AVL5B1kt3pdOIvf/kL48c7vvvTH3l/d0dByYWCG3B9wUgk3AfeHe44PH5BSqILlt3Qk+aZz58+UQ3aahi1J74f96TlMk5ZrCGMvToA1iHOk7LoRDfbU/EYmvHFUSyIM/hgMFQd2CNKKuRNZT4e8U5Jg4ZB5wv8OP0B7yKlFtKs2A0RIS0T83RUIKjVbgVjwHhD6COZoh0MQcGIXjqMrAh4rcObVpYVA/uctOvC97gw4MOIdx1IVJyKM8obL5VMwRiULMjp9YmxOkZYwHirY+vTTJXSIvymcduUxksQ1Qa0CZo5aKVKZ7zq5tYy3jwGZYdlddgN4iO4rBF1MeSaqRTmUlnqzGiDHs/SsqBrit5wNYPlnHEEDZTsxmG4vOtX6ftVF1y+ft63Bi9bwrhrfbq2G16XA9bAasVaXQPGn+ugVw3/hsDuGnR4rceey6+Xd6/lmx2Ad+/eISKtHq9DIUT0pa9SsdboVKsuMqfENM+4Wth1OyyGmjNfvnzi8HTk0/tH/vT3/5HvTEcpBusWQp/p+x0uKLOViODxWKu0nMr57LGucRJkbUWqdU0vG1bGqNVo6oRBubKRmtIXReuKprCeoynXiNCeQSfnePC8Hs+j6l+7Ab+tFGCaQb0G3j1/cJ4/EM+Pp++gudrv9lqfy695jyJbZOu1Q6I2vTbq59db+LZO1sXRslfX15J2Zw/55Uvy8nrXNTjPmdiszVugxbdk+5Iim+PIK1Mnz19Co//mQNhiWvoPVR4Y4nAP6UQxEVzEhzv64YhZKnU60buR3sNyOvLT3+Dhl584TjPRQp4mpumEpIKziuQ2xuCtb9wHrY1LtPziaIQ8GEqeOR4OGJsJMeCMZTrO/Mtff+Lx4cRu8PQxMHFk14/cDXd44zg9TmrQxVBqwRtLdkKtRWlWpY3rzQXTMEGn04kqFtcGthijrWveOZCMMeCdU2KeZUHE6/c3QKf1nlvreHh44M9//jP/9Nf/xX/7x//BP/znf6AbB1zUMkVKGWs8sQvkXST2Fofw4f09w37HcjzQ/1UJcIx1dH1PEejijlI8w+4dzjkSFeMd4h3GRWyIzLkAATERZ3u86xFx5FK0tu0BhOgNDqGkiVoLwQnvv3vP8ekBqQXfd0zzkTBqG/VPP39i//E9sQreGnKaKUtiGCLeGuY0UY2Q8ozxFpzS+9rWfpcPBZOV4MeGgLNKl1tFyLVyP4wsVajFIi7g7Q5jO2pRwqNai+Ks3JpdVHa9LE4dC7FgwpnC3axlRhEoFxd4S+O+gtGc0wyuFKAWqjEUk3S/aIsprXXOblD3Yow6sbkwp5mlNCpGp2S/xmr78JrxXHUGRnMXiM7LMNKc+E2QcaX9rgKYTQbwHKyowb66NhHg0natWfxL+/QaXGyzqiKc58woRm2jU7jWa69lV7fB09d0V9mw467b/ladZ+Tfih64yU1ucpOb3OQm/8/K1+nkbnKTm9zkJje5yf+XcnMAbnKTm9zkJjf5HcrNAbjJTW5yk5vc5HcoNwfgJje5yU1ucpPfodwcgJvc5CY3uclNfodycwBucpOb3OQmN/kdys0BuMlNbnKTm9zkdyg3B+AmN7nJTW5yk9+h3ByAm9zkJje5yU1+h/J/ABFG6UUYO95OAAAAAElFTkSuQmCC",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "#plot an image tensor\n",
        "import matplotlib.pyplot as plt\n",
        "plt.imshow(image)\n",
        "plt.title(class_names[label.numpy()])\n",
        "plt.axis(False);"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xKbIcIgckjNa"
      },
      "source": [
        "## Create preprocessing functions\n",
        "\n",
        "**we're going to be using an EfficientNet0X pretrained model from tf.keras.applications we don't need to rescale our data (these architectures have rescaling built-in).**\n",
        "\n",
        "the function needs to:\n",
        "1. Reshape our images to all the same size\n",
        "2. Convert the dtype of our image tensors from `unit8` to `float32`"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "5dAwtAEPj_qn"
      },
      "outputs": [],
      "source": [
        "# data comes in the tuple structure: (image, label)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "id": "A4hcbwNVj_tH"
      },
      "outputs": [],
      "source": [
        "# Make a function for preprocessing images\n",
        "def preprocess_img(image, label, img_shape=224):\n",
        "  \"\"\"\n",
        "  Converts image datatype from 'uint8' -> 'float32' and reshapes\n",
        "  image to [img_shape, img_shape, colour_channels]\n",
        "  \"\"\"\n",
        "\n",
        "  image= tf.image.resize(image, [img_shape, img_shape])\n",
        "  # image = image/255. # scale image values (not required with EfficientNetBX models from tf.keras.applications)\n",
        "  return tf.cast(image, tf.float32), label# return (float32_image, label) tuple"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "drajjPMbj_vg",
        "outputId": "88cd6df2-ef7b-41c7-fa66-2a0fbeb05672"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Image before preprocessing:\n",
            " [[[230 229 183]\n",
            "  [231 230 184]\n",
            "  [232 231 183]\n",
            "  ...\n",
            "  [232 233 202]\n",
            "  [229 234 204]\n",
            "  [229 236 205]]\n",
            "\n",
            " [[228 227 179]\n",
            "  [227 226 178]\n",
            "  [226 226 176]\n",
            "  ...\n",
            "  [234 235 204]\n",
            "  [232 237 207]\n",
            "  [234 241 210]]]...., \n",
            "Shape: (384, 512, 3), \n",
            "Datatype: <dtype: 'uint8'>\n",
            "\n",
            "Image after preprocessing:\n",
            " [[[229.46939 228.46939 181.7551 ]\n",
            "  [229.59184 228.94897 180.2347 ]\n",
            "  [224.14796 224.14796 171.71939]\n",
            "  ...\n",
            "  [238.21933 231.07143 200.37251]\n",
            "  [237.02545 233.38266 204.23978]\n",
            "  [230.32655 236.04091 205.68373]]\n",
            "\n",
            " [[228.80103 228.87245 174.58673]\n",
            "  [225.95409 225.95918 173.80103]\n",
            "  [226.64795 226.64795 174.21939]\n",
            "  ...\n",
            "  [238.41322 232.41322 199.95409]\n",
            "  [235.8571  233.14287 202.07143]\n",
            "  [233.04602 238.76038 206.4032 ]]]...., \n",
            "Shape: (224, 224, 3), \n",
            "Datatype: <dtype: 'float32'>\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# Preprocess a single sample image and check the outputs\n",
        "preprocessed_img= preprocess_img(image, label)[0]\n",
        "print(f\"Image before preprocessing:\\n {image[:2]}...., \\nShape: {image.shape}, \\nDatatype: {image.dtype}\\n\")\n",
        "print(f\"Image after preprocessing:\\n {preprocessed_img[:2]}...., \\nShape: {preprocessed_img.shape}, \\nDatatype: {preprocessed_img.dtype}\\n\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9PpQ8RqjpsUE"
      },
      "source": [
        "## Batch and prepare datasets"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "id": "fCry4EOPj_xd"
      },
      "outputs": [],
      "source": [
        "# Map preprocessing function to training (and parallelize)\n",
        "train_data = train_data.map(map_func=preprocess_img, num_parallel_calls=tf.data.AUTOTUNE)\n",
        "# Shuffle train_data and turn it into batches and prefetch it (load it faster)\n",
        "train_data = train_data.shuffle(buffer_size=1000).batch(batch_size=32).prefetch(buffer_size=tf.data.AUTOTUNE)\n",
        "\n",
        "# Map preprocessing function to test data\n",
        "test_data = test_data.map(map_func=preprocess_img, num_parallel_calls=tf.data.AUTOTUNE).batch(32).prefetch(tf.data.AUTOTUNE)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wTv8CCX7j_3P",
        "outputId": "432fd7da-ba24-40b8-fc07-a51a232d17b5"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(<_PrefetchDataset element_spec=(TensorSpec(shape=(None, 224, 224, 3), dtype=tf.float32, name=None), TensorSpec(shape=(None,), dtype=tf.int64, name=None))>,\n",
              " <_PrefetchDataset element_spec=(TensorSpec(shape=(None, 224, 224, 3), dtype=tf.float32, name=None), TensorSpec(shape=(None,), dtype=tf.int64, name=None))>)"
            ]
          },
          "execution_count": 20,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "train_data, test_data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HJFQUjAM3jzi"
      },
      "source": [
        "## Create modelling callbacks\n",
        "\n",
        "creating callbacks to help us while our model trains:\n",
        "* TensorBoard callback to log training results (so we can visualize them later if need be), can be imported from helper_functions\n",
        "* ModelCheckpoint callback to save our model's progress after feature extraction"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "id": "pUYJlPf-2Gxz"
      },
      "outputs": [],
      "source": [
        "# Create tensorboard callback (import from helper_functions.py)\n",
        "from helper_functions import create_tensorboard_callback\n",
        "\n",
        "# Create ModelCheckpoint callback to save a model's progress during training\n",
        "checkpoint_path = \"model_checkpoints/cp.ckpt\"\n",
        "model_checkpoint = tf.keras.callbacks.ModelCheckpoint(checkpoint_path,\n",
        "                                                      monitor=\"val_acc\",\n",
        "                                                      save_best=True,\n",
        "                                                      save_weights=True,\n",
        "                                                      )"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jmDtWVL07BDG"
      },
      "source": [
        "## Setup mixed precision training\n",
        "\n",
        "\n",
        "Mixed precision utilizes a combination of float32 and float16 data types to speed up model performance.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "id": "91AvsWME5pI1"
      },
      "outputs": [],
      "source": [
        "# Turn on mixed precision training\n",
        "import tensorflow as tf\n",
        "from tensorflow.keras import mixed_precision\n",
        "mixed_precision.set_global_policy(\"mixed_float16\") # set global data policy to mixed precision"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MGVBsp1Q5pLA",
        "outputId": "60329dec-4cf8-4f62-b844-dc31b3081164"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<Policy \"mixed_float16\">"
            ]
          },
          "execution_count": 23,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "mixed_precision.global_policy()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5FjE6oMbvohd"
      },
      "source": [
        "## Build feature extraction model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xvrL1dOw5pPM",
        "outputId": "dd4ed0cf-6f87-49c0-f168-f3154bd9540c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Downloading data from https://storage.googleapis.com/keras-applications/efficientnetb0_notop.h5\n",
            "16705208/16705208 [==============================] - 0s 0us/step\n"
          ]
        }
      ],
      "source": [
        "from tensorflow.keras import layers\n",
        "from tensorflow.keras.layers.experimental import preprocessing\n",
        "\n",
        "# Create base model\n",
        "input_shape=(224, 224, 3)\n",
