Assignment1-Final Code.ipynb

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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bae6b3cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-2.12.1.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Importing Required Libraries\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "#Plotly Graphing Libraries\n",
    "from plotly.offline import init_notebook_mode, iplot\n",
    "import cufflinks\n",
    "cufflinks.go_offline()\n",
    "cufflinks.set_config_file(world_readable=True, theme='pearl')\n",
    "import plotly.graph_objs as go\n",
    "import plotly\n",
    "import plotly.express as px\n",
    "\n",
    "## Machine Learning Libaries\n",
    "from sklearn import svm,metrics,tree,preprocessing,linear_model\n",
    "from sklearn.preprocessing import MinMaxScaler,StandardScaler\n",
    "import tensorflow as tf\n",
    "import keras\n",
    "from sklearn.model_selection import train_test_split,cross_val_score, cross_val_predict\n",
    "from sklearn import svm,metrics,tree,preprocessing,linear_model\n",
    "from sklearn.preprocessing import MinMaxScaler,StandardScaler\n",
    "import statsmodels.api as sm\n",
    "from sklearn.metrics import accuracy_score,mean_squared_error,recall_score,confusion_matrix,f1_score,roc_curve, auc\n",
    "from keras import Sequential\n",
    "from keras.layers import Dense, Activation\n",
    "from keras.callbacks import CSVLogger\n",
    "from sklearn.neural_network import MLPClassifier\n",
    "from dmba import classificationSummary\n",
    "\n",
    "# from tensorflow_core.estimator import inputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8744ac6c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing the dataset\n",
    "df = pd.read_csv('DataCoSupplyChainDataset.csv',header= 0,encoding= 'unicode_escape')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "898ea938",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Type</th>\n",
       "      <th>Days for shipping (real)</th>\n",
       "      <th>Days for shipment (scheduled)</th>\n",
       "      <th>Benefit per order</th>\n",
       "      <th>Sales per customer</th>\n",
       "      <th>Delivery Status</th>\n",
       "      <th>Late_delivery_risk</th>\n",
       "      <th>Category Id</th>\n",
       "      <th>Category Name</th>\n",
       "      <th>Customer City</th>\n",
       "      <th>...</th>\n",
       "      <th>Order Zipcode</th>\n",
       "      <th>Product Card Id</th>\n",
       "      <th>Product Category Id</th>\n",
       "      <th>Product Description</th>\n",
       "      <th>Product Image</th>\n",
       "      <th>Product Name</th>\n",
       "      <th>Product Price</th>\n",
       "      <th>Product Status</th>\n",
       "      <th>shipping date (DateOrders)</th>\n",
       "      <th>Shipping Mode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DEBIT</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>91.250000</td>\n",
       "      <td>314.640015</td>\n",
       "      <td>Advance shipping</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>Caguas</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.75</td>\n",
       "      <td>0</td>\n",
       "      <td>2/3/2018 22:56</td>\n",
       "      <td>Standard Class</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TRANSFER</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>-249.089996</td>\n",
       "      <td>311.359985</td>\n",
       "      <td>Late delivery</td>\n",
       "      <td>1</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>Caguas</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.75</td>\n",
       "      <td>0</td>\n",
       "      <td>1/18/2018 12:27</td>\n",
       "      <td>Standard Class</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CASH</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>-247.779999</td>\n",
       "      <td>309.720001</td>\n",
       "      <td>Shipping on time</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>San Jose</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.75</td>\n",
       "      <td>0</td>\n",
       "      <td>1/17/2018 12:06</td>\n",
       "      <td>Standard Class</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DEBIT</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>22.860001</td>\n",
       "      <td>304.809998</td>\n",
       "      <td>Advance shipping</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.75</td>\n",
       "      <td>0</td>\n",
       "      <td>1/16/2018 11:45</td>\n",
       "      <td>Standard Class</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>PAYMENT</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>134.210007</td>\n",
       "      <td>298.250000</td>\n",
       "      <td>Advance shipping</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>Sporting Goods</td>\n",
       "      <td>Caguas</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1360</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://images.acmesports.sports/Smart+watch</td>\n",
       "      <td>Smart watch</td>\n",
       "      <td>327.75</td>\n",
       "      <td>0</td>\n",
       "      <td>1/15/2018 11:24</td>\n",
       "      <td>Standard Class</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 53 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Type  Days for shipping (real)  Days for shipment (scheduled)  \\\n",
       "0     DEBIT                         3                              4   \n",
       "1  TRANSFER                         5                              4   \n",
       "2      CASH                         4                              4   \n",
       "3     DEBIT                         3                              4   \n",
       "4   PAYMENT                         2                              4   \n",
       "\n",
       "   Benefit per order  Sales per customer   Delivery Status  \\\n",
       "0          91.250000          314.640015  Advance shipping   \n",
       "1        -249.089996          311.359985     Late delivery   \n",
       "2        -247.779999          309.720001  Shipping on time   \n",
       "3          22.860001          304.809998  Advance shipping   \n",
       "4         134.210007          298.250000  Advance shipping   \n",
       "\n",
       "   Late_delivery_risk  Category Id   Category Name Customer City  ...  \\\n",
       "0                   0           73  Sporting Goods        Caguas  ...   \n",
       "1                   1           73  Sporting Goods        Caguas  ...   \n",
       "2                   0           73  Sporting Goods      San Jose  ...   \n",
       "3                   0           73  Sporting Goods   Los Angeles  ...   \n",
       "4                   0           73  Sporting Goods        Caguas  ...   \n",
       "\n",
       "  Order Zipcode Product Card Id Product Category Id  Product Description  \\\n",
       "0           NaN            1360                  73                  NaN   \n",
       "1           NaN            1360                  73                  NaN   \n",
       "2           NaN            1360                  73                  NaN   \n",
       "3           NaN            1360                  73                  NaN   \n",
       "4           NaN            1360                  73                  NaN   \n",
       "\n",
       "                                  Product Image  Product Name Product Price  \\\n",
       "0  http://images.acmesports.sports/Smart+watch   Smart watch         327.75   \n",
       "1  http://images.acmesports.sports/Smart+watch   Smart watch         327.75   \n",
       "2  http://images.acmesports.sports/Smart+watch   Smart watch         327.75   \n",
       "3  http://images.acmesports.sports/Smart+watch   Smart watch         327.75   \n",
       "4  http://images.acmesports.sports/Smart+watch   Smart watch         327.75   \n",
       "\n",
       "  Product Status shipping date (DateOrders)   Shipping Mode  \n",
       "0              0             2/3/2018 22:56  Standard Class  \n",
       "1              0            1/18/2018 12:27  Standard Class  \n",
       "2              0            1/17/2018 12:06  Standard Class  \n",
       "3              0            1/16/2018 11:45  Standard Class  \n",
       "4              0            1/15/2018 11:24  Standard Class  \n",
       "\n",
       "[5 rows x 53 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef73b6a1",
   "metadata": {},
   "source": [
    "## Data Description"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b26dafcf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(180519, 53)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "024635e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 180519 entries, 0 to 180518\n",
      "Data columns (total 53 columns):\n",
      " #   Column                         Non-Null Count   Dtype  \n",
      "---  ------                         --------------   -----  \n",
      " 0   Type                           180519 non-null  object \n",
      " 1   Days for shipping (real)       180519 non-null  int64  \n",
      " 2   Days for shipment (scheduled)  180519 non-null  int64  \n",
      " 3   Benefit per order              180519 non-null  float64\n",
      " 4   Sales per customer             180519 non-null  float64\n",
      " 5   Delivery Status                180519 non-null  object \n",
      " 6   Late_delivery_risk             180519 non-null  int64  \n",
      " 7   Category Id                    180519 non-null  int64  \n",
      " 8   Category Name                  180519 non-null  object \n",
      " 9   Customer City                  180519 non-null  object \n",
      " 10  Customer Country               180519 non-null  object \n",
      " 11  Customer Email                 180519 non-null  object \n",
      " 12  Customer Fname                 180519 non-null  object \n",
      " 13  Customer Id                    180519 non-null  int64  \n",
      " 14  Customer Lname                 180511 non-null  object \n",
      " 15  Customer Password              180519 non-null  object \n",
      " 16  Customer Segment               180519 non-null  object \n",
      " 17  Customer State                 180519 non-null  object \n",
      " 18  Customer Street                180519 non-null  object \n",
      " 19  Customer Zipcode               180516 non-null  float64\n",
      " 20  Department Id                  180519 non-null  int64  \n",
      " 21  Department Name                180519 non-null  object \n",
      " 22  Latitude                       180519 non-null  float64\n",
      " 23  Longitude                      180519 non-null  float64\n",
      " 24  Market                         180519 non-null  object \n",
      " 25  Order City                     180519 non-null  object \n",
      " 26  Order Country                  180519 non-null  object \n",
      " 27  Order Customer Id              180519 non-null  int64  \n",
      " 28  order date (DateOrders)        180519 non-null  object \n",
      " 29  Order Id                       180519 non-null  int64  \n",
      " 30  Order Item Cardprod Id         180519 non-null  int64  \n",
      " 31  Order Item Discount            180519 non-null  float64\n",
      " 32  Order Item Discount Rate       180519 non-null  float64\n",
      " 33  Order Item Id                  180519 non-null  int64  \n",
      " 34  Order Item Product Price       180519 non-null  float64\n",
      " 35  Order Item Profit Ratio        180519 non-null  float64\n",
      " 36  Order Item Quantity            180519 non-null  int64  \n",
      " 37  Sales                          180519 non-null  float64\n",
      " 38  Order Item Total               180519 non-null  float64\n",
      " 39  Order Profit Per Order         180519 non-null  float64\n",
      " 40  Order Region                   180519 non-null  object \n",
      " 41  Order State                    180519 non-null  object \n",
      " 42  Order Status                   180519 non-null  object \n",
      " 43  Order Zipcode                  24840 non-null   float64\n",
      " 44  Product Card Id                180519 non-null  int64  \n",
      " 45  Product Category Id            180519 non-null  int64  \n",
      " 46  Product Description            0 non-null       float64\n",
      " 47  Product Image                  180519 non-null  object \n",
      " 48  Product Name                   180519 non-null  object \n",
      " 49  Product Price                  180519 non-null  float64\n",
      " 50  Product Status                 180519 non-null  int64  \n",
      " 51  shipping date (DateOrders)     180519 non-null  object \n",
      " 52  Shipping Mode                  180519 non-null  object \n",
      "dtypes: float64(15), int64(14), object(24)\n",
      "memory usage: 73.0+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "842d2aab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Type                                  0\n",
       "Days for shipping (real)              0\n",
       "Days for shipment (scheduled)         0\n",
       "Benefit per order                     0\n",
       "Sales per customer                    0\n",
       "Delivery Status                       0\n",
       "Late_delivery_risk                    0\n",
       "Category Id                           0\n",
       "Category Name                         0\n",
       "Customer City                         0\n",
       "Customer Country                      0\n",
       "Customer Email                        0\n",
       "Customer Fname                        0\n",
       "Customer Id                           0\n",
       "Customer Lname                        8\n",
       "Customer Password                     0\n",
       "Customer Segment                      0\n",
       "Customer State                        0\n",
       "Customer Street                       0\n",
       "Customer Zipcode                      3\n",
       "Department Id                         0\n",
       "Department Name                       0\n",
       "Latitude                              0\n",
       "Longitude                             0\n",
       "Market                                0\n",
       "Order City                            0\n",
       "Order Country                         0\n",
       "Order Customer Id                     0\n",
       "order date (DateOrders)               0\n",
       "Order Id                              0\n",
       "Order Item Cardprod Id                0\n",
       "Order Item Discount                   0\n",
       "Order Item Discount Rate              0\n",
       "Order Item Id                         0\n",
       "Order Item Product Price              0\n",
       "Order Item Profit Ratio               0\n",
       "Order Item Quantity                   0\n",
       "Sales                                 0\n",
       "Order Item Total                      0\n",
       "Order Profit Per Order                0\n",
       "Order Region                          0\n",
       "Order State                           0\n",
       "Order Status                          0\n",
       "Order Zipcode                    155679\n",
       "Product Card Id                       0\n",
       "Product Category Id                   0\n",
       "Product Description              180519\n",
       "Product Image                         0\n",
       "Product Name                          0\n",
       "Product Price                         0\n",
       "Product Status                        0\n",
       "shipping date (DateOrders)            0\n",
       "Shipping Mode                         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e518a694",
   "metadata": {},
   "source": [
    "###### Combining the Last Name and First names to identify unique customers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "189f5b7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Cust_Full_Name'] = df['Customer Fname'].astype(str) + df['Customer Lname'].astype(str)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b94ef527",
   "metadata": {},
   "source": [
    "## Data Cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10b72454",
   "metadata": {},
   "source": [
    "Dropping unimporant columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "87ac003b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(['Customer Email','Product Status','Customer Password','Customer Street','Customer Fname',\n",
    "         'Customer Lname','Latitude','Longitude','Product Description','Product Image','Order Zipcode',\n",
    "         'shipping date (DateOrders)'],axis=1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6abd8139",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(180519, 42)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "139c1469",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Type                             0\n",
       "Days for shipping (real)         0\n",
       "Days for shipment (scheduled)    0\n",
       "Benefit per order                0\n",
       "Sales per customer               0\n",
       "Delivery Status                  0\n",
       "Late_delivery_risk               0\n",
       "Category Id                      0\n",
       "Category Name                    0\n",
       "Customer City                    0\n",
       "Customer Country                 0\n",
       "Customer Id                      0\n",
       "Customer Segment                 0\n",
       "Customer State                   0\n",
       "Customer Zipcode                 3\n",
       "Department Id                    0\n",
       "Department Name                  0\n",
       "Market                           0\n",
       "Order City                       0\n",
       "Order Country                    0\n",
       "Order Customer Id                0\n",
       "order date (DateOrders)          0\n",
       "Order Id                         0\n",
       "Order Item Cardprod Id           0\n",
       "Order Item Discount              0\n",
       "Order Item Discount Rate         0\n",
       "Order Item Id                    0\n",
       "Order Item Product Price         0\n",
       "Order Item Profit Ratio          0\n",
       "Order Item Quantity              0\n",
       "Sales                            0\n",
       "Order Item Total                 0\n",
       "Order Profit Per Order           0\n",
       "Order Region                     0\n",
       "Order State                      0\n",
       "Order Status                     0\n",
       "Product Card Id                  0\n",
       "Product Category Id              0\n",
       "Product Name                     0\n",
       "Product Price                    0\n",
       "Shipping Mode                    0\n",
       "Cust_Full_Name                   0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab1411f2",
   "metadata": {},
   "source": [
    "Customer Zipcode has 3 null values which we will fill with 0 as we cannot be sure of the zip code of the customers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c46d8249",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Customer Zipcode'] = df['Customer Zipcode'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "104d295e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "0bf51e7e",
   "metadata": {},
   "source": [
    "Creating new column using the Order Date Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "615ed254",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1/31/2018 22:56\n",
       "1    1/13/2018 12:27\n",
       "2    1/13/2018 12:06\n",
       "3    1/13/2018 11:45\n",
       "4    1/13/2018 11:24\n",
       "Name: order date (DateOrders), dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['order date (DateOrders)'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "359c5b39",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Splitting Order dates and creating new columns\n",
    "df['order_yr']= pd.DatetimeIndex(df['order date (DateOrders)']).year\n",
    "df['order_month'] = pd.DatetimeIndex(df['order date (DateOrders)']).month\n",
    "df['order_day'] = pd.DatetimeIndex(df['order date (DateOrders)']).weekday\n",
    "df['order_hour'] = pd.DatetimeIndex(df['order date (DateOrders)']).hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b7321a90",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "2ec81676",
   "metadata": {},
   "source": [
    "## Data Visuzalization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a5524df4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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3siQvbW10deOLZvXp3LwBZeyLM2FAN4pZF2b7sbNpDvfbii20bVCHqmVL50ygKOvw4tF1NOk4kkq121DMoRxdtKhDbeZHenWg7bTrNOtJ6fJ1KVzUAbtSlWnRZSwhAd6qO0u1df7IGmo26UbtponxWBQpzpUTmuvyiluyumyqrMtzhxLr8sKRdThVbkCTjsrvoUnHEThVrM+FJN9D+RotKFe9KUWLl6Fo8TK06jaOfAVMeeWe9noqLbpaxrSZbvUGX9Cs0zc4Vfo00/klp8s6LWBqzoCJq6jySTuKlnCipHMN2vf9Ee8X91I9oM0IfapLTfRp3uX29eXLJ9cJ8ntN56GzKeZQnmIO5ek85De8nt/h+YOLGcpV37fjusqvbLUmtOw6lkq122RpPknp0zKXnL7XpT4dG+T29SXAK/eb1GvZDwenahSxLUnTz0dRwNQ8Uye09bk29Tk30J/lLrcvcx+6j5Lb84OsO2bVp2UuNx+zvnK/SY0GnSlToR6FizpQp1lPipcsj9fzu5nOV9frE0/3m1Rv0JnSFephVdSB2k3f5+SR+ZyS56er5RCgWv3Pca7cgCK2JbG1L0vbXlN4FxmGj+ejLMkvqXOH1lK7SVfqNOuBrZ0zHfoq47l8fLPG9ldObMbKugQd+k7D1s6ZOs16UKtJV84eTKzdL0fOo17LPpQoVREbOyc6D/kZRXw87vcvZHn8Quijj/aEtiZubm7cvHmTrl27qt6Lj4/nu+++o0qVKgwcOJAWLVrw+++/AxAREcHmzZtTPBB98ODBbN++nbCwML777js6derEl19+Sfny5enXr1+q3U3Pnz9fdTK9ePHiFC9eHIAxY8YwYcIEJk6cSLVq1Th8+DB79+7FxcVFbfi5c+eyZMkSKlasyOHDh5OPnm7dujFu3DhGjBhB2bJl6dy5M3fu3FFrM2HCBK5evUrNmjX5+++/Wbp0KeXLl0/ze5s3bx4TJ06kbt26vH37lr1796qd2DU1NeWHH35g4MCBNGzYEAsLCzZv1rziT9C8eXOcnZ1p3rw5AwcOZNCgQWoXGqxbtw47OzuaNWtGt27dGD58OLa2tmmOs0mTJjx+/JjQ0NAUnyX/7r766it+/fVXfvjhBypWrMi0adP45ZdfGDBggGqY0NBQBg0aRKVKlRgzZgzDhg1j3LhxacZw+fJlHB0dcXR0TLOdyJiY2DgeePrwaflSau9/Wr4UtzzS/tGs5/z1tPxpGcP+3sblJy+zM8xUBfl5Ehbsi3Plhqr3jE3yUbp8XTzdU3++/Cv3mzglGQbAuXIjXj29CUBcbDReL+6pjRfAqVJDPJ+qj9fj0WXmjW3An9PasnfNdMJD/D8wK4hNZfrOlRvy6qnmvF6530zR3qVyI7w87hEXG5PYpkqyNlUa8cr9ZqqxREUql/uChSwzmkamxcTG8vD5K+pVq6D2fr2qFbj9+Hmqw+09eRHPt34M65a5bg4zK9A39TpMbX5B+vNDmzrIzLSj30Vw8+xOrIo6YFGkuNZ5xsZG4+1xDxdN8aSyvHlqqssq6nWpqY1zlcTlMbn4+DjuXDpA9LsISjrX0Dr+5LnoYhnLzHSzii7rVJOoiFAwMKCAqUUmskmkT3WZGn2ad7l9fRkXGw0GBhgb50vSJj8GBoa8fHJN6zz1fTuem/LLDvq0zCWVm+Zbdu1f6tOxQW5fXwI4lq3F3cuuRIQFER8fz51LB4iNjaF0hU8ylKs+16Y+55ZAX5a73L7Mfeg+Sm7PL7kPOWbVl2Uutx+zOpatxaObJwgJ9EGhUPD8wUX833jgXKVRpvIF3a9PHMvW4nHSnB4qc3L5gJySyk37mLGx0Vw7tYX8Bc0pVrKCxjaZFRsbjZfHPVxSxNyQl6nE8/LpzRTty1ZpyOsktZtczLso4uJiKWiWc79XCpGXfZTP0E7Lw4cPqVYt8ZkFSe9g9vDwYPr06SxdupRvvvkGgBUrVnD+/HlKlCiBt7c31tbWdOzYkdatlc9/cHR05MmTJ5w9q7wb7+XL1E+YhYeHExQUBICPT2I3ExMnTmTu3Lls2aJ8ds6UKVNo3rw5Y8eOZfTo0ap2f/zxB7t27Up1/I6Ojrx584Zjx44RGxvLq1evuHLlilobV1dXli5dCihP8o4bN45mzZrx6FHqVznNmjWLY8eOAco7sj09PenSpQvbtm0DIF++fIwePZrLly+r2jx8+JC6deummH6CwMBARo8eTXx8PI8ePeLAgQO0bNmSFStWUL58eVq3bk2dOnW4dk25w/vVV1/x9OnTVGMEKF26NF5emk9uJv/upk+fzoQJE1TveXh4UKlSJUaMGMG6desA+PXXX1XtX7x4wYIFC+jZsyfz5s1LNYbXr1+rYtFUC/ny5SN//vxp5iFSCgyPJC5egbW5qdr71uaF8Avx0DiMjUUhfvqyNZUcihEdF8f+q/cZvnQbK7/pSe1UnrudXcKCfQEws1B/dnchC+sU3ZCpD+eXYhgzC2vCQpTjiwgNRBEfl7KNpTXud/1Uf7tUbUKlOp9hZW1HoJ8nbruXsHbeIIb/tANjk3xkVsL0C1mmzCss2E/jMGHBvhSyUN/JLmRpTXxcLBFhgZhb2RIW7EchDd9VwveYnEKh4PCWOTiWrU0xh5zrwjsoNJy4+HiKWJqrvW9taY5/cMoLawBeer/lf5v38c+MMRjn8OMvEupG03ebXh2mNT+0qYOMTPvyiY0c3TafmHcRFC3hxICJq9R+EElPRGgg8fFxKaZlZmlN2N3U69LMMlldWqSsS43LY7K69Hn1iBW/9iY25h358pvSa/Rf2NqrX6CWkVx0sYxlZrpZRZd1mlxMzDuObV9A1XodKVDQLMO5JKVPdZkafZp3uX196eBUg3z5C3J023xadhsHKDi6bT4KRXyq20pN9H07nlvyyy76tMwllVvmW3buX+rTsUFuX18C9Bi5iG3LxvH7d/UxNDLGJF8Beo3+kyK2GbsIXZ9rU59zSxov5P3lLrcvcx+6j5Lb80uQFces+rLM5fZj1nZ9fmDfmuksnNAUQyNjDAwM6DTo/yhVrnam8k2IH3S3PmnX5wf2rZ3OoomJOX0+8P9wLJv5nNTizAX7mI9uurF9+QRioiMxt7RhwMRVFDLP2kdIRoQGER8fh5llUfV4LNOqXb8U8ZtZFlWr3eSObFuAReFiOFdqkHXBixxlaGyg6xA+KnJCOxkDAwNVV98AzZo1Y9q0aVSqVAkLCwuMjY0pWLAgpqamREREcOXKFe7du8eAAQOYO3cu/fv35+XLl5w+fRqANWvWcPToUR49esShQ4fYv38/R48e1Toec3Nz7O3tOXfunNr7586dU3X9neDq1atpjmvbtm2MHTuWZ8+ecejQIVxdXdm3b5/aM7Fv376tNsybN2/SvfP5woXELjECAwN59OgRFStWVL0XExOjFtujR48IDAykYsWKqZ7Qvnfvntrzc7y9valatSoA5cuXJyYmhuvXr6s+d3d3T/c53AULFiQqKkrjZ0njK1q0KI6OjqxcuZJ///1X9b6xsTHBwcGqv7t168bYsWNxcXHBzMwMY2NjQkLSfl5zZGQkoLxrXZOpU6cyc+bMNMchUmdgoL4BUaDAIJVtSmnbIpS2LaL6u3ppO94EhrLW7Uq2n9C+fXEf+9fNUP3dZ8wy5X+Sx69I+V4KKXIGSD5M2uOt8kl71f9tHcphV7oKf0xqyZPbJ6mYBV1hGiSPJ528ks9HFKoP0h5niryVXDf8gs+rRwyZulGreLNa8lgVKDRGGhcfz4//W8fw7u0oVSLt9W5WuH1hH/uS1GHfsco6TPH9K99Mc1zazA9t6kCbaSd0LxUa5Mv5w6vYtnQsQ6ZtwsQkYxcDpVhfKDTEqD5EaiNKdZzKodTfsy5RhpGzdhEVEcL9q0fYtWIKg6es/6CTh7paxjI63czIjXUKEBcbw/Zl41EoFHToPyPF55mlT3WpT/MuN+aS1rQLWRShx6g/OLB+FpeOr8fAwJCq9TpQolQlDAwzfrGUvm/HdZ1fVsmNdQrZuL7Uo7rUp2OD3FiH6U37xK4/iAoPYcDE1ZiaFebhjWNs/XssQ6ZuoJhD2r3VaR13Hq3N5PQpN31Z7vLaMpfRfZS8ll+CLDtm1aNlLrces146th5P91v0/u5vLK3tefH4CgfWz8LM0gbnytqdYMxt65OEnHp9+zdW73Ny3TALcysbnDJx0jQ3LodlKtZj5MxdRIQFcv3UNrYtHctXP25NcbI/SyRPSaFIu3ZTzB9V8aZoe+bACm5fdGXolLWY5JMb3ITQhpzQTqZixYo8f/4cUN7R7OrqyrJly5g+fToBAQE0atSIVatWYWJiohpmxYoVjB49mrlz5zJ48GBWr16t+uzGjRuUKVOGdu3a0apVK7Zu3cqxY8fo0aNHhuJKepIdSHHiHZR3eKfF09NTdXdzq1at+Pvvv/n+++9p2rQpsbGxgPLkc/LpGmbimcLJY0v+d2rvJUgrDo0bzDTeT+Dn56c6KZ5c0u8uYTrDhg3j0qVLau0STv7Xq1ePzZs3M2PGDA4fPkxwcDC9evViwoQJacZQpIjyBKqvr+arH2fPns3ChQvV3kvvJLmAwoUKYmRogF+I+jIQEBqBtXkhrcdTrXQJDlx9kNXhpVC+enMcZiT2BBEbGw0or+RLerVeRKh/mjtjZpZFU1wVGB7ij5mF8upBU/PCGBgaERaiqU3q4zW3ssXK2g5/nxfaJ6WBavrJY0wjLzNLG405GRoZY1rI6n2boilzCvVPcdUkgOt/v/Do5gkGT9mAZQa6+MoKVubKZ7L7B6svwwHBYSnu2gaIiIziwbOXPPbwZN6a7QDEKxQoFArq9xvLn1O/pm7lrLsToXyN5tg7JdZhXCp1mF69pDc/tKkDMwsbraddwNScAqbmWBcrjYNzdeaOrsfDa0epWr+jVnmbmhfGUFM8If4prqRNzFG7ugxN1iYsxJ9CyerS2Dgf1sVKAWBfpipeHne5eHQdnQb9rFX8yXPRxTKWmelmVm6q08QYYti2dBxBvp4MnLTmg+82TJi+vtRlAn2ad7kpF23Xly5VGjFm7lHCQwMxNDKioKkF88Y2okpR7S/a0/fteG7ILyvlpjpNjCF71pe6nm9ZXZf6dGyQm+pQm/VlwNuXXD7+H1//sg9b+7IAFHeswIvH17h8YiOfD5iVbs4J9LE2E+hjbvqy3OW1ZQ4yto+SF/ODrDlm1ZdlLjcfs8ZER3F8xx/0Gv0n5ao3A6B4yfK8efmQ84dXaX1COzetT2Kiozi+8w96fpOYU7GS5XnzSplTZk5o56blMEG+/KZYFyuFdbFSlHSuwZIpbblxZjuNO4zIcH6pMTW3Uh6jByX/vgPSqF3N89DQyBhTMyu198+6ruLU/n8YPGkVxR0zfgGdEB8reYZ2Es2bN6datWrs2LEDgDp16mBsbMyECRO4dOkST548wc7OLsVwGzZswNHRkW+//ZbKlSuzdu1atc9DQ0PZunUrw4cPp2fPnnTv3p3ChQtrFVNoaCivX7+mUSP1rlYaNGjAgwcZP/EWFRXFvn37GDNmDM2aNaNBgwapnuTVVv369VX/t7Kyoly5cjx8+FD1nomJCXXq1FH9Xa5cOQoXLqzWJiMePnyIiYkJNWvWVL3n7Oyc7nd648YNKlRI/3kab9++xdPTEycnJ9zd3dVeCc8/b9iwIS9evOC3337j2rVrPH36lFKlSqU77ipVqhAdHc29e/c0fh4dHU1oaKjaS6TPxNiIig7FuPhY/WDv4uMXVC+dcplNzUPPtxS10P4EeGblL2hGkWKlVC8bOxfMLG14dv+8qk1cbDQej67g4Fwz1fGUdK6hNgzAs3vnKOlSAwAj43zYlarMs3vJ2tw/j4NL6uONCAskOMAbcyubTGSXyPj99N2Txeh+7zwlU5l+SecauN9L3v4cdqUrY2Rsknqbu+fUnveqUCg4sOFnHlw7ysBJayhsk7PdyAOYGBtToUxJLt1Rf2TD5bsPqVauTIr2hQoWYNPcKWyYPUn16tqyIaVK2LJh9iSqOKe/jsmI/AXNVAcA1knqMOn8in1fh6nNL0h/fmhTB4VtHDI1bVDe8Z5wwKgNY+N8lChdOUXMz+6fp2Qqy5uDhmXtabK6dHCukWJZc0+yPKYav0KhOiDMKF0tY5mZbmblpjqFxJMz/m9fqO7kygr6VJcJ9Gne5aZcMrq+LGRemIKmFjx7cJHwUH/K12iudd76vh3XZX7ZITfVKWTv+lLf6lKfjg1yUx1qs76MiVb2oGZgoP7TmKGhIYokPcZpQx9rM4E+5qYvy11eW+aS0mYfJS/nl1Rmjln1ZZnLzcescXGxxMfFaN4GKLTfBuSm9Ul8Qk7Jbk4zyMR2LWl+uWU5TI0CBbExH3b8mpyxcT7sSlfmabKYn947j2Mq8Ti61EjZ/u457JPULsAZ15W47V3KwAn/YF+mSpbGLXKegYlBrn3po4/2hHb+/PkpVqwYdnZ21KxZk6lTp7Jnzx727dunekayu7s7JiYmfPvtt5QpU4Z+/foxcuTIFOMKCgpi586dzJs3jyNHjqiekwwwduxYevbsSfny5Slbtiw9evTA29tb9axsbcybN4/Jkyfz5ZdfUq5cOWbPnk2NGjXUnu+tjYEDBzJkyBAqV65MmTJl6N+/PxEREbx48WF3Yf7000+0aNGCypUrs2bNGvz8/Ni9e7fq8+joaP78808++eQTatasyerVq7lw4UKq3Y2n59GjRxw9epR//vmHunXrUqNGDf755x8iIiLSvOvbzc2NQoUKUbly5XSnMXPmTKZOncp3331H2bJlqVKlCoMGDWLcuHEAPH36FEdHR3r27ImTkxPffvstXbp0SXe8jRs35syZM6l2fa4rRoVMsaheAYvqyhP+pmUcsKhegQIlS+g4Mu31b1abnRfvsOvSHZ75+DNvlxvegaH0aKDsmn/x/jP88N9BVfsNp65x4s4TXvgG8tTbj8X7z3Ds9hN6Nc7akzHaMDAwoF6rAZw5sJwH14/y1vMxu1dNxSRfAarWS7yCd9eKyRzbsUD1d71W/XG/d46zrv/i5/2Ms67/8uzBBeq1HqhqU7/NIK6f2c6NMzvw9XLn0ObZBAd4U6dpLwCio8I5smUur57eIMjPE4+Hl9i0ZBSm5oWpULPVB+f2adtBXD+9nesJ09/0fvrNlNM/tn0BO/+drGpfp1kvgv29OLR5Nr5e7lw/s4PrZ3bQoO2QxLxbJ+btmyTv+knyPrDhZ25f2Ee3EfPJV6AQocG+hAb7EhOds8ten/bN2eN2gb0nL/D89RsWrt/JG79AurVUXqT01+a9zPh7PaA8aHIpaaf2KmJhRr58JriUtKNggeztfsjAwID6rQdwZv9yHlw7io/nY3avTFmHO/+dzLHtSepQi/mRXh1oM+2At684c2A5Xh53CfL34tXTG2xbOg4Tk/yUrdY0Q7k2aPM+ntPKeA5umk2wvzd1myvjObpNvS7rNu9FkJ8Xhza9r8vTO7hxegcNP0usy/rvv4czB5Tfw5kD//Ls/gU+TfI9HNu+kBePrxLo54nPq0cc27EIj4eXqfbp5xmKPyldLWPpTRcgIiwI75cP8PVyB8D/zXO8Xz4g9AOeI6vLOo2Li2Xr32Pw8rhLt2HziFfEqdYtGfmBKjX6VJea6NO8y+3rS4AbZ3bwyv0mAW9fcuvCXrb9PYZPWw+kaAmnDOWq79txXeX3Lioc75cP8H6pvEA5yM8T75cPCErjuYMZpU/LXHL6Xpf6dGyQ29eXRYs7UcS2FPvWzcDz2W0C3r7k/KFVuN8/T4VaGc9Xn2tTn3MD/VnucvsyBx+2j5Lb88vKY1Z9WuZy6zFrgYJmlCpflyPb5vH84SUCfT25cXYnt87voWKt1pnOV5frk/zvczq6dR4e73O6eXYnt8/vocIH5JQ8P10th9HvIji2YyGv3G8S5Pcarxf32LP6R0IC3lC57mdZkl9SDT8byLVTO7h2egdvvdxx/e/9MXqLngAc2bqQ7cuTHKO3UB6ju26cw1svd66d3sG10ztp1C6xds8cWMGxHYvpOvRXrIraExrkS2iQL++i0u55Vwih9NF2Od6uXTvevHlDTEwMgYGB3Lp1i++++461a9eqToreunWLcePGMXnyZGbPns3p06eZOnUq69evTzG+lStX0rdvX1atWqX2flhYGJMnT6Zs2bLExcVx5coV2rdvn+aJ1+SWLFmChYUFCxYswNbWlvv379OpUyeePn2aoZyDgoKYMmUKCxcuxMjIiDt37vD555+n++zp9EyZMoXFixdTtmxZbt26RadOndS6DI+IiGDu3Lls3LgRBwcHzp49y5AhQ9IYY/oGDBjAypUrOX36NG/evGHq1KlUrlw5zRPFAQEB7Ny5k759+zJt2rQ0x79y5UoiIiL4/vvv+f333wkPD+fOnTv88ccfAOzdu5dFixbx119/kT9/fg4cOMAvv/yS7vOve/fuzYwZWffsuKxiWbsKnx5PrOtK85Xfz6t1O7k9dKquwsqQz2pWIDg8in8OX8Q3JByXEtb8b3hX7IpYAOAXEs6bwMSun2Ni41i49zRvg8PIb2KMczFr/hrWhcaVMvZDb1Zp2O4rYmOicN3wM5HhwTg4VaP/+JXkT9I1Y3CAl1rX+iVdatF9xAJO7FqM2+4lFLEtSfcRC3Fwqq5qU+WT9kSGBXFq3/8IC/bF1r4sfccsx6qoPQAGhka8ff2YWxf2EBURirmlDaUrfEL3kYvUpp1ZVT5pT0RYEKf2Jpn+2MTphwb7EhyQ+ONtYRsH+o5bzqFNc7hyYiPmVra06/MDleq0VbVxdKlF95ELOLFzMSd2vc975EIcnBPzvuq2CYA1cweoxfPFkN+o2ajrB+elrTaf1iI4LJwVOw/jFxSMs0MJ/pg0khI2yscP+AWF8MY/MMfiSU/Ddl8REx3FgaR1OEFDHRom1qE28yO9OtBm2sYm+Xjx+BoXj64jMjwEMwtrSpWvw9BpmzLczXWVeu2JCFfGE5oQz7jEeMKCfQn2V6/Lfu/r8nJCXfZNVpdlE78Ht11LKGxbkh7JvoewEH92/jOJ0GBfChQ0p1jJ8vSf8C/OlRtmKH61XHS0jGkzTx/dPMGeVYnb2+3LxgPQtNM3NO/8baZz1lWdhgS+4dHNEwAsm9lZLaaBk9ZSpkK9TOcE+lWXqdGneZeb15cAfm88OLZjEZHhwVgVtaNxx5F82mZQhvPU9+24rvLz8rjL2t8Tf7w7vHkOANUbdqbL0DlZlp8+LXNJ6Xtdgn4dG+Tm9aWRsQl9xy3n2PYFbFoyiuioCIrYOtJl6BzKZfDkkzYx5eXa1OfcEujLcpeblzn48H2U3Jxflh6z6tEyl5uPWbuPXMjx7QvZ+c/3RIYHY2ltR4uuY9Uu1M4MXa1PALqPWMjxHQvZ+W+SnLp8eE7J89PFcmhgaISf93NunfuOiLBAChaywr5MVYZM/U/16JCsVLWeMh63PX8TGuRLMfuy9B+/jMJJajcowFvVvoiNAwMmLMN14xwuHVfWbod+06hct42qzaUTm4iLjWHTX2PUptW88ze07DI6y3MQQt8YANqfWRWp6tOnD4sXL8bOzi7F85/1VdOmTTl58iRWVlYEBwdrbDNw4ED++OMPrbtYzyx7e3s8PT1p2bIlJ06cSLVdlSpVOHbsGC4uLoSFhWVrTMm1b9+eefPmUa1aNdWzuLWhUCg4YKKfz9LoEKPsijnK9R8dR5L1CrQfDsDGs/q5iu3TSLlTuumc/uXXu6Eyt5Brh3UcSdazqK08ANTH+QaJ827zef3Lr1cD/V/m9DE3kLrMqz6WutTH/CS3vEuf80vITY4N8p6PoS71MTfQ7+VOlrm8S5/z+xhy08f1CXwc65RtFzPX5Xpu1qO+odpFEUI3jpf6sMf5ZqeWL+7oOoQs99HeoZ1VChYsSJkyZZg6dSrLly//aE5m61rz5s0xMzPjzp07lChRgt9//53nz59z+vTpNIe7e/cukyZNonTp0ty9ezeHolUqVKgQgwcPztDJbCGEEEIIIYQQQgghhBBCCCE+Zh/tM7SzyqRJk7h58yY+Pj7Mnj1b1+F8NExMTPjtt9+4d+8eu3btwtfXl2bNmhEbG5vusOvWrcvxk9kA27Zt4/Llyzk+XSGEEEIIIYQQQgghhBBCCCHyKrlD+wPNmjWLWbNm6ToMnTh16lS63VqsXbuWtWvXZvm0jxw5QtWqubc7ByGEEEIIIYQQQgghhBBCCKGfDEyk2/ecJHdoCyGEEEIIIYQQQgghhBBCCCGEyJXkhLYQQgghhBBCCCGEEEIIIYQQQohcSbocF0IIIYQQQgghhBBCCCGEEEIILRkaS5fjOUnu0BZCCCGEEEIIIYQQQgghhBBCCJErGQAKXQchhEidQiGLqBBCCCGEEEIIIYQQQgghlAwM5O5gXTtZobquQ0hVs4e3dB1ClpMux4UQQgghhBBCCCGEEEIIIYQQQksGRnJRQU6SE9pC5AFRrv/oOoRsUaD9cAAOmJTXcSRZr0PMIwA2ndPPO+x7N1RurDef17/8ejVQ5tZl9BMdR5L1dv1VFtD/utTH/CS3vEuf85Pc8q6PYTuuj/NO6jLv0ue6BP2uzY+hLvUxN9Dv5e5jWOb0MTf4ONYp+jjvEubbxrP6lxtAn0b6m19Cbvpcl0J8TOQZ2kIIIYQQQgghhBBCCCGEEEIIIXIluUNbCCGEEEIIIYQQQgghhBBCCCG0ZChdjucouUNbCCGEEEIIIYQQQgghhBBCCCFEriQntIUQQgghhBBCCCGEEEIIIYQQQuRK0uW4EEIIIYQQQgghhBBCCCGEEEJoycBQuhzPSXKHthBCCCGEEEIIIYQQQgghhBBCiFxJr05oz5gxgzdv3qBQKPjiiy9ybLrPnz9nzJgxqX5eqlQpFAoF1atXz7GYckqRIkXw8fGhVKlSHzyuGTNmcOPGjSyISl3Tpk1RKBRYWlpqPczq1avZtWtXlk63Q4cOXL9+HQMDuWpHCCGEEEIIIYQQQgghhBBCCG1kqMvx1atXM2jQIABiYmIICAjg9u3bbNq0iTVr1qBQKLIjRq1UqFCBmTNn0rlzZy5evEhgYKDOYknu1atXFC9eHD8/P12HopXVq1djZWVFly5d0m07depU9u3bx4sXL3IgsrztwIED/Pzzz/Tp04f//vtPZ3FsOXuTNW5X8AsJx7m4NZM6N6eWs4PGtleevuKr/21N8f7uKYMoU8w6u0PNMkUa1cFpwlAsa1WhgJ0tV7t9jc/e4zqNSaFQcHLPX1w7tZWoiBDsnarRod9P2NqXTXO4+1cPc2LXEgJ9X1LYxpGWXcdSsXZrtTaXT2zk/KGVhAb5Ymvvwme9p1GqXB2tpx0RFsTJPX/ifvccwYFvMDUrTIWaLWnRZQwFTM0znOvlExs5d3AlYUG+2Ni70K6PejzJeTy8zKHNc/B9/RTzwrY0bPcVdZv30vg9BLx9SRFbzd9DSKAPR7fO58md08TGvMO6WGm+GPJ/2JWukuEcskLP9kVo09CSQgUNefIiin+2+PLqTbRWwzaqbcaEwSW4dCuMOf96Z1uMubkuk8f536LhPL17hp6j/6JirVbp5pbe9JPzeHSZw5vn8Pb1U8yt0q7DD8k7LNiPo9vn4373HFGRoZQqV4f2fX/EuljpdHNKiy7npdvuP7l72ZWQgDcYGZtQolRlWnYdi4Nz5i7sy+11uW/tTzy7f4HQoLfky29KSZeatOoxEZsSTunmJnWZM/MyLjaGE7sW8+T2KQJ9Pclf0AynSg1o1X08FoWL5alcMjrtzKwvk9PFdvzyiU1cddtEkN9rAGzsXWjW6RvKVmuS4fhTs+j7FgT7e6V4v27zPnTo/1Omx5vecnrj7E72rJqWYrgflt/CxCR/pqeriT4tc8npoi4XTWxBkKaaadGHjh9QM5ro87zTp30UTfT52EefcsvN2/EPPR7PzbkljzMz+yj6nl/yePRlW5dbj3tmDqmgcfqte3xPw3ZDM52vQqHg1F71WmnfV7s6ddudmFOLrmOpWEs9pysnNnL+cGJObXup5zRrqOacWvX4noafZT6npHSZ3+6VU7h1frfaMPZO1fnqhy2ZziU3r1MC3r7kyJbfefnkGrGx0bhUaUz7vj9iZlk0U/mKrGdgpFf3DOd6Gf62Dx48SPHixSldujTt2rXDzc2NxYsXs3//foyMjLIjRq04OzsDsGfPHnx8fIiO1u4kQXLGxln/WPH4+Hh8fHyIi4vL8nHrUoECBRg6dCgrVqzQdSh5xurVq/n22291Nv1DNx7y+243hrWux5aJ/anl5MDX/+zEOzAkzeH2TB3M8VkjVS9Hm8I5FHHWMCpkSsjtR9wb87OuQ1E5d3AFF46soX2/6Qybvg0zSxvWzR/Cu8iwVId59fQG25aNp3qDToyctYfqDTqxbdk4PN1vqdrcvezKoU2zadxxJCNn7sKxbB02LBqudkCS3rRDg94SGvSWNj0n8fXPe+k8dDZP755hz+ofMpzn3UuuHNo4myYdRzJy1i5KlavDhoXDNR4gAQT6erJh0QhKlavDyFm7aNxhBAf/+5X7Vw+rfw9Lx1Pt006M+nkP1T7txNal6t9DZHgwK3/tjaGxMf3G/8s3v+6nba/JFDC1yHAOWaFLq8J0am7Fv1vfMmneKwJD4pj5rT0F8qffY4NNYWMGdi7KvaeR2R5nbq7LpC4eXQsZ6O1Cm+knFejryX+LRuBYtg4jZ+6icccRHNyooQ4/MG+FQsHmv74h0NeT3t/9zcgZO7GytmPd/CFEv4vQOj9NdDkvrYuXpn3f6Yz6eS9Dpv6HVVF71i8cSnhIQJ7LRZtplyhVmS+G/MY3vx6g34QVKFCwfsFQ4uPT3u+Tusy5eRkTHYX3i/s0+fxrRszYQc/Rf+Lv48GmJV/nuVwyOu2Mri+T09V23LJIMVp1n8DwGdsZPmM7ZSrWZ9OSb3j7+kmmc0lu+PTtTFh0RvXqP2EVAJXqts30OLVZTgHyFzRTm/aERWey/GQ26Ncyl5Su6nL4T9uZ+McZ1WvARGXNVP6AmkmNvs47XeYGWb+Pkpw+H/voW265eTv+ocfjuTm3pDK7j6Lv+ani0aNtXW497gFS7I99MfhXMDCgYu02mc4XktRK3+kM+3EbZhY2rF+Qfp1uX66cPyNnKufP9mXj8HyWLKfNs2ncYSQjZihz+u+P4WoXaU5YeEbt1el9TpU+MKfckh+AS5XGajn2HbP8w3PJheuU6HcRrF8wFAwMGDhpDUOnbSQuLoaNS0YRHx+f6ZyFyMsyfEL73bt3+Pj44OXlxY0bN5g9ezZffPEF7du3V929DTBu3Dhu375NWFgYL1++5H//+x+FChUCwNTUlODgYLp166Y27o4dOxIWFoaZmRkmJib8+eefeHl5ERkZyfPnz5kyZYrGmGbMmMH+/fsB5Y9wCXeKGxgYMH36dF69ekVUVBQ3btygbdvEDXBCV+A9evTAzc2NyMhI+vXrl+o0Xrx4QVRUFK9fv2bx4sVqn5uamrJy5UpCQkJ48eIFw4YNSzGdhC7HE7qibt++PTdv3iQyMpKLFy9SpUri1aUDBw4kMDCQDh068PDhQ8LDw9m2bRumpqYMGDCA58+fExAQwJIlSzA0TJyNJiYmzJ07F09PT8LCwrh48SJNmzZNMd42bdpw//59QkNDVRcpJOQ5aNAgOnfurPoukw6fVLt27YiNjeXixYuq96ysrNiwYQNv374lIiKCx48fq9WFvb09mzZtwt/fn7CwMK5cucInn3yiNt5+/frx/PlzgoKC2LRpE2ZmZmqff//997i7uxMREcHNmzdT1FG7du149OgRERERnDhxgtKlS6eYl8m7Nh8zZgzPnz/XmGdWTRdg79691KtXjzJlyqQ5reyy/uQ1utSrStf61XAqZs2kLs0pbmXO1nO30hyuiLkpRS0KqV5GhnnryiPfw6d5POMP3uw+qutQAOV66uLRdTTpOJJKtdtQzKEcXYbOISY6ijuX9qc63MWj63Cu1IDGHUZgU8KJxh1GUKZifeWB0nsXDq+hVuNu1G7SAxs7Z9r1mYZlkeJcdduk9bSLOZSj5zd/Ur5GC4rYOuJUsT4tu47j8S034uJiM5Tr+SNrqNmkG7WbJsZjUaQ4V05s0tj+ittmLK1L0K7PNGzsnKndtAc1G3fl3KFViTkeWYdT5QY06aj8Hpp0HIFTxfpcSPI9nHVdgUWREnQZOhsHp2oULuqAU6VPKWLrmKH4s0rH5lZsPxzIxVvhvPSOZsl6H/KbGNCkTtpX2BsawLhBxdnsGoCPX0y2xpjb6zLBm5cPuXB4DV8M+VXr3NKbfnJXTyarwybKOjx/OLEOsyJvfx8PPN1v0bH/DOzLVKVoCSc69J9BdFQ4dy4d0Dq/5HQ5LwGq1f8c58oNKGJbElv7srTtNYV3kWH4eD7KU7loO+06zXpSunxdChd1wK5UZVp0GUtIgLfqztLUSF3m3LwsYGrOgImrqPJJO4qWcKKkcw3a9/0R7xf3Uv0hLbfmkt3ry+R0tR0vX6MF5ao3pWjxMhQtXoZW3caRr4Apr9zT3mfNiEIWRTC3tFG9Ht86SWFbR0qXVx6bxMZGc2TrPBaMb8KvI2vy7y9f8vzhpTTHqc1yqmSgNm1zS5ssyyuBPi1zyemqLjXVTJEkNZNV9Hne6dM+iib6fOyjT7nl9u34hxyP5/bcEmR2H0Xf80tKn7Z1ufW4B0ixP/bw5gnKVKhHEduSmc5XoVBw6dg6GncYScXabbB1KEdnLer00rHEnIomyelSkpwuHllDzcbdqPU+p896K3O6cjIxJzNLG7XXoxsnKFO+HoVtMp9TbsoPwMg4n1qOBc2sMp1Lbl6nvHxynSC/13QeOptiDuUp5lCezkN+w+v5HZ4/uKgxNiH0XZaclXJzc+PmzZt07dpV9V58fDzfffcdVapUYeDAgbRo0YLff/8dgIiICDZv3szgwYPVxjN48GC2b99OWFgY3333HZ06deLLL7+kfPny9OvXDw8PD43Tnz9/vuqkafHixVUnZ8eMGcOECROYOHEi1apV4/Dhw+zduxcXFxe14efOncuSJUuoWLEihw8fTj56unXrxrhx4xgxYgRly5alc+fO3LlzR63NhAkTuHr1KjVr1uTvv/9m6dKllC9fPs3vbd68eUycOJG6devy9u1b9u7dq3aHuKmpKd999x29evXis88+o1mzZuzcuZP27dvTvn17+vfvz/Dhw+nevbtqmNWrV9OwYUN69epFtWrV2LZtG4cOHVLL2dTUlIkTJ9K/f3+aNGmCo6Mj8+fPV32XW7ZsUZ3kLl68OOfPn9cYf5MmTbh69arae7/88guVKlWiXbt2VKxYkVGjRqm6Wi9UqBCnTp3Czs6OTp06Ub16dX7//Xe1E/LOzs507tyZjh070rFjR5o2bap2IcP//d//MXjwYEaNGkXlypVZtGgRGzZsoEkTZfeDDg4O7Ny5E1dXV2rUqMGKFSuYM2dOmvNBG1k13ZcvX+Lj40Pjxo0/OKaMiomN44GnD5+WV3/e+aflS3HLI+0fJ3rOX0/Ln5Yx7O9tXH7yMjvD/CgE+noSFuyLc+WGqveMTfJRunxdXj1N/Tnyr9xv4lylodp7LlUa8cr9JqD84dXrxT218QI4V26oGm9mpx0VGUr+AmYYGWnfi0VsbDTeHvdw0RSPu+ZpebrfTBG/S5VGeHncIy42JtU2zlUa8erpTdXfj26ewK5MFbb8bwy/f9eApTO6cPVUyu7zc0Ixa2OKWBpz82HinY2xsQruPY2kglPBNIf9sl0RgsPiOH4h7V4UskJeqMvod5FsXz6B9v2ma/3jvzbT15hT8jqsrF6HWZF3XGz0+1wT78ozNDTCyDgfL59c0yo/TXQ5L5OLjY3m2qkt5C9oTrGSmrs+y625ZGba0e8iuHl2J1ZFHbAoUjzV+KQueT8N3dQlQFREKBgYZOoOr7xQl5lZXyany+14UvHxcdy5dIDodxGUdK6RqVzSExsbze2Le6nZqCsG7++m2rNqGq+eXqf7yIWM+nkPleq2ZcPCYfj7eKQ6Hm2WU1CuKxZ934IFE5ry3x8j8H5xP8tz0qdlLqncUpexsdHcvrCXmo0Tayar6Ou8g9yV24fuo2gan74e++hbbnlhO56ctsfjeSG3D9lH0ff8EujTti43H/ckFxbsx5Pbp6jZuJvGz7UV5Jd6rXimMv9AmZNTingT509cKjk5VWqIZ1o53fnwnJLKDfl5PLrMvLEN+HNaW/aumU54iH+mcsnt65S42GgwMMDYOF+SNvkxMDD8oGNzkbUMjQxy7UsfZVn/2g8fPqRatWqqv5Pewezh4cH06dNZunQp33zzDQArVqzg/PnzlChRAm9vb6ytrenYsSOtWyufNeDo6MiTJ084e/YsoDwRmJrw8HCCgoIA8PHxUb0/ceJE5s6dy5YtymcoTJkyhebNmzN27FhGjx6tavfHH3+wa9euVMfv6OjImzdvOHbsGLGxsbx69YorV66otXF1dWXp0qWA8gT5uHHjaNasGY8epX6l76xZszh27BigvHPa09OTLl26sG3bNgDy5cvHqFGjePbsGQDbt2+nf//+FCtWjPDwcB48eICbmxvNmzdn69atODk50bt3bxwcHPD2Vj5jdcGCBXz22WcMHjyYH374QTXekSNHqsb7119/8dNPP6m+y8jISPLnz6/2XWpSunRpvLzUT4Q6Ojpy48YNrl1TrlSTPlu7T58+2NjYULduXdUzzt3d3dWGNzQ0ZNCgQYSFKbvWWL9+PS1btuTHH3/E1NSU8ePH06JFC9Vd4c+fP6dRo0aMGDGC06dPq76vcePGAfD48WOqVq2a6t392sjq6b5+/Vrj3dugnDf582d9d4MAgeGRxMUrsDY3VXvf2rwQfiEeGoexsSjET1+2ppJDMaLj4th/9T7Dl25j5Tc9qZ3Kc7dF+sJCfAEoZKH+HPJCFtYan+WoGi7YT+MwYcHK8UWEBqKIj6OQpaY2fpmedkRYIKf3LaV2s57ppaY+XGgg8fFxKaZlZmlN2F0/jcOEBftiZtkoRWzxcbFEhAVibmVLWLAfZsnHmeR7AAh8+4qrJzbxadtBNOk4As9ntzn4368YG+ejRsPOGcrjQ1lZKDe1QaHqV9MHhcZhUyT1zXAFpwK0/NSC8XNy5iKSvFCXhzfPpqRLTSrUbKl1XtpMP2VOvhSySFaHlinr8EPzLlrcCUtrO45tX8jnA2dhkr8gFw6vISzYl7AgXzJLl/MywaObbmxfPoGY6EjMLW0YMHEVhcwz/riKvFCXoHw21tFt84l5F0HREk4MmLhK7aAzOalL9WnnVF0miIl5x7HtC6haryMFCpppbJNbc8nO9WVyutyOA/i8esSKX3sTG/OOfPlN6TX6L2zt1S9MzioPrx8nKiKUGg27AMpn1d25dIDx80+qnhvc8LOhPL1zlhtnd9Kq23iN49FmOS1awkl5l4V9Od5FhXHx6DpWzu7DqFm7P/g59Wqx6NEyl5Su6zJB8prJSvo67yB35JZV+yjJ6fOxj77llhe240ll5Hg8L+T2Ifso+p5fAn3a1uXm457kbp7fTb4ChT64u/GEGJJ/19rUqcb5E6KeU4o2lta4p1IXt87vJl/+D89JPU7d5udStQmV6nyGlbUdgX6euO1ewtp5gxj+0w6MTVI/BtcYUy5fpzg41SBf/oIc3Taflt3GAQqObpuPQhGf6nIrhL7LshPaBgYGqq6+AZo1a8a0adOoVKkSFhYWGBsbU7BgQUxNTYmIiODKlSvcu3ePAQMGMHfuXPr378/Lly85ffo0AGvWrOHo0aM8evSIQ4cOsX//fo4ePap1PObm5tjb23Pu3Dm198+dO6fq+jtB8ruMk9u2bRtjx47l2bNnHDp0CFdXV/bt26f2TOzbt2+rDfPmzRtsbW3THO+FCxdU/w8MDOTRo0dUrFhR9V54eLjqpDMoT9Z7eHgQHh6u9l7CdGrVqoWhoSGPHz9Wm07+/Pnx90+8Uin5eL29vdONVZOCBQsSFRWl9t7SpUvZsWMHtWrV4siRI+zevVuVZ40aNbhx44bqZLYmHh4eqpPZyWOrVKkSBQsWTFEH+fLlU3UhXrFiRbUu0EH9e86MrJ5uZGQkpqamGj+bOnUqM2fO/KB405P8qkoFilQf61PatgilbYuo/q5e2o43gaGsdbsiJ7Qz4PaFfexbN0P1d9+xy4CU8+L9m2mOy4BknyuU76bbJtl4tZ12VGQY//0xEpsSzjTr9E2asaUmRc0pNMSoPkRqI0p1nMqhEt9TKBTYla5Mq+7KH5xLlKqEr9dTrrhtyvYT2k3qmDOyd+I69del73eCFertDFB+F5oUyG/A2AHFWbrpLaHh2fNcnLxWlw9vnOD5g0uMmLkzzVgyFGMaeaWIRaH6IO1xZiBvI2MTen6zhD2rf2Tut/UwMDTCqdKnuFRtkmYuyeXGeVmmYj1GztxFRFgg109tY9vSsXz149YUB6fJ5cZctJl2QhemoUG+nD+8im1LxzJk2qZ0n4krdZkyfk2yal4CxMXGsH3ZeBQKBR36z0jxuSa5MZfsXF+mHG3Ob8cBrEuUYeSsXURFhHD/6hF2rZjC4Cnrs+Wk9o0z2ylbtbHq5LX3i/ugUPDntHZq7eJiozF936Xhr6Nqqd6v9unnfD5gljKPdJbTks411O40L+lSi+WzunLp2Aba9/0x0znkxjqFzC1z2tBVXSa4fno7Lklq5kPo87zLjblldh9FW/p87JNXc8uNdZhVx+N5LbeM7qPoe37p0adtXW487knuxpkdVKvfMd1juORuX9zH/iR12mfMshSxwvvff9K70z3Fb7aQcr5qP94bZ3dQtX5Htd63Miq35Vflk/aq/9s6lMOudBX+mNSSJ7dPpnviPq+tUwpZFKHHqD84sH4Wl46vx8DAkKr1OlCiVCUMDI3SjE8IfZVlJ7QrVqyoegaxo6Mjrq6uLFu2jOnTpxMQEECjRo1YtWoVJiYmqmFWrFjB6NGjmTt3LoMHD2b16tWqz27cuEGZMmVo164drVq1YuvWrRw7dowePXpkKC5FsrMFyU+8A2oniDXx9PSkfPnytG7dmlatWvH333/z/fff07RpU2JjlXfcxcTEqA2jUCjUutLOTLyaxpnWdAwNDYmNjaV27dpqJ9sBtZPEWRWrn58fhQsXVnvv0KFDlCpVig4dOtCqVSuOHz/O//73P77//nsiIyPTHWd6+QF06NCB16/Vn0v57t07IJWNQDLx8fEp2iWty+SyaroJihQpgq+v5quoZs+ezcKFC9XeCwnJmq6GCxcqiJGhAX4h6vUeEBqBtXkhrcdTrXQJDlx9kCUxfSzK12iOvVNiDxYJ3bmGBfthbpV44jM8xD/NH1LMLIsSFqJ+1WV4qD9mlkUBMDUvjIGhUYqrTcNDE8drZmGj9bTfRYaxYeFX5MtvSs9v/8LIOPXlRBNT88IYaoonxD/FVYqJOdpobG9oZIxpIav3bYoSmqxNWIg/hd5/DwBmVjbY2Kn/4F20hDP3rx7JUA6ZcflOGI89Ei/2MTFWrh+sLIwJDElcN1uaGxEcGpdieIDiRU0oVtSEaSPsVO8lrGa2L3Zh9C8vePOBz9TOa3X5/MFFAnxfMme0+rO7tv7vOxzL1Wbw5PUa49Nm+ilz0q4OPzRvALvSVRg1azdREaHExcZQyKII//7yJXalq2iMTZPcNC8T5MtvinWxUlgXK0VJ5xosmdKWG2e207jDiDyTS0bWlwVMzSlgao51sdI4OFdn7uh6PLx2lKr1O2qMT+pSN3UZFxvDtqXjCPL1ZOCkNVrfbZibcsnO9WVyutyOAxgb58O6WCkA7MtUxcvjLhePrqPToJ+1il9bQX6veXb/Aj1H/6l6T6GIx8DQiBE/bU/xY1G+AsoLU0fOTOzhK//7WtIm/+QMDQ2xL1OVAJ8XH5RHbqrTxBgyt8ylRdd1CYk10ytJzXwIfZ53uTG3zO6jpEefj33yem65qQ6z+ng8r+WW0X0Ufc8vNfq0rcvtxz0JXjy+iv+b5/QYuShD+QGUr94chxmJdRqbSp1GpJGzKicNeZtZJMsped6p1H9CTt0zkVNSuTW/BOZWtlhZ2+Gvxb50XlungLIr8zFzjxIeGoihkREFTS2YN7YRVYrKjWa5hYGh9ueFxIfLkmdoN2/enGrVqrFjxw4A6tSpg7GxMRMmTODSpUs8efIEOzu7FMNt2LABR0dHvv32WypXrszatWvVPg8NDWXr1q0MHz6cnj170r179xQnUFMTGhrK69evadRIvYuSBg0a8OBBxk/GRUVFsW/fPsaMGUOzZs1o0KABVatWzfB4kqpfv77q/1ZWVpQrV46HDx9menw3btzA2NgYW1tb3N3d1V7pdR+eVHR0NEZG6V/lc+PGDSpVqpTifT8/P9auXUv//v0ZO3Ysw4cPB5R3sdeoUUPreZjc/fv3iYqKwtHRMUV+np6eqjZJv1cgxd++vr6q56wnqFGjRrZPF5R3yzs7O6vu7E4uOjqa0NBQtVdWMTE2oqJDMS4+Vt/AX3z8guqlUy6fqXno+ZaiFtqfABfKHzkTfjSxLlYKGzsXzCxtcL+f+Hz62NhoPB5doaRLzVTHU9K5Bu731J9p7373nOouH2PjfNiVqqw2XgD3e+dV4y1s46DVtKMiw1i/cChGxib0/u7vDF+hmhBPidKVU8T87P55SjprztPBuQbPksX/9N457EpXVh3AOzjX4Fny7+HeOUq61FD97ehSE783z9Xa+Pt4YGWtfa1nVtQ7BW/8YlSvV2+iCQiOpXqFxJ4ZjI2gsktBHj7TfKHPa58Yxvz6gvFzXqpeV+6Ec/dJJOPnvMQv8MNOZkPeq8tGHYYxatYeRs7cpXoBtO01hc5DZqcanzbT1yqnZHWYFXknVcDUnEIWRfD38cDL4y7la7ZINafkctO8TI0CBbEx0XkqF23Xl6nmG5t6vlKXSjlZlwknZ/zfvmDAxNWYmmm/P5qbcsnO9WVyutyOa6JQKFQ/OmWlG2d3UsjCmrLVmqreK+5YEUV8HOGhAWrz3rpYKdXzMJO+l/CjkzbLqaa83rx8gJlV5p6zmSA31Sl82DKXltxQl6qaqd40xWeZoc/zLrflpom2+yjp0edjn7yeW26qw6w+Hs9ruWV0H0Xf80uNPm3r8spxz/Uz2ylRqjLFHStkKD9Q1mmRYqVUr4Q6TTo/4t7XikMq8y8hp+Tz8FmS+WP0Pqfk8/DZ/fM4aMjpRkJOJTOeU1K5Nb8EEWGBBAd4Y67FvnReW6ckVci8MAVNLXj24CLhof6Ur9E83XyF0EcZPqGdP39+ihUrhp2dHTVr1mTq1Kns2bOHffv2sW7dOkD5XGQTExO+/fZbypQpQ79+/Rg5cmSKcQUFBbFz507mzZvHkSNH1O5+HTt2LD179qR8+fKULVuWHj164O3trXpWtjbmzZvH5MmT+fLLLylXrhyzZ8+mRo0aas/31sbAgQMZMmQIlStXpkyZMvTv35+IiAi150Nnxk8//USLFi2oXLkya9aswc/Pj927d2d6fE+ePGHDhg2sW7eOLl26ULp0aerUqcOkSZNo165d+iN4z8PDg2rVqlGuXDmsra0xNtZ8I//hw4epXLkyVlZWqvdmzZpFp06dcHZ2plKlSnTs2FF1AcGmTZt48+YNu3fvpkGDBpQpU4auXbtqPPGrSVhYGPPnz2fRokUMGDAAJycnatSowddff82AAQMAWLZsGc7OzixYsIBy5crRu3dvBg0apDaekydPYmNjw6RJk3BycuLrr79O8/vJqumC8iT3u3fvPrgb9Mzq36w2Oy/eYdelOzzz8WfeLje8A0Pp0UDZDf/i/Wf44b+DqvYbTl3jxJ0nvPAN5Km3H4v3n+HY7Sf0apz2jwK5jVEhUyyqV8CiunInzrSMAxbVK1CgZAmdxGNgYED91gM4s385D64dxcfzMbtXTsUkXwGq1ku8m2/nv5M5tn2B6u96rfvjfu8cZ13/xdf7GWdd/+XZgwvUbz1Q1ebTtoO4fno718/swNfLnUObZhMc4E2dZr20nva7yDDWLxhK9LtIvhj8K++iwggN9iU02Jf4eM13FKemQZv38ZxWxnNw02yC/b2p21wZz9FtC9j572RV+7rNexHk58WhTbPx9XLn+ukd3Di9g4afDVG1qf/+ezhzQPk9nDnwL8/uX+DTpN9Dm0F4PrvF6f3L8Pd5we0L+7h2ciuftOybofizyn63ILq3KUy9aoVwLJGPb/sX512MgtNXEy9a+a5/Mfp1Uv4gHhOr4KV3tNorPDKeyKh4XnpHE5ux2aCV3F6X5pY2FHMop/YCsLS2o7BN2lempjf9Y9vV67BOs14E+3txaPP7Ojyzg+tndtCgbWIdZkXeAPeuHOL5w0sEvH3FwxvHWTd/CBVqtcSlivoFeRmhy3kZ/S6CYzsW8sr9JkF+r/F6cY89q38kJOANlet+lqdy0WbaAW9fcebAcrw87hLk78WrpzfYtnQcJib51U6OaSJ1mXPzMi4ulq1/j8HL4y7dhs0jXhGn2q6ldeFBbswlu9eXyelqO35s+0JePL5KoJ8nPq8ecWzHIjweXqbap59nKP70xMfHc/PcLqo36IyRUeIxT9HiZaha/3N2rZjM/WtHCPT15PXzO5x1/ZfHt0+lOj5tltOTe/7i6d0zBLx9hffLB+xZ/QNvXj1UWwazgj4tc8npqi5BWTM3zu6iRkP1mslK+jzv9GkfRRN9PvbRp9xy+3b8Q47Hc3tuH7qPou/5JaVP27rcfNwDygtI7l85TK0mGesVNjUGBgbUazWAMweW8+D6Ud56Pmb3qpR1umvFZI7tSFKnrRJz8kuSU70kOdVvM4jrZ7ZzIyGnze9zaqqe07vIMO5fzbqcckt+0VHhHNkyl1dPbxDk54nHw0tsWjIKU/PCVKjZKlO55OZ1Cii7wn/lfpOAty+5dWEv2/4ew6etB1K0hFOG8xVCH2R4q9SuXTvevHlDTEwMgYGB3Lp1i++++461a9equsu+desW48aNY/LkycyePZvTp08zdepU1q9P2bXKypUr6du3L6tWrVJ7PywsjMmTJ1O2bFni4uK4cuUK7du3T9FdeFqWLFmChYUFCxYswNbWlvv379OpUyeePn2aoZyDgoKYMmUKCxcuxMjIiDt37vD5558TEBCQofEkN2XKFBYvXkzZsmW5desWnTp1StHldkYNHjyYH3/8kQULFmBvb4+/vz8XLlzA1dVV63H8+++/NGvWjKtXr2Jubk6zZs04dSrlDzd3797l6tWrfPnll/zzzz+A8g7j2bNnU7p0aSIjIzlz5gy9eilX1DExMbRp04YFCxbg6uqKsbEx9+/f55tvtH8u7/Tp03n79i1Tp07FycmJoKAgrl+/zm+//QbAq1ev6NatG4sWLeLrr7/m8uXLTJs2Ta07+4cPH/L1118zbdo0pk+fzo4dO5g/f77qTvLsmi5A7969+e+//7Tqfj07fFazAsHhUfxz+CK+IeG4lLDmf8O7YlfEAgC/kHDeBCZ2cR4TG8fCvad5GxxGfhNjnItZ89ewLjSulLc2mpa1q/Dp8cT1T6X50wB4tW4nt4dO1UlMDdt9RUx0FAc2/ExkeDAOTtXoP2GlqstKgOAAL7VuSxxdatF95AJO7FzMiV1LKGJbku4jF+LgXF3Vpson7YkIC+LU3v8RFuyLrX1Z+o5djlVRe62n7fXiHq+f3QJgyRT158+M+f0YhTPQrU2Veu2JCFfGE5oQz7jEeMKCfQn291K1L2zjQL9xyzm0aQ6XT2zE3MqWdn1/oFKdtonfQ9nE78Ft1xIK25akR7Lvwd6pKr1G/8mx7Qs5tedvrGwc+KzP1Cz/IVxbu44Fki+fAcN72mJmasgTjyhm/fWaqHeJ2zSbIsapPlM7p+TmuvwQ6U0/NNiX4AD1Ouz7vg6vJNRhn2R1mEV5hwa95fDmOYSF+GNuZUP1T7+gSadRH5yzrualgaERft7PuXXuOyLCAilYyAr7MlUZMvU/bO3L5qlctJm2sUk+Xjy+xsWj64gMD8HMwppS5eswdNqmdJ/FKXWZc/MyJPANj26eAGDZzM5qMQ2ctJYyFerlmVy0nXZW0dV2PCzEn53/TCI02JcCBc0pVrI8/Sf8i3Plhlma37P75wn296Jm464pPus85DdO71/KkS1zCQl8i6mZFQ7ONShbLfXnyWuznEZFhLJv7QzCgn3JX9CcEo4VGTx5PQ5Juj/MKvq0zCWlq7qEtGsmK+nrvNNlbtmxj5KcPh/76FtuuXk7/qHH47k5t6yg7/mp4tGjbV1uPu4BuHvpAAoUVK3XIUvyBWWtxMZE4Zq0VsZrqNMkj7As6VKL7iMWcGLXYtx2v89pxEIcnNRzigwL4tS+JDmN0ZDTZWVOVT7JupxyQ34Ghka8ff2YWxf2EBURirmlDaUrfEL3kYsyvRzm9nWK3xsPju1YRGR4MFZF7WjccSSfthmUqVxF9jA0ki7Hc5IB7x9Zryt9+vRh8eLF2NnZffDJ3LyiadOmnDx5EisrK4KDg3Udzgdp164d8+fPp0qVKhm62OBjVLRoUR4+fEidOnXw8PDQejiFQkGU6z/ZF5gOFWivvIjggEl5HUeS9TrEPAJg0zn9XC56N1RurDef17/8ejVQ5tZl9BMdR5L1dv2l/LFO3+tSH/OT3PIufc5Pcsu7PobtuD7OO6nLvEuf6xL0uzY/hrrUx9xAv5e7j2GZ08fc4ONYp+jjvEuYbxvP6l9uAH0a6W9+Cbnpa10mvWhA6Mblhh9+wWd2+eTcJV2HkOWyp48sLRQsWJAyZcowdepUli9f/tGczNY3Bw8epGzZstjb26ueJy00K1OmDF9//XWGTmYLIYQQQgghhBBCCCGEEEII8THT2QntSZMm8cMPP3D69Glmz56tqzBEFliyZImuQ8gTrly5wpUrV3QdhhBCCCGEEEIIIYQQQgghhPgABtLleI4y1NWEZ82aRb58+WjVqhXh4eG6CkMnTp06hYGBQZ7vblwIIYQQQgghhBBCCCGEEEIIIbKTzk5oCyGEEEIIIYQQQgghhBBCCCGEEGnRWZfjQgghhBBCCCGEEEIIIYQQQgiR1xgYyj3DOUm+bSGEEEIIIYQQQgghhBBCCCGEELmSnNAWQgghhBBCCCGEEEIIIYQQQgiRKxkACl0HIYRInUIhi6gQQgghhBBCCCGEEEIIIZQMDAx0HcJH71qLhroOIVW1T5zTdQhZTu7QFkIIIYQQQgghhBBCCCGEEEIIkSsZ6zoAIUT6Np7Vz7u0+zRSXkW26Zz+5de7oTK3AybldRxJ9ugQ8wiAc/fDdBxJ1mtYyQzQz+UuYZnbdTlOx5Fkjy6fGAGw9UK8jiPJel9+qrwGUZ/Xl1KXeU9CXepzbvpel67XY3QcSdZrX8sEgPWndRxINujfRPmvPi5zkLjcud2J1HEkWa951YIAuA/ooONIsofzugMAbLuof7XZo76yLvX5uEcfc4PE/PTxmDzheFwf91MS9lH0MTdIzE+ft3X6uJ+iz8c98HH83qDPuQnxMZET2kIIIYQQQgghhBBCCCGEEEIIoSVDI7mwICdJl+NCCCGEEEIIIYQQQgghhBBCCCFyJTmhLYQQQgghhBBCCCGEEEIIIYQQIleSLseFEEIIIYQQQgghhBBCCCGEEEJLBobS5XhOkju0hRBCCCGEEEIIIYQQQgghhBBC5EpyQltkyhdffMGTJ0+IjY1l0aJFDBw4kMDAQF2HlWNKlSqFQqGgevXqug5FCCGEEEIIIYQQQgghhBBCCL0lXY7nEatXr2bQoEGqv/39/bly5QqTJk3izp07OR7P8uXLWb16NUuWLCE0NJTY2FhcXV1Vn8+YMYPOnTtTs2bNHI/tY6ZQKDi19y+undpKVEQI9k7VaN/3J2zty6Y53P2rh3HbvYRA35cUtnGkRdexVKzVWq3NlRMbOX94JaFBvtjau9C21zRKlauj+nz3yincOr9bbRh7p+p89cOWTOdyco96Lh36aZfLiV2JubTsOpaKtdVzuXxiI+cPJebyWW/1XNKbdkRYECf3/In73XMEB77B1KwwFWq2pEWXMRQwNc9UvplVpFEdnCYMxbJWFQrY2XK129f47D2eozFkhRMHt3Jo93qCAv2wL+lE76ETKVdJ8/ojKMCXLWsW4eH+kLfeL2nZoRd9hk7M4YgT6XK5S2rfup+4fmorbXtNpX7rgVmWX1IXjm3i9IFVhAb7UszehY79plCmvOZ4AJ49uMKBjXPxef0UCytbmnQYQv2WvVSf371yFLd9/+Dv85K42FiKFnekcbvB1GrUKVviT+rS8Y2cPbiKsPffbbs+UymdRi7PH17m0Ka5vH39FPPCtjRqN5RPWvRSa3PvyhGO71pCwNuXFLF1pFW3MVRKsv55FxnO8Z2LuX/9GOEhAZQoVZH2fabh4FQ1y/NLbz2XnMejyxzePEeZn5UtDdt9Rd3m6vmlt349c2A5D64dxc/7Gcb5ClDSpSatu0+gaAmnLM8vKanLvFOXyWV1vj6vn3Bi5594edwjyN+Ldr2n0KBt9qwP06NPdanJ2SObcdu/mpAgX4o7uNB5wGScK9ROtf3T+1fYs2EebzyfYlHYlhYdB9OwdU+1NpHhIRzYsoTbV44RGR5CERt7vuj3PZVqNsnudNQoFApO7/uLG6e3EBURgl2Z6rTr8xM26WzXH1w7zKk9i1XryGadx1EhyXb9nOtyHl4/gv8b5TrSwbkmLbtNxLp49q4jk9Pn5S65k4e2cHTvWoID/bAr6UyPQd9TtlItjW2DA33ZvnYBL5894K33S5q3782XgyflcMQZY9GyA1btu2JkWYSY1y/x++8foh7fS7W92afNsOrQDZNidsRHRhBx+xr+m1cSHxaag1Frdun4Rs64riIs2BdbOxfa902/Lg9unMtbL+V+S+P26nV55eRWbp7bi4/nEwDsSleiTfdxODhXy/Zc0pOXj3u0oe/5JZdXj8f1eT9Fn3PTRJ+2dfq0j6JPx3W6+G0hvenGxcZwYtdintw+RaCvJ/kLmuFUqQGtuo/HonCxDOWXm39/Th7nf4uG8/TuGXqO/ouKtVplKE+RfQwM5Z7hnCTfdh5y8OBBihcvTvHixWnZsiWxsbHs378/x+MoVKgQxYoV4/Dhw3h7exMWFkZUVBS+vr45HktqjIyMsmQ8JiYmWTKenBr3uYMruHBkDe37TmfYj9sws7Bh/YIhvIsMS3WYV09vsH35eKp92omRM/dQ7dNObF82Ds9nt1Rt7l525dDm2TTuMJIRM3bhWLYO//0xnGB/L7VxuVRpzISFZ1SvvmOWf3gu/aYzbPo2zCxtWDc//Vy2LRtP9QadGDlrD9UbdGLbsnF4uifLZdNsGnccyciZylw2LBpOUJJc0pt2aNBbQoPe0qbnJL7+eS+dh87m6d0z7Fn9Q6bzzSyjQqaE3H7EvTE/5/i0s8rls0fYtGoBHbsPYeaCjZStVJNFv3yLv6+3xvaxsTGYWxSmY/chlCxdLoejTUnXyx3Aw+vHeP3sNuZWttmSI8CtiwfZv2E2zb8YwXe/7KB0+dqsnjeCIL+U8QAEvPVk9fyRlC5fm+9+2UGzTsPZt/437lw5ompT0MyS5p1G8PVPGxn72y5qN+nK9n9/4PHts9mWB8CdS64c3DiHpp+PYNTPOylVrjbrF45QWw8kFejryfqFIylVrjajft5Jk47Dcf3vN+4lyeXl0xtsXapc/3zz826qN+jElr/H8yrJ+mf36h95eu883YfPZfT/7cGlckPWzBtCSKBPluanzXoueX7/LRqBY9k6jJy5i8YdR3Bw46/cv3pY1Uab9avHoyvUbdGHr37cwoAJq4iPi2X9wq+IfheRpfklJXWZd+oyJ/KNeRdFYZuStO4xHjPLotkaf1r0qS41uXHhILvXzaF152FMnL0Np/K1+GfOSAL9NG+3/d968u/vX+NUvhYTZ2+j9RdfsWvtbG5dOqpqExsbw9LfhhHg+5pBYxcydcF+eg6bhWWR7NuupebCoX+5dHQ1n/X5iSE/bMfMsij/LRrMu6jUt+ue7jfY+c84qtb/gmE/7aFq/S/Y+c9YXifZrr94fJk6zfsyeOpW+o5bTXxcHP8tGpqt68jk9Hm5S+7qucNsWzOPdl2/4od5m3GpWJO/fvuGgFT2L2NiojGzKEy7rl/hUEr3+5fpKVSvMUX7DiNw7xY8f/qOyMd3KTFxFsbWNhrbFyhXCdsR4wk9dYRXU7/G56/ZFHAqi82Q73I48pTuXHLF9b85NPt8BF//vJNS5WuzbkHqdRng68m6BSMpVb42X/+8k6Ydh3Ngg3pdPn94hWr12zN0yhpGTN+ElbUda+Z/RUhA9m7b0pPXj3vSo+/5aZIXj8f1eT9Fn3PTRJ+2dfq0j6JPx3W6+m0hvenGREfh/eI+TT7/mhEzdtBz9J/4+3iwacnXGc4xN//+nNTFo2vBQJ7VLISc0M5D3r17h4+PDz4+Pty6dYu5c+fi6OhI0aKJG2U7Ozs2b95MQEAAfn5+7N69m1KlSqk+X716Nbt27WLChAl4eXnh5+fHX3/9hbFx4s36JiYmzJ07F09PT8LCwrh48SJNmzYFoGnTpoSFKVeqbm5uKBQKmjZtqtbl+MCBA5k5cyY1atRAoVCgUCgYOFDzFXAJ8fz000/4+PgQHBzMsmXLUpzs/f7773F3dyciIoKbN2/SrVs31WdNmzZFoVDQpk0brly5wrt372jcuLHG6VWpUoXjx48TERGBn58fy5cvp1ChQinimTJlCq9fv+bx48cA1K1bl+vXrxMZGcmVK1c03nlesWJFDhw4QGhoKG/evGHdunVYW1urPndzc+PPP/9kwYIF+Pr6cvTo0RTj+BAKhYJLx9bRuMNIKtZug61DOToPnUNMdBR3LqV+4cOlY+twrtSAxh1GULSEE407jKBMxfpcOrpW1ebikTXUbNyNWk16YGPnzGe9p2FZpDhXTm5SG5eRcT7MLG1Ur4JmVpnO5eLRdTTpOJJKtdtQzKEcXbTI5eLRxFxskuRyMUkuFw6voVbjbtR+n0u7Pspcrrpt0nraxRzK0fObPylfowVFbB1xqlifll3H8fiWG3FxsZnKObN8D5/m8Yw/eLM7a+spJx3eu4HGLb+gSesu2JUsQ5+hEyliXQy3Q9s1ti9qa0efr76nYfOOFDQ1y+Fo1eWG5S4k0AfXjb/Qddg8DI2yr+OVswfXUKdpNz5p1h1be2c+7zcVS+sSXDy+WXOOJ7ZgVbQEn/ebiq29M580606dpl0547pa1ca54idUqdMKW3tnrIs50qhtf4qXLIfH4+vZlgfA+cNrqdWkK3Wa9sDWzpn2fadhUaQ4l09ozuWy22YsrUvQvu80bO2cqdO0B7Uad+XcoVWqNheOrMO5cgOadhyOjZ0TTTsOx6lifS4cWQcoD7juXz1K2y8nUrp8XayLlaJFl9EULurA5RObNE43s9JbzyV39aQyv3Z9pmFj50ztJj2o2bgr5w8n5qfN+rX/+BXUbNQVW/uyFHesQOchswn298LLI/W7xT6U1GXeqcucyNfBqSqf9fqeavU7YGycL1vjT4s+1aUmJw+so17zrtRv0Z1i9s50GTgFK+vinDuqOb/zx7ZiZV2cLgOnUMzemfotuvNJsy64HVijanPJbScRYcEMnbAEp/K1KGJjh1OFWtiXqpBDWSkpFAouH19Ho/YjqVCrDbb25eg0eC4x0VHcTWO7fvnYWpwqNaBh+xEULeFMw/YjKF2hPpeOJa4j+4xdSfWGXbGxL0uxkhX4fPBsQgK88H6RfevI5PR5uUvu2L71NGzRhUatulLCwYkvB0+isHVxTh3ZprF9UVt7eg6ZTP1mn1NAx/uX2rD6rAshp44QeuoIMV6v8P/vX2ID/LBo0V5j+/zOFYj1fUvw0X3E+vkQ9fg+wW6HKFAm7buPcsK5Q2up3aQrdZop67JDX+V+y+VU1plXTmzGyroEHRLqslkPajXpytmDiXX55ch51GvZhxKlKmJj50TnIT+jiI/H/f6FnEpLo7x83KMNfc9Pk7x4PK7P+yn6nJsm+rSt06d9FH06rtPVbwvpTbeAqTkDJq6iyiftKFrCiZLONWjf90e8X9xL9WS7Jrn99+cEb14+5MLhNXwx5FetcxNCX8kJ7TyqUKFC9O3blydPnuDv7w9AwYIFcXNzIywsjCZNmtCoUSPCwsI4dOiQ2gni5s2b4+zsTPPmzRk4cCCDBg1S68589erVNGzYkF69elGtWjW2bdvGoUOHcHFx4fz585Qrp7yKr2vXrhQvXpzz58+rxbZlyxbmz5/P3bt3VXeUb9mSerfTLVu2pGLFijRv3pzevXvTpUsXZsyYofr8//7v/xg8eDCjRo2icuXKLFq0iA0bNtCkiXr3g7///jtTp06lYsWK3L59O8V0ChYsyKFDhwgMDKRu3br06NGDVq1a8ddff2mMp3Xr1nTs2BFTU1P279/Po0ePqF27NjNnzmT+/PlqwxQvXpxTp05x8+ZN6tSpw2effUaxYsXYunWrWruBAwcSGxtLw4YNGTFiRKrfSWYE+XkSFuyLc+WGqveMTfJRunxdPN1vpDrcK/ebOCUZBsC5ciNePb0JQFxsNF4v7qmNF8CpUkM8n6qP1+PRZeaNbcCf09qyd810wkP8M5VLoG/qubx6mnYuzlXU43Sp0ohX7spcYlPJxblyQ9V4MzvtqMhQ8hcwwygbTyjqo9iYGF64P6Ryjfpq71euUZ+nD1Mux7mNrpc7RXw8u1ZMokHboel2h/QhYmOjee1xn7JV1eMpW6UBL57c1DjMi6c3KVulgXr7qo3wfH6PuNiYFO0VCgVP713A19sjzS7hPlRsbDReHvdwSbGuaJjqMv7q6c2U7as25LVHYi6vnt7CJUW+DXn5fpzxcXHEx8dhnC+/WhuTfPl5kYU/hmiznkvulfvNFO1dKjfCK2l+6axfNYmKVHZhWrCQZUbT0IrUZd6py+SyK9/cQJ/qUpPY2Bg8n9+nfDX1eMtXa4DH41sah/F4citF+wrVG/LqWWJ+966fpHTZ6mxf/SvTRzRh7vedObr7H+Lj47InkVQkbNedKjdSvWdsko9S5dLerns+u4lTpUZq7zlXbpzmMO+yeR2ZnD4vd8nFxsTw8tkDKlb/VO39itXr8+yR5jrNU4yMyV/ahci76vMt4s51CpStqHGQqCcPMC5SFNNqynWGkYUVZnUbEn7rSraHm5a06vJlKnX5UkNdlq2Sdl3GvIsiLi6WgmY5s7xpktePe9Kj7/npC33eT9Hn3DTRp22dPu2j6NNxna5+W8jMdAGiIkLBwIACphZa5Qd54/fn6HeRbF8+gfb9pmNuqbknHqFbBoYGufalj+TMSx7SsWNHQkOVP3yYmZnh5eVFx44dUSgUAPTq1Yv4+Hi++uor1TCDBw8mKCiIZs2aqe4IDgwMZPTo0cTHx/Po0SMOHDhAy5YtWbFiBU5OTvTu3RsHBwe8vZVd1CxYsIDPPvuMwYMH88MPP/D27VsAAgIC8PFJ2W1JVFQUYWFhxMbGavw8uejoaIYMGUJkZCT379/np59+Yt68eUyfPp2CBQsyfvx4WrRowcWLFwF4/vw5jRo1YsSIEZw+fVo1np9++oljx46lOp2+fftSsGBBBgwYQEREBPfu3WP06NHs27ePyZMnq/IKDw/nq6++IiZGuaEdNmwYRkZGajE6ODiwbNky1bhHjRrF9evX+eGHxC6nhwwZgqenJ2XLluXJE+Wzu54+fcrkyZNTjTFfvnzkz58/1c/TEhas7PLdzMJa7f1CFtYauyhOHM4vxTBmFtaEhSjHFxEaiCI+LmUbS2vc7/qp/nap2oRKdT7DytqOQD9P3HYvYe28QQz/aQfGJhm7EjJh2oUykYumYRK+m4RcCllqauOX6WlHhAVyet9SajfrqfFzkbrQ0CDi4+OwtFL/vi2srAkOytwFETlJ18vd2YP/YmhoRL1W/T8oj/REvJ9P5sniMbe05nGwn8ZhwoL9ME+2rJlbWBMfF0t4WBAWVsod8aiIUH77rhmxsTEYGhryxcDplK3aQNMos0RCLmYW6l2OmVlYE5pGLinnV1Hi42KJCAvE3Mr2/fpHfZyFLIqq1i35CxaipEsNTu5Zik0JZ8wsrbl98QCez25TpFgpsoo267mU+flSyEL9REwhS2sN+aW+fk1OoVBweMscHMvWpphD9nRnJ3WZd+oyuezKNzfQp7rUJDwkUJlf8ngtrQlJJb/QIA35vV/HhIUGYVnYBv+3njzxfU3thh0YPnkpvm9esGP1r8THxdG226hsyye5hHVayvVd0Uztg4aHpL6OPLp1NiVdamNrnzNdfurzcpdcWKiyTi0si6i9b2FpTUiQ5lzzEiNzCwyMjIgNDlJ7Py4kCCPLwhqHeff0AT7L5lHsm8kYmOTDwNiY8OsX8Vu/TGP7nKKqy2RdwRayTGu/xS/Ffo6ZZdp1eWTbAiwKF8O5Us6uM5PK68c96dH3/PSFPu+n6HNumujTtk6f9lH06bhOV78tZGa6MTHvOLZ9AVXrdaRAQe17H8gLvz8f3jybki41qVCzpdZ5CaHP5IR2HuLm5saoUcofdIoUKcLXX3/NwYMH+eSTT3j58iW1a9fGxcVFddI7QYECBXB2dlad0L537x7x8fGqz729valatSoAtWrVwtDQUNXVdoL8+fOr7gTPardu3SIyMlL194ULFzA3N6dkyZLY2tpSsGDBFN1z58uXjxs31K+Uunr1aprTqVixIrdu3SIiIvE5defOncPIyIjy5curTmjfuXNHdTI76XDJY0yqdu3aNG/ePMV3D+Ds7Kw6oZ1ejFOnTmXmzJlptklw++I+9q9LvJO9z5j3P0Yke56GQpHyvRSSD6N8M3mjNMdb5ZPE7u1sHcphV7oKf0xqyZPbJ6lYu02ak799YR/7kuTSd+yy92FpiDudXAySx61IGbvGNsnGq+20oyLD+O+PkdiUcKZZp2/SjE2kJXl9KXLlo2Fy03Ln5XGXS8fWM+KnHZrrNTukyFORzrST55gyy3wFCvHdrzuJjorg6b2LHNj4O0VsS+Jc8ZMsClqr0JS5pPj+k7bXnEvSEaX4LpKNs/vwuexa+QPzxjXF0NCIEqUqUbV+R7xf3M9MBmnSZj2n1j5F7KoP0h5nKt+Z64Zf8Hn1iCFTN2oV7weRukxsn8vrMoVsyDfX0Ke61CDl+iDt/JK3T7ggN2EYRXw8ZhZF+HLYTAwNjSjpVJmQQF9O7F+drSe071zci+uGxO16r2+XqyJWixeFFmWmKUfNAx3a+DNvPR8zcFIOrCOT0+flLpnkNamMPffHrT1Fsr8N3u8spmRiV5Ki/UYQuGcTEXeuY2RVBOueQ7AZNBrflYuzP9T0JJ8tCkXa+y2prFM0zd8zB1Zw+6IrQ6esxSRf5i4ez1p547gn8/Q9Pz2hz/sp+pybBnq1rdOnfRQ9Oq7T1W8L2k43LjaG7cvGo1Ao6NB/RorPk8prvz8/vHGC5w8uMWLmzjRjEeJjIie085Dw8HDc3d0BcHd3Z+jQoQQHBzNs2DCmT5+OoaEh165do2/fvimG9fVNvDsg6claUG5UDQ2Vvc8bGhoSGxtL7dq1iYtT7+Iv4dnZOSVpXB06dOD169dqn797907t7/Dw8DTHZ2BgkORAN+W0UhuPNieKDA0NVXd6J5dwp7s2Mc6ePZuFCxeqvRcSEqKxbfnqzXGYUU31d2xsNPD+CtMkVyJGhPqnuNIvKTPLoimucAsP8VddTWhqXhgDQyPCQjS1SX285la2WFnb4e/zItU2qlxqNMfeKTGXuFRySW+aZpZFU8YZ6q+64l+VS/J8k3xHZhY2Wk/7XWQYGxZ+Rb78pvT89i+MjNWf/S7SZ25uhaGhEcHJriAODQ7AwjL1ea0ruWm5e/nkGuGh/iya1EL1uSI+jiNb5nLx6FrG/n4ik1mmZPp+PiW/ojgsJCDVPM0si2psb2hkjKmZleo9Q0NDir6/YtiuVEXeej3j5L5/s+3HgYRcUq4HAjBLpeZSm19Jc1G2Ub8TLzzUX+2K3CK2jgydup7odxG8iwzD3MqWLX+Po3BR+yzITEmb9VxyZpY2qedXyOp9m7TXr0m5/vcLj26eYPCUDVgWKf4B2aRN6jLv1GVy2ZVvbqBPdalJIYvCGBoapbgbOzQkIMUdUQnMrYqmaJ+QX6H33f9aWNlgaGyMoaGRqk0xeydCg/yIjY3BOJv2scrVaIG9U3XV33Exyu16eEiy7XqIf4q7YpIysyxKeLJ1ZERogMZhDm38hce3TjDg+w1YZOM6Mjl9Xu6SMzMv/H7/Uv2C7NDgACysct/+ZUbFhYagiIvD2LIwSY+IjSwsiQsJ0jhM4c+/JOrJA4Jc3/8g+soDv3dR2P84j4Dt64gLDsz2uDVR1WVQ8jpLe52pbV2edV3Fqf3/MHjSKoo7ls/S2DMqrx33ZJS+56cv9Hk/RZ9z00SftnX6tI+iT8d1uvptISPTjYuNYdvScQT5ejJw0pp0787Oa78/P39wkQDfl8wZrb6u2fq/73AsV5veezekma/IGYZGueAimo+IPEM7D1MoFMTHx1OwYEEArl+/TtmyZXn79i3u7u5qr9ROiiZ348YNjI2NsbW1TTEObboPTxAdHY2RkVH6DYHq1atToEAB1d/169cnNDQUT09P7t+/T1RUFI6Ojini8fT01DoegPv371OjRg1MTU1V7zVs2JC4uLgUd6QnH05TjEldv36dypUr4+HhkSLOpHeEpyc6OprQ0FC1V2ryFzSjSLFSqpeNnQtmljY8u5/4TPO42Gg8Hl3BwblmquMp6VxDbRiAZ/fOUdKlBgBGxvmwK1WZZ/eStbl/HgeX1McbERZIcIA35lbpP98jf0EzrIuVUr0ScnFPElfs+1xKpjHNks41cE8Wp/vdc5R0VuZi/D4X92T5ut87rxpvYRsHraYdFRnG+oVDMTI2ofd3f2Nikhuu9s97jE1MKOVcgfu3Lqm9f+/WJVwqVEtlKN3JTctdtU87MWrmHkbO2KV6mVvZ0uCzofQbvyKLMlYyNs6HfelKPL2rHs/Tu+cpVbaGxmFKudRI0f7JnXM4lKmc9sUfCgWx708oZAdj43zYla6ccl2RZD2QXEmXlOuWp3fPYV86MZeSLtV5mqLNeRw1jDNfflPMrWyJDA/m6Z1zVKiVdV1HabOeS07juvPeOeyS5pfO+hWU+yUHNvzMg2tHGThpDYVtHLIgo9RJXeadukwuu/LNDfSpLjUxNjbBoUwlHt9W763o8Z0LlC5XXeMwpctW5/Ed9faPbp+npFNifmXK18DvzUu1XqTeentgYWWTbSezAfIXMKOIbSnVq6hqu35O1SYuNpoXj9Perjs41VAbBuDZ/bNqwygUCg5t/JlHN47Qf8JaCtuUzPqE0qDPy11yxiYmODpV5EGyOn1w+xJO5TXXaZ4SF8s7j6cUrKI+30yr1CTqyQONgxjkyw+KeLX3FAnLmw5vn02oyxTbqnuat1UAji41NGzbUtblGdeVuO1dysAJ/2BfpkrWB59Bee24J6P0PT99oc/7Kfqcmyb6tK3Tp30UfTqu09VvC9pON+Fktv/bFwyYuBpTs8Lp5pTXfn9u1GEYo2btYeTMXaoXQNteU+g8ZHa6+Qqhj+SEdh6SP39+ihUrRrFixahQoQJ//vknZmZm7Nu3D4D//vsPPz8/9uzZQ6NGjShdujRNmjThjz/+wN5eu6uxnjx5woYNG1i3bh1dunShdOnS1KlTh0mTJtGuXTutY/Xw8KBMmTJUr14da2tr8uVL/RnK+fLlY+XKlVSsWJHPPvuMWbNm8ddff6FQKAgLC2P+/PksWrSIAQMG4OTkRI0aNfj6668ZMGCA1vGA8vuJiopi7dq1VK5cmWbNmvHnn3+yfv16VXfjmmzcuJH4+HhVjO3atWPixIlqbf73v/9RpEgRNm3aRN26dSlTpgytW7dm5cqVqrvMs5uBgQH1Wg3gzIHlPLh+lLeej9m9aiom+QpQtV5HVbtdKyZzbMcC1d/1WvXH/d45zrr+i5/3M866/suzBxeo13qgqk39NoO4fmY7N87swNfLnUObZxMc4E2dpr0AiI4K58iWubx6eoMgP088Hl5i05JRmJoXpkLNVpnKpX7rAZzZv5wH147i4/mY3StT5rLz38kc254kl9aJufgmyaV+klw+bTuI66e3cz0hl03vc2nWS+tpv4sMY/2CoUS/i+SLwb/yLiqM0GBfQoN9iY9X79kguxkVMsWiegUsqlcAwLSMAxbVK1CgZIkcjeNDtO3Uj9PHdnPm2B68Xj1n06oFBPi9oVnb7gBsX/8n/y7+SW2Yl88f8fL5I6KiIggLCeTl80e8fvUsx2PX5XJnalYYW4dyai9DI2PMLItStLhTlufaqN0grpzczpVTO3j72p19G+YQ5O9NvZbKZ8cf2rKQLcumJObYoieBft7s/28ub1+7c+XUDq6e2kHj9oNVbdz2/sOTO+fxf/uKt17POHNwDdfP7aVmw8+zPP6kGrQdyLVTO7h2egdvvdxx3TibYH9vPmmuzOXItoVs/yexx41PmvciyM+Lg5vm8NbLnWund3D99E4afjZE1ebT1gNwv3ue0wf+xdfrGacP/Iv7/Qt82iZxW/Xkzlme3D5DoK8nT++eY9WcQRQtUYZajbpkaX7preeObV/Azn8T86vTrBfB/l4c2jwbXy93rp/ZwfUzO2jQNjE/bdavBzb8zO0L++g2Yj75ChRSrRdjoqOyNL+kpC7zTl3mRL6xsdF4v3iA94sHxMXFEBL4Fu8XD7TqLSYr6VNdatKswwAuuu3gkttOfF67s2vdXAL9vGnQSpnf/k2L+O/vqar2DVp9SaCfN7vX/47Pa3cuue3kkttOmncYlNimdU8iwoLYtXYOb709uHf9FMd2/0ujNr1yNDcDAwM+aTmAc67LeXj9KG9fP2bvauV2vUqS7fqelZM4sTNxu1635QCe3T/H+YP/4OftzvmD//D8wQXqtUpcRx7aOIs7F/fS+asF5CtQiLBgX8KyeR2ZnD4vd8m1+rw/547v4tzx3Xh7PmPr6nkE+nnTpI1y/3LXf0tYveRHtWFePX/Iq+cPeRcVSWhwIK+eP8Trlbsuwk9X0KFdWDRtg3mT1pjYlcS6zzCMrW0IOeEKQJEeA7EdPl7VPuLGZQrVboBFi/YY2xSnQNmKFO03gij3R8QFBegqDQAafpasLv9T1mXdFu/rcutCti9PrMu6LZR16boxsS6vnd5Jo3aJdXnmwAqO7VhM16G/YlXUntAgX0KDfHkXlXaPadktLx/3aEPf89MkLx6P6/N+ij7npok+bev0aR9Fn47rdPXbQnrTjYuLZevfY/DyuEu3YfOIV8Spfn9I6ElRG7n992dzSxuKOZRTewFYWttl+w0EQuRW0uV4HtKuXTvevHkDKLuhfvjwIT169ODUqVMAREZG0qRJE+bOncvOnTsxNzfn9evXHD9+XOs7tAEGDx7Mjz/+yIIFC7C3t8ff358LFy7g6uqq9Th27NhB165dcXNzo3DhwgwaNIi1a9dqbHv8+HGePHnC6dOnyZ8/P5s3b1Z7jvT06dN5+/YtU6dOxcnJiaCgIK5fv85vv/2mdTyg/H7atm3L4sWLuXLlChEREezYsYPx48enOVx4eDiff/45y5Yt48aNG9y/f5/Jkyezc2fi8yu8vb1p2LAhc+fO5fDhw+TPn58XL15w6NAhtTtNslvDdl8RGxOF64afiQwPxsGpGv3HryR/ki5XggO81LpRL+lSi+4jFnBi12Lcdi+hiG1Juo9YiEOS7herfNKeyLAgTu37H2HBvtjal6XvmOVYve+2xsDQiLevH3Prwh6iIkIxt7ShdIVP6D5ykdq0M5pLTHQUB5LmMkFDLoaJuTi61KL7yAWc2LmYE7ve5zJyIQ7O6rlEhAVxam+SXMYm5qLNtL1e3OP1s1sALJmi/nzwMb8fo3DRnNupsKxdhU+Pr1f9XWn+NABerdvJ7aFTUxssV/mkURvCQoPYu/VfggP9sHd0ZuyPSyhqq/wRIDjQjwDfN2rDzBzfR/X/F+4PuHj6ENY2JZj3z/4cjR10t9zltOr12xERFsTx3UsJDfKluENZBk1cruq+KiTIjyD/xEcsFLF1YPDEZez/bw4Xjm3EwsqWz/tPo2rdxGUm+l0ku9f+THCADyb58mNTwomeI+dSvb72F1BlRtV6yvXAyT1/ExrsSzH7svQfv0z13YYF+RKcJJfCNg70H7+Mg5vmcOn4RsytbGnfdxqVk+TiWLYmPUYt4PiOxZzY+SeFbUvy5agFlEyy/omKDOXotkWEBL6hYCFLKtdpQ6tuY7P8CvL01nOhwb4EB3ip5dd33HIObZrDlRPK/Nr1+YFKddom5qfF+vWq2yYA1sxVv+DsiyG/UbNR1yzNMYHUZd6py5zINzTQl79nJNbauUOrOHdoFaXL12Xo1HXZmk9S+lSXmtT8tB3hocEc3rmMkCBfSpQsy/DJSyliY6fKL9AvMT9rWweGTfqb3et/5+yRTVgWtqXLwKlUr9da1aawdQlGTv2H3et/Z97krlgWtqVJu3607DQ0x/P79LNhxMS849DGWUSGB2PvVJ0+41aRv0DS7bo3BgaJF62WdKlF1+ELObn7D07uWUJhm5J0Hb5IrTvzayeV68j18/urTe/zQbOp3jB71pHJ6fNyl1ydhm0JCw3iwPblhAT6Yefowuhpf2H9vk6DA30JSFKnAL9+n3gBxctn97ly9iBFbErw29KDORq7NsIvncHPzILCX/TG2KoI0Z4v8F4wg1h/ZXekRlZFMLZO7Ckr9OwxDAoWxLJVR6x7DyU+IpzI+7fx37paVymoJNSl256/CQ1KrMvCSfZbggKSrDNtHBgwYRmuGxPrskM/9bq8dGITcbExbPprjNq0mnf+hpZdRudMYhrk9eOe9Oh7fprkxeNxfd5P0efcNNGnbZ0+7aPo03Gdrn5bSG+6IYFveHRT+Zi9ZTM7q8U8cNJaylSop3WOufn3Z5E3JK0Nkf0MeP/IeiF0YfXq1VhZWdGlS/beBZSXKRQKNp7Vz8W0TyPlCn/TOf3Lr3dDZW4HTHT7rLbs0iHmEQDn7ofpOJKs17CScsdRH5e7hGVu1+Wc7Ukgp3T5RPmoi60Xcu5Copzy5afKEyf6vL6Uusx7EupSn3PT97p0vR6j40iyXvtayh/t1p/WcSDZoH8T5b/6uMxB4nLndidSx5FkveZVlY8Jcx/QQceRZA/ndQcA2HZR/2qzR31lXerzcY8+5gaJ+enjMXnC8bg+7qck7KPoY26QmJ8+b+v0cT9Fn4974OP4vUFfczPQ4aNjhNK9zi10HUKqKu8+oesQspx0OS6EEEIIIYQQQgghhBBCCCGEECJXki7HhRBCCCGEEEIIIYQQQgghhBBCSwaGcs9wTpIT2kKnBg8erOsQhBBCCCGEEEIIIYQQQgghhBC5lFw+IIQQQgghhBBCCCGEEEIIIYQQIleSO7SFEEIIIYQQQgghhBBCCCGEEEJLBoYGug7hoyJ3aAshhBBCCCGEEEIIIYQQQgghhMiV5IS2EEIIIYQQQgghhBBCCCGEEEKIXMkAUOg6CCFE6hQKWUSFEEIIIYQQQgghhBBCCKFkYCDdXevawy/b6DqEVFXYekTXIWQ5uUNbCCGEEEIIIYQQQgghhBBCCCFErmSs6wCEEOnbdE4/79Lu3VB5Fdnm8/qXX68GytzO3Q/TcSTZo2ElMwAOmJTXcSRZr0PMIwA2ntW/uuzTSFmXD9xf6ziS7FHR2R4A1+sxOo4k67WvZQLo5/YgYVvw0N1Tx5FkjwrODoB+1+WRW9E6jiTrtameD4BH7q90HEn2KO9cEoCoI6t1HEnWK9BmMAC/74jXcSRZb1I35fXo+rjMQeJy5zm6h44jyXoOf20D9HM7Donbcrc7kTqOJOs1r1oQAFfTCjqOJOu1j3gI6OcxHSQe1+njMXnC8bg+7qck7KPo+zGrPm/r9l+P1XEkWa9jLeUpFH3MDRLz0+ffZ/VxHyxh/0uIj4mc0BZCCCGEEEIIIYQQQgghhBBCCC0ZGMqFBTlJuhwXQgghhBBCCCGEEEIIIYQQQgiRK8kJbSGEEEIIIYQQQgghhBBCCCGEELmSdDkuhBBCCCGEEEIIIYQQQgghhBBaMjCUe4ZzknzbQgghhBBCCCGEEEIIIYQQQgghciU5oS2EEEIIIYQQQgghhBBCCCGEECJXkhPaeczAgQMJDAzUdRhCCCGEEEIIIYQQQgghhBBCfJQMjQxy7UsfyTO0c5CNjQ2//PIL7dq1o1ixYgQGBnLr1i1mzpzJxYsXdR2e3pkxYwadO3emZs2aug4lx1w+sZHzh1YSGuSLrb0Ln/WeRqlydVJt7/HoMoc3z+Ht66eYW9nSsN1X1G3eS63N/auHObFrCYG+Lyls40jLrmOpWLu16vMzB5bz4NpR/LyfYZyvACVdatK6+wSKlnDK8tzOHVxJWJAvNvYutOuTTm4PL3No8xx8Xz/FvHDauQW8fUkR25S5AYQE+nB063ye3DlNbMw7rIuV5osh/4dd6SpZmp82ThzcyqHd6wkK9MO+pBO9h06kXCXN9R0U4MuWNYvwcH/IW++XtOzQiz5DJ+ZwxB+mSKM6OE0YimWtKhSws+Vqt6/x2Xtc12GloFAoOLX3L66d2kpURAj2TtVo3/cnbO3Lpjnc/auHcduduGy16DqWirXU6+/KiY2cP5y4TLftlXrd71v3E9dPbaVtr6nUbz0wy/JLj+v+PezesYXAAH9KlirN0OHfULlKNY1tL5w7zaED+3j+7CkxMTE4lipNr74DqVm7bo7Fm5azRzbjtn81IUG+FHdwofOAyThXqJ1q+6f3r7BnwzzeeD7ForAtLToOpmHrnmptIsNDOLBlCbevHCMyPIQiNvZ80e97KtVskq25KBQKTu5Rr8sO/bSry7TW+ZD+tub+tSNcO7kFrxf3iAwLYsTMXZRwrJgteabGdf8edu3YSmCAP46lSjN0+Ndp1OUZDh7Yy/Nn7u/rshS9+g6kltRltjt9eDPH964hJMiXEg7OdB00GZeKqef25P4Vdq2dh7enO5aFbWjVaQiN2nyp1sbtwHrOHtlKoJ83hSysqFGvNZ36jMUkX/7sTiddrvv3sHPHNlVdfjX8aypXqaqx7flzZzh4YJ9aXfbuOyDX1GVyW05fZ83xS/iFhOFcoiiTurailktJjW2vPHnBV0s2pXh/9w/DKFPcOrtDzRSFQsGN4//j0ZWtvIsMwaZkNRp0mk7hYqmvUwN9nnD92J/4vb5HWJAX9TpMoUrDnNs+p+ZjWu4KNW6DecsvMLK0Isbbk6Adq4l2f5hq+4J1GmHe6guMbUugiIwg6sFNgnetIz48LAejVvrYt+MnD23h6N61BAf6YVfSmR6DvqdspVoa2wYH+rJ97QJePnvAW++XNG/fmy8HT8rReLNC4YZ1cBo3FMualSlQwpZrPb/BZ1/uO/bJjLxyXJcefT4e1+d9FNCvY9bk8vK2LrlzRzZxMslxzxcDpuCUxnGP+/0r7N3wu+q4p3nHITTQcNzjumUxd1THPQ506vc9FXP4uEefctPF77NxcbGc3P0Xty/uIyzYD3MrG2o07EKTz0dhmMXPL9bVPlhcbAwndi3mye1TBPp6kr+gGU6VGtCq+3gsChfL0hyFyMvkDu0ctGPHDqpXr87AgQMpV64cnTp14uTJkxQpUkTXoWU7Y2O5diK5rP5O7l525dCm2TTuOJKRM3fhWLYOGxYNJ8jfS2P7QF9P/ls0AseydRg5cxeNO47g4MZfuX/1sKrNq6c32LZsPNUbdGLkrD1Ub9CJbcvG4el+S9XG49EV6rbow1c/bmHAhFXEx8WyfuFXRL+LyLrcLrlyaONsmnQcychZuyhVrg4bFqad24ZFIyhVrg4jZ+2icYcRHPxPQ25Lx1Pt006M+nkP1T7txNal6rlFhgez8tfeGBob02/8v3zz637a9ppMAVOLLMtNW5fPHmHTqgV07D6EmQs2UrZSTRb98i3+vt4a28fGxmBuUZiO3YdQsnS5HI42axgVMiXk9iPujflZ16Gk6dzBFVw4sob2facz7MdtmFnYsH7BEN5Fpn5A+OrpDbYvV9bfyJnK+tu+bByezxLr7+5lVw5tnk3jDiMZMUO5TP/3x3CCNdT9w+vHeP3sNuZWttmSY2rOnnJj1T//o0fPviz88x8qVa7KLz9Nwfetj8b29+7epnrN2kz/eTYLliyjSrUa/DrrB565P8nRuDW5ceEgu9fNoXXnYUycvQ2n8rX4Z85IAv00L2P+bz359/evcSpfi4mzt9H6i6/YtXY2ty4dVbWJjY1h6W/DCPB9zaCxC5m6YD89h83Cskj2zydVXfabzrDp2zCztGHd/PTrMr11vjbbmph3kZQsW4tW3Sdka46pOXPKjZX//E2Pnn1Y9OdyKlWuys8/TU2zLmvUrM1PP//GwiVLqVqtBr/O+lHqMptdO3+InWvm0rbrMCbP3YZzxdos/W0UAank5vfWk2Wzv8G5Ym0mz91Gmy7D2L56NjcvJuZ25cx+9m78g3Y9RvLDoj30Gfkz1y8cZu/GP3Ioq9SdOeXGin+W8mXPPvzx5zIqVa7KrDTr8g41atZmxs+/smjJ31StVoP/mzUd91xQl8kduvaA33ceY1jbBmyZPJhaziX5eulWvAOC0xxuz/ThHP91tOrlaFs4hyLOuNunV3D33Bo+/fxHOn29lYJmRTm0aijR78JTHSY2JgrzIiWp03Y8Bc2L5mC0qfuYlruCtRpg1W0wIYd34DNnEu/cH1D06x8wKqx5XuRzqkCRAd8SceEEPr+Ox3/lQvI5OlO4z6gcjlzpY96OXz13mG1r5tGu61f8MG8zLhVr8tdv3xCQynFPTEw0ZhaFadf1KxxK5c3jHgDjQgUJvfOQe+N/0XUoWS6vHNelRZ+Px/V5HwX065g1uby+rUvqxoWD7Fk3h5adhzN+9nbKlK/Fv3NGEOin+Xc//7eerPh9FGXK12L87O20/GIYu9f+xu1LR1RtYmOjWf7bVwT6ejFw7CImLzhAj2Ezc/y4R59y09Xvs2ddV3D1/9m776gorjaAwz+asdGkCFIFVLAgghp7i11jNxp7i2CaMbaoMbYvscQSTWKJsfeKRsGGYsfeFRuKgiLSO9L2+2NlYWGBVYGF9T7n7Dk63Jl53507M/fO7Nw5uZ0ug6bz7W9etOs7gXOH13DRZ3Oh56iqNlhqSjIhz+7R4vOvcZ+xh37f/klEaCDbln1d6DkKQmkmbmgXE319fZo3b87kyZM5efIkz58/5/Lly8ybNw9vb29ZuXHjxnHr1i3i4+N5/vw5f//9NxUqVMh32V27duXKlSskJSUREBDAL7/8gpaWluzvM2bM4NmzZyQnJ/PixQuWLl2a57JmzJjB9evXGT16NM+fPychIYGdO3eir68vV27YsGHcu3ePpKQk/P39GTMmq/FjY2ODRCKhb9+++Pr6kpSUxKBBg/L8XlatWsWrV69ISkri9u3bdOnSRS6W7MaOHcvTp09l/2/ZsiUXL14kPj6eqKgozp49i7W1NUOHDmXmzJm4uLggkUiQSCQMHSp9IsLKyop9+/YRFxdHTEwMO3bswNQ064Sfud7hw4fz7Nkz4uLiWL58OZqamkycOJGQkBBCQ0OZOnWqXGx6enqsWrWK0NBQYmJiOH78OM7OzgqXGxAQwJs3b/LcDu/D78h6XJv3xq1FX0yq2NNpwFT0K5lxxTf3EzAAV05uR9/InE4DpmJSxR63Fn2p17wX54+slZW5cGwj9jWb0LyLOybmdjTv4k5Vp0ZcOLZBVmbwj/9Sr1kvTC2qYWbtSI8Rc4mJeMnLwLuFltv5o+up16I3bi2zctOrZMblE4pzu+ybI7eW0tzOHc7Kze/oRuxqNaFFV2luLbq6Y+fUCL9suZ31/he9Sub0HDkXSztnDI0tsavZmEqm1oWWm7KO/LeZ5p91p0W7nlSxqsqAkROoZFQZ38O7FZY3Nq3CgFETadq6K+XKVyzmaAtH2JHTPJzxB6/2HSu4sIpIJBIu+mykeRcPnNzaY2pZnR4j55GaksztiwfznO+iT9a+ZZxt37qYrf5dOLqees174/p2n+74pXSfvnxSvt7HRoXivXUOvb76HU2t4v3x0H7PXbRt34l2HbtgZW3DKPdvMTYx5bDXfwrLj3L/ll59+1OtuiNVLCwZPGwU5lUsuHzRr1jjVuSk10Y+bd2LRm36UNnCnp5Df8LAyIxzx7YrLH/eZycGRmb0HPoTlS3sadSmDw1b9cTXa72szEXfvSTGxzBy/DLsarhSyaQKdo6uWNg4FmkuEomEC8c20qKrBzXd2lPZsjo9laiXyhzzlTnX1G3SnVbdvsGuZuMizTMv+z1307Z9J9rL6uU3GJuYcsjrgMLyo9y/UVgvL4l6WaR8D26kcZteNPmsN2aWdvQeNhlDYzPOHt2hsPy5ozsxNDaj97DJmFna0eSz3jRq3ZPjB9bLyjx9eBO7GvWo36wLRqYWONVtglvTTjx/cq+Yssrbfs89tG3fkfYdO2NlbcNX7l9jbGKKdx718iv3r+ndt5+sXg4ZNvLt8bLkjeq0yfcSPRvXpVeTutiZGTOpd1vMDPXYefZ6vvNVqlgeY72Kso9WIT9dUVgkEgl3z2+kbit3bGu3p5JZdVr2nUdaajJPbuR9TDWxrEPDThOxr9sFLa0yxRhx3j6m/U63TVcS/E6Q6HeCtNAXxOxZT3pUOBWat1dYvkzVaqRHvCb+1CHSI16T8uQ+8eeOoWNduKNOKeNjP4/7HNhE0zY9ada2F+aWdnwxfBKGRmacOrpLYXljUwv6jZhMo1afU7aU9nsAwo6e4eGspYTuL7l9n/dVGvp1BVHn/rg6t1FAvfqsOZXmc11Op7020LB1b1m/p8fQKRgYmXP+mOI2ip/PDgyMzOkxdEq2fk8vTmbr91zy9SQxPpbh45dRVdbvcaNKMfd71Ck3VV2fDQ64To16n1G9bisMjS2p1aAj9rWa8jLwTqHmp8o2WNnyugyZsJbaDTthbG6Hlb0LnQf+TMizu3n+YEAoGTQ0NUrsRx2VzKsGaig+Pp64uDh69OhBmTJ5X9DIyMjg+++/p3bt2gwdOpQ2bdqwYMGCPMu3b9+ezZs3s2zZMmrWrIm7uzvDhg1j2rRpAPTu3Ztx48bh7u5OtWrV6NGjB7dv3843VgcHB7744gs+//xzOnbsiIuLC3///bfs76NGjeLXX39l2rRpODk5MXXqVObMmcOQIUPkljN//nyWLVuGk5MTR44cybkaNDQ0OHToEE2aNGHQoEHUrFmTn376ifT09Hzjy6SlpcW+ffs4deoUzs7ONG7cmH/++QeJRMKOHTtYuHAhd+7cwczMDDMzM3bskDYU9u3bR6VKlWjZsiXt2rXD3t5e9rdM9vb2dOrUiY4dO/Lll18yYsQIvLy8sLS0pGXLlkyePJlff/2VTz/9VDaPl5cXZmZmdO7cGTc3N65du8bx48cxNMx62iTzu+3duzcuLi5K5amMtLQUXj67i32tpvJ51GpK0GPFFxODAm7kKu9QqxkvA++SnpaaVaZ2jjK1mxEUcCPPWJKT4gAoV0E/zzLvIi0thZDAuzgoyi1AcW7BinKrLZ+bojL2tZsR9PiG7P8PbpygStXa7Ph7LAu+b8KKGT25cmpnIWT1btJSU3kWcJ9aLo3kptdyacTj+7eKPR4hS3R4MPExYXJ1SVunDLY1GhCcR/0E6b5ll6tOZ9W/9Dz2abuaTQnOtk9LMjLw/HcSTTqMLHD4o8KWmppKwOOHuLjKDy3lUq8+9/2V+0FLRkYGSUlJVNTVLYoQlZaWlkrw03vUcG4iN72GcxMCH95UOE/go5u5yjvWbUrQk6zjzN1rJ7GtVpfd635lunsL5k/swbF9/5CRodx57n1FheVdL/M6J0DBx/z3OdcUt7zrpds710td3eIfjSM7dauX2aWlpRL05B6OdXPE6tyEpw9uKJzn6aObOObIzcmlKc+f3JPlZu/oStCTewQ+lrZ1w0ODuHf9DLVcmxd+Eu8gNTWVx48fUi9HvaxXz437/srd9JPWy0SVHy9zSk1Lxz/oFY0dbeWmN3a05ebTF/nO22/+Oj6b9idf/bmNSw+fFWGUHyYuKpikuHAsqmUd+7S0y2BWtQGhz0vGsU8ZH9V+p6WNjpUdyf7yx8pk/1t8UrWGwllSnjxAy8CIsm+HD9bU1ae8S2OS714r8nBz+pjP42mpqTx/4o9TXfmb6U51G/HkgeJznyAUNXXuj6tzGwXUq8+aSyk/12WXlpaST7/nhsJ5nino99TI1e/xxaZaXfau+x8z3Fvw+8Tu+BR7v0d9clPl9Vnram48vedH+CvpQ26vnt/n+aNrVHcu3OHVS1obLDkxDjQ0VDJSqCCUVGIc6GKSnp7OsGHDWL16NR4eHly7do1Tp06xfft2uRvM2Z+eDgwMZPr06axYsYJvvvlG4XKnTZvGvHnz2LhxIwBPnz5l+vTpLFiwgNmzZ2Ntbc2rV6/w8fEhLS2NoKAgLl++nG+sZcuWZejQobx4Ib0I9d133+Hl5cX48eMJDQ1l+vTpjB8/Hk9PT1mcmTfTM+MA+OOPP2RlFGnbti0NGzbEycmJR48eyeJXlp6eHgYGBhw8eJAnT54AcP9+1nti4uPjSUtLIzQ0axihtm3b4uzsTNWqVQkODgZg8ODB3Lt3j/r163PlyhUANDU1GTFiBPHx8fj7++Pr60uNGjXo3LkzEomEhw8fMnnyZFq1asXFixdp3bo1derUwdTUlJSUFAAmTpxIjx496NOnD6tXrwagTJkyDB48mPDwcIU5lSlThk8+efd3zSXGRSHJSKeCvvx7ByvoGREfo3hd8TFhVNBrJl9e34iM9DQS46PQNTAlPiacCnqKlhmmcJkSiYQjO+ZhXc2NypaFM6xWYlwUGRnpueKoqG9E/J28c6uonyM3vdy5Vcy5zBy5Rb0O4sqJbTTuMIwWXd0JfnKLQ1t+RVu7DC5NexRKfsqIi4smIyMdfQP5ePUMjIiJjii2OITcMutLzrpUQc9I4dDgWfPlUf9ipcvL3KdzldE3IiBbvT97aDWamlp82nbwB+XxPuJiY8jIyMDAQH6IWH1DQ6KiIpVaxv69O3mTnEzT5q2KIELlJcRKjzO6OY6huvpGxOZxDI2LDldYPiM9jfi4aPQNTYh4HcyjsBe4Ne3C6MkrCHv1jD3rfiUjPZ0OvYtuWLfMeqTo+F1QvczvmP8+55riFptHvTR4h3q5b+8u3iQn0bR5y6IIUWnqVi+zyze3PM5rsdERBebm1rQT8bGR/DF9CBIgIz2NZu370b7HqKJKRSl51Ut9Q0Oi36leJtNMxfUyp6iERNIzJBjpyo8oZaRbgfBYxcNxm+hV5Jf+HalpbUZKWjoHL91h9F/bWPP9ANwcin8UnIIkxUn3t3IV5YfvLFfRiPjo0vO0xMe032lW1EVDS4uMuGi56Rlx0WjqGSicJ+XpQyI3LKPSiHFo6OigoaVN0q3LRO9cq7B8UfqYz+Pxb/t+evryr2XT0zciNrpkxCh8fNS5P67ObRRQrz5rTqX9XJddQqx0H6uon/v6R1we56fY6HBqKCifkZ5GQlw0em/7PY/DLuLatCujJq8g/NUz9q77HxnpabTvXTzDOKtTbqq8Ptus81ckJ8bx19TOaGhqIclIp02vH6jTqGshZfc23hLUBktNfYPP7kXU+bQrZcuV7JE+BKE4iRvaxWjv3r14eXnRvHlzGjduTMeOHZk0aRKjRo1iwwbpEBStWrVi6tSp1KxZEz09PbS1tSlXrhzly5cnMTH3O4nd3Nxo0KCB7IlskD65XK5cOcqVK8euXbv44YcfePLkCYcPH8bb25sDBw7k+xT08+fPZTezAfz8/NDS0qJGjRqkp6djbW3NmjVrZDdpQfo+6JgY+ffkZd4czouLiwvBwcGym9nvKioqinXr1nHkyBGOHTuGj48PO3fu5NWrV3nO4+TkRFBQkOxmNoC/vz9RUVE4OTnJYg4MDCQ+PuvdGKGhoaSnpyORSOSmZQ5V7ubmRsWKFYmIkO/MlCtXDnt7e9n/nz17lufNbIApU6Ywc+ZM5b4ABTTIMZSEBNDIe3gJjZx/k8j+kP8yc057y3vzHEKDHjBiylal4n0XOWOVSBTEJj9HXgvKc5nSubKmSSQSqtjWom2fHwEwt6lJ2MvHXPbdVqw3tLNHl51EIslv8wpF4NaFAxzcOEP2/wFjV0r/oaB+Frhxcs4jnZizUJ7LfRl4h4s+m3D/ZY/Culxsch1HJErFc/rkcbZv2cjUX+bkusCgKrmPd/nnkrN85jkicx5JRgYV9SrxxVcz0dTUwsquFrFRYZw4uK5Qbxze8jvAgWz1cuAPK+XikA86/22jzDH/Xc81qqCgWipZL0+8rZezRb0sBrnTkOR5+paWV7Bhs01/dPcyR/au5otRP2NbrQ5hr4LYs24ehw2M6djHo/ACf08K41eiXp46eYJtWzYx7ZdZJaZe5pSrnUbem9K2shG2lbMu5tStasGr6Fg2HL9UIm5oP75xgHP7Zsr+337ICiB3PtJ9q2Qd+5Txse13cjQ0ZPHnpG1miUHf4cQe2s0b/xto6hui32Mwhv1HE7V1RZGGJc7jueU+ppTO/U1QN+rbH1fnNgqgVn3WApXQc50yFPV78r2mqai89A/S/77t9/SV6/e8xvfgumK7oZ1vrKU0N1Vcn71zyZtbfgfo7b4Q0yoOvAq6z6Gtv6FnYIpLs57vFH92JbUNlp6Wyu6VPyKRSOgyeEauvwsli0YJfXWWuhI3tIvZmzdv8PHxwcfHhzlz5rB69WpmzZrFhg0bsLa2xtvbm5UrVzJ9+nQiIyNp1qwZa9euRUdHR+HyNDU1mTFjBnv37s31t+TkZIKDg6lRowbt2rWjbdu2LF++nIkTJ9KyZUvS0tKUijnzQqhEIkHz7Q761VdfcfHiRblyOW+SJyQofiojU1JSUr5/z8jIyHUCyfk9jBgxgmXLltGxY0f69evH//73P9q1a5crtkwaGhpyN6Xzmp6amir3d4lEonBa5vehqalJSEgIrVq1yrXs6Oho2b8L+k7mzp3L4sWL5abFxsbmOw9AeV1DNDS1cv2qKyEuItev3DJV1DfJXT42Ak0tbcpXMHhbxpj4WAXL1Jd/QgXAe8scHtw4wfCfNqNfyazAmJVVXtcQTUW5xUbk+mVbJmVzy/lryPjYCCpky62igQkmVRzkyhib23PvytH3Tee96OoaoKmpRUyOpxLiYiLRy+M7EIpGjbqtsZzhLPt/Wpp0RIb4mHB0DUxl0xPz2ffg7b6loI5W1JPWP9k+nXP/i81a7vNHV0mIi2DJpDayv0sy0jm6Yz4Xjm3ghwUn3jNL5ejq6aOpqZnrl/sx0dEFdvbPnvLlr6ULmTRlBnXruRVlmEqpoCc9zuR86jUuNhLdPLajroFxrvLxsZFoamlToaL0lQt6BiZoamujqaklK1PZwo646HDS0lLR1lZ8bn9XNVxaY2GXVS/T86iX2euPIgUd89/nXFPc9N7Wy6ioKLnpMdFRBdbLM6d8+XPpQiZP+QUXUS+LlCy3HE815Xde0zPI/XReXI7cDu74i4YtPqfJZ70BqGJdnZTkRLb9M5v2vUbL2m3FLatevvvxUlovFzF5yvQSUS9zMqxQHi1NDcJj4+WmR8YlYKRXIY+5cnO2tcDrsnJDfxY1a6c2mFrlPqYmxodTXi/rmJqcEEm5iiXj2KeMj2m/y4iPQ5Kejqaugdx0zYr6ZMTFKJxHt31P3gQ8IP7423eqvnxO9Js3mP44h5iD28iIjS6yeMV5PEvFt32/nE+9xsVEomdQMmIUPj7q3B9X5zYKqFefNafSdq7LTwU96T6W+xpd3v0ePQNF1/Qy2ygGb8uYoJWj32NqYf+235OCtnberwQtLOqUmyqvzx7d8TvNunxFnU+7AFDZqgbR4S854/XPB93QLoltsPS0VHatGEd0WDBDJ60XT2cLQg7i5wMqdu/ePSpUkF7sqV+/Ptra2owfP56LFy/y6NEjqlSpku/8165do0aNGgQEBOT6ZN6gTU5O5sCBA4wdO5ZWrVrRpEkT6tSpk+cyra2tMTc3l/2/cePGpKen8/DhQ16/fk1wcDB2dna51hcYGPhOud+6dQtLS0uqVVP83tewsDDMzORvjCp67/SNGzeYN28eTZs25c6dOwwYMACAlJQUtLS05Mreu3cPa2trLC0tZdOcnJwwMDDA39//neLP7tq1a5iZmZGWlpbre8n51HZ+UlJSiIuLk/soQ1u7DFVsahFw77zc9IC757FyqKdwHit7FwLu5ix/jiq2tdB6ezFbYZk757Cyd5H9XyKR4LV5Nv5XjzF00noMTSwpTNraZTC3rZUrjif3zmNlrzg3S3sXnuT4Lh7nyM3S3oUnCvK3cnCR/d/aoZ7s/SyZIkIDMTDKf78sbNo6OtjYO3LvpvwPNe7evIiDo3MecwlF4ZNyFalU2Ub2ManiQEV9E7n6lp6WQuCDy1jmUT9Bum/lrKNPstU/rbf7dM46+uTeeSzf7tPOjbsxZuZ+PGZ4yj66BqY06TiSQT/+W0gZ501HRwd7h+rcuH5VbvqN61dxdKqV53ynTx5n2ZL5/DhxGvUbNsqzXHHS1tbBsmpNHt7yk5v+8LYfttXrKpzHtlpdHt6WL//g1nms7LKOM1VruBD+6jkZGRmyMq9DAtEzMCnUm4aflKuIUWUb2SezXmY/J6S9rZd5nROg4GP++5xriltmvbz5zvXyBMuWLGD8xKmiXhYDbW0drOxqcv9Wzlj9qFrDReE8VavV5UGO8vdvnsfarqYst9Q3Sbl+DKmhqfX2iQbFT6oUBx0dHRzyPF7WzHO+UydPsHTJ70yYOJUGJaRe5qSjrYWTlRkX7gfKTb/wIJC6VS2UXs794FCM3+EGeFEq80kF9IxsZB8DUwfK6Rrz8rH8uf7V08tUti4Zxz5lfFT7XXoaqUFPKJujnVzW0Zk3Tx8onEWjTJncT7RJ3h4ni/gRTHEez6Kto4O1nRP+Oeqd/62L2NVQfO4ThKKmzv1xdW6jgHr1WXMpZee6/Ghrl3nb75E/Pz28fR7b6i4K57GpVpeHt+XL5+731MvV7wmT9XuK/mY2qFduqrw+m5qShIaG/G0sDU1NJJIMPkRJa4Nl3syOeP2MIRPWUb5iKRkZQhCKkbihXUwqVarE8ePHGThwIHXq1MHW1pY+ffowadIk9u/fD0BAQAA6Ojp89913VK1alUGDBuHhkf8wbbNnz2bIkCHMmDGDmjVr4ujoyBdffMGcOXMAGDp0KCNGjKBWrVpUrVqVwYMHk5iYyLNnz/JcZnJyMhs2bMDZ2ZlmzZqxbNkydu7cKXsX9cyZM5kyZQrff/891apVo3bt2gwbNoxx48a903dy+vRpTp8+zZ49e2jbti22trZ07NiRDh06AHDy5ElMTEyYNGkSdnZ2fP3113Tq1Ek2v62tLb/99huNGjXC2tqadu3aUb16ddmN6cDAQKpWrUrdunUxMjKiTJky+Pj4cOvWLbZs2UK9evVo0KABGzdu5OTJk1y9elVhnMrw8fHBz8+Pffv20b59e2xsbGjcuDFz5szBza14fsnZuMMwrp3ezbUzewh7GcDhbXOJiQyhfqv+0hh3L2Lv6smy8vVb9Scm4iWHt88l7GUA187s4dqZPTTpMEJW5tN2gwm4e46z3qsJC3nCWe/VPPH3o1G7obIyXptny4Z9KVO2AnExYcTFhJGaklxouTVp/za309LcDm2bS0xECA1aS3M7tks+twat+xMd/pLD297mdnoP10/voWnHrNwavc3tjJc0tzNeq3lyz4/G2XJr3H4YwU9ucvrgSiJCn3HL7wBXT+6k4WcDCy03ZXXoNojTPvs447Ofl0FP2bZ2EZHhr2jVoQ8Auzf9yeqlv8jN8/zpA54/fUByciLxsVE8f/qAF0FPij3296VVoTx6dR3Rq+sIQPmqlujVdaSslXkBcxYfDQ0NPm07hDNeq/C/dozXwQ/Zt3YKOmXKUufTrHf5eP47GZ89i2T//7Rt1r4Vnm3f+jRb/WvUfhjXzuzmeuY+vf3tPt1SWu/LVzTE1LK63EdTS5uK+sYYm9kVS/7de/bF54g3PkcPEfT8GWv++ZvwsFA6dP4cgE3rVvPHwrmy8qdPHmfponkMGzWGGo41iYqMJCoykoSE+LxWUWxadRnCBd89XPTdS+iLADw3zicqPIQmbfsBcHDbErYsnyIr36TtF0SFh7Bv0wJCXwRw0XcvF3330rrLsKwy7fqRGB+N54Z5vA4J5O61U/jsW02z9v2LNBcNDQ0atRvCmYOr8L96jNDgh+xbk7te7l09GZ/d2eqlEsf8gs41AInx0YQ89yfsZQAAEa+eEvLcn7hs78AqSt179uFYtnr57z/LCQ97Tce39XLjun9ZsnCerPzpkyf4Y9E8ho/yEPWyGLXuOgS/43vwO+HJq+An7Fk/n8jwEJq1+wKA/7b+wca/psrKN23/BZHhIezdsIBXwU/wO+GJ34m9fPZ5Vm613Vpx9thOrp47RPjrYO7fOo/Xjr+oXb+V3NMLqtC9Z2+OHTnEsWz1MizsNZ3e1ssNOerlqZMn+GPRfEaMcqeGo1OJqpc5DW7dkL1+N/H0u8mTV+H8vseHkMhY+jaTXpxZ+t9Jpm08ICu/2fcyJ24+5NnrSB6HhLH0v5P43HhA/xYl7+knkB5TazUZws2T/xB49xiRrx5yevdUtHXKYueSdUw9tWsyl49kjbSUnpZCxEt/Il76k5GeSmLsayJe+hMbkXc/rKh9TPtd3ImDVGjyGeUbtUa7sgX6vYaiVcmYhDPSkZb0ug3AcPC3svLJt69SzqUhFZq1R8vIlDJ2NTDoM5yUwEdkxETltZoi8bGfx9t+Pphzxz05d3wfIcFP2Lnud6LCQ2jRXtrv8dyyjHXLfpabJ+jpfYKe3udNchJxMVEEPb3Py6CAYom3sGhVKI+usyO6ztK+TzkbS3SdHSlrWXL6Pu+rNPTrCqLO/XF1bqOAevVZcyrN57qcWnQZysVs/Z79G+cRFR5C47f9Hq9tS9iard/TuG0/osJD2L9pvqzfc8l3D62y9Xsav+337Nswl7CQQO5dO8Xxfatp2v5Lkdt7UtX12RourTlzcCUPb54kKjwY/6vH8DuyHkfXdoWanyrbYOnpaexcPpaXgXfo/dXvZEjSZdfYM0eHFEomDU2NEvtRR2LI8WISHx/PxYsXGTduHPb29ujo6BAUFMTq1av57bffALh58ybjxo1j8uTJzJ07l9OnTzNlyhQ2bdqU53KPHj1K165d+eWXX5g0aRKpqancv3+ff/+VPp0XHR3NTz/9xOLFi9HS0uL27dt8/vnnREZG5rnMx48fs3fvXry9valUqRLe3t58/XXW+zfWrFlDYmIiEydOZMGCBSQkJHD79m3++OOPd/5eevfuzcKFC9m2bRsVKlTg8ePH/PTTTwDcv3+fr7/+mqlTpzJ9+nT27NnDwoULGT16NACJiYk4OjoydOhQjIyMCAkJ4a+//mLVqlUA7Nmzh169euHr64uhoSHDhg1jw4YN9OjRgz///JPTp0+TkZHB4cOH+e6779459pw6d+7Mr7/+ytq1azExMeHVq1ecPn1a9kOAola7YWcS46M59d/fxMeEYWpRjYE/rMLAWPp0TFxMGDGRL2XlDU0sGThuFYe3zePyia3oGpjSacA0atbvICtj7eBKH49FnNi7lBOey6hkakUfj8VY2mf9Ov6K7zYA1s8fIhdP9xG/Ua9Zr8LJ7dPOJCZIc4vLzG1cVm7xMWHERMjnNuhtbpcycxuYI7dqWbn5ei7D0NSKvjlys7CrQ/9v/8Rn92JO7V+OgYklHQdMwbnx54WS17to2Kw98XHR/LdzNTFR4VhY2/PDz8swNpVeBIiJCicyTP798TN/HCD797MAfy6cPoyRiTm//3OwWGN/X/putWl8POv4V3Oh9AJr0Ma93Bo5Ja/Zil3TTqNIS03Ge/NskhJisLRzZvCPa/gk27BAMZEv5Z5esnJwpY/7Ik54LsV339t9y30xlnZZ9a92w84kxUdz6kC2fXpsVr0vCZq1bE1sXCw7tm4kKjISa1tbps+ai2ll6egakVGRhIW9lpU/cugg6enp/LN8Kf8sXyqb3rptB8b+ODnX8otTvcadSIiL4cjelcRGh2FuVY3Rk1dQyUQ6IkNsdDhR4SGy8kamlnw1aTn7Ni3g7NFt6Bua0nPoFOp+mtWhMjQyx2PKP+zbtIDfJ/dC39CUFp0G8Vm3kUWeT9NOo0hNScYre70cr6BeZmvgKnPML+hcA/Dgxgn2r826IbJ75Y8AtOz2Da17fPj5tiDNW7YmLi6WHVs3ERkZiY2tLb/Mmotp5coAREVFEK6gXq5avoxVy5fJprdp217UyyLk1qQjCXHRHN6zktioMMytHBgzZbkst5ioMLncjE0t8ZjyN3s3/M6ZI9vRMzSlz/ApuDTKyq1D79GgocHB7X8SE/mainqG1HZrSdcvvy/W3BTJqpebs9XL37LVS8XHy5XL/2Tl8j9l09u0bc8PP04q9vjz09HNiZiEJP45fI6w2AQczI35e0xfqlSSDkkdHhPPq6isV+ikpqezeN8JXsfE84mONvZmxvzl0ZfmtexVlUKBnFuMIj31Def/m01KUiwmls50GP4vZT7Jeqo8PjpE7smRxLgw9v2V1Ra+fWYtt8+sxaxqA7p8tbFY48/0Me13SdfOE12hInqd+qClZ0hqSBDhy38jPUo61KOWniHalbKGsky8eBKNsmWp2LIj+r2GIElKIPnBHWL2b1FJ/B/zebx+0w7Ex0XjtXsVsVHhVLF24Nupf2GUrZ5GZqunAL9OzLoh//zJPS6fPUQlE3N+W3GoyOMtLPqutWl0JOvYUHOBtL8TvMmTW+4lp+/zPkpLvy4/6twfV+c2CqhXnzWn0n6uy65e404kxkVzbO8KWb9n1OSV2fo9YUTn6PeMmrSC/Zvmc+5tv6fH0Kk4f9peVsbQyJzRU1azf9N8Fk7uib5hZZp3GkSbYu73qFNuqro+23ngz5zwXMbBTbNJiI1A18CU+q360bJ74b8vXFVtsNioVzy4IX114MqZPeRiGjppA1UdPy30XAUhpzFjxjBx4kTMzc25e/cuP/zwA2fPns2z/IABA5g0aRLVqlUjJiaGw4cPM2HChHzvPX4oDVQ5/p5Q4syYMYMePXpQr17JGHJMkA7pve2ceu6mXzaVnvy3n1e//Po3keZ27l7J+xVvYWhaU9qQ89KpoeJICl+XVOnwXFvPql+9HNBMWi/9A16oOJKi4WQv7Qh4X0tVcSSFr7OrdDgudTwfZJ4L7gcEqziSouFoL30VhzrXy6M31e8X4+3rSofqexAQpOJIikYNeysAko+uU3Ekha9s++EALNjzYUMQlkSTektvmKvjPgdZ+13wt31VHEnhs/xrF6Ce53HIOpf73k5ScSSFr3WdcgB4l3dUcSSFr3PifUA9+3SQ1a9Txz55Zn9cHdspmW0Ude+zqvO57uC1NBVHUvi6ukqfCVTH3CArP3W+PquObbAvm2rkevWPUPyejuym6hDyVHXNf0qX/eKLL9i0aRNff/01586dw93dnVGjRlGzZk2CgnK3N5o2bcqpU6cYN24cBw4cwMLCgpUrV/Lo0SN69SqchxwVEUOOC4IgCIIgCIIgCIIgCIIgCIIgCIIgKEnVw4oX1pDjP/74I2vWrGHNmjXcv3+fcePGERQUxJgxYxSWb9SoEYGBgfz5558EBgZy7tw5Vq1aRf369Qvja82TuKEtCIIgCIIgCIIgCIIgCIIgCIIgCIKgBsqUKYOurq7cp0yZMrnK6ejo4ObmxtGjR+WmHz16lCZNmihc9vnz57G0tKRTp04AmJqa0qdPH7y8vAo/kWzEDW1BzqxZs8Rw44IgCIIgCIIgCIIgCIIgCIIgCIJQCk2ZMoXY2Fi5z5QpU3KVMzY2Rltbm9DQULnpoaGhmJmZKVy2n58fAwcOZMeOHaSkpBAaGkp0dDTfffddkeSSSdzQFgRBEARBEARBEARBEARBEARBEARBUJKGpmaJ/cydOxc9PT25z9y5c/PMRSKRf9e8hoZGrmmZnJycWLZsGbNnz8bNzY0OHTpQtWpVVq5cWajfb07aRbp0QRAEQRAEQRAEQRAEQRAEQRAEQRAEoVikpKSQkpJSYLnw8HDS0tJyPY1tamqa66ntTFOmTOHcuXMsXLgQgNu3b5OQkMDZs2f5+eefefXq1YcnoIB4QlsQBEEQBEEQBEEQBEEQBEEQBEEQBOEjkpqaytWrV2nXrp3c9Hbt2nH+/HmF85QvX56MjAy5aenp6YD0ye6iIp7QFgRBEARBEARBEARBEARBEARBEARBUJKGZtHdvC1OixcvZtOmTVy5cgU/Pz9Gjx6NtbW1bAjx3377DQsLC4YOHQrAgQMHWL16NR4eHhw5cgRzc3P++OMPLl68SEhISJHFqQEoHgRdEIQSIa/3FAiCIAiCIAiCIAiCIAiCIAiC8PEpyidhBeU8H9NL1SHkyXrF3ncqP2bMGCZNmoS5uTl37txh3LhxnDlzBoB169Zha2tL69atZeW//fZbPDw8qFq1KtHR0Zw4cYLJkyfz8uXLQs0jO3FDWxBKOHFDWxAEQRAEQRAEQRAEQRAEQRCETOKGtuqp0w3t0kAMOS4IpUDs1SOqDqFI6Ll1AKDnt49UHEnh8/yrGgBbz6rnDxIGNJM2mNQxv8zcvHRqqDiSwtcl9QEA286p33YD+LKpdNupY36ZuW0/r3659W+ivtsNPo56KXIrfdQ5P5Fb6aXO+alzbqDe+WXmps79HnXMDdQ7v8zc1HmfU8fcQL3z+xhyU8f+OKh3nzxz2/13JV3FkRS+bvW1VB2CAGhoaqo6hI+K+LYFQRAEQRAEQRAEQRAEQRAEQRAEQRCEEknc0BYEQRAEQRAEQRAEQRAEQRAEQRAEQRBKJDHkuCAIgiAIgiAIgiAIgiAIgiAIgiAIgrLEe8yLlXhCWxAEQRAEQRAEQRAEQRAEQRAEQRAEQSiRxA1tQRAEQRAEQRAEQRAEQRAEQRAEQRAEoUQSN7SFdzZ06FCioqLeaR6JREL37t0BsLGxQSKRULdu3aIIr8j5+vqyZMmSQi8rCIIgCIIgCIIgCIIgCIIgCIIglHwamhol9qOOxDu0S5h169ZhYGBAz54933neoUOH8scff2BoaFgEkRWeoKAgzMzMCA8PV3Uo76VXr16kpqaqOoz3tuvYGTYfPE54dCx2Fmb8OKQ39RztC5zv5oMnuM9Zhp2VOVvnTi6GSN9fv86VaN9UnwrlNHn0LJl/doQR9CpFqXmbuVVk/HBzLt6MZ97qkCKONItEIuHUf39x9dROkhNjsbBzpvPAXzC1qJbvfPeuHMF33zKiwp5jaGJNm14/4OTaTq7M5RNbOX9kDXHRYZhaONCh/1RsqtdXuLwDG3/h2qmddOg/hUbthorcilClZvWxGz8SfdfalK1iypXeXxP633FVhyXn0omtnD+c9f12/DLv7xcg8MEljmyfx+sXj9E1MKVpp1E0aN1frsy9K0c44Zm1XT/r9QNOblnb9YzXKvyvHiM85AnaZcpi5VCPdn3GY2xuV+pzC3xwmfOH1/Ay8C7xMWH0+/YvnFzbFmpe2fM7d2gN8dFhmFg40GlAAfndv8Th7fMIe/EYXcP884t8/ZxKprnzu3RiG1d8txEd/gIAEwsHWnX7hmrOLQo9N3XdduqcG0jPByf3y58PugxS7nyQXw5Q8Hd37+pRrp7cwctnd0mKj8Z9pifm1k6Flps6bTtVbqeC1h0VHszSSYpz7DvmD2o16JhvjKrYTu+63gMbfuHq2/ZK4/Yf1l5R531Olfmlp6VywnMpj26dIiosmE/KVcSuZhPa9vkRPcPKIrcSkouy675ycge3Lx4k5Nk9UpITmPzXJcqV13uvXDPXqa59H3XOTd3zU6d2SknIrbj6rKBe54OPKTfRH8+WWyk6nihy/tg2TnqtJS46jMoWDnQb/BN2jnnnG+B/mQOb5xP64jF6Bqa06jqCxm2z8r18ypOd/0zLNd9v666jU+aTIslBENSJeEJbKHYZGRmEhoaSnp5eZOvQ1i7832pkLjMqKor4+PhCX35xOOp3jcUb9zK8R3s2/zYJF0d7xs5fwavwyHzni09MYsaKTTSoVb2YIn1/Pdsa0q21Aat3vmbS70FExaYz8zsLyn5S8K+STAy1GdrDmLuPk4ohUnnnDv2L39H1dB44na9+3kVFPRM2LRrBm6S861rQ4+vsXvUjzo274TFzP86Nu7F75TiCn9yUlblzyZvD2+fSvIsH7jM8sa5Wny1/jCYm4mWu5d2/5sOLJ7fQNTAVuRUDrQrlib31gLtjZ6s6FIXuXPLm8La5NO/qgcdM6fe7ecloohV8vwBRYcFsWeKOdbX6eMz0pHlXdw5t/ZV7V47IygQ9vs6ulT9St0k3PGbtp26TbuxaOY7ggKztGvjgMg3aDGDUzzsYMn4tGelpbFo8ipQ3iaU+t9Q3SVS2cqTzoOmFlovC/C56c3jrXFp09cBjlic21euzeXH++W1e4o5N9fp4zPKkeRd3Dm1RkN8K6T45ZrZ0n9y5Qj4//UqVadtnPKNn7Gb0jN1UdWrEtmXf8PrFo8LLTY23nTrnlkl2Phg0na+m76KivgkbFxZ8PigoB2W+u9Q3SVhVc6Vtn/GFnpe6bTtVbqeC1q1fyZzxS87IfVr1+A6dT8rjUKd5vnmpaju9y3r9r/kQXIjtFXXd51SdX2pKMiHP7tHi869xn7GHft/+SURoINuWfS1yK0G5KLvu1JRkHGo3p3kX9/fOUWG+atj3Uefc1Dk/dWunlITciqPPmkmdzgcfS26iPy6fW2k5nihyw+8Q/22ay2fd3fnh1z1UdXRjzQJ3osIV5xv5Opg1v3tQ1dGNH37dQ5vuo9m/8TduXToqV65suYpM//uU3EfczBYE5Ygb2qXIuHHjuHXrFvHx8Tx//py///6bChUqANCyZUvWr1+PgYEBEokEiUTCjBkzANDR0WH+/PkEBwcTHx/PhQsXaNmypdLrHTp0KM+ePSMhIYG9e/diZGSUq0zXrl25cuUKSUlJBAQE8Msvv6ClpaVwedmHHNfQ0CAoKAh3d/nOY7169ZBIJFStWhUAPT09Vq1aRWhoKDExMRw/fhxnZ2dZ+RkzZnD9+nWGDx9OQEAAb968YciQIYSHh1OmTBm5Ze/evZsNGzYUmLeiZULuYcTHjBnDw4cPSUpK4tWrV+zatSvPZXbo0IHo6GgGDx5c4PqLwlZvX7q3akSP1k2oamHG+CG9qWxkyG6fs/nO99u/O+jQpD51qtkWT6AfoGtrA3YfieLCzQSeh6SwbFMon+ho0KK+br7zaWrAuGFmbPeOJDS8eJ/Al0gkXPTZSPMuHji5tcfUsjo9Rs4jNSWZ2xcP5jnfRZ+N2NdsQvMu7hib29G8iztVnRpx8VhW/b5wdD31mvfGtUVfTKrY0/HLqehXMuPyyW1yy4qNCsV76xx6ffU7mlqF94MQdc7tQ4UdOc3DGX/wat8xVYeikN+R9bg2743b2++30wDp93vFd5vC8ldObkffyJxOA6ZiUsUetxZ9qde8F+ePrJWVuXAsa7uaZNuuF7Jt18E//ku9Zr0wtaiGmbUjPUbMJSbiJS8D75b63Ko5t+CzXj9Q0619oeWiyPmj66nXojduLbPy06tkxuUTivO77Jsjv5bS/M4dzsrP7+hG7Go1oUVXaX4turpj59QIv2z51XBpQ/W6LTE2q4qxWVXa9h5HmbLlCcrWEf1Q6rzt1Dk3kJ4PLhzbSIuuHtR0a09ly+r0VOJ8oEwOynx3dZt0p1W3b7Cr2bjQc1OnbafK7aTMujU1tdDVN5H73L/mQ+0GnfikbIV8c1PVdlJ2vbFRoXhvmUPv0YXTXlHnfU7V+ZUtr8uQCWup3bATxuZ2WNm70Hngz4Q8u5vnBd2PNbeSfkwBaNx+KM27jMbS/sNfiabOfR91zk3d81OndkpJya04+qygXueDjyk30R/PUpqOJ4qcPrSeBq1682nrPlS2sKf74CkYGJnj57NdYXm/4zswNDKn++ApVLaw59PWfWjQshenvNbJF9TQQM/ARO4jlF4ampol9qOO1DMrNZWRkcH3339P7dq1GTp0KG3atGHBggUAnD9/nrFjxxITE4OZmRlmZmYsXLgQkA5j3rRpU/r374+zszO7du3i8OHDODg4FLjOhg0bsnbtWpYvX46Liwu+vr78/PPPcmXat2/P5s2bWbZsGTVr1sTd3Z1hw4YxbVru4TNykkgkbN++nYEDB8pNHzBgAOfPn+fp06cAeHl5YWZmRufOnXFzc+PatWscP35cbnh1BwcHvvjiC3r37o2Liws7d+5ES0uLbt26ycoYGRnRtWtX1q3LcSLJQ85l5uTm5sayZcv45ZdfqFGjBh07duT06dMKl9WvXz927tzJkCFD2LRpk1LrL0ypaWncfxrEp86OctM/rePIrYdP85zvv5MXCH4dzle98x/CsSSobKRNJX1tbtzP+lVsWpqEu4+TcLQrl++8X3SqREx8Osf9Yos6zFyiw4OJjwnDvlZT2TRtnTLY1mhAcMD1POcLCriBXbZ5AOxrNSPo8Q0A0tNSePnsrtxyAexqNiX4cdZyJRkZeP47iSYdRhY4tNO7Uufc1FlaHt+vfa2mBD1WvN2CAm7kKu9QqxkvA++SnpaaVaZ2jjK1mxEUcCPPWJKT4gAoV0H/XdNQqCTlVhTS0lIICbyLg6L88tjnghXlV1s+P0Vl7Gtn7ZM5ZWSkc/uiFylvErGyd3m/ZHJQ522nzrlligrL+3yQV45QcA7v890VJnXbdqrcTu+z7peBd3j13J96LXrnm5eqtpOy683IyGDv6kk07Vh47RV13ecylbT8khPjQEODsh8wVHUmdcqttB1TPpQ6933UOTdQ3/zUrZ2SXUnKrbD7rJnU6XyQk7rmJvrj8krL8USRtLQUXjy9R/U68rFVr9OEZ49uKJzn2aMbVK/TRL68czOCn2blC5CSnMiv33/G/75tzdrfx/Ai8F6hxy8I6krc0C5Fli5dysmTJwkMDMTX15fp06fzxRdfAJCamkpMTAwSiYTQ0FBCQ0NJSEjAzs6OL7/8kr59+3L27FmePHnCokWLOHv2LMOHDy9wnWPHjuXIkSPMnz+fR48e8eeff3LkyBG5MtOmTWPevHls3LiRp0+f4uPjw/Tp03M9dZ2XLVu20LRpU6ytrQHQ0NCgf//+bN68GYDWrVtTp04d+vbty9WrV3n8+DETJ04kOjqaPn36yJZTpkwZBg8ezI0bN7h9+zbJycls3bpVLs+BAwcSHBzMyZMnlYot5zJzsra2JiEhgYMHD/L8+XNu3LjBn3/+mavcmDFjWLlyJd27d+e///7Ld326urpyn8ISHZdAekYGlfTll2mkr0tETJzCeZ6HvObv7QeY880QtPN44r4kMdCT/oo5Oi5Nbnp0XDoGennH72hXls8a67F8a2iRxpeX+JgwACrqyY9+UEHPiPiYvN81Hx8TnmueinpGxMdKl5cYF4UkIz13GX355Z49tBpNTS0+bVv4Iweoc27qLPP7raCv/HaLjwmjQs7trG9ERnoaifFRb8uE5y6jZySrJzlJJBKO7JiHdTU3KlsWzisPSkpuRSUxLoqMjPRcseTcN7KLjwmjooLvI2d+CvfJHPmFBj3gVw9X5nzlzMENM+n/7V+YWhT8AzplqPO2U+fcMmUevxXHk//5IL8c3ue7K0zqtu1UuZ3eZ93XzuzB2NweawfXfPNS1XZSdr3nDq1GU6tw2yvqus/J4ixB+aWmvsFn9yLqfNqVsuUqvnMuuWJUo9xK2zHlQ6lz30edc5PGqZ75qVs7JbuSkltR9Fll8arR+SBXjGqam+iPyystxxNFEuKiychIR1c/97aMyyPfuJjwXNtS922+CXHRAJhWseML918ZPv5vBnz7O9o6n/D3rEGEvQosijQEQe2UnLFXhQK1atWKqVOnUrNmTfT09NDW1qZcuXKUL1+exETF72lxdXVFU1OThw8fyk3/5JNPiIiIKHCdTk5OeHp6yk3z8/OjY8esp3Xd3Nxo0KCB3BPZWlpalCtXjnLlypGUlP/7iG/cuMH9+/f58ssvmT9/Pi1btsTU1JSdO3fKll+xYsVc8ZYrVw57e3vZ/589e0Z4uPwJZfXq1Vy+fJkqVarw8uVLhg8fzvr16wvMO79lZnfs2DGePXvGkydPOHz4MIcPH8bT01Mu5969e1O5cmWaNWvG5cuX813flClTmDlzptLxvQ8N5N8lLUGSY4pUekYGP/+9kdF9OmFjXnLeO5xdi/q6eHyZFduvK94ODSSRL6cBSHJMy1T2Ew1+GGLGim2viUvIKJpAc7h14QAHN86Q/X/A2JXSf2jk2DaS3NNyyTmPdGLOQnku92XgHS76bML9lz1oFLQuJahzbh+jnMcLCthuub5niewP+S9T4VEIvDfPITToASOmbFUq3neh6tyKWs54JRIF8cnPkdeC8lymdC75aUbmVfGY5UlyYiz3rhzF89+fGP7TpkLrRCtapzptO3XK7ZbfAQ5kOx8M/GHl29AUrLuAY7QyObzrd1fYSuu2K4nbSdl1p6Ykc/vCQVp+PibfuN51/fnG8p7bKb/1vgy8w4Vjm3Cf8WHtlZK4LQtTSc0vPS2V3St/RCKR0GXwjFx/V4Y65VYSc3mfdStLnfs+6pwbqH9+uUIspe0UZag6t8Lss5bEYyiIc937EP3xbOVL0fFEoVzxS8gvtlzX3TMvSL+dbFOtLjbV6sr+blvdlT+m9ebckS30GDoNofTR0CwhdfUjIW5olxLW1tZ4e3uzcuVKpk+fTmRkJM2aNWPt2rXo6OjkOZ+mpiZpaWm4ubmRnp4u97f4+PgC16tMY1pTU5MZM2awd+/eXH9LTk4ucH6QPqU9YMAA5s+fz4ABAzhy5IjsBrampiYhISG0atUq13zR0dGyfyckJOT6+40bN7h58yZDhgzhyJEj1KlTh88//1ypmPJaZnbx8fG4urrSqlUr2rdvz+zZs5k5cyYNGjQgJiZGFoOrqyvDhw8v8Ib23LlzWbx4sdy02NjCGQLbQLcCWpqaRMTILy8yJj7XU9sAiUnJ+D95zsPAYH5fvxuAjLfvZ2806Af+nPI1DWoV7q9P39Wl2/E8DMyqYzra0vpqoKdNVGxWfdfX1SImLj3X/ABmxjpUNtZhqnsV2bTMar97qQPfznnGq0J+p3aNuq2xnJH1Dvi0tBRA+qtEXYOsG/SJcRG5foGZXUV941y/gkyIjaCinjEA5XUN0dDUIj5WURnpcp8/ukpCXARLJrWR/V2Skc7RHfO5cGwDPyw4IXL7CMm+35zbIJ/tVlHfROE209TSpnwFg7dljHNvs7gIKuob51qe95Y5PLhxguE/bUa/ktkHZCOvJORWlMrrGqKpKL/YiFy/pM6kbH45f4UcHxtBhRz5aWuXwaiyDQAWVeu8vVGzkW7DZn9IWoB6bzt1zK2GS2ss7LLOB+l5nA+yH7cVKSiH9/nuClNp33YlaTtV1DN5p3Xfu3KE1JRk6jbpUWCeqtpOyqz32cO37ZWJitsr435Xrr1SkrZlUSiJ+aWnpbJrxTiiw4IZOmn9ez/VpU65laRc3vWY8j7Uue+jzrl9DPllKu3tlPyUhNwKu89ako6hWTGIc927EP1xeaXleKJIBV0DNDW1iIvO+b1H5npqO5Ouwu0UiaaWNhUqGiicR1NTEyu7OoS/elYocQuCuhNDjpcS9evXR1tbm/Hjx3Px4kUePXpElSpV5MqkpKSglWNY6OvXr6OtrY2pqSkBAQFyn9DQgodXvnfvHo0aNZKblvP/165do0aNGrmWHxAQkPUrpAJs3boVZ2dnXF1d6dOnD1u2bJFbvpmZGWlpabmWr8xT5v/++y/Dhw9nxIgR+Pj4EBwcrFRMykpPT+f48eNMnjwZZ2dnbG1tadMmqyMSEBBA69at6d69u8LhyLNLSUkhLi5O7lNYdLS1caxqxcXbD+SmX7pzH+fqVXOVr1CuLNvm/8TmuZNkn16fNcXG3JTNcydR296m0GJ7X8lvJLwKT5V9gl6lEBmTRl3H8rIy2lpQy6Ec958oHingRWgqY399xo/znss+l28ncOdREj/Oe054VOHezAb4pFxFKlW2kX1MqjhQUd+EJ/fOy8qkp6UQ+OAylvb18lyOlb2L3DwAT+6ew8rBBQAt7TJUsanFk7s5ytw7j6WDdLnOjbsxZuZ+PGZ4yj66BqY06TiSQT/+K3L7SGm//X4DcmyDgLvnsXJQvN2s7F0IuJuz/Dmq2NZCS1sn7zJ3zsm900kikeC1eTb+V48xdNJ6DE0sCyGjLKrMrThoa5fB3LZWrlie3DuPVR77nKWC/e1xjvws7V1y7W8B2fbJvEgkEtnFig+lzttOHXP7pFxFjCrbyD6Z54PsOaa9PR/klSMUnMP7fHeFqbRvu5K0nQxNLN9p3dfO7KaGS2sq6FUqME9VbSdl1lu3STfGzNqPx0xP2SezvTL4HdorJWlbFoWSll/mRfCI188YMmEd5SsaitxKWC7vekx5H+rc91Hn3D6G/DKV9nZKftSxz1qSjqEgznXvQ/TH5ZWW44ki2tplsKhak0d35GN7ePs8NtVcFM5jU82Fh7dzlj+HZdWsfHOSSCS8fH4fPUOTQolbENSduKFdAunr61O3bl25T1hYGDo6Onz33XdUrVqVQYMG4eHhITdfYGAgurq6tGnTBiMjI8qVK8ejR4/YvHkzGzdupGfPntja2lK/fn0mTZpEp06dCoxl2bJldOzYkYkTJ1KtWjW++eYbueHGAWbPns2QIUOYMWMGNWvWxNHRkS+++II5c+YonXNgYCDnzp1jzZo1aGtrs3//ftnffHx88PPzY9++fbRv3x4bGxsaN27MnDlzcHNzK3DZW7ZswcLCgq+++oq1a9cqHZMyunTpwnfffUfdunWxtrZmyJAhaGpq8uCB/E3jR48e0bp1a3r37s2SJUsKNYZ3MaBza/b7+vHfST+evnjF4k17eRUeRe/PmgHw1/b/mLF8EyD9hZiDVRW5TyW9ipQpo4ODVRXKlf1EZXnk56BvNH3aG/KpcwWszcvw3WAz3qRKOH0l68cB3w+uzKBu0l/TpaZJeB6SIvdJSMogKTmD5yEppCl+sLtQaWho8GnbIZzxWoX/tWO8Dn7IvrVT0ClTljqfdpWV8/x3Mj57Fsn+/2nbwQTcPcdZ79WEhzzhrPdqnvj78Wm7obIyjdoP49qZ3Vw/s4ewlwEc3j6XmMgQ6rfsD0D5ioaYWlaX+2hqaVNR3xhjMzuRWxHSqlAevbqO6NV1BKB8VUv06jpS1spcxZFJNe4wjGund3Mt8/vd9vb7bSX9fn12L2Lv6smy8vVb9Scm4iWHt88l7GUA187s4dqZPTTpMEJW5tN2Wds1LNt2bZRtu3ptns0tvwP0dl9ImbIViIsJIy4mjNQU5Ub8KMm5vUlOIOS5PyHP/QGIDg8m5Lk/0REvCy03gCbt3+Z3WprfoW1ziYkIoUFraX7Hdsnn16B1f6LDX3J429v8Tu/h+uk9NO2YlV+jt/md8ZLmd8ZrNU/u+dE4W34+uxfz7OEVosKDCQ16gM+eJQTev4RzY+VHRimIOm87dc4NpOeDRu2GcObgKvyvHiM0+CH71uQ+H+xdPRmf3dnOB0rkUNB3B5AYH03Ic3/CXgYAEPHqKSHP/YkrhHezqdO2U+V2UnbdABGhz3j28AquLfoqnZuqtlNB6y1f0ZDKltXlPrL2ivn7t1fUeZ9TdX7p6WnsXD6Wl4F36P3V72RI0mXtlbRCuGisTrmVhmNKXEwYIc/9iXz9HIDXwQ8Jee5PYnz0e+Wrrn0fdc5N3fNTp3ZKScmtOPqsoF7ng48pN9EfL53HE0VadBrGJd/dXDq5h9AXAfy3aR7RESE0/qwfAN7bF7NtxU9Z389n/YiKCOG/zfMJfRHApZN7uHxyDy27DJeVObrnbx7cOkvE6yBeBPqza/XPvHx2n0ZvlymUPhqamiX2o47EkOMlUOvWrblx44bctPXr1zNu3DgmT57M3LlzOX36NFOmTGHTpk2yMn5+fqxYsYIdO3ZgbGzMzJkzmTVrFsOHD+fnn39m0aJFWFhYEBERgZ+fH97e3gXGcvHiRUaNGsWsWbOYOXMmPj4+/O9//2P69OmyMkePHqVr16788ssvTJo0idTUVO7fv8+//77bL0m3bNnC8uXL2bBhQ66hyjt37syvv/7K2rVrMTEx4dWrV5w+fVqpp8zj4uLYs2cPXbp0Yd++fe8UU0Gio6Pp1asXM2fOpGzZsjx69Igvv/ySe/fu5Sr78OFD2rRpw8mTJ0lPT2fChAmFGosy2jd2JSY+gX/3HiE8OgZ7S3P+mOSBuYn0yZbw6FheRUQVe1yFydMnijJlNBjdz5SK5TV5FJjMrL9ekPwma7QAk0raeb5TW1WadhpFWmoy3ptnk5QQg6WdM4N/XMMn2YY8iol8KfcaACsHV/q4L+KE51J89y2jkqkVfdwXY2mX9S6W2g07kxQfzakDfxMfE4apRTUGjl2FgbGFyE3F9N1q0/h41jG85sKpAARt3MutkVNUFZZM7YadSYyP5tR/2b7fH7K+37iYMGIiszoPhiaWDBy3isPb5nH5xFZ0DUzpNGAaNet3kJWxdnClj8ciTuxdygnPt9vVYzGW9lnb9YrvNgDWzx8iF0/3Eb9Rr1mvUp3by8A7bFiQ1Sk7sn0eAHWb9qDnyHmFkhtA7U87k5ggzS8uM79xWfnFx4QREyGf36C3+V3KzG9gjvyqZeXn67kMQ1Mr+ubILz42gr3/TCIuJoyy5XSpbFWDweNXY1+raeHlpsbbTp1zy9S00yhSU5Lxyn4+GK/gfJDtHVTK5FDQdwfw4MYJ9q+dKvv/7pU/AtCy2ze07vHdB+WlbttOldtJmXUDXD+7Bz2Dyu90fFHVdlIm76KirvucqvOLjXrFgxvSIYBXzuwhF9PQSRuo6vipyK0E5KLsuq/4bufUf3/L/r9u3iDg/due6tz3Uefc1Dk/dWunlITciqPPmkmdzgcfS26iP146jyeKuDTuRGJ8ND6eK4iNDsPMshojJ67C0ORtXYoOJzoiRFa+kqklIyeu5MDmeZw/thU9Q1O6D5mKc8P2sjLJiXHs/ncGcTHhlC2vi4WNE2Omb8Ta3jnX+gVByE0DKGG3dQSh8B09ehR/f3/Gjh2r6lDemUQiIfbqEVWHUST03KQNmJ7fPlJxJIXP869qAGw9q56H2AHNpB0KdcwvMzcvnRoqjqTwdUmVjh6x7Zz6bTeAL5tKt5065peZ2/bz6pdb/ybqu93g46iXIrfSR53zE7mVXuqcnzrnBuqdX2Zu6tzvUcfcQL3zy8xNnfc5dcwN1Du/jyE3deyPg3r3yTO33X9XimEIzmLWrb6W3I+sBNUImTBQ1SHkyXzhloILlTLiCW1BrRkaGtK+fXvatGnDt99+q+pwBEEQBEEQBEEQBEEQBEEQBEEQhFIu+ygSQtFTz4HUBaV5e3sTFxen8DNliuqHvP1Q165dY9WqVUyePJmHDx/K/e3OnTt55j5gwAAVRSwIgiAIgiAIgiAIgiAIgiAIgiAIQibxhPZHbtSoUZQrV07h3yIjI4s5msJXtWrVPP/WuXNndHR0FP5NmXdzC4IgCIIgCIIgCIIgCIIgCIIgCIJQtMQN7Y/cy5cvVR2Cyjx//lzVIQiCIAiCIAiCIAiCIAiCIAiCIAiljBhyvHiJIccFQRAEQRAEQRAEQRAEQRAEQRAEQRCEEknc0BYEQRAEQRAEQRAEQRAEQRAEQRAEQRBKJDHkuCAIgiAIgiAIgiAIgiAIgiAIgiAIgrI0xTPDxUkDkKg6CEEQ8iaRiF1UEARBEARBEARBEARBEARBEAQpDQ3x/mZVC506VNUh5KnybxtUHUKhEz8fEARBEARBEARBEARBEARBEARBEARBEEokMeS4IJQC286p51PaXzaV/opMHfPLzM3zUrqKIykaPRtqAeAf8ELFkRQ+J3sLQL3rpZdODRVHUjS6pD4AIPDxQxVHUvhsHaoDsP28+tXL/k2k9fJG++YqjqRouBw9A6h3vbz9OFTFkRS+Og6VAfAu76jiSIpG58T7AJz3j1NxJIWviZMuoN7n8euPwlUcSdGoV80YgMTTO1UcSeEr3+ILQD3rJWTVzWEz1e98sH6m9HxwPyBYxZEUPkd7S0A9+3SQ1a9Txz55Zn9cHdspmW0Ude+zqvO57trDCBVHUvhcqxsB4H0tVcWRFI3OrjqAerZTPoZrz4Jqiafki5d4QlsQBEEQBEEQBEEQBEEQBEEQBEEQBEEokcQNbUEQBEEQBEEQBEEQBEEQBEEQBEEQBKFEEkOOC4IgCIIgCIIgCIIgCIIgCIIgCIIgKElDUzwzXJzEty0IgiAIgiAIgiAIgiAIgiAIgiAIgiCUSOKGtiAIgiAIgiAIgiAIgiAIgiAIgiAIglAiiSHHBUEQBEEQBEEQBEEQBEEQBEEQBEEQlKShqaHqED4q4gltQShm69atw9PTU9VhCIIgCIIgCIIgCIIgCIIgCIIgCEKJJ57QFj5Y5cqVmTZtGl26dMHCwoLXr19z48YN/vjjD06cOKHUMoYOHcoff/yBoaFhEUdbtGbMmEGPHj2oV69esaxPIpFwcv9fXD21k+TEWCzsnOky6BdMLarlO9+9K0c44bmMqLDnGJpY81mvH3ByaydX5tKJrZw/vIa46DBMLRzo+OVUbKrXf6d1H9jwC0/u+REX/Zoyn5THyqEebftOwMTcrtTnlr3sliWjeXznDP2+/Qsn17YF5qYMP59tnPZaS1xMGJUtHOg66Ceq1qifZ/kn/pfx2jqf0BeP0TMwpUWXETT6rL/s73cuH8P3wD9EhD4nPS0NYzNrmncajmuzboUS74fyPriffXt2EBUZgZWNLSNHf0Ot2s4Ky/qdO81hrwM8ffKY1NRUrG1s6T9wKPXcGhRz1FIF1aecAh9c4sj2ebx+8RhdA1OadhpFg9b95coUVI/PeK3C/+oxwkOeoF2mLFYO9WjXZzzGSuxbxaFSs/rYjR+JvmttylYx5Urvrwn977iqw3pnBw56sWvvXiIjo7CxtsZj9FfUqV1LYdk7d++yZt0GgoKDefPmDaamJnTp2JFePXsUb9BvXTqxlXOH1hAfHYaJhQOdBhRQL+9f4vD2eYS9eIyuYf71MvL1cyqZ5q6Xl05s44rvNqLDXwBgYuFAq27fUM25RdEkmQ+jz3tg2vdLdCoZkfwskBcrlpFw51ae5Y0/74lx916UqWxOyutQQrdtJMrnSDFGrLzSXC+VcfigJ//t3UZUZCRW1rYMG/0dNWvXVVj2wrlTHPXeT+CTR6SmpmJlU5UvBgzHxa1hMUf9/gyb1sdu3Ej069WirLkpV/t9Q+iB0ne8POG9i0P7NhEdFY6FlR0DRo6nei3F7eHoyHC2r1vCswB/QkOCaNulPwNGjS+WOFVxzlZ2vWEvAzi2eyHPHlxGkpGBiUU1+o5ZgoFRlcL7AhQ46rWXA3u3Eh0ZgaV1VYZ89T1OtV0Ulr10/iTHvD0JfPKYtNQULK2r0mfASOq6fVqkMb6vnb4X2XDkLOEx8dhXMWVCv064VrdVWPbKg6d8tXBtrul7Z39PVXOTIo40N1X1hdLTUjnhuZRHt04RFRbMJ+UqYlezCW37/IieYeUiy1eRHq0q0NKtHBXKavLkRSobvWJ5GZaeZ3k3p0/o2rwClStpoaWpQWhkGofPJ3L+VnIxRl0w74P78dyzk6jICKxtbBk5+ut8+j1nOOT1H0+fBLzt99jQf+BQXFXU71FGae7X5fSx9ckVUZd2iiLq0mctzec6ZRz12sPBvVuJjspsp4zFsZaLwrKXzp/k2CFPnj15JGun9B4wkrqujYo3aAXOHt2O78F1xEaHYWbpQI8hk7F3dMuz/ON7l9m/+XdeBT9Gz9CUNl2H07RdP7kySQmxeO1Yxq3LPiQlxFLJxILugyZSs17R97/VuZ2iiv5C4IPLnD+8hpeBd4mPCSvU68uCoG7EE9rCB7GxseHq1au0adOGSZMmUadOHTp27Iivry9///23qsN7b9rapeO3HucO/Yvf0fV0HjSdr6bvoqK+CRsXjuBNUnye8wQ9vs6ulT9St0k3PGbtp26TbuxaOY7ggJuyMncueXN421yad/XAY6Yn1tXqs3nJaKIjXr7Tus1tatF9xG9886sXg8b/iwQJmxaNJCMj7wsRpSW3TBeObQCNwh1a5OaFQxzcPJfW3d35fs4ebGu4se53d6LDXyosH/k6mHULPbCt4cb3c/bQqttoDmz6jduXj8rKlKuoT+tu7nz9y1Z++M0Ttxa92L16Gg9vnS3U2N/H2VO+rP3nb/r2G8jiP/+hZq06zPnlJ8Jehyosf/fOLerWc2P67LksWraS2s4u/DprGk8CHhVz5MrVp+yiwoLZssQd62r18ZjpSfOu7hza+iv3rmTdOFOmHgc+uEyDNgMY9fMOhoxfS0Z6GpsWjyLlTWKR56wMrQrlib31gLtjZ6s6lPd28vQZVq7+ly/7fcHyZUupXbsWP8+YyevXrxWWL1u2LN26dmHh/LmsXrmcAf36sX7TZrwPHS7myOHORW8Ob51Li64eeMzyxKZ6fTYvzr9ebl7ijk31+njM8qR5F3cObVFQL1f8iHPjboyZvR/nxt3YuUK+XupXqkzbPuMZPWM3o2fspqpTI7Yt+4bXL4p33zRo2QYLj+8J3bqJB2NGknD7Jna//o6OianC8kZde2A+wp1Xm9Zx/6vBvNq0Fstvf0SvUZNijVsZpbleKuPc6eOsX/0nvfoN4fdl/+JU25nfZkzK83zgf/cmzvXqM3XWAhYsXU0t53rMm/0TTwIeFnPk70+7Qjnibt/n7o9zVB3Ke7t49ihb1y6ia98RzFq8heo167F4zvdEhL1SWD4tNQVdfUO69h2BlW3+F70Kk6rO2cqsN/L1c9bOHYCxmR3DJm3EY9Z+Wn4+Bm2dT4ruCwHOn/Zhw+ql9PxiCPOWrcOxljPzZk4g/LXibed/5wZ1XBry08yF/PbHWmo6u7JgziSelsB97sjl2/y+4xAju7Rk2y9jqFfNhm+XbSIkIjrf+fbNGcuxhZNkH+vKRsUTcA6q6gulpiQT8uweLT7/GvcZe+j37Z9EhAaybdnXRZ5zdp2blqdD4/Js9o5j1uoIYuIzmDjEkLJl8u53JSRlcOB0AnP+jeTnFRGcuZ7EyB561LYvU4yR5+/MKV/W/LOcvv0GsOTPVdSsVYfZv0zJt9/jUs+NX2b/xuJlK6jj7MKvs35WSb9HGaW5X5fTx9Ynz4s6tFPyog591tJ+riuI3xkfNv67lB5fDGXu0vXUqFWXeTPH591OuXuDOi4NmDxjIb/+sY6azm78PmcSTwMeFHPk8q77HWLfxnm06/EVE+buwq6GK//M8yAqPERh+YjXwaxe8DV2NVyZMHcX7bqPwnPDXG5ePCYrk5aWyorfviIy7AXDfljMlEUH6ffVLPQrKe7zFjZ1baeoqr+Q+iaJylaOdB40vVDyEIqZpmbJ/agh9cxKKDbLly9HIpHQsGFD9uzZw6NHj7h37x5LliyhUaOsX8CNGzeOW7duER8fz/Pnz/n777+pUKECAC1btmT9+vUYGBggkUiQSCTMmDEDAB0dHebPn09wcDDx8fFcuHCBli1bysUwatQonj9/TkJCAnv37mXcuHFERUXJlfHw8ODx48e8efOG+/fvM2jQILm/SyQS3N3d2bdvH/Hx8fz88888evSI8ePlnxapVasW6enp2Nkp9xSkpqYmixYtIioqivDwcObPn49GId38lEgkXDi2kRZdPajp1p7KltXpOXIeqSnJ3L54MM/5LhzbiH3NJjTv4o6JuR3Nu7hT1amR9MbsW35H1uPavDduLfpiUsWeTgOmol/JjCu+295p3fVb9cO2RgMMjS2pYlOLNj1/IDYyRPb0XmnODeDV8/v4HVlP9xG/5pvPuzp7aD31W/amYas+mFrY8/mgKegbmXPh+HaF5S+e2IGBsTmfD5qCqYU9DVv1oX7LXpzxXicrY+/UkNr122JqYY9RZWuadRiMmVV1Ah9eK9TY38d+z120bd+Jdh27YGVtwyj3bzE2MeWw138Ky49y/5ZefftTrbojVSwsGTxsFOZVLLh80a+YIy+4PuV05eR29I3M6TRgKiZV7HFr0Zd6zXtx/kjWr6SVqceDf/yXes16YWpRDTNrR3qMmEtMxEteBt4t8pyVEXbkNA9n/MGrfccKLlxC7fXcR4f27ejUoQPW1laMGf0VJsbGHPQ+pLC8g709rVu1xNbGBrPKlfmsTWvqu7py527xb5PzR9dTr0Vv3Fpm1Uu9SmZcPqG4Xl72zVEvW0rr5bnDWfXS7+hG7Go1oUVXab1s0dUdO6dG+GWrlzVc2lC9bkuMzapibFaVtr3HUaZseYKyddSKg0nvfkQe9iLy8EHeBD3jxco/SQ17jfHnPRWWr/RZeyK8/yP61AlSXoUQffI4kYcPYvrFwGKNWxmluV4q44DnTtq070LbDl2xtLZl+OjvMTI24aj3PoXlh4/+nh59BuBQ3QlzCysGDh2NWRVLrl48X7yBf4Cwo2d4OGspoftL7/Hy6P4ttGjbnZbtelDFqioDRo2nknFlThzerbC8ceUqDBw1gaatu1KufMVii1NV52xl1nt87x9Uc25J+y8mYm5Tk0qmVlSv24qKekV7gdlr3w5at+tKmw7dsLCyZejoHzAyNuWYt+LXIw0d/QPd+gzE/u0+9+VQD8yrWHLtUsm7GbP52Hl6NHOlV/P62JmbMrF/Z8wM9dh16lK+81XSq4Cxvq7so6WCC0Gq7AuVLa/LkAlrqd2wE8bmdljZu9B54M+EPLub58XcotC+UXkOnE7gqv8bXrxOZ7VnDJ/oaNCoTtk857kfmMq1+28ICU8nLCqdYxeTCApNo7q1TrHFXZD9nrtp274T7WX9nm8wNjHlkNcBheVHuX+jsN9zSQX9HmWU5n5dTh9bnzwv6tBOyYs69FlL87lOGV77ttO63edZ7ZSv3rZTDuXRTvnqB7r1HoR99ZqYV7Gi/xAPzMytuHbpXDFHLu+k10Y+bd2LRm36UNnCnp5Df8LAyIxzxxQfT8777MTAyIyeQ3+isoU9jdr0oWGrnvh6rZeVuei7l8T4GEaOX4ZdDVcqmVTBztEVCxvHIs9HndspquovVHNuwWe9fqCmW/sPzkEQ1F3JPGMJpYKhoSEdO3bk77//JjEx91OBMTExsn9nZGTw/fffU7t2bYYOHUqbNm1YsGABAOfPn2fs2LHExMRgZmaGmZkZCxcuBKTvm27atCn9+/fH2dmZXbt2cfjwYRwcHABo0qQJK1euZOnSpbi4uHDs2DGmTZsmF0ePHj1YunQpixYtonbt2qxatYp169bRqlUruXKzZs1i//791KlTh7Vr17J27VqGDx8uV2bEiBGcOXOGJ0+eKPUdjR8/nhEjRjBy5EiaNWtGpUqV6NlT8QX1dxUVFkx8TBj2tZrKpmnrlMG2RgOCHl/Pc76ggBvY124qN82hdjOCAm4AkJaWwstnd+WWC2Bfq6lsue+z7pQ3idw4uxcDY0v0KpmV+txS3iSxe9V4Og+ajq5+4Q3NlJaWwovAe1SrIx9jtdpNePbohsJ5nj2+QbXa8k8SVqvTjOCnd0lPS81VXiKR8PiuH2EhgfkOmVYcUlNTCXj8EBdX+Thc6tXnvr9yN1wyMjJISkqioq5uUYSYJ2XqU05BATdylXeo1YyXgVnbqqB6rEhyUhwA5Srov2saggKpqak8evwYtxyvj3Bzrcc9f3+llvE4IIB7/v7UqVO7KELMU1paCiGBd3FQVC8DFNfLYEX1srZ8vVRUxr52M4Ie31C4zIyMdG5f9CLlTSJW9i7vl8x70NDWpny16sRdk7+IE3f1MhVqKt4WGmXKkJHyRm5aRkoK5Ws4gZZWkcX6rkpzvVRGamoqTx4/pG49+WFG67o24IH/HaWWkZGRQXJSYrGfDz5maampBAbcp5aL/FCOtVwaEXA/72H+i5uqztnKrDcjI4NHN09iVNmWTYtGsmBsE1bP+QL/az7vna8y0lJTefr4Ac715Ifod67XkIf3ld/nkpKSqFBRryhCfG+paWn4P3tJ45oOctMb1XLgZkBQvvP2n72cdhPm475oHZfvK9fnK2yq7AspkpwYBxoalC1fPNvZxFALA10t7gSkyKalpcP9wBQcrJS/Oe1UtQzmRto8eJa7P6QKefd73N6536OrW7L2OSjd/bqcPrY+uVA6lfZzXUHybaf431ZqGVl9A9UdM9PSUgl+eo8azvLHhxrOTQh8qPiH34GPbuYq71i3KUFPso4nd6+dxLZaXXav+5Xp7i2YP7EHx/b9o9SImB9KXdspJekanyAIeSsd4yoLJZKDgwOamprcv3+/wLJLly6V/TswMJDp06ezYsUKvvnmG1JTU4mJiUEikRAamjUUlZ2dHV9++SWWlpaEhEiHYVm0aBEdO3Zk+PDhTJs2je+++45Dhw6xaNEiAB49ekSTJk3o2rWrbDkTJkxg/fr1rFixAkD29PiECRM4efKkrNzWrVtZty7r17Pr1q1j9uzZNGjQgMuXL6Otrc2gQYOYOHGi0t/RDz/8wNy5c9m7dy8gfVK8Q4cOeZYvU6YMn3yi3NCC8bFhAFTI8eRGBT0jYvL5VVp8TLjCeeJjpMtLjItCkpFOBX1FZcLfed2XTmzl2K6FpL5JxNjcjiET1qKtnf+wb6UhtyPb52LlUA/Hep/lm8u7SoyLJiMjHd0c69fVN+Lh2xhzio8JRzdHTrp6RmSkp5EQH42egfSGe3JiHL9934q0tFQ0NTXpPnQ61eqodkjduNgYMjIyMDAwlJuub2hIVFSkUsvYv3cnb5KTadq8VRFEmDdl6lNO8TFhVNBrJl9eX7qtEuOj0DUwLbAe5ySRSDiyYx7W1dyobFn9AzISMsXGxr6tlwZy0w0MDIiKis533oFDhhETE0N6RgaDBnxJp3yO+UUhMS6KjIz0XHWoor4R8XfyrpcV9XPUS73c9TLnk4IVFdTL0KAH/Pvrl6SlvqHMJ+Xp/+1fmFrIX2QpSlp6+mhoaZOaY6SW1KgodA0rKZwn7soljDp+Tsz5MyQ9eki5ajWo1KEzmjo6aOsbkBYZURyhF6g010tlSM8H6ejnPB8YVCJayfPBAc8dJCcn06R5m6IIUVAg7m27Rc9Afv/S16/EnSjFxxxVUNU5W5n1JsRFkPImkbPeq2nTayxt+07g8e0z7Pj7O4ZN2oBtjaJ5J3xsrHTb6ec4NuobGhJ9TbnjnpfnNt4kJ9G4eeG2hz9UVHwi6RkZVNKTHwHASLciETFxCucx1q/I9MHdcbKpQkpaGl4XbuK+eD2rJ4zALY93kRYVVfaFckpNfYPP7kXU+bQrZcsVz4gK+hWlz13EJmTITY9NyMBIP/8fmpX7RIMl443R1tJAIoGNXrHcfZKS7zzFJTaPfo/BO/R79u3dxZvkJJo2b1lw4WJWmvt1OX1sfXKhdCrt57qCyNopOduYBpWIiVbumOK1bxtv3iTRqJnq+gYJsdL+ea7jg74RsXkcT+KiFRxP3rZB4+Oi0Tc0IeJ1MI/CXuDWtAujJ68g7NUz9qz7lYz0dDr0HlNk+YD6tlNKyjU+ofTR0CzcV5EK+RM3tIX3ljl0tkQiKbBsq1atmDp1KjVr1kRPTw9tbW3KlStH+fLlFT7dDeDq6oqmpiYPH8q/k+2TTz4hIkJ6kaVGjRp4esoPNXPp0iW5G9pOTk78888/cmXOnTvH2LFj5aZduXJF7v+vXr3Cy8uLESNGcPnyZbp27UrZsmXZtWtXgfkC6OnpUaVKFfz8sobLSk9P58qVK3kOOz5lyhRmzpyp8G+3/A5wYOMM2f8H/rASQPGyChjWXIMcf5dIpxZYJsdylVm3c6PPsa/VhLjoMM4fWcuuFT8wYuo2dLK9E7C05Xb/+gme+l/EfebefGP5IDnWL5FIChiuPkd5aeJyU8uUrcD3v+4lJTmRx3cv4LV1AZVMrbB3KpoLpe8kZ24F5it1+uRxtm/ZyNRf5uS6eFJclKlPcuVz5Sr7Q/7LzDntLe/NcwgNesCIKVuVildQXs5tJZFI8toMMosWzCMpORn/+w9Yu34DVczNad2q+C865o5dQb2SnyOvBeW5TOlc8tOMzKviMcuT5MRY7l05iue/PzH8p03FelMbkCacjTR0xe2VV1vWo21YiepLV4GG9OZ35NFDVO43EIrhF+7vqjTXS2XkPkZKCjz3A5w96cPOLeuYPP23XDfFhaKX81ggQbntVtxUdc7Ob72SDOlNuxr12tC4/TAAzK2dCAq4zhXf7UV2Qzu/2JRpg507dYzdW9cyYfq8ErvP5d58ebcvbc1MsDXLGnWprr01oZExbDx6tsgv8pfEvhBAeloqu1f+iEQiocvgGbn+Xlga1ynL0M+znshdsiVaGlaO07YyR5TkFAm/rIykbBkNalYtw5cddAmLSud+YMl4ShsUdnuU7PeceNvvma2yfo9SSnG/LpePrU8ulEql5Vz33nIdUiRKnQ/OnTrKnq1rGP/z/Fw3xVUh97k3/+NJrrb125OiRrb2Y0W9Snzx1Uw0NbWwsqtFbFQYJw6uK/Qb2h9bO0XV1/gEQcifuKEtvLdHjx6RkZGBk5MT+/fvz7OctbU13t7erFy5kunTpxMZGUmzZs1Yu3YtOjp5DxmmqalJWloabm5upKfLX1COj48HpCeNnDfUFZ1QFZXJOS0hISHXfP/++y+bNm1i3LhxDB8+nB07dpCUlJRnzB9q7ty5LF68WG5abGwsADVcWmNh5yybnp4m/aV5fEw4ugamsukJsRH5vm+vor4x8bHyvyxLiIugor4xAOV1DdHQ1Mr167OEuKzlVtQzUXrdZcvrUra8LkaVbbG0r8v8bz/l/tVj1GmU9aOD0pbbU/8LRIY9Z9638p3OnX9/j3V1N4ZP3pRnjAUpr2uApqYWcTlijI+NzDP3ivrGCstramlTvqKBbJqmpibGlW0AqGLjxOuXTzh5YLVKO8+6evpoamrmevouJjq6wAsZZ0/58tfShUyaMoO69dyKMkyFlKlPOVXUN8ldPjZCuq0qGLwtk389zs57yxwe3DjB8J82o1/AUP6C8vT09NDU1CQqx1O+MTExGOZ4OjYnMzPpdqhqa0t0dDSbt24r1huH5XUN0VRUL2Mjcv3SOJOy9TL3cSaCCjnqpbZ2GYzeHmcsqtbhZeAdLhzbSLdhsz8kLaWlx8YgSU9Dp5L8RQttA0PScmzPTJKUFIIWzyNo6e/oGFYiNTICo87dSE9IIC3b61NUrTTXS2VIzwdauc8HMVEFng/OnT7O8mXzGf/TbJzriWE7i5Pu23ZLTLT8E72xMVHoGxTt+5/fharO2cqst7yuIZpa2phUkf/hj4m5Pc8fXX23RN+Bnp7B231OftvFREcVeOH3/GkfVi2byw8//Y86Lg3yLasKhhXLo6WpSURMvNz0yLiEXE+y5aeOnSXeFxQPB1qYSlJfKCuGVHatGEd0WDBDJ60v0qezrz94Q8CLrBvO2m8fwtavqElMfNZT2roV5P+viEQCryOl1w6ev0rD3ESbLs0qcD8wutDjfld6b/s9uc7j0QWf586c8uXPpQuZPOUXXFTQ71FGae7X5fSx9cmF0qm0neveVWY7JSbHMSU2JirXyEA5+Z3x4Z9lcxlbAtopFfSk/fOcT2PHxUbmGgUik66Bca7ymceTChWlr5nTMzBBU1sbTc2skUsqW9gRFx1OWloq2trKv6KjIB9LO6UkXOMTBKFg4h3awnuLioriyJEjfPPNN5QvXz7X3/X1pSfZ+vXro62tzfjx47l48SKPHj2iSpUqcmVTUlLQyvGeyuvXr6OtrY2pqSkBAQFyn8yhye/fv0/DhvIN//r15S9k+vv706yZ/PAfTZo0wV+J9016e3uTkJDAmDFj6NSpE2vXri1wnkyxsbG8fPmSRo2y3imopaWFm1veHbSUlBTi4uLkPpk+KVcRo8o2so9JFQcq6psQcO+8rExaWgqBDy5j5VBP0eIBsLJ3IeDueblpAXfOyd5xqq1dhio2teSWCxBw97xsuYYmlu+1bpD+WjQtTX7Yt9KWW7MuXzFm1n48ZnrKPgAd+v9EjxFz882/INraZbCwrcnjO/IxPr5zHptqLgrnsXFwyVX+0e1zWFathVZ+jViJhLRU1Q7Bp6Ojg71DdW5cl79ge+P6VRydauU53+mTx1m2ZD4/TpxG/YaN8ixXlJSpTzkprKN3z1HFNmtbFVSPQfojHa/Ns/G/eoyhk9ZjaGJZCBkJmXR0dKjm4MC16/LvSbp2/QY1nZyUXo5EIiE1tXifCNLWLoO5ba1cdejJvfNY2Suul5b2LjzJUY8f56iXlvYuPFFQd60cXPKNRyKRyDq8xUGSlkbio4fouspfuNB1bUDCvQLeCZueTmp4GGRkYNjqM2Ivns/9eJgKleZ6qQwdHR3sHKpz67r8iDm3rl+hhlPe7/w+e9KHv5fM5YeJv+DWsHFRhynkoK2jg629I3dvXJSbfu/GRewdnfOYq/ip6pytzHq1tctQxbY2Ea+eypWJeBWIvpF8n6kwaevoUNWhBrdvXJabfvvGZao75r3PnTt1jBV//Mp3E2bi2qBkDpOro62Nk00VLvgHyE2/cC+AuvZWSi/n/vMQjPWL/l2+JakvBFkXiSNeP2PIhHWUr1i0T8smp0h4HZku+7wMSyc6Lp1a9lmvqdLSAkfbMjwOerfzlwago10ynoDK7PfcfOd+zwmWLVnA+IlTVdbvUUZp7tfl9LH1yYXSqbSd695VZjvl1vVLctNv37hMdac6ec537tRRVvzxP76dMBPXBk3zLFdctLV1sKxak4e3/OSmP7zth231ugrnsa1Wl4e35cs/uHUeK7us40nVGi6Ev3pORkbWD71ehwSiZ2BSqDez4eNpp6jyGp9QumloaJbYjzpSz6yEYvP111+jpaXFpUuX6NWrFw4ODjg6OvLdd9/JhtoOCAhAR0eH7777jqpVqzJo0CA8PDzklhMYGIiuri5t2rTByMiIcuXK8ejRIzZv3szGjRvp2bMntra21K9fn0mTJtGpUycA/vzzTzp37sy4ceNwcHBg9OjRdOrUSe7p699//51hw4bh7u6Og4MD48aNo1evXixcuLDA/DIyMli/fj1z587l8ePHXLhw4Z2+n6VLl/LTTz/Ro0cPatSowfLly3O9+/J9aWho0KjdEM4cXIX/1WOEBj9k35op6JQpS51Ps55+3rt6Mj67F8n+/2m7wQTcPcdZ79WEhTzhrPdqnvj70ajdUFmZxh2Gce30bq6d2UPYywAOb5tLTGQI9Vv1V3rdka+DOOO1ipeBd4iOeEnQ4+vsWjEOHZ1PqOac/1NhJT03XX0TKltWl/sA6BtVKZQbi806DePyyd1cPrWH1y8COLB5HtERIXz6WT8ADu9YzI6VP2Xl3aYfUeEhHNwyn9cvArh8ag9XTu2heefhsjK+//3Do9vniXgdxOuXTzhzaD3Xzv1Hvaaff3C8H6p7z774HPHG5+ghgp4/Y80/fxMeFkqHztLYNq1bzR8Ls34ocPrkcZYumsewUWOo4ViTqMhIoiIjSUiIz2sVRaag+uSzexF7V0+Wla/fqj8xES85vH0uYS8DuHZmD9fO7KFJhxGyMsrUY6/Ns7nld4De7gspU7YCcTFhxMWEkZqSXHzJ50OrQnn06jqiV9cRgPJVLdGr60hZK3MVR6a8Xj17cPjoMY4cPcbz50Gs/Gc1r8PC6NJZev5Zu34DCxZljajx30EvLly8xIsXL3nx4iVHjvmwe68nbVq3KvbYm7R/Wy9PS+vloW1ziYkIoUFrab08tku+XjZo3Z/o8Jcc3va2Xp7ew/XTe2jaMateNnpbL894SevlGa/VPLnnR+Ns9dJn92KePbxCVHgwoUEP8NmzhMD7l3BuXLzHmbA9O6jUsSuVOnTmEysbqnh8h46pKeEH9wFgPsId64nTZOU/sbDC8LP2lKliSfkaTthMnUlZ26qErPsnjzWoTmmul8r4vOcXHD96kONHvQh+Hsi6f/4kPOw17Tt3B2DL+lUsW/SrrPzZkz78ufhXhoz8hmo1ahIVGUFUZIRKzgfvS6tCeXSdHdF1lh4vy9lYouvsSFnL0nO8bN99IKd99nHaZz8vg56ybc0iIsJf0bpDbwB2bfqL1X/8IjfP8ycPeP7kAW+Sk4iLjeL5kwe8CHpSpHGq6pxd0HoBmnYcyZ1Lh7h6aicRoc+4eHwzD2760qD1gCL9Trr06MeJowfwPXqQF0GBbFi9lPCwUNp27gnAtvUr+HvRHFn5c6eOsXzxHAaP/I5qjrWIjoogOiqCxBK4zw1q1wTPM1fZd/YqT0Jes3CHN68iY+jTUvpj6GV7j/Lzmt2y8lt8zuN7/R7PQiMIeBHKsr1HOX7tHv3afFrssauyL5SensbO5WN5GXiH3l/9ToYkXdbOzPmj5KJ09EIinzevgKvjJ1iYajGqhx5vUiVcuJ3V1v2qpx59Pst6IqtLs/LUsiuDiaEW5sZadGhcniZ1y3L+VsloHwN079mHY9n6Pf/+s5zwsNd0fNvv2bjuX5YsnCcrf/rkCf5YNI/hozxU3u9RRmnu1+X0sfXJ86IO7ZS8qEOftTSf65TRpUd/fI8dwPeYtJ2yMbOd0qkHANs2rGD54qyRwM6dOsqKJXMYNOI7qjnWLjHtlFZdhnDBdw8XffcS+iIAz43ziQoPoUlb6fHk4LYlbFk+RVa+SdsviAoPYd+mBYS+COCi714u+u6ldZdhWWXa9SMxPhrPDfN4HRLI3Wun8Nm3mmbt++dcfaFT53aKqvoLb5ITCHnuT8hz6cN30eHBhDz3Jzqfd5ILwsdKDDkufJDAwEBcXV2ZNm0aixYtwtzcnLCwMK5evcqYMdJ3dty8eZNx48YxefJk5s6dy+nTp5kyZQqbNmUNy+zn58eKFSvYsWMHxsbGzJw5k1mzZjF8+HB+/vlnFi1ahIWFBREREfj5+eHt7Q3A+fPn8fDwYMaMGfzvf//jyJEjLFmyhG+//Va27P379zN27FgmTpzIsmXLePr0KcOHD+fUqVNK5bhmzRqmTZv2Tk9nZ8r8TtavX09GRgZr167F09NT9vT6h2raaRSpKcl4bZ5NUkIMlnbODB6/hk+yDbUSE/kSDc2sX6VbO7jSx2MRJ/Yu5YTnMiqZWtHHYzGW9lm/DKzdsDOJ8dGc+u9v4mPCMLWoxsAfVmFgbKH0urV1yvDs4VUuHNtIUkIsFfWMsKlRn5FTt+U7BE1pyK2o1W3UicT4aI7vW0FcdBhmltUYNmEVhm9jjI0OJzoiRFa+kqklwyes5OCWefj5bEXPwJTPB0+lToP2sjIpb5LYt2E2MZGh6JT5BBNzO/p5zKduo07FklN+mrVsTWxcLDu2biQqMhJrW1umz5qLaWXpELmRUZGEhb2WlT9y6CDp6en8s3wp/yxfKpveum0Hxv44Odfyi1JB9SkuJoyYyKwGqKGJJQPHreLwtnlcPrEVXQNTOg2YRs36HWRllKnHV3y3AbB+/hC5eLqP+I16zXoVZcpK0XerTePjWcf4mgunAhC0cS+3Rk7Ja7YSpVWL5sTFxrJl23YiIyOxsbHhf7NmUNlUOqRWZGQkYWFhsvKSjAzWbtjAq1ehaGlpUcXcjBHDhtKlU8dij732p51JTJDWy7jMejkuq17Gx4QREyFfLwe9rZeXMuvlwBz1slpWvfT1XIahqRV9c9TL+NgI9v4zibiYMMqW06WyVQ0Gj1+Nfa3i/WV89KkTaOnpYTZwGNqVjEh+9pQnP08i9bV0dBedSkaUMa2cNYOmJia9+2FlaY0kPY34m9d59MMYUkJfFWvcyijN9VIZTVt8RlxsLLu3bSAqMgJrm6pMnTUfE1Pp+SAqMoLwsFBZ+aOH/yM9PZ1/Vyzh3xVLZNNbfdaRb3+cWuzxvw9919o0OrJR9v+aC6THyOBNntxyLx3Hy0+btSchNob/dvxLTFQ4Ftb2jJu+FGNT6QXhmMhwIsLk96cZPw6U/TswwJ8Lpw9jZGLOwtUHiixOVZ2zlWl7Orm1o+uQmZz1+odDW3/FyKwq/b5Zhk31oh16t0mLtsTHxbJn+zqiIyOwsrHjp5kLs/a5KPl9zufQftLT01m7YhFrV2RdoGzxWSe+Hvdzkcb6rjo0qENMfCL/HDxJeEwcDlUq8+f3g6liZABAeHQ8ryKzXiuRmpbOkl1HeB0dyyc6OthXMWXZ94NpWrQXIAABAABJREFUXqe6SuJXVV8oNuoVD26cAGDlzB5yMQ2dtIGqjsVz08P7XCJldDQY0kWXCuU0CQhOZeGmKJJTsn64bqSvJTeQyidlNBjcRZdKelqkpEkICU/jn70xXLr7plhiVkbzlq2Ji4tlx9ZN0vO4rS2/zJqLaWVpu0S6z+Xu96xavoxVy5fJprdp277Y+z3KKM39upw+tj55XtShnZIXdeizlvZzXUEaN29LXGwMe7evlbVTJs9YiMnbNmZ0jr7B8cPSdsq6lYtYtzJbO6VNZ8aosJ1Sr3EnEuJiOLJ3JbHRYZhbVWP05BVUMpGOxBMbHU5UeNbxxMjUkq8mLWffpgWcPboNfUNTeg6dQt1P28nKGBqZ4zHlH/ZtWsDvk3uhb2hKi06D+KzbyGLJSV3bKarqL7wMvMOGBVk3uI9sl/64rW7THvQcmfVDN0EQpCMwlZyxFAWhEPzzzz84OjrSokWLQllekyZNOHnyJJaWlrx+/brgGQqZRCJh2zn13E2/bCpt2Khjfpm5eV5KL6Bk6dSzofQVAf4BL1QcSeFzspc2VNW5Xnrp1FBxJEWjS+oDAAIfP1RxJIXP1kF6kWH7efWrl/2bSOvljfbNVRxJ0XA5egZQ73p5+3FoASVLnzoO0psL3uUdVRxJ0eiceB+A8/5xBZQsfZo4SYfNVOfz+PVH4QWULJ3qVZO+SzDx9E4VR1L4yrf4AlDPeglZdXPYTPU7H6yfKT0f3A8IVnEkhc/RXjq6mDr26SCrX6eOffLM/rg6tlMy2yjq3mdV53PdtYcRKo6k8LlWlz6Y432t5L26qTB0dpUOj62O7RR1v/asoVEyXq3yMYv8bYyqQ8hTpakrVB1CoRNPaAul3vjx4zl27BgJCQl06tSJoUOH8vXXX3/wcsuUKYOVlRVz5sxh586dKrmZLQiCIAiCIAiCIAiCIAiCIAiCIAgfM/EObaHUa9iwIceOHeP27dt4eHjw/fffs2bNmg9e7pdffsmDBw/Q19dn0qRJhRCpIAiCIAiCIAiCIAiCIAiCIAiCIAjvQjyhLZR6/fr1K5LlbtiwgQ0bNhTJsgVBEARBEARBEARBEARBEARBEITSSUNTPDNcnMS3LQiCIAiCIAiCIAiCIAiCIAiCIAiCIJRI4oa2IAiCIAiCIAiCIAiCIAiCIAiCIAiCUCKJIccFQRAEQRAEQRAEQRAEQRAEQRAEQRCUpKGpoeoQPiriCW1BEARBEARBEARBEARBEARBEARBEAShRNIAJKoOQhCEvEkkYhcVBEEQBEEQBEEQBEEQBEEQBEFKQ0M8Haxq0Qu+VXUIeTKY9JeqQyh0YshxQRAEQRAEQRAEQRAEQRAEQRAEQRAEZWmIQbCLk7ihLQilwPbz6vmUdv8m0l+RbTunfvl92VSa206/DBVHUjS+aCw9WXtfS1VxJIWvs6sOoN71MvDxQxVHUjRsHaoD4KVTQ8WRFL4uqQ8A9a6X5/3jVBxJ0WjipAuod7288/iViiMpfLUdzAC4HxCs4kiKhqO9JQD7LqerOJLC16OBFqDex8sbj8JUHEnRcKlmAsDJO0kqjqTwtapdDlDPeglZdXPpAfXLb+zn0tzUud+jjrlBVn7q2CfP7I+rYzsls42i7n1WdT7XqWM7JbONcuBqmoojKRqfu0lvEW09q37n8QHN1P/asyB8TMTPBwRBEARBEARBEARBEARBEARBEARBEIQSSTyhLQiCIAiCIAiCIAiCIAiCIAiCIAiCoCQNTfGkfHEST2gLgiAIgiAIgiAIgiAIgiAIgiAIgiAIJZK4oS0IgiAIgiAIgiAIgiAIgiAIgiAIgiCUSGLIcUEQBEEQBEEQBEEQBEEQBEEQBEEQBGVpimeGi5P4tgWhmEkkErp3767qMARBEARBEARBEARBEARBEARBEAShxBNPaAvvrHLlykybNo0uXbpgYWHB69evuXHjBn/88QcnTpz44OXb2NgQGBiIi4sLN2/eLISIi8/Tp0/5448/WLp0qUrWf+nEVs4dWkN8dBgmFg50GjAVm+r18ywfeP8Sh7fPI+zFY3QNTWnaaRQNWveXK3PvyhFOeC4j8vVzKpla81mvH3Bya5dtndu44ruN6PAXAJhYONCq2zdUc27xwbmcP7yGuOgwTC0c6PhlAbk8uMSR7fN4/eIxugb55xIV9hxDk9y5KLPe+Jhwju1eSMCdcyQnxWFTvT6dB/6MUWXbD8r34vGtnD20lvi36+00YAq2NfLO9+n9SxzeNl+ar6EpzTqNpGEb+XzvXj7K8Wzbrm3vsdTMlu+bpASO713KvWs+JMRGYm7jROcBU7G0q/NBuSjj7NHt+B5cR2x0GGaWDvQYMhl7R7c8yz++d5n9m3/nVfBj9AxNadN1OE3b9ZMrk5QQi9eOZdy67ENSQiyVTCzoPmgiNet9WF0siCrqauCDy5w/vIaXgXeJjwmj37d/4eTatshyzM+Bg17s2ruXyMgobKyt8Rj9FXVq11JY9s7du6xZt4Gg4GDevHmDqakJXTp2pFfPHsUb9Aeo1Kw+duNHou9am7JVTLnS+2tC/zuu6rByUUW9POO1Cv+rxwgPeYJ2mbJYOdSjXZ/xGJvbFVmeeTnhvYtD+zYRHRWOhZUdA0aOp3qtegrLRkeGs33dEp4F+BMaEkTbLv0ZMGp8MUf8YUpLvVTG4YOe7N+7najISKysbRk++ltq1q6rsOyFc6c54r2PwCePSU1NxcrGli8GDKeeW8Nijlo53gf347lnJ1GREVjb2DJy9NfUqu2ssKzfuTMc8vqPp08CSE1NxdrGhv4Dh+Lq1qCYo1bM79g2TnmvJS46jMoWDnw+6CeqOuZ9jHnif5mDW+YT+uIxegamtOw6gkaf9VdY9oafN9v+nkBNtzYMHfdXUaUg87EfL4947eXA3m1ER0ZgaW3L0K/G4pTHPnfx/CmOeXsS+OQxaakpWFpXpc+AEbi4fVrMUSvn5OEdHN2/gZiocKpY2fPF8IlUq+mqsGxMVBi71i/i+RN/Xoc8p3XnL+k3YlKxxSqRSDi5/y+untpJcmIsFnbOdBn0C6YW1fKdrzD6N8qs+8CGX3hyz4+46NeU+aQ8Vg71aNt3AiaFVGclEgmXj/7FvYs7eZMYS2VrZ1r0+oVKZvnnH3DrCJcOLyMm4jn6RtZ82ukH7Opk5Z+SHM+lI8t4ctuHpPgIjC2caNZ9GpWti76/k0md+j05qVNuH1t/PCd1aqMoos591tJ0rnsf6tJOOXdsGycPrpO1nbsP+Qm7fI6XAf6X+W/TAlnbudXnI2jSNut4efmUJztW/Zxrvrnrr6FT5pMiySE7iUTCqf/k2w6dByrXbvHdl9VuadPrB5xc5dstl09s5fyRrHZLh/7y7ZaU5AR89izi/vXjJMVHY2BsQcPPBtOg9ZeFlpsq2mTpaamc8FzKo1uniAoL5pNyFbGr2YS2fX5Ez7ByoeQmCOpAPKEtvBMbGxuuXr1KmzZtmDRpEnXq1KFjx474+vry999/qzq8YqOtXfJ+C3LnojeHt86lRVcPPGZ5YlO9PpsXjyY64qXC8lFhwWxe4o5N9fp4zPKkeRd3Dm35lXtXjsjKBD2+zq4VP+LcuBtjZu/HuXE3dq4YR3BA1g8N9CtVpm2f8YyesZvRM3ZT1akR25Z9w+sXj94/l0veHN42l+ZdPfCY6Yl1tfpsXpJ/LluWuGNdrT4eMz1p3tWdQ1sV5LLyR+o26YbHrP3UbdKNXSvlcylovRKJhO1/fUNUWDBffr8cjxl7MTCqwsaFI0h5k/je+d6+6M2hrfNo+bk7Y2bvxaa6G5sWu+eb76bFHthUd2PM7L206Doa7y2/cffyUVmZ54+vs3OFNN9vZu+jbpNu7Fj+I0HZ8t237mce3z1Pn9Hz+fZ/+3Go1ZT1v48gNir0vXNRxnW/Q+zbOI92Pb5iwtxd2NVw5Z95HkSFhygsH/E6mNULvsauhisT5u6iXfdReG6Yy82Lx2Rl0tJSWfHbV0SGvWDYD4uZsugg/b6ahX4l0yLNRVV1NfVNEpWtHOk8aHqR5leQk6fPsHL1v3zZ7wuWL1tK7dq1+HnGTF6/fq2wfNmyZenWtQsL589l9crlDOjXj/WbNuN96HAxR/7+tCqUJ/bWA+6Ona3qUPKkqnoZ+OAyDdoMYNTPOxgyfi0Z6WlsWjzqg46P7+Pi2aNsXbuIrn1HMGvxFqrXrMfiOd8TEfZKYfm01BR09Q3p2ncEVrb5d1JLqtJQL5Vx7vQJ1q3+i979BrNw2Wqcajvz64zJhL1WfF66d/cmdevVZ9qs+SxYuprazvWYN3sKTwIeFnPkBTtzypc1/yynb78BLPlzFTVr1WH2L1PyzO3unVu41HPjl9m/sXjZCuo4u/DrrJ95EvD+7avCcvPCIQ5snkubbu58/7892NZwY+3v7kSFKz7GRL4OZu1CD2xruPH9//bQutto/tv4G7cvHc1VNir8BV5bf6dqjbwv8BWmj/14ef70cTasXkbPL4Ywb9laHGvVZe7MCYS/Vny89L9zgzouDfhp5u/M/WMNtZxdWTBnMk9L4D53+dwRdq77nc69R/Hzwu04ONXjz1+/ITJMcXszNTUFXT1DOvUehaVt9WKOFs4d+he/o+vpPGg6X03fRUV9EzYuHMGbpPg85ymM/o2y6za3qUX3Eb/xza9eDBr/LxIkbFo0koyM9ELJ/7rvv9w8vZ7mPafTZ+wuyuuZ8N8/I0hJzjv/V4HXObr5R6q7daPf+P1Ud+vG0U3jCH2Wlb/vrukEPTxP2y/n03/Cf1hVb8qBf4YTH1O0/Z1M6tTvyUmdcvvY+uM5qVMbRRF17rOWtnPdu1KXdsoNv0P8t3EebXuMZtxvu7FzdOXf+Xm3nSNeB/PvgjHYOboy7rfdfNbjK/Zv+I1bOdrOZctV5JflJ+U+xXEzG7K1HQZO56ufd1FRz4RNiwput+xeJb3G7DFTeo1598pxBD/J0W7ZPpfmXTxwnyFtt2z5YzQx2Y7Hh7fP4/Gds/QatYBv/udFo3ZDObT1f9y/Xjg/6FZVmyw1JZmQZ/do8fnXuM/YQ79v/yQiNJBty74ulLyEoqOhoVFiP+pI3NAW3sny5cuRSCQ0bNiQPXv28OjRI+7du8eSJUto1KgRIL3pLZFIqFs36xdz+vr6SCQSWrZsCYCBgQGbN2/m9evXJCYm8vDhQ4YNGwZAYGAgADdu3EAikeDr6wtIDw7Tp08nKCiI5ORkrl+/TocOHWTryFxv3759OX36NImJiVy6dIlq1apRv359Ll++TFxcHIcOHcLY2Fgur2HDhnHv3j2SkpLw9/dnzJgxCpfr6+tLUlISgwYNUur7cnBw4NSpUyQlJXH37l3ati26JyjPH11PvRa9cWvZF5Mq9nQaMBW9SmZcPrFNYfnLvtvRNzKn04CpmFSxx61lX+o178W5w2tlZfyObsSuVhNadHXHxNyOFl3dsXNqhN+xDbIyNVzaUL1uS4zNqmJsVpW2vcdRpmx5uY7au/I7sh7X5r1xa5GVi34lM674Ks7lyskcubSQ5nL+SFYuF45txL5mE5p3kebSvIs7VZ0acSFbLgWtNyI0kOCAm3QdPAOLqnUwNrejy+AZpCQncPui13vne/7IBlxb9KJ+y76YVrGn80Dptrt0YrvC8pfebrvOA6diWsWe+i374qpg29nXakLLrqMxqWJHy66jpdvu6EZA2lC6d+UYHb6YgG2NBhhVtqFNz28xNLbkUh51prCc9NrIp6170ahNHypb2NNz6E8YGJlx7pjifM/77MTAyIyeQ3+isoU9jdr0oWGrnvh6rZeVuei7l8T4GEaOX4ZdDVcqmVTBztEVCxvHIs1FVXW1mnMLPuv1AzXd2hdpfgXZ67mPDu3b0alDB6ytrRgz+itMjI056H1IYXkHe3tat2qJrY0NZpUr81mb1tR3deXO3bvFHPn7Cztymocz/uDVvmMFF1YRVdXLwT/+S71mvTC1qIaZtSM9RswlJuIlLwOLd/se3b+FFm2707JdD6pYVWXAqPFUMq7MicO7FZY3rlyFgaMm0LR1V8qVr1issRaW0lAvlXHAcydt2nembYeuWFrbMmL0dxgZm3DEe7/C8iNGf0ePPgNwqO5EFQtLBg4djVkVS65cPF/MkRdsv+du2rbvRPuOXbCytmGU+zcYm5hyyOuAwvKj3L+hV9/+VKvuSBULSwYPG4V5FQsuXfQr5shzO3NoPQ1a9aZha+l5vNvgKegbmXPhuOLz+IUTOzAwMqfb4ClUtrCnYes+1G/Zi9Pe6+TKZWSks335ZNr1/pZKplbFkcpHf7z02redNu268lmHz7G0smXY6LEYGZty1HufwvLDRo+le5+BOFR3wtzCii+HumNexZKrl84Va9zK8DmwiaZtetKsbS/MLe3oN2IShkZmnDqyS2F5Y1ML+o2cTONWnxf7uUAikXDh2EZadPWgplt7KltWp+fIeaSmJHP74sE85yuM/o2y667fqh+2NRpgaGxJFZtatOn5A7GRIbJRuj40/1tnNuL2mQf2ddpjZF6dz/rPIy0lmUfX887/5pmNWFVrgttn7hia2uH2mTsW1Rpx84w0/7TUZJ7cPkrjLhOoYt8AfWMbGnb4Dt1Kltw9X7T9nUzq1O/JSZ1y+9j64zmpUxtFEXXus5amc937UJd2yinvDTRs1ZtP37aduw+ZgoGROX4+OxSW9zu+A0Mjc7oPkbadP23dhwatenHq4Hr5ghoa6BmYyH2Kg0Qi4aLPRpp38cDJrT2mltXpoUS75aJPVrvFOFu75WK2dsuFo+up17w3rm/bLR2/lLZbLp/MOi4GB9ygbpMe2Dp+ioGxJW4t+2FmVYOXgXcKJTdVtcnKltdlyIS11G7YCWNzO6zsXeg88GdCnt3N8wdWgvAxEje0BaUZGhrSsWNH/v77bxITcz89EBMTo/Sy5syZQ82aNenUqRNOTk6MGTOG8PBwABo0kA5T9Nlnn2FmZkavXr0AGDt2LOPHj2fChAk4Oztz5MgR/vvvPxwcHOSWPWvWLP73v//h6upKWloa27ZtY8GCBYwdO5bmzZtjb2/P7NlZTzCNGjWKX3/9lWnTpuHk5MTUqVOZM2cOQ4YMkVvu/PnzWbZsGU5OThw5coSCaGhosHfvXtLT02nUqBEeHh7Mnz9f6e/oXaSlpRASeBeHWk3lptvXakpQwHWF8wQH3MA+R3mH2s14GXiX9LTUPMvY125G0OMbCpeZkZHO7YtepLxJxMre5b1zefnsbu711mpK0GPFuQQpyqWWfC5BATewr50736CAG0qvNz0tBQBtnaxfPGpqaqGlXYbnj66+Y6ZkrTfwLg65Yssn38c3cpev05QX2fN9fBOH2k3kylSr05Tnb5eZkZ5ORkY62jl+valT5hOePbz2XrkoIy0tleCn96jhLB9bDecmBD5U/COIwEc3c5V3rNuUoCdZ+d69dhLbanXZve5Xpru3YP7EHhzb90+hPTWiiKrqakmRmprKo8ePcasnP4yzm2s97vn7K7WMxwEB3PP3p06d2kUR4kepJNXL5KQ4AMpV0H/XNN5bWmoqgQH3qeXSSG56LZdGBNy/VWxxCO8uNTWVgMcPcaknP1xlXdcGPPBX7uJERkYGyUmJVNTVK4oQ35ssN1f5oUtd6rlx31+5i6MZGRkkJSWhq+Lc0tJSePH0HtVyHA+q127Cs0c3FM7z/NENqudok1Sv04zgp1nHGAAfz+VU0DWkYavehR63IuJ4mcqTxw9xzrnP1WvAw/vK73NJSYlUrFiy9rm01FSeB/hT06Wx3PSadRsR8KDkvdIqKiyY+JgwubqlrVMG2xoN8qyLUDj9m/dZd8qbRG6c3YuBsSV6lczeKVdFYiODSYwLw6pGVgxa2mWoYt+AV4F55x/67IbcPADWNZrxKvAGABnpaUgy0uX6biDty4U8fb++27tQp35PTuqU28fWH89Jndooiqhzn7W0nevelbq0UzLbztWdc7aFmxD48IbCeZ49ukn1OjmPr00JytF2TklO5H/ft2XOt21Y8/vXvAhUrk5/qOjwvNsOwXlcgwZpu8UuV5sk6xpzeh7tFruaTQnOdjy2rubKwxsniI0KRSKR8PT+BSJeBeJQu9kH56bKNpkiyYlxoKFB2fIl7/gqCKpS8sZNFkosBwcHNDU1uX///gcvy9r6/+zddXgURx/A8W8UiHsIMYhBggV3dy3SFgpFSmmR9m3RIi3aUlxKW6ClOMW1uFtxt2AJDSQkxN3l3j+OXHKXS7iEJJcc83meeyB7s7vzu52dnVmZdeL27dvcvCntSL548UL2XVhYGAARERGEhGQPcTRhwgTmz5/P9u3SO9gmT55MmzZtGDNmDF9//bUs3aJFizh+XDoMyy+//MK2bdto27Ytly5Jn9ZZs2aN7GlwgGnTpjF+/Hj27t0LSJ8Q9/LyYsSIEWzcuFGWbtmyZbI0qmjfvj2enp5UrlyZV6+kd65PnTqVo0fzHqZIX1+fcuUKPjxMYlwUmZkZGJpYyk03MrUk/kG40nniY8IwMpU/2BuaWJKZkU5ifBTGZjbEx4RjpLhME0viY8LkpoUEPOGvOZ+QnpaCfjkD+n/9Gzb28jcaFCQWSWYGhqby6zU0sSQ+Ju9YDE0UYjHNHYvi72OYIxZV1mtV0QVTy0qc3LWEHkNmoVeuApePrSc+Joz4aPnfRPV4o8nMzMDIRH7UACMTS+LyjFfZdrFSEq/8Mg1NrGSxlKtgiKObN2f3r8TazhUjU0vuXTlE4PN7WNg6FyoWVSTESsuqscLvbGxqSWwe8cZFhytNn5mRTnxcNKbm1kSEBvIs7BX1mnXjy0krCXv9gt3r5pCZkUGnvqOULvddqauslhaxsbFkZmZiZmYmN93MzIyoqOh85x04eCgxMTFkZGby6YBP6JJjtA3h3ZSWcimRSDi2fR5O7vWwdSi54ezi3tSpJmYWctNNTS14EKU8fqF0iIuNITMzA1OFbWdmZk50VKRKy/hn73aSk5Np1qJNcWSx0GJjY97Ul+Zy083MzYlSMbZ9e3aSkpxEsxatiiOLKpO1W0xztznjovM4jseEK02fmZFOQlw0JubW+D+9xfWzexjz855iy7ui972+jM3a58wV6ktzC6JvRai0jIN7t5GSnEyTFm2LI4uFFv+mb2RiKh+bsZklsXmUU3WKj5WWDWXlJiafJ3KKon9TkHVfO72FEzsXkZaSiJWdC4MnrEVXV1/VMPOUGCfNg4GRfB4MjCyJi8o7/sS4cCoozFPByFK2PP3yRtg6e3PjxArMbVyoYGzFs9uHCHl5DzOr4uvvZNGkfo8iTYrtfeuPK9KkNooymtxnLWvHuoLSlHZKwps6Rln9l1cdExcdjnEt5fVlVtvZppIL/UbOwc7RneSkBC4c3cRvMz9l3Nw9WNsVbx2S1c5QrAdVabcoPcccK99uyZXG1BK/HOe2uwz4ngMbprF0Qiu0dXTR0tKix5CfcHJ/91cWqbNNpigtLYWTuxZTs1F3ylco/SMqvNe0xTPDJUlc0BZUljXuvkQieedlrVy5kt27d1O3bl2OHz/Ovn37uHw57+GJjI2Nsbe35+JF+WFiLl68KDe0OcC9e9lPYGVdEL9//77cNBsb6TuYrKyscHJyYs2aNaxevVqWRldXN9cT5zdu3ChQjJ6enrx8+VJ2MRvIN0aAKVOmMHPmzAKtJyfFdyNIJKBFfu9LyOO7HMtR9r4FxWVa2lVh5Ky9JCfG4nPjOHv/msxnkzcV+qK2snUgkc9X7iwrSY/8PEqXqTAtv/Xq6OrR76vl7F/3A/P/1wgtbR1cvJrgVrNlvrGoRHG1Ekn+205xW2cHnCNJroXKLfPDL+ezd833LBzbCm1tHeycvajZuDvBL3wKE0GB5P6dJfm+20MxfVY9JKuXMjMxMrHg4y9moq2tg6NLdWKjwjh9cF2xn9hRV1ktLXLXO5K3ZnXxgnkkJSfz6PET1q7fQCU7O9q0Ln0nQMoydZfLw5t/JCTgCcOmbFEpv0UtV52BJN/4hdJDyaFLpW134exJdvy9nknT5mCqcFK2tFAWmyrvtTp/9jTb/t7I1Omzc51wVpfc+X7LcVxJeul0SElKYNvKSfQdPgtD45KPT9SXuY/jqpTLi+dOsGvLWiZMm1tq97k8KhS1ZCWne5cPcGDjDNnfA8esAvKoD96yLd61f5O9mrevu1bjHrhWb0pcdBiXjq1l58oxDJu6FT29gt2Q/fTWAc7uyo6/2+erlK5PomRa7iwq6avmmNb+kwWc2TGVDT+2QktbB2t7L9zrdCc8sPj7O7L8aFC/5215LdOxvWf9cUWa1EZRRqP7rKX0WFdUNKedoqzOKEAdk3Uu/s1kZ/faOLtnnw+v7FGHZd9/yMXjf9NryNSiyLDMvSsHOJij3TLg2zyO26r025Qd63P9Dvkv9+rJTQT63aX//1ZgZmnPi6fXObx5FsZm1rh4NaUgSmObDCAjPY1dq8YhkUjoNmhGru8F4X0mLmgLKnv27BmZmZl4enqyf//+PNNlZmYC8pW/np6eXJqjR4/i7OxMt27daN++PadOneL3339n4sSJ+eZB8WK6lpZWrmlpaWm50itO035z50zWv1988QVXr16VW05GhvywVgkJCfnmTZGyg9/bbgaYO3cuS5YskZsWGxv71nUZGJujra2T666uhNiIXHd/ZTEytVaaXltHFwNDszdprHLdMRgfG4Ghqfydxrq6+li+uYvYvkpNgvwfcOXERnoOnU1BGRibo6UslriIXHfpFTSW+Fgly3wTi6rrrVS5BqNm7SM5MY6M9DQMTSxY/ePHVKpcuOGnDIzNlG+7uMhcTzNlx2uVd7xGOeJVeBIoIU6+PFjYOPH5lE2kpiSSkhSPsZkN21eMxdzKvlCxqMLQRFpWFe/cj4uNxDiP7WtsZpUrfXxsJNo6uhgaSYfmNDGzRltXF21tHVkaW3sX4qLDSU9PQ1dXvg4qCuoqq6WFiYkJ2traREVFyU2PiYnBXOEOeEUVK0qHp6xSuTLR0dFs3rK1dJ4cKINKQ7k8/PePPLlzms8mb8a0CIYiLQjjN3VqTLT8XfuxMVGYmimPXygdjE1M0dbWyfU0dkxM1FtPkF48f5oVyxcwYfIsatepn29adTAxMVVeX0a/PbYL587w6y+LmDRlOt513v2pg3eV1W5RfBo7PibvdouxqZXS9FntlpBXvkSFvWLD4q9k30sk0v7ElME1mbDwEJa2TkUciagvTWT7nEJ9GR2Va6QERZfOn2LV8nmMnfwjtbwb5JtWHYze9I1iFY4FcTGRmJSCY0FV7zbYu9SS/Z31WqP4mHCMzWxk0xNi8y6LUDT9GyMTa5XXXd7AmPIGxljaVsbBtTbzv27E45snqNm4u8qxA1T2akO/cbnjT4wLx9AkOw9J8RG5ntrOycDYisQ4+diS4iOoYJS9r5laOdFr9GbSUhJJTYnH0MSGY5vGYmzhUKA8F4Ym9XsUaVJs71t/XJEmtVGU0eQ+a2k/1r0rTWmnGGa1nRXrv5jIXE9tZzE2U9J2ltWXZkrn0dbWxtGlBmGvXxRJvnOqWrsNDjOyj9vpebRbEvNpQ0PedWfWCBmydoti2yZHmyQtNZlTe5bR76tf8ajdGgBbx6q8DnjMpWNrC3xBuzS1ybLzkMbOlWOJDgtkyHfrxdPZgqBAPA8vqCwqKopjx47x1VdfYWBgkOt7U1NpJyRryHA7OzvZd97e3rnSh4eHs2HDBgYNGsSYMWP48ssvAUhNlR48dHSyOzFxcXG8evWK5s3lh/hr2rQpj1R8740yoaGhBAYG4uLigp+fn9zH39+/0MsF8PHxwcnJSe53aNKkST5zSGOPi4uT+6hCV1cfu8rV8Xt4SW76c59LOLrWUTqPg6s3z33k0/s+vEilytXRedNRdHD15rnCMv0eXsTRzTvf/EgkElkjoKB0dfWp5FwdPx/F9V7C0U15LI6u3rli91OIRWmaBxdl7/ou6HrLGxhjaGJBRIg/Qf4PqFqncEMY6erqU0nJtss3Xrfcsfg+uIh9znjdauObK80lnJQsU7+cAcZmNiQlxOB7/yLV6rYrVCyq0NXVw6GKF0/vyY9W8PT+ZSp71FY6T2X32jy9L5/+yb1LOLpkx1ulqjfhr1/KbqgBCA32x8TMuthO6qirrJYWenp6uLu5ceu2/Pt+bt2+g5enp8rLkUgkcjcdCe9GneVSIpFwaPNsHt08wZDv1mNuXfwnixXp6ulR2bUaD+/I36Tmc+cqrtVq5TGXUBro6enh6ubB3dvyI+Lcu32Dqp553zR24exJfls6lzETp1GvYf7tLHXJjk3+na13bt+kmmf1POc7f/Y0y5cuYPzEqdRv2DjPdCVJV1cf+ypePHsgXx88e3AJZ3dvpfM4uXsrSX8RhyrSOsbazoWxc/fz7Zw9so9n3Ta4eDbk2zl7MLUsngu9or7Uw8XNg3t3rstNv3fnBh7V8t7nLp47wYplc/hmwgzqNijYScOSoqunh5OrJ4/uyrcfH927imtV5e3NklSughGWts6yj3UlN4xMreXKYnp6Kv5PrudZFqFo+jfm1g6FWjdIny5LL0SfT7+8EaZWzrKPua0bBsbWBD7NzkNGeipBftepWDnvPNg6exPwVD62gCcXqVjZO1davXIGGJrYkJwYQ8CTf6lSo/iHn9Wkfo8iTYrtfeuPK9KkNooymtxnLe3HunelKe2UrLbz0/vy9cHTB5eo7OGtdB5n99o8VWg7P713Cccq2XWMIolEwqsXjzExsy6SfOdUroIRFrbOsk9WuyXnOeWMN20HhzzOQYO03aJ4Hvp5jnPMOm/aLYrnoZ/7XMLhTd2ZmZFOZkYaWgpDPGtpayPJcewoSGylpU0G2RezI0JfMHjCOgyMSsPoAsLbaGlrldqPJhIXtIUCGT16NDo6Oly7do0+ffrg5uZGtWrV+N///icbTjs5OZnLly8zefJkPD09adGiBT/99JPccmbNmkXPnj1xdXXFy8uL7t27yy5Mh4aGkpiYSOfOnbGxscHExASAhQsXMmnSJD7++GM8PDyYO3cu3t7e/PLLL+8U08yZM5kyZQrffPMN7u7u1KhRg6FDhzJ27Nh3Wu7Jkyd58uQJGzdupFatWjRv3pw5c+a80zLz07TjUG6d38Wt87sJC/LjyNa5xEQE06BNfwBO7FzMntWTZOkbtOlPdHgQR7fOJSzIj1vnd3P7/G6adR4mS9O4wyD8Hl7kwqHVhAU/58Kh1Tz3uUyTDkOy49y1hBdPbxAVHkhIwBNO7l6K/+Nr1GrSo9CxNOn0JpYL0liObp1LTGQw9Vv3f7NO+Vjqt+5PTEQQR7e9ieXCbm5d2E3TTtmxNHoTy7+HpbH8e3g1zx9dpnGOWN62XoCH14/y3+OrRIYG8Pj2KTYuGka1uu1wqyF/s0VBNO00hJvndnPz/G5Cg/w4vEW67Rq26QfA8Z1L2PVndrwN32y7I1vnERrkx83zu7l1fo/ctmvSYTB+Dy5x/tBqwoKec/7Qavx8LtOk42BZmmf3/+XZvQtEhQXi++Aia+cNxcquCnWb9y50LKpo3W0wV87s5uqZPYS88mPvxvlEhQfTtL003oNbl/L3iinZv0/7j4kKD2bfpgWEvPLj6pk9XD2zhzbdhman6dCPxPho9m6YR2iwPw9vnePkvtU079hfcfVFSl1lNSU5geCXjwh+Ka03o8MDCX75iOh83ulTHPr07sXR4yc4dvwEL18GsOrP1YSGhdGtaxcA1q7fwILF2aNO/HPwEFeuXuPVqyBevQri2ImT7Nqzl7ZtWpdovt+FjqEBJrWrYVK7GgAGVRwwqV2N8o52b5mz5KirXB7aPJt7lw/Qd8Qi9MsbEhcTRlxMGGmpySUXPNDxg4GcP7mP8yf3ExTwH1vXLCYi/DVtOvUFYOem31i9bLrcPC+fP+Hl8yekJCcRFxvFy+dPeBXwvETz/S7KQrlURY/eH3Pq+CFOHT9E4Et/1v35G+FhoXTs2hOAzev/ZPni7LbUhbMn+XXJzwz5fDQeVb2IiowgKjKChIR4dYWQpw96f8iJY4c5efwIAS9f8NefKwgPC6VzV2l7aeO6v1i6aJ4s/fmzp1m2eB6fDR9J1WpeREVGEhUZWSpia9FlKNfP7uL6ud2EvPLjwOZ5REcE07id9Dh+ZPsStq+aLEvfuG0/oiKCObB5PiGv/Lh+bjfXz+6mZdfPANDTL0dFR3e5TwUDE8pVMKSio3uRvKM3L+97fdmtV39OHz/ImeMHCQzwZ8Pq5YSHhdChay8AtqxfxW+Lf5Slv3juBL8v+YlBn3+Ne7XqREdFEB0VQWIpKJeK2vcYxL+n9nLx1D6CA5+zY91CIsODadnxQwD2bl7OuuU/yM0T8N9jAv57THJyEvGxUQT895igAL9iz6uWlhaNOwzmwsE/eHTzBCGBT9m3Zgp6+uWp2Sj76ec9qydxctdi2d9F0b9RZd2RoQFcOPQHQf4PiI4IIsD3NjtXjkVPrxzutd79aUUtLS1qtRjMzVN/8Pz+CSKCn3J6+xR09cvjXic7/pNbJ3H5cHb8tVoMIuDpRW6dXk1U6HNunV5N4LPL1G6RHf/LJxd4+fgCsRGBBDy9yP5VQzCzrkK1Bn3eOd+q0KR+jybH9r71xxVpUhtFGU3us5alY11haEo7pVXXIVw7s5trZ6X15f5N84gOz247H962lK056ssm7foRFR7MP5ukbedrZ/dw7exuWnUfKktzfPcKntz9l4iQAF75P2LHn9MIevGEJu0+LvZ4tLS0aNR+MBcO/cGjWycIDXzKvrW52y17/5rEyd052i3ts9st4TnaLY1ytFsadxzKrQu7uJ3Vbtn2pt3SSnocKFfBCOeqDTixYyH+j68SFRbInX/3cO/SfqrV7VAksamrTZaRkc6OFd8S5P+Avl8sJFOSIesjFOYGQkHQVGLIcaFA/P39qVu3Lt9//z2LFy/Gzs6OsLAwbt68yahR2e80GjZsGGvXruXGjRs8efKE7777jhMnTsi+T01NZe7cuVSuXJmkpCQuXLhA//5ZFXgG33zzDdOnT2f27NlcuHCBNm3asHz5ckxMTFi8eDE2Njb4+PjQs2dPfH193ymmNWvWkJiYyMSJE1mwYAEJCQncv3+fZcuWvdNyJRIJvXv3Zs2aNVy7dg1/f3+++eYbjh079k7LzUuNRl1JTIjm3D+/ExcTho29OwPH/oHZm+Gq4mPCiMlxscvc2oFPx/7B0a3zuHZ6C8ZmNnQZ+D1e9TvJ0ji51+XDkYs5vecXzuxdjrmNIx+NXIKDa/bdnvGxEez58zviYsIoX8EYW8eqDBq/GtfqzQofS8OuJMZLY4nPimVMdixxMWHERMrHMvBNLNezYhmgEItbdiyn9y7HwsaRDxViedt6AeKiQzm2bR7xsREYm1lTu8kHtOz5bu/zqtlIut6z+1cQFxOGrb07g8atyt520WHERATLxTto3CqObJ3H1VPSeLsOnEr1Bh2z43Wvw0ejFnNq9y+c3vMr5jaOfDxqMY454k1OiuPEzqXERr2mgqEp1et3pH3fMXne8VlU6jTpQkJcDMf2rCI2Ogw7R3e+nLQSC+tKAMRGhxMVnh2vpY0DX3y3gn2bFvDv8a2YmtvQe8gUajfKbqyaW9oxcsqf7Nu0gIWT+mBqbkPLLp/SrufnxRqLuspqkP8DNizIbhgf2yY9wVC7WS96f559sqG4tW7ZgrjYWP7euo3IyEicnZ35adYMbG2kQzNFRkbKRu0A6Xvx1m7YwOvXIejo6FDJriLDhg6hW5fOJZbnd2VarwZNTm2S/e21SPp+qoCNe7j3+ZS8ZitR6iqXN85sBWD9/OwTdQAfDPuZOs1L5sQxQKPmHUmIjeGf7X8RExWOvZMrY6f9gpWN9OJuTGQ4EWGv5eaZMW6g7P/+fo+4cv4oltZ2LFp9oMTy/S7KQrlURbOWbYmLjWHn1o1ERUbg5FyFqbPmY2MjfUI3KjKC8LBQWfoTRw+QkZHB6pXLWL1ymWx663ad+d+40hV3i1ZtiIuLZfuWTdL6snJlps+ai42tLQBRUfKxHTtykIyMDP5YsZw/ViyXTW/bviPfjpuUa/klqXbjLiTGRXNq70pio8Oo6ODOZxP/kA2RGhcdTnSO47iFjQPDJqziwOZ5XD65BRNzG3oOnkrNhh3zWkWJed/ry6Yt2xEXF8PubeuJiozA0bkKk2cuxPrNPhcdFUFEWIgs/ckj+8nIyGDtyiWsXZl98r9Vuy6MHvt9ieVbFQ2adSIhLppDO/8gJiqcSk5ufD31NyxtpO3NmKgwInOUU4CfJmRfNHvp58O1C0ewtLbj51VHij2/zboMJy01mUObZ5OUEIODSy0GjV9DuRzDTMZEBsk9aVFU/Zu3rVtXT58XT29y5cRGkhJiMTKxxLlqfT6fujXf4TcLok6b4aSnJXN+z2xSkmKwdapFjy/WoF8+O/74qCC513rZVa5Lx4GLuXr0F64dW46JpSMdBi3B1jk7/tSkeK4cWUJ89GvKG5jhUrMDjbqMRUenZJ5k1qR+jybH9r71xxVpUhtFGU3us5a1Y11BaUo7xbtJFxLiozmxJ7vt/Pl3q3LUl2FERcjXl8O/W8k/m+Zz8cRWTMxt+GDIVGrlaDsnJcayc81M4qLDKW9gjL1zNUZP24CTW8mMStasi/S4fThn22GcknZLjuO2o1tdPhyxmNN7f+HMvjftlhFLcHCRb7ckxUdz7kCOdsu38u2WD0cs4dTuJexZPZGkhBhMLSvRtvcYuYeR3jU2dbTJYqNe8+TOaQBWzewll6ch322gSrVGRRKfIJR1Wrx5Rb0gCKWTRCJh2yXN3E37N5Ue/Lde1Lz4PmkmjW3H5YIPeVMWfNxEOsDH4Vula9itotC1rvQEgiaXS3/fp2rOSfGo7OYBwCG9qmrOSdHrlvYE0OxyeemRaq/ZKGuaehoDml0uH/i+fkvKsqeGm/RE2WO/QDXnpHhUc5UOcb3veoaac1L0ejWQvrZIk+vLO8/C3pKybPJ2lw6TefZBkppzUvRa16gAaGa5hOyy+csBzYvv2x7S2DS536OJsUF2fJrYJ8/qj2tiOyWrjaLpfVZNPtZpYjslq41y4Ga6mnNSPHrUkz7zuOVfzTuOD2iu2eeec940IKhH3O+l72auLMZfzVd3FoqcGHJcEARBEARBEARBEARBEARBEARBEARBKJXEBW1BEARBEARBEARBEARBEARBEARBEAShVBLv0BYEQRAEQRAEQRAEQRAEQRAEQRAEQVCVthj2vSSJJ7QFQRAEQRAEQRAEQRAEQRAEQRAEQRCEUklc0BYEQRAEQRAEQRAEQRAEQRAEQRAEQRBKJTHkuCAIgiAIgiAIgiAIgiAIgiAIgiAIgoq0tMQzwyVJ/NqCIAiCIAiCIAiCIAiCIAiCIAiCIAhCqaQFSNSdCUEQ8iaRiF1UEARBEARBEARBEARBEARBEAQpLS0tdWfhvRe/aqq6s5Ano5E/qzsLRU4MOS4IgiAIgiAIgiAIgiAIgiAIgiAIgqAqbXFTQUkSF7QFoQzYelEzn9L+pJm0wtfE+DQ5NtDs+LJi23ZJ82Lr31RzY4Ps+DS5XB7Sq6rmnBS9bmlPAFEuyyJxLCi7RLksmzQ5NtDs+N6XOmXLv5oX34Dmml8uNTE20Oz4NLlOEX3Wsut92Oc0MTbQ7Pjeh/pSEN4n4h3agiAIgiAIgiAIgiAIgiAIgiAIgiAIQqkkntAWBEEQBEEQBEEQBEEQBEEQBEEQBEFQkZa2eGa4JIlfWxAEQRAEQRAEQRAEQRAEQRAEQRAEQSiVxAVtQRAEQRAEQRAEQRAEQRAEQRAEQRAEoVQSQ44LgiAIgiAIgiAIgiAIgiAIgiAIgiCoSktL3Tl4r4gntAVBEARBEARBEARBEARBEARBEARBEIRSSVzQFjTCjBkzuH37trqzwbp169i7d6+6syEIgiAIgiAIgiAIgiAIgiAIgiAIGkEMOV5K2Nra8v3339OtWzfs7e0JDQ3lzp07LFu2jNOnT7/z8p2dnfH398fb25u7d+8WQY5LxowZM5g5c2a+38+ePZtFixbx66+/llzGSolrp7dw6ega4qLDsLF3o/MnU3H2qJ9nev8n1zi2bR6hr3wxNrOhWZfhNGjTXy6Nz41jnN67nKiwl5hbO9Guzxg863Uo0Hp9bh7n5tntBL14SFJ8NCNm7sXOyfOd45VIJJzd/xs3z+0gOTEWe5dadPt0Ojb27vnOVxQxndn3Kw+uHSY28jU6unrYOVenXZ8xOLjWfue4VFm/oqLYlhcO/cGjmycID36Orn55HN3q0OHD8VjZuRRJTFnUud2Kqywq5uHikTXER4dhbe9GlwFv2XaPr3F02zzCXvlibJ7/tosMfYmFTe7Yr53eyo0zW4kOfwWAtb0brXt+hXutliK2AsSmqfvcu7BoXh+X8Z9jWrcG5SvZcKPvaEL+OaXubMkR5TJHbGWsXGry8UCTyyWob9tlpKdxeu8vPLt3jqiwQMpVMMLFqyntPxyHibltmYpF1XXfOLud+1cPEvzCh9TkBCb9do0KBiZlLtaS2Oc0ub7U5DpFIpFw7h/5ctl1oGrl8sy+7O3Tts8YPOvKl8vrp7dw6Vh2uejUP/fvFhbkx8ldi3jx9DqSzEys7d35aORSTC0rFVl8mrrfaXJsok5RiK8M1SmaHpsml0tNqlNKc/syKjyQX75rr3T9H41aRvUGnd/b2JRRR51yZt+vnN3/u9w8RiZWTPzl3wLnX1ADbfHMcEkSv3Yp4OzszM2bN2nbti3fffcdNWvWpHPnzpw5c4bff//97QvQELq6ue+vWLRoERUrVsz1WbduHVFRUWzZsgWAhIQEIiMjSzrLavXg2mGObp1Li+4jGTlzL07u9dm89EuiI4KUpo8KC+TvpSNwcq/PyJl7adF9BEe2zMHnxjFZmgDf2+xcNY7aTXsyctZ+ajftyc5VYwn0y74JQpX1pqUk4ehel/Yfji/SmC8e+YvLx9fT9dNpfDFtJ0am1mxcNIyUpPg85ymqmCwrVqbrwGmMmv0Pw6b8jZmVPZuWfE5C7LuXO3VtS/8n12nQdgDDf9jO4PFrycxIZ9OS4aSmJL5zTDmpc7sVV1mU5eHqYY5umUvL7iMZOWsvzh712bwk/223eekInD3qM3LWXlp0G8GRv5Vsu5XjqNWkJ6Nm76dWk57sWCkfu6mFLe0/HM+XM3bx5YxdVPFszNblXxH66pmITZXYNHyfexc6hgbE3nvCw29nqzsrSolyKR9bWSuXmno80ORymUVd2y4tNZngFz607DGaETN20+/rX4kI8Wfr8tFlLhZV152WmoxbjRa06Dai0DGWhliLdZ/T8PpS0+sUWbkcOI0vftiJkYk1mxa/vVzu+kOa/5EzpfnftWosgc8VyuW2ubToNpIRM6Tl4u9lXxKT43eLDH3JunkDsLJzYcjEjYyctZ+W3Uehq1eu6OPTsP1Ok2MTdUru+MpKnaLRsWl4uQTNqlNKc/vS1MKO8UsvyH1a9/ofeuUMcKvZ4r2OTZG66hQAG3t3Jiy7IPuM/vGfAudfEN4H4oJ2KbBixQokEgkNGzZk9+7dPHv2DB8fH5YuXUrjxo0B6UVviURC7drZT4OampoikUho1aoVAGZmZmzevJnQ0FASExN5+vQpQ4cOBcDf3x+AO3fuIJFIOHPmDABaWlpMmzaNgIAAkpOTuX37Np06dZKtI2u9H330EefPnycxMZFr167h7u5O/fr1uX79OnFxcRw5cgQrKyu5uIYOHYqPjw9JSUk8evSIUaNGKV3umTNnSEpK4tNPP8312yQkJBASEiL3adeuHYMGDaJ///74+voCuYcczxr6e/r06YSEhBATE8OqVavQ09OTpdHS0uK7777j2bNnJCcn8+LFC6ZOnSr7vkaNGpw6dYrExETCw8P5448/MDQ0lH2vra3N4sWLiYqKIjw8nPnz56OlpZUrhokTJ+Ln50diYiJ37tyhb9++yopBgV0+tp66LfpSr+VHWFdypcuAqZhaVOTGma1K0984uw1TSzu6DJiKdSVX6rX8iDot+nDp2FpZmisnNuLq1ZQW3UZgbedCi24jqOLZmCsnNhRovbWbfkDrnl/h4tWkSGIF6V15V05spGX3kXjV64itgwe9P59HWmoy968ezHO+ooqpVuMeuFZvioWNIzb27nTqP5mUpHhCAp+8c2zq2paDxv1FneZ9sLF3p6JTNXoNm0tMRBBB/g/fOaYs6t5uxVEWc7p0fD11WvalXqvsPJhYVOT6aeXb7voZhW3XSrrtLh7N3naXj2/EpXpTWnaXxt6y+whcPBtzOUfsVb3b4lG7FVYVq2BVsQrt+45Fv7wBAQoNYhGbcpq8z72rsGPneTpjGa/3nVB3VpQS5TJbWSuXmnw80ORyCerdduUNjBk8YS01GnbBys4FR1dvug78geAXD/M8sVRaY1F13U06DqFFty/feRQgTd7nNL2+1OQ6RSKRcPXkRlp0G4lnvY7YOHjQS4VyefVk9vaxyrF9rubI/5Xj66nToi9135SLzp9Iy8X1s9m/2+k9y3Cv2YoOH03EztkLc2tHPGq3xtDEssji09T9TpNjE3WKvLJUp2hybJpeLjWpTint7UttbR2MTa3lPo9vnaRGgy6UK2+oNG/vQ2zKqKtOURaLoYlFgfMvCO8DcUFbzczNzencuTO///47iYm573aLiYlReVk//vgjXl5edOnSBU9PT0aNGkV4eDgADRo0AKBdu3ZUrFiRPn36APDtt98yfvx4JkyYQK1atTh27Bj//PMPbm5ucsueNWsWP/30E3Xr1iU9PZ2tW7eyYMECvv32W1q0aIGrqyuzZ2c/zTV8+HDmzJnD999/j6enJ1OnTuXHH39k8ODBcsudP38+y5cvx9PTk2PHjvE2devWZfXq1UyePJnjx4/nm7Zdu3Z4enrSpk0bPvnkE3r37s2MGTNk38+dO5dJkybJfrcBAwYQEhICQIUKFTh69ChRUVE0aNCAjz76iPbt2/Pbb7/J5h8/fjzDhg3j888/p3nz5lhYWNC7d2+5PPz000989tlnjBo1iurVq7N06VI2b95My5bvNgxRenoqQS8e4lq9mdx01+rNCPBV/i7xAL87udK7VW9OkP9DMtLTstPUUEhTozkBfncKvd6iEhUWSHxMmNy6dfX0qVy1Qb7rLo6Y0tNTuXluO+UqGGPrWK2QEWUvSx3bUpnkpDgAKhiaFjSMPJWm7VbU0tNTCfZ/iJuyPPgpz0Ogsm1XQ37bKUvjWqM5Ab53lC4zMzOD+1cPkZqSiKOrd+GCUaDpsWnyPqfJRLmUV9bKpaYeDzS5XGYpbdsuOTEOtLQoX4hhuNUZS2HXXVilbbsVFU2vLzW9TokOz7tcBuYRH0i3j0uu3yQ7/xl5lAsXr2YEvikXksxMnt07i0XFymxe8jkLxzTlr58+5vGtk0UUnebud6C5sYk6JbeyUqdoemyaXC5Bs+qUsta+DPJ/wOuXj6jT8u0PXGlybIrUXadEhLxg0dgWLJ3Yjp0rxxEZGlDgGAQ10dIqvR8NJN6hrWZubm5oa2vz+PHjd16Wk5MTt2/f5ubNmwC8ePFC9l1YWBgAERERsou2ABMmTGD+/Pls374dgMmTJ9OmTRvGjBnD119/LUu3aNEi2QXkX375hW3bttG2bVsuXboEwJo1a2RPgwNMmzaN8ePHs3fvXkD6hLiXlxcjRoxg48aNsnTLli2TpXkba2tr9u7dy549e1i8ePFb06empjJs2DCSkpLw8fFh+vTpLFy4kGnTpmFoaMi3337L119/LcvP8+fPuXjxIgADBw6kQoUKDB48mMTERB4+fMjXX3/NgQMHmDRpEqGhoYwZM4a5c+eyZ88eAEaOHCn3dLuBgQHjxo2jbdu2XLlyBYD//vuP5s2bM2LECM6fP58rz/r6+pQr9/bhzhLjopBkZmBoKn8nuaGJJfEx4UrniY8Jw9CkuXx6U0syM9JJjI/C2MyG+JjwXHenS5cZVuj1FpX42DDZuhTXHZPPEzpFGdOTO2fY9cd40lKTMDa1ZvCEtRgamxc6poKuPzumd9+WiiQSCce2z8PJvR62Dh7vEJFCXkvBdisuiXFRZGZm5Mqnkakl8Q/y3nZGpgrbziT3tjNSXKaSbRcS8IS/5nxCeloK+uUM6P/1b9jYy9+MVFiaHpsm73OaTJRLeWWtXGrq8UCTy6Usv6Vo26WlpXBy12JqNupO+QpGZSqWwq67sErTditKml5fanqdkrU+xbyoUi6V5j9WvlzmSmNqid+b3y0hLoLUlEQuHl5Nm97f0v7DCfg+uMD2Ff9jyMQNVK7a8N3j09D9DjQ3NlGn5FZW6hRNj02TyyVoVp1S1tqXty7sxsrOFSe3um8LTaNjU6TOOsXBpTZ9vpiHpW1l4mMjOH9gJWvmfMJXcw5gYPRu550FoSBGjRrFxIkTsbOz4+HDh4wZM4Z//837Xe76+vpMnz6dTz/9lIoVKxIYGMicOXNYt25dseVRXNBWs6whqiUSyTsva+XKlezevZu6dety/Phx9u3bx+XLl/NMb2xsjL29vewibpaLFy/KDW0OcO/ePdn/sy6I379/X26ajY0NAFZWVjg5ObFmzRpWr14tS6Orq5vrifMbN26oFJuuri67du0iJCSE4cOHqzTP3bt3SUpKkv19+fJljI2NcXR0xNbWlvLly3Pq1Cml83p6enL37l25p+YvXryIjo4OVatWJTk5mUqVKsn9vhkZGdy4cUO2Tb28vKhQoQInTpyQW7a+vr7c8Og5TZkyhZkzZ6oUH4AWCnfaSMj37ptcQ6JLZF/kv0yFaQVdb2Hcu3yAAxuzn6gfOGaVdN3K1vOWdRdVTFU8GzFy5l4S46O4dW4nO1eOYfgPO3I1TApDXdsyy+HNPxIS8IRhU7aolN+8lMbtVtwUY5NIlORLfo68FpTnMqVzyU+ztKvCyFl7SU6MxefGcfb+NZnPJm8q0pOOGh2bhuxz7yNRLnOkL8Xl8n07HmhSuSyt2y4jPY1dq8YhkUjoNmhGru+VKY2xFGbdqiiNsRYnTaovldGUOuXelQMczFEuB3y7Kle+QBrfW8uP4jxvIlBIlOdyJZmZAFSt05YmHYcCUNHJkwDf29w8u61QF7Q1eb/T5NiUEXVKrjnyWlCey5TOJfqsom+gnCbVKaUxFlXXnZaazP0rB2nVY1Tu9Gh2bKpSR53iXit7JFdbwNHNm1++68idi/to2ukzlfItCO/q448/ZtmyZYwePZqLFy8yYsQIjhw5gpeXFwEBykcM2LFjB7a2tnz++ef4+vpiY2ODrm7xXnIWF7TV7NmzZ2RmZuLp6cn+/fvzTJf5pvOVswLM+T5ogKNHj+Ls7Ey3bt1o3749p06d4vfff2fixIn55kHxYrqWllauaWlpabnSK07T1paOYJ/17xdffMHVq1fllpORkSH3d0JCQr55y7J8+XI8PDyoX78+KSkpKs2TF4lEInehWxllv0HO+VWR9Tt069aNV69eyX2XVwxz585lyZIlctNiY2NzpTMwNkdLWyfX3YUJcRF5Xlw1MrXOnT42Am0dXQwMzd6ksSI+VskyTa0Kvd7CqurdBnuXWrK/M9JTAeldfsZmNnIx5LfuooxJv5wBlrbOWNo64+jqzfLJnbh9YRctuo0oXJAFXH92TO++LXM6/PePPLlzms8mb8bUomKhY4HSud2Ki4GxOdrK8hAbkesu0yyqbrs4hTTxsREYKmw7XV19LG2dAbCvUpMg/wdcObGRnkNn8640PTZN2ufeJ6Jcyivt5fJ9OR5oYrksjdsuIz2NnSvHEh0WyJDv1qv8dHZpisXIxLpQ61ZVaYq1OGlifZmTptUpVWu3wWFGdrlMz6NcJr6l/BiZWimN0chEoVwqbsMc5d3A2BxtHV2s7eQvNlnZuRLge7MQ0Wn2fqfJseUk6pTcSnOdkpOmx6Zp5VKT6pTSFEtB25c+N46RlppM7aa93rvY3kbddUpO+uUMsHHwICLkRSEiEUqalnbpfauzstGAU1JSSE1NzZV23LhxrFmzhjVr1gAwduxYOnXqxKhRo5g6dWqu9J06daJVq1a4uLgQFRUFyI8YXVxK76/9noiKiuLYsWN89dVXGBgY5Pre1FT6jpKsIcPt7Oxk33l7e+dKHx4ezoYNGxg0aBBjxozhyy+/BJAVUh0dHVnauLg4Xr16RfPm8kNjNG3alEePHhU6ptDQUAIDA3FxccHPz0/u4+/vX+DlffHFFwwbNow+ffrkujCcn9q1a1O+fHnZ340bNyYuLo7AwECePXtGYmIi7dq1Uzqvj48P3t7ectukWbNmZGRk8PTpU2JjYwkKCqJx48ay73V0dKhXr57cMpKTk3Fycsr1OwQGBipdb2pqKnFxcXIfZXR19ankXB0/n0ty0/0eXsLRrY7SeRxdvfF7qJj+IpUqV0dHVy/vNA8uyt4DVJj1Fla5Ckayi8eWts5YV3LDyNRabt3p6an4P7me77qLMyYJEtLTch8ACkJd2xKkN2cc2jybRzdPMOS79ZhbO7xTLFA2tltR0dXVx65y9Vz5fO5zCUdX5XlwcPXmuUKefRW2nYOrN8+VbF9HN+988yORSGSdjXel6bFp0j73PhHlUl5pL5fvy/FAE8tladt2WRezI0JfMHjCugINu1eaYjG3dijUulVVmmItTppYX+akaXVKuQpGWNg6yz5Z5TJnfjPelEuHPOID6fZRjPF5jvzrvCkXijE+97mEw5tyoaOrT6XKNYh4/Z9cmsgQf0wtKxU6Pk3d7zQ5tpxEnZJbaa5TctL02DStXGpSnVKaYilo+/LWhV1U9W6DoYnFexfb25SmOiU9LZXwYD+MTa0LEYkgZJsyZQqxsbFynylTpuRKp6enR7169WSvHM5y/PhxmjZtqnTZPXv25MaNG3z33XcEBgby5MkTFi5cKHc9rjiIC9qlwOjRo9HR0eHatWv06dMHNzc3qlWrxv/+9z/ZkNbJyclcvnyZyZMn4+npSYsWLfjpp5/kljNr1ix69uyJq6srXl5edO/eXXZhOjQ0lMTERDp37oyNjQ0mJiYALFy4kEmTJvHxxx/j4eHB3Llz8fb25pdffnmnmGbOnMmUKVP45ptvcHd3p0aNGgwdOpSxY8cWaDlNmzbl119/Zfbs2Tx//hxbW1u5T1Ycyujr67NmzRo8PT3p3Lkzs2bN4rfffkMikZCSksL8+fNZsGABgwYNwsXFhUaNGjFs2DAA/v77b5KTk9mwYQPVq1endevW/Prrr2zatInQ0FBA+i7xyZMn06tXL6pWrcqKFSswMzOTrT8+Pp5FixaxdOlSBg8ejIuLC97e3owePZrBgwcX/EdV0KTTUG6d38WtC7sJC/Lj6Na5xEQGU791fwBO7lrMntWTZOnrt+5PTEQQR7fNJSzIj1sXdnPrwm6adhomS9OowyD8Hl7k38OrCQt+zr+HV/P80WUadxii8noBEuOjCX75iLAgPwAiXv9H8MtHxOXxXh5VaGlp0bjDYC4c/INHN08QEviUfWumoKdfnpqNusvS7Vk9iZO7st+xXhQxpaYkcnL3EgL87hAd/oqgFw/Zv+4HYiNfU71B50LHpOr6i2tbHto8m3uXD9B3xCL0yxsSFxNGXEwYaanJ7xxTFnVuNyiesphT045v8nBemocjW+cSExFMgzbSPJzYKb/tGrTpT3R4EEe3vtl253dz+/xumnXO3naN38R+4ZA09guHVvPc5zJNcsR+ctcSXjy9QVR4ICEBTzi5eyn+j69Rq0mPIolL02PT5H3uXekYGmBSuxomtasBYFDFAZPa1SjvaPeWOUuGKJdlt1xq8vFAk8slqHfbZWSks2PFtwT5P6DvFwvJlGTIymh6IU4aqzMWVdcdFxNG8MtHRIa+BCA08CnBLx+RGB9dZmKF4t3nNL2+1OQ6RUtLi0btB3Ph0B88unWC0MCn7Fubu1zu/WsSJ3fnKJfts7dPeI7t0yhH/ht3HMqtC7u4nVUutr0pF62yy2XTzp/z4PoRbp7bQWTIC66d2syTu2do0GZAkcWnqfudJscm6pSyW6docmyaXi41qU4pC+1LgIiQF7x4eoO6LT8SseVBXXXKsW3z8X98jaiwQAL97rL9929ISYrHu1mvd4pHEObOnYuJiYncZ+7cubnSWVlZoaurK3vVcJaQkBAqVlQ+SoeLiwvNmzenRo0a9O7dmzFjxvDhhx/y+++/F0ssWcSQ46WAv78/devW5fvvv2fx4sXY2dkRFhbGzZs3GTUq+70Pw4YNY+3atdy4cYMnT57w3Xffyb2fOTU1lblz51K5cmWSkpK4cOEC/ftnnQzK4JtvvmH69OnMnj2bCxcu0KZNG5YvX46JiQmLFy/GxsYGHx8fevbsia+v7zvFtGbNGhITE5k4cSILFiwgISGB+/fvs2zZsgItZ/jw4ZQrV445c+YwZ86cXN+vX7+ezz5T/i6JU6dO8ezZM86fP0+5cuXYtm2b3Pupf/zxR9LT05k9ezaVKlUiODiYVauk7wZJSkqiU6dO/PLLL1y/fp3ExER2797NuHHjZPNnbav169eTmZnJ2rVr2bt3r+ypeoBp06YRGhrKlClTcHFxITo6mlu3bvHzzz8X6HdQpkbDriTGR3Pun9+JjwnDxt6dgWP+wMzKHpCeDIuJDJKlN7d2YODYPzi6dR7XT2/B2MyGLgO+x6t+J1kaJ7e6fDhyMaf3/MLpvcuxsHHkw5FLcHCtrfJ6AZ7cOc3+tdlDUexaJf3dWvX8ija9/lfomJt1GU5aajKHNs8mKSEGB5daDBq/hnI5hp2MiQxCSzt7aP6iiElLW4fw4P+4e/EbEuOjqGBohn2Vmgyb8jc29u6FjkfV9RfXtrxxZisA6+fL32DxwbCfqdO8zzvHlUVd2w2KryzK8tCoK4kJ0jzEZeVhbHYe4mPCiImQ33afvtl217K23UCFbeeeHfuZvcsxt3HkI4XY42Mj2PPnd8TFhFG+gjG2jlUZNH41rtWbvXNM70VsGr7PvQvTejVocmqT7G+vRdL9J2DjHu59nvsuzpImymXZLpeaejzQ5HKZRV3bLjbqNU/unAZg1cxecnka8t0GqlRrVGZiUXXdN85s49w/2ScB1s37FJDuk3TqW2ZiLdZ9TsPrS02vU5p1GU56WjKHc5bLcUrKZY7XrTm61eXDEYs5vfcXzux7s31GLMHBRb5cJsVHc+5AjnLxrXy59Kzbge6DZvLv4T85unUOlhWr8PHo5Ti5Z4+0VhTxaeJ+p8mxiTql7NYpGh2bhpdL0Kw6pbS3LwFu/7sbEzPbApdTTY5NkbrqlNioEHb9MZ7EuGgMjM1xcK3N8B+2y/0WQimmVXqfGU5NTVU6vHheVHk1cRZtbW0kEgkDBw6UvTJ33Lhx7Nq1i6+++ork5OJ5eEcLUO2FwIJQhqxbtw4zMzN69+6t7qy8M4lEwtaLmrmbftJM2tjRxPg0OTbQ7PiyYtt2SfNi699Uc2OD7Pg0uVwe0quq5pwUvW5pTwBRLssicSwou0S5LJs0OTbQ7Pjelzply7+aF9+A5ppfLjUxNtDs+DS5ThF91rLrfdjnNDE20Oz4NL2+zHkDoKAeiZtyP4RZWhgM+l6ldHp6eiQmJvLRRx+xb98+2fRly5bh7e1N69atc82zfv16mjVrhrt79sN+1apV49GjR7i7u7/zA7N5Kb23DwiCIAiCIAiCIAiCIAiCIAiCIAiCIAhFLi0tjZs3b9KhQwe56R06dODSpUtK57l48SKVKlXC0NBQNs3Dw4OMjAwCAwOLLa/igrYgCIIgCIIgCIIgCIIgCIIgCIIgCIKqtLVK76cAlixZwvDhw/nss8+oVq0aS5YswcnJSfaK3p9//pkNGzbI0m/ZsoWIiAjWrVuHp6cnLVq0YOHChaxdu7bYhhsH8Q5tQUPl9V5tQRAEQRAEQRAEQRAEQRAEQRAEQRBgx44dWFpaMn36dOzs7Hjw4AFdu3bl5cuXANjZ2eHk5CRLn5CQQIcOHfj111+5ceMGERER7Nixgx9++KFY8ykuaAuCIAiCIAiCIAiCIAiCIAiCIAiCILyHVq5cycqVK5V+p+wB0idPntCxY8fizpYccUFbEARBEARBEARBEARBEARBEARBEARBRVpa4q3OJUn82oIgCIIgCIIgCIIgCIIgCIIgCIIgCEKpJC5oC4IgCIIgCIIgCIIgCIIgCIIgCIIgCKWSFiBRdyYEQcibRCJ2UUEQBEEQBEEQBEEQBEEQBEEQpLS0tNSdhfde0rb56s5Cnir0n6TuLBQ58YS2IAiCIAiCIAiCIAiCIAiCIAiCIAiCUCrpqjsDgiC83daLmvmU9ifNpHeRaWJ8WbHtvZah5pwUj94NdQB47Beo5pwUvWquDoBml8s7HVuoOSfFw/v4BQAuPYpTc06KXlNPYwC2XdK8ctm/qbRcHtKrquacFI9uaU8AzS6XZx8kqTknRa91jQoA3GjVRM05KR71z10G4PKjWDXnpOg18TQBNPs4fua+5u1zAG1qSve7xIu71ZyTomfQrC+gmeUSssvmyPlRas5J0Vs1yRyAJ34Bas5J0avq6ghoZp8Osvt1mtgnz+qPa2I7JauNoul9Vk0+1p26n6zmnBS9djXLA7DvuubVJwC9GkjrFE1sp7wP554F4X0iLmgLgiAIgiAIgiAIgiAIgiAIgiAIgiCoSksMgl2SxK8tCIIgCIIgCIIgCIIgCIIgCIIgCIIglErigrYgCIIgCIIgCIIgCIIgCIIgCIIgCIJQKokhxwVBEARBEARBEARBEARBEARBEARBEFSlJd5lXpLEE9qCIAiCIAiCIAiCIAiCIAiCIAiCIAhCqSQuaAtCCXJ2dkYikVC7dm11Z0UQBEEQBEEQBEEQBEEQBEEQBEEQSj0x5Ph7ZN26dQwdOhSAtLQ0IiMjuXfvHlu3bmX9+vVIJBL1ZvCNVq1acfbsWczMzIiJiVF3dgCQSCT06tWL/fv3F0m64iKRSDi7/zdunttBcmIs9i616PbpdGzs3fOdz+fGMU7vXU5U2EvMrZ1o12cMnvU6yKW5dnoLl46uIS46DBt7Nzp/MhVnj/oAZKSncXrvLzy7d46osEDKVTDCxasp7T8ch4m5bZmKRdV1H9gwnec+l4mLDkW/nAGObnVo/9EErO1cChWvossnt3L+0FriYsKwtXej+6eTqVK1fp7pnz+6zqEt8wl55YuJmQ0tuw2jcbv+su8fXD/BmQN/EhHykoz0dKwqOtGiy2fUbd6zSPL7rg4f3M/e3TuIiozAybkyn385muo1ailNe/niBY4c+of/nvuRlpaGk7Mz/QcOoW69BiWca6m3lSdF/k+ucWzbPEJf+WJsZkOzLsNp0Ka/XJq3lWP/J9e5dHQNQf4PiY8Jo9/Xv+FZt32xxZgfyx69sPnoE/QsLEl+4c+rlctJeHAvz/RWPXpj9UEf9G3tSA0NIWTrRqJOHivBHKvu9OGdHNm3ieiocOwdXRjw+Xg8qtdRmjY6Mpxt65bywu8RIcEBtO/WnwHDx5dwjrNdO72Fi0fWEB8dhrW9G10GvKVcPr7G0W3zCHvli7F5/uUyMvQlFja5y+W101u5cWYr0eGvALC2d6N1z69wr9WyeIIsIIvm9XEZ/zmmdWtQvpINN/qOJuSfU+rOVoGV5XKpirNHt3N8/wZiosKp5OjKx59NxN2rrtK0MVFh7Fy/mJfPHxEa/JI2XT+h37DvSjjHqrPu1YeK/QeiZ2FJkv9/BPy2jPh7d/NJ3xebPh9SrqIdqSGvCd68gYhjR0owx6o7dXgnR/ZtzlEux1E133K5DH9ZuezHwBIql+o4Zquy3jP7fuXBtcPERr5GR1cPO+fqtOszBgfX4r8J9uzR7Zz4J3uf+2ho/vvcrg3y+9zHn5XefW7H6StsOHqB8Og4XO1tmPBJN+p6VHnrfHeevWD4/NW42tuyfdb/SiCnuamzL6TO8phT92blaV67HAbltfAPTmfriUSCwzPzTO/toUeXxuWxNtdGR1uL0KgMTl5P4erD1BLM9dsdPrifPbt3yvo9w78cTfUaNZWmvXTxAkcOHZDr93wycLDa+j2qKMv9OkXvU59ck9sooNl91rJ8rFPFuaPbOfnPemKiwrFzdOWjod/hlk87ZfeGxbx87kNY8Etadx3AR6WknXL5xFbOHV5LXLS0Punx6WSqVMu/Pjn4d3Z90qq7fH2S053Lh9n6+wS86rVlyNjfiisEOeL8s+acfxaKgLZ4ZrgkiV/7PXPkyBEqVqxI5cqV6dKlC2fOnOGXX37h4MGD6OjoqDt76OqKeyzexcUjf3H5+Hq6fjqNL6btxMjUmo2LhpGSFJ/nPAG+t9m5ahy1m/Zk5Kz91G7ak52rxhLol915eXDtMEe3zqVF95GMnLkXJ/f6bF76JdERQQCkpSYT/MKHlj1GM2LGbvp9/SsRIf5sXT66zMWi6rrtnKvzwbCf+WrOIT4d/xcSJGxa/DmZmRmFjjnL3StHOLh5Lm0+GME3P+6mctV6rFs4gujwIKXpI0MDWbdoJJWr1uObH3fTuueXHNj0M/evH5elqWBkSpueIxg9fQtjft5LvZZ92LX6e57e+/ed8/uuLpw7w5o/V/BRvwEs/fUPvKrXZPb0KYSFhihN//DBPbzr1GP67J9ZsnwlNWt5M2fWDzz3e1bCOVetPOUUFRbI30tH4ORen5Ez99Ki+wiObJmDz43szrEq5TgtJQlbx2p0/XRasceYH7NWbbEf+Q0hWzbxZNTnJNy/i8uchehZ2yhNb9m9F3bDRvB60zoefzGI15vW4vD1OEwaNy3hnL/d1X+Ps2XtYrp/NIxZS/7Gw6sOS378hoiw10rTp6elYmxqTvePhuFYOf+OT3F7cPUwR7fMpWX3kYyctRdnj/psXpJ/udy8dATOHvUZOWsvLbqN4MjfSsrlynHUatKTUbP3U6tJT3aslC+Xpha2tP9wPF/O2MWXM3ZRxbMxW5d/Reirkt83ldExNCD23hMefjtb3VkptLJcLlVx/eIxdqxbSNe+w/lh0TbcPOvw65yviAwLVpo+LS0VYxNzuvQdjkNljxLObcGYt2mH49djCN60Hp8vhhB/7y7u85egb6P8xIv1B71x+HIUQev+4sGQAbxa9xdOY8Zj2rR5Cef87aTlcgk9PvqM2Us24+HlzZIfv82zXKalpWJsakaPEi6X6jpmq7Jey4qV6TpwGqNm/8OwKX9jZmXPpiWfkxAbWXw/CHDj4jF2rl9Ilz7D+X6hdJ/77ef89zkjE3O69BmOg3Pp3ueOXbvHwq2H+Lx7a7bO/Jo67pX5eukGgiOi850vLjGZaX/tpKGna8lkNA/q7Aupqzzm1LFROdo1KM+2k4nM2xhLTIKEbz82ppx+3vMkJkk4cjmZBZvj+HFdLJfvpzK4qwFeVUrPOYYL587w158r+bjfAJb9ugqv6jWZlW+/5z7edeoxY/Ycli5fQc1a3vw0axp+auj3qKIs9+sUvU99ck1uo4Bm91nL+rHubW5cPMqu9Qvo3OcLpizcjptnXX7/eXSe7ZT0N+2Uzn2+wL4UtVPuXjnCgc1zadtzBN/8JK1P1i4cQVQ+9cnarPrkp9206fkl/2z8mfvXjudKGxX+ikNbFlKlar3iDkOOOP+sGeefBaEsEhe03zMpKSmEhIQQFBTE7du3mTt3Lh988AFdu3aVPb0NYGJiwh9//EFISAgxMTGcOnWKWrWy76qdMWMGt2/f5ssvv+Tly5ckJCSwY8cOTE1NZWnq16/P8ePHCQsLIzo6mrNnz1KnjvyTGhKJhBEjRrBv3z7i4+P566+/OHv2LADR0dFIJBLWrVsHwJkzZ1i+fDlLly4lMjKS169f88UXX2BgYMDatWuJjY3F19eXzp07y63D09OTQ4cOERcXx+vXr9m4cSOWlpay77Mu6s+fP5+IiAiCg4OZMWOG7Pv//vsPgH379iGRSGR/q6JBgwbcunWLpKQkrl+/niv+oiSRSLhyYiMtu4/Eq15HbB086P35PNJSk7l/9WCe8105sRFXr6a06DYCazsXWnQbQRXPxlw5sUGW5vKx9dRt0Zd6LT/CupIrXQZMxdSiIjfObAWgvIExgyespUbDLljZueDo6k3XgT8Q/OJhnicJS2ssqq67fut+VK7aAHMrByo5V6dt7zHERgbLnkx8F/8eWU/9Vn1p2PpDbOxd6fHpFEwt7bhyapvS9FdPb8fMyo4en07Bxt6Vhq0/pH6rPlw4vE6WxtWzITXqt8fG3hVLWyeadxpERUcP/J/eeuf8vqv9e3fRvmMXOnbuhqOTM8NHfIWVtQ1HDh1Qmn74iK/o81F/3D2qUcnegUFDh2NXyZ5rVy+XcM7fXp4U3Ti7DVNLO7oMmIp1JVfqtfyIOi36cOnYWlkaVcqxe62WtOszBq96HYs9xvxY9+1H5NFDRB49SErAC16t+pW0sFCsevRWmt6iXUciDv9D9LnTpL4OJvrsKSKPHsTm44ElnPO3O77/b1q2/4BWHXpRybEKA4aPx8LKltNHdylNb2VbiYHDJ9CsTXcqGBiVcG7lXTq+njot+1KvVXa5NLGoyPXTysvl9TMK5bKVtFxePJpdLi8f34hL9aa07C4tly27j8DFszGXc5TLqt5t8ajdCquKVbCqWIX2fceiX96AAL+8n+4oSWHHzvN0xjJe7zuh7qwUWlkul6o4eWATzdr2pnn7Ptg5uNBv2HeYW1bk3LGdStNb2djT7/NJNGndo9THZ/vxJ4QfPkD4oQMkv3hBwG/LSA0LxfqDPkrTW3bsQtg/+4g6c4rU4CCiTp8k/NBBKn7yaQnn/O2O7d8iVy4HvqVcWsvKZbcS3W7qOmarst5ajXvgWr0pFjaO2Ni706n/ZFKS4gkJfFJ8Pwi597mPP3uzzx3PZ58bNonGrXtQvpTvc5uP/UuvFvXo07IBLpVsmDigOxUtTNl55mq+8/20cS+dG9WmlqtjCeU0N3X2hUB95TGndvXLc+RyEneephEUnsmGQwno60FDz7yvaD8NSOfOszReR2QSHp3J6ZspvArNwNWh9FzQ3r93N+07dqZj5644OjnzxYjRWFnbcDiPfs8XI0bT96N+sn7P4KGfY1fJnutXr5RwzlVTlvt1it6nPrkmt1FAs/usZflYp4rTBzbRtG1vmr1pp3z02XeYWVbk/PEdStNb2tjz8Zt2SgUD4xLObd4uHFlPg9Z9adjmQ2ztXek5KP/65Mrp7ZhZ2tFz0BRs7V1p2EZan5zPUZ8AZGZmsG3FJDr0/RoLm5LbluL8s+acfxaEskhc0BY4c+YMd+7coU+f7MbqoUOHqFixIl27dqVevXrcunWLU6dOYW5uLkvj5ubGxx9/TI8ePejcuTPe3t78/vvvsu+NjY3ZsGEDLVq0oHHjxjx79ozDhw9jZCR/8mPWrFns37+fmjVrMn36dFk+PDw8qFixIt9++60s7ZAhQwgPD6dhw4b8+uuvrFy5kp07d3Lp0iXq1q3LsWPH2LRpExUqVACgYsWKnDt3jjt37lC/fn06d+6Mra0tO3bIN36GDBlCQkICjRo14rvvvmP69Om0by8dvrdBA+lwV0OHDqVixYqyv9/GwMCAgwcP8uTJE+rVq8fMmTNZtGiRSvMWRlRYIPExYbhWbyabpqunT+WqDQjwvZ3nfAF+d3Ct0UxumluN5gT43QEgPT2VoBcP5ZYL4Fq9Wb7LTU6MAy0tyhuYlKlYCrPu1JRE7vy7BzMrB0wsKhYoVkXp6am88vfBvaZ8Ht1rNOXFsztK53nhewf3GvJ3C7vXbE7gfw/JSE/LlV4ikeD78DJhwf75DplWEtLS0vDzfYp3Xfl8eNepx+NHD1VaRmZmJklJSRgbF7ysvYvC7BsBfndypXer3pwg/+xt9bZyXFpo6epi4O5B3K1rctPjbl7H0KuG8nn09clMTZGblpmaikFVTygFo4RkSU9Lw9/vMdW9G8tNr+7dGL/HeQ9NVxqkp6cS7P8QN2Xl0k95uQxUVi5ryJdLZWlcazQnwPeO0mVmZmZw/+ohUlMScXT1LlwwgpyyXC5VkZ6Wxku/R3h5N5Gb7lW7MX5PSsdNEYWlpauLoUdVYq/L15ex169ilMcws1p6emSmyg+Tm5mSgqGnF1qlsL6s4d1IbnoN70b4lqJyqa5jdmHWm56eys1z2ylXwRhbx2oqx1hQ6WlpvHz+CM/a8vucZ+3GPC/j+1xaejqPXgTRpLr8CACNq7tx1/dFnvPtv3CTwNBIRnzQtrizmK/S1K8rqfKYk5WpNqZG2jz6Lz07HxnwLCAdF3vVL05XddbF1kIH34D0tycuAWlpafj6PqWOQr+nTp16PH7ko9IypP2eRIyMS8+FmixluV+n6H3qk2tyGwU0u89a1o91b5N3O6VJmWqnpKen8uo/H9wVjs8e+dQnL5/dwUOhPvFQUp+c3LsCQ2NzGrbuW+T5zk9paqeAOP8slAJa2qX3o4FKz62qglo9fvxY9gR2mzZtqFmzJjY2NqS+aaROnDiRXr168eGHH7J69WoAypcvz5AhQ3j1SnpH0P/+9z8OHTrE+PHjCQkJ4cyZM3LrGDFiBFFRUbRq1YpDhw7Jpm/ZskX2FDZAlSrSd72Ehobmeof23bt3mTNnDgBz585l8uTJhIeH89dffwEwe/ZsRo8eTa1atbh69SqjRo3i1q1bfP/997JlDBs2jMDAQNzd3Xn2TDqU1b1795g9WzoEqa+vL19//TXt2rXj5MmThIeHA9InxkNClA+VpczAgQPR0dFh2LBhJCUl4ePjg4ODA6tWrcpzHn19fcqVK6fyOnKKjw0DwNDEUm66oYklMfncpRYfE650nvgY6fIS46KQZGZgaKosTbjSZaalpXBy12JqNupO+QoFf3pDnbEUZN3XTm/hxM5FpKUkYmXnwuAJa9HVzWccPBUkxkWTmZmBscL6jU0teZrH7x0fE46xQkzGJpZkZqSTEB+NiZk1IG3k/fxNa9LT09DW1uaDIdNwr6neYbNiY2PIzMzEzMxcbrqZuTlRUaoNa7hvz05SkpNo1qJVcWQxT4XZN+JjwjA0kR+KzdBUuq0S46MwNrN5azkuLXRMTNHS0SUtKkpuelpUFMbmFkrnibtxDcvOPYi5dIGkZ0+p4F4Vi05d0dbTQ9fUjPTIiJLI+lvFvdkPTczk4zA1teBBlPJtW1okxkWRmZmRqwwZmVoS/yDvcmlkqlAuTXKXSyPFZSoplyEBT/hrziekp6WgX86A/l//ho29WxFEJpTlcqmK+Ddl18RUPj5jM0tio8t2fLqmZmjp6pIWKX9cS4uKQs9CeX0Ze/0qVt17EP3vORKfPsGgajWsunaX1Zdppby+NDG1JCaqdOQR1HfMLsh6n9w5w64/xpOWmoSxqTWDJ6zF0Fi+fVSU8trnTEzL/j4XFZdIRmYmFqby/RBLE2MiYpQPZfwiJJzlu4+ydvIIdNV8waI09OtKujzmZGKkBUBsovz7smMTJFiY5n9irrw+zPvKDD0dyJTA1uOJPPIvHRe08+r3mJqbE12gfk8yzUu436OKstyvU/Q+9ck1uY0Cmt1nLevHurfJaqco7ldlrZ2SVZ8Ymebun8flEUdcTLjS9JkZ6STERWNibo3/01tcP7uHMT/vKba856U0tFOyiPPPgvD+ERe0BQC0tLSQSCQA1KtXDyMjIyIi5BtpFSpUwNU1+/0qL1++lF3MBrh8+TI6OjpUrVqVkJAQrK2tmT17Nm3btsXW1hYdHR0MDAxwcnKSW+6NGzdUzue9e9lPemRmZhIREcH9+/dl07IuONvY2MhiadOmDXFxcbmW5erqKndBO6fg4GDZMgrL09OTu3fvkpSUJJt2+XL+Q2dNmTKFmTNnqrT8e5cPcGBj9tDoA8dIL5RraWnlTqxsWs6vUfheIp361jRKlpuRnsauVeOQSCR0GzQj1/fKlMZYVFl31nB8cdFhXDq2lp0rxzBs6lb09Ap3U0J+65JIJMrzlD2DfHpp4HJT9csb8s2cPaQmJ+L78AqHtizAwsYRV8+G757fd6QYmkSSxzZQcP7sabb9vZGp02fnOnlSUlTdN2TpcwUr+yL/ZSpOKy0kErk/pWFIlCZ9/fd6dM0t8PjlD9CSnkiIPH4E234DoRS+/0dxO0iQvLUOKi0Uy5lEoqRcyc+R14LyXKZ0LvlplnZVGDlrL8mJsfjcOM7evybz2eRN4qJ2ESrL5VIlyg4IpbX+KzCF+pJcVahM0IZ16FlYUm3lX2ghrS/Djx7CbsAgJJmZymdSo7JSLtV1zFZlvVU8GzFy5l4S46O4dW4nO1eOYfgPO3LdTFTUch0v0Jx9Lle5lEiUbu6MzEym/rGdkR+0x7miVQnlLltp7AuVZHls6KXPgE4Gsr9/3yV9b6Ri/ailRV5NTJmUVJizLpZy+lpUc9blw7YVCI/O5GkpeUoblNUrqtWX586eZuvfm/h++iy19XtUUZb7dbm8V31yzW2jAO9Xn7WUHusKS1k7Jf9+bemUu+7Ivz5Rll46HVKSEti2chJ9h88qkZvNSmM7BcT552FTtwLl882jIGgicUFbAKQXX7PeDa2trU1wcDCtW7fOlS46OjrPZWRdEM/6d/369VhbWzNmzBhevHhBSkoKly9fRl9f/g6ihIQElfOZliY/VJNEIsk1LSuGrH8PHDjApEmTcqUJDg7Od7lZyygsVTptiubOncuSJUvkpsXGxipNW9W7DfYu2e81z0iXPk0fHxOOsVn2xfiE2Ih8TzwYmVoRHyt/p1tCXARGptIGroGxOVraOrnuhkuIy73cjPQ0dq4cS3RYIEO+W6/y3XGlKRYjE2uV113ewJjyBsZY2lbGwbU2879uxOObJ6jZuLtKcStjYGyGtrYOcQp5jI+NzDN2I1Mrpem1dXQxMDKTTdPW1sbK1hmASs6ehAY95+yB1WrtPJuYmKKtrU2Uwh3TMdFRbz2RceHcGX79ZRGTpkzHu0694symUgXZN7IYmVrnTh8bId1WhmZv0uRfjkuLjNgYJBnpue7c1zUzJ11he2aRpKYSsGQeAb8sRM/cgrTICCy79iQjIYF0hRE51Mn4zX4YEy1/Y1dsTBSmZsV7YeFdGRibo62sXMZG5Lo7OIuq5TJ3PROBoUK51NXVx/JNPWNfpSZB/g+4cmIjPYfOfpewBMp2uVSF0ZuyG6sQX1xMJCZlPL70mGgk6enoWcjHoWtuTnoeT61JUlPwnz+HF4vmoWthQVpEBNY9PnhTX0aXQK5Vk1e5jIuJxNRM+ZNP6qCuY3ZB1qtfzgBLW2csbZ1xdPVm+eRO3L6wixbdRhQ4XlVk7XPKtl1Z3+fMjQ3Q0dYmIkb+pubIuHgsTHL3TxKTU/Dxf8WTl8HM/1v6rt9MiQSJREL94T+wYvxnNPR0zTVfUSlNfaEsJVke7/qm8l9Q9gVn3TdnqUwNtYlNyL54ZGygRWxC/hfLJEBYtDRNYGgGFS116NSkPE8D4os83wWV3e+Rr/djoqNV7PcsZtKUaWrp96iiLPfrFL1PfXJNbqOAZvdZy9qxrqCy+wby+1VcTCTGZaidIqtPFOKIj4nM9RR2FmNTK6Xps+qTkFe+RIW9YsPir2TfSyTSY9+UwTWZsPAQlrbyD5O9i9LYThHnn6Xnn2ndQ6W4hWKmXfZusinLNHMgdaFA2rRpQ61atdi9ezcAt27domLFiqSnp+Pn5yf3yfnUtpOTE3Z2drK/mzRpQkZGBk+fPgWgRYsWLF++nCNHjuDj40NKSgrW1tZvzU/WMOc6RTD8za1bt6hevTr+/v65YklMTFR5OampqQXOj4+PD7Vr16Z8+ey7pRo3bpzPHNL1xMXFyX3yUq6Ckewkg6WtM9aV3DAytcbP55IsTXp6Kv5PruPoVifP5Ti6euP38JLcNL8HF2XvPNXV1aeSc3W55QL4Pbwkt9ysxkRE6AsGT1iHgZHqdwmWpljMrR0KtW6Q3imanp6ab5q30dXVx76yF74P5PPo++ASzu7eSudxdvPOlf7Z/Ys4VKmOjq5ePhmWkJ72bvl9V3p6eri6eXD39k256Xdu36SaZ/U85zt/9jTLly5g/MSp1G+Y/35VXFTdN3JSWkYfXqRS5ext9bZyXFpI0tNJfPYU47oN5KYb121Ags+D/GfOyCAtPAwyMzFv3Y7Yq5fyfgRADXT19KjsWo2Hd67KTfe5cxXXarXymKt00NXVx65y9Vxl6LnPJRxdlZdLB1dvniuUY1+Fcung6s1zJWXX0c073/xIJBJZJ1F4N2W5XKpCV08PJ1dPHt2VH83m0b2ruFatraZcFQ1JejoJT59gUl++vjSp35D4B/fzmOvNvBkZpIVJ60uLth2IvnyxTNSXD+9cw60UlUt1HbMLs94sEoq3naarp4eTiyeP7uXe51zK+D6np6uLp3Mlrvj4yk2/8tCX2m7OudIbli/HztnfsG3m17LPh60bUrmiFdtmfk1NF8dizW9p6gvlpTjLY0qq9CJ01ic4PJOY+Ew8K2c/f6GjDe6Oujx/VbAnrbW0QK+UjKqrp6eHm5sHd5T2e7zynO/c2dP8snQhEyZOpYGa+j2qKMv9OkXvU59ck9sooNl91rJ2rCuo7HbKFbnpj+9dKVPtFF1dfeyrePFMsX7Ipz5xcvdWkj67PrG2c2Hs3P18O2eP7ONZtw0ung35ds4eTC2L9t3Kpa2dIs4/F835Z0Eoq8QF7fdMuXLlsLW1pVKlStSpU4cpU6awf/9+Dhw4wMaNGwE4efIkly9fZt++fXTs2BFnZ2eaNGnCjz/+SL162XfLJicns2HDBmrVqkXz5s1Zvnw5O3bskA377evry6BBg6hWrRoNGzbk77//Vuki8osXL8jMzKR79+5YWVlhaGhY6Hh///13LCws2Lp1Kw0aNKBKlSp06NCBNWvWFOgJbH9/f9q1a4etrS1mZmYqzbNlyxYyMzNZs2YNnp6edOnShQkTJhQykrfT0tKicYfBXDj4B49uniAk8Cn71kxBT788NRtlPzG8Z/UkTu5aLPu7UYdB+D28yL+HVxMW/Jx/D6/m+aPLNO4wRJamSaeh3Dq/i1sXdhMW5MfRrXOJiQymfuv+AGRkpLNjxbcE+T+g7xcLyZRkEBcTRlxMWKEOsOqMRZV1R4YGcOHQHwT5PyA6IogA39vsXDkWPb1yuNd69/d9Ne8ylOtnd3H93G5CX/lxYPM8oiOCadSuHwBHty9h+6rJ2XG37UdUeDAH/55P6Cs/rp/bzY1zu2nR9TNZmjP//Mmz+5eICA0gNOg5F46s59bFf6jTTP13833Q+0NOHDvMyeNHCHj5gr/+XEF4WCidu0rztnHdXyxdNE+W/vzZ0yxbPI/Pho+kajUvoiIjiYqMJCGh5J+8eFt5OrlrMXtWZ48QUb91f2Iigji6bS5hQX7curCbWxd207TTMFkaVcpxSnICwS8fEfzyEQDR4YEEv3xEdD7v+CkOYbu3Y9G5OxadulLO0ZlKI/+Hno0N4Qf3AWA3bAROE7+XpS9n74h5u47oV3LAoKonzlNnUr5yFYLX/Vmi+VZFxw8Gcv7kPs6f3E9QwH9sXbOYiPDXtOnUF4Cdm35j9bLpcvO8fP6El8+fkJKcRFxsFC+fP+FVwPMSz3vTjm/K5XlpuTyydS4xEcE0aCMtlyd2ypfLBm36Ex0exNGtb8rl+d3cPr+bZp2zy2XjN+XywiFpubxwaDXPfS7TJEe5PLlrCS+e3iAqPJCQgCec3L0U/8fXqNVE/fUMgI6hASa1q2FSuxoABlUcMKldjfKOdm+Zs/Qoy+VSFe17DOLfU3u5eGofwYHP2bFuIZHhwbTs+CEAezcvZ93yH+TmCfjvMQH/PSY5OYn42CgC/ntMUICfOrKfr5AdW7Hq1hPLrt0p7+yM41ffom9jS9g/ewGw/2IUladmb7tyDo5YdOhEOXsHDKt54TJ9NhWquPBq9Up1hZCnTh8M4NzJ/Zw/+Q9BAf+xZc2SXOXyz2XywwC+eP6EFznK5YsSKJfqOma/bb2pKYmc3L2EAL87RIe/IujFQ/av+4HYyNdUb9C5WH+T9j0GcVFhn4vKuc/9nfc+l5KcRFxM6d3nPu3UnL3nb7Dvwg2eB4WyaOshXkfG8GFr6VOQy3cd44fVOwHpE5NuDhXlPhbGhujr6eHmUJEK5Ur2HYXq7AupszzmdOpGMp2blMfbXY9KVtoM6WZIahpce5TdtxzazYBeLbNvHu/UuDyelXWxMtXG1kKbdg3K0bi6Plcflp4Tvh/07suJY0c4kaPfExYWSpc3/Z4NCv2ec2dPs2zxfIYNH0HVap5q7feooiz36xS9T31yTW6jgGb3WcvysU4VbXsM4tKpPVw6tZfgwOfsetNOadHxIwD2/f0L65d/LzdPdjslkfg37ZRgNbdTWuSoT0Jy1CeN39QnRxTqk8Zt+xEVEcyBzfMJeVOfXD+7m5Zv6hM9/XJUdHSX+1QwMKFcBUMqOroX+7uVxflnzTn/LAhlkRhy/D3TpUsXXr9+TVpaGlFRUdy9e5dvvvmGDRs2yIYKB+jatStz5sxh7dq1WFtb8/r1a86fPy+7WA3SC9Z79uzh8OHDWFhYcPjwYUaPHi37ftiwYfz555/cvn2bly9fMnXqVBYtWvTWPAYFBTFjxgzmzZvHunXr2LhxI5999tlb51MmODiYZs2aMX/+fI4dO0a5cuV48eIFR48eJbMA7/YZP348S5Ys4YsvvuDVq1dUqVLlrfMkJCTQo0cPVq1axe3bt/Hx8WHSpEns2bOnULGoolmX4aSlJnNo82ySEmJwcKnFoPFrKJdj6JWYyCC0cgyF4eRWlw9HLub0nl84vXc5FjaOfDhyCQ6u2Xc81mjYlcT4aM798zvxMWHY2LszcMwfmFnZAxAb9Zond04DsGpmL7k8DfluA1WqNSozsaiybl09fV48vcmVExtJSojFyMQS56r1+Xzq1iJ5r1ztxl1IjI/m1L6VxEWHUdHBnaET/sA86/eODic6InvIfAsbBz6bsIqDf8/j8sktmJjZ0GPQVGo26ChLk5qSxL4Ns4mJDEFPvxzWdi70Gzmf2o27vHN+31WLVm2Ii4tl+5ZNREZG4ly5MtNnzcXG1haAqKgIwsNCZemPHTlIRkYGf6xYzh8rlsumt23fkW/H5X69QHF6W3mKiwkjJjL7IrO5tQMDx/7B0a3zuH56C8ZmNnQZ8D1e9TvJ0qhSjoP8H7BhQXZD+dg26Ymh2s160fvz7JNExS363Gl0TEyoOHAouhaWJL/4j+c/fEdaqPRYoWdhib6NbfYM2tpY9+2Ho4MTkox04u/e5tmYUaSGvC6xPKuqUfOOJMTG8M/2v4iJCsfeyZWx037BykZ68TMmMpyIMPl8zxg3UPZ/f79HXDl/FEtrOxatPlCiea/RqCuJCdJyGZdVLsdml8v4mDBiIuTL5advyuW1rHI5UKFcumeXyzN7l2Nu48hHCuUyPjaCPX9+R1xMGOUrGGPrWJVB41fjWr1ZyQWfD9N6NWhyapPsb69FUwEI2LiHe59PUVe2CqQsl0tVNGjWiYS4aA7t/IOYqHAqObnx9dTfsLSpBEBMVBiR4cFy8/w0ob/s/y/9fLh24QiW1nb8vOpIieb9baLOnELX1JRKg4ehZ2lJ0n/PeTZpvKz+07O0pFyO+lJLR5uK/QZQztEJSXo6cbdv8uirL0l9XTrry/jYGPbnKJfjpi2TlctopeXyU9n/peXyGJbWdixe/U+x5VNdx+y3rVdLW4fw4P+4e/EbEuOjqGBohn2Vmgyb8jc29u7F9nsA1G/Wifi4aA7t+oPYnPucdd773JyJOfa55z5c//cIFtZ2/LyydO1znRrWIiY+kT//OU14TBxu9rb8OmYIlaykT/GEx8TxOjJavZnMh7r6Quosjzkdv5qCvq4Wn3Q0wKC8Fv8FpbN8RxwpOc5VW5hoyz0sWU4PPulggJmxNmnpEl5HZrL2YAI3H+d+RZm6ZPd7Nufo9/yco98TSZiSfs+qFb+yasWvsult23dkzLjvSjz/b1OW+3WK3qc+uSa3UUCz+6xl/Vj3NvWbdSYhLobDu/4kNioMOyc3Rk/9XdZOiY0KJypcfrvMndhP9n9pO+UwFtaV+EmN7ZTajbuQGBfNqb0riX1Tn3w2Mbs+iYsOJzpcvj4ZNmEVBza/qU/Mbeg5eCo1G3bMaxUlTpx/1ozzz0IR0RLPDJckLd68sl4QCmLGjBn06tWLOnXyHwJDeHcSiYStFzVzN/2kmbQxoInxZcW291rGW1KWTb0bSsfue+wXqOacFL1qrg6AZpfLOx1bqDknxcP7+AUALj3K+3UNZVVTT2MAtl3SvHLZv6m0XB7Sq6rmnBSPbmlPAM0ul2cfJKk5J0WvdY0KANxo1UTNOSke9c9Jh5m+/ChWzTkpek08TQDNPo6fua95+xxAm5rS/S7x4m4156ToGTSTjligieUSssvmyPnK30lblq2aJL0w9MQvQM05KXpVXaVDDGtinw6y+3Wa2CfP6o9rYjslq42i6X1WTT7WnbqfrOacFL12NaUjguy7rnn1CUCvBtI6RRPbKZp+7llLS7y/Wd2S9v369kRqUqHX/9SdhSInbh8QBEEQBEEQBEEQBEEQBEEQBEEQBEEQSiUx5LggCIIgCIIgCIIgCIIgCIIgCIIgCIKqxFPyJUo8oS0UyqxZs8Rw44IgCIIgCIIgCIIgCIIgCIIgCIIgFCtxQVsQBEEQBEEQBEEQBEEQBEEQBEEQBEEolcSQ44IgCIIgCIIgCIIgCIIgCIIgCIIgCKrSFs8MlyTxawuCIAiCIAiCIAiCIAiCIAiCIAiCIAilkrigLQiCIAiCIAiCIAiCIAiCIAiCIAiCIJRKWoBE3ZkQBCFvEonYRQVBEARBEARBEARBEARBEARBkNLS0lJ3Ft57SQdXqjsLearQfZS6s1DkxBPagiAIgiAIgiAIgiAIgiAIgiAIgiAIQqmkq+4MCILwdtsuaeZT2v2bSu8i23pR8+L7pJk0th2XM9Wck+LxcRPp/VCHb6WpOSdFr2tdPUCzy6W/71M156R4VHbzAOCQXlU156TodUt7Amh2ubz0KE7NOSkeTT2NAc0ulw98X6s5J0WvhltFAB77Bao5J8WjmqsDAPuuZ6g5J0WvVwMdQLPryzvPwtSck+Lh7W4NwNkHSWrOSdFrXaMCoJnlErLL5i8HNC++b3tIY9Pkfo8mxgbZ8WlinzyrP66J7ZSsNoqm91k1+Vinie2UrDbKgZvpas5J8ehRT3qJaMu/mnccH9Bc8889C8L7RFzQFgRBEARBEARBEARBEARBEARBEARBUJWWGAS7JIlfWxAEQRAEQRAEQRAEQRAEQRAEQRAEQSiVxAVtQRAEQRAEQRAEQRAEQRAEQRAEQRAEoVQSQ44LgiAIgiAIgiAIgiAIgiAIgiAIgiCoSls8M1ySxK8tCIIgCIIgCIIgCIIgCIIgCIIgCIIglErigrYgCIIgCIIgCIIgCIIgCIIgCIIgCIJQKokL2hpoyJAhREVFqTsbghLOzs5IJBJq166t7qwIgiAIgiAIgiAIgiAIgiAIgiAIhaGlVXo/Gki8Q7sUcHBwYObMmXTp0gUrKyuCg4PZt28fs2fPJjIyUt3Zy8XV1ZXvv/+eDh06YG1tTVBQEFeuXGHx4sXcvHnznZffqlUrzp49i5mZGTExMUWQ45IjkUjo1asX+/fvV8v6r53ewsUja4iPDsPa3o0uA6bi7FE/z/T+j69xdNs8wl75YmxuQ7Muw2nQpr9cGp8bxzi9dzmRoS+xsHGiXZ8xeNbrkGOdW7lxZivR4a8AsLZ3o3XPr3Cv1fKdY7l0dA1x0WHY2LvR+ZO3xPLkGse2zSP0lS/GZvnHEhX2EnPr3LGost74mHBO7FqE34OLJCfF4exRn64Df8DStvI7xXv11Bb+PbKW+Dfr7TJgCpWr5h3vf4+vcXTrfGm85jY07/I5DdvKx/vw+nFO5dh27ft+i1eOeFOSEji15xd8bp0kITYSO2dPug6YioNLzXeKRRX/Ht/GmYPriI0Oo6KDG70GT8K1Wr080/v6XGf/5oW8DvTFxNyGtt0/o1mHfnJpkhJiObR9OfeunyQpIRYLa3s++HQiXnXerSy+jTrKqv+T61w6uoYg/4fEx4TR7+vf8KzbvthizM+Bg4fYuWcPkZFRODs5MfLLL6hZo7rStA8ePmTNug0EBAaSkpKCjY013Tp3pk/vXiWb6Xdg0bw+LuM/x7RuDcpXsuFG39GE/HNK3dnKRR3l8sKhP3h08wThwc/R1S+Po1sdOnw4His7l2KLMy+nD+/kyL5NREeFY+/owoDPx+NRvY7StNGR4Wxbt5QXfo8ICQ6gfbf+DBg+voRz/G7KSrlUxdGDe9m/ZxtRkZE4OlXmsy+/xquG8hsBr1w8z7HD+/B/7ktaWhqOzpX5eMBn1KnXsIRzrZrDB/ezd/cOoiIjcHKuzOdfjqZ6jVpK016+eIEjh/7hv+d+pKWl4eTsTP+BQ6hbr0EJ51q5yye2cu7wWuKiw7C1d6PHp5OpUi3vOub5o+sc/Hs+Ia98MTGzoVX3YTRu119p2juXD7P19wl41WvLkLG/FVcIMu97fXns0B4O7NlKdGQEDk6VGfLFt3jmsc9dvXSOE4f34v/cl/S0VBycqvDhgGF412tUwrlWzdmj2zm+fwMxUeFUcnTl488m4u5VV2namKgwdq5fzMvnjwgNfkmbrp/Qb9h3JZZXiUTC2f2/cfPcDpITY7F3qUW3T6djY++e73xF0b9RZd0HNkznuc9l4qJD0S9ngKNbHdp/NAHrIiqzEomE68d/w+fqDlISY7F1qkXLPtOxqJh//H73jnHt6HJiIl5iaulEoy5jcKmZHX9qcjzXji3n+f2TJMVHYGXvSfMPvsfWqfj7O1k0qd+jSJNie9/644o0qY2ijCb3WcvSsa4wNKWdcvHEVs4eXCdrO38weDIu+dSXfo+u88+mBbK2c+sew2jaPru+vH5uL9v/+CHXfHPX30JPv1yxxJCTRCLh3D/ybYeuA1Vrt5zZl91uadtnDJ515dst109v4dKx7HZLp/7y7ZbU5ARO7l7M49unSIqPxszKnobtBtGgzSdFFps62mQZ6Wmc3vsLz+6dIyoskHIVjHDxakr7D8dhYm5bJLEJgiYQT2irWZUqVbhx4wYeHh588sknuLm5MXLkSNq1a8fly5cxNzfPc149Pb1iy5eurvJ7HerVq8fNmzfx8PBgxIgReHl50bt3bx4/fszixYuLLT+ljY6OjrqzkMuDq4c5umUuLbuPZOSsvTh71Gfzki+JjghSmj4qLJDNS0fg7FGfkbP20qLbCI78PQefG8dkaQJ8b7Nz5ThqNenJqNn7qdWkJztWjiXQ764sjamFLe0/HM+XM3bx5YxdVPFszNblXxH66lnhY7l2mKNb59Ki+0hGztyLk3t9Ni/NP5a/l47Ayb0+I2fupUX3ERzZoiSWVeOo3bQnI2ftp3bTnuxcJR/L29YrkUjY9ttXRIUF8sk3Kxg5Yw9mlpXYuGgYqSmJhY73/tXDHNkyj1Y9RjBq9h6cPeqxacmIfOPdtGQkzh71GDV7Dy27f8nhv3/m4fXjsjQvfW+zY6U03q9m76N2055sXzGOgBzx7lv3A74PL/Hhl/P5+qf9uFVvxvqFw4iNCil0LKq4ffkI+zbOo0OvL5gwdycuVevy57yRRIUHK00fERrI6gWjcalalwlzd9Lhg+Hs3TCXu1dPyNKkp6ex8ucviAx7xdAxS5iy+CD9vpiFqYVNscairrKalpKErWM1un46rVjje5uz5y+wavVffNLvY1Ys/4UaNarzw4yZhIaGKk1fvnx5enbvxqL5c1m9agUD+vVj/abNHD5ytIRzXng6hgbE3nvCw29nqzsreVJXufR/cp0GbQcw/IftDB6/lsyMdDYtGf5O9WNhXP33OFvWLqb7R8OYteRvPLzqsOTHb4gIe600fXpaKsam5nT/aBiOlfPvpJZWZaFcquLi+dOsW/0bffsNYtHy1XjWqMWcGZMIC1V+XPJ5eJfaderz/az5LPhlNTVq1WHe7Ck893tawjl/uwvnzrDmzxV81G8AS3/9A6/qNZk9fUqesT18cA/vOvWYPvtnlixfSc1a3syZ9QPP/Qrfvioqd68c4cDmubTtOYJvftpN5ar1WLtwBFHhyuuYyNBA1i4aSeWq9fjmp9206fkl/2z8mfvXjudKGxX+ikNbFlKlat4n+IrS+15fXjp/ig2rl9P748HMW76WatVrM3fmBMJDldeXjx7coaZ3AybPXMjcZWuoXqsuC36cxH+lcJ+7fvEYO9YtpGvf4fywaBtunnX4dc5XRIYpb2+mpaVibGJOl77DcajsUcK5hYtH/uLy8fV0/XQaX0zbiZGpNRsXDSMlKT7PeYqif6Pquu2cq/PBsJ/5as4hPh3/FxIkbFr8OZmZGUUS/+0zf3H3/Hpa9J7Gh9/uxMDEmn/+HEZqct7xv/a/zfHN4/Co15N+4/fjUa8nxzeNJeRFdvxndk4j4Okl2n8yn/4T/sHRoxkH/vyM+Jji7e9k0aR+jyJNiu19648r0qQ2ijKa3Gcta8e6gtKUdsqdy0f4Z+M82vf6krE/78KlWl3+mp932zkiNJC/FozCpVpdxv68i3a9vmD/hp+5p9B2Ll/BiOkrzsp9SuJiNuRoOwycxhc/7MTIxJpNi9/ebtn1h/Qc88iZ0nPMu1aNJfC5Qrtl21xadBvJiBnSdsvfy74kJkd9fHTbPHwf/Euf4Qv46qdDNO4whCNbfuLx7aK5oVtdbbK01GSCX/jQssdoRszYTb+vfyUixJ+ty0cXSVyCoCnEBW01+/3330lNTaVjx46cP3+egIAAjh49Svv27bG3t2fOnDmytP/99x/ff/8969atIzo6mtWrVwPSIcZfvHhBQkICe/bswdLSMtd6unfvzo0bN0hKSsLPz4/p06fLXZSVSCSMGDGCffv2ER8fzw8/5L7LC2D9+vU8e/aMFi1acPjwYZ4/f87du3eZPXs2H3zwASB9wloikWBqaiqbr3bt2kgkEpydnQFwcnLin3/+ITIykvj4eB48eECXLl1wdnbm7NmzAERHRyORSFi3bh0A+vr6/PLLL4SEhJCUlMSFCxeoXz/7Dq2s9Xbs2JFbt26RmJjIqVOnsLa2pnPnzvj4+BATE8OWLVuoUKGCXFwTJ07Ez8+PxMRE7ty5Q9++fZUu9/r166SkpNCiRYu3b1ygQYMG3Lp1i6SkJK5fv06dOsqfDisKl46vp07LvtRr9RHWlVzpMmAqJhYVuX56q9L0189sw9TSji4DpmJdyZV6rT6iTos+XDy6Vpbm8vGNuFRvSsvuI7C2c6Fl9xG4eDbm8okNsjRVvdviUbsVVhWrYFWxCu37jkW/vIFcR62gLh9bT90WfanXMjsWU4uK3DijPJYbZxViaSmN5dKx7FiunNiIq1dTWnSTxtKi2wiqeDbmSo5Y3rbeiBB/Av3u0n3QDOyr1MTKzoVug2aQmpzA/auHCh3vpWMbqNuyD/VbfYRNJVe6DpRuu2untylNf+3Ntus6cCo2lVyp3+oj6irZdq7Vm9Kq+5dYV3KhVfcvpdvu+EZA2lDyuXGCTh9PoHLVBljaOtO299eYWzlwLY8yU1TOHtpIozZ9aNz2Q2ztXek9ZDJmlhW5eEJ5vJdO7sDMsiK9h0zG1t6Vxm0/pGHr3pw5tF6W5uqZPSTGx/D5+OW4VK2LhXUlXKrVxd65WrHGoq6y6l6rJe36jMGrXsdije9t9uzdR6eOHejSqRNOTo6M+vILrK2sOHj4iNL0bq6utGndisrOzlS0taVd2zbUr1uXBw8flnDOCy/s2HmezljG630n3p5YTdRVLgeN+4s6zftgY+9ORadq9Bo2l5iIIIL8S3b7Ht//Ny3bf0CrDr2o5FiFAcPHY2Fly+mju5Smt7KtxMDhE2jWpjsVDIxKNK9FpSyUS1Uc2LuDth270r5TdxycKjPsy/9haWXNscPKR74Z9uX/6PXhANw8PKlk78DAIV9SsZIDN65eKuGcv93+vbto37ELHTt3w9HJmeEjvsLK2oYjhw4oTT98xFf0+ag/7h7VqGTvwKChw7GrZM+1q5dLOOe5XTiyngat+9KwjfQ43nPQFEwt7bhySvlx/Mrp7ZhZ2tFz0BRs7V1p2OZD6rfqw/nD6+TSZWZmsG3FJDr0/RoLG8eSCOW9ry8P7dtG2w7dadepBw6OlRn65bdYWtlw/PA+pemHfvktH3w4EDcPT+zsHflkyAjsKjlw89rFEs23Kk4e2ESztr1p3r4Pdg4u9Bv2HeaWFTl3bKfS9FY29vT7fBJNWvco8WOBRCLhyomNtOw+Eq96HbF18KD35/NIS03m/tWDec5XFP0bVdddv3U/KldtgLmVA5Wcq9O29xhiI4Nlo3S9a/z3LmykXruRuNbsiKWdB+36zyM9NZlnt/OO/+6FjTi6N6VeuxGY27hQr90I7N0bc/eCNP70tGSe3z9Ok24TqOTaAFMrZxp2+h/GFg48vFS8/Z0smtTvUaRJsb1v/XFFmtRGUUaT+6xl6VhXGJrSTjl3eAMNW/el0Zu28weDp2Bmacflk9uVpr98ajvmlnZ8MFjadm7U5kMatO7DuYPr5RNqaWFiZi33KQkSiYSrJzfSottIPOt1xMbBg14qtFuunsxut1jlaLdczdFuuXJ8PXVa9KXum3ZL50+k7ZbrZ7PrxUC/O9Ru2ovK1RphZuVAvVb9qOhYlSD/B0USm7raZOUNjBk8YS01GnbBys4FR1dvug78geAXD/O8wUooJbS0S+9HA2lmVGWEubk5nTp1YsWKFSQnJ8t9FxISwt9//02/fvLDL02cOJEHDx5Qr149fvzxRxo2bMjatWtZsWIF3t7enDlzJtfF6I4dO7J582aWL1+Ol5cXI0aMYOjQoXz//fdy6WbNmsX+/fupWbMma9euRZG3tzc1atRg8eLFSCSSXN8XZHjw33//nXLlytGyZUtq1qzJpEmTiI+PJyAggD59+gDg4eFBxYoV+fbbbwFYsGABffv2ZciQIdStWxdfX1+OHTuW6yn2mTNn8vXXX9O0aVMcHR3ZsWMHY8aMYcCAAXTr1o0OHTrwv//9T5b+p59+4rPPPmPUqFFUr16dpUuXsnnzZlq2lB/SasGCBUyZMgVPT0/u3bv31hgNDAw4ePAgT548oV69esycOZNFixap/BsVRHp6KsH+D3Gr3kxuumv1ZgT43VY6T6DfHVwV0rvVaE6Q/0My0tPyTONaozkBvneULjMzM4P7Vw+RmpKIo6t3oWMJevEw93qrNyPAV3ksAcpiqS4fS4DfHVxr5I43wO+OyuvNSE8FQFcv+45HbW0ddHT1efmscMPtp6enEuT/ELdcecsnXt87udPXbMarnPH63sWtRlO5NO41m/HyzTIzMzLIzMxAV+HuTT39crx4eqtQsagiPT2NwP98qFpLPm9VazXF/6nymyD8n93Nlb5a7WYEPM+O9+Gts1R2r82udXOYNqIl8yf24sS+P4vsqRFl1FVWS4u0tDSe+fpST+FGnXp16+Dz6JFKy/D188Pn0SNq1qxRHFl8L5WmcpmcFAdABUPTPNMUtfS0NPz9HlPdu7Hc9OrejfF7/PZjt6A+aWlp+Pk+xbuO/HCVtes24Mkj1U5OZGZmkpyUiJGxSXFksdBksdWVH7rUu049Hj9S7eRoZmYmSUlJGKs5tvT0VF7954O7Qn3gUaMpL57dUTrPy2d38FBok3jUbE7gf9l1DMDJvSswNDanYeu+iosoFqK+TOO571NqKe5zdRrw9LHq+1xSUiJGRqVrn0tPS+Ol3yO8vJvITfeq3Ri/J4W/6ba4RIUFEh8TJle2dPX0qVy1QZ5lEYqmf1OYdaemJHLn3z2YWTlgYlGxQLEqExsZSGJcGI5Vs/Ogo6tPJdcGvPbPO/6QF3fk5gFwqtqc1/53AMjMSEeSmSHXdwNpXy74v3d/VdrbaFK/R5Emxfa+9ccVaVIbRRlN7rOWtWNdQWlKOyWr7exRS7Et3BT/p3eUzvPi2V08airWr80IUGg7pyYn8tM37fnx67asWTiaV/6qlel3FR2ed9shMI9z0CBtt7jkapNkn2POyKPd4uLVjMAc9bGTe12e3jlNbFQIEomE/x5fIeK1P241mr9zbOpskymTnBgHWlqUNyh99asgqIt4h7Yaubu7o62tzaM8GlGPHj3CwsICa2trwsLCADh9+rTc0N6zZ8/m2LFjzJ8/H4Bnz57RtGlTOnfuLEvz/fffM2/ePDZulN4J+t9//zFt2jQWLFjA7NnZQ1Nu2bJF9jR0XvkFePz4cSEjzubk5MTu3bt58OCBLE9Zst4bHhoaKrtIbmBgwKhRoxg6dChHj0qH+fniiy/o0KEDn3/+udyF4h9++IFLl6RP5qxZs4Z58+bh4uIiW8euXbto06YNCxYswMDAgHHjxtG2bVuuXLkiy0vz5s0ZMWIE58+fly13+vTpnDx5UuUYBw4ciI6ODsOGDSMpKQkfHx8cHBxYtWpVnvPo6+tTrlzBh4dJjIsiMzMDQxP5p/ONTC2JfxCudJ74mDCMTOUP9oYmlmRmpJMYH4WxmQ3xMeEYKS7TxJL4mDC5aSEBT/hrziekp6WgX86A/l//ho29W4HjyIpFkpmBoan8eg1NLImPyTsWQxOFWExzx6L4+xjmiEWV9VpVdMHUshIndy2hx5BZ6JWrwOVj64mPCSM+Wv43UT3eaDIzMzAysZKbbmRiSVye8SrbLlZK4pVfpqGJlSyWchUMcXTz5uz+lVjbuWJkasm9K4cIfH4PC1vnQsWiioRYaVk1VvidjU0tic0j3rjocKXpMzPSiY+LxtTcmojQQJ6FvaJes258OWklYa9fsHvdHDIzMujUd1SxxKKuslpaxMbGkpmZiZmZmdx0MzMzoqKi85134OChxMTEkJGZyacDPqFLp07Fl9H3TGkplxKJhGPb5+HkXg9bh5Ibzi7uTZ1qYmYhN93U1IIHUcrjF0qHuNgYMjMzMFXYdmZm5kRHRaq0jH/2bic5OZlmLdoURxYLLTY25k19KX8Tppm5OVEqxrZvz05SkpNo1qJVcWRRZbJ2i2nuNmdcdB7H8ZhwpekzM9JJiIvGxNwa/6e3uH52D2N+3lNseVf0vteXsVn7nLlCfWluQfStCJWWcXDvNlKSk2nSom1xZLHQ4t/0jUxM5WMzNrMkNo9yqk7xsdKyoazcxOTzRE5R9G8Ksu5rp7dwYuci0lISsbJzYfCEtejq6qsaZp4S46R5MDCSz4OBkSVxUXnHnxgXTgWFeSoYWcqWp1/eCFtnb26cWIG5jQsVjK14dvsQIS/vYWZVfP2dLJrU71GkSbG9b/1xRZrURlFGk/usZe1YV1Ca0k5JeFPHKKv/8qpj4qLDMa6lvL7MajvbVHKh38g52Dm6k5yUwIWjm/ht5qeMm7sHa7virUOy2hmK9aAq7Ral55hj5dstudKYWuKX49x2lwHfc2DDNJZOaIW2ji5aWlr0GPITTu7v/soidbbJFKWlpXBy12JqNupO+Qqlf0QFQSgp4oJ2KaalpQUg9zT0jRs35NJ4enqyd+9euWmXL1+Wu6Bdr149GjRoIPdEto6ODhUqVKBChQokJSUpXbYq+Sms5cuXs3LlSjp27MjJkyfZvXs39+/fzzO9q6sr+vr6XLyYPUxMeno6165dw9PTUy5tzqenQ0JCSEhIkLtgHhISQsOGDQHw8vKiQoUKnDghP0Snvr4+t2/L3yH1tt9HkaenJ3fv3pX9viDdNvmZMmUKM2fOLNB6csraRlkkEtBCK4/UQF7f5ViO4jKlc8lPs7SrwshZe0lOjMXnxnH2/jWZzyZvKvRFbWXrQCKfr9xZVpIe+XmULlNhWn7r1dHVo99Xy9m/7gfm/68RWto6uHg1wa2m/NP8haK4Wokk/22nuK2zA86RJNdC5Zb54Zfz2bvmexaObYW2tg52zl7UbNyd4Bc+hYmgQHL/zhKlZS2v9Fn1kKxeyszEyMSCj7+Yiba2Do4u1YmNCuP0wXXFfmJHXWW1tMhd70jemtXFC+aRlJzMo8dPWLt+A5Xs7GjTuvSdACnL1F0uD2/+kZCAJwybskWl/Ba1XHUGknzjF0oPJYculbbdhbMn2fH3eiZNm4OpwknZ0kJZbPkd+7KcP3uabX9vZOr02blOOKtL7ny/5TiuJL10OqQkJbBt5ST6Dp+FoXHJxyfqy9zHcVXK5cVzJ9i1ZS0Tps0ttftcHhWKWrKS073LBziwcYbs74FjpDc8K/3d37It3rV/k72at6+7VuMeuFZvSlx0GJeOrWXnyjEMm7oVPb2C3ZD99NYBzu7Kjr/b56uUrk+iZFruLCrpq+aY1v6TBZzZMZUNP7ZCS1sHa3sv3Ot0Jzyw+Ps7svxoUL/nbXkt07G9Z/1xRZrURlFGo/uspfRYV1Q0p52irM4oQB2TdS7+zWRn99o4u9eWfV/Zow7Lvv+Qi8f/pteQqUWRYZl7Vw5wMEe7ZcC3eRy3Vem3KTvW5/od8l/u1ZObCPS7S///rcDM0p4XT69zePMsjM2scfFqSkGUxjYZQEZ6GrtWjUMikdBt0Ixc3wuljDjXVKLEBW018vX1JTMzEy8vL/bv35/r+2rVqhEZGUl4ePadOgkJCXJpVDmIa2trM2PGDPbsyf3EQ86hzhWXrejp06dA9oXavGRmZubKm56enlyaNWvWcOzYMbp160bHjh2ZMmUK48eP57ffflO6zLwupmtpaeWalpaWPfyKRCKR+ztrmra2dLT9rH+7devGq1fy7/9KSUmR+/ttv09eeS6IuXPnsmTJErlpsbGxb53PwNgcbW2dXHd1JcRG5Lr7K4uRqbXS9No6uhgYmr1JY5XrjsH42AgMTeXvNNbV1cfyzV3E9lVqEuT/gCsnNtJz6GwKysDYHC1lscRF5LpLr6CxxMcqWeabWFRdb6XKNRg1ax/JiXFkpKdhaGLB6h8/plLlwg0/ZWBspnzbxUXmepopO16rvOM1yhGvwpNACXHy5cHCxonPp2wiNSWRlKR4jM1s2L5iLOZW9oWKRRWGJtKyqnjnflxsJMZ5bF9jM6tc6eNjI9HW0cXQSDo0p4mZNdq6umhr68jS2Nq7EBcdTnp6Grq68nVQUVBXWS0tTExM0NbWJioqSm56TEwM5gp3wCuqWFE6PGWVypWJjo5m85atpfPkQBlUGsrl4b9/5Mmd03w2eTOmRTAUaUEYv6lTY6Ll79qPjYnC1Ex5/ELpYGxiira2Tq6nsWNiot56gvTi+dOsWL6ACZNnUbtO/XzTqoOJiany+jL67bFdOHeGX39ZxKQp0/Gu8+5PHbyrrHaL4tPY8TF5t1uMTa2Ups9qt4S88iUq7BUbFn8l+14ikfYnpgyuyYSFh7C0dSriSER9aSLb5xTqy+ioXCMlKLp0/hSrls9j7OQfqeXdIN+06mD0pm8Uq3AsiIuJxKQUHAuqerfB3qWW7O+s1xrFx4RjbGYjm54Qm3dZhKLp3xiZWKu87vIGxpQ3MMbStjIOrrWZ/3UjHt88Qc3G3VWOHaCyVxv6jcsdf2JcOIYm2XlIio/I9dR2TgbGViTGyceWFB9BBaPsfc3UyoleozeTlpJIako8hiY2HNs0FmMLhwLluTA0qd+jSJNie9/644o0qY2ijCb3WUv7se5daUo7xTCr7axY/8VE5npqO4uxmZK2s6y+NFM6j7a2No4uNQh7/aJI8p1T1dptcJiRfdxOz6PdkphPGxryrjuzRsiQtVsU2zY52iRpqcmc2rOMfl/9ikft1gDYOlbldcBjLh1bW+AL2qWpTZadhzR2rhxLdFggQ75bL57OFgQF4h3aahQZGcmJEycYPXo05cuXl/vO1taWgQMHsn379nyX4ePjQ+PG8u+JVPz71q1bVK1aFT8/v1yfgjxtfefOHR4+fMj48eOVXqw1NZV2QrKGR7ezs5N95+3tnSt9YGAgf/zxB3379mXx4sV88cUXAKSmSg8eOjrZnRhfX19SUlJo3jx7iD9dXV3q16+f55DtqvDx8SE5ORknJ6dcv01gYGChl5u17Nq1a8ttW8Vtoyg1NZW4uDi5jyp0dfWxq1wdv4eX5KY/97mEo2sdpfM4uHrz3Ec+ve/Di1SqXB2dNx1FB1dvniss0+/hRRzdvPPNj0QikTUCCkpXV59KztXx81Fc7yUc3ZTH4ujqnSt2P4VYlKZ5cFH2ru+Crre8gTGGJhZEhPgT5P+AqnUKN4SRrq4+lZRsu3zjdcsdi++Di9jnjNetNr650lzCScky9csZYGxmQ1JCDL73L1KtbrtCxaIKXV09HKp48fSe/GgFT+9fprJHbaXzVHavzdP78umf3LuEo0t2vFWqehP++qXshhqA0GB/TMysi+2kjrrKammhp6eHu5sbtxRGs7h1+w5eCiNn5EfZjUdC4amzXEokEg5tns2jmycY8t16zK2L/2SxIl09PSq7VuPhnaty033uXMW1Wq085hJKAz09PVzdPLh7W35EnHu3b1DVM++bxi6cPclvS+cyZuI06jVskmc6dcqOTf6drXdu36SaZ/U85zt/9jTLly5g/MSp1G+YfxuypOjq6mNfxYtnD+Trg2cPLuHs7q10Hid3byXpL+JQRVrHWNu5MHbufr6ds0f28azbBhfPhnw7Zw+mlsVzoVfUl3q4uHlw7851uen37tzAo1re+9zFcydYsWwO30yYQd0GBTtpWFJ09fRwcvXk0V359uOje1dxraq8vVmSylUwwtLWWfaxruSGkam1XFlMT0/F/8n1PMsiFE3/xtzaoVDrBunTZemF6PPplzfC1MpZ9jG3dcPA2JrAp9l5yEhPJcjvOhUr550HW2dvAp7Kxxbw5CIVK3vnSqtXzgBDExuSE2MIePIvVWoU//CzmtTvUaRJsb1v/XFFmtRGUUaT+6yl/Vj3rjSlnZLVdn56X74+ePrgEpU9vJXO4+xem6cKbeen9y7hWCW7jlEkkUh49eIxJmbWRZLvnMpVMMLC1ln2yWq35DynnPGm7eCQxzlokLZbFM9DP89xjlnnTbtF8Tz0c59LOLypOzMz0snMSENLW/6Slpa2NpIcx46CxFZa2mSQfTE7IvQFgyesw8CoNIwuIAili7igrWZff/015cqV49ixY7Ro0QIHBwc6derEiRMnePXqldww4cosX76czp07M3HiRNzd3fnqq6/khhsH6Xu2Bw8ezIwZM/Dy8qJatWp8/PHH/PjjjwXO72effYaHhwfnz5+nS5cuVKlShZo1azJ16lTZU+a+vr68fPmSmTNn4u7uTteuXRk/frzccpYuXUrHjh2pXLkyderUoW3btrIL0y9evCAzM5Pu3btjZWWFoaEhiYmJrFy5koULF9KpUyc8PT1ZvXo1BgYGrFmzpsBxZImPj2fRokUsXbqUwYMH4+Ligre3N6NHj2bw4MGFXi5I30memZnJmjVr8PT0pEuXLkyYMOGdlpmfph2Hcuv8Lm6d301YkB9Hts4lJiKYBm36A3Bi52L2rJ4kS9+gTX+iw4M4unUuYUF+3Dq/m9vnd9Os8zBZmsYdBuH38CIXDq0mLPg5Fw6t5rnPZZp0GCJLc3LXEl48vUFUeCAhAU84uXsp/o+vUatJj0LH0qTTm1guSGM5unUuMZHB1G/d/8065WOp37o/MRFBHN32JpYLu7l1YTdNO2XH0uhNLP8elsby7+HVPH90mcY5YnnbegEeXj/Kf4+vEhkawOPbp9i4aBjV6rbDrYb8+xQLommnIdw8t5ub53cTGuTH4S3SbdewTT8Aju9cwq4/s+Nt+GbbHdk6j9AgP26e382t83vktl2TDoPxe3CJ84dWExb0nPOHVuPnc5kmHbPL9bP7//Ls3gWiwgLxfXCRtfOGYmVXhbrNexc6FlW07jaYK2d2c/XMHkJe+bF343yiwoNp2l4a78GtS/l7xZTs36f9x0SFB7Nv0wJCXvlx9cwerp7ZQ5tuQ7PTdOhHYnw0ezfMIzTYn4e3znFy32qad+yvuPoipa6ympKcQPDLRwS/lNab0eGBBL98RHQ+7/QpDn169+Lo8RMcO36Cly8DWPXnakLDwujWtQsAa9dvYMHi7FEn/jl4iCtXr/HqVRCvXgVx7MRJdu3ZS9s2rUs03+9Cx9AAk9rVMKldDQCDKg6Y1K5GeUe7t8xZctRVLg9tns29ywfoO2IR+uUNiYsJIy4mjLTU7NFgSkLHDwZy/uQ+zp/cT1DAf2xds5iI8Ne06dQXgJ2bfmP1suly87x8/oSXz5+QkpxEXGwUL58/4VXA8xLN97soC+VSFT16f8yp44c4dfwQgS/9Wffnb4SHhdKxa08ANq//k+WL58jSXzh7kl+X/MyQz0fj8X/27js8iupr4Pg3jZ5GKiShpFBCC4Tee2+CiIqAKAiir0oXkS4CIvWHFEGpUqQkIC30IoQmTToJBAKEkN4hbd8/lmyyyaaA2WyynM/z7KNM7szes3Nm5t4pd6q6ExEeRkR4GHFxsboKIVu93nmXQz77OHxwP4GPHrL612WEhjync1dle2n9mtUs/HmOqvzJ40dZNH8OQ4aOoGo1dyLCw4kIDy8UsbXo8jEXjm/nwokdBD/x56+Nc4gMC6JxO+VxfP/WBWxd8a2qfOO2/YkIC+KvjXMJfuLPhRM7uHB8By27DgHApFhx7J3c1D4lS5lRvGRp7J3c8uUdvdl52/eX3Xq/z9GDezh2cA+PAwNYt2oJoSHBdOjaG4BNa1ewdH56n/H0iUP8suAHBn76JW7VahAZEUZkRBjxhSAvM2vfYyB/H/Hi9BFvgh7f58818wgPDaJlx3cB8Nq4hDVLvlebJ/DBbQIf3ObFiwRioyMIfHCbp4H+Wq+rgYEBjTsM4tSeldz65xDBj+/i/dtETIqVoFaj9Kefd66awOHt81X/zo/+TV6+O/x5IKf2ruRpwHUiw54S6HeZbctHYWJSHLfa//1pRQMDA2q3GMQ/R1Zy/99DhAXd5ejWiRgXK4Fb3fT4D2+egO++9PhrtxhI4N3TXDq6iojn97l0dBWP7/lSp0V6/I/unOLR7VNEhz0m8O5pdq0YjIVNZao16POf650X+tTv0efY3rb+eGb61EbRRJ/7rEXpWPcm9KWd0qrrYM4f28H548r95a4Nc4gMTW8779uykM0Z9pdN2vUnIjSI3RuUbefzx3dy/vgOWnX/WFXm4I5l3Ln6N2HBgTwJuMWfv07m6cM7NGn3ntbjMTAwoFH7QZzau5Jblw7x/PFdvH/P2m7xWj2BwzsytFvap7dbQjO0WxplaLc07vgxl05t53Jau2XLq3ZLK+VxoHjJMlSs2oBDf84j4PY5IkIec+XvnVw7s4tq9TrkS2y6apOlpCTz57KveRpwnb7D5pGqSFH1Ed7kBkJRgAwNC+9HD8mQ4zrm5+dH/fr1mTZtGlu3bsXKyopnz57h7e3N9OnTswyLk9m5c+cYOnQo06dPZ9q0aRw+fJgffviByZMnq8ocPHiQ7t27M2XKFMaPH09SUhK3b99m9erVr13fCxcuUL9+fSZNmsSqVauwtrYmKCiIM2fO8M033wDKd1t/8MEHLF++nKtXr3LhwgW+//57tm/frlqOkZERv/zyC46OjkRHR3PgwAFGjRoFwNOnT5k6dSpz5sxhzZo1rF+/niFDhvDtt99iaGjIhg0bMDU15eLFi3Tq1InIyMjXjiOjyZMn8/z5cyZOnIizszORkZFcunSJH3/88T8tNy4ujh49erBixQouX77MzZs3mTBhgsah3/NDzUZdiY+L5MTuX4iJCsHWwY0Bo1Zi8Wq4qtioEKIyXOyytHHko1ErObB5DuePbsLUwpYuAybhXr+TqkwFt3q8O2I+R3cu5pjXEixtneg3YgGOLul3e8ZGh7Hz1/HERIVQoqQpdk5VGThmFS41mr15LA27Eh+rjCU2LZZv0mOJiQohKlw9lgGvYrmQFsuHmWJxTY/lqNcSyto68W6mWHL7XoCYyOf4bJlDbHQYphY21GnSi5Y9/9v7vGo1Un7v8V3LiIkKwc7BjYGjV6Svu8gQosKC1OIdOHoF+zfP4dwRZbxdB3xHjQYd0+N1q0u/z+dzZMdiju78H5a2Trz3+XycMsT7IiGGQ9sWEh3xjJKlzalRvyPt+36T7R2f+aVuky7ExUThs3MF0ZEhlHNy47MJyylrUx6A6MhQIkLT47WydWTY+GV4b/iJvw9uxtzSlncGT6ROo/TGqqVVOUZM/BXvDT8xb0IfzC1tadnlI9r1/FSrsegqV58GXGfdT+kNY58tyhMMdZr15p1P0082aFvrli2IiY7mj81bCA8Pp2LFivwwfSp2tsqhmcLDw1WjdoDyvXi/r1vHs2fBGBkZUb6cPZ98PJhuXTpn9xWFjrlnTZoc2aD6t/vPyvdTBa7fybVPJ2Y3W4HSVV5ePLYZgLVz1W8I6/XJj9RtXjAnjgEaNe9IXHQUu7euJioiFIcKLoyavBhrW+XF3ajwUMJCnqnNM3X0ANX/B/jf4uzJA1jZlOPnVX8VWL3/i6KQl3nRrGVbYqKj2LZ5PRHhYVSoWJnvps/F1lb5hG5EeBihIc9V5Q8d+IuUlBRWLV/EquWLVNNbt+vM/40uXHG3aNWGmJhotm7aoNxfVqrElOmzsbWzAyAiQj02n/17SElJYeWyJaxctkQ1vW37jnw9ekKW5RekOo27EB8TyRGv5URHhmDv6MaQcStVQ6TGRIYSmeE4XtbWkU/GruCvjXPwPbwJM0tbeg76jloNO2b3FQXmbd9fNm3ZjpiYKHZsWUtEeBhOFSvz7bR52Lza5iIjwggLCVaVP7x/FykpKfy+fAG/L08/+d+qXRdGjsr5RuyC1qBZJ+JiItm7bSVREaGUr+DKl98txcpW2d6MigghPEOeAvwwNv2i2SP/m5w/tR8rm3L8uGK/1uvbrMtQkhJfsHfjDBLionB0rs3AMb9RPMMwk1HhTzEwTB8pLb/6N7l9t7FJMR7e/Yezh9aTEBdNGTMrKlatz6ffbc5x+M3XUbfNUJKTXnBy5wxeJkRhV6E2PYb9RrES6fHHRjxVGymuXKV6dBwwn3MHFnPeZwlmVk50GLgAu4rp8ScmxHJ2/wJiI59RopQFzrU60KjLKIyMCuZJZn3q9+hzbG9bfzwzfWqjaKLPfdaidqx7XfrSTvFo0oW42EgO7UxvO386fkWG/WUIEWHq+8uh45eze8NcTh/ajJmlLb0Gf0ftDG3nhPhotv02jZjIUEqUMsWhYjVGTl5HBdeCGZWsWRflcXtfxrbDaA3tlgzHbSfXerw7fD5HvRZzzPtVu2X4Ahyd1dstCbGRnPgrQ7vla/V2y7vDF3BkxwJ2rhpHQlwU5lblafvON2oPI/3X2HTRJouOeMadK0cBWDGtt1qdBo9fR+VqjfIlPiGKOgNevaJeCFE4KRQKtpzRz830/abKg//m0/oX3wfNlLH96fv6Q94UBe81Ud7lte9S4Rp2Kz90rac8gaDPeRngd1fHNdGOSq5VANhrUlXHNcl/3ZLuAPqdl2du5e01G0VN0+qmgH7n5XW/Z7mULHpquipPlN32/2+voCmsqrkoh7j2vpCi45rkv94NlK8t0uf95ZV7IbmULJo83JTDZB6/nqDjmuS/1jVLAvqZl5Cem4v/0r/4vu6hjE2f+z36GBukx6ePffK0/rg+tlPS2ij63mfV52OdPrZT0toof/2TrOOaaEcPT+Uzj5v+1r/j+IfN9fvcs6bXwoqClXB4na6rkK2S7QfnXqiIkSe0hRBCCCGEEEIIIYQQQgghhBAijxRyU0GB0s+B1IUQQgghhBBCCCGEEEIIIYQQQhR5ckFbCCGEEEIIIYQQQgghhBBCCCFEoSRDjgshhBBCCCGEEEIIIYQQQgghRF4ZyDPDBUl+bSGEEEIIIYQQQgghhBBCCCGEEIWSXNAWQgghhBBCCCGEEEIIIYQQQghRKMmQ40IIIYQQQgghhBBCCCGEEEIIkVcy5HiBMgAUuq6EECJ7CoVsokIIIYQQQgghhBBCCCGEUDIwMNB1Fd568cc26boK2SrV5kNdVyHfye0DQgghhBBCCCGEEEIIIYQQQgghCiUZclyIImDzaf18SvuDZsq7yPQxvrTY/vRN1XFNtOO9Jsr7oQ5eTdRxTfJfxzrFAP3Oy3/9gnVcE+2o5WoHwHW/ZzquSf6r6WoP6HdeHr+eoOOaaEfrmiUB/c7LvSZVdVyT/Nct6Q4AF+5E6rYiWtKgqgUAf/2TrNuKaEEPT2UXV5/3l/q4zUH6dnfiRryOa5L/WtUoBcCWM/qXlwDvN1Xm5v/26l98/9dNGZs+93v0MTZIj08f++Rp/XF9bKektVH0vc+qz8e6v+vU03FN8l/zq5cA/ezTwdtxvkGfYxO6pZCn5AuUPKEthBBCCCGEEEIIIYQQQgghhBCiUJIL2kIIIYQQQgghhBBCCCGEEEIIIQolGXJcCCGEEEIIIYQQQgghhBBCCCHyykCeGS5I8msLIYQQQgghhBBCCCGEEEIIIYQolOSCthBCCCGEEEIIIYQQQgghhBBCiEJJLmiLt87gwYOJiIjQ2fc/ePCAr7/+WmffL4QQQgghhBBCCCGEEEIIIf4DA4PC+9FD8g5tUeg5Ojoybdo0unTpgrW1NUFBQXh7ezNjxgzCw8N1XT01x44d48qVK4waNUon369QKDi+ayn/nPiTF/HRODjXpttHU7B1cMtxvpsXfTjqtYSIkEdY2lSgXZ9vqO7ZQa3M+aObOHPgN2IiQ7B1cKXzB99RsUp9AFKSkzjqtZh7104QEfKY4iXL4OzelPbvjsbM0k7iewPnjmzi7/2/E/uqPl0+nEilqvWzLf/g9nkObJ7L8yd+mFra0rzLpzRs+77q78FP7nF05/94GnCDyLCndPngW5p2GqyVuufFSZ8tHNm9lujIEMo5utDn4wm4VvfMtvy9mxfwWjePoMf+mFva0L7nJzTv+J5amWN7N/D3wT+JCA2itJkFHo060PPDbzApVlyrsegqLwFu/nOQf45v5enDGyTERjJ8mhflKlTXSpzZObDHi907NxMRHo5ThUp8/Nn/4V6zjsayZ0+f4OC+XQTcv0dSUhJOFSvz3odD8PBsWKB1zqsDe7zYtXOLKrYhn32ZQ2wn8dnnTcB9v1exVeK9D4dQV0exve15efzAVg7uWkdURCjlnVx4b8g43NzraSwbFRHCtrXzeXT/Fs+DHtGm6wf0/2R8gdb3dRTlvHxTZZvXx3nMp5jXq0mJ8rZc7DuS4N1HdF2t13Zo33b27dxIZEQYDhUq89HQUVSrUVdj2QtnjnFk/04ePrhLUlIijhWc6fPBMGrXa1zAtdbs9KHNHN+zhpjIEOwcXOk16Fucq2V/HPe/dYHdG34i+IkfZha2tO7xCU3b91f9/cIJL7au/D7LfLPXXsrX43hu+6/MAu6cx2fLHGX7ysKWZl2G0qDN+2pl8mO/6fXbt1w97a02j4NzHYZ9v/W/B/0G9GWbO77/T3wyHAv6fzI222NBZHgI29ct4KG/8ljQtusH9P90XAHXON35o5s4vf83YiNDsHFwpcuHueTq7fMc2DKHkFd9gZxyNfz5I8raZs3V80c3c/HYZiJDnwBg4+BK655f4Fa7pXaCzEChUHDeZyk3zv7Jy/ho7CrWplXfKVjZ59xu8bvqw7kDS4gKfYS5dQUad/kGl9rpMSW+iOXc/iXcv36Y+JgwbByr06L3JOwq1NJ2SCr61O/JTJ9jA/3vk2ekT20UTfS5z1qUj3V5Yf9ePxw/HkQxa2vi/e9z/6efib58Odvy5fq/R7n3+1O8fDlePnvG41W/8XzP3gKscd4V5X6dPp+ffdvPpQhR2MkT2qJQq1y5MhcvXqRKlSp88MEHuLq6MmLECNq1a4evry+WlpbZzmtiYqK1ehkbF857QU7vX43vwbV0/WgywyZvo4y5Det//oSXCbHZzhPod5ltK0ZTp2lPRkzfRZ2mPdm2YhSP/a+qylw/v48Dm2fTovsIRkzzooJbfTYu/IzIsKcAJCW+IOjhTVr2GMnwqTvo/+X/CAsOYPOSkRLfG/j33D72b5pDqx7D+XzGTipW8WTDguGq+mQWEfKYDQtGULGKJ5/P2EnL7p+x748fuXHhoKpM0ssXWNo40aHfaMqYW2ul3nn1z5kD7Fw7l059hjFh7jZcqnuy/MfPCQ8N0lg+9PljVsz+ApfqnkyYu42O7wxj+5rZXDl7SFXmwqk97N60iC79RjBp4S4+HDGDS74+7N60SOvx6CovAZJeJuDkVo/2747RaozZOX3yCGtX/Y8+/Qcxb8lqqteszY9TxxPyPFhj+Vs3rlK7bn2+m/4TPy1eRY3adZkz41vu+98t4Jrn7vTJo6xZtZS+/Qfy85JVVK9Zm1lTJ2Qb280bV6lTtz6Tps/lp8WrqFm7LnNmTNRZbG9zXl447cOfa+bRte9Qvv95C67V6/K/WV8QHqJ5H5OUlIipmSVd+g7FsVKVAq7t6ynqefmmjEqXIvraHW58PUPXVXljZ08dYuPqhfR8bwg/LFpPVXcP5k0fRWjIM43lb9+4TE2PhoydupAfFq6jei1P5v8whgD/OwVc86yu+O5n9/o5tO/9GaN+3I5ztXqsnjuciFDN7ZSw549Z/dPnOFerx6gft9Ou9zB2rfuRa+cPqpUrUbIMU5YdV/vk5wWMvOy/MooIecwfC4dTwa0+I6Z50aL7cPZvmsXNiz6qMvm13wRwrdmCMQtPqT4DvlmZb7G/Ln3Y5i787cPWNfPo2vdTJs/fjFv1uiz54UvCsjkWJCcnUcbMkq59P9X5seD6uX0c2DSblt1HMGK6FxWr1GfjgpxzdePC4VSsUp8R071o0W04+//QkKvLR1O7SU8+n7GL2k168udy9Vw1L2tH+3fH8NnU7Xw2dTuVqzdm85IveP7kntZjvnR0NVdOrKVVn8m8N2obpU1t2LXiExJfZN9uCQq4jM+G0VT17MkHY3dR1bMnPutH8exhekxH/5xM4N0ztP9wLh+M241TlWbsWjGE2EjNx838pm/9noz0OTbQ/z55RvrURtFEn/usRflYlxfWnTriPH4sgat+43L/D4m6dJkay/5HcXt7jeXt+71Lxa++5NGKlVzq049Hy1fg/N23lG2l/RuzXldR79fp8/nZt/lcihBFgVzQFoXaL7/8QmJiIh07duTkyZMEBgZy4MAB2rdvj4ODA7NmzVKVffDgAZMmTWLNmjVERkayatUqQDnE+MOHD4mLi2Pnzp1YWVll+Z7u3btz8eJFEhIS8Pf3Z8qUKRgZGan+rlAoGD58ON7e3sTGxvL991mfINHExsaG3bt3Ex8fz/379/nwww//4y+SPYVCwdlD62nZfQTunh2xc6zCO5/OISnxBf+e25PtfGcPrcfFvSktug3HppwzLboNp3L1xpw9tE5VxtdnLfVa9MWzZT9syrvQ5cPvMC9rz8VjmwEoUcqUQWN/p2bDLliXc8bJxYOuA74n6OGNbDt8El/2zviso17LPtRv1Q/b8i50HfAdZmXtOX90i8by549twdyqHF0HfIdteRfqt+pHvRZ9OH3gd1UZR+dadH5/HLUbd8PYuFi+1/l1HNuzniZt+9C0XV/sHZ3p+/EELK3t+fug5qeQTh/8E0tre/p+PAF7R2eatutL4zbvcOSvtaoyD+5exblqXeo374aVrQPV6zTFs1kXHt2/qdVYdJmXAHWa9qJ1zy9wdm+i1Tiz85fXn7Tt2I32nbrjWKESQz77CitrGw7u89ZYfshnX9H73Q9xrVKdcg5ODBj8GfblHfnn3JmCrXgeKGPrqortk8/+DytrG3z27dJY/pPP/k8VW3kHR1VsF3UQ29uel4f/2kCztu/QvH0fyjk60/+T8Vha2XPCZ5vG8ta2DvT/dAJNWvegZKkyBVzb11OU8/K/CPE5yd2pi3jmfSj3woXU/l2bad2+J2069sLBqTIDh43GytqOI/t2aCw/cNhouvcdiIubO/blK9B/0Ejsyzlx+cKpAq55Vif2raNh6740avMudg4u9Bo0EQurcvge1nwc9z2yFUurcvQaNBE7BxcatXmXBq37cGLPWvWCBgaYWdioffJTXvZfGV08rmxfdfnwO2zKu+DZsh91W/ThjE96+yq/9psARibFMDW3UX1KlbHI1/hfhz5sc4f+2kjzdr1p0eHVseDTcbkcC8rz/qfjadJG98eCMwfXUrdlXzxbpeeMWVl7LhzVnKsXjmXK1VbKXM3YF/A9uB7nGk1p2V2Zqy27D8e5emN8M+RqVY+2VKnTCmv7yljbV6Z931EUK1GKwAwnY7VBoVBw9eR66rcfgUvtjliVq0L7D+eQnPiCu5eyb7dcPbkepypNqd9+OJZ2ztRvPxxHt8ZcPamMKTnxBf7XDtK0x1gcXBpgYVORRp3/D7Oyjlw/o/m3zG/61O/JTJ9jA/3vk2ekT20UTfS5z1qUj3V54TBwAMFe3gR7eZPw4AEP5v3My2fB2L/3rsbytt278Wz7TkJ9DvLyyRNCDxwk2GsXDkMKx0gIGRXlfp0+n59928+liDdkaFh4P3pIP6MSesHS0pJOnTqxbNkyXrx4ofa34OBg/vjjD/r37682fdy4cVy/fh1PT09mzpxJw4YN+f3331m2bBkeHh4cO3Ysy8Xojh07snHjRpYsWYK7uzvDhw/n448/ZtKkSWrlpk+fzq5du6hVqxa///47ebF27VoqVapE27Zteffddxk5ciS2trZv8GvkLiLkMbFRIbjUaKaaZmxSjEpVGxDol/1wPIH+V3Cp2UxtmmvN5gT6XwEgOTmRpw9vqC0XwKVGsxyX+yI+BgwMKFHK7A2iyUrf40uTnJzI04AbuGapc/b1CfS7krV8rWY8CbhBSnJSvtbvv0pOTiLw/k2q1WmqNr1a7aY8uHNF4zwP7l2lWm318tU9mvHo/k1VfC7V6hF4/yYBfv8CEBocyM3Lp6hRr0X+B5FBYcvLgpSUlMR9v7vUqdtAbXqdeg24c+t6npaRmprKi4R4ypiaaqOKbywpKQl/v7t45Ets+buPyIu3OS+Tk5J45H8Ldw/1DqB7ncb439HuCXltK+p5+TZLTkrigd9tatZtpDa9Zt2G3Lv9b56WkbbuSpcx10YV8yw5OZEnD25SJdNxuUqtpgTcvaJxnof3rlKllnr5qrWbEfhAvZ2S+CKeH75qz8wv2/LbvJE8CbiVr/V+3f1XoP+VLOVdazTnaYb2VX7uNwNun+enr5uyZGIndq+dTGx02GvHKZRUx4I6mY4FHo3xv124jwXJyYkEBdzAVVPO+GvO1ceacrWmeq5qKuNSszmBflc0LjM1NYV/z+0l8WU8Ti4ebxZMHkWHPyY+JoQKVdPrZ2RcDAeXBgQFZN++eBZwRW0egArVmvMs4AoAqanJKFJTMDJWH+nByKQ4Tx/8k38BZEPf+j0Z6XNsoP998oz0qY2iiT73WYvysS4vDIyNKVO9OpG+Z9WmR/r6YlZH87DchsWKkZr4Um1a6ssXmNasiUEhGmmzqPfrCtv5hvw8P1vYYhNCZFV49uZCZOLm5oahoSG3bmk+mXXr1i3Kli2LjY0NISEhABw9epT58+erysyYMQMfHx/mzp0LwL1792jatCmdO3dWlZk0aRJz5sxh/fr1gPJJ78mTJ/PTTz8xY0b6MHubNm1izZo1r1X/rl270qhRI86fPw/Ap59+yu3bt7Odp1ixYhQv/mZDK8ZGK3+D0mbqT6CXNrMiKoe71GKjQjXOExulXF58TASK1BRKm2sqE6pxmUlJLzm8fT61GnWnRMn8uetT3+NLEx8TSWpqCmXM1IcgK2NmRUw29YmNCqVMphjLmFmTmpJMfGwEphbauYniTcRFR5CamoJppt/b1NyK6EjNJ26jI8M0lk9NSSY2JhJzSxs8m3UhNjqcRZMHoQBSU5Jp3rE/HXsP1VYoQOHKy4IWEx1FamoK5hbqr34wtyhLZER4npbxl9dWXrx4QdMWbbVRxTeWHltZtekWFpZ5jm33q9iatWijjSrm6G3Oy9gY5T7GzFx93ZlaWBEdWTjq+KaKel6+zWKiIzWuO3NzKyIjz2Yzl7p93n/w8mUCjZq300YV8yzuVTtF03E5u3ZKTGQoprU1H8fjYiIxs7TBtrwz/UfMopyTGy8S4jh1YANLp33E6Nk7sSlX8T/X+032X7FRIZQ2a65e/lW909pX+bXfdKvVkhr1O2NuVZ7I0Mcc9VrCunkfM3zKDoxNCs9TfEWF6liQaZszy6G9WVjEv6p75rwqY25F7PXsc7WMeaZcNcuaq1n7C+m5miY48A6rZ31ActJLihUvxftfLsXWwTUfIste/Kt2S0lT9fqVNLUiJiL7dkt8TCgly2Sap4wVca+WV6xEGewreXDh0DIs7ZwpZWrNvUt7CX50DQvr/75fyY2+9Xsy0ufYQP/75BnpUxtFE33usxblY11emFhaYGBsTGKYeiyJYeFYWGcdeRMg4owv9u/0JuzoceJu3aKMe3XsevfC0MQEYwsLkkILR3+wqPfrCtP5hvw+P1uYYhNCaCYXtEWRZWBgACiHA0lz8eJFtTLVq1fHy8tLbZqvr6/aBW1PT08aNGig9kS2kZERJUuWpGTJkiQkJGhcdm6qV69OUlKS2nx37twhIiIi23kmTpzItGnT8rT8a75/8df6qap/D/hmBZD+u6jRNC3jn8n0d4Vyaq5lNCw3JTmJ7StGo1Ao6DZwapa/55W+x5erzNVRKLLWUa28+t8UpG0XOf82upL1p1XkWNUs6/3Vdp82/d6NC/jsXMV7Q7+nklstQp4FsmPNHA5YWNP53RH5Vu/Cmpe6pHHd5KGOfx8/zJ9/rGHC5B+znGAoLDSmXR5iO3X8MH/+sZYJk2cVSGySlxpoXnk6qUp+Kyp5KbLKuk3mcmx/5cwJH7w2r2bUpHlZTnzpjqZ2x2u0U9La768mV3SrQ0W39KdtKlWpy6JJ73L64B/0HvxdflT41de93v4r6zFO9Yecl/ma+82aDbuq/t/OsQrlK9Vk4bh23L12HHfPjtnWT+RCU/u4sB2vspE59xQKDXmkPkd2C8p2mcq51KdZlavMiOlevIiP5ubFg3it/pYh327I14vad/75i+Pb0tst3Ydm027JNeZsYsowrcOHP3Fky3esnd4KA0MjbBzcqVK3OyFPCm4I66La78kLfY5NWTH1f+pbnzwj/WqjZKXPfdaifKzLE0WmfxsYqPYdmQX+uopi1lbU2bAWAwMDEsPDeb77LxyHfAypKVqv6usqKv26wnq+IT/OzxbW2ETRopB1WKDkgrYotPz8/EhNTcXd3Z1du7K+Q6RatWqEh4cTmuEOu7i4OLUyGg9AmRgaGjJ16lR27tyZ5W8ZhzrPvOzcaLrgnpvZs2ezYMECtWnR0dEay1b1aIODc23Vv1OSEwHlXWEZ7/6Niw7LcqdwRmXMrYmNVr8bLC4mjDLmyruRS5laYmBolOWOsbiYrMtNSU5i2/JRRIY8ZvD4tf/p7jh9jy87pUwtMNRYn3DKmGuOs4y5ddby0WEYGhnr9P2LmpQ2s8TQ0CjLHcMxUeGYZROfmYYnK2OiwzE0MlYNa7Zn61IatuxB03Z9AShfoQqJL+LZ/OsMOvb5DMN8em9IYcxLXTE1M8fQ0CjLHcRRURFY5NKpOn3yCMuWzGXMtzOoXbe+Nqv5Rv5bbEdZtuQnxn47nToFFJvkZboypjnsYywKRx3fVFHLS5HO1Mzi1bpTz8uoqPBcT/6ePXWI1f+bxf9N+JGaHg21Wc08Kf2qnZL5CbXYqPAsT96lMbWwJibTcTxWdRy30DiPoaEhTs41CXn2MF/q/Sb7rzLmNtm3r0pbvCqjnf2mqYUtFlblCQ/On/jfNqpjQYSm9mbhveACypzR2BeIDsvyVE+avOZqlu02OozS5upPoBobF8PKTvn0skPlWjwNuM7ZQ+vp+fEM8kvlGm2wq5Ch3ZKibLfER4dS2iy93ZIQG5blqe2MSplaEx+jHlNCbBilTNNjMreuQJ8vN5L0Mp7El7GUNrPlwPpRmJV1zK9wslXU+z050efYQP/75BnpUxtFE33usxblY11eJEVEokhOplimp7GLlbUkKUzzU8ypL19yb+p0/GbOwqRsWRJDQ7Hv24fk2FiSIiILoNZ5U9T6dYXxfEN+nZ8tjLEJIXIm79AWhVZ4eDiHDh1i5MiRlChRQu1vdnZ2DBgwgK1bt+a4jJs3b9K4cWO1aZn/fenSJapWrYq/v3+Wz+tcjM7s1q1bmJiYUL9+egOjSpUqWFpm3zhJTEwkJiZG7ZOd4iXLYGVXUfWxKe9KGXMb/G+eUZVJTk4k4M4FnFzrZrscJxcP/G+cUZvmf/206l1pxsbFKF+xhtpyAfxvnFFbblpjIuz5QwaNXUOpMv/tLkF9jy87xsbFKF+pRtY6Z6pPRk6uWWP0u34ah0o1MDI20Uo935SxsQlOzu7cvuarNv3ONV8qV/XQOE9ltzrcyVT+9tUzVHB2V8WX9DIhyw0sBoZGr25xffPtOLPClpe6ZGJigrNrFa5dVh+94trli1StXjPb+f4+fphfFs7mm3FT8GzYJNtyumRiYoKLaxWuvmZsp44fZunC2XwzbnKBxiZ5mc7YxIQKLtW5dVV9n3Hr2jlcqmp+11pRUdTyUqQzNjGhsms1rl85rzb9+pXzuFWrle18Z074sHLxTEaOnUndBs2zLVeQjI2L4VDZnbv/qu8H7l4/Q6UqHhrnqehWh7vXM5W/dganytm3UxQKBU8e3sbMwibf6v26+y+N+8QbpymfoX2lrf1mfGwEUeFBlDHPn/jfNmnHgptX1YfLvXX1LC7VCvexwNi4GOU09AXu3zyDk4vmnHF08eB+phzzy5Srji4e3NeQz06uHjnWR6FQqE7u5pdiJcpgYVNR9Slr50opUxsC76bXLyU5kSf+FyhXKfvtxL6SB4F31GN6dOc09pU8spQ1KV6K0ma2vIiP4tHtv6lcU/tDBxf1fk9O9Dk20P8+eUb61EbRRJ/7rEX5WJcXiuRkYm/dwqKx+vvdLRo3Jvrq1VznTXz+HFJTsencifCTp7J9qlsXilq/rrCdb8jP87OFLTYhRO7kgrYo1L788kuKFy+Oj48PLVq0wNHRkU6dOnHo0CGePHmiNky4JkuWLKFz586MGzcONzc3vvjiC7XhxkH5nu1BgwYxdepU3N3dqVatGu+99x4zZ878T3W/e/cu+/fvZ9WqVTRs2JB69eqxevVq4uPj/9Nys2NgYEDjDoM4tWclt/45RPDju3j/NhGTYiWo1ai7qtzOVRM4vD39PeONOgzE/8Zp/t63ipCg+/y9bxX3b/nSuMNgVZkmnT7m0sntXDq1g5Cn/hzYPJuo8CDqt34fgJSUZP5c9jVPA67Td9g8UhUpxESFEBMVQnI+nQDR9/gyatppMP+c2ME/J3fw/Kk/+zbNJiosiIZt+gNwcNsCtv86QVW+YZv3iQx9yv7Nc3j+1J9/Tu7g0smdNOv8iapMcnIiQQ9vEfTwFikpSURHPCfo4S3CdPDkT5vug/A9sgPfo148e3yfHWvnEh4aRPMO7wGwe9Mi1i9NH160Wcf3CA8NYue6n3j2+D6+R73wPbqTdj0+VpWp6dmavw/9yT+n9xP6/DG3r51h79al1KzfGkNDI63Fosu8BIiPjSTo0S1CnvoDEPbsAUGPbhGT6X2I2tLjnfc4cnAPRw7u5fGjANb8+j9CQ57TsWsvAP5Yu5Il82epyv99/DD/WzCLQZ9+gVtVdyLCw4gIDyMuLrZA6vs6lLHtzRDb0lex9QRg49pf1WI7dfww/1vwI4M/HUkVHcf2tudl+x4D+fuIF6ePeBP0+D5/rplHeGgQLTu+C4DXxiWsWfK92jyBD24T+OA2L14kEBsdQeCD2zwN9C+Q+r6OopyX/4VR6VKY1amGWZ1qAJSq7IhZnWqUcCqn45rlXZdeH3D80C5OHNrNk8AHbFy9kLCQYNp16QPA1nW/sGLhNFX5Myd8WLloOh9+8hWuVWsSGRFGZEQY8YVg3bXqOpjzx3Zw/vhOgp/4s2vDHCJDg2jcTtlO2bdlIZuXTVSVb9KuPxGhQezeMJfgJ/6cP76T88d30Kr7x6oyB3cs487VvwkLDuRJwC3+/HUyTx/eoUm79/Kt3rntvw5vn8/OVentq/qt3ycq7CkHtswm5Kk/l07t4NKpHTTtlN6+yo/95ssXcfhsnUug32UiQh/z4PY5Ni3+nFKmllSv1z7f4n8d+rDNdejxEX8f8eLvV8eCrb//THjoM1q9Ohbs3LiE3xdnPhbcIfDBHV6+iCcmOoLAB3d0cixo2vFVzpxU5sz+zcq+QIM2ypw5tE09Vxu86gsc2PwqV0/u4PLJHWp9gcavcvXUXmWuntq7ivs3fWmSIVcPb1/Aw7sXiQh9THDgHQ7vWEjA7fPUbtJDq/EaGBhQp+UgLh5eif+1Q4QF3eXw5okYFytBlXrp7ZZDmyZwZk96u6VOi4E8unuaf46sIiL4Pv8cWcXju77UaZke08Pbp3h46xTRYY95dOc03ssGY2lbmeoN+2g1pjT61O95m2ID/e+TZ6RPbRRN9LnPWpSPdXnxZMMf2PV5B7vevShZuTKVx46heDl7nm3bAUDFr76kyg/pI4iUqFgBm25dKVHBiTI1a1B17mxKubrw8H9LdRVCtopyv06fz8++7edSxBsyMCy8Hz0kQ46LQs3Pz4/69eszbdo0tm7dipWVFc+ePcPb25vp06fn+D5qgHPnzjF06FCmT5/OtGnTOHz4MD/88AOTJ09WlTl48CDdu3dnypQpjB8/nqSkJG7fvs3q1av/c/2HDBnC6tWrOXHiBMHBwXz//ff/+UJ5Tpp1GUpS4gv2bpxBQlwUjs61GTjmN4pnGHolKvwpBobpdz1XcK3HuyPmc3TnYo56LaGsrRPvjliAo0v6HZ01G3YlPjaSE7t/ITYqBFsHNwZ8sxILawcAoiOecefKUQBWTOutVqfB49dRuZr6HZUSX85qNVLW5/iuZcREhWDn4MbA0StU9YmNDCEqLEhV3tLGkYGjV7B/8xzOHdmEqYUtXQd8R40G6e9cjIkIYdnU9BM3pw/8zukDv1OpagM+nbg+X+ufG8+mnYmLieTAjhVER4RQzsmVzycuo6xNeQCiIkKICE2Pz9rWkRETf2Hnunmc8tmCmaUt7w6ZiEfjDqoynfp+BgYG7NnyP6LCn1PGzJKanq3o/sFXWo9HV3kJcOfKUXb9nn6iaPuK0QC06vkFbXr/nzbDBqBZy3bEREezffM6IsLDqFCxMt9Nn4uNrT0AEeFhhIYEq8ofPLCblJQUVi9fyOrlC1XTW7frzJej8+8dqfmhWcu2xERHsW3zerXYbNVie64qf+jAX6SkpLBq+SJWLV+kmt66XWf+b/TEzIvXurc5Lxs060RcTCR7t60kKiKU8hVc+fK7pVjZpu9jwjPsYwB+GJveiXzkf5Pzp/ZjZVOOH1fs13p9X0dRz8s3Ze5ZkyZHNqj+7f6zMr8C1+/k2qdFI47GLToQExOF19bfiQwPxbGiM+OmLMTaVnmBMDJCfX951MeblJQU1q2Yx7oV81TTW7TtxvBvphR4/TPyaNKFuNhIDu1cTnRkCPaObnw6foXqOB4dGUJEhnaKla0jQ8cvZ/eGuZw+tBkzS1t6Df6O2g3T2ykJ8dFs+20aMZGhlChlikPFaoycvI4KrrWzfP+bym3/FRMVQlT4U1V5SxtHBoxayYHNc7hwVNm+6vLhJNzrd1KVyY/9pqGhEc8f3+XqmV28iI/B1MKGStUa0u/zhWr77IKkD9tcg+adiIuJYu+fv6qOBf836X8ZjgWhhIc+U5tn5pj0Y8FD/1uqY8HslfsKtO41G3UlPk6ZMzFpOTMqPWdio0KIClPP1Y9e5er5tFwdkClX3dJz9ZjXEixtneiXKVdjo8PY+et4YqJCKFHSFDunqgwcswqXGs20HnO9tkNJTnrBiR0zeJkQhV2F2vQa/hvFSqRvAzERT9We3i1XuR6dBs7n7P7FnDuwBHMrJzoNWoB9xfSYEl/E4rt3AbGRzyhRygKX2h1o3HUURkYF88SsvvV73pbYQP/75BnpUxtFE33usxblY11ehPocxNjcHKfPhlHMxpp4P39ufPEVL4OU214xa2uK29uryhsYGuEw6CNKVqyIIjmZqAsXuTZoCC+fBmX3FTpT1Pt1+nx+9m0+lyJEUWBAQY7bI4R4bQqFgs2n9XMz/aCZ8uCvj/Glxfanb6qOa6Id7zVR3uV18Gr+P6Guax3rFAP0Oy//9QvOpWTRVMvVDoDrfs9yKVn01HRVdmz1OS+PX0/QcU20o3XNkoB+5+Vek6o6rkn+65Z0B4ALdyJ1WxEtaVDVAoC//knWbUW0oIen8p5tfd5f6uM2B+nb3Ykb2hnRSpda1SgFwJYz+peXAO83Vebm//bqX3z/100Zmz73e/QxNkiPTx/75Gn9cX1sp6S1UfS9z6rPx7q/69TTcU3yX/OrlwD97NPB23G+QV9jy/yqDlHwYs946boK2SrT9B1dVyHfyRPaQgghhBBCCCGEEEIIIYQQQgiRRwo9Hdq7sJJfWwghhBBCCCGEEEIIIYQQQgghRKEkF7SFEEIIIYQQQgghhBBCCCGEEEIUSjLkuBBCCCGEEEIIIYQQQgghhBBC5JW8x7xAyRPaQgghhBBCCCGEEEIIIYQQQgghCiW5oC2EEEIIIYQQQgghhBBCCCGEEKJQkiHHhRBCCCGEEEIIIYQQQgghhBAijxQG8sxwQTIAFLquhBAiewqFbKJCCCGEEEIIIYQQQgghhFAykPc361z0uT26rkK2zBp113UV8p3cPiCEEEIIIYQQQgghhBBCCCGEEKJQkiHHhSgCNp/Wz6e0P2imvItMH+NLi83rfIqOa6Id7zQ0AuCOf6COa5L/qro4Afqdl/tKVdNxTbSja/xtAG77P9ZxTfJfNRdHALac0b+8fL+pMi8vtmqi45poR/0TvoB+5+WFO5G6rYgWNKhqAcBek6q6rYiWdEu6A8DZ21E6rkn+a1zNHNDv4/h5PVxvAA1frbuEY3/ouCb5r2SbAYB+5iWk5+agyUE6rkn+Wz+zHKDf/R59jA3S49PHPnlaf1wf2ylpbRR977Pq87HO91a0jmuS/5pUNwNg36UkHddEO7rWMwH0s53yNpx7FjomT8kXKHlCWwghhBBCCCGEEEIIIYQQQgghRKEkF7SFEEIIIYQQQgghhBBCCCGEEEIUSjLkuBBCCCGEEEIIIYQQQgghhBBC5JWBPDNckOTXFkIIIYQQQgghhBBCCCGEEEIIUSjJBW0hhBBCCCGEEEIIIYQQQgghhBCFklzQFkIIIYQQQgghhBBCCCGEEEKIPFIYGBTaz+v6/PPPuX//PgkJCVy8eJHmzZvnab6mTZuSlJTE5cuXX/s7X5dc0M5ngwcPJiIiQtfV0EsVK1ZEoVBQp04dnXx/fqxbXccghBBCCCGEEEIIIYQQQgghBMB7773HokWLmDVrFnXr1uXUqVPs378fJyenHOczMzNj/fr1HDlypEDqaVwg31KIOTo6Mm3aNLp06YK1tTVBQUF4e3szY8YMwsPDdV09NceOHePKlSuMGjUKgAcPHrBo0SIWL16sszp5eHjw3Xff0bJlS8zNzXn06BEnTpxg3rx53Lt3T2f10hWFQkHv3r3ZtWtXgX3f8V1L+efEn7yIj8bBuTbdPpqCrYNbjvPdvOjDUa8lRIQ8wtKmAu36fEN1zw5qZc4f3cSZA78RExmCrYMrnT/4jopV6r/Wd4c/f8TBrT/x6N4/JCcn4lqzBV0HfE8Zc+siH1vGsn8s/Ay/66fo/+VSqtdrn2tseeF7eDMn9/5OTFQIdg6udP/oWypXrZ9t+fu3LrB301yCn/hhZmFLy26f0Ljd+6q/X79wiGN//UpY8CNSkpOxtq9Aiy5DqNe8Z77U97/at2cXO3dsIyI8jAoVKzH0s5HUqFlLY9kzp0+xf+9fPLjvT1JSEhUqVuSDAYOo59mggGutlFs+ZRZw5zw+W+bw/Ikfpha2NOsylAZt3lcrk1seB9y5wJkDv/E04AaxUSH5mnv5wbJZfZxHfYp53RqUKGfLP/2/IPivgmnY5Kd9e3bhteNPVV5++tlIatSsrbGs7+lT7N+7Wy0v3x8wWKd5eXr/b8RGhmDj4EqXD3PJy9vnObBlDiFP/DC1zDkvw58/oqxt1rw8f3QzF49tJjL0CQA2Dq607vkFbrVbaifIHNj07oP9+wMwKWtFQsADApcuIvba1RzK98W2z7sUty9HYvAzgjauI8xnfwHWOO+Kcl7mxaF929m3cyOREWE4VKjMR0NHUa1GXY1lL5w5xpH9O3n44C5JSYk4VnCmzwfDqF2vcQHX+s2VbV4f5zGfYl6vJiXK23Kx70iCdxe9/eWRfdvZ57WBqIgwyldwZsCno6iazXqLDA9l85pFBPjdJjgokA7d+zNg6OgCqacujtl5+d5pn1TT+P0d+o2jWZdP/0PEuTu8bzt7X607hwrOfJTDurvge4wj+3fw6MFdkpKScKxQmXfeH0btek20Wsc3tfX4BdYd8iU0KgaX8raM69eRem4VNZa9cCeAYQvXZ5nuNW0kle1z77vkN131hVKSkzjqtZh7104QEfKY4iXL4OzelPbvjsbM0k5r8WryTpsytK5fitIlDfF/nMj6PdE8eZ6cbfn67iXo0bI0tmWNMTaCZ2Ep7D8dx5mrCQVY69wV5X5PXuhTfG9bn1wTfWmnaKIvfdaifKzLiyP7trHfeyOREaE4ODnz4aejc2xjblmziAD/WwQHBdK+W38GDB1TwDXW7O+DWzi2Zw3RkSHYO7rSe9AEXKp5Zlve7+YFdm2cx7PHfphZ2tK2+xCadeivViYhLpq9W5dw7cJhEuKiKWvjQK+PxuFeV/v9b31up8g5PqFPihUrRvHixdWmvXz5ksTExCxlR48ezW+//cZvv/0GwKhRo+jUqROff/453333XbbfsXLlSjZt2kRKSgq9e/fO1/pr8lY/oV25cmUuXrxIlSpV+OCDD3B1dWXEiBG0a9cOX19fLC0ts53XxMREa/UyNi4a9xl069aNs2fPUrx4cQYMGED16tUZOHAgUVFRzJw5842Xq83f1tDQEIM3GG6hsDq9fzW+B9fS9aPJDJu8jTLmNqz/+RNeJsRmO0+g32W2rRhNnaY9GTF9F3Wa9mTbilE89k8/0X/9/D4ObJ5Ni+4jGDHNiwpu9dm48DMiw57m+bsTX8azYf6nYGDA4PFr+fS7TaSkJLFpyeekpqYW6dgyOntoHeRzTl09u589G2fTptdwvpq5g0pVPVkzbziRoU81lg9//pg1P4+gUlVPvpq5g9Y9P+OvDT/y74WDqjIly5jTpudwRk7ZxDc/euHZsg/bV03i7rW/87Xub+LUiWOs/nU57/X/kEX/W4F7jVpMnzKRkOfBGsvfuP4vHnU9mTpjFguXLKNWbQ9+mD4Zf/+Cv4kmL/mUUUTIY/5YOJwKbvUZMc2LFt2Hs3/TLG5e9FGVyUseJ71MwM6pGl0/mqz1GN+EcemSxPx7mxuj3/xYoGunThzjt1+X0a//hyz830rca9RiRo55eQ2Pup5MmfEjC5Ysp1ZtD2ZN/577usjLc/s4sGk2LbuPYMR0LypWqc/GBTnn5caFw6lYpT4jpnvRottw9v+hIS+Xj6Z2k558PmMXtZv05M/l6nlpXtaO9u+O4bOp2/ls6nYqV2/M5iVf8PxJwf4Glm3a4fTlNwRtWMvNYYOJvXYVt7kLKGaruYNr0+sdHD/7nKdrVnN98Ic8WbOaCt+Mwbxp3oZWKkhFOS/z4uypQ2xcvZCe7w3hh0XrqeruwbzpowgNeaax/O0bl6np0ZCxUxfyw8J1VK/lyfwfxhDgf6eAa/7mjEqXIvraHW58PUPXVXlj504d4o/fFtCj3xBmLNxAVXcP5s/4hrBs1ltSUiKmZpb06DcEp0o5n/TKT7o6Zufle8csPKX26TVkFhgYUN2zo/Z+EF5tc78toFe/Icx8te7mzfgm223uTto2N2URMxeso3qt+iyYNYaA+4Vvm/O5eIN523wY2qU5WyZ9Rl3XCnyxdBNB4VE5zrdr+hccnjta9algW7aAaqxOV32hpMQXBD28ScseIxk+dQf9v/wfYcEBbF4yUusxZ9StRWk6Ny3Nhr3RTF0RSlRsKuMHl6VEsez7XbHxqew+EcvMVWFMWhrKqUvxDHvHnFquxQqw5jkryv2evNCn+N62Pnl29KGdkh196LMW9WNdbs79fZBNv79qYy7YSBV3DxbM/DrnNqa5BT36fVKgbczcXPbdj/f6OXToPYyxs7fhXLUev84ZQURokMbyYc8fs+qnkThXrcfY2dvo0GsoXutmc/XcIVWZ5OQklv84jPCQJ3z8zQImzt9D/2HTMS9rWyAx6Ws7Rc7xiTdiYFhoPxMnTiQ6OlrtM3HixCwhmJiY4OnpycGDB9WmHzx4kKZNm2Yb+scff4yLiwvTp0/P9581O2/1Be1ffvmFxMREOnbsyMmTJwkMDOTAgQO0b98eBwcHZs2apSr74MEDJk2axJo1a4iMjGTVqlWAchjqhw8fEhcXx86dO7GyssryPd27d+fixYskJCTg7+/PlClTMDIyUv1doVAwfPhwvL29iY2N5fvvv8+17seOHaNSpUosWrQIhUKBQqFQ/a1JkyacOHGC+Ph4Hj16xOLFiylVqlSWWNatW0dMTAwBAQH07NkTa2trvL29iYmJ4dq1a3h6Zn+nWMmSJVmzZg379u2jV69eHDlyhICAAM6fP8+4ceMYPnw4oLyAvHr1au7fv098fDy3b9/mq6++UlvWmjVr8PLy4ttvv+XJkyfcvXsXgAYNGnDp0iUSEhK4cOECdeuq34HXqlUrFAoFXbt25cqVKyQkJHD27Flq1qypKpM2THi3bt24ceMGL1++pGLFilhYWLBu3TrCw8OJi4tj3759uLq6qi0/L+s2N7nF8F8oFArOHlpPy+4jcPfsiJ1jFd75dA5JiS/499yebOc7e2g9Lu5NadFtODblnGnRbTiVqzdWXph9xddnLfVa9MWzZT9syrvQ5cPvMC9rz8Vjm/P83Y/uXSIy9Am9P52NnWNV7Byr0vuTH3n64F8e3DpbpGNL8+zRbXx91tLrk1nkp7/3r6V+q740bP0utg4u9PhoIuZW5Th7ZIvG8ueObsXCuhw9PpqIrYMLDVu/S/1WfTi1b42qjEv1htSs3x5bBxes7CrQvNNA7J2qEHD3Ur7W/U3s8tpB+46d6di5K04VKjJs+EisbWzZt/cvjeWHDR9J3379catSjfIOjgz6+FPKlXfgwrmc80obcsunzC4e34K5VTm6fPgdNuVd8GzZj7ot+nDG53dVmbzksVvtlrTr8w3uWj7R/aZCDp7i7vTFBO86lHvhQmqX13bad+xCx87dcKpQkaHDv8Daxpb92eTl0OFf0Kff+6q8HPjxUMqVd+D8Od8CrjmcObiWui374tkqPS/Nytpz4ajmvLxwLFNetlLm5ekD6Xnpe3A9zjWa0rK7Mi9bdh+Oc/XG+GbIy6oebalSpxXW9pWxtq9M+76jKFaiFIH+2T8ZrQ12731A6L6/CN37Fy8ePiRw6SISQ55j06uPxvJWHbsQstubiGNHSAx6SsTRw4Tu3YP9Bx8VaL3zoijnZV7s37WZ1u170qZjLxycKjNw2GisrO04sm+HxvIDh42me9+BuLi5Y1++Av0HjcS+nBOXL5wq4Jq/uRCfk9yduohn3kV3f3lg1yZatu9J6469Ke9UmQFDR1PW2o4j+zWvNxu78nw0bAzN23ajVOkyBVZPXR2z8/K9puY2ap/bV45SuVojytrmPLzbf7V/1yZavVp3Dk6V+Wjoq20um3X30dDRdO8zCOdX29x7A19tc+cL3za34bAv7zSrS5/m9XAuZ8P49zphb2nOthMXc5zP0rQ01uZlVB8jw4I/ZaLLvlCJUqYMGvs7NRt2wbqcM04uHnQd8D1BD29kezJXGzo1Kc3uk7FcvPmCJ8+T+XVHJMVMDGhSu2S289wOSOSfWy95GpLM84gUDp6NJzA4mSoVC88F7aLc78kLfYrvbeuTZ0cf2inZ0Yc+a1E+1uWFz65NtGzfi1Yd0tqYYyhrbcfRA9s1lrexK8+AoWNp1qYbJUsVXBszN8f3rqdRmz40bvsudg4uvDP4Wyys7Dl9SPP+5MzhP7Gwsuedwd9i5+BC47bv0rD1Oxzbu1ZV5tyxncTHRvHpmCU4V61HWZvyOFerh0NFzaP+5Cd9bqfIOT6hb2bPno2ZmZnaZ/bs2VnKWVtbY2xsTHCw+k2IwcHB2Nvba1y2q6src+bMYcCAAaSkpGil/poUziNWAbC0tKRTp04sW7aMFy9eqP0tODiYP/74g/791YfyGDduHNevX8fT05OZM2fSsGFDfv/9d5YtW4aHhwfHjh3LcjG6Y8eObNy4kSVLluDu7s7w4cP5+OOPmTRpklq56dOns2vXLmrVqsXvv/9Obvr06UNgYCCTJ0/G3t5elVg1a9bEx8eHnTt3Urt2bfr370/z5s1ZunSp2vyjRo3i9OnT1K1bl71797JhwwbWr1/Pxo0bqVevHn5+fqxfn3UYmjSdOnXCxsaGn376SePfo6KUdwMaGhry+PFj3nvvPdzd3ZkxYwY//vgj/fr1Uyvfrl07qlevTocOHejevTulSpViz5493LlzB09PT6ZNm8bPP/+s8bvmzZvH2LFjadCgAc+fP2f37t1qT7mXKlWKiRMnMnToUGrUqMHz589Zu3Yt9evXp2fPnjRp0gQDAwP27dunmi8v6zY3rxPDm4gIeUxsVAguNZqpphmbFKNS1QYE+l3Odr5A/yu41GymNs21ZnMC/a8AkJycyNOHN9SWC+BSo5lquXn57pTkRDAwwNi4WIYyxTEwMOTRvX+KdGwAiS8T2L5yDF0/moypuU2O8byO5OREngTcxK2Weh3dajbl4b0rGud56HcFt5rqd0u51WrO4wc3SElOylJeoVDgd8OXkKCAHIdMKwhJSUn4+d2lbj31etSt68ntWzfztIzU1FQSEuIpY2qqjSpmKy/5lFmg/5Us5V1rNOdpQPq6yi2PhfYlJSXh73cXj0x56VHXk9u3buRpGcq8TMDU1EwbVcxWcnIiQQE3cNWUl/6a8/KxprysqZ6Xmsq41GxOoN8VjctMTU3h33N7SXwZj5OLx5sF8wYMjI0pXaUq0RfOq02PvnCOMtkMd2lgYkJqpuGWUl++pHR1dwwy3ICoa0U5L/MiOSmJB363qVm3kdr0mnUbcu/2v3laRmpqKi8S4ildxlwbVRQaJCclEeB/m5oemdabRyP8bl/TUa2y0tUx+02+NzYqlHvXTlC3Rd88x/cm0tZdLQ3r7l4e113aNlemkO1TkpJTuPUoiCbVXdSmN67uzNX7gTnO+/6sX2k/fgGfLVzPhTsPtFnNbOmyL6TJi/gYMDCgRKmCWc82lkZYmBpx3e+lalpyCtwJSMStQt5Hc3N3LkY5ayNuB2QdUlEXinK/Jy/0Kb63rU8uiqaifqzLTVFpY+YmOTmJxw9uUrW2+v6hau2mBNzVfON3wL2rWcpXq9OMwPvp+5Mbl45Tya0O29fMYvLwlswd15tD3r+Smqr9i0r62k6Rc3xCHyUmJhITE6P20TTceJqMD80CGBgYZJkGymt+mzZtYurUqQX+2uGiMba1Fri5uWFoaMitW7c0/v3WrVuULVsWGxsbQkJCADh69Cjz589XlZkxYwY+Pj7MnTsXgHv37tG0aVM6d+6sKjNp0iTmzJmjujj84MEDJk+ezE8//cSMGelD9mzatIk1a9Lv3MxNREQEKSkpxMTEqN05MW7cODZt2qR6r7afnx9fffUVJ06c4PPPP+flS2WncN++ffz666+qOEaOHMmFCxfYvl15l9vcuXM5e/YsdnZ2We7MSPv9AG7fvp1jPZOTk5k2bZrq3wEBATRt2pT33nuPbdu2qabHxcUxdOhQkpKUO/thw4ZhZGTEJ598QkJCAjdv3sTR0ZEVK1Zk+Y7p06dz+PBhQPlU9ePHj3nnnXdUyy9WrBgjR47k2jVlg8fV1ZVevXrRtGlTfH2VTygNGDCAwMBAevfuzfbt2/n6669zXbe5GTBgQJ5jSKPpvQbZiY1W5mVpM/Unx0ubWRGVw11psVGhGueJjVIuLz4mAkVqCqXNNZUJzfN3Ozp7UKx4SQ5t+5l2fUcBCg5t+xmFIlX1XUU1NgCfLbNxcq1LtbrtcozldcXHRJKamoJppu83Nbfi7qs6ZhYbFYpppphMzaxITUkmLjYSMwvlBfcX8TH8+FVrkpOTMDQ0pNfgybjVyn7YkIIQHR1FamoqFhbqr3gwt7QkMiI8T8vw3rmNly9e0LxFK21UMVt5yafMYqNCKG2mPoxxaXPluoqPjcDUwjbXPBbal11eWlhaEvFaeZlAMx3kZWpqSpYcKmNuRez17POyjHmmvDTLmpdlMi9TQ14GB95h9awPSE56SbHipXj/y6XYOqiPgKJNxuYWGBgbkxSuvp6SIiIwKat5KL3oC+ew7t6DyL9PEH/3DqWqVsO6a3cMTUwwNrcgKTysIKqeq6Kcl3kRE608/plbqK8nc3MrIiPz9qTWPu8/ePkygUbN8/fYLLKXvt7U9w/mFmWJiigc2w7o7pj9Jt975Yw3xUqU1vpw42nrzuw/rLv9r7a5hs0K1zv+ImLjSUlVUNastNp0K7PShEbHaZzHxrwMkwd0x71iORKTk9lz9l8+W7SB1aMH45nNu0i1RZd9ocySkl5yePt8ajXqTomSBfO0m3kZ5XMXUbHqr6mKik3F2iLnG81KFjdg8ThbjI0NSE2F9XuiuOFfOC5oF+V+T17oU3xvW59cFE1F/ViXm5iYtHaKet/AzNyqULUxcxMXreyfZ9k/mFsRnc3+JCZSw/7kVRs0NiYSc0sbwp4/5l7IEzybdeOzCcsJefaQHWtmkZqSQqe+n2stHtDfdoqc4xNvSkHRf71taGgoycnJWZ7GtrW11Xht0NTUlAYNGlC3bl3Vg7SGhoYYGhqSlJREx44dOXbsmFbq+tZe0M5N2nuWM96BcPGi+pAt1atXx8vLS22ar6+v2kVPT09PGjRooPZEtpGRESVLlqRkyZIkJCRoXPab8vT0xNXVlQEDBqjFYmRkROXKlVUXoNMu7gKqpPz333+zTMsuaV/nPdTDhw9n6NChVKxYkZIlS1KsWDGuXLmiVubff/9VXcwG5W979epV1e8DqC4+Z5ZxekREBHfu3KF69eqqaS9fvlSLt3r16iQlJXHu3DnVtPDwcLX58rJuc/M6MaSZOHGi2g0AGV3z/Yu/1k9V/XvAN8oL4xrXRS7rxyDzjlahnJprmUzLzem7S5uVpd/ni9i7YTrnjmzAwMCQWo26Ua6iOwaG6iciilpsty8f5cGtcwyftjPHuvwnmb5foVDkst1lKq8MXG1qsRKl+WrWThJfxON34yx7N/1EWVsnXKo3zKdKv7kssSkUeXo3+YnjR9n8xwYmTZme5eRJQclLPqmVzxKr6g85L1MPGkhFjea0zH09nDx+lC1/rOe7KTN0l5dZ9iEa8kp9juwWlO0ylXOpT7MqV5kR0714ER/NzYsH8Vr9LUO+3VCgF7WVMt1VivI30OTpujWYlLWi2vLVGKC8+B16YC/lPhyIIjVV80w6VJTzMi+yxqLIJXeVzpzwwWvzakZNmpflorjQvqx5mVu7RTd0dcx+ne+9fGoHtRt3x8Qkbze5/ldvuu58T/qwc8sqRn33c6Hd5jTuL7MpW8nemkr21qp/13F2IjgiivWHfLV+kr8w9oUAUpKT2L5iNAqFgm4Dp2b5e35pUrsEQ3qmj6wxf2OEslqZjtsGBul9nOy8SFTw/bJQShQzwN25OB90NuN5eEqheUobina/Jy/0Kr63rE8uiqaicqx7U5mPWQrytk8pbLIee3Pen2SJ+9VBUXW9IjWVMmZleW/YNAwNjXByrkF0RAhH96zJ9wvab1s7Rc7xibdRUlIS//zzDx06dMDb21s1vUOHDuzatStL+ejoaLXX/gKMHDmStm3b8u677/LggfZG/3hrL2j7+fmRmpqKu7u7xpVSrVo1wsPDCQ1NvwMnLk79Dre8dPQNDQ2ZOnUqO3dmvfCVcajzzMt+U4aGhqxcuZIlS5Zk+dujR49U/5/x4rGmaWkHSsNs3qOS9p7ratWqcfZs9k/N9OvXj4ULFzJmzBh8fX2JiYlh3LhxNGqkPmTMm/y2Ocl4I0LGC8o5LTvjEAr5cQLuTZYxe/ZsFixYoDYtOjoagKoebXBwrq2anpKs7JTHRoViamGrmh4XHZblKbqMyphbExutfmdZXEwYZcyVjdpSppYYGBplufssLiZ9uWXMbPL03a41m/P13EPExURgaGREyVJmzPumOTWtHdWWXdRie3DrLOEhj5jzpXqn889fvqJCFU+GTNiQbR1zU8rUAkNDI2Iy1TE2Ojzb2MuYW2ssb2hkTKkyFqpphoaGWNspOynlK1bn+dP7HP9rlU47z2Zm5hgaGmZ5ujAqMjLXExmnThzjf4vnM2HiZDzqemqzmhrlJZ8yK2Nuk7V8dJhyXZW2eFUm5zwW2peelxFq06MiI/KYlz8zYeIUneWloaa8jA7LcqdxmrzmZdb9TBilM+WlsXExrF7tZxwq1+JpwHXOHlpPz49nUBCSoyJRJCdjUlY9VmNLS5KzeTpIkfiSgLmzePjzHIzLliUpLAybHr1IiYsjOSqyAGqdN0U5L/PC1Ex5/IvM9MRFVFR4rhfLzp46xOr/zeL/JvxITQ85IVyQsltv0VERWZ6o0SVdHbNf93sf3r1I2LMH9Bux8LXiexNp6y7zU055WXfKbe4H/m/C7EK5zVmWKYWRoQFhUep9zPCYOKwyPcmWk1qVHdl3Pm+vPPgvClNfKL0OSWxbPorIkMcMHr9Wq09nX779Ev/H6XUyMVb2oy1MDdWe0jYrbUh0bM43mikU8DxcOdzqo2fJlLcxpkfLMtwOyNsTwtpUlPs9eaFP8b1tfXJRNBW1Y93rMn21HUZFqrdTYvLQNyhMSpsp++eZn8aOiQ7PMgpEGlML6yzl0/Ynaa9WMrOwwdDYGMMMDwzZOTgTExlKcnISxsZ5f0VHbt6Wdoqc4xNvuwULFrBhwwYuXryIr68vn332GRUqVFCNNvzjjz/i4ODA4MGDUSgU3Lih/uq758+f8+LFiyzT89tb+w7t8PBwDh06xMiRIylRooTa3+zs7BgwYABbt27NcRk3b96kcePGatMy//vSpUtUrVoVf3//LB9N48+/jsTERIwyvdvx0qVL1KhRQ+P3abqI/aYOHjxISEgI48eP1/h3c3PlAbZFixacOXOG5cuXc+XKFfz9/XFxcdE4T0Y3b96kTp06ausm82+rabqFhQVVqlTJcSj0mzdvYmJionZRvWzZslSpUkU1BH1e1m1+xpBG03sN0hQvWQYru4qqj015V8qY2+B/84yqTHJyIgF3LuDkWjfb73By8cD/xhm1af7XT6vecWpsXIzyFWuoLRfA/8YZ1XItbRxf67tLm1pSspQZ92+dJS4mjKoebdT+XtRia95tGJ9P38WIaV6qD0Cn97+l9yezs61fXhgbF8Ohkjt+19Xr6Hf9DBXdPDTOU9HVI0v5e/+exrFyDYxyasQqFCQn6fZpBRMTE1xdq3Dlsvp71a9c/odq1d2zne/E8aMsXjiPseO+o0HD19s280te8ikzjTl64zTlK6Wvq9zyWGifiYkJLq5VuKoxL2tkO9/J40dZsvAnxoz7jvo6zMtylWpkyaH7N8/g5KI5Lx1dPLifKY/9MuWlo4sH9zXkrpOrR471USgUqg5vQVAkJxN39w5m9RuoTTer35DY6zmfqFGkpJAUEgKpqZRt24FI39PZP9atA0U5L/PC2MSEyq7VuH5F/f3n16+cx62a5vefg/LJ7JWLZzJy7EzqNmiebTmhHcYmJlRyqcaNq+rr7caV87hWq53NXAVPV8fs1/3eS6e2U65iDewrVHut+N5E2rq7flXTNpf9uvM96cOvS2bw+ZiZeNQvnNucibER1SuUw/fWfbXp527dp46zU56XcyfwGdbm2h9muzD1hSD9JHHY84cMGruGUmW0+7Tsi0QFz8NTVJ8nz5OJjEmhhkv6KAVGRlC1UjHuPXq9cxoGBmBcSB7jKMr9nrzQp/jetj65KJqK2rHudanamFfOqU0vbG3M3Bgbm+BY2Z2719RH7Lz7ry+VqtTROE8ltzrc/Ve9/J1rZ3ByTt+fVK7qQeizR6RmGFHseVAAZhY2+XoxG96edoqc4xNvSmFgWGg/r+PPP//km2++YcqUKVy5coWWLVvStWtX1UOy5cqVo0KFCtr4CV/LW3tBG+DLL7+kePHi+Pj40KJFCxwdHenUqROHDh3iyZMnasOEa7JkyRI6d+7MuHHjcHNz44svvsgyJPWMGTMYNGgQU6dOxd3dnWrVqvHee+8xc+bM/1z/gIAAWrZsSfny5bGyUt4pNHfuXJo0acLSpUupU6cOrq6u9OjRQ+MT2/9FfHw8Q4cOpVu3buzatYt27dpRsWJFPD09mTt3rurODT8/P+rXr0/Hjh1xc3NjxowZNGjQIJelK98pnpqaym+//Ub16tXp0qULY8eO1Vh2ypQptG3blho1arB27VpCQ0PVhkbIzM/PD29vb1atWkWzZs2oXbs2Gzdu5MmTJ6qn9fOybvMzhjdhYGBA4w6DOLVnJbf+OUTw47t4/zYRk2IlqNWou6rczlUTOLw9/d3vjToMxP/Gaf7et4qQoPv8vW8V92/50rjDYFWZJp0+5tLJ7Vw6tYOQp/4c2DybqPAg6rd+/7W++/KpHQT6XyH8+SOu+u5m27KvadJhMNblnIt0bKbmNtg5VlH7AJhblcfSRv3p8zfRvMvHXDi+nQsndvD8iT9/bZxDZFgQjdr1B+DA1gVsXfFtetxt+xMRGsSeP+by/Ik/F07s4OKJHbToOkRV5tjuX7n37xnCngfy/Ol9Tu1fy6XTu6nbrMd/ru9/1eudvhzy2c+hg/sJfPSQ1b8uIyTkOV26Kuu2bs1qFv48R1X+xPGjLJo/l0+GDqdqtepEhIcTER5OXFxsgdc9t3w6vH0+O1dNUJWv3/p9osKecmDLbEKe+nPp1A4undpB006fqMrkJY9fvogj6NEtgh4pb8KJDH1M0KNbRObwvqKCZFS6FKa1q2FaW3lCvmRFR0xrV6OEYzkd1yzver3zLod89nE4Q16Ghjyn86u8XJ8pL08eP8qi+XMYMnQEVau56zQvm3Z8lZcnlXm5f/NsosKCaNBGmZeHtqnnZYM27xMZ+pQDm1/l5ckdXD65g2ad0/Oy8au8PLVXmZen9q7i/k1fmmTIy8PbF/Dw7kUiQh8THHiHwzsWEnD7PLWbFOx+JvjPzVh364lV1+6UqFgRpy++ppitHSG7lTcfOQz7nErfTVGVL+7oRNkOnSju4Ejpau44T5lBycrOPFm1vEDrnRdFOS/zokuvDzh+aBcnDu3mSeADNq5eSFhIMO269AFg67pfWLFwmqr8mRM+rFw0nQ8/+QrXqjWJjAgjMiKM+EIanyZGpUthVqcaZnWU+8tSlR0xq1ONEk5FZ3/ZudeHnDi0i5OHd/M08AF/rF5AWOgz2nZWrrc/1//CyoXqwwA+vH+Xh/fv8iIhnpioCB7ev8uTR/c1LT7f6OqYndv3pnmREMvNCz7Ua9lPq79DRl16fajc5g6nbXPKddfu1brbuv4XVmRYd74nfVi5aBofDvn61TYXSmREaKHc5ga2b4LX6Ut4n77M/aAQ5v3pQ1BEFO+2VD79ucTrCN+v8VaV33jkLEev3OZhcBh+T5+zxOsIhy/f4v3Wufdd85su+0IpKcn8uexrngZcp++weaQqUoiJCiEmKoTkArxBzcc3jh4ty+BZvTgOtsZ81seCxCQFvtfSR1/7rK85/TqYqv7dvWVpargUw8bSiHLWRnRuWppmHiU5czVB01foRFHu9+SFPsX3tvXJs6MP7ZTs6EOftSgf6/KiU68POXE4vY256TdlO6VNp74AbNuwlF8XZW5j3uHh/Tu8fJFATHQED+/f4UmgdtuYuWndbRBnj+3g3LGdBD/xx2v9XCJCg2jaXrk/2bN5IX8sm6gq37T9e0SEBuG94SeCn/hz7thOzh3bSZtuH6eX6dCf+NhIvNbN4XlQADcuneCw9yqad3w/89fnO31up8g5PvG2W758OZUrV6ZEiRLUr1+fU6dOqf42ZMgQ2rRpk+2806dPp27d7G9qyS+F5F5V3Ui72Dpt2jS2bt2KlZUVz549w9vbm+nTp2cZ0jGzc+fOMXToUKZPn860adM4fPgwP/zwA5MnT1aVOXjwIN27d2fKlCmMHz+epKQkbt++zerVq/9z/adMmcLKlSvx9/enRIkSGBgY8O+//9KqVStmzZrFqVOnMDAwwN/fP9enzd/E7t27adq0KRMnTmTTpk2YmZkRGBjI0aNH+f777wFYsWIFHh4ebN26FYVCwebNm1m2bBldunTJcdlxcXH06NGDFStWcPnyZW7evMmECRM0Dt3+7bffsnjxYtzc3Lh69So9e/bM9Wn0IUOGsHjxYvbs2UOxYsU4efIkXbt2JTk5Gcjbus3N68Twppp1GUpS4gv2bpxBQlwUjs61GTjmN4pnGGolKvwpBobpw59XcK3HuyPmc3TnYo56LaGsrRPvjliAo0v6nYE1G3YlPjaSE7t/ITYqBFsHNwZ8sxILa4fX+u7QZwEc3rGQhLgoLKzL06L7CJp0/FgvYtOmOo27EB8byRHv5cREhmDv6MbHY1di+aqO0ZGhRIYFqcqXtXVkyNgV7PljDr6HN2FmYUuPgd9Rq0FHVZnElwl4r5tBVHgwJsWKY1POmf4j5lKncc7bYkFo0aoNMTHRbN20kfDwcCpWqsSU6T9ia2cHQEREOCEhz1XlffbvISUlhRXL/seKZf9TTW/bviPfjNY8aoS25JZPMVEhRIWnN0AtbRwZMGolBzbP4cLRTZha2NLlw0m41++kKpOXPH4acJ11P6U3fn22KE8M1WnWm3c+TT9JpCvm9WrS2Ge96t/uPyk7Z483eHFt+MTsZitU0vNyQ4a8nJ0hL8MI1ZCXK5ctYeWy9JvI2rbvyNejJ2RZvjbVbNSV+DhlXsak5eWo9LyMjQohKkw9Lz96lZfn0/JyQKa8dEvPy2NeS7C0daJfpryMjQ5j56/jiYkKoURJU+ycqjJwzCpcajQruOCBiGNHMHBEM3IAAQAASURBVDY3p/ygTzCxsiLhwX3uTRhDYvAzAEysrChua6cqb2BkiH3/DynuVAFFcjIxl//h1hefkfjsWYHWOy+Kcl7mReMWHYiJicJr6+9EhofiWNGZcVMWYm2rPLEYGRFGaEiwqvxRH29SUlJYt2Ie61bMU01v0bYbw7+ZkmX5hZG5Z02aHEl/VYn7z98BELh+J9c+LRr7y0YtOhAbE8Wurb8RGR6KQ0UXRmdYb1ERoYSHBqvNM2XUR6r/D/C/je9JH6xtyzF/VdZXQeUXXR2z89L2BLh+bi8KFNRq1E1rv0FmjV+tO+9X686xogtj1ba5UMJCM25zXsptbuVPrFv5k2p687bdGP619t6x/CY61a9BZGw8K/eeJDQ6Ftfytiz98kPKW1kAEBIVS1B4lKp8UnIKC3cc4nlkDMVNjHEpb8P/vviAFrXcdFJ/XfWFoiOecefKUQBWTOutVqfB49dRuZr6q8O0Ze+pOIoZGzC4hzmlShhy/3EiP60L50Vi+sgpVuZGKDKMQF7cRFm+rJkRiUkKgkKTWbk9knPXX2j4Bt0oyv2evNCn+N62Pnl29KGdkh196LMW9WNdbho170hsdBS7tq4mKiIUhwoujJ68KL2dEh5KWIh6n23q6IxtzFucPemDlU055q/aXaB1z6huky7ExUThs3MF0ZEhlHNy47MJyylrUx5Q7k8iQtP3J1a2jgwbvwzvDT/x98HNmFva8s7gidRp1EFVxtKqHCMm/or3hp+YN6EP5pa2tOzyEe16flogMelrO0XO8QlR+BmQ/qp6IYqUVq1acfz4cSwsLIiKisp9hiJKoVCw+bR+bqYfNFM2bPQxvrTYvM6n6Lgm2vFOQ+XrDu74B+q4JvmvqotyeC59zst9pbQ/lKkudI1Xvm7itv9jHdck/1VzUY7+sOWM/uXl+02VeXmxVRMd10Q76p9QDhenz3l54U6kbiuiBQ2qWgCw16SqbiuiJd2S7gBw9rb+taEbV1O++kifj+Pn9XC9ATR8te4Sjv2h45rkv5JtBgD6mZeQnpuDJgflUrLoWT9TeeFEn/s9+hgbpMenj33ytP64PrZT0too+t5n1edjne+taB3XJP81qW4GwL5L+fc6z8Kkaz3l8Nj62E7R93PPBgYGuRcUWhVx+Ziuq5Aty7rZP1FdVL3VQ44LIYQQQgghhBBCCCGEEEIIIYQovOSCthBCCCGEEEIIIYQQQgghhBBCiELprX6HtijaTpw4IcNqCCGEEEIIIYQQQgghhBBCiAKlkOtTBUqe0BZCCCGEEEIIIYQQQgghhBBCCFEoyQVtIYQQQgghhBBCCCGEEEIIIYQQhZIMOS6EEEIIIYQQQgghhBBCCCGEEHmkMJBnhguS/NpCCCGEEEIIIYQQQgghhBBCCCEKJQNAoetKCCGyp1DIJiqEEEIIIYQQQgghhBBCCCUDAwNdV+GtF3b1pK6rkC2rOi11XYV8J0OOCyGEEEIIIYQQQgghhBBCCCFEXslNBQVKLmgLUQRsPq2fT2l/0Ey5w99yRv/ie7+pMrZ9l5J0XBPt6FrPBIAXB9fouCb5r0THIYB+bndp29yZWzE6rol2NK1uCoD3hRQd1yT/9W5gBOh3XvreitZxTbSjSXUzQL/z8q9/knVck/zXw1PZTTp7O0rHNdGOxtXMAdhrUlXHNcl/3ZLuABCzeIyOa5L/TL+eD+jnNgfp292LI+t1XJP8V6LdIEA/j+OQfizXx75PWr8n/vepOq5J/iv1yXRAP/t0kN6v0+e81Md2SlobRd/7rPp8rNPnfo/Xef2LDeCdhsr49Pn8rD62wdLaX0K8TeQd2kIIIYQQQgghhBBCCCGEEEIIIQoleUJbCCGEEEIIIYQQQgghhBBCCCHySGEgzwwXJPm1hRBCCCGEEEIIIYQQQgghhBBCFEpyQVsIIYQQQgghhBBCCCGEEEIIIUShJEOOCyGEEEIIIYQQQgghhBBCCCFEHikw0HUV3iryhHYRMHjwYCIiInRdjUKlVatWKBQKzM3NdV0VIYQQQgghhBBCCCGEEEIIIYSWyBPaWuDo6Mi0adPo0qUL1tbWBAUF4e3tzYwZMwgPD9d19dQcO3aMK1euMGrUKAAePHjAokWLWLx4sU7q8+DBAypVqgRAQkICwcHBnD9/nhUrVnDs2DFVuTNnzmBvb09UVJRO6vkm1qxZg4WFBe+8847WvuP80U2cOfAbMZEh2Dq40vmD76hYpX625QPunMdnyxyeP/HD1MKWZl2G0qDN+2plbl704ajXEiJCHmFpU4F2fb6humcH1d9P7V3JrX8OERp0H+NiJXByrUuHd8dgXc4532M7vf83YiNDsHFwpcuHucR2+zwHtswh5IkfppY5xxb+/BFlbbPGdv7oZi4e20xk6BMAbBxcad3zC9xqt8zX2DT5++AWju1ZQ3RkCPaOrvQeNAGXap7Zlve7eYFdG+fx7LEfZpa2tO0+hGYd+quVSYiLZu/WJVy7cJiEuGjK2jjQ66NxuNfVfjy52XryEmuPnCM0OhaXctaM79Oeeq5OGsteuPeQoUs2Z5nuPWkYle2ttFpPhULB8V1L+efEn7yIj8bBuTbdPpqCrYNbjvPlth1B7ttvbt8dEfqYxePba/z+fp8vokaDzv8xes2O7tvGfu8NREaE4uDkzIefjqFKjboay0aGh7JlzUIe+t8iOCiQ9t3e58OhY7RSrzfhe2gzJ/b9TkxkCHYOrvT46FsqV8t+P3P/1gX2/DGX4Cd+mFnY0qr7JzRu977Gsld897H5l7G4e7Zl8Kil2gpBRVe5mpKcxFGvxdy7doKIkMcUL1kGZ/emtH93NGaWdlqLN7Mj+7ax33tjhrwcTdUc83IRAaq87M8AycsCcfrQZo7vWaOKrdegb3HO4Vjnf+sCuzf8pIqtdY9PaNo+/Vh34YQXW1d+n2W+2WsvYVKsuFZieB1H9m1nn9cGoiLCKF/BmQGfjsoxLzevWUSA322CgwLp0L0/A4aOLuAa/3dlm9fHecynmNerSYnytlzsO5Lg3Ud0Xa3XZlK7KcXqtcagtBmpYc94eXIXKU8faCxbosP7mLg3yDI9JewZ8RvnabuquXqbtrutJy6y9vBZQqNicSlnw/h+HajnWkFj2Qt3HzJ00cYs072nDKeyvbW2q5qFLtucx7z/x/Xz+4gOf4aRsQnlKtagXZ9vcHSpo5VYIf/7PktnfIz/rYtZ5qvu0YLPJizXSgx59eele6w7f5vQ2ARcrM0Z264u9Zxssy2fmJzCr2dusPdGAGFxL7AzLcmnTWrQu3b+9rfzS1Hp1+XF29Qn1/c2ij71WTMryse6zPS53+N7eDMn9/5OTJQytu4ffUvlqjnHtndTemwtu2Uf21XffWxeNhb3em0ZVACx6eL8bEYn96zkyI6FNO4wiC4ffpevsYGcSxGisJMntPNZ5cqVuXjxIlWqVOGDDz7A1dWVESNG0K5dO3x9fbG0tMx2XhMTE63Vy9i46Ny7MHnyZOzt7alatSqDBg0iMjKSw4cP89136QeppKQkgoODdVjLwuf6+X0c2DybFt1HMGKaFxXc6rNx4WdEhj3VWD4i5DF/LBxOBbf6jJjmRYvuw9m/aRY3L/qoygT6XWbbitHUadqTEdN3UadpT7atGMVj/6uqMgF3LtCg7YcM/X4rg8b8TmpKMhsWDCXxZXz+xXZuHwc2zaZl9xGMmO5FxSr12bgg59g2LhxOxSr1GTHdixbdhrP/Dw2xLR9N7SY9+XzGLmo36cmfy9VjMy9rR/t3x/DZ1O18NnU7las3ZvOSL3j+5F6+xabJZd/9eK+fQ4fewxg7exvOVevx65wRRIQGaSwf9vwxq34aiXPVeoydvY0OvYbitW42V88dUpVJTk5i+Y/DCA95wsffLGDi/D30HzYd87LZnzwpKAf+ucVPOw8zrFNTtk4YQj0XJ0Yu/5Og8JxvWNk1+TOOzPpS9algm/3+Nb+c3r8a34Nr6frRZIZN3kYZcxvW//wJLxNis50nL9tRXrbf3L7bvGw5xiw8pfZp3fv/MCleCtdaLbTye5z7+yCbfp9P936fMH3BH1Rxr8uCmV8RFvJMY/nkpERMzS3p3u8TnCrl3BkoaFfP7uevjbNp23M4X/2wg0pVPfl93nAiQjXvZ8KfP+b3n0dQqaonX/2wgzY9P2P3+h/59/zBLGUjQp+wd9M8KlfN/gRYftNVriYlviDo4U1a9hjJ8Kk76P/l/wgLDmDzkpFajzmNMi8X0KPfEGYs2EgVdw8WzPw627xMSkrE1NyCHpKXBeqK7352r59D+96fMerH7ThXq8fqudnHFvb8Mat/+hznavUY9eN22vUexq51P3ItU2wlSpZhyrLjah9dX1QDOHfqEH/89iovF26gqrsH82d8k3NemlnSo9+QQpeXr8OodCmir93hxtczdF2VN2bs5kHxlr1IvHCE+E0LSHn6gJK9hmFgaqGx/IsT3sSumpb++W0GioQ4ku9d1Vi+IL1N292Bizf5afshhnVuxtaJQ6nn6sTIX7bk3r6cOoIjs79WfSrYli2gGqvTZZvTyr4SXQdM5vMZu/lk4h9YWDuwYcGnxEVr5+Z8bfR9hoxezPTlx1Wf8T95Y2hohEfjTlqJIa98bj1i3pHLfNrEnc0fd6Kuow1fbjtJUHRctvOM33WG8wHBTO3SEO9hXZndoymVypoVYK3zrij163LzNvXJ9b2Nok991syK+rEuI33u91w9u589G2fTptdwvpqpjG3NvOFE5hDbmrTYZu6gdc/P+GvDj/x7IZvYNs+jUgHFpqvzs2me3P+Xf078iZ1TVa3F+DafSxFvRmFgWGg/+kg/o9KhX375hcTERDp27MjJkycJDAzkwIEDtG/fHgcHB2bNmqUq++DBAyZNmsSaNWuIjIxk1apVgHKI8YcPHxIXF8fOnTuxssp6Z2r37t25ePEiCQkJ+Pv7M2XKFIyMjFR/VygUDB8+HG9vb2JjY/n++6x3zWd27NgxKlWqxKJFi1AoFCgUCtXfmjRpwokTJ4iPj+fRo0csXryYUqVKZYll3bp1xMTEEBAQQM+ePbG2tsbb25uYmBiuXbuGp2fuB9iYmBiCg4MJDAzk1KlTDB8+nJkzZzJjxgyqVKkCZB1yvEKFCuzevZvw8HBiY2O5fv06Xbp0US3T3d2dPXv2EBUVRXR0NCdPnsTZWXlHs4GBAZMnTyYwMJAXL15w+fJlOnVK7+hqGt68Tp06KBQKKlasCKQPC9+xY0du3rxJTEwM+/fvx97eHoCpU6fy8ccf07t3b9Vv26pVq1x/i9fh67OWei364tmyHzblXejy4XeYl7Xn4rGsdzwDXDy+BXOrcnT58Dtsyrvg2bIfdVv04YzP76oyZw+tx8W9KS26DcemnDMtug2ncvXGnD20TlVm4OjV1G3eB1sHN+wrVKP3J7OJCnvK04Ab+RbbmYNrqduyL56t0mMzK2vPhaOaY7twLFNsrZSxnT6QHpvvwfU412hKy+7K2Fp2H45z9cb4ZoitqkdbqtRphbV9ZaztK9O+7yiKlShFoIZGVX46vnc9jdr0oXHbd7FzcOGdwd9iYWXP6UNbNJY/c/hPLKzseWfwt9g5uNC47bs0bP0Ox/auVZU5d2wn8bFRfDpmCc5V61HWpjzO1erhULGaVmPJiw3HzvNOkzr0aVoHZ3trxvdtj72lGX/+fTnH+cqWKYW1WRnVx8hQu4c0hULB2UPradl9BO6eHbFzrMI7n84hKfEF/57bk+18edmOctt+8/LdhoZGmJrbqH1uXzpMzQZdKF6itFZ+k4O7/qBl+1606tCb8k6V+XDoGMpa23H0wHaN5a3tyjNg6FiatelOyVJltFKnN3Vq/1oatO5LwzbK7a7nwImYW5Xj7BHN293Zo1uxsCpHz4ETsXNwoWGbd6nfqg8n961RK5eamsKWZRPo0PdLytpqfjolv+kyV0uUMmXQ2N+p2bAL1uWccXLxoOuA7wl6eCPbTm5+89m1SS0vB+SSlzaqvOwmeVmATuxbR8PWfWn0KrZegyZiYVUO38NbNZb3PbIVS6ty9BqkjK1Rm3dp0LoPJ/asVS9oYICZhY3apzA4sGsTLdv3pHXHtLwcTVlrO47s36GxvI1deT4aNobmbbtRqnThysvXEeJzkrtTF/HM+1DuhQupYvVaknTjPEk3zpEa8ZyXJ3eRGhuJSa2mmmdIfIEiPkb1MbJ1ghIlSbp5oWArrsHbtN1tOHqOd5p60KdZXZzLWTO+X0fsLcz48+SlHOcra1oaa/Myqo+225ea6PI4DlC7cQ9cajSlrK0Ttg5udHr/W14mxBL8+I5W4tVG36d0GXPMLKxVn7v/+mJSvAR1GnXUSgx5tfHCbXrXdqZPHRecrc0Z174e9qal2HbZT2P50/eD+CfwOf/r15LGlewpb16GmuWt8HDU/ZOUmhSVfl1evE19cn1vo+hTnzWzonysy0yf+z1/719L/VZ9adj6XWwdXOjxUc6xnTu6FQvrcvT4aCK2Di40bK2M7ZSm2JZPoEOfLylrUzCx6er8LMDLF3Hs+HUsPT+eSclS2rmx620/lyJEUaD7I5YesbS0pFOnTixbtowXL16o/S04OJg//viD/v3VhxsaN24c169fx9PTk5kzZ9KwYUN+//13li1bhoeHB8eOHctyMbpjx45s3LiRJUuW4O7uzvDhw/n444+ZNGmSWrnp06eza9cuatWqxe+//05u+vTpQ2BgoOoJ6bSLsTVr1sTHx4edO3dSu3Zt+vfvT/PmzVm6VH0Yk1GjRnH69Gnq1q3L3r172bBhA+vXr2fjxo3Uq1cPPz8/1q9fn+ffM6PFixdjYGBAr169NP79l19+oXjx4rRs2ZJatWoxYcIEYmOVd06VL1+ekydP8uLFC9q2bYunpye///676qn1r7/+mjFjxjB27Fhq166Nj48Pu3fvxtXV9bXqWKpUKcaOHcvAgQNp2bIlFSpU4Oeffwbg559/ZuvWraqL3Pb29pw5c+aNfgtNkpMTefrwBi41mqlNd6nRjEA/zZ3HQP8rWcq71mjO04AbpCQnpZepmalMzeYE+l/Jti4vEmIAKFk6f95vnpycSFDADVw1xeavObbHmmKrqR6bpjIuNZsT6HdF4zJTU1P499xeEl/G4+Ti8WbB5EFychKPH9ykam31k6RVazcl4K7mC+kB965mKV+tTjMC76fHe+PScSq51WH7mllMHt6SueN6c8j7V1JTU7QTSB4lJadwK/AZTapVUpvepFolrj54kuO8/eeuod2k/zHsf5s5f/ehFmupFBHymNioELW8MTYpRqWqDbLdziD37Sgv2++bfPfTgOs8e3SLui37vlaceZWclESA/21qeDRWm17DozH+t69p5Tu1JTk5kScPbuKWaT1VqdmUh/euaJzn0b0rVKmpvt1VqdWcxw/StzuAw17LKG1qScPW2lkPmugyVzV5ER8DBgaU0FKnM6O0vKzp0Uhtek2PRvhJXqqm6SIvM0qLrUrtzHVtSsDdKxrneXjvKlVqZT42NiMwU2yJL+L54av2zPyyLb/NG8mTgFv5Xv/XpU95+dYxNMLQ1pGUR+oX8lIe3sGoXKU8LcKkRkNSHt1DEROhhQrm3du03SUlp3DrURBNqldWm96kujNX7z/Ocd7+s1fT7ttFDFv8B+fvBGixltkrTMfx5ORE/jmxleIlTbFzyv+Lbtrq+2R27vhO6jbpQvESpTT+vSAkpaRw61kETSrbq01vXNmeq09CNc5zwu8J7vZlWXvuNh1/2UWvX/ey4OhlXiQlF0SVX0tR6tfl5m3qk+t7G0Wf+qyZFfVjXUZ63+8JuIlbLfXY3HKI7aHfFdwyxeamIbYjr2JrUECx6fr87N4NM3Cr0xqXGtncVJoPClMbDAr2XIoQRUXRGYe6CHBzc8PQ0JBbtzR34G/dukXZsmWxsbEhJCQEgKNHjzJ//nxVmRkzZuDj48PcuXMBuHfvHk2bNqVz5/R3n06aNIk5c+aoLg4/ePCAyZMn89NPPzFjRvpwfps2bWLNGvW7t3ISERFBSkqK6gnpNOPGjWPTpk2q92r7+fnx1VdfceLECT7//HNevnwJwL59+/j1119VcYwcOZILFy6wfbvyrse5c+dy9uxZ7OzsXnu48IiICJ4/f656v3ZmFSpUYMeOHVy/fh1Q/iZpvvjiC6Kionj//fdJTlZ2/O7dSx8yeuzYscydO5etW5VPJnz77be0adOGb775hi+//DLPdSxWrBgjRozg/v37ACxdupQpU6YAEBcXR0JCAsWLF88x9mLFilG8+OsPzxcfE4EiNYXS5upP85c2syI2SnPnODYqhNJmzdXLm1uRmpJMfGwEpha2xEaFUtpM0zJDNC5ToVDgs3UOFdw8sXOs8tpxaBIfE0FqakqWepQxtyL2evaxlTHPFJtZ1tjKZF6mhtiCA++wetYHJCe9pFjxUrz/5VJsHV7vZofXERetjNc007o0NbciOpt1GRMZqrF8akoysTGRmFvaEPb8MfdCnuDZrBufTVhOyLOH7Fgzi9SUFDr1/Vxr8eQmIi6elFQFVqbqTxBbmZYmNJuh92zMyjDl/c64V7AnMTmFPeev89nSzfz21Yd4ZvOuqPwQG63MDU3bRFQOd0vmth3lZft9k+++dGoH1uVcqOBaL7fQ3khMTCSpqSmYWagPT2ZuXpbrEZpztbCKfxVLGfOs+5mYyGy2u6hQjeVTU5KJi4nEzNKGgLuXuHB8J9/8uFNrdddEl7maWVLSSw5vn0+tRt0pUVL7Tzhkl5dm5lZERYRp/fvzk77lZUZxr2LTdOyKyelYV1vzsS4tNtvyzvQfMYtyTm68SIjj1IENLJ32EaNn78SmXEWtxZObmGhlvOYW6vU3tyhb5PLybWNQsjQGhkakxqsPMahIiMWwtGnu85cyxahSNV4c+ENbVcyzt2m7i4hNa1+qH3eszEoTGq15uEgb8zJM+bBrevvy3L98tuQPfvtmIJ5u2mtfalIYjuN3rhxj+8oxJCUmYGpuw6Cxv1PaNP+HgdZW3yejh37/EhR4j/6f6fbVBxHxiaQoFJQtVUJtulXp4oTFvdA4z5PIWK48DqG4sREL3mlORMJLZh+8SPSLRKZ1baRxHl0pSv263LxNfXJ9b6PoU581s6J+rMtIn/s9abGZmmXdP9zN9nythv3Jq3OacbGRmFm8iu3ETr6eVXCx6fL87L/n9hL08CafTdU8skJ+KQxtsDQFfS5F/AcGBrquwVtFLmgXIINXyZ1xKO+LFy+qlalevTpeXl5q03x9fdUuaHt6etKgQQO1J7KNjIwoWbIkJUuWJCEhQeOy35Snpyeurq4MGDBALRYjIyMqV67M7du3Abh2Lf3uxrSLtv/++2+Waba2tm/0/msDAwO13y6jJUuWsHz5cjp27Mjhw4fZsWOH6rs9PDw4deqU6mJ2Rqampjg4OHD69Gm16adPn6ZOnTqvVb+4uDjVxWyAoKAgbG1f711IEydOZNq0aa81T0YGZNqBKshxp2qQ+W8K1R9yXmbmaa/s2ziT4MA7fDJxU57q+zoy11Wh0FA39TmyW1C2y1TOpT7NqlxlRkz34kV8NDcvHsRr9bcM+XaDVi9qa6oHCoXG+mZXPm1bUe13UlMpY1aW94ZNw9DQCCfnGkRHhHB0zxqdXtBOk2X9ku0apJKdFZXs0huBdSo78CwymnVHzufriY9rvn/x1/qpqn8P+GaFxrq+mpjjsvKyHeVl+83rdyclvuDfs3to1UP76zZL7qEoso25rL9vLtudhvLK6fAyIY4tyyfQd+h0rZwAzqgw5ipASnIS21eMRqFQ0G3g1Cx/1ybJS/XyyukFm5d5o2E95XRsz9IWUKgtpqJbHSq6pbffKlWpy6JJ73L64B/0HvxdflT4P8nS7Mrl2C4KEQ19kGy6JWpM3BugePmCZP/rWqjUm3p7trvX2eaytC+dHXkWEc26w2e1fpK/MB7HK1dvxIhpXsTHRnDpxDa2Lf+God//meWEc37J775PRueO76SckxsVXWv994rmg6x5mf0WmPrqd5jVozGmxYsBkNi2LuO8T/NtB09KmBS+U3qFsV/3pt6mPrm+t1H0qW+QWVE51uWFXvd7NLSnct7GNLXXlFNfJsSxdfkE+n6qm9gK+vxsVFgQ+zf9yKAxv2Fi8voPgeWkMLbBQLfnUoQo7Apf67cI8/PzIzU1FXd3d3bt2pXl79WqVSM8PJzQ0PQ7b+Li1O9UzUuD0dDQkKlTp7JzZ9a7sDIOdZ552W/K0NCQlStXsmTJkix/e/Toker/k5KyDu+VcVpaY97wDd7NkvZke8YnrzP67bff8PHxoVu3bnTs2JGJEycyZswYli5dqrrAn5PMF8ozXjxPTU1VTUtjYmKSZRmZ41coFK8d6+zZs1mwYIHatOjo6FznK2VqiYGhUZa7uuJiwrI96VDG3CZr+egwDI2MKVXa4lUZa2KjNSzTPOs7u/b9MZM7V44y5NuNmJe1z/L3N1XK1BJDTbFFh2W5sy1NXmPL/DRKbHQYpTPFZmxcDCs75dMlDpVr8TTgOmcPrafnx9q5w7+0mTLezHd+x0SHZ7mjM42phXWW8rHR4RgaGVO6jHLodzMLGwyNjTE0NFKVsXNwJiYylOTkJIyNs+Z0QbAsXQojQ4MsdxCHx8RhZZb39z7XruTA3gv59952gKoebXBwrq36d0pyIvDqblmL9JtV4qKz384g9+0oL9tvGTOb1/rumxd9SEp8QZ2mvfMS6hsxNbXA0NCIqEj1O/ejoyKy3OFf2JV6FUvmu79jo8Kz3PWdxtTcWmN5QyNjSpWxIPiJHxEhT1g3/wvV3xUK5fFk4qBajJ23Fyu7/DlpUJhyNb0OSWxbPorIkMcMHr+2wO4ozi4vY6LCMc/0ZEZhV9TzMiel02LLfOyKCs/yNEIaUwsNsamOdRYa5zE0NMTJuSYhz3Q7fKmpmTLeyIis+8vMTwyJwkWREIciNQXD0qakZphuULIMiviYXOc3qdGQ5NsXQceveIG3a7uzLJNd+zI+y9OjOald2YG957V/M0JhPI4XK14KK7uKWNlVxMnFgyXfduLyqe206Db8zYLMhrb6PmkSXyZw+cx+Ovf7Al2zLFUMIwODLE9jh8e/pGzpEhrnsS5TEtsyJVUXswEqW5mhAIJjEqhYNveRIgpKYe7Xva63qU+u720UfeqzZlbUjnU50ed+T6ns2l/R4Tmcr9V0vjJTbKFPWLcga2zfDa7FmJ+0E5uuzs8+fXiDuOgwVk5PH1o9NTWFh3cvcv7IH0xedU1tv/o6CmMbTFfnUoQoKuQd2vkoPDycQ4cOMXLkSEqUUO+Q2NnZMWDAANWw1tm5efMmjRurv9sl878vXbpE1apV8ff3z/LJ7gnmvEpMTMTISP0gcOnSJWrUqKHx+zRdxNaGr7/+mtTUVLy9vbMt8/jxY1auXEnfvn2ZP38+w4YNA5RPjrdo0UL1zuyMYmJiePLkCc2bqw9/0rRpU9XQ8WnDw5crV071dw8Pj9eOQdNvq6lMTEyM2icvjI2LUb5iDfxvqr+X2//GGZxc62qcx8nFA/8bmcufpnylGhi96khpLHP9tNo7pBUKBXs3zuDWP4cYPH4tljaOeapzXhkbF6NcpRpZ6nH/5hmcXDTH5ujiwf1Mv4VfptgcXTy4ryF+J1ePHOujUChUDRxtMDY2wbGyO3ev+apNv/uvL5WqaB41oJJbHe7+q17+zrUzODmnx1u5qgehzx6pbtAAeB4UgJmFjc4uZgOYGBtR3cmes7cD1KafvRNAncoOeV7O7cfBWL/GiZK8KF6yjOpEnpVdRWzKu1LG3EZtO0tOTiTgzoVstzPIfTvKy/ZraeP4Wt996dR2qnq0obSZ9k5CGJuYUMmlGjeunFObfvPKOVyq1c5mrsLJ2LgYDpXduXddfR3cu36Gim4eGuep4OahofxpHCsrtzubcs6Mmr2Lr2ftVH2q12uDc/WGfD1rJ+ZW+XfjT2HKVUjvgIU9f8igsWsoVabg7hrPLi9vXDmPq+RlgeZlTtJiu/uvel3vXj9DpSoeGuep6FaHu5liu3vtDE6V0491mSkUCp48vI2ZhY3GvxcUVV5ePa82vSjm5VsnNYXU548xqqD+Kh2jClVICQrIcVYjBxcMLWxIunE+x3IF5W3a7kyMjaheoRxnb6nfDH329gPqOOe9r3L7cTDW5to/iVjYjuOaKFCQnJT/fSBt9X3SXDnrQ3JyIvWb98jfir8BEyMjqttbcjbgmdr0swHPqOOQ9YZxAA8Ha0JiE4hPTD/v8jAiBkMDA+xMS2q1vq+rMPfrXtfb1CfX9zaKPvVZMytqx7qc6H2/p5I7fpnq6pdDbBVdPbKUv/evemzf/LiLr37YqfpUr6uM7asftBebrs7POldvzMiZuxkx3Uv1KV+pJrUa92DEdK83vpgNha8NpstzKeLNKTAstB99pJ9R6dCXX35J8eLF8fHxoUWLFjg6OtKpUycOHTrEkydP1IYJ12TJkiV07tyZcePG4ebmxhdffKE23Dgo3089aNAgpk6diru7O9WqVeO9995j5syZ/7n+AQEBtGzZkvLly2NlpbxDaO7cuTRp0oSlS5dSp04dXF1d6dGjh8YntvODqakpdnZ2ODo60qJFC1auXMn333/PpEmT8Pf31zjPwoUL6dixI5UqVaJu3bq0bdtWdUF66dKlmJmZsWXLFtXw6R999BFVqihPTM2bN48JEybw3nvvUaVKFWbPno2Hh4faO8MfPXrEtGnTcHNzo2vXrowZM+a14woICKB27dpUqVIFKysrjRfY/4smnT7m0sntXDq1g5Cn/hzYPJuo8CDqt34fgMPb57Nz1QRV+fqt3ycq7CkHtswm5Kk/l07t4NKpHTTt9ImqTKMOA/G/cZq/960iJOg+f+9bxf1bvjTuMFhVZu/GGVzz/Yu+w3+mWInSxESFEBMVQlKi5veAvYmmHV/FdlIZ2/7Ns4kKC6JBG2Vsh7apx9agzftEhj7lwOZXsZ3cweWTO2jWOT22xq9iO7VXGdupvau4f9OXJhliO7x9AQ/vXiQi9DHBgXc4vGMhAbfPU7uJdk+ItO42iLPHdnDu2E6Cn/jjtX4uEaFBNG3fH4A9mxfyx7KJ6b9P+/eICA3Ce8NPBD/x59yxnZw7tpM23T5OL9OhP/GxkXitm8PzoABuXDrBYe9VNO/4vlZjyYuBbRqy0/cqXr5Xuf8slHk7DhMUHk2/5spG3eLdx5m0/i9V+Y3HLnD06l0ePg/HLyiExbuPc/jKHd5v6anVehoYGNC4wyBO7VnJrX8OEfz4Lt6/TcSkWAlqNequKrdz1QQOb5+v+ndetqPctt+8fjdAWPBDHt69SL2W/bT6ewB07DWAk4e9OXl4F08DH7D5t/mEhT6jTSflnbPbNixl1aIpavM8un+HR/fv8PJFAjHRETy6f4cngfc1Lb5AtejyMReOb+fCiR0EP/Hnr41ziAwLonE75Xa3f+sCtq74VlW+cdv+RIQF8dfGuQQ/8efCiR1cOL6Dll2HAGBSrDj2Tm5qn5KlzChesjT2Tm4YGxfTWI/8oMtcTUlJ5s9lX/M04Dp9h80jVZGiOi4ka/FmoIw69fqQE4d3cfLwbp4GPmDTbwuy5OWvi9SH7Xp4/w4PM+TlQ8lLrWvVdTDnj+3g/HHlsW7XhjlEhqbHtm/LQjZnONY1adefiNAgdm9Qxnb++E7OH99Bq+4fq8oc3LGMO1f/Jiw4kCcBt/jz18k8fXiHJu3eK7C4stO514ecOJSel3+sVuZl2859APhz/S+sXJg5L+/y8P5dXiTEExMVwcP7d3nySPd5+TqMSpfCrE41zOpUA6BUZUfM6lSjhFO5XOYsPBIvncSkRiOM3RtiaGlL8ZY9MTS1JOnVhYtiTbtSouMHWeYzqdGQlKCHpIY9y/I3XXmbtruBbRux88wVvM5c4X5QKPO2HyIoIop+LeoBsNj7GJPW7laV33j0PEev3FG2L5+GsNj7GIcv3+b9VvULvO66PI4nvozn8I4FBPpfITL0CU8f3mDXmu+JDn9GjQbq5yXyizb6PmnOHttJrfptKW1qoZW6v66PGlTD6+p9vK/d535oFD8fucSz6Hje9VC+zmrJiat8v+esqnwX94qYlyzG1H3n8Q+N4p/A5yw6dpVetSoXyuHGi0q/Li/epj65vrdR9KnPmllRPtZlps/9nuYZYnueIbZGr2I7kCm2Rm2V7a89f8zl+avYLp7YQYscYitRyoziJbQfmy7OzxYvWQY7xypqn2LFS1KqjAV2juo3nf5Xb/u5FCGKgsLXAi7i/Pz8qF+/PtOmTWPr1q1YWVnx7NkzvL29mT59OhERETnOf+7cOYYOHcr06dOZNm0ahw8f5ocffmDy5MmqMgcPHqR79+5MmTKF8ePHk5SUxO3bt1m9evV/rv+UKVNYuXIl/v7+lChRAgMDA/79919atWrFrFmzOHXqFAYGBvj7++f6tPmbmjlzJjNnzuTly5c8e/aMs2fP0q5dO44fP57tPEZGRvzyyy84OjoSHR3NgQMHGDVqFKB8cr5t27bMmzePEydOkJKSwpUrV1TvzV6yZAlmZmbMnz8fW1tbbt68Sc+ePfHz8wMgOTmZDz74gOXLl3P16lUuXLjA999/z/bt218rrlWrVtG6dWsuXryIqakprVu35sSJE2/2I2lQs2FX4mMjObH7F2KjQrB1cGPANyuxsFbeDR0TFUJU+FNVeUsbRwaMWsmBzXO4cHQTpha2dPlwEu71O6nKVHCtx7sj5nN052KOei2hrK0T745YgKNL+l3JF49tBmDt3EFq9en1yY/Ubd4nf2Jr1JX4OGVsMWmxjUqPLTYqhKgw9dg+ehXb+bTYBmSKzS09tmNeS7C0daJfpthio8PY+et4YqJCKFHSFDunqgwcswqXGs3yJa7s1G3ShbiYKHx2riA6MoRyTm58NmE5ZW3KAxAdGUpEaJCqvJWtI8PGL8N7w0/8fXAz5pa2vDN4InUadUj/TazKMWLir3hv+Il5E/pgbmlLyy4f0a7np1qNJS86e1YnKi6BXw+cJiQ6Dtdy1vzyeT/Kl1UOzRYaFcuziPSh95NSUljgfZTnUbEUNzHGxd6apSP60aKGi9br2qzLUJISX7B34wwS4qJwdK7NwDG/UTzDEEBR4U8xMEx/RUFetqPctt+8fjfA5b93YGZhp/U8BWjUvCNx0VHs3rqaqIhQHCq4MGryYqxtlRcqosJDCQtRP5E/dfQA1f8H+N/i7MkDWNmU4+dVf6FLdRp3IT4mkiNey4mODMHe0Y0h41ZimbYPjQwlMsN2V9bWkU/GruCvjXPwPbwJM0tbeg76jloNO+oqBDW6ytXoiGfcuXIUgBXTeqvVafD4dVSu1kiLUSs1at6R2OgodmXIy9GTF6nyMlJjXn6k+n9lXvpgZVOO+at2o0v6lpcZeTTpQlxsJId2psf26fgVGY51IUSEqR/rho5fzu4Nczl9aDNmlrb0GvwdtTPElhAfzbbfphETGUqJUqY4VKzGyMnrqOCq+ydwGrXoQGxMFLu2/kZkeCgOFV0YPWVh+v4yIpTw0GC1eaaMypiXt/E96YO1bTnmr8r6aqPCytyzJk2ObFD92/1n5TuVA9fv5NqnE7ObrVBJvneFlyVLUbxRBwxKmZEaFkTCrtUoYpT9OsPSZhhkvlhWrATGrrV5ecK7wOubk7dpu+tc352ouHh+3fc3IdGxuJaz4ZeR71Pe6lX7MjqWZxFRqvJJySks8DrC88gYZfuynA1LR/anRU1XndRfV8dxA0MjQoMecPX0V8THRlCytAUOlWvxycQ/sHVw00qs2uj7gPLJ1wd3LjFi4q9aqfeb6FS9AlEJL/n19HVC417gam3O//q1pLy58onk0NgEnkWnvzquVDETlvdvw9xD//DRuoOYlyxGh2oV+KJF4XgfeGZFqV+Xm7epT67vbRR96rNmVtSPdRnpc7+nTuMuxMdGcsR7OTGvYvt4bHps0ZGhRIapxzZk7Ar2/PEqNgtbegz8jloNdB+brs7PFqS3+VyKEEWBAa9eUS+EKJwUCgWbT+vnZvpBM+XBf8sZ/Yvv/abK2PZdKphh+Qta13rKoYFeHFyj45rkvxIdlXe96uN2l7bNnbmVt9cZFDVNqyvfI+h9QffvKs1vvRsoh9HS57z0vRWdS8miqUl1M0C/8/Kvf5J1XJP818NTed/v2dtRuZQsmhpXU57o3GtSVcc1yX/dku4AELP49UdUKuxMv1Y+CaKP2xykb3cvjqzXcU3yX4l2ypt/9fE4DunHcn3s+6T1e+J/n5pLyaKn1CfTAf3s00F6v06f81If2ylpbRR977Pq87FOn/s9Xuf1LzaAdxoq49Pn87P62Ab7oJkBBgYGuRcUWvXs5kVdVyFb9u66H4Ejv8mQ40IIIYQQQgghhBBCCCGEEEIIIQoluaAthBBCCCGEEEIIIYQQQgghhBCiUJJ3aAshhBBCCCGEEEIIIYQQQgghRB4pDOSZ4YIkv7YQQgghhBBCCCGEEEIIIYQQQohCSS5oCyGEEEIIIYQQQgghhBBCCCGEKJRkyHEhhBBCCCGEEEIIIYQQQgghhMgjBQa6rsJbRZ7QFkIIIYQQQgghhBBCCCGEEEIIUSgZAApdV0IIkT2FQjZRIYQQQgghhBBCCCGEEEIoGRjI08G69vTWZV1XIVvlq9fVdRXynQw5LoQQQgghhBBCCCGEEEIIIYQQeaQwkEGwC5Jc0BaiCNh8Wj+f0v6gmfIuMn2MLy22DSd1XBEtGdhS+d+fdqTqtiJaML6vsiGiz3mpj7GBfscnsRVd+hyfxFZ0pcUXs3iMjmuS/0y/ng/AXpOqOq5J/uuWdAfQ/7zUx/j0OTbQ7/jehtj0sU8H6f06feyTp/XH9Tkv9TE20O/4JLaiS5/jextiE+JtIrcPCCGEEEIIIYQQQgghhBBCCCGE+H/27jsqiutt4PiXIjaqFBGwUewKihpFRWPvSTSWaKImmqDGN4kxJjHG/jPGGGuM0Rh772hiwYa9996woSDSi3TY9w9kYWGBRcGF9fmcs+fA7J2d59m9d2bulDtFktyhLYQQQgghhBBCCCGEEEIIIYQQGlLIc8zfKLlDWwghhBBCCCGEEEIIIYQQQgghRJEkJ7SFEEIIIYQQQgghhBBCCCGEEEIUSTLkuBBCCCGEEEIIIYQQQgghhBBCaEiBDDn+Jskd2kIIIYQQQgghhBBCCCGEEEIIIYokOaGtxsCBAwkPD9d2GEVKy5YtUSgUmJmZaTsUIYQQQgghhBBCCCGEEEIIIcRbQieGHHdwcGDixIl06tQJKysrAgMD8fb2ZvLkyYSFhWk7PBW+vr5cunSJkSNHAvDgwQPmzJnD3LlztRLPgwcPqFKlCgBxcXEEBQVx5swZFi5ciK+vr7LciRMnsLW1JTIyUitxvoply5Zhbm7OBx98kGe5QYMGAZCcnExAQAA7d+7kp59+IiIiosCXV5jOHFzLiT1LiI4IxsbemY4f/UTlag1zLP/w9hl81v/K86f3MDG3oVmnITR6t69KmRvnfDi4bR7hwY+xsK5Emx7fUNO9XabPOMuJPUsIeHidmMhg+oyYT80GbQs0r9mjWxMZGpBteqN3+9Hlk/Gv/Ll55X/x2Fa2L/0p23xjF12mRImSr7xcTSkUCo78O5+LRzYQHxuFXVVXOvUbj7W9S67z3Tzvw+Htc5W/Wav3R1KjQcZvdnzXIm5d2Evos/sYGpXCwak+bXp+h6WtY2GnlCOFQsHFA39y++xGEuKisK5YD4/u47Aon3Ou4UF3ubD/D0KeXicmIoB3uvxInWYDCzVObbSx/C733xXjOX94Ix36jqFpe82/j6KcW3CAH/s2/86j22dRpKZibe9Cr2GzMbe00zi/opDv0Z2LuHl+HyGBaW2vonN92n04CqsKr9f2FAoFh7bP5/zhjcTHRmHvWI8uH4/HJo91RUH8Ppos+9yhDVw9/R+Bj26QGP+CH+afoXQZU43zK6p109f7D66d2UVU2DMMDEtQoXJt2vT4BgcnV41zKwq5Fla9LKq/27YlP3L5uLfKPPaOrnz+8wadyG/iZzXULr9dr9E06zQ4XznmR4l6Hhg1aIVeWVNSQ5+RcGQ7KQEP1JYt1a4vJWo1yjY9JfQZsatnFFqMBa1c84Y4jhqMWYM6lLKz4VzP4QTtOKDVmIpqvSyIdldUcyuMbQFod9teWDm9ic/PK39f7z84vONPlXnKmloxes6xV1re21YvNVFc+nWaKK798aJaLwtqH6Wo5gev328tqrkV9DolJSWZQ9vnc/XUv8REhmBsZo1b8w/w7DoMff3Xu/euqBzn09Xjs9rKrbD6rOpoax8sJTmJg9vmcvfKYcKDn1CytDGOtTxo++G3mFqUL/A8RcFR6Mk9w29Ssf+2q1atyrlz56hWrRofffQRzs7ODB06lDZt2nDy5EksLCxynLdEiRKFFpehYfG5VmDcuHHY2tpSvXp1BgwYQEREBPv37+ennzI28ElJSQQFBWkxysK1e/dubG1tqVKlCkOGDKFbt24sWLBA22Hly7Uzu9izbhotug5l6MRtVHJpyOrZXxCh5kQwQHjwE9bM9qKSS0OGTtxGi65e7F47lRvnfJRl/O9dZNPCb3H16M7QSdtx9ejOpoUjeeJ3WVkmKSGO8hVr0PnjcYWW2xfjNjNq9lHl65NRSwGo1ajDK3+mJvkDlCxtrLLsUbOPvpGT2QAn9yzm9L5ldOw3ns/GbsbYzIo1sz8lIT4mx3me+F1k698jqdvkPT4fv526Td5j69/f8PR+xm/26M4ZGr7bn0/HbKT/yGWkpqSwZvZgEhNi30Raal058g/Xji+nabef6T58I6WNrdizdDCJCS9ynCc5KR6TchVp2OFbSptYFXqM2mpj+VnuzQv7eXL/CibmNjqTW9jzxyyd1g8rW0cGfb+SoZO207LbMAxfox1qK9+Ht8/SqHU/hvy8gQGjlpKaksyqWUNeu+0d3/0PJ/cup/PH4/h83CaMzaxZ+ftnJMTlvK4oqN9Hk2UnJcbjXKcFLbp45Tu3olw3LW2r0Ln/OIZN3sFnY9ZgbmXPqlmDeRH1ahdT6lK9LMq/G4BznRYq2/X+3yzSmfyy7rO89+lU0NOjpnv7fOWYH4YubpT0fI/EsweIXTuLlIAHlH7vc/RMzNWWjz/sTcziiRmvJZNRxL0g+e5lteWLKoOyZYi6cpvrX0/WdihA0a6X8HrtrijnVtDbgnTa3LYXVk6F/fma5A9gbe+iUheHT97xSst7G+ulJopDv05TxbE/XpTrZUHsoxTl/F6331qUcyvodcrxXf9w7tB6Ovcfx5dTd9Ku93ec2L2EMwdWv9LnpSsqx/l0+fisLvVZc6KtfbCkxHgCH93As9twvCZsoc+IPwgNesi6ecMLPEchirNif0L7zz//JDExkfbt23PkyBH8/f3Zs2cPbdu2xd7enqlTpyrLPnjwgLFjx7Js2TIiIiJYvHgxkDbE+KNHj3jx4gVbt27F0tIy23K6du3KuXPniIuLw8/Pj/Hjx2NgYKB8X6FQ4OXlhbe3NzExMfz88895xu7r60uVKlWYM2cOCoUChUKhfK9p06YcPnyY2NhYHj9+zNy5cylTpky2XFasWEF0dDQPHz6ke/fuWFlZ4e3tTXR0NFeuXMHd3T3POKKjowkKCsLf35+jR4/i5eXFlClTmDx5MtWqVQOyDzleqVIlduzYQVhYGDExMVy7do1OnTopP7NWrVr8999/REZGEhUVxZEjR3B0TLtqSk9Pj3HjxuHv7098fDwXL16kQ4eME5Pqhjd3dXVFoVBQuXJlIGNY+Pbt23Pjxg2io6OVJ6UBJkyYwKBBg3j//feV323Lli1z/A4SEhIICgri6dOn7Nu3jw0bNtC+fcZOtb6+Pv/88w/3798nNjaWW7du8dVXXynfz215dnZ2rF+/nrCwMEJCQvD29lbmUZBO+iynQYueuHv2wtrOiU79fsKsnC3nfNepLX/u0HrMLCvQqd9PWNs54e7Zi/otenDCZ6myzKl9K3Gq5UGLLl5YV3CkRRcvqtZswql9K5RlXOp50qbHN9QqxAOlZU3LYWJmrXzduXwIC5tKVKneGIDk5ET2bpzBzG89mTq0Poun9ObBrdO5fqYm+afRU1m2iZl1IWWpSqFQcObASpp3HkqNBu2xsa9G90+nk5QYz7XT/+U435n9K3Cs5UGzzl5YVXCiWWcvqtRowun9Gb9Zv2+W4NqsB9b2LpSvWINun04jKiyAwEfX30Rq2SgUCq6fWIlrKy+q1GlPOdtqtOz1K8lJ8dy/lHOu1g51adxpNE6uXTAwMCr0OLXVxjRdblR4ELvWTKHnFzPQN8jfRVVFObcDW+fgUq8l7XuPpkLlWpSzqUg111YYm2bfVhf1fD/59h/qN++Bjb0LtpVq8P5n04gMDSDg4au3PYVCwal9K/HsOpRa7u0p71CNDwb/SlJiPFdzWVcUxO+j6bKbth9Iiy5fvNIV/EW5btZr0g2n2h6Us6mIjb0LHfr+SEJcDEFPbuc7T23mWhj1sij/bgAGJYxUtutljM11Jr+s+yy3Lh2kao13KGdTMV855odRA0+Srp8h6fppUsOfk3BkO6kxEZSo66F+hsR4FLHRypeBTUUoVZqkG2cLLcbCEOxzhDsT5vDMe5+2QwGKdr2E12t3RTm3gt4WgHa37YWVU2aafH58bDQ7lo/jt689+GW4O8t/G8izx7dy/VxN8gfQ1zdQqYtlTcu9Uh5vW73URHHp12miuPbHi3K9LIh9lKKc3+v2W4tybgW9TvH3u0gNtzZUc22FhZUDtRt2xKlOMwIeXlOWKc7H+XT5+Kwu9VnV0eY+WKkyJgz4bil1GnfCqoIjFZ3c6Nz/ZwIfXc/xggEh3kbF+oS2hYUFHTp0YMGCBcTHx6u8FxQUxJo1a+jTp4/K9NGjR3Pt2jXc3d2ZMmUKjRs3ZunSpSxYsAA3Nzd8fX2znYxu3749q1evZt68edSqVQsvLy8GDRrE2LFjVcpNmjSJ7du3U7duXZYuzbqxzK5Hjx74+/sr75BOPxlbp04dfHx82Lp1K/Xq1aNPnz40b96c+fPnq8w/cuRIjh8/Tv369dm5cyerVq1i5cqVrF69mgYNGnDv3j1Wrlyp8feZ2dy5c9HT0+O9995T+/6ff/5JyZIl8fT0pG7duvzwww/ExKRdqWRnZ8eRI0eIj4+ndevWuLu7s3TpUuVd619//TWjRo3iu+++o169evj4+LBjxw6cnZ3zFWOZMmX47rvv+OSTT/D09KRSpUr8/vvvAPz+++9s2LBBeZLb1taWEydOaPS5VatWpWPHjiQlJSmn6evr8+TJE3r37k2tWrWYPHkyv/zyC7169cp1eaVLl8bX15eYmBg8PT1p3rw5MTEx7Nmzp0BHCEhOTiTg0XWcajdTme5Uuxn+9y6qncff71K28s61mxPw8DopyUkZZepkKVOnOf5+lwos9vxKTk7kyqkd1G/eAz09PQC2L/0J/3sX+HDoLIZN3k6tRh1YPetzQoMe5vg5muQPkJgQy+zRrZk5qiVr5ngR+OhGoeSVVUTIE2Iig3Gs3Vw5zbCEEZWrNeKJn/rfFODJ/Us41mquMs2pdotc50mIiwagdFmzHMsUpujwJ8RFh2DvkvF7GBgaYVu1EUGPc477TdJWG9N0uampqWxd/D3NOg7Ocxik4pRbamoqdy8fwrJ8FVbNHMxvX3uweEpvbl7Yn68ci0K+6sQXQNsLD05bV2SOz7CEEVWqN8oxH03i1eR7etVla6oo1011sZ4/vIGSpU0oX1H9cIq50aV6WRx+t4e3zvDb1x7MG9OBHcvHERMVqlP5pYuJDOHulcPUb9FT4/zyTd8AfRsHUh6rHtBMeXQbgwpVNPqIErUbk/L4Loro8EII8O1QHOrlq7a74pBb5lhfZ1uQTpvb9qwKKqecqPt8hULBmjlexESF0P+bRXhN2EKFyrVY8fsgYmMicvwsTbd5YUGP+H1kC+Z834ZNC78l7Ln/K8X9ttVLTRSHfp2mimN/vDjVy1fZRynK+b1uv7Uo56Yu1tddp1Rycef+zZOEPEt7PM2zx7d4fPcCLnU9lWWK63G+otSvK2hFKbeCOJaiTlHaB4O0C/zQ06NUPh7ZJt48BXpF9qWLis+42Gq4uLigr6/PzZs31b5/8+ZNypUrh7W1NcHBwQAcPHiQmTNnKstMnjwZHx8fpk+fDsDdu3fx8PCgY8eOyjJjx47l119/VZ4cfvDgAePGjeO3335j8uSMIebWrl3LsmXLNI4/PDyclJQU5R3S6UaPHs3atWuVz9W+d+8eX331FYcPH2bYsGEkJCQAsGvXLv7++29lHsOHD+fs2bNs3rwZgOnTp3Pq1CnKly+f7+HCw8PDef78ufL52llVqlSJLVu2cO1a2tVzDx5kPCPvyy+/JDIykr59+5KcnAykfa/pvvvuO6ZPn86GDWnPTPvxxx959913+eabbxgxYoTGMRoZGTF06FDu378PwPz58xk/Pu15yi9evCAuLo6SJUtqlHvXrl2Jjo7GwMCA0qVLAyifcw5pz9aeOHGi8v+HDx/i4eFB79692bRpU47L+/jjj0lNTWXIkCHKaZ9++ikRERG0atWKfftU7+gwMjKiZMn8D3MTGx2OIjWFsmaqV36WNbUkJjJE7TwxkcGUNVXtaJU1syQ1JZnYmHBMzG2IiQyhrKm6zwzOd4wF5daFA8THRuPWLO1Z5WHPH3P19E6+/f2Q8pkizToO5t7VY1w8tpW2Pb9V+zma5G9VwZH3B0+jvH01EuJjOLVvJUum9WPYJG8sy1cp1DzTv+Ps37+V2ueJZ8yn/jd7EaX+N1MoFOzbOI2Kzu7Y2Fd7zahfTVx0Wh0tbaw6vFxpY0tiIorGVYjaamOaLvf47sXoGxjwTttPdCq3F9GhJCbEcmzXYlr3+Jq2vb7j3tWjbPjz/xj0/QrlKA3FId+sFAoFPht+pZKLO+UdXr3txUTltK6wfKV1RX5+n1ddtqaKct1Md/uSL5sXjSIpMQ4TM2sGfLeUsiY5P+6mqOWaVUHUy6L+u7nU9aR2w46YWdoREfKEg9vmsWLGILzGb8GwRN53hRX1/DK7dMIbo1JlC3W4cb3SZdHTNyA1VnUIPkVcDPplTfKev4wJBlVqEL9nTWGF+FYo6vXyddpdUc8NCm5boIxfi9v2wsopq9w+/8Gt0zx/eofRc04o60eHPj9w6+IBbpzzoWGrPmo/U5NtnoOjKx8M+RVL2yrERIZy5L+/WPLLR3z5v38pY6x5fm9jvdREcejXaao49seLQ71M9yr7KEU5v9fttxbl3NIV5DqleefPSYiLZv7YzujrG5CamkKbHt9Qt0lXoHgf5ysq/brCUFRyK6hjKWrjLQL7YOmSkhLYv3kmdd/pSqnSxvnORQhdVaxPaOcl/e7NzEN5nzt3TqVMzZo12bZtm8q0kydPqpzQdnd3p1GjRip3ZKef+CxdujRxcXFqP/tVubu74+zsTP/+/VVyMTAwoGrVqty6lTbU1pUrV5Tvp59EvXr1arZpNjY2r/T8az09PZXvLrN58+bx119/0b59e/bv38+WLVuUy3Zzc+Po0aPKk9mZmZiYYG9vz/Hjx1WmHz9+HFfX/A1F+uLFC+XJbIDAwEBsbPL33Nh0vr6+DBs2jDJlyjBkyBCqVavGH3/8oVLGy8uLIUOGULlyZUqXLo2RkRGXLl3K9XPTf8vo6GiV6aVKlcLJySnbCe0xY8aonDjPL72sV94oAL2cr8bRy/qeQvlG7p+pxSt8Lh7djEvdFsqd2sBHN0Ch4I+fOqmUS0lOVA5lOHVYA+X0ek270W3AJCDv/Cs6uVHRyU35dkXnBiya1IPT+1fTuX/ejxXIj6undrBr9QTl/33/L/25gqoxKlBo8PVnmUehyDYt3Z61k3n+5A4Dv1+bv4Bfw71L/3Lce6Ly//YD/gKyR5hb3NqirTaW23IDHl7j1L5VeE3Ykn15+VAUc1OkpgJQvX5rmrYfBECFSjXx97vIOd/1r3RCW5Plqi1fwOvLXaunEOR/m8/G5K/tXTn5L/+uzFhX9P9mofr4ssSmzuv+PhmLyf+y86Mo1s10VWu+w9CJ24iNCefC4U1s+usbhvy88ZWHxC+u9VJtbEX0d6vTuLPy7/IO1bCrUofZo9tw58qhfA3PV1Tzy+zi0S3Ua9K1QJ8JmCM1fYYcuhEqStRqhCIhnmS/a3kXFnkqqvWyINpdUc0NXn9bUBS37QW1fcua28cj/6ZytYa5fn7gw+skxscy/asmKp+VnBhPeLA/EaEB/PlzV+X0Fl2+wLPrUI3yd6mXcfdfeQeo6OzG3B/ac+m4Nx4dPs1XbjkuT0fqpSaKc78uK13qjxflepnudfZRimJ+BdVvLYq5pSvIdcq1M7u4cvJfen7xOzb2zjx7fIs9637BxNwGt2Yf6MRxPm336wqTtnMryD5rUdwHA0hJTmLzwm9RKBR0+WRCtveFeJsV6xPa9+7dIzU1lVq1arF9+/Zs79eoUUP53OJ0L168UCmjycF/fX19JkyYwNatW7O9l3mo86yf/ar09fVZtGgR8+bNy/be48ePlX9nHhJb3bT0k9H6+vkfWT79zvbMd15ntmTJEnx8fOjSpQvt27dnzJgxjBo1ivnz5ytP8Ocm64nyzCfPU1/uCGb+bdQNz501f4VC8Uq5Qtpv5+fnB6QNiX7w4EEmTJigvOO7V69ezJ49m1GjRnHy5Emio6MZPXo077zzTq6fq6+vz/nz51UuTkiXPmpAZtOmTWPWrFkq06KiovKMv4yJBXr6Btmu6noRHZrjzqWxmXX28lGh6BsYUqas+csyVsREqflMM9Urrt+UiJCn3L9xkj4jMi42UChS0dM3wGv8ZvT0DVTKG5VKe+780IkZF62UfHlVmyb5Z6Wvr4991bqEBT0qiHRUVHNrjb1jxkUdKUmJL2MKwcQ840KN2KhQyprm/P0bm1nxIstvFhsdpnaePWuncOfyQQaMXo1pOdvXTUFjlWq2xqZiPeX/KclpucbGhFDGNCPX+BdhlDYuuAMur0NbbUyT5T66c54X0aHMHt1a+b4iNYW9G6Zzat8KRs44WGxzK2Nigb6BIdZ2qo+ksK7gxOO753PNKydFYX25a80Ubl86yKc/rsYsn22vutu72Dtmbz8xkarrihdROeejSbyafE/GptavtGxNFeW6mc6oZBksy1fGsnxlKjq5Me/HDlw8upkWXbyKRa6ZvU69LAq5vMpyAUzMbTC3tNN4215c8nt05xyhzx7Qa+hsjfJ6VYq4FyhSU9Ava0Jqpul6pY1RxEbnOF+6ErUbk3zrHKSmFF6Qb4HiUi/T5afdFYfcXndbUJS27QWVU065pV+UnNvnKxSpGJtbM+j77I9PK1XGlFJlTFT6d+nDjb5K39WoZBnKO1TLd//ubaiXmiiO/bqc6EJ/vDjUS3j1fZSinN/r9luLcm7pCnKdsm/jDJp3/py673QBoLxDdSJCAzi682/cmn1QrI/zFYV+XWEpCrkVVJ81XVHcB0tJTmLTXyOJCH7CwO+Xy93ZxYBCr1g/1bnYKdbfdlhYGPv27WP48OGUKlVK5b3y5cvTv39/5bDWOblx4wZNmqhe+Zv1/wsXLlC9enX8/PyyvXK6g1lTiYmJGBiobpwvXLhA7dq11S5P3UnswvD111+TmpqKt7d3jmWePHnCokWL6NmzJzNnzuTzzz8H0u4cb9GihfKZ2ZlFR0fz9OlTmjdXHW7Ew8NDOXR8+oneChUqKN93c3PLdw7qvltNTZo0ie+++04ZQ4sWLThx4gR//fUXly5dws/PDycnpzyXd+HCBVxcXHj+/Hm231LdierExESio6NVXpowNDTCrnJt/G6oPifc7/oJKjrXVztPRSc3/K5nLX8cuyq1MTAskXOZa8dVrmZ8ky4e20pZU0tc6rVUTrOtVBNFagovosOUO9fpLxOztJMtmael7yhokn9WCoWCZ49vYmxuXeC5lSxlTDmbysqXlZ0zxmbW3L+RMZpBSnIij+6cxcFJ/W8K4ODopjIPwP0bx1TmUSgU7Fk7mdsX9/LJqBVYWFcs8HxyY1SyLKaWlZUvcxtnSptYEXAv4/dISU7k2YOzlK+Uc65vkrbamCbLdfXozrBJ2xk6cZvyZWJug0fHwXzy7T/FOjdDQyPsqtQh9JnqxVWhzx5iZmmXZ27qaHN9qVAo2Ll6MjfP72Pg98uxsHbId/wlSxurrNOsX64rMueTnJzIw9tnc8xHk3g1+Z4srB1eadmaKsp1MycKFCS/PACaH8W9XhaFXF71d4uNCScyLBBjM8227cUlvwtHN1Ohcm1sKxXu81JJTSH1+RMMKqkO92dQqRopgQ9zndXA3gl9c2uSrp8pxADfDsWlXqbLT7srbrlB/rcFRWnbXlA5pcuaWwmjUmrLZf78CpVrERMZgr6BQbb+XVkTCwwMDFWmpd+t9yp91+SkRIID/fLdv3sb6qUmimO/Lie60B8vLvXyVfdRinJ+r9tvLcq55eR11ilJiXHoZbkhSV9fH4Ui7fLI4nycT5ePz+pSnzVdUdsHSz+ZHfr8EQO+W5avx6EI8bYo1ie0AUaMGEHJkiXx8fGhRYsWODg40KFDB/bt28fTp09VhglXZ968eXTs2JHRo0fj4uLCl19+qTLcOKQ9n3rAgAFMmDCBWrVqUaNGDXr37s2UKVNeO/6HDx/i6emJnZ0dlpZpG+Dp06fTtGlT5s+fj6urK87OznTr1k3tHdsFwcTEhPLly+Pg4ECLFi1YtGgRP//8M2PHjlXetZzV7Nmzad++PVWqVKF+/fq0bt1aeUJ6/vz5mJqasn79euWQ2x9//DHVqqUd6JoxYwY//PADvXv3plq1akybNg03NzeVZ4Y/fvyYiRMn4uLiQufOnRk1alS+83r48CH16tWjWrVqWFpaqj3BnpPDhw9z/fp1fvrpJ2VMDRs2pH379ri4uDB58mQaNWqU5/LWrFlDSEgI27dvp3nz5lSpUgVPT0/mzJmDvb19vnPKTdMOg7hwZDMXjm4hOMCPPeumERkWSMNWfQHYv3kmWxf/oCzfsFVfIkMD2LN+GsEBflw4uoULR7fg0eEzZZl32n2C3/XjHNu1mODA+xzbtZj7N0/SpN1AZZmE+BcEPr5J4OO03z8i5AmBj28SUQDPT80sNTWVS8e34erxPgYGGb+llW1V6jbpxrZ/fuDG+b2EBz/h6YOrHNu1mDtXDuf4eZrkf2j7fO5dO0rYc38CH99k+7KxPPO/pfxOC5Oenh6N2wzg+K5F3Lqwj+dP77Bj2RhKGJWizjsZQ+xtX/I9B7fOVP7fqM0A7t84zondfxMS6MeJ3X/z4OZJ3mmb8ZvtWTuJq6d28P6QmRiVKktMZDAxkcEkJcajDXp6etT2GMDlQ3/z8Po+wp7d4cjmnzAsUQpHt4xcD2/6gbM+GSMYpCQnEhpwk9CAm6SmJBEb9ZzQgJtEhRb8HfSgvTaW13LLGFtQ3qGaykvfwBBjMyusKjgW69wg7VlZ187s5vzhjYQGPeL0gdXcvuxLo3f7aZRbUcp35+rJaUOref2OUamyREcGE/2abU9PT48m7QZw9L9F3Dy/j6And/BekrauqJtpXbF18Q/s35yxriiI30fTZUdHBhP4+CZhz9NGmXn+5A6Bj28SGxORZ35FtW4mJsSyf8ss/P0uERHylIBH19m+7Geiwp5Ru5HqfqSmdKleFtXfLSH+BT4bpuN/7yLhIU94cOs0a+cOo4yJBTUbtC32+aWLj4vhxlkfGnj20jin15F44Qglar+DYa3G6FvYUNKzO/omFiRdPQmAkUdnSrX/KNt8JWo3JiXwEamhz95InAXNoGwZTF1rYOqadkC+TFUHTF1rUKpihTzmLBxFtV4WRLsrqrkVxrYAtLttL6yc0mny+Y61PKjo5Mb6P0Zw79pRwkOe8PjeBQ5sncPTB1dz/GxN8vfZMJ2Ht88QHvyEJ36X2bjgKxLiYnDzeD/fubxt9VITxaVfp4ni2h8vqvUy3evuoxTl/F6331pUcyuMdUo1t3c58t9C7lw+RHjIE26e38dJn+XUbNAOKP7H+XT5+Kwu9VnV0eY+WEpKMhsXfE3Aw2v0/HwGqYoUZZ7JyQV7QZoQxVmxHnIcMk40Tpw4kQ0bNmBpacmzZ8/w9vZm0qRJhIeH5zr/6dOnGTJkCJMmTWLixIns37+f//3vf4wbN05ZZu/evXTt2pXx48fz/fffk5SUxK1bt/jnn7zvfMvL+PHjWbRoEX5+fpQqVQo9PT2uXr1Ky5YtmTp1KkePHkVPTw8/P7887zZ/VVOmTGHKlCkkJCTw7NkzTp06RZs2bTh06FCO8xgYGPDnn3/i4OBAVFQUe/bsYeTIkUDanfOtW7dmxowZHD58mJSUFC5duqR8bva8efMwNTVl5syZ2NjYcOPGDbp37869e/cASE5O5qOPPuKvv/7i8uXLnD17lp9//pnNmzfnK6/FixfTqlUrzp07h4mJCa1ateLw4Zx3fLKaNWsWy5YtY/r06SxcuBA3Nzc2bNiAQqFg3bp1LFiwgE6dMp7nktPyPD09mT59Olu3bsXExISnT59y4MABjYYSz486jTsTGxPB4R1/EhMZjI29C/2/WYS5VdqJ8+jIYCLDMnZiLKwd6D9yEXvW/crZg2sxMbehU7+x1GrYQVmmknMDPhw6k4Nb53Jw2zzK2VTkw6GzcHDKGIor4OE1VvyW6SDB+l8BcG32Ph8M/rXA8rt/4wSRoQHUb9Ej23vvf/YLR/77i70bphMV/pwyxuY4OLmpPCMtK03yj4+N5t8VE4iJDKZkaRMqVKrJpz+swiHTcDSFqWnHz0lKSmDP2knEvYjE3tGVfiOXUrJUxnAzkWGB6GUa2qSicwN6fDGLQ95zOLR9HhbWFenxxWyV4dPOH1oHwKrfP1FZXrdB03Btlv37fRPqeQ4hJSmBEzsmkxgXhbVDPTp8+g9GJcsqy8REqOYaGx2M9/yMeK8eXcrVo0uxrdqILp9nH6LwdWmrjeW1XF3PraZ7O7oOmMixnX+ze+1ULG2r0ufLeVSu5l7s8j3nm9b2lk8foBLPe5/9Qv3mr972mnUaQlJiPDtXTybuRSQOjvX4ZNQS5dBrAJFhAejpZzzKo6B+H02Wfc53PYd3/Kn8f9mvH2ucd1Gtm3r6BoQEPuDy8a+IjQmndFlz7KvW5bMxa7Cxd8njFytauRZGvSyqv5u+vgHPn9zh8ontxMdGY2JuTZUajek1bLZKnS2u+aW7dnonChTKYRwLW/LdSySULkPJd9qhV8aU1NBA4rb/gyI6rR+mX9YUPRNz1ZmMSmHoXI+Ew95vJMbCYOZeh6YHVin/r/V72oWw/iu3cmXwmDceT1GtlwXR7opqboWxLUinrW17Yeak6efr6enR/5tFHNg6h+1Lx/IiOhxjMysqV2uY69CqmuQfFR7E5oWjiI2JoKyJBQ5OrgwZu+GV9qvfxnqpieLQr9NUceyPF9V6me5191GKcn6v228tqrkVxjqlc7+fObhtHjtXT+ZFVCgm5ja4t+pDy+7DlWWK83E+XT4+q0t91pxoax8sKvwZty+lPTJw4cT3VWIa+P0KqtbI/bGnQrwt9Hj5iHohRNGkUChYd1w3m+lHzdI2/rqYX3puq45oOZBC8snLPsRvW1JzL1gMfd8z7YCELtdLXcwNdDs/ya340uX8JLfiKz2/6Ln5HwWpqDP5Ou1uiZ0lqms5koLXJek2oPv1Uhfz0+XcQLfzexty08U+HWT063SxT57eH9fleqmLuYFu5ye5FV+6nJ+u56anp5d3QVGoHty9re0QclTVRff6xMV+yHEhhBBCCCGEEEIIIYQQQgghhBC6SU5oCyGEEEIIIYQQQgghhBBCCCGEKJKK/TO0hRBCCCGEEEIIIYQQQgghhBDiTVHoyT3Db5J820IIIYQQQgghhBBCCCGEEEIIIYokOaEthBBCCCGEEEIIIYQQQgghhBCiSJIhx4UQQgghhBBCCCGEEEIIIYQQQkMK9LQdwltF7tAWQgghhBBCCCGEEEIIIYQQQghRJOkBCm0HIYTImUIhTVQIIYQQQgghhBBCCCGEEGn09OTuYG3zu3dP2yHkyMnZWdshFDgZclwIIYQQQgghhBBCCCGEEEIIITSkkIsK3ig5oS1EMbDuuG7epf1Rs7QVvi7ml57bxpOpWo6kcPRumvbEir2XE7UcScFr72oE6Ha9vHg3RMuRFI76LlYAXLobrOVICp6bizWg2/XS92qcliMpHO/WLQ3odr3cWaK6liMpeF2SbgNw5lakliMpHI1rmAHw7/lkLUdS8Lq5p3VxdXl9qYttDjLa3eHrsVqOpOC1rF0GgPUndK9eAvT1SKub83fpXn4jOqflpsv9Hl3MDTLy08U+eXp/XBf3U9L3UXS9z6rL27pjrg20HEnBa375AgDX7j3TciSFo46zLaDb+8+6nJsQbxN5hrYQQgghhBBCCCGEEEIIIYQQQogiSe7QFkIIIYQQQgghhBBCCCGEEEIIDSkUcqf8myR3aAshhBBCCCGEEEIIIYQQQgghhCiS5IS2EEIIIYQQQgghhBBCCCGEEEKIIkmGHBdCCCGEEEIIIYQQQgghhBBCCA0p5J7hN0q+bVHoBg4cSHh4uLbDKDIUCgXvvfeetsMQQgghhBBCCCGEEEIIIYQQosiTO7RFNg4ODkycOJFOnTphZWVFYGAg3t7eTJ48mbCwMG2Hp8LX15dLly4xcuRIAB48eMCcOXOYO3euVuLR9vIVCgWHts/n/OGNxMdGYe9Yjy4fj8fG3iXX+W6c8+HgtnmEBz/GwroSbXp8Q033diplzhxcy4k9S4iOCMbG3pmOH/1E5WoNAUhJTuLgtrncvXKY8OAnlCxtjGMtD9p++C2mFuUlv1dw+sBaju1eSszLeDr1G0OV6g1zLP/g1hn2rJvO86f3MLGwoXmnwTRu3Vf5ftDTuxzc+gcBD68TERpAp49+xKPDwEKJXRNHfNZzYMdyoiKCqeDgRI9BP+Bc0z3H8ndvnGXbihkEPvHDzMKatt0/o3n73iplfHeu4tjejYSHBFLW1By3d9rRvd83lDAqWai5aKteAtw4v5fzhzYQ8Og6cTEReE3cRoVKNQslz5zs3bmVf7euJSIsFIdKVRnw+VfUrOOmtuyZE4fYt2sbD+/fIzkpEYdKVfmw32Bc3d95ozFrymfnVv7duu5lblUY+PnX1Kzjqrbs6ROH1eT2GW5ayu1tr5eH9mxg344VRIaHYFfRiV6DRuNSq4HaspHhwWxeMZPH92/yPPAx73b+iN6ffv9G482P4lwvX1W55g1xHDUYswZ1KGVnw7mewwnacUDbYeXb/l2b2bltFZHhodhXcuTjwSOpXru+2rJnT/pyYPcWHj+4Q1JSEg6VqvJB38+p16DpG45aveP71nHov2VERwRT3t6Z9wb8iGONnLfjfjfPsmPVbwQ9vYepuQ2tun2GR9s+yvfPHt7GhkU/Z5tv2vILBbodz2v9ldXD22fwWf9r2v6VuQ3NOg2h0bt9VcoUxHpz25IfuXzcW2Uee0dXPv95w+sn/Qp0pc0d2r0Rn+0Z24I+n32X47YgIiyYzStm8cgvbVvQuvNH9Bk8+g1HnOHMwbUc372EmIhgrO2d6dQvj7p66wx71v9K8Mu+QG51Nez5Y8rZZK+rZw6u45zvOiJCngJgbe9Mq+5f4lLPs3CSzEShUHDGZz7XT24kPi4K20r1aNlzPJYVct9vuXfZh1O75xEZ8hgzq0o07fwNTvUyckpNSea0z3zunP+XF9EhlDWxpmbjD2jUbhh6+m/m/g5d6vdkpcu5ge73yTPTpX0UdXS5z1qct3WasO3dC4dBAzCysiLW7z73f/udqIsXcyxfoU9vKvTtQ0m7CiQ8e8aTxUt4/t/ONxix5vb8t43tW9cTHhZGxUpV+PSLEdTKoV936vgRfHZ58/D+PZKSkqhYuQq9+31KfffGbzjqNLp8fPZtP5YiRFEnd2gLFVWrVuXcuXNUq1aNjz76CGdnZ4YOHUqbNm04efIkFhYWOc5bokSJQovL0FCuvdDE8d3/cHLvcjp/PI7Px23C2Myalb9/RkJcTI7z+N+7yKaF3+Lq0Z2hk7bj6tGdTQtH8sTvsrLMtTO72LNuGi26DmXoxG1UcmnI6tlfEBEaAEBSYjyBj27g2W04XhO20GfEH4QGPWTdvOGS3yu4enoXu9f+SstuXgybvJXK1dxZNctLGU9W4cFPWDVrKJWruTNs8lY8u37BrjW/cP3sXmWZpIR4LKwr0q7XtxibWRVK3Jo6f2IPW5dPp0OPz/lh+iacarrz1y/DCAsJVFs+5PkTFk77Eqea7vwwfRPtP/iczcumcenUPmWZs0f/Y8faOXTqNZSxs7fTb+hkLpz0YcfaOYWej7bqJUBSQhwVXRrQ9sNRhZpjTk4c2c+KxXP5oPcAfp23jBq16/HrxO8Ief5Mbfmb1y5R160xP078nV/mLKVWvQb8NuV7HvjdecOR5+3EkQOsWDzvZW5LqVHblWl55taIHyfOYNqcJdSu14Dfpvygtdze5np57rgPm5bPoFOPIYydsR7nmvWZ/8uXhAWrX8ckJSVibGpBpx5DcKhc7Q1Hmz/FvV6+KoOyZYi6cpvrX0/Wdiiv7NTRfaxeMov3en3KlNmrqF7LjRmTvyEkWP1vd/v6Req4Nea78XOYMmsFNes2ZNbUUTy8f/sNR57dpZO72bHyV9q+/wUjf9mMY40G/DPdi/AQ9fspoc+f8M9vw3Cs0YCRv2ymzfufs33FL1w5s1elXKnSxoxfcEjlVZAnMDRZf2UWHvyENbO9qOTSkKETt9Giqxe7107lxjkfZZmCWm8CONdpwajZR5Wv/t8sKrDc80sX2tzZYz5sWDaDzj0HM27mOlxq1mfe/0YQmsO2IDk5CWNTCzr3HIxDFe1uC66d3sWetdPw7DqUoZO2UblaQ1bPyr2urp7tReVqDRk6aRstunixe42auvrXt9Rr2p1hk7dTr2l3Nv6lWlfNypWn7Yej+GLCZr6YsJmqNZuwbt6XPH96t9BzvnDwHy4eWo5nz3H0GbmJMqbWbF/4GYnxOe+3BD68yJ6V31KjYXc+Gr2dGg27s2fFSJ49ysjp/MF/uHZiPZ49xvHxjztp1u07Lvgu4fLR1YWeE+hevyczXc4NdL9Pnpku7aOoo8t91uK8rdOEVYf2OH7/Hf6Ll3CxTz8iL1yk9oI/KGlrq7a8ba8PqfzVCB4vXMSFHr14/NdCHH/6kXItC//CrPw6fuQgyxbPp2efT/h93mJq1qnH1Ak/EPw8SG35G9cv41q/IWMnTee3uYupU68+v04ew/237HjDmzg++zYfSxGvRoFekX3pIjmhLVT8+eefJCYm0r59e44cOYK/vz979uyhbdu22NvbM3XqVGXZBw8eMHbsWJYtW0ZERASLFy8G0oYYf/ToES9evGDr1q1YWlpmW07Xrl05d+4ccXFx+Pn5MX78eAwMDJTvKxQKvLy88Pb2JiYmhp9/zn7HRla+vr5UqVKFOXPmoFAoUCgUyveaNm3K4cOHiY2N5fHjx8ydO5cyZcpky2XFihVER0fz8OFDunfvjpWVFd7e3kRHR3PlyhXc3XO+2lgdZ2dnDh8+TFxcHNevX6dt27b5mj8/FAoFp/atxLPrUGq5t6e8QzU+GPwrSYnxXD39X47zndq3EqdaHrTo4oV1BUdadPGias0mnNq3QlnmpM9yGrToibtnL6ztnOjU7yfMytlyzncdAKXKmDDgu6XUadwJqwqOVHRyo3P/nwl8dD3HDp/kl7MTPito4NmDhi17YWPnROf+P2FazpYzB9erLX/Gdz1mlhXo3P8nbOycaNiyFw1a9OD4nqXKMg6OdenYdzT1mnTB0NCowGPOD9//VtK0dQ882vTE1sGRnoN+wMLKlmN71d+FdHzvRiysbOk56AdsHRzxaNOTJu9+wIF/lyvLPLhzGcfq9WnYvAuWNvbUdPXAvVknHt+/Uai5aLNeArh6vEer7l/iWEs7V8Pv9N7Au+260rpDd+wrVmHgF99gaWXDvl3b1JYf+MU3dP+wP07ValLBviIfDRxKBTsHLpw59oYjz9tO7/W0bteVNh264VCxCoO++BpLKxv27vJWW37QF1/z3of9cVbm5kUFOwfOnzn+ZgNH6uX+f1fRrPUHNG/bgwoOjvT+9HssLG05vHeT2vJWNvb0+ewHmrTqRqkyxm842vwpzvXydQT7HOHOhDk8896Xd+Eiavf2tbRs251W7d/HvmJVPh7yLZZW5Tmwe4va8h8P+ZauPQbg6FILW7tK9P5kOLYVKnLxzNE3HHl2h3etoHGrnrzz7oeUt3fivQFjMLeswMn96rfjJw9swMKyAu8NGEN5eyfeefdDGrXqweH/lqsW1NPD1Nxa5VWQNFl/ZXbuUNr+Vad+P2Ft54S7Zy/qt+jBCZ+M/auCWm8CGJQwwsTMWvkqY2xeoPnnhy60uX3/rqZ5m/dp0S5tW9Bn8Oi0bYFPTtsCO/oO/p6m73ajtJa3BSf2Lqe+Z0/cW2bUGdNytpw9qL6unvXNUldbptXVzH2Bk3tX4ljbA8+uaXXVs6sXjjWbcDJTXa3u1ppqri2xsq2KlW1V2vYciVGpMvhnOhhbGBQKBZcOr6RRu6E412uPZYVqtOuXtt9y50LO+y2XDq+kYjUPGrb1olx5Rxq29cKhWhMuHc7I6dnDizjWaUPV2q0wLeeAs1tHKlVvxnP/a4WaUzpd6vdkpcu5ge73yTPTpX0UdXS5z1qct3WasP+kP0HbvAna5k3cgwc8mPE7Cc+CsO39odryNl278GzzVkJ89pLw9Ckhe/YStG079p8WjZEQMvt320Zat+9M2w5dcahUhc+++D8srazx2bVdbfnPvvg/3v+wH87VamJn70D/gV9ga+fAudMn3nDkun189m0/liJEcSAntIWShYUFHTp0YMGCBcTHx6u8FxQUxJo1a+jTp4/K9NGjR3Pt2jXc3d2ZMmUKjRs3ZunSpSxYsAA3Nzd8fX2znYxu3749q1evZt68edSqVQsvLy8GDRrE2LFjVcpNmjSJ7du3U7duXZYuXUpeevTogb+/P+PGjcPW1hbbl1fs1alTBx8fH7Zu3Uq9evXo06cPzZs3Z/78+Srzjxw5kuPHj1O/fn127tzJqlWrWLlyJatXr6ZBgwbcu3ePlStXavx96unpsXXrVlJSUmjSpAlDhw5l+vTpGs+fX+HBT4iJDMapdjPlNMMSRlSp3gj/ezkPx+PvdwmnOs1UpjnXaY6/3yUAkpMTCXh0XeVzAZxqN8v1c+Njo0FPj1JlTF8hm+x0Pb90ycmJBDy8jnO2mHOOx//epezl6zbj6cPrpCQnFWh8rys5OQn/+zeo4eqhMr1GPQ8e3L6kdp4Hdy9To55q+ZpuzXh8/4YyP6caDfC/f4OH964CEBLkz42LR6ndoEXBJ5FJUauXb1JyUhIP7t2mXn3VIa7q1W/MnVuaHSRMTU0lLi6OssYF245eV3JSEvfv3aFe/UYq013rN8pnbrEYayG3t71ePr5/k5quqh3Amq5NuH+7cA/IF7biXi/fZslJSTz0u0VdN9WhKuu4vcPdW1c0+ozU1FTi42IxNtHub5ecnMjTBzeolmW7XK2uBw/vXFI7z6O7l6lWV7V89XrN8H+gup+SGB/L/75qy5QRrVkyYzhPH94s0Ljzu/7y97uUrbxz7eYEZNq/Ksj15sNbZ/jtaw/mjenAjuXjiIkKzXeeIk1yUhKP/W5SK8u2oJZbE/xuFe1tQXJyIoEPr+Osrs74qa+rT9TV1TqqdVVdGac6zfG/d0ntZ6ampnD19E4SE2Kp6OT2asloKCr0CbHRwVSqnhGfgaER9s6NCHyQ8/7Fs4eXVOYBqFS9Oc8eXlL+X6GqO/53ThL+/AEAwU9vEXD/AlVqFf7derrW78lMl3MD3e+TZ6ZL+yjq6Hqftbhu6zShZ2iIcc2aRJw8pTI94uRJTF3VD8utb2REamKCyrTUhHhM6tRBrwiN/JmUlITfvTu4Ze3XNWjE7Zua10tttbuidryhII/PFrXchBDZFZ21udA6FxcX9PX1uXlT/cGjmzdvUq5cOaytrQkODgbg4MGDzJw5U1lm8uTJ+Pj4KE/c3r17Fw8PDzp27KgsM3bsWH799VflyeEHDx4wbtw4fvvtNyZPzhjWbu3atSxbtkzj+MPDw0lJSSE6OpqgoIwhWkaPHs3atWuVz7W+d+8eX331FYcPH2bYsGEkJKTt7OzatYu///5bmcfw4cM5e/YsmzdvBmD69OmcOnWK8uXLq3x+Ttq2bUvNmjWpUqUKT5+mPYfsp59+Ys+ePTnOY2RkRMmSrza0YkxU2m9S1lT1jviyppZE5nKVWkxkiNp5YiLTPi82OhxFagplzdSVCVH7mUlJCezfPJO673SlVOmCuepT1/NLFxsdQWpqCsamqkOQGZtaEp1DPDGRIRhnydHY1IrUlGRiY8IxMbcp0Bhfx4uocFJTUzDJ8n2bmFkSFaH+wG1URKja8qkpycRER2BmYY17s07ERIUxZ9wAFKQ9L695+z60f39IYaUCFK16+aZFRaXVVTOLcirTzSwsiLig2UH4ndvWkRAfR9MWbQojxFcWFRWZQ27lNM7tv23rSYiPp2mL1oURYq7e5noZE522jjE1U/3tTM0siYooGjG+quJeL99m0S/Xl6bmqm3HzLwckeGa/Xa7vdeQkBBH42aFN9qPJl683E9Rt13OaT8lOiIEk3rqt+MvoiMwtbDGxs6RPkOnUqGiC/FxLzi6ZxXzJ37Mt9O2Yl2h8mvH/Srrr5jIYMqaNlct/zLu9P2rglpvutT1pHbDjphZ2hER8oSD2+axYsYgvMZvwbBE0bmLr7hQbgvM1W0LivaFArEvY89ar4zNLIm5lnNdNTbLUldNs9fV7P2FjLqaLsj/Nv9M/YjkpASMSpah74j52Ng7F0BmOYuNTouhtIlqfGWMLYkOz3m/JTY6hDJZ5zGx5EVURk7ubT4nMT6a1b92Rl/PgFRFCk07f0O1Bl0LMAP1dK3fk5ku5wa63yfPTJf2UdTR5T5rcd7WaaKEhTl6hoYkhqrmkhgahrlV9pFAAcJPnMT2g/cJPXiIFzdvYlyrJuXffw/9EiUwNDcnKaRo9Aej0/t1WX47c3MLIsLDNPqMHds2EB8fT7MW7xZGiLkqSscbCvr4bFHKTRQfujq0d1ElJ7SFxvT00hpn5qG8z507p1KmZs2abNumOmzPyZMnVU5ou7u706hRI5U7sg0MDChdujSlS5cmLi5O7We/Knd3d5ydnenfv79KLgYGBlStWpVbt24BcOVKxtWn6Sesr169mm2ajY2NRie0a9asyePHj5UnsyHtu8jNmDFjmDhxYt5JAVdO/su/Kyco/+//zUIg43dSoW5a5rezrngVaVPzLKPmc1OSk9i88FsUCgVdPpmQ7X1N6Xp+ecoajkKRPUaV8qrvKUhvp0Vzo5r9q1XkGmq23/3leih9+t3rZ/HZupjeQ36miktdgp/5s2XZr+wxt6Ljh0MLLO6iWi+1SV2Mar+PLI4f3sfmtUv5btyvmJlbFFJ0rydrbgqFIp+5TXsjuUm9zC5r7mnrxKIV46sqLvVSZJd9U6bZb3fyiA9b1y9m5E+/ZzvwpT35bGNZ22R6f+Ll5MourlR2ybjbpkq1+swZ+yHH967h/YE/FUTALxeXv/VX9v0P5Ru5f2Y+15t1GndW/l3eoRp2Veowe3Qb7lw5RC339jnGJ/KgbltQxLZXOcm2HVOoqUeqc+T0QTl+ZtpcqtMsK1Rl6KRtxMdGcePcXrb98yOf/riqQE9q3z7/L74bM/Zbun2+UG0siizxq6M2p0zT7l7cxe3z/9Lh498pZ+tMyNNbHPX+hbKmNtRs/MGrJ5EPxbXfowldzi0tMNV/da1Pnplu7aNkp8t91uK8rdOIIsv/enrKdUdW/n8vxsjKEtdVy9HT0yMxLIznO/7F4dNBkJpS6KHml9pVoga/3dFD+9m4Zjk/jJv6Vh9vKIjjs0U1NyFEzuSEtlC6d+8eqamp1KpVi+3bsz+zo0aNGoSFhRGS6Yq2Fy9eqJTRZIdQX1+fCRMmsHXr1mzvZR7qPOtnvyp9fX0WLVrEvHnzsr33+PFj5d9JSdmHgco8Lf3Am76+ZiP1q/suFDnsdKWbNm0as2bNUpkWFRWltmx1t3exd6yn/D8lORFIuyos89W/L6JCs10pnJmxmRUxUapXg72IDsXYLO1q5DImFujpG2S7YuxFdPbPTUlOYtNfI4kIfsLA75e/1tVxup5fTsqYmKOvNp4wjM3U52lsZpW9fFQo+gaGWn3+ojplTS3Q1zfIdsVwdGQYpjnkZ2qe/c7K6Kgw9A0MKWtsBsB/G+bT2LMbHm16AmBXqRqJ8bGs+3sy7Xt8oXG7zUtRrJfaYmqaVlcjsly5HxkRnufBjBNH9rNo3jS++fF/1HVrlGtZbTA1NVObW5RGuR1g4bxfGfnjFOq9odykXmYwNklbx0SqW8eYF40YX1Vxq5cig8nL9WXWO52iIsOz3VWT1amj+/jnj//xfz9Mo45b41zLvgllX+6nZL1DLSYyLNudd+lMzK2IzrIdj1Fux83VzqOvr09FxzoEP3tUIHG/yvrL2Mw65/2rsuYvyxTOetPE3AZzSzvCggom/7dN+rYgKlzd/mbRPeECaXVGbV8gKjTbXT3pNK2r2dptVChlzVTvQDU0NMKyfNqoCPZV6xLw8Bqn9q2k+6DJFJSqtd+l/HfZ91tio0Moa5ax3xIXE0oZ45zbSRkTK15kaX+x0aGUMcnI6fi/M3Bv8znVGnQBwMquOtHhAZw78Hehn9Au7v2e3OhybqD7ffLMdGkfRR1d7rMW522dJpLCI1AkJ2OU5W5so3IWJIWqv4s5NSGBuxMmcW/KVEqUK0diSAi2PXuQHBNDUnjEG4haMybKfp1qHpGR4ZjncYL6+JGDLJj3G9/9OAnX+g0LM0yloni8oaCOzxbF3IQQuZNnaAulsLAw9u3bx/DhwylVqpTKe+XLl6d///5s2LAh18+4ceMGTZo0UZmW9f8LFy5QvXp1/Pz8sr3yOuGbl8TERAwMDLItr3bt2mqXp+4kdkG5ceMGlSpVokKFCsppTZs2zWWOtPijo6NVXjkpWdoYy/KVlS9rO2eMzazxu3FCWSY5OZGHt89S0bl+jp9T0ckNv+snVKb5XTuufFaaoaERdpVrq3wugN/1Eyqfm74zEfr8EQO+W0YZ49e7SlDX88uJoaERdlVqZ485SzyZVXTOnuO9a8exr1IbA8MShRLnqzI0LEFFx1rcuqI6WsHtKyepWt1N7TxVXVy5naX8rcsnqORYS5lfUkJctotI9PQNXl7i+nrrlcyKWr3UJsMSJajqXJ2rl86qTL966SzVatTJcb7jh/fx15yp/N93E2nQyCPHctpkWKIEjs7VuJIltyuXzuWZ24I5U/nquwlvNDeplxkMS5SgkmNNbmZZZ9y8chrH6uqftVZcFLd6KTIYlihBFacaXLt8RmX6tUtncKlRL4e50u56+nveZIaNmoJbw+Y5lnuTDA2NsK9aiztXVdcDd66doEo1N7XzVHZx5c61LOWvnKBi1Zz3UxQKBU8f3cLU3LrA4s7v+kvtOvH6cewy7V8V1nozNiacyLBAjM0KJv+3jWGJElRyqsmNy6rP3bx5+RRONYr2tsDQ0IgKavoC92+coKKT+jrj4OTG/Sx17F6Wuurg5MZ9NfW5orNbrvEoFArlwd2CYlTKGHPryspXOVtnyphY8/h2RnwpyYk8vXeWClVzbie2Vdzwv6Oa0+Pbx7Gt4qb8PzkxDj091cNeevr6oEgtmGRyUdz7PbnR5dxA9/vkmenSPoo6ut5nLa7bOk0okpOJuXkT8yaqz3c3b9KEqMuX85w38flzSE3FumMHwo4czfGubm0oUaIETs7VuHxRdWTSKxfPUb1mzvXy6KH9zJ89jW9Gj8O9ce7HlwtSUTveUJDHZ4tabqJ4UqBXZF+6SE5oCxUjRoygZMmS+Pj40KJFCxwcHOjQoQP79u3j6dOnKsOEqzNv3jw6duzI6NGjcXFx4csvv1QZbhzSnk89YMAAJkyYQK1atahRowa9e/dmypQprx3/w4cP8fT0xM7ODkvLtCucpk+fTtOmTZk/fz6urq44OzvTrVs3tXdsF6T9+/dz+/ZtVq5cSb169WjevDlTp04ttOXp6enRpN0Ajv63iJvn9xH05A7eS8ZQwqgUdd/JeEbY1sU/sH9zxnPP32n3CX7Xj3Ns12KCA+9zbNdi7t88SZN2A5VlmnYYxIUjm7lwdAvBAX7sWTeNyLBAGrbqC0BKSjIbF3xNwMNr9Px8BqmKFKIjg4mODCa5gA6A6Hp+mXl0GMj5w1s4f2QLzwP82LV2GpGhgTR+tw8AezfNYvPfPyjLN363LxEhAexe9yvPA/w4f2QLF45spVnHz5RlkpMTCXx0k8BHN0lJSSIq/DmBj24SqoU7f97tOoCTB7Zw8uA2nj25z5bl0wkLCaR5u94A7Fg7h5XzM4YXbda+N2EhgWxd8RvPntzn5MFtnDy4lTbdBinL1HFvxbF9Gzl/fDchz59w68oJdm6YT52GrdDXN8gaQoHRZr0EiI2JIPDxTYID/AAIffaAwMc3ic7yPMTC0uX9Phzc+y++e//jqf9DViyeS0hwEG07p93xsm75X/w5M2PdfvzwPhbMmsIng/8Plxq1iQgPJSI8lNgXMW8k3vzo8n5fDu79D9+9//HE/yErFs8jJDiIdp3fB2Dt8oXMz5Lbn7P+xyeDR2g9t7e9Xrbt9gnHD2zj+AFvAp/cZ+OyGYSHBOLZ/kMAtq2Zx7J5P6vM4//gFv4PbpEQH0d0ZDj+D24R4O/3RuLNj+JcL1+HQdkymLrWwNS1BgBlqjpg6lqDUhUr5DFn0dHpvX4c2redw/t38NT/Aav/mUVoyDPadOwBwIaVf7JwdsZwdyeP+LBozkT6ffo1ztXrEBEeQkR4SJH47Vp2HsgZ3y2cObSVoKd+bF/1KxEhgTRpk7afsmv9bNYtGKMs37RNH8JDAtmxajpBT/04c2grZw5toWXXQcoye7cs4PblY4QG+fP04U02/j2OgEe3adqmd4HFndf6a//mmWxdnLF/1bBVXyJDA9izfhrBAX5cOLqFC0e34NEhY/+qINabCfEv8NkwHf97FwkPecKDW6dZO3cYZUwsqNlAO88j1YU2167bxxw7sI1jL7cFG5b+TljIM1q+3BZsXT2PpXOzbgtu4//gNgnxsURHheP/4LZWtgUe7V/WmSNpdWb3urS+QKN30+rMvk2qdbXRy77AnnUv6+qRLVw8skWlL9DkZV09ujOtrh7duZj7N07SNFNd3b95Fo/unCM85AlB/rfZv2U2D2+doV7TboWar56eHm4tB3Bu/yL8ruwjNPAO+9el7bdkftb13jU/cOK/jP0WN89PeHz7OOcPLCYs6D7nDyzmyZ2TuLXMyKlK7Xc5u28hD64fIirsCX5X9nHx0HIc67Yr1JzS6VK/523KDXS/T56ZLu2jqKPLfdbivK3TxNNVayjf4wPKv/8epatWpep3oyhZwZZnm7YAUPmrEVT7X8YIIqUqV8K6S2dKVaqIcZ3aVJ8+jTLOTjz6Y762UshRtw96c2DvTg7s3cmTxw9Z9vd8QoKf075zdwBWL/+beTMzjiEfPbSfP2b9wsDBw6lWvRbhYaGEh4Xy4i073lDYx2ff9mMpQhQHMuS4UHHv3j0aNmzIxIkT2bBhA5aWljx79gxvb28mTZpEeHh4rvOfPn2aIUOGMGnSJCZOnMj+/fv53//+x7hx45Rl9u7dS9euXRk/fjzff/89SUlJ3Lp1i3/++ee14x8/fjyLFi3Cz8+PUqVKoaenx9WrV2nZsiVTp07l6NGj6Onp4efnl+fd5q9LoVDwwQcfsGTJEs6cOcPDhw/56quv8PHxKbRlNus0hKTEeHaunkzci0gcHOvxyagllMw09EpkWAB6+hlX6FRybsCHQ2dycOtcDm6bRzmbinw4dBYOThlXdNZp3JnYmAgO7/iTmMhgbOxd6P/NIsyt7AGICn/G7UsHAVg48X2VmAZ+v4KqNVSvqJT8clf3nbR4Dm1fQHRkMOXtXfjk24XKeGIigokMDVSWt7B24JNvF7J73a+cPrAWE3MbOvf/idqNMp65GB0ezIIJPZT/H9+zlON7llKleiMGj1lZoPHnxd2jIy+iI9izZSFR4cFUqOjMsDELKGdtB0BkeDDhIRn5Wdk4MHTMn2xdMYOjPusxtbDhw0/H4NYk40BUh55fgJ4e/63/g8iw5xibWlDHvSVdP/qq0PPRVr0EuH3pINuXZhwo2rzwWwBadv+Sd9//v8JMGwAPz7bEREexZf0yIsJCqVjZkR8n/o61jS0A4eGhhAQHKcvv372dlJQUlv41k6V/Zez8e7bpxPCRP2f7fG3y8GxDdHQkW9YvJzwslIqVq/LjxBnK3CLCQwlVm9sslv6V8eiIlm06MXxk7heDFYa3uV42bNaBmOgIdm5eRFR4CHaVnBnx03wsM61jwjKtYwCmjs7oRD6+f4Ozx3ZTzroCv/y1u9DjzY/iXi9flZl7HZoeWKX8v9bvafXLf+VWrgwek9NsRUqTFu2IiY7Ee8MSIsJCcKjsxHfjZ2Nlk3aCMCI8hNCQjN/uoM82UlJSWLHoN1Ys+k05vXnrLnh9/WrPiCsobk078SImgn1b/yIqIhhbBxcGf79QuR2PiggmPNN+iqWNA0O+/4sdq6ZzfN86TC1seG/gT9RrnLGfEhcbxaYlE4mOCKFUGRPsK9dg+LgVVHLO+e6w/Mpr/RUdGUxkWICyvIW1A/1HLmLPul85ezBt/6pTv7HUathBWaYg1pv6+gY8f3KHyye2Ex8bjYm5NVVqNKbXsNkq6+w3SRfaXKPmHXgRHcnOjX8T+XJb8H9j/8DSJn1bEEJYyDOVeaaMytgWPPK7yZmju7G0rsC0RbveaOx13ulM7Iu0OhOdXmdGZtSZmMhgIkNV6+rHL+vqmfS62j9LXXXJqKu+2+ZhYVORXlnqakxUKFv//p7oyGBKlTahfMXqfDJqMU61mxV6zg1aDyE5KZ5DmyeTEBdJ+cr1eG/oEoxKZbSBmPAAlbt3K1RtQMdPZnJy91xO7Z6HmWVFOgychW3ljJxa9viZU7vncXjLZGJjQilrakMdjz40bj+80HMC3ev3vC25ge73yTPTpX0UdXS5z1qct3WaCPHZi6GZGRW/+Bwjayti7/lx/cuvSAhMa3tGVlaUtLVVltfTN8B+wMeUrlwZRXIykWfPcWXApyQEBOa0CK1p5tma6KhINq1bSXhYKJUqV+WnSdOxSa+XYaGEBD9Xlt+3519SUlJY/NccFv81Rzm9VZuO/N+3b37fTJePz77Nx1KEKA70eJPj9ggh8k2hULDuuG4204+apW38dTG/9Nw2niz84ey0oXfTtAE+9l4u+DvUta29qxGg2/Xy4t2QPEoWT/Vd0p5PdOmu7l296uaSNuysLtdL36txWo6kcLxbtzSg2/VyZ4nqWo6k4HVJug3AmVuRWo6kcDSukfa80n/PJ2s5koLXzT3tmm1dXl/qYpuDjHZ3+HqsliMpeC1rlwFg/Qndq5cAfT3S6ub8XbqX34jOabnpcr9HF3ODjPx0sU+e3h/Xxf2U9H0UXe+z6vK27phrAy1HUvCaX74AwLV7z/IoWTzVcU47ka7L+8+6mlvWR3WIN+/GvSfaDiFHtZwdtB1CgZMhx4UQQgghhBBCCCGEEEIIIYQQQhRJckJbCCGEEEIIIYQQQgghhBBCCCFEkSTP0BZCCCGEEEIIIYQQQgghhBBCCA0pFDLs+5skd2gLIYQQQgghhBBCCCGEEEIIIYQokuSEthBCCCGEEEIIIYQQQgghhBBCiCJJhhwXQgghhBBCCCGEEEIIIYQQQggNKZAhx98kuUNbCCGEEEIIIYQQQgghhBBCCCFEkaQHKLQdhBAiZwqFNFEhhBBCCCGEEEIIIYQQQqTR05O7g7Xt2t0AbYeQozoudtoOocDJkONCCCGEEEIIIYQQQgghhBBCCKEhGXL8zZIT2kIUA+uO6+Zd2h81S1vhrz+he/n19UjLzfdqnJYjKRzv1i0NwJMRvbQcScFzmL8J0M12l97mYo9s1HIkhaOMZ28ADl3TvXbXqk5am9Ppenl8i5YjKRxlmvUEdLteHr4eq+VICl7L2mUAiPNdo+VICkfpd/sDEH9gpZYjKXil2gwAdHt9qYttDjLa3c4S1bUcScHrknQb0M16CRl1s3m3w1qOpOAd+7clAP7De2o5koJXcUHavpcu9ukgo1+ni33y9P64Lu6npO+j6HqfVZe3dfuvJGg5koLXtl5JAHZfTNJyJIWjU/0SgG4fn9XFfbD0/S8hCsqwYcMYPXo0FSpU4Pr163zzzTccO3ZMbdkPPviAYcOG4ebmRsmSJbl+/ToTJ05k7969hRqjPENbCCGEEEIIIYQQQgghhBBCCCHeMr1792bOnDlMnTqV+vXrc/ToUXbv3k3FihXVlvf09GTfvn107twZd3d3fH19+ffff3FzcyvUOOUObSGEEEIIIYQQQgghhBBCCCGE0JCuDDn+7bffsmTJEpYsWQLAyJEj6dChA8OGDeOnn37KVn7kyJEq/48dO5b33nuPbt26cenSpUKLU+7QFkIIIYQQQgghhBBCCCGEEEIIHWBkZISJiYnKy8jIKFu5EiVK4O7unm248L179+Lh4aHRsvT09DAxMSEsLKxAYs+JnNAWQgghhBBCCCGEEEIIIYQQQggdMGbMGKKiolReY8aMyVbOysoKQ0NDgoKCVKYHBQVha2ur0bJGjRpF2bJl2bhxY4HEnhMZclwIIYQQQgghhBBCCCGEEEIIITSkUBTdIcenTZvGrFmzVKYlJCTkWF6hUKj8r6enl22aOn379mXixIm89957BAcHv1qwGpIT2kIIIYQQQgghhBBCCCGEEEIIoQMSExNJTEzMs1xISAjJycnZ7sa2sbHJdtd2Vr1792bJkiX06tWLAwcOvFa8mpAhx/Nh4MCBhIeHazsMnePr68vs2bO1HYbGli1bxrZt27QdhhBCCCGEEEIIIYQQQgghhBCvJCkpifPnz9OuXTuV6e3atePEiRM5zte3b1+WL19Ov3792LVrV2GHCej4HdoODg5MnDiRTp06YWVlRWBgIN7e3kyePLnQH06eX76+vly6dImRI0cC8ODBA+bMmcPcuXO1Es+DBw+oUqUKALGxsdy/f58//viDv//+Wyvx5MeECRN4//33qV+/fp7lJk6cCEBKSgoBAQH4+PgwZswYQkJCcpzv66+/Rk+vaA4lcebgWk7sWUJ0RDA29s50/OgnKldrmGP5h7fP4LP+V54/vYeJuQ3NOg2h0bt9VcrcOOfDwW3zCA9+jIV1Jdr0+Iaa7hkrt6M7F3Hz/D5CAu9jaFSKis71affhKKwqOBZ4bsd3LyEmIhhre2c69csjt1tn2LP+V4Kf3sPEIvfcwp4/ppxN9txmf9eaiNCAbJ/dqHU/un4yvuCS09ChPRvYt2MFkeEh2FV0oteg0bjUaqC2bGR4MJtXzOTx/Zs8D3zMu50/oven37/hiDVXtkV7TNq8h4GZOUmBT4jYsoxEv1s5li/dsDkmbd/D0KYCirhY4m9eInLbSlJfxLzBqNMoFAoObZ/P+cMbiY+Nwt6xHl0+Ho+NvUuu8+XVtiD3Np2SnMTBbXO5e+Uw4cFPKFnaGMdaHrT98FtMLcoXWr5ZbfQ9zQqfY4RExuBkZ8N3fTrRoFoVtWXP3X7A578vzTZ96+SvqFrBupAjzb9Dezawd3tGm+v9ae5tbtNy1TbX5zPttTld3h5oYuPBU6zYc5SQiGic7G347qMuNKhWNc/5Lt19xJDpi3GyL8+GSf/3BiLNv+JcLzVxaPdGfDLl1+ez73LMLyIsmM0rZvHILy2/1p0/os/g0W84Ys1tOHSWFftOEhIZjZOdDaN7taeBS2W1Zc/efsjns1dmm75t4nCq2loVdqj5tuHwOZbvP5W2Lahgzfe92tHAuZLasmfvPGLInNXZpnuP9yr03LSxbtRkub7ef3DtzC6iwp5hYFiCCpVr06bHNzg4uRbsF6CGLre5nJRr3hDHUYMxa1CHUnY2nOs5nKAdhX83QX687fuXAJ99VJnuHSpgYmzIjTvRzFp4lwePY3Ms36lNecZ+UyPb9NY9jpCYlPdQiW+KsWcHTNq+h4GZBUmB/oRvWkai380cy5dp1AKTdu9n9HtuXCRi6wqt9Hs0UZz7dXnR5f64Lu+jgG73WdUpDts5dY74rGf/9uVERoRQwcGJDz/9Huea7jmWv3v9HFtWzCDwiR9mFta0e+9TWrTvrXw/JTkJn21LOH14BxFhzylvV4X3+n9D7frN30Q6Ko7tXc/Bf5cRFRGMrYMzHwz4Aadccrt34yzeq2bw7Mk9zCxsaN3tU5q166N8/49Jg/C7eS7bfLXqt+CLH/4qlBzSaeP4LEBUeBD7Nv7O3atHSE5KwLJ8Fd777H/YVanzWvloa58rP8v2v3eRA1vn8PT+FfQNDLGtVIOPRy4GSr9W7qJgpFI0zxPl16xZs1i1ahXnzp3j5MmTfPHFF1SqVImFCxcC8Msvv2Bvb8/AgQOBtJPZK1eu5Ouvv+bUqVOUL5/WV4iLiyMqKqrQ4tTZO7SrVq3KuXPnqFatGh999BHOzs4MHTqUNm3acPLkSSwsLHKct0SJEoUWl6Fh8bmGYNy4cdja2lKvXj28vb1ZtGgRvXv3Vlu2ML+zwnTt2jVsbW2pVKkSw4YNo1u3bqxcmX3HHEBfXx89PT2ioqKIjIx8w5Hm7dqZXexZN40WXYcydOI2Krk0ZPXsL9SekAUID37CmtleVHJpyNCJ22jR1Yvda6dy45yPsoz/vYtsWvgtrh7dGTppO64e3dm0cCRP/C4ryzy8fZZGrfsx5OcNDBi1lNSUZFbNGkJiQs4HG/Kd2+ld7Fk7Dc+uQxk6aRuVqzVk9azcc1s924vK1RoydNI2WnTxYvcaNbn99S31mnZn2OTt1GvanY1/qeb2xfjNfDfnqPI14Lu0Tk3tRh0KLDdNnTvuw6blM+jUYwhjZ6zHuWZ95v/yJWHBgWrLJyUlYmxqQaceQ3CoXO0NR5s/pRt4YN7zU6J8thD06/ck+N3EavhYDCzUd4aNHGtQbsD/EXvyIEFTvyV0ySyMKjlh0W/YG448zfHd/3By73I6fzyOz8dtwtjMmpW/f0ZCXM4HYTRpW3m16aTEeAIf3cCz23C8Jmyhz4g/CA16yLp5wws953Q+Z68yY8NuBndpybrxw6jvUpkR81YRGBqR63zeU75m3+/fK1+Vylu+mYDz4exxHzYum0HnnkP4+fe0NvfH1NzbnImpBZ16DsGhinbbnC5vDzThc+YKM9btZHDXVqybOIL6LlUYMXtFnvUyOjaecf9sonFNpzcT6CsozvVSE2eP+bBh2Qw69xzMuJnrcKlZn3n/G0FoDvklJydhbGpB556Di3x+PueuM2OTD0M6NWf92C+o71yJL+evJTAs933K7ZO+ZP/0b5WvSjbl3lDEmttz7ga/bd7H5x2bsWHMEBo4V2T4n+vzzm3CUA5M+1r5KuzctLVu1GS5lrZV6Nx/HMMm7+CzMWswt7Jn1azBvIgq3IuwdbnN5cagbBmirtzm+teTtR1Kjt7m/UuA/j0r0ud9B2YtuseQby8QGp7I7Mn1KF3aINf5Yl4k0/2TEyqvonQyu7S7B+YffkrUni08m/YdCfduYv1lLv0epxqUG/h/vDhxgGdTviHkn98xquyMRf83+3toqrj363Kjy/1xXd5HAd3us+akOGznsjp/fA+bl/1Gh56fM+a3jTjXbMCfU4fn2MZCgp6wYNpwnGs2YMxvG+nQYwiblv7KxVP7lGX+XT+fY/s20+uzMYyb7U3zdr1YPGMk/g9yvoioMFw4sZttK36l3Qef892vm3Cs0YBFvw4lPER9bqHPn/D39OE41mjAd79uou37Q9i6fBqXT2fk9tmouUxeeEj5+mGGN/r6Bri+U7jHK7V1fDbuRSRLpn6EvqEhH3+7mC+n/keHvj9Qqozpa+ekrX0uTZftf+8iq2d/jlPtZnw+biNfjN9E4zb90dPT2dN6Qks2btzIN998w/jx47l06RKenp507tyZx48fA1ChQgUqVcq4aN3Ly4sSJUqwYMECnj17pnwV9g26Olvz//zzTxITE2nfvj1HjhzB39+fPXv20LZtW+zt7Zk6daqy7IMHDxg7dizLli0jIiKCxYsXA2lDjD969IgXL16wdetWLC2z77x07dqVc+fOERcXh5+fH+PHj8fAIKOTpVAo8PLywtvbm5iYGH7++ec8Y/f19aVKlSrMmTMHhUKh8uD1pk2bcvjwYWJjY3n8+DFz586lTJky2XJZsWIF0dHRPHz4kO7du2NlZYW3tzfR0dFcuXIFd/ecrwJLFx0dTVBQEH5+fowbN447d+7w/vvvK2P8448/mDlzJsHBwezbl7ZR9fT05PTp08THxxMQEMC0adNUvo8yZcooYwsICODbb7/NtlyFQsF7772nMi08PFx59QeAvb0969atIzQ0lJiYGM6ePUvjxo0ZOHAgEydOxM3NTfndZZ4vq+TkZIKCgggICGDnzp3MmzeP9u3bU6pUKeUQ8126dOH69eskJCRQuXLlbEOO6+np8f3333P37l3i4+N59OgRP/30k/J9Ozs71q9fT1hYGCEhIXh7e1O5svorXV/HSZ/lNGjRE3fPXljbOdGp30+YlbPlnO86teXPHVqPmWUFOvX7CWs7J9w9e1G/RQ9O+GRciXpq30qcannQoosX1hUcadHFi6o1m3Bq3wplmU++/Yf6zXtgY++CbaUavP/ZNCJDAwh4eL3Acjuxdzn1PXvi3jIjN9Nytpw9qD63s75ZcmuZltvxPRm5ndy7EsfaHnh2TcvNs6sXjjWbcDJTbmVNy2FiZq183bl8iHI2lahSvXGB5aap/f+uolnrD2jetgcVHBzp/en3WFjacnjvJrXlrWzs6fPZDzRp1Y1SZYzfcLT5Y9K6Ky9OHiT25EGSg54SuWU5KeEhlG3RXm15o6oupIQ+J+bwblJCn5N4/xYxx/dRotKbvwtUoVBwat9KPLsOpZZ7e8o7VOODwb+SlBjP1dP/5TifJm0rrzZdqowJA75bSp3GnbCq4EhFJzc69/+ZwEfXc+xMFLTV+07wfvMG9GjREMcKNozu2xlbC1M2HT6T63zlTMtiZWaifBnoF73dkaxtrs9nL9ucTy5tbvAPNG3VjdJabnO6vD3QxGqfY7zfwp0eno1wtLNhdL+u2JYzY5Pv6Vzn+9/KbXR8x5V6ThXfUKT5V5zrpSb2/bua5m3ep0W7l/kNHp1Hfnb0Hfw9Td8t+vmt2n+SD5rVp0fzBjhWsOb73h2wtTBj0+Hsd1ZkZmFSFiszY+WrKK4vVx08zQcebvRoVh/HClZ836s9tuambDxyIdf5yr3h3LS1btRkufWadMOptgflbCpiY+9Ch74/khAXQ9CT24X3haDbbS43wT5HuDNhDs+89+VdWAve9v1LgF7d7Vm58TFHTobw4HEsU2ffomRJA9q3tMl1PoUCwiKSVF5FiUnrbrw4cZAXJw6Q/OwpEZuXkRIRirGn+hMQJatWIyU0mJhDu9L6PX63iDm2F6PKRfPiu+Lcr8uLLvfHdXkfBXS7z5qTor6dU+fAfytp2voDmrXpia2DIx9++gMWVrYc3btRbflj+zZhYVWBDz/9AVsHR5q16UnT1h9wYEfGNu/Mkf/o0GMIdRq0wKq8A54d+lDTzYMD/6q/kamwHNq5knfe7UHT1h9ia+9Ej4E/Ym5py7F969WWP75vI+aWtvQY+CO29k40bf0h77z7AQf/W64sU9bYDFNzK+Xr9tWTlChZCrcm6te3BUVbx2eP7foH03IV+GDwNBwc62Fh5YBjraaUs1E/IpSmtLnPpemy96z/lXfafEKLLl9gY++CZfkq1G7YEcMSRq+VuxDq/PXXX1StWpVSpUrRsGFDjh49qnzv008/5d1331X+/+6776Knp5ft9emnnxZqjMVna5wPFhYWdOjQgQULFhAfH6/yXlBQEGvWrKFPnz4q00ePHs21a9dwd3dnypQpNG7cmKVLl7JgwQLc3Nzw9fXNdjK6ffv2rF69mnnz5lGrVi28vLwYNGgQY8eOVSk3adIktm/fTt26dVm6NPuwNVn16NEDf39/5R3S6Q9jr1OnDj4+PmzdupV69erRp08fmjdvzvz581XmHzlyJMePH6d+/frs3LmTVatWsXLlSlavXk2DBg24d+9ejnch5yY+Pl7lTuyBAweSnJxMs2bN8PLyws7Ojl27dnH27FlcXV0ZNmwYgwcPVvneZsyYwbvvvssHH3xA+/btadWqlUYn1zMrW7Yshw8fxs7Oju7du+Pq6spvv/2Gvr4+GzZs4Pfff1feeW1ra8uGDRs0/uy4uDgMDAyUd9KXKVOGMWPGMGTIEGrXrs3z58+zzTNt2jR++OEHpkyZQq1atejXrx9BQUEAlC5dGl9fX2JiYvD09KR58+bExMSwZ8+eAr2rPTk5kYBH13Gq3UxlulPtZvjfu6h2Hn+/S9nKO9duTsDD66QkJ2WUqZOlTJ3m+PtdyjGW+LhoAEqXNctvGmolJycS+PA6zupy81Of2xN1udVRzU1dGac6zfG/dynHOK6c3EH9Fj3e+JDzyUlJPL5/k5quTVWm13Rtwv3bl3OYq5gwMKRERUfib6rmEX/zCiWrVlc7S+L92xiYW1KqVtpjBfRNzCjj1pT467kfOC8M4cFPiIkMVqlLhiWMqFK9UY5tD/JuW6/SpgHiY6NBT69ArlLNS1JyMjcfBdC0lrPK9Ca1nbns55/rvH0nL6Ddd9PxmrmMs7fuF2aYryQ5KYnHfjep5aba5mq5NsGviLc5Xd4eaEJZL2urDtHVpLYzl+89ynG+7UfP8+R5GF7vtS7sEF9Zca6XmlDml2VbV8utCX63ind+Sckp3HwcSNMsd/83qenI5ft5rC+n/k3b72fxxeyVnL39oDDDfCUZuakO6d+0piOX7z/Jdd4+0/6hzY9z+HzuGs7cfliIUWpv3fgqy01OTuT84Q2ULG1C+YrZh08uKLrc5oq7t3n/EsCufCmsypXkzMVw5bSkZAWXrkVQp0buMZQubcDmJe+wdVkTpo+vg4tjETqRaGCIUSUn4m9eUpkcf/MyRo7q+z0J6f2e2mnDWuubmFG6flPir50v7Gjzr5j363Kjy/1xXd5HAd3us+qS5KQk/O/fpKarh8r0mvWacv/2JbXz3L9zmZr1srZJDx7dv6HcT0tOSqRElpN+JYxK4ncr521eQUtOTuLJgxvUqKeaW416Hjy8o3798fDuZTXlm+F/P2MfNKvTvltp0LQTJUuVUft+QdDm8dnblw5iV7UOG/78mt++8uCvCR9w7rD6ix3yQ5v7XJosOyYqlKf3L1PWtBz/TO3LjG+asezXj3l0pwjuB7zFFOgV2ZcuKj7jX+eDi4sL+vr63LypfgiRmzdvUq5cOaytrQkODgbg4MGDzJw5U1lm8uTJ+Pj4MH36dADu3r2Lh4cHHTt2VJYZO3Ysv/76q/Lk8IMHDxg3bhy//fYbkydnDOuydu1ali1bpnH84eHhpKSkKO+QTjd69GjWrl2rvG3/3r17fPXVVxw+fJhhw4aRkJAAwK5du5TPup48eTLDhw/n7NmzbN68GYDp06crx7XP/Pk5MTAw4OOPP6ZevXr89VfGczju3bvHDz/8oPz/f//7H/7+/owYMQKA27dvY2dnx/Tp05k8eTJlypRh8ODBDBgwgP379wNpJ8WfPMn9YFdW/fr1w9ramkaNGhEentbJ9fPzU74fExOjvPM6P6pXr86wYcM4ffo0MTFpQ3sYGRkxfPhwrly5onYeY2Njvv76a0aMGKGsB/fv3+f48eNA2rMEUlNTGTJkiHKeTz/9lIiICFq1aqW8sz2dkZERJUuWzFfcALHR4ShSUyhrpjqKQFlTS2Ii1T8PPCYymLKmqs+NKWtmSWpKMrEx4ZiY2xATGUJZU3WfGaz2MxUKBT4bfqWSizvlHQpmWK3Y6HBSU1OyxWFsZknMtZxzMzbLkptp9tyMs35mLrndunCA+Nho3Jp98BrZvJqYl9+BqZnqEF6mZpZEReT8vPfiQN/YBD0DA1KjI1Smp0ZHoG9qrnaexAd3CFsxj3KfjUSvRAn0DAyJu3KWiI15XzBU0GKi0uqLunYSmctdLHm1rVdp00lJCezfPJO673SlVOnCP3gXHhNLSmoq5UxVl2VpYkxoZLTaeazMjBn3yXvUrGxHYnIyO09dxmvWchZ/9xnuOTzDTBtyanMm5kW/zeny9kAT4dEv66VZlnppakJo5F218zwKCmHelj0s/dELQ4PchzLVpuJcLzWhzM9c3bYuVEtRFYy09aWCcqZlVaZbmpYlJOqF2nmszYwZ178rtSpXIDE5mf9OXeWLOav459uBuOfwTEttSM/N0iRrmytLSJT6YfqszYwZ368ztSrZkpicwn+nr/LFvDUs+eYT3F1e7y6LnGhr3Zif5d6+5MvmRaNISozDxMyaAd8tpaxJzo/Jel263OaKu7d5/xKgnEXayYewiESV6eERiZS3KZXjfI+fxPLLnFvcf/iCMmUM6dXdnr9+c2PQ/53nSWBcocasifR+T0q06jDOKVERlMqp33P/NqHL52A5+NuMfs/lM4RvWPIGIs6f4t6vy40u98d1eR8FdLvPqksy9klUt0+59XOiI0IxyVLe1DxtPy0mOgIzC2tqunpw4L9VONdyx6p8RW5fPc2Vs4dQpKYUWi5ZvYhKy80ky7bXJJf1R3REiNrymXPL7NG9qwT636WvV+EOMa/N47Phz/05d3AdTTsMwrOrF0/uX2H3mqkYGhrh1uz9V85Jm/tcmiw7PDjtwptD2+fTvvf32FaqyeUT21n5+yCGT/kXUL2oWIi3gU6e0M5L+t2VmYfyPndOdSidmjVrqgwrDXDy5EmVE9ru7u40atRI5Y5sAwMDSpcuTenSpYmLi1P72a/K3d0dZ2dn+vfvr5KLgYEBVatW5datWwAqJ1/TT+pevXo12zQbG5tcT/pOnz6d//3vf5QsWZLExER+++03Fi1apHxf3Xd28uRJlWnHjx/HxMQEBwcHLCwsKFmypEqZ8PBwbt/O31B6bm5uXLx4UXky+3XUrVuX6OhoDAwMKFmyJIcOHeKLL75Qvp+QkJDjyWxIy7lUqVIcOHBA7fvpv1l0tOqOcqlSpXBycsp2QnvMmDFMnDjxlfPRy3rljQLI5W7ibHcaK5Rv5P6ZOVzhs2v1FIL8b/PZmLUaxZsfWWNVKNTEpjpHTh+U42emzaV+vgtHNuNctwWmFuXzjLWwZPsO0n5g7QRT2PT00n5kNQxtHTDv9SlRuzeTcPMS+mYWmL3/CRZ9vyB87V9q5ykoV07+y78rJyj/7//Nwpfhqvkd8riTX5O2pWmbTklOYvPCb1EoFHT5ZEK29wtT9tWIIsdRDKrYWlPFNqPz5epUiaCwSFbuPVY0Dw5kS674tDld3h5oImusCoVCbfopqan8tGgDQ99rS2Vb9c93LHKKcb3UiLpt3RseGaWwqPvpcsqsiq0VVTLVSVfHigSFR7Jy38kid7AY1OWWy7agvCVVMj2H0tXRgWfhUazYf6rQTmin09a6UZPlVq35DkMnbiM2JpwLhzex6a9vGPLzxmwH+AqcDre54uJt379s19KG0V9mXPz2/eSrGXFlpqeXfVom129Hc/12Rr/76s1Ils5xp2c3O+b+7ZfzjG9a1j5OLnkZ2jpg0WswUbs2EX/zEgamFpj1GIBFPy/CVy8o/FgLQhHt170KXe6P6/I+Cuh4n1WnZK+IuY2QmP04oXJHDYAPP/2BtYsmMfnr99DT08OqvANN332Pk77bCzJozahZf+Q6+qPa9Y36fYNTvlupUNGFys51Xz9ODWjj+KxCocCuSm3afpj26NIKlWsRHHCPs77r8nVCuyjuc+W2bIUiFQD3Vn2o36InkJb7/ZsnuXh0C/T4LtcYhdBFOnlC+969e6SmplKrVi22b8++kapRo4byecbpXrxQvfJQkyGF9fX1mTBhAlu3bs32XuahzrN+9qvS19dn0aJFzJs3L9t76Q9nB0hKyj78SOZp6Rt4/Tye/zJjxgyWL19ObGwsgYGB2d5X950psnRUMl88oOkwzampqdnKZh6eO/1CgYJw+/ZtunfvTkpKCgEBASQmql4Fntey8npfX1+f8+fPq1yEkC59dIDMpk2bxqxZs1SmRUVF5boMgDImFujpG2S7sv5FdGiOB8GMzayzl48KRd/AkDJlzV+WsSImSs1nmmU/6L9rzRRuXzrIpz+uxqycbZ4xa6qMiQX66nKLCs12pVs6TXOLzlImJiqUsmpyiwh5yv0bJ+k74o/XyOTVGb/8DiKz3C0THRmW7QrW4iY1JhpFSgr6JuYq0/WNzUjNcvdCOpP2H5Dgd5uYAzvSJgQ8JiIhAZtvpxD53zpSoyIKLd7qbu9i71hP+X9Kcto6IyYyBBPzjGf6vYjKue1B3m0rP206JTmJTX+NJCL4CQO/X/7G7p6xMC6Dgb4+oZGqd+CFRb/IdgV8buo6OrDrVNEaqi+9zWW9Q604tDld3h5owsIkvV6qXkgWFh2jtl7Gxidw4+FTbj8OZPqafwFIVShQKBQ0HPIzC0Z9SuMsQzBqS3Gul5pQ5heuJr8sd0QVN2nrSz1CI1X3ncOiX2CZ5Y6o3NSt6sCuM1fzLvgGpeeW9W7ssOhYLE00z61eVXt2nrlW0OEpaWvdmJ/lGpUsg2X5yliWr0xFJzfm/diBi0c306KLV77z1YQut7ni5m3fvzx2JpQbdzIuljcqkXacopyFEaHhGf1zC7MS2e7azo1CATfvRlPRrvCGX82P9H6PQZa7lQ1MzEjJcldzOtMOPUi4f4vo/WnHtZKePiJ1fTzlR00lcsfaQu335Fdx69flhy73x3V5HwV0u8+qSzL6Oarbp+jIsGx3KqczMbckKjx7eX0DQ4xN0h55ZWJWDq/v55KUmMCL6AjMytmwfc0cLG3sCycRNcqapuUWnSW3mFxzs1JbXt/AkLLGqo/zSkyI4+KJ3XTq9WXBBq6GNo/PGptbY22n+ugAqwpO3Di3N185FKV9LmNT6zyXbWKWNj1r7tYVnIgMy36uRmiHQqEbF7cVFzr5DO2wsDD27dvH8OHDKVVKdUiq8uXL079//zyfq3zjxg2aNGmiMi3r/xcuXKB69er4+flle2U9sZtfiYmJGGQZ9vLChQvUrl1b7fLUncR+XSEhIfj5+ak9ma3OjRs38PBQfcaHh4cHUVFRPH36lHv37pGYmKjyPZqbm1OtmupQpMHBwVSoUEH5v7OzM2XLZuxIX7lyBTc3Nyws1A/Bp+67y0liYiJ+fn48fPgw28lsTdy9e5fY2FjatGmj9v0LFy7g4uLC8+fPs/1m6k5UJyYmEh0drfLShKGhEXaVa+N344TKdL/rJ6joXF/tPBWd3PC7nrX8ceyq1MbAsETOZa4dp6KTm/J/hULBztWTuXl+HwO/X46FtYNGMWvK0NCIClVqZ4vj/o0TVHRSn5uDkxv3s3wX97Lk5uDkxn01+Vd0dsv2eRePbaWsqSUuri1fI5NXZ1iiBJUca3LziuoICDevnMaxuqtWYiowKckk+d+nVI16KpNL1ahHwgP1ozfoGRllv8r/5VWLhX1HUcnSxsqDzZblK2Nt54yxmbVK20tOTuTh7bM5tj3Iu21p2qbTDzaGPn/EgO+WUca48IYmzaqEoSE1K9tx6qbqHS+nbvjh6lRR48+59TgQKzOTgg7vtRiWKEElp5rcvJy9zTkV8Tany9sDTSjr5Y17KtNPXb+Hq3P2O0bKlirJpslfsX7iCOXrw1aNqWJrxfqJI6jrqHldLmzFuV5qIj2/G5dPqUy/efkUTjWKd34lDA2oWakCJ2+qPn/x9M37uOajjt32f4aV2Zu5aElT6bmduqn67MxTtx7g6qj5OuDWk6BCzU1b68ZXWW46BQqSk/LfP9GULre54uZt37+Mi0vhaWC88vXgcSwhYQk0cstYrqGhHm51zLl2K++LvTNzcSxLaFhCQYf8alKSSXzsR6maqu2rVI16JN7Pqd9TMnu/J/XN9HvyrZj16/JDl/vjuryPArrdZ9UlhiVKUNGxJreytLFbV07hWN1N7TyO1Vy5dSXrPswJKjvWUu6npSthVBJzy/KkpiRz8dR+6jVqVZDh58rQsAQOVWtx+6pqbrevnqRKNfXrjyourtnK37pygoqOtbPldvGkD8nJiTRs0a1gA1dDm8dnKznXJ+SZan8jNOgh5pZ2+cqhKO1zWVg75Llscyt7TMxtCA3MnrtZPnMXQlfo5AltgBEjRlCyZEl8fHxo0aIFDg4OdOjQgX379vH06VOVYcLVmTdvHh07dmT06NG4uLjw5Zdfqgw3DmnPpx4wYAATJkygVq1a1KhRg969ezNlypTXjv/hw4d4enpiZ2eHpWXaVTnTp0+nadOmzJ8/H1dXV5ydnenWrZvaO7a1YcGCBVSsWJE//viD6tWr0717dyZNmsSsWbNQKBS8ePGCJUuWMGPGDFq3bk3t2rVZvnw5qekdspcOHjzIiBEjqF+/Pu7u7ixcuFDlZPO6det49uwZ3t7eeHh4ULVqVXr06KE8Uf7w4UOqVq2Kq6srlpaWGBkZFVrOCQkJTJ8+nd9++41PPvkER0dH3nnnHT777DMA1qxZQ0hICNu3b6d58+ZUqVIFT09P5syZg719wV4R2LTDIC4c2cyFo1sIDvBjz7ppRIYF0rBVXwD2b57J1sUZzzxv2KovkaEB7Fk/jeAAPy4c3cKFo1vw6PCZssw77T7B7/pxju1aTHDgfY7tWsz9mydp0m6gsszO1ZO5cvJfenr9jlGpskRHBhMdGUxSYsYoBa/Lo/3L3I6k5bZ73TQiQwNp9G5abvs2qebW6N2+RIQEsGfdy9yObOHikS0065iRW5OXuR3dmZbb0Z2LuX/jJE0z5QZpIwZcPLYNt2bvY2CgvUEt2nb7hOMHtnH8gDeBT+6zcdkMwkMC8Wz/IQDb1sxj2byfVebxf3AL/we3SIiPIzoyHP8HtwjwL0LD7b0UffA/ynq0oUyTdzEsb49Zj4EYlLPixdG0Ky1Nu/fD4pMRyvLxV89T2q0xZZu3x8DSBiPH6ph/+CmJD++SGvn6jyLIDz09PZq0G8DR/xZx8/w+gp7cwXvJGEoYlaLuO12V5bYu/oH9m2cq/9ekbeXVplNSktm44GsCHl6j5+czSFWkKNtfcnLhHQDP7ON2Hmw7eh7vY+e5H/ic3zfs4llYJB+2bAzAvK17+XnJZmX5NftP4HvxBo+CQvF7GsS8rXs5cOEGfVq/80bizY+23T7hWJY2F5a5za3Ouc3Fx8cRE6W9NqfL2wNNfNyhOduOnMP76DnuBzzn93U70+plq5f1crMPPy/eBKSNpOLsYKvyKmdSFqMSJXB2sKV0ycLbh3gVxbleaqJdt485dmAbx17mt2Hp74SFPKPly/y2rp7H0rlZ87uN/4PbJMTHEh0Vjv+D20Uyv0/aNmXb8Qt4H7/I/cBgZmz0ITA8kg893QGYt+0APy/zVpZffeAUBy/d4lFQKPcCnjNv2wH2X7xJ31aNtJRBzj5p/Q5bT1xi24lL3A8MYcbmfQSGR9KrRQMA5nr7Mnb5DmX51QfPcPDSbR49D+NeQDBzvX3Zf/EWfVs2LNQ4tbVuzGu5iQmx7N8yC3+/S0SEPCXg0XW2L/uZqLBn1G6k2v8saLrc5nJjULYMpq41MHWtAUCZqg6YutagVMUKecz5Zrzt+5cAm3Y85ZNelfBsYknVSmUY+011EhJS2Hv4ubLMzyOr4zUg49mRn/atTOP6FtiVL4Vz1bKM+aoaLlWN8d5ddO5gij74L2U92lC2aWsMbe0x7zkIAwsrYl72e8ze60+5gf+nLB939Ryl3d6hbIsOGFiWx8ixOha9B5Pw4M4b7/doojj36/Kiy/1xXd5HAd3us+akqG/n1GnTdQAnDmzlxMFtPHtyn83LfyMsJJDm7XsBsH3NXFb88ZOyfPN2vQgLCWDL8hk8e3KfEwe3cfLgNtp0z9jmPbh7hUun9xMS9IR7N88zf+owFIpU2r336RvNrVWXAZw6uIVTvlt59tSPbSumEx4SSLO2fQD4d91sVv85Rlm+WbvehIcEsm3lbzx76scp362c9t1K666Dsn32ad+t1G3YmrJZRscoLNo6Ptu0/SCe3L/Mkf8WEhr0iCsn/+X8oY00bpN9RNT80OY+lybL1tPTw6PjYE4fWMX1c3sIDXrEwa1zCQm8T4MWH75W7kIUVzo55DikDTvesGFDJk6cyIYNG7C0tFSeBJ00aVKez18+ffo0Q4YMYdKkSUycOJH9+/fzv//9j3HjxinL7N27l65duzJ+/Hi+//57kpKSuHXrFv/8889rxz9+/HgWLVqEn58fpUqVQk9Pj6tXr9KyZUumTp3K0aNH0dPTw8/PL8+7zd+UgIAAOnfuzIwZM7h8+TJhYWEsWbKE//3vf8oyo0ePxtjYmB07dhAdHc3MmTMxM1MdLmXUqFEsW7aMI0eOEBAQwNdff427u7vy/aSkJNq3b8/MmTPZtWsXhoaG3Lhxgy+/TBteZcuWLfTo0QNfX18sLCwYNGgQK1asKLS8p0yZQnJyMpMnT8bOzo7AwEAWLkx7BkdcXByenp5Mnz6drVu3YmJiwtOnTzlw4IBGQ4nnR53GnYmNieDwjj+JiQzGxt6F/t8swtwq7cR5dGQwkWEByvIW1g70H7mIPet+5ezBtZiY29Cp31hqNeygLFPJuQEfDp3Jwa1zObhtHuVsKvLh0Fk4OGVcRXjOdx0Ay6cPUInnvc9+oX7zHgWT2zudiX2Rllt0em4jM3KLiQwmMlQ1t49f5nYmPbf+WXJzycjNd9s8LGwq0itLbpB2pWFkaAD1WxRMLq+qYbMOxERHsHPzIqLCQ7Cr5MyIn+ZjaZ12RV5keDBhIaoHa6aO7qv8+/H9G5w9tpty1hX45a/dbzT2vMRdOEFEWWNMO32IgakFSYH+hCz4hZSXw0cZmFpgWC5jqKHY04fQK1UK45YdMesxAEXcC+JvXyNy+xqtxN+s0xCSEuPZuXoycS8icXCsxyejllAy09CMkWEB6Oln3GWgSdvKq01HhT/j9qWDACyc+L5KTAO/X0HVGoXf4e7QqC6RMbH8/d8hQiKjcbYrzx9ffYKdpTkAIRExPAvLGGIwKTmF2Zt8eB4RRckSJXCys2HeV5/Qom61HJagPY2adeBFdAQ7Ny0iMnObs8m5zf3vu0xtzu8GZ47uxtK6Ar8sfLNtTpe3B5ro0LheWr3ccTCtXtqX549vBmJnlXanV0hkNM/CIt5YPAWpONdLTTRq3oEX0ZHs3Pi3Mr//G/tHpvxCCAt5pjLPlFEZ+T3yu6nMb9qiXW809rx0aFibiJhYFu08QkhUDM52Nswf0U+5vgyOjCEw6/pyyz6eR0RTsoQhTnbW/PHlR7So66KlDHLWsWEtIl/E8veuYwRHxeBcwZo/h/fFzjJtHz8kKoZn4aq5zdp2ICO3CtbMH96HFnWcc1pEgdDWujGv5erpGxAS+IDLx78iNiac0mXNsa9al8/GrMHGvnB/b11uc7kxc69D0wOrlP/X+j3tALn/yq1cGTwmp9neqLd5/xJgzRZ/Shrp8+0wF0yMS3DjThQjx18hLi5FWaa8dSlSM93ca2xsyPcjqlHOwogXL5K5cz+GL3+8zM27mo169ibEnT9BRFkTTDv3etnveZzW7wlLexyZgakFBhaZ+j2nfNEvVQqTlp0w7zkQRewL4u9cJXLbam2lkKvi3q/LjS73x3V5HwV0u8+ak+KwncvKvVlHXsREsHvzIqLCg6lQ0ZnhP/2p0sbCM+2TWJV3YPiYBWxZ8RtHfNZjZmFNr89+pH6TdsoyyYmJ/LtuPiHPn1CyVBlq12/OwP/7hTJlTd9obg08OhEbE4nPloVERQRToaILXj/+RbmXuUWFhxCeaf1haePAFz8swHvlbxzbuw4zCxt6DBqD6zvtVD73ecBD7t++wLCf/n5juWjr+Ky9Y136jviD/ZtncXj7AsytHejYbwz1mr7+nena2ufSdNlN2w8kOSkBn3W/EvcikvIVq/PJqKWUs6n02rmLgqHI9RnyoqDp8fKR9UKIokmhULDuuG4204+apa3w15/Qvfz6eqTl5nu14J75XpS8W7c0AE9G9NJyJAXPYX7anZu62O7S21zskY1ajqRwlPHsDcCha7rX7lrVSWtzOl0vj2/RciSFo0yznoBu18vD12O1HEnBa1k77Zmrcb5F76B6QSj9btrdDPEHVmo5koJXqk3aRTW6vL7UxTYHGe1uZ4nqWo6k4HVJShtyWRfrJWTUzebdDms5koJ37N+0x075D++p5UgKXsUFafteuting4x+nS72ydP747q4n5K+j6LrfVZd3tbtv1JEHvVQgNrWKwnA7osF/8jPoqBT/bThv3X5+Kwu7oN91EwPvSL0iI631bnbodoOIUcNq+f8LPjiSmeHHBdCCCGEEEIIIYQQQgghhBBCCFG86eyQ40IIIYQQQgghhBBCCCGEEEIIUdAUCrlL/k2SO7SFEEIIIYQQQgghhBBCCCGEEEIUSXJCWwghhBBCCCGEEEIIIYQQQgghRJEkQ44LIYQQQgghhBBCCCGEEEIIIYSGFMiQ42+S3KEthBBCCCGEEEIIIYQQQgghhBCiSJIT2kIIIYQQQgghhBBCCCGEEEIIIYokPUCh7SCEEDlTKKSJCiGEEEIIIYQQQgghhBAijZ6eDHetbadvRmg7hBy9U9Nc2yEUOLlDWwghhBBCCCGEEEIIIYQQQgghRJFkqO0AhBB5W3tMN+/S7tc87Sqydcd1L7+PmqXl5jegi5YjKRxOK3cCuv3bSW7Fjy7nl57b+hO6l1tfD9393UDqZXEl9bL4ehty08U2B7rd7tJ/u50lqms5ksLRJek2oNu/neRW/Ohyn1z648WXLucnuRVfupzf25CbEG8TOaEthBBCCCGEEEIIIYQQQgghhBAaStV2AG8ZGXJcCCGEEEIIIYQQQgghhBBCCCFEkSQntIUQQgghhBBCCCGEEEIIIYQQQhRJMuS4EEIIIYQQQgghhBBCCCGEEEJoSKGQZ5m/SXKHthBCCCGEEEIIIYQQQgghhBBCiCJJTmi/AQMHDiQ8PFzbYRR7ixYtIjQ0FIVCgaurK76+vsyePVvbYamQ31oIIYQQQgghhBBCCCGEEEKIgiNDjqvh4ODAxIkT6dSpE1ZWVgQGBuLt7c3kyZMJCwvTdngqfH19uXTpEiNHjgTgwYMHzJkzh7lz52olngcPHlClShUAYmNjuX//Pn/88Qd///33a31ux44dGTRoEK1ateL+/fuEhITQo0cPkpKSVJatSe6ZY4yLi+PRo0csWbKE33//PV8xqVvehg0b2LVrV74+pyApFAoO75jP+cMbiY+Nwt6xHp37j8fG3iXX+W6c88HXex7hwY+xsK5E6x7fULNBO5UyZw+u5YTPEqIjgrGxd6ZD35+oXK2h8n3vJT9y+YS3yjz2jq4MGbuhQPM7tF01vy4fa5bfwW0Z+bXp8Q013VXzO3NwLSf2ZOTX8aOM/FKSkzi4bS53rxwmPPgJJUsb41jLg7YffoupRfkCyy8vpm26YN65BwZm5Uh6+piQNX8Tf+d6juWNm7bCvEtPSpS3IzUultgr5wldv4TUmOg3FjNo73cDuHF+L+cPbSDg0XXiYiLwmriNCpVq6kR+b6Je6lJu2qyHmiz73xXjuX/jJNERzzEqWYaKzvVp2+s7rCs4vlK+Zw6u5fjuJcREBGNt70ynfqoxZfXw1hn2rP+V4Kf3MLGwoVmnITR6t6/a7yLs+WPK2WT/Ls4cXMc533VEhDwFwNremVbdv8Slnucr5ZATbf6Wvt5/cO3MLqLCnmFgWIIKlWvTpsc3ODi5FrtcpF7qRr18U/soutTu3qbcdLnNge63u1dRrnlDHEcNxqxBHUrZ2XCu53CCdhzQakxZ5dUusnp4+ww+63/l+dN7mJjnXi9z+k0f3j7LiT1LCHh4nZjIYPqMmE/NBm0LJT9drpe63q/LS3Htj4PUy+Kam67np43twdGdi7h5fh8hgfcxNCpFRef6tPtwFFav2L95G3MDqZeZFbf9FFHwFMiQ42+S3KGdRdWqVTl37hzVqlXjo48+wtnZmaFDh9KmTRtOnjyJhYVFjvOWKFGi0OIyNCw+1x6MGzcOW1tb6tWrh7e3N4sWLaJ3795qy2r6nTk5OREYGMjJkycJCgoiJSWF8PBwYmJiXivGmjVr8vvvv/PLL7/wxRdfvNJnZRYfH09wcPBrf86rOr77H07uXU7n/uP4/OdNGJtas2rmZyTE5fw9+d+7yOZF31KvaXeGTtxOvabd2bxwJE/uX1aWuXZmF3vWT6NFl6F4TdhGJZeGrJnzBZGhASqf5VynBaNmHVW++n+9qHDy+3gcn4/bhLGZNSt/zzu/TQu/xdWjO0MnbcfVozubFo7kiV+W/NZNo0XXoQydmJbf6tlfEPEyv6TEeAIf3cCz23C8Jmyhz4g/CA16yLp5wws0v9yUfacFVv0/J3zHBp6M/4q4O9eo8N0kDC2t1ZYvVa0WNl7fEn14L/5jhhM0fxqlHF2w/uyrNxZzOm39bgBJCXFUdGlA2w9H6Vx+b6Je6lJu2qyHmiy7QuXavPfZL3w5dScfj/oHBQpWzRxMampKvnO9dnoXe9ZOw7PrUIZO2kblag1ZPUs1pszCg5+werYXlas1ZOikbbTo4sXuNVO5cc5H9bv4K21bMWxy2rZi41+q34VZufK0/XAUX0zYzBcTNlO1ZhPWzfuS50/v5juH3Gjzt7S0rULn/uMYNnkHn41Zg7mVPatmDeZF1Ktd8Cj1UuplUVxfFqX8oODb3duSm663OdD9dvcqDMqWIerKba5/PVnboailSbvILDz4CWtme1HJpSFDJ26jRVcvdq9VUy/z+E2TEuIoX7EGnT8eV+g56nK91PV+XW6Kc38cpF4W19x0OT9tbQ8e3j5Lo9b9GPLzBgaMWkpqSjKrZg0hMSG2QPLS9dzSSb1MUxz3U4Qo7uSEdhZ//vkniYmJtG/fniNHjuDv78+ePXto27Yt9vb2TJ06VVn2wYMHjB07lmXLlhEREcHixYuBtGGnHz16xIsXL9i6dSuWlpbZltO1a1fOnTtHXFwcfn5+jB8/HgMDA+X7CoUCLy8vvL29iYmJ4eeff84zdl9fX6pUqcKcOXNQKBQoFArle02bNuXw4cPExsby+PFj5s6dS5kyZbLlsmLFCqKjo3n48CHdu3fHysoKb29voqOjuXLlCu7u7nnGER0dTVBQEH5+fowbN447d+7w/vvvK2P8448/mDlzJsHBwezbtw8AT09PTp8+TXx8PAEBAUybNk35fSxbtoz58+dTuXJlFAoFDx48UH5W+pDjueWeW4zpd2dfuXKF9u3bK993dHTE29ubZ8+eER0dzZkzZ2jTpk2e37W6IceHDh3KvXv3SEhI4NatW3z88cd5foevQqFQcHr/Slp0GUpN9/bYOFTj/cG/kpQYz9XT/+U43+n9K3Gq5UGLLl5YVXCkRRcvqtZswul9K5RlTu1dTv0WPWng2QtrOyc6fvQTZuVsOXtoncpnGRgaYWxmrXyVNjYv0PxO7VuJZ9eh1HJvT3mHanygQX6n9mXkZ50pv1OZ8jvps5wGLXri/jK/Tv3S8jvnm5ZfqTImDPhuKXUad8KqgiMVndzo3P9nAh9dz3GnpqCZd/yAqMN7iT68l6QAf0LXLCY5LATT1p3Vli/pVIPk4OdE7vuX5JAg4u/cINJ3D6Wq5n61ZEHT5u8G4OrxHq26f4ljraY6l19h10tdyk2buWi67Iat+lCleiMsrBywq1yb1h98Q1RYoPIOt/w4sXc59T174t4yIybTcracPbhObfmzvusxs6xAp34/YW3nhHvLXtRv0YPje5Zm5Ll3JY61PfDsmvZdeHb1wrFmE05m+i6qu7WmmmtLrGyrYmVblbY9R2JUqgz+mTpqr0vb65R6TbrhVNuDcjYVsbF3oUPfH0mIiyHoye1ilYvUS92pl29iH0WX2t3blJsutznQ/Xb3qoJ9jnBnwhyeee/Tahw50aRdZHbuUJZ66ZlWL0/4ZNRLTX5Tl3qetOnxDbXc26tbTIHR5Xqp7fVlYffr8lJc++Mg9bK45qbr+Wlre/DJt/9Qv3kPbOxdsK1Ug/c/m0ZkaAABD3MebUFyUyX1MkNx208RQhfICe1MLCws6NChAwsWLCA+Pl7lvaCgINasWUOfPn1Upo8ePZpr167h7u7OlClTaNy4MUuXLmXBggW4ubnh6+ub7WR0+/btWb16NfPmzaNWrVp4eXkxaNAgxo4dq1Ju0qRJbN++nbp167J06VLy0qNHD/z9/ZV3H9va2gJQp04dfHx82Lp1K/Xq1aNPnz40b96c+fPnq8w/cuRIjh8/Tv369dm5cyerVq1i5cqVrF69mgYNGnDv3j1Wrlyp8feZLj4+XuVO7IEDB5KcnEyzZs3w8vLCzs6OXbt2cfbsWVxdXRk2bBiDBw9Wfm9ff/0148aNw9/fH1tbWxo1aqRx7ppo2bIlNWvWVBm+3NjYmF27dtG2bVvq16+Pj48P//77LxUrVszX8t5////Zu++oKK63geNfqtI7qIBKU8SCikbFHnuNNUZN1FiCMXkTNVFjjP2XWBKNmsQSjT32XlBs2HvvBRABRaX3zr5/rCws7AKahYX1fs7Zo8zemb3P7jMz906504vFixezYMEC6tSpw4oVK1izZg1t2rQpdv2KKzYyjMS4CFxqN5dN09XTp3rNxoQF3lA6X2jgTZzzzAPgUrsFoQE3AcjKTOfFs3tyywVw9mhOWID8coMfXebXsd788WMn9q2dSlJ81H+MKldMhPL4QgMKj8+ljnzdXeu0IDTwJgCZSuJzqd280OWmJieAlhYVDU3fIZq3pKNLhequpNyVr0/ynetUdFM8zFrqkwfoWlpjWE86LI6OqTnGjZuTdOtKiVc3r7L2u6laWYtPlXmpSbGpM5Z3+ez0tGRunt2FubUDppbF35/l1Ck8+B6uiuqkZF8QFnizQAyudVrwIvgeWZkZSsu41MndV+SXnZ3FnUsHSU9LxtGl/lvFUJiylJeZmelcO7WVCgYm2Dm6l6tYRF5qbl6C6tsoZSm+/7re5aepsWn6Ogdl67eDUu4blFPv8t2GKsrL2vJ5WdRvWpo0OS/LWmylqhz3x6Hs/XaanJea3AYD1cVXlvYHqSnSRwAYGJm9bRgKaXJsOURe5ipv7RShZEgkWmX2pYnKzzjWpcDNzQ1tbW0ePHig8P0HDx5gaWmJjY2NbFjpEydOsGDBAlmZWbNm4efnx7x58wB48uQJ3t7edO7cWVZmypQpzJ07V3Zy+OnTp0ydOpX58+cza1bu0GCbNm1izZo1xa5/TEwMWVlZsruPc0yYMIFNmzbJnvUcEBDAN998w6lTp/jyyy9JS0sDwNfXV/as61mzZjFmzBiuXLnCjh07AJg3bx4XL17Ezs5ObvnK6Ojo8Omnn1KvXj2WLVsmmx4QEMCkSZNkf//vf/8jNDSUr7/+GoBHjx5RpUoV5s2bx6xZs4iPjychIYGsrCyln6ssdmXmzZvH//73P/T19dHX1yclJYUlS5bI3r99+za3b9+W/T116lR69+5Nz549+euvv4r9ed9//z1r166Vxf/777/TtGlTvv/+e06ePFmgvL6+PhUqVCiy/ookxklz0thUfkQAI1OrAkODy88XWWAeY1MrEuOly0tOiEGSnVWwjJkVgXcjZX+71m2FR6POmFtVISYyDP89S1j36zC+mLYTXT39d4pJrp5v6mP0DvEpmifn+8qJz8hMUZlIFMnISOPYjgXUbdKdigbGbx3L29IxMUVLR4fMuFi56VnxseiYKX4MQlrAA14t/xW7ryahpaePlq4uSdcvErlheYnXN6+y9LuVhLIUn6rzUpNiU2csb/PZl09s4uj238hIS8a6sjNDvl+Nru7bbT+TE2LIzs4q8HnGZlYk3lX8/SbGRWBs1qJA/bKzMklOjMHE3Fb5viJO/jEbr0IfserngWRmpKFfwZBPvv4TW3vXt4qhMGUhLx/d9GfHiu/ISE/BxMyGId+vxshE+SNpymIsIi81Ly9zlEQbpSzEp6r1rkAdNTQ2TV/noGz8djlKu29QXr3Ld5sYF4GRab68NCuYl4X9pqVJk/OyLMVW2spzfxzK1m+nyXmpqW2wHKqMr6zsDyQSCX5b51LVzQs7hxr/IaJcmhybrL4iL2XKWztFEDSBOKH9FrS0pFc15B3O+urVq3JlatWqxe7du+WmXbhwQe6EtpeXF40bN5a7I1tHRwcDAwMMDAxISUlRuOx35eXlhaurK4MHD5aLRUdHBycnJx4+fAggdwI35yTtnTt3CkyztbUt9CRuzsniChUqkJ6ezvz581mxIvdZyoq+swsXLshNO3fuHCYmJjg4OBAaGvq2IRfp119/Ze3atdjY2PDzzz9z4sQJuToYGhoyffp0unfvTpUqVdDV1cXAwICqVau+1efUqlVLdpFAjnPnzvHtt98qLD958mRmzJhRrGXfvrifA+uny/4e9O2bjpGW/NU3EknBaQXkn0c6MX+hQpdb54PcobZsHWpQpXodFk1sx5PbJ6n1DkOm3L6wn/154hs8dvmbqiqIpYj4tPLHIpFOLbKMguVmZWawY/l4JBIJ3T6bXuD9kpV/KH2tNz9EQXpVHLH+1IeYvZtJvnMdHXNLrAYMx2bY10T8s7jEalhWfzdVKavxqSIvNSm2shhLcT47Z+jZhNgIzvutZvuysQz/cTN6em9/oVP+z5NIFNRTfg5lC1K6TOlc8tOsKjsxeuZuUpPjuX/1CLtX/cDnP2x45xMZZfG3dKrVhNEzdpOcGMP1U9vZvmwsI3/aVuAkT35lMRaRl5qTl6C6NkpZjO9d17v8NDk2hXXUkHUOyuZvB+ruG5RPb9t+L/AbS2RvFL7MQnNdNTQ5L8tqbOpV9vvjUHZ/O03OS01ug0HJ7evUvT/w3TibV6GPGD55U7Hq+zY0KTaRl4o/X1a+DLdTBEETiRPaeQQEBJCdnY2Hhwd79+4t8L67uzvR0dFERuZelZOUlCRXRuHGPB9tbW2mT5/Orl27CryXd6jz/Mt+V9ra2qxYsULuDuQcISEhsv/nHXJb0bScE/na2oWPVJ9zsjg5OZnw8PAC7yv6zvI/81rRxQOqFBkZSWBgIIGBgfTt25eAgAAuXrzI8ePHZTF06tSJ77//noCAAFJSUtixYwf6+m9/p7Gi2JTFNWfOHBYuXCg3LT4+XmHZmp5tcZheT/Z3ZmY6IL3izcTcVjY9OSGq0ANixmbWBa40S4qPwtjUGgBDEwu0tHVIjFdURvlyTcxtMbeqQtSrZ0rLFKZm/bbYO+fGl6UkvqLqYWxmXbDuCVEYm+WLL/93oOB7y8rMYPuyccRGhDF04tpSuwMjKyEeSVYWumYWpOWZrmNqRlZ8rMJ5LHp8TOqTB8T6vtnOhAYTmZaK/U+/Er1jPVlxMSVS17L4u6lSWYxPVXmpSbGVpViMTW2K/dkVDU2oaGiClV11HFw8mfd1Ex5eO0rdpt2LFXdOnbQV1Sk+qsCVxrlx2igsr62ji6GR+Zsy1iTkK5MYH4XRm+8ih66uPlZ21QCwd6rLi+C7XDy6np7DZvEuytJvmUO/giFWdtWwsquGo0t9lvzQiRtndtCym0+5iUXkpeblpSrbKGUxvndd796n2PLStHUOyuZvp66+QXn1Lu334uZlYb9pSdLkvCyLsalLeeqPQ9n87TQ5LzW9DVYS+7qysD/w/Xc2j26e4PMfNmL2lo9TKowmxibysvy2U4TSIREXJ5Qq8QztPKKjozl69ChjxoyhYsWKcu/Z2dkxePBgtm7dWugy7t+/T9OmTeWm5f/7+vXr1KxZU3ZCNe/rv57ATU9PR0dHp8Dn1a5dW+HnKTqJ/V/lnCxWdDJbkfv37+Pt7S03zdvbm/j4eJ4/f17sz1UUe3HExsbyxx9/8Ntvv8mmtWzZkrVr17Jnzx7u3r3Ly5cvqV69+lt/3oMHD2jRQn7oEW9vb6XD2qenp5OQkCD3UqaCgTGWdtVkL5sqrhib2RB0/7ysTFZmOsGPruDg0kDpchxd6svNAxB07xyOrvUB0NHVp0q12gTdy1fm/nkcXJUvNzkxhrjocEzMbZSWKUwFA2PZwT2rPPEF5qlr5pv4HAuph6NLfQLz1T3w7jnZc/x038QXmO87CLx3Xm65OY2lqNfPGPL9GgyNLd4prneSlUlacAAGdeTjNKzTgNQninNJS78CSLLlpkmy3/xdgle6l7XfTdXKWnyqzEtNiq0sxWJh4/BOnw0gQSK7WKm4dHX1qVy9doF6B90/j6OSfYGDgv1AwL1zVKleGx1dvdwy+b+LPPsKpTFIJLIO77soS7+lMhIkZGYUHWNZikXkpWblparbKGUtPkWKu97lp8mx5aVp6xyUvd9OrX2Dcupd1guFv1e+vCzqNy1JmpyXZS02tSpH/XEoe7+dJuelprfBSmpfp879gUQi4eDGWTy4dpShE9diYeOggohyaWJsIi/LbztFEDSROKGdz9dff02FChXw8/OjZcuWODg40KlTJ44ePcrz58/lhglXZMmSJXTu3JkJEybg5ubGV199JTfcOEifTz1kyBCmT5+Oh4cH7u7ufPzxx8yePfs/1z84OJhWrVpRpUoVrKykVw/NmzePZs2a8eeff+Lp6Ymrqys9evRQeMe2OixduhRHR0f++OMPatasSc+ePZk5cyYLFy58qxP8imIvrr/++ouaNWvSt29fQHq3fp8+ffD09KRevXps2rSpwJ3pxfm8X3/9lWHDhuHj44Orqyvjxo2jT58+cifPVUVLS4sm7Ydw5uAKHlw/yuuwx+xZPRk9/YrUbZJ7F9XuVZM4tjP3ue9N2n9G4L1znPVdSWR4EGd9VxL04AJNOgyVlWnacRjXz+zgxpmdRLwI5PCWOcRFh9Oo9ScApKcmcWTrPEIDbhAbGUbww0tsXvIlhiYWuDdor7L4mnYYwpkDK3hw7Sivwh6z55+C8e1aOYljO/LE1yE3vog88TXNE1+zTsO4fnoH13Pi2/wmvjbS+LKyMtm29FteBN+l76hfyZZkkRAXQUJcxFsf1H9XsYd3Y9q6IyatOqBXxRGrQaPQtbIh/oQvAJb9h2L7xXhZ+eQblzHy8sb0w67o2lSiolstrD/1ITXwEVmx0aVSZ1Dv7waQnBhLeMgDIl4EAhD18inhIQ9IUNGzajQ5LzUpNnXGUpzPjn4dypmDK3gRfJfYqBeEBtxg+7Jx6OlVwK1e67eO17vjmzqdltbp0OY5xEWF07ittE5Hty9g18pJsvKN235CbOQLDm+eQ8SLQK6f3smN0ztp3nm4rEzTN9/FmYPS7+LMwZUE3b9AszzfxbEdC3n2+CoxkWG8Cn3EsZ2/E/zwMvWa9XjrGJRR52+ZnpbMsZ0LCQ28SWzkc148u8feNT8RH/2S2o3l23plPRaRl5qTl6XRRtGk9e59ik2T1znQ/PXuXekYGWLq6Y6ppzsAhk4OmHq6U9GxslrrlaOo7/bYDvm8bNTmE+KiXnB4y5u8PLOT62d24t0pNy+L85umpSYRHvKA8BDpycfYyDDCQx4QW8izPt+FJuelpvfrilJe++Mg8rK8xqbp8alrf3Bw4yxuX9hPX5/f0K9oJIspIz13xFQRW+FEXpbfdoogaAIx5Hg+AQEBNGrUiBkzZrB161asrKx4+fIle/bsYebMmcTEFD4s0KVLlxg5ciQzZ85kxowZHDt2jP/9739MnTpVVubIkSN0796dadOmMXHiRDIyMnj48CGrVq36z/WfNm0aK1asIDAwkIoVK6KlpcWdO3do3bo1P//8M2fOnEFLS4vAwMAi7zYvLS9evKBr1678+uuv3Lp1i+joaP755x/+97//vdVyFMVeXJGRkWzYsIEZM2awa9cuxo0bx+rVqzl//jyRkZHMmzcPU1PTt/68vXv38u233zJhwgSWLFnC06dP+fzzzzl16tRbxVZczbuMJDMjFd+Ns0hJisPBuR6fjf+HCnmGXomLfiFXV0fXhvTzWcCJ3Yvx37MES1tH+vksxMHZU1amzgddSUmM5dT+v0iMi8DW3o3B367A3NoeAC1tHV4/f8ytC3tJTU7AxMyG6u4f0G/073KfrYr4MtJTOZg3vu8UxKedG19V14b0G72AE7sWc2L3m/hGL8TBRT6+5MRYTu3LE9/Y3PjiY17y6OYJAJbP6CVXp6ET1+Hk3kRlMSqTdOkMkcamWHw0EF1zS9LDnhG+YDqZUdIOvI65JbpWuXfDJ5w9hpaBAWbtu2M1cATZyUmk3L9N1LY1JV7X/NT1uwE8unmCvat/lP29Y7n0IEPrnl/Rttf/lev4SiMvNSk2deZhUZ+tq6fPs8fXuHh0PSlJ8RibWlGtZiNG/Lj5nYZarNOkK8lJ0jol5NRpXG6dEuMiiMvTMbKwceDTcSs4vHkul09swsTcli6Dp+DRqFPud+GW+134716Cha0j/fN9F4nxUez6eyIJcRFUNDDBzrEmn323Epfazd86hsKo67fU0tYhMvwpt859Q3JiDAZG5tg71WX45H+xtXcrV7EU57NFXr4dTdpelqX4SmK9e19i0/R1DjR/vXsXZl51aHZ8g+xvj9+k7eDQ9bu4PWKyuqolU9R3mxAXQVy0fF4OfpOXV3LyclC+vCzGb/oi+C7r5uceOPbbMhcAz+a96D1irkpj1OS81PR+XWHKc38cRF6W19g0OT517Q+u+m8GYO28IXL1+Wj4LzRo0ec/xfQ+xJZD5KVUeWynCKqXXTJPzBWU0CL3UfWCIJRBEomETWc1czUd1ELasNl8TvPiG9hcGlvgkG5qrknJcFl/ENDs307EVv5ocnw5sW05r3mxfeKtub8biLwsr0Rell/vQ2yauM6BZq93Ob/dQb2aaq5JyeiW8QjQ7N9OxFb+aHKfXPTHyy9Njk/EVn5pcnyaHtvb3NAnlIxTdxPVXQWlWtdR3Y2GZYUYclwQBEEQBEEQBEEQBEEQBEEQBEEQBEEok8SQ44IgCIIgCIIgCIIgCIIgCIIgCIIgCMUkQdwlX5rEHdqCIAiCIAiCIAiCIAiCIAiCIAiCIAhCmSROaAuCIAiCIAiCIAiCIAiCIAiCIAiCIAhlkhhyXBAEQRAEQRAEQRAEQRAEQRAEQRAEoZgkEjHkeGkSd2gLgiAIgiAIgiAIgiAIgiAIgiAIgiAIZZI4oS0IgiAIgiAIgiAIgiAIgiAIgiAIgiCUSVqARN2VEARBOYlErKKCIAiCIAiCIAiCIAiCIAiCIEhpaYnhrtXtxO1kdVdBqQ/rGaq7Cion7tAWBEEQBEEQBEEQBEEQBEEQBEEQBEEQyiRddVdAEISibT6nmXdpD2wuvYpME+PLiW37xWw116Rk9G8qvR7K/06Kmmuiem3rGgCanZfDZrxSc01KxtoZdgAs3q95v923PaS/3aazmhfboBbS2EbPi1FzTUrG8kkWgGbn5R8HNS+2/+smjW3I1HA116RkrJ9dGQDf6xlqronqdW2oB2j2fvxPX82LDeDrrtL4WvQ4peaaqN7Z/a0BzcxLyM3Ng3o11VwT1euW8QiAk3c1r9/Tpo6036OJfTrI7ddpYp88pz+uie2UnDaKpvdZNXlf99chNVekBHzVRfrv2pNqrUaJGdZG+q8mtlPeh2PPgvA+ESe0BUEQBEEQBEEQBEEQBEEQBEEQBEEQiikbcWFBaRJDjguCIAiCIAiCIAiCIAiCIAiCIAiCIAhlkjihLQiCIAiCIAiCIAiCIAiCIAiCIAiCIJRJYshxQRAEQRAEQRAEQRAEQRAEQRAEQRCEYpJIxJDjpUncoS0IgiAIgiAIgiAIgiAIgiAIgiAIgiCUSeKEtiAIgiAIgiAIgiAIgiAIgiAIgiAIglAmiRPa5cTQoUOJiYlRdzWEPKZPn86NGzfUXQ1BEARBEARBEARBEARBEARBEAShFEkkZfelicQztEuIg4MDM2bMoEuXLlhbWxMeHs6ePXuYNWsW0dHR6q6eHH9/f27evMm4ceMAePr0KYsWLWLx4sVqq1OzZs346aefaNasGQYGBjx58oS1a9eyaNEisrOzS70+EomEXr16sXfvXtm03377jT/++EP295o1azA3N6d3796lWq+Te//k2qltpCbHY+9cj26fTsPW3q3Q+e5f9ePE7iXERIRgYVOVdn3GUsurg1yZyyc2cf7wPyTERmBr70rngT9SrUajt/rshLgIjm77lcB750lPTcKqkhMtu39B7Uady128/nv+4O5lX+KjX6Kjq0flarVp12csDi6e7xRLUS4d38QZ39UkxkVgW8WVroMnU71mI6Xlnz68zKFN83j9IgATc1tadh3BBx9+Inv/yslt3Dy3j1dhTwCoUt2Djv3G4eBSr0Tq/7ZOHt7K0X3riIuJpIqjC/2HTcDNo6HCsnExEexYt4CQoAe8Dg+hbdeBfPz5xFKpZ1lf566e3MqdSwcIf3af9NQkJv15GQNDU9V+CQr0amNEay8DjCpqE/Q8g/UH43kRkaW0vFetCnRvaYSdpQ462lq8is7k8Plkzt9OLfG6FkYikXDlyJ/cv7SNtOR47KrWo1WfaVhWKvz3Dbztx+XDS4iLCsHMqipNuozFuW7u75uemshlvyUE3TlGSmIU1va1aPHRFOyq1i3RWE7tk8+XroOLl6v+e3Jz9cM+Y6nVUD5Xr5zYxHm/3Fzt9Il8rgJEvAjk2I7fePb4CpLsbGzs3eg/+nfMrKqoPFZlujevSAvPChhW1CI4PJPNR5MJj1TehqhfQ48uTStiY6GNjrYWr2OyOHYljUv30kutzopoUl7mJ5FIuOz3J/cuvomtWj1a952GVRGxBdzy49LhJcRFhmBmXZWmXcbiUk8+tkuHlhB09xjJCVHYONSiZa/SjU2Z3m2NadPIECMDbQLD0ll/IJ7nrzOVlm/kUZEerYywtdRFVwdeRmVx6FwS52+llGKtCzp7ZAv+B9YQHxtBJQdXeg2ZhIu7l9LyAfevsHfjr7wMC8DUwpYPu39O8w4DZO//OWsYgQ+uFpivVv2WfDFpWYnEkKMk23hF7f/99/zBqX1/yc1jZGrNhEVn//NnKyNb7y5sIzUlnkpV36x3lYte7y4eyl3vmnWVX++yszK55Pcnj6/tJykhEiMTG2p90JvGHb5ES1u919EPH1iNnp0qY2Ksy/3HCSxc/oSnIclKy3dpZ8eUse4Fpn/Y5zTpGaVzZKiodmF+wY8u47dlLq+fS/sCzbuMpHHbT+TKFJWPwY+ucP7wP7wIvkdiXAQDvv6TWg3bl1iMb8uyRSOcvxuBWcM6VKxiy9W+Y3i177i6q/XWTh7eypG9uf2ejz8vvN+zfa18v2fA8NLp97yr8tKvK473rU8OmtNOUURT+qyKlMf9nCISiYRLh//k3oWtb9oonrTpV7w2ygXfxbI2ine3cQXbKIf/4FFOG8XUhlqNe/NBxzGl2kaRSCScPfAnN89sJTU5nipOnnQcOA2bKoXH9/C6H6f3LSY2IgRzm6q0/mgcNRvkxnf91Caun9pMXNRzAKwru9Gi+xhc6rQukTjU0UY5c3AFD64dJTI8CF39iji6NqBDv++wruys8vjUddwvKzODE7sX8+T2KWIiwqhgYIyzhzft+43H1MJO5XEKQnkl7tAuAU5OTly9epUaNWowcOBAXF1dGT16NO3atePChQtYWFgonVdPT6/E6qWrWz6uX+jVqxenTp0iLCyMtm3b4u7uzuLFi5kyZQpbtmxRd/VkkpKS1H5xwrlDq7hwZC1dP53KqKnbMTazYf1vw0lLSVQ6T2jADbYvH4+nd09Gz9yLp3dPti8fR1jgLVmZu5d9Obx5Di27j2b0jN1UdWvExt+/IDbqxVt99u6Vk4h8+ZSB3yzly1n7qOXVgR3LxhP+7H65i9eqUnW6Dp7Kl7P2MXzyv5hb27Nh4QiS4lWfA3cu+eL771za9PBhzKxdVKvpxfoFPnL1ySs6Ioz1C0ZTraYXY2btonX3Lzi48RfuXTkiK/P04RXqNe3KiB/W4jN1M+ZWVVj720jio1+pvP5v6+o5P7av/ZUufUYy5dctuNZqwJ+/fEV0RLjC8hkZ6RibWtClz0gcqtUo1bqW9XUuIz0V1zotadnNp2S+AAW6NjekUzNDNvomMHNlFHGJ2UwYYkFFfS2l8ySlZLP/dBKzV0Xz07IoztxIYUQvU+q46JdavRW54b+KW6fX0rL3VPp9ux1DUxv2/T2c9FTlv+/L4Bsc2TieGl49GfDdXmp49eTIhnG8epb7+/pvn0ro4/O0HziPT77fh2ON5uz/+3MS40pu/ZPly+CpjPppO8amNmxYUHSu7lgxnnrNejJ6xl7qNevJjuXjCAvKl6tb5tCy22h8pktz9d9FXxCXJ1ejX4ewZu4grCs7M3TCekbP3Eur7l+iq1ehxOLNr2OTCrRrXJEtx5KZuz6euCQJ335sQoVCUiw5RcKhC6nM35jA7DXxXLiTzpCuhng4qbf9pEl5md/1E6u4eWotrftM5eNx2zEysWHv8sJjCw++gd+G8dT06snA7/dS06snfuvH8TJPbCe2vYlt0DwGTpDGtnf55yTGqnef162lEZ29jdhwMJ7pyyOJS8xm4lDLQreXicnZ7DuVyOyVUUz5M5Iz15MZ1duMuq7q217euHCIPevn0qHXKL6fsx3nmg35e+5oYiIV77ejXoexcv4YnGs25Ps52+nw0Uh2r5vDrUtHZWU+H7+YmctOyl4T5+9BW1uH+k07lXg8JdXGK87+H8DG3o3vfj8je42Zte8/fW5Rrp9YxY2Ta2nVdyoDxkm3KcVZ7w6vH497o54MnLAX90Y9ObxOfr27dmIVd89voVWfqXz6w0Ga9/ie6/7/cOvMxhKNpyiD+zoyoJcDC1cEMHL8daJi0vl9Vj0MDHQKnS8xKZOen52Xe5XWQf7itAvziokI49/ffajq1ojRM3bTsrsPhzb9zP2rfrIyxcnHjLQU7Bzd6frp1BKP8V3oGBkSf/sR976dpe6qvLMr5/zYtuZXuvYdyU+/Sfs9f/xceL/HxNSCLn1H4lC9dPs976I89euK8r71yUFz2imKaFKfNb/yuJ9T5trxldw4uYbWfafxyfgdGJpas2fZ54W3UZ7e4NC6cbg3+ohBE/fi3ugjDq0dy8vgW3LLvXN+C637TuOzH3xp3mPCmzbKhtIIS+ai30ouH1tDx0+mMWzyDoxMrdmy6HPSCokvLPAGe1aOo06TjxgxdS91mnzEnr/H8vxpbnwm5pVo0/t7hv24k2E/7qS6e1N2LP2KiBdPVB6DutoowY+u0PjDQYz8aStDvltNdlYmGxaOJD1N+YUb70pdx/0y0lMJf3afVj3G4DN9JwO+/oOoV8FsXjJG5TEKQnkmTmiXgL/++ov09HQ6duzI6dOnCQ0N5fDhw7Rv3x57e3t+/vlnWdmnT58yZcoU1qxZQ2xsLCtXrgSkQ4w/e/aMpKQkdu3ahZWVVYHP6d69O1evXiUlJYXAwECmTZuGjk5ug0UikeDj48OePXtITEzkp59+KrLu/v7+VK9enUWLFiGRSJDkGZugWbNmnDp1iuTkZEJCQli8eDGGhoYFYlm3bh0JCQkEBwfTs2dPrK2t2bNnDwkJCdy+fRsvL+V3bxgaGrJy5Ur27duHj48Pt27d4tmzZ/zzzz8MHTqU/v378/HHHwPQunVrJBIJZmZmsvk9PT2RSCRUq1YNAEtLSzZt2kRoaChJSUncvn2bTz6RvwrM39+fxYsXM2/ePKKioggPD2f69OlycQHs2bMHiUQi+zvvkOPTp09n2LBh9OrVS/a9tW7dmuPHj8vdxZ1Tp9TUVNq2bVvk71EYiUTCxaPradV9NB5eHbFzqEHvEXPJSE/lzqUDSue7eHQ9Lh7etOzmg01lZ1p288GpVlMuHl0nK3PBby0NW/bFq1V/bKq40GXQj5hZVuKq/+a3+uzQwJs0afcpDs71sLR1pHWPL6loaPJOJ7TVGS9AvaY9cKntjaWtI7b2bnT65AfSUhJ5FfborWMpyrnD6/Bq1YdGbfpjW8WFboOl9bl8XPEFHVdObMHcqjLdBv+IbRUXGrXpT8NWfTh7aLWszMejf6VJu0FUrlYLmyrO9Bo+C0l2NoH3L6i8/m/r2P4NNP+wNy3a96GygzMffz4RC6tKnDqyXWF5a1t7BgyfRNM2PahoaFxq9SwP61yzjkNp2e2LEhs5QJGOTQ3ZfzqJaw/SeP46i5W746igp0XTuhWVzvMwOIPrD9MIj8wiIiaLo5dSCH2VSY2qJXdRV1EkEgm3z6zHq91oXOp2xKpyDdp9MpfM9FSe3FD++946sx5HN2+82vlgYeuMVzsf7N2acuuM9PfNzEgl6M4RmnX7nioujTGzrsYHnf4PE0sH7p3frHS5/zWWS8fW07LbaGp5dcTWoQa9ipGrl47l5qp1nly9lCdXLx5ZS4OWfWn4Jlc7D5Tm6pWTubGc2LUIt7qt6dB/ApWreWBh40gNzzYYmRZsy5SUdo0qcuhCCjcfZ/AiMpt1B5PQ14MPaik/APU4NJObTzJ4GZVNZGw2J65Jc9rFQX0ntDUpLxXFduv0ehq1H41LPWls7QdJY3t8vZDYTq/HsYY3jdr7YGHnTKP2Pji4NeXW6TexpacSePsI3j2+x96lMeY21WjS+f8wtXTgbinFpkynZkbsO53I1fupPH+dyd87Y9HX06JZPQOl8zwMTufagzReRGTyOiaLIxeTpdvLauo7mHry4HqatO1D0w/7YWfvQu+hP2BuVYlzRxW3U84f24a5VSV6D/0BO3sXmn7Yjw/a9Mb/4FpZGSNjM0zNrWWvx3cuoFehIp5NOpZ4PMVp46UmJ7Bv7VTmf+vNL2O8WDt/KC9DHha63OLs/wG0tXUwMbORvYxMLUskTpCudzdPradxh9G4vlnvOgyS7h8KW+9unspd7yxz1rsaTbl5KjeWl8E3cK7TDqfabTC1dMC1fmeq1mzO69C7JRZPcfTvac/6bSGcvhDJ05Bkfv79IRUq6NCxtW2h80kkEB2bIfcqLcXpm+R19eQWzKwq02XQj9hUccGrVX8atOzDeb/cvkBx8tGtXiva9RmLh1fJr3fvIsLvNI+nL+LlnqNFFy6j8vd7Bgx/0+/xK6TfM2ISzdr0wKAU+z3vqrz064rjfeuTg+a0UxTRlD6rIuVxP6e4PhJunn7TRvF800YZPI+M9FQeXSusjbKOqjW8adzBB0s7Fxp3KNhGCQ++mdtGsXLArX5nqtZswatSbKNIJBKuHF+Pd5fR1GzYERv7GnQfJo3v/mXl8V09vg6nWt54d/HBqpIL3l18qObelCvH8+y/PT/EtW5rrOycsLJzonWvcehXMORF0E2Vx6GuNspn41fRoEUfbO3dqFTVnV7D5xAX9YIXwfdUGp86j/tVNDRhyPerqfNBF6wrO+PoUp+ug38i/Nk9pRcMCGWDBK0y+9JE4oS2illYWNCpUyeWLl1Kaqr8MDSvXr3i33//ZcCAAXLTJ0yYwN27d/Hy8mL27Nl88MEHrF69mqVLl1K/fn38/f0LnIzu2LEjGzduZMmSJXh4eODj48OwYcOYMmWKXLmZM2eyd+9e6taty+rVqylKnz59CA0NZerUqVSqVIlKlSoBUKdOHfz8/Ni1axf16tVjwIABtGjRgj///FNu/nHjxnHu3DkaNGjAwYMH2bBhA+vXr2fjxo00bNiQgIAA1q9fr/TzO3bsiLW1Nb/99luB9w4cOMCjR48YOHBgkXHkqFixIteuXaN79+7UqVOHv//+mw0bNvDBBx/IlRs6dChJSUk0adKEiRMnMm3aNNq3lw6v1rhxYwCGDRtGpUqVZH/n9dtvv7F161YOHTok+97Onz/PqlWrGDRoEPr6uY35wYMH8+LFC/z9/YsdhyIxEWEkxkXgUru5bJqunj7VazYmNED5s71DA2/iUqe53DTXOi0IDbwJQGZmOi+e3ZNbLoBL7eay5Rb3s6u6NeTuZV+SE2PJzs7mzqWDZGZmUN1d/vsv6/Hml5mZzrVTW6lgYIKdY8Fhmv6LzMx0XgTfw7VAnZsToqQ+IQE3C5R3q9Oc58H3yMpU3CnJSEslKysTA2Mzhe+XlsyMDEKCHlDLs5nc9FqeTQl6dEvJXOpRHta50mZjoYO5iQ53A3OHZM7Mkh7YcHUsfke/lpM+la10efRMfZ3o+OgwkhMicKyZ+x3r6OpTxaUxL4OVf8evnt2Umwegas0WvAy+CUiHN5NkZxW4O1lXrwLhT6+pLoA8YiOV50tYYOG56lwgD1sQGnATgCwluers0ZywN3koyc7mye2TWFaqzsaFI/h1rDer/vcxD68fU1F0RbM208bMWJsHT3OHR8zMgiehmTjbF//kdM1quthZ6hAQqnyYxZKmSXmZX05sVfPFZu/SmPBCYnsZfFNuHoCq7nliy5bGpqMrH5uOXgVelFJsisi2lwFpsmmZWfAoOB23tzgw6uGsT2VrHR4Gq2co/MzMDMKe3qdmPW+56TXreRP8WPF+O/jJrQLl3T2bExqkvJ1y6eQuGjTrQoWKhgrfLymK2ngSiYR/F/mQGB/J4LEr8Jm+k8rVPFj32zCSE2OVLquo/X+O6FfP+G1cSxZNbMf25eOJfh2q6rBk4qOUrHeujQl/+pbrXZ5tCkBlJy9CH18g5rX04t+I5w95EXSd6h6tVBvEW6hiVxFrywpcvhEjm5aRKeHm3VjquBf+SBYDAx12/NOEXWuaMm9aHdycS+dk27v0TUIDbxYo71q7BS/y9AWKm49CycnMyCAk8AEe9eX7PR6eTQksY/2ed1Ge+nVFed/65KA57RRFNKnPml953M8pEx8VRnJ8BFXdW8im6ea0UQrpG4QH35SbB6Cae0u5eao4exH6+GK+Nso1qtcqmSG5FYmNDCMpPgInjzzx6elTtUbhffTnQTfl5gFwrt2S50rmyc7O4v6Vg2SkJ2Pv3EA1lX+jLLVRUlMSADAwUu32sywdewbpRbVoaVGxFB4lKAjlRfkYg7occXNzQ1tbmwcPHih8/8GDB1haWmJjY0NERAQAJ06cYMGCBbIys2bNws/Pj3nz5gHw5MkTvL296dw597nDU6ZMYe7cubKTw0+fPmXq1KnMnz+fWbNyh+DatGkTa9asKXb9Y2JiyMrKIiEhgVevcoc9mjBhAps2bZI9VzsgIIBvvvmGU6dO8eWXX5KWJm30+vr68vfff8viGDNmDFeuXGHHjh0AzJs3j4sXL2JnZye3/Bw1atSQfU+KPHz4UFamOF68eCH33f7555907tyZ/v37c/nyZdn027dvy763gIAAvv76a9q1a8exY8eIjIwEIDY2VmGdQTr8eEpKChUqVJArs3PnTv744w8++ugjtm+XXpX8+eefs3btWoXL0dfXp0KF4g3JmhgvzZ/8d7wZmVrJDf1aYL64SIXzJMZJl5ecEIMkOwsjM0VlIt/qs/uP/p3ty8cx/5umaOvooqdfkU++/gNL26rFilGu3mqMN8ejm/7sWPEdGekpmJjZMOT71RiZKH+EwLtIToglOzsLYzNr+fqYFaxPjsS4yAL1NzazJjsrk+TEGEzMC16Ze2T7Akwt7HDx8C7wXmlKTIghOzsLUzP5u5FMzayIj1Ucr7qUh3WutJkZS6+Li0+Sfy5xfFI2VmaFD3FmUEGL37+zRldHC4kE1h+M516Q+g58JCdIv2NDY/nv2NDYioQY5d9xckIkBvnmMTC2ki1Pv6IxdtXqc/XoUixsnTEwsebJjYO8CrmNuXU1FUchlZNbxu+Qq/nnMTa1kuVfTq4WKGNmReBdaa4mJUSRnpbMOd+VtO39Le37fU/A3TNsXfp/DJ2wjuo13/6Cprdlaiy9CjU+OX9eSrA0K/xazor6MPcrc/R0IFsCm48k8yBYfSe0NSkvC9TxTV4ZmOSrp8m7xZYUnxtbper1uXJ0KRZ2zhiaWPPkeunGpkjO9jIuUT4v4xKzsTYvenu5eIIturpaZGfD+gNx3AtUz/YyKV663zbJt88yMbMiXkk7JSE2UmH57KxMEhNiMbOwkXvvWcAdwkOfMOCL0htWuLA23tOHl3j9/DETFp1HV096kWqnAZN4eOM496/60ajNAIXLLGr/D+Dg7EnvkXOxqlSdxLgoTh9Yxj+/DOSr/+3H0Fi1bUzI3abkX++Ks00xzD+PSe56B+DVbhTpqQlsnNsVbS0dsiVZNOs6lhoNu6swgrdjaSH9vaJj5deXmNh07GyV35UXEpbML4seEhSchKGhLv172rNsfn2G/d81wsJL9rmwb9M3yZEYF4GRqfzBbqM361hOX6A4+SiULGX9HhPzstfveRflqV9XlPetTw6a005RRJP6rPmVx/2cMrJ+T4H2hjUJ0f+9jZKWksCGOV3ytFHGUdOr9NooScqO6ZhYE1dIfInxivffeeMDeP38EevnfUJmRhr6FQzpM/ovrKu4qqj2UmWljSKRSPDbOpeqbl7YOaj2cRVl4dhzjoyMNI7tWEDdJt2paFC2RjERBHUSJ7RLmZaW9CBr3qG8r169KlemVq1a7N69W27ahQsX5E5oe3l50bhxY7k7snV0dDAwMMDAwICUlBSFy35XXl5euLq6MnjwYLlYdHR0cHJy4uFD6ZB7t2/flr2fc2L3zp07BabZ2toqPTmcs2xl09PTi9941NbW5ocffmDAgAHY29tToUIFKlSoQFJSkly5vPUGCA8Px9a28OF5iiM9PZ2NGzcyfPhwtm/fjqenJ56envTq1Uth+cmTJzNjxgyF792+sJ/963OHQh88djmg5LtS8v3J3s4/5IREOrXIMvmWW9Rnn9i9iNSkeIZ8vwZDYwse3jjGtqVjGT55I3YONQutY1mM16lWE0bP2E1yYgzXT21n+7KxjPxpW4GTOyqRPySJpNA489c/dxtTcJ4zB1dx+6IvI35Yh55+6T3TtjD5f1eJ9AdQT2XeKIs5+C6frUrN6lZkaA8T2d+//xsLSNNTrkrFWFZquoRpy6OpqK+Fh5M+AzuZEBGTxcPg0rni/fH1/Zzckfv7dhsh/X3zf58SBdPyU/S75J3WfuB8/Lf9yLrZrdHS1sHG3gO3Bt2JDHv7xy8ocvvifg7kydVB3yqJRUFOKai4/DzSifkLKV2uJFt6oKhmgw9p1nEYAJWq1iI04AbXTm4pkRPaH3joM6hT7l2cf+1IzK1X3lprkROQUmnp8POaeCroa+FeTZd+HxoQGZvN41K6S1uT8jK/R9f2c3J7bmzdRyrZpkoUbA/zKSq2DoPmc3zLj6ydmRtbjQbdiXheMrEp0qxeRT7vmXvHwIKN0jtnFOWlpIjETE2X8NPSSOn20rkCAzub8jo6S613PxXcZ0mUtt8Vlc9ppyia59LJXVR2dKOaa93/XtF88u/bPx33N9VqNCq0jRcefI/01GTmfdNUblmZ6anERIQSG/WCv37KPSDastsXtOo+WhpfEft/t3q5dy/bOYCja30WT+rIzXN78O70+X+O99G1/fhvy423x6jlCuulim3Kkxu+PLq2n06f/oZlJVcinz/kzJ5fMDK1pdYHvd89iLfQobUtE77KPbA5cdabfmj+VUy64il171EC9x4lyP6+8yCO1Yu86NujCov/DlRhjZUrTrtQrryCbembNwpfpoYORVimFfit1N/vUaWy2K97ZxrcJ9fkdoom9Vnz06T93MOr++TbKF+sABS3MYv+sQquewXbKPvo/NkCLCu5EvH8AWd2z8HYrOTaKHcv7ePwv7nxffz1m/gUbiOLomjbIj/Nys6J4T/tIS05nkc3jnBg7SQ+/W6jyk9qS2uj3jaK78bZvAp9xPDJm4pV38KUxeN+AFmZGexYPh6JREK3z6YXeF8oW7KLsxoLKiNOaKtYQEAA2dnZeHh4sHfv3gLvu7u7Ex0dLbvrFyhwcrWwg0E5tLW1mT59Ort27SrwXt6hzvMv+11pa2uzYsUKlixZUuC9kJAQ2f8zMgo26vJOy2nQa2srvkPqyZMngPSk/oULBZ8j5O7uzs2bNwHIfnPQPO/3pacnP1zQd999x7hx4xg7dix37twhKSmJRYsWyQ0BrqjeEolEaR3f1qpVq7h58yb29vYMHz6c48ePy31nec2ZM4eFCxfKTYuPjwegZv222DvXk03PypR2DhLjIuWu9k2Kjyr0BKuxmTWJ8fJXfyUlRMmuPjY0sUBLW6fAFWJJCbnLNTa1KfKzo1+HcPn4v4yZvR9bezcAKlV159nja1w+sYkeQ2YqrWNZizeHfgVDrOyqYWVXDUeX+iz5oRM3zuygZTefQmN5G4Ym5mhr65CY7yr2pPhopXEam1kXrH98FNo6uhgam8tNP+u7mlMH/ubziaupVLXwiwpKg7GJBdraOsTFRslNT4iLxtS89J63q0hZysHirHOl4cajNAKf524vdd9c0G5mrC13Nb+JkXaBq/vzk0jgdXQWACEvM6lso0u3FkY8DI5Veb0Vqe7RlgHjC/6+yQmRGJnmfscpiVEF7o7Ny9DEmuQE+d8uJTEKA+PcOzrMrKvSa8xGMtKSSU9LxMjUFr8N4zCxdFBJLDU92+IwPTeWTCW5mqxgu5aXsm2JsWm+XM2fz3ny0NDEAm0dXWwqy3ecrSu7EBpQMsM93wpI5+mL3BPOum9at2ZG2sQnZcmmmxhqFbgzIz8JEBErLRP2OotKVjp0alaRx6GJKq+3IpqUl/k51W6LXdU8sWW9iS2+YGz57x7NS1lshibysfX5Wj62w+vHYVpCsSly42EagWG59dTTlbZXzU3kt4+mRtrEv+X2soqNLj1aGfMwOLoEal44I1Ppfjv/3dgJ8dGYKNm+mJhbFyifGB+Nto4uRvmGWU1PS+HG+UN07v+Vaiv+Rv59u6mFHVB4G08iycbY3IZhEws+NqmioSkVDU0YPSP3YuScoQ+L2v8rol/BEDuHGkS/evaf4szhVLstdt8r2aaYvd02JSlfLMkJ8uvduf2/4tVuFDUadgPAukpNEmJecPX436V2Qvvs5SjuP869oFtfT9qfs7TQJyom98SKhZlegbvZCiORwIMnCThWKfkh8N+mb5LD2MxGeV/AyPxNmbfPR0G1cvo98WWw36MKZblf97behz65prZTQLP6rPlpwn4uh3OdD6lUzVP2d04bJSlfGyU5Xzs/P8V9g2i5ec7um49Xuy8KtlGOrSixNoqb54dUcSoYX2JcJMZm8n10I1Pl8RmbKmqDRReYR0dXH0tb6WhUlavXJTz4DldOrKfLp6ob8agstFF8/53No5sn+PyHjZhZVvoP0UiVpeN+uXXIYPuyccRGhDF04lpxd7Yg5COeoa1i0dHRHD16lDFjxlCxovzwLnZ2dgwePJitW7cWuoz79+/TtKn8HQD5/75+/To1a9YkMDCwwEuS/7LDt5Seno6OjvywO9evX6d27doKP0/RSex35efnR1RUFN99912B93r06EGNGjVkw3XnDNleuXJlWZn69evLzdOyZUv27t3Lv//+y+3btwkKCsLNze2t66XoOylumbt373L16lVGjRrFoEGDCn2WeXp6OgkJCXKvHBUMjGUH2qzsqmFTxRVjMxsC75+XlcnMTCf40RUcXZU/J8XRpT6B987LTQu8ew5Hl/qA9Bk1VarVllsuQOC987LlWtg4FPnZGenSUQK0tOQ3M9ra2rI7+ApTluJVRoKEzAzVXnWsq6tPleq1CchX54B756mqpD5VXesXLH/3HPbVa6Ojm3uRxxnff/Dft4yh3/2NvVMdldb7Xenq6VHVuRYPbstfwPLg9iWca3oqmat0lKUcLM46VxpS0yW8js6SvV5EZBGbkEVtl9yLhHR0wL26PgGhb7dv0CL3QEpp0K9ojJl1NdnLws4VQxMbwh7nfsdZmem8CLxCperKv2O7avUJfSz/24U+Okel6vULlNWrYIiRqS2pyXGEPjqLU50PVRJLBQNjLO2qyV45uRp0Xz6W4EdXcHApPFeD8uVh0L1zOLpKY9F5k6tB+fI56P55HN7koY6uPlWq1yHq5VO5MtGvgjGzqvJfwlQqLV16EjrnFR6ZTVxiNrWq5163qaMNbo66BD1/uzuttbRAr/Ddv0ppUl7mp1/RGHObarKX5ZvYQvPF9jzwCpULia1S9fqEPpKPLaQYsYU8LLnYFMm/vXz+OvPN9jL3LiwdHahZXZ8nIW+5vdTKvXCjtOnq6uHg5MHjfPvtx3cuUL2G4v12dTdPHt+RL//o9nkcneXbKQA3L/qRmZlOoxY9VFvxN/Lv2/X0FQ/HmbeNV7maB4lxkWjr6MjNa2VXDSMTC3R0dOWm5Zy4KGr/r0hmRjoR4YEYm9soLfM2Cqx3laTrXcijfOtdwBUqOxWx3j0ufL3LTE8p0O7X0tYGSdHtflVJScnieXiq7PU0JJnI6DQa17eQldHV1aJ+HXPuPox/q2W7ORsRFZ1WdMH/6F36Jgpz7d45quTpC7xLPgqqpaunR1WXWjy4VbDf46Lmfo8qlOV+3dt6H/rkmtpOAc3qs+anCfu5HArbKKY2hD46Jysja6MU0jeoXL0+IXnmAQh5eFZunsz01AI3j2lp6fzn4+eFqVDRGEvbarKXdWVXjExtCH4gH1/I48L76PbO9Xn6QD6+p/fPYl/IPCC9USvn5KyqqLONIpFIOLhxFg+uHWXoxLVY2KjmQuWydNwPck9mR71+JhvtVBAEeeKEdgn4+uuvqVChAn5+frRs2RIHBwc6derE0aNHef78udww4YosWbKEzp07M2HCBNzc3Pjqq6/khhsH6fOphwwZwvTp0/Hw8MDd3Z2PP/6Y2bNn/+f6BwcH06pVK6pUqYKVlfQqoXnz5tGsWTP+/PNPPD09cXV1pUePHgrv2P4vkpOT8fHx4aOPPmLFihXUrVuXatWqMXz4cNauXcvKlSs5dOgQIL0bPiQkhBkzZuDm5kbXrl0LnAgPCAigQ4cONGvWDHd3d1asWEGlSm9/BVdwcDDt2rXDzs4Oc3NzpWXq1atHjRo1sLKyQjdPC37VqlX88MMP6OjoFBhO/l1paWnRtMMQzhxYwYNrR3kV9pg9/0xGT78idZvkDnu4a+Ukju3IfY54kw6fEXjvHGd9VxIRHsRZ35UEPbhA0w5DZWWadRrG9dM7uH5mJxEvAjm8eQ5x0eE0avNJsT/bupIzlrbV2L9+OmFBt4l+HcL5w6sJvH8e94bty1W86WnJHNu5kNDAm8RGPufFs3vsXfMT8dEvqd1Yft1Uheadh3Lt1E6und7J6xeB+P47h7iocBp/KH1G45FtC9mxYpKsfOMPPyE28gW+m+by+kUg107v5NrpXbToMlxW5szBVRzbuZg+I37G3NqehNgIEmIjSEtVzSgO/0X7Hp9x7vhuzh3fQ3hYENvW/EpMZDitOvYDYPe/S1iz5Ce5eUKfPiT06UPSUlNIiIsh9OlDXoSW7NBYZX2dA0iIiyA85AHRr6WjQLwOe0x4yAOSE2NL7Hs5cjGZHi2NaOheAXtbHUb2MiUtQ8LFO7mjhYzqbUq/drlXlXZrYUhtZ31sLHSobK1Dp2aGeHtW5PztVEUfUSq0tLSo13II146vIOjOUaLCH3Ni62R09Svi1iD3Oz62eRIXfHN/33otPyP08Tmun1hJzOsgrp9YSdiTC3i2zP19Qx6dIeThGeKjwgh9fI69y4dibuOEe+M+JRZLk/ZDOHNwBQ+uH+V12GP2rC6YL7tXTeLYzjy52j43VyPz5GqTPLnatOMwrp/ZwY2cXN3yJldbfyIr4915BHevHOLaqW1Ev3rG5eMbeXTLn8ZtB5VIvIocv5pK52YVqe+mRxVrbYZ2MyI9Ay4/yO3UD+tmSK9WuSezOjWtSK3qulibaWNnqU27xhVoWlufS/fUOKyzBuWlotg8Ww3h6rEVBN6WxnZsszS2vM/cPbppEucP5Mbm2fIzQh6f49rxlcS8CuLa8ZWEPb6AZ6vc2J49PMOzB9LYQh6dY8/SoVjYOlHrg9KJTRm/C0n0aGWMV60K2Nvq8kUfc9IzJFy4nfuswi/6mtG/Q+4wmd1bGVHbJXd72dnbiOb1DTh/Sz3PNwRo020IF/13csl/F6+eB7J7/TxiIsPxbi9tpxzY/Dv/Lp0sK+/d/mNiIsPZs2E+r54Hcsl/F5f8d9G227ACy77ov4u6jT7EyMS8VGIpThvP2cMbR5f6bPnjawLuniEmMoyQgOsc37WI50/vKF12cfb/flvnEfzoMjERYYQF3mLb0m9IS0mkvnevEolXS0uL+q0Lrnd6+da7I//Kr3f1W31GyCPpehedZ72r3zo3luq123Ll6HKe3jtJfHQYgbePcuPkWpzrdiiRWIpr+77nfNa/Kq2aWuFU1ZApY2uSlpbFkVOvZWV+GlcTnyFOsr8//6QaHzSwoIpdRVydjJj8TQ3cnIzZcyi8VOpcVLvw2I4F7FqZ2xdo1OYT4qJecHjLHCJeBHL9zE6un9mJd6fcvkBx8jEtNYnwkAeEhzwAIDYyjPCQB8QW8szI0qRjZIippzumnu4AGDo5YOrpTkXHykXMWXa07/EZZ/P1e6Lz9ns2Ku/3pKamkBhfOv2ed1Ve+nXF8b71yUFz2imKaEqfVZHyuJ9TREtLi/qthnDlaG4b5egmaRsl77Ouj2ycyLn9edoorYcQ8ugcV4/9TfSrQK4e+5vQfG0Up7xtlKicNsoaXOq+/bHJ/xJf43ZDOH9oBY9uHCXi+WMOrJXG5/FBbnz710zk5O7c+Bq1G8LT++e4cPhvol4GcuHw3wQ/uEDjdrnxndy9kNAnV4mNDOP180ec2vM7IY8vU/sD1V8gqq42ysGNs7h9YT99fX5Dv6IRCXERJMRFkJGu2vVRncf9srIy2bb0W14E36XvqF/JlmTJ4sxU8cUJgmpJJFpl9qWJxJDjJSAgIIBGjRoxY8YMtm7dipWVFS9fvmTPnj3MnDmTmJiYQue/dOkSI0eOZObMmcyYMYNjx47xv//9j6lTp8rKHDlyhO6ANVmPAAEAAElEQVTduzNt2jQmTpxIRkYGDx8+ZNWqVf+5/tOmTWPFihUEBgZSsWJFtLS0uHPnDq1bt+bnn3/mzJkzaGlpERgYWOTd5u9i586dtG3blilTpnDmzBnMzKTD9k2aNIn58+fLymVmZjJw4ECWLVvGrVu3uHLlCj/99BM7duyQlZk9ezZOTk74+fmRnJzM33//zZ49e2TLLK7vvvuOhQsXMmrUKJ4/f46Tk1OBMitXrqRNmzZcvXoVExMT2rRpw6lTpwDYvHkzixYtYtOmTaSlqe6Kx+ZdRpKRnsrBjbNISYrDwbken333DxXyDEcSF/0CLe3cDVhV14b0G72AE7sWc2L3EixtHek3eiEOLrlXTdf5oCvJibGc2vcXiXER2Nq7MXjsCsyt7Yv92Tq6egwet4JjOxawecmXpKcmY2lbld4j5lKjXutyFa+Wtg6R4U+5de4bkhNjMDAyx96pLsMn/ysbTl2V6jaR1sd/71ISYiOws3fjs/HLsXhTn4S4CGKjczsaljYODPluOb6b5nLp+CZMzG3p9umP1G7cUVbm0onNZGVmsPnPb+U+q22vr2jX+2uVx/A2GjXvRGJCLAd3rCA+JpIqVV35+sc/sbKR3s0ZFxNBdKR8x+rnCbknz0KC7nPl7CEsbSrzy7JDJVrXsrzOAVz138KpfX/J/l4z91MAPhr+Cw1alMyJHN9zyejraTGkmwlGBtoEhmXw24YYUtNzr3a2MtORe2ZZBX0tPutmgqWpDumZEsIjM/l7VxyX75XeFeGKNGg7ksyMVE7vmkVaShx2VevRY9Q/6FfM/Y4TY17IXd1duXpDOg5ewKXDi7nstwRTK0c6fLYQuzzDp6WnJHLx0EISY19S0dAc57odaNJlHDo68ncmqlLzLtJYfPPmy3gFuZonFkfXhvTzWcCJ3Yvx3/MmV30W4uAsn6spibGc2p8nV7+Vz9VaDTvQ/bMZnPX9m8Obf8aqkhMfj1lCVTevEos3vyOX0tDX1WJgR0MMK2rx9EUmS7YlkJanH2hpqi2fl3owsIMh5ibaZGRKeBmdzeoDSVx7qJ5n5OXQpLzMr+GH0thO7cyN7SMf+dgS8sfm1JBOny3g4qHFXDq8BDMrRzoNWSg3ZGF6aiIXDubG5lKvA027lm5sihw8k4S+rhZDe5hhWFGboLB05q+LLri9zHNDawU9aXlLUx3SM6TbyxU7Yrl0V30HUxs060JSQhx+u5YTHxtBZUc3vpi0DMs3++342Ehi8uy3rWwdGDVxKXs2zOfskc2YWdjSe+hkPJvIn+h8HR7M00fXGT3571KLpThtPC0tLQaPXcHxXYvYu3oKSQkxGJtZU61Go0KHay7O/j8+5hU7ln9HcmIsRiYWOLh4MnLKVrltqqrlrHcnd7xZ76rV46PRRWxTnBrS+bMFXDi0mIuH3qx3Q+XXu9Z9fuLioSWc2jmL5MQojExtqeM9gA86jimxWIrj352hVNDXZvyXbpgY63H/cTzjpt0mJSX3kRR2NhXlnn1nbKzLxK9rYGmhT1JSJo+DEvnqh1s8eJKg4BNUr6h2YUJcBHHRuSeZLWwcGDxuBYc3z+XKCWlfoMugKXg06iQrU5x8fBF8l3Xz81xwsWUuAJ7Ne9F7xNySDrtIZl51aHZ8g+xvj99+BCB0/S5uj5isbLYypXHzTiQlxHJw+wri8vZ7bJX3e/73fZ5+T+B9Lp85hJVNZX5ZXrL9nndRnvp1RXnf+uSgOe0URTSpz5pfedzPKePVbhSZGWn475hJWnIcdtU86fXl6nx9g3C5EWEqOzWk85CFXPRdJGujdB76O5Wq52mj9P2Ji76LObljpqyNUtd7AB90KplH3CjTtJM0Pr9NM0lNjqOKkyeffLuaCnnii4+Wj8/BpSG9Ri7k1N5FnN63BAsbR3qN+h37PMOZJyVEsn/NRBLjXlPBwARb+5oM+GYVTh7NVR6DutooV/03A7B23hC5+pTEsS51HfeLj3nJo5snAFg+o5dcnYZOXIeTexOVxikI5ZUWbx5RLwhlVYUKFdi7dy+Ojo60bt1a7vnj5YWDgwPBwcE0btyYGzduvNW8EomEzec0czUd2Fy689fE+HJi236x9IZZLE39m0ob2P53ytaV16rQtq4BoNl5OWzGKzXXpGSsnSF9Furi/Zr3233bQ/rbbTqrebENaiGNbfS8wi/4K6+WT5IOE6bJefnHQc2L7f+6SWMbMlV9d6qUpPWzpXc0+l5X7wUbJaFrQ+mFC5q8H//TV/NiA/i6qzS+Fj1Oqbkmqnd2v/SCXk3MS8jNzYN66nkecEnqlvEIgJN3Na/f06aOtN+jiX06yO3XaWKfPKc/rontlJw2iqb3WTV5X/dX2bve5j/7qov037Un1VqNEjOsjfRfTWynaPqx5/zD6Qulz/d62b2DvmtD/aILlTNiyHGhzEtLS+Ojjz5i/fr1tGrVSt3VeSu6uro4Ojoyb948Ll68+NYnswVBEARBEARBEARBEARBEARBEISyRSIpuy9NJIYcF8qFtLQ05s2bp+5qvLXmzZtz8uRJHj16RL9+/dRdHUEQBEEQBEEQBEEQBEEQBEEQBEEoV8QJbUEoQadOnRJDfwiCIAiCIAiCIAiCIAiCIAiCIAjCOxIntAVBEARBEARBEARBEARBEARBEARBEIopG3EzY2kSz9AWBEEQBEEQBEEQBEEQBEEQBEEQBEEQyiRxQlsQBEEQBEEQBEEQBEEQBEEQBEEQBEEok8SQ44IgCIIgCIIgCIIgCIIgCIIgCIIgCMUkkai7Bu8XLUB85YJQhknEVlEQBEEQBEEQBEEQBEEQBEEQhDe0tMTzm9Vt39UMdVdBqZ6N9NRdBZUTQ44LgiAIgiAIgiAIgiAIgiAIgiAIgiAIZZIYclwQyoHN5zTzLu2BzaVXkW05r3nxfeItje3c/UQ116RkNPcwBsDX0F3NNVG9rskPAdh0VvPyclALaV4+DAxTc01KhruLAwC+18vu1ZHvqmtD6VWVmrg/yNkXPAoMVXNNSkZNF0dAs/PyyK10NddE9Tp66gOan5fJq6eruSaqZzh8JqDZ20tNXOcgd70LHdNXzTVRPcelOwHNzEvIzc2Td1PUXBPVa1PHAICDejXVXBPV65bxCNDMPh3k9us0sU+e0x/XxHZKThtF0/usmryv0+R+z4HrmWquScno3lB6ikiTj89qYhssp/0lqJdEIn6H0iTu0BYEQRAEQRAEQRAEQRAEQRAEQRAEQRDKJHFCWxAEQRAEQRAEQRAEQRAEQRAEQRAEQSiTxJDjgiAIgiAIgiAIgiAIgiAIgiAIgiAIxZSteaPZl2niDm1BEARBEARBEARBEARBEARBEARBEAShTBIntAVBEARBEARBEARBEARBEARBEARBEIQySZzQFoS3NHToUGJiYtRdDUEQBEEQBEEQBEEQBEEQBEEQBEENJJKy+9JE4hnawnvHxsaG2bNn06VLF+zs7IiJieHWrVvMmDGDixcvqrt6/8nlE5s4f/gfEmIjsLV3pfPAH6lWo5HS8sGPLuO3ZS6vnwdgYm5L8y4jadz2E7ky96/6cWL3EmIiQrCwqUq7PmOp5dVB9v6Zgyt4cO0okeFB6OpXxNG1AR36fYd1ZWeVx3bu0D8kxkZgY+9Kl0FFxPbwMoe3zCXieQAmFoXHFv06BEvbgrEBxMe84ui233hy5zSZGWlY2VXno+H/o0r1OiqNrzhOHNrG4T0biI2JxN7RmYEjvqeGRwOFZWOjI9i69neCAx/yOjyEdt0+YdCI70u5xv+NRfNGOI8bgVmD2lSsbMu1AV/xav9xdVerAIlEwql9f3Lt1DZSk+Oxd65H18HTsLV3K3S++1f98N+Tu2592GcstRrK59+VE5s475e7Tnf6RHne718/jeunttHpk8k07TBUZfEVxffAXnbv3EZMdBRVq1VnxBdjqF2nnsKyF86d4dDBfTwNCiQjI4Oq1arxyeChNPRqXGr1LczZI1vwP7CG+NgIKjm40mvIJFzcvZSWD7h/hb0bf+VlWACmFrZ82P1zmncYIFcmJSmeg1uXcPvKMVKS4rG0seejTyfg0aBVicYikUg4uVc+L7t9Wry8LGybD0Xva+5fO8K1k1t58eweKYmx+MzYTeWqtUokTmV8D+xl187tsrwc+cUYatepq7Ds+XNnOHRwv1xeDhw8RORlKTjtt4Xj+9YSHxtBZQcX+gybhGst5bE9uX+F3et+JTwsEDMLG9r3HE6Ljh/LlfE/uIGzR7YRExmOkak59Zt0oOegsejpVyjpcIqkSXmZ37brT1h3+SGRiSm4WJvxfbsGNHS0VVo+PTOLv8/f4+C9YKKSUrEzMWBEs9r0qqfa9mN+6mgrF+dz/ff8wd3LvsRHv0RHV4/K1WrTrs9YHFw8VfsF8H6td8atOmHS/iN0zCzICA8lZvsa0gMfKC1v2LglJh16oWtbGUlKMqn3bxC7ax3ZSYmlWGspde3HszIzOLF7MU9unyImIowKBsY4e3jTvt94TC3sSize/E4e3sqRveuIi4mkiqMLH38+ATePhgrLxsVEsH3tAkKCHvA6PIS2XQcyYPjEUqurqli2aITzdyMwa1iHilVsudp3DK/2lb2+z7soL/26omhyf1yT2yigWX3W/Mrzvi4/Te73nDuymZN5YvtoyA84FxJb4P0r7Ns4XxZb2+7D8VYQm+/WxdyRxeZAz08nUKuEY1PH8dmsrExO7vmT2xf3kxgXiYm5DfWb96ZVjy/R1lbt/ZrvextMEMo6cYe28N7ZuXMnnp6eDB06lBo1atCzZ09OnjyJpaWluqv2n9y97MvhzXNo2X00o2fspqpbIzb+/gWxUS8Ulo+JCOPf332o6taI0TN207K7D4c2/cz9q36yMqEBN9i+fDye3j0ZPXMvnt492b58HGGBt2Rlgh9dofGHgxj501aGfLea7KxMNiwcSXpasupiu+TL4U1zaNV9NKNn7qZajUZsXFh4bBt/96FajUaMnrmblt18OPSvgtiWjades558OWsv9Zr1ZNsy+dhSkuL45+eBaOvq8un4lXz18wE6fTKJioamKoutuC6fPcLm1Qvo3m84MxZsws2jAb/P/j+iIsIVls/MzMDE1ILu/YbjWL1GKddWNXSNDEi485B742eruyqFOndoFReOrKXr4KmM+mk7xqY2bFgwnLQU5R3C0IAb7Fghzb/RM6T5t2P5OMKCcvPv7mVfDm+ZQ8tuo/GZLl2n/130BXEK8v7h9WM8D7qNibnykwcl4cwpf/75eyn9Bwzi9z9W4FG7LrOmTSbi9SuF5e/dvU39Bl5Mm/ULC5cso269+vw88yeCAp+Uar0VuXHhEHvWz6VDr1F8P2c7zjUb8vfc0cREKl7Hol6HsXL+GJxrNuT7Odvp8NFIdq+bw61LR2VlMjMzWPbLKKIjnjNs7EImLzjAgFEzMbMs+d9JlpefTmXU1O0Ym9mw/rei87KobX5x9jUZaSk4ujWkfb/vSjRGZc6c8mfV38v4eMAgFv2xHI/adZlZaF7eoX4DL6bP+pnflyylbr36/G/mVAJFXpaoa+cPs2vtPDr1GcWkedtxqeXFsl++JFpJbJGvw1g+5ytcankxad52OvYexY41c7h5MTe2K2cOsG/TIrr0H82U3/cyaPQsrl/wY9+mRaUUlXKalJf5+T0I4dfjNxjRzIPNwzrRwMGGr7efJjw+Sek8E/ee53LwK6Z3+YA9o7oyp4c31S1Ltn2lrrZycT7XqlJ1ug6eypez9jF88r+YW9uzYeEIkuKjVfodvE/rnYGXN+b9Pif+8E5ezvmetIAH2Hw1BR0La4Xl9V3csRz6fySdP87L2WOJXPUb+tVcsRg8ppRrLqWu/XhGeirhz+7TqscYfKbvZMDXfxD1KpjNS0rve7hyzo9ta36la9+R/PTbFlxrNeCPn78iWkm/JyMjHRNTC7r0HYlDOe33AOgYGRJ/+xH3vp2l7qqoXHnp1xVGk/vjmtxGAc3qs+ZX3vd1eWlyv+fGhUPsXT+Xdr2+YPycHTjVbMjKuT7ERCpug0a9DmPV/C9xqtmQ8XN20O6jUexZ9wu3Lx2RlcnMTGfFLyOJiXjB0LG/M2nBQfqPmlHisanr+OxZ31VcPbmFbp9O5etfDtKh//ecO/wPl45tVHmM73MbTBDKA3FCW3ivmJmZ0bJlSyZNmsTJkycJCQnhypUrzJ07F19fXwDGjRvH7du3SUxMJCQkhL/++gsjI6NCl9u9e3euXr1KSkoKgYGBTJs2DR0dHdn706dP59mzZ6SmpvL8+XMWL16s8tgu+K2lYcu+eLXqj00VF7oM+hEzy0pc9d+ssPzVk1sws6pMl0E/YlPFBa9W/WnQsg/n/VbLylw8uh4XD29advPBprIzLbv54FSrKRePrpOV+Wz8Khq06IOtvRuVqrrTa/gc4qJe8CL4nspiO39kLQ1a9cWrdW5sppaVuHJCcWxX/PPF1loa27nDubFdOLIe59retOouja1Vdx+cazXlQp7YzvquwtSyMr1HzMHBuR4W1g44ezTD0raqymIrLr99G2nZ7iNadehNFUcnBo34HksrO/wP71BY3tq2CoNGTqB52+4YGBqXcm1VI+LIGR7PXMyrvUeLLqwmEomES8fW07LbaGp5dcTWoQa9RswlIz2VO5cOKJ3v0rHcdcs6z7p1KU/+XTyylgYt+9LwzTrdeaB0nb5yUj7v42Ne4btpNn1G/Yq2TukOvLJ39w7ad+xCx87dcKxajZE+X2FtY8uhg/sVlh/p8xV9+n+CWw13qtg78NmwkVSuYs/lSxdKtd6KnDy4niZt+9D0w37Y2bvQe+gPmFtV4tzRLQrLnz+2DXOrSvQe+gN29i40/bAfH7Tpjf/BtbIyl/x3kZwYx4jvluBcsyGWNlVwdm+IfTX3Eo1FIpFw8eh6WnUfjYdXR+wcatC7GHlZnG1+cfY1nt4f0abnVzh7NCvROJXZu3sn7Tt2pmPnrjhWrcYonzFY29jiqyQvR/mMoW//AbK8HDJsBJWr2HPlkvpHbdGkvMzP/8B6mn3YB+92fank4EzfYZOwsK7E2SNbFZY/d2QbFtaV6DtsEpUcnPFu15embXtzfP9aWZmnj2/hXLMBjVp0w8rWnlqe3ng170JI0P1Siko5TcrL/DZeeUives708XTB2dqMCe0bUsnEkO03AhSWPxcUzrXQ1/zRvxVNq1eiipkxdapYUd9B8cFXVVFXW7k4n1uvaQ9cantjaeuIrb0bnT75gbSURF6FPVLpd/A+rXcmH/Yg6fwJks4fJ/Plc2J3rCErNgrjVp0Ulq/gVIOsqAgST/qSFfWa9MCHJJ49gn41l1KuuXr34xUNTRjy/WrqfNAF68rOOLrUp+vgnwh/dk/pwWpVO7Z/A80/7E2L9n2o7ODMgOETsbCqxCm/7QrLW9vaM2DEJJq16VFu+z0AEX6neTx9ES/3lN2+z7sqD/26omhyf1yT2yigWX3W/Mrzvi4/Te73nD64jg/a9pXF1mvoZMytKnP+qOL214VjWzG3qkyvoZPzxNaHk3liu+y/m+TEeD7/bglOsti8qFLCsanr+GxY4A1qNmhHDc82WFg7ULtxZ1xqN+dF8F2Vxve+t8GEdyNBq8y+NJE4oS28VxITE0lISKBXr17o6+srLJOdnc0333xDnTp1GDp0KB9++CHz589XusyOHTuyceNGlixZgoeHBz4+PgwbNowpU6YA0LdvX8aNG4ePjw9ubm706tWLO3fuqDSuzMx0Xjy7h0vt5nLTXWo3JzTghsJ5QgNvFijvWrsFL4LvkZWZkVumTr4ydVoQGnhTaV1SUxIAMDAye9swFMrMTCc8+B6uimILVBxbmKLY6sjHpqiMS50WhAbclP396OYJqjjVYetf3zL/G2+WTe/N1VPbVBDV28nMyOBZ4ENq128qN712/aYEPLxd6vURcsVGhpEYFyGXS7p6+lSv2ZgwJfkJ0nXLuUBO5+ZflpJ12tmjOWF51mlJdja7V03Eu9OIIoc/UrWMjAwCAx5Tv6H80FL1G3jx8EHxLmjJzs4mJSUFE5PSH/Ugr8zMDMKe3qdmPW+56TXreRP8+JbCeYKf3CpQ3t2zOaFBuduZe9dPUt3Nkx1rfmaqTyvmTejF0T1/k52dVTKBvBEToTwvle0ToOht/rvsa0pbRkYGAQGPaZAvLxs08OLhg+KdXJHmZTLGJiYlUcVi07S8zCszM4PQoPu4e+araz1vnj66qXCep09u4Z4vtlr1mxMSdF8Wm4t7Q0KD7hMcIG1nRb4K5f6NM9Ru2FL1QbwFTcrL/DKysnjwMoZmTpXkpjd1qsSt55EK5zkV8ByPSpasvfSQjn/t5aO/D7LwxA1SMzJLrJ7qaiu/y+dmZqZz7dRWKhiYYOeouoOS79V6p6OLflUXUh/clJuc+uAW+s41Fc6SFvQIHXMrKtaWDmutbWKGQYNmpN69VtK1LaCs7cdTkxNAS6tURqnKzMggJPABHvXlL4rz8GxK4CPF+z5BKGma3B/X5DYKaFaftYByvq/LS7P7PemFxHZT4TzPFMRWs0Bs/lRz82TXmv8x3acVv074iGMlHJs6j89WdfPi6f0LRL58CsDLkIeEPLlOjXqqHV79fW6DCUJ5IZ6hLbxXsrKyGDZsGCtXrmT06NFcv36dU6dOsWXLFtlJ5rx3TwcHBzN16lSWLVvGV199pXCZU6ZMYe7cuaxfvx6Ap0+fMnXqVObPn8+sWbOoWrUqL1++5NixY2RmZhIaGsqVK1cULktfX58KFd7+WXPJCTFIsrMwMrOSm25kakVinOKDiYlxERiZtpAvb2ZFdlYmyYkxmJjbkhgXiZGpomVGKFymRCLBb+tcqrp5YeegmmG1khNiyM7OKlAPYzMrEu8qj83YLF9spgVjM86/zHyxxbwO5eqJzTTrNIxW3X0IC7rNoX9/RldXn/rNe6kkvuJISIglOzsLM3P5+pqaWxEXG1Vq9RAKysmX/LlkZGqlcGjw3PmU5F+8dHk563SBMmZWBObJ+7OHVqKtrUOT9p/9pzjeRXx8HNnZ2ZibW8hNN7ewICameEOk7tm1nbTUFJq3bF0SVSy2pHjpdsYk3zbUxMyKeCXb0ITYSIXls7MySUyIxczChqjXYTyJeI5X8258MWkZES+fsXPNz2RnZdGp75clFk9OHinafheVl4Vt899lX1PalOWlmYUFsW+Vl6m0EHlZYgqNTcl+LT42qsjYvJp3ITE+mkVThyABsrMyadFxAB17jSypUIpFk/Iyv5jkdLIkEiwNK8pNtzKqQFRSqsJ5nscmcjMsggq6Oizs3YKYlDTmHLlKfGo6M7o2KZF6qqut/Daf++imPztWfEdGegomZjYM+X41RibyOfNfvE/rnbaxCVo6OmQlxMlNz4qPpaKpucJ50oMeEbV2EVYjxqOlp4eWji4pty4Ts/WfUqixvLK0H8/ISOPYjgXUbdKdigYlf5dp4pu+n6mZ/OPATMytiI8tG20N4f2jyf1xTW6jgGb1WfMr7/u6vDS73yPdfhibFTy2k6AktvjYSGoqKJ+dlUlSQiymb2ILiLhEw+bdGTlpGZEvn7Frzf/IzsqkY9+SGaJancdnW3QdRWpyAn/+2BUtbR0k2Vl82GcsdZt2V1F0b+r7HrfBBKG8ECe0hffOrl27OHjwIC1btqRZs2Z07tyZiRMnMnLkSNatW0ebNm348ccf8fDwwNTUFF1dXQwMDDA0NCQ5ueBzob28vGjcuLHsjmwAHR0dDAwMMDAwYPv27YwdO5agoCAOHz6Mr68v+/fvJyur4FVzkydPZsaMGe8cm1b+oSQkgJby4SW08r8nkb1R+DKVDFnhu3E2r0IfMXzypmLV923kr6tEoqBu8nMoW5DSZUrnyp0mkUioUr027fuNB6ByNQ8iXgRwxX9zqZ7Qzlu7vCQSSWE/r1ACbl/cz4H102V/D/p2ufQ/CvKzyB8n/zzSifkLKV3ui+C7XDq2AZ9pOxXmcmkpsBmRKF638jt98gRb/l3Pj9NmFTjAoC4Ft3eSQmPJX14iefMrvplHkp2NsaklH4+agba2Do7OtYmPieDEgTUq7UDfvrCf/XnycvDY5XL1kK904b9Ncbb5b7uvUYeC+zdJsep46uQJNv+7gSnTZoq8LAUFw5Ao3X1Lyyv4XfNMf3LvCn67VvLxyJ+o7laXiJeh7Fwzl8Pm1nTuN1p1FX9HmpSX+SkMTUnZ7Dc5/HOPpphUkI6YlP5hAybsOccPHbyoqFdyXVR1tZWL87lOtZowesZukhNjuH5qO9uXjWXkT9sKHOD7r96r9U4ikf9bSyv3N8xHt5IDFv1HEO+7ndQHN9ExtcCszxAsBvkQs3FpiVazrO7HszIz2LF8PBKJhG6fTS/wfolSmHdlq60hvI80tz+uyW0U0Kw+awHlZF9XHBrd71EQW6FtUEXlpW9I/3wTW3+52F7jf2BNiZ3QltVNDcdn71725faF/fT1+Q3bKq68DH3IoU2/YGpuS/0Wvd+q/nmJNpigCtlKtrlCyRAntIX3UlpaGseOHePYsWPMnj2blStXMnPmTPz9/fH19WX58uVMnTqV6OhoWrRowerVq9HT01O4LG1tbaZPn86uXbsKvJeamkpYWBg1a9akQ4cOtG/fnqVLlzJhwgRat25NZqb80Ipz5sxh4cKFctPi4+OLjMfQxAItbZ0CV3UlJUQpPQhmbGZTsHx8FNo6uhgamb8pY01ivIJlmhV8xqHvv7N5dPMEn/+wETPLSgXef1eGJhZoK4otPqrAlW05ihtb/qshE+OjMMoTm7G5DTZVXOXKWFd24f7VI+8azjsxMTFHW1uHuHx3JSTERWOq5DsQSkZNz7Y4TK8n+zszMx2QXo1pYm4rm55cyLoHb9YtBTlqbCrNP9k6nX/9i89dbsiTayQlRPH7xA9l70uysziydR4Xj65j7PwT7xhl8ZiamqGtrU1MTIzc9LjYmCI7+2dO+fPH4t+YNHka9Rt4lWQ1i8XIVLqdyX/1d0J8NCZKfkcTc+sC5RPjo9HW0cXIWPrIBVNzG7R1ddHW1pGVsbN3JiE2kszMDHR1Fe9X3lbN+m2xd87NyywleZk3fxQpapv/Lvua0pabl/J3XMTFxhYzLxcwafJUkZclTBZbvruaCtuvmSq4Oy8hX2wHtv7JB6164N2uLwBVqtYgPTWZzX/PomOfL9DWVs/TljQpL/OzMNRHR0urwN3Y0clpWBpVVDiPtbEBtsYGspPZAE5WpkiAVwkpVLNU/ZCl6morv83n6lcwxMquGlZ21XB0qc+SHzpx48wOWnbzeet4FXmf1rvsxAQkWVno5LtDTcfEjKyEWIXzmHbqQ1rQQxKO7QUg4/kzsrekYvfdz8Tt20R2vOL5VKEs7sezMjPYvmwcsRFhDJ24ttTuDDI2KSRPzctGW0N4/2hyf1yT2yigWX3W/Mrbvq4wmt3vkW4/Ch5/VB6bqbmi45U5sZm/KWODTr7YbO1d3sSWjq6u4sds/hfqPD57ZOuvtOg2irpNugFg51iT2MgXnDn49386oS3aYIJQ/ohnaAsCcP/+fYyMjGjUqBG6urp89913XLp0iSdPnlClSpVC571+/To1a9YkMDCwwCvn6sDU1FT279/Pt99+S5s2bfD29qZu3boFlpWenk5CQoLcqzh0dfWpUq02gffPy00PvHceR9cGCudxdKlP4L385c9RpXptdN406hSWuXsOR5f6sr8lEgkHN87iwbWjDJ24Fgsbh2LVubh0dfWpXL12gXoE3T+Po4vi2Bxc6hOU77sIyBebg0t9ghTE7+haX/Z3VdcGsuez5Ih6FYy5VeE5oWq6enpUc3Hn/q1LctPv3bqEq3s9JXMJJaGCgTGWdtVkL5sqrhib2cjlW1ZmOsGPruCgJD9Bum7lz9GgPPmn82adzp+jQffP4/Bmna7XrCdfztjL6Om7ZS8Tc1u8O4/g0/GrVBSxcnp6eri41uDWDfnnbd28cQ33WrWVznf65AmW/D6f7yb8SKMPmiotV5p0dfVwcPLg8e0LctMf37lA9RqeCuep7ubJ4zvy5R/dPo+jc+52xqlmfSJfhpCdnS0r8zo8GFNzG5V2nisYGMtOgljlycu8+4TMN3mpbJ8ARW/z32VfU9r09PRwda3BTYV56aF0vlMnT7D491/5fsKPNBZ5WeJ0dfVwdPbg4e38db2AU836CudxcvPkUb7yD2+dp6qzhyy2jLSUAlfTa2nrvLmjQX2XTWtSXuanp6NDrUoWXAx+KTf9YvBLPO0LXgAJUN/emojEFJLTM2TTnsUkoK2lhZ2JQYnUU11t5f+y3ZQgITMjvcjYiuu9Wu+yMkkPCaRiLfltZUX3eqQHPVI4i5Z+hYJ3ueVsJ0v4Fsyyth/POZAa9foZQ75fg6Fx6d2VqKunR1WXWjy4JZ93D25fwqWm4n2fIJQ0Te6Pa3IbBTSrz1pAOdvXFUaz+z36b2KT3/c+vnOe6jXqK5ynmpsnj+/Ily8YW4MCsUXIYlP9yWxQ7/HZjPQUtLTkT2NpaWsjkWTzX4g2mCCUP+KEtvBesbS05Pjx4wwePJi6detSvXp1+vXrx8SJE9m7dy+BgYHo6enxf//3fzg5OfHpp58yenThQ+XNmjWLIUOGMH36dDw8PHB3d+fjjz9m9uzZAAwdOpThw4dTu3ZtnJyc+Oyzz0hOTubZs2cqja1Zp2FcP72D62d2EvEikMOb5xAXHU6jNp8AcGzHAnatnCQr36jNJ8RFveDwljlEvAjk+pmdXD+zE+9Ow2VlmnT4jMB75zjru5KI8CDO+q4k6MEFmnYYKitzcOMs2bAv+hWNSIiLICEugox0xc9NfBfeHd/Edloa26HNc4iLCqdxW2lsR7fLx9a47SfERr7g8OY3sZ3eyY3TO2neOTe2pm9iO3NQGtuZgysJun+BZnlia9ZxGGFBtzh9YDlRr55x+8J+rp3cxgftBqsstuLq1PNTTh/bw5lje3kR+pTNqxcQHfmSNp36AbBjwx+sXDxNbp6Qp48IefqI1NRkEuNjCHn6iOehQaVe93elY2SIST13TOq5A2BQzQGTeu5UdKis5prl0tLSokn7IZw5uIIH14/yOuwxe1ZPRk+/InWb5D7LZ/eqSRzbuUD2d5P2uetWZJ51q0me/GvacRjXz+zgRs46veXNOt1amveGxhbYOtSQe2nr6GJsZo11JedSif+j3v046ufLsSOHCA15xqq/lxIZ8ZrOXXsAsH7NKn7/ba6s/OmTJ1i0YC6fjxxNTXcPYqKjiYmOJikpsVTqW5g23YZw0X8nl/x38ep5ILvXzyMmMhzv9gMAOLD5d/5dOllW3rv9x8REhrNnw3xePQ/kkv8uLvnvom23YbllOgwgOTGW3evm8jo8mHvXT3Fsz0padPykRGPR0tKiaYchnDmwggfXjvIq7DF7/imYl7tWTuLYjjx5WYxtflH7GoDkxFjCQx4Q8SIQgKiXTwkPeUBCnmdglaSPevflqN8hjubJy4iI13R5k5fr8uXlqZMnWLRgHsNH+lDTvZbIy1LStvsQLhzfyYUTu3kZFsTOtfOIjgynRYePAdi3aRHr//xRVr55x4+Jjgxn17r5vAwL4sKJ3Vw4sYt2PXJjq+PVhrNHt3Ht3CEiX4fx8PZ5Dm79kzqN2sjdvaAOmpSX+X3a2J3dt4LYczuIoMg4fjt+nZfxyfSrLx3lZsmpW/x04KKsfBePapgZ6DPd9zKBkXFcC33NIv9bfFTXqUSHG1dXW7moz01PS+bYzoWEBt4kNvI5L57dY++an4iPfkntxp1V+h28T+tdwon9GHm3w6jZh+hWsse87zB0LKxJPCMdacnso8FYDv0/WfmUO1cxqN8Eo5ad0LGyQ9+5JhYfjyDt6WOy42KUfUyJUOd+PCsrk21Lv+VF8F36jvqVbEmWrH+XMzJRSWvf4zPOHt/NueN7CA8LYtuaX4mODKdVR2m/Z/fGJaxZ8pPcPKFPHxL69CGpqSkkxscQ+vQhL0IDS6W+qqJjZIippzumntK+j6GTA6ae7lR0LDt9n3dVHvp1RdHk/rgmt1FAs/qs+ZXnfV1+mtzvadVtKJfyxLZ3/VxiIsNp9ia2g5t/Z1Oe2Jq1H0BMZDh7N8yTxXbZfydt8sTW7E1se9bNISI8mPvXT3F8z0qadxxYorGo6/hszfptOXNgOY9vnSQmMowH145ywW8t7g07qDS+970NJrwbiaTsvjSRGHJceK8kJiZy6dIlxo0bh4uLC3p6eoSGhrJy5Up++eUXUlNTGTduHJMmTWLOnDmcPn2ayZMns2HDBqXLPHLkCN27d2fatGlMnDiRjIwMHj58yKpV0jskY2Nj+eGHH1i4cCE6OjrcuXOHHj16EB0drXSZ76LOB11JTozl1L6/SIyLwNbejcFjV2BubQ9AQlwEcdEvZOUtbBwYPG4FhzfP5cqJTZiY29Jl0BQ8GnWSlanq2pB+oxdwYtdiTuxegqWtI/1GL8TBJfcKyav+mwFYO2+IXH0+Gv4LDVr0UU1sTbqSnCSNLSEntnG5sSXGRRAXJR/bp29iu5wT2+B8sbnlxua/ewkWto70zxebvXNdPvn6D47tWMipvUsxt3Gg86DJ1GvWQyVxvY0PWnQkMSGWfdtWEhcTiX1VF8b+tARrW+lBgLiYSKIj5O+OmjF+kOz/zwIfcPH0YaxsKvPr3wdKte7vyqxhHZr6rZf97TFf2sAP27Cb2z6Tlc1W6pp3GUlmRiq+G2eRkhSHg3M9Phv/DxXyDAsUF/1C7u4lR9eG9PNZwIndi/Hf82bd8lmIg3Nu/tX5oCspibGc2p9nnf42N+/Lgpat25KQEM/WTRuIjo6mWvXqTJs5B1s7OwBiYqKIjHgtK+936ABZWVmsWLqEFUuXyKZ/2L4j346fVGD5palBsy4kJcTht2s58bERVHZ044tJy7C0kY7IEB8bSUxkuKy8la0DoyYuZc+G+Zw9shkzC1t6D52MZ5PcDpWFVWVGT/6bPRvm8+ukPphZ2NKqy6e06zmixONp3mUkGempHMybl98pyEvt3Lwszja/qH0NwKObJ9i7OveEyI7l4wFo3fMr2vbKPaBSUnLzcmOevPwlT15GE6EgL5cv/YPlS/+QTf+wfUfGjp9Y4vUtjKblZV5e3p1JSojl8M7lxMdEUNnRlS8nL5XFFhcTIRebta0Doyf/xa51v3LGbwumFrb0+3wy9Zvmxtap7xegpcWBLX8QF/0aY1ML6ni1pvvAb0o1NkU0KS/z61SrKnEpafx97i6RSam4WpvxR/9WVDEzAiAyMYWX8Umy8ob6eiwb0JZ5R6/x6bojmBno08G9Kl+1LDh6kSqpq61c1OdqaesQGf6UW+e+ITkxBgMjc+yd6jJ88r/Y2rup9Dt4n9a7lGvniTUywbRrf3RMLcgIDyFy6S9kRUsvrtIxtUDHIncUgeSL/mhXrIhJ6y6Y9x2KJDmJ1Md3iNu9US31V9d+PD7mJY9uSh9bs3xGL7k6DZ24Dif3JiUYtVTj5p1ISojl4PYVxMVEUqWqK1//+CdWtrl5Gp0nTwH+933uyYmQwPtcPnMIK5vK/LL8UInXV1XMvOrQ7HjucQeP36RtqdD1u7g9ouz0fd5FeenXFUaT++Oa3EYBzeqz5lfe93V5aXK/p0GzLiQnxHJ01zJZbCMnLc8TWwSx+WIbOXEZezfM49yb2HoN/ZF6TTrKxfbF5JXs3TCP3yb1xszCjpZdPuXDEo5NXcdnuw7+iRO7l3BgwyyS4qMwMbelUZsBtP5I9c8Lf5/bYIJQHmihzvH3BEEokkQiYfM5zVxNBzaX7vy3nNe8+D7xlsZ27n7Zu4pXFZp7SBtyvobuaq6J6nVNfgjAprOal5eDWkjz8mFgmJprUjLcXaSPPPC9nlFEyfKna0PpcFyauD/I2Rc8CgxVc01KRk0XR0Cz8/LILc27Yryjp3SoPk3Py+TV09VcE9UzHD4T0OztpSauc5C73oWO6avmmqie49KdgGbmJeTm5sm7KWquieq1qSN9FMJBvZpqronqdcuQDkusiX06yO3XaWKfPKc/rontlJw2iqb3WTV5X6fJ/Z4D1zPVXJOS0b2h9J5HTT4+q4ltsIHNtQo8+kcofdsuZKm7Ckp93Ey9I9WVBHGHtiAIgiAIgiAIgiAIgiAIgiAIgiAIQjFp6tDeZZV4hrYgCIIgCIIgCIIgCIIgCIIgCIIgCIJQJokT2oIgCIIgCIIgCIIgCIIgCIIgCIIgCEKZJIYcFwRBEARBEARBEARBEARBEARBEARBKKZsiXiOeWkSd2gLgiAIgiAIgiAIgiAIgiAIgiAIgiC8h7788kuCgoJISUnh6tWrtGjRotDyrVq14urVq6SkpBAYGIiPj0+J11Gc0BYEQRAEQRAEQRAEQRAEQRAEQRAEQXjPfPzxxyxatIiff/6ZBg0acObMGQ4dOoSjo6PC8tWrV8fX15czZ87QoEEDfvnlF5YsWUKfPn1KtJ5iyHFBEARBEARBEARBEARBEARBEARBEIRikkjUXQPl9PX1qVChgty0tLQ00tPTC5QdP348//zzD//88w8A48aNo1OnTnz55Zf8+OOPBcqPHj2akJAQxo0bB8DDhw9p1KgR33//Pbt27SqBaKS0gDL8lQuCICnLW0VBEARBEARBEARBEARBEARBEEqVlpZ4frO6bTqbre4qKPXo6ExmzJghN23GjBnMnDlTbpqenh7Jycn079+fPXv2yKYvWrSI+vXr06ZNmwLLPnXqFDdu3GDs2LGyab169WLbtm0YGhqSmZmpwkhyiTu0BUEQBEEQBEEQBEEQBEEQBEEQBEEQNMCcOXNYuHCh3LS0tLQC5aytrdHV1eXVq1dy01+9ekWlSpUULrtSpUoKy+vp6WFtbc3Lly//Y+0VEye0BaEc2HxOM+/SHthcehXZlvOaF98n3tLYzt1PVHNNSkZzD2MADurVVHNNVK9bxiMANp3VvLwc1EKalw8Cn6u5JiWjlos9AL7XM9RcE9Xr2lAP0Mz9Qc6+4GFgmJprUjLcXRwAzc7LI7cKDldV3nX01AfgUWCommtSMmq6SJ+DlXpkjZpronoVO34OwPydZfdK+Xc1sa82oJnrHOSud2Ff91dzTVTP4c/tgGbuxyF3X+5/J0XNNVG9tnUNAPA1dFdzTVSva/JDQDP7dJDbr9PEPnlOf1wT2yk5bRRN77Nq8r7uwPWSuStPnbo3lJ5C0cTYIDc+TT4+q4ltsJz2l6BeZXlw3fT0dIXDiyuTf6RgLS2tQkcPVlRe0XRV0i6xJQuCIAiCIAiCIAiCIAiCIAiCIAiCIAhlTmRkJJmZmQXuxra1tS1wF3aOly9fKiyfkZFBVFRUidVVnNAWBEEQBEEQBEEQBEEQBEEQBEEQBEF4j2RkZHDt2jU6dOggN71Dhw6cP39e4TwXLlwoUL5jx45cvXq1xJ6fDeKEtiAIgiAIgiAIgiAIgiAIgiAIgiAIQrFlS8ru620sXLiQkSNH8vnnn+Pu7s7ChQupWrUqy5cvB+CXX35h3bp1svLLly+nWrVqLFiwAHd3dz7//HNGjBjBb7/9psqvtwDxDG1BEARBEARBEARBEARBEARBEARBEIT3zLZt27CysmLatGlUrlyZu3fv0rVrV0JCQgCoXLkyVatWlZUPDg6ma9eu/P7773z11Ve8ePGCb775hl27dpVoPcUJbUEQBEEQBEEQBEEQBEEQBEEQBEEQhPfQsmXLWLZsmcL3Pv/88wLTTp8+jZeXV0lXS444oS0IgiAIgiAIgiAIgiAIgiAIgiAIglBMEomWuqvwXhHP0BYKGDp0KDExMequhkaqVq0aEokET09PdVdFEARBEARBEARBEARBEARBEARBEMo8cYe2BnBwcGDGjBl06dIFa2trwsPD2bNnD7NmzSI6Olrd1ZPj7+/PzZs3GTduHABPnz5l0aJFLF68uFTr0bp1a06ePFlomWHDhsk96F7R/Obm5sTFxZVADd/N5RObOH/4HxJiI7C1d6XzwB+pVqOR0vLBjy7jt2Uur58HYGJuS/MuI2nc9hO5Mvev+nFi9xJiIkKwsKlKuz5jqeXVQfb+mYMreHDtKJHhQejqV8TRtQEd+n2HdWVnlcd27tA/JMZGYGPvSpdBRcT28DKHt8wl4nkAJhaFxxb9OgRL24KxAcTHvOLott94cuc0mRlpWNlV56Ph/6NK9Toqja84ThzaxuE9G4iNicTe0ZmBI76nhkcDhWVjoyPYuvZ3ggMf8jo8hHbdPmHQiO9Lucb/jWWLRjh/NwKzhnWoWMWWq33H8GrfcXVXqwCJRMKpfX9y7dQ2UpPjsXeuR9fB07C1dyt0vvtX/fDfk7tufdhnLLUayufflRObOO+Xu053+kR53u9fP43rp7bR6ZPJNO0wVGXxFcX3wF727NxKTHQUjtWqM+KLr6hdp57CshfOnebwwf08DQogIyODqtWq88ngoTTwalxq9S3M2SNb8D+whvjYCCo5uNJryCRc3JUPnRNw/wp7N/7Ky7AATC1s+bD75zTvMECuTEpSPAe3LuH2lWOkJMVjaWPPR59OwKNBqxKNRSKRcHKvfF52+7R4eVnYNh+K3tfcv3aEaye38uLZPVISY/GZsZvKVWuVSJzK+B7Yy+6d24iJjqJqteqM+GJMIXl5hkMH9/E0KPBNXlbjk8FDaSjyssSd9tvC8X1riY+NoLKDC32GTcK1lvLYnty/wu51vxIeFoiZhQ3tew6nRceP5cr4H9zA2SPbiIkMx8jUnPpNOtBz0Fj09CuUdDhF8j2wl107t8vycuQXY6hdp67CsufPneHQwf1yeTlw8JAyk5f5bT19nbXHLxEZn4hLZWsm9mlPQ1dHhWWvPHnGyCWbC0zfM2UUTpWsSrqq70QikXDj+F88urKNtJR4bBzr4d1zKhZ2yrepMa+ecP3YH0Q+v0di7AuadPuBOs1Lb/+szPu03hm17IhJu4/QMTMnIzyM2J1rSA98qLS8QaMWmLT/CF3bykhSkkl9cJO43evJTkosxVpLve/78ZOHt3J03zriYiKp4uhC/2ETcPNoqLBsXEwEO9YtICToAa/DQ2jbdSAffz6xVOurChbNG+E8bgRmDWpTsbIt1wZ8xav9Za/v8y7KS7+uKJrcH9fkNgpoVp81v/K8r8vv3JHNnMzT7/loyA84F9LvCbx/hX0b58v6PW27D8dbQb/Hd+ti7sj6PQ70/HQCtUq536NJsanj+GxWViYn9/zJ7Yv7SYyLxMTchvrNe9Oqx5doa6v2fk11tcGyMjM4sXsxT26fIiYijAoGxjh7eNO+33hMLexUGqMglGfiDu1yzsnJiatXr1KjRg0GDhyIq6sro0ePpl27dly4cAELCwul8+rp6ZVYvXR1y/a1EufPn6dSpUqy19atWzl06FCBaeXJ3cu+HN48h5bdRzN6xm6qujVi4+9fEBv1QmH5mIgw/v3dh6pujRg9Yzctu/twaNPP3L/qJysTGnCD7cvH4+ndk9Ez9+Lp3ZPty8cRFnhLVib40RUafziIkT9tZch3q8nOymTDwpGkpyWrLrZLvhzeNIdW3UczeuZuqtVoxMaFhce28XcfqtVoxOiZu2nZzYdD/yqIbdl46jXryZez9lKvWU+2LZOPLSUpjn9+Hoi2ri6fjl/JVz8foNMnk6hoaKqy2Irr8tkjbF69gO79hjNjwSbcPBrw++z/IyoiXGH5zMwMTEwt6N5vOI7Va5RybVVDx8iQ+NuPuPftLHVXpVDnDq3iwpG1dB08lVE/bcfY1IYNC4aTlqK8QxgacIMdK6T5N3qGNP92LB9HWFBu/t297MvhLXNo2W00PtOl6/S/i74gTkHeP7x+jOdBtzExty2RGJU5e8qf1X//Rf8Bg1n4x9941K7L7Gk/EPH6lcLy9+7exrOBF1NnzWHBkuXUqVefn2dOISjwSanWW5EbFw6xZ/1cOvQaxfdztuNcsyF/zx1NTKTidSzqdRgr54/BuWZDvp+znQ4fjWT3ujncunRUViYzM4Nlv4wiOuI5w8YuZPKCAwwYNRMzy5L/nWR5+elURk3djrGZDet/Kzovi9rmF2dfk5GWgqNbQ9r3+65EY1TmzCl//vl7Kf0HDOL3P1bgUbsus6ZNLjQv6zfwYtqsX1i4ZBl169Xn55k/ibwsYdfOH2bX2nl06jOKSfO241LLi2W/fEm0ktgiX4exfM5XuNTyYtK87XTsPYoda+Zw82JubFfOHGDfpkV06T+aKb/vZdDoWVy/4Me+TYtKKSrlzpzyZ9Xfy/h4wCAW/bEcj9p1mVloXt6hfgMvps/6md+XLKVuvfr8b+ZUAstAXuZ3+NoD5u86xqhO3myd9DkNXRwZs2wb4dGFX/S5d+oXHP/5a9mrqq3yfou63T69irvn1tKsx0/0HLMNA2NrDq8eQXpaktJ5MjNSMbF0pFGn8RiYWJdibZV7n9Y7g4bemPf9nHi/nbyaO5G0wAdYj5mCjoXi30Lf2R3LIf9H8oUTvPp5PFH/LES/qgsWg74s5ZpLvc/78avn/Ni+9le69BnJlF+34FqrAX/+8hXRSvo9GRnpGJta0KXPSByqlc9+D4CukQEJdx5yb/xsdVdF5cpLv64wmtwf1+Q2CmhWnzW/8r6vy+vGhUPsXT+Xdr2+YPycHTjVbMjKuT7ERCo+7hf1OoxV87/EqWZDxs/ZQbuPRrFn3S/cvnREViYzM50Vv4wkJuIFQ8f+zqQFB+k/akap93s0KTZ1HZ8967uKqye30O3TqXz9y0E69P+ec4f/4dKxjSqPUV1tsIz0VMKf3adVjzH4TN/JgK//IOpVMJuXjFF5jIJqSSRl96WJxAntcu6vv/4iPT2djh07cvr0aUJDQzl8+DDt27fH3t6en3/+WVb26dOnTJkyhTVr1hAbG8vKlSsB6RDjz549IykpiV27dmFlVfDOiO7du3P16lVSUlIIDAxk2rRp6OjoyN6XSCT4+PiwZ88eEhMT+emnn4qsu7+/P9WrV2fRokVIJBIkedayZs2acerUKZKTkwkJCWHx4sUYGhoWiGXdunUkJCQQHBxMz549sba2Zs+ePSQkJHD79m2lD6XPyMjg1atXsldKSgppaWmyv2NiYpg3b57svTNnztCokfSKqWrVqsnu7o6NjUUikbBmzRoAOnXqxJkzZ4iJiSEyMpL9+/fj7KzaO5WVueC3loYt++LVqj82VVzoMuhHzCwrcdW/4B0wAFdPbsHMqjJdBv2ITRUXvFr1p0HLPpz3Wy0rc/Hoelw8vGnZzQebys607OaDU62mXDyae+f6Z+NX0aBFH2zt3ahU1Z1ew+cQF/WCF8H3VBbb+SNradCqL16tc2MztazElROKY7viny+21tLYzh3Oje3CkfU41/amVXdpbK26++BcqykX8sR21ncVppaV6T1iDg7O9bCwdsDZoxmWtlVVFltx+e3bSMt2H9GqQ2+qODoxaMT3WFrZ4X94h8Ly1rZVGDRyAs3bdsfA0LiUa6saEX6neTx9ES/3HC26sJpIJBIuHVtPy26jqeXVEVuHGvQaMZeM9FTuXDqgdL5Lx3LXLes869alPPl38chaGrTsS8M363TngdJ1+spJ+byPj3mF76bZ9Bn1K9o6pXsx0d7d22nfsQsdOnfDsWo1Rvp8jbWNLYcP7lNYfqTP1/Tp/wluNdypYu/AZ8NGUrmKPVcuXSjVeity8uB6mrTtQ9MP+2Fn70LvoT9gblWJc0e3KCx//tg2zK0q0XvoD9jZu9D0w3580KY3/gfXyspc8t9FcmIcI75bgnPNhljaVMHZvSH21dxLNBaJRMLFo+tp1X00Hl4dsXOoQe9i5GVxtvnF2dd4en9Em55f4ezRrETjVGbv7h2079iFjrK8/AprG1sOHdyvsPxIn68U5uVlkZclyv/Aepp92Afvdn2p5OBM32GTsLCuxNkjii8oPHdkGxbWleg7bBKVHJzxbteXpm17c3z/WlmZp49v4VyzAY1adMPK1p5ant54Ne9CSND9UopKub27d9K+Y2c6du6KY9VqjPIZg7WNLb5K8nKUzxj69h8gy8shw0a82V5eLOWaF22D/2V6N/Okj7cnzpWsmdi3PZUsTNl29kah81kaG2Jtaix76aj47gpVkUgk3Du/Hs82PlSv0xHLSjVo3X8umRmpBN1Uvk21cajLB10m4OLZDR0d/VKssXLv03pn8mF3ki6cIPnCCTJfPSdu51qyYiIxatlRYXl9Jzeyol6TeOoQWVGvSQ96SOK5o+hVLZ2+XF7v+3782P4NNP+wNy3a96GygzMffz4RC6tKnDqyXWF5a1t7BgyfRNM2PahYTvs9ABFHzvB45mJe7S27fZ93VR76dUXR5P64JrdRQLP6rPmV531dfqcPruODtn1l/Z5eQydjblWZ80cVt1EuHNuKuVVleg2dnKff04eTefo9l/13k5wYz+ffLcFJ1u/xokop93s0KTZ1HZ8NC7xBzQbtqOHZBgtrB2o37oxL7ea8CL6r0vjU2QaraGjCkO9XU+eDLlhXdsbRpT5dB/9E+LN7Si8YEIT3Udk8aiAUi4WFBZ06dWLp0qWkpqbKvffq1Sv+/fdfBgyQH45kwoQJ3L17Fy8vL2bPns0HH3zA6tWrWbp0KfXr18ff37/AyeiOHTuyceNGlixZgoeHBz4+PgwbNowpU6bIlZs5cyZ79+6lbt26rF69mqL06dOH0NBQpk6dKrsrGqBOnTr4+fmxa9cu6tWrx4ABA2jRogV//vmn3Pzjxo3j3LlzNGjQgIMHD7JhwwbWr1/Pxo0badiwIQEBAaxfv77Y32de8+fPp2/fvgwdOlS2LD8/PywsLAgNDaVPnz4A1KhRg0qVKvHtt98CYGRkxMKFC2ncuDHt2rUjOzub3bt3o6Wl9U71KK7MzHRePLuHS+3mctNdajcnNEDxwcTQwJsFyrvWbsGL4HtkZWbklqmTr0ydFoQG3lRal9SUBAAMjMzeNgyFMjPTCQ++h6ui2AIVxxamKLY68rEpKuNSpwWhATdlfz+6eYIqTnXY+te3zP/Gm2XTe3P11DYVRPV2MjMyeBb4kNr1m8pNr12/KQEPb5d6fYRcsZFhJMZFyOWSrp4+1Ws2JkxJfoJ03XIukNO5+ZelZJ129mhOWJ51WpKdze5VE/HuNKLI4Y9ULSMjg8CAx9RvKD+0VP0GjXj4oHgXtGRnZ5OSkoKxiUlJVLHYMjMzCHt6n5r1vOWm16znTfDjWwrnCX5yq0B5d8/mhAblbmfuXT9JdTdPdqz5mak+rZg3oRdH9/xNdnZWyQTyRkyE8rxUtk+Aorf577KvKW3K89LrrfPSxKT0R+PIS9PyMq/MzAxCg+7j7pmvrvW8efropsJ5nj65hXu+2GrVb05I0H1ZbC7uDQkNuk9wwB0AIl+Fcv/GGWo3bKn6IN5CRkYGAQGPaZAvLxs08OLhg+Kd9JPmZbLat5f5ZWRm8SD0Jc3cq8tNb+ZenVtPnxc674B5a2g35Q9G/bGZy4+flWAt/5uEmDBSEiKxd8vd9uno6lPJqTGvQsrGtq843qv1TkcXPUdnUh/IbytTH9ymglNNhbOkBz1Cx9yKim+GD9Y2McOwfjNS710v8erm9z7vxzMzMggJekAtT/mT6bU8mxL0SPG+TxBKmib3xzW5jQKa1WctoJzv6/LKzEwvpN9zU+E8zxT0e2oW6Pf4U83Nk11r/sd0n1b8OuEjjpV6v0dzYlPn8dmqbl48vX+ByJdPAXgZ8pCQJ9epUU+1w6uXtTZYanICaGmpZaRQQSiryva40EKh3Nzc0NbW5sGDBwrff/DgAZaWltjY2BAREQHAiRMnWLBggazMrFmz8PPzY968eQA8efIEb29vOnfuLCszZcoU5s6dKzs5/PTpU6ZOncr8+fOZNSt3yKhNmzbJ7lQujpiYGLKyskhISODVq9yhfiZMmMCmTZtkz9UOCAjgm2++4dSpU3z55ZekpaUB4Ovry99//y2LY8yYMVy5coUdO6RXyM6bN4+LFy9iZ2cnt/yiGBoa8uWXXzJs2DAOHz4MwKhRo+jQoQMjRozgt99+kz2b/PXr13LP0N61a5fcskaMGEFERAQeHh7cu1d0Y1lfX58KFd7+WXPJCTFIsrMwMpO/u97I1IrEuEiF8yTGRWBk2kK+vJkV2VmZJCfGYGJuS2JcJEamipYZoXCZEokEv61zqermhZ2DaobVSk6IITs7q0A9jM2sSLyrPDZjs3yxmRaMzTj/MvPFFvM6lKsnNtOs0zBadfchLOg2h/79GV1dfeo376WS+IojISGW7OwszMzl62tqbkVcbFSp1UMoKCdf8ueSkamVwqHBc+dTkn/x0uXlrNMFyphZEZgn788eWom2tg5N2n/2n+J4FwnxcWRnZ2NuLj9ErJmFBTEx0cVaxt5d20hLTaV5yzYlUMPiS4qXbmdM8m1DTcysiFeyDU2IjVRYPjsrk8SEWMwsbIh6HcaTiOd4Ne/GF5OWEfHyGTvX/Ex2Vhad+pbcsG45eaRo+11UXha2zX+XfU1pi1eSl+ZvkZd7dm0nLTWF5i1bl0QVi03T8jKvQmNTsl+Lj40qMjav5l1IjI9m0dQhSIDsrExadBxAx14jSyqUYlGWl2YWFsS+VV6m0kLNeZlfTFIyWdkSrEyM5KZbmRgRGa94OG4bU2OmfdIZj6qVSM/M4sDlu3zx52b++WYQXq6lPwpOUVISpOubgbH88J0GxlYkxpafuyXep/VO29gELR0dshNi5aZnJ8SibWqucJ70p4+JXrcEy+Hj0NLTQ0tHl5TbV4jdVvSF2qr2Pu/HE9/0/UzNLOWmm5pZER9bNuoovH80uT+uyW0U0Kw+a37lfV+XV1K8dB0zNit4/CNByf4pPjaSmgrKZ2dlkpQQi+mbfk9AxCUaNu/OyEnLiHz5jF1r/kd2ViYd+5bOMM6aFJs6j8+26DqK1OQE/vyxK1raOkiys/iwz1jqNu2uouje1LcMtcEyMtI4tmMBdZt0p6JB2R7p432XraFDe5dV4oS2Bsu5KzjvUN5Xr16VK1OrVi12794tN+3ChQtyJ7S9vLxo3Lix3B3ZOjo6GBgYYGBgQEpKisJlvysvLy9cXV0ZPHiwXCw6Ojo4OTnx8OFDAG7fzr0SNueE9Z07dwpMs7W1fasT2i4uLujr63Pu3DnZtMzMTC5fvkytWrUKndfZ2ZnZs2fTtGlTrK2t0X4zdGLVqlWLdUJ78uTJzJgxo9h1zU+LfHeCS4BC7g4vcOe4RPZG4cvMP+0N342zeRX6iOGTNxWrvm8jf10lEgV1k59D2YKULlM6V+40iURCleq1ad9vPACVq3kQ8SKAK/6bS/WEdt7a5SWRSAr7eYUScPvifg6sny77e9C3y6X/UZCfRf44+eeRTsxfSOlyXwTf5dKxDfhM21nio0AUqsB2RFKs+pw+eZwt/67nx2mzCxxgUJeC27vCY8lfPmd/K9v/ZmdjbGrJx6NmoK2tg6NzbeJjIjhxYI1KTxzevrCf/XnycvDY5XL1kK904b9Ncbb5b7uvUQcFaVnMvDzxJi9nibwsBQXDkCjdfUvLK/hh80x/cu8KfrtW8vHIn6juVpeIl6HsXDOXw+bWdO43WnUVf0cK61+MvDx18gSb/93AlGkzy0xe5legnYbyn7K6nRXV7XIP5ng62fMyNp51xy+XiRPaATf3c27P/7N331FRXG8Dx79UC71aAFGKFBsK9t5jid3Ye43Jmxg1liT2JGqMmpj8jC323sDexRLFFruiCAqCovTeYd8/FhYWFlgNdb2fc/YkzN6ZuY/7zMy9U+4skP3dZeRfQN54pNtW2dr3KeNj2+7kqKnl+zI5zaqWGA4cQ8zJAyR730PdwAiDPiMwGjyRyF1/FWu1xHE8r7z7lPK5vQmqRnX746rcRgFUqs9aqDJ6rFOGon5Pgec0FZWXfiH9M7PfM1Cu3xOC57HNJXZBu8C6ltPYSuP87KObJ3jgdZT+k37FvLodbwOfcnLXz+gbmuPSqu971T+nstoGS09L5cDaaUgkEnqMmJ/ne0H4mIkL2uWYr68vGRkZODs7c/jw4TzfOzo6EhERQVhY9p0+8fHyT0oo04BTV1dn/vz5eZ4+BuSGOs+97A+lrq7OunXrWL16dZ7vXr16Jfv/1NTUPN/nnJZ1Alf9Pd/Hp+hGgKzpuafldvToUQIDA5kwYQJv3rxBXV2dx48fo62t3HvzlixZwsqVK+WmxcTEFDpfZT0j1NQ18tzVFR8bnucutyy6BmZ5y8eEo66hSWUdw8wypsTFKFimgfwTKgAndi7m2b0LjJm9AwPjqoXWWVmV9YxQVxRbTHieO9uyKBtb7rsh42LC0ckRm66hGWbV7eTKmFaz5cntMx8azgfR0zNEXV2D6FxPJcRGR6Cfz7+BUDwcGrTHcn592d9paSmA9G5MPUNz2fSEArY9yNy2FOSorr40/2TbdO7tLyZ7ua+e/0t8bDirZnaQfS/JSOfM3mVcP7uVqb9c+MAolaOnb4C6unqeO/ejo6IK7ez/c8mTP3//lZlz5tOgoWtxVlMpOvrS/Uzup15jYyLQy+d31DM0zVM+LiYCdQ1NdHSlr1zQNzRDXVMTdXUNWZkqFjbERoWRlpaKpqZWkdTfwaU9FjbZeZmeT17mzB9FCtvnf8ixpqTpZ+ZlZGSk3PToqMhC8/LKJU/++P1XZs2Zh4vIy2Iliy3XU00FHdf0DfM+nRebK7Zje/+kSZtPadGxPwDVa9QmJSmB3esX0aXfxPduExaV7Lx8//2lNC9XMGvO3DKRl7kZ6VRGQ12NsJg4uekRsfGY6OvkM1de9WtacPyWckN/FrcaTh0wt8q7T02IC6OyfvY+NSk+gkq6ZWPfp4yPabvLiItFkp6Oup6h3HR1XQMyYqMVzqPXpS/Jfs+IO5/5TtU3r4hKTsZ82mKij+0mIyaq2OorjuPZdDP7frmfeo2NjkDfsGzUUfj4qHJ/XJXbKKBafdbcytuxriA6+tJtLO85uvz7PfqGis7pZbVRDDPLmKGRq99jbmGb2e9JQVNTuXO1/4UqxVaa52fP7F1Oqx4TqNe0BwBVrByICnvDlePr/9MF7bLYBktPS2X/X98QFRrEqJlbxNPZgpCLeId2ORYREcHZs2eZMmUKFStWlPuuSpUqDBs2jL179xa4jCdPntCsmfx7gHL/fefOHRwcHPDz88vzKewCb2FSUlLQ0NCQm3bnzh3q1KmjcH2KLmIXNV9fX5KTk2nVKntIFE1NTdzc3GTDu6ekSA9wOetubGyMs7MzP/74IxcuXODp06cYGb3fHZwpKSnExsbKfZShqalNdes6+D25Jjfd7/E1rOwaKpzHytYFv8e5y1+les06aGSezFZY5tFVrGxdZH9LJBKO71iE979nGTVzC0ZmlkrVWVmamtpUq1knTz1ePLmGla3i2CxtXXiR69/CN1dslrYuvFAQv5Wdi+zvGnYNZe9nyRL+zh9Dk+ofGs4H0dTSwtrWkSf3b8hNf3z/BnaO9fOZSygOFSrpYlzFWvYxq26HroGZXL6lp6Xg/+wWlvnkJ0i3rdw5+iJH/mlkbtO5c/TFk2tYZm7T9Zv34vMFh5k831320TM0p8Un4xg+bWMRRZw/LS0tbO1qc+/uv3LT7939F0enOvnOd/nieVavWsa0b7/HrUmzfMuVJE1NLSxrOePzwEtuus9DL2rWbqBwnpr2DfB5KF/+2YNrWNlk72dqObgQ9vYVGRkZsjIhwf7oG5oV6UXDCpV0MaliLftk5WXOY0JaZl7md0yAwvf5H3KsKWlZeXn/vfPyAqtX/cL0b78TeVkCNDW1sLJx5umD3HX1opaDi8J5atk34Fmu8k/vX6OGjbMsttTkxDw3a6qpa2Q+0VB644BpaWlhl+/+0jnf+S5dvMDvq5Yz49vvaFxG8jI3LU0NnKyqcv2pv9z068/8aVDLQunlPA16h+l7XAAvTtoVdNA3sZZ9DM3tqKRnyhtf+WP925e3qFKjbOz7lPFRbXfpaaQGvqBirnZyRcf6JL98pnAWNW3tvE+0STL3k8X8CKY4jmfT1NKiho0T3rnyzvvBDWwcFB/7BKG4qXJ/XJXbKKBafdY8ytmxriCamtqZ/R7545PPw2vUrO2icB5r+wb4PJQvn7ff0zBPvydU1u8p/ovZoFqxleb52dSURNTU5C9jqamrI5Fk8F+UtTZY1sXs8JAARs7YTGXdcjIyxEdOIim7H1UkLmiXc19++SUVKlTg9OnTtG7dGktLS7p27crZs2d5/fq13DDhiqxevZpPPvmEb7/9Fnt7e7744gu54cZB+n7qkSNHMn/+fJydnXF0dOSzzz5j8eLF/7n+/v7+tGnThurVq2NiIr0jadmyZTRv3pw///yTBg0aYGdnx6effqrwie3ikJCQwF9//cXy5cvp2rUrTk5ObNiwgcqVK/P3338DEBAQQEZGBj179sTU1BQdHR0iIyMJCwtj4sSJ2Nra0r59+zxPWxen5l1Hc+fyAe5cOUjoGz9O7V5CdEQwbu0GA3DuwAoObZglK+/WbjDR4W84tWcJoW/8uHPlIHeuHKRF17GyMk07j8Dv8VX+ObGB0OAX/HNiAy+8vWjWeZSszPEdi2TDvmhX1CE2OpTY6FBSU7Kf3v+vWnTJjO2yNLaTu5cQHR5M4/bS2M7ul4+tcfvBRIW94dTuzNguH+Tu5YO0/CQ7tmaZsV05Lo3tyvENvHjiRfMcsTXvMpqgF/e5fGwt4e8CeOB1lH8v7qNJx+zh8EtK117DuXzOgyvnDvMm8CW7N60gIuwt7boOAODA9j/Y8Ps8uXlevXzGq5fPSEpKIC4mklcvn/E68EWJ1/1DaehURr+BI/oNHAGoXMsS/QaOVLSqVso1y6ampkbTTiO5cnwd3nfOEhLkg8emOWhpV6Re0+x3+bhvnMW5gytkfzftlL1theXYtprmyL9mXUZz58oB7mZt03syt+m20ryvrGuEuWVtuY+6hia6BqaYVrUpkfh79x3IudMnOHfmJIGvAvh7/f8IC31H1+6fArB98wZ++3WJrPzli+f5fcVSRo//HAdHZyIjIoiMiCA+Pi6/VZSYdj1Gct3zIDc8D/HutR/u25YRGRZMi06DADi2exU718yRlW/R6TMiw4Lx2P4L7177ccPzEDc8D9G+x+jsMp0HkRAXhfvWpYQE+/P4ziXOeWygVZfBxRqLmpoazTqP5MqxdXj/e5Z3QT54/J03Lw9tmMW5AznyUol9fmHHGoCEuCiCX3kT+sYPgPC3Lwl+5U1sjndgFafefQdwNkdebly/hrDQED7JzMttmzey6telsvKXL17gtxVLGTN+ssjLEtS+50i8zh/E64I7b4NecHDLMiLCgmnV+TMAjuz6jW1/ficr37LLZ0SEBXNo6y+8DXqB1wV3vC4couOn2bHVdW3HP2f38e/Vk4SFBPH0wTWO7/2Tum7t5J5eKA29+/bn7OmTnM2Rl6GhIXTLzMutufLy0sUL/LZiGWPHT8LB0alM5WVuI9o34ZDXfdy97vPibRjLD54jOCKGga2kJ2d+P3KR77cdlZXf4XmLC/d9CAiJwDc4lN+PXOTcvWcMblP2nn4C6T61TouR3L+4Hv/HZ4l468PlA9+hqVURG5fsfeql/bO4dTq77Z+elkL4G2/C33iTkZ5KQkwI4W+8iQkPKI0wgI9ru4u9cAydFh2p3Kw9mlUsMOg3Cg1jU+KvSEda0u81FKMRX8rKJz38l0ouTdBp1QUNE3O0bRwwHDCGFP/nZERH5reaYvGxH8c7fTqCq+fduXreg+CgF+zbvJzIsGDadJH2e9x3rmbz6h/k5gl8+ZTAl09JTkokNjqSwJdPeRPoVyL1LSoaOpXRq++IXn1p36eStSV69R2paFl2+j4fqjz06wqjyv1xVW6jgGr1WXMrz8e63Nr0GMWNHP2ew9uWEhkWTPPMfs/x3avYlaPf07zTICLDgjm8fZms33PT8yDtcvR7mmf2ezy2LiE02J8ndy5x3mMDLbsMEbF9oNI6P+vg0p4rx9bic/8ikWFBeP97Fq/TW3Bs1LlI4yvNNlh6ehr71nzNG/9H9J+wnAxJuuwce9bokIIgiCHHyz1fX1/c3NxYsGABe/fuxcTEhLdv3+Lh4cHChQvzDLmZ240bNxg/fjwLFy5kwYIFnDt3jh9//JG5c+fKypw5c4aePXsyb948Zs6cSWpqKk+fPmXjxv/+BOC8efNYt24dfn5+VKxYETU1NR4+fEjbtm356aefuHLlCmpqavj5+RX6tHlRmj17Nurq6mzfvh09PT1u375N165diYqKAuDNmzfMnz+fpUuXsnnzZrZt28aYMWMYPHgwq1ev5tGjRzx79oyvvvqKS5culUid6zbpTkJcFJeO/I+46FDMLewZNnUdhqbSp2Nio0OJjngjK29kZsmwb9ZxavdSbl3YhZ6hOd2Gfo+zW1dZmRp2jRgweQUXDv3OBffVGJtbMWDySixts++Ov+25G4Aty0bK1af32J9p2Kpf0cTWtDsJ8dLYYrNi+yY7trjoUKLD5WMbnhnbzazYhuWKzT47Nk/31RiZWzEwV2wWNvUY/OUfnDuwkkuH12BoZsknQ+dQv/mnRRLX+2jSqgtxsVEc2beB6MgwLGrYMvWH1ZiaS08CREeGERH6Vm6eBdOGyv4/wM+b65dPYWJWjeXrj5Vo3T+UgWtdmp/fLvvb+VfpCdbAbYd4MG5OfrOVuJbdxpOWmsSJHYtIjI/G0qY+I6b9TYUcwwJFR7yRe3rJyq4RAyat4IL773h6ZG5bk1ZiaZOdf3WbdCcxLopLR3Ns019n531Z0Kpte2JiY9i7axuRERHUqFmTuQuXYF5F+tqBiMgIQkNDZOVPnzxGeno669f8zvo1v8umt+/Ula+nzcqz/JLUsHk34mOjOX1oLTFRoVSzsmfirL8wNpOOyBATFUZkWLCsvIm5JRNmrsFj+y/8c2Y3Bkbm9B01hwZNsztURibVmDxnPR7bf2H5rH4YGJnTpttwOvYaV+zxtOw2ntSUJI7nzMvpCvJSPTsvldnnF3asAXh27wKHN2VfEDmwdhoAbXt9Qfs+/1ecYQPQum17YmNj2LtrOxEREVjXrMm8hUswr1IFgMjIcMIU5OW6NatZtyb75rkOnbqIvCxGri0+IT42ilMH1xITGUo1Kzs+n7NGFlt0ZKhcbKbmlkye8z8ObV3OldN70DcyZ8CYObg0y46ta/+JoKbGsT1/EB0Rgq6+EXVd29JzyFclGpsi2Xm5I0de/pwjLxXvL9eu+YO1a/6QTe/QqQtTp80s8foX5BNXJ6LjE1l/6iqhMfHYVTPlf58PpLqxdEjqsOg43kZmv0InNT2dlR4XCImOo4KWJrZVTflz8kBa17EtrRAKVb/NeNJTk7l2ZBEpiTGYWdan65iNaFfIfqo8LipY7smRhNhQPP7Mbgs/vLKJh1c2UbVWY3pM2Fai9c/yMW13iXeuEaWji363AWjoG5EaHEjYmp9Jj5QO9aihb4SmcfZQlgk3LqJWsSK6bT/BoN9IJInxJD17RPThnaVS/4/5OO7WsitxsVEcP7COmMgwqtew48vv/sQkR55G5MhTgJ++zb4g/+rFE279cxJjs2r8/NfJYq9vUTFoVJdmp7P3Dc6/SPs7QdvdeTCp7PR9PkR56dcVRJX746rcRgHV6rPmVt6PdTk1bN6NhNgozh76S9bvGT9rbY5+TyhRufo942f+xeHty7ia2e/pM+o76jftIitjZFKNiXM2cHj7Mn6d1RcDoyq07jacDiXc71Gl2Err/Gz3YT9wwX01x7YvIj4mHD1Dc9zaDaJt76J/X3hptcFiIt/y7J701YFrF/SRq9OomVup5di0yGMVhPJIjdIcf08QhEJJJBJ2X1XNzXRIS+nBf8811YtvcAtpbFeflL27eItCS2dpQ+64lkMp16To9UiVDs+16x/Vy8uhraR56e33upRrUjycbKUdgRN3iv/1FCWteyPpcFyqeDzIOhY89Qsq5ZoUD0db6as4VDkvz9xXvTvGuzSQDtX3zC+wlGtSPBxsrQBIOrO5lGtS9Cp2GQPALwf/2xCEZdHM/tIL5qq4zUH2dhf05cBSrknRs/xzP6Cax3HIPpZ7Pkws5ZoUvfb1KgFworJjKdek6HVPeAqoZp8Osvt1qtgnz+qPq2I7JauNoup9VlU+1h27k1bKNSl6PRtJnwlUxdggOz5VPj+rim2wIS3V8rz6Ryh5f58vu7k1rqPq5YcYclwQBEEQBEEQBEEQBEEQBEEQBEEQBEEok8QFbUEQBEEQBEEQBEEQBEEQBEEQBEEQBKFMEu/QFgRBEARBEARBEARBEARBEARBEARBUFJG2R1xXCWJJ7QFQRAEQRAEQRAEQRAEQRAEQRAEQRCEMklc0BYEQRAEQRAEQRAEQRAEQRAEQRAEQRDKJDHkuCAIgiAIgiAIgiAIgiAIgiAIgiAIgpIkYsjxEiWe0BYEQRAEQRAEQRAEQRAEQRAEQRAEQRDKJDVA3EMgCGWYRNzmIwiCIAiCIAiCIAiCIAiCIAhCJjU1tdKuwkdv/dmye+1mYmfVyw8x5LggCIIgCIIgCIIgCIIgCIIgCIIgCIKSMjJKuwYfF3FBWxDKgV3/lN07ff6Loa2kdwntvqp68Q1pKY3tuJZDKdekePRIfQbA1SdxpVyTotfSWRdQze0ua5tzv5leyjUpHn2baACwz0v1WpOfNZe+JUaV95ciL8ufrLxU5dhUPS9P3Ekt5ZoUve6NtADYfrmUK1IMRrSR/lcVtznI3u48HyaWck2KXvt6lQDwG9mjlGtSPGy3HQdg/3XVy82BzaR5qcr9HlWMDbLjU8U+eVZ/XBXbKVltFFWMDbLjU+VjnSq2U1S53wMfx/kGVY5NED4m4h3agiAIgiAIgiAIgiAIgiAIgiAIgiAIQpkkntAWBEEQBEEQBEEQBEEQBEEQBEEQBEFQkkT1Hv4v08QT2oIgCIIgCIIgCIIgCIIgCIIgCIIgCEKZJC5oC4IgCIIgCIIgCIIgCIIgCIIgCIIgCGWSGHJcEARBEARBEARBEARBEARBEARBEARBSWLI8ZIlntAuRaNGjSIyMrK0q/He5s+fz9u3b5FIJPTu3ZvNmzfj7u5e2tUqcS9fvuTrr78u7WoIgiAIgiAIgiAIgiAIgiAIgiAIgsoST2i/B0tLSxYsWEC3bt0wNTUlODgYDw8PFi1aRERERGlXT46npyft2rUDIDk5mYCAALZs2cKyZcvIyMj44OU6OjqyYMEC+vTpw/Xr14mMjMTT0xM1NTW5dd+7d49vvvmmVOqYn5EjR/LFF19Qp04dMjIyuHv3Lr/88gvHjx8v8nWVFolEwqUjf/LvpX0kJcRgYVOf7sPmYW5hX+B8T26fxtNjNZGhrzAyq0GHflNxatRZrsytC7u4dvpvYqNCMbewo+vg77Cu7Sb73uPv2dy/5iE3j4VNA8Z/v/eDY7l4WD6WHsOVi+WCe3YsHftNxclVPpabF3Zx7VR2LJ8MkY+lsHUnxEVx8fAf+D26SnTkWyrrGuHYsCMd+n5Nxcp6HxTvhzJu5YbN9HEYNKpLxerm3O4/hXdHzpdoHYrChZP7OOWxnajIMCysbBgybga1nRsqLBsVEcreLavw93tKSPArOvYYzNBxM0q4xtlKc7vL6ei2edy5tI+ug+fQrPOoIosvJ69zu7l8fBOx0aFUsbCj5/DZ1HJQXB+AF963OL5rGe9e+6JvaE6bHmNp1nGw7PtHt87ieXQ94e9ekZ6WhmnVGrTuNoZGrXoVS/1zunF+F/+c3ERc5r9tt6FzqFlALC+f3uTU7mWEvPZFz8icVt3G0aTDYLkyj2+d4bz7aiJCXmFsXoNO/b/GOcf+JzkxnvOHfufJnXPEx0RQzdqJ7kO/w9KmXpHHV9h+Ljf/Zzc5vWepND5Dc1p2G0/j9vLxFbZ/vXJ8Hd7/niUs+AWa2hWxsmtI5wHTMa1mU+Tx5STysvzkZW5FHe+718+5cOgP3vg/Jir8Dd2GzKZF1+LZHxZGlfJSkX/O7MHz2GZiokKpamlHn5GzsHV0zbe875NbHN6xnLdBvugbmdOh5xhadh4kVyYxPobje1fz4NY5EuNjMDazoPfwb3Fu2Ka4w5EjkUi4fPRP7l7eS1JCDNVrNaDb0HmYFXJc9/73NJcO/y7bR7br8w2OOY7rV0+s4+mdM4S/le4jLW0b0rH/DEyqFu8+MjdV3u5yu3hqL2ePbCU6MozqVrYMHP0t9s6NFJaNjgzlwNYVvHrhTUjwK9p3H8JnY2aWcI3fj37HHhh274eGgTGpr18RtnM9ST6P8y2v27wdhj36o1WlOhmJCSQ8+JfwPX+TERdbgrVW7Mb5XVw5sYm46FDMq9vRfVjheXly1zJC3kjbLa27y+flrYv7uHf1CO+CngNQvaYzXQZ8g6Vt/WKPpTDlud+jDFWPL7fy2h9X5XaKKsemiCod61SpjaJK/brSOLdQ2HrT01K54P47zx9cIjI0iAqVdLFxbkGnAdPQN6ryXvGV5fPPueu5c9VEfB9dYdCXf+LUqNN7xSkIqkI8oa2kWrVqcfv2bWrXrs2QIUOws7Nj8uTJdOzYES8vL4yMjPKdV0tLq9jqpamZ/z0J69evp2rVqjg4OLB69Wp+/PFHZsxQ3DlQto62trYAHD58mHfv3pGSkkJMTAzR0dHvX/n3rGNh1NXV5S6s57R8+XLWrVvHvn37aNCgAU2aNOHKlSscPnyYL7744oOW+V8V9Nt9qKsnN+J1Zgvdh81lwg/70dU3Y/uKsSQnxuU7T6DvXQ6sm0b95r2YvOAw9Zv34sDabwh6cV9W5tHNE5zas4TWPSYzab47Nezd2PnbRKLD38gty65ua6avvCL7DPt63X+PZfhcJszdj66BGdt+LTyW/Wun0aBFLyYvPEyDFr3Yv/YbgvxyxbJ7Ca17TmbyAmksO1ZNJCpHLIWtOzYqhNioELoMmsmURUfoM24Jvo+ucHjz9x8c74fS0KlMzINnPP56UYmvu6jc/OcMuzetoOeAsSxYsQt754asWvx/hIcGKyyflpaKnr4RPQeMxapm7RKubV6lvd0BPL1zjtcvHqBnaF4sMQLcv36SYzuW0L73JL5afJCaDq5sXj6JqLC89QGICAli86+TqengyleLD9Ku10SObv+Zh7fOyMpU0jWgfa9JTJm3i6k/u+Paph8HNnyPz4N/ii0OgIc3TnBy11LafjqJzxcdwrq2K9tXTpLbD+QUGRrE9pWTsa7tyueLDtGm50RO7PyZxzlieeV7l31/Sfc/XyzyoEGLXuxdM43AHPsfj80/4Pv4GgMmLuPLHw9jV6clW5aPJSbyXZHGp8x+Lnd8O1dNooa9G5MXuNO65yRO7vqJJ7dPy8oos3/1f3aLxh2GMv6HvYycvomM9DS2rxxPSnJCkcaXk8jL8pOXJRFvanISRmZWdB44DV0D02Ktf0FUKS8Vuet1Eo9tS+ncZwIzluzHxqER65dOJjJM8XE7PCSIDb9MwcahETOW7Kdz7/G4b13C/RtnZWXS0lL56+cJRIS+ZvTUlcxZcYxBExZiYFx8x7X8eJ3awI2zm/lk6DzGfn8AXQNTdq4aQ3JS/sf1IL+7HFr/DfWa9WbCvMPUa9abQ+un8jrHcT3A5yZu7YcxZs4+hn2zmYz0dHauGles+8jcVHm7y+321dPs37Kcbv3G8/3yPdg5NeTPn78gIp/2ZWpqCrr6RnTrNx5L69JvXxZGp2lrTIdNIPLIXoLmfUWizyOqzViIpomZwvIVaztjPmkasZfOEDhnCu/+XEJFG3vMxn5VwjXP6+GNE5zYuZR2n05iyqJDWDu4sm1F/nkZERrEthWTsXZwZcqiQ7TtOZHjO+Tz8uXTW9Rv1p1xs7cwae5uDE2qs+XX8cREFO+xrTDlvd9TGFWPT5Hy2B9X5XaKKsemiCod61SpjaJK/brSOrdQ2HpTU5IIDnhCm0+nMGn+QQZ9+Qfh7/zZvXrKe8dYls8/53T97FYopmsUwn+TISm7H1UkLmgr6X//+x8pKSl06dKFy5cvExgYyKlTp+jUqRMWFhb89NNPsrIvX77k+++/Z/PmzURFRbFhwwZAOsR4QEAA8fHxHDp0CBMTkzzr6dmzJ7dv3yYxMRE/Pz/mzZuHhoaG7HuJRMKkSZPw8PAgLi6OH374Id86JyQk8O7dOwICAvjf//7H+fPn6dOnD4BsmPDZs2fz+vVrfHx8AKhbty7nz58nISGBsLAw1q1bh46ODiAdavzYsWOyekgyXxCQc8jxzZs3065dO6ZOnSorY21t/UF11NLSYtmyZQQFBREXF8f169dp27atbN6sIdt79OjB48ePSU5OVriupk2bMmPGDL799ltWrFiBn58fT58+5YcffuC3335j5cqVWFpaFrhMMzMzjhw5QkJCAi9evGDo0KF51qOvr8+6det49+4d0dHRnD9/nvr1s+8Anz9/Pnfv3mXMmDH4+fmRnJyc77/Lh5BIJNw4t43WPSbj5NoFc8va9Bm3lNSUJB7eOJbvfDfObcPWuQWte0zCtJoNrXtMopZTM26c3Sorc/3MFhq27k+jNgMxq27LJ0O+w8C4Krcu7pZbloamNroGZrJPJV3DD47l+tlttOk5GWfXLlSxrE1fJWK5fjY7FrMcsVzPEYvX6S00at0f18xYug2VxnLbc7fS665iWZtBX/yBg0sHjM1rYOPUjI79vsHnvifp6WkfFPOHCj19GZ/5v/HW42zhhcuo00d20Lpjb9p07kt1q1oMHTcDY5MqeJ46oLC8qXl1ho7/lpbte1Kpsm4J11ZeWdjuYiLfcWLXYvpNWI66RvENvPLPyS24te1Pk3YDMLew5dPhczAwqcb183sUx3hhL4am1fh0+BzMLWxp0m4Abm37ceXEZlkZW6cm1HXrhLmFLSZVatCq6wiqWtXG3+dOscUBcO30Vhq16Ydb24GYV7el+7Dv0Deuys0LimO56bkHA5NqdB/2HebVbXFrO5BGrftx9dQmWRmvM9uwrdOCtj0nYlbdhrY9J2Lj1AyvM9sAaYfrye2zdP1sBjUdGmNSxZoOfb/EyNSSmxd2K1zvhypsP5fb7YvS+LoN/Q6z6ra4thlIw9b9uHY6Oz5l9q8jpm2kYat+mFvYU7WGI33GLiE6/A1v/PN/Wuy/EnlZfvKyJOK1tKnHJ4O/pX6zHmhqahdr/QuiSnmpyMXj22javh/NOgygioUtfUfNxtCkKlfPKo7v2rl9GJpUpe+o2VSxsKVZhwE0adcXz+NbZGVueB4iIS6acdNXY+PQCGOz6tg4NsLC2rGEopKSSCTcPL+NVt0n49ioC+YWtek1ZhmpKUk8KuC4fvPcVmycW9Cy+yRMq9nSsvskajo248a57H3k0Kl/06BlP8ws7Kli5cinY5YQE/GG4IDi20fmpsrbXW7njm6nZYe+tOrUj2qWNnw2ZiZGJlW5dGa/wvKm5hYMGjuLZu0+pWIpty+VYfhJX2IunSH20hlS3wQSvnMDaRFh6HforrB8BVtH0kJDiD57lLSwdyT5PCHa8xQVaxX89FFJuHpqK65t+uHWTpqXPYZJ2y0389ln3rqwB0OTavTIyst2A2nUph//nMzOy88mL6dpx6FUs3bCrLoNfcYuQpKRgd8Tr5IKS6Hy3O9RhqrHp0h57I+rcjtFlWNTRJWOdarURlGlfl1pnVsobL0VK+sxcsYm6jbphmk1G6xsXeg+7AeCAx7ne7FdkbJ+/jnL21dP8Tq9hd5jf0IQPnbigrYSjIyM6Nq1K2vWrCEpKUnuu3fv3rFz504GDZIfMu/bb7/l0aNHuLq6snjxYpo0acKmTZtYs2YNLi4ueHp65rkY3aVLF3bs2MHq1atxdnZm0qRJjB49mu+/l3/qc+HChRw+fJh69eqxadMmlJWYmCj3JHbHjh1xcnKic+fO9OzZk0qVKnHq1CkiIyNp3LgxAwcOpFOnTvz5558A/Prrr4wePRqAqlWrUrVq1Tzr+Prrr7l27ZrsyeuqVasSGBj4QXXcvHkzLVu2ZPDgwdSvX5/9+/dz6tQp7OzsZOUrV67MnDlzGD9+PHXq1CEkJCTPMocMGUJsbCzr1uV9WnjFihVoa2vTv3//Ape5ZcsWatasSYcOHRgwYABTpkzB3Fz+iZHjx49TtWpVunfvjqurK3fu3OH8+fNyT+/b2dnx2Wef0b9/f1xcXJT+d1FGVFgQcdGh2NZpKZumqaVNTYfGBPndzXe+QL972OSYB8C2TisCfe8BkJ6WwpuAx3LLBbBxbkmQr/xy/Z/dZPnUFvzxXVeObJlLfEz4B8USGZp/LIG+BcdiW1e+nnZ1WxHoJ40lLZ9YbOu0lC33Q9edlBhLhYq6aBTjBUVVlJaaSoDfU+q4NJObXselGb5PH5RSrZRX2tudJCMD940zadF1XKHDIf0XaWkpvPZ/gn09+frY121BwPN7CucJ8L2Hfd0W8uXrtSLo5WPS01LzlJdIJPg+9iI02L/AIeH+q7S0FN74P8Yuz76iZb7beKDvvbzl67XktX92LIG+97HLE29LXmUuMyM9nYyMdDS1K8iV0dKuQEARngxRZj+XW6DfvTzl7eq04k3O+ArZvyqSlCgdwrSSjsH7hqEUkZflJy9zK654ywJVyktF0tJSCXr5BIf68vV1qN8Cf5/7Cufxf34/T3nHBi0JfJEd3+M7F6lp34ADm39i7qQ2LPu2D2c91pORkV48geQj67huU6eVbJqmljbWtQs+rge9uIeNcyu5abZ1Whc4T3Ix7yNzU+XtLre01FRevfDGqUFzuelODZrx4pniPC1XNDSpUNOOxEfyv1vCwztUtHdSOEvSc280jU2pXF+6z9DQN0S3cUvi798q9uoWpKC8fJVPXr5SkJf2dQvOy9TkJNLT06ikWzLbmyLlvd9TGFWPT1WocjtFlWNTRJWOdarURlGlfl1pnVv4kPUCJCXEgpoaFSvrKxUflI/zzynJiRxYN53uw+eiZ6B4JB5B+JiIKy9KsLe3R11dHW9vb4Xfe3t7Y2xsjJmZGaGhoQBcuHCBFStWyMosWrSI06dPs2zZMgCeP39OixYt+OSTT2Rlvv/+e5YuXcq2bdK7q16+fMncuXP55ZdfWLQoe/iiXbt2sXlz9t2ChVFTU6NLly507dqV3377TTY9Pj6e8ePHk5oqPaCMHz+eSpUqMXLkSBISEnj8+DFffvklR48eZdasWYSEhBAVFQVIL+QrEhMTQ0pKiuzJ6w+to42NDUOGDMHS0pLgYOlQOStWrOCTTz5hzJgxsov82traTJkyhQcP8u8g1a5dGz8/P1mcOQUHBxMVFUXt2tlD7eRepr29Pd27d6dp06bcvHkTgHHjxvH06VPZPO3bt6devXqYm5uTkpICSG9q6NOnDwMGDJA9pa+trc2IESMICwtTWFdtbW0qVKig8LvCxEVLc09XX/7Jfx19E4VDFGfPF5ZnHl19E+JipMtLiI1EkpGet4yBCX6PsuOwq9cGZ7dPMDSpTmRYEJ4eq9m6fDQT5x1EU+v97oTMWrfOB8SiaJ6sf5usWHQMFJUJ++B1J8RFcvnoX7i2G6TweyF/sbFRZGSkY2Ao/++tb2hCdNSH3RBRkkp7u/vn5AbU1TVo2mnEf4qjMAmZv5NervroGZjgE614fxYXHYZerm1NT9+EjPQ04uOi0DeUNsSTEmL5+at2pKWloq6uTu9Rc7Gv10LRIotEViy6+vJDjunqmxBbQCx5fy9TMtLTSIiLRM/QPHP/I79MHX1T2b6lQiUdrOxcuHj4L8yq2aJrYMKD68cJevEA4yr5j2Ty/vEVvp/LG18oOvryF2J0DEwUxJf//jU3iUTC6b1LqWHvShXL4hnOTuRl+cnL3Ior3rJAlfJSkfiYSGl8uetrYEJMPvHFRimIL3MfExcbhYGRGeEhQTwPfY1ryx5MnPUXoW8DOLj5JzLS0+na//Niiye3rH1a3v2d6Qe1QeNj8t9Hnt23BCs7V8wtSmbIT1Xe7nKLi5Xmqb6Bsdx0fQMTYqIUx1qeaOjpo6ahQVp0lNz09JgoNAwUvwot2debd2uXU+WLWahpaaOmqUn8neuEbV9bAjXOnywvcw0Fq2NQULslLE87R9eg4Lw8s38F+kZVsHUu2X1mTuW931MYVY9PVahyO0WVY1NElY51qtRGUaV+XWmdW/iQ9aamJnPuwArqNe1JxUrKjz5QHs4/n96zBCu7hjg27Kh0XELJyhrFWCgZ4oJ2Ech6x3LO5L19+7ZcGScnJ9mw3Fm8vLzkLmi7urrSuHFjuSeyNTQ0qFSpEpUqVSIxMVHhsvMzZcoUxo8fj7a29GLi9u3bWbhwoez7hw8fyl3kdXJy4v79+yQkZL/H7erVq2hoaODg4KDw6ef/Kr869ujRA3V1ddlQ6FkqVKhAeHh2Zyg5ObnAi9nKUFNTk/vtci/TycmJ1NRUuX/3Z8+eERkZKfvb1dUVXV1duboBVKpUSfbecYCAgIB8L2YDzJkzhwULFihV7wfXj3Js23zZ30O/XpsVkFw5iSTvtDxyzyOdmLtQgcut2yR7eDtzy9pUr1mX32Z25PmDizi5dilw9Q+8jnI0RyzDpq7NrJaCehcSi1ruekvy1l1hmVzLVXbdSYlx7PxtMmbVbGnXK//3sQuFyZ1fkjL5apiytN298X/EjXPbmTTvoOJ8LQ554pQUsu7cMeaNUruiDl/9dIiUpAR8H1/n+K5fMDa3wtapSRFVWqmqSWPJ8++fs7ziWHIuKM+/Ra5lDpi4DPe/v2f5N21RV9egmrUz9Zr1JDjgyYdEUCBl9nNy5fPUXfZFwcvM59/sxI7FvAt8xtg5u5Sq738i8jK7fBnPyzyKId4yQ5XyUoG8+4OC48tdPqvtLetHZWSgq2/MZxMWoK6ugZVNHWIiQ7lwbHOxXtB+eP0IJ3ZkH9cH/1/WiE4Kfo9C00xRjIpnOrVrESFBPoyaWQL7yNxUebvLJXdOSute9uutvNwnz9QyG4t5aVW3wnT4JCIP7ybh4R00DI0xGTQWs9FfEvr378Vf1cLk/lkkkoLbLfnsUxT9vleOb+TB9ROMm70VLe0Pu3m8aJWPfs+HU/X4VIQqt1NUOTYFVOpYp0ptFBXq15XWuQVl15uelsqBtdOQSCT0GDE/z/c5lbfzz0/vXuCl9w0mLThUYF0E4WMiLmgrwdfXl4yMDJydnTl8+HCe7x0dHYmIiJC7UBkfHy9XRpmLDerq6syfP59Dh/LupHIOdZ572fnZuXMnP/30E8nJybx584aMjAy57xXVMb87SorrTpP86qiurk5aWhqurq6kp8sPNRgXFyf7/6yL/AXx8fGhVatWaGlp5XlKu1q1ahgYGPD8+fN8l6nohoXc1NXVCQ4Opl27dnm+y3qqHQr/7ZYsWcLKlSvlpsXExCgs69CgPZbzs9/RnZYmfTI8LjpM7k7EhNjwPHf65aRrYJrnDrf4mHDZ3YSV9YxQU9cgLkZRmfyXq2dojqFJdcLfBeRbRhaLS3ssbLJjSc8nlsLWqWtgmreeseGyO/5lseSON8e/ka6+mdLrTk6MY8fK8WhXqMyg//sTDU0thPejp2eIuroG0bnuII6NjkDfIP/furSUpe3u1fN/iY8NZ9XMDrLvJRnpnNm7jOtntzL1lwsfGGVelTN/p9x3FMfFROQbp66BqcLy6hqaVNY1lE1TV1fHNPOO4erWToS8ecHFoxuK7eRAVix59wMR6OaTc/n9XjljkZaRfxIvPjZc7o5cY/MajJuznZTkBJIT49AzNGfvmm8wMrUogsiklNnP5aZrYJZ/fDqGmWUK3r/mdGLnYp7du8CY2TswMM77epKiIvKy/ORlbsUVb1mgSnmpiI6+EerqGnmexo6NicjzRFQWPUPTPOWz4tPJHP5X39AMdU1N1NU1ZGWqWNgQGxVGWloqmsXUxqrt0gELmwayv9NTpcf1+Jhcx/WY8DxPxeSka2BKfK59ZEJshMJ5Tu1ajM/9C4z8dgf6xbiPzE2Vt7vcdPWMMtuX8jcbx0ZHoG9Y9tqX7ys9NgZJejqaBkYk55iuoW9AekyUwnmMPv2MpOfeRJ3IPNcQ6E9YchIWPywn4sA20qMjFc5X3GR5GZU7zwreZyqbl/+c2MSlY+sZM3MTVWs4FGnd31d56/e8L1WPT1WocjtFlWNTRJWOdarURlGlfl1pnVt4n/Wmp6Wy/69viAoNYtTMLYU+nV3ezj+/9L5OROgrln4pv6/Z97+vqFHblSFHdhQYryCoIvEObSVERERw9uxZpkyZQsWKFeW+q1KlCsOGDWPv3r0FLuPJkyc0ayb/LqHcf9+5cwcHBwf8/PzyfD7kgnJ0dDR+fn4EBQXluZidXx1dXFyoXLmybFrLli1JT0/P86R0QVJSUtDQ0Ci8YAF1vHv3Lpqampibm+f5t3ifocwB9uzZg56eHpMmTcrz3YwZM0hJSeHgwYP5zu/t7Y2WlhZubtnvx6ldu7bcu7Hv3LlD1apVSUtLy1Pf3E9tFyQlJYXY2Fi5T34qVNLFuIq17GNW3Q5dAzNePLkmK5OeloL/s1tY2jbMdzlWti5y8wC8eHwVKzsXADQ0taluXYcXj3OVeXINS7v8l5sQF0l0RDB6hoW/36NCJV1MqljLPlmx+OWoV1pmLFYFrNPK1gW/XPX0e3QVK1tpLJqZsfjlitfv8TXZco3MLJVad1JiHNtXjkNDU4shX61BS6ss3O1f/mhqaWFt68iT+zfkpj++fwM7x/r5zFV6ytJ2V795Lz5fcJjJ891lHz1Dc1p8Mo7h0zYWUcRSmpraWNR0xveRfH18H13D2t5F4TzWdi55yj9/eBXLWnUKvvlDIiEt84JCcdDU1KZ6zTp59xU59gO5Wdnl3bf4PrqKRc3sWKzsGuCbp8w1aihYpnaFyugZmpMYH43vw6s4Niq6oaOU2c/lpnDf+fgq1XPGV8j+FaQ3fh3fsQjvf88yauYWjMwsiyCi/Im8LD95mVtxxVsWqFJeKqKpqYVlLWd8HnjJTfd56EXN2g0UzlPTvgE+D+XLP3twDSub7PhqObgQ9vaVXH8gJNgffUOzYruYDVChoi7G5tayj6nsuH5VViY9LYUAn4KP65Y2LnLzALx48o/cPBKJhFO7FvHs7hlGTN+KkZlV0QdUAFXe7nLT1NKiho0T3rny1PvBDWwcFOdpuZKeRrK/L5Xqyv9ules2JOm54tekqWlXAIn8OQFJ1vZWio/PZuVlnmPVY8XHKoAadi4Kjm158/LKib/xPPIXo6avx6JW3aKv/Hsqb/2e96Xq8akKVW6nqHJsiqjSsU6V2iiq1K8rrXMLyq4362J2eEgAI2dsprKuEYUpb+efW/WYwOcLDzN5gbvsA9B18Gz6jF1SaLxCyZBIyu5HFYkL2kr68ssvqVChAqdPn6Z169ZYWlrStWtXzp49y+vXr+WGCVdk9erVfPLJJ3z77bfY29vzxRdfyA03DtL3bI8cOZL58+fj7OyMo6Mjn332GYsXLy7O0GR27txJUlISW7dupU6dOrRr144//viD7du3v9dw4/7+/jRt2hRra2tMTEw+aCjc58+fs2PHDrZt20bfvn2pWbMmbm5uzJw5k27dur3Xsq5fv85vv/3G8uXLmTZtGjY2Njg4OLB48WK+/vprpk+fTlBQUL7z+/j4cPLkSTZs2ECTJk1o1KgRGzdulBua/dy5c3h5eeHh4UGXLl2wtramefPmLF68GFdX1/eO/0OoqanRtNNIrhxfh/eds4QE+eCxaQ5a2hWp17SnrJz7xlmcO5j9fvemnUbg9/gq/5zYQFjwC/45sYEX3l407TxKVqZZl9HcuXKAu1cOEvrGj1N7lhAdEYxb28EApCTFc2bvMgJ97xIVFoT/0xvsXv05lfWMcGzY6YNiadZ5JFeOrcP737O8C/LB4++8sRzaMItzB3LE0jk7ltAcsTTLEUvzrqO5c/kAd7Ji2Z0ZS7vBSq87OTGO7SvGkZKcSO8xP5GcFEdsdCix0aFkZMiPKFDcNHQqo9/AEf0GjgBUrmWJfgNHKlpVK9F6/Bddew3n8jkPrpw7zJvAl+zetIKIsLe06zoAgAPb/2DD7/Pk5nn18hmvXj4jKSmBuJhIXr18xuvAFyVe99Lc7irrGmFuWVvuo66hia6BKaZVbYo81lbdRnPr4gFuXTpIyGs/ju5YSlR4ME07St8df2rvSvaunZ0dY4dBRIYFc2znMkJe+3Hr0kFuXzpI6+5jZGU8j6zn+cNrhIcEEvLmBVdObuHO1SM0bPlpkdc/pxZdR/HvpYP8e/kgIW/8OLFrCdHhwTRpL43lzP6VHFg/S1a+SfvBRIW94eTupYS88ePfywe5c/kQLT8ZKyvTvPNI/B5d4/LxDYS+ecHl4xvwe+JF8y4jZWWeP/yH5w+uEBkahO+jq2xaOhrTarVo1KpvkcZX2H7u3IEVHNqQHZ9bu8FEh7/h1J4lhL7x486Vg9y5cpAWXbPjU2b/enzHIh54HaX/pF/Rrqgj2y+mpmSPMlPURF6Wn7wsiXjT0lIIDvAmOMCb9PRUYiJDCA7wVmq0mKKkSnmpSLseI7nueZAbnod499oP923LiAwLpkUnaXzHdq9i55o5svItOn1GZFgwHtt/4d1rP254HuKG5yHa9xidXabzIBLionDfupSQYH8e37nEOY8NtOoyuERjU1NTo0nHkVw9sY6nd84S8tqHI5ulx/W6OY7rh/+eyYVD2cf1xh1H8uLJVa6dXE9YsB/XTq7npbcXTTtl7yNP7VrIw+tH6DN+BdoVdYiLDiWumPeRuanydpdbp09HcPW8O1fPexAc9IJ9m5cTGRZMmy7S9qX7ztVsXv2D3DyBL58S+PIpyUmJxEZHEvjyKW8C/Uqj+oWKOuWOftsu6LXpjFZ1K0yGTkDTxIyYCycAMB44CvOJ02TlE+7eRMe1BfoduqNpVpWK9k6YDp9Ekt8z0qMiSisMAFp+kisvd0rzsnGHzLzct5ID67LzsnEHaV6e2JWdl/9ePkSrbtl5eeX4Rs4d/J1+437C0NSC2KhQYqNCSU5SbrS74lKe+z3KUPX4FCmP/XFVbqeocmyKqNKxTpXaKKrUryutcwuFrTc9PY19a77mjf8j+k9YToYkXXb+IWskRWWU9fPPegZmVLGsLfcBMDCpXuwPEAhCWSWGHFeSr68vbm5uLFiwgL1792JiYsLbt2/x8PBg4cKFcu9TVuTGjRuMHz+ehQsXsmDBAs6dO8ePP/7I3LlzZWXOnDlDz549mTdvHjNnziQ1NZWnT5+ycWPRPmmXn8TERLp27crvv//OrVu3SEhI4ODBg0ybNq3wmXP49ddf2bp1K0+ePKFy5crUrFmTgID3byyMGTOGH374gRUrVmBhYUF4eDheXl6cOHHivZf1zTff8ODBAz7//HMWL16MRCLhzp079OnTh2PHjilVl40bN3Lp0iXevXvHDz/8kOdGg+7du/PTTz+xadMmzMzMePv2LZcvX37vJ8r/i5bdxpOWmsSJHYtIjI/G0qY+I6b9TYUcQ65ER7yRu8nAyq4RAyat4IL773h6rMbY3IoBk1ZimWP4xbpNupMYF8Wlo/8jLjoUcwt7hn29DsPMYWvU1DUIee3Dfa/DJCXEomdgRk3HJgyYvEpu3e8bS2pKEsdzxjJdQSzq2bHUsGvEgMkruHDody64Z8YyeSWWtvKxJMRFcelIjlimZseizLrfBDzm9Yv7AKyeLf9+8K9/OYeRack1Kgxc69L8/HbZ386/fgdA4LZDPBg3J7/ZypQmrboQFxvFkX0biI4Mw6KGLVN/WI2pufQkQHRkGBGhb+XmWTBtqOz/A/y8uX75FCZm1Vi+vvDtuaiV1nZX0ho060ZCXBTnPf4iNiqUqpb2jJ6xTjZ8VUxUGFHhwbLyxuaWjJmxlmM7l+J1bhf6huZ8OuI76jXO3mZSkhPx2LqI6Ih3aGlXwKyaDYMmL6NBs/e7cel91Wsq3Q9cPLyG2OhQqljYM2LaWtm/bVxUKNE5YjEys2TEtLWc3L2UG+d3oWdoTvdh31EnRyw17Bsy8PMVnD/4OxcO/YGRuRWffb4Cqxz7n6TEWM7uX0VM5Fsq6RhQx60LnfpPLfI7yAvbz8VGhxId8UYuvmHfrOPU7qXcuiCNr9vQ73F265odnxL719ueuwHYsiy7Uw3Qe+zPNGzVr0hjzCLysvzkZUnEGxsZypr52bl29dQmrp7aRE2Hxoybs61Y48lJlfJSkYbNuxEfG83pQ2uJiQqlmpU9E2f9hbFZdVl8kWHZ8ZmYWzJh5ho8tv/CP2d2Y2BkTt9Rc2jQtLOsjJFJNSbPWY/H9l9YPqsfBkbmtOk2nI69xpV4fM0/mUBqajKndi0kMT4aC5sGDP1mExUq5jyuB6Omln1vuJVdI/pNXMlFj9+4eHg1RmZW9Ju4Sm44838vSveR238dIbe+T0cvoUHL4tlH5qbK211ubi27EhcbxfED64iJDKN6DTu+/O5PTDLzNDoylIgceQrw07fZN1C8evGEW/+cxNisGj//dbJE666M+BtXCNPVx6j3EDQNjUkJCiB4xXzSwqXDkWoYGqNpkj1SVuw/51CrVAmDTj0xGTKOjIR4Ep88IHzf5tIKQSYrLz0PryE2KjsvjXK0W6IicuwzzSwZOX0tJ3Zl52WP4fJ5eePCbtLTUtn959dy62rf5ws69v2yZAJToLz3ewqj6vEpUh7746rcTlHl2BRRpWOdKrVRVKlfV1rnFgpbb0zkW57dk75mb+2CPnJ1HjVzK7UcmyodY1k+/ywIQl5qZL6yXhCEskkikbDrH9XcTIe2kjYGdl9VvfiGtJTGdlyrdN/VVlx6pD4D4OqTuEJKlj8tnaUNR1Xc7rK2OfebJTuSQEnp20T6uot9XoW/ZqO8+ay59MKJKu8vRV6WP1l5qcqxqXpenriTWso1KXrdG0lP2m2/XMoVKQYj2kj/q4rbHGRvd54PE0u5JkWvfb1KAPiN7FHKNSkettuOA7D/uurl5sBm0rxU5X6PKsYG2fGpYp88qz+uiu2UrDaKKsYG2fGp8rFOFdspqtzvgY/jfIOqxvYhI+MKReu3I2V3vzC1l+oN0K16EQmCIAiCIAiCIAiCIAiCIAiCIAiCIAgqQVzQFgRBEARBEARBEARBEARBEARBEARBEMok8Q5tQRAEQRAEQRAEQRAEQRAEQRAEQRAEJUlUbzT7Mk08oS0IgiAIgiAIgiAIgiAIgiAIgiAIgiCUSeKCtiAIgiAIgiAIgiAIgiAIgiAIgiAIglAmiSHHBUEQBEEQBEEQBEEQBEEQBEEQBEEQlJQhhhwvUeIJbUEQBEEQBEEQBEEQBEEQBEEQBEEQBKFMUgPEPQSCUIZJJGITFQRBEARBEARBEARBEARBEARBSk1NrbSr8NFb4ZFR2lXI1/Q+qvc8sxhyXBAEQRAEQRAEQRAEQRAEQRAEQRAEQUniWcSSJS5oC0I5sPuqau4Zh7SU3kWmivFlxeZ+M72Ua1I8+jbRAOCZX2Ap16ToOdhaAaqdlycqO5ZyTYpH94SnADz1CyrlmhQ9R1tLAPZcU728HNxCmpe32zYv5ZoUD7dLXoBq5+WtZ1GlW5Fi0NjBEIDjWg6lW5Fi0iP1GQDXn0aXck2KXjNHA0C1j+M3VfB3A2iS+dsleu4s5ZoUvUrthwGqmZeQnZsj5waXck2K3rbF1QDV7veoYmyQHZ8q9smz+uOq2E7JaqOoep9VlY91Xt4xpVyTotfcSR+AE3dSS7kmxaN7Iy1ANdspH8O5Z0H4mKjeM+eCIAiCIAiCIAiCIAiCIAiCIAiCIAiCShBPaAuCIAiCIAiCIAiCIAiCIAiCIAiCIChJkqF6T/+XZeIJbUEQBEEQBEEQBEEQBEEQBEEQBEEQBKFMEhe0BUEQBEEQBEEQBEEQBEEQBEEQBEEQhDJJDDkuCIIgCIIgCIIgCIIgCIIgCIIgCIKgJDHieMkST2gLgiAIgiAIgiAIgiAIgiAIgiAIgiAIZZK4oC38J/Pnz+fu3bulXY0SURSxtm3bFolEgoGBQRHVShAEQRAEQRAEQRAEQRAEQRAEQRBUlxhyXAVt3ryZ0aNHA5CamkpgYCCHDh1i/vz5JCQklG7lCtG2bVsuXryIoaEh0dHRhZafMGEC48aNo06dOqSlpeHr68uOHTtYv349iYmJJVDjbNbW1vj7++Pi4sL9+/dLZJ0SiYSLh//k30v7SEqIwcKmPj2Gz8Pcwr7A+Z7cPs0F99VEhr7CyKwGHftNxcm1s1yZmxd2ce3U38RGhWJuYccnQ77Durbbe607IuQVZ/b+wqvn/5KWloJd3dZ0H/YDugam5T62nGV3rpqI76MrDPryT5wadSo0NmV4ndvN5eObiI0OpYqFHT2Hz6aWg1u+5V943+L4rmW8e+2LvqE5bXqMpVnHwbLvH906i+fR9YS/e0V6WhqmVWvQutsYGrXqVST1/a9OHDvMoYP7iYwIp4Z1TcZPnEKduvUUlr129Qonjx/l5Qs/UlNTqWFtzZBhI2nk2riEay1VWD7l5v/sJqf3LCXktS96hua07Daexu0Hy5UpLI/9n93i2qm/eeP/mLjo0CLNvaJg1NINm2/GYdCwDhWrmfPvoC94d/R8aVfrvZ04dhj3g/tkeTlu4hTq1K2vsKzX1SucPH5ELi8HDxtVqnl59eTfxEWFYmZhR7ehheTl05uc2rOU0Ne+6BkVnJcRIa8wNs+blzcv7Oa2526iwl4DYGZhR7teX2Bfv03xBFkAsz79qDp4GFrGJiT6vyTwz9+Ie5D/sdmsT3/M+w2gQtVqpLx7S/COrYSfPlmCNVZeec5LZZw9cYATh3YQFRmORY1aDB//DY51Giose+uaJ+dPHiLgpQ+pqSlY1rCh35AJ1G/UrIRr/eGMW7lhM30cBo3qUrG6Obf7T+HdkfK3vzx/4gAn3LcTHRlO9Ro2DBv3DQ75/G5REWHs3vwb/r5PeRccSOeegxg2flqJ1LM0jtnKrHfBWEeF6+888Ftadhv3HyIu3LkTBzie+dtZ1LBheAG/3S0vT86fPMirlz6kpqZiWaMWfQdPoH6j5sVaxw+19+Ittp71Iiw6Ftvq5nw7sAuN7K0Vlr31zJ8Jq7blme6+YAq1qhbedylqpdUXSk9L5YL77zx/cInI0CAqVNLFxrkFnQZMQ9+oSrHFq0jf9rq0c6uMTiV1/IJS2HYshtchafmWd3OuyKdtdDA31kRTA96Gp3PyajzX7pfseYHClOd+jzJUKb6PrU+uiKq0UxRRlT5reT7WKeP8if2c9NhBVGQYFlY2DB03rcA25p7Nv+Hv58274EA69RjEsPHTS7jGiv1zZg+exzYTExVKVUs7+oycha2ja77lfZ/c4vCO5bwN8kXfyJwOPcfQsvMguTKJ8TEc37uaB7fOkRgfg7GZBb2Hf4tzw+Lvf6tyO0Wc4xPel0QMOV6ixBPaKurkyZNUrVoVGxsbfvjhB6ZMmcKvv/6qsKymZvm8r2H79u389ttvHD58mPbt2+Pi4sLixYvp3bs3Xbp0+eDllqd/j6snN+J1Zgvdh89lwtz96BqYse3XsSQnxuU7T6DvXfavnUaDFr2YvPAwDVr0Yv/abwjyyz7R/+jmCU7tXkLrnpOZvMCdGvZu7Fg1kajwN0qvOyU5ge0rxoGaGqNmbmHcd7tIT09l1+rPycjIKNex5XT97FZQUys0nvdx//pJju1YQvvek/hq8UFqOriyefkkosLeKCwfERLE5l8nU9PBla8WH6Rdr4kc3f4zD2+dkZWppGtA+16TmDJvF1N/dse1TT8ObPgenwf/FGndP8SVS55sXP8Xnw0aym9/rMW5Tj0WzptDaMg7heUfP3qIS0NX5i/6iVWr11Cvvgs/LpyLn9/zEq65cvmUU2RoEDtXTaKGvRuTF7jTuuckTu76iSe3T8vKKJPHqcmJVLFypPvwucUe44fQ1KlE7MOnPJ62uLSr8sGuXPLk7/VrGDhoKKv+WIdznXosKjAvH+DS0JV5i35m5eq/qFffhZ8W/sCL0sjLGyc4tWsJbXpOZvJCd6xru7FjZcF5uWPVJKxruzF5oTute0zi5E4FefnXNOo378Xniw5Tv3kv9v0ln5cGxlXoNGA6E+cfYOL8A9Ryasbu1V8Q8rpk/w2M2nfE6supBG/fwpMJo4h7cB/7ZSvRNlfcwTXr3RfLiZ/zZvNGHo0ayuvNG6kxdToGLVqVaL2VUZ7zUhnXr5xlx8ZV9PpsDD/+tg0HZxeWL/yGsNC3Css/fXyXui5NmDF/FT+u2opTPVdW/Dgdf79nJVzzD6ehU5mYB894/PWi0q7KB7tx5Sw7/17JpwPHsGjVdhycXVixaCrh+fxuqakp6Okb8enAMVjVLPikV1EqrWO2MuudvuqK3Kf3mJ9ATQ0n1w/v0yjj+pWz7Ph7Jb0HjmFx5m+3fNHUfLe5Z1nb3LzfWLxyK0713Fj503T8X5S9be707ccs33+a8d1asef7iTS0q8EXf+4iOKLgm6YPL/yCc8umyT41zI1LqMbySqsvlJqSRHDAE9p8OoVJ8w8y6Ms/CH/nz+7VU4o95px6tNbhkxY6bD8ew/y1YUTHZTBzlDEVtfPvd8UlZHDkUhyLN4Tz/Z9hXLmTwIS+BtSz0y7BmhesPPd7lKFK8X1sffL8qEI7JT+q0Gct78e6wtz45wy7NmW2MVfuoLazCysXf11wG9PAkE8Hji3RNmZh7nqdxGPbUjr3mcCMJfuxcWjE+qWTiQwLVlg+PCSIDb9MwcahETOW7Kdz7/G4b13C/RtnZWXS0lL56+cJRIS+ZvTUlcxZcYxBExZiYGxeIjGpajtFnOMThLJPXNBWUcnJybx7946goCB2797Nzp076dOnD5A9dPaYMWPw8/MjOTkZACsrKzw8PIiNjSU6Opq9e/dibi5/IJw1axZv374lJiaGjRs3UrFiRbnvPT09WbVqldw0d3d3Nm/eLPtbW1ubZcuW8erVK5KSkvDx8WHs2LFYW1tz8eJFAKKiopBIJHLz5TRw4ECGDx/OkCFDWLJkCbdv3yYgIIAjR47QoUMHPD09AXBzc+PMmTOEhoYSFRXFxYsXadhQ/k4+iUTCpEmT8PDwIC4ujh9++EGpWJXRrVs3nj17RkJCAhcuXKBmzZrvvYz8SCQSrp/dRpuek3F27UIVy9r0HbeU1JQkHt44lu98189uw9a5Ba17TMKsmg2te0yillMz6YXZTF6nt9CodX9c2wzErLot3YZ+h4FxVW577lZ63a+e3yEq7DV9xi2hiqUDVSwd6DP2Z968fMhL7+vlOrYsb189xev0FnqP/anAeN7XPye34Na2P03aDcDcwpZPh8/BwKQa18/vUVj+xoW9GJpW49PhczC3sKVJuwG4te3HlRPZ24+tUxPqunXC3MIWkyo1aNV1BFWtauPvc6dI6/4hDrsfpFOXT+jySXesalgzYdIUTM3MOXH8qMLyEyZNof/AQdjXdqS6hSUjR4+jWnULbt0oOK+KQ2H5lNvti3swMKlGt6HfYVbdFtc2A2nYuh/XTm+SlVEmj+3rt6Fjv6k4F/OJ7g8VeuYKPgt/593hs4UXLqMOux+gU5dudPmkB1Y1rBk/6QtMzcw5mU9ejp/0Bf0GDpbl5YjR46lW3YKbN7xKuOZw7cwWGrbpj2vb7LzUN67KrQuK8/KWZ668bCvNy6unsvPS68w2bOq0oE1PaV626TkJG6dmeOXISweXDtRu0BbTqrUwrVqLTv2/QbtiZQL9SmbUkixVPhtC2ImjhB0/SlJAAIF//kZKaAhmvfspLG/SpRuhRzyI9DxPSvAbIi+cI+z4MaoOGV6i9VZGec5LZZw8vJt2nXrRvktvLKxqMWLCNExMq3D+xEGF5UdMmEbP/iOwtXemavUaDBo5harVrLh760oJ1/zDhZ6+jM/833jrUX73l6cO76JNp16069KH6la1GDZ+GsamVTh/UvHvZlalOsMnTKdVhx5U1tEtsXqW1jFbmfXqGZjJfZ7eu0Atx6YYm1sV3z8IcPLwLtpm/nYWVrUYPj5zm8vntxs+fho9+43EJnOb+2xE5jZ3s+xtc9vPedG3ZUP6tWqETTUzZn7WlapGBuy/dLvA+Yz0dDA10JV9NNRL/pRJafaFKlbWY+SMTdRt0g3TajZY2brQfdgPBAc8zvdkbnHo2lyHI5fjuP0kidchaaw/GIW2lhrN61fKd56n/in8653Mm9A0QiLTOXM9gcB3adS2LjsXtMtzv0cZqhTfx9Ynz48qtFPyowp91vJ8rFPG6cO7aNOpN207Z7Uxp2NsWoULpw4oLG9WpTrDxs+gZfseVKpccm3Mwlw8vo2m7fvRrMMAqljY0nfUbAxNqnL1rOL9ybVz+zA0qUrfUbOpYmFLsw4DaNKuL57Ht8jK3PA8REJcNOOmr8bGoRHGZtWxcWyEhbXiUX+Kkiq3U8Q5PkEo+8rmEUsocomJiWhpacn+trOz47PPPqN///64uLgA4OHhgbGxMW3btqVz587Y2tqyd+9e2TwDBw5k4cKFfP/997i5uREcHMyUKe9/B9S2bdsYPHgwX331FU5OTkyePJm4uDgCAwPp1096srl27dpUrVqVr7/+WuEyhg0bxtOnTzly5IjC72NiYgDQ09Nj69attG7dmmbNmvH8+XNOnDiBrq58w2bhwoUcPnyYevXqsWnTpiKJ1dLSkkOHDnHixAlcXFzYuHEjS5cufa9lFCQyNIi46FBs67SUTdPU0qamQ2MCffN/13eg3z1s67aUm2ZXtxWBfvcASEtL4U3AY7nlAtjWaSlbrjLrTk9LATU1NDW1c5SpgJqaOq+e/1uuYwNISU7kwLrpdB8+Fz0DswLjeR9paSm89n+CfT35OtrXbUHA83sK5wnwvYd93Rby5eu1IujlY9LTUvOUl0gk+D72IjTYv8Ah00pCamoqvr4+NGwkX4+GDV156v1EqWVkZGSQmJiArp5ecVQxX8rkU26BfvfylLer04o3/tm/VWF5LBS/1NRU/Hx9cMmVly4NXXnq/VipZUjzMhE9Pf3iqGK+0tJSCPZ/jJ2ivPRTnJdBivKyrnxeKipjW7cVgb73FC4zIyOdhzeOk5KcgJWty4cF8wHUNDXRqe1AzK2bctNjbt1AN5/hLtW0tMhISZGblpGcjI6TM2oaGsVW1/dVnvNSGWmpqbz0fUrdhk3lptdt2ITnTx8qtYyMjAySEhPQ0TUojioKCqSlpuLv95S6Lrl+N5em+D59UEq1yqu0jtkfst646DCeP7hEw9b9lY7vQ2T9dvUU/HbPlfztsrY53TK2T0lNS8f7VTDNnWzlpjdzsuH+i8AC5x3803o6zVzJxFXbuPXsZXFWM1+l2RdSJCkhFtTUqFi5ZH5nMyMNDPU0eOSbLJuWlg7P/FOwr6FVwJzynG20qWaqwVP/lMILl4Dy3O9RhirF97H1yYXyqbwf6wpTXtqYhUlLSyXo5RMc6svvHxzqt8DfR/GN3/7P7+cp79igJYEvsvcnj+9cpKZ9Aw5s/om5k9qw7Ns+nPVYT0ZGevEEkoOqtlPEOT7hQ2VkSMrsRxWVn7GVhQ/WuHFjhg4dyvnz2e+C0dbWZsSIEYSFhQHQqVMn6tevT61atQgKCgJgxIgRPHnyBDc3N27fvs3UqVPZtGkTf//9NwBz586lU6dO7/Xksr29PYMGDaJTp06y+rx8md14ioiIACAkJKTAd2jb29vz7FnhQ9tlPamdZdKkSURGRtK2bVuOHz8um75r1y65p8F37979n2P9/PPPefHiBd988w0APj4+1KtXj9mzZ+c7j7a2NhUqVFBq+XExoQDo6JvITdfRNyG6gLvS4qLDFM4TFy1dXkJsJJKMdHQMFJUJU3rdljYuaFeoxNn9v9Kx/zeAhLP7f0UiyZCtq7zGBnB6zxKs7Bri2LBjgbG8r4TYKDIy0tHLtX49AxN8MuuYW1x0GHq5YtLTNyEjPY34uCj0DaUX3JMSYvn5q3akpaWirq5O71Fzsa/XQtEiS0xMTDQZGRkYGhrJTTcwMiIqMkKpZXgc2k9yUhKtWrctjirmS5l8yi0uOhQdfflhjHUMpL9VQlwkeobmheaxUPzyy0tDIyMi3ysvE2lZCnmZkZGeJ4d0DUyIe5R/Xuoa5MpL/bx5qZt7mQry8l3gMzb+NIS01GS0K1Rm8Jd/Ym5hVwSRKUfTwBA1TU1SI+R/p9TISLSMFQ+lF3PrBqY9PyXqn0sk+DyjsoMjpt17oq6lhaaBIakR4SVR9UKV57xURmyM9PhnYCj/OxkYmBAVpdyTWic8dpKcnEjTVkV7bBbyl/27ye8fDAyNiY4sG9sOlN4x+0PWe++aB9oVdYp9uPGs307/P/x2JzO3uSYty9Y7/iLjEkjPkGCsryM33URfh7CYeIXzmBnoMndYT5ytq5GSlsax6w+Z+Nt2Nk4bhWs+7yItLqXZF8otNTWZcwdWUK9pTypWKpmn3Qx0pc9dRMfJv6YqOi4DU8OCbzSrVEGN3781R1NTjYwM2HYsmsd+ZeOCdnnu9yhDleL72PrkQvlU3o91hYmNzWqnyPcN9A1MylQbszDxMdL+eZ79g4EJMfnsT2KjFOxPMtugcbFRGBiZER4SxPPQ17i27MHEWX8R+jaAg5t/IiM9na79Py+2eEB12yniHJ8glA/igraK6tmzJ7GxsWhqaqKlpcXhw4f5v//7P9n3AQEBsovZAE5OTgQGBsouZgN4e3sTGRmJk5MTt2/fxsnJibVr18qtx8vLi/bt2ytdLxcXF9LS0rh06dJ/iA7U1NSQSAq/y8TMzIxFixbRoUMHqlSpgoaGBpUrV6ZGjRpy5W7flh+OpyhidXJy4vp1+ROwXl4FD/E5Z84cFixYoPC7B15HObptvuzvYVOl9VNT9P7mQt7prEau7yXSqYWWybXcgtato2/MwM9/4/j2hdw4vx01NXXqNe1BNWtn1NTlT0SUt9ie3r3AS+8bTFpwqMC6/Ce51i+RSBTXKXsG+fLSwOWmalfU4aufDpGSlIDv4+sc3/ULxuZW2Do1KaJKf7g8sUkkSr2b/NLFC+zeuZ3v5y3Mc/KkpCiTT3Ll88Qq+6LgZeaeJhQ7xWlZ+O9w+eIF9uzcxnfzFpVeXubZhyjIK/k58ltQvsuUziU/zaRaLSYvdCcpIYYnt8/gvnE2Y2ZvL9GL2lLybQQ1pP8GirzZuhktYxMc/9qIGtKL32GnjlNt6AgkGRmKZypF5TkvlZE3FkkhuSt17dJp3Hdv5Jvvl+e5KC4Uv7x5WVi7pXSU1jH7fdZ798pB6jfriZaWcje5/lcf+tt5XT7NoT0b+Oa7X8vsNqdwf5lP2ZpVTalZ1VT2dwMbK95FRrPtrFexn+Qvi30hgPS0VA6snYZEIqHHiPl5vi8qzetXZEyv7JE1VuyIlFYr13FbTS27j5OfpBQJP6wJo6K2Gs42FRjyiT4hEell5iltKN/9HmWoVHwfWZ9cKJ/Ky7HuQ+U+ZklQbp9S1uQ99ha8P8kTd+ZBMWseSUYGuvrGfDZhAerqGljZ1CEmMpQLxzYX+QXtj62dIs7xCULZJi5oqyhPT08+//xzUlNTefPmDWlpaXLfx8fL362X3wViZS8cZ8nIyMizI8851HliYqLSyyqIj48PTk5OhZbbsmULZmZmTJ06lYCAAJKTk/Hy8kJbW/49Wrn/PYrCh5zEW7JkCStXrpSbljV8uoNLeyxs6sump6dJO+Vx0WHoGWa/6zw+JjzPU3Q56RqYEhcjf2dZfGw4ugbSRm1lPSPU1DXy3H0WH5u9XF19M6XWbVe3FV8vO0t8bCTqGhpUqqzP8qmtqGtqKbfs8hbbS+/rRIS+YumX8p3Off/7ihq1XRkza3u+dSxMZT1D1NU1iM1Vx7iYiHxj1zUwVVheXUOTyrqGsmnq6uqYVpF2UqpbOxHy5gUXj24o1c6zvr4B6urqeZ4ujI6KKvRExpVLnvzx+wpmzZmLS0PX4qymQsrkU266BmZ5y8eES38rHcPMMgXnsVD8svMyUm56dFSkknn5K7PmzCu1vFRXlJcx4XnuNM6ibF7m3c+Eo5MrLzU1tTHJ3M9Y1KrHG/9HXD+7jV6jF/2XsJSWFh2FJC0NLWP5WDWNjEjL5+kgSUoy/st+IuDXpWgaG5MaHo7Zp71Jj48nLTqqBGqtnPKcl8rQ05ce/6JyPXERHR1R6MWy61fOsvGPn/i/WT9T10WcEC5J+f1uMdGReZ6oKU2ldcx+3/UG+Nwm/O1LBk5e9V7xfYis3y73U07K/HbSbe5H/m/WkjK5zRnpVkZDXY3waPk+XkRsPCa5nmQrSL1alpy4qdwrD/6LstQXyq5DKvv/+oao0CBGzdxSrE9n332ajF9Qdp20NKX9aEM9dbmntPV11ImJK/hGM4kEQiKkw62+eptGdTNNPm2jy1N/5Z4QLk7lud+jDFWK72PrkwvlU3k71r0vvcztMDpKvp0Sq0TfoCzR0Zf2z3M/jR0bE5FnFIgseoamecpn7U+yXq2kb2iGuqYm6jkeGKpiYUNsVBhpaaloair/io7CfCztFHGOT/hQ73HpTCgC4h3aKio+Ph4/Pz9evXqV52K2Ik+ePKFGjRpYWmZfaHRycsLQ0BBvb29A+sR2s2bN5ObL/XdoaCjVqlWT/a2urk7dunVlfz98+BB1dXXatlU8hFRK5jssNQp5Z+WuXbtwcHCgV69eCr/X15e+N6N169asXr2akydP8uTJE5KTkzEzK/x9x8rEWpgnT5689zJSUlKIjY2V+2SpUEkXkyrWso9ZdTt0Dczwe3JNViYtLQX/Z7ewsmuY7zqsbF3we3xNbprfo6uyd5xqampT3bqO3HIB/B5fky3XyMzyvdato2dEpcr6vPC+TnxsOA4u8k+6l7fYWvWYwOcLDzN5gbvsA9B18Gz6jF2Sb/2UoampjUVNZ3wfydfR99E1rO1dFM5jbeeSp/zzh1exrFUHjYIasRIJaaml+7SClpYWdna1uXdX/r3q9+7+i6OTc77zXbp4gd9XLWfGt9/RuMn7bZtFRZl8yk1hjj6+SvWa2b9VYXksFD8tLS1s7WpzX2Fe1sl3vssXL7B61S9M//Y73EoxL6vVrJMnh148uYaVreK8tLR14UWuPPbNlZeWti68UJC7VnYuBdZHIpHIOrwlQZKWRrzPM/TdGstN13drQtyjgk/USNLTSQ0NhYwMjDt0JsrrapnqmZTnvFSGppYWtewceXRP/v3nj+7dxN5R8fvPQfpk9rrfFzNlxmIaNm6VbzmheGhqaVHT1pHH9+V/t8f3bmLnWD+fuUpeaR2z33e9d64coJp1HarWcHyv+D5E1m/36L6ibS7/387r8mnWr17E59MX4+JWNrc5LU0NnGpUw8v7hdz0G94vaGBjpfRyngW+xdSg+IfZLkt9Icg+SRweEsDIGZuprFu8T8smpUgIiUiXfV6HpBEVm04d2+xRCjQ0wKGmNs9f5X0XcUHU1ECzjDzGUZ77PcpQpfg+tj65UD6Vt2Pd+5K1Me/dkJte1tqYhdHU1MKyljM+D+RH7PR56EXN2g0UzlPTvgE+D+XLP3twDSub7P1JLQcXwt6+IiPHiGIhwf7oG5oV6cVs+HjaKeIcnyCUD+KCtgDAuXPnePDgATt37qRhw4Y0btyYbdu2cfHiRf79V9oh+f333xk7dixjxozB3t6eBQsWUKeO/AnUCxcu0KNHD7p3746DgwNr1qzB0NBQ9n1AQABbt25l06ZN9O7dm5o1a9K2bVsGDhwo+z4jI4OePXtiamqKjo7iuwr37dvHnj172L17N7Nnz8bV1ZUaNWrQo0cPzp07Jxsa3NfXlxEjRuDo6EiTJk3YuXMnCQkJhf57KBNrYdauXYutrS0rVqygdu3aDBkyhNGjR7/XMgqipqZGs84juXJsHd7/nuVdkA8ef89BS7si9Zr2lJU7tGEW5w6skP3dtPMI/B5f5Z8TGwgNfsE/JzbwwtuLZp1Hyco07zqaO5cPcOfKQULf+HFq9xKiI4Jxazf4vdZ998pBAv3uERHyivteR9i/5muadx6FaTWbch2bnoEZVSxry30ADEyqY2Qm//T5h2jVbTS3Lh7g1qWDhLz24+iOpUSFB9O04yAATu1dyd612e9ib9phEJFhwRzbuYyQ137cunSQ25cO0rr7GFkZzyPref7wGuEhgYS8ecGVk1u4c/UIDVt++p/r+1/17tufs6dPcvbMSQJfBbBx/RpCQ0Po1l1at62bN7Lq16Wy8pcuXuC3FcsYO34SDo5OREZEEBkRQXx8XInXvbB8OndgBYc2zJKVd2s3mOjwN5zas4TQN37cuXKQO1cO0qLrWFkZZfI4OSme4FfeBL+S3nAUFRZE8Ctvogp4X1FJ0tCpjF59R/TqS0/IV7K2RK++IxUtqxUyZ9nRu+8Azp4+wbkceRkWGsInmXm5LVdeXr54gd9WLGXM+Mk4ODqXal626JKZl5eleXly9xKiw4Np3F6al2f3y+dl4/aDiQp7w6ndmXl5+SB3Lx+k5SfZedksMy+vHJfm5ZXjG3jxxIvmOfLy3IGVBPjcJjIsiHeBzzh3cBX+T29Sv3nJ7mfe7duNaY9emHTvSUVra6y++Bpt8yqEHpHefGQx4XNqfjdPVr6CpRXGnbtSwcISHUdnbOYtolItG15v+KtE662M8pyXyujWewgXzx7m0tkjvA58yY6NqwgPfUfHbv0A2Lv1f6xdtUBW/tql06z7bSFDx36FnUNdoiLDiYoMJ6GMxqeIhk5l9Bs4ot9Aur+sXMsS/QaOVLQqP/vLT3oP5dLZw1w+d4Q3gS/ZuXEl4WFv6fCJ9Hfbt+1/rFslPwxgwAsfAl74kJSYQGx0JAEvfHj96oWixReZ0jpmF7beLEmJcTy5dZpGbQYW679DTt16D5Vuc+eytjnpb9cx87fbu+1/rM3x23ldPs263xYwdMzXmdtcGFGRYWVymxvRqTnuV+/gcfUuL4JDWb7vNMGR0QxoI336c7X7eX7Y7CErv+P8dS7ce0rAu3B834Sw2v085+56M7hd43zWUHxKsy+Unp7GvjVf88b/Ef0nLCdDkk5sdCix0aGkleANaqe94vm0jS6uThWwMNdkYj9DUlIleD3IHvFtYn8DBnbWk/3ds40OdWy1MTPSoJqpBp+00KGlSyWu3S+aUeKKQnnu9yhDleL72Prk+VGFdkp+VKHPWp6Pdcro2nsol85ltzF3/S1tp7Tv2h+A/dv/ZP1vuduYzwh48YzkpERiYyIJePGM14HF28YsTLseI7nueZAbnod499oP923LiAwLpkUn6f7k2O5V7FwzR1a+RafPiAwLxmP7L7x77ccNz0Pc8DxE+x6js8t0HkRCXBTuW5cSEuzP4zuXOOexgVZdBudefZFT5XaKOMcnCGVfGblXVSgL+vTpwx9//MHly5fJyMjg1KlTcu/d3rdvH7a2tixbtoyKFSty8OBB/vrrL7p27Sors2nTJho0aMC2bdtIS0tj1apVeHp6yq3n888/5+eff2bNmjWYmJjw6tUrfv75ZwDevHnD/PnzWbp0KZs3b2bbtm2MGTMGRYYOHcrEiRMZO3YsP/zwA2lpaTx//pxt27Zx+vRpAMaOHcv69eu5e/cur1694rvvvuPXX38t9N9CmVgLExgYSP/+/Vm1ahVTpkzh5s2bfPfdd2zevFnpZRSmZbfxpKYkcXzHIhLjo7G0qc+I6X9TIcdQK9ERb1BTzx7+vIZdIwZMXsGFQ79zwX01xuZWDJi8Ekvb7DsD6zbpTkJcFJeO/I+46FDMLewZNnUdhqYW77XusLf+nDu4isT4aAxNq9O652SadxmtErEVpwbNupEQF8V5j7+IjQqlqqU9o2eswyizjjFRYUSFB8vKG5tbMmbGWo7tXIrXuV3oG5rz6YjvqNe4i6xMSnIiHlsXER3xDi3tCphVs2HQ5GU0aNatRGIqSOu27YmNjWHvrh1ERERgXbMm8xb+jHmVKgBERkYQGhoiK3/65DHS09NZu+YP1q75Qza9Q6cuTJ02s0TrXlg+xUaHEh2R3QA1MrNk2DfrOLV7Kbcu7ELP0JxuQ7/H2S1736JMHr/xf8TWX7Ibv6f3SE8MNWjZh77jsk8SlRaDRnVpdnqb7G/nX6Sds6Dt7jyYNCe/2cqU7LzcniMvl+TIy3DCFOTlujWrWbdmtWx6h05d+HrarDzLL051m3YnIV6al7FZeflNdl7GRYcSHS6fl8Mz8/JmVl4Oy5WX9tl56em+GiNzKwbmysu4mHAOrZ9JbHQoFSvpUcXKgRHTN2Bbp2XJBQ9Eep5H08CA6iPHomViQuLLFzyfNZ2Ud28B0DIxoYJ5FVl5NQ11qg4aSgWrGkjS0oi9+y/eX0wk5e3bEq23MspzXiqjWevOxMZG4753E1ERYVha2/DtvFWYmktPLEZFhhMW+k5W/sJpD9LT09m6djlb1y6XTW/doQeTps7Ls/yyyMC1Ls3PZ7+qxPnX7wAI3HaIB+PKx/6yaevOxMVGc3jv30RFhGFhbcu0HL9bdGQYEWHv5OaZ981w2f/7+z3F6/JpTM2rsWLD4WKrZ2kds5VpewI8unEcCRLqNe1RbP8GuTXL/O08Mn87S2tbZshtc2GEh+Xc5tyl29y6X9i67hfZ9FYdejDp6+J7x/KH6OpWh6i4BNYdv0xYTBx21c3588uhVDcxBCA0Oo7giGhZ+dS0dFYdPEtIVCwVtDSxrW7GH18MoXU9+1Kpf2n1hWIi3/Ls3gUA1i7oI1enUTO3UsuxaTFGne34lXi0NdUY9akBlSuq8yIohV+2RpCUkj1yiomBBpIcI5BX0JKWN9bXICVVQnBYGusORHHjUVKJ1FkZ5bnfowxViu9j65PnRxXaKflRhT5reT/WFaZpqy7ExURzeO9GoiPDsKhhy7S5v2W3UyLCCA+V77PNn5azjenN9cunMTGrxooNR0q07jk1bN6N+NhoTh9aS0xUKNWs7Jk46y+MzaoD0v1JZFj2/sTE3JIJM9fgsf0X/jmzGwMjc/qOmkODpp1lZYxMqjF5zno8tv/C8ln9MDAyp0234XTsNa5EYlLVdoo4xyd8iDI0sN9HQY3sV9ULglAGSSQSdl9Vzc10SEtpw0YV48uKzf1meinXpHj0bSJ9LcAzv8BSrknRc7CVDs+lynl5onLxD2VaGronPAXgqV9QKdek6DnaSkd/2HNN9fJycAtpXt5u27yUa1I83C5Jh4tT5by89SyqdCtSDBo7GAJwXMuhdCtSTHqkPgPg+tPoQkqWP80cpe8WVOXj+E0V/N0AmmT+domeO0u5JkWvUvthgGrmJWTn5si5wYWULH+2LZZeOFHlfo8qxgbZ8alinzyrP66K7ZSsNoqq91lV+Vjn5R1TyjUpes2dpK+2PHHn/V59UV50byQdHlsV2ymqfu5ZTU2t8IJCsfpxd+Gv+y0tPwxRveeZxZDjgiAIgiAIgiAIgiAIgiAIgiAIgiAIQpmkepfoBUEQBEEQBEEQBEEQBEEQBEEQBEEQikmGGHO8RIkntAVBEARBEARBEARBEARBEARBEARBEIQySVzQFgRBEARBEARBEARBEARBEARBEARBEMokMeS4IAiCIAiCIAiCIAiCIAiCIAiCIAiCkiQZpV2Dj4t4QlsQBEEQBEEQBEEQBEEQBEEQBEEQBEEok8QFbUEQBEEQBEEQBEEQBEEQBEEQBEEQBKFMUgMkpV0JQRDyJ5GITVQQBEEQBEEQBEEQBEEQBEEQBCk1NbXSrsJHb8H2lNKuQr4WjNAu7SoUOfGEtiAIgiAIgiAIgiAIgiAIgiAIgiAIglAmaZZ2BQRBKNzuq6r5lPaQltK7yFQxvqzY3G+ml3JNikffJhoAePu9LuWaFD0nWwtAtfPyuJZDKdekePRIfQaAv69PKdek6NW0qw3Anmuql5eDW0jz8l6X1qVck+LhcuYKoNp5+dD3XSnXpOjVs6sCwInKjqVck+LRPeEpANe8Y0u5JkWvhZMeoNrH8bvPw0q5JsWjob0pAAmX95VyTYpe5TafAaqZl5Cdm6MXqN7xYMsC6fHgqV9QKdek6DnaWgKq2aeD7H6dKvbJs/rjqthOyWqjqHqfVZWPdXd8wku5JkWvUW0TAE7cSS3lmhSP7o20ANVsp3wM554F4WMiLmgLgiAIgiAIgiAIgiAIgiAIgiAIgiAoKSOjtGvwcRFDjguCIAiCIAiCIAiCIAiCIAiCIAiCIAhlkrigLQiCIAiCIAiCIAiCIAiCIAiCIAiCIJRJYshxQRAEQRAEQRAEQRAEQRAEQRAEQRAEJUkkqvd+9rJMPKEtCIIgCIIgCIIgCIIgCIIgCIIgCIIglEnigrYKmD9/Pnfv3i3taghKaNu2LRKJBAMDg9KuiiAIgiAIgiAIgiAIgiAIgiAIgiCUeWLI8WKyefNmRo8eDUBqaiqBgYEcOnSI+fPnk5CQULqVK0Tbtm25ePEihoaGREdHF1p+woQJjBs3jjp16pCWloavry87duxg/fr1JCYmKrVOiURCnz59OHz48H+tfqmxtrbG398fFxcX7t+/XyLrlEgkXDz8J/9e2kdSQgwWNvXpMXwe5hb2Bc735PZpLrivJjL0FUZmNejYbypOrp3lyty8sItrp/4mNioUcws7PhnyHda13d5r3Ue3zuPFEy9io0LQrlAZK7uGdBo4A7NqNuU+tpxld66aiO+jKwz68k+cGnUqNDZleJ3bzeXjm4iNDqWKhR09h8+mloNbvuVfeN/i+K5lvHvti76hOW16jKVZx8Gy7x/dOovn0fWEv3tFeloaplVr0LrbGBq16lUk9f2vThw7jMfBvURGhGNlXZNxE7+gTt36Cst6Xb3MqeNHefnCl9TUVGpY12TwsFE0dG1cwrWWKiyfcvN/dpPTe5YS8toXPUNzWnYbT+P2g+XKFJbHV46vw/vfs4QFv0BTuyJWdg3pPGA6pkpsWyXBuJUbNtPHYdCoLhWrm3O7/xTeHTlf2tV6b0ePHWf/oUNERERiXaMGkydOoF7dOgrLPnr8mL83byUwKIjk5GTMzc3o8ckn9Ovbp2QrnenmhV1cPfk3cVGhmFnY0W1oIXn59Can9iwl9LUvekYF52VEyCuMzfPm5c0Lu7ntuZuosNcAmFnY0a7XF9jXb1M8QRbA5NM+mA8cgpaxCUkB/rz+azXxjx7kW970076Y9u6HdpVqpIS8493ubUSeO12CNVZeec5LZZw65s6RQ7uJjIjAqkZNRk/8P5zrNlBY9vrVS5w5cRj/F89JTU3FyroWnw0dg4trkxKu9YczaumGzTfjMGhYh4rVzPl30Be8O1r+9pcXTuznpMd2oiLDsLCyYei46dSu01Bh2aiIMPZsXkWAnzfvggPp1GMwQ8dPL5F6lsYxW9n1hr7x4+yBXwl4dgtJRgZmFvYM/HwVhibVi+4fQIEzxw9x9NAuoiLCsaxRi5ETvsKprovCsjevXeTsCXf8X/iSlpqCZY1aDBg6jgauTYu1jh9qn+cNtp7+h7DoOGyrmzNjUDca1a6psOztZy+Z8OumPNMPLfqKWtXMirmmeZVWXyg9LZUL7r/z/MElIkODqFBJFxvnFnQaMA19oyrFFq8ifdrp0Na1EjoV1XnxOpVtx2N4E5qeb3lXpwr0bK1DFWMNNNTVeBeRxqlrCVx7kFSCtS7ciWOHcT+4j8iIcGpY12TcxCkF9HuucPL4EV6+8Mvs91gzeNgoGpVSv0cZ5blfl9vH1idXRFXaKYqoSp+1PB/rlHHm+EGOHdpFVGRWO+VrHOu4KCx789pFzp50J+DFc1k7pf/QcTRo1KxkK63AP2f24HlsMzFRoVS1tKPPyFnYOrrmW973yS0O71jO2yBf9I3M6dBzDC07D5Irkxgfw/G9q3lw6xyJ8TEYm1nQe/i3ODcs/v63KrdTSqO/4P/sFtdO/c0b/8fERYcW6fllofhliBHHS5R4QrsYnTx5kqpVq2JjY8MPP/zAlClT+PXXXxWW1dQsn/cWbN++nd9++43Dhw/Tvn17XFxcWLx4Mb1796ZLly6lXb0PoqWlVdpVUNrVkxvxOrOF7sPnMmHufnQNzNj261iSE+PynSfQ9y77106jQYteTF54mAYterF/7TcE+WVfhH908wSndi+hdc/JTF7gTg17N3asmkhU+Jv3Wnc16zr0HvszX/x0nOHTNyJBwvYV48jIyP9ERHmJLcv1s1tBTa3QeN7H/esnObZjCe17T+KrxQep6eDK5uWTiAp7o7B8REgQm3+dTE0HV75afJB2vSZydPvPPLx1Rlamkq4B7XtNYsq8XUz92R3XNv04sOF7fB78U6R1/xD/XPJk0/r/MXDQMFb+sR7nOvVYPG82oSHvFJZ//OgBDRq6MnfRElasXkvd+i78tPB7Xvg9L+GaK5dPOUWGBrFz1SRq2LsxeYE7rXtO4uSun3hyO/vCmTJ57P/sFo07DGX8D3sZOX0TGelpbF85npTksnHDlIZOZWIePOPx14tKuyof7OLlK6zdsJEhgz5jzerfqVu3Dj/MX0BISIjC8hUrVqRXzx78umwJG9auYeigQWzZvoMTJ0+VcM3h0Y0TnNq1hDY9JzN5oTvWtd3YsbLgvNyxahLWtd2YvNCd1j0mcXKngrz8axr1m/fi80WHqd+8F/v+ks9LA+MqdBownYnzDzBx/gFqOTVj9+ovCHldstumYdsOWEz+ine7tvPs83HEP7yPzU/L0TIzV1jepGcfqo2dxNvtm3k6YQRvt2/C8stp6DdrUaL1VkZ5zktlXL18ni0b/qDfoJEsX70Rp7r1+Xn+zHyPB96P71O/oRvfLfyFX37fQJ36DVm6aDYv/HxKuOYfTlOnErEPn/J42uLSrsoHu/HPGXZtWkHPgWNZuHIntZ0bsnLxV4SHvlVYPi01BT0DI3oOHItVzYJPehWl0jpmK7PeiJBXbFoyFNOqNoyeuY3JCw/T9tPP0dSqUHz/IMC1y+fYuuF3+n42kqWrN+NYpz5LF8wgLETxb+f96B71XJowe8Gv/PzbJpzrN+KXxTN5WQa3udO3HrJ870nG9WjL7nmf09Demi9Xbyc4PKrA+TwWf83ZX2fKPjWqmJRMhXMprb5QakoSwQFPaPPpFCbNP8igL/8g/J0/u1dPKfaYc+resjJdm1dmx4lYFm4IJzoug29HGlFRO/9+V3xiBkcvx7N4YwQ//BXOlbuJjOujT11b7RKsecGuXPLk7/VrGDhoKKv+WIdznXosmjenwH6PS0NX5i36mZWr/6JefRd+WvhDqfR7lFGe+3W5fWx98vyoQjslP6rQZy3vx7rCeF05x7aNv9Pns1Es+X0LDnUasHTB9PzbKY/vUc+lMbPm/8pPv23Gub4ryxfP5KXfsxKuuby7Xifx2LaUzn0mMGPJfmwcGrF+6WQiw4IVlg8PCWLDL1OwcWjEjCX76dx7PO5bl3D/xllZmbS0VP76eQIRoa8ZPXUlc1YcY9CEhRgYK+7zFjVVbaeUVn8hNTmRKlaOdB8+t0jiEARVJi5oF6Pk5GTevXtHUFAQu3fvZufOnfTp0wfIHiZ8zJgx+Pn5kZycDICVlRUeHh7ExsYSHR3N3r17MTeXPxjNmjWLt2/fEhMTw8aNG6lYsaLc956enqxatUpumru7O5s3b5b9ra2tzbJly3j16hVJSUn4+PgwduxYrK2tuXjxIgBRUVFIJBK5+XIaOHAgw4cPZ8iQISxZsoTbt28TEBDAkSNH6NChA56engC4ublx5swZQkNDiYqK4uLFizRsmP3ExsuXLwHw8PBAIpHI/gbo2bMnt2/fJjExET8/P+bNm4eGhobsewcHB65cuUJiYiKPHz+mY8eOSCQSevfuLStTt25dzp8/T0JCAmFhYaxbtw4dHR3Z95s3b8bd3Z3Zs2fz+vVrfHx8mDt3Lg8e5H2S6/bt2yxcuFDhv4ci3bp149mzZyQkJHDhwgVq1qyp9LyFkUgkXD+7jTY9J+Ps2oUqlrXpO24pqSlJPLxxLN/5rp/dhq1zC1r3mIRZNRta95hELadm0guzmbxOb6FR6/64thmIWXVbug39DgPjqtz23P1e63ZrN4iaDo0xMrWkunUdOvSdSkxEsOzpvfIcG8DbV0/xOr2F3mN/KjCe9/XPyS24te1Pk3YDMLew5dPhczAwqcb183sUlr9xYS+GptX4dPgczC1sadJuAG5t+3HlRPa2a+vUhLpunTC3sMWkSg1adR1BVava+PvcKdK6f4jD7vvp1KUbnT/pgVUNa8ZP+hJTM3NOHT+isPz4SV/Sb+Bg7Gs7Ut3CkhGjx1OtugW3bniVcM0Lz6fcbl/cg4FJNboN/Q6z6ra4thlIw9b9uHY6+y5pZfJ4xLSNNGzVD3MLe6rWcKTP2CVEh7/hjf/jYo9ZGaGnL+Mz/zfeepwtvHAZdcjdg65dOtOta1dq1LDi84kTMDM15diJkwrL29na0r5dW2paW1O1ShU6dmiPW6NGPHpc8r/JtTNbaNimP65ts/NS37gqty4ozstbnrnysq00L6+eys5LrzPbsKnTgjY9pXnZpuckbJya4ZUjLx1cOlC7QVtMq9bCtGotOvX/Bu2KlQn0K5lRS7KY9R9ExKnjRJw6RnJgAK/X/kFqaAimn/ZVWN64YxfCTxwh6tIFUt4GE3XxPBGnjmH+2bASrbcyynNeKuOo+z46dOlBp649saxRkzETv8LE1IwzJzwUlh8z8Sv6DBiKXW0nqllYMWzURKpWt+TfG9dKtuL/QeiZK/gs/J13h8vv/vLM4Z206dSbtp37UN2qFkPHT8fYtAoXTh1QWN60SnWGjZ9By/Y9qVRZt8TqWVrHbGXWe/7Qb9jXb0uXz76lmrUzxuZW1G7QDl394j3BfNxjL+0796RD115YWNVk1MSpmJiac/aEu8LyoyZOpdeAYdhmbnNDRk2mWnVL7twsexdjdpy9Rp9WjejX2g2bauZ8O7g7VY302X/pZoHzGevrYGqgJ/toqJf8KZPS7AtVrKzHyBmbqNukG6bVbLCydaH7sB8IDnic78nc4tClWWWOXo7nX+9kXoeks8E9mgpaajSrVzHfeZ76p3LnaTLBYemERqZz9kYige/SqF2j7Nywftj9AJ26dKOLrN/zBaZm5pw8flRh+fGTvlDY77lZCv0eZZTnfl1uH1ufPD+q0E7Jjyr0WcvzsU4Zxz320L7zp9ntlAmZ7ZST+bRTJkylV//h2NZ2plp1KwaPnEzValbcuXm1hGsu7+LxbTRt349mHQZQxcKWvqNmY2hSlatnFe9Prp3bh6FJVfqOmk0VC1uadRhAk3Z98Ty+RVbmhuchEuKiGTd9NTYOjTA2q46NYyMsrB2LPR5VbqeUVn/Bvn4bOvabirNr+Xw4UBBKUtk8YqmoxMREuad/7ezs+Oyzz+jfvz8uLi6A9KKusbExbdu2pXPnztja2rJ3717ZPAMHDmThwoV8//33uLm5ERwczJQp738X0rZt2xg8eDBfffUVTk5OTJ48mbi4OAIDA+nXrx8AtWvXpmrVqnz99dcKlzFs2DCePn3KkSOKOycxMTEA6OnpsXXrVlq3bk2zZs14/vw5J06cQFdXegKrcWPpcFKjR4+matWqsr+7dOnCjh07WL16Nc7OzkyaNInRo0fz/fffA6CmpoaHhwcJCQk0bdqUiRMn8tNP8hcWK1WqxKlTp4iMjKRx48YMHDiQTp068eeff8qV69ixI05OTnTu3JmePXuyadMmnJ2dcXPLHlKkXr16NGzYkC1btij1b2xpacmhQ4c4ceIELi4ubNy4kaVLlyo1rzIiQ4OIiw7Ftk5L2TRNLW1qOjQm0Df/d6oH+t3Dtm5LuWl2dVsR6HcPgLS0FN4EPJZbLoBtnZay5X7IulOSE7j3zyEMTS3RN65a7mNLSU7kwLrpdB8+Fz2DohuaKS0thdf+T7CvJ19H+7otCHh+T+E8Ab73sK8r/yShfb1WBL18THpaap7yEokE38dehAb7FzhkWklITU3Fz9cHl0by9XBp6MZTb+UuuGRkZJCYmIiunl5xVDFfyuRTboF+9/KUt6vTijf+2b9VYXmsSFJiLACVdAzeNwxBgdTUVJ77+uLaUH64XNdGDXni7a3UMnz9/Hji7U29enWLo4r5SktLIdj/MXaK8tJPcV4GKcrLuvJ5qaiMbd1WBPreU7jMjIx0Ht44TkpyAla2Lh8WzAdQ09Sksn1tYu/In8SJ/fcWOs6Kfws1bW0yUpLlpmWkpFDZwQly3ERX2spzXiojNTWVF74+NGgoP8xog0aNeeb9SKllZGRkkJSYUOLHg49ZWmoq/n5PqeMiP5RjHZdm+D3Nf5j/klZax2xl1puRkcHz+xcxqVKT7SvG8cvXLdiw+DO875z74HiVkZaaykvfZ9RvKD9Ef/2GTfB5qvw2l5iYiI6ufnFU8YOlpqXhHfCG5s52ctOb1bHjvl9ggfMOXrSGzjOWMWnFZm49fVGc1cxXafaFFElKiAU1NSpWLpnf2cxIA0M9DR75pcimpaXDU/8U7KyUvzjtVEubaiaaPAvI2x8qDfn3e1zfu9+jp1e2tjko3/263D62PrlQPpX3Y11hCmyneD9UahnZfYPS22empaUS9PIJDvXl9w8O9Vvg76P4xm//5/fzlHds0JLAF9n7k8d3LlLTvgEHNv/E3EltWPZtH856rFdqRMz/SlXbKWXpHJ9QvkgyJGX2o4rK5zjX5VDjxo0ZOnQo589nv49FW1ubESNGEBYWBkCnTp2oX78+tWrVIigoCIARI0bw5MkT3NzcuH37NlOnTmXTpk38/fffAMydO5dOnTrleUq7IPb29gwaNIhOnTrJ6pPzqeiIiAgAQkJCCnyHtr29Pc+eFT5sS9aT2lkmTZpEZGQkbdu25fjx47L4o6KiePcueyiq77//nqVLl7Jt2zZZHefOncsvv/zCokWL6NKlC7a2trRr10423/fff8+5c9knf4YNG0alSpUYOXIkCQkJPH78mC+//JKjR48ya9Ys2RCd8fHxjB8/ntTU7I7G6dOnGTNmDLdv3wZgzJgxXLp0Se7fqiCff/45L1684JtvvgHAx8eHevXqMXv27Hzn0dbWpkIF5YYWjIsJBUAn15MbOvomRBdwV1pcdJjCeeKipctLiI1EkpGOjoGiMmHvve6bF3Zxdv+vpCYnYFrNhpEzNqGpWfCwb+UhttN7lmBl1xDHhh0LjOV9JcRGkZGRjl6u9esZmOCTWcfc4qLD0MsVk56+CRnpacTHRaFvKL3gnpQQy89ftSMtLRV1dXV6j5qLfb3SHVI3NiaajIwMDA2N5KYbGBkRGRmh1DIOH9pHclISLVu3K4Ya5k+ZfMotLjoUHf1W8uUNpL9VQlwkeobmheZxbhKJhNN7l1LD3pUqlrX/Q0RClpiYmMy8NJSbbmhoSGRkVIHzDhs5mujoaNIzMhg+dAjdunYtvooqkBAbSUZGep4c0jUwIe5R/nmpa5ArL/Xz5mXuJwV1FeTlu8BnbPxpCGmpyWhXqMzgL//E3EL+JEtx0tA3QE1Dk9TISLnpqZGR6BkZK5wn9vZNTD75lOhrV0h87kMleweMu3ZHXUsLTQND0iLCS6LqhSrPeakM6fEgHYPcxwNDY6KUPB4cdd9LUlISLVp3KI4qCgrEZrZb9A3lty8DA2MeRSre55SG0jpmK7Pe+NhwUpIT+OfEBjr0+5pOA2fg+/AKe//3f4yeuZWaDsXzTviYGOlvZ5Br32hgZETUHeX2e8fdd5OclEjz1kXbHv6vIuMSSM/IwFhffgQAEz1dwqNjFc5jaqDL3BG9cbKuTkpaGsev32fSyi1smDEW13zeRVpcSrMvlFtqajLnDqygXtOeVKxUMiMqGOhKn7uIic+Qmx4Tn4GJQcE3mlWqoMaq6aZoaqghkcC24zE8fpFS4DwlJSaffo/he/R7PA7tJzkpkZat2xZHFf+T8tyvy+1j65ML5VN5P9YVRtZOyd3GNDQmOkq5fcpxj90kJyfSrFXp9Q3iY6T98zz7BwMTYvLZn8RGKdifZLZB42KjMDAyIzwkiOehr3Ft2YOJs/4i9G0ABzf/REZ6Ol37f15s8YDqtlPKyjk+QRAKJi5oF6OePXsSGxuLpqYmWlpaHD58mP/7v/+TfR8QECC7mAvg5OREYGCg7GI2gLe3N5GRkTg5OXH79m2cnJxYu3at3Hq8vLxo37690vVycXEhLS2NS5cu/YfopE9ISySF3+lhZmbGokWL6NChA1WqVEFDQ4PKlStTo0aNAudzdXWlcePGsieyATQ0NKhUqRKVKlXCwcGBwMBAuYvgN2/KP5Hl5OTE/fv3SUjIfq/s1atX0dDQwMHBQXZB++HDh3IXswE2bNjApk2bmDZtGunp6QwbNozp06cXGm/OdV+/fl1umpdXwUNnzZkzhwULFij87oHXUY5umy/7e9hUaR6oKXp/cyHvdFYj1/cS6dRCy+RarjLrrt/sU2zrtCA2KpRrpzex/6+pjP1uN1o53glY3mJ7evcCL71vMGnBoQLr8p/kWr9EIlFcp+wZ5MtLA5ebql1Rh69+OkRKUgK+j69zfNcvGJtbYetUPCdK30vu2AqNV+ryxfPs2bmN7+YtznPypKQok09y5fPEKvui4GXmnpbpxI7FvAt8xtg5u5Sqr6C83L+VRCLJ72eQWfHLUhKTkvB++oxNW7ZSvVo12rcr+ZOOeeuuIK/k58hvQfkuUzqX/DSTarWYvNCdpIQYntw+g/vG2YyZvb1EL2oD0oBzkFZdcZvl7c4taBoZU/v3daAmvfgdceYkVQYNgxK4w/19lee8VEbefaSk0GM/wD8Xz7Fv52Zmzf05z0Vxofjl3hdIUO53K2mldcwuaL2SDOlFO4eGHWjeZTQA1Wo4Eeh3l9uee4rtgnZBdVOmDXb10lkO7NrEjLlLy+w2l/fny799WbOqGTWrZo+61MC2Bu8iotl25p9iP8lfFvtCAOlpqRxYOw2JREKPEfPzfF9UmteryKhPs5/IXbUzSlqtXIdtZfYoSSkS5q2NoKK2Gs61tBnSVY/QyHSe+peNp7RBYbdHyX7Phcx+z6JS6/copRz36/L42PrkQrlUXo51HyzPLkWi1PHg6qUzHNz1N9N/WJbnonhpyHvsLXh/kqdtnXlQVMvRftTVN+azCQtQV9fAyqYOMZGhXDi2ucgvaH9s7ZTSPscnCELBxAXtYuTp6cnnn39Oamoqb968IS0tTe77+Ph4ub/zu0Cs7IXjLBkZGXl2pjmHOk9MTFR6WQXx8fHBycmp0HJbtmzBzMyMqVOnEhAQQHJyMl5eXmhrF/yUrrq6OvPnz+fQobwXDZOSkpT6dymoTM7puX8LgKNHj5KcnEzfvn1JTk6mQoUKHDx4sMD15V73+1qyZAkrV66Um5Y1dLuDS3ssbOrLpqenSe80j4sOQ88w+z3r8THhBb5vT9fAlLgY+TvL4mPD0TUwBaCynhFq6hp57j6Lj81erq6+mdLrrlhZj4qV9TCpUhNL2wYs+7IpT/89S71mPWVlyltsL72vExH6iqVfync69/3vK2rUdmXMrO351rEwlfUMUVfXIDZXHeNiIvKNXdfAVGF5dQ1NKusayqapq6tjWsUagOrWToS8ecHFoxtKtfOsp2+Aurp6nqfvoqOiCj2R8c8lT/78/VdmzplPg4auxVlNhZTJp9x0Dczylo8Jl/5WOoaZZQrO45xO7FzMs3sXGDN7BwaFDOUvKE9fXx91dXUicz3lGx0djVGup2Nzq1pV+jvUqlmTqKgoduzaXaIXDivrGaGuKC9jwvPcaZxF2bzMu58JRydXXmpqamOSuZ+xqFWPN/6PuH52G71GL/ovYSktPSYaSXoaWsbyJy00DY1Iy/V7ZpGkpBC4cimBvy9Hy8iY1IhwTLr3Ij0+nrQCRqopaeU5L5UhPR5o5D0eREcWejy4evk8a1YvY/rsRdRvKIbtLEl6me2W6Cj5J3pjoiMxMCze9z+/j9I6Ziuz3sp6RqhraGJWXf7GH7Nqtrx6/u/7Bfoe9PUNM7c5+d8uOiqy0BO/1y6fY93qJUyd/SP1XBoXWLY0GOlWRkNdnfDoOLnpEbHxeZ5kK0g9G0tOXFc8HGhRKkt9oew6pLL/r2+ICg1i1Mwtxfp09t1nyfi9zr7grJn5ELaBrjrRcdlPaevpyP+tiEQCIRHSm9FevU2jmpkmPVrp8NQ/qsjr/b70M/s9eY7jUYUf565c8uSP339l1px5uJRCv0cZ5blfl9vH1icXyqfydqx7X1ntlOhc+5SY6Mg8IwPl5nXlHOtXL+HrMtBO0dGX9s9zP40dGxORZxSILHqGpnnKZ+1PdHSlr5nTNzRDXVMTdfXskUuqWNgQGxVGWloqmprKv6KjMB9LO6UsnOMTyqf3uGwnFAHxDu1iFB8fj5+fH69evcpzMVuRJ0+eUKNGDSwtLWXTnJycMDQ0xDvz3Yje3t40ayb/jrrcf4eGhlKtWjXZ3+rq6tStm/2uxIcPH6Kurk7btopPZKakSA9MGoW8N3LXrl04ODjQq1cvhd/r60vfXdG6dWtWr17NyZMnefLkCcnJyZiZyb9zOCUlJc/67ty5g4ODA35+fnk+EomEp0+fUqNGDczNsw+eWe/fzvLkyRNcXFyoXLmybFrLli1JT0/Hx8enwPjS09PZunUrY8aMYcyYMezZs+e9bgZ48uRJob9VbikpKcTGxsp9slSopItJFWvZx6y6HboGZvg9uSYrk5aWgv+zW1jZNVS0eACsbF3we3xNbprfo6uyd5xqampT3bqO3HIB/B5fky3XyMzyg9YN0rtF09Lkh30rb7G16jGBzxceZvICd9kHoOvg2fQZu6TA+AujqamNRU1nfB/J19H30TWs7V0UzmNt55Kn/POHV7GsVQeNghqxEglpqaU7BJ+Wlha2drW5d1f+hO29u//i6FQn3/kuXzzP6lXLmPbt97g1KXi7Ki7K5FNuCnP08VWq18z+rQrLY5DekHN8xyK8/z3LqJlbMDKzRCg6Wlpa2NvZceeu/HuS7ty9h7MSN3JlkUgkeUb/KG6amtpUq1knTw69eHINK1vFeWlp68KLXHnsmysvLW1deKEgd63sXAqsj0QikXV4S4IkLY2E5z7oNZJvD+g1akz8k0LeCZueTmpYKGRkYNSuIzE3rpWpnkl5zktlaGlpYWNXmwd3b8tNf3D3Ng5O+b/z+5+L5/jfqiVM/XYerk2aF3c1hVw0tbSoaevI43s35KY/uXcDW8f6+cxV8krrmK3MejU1talesy7hb+VfaxT+1h8Dk+rvF+h70NTSopadAw/v3ZKb/vDeLWo75r/NXb10lr9++4n/m7GARo3L5jC5WpqaOFlX57q3n9z060/8aGBrpfRynr4KxtSg+N/lW5b6QpB9kjg8JICRMzZTWbd4n5ZNSpEQEpEu+7wJTScqNp06ttk3wGtogGNNbXwD3+/4pQZoaZaNJ6Cy+j3337vfc4HVq35h+rfflVq/RxnluV+X28fWJxfKp/J2rHtfWe2UB3flR+J8eO8WtZ3q5Tvf1Utn+Ou3H/lyxgIaNW6Zb7mSoqmphWUtZ3weyI/Y6fPQi5q1Gyicp6Z9A3weypd/9uAaVjbZ+5NaDi6EvX1FRkb2jV4hwf7oG5oV6cVs+HjaKaV5jk8QBOWJC9plyLlz53jw4AE7d+6kYcOGNG7cmP9n777Dojj+B46/qSq9FwFRiooNxd67xpLYo4mx15h8U9RY0jTVrtHkZ40Ne8VeUeyo2Bs2EAVBpFel3u+PkzsO7gAVOLjM63nuSdib3ZuPOzM7s2XW29ubU6dOcfWqdFCwePFiRo4cyYgRI3B3d2fmzJnUrq04ODh58iQ9evSge/fu1KhRg6VLlyq8b/Hp06esX7+eNWvW0KtXL6pWrUrbtm0ZMGCA7Pvs7Gx69uyJlZUVhoaGSvO7fft2tm7dypYtW5g2bRoNGzakSpUq9OjRA19fX9k06I8fP2bIkCHUrFmTJk2asGnTJoUpwAFCQkLo2LEjtra2srz++uuvDB06lBkzZlCrVi1q1qzJxx9/zG+//QbA8ePHCQoKYv369dStW5cWLVrwxx9/APKnrzdt2sTr169Zv349tWvXpl27dvz9999s2LBBNt14Qf799186dOhAt27dWLNmTaHpc1u+fDmurq4sWLCA6tWr88knnzB8+PC32kZBtLS0aNZ5KGcPrCDw6nEiwx6yZ/V09PQrUrep/Onn3aum4rtzgezvpp2HEHT3POcOrSIqIphzh1YRHOhPs87DZGmadx3OtTM7uXZ2F1HhQRzZMouE2AgatRtU5N+OfRnK2YMrCA+5Q3xMOKGPr7Nj2bfo6VXAvV7BT4WV9diMTa2xdayu8AEwtaxcLBcWW3UbTsCpnQSc3sXL50Hs3zib+JgImnYcCMCRbQvZtlz+LvamHQYSFx3BgU1zePk8iIDTu7hyehetu4+QpfHbt5JHty8Q8zKUl+HBnD28jmvn99Gg5Yfvnd/31avPAHyPHsL32GFCnz1l9cr/Izoqkq7dpXnbsHYVf82X3yhw5tQJFi+YzfDRn1OjZi3iYmOJi40lJSVZ1U+UmMLKk+/OBexeNVWWvlG7QSTEhHNk6yyiwoO4dnYX187uokXXkbI0RSnHBzf+yi3//fQbNx/9ioYkJUSRlBBFRvrr0gu+ADqGBph41sTEsyYABtUcMfGsSUUn+0LWLDv69unNkWPHOXrsOM+ehbJ85SpeRkXRo3s3ANasW8/cBfIZNfYdOMjFS5d5/jyc58/DOXrcl527fejQvl2p571Flzfl8oy0XB7eMouEmAgat5eWy+M7FMtl4/aDiI8O58iWN+XyzC6un9lFyw/k5bLZm3J59qC0XJ49uIrge/40z1UufXcu5OnDK8RFhxEZ+gDfXYsIuX+Zes1Lt52J2rUNiw96YtG1OxWcnKk8/n/o2dgQfWAPAPYjx1HlO/nrTCo4OGHesQv6lR0xqOGB8/czqVi1GhFrV5ZqvouiPJfLoviwz8ecOHaAE8cOEvYshLUr/yY66iVduvcCYNO6FSxZ8Ics/blTvvy98A+GjvoC9xq1iIuNIS42Ri3Hg3elY2iAcb2aGNeTtpeVnB0xrleTio7lp73s0mswZ3z3cMZ3L+GhT9iyegEx0S9o37UfADs2/MOqv35WWOdZ8AOeBT8g7fUrkhLjeBb8gOehwSWaT3Udswv7XYCWH4zizuXDXD29nZjIp1w6sZEHN/1o3P7TEv036dF7ICeP7cfv2AGeh4awftVioqMi6dS9DwBb1i3j/xb8Jkt//vRxli78jSGj/od7zdrEx8UQHxdDahmsc591boHP2avsOXeV4IiXzN92iBexCfRvK30KcsnuY/y4eqcs/SbfC/hdv8fTyBiCnkeyZPcxTly7x8AOTUs97+ocC2VlZbJ96deEh9yh35h5ZEuyZP3MvDcll6RjF1P5sLUhXjUr4GCjw+jeJqRlSLh4W97XHdPHhP4d5U9k9WhlQG0XfazNdbC30qFrcwNaeFbkwq2y0T8G6NWnP8dzjXv+XbmU6KiXfPBm3OO99l8WzZ8tS3/m1En+WjCbEaPHq33cUxTleVyX139tTK6KJvRTVNGEMWt5PtYVRY/eg/A7vh+/49J+indOP6VbbwC2rF/G0oXymcDOnz7GskW/8dnI/+Fes06Z6ae06zGUi367uOS3m8jnQfh4zyEuOoIWnaTtyYEti9i0dLosfYtOHxMXHcGeDXOJfB7EJb/dXPLbTfsew+VpOg8kNTken/WzeRkRwt1rp/Hds4pWXQbl/flip8n9FHWNF9JepxDxLJCIZ9IHGuOjw4h4Fkh8Ae8kF4T/KjHleBnTu3dv/v77b86cOUN2djZHjhxReO/29u3bcXV1Zc6cOVSsWJFdu3axbNkyunbtKkuzZs0aPD098fb2JjMzk0WLFuHn56fwO59//jl//vknS5cuxdLSkmfPnvHnn38CEB4ezowZM5g9ezZr167F29ubESNGoMynn37K2LFjGTlyJD/++COZmZk8evQIb29vjh49CsDIkSNZuXIl169f59mzZ3z//ffMnz9fYTuTJk1i4cKFjBkzhufPn1OtWjWOHTtGz549+fnnn5kyZQoZGRncv3+ff//9F5BOrd67d2/+/fdfAgICCA4O5rvvvuPAgQO8fi0dtL569YquXbuyePFiAgICSE1NZdeuXUycOLFI++Px48dcuHABS0vLfO/nLkxoaCj9+vVj0aJFTJgwgcuXL/P999+zdu3at9pOQVp2G01G+msObvyVVykJOLrUY8ik1VTINdVKQmw4Wtryu9KruHnRf/wCTu5ezEmfJVjYONF//EIcXeV3BtZp0p3U5HhO7/s/khOisHFwZ/A3KzCzcijyb+vq6fP04VUuHvfmVUoiRiaWONdoxKjvtxQ4BU15iK2keTbrRmpyPCf2LCMpPgo7R3eGT16B+Zs8JsZHEx8TIUtvYePIiMnLObBpNv6+mzExs+HDId9Tt3EXWZr0tFfsWf8rCbGR6OlXwNrehYHj5+DZrFupxFSQVm3bk5iUyLbN3sTFxlKlalV++mUWNrbSKXJj42KJipLfgHL08AGysrJYuXQxK5culi1v36krX0+cmm/7Jamw8pSUEEVCrLwDam7tyOBvV3Bky2wCTm7G2MyGbp/+QK1G8ja8KOX4it8WANbNGaqQn14j/6RBq74lGXKRmDasQ/MT8qn3a83/HoBQ793cGjVd1WplSrs2rUlKTGTTlq3Exsbi7OzM77/MwPbNrCCxsbFERUXJ0kuys1mzfj0vXkSio6NDZXs7Rg4fRo9uH5R63us07U5qirRcJuWUy2/l5TI5IYqEGMVy+dmbcnk5p1wOzlMu3eXl0s9nCeY2TgzIUy6TE2PYvXIKSQlRVKxkjK1TDYZMWoVr7dK9Mz7+9El0TEywGzwcXQtLXj99QvCPU8h4GQmAnoUl+ja28hW0tbHuNxAnxypIsjJJvnmdR998Tnrki1LNd1GU53JZFC3bdCQpMZGdW9YTFxtDFedqfP/LHKxtpMeDuNgYoqMiZemPHdlHVlYW/y5bxL/LFsmWt+v4AV9O/L7U8/8uTL3q0Oyot+zvWnOlbWTYBh9ujSsf7WXTVl1ISUxg37Z/SYiLxqGKK9/+tBgrG+kJ4YTYaGKiFOvTjImDZf8fEhTIxTNHsLS2Z/6q/SWWT3Uds4vS9/Ro2JmeQ2dy7uBKDm/+A0u7agz8YgnO1Ut26t0WbTqRnJTIrq1riY+NwcnZhWkz58vrXJxinfM9vJesrCzWLFvAmmXyE5RtOnZjwrc/lmhe31bXxnVJSE5l5YFTRCck4VbZlr+/GkJlSzMAouOTeRErf61ERmYWi3Yc5WV8IhX09HCtbMOSr4bQum51teRfXWOhxLgXPLhxEoDlM3sr5GnYlPVUq1k6Fz0OnU9FX0+LoT2MMaykTVBYBvM3xPE6XT5ziqWpjsJEKhX0tRjSwxgLEx3SMyVERGeycncCl++mlUqei6J12/YkJSWybfMG6XG8alV+/mUWNrbSfom0zuUf96xYuoQVS5fIlnfo1KXUxz1FUZ7HdXn918bkqmhCP0UVTRizlvdjXWGat+5EUmICu7eukfVTps6Yj/WbPmZ8nrHBiSPSfsra5QtYuzxXP6VDdz5XYz+lQfNupCQlcHT3chLjo7B3cmfs1GVYWEtn4kmMjyYuWt6eWNo4MmbKUvZsmMu5Y1swNbehz7DpeDbtLEtjbmnP+Okr2bNhLvOm9sXU3IY23T6j40ejSiUmTe2nqGu8EB5yh/Vz5Re4j26V3tzm2bI3fUbJb3QTyqbs7LIzs19pMTMzY8mSJbKZm/ft28f//vc/ElS8tk9XV5fff/+d7t274+LiQkJCAr6+vkybNo2IiAil66iihfxV9YJQ7rVo0YLz58/j6upKcHDxPOVx//59VqxYwaJFiwpPXAIkEglbzmtmNf2kpbRjo4nx5cTmczlLzTkpGX2aSF8REBj0XM05KX4ertKOqiaXy4N6NdSck5LRI+MBACGPC36lRHlU1U16kmHrBc0rl4NaSMvljS6t1ZyTklH/2FlAs8vl7ceRhaQsf+q6SS8uHDKoqeaclIzuqfcBuBCYVEjK8qeFh3TaTE0+jl9/FF1IyvKpgbv0XYKpZ7arOSfFz6DNx4BmlkuQl83hMzXveLBupvR4cD8oTM05KX41XaWzi2nimA7k4zpNHJPnjMc1sZ+S00fR9DGrJh/rrj2MUXNOip9XdemDOYeulb1XNxWH7l7S6bE1sZ+i6eeetbTKxqtV/sumriz6K2pL25yxlUpku4cOHcLR0ZGxY8cCsHLlSkJCQgp8NfHOnTtZtWoVN2/exNzcnL/++gtdXd18rxAujHhCWyjXevfuTXJyMo8ePcLNzY3Fixdz7ty5YrmYbW1tzZAhQ3BwcCjWp6oFQRAEQRAEQRAEQRAEQRAEQRAEoSTo6+tToUIFhWVpaWmkp7/7FP01a9akW7duNG3aVDaj8ZgxY7h48SLVq1fn4cP8D3MkJibSpUsXhWX/+9//CAgIwMnJidDQ0CL/vniHtlCuGRsbs3TpUu7fv8+6desICAigV69exbLtly9fMm3aNMaOHUt8fHyxbFMQBEEQBEEQBEEQBEEQBEEQBEEo3yQSSZn9TJ8+ncTERIXP9Onv91qN5s2bEx8fr/B63kuXLhEfH0+LFi2KvB1TU1Oys7Pf+rqbeEJbKNc2bNjAhg0bCk/4DsSUHYIgCIIgCIIgCIIgCIIgCIIgCEJ5MmvWLBYuXKiwLC0t7b22aWdnx8uXL/Mtf/nyJXZ2dkXaRoUKFZg9ezabN28mKentXoMmntAWBEEQBEEQBEEQBEEQBEEQBEEQBEHQAOnp6SQlJSl8VE03PmPGjEKf+G7YsCEgfSo9Ly0tLaXL89LV1WXr1q1oa2szYcKEt45JPKEtCIIgCIIgCIIgCIIgCIIgCIIgCIJQRJJsdeegePzzzz9s3bq1wDQhISHUq1cPW1vbfN9ZW1sTGRlZ4Pq6urps376datWq0aFDh7d+OhvEBW1BEARBEARBEARBEARBEARBEARBEIT/nJiYGGJiYgpN5+/vj5mZGY0bNyYgIACAJk2aYGZmxoULF1Sul3Mx293dnfbt2xMbG/tO+RRTjguCIAiCIAiCIAiCIAiCIAiCIAiCIAhK3b9/n8OHD7Nq1SqaNm1K06ZNWbVqFfv37+fhw4eydIGBgfTu3RsAHR0ddu7cSaNGjRg8eDA6OjrY2tpia2uLnp7eW/2+FlD4xOaCIKhNUd49IAiCIAiCIAiCIAiCIAiCIAjCf4OWlpa6s/CfN2lpirqzoNKCCYYlsl1zc3OWLFnCRx99BMC+ffv48ssvSUhIkKWRSCQMHz6c9evX4+zsTEhIiNJttWvXjtOnTxf5t8WU44IgCIIgCIIgCIIgCIIgCIIgCIIgCIJKcXFxDBkypMA0uW+2ePr0abHdfCEuaAtCObDlvGY+pf1JS2lDtvWC5sU3qIU0Nr/br9Sck5LRvm4lAMK+HKDmnBQ/x392AJpZ73LqXOqZ7WrOSckwaPMxAKfuaF69a1dHWuc0ulye36XmnJQMg5b9AM0ul6fvpqo5J8WvbW0DAF75bVJzTkpGpfaDAXh9wlvNOSl+FTsOBTS7vdTEOgfyendQr4aac1L8emQ8ADSzXIK8bLb6sOhPV5QX5/a3BSB0Qj8156T4OS2V9r00cUwH8nGdJo7Jc8bjmthPyemjaPqYVZOPdb630tSck+LXqV4FAA5fz1BzTkpGtwbSKX81+fysJvbBcvpfgvBfIi5oC4IgCIIgCIIgCIIgCIIgCIIgCIIgFJF4XWzp0lZ3BgRBEARBEARBEARBEARBEARBEARBEARBGXFBWxAEQRAEQRAEQRAEQRAEQRAEQRAEQSiTxJTjgiAIgiAIgiAIgiAIgiAIgiAIgiAIRZSdLaYcL03iCW1BEARBEARBEARBEARBEARBEARBEAShTBIXtAVBEARBEARBEARBEARBEARBEARBEIQySVzQFtRqxowZXL9+Xd3ZKLJhw4YRFxen7mwIgiAIgiAIgiAIgiAIgiAIgiAIaiKRlN2PJhLv0BbyWbt2LcOHDwcgIyOD0NBQdu/ezYwZM0hNTVVv5grRtm1bTp06hZmZGQkJCYWmyxEVFcWVK1eYNm0at27dUrnetm3bOHToUHFmuVhdPrmZC0dWkxQfhY2DGx988j3O1RupTB/y4DJHt87m5fPHGJvZ0LLbaBq3H6SQ5t6Vo5z0WUJc1DPMravQse83eDTsLPv+7MEVBF49TnREMLr6FXFya0Dn/pOwsncp9tjOH15NcnwU1g5udPu0kNjuX+bI1tlEPX+MsXnBscW+fIaFTf7YFk3uQHxMeL5tN+7wKT2H/Fx8wRXRqSPbOL5vPQlx0VR2cmXA8O9wr+WlNG1CXBQ71y/gWXAgLyOe0b77J3w8Ykop57joDFt3wbhjL3RMzciICCN+11rSg+6rTF+pUSuMO/VC18YeyatUXgfeIMHHm+yU5FLMtZREIuHU3n+4eno7r1MTcXCpR4/PfsbGwb3A9QqrW1Bwnc7KzOCkz2Ie3TpNXFQYFSoZ4VKrBZ36T8TE3LbE4s1ru98l1h89R3RCMq6VbZg8sBte1asqTXvlwRPGzF+Tb/nuX7+imr11Cef07Z06so1je+V17uMRBde5HesU69zAkeqrc5p8PCiK7Scvsv7IWaLjk3B1sGHyJz3wql6t0PVuPHrK6DmrcHWwZdsv/yuFnL698lwui+LU4e0czRXfwJGTVcYXHxvFzvULeRokja9D908YOOq7Us5x0W07FcD64/5EJyThWtmG7wZ0wcvdWWnagAchjFnknW+5z8wJVLOzKumsvrVtp6+wzvei9Fhgb82UAZ3xcquiNG3Aw6eM/mtjvuV7fh5X4rGpo20syu/67fmbO5cPkRj7Ah1dPeyda9Ox7zc4unoW7z+AEppc51SxaNUIl0mjMPWqQ8XKNlzpN4HIfSfUnS0F//X+JcDIT5z5qKs9xka63HuYxMLlj3jyTPX5iG4dbfnhm5r5lnfoe4b0jLJzRs+oTVeMO/VCx9ScjIhQ4nasJT0oUGV6g8atMe7cWz7uuXed+N3r1TLuKYryPK4rjCaPxzW5jwKaPWZVpjwc55Q5c3QrvnvXkRAfjb2jK/1HTMHNo6HK9I/uXmHX+nlEhAVham5N514jaN3lY9n3WZkZHPVZzaXT+4iPfYlt5ar0GvwNtRu0Ko1wFJw7tpWT+9eSGB+FnaMbfYZOxbWA2B7fC2DPhnm8CHuMqbkNHT4cQcvOA2Xf//3LcIICr+Rbr1aD1oyduqxEYsihjvOzAIlxkRzfPp9Ht8+QmZGGpW1Veo38ncpV67xXPOrqc73Nb4c+vs6J3X/xPPgW2jq62FWpyWffrgIqvVfsglAeiSe0BaUOHz6MnZ0dLi4u/Pjjj0yYMIH58+crTaurW37vi6hevTp2dnb06NEDc3Nzjhw5gomJidK0urq6vH79mqioqFLOZdHcuXyII1tm0brneMbP9KGKeyM2Lhqr9IIsQFxUGJsWjaOKeyPGz/Shdc9xHN78B/euHJWlCX18nR3LJ+LZ4iPG/7IXzxYfsWP5t4QF3ZSlCXkQQOMOnzL6x20MnbSG7KxMNiwcTXpa8d38cOfSIY5snkWbnuMZ/4sPztUbsXFhwbFtXDQO5+qNGP+LD617jOPwJiWxLZtIveYf8fmve6nX/CO2L1OMbezPO5n811nZZ+hk6aCmduOuxRZbUV05f5Qd6+bRre9ofpi3FTePBvzz5xfERkUoTZ+RkY6RiTnd+o7G0bl6Kef27VTyaoFZvxEkHt1F5OwppAUFYjXhB3TMlQ+G9V1qYjH0f6T6nyTyj4nErF6IfhVXzD/9vJRzLnX+8L/4H1tH989+YsxPOzAytcZ7/kjSXqk+CVOUulVYnc5If03E03u0+XAC42bsYuCXfxMTGcKWJRNKPOYcRwNuM2/bYUb1aMuWnz+ngbszXy7ZQERMfIHr7fnta47PnyL7VLG1LJ0Mv4WA80fZvnYe3fuN5sf50jr39x8F1zljE3O69RuNY1X11jlNPh4UxdHLt5i35SCjerZjy8wvaeBelS8XrS+0XCalvuanf3fQxMO1dDL6DspzuSyKgHNH2bZ2Ht37jeKnBVtw92jAkt+/JEZFfJmZGRiZmNO936gyH9/RK3eZt+Moo7u1YusPY2ngVoUv/tlMRKzqGzAB9v7yBb5zJso+VWwsSinHRXfkyj3m7jzOmA9asm36aLzcnJjwf1sLj23GeE7M+lr2KenY1NU2FuV3Le2q0n3wT3z+6z5GTt+EmZUDGxaOIiUxtuT+QdDsOlcQHUMDEm894O7Xv6o7Kyr9l/uXAIP7OTGwtyMLVzxm9MRrxMSls+jXelSqpFPgeskpmXw05ILCpyxdzK7UsAVm/UeQeGQXL2ZNJu1xINZfFDDuca2JxbD/kXLhBC9++4bof+ej7+yG+eDS3R9FVd7HdQXR5PG4JvdRQLPHrKqUh+NcXlfPH2Hn2rl07TeG6XO34+bhxf/9MUFlHYuODGPprAm4eXgxfe52uvYdzY41s7l+8bgszf6t/3Du+E4GjJzOT4v20KrzAFbN+5bQJ6pvIioJ1y4cxmf9bDr3GcPk2TtwqenFitnjiYtWHlvMyzBWzpmAS00vJs/eQafeo9m9bhY3L8ljGzlpMb8uPyX7TJ23B21tHTybluz5SnWdn32VksDqPz5BW1eXzyau4os/DtB10FQqGig/h/821NXnKupvhz6+zsZFY3Ct3ZIxP21n7M87aNJxMFpa4rKe8N8kSr6gVFpaGpGRkYSFhbFlyxY2bdpE7969Afk04SNGjCAoKIi0tDQAnJyc2LNnD0lJSSQkJLBt2zZsbGwUtjt16lRevHhBYmIi//77LxUrVlT43s/Pj0WLFiks8/HxYe3atbK/9fX1mTNnDs+ePeP169c8fPiQkSNH4uzsLHvqOj4+HolEorCeMi9fviQyMpKAgAAmTZqEvb09zZo1w9nZGYlEwoABA/Dz8+PVq1d89tlnSqcc//DDDwkICODVq1dERUWxa9cu2Xd6enrMmTOHsLAwkpOTuXjxIm3bti18B7wD/6Pr8Grdj4ZtBmBd2ZVun36PqYUdV/y2KE1/5dRWTC3t6fbp91hXdqVhmwE0aN2XC0fld6JePO6Na60WtO4xDmt7F1r3GEc1j2ZcPL5elmbIxH9p0KovNg7u2FWpSe+Rs0iICSc85G6xxXbh2DoatOlHw7by2Ews7Ag4qTy2AL88sbWVxnb+iDw2/2PeuNRuQZue0tja9ByHi0cz/HPFZmhigbGptezz8OYpLGyqULVGk2KLrah892+gZYc+tOrUF3tHFz4eMQVzSztOH9uhNL2VjQMDR06lWbsPqWhgVMq5fTvGHXqS4n+SVP+TZEY+J2HXOrLiojFs3UVpev1q7mTFvCT59GGyYl6SHnyf5PPH0atS+k+BSiQSLh73pk3P8dRq2AVbx+r0GTWbjPTX3L50QOV6RalbhdXpigbGDJ28hjpNumFl74KTa326D/6RiKd3VQ4mitvG4xfo3cqLvq0b4WJvw3eDumNnbsKO05cLXM/CxBArU2PZR0e77HVH8ta5gSPf1LmjBdS5UVNp3u5DKqm5zmny8aAoNh49R+/WDenbpjEulW347tOe2FmYssPvUoHr/e7twwdNPann6lRKOX175blcFsXx/Rtp1bE3rTu/iW/Ud4XEV5lBo6bQvH3Zj2+Drz99WjagbysvXOytmfJxV+zMTdlxOv+TFbmZGxtiZWok+5TF9nLDyUv0aVGfvi0b4GJvxZQBXbAzM2H7mWsFrmdRyrGpq20syu/Wa/YhrrVbYGHjhI2DO10HTSPtVTKRYQ9K7h8Eza5zBYk6eoaHM/7ixZ7jhSdWg/96/xJgwEcOeG9/xhn/aJ48S+WPRfepUEGHLm1tClxPIoHY+AyFT1li3OFDUi6cJOXCCTJfPCd+51qy4mMwaqP8AkSFatXJioki+dQh6bgn6D7J546h71w2b74rz+O6wmjyeFyT+yig2WNWVcr6cU6ZEwe8ad6hDy079sPO0YX+I6ZibmXH2WPblaY/d3wH5lb29B8xFTtHF1p27EfzDn04sU9+zLt85gBd+46mjldrrGwdadN1IB71W3Bif/4ZBkrSqYPeNG3fl+Yd+mPn4ErfYdMws7Tj3PGtStOfP74dM0s7+g6bhp2DK8079Kdp+z6cPLBOlsbQyBQTMyvZ58Ftf/QqVKR+M+XtbXFR1/nZc4f+xcTCnj6jZuHoUg9zK0dcajXHwkb5jFBFpc4+V1F/+8jW2TTtOITWPcZi4+COpW1Vajf6AF09/feKXSg+kmxJmf1oovJzNBbU6tWrV+jp6cn+dnNz4+OPP6Zfv37Ur18fgD179mBhYUHbtm3p3Lkzrq6ubNu2TbbOgAED+OWXX/jhhx9o1KgRERERTJjw9ncWe3t7M2jQIL766is8PDwYP348ycnJhIaG0rdvX0D+5PXXX3/9VjECCnHOmTOHJUuW4OHhwdGjR/Ot0717d3bv3s3Bgwdp0KABHTt25MoVead/7dq1tGzZkkGDBlGvXj127NjBkSNHcHNze+u4C5KZmU7407u41m6psNy1dktCHyt/R3lo0I186d1qtyI85C5ZmRnyNHXypKnTitCgGyrz8vpVEgCVDE3fNgylMjPTiQi5i5uy2IKUxxamLLY6irEpS+NapxWhj2+ozMct/300aN0XLS2td4zm3WRmZPAsOBAPz+YKyz08mxH84KaKtcoJHV30nFx4HagYx+vAW1SoVkPpKunBD9Axs6RirQYAaBubYlC/Oa/vFnzivCTERYWRnBClUJZ09fSpWqOxyroHhdetd6nTAK9Tk0BLq1juUi1MRmYmgU/DaV5LsT1rVtuNm0GhBa476NeldJ48h3EL1hJwP7gks/lOMjMyeBYUSK36inWulmczgsp4ndPk40FRyMplbcUpuprVduPm46cq19t79iphL2MZ16tDSWfxnZXnclkUsvjyHOtq1W9G0P3yHV9GZhaBzyJonufp/2YeLtwMLqS9/GMlnaYsZOwibwIePCnJbL4TeWyKU/o393DhZnBYgesOnPUvHaf9xZjFm7j8IKQEc6m+tvFdfjczM52rp7dRoZIxtk75p08uLppc58q7/3L/EqCybUWsLCpw+br8RvKMTAk37sRTp2bBeahUSYedq5uye20z5vxcB3eXMnQhUUcX/SquvA68obD4deBN9F2Uj3vScsY9taXTWmsbm1KpQXNe37la0rl9e+V8XFcQTR6Pa3IfBTR7zKpJMjMyCA0OxMOzhcJyj3rNCX5wQ+k6wQ9v4lEvb51swdPge7J+WmZGOnp5Lvrp6Vcg6L7qY15xy8zMIOzJPWrWU4ytZr0WhDxU3n6EPLqpJH1LQoPlfdC8Lvntxqt5NypUNCiejCuhzvOzD26cpHK1Omz7v6+Z+1ULls3ow5XTym92eBvq7HMV5beTE2N4HnwTQxML/v1jEPO+acna2Z/x9GEZ7AcIQikpv3NFC6WmcePGfPrpp5w4IX/fir6+PkOGDCE6OhqATp06Ua9ePapVq0ZYmPTk1ZAhQ7h37x6NGjXiypUrfPPNN6xZs4bVq1cD8NNPP9GpU6d8T2kXxN3dnYEDB9KpUydZfp48kXecY2Ol0/K9fPmywHdo52VhYcGMGTNITEzk8uXLGBhIOwB//fUXPj4+Ktf74Ycf2Lp1KzNnzpQty3kHt4uLC5988gmOjo5EREinkVmwYAEffPABI0aM4Icffsi3PX19fSpUqFDkfOdITYpDkp2FoaniFEiGJpYkJ0QrXSc5IQpDE8X3xhiaWpKdlUlqchzGZjYkJ0RjaKJsm8qnXZdIJBzdNpsq7g2xdSyeabVSk+LIzs7Klw8jU0uS76iOzcg0T2wm+WMzyrvNAmK7f+0Er1OTqN+yz3tE826S3/wbmJgqTuFlYmpJYrzyf4PyQtvIGC0dHbKT4hWWZyfFo21ipnSd9CcPiV2/BIuR36Klp4eWji6vbgUQvz3/e65KWnKitLwoqycJBTzFUljdepc6nZGRhu/OBdRt2pOKlUr+5F1ccipZ2dlYmCj+lqWxETEJSUrXsTI14qchvfBwrkx6ZiYHL95k3MJ1rJo8koYq3mGmDqrqnLFZ2a9zmnw8KIq4pDfl0jRPuTQxJibhkdJ1nkZGs2TXEdZMG4euTsFTmapTeS6XRSGLz0zZsS5GTbkqHtL2UoKFiaHCcksTQ6ITU5SuY21qxE+De1LL2Z70zEwOXLzN2L828O/EYTRU8U5LdciJzdI4b50zJDpR+TR91qZG/Pxpd2pVsSM9M4sDl24zdskmVn8zhIbu7/eUhSrqahvf5ncf3PBj54pJZKS/wtjUmqGT12BobP5O8RaFJte58u6/3L8EsDCXXnyIjU9XWB4Xn46tjepzB8/CUvnzr/sEh6RgYKDLgI8cWDa3PsP/d5WwiFclmueiyBn3ZCUpnqfISoynoqpxT/ADYtb9heWoifJxz83LxG1bXQo5fjvlfVxXEE0ej2tyHwU0e8yqSeR9EsXjU0HjnKT4GIzzpDcxk/bTkpPiMTW3xsOzBScObMCtVkOsbJ14cPsStwJOIcnOKrFY8kpJlMZmnOfYa1xA+5EUH600fe7Ycnv6+DYRoY8YNK5kp5hX5/nZuJehXDm5heZdh9Om5zjCgm9xeNMf6OrqU79l73eOSZ19rqL8dlyU9MabU3v/ocvHU7Cr4sHNC3vxnj+cCb/tBxRvKhaE/wJxQVtQqmfPniQlJaGrq4uenh579+7lf//7n+z7p0+fyi5mA3h4eBAaGiq7mA0QGBhIXFwcHh4eXLlyBQ8PD5YvX67wO/7+/rRv377I+apfvz6ZmZmcPn36PaKTy8mvkZERDx8+ZMCAAURFReHsLO2E537aWlV+Vq1apfQ7Ly8vtLW1efjwocLyChUqEBOj/CTR9OnTFS6Ovy0t8jw5LAEKeJo435PGEtkXBW8z77I3Dm38jcjQB4ycvrlI+X0befMqkSjJm+IaqjakcpvStZSvd+3MTtzqtsbE3LbQvJaUfP8G0h2snsyUNC0t6U5WQtfOEbMBI0g8vJO0wBtom5pj2nsI5oPGErd5WYlm65b/fvZ7z5D9Pfib5W+yq2Q/FPIkf1HqVlHrdFZmBjuXT0QikdBjyIx835ek/M2IROUsBlXtrKlqJx98ebpWITI2Ae9j58rmyYF8wZWfOqfJx4OiyJtXiUSiNPys7Gy+X7GN8b064Wyn/P2OZU45LpdFouxYV8ozo5QUZbtOR3SVnAABAABJREFUVWRV7ayomqtMero4ERmXgPdx/zJ3shiUxVbAscDWkqq53kPp6eLIi7hE1vteLLEL2jnU1TYW5XereTRl/EwfUpPjuHZ6BzuWfcPoH7fnO8FX7DS4zpUX//X+Zee2Nnz3hfzmtym/3pbnKzctrfzLcrn7IIm7D+QXqG4HJrDmr4b0+7Ayi1cGFWOO31PeMU4BcenaOWI+YBSJh3bwOvAGOibmmPYdivmn44jbuLTk81ocyui47l1o8nhck/sooOFjVo2SvyAWNENi/vOEso4aAP1HTGXzil/49eteaGlpYWXrSPP2vfD321ucmS4aJe1HgbM/Km1vlPcNLvrtxt7JHWe3uu+fzyJQx/lZiURC5aq16dR/IgD2zrWICn9MgN+Wt7qgXRb7XAX9tkSSDUDDdgNp0LofII09ONCf62d3Qd/JBeZRKB3ZKvo5QskQF7QFpfz8/Pj888/JyMggPDyczMxMhe9TUhTv1NTS0srVcSh8uSrZ2dn5GvLcU4DnTAteXFq3bk1iYiJRUVEkJeW/OzNvnHkVlB9tbW0yMzNp2LAhWVmKd/8lJyt/YmXWrFksXLhQYVliYmKBeQAwMDZHS1sn3531KUkxKk+CGZla50+fGIO2ji4GhmZv0liRnKhkm6b5T/of2vQbD26cZMS0jZha2BWa56IyMDZHW1lsiTH57nTLUdTYkvKkSU6MwVBJbPHRzwm+58+gL/9+j0jendGbf4OEPE/LJCXE5ruDtbzJTk5CkpWFtrGZwnJtI1Oy8zy9kMO4Sx/Sgh6QfGKfdEH4M+LT0rCZ+BsJB7aQnRhfYvmtUb89Di71ZH9nZUqfHElOiMbYTP5Ov5RE1XUPCq9bb1OnszIz2LHsW+Kjwhg2ZV2pPT1jbmSAjrY2MQmK7VlsUkq+O+ALUtfFkUMXy9ZUfTl1Lu8TauWhzmny8aAozI1zyqXiMT02KVlpuUx9nca9kOc8eBbBnE37AelgRCKR0Gj0jyydNIImeaZgVJfyXC6LQhZfnJL48jwRVd5I20stYhIU+5WxSSlY5nkiqiB1qzly6PLt4s7ee8mJLe/T2LFJqVgaFz22etUcOHj5TnFnT0ZdbePb/K5+BQMsbZ2xtHXGybU+S6Z15frZnbTuMe6t4y0KTa5z5c1/vX957nIM9x7KbyTX15O+Gc/CXJ+YOPlT2uamevme2i6IRAKBj5Jwqlxy06++jZxxj06ep5V1jE3JyvNUcw6Trn1JC75Pkq/04kvG86dkb32N7aQ/SNi3uUTHPW+rvI3r3oYmj8c1uY8Cmj1m1STycY7i8SkpITbfk8o5jM0sSYzLn15bRxcjY+krr4xNLRg3ZTEZ6WmkJMVjamHD3k1/YWnjUDKBKGFoIo0tKU9syQXGZqU0vbaOLoZGiq/zSk97xfULh+k24IvizbgS6jw/a2RmjXVlxVcHWNm7cu/KsbeKoSz1uYxMrAv9bWNT6fK8sVvbu5IQG1GEiAVB84h3aAtKpaSkEBQUxLNnz/JdzFbm3r17VKlSBUdHR9kyDw8PzMzMCAwMBKRPbDdr1kxhvbx/R0VFYW9vL/tbW1ubOnXqyP6+ffs22tratG3bVmk+0tOlByKdIk4Z+uTJE4KDg5VezC6KW7du0bFjR6XfXb9+HV1dXWxsbAgKClL4REZGqsx/UlKSwqcodHX1qexcm6B7FxSWB929gJNbA6XrOLnWJ+hu3vTnqVy1Njq6eqrT3DmPk2t92d8SiYSDG38l8Opxhk1Zh7m1I8VJV1cf+6q18+Uj+N4FnFyVx+boWp/gPP8Wj/PE5uhan2Al8Tu51c+3vevndmNoYom7p/JyV9J09fSo4uJB4C1/heWBty7hUsNTLXkqNlmZZIQGU7FmPYXFFWvWI+3JA6WraOnr57/L/81diyX9RFGFSkayk82Wts5YV3bDyNRaoe5lZqYT8iBAZd2DwutWUet0zsnGmJdPGTp5LQZGJTc1aV56urp4OFfmYqDiEy8X7wXh6epU5O3cfxaBlalxcWfvvejq6VHF1YPAm/nrnGsZr3OafDwoClm5vPdYYfnFu4/xdMv/xIhhxQrs+PUrts78Uvbp364JVe2s2DrzS+q6FL0sl7TyXC6LIie+ezcvKiwPvHkR15rlOz49XR08qtjjH6j4/sVLgcF4vkUZexD6AivT0rlpqahyYrsYqPjuzIv3n+DpUvQ24H5YZInGpq628V1+N4cECZkZRb9497Y0uc6VN//1/uWrV1k8j3gt+zx5lkp0bBqN68t/V1dXi/p1zLhzv/CbvXNzdzEkJjatuLP8brIySX8WREUPxfpVsWY90oNVjXsq5B/3ZJfOuOetlbNx3dvQ5PG4JvdRQLPHrJpEV08PJxcP7uepY/dvXcSlRn2l67hU9+T+rbx9mAs4u9SS9dNy6OlXwMzSluysTK5f9KVe43bFmf0C6erq4VitFg9uK8b24LY/Vasrbz+qunvmS3//1gWcXGrni+26/1EyM9Np1PrD4s24Euo8P1vFrQHRLxTHGzGRIZhZVn6rGMpSn8vc2rHQ3zazcsDYzIaYiPyxm75l7IKgKcQFbaFY+Pr6cuvWLTZt2kSDBg1o3Lgx3t7enDp1iqtXrwKwePFiRo4cyYgRI3B3d2fmzJnUrl1bYTsnT56kR48edO/enRo1arB06VLMzMxk3z99+pT169ezZs0aevXqRdWqVWnbti0DBgyQfZ+dnU3Pnj2xsrLC0LDod5S+i19++YVPPvmEmTNnUrNmTerUqcN3330HwKNHj9i4cSPe3t706dOHqlWr0qhRI6ZMmUK3bt2KPS/Nuw7n2pmdXDu7i6jwII5smUVCbASN2g0CwHfnAnavmipL36jdIBJiwjmydRZR4UFcO7uLa2d30aLrSFmapp2HEHT3POcOrSIqIphzh1YRHOhPs87DZGkObvyVW/776TduPvoVDUlKiCIpIYqM9NfFFluLLm9iOyON7fCWWSTERNC4vTS24zsUY2vcfhDx0eEc2fImtjO7uH5mFy0/kMfW7E1sZw9KYzt7cBXB9/xpnis2kM4acP2cD/Vb9kZHR32TWnT6cAjnT/hw/sQeIsKC2b52HnHREbTp0h8An01LWLvkR4V1Qp/cJ/TJfdJevyIpIY7QJ/cJDy1D0+29kXTyAIYtOmLQrD26tg6Y9h2GjoUVKWeld1qafPQp5kO+lKV/ffsqleo3wbBVF3QsbdB3qYFZ/xGkhzwiOyGuVPOupaVFs85DOXtgBYFXjxMZ9pA9q6ejp1+Ruk17ytLtXjUV350LZH8XpW4VVqezsjLZvvRrwkPu0G/MPLIlWbL6l5lZcifAc/uscwt8zl5lz7mrBEe8ZP62Q7yITaB/2yYALNl9jB9X75Sl3+R7Ab/r93gaGUPQ80iW7D7GiWv3GNihaank9210+nAI5/LUudjcdW6j6jr3+vUrkhPVV+c0+XhQFJ91bYXPmSvsOXuF4PCXzN9yUFou270plzuP8uOqHYD0xjk3RzuFj4WxIfp6erg52lGpgn6p5r0w5blcFkXnDz/j3Akfzr2Jb9ua+cRGv6Dtm/h2b1zCmsV543tA6JMHpL1OJSkxjtAnD8pkfEM6Ncfn/DX2nL9OcEQU87YfJSIugf5tGgKwxOcEP67dI0u/8cRFTt64z9PIGB6Hv2SJzwl8rwcyqF1jNUWg2pAOTdl94QY+F24QHBHNvJ3HiYhLYEBrLwAW7/Hjh3X7ZOk3nrzMyRsPePoylsfhUSze44fv9fsMatuoRPOprraxsN9NT0vFd9dCQoNuEB/9nPCnd9m79kcSY19Qu/EHJfpvosl1riA6hgaYeNbExLMmAAbVHDHxrElFJ/tC1iwd//X+JcCOfc8ZMqAKbZpZUq2KAT98U4O0tCyOnX4pS/PjtzUYN1T+7sgRg5xp0sCcyrYVcatmyPSvquNezYg9h8vOE0xJJ/dj2KIjhs07oGvngFm/4eiYW5H8Ztxj2mswFsPkr3p7dfsKleo3xbB1V3QsbdF3qYH5x6NIe/Kw1Mc9RVGex3WF0eTxuCb3UUCzx6yqlPXjnDIdew7lwondXDjpw4uwYHaum0tsdAStukjP9+7dtJj1f38vS9+q8wBio8PZtW4eL8KCuXDSB/+TPnT8SH7Me/LoFjcu+RIdGcbjwKv888fnSCTZdO41olRja9djKBdP7uKi325ePA/CZ/0c4qIjaNlpIAD7tyxi4/9Nl6Vv2flj4qIj8PGey4vnQVz0280lv9106Dk837Yv+e2mbqMOGOaZHaOkqOv8bPMuwwkLvsmZA8uJiXzKLf/9XD21nSYdB79XPOrscxXlt7W0tGjxwSgundjA3StHiIl8ysndi4mOCMardf/3il0oPpJsSZn9aCIx5bhQbHr37s3ff//NmTNnyM7O5siRIwrv3d6+fTuurq7MmTOHihUrsmvXLpYtW0bXrl1ladasWYOnpyfe3t5kZmayaNEi/Pz8FH7n888/588//2Tp0qVYWlry7Nkz/vzzTwDCw8OZMWMGs2fPZu3atXh7ezNiRMl1VE6fPs2AAQP46aefmDZtGomJiZw5c0b2/YgRI/jxxx9ZsGABDg4OxMTE4O/vz6FDh4o9L3WadCc1OZ7T+/6P5IQobBzcGfzNCsyspFPpJCVEkRAbLktvbu3I4G9XcGTLbAJObsbYzIZun/5ArUby/VHFzYv+4xdwcvdiTvoswcLGif7jF+LoKr+L8IrfFgDWzRmqkJ9eI/+kQau+xRNb0+6kpkhjS8qJ7Vt5bMkJUSTEKMb22ZvYLufENjhPbO7y2Px8lmBu48SAPLGB9E7DhJhwGrQunljeVaOWXUlOiufgzhUkxkVTuYobX37/D5bW0jvyEuKiiI1WPFnzx3eDZP//LPgeAecOY2Ftz5/LDpdq3gvz6toF4g2NMOnWHx0TczIiQole+idZb6aP0jExR9dCPtVQ6qVTaFWsiFHbDzDtOxTJqxReP7hDwt5Nasl/y26jyUh/zcGNv/IqJQFHl3oMmbSaCrmmZkyIDUdLW/6UQVHqVmF1OjHuBQ9unARg+czeCnkaNmU91WqW/IC7a+O6JCSnsvLAKaITknCrbMvfXw2hsqUZANHxybyIlU8xmJGZxaIdR3kZn0gFPT1cK9uw5KshtK5bXcUvqE/jll1JSYrn4I4VJOSuczaq69zvk3PVuaB7XD57GEtre/5cXrp1TpOPB0XRtUk9abncd1JaLh1s+fubYVS2kj7pFZ2QxIvY+FLLT3Eqz+WyKBq36kpKUgIHt6+Uxfe/H/7OFV80sdEvFNb5bZI8vqdBgbL4Zq0o/r7W++jaqDbxyamsOHiG6MRk3Crb8M+Xn8ray6iEZCLytpe7jvMyPokKerq4Vrbm7y8+oXVddzVFoNoHjWqRkJLKykPniEpMxs3emv+bMIjKltIpEaMTk3kRpxjbQp8T8tjsrflnwkBa13FT9RPFQl1tY2G/q6WtQ3TEE26e/4rU5DgqGZrhUK0uI6dvwsahZPe3Jte5gpg2rEPzExtkf9eaLz1BHuq9m1ujpqtarVT9l/uXAJt2hVJBX5uJn7tjbKTHvYeJfPvzLV69kr/Ky9a6IrnP0xkZ6TLly+pYmOuTkpLJw+Bkvph2k8BH7zYbW0l4dfUC8YbGmHQf8Gbc80w67omNAqTjHh3zXOOei35oV6yIcdtumPUbhiQ1hdcPb5Pgs1FdIRSovI/rCqLJ43FN7qOAZo9ZVSkPx7m8Grb8gJTkeA7vXEFiXBT2Tm5M+P7/FOpYXK4+iZWtIxOmL2XX+rmcOboVU3NrBoycRoNmnWVpMtPT2b/lH6JfhlGhogG1G7Ri2P/+xMDQpFRj82rRjdTkBI7uWk5ifBT2Tu6Mm7YMizexJcZFE5er/bC0cWTs1KXs8Z7LuWNbMDW3oe/w6Xg27ayw3ZfhIQQ/uMbn368stVjUdX7WwaUug778G9+dCzm9dylm1o588Ol06jV//yfT1dXnKupvN+8yjMyMNI5umc2rlARsnWowZNIaLGyqvHfsglAeafHmlfWCIJRNEomELec1s5p+0lLaGdh6QfPiG9RCGpvf7eJ973tZ0b5uJQDCvhyg5pwUP8d/pE9uamK9y6lzqWe2qzknJcOgzccAnLqjefWuXR1pndPocnl+l5pzUjIMWvYDNLtcnr6bquacFL+2taXvXH3lV/ZOqheHSu2lTzO8PuGt5pwUv4odpTfVaHJ7qYl1DuT17qBeDTXnpPj1yJBOuayJ5RLkZbPVh6fVnJPid26/9LVToRP6qTknxc9pqbTvpYljOpCP6zRxTJ4zHtfEfkpOH0XTx6yafKzzvVVGXvVQjDrVqwDA4esZas5JyejWQDr9tyafn9XEPtgnLbXQKkOv6Piv+mJBvLqzoNL/TTJTdxaKnXhCWxAEQRAEQRAEQRAEQRAEQRAEQRAEoYg0dWrvskq8Q1sQBEEQBEEQBEEQBEEQBEEQBEEQBEEok8QFbUEQBEEQBEEQBEEQBEEQBEEQBEEQBKFMElOOC4IgCIIgCIIgCIIgCIIgCIIgCIIgFJGYcbx0iSe0BUEQBEEQBEEQBEEQBEEQBEEQBEEQhDJJXNAWBEEQBEEQBEEQBEEQBEEQBEEQBEEQyiQx5bggCIIgCIIgCIIgCIIgCIIgCIIgCEIRScSc46VKCxD/4oJQhkkkoooKgiAIgiAIgiAIgiAIgiAIgiClpaWl7iz8542bHavuLKi0YpqFurNQ7MSU44IgCIIgCIIgCIIgCIIgCIIgCIIgCEKZJKYcF4RyYMt5zXxK+5OW0rvINDG+nNi2+2erOScl4+Pm0vuhDlzLVHNOil9PL+mhUZPL5bWHMWrOScnwqm4JwI1HUWrOSfGr724NaHa5PHH7tZpzUjI61q0IaHa5POfppeacFL9WN68B4B+YqOaclIzmHiYA7AnIUnNOil/vxjqAZreXmljnQF7vfG+lqTknxa9TvQqAZpZLkJfN/zus5oyUgC+6Sf976FqGejNSArp76QGaOaYD+bhOE8fkOeNxTeyn5PRRNH3MqsnHuoN6NdSck+LXI+MBALO2a17fGWD6x5rff9bk2AT1ErPrli7xhLYgCIIgCIIgCIIgCIIgCIIgCIIgCIJQJokL2oIgCIIgCIIgCIIgCIIgCIIgCIIgCEKZJKYcFwRBEARBEARBEARBEARBEARBEARBKKLsbDHleGkST2gLgiAIgiAIgiAIgiAIgiAIgiAIgiAIZZK4oC0IgiAIgiAIgiAIgiAIgiAIgiAIgiCUSeKCtqDx/Pz8WLRokbqzIQiCIAiCIAiCIAiCIAiCIAiCIGgAiURSZj+aSLxDWxDKscsnN3PhyGqS4qOwcXDjg0++x7l6I5XpQx5c5ujW2bx8/hhjMxtadhtN4/aDFNLcu3KUkz5LiIt6hrl1FTr2/QaPhp3f6nfTXqfgu3MB96+f4FVyPGZWDjTtNITG7T8p97HNHFlT6e93HvAdLbuNKnJ8hbl0YjPnDq8h+U0+un06nao1VMf/5P5ljmyZI43f3IZW3UbRpIM8/sjnjzi5+2/CQ+4SHxNOt0+m0aLrsGLL79s6f2wLpw6sJTE+CjtHN3oNnYZLzYYq0wfdC2Dfxrm8CHuMibkN7XuOpEXngQppXqUkcmjbYm4H+PIqJRELa0c++uw7PBq0KdFYJBIJp/b+w9XT23mdmoiDSz16fPYzNg7uBa73vuUxKzODkz6LeXTrNHFRYVSoZIRLrRZ06j8RE3PbEos3r2MHd3Fg92bi42JwrFKNoWO+pmbt+krTXr5wiuOHfXga/IjMjHQcq1Sj36ej8PRqVmr5fRtHD+5m/+4txMfG4FilKsPGfI1HHU+laS9dOM3xQz6EBD+Wxdb/05HUb9i0lHMtpa5yCXDv6jGuntpG+NO7vEqOZ9xMH+yreJRInKqcPrIN333rSIiLxt7JlQHDp+BWy0tp2oS4KHatX8Cz4HtERTyjXfdPGTBiSqnm922U53JZFHYfD8Bx+FD0raxIDQomeO58Eq9fV5nefuDH2A8aSIXK9qS9eEHYqtW8PHCwFHNcdCcO7eDwno3Ex0Xj4OTCp6MmUqN2A6Vp42Oj2br2L0KCAomMCKVTj4EMHj2plHOsmv/xLZw+tIak+ChsHdz48LNpVKupup8SHBjAgU1ziHz+GBMzG9r2HEmzjoOUpr3hf4gt/zeZWg07MOzbf0oqBLKyMjm19x9uX9xPckI0RqbW1G/VhzY9P0db+/3u+y6sX3r93G72rvk+33o/rLiJnl6F9/rtt6VJde7M0a347l1HQnw09o6u9B8xBTcP1f3LR3evsGv9PCLCgjA1t6ZzrxG07vKx7PuszAyO+qzm0ul9xMe+xLZyVXoN/obaDVqVeCzqGAudPbiCwKvHiY4IRle/Ik5uDejcfxJW9i4lFmcOiUTCpSP/cNd/G69fJWJXxZN2/X/G0r7gfsvjm0fxP7SYhOhnmFpVoUWPb3GtJ48pOyuTS0f+5sHV/aQkRWNoYo1H4z406TIBrfes50V17thW/HKNe3oPnYprAeOex/cC2Ltxnmzc06HnCFoqGfcc3LaEW7JxjwO9PvuOWiU87slLk8Z0ymj6mDw3TeqjKKNJY1ZNOta9K4tWjXCZNApTrzpUrGzDlX4TiNx3Qt3ZeietamtR30WLinoQHgvHrmUTnag6vZUJtK6jjZ05mBlq4Xs9m4BHpX/RSpPPg6nzXIrfnr+5c/kQibEv0NHVw965Nh37foOjq/LxviD8F4kntAWNoaOjUyLb1dbWRktLq8xt887lQxzZMovWPcczfqYPVdwbsXHRWOJjwpWmj4sKY9OicVRxb8T4mT607jmOw5v/4N6Vo7I0oY+vs2P5RDxbfMT4X/bi2eIjdiz/lrCgm2/1u0e3zubxnXP0HTOXL/44SLPOwzi06XfuXy9aB7MsxzZp0VmFT68Rf4CWFh4NuxQptqK4fekQhzfPpu2H4/j81904V2/IhoXjCox/w8LxOFdvyOe/7qZNz7Ec2vQndwOOydJkpL3G3NqJzgMmYmRqVWx5fRfX/Q+z13s2HXuPZeKsnVSr4cWq2eOIi1YeX8zLMP6d+znVangxcdZOOvYaw571f3Lrkjy+zMx0Vvw5mriocIZ9s4ipCw4yYMxMTC1sSjye84f/xf/YOrp/9hNjftqBkak13vNHkvYqWeU6xVEeM9JfE/H0Hm0+nMC4GbsY+OXfxESGsGXJhBKPOYf/WV+8/11M74+HMWvxOmrU9mT2zElEv3yhNH3g3RvUrd+YqTPm88dfa6lVryHzfpvCk6AHpZbnorpw5gTrVy2hz8dDmb1kDTVrezJr5mTVsd2RxjZt5jxm/bWa2vW8mPvbVJ4EPSzlnEupq1wCZKS9wsndi0791XNi68r5I+xcN5cP+o5h+rxtuHl48X9/TiA2KkJp+syMdIxMzPmg7xgcnKuXcm7fTnkvl4Wx6toFlymTCV21musDPyXh2nVqL/2bCnZ2StPbDeiP81df8mz5Cq71HcCzZctx+X4aFm1L/6R3YS6dO8bmNQv5cMAIfl24keq16rPwt6+JiVK+7zIy0jE2NePDASNxqlrwyZPSdvPiYfZvnEWHj8bx1e+7qFqjIWvmqT6Ox74MY8388VSt0ZCvft9F+4/Gss/7T25fPpYvbVz0cw5unke1GqpPzBaX84f+5cqprXQf/BNf/HGQzh9P5sLh1Vw+sfG9tluUfilAhUpG+fqVpX0xW5Pq3NXzR9i5di5d+41h+tzt0rb/D9Vtf3RkGEtnTcDNw4vpc7fTte9odqyZzfWLx2Vp9m/9h3PHdzJg5HR+WrSHVp0HsGret4Q+CSzRWNQ1Fgp5EEDjDp8y+sdtDJ20huysTDYsHE16WmqJxgtw9cQqrp9aS9t+PzNo4k4MTKzYs2wE6a9V91sinlzn8PpvqdmoF59O2UvNRr04vO4bXoTcVNju7QtbadvvZ4ZMO0TLD7/jmt9qbp7dUOIxgXTcs8d7Np17j2HyrB241PBi5ezxxEUrL5cxL8NYNXcCLjW8mDxrB517jcZn/SxuXpKXy8zMDJb9OYbYqOcM/2Yh0xccYOCYX0pl3JObpo3p8tL0MXlumtRHUUaTxqyadKx7HzqGBiTeesDdr39Vd1beS7OaWjSprsWxa9ms880m5bWEQW210S/g8UM9HYhPlnDqloTkV+p7+lKTz4Op81yKpV1Vug/+ic9/3cfI6Zsws3Jgw8JRpCTGFlt8glDeiQvaQpmlr6/P4sWLiYyM5NWrV5w9e5ZGjaR3LbVt2xaJREKXLl0ICAggLS2N1q1bY2BgwPr160lKSiI8PJyJEyfm266enh5z5swhLCyM5ORkLl68SNu2bWXfDxs2jLi4OHr06MHdu3dJS0vD2dlZZT5bt25Neno6traKd4LNnz+f06dPv9M2i8L/6Dq8WvejYZsBWFd2pdun32NqYccVvy1K0185tRVTS3u6ffo91pVdadhmAA1a9+XC0TWyNBePe+NaqwWte4zD2t6F1j3GUc2jGRePr3+r3w0NukH9Fr2pVrMp5laONGo3EDunGoQ/uVPuYzM2tVb43L9xkmo1m2Jh41Sk2IriwtH1eLXpS6O2A7Cp7Er3wd9jYmHH5ZNblaa/7CeNv/vg77Gp7EqjtgPwat2X80fk8Tu61OWDQd9Rr1kPdHX1iy2v7+LMwfU0ad+PZh36Y+vgSu9h0zGztOfC8W1K0/v7bsPM0p7ew6Zj6+BKsw79adKuL6cOrpOlueznQ2pyIiMmLaFaDS8srCvjUrMhlZ2VP1FfXCQSCRePe9Om53hqNeyCrWN1+oyaTUb6a25fOqByveIojxUNjBk6eQ11mnTDyt4FJ9f6dB/8IxFP76o80VLcDu7ZSvvOH9Kh60c4OFVl2JhvsLSy4fhhH6Xph435ho/6fYZr9VrYV3Zi0NDx2Nk7ce3y+VLJ79s4uGcrHTr3pGPXD3F0qsrwsV9jaWXDsUN7lKYfPvZrevUfjFt1D+wdnPhk2DjsKztyVQ2xqbNcAni26EW7j77ApVbzEo1TlZP7N9CiQx9aduqLvaMLA0ZMwczSjjPHtitNb2njwMcjp9Ks3YdUMjAu5dy+nfJcLovCYchgIn32EOmzh1dPnvBk3nzSXkRi93F/peltevbgxc7dRB89Rtrz50QfOUakz14cRpSNp51yO7p3M2069aJt595UdqrG4NGTsLCy5eSRnUrTW9tWZvDoybRs34NKBkalnNuCnT28jsbt+tGkvfQ4/tGQ6Zha2nPxhPJ+ysWT0uP4R0Okx/Em7fvTqG1fzhxaq5AuOzuLrUun0rnfl8Xar1IlNOg6Net3pLpnO8ytHKnd6ANc67QkPETeX83MTOfY9nksmNiGP8Y3YNVvH/Pk/qUCt1uUfqmUVr5+ZWnTpDp34oA3zTv0oWXHftg5utB/xFTMrew4q6LtP3d8B+ZW9vQfMRU7RxdaduxH8w59OLFPfsy7fOYAXfuOpo5Xa6xsHWnTdSAe9VtwYr93icairrHQkIn/0qBVX2wc3LGrUpPeI2eREBNOeMjdEo1XIpFw44w3jTuPx82zC5b21ek8eA4Z6a95cFV1v+XG6fVUqd6Cxp3HYWHrSuPO43Cs3owbp+UxRYTcwKVOR6rVboeJpSPu9T+gSo1WRIYWbVz6vk4d9KZp+76ycU+fYdMws7Tj/HHl7eUF3+2YWdrRZ9i0XOOePvjlGvdc8ttNanICoyYtwUU27vHCoYTHPXlp0phOGU0fk+emSX0UZTRpzKpJx7r3EXX0DA9n/MWLPccLT1yGNXbX4kKghIfPIToRDlyWoKcDtaqofgAqIg78bkkIDJWQmV2Kmc1Fk8+DqftcSr1mH+JauwUWNk7YOLjTddA00l4lExmm/htqBNUk2ZIy+9FE4oK2UGbNnTuXfv36MWzYMLy8vHj8+DFHjx7F3NxcIc306dPx8PDg1q1bzJs3j/bt29OnTx+6dOlCu3btaNhQ8QmPtWvX0rJlSwYNGkS9evXYsWMHR44cwc3NTZbGwMCA6dOnM3r0aGrXrs3Lly9V5vPs2bMEBwczZMgQ2TIdHR0+++wz1q6Vn6h7m20WJjMznfCnd3Gt3VJhuWvtloQ+Vj5FYGjQjXzp3Wq3IjzkLlmZGfI0dfKkqdOK0KAbb/W7Vdy9eHDjJIlxkUgkEp4EXiTmRQiudQqfsqisx5ZbckI0j26dpkHrfoXGVVSZmemEh9zFLV9eC4j/8Y386eu25Hmu+MuKzMx0wp7co0a9FgrLa9RrQcjDG0rXefroZv70ni0JDZbHd/eaH87unuxe+zszxrVh3ne98N2zkuzsrBKJI0dcVBjJCVEK5UZXT5+qNRqr3F9QMuUR4HVqEmhpUdHA5B2ieTuZGRk8efyAeg2aKCyv16AJDwNvF2kb2dnZvH6VipFxyef3bWRmZBD8+CH1GjRWWO7ZoDEP7xftBGh2djavXqViZFT6sZW1clmaMjMyeBYciIen4sV0D8/mBD+4qWKt8qG8l8vCaOnqYuThQbz/RYXl8f7+mHgqn2JNW1+f7PQ0hWXZaa8xrlMHLd2y82alzIwMQoLuU6e+4lTvdeo35fH9W2rK1bvJzEzn+ZN7uOdpK6rXacHTRzeUrvPs0Q2q11E8jlev24qwJ4r9FF+fpRgam9OkXfH1qwpSxb0hwYH+RL94AsCLZ/d59uga7nXlTxvvXfM9oY+v0X/8Qj7/dS+1Gndl48IxxESGqNxuUfqlAOlpqSz6rgMLJrVl01/jiHh6r3gDLIQm1bnMjAxCgwPx8FQsZx71mhP84IbSdYIf3sSjXt5jRQueBt+T7afMjHT09BQvOunpVyDofskd89Q1FlLm9askACoZmr5tGG8lMSaM1MQoqtSUjxV1dfVxcGtMRIjqf+uIkBsK6wA412ytsE5ll4aEPrxI3EtpPY96fp/w4KtU9WhLScvMzChg3KO8TxKiZNxTM9+45xRV3T3ZufYPfhrXhjnf9eZ4KYx7ctO0MV1emj4mz02T+ijKaNKYVZOOdQKYGYJRJS2evJBfcMrKhmdR4Fh2JnBQqqydbyjO82BlKbbMzHSunt5GhUrG2DqV/o1dglBWlZ0zPYKQi4GBAZ9//jnDhw/nyJEjAIwZM4bOnTszatQoAgICAPj555/x9fUFwNDQkFGjRjF06FDZsmHDhhEWFibbrouLC5988gmOjo5EREin5FmwYAEffPABI0aM4IcffgCkT4dPmDCBW7eK1oFfvXo1I0aMYP78+QD06NEDAwMDtm+X3yVZlG3q6+tToULhUw2mJsUhyc7C0NRSYbmhiSXJCdFK10lOiMLQRHHAb2hqSXZWJqnJcRib2ZCcEI2hibJtRr3V73b79Af2r/uJhZPaoq2ji5aWFh8N/x3n6oVPH1nWY8vtxoU96Fc0LNbpxlOT4snOzsLIRLEHa2RiSZLK+KMxyhObkYmVQvxlRUrim/jy/DsbmaqOLzE+mhpK0mdnZZKSFI+JuTUxL8N4HHUJr5Y9GT11GdEvnrJ77e9kZ2XSpV/JTcGdnCgtP8rKVkIBd4eWRHnMyEjDd+cC6jbtScVKJX+nfOKbfWlqZqGw3NTMgoT4ok2HdHDPFtLSXtGsVYeSyOI7S0xMkMZmnic2cwvir8UUaRsHfLaS9vo1zVuXfmxlqVyWtuSkOLKzszDOk0cTU0sS48tGHt9VeS+XhdEzN0NLV5f0GMVY0mNiMbOyVLpO3AV/7Pr0JubkKVICAzGq5YFt715o6+mha2ZGRnTZ2OdJb47tJnnaSxNTSxLiirbvygpZP0XZcVxFHUtKiFaaPvdxPOThNQJO7eabP3eXWN7zatV9DGmvkvjnh+5oa+uQnZ1Fx77fULdZTwBiXz7j9qWDTJx/SvZOvpYfjOLx7XNcP7ebTv3yzwQFReuXWtm70HvULGwdqpP2OpmLx71ZPetTPv9lD5a2VUs07hyaVOdy2n4TM8V8G5upbvuT4mMwzpPexEy6n5KT4jE1t8bDswUnDmzArVZDrGydeHD7ErcCTiEpwYtr6hoL5SWRSDi6bTZV3Bti61iyr+NITZLmwcBYMX8GxlYkxarut6QmRStZx5KURHlMDTtK6/mGWd3Q1tIhW5JF8+7fUqNhz2KMQLmUROV9EmNTSxJV7Muk+Gil6XOXy5iXYTyKek7Dlj0YO3UZUS+esmvtH2RnZdG13+clFk9umjamy0vTx+S5aVIfRRlNGrNq0rFOAMOK0v+mvFZcnvJagqmhFlB2n6wsS+cbivs8WFmI7cENP3aumERG+iuMTa0ZOnkNhsbmCIIgJS5oC2WSq6sr+vr6nD8vn9InMzOTy5cv4+HhIbugfeXKFYV1KlSogL+/v2xZXFwcDx7Ip+Xw8vJCW1ubhw8V3x1ZoUIFYnKdzElLSyvyxWyAdevW8fvvv9O0aVMuXbrEyJEj2b59O6mp8veNFWWb06dPZ+bMmUX+XS3yTEMjAQp4N3e+93ZLZF8UvM08ywr73Uu+GwgLusknXy3F1NKBpw8DOLjhF4xMrXGtrXg3qcq8ltHYcrt+dhf1mvUsmfcd5s2GRJI/bwrpFb+TyP8BijdfxST/v7Ok4P2rLL30C+mf2dkYmVgwYMxMtLV1cHKpTWLcS/wOrC3Wkx+3/Pez33uG7O/B3yyXZkNZ3guIR5r14iuPWZkZ7Fw+EYlEQo8hM/J9X6KUltXCnT99jF2bVzPpxzn5TjCUFXn//SUSifJ9ncf508fZuXkNk3+ahalZyQ88ymq5VKe8sUsopA0tR8pLuXxnec/daGnJ2/w8QleuQt/KEs8N69DS0iI9NpaX+/bjOGI4lMGTcPn2HQUf+8qy/GWu4HKoLL10OaS9SmHrsqn0G/1LqZ6suXP5ELf899Nv7HxsHNx48ew+R7b8ibGZDfVb9pE+MS2R8Pf33RTWy8pMx8DIDIA/PveSLa/X/EM+HPrLm7gK7pc6udbHybW+7GsnNy9W/NKXS74b6T74x2KNs1AaVefy9xffplxKJIr95/4jprJ5xS/8+nUvtLS0sLJ1pHn7Xvj77S3OTCvPm5rGQjkObfyNyNAHjJy+uUj5fRv3r+zDb7u83/Lh2BUq8icpwlCm4GPio+uHeHB1Hx8MWYCFnRtRzwM56zMLI1MbPJr0eZ8wikxZXAWWSyUxgXwf54x7PlYY90Rx8sDaUrugrSqv5WVMV2QaPibPTZP6KEpp1JhVc451/yW1q2jxQUP5vth+TjpfuLJuWFm7ll1WzzcUx3mwshhbNY+mjJ/pQ2pyHNdO72DHsm8Y/eP2fDdNCWWHpk7tXVaJC9pCmSQbrOU5maKlpaWwLCUlJd86BdHW1iYzM5OGDRuSlaV40iU5OVn2/69evXqr/EZFRbF//35GjBhBcHAw3bt3p127dgppirLNWbNmsXDhQoVliYmJ+dIZGJujpa2T7y6ulKQYlQc4I1Pr/OkTY9DW0cXA0OxNGiuSE5Vs09SqyL+bkf6aE7v+YtCXf1Pdsx0Adk41ePHsPheOrin0gnZZji23pw+vEPPiCQPGLyownrdlYGyGttJ8xOa7Az6HkamV6vjfnHAtKwxNpPHlvbM9OTEWYxX718TMSml6bR1dDN/EZ2JmjY6uLtraOrI0Ng6uJMVHk5mZXmzvKKtRvz0OLvVkf2dlpkvzkxCtcNd9SqLq8grFWx6zMjPYsexb4qPCGDZlXak8nQ1g8mZfJsQp3tmemBCX7w7/vPzP+rJyySy+nvY7des3LjCtOpiYmKKtrUN8nqcSEuPjCj2RceHMCZYvmc23036jXinFVhbLpboYGZujra2T7ymFpITYfE8nlDflrVy+rYy4eCSZmejneTJU38KcjBjlT9Bkp6XxaMYvPP7tD/QsLEiPjsauX18yk5PJiIsvhVwXjfGbY3tCvOK+S0qILUMnR4smp5+S92ns5ATV/RRjUyul6XP6KZHPHxMX9Zz1C76QfS+RSE/yTR9al8nzDmJpW6WYI4Hj2+fRqvsY6jbtAYCtYw3iY8I5e3Al9Vv2QSLJRktbh3E/70QrV/8CQL+iAQDjZ8rfv1nhzfG3KP3SvLS1tXGoVpfYyKfFFV6hNKnOFdj2qyqXZpYkxuVPr62ji5GxdIptY1MLxk1ZTEZ6GilJ8Zha2LB3019Y2jiUTCCobyyU26FNv/HgxklGTNuIqYXde0SjnEudDtg5y6e1z+m3pCRFY2gq77ekJsdgYKx63lUDYytSkxRjepUcq7DOuX1zadhxLNW9pPXcqnINkuLCueK7osQvaBuavCmXefZNUgHjHmMzq3zp5eMeabk0MbNGO8+4x9bB5c24JwNdXb1ijiS/8j6mK4ymj8lz06Q+ijKaNGbVpGPdf9GjcAnhsfLz2TpvXgJrVFHxKW2DClqkpJWti2Nl8XxDcZ0HK4ux6VcwwNLWGUtbZ5xc67NkWleun91J6x7j3ilGQdA04h3aQpn0+PFj0tLSaNUq93u0dGnUqBGBgYEq10lPT6dZs2ayZWZmZlSvLp8i7fr16+jq6mJjY0NQUJDCJzIy8r3y/O+//zJo0CDGjRtHUFAQFy5ceOttpKenk5SUpPBRRldXn8rOtQm6p/gbQXcv4OTWQOk6Tq71CbqbN/15Kletjc6bQa/SNHfOy54gKcrvZmVlkp2VgZaWYvOira0tOzlZkLIcW27Xzu7E3rk2dlWK9z0murr6VK5aW0k8BcTvlj+2x3fO45Ar/rJCV1cfx2q1eHhLMb8Pb1+gavX6Stdxdvfk4W3F9A9uXcDJRR5ftRoNiH7xjOxseRmLigjBxMy6WE98VKhkJOtYWto6Y13ZDSNTa4Vyk5mZTsiDAJX7C4qvPOZ04mNePmXo5LUYGJXek226enpUc6vBreuXFZbfvhFAdY+6Ktc7f/oYy/76nS8nz8SrcUuV6dRJV08PF7fq3LoRoLD81o0rVK9ZR+V6508fZ+lff/DV5Bl4NS7abBTFoayVS3XS1dOjiosHgbcU3wl7/9ZFXGoofydseVHeyuXbkmRmkhwYiFkzxXc4mjVrRuLNgt9/LsnMJP3lS8jOxvqDrsSeOavyCVN10NXTo6prTe7euKSw/O6Ny7jVrKdirbJJV1cfh2q1eHRHsR14dOcCzu71la5Txb2+kvTncawmPY5b27vw7ay9fP3HbtnHw6s9Lh5N+PqP3ZhaFv8FNYCM9Fdoaavur9pV8UCSnUVKUqxCG2tp64yxqTWAwrKck1FF6ZfmJZFIePEsECMz6+IOUyVNqnO6eno4uXhw/5a/wnJp219f6Tou1T25n+dYEXjzAs4utfLtJz39CphZ2pKdlcn1i77Ua9yuOLOvQF1jIZCWw4MbfyXw6nGGTVmHubVjMUSUn35FI8ysnWUfCzs3DEysCX0gn50tKzOd548DsK+qun9hX7U+z3KtA/Ds/jmFdTLTX+e78V1LSyffjfMlQVdX7824R7FcPrztT9XqyvskVd09eXhbMX3+cU/9fOOel7JxT+mM/cr7mK4wmj4mz02T+ijKaNKYVZOOdf9F6ZkQlyz/RCdC8isJVW3lxyhtbahiDWFl461JMmXtfENxngcra7EpI0FCZkb6W0YmCJpLXNAWyqTU1FSWLVvGvHnz6Nq1Kx4eHqxatQoDAwNWr16tdJ2UlBRWr17NvHnz6NChA7Vr12bdunUKg6FHjx6xceNGvL296dOnD1WrVqVRo0ZMmTKFbt26Kd1uUR09epSEhAR+/PFH1q5d+17bKormXYdz7cxOrp3dRVR4EEe2zCIhNoJG7QYB4LtzAbtXTZWlb9RuEAkx4RzZOouo8CCund3FtbO7aNF1pCxN085DCLp7nnOHVhEVEcy5Q6sIDvSnWedhRf7dipWMcK7RmGM75vHk/iXiosK4fm43Ny/sxcOrc7mOLcfrV8ncCziKV5sBRYrnbbXoOoyrp3dx9cwuXoYHcWjzLBJiImjSfiAAx3YsZOdKefxN2g8iPjqcw1tm8zI8iKtndnHtzG5afiCPPzMznYingUQ8DSQrK4PEuJdEPA0kphSfBMrRpscwLvnt4pLfbiKfB7HXezZx0RE07ySN7+CWRWxeOl2WvnmngcRFR7B3wxwinwdxyW83l/120a7HcHmazgNJTY5nz/pZREWEcO/aaU7sWUXLLp+UaCxaWlo06zyUswdWEHj1OJFhD9mzejp6+hWp21T+br7dq6biu3OB7O/iKI9ZWZlsX/o14SF36DdmHtmSLJISokhKiCIzs3Q6uz16D8Lv+H78jh/geWgI3qsWEx0VSaduvQHYsn4ZSxf+Kkt//vQxli36jc9G/g/3mnWIj4shPi6G1JRkFb+gPj16D+LksQP4HTtAWGgI61ctIToqks7dewOwed1y/lnwmyz9+dPH+b+FvzNk1Je416yt1tjUWS4BUpPjiXgWSFR4EAAxL54Q8SyQJBXv6SxuHT4cwoUTu7lwwoeIsGB2rp1HXHQErbtI2+w9mxazbskPCuuEPrlP6JP7pL1OJTkhjtAn94kIDSqV/L6N8lwui+L5hk3Y9u2Dbe9eVKpWjWqTJ1HB3o4XO3YB4PzVl1T/Xd6mVHSugnWP7lSs4oRRndrUmDMLAzdXnv79j7pCUKlrr0857buXM777CA99wubVC4mJfkH7rv0A2LHhH1b+pThV3tPgBzwNfkDa61ckJcbxNPgBz0OD1ZF9Ba27DSfg1E4CTu8i8nkQ+zfOJj4mgmYdpcfxw9sWsm35NFn6Zh0GEhcTwf6N0uN4wOldBJzaRZvuIwDpCVQ7J3eFTyUDEypUMsTOyb3ELmJUr9+eMweW8/DmKeKiwwi8ehz/o+tk/VUru2rUbfYhPv9O5d7VY8RFhfH8yW3OHVrFw1unVW63KP3SU3v/4fGds8S+DCXiWSB71/7Ai9D7+fqcJU2T6lzHnkOlbf9JH16EBbNz3VxioyNo9abt37tpMev//l6WvlXnAcRGh7Nr3TxehAVz4aQP/id96PiR/Jj35NEtblzyJToyjMeBV/nnj8+RSLLp3GtEicairrHQwY2/SqfhHzcf/YqGsn5lRnqeF3wWMy0tLeq3GUrA8RUE3TpOTMRDjm+W9ltyv+v62MYpnN8v77fUbzuUZw/Oc8V3JbGRQVzxXUnoQ3/qt5XHVK12ewKOL+fJ3VMkxoQRdOs410+txbVupxKNKUe7HkO5mGvc4+M9h7joCFq8Gfcc2LKITbnGPS06fUxcdAR7NsyVjXsu+e2mfa5xT4s34x6f9bN5GRHC3Wun8d2zilZdSrf90KQxnTKaPibPTZP6KMpo0phVk45170PH0AATz5qYeEofMDGo5oiJZ00qOtmrOWdvJ+CRhBYeWlR3ACsT6NlYi4wsuPdMftNVzyZatK2reNHbxkz60dEGo0rS/zcvnYn6AM0+D6bO2NLTUvHdtZDQoBvERz8n/Old9q79kcTYF9Ru/MF7xyaUnGyJpMx+NJGYclwos6ZNm4a2tjYbNmzA2NiYK1eu0LVrV+Lj41Wu891332FkZMS+fftISkpiwYIFmJqaKqQZMWIEP/74IwsWLMDBwYGYmBj8/f05dOjQe+VXIpGwbt06vv/+e7y9vd9rW0VRp0l3UpPjOb3v/0hOiMLGwZ3B36zAzEo6LVBSQhQJseGy9ObWjgz+dgVHtswm4ORmjM1s6PbpD9Rq1FWWpoqbF/3HL+Dk7sWc9FmChY0T/ccvxNHVs8i/C9B//EJO7FzI7pXf8SolAVPLynTo+02RT9KV5dgA7lw6iASJbIrK4la3qTQfp/YuJSkhClsHd4ZMXC7LR3J8FAkxEQrxD5m4nMNbZnPphDT+7oO/p3bjLrI0SXFRLJ3RV/b3+SNrOH9kDVVrNGbU9JIvr7k1aN6N1KR4ju9eRmJ8FPZO7oyeuhwL68oAJMZHER8tj8/SxpHRU5axd8Mczh/bgqm5Db2HfU+9pvL4zC3tGTt9FXs3zGH+1D6YmtvSuttndPhoVInH07LbaDLSX3Nw46+8SknA0aUeQyatlk09CpAQG46WtnwQUhzlMTHuBQ9unARg+czeCnkaNmU91WoqPnFVEpq37kRSYgK7t64hPjYGJ2cXps6Yj7WNdCAZHxtDdJR89osTR/aSlZXF2uULWLtc3vlv06E7n39byu8MLUSLNh1JSkpg19Z1xMXG4ORcjWkz52FtI31SMD4uhphcsfkelsa2ZtlC1iyTvzqibcduTPj2h3zbL2nqKpcAD26cZO8a+YmUncsnAtD2oy9o3/t/JRk2AI1afkBKUgKHdq4kMS4K+ypuTPj+/7DMaWPioomLfqGwzqzvBsr+/1nwPQLOHcLCujK/Lztc4vl9G+W9XBYm+ugxdE1NcRo7Bn1rK1IfB3H3i69Ii5AeE/StrKhgJ39aV0tbB4ehn1HJ2RlJZiYJAVe4NXQEaeERqn5CbZq26kJyYgJ7t/1LQlw0DlVcmfjTX1jJ2stoYqIUy+WMiZ/J/j8kKJCLZ45iaW3PglX7SjXveXk2kx7HT/hIj+N2ju6M+G4F5jn9tPhoheO4hY0jIycvZ//G2fj7bsbE3IaPhn5P3SZdVP1Eqej+6Y+c9FnCwY2/kpIYg7GZDQ3bDaTtR/L3tPYe+SdnDizj2LY5JMa9xMDIDEfX+rjXa6Nyu0Xpl75OTWL/+hkkJ0RRoZIx9lU8GDF1A44upfs0nCbVuYYtPyAlOZ7DO1dI234nxbY/IS5Koe23snVkwvSl7Fo/lzNHt2Jqbs2AkdNo0Ex+A25mejr7t/xD9MswKlQ0oHaDVgz7358YGJqUaCzqGgtd8dsCwLo5QxXy02vknzRo1ZeS1LDjGDIz0vDb+QtpqQnYOnvS+/M16FeU91uS4iIUZgGzr+bFB0MXcvHQX1w8vARTSyc+GLYIu6rymNr2+5GLhxZzaucvpCbHYGhiQ90WA2nS9QtKQ4Pm3UhJSuDo7uWycc/YqctyjXuiicsz7hkzZSl7Nszl3JtxT59h0/FsKi+X5pb2jJ++kj0b5jJval9MzW1o0+0zOpbCuCdvbJo0pstL08fkuWlSH0UZTRqzatKx7n2YNqxD8xMbZH/Xmi8de4Z67+bWqOmqVitzLt6XoKsDXb20qagP4TGw9XQ26ZnyNCYGiq/eNK4Io7rIX8vQrKYWzWrC05cSNp8qfFbM4qLJ58HUFZuWtg7REU+4ef4rUpPjqGRohkO1uoycvgkbB/f3jksQNIUWb15RLwjC+1u5ciW2trb06tWr2LYpkUjYcl4zq+knLaUHf02MLye27f6l16EsTR83l55MOnAts5CU5U9PL+m9XppcLq89jCkkZfnkVV063euNR6XzJHBpqu8unYZWk8vlidsl+wSYunSsWxHQ7HJ5ztNLzTkpfq1uXgPAPzBRzTkpGc09pCcp9wRkqTknxa93Y+lJPk1uLzWxzoG83vneSlNzTopfp3oVAM0slyAvm/9Xtu4DKxZfvJnI7dC1DPVmpAR095JOOayJYzqQj+s0cUyeMx7XxH5KTh9F08esmnysO6hXQ805KX49Mh4AMGu75vWdAaZ/rPn9Z02NLe+rVYTSN2zGi8ITqcn6X0rm9V3qJJ7QFoRiYGJiQuPGjRk8eHCxXswWBEEQBEEQBEEQBEEQBEEQBEEQyhZJtubdLFGWiQvaglAESUlJKr/r1q0bv/32G02aNGHFihX4+vqWYs4EQRAEQRAEQRAEQRAEQRAEQRAEQXOJC9qCUAT169dX+d3z589p37596WVGEARBEARBEARBEARBEARBEARBEP4jxAVtQSiCoKAgdWdBEARBEARBEARBEARBEARBEARBKAMkEjHleGnSVncGBEEQBEEQBEEQBEEQBEEQBEEQBEEQBEEZcUFbEARBEARBEARBEARBEARBEARBEARBKJPElOOCIAiCIAiCIAiCIAiCIAiCIAiCIAhFlJ0tphwvTVqA+BcXhDJMvIdBEARBEARBEARBEARBEARBEIQcWlpa6s7Cf97g75+rOwsqbfrTQd1ZKHZiynFBEARBEARBEARBEARBEARBEARBEAShTBJTjgtCObD5nGY+pf1pK+ldZJoYX05s2/2z1ZyTkvFxc+n9UAeuZao5J8Wvp5f00Lj1guaVy0EtpOXy0LUMNeekZHT30gNg/1XNK5cfNpSWyy3nNa9cftJSWi73BGSpOSclo3djHUCzy+Wdxy/UnJPiV8fNDtD89tLnsubVuz5NpHVOk9tLTaxzIK93h69rXr3r1kBa5zSxXIK8bK47pd58lITh7aT/1eRxjybGBvL4NHFMnjMe18R+Sk4fRRNjA3l8mnysm7Vd8/qX0z+W9i8P6tVQc05KRo+MB4Bm9lNy+iiaHJugXhIx5XipEk9oC4IgCIIgCIIgCIIgCIIgCIIgCIIgCGWSuKAtCIIgCIIgCIIgCIIgCIIgCIIgCIIglEliynFBEARBEARBEARBEARBEARBEARBEIQikkjElOOlSTyhLQiCIAiCIAiCIAiCIAiCIAiCIAiCIJRJ4oK2IAiCIAiCIAiCIAiCIAiCIAiCIAiCUCaJKccFQRAEQRAEQRAEQRAEQRAEQRAEQRCKSJKdre4s/KeIJ7SFUuHn58eiRYvUnY1SNWzYMOLi4tSdDUEQBEEQBEEQBEEQBEEQBEEQBEEot8QT2oJQDJ48ecJff/3F4sWL1ZoPiUTC6X3/cPX0dl6nJuLgUo/ug3/GxsG9wPXuXTmK354lxEU9w9y6Ch36foOHV2eFNAEnN3Ph6GqS4qOwcXCj66Dvca7eSPZ9+usUfHct4P71E7xKjsfMyoEmHYfQuP0nGhHfL6NqKt12pwHf0fKDUe8d26UTmzl3eA3Jb36/26fTqVqjkcr0T+5f5siWObx8/hhjcxtadRtFkw6DFNLcDTjGCZ8lxL58hoVNFTr1+5paDeVxp71K4cTuxdy75ktKYiz2zh50//R7HF3qvnc8hTl/bAunDqwlMT4KO0c3eg2dhkvNhirTB90LYN/GubwIe4yJuQ3te46kReeBCmlepSRyaNtibgf48iolEQtrRz767Ds8GrQp0Vgun9zM+cOrSY6PwtrBjW6fKpadvELuX+bI1tlEvdl3LbuNpnF7xX1378pRTubadx37foNHrn13+eQWrvhtIT76OQDWDm60++gL3OuVbKznjm3FL9d+6z10Kq4F7LfH9wLYu3GebL916DmClkr228FtS7gl228O9PrsO2qV8H5T5vxxablMio/C1qEI5TIwgH0b5hL5/DEmZja0+3AkLTrJ4ws47cO2FT/mW2/Wumvo6VcotnxLJBJO7VVsG3t8VrS28aSPvG3MW85AWr4vHJG3jR98oli+C/vtuOgwFk/ppPT3B3z+F7Ubf/Ce0YP/8S2cPrRGtt8+/Gwa1WqqroPBgQEc2DRHtt/a9hxJs46DlKa94X+ILf83mVoNOzDs23/eO6/voryWy3d15IAPe3dvJS42FqcqVRkx9ktq1fFUmvbi+TMcPbSHkODHZGRk4ORclY8/HUGDhk1KOdf5aXp76e+7hTMH15CUIC2XPT+bRrUC+i3BgQEc3Cyvd216qK53N/0PsWXpZGp5dWBoKdS7wtq5vEIeXObo1tnSPphZwcdxVe1ryIMALhxZTXjIXZITohj45T94eClvK0uaptQ5kNa7k/vl9a7P0Km4ehRc7/ZskNY7U3MbOnyoWO/+/mU4QYFX8q1Xq0Frxk5dViIx5FBHuTx7cAWBV48THRGMrn5FnNwa0Ln/JKzsXUoszhwSiYRzB/7hxtltvE5NpHI1T7p88jPWlQvuy9y/dpQz+xYTH/UMM+sqtO31LTUayGO6dnoz105vISFG2me2snenVc8JuNZpW6Lx5KZJ4568NCm2/9p4XJP7KZocG2jWsa6oWtXWor6LFhX1IDwWjl3LJjpRdXorE2hdRxs7czAz1ML3ejYBjySll+H3YNGqES6TRmHqVYeKlW240m8CkftOqDtbCjS9j/JfHxsIQlknntAWipWOjk6JbFdbWxstLa0S2bYmOX/4X/yPraP74J8Y8+MOjEys2bBgJGmvklWuE/r4OjtXTKRe848YP3Mv9Zp/xM7l3xIWfFOW5s7lQxzZOovWPcYzboYPVdwbsemvsSTEhMvSHNk6m8d3ztF39Fy++P0gzToP4/Dm37l/vfg6XuqMb9LCswqfj0b8AVpa1GrY5b3jun3pEIc3z6bth+P4/NfdOFdvyIaF44jP9fu5xUWFsWHheJyrN+TzX3fTpudYDm36k7sBx2Rpnj2+zvZlE/Fs8RFf/LoHzxYfsW3pREKD5HHvWfsjj+9eoP/YOXz5+17cardk3byRJMZFvndMBbnuf5i93rPp2HssE2ftpFoNL1bNHkdctPJ4Y16G8e/cz6lWw4uJs3bSsdcY9qz/k1uX5PFmZqaz4s/RxEWFM+ybRUxdcJABY2ZiamFTorHcuXSII5tn0abneMb/4oNz9UZsXDi2wH23cdE4nKs3YvwvPrTuMY7Dm/7g3pWjsjShj6+zY5m0zH7+q7TMbl/2LWG59p2phS2d+k9i7IydjJ2xk2oezdiy5AtePn9UYrFe9z/MHu/ZdO49hsmzduBSw4uVs8cTFx2hNH3MyzBWzZ2ASw0vJs/aQedeo/FZP4ubl47L0mRmZrDszzHERj1n+DcLmb7gAAPH/FLi+02ZG/6H2ec9m069x/LtnztxqenFv3MKL5cuNb349s+ddOw9hr3r/+TW5WMK6SpWMuLnpacUPsV90VDWNn72E2N+2oGRqTXe8wtvG3csl7YR43/Zi2eLj9ixXLGc3bl8iCNbZtG653jGz5S2jRsXKZbvwn7b1MKeSYvOKnza9f4fehUMcKvb+r1jv3nxMPs3zqLDR+P46vddVK3RkDXzVO+32JdhrJk/nqo1GvLV77to/9FY9nn/ye08+w0gLvo5BzfPo1oN1SeISlp5Lpfv4vyZk6xd9Q/9Bg5h/pJVeNSpxx8zphL1Uvlx6d7dm3g2aMQPv8xh7uJV1KnXgNm/Tic46GEp51yRpreXNy8e5sDGWbTvNY6vfpPWu7XzxhFfQL1bm1PvfttFu4/Gsn/Dn9wOUFHvtsyjainVu6K0cwr5iwpj06JxVHFvxPiZPrTuOY7Dm5UcxwtpXzPSXmHrVJPun/1U4jEWRFPqHMC1C4fxWT+bzn3GMHn2DlxqerGikHq3cs4EXGp6MXn2Djr1Hs3udYr1buSkxfy6/JTsM3XeHrS1dfBs2rVEY1FXuQx5EEDjDp8y+sdtDJ20huysTDYsHE16WmqJxgtw8egqLvuupcugnxk+fSeGJlZs/WsEaa9V92XCgq6zZ9W31Gnai1E/7aVO017sWfkNz5/IYzI2s6Ndn8kM/34Xw7/fRdWazdi59Auiwkuuz5ybJo178tKk2P6L43FN7adocmygWce6ompWU4sm1bU4di2bdb7ZpLyWMKitNvoFPKKnpwPxyRJO3ZKQ/Kp8XMjOoWNoQOKtB9z9+ld1Z0UpTe+j/NfHBsK7yc6WlNmPJhIXtIUC6evrs3jxYiIjI3n16hVnz56lUSPpXUlt27ZFIpHQpUsXAgICSEtLo3Xr1hgYGLB+/XqSkpIIDw9n4sSJ+barp6fHnDlzCAsLIzk5mYsXL9K2rfwu6Zzpunv06MHdu3dJS0vD2dm5wLyuXbsWHx8fpk+fzosXL4iLi+Pnn39GR0eHuXPnEhMTQ2hoKCNGjFBYr06dOpw4cYLU1FSio6NZsWIFhoaG+bY7adIkwsPDiY6O5p9//kFXV9p78vPzo2rVqvz1119IJBIkEsXGokuXLty7d4+kpCQOHz6MnZ3d2+2EIpJIJFzy9aZ1j/F4NOyCjWN1eo+aTUb6a25fOqByvUu+3rjWakHrHuOwsnehdY9xVPNoxqXj62VpLh5bR4PW/fBqMwDryq588Mn3mFrYEXBqiyxNWNANPFv0pmrNpphZOdKw7UDsnGoQHnJHI+IzMrVW+Dy4fpJqNZpibu303rFdOLoerzZ9adR2ADaVXek++HtMLOy4fHKr0vSX/bZiamlP98HfY1PZlUZtB+DVui/nj6yRpfE/5o1r7Ra07TkW68outO05FhePZvgf8wYgI/01964cp+vHk6laozGWts506PMl5laOXD65RenvFpczB9fTpH0/mnXoj62DK72HTcfM0p4Lx7cpTe/vuw0zS3t6D5uOrYMrzTr0p0m7vpw6uC7Xv4kPqcmJjJi0hGo1vLCwroxLzYZUdlb+ZH1xuXBsHQ3a9KNhW2nZ6fapdN8FqPg3DHiz77p9+j3WlV1p2HYADZTsO5faLWjTcxzW9i606TlOuu9yldka9TtQ3bMtVnbVsLKrRqd+36Jf0UDhBElxO3XQm6bt+8r2W59h0zCztOP8ceXl9ILvdsws7egzbFqu/dYHv1z77ZLfblKTExg1aQkusv3mhUMJ7zdlTh9aT5N2/WjaXhpfr6HScunvq6JcntiGuaU9vYZKy2XT9v1p3K4vpw+sU0yopYWJmbXCpzhJJBIuHvemTc/x1GrYBVvH6vQpQtt48bi8bbTO1TZezFXO/I+uw6t1Pxq2kZdvUws7rvhtKfJva2vrYGxqrfC5f82XOo27UaGiodK8vY2zh9fRuF0/mrzZbx8NmY6ppT0XTygvlxdPStuTj4ZI91uT9v1p1LYvZw6tVUiXnZ3F1qVT6dzvSyxs3r+df1fltVy+q/0+2+nQpTuduvbEsUpVRo79H5ZW1hw9tFdp+pFj/0fv/p/iVt2Dyg6ODB42FrvKjly5dKGUc65I09vLc4fX0ahtP5q064+NgysfflZwvbt0chtmVvZ8+Nl0bBxcadJOWu/OKqt3y6bSue+XWBRD/6ooCmvn8rpyKs9xvI30OH7hqPw4XpT21b1eGzr2/aZYbox8H5pS50Be75p36I+dgyt939S7cyrq3fnj0nrXd9g07Bxcad6hP03b9+FkrvbS0MgUEzMr2efBbX/0KlSkfrOS3W/qKpdDJv5Lg1Z9sXFwx65KTXqPnEVCTDjhIXdLNF6JRELACW9adBtPDa8uWDtUp+fwOdLxymXVfZkrJ9ZTzaMFLbqNw9LOlRbdxuFcsxkBJ3LVNc8OuNVti6VtNSxtq9G297foVzAgPPhGicaUQ5PGPXlpUmz/tfG4JvdTNDk20KxjXVE1dtfiQqCEh88hOhEOXJagpwO1qqh+6CkiDvxuSQgMlZBZzl5tG3X0DA9n/MWLPccLT6wGmt5H+a+PDQShPBAXtIUCzZ07l379+jFs2DC8vLx4/PgxR48exdzcXCHN9OnT8fDw4NatW8ybN4/27dvTp08funTpQrt27WjYUPEpi7Vr19KyZUsGDRpEvXr12LFjB0eOHMHNzU2WxsDAgOnTpzN69Ghq167Ny5cvC81vhw4dqFy5Mm3atGHixIn88ssvHDhwgLi4OJo2bcry5ctZvnw5jo6OAFSqVIkjR44QFxdH48aNGTBgAJ06deKffxSnN2zfvj2urq60b9+eYcOGMXz4cIYPHw5A3759CQ0N5aeffsLOzk7hgrWBgQGTJ09myJAhtGnThipVqjB//vy33g9FER8dRnJCFK61W8qW6erpU7VGY8KCrqtcLzToBi651gFwrd2K0Mc3AMjKTCf86V2F7QK41GpJ2GP5dqu4e/HwxkkS4yKRSCQ8uX+RmBchuNVpVQzRqT++3JITonl0+zQNWvd7x2jkMjPTCQ+5i1sdxd93q9OSUBW/H/r4Rv70dVvyPOQuWZkZb9LcxK1OC4U07nVb8uzNNrOzssjOzkI3zxN5evoVePrw2nvFVJDMzHTCntyjRj3FvNWo14KQhzeUrvP00c386T1bEhosj/fuNT+c3T3ZvfZ3Zoxrw7zveuG7ZyXZ2VklEgdIY4kIuYtbvvLVklAVZTIs6Ea+suZWpxXhufadsjSudeRlNq/s7CxuXzpIeloqTq713y2YQmRmZhSw35RfRA9Rst9q5ttvp6jq7snOtX/w07g2zPmuN8dLeL8pk5mZzvMn96ieJ7/V6xZcLqvXzfvv0ZLQJ/L4ANJfp/L7V5347csOrJ43gechgcWa97go1W2jqjYEpG2ja752pxWhQTeAN22TkrbRtba8bXqX3w4PucOLZ4E0aFM87efzJ/dwzxNH9ToteProhtJ1nj26QfU6efdzK8Ly7Ddfn6UYGpvTpN375/Ndledy+S4yMjIIevyQ+g0aKyz39GrMg8Ci3RyXnZ3N61epGBmblEQWi+Q/0V6G3MO9rmK9cy+g3j19fAP3fH2S/PXuxJt617iU6l1R2rm8QpUdx2srHscLa1/LCk2pcyCvdzXz1qNC6l3+9Ir1Lq9Lfrvxat6NChUNiifjSpSlcvn6VRIAlQxN3zaMtxIfHUZKYhTVasnHjbp6+lSpXvA473nwDYV1AFxqt+a5inWys7O4F3CQjPRUHFwaFE/mC6BJ4568NCm2/954XHP7KZocG2jWsa6ozAzBqJIWT17IHxzKyoZnUeBopcaM/Udpeh+lLMUnCIJq4oK2oJKBgQGff/453333HUeOHCEwMJAxY8bw6tUrRo2SvzP4559/xtfXl+DgYNLS0hg1ahSTJ0/G19eXO3fuMGzYMIWpyF1cXPjkk08YMGAA586dIzg4mAULFnDu3DmFp6f19fWZMGEC/v7+PHz4kNTUwqcRiY2N5auvvuLhw4esXbuW+/fvY2BgwKxZs3j8+DGzZs0iPT2dli2lB5LBgwdTqVIlhg4dyt27d/Hz8+PLL79kyJAh2NjIpw+Ki4vjyy+/5MGDBxw8eJCDBw/SsWNH2XdZWVkkJSURGRlJZKR8eih9fX3Gjx/P1atXuX79Ov/8849sPWX09fUxNjZW+BRVckIUAEYmlgrLDU0sSU6ILmC96HzrGJlYkpwo3V5qUhyS7Kz8aUwVt9vt0x+wruzKoslt+X1cXTYtGkP3z2ZQxb14poxUd3y53bywB/0KhngUw51zqUnxZGdnYWSi2Bs3MrEkScXvK4/JiuysTFKT42RpDPNs09DEShZThUqGOLnV59TeZSTGvSQ7O4sbF/YRFnyLpDf/1iUhJfFNvKb5/71VxZsYH600fXZWJilJ8YB0Kq1bl4+RnZ3N6KnL6NRnHKcPrsPXZ0WJxAHSspOdnYXhW5Sd5ISofLEYmljm23dKy2ye/RIZ+oA/xnvx25h6HFg/k0Ff/oONgxslISVRGqtxnrwbm1qSqCLWpPhopemzszJJzrXfbl4+jiQ7i7FTl9G5z1hOHVzPcZ+VJRKHKilv6qGy/KoqlwXFl1MubSq7MHD8H4yc9A+Dv5yHrp4+/8z8jKiIp8WW95y2LG85LErbqHwdxbbRUEl5zdnuu/z2tbO7sLJ3pYqbV2GhFUrWfiprT+JV7LeEwtuTkIfXCDi1m36j1TvNW3kul+8iKTGB7OwsTM0sFJabmZkTHxdbpG3s89nG69evadm6fUlksUg0vb3MqXfGJkUvl8kJSuJ7c+xLSY4H3tS707vpN6r06l1R2rm8khOi8rd5pvmP4wW1r2WFptQ5KKTeqToeFKHe5fb08W0iQh/RrEPJ3nBRVsqlRCLh6LbZVHFviK1j9XcNp0hSVPUnjK1ISSygL5OoPKac7eV4+fwB879qwNwv6nJk0wz6jv8/rCqXTJ85N00a9+SlSbH998bjmttP0eTYQLOOdUVlWFH635TXistTXkswrCheS1naNL2PUlbiE8qfnBl7y+JHExXwxgnhv87V1RV9fX3Onz8vW5aZmcnly5fx8PAgICAAgCtXriisU6FCBfz9/WXL4uLiePDggexvLy8vtLW1efhQ8V1rFSpUICYmRvZ3Wloat27deqs83717V6GyRkZGcueO/AmD7OxsYmJiZBerPTw8uHnzpsLF8vPnz6Ojo0ONGjVkT4XfvXuX7Gz5PDURERHUrVu30PykpKQQHByssF7uC+V5TZ8+nZkzZxYeKHDr4n4OeM+Q/f3p18ul/5PnXeMSSf5l+eRdR7owb6ICt3vJdwNhQTcZ9L+lmFk68PRhAIc2/oKxmTUutVrwtspafLldP7eLus16oqtXjO8bzfNTEokErXx5zJ0+b0w55V4rV5J8G1XYZv+xc/BZ/QPzvm2LtrYO9s61qNusJxFP771LBG8lX2wSSYH7UWl66RfSP7OzMTKxYMCYmWhr6+DkUpvEuJf4HVhLl34TijHnSvKmpEwWuO9UfadVwL4j/zYt7asx/hcfXqcmcu/KMXz+ncaIaRtK7KK2sjwgkSjNq6r0Oe1zzjo5++1jhf0WxckDa+na7/PizXyRKKtXb1EP85RLZ3dPnN09Zd9Xrd6Av37oz/ljm+g97Pt3yuEt//3sz9U2Dv5m+ZusKMlnIW1j/v0pXVpomjzbLepvZ6S/5vbFA7T9sHj3bf7fL6RcKkkvXQ5pr1LYumwq/Ub/gqGxef6V1aLsl8vipOTQVfhxHjh7ypftm9Yx9ac/MDVT/77T+PZSSTkrKD7l5Vi6NO1VCtuWTaXfKPXUu6K0cwrp8xVS2RcFb7PAvoH6aEqdA5T2jwsslyr608rWuei3G3snd5zdCh8DFgd1l8tDG38jMvQBI6dvLlJ+38adS/s4sknel/n4S+nFynx9alkQBVHWdubpM9tWY+SPe0hLTeTB9WMcWDeVzyZtLJWL2tIcas64p0h5La+xifG4xvRTNDm2NxlT+LM8H+vyql1Fiw8ayvO1/Zz0PGzeo4GWlpKFQqnR5D6Kyrz8h8YGglDWiQvagkqyzlueuzm0tLQUlqWkpORbpyDa2tpkZmbSsGFDsrIUp+hJTk6W/f+rV6/eOs8ZGYpT5kgkEqXLtLW1ZflVdbdK7uUFbeNt81PQerNmzWLhwoUKyxITE5WmreHZHscZ9WR/Z2amA2+egjGTXzRPTYrJd/dwbkamVvnuNEtJjJHdoWxgbI6Wtg7JicrSSLebkf6aE7v/YuAXf1Pdsx0Atk41eBF6nwtH17zTBe2yFF9uTx9eIebFE/qPX/TWMSljYGyGtrZO/jwmxea7gz2Hqpi0dXQxMDLLlUbxbr+UpBiFOw0tbKowavoG0tNSSXuVjLGZDduWfou5lUMxRKacoYk03rx3uycnxuZ72iuHiZmV0vTaOroYvonXxMwaHV1dtLXls0HYOLiSFB9NZmY6urr6xRsI0rKjdN8lxuS7ozOHkam16n1naPYmjbJ4YzA0VbzDX1dXH0tbZwAcqtUlPOQOF49789Hw4n+6zdBEGmveO9uTCthvxmZW+dLL95t0WigTM2u08+w3WweXN/stA11dvWKORDlDYxXlMiE23x3tOYzNrPI9BZy3XOalra2Nk0sdol48fee81qjfHgcXeduYpaJtVNWG5TAytcrf7iXFYGSap23M1zbJt2tkYv1Wv33vylEy0l/j2aJ3UUItVE77mW8/JKhuP41Nley3hFhZ+xn5/DFxUc9Zv+AL2fcSifREyvShdZk87yCWtlWKJf+FKU/lsjgYm5iira2T78nQhIQ4zAq5WHb+zEmWLpnL5Gm/4NmgUUlms1Ca3l4aqCqXibEq2xzlx7U89S76OesX5q933w+ry6S5JVPvitLO5VXU43hB7WtZoSl1DuT1Tln7/lbtZYJivcuRnvaK6xcO023AF5S0slAuD236jQc3TjJi2kZMLezyff++3D07ULma/Maq3H0ZI1PFcV7eJ1xzMzLJ/wR3alJsvnV0dPWxsJH2me2r1iUi5DYBJ73p9lnJzgihSeOevDQptv/eeFxz+ymaHBto1rFOlUfhEsJj5edidd6cPjWqqPiUtkEFLVLSxBXt0qbpfZSyEJ8gCIUTU44LKj1+/Ji0tDRatcr1LitdXRo1akRgoPJ3LT5+/Jj09HSaNWsmW2ZmZkb16vIpQK5fv46uri42NjYEBQUpfHJP110a7t27R/369TEwkL8bpmXLlmRlZeV7grwg6enpCtOqv6v09HSSkpIUPqpUqGSEha2z7GNd2Q0jU2uC712QpcnKTCfkQQCOrg1UbsfJtb7COgDBd8/j5FYfkJ4AqOxcm+C7edLcu4Cjm3S72VmZZGdloJXnYr2WtjaSXE+2v42yFF9u18/uxN65NnZONd8prrx0dfWpXLU2QXl+P+juBZyU/D6Ak1v9fOkf3zmPQ9Xa6LwZTDm5efI4X5oLVFGyTf0KBhib2fAqJYHHt89T00v1tPjvS1dXH8dqtXh4SzFvD29foGr1+krXcXb35OFtxfQPbl3AyUUeb7UaDYh+8UxhJoWoiBBMzKxL7KSOrq4+9kr2XfC9CzipKJOOSsrj47vnqZxr3zm61s9XHoNylVlVJBKJ7IRgcdPV1Xuz3/wVlj+87U/V6p5K16nq7snD24rp8++3+vn220vZfiudEwMg3ZcO1WrlK2cP7xRSLu/kSX/rAk7V5PHlJZFIeP70PiZm1u+c1wqVjLC0dZZ9ctrGoFzlKvNN26iqDQFp25iv3blzXvYedt03bWPQPdVtk7m141v99rWzO6lRvz2GJhb5vnsXOfvtUZ798OjOBZzd6ytdp4p7fSXpz+P4Zr9Z27vw7ay9fP3HbtnHw6s9Lh5N+PqP3ZhaFv+JfVXKU7ksDnp6eri6Vefm9SsKy29dv0INjzoq1zt7ypd/Fs3im+9+omGT5iWdzUL9J9rLqrV4fCd/H0NVvXN2q58v/aPbivXumz/38tXvu2UfjwbSevfV7yVX74rSzuWltO3McxwvrH0tKzSlzoG83j3IW48KqXd509/PU+9yXPc/SmZmOo1af1i8GVdCneVSIpFwcOOvBF49zrAp6zC3diyGiPKrUNEICxtn2cfK3g1DE2tCAuUzw2VlpvPsYcHjPAeX+jzJtQ7Ak3vncChgHSjZPnNumjTuyUuTYvvvjcc1t5+iybGBZh3rVEnPhLhk+Sc6EZJfSahqK394SlsbqlhDmOo3UgglRNP7KP/1sYHw7iTZkjL70UTigragUmpqKsuWLWPevHl07doVDw8PVq1ahYGBAatXr1a6TkpKCqtXr2bevHl06NCB2rVrs27dOoWO36NHj9i4cSPe3t706dOHqlWr0qhRI6ZMmUK3bt1KKzwANm3axOvXr1m/fj21a9emXbt2/P3332zYsEE23XhRhISE0KZNGypXroylpeon4kqSlpYWTTsN5ezBFQReO87LsIfsWTMdPf2K1G3aU5bO59+p+O5aIPu7aachBN09z7lDq4iOCObcoVUEB/rTtPMwWZpmXYZz7exOrp/dRVR4EEe2ziIhNoJGbQcB0gsszjUac3z7PELuXyIuKowb53Zz68Jeanp1Lvfx5Uh7lcy9K0fxajOgWGLK0aLrMK6e3sXVM7t4GR7Eoc2zSIiJoEn7gQAc27GQnSunytI3aT+I+OhwDm+ZzcvwIK6e2cW1M7tp+cFIWZrmnYcSdOcCZw6uIio8mDMHVxF0z5/mXYbK0jy6fY5Ht84SFxXG4zvnWTN7OFb21fBq1adY48urTY9hXPLbxSW/3UQ+D2Kv92zioiNo3kka78Eti9i8dLo8lk4DiYuOYO+GOUQ+D+KS324u++2iXY/hueIdSGpyPHvWzyIqIoR7105zYs8qWnb5pERjadFlONfO7OTaGWnZObxFuu8at5eWneM7FrB7lXzfNX6z745smUVUeBDXzuzi+pldCvuuWWdpmT17cBVREcGcPbiK4Hv+NM9VZn13LuTpwyvERYcRGfoA312LCLl/mXrNS27w2a7HUC7m2m8+3nOIi46gxZv9dmDLIjbl2m8tOn1MXHQEezbMle23S367aZ9rv7V4s9981s/mZUQId6+dxnfPKlp1GZT350tc2+7DuOy3i8un3pTLDbOJj46gWUdpfIe2LmJL7nLZUVou970pl5dP7ebyqV207TlclubYrqU8uHmOmMhQnocEsn3lT4Q/fUDzjh8XW761tLRo1nkoZw+sIPDqcSLDHrJndf62cfeqqfjuzNU2dpa3jVG52sZmucpZ865vyndO27jlTdvYbtBb/TZATORTnj68UuztZ+tuwwk4tZOA07uIfB7E/o2ziY+R77fD2xaybfk0WfpmHQYSFxPB/o3S/RZwehcBp3bRpvsIAPT0K2Dn5K7wqWRgQoVKhtg5uZfaieIc5bVcvqsP+3zMiWMHOXHsIGHPQli78h+io17SpftHAGxct5IlC/6QpT97ype/F/75/+zdd1hTZxsG8DthiCiKICiIKMOByFBwgpOKu+6v7oVVtLXuWets60Sr1qpVUNwLN4h74BbRooAoCAqCEPaevt8fSCAMBRI85PD8ruu5Wk9OkvvhrCRnYYLDDDRv0QrxcbGIj4tFampKaW/xTfB9fWlbaLmLLrTcdfg8X3oWWe469MybLy8eXo/oz8ud9203dPnCcqeiWgc1VCp/ufvaeu7aKcntuHX3kUiMjYDnsc/bcS83+Hi5oXPvgu14WdavmRmpiHwfgMj3eQcJJ8SEI/J9ABJiIyqt15LwZZkDPi93N9zw8OZpfPwQjDOuecudzefl7sLRLTi0o2C5s+mVt9ydObABHz8E4+Hn5a5nofVlvkc3T8PMuidqqal/k164mi/dD62G74MLGDZtE5RVaiE5UYTkRBGys4rcvFTGBAIB2tmNx/1LuxH47CpEH17j4v68zxOt2hd8nriwbyFunSn4LGNtNx4h/vfwwPNfxH4MxgPPfxEa8ADt7Ap6unVmM8LeeCMhJhzRHwJx++wWvH/9GKbtv80OGz597+Fzb9Xt+zifP6fwuTeAX9u6snryhqGziQDNGwH16wAD2gmQnQv4vy/YUTOgvQDdzCR3emur55WCEKhdM+//69X+5vHLTaGWKupYtEQdi7yTaFQN9FDHoiVUGutwnCwP3z+jVPfvBoTIA7rkOPmixYsXQygU4uDBg1BTU4O3tzd69+6NhISEUp+zYMEC1K5dG+fPn0dycjKcnJxQt67kpWwmTZqEZcuWwcnJCY0aNUJsbCwePHgADw+PSu5IUnp6Onr37o2tW7fiyZMnSEtLg5ubG+bOnVuu11m+fDl2796N4OBgqKiolOnS65XBpu8U5GRnwOPQaqSnJkLP0Bzj5jqjRs2CT22JcRES+Robt8XwaU64cWYrbp7dBg3txhg+bTP0DAuO8Gzdvh/SUxJw+8IOpCSKoN2oGcbM2g31QpfCGj5tM667bcbpPQuQnpqIupq66DlktnijL+/9AcDLx+5gYGjdvr/MegIAsw79kJaSgFvn/kFyoggNGjXDuLm7xO+fkiBCYmykePx6WnoYN3cXLh1dh0fXj0BNXRv9xiyFaTt78Tj6zdpgxHQnXHfbihunt6OedmP8b7oTGhsV9J2RnoyrJ7cgKf4jataqC1Nre3w3bHapZ/HJSptOfZGWnICrp3ciKUEEncbNMGXRLmho6QIAkhJESIgp6FdTWw9TFu7EuYPrce/KUdStp43BE5bCvENBv/U0dTB1yR6cO7gemxYNQd16DdCl71j0/N6hUntp3aEf0lITcPv8DiTnzztzCuadlEQREgt9AK2npYexc3bD8+g6PL6RN+36jvkVrax7i8fRb9YWwx2dcOP0Vtw8sw31tBtjhONm6BWadilJsTj970IkJ4qgUlMNDRq3wLh5e2BkalNpvbbp1BepyYm4fHqXeLpNXbSz0HSLQXyR6fbjwn9w9uAG3P083YZMWAKLDgUHudTT1IHjkn9x9uAGbFw0FHXraaNr37Gwq+TpVhLLTn2RmlIwXzbUawaHhZLzZXxs8fny/MH1uHf1KOrU08agCUth3r5gvkxPS8JJ55VIToiBiqoaGjVpiRm/uULf2LzY+0vDpu8UZGdlwL3wunFeCetGYcG6Ud+4YD67cebzurHIfNa6fd666fb5QuvG2ZLrxrK8NwA8u+uGOuoNZD6PWnTMW59cP1Mw3SYt2C2+VGNyQozE+kRDWw+T5+/ChUPr8ODaEdSpp43vxy+FWaHpVpXI83xZETZdeyI5KREnjx5AfFws9JsYYOmq9dDWzjtDNz4uFjGiggMOr3peQG5uLvbs/At7dv4lHt7drg9mzl1S9OW/Gb6vLy069kVaSgKun92J5M/z5cT5BctdUkIMEmIll7tJ83fh4uHPy526NgaOWwqzdtwvd19bzyUnipAYJ7kdH/N5O/4kfzs+ush2vAzr14jQl3DdUPAj1uVj6wAAFjaDMcRhXWW3LcaXZQ4A2nbui7SURFx2K1jupi0utNzFF1/upi76B2cPFCx3QydKLncAEB0RireBPpi+9N9v1gtX86X3zaMAgP3rC3a4AcCgyX+ije3QymwZHXv/iJzsTFw+sgoZaYnQNbDAyFkuqKFS8HkiKS4SAkHBORl6Rm0xeMpm3D73F+6c34Z6Wo0x+MctaFTocuapyTG4sG8hUhKjUaOmGrQbtcAPv+yFQavK+8xcGJ++9/C5t+r4fZyvn1P43BvAr21dWT18xaCoAPRuK4SKMhARCxy7/QlZOQXj1FGVvJ2kmgrgYF9wFc2OLQXo2BJ4F81w5FbFriL5rdS1ao1O1w+K/91q01IAQNiB0/B14PazFsD/zyjV/bsBIfJAgIJb1RNCqiDGGI7c5ediOto2b+cKH/vL7+3Eg6r9Ybmi/tcp78ekiz45XxlT/gxom3es17H7/JsvR3bOmy89fLI5TlI5+rXN+/HnwlP+zZcDrfLmy6P3+DdfjrLJmy/PPsnlOEnlGNwu78cUPs+XL4M+cpxE9lob5+3Q4/v68sxj/i13Q9rnLXN8Xl/ycZkDCpa7S8/4t9z1bZO3zPFxvgQK5s39t7jNURkmds/7L5+/9/CxN6CgPz5+J8//Ps7Hzyn5n1H42BtQ0B+ft3VrT/Dv8+WS/+V9vnRXasFxksrRPzsQAD8/p+R/RuFrb1ydVEcKDPslmOsIpXLbZsR1BJmjS44TQgghhBBCCCGEEEIIIYQQQgipkuiS40RuJCcnl/pY3759cffu3W+YhhBCCCGEEEIIIYQQQgghhBBS2WiHNpEblpaWpT724cOHbxeEEEIIIYQQQgghhBBCCCGEVFufGP9ubVKV0Q5tIjeCg6vu/QgIIYQQQgghhBBCCCGEEEIIIbJH99AmhBBCCCGEEEIIIYQQQgghhBBSJdEZ2oQQQgghhBBCCCGEEEIIIYQQUkbsE+M6QrVCZ2gTQgghhBBCCCGEEEIIIYQQQgipkgQA6BACQqowxmgRJYQQQgghhBBCCCGEEEJIHoFAwHWEam/wT6+5jlCqszuacx1B5uiS44QQQgghhBBCCCGEEEIIIYQQUkZ0yfFvi3ZoEyIHjt7j54pxlE3eUWRH7vKvv9G2eb3xfdodu8+//kZ25u+0y59ufOwNoHWKvKL5Un7RfCm/aDsun2i+lF98ni8Bfs+b1WG+5GNvAL+Xu+qwzPGxN6B6rFP4OO2qy3zprtSC4ySy1z87EAA/p13+dCOkOqF7aBNCCCGEEEIIIYQQQgghhBBCCKmS6AxtQgghhBBCCCGEEEIIIYQQQggpI8b4d/Z/VUZnaBNCCCGEEEIIIYQQQgghhBBCCKmSaIc2IYQQQgghhBBCCCGEEEIIIYSQKokuOU4IIYQQQgghhBBCCCGEEEIIIWX06dMnriNUK3SGNpFLN2/exJYtW775++7btw9nzpz55u9LCCGEEEIIIYQQQgghhBBCSHVEZ2gTwiOMMdw69zee3j6BjLQkNDI0R/+xy6HdqNkXn+fvfRk3zmxDvOg96mnpw27obJhY9ZIY5/GNI7jv6YzkBBG0Gxmjz6ilaNLcWvz4zbPb8fKxB5LiPkJBUQk6TUxhN3Q29IwsZNrf7fOS/fUbU7b+bp4t6K/n0NkwaSvZ35MbR3D/ckF/vUdK9nfWeTH+u39W4jmNDC0w5dfj5e7ja3/LokIDH+PysXWI/hAENXVt2PSdgnY9RhbrUZppmJuTjRtntuKN723Ei8JRo2ZtGLbqjO+Gz0Wdeg3K3WPR9713yRkpCSJoNTJG39Ff6ffVY3geWwfRhyCo1ftyv3HR76GhXbzf3Nwc3Dr7N3wfXkBKYgzU1LVgaTMEXQdOh1Ao22O5uJieoYFPcN/TGRGhfkhJFOGHn/+GSdvvZNoXwN06pTLnx6L9cbVOycpIxTU3J7x6dh3pKQlQr98I7e3GoV2PURXqg6t1/9feOz4mHFsXljxvjpj+F0zb9ZGbfmm+lE1vfJ12fO6Ni+14YXcu7sZ1ty3o2Gs8+o5eKpOeCuNiO+7lvhsBT68iJvItFJVV0Ni4DXoNn4f6OoYy7Y3mywKymi+T4qNw9cQmvHlxBznZmdBs0BSDJv8O3aatZdJXPr5PO74uc/n98fW7D596q27fyfm8TuFzb7StK5m8TDs+b+sqSsPWGobzHFC3bWuo6GrDe9gMRJ2/znUsCTTtCKna6AxtUqUpKChUyusKhUIIBIJKeW0u3bu0Fw+u7Ee/sb/hx99OonZdLRzYNBmZ6SmlPics6BlO7poLi87fw3HVOVh0/h4nd81BePB/4nFePvaA59G16DLAEY4rz0C/mTUObZmKhNgI8TiaDZui35jfMH31eUxechjq9Rvh4GYHpCbFyb6/Mb/hx2UnUbuOFg46fb2/U7vnwrzT93BceQ7mnb7HqV1zEP62SH/H1qJLf0dMW5HX3+G/piKxUH8AYNy6C+Zt9hLXmFm7y91DWf6WhcWLwnF4yzToN7OG48oz6DJgGi4d+QP+3pclepR2GmZnZSDynT+6DpyBaSvc8MPP2xEbFYqj22aUu0eJfh95wPPIWnQd4AjHVWfQpLk1Dm3+cr+HtkxDk+bWcFx1Bl36T8OlwyX0uzNvmk5fnTdNT+yU7Peux1543zqG/mN/w89/uqPXiPm45+mMR9cOSdVPsf44mp7Zmelo0Lgl+o39Tab9FMXVOqWy5sdS++NgneJ5bB2CXt7F0Ckb8NPv7ujYawIuHfkdr56V/8scl+v+r713XQ0dzNviJVHdB8+EUg1VGJt1KXevXPZL86UMe+PhtONrb1xtx/N9ePsCT2+fQIPGLWTST7H+ONqOhwY+QbueozFl2XGMn+eCT7k5OLh5CrIy02TaH82XeWQ1X6anJsL5j1EQKipi7Nw9+OmPi+g9chFUVOvIpK/CeDvteL7M8fm7D596q27fyQH+rlP43Btt60omF9OO59s6aSjUUkWSbyD8Zq3mOkqJaNqRimCfWJUtPqId2uSbUlZWxtatWxEVFYX09HR4eXnB2jrvKKdu3bqBMQZ7e3s8efIEmZmZ6NKlC1RVVeHq6ork5GRERERg7ty5xV5XSUkJ69evR3h4OFJSUvDw4UN069ZN/PiECRMQHx+P/v37w8/PD5mZmWjSpMkXswqFQjg5OSE+Ph4xMTFYv359sZ3gvXv3hpeXl3icCxcuwNCw4Oip69evY/v27RLP0dDQQEZGBnr06FHuv9+XMMbw8OoBdB3giFZW9mig1xxDHNYhOysDLx5dLPV5D68egFGrzujSfxq0dAzRpf80GJh0xMOrruJxHlzej7ZdhsGq6who6Rqh7+ilqKvREN43j4rHMe84EEamnaGh3RjajZqh98jFyExPQVR4oMz6e3TtALr0d4SJlT209ZpjcBn6e3StoL/6hfp7VKi/h1f2o02XYWj7ub8+o/L6e3LrqMRrKSgqo3ZdLXHVrK1e7j7K8rcszPvWMdTV1EHf0UuhpWsEq64j0KbLUNy/7FKQXwbTUEVVDePnu6B1+76or2OIxkaW6DdmGSLf+ZX6wa0s7l/ZjzZdh8GqW8H71tFoiCc3Su73yc0i/XbL6/eeZ0G/D64cgKFpZ3QdkNdv1wHTYGjSEQ8K9Rse/Awt2tihuUV31KuvB9N2fWBkaoOI0JcV7qUkXE3PZuZdYTd0NlpZ2cu0n8K4XKdU1vxYtD8u1ynhwc9h0XkwmrbsAPX6erDq9gMaNm5R7nmUy+lUlvcWChWgVldLol75XEPrdn1RQ6VWuXrlul+aL6Xvja/Tjs+9cbUdB4DMjFS4/Tsf309cg5qV8CMqwN12fNzcvWhjOxTajZqhoX5LDJ68FomxEYgI9ZNZbzRfFpDVfHnXYy/qaOhgiMNa6Bmao159PRi26gQNbX2peyqMz9OOz8scwO/vPnzqrbp9J+fzOoXPvdG2rmTyMO34vq2ThujyHbxe8Rc+nr3KdZQS0bQjpOqjHdrkm9qwYQOGDRuGCRMmoG3btggKCsLly5dRr149iXGWLFkCExMT+Pr6YuPGjejRoweGDBkCe3t7dO/eHVZWVhKvu2/fPtjY2GDkyJEwNzfHyZMn4enpCWNjY/E4qqqqWLJkCaZMmQJTU1NER0d/Meu8efMwefJkODg4wNbWFhoaGhgyZIjEOLVq1cLmzZvRrl072NnZ4dOnTzhz5ox4x/fevXsxevRoKCsri58zZswYRERE4ObNmxX+O5YkXhSOlEQRjExtxMMUlZTRtEU7hAU9K/V5YcHPYdTaRmKYcWtbhAU/BwDk5GQh4p2fxOsCgJGpTamvm5OThae3j6NGTTU0aNyygh1JSogpvb/w4C/3Z1gsuy3Cgp4DAHJL6c+wlQ3Ci/QXGvgYG2d3xvalvXF+/29ITYotVw8V+VuGBT8vNr6xqS0iQv2Qm5NdMI6MpyEAZKQlAwJBhY/EzcnJQmSoH4xLet9Spll4Sf22luy3pHGMWhdMUwDQb2aFEP8HiPkYAgD4+P4V3r/xQXPzrhXqpSRcTc9vpSqtUwDp58eiuF6n6Ddri9fPbyApPgqMMYS8eojYj6Ewbm1brj64nE4Vee+I0Jf4+D4AbboOK1ef+Wi+LFlVmy9Lwudpx9feuNyOA4D7wdVoZtEdRqadpeqjNFVpO56RngwAqFmrbnnbKBXNlwVkNV8GPr8BXYPWOL5jFjb80hk7VwyB9+0TUvVTEj5POz4vc3z+7sOn3qrbd3KAv+sUgL+90bZOvqcdn7d1fEbTjpCyU1dXx4EDB5CQkICEhAQcOHAAdeuWfX7dtWsXGGOYNWtWud+b7qFNvhlVVVVMnz4dEydOhKenJwDgxx9/RK9eveDg4IAnT54AAJYvX45r164ByNth7ODggPHjx4uHTZgwAeHh4eLXNTQ0xKhRo6Cnp4fIyEgAgJOTE/r06YNJkybh119/BZB3dviMGTPg6+tbpryzZ8/G2rVrcfr0aQCAo6MjevfuLTFO/mP5HBwcIBKJ0KpVK/j5+cHNzQ3bt2/HoEGDcPLkSQDApEmTsH///hLfU1lZGTVq1ChTvqJSkkQAgFp1NCWG16qjWezS2RLPS4wp8TkpiXmvl5YcD/YpF7XqljROjMSwwOc3cWr3PGRnpUOtrhbGz3dBLbV6kIX8PLUr0F/R59Suoyn+e+X3V2ycupoIflnQn7FZV7Sy7gN1TV3Ex4Tj5tltcN04EVOXu0FRSRllUZ6/ZUF+EWrVkdyRUKuuJj7l5iAtJR5q6toynYb5srMzce2UE8w6DIBKzdpl6q+otOR4fPqUWyxb7bqaSHlZer+16xbpt07xfkucpp/7BQDbfj8iIy0Zfy/tB4FQAexTLnoOnQ2zjgMq1EtJuJqe30pVWKfkk8X8WDwnt+uUvqN/xQXX37BlfjcIFRQhEAgwcMLv0G8mecDWV/vgcDpV5L19vNxQX8cI+sZtv9ZayblpvizleVVrviwxI4+nHV9743I7/uKROyLf+WPqilNS9fAlVWU7zhjD5eProN/MCg30mkvRUZGsNF+KyWq+jI8Og/eNo+jUeyK6DpiG8Le+uHT4DygqKsPSZrBUfUnk5fG04/Myx+fvPnzqrbp9Jwf4u04B+Nsbbevke9rxeVvHZzTtSEUx9onrCN/ckSNHoKenhz59+gAA/v33Xxw8eBDff//9V587aNAgdOjQAR8+fKjQe9MObfLNGBkZQVlZGffu3RMPy8nJwePHj2FiYiLeoe3t7S3xnBo1auDBgwfiYfHx8QgMLLiMddu2bSEUCvH69WuJ96tRowZiYwvOoM3MzCzzzuw6depAV1dX4n1zc3Ph7e0tcdlxQ0NDrFmzBh07dkT9+vUhFOZd9EBfXx9+fn7IysrCoUOHMHnyZJw8eRIWFhawsLDA4MGDS3zfJUuWYOXKlWXK6PvgAi4cWCH+95jZuwCg5HuDf+V+4QIUeZzlDf3qOEVe18CkAxxXnkFaSjx8bp/EyZ2zMWXZiWIfmMvC9+EFXCzU3+hZuz4HkXxPVkKOYoo+J29g0ZG++Lqt2/cT/7+2XnPoNm2Nvxba4Y3vLZiU87LPZflbSoxf9DEmfuDLr1mBaQgAuTnZOLVrLhhj6D9uRbHHy6tofsZKyFIkaSkvVOpr5j2rYNjLxx7wfXABw6ZtgrauMT6GvcKlI3+ijro2LG2HFHuuNLianrJWFdcpgOzmx6q2Tnl07SDCg//DyJn/QF2zEd69fgKPQ6ugpq4Fw1aln41YFadTWd87OysDLx5eRLeB07+Yq7Cq2C9A82VZ8Hna8bm3EjN+4+14YmwkLh35E+PnOUNJqWIHepYH19txj0NrEBUWiMlLjpQpb2lovqz8z5eMMeg2NcV3w/NugaXTpBVEEUF4cvOoVD/yV7tpx5NlrjR8/u7Dp974/J2cz+sUPvdWYkba1pVILqYdz7d1fEbTjpAva9myJfr27YsOHTrg8ePHAPJOWn348CGaN29ebB9dYbq6uvj777/Ru3dvuLu7V+j9aYc2+WbyV/CMsWLDCw9LTU0t9pwvEQqFyMnJgZWVFXJzcyUeS0lJEf9/enp6hXJ/yYULFxAWFoYff/wREREREAqF8PPzk7jE+N69e/H8+XM0atQIkydPxvXr1/H+/fsSX2/t2rXYvHmzxLCkpKQSx21h2QONDM3F/87NyQKQd7Simrq2eHhqUuwXdyjXrlsfKUmSR5qlJseidt36AABVtXoQCBWKHY2Wmlz8dZVrqEKzQRNoNmiCxkaW2La4N555nUKX/tNKff/StLDoAb0VBf3llNJfWgk5ivVXNHtSLGrXKdJf0b/BV/5uauraUNfURWzUuzL3VJ6/ZUF+rRLzCxUUoVpL/fM4spuGuTnZOLlzDhJE4ZiwcL9UR6eqqtWDsKT3TYotdsRjvrL2m1xknJSkWNT63C8AXDm+Ebb9f4RZh/4AgAaNWyAhJgJe7v/K7EcdrqZnZamK6xRZzo9VaZ2SnZWB66f/wg8/bUdzi+4A8ubRj2GvcP+yyxd3HFal6VS7jla53tvf+zKyszJg0XlwqbmKqkr9FmSg+bJMvfF42vG5t8K42o5HvPNDalIsdq8quDXBp0+5ePfaG4+vH8Zve3whFCpI216V2I57HF6DwOc3MGnxIdTVaChFNzRffovPl7XVtaClaywxTn0dI/h7X6loOwCq17Tj0zJXFJ+/+/Cpt+rwnZzP6xQ+91YYbevke9rxeVvHZzTtCB+VdDXgzMxMZGVlVfg1O3XqhISEBPHObAB49OgREhIS0Llz51J3aAsEAhw8eBAbN26Ev79/hd+f7qFNvpmgoCBkZmbC1rbgUhyKioqwtrZGQEBAqc/JyspCx44dxcPU1dXRvHnBJTeePXsGRUVFaGtrIzg4WKKioqIqlDUpKQkRERES76ugoCBx724NDQ20atUKv//+O27cuIFXr15J3As838uXL+Ht7Y0ff/wRo0ePhouLS6nvm5WVheTkZIkqTY2atcU7jzUbNIGWrjFq19VCsP998Tg5OVkIDXyCxsZtSn2dxkaWCPa7LzEs+OU9NDayBAAoKipDt4mpxOsCQLDf/S++LgAwMORkV2wFWaNmbWg0aCKu/P7eFsqR+7k/PaMv9/e2SPa3fvfQ2NgSAKDwub+3Rf4Gb/3vQ+8L/aWlxCMxLhJq6lpl7qkif8sSp4/fPeg2NYWColLp41RgGuZ/mI+Nfofx8/dBtXbx+bk8FBWVodPUtFi2t/730biUaaZXwvQKKtKvnpFlsekVXGiaAkB2VjoEAslNnEAolOllYLianpWlqq1TZD0/VqV1yqfcHHzKzYZAWMI8+unL82hVmk71tPTK9d4+XqfQwrIHatXR+GKPVbVfgObL8vbG12nH594K42o7bmjSETPWnIfjqjPi0m3aGmYdB8Jx1RmZ7MzO74+r7ThjDO6HViPg6VVMWLgf9bT0pO6H5svK/3ypb9xGfB/ffLFRoVDX1K1oOwCq17Tj0zJXFJ+/+/Cpt+rwnZzP6xQ+91YYbevke9rxeVvHZzTtSEWxT6zK1pIlS5CUlCRRS5Yskarfhg0bIjo6utjw6OhoNGxY+oEYixYtQk5ODrZt2ybV+9MObfLNpKWlYefOndi4cSN69+4NExMT7NmzB6qqqnB2di7xOampqXB2dsbGjRvRs2dPmJqaYv/+/fhU6IfVN2/e4NChQzhw4ACGDBmCpk2bwtraGgsXLkTfvn0rnHfr1q1YvHgxBg8ejBYtWuCff/6Burq6+PH4+HjExMRg6tSpMDIyQo8ePYqdXZ1v7969WLx4MRQUFHDmzJkKZ/oSgUCAjr3Gw+vibgQ8vYqo8Nc467wESsoqMOtQcH+p03sW4dopJ/G/O/Qah2C/e7jrsQeiyLe467EHbwMeoGOvCeJxOvWeCJ87p+Dj5QZRRDA8j65FYlwkrLuPBABkZabhmttmhAU/R0LMB0S888O5fcuQFPcRpu36yKy/Dt+Nh5f7bgT4XEV0+GucdSne35m9i3DNrVB/3xX0F1Oovw6F+utoPxE+XqfwLL+/Y5/76/a5v4xUXDm+HmFBz5AQE47QV49wdNt0qKrVQ8s235Wrj6/9La+dcsLpPYvE41t3H4nE2Ah4HlsLUUQwfLzc4OPlhs69Jxf0KINpmJubgxP/zEJE6EsM+3EjPrFcJCeKkJwoEp8xWBGd7T+/75289710dC0SYyPRrkfe+149Kdlvux4jkRATAc+jn/u944Znd9xg06eg346f+/Vyz+vXy30P3vo/QKdC/baw7AGvi7vw+r9biI8JR8DTq3hweT9atu1V4V5KwtX0zMxIReT7AES+zzsYKCEmHJHvA5DwhXtNlReX65TKmh+L9sfVOqVGzdpo0qIdrp7YiNBXjxAvCsfzu6fhe/9cuedRLqdTWd8bAGKj3uHda2+07TqiXP1VpX5pvpS+N75OOz73xsV2vEbN2mig11yilGvUhGptdZnfR46r7bj7odXiS+gqq9QST7PsrAyZ9Ubzpew/X3ayn4jwt//hzsVdiI16B98HF/D01gm0txsjdU+F8Xna8XmZA/j93YdPvVW37+R8XqfwuTfa1uWRx2nH922dNBRqqaKORUvUsWgJAFA10EMdi5ZQaazDcbI8NO0I36xduxZ16tSRqLVr15Y47ooVK8AY+2Lln+xZ9ArMQPGrMBfWtm1bzJo1CxMnTpS6J7rkOPmmFi9eDKFQiIMHD0JNTQ3e3t7o3bs3EhISSn3OggULULt2bZw/fx7JyclwcnJC3bp1JcaZNGkSli1bBicnJzRq1AixsbF48OABPDw8KpzVyckJOjo64h3oLi4uOHPmjPi9GWMYOXIktm3bhpcvXyIwMBC//PILbt++Xey1jh49ir/++gtHjhxBZmZmhTN9jU3fKcjOyoD7odVIT02EnqE5xs1zRo1Cl81JjIuAQFhwKXd947YY7uiEG6e34saZbdDQbozhjpuhZ2QhHqd1+35IS0nA7fM7kJIognajZhgzezfU6zcCAAiECoiJDMF/935BWko8atZSRyMDM0xechjajZrJtL+c7Ax4FO5vbgn9FbpUfWPjthg+zQk3zmzFzbOf+5u2GXqGkv2lpyTg9oVC/c2S7C/6w2v89+AcMtKSoVZXC01btsdwxy0S710WX/tbJieKkBhXsFOynpYexszZDc+j6/DkxhGoqWuj7+hf0cq6t3gcWUzDpPiPCHx+AwCwa+VgicwTFrrCoGWHcvUpft8O/ZCWmve+yfnvO6fgfVMSRUiMlex37Od+H+f3O6ZIv80K+r15ZhvqaTfGiCL99huzDDfObMPFg6uRmhQLNXVtWHf/Ad0GzahQH6X2x9H0jAh9CdcNBR9+Lx9bBwCwsBmMIQ7rZNYfV+uUypofS+qPi3UKAAyfthnX3Tbj9J4FSE9NRF1NXfQcMlv8Ram8fXAxncr63gDw7K4b6qg3gJGpTbn7qyr90nwpm974Ou342htX2/FvhavtuPfNowCA/evHS+QZNPlPtLEdKrP+aL7MI6v5spGhGUb+vB3XTm3G7XP/QF1LD31GL4F5p4FS9VMS3k47ni9zfP7uw6feqtt3coC/6xQ+90bbujxyOe14vq2TRl2r1uh0/aD43602LQUAhB04DV8H6c4alQWadoRvsrKyynx58b///hvHjh374jihoaEwNzdHgwYNij2mpaVV6tWSu3TpAm1tbYnb8CoqKsLJyQmzZ8+GgYFBmTICeXefL3m3OSFEZvT09BAaGop27drh2bNn5XouYwxH7/FzMR1lk/eh9Mhd/vU32javN75Pu2P3+dffyM78nXb5042PvQG0TpFXNF/KL5ov5Rdtx+UTzZfyi8/zJcDvebM6zJd87A3g93JXHZY5PvYGVI91Ch+nXXWZL92VWnCcRPb6ZwcC4Oe0G2UjkDjQnXCjz4T/uI5QKk9X2R803rJlSwQEBKB9+/Z48uQJAKB9+/Z49OgRWrRoUeI9tDU0NKCjI3klhsuXL+PgwYPYt29fqffdLgmdoU1IJVJUVISOjg7WrVuHhw8flntnNiGEEEIIIYQQQgghhBBCCCFcevXqFS5duoQ9e/Zg2rRpAIB///0XFy5ckNgxHRAQgCVLluDs2bOIi4tDXFycxOtkZ2fj48eP5dqZDdA9tEk1lpycXGrZ2trK5D1sbGzw/v17WFlZwdHRUSavSQghhBBCCCGEEEIIIYQQQsi3NGbMGLx48QJXrlzBlStX4Ovri3HjxkmM07Jly2K3DZYFOkObVFuWlpalPvbhwweZvMft27fp0h+EEEIIIYQQQgghhBBCCCE88ol94jrCNxcfH19sB3ZRX9snVp77ZhdGO7RJtRUcHMx1BEIIIYQQQgghhBBCCCGEEELIF9AlxwkhhBBCCCGEEEIIIYQQQgghhFRJdIY2IYQQQgghhBBCCCGEEEIIIYSUEfvEuI5QrdAZ2oQQQgghhBBCCCGEEEIIIYQQQqokAQA6hICQKowxWkQJIYQQQgghhBBCCCGEEJJHIBBwHaHa6zXWh+sIpbp6qC3XEWSOLjlOCCGEEEIIIYQQQgghhBBCCCFlxD594jpCtUI7tAmRAycf8nPFOKJj3l0Pjt7j31noo2zyjpDjY28Av/vL7+28dy7HSWTve2sFAPycbkD1mC+P3edfbyM783e6AdVjvqTe5A+f+6Pe5Bef++NzbwC/+6Pe5Bef+6Pe5Bef+6Pe5Bef+8vvzV2pBcdJZK9/diDXEQj55uge2oQQQgghhBBCCCGEEEIIIYQQQqokOkObEEIIIYQQQgghhBBCCCGEEELKiH3i35UNqjI6Q5sQQgghhBBCCCGEEEIIIYQQQkiVRDu0CSGEEEIIIYQQQgghhBBCCCGEVEl0yXFCCCGEEEIIIYQQQgghhBBCCCkjxj5xHaFaoTO0CSGEEEIIIYQQQgghhBBCCCGEVEm0Q5tUaTdv3sSWLVsq9T327duHM2fOVOp7EEIIIYQQQgghhBBCCCGEEELKjy45TgjPPbp+BF4eLkhJFEFb1xj9xixB0xbWpY4f8uoxLh1Zj+iIIKipa6NLPwe07zlS/PiTWyfw/N55RIW/AQDoNm0F++FzoGdkLtPcjDHcOvc3nt4+gYy0JDQyNEf/scuh3ajZF5/n730ZN85sQ7zoPepp6cNu6GyYWPWSGOfxjSO47+mM5AQRtBsZo8+opWjSvOBvUpb3jot+jyvHN+D9m6fIycmCcesu6DdmGWrXrc+L/gqPe3jLVAS99MIPP/8Nk7bflam/qtBrbk42bpzZije+txEvCkeNmrVh2Kozvhs+F3XqNSh3H2V1/+pR3HJ3QXKCCA0aGeP7cYth2LL0ZS444AkuHFqPqA9BqKOuje4DJqPTd4WWudtncOLfX4s97899z6CkXKNSesj3tXmpqNDAx7h8bB2iP+StP2z6TkG7HiMlxvnadA0NfIL7ns6ICPVDSqKowvNdWfB53nx84wjuXXJGSoIIWo2M0Xf0V6bdq8fwPLYOog9BUKv35WkXF/0eGtrF+755djtundsh8Zzadepjwda7UvVS1deXF1yX463/AyQnREO5hioaG7fBdyPmQ0vHUK76/RbzJZfT0v/pFTy9dRwR7/yQnpKAaSvPQEffRCZ9leX9i6L1ZYHqOl/yuTdA9stcVd8WAEBY0DNcP/0XPrz1hVBBEQ31W2LsnD1QUlYpd798XqfweZnje3986k0e1in540r7fbwsmYqSp3UKn3qTh/lSlts6Lvu9eXY7Xj72QFLcRygoKkGniSnshs6GnpFFufsoCZ/my6rQm5f7bgQ8vYqYyLdQVFZBY+M26DV8HupX8Dt3ZdCwtYbhPAfUbdsaKrra8B42A1Hnr3Mdi3wDnz4xriNUK3SGNqkSFBQUKuV1hUIhBAJBpby2tJSUlCr9PV488oDH4XXoPnAaZqw+jSYtrHDAaRoSYiNKHD9OFI4DTo5o0sIKM1afRrcBU+F+6E/4PbkiHifk1ROYd+wHh8X7Me23o1DX1MX+TVOQFBcl0+z3Lu3Fgyv70W/sb/jxt5OoXVcLBzZNRmZ6SqnPCQt6hpO75sKi8/dwXHUOFp2/x8ldcxAe/J94nJePPeB5dC26DHCE48oz0G9mjUNbpkr8Tb723lmZaTjo5AAIBJiwcD8clh5Bbm42jmybjk+fynbfjKrcX2EPr7oCUi5DXPWanZWByHf+6DpwBqatcMMPP29HbFQojm6bIVU/X/L8wSWcP7gWdoOmYfYfbjBoaQXnDdMQH1PKMhcdDueNjjBoaYXZf7ih56CpOHfgT/g+viIxnkrN2vhtx22Jquyd2WWZlwqLF4Xj8JZp0G9mDceVZ9BlwDRcOvIH/L0vi8cpy3TNzkxHg8Yt0W/sb5XaH8DfefPlIw94HlmLrgMc4bjqDJo0t8ahzV+edoe2TEOT5tZwXHUGXfpPw6XDJUy7nXNh3ul7TF99DuadvseJnZJ9A4B2o2aY/5eXuGasOS91P1V9fanTxBSDJv+Jn/5wx9h5e8HAcNDJAZ8+5cpVv99incnltMzOTEfjZm3x3fB5MuunPO9fGK0vab7ke2+A7Je5qr4tCAt6hkNbfoSRqQ1+/O0Epi4/ifZ2YyAQlP8nF76vU/i8zPG9Pz71VtXXKflk8X2cz+sUvvVW1edLWW7ruO5Xs2FT9BvzG6avPo/JSw5DvX4jHNzsgNSkuAr1Uhjf5suq0Fto4BO06zkaU5Ydx/h5LviUm4ODm6cgKzOt0notL4VaqkjyDYTfrNVcRyGE12iHNqkUysrK2Lp1K6KiopCeng4vLy9YW+cdrdWtWzcwxmBvb48nT54gMzMTXbp0gaqqKlxdXZGcnIyIiAjMnTu32OsqKSlh/fr1CA8PR0pKCh4+fIhu3bqJH58wYQLi4+PRv39/+Pn5ITMzE02aNClT5nnz5iEiIgIxMTH4+++/oahYcAEDdXV1uLq6Ii4uDqmpqfDw8ICxsbH48RUrVuDZs2cSrzdr1iyEhISI/51/afPFixfjw4cPeP36ddn+mFK45+kKq65DYd19BLR1jdB/zFLU1WiIx9ePlTj+kxvHoK6pg/5jlkJb1wjW3UegbdehuHvJRTzO/xw3ooPdaOg0MYGWriEGT14N9ukTgv0fyCw3YwwPrx5A1wGOaGVljwZ6zTHEYR2yszLw4tHFUp/38OoBGLXqjC79p0FLxxBd+k+DgUnHvC+Bnz24vB9tuwyDVdcR0NI1Qt/ReX8T75tHy/ze79/4ICHmAwY7rEUDvRZooNcCgyf/iYiQFwgJeCj3/eX7+P4VHlzej0GT//hqT1WxVxVVNYyf74LW7fuivo4hGhtZot+YZYh851fqh21p3bm0H+26D0OHHsPRoJERBo1bAnVNHTy4VvIy9+D6cdTT1MGgcUvQoJEROvQYjnbdhuK2+z7JEQUC1FHXkqjK9rW/b1Het46hrqYO+o5eCi1dI1h1HYE2XYbi/uWC9UdZpmsz866wGzobrazsK7U/Ps+b96/sR5uuw2DVreD962g0xJMbJU+7JzeLTLtuedPunmfBtHtw5QAMTTuj64C8vrsOmAZDk454UKhvABAKFaBWV0tctepoSNWLPKwvrbv/gKYt2qFefT3oNjFFzyGzkRQXiYSYD3LVb2XPl1z2BgAWnQeh+/c/wbBVJ6l7KYrWlyWj+bL69gbIdpmTh22B57F16GA3Dl36T4V2o2bQbNAUptZ9oKikXO5++bxO4fMyx/f++NSbPKxTANl8Hy9LpqLkaZ3Cp97kYb6U5baO688p5h0Hwsi0MzS0G0O7UTP0HrkYmekpiAoPLHcvRfFpvqwqvY2buxdtbIdCu1EzNNRvicGT1yIxNgIRoX6V1mt5iS7fwesVf+Hj2atcRyGE12iHNqkUGzZswLBhwzBhwgS0bdsWQUFBuHz5MurVqycxzpIlS2BiYgJfX19s3LgRPXr0wJAhQ2Bvb4/u3bvDyspK4nX37dsHGxsbjBw5Eubm5jh58iQ8PT0ldi6rqqpiyZIlmDJlCkxNTREdHf3VvD169ICRkRF69OiBCRMmYOLEiZg4caL48f3798Pa2hrff/89OnXqBIFAAA8PD4md3mVhZ2cHExMT9OrVCwMGDCjXc8srJycLEaF+MG5tIzHcuLUN3gc9K/E574OeFxu/WWsbfAj1Q25OdonPyc7MQG5uDmrWriub4Mg7gi8lUQQj04IsikrKaNqiHcJKyQ4AYcHPYVSsX1uEBT8H8Plv8s5P4nUBwMjURvy6ZXnv3JwsQCCAoqJyoXFqQCAQ4v2bp3LfHwBkZabj1O556Df2N6jVrfjOUy57LUlGWjIgEEBFtU4FuvmynJwsfAjxR3MzyUzNzTrj3ZvnJT7n3ZvnaG7WWXJ8c1uEh0guc1kZafjjFzv8/nMPuGycjg+h/jLPX1hF/r5hwc+LjW9saouIQuuPr03Xb4mv82ZOThYiQ/1gXNL7B5f8/uElTbvWktOupHGMWtsiLOi5xLDYqHfYNKcLtiyww8mdcxEXHSZVP/KwviwsKzMNz++ehnp9PdTRaFiuXiv6nkDVny+BqtebrND6kubLfNRb5S1zVX1bkJIUiw9v/0OtOhrY+8dIbJxtg33rxuLd669/LyiK7+uUqjZfyvq7AZ/741NvVX2dAsju+zif1yl8662qz5ey3NZx3W9ROTlZeHr7OGrUVEODxi0r1E/h1+LTfFlYVeotIz0ZAFCzlux+iyakotinT1W2+Ih2aBOZU1VVxfTp07FgwQJ4enoiICAAP/74I9LT0+Hg4CAeb/ny5bh27Rrevn2LzMxMODg4YP78+bh27RpevnyJCRMmSFyK3NDQEKNGjcKIESNw9+5dvH37Fk5OTrh79y4mTZokHk9ZWRkzZszAgwcP8Pr1a6Slff3yI/Hx8fj5558RGBgId3d3uLu7w87ODgBgbGyMQYMGYcqUKbh79y58fX0xZswYNGrUCIMHDy7X3yY1NRVTpkyBv78//PyKH0WmrKwMNTU1iaqotOQEfPqUW+yezrXqaiIlMabE56QkxqBWXU2JYbXr1sen3BykpcSX+JwrJ51Qp14DGLXqXOLjFZGSJMrLWkcyS606pWcHPucv8Tl5r5eWHA/2KbdYj4VftyzvrWdoCeUaNXH15CZkZaYjKzMNV05sAGOfxO8lz/0BwOVja9HYuA1atrH7aj9fwmWvRWVnZ+LaKSeYdRgAlZq1y93L16R+XubUii1DmkguJVNyYgxqFxlfra4mPuXmIDU5AQCgrWuI/037A5Pm7cDonzdCUakGdqwaC9HHUJn3kK8if9+URFHxafa5l/z1x9em67fE13kzLTkenz7lFstY+4vrflGx+bBWneLTrnbR1ywy7fQMLTD0x3UYN3cvvp+4BimJIjj/MarU7UdZyMP6Esi7j9gf09viz+ltEfTSC+Pnu0gc9FRWfJ0vgarVmyzR+pLmS8nnUG+VoapvC+JFeQdv3Tr3N6y6jsDYOXug08QUBzZNRGxUaHla5f06pSrNl5Xx3YDP/fGpt6q+TgFk932cz+sUvvVW1edLWW7ryvqeJT5PhuuUwOc38cf0tvh9mgUeXnHF+PkuqKVWD9Lg23xZWFXpjTGGy8fXQb+ZFRroNa9oO4QQOVW+00sJKQMjIyMoKyvj3r174mE5OTl4/PgxTExM8OTJEwCAt7e3xHNq1KiBBw8KLlsdHx+PwMCCS720bdsWQqGw2KW6a9SogdjYWPG/MzMz4evrW67Mfn5+Evc+joyMhJmZGQDAxMQE2dnZePTokfjxuLg4BAYGwsTEpFzv8+LFC2RnZ5f6+JIlS7By5cpyveZXFb3dEmNfvAeToMgTGGOlvBDg5b4Xvg894LDYVar7+fo+uIALB1aI/z1m9q68dywp51fuH1U0P1je0K+OU+R1v/TetepoYMT0v+B+cBUeXT8IgUAIsw79odOkFQTC4veDl7f+Xj27gZCAR5i28vQXs5SkKvYKALk52Ti1ay4YY+g/bkWxx2Wq6PszhpKWH/HopS1znwc3aWaBJs0sxI83bd4Wf/06DPcuH8bgCb/KInGZs5X29xWPX6x38QNffs0v/H1kpbrNm0X7YqyETJLPKO2FSn3NvGcVDGtm3lX8/w0ANDa2xNaF9nh+7yw6955U7LklqYrTqSzvnX/JuuQEEe5fdsHJnbMxeelRKCl9edtYFfsFZDNfVtXeKgutL0tG8yX1VhFVsZcvvTdjed8jrbr/gDZdhgEAdJq0wtuAB3jm5Vah+4jzZZ1SFaclILvPX3zuj0+9VcVeKuv7eGn4sk4pibz2Jm/zpbTbuqrYr4FJBziuPIO0lHj43D6JkztnY8qyE8UO5K4IeZ0vy4Lr3jwOrUFUWCAmLzlSpryEEH6hHdpE5gTiDzus2PDCw1JTU4s950uEQiFycnJgZWWF3NxcicdSUlLE/5+enl7uzEV3MjPGIBQKv5itcD+fPn0qNp6SklKx5xTuuSRr167F5s2bJYYlJSV9OXwpVNXUIRQqICVB8ii51KS4Uj+c1a5bv9hRdalJsRAqKEK1trrE8LseLrh98V9MWuiChvotKpQxXwvLHmhkaC7+d25OFoC8o/TU1LUlsnzpg2XtuvWRklQkf3Ks+Cx1VbV6EAgViveYXPC6tetolem9jVvbYtb6q0hNjodQQQE1Vetg42xbtK6vJ/f9hQQ8RJzoPdb93F7idU7s+AX6za0wadHBUjNWpV4LMmTj5M45SBCFY8LC/ZVydjYA1Pq8zCUXWeZSkuKKnbWdT61u/WJnb6ckxUGooIhaRZa5fEKhEI0NzRDz8Z1McpekPH/ffLXrapW+/qil/nmcL0/XylRd5k1VtXp56/4SpkXRI6nzlXXaFZ9XY1HrC9NOuYYqtPWaIzaq7PNqVZpOZd0eAHn3dlRRVYNmg6bQM7LA+p874NXTqzDr+OXbi1SlfgsyyGa+rIq9VQZaX9J8Sb2V3ltFVaVeyrItUKubN1xL11jidbR0jJAYF1mGjgvwbZ1SlaZlQQbZff7ic3986q0q9VLZ38eL4ts6pTB5703e5ktpt3VVqd98yjVUodmgCTQbNEFjI0tsW9wbz7xOoUv/aV/tpzTyPl9+SVXozePwGgQ+v4FJiw+hbgVu8UVIZWCf2NdHIjJDlxwnMhcUFITMzEzY2tqKhykqKsLa2hoBAQGlPicrKwsdO3YUD1NXV0fz5gWXDnn27BkUFRWhra2N4OBgiYqKiqq0fvz9/aGkpIQOHTqIh2loaKB58+bifkQiERo2lNyQWlpalvu9srKykJycLFEVpaioDN2mpgjyuy8xPMjvPvSN25T4HH1jy+Ljv7yHRk1NoaBYsIPey8MZN8/vxIR5/6KRQesKZ8xXo2Zt8YdIzQZNoKVrjNp1tRDsX5AlJycLoYFP0LiU7ADQ2MgSwUXyB7+8h8ZGlgA+/02amEq8LgAE+90Xv249Lb1yvXcttXqoqVoHbwMeIjU5Fi0se8h9f7b9f8T0VefguPKMuACg98jFGDx5ban5qlqvQMGPHrHR7zB+/j6o1q73xfzSUFRURiODVnjzUjLT6xf30aSZZYnPadLMEq9fFB3/HvQMJJe5whhjiHj/CnXqVfxeal9T1r9vYSVOM7970C20/vjadK1M1WXeVFRUhk5T02IZ3/rfR2OjkvvSM7LEW/+i2wrJaadnZIm3JUzfxsaWpWbJyc5CTGRwue77V5WmU3m3B4UxMOR8/pFGXvoFZDtfVrXeKgutL2m+pN5K7k0aVamXsmwL1Os3gpq6NmIjQyReJzYqFHU1dcvVO9/WKVVpWgKy//zF5/741FtV6qWyv48Xxbd1SmHy3pu8zZfSbuuqUr+lYWDIyf76d7gvkff58ku47I0xBvdDqxHw9ComLNyPelrFTyYihFQPtEObyFxaWhp27tyJjRs3onfv3jAxMcGePXugqqoKZ2fnEp+TmpoKZ2dnbNy4ET179oSpqSn2798vcRnwN2/e4NChQzhw4ACGDBmCpk2bwtraGgsXLkTfvn0rrZ+goCCcPXsWe/bsgY2NDczNzXHo0CF8+PAB586dAwDcunULWlpaWLhwIQwNDTFjxoxKzVRWNn0m4OltNzy944boiGB4HF6LxNhItOv5AwDgyonNOLV7kXj8dj1HIiEmAh5H1iE6IhhP77jh6Z3TsO07WTyOl/teXHPbiqEOf0C9fiMkJ4iQnCBCZsaXzz4vD4FAgI69xsPr4m4EPL2KqPDXOOu8BErKKjDrUHC22+k9i3DtlJP43x16jUOw3z3c9dgDUeRb3PXYg7cBD9Cx1wTxOJ16T4TPnVPw8XKDKCIYnkfXIjEuEtbdR5brvZ95uSEs+Dniot/jvwfncfKfWejUawLq6xjKfX9qdbXQQK+5RAFAXU3dcn9o5LLX3NwcnPhnFiJCX2LYjxvxieUiOVGE5ERRmXY0VUTXvhPx+OYpPL7lhqgPwTh/cB0SYiPRyS5vmfM4thlHdy4u6MHuB8THRuL8ofWI+hCMx7fc8OSWG7r1nyQe54rbDgT63kVsdBg+hAbg5J5liHj3Ch0/v2Zl+drf99opJ5zeU7D+sO4+EomxEfA8thaiiGD4eLnBx8sNnXsXrD/KMl0zM1IR+T4Ake/zDhhKiAlH5PsAJMRGyLQ/Ps+bne0/v/+dvPe/dPTzur9H3vtfPSk57dr1yFv3ex79PO3uuOHZHTfY9CmYdh0/9+3lnte3l/sevPV/gE6F+r58bD1CXz1GvCgc4cH/4fiOX5CZngJLm8EV7qWqry/josPg5b4bEaEvkRAbgbCgZzi5cw6UlGqgmXk3ueq3sudLLnsDgLSUBES+D4AoIhgAEPsxBJHvA5Asg/vO0foyD82X1FtlLXNVfVsgEAjQuY8DHl0/CD9vT8RGvcON01sRE/kWbbsML3e/fF6n8HmZ43t/fOqtqq9TZPl9vCyZ5Hmdwqfeqvp8KettHZf9ZmWm4ZrbZoQFP0dCzAdEvPPDuX3LkBT3Eabt+pS7l6L4NF9Wld7cD62G74MLGDZtE5RVaom3AdlZGTLrTVoKtVRRx6Il6li0BACoGuihjkVLqDTW4TgZIfxClxwnlWLx4sUQCoU4ePAg1NTU4O3tjd69eyMhIaHU5yxYsAC1a9fG+fPnkZycDCcnJ9StW1dinEmTJmHZsmVwcnJCo0aNEBsbiwcPHsDDw6NS+5k0aRK2bt2KixcvQllZGXfu3EG/fv2Qk5MDAHj16hVmzJiBpUuX4rfffoObmxs2bdqEqVOnVmqurzHr0A9pKQm4ee4fJCeI0KBRM4ybuwv16jcCACQnipBQ6NJAGlp6GD9vFzyOrMOj60egpq6N/mOXwrSdvXicRzeOIjcnG0f/niXxXj0G/wS7IT/LLLtN3ynIzsqA+6HVSE9NhJ6hOcbNc0aNQpcVS4yLgEBYcKl3feO2GO7ohBunt+LGmW3Q0G6M4Y6boWdUcP/h1u3z/ia3z+9ASqII2o2aYczs3VD//Dcp63vHfAzFNbctSE9NhHp9XXQZ4IhO9hN5058scdVrUvxHBD6/AQDYtXKwRKYJC11h0LIDZM2yU1+kpSTg2pmdSEoQoaFeMzgs2I16Wp8zJcQgIbbQMqetB4cFu3Dh0Drcv3oEdeppY9D4pTBvX7DMZaQl49TeFUhOjIGKqhoaNTHB9N8OQN/IvNj7y9LX/r7JiSIkxhV8MaqnpYcxc3bD8+g6PLmRt/7oO/pXtLLuLR6nLNM1IvQlXDcU3km6DgBgYTMYQxzWybRHvs6brTv0Q1pq3vsn57//nIL3T0kUITFWctqN/TztHudPuzFFpl2zgr5vntmGetqNMaJI30nxUTi1ex7SkhOgqlYPekYWmLLsuMT6pyKq8vpSUUkZ714/xcOrB5CemoTadTTRpIU1HJYerfCld/k6X3LZGwAEPr+Bcy5Lxf8+tWsuAKDb9z+hx+CZUvVF68s8NF9Sb5W5zFXlbQEAdLKfgJzsTFw+ug7pqYlo0LgFxs1zgYa2frl75fs6hc/LHN/741NvVX2dIkt8XqfwrbeqPl/KclvHZb8CoQJiIkPw371fkJYSj5q11NHIwAyTlxyGdqNmFeqlML7Nl1WhN++bRwEA+9ePl8gzaPKfaGM7VCa9SauuVWt0ul5wS4hWm/I+B4cdOA1fhyVcxSKEdwQA6CLvhFRhjDGcfPjp6yPKoREd8y4ScfQe/1ZDo2zyPnDzsTeA3/3l93beO5fjJLL3vbUCAH5ON6B6zJfH7vOvt5Gd+TvdgOoxX1Jv8ofP/VFv8ovP/fG5N4Df/VFv8ovP/VFv8ovP/VFv8ovP/eX35q7UguMkstc/OxACgeDrI5JK1WWwF9cRSuV1tgvXEWSOLjlOCCGEEEIIIYQQQgghhBBCCCGkSqJLjhPeS05OLvWxvn374u7du98wDSGEEEIIIYQQQgghhBBCCCGkrGiHNuE9S0vLUh/78OHDtwtCCCGEEEIIIYQQQgghhBBC5B77xL9L9VdltEOb8F5wcDDXEQghhBBCCCGEEEIIIYQQQgghFUD30CaEEEIIIYQQQgghhBBCCCGEEFIl0RnahBBCCCGEEEIIIYQQQgghhBBSRuzTJ64jVCt0hjYhhBBCCCGEEEIIIYQQQgghhJAqSQCA7lpOSBXGGC2ihBBCCCGEEEIIIYQQQgjJIxAIuI5Q7dkMuMV1hFLdu9id6wiVglFRUVEBYMrKymzFihVMWVmZ8yzUH/VWHXrje3/Um/wWn/uj3uS3+Nwf9Sa/xef++Nwb3/uj3uS3+Nwf9Sa/xef+qDf5LT73R73Jb/G9PyqqKlCcB6CioqoipaamxhhjTE1NjfMs1B/1Vh1643t/1Jv8Fp/7o97kt/jcH/Umv8Xn/vjcG9/7o97kt/jcH/Umv8Xn/qg3+S0+90e9yW/xvT8qKq6L7qFNCCGEEEIIIYQQQgghhBBCCCGkSqId2oQQQgghhBBCCCGEEEIIIYQQQqok2qFNCCGEEEIIIYQQQgghhBBCCCGkSqId2oQQsczMTKxcuRKZmZlcR6kUfO6PepNffO6PepNffO6PepNffO6PepNffO6Pz70B/O6PepNffO6PepNffO6PepNffO6PepNffO+PEK4JkHczbUIIIYQQQgghhBBCCCGEEEIIIaRKoTO0CSGEEEIIIYQQQgghhBBCCCGEVEm0Q5sQQgghhBBCCCGEEEIIIYQQQkiVRDu0CSGEEEIIIYQQQgghhBBCCCGEVEm0Q5sQQgghhBBCCCGEEEIIIYQQQkiVRDu0CSFEzigqKuLGjRto1qwZ11FkTkFBAdnZ2TA1NeU6CiGEEEIqoEuXLlBQUCg2XEFBAV26dOEgkewpKCjAzs4OU6dORe3atQEAOjo6qFWrFsfJyNfQtJM/3bp14zoCIRLoOysh3NHX14eKigrXMQghhHBEkesAhBBu6enpoWnTplBVVYVIJIKfnx+ysrK4jiUTTZo0QZcuXST6e/bsGR48eIDMzEyu41VYTk4OWrduDcYY11FkLjc3F+/evSvxh3BSNbm5uZV53GHDhlViEtkbOHBgmce9cOFCJSb5NmxtbTFt2jQYGRlh+PDhiIiIwNixYxESEoJ79+5xHa9czMzMyjzuixcvKjGJ7PG5NwCYOXNmmcfdvn17JSaRPb5Pu3w3b96Ejo4ORCKRxPC6devi5s2bUFSU76+g+vr68PT0hL6+PmrUqIGrV68iJSUFCxcuhIqKCqZPn851xHKpTts6vk27orp27Yr58+fDxMQEjDEEBARg48aNuHv3LtfRpOLp6YkPHz5g3759cHV1RXh4ONeRKpVQKISZmRnevXuHhIQEruOUW3XY1vH1O6uamlqZx01OTq7EJLLH596KMjQ0xKRJk2BkZIRZs2ZBJBKhd+/eCAsLg7+/P9fxpCIQCPDmzRuYmpoiKCiI6zikHLp164bbt29zHaNSKCoqIjAwEAMGDEBAQADXcQipFhgVFVX1Kn19ffbnn3+ykJAQlpOTw3Jzc8WVnp7Orly5woYPH84EAgHnWStSo0aNYg8ePGC5ubksMjKSeXt7My8vL+bn58cyMjJYQkIC27FjB9PX1+c8a0Vr06ZNbO3atZznqIyaOHEic3d3Z/Xq1eM8S2XVmDFjSn1sw4YNnOcrT7m4uIhr3759LCEhgb179465ubkxNzc3FhoayhISEpiLiwvnWctbhdeNubm5xdaXOTk54uI6q7Q1dOhQlpqayv7991+Wnp7ODAwMGAA2ffp05u7uznm+iky7/OlVeDqVVFxnpd4k6+3btxKVnJzMcnNzWWxsLIuNjWW5ubksOTmZBQcHc56Vpl3pfdavX7/Y8GbNmrHExETO80lbZ86cYQcOHGBKSkosKSlJvL7s2rUre/36Nef5KjK9qsu2jm/TrnCNGTOGZWVlsWPHjrGZM2eyX375hR07doxlZmayUaNGcZ5PmqpXrx6bOXMme/r0KcvOzmaenp5sxIgRTElJifNssqgtW7awyZMnMwBMKBQyLy8v8bauW7dunOcrb5W0HilpHSPv6xQ+fmcty+cTed0e8Lm3wtW1a1eWmprKrly5wjIyMsTbuQULFrCTJ09ynk8W9fLlS9ahQwfOc1RGaWtrswMHDrAPHz6w7OxsXs2b6enpLCgoiP36669MT0+P8zyyrvDwcNayZUvOc1BRVZPiPAAVFdU3rL/++oslJiaykydPsnHjxrEWLVqw2rVrMwUFBaalpcV69OjBli9fzgICAtiLFy+YtbU155nLU0+fPmVPnjxhP/30E2vcuHGxx5WVlVm3bt3Yzp07WXR0NBs+fDjnmStS27ZtYwkJCczb25vt2rWLOTk5SRTX+aQpHx8flpSUxNLT09mrV6/Y06dPJYrrfLKo+Ph41r9//2LDN2/ezCIiIjjPV9Fat24d+/fff5lQKBQPEwqFbNeuXXK3o75o2dnZMW9vb2Zvb8/U1NRY7dq1mb29PXv8+DH77rvvOM8nbfn4+LBx48YxABI/8ltYWLDIyEjO85W39PX1xTVo0CD25s0bNnXqVGZmZsbMzMzY1KlTWWBgIBs0aBDnWam30mvUqFHMy8uLNW/eXDysefPm7Pbt22z06NGc56NpJ1n5BzLl5OSwixcviv/t5ubGzp49y96+fcsuXbrEeU5pSyQSiefJwuvLJk2asNTUVM7zSVN839bxedr5+/uz2bNnFxs+Z84c5u/vz3k+WZWFhQXbunUri46OZjExMWzr1q3M3Nyc81zSVFhYGLOysmIA2KBBg1h4eDhr1qwZW7NmDbt79y7n+cpbhbd1Xyuus0pTfPzO2rVrV3GNHz+eRUREsD///JMNHDiQDRw4kP3555/sw4cPbPz48Zxnpd5Krvv377M5c+YwQHI7Z21tzcLDwznPJ4vq168fu3PnDjM1NeU8i6zLw8ODvXz5kjk6OrJBgwax77//XqK4zidN8f3gtEWLFrF9+/YxBQUFzrNQUVWD4jwAFRXVN6wNGzaUeNZMSdW3b182bNgwzjOXp/r161fmcTU1NeVuh31+3bhxo9S6fv065/mkqeXLl3+xuM4ni+rduzeLj49nXbp0EQ/btm0bCw8PZy1atOA8X0UrOjpaYsdTfjVv3pzFxMRwnk+aevHiBbOxsSk23NbWlhc/FKemprImTZowQPLHDwMDA5aens55Pmnq0aNHrG/fvsWG9+3bl3l7e3Oej3orvYKCgpilpWWx4W3btmVv377lPB9NO8nKv1pHbm4uO3r0qMQVPHbt2sUWL17MNDU1Oc8pbcXGxjITExMGSK4vbWxs2MePHznPJ03xfVvH52mXkZHBjIyMig03MjKS++140dLR0WErVqxg6enpLDk5mWVnZ7M7d+6wVq1acZ6tIpWens4aNWrEALDdu3ezLVu2MACsadOmvLiqBV+L799Zr127xkaOHFls+KhRo9jNmzc5z0e9lVzJycmsadOmDCh+4BZftgVxcXEsIyOD5eTksLS0NPFVnPKL63zSVFJSErOwsOA8R2UXHw9OO336NEtMTGQfPnxgnp6eEgf2urm5cZ6PiopPJd83MCOElNvChQvLPO6lS5cqMUnl8PDwKPO4sbGxiI2NrcQ0ladnz55cR6g0q1ev5jpCpbt8+TIcHR1x9uxZ2NvbY/LkyRg0aBB69OiBN2/ecB2vwhQVFWFiYoLXr19LDDcxMYFQKOQolWwYGRkhMTGx2PDExEQ0bdr02weSscjISBgbG+Pdu3cSw21tbfH27VuOUsmGmZkZQkJCig0PCQlBq1atOEgkO3zuDQB0dHSgpKRUbLiCggIaNGjAQSLZ4eO0mzx5MgAgNDQUmzZtQlpaGseJKsfVq1cxe/ZsTJs2DQDAGEOtWrWwatWqcn0OrYr4vq3j87QLCwuDnZ0dgoODJYbb2dkhLCyMo1Syo6ioiEGDBmHy5Mno1asXvL298fPPP+Po0aPQ0NDA+vXrcfLkSZiamnIdtdyioqLQqlUrREZGok+fPpgxYwYAQFVVFbm5uRynkw0TExPo6+tDWVlZYviFCxc4SiQ9vn9n7dSpExwdHYsN9/b2xt69ezlIJDt87i0hIQE6OjoIDQ2VGN6mTRt8+PCBm1AyNmfOHDDGuI5RKcLCwiAQCLiOUen+++8/rFu3DnFxcVi8eDEmT56MGTNm4MGDB3B0dJTLe70nJCTAzc2N6xiEVBuc71WnoqKiklWpqamVubjOKosyMjJi9vb2TEVFhfMssqy6desyBwcH9ueff4rvS9amTRumq6vLeTZZlqOjI0tPT2fv378v8awaeSsnJycWGxvL5s2bx2xsbJiNjQ2bN28eE4lEcn8p/Nu3b7Nr166xhg0bioc1aNCAXblyhd26dYvzfNLWggUL2MuXL1n79u1ZYmIis7GxYaNHj2ZRUVHsp59+4jyfNPX06VN26NAhVqNGDfEwZWVldujQIbm9JGR16A0AO3/+PHv+/Ln4UqwAmJWVFfPx8WHnzp3jPB9Nu+pZOjo67NWrV8zPz49lZWWx+/fvM5FIxAICApiWlhbn+aQpvm/r+DztHB0dWUZGBvvnn3/Y2LFj2ZgxY9jOnTtZeno6mzp1Kuf5pKlt27YxkUjERCIR27JlS4mXmW3cuDHLzc3lPGtFasWKFSw+Pp75+/uz0NBQpqyszACwSZMmsfv373OeT5oyMDBgz58/L3ZfbT7cDxbg93fWV69esU2bNhUbvmnTJvbq1SvO81FvJdf69evZnTt3WIMGDVhiYiIzMjJinTt3ZkFBQby4cgDfq1evXszT01N85TS+laKiIhs2bBhzd3cXfw5zcHBgqqqqTE9Pjx0+fJj5+flxnpOKiqrKF+cBqKiovmH5+PgUu79TacV11opU4S/IXyuus0pTGhoa7Nq1a+J+8y8ltXfv3hK/nMlTmZmZsaioKPb69WuWlZUl7m316tXM1dWV83wVraL3Oc+vd+/esbNnz/LiHugCgYAtWLCAhYeHi3+wCg8PZwsWLJC4r7Y8lpGREfP19WWZmZnszZs37M2bNywzM5O9ePGCFwcjAGC///47S01NFU+7tLQ0tnr1as5zSVvt2rVjHz9+ZNHR0ezq1avs6tWrLDo6mkVFRbF27dpxno96K73q16/P3N3dWW5uLsvIyBBfXtDd3V3udz7xedppa2uzAwcOsA8fPrDs7Gxeff7KLxUVFTZx4kS2fft2tmPHDubg4MCLgwurw7aOr9MOABs8eDDz8vJiMTExLCYmhnl5ecn9PTeBgssDf+k+mwoKCqxr166cZ61oDRs2jM2ePVt86XEAbPz48XI//c6fP8/OnDnD6tevz5KSkljLli2ZjY0Ne/jwIbO1teU8nzTF1++s+dW3b1+WlpbGXrx4wfbs2cP27NnDXrx4wdLS0kq8ZYo8FZ97U1RUZIcOHRIfQJKZmclycnLYgQMH5P77eH7dvHmTjRs3jjfb7ri4OIlLpud/30lKSuLV5dT5fnAaFRXVtyvB5/8hhFQTy5cvL/O48ngZra5du4r/v2nTpli3bh3279+PBw8eAMi7vNSECROwZMkSHDhwgKuYUnN1dYW2tjamTJmCgIAAWFhYICQkBL169cKWLVvQunVrriNW2NWrV+Hj44NFixYhKSlJ3FunTp1w5MgRGBgYcB2xQm7cuFGm8RhjsLOzq+Q0lU9NTQ0AkJyczHES2erVqxdatmwJgUAAf39/XLt2jetIMlWzZk20atUKQqEQ/v7+SE1N5TqSTNSsWRNjx46VmHZHjhzhxSWR+dxbvmbNmon7CwgIkOtbMxTG12nn4eEBfX19/P3334iMjCx2Wcjz589zlEw2unTpgvv37xe7FLCCggI6d+4MLy8vjpLJDt+3dUS+VIdlLl+NGjWQmZnJdQyZEYlE6NmzJ168eIGEhAS0b98er1+/Ro8ePeDk5IS2bdtyHbHC+PqdtTA9PT1Mnz5dYnuwa9cuhIeHcx1NanzuDQAMDAzQtm1bCIVCPHv2DEFBQVxHkplNmzZhzJgxqFmzJk6cOAFnZ2c8evSI61gVNn78+DKPK8+/YV67dg179+6Fm5sbsrOzSxxHQUEBNjY2uHPnzjdOJ723b99+8VL4RkZG3zANIfzH+V51Kioqqsqo/KP5iw4fNWoUu3nzJuf5pKnIyEhmbm7OALCkpCTxEeFNmzZlycnJnOeTphISEpihoWGx3vT19Vl6ejrn+aioqKioqKhKr6SkJGZhYcF5jsqqnJycEq8QoKGhwZsz0PlaixcvZpMmTSo2fNKkSWzhwoWc56Mqufi+zAmFQrZs2TIWHh7OsrOzJc70nTx5Muf5pKm4uDhxP0FBQax79+4MADM0NGSpqamc55Om6DsrFRV3JRQK2ffff8/OnDnDMjMzmZ+fH5s3bx7T1tbmPBtV9axffvlFoubNm8cOHTrEYmJi2KJFizjPR0XFp1IEIYTwVKdOneDo6FhsuLe3N/bu3ctBItmpVatWiWdw1a9fX+6P6s/IyECdOnWKDW/RogVEIhEHiSqfmpoaevbsiVevXiEwMJDrOOXm4+PzxaNR81lZWX2DNLI1c+bMMo23ffv2Sk4ie25ubmUed9iwYZWYpHIMHDiwTONduHChkpPIHp97AwAnJ6cyjTdv3rxKTiJ7fJ92ABAWFgaBQMB1jEojEAhK3OZpamrK7VUt+LytK2zatGkYPXp0seF+fn44duwYNmzYwEGqiouNjUXz5s0RGxuLuLi4L34W09TU/IbJZIuPy1xhv/76KyZMmICFCxdiz5494uEvXrzAnDlz4OLiwmE66bx8+RLm5uYICQnBo0ePsHDhQmRlZWHq1Kl4+/Yt1/GkwtfvrGZmZmUa78WLF5WcRPb43Fu+kydPwtvbG+vXr5cYPn/+fLRv3x7/+9//OEomW58+fcL58+dx/vx51K9fH9OmTcOaNWvw559/wsPDA9u2bcPNmze5jlluOTk50NHRKbYO0dDQQHR0NBQV5X83jomJCfT19aGsrCwxXJ6/+wDAtm3bShw+Y8YMWFtbf+M0hPCb/K8JCSEVJhQKMWfOHPzvf/8r8QOFPP/wAeT9oOro6Ij58+dLDJ82bRrCwsI4SiUbd+7cwfjx48WXkGeMQSAQYMGCBXL5wb2wc+fOYfny5eIvW4wxNG7cGOvWrSvXDriq7Pjx47hz5w527NgBFRUVeHt7o2nTphAIBBg5ciROnz7NdcRyOXv2LNcRKs2cOXO+Og5jTC5/5E9MTBT/v0AgwJAhQ5CYmAhvb28AeQcgqKury938mK8s8yVjTC5/GOBzbwDQpk2br45TloNoqiK+TzsAmD17NtatW4dp06bh3bt3XMeRmfzPIIwx7N+/X+IAQgUFBZibm+P+/ftcxZMKn7d1hTVs2BCRkZHFhotEIujo6HCQSDpz5swR39plzpw5crteLA2fl7nCxo8fj6lTp+LGjRvYtWuXeLivry9atmzJYTLp/f7776hVqxYAYNmyZbh48SK8vLwQGxuLkSNHcpxOOnz9zvr8+XPxbwulkdfPKXzuLV+3bt2watWqYsM9PT2L/S7GB+3atcOkSZMwatQoREdHY//+/dDR0cGFCxewc+dOLFiwgOuI5VLavFmjRg1kZWV94zSyZWBggDNnzsDMzExiOcz/7CLPy92XXLp0CWvXrsXkyZO5jkIIb/BzbUEIKZMVK1ZgypQp2Lx5M9asWYM//vgDTZs2xeDBg+Xy/tlFzZkzB25ubujduzcePnwIAOjYsSOMjIzk8mzDwhYsWIBbt27B2toaysrK2LBhA0xNTaGhoQEbGxuu40ll/vz58PDwQHR0NGrWrInbt2+jYcOGePDgAX799Veu48lE165d8ccffwAAhgwZAoFAAHV1dUyYMAHLli2Tux2IfFhflMbQ0JDrCJWm8JeqdevW4cSJE3B0dMSnT58A5B309M8//yApKYmriFJRUFDgOkKl4XNvANCzZ0+uI1Qavk87IO+gLVVVVQQHByMtLa3YffLk9YDJ/IOABAIBkpOTkZ6eLn4sKysLDx8+lDi7Up7weVtXWFhYGGxsbBAaGiox3MbGBhEREdyEkkLhe2m6urpymKRy8HmZK6xRo0Yl3t9WKBRCSUmJg0Syc+XKFfH/h4SEwNTUFPXq1UN8fDyHqWSDr99Z+XDv79Lwubd8tWvXLnHHZ3Z2dolXFJBHWlpaGDduHCZNmoRmzZrhwoULGDlyJC5fviwe58SJEzh79qzc7NDOv1IOYwxTpkxBSkqK+DEFBQV07doVr1694iqeTGzduhUhISH47rvv8PbtW7Rv3x6amppwcnLi5cEW+YYPH464uDiuYxDCO5xf95yKioqbCgoKYv369WNA3n2f8u8BNXPmTHb48GHO88mi9PT02B9//MHc3NzY6dOn2e+//8709PQ4zyWLatCgAVu5ciW7cOECc3d3Z2vWrGENGzbkPJesqkePHmzevHlswYIFzM7OjvM8sqy0tDTxfOjq6srWrl3LALDGjRvL/T3QqeSzoqOjWfPmzYsNb968OYuJieE8HxUVlfzU+PHjv1hc55O2li9fzlRVVTnPQVX+WrhwIROJRGzixIlMX1+f6evrs0mTJjGRSMQWL17MeT5pis/3meb7MvfkyRM2ZswYBkjei3n58uXszp07nOeTppydnVnt2rWLDVdVVWXOzs6c55NF8fk7K5X81ePHj9lvv/1WbPiKFSuYt7c35/lkUZmZmczf35/Nnz+f1a9fv8Rx1NTU2I0bNzjPWtZ6+/Yte/v2LcvNzWXv3r0T//vt27fs1atXzNPTk7Vv357znNKUSCRiZmZmDABLSEgQ//bQo0cP5uPjw3k+acvHx4c9ffpUXD4+PiwiIoJlZ2ezH3/8kfN8VFQ8K84DUFFRcVQpKSmscePGDACLiIhgbdq0YQCYgYEBS0hI4DwfFRVfKzAwkI0YMYKpqqqyqKgo1qNHDwaAmZubM5FIxHk+qupXcXFxbNCgQcWGDxo0iMXFxXGej4qKioqKSha1bt06lpaWxnJyclhOTg5LSUkp8cd/eavc3NwSd2jr6OiwtLQ0zvNRlV4DBgxg8fHxbOHChSwlJYXNmzeP/fvvvywjI4N99913nOeTpko70EJTU5NlZ2dzno+Kim81cOBAlpWVxfbv3y8+kNDV1ZVlZWWV+F1PHsvW1rZM43Xu3JkpKytznrc8dePGDaaurs55jsqouLg48QFbQUFBrHv37gwAMzQ0ZKmpqZznk7aWL18uUcuWLWPTpk1jLVq04DwbFRXfii45Tkg1Fh4eDh0dHYSFhSEoKAj29vZ49uwZ2rVrJ3GPMnlma2uLadOmwdDQECNGjEBERATGjh2LkJAQ3Lt3j+t45WJmZlbmcV+8eFGJSSpfu3bt0L17d2hra0MoFEo8Nm/ePI5Syc5ff/2Fw4cPIyUlBe/evcOtW7cA5F2KXN6nHZFP+/btg4uLC/7880+JWzQsXrwY+/bt4zgdIUSeNG7c+IuPh4WFfaMklWfYsGH43//+B319fSgrK0s8ZmVlxVEqUhaLFy/GmjVrYGJigvT0dLx580au70vJ18uUPn36FHZ2dkhISICPj88X7w8u78vcxYsX8cMPP2Dp0qVgjGH16tXw8fHBwIEDce3aNa7jVYiamhoEAgEEAgHU1NSQkZEhfkxBQQH9+vVDdHQ0hwkrJn95K4vt27dXYhJCSnbhwgUMHjwYS5cuxfDhw5Geng5fX1989913uHPnDtfxZOLu3btlGu/SpUuwtLRESEhIJSeSHT7fdunly5cwNzdHSEgIHj16hIULFyIrKwtTp07F27dvuY4nNT7fho+QqoZ2aBNSjZ05cwZ2dnZ4/Pgxtm7diqNHj8LBwQH6+vrYsmUL1/GkNnToUBw8eBCHDx9G27ZtUaNGDQB5X7CXLl2K/v37c5ywfJ4/fw7GGAQCgcSPOgKBAAAkhikqyu/qfcmSJfj9998RGBiIqKgoib6+9GOWPNm5cyceP36Mxo0b4+rVq+K+3r59i2XLlnGcjlRH8+fPx8ePHzFnzhzo6OgAACIjI7FhwwY4OTlxnI4QIk9CQ0O/uL2W588oQN4OjT/++AOurq4YNGgQ9u3bByMjI7Rr1w47duzgOh4pg9TUVHh7e3MdQybmzJkDIO/7gKOjI3Jzc8WPZWVlITQ0FI6OjlzFq7Bz586JD7A+d+4cb74DlObKlSsS95uWdwkJCWCMgTGG169fF3ucMYYVK1ZwkEw6+ctbPi0tLaiqqiIhIQEAoK6ujrS0NERHR9MObcIZDw8PeHh4cB2Dc/m/k8kToVCIiRMnws7OrsSTO+zs7DhKJr3ff/8dtWrVAgAsW7YMFy9ehJeXF2JjY/HDDz9wnE42hEIhBg8eDBMTEzDG4O/vj/Pnz+PTp09cRyOEVwTIO1WbEELQoUMHdO7cGUFBQbhw4QLXcaTm4+ODLVu24ODBg0hKSoKFhQVCQkJgYWEBT09P8U4beaGvry/+/zZt2mDTpk3YuHEjHjx4AADo1KkT5s2bh4ULF+LcuXNcxZTax48fsWjRIri6unIdhZRT06ZNERoaynUMmVNQUMCYMWNw+fJlREVFcR2n0qmpqQEAkpOTOU5CvkQoFMLW1ha+vr7iH1L5REFBAb/++itcXFwQHh7OdRxSDubm5hL/VlJSQps2bTB37lz8+uuvOHPmDEfJZCMgIACrVq3CsWPHJD5frlq1ChoaGuU6g49UPjc3N0ycOBHJyclwc3P74rjDhg37Rqlk78aNGxg6dCgvtwdE/nTt2hUCgQA3btzAsGHDEBcXJ34sKysL7969Q2RkJIcJpTdq1CjMmDEDDg4O4p32zZs3x549e7B7924cOXKE44SEVG+FP6PJi+3bt2PixIlwd3dHZGRksYO55s6dy1GyylGvXj3Ex8dzHUMmjIyM4OHhgUaNGiEwMBACgQDNmzdHWFgY+vfvz4uz0AmpKmiHNiGEt1JTU9GqVSu8e/dO4sOsgYEB/P39UbNmTa4jVtijR4+wcuVKXLp0SWJ43759sWbNGlhbW3OUTHoRERHo2rUrgoKCuI4iU05OTvjtt9+Qlpb21TNe5fWy6jk5Obhz5w6cnZ1x6tQp3ty6AMhbn5iYmOD9+/dcR6lU9evXR4sWLcAYQ2BgIGJjY7mOJLXg4GC0a9dO4sdUAKhbty58fHxgZGTEUTLppaenw8TEhJcHkgB5B1W0bt0a79694zoKkYF+/fphwYIF6NGjB9dRpFJ4exAVFYVevXrB19cXxsbGePjwIerXr891RKlpaWmVeGaQPN4WxcXFBb/88gtSUlLg4uLyxXEnT578jVKR8uDjdjwuLq7MZ51rampWcprKo6+vj7CwMF6eYR8UFIThw4fj+fPnEsPbtm2LU6dOwdDQkJtg5KtWrFiBffv28eZ7XWxsLJo3b47Y2NivrlvkeX1SXvK4Q1skEmH8+PHFfucjVZ+7uzsEAgHGjBkj3kmvoaGBQ4cO4dOnTxgwYADHCQnhD/m+3hshRGpjx46Fo6MjDAwM0KlTJ7x//x6zZs1CSEgIzp8/z3U8qURGRsLY2LjYD+G2trZyf3ScmZlZiR/MQ0JC0KpVKw4Syc6WLVvw008/Fbukm7xr06YNlJSUAOT90FHaF015/sHHwsICkydPhpOTE/7++28cP34czs7OePLkCdfRpPbo0SNYWlry5oePolRVVbF9+3aMHz9evAMjNzcXBw4cwMyZM5Gens5xwopr2rQpFBQUig2vUaMGGjVqxEEi2Xnx4gUMDQ15u0P72rVr6N69O2+u2FFddmCU5vXr12jXrh3XMaT28eNHaGpq4v3793j37h06duwIX19fGBgYyOXlLQtr27YtXF1dYWJiInFLm/zb3cjj5eIL76ReuXIlRCKRXG/TvqRRo0b4/vvvS7y3u7weLAl8eTuup6fHQSLpzZ49m+sI38T79+9Rt25dODg4SFyC1cXFBUlJSVzHk4qOjo74u11hCgoKaNCgAQeJpPe1+9UXJs/3rh84cCCWLVuG27dvw9nZGadPn5brA7HnzJkjvrJWdVm38FVWVhavTuz42pVxCpPnq+QAQLdu3dCxY0eJM87j4uKwePFi3Lt3j8NkhPCP/H0jJYTIjKOjI1avXo2//voLv/76q/iHgoSEBMyePVvud2jv3r0bW7duxeTJk8EYg66uLjp16oRNmzZh9erVXMeTSkBAAJYtWwYHBwfxly9lZWUsW7YMAQEBHKeTzqZNm+Du7o6goCD4+/sjOztb4nF5/aDbs2dP8f/L+9lppfHz8xNf9n7gwIGYOHEi7t69izdv3sDZ2RkHDx5ETEwM1zEr5J9//sHmzZvRuHFjPH36FKmpqRKPy+NZa4Vt3rwZ3bp1w8CBA8VfuGxtbbFt2zY4OTlhxowZHCcsv4EDB4r/v3fv3khMTBT/W0FBAXZ2dnK/I/jXX3/Fpk2b8Ntvv5U4X8r7ZeMvXbqEtWvXonXr1iX2J2+3Ryn8I6OmpiaWLVuGy5cvS9w6pHfv3lizZg1HCWUj/7YF+QQCAXR0dLBy5Uq8efOGo1Syc+PGDQwcOBDPnj2Ds7MztmzZguHDh8Pa2hqnT5/mOp5U9u3bh9evX8PBwQFRUVFyfZBdUQKBAG/evIGpqSmvfizO17NnT5w/fx4hISFo0aIFXr58iaZNm0IgEMDHx4freBVSlu24PJ15V9iBAwe4jvBNWFlZ4fLly0hPT8fjx48hEAjEt5+wt7fHs2fPuI5YYdevX8eePXvg4OCAp0+fAsjrd/fu3bh27RrH6Srm7Nmz4v9XUVHBjBkz4O/vL/6c0rFjR5iamuKff/7hKKFsWFtbw8zMDJMmTcKWLVuwY8cOHDt2DC4uLvD29uY6Xrnlr0/yf8+rLrfJ+hp5/Azj5OSEWbNm4eeff+Y6ikwU3m4LBAIMGTIEiYmJ4uXMysoK6urqcv/5GQAyMzOLfQcCgNq1ayMrK4uDRITwG6Oioqqe5efnxwYNGsQAsKSkJGZgYMAAMFNTUyYSiTjPJ4v6/fffWWpqKsvNzWW5ubksLS2NrV69mvNc0la7du3Yx48fWXR0NLt69Sq7evUqi46OZlFRUaxdu3ac55Om/v77b5aens48PDzYvn37mIuLi0RxnU/aUlBQYNnZ2czU1JTzLJVdysrKbPbs2Sw9PZ3l5uayjIwM5urqyho2bMh5tvJW/jqkcOXk5Ij/y3U+aUskErFu3boVG969e3cWHR3NeT5ppln+dCpcGRkZ7NWrV6x///6c55RFj/l95hdf5suSlrvC/XKdT5o6deoU++mnn4oN/+mnn9iZM2c4zyftdCs8P+bPk6Ghoaxjx46c55O2BAIBU1BQEP97xIgRbOvWrWzmzJlMSUmJ83zSVFJSEjMyMuI8R2XVy5cvWYcOHTjPURn16NEjtmrVKvF0NDAwYLVq1WJnz55ljo6OnOerSFWH7XjRUlFRYWpqahLFdSZp6s6dO8zFxUVinamgoMD27dvHbt++zXk+aap+/frM3d1dPD9mZGSwnJwc5u7uzrS0tDjPJ23t2bOnxN9NVq5cyZydnTnPJ6tSUFBggwcPZufOnWOZmZnM19eX/fLLL6xOnTqcZ6tIpaamMn19fc5zVGbp6+szFRWVr45X+DdOeanTp0+z+Ph4FhwczM6fP8/c3Nwkiut80tS6devYv//+y4RCoXiYUChku3btYhs2bOA8n7Tl6urKXrx4wdq3by8e1qFDB+br68v27dvHeT4qKj4V3UObkGosLS0NLVu2xPv37yXuL2NsbAxfX1+oqqpyHVEmatasiVatWkEoFMLf37/YGV7yqmbNmhg7dixatmwJgUAAf39/HDlyBGlpaVxHk0pSUhJGjhwJDw8PrqNUmqCgIAwdOhS+vr5cR6kUVlZWmDx5MkaOHInU1FS4urrC2dkZurq6WL16NdTU1NChQweuY5aLvr7+Fx+X90uRp6amwsrKCq9evZIY3qpVKzx+/Bi1a9fmKJn03r59i3bt2vHifuBFde3a9YuP37lz5xslIeWVnJwMS0tLBAcHSww3NjbGs2fPSjzCX14UnS8/ffoEkUiEoKAg5ObmcpTq29DV1UVERATXMSrszJkzOHjwIC/OlClJv379sHjxYkyfPh1+fn5cx5GppKQkWFpa4u3bt4iLi4OtrS38/f1hbm6Oc+fOwcDAgOuIFcbn7TiQd9uX9evX43//+1+Jt5uQx0v950tLS0ObNm0QGBgoMdzExATe3t6oVasWR8mkp6+vD5FIhEaNGolv0xAQEMCLK5EAeVfts7a2LnZFC2NjY3h7e0NdXZ2bYDKmpKSEIUOGYPLkyejZsyfu37+PBg0aQFdXFz/++CNOnDjBdcRyuXHjBrZu3Ypz585xHaVSCAQCZGRk8PZqKy4uLl98vPBtVORNdHQ0bG1t8fr1a4nhzZs3x/3791G/fn2OkslG3bp14erqioEDB4qvMqmoqIjz589j4sSJcn+bDUKqGs73qlNRUXFTfn5+7Pvvv2eA5NGLM2fOZN7e3pznoyq5FBUVWXBwMDMxMeE8S2VUaGgoa9GiBec5KrMmTpzI3N3dWb169TjPIsuaM2cO8/X1ZZmZmezMmTOsf//+TCAQSIxjZGTEsrOzOc9KJVnXrl1jx48fZzVq1BAPU1FRYcePH2dXr17lPB8VVeF5kw8VGhrK5s+fX2z4/PnzWWhoKOf5qMpXDRo0YNu2bWNpaWmcZ5GmNDU12cWLF9ny5cvZ0KFD2cCBAyWK63zSVlxcnPgsyrS0NBYbGytRXOeTpiIjI8XfDV6+fCmeXubm5iw5OZnzfFSl199//838/PzYsGHDWGpqKps4cSL79ddf2fv379no0aM5zydNffz4kfXq1avYcHt7e/bx40fO81W0BAIBy8zMZMbGxpxnqayKjIxkEydOLDZ84sSJcj3t8qtt27Zs+/btLCYmhn348IGtXbtW4golc+fOlcs+hw8fzoKCgthPP/3EOnbsyMzMzCSK63yyKD5fbYXPFRcXJ75CaOEaNGgQi4uL4zyfrMrY2JgNGDCADRw4kNdXPaKi4rLk91BPQojUNm7ciB07dkBFRQUCgQDt27fHqFGjsGTJEkyZMoXreBXi5uZW5nHl9V7MOTk5qFGjhlzeE6gsVq5ciVWrVmHSpElIT0/nOk6l+OWXX2BsbIyIiAi8e/eu2FUDrKysOEomnenTp8PFxQX79u0r9b5d79+/h4ODwzdOJhtjx46Fo6MjDAwM0KlTJ7x//x6zZs1CSEgIzp8/z3U8qcyaNQuenp4IDw/Hf//9B8YYLC0tkZGRgd69e3MdT2o9e/aEnZ0dtLW1IRQKJR6T1/kxn62tLaZNmwZDQ0OMGDECERERGDt2LEJCQsT3Q5dXQqEQS5cuhaOjIxo0aIDmzZsjJCQEq1evRmho6FfPYqjKVqxYAWdnZ3Tv3l3i3pR9+vSR289ghRkaGmL27NkwMTEBYwwBAQHYunUr3r59y3W0Cqtbty527NgBe3t7ZGdnY926dfj777+xcuVKzJ8/H35+fnJ95gwAdO7cGba2tujbt2+xxxhjcn2mKADMmTOHt5+fHz58CBsbGwQEBMDd3R1OTk4wMzPD0KFD8fDhQ67jSY3P2/GBAwdi/PjxuH37NlxcXODl5YXg4GC8e/cOY8aMwZEjR7iOWG7jxo3D8ePHcfz4cTg7O2P+/Pm4f/8+GGOwtbXFxo0bcfToUa5jVhhjDG/evIGmpiYvzxIFgL/++gs7d+6ElZWVeB3SsWNHTJ48GatXr+Y4nXT+++8/mJiY4MqVK3BwcMCFCxfw6dMniXEOHDiAjRs3cpSw4o4fPw4A2LZtm3gYYwwCgYAX23EAWLhwITZu3MjLq63kq1+/Plq0aAHGGF6/fo2YmBiuI0lt3759cHFxwZ9//imxTlm8eDH27dvHcTrZCQoK4u12gZCqgi45Tkg1N2XKFCxbtgyNGzcGAHz48AErV66U2x+Jy5Nbnn90XLRoEVq2bIkpU6bw7vKdPj4+MDIygkAgQGhoqPhyPfnkdWdvYcuXL//i4/L4I4GCggKWLVsGZ2dnhIeHcx1H5hwdHbF69Wr89ddf+PXXX9G6dWuEhIRgwoQJmDBhAnr27Ml1RKmpqKgUu43B4cOHkZGRwXU0qSxfvhzLly+Ht7c3IiMji+3MGDp0KEfJpDd06FAcPHgQhw8fxrhx49CqVSuEhIRg+vTpGDBgAPr37891RKn89ttvmDBhApYvX449e/aIl7sRI0Zgzpw56Ny5M9cRpdK+fXv88ssv4kuV+vv7Y9u2bXj8+DHX0aRib2+P8+fP4/nz57h37x4EAgE6d+4MCwsLDBw4ENeuXeM6YoXs2LEDAwcOxPHjx9GnTx+YmJjg8uXLUFFRwapVq3hxif+QkBBcvHgRa9asQXR0NNdxZE5ZWRmKiopyf3uekhgYGKB27dp48eIFatasiU2bNsHW1hZBQUGYM2eOXN8ahc/bcSDvFhSmpqZ4//49wsLCMHToUDx58gRNmzbFixcv5PIWFDk5OdDR0UFCQgI2btwIR0dH8Y607Oxs7Ny5E4sXL0ZWVhbHSSuOz7cwyDdixAjMmjULJiYmACA+OO3kyZMcJ5POsmXL4OLiIte3CCkN32+TBQBxcXFQVVWFoqIisrKyip0EUdKtG+SFqqoqtm/fjvHjx4sP3srNzcWBAwcwc+ZMuT7hQyAQYP78+Zg1axZ0dHQAAJGRkdi6dSucnJyKHVQib4RCISZOnFjqwXd2dnYcJSOEf2iHNiHVlIKCAsaMGYPLly8jKioKmpqaEAqFEIlEXEcjZXD69GnY2dkhJSUFL168KHaGr7yefQ7wc2dvRY0cORLnz5+Xmx9ek5KSYGZmhnfv3nEdReb8/PywdOlSnDt3DklJSbCwsEBISAhMTU1x69YtaGlpcR2RlCIiIgILFy7EoUOHuI4icz4+PtiyZQsOHjwoMV9aWFjA09NT/GOBvHrz5g2mTZuGGzduSPTXokULPHjwABoaGlxHJCXw8fHB5cuXsWTJEonha9euhb29vdwemBYaGgoHBwdcv34dBgYGCAoKwrZt2zBnzhyuo8lM4fsw84mmpiZcXV1hb28PoVCIR48eia9kQao+Pm/HgbyzRWfOnIk7d+7g8uXL8PX1xYIFCzBz5kwsXLhQfOC5PMnNzUXDhg3Fvy3UrFlTfMByUFCQXO+UycfnnWoKCgr49ddf4eLiwrsDlRUVFREYGIgBAwYgICCA6zgyVbt2bXTs2BFKSkp4/PgxYmNjuY5UKcaPH//Fxw8cOPCNksjerl278N133+Hnn38WX2nL1tYW27Ztw9WrVzFjxgyOE8pG/oFaycnJxR7r3LkzvL295e6Ap+3bt2PixIlwd3cv8eC7uXPncpSMEP6hHdqEVGOpqakwMTHhxVGa1c3XzkSX57PPSYHExERYWlrKzQ+uZ86cwdmzZ+Hq6sp1FJlLS0tDy5Yt8f79e4kda8bGxvD19YWqqirXEaWyePFiREVFFbvc16RJk6ClpYUNGzZwlEx6MTExaN++Pe920AB52/FWrVrh3bt3EvOlgYEB/P39UbNmTa4jSqW05c7ExASPHz+Wy7PWChMKhRg8eLD4stz+/v44f/683J+hkJ6eDjMzs2KX22vWrBl8fX3ldr7MyspCkyZNEBkZCSBv+Wvfvj2vzszbv38/vLy84OzszHUUmfr3338xcOBAbNu2DRkZGXB0dMS7d+9gb2/PdbRKN2TIEKxcuRIWFhZcR6kwPm/HAWD27NnIzc3F9u3b0b17d7i7u0NBQQGKioqYO3euxKWD5UVubi4aNGjAi8vklobPO9WAvB1NrVu35uWByuHh4fjuu+/w6tUrrqPIjJmZGS5duoSGDRtCIBAgKSkJw4cPx/Xr17mORspBJBJh+PDhuH37tsTw7t2748SJE9DW1uYo2bcjb7+B5ROJRBg/fjwuXbrEdRRCeE/+b55BCKmwR48eoU2bNrzdof327dsv3ifPyMjoG6aRreqww7pt27YSP/I/f/6c60jfnEAg4DpCuVy6dAlr165F69at8fTp02JXDrhw4QJHyaQXEhICS0vLYuvLvn37wt/fn6NUsjNt2jSMHj262HA/Pz8cO3ZMrndo7927F6NHj8bvv//OdRSZi4yMhLGxcbEfG21tbXnxw7+fnx+6dOmCw4cPSwwfMWIEnj17xlEq2TAyMoKHhwcaNWqEwMBACAQCNG/eHGFhYejfv79cTz+RSARLS8tiO7QtLS3l+jLWQqFQ4jYoubm5xbZz8u7169dYu3YtbG1t8eLFi2K3fdm+fTtHyaTTu3dvTJ48Wfwjo4eHB16+fAlFRUXk5ORwnE56U6ZMEd/bfevWrXj8+DF69OgBJycntGjRAgcPHuQ6olT4vB0H8u5VnO/WrVto2bIlrK2tERwcDF9fX+6CSWn//v3IzMz84jjyfFUxed9h/TXXrl1D9+7deXmg8vbt27Fo0SJe3b5t3bp1eP/+PUaMGIGMjAysWLECf//9t/hy8XxjaGiISZMmwcjICLNmzYJIJELv3r0RFhYm19/NVVVVERUVVWx4dHS03B9AX1by9htYvqysLLp3NiHfCO3QJqQa++eff+Dk5AQ9Pb0Sdz69ePGCo2SyUfjHAQBQUlJCmzZt0KdPH2zcuJGbUDJWv359tGjRAowxvH79mhdHwWtpaeHYsWPo3r07EhISIBAIULduXdy8eRMjR47kRY98tXPnTgAlX06JMSa+d5482rhxI3bs2AEVFRUIBAK0b98eo0aNwpIlSzBlyhSu40mtYcOG4rMOCxOJRHJ/2WoVFRVMnToV3333HXx9fYvtoJk3bx5HyaS3e/dubN26FZMnTwZjDLq6uujUqRM2bdrEi9szrFq1CgcPHkSjRo0gFAoxdOhQtGjRAuPHj8eAAQO4jieVbdu2ITg4GB07dkR8fDwAQENDA4cOHcK2bdvkur89e/bg33//haGhIe7fvw/GGGxtbbFo0SI4OTlxHa/CBAKBxA4aFRUV7Nq1i1e3fZkyZQpSUlLQrVs3dOvWTeIxxpjc7tDW1dWVOAgmMDAQWVlZ0NXVlfsDe+fNm4c///wTvr6+MDExwaBBg/DHH39g7ty52L59O3bs2CH3l53l63a8ffv20NDQgKenp3jYuHHjsGrVKtSqVQtnz57FzJkz5e6yq/mSk5N5cWnx0ujq6mLYsGFo3ry5+Lv46dOneXNfZj4fqNyhQwfY2dnB3t6eN7dvs7a2Rr9+/fD06VMAeSdAREdHo1atWrw7+K5r1664dOkS7t27h65du+LXX3+FSCSCubk5pkyZghEjRnAdscIePHiAVatWYfz48RKfN1esWIEHDx5wnI58iZOTE2bNmoWff/6Z6yiE8B5dcpyQaqyko1EZYxAIBHK/8+lLZsyYAWtra7k+y1lVVRXbt2/H+PHjIRQKAeRNzwMHDmDmzJly/ePBsWPHYGRkhHHjxokvA2ZiYgJXV1cEBQWVeBYpXxW+xC7h3pQpU7Bs2TLxvQw/fPiAlStXfvUWAPLg9evXWLVqVbEzYceOHYtVq1bJ9RUtbty4UepjjDHY2dl9wzSy9/vvv2POnDlQUVEBAGRmZmLTpk1Yvnw5x8lkw97eHkuXLoWVlRWEQiF8fHywevVqXL16letoUklJSUHHjh3x8uVLieHm5ua4d++e3F9Offbs2Zg3bx50dXUB5N0Dd+PGjXJ56dx8ZV3Xy/PnS77KyclBw4YNJQ6KTExMhIWFBUJDQ7kLJgP+/v7YuHEj9u3bh27duuHGjRu4ceMGhg8fjsTERK7jyQRft+MeHh64deuW+Co4rVu3ho+PD/bv3w9/f38sXLgQu3fvxqpVqzhOWn5F76HNN9OnT8fmzZuhrKyMxMRECAQC1KlTB1lZWZg7d674IF959qUzl+X9tyI+3r6tpGUuKSkJ5ubmcr+dK+r+/fs4efIktmzZIvF7ibW1Nc6ePQs9PT2uI1aYqakpPD09oaKigv/++w+MMVhaWiIjIwO9e/eW67PPy0qefgNzc3OT+HfPnj0RFxcHPz+/YgffyeOBMoRUVbRDm5BqTF9f/4uPy/sZC6UxMDDA8+fPUbduXa6jVNiuXbvw3Xff4eeff8a9e/cA5F1idtu2bbh69SpmzJjBccKKS0hIwHfffQdvb2+J4e3atcOVK1dQr149jpJ9e/L0Yb460dTUhFAo5NWPdAsXLsSCBQuwYMEC8Q/HdnZ22LBhA5ycnLBu3TqOE5IvqVmzJlq1agWhUAh/f3/enYnBR7GxsRgwYECxsy06d+6MCxcuQFNTk6NkslW7dm0AeTvwifxQUlKCgYEBgoODeXE51tzcXLx8+VLi8uLm5uZ49eqVxNmvVlZWXMSTSmpqKlq2bImwsDAAQEZGBrp27YrHjx9znIx8TUREBAYOHCg+o/L3339Ht27d0KVLFwDA8OHDsWrVKpiamnIZs0JycnKgo6PDq8/K+fr164dz587hr7/+gpOTEz5+/Agg72pHCxYswMyZMzFo0CC6jyr5pnJyctC8eXPxMicQCBAWFgZbW1uJHdrJyckcJZSd5ORkmJmZITQ0VOL3kiZNmuDVq1eoWbMm1xGloqKigrFjx6Jly5YQCATw9/fH4cOHkZGRwXW0b0KefgMrz4kN8nigDCFVlfweUkcIkRpfd1h/zfDhwxEXF8d1DKkMGzYMw4cPx+3bt8XDLl26hB9//BEnTpyQ6x3aRe9RmS87O1t8Njqpurp27Yr58+eL738eEBCAjRs34u7du1xHkxl5v3RnSTZs2AANDQ38888/UFZWBpD3o/j69et5szPbyMgIRkZGuHPnDu9+EEhPTxf/IE7kw8WLF/Hvv//CwcFBvOOpQ4cO2LVrF86fP89xOuk0bdoUioqKCAoKktiRbWxsjOzs7GL3fCdVR82aNbF9+3ZMmDABANC8eXOEhIRg69atiIiIwPr16zlOWDElneF67tw5DpLInoqKisQ2LSsri5c7EfmoXr16EvdK7datm8Tlx588eSK+KpC8kdd7oJbFwoULsW7dOvz2228Swz9+/Ih58+YhLS0NixYtoh3acoBPt28TCAR4/fp1sWH5t9vg01UYExISoKOjU+zM8zZt2uDDhw/chJKhjIwM7N27l+sYnGFMfs67rMhO6s6dO8Pb21tubydCSFUg/1syQki5dOzYEQ8fPizTuKqqqmjatKncXtbGx8dH4sOQQCBAw4YNoaWlJdc7fIG8aVP4B5B80dHRUFVV5SCR7Ny4cQNbt27FqFGjxPf01dXVxZYtW3D9+nWO031b7969K3HnflU1ZswY7Nu3D6dPn8a2bdsgEAjQuXNnXL9+HRMnTsTRo0e5jlhhGhoaWL16NXr06AFtbe1iB1fw4WzKxYsXY82aNTAxMUF6ejrevHnDiy9aGhoaOHHiBHr06AHGGJo1a4aQkBDs3bsXCQkJmD9/PtcRK6xGjRqYOXNmqfOlPJ5tGBcXV+YfMuR5ufvll1/g6uqKBw8eiNfzioqKOH/+PGbNmsVxOuns378fLi4uCAoKkhjeoUMHTJkyBT169OAoGfmatWvXwsLCAt27d5fYsXbt2jWsWrVKbndor169musIlSr/3udA3npk4sSJxXbMyOv9z/NZW1tjxIgR0NfXFx94l09eL+MZFRUFAwMDhIeHQ0lJCW3btsWKFSvEj6upqcnV94DCevToIfcHkJemTZs2mDp1aqmPHzx4UO634/lUVVXRrVu3Epc7eV6n8PH2bdXps9WRI0ewfv16jBgxAowxCIVCdO7cGZs2bcKBAwe4jic1XV1d2NjYlPjdTp6XO319fURHR3/1wHI+HxAF5J2IZGlpKRdnoBNSVdElxwmpZl6/fo3Q0FDs2bMHHh4eJV6W1MTEBGPHjsWkSZOwcOFCHDp0iIOk0it6/9BPnz5BJBLh1q1bCAwM5CiVbFy7dg2xsbEYP348MjMzAeSdoeHq6goNDQ306tWL44QVp6enh3PnzqF169YICwsDYwz6+vp48eIFBg0axIujbvft2wcXFxd4eXlxHUWm/P398e+//+Kvv/6SGD5nzhz8+OOPaNWqFTfBZMDDwwNGRkZwdnZGVFRUsR1ufPjynE9PTw+MMV4sawDg6uoKbW1tTJkyBQEBAeJLmPXq1QtbtmxB69atuY5YYYcPH0avXr1w6tSpEudLedyJM378ePH/a2pqYtmyZbh8+bL40tydOnVC7969sWbNmmLrGnmir68PkUgEXV1dmJiYiC8pGBwczHU0qSUmJqJt27bFejEyMoK3t3e1unWIvAkNDcUPP/yAR48eSVzy0cjICD4+PnJ9ux6+CgkJ+epBQIwxGBkZfaNEsvfDDz/gwIEDuHLlCnr16oUrV66gWbNmaNiwIc6cOSO3l/HctWsXzMzMsGjRIgwePBgTJkyArq6ueCf26NGjMXv2bLRv357jpKSw5ORkmJubl7ozwsDAAL6+vlBTU/vGyWTL0tISHh4eUFVVRa1atRAXF4f69esjLS0N0dHRcr1O4fPt26oDRUVF7N+/HyNHjoRAIEBOTg4UFBRw5MgRTJw4EZ8+feI6YoVNnDgRu3btQlZWFmJjYyW27/K8LRcIBMjIyICpqWmxA16rG3m6pDohVRmjoqKqPqWoqMh++uknFhAQwLKystjLly/ZlStX2Pnz55mXlxcTiUQsLS2NHTp0iJmamnKel6rkMjU1ZWFhYUwkErFr166xq1evMpFIxMLCwlirVq04zyeL+u6779jPP//MZs6cyezs7DjPI8s6deoUS09PZ69fv2ZLlixhurq6nGeSRWVkZDAjI6Niw42MjFh6ejrn+aSppKQkZm5uznmOyioFBQW2evVqlpCQwHJyclhOTg5LSEhga9asYYqKipznk6YiIyPF0y4pKYkZGBgwAKxp06YsOTmZ83zSVEJCAuvcuTPnOSqrTp06xX766adiw3/66Sd25swZzvNVtAQCAcvMzGTGxsacZ6mMSkhIYJaWlsWGt23bliUlJXGej6r0Sk1NFa8jC68vzc3NWUJCAuf5qKpn/ffff2zGjBkMkJwvd+/ezVauXMl5vopW/fr12Z07d1hubi5LTExkgwcPlnj82rVr7Pfff+c8J5VkPXz4kM2ePbvUx+fMmcMePnzIeU5p6+bNm2z37t1MKBSKlzs9PT1269YtNmTIEM7zSVMikYh169at2PDu3buz6OhozvNRla0MDQ3ZsGHD2IgRI3jzmfr9+/ds6dKlTCAQcJ5F1vXy5UvWoUMHznNwXYU/x1BRUVW4OA9ARUXFUbVp04b98ssvbPPmzWznzp1szZo1bOjQoaxevXqcZ6toqamplbm4ziptqaiosClTprBNmzYxJycn5uDgwFRUVDjPJW2NGzeOKSsrFxuupKTExo0bx3k+WZWGhgb75ZdfmI+PD8vKymIeHh5s2LBhcr3z8M2bN2zq1KnFhk+dOpW9fv2a83zS1OPHj3n9BWznzp3s48ePbOrUqczMzIyZmZmxqVOnsoiICLZz507O80lTSUlJ4h85Cn+BtLa2ZjExMZznk6b8/PyYmZkZ5zkqq5KTk0s8SMbY2FjuD0bg8486Fy5cYMePH2dCoVA8TCgUspMnTzIPDw/O80lbXbp0YQoKCsWGKygosC5dunCeT5q6desW+/nnnxmQt75s2rQpA8C2b9/OLl26xHk+qupZKSkprEmTJgzI2xHVunVrBoC1bNmSRUREcJ5P2qpTp47E+jK/6tWrx5SUlDjPRyVZ48ePZ6mpqWz69OkS2wIFBQU2Y8YMlpqayiZMmMB5TmkrPj6eNW/eXPz/LVu2ZABY+/btWUBAAOf5pKnU1FRxP4WrVatWLCUlhfN8VNW3YmJimKGhIec5KqP69evH7ty5U+1PnKId2lRUMinOA1BRUVHJrHJzc8VnF36tuM5KVXLl5OQwLS2tYsM1NDR4O90sLS3Ztm3bWFpaGouOjmabN2+Wy6OMHR0dWUZGBvvnn3/Y2LFj2ZgxY9jOnTtZenp6iTu65amsra3ZtWvXWNeuXZmGhgbvDpBJSEhgffr0KTa8T58+cn9W3sWLF9nq1asZULCDRiAQsOPHj7OTJ09ynk+a6tOnD/Pw8GD6+vqcZ6mMCg0NZfPnzy82fP78+Sw0NJTzfNIUn3/UMTExYSKRiL1584a5uLgwFxcX9ubNGxYVFcWLfvn8OaVTp04sMTGR/fPPPywtLY1t2bKFXblyhSUnJ7O2bdtyno+qetb79+/FO7GfP3/ORo4cyQCwjh07yv1nFCr5rI0bN7Lc3FyWkJDAnj59yp4+fSq+ytHmzZs5zyeLio6OZs2aNWMA2KtXr5i9vT0DwFq0aMFSU1M5zydNXbt2jR0/fpzVqFFDPExFRYUdP36cXb16lfN8VMXLycmpzMV1Vmlq/fr1bNGiRZznqIyKi4tjGRkZLCcnh6WlpbHY2FiJ4jrftyraoU1FJX0pghBCeKRHjx7i/2/atCnWrVuH/fv3S9x7c8KECViyZAlXEclXCASCEu8FqKenh8TERA4SVa6GDRvC3t4e9vb2yM3NhYeHB0xNTeHv74+FCxfK1T1id+3ahY8fP2LevHn43//+BwAICAjADz/8gPPnz3OcTjoJCQmoW7cubty4ITE8f35VVJTvj1QZGRkIDQ0tNjw0NBRZWVnfPpAMLViwALdu3YK1tTWUlZWxYcMGmJqaQkNDAzY2NlzHk4q3tzdUVFTw9u1bpKWlie+7mU9TU5OjZLKxYsUKODs7o3v37uLteMeOHdGnTx9MmTKF43TSOXToEFRVVfHff/8hKysL6enpEo/L87QLCAiAubk5fv75Z1hYWCA9PR0HDhzA33//jfj4eK7jSa20zymamppITU3lIJHsPHjwADY2Npg/fz6Cg4Nhb28PHx8fdOrUCS9fvuQ6ntTGjRuH48ePF9uuKSkpYeTIkTh48CBHyciXeHl5oVevXnj58iVOnDiBrVu3omfPnujVqxeuX7/OdTxSBlpaWtDW1oZQKJQY/uLFC44SSWfBggU4deoURo0ahWbNmgEA7ty5g2PHjuHRo0ccp5ONZ8+ewdraGm/evMHNmzexevVq1K9fH+PGjZPb6ZZv1qxZ8PT0RHh4OP777z8wxmBpaYmMjAz07t2b63ikBG3atJH4t5WVFRQUFBAYGAgAaN68OXJzc/H06VMu4snMkiVLcPHiRfTp0wcvXrwo9t1u3rx5HCWT3uzZs7mOUCWU9B2CEFI+AuTt2SaEEN65du0a9u7di2PHjkkMHzVqFKZOnSqx85twz8fHB4wxWFhYwM/PDzk5OeLHFBQUYGBgAE9PT/zwww8cppQNRUVFfP/995g0aRLs7e3h6+uLvXv34vDhw0hJSQEA/PDDD9i5cyc0NDQ4TksA4NGjR8jJycHWrVsRFRVV7IvInTt3OEomG7/99htatmyJSZMmiX/oV1ZWhrOzM968eYPVq1dznFA6DRo0wPTp02FlZQWhUAgfHx/s2LEDHz9+5DqaVK5evQp9fX04OzuXOF8eOHCAo2Sy0759e/zyyy8wMTGBQCCAv78/tm3bhsePH3MdTSrjx4//4uN8mHZ84+bmBgAYNGgQPD09kZmZKX5MQUEB5ubmCAwMRN++fbmKSL4iJycHOjo6EIlEEsM1NDQQHR0t9wen8VW9evWgoqKCyMhICAQCzJ8/H7a2tggKCsKaNWuQkJDAdURSirZt28LV1VW8DQfyfsznywGhfGZlZQU1NTXcunUL9evXh6urq3i5mzRpEnx9fbmOKBUVFRWMHTsWLVu2FH++PHz4MDIyMriOJhVnZ2fMmjVL/JtCPlVVVWzfvh0ODg4cJZOdOXPmoHv37pgwYYJ4/a+uro59+/bBy8sLmzdv5jagFJYtW4ZVq1YhMDCw2Hc7xhjs7Ow4TEe+RF9fH9HR0V9dhyQlJcHCwgIhISHfKBkh/EM7tAkhvJWamgoLCwsEBQVJDG/WrBmeP3+OWrVqcZSMlGT58uUA8s7Ic3JykvgSlpWVhdDQULi5uRU7SlUeiUQiCIVCHD16FHv27MF///1XbBx1dXX4+PjA0NCQg4SkqNTUVLRp0wavX7/mOkqlOH36NOzs7JCZmSmeHy0sLKCsrFzs7Kdhw4ZxEZGUIDU1FZ06dZL7HxVLoqioiH///Rdr1qyhL/xypnfv3khJScG9e/cAADNmzMCPP/4If39//PTTT3K788nFxQUAMGHCBJw4cULirPr8zyl79uxBbGwsVxGlxvcdvrm5uWjQoAFiYmIkhpubm+PmzZtyfWUEQqqi//77D0FBQVi/fn2JB969f/+eo2SE8FNp23FNTU18/PgRSkpKHCWTnfDwcNjb28Pf319iuKmpKa5cuYJGjRpxlEx6cXFxmDNnDlxdXbmOUikMDQ0xadIkGBkZYdasWRCJROjduzfCwsKKTU95IhAIkJGRAVNT02K/PxNCZE++v5ESQsgXhIWFwdHREfPnz5cYPm3aNISFhXGUSnpCoRC2trbw9fWV2x+FS5J/BmhoaCiOHTsm95c5/pK5c//P3tnH1Xz///9xzilkIpqwFF0oUXSBEcKoDG1IszHVyMXQlFxTyDYz1zIMNdefmeuZuY5ltKFcJFddnK5cVLq+rnP2/P3h2/k5O9XSOXk5p9f9drvfdF7v/rh3Ozmd836936/XbPzyyy9yd3f9m9zcXLWbzM7Ozq5yCSUiQmlpKeLj47Fr1y7s2rXrzccpyc2bN2FkZKSxE9q5ubmyuw8rUefXyX/TuHFjdOvWrcrlLk+ePMmoSnkePnwIHR0d1hn1gkQiwahRo7BixQrWKfWGUCjEqFGjYGVlBSLCgwcPcOLECUilUtZpSrF69WrMnz8fAGBtbY1169Zh7dq1+OCDD7Bu3TpMnDiRcWHdqOxOSkrCmjVrUFxczLhI9VTeQflvGjdurNbvyypXASIiXLx4sdpVgNQZTb4YwcjIqMbjmvR+RdMwMTHB6NGjkZCQwDqFU0uaNGkCZ2dnXLp0SeEuX11dXQwcOBBnz55V678Jbm5uVY6/+pm1qq2Y3mZ0dXUhEAggEAigq6srd5eoSCTCsGHDkJGRwbBQdTRv3hxt2rRRmAA1MDCArq4uoyrVUFZWJrsgVNNwcnLC6dOncfXqVTg5OWHx4sXIzMxEt27d4OPjAw8PD9aJdYaIEBcXB319fT6hzeG8IZhv5M3lcrn14YcffkjFxcUUExNDO3bsoB07dlBMTAwVFxfThx9+yLxPGUtKSqhjx47MO+rD9u3bk6Ghoexxz549af369TR58mTmbapQJBJRRUUFde3alXmLqvXz86PMzEzas2cPzZw5k3x9fWnPnj2UkZFBCxcupO3bt1NJSQn5+Pgwb31dx4wZQ/fu3SMvLy+yt7cnGxsbOVn3cavX1dWV0tPTSSqVKiiRSJj3KaOzszP9+eefNGDAAGrVqhXp6urKybpPWcPCwsjf3595R33YtWtXio+Pp8LCQoqKiqKoqCgqKCigxMREsra2Zt6njAUFBdShQwcCQEuXLqVDhw4RALKzs6Nnz54x7+Mq6uvrS76+viSRSGjhwoWyx76+vuTn50dHjx6l6Oho5p11NSgoiIKCgkgqldL3338vexwUFEQLFiygTz/9lLS1tZl3KqNUKqXWrVsrjLdr146Ki4uZ9yn7s0kkkmpl3cet3mPHjtHo0aOZd3Br71dffUUXLlyo9vj58+dp+vTpzDuVsfI1parPBZX/Xr58mfT09Ji3vu7PVJ0VFRW0aNEi5p2qcPfu3ZSUlETu7u5kaGhIhoaG5O7uTomJibRr1y7mfcq4YMEC2rhxI/OO+vDatWuyz3X5+flkYmJCAKhHjx6UlpbGvE9Zhw0bRhERERp5no/LfdvkS45zOA0YX1/fKsdfvTI1IiIC//zzzxsuUx3t27fHl19+Kbc30rZt25CWlsY6TSmuX7+OBQsWIDw8nHWKyomIiMD27duxb98+tGnTBo8fP8a9e/dgYWGBTZs2acTdevHx8Rg9erTGLRN8+PBhnD9/Hj/++KPc+JQpU+Di4oIxY8Zg5syZmDJlCrp168aosm5Udcck3wNQPYiLi8PZs2cRHBysMXcmVFL5e/nvlRE05fdy0aJFmDNnDi5evIioqCgUFRXJHQ8JCWFUpjyRkZHIyMhQ2P9v165dMDAwgKOjI9tAJcjKykK/fv3w4MEDXLlyBXv27MGOHTvQoUMH3L9/X+23fDEwMMCaNWswePBgGBgYKNzVrI7/7xITEwEAHTp0QFpamtzfvMrl1IOCgjRi73pNWwWo8vPc+vXrERgYKHdHpUgkgpOTEzp27Ah7e3tWiUrz7/eM2trasLOzw+zZs7F48WIcO3aMURnnv9DX18fu3btx/fp13Lt3T2HrKHVeJae2+6WqG3///TdWrFiB3377rcrjw4cPR1BQEN5///03XKY6PvjgA3zzzTdYvHix7O9ar1698PXXX2PFihXIy8vDjz/+iL///hs+Pj6Ma2uHk5MTBAIBwsPD4e7ujuzsbNmx8vJyJCcn49mzZwwLVYeOjg7WrFmDiRMnypZQl0gkCA0Nxdy5c9V6BZ2jR4/igw8+QFZWFmJjYxVeM9V566+CggLY2NggKSlJbh/pDh06aMSqY9nZ2WjatCm0tLRQXl4utzURAL6tDYejQviENofTgElMTETr1q3RtGlT5OTkQCAQQE9PD8XFxSgsLISBgQESExMxaNAgtZ8A1jScnZ2xatUqBAYGVnmSv6CggFGZ8mRnZ6N37954/PgxfH19MXbsWPTr1w/Ozs7Ytm0bzMzMWCcqjbe3Nzw8PPD5558jJyeHdY7KKCgogK2trcKygmZmZrh9+zZ0dXVhamqKu3fvolmzZowq64axsXGNx9VxD8CoqCgMHjwYubm5suVYq8PBweENlqmWvLw82NnZySZsNAknJ6caj0dERLyhkvqhpueMiNT670FxcTF69OhR5f5/N27cQNOmTRmVKc+JEyfQqFEjXL16FYGBgTAxMcHTp0/h7OyMzZs3w9LSknWiUvz+++8wNjbG5s2b8ezZM4XXzl9//ZVRmfKEh4dj9OjRGrWlzav06NEDQqFQYWK+V69ekEqliIqKYlRWdxrKxQhVMWzYMMydOxeDBg1incKpBjc3N+zdu7fKZYDV+cI7Td4vNTs7G927d692KX8jIyPcuXMHrVq1esNlqiMmJgZTpkxBZGSk3LijoyO2b98Oa2trDB48GGFhYejQoQOjyrphbGyslp9La0vl9nsxMTEoKyuDmZkZBAIB4uPj1Xoiu5KwsLAaj6vrtj3Ay+1BPvnkE0RGRspNaI8cORJr1qyBubk560Sl8PT0rPH4nj173lAJh9MwYH6bOJfLZeOnn35K4eHhZGpqKhszMzOjCxcu0CeffEKGhoZ05coV2VKR6mi/fv1o7969dPXqVXrvvfcIAH3++efUt29f5m3K+O+lsSrVhCV0X12q9MSJEzRv3jwCQEZGRmq/ZGKl0dHRlJ+fTyUlJfTw4UPZcrOVsu6rq8nJyeTn56cw7ufnR8nJyQSAbGxs+JKzb4lBQUGko6Mj+7omWbcqY2hoKE2cOJF5B5f7qrdu3aJBgwYpjA8aNIju3r3LvE8ZjYyM6OTJk3T79m25/3vr1q3TiGUU8/PzqXv37sw7uK/v33//Te7u7grjo0aNor/++ot5nzKGh4er1fK4qtDc3JwKCwuZd3CrVywWU0hICBkYGDBvUbX37t2j999/n3mHqs3Pzyd7e/tqj9vb21N+fj7zTmUsLi6ucllga2tr2fkGY2NjKioqYt76unp7e9OYMWMUxseMGUOenp7M+1ShJm+/V1sdHR2pUaNGzDtex1WrVlFERAS1adOG8vLyyMzMjBwdHSk+Pl7tzzdwudw3q3peDsnhcFTC119/DXd3d7k7oBISEjBnzhwcOXIEZmZmmDdvHo4cOcKwsu6MHj0ae/fuxf79+2Fvb4/GjRsDAHR1dbFo0SIMHz6ccWHd0eQ7EWJjYzFt2jScOnUKzs7OCAwMBAC89957yMrKYlynGo4fP846oV5YsWIFtm7dikGDBuH69esgIvTq1QvDhg3DtGnTALxcXeCPP/5gXFo3TE1N4efnBysrKxARHjx4gI0bN6rtnb/BwcFVfq1pzJw5E4cOHUL//v0RExOjsHSbOi9bDQAtWrTApEmTZL+X9+/fR1hYGPLz81mnqQx9fX0QkdzyierOokWLsGnTJixbtgx//fUXAKB3794ICgrC/Pnz5e5mU7dVV1JTU+Hm5qYwPnv2bAY1qic1NVVhmXF1Z+3atbX6voCAgHouqTmR2HEAAJujSURBVF+6dOmC6OhohfFbt26hS5cuDIpUxwcffMA6od749929AoEA7dq1w7JlyxAXF8eoilMb9PX1sX79eo3b8gUA5s2bh9WrV+PLL79EbGws6xyVERsbiyFDhlT5Wgm8/Cyn7j9vVFQUVq9eDU9PT7x48QIA8O677+L777/HjRs3AACdOnVSy1UKFyxYIPvc/SoZGRnYvn27RtwlGhMTA1NTUyQlJbFOYcbp06dha2sLsVjMOqXWLF68GLt27cKTJ09k20GKRCIcOHAAX3/9Nes8lWBqaoovvvgCZmZmmDVrFjIzM+Hq6orU1FSFVbk4HI5yMJ9V53K5bCwqKiIHBweF8R49esiuRu3QoQMVFBQwb62L0dHRNGHCBAJeXmlsYmJCAKh79+78DtG32AEDBlB2djZJJBIKDQ2VjX/zzTd05MgR5n3cmnV0dKQDBw5QVFQURUdH04EDB6hPnz7Mu5TVxcWFSktL6a+//qK1a9fSunXr6K+//qKSkhIaMmQI8766umTJErlVOv6trq6u3P9DdXTSpElUUVFB+fn5JBaLKTExUWZCQgLzPmV0cHCgFy9eUGpqKh05coSOHj1KKSkplJmZSXZ2dsz7lLFFixa0efNmyszMlK1CkpmZSSEhIdSiRQvmfcpa1UorVT1Wl1VXdHV15b6uSdatyurs7ExnzpyRrSajCYaHh/+nFy9eZN6prC9evKDevXsrjPfp04eys7OZ972ua9eupaZNm8q+rknWrcr47xWpKl8fk5KSqnw+uW+Pu3btokmTJjHvqA+zs7OptLSUJBIJFRcXU1ZWlpys++rq5MmTqaCggIYPH65wbMSIEVRQUECTJ09m3qmMFhYW9ODBAyotLaW4uDh6/PgxlZaW0v3796lTp04EgD7++GP6/PPPmbe+riUlJVW+P+nQoYPGrHbn7OxM0dHRNHz4cGrbtq3Gvc+sja+e31Q3TU1Nyd3dnTw8PMjc3Jx5j6p0cnKioqIiOnfuHJWWlsqen7lz56r1qqdc7tso30Obw2nA/Pbbb2jbti18fHxw+/ZtAICtrS127NiB58+fw83NDSNGjMC3336Lbt26sY2tA0VFRejSpQuSk5Pl9mgxMTHB/fv3oaOjwzpRKfr164epU6fC1NQUHh4eePr0KT7//HOIxWJcvXqVdZ5SCIVCNG/eXG4Pxw4dOqC4uBiZmZnswlRIixYtMGbMGJiZmWH16tXIycmBnZ0d0tPT8fTpU9Z5nH8RHR2Ns2fPYuHChXLjK1euhIuLi9ruMS2VSpGTk4OxY8fi4sWLCscNDAzw9OlTtd3jEACePXuGTZs24bvvvqtxn3B1JCIiAvHx8Zg8ebJs31SRSISdO3fC1NQUAwYMYFxYN1q2bInIyEgYGhpi//79ePDgAQQCAaysrDBu3DikpqbC0dFRrff5/a/9z19FHfZCl0gkaNeuHTIzMyGVSqv8vyYQCNR6z9RKsrOz0bRpU2hpaaG4uFhh1Qd9fX1GZZz/4n//+x/atm2Ljz/+WLaKRYsWLXD8+HFkZGRg7NixjAtfj/DwcIwaNQp5eXm4dOlStX/jiAiDBw9+w3Wq49+vl//88w8yMzMRHx8vt2c45+1j0aJF8PPzw6lTpzRulRxN3i917969GDduHB4+fIhHjx6BiGBlZQULCwv88ssvGDduHOtEleDq6goLCwsIBAI8fPgQ58+fV/vPCsnJyZg5cyZOnjwpN/7RRx/hhx9+gJGREaMy1fHq6/6rz5emvM+sDa+e3+S8HVy7dg2HDh3C+vXr5Z6fHj164Pjx42jfvj3rRA5HY+AT2hxOA6ZNmzbYu3cvBg8eLPtwqaWlhYsXL2LChAnIyMjAwIEDoa2tjfPnzzOufX3i4+MxdepUXLx4Ue4NxYQJE7BgwQJ07dqVdWKdeXU59QkTJqBLly4Qi8X48ssvMWLECLVeTr0hYGNjgwsXLiAvLw8dO3aEpaUlxGIxgoOD0aFDB3h5ebFOrDOVyyxVLs+tKcsslZSUwMbGBvHx8XLjnTp1wt27d9X2AhmpVIpdu3bh888/x/z587Fhwwa545owoZ2VlYWePXuq7dLwNVFcXAw7Ozs8evRIbtzKygo3b97EO++8w6hMOdavX4/BgwdjyJAhCsuUtmnTBufOncPFixc1ZglrTcDJyQlXr16FVCr9z8l6dZigrwlNnsTQdN577z1ERERAX18ft27dAvDyYt709HQ4Ozur3fKyNjY2uHfvntpPwHA0l5reexERzMzM3mAN53Xw8PDAuHHj0KlTJwgEAjx+/BgHDhzAoUOHWKeplMaNG6OsrIx1hspYtWoVPvnkE3zxxRey91sDBgxAWFgYDh8+jLlz5zIuVB5Nf59ZG9RlQru2W9oA6r+tTUFBAWxsbJCUlCT3/HTo0AEPHz5U2/NFHM7bCvPbxLlcLlstLS3Jzc2NPvroI7KwsGDeoyrnzp1L9+7do169elFeXh717duXxo0bR+np6TRjxgzmfcqoycupVy4DXJ2s+1Th+fPnadWqVQrPX58+fUgsFjPvq6uavMxSSkoKjRkzRmHcw8ODkpOTmffVVYlEQq1bt6Zx48ZRYWEh7dq1i7S1tWXHDQwM1GbJ4+pct24dLVy4kHlHffj8+XNydnZWGHdxcaHnz58z76urYrGYXFxcqj3u6uqqlq+VNjY2tZZ1K5erqTZt2pQmT55MmzdvptWrV9OECRNIS0uLeVddrPwbDoASEhKoVatWzJvqwzFjxtCRI0coJiaGoqKi6H//+1+NfyO43DelqakprVixgg4cOCD7v+jq6kpdunRh3satXoFAQEuWLKG0tDSqqKiQfWYNDg6miRMnMu9TRm1tbfr5559JKpVSWVkZlZWVUUVFBYWGhsp9xlN3W7RoQbNnz6YdO3bQ9u3byd/fn5o3b868602pLkuO/3v7mry8PCosLKSoqCiKioqigoICys3N1YhtbVJTU2Vb7b36/IwcOZLi4+OZ93G5GibzAC6Xy603v/76ayoqKpLtS1lcXEzBwcHMu5S1qKhItjfSq2+WTExMqKSkhHmfMn711VdyBgQE0L59++jFixc0f/585n2qMDc3V7Zv8avPn7GxsVo/f9euXSN/f3+Fn6tHjx6UlpbGvE8ZAwMDKTs7m+bNm0f9+vWjvn370vz58yk7O5sWL17MvK+uSqVS2Qk4e3t7SkpKosjISGrbti0BmjGhvXHjRsrJyaHLly/Tpk2bNGpf0Y0bN1JKSgp98skn1L59ezI0NKSxY8dSSkoKrV+/nnlfXS0tLSVDQ8NqjxsaGqrla2XlPrBV7Qf7b1m3KqO5uTkFBARQSEgIbdq0ifz8/NTipFttNTIyqlHWfdyG44sXL6hXr14EvHx9effdd5k3qVKBQCCbmHnw4AEdO3aMjh8/Tg8fPiSJREJbt24lANSqVSsaOXIk815u9Wpra5OFhQWJRCLmLapSky/k1XQDAwMpPj6exo0bR0VFRbLnzsPDg65du8a8TxV26tSJxowZQ8OHDydjY2PmParUwcGBMjMzKTU1lY4cOUJHjx6llJQUyszMJDs7O+Z9b8K8vDy1e2/t7+9PJ06cID09PdmYnp4eHTt2jGbPns28T1lXrVpFERER1KZNG8rLyyMzMzNydHSk+Ph4CgoKYt7H5WqYzAO4XC4jhUIhTZw4kfbv30/nz5+nixcvysm6T1Xq6OiQg4MD9ezZk9555x3mPaowPj6eBg8eTID8xOGECRMoNjaWeV99OH36dAoLC2PeoQqfP39Otra2Cs+fs7MzpaSkMO+rqwUFBdSxY0eFn6tDhw5qOfn0b/38/Cg1NVV2gUxqaip99dVXzLuU8dUJbQDUunVr+uOPP+jJkyfUq1cvjZjQ/veV4f+WdZ8yamtr04YNG6i0tFQ2EVpSUkLr1q2jRo0aMe+rq2lpadS3b99qj/fr108tL5IxNjaW+fHHH1NcXBxNmTJFdlf2lClT6NGjR/Txxx8zb62rCxYsoPLycpJIJPT06VN69uwZSSQSKisro4CAAOZ9qvC/Lkhg3cet3gkTJtQo677X9ccff6SSkhJKTEwkiURCSUlJGrXCkb+/P7148YKGDx+ucMzNzY1evHhBc+bMoZiYGJo7dy7zXq6iOjo6tHPnTqqoqJC7E3bjxo1qf6GyJl/Iq+nGxcXRBx98oPDcWVpaUnZ2NvM+bs1GRERQWFiY3AUyIpGIfvrpJ/rjjz+Y9ymjsbExNWnS5D+/T13u0H7VtLS0Klev6Nq1Kz158oR5n7JqaWnRvn37ZBcvl5WVkUQioT179pBQKGTex+VqmMwDuFwuI0NCQqigoIB+/vlnWr9+Pa1bt05O1n3c6tXk5dSr08TEhPLy8ph3qMIff/yRjh49SlpaWpSfn08dO3YkIyMjioqKUuu7KhvKMkvNmjWjZs2aMe9Qha8uV1qpSCSiLVu2UHFxMS1YsIBP0KiBOjo6ZG1tTTY2NqSjo8O8R1l37txJly9frnJpxEaNGtGlS5do586dzDuV8e+//6YPP/xQYfzDDz+kmzdvMu+riwMHDiSJREJLly6Vu/uiZcuWtHz5cqqoqKD+/fsz71TWbt26yeng4EA+Pj50//59GjVqFPO+uioSiSgoKIjat2/PvKW+zM7OlrOgoICkUimVlJRQVlYW87666OrqSjNmzCCpVEqLFy9WWOmoUtaddfHOnTv0xRdfVHt84sSJJJFI6Pfff9eopXQ1yQ0bNtCNGzeob9++VFBQIPts4ObmRtHR0cz7lFHTL+TVZIuLi2V3Lb/63FlZWVFBQQHzPmUMDQ2tUdZ9qnr+LC0tFcatrKyoqKiIeV9dFQgEVFZWRubm5sxb6sP8/HwaNGiQwvigQYMoPz+feZ+qNDU1JXd3d/Lw8NDY55LLfQtkHsDlchmZmZlZ5clUTbFp06YUHBxMV69epbi4OI24U+FVNXU59eqcO3euWu6ZWpW6urp05coVys7OpoqKCkpOTqaysjK6fPkyNW3alHlfXdXkZZYuXrxILVq0qPK5VOcVLf59h/arTp48mUpKStR+Qjs0NLTKCxCaNm2q9id2NPVnMzQ0pGfPnlFSUhLNnTuX3NzcyM3NjebPn0/Jycn0/PlztZ90Ky4ups6dOyuMd+7cmYqLi5n31cWff/6Ztm3bVu3xH3/8kQ4cOMC8s74cNmwYXbp0iXmHMhYUFMi2tGkompub0/nz59V+T+awsDCNudiu0uLi4hqX8Tc2NiaJRMIns99ik5KS6P333ydAfuLQzMxM7S9UbigX8mqiN27coPHjxys8d0FBQRQREcG8TxmPHj0q58mTJ0ksFlNOTg4dOXKEeZ8qfP78OTk7OyuMu7i40PPnz5n3KeO9e/dkr5ma5u7duykpKYnc3d3J0NCQDA0Nyd3dnRITE2nXrl3M+7hcrlrJPIDL5TLyyZMn1KlTJ+Yd9eWBAwfoyZMn9N1339GsWbM04k6Ff6uJy6lHR0dTVFSUzOjoaHr69ClVVFTQ5MmTmfep0kGDBlFAQADNnTtXtoS8OqvJyyxVN/HbunVrKi8vZ95XV4OCgmq8o9fR0VGtJ0aBqu9CB0D6+vpUUVHBvI//bFXbsWNH+v3332WvJ5XLPJ8+fZrMzMyY9ylrVFQU7du3jxo3biwba9SoEe3bt4+ioqKY99XFxMTE/1wqPjExkXlnfWlubk6FhYXMO5Tx2LFj5OXlxbzjTevg4EAPHjxg3qEqDQ0N6b333mPeoaxZWVlkY2NT7XFra2u+PPBb7qv7E786cditWzfKzc1l3qeMmnwhL6C5F00CoBEjRlBOTg7NmzePCgsLKSAggLZv306lpaU0ZMgQ5n2qViAQ0NatWzVma4aNGzdSSkoKffLJJ9S+fXsyNDSksWPHUkpKilqvdge8vDgyIiKCunbtyrxF1ero6NAPP/wgu2BeIpFQaWkp/fDDD2p7U8fatWtrLetWLleTFPzfFxwOpwEye/ZsmJqaYubMmaxT6oWcnBwMHz4c165dY51Sr7Rv3x5EhCdPnrBOUQlBQUFyj//55x9kZmbi8uXLePToEaMq1dKhQwckJyezzqg3TExMYG9vD6FQiFu3biE+Pp51Up2xsbEBANy+fRsffPABsrOzZcdEIhGGDh2KqVOnwsTEhFUipxp0dXUhEAiQk5ODTp06ITMzU3ZMJBLBzc0N3333HQwNDRlW1g1N/tn+jZ6eHjp16gQAiI+PR05ODuMi1dCzZ0+cPHkSQqEQd+7cAQB0794dRIQRI0bgxo0bjAtfn6KiIlhYWFT7fsTQ0BBxcXFo2rTpGy5TLbq6unKPBQIB2rVrh2XLlqFz586ws7NjVKY8U6ZMwbJly7B//35ERUWhqKhI7vjJkycZldUvtra2+OOPP9CiRQvWKXVGIBBgyZIlCAgIQLNmzQAABQUFWLt2Lb755hsQqd9pn99++w0pKSmYPn16lce3bt0KY2NjDB8+/A2XcWrL5cuXcfjwYWzevBn5+fno1q0bkpKSEBISAnNzc3z44YesE+uMlpYWdu3ahU8//RQCgQASiQQikQgHDhyAt7c3/vnnH9aJSiGRSNCuXTu595gAoK+vj+fPn0NbW5tRmWpwcXHBokWL4ODgAKFQiOjoaAQHB+P8+fOs0+oFCwsLXL58Ge+99x7rFKXR1tbG6tWrMW3aNGhpaQEAKioqsHXrVixYsADl5eWMC+tOdnY2mjZtCi0tLZSXl6OkpETuuL6+PqMy5RAKhejXrx9iYmJQVlYGMzMzCAQCxMfHo7i4mHVenQkPD5d77ODgAJFIJDtvaWFhAalUiqioKAwePJhFIoejsTCfVedyuWw8evQo5eTkUEJCAv3666905MgROVn3KWtiYmKVy3lqgiKRiIKDgyk3N1d2dWNubi6tWLGCtLS0mPdxa1YqldKVK1doypQp1LJlS+Y9qjIwMLDKu32bNGlCgYGBzPvq+lxV/h+rvEv0VQsLC2vc35H7djx3VVlRUUGLFi1i3sl/toarjo4OTZ48mdauXUvr1q0jHx8ftb1DAah5CwMAZGBgoPZbGFT+nP/+PyeVSikpKYl69+7NvE/Zn606NeG5q9y+oNKPPvqIpk6dSjExMfT7778z71PGb7/9ltLT02natGlkY2ND3bp1oy+//JLS09Pp66+/Zt5XF/v06UNlZWV08OBB6tmzJ+nq6lLz5s3p/fffp19++YXKysrI0dGReSe35ucwLy+PtmzZQsXFxbR+/Xo6d+4cFRQUkL29PfM+VWhiYqJR+6VW/j+TSqVkampKurq6MvX09GjChAn05MkT5p3c1/PDDz+kjIwM5h2qVEdHh6ytrcnGxqbGFcfUSU9Pzxpl3aeMJSUl1LFjR+Yd9aW/vz+dOHGC9PT0ZGN6enp07Ngxmj17NvM+LleT5HdoczgNmLCwsBqPT5w48Q2V1A/jx4/Hxx9/DC8vL4UrG9WdrVu3YtSoUQgKCkJkZCQAoE+fPli2bBlOnDiBL7/8knFh3fnwww8hlUpx7tw5uXEXFxcIhUKcOXOGUZnqsLOzw2effYZPP/0UrVu3xtmzZ7Fv3z78+uuvan1FcXVX8rdq1QoZGRmyK6jVCWNjYwgEAiQmJqJXr15yP1t5eTkyMjLU/g4MTcXJyQkCgQDh4eFwd3eXu7u+vLwcycnJePbsGcPCuqPJP1tDQEtLC48ePcKIESPw4MED1jkqQyqVYsmSJSgsLKzyuK6uLoKDg9Xyb8GrODk5yT2uXEkmPj4eUqmUURWnNvz7+SEiZGZmIjw8HAEBAXj+/DmjMuV58uQJpk2bpnAX/UcffYQtW7agffv2jMqUY+TIkdi+fTtatWolN56Tk4OpU6fi6NGjjMo4tcXa2hpz5syRuxN21apVuHfvHuu0OiEQCBAQEICRI0dCW1sbFy5cQHBwMMrKylinqQSpVFrjig5EhKVLl+Lbb799g1WqJSEhAT179pR7/wwALVq0QHR0NMzMzBiVKc/atWvlHleuIjN8+HDs3r0bvr6+jMo4DZ3r169jwYIFCnc1awppaWlwcXHB/fv35ca7du2Kc+fOacTKaRzO2wKf0OZwOBpFdHS03Acwc3NzCAQCJCUloaKiQu57HRwc3nSeysjNzcWnn36qMLk7dOhQ/Pzzz9DT02MTpgLu3LmDBQsW4PTp03Ljrq6uWLVqFWxtbdmE1RMDBw7EuHHj4O7uDpFIhCNHjmDSpEmss+qEVCpFmzZt8OLFC7nxQYMG4eDBgzAwMGBUxmmoiEQi7Ny5E4GBgUhLS2Odo3KMjY2RkpLCOoNTB9LS0jBkyBA8fPiQdYrKEIvFtVrW2NTU9A3UcJSlcePGGjNB0xAoKSlBt27dEBcXJzduYWGB27dvq/VS/zo6OnB1dZVtPxEXF4ezZ89q3AXLHPVgwYIF+Prrr3Hx4kWUlJTA1dUVe/bswdSpU1mnqYSGcNGkVCpF27ZtFS7CNjAwQEpKCpo0acKoTHn+PVlYedFdeHg4wsLC+IV3aoCpqSm++OILmJmZYdasWcjMzISrqytSU1MVJkvVCWdnZ6xatQqBgYFVbmtTUFDAqEw15Ofn4+OPP8alS5fkxgcNGoQTJ06gefPmjMo4HM2DT2hzOByN4t/7L9dEcHBwPZbUL8+fP8fAgQMVToR37twZERERaj1xWFxcDCsrK4U9pjt06IDY2FjZvoCahp2dHUJDQ9GtWze1u3stOzsbRIQWLVogPz9fbkJDJBKhWbNm2LZtG2bOnMmwUjk8PT3x4sUL/P777wCAVatWYcqUKbh//z4+++wztZ5UFIlEGD9+PM6ePYv09HTWOSonPz8fNjY2GrlvvaurKwoLC3H16lUAwPTp0zF58mTcv38fM2bMQG5uLttATrXMnz8fnTt3ho+PDz+5qIaYmprCz88PVlZWICI8ePAAGzduRGJiIus0pRAKhVi0aBGmTZuGNm3awMLCAmKxGMHBwUhKSvrP1Z047Pjrr7/w999/Y9asWXLjmzZtQs+ePdGnTx9GZZyGjCau3vTw4UNs3LgRW7duBfDyvdjx48eho6PDuEy1aOJFk25ubgCA48ePw8vLC3l5ebJjIpEIgwcPhrOzMzp37swqkdPAcXJywunTp3H16lU4OTnBysoKYrEYc+fORa9eveDh4cE6sc68+nnn1fNFAoEARKSWfw9eZffu3RgwYAACAgLw119/AQB69+6N1atXIyIiAt7e3mwDORwNgk9oczgNjKioKAwePBi5ubkKdzP/G3W+g1nTCQwMROfOnfHFF1/Ilqhu1KgRQkNDERcXp9aT9c+ePcO4ceMUrmwcPHgwDhw4gDZt2jAqUz3t27fHZ599hnHjxsHGxgaRkZHYv38/tm3bxjrttfD09IRAIEBYWBj8/PzkTg6Ul5cjKSlJ9qZeXXn48CG+/PJLXLp0Cb1798bFixfh5+eHESNGQCKRwN3dnXWiUhQVFcHKykrjTlwBwLFjx3D8+HHs3r2bdYrKuXv3LubPn4/Tp0/D2toaN2/exNq1a/HBBx/gwYMHar91iCZz9OhRDB48GIWFhYiJiVG4S0HdX1M0GRcXF/z666+4ffs2rl69CoFAAEdHR3Tv3h1ubm64cOEC68Q6ExgYCC8vLwQFBWHHjh2wtraGWCyGh4cH/P394ejoyDrxtfn38qs1ERAQUI8l9YuTkxNOnTqFlJQUREZGgojg6OgIIyMjDBs2DH/++SfrRE4DpLo7Ydu1a4eEhAS1XDmgpKQEFhYWSE1NlY2VlpbC1NQUT58+ZVimWry9vVFYWIjDhw/LjY8ZMwZNmzbFnj17GJXVncoJNSKCQCCQO1ZRUYGkpCQEBATg1KlTLPI4HFy7dg2HDh3C+vXrkZ+fj+7du0MsFqNHjx44fvy42m4fAihu2fNvIiIi3lBJ/aCjo4M1a9Zg4sSJ0NbWBvDyoq7Q0FDMnTsXxcXFjAs5HM1BvS9/4XA4r82JEydkywceP36cbUw906NHDwiFQly/fl1uvFevXpBKpYiKimJUpjx2dnYYPHgw0tLScOfOHQBA9+7d0ahRI1y8eBFHjhyRfa+6nRT/9ddfsWHDBowaNUp2p5OZmRnWrl2LX3/9lXGdapg8eTLGjx+Pvn374tGjR9i/fz9GjhyptneQVp7QEIvFuHbtGiQSCeMi1WNkZIT4+HgAL/dzPHz4MHbs2IGrV6/i8uXLbONUwN9//w1bW1uNnNA+ffo0Vq5cCWtr6yqXN/v3fqPqhImJiWzpOXd3d5w8eRKLFy+GnZ2dbDUBzttJbm6u3N9qjvrw3XffYf369Vi4cKHc+MqVK7Fq1Sq1viDU09MTU6ZMQXh4uNzFdXfv3lXbO9bs7OzkHjs4OEAkEuHRo0cAXi7Jre6fC4CXJ4ItLCwwY8YMdO7cGQKBAEePHsWWLVvUfnlgjvpRuU8vEcHHxweFhYWyYyKRCE5OTmq75UajRo0UlrsvLy9H48aNGRXVDwsWLMC0adMUxjMyMrB9+3a1nNAWiUQAgMTERPTs2RNZWVmMi1TDf92o8irq/B6lIWBjY4Nx48YpjGdmZkJfX59BkeqIiIhAixYtMGnSJLkVjkJDQ5Gfn886TymEQiF69uyJJUuWYO7cuTAzM4NAIEB8fDyfyOZw6gE+oc3hNDBevXNXne/irQ0//PADvv/+e4UJbUNDQ8yfPx+9e/dmVKY8VZ0If/UqcXVm7ty5OHPmDB4+fCjb87Z9+/a4cuUK5syZw7hONQQGBuLnn3/GrFmzZBckaAKvXlXbpEkT2ZWplajzvkiFhYXQ19dHamoqXFxcsH79egAv78jQhCUGt2zZgnXr1sHIyKjKSd+YmBhGZcpTuSTk7NmzFY6p+/Jm5eXlsrubhgwZIju5mJ2dzffpesvhd8+rL1ZWVvjkk08UxitXKVFnDA0NZRdvvYpQKFT4m64ufPDBB7Kv/f39UVBQAC8vL9mWDHp6evjpp59w5coVRoXKo6WlhXPnzmHq1KlYsmQJ6xwOB/7+/gBeLiU7bdo0uaVmK1dvqmqyVF1YsWKF3CRFo0aNsHjxYrlVqtR5xQfg5XZfYrFYYTw5ORnGxsYMilSHqakp6wSV8uqNKk2aNMH06dNx//59REZGAni57HHXrl2xZcsWRoWc2pKbm4t27dohKSlJbtzOzg5PnjxhE6UiHBwccObMGZSWluL69esQCATw9/fHokWL4OLiglu3brFOrDP//PMPzp49CysrKyQlJan1uRMORx1Q3zN4HA5HZTg4OMhdIRcdHc06SSV06dKlyp/l1q1b6NKlC4Mi1aHJJ8Lz8/Ph6OgIZ2dndO/eHSUlJbh7965an2j8N+p+EqA6dHR08P333+OTTz6p8gpidZ44PH/+PHbu3Ilbt27BwsJCthRd165dFT5wqiMHDx4E8HKvzUoql+NT90nfyrsxNJE///wT69atw9WrV9GrVy+MHTsWwMs7DisvCOJwOKolMzMTtra2ChO/tra2yMjIYFSlGmJjY9G/f3/s379fbtzDw0OtTzRWEhAQABcXF9lkNvDy5PGSJUtw7tw5rFu3jl2cEkgkElhbW9f6Dj0Op76pnDAMDw/H6NGj5f7PqTsRERGwtLSUG7t27ZrcJKkm/F/MyMhAt27dFFYQ6969u0bc2dy0aVMMGDAAxsbGaNSokdyxkJAQRlV149UbVXbs2IFNmzYhKChI7nuWLVsGIyOjN53GeU0OHDiAVatWwcPDA0QEoVAIR0dHrFmzRi1XRXiV9evX4+TJk5g8ebLsIieRSISdO3diw4YNGDBgAONC5YiJiYGpqalGnBvicNQB4nK5DVNDQ0OKiIggqVRKWVlZlJWVRVKplK5cuULt27dn3qesL168oN69eyuM9+nTh7Kzs5n3cRuWNjY2JBAIZF/XJOvWurp582aKjY0ld3d3KioqIm9vb1q8eDGlpKTQuHHjmPcpY4sWLSgkJISOHz9Orq6usvFly5bRokWLmPcpq7GxcY2y7uNWrZGREZ08eZJu375NEydOlI2vW7eONm7cyLyPW7Pu7u508OBBioyMpKioKDlZt3GrNzAwkLKzs2nevHnUr18/6tu3L82fP5+ys7Np8eLFzPuUccSIEZSTk0Pz5s2jwsJCCggIoO3bt1NpaSkNGTKEeZ+y5ufn06BBgxTGBw0aRPn5+cz7lHHNmjW0cuVK5h31aevWralr164a876Zy32bXbVqFYnFYho4cCAJhUISCoU0aNAgEovFtHr1auZ9ymhra0tPnz6l3NxcqqiooPT0dJJKpVRQUEAJCQnM+5QxNzeXzM3NFcbNzc0pNzeXeR+3ZrW0tGjfvn0kkUhIKpVSWVkZSSQS2rNnDwmFQuZ9ylhcXEyWlpYK41ZWVlRUVMS8T1mdnZ0pOjqahg8fTm3btiVdXV05WfdxuZqk4P++4HA4DZCzZ8+iefPm8PLywuPHjwG8vKsrLCwMRUVFcHV1ZVyoHP/73//Qtm1bfPzxx7I9WVq0aIHjx48jIyNDdicbh/MmkEqlaNu2LTIzMyGVSmV3v1aiCXfDJicnw9PTE3/88Qfy8vJgb2+PhIQEfP755/jss88wfPhw1omcBoom3YXB0Qx8fX3xzTffYPfu3Zg8eTJ++uknmJmZoWfPnvjhhx80Ytng1q1bw8DAAEKhUG5cE5bh8/PzQ0BAAN577z0AwNOnT7F69Wq5VS7UFRcXFyxatAgODg4QCoWIjo5GcHAwzp8/zzpNaXbv3o0BAwYgICAAf/31F4CXS7GuXr0aERER8Pb2ZhuoBJs2bYKnpyfi4+Nx8+ZNha1D1Hn5Y3t7e+zevRtWVlay986a8L5Zk1m7dm2tvk+dfy81HW1tbezduxceHh6QSCQAXm4/sWfPHkybNg0VFRWMC+vOpUuX8PjxY3z55ZfIzc1F9+7dUVFRgX379mHjxo04duwY68Q68+zZMyxcuBC7du2SG/f29sZ3332Htm3bsgnjvBampqaws7ODUCjErVu3qtwORt14/vw5JkyYoPB+0sXFBXv27FH7381Xt9Z4dZUO/l6Fw1E9fEKbw2nAFBcXw9HREbdv35Ybt7Ozw9WrV2X7cqor7733HiIiIqCvry9bJtHW1hbp6elwdnbmy7Fy3ijGxsZISUmRfV0Tld+nbhQUFKBr165ISUlBamoqRo8ejRs3bqBjx46IiYmBrq4u68Q6079//xqPa8KS+J9//jmmTZsGExMT9OnTBykpKZg1axbEYjF+/fVX1nl1xtbWFr///juaNm2Kd955B9nZ2Xj33XdRXFyMjIwMmJmZsU6sM/+1dGBqauobKuG8Lg8ePMDy5cvx888/Iz8/H927d4dYLMby5cvRqlUr+Pr6sk6sMw1p8qlZs2YAgMLCQsYlnNqgo6ODNWvWYOLEibI9wSUSCUJDQzF37ly5PXHVjfDw8GqPEREGDx78BmtUy507dxAfH49Vq1YhPT1dYTlndX3frMnU9PtYibr/XjYUOnXqJNsGLCYmRiP+v+Xk5OD999/H48ePkZOTgz59+uDhw4fo1auX7P2LujJ//nwsW7YMO3fulLtwa+LEiQgODsaqVasYF3IaKhs3bsSoUaMwZ84cXLt2DUSEfv36YfXq1Thy5Aj8/f1ZJyqFk5NTjccjIiLeUAmHo/loztkEDofz2qSkpMhO5ryKlpYWnjx5wqBItTx9+hTdunXD+PHjZR/CfvrpJ/zvf/+TXWXM4bwpXv3wrwknAqoiMTERHTt2REpKCu7fv49PPvkEN27cgJubm9rvnXf58mWFsVdPqKr7BM20adMQHByMDRs2YPHixbJ9p3Nzc+Hn56fWE9qV+3VV3oXRu3dvubsw1JmkpKQa92lU999LTcbY2BjXrl0DAJSUlMgu+Nm7dy/++usvtZ7Q/umnn/D48WNMmjSpyskndadjx47Q0tJCfHy83ES2ubk5KioqFPYb5bw9lJSUYMaMGZg7dy7MzMwgEAgQHx+v1hPZlXzwwQesE+oNExMTjB49GgkJCaxTOLVEk38fGxpxcXGIi4tjnaFSKioqZO9N0tPTYWxsjIcPHyIvL+8/Lzx/21m1ahUSExMxa9YsjBs3DsDLiyi9vb1x6NAhxnWcqqjtihaAeq9qMWfOHBAR9uzZI/uMWlFRga1bt2LBggWM65QnIiICLVq0wKRJk2BlZQUiwoMHDxAaGipbMZTD4agGfpaLw2nAzJs3DyEhIZgxYwaioqIAAA4ODti4cSPmzJnDuE41FBcXY8eOHawzVM6ECRNw8OBBlJeXy41ra2vj008/xd69exmVKYdIJML48eNx9uxZpKens85RKW5ubrX+3pMnT9ZjSf3x008/oXv37oiIiMDKlStx6tQp+Pr6QktLC7Nnz2adpxQtW7aUe6ytrQ07OzusWLECixcvZlSlOnx9fTF58mScOHFC7gPlzZs3sWbNGoZlymNra4upU6fin3/+gVQqRePGjSEWizFv3jzs3r1brZcVtLOzk3tc+Xs5e/Zsjfi91GSeP38OfX19pKSkIDk5Gb1798bdu3dhYmIitx2FOqLpk0+7du1CWFiYwvKP77//Pnx8fDBo0CBGZXUjOzu71hcd6Ovr13PNm6G4uFj2c2vCZPaYMWMwcuRIaGtr48KFCxr32efixYvo3r27xr6mcDhvI6GhoTUenzRp0hsqUT23bt1Cjx49EBcXh0uXLiE4OBjvvvsuJkyYoBHbohw6dIhPXqsR//485+DgAJFIhEePHgF4uS2kVCqVnbNVVyoqKuDn54eFCxfKXVRYUlLCOk0lODg44MyZMygtLcX169chEAjg7++PRYsWwcXFRbZqKIfDUQ3MN/LmcrlszM7OptLSUpJIJFRaWir3dVZWlpysW+uip6cnDRs2TPZ41apVlJOTQ1evXiVjY2PmfcookUiodevWCuOtWrUiiUTCvE8Zi4qK1P75qUqpVFor1f35e1UjIyMaNWoUdevWjXlLfdm/f3+6efMm8w5lLS4ulv2/y8/PJxMTEwJA5ubmVFxczLxPGTMyMqhTp04EgB4+fEguLi4EgCwtLamoqIh5X304bNgwunTpEvMObvXu2LGDgoKCCABNnTqVioqK6Ny5c5SdnU07d+5k3qeMx44do9GjRzPvqC/z8vLIzMxMYdzMzIxycnKY972unp6eMv39/SkrK4sOHDhAvr6+5OvrSwcOHKCsrCzy8/Nj3qqsAoGAAgMDKTc3lyQSCUkkEsrJyaElS5aQQCBg3lcXJ0+eTFKplB4+fEi3b98miURC3377LfMuVaqvr0+//fYbBQUF0ejRo8nNzU1O1n3chqmRkVGdjqmLR48elfPkyZMkFospJyeHjhw5wrxPGR0cHGjgwIEEgN599106deoU5eXlUVRUlMZ8brW3t6fx48fTuHHjyNbWlnkPt3b6+/vTiRMnSE9PTzamp6dHx44do9mzZzPv41ZvREQEhYWFkUgkko2JRCL66aef6I8//mDex+VqmMwDuFwuI189gfVfsm6tiw8fPqRBgwYRAOrduzcVFRXR5MmT6cSJE2r/IUwqldK7776rMN6tWze1vQCh0vDwcProo4+Yd3C5tbFz585UUFDAvENZY2NjZf/vXp3Q9vX1VfsJ+7Nnz9Jnn31GAGjr1q30119/0bhx4+j06dP0119/Me+rD83NzamwsJB5B7d6BQKB3AkPDw8P2rhxI/n6+pK2tjbzPmXU9Mmn3NzcKk8O29vbU35+PvM+ZTx8+DDNmDFDYXzGjBl07Ngx5n3K+u2331J6ejpNmzaNbGxsqFu3bvTll19Seno6ff3118z76uLdu3cpODhY9tjLy0vtfw//rZubG+Xm5mr8haBc9VKTLzCvToFAQFu3bqW5c+cyb+FWbevWrenixYsklUopKyuLsrOzSSqV0oULF6o8f8R9u0xLS6MuXboojHft2pWePHnCvI9bvcXFxWRpaakwbmVlpbEX0XO5DGUewOVyufViUVGR7Oro7777jnbv3k0AqEuXLpSRkcG8ry5GR0dTVFQUSSQSunPnDkVFRcm8ffs25eXl0cGDB5l3KuOYMWMoPj6eZsyYQb179yYbGxs5Wfep2saNGzNvUNZBgwZRbGws6erqKhxr3rw53bt3j/r168e8Uxn//XvYrVs3cnV1pUuXLtGff/7JvE9Zvb29KTU1lT755BMqKCigsWPH0qJFi2Rfs+5TRk2+C0NXV1fO5s2bk6WlJf3vf/+jW7duMe/jNkw1ffLp5MmTdPDgQRIKhbIxoVBIhw4dot9//515nzIWFBRUefe5ubm5Rly89eTJkyovqvjoo48oLS2NeV9dLCwslF2EBrz8XSwrK6M2bdowb1OVYrGYQkJCyMDAgHkLl1tpdReYGxsba/RFhRYWFvT06VPmHXWxSZMm5ObmRs2aNVM4pqurS25ubtSoUSPmncr4888/040bN6hz586yMSsrK7p+/TodOHCAeR+3ZvPz82U35bzqoEGDNO5iNU3z+fPn5OzsrDDu4uJCz58/Z97H5WqYzAO4XC5DhUIhubu705IlS2jx4sU0evRouTuG1Nn09HTZHTTR0dE0YcIEAkCmpqZqe1IuKCiIgoKCSCqV0vfffy97HBQURAsWLKBPP/1U7e/squ4EuKacCAde/r9bsmQJpaWlUUVFhexEZHBwME2cOJF53+t64sSJGpci9fX1paNHjzLvVMZXfw9f9erVq1VeiauO+vj4UFJSkuxnS0lJUcvfx4Zk5e/lq0qlUkpKSqLevXsz7+Mqam5uTgcOHKj2AqD9+/fLTU6po5o++WRlZUWZmZkUFxdHYWFhFBYWRnFxcZSenk5du3Zl3qeMSUlJNGfOHIXxOXPmUFJSEvM+ZS0pKZFtQfGqFhYWaru9hlQqVbhL9NWVVjTB/Px8MjU1Zd7BfT1FIhEFBQVR+/btmbeo0rVr19LatWtJIpHQ1q1bZY/Xrl1LGzZsoMjISI242LU6P/zwQ7W9OeCrr76iCxcuVHv8/PnzNH36dOadypibm0s9evRQGO/Zs6dabovS0Ny9ezclJSWRu7s7GRoakqGhIbm7u1NiYiLt2rWLeR+3ejdu3EgpKSn0ySefUPv27cnQ0JDGjh1LKSkptH79euZ9XK4mqQUOh9Ng6dq1K06cOIG2bdvi0aNHAAALCwtkZmbio48+wr179xgXKsf58+exc+dO3Lp1CxYWFjh16hSAlz93UlIS27g6EhwcDABISkrCwYMHUVZWxrhI9ZiYmLBOqHcWL14MLy8vzJs3Dzt27JCNx8TEwN/fH2FhYQzrXp/u3btj/vz51R4/d+4c5syZ8waLVM+/fy//+ecfZGZmatT/wZ07d2Lnzp3Q19eHUChEZmYm6ySV0rp1a1haWoKI8OjRI7x48YJ1ktIMGjRI7nHl72V8fDykUimjKk5NzJ07F6mpqSgoKFA4lp+fj9TUVMydOxfTp09nUKca9PX1sX79emRkZLBOqRcePHiAbt26YebMmejevTtKSkqwZ88ebN68GTk5OazzlGLp0qUIDQ3FwIEDERkZCQDo3bs3hg4dCh8fH8Z1ynPnzh3MnDkTs2bNkhufOXMm7ty5w6hKeXx8fFBYWCh7rKWlBW9vb7m/cyEhISzSVMLRo0cxaNAgJCYmsk7hvAZSqRRz587F7t27WaeoFDs7OwCAQCCAjY0NysvLZcfKy8tx584drFmzhlWeyli7dq3cY4FAgHbt2mH48OFq+5yOHz8eK1asqPb4hg0bEBQUhC1btrzBKtUiFApRUVGhMF5RUQGhUMigiPM6TJs2DWvWrMG+ffugra0NAJBIJAgNDcXcuXMZ13FqYs6cOSAi7NmzB1paL6fbKioqsHXrVixYsIBxHYejWQjwcmabw+E0QCIjI5GRkQEvLy/k5uYCAPT09LBr1y4YGBjA0dGRbaCStGjRAl9//TWMjIywdetWnD17FgCwbNkylJeX49tvv2VcyGmoxMXFYerUqQgPD0d+fj66d+8OsVgMS0tLREZGolWrVqwTX4uSkhJYW1sjISGhyuNmZmaIiYlB06ZN33AZhwPo6urihx9+wKeffgqRSATg5UnWgwcPYsaMGcjPz2dcyGlIPHjwABMmTMDNmzerPG5vb48DBw6gc+fOb7hMdezatQtXrlxBaGgo6xROHejVqxe++uorWFlZQSAQ4P79+9i0aROuX7/OOk1pnJyccOrUKaSkpCAyMhJEBEdHRxgZGWHYsGH4888/WSe+NmKxGEQ1n9IhIpiZmb2hItWzaNEi+Pn54dSpU4iJiVGYrFHnyXpN59ixYzh+/LjaToDWRFhYGGbNmlXlBWqaQHh4uNzjyosmw8PDERYWppYXTmZnZ6N79+5ITU2t8riRkRHu3Lmjdp/FX+X48ePQ09PDZ599hmfPngEA3nvvPezfvx85OTkYPXo040JOdQiFQvTr1w8xMTEoKyuDmZkZBAIB4uPjUVxczDqPU0t0dHTknruSkhLWSRyORsL8NnEul8vG4uJi6tKli8J4165d1XbZPU02KyuL9PX1CQBlZ2dTVlZWtbJuVdbPP/+c/vzzT3ry5AkZGxsTAJo1axZ99NFHzNtUYXFxseznenVZSCsrK7VcDj8+Pp5GjhxZ7fFRo0ZRQkIC88662BD2BwdArVq1os2bN1NsbCxlZmZq1GvKwYMH6dGjR+Ti4kK6urrUrFkzcnFxoQcPHtDBgweZ99VFe3t7Cg8Pr/b3Mjw8XO33B9dUX339r0pjY2MqKipi3qmMixYtooyMDPrpp59o9uzZ5OvrKyfrPmV1dXWlvn37yh5Pnz6dbt26Rfv37yc9PT3mfXVVS0uLwsLCNGqp6qps164dff3113T48GE6cuQIrVixgtq1a8e8i1u9iYmJ1aqu7y8bilOmTKGnT5/S6tWr6dNPPyU3Nzc5WfdxG5b5+flkb29f7XF7e3u136e4ffv2FBUVRWVlZRQfH09xcXFUVlZGN2/eJENDQ+Z93JotKSmhjh07Mu/gcrnct1m+5DiH04B59OgR2rRpg/v378uNGxgYID4+nlGVchgZGVV7xW1VvPfee3j69Gk9FqkOf39/2RXgfn5+bGPqkWnTpiE4OBgbNmzA4sWLZXdU5ubmws/PD7/++ivjQuWJjY1F//79sX//frlxDw8P3Lp1i1FV3fn9998RHByM06dPKyzB3aRJEyxfvhy//fYbozrl8PPzw44dO6pdHvjHH3/E7Nmz1fKurlfZt28fzMzMEBoaivT09P+820udGD58OFxdXXH16lXZ2Llz5zB58mScOXOGYVndCQgIQHh4eLW/l+fPn8fcuXMxYcIEBnWcmsjLy4OZmRlSUlKqPG5ubq72qwZULn88YMAADBgwQO4YEan93ZSrV6+WbbNhbW2NdevWYe3atfjggw+wbt06TJw4kXFh3ZBIJBg1alSNy7GqM1paWjh37hymTp2KJUuWsM7hvAampqasEzh1ZOvWrQCA2bNnKxwjItmyrOrCkSNH4O3tjYKCAhw5cqTG73V3d39DVZzaEhsbiyFDhiA6OrrK487OzoiNjX3DVaolLS0NDg4OGDJkCDp37ixbaeXixYus0zi1ICYmBqampmq7RSKHw+G8KZjPqnO5XDZ++OGHFBMTQ+7u7mRoaEiGhobk7u5Od+7coQ8//JB0dXVlsm6trc+fP6ft27dTz549q/2e5s2bk4+PD8XExNDMmTOZN9fWtWvXUtOmTQkA9e/fn0QiEfOm+jA2NpY+/vhjAuTvXu7atStlZmYy71OFI0aMoJycHJo3bx4VFhZSQEAAbd++nUpLS2nIkCHM+15XAwMDSktLo+TkZJo7dy599NFH5ObmRvPmzaPk5GRKS0sjAwMD5p11MSkpiTp37lztcUtLS0pOTmbeqaz5+fkae0dvcnIyWVtbK4zb2NhQamoq8766GB8fTzY2NtUet7a25netvaUePHiQjh49Wu3x48eP0y+//MK8k1u9BQUF1KFDBwJAS5cupUOHDhEAsrOzo2fPnjHvU8awsDDy9/dn3lFfZmRkkLm5OfMObt3U1tYmCwsLjf0MxH37DQsLo2bNmhEA+umnnygsLKxaWbfWxejoaIqKiqqVrFvr4uTJk6mgoICGDx+ucGzEiBFUUFBAkydPZt5ZV0UiEVVUVFDXrl2Zt3DrprOzM0VHR9Pw4cOpbdu2cudk1em8LJfL5dazzAO4XC4jpVKpTIlEQhKJpMrHEomEeWttbdmyJa1evZqysrLo+fPn9Ntvv9H27dtp06ZNtHfvXoqKiqLS0lL6888/aejQocx7X8fy8nLZpKBEIqHWrVszb6oPq1uO29zcXKOWwndxcaHLly9TQUEBFRUV0ZUrV8jZ2Zl5V101NjamU6dOKbyOnDp1SnbiXx0tKSkhMzOzao+bmZlpxO/l9evX6f3332feUR9OnjyZzp07R23btpWNtWnThs6cOUNTpkxh3lcX/2s5uo4dO2rE76UmamtrSyUlJXTo0CHq2bMnNW/enJo3b069evWiw4cPU0lJCdnZ2THvVIWaOvmUlZVFVlZWBICuXLkiO/ndoUMHjVguPjs7mw4dOkQLFizQuOXi16xZQytXrmTewX09dXR0aOfOnVRRUUEVFRWyzwYbN26k+fPnM+/j1s7GjRszb1BWNzc30tLSYt5RXwYFBcn89ttvKTc3l65du0Zr166ltWvX0tWrVyk3N5e+/fZb5q11de/evSSVSik2NpaOHj1KR44cofv375NEIqEDBw4w71PW+Ph4jb1IuSFY1TladTwvy+VyufWp4P++4HA4DRAnJ6daf29EREQ9lqiexo0bY9iwYejfvz86duwIHR0dvHjxArdu3cLZs2fVcimpx48f45dffsG5c+dw6dIljBo1Cjk5OVV+75UrV95wneqIjY3FwoUL8euvvyI/Px/du3eHWCyGr68vvLy80KNHD9aJnBrQ09ODubk5BAIB4uLikJubyzpJKeLj4zFnzhwcP368yuOjRo3CmjVrYGZm9mbDVEyPHj3w3XffITg4GPfu3UNFRYXc8aqWtlYXoqOjYW5ujsaNG8uWeTY2NkZZWRni4uLkvtfBwYFF4muTkpKCyZMn4+zZs1UeHzp0KLZv3w5jY+M3XMapDcOHD0dYWBj09fXlxrOysuDj44OTJ08yKlMNOjo6CAkJgZeXFwDAwsICYrEYGzduxNOnT7Fq1SrGhcpx4sQJNGrUCFevXkVgYCBMTEzw9OlTODs7Y/PmzbC0tGSdWGcSExOrPUZEav+3btOmTfD09ER8fDxu3ryJoqIiueMBAQGMyjg1sWHDBvTt2xd+fn44c+YMunXrBrFYDDc3Nyxfvhz29vasEznVIBQKsWjRIkybNg1t2rSR/T0IDg5GUlISwsLCWCe+FhKJBG3btsWLFy8gkUjQrl07ZGZmss6qF3bs2IFnz54hKChIbnzZsmUwMjLCpEmTGJUpj4eHB8aNG4dOnTpBIBDg8ePHOHDgAA4dOsQ6TWm8vb3h4eGBzz//vNpzRZy3l/86R6tu52U5HA6nPuAT2hwOh6MmfPzxx9i2bRsMDAxARBAIBFV+nzruR/Yq3t7eWLFiBQICAhAaGgofHx+YmZlh4cKF8PHxwcGDB1knchoQmzZtwsCBA9GzZ88q9we/fv06Ll26hFmzZjEqVA3m5ub43//+Bzs7O7lxgUCg9q8p/z4RVxPBwcH1WKI6wsLCYG5uXu1Jj4iICMTHx6vtXr4NgSZNmmDo0KGyC4AeP36Mc+fOoaSkhHWa0mj65JORkRG2bNkCIyMjbNq0STYhs27dOohEIrX/e6DJhIeHV3uMiDB48OA3WMOpLUlJSRg7diz+/vtvuYtdzczMEB0djRYtWrBO5FRDYGAgvLy8EBQUhB07dsDa2hpisRgeHh7w9/eHo6Mj68TX4tmzZ5g8eTJ+++03SKVStGnTBi9evGCdVS/k5uaiR48eiI+Plxs3NzfHzZs3oaenxyaMUyOVF/Jqa2sjOTlZ4cItdbl4tyHTokULTJo0CVZWViAiPHjwAKGhocjPz2edxuFwOG8FfEKbw2lg2NjY4N69eyAi2NjY1Pi9MTExb6iK8zq88847yM/Ph6WlJTIyMqr8HnV/s+vj44MlS5bAyMgIAPDkyRMsW7ZM7a7if5Xs7GwQ1e5P7r/v2uOww8DAANHR0ZBKpdi8eTMePXoEIoKVlRVmzJgBkUgEe3v7av8vqgt///03JBIJNm7ciPT0dIXfVX41+NuFqakpoqKi8OjRI6xdu1bu9zIgIAAWFhbo0aMHEhISWKdyGiB88kn90dfXBxEhOzubdQrnNWndujUMDAwgFArlxtX5c11RUZFsIvTV15Ru3bohIiKCT6y9xcTFxWHq1KkIDw+Xe+4sLS0RGRmJVq1asU58LZYuXYqgoKBafaZT54tBgZeT9wsXLsSuXbvkxr29vfHdd9+hbdu2bMI4NbJ06dIafz/V5eLdhoqDgwPOnDmD0tJSXL9+HQKBAD169ICOjg5cXFxw69Yt1okcDofzVsB83XMul/vmlEqlsr2XK/dheXWfllf3a2Hdyq1eJycnjduTsir19fU1Zq9wT09Pmf7+/pSVlUUHDhyQ7Ut54MABysrKIj8/P+atXHk1dX/wVy0qKiILCwvmHfVlixYtaNKkSfTtt99Sy5YtCQDZ2dnRe++9x7ytrjo4OFBMTIzcHmtSqZRiYmKoR48ezPu4DdeioiLZHrf5+fmyr7t160a5ubnM++qirq6u3Nc1ybq1rrZo0YI2b95MmZmZsteUzMxMCgkJoRYtWjDvU9YxY8bQvn376ODBg7J9zzVJe3t7iomJUXivogmf6y5fvkwzZ84k4OVrSseOHQkAhYSE0OnTp5n3cau3uLiYjI2NZc9d5d8DKysrKigoYN5XFy0tLWn48OEklUrJ09OTPvrooypl3ams8+fPp5KSEgoJCaHx48fT+PHjKSQkhIqKivje9VxuPRkREUFhYWFy5/pEIhH99NNP9McffzDv43K53LdE5gFcLvcNWvmBsvLrmmTdyq1ZU1NTWrFiBR04cEA26evq6kpdunRh3qYKW7duTf369aO+ffvSu+++y7xHlR4+fJhmzJihMD5jxgw6duwY8z5u1erp6VGPHj2oZ8+epKenx7xHlf7xxx80ePBg5h31oY2NDaWnp9Pjx4+pvLxcdjI1ODiYdu/ezbxPWbt3705jxowhDw8P6t69O/MeLlcTJ58kEonCBaH/Vp0nDlu2bEkPHz6kgoIC2rZtG82aNYv8/Pzoxx9/pIKCArp//75a/92bPHkySaVSevjwId2+fZskEgl9++23zLtU6Z07d+jIkSPUq1cv6tChg0Z9ruvTpw/l5eXRli1bqLi4mNavX0/nzp2jgoICsre3Z97Hrd4bN27Q+PHjCZCf0A4KCqKIiAjmfcoYFBREOjo6zDvqUw8PD/rzzz8pKyuLsrKy6M8//yQPDw/mXVxFdXR0aPPmzZSWlkbp6em0f/9+0tfXZ97FfT2Li4vJ0tJSYdzKyoqKioqY93G5XO5bIvMALpfL5b6mTk5OVFRUROfOnaPS0lLZyYG5c+fSoUOHmPcpo66uLu3Zs4cqKipkd5iUl5fT3r17qXnz5sz7VGFBQQGZmZkpjJubm6vt3Qpc9XbMmDF079498vLyInt7e7KxsZGTdZ8ynj9/nlatWkWA/MnUPn36kFgsZt7H5Wqamjj59OrKOE5OTjXKurUurl+/nu7evUsGBgYKx9q0aUN37tyhdevWMe+sq3fv3qXg4GDZYy8vL8rPz2fepUrz8/OrfG+pKVpbW9OuXbsoJiaGYmNjae/evWRtbc28i1uzI0aMoJycHJo3bx4VFhZSQEAAbd++nUpLS2nIkCHM+1Thu+++S3379iVHR0eNuwibqz5+//33VFhYSD/++CNt3LiRMjIy6JdffmHexX09nz9/Ts7OzgrjLi4u9Pz5c+Z9XC6X+5bIPIDL5TK0U6dONHnyZFq8eDEFBgbKybpNWfv371/lstwikYj69+/PvE8Zr127Rv7+/gTIT9D06NGD0tLSmPcp48GDB+nRo0fk4uJCurq61KxZM3JxcaEHDx7QwYMHmfepwqSkJJozZ47C+Jw5cygpKYl5H7fhWd3WE+p8x2Glubm5ZGpqSoD866WxsTGVlJQw7+NyNVE++aReisVicnFxqfa4q6urWl8AVFhYKHvtB0BCoZDKysqoTZs2zNtU5bFjx2j06NHMO7jcf+vi4kKXL1+mgoICKioqoitXrlQ5YaNu6ujoUGhoKJWXl8tdhL1z506NunPb3t6exo8fT+PGjSNbW1vmPaowNDSUmjVrpjDetGlTCg0NZd5XF+Pj42ns2LGyxz179qTy8nISCoXM27i1d+PGjZSSkkKffPIJtW/fngwNDWns2LGUkpJC69evZ97H5XK5b4OC//uCw+E0QHx8fLB161a8ePECz58/B9H/fzkgIjg4ODCsUx6JRIJ27dohMzNTbrxVq1bIyMiAlpYWozLlKSgogI2NDZKSkpCfn4/u3btDLBajQ4cOePjwIXR0dFgn1pnCwkK4urri6tWrcuP9+vXDmTNn0KxZM0ZlqsPLywuhoaE4c+YMIiMjAQC9e/fG0KFD4ePjg927dzMu5DQ0jI2NazyekpLyhkpUz/PnzzF06FDcvn1b7vXS2dkZoaGh//mzczj1SevWrWFgYAChUCg3HhMTw6iI81+Ym5vj448/RseOHUFESExMxIkTJyAWi1mn1ZnS0lKYmZnhyZMnVR43NDREfHy82r6/lEqlaNu2rdxnglf/HmgC+vr62L17N65fv4579+6hoqJC7vjJkycZlSmPJn+m46gv27Ztw5AhQzBz5kzZ59Z+/fph06ZNOH/+PKZPn864UDlat26Nn3/+GQMHDkRubi4EAgFatGiBS5cu4dNPP8WLFy9YJ9aZ6l5T9PX18fz5c2hrazMqqztlZWUwMTHB06dPZWPFxcWwsLBAWloawzLO66CtrY3Vq1dj2rRpsr9tFRUV2Lp1KxYsWIDy8nLGhRwOh/N2wHxWncvlsjEpKYnmzZvHvKO+lEqlVS771alTJ8rLy2Pep4ypqanUp08fAuTvOBw5ciTFx8cz71PG5OTkKu/isrGxodTUVOZ9qrJXr160b98+ioqKoujoaNq3bx/16tWLeReXq2n++OOPdPToUdLS0pLt52tkZERRUVH8SncuM+3t7SkmJka2EoImrYrw6n7Tr9qqVSu1/9kWLFhA5eXlJJFI6OnTp/Ts2TOSSCRUVlZGAQEBzPvqalpaGvXt27fa4/369VPrFYCkUiktXLiQfH19ZRYXF9Py5cvlxlh3KqObmxvl5uZWu+IK6z5ln7+qXlPatWtHxcXFzPu4DdPMzEwaMGCAwvjAgQMpIyODeZ+y/vzzz3Tjxg3q3LmzbMzKyoquX79OBw4cYN5XF3V1dal58+YklUrJ1NSUdHV1Zerp6dGECRPoyZMnzDvrokQiUTj3Vfm5h3Ub9/XV0dEha2trsrGx0agVH7hcLlcV8ju0OZwGTF5eHmxtbTXmzoRKjhw5AgD4+OOPcebMGZSVlcmOiUQidOvWDY8ePcKHH37IKlFpVq1ahT59+sDDwwOPHz+Gvb092rRpgz179mDPnj0IDg5mnVhnJk+eDA8PD3h6euL58+cAgDZt2mD37t04evQotm/fzrjwzTF//nxs27YNeXl5rFM4DQBTU1P4+fnBysoKRIQHDx5g48aNSExMZJ2mFLq6uvj999/RtWtX6Orq4unTp2jbti0iIyMxbNgwFBcXs06sEyKRCIsXL0ZYWBi/80INuXPnDuLj47Fq1Sqkp6fLrZIDqPeqCFXdDQsA7dq1Q0JCApo2bcqoTDkGDhyICxcuYMWKFdi4cSNyc3MBAC1btoSfnx8WLVqEDz74AFeuXGEbWgd27twJc3NzODs7K9zZ26hRI5w9exYJCQnw8fFhVKgcYrFY4f/YvyEimJmZvaEi1SMWi/Hbb79hxYoVyMjIYJ2jEnx9fQEA69evR2BgIAoLC2XHRCIRnJyc0LFjR9jb27NK5FRBdnb2f/5/q0RfX7+ea+qPoqIiODg44OHDh3LjXbp0wfXr19V+VbHc3FwMGTIEN2/elBvv2bMnzp07h5YtWzIqqztSqbTG300iwtKlS/Htt9++wSrVIJVKcfr0ablzX25ubggPD0dRUZFszN3dnUUeh8PhcDgqg09oczgNmJ07d+LGjRv48ccfWaeolLCwMAAvl3X+5ZdfUFJSIjtWXl6OpKQk7NixA1lZWawSlUZLSwu7du3Cp59+CoFAAIlEApFIhAMHDsDb2xv//PMP68Q6Ex0dDXNzczRu3Fh2Qt/Y2BhlZWWIi4uT+151Xxb/v9DUi044bx8uLi749ddfcfv2bVy9ehUCgQCOjo7o3r073NzccOHCBdaJSjNo0CDY29tDKBQiOjoaFy9eZJ2kNAUFBbC2tkZycjLrFM5rkp+fDzs7OyQkJLBOURmaPvn0888/Izc3F9OmTavy+I8//ghdXV2MGzfuDZcpj6GhIW7evImysjL88MMPsgmaLl26YPr06WjcuDF69OjBL555i8nPz4etra3aX4T2KpU/S4cOHZCWlgapVCo7VvmZLigoCNevX2eVyKkCT09P2df6+vpYsmQJzp49K9tmqU+fPnB1dcWKFSuwYcMGRpXKc+HCBWRlZcHT01M2idikSRPs3r0brVq1grOzM+NC5cjPz0f//v1x584duXFbW1v88ccfaNGiBaOyuuPk5ASBQIDw8HC4u7sjOztbdqy8vBzJycl49uwZw8K6U3kO7L+YOHFiPZdwOBwOh1O/8AltDqeBUXmyEQDeeecdzJ49G6dOnUJMTIzCHRkhISFvOk+lBAUFYc2aNWp7911tMDU1hZ2dHYRCIW7duoX4+HjWSUoTFBRU6+9V5zvRa4Om7e/IeXuJjo7G2bNnsXDhQrnxlStXwsXFReMvHlFXjh07huPHj2P37t2sUzivybFjx7B3714cPXqUdYrK0PTJp8TEREyYMEG2V+q/6devH/bs2QNTU9M3XKYaOnbsiC1btsDFxQUCgQDAy7vVzp8/j5kzZ2rUxReayK5du3DlyhWEhoayTlE54eHhGD16tGxVBI76cPjwYVy6dAk//PCD3PiMGTMwZMgQjBo1ilGZ8lhbW+P06dNo0qQJ7ty5AyKCra0tSktL4erqivv377NOVIrjx49DT08Pn332mWyS97333sP+/fuRk5OD0aNHMy6sO8bGxmq9Eg6Hw+FwOA0ZPqHN4TQwanvVvrovu8fhaAJ8QpvzpigpKYGNjY3CRTGdOnXC3bt3oaOjw6