MOSFETCharacteristics.ipynb

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      "authorship_tag": "ABX9TyMi2J21srpQe0YcWGhzy2ro",
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      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
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      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Sohammhatre10/MOSCharacteristics/blob/main/MOSFETCharacteristics.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install gdown\n",
        "import gdown\n",
        "\n",
        "input_file = \"https://drive.google.com/uc?id=1r0oTr73TmgzlxfRxQmOhnTWxkwFVwC4X\"\n",
        "output_file = \"moschar.zip\"\n",
        "gdown.download(input_file, output_file)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "id": "YHG8zaom8oo3",
        "outputId": "146545d1-906c-43d2-b866-3f627e8497fe"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: gdown in /usr/local/lib/python3.10/dist-packages (5.1.0)\n",
            "Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.10/dist-packages (from gdown) (4.12.3)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from gdown) (3.14.0)\n",
            "Requirement already satisfied: requests[socks] in /usr/local/lib/python3.10/dist-packages (from gdown) (2.31.0)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from gdown) (4.66.4)\n",
            "Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.10/dist-packages (from beautifulsoup4->gdown) (2.5)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests[socks]->gdown) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests[socks]->gdown) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests[socks]->gdown) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests[socks]->gdown) (2024.6.2)\n",
            "Requirement already satisfied: PySocks!=1.5.7,>=1.5.6 in /usr/local/lib/python3.10/dist-packages (from requests[socks]->gdown) (1.7.1)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1r0oTr73TmgzlxfRxQmOhnTWxkwFVwC4X\n",
            "To: /content/moschar.zip\n",
            "100%|██████████| 89.2k/89.2k [00:00<00:00, 40.7MB/s]\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'moschar.zip'"
            ],
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              "type": "string"
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          "metadata": {},
          "execution_count": 2
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    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TEJcHYYChWVx",
        "outputId": "0d7bb227-d425-4570-ebcd-1f794d9cd7fe"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  moschar.zip\n",
            "  inflating: training_data.csv       \n",
            "  inflating: val01.csv               \n",
            "  inflating: val02.csv               \n",
            "  inflating: val03.csv               \n",
            "  inflating: val04.csv               \n",
            "  inflating: val05.csv               \n",
            "  inflating: val06.csv               \n"
          ]
        }
      ],
      "source": [
        "!unzip moschar.zip"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "train_data = pd.read_csv(\"training_data.csv\")\n",
        "\n",
        "train_data"
      ],
      "metadata": {
        "id": "jTkKBksAtAKa",
        "colab": {
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          "height": 423
        },
        "outputId": "e0d261fb-8343-4f43-a930-d30950215871"
      },
      "execution_count": 4,
      "outputs": [
        {
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              "type": "dataframe",
              "variable_name": "train_data",
              "summary": "{\n  \"name\": \"train_data\",\n  \"rows\": 25351,\n  \"fields\": [\n    {\n      \"column\": \"Vds\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.4491662569342023,\n        \"min\": 0.0,\n        \"max\": 5.0,\n        \"num_unique_values\": 251,\n        \"samples\": [\n          3.1,\n          0.12,\n          3.28\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Vgs\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.4577667256560565,\n        \"min\": 0.0,\n        \"max\": 5.0,\n        \"num_unique_values\": 101,\n        \"samples\": [\n          4.2,\n          2.75,\n          3.3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 4.0356707237378814e-05,\n        \"min\": 0.0,\n        \"max\": 0.000144,\n        \"num_unique_values\": 5038,\n        \"samples\": [\n          8e-05,\n          1.51e-06,\n          3.68e-07\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "val01 = pd.read_csv('val01.csv')\n",
        "val01\n",
        "df = train_data"
      ],
      "metadata": {
        "id": "x0dw-RwHtSid"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"Id\"].replace({0:1e-13}, inplace=True)\n",
        "df[\"Vgs\"].replace({0:1e-3}, inplace=True)\n",
        "df[\"Vds\"].replace({0:1e-3}, inplace=True)"
      ],
      "metadata": {
        "id": "A-IxqQnwtbSm"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['Id']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TxEdfY4hDPpO",
        "outputId": "bec13f00-dad5-4ece-af65-a7547155e25b"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0        1.000000e-13\n",
              "1        2.770000e-14\n",
              "2        4.790000e-14\n",
              "3        6.900000e-14\n",
              "4        8.950000e-14\n",
              "             ...     \n",
              "25346    1.430000e-04\n",
              "25347    1.430000e-04\n",
              "25348    1.430000e-04\n",
              "25349    1.430000e-04\n",
              "25350    1.440000e-04\n",
              "Name: Id, Length: 25351, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "id=df[\"Id\"]\n",
        "Vgs=df[\"Vgs\"]\n",
        "Vds=df[\"Vds\"]"
      ],
      "metadata": {
        "id": "e_yZ2gc3vuZR"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "yy=np.ravel(id)\n",
        "X1=df.iloc[:,0:2]\n",
        "X=np.log10(X1)\n",
        "X"
      ],
      "metadata": {
        "id": "_uXX-qZavx83",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "outputId": "a0a999cd-8712-4832-c861-d7eb613ecc48"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Vds      Vgs\n",
              "0     -3.000000 -3.00000\n",
              "1     -1.698970 -3.00000\n",
              "2     -1.397940 -3.00000\n",
              "3     -1.221849 -3.00000\n",
              "4     -1.096910 -3.00000\n",
              "...         ...      ...\n",
              "25346  0.691965  0.69897\n",
              "25347  0.693727  0.69897\n",
              "25348  0.695482  0.69897\n",
              "25349  0.697229  0.69897\n",
              "25350  0.698970  0.69897\n",
              "\n",
              "[25351 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-367a8f05-ab59-4190-9b6e-62d7f968ff20\" class=\"colab-df-container\">\n",
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              "        vertical-align: middle;\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Vds</th>\n",
              "      <th>Vgs</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-3.000000</td>\n",
              "      <td>-3.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-1.698970</td>\n",
              "      <td>-3.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-1.397940</td>\n",
              "      <td>-3.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-1.221849</td>\n",
              "      <td>-3.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-1.096910</td>\n",
              "      <td>-3.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
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              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>25346</th>\n",
              "      <td>0.691965</td>\n",
              "      <td>0.69897</td>\n",
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              "      <th>25347</th>\n",
              "      <td>0.693727</td>\n",
              "      <td>0.69897</td>\n",
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              "    <tr>\n",
              "      <th>25348</th>\n",
              "      <td>0.695482</td>\n",
              "      <td>0.69897</td>\n",
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              "      <td>0.698970</td>\n",
              "      <td>0.69897</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>25351 rows × 2 columns</p>\n",
              "</div>\n",
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              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "    border: 2px solid var(--fill-color);\n",
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              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
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              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
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              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
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              "\n",
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              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('X')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('X');\n",
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              "\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "X",
              "summary": "{\n  \"name\": \"X\",\n  \"rows\": 25351,\n  \"fields\": [\n    {\n      \"column\": \"Vds\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.4639292274912774,\n        \"min\": -3.0,\n        \"max\": 0.6989700043360189,\n        \"num_unique_values\": 251,\n        \"samples\": [\n          0.4913616938342727,\n          -0.9208187539523752,\n          0.515873843711679\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Vgs\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.514412579498903,\n        \"min\": -3.0,\n        \"max\": 0.6989700043360189,\n        \"num_unique_values\": 101,\n        \"samples\": [\n          0.6232492903979004,\n          0.43933269383026263,\n          0.5185139398778874\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "y = np.log10(yy)\n",
        "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.2)\n",
        "y_train = y_train.reshape(-1,1)\n",
        "y_test = y_test.reshape(-1,1)"
      ],
      "metadata": {
        "id": "47Qe82htwz9F"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import tensorflow as tf\n",
        "from tensorflow.keras.callbacks import LearningRateScheduler\n",
        "\n",
        "model = tf.keras.Sequential([\n",
        "    tf.keras.layers.Dense(16, activation='tanh'),\n",
        "    tf.keras.layers.Dense(16, activation='tanh'),\n",
        "    tf.keras.layers.Dense(1)\n",
        "])\n",
        "\n",
        "model.compile(\n",
        "    loss='mae',\n",
        "    optimizer=tf.keras.optimizers.Adam(),\n",
        "    metrics=['mse']\n",
        ")\n",
        "\n",
        "def learning_rate_scheduler(epochs):\n",
        "    return 0.01\n",
        "\n",
        "lr_scheduler = tf.keras.callbacks.LearningRateScheduler(learning_rate_scheduler)\n",
        "\n",
        "history = model.fit(X_train, y_train, epochs=100, callbacks=[lr_scheduler], validation_data=(X_test, y_test))\n"
      ],
      "metadata": {
        "id": "l0oqiWT8wEtc",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ce62ef40-575a-4c2f-eb7c-79ee8ec78caf"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/100\n",
            "634/634 [==============================] - 3s 3ms/step - loss: 0.6911 - mse: 3.3953 - val_loss: 0.0797 - val_mse: 0.0725 - lr: 0.0100\n",
            "Epoch 2/100\n",
            "634/634 [==============================] - 3s 5ms/step - loss: 0.1017 - mse: 0.1061 - val_loss: 0.0914 - val_mse: 0.0628 - lr: 0.0100\n",
            "Epoch 3/100\n",
            "634/634 [==============================] - 3s 5ms/step - loss: 0.0779 - mse: 0.0738 - val_loss: 0.0377 - val_mse: 0.0329 - lr: 0.0100\n",
            "Epoch 4/100\n",
            "634/634 [==============================] - 3s 5ms/step - loss: 0.0621 - mse: 0.0429 - val_loss: 0.0743 - val_mse: 0.0195 - lr: 0.0100\n",
            "Epoch 5/100\n",
            "634/634 [==============================] - 3s 5ms/step - loss: 0.0536 - mse: 0.0235 - val_loss: 0.0630 - val_mse: 0.0131 - lr: 0.0100\n",
            "Epoch 6/100\n",
            "634/634 [==============================] - 5s 8ms/step - loss: 0.0489 - mse: 0.0190 - val_loss: 0.0465 - val_mse: 0.0102 - lr: 0.0100\n",
            "Epoch 7/100\n",
            "634/634 [==============================] - 3s 5ms/step - loss: 0.0444 - mse: 0.0141 - val_loss: 0.0310 - val_mse: 0.0071 - lr: 0.0100\n",
            "Epoch 8/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0411 - mse: 0.0117 - val_loss: 0.0344 - val_mse: 0.0053 - lr: 0.0100\n",
            "Epoch 9/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0406 - mse: 0.0108 - val_loss: 0.0321 - val_mse: 0.0046 - lr: 0.0100\n",
            "Epoch 10/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0392 - mse: 0.0099 - val_loss: 0.0306 - val_mse: 0.0045 - lr: 0.0100\n",
            "Epoch 11/100\n",
            "634/634 [==============================] - 2s 2ms/step - loss: 0.0381 - mse: 0.0095 - val_loss: 0.0193 - val_mse: 0.0035 - lr: 0.0100\n",
            "Epoch 12/100\n",
            "634/634 [==============================] - 2s 4ms/step - loss: 0.0434 - mse: 0.0093 - val_loss: 0.0380 - val_mse: 0.0060 - lr: 0.0100\n",
            "Epoch 13/100\n",
            "634/634 [==============================] - 2s 2ms/step - loss: 0.0360 - mse: 0.0087 - val_loss: 0.0460 - val_mse: 0.0074 - lr: 0.0100\n",
            "Epoch 14/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0378 - mse: 0.0078 - val_loss: 0.0240 - val_mse: 0.0031 - lr: 0.0100\n",
            "Epoch 15/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0352 - mse: 0.0084 - val_loss: 0.0296 - val_mse: 0.0044 - lr: 0.0100\n",
            "Epoch 16/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0352 - mse: 0.0073 - val_loss: 0.0349 - val_mse: 0.0037 - lr: 0.0100\n",
            "Epoch 17/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0354 - mse: 0.0072 - val_loss: 0.0410 - val_mse: 0.0063 - lr: 0.0100\n",
            "Epoch 18/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0372 - mse: 0.0071 - val_loss: 0.0259 - val_mse: 0.0027 - lr: 0.0100\n",
            "Epoch 19/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0373 - mse: 0.0070 - val_loss: 0.0281 - val_mse: 0.0030 - lr: 0.0100\n",
            "Epoch 20/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0343 - mse: 0.0070 - val_loss: 0.0190 - val_mse: 0.0022 - lr: 0.0100\n",
            "Epoch 21/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0329 - mse: 0.0057 - val_loss: 0.0418 - val_mse: 0.0040 - lr: 0.0100\n",
            "Epoch 22/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0345 - mse: 0.0061 - val_loss: 0.0556 - val_mse: 0.0056 - lr: 0.0100\n",
            "Epoch 23/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0331 - mse: 0.0052 - val_loss: 0.0374 - val_mse: 0.0031 - lr: 0.0100\n",
            "Epoch 24/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0344 - mse: 0.0055 - val_loss: 0.0345 - val_mse: 0.0037 - lr: 0.0100\n",
            "Epoch 25/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0315 - mse: 0.0049 - val_loss: 0.0300 - val_mse: 0.0030 - lr: 0.0100\n",
            "Epoch 26/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0327 - mse: 0.0051 - val_loss: 0.0465 - val_mse: 0.0049 - lr: 0.0100\n",