        "base_model= tf.keras.applications.EfficientNetB0(include_top=False)\n",
        "base_model.trainable=False\n",
        "\n",
        "# Create functional model\n",
        "inputs= layers.Input(shape=input_shape, name=\"input_layer\")\n",
        "# EfficientNetBX models have rescaling built-in but if your model doesn't you can have a layer like below\n",
        "# x = preprocessing.Rescaling(1./255)(x)\n",
        "x= base_model(inputs, training =False)\n",
        "x= layers.GlobalAveragePooling2D()(x)\n",
        "x= layers.Dense(len(class_names))(x)\n",
        "\n",
        "outputs= layers.Activation(\"softmax\", dtype=tf.float32, name=\"softmax_float32\")(x)\n",
        "model= tf.keras.Model(inputs,outputs)\n",
        "\n",
        "# Compile the model\n",
        "model.compile(loss=\"sparse_categorical_crossentropy\",\n",
        "              optimizer=tf.keras.optimizers.Adam(),\n",
        "              metrics=[\"accuracy\"])\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hCOXG6XO5pNZ",
        "outputId": "4d0c6c9a-5948-4b5a-c522-71a018ca1df3"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"model\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " input_layer (InputLayer)    [(None, 224, 224, 3)]     0         \n",
            "                                                                 \n",
            " efficientnetb0 (Functional  (None, None, None, 1280   4049571   \n",
            " )                           )                                   \n",
            "                                                                 \n",
            " global_average_pooling2d (  (None, 1280)              0         \n",
            " GlobalAveragePooling2D)                                         \n",
            "                                                                 \n",
            " dense (Dense)               (None, 101)               129381    \n",
            "                                                                 \n",
            " softmax_float32 (Activatio  (None, 101)               0         \n",
            " n)                                                              \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 4178952 (15.94 MB)\n",
            "Trainable params: 129381 (505.39 KB)\n",
            "Non-trainable params: 4049571 (15.45 MB)\n",
            "_________________________________________________________________\n"
          ]
        }
      ],
      "source": [
        "model.summary()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5Uu7rIbk30em"
      },
      "source": [
        "## Checking which layers use mixed precision"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZM4NiKqd5pRz",
        "outputId": "befe0a46-0699-4ac3-84f1-630e28f9fac2"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "input_layer True float32 <Policy \"float32\">\n",
            "efficientnetb0 False float32 <Policy \"mixed_float16\">\n",
            "global_average_pooling2d True float32 <Policy \"mixed_float16\">\n",
            "dense True float32 <Policy \"mixed_float16\">\n",
            "softmax_float32 True float32 <Policy \"float32\">\n"
          ]
        }
      ],
      "source": [
        "for layer in model.layers:\n",
        "  print(layer.name, layer.trainable, layer.dtype, layer.dtype_policy)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-C7axpG42G0F",
        "outputId": "317ed17f-bd76-4b16-8d0e-7f938c87fc94"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "input_1 False float32 <Policy \"float32\">\n",
            "rescaling False float32 <Policy \"mixed_float16\">\n",
            "normalization False float32 <Policy \"mixed_float16\">\n",
            "rescaling_1 False float32 <Policy \"mixed_float16\">\n",
            "stem_conv_pad False float32 <Policy \"mixed_float16\">\n",
            "stem_conv False float32 <Policy \"mixed_float16\">\n",
            "stem_bn False float32 <Policy \"mixed_float16\">\n",
            "stem_activation False float32 <Policy \"mixed_float16\">\n",
            "block1a_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block1a_bn False float32 <Policy \"mixed_float16\">\n",
            "block1a_activation False float32 <Policy \"mixed_float16\">\n",
            "block1a_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block1a_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block1a_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block1a_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block1a_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block1a_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block1a_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block2a_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block2a_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block2a_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block2a_dwconv_pad False float32 <Policy \"mixed_float16\">\n",
            "block2a_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block2a_bn False float32 <Policy \"mixed_float16\">\n",
            "block2a_activation False float32 <Policy \"mixed_float16\">\n",
            "block2a_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block2a_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block2a_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block2a_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block2a_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block2a_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block2a_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block2b_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block2b_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block2b_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block2b_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block2b_bn False float32 <Policy \"mixed_float16\">\n",
            "block2b_activation False float32 <Policy \"mixed_float16\">\n",
            "block2b_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block2b_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block2b_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block2b_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block2b_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block2b_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block2b_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block2b_drop False float32 <Policy \"mixed_float16\">\n",
            "block2b_add False float32 <Policy \"mixed_float16\">\n",
            "block3a_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block3a_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block3a_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block3a_dwconv_pad False float32 <Policy \"mixed_float16\">\n",
            "block3a_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block3a_bn False float32 <Policy \"mixed_float16\">\n",
            "block3a_activation False float32 <Policy \"mixed_float16\">\n",
            "block3a_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block3a_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block3a_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block3a_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block3a_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block3a_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block3a_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block3b_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block3b_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block3b_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block3b_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block3b_bn False float32 <Policy \"mixed_float16\">\n",
            "block3b_activation False float32 <Policy \"mixed_float16\">\n",
            "block3b_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block3b_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block3b_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block3b_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block3b_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block3b_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block3b_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block3b_drop False float32 <Policy \"mixed_float16\">\n",
            "block3b_add False float32 <Policy \"mixed_float16\">\n",
            "block4a_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block4a_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block4a_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block4a_dwconv_pad False float32 <Policy \"mixed_float16\">\n",
            "block4a_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block4a_bn False float32 <Policy \"mixed_float16\">\n",
            "block4a_activation False float32 <Policy \"mixed_float16\">\n",
            "block4a_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block4a_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block4a_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block4a_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block4a_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block4a_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block4a_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block4b_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block4b_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block4b_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block4b_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block4b_bn False float32 <Policy \"mixed_float16\">\n",
            "block4b_activation False float32 <Policy \"mixed_float16\">\n",