hMOQQCAby9vTF69Gh07NgRRASxWIzDhw9j7969rPOUZsqUKVi2bBn279+PqKgouSUFAeDkyZOMyjj/hb6+Pnbv3o3r16/j3r17ChcVqvNzp6mTT0VFRbCwsMCTJ0+qPG5oaIi4uDi1XVK9Ej09PXTq1AkAEB8fj5ycHMZFnNqwaNEi+Pn5aeyFyhz1pKCgALa2tgoXxJibm+PWrVvQ1dVlVKYamjRpgs8//xydO3eGQCDA/fv3sX//fpSWlrJOU5r27dvjxIkTsLa2RmpqKogIxsbGiImJwccff1zt30J1wNvbG4WFhTh8+LDc+JgxY9C0aVPs2bOHURmHw+FwOJz/gk9oczgcjcXAwABr1qzB4MGDYWBgILvbpBItLS1GZcojFArh7e0t+9mEQqHc8cGDBzMq46gSPqHNeVOkpKRg9uzZCid2PDw8sGbNGnTo0IFRmXKcPHkSw4YNw507d/Dw4UMIBAJYWVnBxsYGv/76q1rfGQRA7g7Yf0NEav13TtNxc3PD3r17qzyZz5+7t5Pq9gavxMDAAE+fPuXPHYcJNV20rK4XKq9du7ZW3xcQEFDPJZy6kpSUhM2bN2PNmjVy43PmzMHMmTPRsWNHNmFKoqWlhUePHmHEiBF48OAB65x6ZciQIXIT9pqwZc/Dhw8xbdo0XL58WW7cyckJ27dvR+fOndmEcTgcDofD+U/4p20OhyNDKBTCxsYGycnJGnFXza5du2BsbIwVK1bg2bNnINKc63c2btwIb29vnDp1Cvfu3dOon43D4bx5duzYge3bt8PU1BTXrl0DEaFfv36YP39+rU8ov214e3vDyckJgwcPVjhhNWjQIBw/fhwTJkxQ6zu1RSIR6wROHdm0aRP27t2LFStWICMjg3WOSmgIk08+Pj5ye4O/irrfachRb9R1qfuasLOz+8/v4Z+B3m6WLl2K0NBQDBw4ULaHdu/evTF06FD4+Pgwrqs7EokEjRs31tjfP5FIhNLSUtja2uLChQu4cOEC6ySV0qFDhyovGE9OToaxsTGDIg6Hw+FwOLWF36HN4TRg1q9fj5iYGISFhUEoFCIiIgJ9+vRBcXExRowYgT/++IN1olLk5+ejf//+uHPnDusUlZOZmQlPT0+cPn2adQqnHuF3aHPeJH5+fggICMB7770HAHj69ClWr16NTZs2MS6rG2fPnkV4eDhWrVpV5fGFCxdiwIABGDp06Bsuqx8aN26MsrIy1hmcWpKfnw9bW9tabwWjDoSHh//n9xCR2q4iIxaLazV5oYkTixz1QVtbGyYmJkhISKhxFQ8O503Rq1cvfPXVV7CyspLd5btp0yZcv36ddZpSzJ8/H507d4aPj49G/l+Lj4/H6NGjcffuXdYpKic5ORkzZ85U2N7lo48+wg8//AAjIyNGZRwOh8PhcGoDcbnchmlqaio5ODgQAPr4448pLS2NOnXqRCtWrKA///yTeZ+yxsbGkq2tLfOO+vDJkyfUqVMn5h3c+vXUqVPUtm1b5h3chmWzZs2oWbNmzDuU9dmzZ9S9e/dqj9va2tKzZ8+YdyqjUCikJUuWUFpaGlVUVJCJiQkBoODgYJo4cSLzPm717tq1iyZNmsS8g8ttiLZu3Zq6du1KNjY2crLuUkYdHR3auXMnVVRUyP092LhxI82fP595H7fhqaWlRWFhYbLfRU3z6NGjlJeXR0+ePKEzZ87QkSNH5GTdp6ze3t506tQpatmyJfMWVbtq1SoSi8U0cOBAEgqFJBQKadCgQSQWi2n16tXM+7hcLpfL5VYvv0Obw2nAlJSUwNzcHE+ePMGPP/6I4uJi+Pv7o2PHjrhz5w5atGjBOlEpnJ2dERAQgKlTpyI5OZl1jkqZPXs2TE1NMXPmTNYp9Y6mLYVfiampKb744guYmZlh1qxZyMzMhKurK1JTU3H//n3WeZwGxsWLFzF69Gjk5eXJjevq6uL48eNqeUdlWVkZOnTogOfPn1d5vF27dhCLxWjSpMkbLlMdgYGB8PLyQlBQEHbs2AFra2uIxWJ4eHjA398fjo6OrBM51bBo0SL4+fnh1KlTiImJQUVFhdzxkJAQRmUcjuZib2+P3bt3y+4UBQAigkAgUPu96zds2IC+ffvCz88PZ86cQbdu3SAWi+Hm5obly5fD3t6edSKnAZKTkwN7e3uNXG0qLCysxuMTJ058QyX1Q3R0NMzNzaGtrY3k5GQUFRXJHXdwcGBUpjza2trYu3cvPDw8IJFIALw857Bnzx5MmzZN4T0Zh8PhcDictwc+oc3hNGCSkpIwefJkXLx4EWKxGNOnT8epU6fQpUsX/Pnnn2jVqhXrRKXIzs5G06ZNoaWlheLiYoUPJvr6+ozKlOfo0aMYNGgQsrOzERsbq/Czubu7MypTnn8vhf/HH3/A0dFRY5bCBwAnJyecPn0aV69ehZOTE6ysrCAWizF37lz06tULHh4erBM5DQypVIq2bdsiMzNTbrx169Z48uQJGjVqxKis7kgkErRt2xYvXryo8riBgQGePn2q1hMYcXFxmDp1KsLDw+W2KLC0tERkZKTa/x3XZGpaapyIYGZm9gZrOJyGwZ07dxAfH49Vq1YhPT1dYQn5lJQURmXKk5SUhLFjx+Lvv/+W+3tgZmaG6Ohotb9QmaOehIWFISYmBuvXr2edwnlNli5dWuM2G8HBwW+wpn7o1KkTunfvjpKSEsTExKj13wAOh8PhcBoK6nsGj8PhKM1PP/2EX375Bc+ePQMR4fz58wCA999/Hw8fPmRcpzx+fn6sE+qN3NxcHDt2jHVGvTBmzBjs27cPAODm5gYTExN07twZnp6e+Oabb9CvXz/Ghcrz3XffYcmSJVi/fj3y8/Nl45cuXcKsWbMYlnEaGjY2NrKvu3TpguzsbNljkUiEoUOH4smTJyzSlEYgEGDXrl3V7ivduHHjN1ykegwNDREfH68wLhQKoa2tzaCIU1v4PssczpvHxMQEo0ePRkJCAusUldO6dWtkZGQojL/zzju12vudw6kP4uPjERgYCEdHR0RFRSnc5auOq5EIBAIEBARg5MiR0NbWxoULFxAcHFzt+011Zfny5awT6p24uDjExcWxzuBwOBwOh/Ma8AltDqcBs3z5cty7dw9GRkY4dOgQysvLAby8U++7775jXKc8e/bsYZ1Qb6j7EmY18e6778qWCB42bBgOHTqEuLg4hIaG4quvvmJcpxpsbGwwbtw4hfHMzEy1XjmAo37cvn0bRAQiQnh4uMLxkpIS+Pr6MihTnt27d//n96j734nY2Fj0798f+/fvlxv38PDArVu3GFVxXgdtbW2YmJggISEBUqmUdQ6Ho9FcvHgR3bt318gJ7Rs3bmD48OHYvHkzAMgmsSdPnozIyEiWaUohEomwePFihIWFIS0tjXUO5zXx8fFBbm4uHBwcFJaoJiK1nNCeP38+vv76a1y8eBElJSWYPXs23n33XUydOpV1mkrQ0dHB6tWr5Sbsv/rqK2RlZbFOUxmhoaE1Hp80adIbKuFwOBwOh/O68AltDqeBc+TIEYUxdT/B/yqavE+xSCTCwIEDYWZmhgMHDqCwsBDt2rVDfn6+wtXv6kR6ejq6dOmCZ8+eYejQoZg+fToAoGnTphpzsj83Nxft2rVDUlKS3LidnZ3a3g3LUU9MTEwgEAiQmJiIXr16yS05Xl5ejoyMDPzzzz8MC+uOJl/4U8ny5cuxd+9eGBoaQigUYvTo0bC0tISnpydGjBjBOo9TAzo6OggJCYGXlxcAwMLCAmKxGBs3bsTTp0+xatUqxoV1g08+cd5mfHx8sHv3blhbW+PevXsKW/acPHmSUZnyLFy4EGfOnEGXLl2gpaWFWbNmoWvXrujTpw8GDBjAOq/OSKVSzJ07t1YXqXHePjRxNRJvb2/4+vpi69atAABXV1ccP35cYya0ly9fDm9vb+zfvx+lpaX47LPPsHXrVnzyySes01RGy5Yt5R5ra2vD2toaenp6VV7gy+FwOBwO5+2CuFwuVxN1cnKioqIiOnfuHJWWlpKJiQkBoLlz59KhQ4eY9ymjsbEx3b9/nwoLC6miokL2s61fv562bt3KvE8Zly5dSjk5OXT//n1KSkqiRo0aEQD64osv6Nq1a8z7VOGqVasoIiKC2rRpQ3l5eWRmZkaOjo4UHx9PQUFBzPu4XK766OLiQpcvX6aCggIqKiqiK1eukLOzM/Mubs1u2LCBbty4QX379qWCggLZ33E3NzeKjo5m3qeMBQUF1KFDB+Yd9W3r1q2pa9euZGNjIyfrLm71urm5UW5uLkmlUgUlEgnzPmW1tramXbt2UUxMDMXGxtLevXvJ2tqaeZeyHjt2jLy8vJh3cOuuvr4+tWrVinmHKiwpKSEjIyO5sdLSUnrvvfeYt6nC+Ph4Gjt2rOxxz549qby8nIRCIfO2+lQgENDWrVtp7ty5zFu4XC6Xy+XWKPMALpfLrRevXbtG/v7+BIDy8/NlJ4t79OhBaWlpzPuU8dixY7Rnzx7S1taW+9mcnJzo8ePHzPuU1d3dnfz8/MjQ0FA25unpSR999BHzNlWopaVF+/btI4lEQlKplMrKykgikdCePXs0/mQB9+3U09OThg0bJnu8atUqysnJoatXr5KxsTHzPi5X00xKSqL333+fAPn3KGZmZpSXl8e8Txk1ffLJ3t6eYmJiZH/DKydDNWVSVJMVi8UUEhJCBgYGzFu4tXfKlCn09OlTWr16NX366afk5uYmJ+s+btW2aNGCNm/eTJmZmSSRSEgikVBmZiaFhIRQixYtmPfVValUSu+++67c2Kt/x9XdsrIyhcn54uJiat++PfO2+tbCwoKePn3KvIPL5XK5XG718iXHORyOxqLJ+xT369cPffv2VVgqMTk5GYaGhoyqVEflUviNGzeWjWnSUvgSiQSff/45AgMDYW9vD6FQiFu3biE+Pp51GqeBsmjRInz55ZcAgN69e2PmzJnw8/PDiBEjsH79eri7uzMu5HA0i9atWyMjI0Nh/J133pHtfauunD59GitXroS1tTWioqIUtkFR52WdAeCnn37C48ePMWnSJKSnp6v989WQ0NfXx/r166v8v6fuSCQStGvXTm7rEABo1aoVMjIyoKWlvqd+Kpd2nj17tsIxIlLrn01TadmyJSIjI2FoaIj9+/fjwYMHEAgEsLKygre3NwYPHgxHR0fk5uayTq0TK1asQHFxsexxo0aNsHjxYuTl5cnGAgICWKQpjUgkQnl5udyYRCJpEP/PzMzMGsTPyeFwOByOOsP/UnM4DRSRSITx48fj7NmzSE9PZ51TL2jyPsVCoRAikUhhvH379igoKGBQpDqEQiEWLVqEadOmoU2bNrJ9RYODg5GUlISwsDDWiUoTGBiINWvWQCwWQywWy8abNGmCuXPnYsWKFQzrOA0RIyMj2QUVI0eOxOHDh7Fjxw5cvXoVly9fZhvHkSM7O7vWE2jqfvGWJnPjxg0MHz4cmzdvBgDZczp58mRERkayTFMaTZ98MjExwejRo5GQkMA6hfOaHD16FIMGDUJiYiLrFJUjEAiqHG/cuLHC5JS6UdVnHs7bTVBQEMrLy2FmZqZwAUlQUBDOnTuHoKCgKv9OvO1ERETA0tJSbuzatWty+4Wr84VOAoEAu3btQllZmWysSZMm2LZtm9wFaup8sevatWvlHgsEArRr1w7Dhw/H7t27GVVxOBwOh8OpDep9NoHD4dQZqVSKrVu3wsrKinVKvXHgwAGsWrUKHh4eICIIhUI4OjpizZo1an+37/nz5+Hn54epU6cCePmh+Z133sHy5cvx+++/M65TjsWLF8PLywvz5s3Djh07ZOMxMTHw9/fXiAntpUuXYtu2bSgpKZEbb9q0KZYuXcontDlvnMLCQujr6yM1NRUuLi5Yv349AKC0tBQ6OjqM6ziv4ufnJ/taX18fS5YswdmzZ2WToH369IGrqyt/HXnLWbhwIc6cOYMuXbpAS0sLs2bNQteuXdGnTx8MGDCAdZ5SaPrk08WLF9G9e3c+oa2GPH78GCtXrkS/fv0QExOjsNJRSEgIo7K64+vrC+DlZwEfHx8UFhbKjolEIjg5OeHhw4es8lRO48aN5SbaOG8nI0eOxNSpU6tcDSE9PR3z5s3Dtm3b1HJCe9CgQawT6pWqJnT37dvHoKT+sLOzk3v8zz//IDMzEwEBARpxroHD4XA4HE2H+brnXC6XjeHh4RqzJ3FVavI+xe3ataOHDx9SbGwslZeX07Vr1ygzM5MePHhArVu3Zt6njHFxcfTBBx8QIL8fmaWlJWVnZzPvU4VV7b0GgAYNGkQZGRnM+7gNz3379tHNmzdpx44dVFhYSK1atSIA5ObmRjExMcz7uFV7+PBhmjFjhsL4jBkz6NixY8z7uDVrbW1Nu3btopiYGIqNjaW9e/eStbU18y5V2rhxY+YNqlZfX59+++03CgoKotGjR/P9fNXIxMTEak1ISGDep8zPJJVKKTk5We5nevjwIZ05c4Z69erFvFMZhUIhLVmyhNLS0qiiokL22SA4OJgmTpzIvI+raGlpKRkaGlZ73NDQkEpKSph3crlcLpfL5XLVTuYBXC6XkWPGjKH4+HiaMWMG9e7dm2xsbORk3acqTU1Nyd3dnTw8PMjc3Jx5j6ps0qQJeXt7U0hICP3www80adIkatKkCfMuZS0uLiZjY2MC5Ce0raysqKCggHmfMmZnZ1NWVhZJJBLZ15Xm5uaSRCKhzZs3M+/kNjxbtGhBISEhdPz4cXJ1dZWNL1u2jBYtWsS8j1u1BQUFZGZmpjBubm6u9q+XXPVV0yef3NzcKDc3l6RSqYISiYR5H7dhGh4eTnp6esw76sPAwECKj4+ncePGUVFRkew1xcPDg65du8a8j6toWloa9e3bt9rj/fr1o7S0NOadXC6Xy+VyuVz1UvB/X3A4nAaIVCpVGCMiCAQCjdjjkKOe3LhxAxs2bMD+/fuRn5+P7t27QywWIygoCEOGDIGTkxPrxDrj6ekJgUCAsLAw+Pn5IS8vT3asvLwcSUlJ+OuvvxgWcjgcdSIpKQmbN2/GmjVr5MbnzJmDmTNnomPHjmzCOP+JRCJBu3btkJmZKTfeqlUrZGRkqPV7sMDAQHh5eSEoKAg7duyAtbU1xGIxPDw84O/vD0dHR9aJSiEWi/Hbb79hxYoVVS6ny3n70dbWhomJCRISEqr8PMR5u4iLi8PUqVMRHh4u99nA0tISkZGRaNWqFetEzr/YuXMnzM3N4ezsrLC0f6NGjXD27FkkJCTAx8eHUSGnoREdHV3rvc0dHBzquYbD4XA4HE5dUd8zJRwOR2lMTExYJ9Q7Y8aMwaBBg2BgYAChUCh3zN3dnVGV8rRq1QrZ2dkAgPbt22Py5MnQ0dHByZMnceXKFcZ1yrF8+XLs3bsXhoaGEAqFGD16NCwtLeHp6YkRI0awzlOKyr3bxWIxrl27BolEwriIw3lJ//79azyu7q8rmsrSpUsRGhqKgQMHyvbQ7t27N4YOHcpPEr/lCASCKscbN26M8vLyN1yjWjw9PTFlyhSEh4dj27ZtsvG7d++ic+fODMtUg76+PtavX88ns9UQHR0dhISEwMvLCwBgYWEBsViMjRs34unTp1i1ahXjwtdn7dq1tfq+gICAei6pPwwNDREfH68wLhQKoa2tzaCI818sXboUN2/eRFxcHH744QfZPu5dunTB9OnT0bhxY0yYMIFxJachcfz4cdnXTZo0wfTp03H//n25989du3bFli1bGBVyOBwOh8OpDXxCm8NpwKSkpLBOqFc2btyIKVOm4NKlS0hPT6/1FblvM9bW1jh58iSMjIwQFxeHTz/9FGfOnME777yDf/75B/7+/hgzZgxOnDjBOrXO/Pbbbxg7diwWLVoEIkJwcDCio6Ph5uaGCxcusM5TCREREbKvmzRponAyrqCg4E0ncRo4ly9fVhh79TVTne8W1WR2796NBw8e4KuvvsLo0aMhEAhw//599O3bF9evX2edx6kCX19fAC//f/n4+KCwsFB2TCQSwcnJSXbiX13R9Mmno0ePYtCgQUhMTGSdwnlNVq5cie7du2PgwIE4c+aMbPzChQtYvny5Wk5o29nZ/ef3qPtnoNjYWPTv3x/79++XG/fw8MCtW7cYVXFq4smTJ+jTpw+2bNmClStXyi7iIiKcP38eM2fORFpaGuPKuiMSibB48WKEhYWp9c/RkAgODpZ9vWPHDmzatAlBQUFy37Ns2TIYGRm96TQOh8PhcDivCfN1z7lcLjtNTU1p06ZNdP78eTp37hxt3LiRTE1NmXepwqysLPrwww+Zd6jS33//nX799Vfq27cvbd26lVJTUyk0NJQEAgEJBALavHkzRUZGMu/k1qyOjg6FhIRQeno6SSQSBVn3cRuezZs3l1NfX5+GDBlCkZGR9MEHHzDv4yqqpaVFYWFhsr1EuephYmIiJSYmklQqpeTkZNnjxMREevjwIZ05c4Z69erFvFMZb9y4QePHjycAlJ+fL/sdDQoKooiICOZ9yrpo0SLKyMign376iWbPnk2+vr5ysu7jVm9SUhK9//77BMj/bpqZmVFeXh7zPm7VjhgxgnJycmjevHlUWFhIAQEBtH37diotLaUhQ4Yw7+PWrJ6eHvXs2ZN69uxJLVu2ZN6jKgsKCqhDhw7MO7ivb25uLpmbmyuMm5ubU25uLvM+LpfL5XK5Nco8gMvlMtLFxYVKS0vpr7/+orVr19K6devor7/+opKSEo04OZCYmEiWlpbMO1RpZmYm2djYEAB65513SCqVkoODg+y4paUl5eTkMO/k1uzmzZspNjaW3N3dqaioiLy9vWnx4sWUkpJC48aNY97H5Vbav39/unnzJvMObtXm5OTwCW01NTw8nPT09Jh31IeaPvn06kUI/zYhIYF5H7d6i4qKZK+Zr05od+vWjU9ivOW6uLjQ5cuXqaCggIqKiujKlSvk7OzMvIvbcD127Bh5eXkx7+C+vs+ePSNvb2+FcW9vb3r+/DnzPi6Xy+VyuTXKPIDL5TIyOjqaVq5cqTC+cuVKioqKYt6nrJ6ennTgwAFq0qQJ8xZVKZVKqXXr1rLHr56MA0AGBgZqeYdvdnY2ZWVl1UrWraowOTmZBgwYQAAoLy+PzMzMCAB9/vnndOrUKeZ9XG6lnTt3poKCAuYd3KoNCwsjf39/5h1c7r/lk0/ct9HLly/TzJkzCXj5Hrpjx44EgEJCQuj06dPM+7hcrvo4ZcoUevr0Ka1evZo+/fRTcnNzk5N1H7d658+fTyUlJRQSEkLjx4+n8ePHU0hICBUVFdH8+fOZ93G5XC6Xy61ewf99weFwGiAlJSWwsbFR2OewU6dOuHv3LnR0dBiVqQYdHR0cPXoUffv2RVJSEioqKuSOOzg4MCqrO1KpFG3atMGLFy8AAPn5+ejWrRuSkpIAAAYGBnj69Kna7Xfr6elZ6+/ds2dPPZa8GQoKCtC1a1ekpKQgNTUVo0ePxo0bN9CxY0fExMRAV1eXdSKngWFjYyP3WCAQoF27dliwYAG0tbXRr18/RmWcmli0aBHmzJmDixcvIioqCkVFRXLHQ0JCGJVxqmPt2rW1+r6AgIB6LuEoi7a2NkxMTJCQkACpVMo6h1ML+vTpgzNnzmD//v3w9vbGjz/+iK5du6JPnz4YMGAAoqOjWSdyOBw1oabXfSJSu8/jDQ0PDw/MmjULVlZWAIAHDx5g48aNOHToEOMyDofD4XA4NcHfYXE4DZjMzEzY2toqTGjb2toiIyODUZXq2LVrFxwcHLBv3z6kp6eDSDOu39m1axfKysoAAE2aNMG2bdtkkxiNGzdmmVZnNGGS+nVITExEx44dkZKSgvv37+OTTz7BjRs34Obmhry8PNZ5nAbI7du3QUQQCARy43/99RcmTpzIqIrzX/j4+CA3NxcODg4KF2kREZ/Qfguxs7P7z+/RlPcrmoqOjg5CQkLg5eUFALCwsIBYLMbGjRvx9OlTrFq1inEhpzoiIyPRt29fzJkzBwkJCXBxcUF0dDT69OmDe/fusc7jvEJ2dnatXwv19fXruYbDUUQkErFO4CjBoUOH+OQ1h8PhcDhqCL9Dm8NpwAQGBsLf3x/fffcdrl27BiJCv379MH/+fKxduxbffPMN60SlKCwshKurK65evco6RWWEhYXV6vs0ZQKqSZMm0NbWlhsrKChgVKM6/Pz8IJVKERISgoEDB+LUqVMQiUTQ0tLC7NmzsWnTJtaJnAaGsbGx3ON//vkHmZmZsotnOBwOpyYa0uTThg0b0LdvX/j5+eHMmTPo1q0bxGIx3NzcsHz5ctjb27NO5DQwRCIRFi9ejLCwMKSlpbHOUQmvrt6kr6+PJUuW4OzZs4iMjATw8m57V1dXrFixAhs2bGBUyeG8pHHjxvw9sxpib28PKysrEBHu37+P27dvs07icDgcDodTC5ive87lctnp5+dHqampJJVKSSqVUmpqKn311VfMu1ThgwcPyMbGhnkH9/Vs2rQphYSEUHp6OkkkEgVZ99WHRkZGNGrUKOrXrx+FhoYy7+Fyueqlvr4+tWrVinkHt+Hq6ekp09/fn7KysujAgQPk6+tLvr6+dODAAcrKyiI/Pz/mrcqalJRE77//PgEv92E2MTEhAGRmZkZ5eXnM+7jVK5FIqHXr1grjrVq1Uvv3mAUFBdShQwfmHfXh4cOHacaMGQrjM2bMoGPHjjHv4zZMhUIhLVmyhNLS0qiiokL2tyA4OJgmTpzIvI9bva1bt6aLFy+SVCqlrKwsys7OJqlUShcuXKB3332XeR+Xy+VyudwaZR7A5XLfoG5ubqSlpaUw3qxZM2rWrBnzPlU6bNgwOn36tMae3NFUN2/eTLGxseTu7k5FRUXk7e1NixcvppSUFBo3bhzzvvq0W7duan9ClateDho0iGJjY0lXV1fhWPPmzenevXvUr18/5p1cRVu0aEGbN2+mzMxM2QU/mZmZFBISQi1atGDex224avrkU1FRkWzi4tUJ7W7dulFubi7zPm71SqXSKie027VrR8XFxcz7lPHYsWPk5eXFvKM+LCgoIDMzM4Vxc3NzKigoYN7HbZgGBgZSfHw8jRs3Tu7vgoeHB127do15H7d6f/75Z7px4wZ17txZNmZlZUXXr1+nAwcOMO/jcrlcLpdbvXwPbQ6ngXHs2DG0bdsWL168gEQiQbt27ZCZmYnCwkLWaSpn3759aNq0KRISElBcXIyKigq54+q+5KWm4ubmBk9PT/zxxx8ICwvDlStXkJCQgOTkZIwfPx4HDhxgncjhaAx+fn7YsWNHlUv55+fn48cff8Ts2bPx559/MqjjVEfLli0RGRkJQ0ND7N+/Hw8ePIBAIICVlRW8vb0xePBgODo6Ijc3l3UqpwHi6uqK+fPnK4yfPXsW3333HYMi1XLjxg0MHz4cmzdvBgDZUuuTJ0+WLYfMebvw9fUF8PK58vHxkfvcIxKJ4OTkhIcPH7LKUwmnT5/GypUrYW1tjaioKBQVFckdP3nyJKMy5cnKysKoUaOwZs0aufGRI0ciKyuLURWnoePp6YkpU6YgPDwc27Ztk43fvXsXnTt3ZljG+S+GDh2KIUOGyL3uP3jwADNmzMC5c+cYlnE4HA6Hw/kv+IQ2h9PAyMzMRO/evfHbb79BIBDUer9DdcTPz491AqcOtGrVCmKxGMDLCbVWrVohISEBf/75J7Zu3cq4jsPRLLp3717lxFMl586dw5w5c95gEac2BAUFoby8HGZmZsjIyFA4du7cOQQFBWH27NmMCjkNGU2ffFq4cCHOnDmDLl26QEtLC7NmzULXrl3Rp08fDBgwgHUepwr8/f0BAAKBANOmTYNUKpUdKy8vR1JSEqZNm8YqTyVUvkeu6nWfiKClpb6nfpYuXYrQ0FAMHDhQdtFI7969MXToUPj4+DCu4zRUDA0NER8frzAuFAqhra3NoIhTW4RCocLNDgBQUVEBoVDIoIjD4XA4HM7rwPw2cS6X++ZcunQpSaXSKvcmbgh7FXPffu/cuUNOTk4EgM6ePUurV68mAOTr60upqanM++pTvuQ4901bUlJS5TKelZqZman9MqyaqFgsJhcXl2qPu7q6klgsZt7JrVqRSERBQUHUvn175i31oZeXF0kkEvrtt99o8eLFtHjxYjp58iRVVFRozJLI1tbWtGvXLoqJiaHY2Fjau3cvWVtbM+/i1mx4eDjp6ekx7+C+vr169aJ9+/ZRVFQURUdH0759+6hXr17Mu7gN1xs3btD48eMJkN9+IigoiCIiIpj3cav3+PHjdPnyZWrXrp1s7L333qNLly7R0aNHmfdxuVwul8utXsH/fcHhcBoQlpaWMDc3x6+//oovvvii2iVJf/311zcbVg8IhUKMGjUKVlZWICI8ePAAJ06ckLszg/N24efnB6lUipCQEAwcOBCnTp2CSCSClpYWZs+ejU2bNrFOrDNHjhyp8bienh4GDBig1nfRcNSL+Ph4zJkzB8ePH6/yeOVdlmZmZm82jFMjpaWlMDMzw5MnT6o8XnnXkI6Ozhsu49SWgoICWFtbIzk5mXVKvdCrVy989dVXsLKygkAgwP3797Fp0yZcv36ddRqHo/E0btwYZWVlrDNUgpaWFrZv344VK1bIVnDicN4GRowYgb1792LlypUICgrC0qVLYWlpCU9PT4wYMQIXLlxgnciphvbt2+PEiROwtrZGamoqiAjGxsaIiYnBxx9/XO37aw6Hw+FwOOzhE9ocTgMmKCgIq1evRklJCeuUeqFr1644ceIE2rZti0ePHgEALCwskJmZiY8++gj37t1jXMipDcbGxnBwcEBCQgLu3r3LOkcpwsLCavV9EydOrOcSDuclmzZtwsCBA9GzZ0+Fk99NmjTB9evXcenSJcyaNYtRIacq0tLSMHbsWFy9erXK4/369cPPP/+M9u3bv+EyTm05duwYjh8/jt27d7NOUSkNYfJJIpGgXbt2yMzMlBtv1aoVMjIy+EVpbyFr166t1fcFBATUc0n9IRQKsWjRIkybNg1t2rSBhYUFxGIxgoODkZSUVOv3oG8jOTk5sLe319jXFI764uLigkWLFsHBwQFCoRDR0dEIDg7G+fPnWadxasGQIUPQuXNn2YV3Fy9eZJ3E4XA4HA7nP+AT2hwOR2OJjIxERkYGvLy8ZHeh6+npYdeuXTAwMICjoyPbQA6Hw2GMgYEBoqOjIZVKsXnzZjx69AhEBCsrK8yYMQMikQj29vYK+zRz2LJz506Ym5vD2dlZYQ/ARo0a4ezZs0hISOB7i77FTJkyBcuWLcP+/fsRFRWFoqIiueMnT55kVKY8mj75JJVK0bZtW4UJ7Xbt2iEhIQFNmzZlVMapjvDw8P/8HiLC4MGD30BN/RAYGAgvLy8EBQVhx44dsLa2hlgshoeHB/z9/dX6c09YWBhiYmKwfv161ikcDkfNEYlEKC0tha2tLWJjY1nncDgcDofDeU34hDaHw9FYiouL0aNHD9y/f19uvGvXrrhx4wY/4fiW0atXL7Rq1QpnzpyRjU2YMAHLly/HO++8g+PHj8PX1xfl5eUMKzkczcPY2Bhbt26Fq6srBAIBgJcn9s+ePYvp06dr7JLI6oyhoSFu3ryJsrIy/PDDD3j48CEAoEuXLpg+fToaN26MHj16IC0tjXEppzpq2vqEiNT6Ll9NnXzy9fUFAKxfvx6BgYEoLCyUHROJRHByckLHjh1hb2/PKpHTgImLi8PUqVMRHh6O/Px8dO/eHWKxGJaWloiMjESrVq1YJ9aZRYsWYc6cObh48WKVFwCFhIQwKuNwOOpIfHw8Ro8erfarv3E4HA6H0xBR3zMlHA6H8x88evQIbdq0UZjQNjAwQHx8PKMqTnUsW7YMly9flk1oW1tbIzQ0FLt27cKDBw8wd+5cPH36FMuXL2dcyuFoFikpKRg+fDj09PRgbm4OgUCAuLg42coWnLePJ0+eoE+fPtiyZQtWrlwpdyHC+fPnMXPmTD6Z/ZYjEolYJ9Qb8fHxCAwMhKOjo0ZNPvn7+wMABAIBpk2bJndRQnl5OZKSkjBt2jRWeZwGjqGhYZWfb4RCIbS1tRkUqQ4fHx/k5ubCwcEBDg4OcseISG1fUzjqR3Z2Nohqd0+Qvr5+Pddw6srXX3+NlStX4vPPP0dOTg7rHA6Hw+FwOK8Bv0Obw+FoLB9++CG+//57LFu2DH/99RcAoHfv3ggKCsKCBQvw559/yr63oKCAVSbn/3j69Cnc3NwQFRUF4OUHzQEDBqB///4AgDFjxmD58uXo2rUry0wOh8N5q9DT00OnTp0AvJxI5Cfm1I/GjRsr7GGvziQmJlZ7jIhgZmb2BmtUT3h4OEaPHs0v+uG8Vdy4cQMbNmzA/v375e7QDgoKwpAhQ+Dk5MQ6kcNRezw9PWVf6+vrY8mSJTh79iwiIyMBAH369IGrqytWrFiBDRs2MKrk/BfR0dEwNzeHtrY2kpOTFS68+/eFMxwOh8PhcN4e+IQ2h8ORo0WLFsjLy2OdoRJevXOm8krqV+9iq3ys7kt7agolJSXo1KmT7K7CK1eu4MyZM/jmm28AAB06dEBMTAyaN2/OMpPD4XA4HKURCoVYtGgRpk2bhjZt2sDCwgJisRjBwcFISkpCWFgY60QOh6NGjBgxAnv37sXKlSsRFBSEpUuXwtLSEp6enhgxYgQuXLjAOlFp9PX1QUTIzs5mncLh4PDhw7h06RJ++OEHufEZM2ZgyJAhGDVqFKMyzn+xdOnSGu+0Dw4OfoM1HA6Hw+FwXgc+oc3hNGDmzZuHpKQk/PLLLwCAgwcPwt3dHc+fP8ewYcPUfk+h17kTISIioh5LOLUhKSkJEyZMwJUrV6CtrY3c3Fy4ubkhPDwcwMslyP/44w++fBuHw+Fw1J7AwEB4eXkhKCgIO3bsgLW1NcRiMTw8PODv7w9HR0fWiUqjaZNPa9eurdX3BQQE1HMJh1M1Li4uWLRoERwcHCAUChEdHY3g4GCcP3+edVqdadGiBb755huMHTsWLVu2BADk5OTg559/xpIlSzTmQmyO+lFQUABbW1skJCTIjZubm+PWrVvQ1dVlVMbhcDgcDoejufBbEjmcBszUqVPx+eefAwCGDBkCZ2dnfPjhh/jkk0+wevVquLq6Mi5UDj5JrV6cOXMG3333HebPn4+RI0eiuLgYV65ckR3v1q2bwgkDDofD4XDUEU9PT0yZMgXh4eHYtm2bbPzu3bvo3LkzwzLl0OTJJzs7u//8ntrurcp584hEIixevBhhYWGy1YA0jXPnzuHcuXOsM1RGy5YtERkZCUNDQ+zfvx8PHjyAQCCAlZUVvL29MXjwYDg6OvLl/zlMyMrKwqhRo7BmzRq58ZEjRyIrK4tRFacmdHR0sHr1aowcORLa2tq4cOECvvrqK/58cTgcDoejRvAJbQ6nAdOuXTukpqYCeLlM3S+//ILz588jKSkJf//9N+O6umFjY4N79+6BiGBjY1Pj98bExLyhKk5tWLJkCY4ePYo//vgDhYWF8PLyQkVFhez4xIkTNeokHYfD4XAaLoaGhoiPj1cYFwqF0NbWZlCkPJo++fTBBx+wTuAogVQqxdy5c7F7927WKZxaEhQUhPLycpiZmSEjI0Ph2Llz5xAUFITZs2czKuQ0ZJYuXYrQ0FAMHDhQtod27969MXToUPj4+DCu41TF8uXL4e3tjf3796O0tBSfffYZtm7dik8++YR1GofD4XA4nNeAuFxuw/TJkyfUp08fAkAPHz6kMWPGEACysLCgvLw85n11USqVUuvWrWVfSyQSkkqlCkokEuat3Kpt3rw5CYVChfGWLVuStrY28z4ul8vlcpX1xo0bNH78eAJA+fn5ZGJiQgAoKCiIIiIimPfVxfXr19Pdu3fJwMBA4VibNm3ozp07tG7dOuad3IbrsWPHyMvLi3mHqszOzqasrKxaybq1LorFYnJxcan2uKurK4nFYuad3IZrr169aN++fRQVFUXR0dG0b98+6tWrF/MubtXGx8fT2LFjZY979uxJ5eXlVZ574HK5XC6X+3bK79DmcBowR48exYEDBxAXFwd9fX2cPn0aAGBra1vlXUPqgImJCTIzM2Vfc9SP/Pz8KsdzcnLecAmHw+FwOPXD8uXLsXfvXhgaGkIoFGL06NGwtLSEp6cnRowYwTqvTowcORJTp05VuJMSANLT0zFv3jxs27aN303JYcbp06excuVKWFtbIyoqCkVFRXLHT548yaisbvj5+cm+1tfXx5IlS3D27FnZ3aJ9+vSBq6srVqxYwahQOdq1a4fY2Nhqj9+7dw9t27Z9g0Uczku0tLSwfft2rFixQraFG+ftx8jISG5Lsxs3bkAikeC9997T2K0oOBwOh8PRRJjPqnO5XDZqaWlRQEAAbdiwgWxtbWXjs2bNokmTJjHv43K5XC6Xy9VUXVxc6PLly1RQUEBFRUV05coVcnZ2Zt5VV0tLS8nQ0LDa44aGhlRSUsK8k9twrWrVJk1Zvenw4cM0Y8YMhfEZM2bQsWPHmPfVxbS0NOrbt2+1x/v160dpaWnMO7kN05ycHNnqKlz1UCKR0Lvvvis3lp+fTx07dmTexuVyuVwut3YK/u8LDofTAGnatCmKi4tZZ9QrnTp1wsCBA2FgYAChUCh3TF3vVuBwOBwOh8N520hLS8PYsWNx9erVKo/369cPP//8M9q3b/+GyzgczaegoAC2trZISEiQGzc3N8etW7egq6vLqKzu7Ny5E+bm5nB2dkZFRYXcsUaNGuHs2bNISEjg+xVzmBAWFoaYmBisX7+edQqnlkilUpw+fRplZWWyMTc3N4SHh8ut2OHu7s4ij8PhcDgcTi3gS45zOA2Y9PR0/PLLLwgLC6v25KM64+Pjg61bt+LFixd4/vw5iP7/9TtExCe0ORwOh8PhcFTEmTNn8M0331Q7+bRixQqcOXOGUZ1qEIlEWLx4McLCwvjypGpO48aN5SY11J2srCyMGjUKa9askRsfOXIksrKyGFUpx9KlS3Hz5k3ExcXhhx9+wMOHDwEAXbp0wfTp09G4cWNMmDCBcSWnoRIfH4/AwEA4OjpWuYVBSEgIozJOdezevVthbN++fQxKOBwOh8Ph1BV+hzaH04AZMWIEvL29MWLECCQnJyMsLAx79uzBs2fPWKephKSkJGzZsgXff/896xQOh8PhcDgNnOzsbLmL62pCX1+/nmtUj6GhIW7evImysrJqJ5969Oih9hPBBQUFsLa2RnJyMusUzmsiFAqxaNEiTJs2DW3atIGFhQXEYjGCg4ORlJSEsLAw1ol1xsvLC6GhoThz5oxsD+3evXtj6NCh8PHxqXIiRx3o2LEjtmzZAhcXFwgEAgAvL0w+///au/+Yqu97j+Ovgwjq1iCwFPWk7lBwesisxFpjca22KrBON3G1RrueYkPqgtQobWxr/LGVsLnajBaKsVboOotzmxlOYxGsrU27kSr+nugicGy1WgQ8WKTKysnn/tF7zWWCUn+cjxyej+SVHD7v88crIRqP7/P9fnfsUFZW1hVXpAOBUldX1+XMGKO4uLgAtgEAAOgdWGgDUFRUlDwej9LT05WQkKDy8nIVFxdry5Yt8vv9tutdt/PnzysxMVFer9d2FQAA0Mt5PJ7Lr6Ojo7V06VKVl5dfXj7df//9SklJUU5Ojl599VVLLW9Mb1g+lZaWavPmzT12QdibLVu2TE8++aSWL1+uN998Uz/84Q/l9Xo1c+ZMLVq0SElJSbYr3pCxY8dqwYIFcrvdcjgcqq6uVn5+vnbv3m272g0bOHCghg0bJumbK2N9Pp/lRgAAAAACjYU2gA6ysrK0atUqhYWFqbGxUWvWrNHKlSt18eJF29W+tXXr1mnPnj164403bFcBAAC4bNOmTfrggw9UWFjY4Xz+/PmaPHmy0tLSLDW7OYJ5+fT000/rV7/6lUpKSjq9zezWrVstNcO1HD9+XPPmzdP777+vL7/8UqNGjZLX69Xw4cNVWVmpqKgo2xWvS2hoqNauXaucnBy+yAsEWHR0tIwxOnfunO0qAAAAQY+FNgDFxMTI4/Fo7ty5Gjp0qEpLS1VUVKQhQ4bohRde0JkzZ5SSkmK7Zrc888wzl19/5zvfUXZ2trZt26bDhw9f8TxHnmsFAABsaGlpUWJi4hVXLMfHx2v//v264447LDXDtVzt7kXGGIWGhgawDb6Nr776SiNGjNBnn33WYaHtdru1e/fuHv3nzufzafTo0Sy0gQCIiIhQbm6uZs2apcjISEnf/BncuHGjli5dqvPnz1tuCAAAEJz4tA30YmlpaZo7d65SUlJUXV2twsJCvfPOOx0+gB04cED79++32PLbWbRoUYefL1y4oAkTJmjChAkdzo0xLLQBAIAVTU1NSktL0yuvvNLhfPr06WpqarLUCt3Rp08f2xVwnY4cOaIHHnhAJSUlHc5nzpzZoz7vdKa0tFTTp09XXl6e7SpAUIuMjFRlZaWcTqdKSkp09OhRORwOud1upaena9KkSUpKSlJzc7PtqgAAAEGHhTbQi7311lvauHGjxo8fr6qqqk7fU1dXp9zc3AA3u35333237QoAAABXtWLFChUVFWnixImXn6E9btw4paamKiMjw3I7dFd4eLja2tps10A3/frXv9b69evldDoVEhKiGTNmaPjw4fJ4PJo6dartejekpqZGy5YtU1JSUqe3wueLvMDNsXz5cv3nP/9RXFyczp49e8WsoqJCy5cvV3Z2tqWGAAAAwYtbjgO9WP/+/Xvks7GvV0hIiEaOHKlPP/2Ub0wDAACrxo4dqwULFsjtdsvhcKi6ulr5+fnavXu37Wq4ipCQEC1ZskS//OUvFRMTox/84Afyer166aWXdOLECRUXF9uuiKtITk7WkiVLdO+99yokJET79u3TSy+9pB07dtiudkPq6uq6nBljFBcXF8A2QPDyer2aN2+eKioqOp2npKRozZo1io2NDXAzAACA3sEQQki/fv3MHXfc0SG2O91o8vLyzFNPPWUkmZCQEPPxxx8bv99vWlpazIQJE6z3I4QQQkjvS2hoqCkuLjaxsbHWu5Bvn2XLlpmamhozZ84c09raevn3OHPmTPPPf/7Tej9CCCG3LpcuXTJOp7PLudPpNBcvXrTekxBCCCEkGBMiAL3WgAEDVFBQoPr6el24cEE+n69DerpHH31UBw8elCRNmzZNLpdLI0aM0KuvvtqjbqMOAACCR3t7u9LS0mzXwHXyeDx6+umntWHDBvn9/svnhw4d0ogRIyw2A6To6GhFRUXZrgEErcbGRrlcri7nsbGxampqClwhAACAXoSFNtCLvfzyy3r44YeVmZmptrY2ZWRkaMWKFTp9+rQ8Ho/tejfse9/7nr744gtJ0iOPPKK//vWvOn78uIqKijRy5EjL7QAAQG9VWlqq6dOn266B6+B0OlVTU3PFeUhIiPr27WuhEa7m3Llzampq6lZ6qoiICL3++utqaGhQfX29zp49q4aGBhUUFCgiIsJ2PSCobN++Xbm5uZ3+fR8WFqacnBxt377dQjMAAIDgF2q7AAB7pk2bJo/How8//FDFxcX66KOPVFtbq08//VSPP/64NmzYYLviDamvr1dCQoLOnDmj1NRUZWZmSvrmyvT/f0UNAABAINXU1GjZsmVKSkrS3r171dra2mFeUFBgqRmu5ciRI3rggQdUUlLS4XzmzJnav3+/pVboysKFCy+/jo6O1tKlS1VeXq7KykpJ0v3336+UlBTl5ORYanhjIiMjVVlZKafTqZKSEh09elQOh0Nut1vp6emaNGmSkpKS1NzcbLsqEBRWrFihqqoqHT9+XIWFhTp27JgkKSEhQZmZmQoPD9cTTzxhuSUAAEDwsn7fc0KInbS0tJihQ4caSebkyZPmvvvuM5KMy+UyLS0t1vvdaFasWGF8Pp+prq42J06cMGFhYUaSmTt3Ls84JIQQQoi11NXVdZna2lrr/UjXmTp1qvH5fGbx4sXmwoUL5tlnnzVr1641ly5dMpMnT7bej3SdTZs2mfnz519xPn/+fFNaWmq93/UkLy/PHDp0yNx5551XzGJiYszBgwfN73//e+s9CQmmuFwu8+6775r29nbj9/uN3+837e3tpqyszMTFxVnvRwghhBASxLFegBBiKQcPHjQPPvigkWTKy8vNqlWrjCTzzDPPmJMnT1rvdzPy85//3CxcuNA4nc7LZx6Px/z0pz+13o0QQgghhPS8JCcnm127dpmWlhbT2tpqPvroIzNlyhTrvcjV09LS0umyKT4+vsd+mdfr9Zrk5OQu5ykpKcbr9VrvSUgwZuDAgea+++4z9913n4mMjLTehxBCCCEk2OP43xcAeqGFCxfK7/eroKBAEydO1LZt29SnTx+FhoYqOztb+fn5tisCAAAErejoaBljdO7cOdtVgKB34sQJvf7663rllVc6nD/33HPKysqSy+WyU+wGXLp0SXFxcfr88887nf/fM9/79+8f4GYAAAAAcHPxDG2gF3v11Vcvv961a5dGjBihMWPGqLa2VocOHbJXDAAAIEhFREQoNzdXs2bNUmRkpCTJ5/Np48aNWrp0qc6fP2+5IRCcVqxYoaKiIk2cOPHyM7THjRun1NRUZWRkWG53fRobG+VyubpcaMfGxqqpqSnArQAAAADg5uMKbQAAAAAIgMjISFVWVsrpdKqkpERHjx6Vw+GQ2+3WnDlzdPLkSSUlJam5udl2Vfw/586dkzHd+9gcHR19i9vgRowdO1YLFiyQ2+2Ww+FQdXW18vPztXv3btvVrsu6desUHx+vKVOm6Ouvv+4wCwsLU3l5uWpra3vswh4AAAAA/g8LbaCXcjgcSk9P14wZM+RyuWSMkdfr1aZNm7R+/Xrb9QAAAIJOXl6eJk2apMmTJ+vs2bMdZjExMaqoqNDOnTuVnZ1tqSE64/F4Lr+Ojo7W0qVLVV5efvkq3/vvv18pKSnKycnpcAck3D5CQ0O1du1a5eTkyOv12q5z0zidTlVVVamtrU2FhYU6duyYJCkhIUGZmZkKDw/XmDFjdOrUKctNAQAAAODGWX+QNyEk8Nm6davx+/1m3759ZsOGDeZPf/qTOXDggPH7/aa0tNR6vxtNnz59jMfjMTExMda7EEIIIYRIMl6v1yQnJ3c5T0lJMV6v13pP0nU2bdpk5s+ff8X5/Pnzg+Lf0MEcn89nYmNjrfe42XG5XObdd9817e3txu/3G7/fb9rb201ZWZmJi4uz3o8QQgghhBBCbka4QhvohdLT0/Xaa6/pZz/7mXbt2tVh9tBDD2nz5s3Kysrq8Vdqt7a2yu1267PPPrNdBQAAQJcuXVJcXFyXz7t1Op2qqalR//79A9wM3dXS0qLExETV1tZ2OI+Pj9f+/ft1xx13WGqGaykuLtbhw4eVl5dnu8otMXDgQA0bNkySVFNTI5/PZ7kRAAAAANw8obYLAAi82bNn6ze/+c0Vy2xJ+uCDD7Ry5Uo9/vjjPX6h/cknnygxMZGFNgAAuC00NjbK5XJ1udCOjY1VU1NTgFvh22hqalJaWppeeeWVDufTp0/nd3ebq6mp0bJly5SUlKS9e/eqtbW1w7ygoMBSs5ujublZe/bssV0DAAAAAG4JrtAGeqEzZ84oNTVVBw8e7HSemJiosrIyDR48OMDNbq5HH31UK1euVF5eXqf/aXX48GFLzQAAQG+0bt06xcfHa8qUKfr66687zMLCwlReXq7a2lplZGRYaohrefLJJ1VUVKTt27dffob2uHHjlJqaqoyMDL399tuWG6IrdXV1Xc6MMYqLiwtgGwAAAADAt8FCG+iF2tra9P3vf19ffPFFp/PBgwfL6/WqX79+AW52c/n9/ivOjDFyOBwyxig0lJtUAACAwHE6naqqqlJbW5sKCwt17NgxSVJCQoIyMzMVHh6uMWPG6NSpU5ab4mrGjh2rBQsWyO12y+FwqLq6Wvn5+dq9e7ftagAAAAAABCUW2kAv1N7erkGDBqmxsbHT+Z133qnTp0/3+IXv0KFDrzrnVuQAACDQXC6XVq9ereTkZDkcDknffOFux44dysrKuuLZzLh9hIaGau3atcrJyZHX67VdB9cpOjpaxhidO3fOdhUAAAAAQDex0AZ6Ib/fr7KyMrW1tXU6Dw8PV2pqao9faAMAANyuBg4cqGHDhkn65tm+Pp/PciN0h8/n0+jRo1lo9zARERHKzc3VrFmzFBkZKemb3+XGjRu1dOlSnT9/3nJDAAAAAMDVsNAGeqHi4uJuve+pp566xU1uvbvvvlsLFy6U2+2WMUZHjx7Va6+9dtVn6AEAAACdKS4u1uHDh5WXl2e7CropMjJSlZWVcjqdKikp0dGjR+VwOOR2uzVnzhydPHlSSUlJam5utl0VAAAAANAFFtoAglZycrK2bNmiAwcO6B//+IccDoeSkpI0atQoTZs2Te+9957tigAAAOhBlixZoueee047d+7U3r171dra2mFeUFBgqRm6kpeXp0mTJmny5Mk6e/Zsh1lMTIwqKiq0c+dOZWdnW2oIAAAAALgWFtoAgta+fftUXl6uF198scP5b3/7WyUnJ+vee++11AwAAAA90dXu8mOMUVxcXADboDu8Xq/mzZunioqKTucpKSlas2aNYmNjA9wMAAAAANBdLLQBBK2LFy9q5MiRqqmp6XA+bNgwHTp0SP3797fUDAAAAEAgXLp0SXFxcfr88887nTudTtXU1PDZAAAAAABuYyG2CwDArdLQ0KDExMQrzhMTE6+43SAAAADQXdHR0YqKirJdA93Q2Ngol8vV5Tw2NlZNTU2BKwQAAAAA+NZYaAMIWm+++abWrl2rxYsX60c/+pHGjx+v559/Xm+88YbWrl1rux4AAAB6kIiICL3++utqaGhQfX29zp49q4aGBhUUFCgiIsJ2PXRh+/btys3NVd++fa+YhYWFKScnR9u3b7fQDAAAAADQXdxyHEBQW7hwoZ599lkNGTJEknT69GmtWrVK+fn5lpsBAACgp4iMjFRlZaWcTqdKSkp09OhRORwOud1uzZkzRydPnlRSUpKam5ttV8V/cTqdqqqqUltbmwoLC3Xs2DFJUkJCgjIzMxUeHq4xY8bo1KlTlpsCAAAAALrCQhtAUJk2bZrKysrU3t7e4fy73/2uJOnChQs2agEAAKAHy8vL06RJkzR58uQrHl0TExOjiooK7dy5U9nZ2ZYa4mpcLpdWr16t5ORkORwOSZIxRjt27FBWVpZqa2stNwQAAAAAXA0LbQBBpb29XYMGDVJjY6Pa29s1ePBgNTQ02K4FAACAHszr9WrevHmqqKjodJ6SkqI1a9YoNjY2wM3wbQwcOFDDhg2TJNXU1Mjn81luBAAAAADoDp6hDSCoNDQ0aNy4cZIkh8MhY/jODgAAAG7M4MGDdeTIkS7n//rXvzRo0KAANsL1aG5u1p49e7Rnzx6W2QAAAADQg7DQBhBU1qxZo7///e9qb2+XMUZffPGF2tvbOw0AAADQHY2NjXK5XF3OY2Nj1dTUFLhCAAAAAAD0ItxyHEDQGT58uOLj47VlyxbNnTtXzc3Nnb5vy5YtgS0GAACAHmndunWKj4/XlClT9PXXX3eYhYWFqby8XLW1tcrIyLDUEAAAAACA4MVCG0DQWr58uVatWqWLFy/argIAAIAezOl0qqqqSm1tbSosLNSxY8ckSQkJCcrMzFR4eLjGjBmjU6dOWW4KAAAAAEDwYaENAAAAAMA1uFwurV69WsnJyXI4HJIkY4x27NihrKws1dbWWm4IAAAAAEBwYqENAAAAAEA3DRw4UMOGDZMk1dTUyOfzWW4EAAAAAEBwY6ENAAAAAAAAAAAAALgthdguAAAAAAAAAAAAAABAZ1hoA+hVIiIibFcAAAAAAAAAAABAN7HQBhC0Fi9erMcee+zyz3/+85/V1NSkU6dO6Z577rHYDAAAAAAAAAAAAN3BQhtA0Jo3b55OnjwpSZo8ebKmTJmiH//4xyorK9OqVasstwMAAAAAAAAAAMC1hNouAAC3yuDBgy8vtKdOnaq//OUv2rFjh06cOKFPPvnEcjsAAAAAAAAAAABcC1doAwhaPp9Pd911lyQpNTVV7733niTJ4XCoT58+NqsBAAAAAAAAAACgG7hCG0DQ+tvf/qYNGzbo+PHjio6OVllZmSQpMTFRNTU1ltsBAAAAAAAAAADgWlhoAwhaixYt0okTJ3TXXXdp8eLFam1tlfTNrchXr15tuR0AAAAAAAAAAACuxSHJ2C4BALfCgAED9NVXX9muAQAAAAAAAAAAgOvEM7QBBK36+noVFRVp/PjxtqsAAAAAAAAAAADgOrDQBhC0Zs+erYiICO3cuVP//ve/9fzzz2vw4MG2awEAAAAAAAAAAKCbuOU4gKAXFRUlj8ej9PR0JSQkqLy8XMXFxdqyZYv8fr/tegAAAAAAAAAAAOgCC20AvUpWVpZWrVqlsLAwNTY2as2aNVq5cqUuXrxouxoAAAAAAAAAAAD+CwttAEEvJiZGHo9Hc+fO1dChQ1VaWqqioiINGTJEL7zwgs6cOaOUlBTbNQEAAAAAAAAAAPBfWGgDCFppaWmaO3euUlJSVF1drXXr1umdd97R+fPnL78nISFB+/fvV3h4uMWmAAAAAAAAAAAA6Eyo7QIAcKu89dZb2rhxo8aPH6+qqqpO31NXV6fc3NwANwMAAAAAAAAAAEB3cIU2gKDVv39/no0NAAAAAAAAAADQg7HQBtAr9OvXT3379u1w1tLSYqkNAAAAAAAAAAAAuiPEdgEAuFUGDBiggoIC1dfX68KFC/L5fB0CAAAAAAAAAACA2xsLbQBB6+WXX9bDDz+szMxMtbW1KSMjQytWrNDp06fl8Xhs1wMAAAAAAAAAAMA1cMtxAEHr008/lcfj0Ycffqjz589r9OjRqq2t1S9+8QvNnj1bP/nJT2xXBAAAAAAAAAAAwFVwhTaAoBUVFSWv1ytJ+vLLLxUVFSVJ+vjjj/Xggw/arAYAAAAAAAAAAIBuYKENIGjV1dXJ5XJJkqqrq/XYY49JkqZNm6bm5mZ7xQAAAAAAAAAAANAt3HIcQNBauHCh/H6/CgoKNHHiRG3btk19+vRRaGiosrOzlZ+fb7siAAAAAAAAAAAAroKFNoBe46677tKYMWNUW1urQ4cO2a4DAAAAAAAAAACAa2ChDQAAAAAAAAAAAAC4LYXaLgAAt4LD4VB6erpmzJghl8slY4y8Xq82bdqk9evX264HAAAAAAAAAACAbuAKbQBBaevWrXrkkUd08OBBHTt2TA6HQ263WyNHjtSWLVuUlpZmuyIAAAAAAAAAAACugSu0AQSd9PR0Pfjgg5o0aZJ27drVYfbQQw9p8+bNeuKJJ7hSGwAAAAAAAAAA4DbHFdoAgk55ebnef/99/e53v+t0/uKLL2rChAlKTU0NcDMAAAAAAAAAAAB8GyG2CwDAzXbPPfdo+/btXc7Lyso0atSoADYCAAAAAAAAAADA9WChDSDoREVFqb6+vst5fX29IiMjA9gIAAAAAAAAAAAA14OFNoCg06dPH7W3t3c59/v9Cg0NDWAjAAA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      "text/plain": [
       "<Figure size 2500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use(\"dark_background\")\n",
    "fig, ax = plt.subplots(figsize=(25,10))         # figsize\n",
    "sns.heatmap(df.corr(),annot=True, linewidths=.3 ,fmt='.1g', cmap= 'coolwarm')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "976b34e5",
   "metadata": {},
   "source": [
    "Some products have a negative benefit per order, indicating that the orders are costing the company money."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c4431fd6",
   "metadata": {},
   "outputs": [],
   "source": [
    "loss = df[(df['Benefit per order']<0)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "29a973f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0, 1, 2, 3, 4]),\n",
       " [Text(0, 0, 'LATAM'),\n",
       "  Text(1, 0, 'Europe'),\n",
       "  Text(2, 0, 'Pacific Asia'),\n",
       "  Text(3, 0, 'USCA'),\n",
       "  Text(4, 0, 'Africa')])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(1)\n",
    "loss['Category Name'].value_counts().nlargest(10).plot.bar(figsize=(15,7), title=\"Most Loss Making Products\")\n",
    "plt.xticks(rotation = 45)\n",
    "plt.figure(2)\n",
    "loss['Market'].value_counts().nlargest(10).plot.bar(figsize=(15,7), title=\"Most Loss Making Market\")\n",
    "plt.xticks(rotation = 45)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3231e32a",
   "metadata": {},
   "source": [
    "Order Status as per the payment types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d40e4d18",
   "metadata": {},
   "outputs": [],
   "source": [
    "status = df.groupby('Type')['Order Status'].value_counts()\n",
    "status_df = status.to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a51b7766",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Order Status</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Type</th>\n",
       "      <th>Order Status</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CASH</th>\n",
       "      <th>CLOSED</th>\n",
       "      <td>19616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">DEBIT</th>\n",
       "      <th>COMPLETE</th>\n",
       "      <td>59491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ON_HOLD</th>\n",
       "      <td>9804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">PAYMENT</th>\n",
       "      <th>PENDING_PAYMENT</th>\n",
       "      <td>39832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAYMENT_REVIEW</th>\n",
       "      <td>1893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">TRANSFER</th>\n",
       "      <th>PROCESSING</th>\n",
       "      <td>21902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PENDING</th>\n",
       "      <td>20227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUSPECTED_FRAUD</th>\n",
       "      <td>4062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CANCELED</th>\n",
       "      <td>3692</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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      "text/plain": [
       "                          Order Status\n",
       "Type     Order Status                 \n",
       "CASH     CLOSED                  19616\n",
       "DEBIT    COMPLETE                59491\n",
       "         ON_HOLD                  9804\n",
       "PAYMENT  PENDING_PAYMENT         39832\n",
       "         PAYMENT_REVIEW           1893\n",
       "TRANSFER PROCESSING              21902\n",
       "         PENDING                 20227\n",
       "         SUSPECTED_FRAUD          4062\n",
       "         CANCELED                 3692"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
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    "status_df"
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  {
   "cell_type": "markdown",
   "id": "92a31ae2",
   "metadata": {},
   "source": [
    "As we can see that only Transfer payments have a possible suspected fraud situation, what products have the most fraud?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a0c1468d",
   "metadata": {},
   "outputs": [],
   "source": [
    "fraud_region = df[(df['Order Status'] == 'SUSPECTED_FRAUD')]"
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use(\"dark_background\")\n",
    "temp = fraud_region['Category Name'].value_counts().nlargest(10)\n",
    "temp.iplot(kind='bar', xTitle = 'Category', yTitle = \"Count\", title = 'Count of Products with suspected fraud', color = '#FF0000')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f405e23b",
   "metadata": {},
   "source": [
    "## Data Modelling and Neural Networks to predict possible fraud"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a7429d49",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a copy of the datafram\n",
    "train_df = df.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3092c889",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating Binary enocode for Suspected Fraud and Late delivery\n",
    "\n",
    "train_df['fraud'] = np.where(train_df['Order Status'] == 'SUSPECTED_FRAUD', 1, 0)\n",
    "train_df['late_delivery']=np.where(train_df['Delivery Status'] == 'Late delivery', 1, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "1ac9b221",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Type', 'Days for shipping (real)', 'Days for shipment (scheduled)',\n",
       "       'Benefit per order', 'Sales per customer', 'Delivery Status',\n",
       "       'Late_delivery_risk', 'Category Id', 'Category Name', 'Customer City',\n",
       "       'Customer Country', 'Customer Id', 'Customer Segment', 'Customer State',\n",
       "       'Customer Zipcode', 'Department Id', 'Department Name', 'Market',\n",
       "       'Order City', 'Order Country', 'Order Customer Id',\n",
       "       'order date (DateOrders)', 'Order Id', 'Order Item Cardprod Id',\n",
       "       'Order Item Discount', 'Order Item Discount Rate', 'Order Item Id',\n",
       "       'Order Item Product Price', 'Order Item Profit Ratio',\n",
       "       'Order Item Quantity', 'Sales', 'Order Item Total',\n",
       "       'Order Profit Per Order', 'Order Region', 'Order State', 'Order Status',\n",
       "       'Product Card Id', 'Product Category Id', 'Product Name',\n",
       "       'Product Price', 'Shipping Mode', 'Cust_Full_Name', 'order_yr',\n",
       "       'order_month', 'order_day', 'order_hour', 'fraud', 'late_delivery'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "a994351f",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Removing Identical columns after creating new columns \n",
    "\n",
    "train_df.drop(['Delivery Status','Late_delivery_risk','Order Status','order date (DateOrders)'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "7b801bdd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(180519, 44)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Final dimensions of the dataset after wrangling and cleaning\n",
    "\n",
    "train_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c8005d0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Type                              object\n",
       "Days for shipping (real)           int64\n",
       "Days for shipment (scheduled)      int64\n",
       "Benefit per order                float64\n",
       "Sales per customer               float64\n",
       "Category Id                        int64\n",
       "Category Name                     object\n",
       "Customer City                     object\n",
       "Customer Country                  object\n",
       "Customer Id                        int64\n",
       "Customer Segment                  object\n",
       "Customer State                    object\n",
       "Customer Zipcode                 float64\n",
       "Department Id                      int64\n",
       "Department Name                   object\n",
       "Market                            object\n",
       "Order City                        object\n",
       "Order Country                     object\n",
       "Order Customer Id                  int64\n",
       "Order Id                           int64\n",
       "Order Item Cardprod Id             int64\n",
       "Order Item Discount              float64\n",
       "Order Item Discount Rate         float64\n",
       "Order Item Id                      int64\n",
       "Order Item Product Price         float64\n",
       "Order Item Profit Ratio          float64\n",
       "Order Item Quantity                int64\n",
       "Sales                            float64\n",
       "Order Item Total                 float64\n",
       "Order Profit Per Order           float64\n",
       "Order Region                      object\n",
       "Order State                       object\n",
       "Product Card Id                    int64\n",
       "Product Category Id                int64\n",
       "Product Name                      object\n",
       "Product Price                    float64\n",
       "Shipping Mode                     object\n",
       "Cust_Full_Name                    object\n",
       "order_yr                           int64\n",
       "order_month                        int64\n",
       "order_day                          int64\n",
       "order_hour                         int64\n",
       "fraud                              int32\n",
       "late_delivery                      int32\n",
       "dtype: object"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7eee61f",
   "metadata": {},
   "source": [
    "### Encoding all Object type variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e836a81d",
   "metadata": {},
   "outputs": [],
   "source": [
    "le = preprocessing.LabelEncoder()\n",
    "#convert the categorical columns into numeric\n",
    "train_df['Customer Country']  = le.fit_transform(train_df['Customer Country'])\n",
    "train_df['Market']            = le.fit_transform(train_df['Market'])\n",
    "train_df['Type']              = le.fit_transform(train_df['Type'])\n",
    "train_df['Product Name']      = le.fit_transform(train_df['Product Name'])\n",
    "train_df['Customer Segment']  = le.fit_transform(train_df['Customer Segment'])\n",
    "train_df['Customer State']    = le.fit_transform(train_df['Customer State'])\n",
    "train_df['Order Region']      = le.fit_transform(train_df['Order Region'])\n",
    "train_df['Order City']        = le.fit_transform(train_df['Order City'])\n",
    "train_df['Category Name']     = le.fit_transform(train_df['Category Name'])\n",
    "train_df['Customer City']     = le.fit_transform(train_df['Customer City'])\n",
    "train_df['Department Name']   = le.fit_transform(train_df['Department Name'])\n",
    "train_df['Order State']       = le.fit_transform(train_df['Order State'])\n",
    "train_df['Shipping Mode']     = le.fit_transform(train_df['Shipping Mode'])\n",
    "train_df['Order Country']     = le.fit_transform(train_df['Order Country'])\n",
    "train_df['Cust_Full_Name']    = le.fit_transform(train_df['Cust_Full_Name'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ec040225",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Type</th>\n",
       "      <th>Days for shipping (real)</th>\n",
       "      <th>Days for shipment (scheduled)</th>\n",
       "      <th>Benefit per order</th>\n",
       "      <th>Sales per customer</th>\n",
       "      <th>Category Id</th>\n",
       "      <th>Category Name</th>\n",
       "      <th>Customer City</th>\n",
       "      <th>Customer Country</th>\n",
       "      <th>Customer Id</th>\n",
       "      <th>...</th>\n",
       "      <th>Product Name</th>\n",
       "      <th>Product Price</th>\n",
       "      <th>Shipping Mode</th>\n",
       "      <th>Cust_Full_Name</th>\n",
       "      <th>order_yr</th>\n",
       "      <th>order_month</th>\n",
       "      <th>order_day</th>\n",
       "      <th>order_hour</th>\n",
       "      <th>fraud</th>\n",
       "      <th>late_delivery</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
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       "      <td>20755</td>\n",
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       "      <td>327.75</td>\n",
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       "      <td>1</td>\n",
       "      <td>19492</td>\n",
       "      <td>...</td>\n",
       "      <td>78</td>\n",
       "      <td>327.75</td>\n",
       "      <td>3</td>\n",
       "      <td>5378</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>-247.779999</td>\n",
       "      <td>309.720001</td>\n",
       "      <td>73</td>\n",
       "      <td>40</td>\n",
       "      <td>452</td>\n",
       "      <td>0</td>\n",
       "      <td>19491</td>\n",
       "      <td>...</td>\n",
       "      <td>78</td>\n",
       "      <td>327.75</td>\n",
       "      <td>3</td>\n",
       "      <td>4429</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>22.860001</td>\n",
       "      <td>304.809998</td>\n",
       "      <td>73</td>\n",
       "      <td>40</td>\n",
       "      <td>285</td>\n",
       "      <td>0</td>\n",
       "      <td>19490</td>\n",
       "      <td>...</td>\n",
       "      <td>78</td>\n",
       "      <td>327.75</td>\n",
       "      <td>3</td>\n",
       "      <td>12929</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>134.210007</td>\n",
       "      <td>298.250000</td>\n",
       "      <td>73</td>\n",
       "      <td>40</td>\n",
       "      <td>66</td>\n",
       "      <td>1</td>\n",
       "      <td>19489</td>\n",
       "      <td>...</td>\n",
       "      <td>78</td>\n",
       "      <td>327.75</td>\n",
       "      <td>3</td>\n",
       "      <td>10638</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 44 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Type  Days for shipping (real)  Days for shipment (scheduled)  \\\n",
       "0     1                         3                              4   \n",
       "1     3                         5                              4   \n",
       "2     0                         4                              4   \n",
       "3     1                         3                              4   \n",
       "4     2                         2                              4   \n",
       "\n",
       "   Benefit per order  Sales per customer  Category Id  Category Name  \\\n",
       "0          91.250000          314.640015           73             40   \n",
       "1        -249.089996          311.359985           73             40   \n",
       "2        -247.779999          309.720001           73             40   \n",
       "3          22.860001          304.809998           73             40   \n",
       "4         134.210007          298.250000           73             40   \n",
       "\n",
       "   Customer City  Customer Country  Customer Id  ...  Product Name  \\\n",
       "0             66                 1        20755  ...            78   \n",
       "1             66                 1        19492  ...            78   \n",
       "2            452                 0        19491  ...            78   \n",
       "3            285                 0        19490  ...            78   \n",
       "4             66                 1        19489  ...            78   \n",
       "\n",
       "   Product Price  Shipping Mode  Cust_Full_Name  order_yr  order_month  \\\n",
       "0         327.75              3            1876      2018            1   \n",
       "1         327.75              3            5378      2018            1   \n",
       "2         327.75              3            4429      2018            1   \n",
       "3         327.75              3           12929      2018            1   \n",
       "4         327.75              3           10638      2018            1   \n",
       "\n",
       "   order_day  order_hour  fraud  late_delivery  \n",
       "0          2          22      0              0  \n",
       "1          5          12      0              1  \n",
       "2          5          12      0              0  \n",
       "3          5          11      0              0  \n",
       "4          5          11      0              0  \n",
       "\n",
       "[5 rows x 44 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebe94ec2",
   "metadata": {},
   "source": [
    "## Preparing Data for Neural Networks"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67d839ef",
   "metadata": {},
   "source": [
    "Creating a Validation Set from the orignal data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "165ab189",
   "metadata": {},
   "outputs": [],
   "source": [
    "# rows = int(train_df.shape[0] * 0.1)\n",
    "\n",
    "# randomly select the specified number of rows\n",
    "# random_rows = np.random.choice(train_df.index, rows, replace=False)\n",
    "\n",
    "# create a new dataframe from the randomly selected rows\n",
    "# validation_df = df.loc[random_rows]\n",
    "\n",
    "# Dropping those rows from the original dataset\n",
    "# train_df.drop(random_rows,inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "05daa28b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Type</th>\n",
       "      <th>Days for shipping (real)</th>\n",
       "      <th>Days for shipment (scheduled)</th>\n",
       "      <th>Benefit per order</th>\n",
       "      <th>Sales per customer</th>\n",
       "      <th>Category Id</th>\n",
       "      <th>Category Name</th>\n",
       "      <th>Customer City</th>\n",
       "      <th>Customer Country</th>\n",
       "      <th>Customer Id</th>\n",
       "      <th>...</th>\n",
       "      <th>Product Name</th>\n",
       "      <th>Product Price</th>\n",
       "      <th>Shipping Mode</th>\n",
       "      <th>Cust_Full_Name</th>\n",
       "      <th>order_yr</th>\n",
       "      <th>order_month</th>\n",
       "      <th>order_day</th>\n",
       "      <th>order_hour</th>\n",
       "      <th>fraud</th>\n",
       "      <th>late_delivery</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>101369</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>71.849998</td>\n",
       "      <td>197.919998</td>\n",
       "      <td>46</td>\n",
       "      <td>30</td>\n",
       "      <td>529</td>\n",
       "      <td>0</td>\n",
       "      <td>6862</td>\n",
       "      <td>...</td>\n",
       "      <td>67</td>\n",
       "      <td>49.980000</td>\n",
       "      <td>3</td>\n",
       "      <td>9418</td>\n",
       "      <td>2016</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3026</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>57.529999</td>\n",
       "      <td>164.380005</td>\n",
       "      <td>67</td>\n",
       "      <td>16</td>\n",
       "      <td>66</td>\n",
       "      <td>1</td>\n",
       "      <td>15052</td>\n",
       "      <td>...</td>\n",
       "      <td>17</td>\n",
       "      <td>164.380005</td>\n",
       "      <td>3</td>\n",
       "      <td>7715</td>\n",
       "      <td>2017</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57549</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>22.680000</td>\n",
       "      <td>226.759995</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>66</td>\n",
       "      <td>1</td>\n",
       "      <td>7391</td>\n",
       "      <td>...</td>\n",
       "      <td>71</td>\n",
       "      <td>59.990002</td>\n",
       "      <td>3</td>\n",
       "      <td>8910</td>\n",
       "      <td>2016</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127144</th>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>-3.020000</td>\n",
       "      <td>103.989998</td>\n",
       "      <td>18</td>\n",
       "      <td>34</td>\n",
       "      <td>66</td>\n",
       "      <td>1</td>\n",
       "      <td>2588</td>\n",
       "      <td>...</td>\n",
       "      <td>56</td>\n",
       "      <td>129.990005</td>\n",
       "      <td>3</td>\n",
       "      <td>9384</td>\n",
       "      <td>2015</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160375</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>11.760000</td>\n",
       "      <td>37.560001</td>\n",
       "      <td>75</td>\n",
       "      <td>45</td>\n",
       "      <td>66</td>\n",
       "      <td>1</td>\n",
       "      <td>19769</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>39.750000</td>\n",
       "      <td>3</td>\n",
       "      <td>10054</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22603</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>34.849998</td>\n",
       "      <td>99.580002</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>66</td>\n",
       "      <td>1</td>\n",
       "      <td>4792</td>\n",
       "      <td>...</td>\n",
       "      <td>71</td>\n",
       "      <td>59.990002</td>\n",
       "      <td>3</td>\n",
       "      <td>3574</td>\n",
       "      <td>2016</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152893</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>135.190002</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>45</td>\n",
       "      <td>18</td>\n",
       "      <td>271</td>\n",
       "      <td>0</td>\n",
       "      <td>4055</td>\n",
       "      <td>...</td>\n",
       "      <td>24</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>0</td>\n",
       "      <td>7188</td>\n",
       "      <td>2016</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172935</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>-39.320000</td>\n",
       "      <td>347.980011</td>\n",
       "      <td>45</td>\n",
       "      <td>18</td>\n",
       "      <td>66</td>\n",
       "      <td>1</td>\n",
       "      <td>148</td>\n",
       "      <td>...</td>\n",
       "      <td>24</td>\n",
       "      <td>399.980011</td>\n",
       "      <td>2</td>\n",
       "      <td>12636</td>\n",
       "      <td>2015</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79244</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>159.990005</td>\n",
       "      <td>48</td>\n",
       "      <td>46</td>\n",
       "      <td>66</td>\n",
       "      <td>1</td>\n",
       "      <td>8580</td>\n",
       "      <td>...</td>\n",
       "      <td>70</td>\n",
       "      <td>199.990005</td>\n",
       "      <td>0</td>\n",
       "      <td>7085</td>\n",
       "      <td>2016</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62015</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>50.959999</td>\n",
       "      <td>195.990005</td>\n",
       "      <td>48</td>\n",
       "      <td>46</td>\n",
       "      <td>261</td>\n",
       "      <td>0</td>\n",
       "      <td>6574</td>\n",
       "      <td>...</td>\n",
       "      <td>70</td>\n",
       "      <td>199.990005</td>\n",
       "      <td>3</td>\n",
       "      <td>9384</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18052 rows × 44 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Type  Days for shipping (real)  Days for shipment (scheduled)  \\\n",
       "101369     3                         2                              4   \n",
       "3026       2                         5                              4   \n",
       "57549      1                         5                              4   \n",
       "127144     2                         6                              4   \n",
       "160375     3                         2                              4   \n",
       "...      ...                       ...                            ...   \n",
       "22603      1                         5                              4   \n",
       "152893     3                         2                              1   \n",
       "172935     0                         2                              2   \n",
       "79244      1                         2                              1   \n",
       "62015      1                         2                              4   \n",
       "\n",
       "        Benefit per order  Sales per customer  Category Id  Category Name  \\\n",
       "101369          71.849998          197.919998           46             30   \n",
       "3026            57.529999          164.380005           67             16   \n",
       "57549           22.680000          226.759995           17             12   \n",
       "127144          -3.020000          103.989998           18             34   \n",
       "160375          11.760000           37.560001           75             45   \n",
       "...                   ...                 ...          ...            ...   \n",
       "22603           34.849998           99.580002           17             12   \n",
       "152893         135.190002          399.980011           45             18   \n",
       "172935         -39.320000          347.980011           45             18   \n",
       "79244           40.000000          159.990005           48             46   \n",
       "62015           50.959999          195.990005           48             46   \n",
       "\n",
       "        Customer City  Customer Country  Customer Id  ...  Product Name  \\\n",
       "101369            529                 0         6862  ...            67   \n",
       "3026               66                 1        15052  ...            17   \n",
       "57549              66                 1         7391  ...            71   \n",
       "127144             66                 1         2588  ...            56   \n",
       "160375             66                 1        19769  ...            25   \n",
       "...               ...               ...          ...  ...           ...   \n",
       "22603              66                 1         4792  ...            71   \n",
       "152893            271                 0         4055  ...            24   \n",
       "172935             66                 1          148  ...            24   \n",
       "79244              66                 1         8580  ...            70   \n",
       "62015             261                 0         6574  ...            70   \n",
       "\n",
       "        Product Price  Shipping Mode  Cust_Full_Name  order_yr  order_month  \\\n",
       "101369      49.980000              3            9418      2016            4   \n",
       "3026       164.380005              3            7715      2017           11   \n",
       "57549       59.990002              3            8910      2016           10   \n",
       "127144     129.990005              3            9384      2015            2   \n",
       "160375      39.750000              3           10054      2018            1   \n",
       "...               ...            ...             ...       ...          ...   \n",
       "22603       59.990002              3            3574      2016            8   \n",
       "152893     399.980011              0            7188      2016            4   \n",
       "172935     399.980011              2           12636      2015            8   \n",
       "79244      199.990005              0            7085      2016            5   \n",
       "62015      199.990005              3            9384      2015            4   \n",
       "\n",
       "        order_day  order_hour  fraud  late_delivery  \n",
       "101369          4          11      0              0  \n",
       "3026            3          16      0              1  \n",
       "57549           2           2      0              1  \n",
       "127144          5           0      0              1  \n",
       "160375          2          13      0              0  \n",
       "...           ...         ...    ...            ...  \n",
       "22603           5           7      0              1  \n",
       "152893          0           8      0              1  \n",
       "172935          5          20      0              0  \n",
       "79244           4          17      0              1  \n",
       "62015           0          15      0              0  \n",
       "\n",
       "[18052 rows x 44 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Selecting 10% of the dataset for validation\n",
    "\n",
    "fraction_of_rows = train_df.sample(frac=0.1, random_state = 1)\n",
    "fraction_of_rows"
   ]
  },
  {
   "cell_type": "code",
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       " ...]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Creating a list of index of the samples to be dropped from the main dataset\n",
    "\n",
    "index = fraction_of_rows.index.values.tolist()\n",
    "index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "1a4de220",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Dropping rows with the index numbers\n",
    "\n",
    "train_df.drop(index = index, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "d583c96e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(162467, 44)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "1bfd2a68",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Resetting index for the validation dataset\n",
    "\n",
    "fraction_of_rows.reset_index(drop = True, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "5a22996b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(18052, 44)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fraction_of_rows.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "fb9cd471",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Creating X and y for dependant and independent variables\n",
    "\n",
    "X = train_df.loc[:,train_df.columns != 'fraud']\n",
    "y = train_df['fraud']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "4979dc77",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Splitting the dataset into training and test data\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.30, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "dab7294a",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Creating dataframe for X and y validation dataset\n",
    "\n",
    "X_valid = fraction_of_rows.loc[:,fraction_of_rows.columns != 'fraud']\n",
    "y_valid = fraction_of_rows['fraud']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "56436168",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(113726, 43)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "14d2d257",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Defining the classes \n",
    "classes = sorted(y_train.unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f31754b3",
   "metadata": {},
   "source": [
    "### Standardizing the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "1b98a7d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Standardizing the X dataset\n",
    "\n",
    "ss = StandardScaler()\n",
    "X_train=ss.fit_transform(X_train)\n",
    "X_test=ss.transform(X_test)\n",
    "X_valid=ss.transform(X_valid)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2cf6e5c3",
   "metadata": {},
   "source": [
    "## Creating MLPClassifier Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "3fd9475d",
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = MLPClassifier(hidden_layer_sizes=(6), activation='logistic', solver='lbfgs',random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "37445d16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>MLPClassifier(activation=&#x27;logistic&#x27;, hidden_layer_sizes=6, random_state=1,\n",
       "              solver=&#x27;lbfgs&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">MLPClassifier</label><div class=\"sk-toggleable__content\"><pre>MLPClassifier(activation=&#x27;logistic&#x27;, hidden_layer_sizes=6, random_state=1,\n",
       "              solver=&#x27;lbfgs&#x27;)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "MLPClassifier(activation='logistic', hidden_layer_sizes=6, random_state=1,\n",
       "              solver='lbfgs')"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Fitting the data using MLPClassifier\n",
    "\n",
    "clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "0fb1fad2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, ..., 0, 0, 0])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Predicting the trained model\n",
    "\n",
    "clf.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "96a7e492",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Confusion Matrix (Accuracy 0.9789)\n",
      "\n",
      "       Prediction\n",
      "Actual     0     1\n",
      "     0 47280   330\n",
      "     1   697   434\n"
     ]
    }
   ],
   "source": [
    "## Creating a Classification matrix for MLPClassifier\n",
    "\n",
    "classificationSummary(y_test, clf.predict(X_test), class_names=classes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f53abb20",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "532eb526",
   "metadata": {},
   "source": [
    "## Creating a Custom Neural Network Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "23893174",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(162467, 44)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "a17b704a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " dense (Dense)               (None, 1024)              45056     \n",
      "                                                                 \n",
      " dense_1 (Dense)             (None, 512)               524800    \n",
      "                                                                 \n",
      " dense_2 (Dense)             (None, 256)               131328    \n",
      "                                                                 \n",
      " dense_3 (Dense)             (None, 128)               32896     \n",
      "                                                                 \n",
      " dense_4 (Dense)             (None, 64)                8256      \n",
      "                                                                 \n",
      " dense_5 (Dense)             (None, 32)                2080      \n",
      "                                                                 \n",
      " dense_6 (Dense)             (None, 16)                528       \n",
      "                                                                 \n",
      " dense_7 (Dense)             (None, 8)                 136       \n",
      "                                                                 \n",
      " dense_8 (Dense)             (None, 4)                 36        \n",
      "                                                                 \n",
      " dense_9 (Dense)             (None, 2)                 10        \n",
      "                                                                 \n",
      " dense_10 (Dense)            (None, 1)                 3         \n",
      "                                                                 \n",
      " activation (Activation)     (None, 1)                 0         \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 745,129\n",
      "Trainable params: 745,129\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "keras.layers.BatchNormalization()\n",
    "model = Sequential()\n",
    "#First Hidden Layer\n",
    "model.add(Dense(1024, activation='relu', kernel_initializer='random_normal', input_dim=43)) #As we have 43 columns\n",
    "\n",
    "#All other hidden layers in a for loop with nodes reducing in each loop\n",
    "nodes = 1024\n",
    "for i in range(9):\n",
    "    nodes = nodes // 2\n",
    "    model.add(Dense(nodes, activation='relu', kernel_initializer='random_normal'))\n",
    "\n",
    "#Output Layer\n",
    "model.add(Dense(1))\n",
    "model.add(Activation('sigmoid'))\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39411e81",
   "metadata": {},
   "source": [
    "As F1 score is not accessible in Keras, binary crossentropy is used to measure loss and accuracy because the output data is binary classification."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "9c28394f",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Compiling the model created\n",
    "\n",
    "model.compile(optimizer='adam',loss='binary_crossentropy',metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc6109fb",
   "metadata": {},
   "source": [
    "### Fitting the model using custom neural network"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77206bd4",
   "metadata": {},
   "source": [
    "Intitally we'll tried with 10 epochs which had a good accuracy but the loss was high, then we increased it to 15 which reduced the loss significantly and we stopped there to avoid overfitting of the data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "b61e8640",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/15\n",
      "223/223 [==============================] - 8s 26ms/step - loss: 0.6431 - accuracy: 0.9759\n",
      "Epoch 2/15\n",
      "223/223 [==============================] - 5s 24ms/step - loss: 0.5534 - accuracy: 0.9777\n",
      "Epoch 3/15\n",
      "223/223 [==============================] - 6s 25ms/step - loss: 0.4789 - accuracy: 0.9777\n",
      "Epoch 4/15\n",
      "223/223 [==============================] - 6s 25ms/step - loss: 0.4172 - accuracy: 0.9777\n",
      "Epoch 5/15\n",
      "223/223 [==============================] - 5s 24ms/step - loss: 0.3662 - accuracy: 0.9777\n",
      "Epoch 6/15\n",
      "223/223 [==============================] - 5s 24ms/step - loss: 0.3240 - accuracy: 0.9777\n",
      "Epoch 7/15\n",
      "223/223 [==============================] - 6s 25ms/step - loss: 0.2889 - accuracy: 0.9777\n",
      "Epoch 8/15\n",
      "223/223 [==============================] - 6s 25ms/step - loss: 0.2597 - accuracy: 0.9777\n",
      "Epoch 9/15\n",
      "223/223 [==============================] - 6s 27ms/step - loss: 0.2354 - accuracy: 0.9777\n",
      "Epoch 10/15\n",
      "223/223 [==============================] - 7s 31ms/step - loss: 0.2150 - accuracy: 0.9777\n",
      "Epoch 11/15\n",
      "223/223 [==============================] - 6s 29ms/step - loss: 0.1978 - accuracy: 0.9777\n",
      "Epoch 12/15\n",
      "223/223 [==============================] - 7s 31ms/step - loss: 0.1834 - accuracy: 0.9777\n",
      "Epoch 13/15\n",
      "223/223 [==============================] - 7s 30ms/step - loss: 0.1712 - accuracy: 0.9777\n",
      "Epoch 14/15\n",
      "223/223 [==============================] - 7s 31ms/step - loss: 0.1608 - accuracy: 0.9777\n",
      "Epoch 15/15\n",
      "223/223 [==============================] - 7s 33ms/step - loss: 0.1521 - accuracy: 0.9777\n"
     ]
    }
   ],
   "source": [
    "csvlogger = CSVLogger('training.log',separator=',',append=False)\n",
    "\n",
    "result = model.fit(X_train, y_train, batch_size = 512, epochs = 15, callbacks=[csvlogger])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "bc621436",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x171efd29f70>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(result.history['accuracy'],'green',label='Accuracy')\n",
    "plt.plot(result.history['loss'],'red',label='Loss')\n",
    "plt.title('Training Accuracy & Loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.legend(loc=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "5df25416",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3554/3554 [==============================] - 12s 3ms/step - loss: 0.1481 - accuracy: 0.9777\n",
      "1524/1524 [==============================] - 5s 3ms/step - loss: 0.1501 - accuracy: 0.9768\n",
      "accuracy for Train set is [0.14811132848262787, 0.9776568412780762]\n",
      "accuracy for Test set is [0.15007199347019196, 0.9767957329750061]\n",
      "96/96 [==============================] - 1s 9ms/step\n",
      "0.9653297639890498\n"
     ]
    }
   ],
   "source": [
    "# Predicting the custom model model\n",
    "\n",
    "train_evaluate=model.evaluate(X_train, y_train)\n",
    "test_evaluate=model.evaluate(X_test, y_test)\n",
    "print('accuracy for Train set is',train_evaluate)\n",
    "print('accuracy for Test set is',test_evaluate) # evaluation of model.\n",
    "yf_pred1=model.predict(X_test,batch_size=512,verbose=1)\n",
    "yf_pred=np.argmax(yf_pred1,axis=1)\n",
    "print(f1_score(y_test,yf_pred,average=\"weighted\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66e56c7a",
   "metadata": {},
   "source": [
    "As we can see that the Train and test accuracy is very high at ~99% and loss is at ~8.88%.  \n",
    "Along with that the F1 Score calculated is 96.58%. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2d83f502",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "1a431811",
   "metadata": {},
   "source": [
    "## Validating the Models"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42fb04fb",
   "metadata": {},
   "source": [
    "### MLP Classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "f57fdf5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, ..., 0, 0, 0])"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Predicting the validation dataset\n",
    "\n",
    "clf_pred = clf.predict(X_valid)\n",
    "clf_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "27a9dc42",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Confusion Matrix (Accuracy 0.9787)\n",
      "\n",
      "       Prediction\n",
      "Actual     0     1\n",
      "     0 17532   130\n",
      "     1   254   136\n"
     ]
    }
   ],
   "source": [
    "## Classification Matrix for Validation Dataset\n",
    "\n",
    "classificationSummary(y_valid, clf.predict(X_valid), class_names=classes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "85e14611",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9787281187680036"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_valid,clf_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3bfd8671",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "b9ebd8f2",
   "metadata": {},
   "source": [
    "### Custom NN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "964593c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "565/565 [==============================] - 2s 3ms/step\n"
     ]
    }
   ],
   "source": [
    "predictions = model.predict(X_valid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "774e5d03",
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = (predictions > 0.5).astype(np.float32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "90e8cd6a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.],\n",
       "       [0.],\n",
       "       [0.],\n",
       "       ...,\n",
       "       [0.],\n",
       "       [0.],\n",
       "       [0.]], dtype=float32)"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "8eb08866",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9783957456237536"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_valid,predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe7e209b",
   "metadata": {},
   "outputs": [],
   "source": [
    "keras.backend.clear_session()"
   ]
  }
 ],
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