            "Epoch 27/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0336 - mse: 0.0050 - val_loss: 0.0480 - val_mse: 0.0063 - lr: 0.0100\n",
            "Epoch 28/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0328 - mse: 0.0046 - val_loss: 0.0324 - val_mse: 0.0032 - lr: 0.0100\n",
            "Epoch 29/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0331 - mse: 0.0048 - val_loss: 0.0365 - val_mse: 0.0025 - lr: 0.0100\n",
            "Epoch 30/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0307 - mse: 0.0046 - val_loss: 0.0266 - val_mse: 0.0021 - lr: 0.0100\n",
            "Epoch 31/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0315 - mse: 0.0044 - val_loss: 0.0235 - val_mse: 0.0021 - lr: 0.0100\n",
            "Epoch 32/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0299 - mse: 0.0039 - val_loss: 0.0211 - val_mse: 0.0024 - lr: 0.0100\n",
            "Epoch 33/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0305 - mse: 0.0043 - val_loss: 0.0191 - val_mse: 0.0016 - lr: 0.0100\n",
            "Epoch 34/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0287 - mse: 0.0037 - val_loss: 0.0313 - val_mse: 0.0020 - lr: 0.0100\n",
            "Epoch 35/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0297 - mse: 0.0037 - val_loss: 0.0205 - val_mse: 0.0014 - lr: 0.0100\n",
            "Epoch 36/100\n",
            "634/634 [==============================] - 2s 2ms/step - loss: 0.0274 - mse: 0.0033 - val_loss: 0.0326 - val_mse: 0.0042 - lr: 0.0100\n",
            "Epoch 37/100\n",
            "634/634 [==============================] - 2s 4ms/step - loss: 0.0296 - mse: 0.0033 - val_loss: 0.0328 - val_mse: 0.0036 - lr: 0.0100\n",
            "Epoch 38/100\n",
            "634/634 [==============================] - 3s 4ms/step - loss: 0.0295 - mse: 0.0034 - val_loss: 0.0280 - val_mse: 0.0019 - lr: 0.0100\n",
            "Epoch 39/100\n",
            "634/634 [==============================] - 2s 4ms/step - loss: 0.0283 - mse: 0.0031 - val_loss: 0.0315 - val_mse: 0.0023 - lr: 0.0100\n",
            "Epoch 40/100\n",
            "634/634 [==============================] - 2s 2ms/step - loss: 0.0290 - mse: 0.0029 - val_loss: 0.0185 - val_mse: 0.0012 - lr: 0.0100\n",
            "Epoch 41/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0293 - mse: 0.0030 - val_loss: 0.0256 - val_mse: 0.0020 - lr: 0.0100\n",
            "Epoch 42/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0303 - mse: 0.0032 - val_loss: 0.0263 - val_mse: 0.0026 - lr: 0.0100\n",
            "Epoch 43/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0278 - mse: 0.0027 - val_loss: 0.0225 - val_mse: 0.0018 - lr: 0.0100\n",
            "Epoch 44/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0275 - mse: 0.0027 - val_loss: 0.0280 - val_mse: 0.0023 - lr: 0.0100\n",
            "Epoch 45/100\n",
            "634/634 [==============================] - 2s 2ms/step - loss: 0.0309 - mse: 0.0032 - val_loss: 0.0190 - val_mse: 0.0012 - lr: 0.0100\n",
            "Epoch 46/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0275 - mse: 0.0028 - val_loss: 0.0268 - val_mse: 0.0019 - lr: 0.0100\n",
            "Epoch 47/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0280 - mse: 0.0028 - val_loss: 0.0297 - val_mse: 0.0017 - lr: 0.0100\n",
            "Epoch 48/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0270 - mse: 0.0024 - val_loss: 0.0196 - val_mse: 0.0010 - lr: 0.0100\n",
            "Epoch 49/100\n",
            "634/634 [==============================] - 2s 2ms/step - loss: 0.0265 - mse: 0.0023 - val_loss: 0.0297 - val_mse: 0.0036 - lr: 0.0100\n",
            "Epoch 50/100\n",
            "634/634 [==============================] - 2s 2ms/step - loss: 0.0273 - mse: 0.0024 - val_loss: 0.0191 - val_mse: 0.0010 - lr: 0.0100\n",
            "Epoch 51/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0274 - mse: 0.0023 - val_loss: 0.0353 - val_mse: 0.0024 - lr: 0.0100\n",
            "Epoch 52/100\n",
            "634/634 [==============================] - 2s 2ms/step - loss: 0.0267 - mse: 0.0022 - val_loss: 0.0355 - val_mse: 0.0032 - lr: 0.0100\n",
            "Epoch 53/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0290 - mse: 0.0025 - val_loss: 0.0383 - val_mse: 0.0026 - lr: 0.0100\n",
            "Epoch 54/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0272 - mse: 0.0022 - val_loss: 0.0226 - val_mse: 0.0019 - lr: 0.0100\n",
            "Epoch 55/100\n",
            "634/634 [==============================] - 2s 4ms/step - loss: 0.0276 - mse: 0.0022 - val_loss: 0.0147 - val_mse: 9.6367e-04 - lr: 0.0100\n",
            "Epoch 56/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0246 - mse: 0.0019 - val_loss: 0.0323 - val_mse: 0.0035 - lr: 0.0100\n",
            "Epoch 57/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0280 - mse: 0.0023 - val_loss: 0.0242 - val_mse: 0.0012 - lr: 0.0100\n",
            "Epoch 58/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0256 - mse: 0.0018 - val_loss: 0.0299 - val_mse: 0.0022 - lr: 0.0100\n",
            "Epoch 59/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0261 - mse: 0.0020 - val_loss: 0.0216 - val_mse: 0.0013 - lr: 0.0100\n",
            "Epoch 60/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0263 - mse: 0.0019 - val_loss: 0.0361 - val_mse: 0.0024 - lr: 0.0100\n",
            "Epoch 61/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0252 - mse: 0.0019 - val_loss: 0.0175 - val_mse: 9.2180e-04 - lr: 0.0100\n",
            "Epoch 62/100\n",
            "634/634 [==============================] - 2s 2ms/step - loss: 0.0254 - mse: 0.0018 - val_loss: 0.0182 - val_mse: 0.0014 - lr: 0.0100\n",
            "Epoch 63/100\n",
            "634/634 [==============================] - 3s 4ms/step - loss: 0.0273 - mse: 0.0020 - val_loss: 0.0139 - val_mse: 8.2460e-04 - lr: 0.0100\n",
            "Epoch 64/100\n",
            "634/634 [==============================] - 2s 2ms/step - loss: 0.0240 - mse: 0.0016 - val_loss: 0.0156 - val_mse: 6.9167e-04 - lr: 0.0100\n",
            "Epoch 65/100\n",
            "634/634 [==============================] - 2s 2ms/step - loss: 0.0258 - mse: 0.0018 - val_loss: 0.0231 - val_mse: 0.0013 - lr: 0.0100\n",
            "Epoch 66/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0224 - mse: 0.0014 - val_loss: 0.0163 - val_mse: 0.0018 - lr: 0.0100\n",
            "Epoch 67/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0252 - mse: 0.0018 - val_loss: 0.0176 - val_mse: 7.9697e-04 - lr: 0.0100\n",
            "Epoch 68/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0259 - mse: 0.0017 - val_loss: 0.0227 - val_mse: 0.0015 - lr: 0.0100\n",
            "Epoch 69/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0267 - mse: 0.0019 - val_loss: 0.0236 - val_mse: 0.0011 - lr: 0.0100\n",
            "Epoch 70/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0241 - mse: 0.0016 - val_loss: 0.0344 - val_mse: 0.0024 - lr: 0.0100\n",
            "Epoch 71/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0248 - mse: 0.0016 - val_loss: 0.0337 - val_mse: 0.0017 - lr: 0.0100\n",
            "Epoch 72/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0240 - mse: 0.0015 - val_loss: 0.0272 - val_mse: 0.0015 - lr: 0.0100\n",
            "Epoch 73/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0220 - mse: 0.0013 - val_loss: 0.0243 - val_mse: 0.0016 - lr: 0.0100\n",
            "Epoch 74/100\n",
            "634/634 [==============================] - 2s 4ms/step - loss: 0.0233 - mse: 0.0016 - val_loss: 0.0217 - val_mse: 9.8380e-04 - lr: 0.0100\n",
            "Epoch 75/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0239 - mse: 0.0015 - val_loss: 0.0248 - val_mse: 0.0021 - lr: 0.0100\n",
            "Epoch 76/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0259 - mse: 0.0017 - val_loss: 0.0164 - val_mse: 0.0010 - lr: 0.0100\n",
            "Epoch 77/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0236 - mse: 0.0014 - val_loss: 0.0233 - val_mse: 0.0021 - lr: 0.0100\n",
            "Epoch 78/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0238 - mse: 0.0014 - val_loss: 0.0332 - val_mse: 0.0016 - lr: 0.0100\n",
            "Epoch 79/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0229 - mse: 0.0013 - val_loss: 0.0351 - val_mse: 0.0027 - lr: 0.0100\n",
            "Epoch 80/100\n",
            "634/634 [==============================] - 2s 4ms/step - loss: 0.0234 - mse: 0.0014 - val_loss: 0.0259 - val_mse: 0.0012 - lr: 0.0100\n",
            "Epoch 81/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0223 - mse: 0.0012 - val_loss: 0.0603 - val_mse: 0.0047 - lr: 0.0100\n",
            "Epoch 82/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0248 - mse: 0.0014 - val_loss: 0.0197 - val_mse: 0.0017 - lr: 0.0100\n",
            "Epoch 83/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0225 - mse: 0.0012 - val_loss: 0.0143 - val_mse: 5.7583e-04 - lr: 0.0100\n",
            "Epoch 84/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0219 - mse: 0.0012 - val_loss: 0.0165 - val_mse: 6.4777e-04 - lr: 0.0100\n",
            "Epoch 85/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0230 - mse: 0.0012 - val_loss: 0.0254 - val_mse: 0.0012 - lr: 0.0100\n",
            "Epoch 86/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0235 - mse: 0.0013 - val_loss: 0.0265 - val_mse: 0.0013 - lr: 0.0100\n",
            "Epoch 87/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0245 - mse: 0.0015 - val_loss: 0.0307 - val_mse: 0.0012 - lr: 0.0100\n",
            "Epoch 88/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0214 - mse: 0.0011 - val_loss: 0.0157 - val_mse: 8.2422e-04 - lr: 0.0100\n",
            "Epoch 89/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0219 - mse: 0.0012 - val_loss: 0.0186 - val_mse: 0.0011 - lr: 0.0100\n",
            "Epoch 90/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0232 - mse: 0.0012 - val_loss: 0.0229 - val_mse: 8.2689e-04 - lr: 0.0100\n",
            "Epoch 91/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0222 - mse: 0.0012 - val_loss: 0.0401 - val_mse: 0.0026 - lr: 0.0100\n",
            "Epoch 92/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0217 - mse: 0.0011 - val_loss: 0.0288 - val_mse: 0.0017 - lr: 0.0100\n",
            "Epoch 93/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0228 - mse: 0.0012 - val_loss: 0.0275 - val_mse: 0.0013 - lr: 0.0100\n",
            "Epoch 94/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0232 - mse: 0.0012 - val_loss: 0.0183 - val_mse: 8.8060e-04 - lr: 0.0100\n",
            "Epoch 95/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0206 - mse: 0.0010 - val_loss: 0.0172 - val_mse: 4.9206e-04 - lr: 0.0100\n",
            "Epoch 96/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0209 - mse: 0.0010 - val_loss: 0.0190 - val_mse: 9.3195e-04 - lr: 0.0100\n",
            "Epoch 97/100\n",
            "634/634 [==============================] - 2s 4ms/step - loss: 0.0221 - mse: 0.0012 - val_loss: 0.0271 - val_mse: 0.0016 - lr: 0.0100\n",
            "Epoch 98/100\n",
            "634/634 [==============================] - 2s 3ms/step - loss: 0.0216 - mse: 0.0011 - val_loss: 0.0240 - val_mse: 9.4299e-04 - lr: 0.0100\n",
            "Epoch 99/100\n",
            "634/634 [==============================] - 2s 2ms/step - loss: 0.0209 - mse: 0.0011 - val_loss: 0.0350 - val_mse: 0.0016 - lr: 0.0100\n",
            "Epoch 100/100\n",
            "634/634 [==============================] - 1s 2ms/step - loss: 0.0219 - mse: 0.0011 - val_loss: 0.0205 - val_mse: 7.5240e-04 - lr: 0.0100\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Read data files\n",
        "data1 = pd.read_csv('val02.csv')\n",
        "data2 = pd.read_csv('val01.csv')\n",
        "\n",
        "# Create subplots\n",
        "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5))\n",
        "\n",
        "# Function to plot data\n",
        "def plot_data(data, ax):\n",
        "    val_feature = data.iloc[:, 0:2]\n",
        "    X = val_feature\n",
        "    y_true = np.ravel(data[\"id\"])\n",
        "\n",
        "    # Normalize input data and target variable\n",
        "    X_norm = np.log10(X)\n",
        "    y_norm = np.log10(y_true)\n",
        "    y_norm = y_norm.reshape(-1, 1)\n",
        "\n",
        "    # Predict the target variable\n",
        "    y_pred = model.predict(X_norm)\n",
        "\n",
        "    # Plot the result\n",
        "    vg1 = data[\"vgs\"]\n",
        "    vg = np.ravel(vg1)\n",
        "    vg = vg.reshape(-1, 1)\n",
        "\n",
        "    # Plot the actual values\n",
        "    ax.plot(vg, 10**y_norm, 'black', label='Actual', linestyle=\"dashed\")\n",
        "\n",
        "    # Plot the predicted values\n",
        "    ax.plot(vg, 10**y_pred, 'green', label='Predicted')\n",
        "\n",
        "    ax.set_title(f'{data.columns[0]} = {data[\"vds\"][0]}V', fontsize=14)\n",
        "    ax.set_xlabel('Gate Voltage (V)', fontsize=12)\n",
        "    ax.set_ylabel('Drain Current (A)', fontsize=12)\n",
        "    ax.legend()\n",
        "    ax.grid(True)\n",
        "\n",
        "# Plot data for each file\n",
        "plot_data(data1, ax1)\n",
        "plot_data(data2, ax2)\n",
        "\n",
        "# Set the overall title\n",
        "fig.suptitle('Actual and Predicted Drain Current vs. Gate Voltage', fontsize=16, y=1.05)\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.savefig('plot_vgs.png')\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "MUHaw_eG5gTR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 583
        },
        "outputId": "2fa140f2-0d40-474c-d5fc-d2d3a4a07eb3"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1/1 [==============================] - 0s 92ms/step\n",
            "1/1 [==============================] - 0s 21ms/step\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Read data files\n",
        "data1 = pd.read_csv('val03.csv')\n",
        "data2 = pd.read_csv('val04.csv')\n",
        "data3 = pd.read_csv('val06.csv')\n",
        "\n",
        "# Create subplots\n",
        "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(18, 5))\n",
        "\n",
        "# Function to plot data\n",
        "def plot_data(data, ax, vgs_val):\n",
        "    input_data = data.iloc[:, 0:2]\n",
        "    X = input_data\n",
        "    y_true = np.ravel(data[\"id\"])\n",
        "\n",
        "    # Normalize input data and target variable\n",
        "    X_norm = np.log10(X)\n",
        "    y_norm = np.log10(y_true)\n",
        "    y_norm = y_norm.reshape(-1, 1)\n",
        "\n",
        "    # Predict the target variable\n",
        "    y_pred = model.predict(X_norm)\n",
        "\n",
        "    # Plot the result\n",
        "    vds_data = data[\"vds\"]\n",
        "    vds = np.ravel(vds_data)\n",
        "    vds = vds.reshape(-1, 1)\n",
        "\n",
        "    # Plot the actual values\n",
        "    mask = data['vgs'] == vgs_val\n",
        "    ax.plot(vds[mask], 10**y_norm[mask], label=f'Actual (Vgs = {vgs_val}V)', linestyle='--')\n",
        "\n",
        "    # Plot the predicted values\n",
        "    mask = data['vgs'] == vgs_val\n",
        "    ax.plot(vds[mask], 10**y_pred[mask], label=f'Predicted (Vgs = {vgs_val}V)')\n",
        "\n",
        "    ax.set_title(f'Vgs = {vgs_val}V', fontsize=14)\n",
        "    ax.set_xlabel('Drain-to-Source Voltage (V)', fontsize=12)\n",
        "    ax.set_ylabel('Drain Current (A)', fontsize=12)\n",
        "    ax.legend()\n",
        "    ax.grid(True)\n",
        "\n",