            "block4b_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block4b_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block4b_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block4b_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block4b_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block4b_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block4b_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block4b_drop False float32 <Policy \"mixed_float16\">\n",
            "block4b_add False float32 <Policy \"mixed_float16\">\n",
            "block4c_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block4c_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block4c_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block4c_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block4c_bn False float32 <Policy \"mixed_float16\">\n",
            "block4c_activation False float32 <Policy \"mixed_float16\">\n",
            "block4c_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block4c_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block4c_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block4c_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block4c_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block4c_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block4c_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block4c_drop False float32 <Policy \"mixed_float16\">\n",
            "block4c_add False float32 <Policy \"mixed_float16\">\n",
            "block5a_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block5a_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block5a_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block5a_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block5a_bn False float32 <Policy \"mixed_float16\">\n",
            "block5a_activation False float32 <Policy \"mixed_float16\">\n",
            "block5a_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block5a_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block5a_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block5a_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block5a_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block5a_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block5a_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block5b_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block5b_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block5b_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block5b_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block5b_bn False float32 <Policy \"mixed_float16\">\n",
            "block5b_activation False float32 <Policy \"mixed_float16\">\n",
            "block5b_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block5b_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block5b_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block5b_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block5b_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block5b_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block5b_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block5b_drop False float32 <Policy \"mixed_float16\">\n",
            "block5b_add False float32 <Policy \"mixed_float16\">\n",
            "block5c_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block5c_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block5c_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block5c_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block5c_bn False float32 <Policy \"mixed_float16\">\n",
            "block5c_activation False float32 <Policy \"mixed_float16\">\n",
            "block5c_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block5c_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block5c_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block5c_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block5c_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block5c_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block5c_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block5c_drop False float32 <Policy \"mixed_float16\">\n",
            "block5c_add False float32 <Policy \"mixed_float16\">\n",
            "block6a_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block6a_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block6a_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block6a_dwconv_pad False float32 <Policy \"mixed_float16\">\n",
            "block6a_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block6a_bn False float32 <Policy \"mixed_float16\">\n",
            "block6a_activation False float32 <Policy \"mixed_float16\">\n",
            "block6a_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block6a_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block6a_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block6a_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block6a_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block6a_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block6a_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block6b_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block6b_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block6b_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block6b_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block6b_bn False float32 <Policy \"mixed_float16\">\n",
            "block6b_activation False float32 <Policy \"mixed_float16\">\n",
            "block6b_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block6b_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block6b_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block6b_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block6b_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block6b_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block6b_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block6b_drop False float32 <Policy \"mixed_float16\">\n",
            "block6b_add False float32 <Policy \"mixed_float16\">\n",
            "block6c_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block6c_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block6c_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block6c_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block6c_bn False float32 <Policy \"mixed_float16\">\n",
            "block6c_activation False float32 <Policy \"mixed_float16\">\n",
            "block6c_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block6c_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block6c_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block6c_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block6c_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block6c_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block6c_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block6c_drop False float32 <Policy \"mixed_float16\">\n",
            "block6c_add False float32 <Policy \"mixed_float16\">\n",
            "block6d_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block6d_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block6d_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block6d_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block6d_bn False float32 <Policy \"mixed_float16\">\n",
            "block6d_activation False float32 <Policy \"mixed_float16\">\n",
            "block6d_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block6d_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block6d_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block6d_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block6d_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block6d_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block6d_project_bn False float32 <Policy \"mixed_float16\">\n",
            "block6d_drop False float32 <Policy \"mixed_float16\">\n",
            "block6d_add False float32 <Policy \"mixed_float16\">\n",
            "block7a_expand_conv False float32 <Policy \"mixed_float16\">\n",
            "block7a_expand_bn False float32 <Policy \"mixed_float16\">\n",
            "block7a_expand_activation False float32 <Policy \"mixed_float16\">\n",
            "block7a_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block7a_bn False float32 <Policy \"mixed_float16\">\n",
            "block7a_activation False float32 <Policy \"mixed_float16\">\n",
            "block7a_se_squeeze False float32 <Policy \"mixed_float16\">\n",
            "block7a_se_reshape False float32 <Policy \"mixed_float16\">\n",
            "block7a_se_reduce False float32 <Policy \"mixed_float16\">\n",
            "block7a_se_expand False float32 <Policy \"mixed_float16\">\n",
            "block7a_se_excite False float32 <Policy \"mixed_float16\">\n",
            "block7a_project_conv False float32 <Policy \"mixed_float16\">\n",
            "block7a_project_bn False float32 <Policy \"mixed_float16\">\n",
            "top_conv False float32 <Policy \"mixed_float16\">\n",
            "top_bn False float32 <Policy \"mixed_float16\">\n",
            "top_activation False float32 <Policy \"mixed_float16\">\n"
          ]
        }
      ],
      "source": [
        "#further checking which induvidual layers in the base model(efficientnetB0) uses mixed precision\n",
        "for layer in model.layers[1].layers:\n",
        "  print(layer.name, layer.trainable, layer.dtype, layer.dtype_policy)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1agq4Bqh5QVD"
      },
      "source": [
        "## Fit the feature extraction model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UWVO7huwuMQY",
        "outputId": "97046b3e-31e2-40a1-ea39-d37123cda19d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Saving TensorBoard log files to: training_logs/efficientnetB0_101_food_classes/20230831-162614\n",
            "Epoch 1/3\n",
            "2368/2368 [==============================] - 249s 97ms/step - loss: 1.7162 - accuracy: 0.5824 - val_loss: 1.1231 - val_accuracy: 0.7063\n",
            "Epoch 2/3\n",
            "2368/2368 [==============================] - 220s 91ms/step - loss: 1.1995 - accuracy: 0.6888 - val_loss: 1.0242 - val_accuracy: 0.7169\n",
            "Epoch 3/3\n",
            "2368/2368 [==============================] - 216s 90ms/step - loss: 1.0545 - accuracy: 0.7234 - val_loss: 0.9937 - val_accuracy: 0.7267\n"
          ]
        }
      ],
      "source": [
        "# Fit the feature extraction model with callbacks\n",
        "history_101_food_classes_feature_extract = model.fit(train_data,\n",
        "                                                      epochs=3,\n",
        "                                                      steps_per_epoch=(len(train_data)),\n",
        "                                                      validation_data=test_data,\n",
        "                                                      validation_steps=int(0.15* len(test_data)),\n",
        "                                                      callbacks=[create_tensorboard_callback(dir_name=\"training_logs\",\n",
        "                                                                                            experiment_name=\"efficientnetB0_101_food_classes\"),\n",
        "                                                      model_checkpoint])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rfiZOiJKVnOB",
        "outputId": "69cc58d9-b545-4ef2-9316-c87d160d3346"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "790/790 [==============================] - 52s 66ms/step - loss: 1.0017 - accuracy: 0.7272\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "[1.0017063617706299, 0.7272475361824036]"
            ]
          },
          "execution_count": 29,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Evaluate model on whole test dataset\n",
        "results_feature_extract_model = model.evaluate(test_data)\n",
        "results_feature_extract_model"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_2zT65B8zt1d"
      },
      "source": [
        "## Load and evaluate checkpoint weights"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rxfFOCJfVnSm",
        "outputId": "3e3968d8-c7b4-4bd8-ee32-84efec98e295"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "790/790 [==============================] - 55s 66ms/step - loss: 1.0017 - accuracy: 0.7272\n"
          ]
        }
      ],
      "source": [
        "# 1. Create a function to recreate the original model\n",
        "def create_model():\n",
        "  # Create base model\n",
        "  input_shape = (224, 224, 3)\n",
        "  base_model = tf.keras.applications.efficientnet.EfficientNetB0(include_top=False)\n",
        "  base_model.trainable = False # freeze base model layers\n",
        "\n",
        "  # Create Functional model\n",
        "  inputs = layers.Input(shape=input_shape, name=\"input_layer\")\n",
        "  # Note: EfficientNetBX models have rescaling built-in but if your model didn't you could have a layer like below\n",
        "  # x = layers.Rescaling(1./255)(x)\n",
        "  x = base_model(inputs, training=False) # set base_model to inference mode only\n",
        "  x = layers.GlobalAveragePooling2D(name=\"pooling_layer\")(x)\n",
        "  x = layers.Dense(len(class_names))(x) # want one output neuron per class\n",
        "  # Separate activation of output layer so we can output float32 activations\n",
        "  outputs = layers.Activation(\"softmax\", dtype=tf.float32, name=\"softmax_float32\")(x)\n",
        "  model = tf.keras.Model(inputs, outputs)\n",
        "\n",
        "  return model\n",
        "\n",
        "# 2. Create and compile a new version of the original model (new weights)\n",
        "created_model = create_model()\n",
        "created_model.compile(loss=\"sparse_categorical_crossentropy\",\n",
        "                      optimizer=tf.keras.optimizers.Adam(),\n",
        "                      metrics=[\"accuracy\"])\n",
        "\n",
        "# 3. Load the saved weights\n",
        "created_model.load_weights(checkpoint_path)\n",
        "\n",
        "# 4. Evaluate the model with loaded weights\n",
        "results_created_model_with_loaded_weights = created_model.evaluate(test_data)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PxSY4Ygb3ox-",
        "outputId": "7b6d6a32-e574-4363-ea5a-a52d30a1b6ef"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 31,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# 5. Loaded checkpoint weights should return very similar results to checkpoint weights prior to saving\n",
        "import numpy as np\n",
        "np.isclose(results_feature_extract_model, results_created_model_with_loaded_weights).all()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uwfoujnR3o0L",
        "outputId": "a7ce1dec-0d59-4020-dcdb-38a293cb8079"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "input_2 False float32 <Policy \"float32\">\n",
            "rescaling_2 False float32 <Policy \"mixed_float16\">\n",
            "normalization_1 False float32 <Policy \"mixed_float16\">\n",
            "rescaling_3 False float32 <Policy \"mixed_float16\">\n",
            "stem_conv_pad False float32 <Policy \"mixed_float16\">\n",
            "stem_conv False float32 <Policy \"mixed_float16\">\n",
            "stem_bn False float32 <Policy \"mixed_float16\">\n",
            "stem_activation False float32 <Policy \"mixed_float16\">\n",
            "block1a_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block1a_bn False float32 <Policy \"mixed_float16\">\n"
          ]
        }
      ],
      "source": [
        "# Check the layers in the base model and see what dtype policy they're using\n",
        "for layer in created_model.layers[1].layers[:10]: #only displaying the first 10\n",
        "  print(layer.name, layer.trainable, layer.dtype, layer.dtype_policy)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ic3GBqLf505i"
      },
      "source": [
        "## Save the whole model to file"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "id": "ZIgdC0jl5zY3"
      },
      "outputs": [],
      "source": [
        "## Saving model to Google Drive\n",
        "\n",
        "# Create save path to drive\n",
        "save_dir = \"/content/drive/MyDrive/Food Vision/efficientnetb0_feature_extract_model_mixed_precision/\"\n",
        "# os.makedirs(save_dir) # Make directory if it doesn't exist\n",
        "\n",
        "# Save model\n",
        "model.save(save_dir)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 34,
      "metadata": {
        "id": "9qeOmCDL3pDO"
      },
      "outputs": [],
      "source": [
        "# Load model previously saved above\n",
        "loaded_saved_model = tf.keras.models.load_model(save_dir)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 35,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I2DKrLlT3pFt",
        "outputId": "1145f78d-3a1f-4598-a9a8-4c9d80efe5f4"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "input_1 True float32 <Policy \"float32\">\n",
            "rescaling False float32 <Policy \"mixed_float16\">\n",
            "normalization False float32 <Policy \"mixed_float16\">\n",
            "rescaling_1 False float32 <Policy \"mixed_float16\">\n",
            "stem_conv_pad False float32 <Policy \"mixed_float16\">\n",
            "stem_conv False float32 <Policy \"mixed_float16\">\n",
            "stem_bn False float32 <Policy \"mixed_float16\">\n",
            "stem_activation False float32 <Policy \"mixed_float16\">\n",
            "block1a_dwconv False float32 <Policy \"mixed_float16\">\n",
            "block1a_bn False float32 <Policy \"mixed_float16\">\n"
          ]
        }
      ],
      "source": [
        "# Check the layers in the base model and see what dtype policy they're using\n",
        "for layer in loaded_saved_model.layers[1].layers[:10]: # check only the first 10 layers to save output space\n",
        "    print(layer.name, layer.trainable, layer.dtype, layer.dtype_policy)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3wONl_UnEGlc",
        "outputId": "c4449252-0c6b-4939-cbc5-308622a828a3"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "790/790 [==============================] - 56s 67ms/step - loss: 1.0017 - accuracy: 0.7272\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "[1.0017058849334717, 0.7272475361824036]"
            ]
          },
          "execution_count": 36,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Check loaded model performance (this should be the same as results_feature_extract_model)\n",
        "results_loaded_saved_model = loaded_saved_model.evaluate(test_data)\n",
        "results_loaded_saved_model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-YO7Y4_hEGoS",
        "outputId": "14e20f30-224c-40a7-b616-fd4f40ccbc61"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 37,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#Comparing results of original and loaded saved model\n",
        "import numpy as np\n",
        "np.isclose(results_feature_extract_model, results_loaded_saved_model).all()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fv6A0D8fFeey"
      },
      "source": [
        "## Fine tuning EfficientNetB0"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G-QP3DScHDpF"
      },
      "source": [
        "Now we'll download the feature extraction model begin fine tuning it.(same as the feature extrcation model above)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 38,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YHRYQfcgEGq6",
        "outputId": "9cc6d3ea-272b-4d88-b84d-fea83a422ed7"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "--2023-08-31 16:42:30--  https://storage.googleapis.com/ztm_tf_course/food_vision/07_efficientnetb0_feature_extract_model_mixed_precision.zip\n",
            "Resolving storage.googleapis.com (storage.googleapis.com)... 74.125.135.128, 74.125.142.128, 173.194.202.128, ...\n",