        "# Plot data for each file with specific vgs values\n",
        "plot_data(data1, ax1, 2.0)  # vgs = 2.0V for val03.csv\n",
        "plot_data(data2, ax2, 3.5)  # vgs = 3.5V for val04.csv\n",
        "plot_data(data3, ax3, 4.2)  # vgs = 4.2V for val06.csv\n",
        "\n",
        "# Set the overall title\n",
        "fig.suptitle('Actual and Predicted Drain Current vs. Drain-to-Source Voltage', fontsize=16, y=1.05)\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "plt.savefig('plot_vds.png')\n",
        "\n",
        "# Download the plot as an image file\n",
        "# files.download('plot_vds.png')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 632
        },
        "id": "ollS3ifNoJPW",
        "outputId": "f754b1ed-a10b-4241-ff5a-2ce52aded8d0"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1/1 [==============================] - 0s 33ms/step\n",
            "1/1 [==============================] - 0s 33ms/step\n",
            "1/1 [==============================] - 0s 29ms/step\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/pandas/core/internals/blocks.py:329: RuntimeWarning: divide by zero encountered in log10\n",
            "  result = func(self.values, **kwargs)\n",
            "<ipython-input-13-f1242fe595ae>:21: RuntimeWarning: divide by zero encountered in log10\n",
            "  y_norm = np.log10(y_true)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x500 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Assume the length of Drain to source common being 5nm and assuming no extension or contraction\n",
        "# For Parallel\n",
        "train_data = pd.read_csv('training_data.csv')\n",
        "val01 = pd.read_csv('val01.csv')\n",
        "val02 = pd.read_csv('val02.csv')\n",
        "val03 = pd.read_csv('val03.csv')\n",
        "val04 = pd.read_csv('val04.csv')\n",
        "val06 = pd.read_csv('val06.csv')\n",
        "\n",
        "train_data[\"Vfg\"] = \"0V\"\n",
        "train_data[\"Vfd\"] = \"0V\"\n",
        "\n",
        "val01[\"Vfg\"] = \"0V\"\n",
        "val01[\"Vfd\"] = \"0V\"\n",
        "\n",
        "val02[\"Vfg\"] = \"0V\"\n",
        "val02[\"Vfd\"] = \"0V\"\n",
        "\n",
        "val03[\"Vfg\"] = \"0V\"\n",
        "val03[\"Vfd\"] = \"0V\"\n",
        "\n",
        "val04[\"Vfg\"] = \"0V\"\n",
        "val04[\"Vfd\"] = \"0V\"\n",
        "\n",
        "val06[\"Vfg\"] = \"0V\"\n",
        "val06[\"Vfd\"] = \"0V\""
      ],
      "metadata": {
        "id": "He1zIGHISWJy"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "###`Assumptions here are - `\n",
        "1) High Gravitational Forces to be assumed to the power of 10^9N.\n",
        "\n",
        "2) Event horizon for high Gravitational body to be 3*10^30m according to  Schwarzschild Radius.\n",
        "\n",
        "3) Gradual Channel Approximation (GCA) Approach used for maintaining the channel shape and its resistance.\n",
        "\n"
      ],
      "metadata": {
        "id": "n10Y546i-IL-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "train_data[\"Vfg\"] = np.sqrt(train_data[\"Vgs\"]**2 + 6.4009)\n",
        "train_data[\"Vfd\"] = train_data[\"Vds\"] + 2.53\n",
        "\n",
        "val01[\"Vfg\"] = np.sqrt(val01[\"vgs\"]**2 + 6.4009)\n",
        "val01[\"Vfd\"] = val01[\"vds\"] + 2.53\n",
        "\n",
        "val02[\"Vfg\"] = np.sqrt(val02[\"vgs\"]**2 + 6.4009)\n",
        "val02[\"Vfd\"] = val02[\"vds\"] + 2.53\n",
        "\n",
        "val03[\"Vfg\"] = np.sqrt(val03[\"vgs\"]**2 + 6.4009)\n",
        "val03[\"Vfd\"] = val03[\"vds\"] + 2.53\n",
        "\n",
        "val04[\"Vfg\"] = np.sqrt(val04[\"vgs\"]**2 + 6.4009)\n",
        "val04[\"Vfd\"] = val04[\"vds\"] + 2.53\n",
        "\n",
        "val06[\"Vfg\"] = np.sqrt(val06[\"vgs\"]**2 + 6.4009)\n",
        "val06[\"Vfd\"] = val06[\"vds\"] + 2.53\n",
        "\n",
        "# train_data[\"Ids_g\"] = 10**-4 * ((train_data[\"Vfg\"] - 5) * train_data[\"Vfd\"] - (train_data[\"Vfd\"]**2 / 2))\n",
        "# val01[\"Ids_g\"] = 10**-4 * ((val01[\"Vfg\"] - 5) * val01[\"Vfd\"] - (val01[\"Vfd\"]**2 / 2))\n",
        "# val02[\"Ids_g\"] = 10**-4 * ((val02[\"Vfg\"] - 5) * val02[\"Vfd\"] - (val02[\"Vfd\"]**2 / 2))\n",
        "# val03[\"Ids_g\"] = 10**-4 * ((val03[\"Vfg\"] - 5) * val03[\"Vfd\"] - (val03[\"Vfd\"]**2 / 2))\n",
        "# val04[\"Ids_g\"] = 10**-4 * ((val04[\"Vfg\"] - 5) * val04[\"Vfd\"] - (val04[\"Vfd\"]**2 / 2))\n",
        "# val06[\"Ids_g\"] = 10**-4 * ((val06[\"Vfg\"] - 5) * val06[\"Vfd\"] - (val06[\"Vfd\"]**2 / 2))\n",
        "\n",
        "\n",
        "train_data[\"Ids_g\"] = 10**-4 * abs((train_data[\"Vfg\"] - 5) * train_data[\"Vfd\"] - (train_data[\"Vfd\"]**2 / 2))\n",
        "val01[\"Ids_g\"] = 10**-4 * abs((val01[\"Vfg\"] - 5) * val01[\"Vfd\"] - (val01[\"Vfd\"]**2 / 2))\n",
        "val02[\"Ids_g\"] = 10**-4 * abs((val02[\"Vfg\"] - 5) * val02[\"Vfd\"] - (val02[\"Vfd\"]**2 / 2))\n",
        "val03[\"Ids_g\"] = 10**-4 * abs((val03[\"Vfg\"] - 5) * val03[\"Vfd\"] - (val03[\"Vfd\"]**2 / 2))\n",
        "val04[\"Ids_g\"] = 10**-4 * abs((val04[\"Vfg\"] - 5) * val04[\"Vfd\"] - (val04[\"Vfd\"]**2 / 2))\n",
        "val06[\"Ids_g\"] = 10**-4 * abs((val06[\"Vfg\"] - 5) * val06[\"Vfd\"] - (val06[\"Vfd\"]**2 / 2))"
      ],
      "metadata": {
        "id": "VrEGYrmhQl4H"
      },
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(18, 5))\n",
        "\n",
        "# Function to plot data\n",
        "def plot_data(data, ax, vgs_val):\n",
        "    val_feature = data.iloc[:, [-3, -2]]\n",
        "    X = val_feature\n",
        "    y_true = np.ravel(data[\"id\"])\n",
        "\n",
        "    # Normalize input data and target variable\n",
        "    X_norm = np.log10(X)\n",
        "    y_norm = np.log10(y_true)\n",
        "    y_norm = y_norm.reshape(-1, 1)\n",
        "\n",
        "    # Predict the target variable\n",
        "    y_pred = model.predict(X_norm)\n",
        "\n",
        "    # Plot the result\n",
        "    vds_data = data[\"Vfd\"]\n",
        "    vds = np.ravel(vds_data)\n",
        "    vds = vds.reshape(-1, 1)\n",
        "\n",
        "    # Plot the actual values\n",
        "    mask = data['vgs'] == vgs_val\n",
        "    ax.plot(vds[mask], 10**y_norm[mask], label='Actual', linestyle='--')\n",
        "\n",
        "    # Plot the predicted values\n",
        "    mask = data['vgs'] == vgs_val\n",
        "    ax.plot(vds[mask], 10**y_pred[mask], label='Predicted')\n",
        "\n",
        "    # Plot the Ids_g values\n",
        "    mask = data['vgs'] == vgs_val\n",
        "    ax.plot(vds[mask], data.loc[mask, 'Ids_g'], label='Using Id Expression', linestyle='--', color='green')\n",
        "\n",
        "    ax.set_title(f'Vfg = {data[\"Vfg\"][0]}V', fontsize=14)\n",
        "    ax.set_xlabel('Drain-to-Source Voltage (V)', fontsize=12)\n",
        "    ax.set_ylabel('Drain Current (A)', fontsize=12)\n",
        "    ax.legend()\n",
        "    ax.grid(True)\n",
        "\n",
        "# Plot data for each file with specific vgs values\n",
        "plot_data(val03, ax1, 2.0)  # vgs = 2.0V for val03.csv\n",
        "plot_data(val04, ax2, 3.5)  # vgs = 3.5V for val04.csv\n",
        "plot_data(val06, ax3, 4.2)  # vgs = 4.2V for val06.csv\n",
        "\n",
        "# Set the overall title\n",
        "fig.suptitle('Actual and Predicted Drain Current vs. Drain-to-Source Voltage at Influential Gravitational Fields', fontsize=14, y=1.05)\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "plt.savefig('plot_vds_high_grav.png')\n",
        "# files.download('plot_vds_high_grav.png')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 595
        },
        "id": "tSxpY4o9TWSI",
        "outputId": "6dfe0d17-26b0-47e0-9ccf-f950a28d4e4f"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1/1 [==============================] - 0s 23ms/step\n",
            "1/1 [==============================] - 0s 21ms/step\n",
            "1/1 [==============================] - 0s 22ms/step\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-62-e6077cbf6016>:11: RuntimeWarning: divide by zero encountered in log10\n",
            "  y_norm = np.log10(y_true)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x500 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5))\n",
        "\n",
        "# Function to plot data\n",
        "def plot_data(data, ax):\n",
        "    val_feature = data.iloc[:, [-2, -3]]\n",
        "    X = val_feature\n",
        "    y_true = np.ravel(data[\"id\"])\n",
        "\n",
        "    # Normalize input data and target variable\n",
        "    X_norm = np.log10(X)\n",
        "    y_norm = np.log10(y_true)\n",
        "    y_norm = y_norm.reshape(-1, 1)\n",
        "\n",
        "    # Predict the target variable\n",
        "    y_pred = model.predict(X_norm)\n",
        "\n",
        "    # Plot the result\n",
        "    vg1 = data[\"Vfg\"]\n",
        "    vg = np.ravel(vg1)\n",
        "    vg = vg.reshape(-1, 1)\n",
        "    ax.plot(vg, data[\"Ids_g\"], 'red', label='Using Id Expression', linestyle=\"dotted\")\n",
        "    ax.plot(vg, 10**y_norm, 'black', label='Actual', linestyle=\"dashed\")\n",
        "    ax.plot(vg, 10**y_pred, 'green', label='Predicted')\n",
        "\n",
        "    ax.set_title(f'{data.columns[0]} = {data[\"Vfd\"][0]}V', fontsize=14)\n",
        "    ax.set_xlabel('Gate Voltage (V)', fontsize=12)\n",
        "    ax.set_ylabel('Drain Current (A)', fontsize=12)\n",
        "    ax.legend()\n",
        "    ax.grid(True)\n",
        "\n",
        "# Plot data for each file\n",
        "plot_data(val01, ax1)\n",
        "plot_data(val02, ax2)\n",
        "\n",
        "# Set the overall title\n",
        "fig.suptitle('Actual and Predicted Drain Current vs. Gate Voltage at Influential gravitational fields', fontsize=14, y=1.05)\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.savefig('plot_vgs_high_grav.png')\n",
        "plt.show()\n",
        "# files.download('plot_vgs_high_grav.png')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 583
        },
        "id": "uri6v2IiUJuO",
        "outputId": "f54fb615-8e2c-4f7c-cbd5-a9ea8c733bcc"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1/1 [==============================] - 0s 38ms/step\n",
            "1/1 [==============================] - 0s 58ms/step\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x500 with 2 Axes>"
            ],
            "image/png": 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/IiEhQSXvtGnTBACxefNmpfTs9pR69OiRStq7d++Ep6ensLKyUrp7n/6u55w5c5TWmTx5sgAgZs+erUhLSUkRJUuWFBKJROkOUmpqqujevbtiW5rIrKfUlClTBADRpEkTRZp823379hXJyclK+W/fvi309fVFlSpVVO4Cz549WwAQCxYsUKTJe/5UqVJFqefPf//9J2xtbTXuKXXgwAEBQHh6eqrsNykpSYSHhyveZ/Y5JiYmCjc3N2FhYSGuXLmitOz06dNCT09PtGnTRpEWHR0tLC0thZmZmbh//77Sdry8vFR682VGk55SQgjx008/CQDip59+UqTJvxtmZmbixo0bKutERUWJ169fq6QfP35cSKVSMWDAAKX0zHpKARBDhw5V+i7/8ccfGpVdCNnnYWBgIPT19cWHDx+yzP/x/nPSU8rZ2VmEhoaqXUd+7r9//15p2atXr4SlpaUoXry4yl33bdu2CQBi+PDhirTsfoczKnNWjh07JgCIIUOGqCwbN26cACAOHjwohJB97hKJRNSoUUPlu5qcnCzevn2brX2nt2HDBgFA9OzZM0frh4aGqpQpNTVV9OvXTwAQZ86cUVqWWV1l97qTmTlz5ggAYvLkySrLOnTooFS/wcHBQl9fX9jb24unT58q8sXHx4uGDRsKAGLjxo1K21B3Dmf125Kd35L79+8LPT09Ubx4caXeSTExMaJChQpq9y//zVi9erVSekREhHBxcRF2dnYafVcjIiLU9jKWnyszZ85USs/ub+rH66nrKZWd719mMUVu9JTS9jUkox4p2f3uZaenVE7OP/n2q1atqvZ3KjuxWkxMjDAxMREVKlRQyS+PE8aPH69Iy6iOsjrmx48fq6S9ePFCODk5CQ8PD6V0+W97Rr1g1Z1X2b225OTcUXcMSUlJonnz5kJPT0/lNzO7v1cZ5c+ozrN7HVJ3/chuTLl06VIBQCxevFilnOrORaKCgrPvUYGXlJSETZs2wdLSUnFHw9zcHB06dMDTp09x7NgxpfyrVq1CamoqZs6cqXKHUiKRfNaxHooXL672zvnw4cMBQKWs2fXxXXZAVhd9+vRBdHQ0Ll68qLLc3d0dEyZMUEqTj12SPv+ZM2fw+PFjtGnTBg0bNlSkSyQSzJo1S9FDJjuCg4MxdepUTJ06FRMmTICXlxemT58OY2Nj/Pzzz0p5DQ0NMW/ePJX9rFq1CsnJyfj1119RtGhRpWUTJ06EnZ0dtm3bpkjbuHEjANmdVTMzM0V68eLFszUo8ooVKwDIet19vN/0PV+ycvDgQYSEhGDChAmoVq2a0rKGDRuiffv2OHTokGJ8HH9/f8TExKBfv34oU6aMIq+BgYFKneUW+Xfi1atXKssGDRoET09PlXQrKyvY2NiopDdp0gQVK1bM1rluZmaGuXPnKvVw6t27N/T19dWe0x97/fo1kpKSYGtrC2NjY433+ykmTJiQ6Vhk8+bNUxnYeuPGjYiJicHs2bNVepF169YN1atXx/bt21W2pel3OKeaNGmC4sWLY+fOnUhKSlKkp6amYuvWrbCzs4OPjw8A2fVACAFjY2OVHml6enqf1NM0PDwcgPrxeKKiohTXEvlLftdcrkSJEirXD4lEgmHDhgHI3vU3u9edzMjP5Q0bNiA1NVWRHhkZiYMHD8LJyQktW7YEAGzduhXJyckYN24cXFxcFHmNjIwwd+5cAMD69es1Po6MZOe3ZNu2bUhJScG4ceOUegRaWFhg8uTJKtt59eoVduzYgaZNm2LAgAFKy+zt7TFhwgRERkZq9HnY29vD3NxcJb1nz56wtLT85N9UTXzu71926Oo1JDe/ex/L7vmX3rRp09T+TmUnVrOwsICvry/u3LmDK1euKOXftGkTACgmdPkU8l5c6Tk6OqJjx454+PAhQkNDP2n7Ob22ZOfcUXcM+vr6GDx4MFJSUnDixIlPOobsyK3rUE5jSnUTW6g7F4kKCvb/owJv3759iIyMRP/+/ZX+4OzVqxc2b96MNWvWoEWLFor0CxcuAIBSWl4RQmDdunVYv349bt26hejoaKU/QuSDoObUy5cvMWfOHPz9998IDQ3Fhw8flJar237VqlVV/nh0dnYGIPtDT+769esAZI+bfMzV1RUuLi7Znmb70aNHmDZtGgBZo0qxYsXQvXt3fP/99yoNHe7u7moH5pRP0f3PP/8gICBAZbmBgYFSF/7MjkNdWkYuXLgAIyMjNGrUSON11JGX//79+2ofNQ0PD0dqaioePHiAmjVrZlr+evXq5Xm379q1a2e4LDAwEIsXL8b58+fx6tUrJCcnK5Zl5xHDMmXKqPzhKW/4S3+O6pLM6sXY2FhtQ578XDh//jwePXqksjw+Ph6vXr3Cq1evlL4Lmn6Hc0oqlaJHjx6YN28eDh06pHhMJCAgAGFhYRgxYoTivLO0tESrVq1w6NAhVK9eHZ07d0bjxo1Rq1atT3o0OStRUVGKa4mcq6ur0iNGiYmJWLZsGbZv34579+4hNjYWQgjF8uxcf7N73cmMg4MDWrdujX379uHo0aOKBr5NmzYhKSkJvXv3VvxBf/XqVQDqH5eqV68ejI2Nce3aNY2PIyPZ+S2RX5PS36yQUzeD6sWLF5GSkoKEhAS117yHDx8CAO7du6eYFTQze/fuxapVq3DlyhW8ffsWKSkpasv5uXzu71926Oo1JDe/ex/L7vmXXkbX6ezGaj179sS2bduwadMmVK9eHQAQExODAwcOwNPTM8ePLKf3+PFjzJ49G8ePH8fz58+RkJCgtPzFixcaPxKvTk6vLdk5d969e4cFCxbA398fjx49QlxcnMox5JXcug5lN6Zs27YtJk2ahGHDhiEgIAAtW7ZEo0aN1N4IICpI2ChFBZ58rJiPxxhp1qwZihcvjn379uHNmzeKOxDR0dGQSCSfder5jIwcORLLli2Di4sL2rVrB0dHR8X4NdOmTVMJMrLjzZs3qFWrFp4+fYoGDRrA29sb1tbW0NPTw7Vr17Bv3z612/94BjIgbSyW9MG9fEay9Hci0ytWrFi2G6V8fHxw+PBhjfJm1PPozZs3AKBxL6Ho6GhIpVK1DVya9m6Sb6d48eJZjk+UFXn5t2zZkmk+efCW2eegp6en0msjN8gDRTs7O5VlGdXZrl270LVrV5ibm8PHxwdubm4wNTWFRCJRjJ2hKXXnKCA7T9OfoxkpWrQoDAwM8Pr1ayQkJOTKmFFZyexcsre3Vzvmj/xcWL58eabbjouLUzp/Nf0Of4qePXti3rx52Lx5s6JRSt4L4ONZ43bt2oVZs2Zh69at+PHHHxVl7Nu3L2bNmgVTU9MclUFep+r+cHFzc1P6I1ddj7hOnTrhwIEDKFOmDLp27Qp7e3sYGBggKioKS5Ysydb1N7vXnaz0798f+/btw9q1axWNUuvWrQMApVkv5T0m1Z1fEokExYoVw/Pnzz+pLNn9LZGXSd01SV055XX377//4t9//82wHB//warOwoULMX78eNjZ2aFFixZwdnZW9EBYvHjxJ/2maiovvn+a0tVrSG5+9z6W3fNPk+XZjdVatGiBYsWKYfv27ViwYAH09PSwe/dufPjwIcNZNbMjODgYtWvXRkxMDJo0aYK2bdvC0tISUqlUMU7Zp57rOb22aHruJCYmonHjxrhy5QqqVauGnj17omjRotDX11eMgZUX31e53LoOZTemdHNzw7lz5zB16lQcOnQIO3fuBACUK1cO06dPR+fOnbNzGET5BhulqEB79uwZjhw5AgCZ9ljZvHkzRo4cCUA28KEQAmFhYShevPgn7V8ikSj1/kgvOjpaaYr7ly9fYvny5ahcuTKCgoKU/jALDw9XucufXWvWrMHTp08xY8YMlS7rc+bMwb59+z5p+/JjefnypdrlERERn7T9rGQ0cK88IIqJiYGFhUWW27GyskJqaipevXql0siSnWOwtrZW9GL6lIYpefkPHDigUa+AzD6HlJQUvH79+pPP648FBgYCAGrVqqWyLKPPZerUqTA2Nsbly5fh4eGhtEzd4yOfk76+PmrXro1///0Xp06dQvPmzTVeNzvf8Y/Xy2yb6sjPhZs3b2o0eHteqlSpEqpWrYqDBw8iOjoaBgYG+PPPP1G2bFmV88LU1BQzZ87EzJkz8eTJE5w4cQIrV67EkiVL8OHDB6xatSpHZZAPsn7y5Mlsf+8uXryIAwcOwMfHB3/99ZfSo0Tnzp3DkiVLslWW7F53stKqVSs4OjoqbqI8evQIt27dQqNGjVC6dGmV/UZERKj0ihBCICIiIsNGXE1l97dEvr+XL1+qlEndNVWef9y4cViwYEGOy5mcnIwZM2bA0dER165dU2qUEEJg3rx5Od62rpCf4+quQfIbFOnp4jUkt797H8vu+ZeeumtxTmI1PT09fP3111i8eDGOHTsGHx8fbNq0CVKpFN27d8/JYSn55Zdf8PbtW2zatEnlUcDBgwfj5MmTn7yPz31t2bdvH65cuYL+/fvjjz/+UFq2fft2bNiwIcfbzoncug7lJKasVKkSdu/ejaSkJFy+fBl///03li5dqphAKKsefkT5EceUogJt/fr1SE1NRcOGDdG/f3+VV+/evQGk9aYC0rpryxuzMiMPnjK6U1ikSBG1d45CQkJUui0/fvwYQgh4e3ur9BQ4ffp0lmXJiryrvrwXQ25vX979XN22QkND8ezZs0/eR07UqVMHQNpjC1nJ7DiyU0+1a9dGQkKCRsFgZueRvPxBQUEa7Tez8gcFBWXYgJJTJ0+exOnTp2Fvb4+mTZtqvN6jR49Qvnx5lQapsLAwPH78OFfLqAn5GBezZs1S6lGjTvq7tdn5jn+q7J4LOaGnp5fjng89e/ZEfHw8du/ejT///BOxsbFZjpXi7u6Ofv364eTJkzA3N8f+/ftztG8A8PDwQMOGDfH06VNs3rw5W+vKr4+tW7dWGdsmo+99ZnWV3etOVvT09NC7d28kJCRg8+bNWLt2LYC081ZOPu6cvKE4vfPnzyM+Pl5pxq7M9geovyZl97dEfk1S19tA3exTtWrVgkQi+eTz/NWrV4iOjka9evVUeslcunRJ5ZFDIOvfdF0jnyVP3TVI/rhVerp4DcnJdy87snv+ZSWnsZq8R9TmzZvx7NkznDx5UjEenyZy8p0UQqg97pyc57l1bcnI545Rsyu3rkOfElMaGBigbt26mDZtGpYuXQohBA4ePPhJ5SHSVWyUogJL/sy/RCLBhg0b8Mcff6i81q9fj3r16uHGjRu4dOkSANldJT09PUyePFnlESIhhNKjIfJH/jJqcKlVqxZCQkKUGiYSExMxduxYlbzyO09nz55VGpvgv//+w6RJk3JYC6rbP3PmjFL61q1bcejQoU/efsOGDeHu7o6DBw8q7UMIgR9++EFrQf7QoUOhr6+PESNG4OnTpyrLo6KilIJ3eeA4ffp0pW7Zz58/z9YdW/kAraNGjVJ0A5dLTk5WukOW2XnUvn17lChRAosWLcKpU6dUliclJSnVd/v27WFpaYm1a9fiwYMHSvmyGtQ1uw4cOICOHTsCkE3lnJ3HrlxdXREcHKxUD/Hx8RgyZIjSYNl5pWfPnvjiiy8QGBiIvn374t27dyp5IiIiMHDgQKVHSrPzHf9Uffv2hYWFBX788Ufcvn1bZfn79+8/uRHExsYGr169Qnx8fLbX7d69O/T09LBp0yZs2rQJEolEpVEqMjISt27dUln37du3SEhIUHms7t69exqPvQQAS5cuhYmJCYYOHZrhQOIxMTEqDY8ZXR9v376N2bNnq91OZnWV3euOJuSP6f3+++/Yvn07rKys0KlTJ6U83bt3h76+PhYtWqT0W5WYmIjvvvsOANCnT58s95XZNSm7vyXdunWDVCrFwoULlSZDiIuLU/t4o4ODA7p06YKzZ89i/vz5ahuJz58/j/fv32d6DPb29jAxMcGVK1eU8r59+xYjRoxQu05Wv+m6Rt4LcePGjUpxQ1BQkNpHvnXxGpKT7152ZPf8y0pOY7Xq1aujQoUK+PPPP7Fq1SoIIbL16F5OvpNz5sxRe73NyXmeW9eWjGR0DCdPnsTq1atzvN2cyq3rUHZjysuXLyselUxPHivl1WQsRHmNj+9RgXX8+HE8efIkywEC+/bti6CgIKxZswY1a9aEp6cnFi9ejJEjR6JixYrw9fWFq6srwsPDcerUKbRu3Voxa1OTJk0gkUjwww8/4Pbt27CysoK1tbViBpaxY8fiyJEjaNWqFb7++muYmpri6NGjsLa2VhmzSj5Lyp49e1CzZk00a9YMEREROHjwIJo1a6Z2UNLs6NmzJ+bOnYsRI0bgxIkTcHV1xfXr1xEQEICvvvoKe/fu/aTtS6VS/P7772jVqhW8vb0V3YyPHz+OsLAwVK5cGTdu3PikfeREpUqVsGLFCgwZMgRly5ZFq1atUKpUKbx79w6PHz/GyZMn0adPH6xcuRKA7DPt27cv1q1bB09PT3To0AEJCQnYsWMH6tatq/FdqlatWmH8+PFYsGABPDw80KFDB9jb2+P58+cICAjA+PHjFYMsN23aFAsWLMCgQYPQsWNHmJmZwdXVFT179oSRkRF2796NL7/8Eo0aNULTpk3h6ekJiUSC0NBQnD59GkWLFlX84W5lZYWlS5eiT58+qFWrFrp16wYrKyscPHgQJiYmORor7dKlS4qBPuPj4xEWFoazZ88iODgYJiYmWL58ebaD0REjRmDEiBGoVq0aOnXqhOTkZBw9ehRCCFSpUkUxOGhe0dfXh7+/Pzp37owNGzZg//79aNGiBdzd3ZGYmIg7d+4gMDAQSUlJSg0t2fmOfyr5jG2dO3dGlSpV0LJlS5QrVw4JCQmKhrH69etrPA6bOk2bNsWlS5fw5Zdf4osvvoChoSG8vLzg5eWV5boODg7w9vbGkSNHIJVK0bBhQ5UZTJ8/f45q1aqhSpUqqFy5MooXL47Xr19j3759SEpKwvjx45Xyly9fHgCy7L0mV61aNRw8eBBdu3ZF9+7d4efnBy8vLxQrVgzv3r3D06dPceTIESQmJioNfFy7dm3Url0bO3fuRFhYGOrWrYunT59i//79aN26NXbv3p2tusrudUcTHh4e8PLyUjRODx48WGWGplKlSmHu3LkYN24cKleujC5dusDMzAwHDhzA/fv30b59e41m+srsmpTd35KyZcvi+++/x6xZs+Dp6YkuXbpAX18fe/fuhaenJ27duqXyqOWKFStw//59TJw4EZs2bUK9evVgbW2NZ8+e4dKlS3j48CHCwsIybQiXSqUYOnQoFi5ciCpVqqBt27aIiYnB33//DVdXV7WzNGZ23Lqobt26aNCgAY4fP4569erBy8sLoaGh2LdvH9q2bYs///xTKb8uXkNy8t3Ljpycf5n5lFitZ8+emDRpEubNmwdTU1PFTR1NNG3aFLt370bHjh3x5ZdfwtjYWHFeDx48GOvWrUPHjh3RpUsXFC1aFOfOncOVK1fQunVr/PXXX0rbKleuHJycnLB9+3YYGRnB2dkZEokEI0aMyPCR89y6tmSkbdu2cHNzw7x583Dr1i1UqlQJ9+/fx8GDB9GhQ4dPPg9yIjeuQ9mNKTdt2oRVq1bBy8sLpUqVgqWlJe7cuYNDhw7BxsYGffv2/dyHTaQdgqiA+vrrrwUAsW7dukzzRUdHCxMTE2FlZSXev3+vSD9x4oRo06aNsLGxEYaGhsLZ2Vl07NhR/Pvvv0rrr1+/Xnh6egojIyMBQLi6uiot37Vrl/D09BSGhobCwcFBjBgxQrx79064urqq5H337p0YN26ccHNzE0ZGRsLDw0PMmDFDJCYmCgCiUaNGSvl79+4tAIgnT55oVCfXrl0TLVq0EEWKFBEWFhaiUaNG4tixY2LdunUqdfXkyRMBQPTu3VvtttSVRwghTp06Jby8vISJiYmwsbERnTt3FqGhoaJRo0ZC00uOfN8+Pj4a5c+oLOlduHBBdOvWTTg5OQkDAwNha2srqlevLr7//ntx9+5dpbzJycli9uzZomTJksLQ0FCULFlSzJo1SwQHB6utk8yObc+ePaJJkybCyspKGBkZCTc3N9GzZ09x69YtpXzz5s0THh4ewsDAQO3x/Pfff2LUqFHCw8NDGBkZCUtLS1G+fHkxYMAAERAQoLLfP//8U9SoUUMYGRkJe3t7MWDAAPHmzRu1511GTpw4IQAovUxNTYWzs7Pw8fERc+bMES9evFC7rp+fnwAgTpw4oXZ5amqqWLlypahYsaIwNjYWDg4Oon///uLly5dq61PdOSpE5p99do41fbl2794tfH19hZOTkzA0NBSmpqaiUqVKYuTIkeLOnTsq62TnO57Vd1aTMt+7d0/0799fuLq6CkNDQ1GkSBHh6ekpRo4cKS5cuKDIl5Pv8Lt378TAgQOFo6Oj0NPTEwCEn59fpuVJb/PmzYpzZdWqVSrL3759K6ZOnSq8vLyEo6OjMDQ0FE5OTqJly5bi77//VlvGnIQqb9++FbNnzxYNGzYURYsWFfr6+sLS0lJUqVJFDBs2TJw/f15lnZcvX4p+/foJJycnYWxsLDw9PcXy5cvF48eP1dajJnWVneuOJjZs2KCok/Sf9cf27dsnGjVqJCwsLISRkZHw9PQUCxcuFElJSSp5M/oOZXZNys5vidyKFStE+fLlFb+n48ePF8+ePRMARPv27VXyv3//XsybN0/UqFFDmJmZCRMTE+Hu7i58fX3Fxo0b1R7LxxITE8XPP/+suG6WKFFCjBs3LsPvZ1bHnRH59zooKEiRlpPvX2bXzYx+Z169eiV69eolbGxshImJiahbt674559/Mv0stHUNyWh72f3uZSeekMvO+ZfV9rMbq8k9ffpUSKVSAUB8/fXXavNkVEdJSUli4sSJokSJEkJfX18lz4kTJ0SDBg2EhYWFsLa2Fq1atRKXL1/O8Jw6d+6c4hohv6bIf5cyOw81vbbk5Nx5/Pix6Nixo7CzsxOmpqaiVq1aYvv27YpY5OPra3Z/4zPKn1lZs3Mdyuj3PTsx5blz58S3334rKlWqJKytrYWJiYnw8PAQw4cPF6GhoRofK1F+IxFCw9uPRERERES55NixY2jevDkmTpyIuXPnars4VMjw/CMi0g0cU4qIiIiIPpvIyEiVcQWjoqIUY/D4+vpqoVRUWPD8IyLSbRxTioiIiIg+my1btmDBggVo2rQpnJycEBYWhsOHD+Ply5fo06cP6tWrp+0iUgHG84+ISLexUYqIiIiIPpv69eujRo0aOHbsGN68eQM9PT2UL18eP/30E4YOHart4lEBx/OPiEi3cUwpIiIiIiIiIiLKcxxTioiIiIiIiIiI8hwbpYiIiIiIiIiIKM+xUYqIiIiIiIiIiPIcG6WIiIiIiIiIiCjPsVGKiIiIiIiIiIjyHBuliIiIiIiIiIgoz7FRioiIiIiIiIiI8hwbpYiIiIiIiIiIKM+xUYqIiIiIiIiIiPIcG6WIiIiIiIiIiCjPsVGKiIiIiIiIiIjyHBuliIiIiIiIiIgoz7FRioiIiIiIiIiI8hwbpYiIiIiIiIiIKM+xUYqIiIiIiIiIiPIcG6WIiIiIiIiIiCjPsVGKiIiIiIiIiIjyHBuliIiIiIiIiIgoz7FRioiIiIiIiIiI8hwbpYiIiIiIiIiIKM+xUYqIiIiIiIiIiPIcG6WIiIiIiIiIiCjPsVGKiIiIiIiIiIjyHBuliIiIiIiIiIgoz7FRioiIiIiIiIiI8hwbpYiIiIiIiIiIKM+xUYqIiIiIiIiIiPIcG6WIiIiIiIiIiCjPsVGKiIiIiIiIiIjyHBuliIiIiIiIiIgoz7FRioiIiIiIiIiI8hwbpYiIiIiIiIiIKM+xUYqIiIiIiIiIiPIcG6WIiIiIiIiIiCjPsVGKiIiIiIiIiIjyHBuliIiIiIiIiIgoz7FRioiIiIiIiIiI8hwbpYiIiIiIiIiIKM+xUYqIiIiIiIiIiPIcG6WIiIiIiIiIiCjPsVGKiIiIiIiIiIjyHBuliIiIiIiIiIgoz7FRioiIiIiIiIiI8hwbpYiIiIiIiIiIKM+xUYqIiIiIiIiIiPIcG6WIiIiIiIiIiCjPsVGKiIiIiIiIiIjyHBuliIiIiIiIiIgoz7FRioiIiIiIiIiI8hwbpYiIiIiIiIiIKM+xUYqIiIiIiIiIiPIcG6WIiIiIiIiIiCjPsVGKiIiIiIiIiIjyHBuliIiIiIiIiIgoz7FRiiiP9OnTBxKJBCEhIdouChEREVG+wRiKiKjgYqMUEWls7ty5kEgkkEgkOHfunMbrBQYGKtZT91q/fr1S/tevX+P3339Hu3btULJkSRgZGcHW1hZffvkl/vnnnwz3c/fuXfTo0QMODg4wMjKCq6srRo0ahTdv3qjNHx8fjxkzZqBChQowNjZGkSJF8OWXX+Lff//NcB+HDx+Gt7c3rK2tYWJiAk9PTyxatAgpKSlq8//333/49ttvUaJECRgaGsLJyQl9+/bFs2fP1OZPTU3FsmXLUL16dZiamsLS0hJeXl7Yv39/hmU6f/482rdvD1tbWxgZGcHDwwNTpkzBhw8f1OZ/+/Ytxo8fj9KlS8PIyAh2dnbo1KkTbt++neE+tm7digYNGsDc3BxmZmaoVauWyueWXmH6LI4cOQKJRAIfH58MyyrXo0cPSCQSbN26Ncu8RESUf7m5uWUY9zRu3Fjj7YSEhGQaQ02dOlUpf1xcHDZv3owuXbqgTJkyMDExgbW1NRo1aoRt27ZluB/GKwU/XklPVz6L+/fvQyKRoFy5chluR+7HH3+ERCLBrFmzssxL+YwgojzRu3dvAUA8efJE20XJkZs3bwojIyNhZmYmAIigoCCN1z1x4oQAIBo1aiT8/PxUXlevXlXK/9tvvwkAwsnJSfTs2VN8//334ptvvhEmJiYCgJg3b57KPoKCgoSZmZmQSqWiQ4cOYvz48cLb21sAEGXKlBGvXr1Syv/hwwdRv359AUBUrlxZjB49WvTp00dYWFgIPT094e/vr7KPJUuWCADC0tJS9OnTR4wePVpUqlRJABCdOnVSyR8cHCzs7e0FANGiRQsxfvx40b59eyGRSIS9vb0IDg5Wyp+amio6duwoAIhSpUqJ4cOHi4EDByq28euvv6rsY8+ePUJfX18YGRmJ7t27i7Fjx4o6deoIAKJBgwYiPj5eKf+rV6+Eh4eHACDq1asnxo4dK77++mthaGgoTE1Nxblz51T2MXbsWAFAODg4iEGDBolhw4YJd3d3AUCMGzeu0H8WKSkpokSJEkIqlYqnT5+q7FsuKipKmJiYCGtra/Hhw4cM8xERkbL8GEO5uroKKysrtXHPunXrNN7OkydPBABRpUoVtds6ceKEUv6///5bABBFixYVXbp0Ed9//73o16+fsLa2FgDEsGHDVPbBeKVwxCu6+lk0bNhQABBnzpxR2Y5cSkqKcHZ2Fnp6euL58+cZ5qP8iY1SRHkkPwZUcomJiaJ69eqiTp064ptvvslxo5Sfn59G+QMCAsT+/ftFSkqKUvq9e/eElZWVMDAwUPlBkv/A79u3Tyl93rx5AoD49ttvldLnz58vAIjOnTuL5ORkRXpwcLCwtLQUdnZ2IiYmRpH+/PlzYWRkJIoUKSJCQkIU6UlJSaJ9+/YCgNi2bZvSPlq3bi0AiCVLliil79y5UwAQPj4+Sum7du1SBATv379XpEdGRgpXV1dhZGSkdP68f/9e2NnZCQMDA3Hp0iVFempqqhg2bJgAIGbPnq20D3n62LFjldLPnj0r9PT0RIUKFZTq/eLFiwKAKF26tHj9+rUiPTY2VtSqVUsAEGfPnlXaVmH8LPz8/AQAMX36dJGRFStWZPgHARERZSw/xlCurq7C1dX1k7cjb5Tq3bu3RvmvXr0qNm3aJBISEpTSw8PDhaurqwAgzp8/r7SM8UrhiVd08bNYt26dACD69esnMnLo0CEBQLRu3TrDPJR/sVGKKAOnTp0SAETfvn3VLo+IiBD6+vqifv36Sum3bt0SrVu3Fubm5sLS0lJ8+eWX4ubNm2oDqpSUFLF69WpRq1YtUaRIEWFsbCyKFy8u2rRpo3LnS5v8/PyEkZGRuH37tuI4PmejVGYGDRokAIhdu3Yp0oKDgwUAUatWLZX8KSkpomjRosLU1FTExsYq0uV3ZW7fvq2yzujRowUAsXbtWkXaH3/8IQCICRMmqOS/du2aACC8vLwUaR8+fBD6+vqiWLFiIjU1VWWdqlWrCgDi0aNHijR5g99ff/2lkn/x4sUCgJgyZYoi7dixY4rg6GNv374VAISrq6vS/p2dnYVUKhXv3r1TWcfX11cAEMePH1ekTZ48WQAQy5cvV8nv7+8vAIhevXop0grrZxESEiIkEokoWbKk2n0IIUTNmjUFAHHlyhW1y4mICgrGUNprlMrMrFmzBAAxf/58RRrjlcIVr+jiZxEbGyssLCyEubm5Un2n16lTJwFA7N27V+1yyt84phRRBho2bAg3Nzfs2bMH8fHxKsu3bduG5ORk9OzZU5F269Yt1K9fH3///TdatmyJYcOGITExEQ0aNMDjx49VtjFp0iQMHDgQb968Qffu3TF69Gg0bdoUt2/fxrFjxz7r8WnqypUr+Pnnn+Hn54cKFSp80rYePnyIxYsXY/bs2di0aROeP3+e7W0YGBgAAPT19RVp4eHhAAB3d3eV/FKpFCVKlMD79++VxsHKbB152vHjx7OV/+zZs0hISAAgGxcrOTkZrq6ukEgkGa5z4sSJz1Ima2trFClSBKGhoUrnXnh4OGxtbWFubp5rx61p/oL8Wbi6usLb2xuPHz9GYGCgyjq3bt3CpUuXUK1aNVSrVk1lORFRQcIYSiYhIQHr16/HrFmzsGzZMpw/fz7H23rx4gWWL1+OWbNmYc2aNXj06FG2t6EuhmK8UrjiFV38LMzMzNCtWzfExsZi586dKuu8fv0a+/fvh729Pdq0aaOynPI//ayzEBVOEokE33zzDWbOnIn9+/ejS5cuSss3bdoEQ0NDpfThw4cjJiYGmzdvRo8ePRTpP/zwA2bPnq2yjz/++ANOTk64ceMGTE1NlZZlNMDix/z9/XHt2jWNj6tq1arw9fXVKG9CQgJ69eqFqlWrYuLEiRrvIyNbt25VGuBZX18fI0aMwPz586Gnp5fl+jExMdi9ezeMjY3xxRdfKNJtbW0BAE+ePFFZJzU1FU+fPgUAPHjwAM2aNVOsExwcjCdPnqg0tsm38+DBA432IU9LTk7G48ePUb58eRQpUgR6enoIDQ2FEEIluMhqH+XLl/+kMkVHR+Pt27eKdUqVKqVY5+XLl4iNjVUJLnJ63P/99x/ev38PU1PTQvtZAED//v1x9OhRrF27Fk2aNFFatnbtWkUeIqKCjjGUTHh4OPr27auUVqtWLWzbtk3xu6ypo0eP4ujRo4r3EokEPXr0wMqVK2FmZpbl+ikpKdi4cSMkEgm8vb0V6YxXCle8ooufBSCLj1avXo21a9eqfGe2bNmCxMRE9OrVS9GwSgWMdjtqEem2+/fvCwCibdu2Sul37twRAISvr68iLTQ0VOD/Ax9+7N27d4oBJtN3PbexsRFubm4qAwpmh7xLu6av7HT/njhxojA0NBQ3b95U2V92Ht+7deuWmDNnjrh165aIjY0VERERwt/fX5QrV07tM+oZ+frrrwXUjNuTmpoqSpYsKQCIgwcPKi1buHCh4thnzZqlSJ82bZoAILp27ao0LsDjx4+FlZWVAGSDXKZP19PTEzY2NkqDWSclJYkOHToo9pH+GfkmTZoIAGLZsmVKZdqzZ48i/6BBgxTpGzZsEADEF198oTQQ9qtXr4Sbm5sAIAwNDRXp7969E5aWlsLAwEDlkbCRI0cq9rF161ZFet++fQUAMX78eKX8586dE/r6+gKQDawpd/LkSQFAeHh4iLdv3yrS4+LiFINiAhAvXrwo1J+FEELEx8eLokWLChMTExEdHa1IT0xMFHZ2dsLY2Fi8efNGEBEVBoU9hpo6daoICAgQERERIi4uTly9elX07NlT8XhU+rGHMhMRESF++ukncfnyZREVFSXevHkjjh07pvgN/uqrrzTazqRJkwQyGLeH8UrhiVd08bOQk4/x9eDBA6V0+WOLd+7cEVQwsVGKKAu1a9cWBgYGIjIyUpH2ww8/CABiz549irT9+/cLAGLo0KFqt9O4cWOVgGro0KECkA0EOHnyZBEQEKA0SKE2nT17VkilUpUGoJw0SmUkLCxM2NnZCX19fREREZFp3u+//14AEC1btlQKBOQOHz4sDAwMhFQqFV999ZWYMGGCaNGihQAgPD09BQAxZ84cRf6YmBhRoUIFAchmtBkzZozo27evsLS0FJUrVxYARLly5ZT28dNPPwkAwsrKSvTt21eMHj1aeHp6CisrK1GiRAkBQGkGkmvXrglzc3MByAamnDBhgujQoYOQSqWKfQwePFiRPykpSRGMlC5dWgwfPlx8++23olixYor8xsbGSmWSj1dgZGQkevToIcaNGyfq1asnDA0NFY1+27dvV+R/9uyZcHR0FIBsUMxx48aJ7t27C0NDQ8U+WrZsqbQPeRDt6Ogovv32WzF8+HBRsmRJUaJECUUQFh4eXug/CyGEGDVqlAAgVq5cqUiTB5Jff/21Sn4iooKssMZQmZH/pi5cuPCTthMXFyfKli0rAIjLly9nmlc+q3G1atXUjgvEeKVwxSu6+FkIIcQvv/wiAIjvv/9ekXb58mUByGb9o4KLjVJEWfj111+V7likpqYKV1dXUaRIEaW7c5s2bRIAxNSpU9Vup2vXrioBVVJSkpg/f77iB07+w9GrVy+lAC6vJSUlCQ8PD1G1alWRmJiotCw3G6WEEGLAgAECgNi/f3+GeeQDJjZt2jTTgPPcuXOidevWwtraWhgZGYkaNWqIP//8UwwfPlwAyoNPCiEb0HHMmDHCzc1NGBgYiOLFi4uJEycqBmhNP/ik3KZNm0Tt2rWFiYmJsLCwEF9++aW4deuW4u7O48ePlfLfvXtXdOnSRdjZ2QlDQ0NRoUIFsXr1asUMLukHnxRC1ttm6tSpokyZMsLQ0FDY2dmJQYMGiQcPHggAokSJEiplOnTokGjcuLEwNzcXJiYmwsvLS5w+fVq0adNGAMqDTwohxH///Sf69+8vnJychIGBgShZsqSYM2eO2L59uwCUB58UQjbg55IlS0TlypWFkZGRsLa2Fl27dhWhoaHC3Nxc6Ovrq5wnhfWzuHHjhgAgateurUiTz6Rz7NgxlfxERAVZYYyhsnLmzBkBaN7DKTMzZ84UAMTSpUszzLN69WohkUiEp6enePXqVYb5GK8UrnhFFz+LyMhIYWhoKJycnBQ3oOUz//3xxx8qx0AFBxuliLIQGRkpDAwMRN26dYUQQgQGBgpAdZrYnNzlS+/58+di69atonnz5irdYDPz559/Cj8/P41ff/75Z5bblM++oclLk+1lRt4D6uMpceXkDVKNGzcWcXFxOdpHo0aNBABx48YNjfLLp6bV9LHC+Ph4YWRkJIoWLapxmeSNe5k1xqUnn8EwO0Gsm5ubkEqlIioqSqP8fn5+WQa36clnBKpevbrGZSoMn4V8uuNbt26JFy9eCD09PeHu7p7hrHxERAVVYYyhsnLv3j1FL5hPtXLlSgFAzJ49W+3y33//XUgkElGxYkXx8uXLHO2D8UrBjVfU0fZn0blzZwFAHDhwQMTHx4siRYoIc3NztT38qOBgoxSRBtq2bSsAiIcPHyp69pw+fVopT07GQ1AnJSVFlC5dWkilUo26oX+O8RDev38v+vfvr/bl4eEhAIh27dqJ/v37i6tXr2a5vczIuxyr63klb5Bq1KhRjhukQkJChJ6enqhQoYLG63h7ewsA4sKFCxrl37x5c6bB9MdiYmKEjY2NKFq0qNLz/5mRn3c7d+7UKL/8TmyrVq00yp+cnCzKli0r9PX1xfPnzzVaR36Hdt68eRrlLyyfhfyPhDFjxog5c+YIQHUcNCKiwqKwxVBZkY8B9HHDXE7Ix/pRd2NP3iBVoUKFLIdIyAjjlYIdr3xMFz6Lw4cPCwCiQ4cOil5Y6sZBo4KFjVJEGti5c6cAIL777jthZWWVYa8HLy8vAUBs3rxZKV0+uGT6gCo+Pl78+++/KtuIiYkRDg4OwsjI6JMG7/xcMnt8LzIyUty9e1el2/ylS5fUbmvx4sUCkA2E+PE4UfJn8L/44gsRGxubZbnevXun8plERUWJL774QgAQ+/btU1kn/WDUcosWLVL8GGqS/86dO6JYsWLC0tJSaRBLIWSNe0lJSUpp8fHxirtAS5Ys0Wgfu3btElKpVNSqVUulntTlf/78uShXrpzQ19dXGWciMTFRJVBPSUkRo0ePVjSkaFKmU6dOCTMzM7WDtRbWzyL9eqampsLOzk6UKVNGSKVSlfIQERUWhTGGunv3rtqbaXfv3hUODg4CgDh58qTSsqioKHH37l2VwZ+vXLmitr727NkjpFKpKFKkiEqvFvkje+XLl1cZt0cdxitpCkO8ooufRfrturi4CAMDA1G7dm0BQO13nQoWfRBRltq2bQsrKyssWrQISUlJGDlypMo0rQCwfPlyNGjQAL169YK/vz88PDxw4cIFXLx4EV988QVOnz6tyPvhwwc0aNAAZcqUQY0aNVCiRAnExsbi4MGDCA8Px/jx42FkZJSXh/nJli1bhmnTpsHPzw9Tp05VpHfs2BEGBgaoWbMmnJ2dERcXh3PnzuHq1auwtrbG5s2boaenp8i/fv16zJgxA/r6+qhduzbmz5+vsq/GjRujcePGivf+/v744Ycf0LRpUzg5OeHly5fYv38/IiMjMWPGDLRr105lG8WLF0eTJk3g4eEBiUSCwMBAXL58GTVr1sSaNWtU8o8bNw5XrlxBrVq1YGNjg4cPH+LAgQOQSqXw9/eHi4uLUv7Lly/jq6++QvPmzeHi4oKYmBj89ddfePr0KQYOHIgRI0ao7KNOnTpwcXFB+fLlYWxsjAsXLiAwMBAlS5bErl27lOoJAJYuXYrNmzejYcOGsLe3x7Nnz7Bv3z68f/8ea9asQfXq1ZXyR0REoGLFimjRogXc3d2RmJiIf/75B/fu3UPr1q3VTrvdqVMnfPjwAZUrV4alpSVu3ryJv//+GzY2NvD394eFhYVS/sL6WchZWlqiU6dO2LhxIyIjI9GyZUuV8hARFRaFMYbavn07Fi1aBC8vL7i6usLMzAwPHjzAoUOHkJSUhEmTJsHLy0tpnT///BN9+/ZF7969sX79ekX6mDFj8OjRI9SrVw/Ozs5ISUnBlStXcObMGRgZGWH9+vWwsrJS5D9+/DgGDRoEIQS8vLzw22+/qZSvatWq8PX1VbxnvFK44hVd/CzkpFIp+vbti+nTp+PChQsoV64c6tevrzYvFSDabhUjyi/kXWABiPv372eY7+bNm6JVq1bC3NxcMZjhzZs3FT2M5Hf5EhMTxdy5c0WLFi2Es7OzMDQ0FMWKFRNeXl5i69atOjv+TGY9peTPlfv5+Smlz5kzRzRp0kQ4OTkJIyMjYWJiIsqVKydGjx4tnj17luF2Mnt9vI9r166JNm3aCEdHR2FgYCBsbW1FmzZtVAZqTG/w4MGibNmywtTUVJiZmYlq1aqJ+fPnZ3h3defOnaJhw4bCxsZGGBgYCBcXF9GvXz8RHBysNn9oaKjo3LmzcHFxEYaGhsLa2lo0bdpU7N69O8My+fn5CU9PT2FhYSGMjY1F+fLlxeTJk9XecRJCiICAAOHt7S3s7e2FgYGBcHBwEF27dlWZ5lcuJiZG9OzZU5QsWVIYGxsLCwsLUa9ePbF69WqRkpKidp3ly5eLWrVqCSsrK2FoaChKlSolRo0aleHd18L6WaQnnw4Z2eg2T0RUUBW2GCowMFB06dJFeHh4CEtLS6Gvry8cHBxE+/btxT///KN2HfmYRB8/Irh69WrRsmVL4eLiIkxMTISRkZEoWbKkGDBggLh7926G28ns9fE+GK8UrnhFFz+L9J48eSIkEkm2Hrmk/E0ihBB50/xFREREREREREQkI9V2AYiIiIiIiIiIqPBhoxQREREREREREeU5NkoREREREREREVGeY6MUERERERERERHlOTZKERERERERERFRnmOjFBERERERERER5Tl9bRegMElNTcWLFy9gYWEBiUSi7eIQERGRBoQQePfuHZycnCCV8n5eXmP8RERElP9oGj+xUSoPvXjxAi4uLtouBhEREeXAs2fP4OzsrO1iFDqMn4iIiPKvrOInNkrlIQsLCwCyD8XS0lLLpdGepKQkHDlyBC1atICBgYG2i5NvsN5yhvWWM6y3nGPd5Ywu11tMTAxcXFwUv+OUtxg/yejyd0SXsd5yjnWXM6y3nGG95Ywu15um8RMbpfKQvMu5paVloQ+qTE1NYWlpqXNfHF3GessZ1lvOsN5yjnWXM/mh3vjomHYwfpLJD98RXcR6yznWXc6w3nKG9ZYz+aHesoqfODACERERERERERHlOTZKERERERERERFRnmOjFBERERERERER5TmOKUVERBpLSUlBUlKStouh05KSkqCvr4/4+HikpKRouzj5hjbrzcDAAHp6enm6TyIiKjwYP2WN8VPOFIT4iY1SRESUJSEEwsPDERUVpe2i6DwhBBwcHPDs2TMOjJ0N2q43a2trODg48DMjIqJcw/hJc9qOA/IrbddbbsRPbJQiIqIsyQMqe3t7mJqaMljIRGpqKmJjY2Fubg6plE/Ja0pb9SaEwPv37/Hy5UsAgKOjY57tm4iICjbGT5pj/JQzBSF+YqMUERFlKiUlRRFQFS1aVNvF0XmpqalITEyEsbExg6ps0Ga9mZiYAABevnwJe3t7PspHRESfjPFT9jB+ypmCED/x0yYiokzJx0AwNTXVckmIPh/5+c0xP4iIKDckJycDYPxEBVtuxE9slCIiIo2wyzkVZDy/iYgoNwkhAPD3hQq23Di/2ShFRERERERERER5jo1SREREGZg6dSqqVq2q7WIAAPr06QNfX19tFyPPBQYGQiKRcOYiIiKifIQxlPbllxiKjVJERFQgNW7cGKNHj1ZJX79+PaytrTXaxvjx4xEQEJC7BVMjNwI3eeCh7hUeHp47BdWC+vXrIywsDFZWVtouChERUaHAGIoxVF7i7HtEREQZMDc3h7m5ubaLkS3379+HpaWlUpq9vf1n219iYiIMDQ0/2/YNDQ3h4ODw2bZPhdz/x3wBx3whIspVjKGyxhhKhj2lCorOnYEJE4CXL7VdEiKifCUwMBC1a9eGmZkZrK2t0aBBA4SGhgJQvfsm7/69YMECODo6omjRohg2bJjSjCNhYWHo0qULzMzM4O7ujq1bt8LNzQ2LFy/WuEwpKSkYO3YsrK2tUbRoUUycOFExYGpW7O3t4eDgoPSSSqWIj49HxYoVMWjQIEXeR48ewcLCAmvXrgWQdgfU398fHh4eMDY2ho+PD549e6ZYR14nf/zxB9zd3WFsbAwAiIqKwoABA2BnZwdLS0s0bdoU169fV6x3/fp1NGnSBBYWFrC0tESNGjVw6dIlAEBoaCjatWsHNzc3WFhYoGLFijh06JDi8/m46/mePXtQsWJFGBkZwc3NDQsXLlSqAzc3N8yaNQv9+vWDhYUFSpQogd9//13j+qdC5NQpoGZNYOtWbZeEiCjfye0YKjw8HG3atIGJiQljqGzEUN26dUPRokVhZmaWL2MoNkoVBDdvArt3A7/8AsTFabs0RFRYxMXJXul/6BMTZWkJCerzpqampSUlydLi4zXL+xkkJyfD19cXjRo1wo0bNxAUFIRBgwZlOpPIiRMn8OjRI5w4cQIbNmzA+vXrsX79esXy3r17Izw8HMePH8eePXvw+++/42U2bxgsXLgQ69evx9q1a3HmzBm8efMGf/75Z04PEwBgbGyMLVu2YMOGDdi3bx9SUlLwzTffoHnz5ujXr58i3/v37/Hzzz9j48aN+PfffxEVFYVu3bopbSs4OBh79uzB3r17ce3aNQBA586d8fLlS/z999+4fPkyqlevjmbNmuHNmzcAgB49esDZ2RkXL17E5cuX8f3338PAwAAAMGzYMCQkJOCvv/7C9evXMXfu3Azvrl6+fBldunRBt27dcPPmTUydOhU//fST0mcgr8OaNWvi6tWrGDp0KIYMGYL79+9/Uh1SAbRyJXDliqxxiogorzCGUhtDDRkyBGFhYQgMDGQMpWEMNXz4cCQmJiIwMBA3b97MnzGUoDwTHR0tAIjo6Ojc3XBqqhAHDwoxa5Zy+vr1Qly4kLv7ygWJiYnC399fJCYmarso+QrrLWdYbzmTvt4+fPgg7ty5Iz58+KCcSRZKCfHyZVrazJmytAEDlPOamsrSnzxJS/vlF1la9+7KeW1tZem3bqWl/f57to+hUaNGYtSoUSrp69atE1ZWVkIIIV6/fi0AiMDAQLXb8PPzE1WqVFG87927t3B1dRXJycmKtM6dO4uuXbsKIYS4e/euACCOHz8uUlJShBBCPHz4UAAQv/zyS4Zl/Xg/jo6OYt68eYr3SUlJwtnZWbRv3z7DbZw4cUIAEGZmZkqvChUqKOWbN2+esLW1FcOHDxeOjo7i1atXSnUDQJw7d06RJj+m8+fPK8pqYGAgXqb73E+fPi0sLS1FfHy80r5KlSolVq1aJYQQwsLCQqxfv15t2T09PYWfn594+/atot4+Pq63b98KIYTo3r27aN68uVKeCRMmKB2nq6ur+OabbxTvU1NThb29vfjtt9/UV54QGZ/n4jP+fpNGPmv9R0YKMXeu8vXm6VMh2rcX4p9/cn9/n4C/ZznDess51l3OyOstJiYmw98VxlAy6WOo27dvK8UbQjCG0jSG+v7771Xip/TH9TljqNyIn9hTqiCQSIDWrYFJk9LSXr0Chg4FatcGLlzQXtmIiHSYjY0N+