            "Connecting to storage.googleapis.com (storage.googleapis.com)|74.125.135.128|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 16976857 (16M) [application/zip]\n",
            "Saving to: ‘07_efficientnetb0_feature_extract_model_mixed_precision.zip’\n",
            "\n",
            "07_efficientnetb0_f 100%[===================>]  16.19M  --.-KB/s    in 0.1s    \n",
            "\n",
            "2023-08-31 16:42:31 (120 MB/s) - ‘07_efficientnetb0_feature_extract_model_mixed_precision.zip’ saved [16976857/16976857]\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# Download the saved model from Google Storage\n",
        "!wget https://storage.googleapis.com/ztm_tf_course/food_vision/07_efficientnetb0_feature_extract_model_mixed_precision.zip"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 39,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WLY7Oz49EGtp",
        "outputId": "da3da44f-0a38-4989-ae0f-4661242ae5a7"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Archive:  07_efficientnetb0_feature_extract_model_mixed_precision.zip\n",
            "   creating: downloaded_gs_model/07_efficientnetb0_feature_extract_model_mixed_precision/\n",
            "   creating: downloaded_gs_model/07_efficientnetb0_feature_extract_model_mixed_precision/variables/\n",
            "  inflating: downloaded_gs_model/07_efficientnetb0_feature_extract_model_mixed_precision/variables/variables.data-00000-of-00001  \n",
            "  inflating: downloaded_gs_model/07_efficientnetb0_feature_extract_model_mixed_precision/variables/variables.index  \n",
            "  inflating: downloaded_gs_model/07_efficientnetb0_feature_extract_model_mixed_precision/saved_model.pb  \n",
            "   creating: downloaded_gs_model/07_efficientnetb0_feature_extract_model_mixed_precision/assets/\n"
          ]
        }
      ],
      "source": [
        "# Unzip the SavedModel downloaded from Google Stroage\n",
        "!mkdir downloaded_gs_model # create new dir to store downloaded feature extraction model\n",
        "!unzip 07_efficientnetb0_feature_extract_model_mixed_precision.zip -d downloaded_gs_model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 40,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bz_v1EfZEGwC",
        "outputId": "135bee15-41ff-4bf3-d562-f0cafb790d2a"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:SavedModel saved prior to TF 2.5 detected when loading Keras model. Please ensure that you are saving the model with model.save() or tf.keras.models.save_model(), *NOT* tf.saved_model.save(). To confirm, there should be a file named \"keras_metadata.pb\" in the SavedModel directory.\n"
          ]
        }
      ],
      "source": [
        "# Load and evaluate downloaded gs model\n",
        "import absl.logging\n",
        "absl.logging.set_verbosity(absl.logging.ERROR)\n",
        "loaded_gs_model = tf.keras.models.load_model(\"downloaded_gs_model/07_efficientnetb0_feature_extract_model_mixed_precision\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 41,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ED_SAjUgQbKw",
        "outputId": "281e2643-753a-4192-b992-3228de091b0b"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"model\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " input_layer (InputLayer)    [(None, 224, 224, 3)]     0         \n",
            "                                                                 \n",
            " efficientnetb0 (Functional  (None, None, None, 1280   4049571   \n",
            " )                           )                                   \n",
            "                                                                 \n",
            " pooling_layer (GlobalAvera  (None, 1280)              0         \n",
            " gePooling2D)                                                    \n",
            "                                                                 \n",
            " dense (Dense)               (None, 101)               129381    \n",
            "                                                                 \n",
            " softmax_float32 (Activatio  (None, 101)               0         \n",
            " n)                                                              \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 4178952 (15.94 MB)\n",
            "Trainable params: 129381 (505.39 KB)\n",
            "Non-trainable params: 4049571 (15.45 MB)\n",
            "_________________________________________________________________\n"
          ]
        }
      ],
      "source": [
        "# Get a summary of our downloaded model\n",
        "loaded_gs_model.summary()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 42,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PD6LW9USQbNC",
        "outputId": "f253e555-2a2a-4556-cd24-33b1ad3db3ae"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "790/790 [==============================] - 59s 70ms/step - loss: 1.0881 - accuracy: 0.7066\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "[1.0880995988845825, 0.7066138386726379]"
            ]
          },
          "execution_count": 42,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# How does the loaded model perform?\n",
        "results_loaded_gs_model = loaded_gs_model.evaluate(test_data)\n",
        "results_loaded_gs_model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 43,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LuG5syPmQbPQ",
        "outputId": "c63933c8-aa78-4b71-8055-39b8d7cfb1b9"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "input_layer True float32 <Policy \"float32\">\n",
            "efficientnetb0 True float32 <Policy \"mixed_float16\">\n",
            "pooling_layer True float32 <Policy \"mixed_float16\">\n",
            "dense True float32 <Policy \"mixed_float16\">\n",
            "softmax_float32 True float32 <Policy \"float32\">\n"
          ]
        }
      ],
      "source": [
        "#Unfreezing all layers to begin fine tuning\n",
        "for layer in loaded_gs_model.layers:\n",
        "  layer.trainable = True#setting all layers to trainable\n",
        "  print(layer.name, layer.trainable, layer.dtype, layer.dtype_policy)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 44,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ak_b9bU7QbRo",
        "outputId": "48243687-18cd-4545-b44b-4b1f6b5fd520"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "input_1 True float32 <Policy \"float32\">\n",
            "rescaling True float32 <Policy \"mixed_float16\">\n",
            "normalization True float32 <Policy \"float32\">\n",
            "stem_conv_pad True float32 <Policy \"mixed_float16\">\n",
            "stem_conv True float32 <Policy \"mixed_float16\">\n",
            "stem_bn True float32 <Policy \"mixed_float16\">\n",
            "stem_activation True float32 <Policy \"mixed_float16\">\n",
            "block1a_dwconv True float32 <Policy \"mixed_float16\">\n",
            "block1a_bn True float32 <Policy \"mixed_float16\">\n",
            "block1a_activation True float32 <Policy \"mixed_float16\">\n"
          ]
        }
      ],
      "source": [
        "# Check the layers in the base model(EfficientNetB0) and see what dtype policy they're using\n",
        "for layer in loaded_gs_model.layers[1].layers[:10]:\n",
        "    print(layer.name, layer.trainable, layer.dtype, layer.dtype_policy)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SfiOv2ieSPvA"
      },
      "source": [
        "### Setting up EarlyStopping,  ModelCheckpoint and ReduceLROnPlateau callbacks."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 45,
      "metadata": {
        "id": "oW_yOJ31QbTv"
      },
      "outputs": [],
      "source": [
        "early_stopping = tf.keras.callbacks.EarlyStopping(monitor=\"val_loss\",\n",
        "                                                  patience=3 # if val loss decreases for 3 epochs in a row, stop training\n",
        "                                                  )\n",
        "\n",
        "checkpoint_path = \"fine_tune_checkpoints/\"\n",
        "model_checkpoint = tf.keras.callbacks.ModelCheckpoint(checkpoint_path,\n",
        "                                                      save_best=True,\n",
        "                                                      monitor=\"val_loss\"\n",
        "                                                      )\n",
        "reduce_lr = tf.keras.callbacks.ReduceLROnPlateau(monitor=\"val_loss\",\n",
        "                                                 factor=0.2,# multiply the learning rate by 0.2 (reduce by 5x)\n",
        "                                                 patience=2,\n",
        "                                                 verbose=1, # print out when learning rate goes down\n",
        "                                                 min_lr=1e-7\n",
        "                                                )"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 46,
      "metadata": {
        "id": "SvhaAoE5EG26"
      },
      "outputs": [],
      "source": [
        "# Compile the model\n",
        "loaded_gs_model.compile(loss=\"sparse_categorical_crossentropy\",# sparse_categorical_crossentropy for labels that are not one-hot encoded\n",
        "                        optimizer=tf.keras.optimizers.Adam(0.0001),# 10x lower learning rate than the default since fine tuning\n",
        "                        metrics=[\"accuracy\"]\n",
        "                        )"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 47,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zNKq37l0EG5Z",
        "outputId": "85c50513-fc6d-46a4-86cb-1786fdb34cd6"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Saving TensorBoard log files to: training_logs/efficientb0_101_classes_all_data_fine_tuning/20230831-164410\n",
            "Epoch 1/100\n",
            "2368/2368 [==============================] - 500s 185ms/step - loss: 0.9235 - accuracy: 0.7509 - val_loss: 0.8219 - val_accuracy: 0.7696 - lr: 1.0000e-04\n",
            "Epoch 2/100\n",
            "2368/2368 [==============================] - 445s 187ms/step - loss: 0.5795 - accuracy: 0.8409 - val_loss: 0.7620 - val_accuracy: 0.7860 - lr: 1.0000e-04\n",
            "Epoch 3/100\n",
            "2368/2368 [==============================] - 433s 182ms/step - loss: 0.3292 - accuracy: 0.9072 - val_loss: 0.8512 - val_accuracy: 0.7812 - lr: 1.0000e-04\n",
            "Epoch 4/100\n",
            "2368/2368 [==============================] - ETA: 0s - loss: 0.1735 - accuracy: 0.9478\n",
            "Epoch 4: ReduceLROnPlateau reducing learning rate to 1.9999999494757503e-05.\n",
            "2368/2368 [==============================] - 444s 187ms/step - loss: 0.1735 - accuracy: 0.9478 - val_loss: 0.9088 - val_accuracy: 0.7958 - lr: 1.0000e-04\n",
            "Epoch 5/100\n",
            "2368/2368 [==============================] - 436s 183ms/step - loss: 0.0366 - accuracy: 0.9912 - val_loss: 1.0257 - val_accuracy: 0.8064 - lr: 2.0000e-05\n"
          ]
        }
      ],
      "source": [
        "# Starting to fine-tune all layers\n",
        "history_101_food_classes_all_data_fine_tune = loaded_gs_model.fit(train_data,\n",
        "                                                                  epochs=100,\n",
        "                                                                  steps_per_epoch=len(train_data),\n",
        "                                                                  validation_data=test_data,\n",
        "                                                                  validation_steps=int(0.15* len(test_data)),\n",
        "                                                                  callbacks=[create_tensorboard_callback(\"training_logs\", \"efficientb0_101_classes_all_data_fine_tuning\"),\n",
        "                                                                             model_checkpoint, # save only the best model during training\n",
        "                                                                             early_stopping,# stop model after 3 epochs of no improvements\n",
        "                                                                             reduce_lr]) # reduce the learning rate after X epochs of no improvements                                                                            ]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 48,
      "metadata": {
        "id": "QrlhiqZg3pH7"
      },
      "outputs": [],
      "source": [
        "# Save model to Google Drive\n",
        "loaded_gs_model.save(\"/content/drive/MyDrive/Food Vision/efficientnetb0_fine_tuned_101_classes_mixed_precision/\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bgbV2gkY0CnT"
      },
      "source": [
        "## Download fine-tuned model from Google Storage"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 49,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Fmys65kRzafZ",
        "outputId": "4369b4ad-b157-4052-9eaa-d888d2572a5a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "--2023-08-31 17:22:40--  https://storage.googleapis.com/ztm_tf_course/food_vision/07_efficientnetb0_fine_tuned_101_classes_mixed_precision.zip\n",
            "Resolving storage.googleapis.com (storage.googleapis.com)... 142.250.107.128, 74.125.20.128, 108.177.98.128, ...\n",
            "Connecting to storage.googleapis.com (storage.googleapis.com)|142.250.107.128|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 46790356 (45M) [application/zip]\n",
            "Saving to: ‘07_efficientnetb0_fine_tuned_101_classes_mixed_precision.zip’\n",
            "\n",
            "07_efficientnetb0_f 100%[===================>]  44.62M   146MB/s    in 0.3s    \n",
            "\n",
            "2023-08-31 17:22:41 (146 MB/s) - ‘07_efficientnetb0_fine_tuned_101_classes_mixed_precision.zip’ saved [46790356/46790356]\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# Download and evaluate fine-tuned model from Google Storage\n",
        "!wget https://storage.googleapis.com/ztm_tf_course/food_vision/07_efficientnetb0_fine_tuned_101_classes_mixed_precision.zip"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 50,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "431JrzM-3pKN",
        "outputId": "3bf5da1b-0813-4f19-a531-5c3a69074b0b"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Archive:  07_efficientnetb0_fine_tuned_101_classes_mixed_precision.zip\n",
            "   creating: downloaded_fine_tuned_gs_model/07_efficientnetb0_fine_tuned_101_classes_mixed_precision/\n",
            "   creating: downloaded_fine_tuned_gs_model/07_efficientnetb0_fine_tuned_101_classes_mixed_precision/variables/\n",
            "  inflating: downloaded_fine_tuned_gs_model/07_efficientnetb0_fine_tuned_101_classes_mixed_precision/variables/variables.data-00000-of-00001  \n",
            "  inflating: downloaded_fine_tuned_gs_model/07_efficientnetb0_fine_tuned_101_classes_mixed_precision/variables/variables.index  \n",
            "  inflating: downloaded_fine_tuned_gs_model/07_efficientnetb0_fine_tuned_101_classes_mixed_precision/saved_model.pb  \n",
            "   creating: downloaded_fine_tuned_gs_model/07_efficientnetb0_fine_tuned_101_classes_mixed_precision/assets/\n"
          ]
        }
      ],
      "source": [
        "# Unzip fine-tuned model\n",
        "!mkdir downloaded_fine_tuned_gs_model # create separate directory for fine-tuned model downloaded from Google Storage\n",
        "!unzip 07_efficientnetb0_fine_tuned_101_classes_mixed_precision -d downloaded_fine_tuned_gs_model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 51,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bdNb8ncsgboc",
        "outputId": "0c903b44-dd78-49be-eeab-52551146a318"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:SavedModel saved prior to TF 2.5 detected when loading Keras model. Please ensure that you are saving the model with model.save() or tf.keras.models.save_model(), *NOT* tf.saved_model.save(). To confirm, there should be a file named \"keras_metadata.pb\" in the SavedModel directory.\n"
          ]
        }
      ],
      "source": [
        "# Load in fine-tuned model from Google Storage and evaluate\n",
        "loaded_fine_tuned_gs_model = tf.keras.models.load_model(\"downloaded_fine_tuned_gs_model/07_efficientnetb0_fine_tuned_101_classes_mixed_precision\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 52,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PJ0QmLcN0csb",
        "outputId": "4f8ba050-ea11-4a9b-b3a2-e0b0fbc5bb38"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"model\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " input_layer (InputLayer)    [(None, 224, 224, 3)]     0         \n",
            "                                                                 \n",
            " efficientnetb0 (Functional  (None, None, None, 1280   4049571   \n",
            " )                           )                                   \n",
            "                                                                 \n",
            " pooling_layer (GlobalAvera  (None, 1280)              0         \n",
            " gePooling2D)                                                    \n",
            "                                                                 \n",
            " dense (Dense)               (None, 101)               129381    \n",
            "                                                                 \n",
            " softmax_float32 (Activatio  (None, 101)               0         \n",
            " n)                                                              \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 4178952 (15.94 MB)\n",
            "Trainable params: 4136929 (15.78 MB)\n",
            "Non-trainable params: 42023 (164.16 KB)\n",
            "_________________________________________________________________\n"
          ]
        }
      ],
      "source": [
        "# Get a model summary (same model architecture as above)\n",
        "loaded_fine_tuned_gs_model.summary()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 53,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WjKIbt5T0cuy",
        "outputId": "0d014d7c-e7a4-4606-d739-5f2e775d02fa"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "790/790 [==============================] - 62s 76ms/step - loss: 0.9072 - accuracy: 0.8015\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "[0.9072167873382568, 0.8014653325080872]"
            ]
          },
          "execution_count": 53,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Note: Even if you're loading in the model from Google Storage, you will still need to load the test_data variable for this cell to work\n",
        "results_downloaded_fine_tuned_gs_model = loaded_fine_tuned_gs_model.evaluate(test_data)\n",
        "results_downloaded_fine_tuned_gs_model"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "21RabhUT1JTf"
      },
      "source": [
        "## View training results on TensorBoard"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 56,
      "metadata": {
        "id": "MvUAPy7g1GUR"
      },
      "outputs": [],
      "source": [
        "# # Upload experiment results to TensorBoard\n",
        "# !tensorboard dev upload --logdir ./training_logs \\\n",
        "#   --name \"Fine-tuning EfficientNetB0 on all Food101 Data\" \\\n",
        "#   --description \"Training results for fine-tuning EfficientNetB0 on Food101 Data with learning rate 0.0001\" \\\n",
        "#   --one_shot"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nKwYkCOboPPY"
      },
      "source": [
        "## Custom predictions"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 95,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "RX-OloRioaNj",