vTpAx8fH7Rt2xZLlixBWFhYputUrFgRenp6iveOjo6Ku3j379+Hvr4+qlSpolheunRpFClSROMyRUdHIywsDHXq1FGk6evro2bNmhqtf/r0aVy7dk3xknfhlhs3bhzKlCmDZcuWYe3atShatKjScn19fdSqVUvxvly5crC2tsbdu3cVaa6urrCzs1O8v379OmJjY1G0aFHFGBLm5uZ48uQJHj16BAAYO3YsBgwYAG9vb8yZM0eRDgAjR47Ezz//DB8fH0ydOhU3btzI8Pju3r2LBg0aKKU1aNAADx8+REpKiiKtcuXKiv9LJBI4ODhk+24rFQK2tsDEiUDFimlpq1YB+/YBc+Zor1xERDruc8VQ1atXVyxnDJV1DDV8+HAsWLAAX3zxBfz8/PJlDMVGqYIqIQHo1AmoUwdI98XA48dAuhOOiCjHYmNlL1vbtLQJE2Rpy5Yp5335UpZeokRa2rBhsrQ1a5TzhoTI0suXT0vr0yfbxbO0tER0dLRKelRUlNIsJOvWrUNQUBDq16+PHTt2oEyZMjh37lyG25V3l5aTSCRITd9NXsvc3d1RunRpxcvV1VVp+cuXL/HgwQPo6enh4cOHOdqHmZmZ0vvY2Fg4OjoqBXLXrl3D/fv3MWHCBACycRRu376N1q1b4/jx46hQoYKiO/2AAQMQHByMrl274ubNm6hZsyZ+/fXXHJVNTtc/J9JhvXoBI0cCY8empcXHA2PGALduaa9cRFRwMIYCoHu/zfk1hrp69Sp69OiRb2MoNkoVVMWLAxs2AGfOpM0ok5wMNG8OlC3LoIqIPp2ZmeyVfuwAQ0NZmpGR+rzSdD87BgaytP8P8phl3mwqW7Ysrly5opJ+5coVlClTRimtWrVqmDRpEs6ePYtKlSphaw4HPS5btiySk5OV7lIFBwfj7du3Gm/DysoKjo6OOH/+vCItOTkZly9fzlGZPtavXz94enpiw4YN+O6775Tu3sn3JR88E5DduYyKikL59AHuR6pXr47w8HDo6+srBXOlS5eGbbqAu0yZMhgzZgyOHDmCr776CuvWrVMsc3FxQb9+/bBnzx6MGzcOq1evVruv8uXL499//1VK+/fff1GmTBmlu69EOVamDLBkCdCmTVrajh3A4sVAq1bKY7UQEeUEYyi1+0xOTsbVq1cVaYyhNIuhnJ2dMXjwYOzduzdfxlA62Si1fPlyuLm5wdjYGHXq1MGFLB4/27VrF8qVKwdjY2N4enqqdLMTQmDKlClwdHSEiYkJvL29lVo2Q0JC0L9/f7i7u8PExASlSpWCn58fEhMTlbZz48YNfPHFFzA2NoaLiwvmzZuXewf9uejrp/3/wQMgKgqIjgZKltRakYiI8sKQIUPw4MEDjBw5Ejdu3MD9+/exaNEibNu2DePGjQMAPHnyBJMmTUJQUBBCQ0Nx5MgRPHz4MNPgITPlypVDs2bNMHr0aFy4cAFXr17FoEGDYGJikunAnx8bNWoU5syZA39/f9y7dw9Dhw5VmjklMy9fvkR4eLjSSz6zzfLlyxEUFIQNGzagR48e8PX1RY8ePZR+7wwMDDBixAicP38ely9fRp8+fVC3bl3Url07w316e3ujXr168PX1xZEjRxASEoKzZ8/ixx9/xKVLl/DhwwcMHz4cgYGBCA0Nxb///ouLFy8q6nn06NH4559/EBoaiitXruDEiRMZfgbjxo1DQEAAZsyYgQcPHmDDhg1YtmwZxo8fr2HtEuVAhQpAx47A8OFpf+wJIXvULyJCu2UjIspl2oqhGjdujMGDBzOGykYMNWbMGAQEBODJkyf5NobSuUapHTt2YOzYsfDz88OVK1dQpUoV+Pj4ZPgM49mzZ/H111+jf//+uHr1Knx9feHr64tb6XoCzZs3D0uXLsXKlStx/vx5mJmZwcfHB/H/n63g3r17SE1NxapVq3D79m388ssvWLlyJX744QfFNmJiYtCiRQu4urri8uXLmD9/PqZOnZq/ppiuUAF4+hQ4eBAwNU1L79YN+P57IDJSe2UjIsplJUuWxKlTp3Dv3j14e3ujTp062LlzJ3bt2oWWLVsCAExNTXHv3j107NgRZcqUwaBBgzBs2DB8++23Od7vhg0bYGdnh8aNG6NDhw4YOHAgLCwsFNP+amLcuHHo2bMnevfujXr16sHCwgIdOnTQaN2yZcvC0dFR6XX58mXcu3cPEyZMwIoVK+Di4gIAWLFiBV69eoWffvpJsb6pqSm+++47dO/eHQ0aNIC5uTl27NiR6T4lEgkOHToELy8v9O3bF2XKlEG3bt0QGhqKYsWKQU9PD69fv0avXr1QpkwZdOnSBV9++SWmTZsGQDZ984gRI1CnTh20atUKZcqUwYoVK9Tuq3r16ti5cye2b9+OSpUqYcqUKZg+fTr65ODxBCKN1aolm+l44sS0tPPngcGDZT2r3r/XXtmIiHKZtmKo3377Dfb29vDy8mIMlY0YasKECahYsSJatmyZP2OoTIdB14LatWuLYcOGKd6npKQIJycnMXv2bLX5u3TpIlq3bq2UVqdOHfHtt98KIWSjxTs4OIj58+crlkdFRQkjIyOxbdu2DMsxb9484e7urni/YsUKUaRIEZGQkKBI++6770TZsmU1PjadnL3n1i3ZDA1SqRDBwXmyS87kkTOst5xhveWMRrPvkVopKSlKs8g9e/ZMABDHjh3Tcsmyln5Wnbz2cb3lNc6+p7t0tv5Pnxaibl0h+vZVTj9+XIj373N9d/w9yxnWW86x7nJGo9n3SIW6OIAxVNYKQvykn1mDVV5LTEzE5cuXMSndLHJSqRTe3t4ICgpSu05QUBDGph+IEoCPjw/8/f0ByLoVhoeHw9vbW7HcysoKderUQVBQELp166Z2u9HR0bCxsVHaj5eXFwwNDZX2M3fuXLx9+1btrAAJCQlISEhQvI+JiQEAJCUlKboBal3p0pDs3QvJ9etILVEC+H+5JJs3Q1SoAKSb/SC3yI9dZ+ogn2C95QzrLWfS11tKSgqEEEhNTdWpwSh1VUBAACIjI1G7dm2Eh4fj+++/h5ubGxo2bKjz9ScvnzbKKYRQ/KuN/aempkIIgaSkJJVxFXj9ILUaNgSCgmSTy8iFhQEtWgCWlsCdO0CxYtorHxFRPnPq1CmkpqaiSpUqCAsLw8SJE+Hm5gYvLy9tF40+I51qlHr16hVSUlJQ7KMf8GLFiuHevXtq1wkPD1ebPzw8XLFcnpZRno8FBwfj119/xYIFC5T24+7urrIN+TJ1jVKzZ89WdKtL78iRIzBN//ictkmlQLVqwP/H4jJ49w4thg6FQXw8Ts2bh7cfDWaXW44ePfpZtlvQsd5yhvWWM0ePHoW+vj4cHBwQGxurMtYeqYqJicGMGTMQGhoKc3Nz1K5dGytWrMCHDx/w4cMHbRcvU/Hx8RBCKG6iaMO7d++0st/ExER8+PABp06dQnJystKy93w0izKTflDix49lk80UL67cIPXkCeDqqjz4MBERKUlKSoKfnx8eP34MCwsL1K9fH1u2bFGZDY4KFp1qlNIFz58/R8uWLdG5c2cMHDjwk7Y1adIkpV5cMTExcHFxQYsWLWBpafmpRf18nj+H9KuvkHr/PuqNGpU2K0RoKODsDHziyPxJSUk4evQomjdvzgtMNrDecob1ljPp6y0lJQXPnj2Dubl5tp7pL6x8fX3RrFkzWFhYZGtgTl0wePBgDB48WCv7FkLg3bt3Wqu3+Ph4mJiYwMvLS+U812YjHeUzDRoAjx4pD36emAjUry/rPfXXX0Dp0torHxGRDmvWrBk6dOgAaT5swO/Tp4/2x2bKp3SqUcrW1hZ6enqI+GgWk4iICDg4OKhdx8HBIdP88n8jIiLg6OiolKdq1apK67148QJNmjRB/fr1VQYwz2g/6ffxMSMjIxh9PKUnZKPy6/Qfx25uwJYtQFISpPJypqQAX34pu8O3Zw9QqdIn70bn60FHsd5yhvWWMwYGBpBKpZBIJJBKpfkySMhr8kfP5HVGmtF2vcnPc3XXCl47KFv09AAnp7T3t24BcXGym3yurmnp798rTzxDRERUCOlUtGxoaIgaNWogICBAkZaamoqAgADUq1dP7Tr16tVTyg/IHjeR53d3d4eDg4NSnpiYGJw/f15pm8+fP0fjxo1Ro0YNrFu3TiUgrlevHk6dOqU0rsTRo0dRtmxZtY/uFQjpg/D794HXr2Uz9Lm5aa1IRERERPlK9erA8+fA/v3KsVWzZkCTJrKxp4iIiAopnWqUAoCxY8di9erV2LBhA+7evYshQ4YgLi4Offv2BQD06tVLaSD0UaNG4fDhw1i4cCHu3buHqVOn4tKlSxg+fDgA2R3X0aNHY+bMmdi/fz9u3ryJXr16wcnJCb6+vgDSGqRKlCiBBQsWIDIyEuHh4UpjTnXv3h2Ghobo378/bt++jR07dmDJkiUqg6wXWBUqAE+fAgcPAubmaek9ewI//AC8eqW9shERERHpMgsLoGbNtPePHwMXLwL//gsULZqW/v8B/4mIiAoLnXp8DwC6du2KyMhITJkyBeHh4ahatSoOHz6sGFT86dOnSr2Y6tevj61bt2Ly5Mn44Ycf4OHhAX9/f1RK93jZxIkTERcXh0GDBiEqKgoNGzbE4cOHFWNGHD16FMHBwQgODoazs7NSeeSzAVlZWeHIkSMYNmwYatSoAVtbW0yZMgWDBg363FWiO8zNZWMiyN25A2zeLHukr18/wNZWe2UjIiIiyi9KlpQNfn72rPKA6N9+K3usb/JkoFw57ZWPiIgoj+hcoxQADB8+XNHT6WOBgYEqaZ07d0bnzp0z3J5EIsH06dMxffp0tcs1HZSscuXKOH36dJb5Co1y5YA//wSuXVMetHPbNqB8eeCjMbuIiIiI6P9cXICuXdPev30LbNggGxh95EjtlYuIiCgP6WSjFOUTUing6yt7yb19CwwaBMTGAkFBQN262iodERERUf5RpIjscb6DB4HatdPSf/0V+O8/4BNnhSYiItJFOjemFOVzcXFAmzZAtWpAnTpp6c+eAf+fWYmIqLCTSCTw9/fXdjGISNfUrAlMnZr2PjkZmDcPmDcPkjNntFYsIiJdwRiq4GGjFOUuZ2fZ43vnzsmmPgaAlBSgeXOgYkXZtMhERHkoKCgIenp6aN26dbbWc3Nzw+LFiz9PoYiINCGRAMuXA506QXTqlJZ+5AiwdCkQHa29shFRgccYivICG6Xo8zA0TPv/gwdAeLjs5eqqvTIRUaG0Zs0ajBgxAqdOncKLFy+0XRwiIs3p6QHt2gG7dgFGRmnpP/8MjBoFLFyovbIRUYHHGIryAhul6PMrXx54+hQ4cEA2JfL/6Q0YAPz0E/D6tRYLR0QFWWxsLHbs2IEhQ4agdevWWL9+vdLyAwcOoFatWjA2NoatrS06dOgAAGjcuDFCQ0MxZswYSCQSSP7f83Pq1Kmo+tEkDosXL4abm5vi/cWLF9GhQwfY29vDysoKjRo1wpUrVz7nYRJRYSIE0K0bUKWKbBxPuXv3gD17ZI/8ERF9Im3EUFeuXEGLFi1ga2vLGKoQYaMU5Q1LS6BhQ8Vb82fPIN24UXan79UrLRaMiHIqLi4uw1d8fLzGeT98+KBR3pzYuXMnypUrh7Jly+Kbb77B2rVrIYQAAPz111/o0KEDWrVqhatXryIgIAC1/z+48N69e+Hs7Izp06cjLCwMYWFhGu/z3bt36NatG06dOoVz587Bw8MDrVq1wrt373J0DERESiQSYMgQ2ezHzs5p6YsWAZ06ARnMYE1EuoMxlHqxsbHo1asXzpw5wxiqEOHse6QVsU5OSN6+Hfo3bwJly6Yt2LlT1rPK01N7hSMijZibm2e4rFWrVvjrr78U7+3t7fH+/Xu1eRs1aoTAwEDFezc3N7xS01gtD4SyY82aNfjmm28AAC1btkR0dDROnjyJxo0b4+eff0a3bt0wbdo0Rf4qVaoAAGxsbKCnpwcLCws4ODhka59NmzZFzZo1YWlpCalUit9//x3W1tY4efIk2rRpk+1jICLSiKsrYGcH/P+aBwB480Y2jEKdOmljfRKR1jGGUs/Ly0sRPwFgDFVIsKcUaYeeHsRXXwEzZ6alRUfLpjuuXFk2UDoR0Se4f/8+Lly4gK+//hoAoK+vj65du2LNmjUAgGvXrqFZs2a5vt+IiAiMGjUKZcuWhZWVFSwtLREbG4unT5/m+r6IiBR+/FE223GDBmlpa9YA9eoBffporVhElP9oK4Z6+fIlBg0aBA8PD8ZQhQh7SpHuePcOaNkSuHsX+H/3TwDA8+eAoyMgZRsqkS6JjY3NcJmenp7S+5cvX2aYV/rRdzskJOSTyiW3Zs0aJCcnw8nJSZEmhICRkRGWLVsGExOTbG9TKpWq3G1MSkpSet+nTx9ERkbil19+gbu7O4yMjFCvXj0kJibm7ECIiDSVfjB0AIiKkqU1apSWlpIia7xKN44LEeUtxlAyH8dQQ4cORXR0NJYsWQJXV1fGUIUEG6VIdzg7Azt2APHxaQ1QqalA8+ayLufbt/OxPiIdYmZmpvW8GUlOTsbGjRuxcOFCtGjRQmmZr68vtm3bhsqVKyMgIAB9+/ZVuw1DQ0OkpKQopdnZ2SE8PBxCCMXAndeuXVPKc/bsWcyfPx+tWrWCVCrFs2fP1HalJyL67H7+GRgzBkj/qNDBg0CHDrLeU2vXaq1oRIUZYyj1MdT58+exbNkytGrVCgAYQxUSbJQi3WNsnPb/+/dlPaUkEtlYCUREGjh48CDevn2L/v37w8rKSmlZx44dsWbNGsyfPx/NmjVDqVKl0K1bNyQnJ+PQoUP47rvvAMjGZTh16hS6desGIyMj2NraonHjxoiMjMS8efPQqVMnHD58GH///TcsLS0V2/fw8MDOnTvxxRdfIDY2FhMmTMjRHUUiolxha6v8/vx52Qx+9vbK6XFxQC78QUtE+Zs2Y6iSJUti8+bNqF27NmJiYhhDFRJ8Hop0W/nywNOnwL59shn85AYOBKZOlQ3gSUT0kTVr1sDb21slmAJkAdWlS5dgY2ODXbt2Yf/+/ahatSqaNm2KCxcuKPJNnz4dISEhKFWqFOzs7AAA5cuXx4oVK7B8+XJUqVIFFy5cwPjx45W2v3r1akRFRaFmzZro2bMnRo4cCfuP//gjItKWWbOAe/eA0aPT0m7fBooVk83cl4MBkYmo4NBmDPXrr78iKioK1atXZwxViLCnFOk+KyvlsRDu35cN3CkE0LUrYGOjvbIRkU46cOBAhstq166tGNOgcuXK+Oqrr9Tmq1u3Lq5fv66SPnjwYAwePFgp7YcfflD8v1q1ajh+/LjS7DGdOnVSyp+TWXCIiHJN+pmPAWDXLllPqRcvlGfpE4Kz9hEVMtqMoSpXrozz588rjZXFGKrgY6MU5T+lS8vGnrp8WdaTSm73btn7ihW1VzYiIiKi/MbPT3YDsEiRtLSoKKBuXaBnT2DCBMDQUGvFIyKigouP71H+o6cHdO4MzJmTlhYdDfTvD1SqBAQFaa9sREREWrJ8+XK4ubnB2NgYderUUXqUQp1du3ahXLlyMDY2hqenJw4dOqS0XAiBKVOmwNHRESYmJvD29sbDhw8Vy0NCQtC/f3+4u7vDxMQEpUqVgp+fn9IsSSEhIZBIJCqvc+fO5e7B06eRSIAmTYCqVdPStmyR9U7fvh0wMNBa0YiIqGBjoxQVDO/eyWbpq1gRqFMnLT0sjGMjEBFRgbdjxw6MHTsWfn5+uHLlCqpUqQIfH58MpxI/e/Ysvv76a/Tv3x9Xr16Fr68vfH19cevWLUWeefPmYenSpVi5ciXOnz8PMzMz+Pj4ID4+HgBw7949pKamYtWqVbh9+zZ++eUXrFy5UulRDLljx44hLCxM8apRo8bnqQjKPQMGAJs3AzNnpj3Cl5oKdOwIrFsHJCRot3xERFQgsFGKCgZnZ9njexcvAvJnkFNTZQ1VVaoA6YJsIiKigmbRokUYOHAg+vbtiwoVKmDlypUwNTXF2rVr1eZfsmQJWrZsiQkTJqB8+fKYMWMGqlevjmXLlgGQ9ZJavHgxJk+ejPbt26Ny5crYuHEjXrx4AX9/fwBAy5YtsW7dOrRo0QIlS5ZEu3btMH78eOzdu1dlf0WLFoWDg4PiZcCeN7rPyAjo0QNo3z4t7Z9/gL17gTFjgORk7ZWNiIgKDI4pRQVL+ilDHzwAQkNld/ecnbVXJiIios8oMTERly9fxqRJkxRpUqkU3t7eCMrgkfagoCCMHTtWKc3Hx0fR4PTkyROEh4fD29tbsdzKygp16tRBUFAQunXrpna70dHRsFEzAUm7du0QHx+PMmXKYOLEiWjXrl2Gx5OQkICEdL1wYmJiAABJSUlISkrKcL2CTn7sWq2DatUgnTULEAKphobA/8sinTkTok4diGbN0m4O6gidqLd8inWXM/L6Sk5OhhACqampSE1N1XKpdJ98AHN5nZFmtF1vqampEEIgKSkJenp6Sss0vXawUYoKrnLlgKdPgatXAWvrtPTBg4HixWXTHqcf0JOIiCgfevXqFVJSUlCsWDGl9GLFiuHevXtq1wkPD1ebPzw8XLFcnpZRno8FBwfj119/xYIFCxRp5ubmWLhwIRo0aACpVIo9e/bA19cX/v7+GTZMzZ49G9OmTVNJP3LkCExNTdWuU5gcPXpUuwWoUEH27//HIDN78QLe06dDSCQ4tnIl3n90zugKrddbPsa6y5mzZ8/CwcEBsbGxSmPtUebevXun7SLkS9qqt8TERHz48AGnTp1C8kc9aN+/f6/RNtgoRQVbkSJA06Zp7x88AH7/XTbO1FdfsVGKiIgoFzx//hwtW7ZE586dMXDgQEW6ra2tUo+sWrVq4cWLF5g/f36GjVKTJk1SWicmJgYuLi5o0aIFLC0tP99B6LikpCQcPXoUzZs3163HH//7DynDh0MSGYnGffsqkiW7d0OUKyebhEaLdLbe8gHWXc7I661+/foICwuDubk5jI2NtV0snSeEwLt372BhYQGJfBw7ypK26y0+Ph4mJibw8vJSOc/lPZ2zwkYpKlxKlgS2bgUuX5YNii7n7w+ULQuUL6+1ohEREeWEra0t9PT0EBERoZQeEREBBwcHtes4ODhkml/+b0REBBwdHZXyVE0/QxuAFy9eoEmTJqhfvz5+//33LMtbp06dTHteGBkZwcjISCXdwMCAfxhDB+vB3R349VcA6QarffdO1jM9JgY4d055Ehot0bl6y0dYdzmjr68PiUQCqVQKqY491qqL5I+eyeuMNKPtepNKpZBIJGqvE5peN/hpU+Girw906wbMn5+W9u4d0LevrDv6v/9qr2xEREQ5YGhoiBo1aiAgIECRlpqaioCAANSrV0/tOvXq1VPKD8ge0ZHnd3d3h4ODg1KemJgYnD9/Xmmbz58/R+PGjVGjRg2sW7dOo4D42rVrSg1dVABFR8smm6lQAahVKy390iUggxkhiYiocGKjFFF0NNC4sWwMqrp109IjImSP+RERZaFPnz7w9fVVvG/Tpg3GjBmT5+UIDAyERCJBVFRUnu+btGvs2LFYvXo1NmzYgLt372LIkCGIi4tD3/8/TtWrVy+lgdBHjRqFw4cPY+HChbh37x6mTp2KS5cuYfjw4QBkd1xHjx6NmTNnYv/+/bh58yZ69eoFJycnxbkub5AqUaIEFixYgMjISISHhyuNObVhwwZs27YN9+7dw7179zBr1iysXbsWI0aMyLvKobwnnxX5ypW0gc+FAHr2BFxcgCNHtFs+ItIJjJ8I4ON7RLLA6c8/gffvAfmMAULI7vBJpcDmzVofD4GIcqZPnz7YsGEDAFkX4hIlSqBXr1744YcfoK//+X4CN23apHYGMnUCAwPRpEkTvH37FtbpJ2UgyoauXbsiMjISU6ZMQXh4OKpWrYrDhw8rBip/+vSpUi+m+vXrY+vWrZg8eTJ++OEHeHh4wN/fH5XS/d5NnDgRcXFxGDRoEKKiotCwYUMcPnxYMWbE0aNHERwcjODgYDh/NMutSHdTZ8aMGQgNDYW+vj7KlSuHHTt2oFOnTp+zOkhXpH8M89Ur2cQzhobKNwGfPwdsbJRnUCYirWL8RHmJjVJEculn9HnwAHj8GJBIZDP1EVG+1bJlS6xbtw4JCQk4dOgQhg0bBgMDA6VeI4Bs9hBDQ8Nc2WeRIkVgYWGRK9si0tTw4cMVPZ0+FhgYqJLWuXNndO7cOcPtSSQSTJ8+HdOnT1e7vE+fPujTp0+mZerduzd69+6daR4qJOzsgKAgWSNU+gHrhw4FzpwB1q0DMhj8nojyHuMnyit8fI9InbJlgadPgb17lWfoGz4c+PlngF07ifINIyMjODg4wNXVFUOGDIG3tzf279+v6DL+888/w8nJCWXLlgUAPHv2DF26dIG1tTVsbGzQvn17hISEKLaXkpKCsWPHwtraGkWLFsXEiROVeoUAqt3PExIS8N1338HFxQVGRkYoXbo01qxZg5CQEDRp0gSALBCTSCSKP/JTU1Mxe/ZsuLu7w8TEBFWqVMHu3buV9nPo0CGUKVMGJiYmaNKkiVI5iYh0UvqbfR8+ALduAW/eyGIvuffvgf8P3ktE2sH4ifIKe0oRZcTGRvYIn1xwMPDbb7IgqV07WRd0okJICIH3Se+1sm9TA9NPnu7WxMQEr1+/BgAEBATA0tJSMRNYUlISfHx8UK9ePZw+fRr6+vqYOXMmWrZsiRs3bsDQ0BALFy7E+vXrsXbtWpQvXx4LFy7En3/+iaZNm2a4z169eiEoKAhLly5FlSpV8OTJE7x69QouLi7Ys2cPOnbsiPv378PS0hIm/3+EZfbs2di8eTNWrlwJDw8PnDp1Ct988w3s7OzQqFEjPHv2DF999RWGDRuGQYMG4dKlSxg3btwn1Q0RUZ4yMZH1Tg8KUm6UmjIFOHBANjENe09RAZKfYyjGT/S5sFGKSFOursDGjbKZYzw909L375cFUumDKaIC7H3Se5jPNtfKvmMnxcLM0CxH6wohEBAQgH/++QcjRoxAZGQkzMzM8Mcffyi6nW/evBmpqan4448/FIHbunXrYG1tjcDAQLRo0QKLFy/GpEmT8NVXXwEAVq5ciX/++SfD/T548AA7d+7E0aNH4e3tDQAoWbKkYrl87AR7e3vFmAgJCQmYNWsWjh07ppjprGTJkjhz5gxWrVqFRo0a4bfffkOpUqWwcOFCAEDZsmVx8+ZNzJ07N0f1Q0SkFXp6QMOGae9TU2WDpIeGpg2SDsjG+/zEmxJE2pYfYyjGT/S5sVGKSFMGBkCPHrKXXFwc0Lcv8PYtcPo00KCB9spHRGodPHgQ5ubmSEpKQmpqKrp3746pU6di2LBh8PT0VBoH4fr16wgODlYZzyA+Ph6PHj1CdHQ0wsLCUKdOHcUyfX191KxZU6ULuty1a9egp6eHRo0aaVzm4OBgvH//Hs3T99aEbNyGatWqAQDu3r2rVA4AigCMiCjfkkqBmzeBXbuAL79MS//jD2DrVmDSJKBFC+2Vj6iQYPxEeYWNUkSf4u1b2d29e/eUZ5KJjARsbXlHjwokUwNTxE6K1dq+s6tJkyb47bffYGhoCCcnJ6VZY8zMlO8YxsbGokaNGtiyZYvKduzs7LJfYEDRnTw7YmNl9fvXX3+h+EeTLRiln82KiKggsrAA+vVTTlu5ErhyRfY4HxulKJ/KTzEU4yfKK2yUIvoUzs7Avn1AbKys+zkg617eooWsQWrjRiDd9NpEBYFEIsnxI3TaYGZmhtKlS2uUt3r16tixYwfs7e1hmX52qHQcHR1x/vx5eHl5AQCSk5Nx+fJlVK9eXW1+T09PpKam4uTJk4ru5+nJ7zSmpKQo0ipUqAAjIyM8ffo0wzuE5cuXx/79+5XSzp07l/VBEhHlR/7+wO+/A+lnfDx9Gli1Chg5EqhdW1slI9JYfoqhGD9RXuHse0S5wTzds+EPHqS9HB21VyYiyrYePXrA1tYW7du3x+nTp/HkyRMEBgZi5MiR+O+//wAAo0aNwpw5c+Dv74979+5h6NChiMpkRk43Nzf07t0b/fr1g7+/v2KbO3fuBAC4urpCIpHg4MGDiIyMRGxsLCwsLDB+/HiMGTMGGzZswKNHj3DlyhX8+uuv2LBhAwBg8ODBePjwISZMmID79+9j69atWL9+/eeuIiIi7XBxAWbMUJ4VeelSYMsWYO1a7ZWLiBg/0SdhoxRRbitbVjY45549QNGiaemjRwNz5wLR0VorGhFlztTUFKdOnUKJEiXw1VdfoXz58ujfvz/i4+MVd/7GjRuHnj17onfv3qhXrx4sLCzQoUOHTLf722+/oVOnThg6dCjKlSuHgQMHIi4uDgBQvHhxTJs2Dd9//z2KFSuG4cOHAwBmzJiBn376CbNnz0b58uXRsmVL/PXXX3B3dwcAlChRAnv27IG/vz+qVKmClStXYtasWZ+xdoiIdMz338t6Tg0blpb29Cnw3XcAp3gnyjOMn+hTSERGI4tRrouJiYGVlRWio6Mz7NZYGCQlJeHQoUNo1aoVDAwMtF2cvPH4MeDhIZtR5upVoGrVbG+iUNZbLmC95Uz6ektJScGTJ0/g7u4OY2NjbRdN56WmpiImJgaWlpaQSnnvR1Parrf4+PgMz3P+fmsX61+Gv2ca+vFHYNYsoGlTICCA9fYJWHc5I6+3pk2b4r///mP8pCFtxwH5lbbrLTfiJ37aRHnBxQVYtw4YPly5Qeqvv4DgYK0Vi4iIiKhAadQIaN5cqfeUNDER0pUrgZgYLRaMiIjUYaMUUV4wMAB69QJ+/TUtLS4O6N1b9rjfmTPaKxsRERFRQdGiBXDkCPDVV4qk4mfOQG/kSKB+fdmENEREpDPYKEWkLW/fAnXrAu7usn/lXr9mwERERESUS5JNTSHKlwd69pTNjgzIYq3Dh4HkZO0WjoiokGOjFJG2ODsDBw/KxpjS15elCSG7w1enDnD7tnbLR0RERFQAhNWti+Rr14AxY9ISg4KAL78EKlRgwxQRkRbpa7sARIWehUXa/x8+BO7ckd3FK1ZMe2UiIiIiKkgkEtlwCnLPnwN2dkDDhmk3BwHg0SOgZMm0HlVERPRZsVGKSJeUKQOEhgIXLwK2tmnp48dDamsLfVdX7ZWNCr3U1FRtF4Hos+H5TVTIdO4MtGsHvHuXlhYWBpQrB1SpApw4oXzjkCibJP9v2OTvCxVkuXF+s1GKSNfY2wOtW6e9DwkBFi+GXkoKzBYs0FqxqPAyNDSEVCrFixcvYGdnB0NDQ0WgRapSU1ORmJiI+Ph4TmmcDdqqNyEEEhMTERkZCalUCkNDwzzbNxFpmZGR7CV3/jygpweYmCg3SMXFAWZmeV8+ytcMDAwYP2UD46ecKQjxExuliHSdkxPwxx9ICQpCdOnSaemHD8t6VpUsqb2yUaEglUrh7u6OsLAwvHjxQtvF0XlCCHz48AEmJiYMPrNB2/VmamqKEiVKMBAmKsx8fYH//gNevkxLS0gAPDyAWrWA33/n8AqkMcZP2aPtOCC/0na95Ub8xEYpIl1naAj06YPUHj2AQ4dkaR8+AL16yWbqO3lSNh4C0WdkaGiIEiVKIDk5GSkpKdoujk5LSkrCqVOn4OXlBYP045dQprRZb3p6etDX12cQTESy4RPSD6Fw+rTssb5LlwAbm7R0ITjuFGWJ8ZPmGD/lTEGIn9goRZQfvX4N1KgB3L8P1K2blv72LWBtzSCJPguJRAIDAwMGClnQ09NDcnIyjI2NWVfZwHojIp3k7Q3cvSsbTiH9tal5c1kPqp9+kvVqJ8oA4yfNMA7ImYJQb+yjTpQfOTsDf/8NXL2aNmOMEICPD1CvHnD7tnbLR0RERFRQlCsHtGyZ9v7aNSAgAFi7VnnmPiIiyjZeRYnyMyurtP8HBwM3b8r+b2ennfIQERERFXRVqgDHjwO3bskmqJGbOFEWm337rfIjgERElCE2ShEVFB4esq7l588rB0jffScblHPgQE5tTERERPSpJBKgSRPZS+7lS2DJEiAxEWjRgo1SREQaYqMUUUFSrBjQrl3a+6dPgUWLgORk4IsvZDPHEBEREVHusrKSPc538qRyvLV+vWyIhW7dABMTrRWPiEhXsVGKqCArVgz47TfgwgXlAOnoUVnPKjc3rRWNiIiIqMAwMgJ69JC95JKSgMmTgefPZbMpp19GREQAONA5UcFmZAQMGAD8/nta2ocPQM+eQOnSsmmOiYiIiCj3JScDI0bIbgx26pSWfuaM7AZhaqr2ykZEpCPYKEVU2Lx6BVSuLJvBr27dtPToaFn3ciIiIiL6dCYmsrE9L1yQ3SiU+/FH2bhTixdrrWhERLqCjVJEhY2LC3DkCHD1KmBgIEsTAvDxARo0AG7f1m75iIiIiAqq5GSgalWgaFHZOFNyjx/LZvMjIipk2ChFVFgVKZL2/0ePgGvXgCtXOFsMERER0eeiry+bpe/FC8DJKS191izA0xOYMUN7ZSMi0gIOdE5EsvGlQkKAc+dkg6PL/fgjYG8vG5fKzExrxSMiIiIqUAwN0/4vBJCQAOjpAU2apKVHR8vS7e3zvnxERHmEPaWISMbBAfD1TXv/7Bkwfz4wejRw86a2SkVERERUsEkkwKZNwNOnsqEU5Fatkg27MH269spGRPSZsVGKiNSzswOWLQP69FEeED0gQBY0EREREVHucXKSNVDJXb4MJCbKGqbkUlJkMykTERUQbJQiIvWMjYFBg4B169LS4uOBb74BSpUCTp/WXtmIiIiICrodO4CLF5UHRD9wQDaD8uzZ2isXEVEuYqMUEWnu1SugYkXZo3516qSlv3unvTIRERERFVQ1awImJmnvd+0C3rwBYmKU8wmRt+UiIsolbJQiIs05OwPHjslm6ks/QOeXXwJffAHcvq21ohEREREVeBs3Av7+wNChaWm3bwPlywMrVmitWEREOcVGKSLKvqJF0/7/6BFw4YLsZWOjvTIRERERFXR6ekD79srjTK1aBdy/Lxv3k4gon9HXdgGIKJ8rVQp48gQICgIcHdPSp0yRTWHcrx9gaqq98hEREREVZD//LOspVa1aWlpUFPD118CAAUCHDoCUfRGISDexUYqIPl3x4kCnTmnvnz8H5swBkpKA6tWB+vW1VzYiIiKigszCAhgyRDlt/Xrg8GHgv/+Ar77SSrGIiDTBRikiyn02NsCSJcDZs8oNUidPynpWOTtrr2xEREREBV3HjrIJasqXByQSWVpqKjB2rGw2vzp10tKJiLSI/TiJKPeZmMju2G3alJaWkAB07w6ULAmcOqW9shEREREVdC4uwMyZQI8eaWmHD8tuGn75JfDhg/bKRkSUDntKEVHeiIwEypSR/b9OnbT02FjA3Fw7ZSIiIiIqLNzcgD59ZGOAph/v848/AG9v2XIiojzGRikiyhvOzsCJE7LGKSOjtPTWrWXdx1esACpU0F75iIiIiAqyChWAdeuU0x48AAYOBPT1ZWOC2ttrp2xEVGixUYqI8padXdr/Hz+WzdoHAFZW2ikPERERUWEVHw80bw4YGys3SJ08CVSqpL1yEVGhwUYpItKekiVlDVP//iubwU9u2jRZYNSnj2x8KiIiIiLKfZUrA0eOAImJaWnv3gFt20I/NRXmc+dqr2xEVCiwUYqItMvZGejaNe19WBgwa5YsOPL0BBo21F7ZiIiIiAoDQ8O0/4eGygZKT05GrJNTWvrjx0CJErJH/YiIcgln3yMi3