        "outputId": "3ad04e7b-4a2b-49c1-b44e-25a9caf6aef0"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'/content/hamburger.jpeg'"
            ]
          },
          "execution_count": 95,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Get the custom food images filepaths\n",
        "custom_food_image_filename = \"/content/hamburger.jpeg\"#Change this filepath\n",
        "custom_food_image_filename"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 96,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 480
        },
        "id": "x4wvy_fdoaSO",
        "outputId": "28d1e745-fd5a-4c72-e7ed-e9bfa253a678"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "1/1 [==============================] - 0s 42ms/step\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "WARNING:matplotlib.image:Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "(-0.5, 223.5, 223.5, -0.5)"
            ]
          },
          "execution_count": 96,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Make predictions on and plot custom food images\n",
        "\n",
        "img = load_and_prep_image(custom_food_image_filename, scale=False) # don't need to scale for our EfficientNetB0 model\n",
        "pred_prob = model.predict(tf.expand_dims(img, axis=0)) # make prediction on image with shape [1, 224, 224, 3] (same shape as model was trained on)\n",
        "pred_class = class_names[pred_prob.argmax()] # get the index with the highet prediction probability\n",
        "# Plot the appropriate information\n",
        "plt.figure()\n",
        "plt.imshow(img/225.)\n",
        "plt.title(f\"pred: {pred_class}, prob: {pred_prob.max():.2f}\")\n",
        "plt.axis(False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 57,
      "metadata": {
        "id": "_7fxNzYVQbV-"
      },
      "outputs": [],
      "source": [
        "# #download files from colab\n",
        "# from google.colab import files\n",
        "\n",
        "# %cd /root/tensorflow_datasets/training_logs\n",
        "\n",
        "# !zip -r efficientb0_101_classes_all_data_fine_tuning.zip efficientb0_101_classes_all_data_fine_tuning/\n",
        "\n",
        "# files.download('efficientb0_101_classes_all_data_fine_tuning.zip')"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "gpuType": "T4",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    },
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "03d2cc91c98e410db580235cf0780928": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "04a88c825af941bea2038ee29c5a9c0f": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "FloatProgressModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_82f09c30b057455b9130cca6a171c94e",
            "max": 25250,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_1f0b8b75dd134f98ad1a7e1acd5aede0",
            "value": 25250
          }
        },
        "0939efe8947a44dc893da1580a4aeca4": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "09618ebca4fb453f9d492bced46a4a6f": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_1818748600f44388958dfd4ff50f68c5",
            "placeholder": "​",
            "style": "IPY_MODEL_0ca42c19fb9d419389d6f3dbd2696128",
            "value": "Generating splits...: 100%"
          }
        },
        "0c0fdfc54c1d485abe482c5b926566ba": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_bbd82f1a4c284870999c855e25488f2d",
            "placeholder": "​",
            "style": "IPY_MODEL_b498fdc1472747299067fab018efacf3",
            "value": " 2/2 [03:38&lt;00:00, 100.78s/ splits]"
          }
        },
        "0ca42c19fb9d419389d6f3dbd2696128": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "0d1d9ae0d830454d9df771e2fdaf2fcd": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "0d5b1b8ba1294db3ba0fb86692d9c8f9": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HBoxModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_29d22a15659945ebbcaf27a89a13b77c",
              "IPY_MODEL_b3b2f72730764745ba370a3f59e81ea8",
              "IPY_MODEL_1f759cb7ce3b424abdf382d4a0689f07"
            ],
            "layout": "IPY_MODEL_5206303bb07547fda37d806707272594"
          }
        },
        "10e55330eda8498ea164f1ecbf6580cd": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "ProgressStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "16af0423a30348158f79357694286285": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HBoxModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_d3481ca4b1d740438a1557b7f7318e7a",
              "IPY_MODEL_636e1e5b421b4b84ad282bd7b5fec7bd",
              "IPY_MODEL_363889fb320b462ea98a71ac508c9814"
            ],
            "layout": "IPY_MODEL_03d2cc91c98e410db580235cf0780928"
          }
        },
        "1818748600f44388958dfd4ff50f68c5": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "1861de3586db45acbfddb5a3aff39307": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HBoxModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_3b6bb34cd9284777a5d5a42cbbef841a",
              "IPY_MODEL_d0b1f16b3ff243ceb4a90d64c0ce3612",
              "IPY_MODEL_2000cb762d4c4a1baaa4343c95820a5d"
            ],
            "layout": "IPY_MODEL_7eb886c129d947c48defcc99783baad6"
          }
        },
        "1d2b146a59354365a10d4745912e5cc8": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_d54ccdeed2804cb68bd7a027baee1838",
            "placeholder": "​",
            "style": "IPY_MODEL_549c73a23f89453b9ce068398117d677",
            "value": " 75595/75750 [00:39&lt;00:00, 2536.70 examples/s]"
          }
        },
        "1f0b8b75dd134f98ad1a7e1acd5aede0": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "ProgressStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "1f759cb7ce3b424abdf382d4a0689f07": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_93ab551775a14d008bfdb8c67b08a664",
            "placeholder": "​",
            "style": "IPY_MODEL_ffb1e015f3e54fecbf45e1ae50240680",
            "value": " 4764/4764 [09:57&lt;00:00, 17.43 MiB/s]"
          }
        },
        "2000cb762d4c4a1baaa4343c95820a5d": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_bf061d7e7a61404f8ec405f521235b99",
            "placeholder": "​",
            "style": "IPY_MODEL_c6f160453bc84e1d9d8c3ab68f3f073a",
            "value": " 101008/101008 [09:56&lt;00:00, 978.25 file/s]"
          }
        },
        "260ecced730049ec8dc8a08b6dd9c2a9": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "29d22a15659945ebbcaf27a89a13b77c": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_ee20a91e86654bb491ee0d19877de1bd",
            "placeholder": "​",
            "style": "IPY_MODEL_6907f773f9e642e2a3b6597a5bc0e3c3",
            "value": "Dl Size...: 100%"
          }
        },
        "29ea1116d98147d28a50720cd449e25f": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_a8f00aff4e8c45238bb339cf2a915abb",
            "placeholder": "​",
            "style": "IPY_MODEL_5b99433e1a1f4c13831251a6086e394b",
            "value": "Shuffling /root/tensorflow_datasets/food101/2.0.0.incompleteY886C4/food101-validation.tfrecord*...:  99%"
          }
        },
        "2c8c131849154e62ac1a8ad4245e48f3": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_36b37aab113849b3a749026f67d66d88",
            "placeholder": "​",
            "style": "IPY_MODEL_4c692a547b274feb98ea1a742d6e3870",
            "value": " 25003/25250 [00:04&lt;00:00, 3619.86 examples/s]"
          }
        },
        "2c95db439cbe40d0ab7dcbc1e5ff8c24": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "2d6622ddde744ce0872861296fc228ae": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": "20px"
          }
        },
        "30faadb004824b72905d803a2e7d212b": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_a72413f5c88b4ee59959ae8d088b062e",
            "placeholder": "​",
            "style": "IPY_MODEL_83e95e5c41c94fe69243124a19de7a93",
            "value": "Shuffling /root/tensorflow_datasets/food101/2.0.0.incompleteY886C4/food101-train.tfrecord*...: 100%"
          }
        },
        "34bd38e5fac64f8085af23e38b570d25": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "363889fb320b462ea98a71ac508c9814": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_ae0ff9e130ae4e48a796afbb833f2cfa",
            "placeholder": "​",
            "style": "IPY_MODEL_9d1c3d650ea84257a6e0f3001899bd96",
            "value": " 1/1 [09:57&lt;00:00, 272.26s/ url]"
          }
        },
        "36b37aab113849b3a749026f67d66d88": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "3b6bb34cd9284777a5d5a42cbbef841a": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_7d098c892d254267a54765e46933fa02",
            "placeholder": "​",
            "style": "IPY_MODEL_b08e0162001c42148bf88bec9f36fef9",
            "value": "Extraction completed...:  97%"
          }
        },
        "3c8b6cbce479466cab5a7902181c474a": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "FloatProgressModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_260ecced730049ec8dc8a08b6dd9c2a9",
            "max": 75750,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_9cb2d4296e42416a94506ea251a8ea96",
            "value": 75750
          }
        },
        "459818f321724e6d9ca0d668b5d30551": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "ProgressStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "4c53d86f4a4e4ec59b4fc8ae95182e3e": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "4c692a547b274feb98ea1a742d6e3870": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "4d61904c2290432684ba7a5398633d12": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "ProgressStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "5206303bb07547fda37d806707272594": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "549c73a23f89453b9ce068398117d677": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "55ce6507622c4936ad7be3062dbdae88": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "56b4c9286169498f8c29fced05124ece": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_0d1d9ae0d830454d9df771e2fdaf2fcd",
            "placeholder": "​",
            "style": "IPY_MODEL_719f86ba47744c0c844ebef01109f9c6",
            "value": " 25218/25250 [00:57&lt;00:00, 485.42 examples/s]"
          }
        },
        "5aa2e375c8b34969b5a852baefb27928": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "ProgressStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "5b99433e1a1f4c13831251a6086e394b": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "5ede47b1f5c14537b641ec5ac42af993": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "60f2ec19834842359e41f19f773905f4": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "ProgressStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "636e1e5b421b4b84ad282bd7b5fec7bd": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "FloatProgressModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_6a53e097d8354e0a88a95cb53c2f1b69",
            "max": 1,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_5aa2e375c8b34969b5a852baefb27928",
            "value": 1
          }
        },
        "675ab053feac4c288445b824ad4dbf0b": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HBoxModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_29ea1116d98147d28a50720cd449e25f",
              "IPY_MODEL_04a88c825af941bea2038ee29c5a9c0f",
              "IPY_MODEL_2c8c131849154e62ac1a8ad4245e48f3"
            ],
            "layout": "IPY_MODEL_b8d61b5fc777479c9851c339f8210a8b"
          }
        },
        "68b334c6e6344565af3f32dd0b138c06": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "6907f773f9e642e2a3b6597a5bc0e3c3": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "6a53e097d8354e0a88a95cb53c2f1b69": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": "20px"
          }
        },
        "719f86ba47744c0c844ebef01109f9c6": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "722a0cbfb6454a41827fea08a3c2d3cd": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": "hidden",
            "width": null
          }
        },
        "7603f9f135af4be891cb9065347db445": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_2c95db439cbe40d0ab7dcbc1e5ff8c24",
            "placeholder": "​",
            "style": "IPY_MODEL_68b334c6e6344565af3f32dd0b138c06",
            "value": " 75641/75750 [01:56&lt;00:00, 785.85 examples/s]"
          }
        },
        "792ae281d0594abd81d5218d006e98f7": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": "hidden",
            "width": null
          }
        },
        "7d098c892d254267a54765e46933fa02": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "7d403af9f66443cab63d62238fb37e92": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "FloatProgressModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_0939efe8947a44dc893da1580a4aeca4",
            "max": 2,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_4d61904c2290432684ba7a5398633d12",
            "value": 2
          }
        },
        "7eb886c129d947c48defcc99783baad6": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "7ffa33ca29cf43259fa365323de6e127": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HBoxModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_09618ebca4fb453f9d492bced46a4a6f",
              "IPY_MODEL_7d403af9f66443cab63d62238fb37e92",
              "IPY_MODEL_0c0fdfc54c1d485abe482c5b926566ba"
            ],
            "layout": "IPY_MODEL_9afd82d9d6434e1e9b223c4278d02eaf"
          }
        },
        "82f09c30b057455b9130cca6a171c94e": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "83e6f7f9cf7e45129b89ce8c580d409e": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "83e95e5c41c94fe69243124a19de7a93": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "90807f664fd341d594e22ac96d0ed1a7": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": "20px"
          }
        },
        "93ab551775a14d008bfdb8c67b08a664": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "9afd82d9d6434e1e9b223c4278d02eaf": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": "hidden",
            "width": null
          }
        },
        "9cb2d4296e42416a94506ea251a8ea96": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "ProgressStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "9d1c3d650ea84257a6e0f3001899bd96": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "a08ae2744e664f65bb8ffbdb9306fd91": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "a72413f5c88b4ee59959ae8d088b062e": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "a8f00aff4e8c45238bb339cf2a915abb": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "ae0ff9e130ae4e48a796afbb833f2cfa": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "b08e0162001c42148bf88bec9f36fef9": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "b2bce047d775472bad88944e10b9f9c7": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "FloatProgressModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_fa6eb00a5adf4be1a41aab5fe5455dc0",
            "max": 75750,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_459818f321724e6d9ca0d668b5d30551",
            "value": 75750
          }
        },
        "b3b2f72730764745ba370a3f59e81ea8": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "FloatProgressModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_90807f664fd341d594e22ac96d0ed1a7",
            "max": 1,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_60f2ec19834842359e41f19f773905f4",
            "value": 1
          }
        },
        "b424eb0a47274cc0822abefe3a9311d4": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "ProgressStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "b498fdc1472747299067fab018efacf3": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "b8d61b5fc777479c9851c339f8210a8b": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": "hidden",
            "width": null
          }
        },
        "bbd82f1a4c284870999c855e25488f2d": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "bd442e88a3f8416893ee481b09c57a70": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "FloatProgressModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_4c53d86f4a4e4ec59b4fc8ae95182e3e",
            "max": 25250,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_10e55330eda8498ea164f1ecbf6580cd",
            "value": 25250
          }
        },
        "bd87b229b4ea4f10842cdd9a2447bd27": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_d37c17434377468d88b0a520834e8297",
            "placeholder": "​",
            "style": "IPY_MODEL_5ede47b1f5c14537b641ec5ac42af993",
            "value": "Generating train examples...: 100%"
          }
        },
        "bf061d7e7a61404f8ec405f521235b99": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "c5402c24043b46bfa480408723b0f845": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_55ce6507622c4936ad7be3062dbdae88",
            "placeholder": "​",
            "style": "IPY_MODEL_a08ae2744e664f65bb8ffbdb9306fd91",
            "value": "Generating validation examples...: 100%"
          }
        },
        "c64b7a78b4484872aa9bb19e7a263caf": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HBoxModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_c5402c24043b46bfa480408723b0f845",
              "IPY_MODEL_bd442e88a3f8416893ee481b09c57a70",
              "IPY_MODEL_56b4c9286169498f8c29fced05124ece"
            ],
            "layout": "IPY_MODEL_722a0cbfb6454a41827fea08a3c2d3cd"
          }
        },
        "c6f160453bc84e1d9d8c3ab68f3f073a": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "d0b1f16b3ff243ceb4a90d64c0ce3612": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "FloatProgressModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_2d6622ddde744ce0872861296fc228ae",
            "max": 1,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_b424eb0a47274cc0822abefe3a9311d4",
            "value": 1
          }
        },
        "d3481ca4b1d740438a1557b7f7318e7a": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_83e6f7f9cf7e45129b89ce8c580d409e",
            "placeholder": "​",
            "style": "IPY_MODEL_34bd38e5fac64f8085af23e38b570d25",
            "value": "Dl Completed...: 100%"
          }
        },
        "d37c17434377468d88b0a520834e8297": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "d54ccdeed2804cb68bd7a027baee1838": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "da6a5ac1c33d44259cd5e01d7073399f": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HBoxModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_30faadb004824b72905d803a2e7d212b",
              "IPY_MODEL_b2bce047d775472bad88944e10b9f9c7",
              "IPY_MODEL_1d2b146a59354365a10d4745912e5cc8"
            ],
            "layout": "IPY_MODEL_e9f4edfb194c45ce826f8e60535a49c5"
          }
        },
        "e9f4edfb194c45ce826f8e60535a49c5": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": "hidden",
            "width": null
          }
        },
        "ee20a91e86654bb491ee0d19877de1bd": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "f49ab68aa95a4d869c6973fe8cdc7e48": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HBoxModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_bd87b229b4ea4f10842cdd9a2447bd27",
              "IPY_MODEL_3c8b6cbce479466cab5a7902181c474a",
              "IPY_MODEL_7603f9f135af4be891cb9065347db445"
            ],
            "layout": "IPY_MODEL_792ae281d0594abd81d5218d006e98f7"
          }
        },
        "fa6eb00a5adf4be1a41aab5fe5455dc0": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "ffb1e015f3e54fecbf45e1ae50240680": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        }
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}