WJlBSxcCHz9tXKD1OnTwIsX2isXERERUWFQqRJw6xaSjx4FpP//c1EIoFUrwN0duHxZu+UjogJF5xqlli9fDjc3NxgbG6NOnTq4cOFCpvl37dqFcuXKwdjYGJ6enjh06JDSciEEpkyZAkdHR5iYmMDb2xsPHz5UyvPzzz+jfv36MDU1hbW1tdr9SCQSldf27ds/6ViJSA1TU2D4cGDr1rS0xESge3dZIHTypPbKRkRERFQYSCSyWfrkQkKA16+B6Oi02ZQB2SzKQuR58Yio4NCpRqkdO3Zg7Nix8PPzw5UrV1ClShX4+Pjg5cuXavOfPXsWX3/9Nfr374+rV6/C19cXvr6+uHXrliLPvHnzsHTpUqxcuRLnz5+HmZkZfHx8EB8fr8iTmJiIzp07Y8iQIZmWb926dQgLC1O8fH19c+W4iSgLL1/KGqRsbIA6ddLS37/XXpmIiIiICgt3d+DZM+DYMcDCIi29e3egdm3g/HntlY2I8jWdapRatGgRBg4ciL59+6JChQpYuXIlTE1NsXbtWrX5lyxZgpYtW2LChAkoX748ZsyYgerVq2PZsmUAZL2kFi9ejMmTJ6N9+/aoXLkyNm7ciBcvXsDf31+xnWnTpmHMmDHw9PTMtHzW1tZwcHBQvIyNjXPt2IkoE87OwKlTwLVrstlh5Fq3Bpo1A+7c0VrRiIiIiAoFY2NZA5TcmzdAQABw6RKQ/mkT9pwiomzQmVHqEhMTcfnyZUyaNEmRJpVK4e3tjSD5lPEfCQoKwtixY5XSfHx8FA1OT548QXh4OLy9vRXLraysUKdOHQQFBaFbt27ZKuOwYcMwYMAAlCxZEoMHD0bfvn0hkUgyzJ+QkICEhATF+5iYGABAUlISkpKSsrXvgkR+7IW5DnKC9QZZTyn58T95Av0zZwCJBMkmJmnpH2G95QzrLedYdzmjy/Wmi2VSZ/ny5Zg/fz7Cw8NRpUoV/Prrr6id/g/Ij+zatQs//fQTQkJC4OHhgblz56JVq1aK5UII+Pn5YfXq1YiKikKDBg3w22+/wcPDAwAQEhKCGTNm4Pjx4wgPD4eTkxO++eYb/PjjjzBMN2jyjRs3MGzYMFy8eBF2dnYYMWIEJk6c+Pkqgojyho2NbFD0o0eBsmXT0r/7Drh/H/jpJ6BmTe2Vj4jyBZ1plHr16hVSUlJQrFgxpfRixYrh3r17atcJDw9Xmz88PFyxXJ6WUR5NTZ8+HU2bNoWpqSmOHDmCoUOHIjY2FiNHjsxwndmzZ2PatGkq6UeOHIGpqWm29l8QHT16VNtFyJdYb2lMfvsNNnfu4PmNG8CNGwCAMrt2IcHSEs+aNEFquj+KWG85w3rLOdZdzuhivb3PB48Ky4dAWLlyJerUqYPFixfDx8cH9+/fh729vUp++RAIs2fPRps2bbB161b4+vriypUrqFSpEoC0IRA2bNgAd3d3/PTTT/Dx8cGdO3dgbGyMe/fuITU1FatWrULp0qVx69YtDBw4EHFxcViwYAEA2Q25Fi1awNvbGytXrsTNmzfRr18/WFtbY9CgQXlaR0T0GdjayiankUtMBP74A3j7Fvj2W+2Vi4jyDZ1plNJ1P/30k+L/1apVQ1xcHObPn59po9SkSZOUenLFxMTAxcUFLVq0gKWl5Wctry5LSkrC0aNH0bx5cxgYGGi7OPkG6y1jVeT/iYiAfteukCQkoFLHjhBeXqy3HGK95RzrLmd0ud7kPZ11WfohEABg5cqV+Ouvv7B27Vp8//33KvnTD4EAADNmzMDRo0exbNkyrFy5UmUIBADYuHEjihUrBn9/f3Tr1g0tW7ZEy5YtFdssWbIk7t+/j99++03RKLVlyxYkJiZi7dq1MDQ0RMWKFXHt2jUsWrSIjVJEBZGhIXD2LLBlC5Du+oCNG4GgIGDkSKB8ee2Vj4h0js40Stna2kJPTw8RERFK6REREXBwcFC7joODQ6b55f9GRETAMd3sEREREahateonlbdOnTqYMWMGEhISYGRkpDaPkZGR2mUGBgY6F3BrA+shZ1hvmbCxAebOBc6cgX7TprKZYwDY3L0Lg2rVYFCihJYLmP/wfMs51l3O6GK96Vp5PqZLQyBER0fDxsZGaT9eXl5Kj/P5+Phg7ty5ePv2LYoUKZLt4yUiHVeuHDBjRtp7IYAFC4CbN2Uz97FRiojS0ZlGKUNDQ9SoUQMBAQGKWe1SU1MREBCA4cOHq12nXr16CAgIwOjRoxVpR48eRb169QAA7u7ucHBwQEBAgKIRKiYmBufPn89ypr2sXLt2DUWKFMmwQYqItMDUFBg1SvaSS0pCjUWLoO/nBxw5AjRqpL3yERF9BroyBEJwcDB+/fVXRS8p+Xbc3d1VtiFfpq5RimNyqqfL467pMtZbzuVa3QkBycKFkK5ejZQePRTjgEqCgiAJDERq//6AmseM8yuecznDessZXa43TcukM41SADB27Fj07t0bNWvWRO3atbF48WLExcUpuqL36tULxYsXx+zZswEAo0aNQqNGjbBw4UK0bt0a27dvx6VLl/D7778DACQSCUaPHo2ZM2fCw8NDMR6Ck5OTouELAJ4+fYo3b97g6dOnSElJwbVr1wAApUuXhrm5OQ4cOICIiAjUrVsXxsbGOHr0KGbNmoXx48fnaf0QUQ5EROBD0aIwkUqBOnXS0j98AExMtFcuIqIC5Pnz52jZsiU6d+6MgQMHftK2OCZn5nRx3LX8gPWWc7lWdz16yB7h+79ac+fCKSgIT4OCcGPw4NzZhw7hOZczrLec0cV603RMTp1qlOratSsiIyMxZcoUhIeHo2rVqjh8+LDijtrTp08hlUoV+evXr4+tW7di8uTJ+OGHH+Dh4QF/f3/FAJ0AMHHiRMTFxWHQoEGIiopCw4YNcfjwYRinm1Z+ypQp2LBhg+J9tWrVAAAnTpxA48aNYWBggOXLl2PMmDEQQqB06dKKsRuISMc5O+PMnDloVa0aDNJ979G2LSCVAkuWsBs5EeVr2h4C4cWLF2jSpAnq16+vuDGY1X7S7+NjHJNTPV0ed02Xsd5y7nPXnSQmBqkpKXCeNQvO8r/fnj2D5PhxiC5d8u3NQ55zOcN6yxldrjdNx+TUqUYpABg+fHiGj+sFBgaqpHXu3BmdO3fOcHsSiQTTp0/H9OnTM8yzfv16rF+/PsPlHw/kSUT5ULo/qhASAgQGysacMjPTVomIiHKFNodAeP78OZo0aYIaNWpg3bp1SjcP5fv58ccfkZSUpAiWjx49irJly2Y4nhTH5Mwc6yFnWG8599nqrmdPoGdPKF01/vgDmD0b+Osv4M8/c3+feYjnXM6w3nJGF+tN0/LkqFHq+vXr+Pfff3Hnzh28evUKEokEtra2KF++POrXr//Jg4gTEX1Wbm5AcDBw+jSQfvDzuXOBokVlQRLHiyOiXPY54ydtDIHw/PlzNG7cGK6urliwYAEiIyMV5ZH3gurevTumTZuG/v3747vvvsOtW7ewZMkS/PLLLzk+ViIqwFxcZLFZr15paR8+AGfOAN7eiklsiKjg0LhR6uXLl1ixYgU2btyI0NBQCCFgaGiIIkWKQAiBqKgoJCYmQiKRoESJEujduzeGDBmiMkAmEZFOcHOTveRevgSmTgXi44FSpYAmTbRUMCIqSPIqftLGEAhHjx5FcHAwgoOD4ezsrFQeIQQA2Yx9R44cwbBhw1CjRg3Y2tpiypQpGDRoUI7qk4gKuCFDgI+vD9u3A/36AS1aAP/8o51yEdFno1Gj1HfffYfly5fD0tISnTp1QvPmzVGjRg04OTkp5Xvx4gUuX76MI0eOYPXq1ViwYAFGjBihuCtHRKSzzMyAWbOAU6eAxo3T0s+dA9zdATawE1E25XX8lNdDIPTp0wd9+vTJslyVK1fG6dOns8xHRAQA0NNTfh8dDVhYAE2bpqUJATx8CJQpk7dlI6Jcp1Gj1KlTp7B582a0b98ekky6TDo5OcHJyQlt27bF0qVLsW/fPsybNy/XCktE9NmYmQFjxshecsnJwNdfA2FhsjtzjRppr3xElO8wfiIiygWjRwP9+yunBQUBDRoArVoBBw/ysT6ifEyjRqmgdFN3akoikcDX11cx7gARUb4THi7rIRUXB9SunZYeHw+kn8mPiEgNxk9ERLnEwkL5/YULslmUHR2VG6RiYwFz87wtGxF9EmnWWbIvJSUFBw8e/BybJiLKO87OsjtxV68qT0vcrh3w5ZfAvXvaKxsRFTiMn4iINDR6NPDkCTBlSlra8+eAg4NswprERK0VjYiyJ0ez72Xk7Nmz2LJlC3bt2oXXr18jJSUlNzdPRJT3JBKgePG09yEhwPHjsv+ztxQR5QLGT0REOZB+BmUAOHBA1rs9JAQwNExLF4KP9xHpsE9ulLp79y62bNmCrVu3IjQ0FGZmZvDx8UHbtm1zo3xERLrFzQ148AA4eVJ59r4FC4CiRYEePZQDISIiNRg/ERHlssGDgZo1ZWOCyiUkANWrA23aAJMnqz4GSERal6NGqRcvXmDbtm3YsmULrl+/DhMTE3z48AEzZ87EuHHjYMg/yIioICtZUvaSe/UK8PMD3r8HXFwAb2/tlY2IdBbjJyKiz6xmTeX3+/cDd+4AUVHAzJlaKRIRZU7jMaViYmKwdu1aNGvWDK6urpg2bRoqVKiA/fv34+LFixBCoGzZsgyoiKjwMTYGpk2T3YVr1iwt/cIFIDJSe+UiIq1j/EREpEVffQX4+8t6tBsYpKV/8w3w66+ygdGJSKs07inl4OAAAGjVqhW2bt2Ktm3bwvj/46k8evTo85SOiCg/MDcHxo+XveSSk4GvvwbCwoC//wYaNdJe+YhIaxg/ERFpkZ4e0L69ctrFi8CWLcCuXUDXrpytj0jLNG6Uio+Ph6OjI9zd3VGyZElFQEVERGqEhwM2NkB0tHJX8sREjjlFVIgwfiIi0jHlywMrVshuHNrbp6XPmweUKiVrxNLP1fnAiCgTGj++d+fOHfTt2xd79uxB7dq1UaZMGfj5+eEep0QnIlLl7Cx7fO/yZcDMLC3d1xdo3RrgtZOoUGD8RESkY8zNgSFDgOnT09JevgR++gno1Am4dk1rRSMqjDRulCpXrhxmzpyJx48f4+TJk2jWrBlWrFiBihUrwsfHBxKJBK9fv/6cZSUiyl8kEsDVNe19aCjwzz/A4cPsLUVUSDB+IiLKB/T0ZMMwtG6t3MN93z7g/HlACO2VjaiA07hRKr2GDRvit99+Q1hYGP78809Ur14dRkZGGDx4MDw8PDB+/HgEBgbmclGJiPI5V1fg/n1g1Srl2fsWLwY2bgSSkrRWNCL6/Bg/ERHpqKJFgZ9/Bg4eTEtLSgKGDQPq1lVOJ6JclaNGKTl9fX20a9cOO3fuREREBNasWQM3NzcsXrwYzdLPQEVERDKlSwMDBqS9f/MGmDwZ6N0b4B+jRIUC4ycionzg3TugeXPZTUUfn7T0a9eAkBBtlYqowPmkRqn0LCws0KdPHxw9ehRPnz7FggULcmvTREQFl6GhbAyDli0Bb++09MuXgVevtFcuIsoTjJ+IiHSUjQ2wbh3w8KHysAsjRsh6vG/Zor2yERUgudYolZ6TkxPGjBnzOTZNRFSwmJsD330H/P23bAwqAEhJAbp1k92ZY+8pokKD8RMRkQ4yMEj7//v3gLGxbHa+Jk3S0sPDgZiYvC8bUQGgUaOUj48PTp06le2NnzhxAj7puzoSEVHWwsMBS0tZ0JN+sE2OOUWUrzB+IiIqYExNgaNHZZPXODmlpU+eDBQvDqxfr7WiEeVXGjVKlSpVCv9r787Dm6j2N4C/SZs2TUv30rJToSyVVZBSRFAsFAShyA4KooIiBREVwR8gi4jiFcum4FUB8Va4CKIiAqWCcqWCgCi7iJSK0JbSfU2azO+PmGmmSUo6tE3avp/7zJPJmTOZk3MDfP3OmXP69++P9u3bY9GiRTh8+DDy8/Mt6uXl5eHQoUOYP38+2rZti0GDBqF169ZV3mgiojqtSRPg+HHj5uVVVv7oo8DQoQCXkieqFRg/ERHVUY0ale0bDMZ5pvLzgTZtysqLioDS0hpvGlFtY1dS6r333sOFCxcQHR2N9957Dw888AB8fX3RsGFDtG3bFm3atEFQUBD8/Pzw0EMPYcOGDRg0aBDOnz+PdevWVfd3ICKqexQKIDS07H1KCrBnD/DNN8Yh40Tk9Bg/ERHVA0ol8PPPwJEjQGRkWfHatcZYbvNmBzaOyPnZ/V82oaGhiIuLw7/+9S8cPnwYSUlJuHDhAm7dugUACAgIQLt27RAZGYnevXtDZf7sLRER3ZnmzYFz54xzTJmPoFizxjgR55gxTFYROSHGT0RE9YBCIUlIAYBi507g2jVAEMoKTfumeUSJyP6klHiCqysefPBBPGg+sRsREVW/tm2Nm0lWFvDqq8bh4oGB0uWKicipMH4iIqpf9AcPQvnll8CIEWWFu3YBb7xhXORm5EiHtY3ImVTL6ntERFQDXF2BefOAqChgwICy8l9+ATIzHdcuIiIiovpOrQYeewzw8Cgr27DBOGfoyZOOaxeRk2FSioiotmrQwDhSKiGhbBi4Xg+MHWt83O/QIYc2j4iIiIjMfPop8OabwLPPlpWdPQsMGwYkJjquXUQOxAlIiIjqktRU4x05lQro1q2svLSUc04REREROVJgoPHRPXPr1gFffWWM3R56yDHtInIgjpQiIqpLmjQxPr53/LhxJJXJyJHA8OHAxYuOaxsRERERSc2cCcyYATz/fFlZVpax7OxZx7WLqIYwKUVEVNcoFECrVmXv//oL+Ppr4MsvHdcmIiIiIrLUrh2wejVw//1lZZs2AWvXAuPGSVfvI6qDZCWlfvjhB9y8edPm8YyMDPzwww+yG0VERFWoWTPgzBlgzRrp6n3vvQd89pnx0T4iqnaMn4iIyC49ewKPPmocPWU+b2hcHJCe7tCmEVU1WUmpBx98EAkJCTaPJyYmcsljIiJn0r49MH162fucHOPKfePHGydKJ6Jqx/iJiIjsEhkJ7NgBPPVUWdnevcALLwCdOvGGItUpspJSwm2GEJaUlMDFxUVWg4iIqAYoFMBLLwEPPghER5eV//orkJ3tsGYR1WWMn4iISDYPDyAiAnjsMeniNXv3AkVFjmsX0R2yeymmlJQUJCcni+8vXLhgdYh5dnY2NmzYgBYtWlRJA4mIqBp4ewMLFhg3E4MBGDsW+PtvKHbudFzbiOoQxk9ERFQl+vUDfvoJ0OnKyi5eBAYNAoKCgMuXpYvcENUSdielNm7ciMWLF0OhUEChUGDZsmVYtmyZRT1BEODi4oINGzZUaUOJiKiapaYa77wplRC6dgX+9z9juV4PcPQGkSyMn4iIqEqpVGX7f/0FNG8OdO4sTUj9/jsQFlY2HxWRE7M7KTV69Gh06NABgiBg9OjRmDlzJu43XyEAgEKhgKenJ7p06YLg4OAqbywREVWjxo2B334DLl0yjqQyGT3aGNS88QbQpo3j2kdUCzF+IiKiahMVBfz5J5CZWVaWmwt06wY0aQJ8950xviNyYnYnpdq3b4/27dsDMN7169OnD0JDQ6utYURE5AAKhTHxZBoafu0asGuXcTnipUsd2jSi2ojxExERVSsXF+Pjeya//mqM5xQKoFGjsvK8PD7eR07J7qSUuUmTJlV1O4iIyBk1bWocPZWYaFzBz2TDBsDf37hcMR/tI7IL4yciIqp2998P/P03kJxc9viewQDce68xSfXhh0CrVg5tIpE5WUkpADh//jw2btyIP//8E1lZWRYryigUCiQmJt5xA4mIyMHuvtu4meTkAHPmGIeHf/MN8PDDjmsbUS3D+ImIiKpdgwZAx45l703TM1y/DjRsWFYuCJx3ihxOVlJqy5YtmDx5MlQqFdq2bQs/Pz+LOrdb9piIiGophQJ44QXj6KmBA8vKz5wBmjUDfHwc1zYiJ8b4iYiIHKJLF+DKFeOjfeaP8I0aBXh4AIsWcfQUOYyspNSiRYvQtWtXfPvttwgMDKzqNhERkTPz9jYGL6+9Jh0WPnascRWYL78EHnjAkS0kckqMn4iIyGGaNzduJteuATt3GkdLLVzouHZRvaeUc9L169fx5JNPMqAiIqrPzId7p6YagxpBMN6NM9Hra7xZRM6K8RMRETmNpk2BY8eAt98GwsLKypcuBV55xXijkagGyBop1alTJ1y/fr2q20JERLVV48bA6dPA778Dvr5l5ePHGxNVy5ZJAx6ieojxExEROZXu3Y2bSWEhsHIlkJ0N9O1rnJaBqJrJGim1cuVKfPTRRzhy5EhVt4eIiGorpRJo167s/d9/A59/DmzfDmi1jmsXkZNg/ERERE7N3R3YtAmYOFE6b+jnnwNr1hgXuSGqYrJGSr311lvw8fHB/fffj/DwcDRv3hwu5ZYEVygU+PLLL6ukkUREVAs1aQL88gtw4IB09b4PPwT8/ICYGKDcvx1EdRnjJyIicmouLsCwYcbNRBCAxYuNC9ro9cCsWQ5rHtVNspJSv/32GxQKBZo3b478/HycO3fOoo6CS0sSEVGnTsbNJC8PePll47Dwr78GhgxxWNOIahrjJyIiqnX0euC554CNG4EnnigrP3ECSE42JrBcZaUViADITEolJydXcTOIiKheEARgxgwgIQEYNKis/Nw544Sb3t6OaxtRNWP8REREtY6rKzBtmnEz98YbxtX75swB3nrLMW2jOkHWnFJERESyeHsDS5YAR46UPbonCMDYscZlig8dcmjziIiIiOg2BME4NUNQkHH+KZPr14GjR43HiewkOyml1+uxdetWPPPMMxg+fDhOnz4NAMjJycHOnTuRlpZWZY0kIqI6xvwRpRs3jBOh6/VA585l5QZDzbeLqJoxfiIiolpPoTDeZPz7b+m8oatXAz17GkfFE9lJVlIqOzsb9913H8aPH4/PPvsMX331FW7evAkA8PLywsyZM7Fq1aoqbSgREdVRjRsbH9/76SfjBOgmjz0GjB8P/PGH49pGVIUYPxERUZ2iUknfa7XGFfyiosrKioqMc08R2SArKTV37lycPXsW+/btw59//gnBbHiei4sLRo4ciT179lRZI4mIqI5TKqV32q5fB7ZtAz77zBjMENUBjJ+IiKhOW7kS+Osv6UI2W7cCrVoBsbGOaxc5NVlJqV27dmHGjBno37+/1VVi2rRpw8k8iYhIvsaNjau6rFgBdOxYVr5xI/DFF3y0j2olxk9ERFTnBQVJV+P75Rdj3NaiRVmZIBhXZCaCzKRUTk4OQkNDbR7X6XQoLS2V3SgiIiJ06QK8/HLZ+/x84MUXgUcfBXbvdliziORi/ERERPXO6tXGaRqefrqs7McfjTcgX3rJce0ipyErKdWqVSucPHnS5vH9+/cjPDxcdqOIiIgsGAzAc88B994LDB5cVn7hgjFhReTkGD8REVG91L69dN7QnTuNsVt2trQeV+2rl2QlpZ5++ml8/PHH2LZtmzgfgkKhQElJCf7v//4Pe/fuxTPPPFOlDSUionrO2xt4/XXjUsMuLsYyQQDGjQOaNwcOHXJo84hup7rjp3Xr1qFly5ZQq9WIiIjAsWPHKqy/fft2tGvXDmq1Gh07drSYz0oQBCxcuBCNGjWCh4cHoqKicOnSJUmdZcuWoVevXtBoNPD19bV6HYVCYbFt3bpV9vckIqJa7p13gO++A+bMKSv7+29EPfsslMuXc5qGesb19lUsPf/88zh79izGjRsnBiDjx4/HrVu3UFpaimeeeQZPPfVUVbaTiIjIyHwuntRUoKDAuNqL+dxTgiCtR+QEqjN+2rZtG2bPno3169cjIiICcXFxiI6OxsWLF9GwYUOL+keOHMG4ceOwfPlyDBkyBPHx8YiJicHJkyfRoUMHAMCKFSuwevVqbN68GaGhoViwYAGio6Nx7tw5qNVqAIBWq8WoUaMQGRmJjz76yGb7Nm7ciIEDB4rvbSWwiIioHlAogAcflBQpN2+GZ1oaDAkJwMKFDmoYOYKspJRCocC///1vTJo0CZ9//jkuXboEg8GAVq1aYfTo0ejTp09Vt5OIiMhSo0bA+fPA2bNAQEBZ+cSJxsTU4sXGFV+InEB1xk8rV67ElClTMHnyZADA+vXr8c033+Djjz/G3LlzLeqvWrUKAwcOxMv/zNu2dOlSJCQkYO3atVi/fj0EQUBcXBzmz5+PYcOGAQA++eQTBAcHY9euXRg7diwAYPHixQCATZs2Vdg+X19fhISEyP5+RERUtxlmz8aprCx0HjSo7HGukhIgJgYYOxYYPx5QqRzYQqoulU5KFRYW4rHHHsOIESMwYcIE9O7duzraRUREZB8XF6BTp7L3168D8fHGod+cQJOcRHXGT1qtFidOnMC8efPEMqVSiaioKCQlJVk9JykpCbNnz5aURUdHY9euXQCAK1euIDU1FVFRUeJxHx8fREREICkpSUxK2Wv69Ol4+umncdddd+HZZ5/F5MmTra5ASERE9ZRajWsPPohO/fqVlX3+ObB3L3DmDDBhguPaRtWq0kkpjUaDAwcOYNCgQdXRHiIiojvTuDHw88/Avn3GFfxMtmwBfHyAIUMApawpFYlkq874KSMjA3q9HsHBwZLy4OBgXLhwweo5qampVuunpqaKx01lturYa8mSJejXrx80Gg3279+P5557Dvn5+Zg5c6bV+iUlJSgpKRHf5+bmAjCuTqjT6Sp17brE9N3rcx/IwX6Tj30nD/tNHqv91q8flMuWAT4+MAgC8M8x5SuvQOjfH8JDD9X76Rqc+fdmb5tkPb7Xu3dvJCUlYcqUKXJOJyIiql733GPcTAoKgBdeAG7dAnbtAv55HImoJtXX+GnBggXifteuXVFQUIC3337bZlJq+fLl4mOB5vbv3w+NRlNt7awtEhISHN2EWon9Jh/7Th72mzwW/Xb33cbXfxbj8P39d/R9913o16xBwkcfQevjU8MtdE7O+HsrLCy0q56spNTatWsRHR2N+fPn49lnn0XTpk3lfAwREVHNKC0Fnn4a2L8fGDy4rPz334EmTQBPT8e1jeqN6oqfAgMD4eLigrS0NEl5WlqazXmcQkJCKqxvek1LS0OjRo0kdbqYj0CUISIiAkuXLkVJSQnc3d0tjs+bN0/yaGFubi6aNWuGAQMGwNvb+46uXZvpdDokJCSgf//+UHFeFbux3+Rj38nDfpPH7n4LD4c+ORkwGBA1bpxYrPjkEwjduwPh4dXfWCfizL8300jn25GVlOrcuTNKS0uxfPlyLF++HK6urhZBhUKhQE5OjpyPJyIiqlo+PsCbbwLLl5cN8xYEYNw4IDkZ2LEDeOABR7aQ6oHqip/c3NzQrVs3JCYmIiYmBgBgMBiQmJiI2NhYq+dERkYiMTERs2bNEssSEhIQGRkJAAgNDUVISAgSExPFJFRubi6OHj2KadOmVap95Z06dQp+fn5WE1IA4O7ubvWYSqVyuoDbEdgP8rDf5GPfycN+k+e2/RYWBqxbBwBwMZWlpQHPPWdcjfn8eaBdu2pvp7Nxxt+bve2RlZQaMWIEJ6ckIqLax/zfrtRUICcHKC4GOnQoKxeEej8/AVWP6oyfZs+ejUmTJqF79+7o0aMH4uLiUFBQIK7GN3HiRDRp0gTLly8HADz//PPo27cv3nnnHQwePBhbt27F8ePH8cEHHwAwJsdmzZqF119/HWFhYQgNDcWCBQvQuHFjMfEFACkpKcjMzERKSgr0ej1OnToFAGjdujW8vLzw9ddfIy0tDT179oRarUZCQgLeeOMNvMRFCIiIqKoUFBjnDE1Lkyak/vc/oE0boGFDx7WNbqvSSSlBELB69WqoVCp4eHhUR5uIiIiqX6NGwMWLwOnTQGBgWfmTTxpX7lu4EGjVynHtozqluuOnMWPG4ObNm1i4cCFSU1PRpUsX7N27V5yoPCUlBUqzCf579eqF+Ph4zJ8/H6+++irCwsKwa9cudDBL0M6ZMwcFBQWYOnUqsrOz0bt3b+zduxdqtVqss3DhQmzevFl837VrVwDAwYMH8cADD0ClUmHdunV44YUXIAgCWrdujZUrV9a7ebWIiKga3XWXcdS7+cTaOh0werRxPtGDB4FevRzXPqpQpZNSWq0W/v7+WL58OV5++eXqaBMREVHNcHGRrtCXmmpcpU+vB55/3mHNorqnJuKn2NhYm4/rHTp0yKJs1KhRGDVqlM3PUygUWLJkCZYsWWKzzqZNm7Bp0yabxwcOHIiBAwfaPE5ERFRlzB8Xu3EDaNbMeKOxe/ey8itXgJAQgANsnEal18R2d3dHSEgI3NzcqqM9REREjhMSAhw5AixZIl297z//Ab75xvhoH5EMjJ+IiIhqUPPmwNGjwKlTgPm/vY8/bkxWHTjgsKaRVKWTUgDwxBNP4JNPPoFWq63q9hARETlWjx6A2RL2KCwEXnjBOFfBl186rl1U6zF+IiIiqmHmq9BmZgJ//WWcU/Tuu8vK8/J449GBZE103rFjR+zatQt33303nnjiCbRs2dLq/AiPPvroHTeQiIjIoXQ64IkngH37jIkpkz/+ABo3BjQahzWNahfGT0RERA7k7w/8+Sdw8qRxblGT5583jpRfvRoYMMBx7aunZCWlxo0bJ+4vML+bbEahUECv18trFRERkbPw8QFWrADefBMwTRQtCMD48cZ5CbZvBx54wKFNpNqB8RMREZGDubgA995b9r6kxDhFQ3o60KBBWTlXY64xspJSBw8erOp2EBEROTezlcuQlgZkZBiXIDYf/s2h31QBxk9EREROxt3dOPr966+Bnj3Lyt96C9i/3zilw4MPOq599YCspFTfvn2ruh1ERES1R0gI8PvvwK+/AkFBZeVTp8JFp4OGyw6TFYyfiIiInFCDBsYR8CaCAPz738ZH/SZNcly76glZE51Xp3Xr1qFly5ZQq9WIiIjAsWPHKqy/fft2tGvXDmq1Gh07dsSePXskxwVBwMKFC9GoUSN4eHggKioKly5dktRZtmwZevXqBY1GA19fX6vXSUlJweDBg6HRaNCwYUO8/PLLKC0tvaPvSkREtZirK9CtW9n71FRg0yYoN2+GW26u49pFRERERPIpFMDBg8BrrwFjxpSVf/21cfW+48cd17Y6SNZIqX79+t22jkKhQGJiYqU+d9u2bZg9ezbWr1+PiIgIxMXFITo6GhcvXkTDhg0t6h85cgTjxo3D8uXLMWTIEMTHxyMmJgYnT55Ehw4dAAArVqzA6tWrsXnzZoSGhmLBggWIjo7GuXPnoFarAQBarRajRo1CZGQkPvroI4vr6PV6DB48GCEhIThy5Ahu3LiBiRMnQqVS4Y033qjUdyQiojoqJAQ4fBj6b75BdlhYWfnWrYCvLxAdzbkJ6rnqip+IiIioijVvDixaJC2LiwO++854rHt3R7SqTpI1UspgMEAQBMlWWlqKy5cv49ChQ7h27RoMBkOlP3flypWYMmUKJk+ejPDwcKxfvx4ajQYff/yx1fqrVq3CwIED8fLLL6N9+/ZYunQp7rnnHqxduxaAcZRUXFwc5s+fj2HDhqFTp0745JNPcP36dezatUv8nMWLF+OFF15Ax44drV5n//79OHfuHD799FN06dIFgwYNwtKlS7Fu3Tou60xERGV69oRh4cKy90VFwKxZwKBBgNm/O1Q/VVf8RERERDXgrbeMKzI/80xZ2ZkzwNy5QHKyo1pV68kaKXXo0CGbx3bv3o2pU6di5cqVlfpMrVaLEydOYN68eWKZUqlEVFQUkpKSrJ6TlJSE2bNnS8qio6PFhNOVK1eQmpqKqKgo8biPjw8iIiKQlJSEsWPH2tW2pKQkdOzYEcHBwZLrTJs2DWfPnkXXrl3t/ZpERFSfaLXAhAnAvn3AkCFl5X/+aVyK2MPDcW2jGlcd8RMRERHVkO7dgY0bpWVr1wIbNgCXLxtXZKZKk5WUqsiQIUPw2GOPYdasWfj+++/tPi8jIwN6vV6S+AGA4OBgXLhwweo5qampVuunpqaKx01lturYw9Z1zK9hTUlJCUpKSsT3uf/MMaLT6aDT6ey+fl1j+u71uQ/kYL/Jw36Th/0mn6TvNBrgzTeBZctMBwFBgMu4cVAkJ0P/n/9A4OTXAJz7N1cTbZIbPxEREZEDDR1qTEhNn15WlpUFfPqpcZJ0b2/Hta2WqPKkFAC0atVKfISuPlu+fDkWL15sUb5//35oNBoHtMi5JCQkOLoJtRL7TR72mzzsN/ls9Z17djb6XLkC9+xsHPj7b5SYFugQBM45Bef8zRUWFtbIdRg/ERER1TIPP2zczG3cCLz4onFe0R9/dEy7apEqT0qVlpbiv//9LwIDAyt1XmBgIFxcXJCWliYpT0tLQ0hIiNVzQkJCKqxvek1LS0OjRo0kdbp06WJ320JCQixWATRd11bbAGDevHmSxwtzc3PRrFkzDBgwAN71OGOq0+mQkJCA/v37Q6VSObo5tQb7TR72mzzsN/ns6rtRoyCcOoWH7r1XLFLGxkKh00E/dy4QGlpDrXUezvyby62B1RTlxk9ERETkZJo0Adq3N84/ZaLXA3v2GOcZda2WsUG1lqzeePLJJ62WZ2dn46effkJqamql50Rwc3NDt27dkJiYiJiYGADGCUETExMRGxtr9ZzIyEgkJiZi1qxZYllCQgIiIyMBAKGhoQgJCUFiYqKYhMrNzcXRo0cxbdo0u9sWGRmJZcuWIT09XVwFMCEhAd7e3ggPD7d5nru7O9zd3S3KVSqV0wXcjsB+kIf9Jg/7TR72m3wV9p1KBfTqVfY+Lc14V02ng3LqVKBNm5pppBNyxt9cVbWnOuInIiIicjJjxgCjRxsTUSbffmt81K9TJ+DUKY6ONyMrKfXdd99BUa4TFQoF/Pz80Lt3bzz99NMYMGBApT939uzZmDRpErp3744ePXogLi4OBQUFmDx5MgBg4sSJaNKkCZYvXw4AeP7559G3b1+88847GDx4MLZu3Yrjx4/jgw8+ENs0a9YsvP766wgLC0NoaCgWLFiAxo0bi4kvAEhJSUFmZiZSUlKg1+tx6tQpAEDr1q3h5eWFAQMGIDw8HI8//jhWrFiB1NRUzJ8/H9OnT7eadCIiIqqU4GDg0CHjHbSePcvKP/8c8PEBoqIYvNQB1RU/ERERkZNRKKQjojIzgcBAYMAAaUx3/rxxVFU9JisplVxNyx2OGTMGN2/exMKFC5GamoouXbpg79694qTiKSkpUCqVYv1evXohPj4e8+fPx6uvvoqwsDDs2rULHTp0EOvMmTMHBQUFmDp1KrKzs9G7d2/s3bsXarVarLNw4UJs3rxZfG9aTe/gwYN44IEH4OLigt27d2PatGmIjIyEp6cnJk2ahCVLllRLPxARUT3Uq5d09FRxMTBjBpCaCuzYATz6qOPaRlWiuuInIiIicnITJxpHTxUXl5VduACEhwMREcAPPwBubo5rnwM53cOMsbGxNh/Xs7aU8qhRozBq1Cibn6dQKLBkyZIKE0ibNm3Cpk2bKmxXixYtsMc0GS0REVF1Ky42Dv/euxcYMqSsPDkZCAkBzG6uEBEREZGTU6ul8dvx44C7u3HEvHlCKje3Xq3ap7x9FaMbN26gXbt2WLBgQYX15s+fj/bt2yM9Pf2OG0dERFRv+foCcXHA2bPSQGXCBKBlS+PjfuT0GD8RERGRVY89Bly7BpjPJ5mbCzRvDgwbBmRnO6xpNcnupNSqVauQmZmJV155pcJ6r7zyCjIzM7FmzZo7bhwREVG95+JStp+eDvz1F5CVBbRtW1YuCDXfLrIL4yciIiKyKTAQaNWq7P2BA0BODvD778Z5RU3qcKxnd1Lqm2++wbhx4+Dl5VVhvQYNGmD8+PH46quv7rhxREREZKZhQ+DyZeMoqUaNyspjY4FnnjE+2kdOhfETERER2e3RR42Tn2/YUDYhusEA3HsvMH06cPOmY9tXDexOSl2+fBmdOnWyq+7dd9+NP/74Q3ajiIiIyAaVCoiMLHufng78+9/ABx8AN244rl1kFeMnIiIiqpR27YA+fcre//ADcOIE8OmngIeH49pVTeye6NzFxQVardauujqdTrJKHhEREVWToCAgMRHYs0earNq50zgv1YMPSpcephrF+ImIiIjuSN++xljv6lXAfOT11KlQNm0K1V13Oa5tVcDuyKdVq1b43//+Z1fdH3/8Ea3Mn4skIiKi6qFQAPffDyxfXlZWUgLMmAE89JAxOUUOw/iJiIiI7ohCAfTrB0yeXFb255/Ahx/C5bXX4JaX57i2VQG7k1LDhw/H9u3bkZSUVGG9n376Cf/9738xfPjwO24cERERyVBUZJyToHVrYMiQsvK//jImrKjGMH4iIiKiKte4MbB5M/QvvICCxo3LyteuBTZvBoqLHde2SrI7KTV79mw0bdoUAwYMwFtvvYW///5bcvzvv//GW2+9hQEDBqBp06Z44YUXqryxREREZAdfX2DNGuNEme7uZeUTJgB33WWcKJ1qBOMnIiIiqnJqNfD44zC89VZZWUEBMH8+8MQTwMGDDmtaZdmdlGrQoAEOHDiAVq1aYd68eWjevDn8/f3RokUL+Pv7o3nz5pg3bx5CQ0ORkJAAb2/v6mw3ERER3Y6r2dSRN28ah3pnZABt2jiuTfUM4yciIiKqEYIAzJtnfNQvOrqsfN8+ICHBeNwJ2T3ROQDcddddOHHiBD7//HN89dVXuHDhAnJzcxEaGop27drhkUcewciRI+HqWqmPJSIiouoWFGRMSh07ZhzybTJrFqDVAnPnAs2bO6x5dRnjJyIiIqp2Xl7AK68YNxNBAF58ETh7FvjwQ+CppxzXPhsqHf24uLhgzJgxGDNmTHW0h4iIiKqLmxvQu3fZ+5s3gfffNyalxo9nUqoaMX4iIiKiGldcbFyJ+dYtYMSIsvJz54yv4eGOaZcZrjtMRERUXwUGGod0v/iiNFn15ZfA99877TBvIiIiIrKDh4dxntGUFOOcoybz5wN33w3ExTmqZSKOEyciIqqvFArggQeMm4lWC8TGAteuAZ9/Lr2rRkRERES1j0pVtq/XG+cddXEBBgxwXJv+wZFSREREVKawEBg61LhK35AhZeXXrhkTVkRERERUe7m4AP/9L3D9Oh/fIyIiIifj6wusWwdcuAC4u5eVP/440KqV8bE+IiIiIqrdGjZ0dAsA8PE9IiIissZ8mPfNm8DFi0BGhjExRURERERUBThSioiIiCoWFARcuQIkJABNm5aVv/giMGMG8NdfjmsbEREREdVaskdKZWVl4bPPPsOff/6JrKwsCOVW6FEoFPjoo4/uuIFERETkBNzdgb59y97fvGl8zK+kBBg1CmjWzHFtq0UYPxERERGVkZWU2rdvH0aOHImCggJ4e3vDz8/Poo5CobjjxhEREZGTCgwE9uwBvv4auP/+svLduwEfH6B3b+PqfiRi/EREREQkJSsp9eKLLyIkJAQ7d+5Ex44dq7pNRERE5OwUCqBfP+NmotMB06cDKSnGVV1GjXJc+5wQ4yciIiIiKVlzSv3xxx+YOXMmAyoiIiIqU1AADBwItGgBPPJIWfn168aEVT3H+ImIiIhISlZSKiwsDHl5eVXdFiIiIqrNfH2BDRuA338H1Oqy8scfN67a9/33DmuaM2D8RERERCQlKyn1+uuv47333kNycnIVN4eIiIhqPTe3sv2MDODsWeDGDSA01HFtcgKMn4iIiIikZM0plZiYiKCgILRv3x79+/dHs2bN4OLiIqmjUCiwatWqKmkkERER1VKBgUByMnDkCNC8eVn5K68AxcXAyy8DTZs6rHk1ifETERERkZSspNTatWvF/d27d1utw6CKiIiIABgf5TOfED0jA1i92piUiompN0kpxk9EREREUrKSUgaDoarbQURERPVFQADw1VfG7YEHxOKGJ05A4ecH9OnjuLZVI8ZPRERERFKy5pQiIiIikk2hAPr3B9asMe4DQGkpOm3YANe+fYHt2x3bPiIiIiKqEUxKERERkePl5+Nm584QmjYFBg8uK09NBXQ6x7WLiIiIiKqNXUkppVIJV1dXaLVa8b2Li0uFm6urrCcDiYiIqD7y9cWv06ej9Nw5QKMpK584EQgLA77/3nFtk4nxExEREVHF7Ip8Fi5cCIVCIQZKpvdEREREVUqtLtvPyAB+/RW4dQto0cJxbZKJ8RMRERFRxexKSi1atKjC90RERERVLjAQSE4G/vc/oGXLsvJXXwVKSoAXXwQaN3ZU626L8RMRERFRxThGnIiIiJyXh4dxUnSTzEwgLg4oKgIGDnTqpBQRERERVeyOklLXrl3DL7/8gpycHKvLHE+cOPFOPp6IiIhIys8P2LkT2LULiIoqK9+3D2jTBggNdVjT7FVd8dO6devw9ttvIzU1FZ07d8aaNWvQo0cPm/W3b9+OBQsWIDk5GWFhYXjrrbfw8MMPi8cFQcBrr72Gf//738jOzsZ9992H999/H2FhYWKdZcuW4ZtvvsGpU6fg5uaG7Oxsi+ukpKRg2rRpOHjwILy8vDBp0iQsX76c82cRERGRvKRUcXExJk2ahB07dsBgMEChUEAQBACQzJXApBQRERFVKYXCOEJq4MCystJS4KWXgO++c1y77FCd8dO2bdswe/ZsrF+/HhEREYiLi0N0dDQuXryIhg0bWtQ/cuQIxo0bh+XLl2PIkCGIj49HTEwMTp48iQ4dOgAAVqxYgdWrV2Pz5s0IDQ3FggULEB0djXPnzkH9z9xfWq0Wo0aNQmRkJD766COL6+j1egwePBghISE4cuQIbty4gYkTJ0KlUuGNN96o9PckIiKiusWu1ffKe/XVV7Fz504sW7YMhw4dgiAI2Lx5M/bv349Bgwahc+fO+PXXX6u6rURERESW8vOBefOAoCBHt6RC1Rk/rVy5ElOmTMHkyZMRHh6O9evXQ6PR4OOPP7Zaf9WqVRg4cCBefvlltG/fHkuXLsU999yDtWvXAjCOkoqLi8P8+fMxbNgwdOrUCZ988gmuX7+OXbt2iZ+zePFivPDCC+jYsaPV6+zfvx/nzp3Dp59+ii5dumDQoEFYunQp1q1bJ65KSERERPWXrJFSn3/+OSZPnoxXXnkFt27dAgA0adIE/fr1Q1RUFPr164d169bh/fffr9LGEhEREVnw9QXGj3d0K26ruuInrVaLEydOYN68eWKZUqlEVFQUkpKSrJ6TlJSE2bNnS8qio6PFhNOVK1eQmpqKKLNHJH18fBAREYGkpCSMHTvWrrYlJSWhY8eOCA4Ollxn2rRpOHv2LLp27WpxTklJCUpKSsT3ubm5AACdTgedTmfXdesi03evz30gB/tNPvadPOw3edhv8jhzv9nbJllJqfT0dHGOAg8PDwBAQUGBeHzEiBFYsmQJk1JERERE/6iu+CkjIwN6vV6S+AGA4OBgXLhwweo5qampVuunpqaKx01lturYw9Z1zK9R3vLly7F48WKL8v3790Oj0dh97boqISHB0U2oldhv8rHv5GG/ycN+k8cZ+62wsNCuerKSUsHBweIdPo1GAz8/P1y8eBGPPPIIAOMdreLiYjkfTURERFQnMX6yz7x58ySjuHJzc9GsWTMMGDAA3t7eDmyZY+l0OiQkJKB///5QqVSObk6twX6Tj30nD/tNHvabPM7cb6aRzrcjKykVERGB//3vf3jllVcAAI888gjefvttNGrUCAaDAe+++y569uwp56OJiIiI6qTqip8CAwPh4uKCtLQ0SXlaWhpCQkKsnhMSElJhfdNrWloaGjVqJKnTpUsXu9sWEhKCY8eOWVzH/Brlubu7w93d3aJcpVI5XcDtCOwHedhv8rHv5GG/ycN+k8cZ+83e9sia6HzmzJm46667xOf9ly5dCl9fXzz++OOYNGkSfHx8sHr1ajkfTURERFQnVVf85Obmhm7duiExMVEsMxgMSExMRGRkpNVzIiMjJfUB49B/U/3Q0FCEhIRI6uTm5uLo0aM2P9PWdU6fPo309HTJdby9vREeHm735xAREVHdJGukVO/evdG7d2/xfbNmzXD+/HmcPn0aLi4uaNeuHVxdZX00ERERUZ1UnfHT7NmzMWnSJHTv3h09evRAXFwcCgoKMHnyZADAxIkT0aRJEyxfvhwA8Pzzz6Nv37545513MHjwYGzduhXHjx/HBx98AABQKBSYNWsWXn/9dYSFhSE0NBQLFixA48aNERMTI143JSUFmZmZSElJgV6vx6lTpwAArVu3hpeXFwYMGIDw8HA8/vjjWLFiBVJTUzF//nxMnz7d6mgoIiIiql8qHfkUFhbisccew4gRIzBhwgSxXKlUonPnzlXaOCIiIqK6oLrjpzFjxuDmzZtYuHAhUlNT0aVLF+zdu1ecVDwlJQVKZdkA+V69eiE+Ph7z58/Hq6++irCwMOzatQsdOnQQ68yZMwcFBQWYOnUqsrOz0bt3b+zduxdqtVqss3DhQmzevFl8b1pN7+DBg3jggQfg4uKC3bt3Y9q0aYiMjISnpycmTZqEJUuW3PF3JiIiotqv0kkpjUaDAwcOYNCgQdXRHiIiIqI6pybip9jYWMTGxlo9dujQIYuyUaNGYdSoUTY/T6FQYMmSJRUmkDZt2oRNmzZV2K4WLVpgz549FdYhIiKi+knWnFK9e/dGUlJSVbeFiIiIqM5i/EREREQkJSsptXbtWhw+fBjz58/HtWvXqrpNRERERHUO4yciIiIiKVlJqc6dO+PatWtYvnw5WrRoAXd3d3h7e0s2Hx+fqm4rERERUa3F+ImIiIhIStYSLyNGjIBCoajqthARERHVWYyfiIiIiKRkJaVuN6ElEREREUkxfiIiIiKSkvX4HhERERERERER0Z2o9EipkpISfPrpp9i/fz8uX76MvLw8NGjQAK1bt8bAgQMxfvx4uLm5VUdbiYiIiGolxk9EREREliqVlDp9+jSGDRuGq1evQhAE+Pj4wMvLC+np6Th58iS2b9+OZcuW4auvvkL79u2rq81EREREtQbjJyIiIiLr7H58Lz8/H0OHDkVaWhqWLVuGv/76C1lZWZLX119/HdevX8cjjzyCgoKC6mw3ERERkdNj/ERERERkm91JqY0bNyIlJQXffPMN5s6diyZNmkiON2nSBPPmzcPXX3+NK1eucDJPIiIiqvcYPxERERHZZndS6ptvvsGAAQPwwAMPVFivX79+6N+/P77++us7bRsRERFRrcb4iYiIiMg2u5NSp0+fvm1AZdKvXz+cPn1abpuIiIiI6gTGT0RERES22Z2UyszMREhIiF11g4ODkZmZKbtRRERERHUB4yciIiIi2+xOSpWUlEClUtlV19XVFVqtVnajiIiIiOoCxk9EREREtrlWpnJycjJOnjx523pXrlyR3SAiIiKiuoTxExEREZF1lUpKLViwAAsWLLhtPUEQoFAoZDeKiIiIqK5g/ERERERknd1JqY0bN1ZnO4iIiIjqHMZPRERERLbZnZSaNGlSdbaDiIiIqM5h/ERERERkm90TnRMREREREREREVUVJqWIiIiIiIiIiKjGMSlFREREREREREQ1jkkpIiIiIiIiIiKqcUxKERERERERERFRjWNSioiIiIiIiIiIahyTUkREREREREREVOOYlCIiIiIiIiIiohrHpBQREREREREREdU4p0xKrVu3Di1btoRarUZERASOHTtWYf3t27ejXbt2UKvV6NixI/bs2SM5LggCFi5ciEaNGsHDwwNRUVG4dOmSpE5mZiYmTJgAb29v+Pr64qmnnkJ+fr54PDk5GQqFwmL76aefqu6LExERERERERHVE06XlNq2bRtmz56N1157DSdPnkTnzp0RHR2N9PR0q/WPHDmCcePG4amnnsIvv/yCmJgYxMTE4MyZM2KdFStWYPXq1Vi/fj2OHj0KT09PREdHo7i4WKwzYcIEnD17FgkJCdi9ezd++OEHTJ061eJ6Bw4cwI0bN8StW7duVd8JRERERERERER1nNMlpVauXIkpU6Zg8uTJCA8Px/r166HRaPDxxx9brb9q1SoMHDgQL7/8Mtq3b4+lS5finnvuwdq1awEYR0nFxcVh/vz5GDZsGDp16oRPPvkE169fx65duwAA58+fx969e/Hhhx8iIiICvXv3xpo1a7B161Zcv35dcr2AgACEhISIm0qlqtb+ICIiIiIiIiKqi1wd3QBzWq0WJ06cwLx588QypVKJqKgoJCUlWT0nKSkJs2fPlpRFR0eLCacrV64gNTUVUVFR4nEfHx9EREQgKSkJY8eORVJSEnx9fdG9e3exTlRUFJRKJY4ePYrhw4eL5UOHDkVxcTHatGmDOXPmYOjQoTa/T0lJCUpKSsT3ubm5AACdTgedTmdHj9RNpu9en/tADvabPOw3edhv8rHv5HHmfnPGNhERERHVBU6VlMrIyIBer0dwcLCkPDg4GBcuXLB6TmpqqtX6qamp4nFTWUV1GjZsKDnu6uoKf39/sY6Xlxfeeecd3HfffVAqldixYwdiYmKwa9cum4mp5cuXY/HixRbl+/fvh0ajsXpOfZKQkODoJtRK7Dd52G/ysN/kY9/J44z9VlhY6OgmEBEREdVJTpWUcmaBgYGSEVn33nsvrl+/jrfffttmUmrevHmSc3Jzc9GsWTMMGDAA3t7e1d5mZ6XT6ZCQkID+/fvz8cdKYL/Jw36Th/0mH/tOHmfuN9NIZyIiIiKqWk6VlAoMDISLiwvS0tIk5WlpaQgJCbF6TkhISIX1Ta9paWlo1KiRpE6XLl3EOuUnUi8tLUVmZqbN6wJAREREhXd03d3d4e7ublGuUqmcLuB2BPaDPOw3edhv8rDf5GPfyeOM/eZs7SEiIiKqK5xqonM3Nzd069YNiYmJYpnBYEBiYiIiIyOtnhMZGSmpDxiH/pvqh4aGIiQkRFInNzcXR48eFetERkYiOzsbJ06cEOt89913MBgMiIiIsNneU6dOSRJdRERERERERERkH6caKQUAs2fPxqRJk9C9e3f06NEDcXFxKCgowOTJkwEAEydORJMmTbB8+XIAwPPPP4++ffvinXfeweDBg7F161YcP34cH3zwAQBAoVBg1qxZeP311xEWFobQ0FAsWLAAjRs3RkxMDACgffv2GDhwIKZMmYL169dDp9MhNjYWY8eORePGjQEAmzdvhpubG7p27QoA2LlzJz7++GN8+OGHNdxDRERERERERES1n9MlpcaMGYObN29i4cKFSE1NRZcuXbB3715xovKUlBQolWUDvHr16oX4+HjMnz8fr776KsLCwrBr1y506NBBrDNnzhwUFBRg6tSpyM7ORu/evbF3716o1Wqxzn/+8x/ExsbioYceglKpxIgRI7B69WpJ25YuXYqrV6/C1dUV7dq1w7Zt2zBy5Mhq7hEiIiIiIiIiorrH6ZJSABAbG4vY2Firxw4dOmRRNmrUKIwaNcrm5ykUCixZsgRLliyxWcff3x/x8fE2j0+aNAmTJk2y3WgiIiIiIiIiIrKbU80pRURERERERERE9QOTUkREREREREREVOOYlCIiIiIiIiIiohrHpBQREREREREREdU4JqWIiIiIiIiIiKjGMSlFREREREREREQ1jkkpIiIiIiIiIiKqcUxKERERERERERFRjWNSioiIiIiIiIiIahyTUkREREREREREVOOYlCIiIiKqA9atW4eWLVtCrVYjIiICx44dq7D+9u3b0a5dO6jVanTs2BF79uyRHBcEAQsXLkSjRo3g4eGBqKgoXLp0SVInMzMTEyZMgLe3N3x9ffHUU08hPz9fPJ6cnAyFQmGx/fTTT1X3xYmIiKjWYlKKiIiIqJbbtm0bZs+ejddeew0nT55E586dER0djfT0dKv1jxw5gnHjxuGpp57CL7/8gpiYGMTExODMmTNinRUrVmD16tVYv349jh49Ck9PT0RHR6O4uFisM2HCBJw9exYJCQnYvXs3fvjhB0ydOtXiegcOHMCNGzfErVu3blXfCURERFTrMClFREREVMutXLkSU6ZMweTJkxEeHo7169dDo9Hg448/tlp/1apVGDhwIF5++WW0b98eS5cuxT333IO1a9cCMI6SiouLw/z58zFs2DB06tQJn3zyCa5fv45du3YBAM6fP4+9e/fiww8/REREBHr37o01a9Zg69atuH79uuR6AQEBCAkJETeVSlWt/UFERES1A5NSRERERLWYVqvFiRMnEBUVJZYplUpERUUhKSnJ6jlJSUmS+gAQHR0t1r9y5QpSU1MldXx8fBARESHWSUpKgq+vL7p37y7WiYqKglKpxNGjRyWfPXToUDRs2BC9e/fGV199dWdfmIiIiOoMV0c3gIiIiIjky8jIgF6vR3BwsKQ8ODgYFy5csHpOamqq1fqpqanicVNZRXUaNmwoOe7q6gp/f3+xjpeXF9555x3cd999UCqV2LFjB2JiYrBr1y4MHTrUattKSkpQUlIivs/NzQUA6HQ66HQ62x1Rx5m+e33uAznYb/Kx7+Rhv8nDfpPHmfvN3jYxKUVERERE1SIwMBCzZ88W39977724fv063n77bZtJqeXLl2Px4sUW5fv374dGo6m2ttYWCQkJjm5CrcR+k499Jw/7TR72mzzO2G+FhYV21WNSioiIiKgWCwwMhIuLC9LS0iTlaWlpCAkJsXpOSEhIhfVNr2lpaWjUqJGkTpcuXcQ65SdSLy0tRWZmps3rAkBERESFwfO8efMkiazc3Fw0a9YMAwYMgLe3t83z6jqdToeEhAT079+fc3JVAvtNPvadPOw3edhv8jhzv5lGOt8Ok1JEREREtZibmxu6deuGxMRExMTEAAAMBgMSExMRGxtr9ZzIyEgkJiZi1qxZYllCQgIiIyMBAKGhoQgJCUFiYqKYhMrNzcXRo0cxbdo08TOys7Nx4sQJcTW97777DgaDARERETbbe+rUKUmiqzx3d3e4u7tblKtUKqcLuB2B/SAP+00+9p087Dd52G/yOGO/2dseJqWIiIiIarnZs2dj0qRJ6N69O3r06IG4uDgUFBRg8uTJAICJEyeiSZMmWL58OQDg+eefR9++ffHOO+9g8ODB2Lp1K44fP44PPvgAAKBQKDBr1iy8/vrrCAsLQ2hoKBYsWIDGjRuLia/27dtj4MCBmDJlCtavXw+dTofY2FiMHTsWjRs3BgBs3rwZbm5u6Nq1KwBg586d+Pjjj/Hhhx/WcA8RERGRM2JSioiIiKiWGzNmDG7evImFCxciNTUVXbp0wd69e8WJylNSUqBUli263KtXL8THx2P+/Pl49dVXERYWhl27dqFDhw5inTlz5qCgoABTp05FdnY2evfujb1790KtVot1/vOf/yA2NhYPPfQQlEolRowYgdWrV0vatnTpUly9ehWurq5o164dtm3bhpEjR1ZzjxAREVFtwKQUERERUR0QGxtr83G9Q4cOWZSNGjUKo0aNsvl5CoUCS5YswZIlS2zW8ff3R3x8vM3jkyZNwqRJk2w3moiIiOo15e2rEBERERERERERVS0mpYiIiIiIiIiIqMYxKUVERERERERERDWOSSkiIiIiIiIiIqpxTEoREREREREREVGNY1KKiIiIiIiIiIhqHJNSRERERERERERU45iUIiIiIiIiIiKiGsekFBERERERERER1TgmpYiIiIiIiIiIqMYxKUVERERERERERDWOSSkiIiIiIiIiIqpxTEoREREREREREVGNY1KKiIiIiIiIiIhqHJNSRERERERERERU45iUIiIiIiIiIiKiGsekFBERERERERER1TgmpYiIiIiIiIiIqMYxKUVERERERERERDWOSSkiIiIiIiIiIqpxTEoREREREREREVGNc3V0A4iIiIjsodVrkZafhtT8VMutIBWFukJ8O+FbRzeTiIiIiOzEpBQRERE5jEEw4FbhLfyV/RdO5Z1C5ulMZBRliIkm88RTZlHmbT9Pq9fCzcWtBlpORERERHeKSSkiIiKqUoIgILckF+kF6TZHNZn20/LToBf0ZSdfrvizXZWuCPEKKds8QyTviYiIiKj2YFKKiIiIKmQQDMgqysLNwpu4WXDT+qvZfkZhBrR6baWuEegRCI2gQVhIGBp5N7JINpk2Pw8/KBWcEpOIiIioLmBSioiIqJ4pNZQiozDDrgTTzYKbuFV0CwbBUOnreLl5VTiqybQ19GwIGIA9e/bg4YcfhkqlqoZvTURERETOhkkpIiKiWqxQV4jMokzcKryFW0W3LF4zizIl728W3ERWcZasa/mqfRGkCUKQZ5Dx9Z/9QE2gtPyfVw+Vh92frTPoZLWJiIiIiGovJqWIiIicgN6gR2ZRpkUSyVZyyfRaXFos63pKhRIBHgHGhFK5JJO110BNIFQuHMFERERERFWHSSkiIqIqVFJagixdFs7dPIe80jxkFmUiqyhLTDhlFZftmyehsouzZV/TVemKAI8ABGgCpK8eAfD38JeUmxJNfmo/uChdqu6LExERERFVEpNSRERE5QiCgDxtXlkiqUiaSCqfWDJ/X6grNH7IWXnX9nH3EZNIkoSStaSTxlingVsDKBSKqusAIiIiIqr1SkpLkFWchezibHHLKir3vjgLw9oOw+A2gx3SRialiIiozirSFSGrOEtMKpmSR+bvrZYVZUEv6GVfVwEF/Dz84O/hDz+18dW0Wbz38JMkmFyV/KfZnF6vx3fffYebN29KtoyMDNy8eRPdunXDu+++6+hmEhEREVU5nV6HnJIcmwmljMIM/PbXb/hs12fI1eZaJKDsneahkVcjJqWIiIisKTWUIrs42yJxZE9ySe58SybuLu4WCSR/D3/4q8u9N9u8XLzw43c/YsjgIVxF7h+CIECn08HNzQ2AMdG0ZcsWSZIpPT0df/zxB2bPno3evXtj8+bNAACFQoFBgwZBr7eeJFQqlTX2PYiIiIjsVVxajNySXOQU5xhfS3Ik++WPmb+akkr52nz7LnbL9iEFFPBR+8BX7Stufmo/yfu+LfpWzZeWgUkpIiKqdoIgoEBXYHN+JbGs2DLxlFuSe0fXViqU8FP7SUYu+Xn4wV/tb1lmth/gEVCp1eNMdDodlIq6mygRBAGFhYXIyMiAQqFA8+bNAQClpaV4/fXXkZGRgVu3buHWrVuSEU1DhgzB559/DsCYSJoyZQpKS0utXqNp06bivlKpxP333w+lUomgoCAEBgYiKChI3Fq2bFnt35mIiIjqj5LSEuRp85Bbkou8EuOrPYmk8uVavbbK2tTArYE0qeRhTCp5q7xx86+b6N6xOwI0AWK5+ebt7u3UsSmTUkREZDe9QY/s4mxxNTjJvErlkknlk046g+6Ort3ArYFkxJLpMTjx1bzMLMHUwL2BU/9D7EiCICA/P19MJGVkZMDPzw8REREAAK1Wi8cee0w8ZnotKSkBAAwfPhw7d+4EALi4uGDZsmU2E003b94U9xUKBUaNGgVXV1cx0eTv74+rV69i4MCBYqLL5ODBg9Xx9YmIiKiO0Oq1YgKpfELJ9N5ambW6VZlMAgBvd294u3vDx93H+Kr2kb63Um6eVPJR+9ic3kGn02HPnj14uMfDtXaEPpNSRET1kE6vkySPbhVKk0wZBRk4m3wW6z5bh6ySsnp3skIcAKiUKquPw5nPsyTZ/+e4r9qXcy3dhiAIyM3NFRNH5kmkli1bYvjw4QCAoqIi9OjRQzym00mThTExMfjiiy8AACqVCrt27bKoA0B8FM9EoVDghRdegLu7OwICAhAYGIiAgADJqCZz8fHxkvemoCoyMrLWBlVERERkH0EQUKgrRJ42D3klecgqzMKZ/DMwXDKgSF+EvJI88Zj5qylxJHlfkocSfUmVt9FT5YkG7g3g7e6NBm4N4KP2sZpIsplsUvvAy82LN0dvgxE+EVEtptVrkVWUJRm5ZEowWRvNZNrytHn2XSDberG3u7ckiRSgCbAYuVR+ziU/tR80Kg1XibOTXq/H1atXLRJMptfOnTtj2rRpAICCggL4+vraHKUUExMjJqXUajV+//13aLVldwE9PDzEJFJoaKhYrlAosG7dOnh6ekoSTYGBgfD09LT4/3LFihVV3Q1ERETkJEoNpcjX5ouJIFNyyFaiKE9rO7GUr82HQTBYXuSPO2ujRqVBA7d/EklmCSXTaCVbx8q/93LzgovS5c4a42AGgwE5OTnIyclBdna2xf4999yD++67z9HNZFKKiMgZmI9cMh+1ZEos3Sq8hcxiy6ST3ZMfWqGAAr5qX4uJuv09/OHj5oPUK6m4r9t9aOjVEAEeAeIxX7UvVC4cySKHVqtFQkKCZN4l85FNffr0wZIlSwAYRzS1atXK5mcNGzZMTEppNBq4uLigtLQUGo1GkjwKCAgQH8cDjImmhIQEeHt7IyAgAAEBAdBoNDavM2XKlCr69kRERFTTys+PZE8iydaxotKiKm+fAgp4uXnB290bCq0CIf4h8FYbk0MN3BvA282YMDK9N38VE03uZYmkujKyXhAEFBQUICcnBxqNBn5+fgCA9PR07Ny5U0wsZWVl4dy5c9iwYQNyc3MxefJkPPXUUwCAU6dOoVu3bjav8corrzApRURU19zusbjyI5hM+3cymbcCCsmIJPMEkvl++c1X7WvzDpBOp8Oegj14uGPtfT69OpSWliIzMxMA0LBhQwBAYWEh1qxZIyaY0tPTcfnyZcyZMweZmZkYPnw4PvjgAwDGpNSQIUNsfr6Pj4+47+npCT8/PzRo0EBMMJlvHTp0EOsqFAr8+eef8PPzg4fH7Sdn79Onj6zvT0RERNVPp9dJkkfW5j6yNi+StTmTqnp+JMA4HYMpGSQmj/4ZZVQ+aWQtkWReplFpoFQoy+ZGerhuxJ56vR5ZWVmSkUnmr/fffz+6d+8OADh9+jRmzpxpMaLJtPLw8uXLMXfuXADAtWvXxJuS1vTu3Vvc9/X1BWAcEe/j4wMfHx/4+vqK++axpCMxKUVEZIXpsThriaTyI5fMy+x+LM4GX7WvNKmkCYC/+p9Xa0knTQB83H1q/fDimma6+3Tr1i1kZmbi1q1bCAwMRJcuXQAAOTk5iI2NlYxkunXrFnJycgAATzzxBDZu3Ch+nilQsCYtLU3c9/T0RM+ePcVRSuYjmgIDAyUjoxQKhZgAs0fjxo3trktERERVyzRH0q2CW/i7+G8cv34chfpCMVlksWmtJ5hyS3JRXFpc5e3zcPWoMJFk85iVZJK7q3uVt8+Z6PV65OXlITc3V0zgAMBff/2F3bt3S5JL5vsvvPACRo8eDQD4/vvv8dBDD9m8xptvvikmpXQ6HQ4dOmS1nouLi7jADACEhIQgJiZGTDB5eXnhxo0b6NmzJwICAhAeHi7WbdmyJUpKSizmAXU2TEoRUZ1lEAzIKspCakkqTtw4gTxdnmQ1OHHfStmdPBYHWCaXyieU/Dz8EOARIEk2+an9mFySQavVIjMzU0wumbbMzEyEh4dj8ODBAIyrvz344INiPfM5lQBg0qRJ2LRpEwDjBN+ffvqpzWsWF5cFixqNBk8++SR8fHwQGBgIX19fXL16Ff3790dwcDBCQkLEugqFAklJSVX47YmIiOhO6A16SULI3s3aOZI5ki7cedvcXdwtHlGzNj+SzeN18LE2exQWFuLvv/8WRxzl5uZK9ocMGYKuXbsCAH788Ue89NJLkjr5+WX/HfD+++/j2WefBQD8/vvveO6552xe98qVK+K+aZSSl5eXZISS6bVdu3Zi3VatWuGzzz6TjGIy7Ws00vlYGzduLC5IA6DCEWZKpdLpE1IAk1JE5OQMggE5xTnILs4Wt6ziLGlSqSgLmcWZFmXZxdkQIBg/6Hzlr22ac8k8ceTv4W8xcql8wqmix+Lo9kpKSnDy5Ekx0WRKIpn2H3jgAUydOhUA8Pfff6Np06Y2P+uJJ54Qk1Kenp44e/as5LibmxsCAgLg7++PRo0aieUajQb/+te/4OfnJ45mMm1+fn5wdZX+8/nRRx+J+6bgoG/fvnVi+DkREZEz0uq1lU4kWdsKdAVV2i4FFPBQeiDAK0BMDtnarCWQzEcoubk4f0Khquj1euTn5yMlJQWFhYXIzc1FmzZtxNV7T58+ja1bt4rJo/Kv//rXvxATEwMA2Lt3L0aMGGHzWg0bNhSTUsXFxfjpp5+s1nN3d5fcxGzWrBkeffRRq0kmX19fdOzYUazbpUsX6HQ6i5jRGh8fH4wdO/a29eoqJqWIqFoZBAPySvIkSaXyW1Zxls1juSW5ZYklmdyV7gj0DBRHKJVfJU5S9s8+H4uTT6vVIisrC66urggICAAAZGdn46OPPpIkmsy3CRMm4PXXXwcAZGRkoFevXjY/383NTUxK+fv7AzCOQPLz8xMTTKYEkvnkjRqNBgcOHBCP+/v7W11BzuTFF1+skv4gIiIio1JDqcWcR7d7b2s+pRJ9ye0vWAluLm6SpJCP2qcsgeRWcXLJfFNBhW+//bbOzI10O4IgQBAEKJVKAEBqairOnj1rc5TS9OnTxekSdu7ciZkzZyI3Nxd5eZZTYGzduhVjxowBYByl9MYbb9hsR3p6urjv6+sLb29veHt7iyOPTPve3t5o27atWLdz58744osvrNZ1d5c+ptimTRvs2LHDrn5RKpVin1DFmJQiIpvMhzPnFOcgpyTH5r7F+39GN+WU5Fhf7rWSPFw94Kv2ha/aFz5qH2lSySyhZHpv2vdy8ULi/sR6ExhUFYPBgPz8fPz555/Iz89HVlYWMjMz0apVK3EVj+vXr2PmzJniMdNmGvL8wgsvYOXKlQCMw6hfeuklm9e7du2auO/v74+77roL/v7+ks2UdOrcubNY18PDAxkZGfD19YWLy+0TiBU9209ERERSgiCgQFuA4pJi5JXkIV+bL07AbWvffK6k8smk6li9zVPlaXfCqKIRS1U1T5JOp6uSz6lu5qu75ebmWmwDBw4UR5EfOHAAH374odV6ubm5+OabbxAdHQ0A+Oabb/D000/bvG7//v3FpJQgCPj7778lx93d3cWkkHns3q5dO8TGxkqSRub7bdq0Eev269dPnAf0dgIDA8URVuQYTEoR1UGmu1AVrtJRkleWSPoniVR+/04n7Tbn5uIGP7UffNW+8PPwExNMvu6+Zfs2Nh+1D9SualnXrS2BQXUqLi7GhQsXxORRVlaWZD8qKgojR44EAFy6dAkRERHIzs6GIFiOUJs1a5ZkaVlbd4sUCgWKisoCT39/f0yYMMEi0WTazB/B8/DwwOXLl+3+fqbRWERERPWZIAgo0ZegQFuAfG0+8rX5KNCZ7WsLrCeUdPli3Ggt2ST8emcj1q0xzZVU0TxJFc2RZNrq21xJgiCguLhYHFmUm5uLtm3bwtPTEwBw/PhxHDx4UDxuqmN6Xb9+PTp16gQAePfddyscFb5v3z4xKXX16lVs27bNZl3zBFDjxo3RoUMHm6OU7r77brHugw8+iBMnTsDb2xsajQZHjhzBsGHDrN5Ivvvuu7FmzZrKdRjVCvXnTzCRk9PqtZKAIE/7T1Dwz35WYRaOpx7H4e8Oo0BXUOESsFV9F8rNxQ0+7j7wUfvAx904lFmyb+VY+cSS3KRSfafVasWVPXx8fBAcHAzAODR648aNyM7ORlZWlsXrtGnTxEDj8uXL4nPz1nh4eIhJKU9PT2RlZYnHNBoN/Pz8xK1ly5biscDAQKxduxZ+fn4WSSZfX1/JkGW1Wl3hxOFERET1hd6gR4GuAAXaAhTqClGg++dVWyCWW00q/bNfUdJJL+irrd1ebl6S1di83Lyk++VWbbM1AXd9mytJEAQUFhZCrVaLo7r/+OMPXLhwwSJpZHpdvHixeMNu3bp1WLFihXhMr5f+f/zTTz8hIiICgHHFtzlz5thsS2pqqpiU8vb2BmBc3c2UMCq/mURGRiIuLk6SXDLfzG8QDho0CIMGDbKrb0xxI2C8kcynGuonJqWIZDIfjWSePKoosWTtuOlVq9fe/qIAkGp/G03PxlcUGJgSSrb2fdx96vyyr9VJr9dbLBdrvoRsZGQkevbsCQA4f/48pkyZIkkwFRYWip+1ePFiLFy4EABw69YtvPrqqzava/44XEBAAEJCQsTkkXmSyd/fXzJ/U3BwMM6dOwcvLy8cPXrU5t0qwDi30/Tp0++of4iIiJyJIAgoLi1Goa7Q5maeRDK9l+zf5rjdMd8dULuq4anyhJebF7zcvODp5glPlafVJJKtZJNaqcbRw0cRMygGPhofKBX1b36cjIwMpKamSkYemW+mx8kA46Inn332GXJzc3Hjxg0AQG5uLvLz82EwGHDhwgVxLqPNmzeLc2la88wzz4hJqaKiIqSkpFjU8fLygre3tyRJ1alTJzz++ONo0KABvL29Ja8+Pj7iY3MA8Nhjj2H8+PHw8PCwOb+mSXh4OMLDw+3rNKJKYlKK6gVTgGG6k2RKFpknjCz2b/O8fFVPrmji7uIuBgXmr14qL+Sk5SC8dTh8PXwthjaXvwNVlc/G11emZ+2zs7Ph5eUlLu16/fp1fPnllxZJJtPrc889h8ceewyA8e5V7969bV5j0aJFYlLKYDDgxx9/tFrP/G4VAISEhGDy5Mnw9fWFn58ffH19JfvmI5pCQkLE4Oh2XFxc0L59e96tIiIip2KeLCoqLRITREU6s30r5XkleTh/7Ty+2vMVivUVJ5tMW01RQCEmizzdPKFRacREkqfbPwklVdl++SSTeZlY380LGpWmSh5p0+l0uKS6BC83L6dPSBUWFiInJwf5+fnIy8tDfn6+ZP/xxx+Hm5txdNaWLVuQkJBgUce0f+bMGYSEhAAw3hBcu3atzeuOGjVKTEpduXIFiYmJNuuaT+QdGhqKe++9V5I0Mt83XxF43Lhx6NOnj+S4l5eX1Um0+/fvj/79+9vVZ2o1n2Ig58CkFDkdQRBQVFpkMTy5/BBlUxLJaqLJLMlkKquu4cxuLm4V3m0qn1yq6NXLzQsqF+uJANMy8w9HccJuexUVFeHq1au4fPkyvv/+ezFgMU3KOGDAAHF+pBMnTmD27NmSFUJycnLEu09xcXF4/vnnAQB//vknnnvuOZvXHThwoLhvSmR5enpKlo318fGBn5+f5Ln6Fi1aYPv27WJiyfTq4+NjMYl3QEAAPv744yrpJyIiIrl0ep1FUsiUELKWJKqwzm2STXcko/KnuLm4QaPSWN08VWVJJPOEkj37GpUGnm6ecHdxv+0IlbqmqKgIeXl5KCgoQH5+vvhq2h8/frzYJ1u2bMHRo0clx037+fn5OH36tJhYefbZZ7Flyxab133kkUfQsGFDAMCxY8cqrJuXlycmpQICAhAYGCgmjconkTQajXjeyJEjER4eDg8PD5w9exb9+/eHn5+fWNc07xMAPPnkk3jyySft6rMmTZqgSZMmdtUlqo2YlCJZDIKhbAizjaHJ5s/Gm+/nleThcsplvLf1vbJn48s9Dy+g6idUNNGoNOKdJPMhymIyydoz8hXs16dn4quTIAjQarXicGjzO1d33323+I/xuXPn8Omnn4qJpfIrhixbtgyjR48GABw8eBCDBw+2eU1PT08xKVVcXIwffvjBaj1XV1eUlJSNjGvSpAmGDx8uJozKv3bo0EGs2759e2i1WrsSiV5eXuLcTkRERHLo9DoUlxajqLQIRboii31Tksc8KVR+X0wc3aZeoa6wWucwskWlVInJIQ+VR9m+q4ek3MPVAx4uHriech0d23VEA/cGNpNM5TcPlUe9mkC7vFu3biEjIwPJyck4evQotFotCgoKUFBQgNLSUnFEOACsX78ep06dQmFhoUWyqaSkBOfPnxfrjh07Fl999ZXN644cORLu7saR/vv3769wPsq8vDwxKWUaOeTl5QUvLy9xNJHp1dywYcPQvHlzyXHz/ebNm4t1Fy1ahEWLFtnVZ126dEGXLl2g0+mgVCpxzz338EYykR2c8m/adevW4e2330Zqaio6d+6MNWvWoEePHjbrb9++HQsWLEBycjLCwsLw1ltv4eGHHxaPC4KA1157Df/+97+RnZ2N++67D++//z7CwsLEOpmZmZgxYwa+/vprKJVKjBgxAqtWrZL8Jfbbb79h+vTp+PnnnxEUFIQZM2ZUOJFcTREEAVq9FsWlxWLgYdovLi0WgxBJWfmgo5IBSJVMpG3HKp2mBJL5cGXTEGVTYsg8uVQ+wVS+zFPlCRfl7ZeNp4oJgoCioiIxODFtrVu3FicrvHDhAvbu3WuRYDIlnRYsWIC+ffsCAD7//HOMGzcOpaWlVq+3adMmTJo0CYBxlNLy5cttti0tLU3c9/b2hqenJ9zd3REUFARfX1/JBI3t2rUT67Zr1w7btm2TrBBiSjJpNBrJnczQ0FDs3LnTrr5SKpVWh1cTEVU1xk+OZxAMKCktgVavRYm+BCWlJeKreaxWXFqMEn2J9H1piUW8Zl6nUFuIv278hXc/fRfF+rJ4zxTDmfYdkSQCjI+i2UoSmcokSaMKjt0u2VSZZJE40vy+2j3S3LTqmlarFR8XA4BTp04hMzMThYWFKCwsRFFRkbjv5uaGGTNmiHUXLVqEM2fOiHGbKYlUUFAAjUaDCxcuiHVHjBiB77//3mpb3N3dJUmpb775Brt377bZdq1WKz46Z/q7QaPRwNPTE15eXuKrl5cXdDqdmJQaNmwYQkNDJcdN+6Y5kkxWrVqFdevW2TXyLCoqClFRUbetR0Q1w+mSUtu2bcPs2bOxfv16REREIC4uDtHR0bh48aI45NLckSNHMG7cOCxfvhxDhgxBfHw8YmJicPLkSXG0wooVK7B69Wps3rwZoaGhWLBgAaKjo3Hu3Dkxuz5hwgTcuHEDCQkJ0Ol0mDx5MqZOnYr4+HgAEB/1iYqKwvr163H69Gk8+eST8PX1xdSpU2uug8oRBAGqpSqHBSAA4OHqIT4PbxqObHOossoTahc1ki8lI6JrBHzUPhbJJvPn4Z39+XVnZRpxVFxcjKKiIslWXFyMe++9V0wenThxAvv37xfvapXf3nzzTXTv3h2AcVLG2NhYFBQUQBAsR7N98cUXiImJET/3hRdesNlGU5IJMAY35gkpDw8PcaizKQgxCQsLw8yZMy2WlzXtt2rVSqzbu3dvZGVlGYPRhysORgMCAsQRVkREtQ3jp8r74eoPSLicAK1eK90MWssys8080VSiL5GUlRqs31ypUnm3r2Li7uIujhhSu6rFffORRKakj81jFeybJ4zcXNzq3aNo6enpKCwsRHFxsbiZYi2NRiPefAOADRs2ICMjQzxuXj8kJATvvPOOWHfo0KG4ePGiJMFUVGS8Idy6dWtcunRJrDt58mScOnXKavuCg4MlSanvvvsOhw8ftlrX/DE0AOLjZq6urvDz84Onp6eYSPL09ITBYBBvuo0bNw733nuvJNFknkAyn4Lg448/xpYtW+y6YTdy5Ei7R5DX5oQjUX2nEKz9l6UDRURE4N577xUnlDMYDGjWrBlmzJiBuXPnWtQfM2YMCgoKJNn5nj17okuXLli/fj0EQUDjxo3x4osv4qWXXgIA5OTkIDg4GJs2bcLYsWNx/vx5hIeH4+effxb/43vv3r14+OGHce3aNTRu3Bjvv/8+/u///g+pqalipn/u3LnYtWuX5K5CRXJzc+Hj44OcnByLSYvvhGaZRjJyyRR4mIIP075Y5uoBd1f3siDEzgDE9GqegPJQeVQ6cSTesbpNksCZlJaWQq/Xw2AwwGAwSPYNBgP8/PzEf3Bv3bqFzMxMaLVaq1vfvn3Ff/h//vlnnDhxwmbdF198UZzoMD4+XlyKtaSkxCLZtGfPHnTt2hWA8T8kXnnlFZvf57vvvsODDz4IwHhnPTY21mbdL7/8EkOHDgVgfLZ/4sSJkuNqtVoMUNauXYtHHnkEAHD06FHExcVJhk+b7/fq1QuhoaEAjJNTZmZmSgKgqlIbf2/OgP0mH/tOHmfut+r697sqMX6qvOWHl+PV72yvYloV3Fzc4O7ibnx1dbeIydxdbl9mOk+lUOH3c7+jxz090EDdwCLRZB73mWI9Z7i5JwgCBEEQYybzfVdXV3FUjMFgwM2bN6HT6VBaWgqdTifZ9/X1FW886fV67Nu3z6KOab958+bi/I46nQ6PP/44mjVrhtLSUpSUlECr1aKkpAQlJSXo2LEjFixYILa3T58+yM7Otqin1WoRERGBAwcOiHWDgoKQkWF9sqpu3brh+PHj4vu77roLV65csVq3bdu2kj8PnTp1wunTp63Wbdy4Mf7++2/x/ejRo3Hu3DloNBpoNBp4eHiIrwEBAVi1apVY9/PPP0d6erokuWSebDJfXU0QBJSWljrt38vOzJn/PXNm7Dd5nLnf7P3326lGSmm1Wpw4cQLz5s0Ty5RKJaKiopCUlGT1nKSkJMyePVtSFh0djV27dgEwroKQmpoqGaLp4+ODiIgIJCUlYezYsUhKSoKvr68YUAHGYZ1KpRJHjx7F8OHDkZSUhD59+ogBlek6b731FrKysuDn52fRNtM/Yia5ubkAIP6jWVUuTb+E+yLuQ05mDqA3Dp8GgOJ//tetWzfs2bNHrN+lSxebK3G1b98ehw4dEt/fd999+OOPP6zWbdGiBY4dOwY9jKO0oqKibP4DGhQUhDNnzgAwfv8lS5Zg8uTJVus2aNBAcs0xY8ZI2mROqVRKvssTTzwh+a7lpaSkiHd3n3vuOfz3v/+VBEfm2/Xr18X/X6dNm4aPPvrI5uf++eef4rKtixYtqnCVjrNnz4qPPnz++edYsWKFzbqjR49GYGAgAODSpUv4+eefbdbNzs4Wf1emv5BcXV3h4eEBDw8PqNVqqNVqeHh4wNXVVazbrl07PPHEExZ3wLy8vKDRaNCxY0ex7qBBg3D+/HlJEFN+Am5T3XvuuQeffPKJzfaa11WpVAgODgZgDIKq8s+H6bOq8jPrA/abfOw7eZy535yxTeYYP8nTJbgL+qr74qcjP0GhVwAGGOMovcL4alDgmaefQacOneCmdEPS/5Kw6aNNgL5cvX9e31nxDgZHD4abixv27t6L2OdixZjMAAOK/vkfAKxZs0Ycnbt3717J6OHyVqxYgUmTJkGn0+HdA+9ixoszbNZdvHgxnn32WQDA0Z+OVjiv4pw5c/Diiy8CMMYmpptV1syYMUNM3Fy5cgUREREWySbTNm3aNLz99tsAjKvVmq8GW97kyZOxYcMGAEBWVpY4ubQ1Y8eOFeMKnU5X4XcbMmQIHnroIbHujh07bE4RcOvWLUni9vTp08jOzrZaNy8vT/IbNCV/zGMsd3d3qNVqtG3bVlL30UcfRVZWlqSO6dzAwEBJ3ffeew86nU6M4conm8zr/uc//7HZD6bvbzJs2DC765q/d/a/A50N+00e9ps8ztxv9rbJqZJSGRkZ0Ov14n+cmgQHB9u8m5aammq1fmpqqnjcVFZRnfJD211dXeHv7y+pYxrVYf4ZpmPWgqrly5dj8eLFFuX79++3GCJ7p25dv4X8/Hyrx1JSUiSJmrS0NGRlZVmt+/fff0vqXr9+3WZdNzc3Sd1r167ZrCsIgqRuUVGRzbrFxcWSusnJyTbrKpVKSd0///zTZiABGAM/U2B86dIlMdC1Zt++fWJG99q1azbrAUBiYiKCgoIAADdu3IBGo4Grq6vV7fDhw+Kwa51Oh549e9qse/r0aTHp5u3tjeeeew5ubm7i5u7uDjc3N6hUKqSnp4t90bx5c+zYscMiYWSSmZkp6TfTI3fW/Pbbb/jtt98q/P61QUJCgqObUCux3+Rj38njjP1WWFhzS8TLwfhJvrA/wvD9V9bnzQGABg80gJ+3sY3CeQH5v1iPtQDgj5N/4Jj7MQDAL8d/QXZWts26P//8s/ho+rFjx2zGOYDxcXhTjKHX6yus+8svv4j/vl+8eLHCur/99ptYNzk5ucL46ezZs2LdGzduVFj30qVLYt3MzEyb9QBpjGp6PM3FxQUuLi5wdXUV911cXJCbmyvWFQQBrVq1sqhj2nx8fCRxjmmuNJVKJcZYKpUKKpUKQUFBkrqzZs2CQqEQ65i/qtVqSd1Vq1ZV+Miied3777+/wr6wdlO1oji1Jjnj38u1AftNHvabPM7Yb/bGT06VlKpr5s2bJ7kLmZubi2bNmmHAgAFVPvz/p59+gsFgsHpMrVZL7lIdPnzY5t0id3d3SfCYmJgIrVZrta5KpZLM39O+fXvJnU1zLi4u4uggnU6H9PR0dO/e3epjWkqlEm3atBHfd+zYEQUFBRb1TEFA27ZtxbLOnTtbrWvSunVr8Rn2rl27Ii8vT5yI2rS5uLhAqVQiODhYrPvAAw+gtLTUoq5pUygUYnvMJ4m9ncrU1el0SEhIQP/+/Z1uaKYzY7/Jw36Tj30njzP3m7P8h2F9UZPxU8+ePTFz5kybx5s2bSomj3r16oVnnnnGZt0mTZqgQYMGAIxzGlY0+qlRo0biJM33338/xo4da7NucHAw/Pz8oNPpUFxcjJMnT9p8zL1hw4binJEPPvggBg0aZFHHFK+YlroHjKPTKpr42c/PT0yMabVaMcFiHgeZ9r28vMRko8FgQHR0tNV6CoUCKpVKvFkoCAJKSkrsnpeqopFS5kx36u39u6UysVld58x/Lzsz9ps87Dd5nLnf7I2fnCopFRgYCBcXF8nqWYBxZI+t4bwhISEV1je9pqWliXPzmN536dJFrJOeni75jNLSUmRmZko+x9p1zK9Rnru7u/icvDnTnZmqdPfdd9tdt3379nbXNU/43I55Iul2GjZsiA4dOtjVD3fddZfdn1vREPHyzJd7vR3z1T0crTp+P/UB+00e9pt87Dt5nLHfnK095TF+ki84ONhiNJgtQUFBYmLmdgICAhAQEGBXXX9/fzGRdDtqtdru+EmlUqFjx452fa5KpbI7lqxMXcA4B5IzcMa/W2oL9p087Dd52G/yOGO/2dsex89+aMbNzQ3dunVDYmKiWGYwGJCYmIjIyEir50RGRkrqA8aha6b6oaGhCAkJkdTJzc3F0aNHxTqRkZHIzs7GiRMnxDrfffcdDAYDIiIixDo//PCD5LnIhIQEtG3b1urQcyIiIqKawPiJiIiIaiunSkoBwOzZs/Hvf/8bmzdvxvnz5zFt2jQUFBSIk2JPnDhRMpHn888/j7179+Kdd97BhQsXsGjRIhw/flxcTUyhUGDWrFl4/fXX8dVXX+H06dOYOHEiGjduLM6j0759ewwcOBBTpkzBsWPH8OOPPyI2NhZjx44V7+6MHz8ebm5ueOqpp3D27Fls27YNq1atspgklIiIiKimMX4iIiKi2sipHt8DjCut3bx5EwsXLkRqaiq6dOmCvXv3ikOrU1JSxHl+AOPz/fHx8Zg/fz5effVVhIWFYdeuXejQoYNYZ86cOSgoKMDUqVORnZ2N3r17Y+/eveIqbIBx5YrY2Fg89NBDUCqVGDFiBFavXi0e9/Hxwf79+zF9+nR069YNgYGBWLhwIaZOnVoDvUJERERkG+MnIiIiqo2cLikFALGxseKduvIOHTpkUTZq1CiMGjXK5ucpFAosWbIES5YssVnH398f8fHxFbarU6dOOHz4cIV1iIiIiByB8RMRERHVNk73+B4REREREREREdV9TEoREREREREREVGNY1KKiIiIiIiIiIhqHJNSRERERERERERU45iUIiIiIiIiIiKiGsekFBERERERERER1TgmpYiIiIiIiIiIqMYxKUVERERERERERDWOSSkiIiIiIiIiIqpxro5uQH0iCAIAIDc318EtcSydTofCwkLk5uZCpVI5ujm1BvtNHvabPOw3+dh38jhzv5n+3Tb9O041i/GTkTP/GXFm7Df52HfysN/kYb/J48z9Zm/8xKRUDcrLywMANGvWzMEtISIiosrKy8uDj4+Po5tR7zB+IiIiqr1uFz8pBN72qzEGgwHXr19HgwYNoFAoHN0ch8nNzUWzZs3w119/wdvb29HNqTXYb/Kw3+Rhv8nHvpPHmftNEATk5eWhcePGUCo580FNY/xk5Mx/RpwZ+00+9p087Dd52G/yOHO/2Rs/caRUDVIqlWjatKmjm+E0vL29ne4PTm3AfpOH/SYP+00+9p08ztpvHCHlOIyfpJz1z4izY7/Jx76Th/0mD/tNHmftN3viJ97uIyIiIiIiIiKiGsekFBERERERERER1TgmpajGubu747XXXoO7u7ujm1KrsN/kYb/Jw36Tj30nD/uNqGL8MyIP+00+9p087Dd52G/y1IV+40TnRERERERERERU4zhSioiIiIiIiIiIahyTUkREREREREREVOOYlCIiIiIiIiIiohrHpBRVqffffx+dOnWCt7c3vL29ERkZiW+//bbCc7Zv34527dpBrVajY8eO2LNnTw211nlUtt82bdoEhUIh2dRqdQ222Dm9+eabUCgUmDVrVoX1+JuTsqff+JszWrRokUU/tGvXrsJz+HurfL/x90b1DeMn+RhD3TnGT/IxhrIP4yd56kv8xKQUVammTZvizTffxIkTJ3D8+HH069cPw4YNw9mzZ63WP3LkCMaNG4ennnoKv/zyC2JiYhATE4MzZ87UcMsdq7L9BgDe3t64ceOGuF29erUGW+x8fv75Z2zYsAGdOnWqsB5/c1L29hvA35zJ3XffLemH//3vfzbr8vdWpjL9BvD3RvUL4yf5GEPdGcZP8jGGqhzGT/LUi/hJIKpmfn5+wocffmj12OjRo4XBgwdLyiIiIoRnnnmmJprm1Crqt40bNwo+Pj412yAnlpeXJ4SFhQkJCQlC3759heeff95mXf7mylSm3/ibM3rttdeEzp07212fvzejyvYbf29EjJ/uBGMo+zB+ko8xVOUwfpKnvsRPHClF1Uav12Pr1q0oKChAZGSk1TpJSUmIioqSlEVHRyMpKakmmuiU7Ok3AMjPz0eLFi3QrFmz294RrOumT5+OwYMHW/yWrOFvrkxl+g3gb87k0qVLaNy4Me666y5MmDABKSkpNuvy91amMv0G8PdG9RfjJ/kYQ1UO4yf5GENVHuMneepD/OTq6AZQ3XP69GlERkaiuLgYXl5e+OKLLxAeHm61bmpqKoKDgyVlwcHBSE1NrYmmOpXK9Fvbtm3x8ccfo1OnTsjJycG//vUv9OrVC2fPnkXTpk1ruOWOtXXrVpw8eRI///yzXfX5mzOqbL/xN2cUERGBTZs2oW3btrhx4wYWL16M+++/H2fOnEGDBg0s6vP3ZlTZfuPvjeojxk/yMYaqPMZP8jGGqjzGT/LUm/jJ0UO1qO4pKSkRLl26JBw/flyYO3euEBgYKJw9e9ZqXZVKJcTHx0vK1q1bJzRs2LAmmupUKtNv5Wm1WqFVq1bC/Pnzq7mVziUlJUVo2LCh8Ouvv4pltxtCzd+cvH4rr77+5srLysoSvL29bT4mwt+bdbfrt/L4e6P6gPGTfIyhKofxk3yMoaoG4yd56mr8xJFSVOXc3NzQunVrAEC3bt3w888/Y9WqVdiwYYNF3ZCQEKSlpUnK0tLSEBISUiNtdSaV6bfyVCoVunbtij/++KO6m+lUTpw4gfT0dNxzzz1imV6vxw8//IC1a9eipKQELi4uknP4m5PXb+XV199ceb6+vmjTpo3NfuDvzbrb9Vt5/L1RfcD4ST7GUJXD+Ek+xlBVg/GTPHU1fuKcUlTtDAYDSkpKrB6LjIxEYmKipCwhIaHCeQDqi4r6rTy9Xo/Tp0+jUaNG1dwq5/LQQw/h9OnTOHXqlLh1794dEyZMwKlTp6wGBfzNyeu38urrb668/Px8XL582WY/8Pdm3e36rTz+3qg+YvwkH2OoijF+ko8xVNVg/CRPnY2fHD1Ui+qWuXPnCt9//71w5coV4bfffhPmzp0rKBQKYf/+/YIgCMLjjz8uzJ07V6z/448/Cq6ursK//vUv4fz588Jrr70mqFQq4fTp0476Cg5R2X5bvHixsG/fPuHy5cvCiRMnhLFjxwpqtdruoep1Wfkh1PzN2ed2/cbfnNGLL74oHDp0SLhy5Yrw448/ClFRUUJgYKCQnp4uCAJ/b7ZUtt/4e6P6hvGTfIyhqgbjJ/kYQ90e4yd56kv8xMf3qEqlp6dj4sSJuHHjBnx8fNCpUyfs27cP/fv3BwCkpKRAqSwboNerVy/Ex8dj/vz5ePXVVxEWFoZdu3ahQ4cOjvoKDlHZfsvKysKUKVOQmpoKPz8/dOvWDUeOHLE5qWd9xt+cPPzNWXft2jWMGzcOt27dQlBQEHr37o2ffvoJQUFBAPh7s6Wy/cbfG9U3jJ/kYwxVPfibk4+/OUuMn+SpL/GTQhAEwdGNICIiIiIiIiKi+oVzShERERERERERUY1jUoqIiIiIiIiIiGock1JERERERERERFTjmJQiIiIiIiIiIqIax6QUERERERERERHVOCaliIiIiIiIiIioxjEpRURERERERERENY5JKSIiIiIiIiIiqnFMShER3YHk5GQoFAps2rTJ0U2RLT8/Hw0bNsR//vMfWeefO3cOrq6uOHPmTBW3jIiIiOoqxlCMoYgAJqWIqApcuXIFsbGxaNOmDTQaDTQaDcLDwzF9+nT89ttvsj7zyJEjWLRoEbKzs6usnUOHDoVGo0FeXp7NOhMmTICbmxtu3bol+zp79uzBokWLZJ9f01atWoUGDRpg7NixAIBOnTqhefPmEATB5jn33XcfgoODUVpaivDwcAwePBgLFy6sqSYTERHVCYyhpBhDEdU/TEoR0R3ZvXs3OnTogC1btiAqKgrvvvsuVq1ahUGDBmHPnj3o0qULrl69WunPPXLkCBYvXlylAdWECRNQVFSEL774wurxwsJCfPnllxg4cCACAgJkX2fPnj1YvHix7PNrkk6nw6pVq/D000/DxcUFgLGf/vrrLxw+fNjqOcnJyUhKSsKYMWPg6uoKAHj22WfxxRdf4PLlyzXWdiIiotqMMZQlxlBE9Q+TUkQk2+XLlzF27Fi0aNECFy5cwHvvvYdnnnkGU6ZMwTvvvINLly4hLi4OSqVz/FUzdOhQNGjQAPHx8VaPf/nllygoKMCECRNquGWOs3v3bty8eROjR48Wy8aPHw+FQmGznz777DMIgiDpp6ioKPj5+WHz5s3V3mYiIqLajjFU7ccYiqiKCEREMk2dOlUAIPz00092n/Prr78KkyZNEkJDQwV3d3chODhYmDx5spCRkSHWee211wQAFtuVK1fEOlu2bBHuueceQa1WC35+fsKYMWOElJSU215/0qRJgqurq5CWlmZxbMiQIUKDBg2EwsJCQRAE4fLly8LIkSMFPz8/wcPDQ4iIiBB2794tOefKlSsCAGHjxo3i51tru8nbb78tREZGCv7+/oJarRbuueceYfv27RZtKSwsFGbMmCEEBAQIXl5ewiOPPCJcu3ZNACC89tprkrrXrl0TJk+eLDRs2FBwc3MTwsPDhY8++ui2fSEIgjBx4kShZcuWFuV9+/YVAgICBK1Wa3GsQ4cOQqtWrSzKhw8fLnTq1Mmu6xIREdVnjKEYQ5ljDEX1mXOk3omoVtq9ezdat26NiIgIu89JSEjAn3/+icmTJ2PNmjUYO3Ystm7diocfflh8/v7RRx/FuHHjAADvvvsutmzZgi1btiAoKAgAsGzZMkycOBFhYWFYuXIlZs2ahcTERPTp0+e2Q9UnTJiA0tJS/Pe//5WUZ2ZmYt++fRg+fDg8PDyQlpaGXr16Yd++fXjuueewbNkyFBcXY+jQoTaHrgPAM888g/79+wOA2O4tW7aIx1etWoWuXbtiyZIleOONN+Dq6opRo0bhm2++kXzOE088gTVr1uDhhx/GW2+9BQ8PDwwePNjiemlpaejZsycOHDiA2NhYrFq1Cq1bt8ZTTz2FuLi4CvsCMA7xv+eee6z2061bt7Bv3z5J+enTp3HmzBmrd0K7deuGM2fOIDc397bXJSIiqs8YQ1liDMUYiuopR2fFiKh2ysnJEQAIMTExFseysrKEmzdvipvprpkgCJJ9k88++0wAIPzwww9i2dtvv21xZ08QBCE5OVlwcXERli1bJik/ffq04OrqalFeXmlpqdCoUSMhMjJSUr5+/XoBgLBv3z5BEARh1qxZAgDh8OHDYp28vDwhNDRUaNmypaDX6wVBsLzLJwiCMH36dMHWX6/lv79WqxU6dOgg9OvXTyw7ceKEAECYNWuWpO4TTzxhcZfvqaeeEho1aiS5SyoIgjB27FjBx8fHan+b6HQ6QaFQCC+++KLFsczMTMHd3V0YN26cpHzu3LkCAOHixYsW58THxwsAhKNHj9q8JhERUX3HGIoxVHmMoag+40gpIpLFdCfHy8vL4tgDDzyAoKAgcVu3bp14zMPDQ9wvLi5GRkYGevbsCQA4efLkba+7c+dOGAwGjB49GhkZGeIWEhKCsLAwHDx4sMLzXVxcMHbsWCQlJSE5OVksj4+PR3BwMB566CEAxok2e/Togd69e4t1vLy8MHXqVCQnJ+PcuXO3bas15t8/KysLOTk5uP/++yXffe/evQCA5557TnLujBkzJO8FQcCOHTvwyCOPQBAESX9ER0cjJyenwj7NzMyEIAjw8/OzOObn54eHH34YX331FQoKCsTrbd26Fd27d0ebNm2sngMAGRkZt+sGIiKieosxFGMoa+cAjKGofmJSiohkadCgAQAgPz/f4tiGDRuQkJCATz/91OJYZmYmnn/+eQQHB8PDwwNBQUEIDQ0FAOTk5Nz2upcuXYIgCAgLC5MEbUFBQTh//jzS09Nv+xmmYdOmSSivXbuGw4cPY+zYseLqKVevXkXbtm0tzm3fvr14XI7du3ejZ8+eUKvV8Pf3R1BQEN5//33Jd7969SqUSqXYLyatW7eWvL958yays7PxwQcfWPTF5MmTAcCu/hBsLFs8YcIEFBQU4MsvvwRgHKaenJxscxJT0+coFIrbXpOIiKi+YgzFGMrW5zCGovrI1dENIKLaycfHB40aNcKZM2csjpnmRzC/i2YyevRoHDlyBC+//DK6dOkCLy8vGAwGDBw4EAaD4bbXNRgMUCgU+Pbbb8Xgx5y1u47ldevWDe3atcNnn32GV1991epKKNXh8OHDGDp0KPr06YP33nsPjRo1gkqlwsaNG22u0lIRU3899thjmDRpktU6nTp1snm+v78/FAoFsrKyrB4fMmQIfHx8EB8fj/HjxyM+Pl68S2qN6XMCAwMr8zWIiIjqFcZQlccYiqjuYlKKiGQbPHgwPvzwQxw7dgw9evS4bf2srCwkJiZi8eLFWLhwoVh+6dIli7q27hS1atUKgiAgNDTU6vBne02YMAELFizAb7/9hvj4eISFheHee+8Vj7do0QIXL160OO/ChQvicVtstX3Hjh1Qq9XYt28f3N3dxfKNGzdK6rVo0QIGgwFXrlxBWFiYWP7HH39I6gUFBaFBgwbQ6/WIioqq4Nta5+rqilatWuHKlStWj7u7u2PkyJH45JNPkJaWhu3bt6Nfv34ICQmxWv/KlStQKpV39P8LERFRfcAYyjrGUIyhqP7h43tEJNucOXOg0Wjw5JNPIi0tzeJ4+SHNprty5cutrXDi6ekJABYrwTz66KNwcXHB4sWLLT5HEATcunXLrrab7ugtXLgQp06dsrjD9/DDD+PYsWNISkoSywoKCvDBBx+gZcuWCA8Pt/nZttru4uIChUIBvV4vliUnJ2PXrl2SetHR0QCA9957T1K+Zs0ai88bMWIEduzYYfVu682bN2220SQyMhLHjx+3eXzChAnQ6XR45plncPPmzQrvhJ44cQJ33303fHx8bntdIiKi+owxlHWMoRhDUf3DkVJEJFtYWBji4+Mxbtw4tG3bFhMmTEDnzp0hCAKuXLmC+Ph4KJVKNG3aFADg7e2NPn36YMWKFdDpdGjSpAn2799v9S5Tt27dAAD/93//h7Fjx0KlUuGRRx5Bq1at8Prrr2PevHlITk5GTEwMGjRogCtXruCLL77A1KlT8dJLL9227aGhoejVq5f4rH/5QGHu3Ln47LPPMGjQIMycORP+/v7YtzT1QQAAA1tJREFUvHkzrly5gh07dkCptJ3TN7V95syZiI6OFodrDx48GCtXrsTAgQMxfvx4pKenY926dWjdujV+++03yfkjRoxAXFwcbt26hZ49e+L777/H77//DkB6F/HNN9/EwYMHERERgSlTpiA8PByZmZk4efIkDhw4gMzMzAr7YdiwYdiyZQt+//13q3fn+vbti6ZNm+LLL7+Eh4cHHn30Uaufo9Pp8P3331tMLEpERESWGENZxxiKqB6qmUX+iKgu++OPP4Rp06YJrVu3FtRqteDh4SG0a9dOePbZZ4VTp05J6l67dk0YPny44OvrK/j4+AijRo0Srl+/brFMryAIwtKlS4UmTZoISqXSYmnjHTt2CL179xY8PT0FT09PoV27dsL06dOtLrNry7p16wQAQo8ePawev3z5sjBy5EjB19dXUKvVQo8ePYTdu3dL6lhbzri0tFSYMWOGEBQUJCgUCsnSxh999JEQFhYmuLu7C+3atRM2btwovPbaaxbLHxcUFAjTp08X/P39BS8vLyEmJka4ePGiAEB48803JXXT0tKE6dOnC82aNRNUKpUQEhIiPPTQQ8IHH3xw2z4oKSkRAgMDhaVLl9qs8/LLLwsAhNGjR9us8+233woAhEuXLt32mkRERGTEGIoxFGMoqu8UgmBjyQAiInIqp06dQteuXfHpp59W6YSiS5cuxcaNG3Hp0iWrE5/aIyYmBgqFAl988UWVtYuIiIioKjCGInJenFOKiMgJFRUVWZTFxcVBqVSiT58+VXqtF154Afn5+di6daus88+fP4/du3dj6dKlVdouIiIiospiDEVUu3BOKSIiJ7RixQqcOHECDz74IFxdXfHtt9/i22+/xdSpU9GsWbMqvZaXlxfS09Nln9++fXuUlpZWYYuIiIiI5GEMRVS78PE9IiInlJCQgMWLF+PcuXPIz89H8+bN8fjjj+P//u//4OrK+wlERERE1jCGIqpdmJQiIiIiIiIiIqIaxzmliIiIiIiIiIioxjEpRURERERERERENY5JKSIiIiIiIiIiqnFMShERERERERERUY1jUoqIiIiIiIiIiGock1JERERERERERFTjmJQiIiIiIiIiIqIax6QUERERERERERHVOCaliIiIiIiIiIioxv0/wRAzqsckEDEAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}